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/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Analysis.Convex.Between
import Mathlib.Analysis.Normed.Group.AddTorsor
import Mathlib.Analysis.Normed.Module.Convex
/-!
# Sides of affine subspaces
This file defines notions of two points being on the same or opposite sides of an affine subspace.
## Main definitions
* `s.WSameSide x y`: The points `x` and `y` are weakly on the same side of the affine
subspace `s`.
* `s.SSameSide x y`: The points `x` and `y` are strictly on the same side of the affine
subspace `s`.
* `s.WOppSide x y`: The points `x` and `y` are weakly on opposite sides of the affine
subspace `s`.
* `s.SOppSide x y`: The points `x` and `y` are strictly on opposite sides of the affine
subspace `s`.
-/
variable {R V V' P P' : Type*}
open AffineEquiv AffineMap
namespace AffineSubspace
section StrictOrderedCommRing
variable [CommRing R] [PartialOrder R] [IsStrictOrderedRing R]
[AddCommGroup V] [Module R V] [AddTorsor V P]
variable [AddCommGroup V'] [Module R V'] [AddTorsor V' P']
/-- The points `x` and `y` are weakly on the same side of `s`. -/
def WSameSide (s : AffineSubspace R P) (x y : P) : Prop :=
∃ᵉ (p₁ ∈ s) (p₂ ∈ s), SameRay R (x -ᵥ p₁) (y -ᵥ p₂)
/-- The points `x` and `y` are strictly on the same side of `s`. -/
def SSameSide (s : AffineSubspace R P) (x y : P) : Prop :=
s.WSameSide x y ∧ x ∉ s ∧ y ∉ s
/-- The points `x` and `y` are weakly on opposite sides of `s`. -/
def WOppSide (s : AffineSubspace R P) (x y : P) : Prop :=
∃ᵉ (p₁ ∈ s) (p₂ ∈ s), SameRay R (x -ᵥ p₁) (p₂ -ᵥ y)
/-- The points `x` and `y` are strictly on opposite sides of `s`. -/
def SOppSide (s : AffineSubspace R P) (x y : P) : Prop :=
s.WOppSide x y ∧ x ∉ s ∧ y ∉ s
theorem WSameSide.map {s : AffineSubspace R P} {x y : P} (h : s.WSameSide x y) (f : P →ᵃ[R] P') :
(s.map f).WSameSide (f x) (f y) := by
rcases h with ⟨p₁, hp₁, p₂, hp₂, h⟩
refine ⟨f p₁, mem_map_of_mem f hp₁, f p₂, mem_map_of_mem f hp₂, ?_⟩
simp_rw [← linearMap_vsub]
exact h.map f.linear
theorem _root_.Function.Injective.wSameSide_map_iff {s : AffineSubspace R P} {x y : P}
{f : P →ᵃ[R] P'} (hf : Function.Injective f) :
(s.map f).WSameSide (f x) (f y) ↔ s.WSameSide x y := by
refine ⟨fun h => ?_, fun h => h.map _⟩
rcases h with ⟨fp₁, hfp₁, fp₂, hfp₂, h⟩
rw [mem_map] at hfp₁ hfp₂
rcases hfp₁ with ⟨p₁, hp₁, rfl⟩
rcases hfp₂ with ⟨p₂, hp₂, rfl⟩
refine ⟨p₁, hp₁, p₂, hp₂, ?_⟩
simp_rw [← linearMap_vsub, (f.linear_injective_iff.2 hf).sameRay_map_iff] at h
exact h
theorem _root_.Function.Injective.sSameSide_map_iff {s : AffineSubspace R P} {x y : P}
{f : P →ᵃ[R] P'} (hf : Function.Injective f) :
(s.map f).SSameSide (f x) (f y) ↔ s.SSameSide x y := by
simp_rw [SSameSide, hf.wSameSide_map_iff, mem_map_iff_mem_of_injective hf]
@[simp]
theorem _root_.AffineEquiv.wSameSide_map_iff {s : AffineSubspace R P} {x y : P} (f : P ≃ᵃ[R] P') :
| (s.map ↑f).WSameSide (f x) (f y) ↔ s.WSameSide x y :=
(show Function.Injective f.toAffineMap from f.injective).wSameSide_map_iff
@[simp]
| Mathlib/Analysis/Convex/Side.lean | 83 | 86 |
/-
Copyright (c) 2024 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.MvPolynomial.Monad
import Mathlib.LinearAlgebra.Charpoly.ToMatrix
import Mathlib.LinearAlgebra.FreeModule.StrongRankCondition
import Mathlib.LinearAlgebra.Matrix.Charpoly.Univ
import Mathlib.RingTheory.TensorProduct.Finite
import Mathlib.RingTheory.TensorProduct.Free
/-!
# Characteristic polynomials of linear families of endomorphisms
The coefficients of the characteristic polynomials of a linear family of endomorphisms
are homogeneous polynomials in the parameters.
This result is used in Lie theory
to establish the existence of regular elements and Cartan subalgebras,
and ultimately a well-defined notion of rank for Lie algebras.
In this file we prove this result about characteristic polynomials.
Let `L` and `M` be modules over a nontrivial commutative ring `R`,
and let `φ : L →ₗ[R] Module.End R M` be a linear map.
Let `b` be a basis of `L`, indexed by `ι`.
Then we define a multivariate polynomial with variables indexed by `ι`
that evaluates on elements `x` of `L` to the characteristic polynomial of `φ x`.
## Main declarations
* `Matrix.toMvPolynomial M i`: the family of multivariate polynomials that evaluates on `c : n → R`
to the dot product of the `i`-th row of `M` with `c`.
`Matrix.toMvPolynomial M i` is the sum of the monomials `C (M i j) * X j`.
* `LinearMap.toMvPolynomial b₁ b₂ f`: a version of `Matrix.toMvPolynomial` for linear maps `f`
with respect to bases `b₁` and `b₂` of the domain and codomain.
* `LinearMap.polyCharpoly`: the multivariate polynomial that evaluates on elements `x` of `L`
to the characteristic polynomial of `φ x`.
* `LinearMap.polyCharpoly_map_eq_charpoly`: the evaluation of `polyCharpoly` on elements `x` of `L`
is the characteristic polynomial of `φ x`.
* `LinearMap.polyCharpoly_coeff_isHomogeneous`: the coefficients of `polyCharpoly`
are homogeneous polynomials in the parameters.
* `LinearMap.nilRank`: the smallest index at which `polyCharpoly` has a non-zero coefficient,
which is independent of the choice of basis for `L`.
* `LinearMap.IsNilRegular`: an element `x` of `L` is *nil-regular* with respect to `φ`
if the `n`-th coefficient of the characteristic polynomial of `φ x` is non-zero,
where `n` denotes the nil-rank of `φ`.
## Implementation details
We show that `LinearMap.polyCharpoly` does not depend on the choice of basis of the target module.
This is done via `LinearMap.polyCharpoly_eq_polyCharpolyAux`
and `LinearMap.polyCharpolyAux_basisIndep`.
The latter is proven by considering
the base change of the `R`-linear map `φ : L →ₗ[R] End R M`
to the multivariate polynomial ring `MvPolynomial ι R`,
and showing that `polyCharpolyAux φ` is equal to the characteristic polynomial of this base change.
The proof concludes because characteristic polynomials are independent of the chosen basis.
## References
* [barnes1967]: "On Cartan subalgebras of Lie algebras" by D.W. Barnes.
-/
open scoped Matrix
namespace Matrix
variable {m n o R S : Type*}
variable [Fintype n] [Fintype o] [CommSemiring R] [CommSemiring S]
open MvPolynomial
/-- Let `M` be an `(m × n)`-matrix over `R`.
Then `Matrix.toMvPolynomial M` is the family (indexed by `i : m`)
of multivariate polynomials in `n` variables over `R` that evaluates on `c : n → R`
to the dot product of the `i`-th row of `M` with `c`:
`Matrix.toMvPolynomial M i` is the sum of the monomials `C (M i j) * X j`. -/
noncomputable
def toMvPolynomial (M : Matrix m n R) (i : m) : MvPolynomial n R :=
∑ j, monomial (.single j 1) (M i j)
lemma toMvPolynomial_eval_eq_apply (M : Matrix m n R) (i : m) (c : n → R) :
eval c (M.toMvPolynomial i) = (M *ᵥ c) i := by
simp only [toMvPolynomial, map_sum, eval_monomial, pow_zero, Finsupp.prod_single_index, pow_one,
mulVec, dotProduct]
lemma toMvPolynomial_map (f : R →+* S) (M : Matrix m n R) (i : m) :
(M.map f).toMvPolynomial i = MvPolynomial.map f (M.toMvPolynomial i) := by
simp only [toMvPolynomial, map_apply, map_sum, map_monomial]
lemma toMvPolynomial_isHomogeneous (M : Matrix m n R) (i : m) :
(M.toMvPolynomial i).IsHomogeneous 1 := by
apply MvPolynomial.IsHomogeneous.sum
rintro j -
apply MvPolynomial.isHomogeneous_monomial _ _
simp [Finsupp.degree, Finsupp.support_single_ne_zero _ one_ne_zero, Finset.sum_singleton,
Finsupp.single_eq_same]
lemma toMvPolynomial_totalDegree_le (M : Matrix m n R) (i : m) :
(M.toMvPolynomial i).totalDegree ≤ 1 := by
apply (toMvPolynomial_isHomogeneous _ _).totalDegree_le
@[simp]
lemma toMvPolynomial_constantCoeff (M : Matrix m n R) (i : m) :
constantCoeff (M.toMvPolynomial i) = 0 := by
simp only [toMvPolynomial, ← C_mul_X_eq_monomial, map_sum, map_mul, constantCoeff_X,
mul_zero, Finset.sum_const_zero]
@[simp]
lemma toMvPolynomial_zero : (0 : Matrix m n R).toMvPolynomial = 0 := by
ext; simp only [toMvPolynomial, zero_apply, map_zero, Finset.sum_const_zero, Pi.zero_apply]
@[simp]
lemma toMvPolynomial_one [DecidableEq n] : (1 : Matrix n n R).toMvPolynomial = X := by
ext i : 1
rw [toMvPolynomial, Finset.sum_eq_single i]
· simp only [one_apply_eq, ← C_mul_X_eq_monomial, C_1, one_mul]
· rintro j - hj
simp only [one_apply_ne hj.symm, map_zero]
· intro h
exact (h (Finset.mem_univ _)).elim
lemma toMvPolynomial_add (M N : Matrix m n R) :
(M + N).toMvPolynomial = M.toMvPolynomial + N.toMvPolynomial := by
ext i : 1
simp only [toMvPolynomial, add_apply, map_add, Finset.sum_add_distrib, Pi.add_apply]
lemma toMvPolynomial_mul (M : Matrix m n R) (N : Matrix n o R) (i : m) :
(M * N).toMvPolynomial i = bind₁ N.toMvPolynomial (M.toMvPolynomial i) := by
simp only [toMvPolynomial, mul_apply, map_sum, Finset.sum_comm (γ := o), bind₁, aeval,
AlgHom.coe_mk, coe_eval₂Hom, eval₂_monomial, algebraMap_apply, Algebra.id.map_eq_id,
RingHom.id_apply, C_apply, pow_zero, Finsupp.prod_single_index, pow_one, Finset.mul_sum,
monomial_mul, zero_add]
end Matrix
namespace LinearMap
open MvPolynomial
section
variable {R M₁ M₂ ι₁ ι₂ : Type*}
variable [CommRing R] [AddCommGroup M₁] [AddCommGroup M₂]
variable [Module R M₁] [Module R M₂]
variable [Fintype ι₁] [Finite ι₂]
variable [DecidableEq ι₁]
variable (b₁ : Basis ι₁ R M₁) (b₂ : Basis ι₂ R M₂)
/-- Let `f : M₁ →ₗ[R] M₂` be an `R`-linear map
between modules `M₁` and `M₂` with bases `b₁` and `b₂` respectively.
Then `LinearMap.toMvPolynomial b₁ b₂ f` is the family of multivariate polynomials over `R`
that evaluates on an element `x` of `M₁` (represented on the basis `b₁`)
to the element `f x` of `M₂` (represented on the basis `b₂`). -/
noncomputable
def toMvPolynomial (f : M₁ →ₗ[R] M₂) (i : ι₂) :
MvPolynomial ι₁ R :=
(toMatrix b₁ b₂ f).toMvPolynomial i
lemma toMvPolynomial_eval_eq_apply (f : M₁ →ₗ[R] M₂) (i : ι₂) (c : ι₁ →₀ R) :
eval c (f.toMvPolynomial b₁ b₂ i) = b₂.repr (f (b₁.repr.symm c)) i := by
rw [toMvPolynomial, Matrix.toMvPolynomial_eval_eq_apply,
← LinearMap.toMatrix_mulVec_repr b₁ b₂, LinearEquiv.apply_symm_apply]
open Algebra.TensorProduct in
lemma toMvPolynomial_baseChange (f : M₁ →ₗ[R] M₂) (i : ι₂) (A : Type*) [CommRing A] [Algebra R A] :
(f.baseChange A).toMvPolynomial (basis A b₁) (basis A b₂) i =
MvPolynomial.map (algebraMap R A) (f.toMvPolynomial b₁ b₂ i) := by
simp only [toMvPolynomial, toMatrix_baseChange, Matrix.toMvPolynomial_map]
lemma toMvPolynomial_isHomogeneous (f : M₁ →ₗ[R] M₂) (i : ι₂) :
(f.toMvPolynomial b₁ b₂ i).IsHomogeneous 1 :=
Matrix.toMvPolynomial_isHomogeneous _ _
lemma toMvPolynomial_totalDegree_le (f : M₁ →ₗ[R] M₂) (i : ι₂) :
(f.toMvPolynomial b₁ b₂ i).totalDegree ≤ 1 :=
Matrix.toMvPolynomial_totalDegree_le _ _
@[simp]
lemma toMvPolynomial_constantCoeff (f : M₁ →ₗ[R] M₂) (i : ι₂) :
constantCoeff (f.toMvPolynomial b₁ b₂ i) = 0 :=
Matrix.toMvPolynomial_constantCoeff _ _
|
@[simp]
lemma toMvPolynomial_zero : (0 : M₁ →ₗ[R] M₂).toMvPolynomial b₁ b₂ = 0 := by
| Mathlib/Algebra/Module/LinearMap/Polynomial.lean | 184 | 186 |
/-
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.Finite.Defs
import Mathlib.Data.Finset.BooleanAlgebra
import Mathlib.Data.Finset.Image
import Mathlib.Data.Fintype.Defs
import Mathlib.Data.Fintype.OfMap
import Mathlib.Data.Fintype.Sets
import Mathlib.Data.List.FinRange
/-!
# Instances for finite types
This file is a collection of basic `Fintype` instances for types such as `Fin`, `Prod` and pi types.
-/
assert_not_exists Monoid
open Function
open Nat
universe u v
variable {α β γ : Type*}
open Finset
instance Fin.fintype (n : ℕ) : Fintype (Fin n) :=
⟨⟨List.finRange n, List.nodup_finRange n⟩, List.mem_finRange⟩
theorem Fin.univ_def (n : ℕ) : (univ : Finset (Fin n)) = ⟨List.finRange n, List.nodup_finRange n⟩ :=
rfl
theorem Finset.val_univ_fin (n : ℕ) : (Finset.univ : Finset (Fin n)).val = List.finRange n := rfl
/-- See also `nonempty_encodable`, `nonempty_denumerable`. -/
theorem nonempty_fintype (α : Type*) [Finite α] : Nonempty (Fintype α) := by
rcases Finite.exists_equiv_fin α with ⟨n, ⟨e⟩⟩
exact ⟨.ofEquiv _ e.symm⟩
@[simp] theorem List.toFinset_finRange (n : ℕ) : (List.finRange n).toFinset = Finset.univ := by
ext; simp
@[simp] theorem Fin.univ_val_map {n : ℕ} (f : Fin n → α) :
Finset.univ.val.map f = List.ofFn f := by
simp [List.ofFn_eq_map, univ_def]
theorem Fin.univ_image_def {n : ℕ} [DecidableEq α] (f : Fin n → α) :
Finset.univ.image f = (List.ofFn f).toFinset := by
simp [Finset.image]
theorem Fin.univ_map_def {n : ℕ} (f : Fin n ↪ α) :
Finset.univ.map f = ⟨List.ofFn f, List.nodup_ofFn.mpr f.injective⟩ := by
simp [Finset.map]
@[simp]
theorem Fin.image_succAbove_univ {n : ℕ} (i : Fin (n + 1)) : univ.image i.succAbove = {i}ᶜ := by
ext m
simp
@[simp]
theorem Fin.image_succ_univ (n : ℕ) : (univ : Finset (Fin n)).image Fin.succ = {0}ᶜ := by
rw [← Fin.succAbove_zero, Fin.image_succAbove_univ]
@[simp]
theorem Fin.image_castSucc (n : ℕ) :
(univ : Finset (Fin n)).image Fin.castSucc = {Fin.last n}ᶜ := by
rw [← Fin.succAbove_last, Fin.image_succAbove_univ]
/- The following three lemmas use `Finset.cons` instead of `insert` and `Finset.map` instead of
`Finset.image` to reduce proof obligations downstream. -/
/-- Embed `Fin n` into `Fin (n + 1)` by prepending zero to the `univ` -/
theorem Fin.univ_succ (n : ℕ) :
(univ : Finset (Fin (n + 1))) =
Finset.cons 0 (univ.map ⟨Fin.succ, Fin.succ_injective _⟩) (by simp [map_eq_image]) := by
simp [map_eq_image]
/-- Embed `Fin n` into `Fin (n + 1)` by appending a new `Fin.last n` to the `univ` -/
theorem Fin.univ_castSuccEmb (n : ℕ) :
(univ : Finset (Fin (n + 1))) =
Finset.cons (Fin.last n) (univ.map Fin.castSuccEmb) (by simp [map_eq_image]) := by
simp [map_eq_image]
/-- Embed `Fin n` into `Fin (n + 1)` by inserting
around a specified pivot `p : Fin (n + 1)` into the `univ` -/
theorem Fin.univ_succAbove (n : ℕ) (p : Fin (n + 1)) :
(univ : Finset (Fin (n + 1))) = Finset.cons p (univ.map <| Fin.succAboveEmb p) (by simp) := by
simp [map_eq_image]
@[simp] theorem Fin.univ_image_get [DecidableEq α] (l : List α) :
Finset.univ.image l.get = l.toFinset := by
simp [univ_image_def]
@[simp] theorem Fin.univ_image_getElem' [DecidableEq β] (l : List α) (f : α → β) :
Finset.univ.image (fun i : Fin l.length => f <| l[(i : Nat)]) = (l.map f).toFinset := by
simp only [univ_image_def, List.ofFn_getElem_eq_map]
theorem Fin.univ_image_get' [DecidableEq β] (l : List α) (f : α → β) :
Finset.univ.image (f <| l.get ·) = (l.map f).toFinset := by
simp
@[instance]
def Unique.fintype {α : Type*} [Unique α] : Fintype α :=
Fintype.ofSubsingleton default
/-- Short-circuit instance to decrease search for `Unique.fintype`,
since that relies on a subsingleton elimination for `Unique`. -/
instance Fintype.subtypeEq (y : α) : Fintype { x // x = y } :=
Fintype.subtype {y} (by simp)
/-- Short-circuit instance to decrease search for `Unique.fintype`,
since that relies on a subsingleton elimination for `Unique`. -/
instance Fintype.subtypeEq' (y : α) : Fintype { x // y = x } :=
Fintype.subtype {y} (by simp [eq_comm])
theorem Fintype.univ_empty : @univ Empty _ = ∅ :=
rfl
theorem Fintype.univ_pempty : @univ PEmpty _ = ∅ :=
rfl
instance Unit.fintype : Fintype Unit :=
Fintype.ofSubsingleton ()
theorem Fintype.univ_unit : @univ Unit _ = {()} :=
rfl
instance PUnit.fintype : Fintype PUnit :=
Fintype.ofSubsingleton PUnit.unit
theorem Fintype.univ_punit : @univ PUnit _ = {PUnit.unit} :=
rfl
@[simp]
theorem Fintype.univ_bool : @univ Bool _ = {true, false} :=
rfl
/-- Given that `α × β` is a fintype, `α` is also a fintype. -/
def Fintype.prodLeft {α β} [DecidableEq α] [Fintype (α × β)] [Nonempty β] : Fintype α :=
⟨(@univ (α × β) _).image Prod.fst, fun a => by simp⟩
/-- Given that `α × β` is a fintype, `β` is also a fintype. -/
def Fintype.prodRight {α β} [DecidableEq β] [Fintype (α × β)] [Nonempty α] : Fintype β :=
⟨(@univ (α × β) _).image Prod.snd, fun b => by simp⟩
instance ULift.fintype (α : Type*) [Fintype α] : Fintype (ULift α) :=
Fintype.ofEquiv _ Equiv.ulift.symm
instance PLift.fintype (α : Type*) [Fintype α] : Fintype (PLift α) :=
Fintype.ofEquiv _ Equiv.plift.symm
instance PLift.fintypeProp (p : Prop) [Decidable p] : Fintype (PLift p) :=
⟨if h : p then {⟨h⟩} else ∅, fun ⟨h⟩ => by simp [h]⟩
instance Quotient.fintype [Fintype α] (s : Setoid α) [DecidableRel ((· ≈ ·) : α → α → Prop)] :
Fintype (Quotient s) :=
Fintype.ofSurjective Quotient.mk'' Quotient.mk''_surjective
instance PSigma.fintypePropLeft {α : Prop} {β : α → Type*} [Decidable α] [∀ a, Fintype (β a)] :
Fintype (Σ'a, β a) :=
if h : α then Fintype.ofEquiv (β h) ⟨fun x => ⟨h, x⟩, PSigma.snd, fun _ => rfl, fun ⟨_, _⟩ => rfl⟩
else ⟨∅, fun x => (h x.1).elim⟩
instance PSigma.fintypePropRight {α : Type*} {β : α → Prop} [∀ a, Decidable (β a)] [Fintype α] :
Fintype (Σ'a, β a) :=
Fintype.ofEquiv { a // β a }
⟨fun ⟨x, y⟩ => ⟨x, y⟩, fun ⟨x, y⟩ => ⟨x, y⟩, fun ⟨_, _⟩ => rfl, fun ⟨_, _⟩ => rfl⟩
instance PSigma.fintypePropProp {α : Prop} {β : α → Prop} [Decidable α] [∀ a, Decidable (β a)] :
Fintype (Σ'a, β a) :=
if h : ∃ a, β a then ⟨{⟨h.fst, h.snd⟩}, fun ⟨_, _⟩ => by simp⟩ else ⟨∅, fun ⟨x, y⟩ =>
(h ⟨x, y⟩).elim⟩
instance pfunFintype (p : Prop) [Decidable p] (α : p → Type*) [∀ hp, Fintype (α hp)] :
Fintype (∀ hp : p, α hp) :=
if hp : p then Fintype.ofEquiv (α hp) ⟨fun a _ => a, fun f => f hp, fun _ => rfl, fun _ => rfl⟩
else ⟨singleton fun h => (hp h).elim, fun h => mem_singleton.2
(funext fun x => by contradiction)⟩
section Trunc
/-- For `s : Multiset α`, we can lift the existential statement that `∃ x, x ∈ s` to a `Trunc α`.
-/
def truncOfMultisetExistsMem {α} (s : Multiset α) : (∃ x, x ∈ s) → Trunc α :=
Quotient.recOnSubsingleton s fun l h =>
match l, h with
| [], _ => False.elim (by tauto)
| a :: _, _ => Trunc.mk a
/-- A `Nonempty` `Fintype` constructively contains an element.
-/
def truncOfNonemptyFintype (α) [Nonempty α] [Fintype α] : Trunc α :=
truncOfMultisetExistsMem Finset.univ.val (by simp)
/-- By iterating over the elements of a fintype, we can lift an existential statement `∃ a, P a`
to `Trunc (Σ' a, P a)`, containing data.
-/
def truncSigmaOfExists {α} [Fintype α] {P : α → Prop} [DecidablePred P] (h : ∃ a, P a) :
Trunc (Σ'a, P a) :=
@truncOfNonemptyFintype (Σ'a, P a) ((Exists.elim h) fun a ha => ⟨⟨a, ha⟩⟩) _
end Trunc
namespace Multiset
variable [Fintype α] [Fintype β]
@[simp]
theorem count_univ [DecidableEq α] (a : α) : count a Finset.univ.val = 1 :=
count_eq_one_of_mem Finset.univ.nodup (Finset.mem_univ _)
@[simp]
theorem map_univ_val_equiv (e : α ≃ β) :
map e univ.val = univ.val := by
rw [← congr_arg Finset.val (Finset.map_univ_equiv e), Finset.map_val, Equiv.coe_toEmbedding]
/-- For functions on finite sets, they are bijections iff they map universes into universes. -/
@[simp]
theorem bijective_iff_map_univ_eq_univ (f : α → β) :
f.Bijective ↔ map f (Finset.univ : Finset α).val = univ.val :=
⟨fun bij ↦ congr_arg (·.val) (map_univ_equiv <| Equiv.ofBijective f bij),
fun eq ↦ ⟨
fun a₁ a₂ ↦ inj_on_of_nodup_map (eq.symm ▸ univ.nodup) _ (mem_univ a₁) _ (mem_univ a₂),
fun b ↦ have ⟨a, _, h⟩ := mem_map.mp (eq.symm ▸ mem_univ_val b); ⟨a, h⟩⟩⟩
end Multiset
/-- Auxiliary definition to show `exists_seq_of_forall_finset_exists`. -/
noncomputable def seqOfForallFinsetExistsAux {α : Type*} [DecidableEq α] (P : α → Prop)
(r : α → α → Prop) (h : ∀ s : Finset α, ∃ y, (∀ x ∈ s, P x) → P y ∧ ∀ x ∈ s, r x y) : ℕ → α
| n =>
Classical.choose
(h
(Finset.image (fun i : Fin n => seqOfForallFinsetExistsAux P r h i)
(Finset.univ : Finset (Fin n))))
/-- Induction principle to build a sequence, by adding one point at a time satisfying a given
relation with respect to all the previously chosen points.
More precisely, Assume that, for any finite set `s`, one can find another point satisfying
some relation `r` with respect to all the points in `s`. Then one may construct a
function `f : ℕ → α` such that `r (f m) (f n)` holds whenever `m < n`.
We also ensure that all constructed points satisfy a given predicate `P`. -/
theorem exists_seq_of_forall_finset_exists {α : Type*} (P : α → Prop) (r : α → α → Prop)
(h : ∀ s : Finset α, (∀ x ∈ s, P x) → ∃ y, P y ∧ ∀ x ∈ s, r x y) :
∃ f : ℕ → α, (∀ n, P (f n)) ∧ ∀ m n, m < n → r (f m) (f n) := by
classical
have : Nonempty α := by
rcases h ∅ (by simp) with ⟨y, _⟩
exact ⟨y⟩
choose! F hF using h
have h' : ∀ s : Finset α, ∃ y, (∀ x ∈ s, P x) → P y ∧ ∀ x ∈ s, r x y := fun s => ⟨F s, hF s⟩
set f := seqOfForallFinsetExistsAux P r h' with hf
have A : ∀ n : ℕ, P (f n) := by
intro n
induction' n using Nat.strong_induction_on with n IH
have IH' : ∀ x : Fin n, P (f x) := fun n => IH n.1 n.2
rw [hf, seqOfForallFinsetExistsAux]
exact
(Classical.choose_spec
(h' (Finset.image (fun i : Fin n => f i) (Finset.univ : Finset (Fin n))))
(by simp [IH'])).1
refine ⟨f, A, fun m n hmn => ?_⟩
conv_rhs => rw [hf]
rw [seqOfForallFinsetExistsAux]
apply
(Classical.choose_spec
(h' (Finset.image (fun i : Fin n => f i) (Finset.univ : Finset (Fin n)))) (by simp [A])).2
exact Finset.mem_image.2 ⟨⟨m, hmn⟩, Finset.mem_univ _, rfl⟩
/-- Induction principle to build a sequence, by adding one point at a time satisfying a given
symmetric relation with respect to all the previously chosen points.
More precisely, Assume that, for any finite set `s`, one can find another point satisfying
some relation `r` with respect to all the points in `s`. Then one may construct a
function `f : ℕ → α` such that `r (f m) (f n)` holds whenever `m ≠ n`.
We also ensure that all constructed points satisfy a given predicate `P`. -/
theorem exists_seq_of_forall_finset_exists' {α : Type*} (P : α → Prop) (r : α → α → Prop)
[IsSymm α r] (h : ∀ s : Finset α, (∀ x ∈ s, P x) → ∃ y, P y ∧ ∀ x ∈ s, r x y) :
∃ f : ℕ → α, (∀ n, P (f n)) ∧ Pairwise (r on f) := by
rcases exists_seq_of_forall_finset_exists P r h with ⟨f, hf, hf'⟩
refine ⟨f, hf, fun m n hmn => ?_⟩
rcases lt_trichotomy m n with (h | rfl | h)
· exact hf' m n h
· exact (hmn rfl).elim
· unfold Function.onFun
apply symm
exact hf' n m h
| Mathlib/Data/Fintype/Basic.lean | 794 | 797 | |
/-
Copyright (c) 2020 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel, Adam Topaz, Johan Commelin, Jakob von Raumer
-/
import Mathlib.Algebra.Homology.ImageToKernel
import Mathlib.Algebra.Homology.ShortComplex.Exact
import Mathlib.CategoryTheory.Abelian.Opposite
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Zero
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
import Mathlib.CategoryTheory.Adjunction.Limits
import Mathlib.Tactic.TFAE
/-!
# Exact sequences in abelian categories
In an abelian category, we get several interesting results related to exactness which are not
true in more general settings.
## Main results
* A short complex `S` is exact iff `imageSubobject S.f = kernelSubobject S.g`.
* If `(f, g)` is exact, then `image.ι f` has the universal property of the kernel of `g`.
* `f` is a monomorphism iff `kernel.ι f = 0` iff `Exact 0 f`, and `f` is an epimorphism iff
`cokernel.π = 0` iff `Exact f 0`.
* A faithful functor between abelian categories that preserves zero morphisms reflects exact
sequences.
* `X ⟶ Y ⟶ Z ⟶ 0` is exact if and only if the second map is a cokernel of the first, and
`0 ⟶ X ⟶ Y ⟶ Z` is exact if and only if the first map is a kernel of the second.
* A functor `F` such that for all `S`, we have `S.Exact → (S.map F).Exact` preserves both
finite limits and colimits.
-/
universe v₁ v₂ u₁ u₂
noncomputable section
open CategoryTheory Limits Preadditive
variable {C : Type u₁} [Category.{v₁} C] [Abelian C]
namespace CategoryTheory
namespace ShortComplex
variable (S : ShortComplex C)
attribute [local instance] hasEqualizers_of_hasKernels
theorem exact_iff_epi_imageToKernel' : S.Exact ↔ Epi (imageToKernel' S.f S.g S.zero) := by
rw [S.exact_iff_epi_kernel_lift]
have : factorThruImage S.f ≫ imageToKernel' S.f S.g S.zero = kernel.lift S.g S.f S.zero := by
simp only [← cancel_mono (kernel.ι _), kernel.lift_ι, imageToKernel',
Category.assoc, image.fac]
constructor
· intro
exact epi_of_epi_fac this
· intro
rw [← this]
apply epi_comp
theorem exact_iff_epi_imageToKernel : S.Exact ↔ Epi (imageToKernel S.f S.g S.zero) := by
rw [S.exact_iff_epi_imageToKernel']
apply (MorphismProperty.epimorphisms C).arrow_mk_iso_iff
exact Arrow.isoMk (imageSubobjectIso S.f).symm (kernelSubobjectIso S.g).symm
theorem exact_iff_isIso_imageToKernel : S.Exact ↔ IsIso (imageToKernel S.f S.g S.zero) := by
rw [S.exact_iff_epi_imageToKernel]
constructor
· intro
apply isIso_of_mono_of_epi
· intro
infer_instance
/-- In an abelian category, a short complex `S` is exact
iff `imageSubobject S.f = kernelSubobject S.g`.
-/
theorem exact_iff_image_eq_kernel : S.Exact ↔ imageSubobject S.f = kernelSubobject S.g := by
rw [exact_iff_isIso_imageToKernel]
constructor
· intro
exact Subobject.eq_of_comm (asIso (imageToKernel _ _ S.zero)) (by simp)
· intro h
exact ⟨Subobject.ofLE _ _ h.ge, by ext; simp, by ext; simp⟩
theorem exact_iff_of_forks {cg : KernelFork S.g} (hg : IsLimit cg) {cf : CokernelCofork S.f}
(hf : IsColimit cf) : S.Exact ↔ cg.ι ≫ cf.π = 0 := by
rw [exact_iff_kernel_ι_comp_cokernel_π_zero]
let e₁ := IsLimit.conePointUniqueUpToIso (kernelIsKernel S.g) hg
let e₂ := IsColimit.coconePointUniqueUpToIso (cokernelIsCokernel S.f) hf
have : cg.ι ≫ cf.π = e₁.inv ≫ kernel.ι S.g ≫ cokernel.π S.f ≫ e₂.hom := by
have eq₁ := IsLimit.conePointUniqueUpToIso_inv_comp (kernelIsKernel S.g) hg (.zero)
have eq₂ := IsColimit.comp_coconePointUniqueUpToIso_hom (cokernelIsCokernel S.f) hf (.one)
dsimp at eq₁ eq₂
rw [← eq₁, ← eq₂, Category.assoc]
rw [this, IsIso.comp_left_eq_zero e₁.inv, ← Category.assoc,
IsIso.comp_right_eq_zero _ e₂.hom]
variable {S}
/-- If `(f, g)` is exact, then `Abelian.image.ι S.f` is a kernel of `S.g`. -/
def Exact.isLimitImage (h : S.Exact) :
IsLimit (KernelFork.ofι (Abelian.image.ι S.f)
(Abelian.image_ι_comp_eq_zero S.zero) : KernelFork S.g) := by
rw [exact_iff_kernel_ι_comp_cokernel_π_zero] at h
exact KernelFork.IsLimit.ofι _ _
(fun u hu ↦ kernel.lift (cokernel.π S.f) u
(by rw [← kernel.lift_ι S.g u hu, Category.assoc, h, comp_zero])) (by simp)
(fun _ _ _ hm => by rw [← cancel_mono (Abelian.image.ι S.f), hm, kernel.lift_ι])
/-- If `(f, g)` is exact, then `image.ι f` is a kernel of `g`. -/
def Exact.isLimitImage' (h : S.Exact) :
IsLimit (KernelFork.ofι (Limits.image.ι S.f)
(image_ι_comp_eq_zero S.zero) : KernelFork S.g) :=
IsKernel.isoKernel _ _ h.isLimitImage (Abelian.imageIsoImage S.f).symm <| IsImage.lift_fac _ _
/-- If `(f, g)` is exact, then `Abelian.coimage.π g` is a cokernel of `f`. -/
def Exact.isColimitCoimage (h : S.Exact) :
IsColimit
(CokernelCofork.ofπ (Abelian.coimage.π S.g) (Abelian.comp_coimage_π_eq_zero S.zero) :
CokernelCofork S.f) := by
rw [exact_iff_kernel_ι_comp_cokernel_π_zero] at h
refine CokernelCofork.IsColimit.ofπ _ _
(fun u hu => cokernel.desc (kernel.ι S.g) u
(by rw [← cokernel.π_desc S.f u hu, ← Category.assoc, h, zero_comp]))
(by simp) ?_
intros _ _ _ _ hm
ext
rw [hm, cokernel.π_desc]
/-- If `(f, g)` is exact, then `factorThruImage g` is a cokernel of `f`. -/
def Exact.isColimitImage (h : S.Exact) :
IsColimit (CokernelCofork.ofπ (Limits.factorThruImage S.g)
(comp_factorThruImage_eq_zero S.zero)) :=
IsCokernel.cokernelIso _ _ h.isColimitCoimage (Abelian.coimageIsoImage' S.g) <|
(cancel_mono (Limits.image.ι S.g)).1 <| by simp
theorem exact_kernel {X Y : C} (f : X ⟶ Y) :
(ShortComplex.mk (kernel.ι f) f (by simp)).Exact :=
exact_of_f_is_kernel _ (kernelIsKernel f)
theorem exact_cokernel {X Y : C} (f : X ⟶ Y) :
(ShortComplex.mk f (cokernel.π f) (by simp)).Exact :=
exact_of_g_is_cokernel _ (cokernelIsCokernel f)
variable (S)
theorem exact_iff_exact_image_ι :
S.Exact ↔ (ShortComplex.mk (Abelian.image.ι S.f) S.g
(Abelian.image_ι_comp_eq_zero S.zero)).Exact :=
ShortComplex.exact_iff_of_epi_of_isIso_of_mono
{ τ₁ := Abelian.factorThruImage S.f
τ₂ := 𝟙 _
τ₃ := 𝟙 _ }
theorem exact_iff_exact_coimage_π :
S.Exact ↔ (ShortComplex.mk S.f (Abelian.coimage.π S.g)
(Abelian.comp_coimage_π_eq_zero S.zero)).Exact := by
symm
exact ShortComplex.exact_iff_of_epi_of_isIso_of_mono
{ τ₁ := 𝟙 _
τ₂ := 𝟙 _
τ₃ := Abelian.factorThruCoimage S.g }
end ShortComplex
section
open List in
theorem Abelian.tfae_mono {X Y : C} (f : X ⟶ Y) (Z : C) :
TFAE [Mono f, kernel.ι f = 0, (ShortComplex.mk (0 : Z ⟶ X) f zero_comp).Exact] := by
tfae_have 2 → 1 := mono_of_kernel_ι_eq_zero _
tfae_have 1 → 2
| _ => by rw [← cancel_mono f, kernel.condition, zero_comp]
tfae_have 3 ↔ 1 := ShortComplex.exact_iff_mono _ (by simp)
tfae_finish
open List in
theorem Abelian.tfae_epi {X Y : C} (f : X ⟶ Y) (Z : C) :
TFAE [Epi f, cokernel.π f = 0, (ShortComplex.mk f (0 : Y ⟶ Z) comp_zero).Exact] := by
tfae_have 2 → 1 := epi_of_cokernel_π_eq_zero _
tfae_have 1 → 2
| _ => by rw [← cancel_epi f, cokernel.condition, comp_zero]
tfae_have 3 ↔ 1 := ShortComplex.exact_iff_epi _ (by simp)
tfae_finish
end
namespace Functor
section
variable {D : Type u₂} [Category.{v₂} D] [Abelian D]
variable (F : C ⥤ D) [PreservesZeroMorphisms F]
lemma reflects_exact_of_faithful [F.Faithful] (S : ShortComplex C) (hS : (S.map F).Exact) :
S.Exact := by
| rw [ShortComplex.exact_iff_kernel_ι_comp_cokernel_π_zero] at hS ⊢
dsimp at hS
apply F.zero_of_map_zero
obtain ⟨k, hk⟩ :=
kernel.lift' (F.map S.g) (F.map (kernel.ι S.g))
| Mathlib/CategoryTheory/Abelian/Exact.lean | 198 | 202 |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Matrix.Basis
import Mathlib.Data.Matrix.DMatrix
import Mathlib.LinearAlgebra.Matrix.Determinant.Basic
import Mathlib.LinearAlgebra.Matrix.Reindex
import Mathlib.Tactic.FieldSimp
/-!
# Transvections
Transvections are matrices of the form `1 + stdBasisMatrix i j c`, where `stdBasisMatrix i j c`
is the basic matrix with a `c` at position `(i, j)`. Multiplying by such a transvection on the left
(resp. on the right) amounts to adding `c` times the `j`-th row to the `i`-th row
(resp `c` times the `i`-th column to the `j`-th column). Therefore, they are useful to present
algorithms operating on rows and columns.
Transvections are a special case of *elementary matrices* (according to most references, these also
contain the matrices exchanging rows, and the matrices multiplying a row by a constant).
We show that, over a field, any matrix can be written as `L * D * L'`, where `L` and `L'` are
products of transvections and `D` is diagonal. In other words, one can reduce a matrix to diagonal
form by operations on its rows and columns, a variant of Gauss' pivot algorithm.
## Main definitions and results
* `transvection i j c` is the matrix equal to `1 + stdBasisMatrix i j c`.
* `TransvectionStruct n R` is a structure containing the data of `i, j, c` and a proof that
`i ≠ j`. These are often easier to manipulate than straight matrices, especially in inductive
arguments.
* `exists_list_transvec_mul_diagonal_mul_list_transvec` states that any matrix `M` over a field can
be written in the form `t_1 * ... * t_k * D * t'_1 * ... * t'_l`, where `D` is diagonal and
the `t_i`, `t'_j` are transvections.
* `diagonal_transvection_induction` shows that a property which is true for diagonal matrices and
transvections, and invariant under product, is true for all matrices.
* `diagonal_transvection_induction_of_det_ne_zero` is the same statement over invertible matrices.
## Implementation details
The proof of the reduction results is done inductively on the size of the matrices, reducing an
`(r + 1) × (r + 1)` matrix to a matrix whose last row and column are zeroes, except possibly for
the last diagonal entry. This step is done as follows.
If all the coefficients on the last row and column are zero, there is nothing to do. Otherwise,
one can put a nonzero coefficient in the last diagonal entry by a row or column operation, and then
subtract this last diagonal entry from the other entries in the last row and column to make them
vanish.
This step is done in the type `Fin r ⊕ Unit`, where `Fin r` is useful to choose arbitrarily some
order in which we cancel the coefficients, and the sum structure is useful to use the formalism of
block matrices.
To proceed with the induction, we reindex our matrices to reduce to the above situation.
-/
universe u₁ u₂
namespace Matrix
variable (n p : Type*) (R : Type u₂) {𝕜 : Type*} [Field 𝕜]
variable [DecidableEq n] [DecidableEq p]
variable [CommRing R]
section Transvection
variable {R n} (i j : n)
/-- The transvection matrix `transvection i j c` is equal to the identity plus `c` at position
`(i, j)`. Multiplying by it on the left (as in `transvection i j c * M`) corresponds to adding
`c` times the `j`-th row of `M` to its `i`-th row. Multiplying by it on the right corresponds
to adding `c` times the `i`-th column to the `j`-th column. -/
def transvection (c : R) : Matrix n n R :=
1 + Matrix.stdBasisMatrix i j c
@[simp]
theorem transvection_zero : transvection i j (0 : R) = 1 := by simp [transvection]
section
/-- A transvection matrix is obtained from the identity by adding `c` times the `j`-th row to
the `i`-th row. -/
theorem updateRow_eq_transvection [Finite n] (c : R) :
updateRow (1 : Matrix n n R) i ((1 : Matrix n n R) i + c • (1 : Matrix n n R) j) =
transvection i j c := by
cases nonempty_fintype n
ext a b
by_cases ha : i = a
· by_cases hb : j = b
· simp only [ha, updateRow_self, Pi.add_apply, one_apply, Pi.smul_apply, hb, ↓reduceIte,
smul_eq_mul, mul_one, transvection, add_apply, StdBasisMatrix.apply_same]
· simp only [ha, updateRow_self, Pi.add_apply, one_apply, Pi.smul_apply, hb, ↓reduceIte,
smul_eq_mul, mul_zero, add_zero, transvection, add_apply, and_false, not_false_eq_true,
StdBasisMatrix.apply_of_ne]
· simp only [updateRow_ne, transvection, ha, Ne.symm ha, StdBasisMatrix.apply_of_ne, add_zero,
Algebra.id.smul_eq_mul, Ne, not_false_iff, DMatrix.add_apply, Pi.smul_apply,
mul_zero, false_and, add_apply]
variable [Fintype n]
theorem transvection_mul_transvection_same (h : i ≠ j) (c d : R) :
transvection i j c * transvection i j d = transvection i j (c + d) := by
simp [transvection, Matrix.add_mul, Matrix.mul_add, h, h.symm, add_smul, add_assoc,
stdBasisMatrix_add]
@[simp]
theorem transvection_mul_apply_same (b : n) (c : R) (M : Matrix n n R) :
(transvection i j c * M) i b = M i b + c * M j b := by simp [transvection, Matrix.add_mul]
@[simp]
theorem mul_transvection_apply_same (a : n) (c : R) (M : Matrix n n R) :
(M * transvection i j c) a j = M a j + c * M a i := by
simp [transvection, Matrix.mul_add, mul_comm]
@[simp]
theorem transvection_mul_apply_of_ne (a b : n) (ha : a ≠ i) (c : R) (M : Matrix n n R) :
(transvection i j c * M) a b = M a b := by simp [transvection, Matrix.add_mul, ha]
@[simp]
theorem mul_transvection_apply_of_ne (a b : n) (hb : b ≠ j) (c : R) (M : Matrix n n R) :
(M * transvection i j c) a b = M a b := by simp [transvection, Matrix.mul_add, hb]
@[simp]
theorem det_transvection_of_ne (h : i ≠ j) (c : R) : det (transvection i j c) = 1 := by
rw [← updateRow_eq_transvection i j, det_updateRow_add_smul_self _ h, det_one]
end
variable (R n)
/-- A structure containing all the information from which one can build a nontrivial transvection.
This structure is easier to manipulate than transvections as one has a direct access to all the
relevant fields. -/
structure TransvectionStruct where
(i j : n)
hij : i ≠ j
c : R
instance [Nontrivial n] : Nonempty (TransvectionStruct n R) := by
choose x y hxy using exists_pair_ne n
exact ⟨⟨x, y, hxy, 0⟩⟩
namespace TransvectionStruct
variable {R n}
/-- Associating to a `transvection_struct` the corresponding transvection matrix. -/
def toMatrix (t : TransvectionStruct n R) : Matrix n n R :=
transvection t.i t.j t.c
@[simp]
theorem toMatrix_mk (i j : n) (hij : i ≠ j) (c : R) :
TransvectionStruct.toMatrix ⟨i, j, hij, c⟩ = transvection i j c :=
rfl
@[simp]
protected theorem det [Fintype n] (t : TransvectionStruct n R) : det t.toMatrix = 1 :=
det_transvection_of_ne _ _ t.hij _
@[simp]
theorem det_toMatrix_prod [Fintype n] (L : List (TransvectionStruct n 𝕜)) :
det (L.map toMatrix).prod = 1 := by
induction L with
| nil => simp
| cons _ _ IH => simp [IH]
/-- The inverse of a `TransvectionStruct`, designed so that `t.inv.toMatrix` is the inverse of
`t.toMatrix`. -/
@[simps]
protected def inv (t : TransvectionStruct n R) : TransvectionStruct n R where
i := t.i
j := t.j
hij := t.hij
c := -t.c
section
variable [Fintype n]
|
theorem inv_mul (t : TransvectionStruct n R) : t.inv.toMatrix * t.toMatrix = 1 := by
rcases t with ⟨_, _, t_hij⟩
simp [toMatrix, transvection_mul_transvection_same, t_hij]
| Mathlib/LinearAlgebra/Matrix/Transvection.lean | 184 | 188 |
/-
Copyright (c) 2024 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.Cardinal.Arithmetic
import Mathlib.SetTheory.Ordinal.Principal
/-!
# Ordinal arithmetic with cardinals
This file collects results about the cardinality of different ordinal operations.
-/
universe u v
open Cardinal Ordinal Set
/-! ### Cardinal operations with ordinal indices -/
namespace Cardinal
/-- Bounds the cardinal of an ordinal-indexed union of sets. -/
lemma mk_iUnion_Ordinal_lift_le_of_le {β : Type v} {o : Ordinal.{u}} {c : Cardinal.{v}}
(ho : lift.{v} o.card ≤ lift.{u} c) (hc : ℵ₀ ≤ c) (A : Ordinal → Set β)
(hA : ∀ j < o, #(A j) ≤ c) : #(⋃ j < o, A j) ≤ c := by
simp_rw [← mem_Iio, biUnion_eq_iUnion, iUnion, iSup, ← o.enumIsoToType.symm.surjective.range_comp]
rw [← lift_le.{u}]
apply ((mk_iUnion_le_lift _).trans _).trans_eq (mul_eq_self (aleph0_le_lift.2 hc))
rw [mk_toType]
refine mul_le_mul' ho (ciSup_le' ?_)
intro i
simpa using hA _ (o.enumIsoToType.symm i).2
lemma mk_iUnion_Ordinal_le_of_le {β : Type*} {o : Ordinal} {c : Cardinal}
(ho : o.card ≤ c) (hc : ℵ₀ ≤ c) (A : Ordinal → Set β)
(hA : ∀ j < o, #(A j) ≤ c) : #(⋃ j < o, A j) ≤ c := by
apply mk_iUnion_Ordinal_lift_le_of_le _ hc A hA
rwa [Cardinal.lift_le]
end Cardinal
@[deprecated mk_iUnion_Ordinal_le_of_le (since := "2024-11-02")]
alias Ordinal.Cardinal.mk_iUnion_Ordinal_le_of_le := mk_iUnion_Ordinal_le_of_le
/-! ### Cardinality of ordinals -/
namespace Ordinal
theorem lift_card_iSup_le_sum_card {ι : Type u} [Small.{v} ι] (f : ι → Ordinal.{v}) :
Cardinal.lift.{u} (⨆ i, f i).card ≤ Cardinal.sum fun i ↦ (f i).card := by
simp_rw [← mk_toType]
rw [← mk_sigma, ← Cardinal.lift_id'.{v} #(Σ _, _), ← Cardinal.lift_umax.{v, u}]
apply lift_mk_le_lift_mk_of_surjective (f := enumIsoToType _ ∘ (⟨(enumIsoToType _).symm ·.2,
(mem_Iio.mp ((enumIsoToType _).symm _).2).trans_le (Ordinal.le_iSup _ _)⟩))
rw [EquivLike.comp_surjective]
rintro ⟨x, hx⟩
obtain ⟨i, hi⟩ := Ordinal.lt_iSup_iff.mp hx
exact ⟨⟨i, enumIsoToType _ ⟨x, hi⟩⟩, by simp⟩
theorem card_iSup_le_sum_card {ι : Type u} (f : ι → Ordinal.{max u v}) :
(⨆ i, f i).card ≤ Cardinal.sum (fun i ↦ (f i).card) := by
have := lift_card_iSup_le_sum_card f
rwa [Cardinal.lift_id'] at this
theorem card_iSup_Iio_le_sum_card {o : Ordinal.{u}} (f : Iio o → Ordinal.{max u v}) :
(⨆ a : Iio o, f a).card ≤ Cardinal.sum fun i ↦ (f ((enumIsoToType o).symm i)).card := by
apply le_of_eq_of_le (congr_arg _ _).symm (card_iSup_le_sum_card _)
simpa using (enumIsoToType o).symm.iSup_comp (g := fun x ↦ f x)
theorem card_iSup_Iio_le_card_mul_iSup {o : Ordinal.{u}} (f : Iio o → Ordinal.{max u v}) :
(⨆ a : Iio o, f a).card ≤ Cardinal.lift.{v} o.card * ⨆ a : Iio o, (f a).card := by
apply (card_iSup_Iio_le_sum_card f).trans
convert ← sum_le_iSup_lift _
· exact mk_toType o
· exact (enumIsoToType o).symm.iSup_comp (g := fun x ↦ (f x).card)
theorem card_opow_le_of_omega0_le_left {a : Ordinal} (ha : ω ≤ a) (b : Ordinal) :
(a ^ b).card ≤ max a.card b.card := by
refine limitRecOn b ?_ ?_ ?_
· simpa using one_lt_omega0.le.trans ha
· intro b IH
rw [opow_succ, card_mul, card_succ, Cardinal.mul_eq_max_of_aleph0_le_right, max_comm]
· apply (max_le_max_left _ IH).trans
rw [← max_assoc, max_self]
exact max_le_max_left _ le_self_add
· rw [ne_eq, card_eq_zero, opow_eq_zero]
rintro ⟨rfl, -⟩
cases omega0_pos.not_le ha
· rwa [aleph0_le_card]
· intro b hb IH
rw [(isNormal_opow (one_lt_omega0.trans_le ha)).apply_of_isLimit hb]
apply (card_iSup_Iio_le_card_mul_iSup _).trans
rw [Cardinal.lift_id, Cardinal.mul_eq_max_of_aleph0_le_right, max_comm]
· apply max_le _ (le_max_right _ _)
apply ciSup_le'
intro c
exact (IH c.1 c.2).trans (max_le_max_left _ (card_le_card c.2.le))
· simpa using hb.pos.ne'
· refine le_ciSup_of_le ?_ ⟨1, one_lt_omega0.trans_le <| omega0_le_of_isLimit hb⟩ ?_
· exact Cardinal.bddAbove_of_small _
· simpa
theorem card_opow_le_of_omega0_le_right (a : Ordinal) {b : Ordinal} (hb : ω ≤ b) :
(a ^ b).card ≤ max a.card b.card := by
obtain ⟨n, rfl⟩ | ha := eq_nat_or_omega0_le a
· apply (card_le_card <| opow_le_opow_left b (nat_lt_omega0 n).le).trans
apply (card_opow_le_of_omega0_le_left le_rfl _).trans
simp [hb]
· exact card_opow_le_of_omega0_le_left ha b
theorem card_opow_le (a b : Ordinal) : (a ^ b).card ≤ max ℵ₀ (max a.card b.card) := by
obtain ⟨n, rfl⟩ | ha := eq_nat_or_omega0_le a
· obtain ⟨m, rfl⟩ | hb := eq_nat_or_omega0_le b
· rw [← natCast_opow, card_nat]
exact le_max_of_le_left (nat_lt_aleph0 _).le
· exact (card_opow_le_of_omega0_le_right _ hb).trans (le_max_right _ _)
· exact (card_opow_le_of_omega0_le_left ha _).trans (le_max_right _ _)
theorem card_opow_eq_of_omega0_le_left {a b : Ordinal} (ha : ω ≤ a) (hb : 0 < b) :
(a ^ b).card = max a.card b.card := by
apply (card_opow_le_of_omega0_le_left ha b).antisymm (max_le _ _) <;> apply card_le_card
· exact left_le_opow a hb
· exact right_le_opow b (one_lt_omega0.trans_le ha)
theorem card_opow_eq_of_omega0_le_right {a b : Ordinal} (ha : 1 < a) (hb : ω ≤ b) :
(a ^ b).card = max a.card b.card := by
apply (card_opow_le_of_omega0_le_right a hb).antisymm (max_le _ _) <;> apply card_le_card
· exact left_le_opow a (omega0_pos.trans_le hb)
· exact right_le_opow b ha
theorem card_omega0_opow {a : Ordinal} (h : a ≠ 0) : card (ω ^ a) = max ℵ₀ a.card := by
rw [card_opow_eq_of_omega0_le_left le_rfl h.bot_lt, card_omega0]
theorem card_opow_omega0 {a : Ordinal} (h : 1 < a) : card (a ^ ω) = max ℵ₀ a.card := by
rw [card_opow_eq_of_omega0_le_right h le_rfl, card_omega0, max_comm]
theorem principal_opow_omega (o : Ordinal) : Principal (· ^ ·) (ω_ o) := by
obtain rfl | ho := Ordinal.eq_zero_or_pos o
· rw [omega_zero]
exact principal_opow_omega0
· intro a b ha hb
rw [lt_omega_iff_card_lt] at ha hb ⊢
apply (card_opow_le a b).trans_lt (max_lt _ (max_lt ha hb))
rwa [← aleph_zero, aleph_lt_aleph]
theorem IsInitial.principal_opow {o : Ordinal} (h : IsInitial o) (ho : ω ≤ o) :
Principal (· ^ ·) o := by
obtain ⟨a, rfl⟩ := mem_range_omega_iff.2 ⟨ho, h⟩
exact principal_opow_omega a
| theorem principal_opow_ord {c : Cardinal} (hc : ℵ₀ ≤ c) : Principal (· ^ ·) c.ord := by
apply (isInitial_ord c).principal_opow
| Mathlib/SetTheory/Cardinal/Ordinal.lean | 151 | 152 |
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Jeremy Avigad, Simon Hudon
-/
import Batteries.WF
import Mathlib.Data.Part
import Mathlib.Data.Rel
import Mathlib.Tactic.GeneralizeProofs
/-!
# Partial functions
This file defines partial functions. Partial functions are like functions, except they can also be
"undefined" on some inputs. We define them as functions `α → Part β`.
## Definitions
* `PFun α β`: Type of partial functions from `α` to `β`. Defined as `α → Part β` and denoted
`α →. β`.
* `PFun.Dom`: Domain of a partial function. Set of values on which it is defined. Not to be confused
with the domain of a function `α → β`, which is a type (`α` presently).
* `PFun.fn`: Evaluation of a partial function. Takes in an element and a proof it belongs to the
partial function's `Dom`.
* `PFun.asSubtype`: Returns a partial function as a function from its `Dom`.
* `PFun.toSubtype`: Restricts the codomain of a function to a subtype.
* `PFun.evalOpt`: Returns a partial function with a decidable `Dom` as a function `a → Option β`.
* `PFun.lift`: Turns a function into a partial function.
* `PFun.id`: The identity as a partial function.
* `PFun.comp`: Composition of partial functions.
* `PFun.restrict`: Restriction of a partial function to a smaller `Dom`.
* `PFun.res`: Turns a function into a partial function with a prescribed domain.
* `PFun.fix` : First return map of a partial function `f : α →. β ⊕ α`.
* `PFun.fix_induction`: A recursion principle for `PFun.fix`.
### Partial functions as relations
Partial functions can be considered as relations, so we specialize some `Rel` definitions to `PFun`:
* `PFun.image`: Image of a set under a partial function.
* `PFun.ran`: Range of a partial function.
* `PFun.preimage`: Preimage of a set under a partial function.
* `PFun.core`: Core of a set under a partial function.
* `PFun.graph`: Graph of a partial function `a →. β`as a `Set (α × β)`.
* `PFun.graph'`: Graph of a partial function `a →. β`as a `Rel α β`.
### `PFun α` as a monad
Monad operations:
* `PFun.pure`: The monad `pure` function, the constant `x` function.
* `PFun.bind`: The monad `bind` function, pointwise `Part.bind`
* `PFun.map`: The monad `map` function, pointwise `Part.map`.
-/
-- Pending rename in core.
alias WellFounded.fixF_eq := WellFounded.fixFEq
open Function
/-- `PFun α β`, or `α →. β`, is the type of partial functions from
`α` to `β`. It is defined as `α → Part β`. -/
def PFun (α β : Type*) :=
α → Part β
/-- `α →. β` is notation for the type `PFun α β` of partial functions from `α` to `β`. -/
infixr:25 " →. " => PFun
namespace PFun
variable {α β γ δ ε ι : Type*}
instance inhabited : Inhabited (α →. β) :=
⟨fun _ => Part.none⟩
/-- The domain of a partial function -/
def Dom (f : α →. β) : Set α :=
{ a | (f a).Dom }
@[simp]
theorem mem_dom (f : α →. β) (x : α) : x ∈ Dom f ↔ ∃ y, y ∈ f x := by simp [Dom, Part.dom_iff_mem]
@[simp]
theorem dom_mk (p : α → Prop) (f : ∀ a, p a → β) : (PFun.Dom fun x => ⟨p x, f x⟩) = { x | p x } :=
rfl
theorem dom_eq (f : α →. β) : Dom f = { x | ∃ y, y ∈ f x } :=
Set.ext (mem_dom f)
/-- Evaluate a partial function -/
def fn (f : α →. β) (a : α) : Dom f a → β :=
(f a).get
@[simp]
theorem fn_apply (f : α →. β) (a : α) : f.fn a = (f a).get :=
rfl
/-- Evaluate a partial function to return an `Option` -/
def evalOpt (f : α →. β) [D : DecidablePred (· ∈ Dom f)] (x : α) : Option β :=
@Part.toOption _ _ (D x)
/-- Partial function extensionality -/
theorem ext' {f g : α →. β} (H1 : ∀ a, a ∈ Dom f ↔ a ∈ Dom g) (H2 : ∀ a p q, f.fn a p = g.fn a q) :
f = g :=
funext fun a => Part.ext' (H1 a) (H2 a)
@[ext]
theorem ext {f g : α →. β} (H : ∀ a b, b ∈ f a ↔ b ∈ g a) : f = g :=
funext fun a => Part.ext (H a)
/-- Turns a partial function into a function out of its domain. -/
def asSubtype (f : α →. β) (s : f.Dom) : β :=
f.fn s s.2
/-- The type of partial functions `α →. β` is equivalent to
the type of pairs `(p : α → Prop, f : Subtype p → β)`. -/
def equivSubtype : (α →. β) ≃ Σp : α → Prop, Subtype p → β :=
⟨fun f => ⟨fun a => (f a).Dom, asSubtype f⟩, fun f x => ⟨f.1 x, fun h => f.2 ⟨x, h⟩⟩, fun _ =>
funext fun _ => Part.eta _, fun ⟨p, f⟩ => by dsimp; congr⟩
theorem asSubtype_eq_of_mem {f : α →. β} {x : α} {y : β} (fxy : y ∈ f x) (domx : x ∈ f.Dom) :
f.asSubtype ⟨x, domx⟩ = y :=
Part.mem_unique (Part.get_mem _) fxy
/-- Turn a total function into a partial function. -/
@[coe]
protected def lift (f : α → β) : α →. β := fun a => Part.some (f a)
instance coe : Coe (α → β) (α →. β) :=
⟨PFun.lift⟩
@[simp]
theorem coe_val (f : α → β) (a : α) : (f : α →. β) a = Part.some (f a) :=
rfl
@[simp]
theorem dom_coe (f : α → β) : (f : α →. β).Dom = Set.univ :=
rfl
theorem lift_injective : Injective (PFun.lift : (α → β) → α →. β) := fun _ _ h =>
funext fun a => Part.some_injective <| congr_fun h a
/-- Graph of a partial function `f` as the set of pairs `(x, f x)` where `x` is in the domain of
`f`. -/
def graph (f : α →. β) : Set (α × β) :=
{ p | p.2 ∈ f p.1 }
/-- Graph of a partial function as a relation. `x` and `y` are related iff `f x` is defined and
"equals" `y`. -/
def graph' (f : α →. β) : Rel α β := fun x y => y ∈ f x
/-- The range of a partial function is the set of values
`f x` where `x` is in the domain of `f`. -/
def ran (f : α →. β) : Set β :=
{ b | ∃ a, b ∈ f a }
/-- Restrict a partial function to a smaller domain. -/
def restrict (f : α →. β) {p : Set α} (H : p ⊆ f.Dom) : α →. β := fun x =>
(f x).restrict (x ∈ p) (@H x)
@[simp]
theorem mem_restrict {f : α →. β} {s : Set α} (h : s ⊆ f.Dom) (a : α) (b : β) :
b ∈ f.restrict h a ↔ a ∈ s ∧ b ∈ f a := by simp [restrict]
/-- Turns a function into a partial function with a prescribed domain. -/
def res (f : α → β) (s : Set α) : α →. β :=
(PFun.lift f).restrict s.subset_univ
theorem mem_res (f : α → β) (s : Set α) (a : α) (b : β) : b ∈ res f s a ↔ a ∈ s ∧ f a = b := by
simp [res, @eq_comm _ b]
theorem res_univ (f : α → β) : PFun.res f Set.univ = f :=
rfl
theorem dom_iff_graph (f : α →. β) (x : α) : x ∈ f.Dom ↔ ∃ y, (x, y) ∈ f.graph :=
Part.dom_iff_mem
theorem lift_graph {f : α → β} {a b} : (a, b) ∈ (f : α →. β).graph ↔ f a = b :=
show (∃ _ : True, f a = b) ↔ f a = b by simp
/-- The monad `pure` function, the total constant `x` function -/
protected def pure (x : β) : α →. β := fun _ => Part.some x
/-- The monad `bind` function, pointwise `Part.bind` -/
def bind (f : α →. β) (g : β → α →. γ) : α →. γ := fun a => (f a).bind fun b => g b a
@[simp]
theorem bind_apply (f : α →. β) (g : β → α →. γ) (a : α) : f.bind g a = (f a).bind fun b => g b a :=
rfl
/-- The monad `map` function, pointwise `Part.map` -/
def map (f : β → γ) (g : α →. β) : α →. γ := fun a => (g a).map f
instance monad : Monad (PFun α) where
pure := PFun.pure
bind := PFun.bind
map := PFun.map
instance lawfulMonad : LawfulMonad (PFun α) := LawfulMonad.mk'
(bind_pure_comp := fun _ _ => funext fun _ => Part.bind_some_eq_map _ _)
(id_map := fun f => by funext a; dsimp [Functor.map, PFun.map]; cases f a; rfl)
(pure_bind := fun x f => funext fun _ => Part.bind_some _ (f x))
(bind_assoc := fun f g k => funext fun a => (f a).bind_assoc (fun b => g b a) fun b => k b a)
theorem pure_defined (p : Set α) (x : β) : p ⊆ (@PFun.pure α _ x).Dom :=
p.subset_univ
theorem bind_defined {α β γ} (p : Set α) {f : α →. β} {g : β → α →. γ} (H1 : p ⊆ f.Dom)
(H2 : ∀ x, p ⊆ (g x).Dom) : p ⊆ (f >>= g).Dom := fun a ha =>
(⟨H1 ha, H2 _ ha⟩ : (f >>= g).Dom a)
/-- First return map. Transforms a partial function `f : α →. β ⊕ α` into the partial function
`α →. β` which sends `a : α` to the first value in `β` it hits by iterating `f`, if such a value
exists. By abusing notation to illustrate, either `f a` is in the `β` part of `β ⊕ α` (in which
case `f.fix a` returns `f a`), or it is undefined (in which case `f.fix a` is undefined as well), or
it is in the `α` part of `β ⊕ α` (in which case we repeat the procedure, so `f.fix a` will return
`f.fix (f a)`). -/
def fix (f : α →. β ⊕ α) : α →. β := fun a =>
Part.assert (Acc (fun x y => Sum.inr x ∈ f y) a) fun h =>
WellFounded.fixF
(fun a IH =>
Part.assert (f a).Dom fun hf =>
match e : (f a).get hf with
| Sum.inl b => Part.some b
| Sum.inr a' => IH a' ⟨hf, e⟩)
a h
theorem dom_of_mem_fix {f : α →. β ⊕ α} {a : α} {b : β} (h : b ∈ f.fix a) : (f a).Dom := by
let ⟨h₁, h₂⟩ := Part.mem_assert_iff.1 h
rw [WellFounded.fixF_eq] at h₂; exact h₂.fst.fst
theorem mem_fix_iff {f : α →. β ⊕ α} {a : α} {b : β} :
b ∈ f.fix a ↔ Sum.inl b ∈ f a ∨ ∃ a', Sum.inr a' ∈ f a ∧ b ∈ f.fix a' :=
⟨fun h => by
let ⟨h₁, h₂⟩ := Part.mem_assert_iff.1 h
rw [WellFounded.fixF_eq] at h₂
simp only [Part.mem_assert_iff] at h₂
obtain ⟨h₂, h₃⟩ := h₂
split at h₃
next e => simp only [Part.mem_some_iff] at h₃; subst b; exact Or.inl ⟨h₂, e⟩
next e => exact Or.inr ⟨_, ⟨_, e⟩, Part.mem_assert _ h₃⟩,
fun h => by
simp only [fix, Part.mem_assert_iff]
rcases h with (⟨h₁, h₂⟩ | ⟨a', h, h₃⟩)
· refine ⟨⟨_, fun y h' => ?_⟩, ?_⟩
· injection Part.mem_unique ⟨h₁, h₂⟩ h'
· rw [WellFounded.fixF_eq]
-- Porting note: used to be simp [h₁, h₂]
apply Part.mem_assert h₁
split
next e =>
injection h₂.symm.trans e with h; simp [h]
next e =>
injection h₂.symm.trans e
· simp only [fix, Part.mem_assert_iff] at h₃
obtain ⟨h₃, h₄⟩ := h₃
refine ⟨⟨_, fun y h' => ?_⟩, ?_⟩
· injection Part.mem_unique h h' with e
exact e ▸ h₃
· obtain ⟨h₁, h₂⟩ := h
rw [WellFounded.fixF_eq]
-- Porting note: used to be simp [h₁, h₂, h₄]
apply Part.mem_assert h₁
split
next e =>
injection h₂.symm.trans e
next e =>
injection h₂.symm.trans e; subst a'; exact h₄⟩
/-- If advancing one step from `a` leads to `b : β`, then `f.fix a = b` -/
theorem fix_stop {f : α →. β ⊕ α} {b : β} {a : α} (hb : Sum.inl b ∈ f a) : b ∈ f.fix a := by
rw [PFun.mem_fix_iff]
exact Or.inl hb
/-- If advancing one step from `a` on `f` leads to `a' : α`, then `f.fix a = f.fix a'` -/
theorem fix_fwd_eq {f : α →. β ⊕ α} {a a' : α} (ha' : Sum.inr a' ∈ f a) : f.fix a = f.fix a' := by
ext b; constructor
· intro h
obtain h' | ⟨a, h', e'⟩ := mem_fix_iff.1 h <;> cases Part.mem_unique ha' h'
exact e'
· intro h
rw [PFun.mem_fix_iff]
exact Or.inr ⟨a', ha', h⟩
theorem fix_fwd {f : α →. β ⊕ α} {b : β} {a a' : α} (hb : b ∈ f.fix a) (ha' : Sum.inr a' ∈ f a) :
b ∈ f.fix a' := by rwa [← fix_fwd_eq ha']
/-- A recursion principle for `PFun.fix`. -/
@[elab_as_elim]
def fixInduction {C : α → Sort*} {f : α →. β ⊕ α} {b : β} {a : α} (h : b ∈ f.fix a)
(H : ∀ a', b ∈ f.fix a' → (∀ a'', Sum.inr a'' ∈ f a' → C a'') → C a') : C a := by
have h₂ := (Part.mem_assert_iff.1 h).snd
generalize_proofs at h₂
clear h
induction ‹Acc _ _› with | intro a ha IH => _
have h : b ∈ f.fix a := Part.mem_assert_iff.2 ⟨⟨a, ha⟩, h₂⟩
exact H a h fun a' fa' => IH a' fa' (Part.mem_assert_iff.1 (fix_fwd h fa')).snd
theorem fixInduction_spec {C : α → Sort*} {f : α →. β ⊕ α} {b : β} {a : α} (h : b ∈ f.fix a)
(H : ∀ a', b ∈ f.fix a' → (∀ a'', Sum.inr a'' ∈ f a' → C a'') → C a') :
@fixInduction _ _ C _ _ _ h H = H a h fun _ h' => fixInduction (fix_fwd h h') H := by
unfold fixInduction
generalize_proofs
induction ‹Acc _ _›
rfl
/-- Another induction lemma for `b ∈ f.fix a` which allows one to prove a predicate `P` holds for
`a` given that `f a` inherits `P` from `a` and `P` holds for preimages of `b`.
-/
@[elab_as_elim]
def fixInduction' {C : α → Sort*} {f : α →. β ⊕ α} {b : β} {a : α}
(h : b ∈ f.fix a) (hbase : ∀ a_final : α, Sum.inl b ∈ f a_final → C a_final)
(hind : ∀ a₀ a₁ : α, b ∈ f.fix a₁ → Sum.inr a₁ ∈ f a₀ → C a₁ → C a₀) : C a := by
refine fixInduction h fun a' h ih => ?_
rcases e : (f a').get (dom_of_mem_fix h) with b' | a'' <;> replace e : _ ∈ f a' := ⟨_, e⟩
· apply hbase
convert e
exact Part.mem_unique h (fix_stop e)
· exact hind _ _ (fix_fwd h e) e (ih _ e)
theorem fixInduction'_stop {C : α → Sort*} {f : α →. β ⊕ α} {b : β} {a : α} (h : b ∈ f.fix a)
(fa : Sum.inl b ∈ f a) (hbase : ∀ a_final : α, Sum.inl b ∈ f a_final → C a_final)
(hind : ∀ a₀ a₁ : α, b ∈ f.fix a₁ → Sum.inr a₁ ∈ f a₀ → C a₁ → C a₀) :
@fixInduction' _ _ C _ _ _ h hbase hind = hbase a fa := by
unfold fixInduction'
rw [fixInduction_spec]
-- Porting note: the explicit motive required because `simp` does not apply `Part.get_eq_of_mem`
refine Eq.rec (motive := fun x e ↦
Sum.casesOn x ?_ ?_ (Eq.trans (Part.get_eq_of_mem fa (dom_of_mem_fix h)) e) = hbase a fa) ?_
(Part.get_eq_of_mem fa (dom_of_mem_fix h)).symm
simp
theorem fixInduction'_fwd {C : α → Sort*} {f : α →. β ⊕ α} {b : β} {a a' : α} (h : b ∈ f.fix a)
(h' : b ∈ f.fix a') (fa : Sum.inr a' ∈ f a)
(hbase : ∀ a_final : α, Sum.inl b ∈ f a_final → C a_final)
(hind : ∀ a₀ a₁ : α, b ∈ f.fix a₁ → Sum.inr a₁ ∈ f a₀ → C a₁ → C a₀) :
@fixInduction' _ _ C _ _ _ h hbase hind = hind a a' h' fa (fixInduction' h' hbase hind) := by
unfold fixInduction'
rw [fixInduction_spec]
-- Porting note: the explicit motive required because `simp` does not apply `Part.get_eq_of_mem`
refine Eq.rec (motive := fun x e =>
Sum.casesOn (motive := fun y => (f a).get (dom_of_mem_fix h) = y → C a) x ?_ ?_
(Eq.trans (Part.get_eq_of_mem fa (dom_of_mem_fix h)) e) = _) ?_
(Part.get_eq_of_mem fa (dom_of_mem_fix h)).symm
simp
variable (f : α →. β)
/-- Image of a set under a partial function. -/
def image (s : Set α) : Set β :=
f.graph'.image s
theorem image_def (s : Set α) : f.image s = { y | ∃ x ∈ s, y ∈ f x } :=
rfl
theorem mem_image (y : β) (s : Set α) : y ∈ f.image s ↔ ∃ x ∈ s, y ∈ f x :=
Iff.rfl
theorem image_mono {s t : Set α} (h : s ⊆ t) : f.image s ⊆ f.image t :=
Rel.image_mono _ h
theorem image_inter (s t : Set α) : f.image (s ∩ t) ⊆ f.image s ∩ f.image t :=
Rel.image_inter _ s t
theorem image_union (s t : Set α) : f.image (s ∪ t) = f.image s ∪ f.image t :=
Rel.image_union _ s t
/-- Preimage of a set under a partial function. -/
def preimage (s : Set β) : Set α :=
Rel.image (fun x y => x ∈ f y) s
theorem Preimage_def (s : Set β) : f.preimage s = { x | ∃ y ∈ s, y ∈ f x } :=
rfl
@[simp]
theorem mem_preimage (s : Set β) (x : α) : x ∈ f.preimage s ↔ ∃ y ∈ s, y ∈ f x :=
Iff.rfl
theorem preimage_subset_dom (s : Set β) : f.preimage s ⊆ f.Dom := fun _ ⟨y, _, fxy⟩ =>
Part.dom_iff_mem.mpr ⟨y, fxy⟩
theorem preimage_mono {s t : Set β} (h : s ⊆ t) : f.preimage s ⊆ f.preimage t :=
Rel.preimage_mono _ h
theorem preimage_inter (s t : Set β) : f.preimage (s ∩ t) ⊆ f.preimage s ∩ f.preimage t :=
Rel.preimage_inter _ s t
theorem preimage_union (s t : Set β) : f.preimage (s ∪ t) = f.preimage s ∪ f.preimage t :=
Rel.preimage_union _ s t
theorem preimage_univ : f.preimage Set.univ = f.Dom := by ext; simp [mem_preimage, mem_dom]
theorem coe_preimage (f : α → β) (s : Set β) : (f : α →. β).preimage s = f ⁻¹' s := by ext; simp
/-- Core of a set `s : Set β` with respect to a partial function `f : α →. β`. Set of all `a : α`
such that `f a ∈ s`, if `f a` is defined. -/
def core (s : Set β) : Set α :=
f.graph'.core s
theorem core_def (s : Set β) : f.core s = { x | ∀ y, y ∈ f x → y ∈ s } :=
rfl
@[simp]
theorem mem_core (x : α) (s : Set β) : x ∈ f.core s ↔ ∀ y, y ∈ f x → y ∈ s :=
Iff.rfl
theorem compl_dom_subset_core (s : Set β) : f.Domᶜ ⊆ f.core s := fun x hx y fxy =>
absurd ((mem_dom f x).mpr ⟨y, fxy⟩) hx
theorem core_mono {s t : Set β} (h : s ⊆ t) : f.core s ⊆ f.core t :=
Rel.core_mono _ h
theorem core_inter (s t : Set β) : f.core (s ∩ t) = f.core s ∩ f.core t :=
Rel.core_inter _ s t
theorem mem_core_res (f : α → β) (s : Set α) (t : Set β) (x : α) :
x ∈ (res f s).core t ↔ x ∈ s → f x ∈ t := by simp [mem_core, mem_res]
theorem core_res (f : α → β) (s : Set α) (t : Set β) : (res f s).core t = sᶜ ∪ f ⁻¹' t := by
ext x
rw [mem_core_res]
by_cases h : x ∈ s <;> simp [h]
theorem core_restrict (f : α → β) (s : Set β) : (f : α →. β).core s = s.preimage f := by
ext x; simp [core_def]
theorem preimage_subset_core (f : α →. β) (s : Set β) : f.preimage s ⊆ f.core s :=
fun _ ⟨y, ys, fxy⟩ y' fxy' =>
have : y = y' := Part.mem_unique fxy fxy'
this ▸ ys
theorem preimage_eq (f : α →. β) (s : Set β) : f.preimage s = f.core s ∩ f.Dom :=
Set.eq_of_subset_of_subset (Set.subset_inter (f.preimage_subset_core s) (f.preimage_subset_dom s))
fun x ⟨xcore, xdom⟩ =>
let y := (f x).get xdom
have ys : y ∈ s := xcore _ (Part.get_mem _)
show x ∈ f.preimage s from ⟨(f x).get xdom, ys, Part.get_mem _⟩
theorem core_eq (f : α →. β) (s : Set β) : f.core s = f.preimage s ∪ f.Domᶜ := by
rw [preimage_eq, Set.inter_union_distrib_right, Set.union_comm (Dom f), Set.compl_union_self,
Set.inter_univ, Set.union_eq_self_of_subset_right (f.compl_dom_subset_core s)]
theorem preimage_asSubtype (f : α →. β) (s : Set β) :
f.asSubtype ⁻¹' s = Subtype.val ⁻¹' f.preimage s := by
ext x
simp only [Set.mem_preimage, Set.mem_setOf_eq, PFun.asSubtype, PFun.mem_preimage]
show f.fn x.val _ ∈ s ↔ ∃ y ∈ s, y ∈ f x.val
exact
Iff.intro (fun h => ⟨_, h, Part.get_mem _⟩) fun ⟨y, ys, fxy⟩ =>
have : f.fn x.val x.property ∈ f x.val := Part.get_mem _
Part.mem_unique fxy this ▸ ys
/-- Turns a function into a partial function to a subtype. -/
def toSubtype (p : β → Prop) (f : α → β) : α →. Subtype p := fun a => ⟨p (f a), Subtype.mk _⟩
@[simp]
theorem dom_toSubtype (p : β → Prop) (f : α → β) : (toSubtype p f).Dom = { a | p (f a) } :=
rfl
@[simp]
theorem toSubtype_apply (p : β → Prop) (f : α → β) (a : α) :
toSubtype p f a = ⟨p (f a), Subtype.mk _⟩ :=
rfl
theorem dom_toSubtype_apply_iff {p : β → Prop} {f : α → β} {a : α} :
(toSubtype p f a).Dom ↔ p (f a) :=
Iff.rfl
theorem mem_toSubtype_iff {p : β → Prop} {f : α → β} {a : α} {b : Subtype p} :
b ∈ toSubtype p f a ↔ ↑b = f a := by
rw [toSubtype_apply, Part.mem_mk_iff, exists_subtype_mk_eq_iff, eq_comm]
/-- The identity as a partial function -/
protected def id (α : Type*) : α →. α :=
Part.some
@[simp, norm_cast]
theorem coe_id (α : Type*) : ((id : α → α) : α →. α) = PFun.id α :=
rfl
@[simp]
theorem id_apply (a : α) : PFun.id α a = Part.some a :=
rfl
/-- Composition of partial functions as a partial function. -/
def comp (f : β →. γ) (g : α →. β) : α →. γ := fun a => (g a).bind f
@[simp]
theorem comp_apply (f : β →. γ) (g : α →. β) (a : α) : f.comp g a = (g a).bind f :=
rfl
@[simp]
theorem id_comp (f : α →. β) : (PFun.id β).comp f = f :=
ext fun _ _ => by simp
@[simp]
theorem comp_id (f : α →. β) : f.comp (PFun.id α) = f :=
ext fun _ _ => by simp
@[simp]
theorem dom_comp (f : β →. γ) (g : α →. β) : (f.comp g).Dom = g.preimage f.Dom := by
ext
simp_rw [mem_preimage, mem_dom, comp_apply, Part.mem_bind_iff, ← exists_and_right]
rw [exists_comm]
simp_rw [and_comm]
@[simp]
theorem preimage_comp (f : β →. γ) (g : α →. β) (s : Set γ) :
(f.comp g).preimage s = g.preimage (f.preimage s) := by
ext
simp_rw [mem_preimage, comp_apply, Part.mem_bind_iff, ← exists_and_right, ← exists_and_left]
rw [exists_comm]
simp_rw [and_assoc, and_comm]
@[simp]
theorem Part.bind_comp (f : β →. γ) (g : α →. β) (a : Part α) :
a.bind (f.comp g) = (a.bind g).bind f := by
ext c
simp_rw [Part.mem_bind_iff, comp_apply, Part.mem_bind_iff, ← exists_and_right, ← exists_and_left]
rw [exists_comm]
simp_rw [and_assoc]
@[simp]
theorem comp_assoc (f : γ →. δ) (g : β →. γ) (h : α →. β) : (f.comp g).comp h = f.comp (g.comp h) :=
ext fun _ _ => by simp only [comp_apply, Part.bind_comp]
-- This can't be `simp`
theorem coe_comp (g : β → γ) (f : α → β) : ((g ∘ f : α → γ) : α →. γ) = (g : β →. γ).comp f :=
ext fun _ _ => by simp only [coe_val, comp_apply, Function.comp, Part.bind_some]
/-- Product of partial functions. -/
def prodLift (f : α →. β) (g : α →. γ) : α →. β × γ := fun x =>
⟨(f x).Dom ∧ (g x).Dom, fun h => ((f x).get h.1, (g x).get h.2)⟩
@[simp]
theorem dom_prodLift (f : α →. β) (g : α →. γ) :
(f.prodLift g).Dom = { x | (f x).Dom ∧ (g x).Dom } :=
rfl
theorem get_prodLift (f : α →. β) (g : α →. γ) (x : α) (h) :
(f.prodLift g x).get h = ((f x).get h.1, (g x).get h.2) :=
rfl
@[simp]
theorem prodLift_apply (f : α →. β) (g : α →. γ) (x : α) :
f.prodLift g x = ⟨(f x).Dom ∧ (g x).Dom, fun h => ((f x).get h.1, (g x).get h.2)⟩ :=
rfl
theorem mem_prodLift {f : α →. β} {g : α →. γ} {x : α} {y : β × γ} :
y ∈ f.prodLift g x ↔ y.1 ∈ f x ∧ y.2 ∈ g x := by
trans ∃ hp hq, (f x).get hp = y.1 ∧ (g x).get hq = y.2
· simp only [prodLift, Part.mem_mk_iff, And.exists, Prod.ext_iff]
· simp only [exists_and_left, exists_and_right, Membership.mem, Part.Mem]
/-- Product of partial functions. -/
def prodMap (f : α →. γ) (g : β →. δ) : α × β →. γ × δ := fun x =>
⟨(f x.1).Dom ∧ (g x.2).Dom, fun h => ((f x.1).get h.1, (g x.2).get h.2)⟩
@[simp]
theorem dom_prodMap (f : α →. γ) (g : β →. δ) :
(f.prodMap g).Dom = { x | (f x.1).Dom ∧ (g x.2).Dom } :=
rfl
theorem get_prodMap (f : α →. γ) (g : β →. δ) (x : α × β) (h) :
(f.prodMap g x).get h = ((f x.1).get h.1, (g x.2).get h.2) :=
rfl
@[simp]
theorem prodMap_apply (f : α →. γ) (g : β →. δ) (x : α × β) :
f.prodMap g x = ⟨(f x.1).Dom ∧ (g x.2).Dom, fun h => ((f x.1).get h.1, (g x.2).get h.2)⟩ :=
rfl
theorem mem_prodMap {f : α →. γ} {g : β →. δ} {x : α × β} {y : γ × δ} :
y ∈ f.prodMap g x ↔ y.1 ∈ f x.1 ∧ y.2 ∈ g x.2 := by
trans ∃ hp hq, (f x.1).get hp = y.1 ∧ (g x.2).get hq = y.2
· simp only [prodMap, Part.mem_mk_iff, And.exists, Prod.ext_iff]
· simp only [exists_and_left, exists_and_right, Membership.mem, Part.Mem]
@[simp]
theorem prodLift_fst_comp_snd_comp (f : α →. γ) (g : β →. δ) :
prodLift (f.comp ((Prod.fst : α × β → α) : α × β →. α))
(g.comp ((Prod.snd : α × β → β) : α × β →. β)) =
prodMap f g := by
aesop
@[simp]
theorem prodMap_id_id : (PFun.id α).prodMap (PFun.id β) = PFun.id _ := by
aesop
@[simp]
theorem prodMap_comp_comp (f₁ : α →. β) (f₂ : β →. γ) (g₁ : δ →. ε) (g₂ : ε →. ι) :
(f₂.comp f₁).prodMap (g₂.comp g₁) = (f₂.prodMap g₂).comp (f₁.prodMap g₁) :=
-- `aesop` can prove this but takes over a second, so we do it manually
ext <| fun ⟨_, _⟩ ⟨_, _⟩ ↦
⟨fun ⟨⟨⟨h1l1, h1l2⟩, ⟨h1r1, h1r2⟩⟩, h2⟩ ↦ ⟨⟨⟨h1l1, h1r1⟩, ⟨h1l2, h1r2⟩⟩, h2⟩,
fun ⟨⟨⟨h1l1, h1r1⟩, ⟨h1l2, h1r2⟩⟩, h2⟩ ↦ ⟨⟨⟨h1l1, h1l2⟩, ⟨h1r1, h1r2⟩⟩, h2⟩⟩
end PFun
| Mathlib/Data/PFun.lean | 647 | 652 | |
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nathaniel Thomas, Jeremy Avigad, Johannes Hölzl, Mario Carneiro, Anne Baanen,
Frédéric Dupuis, Heather Macbeth
-/
import Mathlib.Algebra.Group.Hom.Instances
import Mathlib.Algebra.Module.NatInt
import Mathlib.Algebra.Module.RingHom
import Mathlib.Algebra.Ring.CompTypeclasses
import Mathlib.GroupTheory.GroupAction.Hom
/-!
# (Semi)linear maps
In this file we define
* `LinearMap σ M M₂`, `M →ₛₗ[σ] M₂` : a semilinear map between two `Module`s. Here,
`σ` is a `RingHom` from `R` to `R₂` and an `f : M →ₛₗ[σ] M₂` satisfies
`f (c • x) = (σ c) • (f x)`. We recover plain linear maps by choosing `σ` to be `RingHom.id R`.
This is denoted by `M →ₗ[R] M₂`. We also add the notation `M →ₗ⋆[R] M₂` for star-linear maps.
* `IsLinearMap R f` : predicate saying that `f : M → M₂` is a linear map. (Note that this
was not generalized to semilinear maps.)
We then provide `LinearMap` with the following instances:
* `LinearMap.addCommMonoid` and `LinearMap.addCommGroup`: the elementwise addition structures
corresponding to addition in the codomain
* `LinearMap.distribMulAction` and `LinearMap.module`: the elementwise scalar action structures
corresponding to applying the action in the codomain.
## Implementation notes
To ensure that composition works smoothly for semilinear maps, we use the typeclasses
`RingHomCompTriple`, `RingHomInvPair` and `RingHomSurjective` from
`Mathlib.Algebra.Ring.CompTypeclasses`.
## Notation
* Throughout the file, we denote regular linear maps by `fₗ`, `gₗ`, etc, and semilinear maps
by `f`, `g`, etc.
## TODO
* Parts of this file have not yet been generalized to semilinear maps (i.e. `CompatibleSMul`)
## Tags
linear map
-/
assert_not_exists Star DomMulAct Pi.module WCovBy.image Field
open Function
universe u u' v w
variable {R R₁ R₂ R₃ S S₃ T M M₁ M₂ M₃ N₂ N₃ : Type*}
/-- A map `f` between modules over a semiring is linear if it satisfies the two properties
`f (x + y) = f x + f y` and `f (c • x) = c • f x`. The predicate `IsLinearMap R f` asserts this
property. A bundled version is available with `LinearMap`, and should be favored over
`IsLinearMap` most of the time. -/
structure IsLinearMap (R : Type u) {M : Type v} {M₂ : Type w} [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂] (f : M → M₂) : Prop where
/-- A linear map preserves addition. -/
map_add : ∀ x y, f (x + y) = f x + f y
/-- A linear map preserves scalar multiplication. -/
map_smul : ∀ (c : R) (x), f (c • x) = c • f x
section
/-- 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`. Elements of `LinearMap σ M M₂` (available under the notation
`M →ₛₗ[σ] M₂`) are bundled versions of such maps. For plain linear maps (i.e. for which
`σ = RingHom.id R`), the notation `M →ₗ[R] M₂` is available. An unbundled version of plain linear
maps is available with the predicate `IsLinearMap`, but it should be avoided most of the time. -/
structure LinearMap {R S : Type*} [Semiring R] [Semiring S] (σ : R →+* S) (M : Type*)
(M₂ : Type*) [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂] extends
AddHom M M₂, MulActionHom σ M M₂
/-- The `MulActionHom` underlying a `LinearMap`. -/
add_decl_doc LinearMap.toMulActionHom
/-- The `AddHom` underlying a `LinearMap`. -/
add_decl_doc LinearMap.toAddHom
/-- `M →ₛₗ[σ] N` is the type of `σ`-semilinear maps from `M` to `N`. -/
notation:25 M " →ₛₗ[" σ:25 "] " M₂:0 => LinearMap σ M M₂
/-- `M →ₗ[R] N` is the type of `R`-linear maps from `M` to `N`. -/
notation:25 M " →ₗ[" R:25 "] " M₂:0 => LinearMap (RingHom.id R) M M₂
/-- `SemilinearMapClass F σ M M₂` asserts `F` is a type of bundled `σ`-semilinear maps `M → M₂`.
See also `LinearMapClass 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 SemilinearMapClass (F : Type*) {R S : outParam Type*} [Semiring R] [Semiring S]
(σ : outParam (R →+* S)) (M M₂ : outParam Type*) [AddCommMonoid M] [AddCommMonoid M₂]
[Module R M] [Module S M₂] [FunLike F M M₂] : Prop
extends AddHomClass F M M₂, MulActionSemiHomClass F σ M M₂
end
-- `map_smulₛₗ` should be `@[simp]` but doesn't fire due to https://github.com/leanprover/lean4/pull/3701.
-- attribute [simp] map_smulₛₗ
/-- `LinearMapClass F R M M₂` asserts `F` is a type of bundled `R`-linear maps `M → M₂`.
This is an abbreviation for `SemilinearMapClass F (RingHom.id R) M M₂`.
-/
abbrev LinearMapClass (F : Type*) (R : outParam Type*) (M M₂ : Type*)
[Semiring R] [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module R M₂]
[FunLike F M M₂] :=
SemilinearMapClass F (RingHom.id R) M M₂
protected lemma LinearMapClass.map_smul {R M M₂ : outParam Type*} [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂]
{F : Type*} [FunLike F M M₂] [LinearMapClass F R M M₂] (f : F) (r : R) (x : M) :
f (r • x) = r • f x := by rw [map_smul]
namespace SemilinearMapClass
variable (F : Type*)
variable [Semiring R] [Semiring S]
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable [Module R M] [Module R M₂] [Module S M₃]
variable {σ : R →+* S}
instance (priority := 100) instAddMonoidHomClass [FunLike F M M₃] [SemilinearMapClass F σ M M₃] :
AddMonoidHomClass F M M₃ :=
{ SemilinearMapClass.toAddHomClass with
map_zero := fun f ↦
show f 0 = 0 by
rw [← zero_smul R (0 : M), map_smulₛₗ]
simp }
instance (priority := 100) distribMulActionSemiHomClass
[FunLike F M M₃] [SemilinearMapClass F σ M M₃] :
DistribMulActionSemiHomClass F σ M M₃ :=
{ SemilinearMapClass.toAddHomClass with
map_smulₛₗ := fun f c x ↦ by rw [map_smulₛₗ] }
variable {F} (f : F) [FunLike F M M₃] [SemilinearMapClass F σ M M₃]
theorem map_smul_inv {σ' : S →+* R} [RingHomInvPair σ σ'] (c : S) (x : M) :
c • f x = f (σ' c • x) := by simp [map_smulₛₗ _]
/-- Reinterpret an element of a type of semilinear maps as a semilinear map. -/
@[coe]
def semilinearMap : M →ₛₗ[σ] M₃ where
toFun := f
map_add' := map_add f
map_smul' := map_smulₛₗ f
/-- Reinterpret an element of a type of semilinear maps as a semilinear map. -/
instance instCoeToSemilinearMap : CoeHead F (M →ₛₗ[σ] M₃) where
coe f := semilinearMap f
end SemilinearMapClass
namespace LinearMapClass
variable {F : Type*} [Semiring R] [AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁] [Module R M₂]
(f : F) [FunLike F M₁ M₂] [LinearMapClass F R M₁ M₂]
/-- Reinterpret an element of a type of linear maps as a linear map. -/
abbrev linearMap : M₁ →ₗ[R] M₂ := SemilinearMapClass.semilinearMap f
/-- Reinterpret an element of a type of linear maps as a linear map. -/
instance instCoeToLinearMap : CoeHead F (M₁ →ₗ[R] M₂) where
coe f := SemilinearMapClass.semilinearMap f
end LinearMapClass
namespace LinearMap
section AddCommMonoid
variable [Semiring R] [Semiring S]
section
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid M₃]
variable [Module R M] [Module R M₂] [Module S M₃]
variable {σ : R →+* S}
instance instFunLike : FunLike (M →ₛₗ[σ] M₃) M M₃ where
coe f := f.toFun
coe_injective' f g h := by
cases f
cases g
congr
apply DFunLike.coe_injective'
exact h
instance semilinearMapClass : SemilinearMapClass (M →ₛₗ[σ] M₃) σ M M₃ where
map_add f := f.map_add'
map_smulₛₗ := LinearMap.map_smul'
@[simp, norm_cast]
lemma coe_coe {F : Type*} [FunLike F M M₃] [SemilinearMapClass F σ M M₃] {f : F} :
⇑(f : M →ₛₗ[σ] M₃) = f :=
rfl
/-- The `DistribMulActionHom` underlying a `LinearMap`. -/
def toDistribMulActionHom (f : M →ₛₗ[σ] M₃) : DistribMulActionHom σ.toMonoidHom M M₃ :=
{ f with map_zero' := show f 0 = 0 from map_zero f }
@[simp]
theorem coe_toAddHom (f : M →ₛₗ[σ] M₃) : ⇑f.toAddHom = f := rfl
-- Porting note: no longer a `simp`
theorem toFun_eq_coe {f : M →ₛₗ[σ] M₃} : f.toFun = (f : M → M₃) := rfl
@[ext]
theorem ext {f g : M →ₛₗ[σ] M₃} (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
/-- Copy of a `LinearMap` with a new `toFun` equal to the old one. Useful to fix definitional
equalities. -/
protected def copy (f : M →ₛₗ[σ] M₃) (f' : M → M₃) (h : f' = ⇑f) : M →ₛₗ[σ] M₃ where
toFun := f'
map_add' := h.symm ▸ f.map_add'
map_smul' := h.symm ▸ f.map_smul'
@[simp]
theorem coe_copy (f : M →ₛₗ[σ] M₃) (f' : M → M₃) (h : f' = ⇑f) : ⇑(f.copy f' h) = f' :=
rfl
theorem copy_eq (f : M →ₛₗ[σ] M₃) (f' : M → M₃) (h : f' = ⇑f) : f.copy f' h = f :=
DFunLike.ext' h
initialize_simps_projections LinearMap (toFun → apply)
@[simp]
theorem coe_mk {σ : R →+* S} (f : AddHom M M₃) (h) :
((LinearMap.mk f h : M →ₛₗ[σ] M₃) : M → M₃) = f :=
rfl
@[simp]
theorem coe_addHom_mk {σ : R →+* S} (f : AddHom M M₃) (h) :
((LinearMap.mk f h : M →ₛₗ[σ] M₃) : AddHom M M₃) = f :=
rfl
theorem coe_semilinearMap {F : Type*} [FunLike F M M₃] [SemilinearMapClass F σ M M₃] (f : F) :
((f : M →ₛₗ[σ] M₃) : M → M₃) = f :=
rfl
theorem toLinearMap_injective {F : Type*} [FunLike F M M₃] [SemilinearMapClass F σ M M₃]
{f g : F} (h : (f : M →ₛₗ[σ] M₃) = (g : M →ₛₗ[σ] M₃)) :
f = g := by
apply DFunLike.ext
intro m
exact DFunLike.congr_fun h m
/-- Identity map as a `LinearMap` -/
def id : M →ₗ[R] M :=
{ DistribMulActionHom.id R with toFun := _root_.id }
theorem id_apply (x : M) : @id R M _ _ _ x = x :=
rfl
@[simp, norm_cast]
theorem id_coe : ((LinearMap.id : M →ₗ[R] M) : M → M) = _root_.id :=
rfl
/-- A generalisation of `LinearMap.id` that constructs the identity function
as a `σ`-semilinear map for any ring homomorphism `σ` which we know is the identity. -/
@[simps]
def id' {σ : R →+* R} [RingHomId σ] : M →ₛₗ[σ] M where
toFun x := x
map_add' _ _ := rfl
map_smul' r x := by
have := (RingHomId.eq_id : σ = _)
subst this
rfl
|
@[simp, norm_cast]
theorem id'_coe {σ : R →+* R} [RingHomId σ] : ((id' : M →ₛₗ[σ] M) : M → M) = _root_.id :=
rfl
end
| Mathlib/Algebra/Module/LinearMap/Defs.lean | 283 | 288 |
/-
Copyright (c) 2022 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.LinearAlgebra.CliffordAlgebra.Conjugation
import Mathlib.LinearAlgebra.CliffordAlgebra.Even
import Mathlib.LinearAlgebra.QuadraticForm.Prod
import Mathlib.Tactic.LiftLets
/-!
# Isomorphisms with the even subalgebra of a Clifford algebra
This file provides some notable isomorphisms regarding the even subalgebra, `CliffordAlgebra.even`.
## Main definitions
* `CliffordAlgebra.equivEven`: Every Clifford algebra is isomorphic as an algebra to the even
subalgebra of a Clifford algebra with one more dimension.
* `CliffordAlgebra.EquivEven.Q'`: The quadratic form used by this "one-up" algebra.
* `CliffordAlgebra.toEven`: The simp-normal form of the forward direction of this isomorphism.
* `CliffordAlgebra.ofEven`: The simp-normal form of the reverse direction of this isomorphism.
* `CliffordAlgebra.evenEquivEvenNeg`: Every even subalgebra is isomorphic to the even subalgebra
of the Clifford algebra with negated quadratic form.
* `CliffordAlgebra.evenToNeg`: The simp-normal form of each direction of this isomorphism.
## Main results
* `CliffordAlgebra.coe_toEven_reverse_involute`: the behavior of `CliffordAlgebra.toEven` on the
"Clifford conjugate", that is `CliffordAlgebra.reverse` composed with
`CliffordAlgebra.involute`.
-/
namespace CliffordAlgebra
variable {R M : Type*} [CommRing R] [AddCommGroup M] [Module R M]
variable (Q : QuadraticForm R M)
/-! ### Constructions needed for `CliffordAlgebra.equivEven` -/
namespace EquivEven
/-- The quadratic form on the augmented vector space `M × R` sending `v + r•e0` to `Q v - r^2`. -/
abbrev Q' : QuadraticForm R (M × R) :=
Q.prod <| -QuadraticMap.sq (R := R)
theorem Q'_apply (m : M × R) : Q' Q m = Q m.1 - m.2 * m.2 :=
(sub_eq_add_neg _ _).symm
/-- The unit vector in the new dimension -/
def e0 : CliffordAlgebra (Q' Q) :=
ι (Q' Q) (0, 1)
/-- The embedding from the existing vector space -/
def v : M →ₗ[R] CliffordAlgebra (Q' Q) :=
ι (Q' Q) ∘ₗ LinearMap.inl _ _ _
theorem ι_eq_v_add_smul_e0 (m : M) (r : R) : ι (Q' Q) (m, r) = v Q m + r • e0 Q := by
rw [e0, v, LinearMap.comp_apply, LinearMap.inl_apply, ← LinearMap.map_smul, Prod.smul_mk,
smul_zero, smul_eq_mul, mul_one, ← LinearMap.map_add, Prod.mk_add_mk, zero_add, add_zero]
theorem e0_mul_e0 : e0 Q * e0 Q = -1 :=
(ι_sq_scalar _ _).trans <| by simp
theorem v_sq_scalar (m : M) : v Q m * v Q m = algebraMap _ _ (Q m) :=
(ι_sq_scalar _ _).trans <| by simp
theorem neg_e0_mul_v (m : M) : -(e0 Q * v Q m) = v Q m * e0 Q := by
refine neg_eq_of_add_eq_zero_right ((ι_mul_ι_add_swap _ _).trans ?_)
dsimp [QuadraticMap.polar]
simp only [add_zero, mul_zero, mul_one, zero_add, neg_zero, QuadraticMap.map_zero,
add_sub_cancel_right, sub_self, map_zero, zero_sub]
theorem neg_v_mul_e0 (m : M) : -(v Q m * e0 Q) = e0 Q * v Q m := by
rw [neg_eq_iff_eq_neg]
exact (neg_e0_mul_v _ m).symm
@[simp]
theorem e0_mul_v_mul_e0 (m : M) : e0 Q * v Q m * e0 Q = v Q m := by
rw [← neg_v_mul_e0, ← neg_mul, mul_assoc, e0_mul_e0, mul_neg_one, neg_neg]
@[simp]
theorem reverse_v (m : M) : reverse (Q := Q' Q) (v Q m) = v Q m :=
reverse_ι _
@[simp]
theorem involute_v (m : M) : involute (v Q m) = -v Q m :=
involute_ι _
@[simp]
theorem reverse_e0 : reverse (Q := Q' Q) (e0 Q) = e0 Q :=
reverse_ι _
@[simp]
theorem involute_e0 : involute (e0 Q) = -e0 Q :=
involute_ι _
end EquivEven
open EquivEven
/-- The embedding from the smaller algebra into the new larger one. -/
def toEven : CliffordAlgebra Q →ₐ[R] CliffordAlgebra.even (Q' Q) := by
refine CliffordAlgebra.lift Q ⟨?_, fun m => ?_⟩
· refine LinearMap.codRestrict _ ?_ fun m => Submodule.mem_iSup_of_mem ⟨2, rfl⟩ ?_
· exact (LinearMap.mulLeft R <| e0 Q).comp (v Q)
rw [Subtype.coe_mk, pow_two]
exact Submodule.mul_mem_mul (LinearMap.mem_range_self _ _) (LinearMap.mem_range_self _ _)
· ext1
rw [Subalgebra.coe_mul] -- Porting note: was part of the `dsimp only` below
erw [LinearMap.codRestrict_apply] -- Porting note: was part of the `dsimp only` below
dsimp only [LinearMap.comp_apply, LinearMap.mulLeft_apply, Subalgebra.coe_algebraMap]
rw [← mul_assoc, e0_mul_v_mul_e0, v_sq_scalar]
theorem toEven_ι (m : M) : (toEven Q (ι Q m) : CliffordAlgebra (Q' Q)) = e0 Q * v Q m := by
rw [toEven, CliffordAlgebra.lift_ι_apply]
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11224): was `rw`
erw [LinearMap.codRestrict_apply]
rw [LinearMap.coe_comp, Function.comp_apply, LinearMap.mulLeft_apply]
/-- The embedding from the even subalgebra with an extra dimension into the original algebra. -/
def ofEven : CliffordAlgebra.even (Q' Q) →ₐ[R] CliffordAlgebra Q := by
/-
Recall that we need:
* `f ⟨0,1⟩ ⟨x,0⟩ = ι x`
* `f ⟨x,0⟩ ⟨0,1⟩ = -ι x`
* `f ⟨x,0⟩ ⟨y,0⟩ = ι x * ι y`
* `f ⟨0,1⟩ ⟨0,1⟩ = -1`
-/
let f : M × R →ₗ[R] M × R →ₗ[R] CliffordAlgebra Q :=
((Algebra.lmul R (CliffordAlgebra Q)).toLinearMap.comp <|
(ι Q).comp (LinearMap.fst _ _ _) +
(Algebra.linearMap R _).comp (LinearMap.snd _ _ _)).compl₂
((ι Q).comp (LinearMap.fst _ _ _) - (Algebra.linearMap R _).comp (LinearMap.snd _ _ _))
haveI f_apply : ∀ x y, f x y = (ι Q x.1 + algebraMap R _ x.2) * (ι Q y.1 - algebraMap R _ y.2) :=
fun x y => by rfl
haveI hc : ∀ (r : R) (x : CliffordAlgebra Q), Commute (algebraMap _ _ r) x := Algebra.commutes
haveI hm :
∀ m : M × R,
ι Q m.1 * ι Q m.1 - algebraMap R _ m.2 * algebraMap R _ m.2 = algebraMap R _ (Q' Q m) := by
intro m
rw [ι_sq_scalar, ← RingHom.map_mul, ← RingHom.map_sub, sub_eq_add_neg, Q'_apply, sub_eq_add_neg]
refine even.lift (Q' Q) ⟨f, ?_, ?_⟩ <;> simp_rw [f_apply]
· intro m
rw [← (hc _ _).symm.mul_self_sub_mul_self_eq, hm]
· intro m₁ m₂ m₃
rw [← mul_smul_comm, ← mul_assoc, mul_assoc (_ + _), ← (hc _ _).symm.mul_self_sub_mul_self_eq',
Algebra.smul_def, ← mul_assoc, hm]
theorem ofEven_ι (x y : M × R) :
ofEven Q ((even.ι (Q' Q)).bilin x y) =
(ι Q x.1 + algebraMap R _ x.2) * (ι Q y.1 - algebraMap R _ y.2) :=
even.lift_ι (Q' Q) _ x y
theorem toEven_comp_ofEven : (toEven Q).comp (ofEven Q) = AlgHom.id R _ :=
even.algHom_ext (Q' Q) <|
EvenHom.ext <|
LinearMap.ext fun m₁ =>
LinearMap.ext fun m₂ =>
Subtype.ext <|
let ⟨m₁, r₁⟩ := m₁
let ⟨m₂, r₂⟩ := m₂
calc
↑(toEven Q (ofEven Q ((even.ι (Q' Q)).bilin (m₁, r₁) (m₂, r₂)))) =
(e0 Q * v Q m₁ + algebraMap R _ r₁) * (e0 Q * v Q m₂ - algebraMap R _ r₂) := by
rw [ofEven_ι, map_mul, map_add, map_sub, AlgHom.commutes,
AlgHom.commutes, Subalgebra.coe_mul, Subalgebra.coe_add, Subalgebra.coe_sub,
toEven_ι, toEven_ι, Subalgebra.coe_algebraMap, Subalgebra.coe_algebraMap]
_ =
e0 Q * v Q m₁ * (e0 Q * v Q m₂) + r₁ • e0 Q * v Q m₂ - r₂ • e0 Q * v Q m₁ -
algebraMap R _ (r₁ * r₂) := by
rw [mul_sub, add_mul, add_mul, ← Algebra.commutes, ← Algebra.smul_def, ← map_mul, ←
Algebra.smul_def, sub_add_eq_sub_sub, smul_mul_assoc, smul_mul_assoc]
_ =
v Q m₁ * v Q m₂ + r₁ • e0 Q * v Q m₂ + v Q m₁ * r₂ • e0 Q +
r₁ • e0 Q * r₂ • e0 Q := by
have h1 : e0 Q * v Q m₁ * (e0 Q * v Q m₂) = v Q m₁ * v Q m₂ := by
rw [← mul_assoc, e0_mul_v_mul_e0]
have h2 : -(r₂ • e0 Q * v Q m₁) = v Q m₁ * r₂ • e0 Q := by
rw [mul_smul_comm, smul_mul_assoc, ← smul_neg, neg_e0_mul_v]
have h3 : -algebraMap R _ (r₁ * r₂) = r₁ • e0 Q * r₂ • e0 Q := by
| rw [Algebra.algebraMap_eq_smul_one, smul_mul_smul_comm, e0_mul_e0, smul_neg]
rw [sub_eq_add_neg, sub_eq_add_neg, h1, h2, h3]
_ = ι (Q' Q) (m₁, r₁) * ι (Q' Q) (m₂, r₂) := by
rw [ι_eq_v_add_smul_e0, ι_eq_v_add_smul_e0, mul_add, add_mul, add_mul, add_assoc]
theorem ofEven_comp_toEven : (ofEven Q).comp (toEven Q) = AlgHom.id R _ :=
CliffordAlgebra.hom_ext <|
LinearMap.ext fun m =>
calc
ofEven Q (toEven Q (ι Q m)) = ofEven Q ⟨_, (toEven Q (ι Q m)).prop⟩ := by
rw [Subtype.coe_eta]
_ = (ι Q 0 + algebraMap R _ 1) * (ι Q m - algebraMap R _ 0) := by
simp_rw [toEven_ι]
exact ofEven_ι Q _ _
_ = ι Q m := by rw [map_one, map_zero, map_zero, sub_zero, zero_add, one_mul]
/-- Any clifford algebra is isomorphic to the even subalgebra of a clifford algebra with an extra
dimension (that is, with vector space `M × R`), with a quadratic form evaluating to `-1` on that new
basis vector. -/
def equivEven : CliffordAlgebra Q ≃ₐ[R] CliffordAlgebra.even (Q' Q) :=
AlgEquiv.ofAlgHom (toEven Q) (ofEven Q) (toEven_comp_ofEven Q) (ofEven_comp_toEven Q)
/-- The representation of the clifford conjugate (i.e. the reverse of the involute) in the even
subalgebra is just the reverse of the representation. -/
theorem coe_toEven_reverse_involute (x : CliffordAlgebra Q) :
↑(toEven Q (reverse (involute x))) =
reverse (Q := Q' Q) (toEven Q x : CliffordAlgebra (Q' Q)) := by
induction x using CliffordAlgebra.induction with
| algebraMap r => simp only [AlgHom.commutes, Subalgebra.coe_algebraMap, reverse.commutes]
| ι m =>
simp only [involute_ι, Subalgebra.coe_neg, toEven_ι, reverse.map_mul, reverse_v, reverse_e0,
| Mathlib/LinearAlgebra/CliffordAlgebra/EvenEquiv.lean | 185 | 215 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.Data.ENNReal.Operations
/-!
# Results about division in extended non-negative reals
This file establishes basic properties related to the inversion and division operations on `ℝ≥0∞`.
For instance, as a consequence of being a `DivInvOneMonoid`, `ℝ≥0∞` inherits a power operation
with integer exponent.
## Main results
A few order isomorphisms are worthy of mention:
- `OrderIso.invENNReal : ℝ≥0∞ ≃o ℝ≥0∞ᵒᵈ`: The map `x ↦ x⁻¹` as an order isomorphism to the dual.
- `orderIsoIicOneBirational : ℝ≥0∞ ≃o Iic (1 : ℝ≥0∞)`: The birational order isomorphism between
`ℝ≥0∞` and the unit interval `Set.Iic (1 : ℝ≥0∞)` given by `x ↦ (x⁻¹ + 1)⁻¹` with inverse
`x ↦ (x⁻¹ - 1)⁻¹`
- `orderIsoIicCoe (a : ℝ≥0) : Iic (a : ℝ≥0∞) ≃o Iic a`: Order isomorphism between an initial
interval in `ℝ≥0∞` and an initial interval in `ℝ≥0` given by the identity map.
- `orderIsoUnitIntervalBirational : ℝ≥0∞ ≃o Icc (0 : ℝ) 1`: An order isomorphism between
the extended nonnegative real numbers and the unit interval. This is `orderIsoIicOneBirational`
composed with the identity order isomorphism between `Iic (1 : ℝ≥0∞)` and `Icc (0 : ℝ) 1`.
-/
assert_not_exists Finset
open Set NNReal
namespace ENNReal
noncomputable section Inv
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0}
protected theorem div_eq_inv_mul : a / b = b⁻¹ * a := by rw [div_eq_mul_inv, mul_comm]
@[simp] theorem inv_zero : (0 : ℝ≥0∞)⁻¹ = ∞ :=
show sInf { b : ℝ≥0∞ | 1 ≤ 0 * b } = ∞ by simp
@[simp] theorem inv_top : ∞⁻¹ = 0 :=
bot_unique <| le_of_forall_gt_imp_ge_of_dense fun a (h : 0 < a) => sInf_le <| by
simp [*, h.ne', top_mul]
theorem coe_inv_le : (↑r⁻¹ : ℝ≥0∞) ≤ (↑r)⁻¹ :=
le_sInf fun b (hb : 1 ≤ ↑r * b) =>
coe_le_iff.2 <| by
rintro b rfl
apply NNReal.inv_le_of_le_mul
rwa [← coe_mul, ← coe_one, coe_le_coe] at hb
@[simp, norm_cast]
theorem coe_inv (hr : r ≠ 0) : (↑r⁻¹ : ℝ≥0∞) = (↑r)⁻¹ :=
coe_inv_le.antisymm <| sInf_le <| mem_setOf.2 <| by rw [← coe_mul, mul_inv_cancel₀ hr, coe_one]
@[norm_cast]
theorem coe_inv_two : ((2⁻¹ : ℝ≥0) : ℝ≥0∞) = 2⁻¹ := by rw [coe_inv _root_.two_ne_zero, coe_two]
@[simp, norm_cast]
theorem coe_div (hr : r ≠ 0) : (↑(p / r) : ℝ≥0∞) = p / r := by
rw [div_eq_mul_inv, div_eq_mul_inv, coe_mul, coe_inv hr]
lemma coe_div_le : ↑(p / r) ≤ (p / r : ℝ≥0∞) := by
simpa only [div_eq_mul_inv, coe_mul] using mul_le_mul_left' coe_inv_le _
theorem div_zero (h : a ≠ 0) : a / 0 = ∞ := by simp [div_eq_mul_inv, h]
instance : DivInvOneMonoid ℝ≥0∞ :=
{ inferInstanceAs (DivInvMonoid ℝ≥0∞) with
inv_one := by simpa only [coe_inv one_ne_zero, coe_one] using coe_inj.2 inv_one }
protected theorem inv_pow : ∀ {a : ℝ≥0∞} {n : ℕ}, (a ^ n)⁻¹ = a⁻¹ ^ n
| _, 0 => by simp only [pow_zero, inv_one]
| ⊤, n + 1 => by simp [top_pow]
| (a : ℝ≥0), n + 1 => by
rcases eq_or_ne a 0 with (rfl | ha)
· simp [top_pow]
· have := pow_ne_zero (n + 1) ha
norm_cast
rw [inv_pow]
protected theorem mul_inv_cancel (h0 : a ≠ 0) (ht : a ≠ ∞) : a * a⁻¹ = 1 := by
lift a to ℝ≥0 using ht
norm_cast at h0; norm_cast
exact mul_inv_cancel₀ h0
protected theorem inv_mul_cancel (h0 : a ≠ 0) (ht : a ≠ ∞) : a⁻¹ * a = 1 :=
mul_comm a a⁻¹ ▸ ENNReal.mul_inv_cancel h0 ht
/-- See `ENNReal.inv_mul_cancel_left` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma inv_mul_cancel_left' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) :
a⁻¹ * (a * b) = b := by
obtain rfl | ha₀ := eq_or_ne a 0
· simp_all
obtain rfl | ha := eq_or_ne a ⊤
· simp_all
· simp [← mul_assoc, ENNReal.inv_mul_cancel, *]
/-- See `ENNReal.inv_mul_cancel_left'` for a stronger version. -/
protected lemma inv_mul_cancel_left (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a⁻¹ * (a * b) = b :=
ENNReal.inv_mul_cancel_left' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_inv_cancel_left` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma mul_inv_cancel_left' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) :
a * (a⁻¹ * b) = b := by
obtain rfl | ha₀ := eq_or_ne a 0
· simp_all
obtain rfl | ha := eq_or_ne a ⊤
· simp_all
· simp [← mul_assoc, ENNReal.mul_inv_cancel, *]
/-- See `ENNReal.mul_inv_cancel_left'` for a stronger version. -/
protected lemma mul_inv_cancel_left (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a * (a⁻¹ * b) = b :=
ENNReal.mul_inv_cancel_left' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_inv_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma mul_inv_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b * b⁻¹ = a := by
obtain rfl | hb₀ := eq_or_ne b 0
· simp_all
obtain rfl | hb := eq_or_ne b ⊤
· simp_all
· simp [mul_assoc, ENNReal.mul_inv_cancel, *]
/-- See `ENNReal.mul_inv_cancel_right'` for a stronger version. -/
protected lemma mul_inv_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b * b⁻¹ = a :=
ENNReal.mul_inv_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.inv_mul_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma inv_mul_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b⁻¹ * b = a := by
obtain rfl | hb₀ := eq_or_ne b 0
· simp_all
obtain rfl | hb := eq_or_ne b ⊤
· simp_all
· simp [mul_assoc, ENNReal.inv_mul_cancel, *]
/-- See `ENNReal.inv_mul_cancel_right'` for a stronger version. -/
protected lemma inv_mul_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b⁻¹ * b = a :=
ENNReal.inv_mul_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.mul_div_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma mul_div_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b / b = a := ENNReal.mul_inv_cancel_right' hb₀ hb
/-- See `ENNReal.mul_div_cancel_right'` for a stronger version. -/
protected lemma mul_div_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b / b = a :=
ENNReal.mul_div_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.div_mul_cancel` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma div_mul_cancel' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) : b / a * a = b :=
ENNReal.inv_mul_cancel_right' ha₀ ha
/-- See `ENNReal.div_mul_cancel'` for a stronger version. -/
protected lemma div_mul_cancel (ha₀ : a ≠ 0) (ha : a ≠ ∞) : b / a * a = b :=
ENNReal.div_mul_cancel' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_div_cancel` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma mul_div_cancel' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) : a * (b / a) = b := by
rw [mul_comm, ENNReal.div_mul_cancel' ha₀ ha]
/-- See `ENNReal.mul_div_cancel'` for a stronger version. -/
protected lemma mul_div_cancel (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a * (b / a) = b :=
ENNReal.mul_div_cancel' (by simp [ha₀]) (by simp [ha])
protected theorem mul_comm_div : a / b * c = a * (c / b) := by
simp only [div_eq_mul_inv, mul_left_comm, mul_comm, mul_assoc]
protected theorem mul_div_right_comm : a * b / c = a / c * b := by
simp only [div_eq_mul_inv, mul_right_comm]
instance : InvolutiveInv ℝ≥0∞ where
inv_inv a := by
by_cases a = 0 <;> cases a <;> simp_all [none_eq_top, some_eq_coe, -coe_inv, (coe_inv _).symm]
@[simp] protected lemma inv_eq_one : a⁻¹ = 1 ↔ a = 1 := by rw [← inv_inj, inv_inv, inv_one]
@[simp] theorem inv_eq_top : a⁻¹ = ∞ ↔ a = 0 := inv_zero ▸ inv_inj
theorem inv_ne_top : a⁻¹ ≠ ∞ ↔ a ≠ 0 := by simp
@[aesop (rule_sets := [finiteness]) safe apply]
protected alias ⟨_, Finiteness.inv_ne_top⟩ := ENNReal.inv_ne_top
@[simp]
theorem inv_lt_top {x : ℝ≥0∞} : x⁻¹ < ∞ ↔ 0 < x := by
simp only [lt_top_iff_ne_top, inv_ne_top, pos_iff_ne_zero]
theorem div_lt_top {x y : ℝ≥0∞} (h1 : x ≠ ∞) (h2 : y ≠ 0) : x / y < ∞ :=
mul_lt_top h1.lt_top (inv_ne_top.mpr h2).lt_top
@[simp]
protected theorem inv_eq_zero : a⁻¹ = 0 ↔ a = ∞ :=
inv_top ▸ inv_inj
protected theorem inv_ne_zero : a⁻¹ ≠ 0 ↔ a ≠ ∞ := by simp
protected theorem div_pos (ha : a ≠ 0) (hb : b ≠ ∞) : 0 < a / b :=
ENNReal.mul_pos ha <| ENNReal.inv_ne_zero.2 hb
protected theorem inv_mul_le_iff {x y z : ℝ≥0∞} (h1 : x ≠ 0) (h2 : x ≠ ∞) :
x⁻¹ * y ≤ z ↔ y ≤ x * z := by
rw [← mul_le_mul_left h1 h2, ← mul_assoc, ENNReal.mul_inv_cancel h1 h2, one_mul]
protected theorem mul_inv_le_iff {x y z : ℝ≥0∞} (h1 : y ≠ 0) (h2 : y ≠ ∞) :
x * y⁻¹ ≤ z ↔ x ≤ z * y := by
rw [mul_comm, ENNReal.inv_mul_le_iff h1 h2, mul_comm]
protected theorem div_le_iff {x y z : ℝ≥0∞} (h1 : y ≠ 0) (h2 : y ≠ ∞) :
x / y ≤ z ↔ x ≤ z * y := by
rw [div_eq_mul_inv, ENNReal.mul_inv_le_iff h1 h2]
protected theorem div_le_iff' {x y z : ℝ≥0∞} (h1 : y ≠ 0) (h2 : y ≠ ∞) :
x / y ≤ z ↔ x ≤ y * z := by
rw [mul_comm, ENNReal.div_le_iff h1 h2]
protected theorem mul_inv {a b : ℝ≥0∞} (ha : a ≠ 0 ∨ b ≠ ∞) (hb : a ≠ ∞ ∨ b ≠ 0) :
(a * b)⁻¹ = a⁻¹ * b⁻¹ := by
induction' b with b
· replace ha : a ≠ 0 := ha.neg_resolve_right rfl
simp [ha]
induction' a with a
· replace hb : b ≠ 0 := coe_ne_zero.1 (hb.neg_resolve_left rfl)
simp [hb]
by_cases h'a : a = 0
· simp only [h'a, top_mul, ENNReal.inv_zero, ENNReal.coe_ne_top, zero_mul, Ne,
not_false_iff, ENNReal.coe_zero, ENNReal.inv_eq_zero]
by_cases h'b : b = 0
· simp only [h'b, ENNReal.inv_zero, ENNReal.coe_ne_top, mul_top, Ne, not_false_iff,
mul_zero, ENNReal.coe_zero, ENNReal.inv_eq_zero]
rw [← ENNReal.coe_mul, ← ENNReal.coe_inv, ← ENNReal.coe_inv h'a, ← ENNReal.coe_inv h'b, ←
ENNReal.coe_mul, mul_inv_rev, mul_comm]
simp [h'a, h'b]
protected theorem inv_div {a b : ℝ≥0∞} (htop : b ≠ ∞ ∨ a ≠ ∞) (hzero : b ≠ 0 ∨ a ≠ 0) :
(a / b)⁻¹ = b / a := by
rw [← ENNReal.inv_ne_zero] at htop
rw [← ENNReal.inv_ne_top] at hzero
rw [ENNReal.div_eq_inv_mul, ENNReal.div_eq_inv_mul, ENNReal.mul_inv htop hzero, mul_comm, inv_inv]
protected theorem mul_div_mul_left (a b : ℝ≥0∞) (hc : c ≠ 0) (hc' : c ≠ ⊤) :
c * a / (c * b) = a / b := by
rw [div_eq_mul_inv, div_eq_mul_inv, ENNReal.mul_inv (Or.inl hc) (Or.inl hc'), mul_mul_mul_comm,
ENNReal.mul_inv_cancel hc hc', one_mul]
protected theorem mul_div_mul_right (a b : ℝ≥0∞) (hc : c ≠ 0) (hc' : c ≠ ⊤) :
a * c / (b * c) = a / b := by
rw [div_eq_mul_inv, div_eq_mul_inv, ENNReal.mul_inv (Or.inr hc') (Or.inr hc), mul_mul_mul_comm,
ENNReal.mul_inv_cancel hc hc', mul_one]
protected theorem sub_div (h : 0 < b → b < a → c ≠ 0) : (a - b) / c = a / c - b / c := by
simp_rw [div_eq_mul_inv]
exact ENNReal.sub_mul (by simpa using h)
@[simp]
protected theorem inv_pos : 0 < a⁻¹ ↔ a ≠ ∞ :=
pos_iff_ne_zero.trans ENNReal.inv_ne_zero
theorem inv_strictAnti : StrictAnti (Inv.inv : ℝ≥0∞ → ℝ≥0∞) := by
intro a b h
lift a to ℝ≥0 using h.ne_top
induction b; · simp
rw [coe_lt_coe] at h
rcases eq_or_ne a 0 with (rfl | ha); · simp [h]
rw [← coe_inv h.ne_bot, ← coe_inv ha, coe_lt_coe]
exact NNReal.inv_lt_inv ha h
@[simp]
protected theorem inv_lt_inv : a⁻¹ < b⁻¹ ↔ b < a :=
inv_strictAnti.lt_iff_lt
theorem inv_lt_iff_inv_lt : a⁻¹ < b ↔ b⁻¹ < a := by
simpa only [inv_inv] using @ENNReal.inv_lt_inv a b⁻¹
theorem lt_inv_iff_lt_inv : a < b⁻¹ ↔ b < a⁻¹ := by
simpa only [inv_inv] using @ENNReal.inv_lt_inv a⁻¹ b
@[simp]
protected theorem inv_le_inv : a⁻¹ ≤ b⁻¹ ↔ b ≤ a :=
inv_strictAnti.le_iff_le
theorem inv_le_iff_inv_le : a⁻¹ ≤ b ↔ b⁻¹ ≤ a := by
simpa only [inv_inv] using @ENNReal.inv_le_inv a b⁻¹
theorem le_inv_iff_le_inv : a ≤ b⁻¹ ↔ b ≤ a⁻¹ := by
simpa only [inv_inv] using @ENNReal.inv_le_inv a⁻¹ b
@[gcongr] protected theorem inv_le_inv' (h : a ≤ b) : b⁻¹ ≤ a⁻¹ :=
ENNReal.inv_strictAnti.antitone h
@[gcongr] protected theorem inv_lt_inv' (h : a < b) : b⁻¹ < a⁻¹ := ENNReal.inv_strictAnti h
@[simp]
protected theorem inv_le_one : a⁻¹ ≤ 1 ↔ 1 ≤ a := by rw [inv_le_iff_inv_le, inv_one]
protected theorem one_le_inv : 1 ≤ a⁻¹ ↔ a ≤ 1 := by rw [le_inv_iff_le_inv, inv_one]
@[simp]
protected theorem inv_lt_one : a⁻¹ < 1 ↔ 1 < a := by rw [inv_lt_iff_inv_lt, inv_one]
@[simp]
protected theorem one_lt_inv : 1 < a⁻¹ ↔ a < 1 := by rw [lt_inv_iff_lt_inv, inv_one]
/-- The inverse map `fun x ↦ x⁻¹` is an order isomorphism between `ℝ≥0∞` and its `OrderDual` -/
@[simps! apply]
def _root_.OrderIso.invENNReal : ℝ≥0∞ ≃o ℝ≥0∞ᵒᵈ where
map_rel_iff' := ENNReal.inv_le_inv
toEquiv := (Equiv.inv ℝ≥0∞).trans OrderDual.toDual
@[simp]
theorem _root_.OrderIso.invENNReal_symm_apply (a : ℝ≥0∞ᵒᵈ) :
OrderIso.invENNReal.symm a = (OrderDual.ofDual a)⁻¹ :=
rfl
@[simp] theorem div_top : a / ∞ = 0 := by rw [div_eq_mul_inv, inv_top, mul_zero]
theorem top_div : ∞ / a = if a = ∞ then 0 else ∞ := by simp [div_eq_mul_inv, top_mul']
theorem top_div_of_ne_top (h : a ≠ ∞) : ∞ / a = ∞ := by simp [top_div, h]
@[simp] theorem top_div_coe : ∞ / p = ∞ := top_div_of_ne_top coe_ne_top
theorem top_div_of_lt_top (h : a < ∞) : ∞ / a = ∞ := top_div_of_ne_top h.ne
@[simp] protected theorem zero_div : 0 / a = 0 := zero_mul a⁻¹
theorem div_eq_top : a / b = ∞ ↔ a ≠ 0 ∧ b = 0 ∨ a = ∞ ∧ b ≠ ∞ := by
simp [div_eq_mul_inv, ENNReal.mul_eq_top]
protected theorem le_div_iff_mul_le (h0 : b ≠ 0 ∨ c ≠ 0) (ht : b ≠ ∞ ∨ c ≠ ∞) :
a ≤ c / b ↔ a * b ≤ c := by
induction' b with b
· lift c to ℝ≥0 using ht.neg_resolve_left rfl
rw [div_top, nonpos_iff_eq_zero]
rcases eq_or_ne a 0 with (rfl | ha) <;> simp [*]
rcases eq_or_ne b 0 with (rfl | hb)
· have hc : c ≠ 0 := h0.neg_resolve_left rfl
simp [div_zero hc]
· rw [← coe_ne_zero] at hb
rw [← ENNReal.mul_le_mul_right hb coe_ne_top, ENNReal.div_mul_cancel hb coe_ne_top]
protected theorem div_le_iff_le_mul (hb0 : b ≠ 0 ∨ c ≠ ∞) (hbt : b ≠ ∞ ∨ c ≠ 0) :
a / b ≤ c ↔ a ≤ c * b := by
suffices a * b⁻¹ ≤ c ↔ a ≤ c / b⁻¹ by simpa [div_eq_mul_inv]
refine (ENNReal.le_div_iff_mul_le ?_ ?_).symm <;> simpa
protected theorem lt_div_iff_mul_lt (hb0 : b ≠ 0 ∨ c ≠ ∞) (hbt : b ≠ ∞ ∨ c ≠ 0) :
c < a / b ↔ c * b < a :=
lt_iff_lt_of_le_iff_le (ENNReal.div_le_iff_le_mul hb0 hbt)
theorem div_le_of_le_mul (h : a ≤ b * c) : a / c ≤ b := by
by_cases h0 : c = 0
· have : a = 0 := by simpa [h0] using h
simp [*]
by_cases hinf : c = ∞; · simp [hinf]
exact (ENNReal.div_le_iff_le_mul (Or.inl h0) (Or.inl hinf)).2 h
theorem div_le_of_le_mul' (h : a ≤ b * c) : a / b ≤ c :=
div_le_of_le_mul <| mul_comm b c ▸ h
@[simp] protected theorem div_self_le_one : a / a ≤ 1 := div_le_of_le_mul <| by rw [one_mul]
@[simp] protected lemma mul_inv_le_one (a : ℝ≥0∞) : a * a⁻¹ ≤ 1 := ENNReal.div_self_le_one
@[simp] protected lemma inv_mul_le_one (a : ℝ≥0∞) : a⁻¹ * a ≤ 1 := by simp [mul_comm]
@[simp] lemma mul_inv_ne_top (a : ℝ≥0∞) : a * a⁻¹ ≠ ⊤ :=
ne_top_of_le_ne_top one_ne_top a.mul_inv_le_one
@[simp] lemma inv_mul_ne_top (a : ℝ≥0∞) : a⁻¹ * a ≠ ⊤ := by simp [mul_comm]
theorem mul_le_of_le_div (h : a ≤ b / c) : a * c ≤ b := by
rw [← inv_inv c]
exact div_le_of_le_mul h
theorem mul_le_of_le_div' (h : a ≤ b / c) : c * a ≤ b :=
mul_comm a c ▸ mul_le_of_le_div h
protected theorem div_lt_iff (h0 : b ≠ 0 ∨ c ≠ 0) (ht : b ≠ ∞ ∨ c ≠ ∞) : c / b < a ↔ c < a * b :=
lt_iff_lt_of_le_iff_le <| ENNReal.le_div_iff_mul_le h0 ht
theorem mul_lt_of_lt_div (h : a < b / c) : a * c < b := by
contrapose! h
exact ENNReal.div_le_of_le_mul h
theorem mul_lt_of_lt_div' (h : a < b / c) : c * a < b :=
mul_comm a c ▸ mul_lt_of_lt_div h
theorem div_lt_of_lt_mul (h : a < b * c) : a / c < b :=
mul_lt_of_lt_div <| by rwa [div_eq_mul_inv, inv_inv]
theorem div_lt_of_lt_mul' (h : a < b * c) : a / b < c :=
div_lt_of_lt_mul <| by rwa [mul_comm]
theorem inv_le_iff_le_mul (h₁ : b = ∞ → a ≠ 0) (h₂ : a = ∞ → b ≠ 0) : a⁻¹ ≤ b ↔ 1 ≤ a * b := by
rw [← one_div, ENNReal.div_le_iff_le_mul, mul_comm]
exacts [or_not_of_imp h₁, not_or_of_imp h₂]
@[simp 900]
theorem le_inv_iff_mul_le : a ≤ b⁻¹ ↔ a * b ≤ 1 := by
rw [← one_div, ENNReal.le_div_iff_mul_le] <;>
· right
simp
@[gcongr] protected theorem div_le_div (hab : a ≤ b) (hdc : d ≤ c) : a / c ≤ b / d :=
div_eq_mul_inv b d ▸ div_eq_mul_inv a c ▸ mul_le_mul' hab (ENNReal.inv_le_inv.mpr hdc)
@[gcongr] protected theorem div_le_div_left (h : a ≤ b) (c : ℝ≥0∞) : c / b ≤ c / a :=
ENNReal.div_le_div le_rfl h
@[gcongr] protected theorem div_le_div_right (h : a ≤ b) (c : ℝ≥0∞) : a / c ≤ b / c :=
ENNReal.div_le_div h le_rfl
protected theorem eq_inv_of_mul_eq_one_left (h : a * b = 1) : a = b⁻¹ := by
rw [← mul_one a, ← ENNReal.mul_inv_cancel (right_ne_zero_of_mul_eq_one h), ← mul_assoc, h,
one_mul]
rintro rfl
simp [left_ne_zero_of_mul_eq_one h] at h
theorem mul_le_iff_le_inv {a b r : ℝ≥0∞} (hr₀ : r ≠ 0) (hr₁ : r ≠ ∞) : r * a ≤ b ↔ a ≤ r⁻¹ * b := by
rw [← @ENNReal.mul_le_mul_left _ a _ hr₀ hr₁, ← mul_assoc, ENNReal.mul_inv_cancel hr₀ hr₁,
one_mul]
theorem le_of_forall_nnreal_lt {x y : ℝ≥0∞} (h : ∀ r : ℝ≥0, ↑r < x → ↑r ≤ y) : x ≤ y := by
refine le_of_forall_lt_imp_le_of_dense fun r hr => ?_
lift r to ℝ≥0 using ne_top_of_lt hr
exact h r hr
lemma eq_of_forall_nnreal_iff {x y : ℝ≥0∞} (h : ∀ r : ℝ≥0, ↑r ≤ x ↔ ↑r ≤ y) : x = y :=
le_antisymm (le_of_forall_nnreal_lt fun _r hr ↦ (h _).1 hr.le)
(le_of_forall_nnreal_lt fun _r hr ↦ (h _).2 hr.le)
theorem le_of_forall_pos_nnreal_lt {x y : ℝ≥0∞} (h : ∀ r : ℝ≥0, 0 < r → ↑r < x → ↑r ≤ y) : x ≤ y :=
le_of_forall_nnreal_lt fun r hr =>
(zero_le r).eq_or_lt.elim (fun h => h ▸ zero_le _) fun h0 => h r h0 hr
theorem eq_top_of_forall_nnreal_le {x : ℝ≥0∞} (h : ∀ r : ℝ≥0, ↑r ≤ x) : x = ∞ :=
top_unique <| le_of_forall_nnreal_lt fun r _ => h r
protected theorem add_div : (a + b) / c = a / c + b / c :=
right_distrib a b c⁻¹
protected theorem div_add_div_same {a b c : ℝ≥0∞} : a / c + b / c = (a + b) / c :=
ENNReal.add_div.symm
protected theorem div_self (h0 : a ≠ 0) (hI : a ≠ ∞) : a / a = 1 :=
ENNReal.mul_inv_cancel h0 hI
theorem mul_div_le : a * (b / a) ≤ b :=
mul_le_of_le_div' le_rfl
theorem eq_div_iff (ha : a ≠ 0) (ha' : a ≠ ∞) : b = c / a ↔ a * b = c :=
⟨fun h => by rw [h, ENNReal.mul_div_cancel ha ha'], fun h => by
rw [← h, mul_div_assoc, ENNReal.mul_div_cancel ha ha']⟩
protected theorem div_eq_div_iff (ha : a ≠ 0) (ha' : a ≠ ∞) (hb : b ≠ 0) (hb' : b ≠ ∞) :
c / b = d / a ↔ a * c = b * d := by
rw [eq_div_iff ha ha']
conv_rhs => rw [eq_comm]
rw [← eq_div_iff hb hb', mul_div_assoc, eq_comm]
theorem div_eq_one_iff {a b : ℝ≥0∞} (hb₀ : b ≠ 0) (hb₁ : b ≠ ∞) : a / b = 1 ↔ a = b :=
⟨fun h => by rw [← (eq_div_iff hb₀ hb₁).mp h.symm, mul_one], fun h =>
h.symm ▸ ENNReal.div_self hb₀ hb₁⟩
theorem inv_two_add_inv_two : (2 : ℝ≥0∞)⁻¹ + 2⁻¹ = 1 := by
rw [← two_mul, ← div_eq_mul_inv, ENNReal.div_self two_ne_zero ofNat_ne_top]
theorem inv_three_add_inv_three : (3 : ℝ≥0∞)⁻¹ + 3⁻¹ + 3⁻¹ = 1 := by
rw [← ENNReal.mul_inv_cancel three_ne_zero ofNat_ne_top]
ring
@[simp]
protected theorem add_halves (a : ℝ≥0∞) : a / 2 + a / 2 = a := by
rw [div_eq_mul_inv, ← mul_add, inv_two_add_inv_two, mul_one]
|
@[simp]
| Mathlib/Data/ENNReal/Inv.lean | 482 | 483 |
/-
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.Data.ENat.Lattice
import Mathlib.Order.OrderIsoNat
import Mathlib.Tactic.TFAE
/-!
# Maximal length of chains
This file contains lemmas to work with the maximal length of strictly descending finite
sequences (chains) in a partial order.
## Main definition
- `Set.subchain`: The set of strictly ascending lists of `α` contained in a `Set α`.
- `Set.chainHeight`: The maximal length of a strictly ascending sequence in a partial order.
This is defined as the maximum of the lengths of `Set.subchain`s, valued in `ℕ∞`.
## Main results
- `Set.exists_chain_of_le_chainHeight`: For each `n : ℕ` such that `n ≤ s.chainHeight`, there
exists `s.subchain` of length `n`.
- `Set.chainHeight_mono`: If `s ⊆ t` then `s.chainHeight ≤ t.chainHeight`.
- `Set.chainHeight_image`: If `f` is an order embedding, then
`(f '' s).chainHeight = s.chainHeight`.
- `Set.chainHeight_insert_of_forall_lt`: If `∀ y ∈ s, y < x`, then
`(insert x s).chainHeight = s.chainHeight + 1`.
- `Set.chainHeight_insert_of_forall_gt`: If `∀ y ∈ s, x < y`, then
`(insert x s).chainHeight = s.chainHeight + 1`.
- `Set.chainHeight_union_eq`: If `∀ x ∈ s, ∀ y ∈ t, s ≤ t`, then
`(s ∪ t).chainHeight = s.chainHeight + t.chainHeight`.
- `Set.wellFoundedGT_of_chainHeight_ne_top`:
If `s` has finite height, then `>` is well-founded on `s`.
- `Set.wellFoundedLT_of_chainHeight_ne_top`:
If `s` has finite height, then `<` is well-founded on `s`.
-/
assert_not_exists Field
open List hiding le_antisymm
open OrderDual
universe u v
variable {α β : Type*}
namespace Set
section LT
variable [LT α] [LT β] (s t : Set α)
/-- The set of strictly ascending lists of `α` contained in a `Set α`. -/
def subchain : Set (List α) :=
{ l | l.Chain' (· < ·) ∧ ∀ i ∈ l, i ∈ s }
@[simp]
theorem nil_mem_subchain : [] ∈ s.subchain := ⟨trivial, fun _ ↦ nofun⟩
variable {s} {l : List α} {a : α}
theorem cons_mem_subchain_iff :
(a::l) ∈ s.subchain ↔ a ∈ s ∧ l ∈ s.subchain ∧ ∀ b ∈ l.head?, a < b := by
simp only [subchain, mem_setOf_eq, forall_mem_cons, chain'_cons', and_left_comm, and_comm,
and_assoc]
@[simp]
theorem singleton_mem_subchain_iff : [a] ∈ s.subchain ↔ a ∈ s := by simp [cons_mem_subchain_iff]
instance : Nonempty s.subchain :=
⟨⟨[], s.nil_mem_subchain⟩⟩
variable (s)
/-- The maximal length of a strictly ascending sequence in a partial order. -/
noncomputable def chainHeight : ℕ∞ :=
⨆ l ∈ s.subchain, length l
theorem chainHeight_eq_iSup_subtype : s.chainHeight = ⨆ l : s.subchain, ↑l.1.length :=
iSup_subtype'
theorem exists_chain_of_le_chainHeight {n : ℕ} (hn : ↑n ≤ s.chainHeight) :
∃ l ∈ s.subchain, length l = n := by
rcases (le_top : s.chainHeight ≤ ⊤).eq_or_lt with ha | ha <;>
rw [chainHeight_eq_iSup_subtype] at ha
· obtain ⟨_, ⟨⟨l, h₁, h₂⟩, rfl⟩, h₃⟩ :=
not_bddAbove_iff'.mp (WithTop.iSup_coe_eq_top.1 ha) n
exact ⟨l.take n, ⟨h₁.take _, fun x h ↦ h₂ _ <| take_subset _ _ h⟩,
(l.length_take).trans <| min_eq_left <| le_of_not_ge h₃⟩
· rw [ENat.iSup_coe_lt_top] at ha
obtain ⟨⟨l, h₁, h₂⟩, e : l.length = _⟩ := Nat.sSup_mem (Set.range_nonempty _) ha
refine
⟨l.take n, ⟨h₁.take _, fun x h ↦ h₂ _ <| take_subset _ _ h⟩,
(l.length_take).trans <| min_eq_left <| ?_⟩
rwa [e, ← Nat.cast_le (α := ℕ∞), sSup_range, ENat.coe_iSup ha, ← chainHeight_eq_iSup_subtype]
theorem le_chainHeight_TFAE (n : ℕ) :
TFAE [↑n ≤ s.chainHeight, ∃ l ∈ s.subchain, length l = n, ∃ l ∈ s.subchain, n ≤ length l] := by
tfae_have 1 → 2 := s.exists_chain_of_le_chainHeight
tfae_have 2 → 3 := fun ⟨l, hls, he⟩ ↦ ⟨l, hls, he.ge⟩
tfae_have 3 → 1 := fun ⟨l, hs, hn⟩ ↦ le_iSup₂_of_le l hs (WithTop.coe_le_coe.2 hn)
tfae_finish
variable {s t}
theorem le_chainHeight_iff {n : ℕ} : ↑n ≤ s.chainHeight ↔ ∃ l ∈ s.subchain, length l = n :=
(le_chainHeight_TFAE s n).out 0 1
theorem length_le_chainHeight_of_mem_subchain (hl : l ∈ s.subchain) : ↑l.length ≤ s.chainHeight :=
le_chainHeight_iff.mpr ⟨l, hl, rfl⟩
theorem chainHeight_eq_top_iff : s.chainHeight = ⊤ ↔ ∀ n, ∃ l ∈ s.subchain, length l = n := by
refine ⟨fun h n ↦ le_chainHeight_iff.1 (le_top.trans_eq h.symm), fun h ↦ ?_⟩
contrapose! h; obtain ⟨n, hn⟩ := WithTop.ne_top_iff_exists.1 h
exact ⟨n + 1, fun l hs ↦ (Nat.lt_succ_iff.2 <| Nat.cast_le.1 <|
(length_le_chainHeight_of_mem_subchain hs).trans_eq hn.symm).ne⟩
@[simp]
theorem one_le_chainHeight_iff : 1 ≤ s.chainHeight ↔ s.Nonempty := by
rw [← Nat.cast_one, Set.le_chainHeight_iff]
simp only [length_eq_one_iff, @and_comm (_ ∈ _), @eq_comm _ _ [_], exists_exists_eq_and,
| singleton_mem_subchain_iff, Set.Nonempty]
@[simp]
theorem chainHeight_eq_zero_iff : s.chainHeight = 0 ↔ s = ∅ := by
rw [← not_iff_not, ← Ne, ← ENat.one_le_iff_ne_zero, one_le_chainHeight_iff,
| Mathlib/Order/Height.lean | 127 | 131 |
/-
Copyright (c) 2022 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Data.Fintype.Basic
import Mathlib.ModelTheory.Substructures
/-!
# Elementary Maps Between First-Order Structures
## Main Definitions
- A `FirstOrder.Language.ElementaryEmbedding` is an embedding that commutes with the
realizations of formulas.
- The `FirstOrder.Language.elementaryDiagram` of a structure is the set of all sentences with
parameters that the structure satisfies.
- `FirstOrder.Language.ElementaryEmbedding.ofModelsElementaryDiagram` is the canonical
elementary embedding of any structure into a model of its elementary diagram.
## Main Results
- The Tarski-Vaught Test for embeddings: `FirstOrder.Language.Embedding.isElementary_of_exists`
gives a simple criterion for an embedding to be elementary.
-/
open FirstOrder
namespace FirstOrder
namespace Language
open Structure
variable (L : Language) (M : Type*) (N : Type*) {P : Type*} {Q : Type*}
variable [L.Structure M] [L.Structure N] [L.Structure P] [L.Structure Q]
/-- An elementary embedding of first-order structures is an embedding that commutes with the
realizations of formulas. -/
structure ElementaryEmbedding where
/-- The underlying embedding -/
toFun : M → N
-- Porting note:
-- The autoparam here used to be `obviously`.
-- We have replaced it with `aesop` but that isn't currently sufficient.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Aesop.20and.20cases
-- If that can be improved, we should remove the proofs below.
map_formula' :
∀ ⦃n⦄ (φ : L.Formula (Fin n)) (x : Fin n → M), φ.Realize (toFun ∘ x) ↔ φ.Realize x := by
aesop
@[inherit_doc FirstOrder.Language.ElementaryEmbedding]
scoped[FirstOrder] notation:25 A " ↪ₑ[" L "] " B => FirstOrder.Language.ElementaryEmbedding L A B
variable {L} {M} {N}
namespace ElementaryEmbedding
attribute [coe] toFun
instance instFunLike : FunLike (M ↪ₑ[L] N) M N where
coe f := f.toFun
coe_injective' f g h := by
cases f
cases g
simp only [ElementaryEmbedding.mk.injEq]
ext x
exact funext_iff.1 h x
@[simp]
theorem map_boundedFormula (f : M ↪ₑ[L] N) {α : Type*} {n : ℕ} (φ : L.BoundedFormula α n)
(v : α → M) (xs : Fin n → M) : φ.Realize (f ∘ v) (f ∘ xs) ↔ φ.Realize v xs := by
classical
rw [← BoundedFormula.realize_restrictFreeVar' Set.Subset.rfl, Set.inclusion_eq_id, iff_eq_eq]
have h :=
f.map_formula' ((φ.restrictFreeVar id).toFormula.relabel (Fintype.equivFin _))
(Sum.elim (v ∘ (↑)) xs ∘ (Fintype.equivFin _).symm)
simp only [Formula.realize_relabel, BoundedFormula.realize_toFormula, iff_eq_eq] at h
rw [← Function.comp_assoc _ _ (Fintype.equivFin _).symm,
Function.comp_assoc _ (Fintype.equivFin _).symm (Fintype.equivFin _),
_root_.Equiv.symm_comp_self, Function.comp_id, Function.comp_assoc, Sum.elim_comp_inl,
Function.comp_assoc _ _ Sum.inr, Sum.elim_comp_inr, ← Function.comp_assoc] at h
refine h.trans ?_
erw [Function.comp_assoc _ _ (Fintype.equivFin _), _root_.Equiv.symm_comp_self,
Function.comp_id, Sum.elim_comp_inl, Sum.elim_comp_inr (v ∘ Subtype.val) xs,
← Set.inclusion_eq_id (s := (BoundedFormula.freeVarFinset φ : Set α)) Set.Subset.rfl,
BoundedFormula.realize_restrictFreeVar' Set.Subset.rfl]
@[simp]
theorem map_formula (f : M ↪ₑ[L] N) {α : Type*} (φ : L.Formula α) (x : α → M) :
φ.Realize (f ∘ x) ↔ φ.Realize x := by
rw [Formula.Realize, Formula.Realize, ← f.map_boundedFormula, Unique.eq_default (f ∘ default)]
theorem map_sentence (f : M ↪ₑ[L] N) (φ : L.Sentence) : M ⊨ φ ↔ N ⊨ φ := by
rw [Sentence.Realize, Sentence.Realize, ← f.map_formula, Unique.eq_default (f ∘ default)]
| theorem theory_model_iff (f : M ↪ₑ[L] N) (T : L.Theory) : M ⊨ T ↔ N ⊨ T := by
simp only [Theory.model_iff, f.map_sentence]
| Mathlib/ModelTheory/ElementaryMaps.lean | 98 | 100 |
/-
Copyright (c) 2024 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.CategoryTheory.Limits.Shapes.Pullback.CommSq
/-!
# Relation between mono/epi and pullback/pushout squares
In this file, monomorphisms and epimorphisms are characterized in terms
of pullback and pushout squares. For example, we obtain `mono_iff_isPullback`
which asserts that a morphism `f : X ⟶ Y` is a monomorphism iff the obvious
square
```
X ⟶ X
| |
v v
X ⟶ Y
```
is a pullback square.
-/
namespace CategoryTheory
open Category Limits
variable {C : Type*} [Category C] {X Y : C} {f : X ⟶ Y}
section Mono
variable {c : PullbackCone f f}
lemma mono_iff_fst_eq_snd (hc : IsLimit c) : Mono f ↔ c.fst = c.snd := by
constructor
· intro hf
simpa only [← cancel_mono f] using c.condition
· intro hf
constructor
intro Z g g' h
obtain ⟨φ, rfl, rfl⟩ := PullbackCone.IsLimit.lift' hc g g' h
rw [hf]
lemma mono_iff_isIso_fst (hc : IsLimit c) : Mono f ↔ IsIso c.fst := by
rw [mono_iff_fst_eq_snd hc]
constructor
· intro h
obtain ⟨φ, hφ₁, hφ₂⟩ := PullbackCone.IsLimit.lift' hc (𝟙 X) (𝟙 X) (by simp)
refine ⟨φ, PullbackCone.IsLimit.hom_ext hc ?_ ?_, hφ₁⟩
· dsimp
simp only [assoc, hφ₁, id_comp, comp_id]
· dsimp
simp only [assoc, hφ₂, id_comp, comp_id, h]
· intro
obtain ⟨φ, hφ₁, hφ₂⟩ := PullbackCone.IsLimit.lift' hc (𝟙 X) (𝟙 X) (by simp)
have : IsSplitEpi φ := IsSplitEpi.mk ⟨SplitEpi.mk c.fst (by
rw [← cancel_mono c.fst, assoc, id_comp, hφ₁, comp_id])⟩
rw [← cancel_epi φ, hφ₁, hφ₂]
lemma mono_iff_isIso_snd (hc : IsLimit c) : Mono f ↔ IsIso c.snd :=
mono_iff_isIso_fst (PullbackCone.flipIsLimit hc)
variable (f)
lemma mono_iff_isPullback : Mono f ↔ IsPullback (𝟙 X) (𝟙 X) f f := by
constructor
· intro
exact IsPullback.of_isLimit (PullbackCone.isLimitMkIdId f)
· intro hf
exact (mono_iff_fst_eq_snd hf.isLimit).2 rfl
end Mono
section Epi
variable {c : PushoutCocone f f}
lemma epi_iff_inl_eq_inr (hc : IsColimit c) : Epi f ↔ c.inl = c.inr := by
constructor
· intro hf
simpa only [← cancel_epi f] using c.condition
· intro hf
constructor
intro Z g g' h
obtain ⟨φ, rfl, rfl⟩ := PushoutCocone.IsColimit.desc' hc g g' h
rw [hf]
lemma epi_iff_isIso_inl (hc : IsColimit c) : Epi f ↔ IsIso c.inl := by
rw [epi_iff_inl_eq_inr hc]
constructor
· intro h
obtain ⟨φ, hφ₁, hφ₂⟩ := PushoutCocone.IsColimit.desc' hc (𝟙 Y) (𝟙 Y) (by simp)
refine ⟨φ, hφ₁, PushoutCocone.IsColimit.hom_ext hc ?_ ?_⟩
· dsimp
simp only [comp_id, reassoc_of% hφ₁]
· dsimp
simp only [comp_id, h, reassoc_of% hφ₂]
· intro
obtain ⟨φ, hφ₁, hφ₂⟩ := PushoutCocone.IsColimit.desc' hc (𝟙 Y) (𝟙 Y) (by simp)
have : IsSplitMono φ := IsSplitMono.mk ⟨SplitMono.mk c.inl (by
rw [← cancel_epi c.inl, reassoc_of% hφ₁, comp_id])⟩
rw [← cancel_mono φ, hφ₁, hφ₂]
lemma epi_iff_isIso_inr (hc : IsColimit c) : Epi f ↔ IsIso c.inr :=
epi_iff_isIso_inl (PushoutCocone.flipIsColimit hc)
variable (f)
| lemma epi_iff_isPushout : Epi f ↔ IsPushout f f (𝟙 Y) (𝟙 Y) := by
constructor
· intro
exact IsPushout.of_isColimit (PushoutCocone.isColimitMkIdId f)
· intro hf
exact (epi_iff_inl_eq_inr hf.isColimit).2 rfl
| Mathlib/CategoryTheory/Limits/EpiMono.lean | 113 | 118 |
/-
Copyright (c) 2021 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Analysis.Convex.Extreme
import Mathlib.Analysis.Convex.Function
import Mathlib.Topology.Algebra.Module.LinearMap
import Mathlib.Topology.Order.OrderClosed
/-!
# Exposed sets
This file defines exposed sets and exposed points for sets in a real vector space.
An exposed subset of `A` is a subset of `A` that is the set of all maximal points of a functional
(a continuous linear map `E → 𝕜`) over `A`. By convention, `∅` is an exposed subset of all sets.
This allows for better functoriality of the definition (the intersection of two exposed subsets is
exposed, faces of a polytope form a bounded lattice).
This is an analytic notion of "being on the side of". It is stronger than being extreme (see
`IsExposed.isExtreme`), but weaker (for exposed points) than being a vertex.
An exposed set of `A` is sometimes called a "face of `A`", but we decided to reserve this
terminology to the more specific notion of a face of a polytope (sometimes hopefully soon out
on mathlib!).
## Main declarations
* `IsExposed 𝕜 A B`: States that `B` is an exposed set of `A` (in the literature, `A` is often
implicit).
* `IsExposed.isExtreme`: An exposed set is also extreme.
## References
See chapter 8 of [Barry Simon, *Convexity*][simon2011]
## TODO
Prove lemmas relating exposed sets and points to the intrinsic frontier.
-/
open Affine Set
section PreorderSemiring
variable (𝕜 : Type*) {E : Type*} [TopologicalSpace 𝕜] [Semiring 𝕜] [Preorder 𝕜] [AddCommMonoid E]
[TopologicalSpace E] [Module 𝕜 E] {A B : Set E}
/-- A set `B` is exposed with respect to `A` iff it maximizes some functional over `A` (and contains
all points maximizing it). Written `IsExposed 𝕜 A B`. -/
def IsExposed (A B : Set E) : Prop :=
B.Nonempty → ∃ l : E →L[𝕜] 𝕜, B = { x ∈ A | ∀ y ∈ A, l y ≤ l x }
end PreorderSemiring
section OrderedRing
variable {𝕜 : Type*} {E : Type*} [TopologicalSpace 𝕜] [Ring 𝕜] [PartialOrder 𝕜] [AddCommMonoid E]
[TopologicalSpace E] [Module 𝕜 E] {l : E →L[𝕜] 𝕜} {A B C : Set E} {x : E}
/-- A useful way to build exposed sets from intersecting `A` with half-spaces (modelled by an
inequality with a functional). -/
def ContinuousLinearMap.toExposed (l : E →L[𝕜] 𝕜) (A : Set E) : Set E :=
{ x ∈ A | ∀ y ∈ A, l y ≤ l x }
theorem ContinuousLinearMap.toExposed.isExposed : IsExposed 𝕜 A (l.toExposed A) := fun _ => ⟨l, rfl⟩
theorem isExposed_empty : IsExposed 𝕜 A ∅ := fun ⟨_, hx⟩ => by
exfalso
exact hx
namespace IsExposed
protected theorem subset (hAB : IsExposed 𝕜 A B) : B ⊆ A := by
rintro x hx
obtain ⟨_, rfl⟩ := hAB ⟨x, hx⟩
exact hx.1
@[refl]
protected theorem refl (A : Set E) : IsExposed 𝕜 A A := fun ⟨_, _⟩ =>
⟨0, Subset.antisymm (fun _ hx => ⟨hx, fun _ _ => le_refl 0⟩) fun _ hx => hx.1⟩
protected theorem antisymm (hB : IsExposed 𝕜 A B) (hA : IsExposed 𝕜 B A) : A = B :=
hA.subset.antisymm hB.subset
/-! `IsExposed` is *not* transitive: Consider a (topologically) open cube with vertices
`A₀₀₀, ..., A₁₁₁` and add to it the triangle `A₀₀₀A₀₀₁A₀₁₀`. Then `A₀₀₁A₀₁₀` is an exposed subset
of `A₀₀₀A₀₀₁A₀₁₀` which is an exposed subset of the cube, but `A₀₀₁A₀₁₀` is not itself an exposed
subset of the cube. -/
protected theorem mono (hC : IsExposed 𝕜 A C) (hBA : B ⊆ A) (hCB : C ⊆ B) : IsExposed 𝕜 B C := by
rintro ⟨w, hw⟩
obtain ⟨l, rfl⟩ := hC ⟨w, hw⟩
exact ⟨l, Subset.antisymm (fun x hx => ⟨hCB hx, fun y hy => hx.2 y (hBA hy)⟩) fun x hx =>
⟨hBA hx.1, fun y hy => (hw.2 y hy).trans (hx.2 w (hCB hw))⟩⟩
/-- If `B` is a nonempty exposed subset of `A`, then `B` is the intersection of `A` with some closed
half-space. The converse is *not* true. It would require that the corresponding open half-space
doesn't intersect `A`. -/
theorem eq_inter_halfSpace' {A B : Set E} (hAB : IsExposed 𝕜 A B) (hB : B.Nonempty) :
∃ l : E →L[𝕜] 𝕜, ∃ a, B = { x ∈ A | a ≤ l x } := by
obtain ⟨l, rfl⟩ := hAB hB
obtain ⟨w, hw⟩ := hB
exact ⟨l, l w, Subset.antisymm (fun x hx => ⟨hx.1, hx.2 w hw.1⟩) fun x hx =>
⟨hx.1, fun y hy => (hw.2 y hy).trans hx.2⟩⟩
@[deprecated (since := "2024-11-12")] alias eq_inter_halfspace' := eq_inter_halfSpace'
/-- For nontrivial `𝕜`, if `B` is an exposed subset of `A`, then `B` is the intersection of `A` with
some closed half-space. The converse is *not* true. It would require that the corresponding open
half-space doesn't intersect `A`. -/
theorem eq_inter_halfSpace [IsOrderedRing 𝕜] [Nontrivial 𝕜] {A B : Set E} (hAB : IsExposed 𝕜 A B) :
∃ l : E →L[𝕜] 𝕜, ∃ a, B = { x ∈ A | a ≤ l x } := by
obtain rfl | hB := B.eq_empty_or_nonempty
· refine ⟨0, 1, ?_⟩
rw [eq_comm, eq_empty_iff_forall_not_mem]
rintro x ⟨-, h⟩
rw [ContinuousLinearMap.zero_apply] at h
have : ¬(1 : 𝕜) ≤ 0 := not_le_of_lt zero_lt_one
contradiction
exact hAB.eq_inter_halfSpace' hB
@[deprecated (since := "2024-11-12")] alias eq_inter_halfspace := eq_inter_halfSpace
protected theorem inter [IsOrderedRing 𝕜] [ContinuousAdd 𝕜] {A B C : Set E} (hB : IsExposed 𝕜 A B)
(hC : IsExposed 𝕜 A C) : IsExposed 𝕜 A (B ∩ C) := by
rintro ⟨w, hwB, hwC⟩
obtain ⟨l₁, rfl⟩ := hB ⟨w, hwB⟩
obtain ⟨l₂, rfl⟩ := hC ⟨w, hwC⟩
refine ⟨l₁ + l₂, Subset.antisymm ?_ ?_⟩
· rintro x ⟨⟨hxA, hxB⟩, ⟨-, hxC⟩⟩
exact ⟨hxA, fun z hz => add_le_add (hxB z hz) (hxC z hz)⟩
rintro x ⟨hxA, hx⟩
refine ⟨⟨hxA, fun y hy => ?_⟩, hxA, fun y hy => ?_⟩
· exact
(add_le_add_iff_right (l₂ x)).1 ((add_le_add (hwB.2 y hy) (hwC.2 x hxA)).trans (hx w hwB.1))
· exact
(add_le_add_iff_left (l₁ x)).1 (le_trans (add_le_add (hwB.2 x hxA) (hwC.2 y hy)) (hx w hwB.1))
theorem sInter [IsOrderedRing 𝕜] [ContinuousAdd 𝕜] {F : Finset (Set E)} (hF : F.Nonempty)
(hAF : ∀ B ∈ F, IsExposed 𝕜 A B) : IsExposed 𝕜 A (⋂₀ F) := by
classical
induction F using Finset.induction with
| empty => exfalso; exact Finset.not_nonempty_empty hF
| insert C F _ hF' =>
rw [Finset.coe_insert, sInter_insert]
obtain rfl | hFnemp := F.eq_empty_or_nonempty
· rw [Finset.coe_empty, sInter_empty, inter_univ]
exact hAF C (Finset.mem_singleton_self C)
· exact (hAF C (Finset.mem_insert_self C F)).inter
(hF' hFnemp fun B hB => hAF B (Finset.mem_insert_of_mem hB))
theorem inter_left (hC : IsExposed 𝕜 A C) (hCB : C ⊆ B) : IsExposed 𝕜 (A ∩ B) C := by
rintro ⟨w, hw⟩
obtain ⟨l, rfl⟩ := hC ⟨w, hw⟩
exact ⟨l, Subset.antisymm (fun x hx => ⟨⟨hx.1, hCB hx⟩, fun y hy => hx.2 y hy.1⟩)
fun x ⟨⟨hxC, _⟩, hx⟩ => ⟨hxC, fun y hy => (hw.2 y hy).trans (hx w ⟨hC.subset hw, hCB hw⟩)⟩⟩
theorem inter_right (hC : IsExposed 𝕜 B C) (hCA : C ⊆ A) : IsExposed 𝕜 (A ∩ B) C := by
rw [inter_comm]
exact hC.inter_left hCA
protected theorem isClosed [OrderClosedTopology 𝕜] {A B : Set E} (hAB : IsExposed 𝕜 A B)
(hA : IsClosed A) : IsClosed B := by
obtain rfl | hB := B.eq_empty_or_nonempty
· simp
obtain ⟨l, a, rfl⟩ := hAB.eq_inter_halfSpace' hB
exact hA.isClosed_le continuousOn_const l.continuous.continuousOn
protected theorem isCompact [OrderClosedTopology 𝕜] [T2Space E] {A B : Set E}
(hAB : IsExposed 𝕜 A B) (hA : IsCompact A) : IsCompact B :=
hA.of_isClosed_subset (hAB.isClosed hA.isClosed) hAB.subset
end IsExposed
variable (𝕜) in
/-- A point is exposed with respect to `A` iff there exists a hyperplane whose intersection with
`A` is exactly that point. -/
def Set.exposedPoints (A : Set E) : Set E :=
{ x ∈ A | ∃ l : E →L[𝕜] 𝕜, ∀ y ∈ A, l y ≤ l x ∧ (l x ≤ l y → y = x) }
theorem exposed_point_def :
x ∈ A.exposedPoints 𝕜 ↔ x ∈ A ∧ ∃ l : E →L[𝕜] 𝕜, ∀ y ∈ A, l y ≤ l x ∧ (l x ≤ l y → y = x) :=
Iff.rfl
theorem exposedPoints_subset : A.exposedPoints 𝕜 ⊆ A := fun _ hx => hx.1
@[simp]
theorem exposedPoints_empty : (∅ : Set E).exposedPoints 𝕜 = ∅ :=
subset_empty_iff.1 exposedPoints_subset
/-- Exposed points exactly correspond to exposed singletons. -/
theorem mem_exposedPoints_iff_exposed_singleton : x ∈ A.exposedPoints 𝕜 ↔ IsExposed 𝕜 A {x} := by
use fun ⟨hxA, l, hl⟩ _ =>
⟨l,
Eq.symm <|
eq_singleton_iff_unique_mem.2
⟨⟨hxA, fun y hy => (hl y hy).1⟩, fun z hz => (hl z hz.1).2 (hz.2 x hxA)⟩⟩
rintro h
obtain ⟨l, hl⟩ := h ⟨x, mem_singleton _⟩
rw [eq_comm, eq_singleton_iff_unique_mem] at hl
exact
⟨hl.1.1, l, fun y hy =>
⟨hl.1.2 y hy, fun hxy => hl.2 y ⟨hy, fun z hz => (hl.1.2 z hz).trans hxy⟩⟩⟩
end OrderedRing
section LinearOrderedRing
variable {𝕜 : Type*} {E : Type*} [TopologicalSpace 𝕜]
[Ring 𝕜] [LinearOrder 𝕜] [IsStrictOrderedRing 𝕜] [AddCommMonoid E]
[TopologicalSpace E] [Module 𝕜 E] {A B : Set E}
namespace IsExposed
protected theorem convex (hAB : IsExposed 𝕜 A B) (hA : Convex 𝕜 A) : Convex 𝕜 B := by
obtain rfl | hB := B.eq_empty_or_nonempty
· exact convex_empty
obtain ⟨l, rfl⟩ := hAB hB
exact fun x₁ hx₁ x₂ hx₂ a b ha hb hab =>
⟨hA hx₁.1 hx₂.1 ha hb hab, fun y hy =>
((l.toLinearMap.concaveOn convex_univ).convex_ge _ ⟨mem_univ _, hx₁.2 y hy⟩
⟨mem_univ _, hx₂.2 y hy⟩ ha hb hab).2⟩
protected theorem isExtreme (hAB : IsExposed 𝕜 A B) : IsExtreme 𝕜 A B := by
refine ⟨hAB.subset, fun x₁ hx₁A x₂ hx₂A x hxB hx => ?_⟩
obtain ⟨l, rfl⟩ := hAB ⟨x, hxB⟩
have hl : ConvexOn 𝕜 univ l := l.toLinearMap.convexOn convex_univ
have hlx₁ := hxB.2 x₁ hx₁A
have hlx₂ := hxB.2 x₂ hx₂A
refine ⟨⟨hx₁A, fun y hy => ?_⟩, ⟨hx₂A, fun y hy => ?_⟩⟩
· rw [hlx₁.antisymm (hl.le_left_of_right_le (mem_univ _) (mem_univ _) hx hlx₂)]
exact hxB.2 y hy
· rw [hlx₂.antisymm (hl.le_right_of_left_le (mem_univ _) (mem_univ _) hx hlx₁)]
exact hxB.2 y hy
end IsExposed
theorem exposedPoints_subset_extremePoints : A.exposedPoints 𝕜 ⊆ A.extremePoints 𝕜 := fun _ hx =>
(mem_exposedPoints_iff_exposed_singleton.1 hx).isExtreme.mem_extremePoints
end LinearOrderedRing
| Mathlib/Analysis/Convex/Exposed.lean | 243 | 250 | |
/-
Copyright (c) 2020 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis
-/
import Batteries.Tactic.Lint.Basic
import Mathlib.Algebra.Order.Monoid.Unbundled.Basic
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Algebra.Order.ZeroLEOne
import Mathlib.Data.Nat.Cast.Order.Ring
import Mathlib.Data.Int.Order.Basic
import Mathlib.Data.Ineq
/-!
# Lemmas for `linarith`.
Those in the `Linarith` namespace should stay here.
Those outside the `Linarith` namespace may be deleted as they are ported to mathlib4.
-/
namespace Linarith
universe u
theorem lt_irrefl {α : Type u} [Preorder α] {a : α} : ¬a < a := _root_.lt_irrefl a
theorem eq_of_eq_of_eq {α} [Semiring α] {a b : α} (ha : a = 0) (hb : b = 0) : a + b = 0 := by
simp [*]
section Semiring
variable {α : Type u} [Semiring α] [PartialOrder α]
theorem zero_lt_one [IsStrictOrderedRing α] : (0:α) < 1 :=
_root_.zero_lt_one
theorem le_of_eq_of_le {a b : α} (ha : a = 0) (hb : b ≤ 0) : a + b ≤ 0 := by
simp [*]
theorem lt_of_eq_of_lt {a b : α} (ha : a = 0) (hb : b < 0) : a + b < 0 := by
simp [*]
theorem le_of_le_of_eq {a b : α} (ha : a ≤ 0) (hb : b = 0) : a + b ≤ 0 := by
simp [*]
theorem lt_of_lt_of_eq {a b : α} (ha : a < 0) (hb : b = 0) : a + b < 0 := by
simp [*]
theorem add_nonpos [IsOrderedRing α] {a b : α} (ha : a ≤ 0) (hb : b ≤ 0) :
a + b ≤ 0 :=
_root_.add_nonpos ha hb
theorem add_lt_of_le_of_neg [IsStrictOrderedRing α] {a b c : α} (hbc : b ≤ c)
(ha : a < 0) : b + a < c :=
_root_.add_lt_of_le_of_neg hbc ha
theorem add_lt_of_neg_of_le [IsStrictOrderedRing α] {a b c : α} (ha : a < 0)
(hbc : b ≤ c) : a + b < c :=
_root_.add_lt_of_neg_of_le ha hbc
theorem add_neg [IsStrictOrderedRing α] {a b : α} (ha : a < 0)
(hb : b < 0) : a + b < 0 :=
_root_.add_neg ha hb
variable (α) in
| lemma natCast_nonneg [IsOrderedRing α] (n : ℕ) : (0 : α) ≤ n := Nat.cast_nonneg n
-- used alongside `mul_neg` and `mul_nonpos`, so has the same argument pattern for uniformity
@[nolint unusedArguments]
| Mathlib/Tactic/Linarith/Lemmas.lean | 65 | 68 |
/-
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.Nat.PrimeFin
import Mathlib.Data.Nat.Factorization.Defs
import Mathlib.Data.Nat.GCD.BigOperators
import Mathlib.Order.Interval.Finset.Nat
import Mathlib.Tactic.IntervalCases
/-!
# Basic lemmas on prime factorizations
-/
open Finset List Finsupp
namespace Nat
variable {a b m n p : ℕ}
/-! ### Basic facts about factorization -/
/-! ## Lemmas characterising when `n.factorization p = 0` -/
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))
@[simp]
theorem factorization_one_right (n : ℕ) : n.factorization 1 = 0 :=
factorization_eq_zero_of_non_prime _ not_prime_one
theorem dvd_of_factorization_pos {n p : ℕ} (hn : n.factorization p ≠ 0) : p ∣ n :=
dvd_of_mem_primeFactorsList <| mem_primeFactors_iff_mem_primeFactorsList.1 <| mem_support_iff.2 hn
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.1 hr0).2
/-- 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_primeFactorsList_multiset n]
simp [factorization, AddEquiv.map_eq_zero_iff, Multiset.coe_eq_zero]
/-! ## Lemmas about factorizations of products and powers -/
/-- 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
/-- 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
/-! ## Lemmas about factorizations of primes and prime powers -/
/-- 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]
/-- 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
rw [← Nat.factorization_prod_pow_eq_self hn, h]
simp
/-- 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
/-! ### Equivalence between `ℕ+` and `ℕ →₀ ℕ` with support in the primes. -/
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]⟩
theorem factorizationEquiv_inv_apply {f : ℕ →₀ ℕ} (hf : ∀ p ∈ f.support, Prime p) :
(factorizationEquiv.symm ⟨f, hf⟩).1 = f.prod (· ^ ·) :=
rfl
@[simp]
theorem ordProj_of_not_prime (n p : ℕ) (hp : ¬p.Prime) : ordProj[p] n = 1 := by
simp [factorization_eq_zero_of_non_prime n hp]
@[deprecated (since := "2024-10-24")] alias ord_proj_of_not_prime := ordProj_of_not_prime
@[simp]
theorem ordCompl_of_not_prime (n p : ℕ) (hp : ¬p.Prime) : ordCompl[p] n = n := by
simp [factorization_eq_zero_of_non_prime n hp]
@[deprecated (since := "2024-10-24")] alias ord_compl_of_not_prime := ordCompl_of_not_prime
theorem ordCompl_dvd (n p : ℕ) : ordCompl[p] n ∣ n :=
div_dvd_of_dvd (ordProj_dvd n p)
@[deprecated (since := "2024-10-24")] alias ord_compl_dvd := ordCompl_dvd
theorem ordProj_pos (n p : ℕ) : 0 < ordProj[p] n := by
if pp : p.Prime then simp [pow_pos pp.pos] else simp [pp]
@[deprecated (since := "2024-10-24")] alias ord_proj_pos := ordProj_pos
theorem ordProj_le {n : ℕ} (p : ℕ) (hn : n ≠ 0) : ordProj[p] n ≤ n :=
le_of_dvd hn.bot_lt (Nat.ordProj_dvd n p)
@[deprecated (since := "2024-10-24")] alias ord_proj_le := ordProj_le
theorem ordCompl_pos {n : ℕ} (p : ℕ) (hn : n ≠ 0) : 0 < ordCompl[p] n := by
if pp : p.Prime then
exact Nat.div_pos (ordProj_le p hn) (ordProj_pos n p)
else
simpa [Nat.factorization_eq_zero_of_non_prime n pp] using hn.bot_lt
@[deprecated (since := "2024-10-24")] alias ord_compl_pos := ordCompl_pos
theorem ordCompl_le (n p : ℕ) : ordCompl[p] n ≤ n :=
Nat.div_le_self _ _
@[deprecated (since := "2024-10-24")] alias ord_compl_le := ordCompl_le
theorem ordProj_mul_ordCompl_eq_self (n p : ℕ) : ordProj[p] n * ordCompl[p] n = n :=
Nat.mul_div_cancel' (ordProj_dvd n p)
@[deprecated (since := "2024-10-24")]
alias ord_proj_mul_ord_compl_eq_self := ordProj_mul_ordCompl_eq_self
theorem ordProj_mul {a b : ℕ} (p : ℕ) (ha : a ≠ 0) (hb : b ≠ 0) :
ordProj[p] (a * b) = ordProj[p] a * ordProj[p] b := by
simp [factorization_mul ha hb, pow_add]
@[deprecated (since := "2024-10-24")] alias ord_proj_mul := ordProj_mul
theorem ordCompl_mul (a b p : ℕ) : ordCompl[p] (a * b) = ordCompl[p] a * ordCompl[p] b := by
if ha : a = 0 then simp [ha] else
if hb : b = 0 then simp [hb] else
simp only [ordProj_mul p ha hb]
rw [div_mul_div_comm (ordProj_dvd a p) (ordProj_dvd b p)]
@[deprecated (since := "2024-10-24")] alias ord_compl_mul := ordCompl_mul
/-! ### Factorization and divisibility -/
/-- 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 (Nat.pow_lt_pow_iff_right pp.one_lt).1 <| (ordProj_le p hn).trans_lt <|
Nat.lt_pow_self pp.one_lt
· simpa only [factorization_eq_zero_of_non_prime n pp] using hn.bot_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 (Nat.pow_le_pow_iff_right pp.one_lt).1 ((ordProj_le p hn).trans hb)
else
simp [factorization_eq_zero_of_non_prime n pp]
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
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
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
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]
theorem Prime.pow_dvd_iff_dvd_ordProj {p k n : ℕ} (pp : Prime p) (hn : n ≠ 0) :
p ^ k ∣ n ↔ p ^ k ∣ ordProj[p] n := by
rw [pow_dvd_pow_iff_le_right pp.one_lt, pp.pow_dvd_iff_le_factorization hn]
@[deprecated (since := "2024-10-24")]
alias Prime.pow_dvd_iff_dvd_ord_proj := Prime.pow_dvd_iff_dvd_ordProj
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)
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
@[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 [tsub_eq_zero_of_le]
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]
theorem dvd_ordProj_of_dvd {n p : ℕ} (hn : n ≠ 0) (pp : p.Prime) (h : p ∣ n) : p ∣ ordProj[p] n :=
dvd_pow_self p (Prime.factorization_pos_of_dvd pp hn h).ne'
@[deprecated (since := "2024-10-24")] alias dvd_ord_proj_of_dvd := dvd_ordProj_of_dvd
theorem not_dvd_ordCompl {n p : ℕ} (hp : Prime p) (hn : n ≠ 0) : ¬p ∣ ordCompl[p] n := by
rw [Nat.Prime.dvd_iff_one_le_factorization hp (ordCompl_pos p hn).ne']
rw [Nat.factorization_div (Nat.ordProj_dvd n p)]
simp [hp.factorization]
@[deprecated (since := "2024-10-24")] alias not_dvd_ord_compl := not_dvd_ordCompl
theorem coprime_ordCompl {n p : ℕ} (hp : Prime p) (hn : n ≠ 0) : Coprime p (ordCompl[p] n) :=
(or_iff_left (not_dvd_ordCompl hp hn)).mp <| coprime_or_dvd_of_prime hp _
@[deprecated (since := "2024-10-24")] alias coprime_ord_compl := coprime_ordCompl
theorem factorization_ordCompl (n p : ℕ) :
(ordCompl[p] n).factorization = n.factorization.erase p := by
if hn : n = 0 then simp [hn] else
if pp : p.Prime then ?_ else
simp [pp]
ext q
rcases eq_or_ne q p with (rfl | hqp)
· simp only [Finsupp.erase_same, factorization_eq_zero_iff, not_dvd_ordCompl pp hn]
simp
· rw [Finsupp.erase_ne hqp, factorization_div (ordProj_dvd n p)]
simp [pp.factorization, hqp.symm]
@[deprecated (since := "2024-10-24")] alias factorization_ord_compl := factorization_ordCompl
-- `ordCompl[p] n` is the largest divisor of `n` not divisible by `p`.
theorem dvd_ordCompl_of_dvd_not_dvd {p d n : ℕ} (hdn : d ∣ n) (hpd : ¬p ∣ d) :
d ∣ ordCompl[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 (ordCompl_pos p hn0).ne', factorization_ordCompl]
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]
@[deprecated (since := "2024-10-24")]
alias dvd_ord_compl_of_dvd_not_dvd := dvd_ordCompl_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⟩ :=
(Nat.finiteMultiplicity_iff.mpr ⟨hp, Nat.pos_of_ne_zero hn⟩).exists_eq_pow_mul_and_not_dvd
⟨_, a', h₂, h₁⟩
/-- Any nonzero natural number is the product of an odd part `m` and a power of
two `2 ^ k`. -/
theorem exists_eq_two_pow_mul_odd {n : ℕ} (hn : n ≠ 0) :
∃ k m : ℕ, Odd m ∧ n = 2 ^ k * m :=
let ⟨k, m, hm, hn⟩ := exists_eq_pow_mul_and_not_dvd hn 2 (succ_ne_self 1)
⟨k, m, not_even_iff_odd.1 (mt Even.two_dvd hm), hn⟩
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 := by simp [*]
intro h
rw [dvd_iff_le_div_mul n d]
by_contra h2
obtain ⟨p, hp⟩ := exists_factorization_lt_of_lt (mul_ne_zero h1 hd) (not_le.mp h2)
rwa [factorization_mul h1 hd, add_apply, ← lt_tsub_iff_right, h, tsub_apply,
lt_self_iff_false] at hp
theorem ordProj_dvd_ordProj_of_dvd {a b : ℕ} (hb0 : b ≠ 0) (hab : a ∣ b) (p : ℕ) :
ordProj[p] a ∣ ordProj[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
@[deprecated (since := "2024-10-24")]
alias ord_proj_dvd_ord_proj_of_dvd := ordProj_dvd_ordProj_of_dvd
theorem ordProj_dvd_ordProj_iff_dvd {a b : ℕ} (ha0 : a ≠ 0) (hb0 : b ≠ 0) :
(∀ p : ℕ, ordProj[p] a ∣ ordProj[p] b) ↔ a ∣ b := by
refine ⟨fun h => ?_, fun hab p => ordProj_dvd_ordProj_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)
@[deprecated (since := "2024-10-24")]
alias ord_proj_dvd_ord_proj_iff_dvd := ordProj_dvd_ordProj_iff_dvd
theorem ordCompl_dvd_ordCompl_of_dvd {a b : ℕ} (hab : a ∣ b) (p : ℕ) :
ordCompl[p] a ∣ ordCompl[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 (ordProj_le p ha0) (ordProj_pos a p)).ne'
have hb := (Nat.div_pos (ordProj_le p hb0) (ordProj_pos b p)).ne'
rw [← factorization_le_iff_dvd ha hb, factorization_ordCompl a p, factorization_ordCompl 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
@[deprecated (since := "2024-10-24")]
alias ord_compl_dvd_ord_compl_of_dvd := ordCompl_dvd_ordCompl_of_dvd
theorem ordCompl_dvd_ordCompl_iff_dvd (a b : ℕ) :
(∀ p : ℕ, ordCompl[p] a ∣ ordCompl[p] b) ↔ a ∣ b := by
refine ⟨fun h => ?_, fun hab p => ordCompl_dvd_ordCompl_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
@[deprecated (since := "2024-10-24")]
alias ord_compl_dvd_ord_compl_iff_dvd := ordCompl_dvd_ordCompl_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, not_forall]
exact ⟨2, n, prime_two, dvd_zero _, mt (le_of_dvd hn.bot_lt) (n.lt_two_pow_self).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 (ordProj_dvd _ _)
theorem prod_primeFactors_dvd (n : ℕ) : ∏ p ∈ n.primeFactors, p ∣ n := by
by_cases hn : n = 0
· subst hn
simp
· simpa [prod_primeFactorsList hn] using (n.primeFactorsList : Multiset ℕ).toFinset_prod_dvd_prod
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.primeFactorsList ∧ p ∈ b.primeFactorsList := by simpa [dfac] using hp
exact prime_of_mem_primeFactorsList 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']
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
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, reduceCtorEq] 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]
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]
/-- 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) = {i ∈ Ico 1 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)
theorem factorization_eq_card_pow_dvd (n : ℕ) {p : ℕ} (pp : p.Prime) :
n.factorization p = #{i ∈ Ico 1 n | p ^ i ∣ n} := by
simp [← Icc_factorization_eq_pow_dvd n pp]
theorem Ico_filter_pow_dvd_eq {n p b : ℕ} (pp : p.Prime) (hn : n ≠ 0) (hb : n ≤ p ^ b) :
{i ∈ Ico 1 n | p ^ i ∣ n} = {i ∈ Icc 1 b | 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) <|
(Nat.pow_le_pow_iff_right pp.one_lt).1 <| (le_of_dvd hn.bot_lt h1).trans hb
/-! ### Factorization and coprimes -/
/-- If `p` is a prime factor of `a` then the power of `p` in `a` is the same that in `a * b`,
for any `b` coprime to `a`. -/
theorem factorization_eq_of_coprime_left {p a b : ℕ} (hab : Coprime a b)
(hpa : p ∈ a.primeFactorsList) : (a * b).factorization p = a.factorization p := by
rw [factorization_mul_apply_of_coprime hab, ← primeFactorsList_count_eq,
← primeFactorsList_count_eq,
count_eq_zero_of_not_mem (coprime_primeFactorsList_disjoint hab hpa), add_zero]
/-- If `p` is a prime factor of `b` then the power of `p` in `b` is the same that in `a * b`,
for any `a` coprime to `b`. -/
theorem factorization_eq_of_coprime_right {p a b : ℕ} (hab : Coprime a b)
(hpb : p ∈ b.primeFactorsList) : (a * b).factorization p = b.factorization p := by
rw [mul_comm]
exact factorization_eq_of_coprime_left (coprime_comm.mp hab) hpb
/-- Two positive naturals are equal if their prime padic valuations are equal -/
theorem eq_iff_prime_padicValNat_eq (a b : ℕ) (ha : a ≠ 0) (hb : b ≠ 0) :
a = b ↔ ∀ p : ℕ, p.Prime → padicValNat p a = padicValNat p b := by
constructor
· rintro rfl
simp
· intro h
refine eq_of_factorization_eq ha hb fun p => ?_
by_cases pp : p.Prime
· simp [factorization_def, pp, h p pp]
· simp [factorization_eq_zero_of_non_prime, pp]
theorem prod_pow_prime_padicValNat (n : Nat) (hn : n ≠ 0) (m : Nat) (pr : n < m) :
∏ p ∈ range m with p.Prime, p ^ padicValNat p n = n := by
nth_rw 2 [← factorization_prod_pow_eq_self hn]
rw [eq_comm]
apply Finset.prod_subset_one_on_sdiff
· exact fun p hp => Finset.mem_filter.mpr ⟨Finset.mem_range.2 <| pr.trans_le' <|
le_of_mem_primeFactors hp, prime_of_mem_primeFactors hp⟩
· intro p hp
obtain ⟨hp1, hp2⟩ := Finset.mem_sdiff.mp hp
rw [← factorization_def n (Finset.mem_filter.mp hp1).2]
simp [Finsupp.not_mem_support_iff.mp hp2]
· intro p hp
simp [factorization_def n (prime_of_mem_primeFactors hp)]
/-! ### Lemmas about factorizations of particular functions -/
-- TODO: Port lemmas from `Data/Nat/Multiplicity` to here, re-written in terms of `factorization`
/-- Exactly `n / p` naturals in `[1, n]` are multiples of `p`.
See `Nat.card_multiples'` for an alternative spelling of the statement. -/
theorem card_multiples (n p : ℕ) : #{e ∈ range n | p ∣ e + 1} = n / p := by
induction' n with n hn
· simp
simp [Nat.succ_div, add_ite, add_zero, Finset.range_succ, filter_insert, apply_ite card,
card_insert_of_not_mem, hn]
/-- Exactly `n / p` naturals in `(0, n]` are multiples of `p`. -/
theorem Ioc_filter_dvd_card_eq_div (n p : ℕ) : #{x ∈ Ioc 0 n | p ∣ x} = n / p := by
induction' n with n IH
· simp
-- TODO: Golf away `h1` after Yaël PRs a lemma asserting this
have h1 : Ioc 0 n.succ = insert n.succ (Ioc 0 n) := by
rcases n.eq_zero_or_pos with (rfl | hn)
· simp
simp_rw [← Ico_succ_succ, Ico_insert_right (succ_le_succ hn.le), Ico_succ_right]
simp [Nat.succ_div, add_ite, add_zero, h1, filter_insert, apply_ite card, card_insert_eq_ite, IH,
Finset.mem_filter, mem_Ioc, not_le.2 (lt_add_one n)]
/-- There are exactly `⌊N/n⌋` positive multiples of `n` that are `≤ N`.
See `Nat.card_multiples` for a "shifted-by-one" version. -/
lemma card_multiples' (N n : ℕ) : #{k ∈ range N.succ | k ≠ 0 ∧ n ∣ k} = N / n := by
induction N with
| zero => simp [Finset.filter_false_of_mem]
| succ N ih =>
rw [Finset.range_succ, Finset.filter_insert]
by_cases h : n ∣ N.succ
· simp [h, succ_div_of_dvd, ih]
· simp [h, succ_div_of_not_dvd, ih]
end Nat
| Mathlib/Data/Nat/Factorization/Basic.lean | 932 | 937 | |
/-
Copyright (c) 2024 Mitchell Lee. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mitchell Lee
-/
import Mathlib.Topology.Algebra.GroupCompletion
import Mathlib.Topology.Algebra.InfiniteSum.Group
/-!
# Infinite sums in the completion of a topological group
-/
open UniformSpace.Completion
variable {α β : Type*} [AddCommGroup α] [UniformSpace α] [IsUniformAddGroup α]
/-- A function `f` has a sum in an uniform additive group `α` if and only if it has that sum in the
completion of `α`. -/
theorem hasSum_iff_hasSum_compl (f : β → α) (a : α) :
HasSum (toCompl ∘ f) a ↔ HasSum f a := (isDenseInducing_toCompl α).hasSum_iff f a
/-- A function `f` is summable in a uniform additive group `α` if and only if it is summable in
`Completion α` and its sum in `Completion α` lies in the range of `toCompl : α →+ Completion α`. -/
theorem summable_iff_summable_compl_and_tsum_mem (f : β → α) :
Summable f ↔ Summable (toCompl ∘ f) ∧ ∑' i, toCompl (f i) ∈ Set.range toCompl :=
(isDenseInducing_toCompl α).summable_iff_tsum_comp_mem_range f
/-- A function `f` is summable in a uniform additive group `α` if and only if the net of its partial
sums is Cauchy and its sum in `Completion α` lies in the range of `toCompl : α →+ Completion α`.
(The condition that the net of partial sums is Cauchy can be checked using
`cauchySeq_finset_iff_sum_vanishing` or `cauchySeq_finset_iff_tsum_vanishing`.) -/
| theorem summable_iff_cauchySeq_finset_and_tsum_mem (f : β → α) :
Summable f ↔ CauchySeq (fun s : Finset β ↦ ∑ b ∈ s, f b) ∧
∑' i, toCompl (f i) ∈ Set.range toCompl := by
classical
constructor
· rintro ⟨a, ha⟩
exact ⟨ha.cauchySeq, ((summable_iff_summable_compl_and_tsum_mem f).mp ⟨a, ha⟩).2⟩
· rintro ⟨h_cauchy, h_tsum⟩
apply (summable_iff_summable_compl_and_tsum_mem f).mpr
constructor
· apply summable_iff_cauchySeq_finset.mpr
simp_rw [Function.comp_apply, ← map_sum]
exact h_cauchy.map (uniformContinuous_coe α)
· exact h_tsum
| Mathlib/Topology/Algebra/InfiniteSum/GroupCompletion.lean | 32 | 45 |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Constructions.BorelSpace.Order
import Mathlib.MeasureTheory.Group.MeasurableEquiv
import Mathlib.Topology.MetricSpace.HausdorffDistance
/-!
# Regular measures
A measure is `OuterRegular` if the measure of any measurable set `A` is the infimum of `μ U` over
all open sets `U` containing `A`.
A measure is `WeaklyRegular` if it satisfies the following properties:
* it is outer regular;
* it is inner regular for open sets with respect to closed sets: the measure of any open set `U`
is the supremum of `μ F` over all closed sets `F` contained in `U`.
A measure is `Regular` if it satisfies the following properties:
* it is finite on compact sets;
* it is outer regular;
* it is inner regular for open sets with respect to compacts closed sets: the measure of any open
set `U` is the supremum of `μ K` over all compact sets `K` contained in `U`.
A measure is `InnerRegular` if it is inner regular for measurable sets with respect to compact
sets: the measure of any measurable set `s` is the supremum of `μ K` over all compact
sets contained in `s`.
A measure is `InnerRegularCompactLTTop` if it is inner regular for measurable sets of finite
measure with respect to compact sets: the measure of any measurable set `s` is the supremum
of `μ K` over all compact sets contained in `s`.
There is a reason for this zoo of regularity classes:
* A finite measure on a metric space is always weakly regular. Therefore, in probability theory,
weakly regular measures play a prominent role.
* In locally compact topological spaces, there are two competing notions of Radon measures: the
ones that are regular, and the ones that are inner regular. For any of these two notions, there is
a Riesz representation theorem, and an existence and uniqueness statement for the Haar measure in
locally compact topological groups. The two notions coincide in sigma-compact spaces, but they
differ in general, so it is worth having the two of them.
* Both notions of Haar measure satisfy the weaker notion `InnerRegularCompactLTTop`, so it is worth
trying to express theorems using this weaker notion whenever possible, to make sure that it
applies to both Haar measures simultaneously.
While traditional textbooks on measure theory on locally compact spaces emphasize regular measures,
more recent textbooks emphasize that inner regular Haar measures are better behaved than regular
Haar measures, so we will develop both notions.
The five conditions above are registered as typeclasses for a measure `μ`, and implications between
them are recorded as instances. For example, in a Hausdorff topological space, regularity implies
weak regularity. Also, regularity or inner regularity both imply `InnerRegularCompactLTTop`.
In a regular locally compact finite measure space, then regularity, inner regularity
and `InnerRegularCompactLTTop` are all equivalent.
In order to avoid code duplication, we also define a measure `μ` to be `InnerRegularWRT` for sets
satisfying a predicate `q` with respect to sets satisfying a predicate `p` if for any set
`U ∈ {U | q U}` and a number `r < μ U` there exists `F ⊆ U` such that `p F` and `r < μ F`.
There are two main nontrivial results in the development below:
* `InnerRegularWRT.measurableSet_of_isOpen` shows that, for an outer regular measure, inner
regularity for open sets with respect to compact sets or closed sets implies inner regularity for
all measurable sets of finite measure (with respect to compact sets or closed sets respectively).
* `InnerRegularWRT.weaklyRegular_of_finite` shows that a finite measure which is inner regular for
open sets with respect to closed sets (for instance a finite measure on a metric space) is weakly
regular.
All other results are deduced from these ones.
Here is an example showing how regularity and inner regularity may differ even on locally compact
spaces. Consider the group `ℝ × ℝ` where the first factor has the discrete topology and the second
one the usual topology. It is a locally compact Hausdorff topological group, with Haar measure equal
to Lebesgue measure on each vertical fiber. Let us consider the regular version of Haar measure.
Then the set `ℝ × {0}` has infinite measure (by outer regularity), but any compact set it contains
has zero measure (as it is finite). In fact, this set only contains subset with measure zero or
infinity. The inner regular version of Haar measure, on the other hand, gives zero mass to the
set `ℝ × {0}`.
Another interesting example is the sum of the Dirac masses at rational points in the real line.
It is a σ-finite measure on a locally compact metric space, but it is not outer regular: for
outer regularity, one needs additional locally finite assumptions. On the other hand, it is
inner regular.
Several authors require both regularity and inner regularity for their measures. We have opted
for the more fine grained definitions above as they apply more generally.
## Main definitions
* `MeasureTheory.Measure.OuterRegular μ`: a typeclass registering that a measure `μ` on a
topological space is outer regular.
* `MeasureTheory.Measure.Regular μ`: a typeclass registering that a measure `μ` on a topological
space is regular.
* `MeasureTheory.Measure.WeaklyRegular μ`: a typeclass registering that a measure `μ` on a
topological space is weakly regular.
* `MeasureTheory.Measure.InnerRegularWRT μ p q`: a non-typeclass predicate saying that a measure `μ`
is inner regular for sets satisfying `q` with respect to sets satisfying `p`.
* `MeasureTheory.Measure.InnerRegular μ`: a typeclass registering that a measure `μ` on a
topological space is inner regular for measurable sets with respect to compact sets.
* `MeasureTheory.Measure.InnerRegularCompactLTTop μ`: a typeclass registering that a measure `μ`
on a topological space is inner regular for measurable sets of finite measure with respect to
compact sets.
## Main results
### Outer regular measures
* `Set.measure_eq_iInf_isOpen` asserts that, when `μ` is outer regular, the measure of a
set is the infimum of the measure of open sets containing it.
* `Set.exists_isOpen_lt_of_lt` asserts that, when `μ` is outer regular, for every set `s`
and `r > μ s` there exists an open superset `U ⊇ s` of measure less than `r`.
* push forward of an outer regular measure is outer regular, and scalar multiplication of a regular
measure by a finite number is outer regular.
### Weakly regular measures
* `IsOpen.measure_eq_iSup_isClosed` asserts that the measure of an open set is the supremum of
the measure of closed sets it contains.
* `IsOpen.exists_lt_isClosed`: for an open set `U` and `r < μ U`, there exists a closed `F ⊆ U`
of measure greater than `r`;
* `MeasurableSet.measure_eq_iSup_isClosed_of_ne_top` asserts that the measure of a measurable set
of finite measure is the supremum of the measure of closed sets it contains.
* `MeasurableSet.exists_lt_isClosed_of_ne_top` and `MeasurableSet.exists_isClosed_lt_add`:
a measurable set of finite measure can be approximated by a closed subset (stated as
`r < μ F` and `μ s < μ F + ε`, respectively).
* `MeasureTheory.Measure.WeaklyRegular.of_pseudoMetrizableSpace_of_isFiniteMeasure` is an
instance registering that a finite measure on a metric space is weakly regular (in fact, a pseudo
metrizable space is enough);
* `MeasureTheory.Measure.WeaklyRegular.of_pseudoMetrizableSpace_secondCountable_of_locallyFinite`
is an instance registering that a locally finite measure on a second countable metric space (or
even a pseudo metrizable space) is weakly regular.
### Regular measures
* `IsOpen.measure_eq_iSup_isCompact` asserts that the measure of an open set is the supremum of
the measure of compact sets it contains.
* `IsOpen.exists_lt_isCompact`: for an open set `U` and `r < μ U`, there exists a compact `K ⊆ U`
of measure greater than `r`;
* `MeasureTheory.Measure.Regular.of_sigmaCompactSpace_of_isLocallyFiniteMeasure` is an
instance registering that a locally finite measure on a `σ`-compact metric space is regular (in
fact, an emetric space is enough).
### Inner regular measures
* `MeasurableSet.measure_eq_iSup_isCompact` asserts that the measure of a measurable set is the
supremum of the measure of compact sets it contains.
* `MeasurableSet.exists_lt_isCompact`: for a measurable set `s` and `r < μ s`, there exists a
compact `K ⊆ s` of measure greater than `r`;
### Inner regular measures for finite measure sets with respect to compact sets
* `MeasurableSet.measure_eq_iSup_isCompact_of_ne_top` asserts that the measure of a measurable set
of finite measure is the supremum of the measure of compact sets it contains.
* `MeasurableSet.exists_lt_isCompact_of_ne_top` and `MeasurableSet.exists_isCompact_lt_add`:
a measurable set of finite measure can be approximated by a compact subset (stated as
`r < μ K` and `μ s < μ K + ε`, respectively).
## Implementation notes
The main nontrivial statement is `MeasureTheory.Measure.InnerRegular.weaklyRegular_of_finite`,
expressing that in a finite measure space, if every open set can be approximated from inside by
closed sets, then the measure is in fact weakly regular. To prove that we show that any measurable
set can be approximated from inside by closed sets and from outside by open sets. This statement is
proved by measurable induction, starting from open sets and checking that it is stable by taking
complements (this is the point of this condition, being symmetrical between inside and outside) and
countable disjoint unions.
Once this statement is proved, one deduces results for `σ`-finite measures from this statement, by
restricting them to finite measure sets (and proving that this restriction is weakly regular, using
again the same statement).
For non-Hausdorff spaces, one may argue whether the right condition for inner regularity is with
respect to compact sets, or to compact closed sets. For instance,
[Fremlin, *Measure Theory* (volume 4, 411J)][fremlin_vol4] considers measures which are inner
regular with respect to compact closed sets (and calls them *tight*). However, since most of the
literature uses mere compact sets, we have chosen to follow this convention. It doesn't make a
difference in Hausdorff spaces, of course. In locally compact topological groups, the two
conditions coincide, since if a compact set `k` is contained in a measurable set `u`, then the
closure of `k` is a compact closed set still contained in `u`, see
`IsCompact.closure_subset_of_measurableSet_of_group`.
## References
[Halmos, Measure Theory, §52][halmos1950measure]. Note that Halmos uses an unusual definition of
Borel sets (for him, they are elements of the `σ`-algebra generated by compact sets!), so his
proofs or statements do not apply directly.
[Billingsley, Convergence of Probability Measures][billingsley1999]
[Bogachev, Measure Theory, volume 2, Theorem 7.11.1][bogachev2007]
-/
open Set Filter ENNReal NNReal TopologicalSpace
open scoped symmDiff Topology
namespace MeasureTheory
namespace Measure
/-- We say that a measure `μ` is *inner regular* with respect to predicates `p q : Set α → Prop`,
if for every `U` such that `q U` and `r < μ U`, there exists a subset `K ⊆ U` satisfying `p K`
of measure greater than `r`.
This definition is used to prove some facts about regular and weakly regular measures without
repeating the proofs. -/
def InnerRegularWRT {α} {_ : MeasurableSpace α} (μ : Measure α) (p q : Set α → Prop) :=
∀ ⦃U⦄, q U → ∀ r < μ U, ∃ K, K ⊆ U ∧ p K ∧ r < μ K
namespace InnerRegularWRT
variable {α : Type*} {m : MeasurableSpace α} {μ : Measure α} {p q : Set α → Prop} {U : Set α}
{ε : ℝ≥0∞}
theorem measure_eq_iSup (H : InnerRegularWRT μ p q) (hU : q U) :
μ U = ⨆ (K) (_ : K ⊆ U) (_ : p K), μ K := by
refine
le_antisymm (le_of_forall_lt fun r hr => ?_) (iSup₂_le fun K hK => iSup_le fun _ => μ.mono hK)
simpa only [lt_iSup_iff, exists_prop] using H hU r hr
theorem exists_subset_lt_add (H : InnerRegularWRT μ p q) (h0 : p ∅) (hU : q U) (hμU : μ U ≠ ∞)
(hε : ε ≠ 0) : ∃ K, K ⊆ U ∧ p K ∧ μ U < μ K + ε := by
rcases eq_or_ne (μ U) 0 with h₀ | h₀
· refine ⟨∅, empty_subset _, h0, ?_⟩
rwa [measure_empty, h₀, zero_add, pos_iff_ne_zero]
· rcases H hU _ (ENNReal.sub_lt_self hμU h₀ hε) with ⟨K, hKU, hKc, hrK⟩
exact ⟨K, hKU, hKc, ENNReal.lt_add_of_sub_lt_right (Or.inl hμU) hrK⟩
protected theorem map {α β} [MeasurableSpace α] [MeasurableSpace β]
{μ : Measure α} {pa qa : Set α → Prop}
(H : InnerRegularWRT μ pa qa) {f : α → β} (hf : AEMeasurable f μ) {pb qb : Set β → Prop}
(hAB : ∀ U, qb U → qa (f ⁻¹' U)) (hAB' : ∀ K, pa K → pb (f '' K))
(hB₂ : ∀ U, qb U → MeasurableSet U) :
InnerRegularWRT (map f μ) pb qb := by
intro U hU r hr
rw [map_apply_of_aemeasurable hf (hB₂ _ hU)] at hr
rcases H (hAB U hU) r hr with ⟨K, hKU, hKc, hK⟩
refine ⟨f '' K, image_subset_iff.2 hKU, hAB' _ hKc, ?_⟩
exact hK.trans_le (le_map_apply_image hf _)
theorem map' {α β} [MeasurableSpace α] [MeasurableSpace β] {μ : Measure α} {pa qa : Set α → Prop}
(H : InnerRegularWRT μ pa qa) (f : α ≃ᵐ β) {pb qb : Set β → Prop}
(hAB : ∀ U, qb U → qa (f ⁻¹' U)) (hAB' : ∀ K, pa K → pb (f '' K)) :
InnerRegularWRT (map f μ) pb qb := by
intro U hU r hr
rw [f.map_apply U] at hr
rcases H (hAB U hU) r hr with ⟨K, hKU, hKc, hK⟩
refine ⟨f '' K, image_subset_iff.2 hKU, hAB' _ hKc, ?_⟩
rwa [f.map_apply, f.preimage_image]
theorem smul (H : InnerRegularWRT μ p q) (c : ℝ≥0∞) : InnerRegularWRT (c • μ) p q := by
intro U hU r hr
rw [smul_apply, H.measure_eq_iSup hU, smul_eq_mul] at hr
simpa only [ENNReal.mul_iSup, lt_iSup_iff, exists_prop] using hr
theorem trans {q' : Set α → Prop} (H : InnerRegularWRT μ p q) (H' : InnerRegularWRT μ q q') :
InnerRegularWRT μ p q' := by
intro U hU r hr
rcases H' hU r hr with ⟨F, hFU, hqF, hF⟩; rcases H hqF _ hF with ⟨K, hKF, hpK, hrK⟩
exact ⟨K, hKF.trans hFU, hpK, hrK⟩
theorem rfl {p : Set α → Prop} : InnerRegularWRT μ p p :=
fun U hU _r hr ↦ ⟨U, Subset.rfl, hU, hr⟩
theorem of_imp (h : ∀ s, q s → p s) : InnerRegularWRT μ p q :=
fun U hU _ hr ↦ ⟨U, Subset.rfl, h U hU, hr⟩
theorem mono {p' q' : Set α → Prop} (H : InnerRegularWRT μ p q)
(h : ∀ s, q' s → q s) (h' : ∀ s, p s → p' s) : InnerRegularWRT μ p' q' :=
of_imp h' |>.trans H |>.trans (of_imp h)
end InnerRegularWRT
variable {α β : Type*} [MeasurableSpace α] {μ : Measure α}
section Classes
variable [TopologicalSpace α]
/-- A measure `μ` is outer regular if `μ(A) = inf {μ(U) | A ⊆ U open}` for a measurable set `A`.
This definition implies the same equality for any (not necessarily measurable) set, see
`Set.measure_eq_iInf_isOpen`. -/
class OuterRegular (μ : Measure α) : Prop where
protected outerRegular :
∀ ⦃A : Set α⦄, MeasurableSet A → ∀ r > μ A, ∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < r
/-- A measure `μ` is regular if
- it is finite on all compact sets;
- it is outer regular: `μ(A) = inf {μ(U) | A ⊆ U open}` for `A` measurable;
- it is inner regular for open sets, using compact sets:
`μ(U) = sup {μ(K) | K ⊆ U compact}` for `U` open. -/
class Regular (μ : Measure α) : Prop extends IsFiniteMeasureOnCompacts μ, OuterRegular μ where
innerRegular : InnerRegularWRT μ IsCompact IsOpen
/-- A measure `μ` is weakly regular if
- it is outer regular: `μ(A) = inf {μ(U) | A ⊆ U open}` for `A` measurable;
- it is inner regular for open sets, using closed sets:
`μ(U) = sup {μ(F) | F ⊆ U closed}` for `U` open. -/
class WeaklyRegular (μ : Measure α) : Prop extends OuterRegular μ where
protected innerRegular : InnerRegularWRT μ IsClosed IsOpen
/-- A measure `μ` is inner regular if, for any measurable set `s`, then
`μ(s) = sup {μ(K) | K ⊆ s compact}`. -/
class InnerRegular (μ : Measure α) : Prop where
protected innerRegular : InnerRegularWRT μ IsCompact MeasurableSet
/-- A measure `μ` is inner regular for finite measure sets with respect to compact sets:
for any measurable set `s` with finite measure, then `μ(s) = sup {μ(K) | K ⊆ s compact}`.
The main interest of this class is that it is satisfied for both natural Haar measures (the
regular one and the inner regular one). -/
class InnerRegularCompactLTTop (μ : Measure α) : Prop where
protected innerRegular : InnerRegularWRT μ IsCompact (fun s ↦ MeasurableSet s ∧ μ s ≠ ∞)
-- see Note [lower instance priority]
/-- A regular measure is weakly regular in an R₁ space. -/
instance (priority := 100) Regular.weaklyRegular [R1Space α] [Regular μ] :
WeaklyRegular μ where
innerRegular := fun _U hU r hr ↦
let ⟨K, KU, K_comp, hK⟩ := Regular.innerRegular hU r hr
⟨closure K, K_comp.closure_subset_of_isOpen hU KU, isClosed_closure,
hK.trans_le (measure_mono subset_closure)⟩
end Classes
namespace OuterRegular
variable [TopologicalSpace α]
instance zero : OuterRegular (0 : Measure α) :=
⟨fun A _ _r hr => ⟨univ, subset_univ A, isOpen_univ, hr⟩⟩
/-- Given `r` larger than the measure of a set `A`, there exists an open superset of `A` with
measure less than `r`. -/
theorem _root_.Set.exists_isOpen_lt_of_lt [OuterRegular μ] (A : Set α) (r : ℝ≥0∞) (hr : μ A < r) :
∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < r := by
rcases OuterRegular.outerRegular (measurableSet_toMeasurable μ A) r
(by rwa [measure_toMeasurable]) with
⟨U, hAU, hUo, hU⟩
exact ⟨U, (subset_toMeasurable _ _).trans hAU, hUo, hU⟩
/-- For an outer regular measure, the measure of a set is the infimum of the measures of open sets
containing it. -/
theorem _root_.Set.measure_eq_iInf_isOpen (A : Set α) (μ : Measure α) [OuterRegular μ] :
μ A = ⨅ (U : Set α) (_ : A ⊆ U) (_ : IsOpen U), μ U := by
refine le_antisymm (le_iInf₂ fun s hs => le_iInf fun _ => μ.mono hs) ?_
refine le_of_forall_lt' fun r hr => ?_
simpa only [iInf_lt_iff, exists_prop] using A.exists_isOpen_lt_of_lt r hr
| theorem _root_.Set.exists_isOpen_lt_add [OuterRegular μ] (A : Set α) (hA : μ A ≠ ∞) {ε : ℝ≥0∞}
(hε : ε ≠ 0) : ∃ U, U ⊇ A ∧ IsOpen U ∧ μ U < μ A + ε :=
A.exists_isOpen_lt_of_lt _ (ENNReal.lt_add_right hA hε)
theorem _root_.Set.exists_isOpen_le_add (A : Set α) (μ : Measure α) [OuterRegular μ] {ε : ℝ≥0∞}
| Mathlib/MeasureTheory/Measure/Regular.lean | 349 | 353 |
/-
Copyright (c) 2024 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.MvPolynomial.Equiv
import Mathlib.LinearAlgebra.Matrix.Charpoly.Coeff
import Mathlib.RingTheory.MvPolynomial.Homogeneous
/-!
# The universal characteristic polynomial
In this file we define the universal characteristic polynomial `Matrix.charpoly.univ`,
which is the charactistic polynomial of the matrix with entries `Xᵢⱼ`,
and hence has coefficients that are multivariate polynomials.
It is universal in the sense that one obtains the characteristic polynomial of a matrix `M`
by evaluating the coefficients of `univ` at the entries of `M`.
We use it to show that the coefficients of the characteristic polynomial
of a matrix are homogeneous polynomials in the matrix entries.
## Main results
* `Matrix.charpoly.univ`: the universal characteristic polynomial
* `Matrix.charpoly.univ_map_eval₂Hom`: evaluating `univ` on the entries of a matrix `M`
gives the characteristic polynomial of `M`.
* `Matrix.charpoly.univ_coeff_isHomogeneous`:
the `i`-th coefficient of `univ` is a homogeneous polynomial of degree `n - i`.
-/
namespace Matrix.charpoly
variable {R S : Type*} (n : Type*) [CommRing R] [CommRing S] [Fintype n] [DecidableEq n]
variable (f : R →+* S)
variable (R) in
/-- The universal characteristic polynomial for `n × n`-matrices,
is the charactistic polynomial of `Matrix.mvPolynomialX n n ℤ` with entries `Xᵢⱼ`.
Its `i`-th coefficient is a homogeneous polynomial of degree `n - i`,
see `Matrix.charpoly.univ_coeff_isHomogeneous`.
By evaluating the coefficients at the entries of a matrix `M`,
one obtains the characteristic polynomial of `M`,
see `Matrix.charpoly.univ_map_eval₂Hom`. -/
noncomputable
abbrev univ : Polynomial (MvPolynomial (n × n) R) :=
charpoly <| mvPolynomialX n n R
open MvPolynomial RingHomClass in
@[simp]
lemma univ_map_eval₂Hom (M : n × n → S) :
| (univ R n).map (eval₂Hom f M) = charpoly (Matrix.of M.curry) := by
rw [univ, ← charpoly_map, coe_eval₂Hom, ← mvPolynomialX_map_eval₂ f (Matrix.of M.curry)]
simp only [of_apply, Function.curry_apply, Prod.mk.eta]
lemma univ_map_map :
| Mathlib/LinearAlgebra/Matrix/Charpoly/Univ.lean | 54 | 58 |
/-
Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn
-/
import Mathlib.Data.Fin.VecNotation
import Mathlib.SetTheory.Cardinal.Basic
/-!
# Basics on First-Order Structures
This file defines first-order languages and structures in the style of the
[Flypitch project](https://flypitch.github.io/), as well as several important maps between
structures.
## Main Definitions
- A `FirstOrder.Language` defines a language as a pair of functions from the natural numbers to
`Type l`. One sends `n` to the type of `n`-ary functions, and the other sends `n` to the type of
`n`-ary relations.
- A `FirstOrder.Language.Structure` interprets the symbols of a given `FirstOrder.Language` in the
context of a given type.
- A `FirstOrder.Language.Hom`, denoted `M →[L] N`, is a map from the `L`-structure `M` to the
`L`-structure `N` that commutes with the interpretations of functions, and which preserves the
interpretations of relations (although only in the forward direction).
- A `FirstOrder.Language.Embedding`, denoted `M ↪[L] N`, is an embedding from the `L`-structure `M`
to the `L`-structure `N` that commutes with the interpretations of functions, and which preserves
the interpretations of relations in both directions.
- A `FirstOrder.Language.Equiv`, denoted `M ≃[L] N`, is an equivalence from the `L`-structure `M`
to the `L`-structure `N` that commutes with the interpretations of functions, and which preserves
the interpretations of relations in both directions.
## References
For the Flypitch project:
- [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*]
[flypitch_cpp]
- [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of
the continuum hypothesis*][flypitch_itp]
-/
universe u v u' v' w w'
open Cardinal
namespace FirstOrder
/-! ### Languages and Structures -/
-- intended to be used with explicit universe parameters
/-- A first-order language consists of a type of functions of every natural-number arity and a
type of relations of every natural-number arity. -/
@[nolint checkUnivs]
structure Language where
/-- For every arity, a `Type*` of functions of that arity -/
Functions : ℕ → Type u
/-- For every arity, a `Type*` of relations of that arity -/
Relations : ℕ → Type v
namespace Language
variable (L : Language.{u, v})
/-- A language is relational when it has no function symbols. -/
abbrev IsRelational : Prop := ∀ n, IsEmpty (L.Functions n)
/-- A language is algebraic when it has no relation symbols. -/
abbrev IsAlgebraic : Prop := ∀ n, IsEmpty (L.Relations n)
/-- The empty language has no symbols. -/
protected def empty : Language :=
⟨fun _ => Empty, fun _ => Empty⟩
deriving IsAlgebraic, IsRelational
instance : Inhabited Language :=
⟨Language.empty⟩
/-- The sum of two languages consists of the disjoint union of their symbols. -/
protected def sum (L' : Language.{u', v'}) : Language :=
⟨fun n => L.Functions n ⊕ L'.Functions n, fun n => L.Relations n ⊕ L'.Relations n⟩
/-- The type of constants in a given language. -/
protected abbrev Constants :=
L.Functions 0
/-- The type of symbols in a given language. -/
abbrev Symbols :=
(Σ l, L.Functions l) ⊕ (Σ l, L.Relations l)
/-- The cardinality of a language is the cardinality of its type of symbols. -/
def card : Cardinal :=
#L.Symbols
variable {L} {L' : Language.{u', v'}}
theorem card_eq_card_functions_add_card_relations :
L.card =
(Cardinal.sum fun l => Cardinal.lift.{v} #(L.Functions l)) +
Cardinal.sum fun l => Cardinal.lift.{u} #(L.Relations l) := by
simp only [card, mk_sum, mk_sigma, lift_sum]
instance isRelational_sum [L.IsRelational] [L'.IsRelational] : IsRelational (L.sum L') :=
fun _ => instIsEmptySum
instance isAlgebraic_sum [L.IsAlgebraic] [L'.IsAlgebraic] : IsAlgebraic (L.sum L') :=
fun _ => instIsEmptySum
@[simp]
theorem card_empty : Language.empty.card = 0 := by simp only [card, mk_sum, mk_sigma, mk_eq_zero,
sum_const, mk_eq_aleph0, lift_id', mul_zero, add_zero]
@[deprecated (since := "2025-02-05")] alias empty_card := card_empty
instance isEmpty_empty : IsEmpty Language.empty.Symbols := by
simp only [Language.Symbols, isEmpty_sum, isEmpty_sigma]
exact ⟨fun _ => inferInstance, fun _ => inferInstance⟩
instance Countable.countable_functions [h : Countable L.Symbols] : Countable (Σl, L.Functions l) :=
@Function.Injective.countable _ _ h _ Sum.inl_injective
@[simp]
theorem card_functions_sum (i : ℕ) :
#((L.sum L').Functions i)
= (Cardinal.lift.{u'} #(L.Functions i) + Cardinal.lift.{u} #(L'.Functions i) : Cardinal) := by
simp [Language.sum]
@[simp]
theorem card_relations_sum (i : ℕ) :
#((L.sum L').Relations i) =
Cardinal.lift.{v'} #(L.Relations i) + Cardinal.lift.{v} #(L'.Relations i) := by
simp [Language.sum]
theorem card_sum :
(L.sum L').card = Cardinal.lift.{max u' v'} L.card + Cardinal.lift.{max u v} L'.card := by
simp only [card, mk_sum, mk_sigma, card_functions_sum, sum_add_distrib', lift_add, lift_sum,
lift_lift, card_relations_sum, add_assoc,
add_comm (Cardinal.sum fun i => (#(L'.Functions i)).lift)]
/-- Passes a `DecidableEq` instance on a type of function symbols through the `Language`
constructor. Despite the fact that this is proven by `inferInstance`, it is still needed -
see the `example`s in `ModelTheory/Ring/Basic`. -/
instance instDecidableEqFunctions {f : ℕ → Type*} {R : ℕ → Type*} (n : ℕ) [DecidableEq (f n)] :
DecidableEq ((⟨f, R⟩ : Language).Functions n) := inferInstance
/-- Passes a `DecidableEq` instance on a type of relation symbols through the `Language`
constructor. Despite the fact that this is proven by `inferInstance`, it is still needed -
see the `example`s in `ModelTheory/Ring/Basic`. -/
instance instDecidableEqRelations {f : ℕ → Type*} {R : ℕ → Type*} (n : ℕ) [DecidableEq (R n)] :
DecidableEq ((⟨f, R⟩ : Language).Relations n) := inferInstance
variable (L) (M : Type w)
/-- A first-order structure on a type `M` consists of interpretations of all the symbols in a given
language. Each function of arity `n` is interpreted as a function sending tuples of length `n`
(modeled as `(Fin n → M)`) to `M`, and a relation of arity `n` is a function from tuples of length
`n` to `Prop`. -/
@[ext]
class Structure where
/-- Interpretation of the function symbols -/
funMap : ∀ {n}, L.Functions n → (Fin n → M) → M := by
exact fun {n} => isEmptyElim
/-- Interpretation of the relation symbols -/
RelMap : ∀ {n}, L.Relations n → (Fin n → M) → Prop := by
exact fun {n} => isEmptyElim
variable (N : Type w') [L.Structure M] [L.Structure N]
| open Structure
/-- Used for defining `FirstOrder.Language.Theory.ModelType.instInhabited`. -/
def Inhabited.trivialStructure {α : Type*} [Inhabited α] : L.Structure α :=
⟨default, default⟩
| Mathlib/ModelTheory/Basic.lean | 169 | 173 |
/-
Copyright (c) 2021 Vladimir Goryachev. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Vladimir Goryachev, Kyle Miller, Kim Morrison, Eric Rodriguez
-/
import Mathlib.Data.List.GetD
import Mathlib.Data.Nat.Count
import Mathlib.Data.Nat.SuccPred
import Mathlib.Order.Interval.Set.Monotone
import Mathlib.Order.OrderIsoNat
import Mathlib.Order.WellFounded
import Mathlib.Order.OmegaCompletePartialOrder
import Mathlib.Data.Finset.Sort
/-!
# The `n`th Number Satisfying a Predicate
This file defines a function for "what is the `n`th number that satisfies a given predicate `p`",
and provides lemmas that deal with this function and its connection to `Nat.count`.
## Main definitions
* `Nat.nth p n`: The `n`-th natural `k` (zero-indexed) such that `p k`. If there is no
such natural (that is, `p` is true for at most `n` naturals), then `Nat.nth p n = 0`.
## Main results
* `Nat.nth_eq_orderEmbOfFin`: For a finitely-often true `p`, gives the cardinality of the set of
numbers satisfying `p` above particular values of `nth p`
* `Nat.gc_count_nth`: Establishes a Galois connection between `Nat.nth p` and `Nat.count p`.
* `Nat.nth_eq_orderIsoOfNat`: For an infinitely-often true predicate, `nth` agrees with the
order-isomorphism of the subtype to the natural numbers.
There has been some discussion on the subject of whether both of `nth` and
`Nat.Subtype.orderIsoOfNat` should exist. See discussion
[here](https://github.com/leanprover-community/mathlib/pull/9457#pullrequestreview-767221180).
Future work should address how lemmas that use these should be written.
-/
open Finset
namespace Nat
variable (p : ℕ → Prop)
/-- Find the `n`-th natural number satisfying `p` (indexed from `0`, so `nth p 0` is the first
natural number satisfying `p`), or `0` if there is no such number. See also
`Subtype.orderIsoOfNat` for the order isomorphism with ℕ when `p` is infinitely often true. -/
noncomputable def nth (p : ℕ → Prop) (n : ℕ) : ℕ := by
classical exact
if h : Set.Finite (setOf p) then (h.toFinset.sort (· ≤ ·)).getD n 0
else @Nat.Subtype.orderIsoOfNat (setOf p) (Set.Infinite.to_subtype h) n
variable {p}
/-!
### Lemmas about `Nat.nth` on a finite set
-/
theorem nth_of_card_le (hf : (setOf p).Finite) {n : ℕ} (hn : #hf.toFinset ≤ n) :
nth p n = 0 := by rw [nth, dif_pos hf, List.getD_eq_default]; rwa [Finset.length_sort]
theorem nth_eq_getD_sort (h : (setOf p).Finite) (n : ℕ) :
nth p n = (h.toFinset.sort (· ≤ ·)).getD n 0 :=
dif_pos h
theorem nth_eq_orderEmbOfFin (hf : (setOf p).Finite) {n : ℕ} (hn : n < #hf.toFinset) :
nth p n = hf.toFinset.orderEmbOfFin rfl ⟨n, hn⟩ := by
rw [nth_eq_getD_sort hf, Finset.orderEmbOfFin_apply, List.getD_eq_getElem, Fin.getElem_fin]
theorem nth_strictMonoOn (hf : (setOf p).Finite) :
StrictMonoOn (nth p) (Set.Iio #hf.toFinset) := by
rintro m (hm : m < _) n (hn : n < _) h
simp only [nth_eq_orderEmbOfFin, *]
exact OrderEmbedding.strictMono _ h
theorem nth_lt_nth_of_lt_card (hf : (setOf p).Finite) {m n : ℕ} (h : m < n)
(hn : n < #hf.toFinset) : nth p m < nth p n :=
nth_strictMonoOn hf (h.trans hn) hn h
theorem nth_le_nth_of_lt_card (hf : (setOf p).Finite) {m n : ℕ} (h : m ≤ n)
(hn : n < #hf.toFinset) : nth p m ≤ nth p n :=
(nth_strictMonoOn hf).monotoneOn (h.trans_lt hn) hn h
theorem lt_of_nth_lt_nth_of_lt_card (hf : (setOf p).Finite) {m n : ℕ} (h : nth p m < nth p n)
(hm : m < #hf.toFinset) : m < n :=
not_le.1 fun hle => h.not_le <| nth_le_nth_of_lt_card hf hle hm
theorem le_of_nth_le_nth_of_lt_card (hf : (setOf p).Finite) {m n : ℕ} (h : nth p m ≤ nth p n)
(hm : m < #hf.toFinset) : m ≤ n :=
not_lt.1 fun hlt => h.not_lt <| nth_lt_nth_of_lt_card hf hlt hm
theorem nth_injOn (hf : (setOf p).Finite) : (Set.Iio #hf.toFinset).InjOn (nth p) :=
(nth_strictMonoOn hf).injOn
theorem range_nth_of_finite (hf : (setOf p).Finite) : Set.range (nth p) = insert 0 (setOf p) := by
simpa only [← List.getD_eq_getElem?_getD, ← nth_eq_getD_sort hf, mem_sort,
Set.Finite.mem_toFinset] using Set.range_list_getD (hf.toFinset.sort (· ≤ ·)) 0
@[simp]
theorem image_nth_Iio_card (hf : (setOf p).Finite) : nth p '' Set.Iio #hf.toFinset = setOf p :=
calc
nth p '' Set.Iio #hf.toFinset = Set.range (hf.toFinset.orderEmbOfFin rfl) := by
ext x
simp only [Set.mem_image, Set.mem_range, Fin.exists_iff, ← nth_eq_orderEmbOfFin hf,
Set.mem_Iio, exists_prop]
_ = setOf p := by rw [range_orderEmbOfFin, Set.Finite.coe_toFinset]
theorem nth_mem_of_lt_card {n : ℕ} (hf : (setOf p).Finite) (hlt : n < #hf.toFinset) :
p (nth p n) :=
(image_nth_Iio_card hf).subset <| Set.mem_image_of_mem _ hlt
theorem exists_lt_card_finite_nth_eq (hf : (setOf p).Finite) {x} (h : p x) :
∃ n, n < #hf.toFinset ∧ nth p n = x := by
rwa [← @Set.mem_setOf_eq _ _ p, ← image_nth_Iio_card hf] at h
/-!
### Lemmas about `Nat.nth` on an infinite set
-/
/-- When `s` is an infinite set, `nth` agrees with `Nat.Subtype.orderIsoOfNat`. -/
theorem nth_apply_eq_orderIsoOfNat (hf : (setOf p).Infinite) (n : ℕ) :
nth p n = @Nat.Subtype.orderIsoOfNat (setOf p) hf.to_subtype n := by rw [nth, dif_neg hf]
/-- When `s` is an infinite set, `nth` agrees with `Nat.Subtype.orderIsoOfNat`. -/
theorem nth_eq_orderIsoOfNat (hf : (setOf p).Infinite) :
nth p = (↑) ∘ @Nat.Subtype.orderIsoOfNat (setOf p) hf.to_subtype :=
funext <| nth_apply_eq_orderIsoOfNat hf
theorem nth_strictMono (hf : (setOf p).Infinite) : StrictMono (nth p) := by
rw [nth_eq_orderIsoOfNat hf]
exact (Subtype.strictMono_coe _).comp (OrderIso.strictMono _)
theorem nth_injective (hf : (setOf p).Infinite) : Function.Injective (nth p) :=
(nth_strictMono hf).injective
theorem nth_monotone (hf : (setOf p).Infinite) : Monotone (nth p) :=
(nth_strictMono hf).monotone
theorem nth_lt_nth (hf : (setOf p).Infinite) {k n} : nth p k < nth p n ↔ k < n :=
(nth_strictMono hf).lt_iff_lt
theorem nth_le_nth (hf : (setOf p).Infinite) {k n} : nth p k ≤ nth p n ↔ k ≤ n :=
(nth_strictMono hf).le_iff_le
theorem range_nth_of_infinite (hf : (setOf p).Infinite) : Set.range (nth p) = setOf p := by
rw [nth_eq_orderIsoOfNat hf]
haveI := hf.to_subtype
classical exact Nat.Subtype.coe_comp_ofNat_range
theorem nth_mem_of_infinite (hf : (setOf p).Infinite) (n : ℕ) : p (nth p n) :=
Set.range_subset_iff.1 (range_nth_of_infinite hf).le n
/-!
### Lemmas that work for finite and infinite sets
-/
theorem exists_lt_card_nth_eq {x} (h : p x) :
∃ n, (∀ hf : (setOf p).Finite, n < #hf.toFinset) ∧ nth p n = x := by
refine (setOf p).finite_or_infinite.elim (fun hf => ?_) fun hf => ?_
· rcases exists_lt_card_finite_nth_eq hf h with ⟨n, hn, hx⟩
exact ⟨n, fun _ => hn, hx⟩
· rw [← @Set.mem_setOf_eq _ _ p, ← range_nth_of_infinite hf] at h
rcases h with ⟨n, hx⟩
exact ⟨n, fun hf' => absurd hf' hf, hx⟩
theorem subset_range_nth : setOf p ⊆ Set.range (nth p) := fun x (hx : p x) =>
let ⟨n, _, hn⟩ := exists_lt_card_nth_eq hx
⟨n, hn⟩
theorem range_nth_subset : Set.range (nth p) ⊆ insert 0 (setOf p) :=
(setOf p).finite_or_infinite.elim (fun h => (range_nth_of_finite h).subset) fun h =>
(range_nth_of_infinite h).trans_subset (Set.subset_insert _ _)
theorem nth_mem (n : ℕ) (h : ∀ hf : (setOf p).Finite, n < #hf.toFinset) : p (nth p n) :=
(setOf p).finite_or_infinite.elim (fun hf => nth_mem_of_lt_card hf (h hf)) fun h =>
nth_mem_of_infinite h n
theorem nth_lt_nth' {m n : ℕ} (hlt : m < n) (h : ∀ hf : (setOf p).Finite, n < #hf.toFinset) :
nth p m < nth p n :=
(setOf p).finite_or_infinite.elim (fun hf => nth_lt_nth_of_lt_card hf hlt (h _)) fun hf =>
(nth_lt_nth hf).2 hlt
theorem nth_le_nth' {m n : ℕ} (hle : m ≤ n) (h : ∀ hf : (setOf p).Finite, n < #hf.toFinset) :
nth p m ≤ nth p n :=
(setOf p).finite_or_infinite.elim (fun hf => nth_le_nth_of_lt_card hf hle (h _)) fun hf =>
(nth_le_nth hf).2 hle
theorem le_nth {n : ℕ} (h : ∀ hf : (setOf p).Finite, n < #hf.toFinset) : n ≤ nth p n :=
(setOf p).finite_or_infinite.elim
(fun hf => ((nth_strictMonoOn hf).mono <| Set.Iic_subset_Iio.2 (h _)).Iic_id_le _ le_rfl)
fun hf => (nth_strictMono hf).id_le _
theorem isLeast_nth {n} (h : ∀ hf : (setOf p).Finite, n < #hf.toFinset) :
IsLeast {i | p i ∧ ∀ k < n, nth p k < i} (nth p n) :=
⟨⟨nth_mem n h, fun _k hk => nth_lt_nth' hk h⟩, fun _x hx =>
let ⟨k, hk, hkx⟩ := exists_lt_card_nth_eq hx.1
(lt_or_le k n).elim (fun hlt => absurd hkx (hx.2 _ hlt).ne) fun hle => hkx ▸ nth_le_nth' hle hk⟩
theorem isLeast_nth_of_lt_card {n : ℕ} (hf : (setOf p).Finite) (hn : n < #hf.toFinset) :
IsLeast {i | p i ∧ ∀ k < n, nth p k < i} (nth p n) :=
isLeast_nth fun _ => hn
theorem isLeast_nth_of_infinite (hf : (setOf p).Infinite) (n : ℕ) :
IsLeast {i | p i ∧ ∀ k < n, nth p k < i} (nth p n) :=
isLeast_nth fun h => absurd h hf
/-- An alternative recursive definition of `Nat.nth`: `Nat.nth s n` is the infimum of `x ∈ s` such
that `Nat.nth s k < x` for all `k < n`, if this set is nonempty. We do not assume that the set is
nonempty because we use the same "garbage value" `0` both for `sInf` on `ℕ` and for `Nat.nth s n`
for `n ≥ #s`. -/
theorem nth_eq_sInf (p : ℕ → Prop) (n : ℕ) : nth p n = sInf {x | p x ∧ ∀ k < n, nth p k < x} := by
by_cases hn : ∀ hf : (setOf p).Finite, n < #hf.toFinset
· exact (isLeast_nth hn).csInf_eq.symm
· push_neg at hn
rcases hn with ⟨hf, hn⟩
rw [nth_of_card_le _ hn]
refine ((congr_arg sInf <| Set.eq_empty_of_forall_not_mem fun k hk => ?_).trans sInf_empty).symm
rcases exists_lt_card_nth_eq hk.1 with ⟨k, hlt, rfl⟩
exact (hk.2 _ ((hlt hf).trans_le hn)).false
theorem nth_zero : nth p 0 = sInf (setOf p) := by rw [nth_eq_sInf]; simp
@[simp]
theorem nth_zero_of_zero (h : p 0) : nth p 0 = 0 := by simp [nth_zero, h]
theorem nth_zero_of_exists [DecidablePred p] (h : ∃ n, p n) : nth p 0 = Nat.find h := by
rw [nth_zero]; convert Nat.sInf_def h
theorem nth_eq_zero {n} :
nth p n = 0 ↔ p 0 ∧ n = 0 ∨ ∃ hf : (setOf p).Finite, #hf.toFinset ≤ n := by
refine ⟨fun h => ?_, ?_⟩
· simp only [or_iff_not_imp_right, not_exists, not_le]
exact fun hn => ⟨h ▸ nth_mem _ hn, nonpos_iff_eq_zero.1 <| h ▸ le_nth hn⟩
· rintro (⟨h₀, rfl⟩ | ⟨hf, hle⟩)
exacts [nth_zero_of_zero h₀, nth_of_card_le hf hle]
lemma lt_card_toFinset_of_nth_ne_zero {n : ℕ} (h : nth p n ≠ 0) (hf : (setOf p).Finite) :
n < #hf.toFinset := by
simp only [ne_eq, nth_eq_zero, not_or, not_exists, not_le] at h
exact h.2 hf
lemma nth_mem_of_ne_zero {n : ℕ} (h : nth p n ≠ 0) : p (Nat.nth p n) :=
| nth_mem n (lt_card_toFinset_of_nth_ne_zero h)
theorem nth_eq_zero_mono (h₀ : ¬p 0) {a b : ℕ} (hab : a ≤ b) (ha : nth p a = 0) : nth p b = 0 := by
simp only [nth_eq_zero, h₀, false_and, false_or] at ha ⊢
exact ha.imp fun hf hle => hle.trans hab
lemma nth_ne_zero_anti (h₀ : ¬p 0) {a b : ℕ} (hab : a ≤ b) (hb : nth p b ≠ 0) : nth p a ≠ 0 :=
mt (nth_eq_zero_mono h₀ hab) hb
| Mathlib/Data/Nat/Nth.lean | 247 | 255 |
/-
Copyright (c) 2020 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Logic.IsEmpty
import Mathlib.Order.Basic
import Mathlib.Tactic.MkIffOfInductiveProp
import Batteries.WF
/-!
# Unbundled relation classes
In this file we prove some properties of `Is*` classes defined in `Mathlib.Order.Defs`. The main
difference between these classes and the usual order classes (`Preorder` etc) is that usual classes
extend `LE` and/or `LT` while these classes take a relation as an explicit argument.
-/
universe u v
variable {α : Type u} {β : Type v} {r : α → α → Prop} {s : β → β → Prop}
open Function
theorem IsRefl.swap (r) [IsRefl α r] : IsRefl α (swap r) :=
⟨refl_of r⟩
theorem IsIrrefl.swap (r) [IsIrrefl α r] : IsIrrefl α (swap r) :=
⟨irrefl_of r⟩
theorem IsTrans.swap (r) [IsTrans α r] : IsTrans α (swap r) :=
⟨fun _ _ _ h₁ h₂ => trans_of r h₂ h₁⟩
theorem IsAntisymm.swap (r) [IsAntisymm α r] : IsAntisymm α (swap r) :=
⟨fun _ _ h₁ h₂ => _root_.antisymm h₂ h₁⟩
theorem IsAsymm.swap (r) [IsAsymm α r] : IsAsymm α (swap r) :=
⟨fun _ _ h₁ h₂ => asymm_of r h₂ h₁⟩
theorem IsTotal.swap (r) [IsTotal α r] : IsTotal α (swap r) :=
⟨fun a b => (total_of r a b).symm⟩
theorem IsTrichotomous.swap (r) [IsTrichotomous α r] : IsTrichotomous α (swap r) :=
⟨fun a b => by simpa [Function.swap, or_comm, or_left_comm] using trichotomous_of r a b⟩
theorem IsPreorder.swap (r) [IsPreorder α r] : IsPreorder α (swap r) :=
{ @IsRefl.swap α r _, @IsTrans.swap α r _ with }
theorem IsStrictOrder.swap (r) [IsStrictOrder α r] : IsStrictOrder α (swap r) :=
{ @IsIrrefl.swap α r _, @IsTrans.swap α r _ with }
theorem IsPartialOrder.swap (r) [IsPartialOrder α r] : IsPartialOrder α (swap r) :=
{ @IsPreorder.swap α r _, @IsAntisymm.swap α r _ with }
theorem eq_empty_relation (r) [IsIrrefl α r] [Subsingleton α] : r = EmptyRelation :=
funext₂ <| by simpa using not_rel_of_subsingleton r
/-- Construct a partial order from an `isStrictOrder` relation.
See note [reducible non-instances]. -/
abbrev partialOrderOfSO (r) [IsStrictOrder α r] : PartialOrder α where
le x y := x = y ∨ r x y
lt := r
le_refl _ := Or.inl rfl
le_trans x y z h₁ h₂ :=
match y, z, h₁, h₂ with
| _, _, Or.inl rfl, h₂ => h₂
| _, _, h₁, Or.inl rfl => h₁
| _, _, Or.inr h₁, Or.inr h₂ => Or.inr (_root_.trans h₁ h₂)
le_antisymm x y h₁ h₂ :=
match y, h₁, h₂ with
| _, Or.inl rfl, _ => rfl
| _, _, Or.inl rfl => rfl
| _, Or.inr h₁, Or.inr h₂ => (asymm h₁ h₂).elim
lt_iff_le_not_le x y :=
⟨fun h => ⟨Or.inr h, not_or_intro (fun e => by rw [e] at h; exact irrefl _ h) (asymm h)⟩,
fun ⟨h₁, h₂⟩ => h₁.resolve_left fun e => h₂ <| e ▸ Or.inl rfl⟩
/-- Construct a linear order from an `IsStrictTotalOrder` relation.
See note [reducible non-instances]. -/
abbrev linearOrderOfSTO (r) [IsStrictTotalOrder α r] [DecidableRel r] : LinearOrder α :=
let hD : DecidableRel (fun x y => x = y ∨ r x y) := fun x y => decidable_of_iff (¬r y x)
⟨fun h => ((trichotomous_of r y x).resolve_left h).imp Eq.symm id, fun h =>
h.elim (fun h => h ▸ irrefl_of _ _) (asymm_of r)⟩
{ __ := partialOrderOfSO r
le_total := fun x y =>
match y, trichotomous_of r x y with
| _, Or.inl h => Or.inl (Or.inr h)
| _, Or.inr (Or.inl rfl) => Or.inl (Or.inl rfl)
| _, Or.inr (Or.inr h) => Or.inr (Or.inr h),
toMin := minOfLe,
toMax := maxOfLe,
toDecidableLE := hD }
theorem IsStrictTotalOrder.swap (r) [IsStrictTotalOrder α r] : IsStrictTotalOrder α (swap r) :=
{ IsTrichotomous.swap r, IsStrictOrder.swap r with }
/-! ### Order connection -/
/-- A connected order is one satisfying the condition `a < c → a < b ∨ b < c`.
This is recognizable as an intuitionistic substitute for `a ≤ b ∨ b ≤ a` on
the constructive reals, and is also known as negative transitivity,
since the contrapositive asserts transitivity of the relation `¬ a < b`. -/
class IsOrderConnected (α : Type u) (lt : α → α → Prop) : Prop where
/-- A connected order is one satisfying the condition `a < c → a < b ∨ b < c`. -/
conn : ∀ a b c, lt a c → lt a b ∨ lt b c
theorem IsOrderConnected.neg_trans {r : α → α → Prop} [IsOrderConnected α r] {a b c}
(h₁ : ¬r a b) (h₂ : ¬r b c) : ¬r a c :=
mt (IsOrderConnected.conn a b c) <| by simp [h₁, h₂]
theorem isStrictWeakOrder_of_isOrderConnected [IsAsymm α r] [IsOrderConnected α r] :
IsStrictWeakOrder α r :=
{ @IsAsymm.isIrrefl α r _ with
trans := fun _ _ c h₁ h₂ => (IsOrderConnected.conn _ c _ h₁).resolve_right (asymm h₂),
incomp_trans := fun _ _ _ ⟨h₁, h₂⟩ ⟨h₃, h₄⟩ =>
⟨IsOrderConnected.neg_trans h₁ h₃, IsOrderConnected.neg_trans h₄ h₂⟩ }
-- see Note [lower instance priority]
instance (priority := 100) isStrictOrderConnected_of_isStrictTotalOrder [IsStrictTotalOrder α r] :
IsOrderConnected α r :=
⟨fun _ _ _ h ↦ (trichotomous _ _).imp_right
fun o ↦ o.elim (fun e ↦ e ▸ h) fun h' ↦ _root_.trans h' h⟩
/-! ### Inverse Image -/
theorem InvImage.isTrichotomous [IsTrichotomous α r] {f : β → α} (h : Function.Injective f) :
IsTrichotomous β (InvImage r f) where
trichotomous a b := trichotomous (f a) (f b) |>.imp3 id (h ·) id
instance InvImage.isAsymm [IsAsymm α r] (f : β → α) : IsAsymm β (InvImage r f) where
asymm a b h h2 := IsAsymm.asymm (f a) (f b) h h2
/-! ### Well-order -/
/-- A well-founded relation. Not to be confused with `IsWellOrder`. -/
@[mk_iff] class IsWellFounded (α : Type u) (r : α → α → Prop) : Prop where
/-- The relation is `WellFounded`, as a proposition. -/
wf : WellFounded r
instance WellFoundedRelation.isWellFounded [h : WellFoundedRelation α] :
IsWellFounded α WellFoundedRelation.rel :=
{ h with }
theorem WellFoundedRelation.asymmetric {α : Sort*} [WellFoundedRelation α] {a b : α} :
WellFoundedRelation.rel a b → ¬ WellFoundedRelation.rel b a :=
fun hab hba => WellFoundedRelation.asymmetric hba hab
termination_by a
theorem WellFoundedRelation.asymmetric₃ {α : Sort*} [WellFoundedRelation α] {a b c : α} :
WellFoundedRelation.rel a b → WellFoundedRelation.rel b c → ¬ WellFoundedRelation.rel c a :=
fun hab hbc hca => WellFoundedRelation.asymmetric₃ hca hab hbc
termination_by a
lemma WellFounded.prod_lex {ra : α → α → Prop} {rb : β → β → Prop} (ha : WellFounded ra)
(hb : WellFounded rb) : WellFounded (Prod.Lex ra rb) :=
(Prod.lex ⟨_, ha⟩ ⟨_, hb⟩).wf
section PSigma
open PSigma
/-- The lexicographical order of well-founded relations is well-founded. -/
theorem WellFounded.psigma_lex
{α : Sort*} {β : α → Sort*} {r : α → α → Prop} {s : ∀ a : α, β a → β a → Prop}
(ha : WellFounded r) (hb : ∀ x, WellFounded (s x)) : WellFounded (Lex r s) :=
WellFounded.intro fun ⟨a, b⟩ => lexAccessible (WellFounded.apply ha a) hb b
theorem WellFounded.psigma_revLex
{α : Sort*} {β : Sort*} {r : α → α → Prop} {s : β → β → Prop}
(ha : WellFounded r) (hb : WellFounded s) : WellFounded (RevLex r s) :=
WellFounded.intro fun ⟨a, b⟩ => revLexAccessible (apply hb b) (WellFounded.apply ha) a
theorem WellFounded.psigma_skipLeft (α : Type u) {β : Type v} {s : β → β → Prop}
(hb : WellFounded s) : WellFounded (SkipLeft α s) :=
psigma_revLex emptyWf.wf hb
end PSigma
namespace IsWellFounded
variable (r) [IsWellFounded α r]
/-- Induction on a well-founded relation. -/
theorem induction {C : α → Prop} (a : α) (ind : ∀ x, (∀ y, r y x → C y) → C x) : C a :=
wf.induction _ ind
/-- All values are accessible under the well-founded relation. -/
theorem apply : ∀ a, Acc r a :=
wf.apply
/-- Creates data, given a way to generate a value from all that compare as less under a well-founded
relation. See also `IsWellFounded.fix_eq`. -/
def fix {C : α → Sort*} : (∀ x : α, (∀ y : α, r y x → C y) → C x) → ∀ x : α, C x :=
wf.fix
/-- The value from `IsWellFounded.fix` is built from the previous ones as specified. -/
theorem fix_eq {C : α → Sort*} (F : ∀ x : α, (∀ y : α, r y x → C y) → C x) :
∀ x, fix r F x = F x fun y _ => fix r F y :=
wf.fix_eq F
/-- Derive a `WellFoundedRelation` instance from an `isWellFounded` instance. -/
def toWellFoundedRelation : WellFoundedRelation α :=
⟨r, IsWellFounded.wf⟩
end IsWellFounded
theorem WellFounded.asymmetric {α : Sort*} {r : α → α → Prop} (h : WellFounded r) (a b) :
r a b → ¬r b a :=
@WellFoundedRelation.asymmetric _ ⟨_, h⟩ _ _
theorem WellFounded.asymmetric₃ {α : Sort*} {r : α → α → Prop} (h : WellFounded r) (a b c) :
r a b → r b c → ¬r c a :=
@WellFoundedRelation.asymmetric₃ _ ⟨_, h⟩ _ _ _
-- see Note [lower instance priority]
instance (priority := 100) (r : α → α → Prop) [IsWellFounded α r] : IsAsymm α r :=
⟨IsWellFounded.wf.asymmetric⟩
-- see Note [lower instance priority]
instance (priority := 100) (r : α → α → Prop) [IsWellFounded α r] : IsIrrefl α r :=
IsAsymm.isIrrefl
instance (r : α → α → Prop) [i : IsWellFounded α r] : IsWellFounded α (Relation.TransGen r) :=
⟨i.wf.transGen⟩
/-- A class for a well founded relation `<`. -/
abbrev WellFoundedLT (α : Type*) [LT α] : Prop :=
IsWellFounded α (· < ·)
/-- A class for a well founded relation `>`. -/
abbrev WellFoundedGT (α : Type*) [LT α] : Prop :=
IsWellFounded α (· > ·)
lemma wellFounded_lt [LT α] [WellFoundedLT α] : @WellFounded α (· < ·) := IsWellFounded.wf
lemma wellFounded_gt [LT α] [WellFoundedGT α] : @WellFounded α (· > ·) := IsWellFounded.wf
-- See note [lower instance priority]
instance (priority := 100) (α : Type*) [LT α] [h : WellFoundedLT α] : WellFoundedGT αᵒᵈ :=
h
-- See note [lower instance priority]
instance (priority := 100) (α : Type*) [LT α] [h : WellFoundedGT α] : WellFoundedLT αᵒᵈ :=
h
theorem wellFoundedGT_dual_iff (α : Type*) [LT α] : WellFoundedGT αᵒᵈ ↔ WellFoundedLT α :=
⟨fun h => ⟨h.wf⟩, fun h => ⟨h.wf⟩⟩
theorem wellFoundedLT_dual_iff (α : Type*) [LT α] : WellFoundedLT αᵒᵈ ↔ WellFoundedGT α :=
⟨fun h => ⟨h.wf⟩, fun h => ⟨h.wf⟩⟩
/-- A well order is a well-founded linear order. -/
class IsWellOrder (α : Type u) (r : α → α → Prop) : Prop
extends IsTrichotomous α r, IsTrans α r, IsWellFounded α r
-- see Note [lower instance priority]
instance (priority := 100) {α} (r : α → α → Prop) [IsWellOrder α r] :
IsStrictTotalOrder α r where
-- see Note [lower instance priority]
instance (priority := 100) {α} (r : α → α → Prop) [IsWellOrder α r] : IsTrichotomous α r := by
infer_instance
-- see Note [lower instance priority]
instance (priority := 100) {α} (r : α → α → Prop) [IsWellOrder α r] : IsTrans α r := by
infer_instance
-- see Note [lower instance priority]
instance (priority := 100) {α} (r : α → α → Prop) [IsWellOrder α r] : IsIrrefl α r := by
infer_instance
-- see Note [lower instance priority]
instance (priority := 100) {α} (r : α → α → Prop) [IsWellOrder α r] : IsAsymm α r := by
infer_instance
namespace WellFoundedLT
variable [LT α] [WellFoundedLT α]
/-- Inducts on a well-founded `<` relation. -/
theorem induction {C : α → Prop} (a : α) (ind : ∀ x, (∀ y, y < x → C y) → C x) : C a :=
IsWellFounded.induction _ _ ind
/-- All values are accessible under the well-founded `<`. -/
theorem apply : ∀ a : α, Acc (· < ·) a :=
IsWellFounded.apply _
/-- Creates data, given a way to generate a value from all that compare as lesser. See also
`WellFoundedLT.fix_eq`. -/
def fix {C : α → Sort*} : (∀ x : α, (∀ y : α, y < x → C y) → C x) → ∀ x : α, C x :=
IsWellFounded.fix (· < ·)
/-- The value from `WellFoundedLT.fix` is built from the previous ones as specified. -/
theorem fix_eq {C : α → Sort*} (F : ∀ x : α, (∀ y : α, y < x → C y) → C x) :
∀ x, fix F x = F x fun y _ => fix F y :=
IsWellFounded.fix_eq _ F
/-- Derive a `WellFoundedRelation` instance from a `WellFoundedLT` instance. -/
def toWellFoundedRelation : WellFoundedRelation α :=
IsWellFounded.toWellFoundedRelation (· < ·)
end WellFoundedLT
namespace WellFoundedGT
variable [LT α] [WellFoundedGT α]
/-- Inducts on a well-founded `>` relation. -/
theorem induction {C : α → Prop} (a : α) (ind : ∀ x, (∀ y, x < y → C y) → C x) : C a :=
IsWellFounded.induction _ _ ind
/-- All values are accessible under the well-founded `>`. -/
theorem apply : ∀ a : α, Acc (· > ·) a :=
IsWellFounded.apply _
/-- Creates data, given a way to generate a value from all that compare as greater. See also
`WellFoundedGT.fix_eq`. -/
def fix {C : α → Sort*} : (∀ x : α, (∀ y : α, x < y → C y) → C x) → ∀ x : α, C x :=
IsWellFounded.fix (· > ·)
/-- The value from `WellFoundedGT.fix` is built from the successive ones as specified. -/
theorem fix_eq {C : α → Sort*} (F : ∀ x : α, (∀ y : α, x < y → C y) → C x) :
∀ x, fix F x = F x fun y _ => fix F y :=
IsWellFounded.fix_eq _ F
/-- Derive a `WellFoundedRelation` instance from a `WellFoundedGT` instance. -/
def toWellFoundedRelation : WellFoundedRelation α :=
IsWellFounded.toWellFoundedRelation (· > ·)
end WellFoundedGT
open Classical in
/-- Construct a decidable linear order from a well-founded linear order. -/
noncomputable def IsWellOrder.linearOrder (r : α → α → Prop) [IsWellOrder α r] : LinearOrder α :=
linearOrderOfSTO r
/-- Derive a `WellFoundedRelation` instance from an `IsWellOrder` instance. -/
def IsWellOrder.toHasWellFounded [LT α] [hwo : IsWellOrder α (· < ·)] : WellFoundedRelation α where
rel := (· < ·)
wf := hwo.wf
-- This isn't made into an instance as it loops with `IsIrrefl α r`.
theorem Subsingleton.isWellOrder [Subsingleton α] (r : α → α → Prop) [hr : IsIrrefl α r] :
IsWellOrder α r :=
{ hr with
trichotomous := fun a b => Or.inr <| Or.inl <| Subsingleton.elim a b,
trans := fun a b _ h => (not_rel_of_subsingleton r a b h).elim,
wf := ⟨fun a => ⟨_, fun y h => (not_rel_of_subsingleton r y a h).elim⟩⟩ }
instance [Subsingleton α] : IsWellOrder α EmptyRelation :=
Subsingleton.isWellOrder _
instance (priority := 100) [IsEmpty α] (r : α → α → Prop) : IsWellOrder α r where
trichotomous := isEmptyElim
trans := isEmptyElim
wf := wellFounded_of_isEmpty r
instance Prod.Lex.instIsWellFounded [IsWellFounded α r] [IsWellFounded β s] :
IsWellFounded (α × β) (Prod.Lex r s) :=
⟨IsWellFounded.wf.prod_lex IsWellFounded.wf⟩
instance [IsWellOrder α r] [IsWellOrder β s] : IsWellOrder (α × β) (Prod.Lex r s) where
trichotomous := fun ⟨a₁, a₂⟩ ⟨b₁, b₂⟩ =>
match @trichotomous _ r _ a₁ b₁ with
| Or.inl h₁ => Or.inl <| Prod.Lex.left _ _ h₁
| Or.inr (Or.inr h₁) => Or.inr <| Or.inr <| Prod.Lex.left _ _ h₁
| Or.inr (Or.inl (.refl _)) =>
match @trichotomous _ s _ a₂ b₂ with
| Or.inl h => Or.inl <| Prod.Lex.right _ h
| Or.inr (Or.inr h) => Or.inr <| Or.inr <| Prod.Lex.right _ h
| Or.inr (Or.inl (.refl _)) => Or.inr <| Or.inl rfl
trans a b c h₁ h₂ := by
rcases h₁ with ⟨a₂, b₂, ab⟩ | ⟨a₁, ab⟩ <;> rcases h₂ with ⟨c₁, c₂, bc⟩ | ⟨c₂, bc⟩
exacts [.left _ _ (_root_.trans ab bc), .left _ _ ab, .left _ _ bc,
.right _ (_root_.trans ab bc)]
instance (r : α → α → Prop) [IsWellFounded α r] (f : β → α) : IsWellFounded _ (InvImage r f) :=
⟨InvImage.wf f IsWellFounded.wf⟩
instance (f : α → ℕ) : IsWellFounded _ (InvImage (· < ·) f) :=
⟨(measure f).wf⟩
theorem Subrelation.isWellFounded (r : α → α → Prop) [IsWellFounded α r] {s : α → α → Prop}
(h : Subrelation s r) : IsWellFounded α s :=
⟨h.wf IsWellFounded.wf⟩
/-- See `Prod.wellFoundedLT` for a version that only requires `Preorder α`. -/
theorem Prod.wellFoundedLT' [PartialOrder α] [WellFoundedLT α] [Preorder β] [WellFoundedLT β] :
WellFoundedLT (α × β) :=
Subrelation.isWellFounded (Prod.Lex (· < ·) (· < ·))
fun {x y} h ↦ (Prod.lt_iff.mp h).elim (fun h ↦ .left _ _ h.1)
fun h ↦ h.1.lt_or_eq.elim (.left _ _) <| by cases x; cases y; rintro rfl; exact .right _ h.2
/-- See `Prod.wellFoundedGT` for a version that only requires `Preorder α`. -/
theorem Prod.wellFoundedGT' [PartialOrder α] [WellFoundedGT α] [Preorder β] [WellFoundedGT β] :
WellFoundedGT (α × β) :=
@Prod.wellFoundedLT' αᵒᵈ βᵒᵈ _ _ _ _
namespace Set
/-- An unbounded or cofinal set. -/
def Unbounded (r : α → α → Prop) (s : Set α) : Prop :=
∀ a, ∃ b ∈ s, ¬r b a
/-- A bounded or final set. Not to be confused with `Bornology.IsBounded`. -/
def Bounded (r : α → α → Prop) (s : Set α) : Prop :=
∃ a, ∀ b ∈ s, r b a
@[simp]
theorem not_bounded_iff {r : α → α → Prop} (s : Set α) : ¬Bounded r s ↔ Unbounded r s := by
simp only [Bounded, Unbounded, not_forall, not_exists, exists_prop, not_and, not_not]
@[simp]
theorem not_unbounded_iff {r : α → α → Prop} (s : Set α) : ¬Unbounded r s ↔ Bounded r s := by
rw [not_iff_comm, not_bounded_iff]
theorem unbounded_of_isEmpty [IsEmpty α] {r : α → α → Prop} (s : Set α) : Unbounded r s :=
isEmptyElim
end Set
namespace Order.Preimage
instance instIsRefl [IsRefl α r] {f : β → α} : IsRefl β (f ⁻¹'o r) :=
⟨fun _ => refl_of r _⟩
instance instIsIrrefl [IsIrrefl α r] {f : β → α} : IsIrrefl β (f ⁻¹'o r) :=
⟨fun _ => irrefl_of r _⟩
instance instIsSymm [IsSymm α r] {f : β → α} : IsSymm β (f ⁻¹'o r) :=
⟨fun _ _ ↦ symm_of r⟩
instance instIsAsymm [IsAsymm α r] {f : β → α} : IsAsymm β (f ⁻¹'o r) :=
⟨fun _ _ ↦ asymm_of r⟩
instance instIsTrans [IsTrans α r] {f : β → α} : IsTrans β (f ⁻¹'o r) :=
⟨fun _ _ _ => trans_of r⟩
instance instIsPreorder [IsPreorder α r] {f : β → α} : IsPreorder β (f ⁻¹'o r) where
instance instIsStrictOrder [IsStrictOrder α r] {f : β → α} : IsStrictOrder β (f ⁻¹'o r) where
instance instIsStrictWeakOrder [IsStrictWeakOrder α r] {f : β → α} :
IsStrictWeakOrder β (f ⁻¹'o r) where
incomp_trans _ _ _ := IsStrictWeakOrder.incomp_trans (lt := r) _ _ _
instance instIsEquiv [IsEquiv α r] {f : β → α} : IsEquiv β (f ⁻¹'o r) where
instance instIsTotal [IsTotal α r] {f : β → α} : IsTotal β (f ⁻¹'o r) :=
⟨fun _ _ => total_of r _ _⟩
theorem isAntisymm [IsAntisymm α r] {f : β → α} (hf : f.Injective) :
IsAntisymm β (f ⁻¹'o r) :=
⟨fun _ _ h₁ h₂ ↦ hf <| antisymm_of r h₁ h₂⟩
end Order.Preimage
/-! ### Strict-non strict relations -/
/-- An unbundled relation class stating that `r` is the nonstrict relation corresponding to the
strict relation `s`. Compare `Preorder.lt_iff_le_not_le`. This is mostly meant to provide dot
notation on `(⊆)` and `(⊂)`. -/
class IsNonstrictStrictOrder (α : Type*) (r : semiOutParam (α → α → Prop)) (s : α → α → Prop) :
Prop where
/-- The relation `r` is the nonstrict relation corresponding to the strict relation `s`. -/
right_iff_left_not_left (a b : α) : s a b ↔ r a b ∧ ¬r b a
theorem right_iff_left_not_left {r s : α → α → Prop} [IsNonstrictStrictOrder α r s] {a b : α} :
s a b ↔ r a b ∧ ¬r b a :=
IsNonstrictStrictOrder.right_iff_left_not_left _ _
/-- A version of `right_iff_left_not_left` with explicit `r` and `s`. -/
theorem right_iff_left_not_left_of (r s : α → α → Prop) [IsNonstrictStrictOrder α r s] {a b : α} :
s a b ↔ r a b ∧ ¬r b a :=
right_iff_left_not_left
instance {s : α → α → Prop} [IsNonstrictStrictOrder α r s] : IsIrrefl α s :=
⟨fun _ h => ((right_iff_left_not_left_of r s).1 h).2 ((right_iff_left_not_left_of r s).1 h).1⟩
/-! #### `⊆` and `⊂` -/
section Subset
variable [HasSubset α] {a b c : α}
lemma subset_of_eq_of_subset (hab : a = b) (hbc : b ⊆ c) : a ⊆ c := by rwa [hab]
lemma subset_of_subset_of_eq (hab : a ⊆ b) (hbc : b = c) : a ⊆ c := by rwa [← hbc]
@[refl, simp]
lemma subset_refl [IsRefl α (· ⊆ ·)] (a : α) : a ⊆ a := refl _
lemma subset_rfl [IsRefl α (· ⊆ ·)] : a ⊆ a := refl _
lemma subset_of_eq [IsRefl α (· ⊆ ·)] : a = b → a ⊆ b := fun h => h ▸ subset_rfl
lemma superset_of_eq [IsRefl α (· ⊆ ·)] : a = b → b ⊆ a := fun h => h ▸ subset_rfl
lemma ne_of_not_subset [IsRefl α (· ⊆ ·)] : ¬a ⊆ b → a ≠ b := mt subset_of_eq
lemma ne_of_not_superset [IsRefl α (· ⊆ ·)] : ¬a ⊆ b → b ≠ a := mt superset_of_eq
@[trans]
lemma subset_trans [IsTrans α (· ⊆ ·)] {a b c : α} : a ⊆ b → b ⊆ c → a ⊆ c := _root_.trans
lemma subset_antisymm [IsAntisymm α (· ⊆ ·)] : a ⊆ b → b ⊆ a → a = b := antisymm
lemma superset_antisymm [IsAntisymm α (· ⊆ ·)] : a ⊆ b → b ⊆ a → b = a := antisymm'
alias Eq.trans_subset := subset_of_eq_of_subset
alias HasSubset.subset.trans_eq := subset_of_subset_of_eq
alias Eq.subset' := subset_of_eq --TODO: Fix it and kill `Eq.subset`
alias Eq.superset := superset_of_eq
alias HasSubset.Subset.trans := subset_trans
alias HasSubset.Subset.antisymm := subset_antisymm
alias HasSubset.Subset.antisymm' := superset_antisymm
theorem subset_antisymm_iff [IsRefl α (· ⊆ ·)] [IsAntisymm α (· ⊆ ·)] : a = b ↔ a ⊆ b ∧ b ⊆ a :=
⟨fun h => ⟨h.subset', h.superset⟩, fun h => h.1.antisymm h.2⟩
theorem superset_antisymm_iff [IsRefl α (· ⊆ ·)] [IsAntisymm α (· ⊆ ·)] : a = b ↔ b ⊆ a ∧ a ⊆ b :=
⟨fun h => ⟨h.superset, h.subset'⟩, fun h => h.1.antisymm' h.2⟩
end Subset
section Ssubset
variable [HasSSubset α] {a b c : α}
lemma ssubset_of_eq_of_ssubset (hab : a = b) (hbc : b ⊂ c) : a ⊂ c := by rwa [hab]
lemma ssubset_of_ssubset_of_eq (hab : a ⊂ b) (hbc : b = c) : a ⊂ c := by rwa [← hbc]
lemma ssubset_irrefl [IsIrrefl α (· ⊂ ·)] (a : α) : ¬a ⊂ a := irrefl _
lemma ssubset_irrfl [IsIrrefl α (· ⊂ ·)] {a : α} : ¬a ⊂ a := irrefl _
lemma ne_of_ssubset [IsIrrefl α (· ⊂ ·)] {a b : α} : a ⊂ b → a ≠ b := ne_of_irrefl
lemma ne_of_ssuperset [IsIrrefl α (· ⊂ ·)] {a b : α} : a ⊂ b → b ≠ a := ne_of_irrefl'
@[trans]
lemma ssubset_trans [IsTrans α (· ⊂ ·)] {a b c : α} : a ⊂ b → b ⊂ c → a ⊂ c := _root_.trans
|
lemma ssubset_asymm [IsAsymm α (· ⊂ ·)] {a b : α} : a ⊂ b → ¬b ⊂ a := asymm
| Mathlib/Order/RelClasses.lean | 552 | 553 |
/-
Copyright (c) 2020 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Algebra.Algebra.ZMod
import Mathlib.RingTheory.Polynomial.Cyclotomic.Roots
/-!
# Cyclotomic polynomials and `expand`.
We gather results relating cyclotomic polynomials and `expand`.
## Main results
* `Polynomial.cyclotomic_expand_eq_cyclotomic_mul` : If `p` is a prime such that `¬ p ∣ n`, then
`expand R p (cyclotomic n R) = (cyclotomic (n * p) R) * (cyclotomic n R)`.
* `Polynomial.cyclotomic_expand_eq_cyclotomic` : If `p` is a prime such that `p ∣ n`, then
`expand R p (cyclotomic n R) = cyclotomic (p * n) R`.
* `Polynomial.cyclotomic_mul_prime_eq_pow_of_not_dvd` : If `R` is of characteristic `p` and
`¬p ∣ n`, then `cyclotomic (n * p) R = (cyclotomic n R) ^ (p - 1)`.
* `Polynomial.cyclotomic_mul_prime_dvd_eq_pow` : If `R` is of characteristic `p` and `p ∣ n`, then
`cyclotomic (n * p) R = (cyclotomic n R) ^ p`.
* `Polynomial.cyclotomic_mul_prime_pow_eq` : If `R` is of characteristic `p` and `¬p ∣ m`, then
`cyclotomic (p ^ k * m) R = (cyclotomic m R) ^ (p ^ k - p ^ (k - 1))`.
-/
namespace Polynomial
/-- If `p` is a prime such that `¬ p ∣ n`, then
`expand R p (cyclotomic n R) = (cyclotomic (n * p) R) * (cyclotomic n R)`. -/
@[simp]
theorem cyclotomic_expand_eq_cyclotomic_mul {p n : ℕ} (hp : Nat.Prime p) (hdiv : ¬p ∣ n)
(R : Type*) [CommRing R] :
| expand R p (cyclotomic n R) = cyclotomic (n * p) R * cyclotomic n R := by
rcases Nat.eq_zero_or_pos n with (rfl | hnpos)
· simp
haveI := NeZero.of_pos hnpos
suffices expand ℤ p (cyclotomic n ℤ) = cyclotomic (n * p) ℤ * cyclotomic n ℤ by
rw [← map_cyclotomic_int, ← map_expand, this, Polynomial.map_mul, map_cyclotomic_int,
map_cyclotomic]
refine eq_of_monic_of_dvd_of_natDegree_le ((cyclotomic.monic _ ℤ).mul (cyclotomic.monic _ ℤ))
((cyclotomic.monic n ℤ).expand hp.pos) ?_ ?_
· refine (IsPrimitive.Int.dvd_iff_map_cast_dvd_map_cast _ _
(IsPrimitive.mul (cyclotomic.isPrimitive (n * p) ℤ) (cyclotomic.isPrimitive n ℤ))
((cyclotomic.monic n ℤ).expand hp.pos).isPrimitive).2 ?_
rw [Polynomial.map_mul, map_cyclotomic_int, map_cyclotomic_int, map_expand, map_cyclotomic_int]
refine IsCoprime.mul_dvd (cyclotomic.isCoprime_rat fun h => ?_) ?_ ?_
· replace h : n * p = n * 1 := by simp [h]
exact Nat.Prime.ne_one hp (mul_left_cancel₀ hnpos.ne' h)
· have hpos : 0 < n * p := mul_pos hnpos hp.pos
have hprim := Complex.isPrimitiveRoot_exp _ hpos.ne'
rw [cyclotomic_eq_minpoly_rat hprim hpos]
refine minpoly.dvd ℚ _ ?_
rw [aeval_def, ← eval_map, map_expand, map_cyclotomic, expand_eval, ← IsRoot.def,
@isRoot_cyclotomic_iff]
convert IsPrimitiveRoot.pow_of_dvd hprim hp.ne_zero (dvd_mul_left p n)
rw [Nat.mul_div_cancel _ (Nat.Prime.pos hp)]
· have hprim := Complex.isPrimitiveRoot_exp _ hnpos.ne.symm
rw [cyclotomic_eq_minpoly_rat hprim hnpos]
refine minpoly.dvd ℚ _ ?_
rw [aeval_def, ← eval_map, map_expand, expand_eval, ← IsRoot.def, ←
cyclotomic_eq_minpoly_rat hprim hnpos, map_cyclotomic, @isRoot_cyclotomic_iff]
exact IsPrimitiveRoot.pow_of_prime hprim hp hdiv
· rw [natDegree_expand, natDegree_cyclotomic,
natDegree_mul (cyclotomic_ne_zero _ ℤ) (cyclotomic_ne_zero _ ℤ), natDegree_cyclotomic,
natDegree_cyclotomic, mul_comm n,
Nat.totient_mul ((Nat.Prime.coprime_iff_not_dvd hp).2 hdiv), Nat.totient_prime hp,
mul_comm (p - 1), ← Nat.mul_succ, Nat.sub_one, Nat.succ_pred_eq_of_pos hp.pos]
/-- If `p` is a prime such that `p ∣ n`, then
| Mathlib/RingTheory/Polynomial/Cyclotomic/Expand.lean | 36 | 72 |
/-
Copyright (c) 2024 Theodore Hwa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Kim Morrison, Violeta Hernández Palacios, Junyan Xu, Theodore Hwa
-/
import Mathlib.Logic.Hydra
import Mathlib.SetTheory.Surreal.Basic
/-!
### Surreal multiplication
In this file, we show that multiplication of surreal numbers is well-defined, and thus the
surreal numbers form a linear ordered commutative ring.
An inductive argument proves the following three main theorems:
* P1: being numeric is closed under multiplication,
* P2: multiplying a numeric pregame by equivalent numeric pregames results in equivalent pregames,
* P3: the product of two positive numeric pregames is positive (`mul_pos`).
This is Theorem 8 in [Conway2001], or Theorem 3.8 in [SchleicherStoll]. P1 allows us to define
multiplication as an operation on numeric pregames, P2 says that this is well-defined as an
operation on the quotient by `PGame.Equiv`, namely the surreal numbers, and P3 is an axiom that
needs to be satisfied for the surreals to be a `OrderedRing`.
We follow the proof in [SchleicherStoll], except that we use the well-foundedness of
the hydra relation `CutExpand` on `Multiset PGame` instead of the argument based
on a depth function in the paper.
In the argument, P3 is stated with four variables `x₁`, `x₂`, `y₁`, `y₂` satisfying `x₁ < x₂` and
`y₁ < y₂`, and says that `x₁ * y₂ + x₂ * x₁ < x₁ * y₁ + x₂ * y₂`, which is equivalent to
`0 < x₂ - x₁ → 0 < y₂ - y₁ → 0 < (x₂ - x₁) * (y₂ - y₁)`, i.e.
`@mul_pos PGame _ (x₂ - x₁) (y₂ - y₁)`. It has to be stated in this form and not in terms of
`mul_pos` because we need to show P1, P2 and (a specialized form of) P3 simultaneously, and
for example `P1 x y` will be deduced from P3 with variables taking values simpler than `x` or `y`
(among other induction hypotheses), but if you subtract two pregames simpler than `x` or `y`,
the result may no longer be simpler.
The specialized version of P3 is called P4, which takes only three arguments `x₁`, `x₂`, `y` and
requires that `y₂ = y` or `-y` and that `y₁` is a left option of `y₂`. After P1, P2 and P4 are
shown, a further inductive argument (this time using the `GameAdd` relation) proves P3 in full.
Implementation strategy of the inductive argument: we
* extract specialized versions (`IH1`, `IH2`, `IH3`, `IH4` and `IH24`) of the induction hypothesis
that are easier to apply (taking `IsOption` arguments directly), and
* show they are invariant under certain symmetries (permutation and negation of arguments) and that
the induction hypothesis indeed implies the specialized versions.
* utilize the symmetries to minimize calculation.
The whole proof features a clear separation into lemmas of different roles:
* verification of symmetry properties of P and IH (`P3_comm`, `ih1_neg_left`, etc.),
* calculations that connect P1, P2, P3, and inequalities between the product of
two surreals and its options (`mulOption_lt_iff_P1`, etc.),
* specializations of the induction hypothesis
(`numeric_option_mul`, `ih1`, `ih1_swap`, `ih₁₂`, `ih4`, etc.),
* application of specialized induction hypothesis
(`P1_of_ih`, `mul_right_le_of_equiv`, `P3_of_lt`, etc.).
## References
* [Conway, *On numbers and games*][Conway2001]
* [Schleicher, Stoll, *An introduction to Conway's games and numbers*][SchleicherStoll]
-/
universe u
open SetTheory Game PGame WellFounded
namespace Surreal.Multiplication
/-- The nontrivial part of P1 in [SchleicherStoll] says that the left options of `x * y` are less
than the right options, and this is the general form of these statements. -/
def P1 (x₁ x₂ x₃ y₁ y₂ y₃ : PGame) :=
⟦x₁ * y₁⟧ + ⟦x₂ * y₂⟧ - ⟦x₁ * y₂⟧ < ⟦x₃ * y₁⟧ + ⟦x₂ * y₃⟧ - (⟦x₃ * y₃⟧ : Game)
/-- The proposition P2, without numericity assumptions. -/
def P2 (x₁ x₂ y : PGame) := x₁ ≈ x₂ → ⟦x₁ * y⟧ = (⟦x₂ * y⟧ : Game)
/-- The proposition P3, without the `x₁ < x₂` and `y₁ < y₂` assumptions. -/
def P3 (x₁ x₂ y₁ y₂ : PGame) := ⟦x₁ * y₂⟧ + ⟦x₂ * y₁⟧ < ⟦x₁ * y₁⟧ + (⟦x₂ * y₂⟧ : Game)
/-- The proposition P4, without numericity assumptions. In the references, the second part of the
conjunction is stated as `∀ j, P3 x₁ x₂ y (y.moveRight j)`, which is equivalent to our statement
by `P3_comm` and `P3_neg`. We choose to state everything in terms of left options for uniform
treatment. -/
def P4 (x₁ x₂ y : PGame) :=
x₁ < x₂ → (∀ i, P3 x₁ x₂ (y.moveLeft i) y) ∧ ∀ j, P3 x₁ x₂ ((-y).moveLeft j) (-y)
/-- The conjunction of P2 and P4. -/
def P24 (x₁ x₂ y : PGame) : Prop := P2 x₁ x₂ y ∧ P4 x₁ x₂ y
variable {x x₁ x₂ x₃ x' y y₁ y₂ y₃ y' : PGame.{u}}
/-! #### Symmetry properties of P1, P2, P3, and P4 -/
lemma P3_comm : P3 x₁ x₂ y₁ y₂ ↔ P3 y₁ y₂ x₁ x₂ := by
rw [P3, P3, add_comm]
congr! 2 <;> rw [quot_mul_comm]
lemma P3.trans (h₁ : P3 x₁ x₂ y₁ y₂) (h₂ : P3 x₂ x₃ y₁ y₂) : P3 x₁ x₃ y₁ y₂ := by
rw [P3] at h₁ h₂
rw [P3, ← add_lt_add_iff_left (⟦x₂ * y₁⟧ + ⟦x₂ * y₂⟧)]
convert add_lt_add h₁ h₂ using 1 <;> abel
lemma P3_neg : P3 x₁ x₂ y₁ y₂ ↔ P3 (-x₂) (-x₁) y₁ y₂ := by
simp_rw [P3, quot_neg_mul]
rw [← _root_.neg_lt_neg_iff]
abel_nf
lemma P2_neg_left : P2 x₁ x₂ y ↔ P2 (-x₂) (-x₁) y := by
rw [P2, P2]
constructor
· rw [quot_neg_mul, quot_neg_mul, eq_comm, neg_inj, neg_equiv_neg_iff, PGame.equiv_comm]
exact (· ·)
· rw [PGame.equiv_comm, neg_equiv_neg_iff, quot_neg_mul, quot_neg_mul, neg_inj, eq_comm]
exact (· ·)
lemma P2_neg_right : P2 x₁ x₂ y ↔ P2 x₁ x₂ (-y) := by
rw [P2, P2, quot_mul_neg, quot_mul_neg, neg_inj]
lemma P4_neg_left : P4 x₁ x₂ y ↔ P4 (-x₂) (-x₁) y := by
simp_rw [P4, PGame.neg_lt_neg_iff, moveLeft_neg, ← P3_neg]
lemma P4_neg_right : P4 x₁ x₂ y ↔ P4 x₁ x₂ (-y) := by
rw [P4, P4, neg_neg, and_comm]
| lemma P24_neg_left : P24 x₁ x₂ y ↔ P24 (-x₂) (-x₁) y := by rw [P24, P24, P2_neg_left, P4_neg_left]
| Mathlib/SetTheory/Surreal/Multiplication.lean | 127 | 127 |
/-
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.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Equiv
import Mathlib.Analysis.Calculus.FDeriv.Prod
import Mathlib.Analysis.Calculus.Monotone
import Mathlib.Topology.EMetricSpace.BoundedVariation
/-!
# Almost everywhere differentiability of functions with locally bounded variation
In this file we show that a bounded variation function is differentiable almost everywhere.
This implies that Lipschitz functions from the real line into finite-dimensional vector space
are also differentiable almost everywhere.
## Main definitions and results
* `LocallyBoundedVariationOn.ae_differentiableWithinAt` shows that a bounded variation
function into a finite dimensional real vector space is differentiable almost everywhere.
* `LipschitzOnWith.ae_differentiableWithinAt` is the same result for Lipschitz functions.
We also give several variations around these results.
-/
open scoped NNReal ENNReal Topology
open Set MeasureTheory Filter
variable {α : Type*} [LinearOrder α] {E : Type*} [PseudoEMetricSpace E]
/-! ## -/
variable {V : Type*} [NormedAddCommGroup V] [NormedSpace ℝ V] [FiniteDimensional ℝ V]
namespace LocallyBoundedVariationOn
/-- A bounded variation function into `ℝ` is differentiable almost everywhere. Superseded by
`ae_differentiableWithinAt_of_mem`. -/
theorem ae_differentiableWithinAt_of_mem_real {f : ℝ → ℝ} {s : Set ℝ}
(h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by
obtain ⟨p, q, hp, hq, rfl⟩ : ∃ p q, MonotoneOn p s ∧ MonotoneOn q s ∧ f = p - q :=
h.exists_monotoneOn_sub_monotoneOn
filter_upwards [hp.ae_differentiableWithinAt_of_mem, hq.ae_differentiableWithinAt_of_mem] with
x hxp hxq xs
exact (hxp xs).sub (hxq xs)
/-- A bounded variation function into a finite dimensional product vector space is differentiable
almost everywhere. Superseded by `ae_differentiableWithinAt_of_mem`. -/
theorem ae_differentiableWithinAt_of_mem_pi {ι : Type*} [Fintype ι] {f : ℝ → ι → ℝ} {s : Set ℝ}
(h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by
have A : ∀ i : ι, LipschitzWith 1 fun x : ι → ℝ => x i := fun i => LipschitzWith.eval i
have : ∀ i : ι, ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ (fun x : ℝ => f x i) s x := fun i ↦ by
apply ae_differentiableWithinAt_of_mem_real
exact LipschitzWith.comp_locallyBoundedVariationOn (A i) h
filter_upwards [ae_all_iff.2 this] with x hx xs
exact differentiableWithinAt_pi.2 fun i => hx i xs
/-- A real function into a finite dimensional real vector space with bounded variation on a set
is differentiable almost everywhere in this set. -/
theorem ae_differentiableWithinAt_of_mem {f : ℝ → V} {s : Set ℝ}
(h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by
let A := (Basis.ofVectorSpace ℝ V).equivFun.toContinuousLinearEquiv
suffices H : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ (A ∘ f) s x by
filter_upwards [H] with x hx xs
have : f = (A.symm ∘ A) ∘ f := by
simp only [ContinuousLinearEquiv.symm_comp_self, Function.id_comp]
rw [this]
exact A.symm.differentiableAt.comp_differentiableWithinAt x (hx xs)
apply ae_differentiableWithinAt_of_mem_pi
exact A.lipschitz.comp_locallyBoundedVariationOn h
/-- A real function into a finite dimensional real vector space with bounded variation on a set
is differentiable almost everywhere in this set. -/
theorem ae_differentiableWithinAt {f : ℝ → V} {s : Set ℝ} (h : LocallyBoundedVariationOn f s)
(hs : MeasurableSet s) : ∀ᵐ x ∂volume.restrict s, DifferentiableWithinAt ℝ f s x := by
rw [ae_restrict_iff' hs]
exact h.ae_differentiableWithinAt_of_mem
/-- A real function into a finite dimensional real vector space with bounded variation
is differentiable almost everywhere. -/
theorem ae_differentiableAt {f : ℝ → V} (h : LocallyBoundedVariationOn f univ) :
∀ᵐ x, DifferentiableAt ℝ f x := by
filter_upwards [h.ae_differentiableWithinAt_of_mem] with x hx
rw [differentiableWithinAt_univ] at hx
exact hx (mem_univ _)
end LocallyBoundedVariationOn
/-- A real function into a finite dimensional real vector space which is Lipschitz on a set
is differentiable almost everywhere in this set. For the general Rademacher theorem assuming
that the source space is finite dimensional, see `LipschitzOnWith.ae_differentiableWithinAt_of_mem`.
-/
theorem LipschitzOnWith.ae_differentiableWithinAt_of_mem_real {C : ℝ≥0} {f : ℝ → V} {s : Set ℝ}
(h : LipschitzOnWith C f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x :=
h.locallyBoundedVariationOn.ae_differentiableWithinAt_of_mem
/-- A real function into a finite dimensional real vector space which is Lipschitz on a set
is differentiable almost everywhere in this set. For the general Rademacher theorem assuming
that the source space is finite dimensional, see `LipschitzOnWith.ae_differentiableWithinAt`. -/
theorem LipschitzOnWith.ae_differentiableWithinAt_real {C : ℝ≥0} {f : ℝ → V} {s : Set ℝ}
(h : LipschitzOnWith C f s) (hs : MeasurableSet s) :
∀ᵐ x ∂volume.restrict s, DifferentiableWithinAt ℝ f s x :=
h.locallyBoundedVariationOn.ae_differentiableWithinAt hs
/-- A real Lipschitz function into a finite dimensional real vector space is differentiable
almost everywhere. For the general Rademacher theorem assuming
that the source space is finite dimensional, see `LipschitzWith.ae_differentiableAt`. -/
theorem LipschitzWith.ae_differentiableAt_real {C : ℝ≥0} {f : ℝ → V} (h : LipschitzWith C f) :
∀ᵐ x, DifferentiableAt ℝ f x :=
(h.locallyBoundedVariationOn univ).ae_differentiableAt
| Mathlib/Analysis/BoundedVariation.lean | 700 | 703 | |
/-
Copyright (c) 2021 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Johan Commelin
-/
import Mathlib.Algebra.Category.ModuleCat.Monoidal.Basic
import Mathlib.CategoryTheory.Monoidal.Types.Basic
import Mathlib.LinearAlgebra.DirectSum.Finsupp
import Mathlib.CategoryTheory.Linear.LinearFunctor
/-!
The functor of forming finitely supported functions on a type with values in a `[Ring R]`
is the left adjoint of
the forgetful functor from `R`-modules to types.
-/
assert_not_exists Cardinal
noncomputable section
open CategoryTheory
namespace ModuleCat
universe u
variable (R : Type u)
section
variable [Ring R]
/-- The free functor `Type u ⥤ ModuleCat R` sending a type `X` to the
free `R`-module with generators `x : X`, implemented as the type `X →₀ R`.
-/
def free : Type u ⥤ ModuleCat R where
obj X := ModuleCat.of R (X →₀ R)
map {_ _} f := ofHom <| Finsupp.lmapDomain _ _ f
map_id := by intros; ext : 1; exact Finsupp.lmapDomain_id _ _
map_comp := by intros; ext : 1; exact Finsupp.lmapDomain_comp _ _ _ _
variable {R}
/-- Constructor for elements in the module `(free R).obj X`. -/
noncomputable def freeMk {X : Type u} (x : X) : (free R).obj X := Finsupp.single x 1
@[ext 1200]
lemma free_hom_ext {X : Type u} {M : ModuleCat.{u} R} {f g : (free R).obj X ⟶ M}
(h : ∀ (x : X), f (freeMk x) = g (freeMk x)) :
f = g :=
ModuleCat.hom_ext (Finsupp.lhom_ext' (fun x ↦ LinearMap.ext_ring (h x)))
/-- The morphism of modules `(free R).obj X ⟶ M` corresponding
to a map `f : X ⟶ M`. -/
noncomputable def freeDesc {X : Type u} {M : ModuleCat.{u} R} (f : X ⟶ M) :
(free R).obj X ⟶ M :=
ofHom <| Finsupp.lift M R X f
@[simp]
lemma freeDesc_apply {X : Type u} {M : ModuleCat.{u} R} (f : X ⟶ M) (x : X) :
freeDesc f (freeMk x) = f x := by
dsimp [freeDesc]
erw [Finsupp.lift_apply, Finsupp.sum_single_index]
all_goals simp
@[simp]
lemma free_map_apply {X Y : Type u} (f : X → Y) (x : X) :
(free R).map f (freeMk x) = freeMk (f x) := by
apply Finsupp.mapDomain_single
/-- The bijection `((free R).obj X ⟶ M) ≃ (X → M)` when `X` is a type and `M` a module. -/
@[simps]
def freeHomEquiv {X : Type u} {M : ModuleCat.{u} R} :
((free R).obj X ⟶ M) ≃ (X → M) where
toFun φ x := φ (freeMk x)
invFun ψ := freeDesc ψ
left_inv _ := by ext; simp
right_inv _ := by ext; simp
variable (R)
/-- The free-forgetful adjunction for R-modules.
-/
def adj : free R ⊣ forget (ModuleCat.{u} R) :=
Adjunction.mkOfHomEquiv
{ homEquiv := fun _ _ => freeHomEquiv
homEquiv_naturality_left_symm := fun {X Y M} f g ↦ by ext; simp [freeHomEquiv] }
@[simp]
lemma adj_homEquiv (X : Type u) (M : ModuleCat.{u} R) :
(adj R).homEquiv X M = freeHomEquiv := by
simp only [adj, Adjunction.mkOfHomEquiv_homEquiv]
instance : (forget (ModuleCat.{u} R)).IsRightAdjoint :=
(adj R).isRightAdjoint
end
section Free
open MonoidalCategory
variable [CommRing R]
namespace FreeMonoidal
/-- The canonical isomorphism `𝟙_ (ModuleCat R) ≅ (free R).obj (𝟙_ (Type u))`.
(This should not be used directly: it is part of the implementation of the
monoidal structure on the functor `free R`.) -/
def εIso : 𝟙_ (ModuleCat R) ≅ (free R).obj (𝟙_ (Type u)) where
hom := ofHom <| Finsupp.lsingle PUnit.unit
inv := ofHom <| Finsupp.lapply PUnit.unit
hom_inv_id := by
ext
simp [free]
inv_hom_id := by
ext ⟨⟩
dsimp [freeMk]
erw [Finsupp.lapply_apply, Finsupp.lsingle_apply]
rw [Finsupp.single_eq_same]
@[simp]
lemma εIso_hom_one : (εIso R).hom 1 = freeMk PUnit.unit := rfl
@[simp]
lemma εIso_inv_freeMk (x : PUnit) : (εIso R).inv (freeMk x) = 1 := by
dsimp [εIso, freeMk]
erw [Finsupp.lapply_apply]
rw [Finsupp.single_eq_same]
| /-- The canonical isomorphism `(free R).obj X ⊗ (free R).obj Y ≅ (free R).obj (X ⊗ Y)`
for two types `X` and `Y`.
(This should not be used directly: it is is part of the implementation of the
monoidal structure on the functor `free R`.) -/
def μIso (X Y : Type u) :
(free R).obj X ⊗ (free R).obj Y ≅ (free R).obj (X ⊗ Y) :=
(finsuppTensorFinsupp' R _ _).toModuleIso
@[simp]
lemma μIso_hom_freeMk_tmul_freeMk {X Y : Type u} (x : X) (y : Y) :
(μIso R X Y).hom (freeMk x ⊗ₜ freeMk y) = freeMk ⟨x, y⟩ := by
dsimp [μIso, freeMk]
erw [finsuppTensorFinsupp'_single_tmul_single]
rw [mul_one]
@[simp]
lemma μIso_inv_freeMk {X Y : Type u} (z : X ⊗ Y) :
(μIso R X Y).inv (freeMk z) = freeMk z.1 ⊗ₜ freeMk z.2 := by
| Mathlib/Algebra/Category/ModuleCat/Adjunctions.lean | 132 | 149 |
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.Deriv.AffineMap
import Mathlib.Analysis.Calculus.Deriv.Comp
import Mathlib.Analysis.Calculus.Deriv.Mul
import Mathlib.Analysis.Calculus.Deriv.Slope
import Mathlib.Analysis.Normed.Group.AddTorsor
import Mathlib.Analysis.Normed.Module.Convex
import Mathlib.Analysis.RCLike.Basic
import Mathlib.Topology.Instances.RealVectorSpace
import Mathlib.Topology.LocallyConstant.Basic
/-!
# The mean value inequality and equalities
In this file we prove the following facts:
* `Convex.norm_image_sub_le_of_norm_deriv_le` : if `f` is differentiable on a convex set `s`
and the norm of its derivative is bounded by `C`, then `f` is Lipschitz continuous on `s` with
constant `C`; also a variant in which what is bounded by `C` is the norm of the difference of the
derivative from a fixed linear map. This lemma and its versions are formulated using `RCLike`,
so they work both for real and complex derivatives.
* `image_le_of*`, `image_norm_le_of_*` : several similar lemmas deducing `f x ≤ B x` or
`‖f x‖ ≤ B x` from upper estimates on `f'` or `‖f'‖`, respectively. These lemmas differ by
their assumptions:
* `of_liminf_*` lemmas assume that limit inferior of some ratio is less than `B' x`;
* `of_deriv_right_*`, `of_norm_deriv_right_*` lemmas assume that the right derivative
or its norm is less than `B' x`;
* `of_*_lt_*` lemmas assume a strict inequality whenever `f x = B x` or `‖f x‖ = B x`;
* `of_*_le_*` lemmas assume a non-strict inequality everywhere on `[a, b)`;
* name of a lemma ends with `'` if (1) it assumes that `B` is continuous on `[a, b]`
and has a right derivative at every point of `[a, b)`, and (2) the lemma has
a counterpart assuming that `B` is differentiable everywhere on `ℝ`
* `norm_image_sub_le_*_segment` : if derivative of `f` on `[a, b]` is bounded above
by a constant `C`, then `‖f x - f a‖ ≤ C * ‖x - a‖`; several versions deal with
right derivative and derivative within `[a, b]` (`HasDerivWithinAt` or `derivWithin`).
* `Convex.is_const_of_fderivWithin_eq_zero` : if a function has derivative `0` on a convex set `s`,
then it is a constant on `s`.
* `hasStrictFDerivAt_of_hasFDerivAt_of_continuousAt` : a C^1 function over the reals is
strictly differentiable. (This is a corollary of the mean value inequality.)
-/
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] {F : Type*} [NormedAddCommGroup F]
[NormedSpace ℝ F]
open Metric Set Asymptotics ContinuousLinearMap Filter
open scoped Topology NNReal
/-! ### One-dimensional fencing inequalities -/
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `f a ≤ B a`;
* `B` has right derivative `B'` at every point of `[a, b)`;
* for each `x ∈ [a, b)` the right-side limit inferior of `(f z - f x) / (z - x)`
is bounded above by a function `f'`;
* we have `f' x < B' x` whenever `f x = B x`.
Then `f x ≤ B x` everywhere on `[a, b]`. -/
theorem image_le_of_liminf_slope_right_lt_deriv_boundary' {f f' : ℝ → ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b))
-- `hf'` actually says `liminf (f z - f x) / (z - x) ≤ f' x`
(hf' : ∀ x ∈ Ico a b, ∀ r, f' x < r → ∃ᶠ z in 𝓝[>] x, slope f x z < r)
{B B' : ℝ → ℝ} (ha : f a ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, f x = B x → f' x < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → f x ≤ B x := by
change Icc a b ⊆ { x | f x ≤ B x }
set s := { x | f x ≤ B x } ∩ Icc a b
have A : ContinuousOn (fun x => (f x, B x)) (Icc a b) := hf.prodMk hB
have : IsClosed s := by
simp only [s, inter_comm]
exact A.preimage_isClosed_of_isClosed isClosed_Icc OrderClosedTopology.isClosed_le'
apply this.Icc_subset_of_forall_exists_gt ha
rintro x ⟨hxB : f x ≤ B x, xab⟩ y hy
rcases hxB.lt_or_eq with hxB | hxB
· -- If `f x < B x`, then all we need is continuity of both sides
refine nonempty_of_mem (inter_mem ?_ (Ioc_mem_nhdsGT hy))
have : ∀ᶠ x in 𝓝[Icc a b] x, f x < B x :=
A x (Ico_subset_Icc_self xab) (IsOpen.mem_nhds (isOpen_lt continuous_fst continuous_snd) hxB)
have : ∀ᶠ x in 𝓝[>] x, f x < B x := nhdsWithin_le_of_mem (Icc_mem_nhdsGT_of_mem xab) this
exact this.mono fun y => le_of_lt
· rcases exists_between (bound x xab hxB) with ⟨r, hfr, hrB⟩
specialize hf' x xab r hfr
have HB : ∀ᶠ z in 𝓝[>] x, r < slope B x z :=
(hasDerivWithinAt_iff_tendsto_slope' <| lt_irrefl x).1 (hB' x xab).Ioi_of_Ici
(Ioi_mem_nhds hrB)
obtain ⟨z, hfz, hzB, hz⟩ : ∃ z, slope f x z < r ∧ r < slope B x z ∧ z ∈ Ioc x y :=
hf'.and_eventually (HB.and (Ioc_mem_nhdsGT hy)) |>.exists
refine ⟨z, ?_, hz⟩
have := (hfz.trans hzB).le
rwa [slope_def_field, slope_def_field, div_le_div_iff_of_pos_right (sub_pos.2 hz.1), hxB,
sub_le_sub_iff_right] at this
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `f a ≤ B a`;
* `B` has derivative `B'` everywhere on `ℝ`;
* for each `x ∈ [a, b)` the right-side limit inferior of `(f z - f x) / (z - x)`
is bounded above by a function `f'`;
* we have `f' x < B' x` whenever `f x = B x`.
Then `f x ≤ B x` everywhere on `[a, b]`. -/
theorem image_le_of_liminf_slope_right_lt_deriv_boundary {f f' : ℝ → ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b))
-- `hf'` actually says `liminf (f z - f x) / (z - x) ≤ f' x`
(hf' : ∀ x ∈ Ico a b, ∀ r, f' x < r → ∃ᶠ z in 𝓝[>] x, slope f x z < r)
{B B' : ℝ → ℝ} (ha : f a ≤ B a) (hB : ∀ x, HasDerivAt B (B' x) x)
(bound : ∀ x ∈ Ico a b, f x = B x → f' x < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → f x ≤ B x :=
image_le_of_liminf_slope_right_lt_deriv_boundary' hf hf' ha
(fun x _ => (hB x).continuousAt.continuousWithinAt) (fun x _ => (hB x).hasDerivWithinAt) bound
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `f a ≤ B a`;
* `B` has right derivative `B'` at every point of `[a, b)`;
* for each `x ∈ [a, b)` the right-side limit inferior of `(f z - f x) / (z - x)`
is bounded above by `B'`.
Then `f x ≤ B x` everywhere on `[a, b]`. -/
theorem image_le_of_liminf_slope_right_le_deriv_boundary {f : ℝ → ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b)) {B B' : ℝ → ℝ} (ha : f a ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
-- `bound` actually says `liminf (f z - f x) / (z - x) ≤ B' x`
(bound : ∀ x ∈ Ico a b, ∀ r, B' x < r → ∃ᶠ z in 𝓝[>] x, slope f x z < r) :
∀ ⦃x⦄, x ∈ Icc a b → f x ≤ B x := by
have Hr : ∀ x ∈ Icc a b, ∀ r > 0, f x ≤ B x + r * (x - a) := fun x hx r hr => by
apply image_le_of_liminf_slope_right_lt_deriv_boundary' hf bound
· rwa [sub_self, mul_zero, add_zero]
· exact hB.add (continuousOn_const.mul (continuousOn_id.sub continuousOn_const))
· intro x hx
exact (hB' x hx).add (((hasDerivWithinAt_id x (Ici x)).sub_const a).const_mul r)
· intro x _ _
rw [mul_one]
exact (lt_add_iff_pos_right _).2 hr
exact hx
intro x hx
have : ContinuousWithinAt (fun r => B x + r * (x - a)) (Ioi 0) 0 :=
continuousWithinAt_const.add (continuousWithinAt_id.mul continuousWithinAt_const)
convert continuousWithinAt_const.closure_le _ this (Hr x hx) using 1 <;> simp
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `f a ≤ B a`;
* `B` has right derivative `B'` at every point of `[a, b)`;
* `f` has right derivative `f'` at every point of `[a, b)`;
* we have `f' x < B' x` whenever `f x = B x`.
Then `f x ≤ B x` everywhere on `[a, b]`. -/
theorem image_le_of_deriv_right_lt_deriv_boundary' {f f' : ℝ → ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : f a ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, f x = B x → f' x < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → f x ≤ B x :=
image_le_of_liminf_slope_right_lt_deriv_boundary' hf
(fun x hx _ hr => (hf' x hx).liminf_right_slope_le hr) ha hB hB' bound
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `f a ≤ B a`;
* `B` has derivative `B'` everywhere on `ℝ`;
* `f` has right derivative `f'` at every point of `[a, b)`;
* we have `f' x < B' x` whenever `f x = B x`.
Then `f x ≤ B x` everywhere on `[a, b]`. -/
theorem image_le_of_deriv_right_lt_deriv_boundary {f f' : ℝ → ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : f a ≤ B a) (hB : ∀ x, HasDerivAt B (B' x) x)
(bound : ∀ x ∈ Ico a b, f x = B x → f' x < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → f x ≤ B x :=
image_le_of_deriv_right_lt_deriv_boundary' hf hf' ha
(fun x _ => (hB x).continuousAt.continuousWithinAt) (fun x _ => (hB x).hasDerivWithinAt) bound
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `f a ≤ B a`;
* `B` has derivative `B'` everywhere on `ℝ`;
* `f` has right derivative `f'` at every point of `[a, b)`;
* we have `f' x ≤ B' x` on `[a, b)`.
Then `f x ≤ B x` everywhere on `[a, b]`. -/
theorem image_le_of_deriv_right_le_deriv_boundary {f f' : ℝ → ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : f a ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, f' x ≤ B' x) : ∀ ⦃x⦄, x ∈ Icc a b → f x ≤ B x :=
image_le_of_liminf_slope_right_le_deriv_boundary hf ha hB hB' fun x hx _ hr =>
(hf' x hx).liminf_right_slope_le (lt_of_le_of_lt (bound x hx) hr)
/-! ### Vector-valued functions `f : ℝ → E` -/
section
variable {f : ℝ → E} {a b : ℝ}
/-- General fencing theorem for continuous functions with an estimate on the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `‖f a‖ ≤ B a`;
* `B` has right derivative at every point of `[a, b)`;
* for each `x ∈ [a, b)` the right-side limit inferior of `(‖f z‖ - ‖f x‖) / (z - x)`
is bounded above by a function `f'`;
* we have `f' x < B' x` whenever `‖f x‖ = B x`.
Then `‖f x‖ ≤ B x` everywhere on `[a, b]`. -/
theorem image_norm_le_of_liminf_right_slope_norm_lt_deriv_boundary {E : Type*}
[NormedAddCommGroup E] {f : ℝ → E} {f' : ℝ → ℝ} (hf : ContinuousOn f (Icc a b))
-- `hf'` actually says `liminf (‖f z‖ - ‖f x‖) / (z - x) ≤ f' x`
(hf' : ∀ x ∈ Ico a b, ∀ r, f' x < r → ∃ᶠ z in 𝓝[>] x, slope (norm ∘ f) x z < r)
{B B' : ℝ → ℝ} (ha : ‖f a‖ ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, ‖f x‖ = B x → f' x < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → ‖f x‖ ≤ B x :=
image_le_of_liminf_slope_right_lt_deriv_boundary' (continuous_norm.comp_continuousOn hf) hf' ha hB
hB' bound
/-- General fencing theorem for continuous functions with an estimate on the norm of the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `‖f a‖ ≤ B a`;
* `f` and `B` have right derivatives `f'` and `B'` respectively at every point of `[a, b)`;
* the norm of `f'` is strictly less than `B'` whenever `‖f x‖ = B x`.
Then `‖f x‖ ≤ B x` everywhere on `[a, b]`. We use one-sided derivatives in the assumptions
to make this theorem work for piecewise differentiable functions.
-/
theorem image_norm_le_of_norm_deriv_right_lt_deriv_boundary' {f' : ℝ → E}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : ‖f a‖ ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, ‖f x‖ = B x → ‖f' x‖ < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → ‖f x‖ ≤ B x :=
image_norm_le_of_liminf_right_slope_norm_lt_deriv_boundary hf
(fun x hx _ hr => (hf' x hx).liminf_right_slope_norm_le hr) ha hB hB' bound
/-- General fencing theorem for continuous functions with an estimate on the norm of the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `‖f a‖ ≤ B a`;
* `f` has right derivative `f'` at every point of `[a, b)`;
* `B` has derivative `B'` everywhere on `ℝ`;
* the norm of `f'` is strictly less than `B'` whenever `‖f x‖ = B x`.
Then `‖f x‖ ≤ B x` everywhere on `[a, b]`. We use one-sided derivatives in the assumptions
to make this theorem work for piecewise differentiable functions.
-/
theorem image_norm_le_of_norm_deriv_right_lt_deriv_boundary {f' : ℝ → E}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : ‖f a‖ ≤ B a) (hB : ∀ x, HasDerivAt B (B' x) x)
(bound : ∀ x ∈ Ico a b, ‖f x‖ = B x → ‖f' x‖ < B' x) : ∀ ⦃x⦄, x ∈ Icc a b → ‖f x‖ ≤ B x :=
image_norm_le_of_norm_deriv_right_lt_deriv_boundary' hf hf' ha
(fun x _ => (hB x).continuousAt.continuousWithinAt) (fun x _ => (hB x).hasDerivWithinAt) bound
/-- General fencing theorem for continuous functions with an estimate on the norm of the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `‖f a‖ ≤ B a`;
* `f` and `B` have right derivatives `f'` and `B'` respectively at every point of `[a, b)`;
* we have `‖f' x‖ ≤ B x` everywhere on `[a, b)`.
Then `‖f x‖ ≤ B x` everywhere on `[a, b]`. We use one-sided derivatives in the assumptions
to make this theorem work for piecewise differentiable functions.
-/
theorem image_norm_le_of_norm_deriv_right_le_deriv_boundary' {f' : ℝ → E}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : ‖f a‖ ≤ B a) (hB : ContinuousOn B (Icc a b))
(hB' : ∀ x ∈ Ico a b, HasDerivWithinAt B (B' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, ‖f' x‖ ≤ B' x) : ∀ ⦃x⦄, x ∈ Icc a b → ‖f x‖ ≤ B x :=
image_le_of_liminf_slope_right_le_deriv_boundary (continuous_norm.comp_continuousOn hf) ha hB hB'
fun x hx _ hr => (hf' x hx).liminf_right_slope_norm_le ((bound x hx).trans_lt hr)
/-- General fencing theorem for continuous functions with an estimate on the norm of the derivative.
Let `f` and `B` be continuous functions on `[a, b]` such that
* `‖f a‖ ≤ B a`;
* `f` has right derivative `f'` at every point of `[a, b)`;
* `B` has derivative `B'` everywhere on `ℝ`;
* we have `‖f' x‖ ≤ B x` everywhere on `[a, b)`.
Then `‖f x‖ ≤ B x` everywhere on `[a, b]`. We use one-sided derivatives in the assumptions
to make this theorem work for piecewise differentiable functions.
-/
theorem image_norm_le_of_norm_deriv_right_le_deriv_boundary {f' : ℝ → E}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
{B B' : ℝ → ℝ} (ha : ‖f a‖ ≤ B a) (hB : ∀ x, HasDerivAt B (B' x) x)
(bound : ∀ x ∈ Ico a b, ‖f' x‖ ≤ B' x) : ∀ ⦃x⦄, x ∈ Icc a b → ‖f x‖ ≤ B x :=
image_norm_le_of_norm_deriv_right_le_deriv_boundary' hf hf' ha
(fun x _ => (hB x).continuousAt.continuousWithinAt) (fun x _ => (hB x).hasDerivWithinAt) bound
/-- A function on `[a, b]` with the norm of the right derivative bounded by `C`
satisfies `‖f x - f a‖ ≤ C * (x - a)`. -/
theorem norm_image_sub_le_of_norm_deriv_right_le_segment {f' : ℝ → E} {C : ℝ}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
(bound : ∀ x ∈ Ico a b, ‖f' x‖ ≤ C) : ∀ x ∈ Icc a b, ‖f x - f a‖ ≤ C * (x - a) := by
let g x := f x - f a
have hg : ContinuousOn g (Icc a b) := hf.sub continuousOn_const
have hg' : ∀ x ∈ Ico a b, HasDerivWithinAt g (f' x) (Ici x) x := by
intro x hx
simp [g, hf' x hx]
let B x := C * (x - a)
have hB : ∀ x, HasDerivAt B C x := by
intro x
simpa using (hasDerivAt_const x C).mul ((hasDerivAt_id x).sub (hasDerivAt_const x a))
convert image_norm_le_of_norm_deriv_right_le_deriv_boundary hg hg' _ hB bound
simp only [g, B]; rw [sub_self, norm_zero, sub_self, mul_zero]
/-- A function on `[a, b]` with the norm of the derivative within `[a, b]`
bounded by `C` satisfies `‖f x - f a‖ ≤ C * (x - a)`, `HasDerivWithinAt`
version. -/
theorem norm_image_sub_le_of_norm_deriv_le_segment' {f' : ℝ → E} {C : ℝ}
(hf : ∀ x ∈ Icc a b, HasDerivWithinAt f (f' x) (Icc a b) x)
(bound : ∀ x ∈ Ico a b, ‖f' x‖ ≤ C) : ∀ x ∈ Icc a b, ‖f x - f a‖ ≤ C * (x - a) := by
refine
norm_image_sub_le_of_norm_deriv_right_le_segment (fun x hx => (hf x hx).continuousWithinAt)
(fun x hx => ?_) bound
exact (hf x <| Ico_subset_Icc_self hx).mono_of_mem_nhdsWithin (Icc_mem_nhdsGE_of_mem hx)
/-- A function on `[a, b]` with the norm of the derivative within `[a, b]`
bounded by `C` satisfies `‖f x - f a‖ ≤ C * (x - a)`, `derivWithin`
version. -/
theorem norm_image_sub_le_of_norm_deriv_le_segment {C : ℝ} (hf : DifferentiableOn ℝ f (Icc a b))
(bound : ∀ x ∈ Ico a b, ‖derivWithin f (Icc a b) x‖ ≤ C) :
∀ x ∈ Icc a b, ‖f x - f a‖ ≤ C * (x - a) := by
refine norm_image_sub_le_of_norm_deriv_le_segment' ?_ bound
exact fun x hx => (hf x hx).hasDerivWithinAt
/-- A function on `[0, 1]` with the norm of the derivative within `[0, 1]`
bounded by `C` satisfies `‖f 1 - f 0‖ ≤ C`, `HasDerivWithinAt`
version. -/
theorem norm_image_sub_le_of_norm_deriv_le_segment_01' {f' : ℝ → E} {C : ℝ}
(hf : ∀ x ∈ Icc (0 : ℝ) 1, HasDerivWithinAt f (f' x) (Icc (0 : ℝ) 1) x)
(bound : ∀ x ∈ Ico (0 : ℝ) 1, ‖f' x‖ ≤ C) : ‖f 1 - f 0‖ ≤ C := by
simpa only [sub_zero, mul_one] using
norm_image_sub_le_of_norm_deriv_le_segment' hf bound 1 (right_mem_Icc.2 zero_le_one)
/-- A function on `[0, 1]` with the norm of the derivative within `[0, 1]`
bounded by `C` satisfies `‖f 1 - f 0‖ ≤ C`, `derivWithin` version. -/
theorem norm_image_sub_le_of_norm_deriv_le_segment_01 {C : ℝ}
(hf : DifferentiableOn ℝ f (Icc (0 : ℝ) 1))
(bound : ∀ x ∈ Ico (0 : ℝ) 1, ‖derivWithin f (Icc (0 : ℝ) 1) x‖ ≤ C) : ‖f 1 - f 0‖ ≤ C := by
simpa only [sub_zero, mul_one] using
norm_image_sub_le_of_norm_deriv_le_segment hf bound 1 (right_mem_Icc.2 zero_le_one)
theorem constant_of_has_deriv_right_zero (hcont : ContinuousOn f (Icc a b))
(hderiv : ∀ x ∈ Ico a b, HasDerivWithinAt f 0 (Ici x) x) : ∀ x ∈ Icc a b, f x = f a := by
have : ∀ x ∈ Icc a b, ‖f x - f a‖ ≤ 0 * (x - a) := fun x hx =>
norm_image_sub_le_of_norm_deriv_right_le_segment hcont hderiv (fun _ _ => norm_zero.le) x hx
simpa only [zero_mul, norm_le_zero_iff, sub_eq_zero] using this
theorem constant_of_derivWithin_zero (hdiff : DifferentiableOn ℝ f (Icc a b))
(hderiv : ∀ x ∈ Ico a b, derivWithin f (Icc a b) x = 0) : ∀ x ∈ Icc a b, f x = f a := by
have H : ∀ x ∈ Ico a b, ‖derivWithin f (Icc a b) x‖ ≤ 0 := by
simpa only [norm_le_zero_iff] using fun x hx => hderiv x hx
simpa only [zero_mul, norm_le_zero_iff, sub_eq_zero] using fun x hx =>
norm_image_sub_le_of_norm_deriv_le_segment hdiff H x hx
variable {f' g : ℝ → E}
/-- If two continuous functions on `[a, b]` have the same right derivative and are equal at `a`,
then they are equal everywhere on `[a, b]`. -/
theorem eq_of_has_deriv_right_eq (derivf : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
(derivg : ∀ x ∈ Ico a b, HasDerivWithinAt g (f' x) (Ici x) x) (fcont : ContinuousOn f (Icc a b))
(gcont : ContinuousOn g (Icc a b)) (hi : f a = g a) : ∀ y ∈ Icc a b, f y = g y := by
simp only [← @sub_eq_zero _ _ (f _)] at hi ⊢
exact hi ▸ constant_of_has_deriv_right_zero (fcont.sub gcont) fun y hy => by
simpa only [sub_self] using (derivf y hy).sub (derivg y hy)
/-- If two differentiable functions on `[a, b]` have the same derivative within `[a, b]` everywhere
on `[a, b)` and are equal at `a`, then they are equal everywhere on `[a, b]`. -/
theorem eq_of_derivWithin_eq (fdiff : DifferentiableOn ℝ f (Icc a b))
(gdiff : DifferentiableOn ℝ g (Icc a b))
(hderiv : EqOn (derivWithin f (Icc a b)) (derivWithin g (Icc a b)) (Ico a b)) (hi : f a = g a) :
∀ y ∈ Icc a b, f y = g y := by
have A : ∀ y ∈ Ico a b, HasDerivWithinAt f (derivWithin f (Icc a b) y) (Ici y) y := fun y hy =>
(fdiff y (mem_Icc_of_Ico hy)).hasDerivWithinAt.mono_of_mem_nhdsWithin
(Icc_mem_nhdsGE_of_mem hy)
have B : ∀ y ∈ Ico a b, HasDerivWithinAt g (derivWithin g (Icc a b) y) (Ici y) y := fun y hy =>
(gdiff y (mem_Icc_of_Ico hy)).hasDerivWithinAt.mono_of_mem_nhdsWithin
(Icc_mem_nhdsGE_of_mem hy)
exact eq_of_has_deriv_right_eq A (fun y hy => (hderiv hy).symm ▸ B y hy) fdiff.continuousOn
gdiff.continuousOn hi
end
/-!
### Vector-valued functions `f : E → G`
Theorems in this section work both for real and complex differentiable functions. We use assumptions
`[NontriviallyNormedField 𝕜] [IsRCLikeNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 G]` to
achieve this result. For the domain `E` we also assume `[NormedSpace ℝ E]` to have a notion
of a `Convex` set. -/
section
namespace Convex
variable {𝕜 G : Type*} [NontriviallyNormedField 𝕜] [IsRCLikeNormedField 𝕜]
[NormedSpace 𝕜 E] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
{f g : E → G} {C : ℝ} {s : Set E} {x y : E} {f' g' : E → E →L[𝕜] G} {φ : E →L[𝕜] G}
instance (priority := 100) : PathConnectedSpace 𝕜 := by
letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜
infer_instance
/-- The mean value theorem on a convex set: if the derivative of a function is bounded by `C`, then
the function is `C`-Lipschitz. Version with `HasFDerivWithinAt`. -/
theorem norm_image_sub_le_of_norm_hasFDerivWithin_le
(hf : ∀ x ∈ s, HasFDerivWithinAt f (f' x) s x) (bound : ∀ x ∈ s, ‖f' x‖ ≤ C) (hs : Convex ℝ s)
(xs : x ∈ s) (ys : y ∈ s) : ‖f y - f x‖ ≤ C * ‖y - x‖ := by
letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜
letI : NormedSpace ℝ G := RestrictScalars.normedSpace ℝ 𝕜 G
/- By composition with `AffineMap.lineMap x y`, we reduce to a statement for functions defined
on `[0,1]`, for which it is proved in `norm_image_sub_le_of_norm_deriv_le_segment`.
We just have to check the differentiability of the composition and bounds on its derivative,
which is straightforward but tedious for lack of automation. -/
set g := (AffineMap.lineMap x y : ℝ → E)
have segm : MapsTo g (Icc 0 1 : Set ℝ) s := hs.mapsTo_lineMap xs ys
have hD : ∀ t ∈ Icc (0 : ℝ) 1,
HasDerivWithinAt (f ∘ g) (f' (g t) (y - x)) (Icc 0 1) t := fun t ht => by
simpa using ((hf (g t) (segm ht)).restrictScalars ℝ).comp_hasDerivWithinAt _
AffineMap.hasDerivWithinAt_lineMap segm
have bound : ∀ t ∈ Ico (0 : ℝ) 1, ‖f' (g t) (y - x)‖ ≤ C * ‖y - x‖ := fun t ht =>
le_of_opNorm_le _ (bound _ <| segm <| Ico_subset_Icc_self ht) _
simpa [g] using norm_image_sub_le_of_norm_deriv_le_segment_01' hD bound
/-- The mean value theorem on a convex set: if the derivative of a function is bounded by `C` on
`s`, then the function is `C`-Lipschitz on `s`. Version with `HasFDerivWithinAt` and
`LipschitzOnWith`. -/
theorem lipschitzOnWith_of_nnnorm_hasFDerivWithin_le {C : ℝ≥0}
(hf : ∀ x ∈ s, HasFDerivWithinAt f (f' x) s x) (bound : ∀ x ∈ s, ‖f' x‖₊ ≤ C)
(hs : Convex ℝ s) : LipschitzOnWith C f s := by
rw [lipschitzOnWith_iff_norm_sub_le]
intro x x_in y y_in
exact hs.norm_image_sub_le_of_norm_hasFDerivWithin_le hf bound y_in x_in
/-- Let `s` be a convex set in a real normed vector space `E`, let `f : E → G` be a function
differentiable within `s` in a neighborhood of `x : E` with derivative `f'`. Suppose that `f'` is
continuous within `s` at `x`. Then for any number `K : ℝ≥0` larger than `‖f' x‖₊`, `f` is
`K`-Lipschitz on some neighborhood of `x` within `s`. See also
`Convex.exists_nhdsWithin_lipschitzOnWith_of_hasFDerivWithinAt` for a version that claims
existence of `K` instead of an explicit estimate. -/
theorem exists_nhdsWithin_lipschitzOnWith_of_hasFDerivWithinAt_of_nnnorm_lt (hs : Convex ℝ s)
{f : E → G} (hder : ∀ᶠ y in 𝓝[s] x, HasFDerivWithinAt f (f' y) s y)
(hcont : ContinuousWithinAt f' s x) (K : ℝ≥0) (hK : ‖f' x‖₊ < K) :
∃ t ∈ 𝓝[s] x, LipschitzOnWith K f t := by
obtain ⟨ε, ε0, hε⟩ : ∃ ε > 0,
ball x ε ∩ s ⊆ { y | HasFDerivWithinAt f (f' y) s y ∧ ‖f' y‖₊ < K } :=
mem_nhdsWithin_iff.1 (hder.and <| hcont.nnnorm.eventually (gt_mem_nhds hK))
rw [inter_comm] at hε
refine ⟨s ∩ ball x ε, inter_mem_nhdsWithin _ (ball_mem_nhds _ ε0), ?_⟩
exact
(hs.inter (convex_ball _ _)).lipschitzOnWith_of_nnnorm_hasFDerivWithin_le
(fun y hy => (hε hy).1.mono inter_subset_left) fun y hy => (hε hy).2.le
/-- Let `s` be a convex set in a real normed vector space `E`, let `f : E → G` be a function
differentiable within `s` in a neighborhood of `x : E` with derivative `f'`. Suppose that `f'` is
continuous within `s` at `x`. Then for any number `K : ℝ≥0` larger than `‖f' x‖₊`, `f` is Lipschitz
on some neighborhood of `x` within `s`. See also
`Convex.exists_nhdsWithin_lipschitzOnWith_of_hasFDerivWithinAt_of_nnnorm_lt` for a version
with an explicit estimate on the Lipschitz constant. -/
theorem exists_nhdsWithin_lipschitzOnWith_of_hasFDerivWithinAt (hs : Convex ℝ s) {f : E → G}
(hder : ∀ᶠ y in 𝓝[s] x, HasFDerivWithinAt f (f' y) s y) (hcont : ContinuousWithinAt f' s x) :
∃ K, ∃ t ∈ 𝓝[s] x, LipschitzOnWith K f t :=
(exists_gt _).imp <|
hs.exists_nhdsWithin_lipschitzOnWith_of_hasFDerivWithinAt_of_nnnorm_lt hder hcont
/-- The mean value theorem on a convex set: if the derivative of a function within this set is
bounded by `C`, then the function is `C`-Lipschitz. Version with `fderivWithin`. -/
theorem norm_image_sub_le_of_norm_fderivWithin_le (hf : DifferentiableOn 𝕜 f s)
(bound : ∀ x ∈ s, ‖fderivWithin 𝕜 f s x‖ ≤ C) (hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) :
‖f y - f x‖ ≤ C * ‖y - x‖ :=
hs.norm_image_sub_le_of_norm_hasFDerivWithin_le (fun x hx => (hf x hx).hasFDerivWithinAt) bound
xs ys
/-- The mean value theorem on a convex set: if the derivative of a function is bounded by `C` on
`s`, then the function is `C`-Lipschitz on `s`. Version with `fderivWithin` and
`LipschitzOnWith`. -/
theorem lipschitzOnWith_of_nnnorm_fderivWithin_le {C : ℝ≥0} (hf : DifferentiableOn 𝕜 f s)
(bound : ∀ x ∈ s, ‖fderivWithin 𝕜 f s x‖₊ ≤ C) (hs : Convex ℝ s) : LipschitzOnWith C f s :=
hs.lipschitzOnWith_of_nnnorm_hasFDerivWithin_le (fun x hx => (hf x hx).hasFDerivWithinAt) bound
/-- The mean value theorem on a convex set: if the derivative of a function is bounded by `C`,
then the function is `C`-Lipschitz. Version with `fderiv`. -/
theorem norm_image_sub_le_of_norm_fderiv_le (hf : ∀ x ∈ s, DifferentiableAt 𝕜 f x)
(bound : ∀ x ∈ s, ‖fderiv 𝕜 f x‖ ≤ C) (hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) :
‖f y - f x‖ ≤ C * ‖y - x‖ :=
hs.norm_image_sub_le_of_norm_hasFDerivWithin_le
(fun x hx => (hf x hx).hasFDerivAt.hasFDerivWithinAt) bound xs ys
/-- The mean value theorem on a convex set: if the derivative of a function is bounded by `C` on
`s`, then the function is `C`-Lipschitz on `s`. Version with `fderiv` and `LipschitzOnWith`. -/
theorem lipschitzOnWith_of_nnnorm_fderiv_le {C : ℝ≥0} (hf : ∀ x ∈ s, DifferentiableAt 𝕜 f x)
(bound : ∀ x ∈ s, ‖fderiv 𝕜 f x‖₊ ≤ C) (hs : Convex ℝ s) : LipschitzOnWith C f s :=
hs.lipschitzOnWith_of_nnnorm_hasFDerivWithin_le
(fun x hx => (hf x hx).hasFDerivAt.hasFDerivWithinAt) bound
/-- The mean value theorem: if the derivative of a function is bounded by `C`, then the function is
`C`-Lipschitz. Version with `fderiv` and `LipschitzWith`. -/
theorem _root_.lipschitzWith_of_nnnorm_fderiv_le
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {f : E → G}
{C : ℝ≥0} (hf : Differentiable 𝕜 f)
(bound : ∀ x, ‖fderiv 𝕜 f x‖₊ ≤ C) : LipschitzWith C f := by
letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜
let A : NormedSpace ℝ E := RestrictScalars.normedSpace ℝ 𝕜 E
rw [← lipschitzOnWith_univ]
exact lipschitzOnWith_of_nnnorm_fderiv_le (fun x _ ↦ hf x) (fun x _ ↦ bound x) convex_univ
/-- Variant of the mean value inequality on a convex set, using a bound on the difference between
the derivative and a fixed linear map, rather than a bound on the derivative itself. Version with
`HasFDerivWithinAt`. -/
theorem norm_image_sub_le_of_norm_hasFDerivWithin_le'
(hf : ∀ x ∈ s, HasFDerivWithinAt f (f' x) s x) (bound : ∀ x ∈ s, ‖f' x - φ‖ ≤ C)
(hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) : ‖f y - f x - φ (y - x)‖ ≤ C * ‖y - x‖ := by
/- We subtract `φ` to define a new function `g` for which `g' = 0`, for which the previous theorem
applies, `Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le`. Then, we just need to glue
together the pieces, expressing back `f` in terms of `g`. -/
let g y := f y - φ y
have hg : ∀ x ∈ s, HasFDerivWithinAt g (f' x - φ) s x := fun x xs =>
(hf x xs).sub φ.hasFDerivWithinAt
calc
‖f y - f x - φ (y - x)‖ = ‖f y - f x - (φ y - φ x)‖ := by simp
_ = ‖f y - φ y - (f x - φ x)‖ := by congr 1; abel
_ = ‖g y - g x‖ := by simp [g]
_ ≤ C * ‖y - x‖ := Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le hg bound hs xs ys
/-- Variant of the mean value inequality on a convex set. Version with `fderivWithin`. -/
theorem norm_image_sub_le_of_norm_fderivWithin_le' (hf : DifferentiableOn 𝕜 f s)
(bound : ∀ x ∈ s, ‖fderivWithin 𝕜 f s x - φ‖ ≤ C) (hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) :
‖f y - f x - φ (y - x)‖ ≤ C * ‖y - x‖ :=
hs.norm_image_sub_le_of_norm_hasFDerivWithin_le' (fun x hx => (hf x hx).hasFDerivWithinAt) bound
xs ys
/-- Variant of the mean value inequality on a convex set. Version with `fderiv`. -/
theorem norm_image_sub_le_of_norm_fderiv_le' (hf : ∀ x ∈ s, DifferentiableAt 𝕜 f x)
(bound : ∀ x ∈ s, ‖fderiv 𝕜 f x - φ‖ ≤ C) (hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) :
‖f y - f x - φ (y - x)‖ ≤ C * ‖y - x‖ :=
hs.norm_image_sub_le_of_norm_hasFDerivWithin_le'
(fun x hx => (hf x hx).hasFDerivAt.hasFDerivWithinAt) bound xs ys
/-- If a function has zero Fréchet derivative at every point of a convex set,
then it is a constant on this set. -/
theorem is_const_of_fderivWithin_eq_zero (hs : Convex ℝ s) (hf : DifferentiableOn 𝕜 f s)
(hf' : ∀ x ∈ s, fderivWithin 𝕜 f s x = 0) (hx : x ∈ s) (hy : y ∈ s) : f x = f y := by
have bound : ∀ x ∈ s, ‖fderivWithin 𝕜 f s x‖ ≤ 0 := fun x hx => by
simp only [hf' x hx, norm_zero, le_rfl]
simpa only [(dist_eq_norm _ _).symm, zero_mul, dist_le_zero, eq_comm] using
hs.norm_image_sub_le_of_norm_fderivWithin_le hf bound hx hy
theorem _root_.is_const_of_fderiv_eq_zero
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {f : E → G}
(hf : Differentiable 𝕜 f) (hf' : ∀ x, fderiv 𝕜 f x = 0)
(x y : E) : f x = f y := by
letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜
let A : NormedSpace ℝ E := RestrictScalars.normedSpace ℝ 𝕜 E
exact convex_univ.is_const_of_fderivWithin_eq_zero hf.differentiableOn
(fun x _ => by rw [fderivWithin_univ]; exact hf' x) trivial trivial
/-- If two functions have equal Fréchet derivatives at every point of a convex set, and are equal at
one point in that set, then they are equal on that set. -/
theorem eqOn_of_fderivWithin_eq (hs : Convex ℝ s) (hf : DifferentiableOn 𝕜 f s)
(hg : DifferentiableOn 𝕜 g s) (hs' : UniqueDiffOn 𝕜 s)
(hf' : s.EqOn (fderivWithin 𝕜 f s) (fderivWithin 𝕜 g s)) (hx : x ∈ s) (hfgx : f x = g x) :
s.EqOn f g := fun y hy => by
suffices f x - g x = f y - g y by rwa [hfgx, sub_self, eq_comm, sub_eq_zero] at this
refine hs.is_const_of_fderivWithin_eq_zero (hf.sub hg) (fun z hz => ?_) hx hy
rw [fderivWithin_sub (hs' _ hz) (hf _ hz) (hg _ hz), sub_eq_zero, hf' hz]
/-- If `f` has zero derivative on an open set, then `f` is locally constant on `s`. -/
-- TODO: change the spelling once we have `IsLocallyConstantOn`.
theorem _root_.IsOpen.isOpen_inter_preimage_of_fderiv_eq_zero
(hs : IsOpen s) (hf : DifferentiableOn 𝕜 f s)
(hf' : s.EqOn (fderiv 𝕜 f) 0) (t : Set G) : IsOpen (s ∩ f ⁻¹' t) := by
refine Metric.isOpen_iff.mpr fun y ⟨hy, hy'⟩ ↦ ?_
obtain ⟨r, hr, h⟩ := Metric.isOpen_iff.mp hs y hy
refine ⟨r, hr, Set.subset_inter h fun x hx ↦ ?_⟩
have := (convex_ball y r).is_const_of_fderivWithin_eq_zero (hf.mono h) ?_ hx (mem_ball_self hr)
· simpa [this]
· intro z hz
simpa only [fderivWithin_of_isOpen Metric.isOpen_ball hz] using hf' (h hz)
theorem _root_.isLocallyConstant_of_fderiv_eq_zero (h₁ : Differentiable 𝕜 f)
(h₂ : ∀ x, fderiv 𝕜 f x = 0) : IsLocallyConstant f := by
simpa using isOpen_univ.isOpen_inter_preimage_of_fderiv_eq_zero h₁.differentiableOn fun _ _ ↦ h₂ _
/-- If `f` has zero derivative on a connected open set, then `f` is constant on `s`. -/
theorem _root_.IsOpen.exists_is_const_of_fderiv_eq_zero
(hs : IsOpen s) (hs' : IsPreconnected s) (hf : DifferentiableOn 𝕜 f s)
(hf' : s.EqOn (fderiv 𝕜 f) 0) : ∃ a, ∀ x ∈ s, f x = a := by
obtain (rfl|⟨y, hy⟩) := s.eq_empty_or_nonempty
· exact ⟨0, by simp⟩
· refine ⟨f y, fun x hx ↦ ?_⟩
have h₁ := hs.isOpen_inter_preimage_of_fderiv_eq_zero hf hf' {f y}
have h₂ := hf.continuousOn.comp_continuous continuous_subtype_val (fun x ↦ x.2)
by_contra h₃
obtain ⟨t, ht, ht'⟩ := (isClosed_singleton (x := f y)).preimage h₂
have ht'' : ∀ a ∈ s, a ∈ t ↔ f a ≠ f y := by simpa [Set.ext_iff] using ht'
obtain ⟨z, H₁, H₂, H₃⟩ := hs' _ _ h₁ ht (fun x h ↦ by simp [h, ht'', eq_or_ne]) ⟨y, by simpa⟩
⟨x, by simp [ht'' _ hx, hx, h₃]⟩
exact (ht'' _ H₁).mp H₃ H₂.2
theorem _root_.IsOpen.is_const_of_fderiv_eq_zero
(hs : IsOpen s) (hs' : IsPreconnected s) (hf : DifferentiableOn 𝕜 f s)
(hf' : s.EqOn (fderiv 𝕜 f) 0) {x y : E} (hx : x ∈ s) (hy : y ∈ s) : f x = f y := by
obtain ⟨a, ha⟩ := hs.exists_is_const_of_fderiv_eq_zero hs' hf hf'
rw [ha x hx, ha y hy]
theorem _root_.IsOpen.exists_eq_add_of_fderiv_eq (hs : IsOpen s) (hs' : IsPreconnected s)
(hf : DifferentiableOn 𝕜 f s) (hg : DifferentiableOn 𝕜 g s)
(hf' : s.EqOn (fderiv 𝕜 f) (fderiv 𝕜 g)) : ∃ a, s.EqOn f (g · + a) := by
simp_rw [Set.EqOn, ← sub_eq_iff_eq_add']
refine hs.exists_is_const_of_fderiv_eq_zero hs' (hf.sub hg) fun x hx ↦ ?_
rw [fderiv_sub (hf.differentiableAt (hs.mem_nhds hx)) (hg.differentiableAt (hs.mem_nhds hx)),
hf' hx, sub_self, Pi.zero_apply]
/-- If two functions have equal Fréchet derivatives at every point of a connected open set,
and are equal at one point in that set, then they are equal on that set. -/
theorem _root_.IsOpen.eqOn_of_fderiv_eq (hs : IsOpen s) (hs' : IsPreconnected s)
(hf : DifferentiableOn 𝕜 f s) (hg : DifferentiableOn 𝕜 g s)
(hf' : ∀ x ∈ s, fderiv 𝕜 f x = fderiv 𝕜 g x) (hx : x ∈ s) (hfgx : f x = g x) :
s.EqOn f g := by
obtain ⟨a, ha⟩ := hs.exists_eq_add_of_fderiv_eq hs' hf hg hf'
obtain rfl := left_eq_add.mp (hfgx.symm.trans (ha hx))
simpa using ha
theorem _root_.eq_of_fderiv_eq
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {f g : E → G}
(hf : Differentiable 𝕜 f) (hg : Differentiable 𝕜 g)
(hf' : ∀ x, fderiv 𝕜 f x = fderiv 𝕜 g x) (x : E) (hfgx : f x = g x) : f = g := by
letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜
let A : NormedSpace ℝ E := RestrictScalars.normedSpace ℝ 𝕜 E
suffices Set.univ.EqOn f g from funext fun x => this <| mem_univ x
exact convex_univ.eqOn_of_fderivWithin_eq hf.differentiableOn hg.differentiableOn
uniqueDiffOn_univ (fun x _ => by simpa using hf' _) (mem_univ _) hfgx
lemma isLittleO_pow_succ {x₀ : E} {n : ℕ} (hs : Convex ℝ s) (hx₀s : x₀ ∈ s)
(hff' : ∀ x ∈ s, HasFDerivWithinAt f (f' x) s x) (hf' : f' =o[𝓝[s] x₀] fun x ↦ ‖x - x₀‖ ^ n) :
(fun x ↦ f x - f x₀) =o[𝓝[s] x₀] fun x ↦ ‖x - x₀‖ ^ (n + 1) := by
rw [Asymptotics.isLittleO_iff] at hf' ⊢
intro c hc
simp_rw [norm_pow, pow_succ, ← mul_assoc, norm_norm]
simp_rw [norm_pow, norm_norm] at hf'
have : ∀ᶠ x in 𝓝[s] x₀, segment ℝ x₀ x ⊆ s ∧ ∀ y ∈ segment ℝ x₀ x, ‖f' y‖ ≤ c * ‖x - x₀‖ ^ n := by
have h1 : ∀ᶠ x in 𝓝[s] x₀, x ∈ s := eventually_mem_nhdsWithin
filter_upwards [h1, hs.eventually_nhdsWithin_segment hx₀s (hf' hc)] with x hxs h
refine ⟨hs.segment_subset hx₀s hxs, fun y hy ↦ (h y hy).trans ?_⟩
gcongr
exact norm_sub_le_of_mem_segment hy
filter_upwards [this] with x ⟨h_segment, h⟩
convert (convex_segment x₀ x).norm_image_sub_le_of_norm_hasFDerivWithin_le
(f := fun x ↦ f x - f x₀) (y := x) (x := x₀) (s := segment ℝ x₀ x) ?_ h
(left_mem_segment ℝ x₀ x) (right_mem_segment ℝ x₀ x) using 1
· simp
· simp only [hasFDerivWithinAt_sub_const_iff]
exact fun x hx ↦ (hff' x (h_segment hx)).mono h_segment
theorem isLittleO_pow_succ_real {f f' : ℝ → E} {x₀ : ℝ} {n : ℕ} {s : Set ℝ}
(hs : Convex ℝ s) (hx₀s : x₀ ∈ s)
(hff' : ∀ x ∈ s, HasDerivWithinAt f (f' x) s x) (hf' : f' =o[𝓝[s] x₀] fun x ↦ (x - x₀) ^ n) :
(fun x ↦ f x - f x₀) =o[𝓝[s] x₀] fun x ↦ (x - x₀) ^ (n + 1) := by
have h := hs.isLittleO_pow_succ hx₀s hff' ?_ (n := n)
· rw [Asymptotics.isLittleO_iff] at h ⊢
simpa using h
· rw [Asymptotics.isLittleO_iff] at hf' ⊢
convert hf' using 4 with c hc x
simp
end Convex
namespace Convex
variable {𝕜 G : Type*} [RCLike 𝕜] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
{f f' : 𝕜 → G} {s : Set 𝕜} {x y : 𝕜}
/-- The mean value theorem on a convex set in dimension 1: if the derivative of a function is
bounded by `C`, then the function is `C`-Lipschitz. Version with `HasDerivWithinAt`. -/
theorem norm_image_sub_le_of_norm_hasDerivWithin_le {C : ℝ}
(hf : ∀ x ∈ s, HasDerivWithinAt f (f' x) s x) (bound : ∀ x ∈ s, ‖f' x‖ ≤ C) (hs : Convex ℝ s)
(xs : x ∈ s) (ys : y ∈ s) : ‖f y - f x‖ ≤ C * ‖y - x‖ :=
Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le (fun x hx => (hf x hx).hasFDerivWithinAt)
(fun x hx => le_trans (by simp) (bound x hx)) hs xs ys
/-- The mean value theorem on a convex set in dimension 1: if the derivative of a function is
bounded by `C` on `s`, then the function is `C`-Lipschitz on `s`.
Version with `HasDerivWithinAt` and `LipschitzOnWith`. -/
theorem lipschitzOnWith_of_nnnorm_hasDerivWithin_le {C : ℝ≥0} (hs : Convex ℝ s)
(hf : ∀ x ∈ s, HasDerivWithinAt f (f' x) s x) (bound : ∀ x ∈ s, ‖f' x‖₊ ≤ C) :
LipschitzOnWith C f s :=
Convex.lipschitzOnWith_of_nnnorm_hasFDerivWithin_le (fun x hx => (hf x hx).hasFDerivWithinAt)
(fun x hx => le_trans (by simp) (bound x hx)) hs
/-- The mean value theorem on a convex set in dimension 1: if the derivative of a function within
this set is bounded by `C`, then the function is `C`-Lipschitz. Version with `derivWithin` -/
theorem norm_image_sub_le_of_norm_derivWithin_le {C : ℝ} (hf : DifferentiableOn 𝕜 f s)
(bound : ∀ x ∈ s, ‖derivWithin f s x‖ ≤ C) (hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) :
‖f y - f x‖ ≤ C * ‖y - x‖ :=
hs.norm_image_sub_le_of_norm_hasDerivWithin_le (fun x hx => (hf x hx).hasDerivWithinAt) bound xs
ys
/-- The mean value theorem on a convex set in dimension 1: if the derivative of a function is
bounded by `C` on `s`, then the function is `C`-Lipschitz on `s`.
Version with `derivWithin` and `LipschitzOnWith`. -/
theorem lipschitzOnWith_of_nnnorm_derivWithin_le {C : ℝ≥0} (hs : Convex ℝ s)
(hf : DifferentiableOn 𝕜 f s) (bound : ∀ x ∈ s, ‖derivWithin f s x‖₊ ≤ C) :
LipschitzOnWith C f s :=
hs.lipschitzOnWith_of_nnnorm_hasDerivWithin_le (fun x hx => (hf x hx).hasDerivWithinAt) bound
/-- The mean value theorem on a convex set in dimension 1: if the derivative of a function is
bounded by `C`, then the function is `C`-Lipschitz. Version with `deriv`. -/
theorem norm_image_sub_le_of_norm_deriv_le {C : ℝ} (hf : ∀ x ∈ s, DifferentiableAt 𝕜 f x)
(bound : ∀ x ∈ s, ‖deriv f x‖ ≤ C) (hs : Convex ℝ s) (xs : x ∈ s) (ys : y ∈ s) :
‖f y - f x‖ ≤ C * ‖y - x‖ :=
hs.norm_image_sub_le_of_norm_hasDerivWithin_le
(fun x hx => (hf x hx).hasDerivAt.hasDerivWithinAt) bound xs ys
/-- The mean value theorem on a convex set in dimension 1: if the derivative of a function is
bounded by `C` on `s`, then the function is `C`-Lipschitz on `s`.
Version with `deriv` and `LipschitzOnWith`. -/
theorem lipschitzOnWith_of_nnnorm_deriv_le {C : ℝ≥0} (hf : ∀ x ∈ s, DifferentiableAt 𝕜 f x)
(bound : ∀ x ∈ s, ‖deriv f x‖₊ ≤ C) (hs : Convex ℝ s) : LipschitzOnWith C f s :=
hs.lipschitzOnWith_of_nnnorm_hasDerivWithin_le
(fun x hx => (hf x hx).hasDerivAt.hasDerivWithinAt) bound
/-- The mean value theorem set in dimension 1: if the derivative of a function is bounded by `C`,
then the function is `C`-Lipschitz. Version with `deriv` and `LipschitzWith`. -/
theorem _root_.lipschitzWith_of_nnnorm_deriv_le {C : ℝ≥0} (hf : Differentiable 𝕜 f)
(bound : ∀ x, ‖deriv f x‖₊ ≤ C) : LipschitzWith C f :=
lipschitzOnWith_univ.1 <|
convex_univ.lipschitzOnWith_of_nnnorm_deriv_le (fun x _ => hf x) fun x _ => bound x
/-- If `f : 𝕜 → G`, `𝕜 = R` or `𝕜 = ℂ`, is differentiable everywhere and its derivative equal zero,
then it is a constant function. -/
theorem _root_.is_const_of_deriv_eq_zero (hf : Differentiable 𝕜 f) (hf' : ∀ x, deriv f x = 0)
(x y : 𝕜) : f x = f y :=
is_const_of_fderiv_eq_zero hf (fun z => by ext; simp [← deriv_fderiv, hf']) _ _
theorem _root_.IsOpen.isOpen_inter_preimage_of_deriv_eq_zero
(hs : IsOpen s) (hf : DifferentiableOn 𝕜 f s)
(hf' : s.EqOn (deriv f) 0) (t : Set G) : IsOpen (s ∩ f ⁻¹' t) :=
hs.isOpen_inter_preimage_of_fderiv_eq_zero hf
(fun x hx ↦ by ext; simp [← deriv_fderiv, hf' hx]) t
theorem _root_.IsOpen.exists_is_const_of_deriv_eq_zero
(hs : IsOpen s) (hs' : IsPreconnected s) (hf : DifferentiableOn 𝕜 f s)
(hf' : s.EqOn (deriv f) 0) : ∃ a, ∀ x ∈ s, f x = a :=
hs.exists_is_const_of_fderiv_eq_zero hs' hf (fun {x} hx ↦ by ext; simp [← deriv_fderiv, hf' hx])
theorem _root_.IsOpen.is_const_of_deriv_eq_zero
(hs : IsOpen s) (hs' : IsPreconnected s) (hf : DifferentiableOn 𝕜 f s)
(hf' : s.EqOn (deriv f) 0) {x y : 𝕜} (hx : x ∈ s) (hy : y ∈ s) : f x = f y :=
hs.is_const_of_fderiv_eq_zero hs' hf (fun a ha ↦ by ext; simp [← deriv_fderiv, hf' ha]) hx hy
theorem _root_.IsOpen.exists_eq_add_of_deriv_eq {f g : 𝕜 → G} (hs : IsOpen s)
(hs' : IsPreconnected s)
(hf : DifferentiableOn 𝕜 f s) (hg : DifferentiableOn 𝕜 g s)
(hf' : s.EqOn (deriv f) (deriv g)) : ∃ a, s.EqOn f (g · + a) :=
hs.exists_eq_add_of_fderiv_eq hs' hf hg (fun x hx ↦ by ext; simp [← deriv_fderiv, hf' hx])
theorem _root_.IsOpen.eqOn_of_deriv_eq {f g : 𝕜 → G} (hs : IsOpen s)
(hs' : IsPreconnected s) (hf : DifferentiableOn 𝕜 f s) (hg : DifferentiableOn 𝕜 g s)
(hf' : s.EqOn (deriv f) (deriv g)) (hx : x ∈ s) (hfgx : f x = g x) :
s.EqOn f g :=
hs.eqOn_of_fderiv_eq hs' hf hg (fun _ hx ↦ ContinuousLinearMap.ext_ring (hf' hx)) hx hfgx
end Convex
end
section RCLike
/-!
### Vector-valued functions `f : E → F`. Strict differentiability.
A `C^1` function is strictly differentiable, when the field is `ℝ` or `ℂ`. This follows from the
mean value inequality on balls, which is a particular case of the above results after restricting
the scalars to `ℝ`. Note that it does not make sense to talk of a convex set over `ℂ`, but balls
make sense and are enough. Many formulations of the mean value inequality could be generalized to
balls over `ℝ` or `ℂ`. For now, we only include the ones that we need.
-/
variable {𝕜 : Type*} [RCLike 𝕜] {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G] {H : Type*}
[NormedAddCommGroup H] [NormedSpace 𝕜 H] {f : G → H} {f' : G → G →L[𝕜] H} {x : G}
/-- Over the reals or the complexes, a continuously differentiable function is strictly
differentiable. -/
theorem hasStrictFDerivAt_of_hasFDerivAt_of_continuousAt
(hder : ∀ᶠ y in 𝓝 x, HasFDerivAt f (f' y) y) (hcont : ContinuousAt f' x) :
HasStrictFDerivAt f (f' x) x := by
-- turn little-o definition of strict_fderiv into an epsilon-delta statement
rw [hasStrictFDerivAt_iff_isLittleO, isLittleO_iff]
refine fun c hc => Metric.eventually_nhds_iff_ball.mpr ?_
-- the correct ε is the modulus of continuity of f'
rcases Metric.mem_nhds_iff.mp (inter_mem hder (hcont <| ball_mem_nhds _ hc)) with ⟨ε, ε0, hε⟩
refine ⟨ε, ε0, ?_⟩
-- simplify formulas involving the product E × E
rintro ⟨a, b⟩ h
rw [← ball_prod_same, prodMk_mem_set_prod_eq] at h
-- exploit the choice of ε as the modulus of continuity of f'
have hf' : ∀ x' ∈ ball x ε, ‖f' x' - f' x‖ ≤ c := fun x' H' => by
rw [← dist_eq_norm]
exact le_of_lt (hε H').2
-- apply mean value theorem
letI : NormedSpace ℝ G := RestrictScalars.normedSpace ℝ 𝕜 G
refine (convex_ball _ _).norm_image_sub_le_of_norm_hasFDerivWithin_le' ?_ hf' h.2 h.1
exact fun y hy => (hε hy).1.hasFDerivWithinAt
/-- Over the reals or the complexes, a continuously differentiable function is strictly
differentiable. -/
theorem hasStrictDerivAt_of_hasDerivAt_of_continuousAt {f f' : 𝕜 → G} {x : 𝕜}
(hder : ∀ᶠ y in 𝓝 x, HasDerivAt f (f' y) y) (hcont : ContinuousAt f' x) :
HasStrictDerivAt f (f' x) x :=
hasStrictFDerivAt_of_hasFDerivAt_of_continuousAt (hder.mono fun _ hy => hy.hasFDerivAt) <|
(smulRightL 𝕜 𝕜 G 1).continuous.continuousAt.comp hcont
end RCLike
| Mathlib/Analysis/Calculus/MeanValue.lean | 1,060 | 1,080 | |
/-
Copyright (c) 2021 Shing Tak Lam. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Shing Tak Lam
-/
import Mathlib.Topology.Order.ProjIcc
import Mathlib.Topology.ContinuousMap.Ordered
import Mathlib.Topology.CompactOpen
import Mathlib.Topology.UnitInterval
/-!
# Homotopy between functions
In this file, we define a homotopy between two functions `f₀` and `f₁`. First we define
`ContinuousMap.Homotopy` between the two functions, with no restrictions on the intermediate
maps. Then, as in the formalisation in HOL-Analysis, we define
`ContinuousMap.HomotopyWith f₀ f₁ P`, for homotopies between `f₀` and `f₁`, where the
intermediate maps satisfy the predicate `P`. Finally, we define
`ContinuousMap.HomotopyRel f₀ f₁ S`, for homotopies between `f₀` and `f₁` which are fixed
on `S`.
## Definitions
* `ContinuousMap.Homotopy f₀ f₁` is the type of homotopies between `f₀` and `f₁`.
* `ContinuousMap.HomotopyWith f₀ f₁ P` is the type of homotopies between `f₀` and `f₁`, where
the intermediate maps satisfy the predicate `P`.
* `ContinuousMap.HomotopyRel f₀ f₁ S` is the type of homotopies between `f₀` and `f₁` which
are fixed on `S`.
For each of the above, we have
* `refl f`, which is the constant homotopy from `f` to `f`.
* `symm F`, which reverses the homotopy `F`. For example, if `F : ContinuousMap.Homotopy f₀ f₁`,
then `F.symm : ContinuousMap.Homotopy f₁ f₀`.
* `trans F G`, which concatenates the homotopies `F` and `G`. For example, if
`F : ContinuousMap.Homotopy f₀ f₁` and `G : ContinuousMap.Homotopy f₁ f₂`, then
`F.trans G : ContinuousMap.Homotopy f₀ f₂`.
We also define the relations
* `ContinuousMap.Homotopic f₀ f₁` is defined to be `Nonempty (ContinuousMap.Homotopy f₀ f₁)`
* `ContinuousMap.HomotopicWith f₀ f₁ P` is defined to be
`Nonempty (ContinuousMap.HomotopyWith f₀ f₁ P)`
* `ContinuousMap.HomotopicRel f₀ f₁ P` is defined to be
`Nonempty (ContinuousMap.HomotopyRel f₀ f₁ P)`
and for `ContinuousMap.homotopic` and `ContinuousMap.homotopic_rel`, we also define the
`setoid` and `quotient` in `C(X, Y)` by these relations.
## References
- [HOL-Analysis formalisation](https://isabelle.in.tum.de/library/HOL/HOL-Analysis/Homotopy.html)
-/
noncomputable section
universe u v w x
variable {F : Type*} {X : Type u} {Y : Type v} {Z : Type w} {Z' : Type x} {ι : Type*}
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] [TopologicalSpace Z']
open unitInterval
namespace ContinuousMap
/-- `ContinuousMap.Homotopy f₀ f₁` is the type of homotopies from `f₀` to `f₁`.
When possible, instead of parametrizing results over `(f : Homotopy f₀ f₁)`,
you should parametrize over `{F : Type*} [HomotopyLike F f₀ f₁] (f : F)`.
When you extend this structure, make sure to extend `ContinuousMap.HomotopyLike`. -/
structure Homotopy (f₀ f₁ : C(X, Y)) extends C(I × X, Y) where
/-- value of the homotopy at 0 -/
map_zero_left : ∀ x, toFun (0, x) = f₀ x
/-- value of the homotopy at 1 -/
map_one_left : ∀ x, toFun (1, x) = f₁ x
section
/-- `ContinuousMap.HomotopyLike F f₀ f₁` states that `F` is a type of homotopies between `f₀` and
`f₁`.
You should extend this class when you extend `ContinuousMap.Homotopy`. -/
class HomotopyLike {X Y : outParam Type*} [TopologicalSpace X] [TopologicalSpace Y]
(F : Type*) (f₀ f₁ : outParam <| C(X, Y)) [FunLike F (I × X) Y] : Prop
extends ContinuousMapClass F (I × X) Y where
/-- value of the homotopy at 0 -/
map_zero_left (f : F) : ∀ x, f (0, x) = f₀ x
/-- value of the homotopy at 1 -/
map_one_left (f : F) : ∀ x, f (1, x) = f₁ x
end
namespace Homotopy
section
variable {f₀ f₁ : C(X, Y)}
instance instFunLike : FunLike (Homotopy f₀ f₁) (I × X) Y where
coe f := f.toFun
coe_injective' f g h := by
obtain ⟨⟨_, _⟩, _⟩ := f
obtain ⟨⟨_, _⟩, _⟩ := g
congr
instance : HomotopyLike (Homotopy f₀ f₁) f₀ f₁ where
map_continuous f := f.continuous_toFun
map_zero_left f := f.map_zero_left
map_one_left f := f.map_one_left
@[ext]
theorem ext {F G : Homotopy f₀ f₁} (h : ∀ x, F x = G x) : F = G :=
DFunLike.ext _ _ h
/-- 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 (F : Homotopy f₀ f₁) : I × X → Y :=
F
initialize_simps_projections Homotopy (toFun → apply, -toContinuousMap)
/-- Deprecated. Use `map_continuous` instead. -/
protected theorem continuous (F : Homotopy f₀ f₁) : Continuous F :=
F.continuous_toFun
@[simp]
theorem apply_zero (F : Homotopy f₀ f₁) (x : X) : F (0, x) = f₀ x :=
F.map_zero_left x
@[simp]
theorem apply_one (F : Homotopy f₀ f₁) (x : X) : F (1, x) = f₁ x :=
F.map_one_left x
@[simp]
theorem coe_toContinuousMap (F : Homotopy f₀ f₁) : ⇑F.toContinuousMap = F :=
rfl
/-- Currying a homotopy to a continuous function from `I` to `C(X, Y)`.
-/
def curry (F : Homotopy f₀ f₁) : C(I, C(X, Y)) :=
F.toContinuousMap.curry
@[simp]
theorem curry_apply (F : Homotopy f₀ f₁) (t : I) (x : X) : F.curry t x = F (t, x) :=
rfl
/-- Continuously extending a curried homotopy to a function from `ℝ` to `C(X, Y)`.
-/
def extend (F : Homotopy f₀ f₁) : C(ℝ, C(X, Y)) :=
F.curry.IccExtend zero_le_one
theorem extend_apply_of_le_zero (F : Homotopy f₀ f₁) {t : ℝ} (ht : t ≤ 0) (x : X) :
F.extend t x = f₀ x := by
rw [← F.apply_zero]
exact ContinuousMap.congr_fun (Set.IccExtend_of_le_left (zero_le_one' ℝ) F.curry ht) x
theorem extend_apply_of_one_le (F : Homotopy f₀ f₁) {t : ℝ} (ht : 1 ≤ t) (x : X) :
F.extend t x = f₁ x := by
rw [← F.apply_one]
exact ContinuousMap.congr_fun (Set.IccExtend_of_right_le (zero_le_one' ℝ) F.curry ht) x
theorem extend_apply_coe (F : Homotopy f₀ f₁) (t : I) (x : X) : F.extend t x = F (t, x) :=
ContinuousMap.congr_fun (Set.IccExtend_val (zero_le_one' ℝ) F.curry t) x
@[simp]
theorem extend_apply_of_mem_I (F : Homotopy f₀ f₁) {t : ℝ} (ht : t ∈ I) (x : X) :
F.extend t x = F (⟨t, ht⟩, x) :=
ContinuousMap.congr_fun (Set.IccExtend_of_mem (zero_le_one' ℝ) F.curry ht) x
protected theorem congr_fun {F G : Homotopy f₀ f₁} (h : F = G) (x : I × X) : F x = G x :=
ContinuousMap.congr_fun (congr_arg _ h) x
protected theorem congr_arg (F : Homotopy f₀ f₁) {x y : I × X} (h : x = y) : F x = F y :=
F.toContinuousMap.congr_arg h
end
/-- Given a continuous function `f`, we can define a `Homotopy f f` by `F (t, x) = f x`
-/
@[simps]
def refl (f : C(X, Y)) : Homotopy f f where
toFun x := f x.2
map_zero_left _ := rfl
map_one_left _ := rfl
instance : Inhabited (Homotopy (ContinuousMap.id X) (ContinuousMap.id X)) :=
⟨Homotopy.refl _⟩
/-- Given a `Homotopy f₀ f₁`, we can define a `Homotopy f₁ f₀` by reversing the homotopy.
-/
@[simps]
def symm {f₀ f₁ : C(X, Y)} (F : Homotopy f₀ f₁) : Homotopy f₁ f₀ where
toFun x := F (σ x.1, x.2)
map_zero_left := by norm_num
map_one_left := by norm_num
@[simp]
theorem symm_symm {f₀ f₁ : C(X, Y)} (F : Homotopy f₀ f₁) : F.symm.symm = F := by
ext
simp
theorem symm_bijective {f₀ f₁ : C(X, Y)} :
Function.Bijective (Homotopy.symm : Homotopy f₀ f₁ → Homotopy f₁ f₀) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
/--
Given `Homotopy f₀ f₁` and `Homotopy f₁ f₂`, we can define a `Homotopy f₀ f₂` by putting the first
homotopy on `[0, 1/2]` and the second on `[1/2, 1]`.
-/
def trans {f₀ f₁ f₂ : C(X, Y)} (F : Homotopy f₀ f₁) (G : Homotopy f₁ f₂) : Homotopy f₀ f₂ where
toFun x := if (x.1 : ℝ) ≤ 1 / 2 then F.extend (2 * x.1) x.2 else G.extend (2 * x.1 - 1) x.2
continuous_toFun := by
refine
continuous_if_le (by fun_prop) continuous_const
(F.continuous.comp (by continuity)).continuousOn
(G.continuous.comp (by continuity)).continuousOn ?_
rintro x hx
norm_num [hx]
map_zero_left x := by norm_num
map_one_left x := by norm_num
theorem trans_apply {f₀ f₁ f₂ : C(X, Y)} (F : Homotopy f₀ f₁) (G : Homotopy f₁ f₂) (x : I × X) :
(F.trans G) x =
if h : (x.1 : ℝ) ≤ 1 / 2 then
F (⟨2 * x.1, (unitInterval.mul_pos_mem_iff zero_lt_two).2 ⟨x.1.2.1, h⟩⟩, x.2)
else
G (⟨2 * x.1 - 1, unitInterval.two_mul_sub_one_mem_iff.2 ⟨(not_le.1 h).le, x.1.2.2⟩⟩, x.2) :=
show ite _ _ _ = _ by
split_ifs <;>
· rw [extend, ContinuousMap.coe_IccExtend, Set.IccExtend_of_mem]
rfl
theorem symm_trans {f₀ f₁ f₂ : C(X, Y)} (F : Homotopy f₀ f₁) (G : Homotopy f₁ f₂) :
(F.trans G).symm = G.symm.trans F.symm := by
ext ⟨t, _⟩
rw [trans_apply, symm_apply, trans_apply]
simp only [coe_symm_eq, symm_apply]
split_ifs with h₁ h₂ h₂
· have ht : (t : ℝ) = 1 / 2 := by linarith
norm_num [ht]
· congr 2
apply Subtype.ext
simp only [coe_symm_eq]
linarith
· congr 2
apply Subtype.ext
simp only [coe_symm_eq]
linarith
· exfalso
linarith
/-- Casting a `Homotopy f₀ f₁` to a `Homotopy g₀ g₁` where `f₀ = g₀` and `f₁ = g₁`.
-/
@[simps]
def cast {f₀ f₁ g₀ g₁ : C(X, Y)} (F : Homotopy f₀ f₁) (h₀ : f₀ = g₀) (h₁ : f₁ = g₁) :
Homotopy g₀ g₁ where
toFun := F
map_zero_left := by simp [← h₀]
map_one_left := by simp [← h₁]
/-- Composition of a `Homotopy g₀ g₁` and `f : C(X, Y)` as a homotopy between `g₀.comp f` and
`g₁.comp f`. -/
@[simps!]
def compContinuousMap {g₀ g₁ : C(Y, Z)} (G : Homotopy g₀ g₁) (f : C(X, Y)) :
Homotopy (g₀.comp f) (g₁.comp f) where
toContinuousMap := G.comp (.prodMap (.id _) f)
map_zero_left _ := G.map_zero_left _
map_one_left _ := G.map_one_left _
/-- If we have a `Homotopy f₀ f₁` and a `Homotopy g₀ g₁`, then we can compose them and get a
`Homotopy (g₀.comp f₀) (g₁.comp f₁)`.
-/
@[simps]
def hcomp {f₀ f₁ : C(X, Y)} {g₀ g₁ : C(Y, Z)} (F : Homotopy f₀ f₁) (G : Homotopy g₀ g₁) :
Homotopy (g₀.comp f₀) (g₁.comp f₁) where
toFun x := G (x.1, F x)
map_zero_left := by simp
map_one_left := by simp
/-- Let `F` be a homotopy between `f₀ : C(X, Y)` and `f₁ : C(X, Y)`. Let `G` be a homotopy between
`g₀ : C(X, Z)` and `g₁ : C(X, Z)`. Then `F.prodMk G` is the homotopy between `f₀.prodMk g₀` and
`f₁.prodMk g₁` that sends `p` to `(F p, G p)`. -/
nonrec def prodMk {f₀ f₁ : C(X, Y)} {g₀ g₁ : C(X, Z)} (F : Homotopy f₀ f₁) (G : Homotopy g₀ g₁) :
Homotopy (f₀.prodMk g₀) (f₁.prodMk g₁) where
toContinuousMap := F.prodMk G
map_zero_left _ := Prod.ext (F.map_zero_left _) (G.map_zero_left _)
map_one_left _ := Prod.ext (F.map_one_left _) (G.map_one_left _)
/-- Let `F` be a homotopy between `f₀ : C(X, Y)` and `f₁ : C(X, Y)`. Let `G` be a homotopy between
`g₀ : C(Z, Z')` and `g₁ : C(Z, Z')`. Then `F.prodMap G` is the homotopy between `f₀.prodMap g₀` and
`f₁.prodMap g₁` that sends `(t, x, z)` to `(F (t, x), G (t, z))`. -/
def prodMap {f₀ f₁ : C(X, Y)} {g₀ g₁ : C(Z, Z')} (F : Homotopy f₀ f₁) (G : Homotopy g₀ g₁) :
Homotopy (f₀.prodMap g₀) (f₁.prodMap g₁) :=
.prodMk (.hcomp (.refl .fst) F) (.hcomp (.refl .snd) G)
/-- Given a family of homotopies `F i` between `f₀ i : C(X, Y i)` and `f₁ i : C(X, Y i)`, returns a
homotopy between `ContinuousMap.pi f₀` and `ContinuousMap.pi f₁`. -/
protected def pi {Y : ι → Type*} [∀ i, TopologicalSpace (Y i)] {f₀ f₁ : ∀ i, C(X, Y i)}
(F : ∀ i, Homotopy (f₀ i) (f₁ i)) :
Homotopy (.pi f₀) (.pi f₁) where
toContinuousMap := .pi fun i ↦ F i
map_zero_left x := funext fun i ↦ (F i).map_zero_left x
map_one_left x := funext fun i ↦ (F i).map_one_left x
/-- Given a family of homotopies `F i` between `f₀ i : C(X i, Y i)` and `f₁ i : C(X i, Y i)`,
returns a homotopy between `ContinuousMap.piMap f₀` and `ContinuousMap.piMap f₁`. -/
protected def piMap {X Y : ι → Type*} [∀ i, TopologicalSpace (X i)] [∀ i, TopologicalSpace (Y i)]
{f₀ f₁ : ∀ i, C(X i, Y i)} (F : ∀ i, Homotopy (f₀ i) (f₁ i)) :
Homotopy (.piMap f₀) (.piMap f₁) :=
.pi fun i ↦ .hcomp (.refl <| .eval i) (F i)
end Homotopy
/-- Given continuous maps `f₀` and `f₁`, we say `f₀` and `f₁` are homotopic if there exists a
`Homotopy f₀ f₁`.
-/
def Homotopic (f₀ f₁ : C(X, Y)) : Prop :=
Nonempty (Homotopy f₀ f₁)
namespace Homotopic
@[refl]
theorem refl (f : C(X, Y)) : Homotopic f f :=
⟨Homotopy.refl f⟩
@[symm]
theorem symm ⦃f g : C(X, Y)⦄ (h : Homotopic f g) : Homotopic g f :=
h.map Homotopy.symm
@[trans]
theorem trans ⦃f g h : C(X, Y)⦄ (h₀ : Homotopic f g) (h₁ : Homotopic g h) : Homotopic f h :=
h₀.map2 Homotopy.trans h₁
theorem hcomp {f₀ f₁ : C(X, Y)} {g₀ g₁ : C(Y, Z)} (h₀ : Homotopic f₀ f₁) (h₁ : Homotopic g₀ g₁) :
Homotopic (g₀.comp f₀) (g₁.comp f₁) :=
h₀.map2 Homotopy.hcomp h₁
theorem equivalence : Equivalence (@Homotopic X Y _ _) :=
⟨refl, by apply symm, by apply trans⟩
nonrec theorem prodMk {f₀ f₁ : C(X, Y)} {g₀ g₁ : C(X, Z)} :
Homotopic f₀ f₁ → Homotopic g₀ g₁ → Homotopic (f₀.prodMk g₀) (f₁.prodMk g₁)
| ⟨F⟩, ⟨G⟩ => ⟨F.prodMk G⟩
nonrec theorem prodMap {f₀ f₁ : C(X, Y)} {g₀ g₁ : C(Z, Z')} :
Homotopic f₀ f₁ → Homotopic g₀ g₁ → Homotopic (f₀.prodMap g₀) (f₁.prodMap g₁)
| ⟨F⟩, ⟨G⟩ => ⟨F.prodMap G⟩
/-- If each `f₀ i : C(X, Y i)` is homotopic to `f₁ i : C(X, Y i)`, then `ContinuousMap.pi f₀` is
homotopic to `ContinuousMap.pi f₁`. -/
protected theorem pi {Y : ι → Type*} [∀ i, TopologicalSpace (Y i)] {f₀ f₁ : ∀ i, C(X, Y i)}
(F : ∀ i, Homotopic (f₀ i) (f₁ i)) :
Homotopic (.pi f₀) (.pi f₁) :=
⟨.pi fun i ↦ (F i).some⟩
/-- If each `f₀ i : C(X, Y i)` is homotopic to `f₁ i : C(X, Y i)`, then `ContinuousMap.pi f₀` is
homotopic to `ContinuousMap.pi f₁`. -/
protected theorem piMap {X Y : ι → Type*} [∀ i, TopologicalSpace (X i)]
[∀ i, TopologicalSpace (Y i)] {f₀ f₁ : ∀ i, C(X i, Y i)} (F : ∀ i, Homotopic (f₀ i) (f₁ i)) :
Homotopic (.piMap f₀) (.piMap f₁) :=
.pi fun i ↦ .hcomp (.refl <| .eval i) (F i)
end Homotopic
/--
The type of homotopies between `f₀ f₁ : C(X, Y)`, where the intermediate maps satisfy the predicate
`P : C(X, Y) → Prop`
-/
structure HomotopyWith (f₀ f₁ : C(X, Y)) (P : C(X, Y) → Prop) extends Homotopy f₀ f₁ where
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11215): TODO: use `toHomotopy.curry t`
/-- the intermediate maps of the homotopy satisfy the property -/
prop' : ∀ t, P ⟨fun x => toFun (t, x),
Continuous.comp continuous_toFun (continuous_const.prodMk continuous_id')⟩
namespace HomotopyWith
section
variable {f₀ f₁ : C(X, Y)} {P : C(X, Y) → Prop}
instance instFunLike : FunLike (HomotopyWith f₀ f₁ P) (I × X) Y where
coe F := ⇑F.toHomotopy
coe_injective'
| ⟨⟨⟨_, _⟩, _, _⟩, _⟩, ⟨⟨⟨_, _⟩, _, _⟩, _⟩, rfl => rfl
instance : HomotopyLike (HomotopyWith f₀ f₁ P) f₀ f₁ where
map_continuous F := F.continuous_toFun
map_zero_left F := F.map_zero_left
map_one_left F := F.map_one_left
theorem coeFn_injective : @Function.Injective (HomotopyWith f₀ f₁ P) (I × X → Y) (⇑) :=
DFunLike.coe_injective'
@[ext]
theorem ext {F G : HomotopyWith f₀ f₁ P} (h : ∀ x, F x = G x) : F = G := DFunLike.ext F G h
/-- 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 (F : HomotopyWith f₀ f₁ P) : I × X → Y := F
initialize_simps_projections HomotopyWith (toFun → apply, -toHomotopy_toContinuousMap)
@[continuity]
protected theorem continuous (F : HomotopyWith f₀ f₁ P) : Continuous F :=
F.continuous_toFun
@[simp]
theorem apply_zero (F : HomotopyWith f₀ f₁ P) (x : X) : F (0, x) = f₀ x :=
F.map_zero_left x
@[simp]
theorem apply_one (F : HomotopyWith f₀ f₁ P) (x : X) : F (1, x) = f₁ x :=
F.map_one_left x
theorem coe_toContinuousMap (F : HomotopyWith f₀ f₁ P) : ⇑F.toContinuousMap = F :=
rfl
@[simp]
theorem coe_toHomotopy (F : HomotopyWith f₀ f₁ P) : ⇑F.toHomotopy = F :=
rfl
theorem prop (F : HomotopyWith f₀ f₁ P) (t : I) : P (F.toHomotopy.curry t) := F.prop' t
theorem extendProp (F : HomotopyWith f₀ f₁ P) (t : ℝ) : P (F.toHomotopy.extend t) := F.prop _
end
variable {P : C(X, Y) → Prop}
/-- Given a continuous function `f`, and a proof `h : P f`, we can define a `HomotopyWith f f P` by
`F (t, x) = f x`
-/
@[simps!]
def refl (f : C(X, Y)) (hf : P f) : HomotopyWith f f P where
toHomotopy := Homotopy.refl f
prop' := fun _ => hf
instance : Inhabited (HomotopyWith (ContinuousMap.id X) (ContinuousMap.id X) fun _ => True) :=
⟨HomotopyWith.refl _ trivial⟩
/--
Given a `HomotopyWith f₀ f₁ P`, we can define a `HomotopyWith f₁ f₀ P` by reversing the homotopy.
-/
@[simps!]
def symm {f₀ f₁ : C(X, Y)} (F : HomotopyWith f₀ f₁ P) : HomotopyWith f₁ f₀ P where
toHomotopy := F.toHomotopy.symm
prop' := fun t => F.prop (σ t)
@[simp]
theorem symm_symm {f₀ f₁ : C(X, Y)} (F : HomotopyWith f₀ f₁ P) : F.symm.symm = F :=
ext <| Homotopy.congr_fun <| Homotopy.symm_symm _
theorem symm_bijective {f₀ f₁ : C(X, Y)} :
Function.Bijective (HomotopyWith.symm : HomotopyWith f₀ f₁ P → HomotopyWith f₁ f₀ P) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
/--
Given `HomotopyWith f₀ f₁ P` and `HomotopyWith f₁ f₂ P`, we can define a `HomotopyWith f₀ f₂ P`
by putting the first homotopy on `[0, 1/2]` and the second on `[1/2, 1]`.
-/
def trans {f₀ f₁ f₂ : C(X, Y)} (F : HomotopyWith f₀ f₁ P) (G : HomotopyWith f₁ f₂ P) :
HomotopyWith f₀ f₂ P :=
{ F.toHomotopy.trans G.toHomotopy with
prop' := fun t => by
simp only [Homotopy.trans]
change P ⟨fun _ => ite ((t : ℝ) ≤ _) _ _, _⟩
split_ifs
· exact F.extendProp _
· exact G.extendProp _ }
theorem trans_apply {f₀ f₁ f₂ : C(X, Y)} (F : HomotopyWith f₀ f₁ P) (G : HomotopyWith f₁ f₂ P)
(x : I × X) :
(F.trans G) x =
if h : (x.1 : ℝ) ≤ 1 / 2 then
F (⟨2 * x.1, (unitInterval.mul_pos_mem_iff zero_lt_two).2 ⟨x.1.2.1, h⟩⟩, x.2)
else
G (⟨2 * x.1 - 1, unitInterval.two_mul_sub_one_mem_iff.2 ⟨(not_le.1 h).le, x.1.2.2⟩⟩, x.2) :=
Homotopy.trans_apply _ _ _
theorem symm_trans {f₀ f₁ f₂ : C(X, Y)} (F : HomotopyWith f₀ f₁ P) (G : HomotopyWith f₁ f₂ P) :
(F.trans G).symm = G.symm.trans F.symm :=
ext <| Homotopy.congr_fun <| Homotopy.symm_trans _ _
/-- Casting a `HomotopyWith f₀ f₁ P` to a `HomotopyWith g₀ g₁ P` where `f₀ = g₀` and `f₁ = g₁`.
-/
@[simps!]
def cast {f₀ f₁ g₀ g₁ : C(X, Y)} (F : HomotopyWith f₀ f₁ P) (h₀ : f₀ = g₀) (h₁ : f₁ = g₁) :
HomotopyWith g₀ g₁ P where
toHomotopy := F.toHomotopy.cast h₀ h₁
prop' := F.prop
end HomotopyWith
/-- Given continuous maps `f₀` and `f₁`, we say `f₀` and `f₁` are homotopic with respect to the
predicate `P` if there exists a `HomotopyWith f₀ f₁ P`.
-/
def HomotopicWith (f₀ f₁ : C(X, Y)) (P : C(X, Y) → Prop) : Prop :=
Nonempty (HomotopyWith f₀ f₁ P)
namespace HomotopicWith
variable {P : C(X, Y) → Prop}
-- Porting note: removed @[refl]
theorem refl (f : C(X, Y)) (hf : P f) : HomotopicWith f f P :=
⟨HomotopyWith.refl f hf⟩
@[symm]
theorem symm ⦃f g : C(X, Y)⦄ (h : HomotopicWith f g P) : HomotopicWith g f P :=
⟨h.some.symm⟩
-- Note: this was formerly tagged with `@[trans]`, and although the `trans` attribute accepted it
-- the `trans` tactic could not use it.
-- An update to the trans tactic coming in https://github.com/leanprover-community/mathlib4/pull/7014 will reject this attribute.
-- It could be restored by changing the argument order to `HomotopicWith P f g`.
@[trans]
theorem trans ⦃f g h : C(X, Y)⦄ (h₀ : HomotopicWith f g P) (h₁ : HomotopicWith g h P) :
HomotopicWith f h P :=
⟨h₀.some.trans h₁.some⟩
end HomotopicWith
/--
A `HomotopyRel f₀ f₁ S` is a homotopy between `f₀` and `f₁` which is fixed on the points in `S`.
-/
abbrev HomotopyRel (f₀ f₁ : C(X, Y)) (S : Set X) :=
HomotopyWith f₀ f₁ fun f ↦ ∀ x ∈ S, f x = f₀ x
namespace HomotopyRel
section
variable {f₀ f₁ : C(X, Y)} {S : Set X}
theorem eq_fst (F : HomotopyRel f₀ f₁ S) (t : I) {x : X} (hx : x ∈ S) : F (t, x) = f₀ x :=
F.prop t x hx
theorem eq_snd (F : HomotopyRel f₀ f₁ S) (t : I) {x : X} (hx : x ∈ S) : F (t, x) = f₁ x := by
rw [F.eq_fst t hx, ← F.eq_fst 1 hx, F.apply_one]
theorem fst_eq_snd (F : HomotopyRel f₀ f₁ S) {x : X} (hx : x ∈ S) : f₀ x = f₁ x :=
F.eq_fst 0 hx ▸ F.eq_snd 0 hx
end
variable {f₀ f₁ f₂ : C(X, Y)} {S : Set X}
/-- Given a map `f : C(X, Y)` and a set `S`, we can define a `HomotopyRel f f S` by setting
`F (t, x) = f x` for all `t`. This is defined using `HomotopyWith.refl`, but with the proof
filled in.
-/
@[simps!]
def refl (f : C(X, Y)) (S : Set X) : HomotopyRel f f S :=
HomotopyWith.refl f fun _ _ ↦ rfl
/--
Given a `HomotopyRel f₀ f₁ S`, we can define a `HomotopyRel f₁ f₀ S` by reversing the homotopy.
-/
@[simps!]
def symm (F : HomotopyRel f₀ f₁ S) : HomotopyRel f₁ f₀ S where
toHomotopy := F.toHomotopy.symm
prop' := fun _ _ hx ↦ F.eq_snd _ hx
@[simp]
theorem symm_symm (F : HomotopyRel f₀ f₁ S) : F.symm.symm = F :=
HomotopyWith.symm_symm F
theorem symm_bijective :
Function.Bijective (HomotopyRel.symm : HomotopyRel f₀ f₁ S → HomotopyRel f₁ f₀ S) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
/-- Given `HomotopyRel f₀ f₁ S` and `HomotopyRel f₁ f₂ S`, we can define a `HomotopyRel f₀ f₂ S`
by putting the first homotopy on `[0, 1/2]` and the second on `[1/2, 1]`.
-/
def trans (F : HomotopyRel f₀ f₁ S) (G : HomotopyRel f₁ f₂ S) : HomotopyRel f₀ f₂ S where
toHomotopy := F.toHomotopy.trans G.toHomotopy
prop' t x hx := by
simp only [Homotopy.trans]
split_ifs
· simp [HomotopyWith.extendProp F (2 * t) x hx, F.fst_eq_snd hx, G.fst_eq_snd hx]
· simp [HomotopyWith.extendProp G (2 * t - 1) x hx, F.fst_eq_snd hx, G.fst_eq_snd hx]
theorem trans_apply (F : HomotopyRel f₀ f₁ S) (G : HomotopyRel f₁ f₂ S) (x : I × X) :
(F.trans G) x =
if h : (x.1 : ℝ) ≤ 1 / 2 then
F (⟨2 * x.1, (unitInterval.mul_pos_mem_iff zero_lt_two).2 ⟨x.1.2.1, h⟩⟩, x.2)
else
G (⟨2 * x.1 - 1, unitInterval.two_mul_sub_one_mem_iff.2 ⟨(not_le.1 h).le, x.1.2.2⟩⟩, x.2) :=
Homotopy.trans_apply _ _ _
theorem symm_trans (F : HomotopyRel f₀ f₁ S) (G : HomotopyRel f₁ f₂ S) :
(F.trans G).symm = G.symm.trans F.symm :=
HomotopyWith.ext <| Homotopy.congr_fun <| Homotopy.symm_trans _ _
/-- Casting a `HomotopyRel f₀ f₁ S` to a `HomotopyRel g₀ g₁ S` where `f₀ = g₀` and `f₁ = g₁`.
-/
@[simps!]
def cast {f₀ f₁ g₀ g₁ : C(X, Y)} (F : HomotopyRel f₀ f₁ S) (h₀ : f₀ = g₀) (h₁ : f₁ = g₁) :
| HomotopyRel g₀ g₁ S where
toHomotopy := Homotopy.cast F.toHomotopy h₀ h₁
| Mathlib/Topology/Homotopy/Basic.lean | 600 | 601 |
/-
Copyright (c) 2021 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Algebra.Group.Support
import Mathlib.Algebra.Order.Monoid.Unbundled.WithTop
import Mathlib.Order.WellFoundedSet
/-!
# Hahn Series
If `Γ` is ordered and `R` has zero, then `HahnSeries Γ R` consists of formal series over `Γ` with
coefficients in `R`, whose supports are partially well-ordered. With further structure on `R` and
`Γ`, we can add further structure on `HahnSeries Γ R`, with the most studied case being when `Γ` is
a linearly ordered abelian group and `R` is a field, in which case `HahnSeries Γ R` is a
valued field, with value group `Γ`.
These generalize Laurent series (with value group `ℤ`), and Laurent series are implemented that way
in the file `Mathlib/RingTheory/LaurentSeries.lean`.
## Main Definitions
* If `Γ` is ordered and `R` has zero, then `HahnSeries Γ R` consists of
formal series over `Γ` with coefficients in `R`, whose supports are partially well-ordered.
* `support x` is the subset of `Γ` whose coefficients are nonzero.
* `single a r` is the Hahn series which has coefficient `r` at `a` and zero otherwise.
* `orderTop x` is a minimal element of `WithTop Γ` where `x` has a nonzero
coefficient if `x ≠ 0`, and is `⊤` when `x = 0`.
* `order x` is a minimal element of `Γ` where `x` has a nonzero coefficient if `x ≠ 0`, and is zero
when `x = 0`.
* `map` takes each coefficient of a Hahn series to its target under a zero-preserving map.
* `embDomain` preserves coefficients, but embeds the index set `Γ` in a larger poset.
## References
- [J. van der Hoeven, *Operators on Generalized Power Series*][van_der_hoeven]
-/
open Finset Function
noncomputable section
/-- If `Γ` is linearly ordered and `R` has zero, then `HahnSeries Γ R` consists of
formal series over `Γ` with coefficients in `R`, whose supports are well-founded. -/
@[ext]
structure HahnSeries (Γ : Type*) (R : Type*) [PartialOrder Γ] [Zero R] where
/-- The coefficient function of a Hahn Series. -/
coeff : Γ → R
isPWO_support' : (Function.support coeff).IsPWO
variable {Γ Γ' R S : Type*}
namespace HahnSeries
section Zero
variable [PartialOrder Γ] [Zero R]
theorem coeff_injective : Injective (coeff : HahnSeries Γ R → Γ → R) :=
fun _ _ => HahnSeries.ext
@[simp]
theorem coeff_inj {x y : HahnSeries Γ R} : x.coeff = y.coeff ↔ x = y :=
coeff_injective.eq_iff
/-- The support of a Hahn series is just the set of indices whose coefficients are nonzero.
Notably, it is well-founded. -/
nonrec def support (x : HahnSeries Γ R) : Set Γ :=
support x.coeff
@[simp]
theorem isPWO_support (x : HahnSeries Γ R) : x.support.IsPWO :=
x.isPWO_support'
@[simp]
theorem isWF_support (x : HahnSeries Γ R) : x.support.IsWF :=
x.isPWO_support.isWF
@[simp]
theorem mem_support (x : HahnSeries Γ R) (a : Γ) : a ∈ x.support ↔ x.coeff a ≠ 0 :=
Iff.refl _
instance : Zero (HahnSeries Γ R) :=
⟨{ coeff := 0
isPWO_support' := by simp }⟩
instance : Inhabited (HahnSeries Γ R) :=
⟨0⟩
instance [Subsingleton R] : Subsingleton (HahnSeries Γ R) :=
⟨fun _ _ => HahnSeries.ext (by subsingleton)⟩
@[simp]
theorem coeff_zero {a : Γ} : (0 : HahnSeries Γ R).coeff a = 0 :=
rfl
@[deprecated (since := "2025-01-31")] alias zero_coeff := coeff_zero
@[simp]
theorem coeff_fun_eq_zero_iff {x : HahnSeries Γ R} : x.coeff = 0 ↔ x = 0 :=
coeff_injective.eq_iff' rfl
theorem ne_zero_of_coeff_ne_zero {x : HahnSeries Γ R} {g : Γ} (h : x.coeff g ≠ 0) : x ≠ 0 :=
mt (fun x0 => (x0.symm ▸ coeff_zero : x.coeff g = 0)) h
@[simp]
theorem support_zero : support (0 : HahnSeries Γ R) = ∅ :=
Function.support_zero
@[simp]
nonrec theorem support_nonempty_iff {x : HahnSeries Γ R} : x.support.Nonempty ↔ x ≠ 0 := by
rw [support, support_nonempty_iff, Ne, coeff_fun_eq_zero_iff]
@[simp]
theorem support_eq_empty_iff {x : HahnSeries Γ R} : x.support = ∅ ↔ x = 0 :=
Function.support_eq_empty_iff.trans coeff_fun_eq_zero_iff
/-- The map of Hahn series induced by applying a zero-preserving map to each coefficient. -/
@[simps]
def map [Zero S] (x : HahnSeries Γ R) {F : Type*} [FunLike F R S] [ZeroHomClass F R S] (f : F) :
HahnSeries Γ S where
coeff g := f (x.coeff g)
isPWO_support' := x.isPWO_support.mono <| Function.support_comp_subset (ZeroHomClass.map_zero f) _
@[simp]
protected lemma map_zero [Zero S] (f : ZeroHom R S) :
(0 : HahnSeries Γ R).map f = 0 := by
ext; simp
/-- Change a HahnSeries with coefficients in HahnSeries to a HahnSeries on the Lex product. -/
def ofIterate [PartialOrder Γ'] (x : HahnSeries Γ (HahnSeries Γ' R)) :
HahnSeries (Γ ×ₗ Γ') R where
coeff := fun g => coeff (coeff x g.1) g.2
isPWO_support' := by
refine Set.PartiallyWellOrderedOn.subsetProdLex ?_ ?_
· refine Set.IsPWO.mono x.isPWO_support' ?_
simp_rw [Set.image_subset_iff, support_subset_iff, Set.mem_preimage, Function.mem_support]
exact fun _ ↦ ne_zero_of_coeff_ne_zero
· exact fun a => by simpa [Function.mem_support, ne_eq] using (x.coeff a).isPWO_support'
@[simp]
lemma mk_eq_zero (f : Γ → R) (h) : HahnSeries.mk f h = 0 ↔ f = 0 := by
simp_rw [HahnSeries.ext_iff, funext_iff, coeff_zero, Pi.zero_apply]
/-- Change a Hahn series on a lex product to a Hahn series with coefficients in a Hahn series. -/
def toIterate [PartialOrder Γ'] (x : HahnSeries (Γ ×ₗ Γ') R) :
HahnSeries Γ (HahnSeries Γ' R) where
coeff := fun g => {
coeff := fun g' => coeff x (g, g')
isPWO_support' := Set.PartiallyWellOrderedOn.fiberProdLex x.isPWO_support' g
}
isPWO_support' := by
have h₁ : (Function.support fun g => HahnSeries.mk (fun g' => x.coeff (g, g'))
(Set.PartiallyWellOrderedOn.fiberProdLex x.isPWO_support' g)) = Function.support
fun g => fun g' => x.coeff (g, g') := by
simp only [Function.support, ne_eq, mk_eq_zero]
rw [h₁, Function.support_curry' x.coeff]
exact Set.PartiallyWellOrderedOn.imageProdLex x.isPWO_support'
/-- The equivalence between iterated Hahn series and Hahn series on the lex product. -/
@[simps]
def iterateEquiv [PartialOrder Γ'] :
HahnSeries Γ (HahnSeries Γ' R) ≃ HahnSeries (Γ ×ₗ Γ') R where
toFun := ofIterate
invFun := toIterate
left_inv := congrFun rfl
right_inv := congrFun rfl
open Classical in
/-- `single a r` is the Hahn series which has coefficient `r` at `a` and zero otherwise. -/
def single (a : Γ) : ZeroHom R (HahnSeries Γ R) where
toFun r :=
{ coeff := Pi.single a r
isPWO_support' := (Set.isPWO_singleton a).mono Pi.support_single_subset }
map_zero' := HahnSeries.ext (Pi.single_zero _)
variable {a b : Γ} {r : R}
@[simp]
theorem coeff_single_same (a : Γ) (r : R) : (single a r).coeff a = r := by
classical exact Pi.single_eq_same (f := fun _ => R) a r
@[deprecated (since := "2025-01-31")] alias single_coeff_same := coeff_single_same
@[simp]
theorem coeff_single_of_ne (h : b ≠ a) : (single a r).coeff b = 0 := by
classical exact Pi.single_eq_of_ne (f := fun _ => R) h r
@[deprecated (since := "2025-01-31")] alias single_coeff_of_ne := coeff_single_of_ne
open Classical in
theorem coeff_single : (single a r).coeff b = if b = a then r else 0 := by
split_ifs with h <;> simp [h]
@[deprecated (since := "2025-01-31")] alias single_coeff := coeff_single
@[simp]
theorem support_single_of_ne (h : r ≠ 0) : support (single a r) = {a} := by
classical exact Pi.support_single_of_ne h
theorem support_single_subset : support (single a r) ⊆ {a} := by
classical exact Pi.support_single_subset
theorem eq_of_mem_support_single {b : Γ} (h : b ∈ support (single a r)) : b = a :=
support_single_subset h
theorem single_eq_zero : single a (0 : R) = 0 :=
(single a).map_zero
theorem single_injective (a : Γ) : Function.Injective (single a : R → HahnSeries Γ R) :=
fun r s rs => by rw [← coeff_single_same a r, ← coeff_single_same a s, rs]
|
theorem single_ne_zero (h : r ≠ 0) : single a r ≠ 0 := fun con =>
| Mathlib/RingTheory/HahnSeries/Basic.lean | 210 | 211 |
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Yury Kudryashov, Neil Strickland
-/
import Mathlib.Algebra.Group.Defs
import Mathlib.Algebra.GroupWithZero.Defs
import Mathlib.Data.Int.Cast.Defs
import Mathlib.Tactic.Spread
import Mathlib.Util.AssertExists
import Mathlib.Tactic.StacksAttribute
/-!
# Semirings and rings
This file defines semirings, rings and domains. This is analogous to `Algebra.Group.Defs` and
`Algebra.Group.Basic`, the difference being that the former is about `+` and `*` separately, while
the present file is about their interaction.
## Main definitions
* `Distrib`: Typeclass for distributivity of multiplication over addition.
* `HasDistribNeg`: Typeclass for commutativity of negation and multiplication. This is useful when
dealing with multiplicative submonoids which are closed under negation without being closed under
addition, for example `Units`.
* `(NonUnital)(NonAssoc)(Semi)Ring`: Typeclasses for possibly non-unital or non-associative
rings and semirings. Some combinations are not defined yet because they haven't found use.
For Lie Rings, there is a type synonym `CommutatorRing` defined in
`Mathlib/Algebra/Algebra/NonUnitalHom.lean` turning the bracket into a multiplication so that the
instance `instNonUnitalNonAssocSemiringCommutatorRing` can be defined.
## Tags
`Semiring`, `CommSemiring`, `Ring`, `CommRing`, domain, `IsDomain`, nonzero, units
-/
/-!
Previously an import dependency on `Mathlib.Algebra.Group.Basic` had crept in.
In general, the `.Defs` files in the basic algebraic hierarchy should only depend on earlier `.Defs`
files, without importing `.Basic` theory development.
These `assert_not_exists` statements guard against this returning.
-/
assert_not_exists DivisionMonoid.toDivInvOneMonoid mul_rotate
universe u v
variable {α : Type u} {R : Type v}
open Function
/-!
### `Distrib` class
-/
/-- A typeclass stating that multiplication is left and right distributive
over addition. -/
class Distrib (R : Type*) extends Mul R, Add R where
/-- Multiplication is left distributive over addition -/
protected left_distrib : ∀ a b c : R, a * (b + c) = a * b + a * c
/-- Multiplication is right distributive over addition -/
protected right_distrib : ∀ a b c : R, (a + b) * c = a * c + b * c
/-- A typeclass stating that multiplication is left distributive over addition. -/
class LeftDistribClass (R : Type*) [Mul R] [Add R] : Prop where
/-- Multiplication is left distributive over addition -/
protected left_distrib : ∀ a b c : R, a * (b + c) = a * b + a * c
/-- A typeclass stating that multiplication is right distributive over addition. -/
class RightDistribClass (R : Type*) [Mul R] [Add R] : Prop where
/-- Multiplication is right distributive over addition -/
protected right_distrib : ∀ a b c : R, (a + b) * c = a * c + b * c
-- see Note [lower instance priority]
instance (priority := 100) Distrib.leftDistribClass (R : Type*) [Distrib R] : LeftDistribClass R :=
⟨Distrib.left_distrib⟩
-- see Note [lower instance priority]
instance (priority := 100) Distrib.rightDistribClass (R : Type*) [Distrib R] :
RightDistribClass R :=
⟨Distrib.right_distrib⟩
theorem left_distrib [Mul R] [Add R] [LeftDistribClass R] (a b c : R) :
a * (b + c) = a * b + a * c :=
LeftDistribClass.left_distrib a b c
alias mul_add := left_distrib
theorem right_distrib [Mul R] [Add R] [RightDistribClass R] (a b c : R) :
(a + b) * c = a * c + b * c :=
RightDistribClass.right_distrib a b c
alias add_mul := right_distrib
theorem distrib_three_right [Mul R] [Add R] [RightDistribClass R] (a b c d : R) :
(a + b + c) * d = a * d + b * d + c * d := by simp [right_distrib]
/-!
### Classes of semirings and rings
We make sure that the canonical path from `NonAssocSemiring` to `Ring` passes through `Semiring`,
as this is a path which is followed all the time in linear algebra where the defining semilinear map
`σ : R →+* S` depends on the `NonAssocSemiring` structure of `R` and `S` while the module
definition depends on the `Semiring` structure.
It is not currently possible to adjust priorities by hand (see https://github.com/leanprover/lean4/issues/2115). Instead, the last
declared instance is used, so we make sure that `Semiring` is declared after `NonAssocRing`, so
that `Semiring -> NonAssocSemiring` is tried before `NonAssocRing -> NonAssocSemiring`.
TODO: clean this once https://github.com/leanprover/lean4/issues/2115 is fixed
-/
/-- A not-necessarily-unital, not-necessarily-associative semiring. See `CommutatorRing` and the
documentation thereof in case you need a `NonUnitalNonAssocSemiring` instance on a Lie ring
or a Lie algebra. -/
class NonUnitalNonAssocSemiring (α : Type u) extends AddCommMonoid α, Distrib α, MulZeroClass α
/-- An associative but not-necessarily unital semiring. -/
class NonUnitalSemiring (α : Type u) extends NonUnitalNonAssocSemiring α, SemigroupWithZero α
/-- A unital but not-necessarily-associative semiring. -/
class NonAssocSemiring (α : Type u) extends NonUnitalNonAssocSemiring α, MulZeroOneClass α,
AddCommMonoidWithOne α
/-- A not-necessarily-unital, not-necessarily-associative ring. -/
class NonUnitalNonAssocRing (α : Type u) extends AddCommGroup α, NonUnitalNonAssocSemiring α
/-- An associative but not-necessarily unital ring. -/
class NonUnitalRing (α : Type*) extends NonUnitalNonAssocRing α, NonUnitalSemiring α
/-- A unital but not-necessarily-associative ring. -/
class NonAssocRing (α : Type*) extends NonUnitalNonAssocRing α, NonAssocSemiring α,
AddCommGroupWithOne α
/-- A `Semiring` is a type with addition, multiplication, a `0` and a `1` where addition is
commutative and associative, multiplication is associative and left and right distributive over
addition, and `0` and `1` are additive and multiplicative identities. -/
class Semiring (α : Type u) extends NonUnitalSemiring α, NonAssocSemiring α, MonoidWithZero α
/-- A `Ring` is a `Semiring` with negation making it an additive group. -/
class Ring (R : Type u) extends Semiring R, AddCommGroup R, AddGroupWithOne R
/-!
### Semirings
-/
section DistribMulOneClass
variable [Add α] [MulOneClass α]
theorem add_one_mul [RightDistribClass α] (a b : α) : (a + 1) * b = a * b + b := by
rw [add_mul, one_mul]
theorem mul_add_one [LeftDistribClass α] (a b : α) : a * (b + 1) = a * b + a := by
rw [mul_add, mul_one]
theorem one_add_mul [RightDistribClass α] (a b : α) : (1 + a) * b = b + a * b := by
rw [add_mul, one_mul]
theorem mul_one_add [LeftDistribClass α] (a b : α) : a * (1 + b) = a + a * b := by
rw [mul_add, mul_one]
end DistribMulOneClass
section NonAssocSemiring
variable [NonAssocSemiring α]
-- Porting note: was [has_add α] [mul_one_class α] [right_distrib_class α]
theorem two_mul (n : α) : 2 * n = n + n :=
(congrArg₂ _ one_add_one_eq_two.symm rfl).trans <| (right_distrib 1 1 n).trans (by rw [one_mul])
-- Porting note: was [has_add α] [mul_one_class α] [left_distrib_class α]
theorem mul_two (n : α) : n * 2 = n + n :=
(congrArg₂ _ rfl one_add_one_eq_two.symm).trans <| (left_distrib n 1 1).trans (by rw [mul_one])
end NonAssocSemiring
section MulZeroClass
variable [MulZeroClass α] (P Q : Prop) [Decidable P] [Decidable Q] (a b : α)
lemma ite_zero_mul : ite P a 0 * b = ite P (a * b) 0 := by simp
lemma mul_ite_zero : a * ite P b 0 = ite P (a * b) 0 := by simp
lemma ite_zero_mul_ite_zero : ite P a 0 * ite Q b 0 = ite (P ∧ Q) (a * b) 0 := by
simp only [← ite_and, ite_mul, mul_ite, mul_zero, zero_mul, and_comm]
end MulZeroClass
theorem mul_boole {α} [MulZeroOneClass α] (P : Prop) [Decidable P] (a : α) :
(a * if P then 1 else 0) = if P then a else 0 := by simp
theorem boole_mul {α} [MulZeroOneClass α] (P : Prop) [Decidable P] (a : α) :
(if P then 1 else 0) * a = if P then a else 0 := by simp
/-- A not-necessarily-unital, not-necessarily-associative, but commutative semiring. -/
class NonUnitalNonAssocCommSemiring (α : Type u) extends NonUnitalNonAssocSemiring α, CommMagma α
/-- A non-unital commutative semiring is a `NonUnitalSemiring` with commutative multiplication.
In other words, it is a type with the following structures: additive commutative monoid
(`AddCommMonoid`), commutative semigroup (`CommSemigroup`), distributive laws (`Distrib`), and
multiplication by zero law (`MulZeroClass`). -/
class NonUnitalCommSemiring (α : Type u) extends NonUnitalSemiring α, CommSemigroup α
/-- A commutative semiring is a semiring with commutative multiplication. -/
class CommSemiring (R : Type u) extends Semiring R, CommMonoid R
-- see Note [lower instance priority]
instance (priority := 100) CommSemiring.toNonUnitalCommSemiring [CommSemiring α] :
NonUnitalCommSemiring α :=
{ inferInstanceAs (CommMonoid α), inferInstanceAs (CommSemiring α) with }
-- see Note [lower instance priority]
instance (priority := 100) CommSemiring.toCommMonoidWithZero [CommSemiring α] :
CommMonoidWithZero α :=
{ inferInstanceAs (CommMonoid α), inferInstanceAs (CommSemiring α) with }
section CommSemiring
variable [CommSemiring α]
theorem add_mul_self_eq (a b : α) : (a + b) * (a + b) = a * a + 2 * a * b + b * b := by
simp only [two_mul, add_mul, mul_add, add_assoc, mul_comm b]
lemma add_sq (a b : α) : (a + b) ^ 2 = a ^ 2 + 2 * a * b + b ^ 2 := by
simp only [sq, add_mul_self_eq]
lemma add_sq' (a b : α) : (a + b) ^ 2 = a ^ 2 + b ^ 2 + 2 * a * b := by
rw [add_sq, add_assoc, add_comm _ (b ^ 2), add_assoc]
alias add_pow_two := add_sq
end CommSemiring
section HasDistribNeg
/-- Typeclass for a negation operator that distributes across multiplication.
This is useful for dealing with submonoids of a ring that contain `-1` without having to duplicate
lemmas. -/
class HasDistribNeg (α : Type*) [Mul α] extends InvolutiveNeg α where
/-- Negation is left distributive over multiplication -/
neg_mul : ∀ x y : α, -x * y = -(x * y)
/-- Negation is right distributive over multiplication -/
mul_neg : ∀ x y : α, x * -y = -(x * y)
section Mul
variable [Mul α] [HasDistribNeg α]
@[simp]
theorem neg_mul (a b : α) : -a * b = -(a * b) :=
HasDistribNeg.neg_mul _ _
@[simp]
theorem mul_neg (a b : α) : a * -b = -(a * b) :=
HasDistribNeg.mul_neg _ _
theorem neg_mul_neg (a b : α) : -a * -b = a * b := by simp
theorem neg_mul_eq_neg_mul (a b : α) : -(a * b) = -a * b :=
(neg_mul _ _).symm
theorem neg_mul_eq_mul_neg (a b : α) : -(a * b) = a * -b :=
(mul_neg _ _).symm
theorem neg_mul_comm (a b : α) : -a * b = a * -b := by simp
end Mul
section MulOneClass
variable [MulOneClass α] [HasDistribNeg α]
theorem neg_eq_neg_one_mul (a : α) : -a = -1 * a := by simp
/-- An element of a ring multiplied by the additive inverse of one is the element's additive
inverse. -/
theorem mul_neg_one (a : α) : a * -1 = -a := by simp
/-- The additive inverse of one multiplied by an element of a ring is the element's additive
inverse. -/
theorem neg_one_mul (a : α) : -1 * a = -a := by simp
end MulOneClass
section MulZeroClass
variable [MulZeroClass α] [HasDistribNeg α]
instance (priority := 100) MulZeroClass.negZeroClass : NegZeroClass α where
__ := inferInstanceAs (Zero α); __ := inferInstanceAs (InvolutiveNeg α)
neg_zero := by rw [← zero_mul (0 : α), ← neg_mul, mul_zero, mul_zero]
end MulZeroClass
end HasDistribNeg
/-!
### Rings
-/
section NonUnitalNonAssocRing
variable [NonUnitalNonAssocRing α]
instance (priority := 100) NonUnitalNonAssocRing.toHasDistribNeg : HasDistribNeg α where
neg := Neg.neg
neg_neg := neg_neg
neg_mul a b := eq_neg_of_add_eq_zero_left <| by rw [← right_distrib, neg_add_cancel, zero_mul]
mul_neg a b := eq_neg_of_add_eq_zero_left <| by rw [← left_distrib, neg_add_cancel, mul_zero]
theorem mul_sub_left_distrib (a b c : α) : a * (b - c) = a * b - a * c := by
simpa only [sub_eq_add_neg, neg_mul_eq_mul_neg] using mul_add a b (-c)
alias mul_sub := mul_sub_left_distrib
theorem mul_sub_right_distrib (a b c : α) : (a - b) * c = a * c - b * c := by
simpa only [sub_eq_add_neg, neg_mul_eq_neg_mul] using add_mul a (-b) c
alias sub_mul := mul_sub_right_distrib
end NonUnitalNonAssocRing
section NonAssocRing
variable [NonAssocRing α]
theorem sub_one_mul (a b : α) : (a - 1) * b = a * b - b := by rw [sub_mul, one_mul]
theorem mul_sub_one (a b : α) : a * (b - 1) = a * b - a := by rw [mul_sub, mul_one]
theorem one_sub_mul (a b : α) : (1 - a) * b = b - a * b := by rw [sub_mul, one_mul]
theorem mul_one_sub (a b : α) : a * (1 - b) = a - a * b := by rw [mul_sub, mul_one]
end NonAssocRing
section Ring
variable [Ring α]
-- A (unital, associative) ring is a not-necessarily-unital ring
-- see Note [lower instance priority]
instance (priority := 100) Ring.toNonUnitalRing : NonUnitalRing α :=
{ ‹Ring α› with }
-- A (unital, associative) ring is a not-necessarily-associative ring
| -- see Note [lower instance priority]
| Mathlib/Algebra/Ring/Defs.lean | 352 | 352 |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Aurélien Saue, Anne Baanen
-/
import Mathlib.Tactic.NormNum.Inv
import Mathlib.Tactic.NormNum.Pow
import Mathlib.Util.AtomM
/-!
# `ring` tactic
A tactic for solving equations in commutative (semi)rings,
where the exponents can also contain variables.
Based on <http://www.cs.ru.nl/~freek/courses/tt-2014/read/10.1.1.61.3041.pdf> .
More precisely, expressions of the following form are supported:
- constants (non-negative integers)
- variables
- coefficients (any rational number, embedded into the (semi)ring)
- addition of expressions
- multiplication of expressions (`a * b`)
- scalar multiplication of expressions (`n • a`; the multiplier must have type `ℕ`)
- exponentiation of expressions (the exponent must have type `ℕ`)
- subtraction and negation of expressions (if the base is a full ring)
The extension to exponents means that something like `2 * 2^n * b = b * 2^(n+1)` can be proved,
even though it is not strictly speaking an equation in the language of commutative rings.
## Implementation notes
The basic approach to prove equalities is to normalise both sides and check for equality.
The normalisation is guided by building a value in the type `ExSum` at the meta level,
together with a proof (at the base level) that the original value is equal to
the normalised version.
The outline of the file:
- Define a mutual inductive family of types `ExSum`, `ExProd`, `ExBase`,
which can represent expressions with `+`, `*`, `^` and rational numerals.
The mutual induction ensures that associativity and distributivity are applied,
by restricting which kinds of subexpressions appear as arguments to the various operators.
- Represent addition, multiplication and exponentiation in the `ExSum` type,
thus allowing us to map expressions to `ExSum` (the `eval` function drives this).
We apply associativity and distributivity of the operators here (helped by `Ex*` types)
and commutativity as well (by sorting the subterms; unfortunately not helped by anything).
Any expression not of the above formats is treated as an atom (the same as a variable).
There are some details we glossed over which make the plan more complicated:
- The order on atoms is not initially obvious.
We construct a list containing them in order of initial appearance in the expression,
then use the index into the list as a key to order on.
- For `pow`, the exponent must be a natural number, while the base can be any semiring `α`.
We swap out operations for the base ring `α` with those for the exponent ring `ℕ`
as soon as we deal with exponents.
## Caveats and future work
The normalized form of an expression is the one that is useful for the tactic,
but not as nice to read. To remedy this, the user-facing normalization calls `ringNFCore`.
Subtraction cancels out identical terms, but division does not.
That is: `a - a = 0 := by ring` solves the goal,
but `a / a := 1 by ring` doesn't.
Note that `0 / 0` is generally defined to be `0`,
so division cancelling out is not true in general.
Multiplication of powers can be simplified a little bit further:
`2 ^ n * 2 ^ n = 4 ^ n := by ring` could be implemented
in a similar way that `2 * a + 2 * a = 4 * a := by ring` already works.
This feature wasn't needed yet, so it's not implemented yet.
## Tags
ring, semiring, exponent, power
-/
assert_not_exists OrderedAddCommMonoid
namespace Mathlib.Tactic
namespace Ring
open Mathlib.Meta Qq NormNum Lean.Meta AtomM
attribute [local instance] monadLiftOptionMetaM
open Lean (MetaM Expr mkRawNatLit)
/-- A shortcut instance for `CommSemiring ℕ` used by ring. -/
def instCommSemiringNat : CommSemiring ℕ := inferInstance
/--
A typed expression of type `CommSemiring ℕ` used when we are working on
ring subexpressions of type `ℕ`.
-/
def sℕ : Q(CommSemiring ℕ) := q(instCommSemiringNat)
mutual
/-- The base `e` of a normalized exponent expression. -/
inductive ExBase : ∀ {u : Lean.Level} {α : Q(Type u)}, Q(CommSemiring $α) → (e : Q($α)) → Type
/--
An atomic expression `e` with id `id`.
Atomic expressions are those which `ring` cannot parse any further.
For instance, `a + (a % b)` has `a` and `(a % b)` as atoms.
The `ring1` tactic does not normalize the subexpressions in atoms, but `ring_nf` does.
Atoms in fact represent equivalence classes of expressions, modulo definitional equality.
The field `index : ℕ` should be a unique number for each class,
while `value : expr` contains a representative of this class.
The function `resolve_atom` determines the appropriate atom for a given expression.
-/
| atom {sα} {e} (id : ℕ) : ExBase sα e
/-- A sum of monomials. -/
| sum {sα} {e} (_ : ExSum sα e) : ExBase sα e
/--
A monomial, which is a product of powers of `ExBase` expressions,
terminated by a (nonzero) constant coefficient.
-/
inductive ExProd : ∀ {u : Lean.Level} {α : Q(Type u)}, Q(CommSemiring $α) → (e : Q($α)) → Type
/-- A coefficient `value`, which must not be `0`. `e` is a raw rat cast.
If `value` is not an integer, then `hyp` should be a proof of `(value.den : α) ≠ 0`. -/
| const {sα} {e} (value : ℚ) (hyp : Option Expr := none) : ExProd sα e
/-- A product `x ^ e * b` is a monomial if `b` is a monomial. Here `x` is an `ExBase`
and `e` is an `ExProd` representing a monomial expression in `ℕ` (it is a monomial instead of
a polynomial because we eagerly normalize `x ^ (a + b) = x ^ a * x ^ b`.) -/
| mul {u : Lean.Level} {α : Q(Type u)} {sα} {x : Q($α)} {e : Q(ℕ)} {b : Q($α)} :
ExBase sα x → ExProd sℕ e → ExProd sα b → ExProd sα q($x ^ $e * $b)
/-- A polynomial expression, which is a sum of monomials. -/
inductive ExSum : ∀ {u : Lean.Level} {α : Q(Type u)}, Q(CommSemiring $α) → (e : Q($α)) → Type
/-- Zero is a polynomial. `e` is the expression `0`. -/
| zero {u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} : ExSum sα q(0 : $α)
/-- A sum `a + b` is a polynomial if `a` is a monomial and `b` is another polynomial. -/
| add {u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExProd sα a → ExSum sα b → ExSum sα q($a + $b)
end
mutual -- partial only to speed up compilation
/-- Equality test for expressions. This is not a `BEq` instance because it is heterogeneous. -/
partial def ExBase.eq
{u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExBase sα a → ExBase sα b → Bool
| .atom i, .atom j => i == j
| .sum a, .sum b => a.eq b
| _, _ => false
@[inherit_doc ExBase.eq]
partial def ExProd.eq
{u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExProd sα a → ExProd sα b → Bool
| .const i _, .const j _ => i == j
| .mul a₁ a₂ a₃, .mul b₁ b₂ b₃ => a₁.eq b₁ && a₂.eq b₂ && a₃.eq b₃
| _, _ => false
@[inherit_doc ExBase.eq]
partial def ExSum.eq
{u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExSum sα a → ExSum sα b → Bool
| .zero, .zero => true
| .add a₁ a₂, .add b₁ b₂ => a₁.eq b₁ && a₂.eq b₂
| _, _ => false
end
mutual -- partial only to speed up compilation
/--
A total order on normalized expressions.
This is not an `Ord` instance because it is heterogeneous.
-/
partial def ExBase.cmp
{u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExBase sα a → ExBase sα b → Ordering
| .atom i, .atom j => compare i j
| .sum a, .sum b => a.cmp b
| .atom .., .sum .. => .lt
| .sum .., .atom .. => .gt
@[inherit_doc ExBase.cmp]
partial def ExProd.cmp
{u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExProd sα a → ExProd sα b → Ordering
| .const i _, .const j _ => compare i j
| .mul a₁ a₂ a₃, .mul b₁ b₂ b₃ => (a₁.cmp b₁).then (a₂.cmp b₂) |>.then (a₃.cmp b₃)
| .const _ _, .mul .. => .lt
| .mul .., .const _ _ => .gt
@[inherit_doc ExBase.cmp]
partial def ExSum.cmp
{u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a b : Q($α)} :
ExSum sα a → ExSum sα b → Ordering
| .zero, .zero => .eq
| .add a₁ a₂, .add b₁ b₂ => (a₁.cmp b₁).then (a₂.cmp b₂)
| .zero, .add .. => .lt
| .add .., .zero => .gt
end
variable {u : Lean.Level} {α : Q(Type u)} {sα : Q(CommSemiring $α)}
instance : Inhabited (Σ e, (ExBase sα) e) := ⟨default, .atom 0⟩
instance : Inhabited (Σ e, (ExSum sα) e) := ⟨_, .zero⟩
instance : Inhabited (Σ e, (ExProd sα) e) := ⟨default, .const 0 none⟩
mutual
/-- Converts `ExBase sα` to `ExBase sβ`, assuming `sα` and `sβ` are defeq. -/
partial def ExBase.cast
{v : Lean.Level} {β : Q(Type v)} {sβ : Q(CommSemiring $β)} {a : Q($α)} :
ExBase sα a → Σ a, ExBase sβ a
| .atom i => ⟨a, .atom i⟩
| .sum a => let ⟨_, vb⟩ := a.cast; ⟨_, .sum vb⟩
/-- Converts `ExProd sα` to `ExProd sβ`, assuming `sα` and `sβ` are defeq. -/
partial def ExProd.cast
{v : Lean.Level} {β : Q(Type v)} {sβ : Q(CommSemiring $β)} {a : Q($α)} :
ExProd sα a → Σ a, ExProd sβ a
| .const i h => ⟨a, .const i h⟩
| .mul a₁ a₂ a₃ => ⟨_, .mul a₁.cast.2 a₂ a₃.cast.2⟩
/-- Converts `ExSum sα` to `ExSum sβ`, assuming `sα` and `sβ` are defeq. -/
partial def ExSum.cast
{v : Lean.Level} {β : Q(Type v)} {sβ : Q(CommSemiring $β)} {a : Q($α)} :
ExSum sα a → Σ a, ExSum sβ a
| .zero => ⟨_, .zero⟩
| .add a₁ a₂ => ⟨_, .add a₁.cast.2 a₂.cast.2⟩
end
variable {u : Lean.Level}
/--
The result of evaluating an (unnormalized) expression `e` into the type family `E`
(one of `ExSum`, `ExProd`, `ExBase`) is a (normalized) element `e'`
and a representation `E e'` for it, and a proof of `e = e'`.
-/
structure Result {α : Q(Type u)} (E : Q($α) → Type) (e : Q($α)) where
/-- The normalized result. -/
expr : Q($α)
/-- The data associated to the normalization. -/
val : E expr
/-- A proof that the original expression is equal to the normalized result. -/
proof : Q($e = $expr)
instance {α : Q(Type u)} {E : Q($α) → Type} {e : Q($α)} [Inhabited (Σ e, E e)] :
Inhabited (Result E e) :=
let ⟨e', v⟩ : Σ e, E e := default; ⟨e', v, default⟩
variable {α : Q(Type u)} (sα : Q(CommSemiring $α)) {R : Type*} [CommSemiring R]
/--
Constructs the expression corresponding to `.const n`.
(The `.const` constructor does not check that the expression is correct.)
-/
def ExProd.mkNat (n : ℕ) : (e : Q($α)) × ExProd sα e :=
let lit : Q(ℕ) := mkRawNatLit n
⟨q(($lit).rawCast : $α), .const n none⟩
/--
Constructs the expression corresponding to `.const (-n)`.
(The `.const` constructor does not check that the expression is correct.)
-/
def ExProd.mkNegNat (_ : Q(Ring $α)) (n : ℕ) : (e : Q($α)) × ExProd sα e :=
let lit : Q(ℕ) := mkRawNatLit n
⟨q((Int.negOfNat $lit).rawCast : $α), .const (-n) none⟩
/--
Constructs the expression corresponding to `.const q h` for `q = n / d`
and `h` a proof that `(d : α) ≠ 0`.
(The `.const` constructor does not check that the expression is correct.)
-/
def ExProd.mkRat (_ : Q(DivisionRing $α)) (q : ℚ) (n : Q(ℤ)) (d : Q(ℕ)) (h : Expr) :
(e : Q($α)) × ExProd sα e :=
⟨q(Rat.rawCast $n $d : $α), .const q h⟩
section
/-- Embed an exponent (an `ExBase, ExProd` pair) as an `ExProd` by multiplying by 1. -/
def ExBase.toProd {α : Q(Type u)} {sα : Q(CommSemiring $α)} {a : Q($α)} {b : Q(ℕ)}
| (va : ExBase sα a) (vb : ExProd sℕ b) :
ExProd sα q($a ^ $b * (nat_lit 1).rawCast) := .mul va vb (.const 1 none)
| Mathlib/Tactic/Ring/Basic.lean | 280 | 281 |
/-
Copyright (c) 2020 Aaron Anderson, Jalex Stark, Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jalex Stark, Kyle Miller, Alena Gusakov, Hunter Monroe
-/
import Mathlib.Combinatorics.SimpleGraph.Init
import Mathlib.Data.Finite.Prod
import Mathlib.Data.Rel
import Mathlib.Data.Set.Finite.Basic
import Mathlib.Data.Sym.Sym2
/-!
# Simple graphs
This module defines simple graphs on a vertex type `V` as an irreflexive symmetric relation.
## Main definitions
* `SimpleGraph` is a structure for symmetric, irreflexive relations.
* `SimpleGraph.neighborSet` is the `Set` of vertices adjacent to a given vertex.
* `SimpleGraph.commonNeighbors` is the intersection of the neighbor sets of two given vertices.
* `SimpleGraph.incidenceSet` is the `Set` of edges containing a given vertex.
* `CompleteAtomicBooleanAlgebra` instance: Under the subgraph relation, `SimpleGraph` forms a
`CompleteAtomicBooleanAlgebra`. In other words, this is the complete lattice of spanning subgraphs
of the complete graph.
## TODO
* This is the simplest notion of an unoriented graph.
This should eventually fit into a more complete combinatorics hierarchy which includes
multigraphs and directed graphs.
We begin with simple graphs in order to start learning what the combinatorics hierarchy should
look like.
-/
attribute [aesop norm unfold (rule_sets := [SimpleGraph])] Symmetric
attribute [aesop norm unfold (rule_sets := [SimpleGraph])] Irreflexive
/--
A variant of the `aesop` tactic for use in the graph library. Changes relative
to standard `aesop`:
- We use the `SimpleGraph` rule set in addition to the default rule sets.
- We instruct Aesop's `intro` rule to unfold with `default` transparency.
- We instruct Aesop to fail if it can't fully solve the goal. This allows us to
use `aesop_graph` for auto-params.
-/
macro (name := aesop_graph) "aesop_graph" c:Aesop.tactic_clause* : tactic =>
`(tactic|
aesop $c*
(config := { introsTransparency? := some .default, terminal := true })
(rule_sets := [$(Lean.mkIdent `SimpleGraph):ident]))
/--
Use `aesop_graph?` to pass along a `Try this` suggestion when using `aesop_graph`
-/
macro (name := aesop_graph?) "aesop_graph?" c:Aesop.tactic_clause* : tactic =>
`(tactic|
aesop? $c*
(config := { introsTransparency? := some .default, terminal := true })
(rule_sets := [$(Lean.mkIdent `SimpleGraph):ident]))
/--
A variant of `aesop_graph` which does not fail if it is unable to solve the goal.
Use this only for exploration! Nonterminal Aesop is even worse than nonterminal `simp`.
-/
macro (name := aesop_graph_nonterminal) "aesop_graph_nonterminal" c:Aesop.tactic_clause* : tactic =>
`(tactic|
aesop $c*
(config := { introsTransparency? := some .default, warnOnNonterminal := false })
(rule_sets := [$(Lean.mkIdent `SimpleGraph):ident]))
open Finset Function
universe u v w
/-- A simple graph is an irreflexive symmetric relation `Adj` on a vertex type `V`.
The relation describes which pairs of vertices are adjacent.
There is exactly one edge for every pair of adjacent vertices;
see `SimpleGraph.edgeSet` for the corresponding edge set.
-/
@[ext, aesop safe constructors (rule_sets := [SimpleGraph])]
structure SimpleGraph (V : Type u) where
/-- The adjacency relation of a simple graph. -/
Adj : V → V → Prop
symm : Symmetric Adj := by aesop_graph
loopless : Irreflexive Adj := by aesop_graph
initialize_simps_projections SimpleGraph (Adj → adj)
/-- Constructor for simple graphs using a symmetric irreflexive boolean function. -/
@[simps]
def SimpleGraph.mk' {V : Type u} :
{adj : V → V → Bool // (∀ x y, adj x y = adj y x) ∧ (∀ x, ¬ adj x x)} ↪ SimpleGraph V where
toFun x := ⟨fun v w ↦ x.1 v w, fun v w ↦ by simp [x.2.1], fun v ↦ by simp [x.2.2]⟩
inj' := by
rintro ⟨adj, _⟩ ⟨adj', _⟩
simp only [mk.injEq, Subtype.mk.injEq]
intro h
funext v w
simpa [Bool.coe_iff_coe] using congr_fun₂ h v w
/-- We can enumerate simple graphs by enumerating all functions `V → V → Bool`
and filtering on whether they are symmetric and irreflexive. -/
instance {V : Type u} [Fintype V] [DecidableEq V] : Fintype (SimpleGraph V) where
elems := Finset.univ.map SimpleGraph.mk'
complete := by
classical
rintro ⟨Adj, hs, hi⟩
simp only [mem_map, mem_univ, true_and, Subtype.exists, Bool.not_eq_true]
refine ⟨fun v w ↦ Adj v w, ⟨?_, ?_⟩, ?_⟩
· simp [hs.iff]
· intro v; simp [hi v]
· ext
simp
/-- There are finitely many simple graphs on a given finite type. -/
instance SimpleGraph.instFinite {V : Type u} [Finite V] : Finite (SimpleGraph V) :=
.of_injective SimpleGraph.Adj fun _ _ ↦ SimpleGraph.ext
/-- Construct the simple graph induced by the given relation. It
symmetrizes the relation and makes it irreflexive. -/
def SimpleGraph.fromRel {V : Type u} (r : V → V → Prop) : SimpleGraph V where
Adj a b := a ≠ b ∧ (r a b ∨ r b a)
symm := fun _ _ ⟨hn, hr⟩ => ⟨hn.symm, hr.symm⟩
loopless := fun _ ⟨hn, _⟩ => hn rfl
@[simp]
theorem SimpleGraph.fromRel_adj {V : Type u} (r : V → V → Prop) (v w : V) :
(SimpleGraph.fromRel r).Adj v w ↔ v ≠ w ∧ (r v w ∨ r w v) :=
Iff.rfl
attribute [aesop safe (rule_sets := [SimpleGraph])] Ne.symm
attribute [aesop safe (rule_sets := [SimpleGraph])] Ne.irrefl
/-- The complete graph on a type `V` is the simple graph with all pairs of distinct vertices
adjacent. In `Mathlib`, this is usually referred to as `⊤`. -/
def completeGraph (V : Type u) : SimpleGraph V where Adj := Ne
/-- The graph with no edges on a given vertex type `V`. `Mathlib` prefers the notation `⊥`. -/
def emptyGraph (V : Type u) : SimpleGraph V where Adj _ _ := False
/-- Two vertices are adjacent in the complete bipartite graph on two vertex types
if and only if they are not from the same side.
Any bipartite graph may be regarded as a subgraph of one of these. -/
@[simps]
def completeBipartiteGraph (V W : Type*) : SimpleGraph (V ⊕ W) where
Adj v w := v.isLeft ∧ w.isRight ∨ v.isRight ∧ w.isLeft
symm v w := by cases v <;> cases w <;> simp
loopless v := by cases v <;> simp
namespace SimpleGraph
variable {ι : Sort*} {V : Type u} (G : SimpleGraph V) {a b c u v w : V} {e : Sym2 V}
@[simp]
protected theorem irrefl {v : V} : ¬G.Adj v v :=
G.loopless v
theorem adj_comm (u v : V) : G.Adj u v ↔ G.Adj v u :=
⟨fun x => G.symm x, fun x => G.symm x⟩
@[symm]
theorem adj_symm (h : G.Adj u v) : G.Adj v u :=
G.symm h
theorem Adj.symm {G : SimpleGraph V} {u v : V} (h : G.Adj u v) : G.Adj v u :=
G.symm h
theorem ne_of_adj (h : G.Adj a b) : a ≠ b := by
rintro rfl
exact G.irrefl h
protected theorem Adj.ne {G : SimpleGraph V} {a b : V} (h : G.Adj a b) : a ≠ b :=
G.ne_of_adj h
protected theorem Adj.ne' {G : SimpleGraph V} {a b : V} (h : G.Adj a b) : b ≠ a :=
h.ne.symm
theorem ne_of_adj_of_not_adj {v w x : V} (h : G.Adj v x) (hn : ¬G.Adj w x) : v ≠ w := fun h' =>
hn (h' ▸ h)
theorem adj_injective : Injective (Adj : SimpleGraph V → V → V → Prop) :=
fun _ _ => SimpleGraph.ext
@[simp]
theorem adj_inj {G H : SimpleGraph V} : G.Adj = H.Adj ↔ G = H :=
adj_injective.eq_iff
theorem adj_congr_of_sym2 {u v w x : V} (h : s(u, v) = s(w, x)) : G.Adj u v ↔ G.Adj w x := by
simp only [Sym2.eq, Sym2.rel_iff', Prod.mk.injEq, Prod.swap_prod_mk] at h
rcases h with hl | hr
· rw [hl.1, hl.2]
· rw [hr.1, hr.2, adj_comm]
section Order
/-- The relation that one `SimpleGraph` is a subgraph of another.
Note that this should be spelled `≤`. -/
def IsSubgraph (x y : SimpleGraph V) : Prop :=
∀ ⦃v w : V⦄, x.Adj v w → y.Adj v w
instance : LE (SimpleGraph V) :=
⟨IsSubgraph⟩
@[simp]
theorem isSubgraph_eq_le : (IsSubgraph : SimpleGraph V → SimpleGraph V → Prop) = (· ≤ ·) :=
rfl
/-- The supremum of two graphs `x ⊔ y` has edges where either `x` or `y` have edges. -/
instance : Max (SimpleGraph V) where
max x y :=
{ Adj := x.Adj ⊔ y.Adj
symm := fun v w h => by rwa [Pi.sup_apply, Pi.sup_apply, x.adj_comm, y.adj_comm] }
@[simp]
theorem sup_adj (x y : SimpleGraph V) (v w : V) : (x ⊔ y).Adj v w ↔ x.Adj v w ∨ y.Adj v w :=
Iff.rfl
/-- The infimum of two graphs `x ⊓ y` has edges where both `x` and `y` have edges. -/
instance : Min (SimpleGraph V) where
min x y :=
{ Adj := x.Adj ⊓ y.Adj
symm := fun v w h => by rwa [Pi.inf_apply, Pi.inf_apply, x.adj_comm, y.adj_comm] }
@[simp]
theorem inf_adj (x y : SimpleGraph V) (v w : V) : (x ⊓ y).Adj v w ↔ x.Adj v w ∧ y.Adj v w :=
Iff.rfl
/-- We define `Gᶜ` to be the `SimpleGraph V` such that no two adjacent vertices in `G`
are adjacent in the complement, and every nonadjacent pair of vertices is adjacent
(still ensuring that vertices are not adjacent to themselves). -/
instance hasCompl : HasCompl (SimpleGraph V) where
compl G :=
{ Adj := fun v w => v ≠ w ∧ ¬G.Adj v w
symm := fun v w ⟨hne, _⟩ => ⟨hne.symm, by rwa [adj_comm]⟩
loopless := fun _ ⟨hne, _⟩ => (hne rfl).elim }
@[simp]
theorem compl_adj (G : SimpleGraph V) (v w : V) : Gᶜ.Adj v w ↔ v ≠ w ∧ ¬G.Adj v w :=
Iff.rfl
/-- The difference of two graphs `x \ y` has the edges of `x` with the edges of `y` removed. -/
instance sdiff : SDiff (SimpleGraph V) where
sdiff x y :=
{ Adj := x.Adj \ y.Adj
symm := fun v w h => by change x.Adj w v ∧ ¬y.Adj w v; rwa [x.adj_comm, y.adj_comm] }
@[simp]
theorem sdiff_adj (x y : SimpleGraph V) (v w : V) : (x \ y).Adj v w ↔ x.Adj v w ∧ ¬y.Adj v w :=
Iff.rfl
instance supSet : SupSet (SimpleGraph V) where
sSup s :=
{ Adj := fun a b => ∃ G ∈ s, Adj G a b
symm := fun _ _ => Exists.imp fun _ => And.imp_right Adj.symm
loopless := by
rintro a ⟨G, _, ha⟩
exact ha.ne rfl }
instance infSet : InfSet (SimpleGraph V) where
sInf s :=
{ Adj := fun a b => (∀ ⦃G⦄, G ∈ s → Adj G a b) ∧ a ≠ b
symm := fun _ _ => And.imp (forall₂_imp fun _ _ => Adj.symm) Ne.symm
loopless := fun _ h => h.2 rfl }
@[simp]
theorem sSup_adj {s : Set (SimpleGraph V)} {a b : V} : (sSup s).Adj a b ↔ ∃ G ∈ s, Adj G a b :=
Iff.rfl
@[simp]
theorem sInf_adj {s : Set (SimpleGraph V)} : (sInf s).Adj a b ↔ (∀ G ∈ s, Adj G a b) ∧ a ≠ b :=
Iff.rfl
@[simp]
theorem iSup_adj {f : ι → SimpleGraph V} : (⨆ i, f i).Adj a b ↔ ∃ i, (f i).Adj a b := by simp [iSup]
@[simp]
theorem iInf_adj {f : ι → SimpleGraph V} : (⨅ i, f i).Adj a b ↔ (∀ i, (f i).Adj a b) ∧ a ≠ b := by
simp [iInf]
theorem sInf_adj_of_nonempty {s : Set (SimpleGraph V)} (hs : s.Nonempty) :
(sInf s).Adj a b ↔ ∀ G ∈ s, Adj G a b :=
sInf_adj.trans <|
and_iff_left_of_imp <| by
obtain ⟨G, hG⟩ := hs
exact fun h => (h _ hG).ne
theorem iInf_adj_of_nonempty [Nonempty ι] {f : ι → SimpleGraph V} :
(⨅ i, f i).Adj a b ↔ ∀ i, (f i).Adj a b := by
rw [iInf, sInf_adj_of_nonempty (Set.range_nonempty _), Set.forall_mem_range]
/-- For graphs `G`, `H`, `G ≤ H` iff `∀ a b, G.Adj a b → H.Adj a b`. -/
instance distribLattice : DistribLattice (SimpleGraph V) :=
{ show DistribLattice (SimpleGraph V) from
adj_injective.distribLattice _ (fun _ _ => rfl) fun _ _ => rfl with
le := fun G H => ∀ ⦃a b⦄, G.Adj a b → H.Adj a b }
instance completeAtomicBooleanAlgebra : CompleteAtomicBooleanAlgebra (SimpleGraph V) :=
{ SimpleGraph.distribLattice with
le := (· ≤ ·)
sup := (· ⊔ ·)
inf := (· ⊓ ·)
compl := HasCompl.compl
sdiff := (· \ ·)
top := completeGraph V
bot := emptyGraph V
le_top := fun x _ _ h => x.ne_of_adj h
bot_le := fun _ _ _ h => h.elim
sdiff_eq := fun x y => by
ext v w
refine ⟨fun h => ⟨h.1, ⟨?_, h.2⟩⟩, fun h => ⟨h.1, h.2.2⟩⟩
rintro rfl
exact x.irrefl h.1
inf_compl_le_bot := fun _ _ _ h => False.elim <| h.2.2 h.1
top_le_sup_compl := fun G v w hvw => by
by_cases h : G.Adj v w
· exact Or.inl h
· exact Or.inr ⟨hvw, h⟩
sSup := sSup
le_sSup := fun _ G hG _ _ hab => ⟨G, hG, hab⟩
sSup_le := fun s G hG a b => by
rintro ⟨H, hH, hab⟩
exact hG _ hH hab
sInf := sInf
sInf_le := fun _ _ hG _ _ hab => hab.1 hG
le_sInf := fun _ _ hG _ _ hab => ⟨fun _ hH => hG _ hH hab, hab.ne⟩
iInf_iSup_eq := fun f => by ext; simp [Classical.skolem] }
@[simp]
theorem top_adj (v w : V) : (⊤ : SimpleGraph V).Adj v w ↔ v ≠ w :=
Iff.rfl
@[simp]
theorem bot_adj (v w : V) : (⊥ : SimpleGraph V).Adj v w ↔ False :=
Iff.rfl
@[simp]
theorem completeGraph_eq_top (V : Type u) : completeGraph V = ⊤ :=
rfl
@[simp]
theorem emptyGraph_eq_bot (V : Type u) : emptyGraph V = ⊥ :=
rfl
@[simps]
instance (V : Type u) : Inhabited (SimpleGraph V) :=
⟨⊥⟩
instance [Subsingleton V] : Unique (SimpleGraph V) where
default := ⊥
uniq G := by ext a b; have := Subsingleton.elim a b; simp [this]
instance [Nontrivial V] : Nontrivial (SimpleGraph V) :=
⟨⟨⊥, ⊤, fun h ↦ not_subsingleton V ⟨by simpa only [← adj_inj, funext_iff, bot_adj,
top_adj, ne_eq, eq_iff_iff, false_iff, not_not] using h⟩⟩⟩
section Decidable
variable (V) (H : SimpleGraph V) [DecidableRel G.Adj] [DecidableRel H.Adj]
instance Bot.adjDecidable : DecidableRel (⊥ : SimpleGraph V).Adj :=
inferInstanceAs <| DecidableRel fun _ _ => False
instance Sup.adjDecidable : DecidableRel (G ⊔ H).Adj :=
inferInstanceAs <| DecidableRel fun v w => G.Adj v w ∨ H.Adj v w
instance Inf.adjDecidable : DecidableRel (G ⊓ H).Adj :=
inferInstanceAs <| DecidableRel fun v w => G.Adj v w ∧ H.Adj v w
instance Sdiff.adjDecidable : DecidableRel (G \ H).Adj :=
inferInstanceAs <| DecidableRel fun v w => G.Adj v w ∧ ¬H.Adj v w
variable [DecidableEq V]
instance Top.adjDecidable : DecidableRel (⊤ : SimpleGraph V).Adj :=
inferInstanceAs <| DecidableRel fun v w => v ≠ w
instance Compl.adjDecidable : DecidableRel (Gᶜ.Adj) :=
inferInstanceAs <| DecidableRel fun v w => v ≠ w ∧ ¬G.Adj v w
end Decidable
end Order
/-- `G.support` is the set of vertices that form edges in `G`. -/
def support : Set V :=
Rel.dom G.Adj
theorem mem_support {v : V} : v ∈ G.support ↔ ∃ w, G.Adj v w :=
Iff.rfl
theorem support_mono {G G' : SimpleGraph V} (h : G ≤ G') : G.support ⊆ G'.support :=
Rel.dom_mono h
/-- `G.neighborSet v` is the set of vertices adjacent to `v` in `G`. -/
def neighborSet (v : V) : Set V := {w | G.Adj v w}
instance neighborSet.memDecidable (v : V) [DecidableRel G.Adj] :
DecidablePred (· ∈ G.neighborSet v) :=
inferInstanceAs <| DecidablePred (Adj G v)
lemma neighborSet_subset_support (v : V) : G.neighborSet v ⊆ G.support :=
fun _ hadj ↦ ⟨v, hadj.symm⟩
section EdgeSet
variable {G₁ G₂ : SimpleGraph V}
/-- The edges of G consist of the unordered pairs of vertices related by
`G.Adj`. This is the order embedding; for the edge set of a particular graph, see
`SimpleGraph.edgeSet`.
The way `edgeSet` is defined is such that `mem_edgeSet` is proved by `Iff.rfl`.
(That is, `s(v, w) ∈ G.edgeSet` is definitionally equal to `G.Adj v w`.)
-/
-- Porting note: We need a separate definition so that dot notation works.
def edgeSetEmbedding (V : Type*) : SimpleGraph V ↪o Set (Sym2 V) :=
OrderEmbedding.ofMapLEIff (fun G => Sym2.fromRel G.symm) fun _ _ =>
⟨fun h a b => @h s(a, b), fun h e => Sym2.ind @h e⟩
/-- `G.edgeSet` is the edge set for `G`.
This is an abbreviation for `edgeSetEmbedding G` that permits dot notation. -/
abbrev edgeSet (G : SimpleGraph V) : Set (Sym2 V) := edgeSetEmbedding V G
@[simp]
theorem mem_edgeSet : s(v, w) ∈ G.edgeSet ↔ G.Adj v w :=
Iff.rfl
theorem not_isDiag_of_mem_edgeSet : e ∈ edgeSet G → ¬e.IsDiag :=
Sym2.ind (fun _ _ => Adj.ne) e
theorem edgeSet_inj : G₁.edgeSet = G₂.edgeSet ↔ G₁ = G₂ := (edgeSetEmbedding V).eq_iff_eq
@[simp]
theorem edgeSet_subset_edgeSet : edgeSet G₁ ⊆ edgeSet G₂ ↔ G₁ ≤ G₂ :=
(edgeSetEmbedding V).le_iff_le
@[simp]
theorem edgeSet_ssubset_edgeSet : edgeSet G₁ ⊂ edgeSet G₂ ↔ G₁ < G₂ :=
(edgeSetEmbedding V).lt_iff_lt
theorem edgeSet_injective : Injective (edgeSet : SimpleGraph V → Set (Sym2 V)) :=
(edgeSetEmbedding V).injective
alias ⟨_, edgeSet_mono⟩ := edgeSet_subset_edgeSet
alias ⟨_, edgeSet_strict_mono⟩ := edgeSet_ssubset_edgeSet
attribute [mono] edgeSet_mono edgeSet_strict_mono
variable (G₁ G₂)
@[simp]
theorem edgeSet_bot : (⊥ : SimpleGraph V).edgeSet = ∅ :=
Sym2.fromRel_bot
@[simp]
theorem edgeSet_top : (⊤ : SimpleGraph V).edgeSet = {e | ¬e.IsDiag} :=
Sym2.fromRel_ne
@[simp]
theorem edgeSet_subset_setOf_not_isDiag : G.edgeSet ⊆ {e | ¬e.IsDiag} :=
fun _ h => (Sym2.fromRel_irreflexive (sym := G.symm)).mp G.loopless h
@[simp]
theorem edgeSet_sup : (G₁ ⊔ G₂).edgeSet = G₁.edgeSet ∪ G₂.edgeSet := by
ext ⟨x, y⟩
rfl
@[simp]
theorem edgeSet_inf : (G₁ ⊓ G₂).edgeSet = G₁.edgeSet ∩ G₂.edgeSet := by
ext ⟨x, y⟩
rfl
@[simp]
theorem edgeSet_sdiff : (G₁ \ G₂).edgeSet = G₁.edgeSet \ G₂.edgeSet := by
ext ⟨x, y⟩
rfl
variable {G G₁ G₂}
@[simp] lemma disjoint_edgeSet : Disjoint G₁.edgeSet G₂.edgeSet ↔ Disjoint G₁ G₂ := by
rw [Set.disjoint_iff, disjoint_iff_inf_le, ← edgeSet_inf, ← edgeSet_bot, ← Set.le_iff_subset,
OrderEmbedding.le_iff_le]
@[simp] lemma edgeSet_eq_empty : G.edgeSet = ∅ ↔ G = ⊥ := by rw [← edgeSet_bot, edgeSet_inj]
@[simp] lemma edgeSet_nonempty : G.edgeSet.Nonempty ↔ G ≠ ⊥ := by
rw [Set.nonempty_iff_ne_empty, edgeSet_eq_empty.ne]
/-- This lemma, combined with `edgeSet_sdiff` and `edgeSet_from_edgeSet`,
allows proving `(G \ from_edgeSet s).edge_set = G.edgeSet \ s` by `simp`. -/
@[simp]
theorem edgeSet_sdiff_sdiff_isDiag (G : SimpleGraph V) (s : Set (Sym2 V)) :
G.edgeSet \ (s \ { e | e.IsDiag }) = G.edgeSet \ s := by
ext e
simp only [Set.mem_diff, Set.mem_setOf_eq, not_and, not_not, and_congr_right_iff]
intro h
simp only [G.not_isDiag_of_mem_edgeSet h, imp_false]
/-- Two vertices are adjacent iff there is an edge between them. The
condition `v ≠ w` ensures they are different endpoints of the edge,
which is necessary since when `v = w` the existential
`∃ (e ∈ G.edgeSet), v ∈ e ∧ w ∈ e` is satisfied by every edge
incident to `v`. -/
theorem adj_iff_exists_edge {v w : V} : G.Adj v w ↔ v ≠ w ∧ ∃ e ∈ G.edgeSet, v ∈ e ∧ w ∈ e := by
refine ⟨fun _ => ⟨G.ne_of_adj ‹_›, s(v, w), by simpa⟩, ?_⟩
rintro ⟨hne, e, he, hv⟩
rw [Sym2.mem_and_mem_iff hne] at hv
subst e
rwa [mem_edgeSet] at he
theorem adj_iff_exists_edge_coe : G.Adj a b ↔ ∃ e : G.edgeSet, e.val = s(a, b) := by
simp only [mem_edgeSet, exists_prop, SetCoe.exists, exists_eq_right, Subtype.coe_mk]
variable (G G₁ G₂)
theorem edge_other_ne {e : Sym2 V} (he : e ∈ G.edgeSet) {v : V} (h : v ∈ e) :
Sym2.Mem.other h ≠ v := by
rw [← Sym2.other_spec h, Sym2.eq_swap] at he
exact G.ne_of_adj he
instance decidableMemEdgeSet [DecidableRel G.Adj] : DecidablePred (· ∈ G.edgeSet) :=
Sym2.fromRel.decidablePred G.symm
instance fintypeEdgeSet [Fintype (Sym2 V)] [DecidableRel G.Adj] : Fintype G.edgeSet :=
| Subtype.fintype _
instance fintypeEdgeSetBot : Fintype (⊥ : SimpleGraph V).edgeSet := by
| Mathlib/Combinatorics/SimpleGraph/Basic.lean | 532 | 534 |
/-
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.RingTheory.IntegralClosure.IntegrallyClosed
import Mathlib.RingTheory.Trace.Basic
import Mathlib.RingTheory.Norm.Basic
/-!
# Discriminant of a family of vectors
Given an `A`-algebra `B` and `b`, an `ι`-indexed family of elements of `B`, we define the
*discriminant* of `b` as the determinant of the matrix whose `(i j)`-th element is the trace of
`b i * b j`.
## Main definition
* `Algebra.discr A b` : the discriminant of `b : ι → B`.
## Main results
* `Algebra.discr_zero_of_not_linearIndependent` : if `b` is not linear independent, then
`Algebra.discr A b = 0`.
* `Algebra.discr_of_matrix_vecMul` and `Algebra.discr_of_matrix_mulVec` : formulas relating
`Algebra.discr A ι b` with `Algebra.discr A (b ᵥ* P.map (algebraMap A B))` and
`Algebra.discr A (P.map (algebraMap A B) *ᵥ b)`.
* `Algebra.discr_not_zero_of_basis` : over a field, if `b` is a basis, then
`Algebra.discr K b ≠ 0`.
* `Algebra.discr_eq_det_embeddingsMatrixReindex_pow_two` : if `L/K` is a field extension and
`b : ι → L`, then `discr K b` is the square of the determinant of the matrix whose `(i, j)`
coefficient is `σⱼ (b i)`, where `σⱼ : L →ₐ[K] E` is the embedding in an algebraically closed
field `E` corresponding to `j : ι` via a bijection `e : ι ≃ (L →ₐ[K] E)`.
* `Algebra.discr_powerBasis_eq_prod` : the discriminant of a power basis.
* `Algebra.discr_isIntegral` : if `K` and `L` are fields and `IsScalarTower R K L`, if
`b : ι → L` satisfies `∀ i, IsIntegral R (b i)`, then `IsIntegral R (discr K b)`.
* `Algebra.discr_mul_isIntegral_mem_adjoin` : let `K` be the fraction field of an integrally
closed domain `R` and let `L` be a finite separable extension of `K`. Let `B : PowerBasis K L`
be such that `IsIntegral R B.gen`. Then for all, `z : L` we have
`(discr K B.basis) • z ∈ adjoin R ({B.gen} : Set L)`.
## Implementation details
Our definition works for any `A`-algebra `B`, but note that if `B` is not free as an `A`-module,
then `trace A B = 0` by definition, so `discr A b = 0` for any `b`.
-/
universe u v w z
open scoped Matrix
open Matrix Module Fintype Polynomial Finset IntermediateField
namespace Algebra
variable (A : Type u) {B : Type v} (C : Type z) {ι : Type w} [DecidableEq ι]
variable [CommRing A] [CommRing B] [Algebra A B] [CommRing C] [Algebra A C]
section Discr
/-- Given an `A`-algebra `B` and `b`, an `ι`-indexed family of elements of `B`, we define
`discr A ι b` as the determinant of `traceMatrix A ι b`. -/
-- Porting note: using `[DecidableEq ι]` instead of `by classical...` did not work in
-- mathlib3.
noncomputable def discr (A : Type u) {B : Type v} [CommRing A] [CommRing B] [Algebra A B]
[Fintype ι] (b : ι → B) := (traceMatrix A b).det
theorem discr_def [Fintype ι] (b : ι → B) : discr A b = (traceMatrix A b).det := rfl
variable {A C} in
/-- Mapping a family of vectors along an `AlgEquiv` preserves the discriminant. -/
theorem discr_eq_discr_of_algEquiv [Fintype ι] (b : ι → B) (f : B ≃ₐ[A] C) :
Algebra.discr A b = Algebra.discr A (f ∘ b) := by
rw [discr_def]; congr; ext
simp_rw [traceMatrix_apply, traceForm_apply, Function.comp, ← map_mul f, trace_eq_of_algEquiv]
variable {ι' : Type*} [Fintype ι'] [Fintype ι] [DecidableEq ι']
section Basic
@[simp]
theorem discr_reindex (b : Basis ι A B) (f : ι ≃ ι') : discr A (b ∘ ⇑f.symm) = discr A b := by
classical rw [← Basis.coe_reindex, discr_def, traceMatrix_reindex, det_reindex_self, ← discr_def]
/-- If `b` is not linear independent, then `Algebra.discr A b = 0`. -/
theorem discr_zero_of_not_linearIndependent [IsDomain A] {b : ι → B}
(hli : ¬LinearIndependent A b) : discr A b = 0 := by
classical
obtain ⟨g, hg, i, hi⟩ := Fintype.not_linearIndependent_iff.1 hli
have : (traceMatrix A b) *ᵥ g = 0 := by
ext i
have : ∀ j, (trace A B) (b i * b j) * g j = (trace A B) (g j • b j * b i) := by
intro j
simp [mul_comm]
simp only [mulVec, dotProduct, traceMatrix_apply, Pi.zero_apply, traceForm_apply, fun j =>
this j, ← map_sum, ← sum_mul, hg, zero_mul, LinearMap.map_zero]
by_contra h
rw [discr_def] at h
simp [Matrix.eq_zero_of_mulVec_eq_zero h this] at hi
variable {A}
/-- Relation between `Algebra.discr A ι b` and
`Algebra.discr A (b ᵥ* P.map (algebraMap A B))`. -/
theorem discr_of_matrix_vecMul (b : ι → B) (P : Matrix ι ι A) :
discr A (b ᵥ* P.map (algebraMap A B)) = P.det ^ 2 * discr A b := by
rw [discr_def, traceMatrix_of_matrix_vecMul, det_mul, det_mul, det_transpose, mul_comm, ←
mul_assoc, discr_def, pow_two]
/-- Relation between `Algebra.discr A ι b` and
`Algebra.discr A ((P.map (algebraMap A B)) *ᵥ b)`. -/
theorem discr_of_matrix_mulVec (b : ι → B) (P : Matrix ι ι A) :
discr A (P.map (algebraMap A B) *ᵥ b) = P.det ^ 2 * discr A b := by
rw [discr_def, traceMatrix_of_matrix_mulVec, det_mul, det_mul, det_transpose, mul_comm, ←
mul_assoc, discr_def, pow_two]
end Basic
section Field
variable (K : Type u) {L : Type v} (E : Type z) [Field K] [Field L] [Field E]
variable [Algebra K L] [Algebra K E]
variable [Module.Finite K L] [IsAlgClosed E]
/-- If `b` is a basis of a finite separable field extension `L/K`, then `Algebra.discr K b ≠ 0`. -/
theorem discr_not_zero_of_basis [Algebra.IsSeparable K L] (b : Basis ι K L) :
discr K b ≠ 0 := by
rw [discr_def, traceMatrix_of_basis, ← LinearMap.BilinForm.nondegenerate_iff_det_ne_zero]
exact traceForm_nondegenerate _ _
/-- If `b` is a basis of a finite separable field extension `L/K`,
then `Algebra.discr K b` is a unit. -/
theorem discr_isUnit_of_basis [Algebra.IsSeparable K L] (b : Basis ι K L) : IsUnit (discr K b) :=
IsUnit.mk0 _ (discr_not_zero_of_basis _ _)
variable (b : ι → L) (pb : PowerBasis K L)
/-- If `L/K` is a field extension and `b : ι → L`, then `discr K b` is the square of the
determinant of the matrix whose `(i, j)` coefficient is `σⱼ (b i)`, where `σⱼ : L →ₐ[K] E` is the
embedding in an algebraically closed field `E` corresponding to `j : ι` via a bijection
`e : ι ≃ (L →ₐ[K] E)`. -/
theorem discr_eq_det_embeddingsMatrixReindex_pow_two
[Algebra.IsSeparable K L] (e : ι ≃ (L →ₐ[K] E)) :
algebraMap K E (discr K b) = (embeddingsMatrixReindex K E b e).det ^ 2 := by
rw [discr_def, RingHom.map_det, RingHom.mapMatrix_apply,
traceMatrix_eq_embeddingsMatrixReindex_mul_trans, det_mul, det_transpose, pow_two]
/-- The discriminant of a power basis. -/
theorem discr_powerBasis_eq_prod (e : Fin pb.dim ≃ (L →ₐ[K] E)) [Algebra.IsSeparable K L] :
algebraMap K E (discr K pb.basis) =
∏ i : Fin pb.dim, ∏ j ∈ Ioi i, (e j pb.gen - e i pb.gen) ^ 2 := by
rw [discr_eq_det_embeddingsMatrixReindex_pow_two K E pb.basis e,
embeddingsMatrixReindex_eq_vandermonde, det_transpose, det_vandermonde, ← prod_pow]
congr; ext i
rw [← prod_pow]
/-- A variation of `Algebra.discr_powerBasis_eq_prod`. -/
theorem discr_powerBasis_eq_prod' [Algebra.IsSeparable K L] (e : Fin pb.dim ≃ (L →ₐ[K] E)) :
algebraMap K E (discr K pb.basis) =
∏ i : Fin pb.dim, ∏ j ∈ Ioi i, -((e j pb.gen - e i pb.gen) * (e i pb.gen - e j pb.gen)) := by
rw [discr_powerBasis_eq_prod _ _ _ e]
congr; ext i; congr; ext j
ring
local notation "n" => finrank K L
/-- A variation of `Algebra.discr_powerBasis_eq_prod`. -/
theorem discr_powerBasis_eq_prod'' [Algebra.IsSeparable K L] (e : Fin pb.dim ≃ (L →ₐ[K] E)) :
algebraMap K E (discr K pb.basis) =
| (-1) ^ (n * (n - 1) / 2) *
∏ i : Fin pb.dim, ∏ j ∈ Ioi i, (e j pb.gen - e i pb.gen) * (e i pb.gen - e j pb.gen) := by
rw [discr_powerBasis_eq_prod' _ _ _ e]
simp_rw [fun i j => neg_eq_neg_one_mul ((e j pb.gen - e i pb.gen) * (e i pb.gen - e j pb.gen)),
prod_mul_distrib]
congr
| Mathlib/RingTheory/Discriminant.lean | 171 | 176 |
/-
Copyright (c) 2019 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Analytic.Constructions
import Mathlib.Analysis.Calculus.FDeriv.Analytic
import Mathlib.Analysis.Calculus.FDeriv.Bilinear
/-!
# Multiplicative operations on derivatives
For detailed documentation of the Fréchet derivative,
see the module docstring of `Mathlib/Analysis/Calculus/FDeriv/Basic.lean`.
This file contains the usual formulas (and existence assertions) for the derivative of
* multiplication of a function by a scalar function
* product of finitely many scalar functions
* taking the pointwise multiplicative inverse (i.e. `Inv.inv` or `Ring.inverse`) of a function
-/
open Asymptotics ContinuousLinearMap Topology
section
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
variable {f : E → F}
variable {f' : E →L[𝕜] F}
variable {x : E}
variable {s : Set E}
section CLMCompApply
/-! ### Derivative of the pointwise composition/application of continuous linear maps -/
variable {H : Type*} [NormedAddCommGroup H] [NormedSpace 𝕜 H] {c : E → G →L[𝕜] H}
{c' : E →L[𝕜] G →L[𝕜] H} {d : E → F →L[𝕜] G} {d' : E →L[𝕜] F →L[𝕜] G} {u : E → G} {u' : E →L[𝕜] G}
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
split proof term into steps to solve unification issues. -/
@[fun_prop]
theorem HasStrictFDerivAt.clm_comp (hc : HasStrictFDerivAt c c' x) (hd : HasStrictFDerivAt d d' x) :
HasStrictFDerivAt (fun y => (c y).comp (d y))
((compL 𝕜 F G H (c x)).comp d' + ((compL 𝕜 F G H).flip (d x)).comp c') x := by
have := isBoundedBilinearMap_comp.hasStrictFDerivAt (c x, d x)
have := this.comp x (hc.prodMk hd)
exact this
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.clm_comp (hc : HasFDerivWithinAt c c' s x)
(hd : HasFDerivWithinAt d d' s x) :
HasFDerivWithinAt (fun y => (c y).comp (d y))
((compL 𝕜 F G H (c x)).comp d' + ((compL 𝕜 F G H).flip (d x)).comp c') s x := by
exact (isBoundedBilinearMap_comp.hasFDerivAt (c x, d x) :).comp_hasFDerivWithinAt x (hc.prodMk hd)
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.clm_comp (hc : HasFDerivAt c c' x) (hd : HasFDerivAt d d' x) :
HasFDerivAt (fun y => (c y).comp (d y))
((compL 𝕜 F G H (c x)).comp d' + ((compL 𝕜 F G H).flip (d x)).comp c') x := by
exact (isBoundedBilinearMap_comp.hasFDerivAt (c x, d x) :).comp x <| hc.prodMk hd
@[fun_prop]
theorem DifferentiableWithinAt.clm_comp (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
DifferentiableWithinAt 𝕜 (fun y => (c y).comp (d y)) s x :=
(hc.hasFDerivWithinAt.clm_comp hd.hasFDerivWithinAt).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.clm_comp (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
DifferentiableAt 𝕜 (fun y => (c y).comp (d y)) x :=
(hc.hasFDerivAt.clm_comp hd.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.clm_comp (hc : DifferentiableOn 𝕜 c s) (hd : DifferentiableOn 𝕜 d s) :
DifferentiableOn 𝕜 (fun y => (c y).comp (d y)) s := fun x hx => (hc x hx).clm_comp (hd x hx)
@[fun_prop]
theorem Differentiable.clm_comp (hc : Differentiable 𝕜 c) (hd : Differentiable 𝕜 d) :
Differentiable 𝕜 fun y => (c y).comp (d y) := fun x => (hc x).clm_comp (hd x)
theorem fderivWithin_clm_comp (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
fderivWithin 𝕜 (fun y => (c y).comp (d y)) s x =
(compL 𝕜 F G H (c x)).comp (fderivWithin 𝕜 d s x) +
((compL 𝕜 F G H).flip (d x)).comp (fderivWithin 𝕜 c s x) :=
(hc.hasFDerivWithinAt.clm_comp hd.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_clm_comp (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
fderiv 𝕜 (fun y => (c y).comp (d y)) x =
(compL 𝕜 F G H (c x)).comp (fderiv 𝕜 d x) +
((compL 𝕜 F G H).flip (d x)).comp (fderiv 𝕜 c x) :=
(hc.hasFDerivAt.clm_comp hd.hasFDerivAt).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.clm_apply (hc : HasStrictFDerivAt c c' x)
(hu : HasStrictFDerivAt u u' x) :
HasStrictFDerivAt (fun y => (c y) (u y)) ((c x).comp u' + c'.flip (u x)) x :=
(isBoundedBilinearMap_apply.hasStrictFDerivAt (c x, u x)).comp x (hc.prodMk hu)
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.clm_apply (hc : HasFDerivWithinAt c c' s x)
(hu : HasFDerivWithinAt u u' s x) :
HasFDerivWithinAt (fun y => (c y) (u y)) ((c x).comp u' + c'.flip (u x)) s x := by
exact (isBoundedBilinearMap_apply.hasFDerivAt (c x, u x) :).comp_hasFDerivWithinAt x
(hc.prodMk hu)
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.clm_apply (hc : HasFDerivAt c c' x) (hu : HasFDerivAt u u' x) :
HasFDerivAt (fun y => (c y) (u y)) ((c x).comp u' + c'.flip (u x)) x := by
exact (isBoundedBilinearMap_apply.hasFDerivAt (c x, u x) :).comp x (hc.prodMk hu)
@[fun_prop]
theorem DifferentiableWithinAt.clm_apply (hc : DifferentiableWithinAt 𝕜 c s x)
(hu : DifferentiableWithinAt 𝕜 u s x) : DifferentiableWithinAt 𝕜 (fun y => (c y) (u y)) s x :=
(hc.hasFDerivWithinAt.clm_apply hu.hasFDerivWithinAt).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.clm_apply (hc : DifferentiableAt 𝕜 c x) (hu : DifferentiableAt 𝕜 u x) :
DifferentiableAt 𝕜 (fun y => (c y) (u y)) x :=
(hc.hasFDerivAt.clm_apply hu.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.clm_apply (hc : DifferentiableOn 𝕜 c s) (hu : DifferentiableOn 𝕜 u s) :
DifferentiableOn 𝕜 (fun y => (c y) (u y)) s := fun x hx => (hc x hx).clm_apply (hu x hx)
@[fun_prop]
theorem Differentiable.clm_apply (hc : Differentiable 𝕜 c) (hu : Differentiable 𝕜 u) :
Differentiable 𝕜 fun y => (c y) (u y) := fun x => (hc x).clm_apply (hu x)
theorem fderivWithin_clm_apply (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (hu : DifferentiableWithinAt 𝕜 u s x) :
fderivWithin 𝕜 (fun y => (c y) (u y)) s x =
(c x).comp (fderivWithin 𝕜 u s x) + (fderivWithin 𝕜 c s x).flip (u x) :=
(hc.hasFDerivWithinAt.clm_apply hu.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_clm_apply (hc : DifferentiableAt 𝕜 c x) (hu : DifferentiableAt 𝕜 u x) :
fderiv 𝕜 (fun y => (c y) (u y)) x = (c x).comp (fderiv 𝕜 u x) + (fderiv 𝕜 c x).flip (u x) :=
(hc.hasFDerivAt.clm_apply hu.hasFDerivAt).fderiv
end CLMCompApply
section ContinuousMultilinearApplyConst
/-! ### Derivative of the application of continuous multilinear maps to a constant -/
variable {ι : Type*} [Fintype ι]
{M : ι → Type*} [∀ i, NormedAddCommGroup (M i)] [∀ i, NormedSpace 𝕜 (M i)]
{H : Type*} [NormedAddCommGroup H] [NormedSpace 𝕜 H]
{c : E → ContinuousMultilinearMap 𝕜 M H}
{c' : E →L[𝕜] ContinuousMultilinearMap 𝕜 M H}
@[fun_prop]
theorem HasStrictFDerivAt.continuousMultilinear_apply_const (hc : HasStrictFDerivAt c c' x)
(u : ∀ i, M i) : HasStrictFDerivAt (fun y ↦ (c y) u) (c'.flipMultilinear u) x :=
(ContinuousMultilinearMap.apply 𝕜 M H u).hasStrictFDerivAt.comp x hc
@[fun_prop]
theorem HasFDerivWithinAt.continuousMultilinear_apply_const (hc : HasFDerivWithinAt c c' s x)
(u : ∀ i, M i) :
HasFDerivWithinAt (fun y ↦ (c y) u) (c'.flipMultilinear u) s x :=
(ContinuousMultilinearMap.apply 𝕜 M H u).hasFDerivAt.comp_hasFDerivWithinAt x hc
@[fun_prop]
theorem HasFDerivAt.continuousMultilinear_apply_const (hc : HasFDerivAt c c' x) (u : ∀ i, M i) :
HasFDerivAt (fun y ↦ (c y) u) (c'.flipMultilinear u) x :=
(ContinuousMultilinearMap.apply 𝕜 M H u).hasFDerivAt.comp x hc
@[fun_prop]
theorem DifferentiableWithinAt.continuousMultilinear_apply_const
(hc : DifferentiableWithinAt 𝕜 c s x) (u : ∀ i, M i) :
DifferentiableWithinAt 𝕜 (fun y ↦ (c y) u) s x :=
(hc.hasFDerivWithinAt.continuousMultilinear_apply_const u).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.continuousMultilinear_apply_const (hc : DifferentiableAt 𝕜 c x)
(u : ∀ i, M i) :
DifferentiableAt 𝕜 (fun y ↦ (c y) u) x :=
(hc.hasFDerivAt.continuousMultilinear_apply_const u).differentiableAt
@[fun_prop]
theorem DifferentiableOn.continuousMultilinear_apply_const (hc : DifferentiableOn 𝕜 c s)
(u : ∀ i, M i) : DifferentiableOn 𝕜 (fun y ↦ (c y) u) s :=
fun x hx ↦ (hc x hx).continuousMultilinear_apply_const u
@[fun_prop]
theorem Differentiable.continuousMultilinear_apply_const (hc : Differentiable 𝕜 c) (u : ∀ i, M i) :
Differentiable 𝕜 fun y ↦ (c y) u := fun x ↦ (hc x).continuousMultilinear_apply_const u
theorem fderivWithin_continuousMultilinear_apply_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (u : ∀ i, M i) :
fderivWithin 𝕜 (fun y ↦ (c y) u) s x = ((fderivWithin 𝕜 c s x).flipMultilinear u) :=
(hc.hasFDerivWithinAt.continuousMultilinear_apply_const u).fderivWithin hxs
theorem fderiv_continuousMultilinear_apply_const (hc : DifferentiableAt 𝕜 c x) (u : ∀ i, M i) :
(fderiv 𝕜 (fun y ↦ (c y) u) x) = (fderiv 𝕜 c x).flipMultilinear u :=
(hc.hasFDerivAt.continuousMultilinear_apply_const u).fderiv
/-- Application of a `ContinuousMultilinearMap` to a constant commutes with `fderivWithin`. -/
theorem fderivWithin_continuousMultilinear_apply_const_apply (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (u : ∀ i, M i) (m : E) :
(fderivWithin 𝕜 (fun y ↦ (c y) u) s x) m = (fderivWithin 𝕜 c s x) m u := by
simp [fderivWithin_continuousMultilinear_apply_const hxs hc]
/-- Application of a `ContinuousMultilinearMap` to a constant commutes with `fderiv`. -/
theorem fderiv_continuousMultilinear_apply_const_apply (hc : DifferentiableAt 𝕜 c x)
(u : ∀ i, M i) (m : E) :
(fderiv 𝕜 (fun y ↦ (c y) u) x) m = (fderiv 𝕜 c x) m u := by
simp [fderiv_continuousMultilinear_apply_const hc]
end ContinuousMultilinearApplyConst
section SMul
/-! ### Derivative of the product of a scalar-valued function and a vector-valued function
If `c` is a differentiable scalar-valued function and `f` is a differentiable vector-valued
function, then `fun x ↦ c x • f x` is differentiable as well. Lemmas in this section works for
function `c` taking values in the base field, as well as in a normed algebra over the base
field: e.g., they work for `c : E → ℂ` and `f : E → F` provided that `F` is a complex
normed vector space.
-/
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F]
[IsScalarTower 𝕜 𝕜' F]
variable {c : E → 𝕜'} {c' : E →L[𝕜] 𝕜'}
@[fun_prop]
theorem HasStrictFDerivAt.smul (hc : HasStrictFDerivAt c c' x) (hf : HasStrictFDerivAt f f' x) :
HasStrictFDerivAt (fun y => c y • f y) (c x • f' + c'.smulRight (f x)) x :=
(isBoundedBilinearMap_smul.hasStrictFDerivAt (c x, f x)).comp x <| hc.prodMk hf
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.smul (hc : HasFDerivWithinAt c c' s x) (hf : HasFDerivWithinAt f f' s x) :
HasFDerivWithinAt (fun y => c y • f y) (c x • f' + c'.smulRight (f x)) s x := by
exact (isBoundedBilinearMap_smul.hasFDerivAt (𝕜 := 𝕜) (c x, f x) :).comp_hasFDerivWithinAt x <|
hc.prodMk hf
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.smul (hc : HasFDerivAt c c' x) (hf : HasFDerivAt f f' x) :
HasFDerivAt (fun y => c y • f y) (c x • f' + c'.smulRight (f x)) x := by
exact (isBoundedBilinearMap_smul.hasFDerivAt (𝕜 := 𝕜) (c x, f x) :).comp x <| hc.prodMk hf
@[fun_prop]
theorem DifferentiableWithinAt.smul (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) : DifferentiableWithinAt 𝕜 (fun y => c y • f y) s x :=
(hc.hasFDerivWithinAt.smul hf.hasFDerivWithinAt).differentiableWithinAt
@[simp, fun_prop]
theorem DifferentiableAt.smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
DifferentiableAt 𝕜 (fun y => c y • f y) x :=
(hc.hasFDerivAt.smul hf.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.smul (hc : DifferentiableOn 𝕜 c s) (hf : DifferentiableOn 𝕜 f s) :
DifferentiableOn 𝕜 (fun y => c y • f y) s := fun x hx => (hc x hx).smul (hf x hx)
@[simp, fun_prop]
theorem Differentiable.smul (hc : Differentiable 𝕜 c) (hf : Differentiable 𝕜 f) :
Differentiable 𝕜 fun y => c y • f y := fun x => (hc x).smul (hf x)
theorem fderivWithin_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) :
fderivWithin 𝕜 (fun y => c y • f y) s x =
c x • fderivWithin 𝕜 f s x + (fderivWithin 𝕜 c s x).smulRight (f x) :=
(hc.hasFDerivWithinAt.smul hf.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
fderiv 𝕜 (fun y => c y • f y) x = c x • fderiv 𝕜 f x + (fderiv 𝕜 c x).smulRight (f x) :=
(hc.hasFDerivAt.smul hf.hasFDerivAt).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.smul_const (hc : HasStrictFDerivAt c c' x) (f : F) :
HasStrictFDerivAt (fun y => c y • f) (c'.smulRight f) x := by
simpa only [smul_zero, zero_add] using hc.smul (hasStrictFDerivAt_const f x)
@[fun_prop]
theorem HasFDerivWithinAt.smul_const (hc : HasFDerivWithinAt c c' s x) (f : F) :
HasFDerivWithinAt (fun y => c y • f) (c'.smulRight f) s x := by
simpa only [smul_zero, zero_add] using hc.smul (hasFDerivWithinAt_const f x s)
@[fun_prop]
theorem HasFDerivAt.smul_const (hc : HasFDerivAt c c' x) (f : F) :
HasFDerivAt (fun y => c y • f) (c'.smulRight f) x := by
simpa only [smul_zero, zero_add] using hc.smul (hasFDerivAt_const f x)
@[fun_prop]
theorem DifferentiableWithinAt.smul_const (hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
DifferentiableWithinAt 𝕜 (fun y => c y • f) s x :=
(hc.hasFDerivWithinAt.smul_const f).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
DifferentiableAt 𝕜 (fun y => c y • f) x :=
(hc.hasFDerivAt.smul_const f).differentiableAt
@[fun_prop]
theorem DifferentiableOn.smul_const (hc : DifferentiableOn 𝕜 c s) (f : F) :
DifferentiableOn 𝕜 (fun y => c y • f) s := fun x hx => (hc x hx).smul_const f
@[fun_prop]
theorem Differentiable.smul_const (hc : Differentiable 𝕜 c) (f : F) :
Differentiable 𝕜 fun y => c y • f := fun x => (hc x).smul_const f
theorem fderivWithin_smul_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
fderivWithin 𝕜 (fun y => c y • f) s x = (fderivWithin 𝕜 c s x).smulRight f :=
(hc.hasFDerivWithinAt.smul_const f).fderivWithin hxs
theorem fderiv_smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
fderiv 𝕜 (fun y => c y • f) x = (fderiv 𝕜 c x).smulRight f :=
(hc.hasFDerivAt.smul_const f).fderiv
end SMul
section Mul
/-! ### Derivative of the product of two functions -/
variable {𝔸 𝔸' : Type*} [NormedRing 𝔸] [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸] [NormedAlgebra 𝕜 𝔸']
{a b : E → 𝔸} {a' b' : E →L[𝕜] 𝔸} {c d : E → 𝔸'} {c' d' : E →L[𝕜] 𝔸'}
@[fun_prop]
theorem HasStrictFDerivAt.mul' {x : E} (ha : HasStrictFDerivAt a a' x)
(hb : HasStrictFDerivAt b b' x) :
HasStrictFDerivAt (fun y => a y * b y) (a x • b' + a'.smulRight (b x)) x :=
((ContinuousLinearMap.mul 𝕜 𝔸).isBoundedBilinearMap.hasStrictFDerivAt (a x, b x)).comp x
(ha.prodMk hb)
@[fun_prop]
theorem HasStrictFDerivAt.mul (hc : HasStrictFDerivAt c c' x) (hd : HasStrictFDerivAt d d' x) :
HasStrictFDerivAt (fun y => c y * d y) (c x • d' + d x • c') x := by
convert hc.mul' hd
ext z
apply mul_comm
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivWithinAt.mul' (ha : HasFDerivWithinAt a a' s x) (hb : HasFDerivWithinAt b b' s x) :
HasFDerivWithinAt (fun y => a y * b y) (a x • b' + a'.smulRight (b x)) s x := by
exact ((ContinuousLinearMap.mul 𝕜 𝔸).isBoundedBilinearMap.hasFDerivAt
(a x, b x)).comp_hasFDerivWithinAt x (ha.prodMk hb)
@[fun_prop]
theorem HasFDerivWithinAt.mul (hc : HasFDerivWithinAt c c' s x) (hd : HasFDerivWithinAt d d' s x) :
HasFDerivWithinAt (fun y => c y * d y) (c x • d' + d x • c') s x := by
convert hc.mul' hd
ext z
apply mul_comm
#adaptation_note /-- https://github.com/leanprover/lean4/pull/6024
`by exact` to solve unification issues. -/
@[fun_prop]
theorem HasFDerivAt.mul' (ha : HasFDerivAt a a' x) (hb : HasFDerivAt b b' x) :
HasFDerivAt (fun y => a y * b y) (a x • b' + a'.smulRight (b x)) x := by
exact ((ContinuousLinearMap.mul 𝕜 𝔸).isBoundedBilinearMap.hasFDerivAt
(a x, b x)).comp x (ha.prodMk hb)
@[fun_prop]
theorem HasFDerivAt.mul (hc : HasFDerivAt c c' x) (hd : HasFDerivAt d d' x) :
HasFDerivAt (fun y => c y * d y) (c x • d' + d x • c') x := by
convert hc.mul' hd
ext z
apply mul_comm
@[fun_prop]
theorem DifferentiableWithinAt.mul (ha : DifferentiableWithinAt 𝕜 a s x)
(hb : DifferentiableWithinAt 𝕜 b s x) : DifferentiableWithinAt 𝕜 (fun y => a y * b y) s x :=
(ha.hasFDerivWithinAt.mul' hb.hasFDerivWithinAt).differentiableWithinAt
@[simp, fun_prop]
theorem DifferentiableAt.mul (ha : DifferentiableAt 𝕜 a x) (hb : DifferentiableAt 𝕜 b x) :
DifferentiableAt 𝕜 (fun y => a y * b y) x :=
(ha.hasFDerivAt.mul' hb.hasFDerivAt).differentiableAt
@[fun_prop]
theorem DifferentiableOn.mul (ha : DifferentiableOn 𝕜 a s) (hb : DifferentiableOn 𝕜 b s) :
DifferentiableOn 𝕜 (fun y => a y * b y) s := fun x hx => (ha x hx).mul (hb x hx)
@[simp, fun_prop]
theorem Differentiable.mul (ha : Differentiable 𝕜 a) (hb : Differentiable 𝕜 b) :
Differentiable 𝕜 fun y => a y * b y := fun x => (ha x).mul (hb x)
@[fun_prop]
theorem DifferentiableWithinAt.pow (ha : DifferentiableWithinAt 𝕜 a s x) :
∀ n : ℕ, DifferentiableWithinAt 𝕜 (fun x => a x ^ n) s x
| 0 => by simp only [pow_zero, differentiableWithinAt_const]
| n + 1 => by simp only [pow_succ', DifferentiableWithinAt.pow ha n, ha.mul]
@[simp, fun_prop]
theorem DifferentiableAt.pow (ha : DifferentiableAt 𝕜 a x) (n : ℕ) :
DifferentiableAt 𝕜 (fun x => a x ^ n) x :=
differentiableWithinAt_univ.mp <| ha.differentiableWithinAt.pow n
@[fun_prop]
theorem DifferentiableOn.pow (ha : DifferentiableOn 𝕜 a s) (n : ℕ) :
DifferentiableOn 𝕜 (fun x => a x ^ n) s := fun x h => (ha x h).pow n
@[simp, fun_prop]
theorem Differentiable.pow (ha : Differentiable 𝕜 a) (n : ℕ) : Differentiable 𝕜 fun x => a x ^ n :=
fun x => (ha x).pow n
theorem fderivWithin_mul' (hxs : UniqueDiffWithinAt 𝕜 s x) (ha : DifferentiableWithinAt 𝕜 a s x)
(hb : DifferentiableWithinAt 𝕜 b s x) :
fderivWithin 𝕜 (fun y => a y * b y) s x =
a x • fderivWithin 𝕜 b s x + (fderivWithin 𝕜 a s x).smulRight (b x) :=
(ha.hasFDerivWithinAt.mul' hb.hasFDerivWithinAt).fderivWithin hxs
theorem fderivWithin_mul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
fderivWithin 𝕜 (fun y => c y * d y) s x =
c x • fderivWithin 𝕜 d s x + d x • fderivWithin 𝕜 c s x :=
(hc.hasFDerivWithinAt.mul hd.hasFDerivWithinAt).fderivWithin hxs
theorem fderiv_mul' (ha : DifferentiableAt 𝕜 a x) (hb : DifferentiableAt 𝕜 b x) :
fderiv 𝕜 (fun y => a y * b y) x = a x • fderiv 𝕜 b x + (fderiv 𝕜 a x).smulRight (b x) :=
(ha.hasFDerivAt.mul' hb.hasFDerivAt).fderiv
theorem fderiv_mul (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
fderiv 𝕜 (fun y => c y * d y) x = c x • fderiv 𝕜 d x + d x • fderiv 𝕜 c x :=
(hc.hasFDerivAt.mul hd.hasFDerivAt).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.mul_const' (ha : HasStrictFDerivAt a a' x) (b : 𝔸) :
HasStrictFDerivAt (fun y => a y * b) (a'.smulRight b) x :=
((ContinuousLinearMap.mul 𝕜 𝔸).flip b).hasStrictFDerivAt.comp x ha
@[fun_prop]
theorem HasStrictFDerivAt.mul_const (hc : HasStrictFDerivAt c c' x) (d : 𝔸') :
HasStrictFDerivAt (fun y => c y * d) (d • c') x := by
convert hc.mul_const' d
ext z
apply mul_comm
@[fun_prop]
theorem HasFDerivWithinAt.mul_const' (ha : HasFDerivWithinAt a a' s x) (b : 𝔸) :
HasFDerivWithinAt (fun y => a y * b) (a'.smulRight b) s x :=
((ContinuousLinearMap.mul 𝕜 𝔸).flip b).hasFDerivAt.comp_hasFDerivWithinAt x ha
@[fun_prop]
theorem HasFDerivWithinAt.mul_const (hc : HasFDerivWithinAt c c' s x) (d : 𝔸') :
HasFDerivWithinAt (fun y => c y * d) (d • c') s x := by
convert hc.mul_const' d
ext z
apply mul_comm
@[fun_prop]
theorem HasFDerivAt.mul_const' (ha : HasFDerivAt a a' x) (b : 𝔸) :
HasFDerivAt (fun y => a y * b) (a'.smulRight b) x :=
((ContinuousLinearMap.mul 𝕜 𝔸).flip b).hasFDerivAt.comp x ha
@[fun_prop]
theorem HasFDerivAt.mul_const (hc : HasFDerivAt c c' x) (d : 𝔸') :
HasFDerivAt (fun y => c y * d) (d • c') x := by
convert hc.mul_const' d
ext z
apply mul_comm
@[fun_prop]
theorem DifferentiableWithinAt.mul_const (ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
DifferentiableWithinAt 𝕜 (fun y => a y * b) s x :=
(ha.hasFDerivWithinAt.mul_const' b).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.mul_const (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
DifferentiableAt 𝕜 (fun y => a y * b) x :=
(ha.hasFDerivAt.mul_const' b).differentiableAt
@[fun_prop]
theorem DifferentiableOn.mul_const (ha : DifferentiableOn 𝕜 a s) (b : 𝔸) :
DifferentiableOn 𝕜 (fun y => a y * b) s := fun x hx => (ha x hx).mul_const b
@[fun_prop]
theorem Differentiable.mul_const (ha : Differentiable 𝕜 a) (b : 𝔸) :
Differentiable 𝕜 fun y => a y * b := fun x => (ha x).mul_const b
theorem fderivWithin_mul_const' (hxs : UniqueDiffWithinAt 𝕜 s x)
(ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
fderivWithin 𝕜 (fun y => a y * b) s x = (fderivWithin 𝕜 a s x).smulRight b :=
(ha.hasFDerivWithinAt.mul_const' b).fderivWithin hxs
theorem fderivWithin_mul_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (d : 𝔸') :
fderivWithin 𝕜 (fun y => c y * d) s x = d • fderivWithin 𝕜 c s x :=
(hc.hasFDerivWithinAt.mul_const d).fderivWithin hxs
theorem fderiv_mul_const' (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
fderiv 𝕜 (fun y => a y * b) x = (fderiv 𝕜 a x).smulRight b :=
(ha.hasFDerivAt.mul_const' b).fderiv
theorem fderiv_mul_const (hc : DifferentiableAt 𝕜 c x) (d : 𝔸') :
fderiv 𝕜 (fun y => c y * d) x = d • fderiv 𝕜 c x :=
(hc.hasFDerivAt.mul_const d).fderiv
@[fun_prop]
theorem HasStrictFDerivAt.const_mul (ha : HasStrictFDerivAt a a' x) (b : 𝔸) :
HasStrictFDerivAt (fun y => b * a y) (b • a') x :=
((ContinuousLinearMap.mul 𝕜 𝔸) b).hasStrictFDerivAt.comp x ha
@[fun_prop]
theorem HasFDerivWithinAt.const_mul (ha : HasFDerivWithinAt a a' s x) (b : 𝔸) :
HasFDerivWithinAt (fun y => b * a y) (b • a') s x :=
((ContinuousLinearMap.mul 𝕜 𝔸) b).hasFDerivAt.comp_hasFDerivWithinAt x ha
@[fun_prop]
theorem HasFDerivAt.const_mul (ha : HasFDerivAt a a' x) (b : 𝔸) :
HasFDerivAt (fun y => b * a y) (b • a') x :=
((ContinuousLinearMap.mul 𝕜 𝔸) b).hasFDerivAt.comp x ha
@[fun_prop]
theorem DifferentiableWithinAt.const_mul (ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
DifferentiableWithinAt 𝕜 (fun y => b * a y) s x :=
(ha.hasFDerivWithinAt.const_mul b).differentiableWithinAt
@[fun_prop]
theorem DifferentiableAt.const_mul (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
DifferentiableAt 𝕜 (fun y => b * a y) x :=
(ha.hasFDerivAt.const_mul b).differentiableAt
@[fun_prop]
theorem DifferentiableOn.const_mul (ha : DifferentiableOn 𝕜 a s) (b : 𝔸) :
DifferentiableOn 𝕜 (fun y => b * a y) s := fun x hx => (ha x hx).const_mul b
@[fun_prop]
theorem Differentiable.const_mul (ha : Differentiable 𝕜 a) (b : 𝔸) :
Differentiable 𝕜 fun y => b * a y := fun x => (ha x).const_mul b
theorem fderivWithin_const_mul (hxs : UniqueDiffWithinAt 𝕜 s x)
(ha : DifferentiableWithinAt 𝕜 a s x) (b : 𝔸) :
fderivWithin 𝕜 (fun y => b * a y) s x = b • fderivWithin 𝕜 a s x :=
(ha.hasFDerivWithinAt.const_mul b).fderivWithin hxs
theorem fderiv_const_mul (ha : DifferentiableAt 𝕜 a x) (b : 𝔸) :
fderiv 𝕜 (fun y => b * a y) x = b • fderiv 𝕜 a x :=
(ha.hasFDerivAt.const_mul b).fderiv
end Mul
section Prod
/-! ### Derivative of a finite product of functions -/
variable {ι : Type*} {𝔸 𝔸' : Type*} [NormedRing 𝔸] [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸]
[NormedAlgebra 𝕜 𝔸'] {u : Finset ι} {f : ι → E → 𝔸} {f' : ι → E →L[𝕜] 𝔸} {g : ι → E → 𝔸'}
{g' : ι → E →L[𝕜] 𝔸'}
@[fun_prop]
theorem hasStrictFDerivAt_list_prod' [Fintype ι] {l : List ι} {x : ι → 𝔸} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.map x).prod)
(∑ i : Fin l.length, ((l.take i).map x).prod •
smulRight (proj l[i]) ((l.drop (.succ i)).map x).prod) x := by
induction l with
| nil => simp [hasStrictFDerivAt_const]
| cons a l IH =>
simp only [List.map_cons, List.prod_cons, ← proj_apply (R := 𝕜) (φ := fun _ : ι ↦ 𝔸) a]
exact .congr_fderiv (.mul' (ContinuousLinearMap.hasStrictFDerivAt _) IH)
(by ext; simp [Fin.sum_univ_succ, Finset.mul_sum, mul_assoc, add_comm])
@[fun_prop]
theorem hasStrictFDerivAt_list_prod_finRange' {n : ℕ} {x : Fin n → 𝔸} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ ((List.finRange n).map x).prod)
(∑ i : Fin n, (((List.finRange n).take i).map x).prod •
smulRight (proj i) (((List.finRange n).drop (.succ i)).map x).prod) x :=
hasStrictFDerivAt_list_prod'.congr_fderiv <|
Finset.sum_equiv (finCongr List.length_finRange) (by simp) (by simp [Fin.forall_iff])
@[fun_prop]
theorem hasStrictFDerivAt_list_prod_attach' {l : List ι} {x : {i // i ∈ l} → 𝔸} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.attach.map x).prod)
(∑ i : Fin l.length, ((l.attach.take i).map x).prod •
smulRight (proj l.attach[i.cast List.length_attach.symm])
((l.attach.drop (.succ i)).map x).prod) x := by
classical exact hasStrictFDerivAt_list_prod'.congr_fderiv <| Eq.symm <|
Finset.sum_equiv (finCongr List.length_attach.symm) (by simp) (by simp)
@[fun_prop]
theorem hasFDerivAt_list_prod' [Fintype ι] {l : List ι} {x : ι → 𝔸'} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.map x).prod)
(∑ i : Fin l.length, ((l.take i).map x).prod •
smulRight (proj l[i]) ((l.drop (.succ i)).map x).prod) x :=
hasStrictFDerivAt_list_prod'.hasFDerivAt
@[fun_prop]
theorem hasFDerivAt_list_prod_finRange' {n : ℕ} {x : Fin n → 𝔸} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ ((List.finRange n).map x).prod)
(∑ i : Fin n, (((List.finRange n).take i).map x).prod •
smulRight (proj i) (((List.finRange n).drop (.succ i)).map x).prod) x :=
(hasStrictFDerivAt_list_prod_finRange').hasFDerivAt
@[fun_prop]
theorem hasFDerivAt_list_prod_attach' {l : List ι} {x : {i // i ∈ l} → 𝔸} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.attach.map x).prod)
(∑ i : Fin l.length, ((l.attach.take i).map x).prod •
smulRight (proj l.attach[i.cast List.length_attach.symm])
((l.attach.drop (.succ i)).map x).prod) x := by
classical exact hasStrictFDerivAt_list_prod_attach'.hasFDerivAt
/--
Auxiliary lemma for `hasStrictFDerivAt_multiset_prod`.
For `NormedCommRing 𝔸'`, can rewrite as `Multiset` using `Multiset.prod_coe`.
-/
@[fun_prop]
theorem hasStrictFDerivAt_list_prod [DecidableEq ι] [Fintype ι] {l : List ι} {x : ι → 𝔸'} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (l.map x).prod)
(l.map fun i ↦ ((l.erase i).map x).prod • proj i).sum x := by
refine hasStrictFDerivAt_list_prod'.congr_fderiv ?_
conv_rhs => arg 1; arg 2; rw [← List.finRange_map_get l]
simp only [List.map_map, ← List.sum_toFinset _ (List.nodup_finRange _), List.toFinset_finRange,
Function.comp_def, ((List.erase_getElem _).map _).prod_eq, List.eraseIdx_eq_take_drop_succ,
List.map_append, List.prod_append, List.get_eq_getElem, Fin.getElem_fin, Nat.succ_eq_add_one]
exact Finset.sum_congr rfl fun i _ ↦ by
ext; simp only [smul_apply, smulRight_apply, smul_eq_mul]; ring
@[fun_prop]
theorem hasStrictFDerivAt_multiset_prod [DecidableEq ι] [Fintype ι] {u : Multiset ι} {x : ι → 𝔸'} :
HasStrictFDerivAt (𝕜 := 𝕜) (fun x ↦ (u.map x).prod)
(u.map (fun i ↦ ((u.erase i).map x).prod • proj i)).sum x :=
u.inductionOn fun l ↦ by simpa using hasStrictFDerivAt_list_prod
@[fun_prop]
theorem hasFDerivAt_multiset_prod [DecidableEq ι] [Fintype ι] {u : Multiset ι} {x : ι → 𝔸'} :
HasFDerivAt (𝕜 := 𝕜) (fun x ↦ (u.map x).prod)
(Multiset.sum (u.map (fun i ↦ ((u.erase i).map x).prod • proj i))) x :=
hasStrictFDerivAt_multiset_prod.hasFDerivAt
theorem hasStrictFDerivAt_finset_prod [DecidableEq ι] [Fintype ι] {x : ι → 𝔸'} :
HasStrictFDerivAt (𝕜 := 𝕜) (∏ i ∈ u, · i) (∑ i ∈ u, (∏ j ∈ u.erase i, x j) • proj i) x := by
simp only [Finset.sum_eq_multiset_sum, Finset.prod_eq_multiset_prod]
exact hasStrictFDerivAt_multiset_prod
theorem hasFDerivAt_finset_prod [DecidableEq ι] [Fintype ι] {x : ι → 𝔸'} :
HasFDerivAt (𝕜 := 𝕜) (∏ i ∈ u, · i) (∑ i ∈ u, (∏ j ∈ u.erase i, x j) • proj i) x :=
hasStrictFDerivAt_finset_prod.hasFDerivAt
section Comp
@[fun_prop]
theorem HasStrictFDerivAt.list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, HasStrictFDerivAt (f i ·) (f' i) x) :
HasStrictFDerivAt (fun x ↦ (l.map (f · x)).prod)
(∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (f' l[i]) ((l.drop (.succ i)).map (f · x)).prod) x := by
simp_rw [Fin.getElem_fin, ← l.get_eq_getElem, ← List.finRange_map_get l, List.map_map]
-- After #19108, we have to be optimistic with `:)`s; otherwise Lean decides it need to find
-- `NormedAddCommGroup (List 𝔸)` which is nonsense.
refine .congr_fderiv (hasStrictFDerivAt_list_prod_finRange'.comp x
(hasStrictFDerivAt_pi.mpr fun i ↦ h (l.get i) (List.getElem_mem ..)) :) ?_
ext m
simp_rw [List.map_take, List.map_drop, List.map_map, comp_apply, sum_apply, smul_apply,
smulRight_apply, proj_apply, pi_apply, Function.comp_def]
/--
Unlike `HasFDerivAt.finset_prod`, supports non-commutative multiply and duplicate elements.
-/
@[fun_prop]
theorem HasFDerivAt.list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, HasFDerivAt (f i ·) (f' i) x) :
HasFDerivAt (fun x ↦ (l.map (f · x)).prod)
(∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (f' l[i]) ((l.drop (.succ i)).map (f · x)).prod) x := by
simp_rw [Fin.getElem_fin, ← l.get_eq_getElem, ← List.finRange_map_get l, List.map_map]
refine .congr_fderiv (hasFDerivAt_list_prod_finRange'.comp x
(hasFDerivAt_pi.mpr fun i ↦ h (l.get i) (l.get_mem i)) :) ?_
ext m
simp_rw [List.map_take, List.map_drop, List.map_map, comp_apply, sum_apply, smul_apply,
smulRight_apply, proj_apply, pi_apply, Function.comp_def]
@[fun_prop]
theorem HasFDerivWithinAt.list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, HasFDerivWithinAt (f i ·) (f' i) s x) :
HasFDerivWithinAt (fun x ↦ (l.map (f · x)).prod)
(∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (f' l[i]) ((l.drop (.succ i)).map (f · x)).prod) s x := by
simp_rw [Fin.getElem_fin, ← l.get_eq_getElem, ← List.finRange_map_get l, List.map_map]
refine .congr_fderiv (hasFDerivAt_list_prod_finRange'.comp_hasFDerivWithinAt x
(hasFDerivWithinAt_pi.mpr fun i ↦ h (l.get i) (l.get_mem i)) :) ?_
ext m
simp_rw [List.map_take, List.map_drop, List.map_map, comp_apply, sum_apply, smul_apply,
smulRight_apply, proj_apply, pi_apply, Function.comp_def]
theorem fderiv_list_prod' {l : List ι} {x : E}
(h : ∀ i ∈ l, DifferentiableAt 𝕜 (f i ·) x) :
fderiv 𝕜 (fun x ↦ (l.map (f · x)).prod) x =
∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (fderiv 𝕜 (fun x ↦ f l[i] x) x) ((l.drop (.succ i)).map (f · x)).prod :=
(HasFDerivAt.list_prod' fun i hi ↦ (h i hi).hasFDerivAt).fderiv
theorem fderivWithin_list_prod' {l : List ι} {x : E}
(hxs : UniqueDiffWithinAt 𝕜 s x) (h : ∀ i ∈ l, DifferentiableWithinAt 𝕜 (f i ·) s x) :
fderivWithin 𝕜 (fun x ↦ (l.map (f · x)).prod) s x =
∑ i : Fin l.length, ((l.take i).map (f · x)).prod •
smulRight (fderivWithin 𝕜 (fun x ↦ f l[i] x) s x) ((l.drop (.succ i)).map (f · x)).prod :=
(HasFDerivWithinAt.list_prod' fun i hi ↦ (h i hi).hasFDerivWithinAt).fderivWithin hxs
@[fun_prop]
theorem HasStrictFDerivAt.multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, HasStrictFDerivAt (g i ·) (g' i) x) :
HasStrictFDerivAt (fun x ↦ (u.map (g · x)).prod)
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • g' i).sum x := by
simp only [← Multiset.attach_map_val u, Multiset.map_map]
exact .congr_fderiv
(hasStrictFDerivAt_multiset_prod.comp x <|
hasStrictFDerivAt_pi.mpr fun i ↦ h (Subtype.val i) i.prop :)
(by ext; simp [Finset.sum_multiset_map_count, u.erase_attach_map (g · x)])
/--
Unlike `HasFDerivAt.finset_prod`, supports duplicate elements.
-/
@[fun_prop]
theorem HasFDerivAt.multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, HasFDerivAt (g i ·) (g' i) x) :
HasFDerivAt (fun x ↦ (u.map (g · x)).prod)
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • g' i).sum x := by
simp only [← Multiset.attach_map_val u, Multiset.map_map]
exact .congr_fderiv
(hasFDerivAt_multiset_prod.comp x <| hasFDerivAt_pi.mpr fun i ↦ h (Subtype.val i) i.prop :)
(by ext; simp [Finset.sum_multiset_map_count, u.erase_attach_map (g · x)])
@[fun_prop]
theorem HasFDerivWithinAt.multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, HasFDerivWithinAt (g i ·) (g' i) s x) :
HasFDerivWithinAt (fun x ↦ (u.map (g · x)).prod)
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • g' i).sum s x := by
simp only [← Multiset.attach_map_val u, Multiset.map_map]
exact .congr_fderiv
(hasFDerivAt_multiset_prod.comp_hasFDerivWithinAt x <|
hasFDerivWithinAt_pi.mpr fun i ↦ h (Subtype.val i) i.prop :)
(by ext; simp [Finset.sum_multiset_map_count, u.erase_attach_map (g · x)])
theorem fderiv_multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(h : ∀ i ∈ u, DifferentiableAt 𝕜 (g i ·) x) :
fderiv 𝕜 (fun x ↦ (u.map (g · x)).prod) x =
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • fderiv 𝕜 (g i) x).sum :=
(HasFDerivAt.multiset_prod fun i hi ↦ (h i hi).hasFDerivAt).fderiv
theorem fderivWithin_multiset_prod [DecidableEq ι] {u : Multiset ι} {x : E}
(hxs : UniqueDiffWithinAt 𝕜 s x) (h : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (g i ·) s x) :
fderivWithin 𝕜 (fun x ↦ (u.map (g · x)).prod) s x =
(u.map fun i ↦ ((u.erase i).map (g · x)).prod • fderivWithin 𝕜 (g i) s x).sum :=
(HasFDerivWithinAt.multiset_prod fun i hi ↦ (h i hi).hasFDerivWithinAt).fderivWithin hxs
theorem HasStrictFDerivAt.finset_prod [DecidableEq ι] {x : E}
(hg : ∀ i ∈ u, HasStrictFDerivAt (g i) (g' i) x) :
HasStrictFDerivAt (∏ i ∈ u, g i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, g j x) • g' i) x := by
simpa [← Finset.prod_attach u] using .congr_fderiv
(hasStrictFDerivAt_finset_prod.comp x <| hasStrictFDerivAt_pi.mpr fun i ↦ hg i i.prop)
(by ext; simp [Finset.prod_erase_attach (g · x), ← u.sum_attach])
theorem HasFDerivAt.finset_prod [DecidableEq ι] {x : E}
(hg : ∀ i ∈ u, HasFDerivAt (g i) (g' i) x) :
HasFDerivAt (∏ i ∈ u, g i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, g j x) • g' i) x := by
simpa [← Finset.prod_attach u] using .congr_fderiv
(hasFDerivAt_finset_prod.comp x <| hasFDerivAt_pi.mpr fun i ↦ hg (Subtype.val i) i.prop :)
(by ext; simp [Finset.prod_erase_attach (g · x), ← u.sum_attach])
theorem HasFDerivWithinAt.finset_prod [DecidableEq ι] {x : E}
(hg : ∀ i ∈ u, HasFDerivWithinAt (g i) (g' i) s x) :
HasFDerivWithinAt (∏ i ∈ u, g i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, g j x) • g' i) s x := by
simpa [← Finset.prod_attach u] using .congr_fderiv
(hasFDerivAt_finset_prod.comp_hasFDerivWithinAt x <|
hasFDerivWithinAt_pi.mpr fun i ↦ hg (Subtype.val i) i.prop :)
(by ext; simp [Finset.prod_erase_attach (g · x), ← u.sum_attach])
theorem fderiv_finset_prod [DecidableEq ι] {x : E} (hg : ∀ i ∈ u, DifferentiableAt 𝕜 (g i) x) :
fderiv 𝕜 (∏ i ∈ u, g i ·) x = ∑ i ∈ u, (∏ j ∈ u.erase i, (g j x)) • fderiv 𝕜 (g i) x :=
(HasFDerivAt.finset_prod fun i hi ↦ (hg i hi).hasFDerivAt).fderiv
theorem fderivWithin_finset_prod [DecidableEq ι] {x : E} (hxs : UniqueDiffWithinAt 𝕜 s x)
(hg : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (g i) s x) :
fderivWithin 𝕜 (∏ i ∈ u, g i ·) s x =
∑ i ∈ u, (∏ j ∈ u.erase i, (g j x)) • fderivWithin 𝕜 (g i) s x :=
(HasFDerivWithinAt.finset_prod fun i hi ↦ (hg i hi).hasFDerivWithinAt).fderivWithin hxs
end Comp
end Prod
section AlgebraInverse
variable {R : Type*} [NormedRing R] [HasSummableGeomSeries R] [NormedAlgebra 𝕜 R]
open NormedRing ContinuousLinearMap Ring
/-- At an invertible element `x` of a normed algebra `R`, the Fréchet derivative of the inversion
operation is the linear map `fun t ↦ - x⁻¹ * t * x⁻¹`.
TODO (low prio): prove a version without assumption `[HasSummableGeomSeries R]` but within the set
of units. -/
@[fun_prop]
theorem hasFDerivAt_ringInverse (x : Rˣ) :
HasFDerivAt Ring.inverse (-mulLeftRight 𝕜 R ↑x⁻¹ ↑x⁻¹) x :=
have : (fun t : R => Ring.inverse (↑x + t) - ↑x⁻¹ + ↑x⁻¹ * t * ↑x⁻¹) =o[𝓝 0] id :=
(inverse_add_norm_diff_second_order x).trans_isLittleO (isLittleO_norm_pow_id one_lt_two)
by simpa [hasFDerivAt_iff_isLittleO_nhds_zero] using this
@[deprecated (since := "2025-04-22")] alias hasFDerivAt_ring_inverse := hasFDerivAt_ringInverse
@[fun_prop]
theorem differentiableAt_inverse {x : R} (hx : IsUnit x) :
DifferentiableAt 𝕜 (@Ring.inverse R _) x :=
let ⟨u, hu⟩ := hx; hu ▸ (hasFDerivAt_ringInverse u).differentiableAt
@[fun_prop]
theorem differentiableWithinAt_inverse {x : R} (hx : IsUnit x) (s : Set R) :
DifferentiableWithinAt 𝕜 (@Ring.inverse R _) s x :=
(differentiableAt_inverse hx).differentiableWithinAt
@[fun_prop]
theorem differentiableOn_inverse : DifferentiableOn 𝕜 (@Ring.inverse R _) {x | IsUnit x} :=
fun _x hx => differentiableWithinAt_inverse hx _
theorem fderiv_inverse (x : Rˣ) : fderiv 𝕜 (@Ring.inverse R _) x = -mulLeftRight 𝕜 R ↑x⁻¹ ↑x⁻¹ :=
(hasFDerivAt_ringInverse x).fderiv
theorem hasStrictFDerivAt_ringInverse (x : Rˣ) :
HasStrictFDerivAt Ring.inverse (-mulLeftRight 𝕜 R ↑x⁻¹ ↑x⁻¹) x := by
convert (analyticAt_inverse (𝕜 := 𝕜) x).hasStrictFDerivAt
exact (fderiv_inverse x).symm
@[deprecated (since := "2025-04-22")]
alias hasStrictFDerivAt_ring_inverse := hasStrictFDerivAt_ringInverse
variable {h : E → R} {z : E} {S : Set E}
@[fun_prop]
theorem DifferentiableWithinAt.inverse (hf : DifferentiableWithinAt 𝕜 h S z) (hz : IsUnit (h z)) :
DifferentiableWithinAt 𝕜 (fun x => Ring.inverse (h x)) S z :=
(differentiableAt_inverse hz).comp_differentiableWithinAt z hf
@[simp, fun_prop]
theorem DifferentiableAt.inverse (hf : DifferentiableAt 𝕜 h z) (hz : IsUnit (h z)) :
DifferentiableAt 𝕜 (fun x => Ring.inverse (h x)) z :=
(differentiableAt_inverse hz).comp z hf
@[fun_prop]
theorem DifferentiableOn.inverse (hf : DifferentiableOn 𝕜 h S) (hz : ∀ x ∈ S, IsUnit (h x)) :
DifferentiableOn 𝕜 (fun x => Ring.inverse (h x)) S := fun x h => (hf x h).inverse (hz x h)
@[simp, fun_prop]
theorem Differentiable.inverse (hf : Differentiable 𝕜 h) (hz : ∀ x, IsUnit (h x)) :
Differentiable 𝕜 fun x => Ring.inverse (h x) := fun x => (hf x).inverse (hz x)
end AlgebraInverse
/-! ### Derivative of the inverse in a division ring
Note that some lemmas are primed as they are expressed without commutativity, whereas their
counterparts in commutative fields involve simpler expressions, and are given in
`Mathlib/Analysis/Calculus/Deriv/Inv.lean`.
-/
section DivisionRingInverse
variable {R : Type*} [NormedDivisionRing R] [NormedAlgebra 𝕜 R]
open NormedRing ContinuousLinearMap Ring
/-- At an invertible element `x` of a normed division algebra `R`, the inversion is strictly
differentiable, with derivative the linear map `fun t ↦ - x⁻¹ * t * x⁻¹`. For a nicer formula in
the commutative case, see `hasStrictFDerivAt_inv`. -/
theorem hasStrictFDerivAt_inv' {x : R} (hx : x ≠ 0) :
HasStrictFDerivAt Inv.inv (-mulLeftRight 𝕜 R x⁻¹ x⁻¹) x := by
simpa using hasStrictFDerivAt_ringInverse (Units.mk0 _ hx)
/-- At an invertible element `x` of a normed division algebra `R`, the Fréchet derivative of the
inversion operation is the linear map `fun t ↦ - x⁻¹ * t * x⁻¹`. For a nicer formula in the
commutative case, see `hasFDerivAt_inv`. -/
@[fun_prop]
theorem hasFDerivAt_inv' {x : R} (hx : x ≠ 0) :
HasFDerivAt Inv.inv (-mulLeftRight 𝕜 R x⁻¹ x⁻¹) x := by
simpa using hasFDerivAt_ringInverse (Units.mk0 _ hx)
@[fun_prop]
theorem differentiableAt_inv {x : R} (hx : x ≠ 0) : DifferentiableAt 𝕜 Inv.inv x :=
(hasFDerivAt_inv' hx).differentiableAt
@[fun_prop]
theorem differentiableWithinAt_inv {x : R} (hx : x ≠ 0) (s : Set R) :
DifferentiableWithinAt 𝕜 (fun x => x⁻¹) s x :=
(differentiableAt_inv hx).differentiableWithinAt
@[fun_prop]
theorem differentiableOn_inv : DifferentiableOn 𝕜 (fun x : R => x⁻¹) {x | x ≠ 0} := fun _x hx =>
differentiableWithinAt_inv hx _
/-- Non-commutative version of `fderiv_inv` -/
theorem fderiv_inv' {x : R} (hx : x ≠ 0) : fderiv 𝕜 Inv.inv x = -mulLeftRight 𝕜 R x⁻¹ x⁻¹ :=
(hasFDerivAt_inv' hx).fderiv
/-- Non-commutative version of `fderivWithin_inv` -/
theorem fderivWithin_inv' {s : Set R} {x : R} (hx : x ≠ 0) (hxs : UniqueDiffWithinAt 𝕜 s x) :
fderivWithin 𝕜 (fun x => x⁻¹) s x = -mulLeftRight 𝕜 R x⁻¹ x⁻¹ := by
rw [DifferentiableAt.fderivWithin (differentiableAt_inv hx) hxs]
exact fderiv_inv' hx
variable {h : E → R} {z : E} {S : Set E}
@[fun_prop]
theorem DifferentiableWithinAt.inv (hf : DifferentiableWithinAt 𝕜 h S z) (hz : h z ≠ 0) :
DifferentiableWithinAt 𝕜 (fun x => (h x)⁻¹) S z :=
(differentiableAt_inv hz).comp_differentiableWithinAt z hf
@[simp, fun_prop]
theorem DifferentiableAt.inv (hf : DifferentiableAt 𝕜 h z) (hz : h z ≠ 0) :
DifferentiableAt 𝕜 (fun x => (h x)⁻¹) z :=
(differentiableAt_inv hz).comp z hf
@[fun_prop]
theorem DifferentiableOn.inv (hf : DifferentiableOn 𝕜 h S) (hz : ∀ x ∈ S, h x ≠ 0) :
DifferentiableOn 𝕜 (fun x => (h x)⁻¹) S := fun x h => (hf x h).inv (hz x h)
@[simp, fun_prop]
theorem Differentiable.inv (hf : Differentiable 𝕜 h) (hz : ∀ x, h x ≠ 0) :
Differentiable 𝕜 fun x => (h x)⁻¹ := fun x => (hf x).inv (hz x)
|
end DivisionRingInverse
| Mathlib/Analysis/Calculus/FDeriv/Mul.lean | 937 | 939 |
/-
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.Family
/-! # 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 Set Equiv Order
open scoped Cardinal Ordinal
universe u v w
namespace Ordinal
/-- The ordinal exponential, defined by transfinite recursion.
We call this `opow` in theorems in order to disambiguate from other exponentials. -/
instance instPow : Pow Ordinal Ordinal :=
⟨fun a b ↦ if a = 0 then 1 - b else
limitRecOn b 1 (fun _ x ↦ x * a) fun o _ f ↦ ⨆ x : Iio o, f x.1 x.2⟩
private theorem opow_of_ne_zero {a b : Ordinal} (h : a ≠ 0) : a ^ b =
limitRecOn b 1 (fun _ x ↦ x * a) fun o _ f ↦ ⨆ x : Iio o, f x.1 x.2 :=
if_neg h
/-- `0 ^ a = 1` if `a = 0` and `0 ^ a = 0` otherwise. -/
theorem zero_opow' (a : Ordinal) : 0 ^ a = 1 - a :=
if_pos rfl
theorem zero_opow_le (a : Ordinal) : (0 : Ordinal) ^ a ≤ 1 := by
rw [zero_opow']
exact sub_le_self 1 a
@[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]
@[simp]
theorem opow_zero (a : Ordinal) : a ^ (0 : Ordinal) = 1 := by
obtain rfl | h := eq_or_ne a 0
· rw [zero_opow', Ordinal.sub_zero]
· rw [opow_of_ne_zero h, limitRecOn_zero]
@[simp]
theorem opow_succ (a b : Ordinal) : a ^ succ b = a ^ b * a := by
obtain rfl | h := eq_or_ne a 0
· rw [zero_opow (succ_ne_zero b), mul_zero]
· rw [opow_of_ne_zero h, opow_of_ne_zero h, limitRecOn_succ]
theorem opow_limit {a b : Ordinal} (ha : a ≠ 0) (hb : IsLimit b) :
a ^ b = ⨆ x : Iio b, a ^ x.1 := by
simp_rw [opow_of_ne_zero ha, limitRecOn_limit _ _ _ _ hb]
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, Ordinal.iSup_le_iff, Subtype.forall]
rfl
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]
@[simp]
theorem opow_one (a : Ordinal) : a ^ (1 : Ordinal) = a := by
rw [← succ_zero, opow_succ]
simp only [opow_zero, one_mul]
@[simp]
theorem one_opow (a : Ordinal) : (1 : Ordinal) ^ a = 1 := by
induction a using limitRecOn with
| zero => simp only [opow_zero]
| succ _ ih =>
simp only [opow_succ, ih, mul_one]
| isLimit 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]⟩
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
| zero => exact h0
| succ b IH =>
rw [opow_succ]
exact mul_pos IH a0
| isLimit b l _ =>
exact (lt_opow_of_limit (Ordinal.pos_iff_ne_zero.1 a0) l).2 ⟨0, l.pos, h0⟩
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
@[simp]
theorem opow_eq_zero {a b : Ordinal} : a ^ b = 0 ↔ a = 0 ∧ b ≠ 0 := by
obtain rfl | ha := eq_or_ne a 0
· obtain rfl | hb := eq_or_ne b 0
· simp
· simp [hb]
· simp [opow_ne_zero b ha, ha]
@[simp, norm_cast]
theorem opow_natCast (a : Ordinal) (n : ℕ) : a ^ (n : Ordinal) = a ^ n := by
induction n with
| zero => rw [Nat.cast_zero, opow_zero, pow_zero]
| succ n IH => rw [Nat.cast_succ, add_one_eq_succ, opow_succ, pow_succ, IH]
theorem isNormal_opow {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 _ l _ => opow_le_of_limit (ne_of_gt a0) l⟩
theorem opow_lt_opow_iff_right {a b c : Ordinal} (a1 : 1 < a) : a ^ b < a ^ c ↔ b < c :=
(isNormal_opow a1).lt_iff
theorem opow_le_opow_iff_right {a b c : Ordinal} (a1 : 1 < a) : a ^ b ≤ a ^ c ↔ b ≤ c :=
(isNormal_opow a1).le_iff
theorem opow_right_inj {a b c : Ordinal} (a1 : 1 < a) : a ^ b = a ^ c ↔ b = c :=
(isNormal_opow a1).inj
theorem isLimit_opow {a b : Ordinal} (a1 : 1 < a) : IsLimit b → IsLimit (a ^ b) :=
(isNormal_opow a1).isLimit
theorem isLimit_opow_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 isLimit_mul (opow_pos _ l.pos) l
· exact isLimit_opow l.one_lt l'
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]
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
| zero => simp only [opow_zero, le_refl]
| succ c IH =>
simpa only [opow_succ] using mul_le_mul' IH ab
| isLimit 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)
theorem opow_le_opow {a b c d : Ordinal} (hac : a ≤ c) (hbd : b ≤ d) (hc : 0 < c) : a ^ b ≤ c ^ d :=
(opow_le_opow_left b hac).trans (opow_le_opow_right hc hbd)
theorem left_le_opow (a : Ordinal) {b : Ordinal} (b1 : 0 < b) : a ≤ a ^ b := by
nth_rw 1 [← opow_one a]
rcases 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]
theorem left_lt_opow {a b : Ordinal} (ha : 1 < a) (hb : 1 < b) : a < a ^ b := by
conv_lhs => rw [← opow_one a]
rwa [opow_lt_opow_iff_right ha]
theorem right_le_opow {a : Ordinal} (b : Ordinal) (a1 : 1 < a) : b ≤ a ^ b :=
(isNormal_opow a1).le_apply
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)))
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
| zero => simp
| succ c IH =>
rw [add_succ, opow_succ, IH, opow_succ, mul_assoc]
| isLimit c l IH =>
refine
eq_of_forall_ge_iff fun d =>
(((isNormal_opow a1).trans (isNormal_add_right b)).limit_le l).trans ?_
dsimp only [Function.comp_def]
simp +contextual only [IH]
exact
| Mathlib/SetTheory/Ordinal/Exponential.lean | 187 | 208 |
/-
Copyright (c) 2023 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Algebra.NoZeroSMulDivisors.Basic
import Mathlib.SetTheory.Cardinal.Basic
/-!
# Cardinality of a module
This file proves that the cardinality of a module without zero divisors is at least the cardinality
of its base ring.
-/
open Function
universe u v
namespace Cardinal
/-- The cardinality of a nontrivial module over a ring is at least the cardinality of the ring if
there are no zero divisors (for instance if the ring is a field) -/
| theorem mk_le_of_module (R : Type u) (E : Type v)
[AddCommGroup E] [Ring R] [Module R E] [Nontrivial E] [NoZeroSMulDivisors R E] :
Cardinal.lift.{v} (#R) ≤ Cardinal.lift.{u} (#E) := by
obtain ⟨x, hx⟩ : ∃ (x : E), x ≠ 0 := exists_ne 0
have : Injective (fun k ↦ k • x) := smul_left_injective R hx
exact lift_mk_le_lift_mk_of_injective this
| Mathlib/Algebra/Module/Card.lean | 24 | 29 |
/-
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.MeasurableSpace.MeasurablyGenerated
import Mathlib.MeasureTheory.Measure.NullMeasurable
import Mathlib.Order.Interval.Set.Monotone
/-!
# Measure spaces
The definition of a measure and a measure space are in `MeasureTheory.MeasureSpaceDef`, with
only a few basic properties. This file provides many more properties of these objects.
This separation allows the measurability tactic to import only the file `MeasureSpaceDef`, and to
be available in `MeasureSpace` (through `MeasurableSpace`).
Given a measurable space `α`, a measure on `α` is a function that sends measurable sets to the
extended nonnegative reals that satisfies the following conditions:
1. `μ ∅ = 0`;
2. `μ` is countably additive. This means that the measure of a countable union of pairwise disjoint
sets is equal to the measure of the individual sets.
Every measure can be canonically extended to an outer measure, so that it assigns values to
all subsets, not just the measurable subsets. On the other hand, a measure that is countably
additive on measurable sets can be restricted to measurable sets to obtain a measure.
In this file a measure is defined to be an outer measure that is countably additive on
measurable sets, with the additional assumption that the outer measure is the canonical
extension of the restricted measure.
Measures on `α` form a complete lattice, and are closed under scalar multiplication with `ℝ≥0∞`.
Given a measure, the null sets are the sets where `μ s = 0`, where `μ` denotes the corresponding
outer measure (so `s` might not be measurable). We can then define the completion of `μ` as the
measure on the least `σ`-algebra that also contains all null sets, by defining the measure to be `0`
on the null sets.
## Main statements
* `completion` is the completion of a measure to all null measurable sets.
* `Measure.ofMeasurable` and `OuterMeasure.toMeasure` are two important ways to define a measure.
## Implementation notes
Given `μ : Measure α`, `μ s` is the value of the *outer measure* applied to `s`.
This conveniently allows us to apply the measure to sets without proving that they are measurable.
We get countable subadditivity for all sets, but only countable additivity for measurable sets.
You often don't want to define a measure via its constructor.
Two ways that are sometimes more convenient:
* `Measure.ofMeasurable` is a way to define a measure by only giving its value on measurable sets
and proving the properties (1) and (2) mentioned above.
* `OuterMeasure.toMeasure` is a way of obtaining a measure from an outer measure by showing that
all measurable sets in the measurable space are Carathéodory measurable.
To prove that two measures are equal, there are multiple options:
* `ext`: two measures are equal if they are equal on all measurable sets.
* `ext_of_generateFrom_of_iUnion`: two measures are equal if they are equal on a π-system generating
the measurable sets, if the π-system contains a spanning increasing sequence of sets where the
measures take finite value (in particular the measures are σ-finite). This is a special case of
the more general `ext_of_generateFrom_of_cover`
* `ext_of_generate_finite`: two finite measures are equal if they are equal on a π-system
generating the measurable sets. This is a special case of `ext_of_generateFrom_of_iUnion` using
`C ∪ {univ}`, but is easier to work with.
A `MeasureSpace` is a class that is a measurable space with a canonical measure.
The measure is denoted `volume`.
## References
* <https://en.wikipedia.org/wiki/Measure_(mathematics)>
* <https://en.wikipedia.org/wiki/Complete_measure>
* <https://en.wikipedia.org/wiki/Almost_everywhere>
## Tags
measure, almost everywhere, measure space, completion, null set, null measurable set
-/
noncomputable section
open Set
open Filter hiding map
open Function MeasurableSpace Topology Filter ENNReal NNReal Interval MeasureTheory
open scoped symmDiff
variable {α β γ δ ι R R' : Type*}
namespace MeasureTheory
section
variable {m : MeasurableSpace α} {μ μ₁ μ₂ : Measure α} {s s₁ s₂ t : Set α}
instance ae_isMeasurablyGenerated : IsMeasurablyGenerated (ae μ) :=
⟨fun _s hs =>
let ⟨t, hst, htm, htμ⟩ := exists_measurable_superset_of_null hs
⟨tᶜ, compl_mem_ae_iff.2 htμ, htm.compl, compl_subset_comm.1 hst⟩⟩
/-- See also `MeasureTheory.ae_restrict_uIoc_iff`. -/
theorem ae_uIoc_iff [LinearOrder α] {a b : α} {P : α → Prop} :
(∀ᵐ x ∂μ, x ∈ Ι a b → P x) ↔ (∀ᵐ x ∂μ, x ∈ Ioc a b → P x) ∧ ∀ᵐ x ∂μ, x ∈ Ioc b a → P x := by
simp only [uIoc_eq_union, mem_union, or_imp, eventually_and]
theorem measure_union (hd : Disjoint s₁ s₂) (h : MeasurableSet s₂) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀ h.nullMeasurableSet hd.aedisjoint
theorem measure_union' (hd : Disjoint s₁ s₂) (h : MeasurableSet s₁) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀' h.nullMeasurableSet hd.aedisjoint
theorem measure_inter_add_diff (s : Set α) (ht : MeasurableSet t) : μ (s ∩ t) + μ (s \ t) = μ s :=
measure_inter_add_diff₀ _ ht.nullMeasurableSet
theorem measure_diff_add_inter (s : Set α) (ht : MeasurableSet t) : μ (s \ t) + μ (s ∩ t) = μ s :=
(add_comm _ _).trans (measure_inter_add_diff s ht)
theorem measure_diff_eq_top (hs : μ s = ∞) (ht : μ t ≠ ∞) : μ (s \ t) = ∞ := by
contrapose! hs
exact ((measure_mono (subset_diff_union s t)).trans_lt
((measure_union_le _ _).trans_lt (ENNReal.add_lt_top.2 ⟨hs.lt_top, ht.lt_top⟩))).ne
theorem measure_union_add_inter (s : Set α) (ht : MeasurableSet t) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [← measure_inter_add_diff (s ∪ t) ht, Set.union_inter_cancel_right, union_diff_right, ←
measure_inter_add_diff s ht]
ac_rfl
theorem measure_union_add_inter' (hs : MeasurableSet s) (t : Set α) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [union_comm, inter_comm, measure_union_add_inter t hs, add_comm]
lemma measure_symmDiff_eq (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) :
μ (s ∆ t) = μ (s \ t) + μ (t \ s) := by
simpa only [symmDiff_def, sup_eq_union]
using measure_union₀ (ht.diff hs) disjoint_sdiff_sdiff.aedisjoint
lemma measure_symmDiff_le (s t u : Set α) :
μ (s ∆ u) ≤ μ (s ∆ t) + μ (t ∆ u) :=
le_trans (μ.mono <| symmDiff_triangle s t u) (measure_union_le (s ∆ t) (t ∆ u))
theorem measure_symmDiff_eq_top (hs : μ s ≠ ∞) (ht : μ t = ∞) : μ (s ∆ t) = ∞ :=
measure_mono_top subset_union_right (measure_diff_eq_top ht hs)
theorem measure_add_measure_compl (h : MeasurableSet s) : μ s + μ sᶜ = μ univ :=
measure_add_measure_compl₀ h.nullMeasurableSet
theorem measure_biUnion₀ {s : Set β} {f : β → Set α} (hs : s.Countable)
(hd : s.Pairwise (AEDisjoint μ on f)) (h : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) := by
haveI := hs.toEncodable
rw [biUnion_eq_iUnion]
exact measure_iUnion₀ (hd.on_injective Subtype.coe_injective fun x => x.2) fun x => h x x.2
theorem measure_biUnion {s : Set β} {f : β → Set α} (hs : s.Countable) (hd : s.PairwiseDisjoint f)
(h : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) :=
measure_biUnion₀ hs hd.aedisjoint fun b hb => (h b hb).nullMeasurableSet
theorem measure_sUnion₀ {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise (AEDisjoint μ))
(h : ∀ s ∈ S, NullMeasurableSet s μ) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion₀ hs hd h]
theorem measure_sUnion {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise Disjoint)
(h : ∀ s ∈ S, MeasurableSet s) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion hs hd h]
theorem measure_biUnion_finset₀ {s : Finset ι} {f : ι → Set α}
(hd : Set.Pairwise (↑s) (AEDisjoint μ on f)) (hm : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) := by
rw [← Finset.sum_attach, Finset.attach_eq_univ, ← tsum_fintype]
exact measure_biUnion₀ s.countable_toSet hd hm
theorem measure_biUnion_finset {s : Finset ι} {f : ι → Set α} (hd : PairwiseDisjoint (↑s) f)
(hm : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) :=
measure_biUnion_finset₀ hd.aedisjoint fun b hb => (hm b hb).nullMeasurableSet
/-- The measure of an a.e. disjoint union (even uncountable) of null-measurable sets is at least
the sum of the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint₀ {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, NullMeasurableSet (As i) μ)
(As_disj : Pairwise (AEDisjoint μ on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) := by
rw [ENNReal.tsum_eq_iSup_sum, iSup_le_iff]
intro s
simp only [← measure_biUnion_finset₀ (fun _i _hi _j _hj hij => As_disj hij) fun i _ => As_mble i]
gcongr
exact iUnion_subset fun _ ↦ Subset.rfl
/-- The measure of a disjoint union (even uncountable) of measurable sets is at least the sum of
the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, MeasurableSet (As i))
(As_disj : Pairwise (Disjoint on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) :=
tsum_meas_le_meas_iUnion_of_disjoint₀ μ (fun i ↦ (As_mble i).nullMeasurableSet)
(fun _ _ h ↦ Disjoint.aedisjoint (As_disj h))
/-- If `s` is a countable set, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem tsum_measure_preimage_singleton {s : Set β} (hs : s.Countable) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑' b : s, μ (f ⁻¹' {↑b})) = μ (f ⁻¹' s) := by
rw [← Set.biUnion_preimage_singleton, measure_biUnion hs (pairwiseDisjoint_fiber f s) hf]
lemma measure_preimage_eq_zero_iff_of_countable {s : Set β} {f : α → β} (hs : s.Countable) :
μ (f ⁻¹' s) = 0 ↔ ∀ x ∈ s, μ (f ⁻¹' {x}) = 0 := by
rw [← biUnion_preimage_singleton, measure_biUnion_null_iff hs]
/-- If `s` is a `Finset`, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem sum_measure_preimage_singleton (s : Finset β) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑ b ∈ s, μ (f ⁻¹' {b})) = μ (f ⁻¹' ↑s) := by
simp only [← measure_biUnion_finset (pairwiseDisjoint_fiber f s) hf,
Finset.set_biUnion_preimage_singleton]
@[simp] lemma sum_measure_singleton {s : Finset α} [MeasurableSingletonClass α] :
∑ x ∈ s, μ {x} = μ s := by
trans ∑ x ∈ s, μ (id ⁻¹' {x})
· simp
rw [sum_measure_preimage_singleton]
· simp
· simp
theorem measure_diff_null' (h : μ (s₁ ∩ s₂) = 0) : μ (s₁ \ s₂) = μ s₁ :=
measure_congr <| diff_ae_eq_self.2 h
theorem measure_add_diff (hs : NullMeasurableSet s μ) (t : Set α) :
μ s + μ (t \ s) = μ (s ∪ t) := by
rw [← measure_union₀' hs disjoint_sdiff_right.aedisjoint, union_diff_self]
theorem measure_diff' (s : Set α) (hm : NullMeasurableSet t μ) (h_fin : μ t ≠ ∞) :
μ (s \ t) = μ (s ∪ t) - μ t :=
ENNReal.eq_sub_of_add_eq h_fin <| by rw [add_comm, measure_add_diff hm, union_comm]
theorem measure_diff (h : s₂ ⊆ s₁) (h₂ : NullMeasurableSet s₂ μ) (h_fin : μ s₂ ≠ ∞) :
μ (s₁ \ s₂) = μ s₁ - μ s₂ := by rw [measure_diff' _ h₂ h_fin, union_eq_self_of_subset_right h]
theorem le_measure_diff : μ s₁ - μ s₂ ≤ μ (s₁ \ s₂) :=
tsub_le_iff_left.2 <| (measure_le_inter_add_diff μ s₁ s₂).trans <| by
gcongr; apply inter_subset_right
/-- If the measure of the symmetric difference of two sets is finite,
then one has infinite measure if and only if the other one does. -/
theorem measure_eq_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s = ∞ ↔ μ t = ∞ := by
suffices h : ∀ u v, μ (u ∆ v) ≠ ∞ → μ u = ∞ → μ v = ∞
from ⟨h s t hμst, h t s (symmDiff_comm s t ▸ hμst)⟩
intro u v hμuv hμu
by_contra! hμv
apply hμuv
rw [Set.symmDiff_def, eq_top_iff]
calc
∞ = μ u - μ v := by rw [ENNReal.sub_eq_top_iff.2 ⟨hμu, hμv⟩]
_ ≤ μ (u \ v) := le_measure_diff
_ ≤ μ (u \ v ∪ v \ u) := measure_mono subset_union_left
/-- If the measure of the symmetric difference of two sets is finite,
then one has finite measure if and only if the other one does. -/
theorem measure_ne_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s ≠ ∞ ↔ μ t ≠ ∞ :=
(measure_eq_top_iff_of_symmDiff hμst).ne
theorem measure_diff_lt_of_lt_add (hs : NullMeasurableSet s μ) (hst : s ⊆ t) (hs' : μ s ≠ ∞)
{ε : ℝ≥0∞} (h : μ t < μ s + ε) : μ (t \ s) < ε := by
rw [measure_diff hst hs hs']; rw [add_comm] at h
exact ENNReal.sub_lt_of_lt_add (measure_mono hst) h
theorem measure_diff_le_iff_le_add (hs : NullMeasurableSet s μ) (hst : s ⊆ t) (hs' : μ s ≠ ∞)
{ε : ℝ≥0∞} : μ (t \ s) ≤ ε ↔ μ t ≤ μ s + ε := by
rw [measure_diff hst hs hs', tsub_le_iff_left]
theorem measure_eq_measure_of_null_diff {s t : Set α} (hst : s ⊆ t) (h_nulldiff : μ (t \ s) = 0) :
μ s = μ t := measure_congr <|
EventuallyLE.antisymm (HasSubset.Subset.eventuallyLE hst) (ae_le_set.mpr h_nulldiff)
theorem measure_eq_measure_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂) (h23 : s₂ ⊆ s₃)
(h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ ∧ μ s₂ = μ s₃ := by
have le12 : μ s₁ ≤ μ s₂ := measure_mono h12
have le23 : μ s₂ ≤ μ s₃ := measure_mono h23
have key : μ s₃ ≤ μ s₁ :=
calc
μ s₃ = μ (s₃ \ s₁ ∪ s₁) := by rw [diff_union_of_subset (h12.trans h23)]
_ ≤ μ (s₃ \ s₁) + μ s₁ := measure_union_le _ _
_ = μ s₁ := by simp only [h_nulldiff, zero_add]
exact ⟨le12.antisymm (le23.trans key), le23.antisymm (key.trans le12)⟩
theorem measure_eq_measure_smaller_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂)
(h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ :=
(measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).1
theorem measure_eq_measure_larger_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂)
(h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₂ = μ s₃ :=
(measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).2
lemma measure_compl₀ (h : NullMeasurableSet s μ) (hs : μ s ≠ ∞) :
μ sᶜ = μ Set.univ - μ s := by
rw [← measure_add_measure_compl₀ h, ENNReal.add_sub_cancel_left hs]
theorem measure_compl (h₁ : MeasurableSet s) (h_fin : μ s ≠ ∞) : μ sᶜ = μ univ - μ s :=
measure_compl₀ h₁.nullMeasurableSet h_fin
lemma measure_inter_conull' (ht : μ (s \ t) = 0) : μ (s ∩ t) = μ s := by
rw [← diff_compl, measure_diff_null']; rwa [← diff_eq]
lemma measure_inter_conull (ht : μ tᶜ = 0) : μ (s ∩ t) = μ s := by
rw [← diff_compl, measure_diff_null ht]
@[simp]
theorem union_ae_eq_left_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] s ↔ t ≤ᵐ[μ] s := by
rw [ae_le_set]
refine
⟨fun h => by simpa only [union_diff_left] using (ae_eq_set.mp h).1, fun h =>
eventuallyLE_antisymm_iff.mpr
⟨by rwa [ae_le_set, union_diff_left],
HasSubset.Subset.eventuallyLE subset_union_left⟩⟩
@[simp]
theorem union_ae_eq_right_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] t ↔ s ≤ᵐ[μ] t := by
rw [union_comm, union_ae_eq_left_iff_ae_subset]
theorem ae_eq_of_ae_subset_of_measure_ge (h₁ : s ≤ᵐ[μ] t) (h₂ : μ t ≤ μ s)
(hsm : NullMeasurableSet s μ) (ht : μ t ≠ ∞) : s =ᵐ[μ] t := by
refine eventuallyLE_antisymm_iff.mpr ⟨h₁, ae_le_set.mpr ?_⟩
replace h₂ : μ t = μ s := h₂.antisymm (measure_mono_ae h₁)
replace ht : μ s ≠ ∞ := h₂ ▸ ht
rw [measure_diff' t hsm ht, measure_congr (union_ae_eq_left_iff_ae_subset.mpr h₁), h₂, tsub_self]
/-- If `s ⊆ t`, `μ t ≤ μ s`, `μ t ≠ ∞`, and `s` is measurable, then `s =ᵐ[μ] t`. -/
theorem ae_eq_of_subset_of_measure_ge (h₁ : s ⊆ t) (h₂ : μ t ≤ μ s) (hsm : NullMeasurableSet s μ)
(ht : μ t ≠ ∞) : s =ᵐ[μ] t :=
ae_eq_of_ae_subset_of_measure_ge (HasSubset.Subset.eventuallyLE h₁) h₂ hsm ht
theorem measure_iUnion_congr_of_subset {ι : Sort*} [Countable ι] {s : ι → Set α} {t : ι → Set α}
(hsub : ∀ i, s i ⊆ t i) (h_le : ∀ i, μ (t i) ≤ μ (s i)) : μ (⋃ i, s i) = μ (⋃ i, t i) := by
refine le_antisymm (by gcongr; apply hsub) ?_
rcases Classical.em (∃ i, μ (t i) = ∞) with (⟨i, hi⟩ | htop)
· calc
μ (⋃ i, t i) ≤ ∞ := le_top
_ ≤ μ (s i) := hi ▸ h_le i
_ ≤ μ (⋃ i, s i) := measure_mono <| subset_iUnion _ _
push_neg at htop
set M := toMeasurable μ
have H : ∀ b, (M (t b) ∩ M (⋃ b, s b) : Set α) =ᵐ[μ] M (t b) := by
refine fun b => ae_eq_of_subset_of_measure_ge inter_subset_left ?_ ?_ ?_
· calc
μ (M (t b)) = μ (t b) := measure_toMeasurable _
_ ≤ μ (s b) := h_le b
_ ≤ μ (M (t b) ∩ M (⋃ b, s b)) :=
measure_mono <|
subset_inter ((hsub b).trans <| subset_toMeasurable _ _)
((subset_iUnion _ _).trans <| subset_toMeasurable _ _)
· measurability
· rw [measure_toMeasurable]
exact htop b
calc
μ (⋃ b, t b) ≤ μ (⋃ b, M (t b)) := measure_mono (iUnion_mono fun b => subset_toMeasurable _ _)
_ = μ (⋃ b, M (t b) ∩ M (⋃ b, s b)) := measure_congr (EventuallyEq.countable_iUnion H).symm
_ ≤ μ (M (⋃ b, s b)) := measure_mono (iUnion_subset fun b => inter_subset_right)
_ = μ (⋃ b, s b) := measure_toMeasurable _
theorem measure_union_congr_of_subset {t₁ t₂ : Set α} (hs : s₁ ⊆ s₂) (hsμ : μ s₂ ≤ μ s₁)
(ht : t₁ ⊆ t₂) (htμ : μ t₂ ≤ μ t₁) : μ (s₁ ∪ t₁) = μ (s₂ ∪ t₂) := by
rw [union_eq_iUnion, union_eq_iUnion]
exact measure_iUnion_congr_of_subset (Bool.forall_bool.2 ⟨ht, hs⟩) (Bool.forall_bool.2 ⟨htμ, hsμ⟩)
@[simp]
theorem measure_iUnion_toMeasurable {ι : Sort*} [Countable ι] (s : ι → Set α) :
μ (⋃ i, toMeasurable μ (s i)) = μ (⋃ i, s i) :=
Eq.symm <| measure_iUnion_congr_of_subset (fun _i => subset_toMeasurable _ _) fun _i ↦
(measure_toMeasurable _).le
theorem measure_biUnion_toMeasurable {I : Set β} (hc : I.Countable) (s : β → Set α) :
μ (⋃ b ∈ I, toMeasurable μ (s b)) = μ (⋃ b ∈ I, s b) := by
haveI := hc.toEncodable
simp only [biUnion_eq_iUnion, measure_iUnion_toMeasurable]
@[simp]
theorem measure_toMeasurable_union : μ (toMeasurable μ s ∪ t) = μ (s ∪ t) :=
Eq.symm <|
measure_union_congr_of_subset (subset_toMeasurable _ _) (measure_toMeasurable _).le Subset.rfl
le_rfl
@[simp]
theorem measure_union_toMeasurable : μ (s ∪ toMeasurable μ t) = μ (s ∪ t) :=
Eq.symm <|
measure_union_congr_of_subset Subset.rfl le_rfl (subset_toMeasurable _ _)
(measure_toMeasurable _).le
theorem sum_measure_le_measure_univ {s : Finset ι} {t : ι → Set α}
(h : ∀ i ∈ s, NullMeasurableSet (t i) μ) (H : Set.Pairwise s (AEDisjoint μ on t)) :
(∑ i ∈ s, μ (t i)) ≤ μ (univ : Set α) := by
rw [← measure_biUnion_finset₀ H h]
exact measure_mono (subset_univ _)
theorem tsum_measure_le_measure_univ {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ)
(H : Pairwise (AEDisjoint μ on s)) : ∑' i, μ (s i) ≤ μ (univ : Set α) := by
rw [ENNReal.tsum_eq_iSup_sum]
exact iSup_le fun s =>
sum_measure_le_measure_univ (fun i _hi => hs i) fun i _hi j _hj hij => H hij
/-- Pigeonhole principle for measure spaces: if `∑' i, μ (s i) > μ univ`, then
one of the intersections `s i ∩ s j` is not empty. -/
theorem exists_nonempty_inter_of_measure_univ_lt_tsum_measure {m : MeasurableSpace α}
(μ : Measure α) {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ)
(H : μ (univ : Set α) < ∑' i, μ (s i)) : ∃ i j, i ≠ j ∧ (s i ∩ s j).Nonempty := by
contrapose! H
apply tsum_measure_le_measure_univ hs
intro i j hij
exact (disjoint_iff_inter_eq_empty.mpr (H i j hij)).aedisjoint
/-- Pigeonhole principle for measure spaces: if `s` is a `Finset` and
`∑ i ∈ s, μ (t i) > μ univ`, then one of the intersections `t i ∩ t j` is not empty. -/
theorem exists_nonempty_inter_of_measure_univ_lt_sum_measure {m : MeasurableSpace α} (μ : Measure α)
{s : Finset ι} {t : ι → Set α} (h : ∀ i ∈ s, NullMeasurableSet (t i) μ)
(H : μ (univ : Set α) < ∑ i ∈ s, μ (t i)) :
∃ i ∈ s, ∃ j ∈ s, ∃ _h : i ≠ j, (t i ∩ t j).Nonempty := by
contrapose! H
apply sum_measure_le_measure_univ h
intro i hi j hj hij
exact (disjoint_iff_inter_eq_empty.mpr (H i hi j hj hij)).aedisjoint
/-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`,
then `s` intersects `t`. Version assuming that `t` is measurable. -/
theorem nonempty_inter_of_measure_lt_add {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α}
(ht : MeasurableSet t) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) :
(s ∩ t).Nonempty := by
rw [← Set.not_disjoint_iff_nonempty_inter]
contrapose! h
calc
μ s + μ t = μ (s ∪ t) := (measure_union h ht).symm
_ ≤ μ u := measure_mono (union_subset h's h't)
/-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`,
then `s` intersects `t`. Version assuming that `s` is measurable. -/
theorem nonempty_inter_of_measure_lt_add' {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α}
(hs : MeasurableSet s) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) :
(s ∩ t).Nonempty := by
rw [add_comm] at h
rw [inter_comm]
exact nonempty_inter_of_measure_lt_add μ hs h't h's h
/-- Continuity from below:
the measure of the union of a directed sequence of (not necessarily measurable) sets
is the supremum of the measures. -/
theorem _root_.Directed.measure_iUnion [Countable ι] {s : ι → Set α} (hd : Directed (· ⊆ ·) s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) := by
-- WLOG, `ι = ℕ`
rcases Countable.exists_injective_nat ι with ⟨e, he⟩
generalize ht : Function.extend e s ⊥ = t
replace hd : Directed (· ⊆ ·) t := ht ▸ hd.extend_bot he
suffices μ (⋃ n, t n) = ⨆ n, μ (t n) by
simp only [← ht, Function.apply_extend μ, ← iSup_eq_iUnion, iSup_extend_bot he,
Function.comp_def, Pi.bot_apply, bot_eq_empty, measure_empty] at this
exact this.trans (iSup_extend_bot he _)
clear! ι
-- The `≥` inequality is trivial
refine le_antisymm ?_ (iSup_le fun i ↦ measure_mono <| subset_iUnion _ _)
-- Choose `T n ⊇ t n` of the same measure, put `Td n = disjointed T`
set T : ℕ → Set α := fun n => toMeasurable μ (t n)
set Td : ℕ → Set α := disjointed T
have hm : ∀ n, MeasurableSet (Td n) := .disjointed fun n ↦ measurableSet_toMeasurable _ _
calc
μ (⋃ n, t n) = μ (⋃ n, Td n) := by rw [iUnion_disjointed, measure_iUnion_toMeasurable]
_ ≤ ∑' n, μ (Td n) := measure_iUnion_le _
_ = ⨆ I : Finset ℕ, ∑ n ∈ I, μ (Td n) := ENNReal.tsum_eq_iSup_sum
_ ≤ ⨆ n, μ (t n) := iSup_le fun I => by
rcases hd.finset_le I with ⟨N, hN⟩
calc
(∑ n ∈ I, μ (Td n)) = μ (⋃ n ∈ I, Td n) :=
(measure_biUnion_finset ((disjoint_disjointed T).set_pairwise I) fun n _ => hm n).symm
_ ≤ μ (⋃ n ∈ I, T n) := measure_mono (iUnion₂_mono fun n _hn => disjointed_subset _ _)
_ = μ (⋃ n ∈ I, t n) := measure_biUnion_toMeasurable I.countable_toSet _
_ ≤ μ (t N) := measure_mono (iUnion₂_subset hN)
_ ≤ ⨆ n, μ (t n) := le_iSup (μ ∘ t) N
/-- Continuity from below:
the measure of the union of a monotone family of sets is equal to the supremum of their measures.
The theorem assumes that the `atTop` filter on the index set is countably generated,
so it works for a family indexed by a countable type, as well as `ℝ`. -/
theorem _root_.Monotone.measure_iUnion [Preorder ι] [IsDirected ι (· ≤ ·)]
[(atTop : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Monotone s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) := by
cases isEmpty_or_nonempty ι with
| inl _ => simp
| inr _ =>
rcases exists_seq_monotone_tendsto_atTop_atTop ι with ⟨x, hxm, hx⟩
rw [← hs.iUnion_comp_tendsto_atTop hx, ← Monotone.iSup_comp_tendsto_atTop _ hx]
exacts [(hs.comp hxm).directed_le.measure_iUnion, fun _ _ h ↦ measure_mono (hs h)]
theorem _root_.Antitone.measure_iUnion [Preorder ι] [IsDirected ι (· ≥ ·)]
[(atBot : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Antitone s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) :=
hs.dual_left.measure_iUnion
/-- Continuity from below: the measure of the union of a sequence of
(not necessarily measurable) sets is the supremum of the measures of the partial unions. -/
theorem measure_iUnion_eq_iSup_accumulate [Preorder ι] [IsDirected ι (· ≤ ·)]
[(atTop : Filter ι).IsCountablyGenerated] {f : ι → Set α} :
μ (⋃ i, f i) = ⨆ i, μ (Accumulate f i) := by
rw [← iUnion_accumulate]
exact monotone_accumulate.measure_iUnion
theorem measure_biUnion_eq_iSup {s : ι → Set α} {t : Set ι} (ht : t.Countable)
(hd : DirectedOn ((· ⊆ ·) on s) t) : μ (⋃ i ∈ t, s i) = ⨆ i ∈ t, μ (s i) := by
haveI := ht.to_subtype
rw [biUnion_eq_iUnion, hd.directed_val.measure_iUnion, ← iSup_subtype'']
/-- **Continuity from above**:
the measure of the intersection of a directed downwards countable family of measurable sets
is the infimum of the measures. -/
theorem _root_.Directed.measure_iInter [Countable ι] {s : ι → Set α}
(h : ∀ i, NullMeasurableSet (s i) μ) (hd : Directed (· ⊇ ·) s) (hfin : ∃ i, μ (s i) ≠ ∞) :
μ (⋂ i, s i) = ⨅ i, μ (s i) := by
rcases hfin with ⟨k, hk⟩
have : ∀ t ⊆ s k, μ t ≠ ∞ := fun t ht => ne_top_of_le_ne_top hk (measure_mono ht)
rw [← ENNReal.sub_sub_cancel hk (iInf_le (fun i => μ (s i)) k), ENNReal.sub_iInf, ←
ENNReal.sub_sub_cancel hk (measure_mono (iInter_subset _ k)), ←
measure_diff (iInter_subset _ k) (.iInter h) (this _ (iInter_subset _ k)),
diff_iInter, Directed.measure_iUnion]
· congr 1
refine le_antisymm (iSup_mono' fun i => ?_) (iSup_mono fun i => le_measure_diff)
rcases hd i k with ⟨j, hji, hjk⟩
use j
rw [← measure_diff hjk (h _) (this _ hjk)]
gcongr
· exact hd.mono_comp _ fun _ _ => diff_subset_diff_right
/-- **Continuity from above**:
the measure of the intersection of a monotone family of measurable sets
indexed by a type with countably generated `atBot` filter
is equal to the infimum of the measures. -/
theorem _root_.Monotone.measure_iInter [Preorder ι] [IsDirected ι (· ≥ ·)]
[(atBot : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Monotone s)
(hsm : ∀ i, NullMeasurableSet (s i) μ) (hfin : ∃ i, μ (s i) ≠ ∞) :
μ (⋂ i, s i) = ⨅ i, μ (s i) := by
refine le_antisymm (le_iInf fun i ↦ measure_mono <| iInter_subset _ _) ?_
have := hfin.nonempty
rcases exists_seq_antitone_tendsto_atTop_atBot ι with ⟨x, hxm, hx⟩
calc
⨅ i, μ (s i) ≤ ⨅ n, μ (s (x n)) := le_iInf_comp (μ ∘ s) x
_ = μ (⋂ n, s (x n)) := by
refine .symm <| (hs.comp_antitone hxm).directed_ge.measure_iInter (fun n ↦ hsm _) ?_
rcases hfin with ⟨k, hk⟩
rcases (hx.eventually_le_atBot k).exists with ⟨n, hn⟩
exact ⟨n, ne_top_of_le_ne_top hk <| measure_mono <| hs hn⟩
_ ≤ μ (⋂ i, s i) := by
refine measure_mono <| iInter_mono' fun i ↦ ?_
rcases (hx.eventually_le_atBot i).exists with ⟨n, hn⟩
exact ⟨n, hs hn⟩
/-- **Continuity from above**:
the measure of the intersection of an antitone family of measurable sets
indexed by a type with countably generated `atTop` filter
is equal to the infimum of the measures. -/
theorem _root_.Antitone.measure_iInter [Preorder ι] [IsDirected ι (· ≤ ·)]
[(atTop : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Antitone s)
(hsm : ∀ i, NullMeasurableSet (s i) μ) (hfin : ∃ i, μ (s i) ≠ ∞) :
μ (⋂ i, s i) = ⨅ i, μ (s i) :=
hs.dual_left.measure_iInter hsm hfin
/-- Continuity from above: the measure of the intersection of a sequence of
measurable sets is the infimum of the measures of the partial intersections. -/
theorem measure_iInter_eq_iInf_measure_iInter_le {α ι : Type*} {_ : MeasurableSpace α}
{μ : Measure α} [Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)]
{f : ι → Set α} (h : ∀ i, NullMeasurableSet (f i) μ) (hfin : ∃ i, μ (f i) ≠ ∞) :
μ (⋂ i, f i) = ⨅ i, μ (⋂ j ≤ i, f j) := by
rw [← Antitone.measure_iInter]
· rw [iInter_comm]
exact congrArg μ <| iInter_congr fun i ↦ (biInf_const nonempty_Ici).symm
· exact fun i j h ↦ biInter_mono (Iic_subset_Iic.2 h) fun _ _ ↦ Set.Subset.rfl
· exact fun i ↦ .biInter (to_countable _) fun _ _ ↦ h _
· refine hfin.imp fun k hk ↦ ne_top_of_le_ne_top hk <| measure_mono <| iInter₂_subset k ?_
rfl
/-- Continuity from below: the measure of the union of an increasing sequence of (not necessarily
measurable) sets is the limit of the measures. -/
theorem tendsto_measure_iUnion_atTop [Preorder ι] [IsCountablyGenerated (atTop : Filter ι)]
{s : ι → Set α} (hm : Monotone s) : Tendsto (μ ∘ s) atTop (𝓝 (μ (⋃ n, s n))) := by
refine .of_neBot_imp fun h ↦ ?_
have := (atTop_neBot_iff.1 h).2
rw [hm.measure_iUnion]
exact tendsto_atTop_iSup fun n m hnm => measure_mono <| hm hnm
theorem tendsto_measure_iUnion_atBot [Preorder ι] [IsCountablyGenerated (atBot : Filter ι)]
{s : ι → Set α} (hm : Antitone s) : Tendsto (μ ∘ s) atBot (𝓝 (μ (⋃ n, s n))) :=
tendsto_measure_iUnion_atTop (ι := ιᵒᵈ) hm.dual_left
/-- Continuity from below: the measure of the union of a sequence of (not necessarily measurable)
sets is the limit of the measures of the partial unions. -/
theorem tendsto_measure_iUnion_accumulate {α ι : Type*}
[Preorder ι] [IsCountablyGenerated (atTop : Filter ι)]
{_ : MeasurableSpace α} {μ : Measure α} {f : ι → Set α} :
Tendsto (fun i ↦ μ (Accumulate f i)) atTop (𝓝 (μ (⋃ i, f i))) := by
refine .of_neBot_imp fun h ↦ ?_
have := (atTop_neBot_iff.1 h).2
rw [measure_iUnion_eq_iSup_accumulate]
exact tendsto_atTop_iSup fun i j hij ↦ by gcongr
/-- Continuity from above: the measure of the intersection of a decreasing sequence of measurable
sets is the limit of the measures. -/
theorem tendsto_measure_iInter_atTop [Preorder ι]
[IsCountablyGenerated (atTop : Filter ι)] {s : ι → Set α}
(hs : ∀ i, NullMeasurableSet (s i) μ) (hm : Antitone s) (hf : ∃ i, μ (s i) ≠ ∞) :
Tendsto (μ ∘ s) atTop (𝓝 (μ (⋂ n, s n))) := by
refine .of_neBot_imp fun h ↦ ?_
have := (atTop_neBot_iff.1 h).2
rw [hm.measure_iInter hs hf]
exact tendsto_atTop_iInf fun n m hnm => measure_mono <| hm hnm
/-- Continuity from above: the measure of the intersection of an increasing sequence of measurable
sets is the limit of the measures. -/
theorem tendsto_measure_iInter_atBot [Preorder ι] [IsCountablyGenerated (atBot : Filter ι)]
{s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ) (hm : Monotone s)
(hf : ∃ i, μ (s i) ≠ ∞) : Tendsto (μ ∘ s) atBot (𝓝 (μ (⋂ n, s n))) :=
tendsto_measure_iInter_atTop (ι := ιᵒᵈ) hs hm.dual_left hf
/-- Continuity from above: the measure of the intersection of a sequence of measurable
sets such that one has finite measure is the limit of the measures of the partial intersections. -/
theorem tendsto_measure_iInter_le {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α}
[Countable ι] [Preorder ι] {f : ι → Set α} (hm : ∀ i, NullMeasurableSet (f i) μ)
(hf : ∃ i, μ (f i) ≠ ∞) :
Tendsto (fun i ↦ μ (⋂ j ≤ i, f j)) atTop (𝓝 (μ (⋂ i, f i))) := by
refine .of_neBot_imp fun hne ↦ ?_
cases atTop_neBot_iff.mp hne
rw [measure_iInter_eq_iInf_measure_iInter_le hm hf]
exact tendsto_atTop_iInf
fun i j hij ↦ measure_mono <| biInter_subset_biInter_left fun k hki ↦ le_trans hki hij
/-- Some version of continuity of a measure in the empty set using the intersection along a set of
sets. -/
theorem exists_measure_iInter_lt {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α}
[SemilatticeSup ι] [Countable ι] {f : ι → Set α}
(hm : ∀ i, NullMeasurableSet (f i) μ) {ε : ℝ≥0∞} (hε : 0 < ε) (hfin : ∃ i, μ (f i) ≠ ∞)
(hfem : ⋂ n, f n = ∅) : ∃ m, μ (⋂ n ≤ m, f n) < ε := by
let F m := μ (⋂ n ≤ m, f n)
have hFAnti : Antitone F :=
fun i j hij => measure_mono (biInter_subset_biInter_left fun k hki => le_trans hki hij)
suffices Filter.Tendsto F Filter.atTop (𝓝 0) by
rw [@ENNReal.tendsto_atTop_zero_iff_lt_of_antitone
_ (nonempty_of_exists hfin) _ _ hFAnti] at this
exact this ε hε
have hzero : μ (⋂ n, f n) = 0 := by
simp only [hfem, measure_empty]
rw [← hzero]
exact tendsto_measure_iInter_le hm hfin
/-- The measure of the intersection of a decreasing sequence of measurable
sets indexed by a linear order with first countable topology is the limit of the measures. -/
theorem tendsto_measure_biInter_gt {ι : Type*} [LinearOrder ι] [TopologicalSpace ι]
[OrderTopology ι] [DenselyOrdered ι] [FirstCountableTopology ι] {s : ι → Set α}
{a : ι} (hs : ∀ r > a, NullMeasurableSet (s r) μ) (hm : ∀ i j, a < i → i ≤ j → s i ⊆ s j)
(hf : ∃ r > a, μ (s r) ≠ ∞) : Tendsto (μ ∘ s) (𝓝[Ioi a] a) (𝓝 (μ (⋂ r > a, s r))) := by
have : (atBot : Filter (Ioi a)).IsCountablyGenerated := by
rw [← comap_coe_Ioi_nhdsGT]
infer_instance
simp_rw [← map_coe_Ioi_atBot, tendsto_map'_iff, ← mem_Ioi, biInter_eq_iInter]
apply tendsto_measure_iInter_atBot
· rwa [Subtype.forall]
· exact fun i j h ↦ hm i j i.2 h
· simpa only [Subtype.exists, exists_prop]
theorem measure_if {x : β} {t : Set β} {s : Set α} [Decidable (x ∈ t)] :
μ (if x ∈ t then s else ∅) = indicator t (fun _ => μ s) x := by split_ifs with h <;> simp [h]
end
section OuterMeasure
variable [ms : MeasurableSpace α] {s t : Set α}
/-- Obtain a measure by giving an outer measure where all sets in the σ-algebra are
Carathéodory measurable. -/
def OuterMeasure.toMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) : Measure α :=
Measure.ofMeasurable (fun s _ => m s) m.empty fun _f hf hd =>
m.iUnion_eq_of_caratheodory (fun i => h _ (hf i)) hd
theorem le_toOuterMeasure_caratheodory (μ : Measure α) : ms ≤ μ.toOuterMeasure.caratheodory :=
fun _s hs _t => (measure_inter_add_diff _ hs).symm
@[simp]
theorem toMeasure_toOuterMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) :
(m.toMeasure h).toOuterMeasure = m.trim :=
rfl
@[simp]
theorem toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α}
(hs : MeasurableSet s) : m.toMeasure h s = m s :=
m.trim_eq hs
theorem le_toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) (s : Set α) :
m s ≤ m.toMeasure h s :=
m.le_trim s
theorem toMeasure_apply₀ (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α}
(hs : NullMeasurableSet s (m.toMeasure h)) : m.toMeasure h s = m s := by
refine le_antisymm ?_ (le_toMeasure_apply _ _ _)
rcases hs.exists_measurable_subset_ae_eq with ⟨t, hts, htm, heq⟩
calc
m.toMeasure h s = m.toMeasure h t := measure_congr heq.symm
_ = m t := toMeasure_apply m h htm
_ ≤ m s := m.mono hts
@[simp]
theorem toOuterMeasure_toMeasure {μ : Measure α} :
μ.toOuterMeasure.toMeasure (le_toOuterMeasure_caratheodory _) = μ :=
Measure.ext fun _s => μ.toOuterMeasure.trim_eq
@[simp]
theorem boundedBy_measure (μ : Measure α) : OuterMeasure.boundedBy μ = μ.toOuterMeasure :=
μ.toOuterMeasure.boundedBy_eq_self
end OuterMeasure
section
variable {m0 : MeasurableSpace α} {mβ : MeasurableSpace β} [MeasurableSpace γ]
variable {μ μ₁ μ₂ μ₃ ν ν' ν₁ ν₂ : Measure α} {s s' t : Set α}
namespace Measure
/-- If `u` is a superset of `t` with the same (finite) measure (both sets possibly non-measurable),
then for any measurable set `s` one also has `μ (t ∩ s) = μ (u ∩ s)`. -/
theorem measure_inter_eq_of_measure_eq {s t u : Set α} (hs : MeasurableSet s) (h : μ t = μ u)
(htu : t ⊆ u) (ht_ne_top : μ t ≠ ∞) : μ (t ∩ s) = μ (u ∩ s) := by
rw [h] at ht_ne_top
refine le_antisymm (by gcongr) ?_
have A : μ (u ∩ s) + μ (u \ s) ≤ μ (t ∩ s) + μ (u \ s) :=
calc
μ (u ∩ s) + μ (u \ s) = μ u := measure_inter_add_diff _ hs
_ = μ t := h.symm
_ = μ (t ∩ s) + μ (t \ s) := (measure_inter_add_diff _ hs).symm
_ ≤ μ (t ∩ s) + μ (u \ s) := by gcongr
have B : μ (u \ s) ≠ ∞ := (lt_of_le_of_lt (measure_mono diff_subset) ht_ne_top.lt_top).ne
exact ENNReal.le_of_add_le_add_right B A
/-- The measurable superset `toMeasurable μ t` of `t` (which has the same measure as `t`)
satisfies, for any measurable set `s`, the equality `μ (toMeasurable μ t ∩ s) = μ (u ∩ s)`.
Here, we require that the measure of `t` is finite. The conclusion holds without this assumption
when the measure is s-finite (for example when it is σ-finite),
see `measure_toMeasurable_inter_of_sFinite`. -/
theorem measure_toMeasurable_inter {s t : Set α} (hs : MeasurableSet s) (ht : μ t ≠ ∞) :
μ (toMeasurable μ t ∩ s) = μ (t ∩ s) :=
(measure_inter_eq_of_measure_eq hs (measure_toMeasurable t).symm (subset_toMeasurable μ t)
ht).symm
/-! ### The `ℝ≥0∞`-module of measures -/
instance instZero {_ : MeasurableSpace α} : Zero (Measure α) :=
⟨{ toOuterMeasure := 0
m_iUnion := fun _f _hf _hd => tsum_zero.symm
trim_le := OuterMeasure.trim_zero.le }⟩
| @[simp]
theorem zero_toOuterMeasure {_m : MeasurableSpace α} : (0 : Measure α).toOuterMeasure = 0 :=
rfl
@[simp, norm_cast]
theorem coe_zero {_m : MeasurableSpace α} : ⇑(0 : Measure α) = 0 :=
rfl
| Mathlib/MeasureTheory/Measure/MeasureSpace.lean | 748 | 755 |
/-
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.Attach
import Mathlib.Data.Finset.Disjoint
import Mathlib.Data.Finset.Erase
import Mathlib.Data.Finset.Filter
import Mathlib.Data.Finset.Range
import Mathlib.Data.Finset.SDiff
import Mathlib.Data.Multiset.Basic
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Defs
import Mathlib.Data.Set.SymmDiff
/-!
# Basic lemmas on finite sets
This file contains lemmas on the interaction of various definitions on the `Finset` type.
For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`.
## Main declarations
### Main definitions
* `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.
### Equivalences between finsets
* The `Mathlib/Logic/Equiv/Defs.lean` file describes 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 Multiset.powerset CompleteLattice Monoid
open Multiset Subtype Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
namespace Finset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
set_option linter.deprecated false in
@[deprecated "Deprecated without replacement." (since := "2025-02-07")]
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
cases s
dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf]
rw [Nat.add_comm]
refine lt_trans ?_ (Nat.lt_succ_self _)
exact Multiset.sizeOf_lt_sizeOf_of_mem hx
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-! #### union -/
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
@[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]
@[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]
/-! #### inter -/
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
omit [DecidableEq α] in
theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) :
Disjoint s t ↔ s = ∅ :=
disjoint_of_le_iff_left_eq_bot h
lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by
simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _),
not_disjoint_iff_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}
@[simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
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
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp +contextual only [mem_erase, mem_insert, and_congr_right_iff,
false_or, iff_self, imp_true_iff]
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]
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]
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]
@[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]
apply or_iff_right_of_imp
rintro rfl
exact h
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_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
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⟩⟩
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 _ _⟩
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]
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
theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s :=
subset_insert_iff.1 <| Subset.rfl
theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) :=
subset_insert_iff.2 <| Subset.rfl
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]
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]
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]
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}
lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by
ext; aesop
-- 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 \ {a} = erase s a := by
ext
rw [mem_erase, mem_sdiff, mem_singleton, and_comm]
-- 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
theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by
simp_rw [erase_eq, disjoint_sdiff_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⟩
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⟩
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]
@[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
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]
theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by
rw [erase_inter, inter_erase]
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]
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]
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]
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]
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]
theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by
simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)]
theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by
simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib,
inter_comm]
theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) :
insert x (s \ insert x t) = s \ t := by
rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)]
theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by
rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq,
union_comm]
theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by
rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq]
theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by
rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff]
--TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra`
theorem sdiff_disjoint : Disjoint (t \ s) s :=
disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2
theorem disjoint_sdiff : Disjoint s (t \ s) :=
sdiff_disjoint.symm
theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) :=
disjoint_of_subset_right inter_subset_right sdiff_disjoint
end Sdiff
/-! ### attach -/
@[simp]
theorem attach_empty : attach (∅ : Finset α) = ∅ :=
rfl
@[simp]
theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by
simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff
@[simp]
theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by
simp [eq_empty_iff_forall_not_mem]
/-! ### filter -/
section Filter
variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α}
theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by
classical
ext x
simp only [mem_singleton, forall_eq, mem_filter]
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) :
filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) :=
eq_of_veq <| Multiset.filter_cons_of_pos s.val hp
theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) :
filter p (cons a s ha) = filter p s :=
eq_of_veq <| Multiset.filter_cons_of_neg s.val hp
theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] :
Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by
constructor <;> simp +contextual [disjoint_left]
theorem disjoint_filter_filter' (s t : Finset α)
{p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) :
Disjoint (s.filter p) (t.filter q) := by
simp_rw [disjoint_left, mem_filter]
rintro a ⟨_, hp⟩ ⟨_, hq⟩
rw [Pi.disjoint_iff] at h
simpa [hp, hq] using h a
theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop)
[DecidablePred p] [∀ x, Decidable (¬p x)] :
Disjoint (s.filter p) (t.filter fun a => ¬p a) :=
disjoint_filter_filter' s t disjoint_compl_right
theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) :
filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) :=
eq_of_veq <| Multiset.filter_add _ _ _
theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) :
filter p (cons a s ha) =
if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by
split_ifs with h
· rw [filter_cons_of_pos _ _ _ ha h]
· rw [filter_cons_of_neg _ _ _ ha h]
section
variable [DecidableEq α]
theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p :=
ext fun _ => by simp only [mem_filter, mem_union, or_and_right]
theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x :=
ext fun x => by simp [mem_filter, mem_union, ← and_or_left]
theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] :
(s.filter fun i => i ∈ t) = s ∩ t :=
ext fun i => by simp [mem_filter, mem_inter]
theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by
ext
simp [mem_filter, mem_inter, and_assoc]
theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by
ext
simp only [mem_inter, mem_filter, and_right_comm]
theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by
rw [inter_comm, filter_inter, inter_comm]
theorem filter_insert (a : α) (s : Finset α) :
filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by
ext x
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by
ext x
simp only [and_assoc, mem_filter, iff_self, mem_erase]
theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q :=
ext fun _ => by simp [mem_filter, mem_union, and_or_left]
theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q :=
ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc]
theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p :=
ext fun a => by
simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or,
Bool.not_eq_true, and_or_left, and_not_self, or_false]
lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] :
s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by
rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)]
theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ :=
ext fun _ => by simp [mem_sdiff, mem_filter]
theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) :
∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by
classical
refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩
· simp [filter_union_right, em]
· intro x
simp
· intro x
simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp]
intro hx hx₂
exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩
-- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing
-- on, e.g. `x ∈ s.filter (Eq b)`.
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq'` with the equality the other way.
-/
theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) :
s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by
split_ifs with h
· ext
simp only [mem_filter, mem_singleton, decide_eq_true_eq]
refine ⟨fun h => h.2.symm, ?_⟩
rintro rfl
exact ⟨h, rfl⟩
· ext
simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq]
rintro m rfl
exact h m
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq` with the equality the other way.
-/
theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b)
theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => b ≠ a) = s.erase b := by
ext
simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not]
tauto
theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b)
theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) :
s.filter p ∪ s.filter q = s :=
(filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial
theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) :
(s.filter p ∪ s.filter fun a => ¬p a) = s :=
filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p
end
end Filter
/-! ### range -/
section Range
open Nat
variable {n m l : ℕ}
@[simp]
theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by
convert filter_eq (range n) m using 2
· ext
rw [eq_comm]
· simp
end Range
end Finset
/-! ### dedup on list and multiset -/
namespace Multiset
variable [DecidableEq α] {s t : Multiset α}
@[simp]
theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by
ext; simp
@[simp]
theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 :=
Finset.val_inj.symm.trans Multiset.dedup_eq_zero
@[simp]
theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by
simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty
@[simp]
theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] :
Multiset.toFinset (s.filter p) = s.toFinset.filter p := by
ext; simp
end Multiset
namespace List
variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β}
{s : Finset α} {t : Set β} {t' : Finset β}
@[simp]
theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by
ext
simp
@[simp]
theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by
ext
simp
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff
@[simp]
theorem toFinset_filter (s : List α) (p : α → Bool) :
(s.filter p).toFinset = s.toFinset.filter (p ·) := by
ext; simp [List.mem_filter]
end List
namespace Finset
section ToList
@[simp]
theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ :=
Multiset.toList_eq_nil.trans val_eq_zero
theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp
@[simp]
theorem toList_empty : (∅ : Finset α).toList = [] :=
toList_eq_nil.mpr rfl
theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] :=
mt toList_eq_nil.mp hs.ne_empty
theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty :=
mt empty_toList.mp hs.ne_empty
end ToList
/-! ### choose -/
section Choose
variable (p : α → Prop) [DecidablePred p] (l : Finset α)
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the corresponding subtype. -/
def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } :=
Multiset.chooseX p l.val hp
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the ambient type. -/
def choose (hp : ∃! a, a ∈ l ∧ p a) : α :=
chooseX p l hp
theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) :=
(chooseX p l hp).property
theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l :=
(choose_spec _ _ _).1
theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) :=
(choose_spec _ _ _).2
end Choose
end Finset
namespace Equiv
variable [DecidableEq α] {s t : Finset α}
open Finset
/-- The disjoint union of finsets is a sum -/
def Finset.union (s t : Finset α) (h : Disjoint s t) :
s ⊕ t ≃ (s ∪ t : Finset α) :=
Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm
@[simp]
theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) :
Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ :=
rfl
@[simp]
theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) :
Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ :=
rfl
/-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the
type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/
def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) :
((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i :=
let e := Equiv.Finset.union s t h
sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e)
/-- A finset is equivalent to its coercion as a set. -/
def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where
toFun a := ⟨a.1, mem_coe.2 a.2⟩
invFun a := ⟨a.1, mem_coe.1 a.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end Equiv
namespace Multiset
variable [DecidableEq α]
@[simp]
lemma toFinset_replicate (n : ℕ) (a : α) :
(replicate n a).toFinset = if n = 0 then ∅ else {a} := by
ext x
simp only [mem_toFinset, Finset.mem_singleton, mem_replicate]
split_ifs with hn <;> simp [hn]
end Multiset
| Mathlib/Data/Finset/Basic.lean | 2,292 | 2,294 | |
/-
Copyright (c) 2018 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Mario Carneiro, Simon Hudon
-/
import Mathlib.Data.Fin.Fin2
import Mathlib.Logic.Function.Basic
import Mathlib.Tactic.Common
/-!
# Tuples of types, and their categorical structure.
## Features
* `TypeVec n` - n-tuples of types
* `α ⟹ β` - n-tuples of maps
* `f ⊚ g` - composition
Also, support functions for operating with n-tuples of types, such as:
* `append1 α β` - append type `β` to n-tuple `α` to obtain an (n+1)-tuple
* `drop α` - drops the last element of an (n+1)-tuple
* `last α` - returns the last element of an (n+1)-tuple
* `appendFun f g` - appends a function g to an n-tuple of functions
* `dropFun f` - drops the last function from an n+1-tuple
* `lastFun f` - returns the last function of a tuple.
Since e.g. `append1 α.drop α.last` is propositionally equal to `α` but not definitionally equal
to it, we need support functions and lemmas to mediate between constructions.
-/
universe u v w
/-- n-tuples of types, as a category -/
@[pp_with_univ]
def TypeVec (n : ℕ) :=
Fin2 n → Type*
instance {n} : Inhabited (TypeVec.{u} n) :=
⟨fun _ => PUnit⟩
namespace TypeVec
variable {n : ℕ}
/-- arrow in the category of `TypeVec` -/
def Arrow (α β : TypeVec n) :=
∀ i : Fin2 n, α i → β i
@[inherit_doc] scoped[MvFunctor] infixl:40 " ⟹ " => TypeVec.Arrow
open MvFunctor
/-- Extensionality for arrows -/
@[ext]
theorem Arrow.ext {α β : TypeVec n} (f g : α ⟹ β) :
(∀ i, f i = g i) → f = g := by
intro h; funext i; apply h
instance Arrow.inhabited (α β : TypeVec n) [∀ i, Inhabited (β i)] : Inhabited (α ⟹ β) :=
⟨fun _ _ => default⟩
/-- identity of arrow composition -/
def id {α : TypeVec n} : α ⟹ α := fun _ x => x
/-- arrow composition in the category of `TypeVec` -/
def comp {α β γ : TypeVec n} (g : β ⟹ γ) (f : α ⟹ β) : α ⟹ γ := fun i x => g i (f i x)
@[inherit_doc] scoped[MvFunctor] infixr:80 " ⊚ " => TypeVec.comp -- type as \oo
@[simp]
theorem id_comp {α β : TypeVec n} (f : α ⟹ β) : id ⊚ f = f :=
rfl
@[simp]
theorem comp_id {α β : TypeVec n} (f : α ⟹ β) : f ⊚ id = f :=
rfl
theorem comp_assoc {α β γ δ : TypeVec n} (h : γ ⟹ δ) (g : β ⟹ γ) (f : α ⟹ β) :
(h ⊚ g) ⊚ f = h ⊚ g ⊚ f :=
rfl
/-- Support for extending a `TypeVec` by one element. -/
def append1 (α : TypeVec n) (β : Type*) : TypeVec (n + 1)
| Fin2.fs i => α i
| Fin2.fz => β
@[inherit_doc] infixl:67 " ::: " => append1
/-- retain only a `n-length` prefix of the argument -/
def drop (α : TypeVec.{u} (n + 1)) : TypeVec n := fun i => α i.fs
/-- take the last value of a `(n+1)-length` vector -/
def last (α : TypeVec.{u} (n + 1)) : Type _ :=
α Fin2.fz
instance last.inhabited (α : TypeVec (n + 1)) [Inhabited (α Fin2.fz)] : Inhabited (last α) :=
⟨show α Fin2.fz from default⟩
theorem drop_append1 {α : TypeVec n} {β : Type*} {i : Fin2 n} : drop (append1 α β) i = α i :=
rfl
theorem drop_append1' {α : TypeVec n} {β : Type*} : drop (append1 α β) = α :=
funext fun _ => drop_append1
theorem last_append1 {α : TypeVec n} {β : Type*} : last (append1 α β) = β :=
rfl
@[simp]
theorem append1_drop_last (α : TypeVec (n + 1)) : append1 (drop α) (last α) = α :=
funext fun i => by cases i <;> rfl
/-- cases on `(n+1)-length` vectors -/
@[elab_as_elim]
def append1Cases {C : TypeVec (n + 1) → Sort u} (H : ∀ α β, C (append1 α β)) (γ) : C γ := by
rw [← @append1_drop_last _ γ]; apply H
@[simp]
theorem append1_cases_append1 {C : TypeVec (n + 1) → Sort u} (H : ∀ α β, C (append1 α β)) (α β) :
@append1Cases _ C H (append1 α β) = H α β :=
rfl
/-- append an arrow and a function for arbitrary source and target type vectors -/
def splitFun {α α' : TypeVec (n + 1)} (f : drop α ⟹ drop α') (g : last α → last α') : α ⟹ α'
| Fin2.fs i => f i
| Fin2.fz => g
/-- append an arrow and a function as well as their respective source and target types / typevecs -/
def appendFun {α α' : TypeVec n} {β β' : Type*} (f : α ⟹ α') (g : β → β') :
append1 α β ⟹ append1 α' β' :=
splitFun f g
@[inherit_doc] infixl:0 " ::: " => appendFun
/-- split off the prefix of an arrow -/
def dropFun {α β : TypeVec (n + 1)} (f : α ⟹ β) : drop α ⟹ drop β := fun i => f i.fs
/-- split off the last function of an arrow -/
def lastFun {α β : TypeVec (n + 1)} (f : α ⟹ β) : last α → last β :=
f Fin2.fz
/-- arrow in the category of `0-length` vectors -/
def nilFun {α : TypeVec 0} {β : TypeVec 0} : α ⟹ β := fun i => by apply Fin2.elim0 i
theorem eq_of_drop_last_eq {α β : TypeVec (n + 1)} {f g : α ⟹ β} (h₀ : dropFun f = dropFun g)
(h₁ : lastFun f = lastFun g) : f = g := by
refine funext (fun x => ?_)
cases x
· apply h₁
· apply congr_fun h₀
@[simp]
theorem dropFun_splitFun {α α' : TypeVec (n + 1)} (f : drop α ⟹ drop α') (g : last α → last α') :
dropFun (splitFun f g) = f :=
rfl
/-- turn an equality into an arrow -/
def Arrow.mp {α β : TypeVec n} (h : α = β) : α ⟹ β
| _ => Eq.mp (congr_fun h _)
/-- turn an equality into an arrow, with reverse direction -/
def Arrow.mpr {α β : TypeVec n} (h : α = β) : β ⟹ α
| _ => Eq.mpr (congr_fun h _)
/-- decompose a vector into its prefix appended with its last element -/
def toAppend1DropLast {α : TypeVec (n + 1)} : α ⟹ (drop α ::: last α) :=
Arrow.mpr (append1_drop_last _)
/-- stitch two bits of a vector back together -/
def fromAppend1DropLast {α : TypeVec (n + 1)} : (drop α ::: last α) ⟹ α :=
Arrow.mp (append1_drop_last _)
@[simp]
theorem lastFun_splitFun {α α' : TypeVec (n + 1)} (f : drop α ⟹ drop α') (g : last α → last α') :
lastFun (splitFun f g) = g :=
rfl
@[simp]
theorem dropFun_appendFun {α α' : TypeVec n} {β β' : Type*} (f : α ⟹ α') (g : β → β') :
dropFun (f ::: g) = f :=
rfl
@[simp]
theorem lastFun_appendFun {α α' : TypeVec n} {β β' : Type*} (f : α ⟹ α') (g : β → β') :
lastFun (f ::: g) = g :=
rfl
theorem split_dropFun_lastFun {α α' : TypeVec (n + 1)} (f : α ⟹ α') :
splitFun (dropFun f) (lastFun f) = f :=
eq_of_drop_last_eq rfl rfl
theorem splitFun_inj {α α' : TypeVec (n + 1)} {f f' : drop α ⟹ drop α'} {g g' : last α → last α'}
(H : splitFun f g = splitFun f' g') : f = f' ∧ g = g' := by
rw [← dropFun_splitFun f g, H, ← lastFun_splitFun f g, H]; simp
theorem appendFun_inj {α α' : TypeVec n} {β β' : Type*} {f f' : α ⟹ α'} {g g' : β → β'} :
(f ::: g : (α ::: β) ⟹ _) = (f' ::: g' : (α ::: β) ⟹ _)
→ f = f' ∧ g = g' :=
splitFun_inj
theorem splitFun_comp {α₀ α₁ α₂ : TypeVec (n + 1)} (f₀ : drop α₀ ⟹ drop α₁)
(f₁ : drop α₁ ⟹ drop α₂) (g₀ : last α₀ → last α₁) (g₁ : last α₁ → last α₂) :
splitFun (f₁ ⊚ f₀) (g₁ ∘ g₀) = splitFun f₁ g₁ ⊚ splitFun f₀ g₀ :=
eq_of_drop_last_eq rfl rfl
theorem appendFun_comp_splitFun {α γ : TypeVec n} {β δ : Type*} {ε : TypeVec (n + 1)}
(f₀ : drop ε ⟹ α) (f₁ : α ⟹ γ) (g₀ : last ε → β) (g₁ : β → δ) :
appendFun f₁ g₁ ⊚ splitFun f₀ g₀ = splitFun (α' := γ.append1 δ) (f₁ ⊚ f₀) (g₁ ∘ g₀) :=
(splitFun_comp _ _ _ _).symm
theorem appendFun_comp {α₀ α₁ α₂ : TypeVec n}
{β₀ β₁ β₂ : Type*}
(f₀ : α₀ ⟹ α₁) (f₁ : α₁ ⟹ α₂)
(g₀ : β₀ → β₁) (g₁ : β₁ → β₂) :
(f₁ ⊚ f₀ ::: g₁ ∘ g₀) = (f₁ ::: g₁) ⊚ (f₀ ::: g₀) :=
eq_of_drop_last_eq rfl rfl
theorem appendFun_comp' {α₀ α₁ α₂ : TypeVec n} {β₀ β₁ β₂ : Type*}
(f₀ : α₀ ⟹ α₁) (f₁ : α₁ ⟹ α₂) (g₀ : β₀ → β₁) (g₁ : β₁ → β₂) :
(f₁ ::: g₁) ⊚ (f₀ ::: g₀) = (f₁ ⊚ f₀ ::: g₁ ∘ g₀) :=
eq_of_drop_last_eq rfl rfl
theorem nilFun_comp {α₀ : TypeVec 0} (f₀ : α₀ ⟹ Fin2.elim0) : nilFun ⊚ f₀ = f₀ :=
funext Fin2.elim0
theorem appendFun_comp_id {α : TypeVec n} {β₀ β₁ β₂ : Type u} (g₀ : β₀ → β₁) (g₁ : β₁ → β₂) :
(@id _ α ::: g₁ ∘ g₀) = (id ::: g₁) ⊚ (id ::: g₀) :=
eq_of_drop_last_eq rfl rfl
@[simp]
theorem dropFun_comp {α₀ α₁ α₂ : TypeVec (n + 1)} (f₀ : α₀ ⟹ α₁) (f₁ : α₁ ⟹ α₂) :
dropFun (f₁ ⊚ f₀) = dropFun f₁ ⊚ dropFun f₀ :=
rfl
@[simp]
theorem lastFun_comp {α₀ α₁ α₂ : TypeVec (n + 1)} (f₀ : α₀ ⟹ α₁) (f₁ : α₁ ⟹ α₂) :
lastFun (f₁ ⊚ f₀) = lastFun f₁ ∘ lastFun f₀ :=
rfl
theorem appendFun_aux {α α' : TypeVec n} {β β' : Type*} (f : (α ::: β) ⟹ (α' ::: β')) :
(dropFun f ::: lastFun f) = f :=
eq_of_drop_last_eq rfl rfl
theorem appendFun_id_id {α : TypeVec n} {β : Type*} :
(@TypeVec.id n α ::: @_root_.id β) = TypeVec.id :=
eq_of_drop_last_eq rfl rfl
instance subsingleton0 : Subsingleton (TypeVec 0) :=
⟨fun _ _ => funext Fin2.elim0⟩
-- See `Mathlib.Tactic.Attr.Register` for `register_simp_attr typevec`
/-- cases distinction for 0-length type vector -/
protected def casesNil {β : TypeVec 0 → Sort*} (f : β Fin2.elim0) : ∀ v, β v :=
fun v => cast (by congr; funext i; cases i) f
/-- cases distinction for (n+1)-length type vector -/
protected def casesCons (n : ℕ) {β : TypeVec (n + 1) → Sort*}
(f : ∀ (t) (v : TypeVec n), β (v ::: t)) :
∀ v, β v :=
fun v : TypeVec (n + 1) => cast (by simp) (f v.last v.drop)
protected theorem casesNil_append1 {β : TypeVec 0 → Sort*} (f : β Fin2.elim0) :
TypeVec.casesNil f Fin2.elim0 = f :=
rfl
protected theorem casesCons_append1 (n : ℕ) {β : TypeVec (n + 1) → Sort*}
(f : ∀ (t) (v : TypeVec n), β (v ::: t)) (v : TypeVec n) (α) :
TypeVec.casesCons n f (v ::: α) = f α v :=
rfl
/-- cases distinction for an arrow in the category of 0-length type vectors -/
def typevecCasesNil₃ {β : ∀ v v' : TypeVec 0, v ⟹ v' → Sort*}
(f : β Fin2.elim0 Fin2.elim0 nilFun) :
∀ v v' fs, β v v' fs := fun v v' fs => by
refine cast ?_ f
have eq₁ : v = Fin2.elim0 := by funext i; contradiction
have eq₂ : v' = Fin2.elim0 := by funext i; contradiction
have eq₃ : fs = nilFun := by funext i; contradiction
cases eq₁; cases eq₂; cases eq₃; rfl
/-- cases distinction for an arrow in the category of (n+1)-length type vectors -/
def typevecCasesCons₃ (n : ℕ) {β : ∀ v v' : TypeVec (n + 1), v ⟹ v' → Sort*}
(F : ∀ (t t') (f : t → t') (v v' : TypeVec n) (fs : v ⟹ v'),
β (v ::: t) (v' ::: t') (fs ::: f)) :
∀ v v' fs, β v v' fs := by
intro v v'
rw [← append1_drop_last v, ← append1_drop_last v']
intro fs
rw [← split_dropFun_lastFun fs]
apply F
/-- specialized cases distinction for an arrow in the category of 0-length type vectors -/
def typevecCasesNil₂ {β : Fin2.elim0 ⟹ Fin2.elim0 → Sort*} (f : β nilFun) : ∀ f, β f := by
intro g
suffices g = nilFun by rwa [this]
ext ⟨⟩
/-- specialized cases distinction for an arrow in the category of (n+1)-length type vectors -/
def typevecCasesCons₂ (n : ℕ) (t t' : Type*) (v v' : TypeVec n)
{β : (v ::: t) ⟹ (v' ::: t') → Sort*}
(F : ∀ (f : t → t') (fs : v ⟹ v'), β (fs ::: f)) : ∀ fs, β fs := by
intro fs
rw [← split_dropFun_lastFun fs]
apply F
theorem typevecCasesNil₂_appendFun {β : Fin2.elim0 ⟹ Fin2.elim0 → Sort*} (f : β nilFun) :
typevecCasesNil₂ f nilFun = f :=
rfl
theorem typevecCasesCons₂_appendFun (n : ℕ) (t t' : Type*) (v v' : TypeVec n)
{β : (v ::: t) ⟹ (v' ::: t') → Sort*}
(F : ∀ (f : t → t') (fs : v ⟹ v'), β (fs ::: f))
(f fs) :
typevecCasesCons₂ n t t' v v' F (fs ::: f) = F f fs :=
rfl
-- for lifting predicates and relations
/-- `PredLast α p x` predicates `p` of the last element of `x : α.append1 β`. -/
def PredLast (α : TypeVec n) {β : Type*} (p : β → Prop) : ∀ ⦃i⦄, (α.append1 β) i → Prop
| Fin2.fs _ => fun _ => True
| Fin2.fz => p
/-- `RelLast α r x y` says that `p` the last elements of `x y : α.append1 β` are related by `r` and
all the other elements are equal. -/
def RelLast (α : TypeVec n) {β γ : Type u} (r : β → γ → Prop) :
∀ ⦃i⦄, (α.append1 β) i → (α.append1 γ) i → Prop
| Fin2.fs _ => Eq
| Fin2.fz => r
section Liftp'
open Nat
/-- `repeat n t` is a `n-length` type vector that contains `n` occurrences of `t` -/
def «repeat» : ∀ (n : ℕ), Sort _ → TypeVec n
| 0, _ => Fin2.elim0
| Nat.succ i, t => append1 («repeat» i t) t
/-- `prod α β` is the pointwise product of the components of `α` and `β` -/
def prod : ∀ {n}, TypeVec.{u} n → TypeVec.{u} n → TypeVec n
| 0, _, _ => Fin2.elim0
| n + 1, α, β => (@prod n (drop α) (drop β)) ::: (last α × last β)
@[inherit_doc] scoped[MvFunctor] infixl:45 " ⊗ " => TypeVec.prod
/-- `const x α` is an arrow that ignores its source and constructs a `TypeVec` that
contains nothing but `x` -/
protected def const {β} (x : β) : ∀ {n} (α : TypeVec n), α ⟹ «repeat» _ β
| succ _, α, Fin2.fs _ => TypeVec.const x (drop α) _
| succ _, _, Fin2.fz => fun _ => x
open Function (uncurry)
/-- vector of equality on a product of vectors -/
def repeatEq : ∀ {n} (α : TypeVec n), (α ⊗ α) ⟹ «repeat» _ Prop
| 0, _ => nilFun
| succ _, α => repeatEq (drop α) ::: uncurry Eq
theorem const_append1 {β γ} (x : γ) {n} (α : TypeVec n) :
TypeVec.const x (α ::: β) = appendFun (TypeVec.const x α) fun _ => x := by
ext i : 1; cases i <;> rfl
theorem eq_nilFun {α β : TypeVec 0} (f : α ⟹ β) : f = nilFun := by
ext x; cases x
theorem id_eq_nilFun {α : TypeVec 0} : @id _ α = nilFun := by
ext x; cases x
theorem const_nil {β} (x : β) (α : TypeVec 0) : TypeVec.const x α = nilFun := by
ext i : 1; cases i
@[typevec]
theorem repeat_eq_append1 {β} {n} (α : TypeVec n) :
repeatEq (α ::: β) = splitFun (α := (α ⊗ α) ::: _)
(α' := («repeat» n Prop) ::: _) (repeatEq α) (uncurry Eq) := by
induction n <;> rfl
@[typevec]
theorem repeat_eq_nil (α : TypeVec 0) : repeatEq α = nilFun := by ext i; cases i
/-- predicate on a type vector to constrain only the last object -/
def PredLast' (α : TypeVec n) {β : Type*} (p : β → Prop) :
(α ::: β) ⟹ «repeat» (n + 1) Prop :=
splitFun (TypeVec.const True α) p
/-- predicate on the product of two type vectors to constrain only their last object -/
def RelLast' (α : TypeVec n) {β : Type*} (p : β → β → Prop) :
(α ::: β) ⊗ (α ::: β) ⟹ «repeat» (n + 1) Prop :=
splitFun (repeatEq α) (uncurry p)
/-- given `F : TypeVec.{u} (n+1) → Type u`, `curry F : Type u → TypeVec.{u} → Type u`,
i.e. its first argument can be fed in separately from the rest of the vector of arguments -/
def Curry (F : TypeVec.{u} (n + 1) → Type*) (α : Type u) (β : TypeVec.{u} n) : Type _ :=
F (β ::: α)
instance Curry.inhabited (F : TypeVec.{u} (n + 1) → Type*) (α : Type u) (β : TypeVec.{u} n)
[I : Inhabited (F <| (β ::: α))] : Inhabited (Curry F α β) :=
I
/-- arrow to remove one element of a `repeat` vector -/
def dropRepeat (α : Type*) : ∀ {n}, drop («repeat» (succ n) α) ⟹ «repeat» n α
| succ _, Fin2.fs i => dropRepeat α i
| succ _, Fin2.fz => fun (a : α) => a
/-- projection for a repeat vector -/
def ofRepeat {α : Sort _} : ∀ {n i}, «repeat» n α i → α
| _, Fin2.fz => fun (a : α) => a
| _, Fin2.fs i => @ofRepeat _ _ i
theorem const_iff_true {α : TypeVec n} {i x p} : ofRepeat (TypeVec.const p α i x) ↔ p := by
induction i with
| fz => rfl
| fs _ ih =>
rw [TypeVec.const]
exact ih
section
variable {α β : TypeVec.{u} n}
variable (p : α ⟹ «repeat» n Prop)
/-- left projection of a `prod` vector -/
def prod.fst : ∀ {n} {α β : TypeVec.{u} n}, α ⊗ β ⟹ α
| succ _, α, β, Fin2.fs i => @prod.fst _ (drop α) (drop β) i
| succ _, _, _, Fin2.fz => Prod.fst
/-- right projection of a `prod` vector -/
def prod.snd : ∀ {n} {α β : TypeVec.{u} n}, α ⊗ β ⟹ β
| succ _, α, β, Fin2.fs i => @prod.snd _ (drop α) (drop β) i
| succ _, _, _, Fin2.fz => Prod.snd
/-- introduce a product where both components are the same -/
def prod.diag : ∀ {n} {α : TypeVec.{u} n}, α ⟹ α ⊗ α
| succ _, α, Fin2.fs _, x => @prod.diag _ (drop α) _ x
| succ _, _, Fin2.fz, x => (x, x)
/-- constructor for `prod` -/
def prod.mk : ∀ {n} {α β : TypeVec.{u} n} (i : Fin2 n), α i → β i → (α ⊗ β) i
| succ _, α, β, Fin2.fs i => mk (α := fun i => α i.fs) (β := fun i => β i.fs) i
| succ _, _, _, Fin2.fz => Prod.mk
end
@[simp]
theorem prod_fst_mk {α β : TypeVec n} (i : Fin2 n) (a : α i) (b : β i) :
TypeVec.prod.fst i (prod.mk i a b) = a := by
induction i with
| fz => simp_all only [prod.fst, prod.mk]
| fs _ i_ih => apply i_ih
@[simp]
theorem prod_snd_mk {α β : TypeVec n} (i : Fin2 n) (a : α i) (b : β i) :
TypeVec.prod.snd i (prod.mk i a b) = b := by
induction i with
| fz => simp_all [prod.snd, prod.mk]
| fs _ i_ih => apply i_ih
/-- `prod` is functorial -/
protected def prod.map : ∀ {n} {α α' β β' : TypeVec.{u} n}, α ⟹ β → α' ⟹ β' → α ⊗ α' ⟹ β ⊗ β'
| succ _, α, α', β, β', x, y, Fin2.fs _, a =>
@prod.map _ (drop α) (drop α') (drop β) (drop β') (dropFun x) (dropFun y) _ a
| succ _, _, _, _, _, x, y, Fin2.fz, a => (x _ a.1, y _ a.2)
@[inherit_doc] scoped[MvFunctor] infixl:45 " ⊗' " => TypeVec.prod.map
theorem fst_prod_mk {α α' β β' : TypeVec n} (f : α ⟹ β) (g : α' ⟹ β') :
TypeVec.prod.fst ⊚ (f ⊗' g) = f ⊚ TypeVec.prod.fst := by
funext i; induction i with
| fz => rfl
| fs _ i_ih => apply i_ih
theorem snd_prod_mk {α α' β β' : TypeVec n} (f : α ⟹ β) (g : α' ⟹ β') :
TypeVec.prod.snd ⊚ (f ⊗' g) = g ⊚ TypeVec.prod.snd := by
funext i; induction i with
| fz => rfl
| fs _ i_ih => apply i_ih
theorem fst_diag {α : TypeVec n} : TypeVec.prod.fst ⊚ (prod.diag : α ⟹ _) = id := by
funext i; induction i with
| fz => rfl
| fs _ i_ih => apply i_ih
theorem snd_diag {α : TypeVec n} : TypeVec.prod.snd ⊚ (prod.diag : α ⟹ _) = id := by
funext i; induction i with
| fz => rfl
| fs _ i_ih => apply i_ih
theorem repeatEq_iff_eq {α : TypeVec n} {i x y} :
ofRepeat (repeatEq α i (prod.mk _ x y)) ↔ x = y := by
induction i with
| fz => rfl
| fs _ i_ih =>
rw [repeatEq]
exact i_ih
/-- given a predicate vector `p` over vector `α`, `Subtype_ p` is the type of vectors
that contain an `α` that satisfies `p` -/
def Subtype_ : ∀ {n} {α : TypeVec.{u} n}, (α ⟹ «repeat» n Prop) → TypeVec n
| _, _, p, Fin2.fz => Subtype fun x => p Fin2.fz x
| _, _, p, Fin2.fs i => Subtype_ (dropFun p) i
/-- projection on `Subtype_` -/
def subtypeVal : ∀ {n} {α : TypeVec.{u} n} (p : α ⟹ «repeat» n Prop), Subtype_ p ⟹ α
| succ n, _, _, Fin2.fs i => @subtypeVal n _ _ i
| succ _, _, _, Fin2.fz => Subtype.val
/-- arrow that rearranges the type of `Subtype_` to turn a subtype of vector into
a vector of subtypes -/
def toSubtype :
∀ {n} {α : TypeVec.{u} n} (p : α ⟹ «repeat» n Prop),
(fun i : Fin2 n => { x // ofRepeat <| p i x }) ⟹ Subtype_ p
| succ _, _, p, Fin2.fs i, x => toSubtype (dropFun p) i x
| succ _, _, _, Fin2.fz, x => x
/-- arrow that rearranges the type of `Subtype_` to turn a vector of subtypes
into a subtype of vector -/
def ofSubtype {n} {α : TypeVec.{u} n} (p : α ⟹ «repeat» n Prop) :
Subtype_ p ⟹ fun i : Fin2 n => { x // ofRepeat <| p i x }
| Fin2.fs i, x => ofSubtype _ i x
| Fin2.fz, x => x
/-- similar to `toSubtype` adapted to relations (i.e. predicate on product) -/
def toSubtype' {n} {α : TypeVec.{u} n} (p : α ⊗ α ⟹ «repeat» n Prop) :
(fun i : Fin2 n => { x : α i × α i // ofRepeat <| p i (prod.mk _ x.1 x.2) }) ⟹ Subtype_ p
| Fin2.fs i, x => toSubtype' (dropFun p) i x
| Fin2.fz, x => ⟨x.val, cast (by congr) x.property⟩
/-- similar to `of_subtype` adapted to relations (i.e. predicate on product) -/
def ofSubtype' {n} {α : TypeVec.{u} n} (p : α ⊗ α ⟹ «repeat» n Prop) :
Subtype_ p ⟹ fun i : Fin2 n => { x : α i × α i // ofRepeat <| p i (prod.mk _ x.1 x.2) }
| Fin2.fs i, x => ofSubtype' _ i x
| Fin2.fz, x => ⟨x.val, cast (by congr) x.property⟩
/-- similar to `diag` but the target vector is a `Subtype_`
guaranteeing the equality of the components -/
def diagSub {n} {α : TypeVec.{u} n} : α ⟹ Subtype_ (repeatEq α)
| Fin2.fs _, x => @diagSub _ (drop α) _ x
| Fin2.fz, x => ⟨(x, x), rfl⟩
theorem subtypeVal_nil {α : TypeVec.{u} 0} (ps : α ⟹ «repeat» 0 Prop) :
TypeVec.subtypeVal ps = nilFun :=
funext <| by rintro ⟨⟩
theorem diag_sub_val {n} {α : TypeVec.{u} n} : subtypeVal (repeatEq α) ⊚ diagSub = prod.diag := by
ext i x
induction i with
| fz => simp only [comp, subtypeVal, repeatEq.eq_2, diagSub, prod.diag]
| fs _ i_ih => apply @i_ih (drop α)
theorem prod_id : ∀ {n} {α β : TypeVec.{u} n}, (id ⊗' id) = (id : α ⊗ β ⟹ _) := by
intros
ext i a
induction i with
| fz => cases a; rfl
| fs _ i_ih => apply i_ih
theorem append_prod_appendFun {n} {α α' β β' : TypeVec.{u} n} {φ φ' ψ ψ' : Type u}
{f₀ : α ⟹ α'} {g₀ : β ⟹ β'} {f₁ : φ → φ'} {g₁ : ψ → ψ'} :
((f₀ ⊗' g₀) ::: (_root_.Prod.map f₁ g₁)) = ((f₀ ::: f₁) ⊗' (g₀ ::: g₁)) := by
ext i a
cases i
· cases a
rfl
· rfl
end Liftp'
@[simp]
theorem dropFun_diag {α} : dropFun (@prod.diag (n + 1) α) = prod.diag := by
ext i : 2
induction i <;> simp [dropFun, *] <;> rfl
@[simp]
theorem dropFun_subtypeVal {α} (p : α ⟹ «repeat» (n + 1) Prop) :
dropFun (subtypeVal p) = subtypeVal _ :=
rfl
@[simp]
theorem lastFun_subtypeVal {α} (p : α ⟹ «repeat» (n + 1) Prop) :
lastFun (subtypeVal p) = Subtype.val :=
rfl
@[simp]
theorem dropFun_toSubtype {α} (p : α ⟹ «repeat» (n + 1) Prop) :
dropFun (toSubtype p) = toSubtype _ := by
ext i
induction i <;> simp [dropFun, *] <;> rfl
@[simp]
theorem lastFun_toSubtype {α} (p : α ⟹ «repeat» (n + 1) Prop) :
lastFun (toSubtype p) = _root_.id := by
ext i : 2
induction i; simp [dropFun, *]; rfl
@[simp]
theorem dropFun_of_subtype {α} (p : α ⟹ «repeat» (n + 1) Prop) :
dropFun (ofSubtype p) = ofSubtype _ := by
ext i : 2
induction i <;> simp [dropFun, *] <;> rfl
@[simp]
theorem lastFun_of_subtype {α} (p : α ⟹ «repeat» (n + 1) Prop) :
lastFun (ofSubtype p) = _root_.id := rfl
@[simp]
theorem dropFun_RelLast' {α : TypeVec n} {β} (R : β → β → Prop) :
dropFun (RelLast' α R) = repeatEq α :=
rfl
attribute [simp] drop_append1'
open MvFunctor
@[simp]
theorem dropFun_prod {α α' β β' : TypeVec (n + 1)} (f : α ⟹ β) (f' : α' ⟹ β') :
dropFun (f ⊗' f') = (dropFun f ⊗' dropFun f') := by
ext i : 2
induction i <;> simp [dropFun, *] <;> rfl
@[simp]
theorem lastFun_prod {α α' β β' : TypeVec (n + 1)} (f : α ⟹ β) (f' : α' ⟹ β') :
lastFun (f ⊗' f') = Prod.map (lastFun f) (lastFun f') := by
ext i : 1
induction i; simp [lastFun, *]; rfl
@[simp]
theorem dropFun_from_append1_drop_last {α : TypeVec (n + 1)} :
dropFun (@fromAppend1DropLast _ α) = id :=
rfl
@[simp]
theorem lastFun_from_append1_drop_last {α : TypeVec (n + 1)} :
lastFun (@fromAppend1DropLast _ α) = _root_.id :=
rfl
@[simp]
theorem dropFun_id {α : TypeVec (n + 1)} : dropFun (@TypeVec.id _ α) = id :=
rfl
@[simp]
theorem prod_map_id {α β : TypeVec n} : (@TypeVec.id _ α ⊗' @TypeVec.id _ β) = id := by
ext i x : 2
induction i <;> simp only [TypeVec.prod.map, *, dropFun_id]
cases x
· rfl
· rfl
@[simp]
theorem subtypeVal_diagSub {α : TypeVec n} : subtypeVal (repeatEq α) ⊚ diagSub = prod.diag := by
ext i x
induction i with
| fz => simp [comp, diagSub, subtypeVal, prod.diag]
| fs _ i_ih =>
simp only [comp, subtypeVal, diagSub, prod.diag] at *
apply i_ih
@[simp]
theorem toSubtype_of_subtype {α : TypeVec n} (p : α ⟹ «repeat» n Prop) :
toSubtype p ⊚ ofSubtype p = id := by
ext i x
induction i <;> simp only [id, toSubtype, comp, ofSubtype] at *
simp [*]
@[simp]
theorem subtypeVal_toSubtype {α : TypeVec n} (p : α ⟹ «repeat» n Prop) :
subtypeVal p ⊚ toSubtype p = fun _ => Subtype.val := by
ext i x
induction i <;> simp only [toSubtype, comp, subtypeVal] at *
simp [*]
@[simp]
theorem toSubtype_of_subtype_assoc
{α β : TypeVec n} (p : α ⟹ «repeat» n Prop) (f : β ⟹ Subtype_ p) :
@toSubtype n _ p ⊚ ofSubtype _ ⊚ f = f := by
rw [← comp_assoc, toSubtype_of_subtype]; simp
@[simp]
theorem toSubtype'_of_subtype' {α : TypeVec n} (r : α ⊗ α ⟹ «repeat» n Prop) :
toSubtype' r ⊚ ofSubtype' r = id := by
ext i x
induction i
<;> dsimp only [id, toSubtype', comp, ofSubtype'] at *
<;> simp [Subtype.eta, *]
theorem subtypeVal_toSubtype' {α : TypeVec n} (r : α ⊗ α ⟹ «repeat» n Prop) :
subtypeVal r ⊚ toSubtype' r = fun i x => prod.mk i x.1.fst x.1.snd := by
ext i x
induction i <;> simp only [id, toSubtype', comp, subtypeVal, prod.mk] at *
simp [*]
end TypeVec
| Mathlib/Data/TypeVec.lean | 699 | 702 | |
/-
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.Logic.Equiv.PartialEquiv
import Mathlib.Topology.Homeomorph.Lemmas
import Mathlib.Topology.Sets.Opens
/-!
# Partial homeomorphisms
This file defines homeomorphisms between open subsets of topological spaces. An element `e` of
`PartialHomeomorph X Y` is an extension of `PartialEquiv X Y`, i.e., it is a pair of functions
`e.toFun` and `e.invFun`, inverse of each other on the sets `e.source` and `e.target`.
Additionally, we require that these sets are open, and that the functions are continuous on them.
Equivalently, they are homeomorphisms there.
As in equivs, we register a coercion to functions, and we use `e x` and `e.symm x` throughout
instead of `e.toFun x` and `e.invFun x`.
## Main definitions
* `Homeomorph.toPartialHomeomorph`: associating a partial homeomorphism to a homeomorphism, with
`source = target = Set.univ`;
* `PartialHomeomorph.symm`: the inverse of a partial homeomorphism
* `PartialHomeomorph.trans`: the composition of two partial homeomorphisms
* `PartialHomeomorph.refl`: the identity partial homeomorphism
* `PartialHomeomorph.const`: a partial homeomorphism which is a constant map,
whose source and target are necessarily singleton sets
* `PartialHomeomorph.ofSet`: the identity on a set `s`
* `PartialHomeomorph.restr s`: restrict a partial homeomorphism `e` to `e.source ∩ interior s`
* `PartialHomeomorph.EqOnSource`: equivalence relation describing the "right" notion of equality
for partial homeomorphisms
* `PartialHomeomorph.prod`: the product of two partial homeomorphisms,
as a partial homeomorphism on the product space
* `PartialHomeomorph.pi`: the product of a finite family of partial homeomorphisms
* `PartialHomeomorph.disjointUnion`: combine two partial homeomorphisms with disjoint sources
and disjoint targets
* `PartialHomeomorph.lift_openEmbedding`: extend a partial homeomorphism `X → Y`
under an open embedding `X → X'`, to a partial homeomorphism `X' → Z`.
(This is used to define the disjoint union of charted spaces.)
## Implementation notes
Most statements are copied from their `PartialEquiv` versions, although some care is required
especially when restricting to subsets, as these should be open subsets.
For design notes, see `PartialEquiv.lean`.
### Local coding conventions
If a lemma deals with the intersection of a set with either source or target of a `PartialEquiv`,
then it should use `e.source ∩ s` or `e.target ∩ t`, not `s ∩ e.source` or `t ∩ e.target`.
-/
open Function Set Filter Topology
variable {X X' : Type*} {Y Y' : Type*} {Z Z' : Type*}
[TopologicalSpace X] [TopologicalSpace X'] [TopologicalSpace Y] [TopologicalSpace Y']
[TopologicalSpace Z] [TopologicalSpace Z']
/-- Partial homeomorphisms, defined on open subsets of the space -/
structure PartialHomeomorph (X : Type*) (Y : Type*) [TopologicalSpace X]
[TopologicalSpace Y] extends PartialEquiv X Y where
open_source : IsOpen source
open_target : IsOpen target
continuousOn_toFun : ContinuousOn toFun source
continuousOn_invFun : ContinuousOn invFun target
namespace PartialHomeomorph
variable (e : PartialHomeomorph X Y)
/-! Basic properties; inverse (symm instance) -/
section Basic
/-- Coercion of a partial homeomorphisms to a function. We don't use `e.toFun` because it is
actually `e.toPartialEquiv.toFun`, so `simp` will apply lemmas about `toPartialEquiv`.
While we may want to switch to this behavior later, doing it mid-port will break a lot of proofs. -/
@[coe] def toFun' : X → Y := e.toFun
/-- Coercion of a `PartialHomeomorph` to function.
Note that a `PartialHomeomorph` is not `DFunLike`. -/
instance : CoeFun (PartialHomeomorph X Y) fun _ => X → Y :=
⟨fun e => e.toFun'⟩
/-- The inverse of a partial homeomorphism -/
@[symm]
protected def symm : PartialHomeomorph Y X where
toPartialEquiv := e.toPartialEquiv.symm
open_source := e.open_target
open_target := e.open_source
continuousOn_toFun := e.continuousOn_invFun
continuousOn_invFun := e.continuousOn_toFun
/-- 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 (e : PartialHomeomorph X Y) : X → Y := e
/-- See Note [custom simps projection] -/
def Simps.symm_apply (e : PartialHomeomorph X Y) : Y → X := e.symm
initialize_simps_projections PartialHomeomorph (toFun → apply, invFun → symm_apply)
protected theorem continuousOn : ContinuousOn e e.source :=
e.continuousOn_toFun
theorem continuousOn_symm : ContinuousOn e.symm e.target :=
e.continuousOn_invFun
@[simp, mfld_simps]
theorem mk_coe (e : PartialEquiv X Y) (a b c d) : (PartialHomeomorph.mk e a b c d : X → Y) = e :=
rfl
@[simp, mfld_simps]
theorem mk_coe_symm (e : PartialEquiv X Y) (a b c d) :
((PartialHomeomorph.mk e a b c d).symm : Y → X) = e.symm :=
rfl
theorem toPartialEquiv_injective :
Injective (toPartialEquiv : PartialHomeomorph X Y → PartialEquiv X Y)
| ⟨_, _, _, _, _⟩, ⟨_, _, _, _, _⟩, rfl => rfl
/- Register a few simp lemmas to make sure that `simp` puts the application of a local
homeomorphism in its normal form, i.e., in terms of its coercion to a function. -/
@[simp, mfld_simps]
theorem toFun_eq_coe (e : PartialHomeomorph X Y) : e.toFun = e :=
rfl
@[simp, mfld_simps]
theorem invFun_eq_coe (e : PartialHomeomorph X Y) : e.invFun = e.symm :=
rfl
@[simp, mfld_simps]
theorem coe_coe : (e.toPartialEquiv : X → Y) = e :=
rfl
@[simp, mfld_simps]
theorem coe_coe_symm : (e.toPartialEquiv.symm : Y → X) = e.symm :=
rfl
@[simp, mfld_simps]
theorem map_source {x : X} (h : x ∈ e.source) : e x ∈ e.target :=
e.map_source' h
/-- Variant of `map_source`, stated for images of subsets of `source`. -/
lemma map_source'' : e '' e.source ⊆ e.target :=
fun _ ⟨_, hx, hex⟩ ↦ mem_of_eq_of_mem (id hex.symm) (e.map_source' hx)
@[simp, mfld_simps]
theorem map_target {x : Y} (h : x ∈ e.target) : e.symm x ∈ e.source :=
e.map_target' h
@[simp, mfld_simps]
theorem left_inv {x : X} (h : x ∈ e.source) : e.symm (e x) = x :=
e.left_inv' h
@[simp, mfld_simps]
theorem right_inv {x : Y} (h : x ∈ e.target) : e (e.symm x) = x :=
e.right_inv' h
theorem eq_symm_apply {x : X} {y : Y} (hx : x ∈ e.source) (hy : y ∈ e.target) :
x = e.symm y ↔ e x = y :=
e.toPartialEquiv.eq_symm_apply hx hy
protected theorem mapsTo : MapsTo e e.source e.target := fun _ => e.map_source
protected theorem symm_mapsTo : MapsTo e.symm e.target e.source :=
e.symm.mapsTo
protected theorem leftInvOn : LeftInvOn e.symm e e.source := fun _ => e.left_inv
protected theorem rightInvOn : RightInvOn e.symm e e.target := fun _ => e.right_inv
protected theorem invOn : InvOn e.symm e e.source e.target :=
⟨e.leftInvOn, e.rightInvOn⟩
protected theorem injOn : InjOn e e.source :=
e.leftInvOn.injOn
protected theorem bijOn : BijOn e e.source e.target :=
e.invOn.bijOn e.mapsTo e.symm_mapsTo
protected theorem surjOn : SurjOn e e.source e.target :=
e.bijOn.surjOn
end Basic
/-- Interpret a `Homeomorph` as a `PartialHomeomorph` by restricting it
to an open set `s` in the domain and to `t` in the codomain. -/
@[simps! -fullyApplied apply symm_apply toPartialEquiv,
simps! -isSimp source target]
def _root_.Homeomorph.toPartialHomeomorphOfImageEq (e : X ≃ₜ Y) (s : Set X) (hs : IsOpen s)
(t : Set Y) (h : e '' s = t) : PartialHomeomorph X Y where
toPartialEquiv := e.toPartialEquivOfImageEq s t h
open_source := hs
open_target := by simpa [← h]
continuousOn_toFun := e.continuous.continuousOn
continuousOn_invFun := e.symm.continuous.continuousOn
/-- A homeomorphism induces a partial homeomorphism on the whole space -/
@[simps! (config := mfld_cfg)]
def _root_.Homeomorph.toPartialHomeomorph (e : X ≃ₜ Y) : PartialHomeomorph X Y :=
e.toPartialHomeomorphOfImageEq univ isOpen_univ univ <| by rw [image_univ, e.surjective.range_eq]
/-- Replace `toPartialEquiv` field to provide better definitional equalities. -/
def replaceEquiv (e : PartialHomeomorph X Y) (e' : PartialEquiv X Y) (h : e.toPartialEquiv = e') :
PartialHomeomorph X Y where
toPartialEquiv := e'
open_source := h ▸ e.open_source
open_target := h ▸ e.open_target
continuousOn_toFun := h ▸ e.continuousOn_toFun
continuousOn_invFun := h ▸ e.continuousOn_invFun
theorem replaceEquiv_eq_self (e' : PartialEquiv X Y)
(h : e.toPartialEquiv = e') : e.replaceEquiv e' h = e := by
cases e
subst e'
rfl
theorem source_preimage_target : e.source ⊆ e ⁻¹' e.target :=
e.mapsTo
theorem eventually_left_inverse {x} (hx : x ∈ e.source) :
∀ᶠ y in 𝓝 x, e.symm (e y) = y :=
(e.open_source.eventually_mem hx).mono e.left_inv'
theorem eventually_left_inverse' {x} (hx : x ∈ e.target) :
∀ᶠ y in 𝓝 (e.symm x), e.symm (e y) = y :=
e.eventually_left_inverse (e.map_target hx)
theorem eventually_right_inverse {x} (hx : x ∈ e.target) :
∀ᶠ y in 𝓝 x, e (e.symm y) = y :=
| (e.open_target.eventually_mem hx).mono e.right_inv'
theorem eventually_right_inverse' {x} (hx : x ∈ e.source) :
∀ᶠ y in 𝓝 (e x), e (e.symm y) = y :=
e.eventually_right_inverse (e.map_source hx)
| Mathlib/Topology/PartialHomeomorph.lean | 234 | 238 |
/-
Copyright (c) 2020 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Shing Tak Lam, Mario Carneiro
-/
import Mathlib.Algebra.BigOperators.Intervals
import Mathlib.Algebra.BigOperators.Ring.List
import Mathlib.Data.Int.ModEq
import Mathlib.Data.Nat.Bits
import Mathlib.Data.Nat.Log
import Mathlib.Data.List.Palindrome
import Mathlib.Tactic.IntervalCases
import Mathlib.Tactic.Linarith
import Mathlib.Tactic.Ring
/-!
# Digits of a natural number
This provides a basic API for extracting the digits of a natural number in a given base,
and reconstructing numbers from their digits.
We also prove some divisibility tests based on digits, in particular completing
Theorem #85 from https://www.cs.ru.nl/~freek/100/.
Also included is a bound on the length of `Nat.toDigits` from core.
## TODO
A basic `norm_digits` tactic for proving goals of the form `Nat.digits a b = l` where `a` and `b`
are numerals is not yet ported.
-/
namespace Nat
variable {n : ℕ}
/-- (Impl.) An auxiliary definition for `digits`, to help get the desired definitional unfolding. -/
def digitsAux0 : ℕ → List ℕ
| 0 => []
| n + 1 => [n + 1]
/-- (Impl.) An auxiliary definition for `digits`, to help get the desired definitional unfolding. -/
def digitsAux1 (n : ℕ) : List ℕ :=
List.replicate n 1
/-- (Impl.) An auxiliary definition for `digits`, to help get the desired definitional unfolding. -/
def digitsAux (b : ℕ) (h : 2 ≤ b) : ℕ → List ℕ
| 0 => []
| n + 1 =>
((n + 1) % b) :: digitsAux b h ((n + 1) / b)
decreasing_by exact Nat.div_lt_self (Nat.succ_pos _) h
@[simp]
theorem digitsAux_zero (b : ℕ) (h : 2 ≤ b) : digitsAux b h 0 = [] := by rw [digitsAux]
theorem digitsAux_def (b : ℕ) (h : 2 ≤ b) (n : ℕ) (w : 0 < n) :
digitsAux b h n = (n % b) :: digitsAux b h (n / b) := by
cases n
· cases w
· rw [digitsAux]
/-- `digits b n` gives the digits, in little-endian order,
of a natural number `n` in a specified base `b`.
In any base, we have `ofDigits b L = L.foldr (fun x y ↦ x + b * y) 0`.
* For any `2 ≤ b`, we have `l < b` for any `l ∈ digits b n`,
and the last digit is not zero.
This uniquely specifies the behaviour of `digits b`.
* For `b = 1`, we define `digits 1 n = List.replicate n 1`.
* For `b = 0`, we define `digits 0 n = [n]`, except `digits 0 0 = []`.
Note this differs from the existing `Nat.toDigits` in core, which is used for printing numerals.
In particular, `Nat.toDigits b 0 = ['0']`, while `digits b 0 = []`.
-/
def digits : ℕ → ℕ → List ℕ
| 0 => digitsAux0
| 1 => digitsAux1
| b + 2 => digitsAux (b + 2) (by norm_num)
@[simp]
theorem digits_zero (b : ℕ) : digits b 0 = [] := by
rcases b with (_ | ⟨_ | ⟨_⟩⟩) <;> simp [digits, digitsAux0, digitsAux1]
theorem digits_zero_zero : digits 0 0 = [] :=
rfl
@[simp]
theorem digits_zero_succ (n : ℕ) : digits 0 n.succ = [n + 1] :=
rfl
theorem digits_zero_succ' : ∀ {n : ℕ}, n ≠ 0 → digits 0 n = [n]
| 0, h => (h rfl).elim
| _ + 1, _ => rfl
@[simp]
theorem digits_one (n : ℕ) : digits 1 n = List.replicate n 1 :=
rfl
-- no `@[simp]`: dsimp can prove this
theorem digits_one_succ (n : ℕ) : digits 1 (n + 1) = 1 :: digits 1 n :=
rfl
theorem digits_add_two_add_one (b n : ℕ) :
digits (b + 2) (n + 1) = ((n + 1) % (b + 2)) :: digits (b + 2) ((n + 1) / (b + 2)) := by
simp [digits, digitsAux_def]
@[simp]
lemma digits_of_two_le_of_pos {b : ℕ} (hb : 2 ≤ b) (hn : 0 < n) :
Nat.digits b n = n % b :: Nat.digits b (n / b) := by
rw [Nat.eq_add_of_sub_eq hb rfl, Nat.eq_add_of_sub_eq hn rfl, Nat.digits_add_two_add_one]
theorem digits_def' :
∀ {b : ℕ} (_ : 1 < b) {n : ℕ} (_ : 0 < n), digits b n = (n % b) :: digits b (n / b)
| 0, h => absurd h (by decide)
| 1, h => absurd h (by decide)
| b + 2, _ => digitsAux_def _ (by simp) _
@[simp]
theorem digits_of_lt (b x : ℕ) (hx : x ≠ 0) (hxb : x < b) : digits b x = [x] := by
rcases exists_eq_succ_of_ne_zero hx with ⟨x, rfl⟩
rcases Nat.exists_eq_add_of_le' ((Nat.le_add_left 1 x).trans_lt hxb) with ⟨b, rfl⟩
rw [digits_add_two_add_one, div_eq_of_lt hxb, digits_zero, mod_eq_of_lt hxb]
theorem digits_add (b : ℕ) (h : 1 < b) (x y : ℕ) (hxb : x < b) (hxy : x ≠ 0 ∨ y ≠ 0) :
digits b (x + b * y) = x :: digits b y := by
rcases Nat.exists_eq_add_of_le' h with ⟨b, rfl : _ = _ + 2⟩
cases y
· simp [hxb, hxy.resolve_right (absurd rfl)]
dsimp [digits]
rw [digitsAux_def]
· congr
· simp [Nat.add_mod, mod_eq_of_lt hxb]
· simp [add_mul_div_left, div_eq_of_lt hxb]
· apply Nat.succ_pos
-- If we had a function converting a list into a polynomial,
-- and appropriate lemmas about that function,
-- we could rewrite this in terms of that.
/-- `ofDigits b L` takes a list `L` of natural numbers, and interprets them
as a number in semiring, as the little-endian digits in base `b`.
-/
def ofDigits {α : Type*} [Semiring α] (b : α) : List ℕ → α
| [] => 0
| h :: t => h + b * ofDigits b t
theorem ofDigits_eq_foldr {α : Type*} [Semiring α] (b : α) (L : List ℕ) :
ofDigits b L = List.foldr (fun x y => ↑x + b * y) 0 L := by
induction' L with d L ih
· rfl
· dsimp [ofDigits]
rw [ih]
theorem ofDigits_eq_sum_mapIdx_aux (b : ℕ) (l : List ℕ) :
(l.zipWith ((fun a i : ℕ => a * b ^ (i + 1))) (List.range l.length)).sum =
b * (l.zipWith (fun a i => a * b ^ i) (List.range l.length)).sum := by
suffices
l.zipWith (fun a i : ℕ => a * b ^ (i + 1)) (List.range l.length) =
l.zipWith (fun a i=> b * (a * b ^ i)) (List.range l.length)
by simp [this]
congr; ext; simp [pow_succ]; ring
theorem ofDigits_eq_sum_mapIdx (b : ℕ) (L : List ℕ) :
ofDigits b L = (L.mapIdx fun i a => a * b ^ i).sum := by
rw [List.mapIdx_eq_zipIdx_map, List.zipIdx_eq_zip_range', List.map_zip_eq_zipWith,
ofDigits_eq_foldr, ← List.range_eq_range']
induction' L with hd tl hl
· simp
· simpa [List.range_succ_eq_map, List.zipWith_map_right, ofDigits_eq_sum_mapIdx_aux] using
Or.inl hl
@[simp]
theorem ofDigits_nil {b : ℕ} : ofDigits b [] = 0 := rfl
@[simp]
theorem ofDigits_singleton {b n : ℕ} : ofDigits b [n] = n := by simp [ofDigits]
@[simp]
theorem ofDigits_one_cons {α : Type*} [Semiring α] (h : ℕ) (L : List ℕ) :
ofDigits (1 : α) (h :: L) = h + ofDigits 1 L := by simp [ofDigits]
theorem ofDigits_cons {b hd} {tl : List ℕ} :
ofDigits b (hd :: tl) = hd + b * ofDigits b tl := rfl
theorem ofDigits_append {b : ℕ} {l1 l2 : List ℕ} :
ofDigits b (l1 ++ l2) = ofDigits b l1 + b ^ l1.length * ofDigits b l2 := by
induction' l1 with hd tl IH
· simp [ofDigits]
· rw [ofDigits, List.cons_append, ofDigits, IH, List.length_cons, pow_succ']
ring
@[norm_cast]
theorem coe_ofDigits (α : Type*) [Semiring α] (b : ℕ) (L : List ℕ) :
((ofDigits b L : ℕ) : α) = ofDigits (b : α) L := by
induction' L with d L ih
· simp [ofDigits]
· dsimp [ofDigits]; push_cast; rw [ih]
@[norm_cast]
theorem coe_int_ofDigits (b : ℕ) (L : List ℕ) : ((ofDigits b L : ℕ) : ℤ) = ofDigits (b : ℤ) L := by
induction' L with d L _
· rfl
· dsimp [ofDigits]; push_cast; simp only
theorem digits_zero_of_eq_zero {b : ℕ} (h : b ≠ 0) :
∀ {L : List ℕ} (_ : ofDigits b L = 0), ∀ l ∈ L, l = 0
| _ :: _, h0, _, List.Mem.head .. => Nat.eq_zero_of_add_eq_zero_right h0
| _ :: _, h0, _, List.Mem.tail _ hL =>
digits_zero_of_eq_zero h (mul_right_injective₀ h (Nat.eq_zero_of_add_eq_zero_left h0)) _ hL
theorem digits_ofDigits (b : ℕ) (h : 1 < b) (L : List ℕ) (w₁ : ∀ l ∈ L, l < b)
(w₂ : ∀ h : L ≠ [], L.getLast h ≠ 0) : digits b (ofDigits b L) = L := by
induction' L with d L ih
· dsimp [ofDigits]
simp
· dsimp [ofDigits]
replace w₂ := w₂ (by simp)
rw [digits_add b h]
· rw [ih]
· intro l m
apply w₁
exact List.mem_cons_of_mem _ m
· intro h
rw [List.getLast_cons h] at w₂
convert w₂
· exact w₁ d List.mem_cons_self
· by_cases h' : L = []
· rcases h' with rfl
left
simpa using w₂
· right
contrapose! w₂
refine digits_zero_of_eq_zero h.ne_bot w₂ _ ?_
rw [List.getLast_cons h']
exact List.getLast_mem h'
theorem ofDigits_digits (b n : ℕ) : ofDigits b (digits b n) = n := by
rcases b with - | b
· rcases n with - | n
· rfl
| · simp
· rcases b with - | b
· induction' n with n ih
· rfl
· rw [Nat.zero_add] at ih ⊢
simp only [ih, add_comm 1, ofDigits_one_cons, Nat.cast_id, digits_one_succ]
· induction n using Nat.strongRecOn with | ind n h => ?_
cases n
· rw [digits_zero]
rfl
· simp only [Nat.succ_eq_add_one, digits_add_two_add_one]
dsimp [ofDigits]
rw [h _ (Nat.div_lt_self' _ b)]
rw [Nat.mod_add_div]
theorem ofDigits_one (L : List ℕ) : ofDigits 1 L = L.sum := by
induction L with
| nil => rfl
| cons _ _ ih => simp [ofDigits, List.sum_cons, ih]
/-!
### Properties
This section contains various lemmas of properties relating to `digits` and `ofDigits`.
-/
| Mathlib/Data/Nat/Digits.lean | 240 | 264 |
/-
Copyright (c) 2023 Frédéric Dupuis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Frédéric Dupuis
-/
import Mathlib.Analysis.Asymptotics.AsymptoticEquivalent
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Mathlib.Algebra.Order.ToIntervalMod
import Mathlib.Analysis.SpecialFunctions.Log.Base
/-!
# Akra-Bazzi theorem: The polynomial growth condition
This file defines and develops an API for the polynomial growth condition that appears in the
statement of the Akra-Bazzi theorem: for the Akra-Bazzi theorem to hold, the function `g` must
satisfy the condition that `c₁ g(n) ≤ g(u) ≤ c₂ g(n)`, for u between b*n and n for any constant
`b ∈ (0,1)`.
## Implementation notes
Our definition states that the condition must hold for any `b ∈ (0,1)`. This is equivalent to
only requiring it for `b = 1/2` or any other particular value between 0 and 1. While this
could in principle make it harder to prove that a particular function grows polynomially,
this issue doesn't seem to arise in practice.
-/
open Finset Real Filter Asymptotics
open scoped Topology
namespace AkraBazziRecurrence
/-- The growth condition that the function `g` must satisfy for the Akra-Bazzi theorem to apply.
It roughly states that `c₁ g(n) ≤ g(u) ≤ c₂ g(n)`, for `u` between `b*n` and `n` for any
constant `b ∈ (0,1)`. -/
def GrowsPolynomially (f : ℝ → ℝ) : Prop :=
∀ b ∈ Set.Ioo 0 1, ∃ c₁ > 0, ∃ c₂ > 0,
∀ᶠ x in atTop, ∀ u ∈ Set.Icc (b * x) x, f u ∈ Set.Icc (c₁ * (f x)) (c₂ * f x)
namespace GrowsPolynomially
lemma congr_of_eventuallyEq {f g : ℝ → ℝ} (hfg : f =ᶠ[atTop] g) (hg : GrowsPolynomially g) :
GrowsPolynomially f := by
intro b hb
have hg' := hg b hb
obtain ⟨c₁, hc₁_mem, c₂, hc₂_mem, hg'⟩ := hg'
refine ⟨c₁, hc₁_mem, c₂, hc₂_mem, ?_⟩
filter_upwards [hg', (tendsto_id.const_mul_atTop hb.1).eventually_forall_ge_atTop hfg, hfg]
with x hx₁ hx₂ hx₃
intro u hu
rw [hx₂ u hu.1, hx₃]
exact hx₁ u hu
lemma iff_eventuallyEq {f g : ℝ → ℝ} (h : f =ᶠ[atTop] g) :
GrowsPolynomially f ↔ GrowsPolynomially g :=
⟨fun hf => congr_of_eventuallyEq h.symm hf, fun hg => congr_of_eventuallyEq h hg⟩
variable {f : ℝ → ℝ}
| lemma eventually_atTop_le {b : ℝ} (hb : b ∈ Set.Ioo 0 1) (hf : GrowsPolynomially f) :
∃ c > 0, ∀ᶠ x in atTop, ∀ u ∈ Set.Icc (b * x) x, f u ≤ c * f x := by
obtain ⟨c₁, _, c₂, hc₂, h⟩ := hf b hb
refine ⟨c₂, hc₂, ?_⟩
filter_upwards [h]
exact fun _ H u hu => (H u hu).2
| Mathlib/Computability/AkraBazzi/GrowsPolynomially.lean | 61 | 66 |
/-
Copyright (c) 2023 Scott Carnahan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Carnahan
-/
import Mathlib.Algebra.Group.NatPowAssoc
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Eval.SMul
/-!
# Scalar-multiple polynomial evaluation
This file defines polynomial evaluation via scalar multiplication. Our polynomials have
coefficients in a semiring `R`, and we evaluate at a weak form of `R`-algebra, namely an additive
commutative monoid with an action of `R` and a notion of natural number power. This
is a generalization of `Algebra.Polynomial.Eval`.
## Main definitions
* `Polynomial.smeval`: function for evaluating a polynomial with coefficients in a `Semiring`
`R` at an element `x` of an `AddCommMonoid` `S` that has natural number powers and an `R`-action.
* `smeval.linearMap`: the `smeval` function as an `R`-linear map, when `S` is an `R`-module.
* `smeval.algebraMap`: the `smeval` function as an `R`-algebra map, when `S` is an `R`-algebra.
## Main results
* `smeval_monomial`: monomials evaluate as we expect.
* `smeval_add`, `smeval_smul`: linearity of evaluation, given an `R`-module.
* `smeval_mul`, `smeval_comp`: multiplicativity of evaluation, given power-associativity.
* `eval₂_smulOneHom_eq_smeval`, `leval_eq_smeval.linearMap`,
`aeval_eq_smeval`, etc.: comparisons
## TODO
* `smeval_neg` and `smeval_intCast` for `R` a ring and `S` an `AddCommGroup`.
* Nonunital evaluation for polynomials with vanishing constant term for `Pow S ℕ+` (different file?)
-/
namespace Polynomial
section MulActionWithZero
variable {R : Type*} [Semiring R] (r : R) (p : R[X]) {S : Type*} [AddCommMonoid S] [Pow S ℕ]
[MulActionWithZero R S] (x : S)
/-- Scalar multiplication together with taking a natural number power. -/
def smul_pow : ℕ → R → S := fun n r => r • x^n
/-- Evaluate a polynomial `p` in the scalar semiring `R` at an element `x` in the target `S` using
scalar multiple `R`-action. -/
irreducible_def smeval : S := p.sum (smul_pow x)
theorem smeval_eq_sum : p.smeval x = p.sum (smul_pow x) := by rw [smeval_def]
@[simp]
theorem smeval_C : (C r).smeval x = r • x ^ 0 := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_C_index]
@[simp]
| theorem smeval_monomial (n : ℕ) :
(monomial n r).smeval x = r • x ^ n := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_monomial_index]
| Mathlib/Algebra/Polynomial/Smeval.lean | 61 | 63 |
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Nat.Totient
import Mathlib.Data.ZMod.Aut
import Mathlib.Data.ZMod.QuotientGroup
import Mathlib.GroupTheory.Exponent
import Mathlib.GroupTheory.Subgroup.Simple
import Mathlib.Tactic.Group
/-!
# Cyclic groups
A group `G` is called cyclic if there exists an element `g : G` such that every element of `G` is of
the form `g ^ n` for some `n : ℕ`. This file only deals with the predicate on a group to be cyclic.
For the concrete cyclic group of order `n`, see `Data.ZMod.Basic`.
## Main definitions
* `IsCyclic` is a predicate on a group stating that the group is cyclic.
## Main statements
* `isCyclic_of_prime_card` proves that a finite group of prime order is cyclic.
* `isSimpleGroup_of_prime_card`, `IsSimpleGroup.isCyclic`,
and `IsSimpleGroup.prime_card` classify finite simple abelian groups.
* `IsCyclic.exponent_eq_card`: For a finite cyclic group `G`, the exponent is equal to
the group's cardinality.
* `IsCyclic.exponent_eq_zero_of_infinite`: Infinite cyclic groups have exponent zero.
* `IsCyclic.iff_exponent_eq_card`: A finite commutative group is cyclic iff its exponent
is equal to its cardinality.
## Tags
cyclic group
-/
assert_not_exists Ideal TwoSidedIdeal
variable {α G G' : Type*} {a : α}
section Cyclic
open Subgroup
@[to_additive]
theorem IsCyclic.exists_generator [Group α] [IsCyclic α] : ∃ g : α, ∀ x, x ∈ zpowers g :=
exists_zpow_surjective α
@[to_additive]
theorem isCyclic_iff_exists_zpowers_eq_top [Group α] : IsCyclic α ↔ ∃ g : α, zpowers g = ⊤ := by
simp only [eq_top_iff', mem_zpowers_iff]
exact ⟨fun ⟨h⟩ ↦ h, fun h ↦ ⟨h⟩⟩
@[to_additive]
protected theorem Subgroup.isCyclic_iff_exists_zpowers_eq_top [Group α] (H : Subgroup α) :
IsCyclic H ↔ ∃ g : α, Subgroup.zpowers g = H := by
rw [isCyclic_iff_exists_zpowers_eq_top]
simp_rw [← (map_injective H.subtype_injective).eq_iff, ← MonoidHom.range_eq_map,
H.range_subtype, MonoidHom.map_zpowers, Subtype.exists, coe_subtype, exists_prop]
exact exists_congr fun g ↦ and_iff_right_of_imp fun h ↦ h ▸ mem_zpowers g
@[to_additive]
instance (priority := 100) isCyclic_of_subsingleton [Group α] [Subsingleton α] : IsCyclic α :=
⟨⟨1, fun _ => ⟨0, Subsingleton.elim _ _⟩⟩⟩
@[simp]
theorem isCyclic_multiplicative_iff [SubNegMonoid α] :
IsCyclic (Multiplicative α) ↔ IsAddCyclic α :=
⟨fun H ↦ ⟨H.1⟩, fun H ↦ ⟨H.1⟩⟩
instance isCyclic_multiplicative [AddGroup α] [IsAddCyclic α] : IsCyclic (Multiplicative α) :=
isCyclic_multiplicative_iff.mpr inferInstance
@[simp]
theorem isAddCyclic_additive_iff [DivInvMonoid α] : IsAddCyclic (Additive α) ↔ IsCyclic α :=
⟨fun H ↦ ⟨H.1⟩, fun H ↦ ⟨H.1⟩⟩
instance isAddCyclic_additive [Group α] [IsCyclic α] : IsAddCyclic (Additive α) :=
isAddCyclic_additive_iff.mpr inferInstance
@[to_additive]
instance IsCyclic.commutative [Group α] [IsCyclic α] :
Std.Commutative (· * · : α → α → α) where
comm x y :=
let ⟨_, hg⟩ := IsCyclic.exists_generator (α := α)
let ⟨_, hx⟩ := hg x
let ⟨_, hy⟩ := hg y
hy ▸ hx ▸ zpow_mul_comm _ _ _
/-- A cyclic group is always commutative. This is not an `instance` because often we have a better
proof of `CommGroup`. -/
@[to_additive
"A cyclic group is always commutative. This is not an `instance` because often we have
a better proof of `AddCommGroup`."]
def IsCyclic.commGroup [hg : Group α] [IsCyclic α] : CommGroup α :=
{ hg with mul_comm := commutative.comm }
instance [Group G] (H : Subgroup G) [IsCyclic H] : IsMulCommutative H :=
⟨IsCyclic.commutative⟩
variable [Group α] [Group G] [Group G']
/-- A non-cyclic multiplicative group is non-trivial. -/
@[to_additive "A non-cyclic additive group is non-trivial."]
theorem Nontrivial.of_not_isCyclic (nc : ¬IsCyclic α) : Nontrivial α := by
contrapose! nc
exact @isCyclic_of_subsingleton _ _ (not_nontrivial_iff_subsingleton.mp nc)
@[to_additive]
theorem MonoidHom.map_cyclic [h : IsCyclic G] (σ : G →* G) :
∃ m : ℤ, ∀ g : G, σ g = g ^ m := by
obtain ⟨h, hG⟩ := IsCyclic.exists_generator (α := G)
obtain ⟨m, hm⟩ := hG (σ h)
refine ⟨m, fun g => ?_⟩
obtain ⟨n, rfl⟩ := hG g
rw [MonoidHom.map_zpow, ← hm, ← zpow_mul, ← zpow_mul']
@[to_additive]
lemma isCyclic_iff_exists_orderOf_eq_natCard [Finite α] :
IsCyclic α ↔ ∃ g : α, orderOf g = Nat.card α := by
simp_rw [isCyclic_iff_exists_zpowers_eq_top, ← card_eq_iff_eq_top, Nat.card_zpowers]
@[to_additive]
lemma isCyclic_iff_exists_natCard_le_orderOf [Finite α] :
IsCyclic α ↔ ∃ g : α, Nat.card α ≤ orderOf g := by
rw [isCyclic_iff_exists_orderOf_eq_natCard]
apply exists_congr
intro g
exact ⟨Eq.ge, le_antisymm orderOf_le_card⟩
@[deprecated (since := "2024-12-20")]
alias isCyclic_iff_exists_ofOrder_eq_natCard := isCyclic_iff_exists_orderOf_eq_natCard
@[deprecated (since := "2024-12-20")]
alias isAddCyclic_iff_exists_ofOrder_eq_natCard := isAddCyclic_iff_exists_addOrderOf_eq_natCard
@[deprecated (since := "2024-12-20")]
alias IsCyclic.iff_exists_ofOrder_eq_natCard_of_Fintype :=
isCyclic_iff_exists_orderOf_eq_natCard
@[deprecated (since := "2024-12-20")]
alias IsAddCyclic.iff_exists_ofOrder_eq_natCard_of_Fintype :=
isAddCyclic_iff_exists_addOrderOf_eq_natCard
@[to_additive]
theorem isCyclic_of_orderOf_eq_card [Finite α] (x : α) (hx : orderOf x = Nat.card α) :
IsCyclic α :=
isCyclic_iff_exists_orderOf_eq_natCard.mpr ⟨x, hx⟩
@[to_additive]
theorem isCyclic_of_card_le_orderOf [Finite α] (x : α) (hx : Nat.card α ≤ orderOf x) :
IsCyclic α :=
isCyclic_iff_exists_natCard_le_orderOf.mpr ⟨x, hx⟩
@[to_additive]
theorem Subgroup.eq_bot_or_eq_top_of_prime_card
(H : Subgroup G) [hp : Fact (Nat.card G).Prime] : H = ⊥ ∨ H = ⊤ := by
have : Finite G := Nat.finite_of_card_ne_zero hp.1.ne_zero
have := card_subgroup_dvd_card H
rwa [Nat.dvd_prime hp.1, ← eq_bot_iff_card, card_eq_iff_eq_top] at this
/-- Any non-identity element of a finite group of prime order generates the group. -/
@[to_additive "Any non-identity element of a finite group of prime order generates the group."]
theorem zpowers_eq_top_of_prime_card {p : ℕ}
[hp : Fact p.Prime] (h : Nat.card G = p) {g : G} (hg : g ≠ 1) : zpowers g = ⊤ := by
subst h
have := (zpowers g).eq_bot_or_eq_top_of_prime_card
rwa [zpowers_eq_bot, or_iff_right hg] at this
@[to_additive]
theorem mem_zpowers_of_prime_card {p : ℕ} [hp : Fact p.Prime]
(h : Nat.card G = p) {g g' : G} (hg : g ≠ 1) : g' ∈ zpowers g := by
simp_rw [zpowers_eq_top_of_prime_card h hg, Subgroup.mem_top]
@[to_additive]
theorem mem_powers_of_prime_card {p : ℕ} [hp : Fact p.Prime]
(h : Nat.card G = p) {g g' : G} (hg : g ≠ 1) : g' ∈ Submonoid.powers g := by
have : Finite G := Nat.finite_of_card_ne_zero (h ▸ hp.1.ne_zero)
rw [mem_powers_iff_mem_zpowers]
exact mem_zpowers_of_prime_card h hg
@[to_additive]
theorem powers_eq_top_of_prime_card {p : ℕ}
[hp : Fact p.Prime] (h : Nat.card G = p) {g : G} (hg : g ≠ 1) : Submonoid.powers g = ⊤ := by
ext x
simp [mem_powers_of_prime_card h hg]
/-- A finite group of prime order is cyclic. -/
@[to_additive "A finite group of prime order is cyclic."]
theorem isCyclic_of_prime_card {p : ℕ} [hp : Fact p.Prime]
(h : Nat.card α = p) : IsCyclic α := by
have : Finite α := Nat.finite_of_card_ne_zero (h ▸ hp.1.ne_zero)
have : Nontrivial α := Finite.one_lt_card_iff_nontrivial.mp (h ▸ hp.1.one_lt)
obtain ⟨g, hg⟩ : ∃ g : α, g ≠ 1 := exists_ne 1
exact ⟨g, fun g' ↦ mem_zpowers_of_prime_card h hg⟩
/-- A finite group of order dividing a prime is cyclic. -/
@[to_additive "A finite group of order dividing a prime is cyclic."]
theorem isCyclic_of_card_dvd_prime {p : ℕ} [hp : Fact p.Prime]
(h : Nat.card α ∣ p) : IsCyclic α := by
rcases (Nat.dvd_prime hp.out).mp h with h | h
· exact @isCyclic_of_subsingleton α _ (Nat.card_eq_one_iff_unique.mp h).1
· exact isCyclic_of_prime_card h
@[to_additive]
theorem isCyclic_of_surjective {F : Type*} [hH : IsCyclic G']
[FunLike F G' G] [MonoidHomClass F G' G] (f : F) (hf : Function.Surjective f) :
IsCyclic G := by
obtain ⟨x, hx⟩ := hH
refine ⟨f x, fun a ↦ ?_⟩
obtain ⟨a, rfl⟩ := hf a
obtain ⟨n, rfl⟩ := hx a
exact ⟨n, (map_zpow _ _ _).symm⟩
@[to_additive]
theorem orderOf_eq_card_of_forall_mem_zpowers {g : α} (hx : ∀ x, x ∈ zpowers g) :
orderOf g = Nat.card α := by
rw [← Nat.card_zpowers, (zpowers g).eq_top_iff'.mpr hx, card_top]
@[deprecated (since := "2024-11-15")]
alias orderOf_generator_eq_natCard := orderOf_eq_card_of_forall_mem_zpowers
@[deprecated (since := "2024-11-15")]
alias addOrderOf_generator_eq_natCard := addOrderOf_eq_card_of_forall_mem_zmultiples
@[to_additive]
theorem exists_pow_ne_one_of_isCyclic [G_cyclic : IsCyclic G]
{k : ℕ} (k_pos : k ≠ 0) (k_lt_card_G : k < Nat.card G) : ∃ a : G, a ^ k ≠ 1 := by
have : Finite G := Nat.finite_of_card_ne_zero (Nat.ne_zero_of_lt k_lt_card_G)
rcases G_cyclic with ⟨a, ha⟩
use a
contrapose! k_lt_card_G
convert orderOf_le_of_pow_eq_one k_pos.bot_lt k_lt_card_G
rw [← Nat.card_zpowers, eq_comm, card_eq_iff_eq_top, eq_top_iff]
exact fun x _ ↦ ha x
@[to_additive]
theorem Infinite.orderOf_eq_zero_of_forall_mem_zpowers [Infinite α] {g : α}
(h : ∀ x, x ∈ zpowers g) : orderOf g = 0 := by
rw [orderOf_eq_card_of_forall_mem_zpowers h, Nat.card_eq_zero_of_infinite]
@[to_additive]
instance Bot.isCyclic : IsCyclic (⊥ : Subgroup α) :=
⟨⟨1, fun x => ⟨0, Subtype.eq <| (zpow_zero (1 : α)).trans <| Eq.symm (Subgroup.mem_bot.1 x.2)⟩⟩⟩
@[to_additive]
instance Subgroup.isCyclic [IsCyclic α] (H : Subgroup α) : IsCyclic H :=
haveI := Classical.propDecidable
let ⟨g, hg⟩ := IsCyclic.exists_generator (α := α)
if hx : ∃ x : α, x ∈ H ∧ x ≠ (1 : α) then
let ⟨x, hx₁, hx₂⟩ := hx
let ⟨k, hk⟩ := hg x
have hk : g ^ k = x := hk
have hex : ∃ n : ℕ, 0 < n ∧ g ^ n ∈ H :=
⟨k.natAbs,
Nat.pos_of_ne_zero fun h => hx₂ <| by
rw [← hk, Int.natAbs_eq_zero.mp h, zpow_zero], by
rcases k with k | k
· rw [Int.ofNat_eq_coe, Int.natAbs_cast k, ← zpow_natCast, ← Int.ofNat_eq_coe, hk]
exact hx₁
· rw [Int.natAbs_negSucc, ← Subgroup.inv_mem_iff H]; simp_all⟩
⟨⟨⟨g ^ Nat.find hex, (Nat.find_spec hex).2⟩, fun ⟨x, hx⟩ =>
let ⟨k, hk⟩ := hg x
have hk : g ^ k = x := hk
have hk₂ : g ^ ((Nat.find hex : ℤ) * (k / Nat.find hex : ℤ)) ∈ H := by
rw [zpow_mul]
apply H.zpow_mem
exact mod_cast (Nat.find_spec hex).2
have hk₃ : g ^ (k % Nat.find hex : ℤ) ∈ H :=
(Subgroup.mul_mem_cancel_right H hk₂).1 <| by
rw [← zpow_add, Int.emod_add_ediv, hk]; exact hx
have hk₄ : k % Nat.find hex = (k % Nat.find hex).natAbs := by
rw [Int.natAbs_of_nonneg
(Int.emod_nonneg _ (Int.natCast_ne_zero_iff_pos.2 (Nat.find_spec hex).1))]
have hk₅ : g ^ (k % Nat.find hex).natAbs ∈ H := by rwa [← zpow_natCast, ← hk₄]
have hk₆ : (k % (Nat.find hex : ℤ)).natAbs = 0 :=
by_contradiction fun h =>
Nat.find_min hex
(Int.ofNat_lt.1 <| by
rw [← hk₄]; exact Int.emod_lt_of_pos _ (Int.natCast_pos.2 (Nat.find_spec hex).1))
⟨Nat.pos_of_ne_zero h, hk₅⟩
⟨k / (Nat.find hex : ℤ),
Subtype.ext_iff_val.2
(by
suffices g ^ ((Nat.find hex : ℤ) * (k / Nat.find hex : ℤ)) = x by simpa [zpow_mul]
rw [Int.mul_ediv_cancel'
(Int.dvd_of_emod_eq_zero (Int.natAbs_eq_zero.mp hk₆)),
hk])⟩⟩⟩
else by
have : H = (⊥ : Subgroup α) :=
Subgroup.ext fun x =>
⟨fun h => by simp at *; tauto, fun h => by rw [Subgroup.mem_bot.1 h]; exact H.one_mem⟩
subst this; infer_instance
@[to_additive]
theorem isCyclic_of_injective [IsCyclic G'] (f : G →* G') (hf : Function.Injective f) :
IsCyclic G :=
isCyclic_of_surjective (MonoidHom.ofInjective hf).symm (MonoidHom.ofInjective hf).symm.surjective
@[to_additive]
lemma Subgroup.isCyclic_of_le {H H' : Subgroup G} (h : H ≤ H') [IsCyclic H'] : IsCyclic H :=
isCyclic_of_injective (Subgroup.inclusion h) (Subgroup.inclusion_injective h)
open Finset Nat
section Classical
open scoped Classical in
@[to_additive IsAddCyclic.card_nsmul_eq_zero_le]
theorem IsCyclic.card_pow_eq_one_le [DecidableEq α] [Fintype α] [IsCyclic α] {n : ℕ} (hn0 : 0 < n) :
#{a : α | a ^ n = 1} ≤ n :=
let ⟨g, hg⟩ := IsCyclic.exists_generator (α := α)
calc
#{a : α | a ^ n = 1} ≤
#(zpowers (g ^ (Fintype.card α / Nat.gcd n (Fintype.card α))) : Set α).toFinset :=
card_le_card fun x hx =>
let ⟨m, hm⟩ := show x ∈ Submonoid.powers g from mem_powers_iff_mem_zpowers.2 <| hg x
Set.mem_toFinset.2
⟨(m / (Fintype.card α / Nat.gcd n (Fintype.card α)) : ℕ), by
dsimp at hm
have hgmn : g ^ (m * Nat.gcd n (Fintype.card α)) = 1 := by
rw [pow_mul, hm, ← pow_gcd_card_eq_one_iff]; exact (mem_filter.1 hx).2
dsimp only
rw [zpow_natCast, ← pow_mul, Nat.mul_div_cancel_left', hm]
refine Nat.dvd_of_mul_dvd_mul_right (gcd_pos_of_pos_left (Fintype.card α) hn0) ?_
conv_lhs =>
rw [Nat.div_mul_cancel (Nat.gcd_dvd_right _ _), ← Nat.card_eq_fintype_card,
← orderOf_eq_card_of_forall_mem_zpowers hg]
exact orderOf_dvd_of_pow_eq_one hgmn⟩
_ ≤ n := by
let ⟨m, hm⟩ := Nat.gcd_dvd_right n (Fintype.card α)
have hm0 : 0 < m :=
Nat.pos_of_ne_zero fun hm0 => by
rw [hm0, mul_zero, Fintype.card_eq_zero_iff] at hm
exact hm.elim' 1
simp only [Set.toFinset_card, SetLike.coe_sort_coe]
rw [Fintype.card_zpowers, orderOf_pow g, orderOf_eq_card_of_forall_mem_zpowers hg,
Nat.card_eq_fintype_card]
nth_rw 2 [hm]; nth_rw 3 [hm]
rw [Nat.mul_div_cancel_left _ (gcd_pos_of_pos_left _ hn0), gcd_mul_left_left, hm,
Nat.mul_div_cancel _ hm0]
exact le_of_dvd hn0 (Nat.gcd_dvd_left _ _)
end Classical
@[to_additive]
theorem IsCyclic.exists_monoid_generator [Finite α] [IsCyclic α] :
∃ x : α, ∀ y : α, y ∈ Submonoid.powers x := by
simp_rw [mem_powers_iff_mem_zpowers]
exact IsCyclic.exists_generator
@[to_additive]
lemma IsCyclic.exists_ofOrder_eq_natCard [h : IsCyclic α] : ∃ g : α, orderOf g = Nat.card α := by
obtain ⟨g, hg⟩ := h.exists_generator
use g
rw [← card_zpowers g, (eq_top_iff' (zpowers g)).mpr hg]
exact Nat.card_congr (Equiv.Set.univ α)
variable (G) in
/-- A distributive action of a monoid on a finite cyclic group of order `n` factors through an
action on `ZMod n`. -/
noncomputable def MulDistribMulAction.toMonoidHomZModOfIsCyclic (M : Type*) [Monoid M]
[IsCyclic G] [MulDistribMulAction M G] {n : ℕ} (hn : Nat.card G = n) : M →* ZMod n where
toFun m := (MulDistribMulAction.toMonoidHom G m).map_cyclic.choose
map_one' := by
obtain ⟨g, hg⟩ := IsCyclic.exists_ofOrder_eq_natCard (α := G)
rw [← Int.cast_one, ZMod.intCast_eq_intCast_iff, ← hn, ← hg, ← zpow_eq_zpow_iff_modEq,
zpow_one, ← (MulDistribMulAction.toMonoidHom G 1).map_cyclic.choose_spec,
MulDistribMulAction.toMonoidHom_apply, one_smul]
map_mul' m n := by
obtain ⟨g, hg⟩ := IsCyclic.exists_ofOrder_eq_natCard (α := G)
rw [← Int.cast_mul, ZMod.intCast_eq_intCast_iff, ← hn, ← hg, ← zpow_eq_zpow_iff_modEq,
zpow_mul', ← (MulDistribMulAction.toMonoidHom G m).map_cyclic.choose_spec,
← (MulDistribMulAction.toMonoidHom G n).map_cyclic.choose_spec,
← (MulDistribMulAction.toMonoidHom G (m * n)).map_cyclic.choose_spec,
MulDistribMulAction.toMonoidHom_apply, MulDistribMulAction.toMonoidHom_apply,
MulDistribMulAction.toMonoidHom_apply, mul_smul]
theorem MulDistribMulAction.toMonoidHomZModOfIsCyclic_apply {M : Type*} [Monoid M] [IsCyclic G]
[MulDistribMulAction M G] {n : ℕ} (hn : Nat.card G = n) (m : M) (g : G) (k : ℤ)
(h : toMonoidHomZModOfIsCyclic G M hn m = k) : m • g = g ^ k := by
rw [← MulDistribMulAction.toMonoidHom_apply,
(MulDistribMulAction.toMonoidHom G m).map_cyclic.choose_spec g, zpow_eq_zpow_iff_modEq]
apply Int.ModEq.of_dvd (Int.natCast_dvd_natCast.mpr (orderOf_dvd_natCard g))
rwa [hn, ← ZMod.intCast_eq_intCast_iff]
section
variable [Fintype α]
@[to_additive]
theorem IsCyclic.unique_zpow_zmod (ha : ∀ x : α, x ∈ zpowers a) (x : α) :
| ∃! n : ZMod (Fintype.card α), x = a ^ n.val := by
obtain ⟨n, rfl⟩ := ha x
refine ⟨n, (?_ : a ^ n = _), fun y (hy : a ^ n = _) ↦ ?_⟩
· rw [← zpow_natCast, zpow_eq_zpow_iff_modEq, orderOf_eq_card_of_forall_mem_zpowers ha,
Int.modEq_comm, Int.modEq_iff_add_fac, Nat.card_eq_fintype_card, ← ZMod.intCast_eq_iff]
· rw [← zpow_natCast, zpow_eq_zpow_iff_modEq, orderOf_eq_card_of_forall_mem_zpowers ha,
Nat.card_eq_fintype_card, ← ZMod.intCast_eq_intCast_iff] at hy
simp [hy]
| Mathlib/GroupTheory/SpecificGroups/Cyclic.lean | 396 | 404 |
/-
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.Attach
import Mathlib.Data.Finset.Disjoint
import Mathlib.Data.Finset.Erase
import Mathlib.Data.Finset.Filter
import Mathlib.Data.Finset.Range
import Mathlib.Data.Finset.SDiff
import Mathlib.Data.Multiset.Basic
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Defs
import Mathlib.Data.Set.SymmDiff
/-!
# Basic lemmas on finite sets
This file contains lemmas on the interaction of various definitions on the `Finset` type.
For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`.
## Main declarations
### Main definitions
* `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.
### Equivalences between finsets
* The `Mathlib/Logic/Equiv/Defs.lean` file describes 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 Multiset.powerset CompleteLattice Monoid
open Multiset Subtype Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
namespace Finset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
set_option linter.deprecated false in
@[deprecated "Deprecated without replacement." (since := "2025-02-07")]
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
cases s
dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf]
rw [Nat.add_comm]
refine lt_trans ?_ (Nat.lt_succ_self _)
exact Multiset.sizeOf_lt_sizeOf_of_mem hx
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-! #### union -/
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
@[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]
@[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]
/-! #### inter -/
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
omit [DecidableEq α] in
theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) :
Disjoint s t ↔ s = ∅ :=
disjoint_of_le_iff_left_eq_bot h
lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by
simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _),
not_disjoint_iff_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}
@[simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
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
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp +contextual only [mem_erase, mem_insert, and_congr_right_iff,
false_or, iff_self, imp_true_iff]
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]
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]
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]
@[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]
apply or_iff_right_of_imp
rintro rfl
exact h
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_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
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⟩⟩
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 _ _⟩
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]
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
theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s :=
subset_insert_iff.1 <| Subset.rfl
theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) :=
subset_insert_iff.2 <| Subset.rfl
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]
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]
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]
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}
lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by
ext; aesop
-- 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 \ {a} = erase s a := by
ext
rw [mem_erase, mem_sdiff, mem_singleton, and_comm]
-- 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
theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by
simp_rw [erase_eq, disjoint_sdiff_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⟩
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⟩
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]
@[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
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]
theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by
rw [erase_inter, inter_erase]
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]
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]
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]
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]
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]
theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by
simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)]
theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by
simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib,
inter_comm]
theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) :
insert x (s \ insert x t) = s \ t := by
rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)]
theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by
rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq,
union_comm]
theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by
rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq]
theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by
rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff]
--TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra`
theorem sdiff_disjoint : Disjoint (t \ s) s :=
disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2
theorem disjoint_sdiff : Disjoint s (t \ s) :=
sdiff_disjoint.symm
theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) :=
disjoint_of_subset_right inter_subset_right sdiff_disjoint
end Sdiff
/-! ### attach -/
@[simp]
theorem attach_empty : attach (∅ : Finset α) = ∅ :=
rfl
@[simp]
theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by
simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff
@[simp]
theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by
simp [eq_empty_iff_forall_not_mem]
/-! ### filter -/
section Filter
variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α}
theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by
classical
ext x
simp only [mem_singleton, forall_eq, mem_filter]
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) :
filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) :=
eq_of_veq <| Multiset.filter_cons_of_pos s.val hp
theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) :
filter p (cons a s ha) = filter p s :=
eq_of_veq <| Multiset.filter_cons_of_neg s.val hp
theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] :
Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by
constructor <;> simp +contextual [disjoint_left]
theorem disjoint_filter_filter' (s t : Finset α)
{p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) :
Disjoint (s.filter p) (t.filter q) := by
simp_rw [disjoint_left, mem_filter]
rintro a ⟨_, hp⟩ ⟨_, hq⟩
rw [Pi.disjoint_iff] at h
simpa [hp, hq] using h a
theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop)
[DecidablePred p] [∀ x, Decidable (¬p x)] :
Disjoint (s.filter p) (t.filter fun a => ¬p a) :=
disjoint_filter_filter' s t disjoint_compl_right
theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) :
filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) :=
eq_of_veq <| Multiset.filter_add _ _ _
theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) :
filter p (cons a s ha) =
if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by
split_ifs with h
· rw [filter_cons_of_pos _ _ _ ha h]
· rw [filter_cons_of_neg _ _ _ ha h]
section
variable [DecidableEq α]
theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p :=
ext fun _ => by simp only [mem_filter, mem_union, or_and_right]
theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x :=
ext fun x => by simp [mem_filter, mem_union, ← and_or_left]
theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] :
(s.filter fun i => i ∈ t) = s ∩ t :=
ext fun i => by simp [mem_filter, mem_inter]
theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by
ext
simp [mem_filter, mem_inter, and_assoc]
theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by
ext
simp only [mem_inter, mem_filter, and_right_comm]
theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by
rw [inter_comm, filter_inter, inter_comm]
theorem filter_insert (a : α) (s : Finset α) :
filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by
ext x
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by
ext x
simp only [and_assoc, mem_filter, iff_self, mem_erase]
theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q :=
ext fun _ => by simp [mem_filter, mem_union, and_or_left]
theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q :=
ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc]
theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p :=
ext fun a => by
simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or,
Bool.not_eq_true, and_or_left, and_not_self, or_false]
lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] :
s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by
rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)]
theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ :=
ext fun _ => by simp [mem_sdiff, mem_filter]
theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) :
∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by
classical
refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩
· simp [filter_union_right, em]
· intro x
simp
· intro x
simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp]
intro hx hx₂
exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩
-- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing
-- on, e.g. `x ∈ s.filter (Eq b)`.
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq'` with the equality the other way.
-/
theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) :
s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by
split_ifs with h
· ext
simp only [mem_filter, mem_singleton, decide_eq_true_eq]
refine ⟨fun h => h.2.symm, ?_⟩
rintro rfl
exact ⟨h, rfl⟩
· ext
simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq]
rintro m rfl
exact h m
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq` with the equality the other way.
-/
theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b)
theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => b ≠ a) = s.erase b := by
ext
simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not]
tauto
theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b)
theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) :
s.filter p ∪ s.filter q = s :=
(filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial
theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) :
(s.filter p ∪ s.filter fun a => ¬p a) = s :=
filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p
end
end Filter
/-! ### range -/
section Range
open Nat
variable {n m l : ℕ}
@[simp]
theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by
convert filter_eq (range n) m using 2
· ext
rw [eq_comm]
· simp
end Range
end Finset
/-! ### dedup on list and multiset -/
namespace Multiset
variable [DecidableEq α] {s t : Multiset α}
@[simp]
theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by
ext; simp
@[simp]
theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 :=
Finset.val_inj.symm.trans Multiset.dedup_eq_zero
@[simp]
theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by
simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty
@[simp]
theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] :
Multiset.toFinset (s.filter p) = s.toFinset.filter p := by
ext; simp
end Multiset
namespace List
variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β}
{s : Finset α} {t : Set β} {t' : Finset β}
@[simp]
theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by
ext
simp
@[simp]
theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by
ext
simp
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff
@[simp]
theorem toFinset_filter (s : List α) (p : α → Bool) :
(s.filter p).toFinset = s.toFinset.filter (p ·) := by
ext; simp [List.mem_filter]
end List
namespace Finset
section ToList
@[simp]
theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ :=
Multiset.toList_eq_nil.trans val_eq_zero
theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp
@[simp]
theorem toList_empty : (∅ : Finset α).toList = [] :=
toList_eq_nil.mpr rfl
theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] :=
mt toList_eq_nil.mp hs.ne_empty
theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty :=
mt empty_toList.mp hs.ne_empty
end ToList
/-! ### choose -/
section Choose
variable (p : α → Prop) [DecidablePred p] (l : Finset α)
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the corresponding subtype. -/
def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } :=
Multiset.chooseX p l.val hp
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the ambient type. -/
def choose (hp : ∃! a, a ∈ l ∧ p a) : α :=
chooseX p l hp
theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) :=
(chooseX p l hp).property
theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l :=
(choose_spec _ _ _).1
theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) :=
(choose_spec _ _ _).2
end Choose
end Finset
namespace Equiv
variable [DecidableEq α] {s t : Finset α}
open Finset
/-- The disjoint union of finsets is a sum -/
def Finset.union (s t : Finset α) (h : Disjoint s t) :
s ⊕ t ≃ (s ∪ t : Finset α) :=
Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm
@[simp]
theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) :
Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ :=
rfl
@[simp]
theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) :
Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ :=
rfl
/-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the
type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/
def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) :
((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i :=
let e := Equiv.Finset.union s t h
sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e)
/-- A finset is equivalent to its coercion as a set. -/
def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where
toFun a := ⟨a.1, mem_coe.2 a.2⟩
invFun a := ⟨a.1, mem_coe.1 a.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end Equiv
namespace Multiset
variable [DecidableEq α]
@[simp]
lemma toFinset_replicate (n : ℕ) (a : α) :
(replicate n a).toFinset = if n = 0 then ∅ else {a} := by
ext x
simp only [mem_toFinset, Finset.mem_singleton, mem_replicate]
split_ifs with hn <;> simp [hn]
end Multiset
| Mathlib/Data/Finset/Basic.lean | 820 | 820 | |
/-
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.FinitePresentation
import Mathlib.RingTheory.FiniteStability
import Mathlib.RingTheory.Ideal.Cotangent
import Mathlib.RingTheory.Ideal.Quotient.Nilpotent
import Mathlib.RingTheory.Localization.Away.AdjoinRoot
import Mathlib.RingTheory.Localization.Away.Basic
import Mathlib.RingTheory.TensorProduct.Basic
/-!
# 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.
-/
-- 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, stacks 00TI]
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)
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]
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 (S := 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⟩
/-- 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
@[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
@[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
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)
@[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) (x : A) :
g (FormallySmooth.liftOfSurjective f g hg hg' x) = f x := by
apply (Ideal.quotientKerAlgEquivOfSurjective hg).symm.injective
conv_rhs => rw [← AlgHom.coe_coe, ← AlgHom.comp_apply, ← FormallySmooth.mk_lift (A := A) _ hg']
apply (Ideal.quotientKerAlgEquivOfSurjective hg).injective
rw [AlgEquiv.apply_symm_apply, Ideal.quotientKerAlgEquivOfSurjective_apply]
simp only [liftOfSurjective, ← RingHom.ker_coe_toRingHom g, RingHom.kerLift_mk,
AlgEquiv.toAlgHom_eq_coe, RingHom.coe_coe]
@[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')
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]
theorem iff_of_equiv (e : A ≃ₐ[R] B) : FormallySmooth R A ↔ FormallySmooth R B :=
⟨fun _ ↦ of_equiv e, fun _ ↦ of_equiv e.symm⟩
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
instance polynomial : FormallySmooth R R[X] :=
FormallySmooth.of_equiv (MvPolynomial.pUnitAlgEquiv R)
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)⟩
end Comp
section OfSurjective
variable {R : Type u} [CommRing R]
variable {P A : Type u} [CommRing A] [Algebra R A] [CommRing P] [Algebra R P]
variable (f : P →ₐ[R] A)
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]⟩
variable (hf : Function.Surjective f)
include hf
/-- 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. -/
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]
dsimp only [AlgHom.toRingHom_eq_coe, RingHom.ker_coe_toRingHom] at sqz
refine
⟨FormallySmooth.lift _ ⟨2, sqz⟩ (Ideal.quotientKerAlgEquivOfSurjective surj).symm.toAlgHom,
?_⟩
dsimp only [AlgHom.toRingHom_eq_coe, AlgEquiv.toAlgHom_eq_coe]
ext x
have :=
(Ideal.quotientKerAlgEquivOfSurjective surj).congr_arg
(FormallySmooth.mk_lift (R := R) _ ⟨2, sqz⟩
(Ideal.quotientKerAlgEquivOfSurjective surj).symm x)
dsimp only [AlgHom.toRingHom_eq_coe, AlgHom.coe_coe] at this
rw [AlgEquiv.apply_symm_apply] at this
conv_rhs => rw [← this, AlgHom.id_apply]
rfl
· rintro ⟨g, hg⟩; exact FormallySmooth.of_split f g hg
end OfSurjective
section BaseChange
open scoped TensorProduct
variable {R : Type u} [CommSemiring R]
variable {A : Type u} [Semiring A] [Algebra R A]
variable (B : Type u) [CommSemiring B] [Algebra R B]
instance base_change [FormallySmooth R A] : FormallySmooth B (B ⊗[R] A) := by
constructor
intro C _ _ I hI f
letI := ((algebraMap B C).comp (algebraMap R B)).toAlgebra
haveI : IsScalarTower R B C := IsScalarTower.of_algebraMap_eq' rfl
refine ⟨TensorProduct.productLeftAlgHom (Algebra.ofId B C) ?_, ?_⟩
· exact FormallySmooth.lift I ⟨2, hI⟩ ((f.restrictScalars R).comp TensorProduct.includeRight)
· apply AlgHom.restrictScalars_injective R
apply TensorProduct.ext'
intro b a
suffices algebraMap B _ b * f (1 ⊗ₜ[R] a) = f (b ⊗ₜ[R] a) by simpa [Algebra.ofId_apply]
rw [← Algebra.smul_def, ← map_smul, TensorProduct.smul_tmul', smul_eq_mul, mul_one]
end BaseChange
section Localization
variable {R S Rₘ Sₘ : Type u} [CommRing R] [CommRing S] [CommRing Rₘ] [CommRing Sₘ]
variable (M : Submonoid R)
variable [Algebra R S] [Algebra R Sₘ] [Algebra S Sₘ] [Algebra R Rₘ] [Algebra Rₘ Sₘ]
variable [IsScalarTower R Rₘ Sₘ] [IsScalarTower R S Sₘ]
variable [IsLocalization M Rₘ] [IsLocalization (M.map (algebraMap R S)) Sₘ]
include M
-- Porting note: no longer supported
-- attribute [local elab_as_elim] Ideal.IsNilpotent.induction_on
theorem of_isLocalization : FormallySmooth R Rₘ := by
constructor
intro Q _ _ I e f
have : ∀ x : M, IsUnit (algebraMap R Q x) := by
intro x
apply (IsNilpotent.isUnit_quotient_mk_iff ⟨2, e⟩).mp
convert (IsLocalization.map_units Rₘ x).map f
simp only [Ideal.Quotient.mk_algebraMap, AlgHom.commutes]
let this : Rₘ →ₐ[R] Q :=
{ IsLocalization.lift this with commutes' := IsLocalization.lift_eq this }
use this
apply AlgHom.coe_ringHom_injective
refine IsLocalization.ringHom_ext M ?_
ext
simp
theorem localization_base [FormallySmooth R Sₘ] : FormallySmooth Rₘ Sₘ := by
constructor
intro Q _ _ I e f
letI := ((algebraMap Rₘ Q).comp (algebraMap R Rₘ)).toAlgebra
letI : IsScalarTower R Rₘ Q := IsScalarTower.of_algebraMap_eq' rfl
let f : Sₘ →ₐ[Rₘ] Q := by
refine { FormallySmooth.lift I ⟨2, e⟩ (f.restrictScalars R) with commutes' := ?_ }
intro r
change
(RingHom.comp (FormallySmooth.lift I ⟨2, e⟩ (f.restrictScalars R) : Sₘ →+* Q)
(algebraMap _ _))
r =
algebraMap _ _ r
congr 1
refine IsLocalization.ringHom_ext M ?_
rw [RingHom.comp_assoc, ← IsScalarTower.algebraMap_eq, ← IsScalarTower.algebraMap_eq,
AlgHom.comp_algebraMap]
use f
ext
simp [f]
theorem localization_map [FormallySmooth R S] : FormallySmooth Rₘ Sₘ := by
haveI : FormallySmooth S Sₘ := FormallySmooth.of_isLocalization (M.map (algebraMap R S))
haveI : FormallySmooth R Sₘ := FormallySmooth.comp R S Sₘ
exact FormallySmooth.localization_base M
end Localization
end FormallySmooth
section
variable (R : Type u) [CommSemiring R]
variable (A : Type u) [Semiring A] [Algebra R A]
/-- An `R` algebra `A` is smooth if it is formally smooth and of finite presentation. -/
@[stacks 00T2 "In the stacks project, the definition of smooth is completely different, and tag
<https://stacks.math.columbia.edu/tag/00TN> proves that their definition is equivalent to this."]
class Smooth [CommSemiring R] (A : Type u) [Semiring A] [Algebra R A] : Prop where
formallySmooth : FormallySmooth R A := by infer_instance
finitePresentation : FinitePresentation R A := by infer_instance
end
namespace Smooth
attribute [instance] formallySmooth finitePresentation
|
variable {R : Type u} [CommRing R]
variable {A B : Type u} [CommRing A] [Algebra R A] [CommRing B] [Algebra R B]
| Mathlib/RingTheory/Smooth/Basic.lean | 344 | 347 |
/-
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.Family
/-! # 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 Set Equiv Order
open scoped Cardinal Ordinal
universe u v w
namespace Ordinal
/-- The ordinal exponential, defined by transfinite recursion.
We call this `opow` in theorems in order to disambiguate from other exponentials. -/
instance instPow : Pow Ordinal Ordinal :=
⟨fun a b ↦ if a = 0 then 1 - b else
limitRecOn b 1 (fun _ x ↦ x * a) fun o _ f ↦ ⨆ x : Iio o, f x.1 x.2⟩
private theorem opow_of_ne_zero {a b : Ordinal} (h : a ≠ 0) : a ^ b =
limitRecOn b 1 (fun _ x ↦ x * a) fun o _ f ↦ ⨆ x : Iio o, f x.1 x.2 :=
if_neg h
/-- `0 ^ a = 1` if `a = 0` and `0 ^ a = 0` otherwise. -/
theorem zero_opow' (a : Ordinal) : 0 ^ a = 1 - a :=
if_pos rfl
theorem zero_opow_le (a : Ordinal) : (0 : Ordinal) ^ a ≤ 1 := by
rw [zero_opow']
exact sub_le_self 1 a
@[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]
@[simp]
theorem opow_zero (a : Ordinal) : a ^ (0 : Ordinal) = 1 := by
obtain rfl | h := eq_or_ne a 0
· rw [zero_opow', Ordinal.sub_zero]
· rw [opow_of_ne_zero h, limitRecOn_zero]
@[simp]
theorem opow_succ (a b : Ordinal) : a ^ succ b = a ^ b * a := by
obtain rfl | h := eq_or_ne a 0
· rw [zero_opow (succ_ne_zero b), mul_zero]
· rw [opow_of_ne_zero h, opow_of_ne_zero h, limitRecOn_succ]
theorem opow_limit {a b : Ordinal} (ha : a ≠ 0) (hb : IsLimit b) :
a ^ b = ⨆ x : Iio b, a ^ x.1 := by
simp_rw [opow_of_ne_zero ha, limitRecOn_limit _ _ _ _ hb]
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, Ordinal.iSup_le_iff, Subtype.forall]
rfl
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]
@[simp]
theorem opow_one (a : Ordinal) : a ^ (1 : Ordinal) = a := by
rw [← succ_zero, opow_succ]
simp only [opow_zero, one_mul]
@[simp]
theorem one_opow (a : Ordinal) : (1 : Ordinal) ^ a = 1 := by
induction a using limitRecOn with
| zero => simp only [opow_zero]
| succ _ ih =>
simp only [opow_succ, ih, mul_one]
| isLimit 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]⟩
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
| zero => exact h0
| succ b IH =>
rw [opow_succ]
exact mul_pos IH a0
| isLimit b l _ =>
exact (lt_opow_of_limit (Ordinal.pos_iff_ne_zero.1 a0) l).2 ⟨0, l.pos, h0⟩
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
@[simp]
theorem opow_eq_zero {a b : Ordinal} : a ^ b = 0 ↔ a = 0 ∧ b ≠ 0 := by
obtain rfl | ha := eq_or_ne a 0
· obtain rfl | hb := eq_or_ne b 0
· simp
· simp [hb]
· simp [opow_ne_zero b ha, ha]
@[simp, norm_cast]
theorem opow_natCast (a : Ordinal) (n : ℕ) : a ^ (n : Ordinal) = a ^ n := by
induction n with
| zero => rw [Nat.cast_zero, opow_zero, pow_zero]
| succ n IH => rw [Nat.cast_succ, add_one_eq_succ, opow_succ, pow_succ, IH]
theorem isNormal_opow {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 _ l _ => opow_le_of_limit (ne_of_gt a0) l⟩
theorem opow_lt_opow_iff_right {a b c : Ordinal} (a1 : 1 < a) : a ^ b < a ^ c ↔ b < c :=
(isNormal_opow a1).lt_iff
theorem opow_le_opow_iff_right {a b c : Ordinal} (a1 : 1 < a) : a ^ b ≤ a ^ c ↔ b ≤ c :=
(isNormal_opow a1).le_iff
theorem opow_right_inj {a b c : Ordinal} (a1 : 1 < a) : a ^ b = a ^ c ↔ b = c :=
(isNormal_opow a1).inj
theorem isLimit_opow {a b : Ordinal} (a1 : 1 < a) : IsLimit b → IsLimit (a ^ b) :=
(isNormal_opow a1).isLimit
theorem isLimit_opow_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 isLimit_mul (opow_pos _ l.pos) l
· exact isLimit_opow l.one_lt l'
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]
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
| zero => simp only [opow_zero, le_refl]
| succ c IH =>
simpa only [opow_succ] using mul_le_mul' IH ab
| isLimit 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)
theorem opow_le_opow {a b c d : Ordinal} (hac : a ≤ c) (hbd : b ≤ d) (hc : 0 < c) : a ^ b ≤ c ^ d :=
(opow_le_opow_left b hac).trans (opow_le_opow_right hc hbd)
theorem left_le_opow (a : Ordinal) {b : Ordinal} (b1 : 0 < b) : a ≤ a ^ b := by
nth_rw 1 [← opow_one a]
rcases 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]
theorem left_lt_opow {a b : Ordinal} (ha : 1 < a) (hb : 1 < b) : a < a ^ b := by
conv_lhs => rw [← opow_one a]
rwa [opow_lt_opow_iff_right ha]
theorem right_le_opow {a : Ordinal} (b : Ordinal) (a1 : 1 < a) : b ≤ a ^ b :=
(isNormal_opow a1).le_apply
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)))
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
| zero => simp
| succ c IH =>
rw [add_succ, opow_succ, IH, opow_succ, mul_assoc]
| isLimit c l IH =>
refine
eq_of_forall_ge_iff fun d =>
(((isNormal_opow a1).trans (isNormal_add_right b)).limit_le l).trans ?_
dsimp only [Function.comp_def]
simp +contextual only [IH]
exact
(((isNormal_mul_right <| opow_pos b (Ordinal.pos_iff_ne_zero.2 a0)).trans
(isNormal_opow a1)).limit_le
l).symm
theorem opow_one_add (a b : Ordinal) : a ^ (1 + b) = a * a ^ b := by rw [opow_add, opow_one]
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]⟩
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 _⟩
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)]
rcases 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
| zero => simp only [mul_zero, opow_zero]
| succ c IH =>
rw [mul_succ, opow_add, IH, opow_succ]
| isLimit c l IH =>
refine
eq_of_forall_ge_iff fun d =>
(((isNormal_opow a1).trans (isNormal_mul_right (Ordinal.pos_iff_ne_zero.2 b0))).limit_le
l).trans
?_
dsimp only [Function.comp_def]
simp +contextual only [IH]
exact (opow_le_of_limit (opow_ne_zero _ a0) l).symm
theorem opow_mul_add_pos {b v : Ordinal} (hb : b ≠ 0) (u : Ordinal) (hv : v ≠ 0) (w : Ordinal) :
0 < b ^ u * v + w :=
(opow_pos u <| Ordinal.pos_iff_ne_zero.2 hb).trans_le <|
(le_mul_left _ <| Ordinal.pos_iff_ne_zero.2 hv).trans <| le_add_right _ _
theorem opow_mul_add_lt_opow_mul_succ {b u w : Ordinal} (v : Ordinal) (hw : w < b ^ u) :
b ^ u * v + w < b ^ u * succ v := by
rwa [mul_succ, add_lt_add_iff_left]
theorem opow_mul_add_lt_opow_succ {b u v w : Ordinal} (hvb : v < b) (hw : w < b ^ u) :
b ^ u * v + w < b ^ succ u := by
convert (opow_mul_add_lt_opow_mul_succ v hw).trans_le
(mul_le_mul_left' (succ_le_of_lt hvb) _) using 1
exact opow_succ b u
/-! ### 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]
def log (b : Ordinal) (x : Ordinal) : Ordinal :=
if 1 < b then pred (sInf { o | x < b ^ o }) else 0
/-- The set in the definition of `log` is nonempty. -/
private theorem log_nonempty {b x : Ordinal} (h : 1 < b) : { o : Ordinal | x < b ^ o }.Nonempty :=
⟨_, succ_le_iff.1 (right_le_opow _ h)⟩
theorem log_def {b : Ordinal} (h : 1 < b) (x : Ordinal) : log b x = pred (sInf { o | x < b ^ o }) :=
if_pos h
theorem log_of_left_le_one {b : Ordinal} (h : b ≤ 1) (x : Ordinal) : log b x = 0 :=
if_neg h.not_lt
@[simp]
theorem log_zero_left : ∀ b, log 0 b = 0 :=
log_of_left_le_one zero_le_one
@[simp]
theorem log_zero_right (b : Ordinal) : log b 0 = 0 := by
obtain hb | hb := lt_or_le 1 b
· rw [log_def hb, ← Ordinal.le_zero, pred_le, succ_zero]
apply csInf_le'
rw [mem_setOf, opow_one]
exact bot_lt_of_lt hb
· rw [log_of_left_le_one hb]
@[simp]
theorem log_one_left : ∀ b, log 1 b = 0 :=
log_of_left_le_one le_rfl
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)
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)
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)
· exact (zero_opow_le _).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]
/-- `opow b` and `log b` (almost) form a Galois connection.
See `opow_le_iff_le_log'` for a variant assuming `c ≠ 0` rather than `x ≠ 0`. See also
`le_log_of_opow_le` and `opow_le_of_le_log`, which are both separate implications under weaker
assumptions. -/
theorem opow_le_iff_le_log {b x c : Ordinal} (hb : 1 < b) (hx : x ≠ 0) :
b ^ c ≤ x ↔ c ≤ log b x := by
constructor <;>
intro h
· apply le_of_not_lt
intro hn
apply (lt_opow_succ_log_self hb x).not_le <|
((opow_le_opow_iff_right hb).2 <| succ_le_of_lt hn).trans h
· exact ((opow_le_opow_iff_right hb).2 h).trans <| opow_log_le_self b hx
/-- `opow b` and `log b` (almost) form a Galois connection.
See `opow_le_iff_le_log` for a variant assuming `x ≠ 0` rather than `c ≠ 0`. See also
`le_log_of_opow_le` and `opow_le_of_le_log`, which are both separate implications under weaker
assumptions. -/
| theorem opow_le_iff_le_log' {b x c : Ordinal} (hb : 1 < b) (hc : c ≠ 0) :
b ^ c ≤ x ↔ c ≤ log b x := by
obtain rfl | hx := eq_or_ne x 0
· rw [log_zero_right, Ordinal.le_zero, Ordinal.le_zero, opow_eq_zero]
simp [hc, (zero_lt_one.trans hb).ne']
· exact opow_le_iff_le_log hb hx
theorem le_log_of_opow_le {b x c : Ordinal} (hb : 1 < b) (h : b ^ c ≤ x) : c ≤ log b x := by
| Mathlib/SetTheory/Ordinal/Exponential.lean | 347 | 354 |
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.AffineScheme
import Mathlib.AlgebraicGeometry.Pullbacks
import Mathlib.AlgebraicGeometry.Limits
import Mathlib.CategoryTheory.MorphismProperty.Limits
import Mathlib.Data.List.TFAE
/-!
# Properties of morphisms between Schemes
We provide the basic framework for talking about properties of morphisms between Schemes.
A `MorphismProperty Scheme` is a predicate on morphisms between schemes. For properties local at
the target, its behaviour is entirely determined by its definition on morphisms into affine schemes,
which we call an `AffineTargetMorphismProperty`. In this file, we provide API lemmas for properties
local at the target, and special support for those properties whose `AffineTargetMorphismProperty`
takes on a more simple form. We also provide API lemmas for properties local at the target.
The main interfaces of the API are the typeclasses `IsLocalAtTarget`, `IsLocalAtSource` and
`HasAffineProperty`, which we describle in detail below.
## `IsLocalAtTarget`
- `AlgebraicGeometry.IsLocalAtTarget`: We say that `IsLocalAtTarget P` for
`P : MorphismProperty Scheme` if
1. `P` respects isomorphisms.
2. `P` holds for `f ∣_ U` for an open cover `U` of `Y` if and only if `P` holds for `f`.
For a morphism property `P` local at the target and `f : X ⟶ Y`, we provide these API lemmas:
- `AlgebraicGeometry.IsLocalAtTarget.of_isPullback`:
`P` is preserved under pullback along open immersions.
- `AlgebraicGeometry.IsLocalAtTarget.restrict`:
`P f → P (f ∣_ U)` for an open `U` of `Y`.
- `AlgebraicGeometry.IsLocalAtTarget.iff_of_iSup_eq_top`:
`P f ↔ ∀ i, P (f ∣_ U i)` for a family `U i` of open sets covering `Y`.
- `AlgebraicGeometry.IsLocalAtTarget.iff_of_openCover`:
`P f ↔ ∀ i, P (𝒰.pullbackHom f i)` for `𝒰 : Y.openCover`.
## `IsLocalAtSource`
- `AlgebraicGeometry.IsLocalAtSource`: We say that `IsLocalAtSource P` for
`P : MorphismProperty Scheme` if
1. `P` respects isomorphisms.
2. `P` holds for `𝒰.map i ≫ f` for an open cover `𝒰` of `X` iff `P` holds for `f : X ⟶ Y`.
For a morphism property `P` local at the source and `f : X ⟶ Y`, we provide these API lemmas:
- `AlgebraicGeometry.IsLocalAtTarget.comp`:
`P` is preserved under composition with open immersions at the source.
- `AlgebraicGeometry.IsLocalAtTarget.iff_of_iSup_eq_top`:
`P f ↔ ∀ i, P (U.ι ≫ f)` for a family `U i` of open sets covering `X`.
- `AlgebraicGeometry.IsLocalAtTarget.iff_of_openCover`:
`P f ↔ ∀ i, P (𝒰.map i ≫ f)` for `𝒰 : X.openCover`.
- `AlgebraicGeometry.IsLocalAtTarget.of_isOpenImmersion`: If `P` contains identities then `P` holds
for open immersions.
## `AffineTargetMorphismProperty`
- `AlgebraicGeometry.AffineTargetMorphismProperty`:
The type of predicates on `f : X ⟶ Y` with `Y` affine.
- `AlgebraicGeometry.AffineTargetMorphismProperty.IsLocal`: We say that `P.IsLocal` if `P`
satisfies the assumptions of the affine communication lemma
(`AlgebraicGeometry.of_affine_open_cover`). That is,
1. `P` respects isomorphisms.
2. If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ Y.basicOpen r` for any
global section `r`.
3. If `P` holds for `f ∣_ Y.basicOpen r` for all `r` in a spanning set of the global sections,
then `P` holds for `f`.
## `HasAffineProperty`
- `AlgebraicGeometry.HasAffineProperty`:
`HasAffineProperty P Q` is a type class asserting that `P` is local at the target,
and over affine schemes, it is equivalent to `Q : AffineTargetMorphismProperty`.
For `HasAffineProperty P Q` and `f : X ⟶ Y`, we provide these API lemmas:
- `AlgebraicGeometry.HasAffineProperty.of_isPullback`:
`P` is preserved under pullback along open immersions from affine schemes.
- `AlgebraicGeometry.HasAffineProperty.restrict`:
`P f → Q (f ∣_ U)` for affine `U` of `Y`.
- `AlgebraicGeometry.HasAffineProperty.iff_of_iSup_eq_top`:
`P f ↔ ∀ i, Q (f ∣_ U i)` for a family `U i` of affine open sets covering `Y`.
- `AlgebraicGeometry.HasAffineProperty.iff_of_openCover`:
`P f ↔ ∀ i, P (𝒰.pullbackHom f i)` for affine open covers `𝒰` of `Y`.
- `AlgebraicGeometry.HasAffineProperty.isStableUnderBaseChange_mk`:
If `Q` is stable under affine base change, then `P` is stable under arbitrary base change.
-/
universe u v
open TopologicalSpace CategoryTheory CategoryTheory.Limits Opposite
noncomputable section
namespace AlgebraicGeometry
/--
We say that `P : MorphismProperty Scheme` is local at the target if
1. `P` respects isomorphisms.
2. `P` holds for `f ∣_ U` for an open cover `U` of `Y` if and only if `P` holds for `f`.
Also see `IsLocalAtTarget.mk'` for a convenient constructor.
-/
class IsLocalAtTarget (P : MorphismProperty Scheme) : Prop where
/-- `P` respects isomorphisms. -/
respectsIso : P.RespectsIso := by infer_instance
/-- `P` holds for `f ∣_ U` for an open cover `U` of `Y` if and only if `P` holds for `f`. -/
iff_of_openCover' :
∀ {X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} Y),
P f ↔ ∀ i, P (𝒰.pullbackHom f i)
namespace IsLocalAtTarget
attribute [instance] respectsIso
/--
`P` is local at the target if
1. `P` respects isomorphisms.
2. If `P` holds for `f : X ⟶ Y`, then `P` holds for `f ∣_ U` for any `U`.
3. If `P` holds for `f ∣_ U` for an open cover `U` of `Y`, then `P` holds for `f`.
-/
protected lemma mk' {P : MorphismProperty Scheme} [P.RespectsIso]
(restrict : ∀ {X Y : Scheme} (f : X ⟶ Y) (U : Y.Opens), P f → P (f ∣_ U))
(of_sSup_eq_top :
∀ {X Y : Scheme.{u}} (f : X ⟶ Y) {ι : Type u} (U : ι → Y.Opens), iSup U = ⊤ →
(∀ i, P (f ∣_ U i)) → P f) :
IsLocalAtTarget P := by
refine ⟨inferInstance, fun {X Y} f 𝒰 ↦ ⟨?_, fun H ↦ of_sSup_eq_top f _ 𝒰.iSup_opensRange ?_⟩⟩
· exact fun H i ↦ (P.arrow_mk_iso_iff (morphismRestrictOpensRange f _)).mp (restrict _ _ H)
· exact fun i ↦ (P.arrow_mk_iso_iff (morphismRestrictOpensRange f _)).mpr (H i)
/-- The intersection of two morphism properties that are local at the target is again local at
the target. -/
instance inf (P Q : MorphismProperty Scheme) [IsLocalAtTarget P] [IsLocalAtTarget Q] :
IsLocalAtTarget (P ⊓ Q) where
iff_of_openCover' {_ _} f 𝒰 :=
⟨fun h i ↦ ⟨(iff_of_openCover' f 𝒰).mp h.left i, (iff_of_openCover' f 𝒰).mp h.right i⟩,
fun h ↦ ⟨(iff_of_openCover' f 𝒰).mpr (fun i ↦ (h i).left),
(iff_of_openCover' f 𝒰).mpr (fun i ↦ (h i).right)⟩⟩
variable {P} [hP : IsLocalAtTarget P] {X Y : Scheme.{u}} {f : X ⟶ Y} (𝒰 : Y.OpenCover)
lemma of_isPullback {UX UY : Scheme.{u}} {iY : UY ⟶ Y} [IsOpenImmersion iY]
{iX : UX ⟶ X} {f' : UX ⟶ UY} (h : IsPullback iX f' f iY) (H : P f) : P f' := by
rw [← P.cancel_left_of_respectsIso h.isoPullback.inv, h.isoPullback_inv_snd]
exact (iff_of_openCover' f (Y.affineCover.add iY)).mp H .none
theorem restrict (hf : P f) (U : Y.Opens) : P (f ∣_ U) :=
of_isPullback (isPullback_morphismRestrict f U).flip hf
lemma of_iSup_eq_top {ι} (U : ι → Y.Opens) (hU : iSup U = ⊤)
(H : ∀ i, P (f ∣_ U i)) : P f := by
refine (IsLocalAtTarget.iff_of_openCover' f
(Y.openCoverOfISupEqTop (s := Set.range U) Subtype.val (by ext; simp [← hU]))).mpr fun i ↦ ?_
obtain ⟨_, i, rfl⟩ := i
refine (P.arrow_mk_iso_iff (morphismRestrictOpensRange f _)).mp ?_
show P (f ∣_ (U i).ι.opensRange)
rw [Scheme.Opens.opensRange_ι]
exact H i
theorem iff_of_iSup_eq_top {ι} (U : ι → Y.Opens) (hU : iSup U = ⊤) :
P f ↔ ∀ i, P (f ∣_ U i) :=
⟨fun H _ ↦ restrict H _, of_iSup_eq_top U hU⟩
|
lemma of_openCover (H : ∀ i, P (𝒰.pullbackHom f i)) : P f := by
apply of_iSup_eq_top (fun i ↦ (𝒰.map i).opensRange) 𝒰.iSup_opensRange
exact fun i ↦ (P.arrow_mk_iso_iff (morphismRestrictOpensRange f _)).mpr (H i)
theorem iff_of_openCover (𝒰 : Y.OpenCover) :
P f ↔ ∀ i, P (𝒰.pullbackHom f i) :=
⟨fun H _ ↦ of_isPullback (.of_hasPullback _ _) H, of_openCover _⟩
lemma of_range_subset_iSup [P.RespectsRight @IsOpenImmersion] {ι : Type*} (U : ι → Y.Opens)
(H : Set.range f.base ⊆ (⨆ i, U i : Y.Opens)) (hf : ∀ i, P (f ∣_ U i)) : P f := by
let g : X ⟶ (⨆ i, U i : Y.Opens) := IsOpenImmersion.lift (Scheme.Opens.ι _) f (by simpa using H)
rw [← IsOpenImmersion.lift_fac (⨆ i, U i).ι f (by simpa using H)]
apply MorphismProperty.RespectsRight.postcomp (Q := @IsOpenImmersion) _ inferInstance
rw [IsLocalAtTarget.iff_of_iSup_eq_top (P := P) (U := fun i : ι ↦ (⨆ i, U i).ι ⁻¹ᵁ U i)]
· intro i
have heq : g ⁻¹ᵁ (⨆ i, U i).ι ⁻¹ᵁ U i = f ⁻¹ᵁ U i := by
show (g ≫ (⨆ i, U i).ι) ⁻¹ᵁ U i = _
simp [g]
let e : Arrow.mk (g ∣_ (⨆ i, U i).ι ⁻¹ᵁ U i) ≅ Arrow.mk (f ∣_ U i) :=
Arrow.isoMk (X.isoOfEq heq) (Scheme.Opens.isoOfLE (le_iSup U i)) <| by
simp [← CategoryTheory.cancel_mono (U i).ι, g]
rw [P.arrow_mk_iso_iff e]
exact hf i
apply (⨆ i, U i).ι.image_injective
dsimp
rw [Scheme.Hom.image_iSup, Scheme.Hom.image_top_eq_opensRange, Scheme.Opens.opensRange_ι]
simp [Scheme.Hom.image_preimage_eq_opensRange_inter, le_iSup U]
end IsLocalAtTarget
/--
We say that `P : MorphismProperty Scheme` is local at the source if
1. `P` respects isomorphisms.
2. `P` holds for `𝒰.map i ≫ f` for an open cover `𝒰` of `X` iff `P` holds for `f : X ⟶ Y`.
Also see `IsLocalAtSource.mk'` for a convenient constructor.
-/
class IsLocalAtSource (P : MorphismProperty Scheme) : Prop where
| Mathlib/AlgebraicGeometry/Morphisms/Basic.lean | 169 | 206 |
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Kexing Ying, Eric Wieser
-/
import Mathlib.Data.Finset.Sym
import Mathlib.LinearAlgebra.BilinearMap
import Mathlib.LinearAlgebra.FiniteDimensional.Lemmas
import Mathlib.LinearAlgebra.Matrix.Determinant.Basic
import Mathlib.LinearAlgebra.Matrix.SesquilinearForm
import Mathlib.LinearAlgebra.Matrix.Symmetric
/-!
# Quadratic maps
This file defines quadratic maps on an `R`-module `M`, taking values in an `R`-module `N`.
An `N`-valued quadratic map on a module `M` over a commutative ring `R` is a map `Q : M → N` such
that:
* `QuadraticMap.map_smul`: `Q (a • x) = (a * a) • Q x`
* `QuadraticMap.polar_add_left`, `QuadraticMap.polar_add_right`,
`QuadraticMap.polar_smul_left`, `QuadraticMap.polar_smul_right`:
the map `QuadraticMap.polar Q := fun x y ↦ Q (x + y) - Q x - Q y` is bilinear.
This notion generalizes to commutative semirings using the approach in [izhakian2016][] which
requires that there be a (possibly non-unique) companion bilinear map `B` such that
`∀ x y, Q (x + y) = Q x + Q y + B x y`. Over a ring, this `B` is precisely `QuadraticMap.polar Q`.
To build a `QuadraticMap` from the `polar` axioms, use `QuadraticMap.ofPolar`.
Quadratic maps come with a scalar multiplication, `(a • Q) x = a • Q x`,
and composition with linear maps `f`, `Q.comp f x = Q (f x)`.
## Main definitions
* `QuadraticMap.ofPolar`: a more familiar constructor that works on rings
* `QuadraticMap.associated`: associated bilinear map
* `QuadraticMap.PosDef`: positive definite quadratic maps
* `QuadraticMap.Anisotropic`: anisotropic quadratic maps
* `QuadraticMap.discr`: discriminant of a quadratic map
* `QuadraticMap.IsOrtho`: orthogonality of vectors with respect to a quadratic map.
## Main statements
* `QuadraticMap.associated_left_inverse`,
* `QuadraticMap.associated_rightInverse`: in a commutative ring where 2 has
an inverse, there is a correspondence between quadratic maps and symmetric
bilinear forms
* `LinearMap.BilinForm.exists_orthogonal_basis`: There exists an orthogonal basis with
respect to any nondegenerate, symmetric bilinear map `B`.
## Notation
In this file, the variable `R` is used when a `CommSemiring` structure is available.
The variable `S` is used when `R` itself has a `•` action.
## Implementation notes
While the definition and many results make sense if we drop commutativity assumptions,
the correct definition of a quadratic maps in the noncommutative setting would require
substantial refactors from the current version, such that $Q(rm) = rQ(m)r^*$ for some
suitable conjugation $r^*$.
The [Zulip thread](https://leanprover.zulipchat.com/#narrow/stream/116395-maths/topic/Quadratic.20Maps/near/395529867)
has some further discussion.
## References
* https://en.wikipedia.org/wiki/Quadratic_form
* https://en.wikipedia.org/wiki/Discriminant#Quadratic_forms
## Tags
quadratic map, homogeneous polynomial, quadratic polynomial
-/
universe u v w
variable {S T : Type*}
variable {R : Type*} {M N P A : Type*}
open LinearMap (BilinMap BilinForm)
section Polar
variable [CommRing R] [AddCommGroup M] [AddCommGroup N]
namespace QuadraticMap
/-- Up to a factor 2, `Q.polar` is the associated bilinear map for a quadratic map `Q`.
Source of this name: https://en.wikipedia.org/wiki/Quadratic_form#Generalization
-/
def polar (f : M → N) (x y : M) :=
f (x + y) - f x - f y
protected theorem map_add (f : M → N) (x y : M) :
f (x + y) = f x + f y + polar f x y := by
rw [polar]
abel
theorem polar_add (f g : M → N) (x y : M) : polar (f + g) x y = polar f x y + polar g x y := by
simp only [polar, Pi.add_apply]
abel
theorem polar_neg (f : M → N) (x y : M) : polar (-f) x y = -polar f x y := by
simp only [polar, Pi.neg_apply, sub_eq_add_neg, neg_add]
theorem polar_smul [Monoid S] [DistribMulAction S N] (f : M → N) (s : S) (x y : M) :
| polar (s • f) x y = s • polar f x y := by simp only [polar, Pi.smul_apply, smul_sub]
| Mathlib/LinearAlgebra/QuadraticForm/Basic.lean | 111 | 112 |
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Data.Finset.NAry
import Mathlib.Data.Finset.Slice
import Mathlib.Data.Set.Sups
/-!
# Set family operations
This file defines a few binary operations on `Finset α` for use in set family combinatorics.
## Main declarations
* `Finset.sups s t`: Finset of elements of the form `a ⊔ b` where `a ∈ s`, `b ∈ t`.
* `Finset.infs s t`: Finset of elements of the form `a ⊓ b` where `a ∈ s`, `b ∈ t`.
* `Finset.disjSups s t`: Finset of elements of the form `a ⊔ b` where `a ∈ s`, `b ∈ t` and `a`
and `b` are disjoint.
* `Finset.diffs`: Finset of elements of the form `a \ b` where `a ∈ s`, `b ∈ t`.
* `Finset.compls`: Finset of elements of the form `aᶜ` where `a ∈ s`.
## Notation
We define the following notation in locale `FinsetFamily`:
* `s ⊻ t` for `Finset.sups`
* `s ⊼ t` for `Finset.infs`
* `s ○ t` for `Finset.disjSups s t`
* `s \\ t` for `Finset.diffs`
* `sᶜˢ` for `Finset.compls`
## References
[B. Bollobás, *Combinatorics*][bollobas1986]
-/
open Function
open SetFamily
variable {F α β : Type*}
namespace Finset
section Sups
variable [DecidableEq α] [DecidableEq β]
variable [SemilatticeSup α] [SemilatticeSup β] [FunLike F α β] [SupHomClass F α β]
variable (s s₁ s₂ t t₁ t₂ u v : Finset α)
/-- `s ⊻ t` is the finset of elements of the form `a ⊔ b` where `a ∈ s`, `b ∈ t`. -/
protected def hasSups : HasSups (Finset α) :=
⟨image₂ (· ⊔ ·)⟩
scoped[FinsetFamily] attribute [instance] Finset.hasSups
open FinsetFamily
variable {s t} {a b c : α}
@[simp]
theorem mem_sups : c ∈ s ⊻ t ↔ ∃ a ∈ s, ∃ b ∈ t, a ⊔ b = c := by simp [(· ⊻ ·)]
variable (s t)
@[simp, norm_cast]
theorem coe_sups : (↑(s ⊻ t) : Set α) = ↑s ⊻ ↑t :=
coe_image₂ _ _ _
theorem card_sups_le : #(s ⊻ t) ≤ #s * #t := card_image₂_le _ _ _
theorem card_sups_iff : #(s ⊻ t) = #s * #t ↔ (s ×ˢ t : Set (α × α)).InjOn fun x => x.1 ⊔ x.2 :=
card_image₂_iff
variable {s s₁ s₂ t t₁ t₂ u}
theorem sup_mem_sups : a ∈ s → b ∈ t → a ⊔ b ∈ s ⊻ t :=
mem_image₂_of_mem
theorem sups_subset : s₁ ⊆ s₂ → t₁ ⊆ t₂ → s₁ ⊻ t₁ ⊆ s₂ ⊻ t₂ :=
image₂_subset
theorem sups_subset_left : t₁ ⊆ t₂ → s ⊻ t₁ ⊆ s ⊻ t₂ :=
image₂_subset_left
theorem sups_subset_right : s₁ ⊆ s₂ → s₁ ⊻ t ⊆ s₂ ⊻ t :=
image₂_subset_right
lemma image_subset_sups_left : b ∈ t → s.image (· ⊔ b) ⊆ s ⊻ t := image_subset_image₂_left
lemma image_subset_sups_right : a ∈ s → t.image (a ⊔ ·) ⊆ s ⊻ t := image_subset_image₂_right
theorem forall_sups_iff {p : α → Prop} : (∀ c ∈ s ⊻ t, p c) ↔ ∀ a ∈ s, ∀ b ∈ t, p (a ⊔ b) :=
forall_mem_image₂
@[simp]
theorem sups_subset_iff : s ⊻ t ⊆ u ↔ ∀ a ∈ s, ∀ b ∈ t, a ⊔ b ∈ u :=
image₂_subset_iff
@[simp]
theorem sups_nonempty : (s ⊻ t).Nonempty ↔ s.Nonempty ∧ t.Nonempty :=
image₂_nonempty_iff
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected theorem Nonempty.sups : s.Nonempty → t.Nonempty → (s ⊻ t).Nonempty :=
Nonempty.image₂
theorem Nonempty.of_sups_left : (s ⊻ t).Nonempty → s.Nonempty :=
Nonempty.of_image₂_left
theorem Nonempty.of_sups_right : (s ⊻ t).Nonempty → t.Nonempty :=
Nonempty.of_image₂_right
@[simp]
theorem empty_sups : ∅ ⊻ t = ∅ :=
image₂_empty_left
@[simp]
theorem sups_empty : s ⊻ ∅ = ∅ :=
image₂_empty_right
@[simp]
theorem sups_eq_empty : s ⊻ t = ∅ ↔ s = ∅ ∨ t = ∅ :=
image₂_eq_empty_iff
@[simp] lemma singleton_sups : {a} ⊻ t = t.image (a ⊔ ·) := image₂_singleton_left
@[simp] lemma sups_singleton : s ⊻ {b} = s.image (· ⊔ b) := image₂_singleton_right
theorem singleton_sups_singleton : ({a} ⊻ {b} : Finset α) = {a ⊔ b} :=
image₂_singleton
theorem sups_union_left : (s₁ ∪ s₂) ⊻ t = s₁ ⊻ t ∪ s₂ ⊻ t :=
image₂_union_left
theorem sups_union_right : s ⊻ (t₁ ∪ t₂) = s ⊻ t₁ ∪ s ⊻ t₂ :=
image₂_union_right
theorem sups_inter_subset_left : (s₁ ∩ s₂) ⊻ t ⊆ s₁ ⊻ t ∩ s₂ ⊻ t :=
image₂_inter_subset_left
theorem sups_inter_subset_right : s ⊻ (t₁ ∩ t₂) ⊆ s ⊻ t₁ ∩ s ⊻ t₂ :=
image₂_inter_subset_right
theorem subset_sups {s t : Set α} :
↑u ⊆ s ⊻ t → ∃ s' t' : Finset α, ↑s' ⊆ s ∧ ↑t' ⊆ t ∧ u ⊆ s' ⊻ t' :=
subset_set_image₂
lemma image_sups (f : F) (s t : Finset α) : image f (s ⊻ t) = image f s ⊻ image f t :=
image_image₂_distrib <| map_sup f
lemma map_sups (f : F) (hf) (s t : Finset α) :
map ⟨f, hf⟩ (s ⊻ t) = map ⟨f, hf⟩ s ⊻ map ⟨f, hf⟩ t := by
simpa [map_eq_image] using image_sups f s t
lemma subset_sups_self : s ⊆ s ⊻ s := fun _a ha ↦ mem_sups.2 ⟨_, ha, _, ha, sup_idem _⟩
lemma sups_subset_self : s ⊻ s ⊆ s ↔ SupClosed (s : Set α) := sups_subset_iff
@[simp] lemma sups_eq_self : s ⊻ s = s ↔ SupClosed (s : Set α) := by simp [← coe_inj]
@[simp] lemma univ_sups_univ [Fintype α] : (univ : Finset α) ⊻ univ = univ := by simp
lemma filter_sups_le [DecidableLE α] (s t : Finset α) (a : α) :
{b ∈ s ⊻ t | b ≤ a} = {b ∈ s | b ≤ a} ⊻ {b ∈ t | b ≤ a} := by
simp only [← coe_inj, coe_filter, coe_sups, ← mem_coe, Set.sep_sups_le]
variable (s t u)
lemma biUnion_image_sup_left : s.biUnion (fun a ↦ t.image (a ⊔ ·)) = s ⊻ t := biUnion_image_left
lemma biUnion_image_sup_right : t.biUnion (fun b ↦ s.image (· ⊔ b)) = s ⊻ t := biUnion_image_right
theorem image_sup_product (s t : Finset α) : (s ×ˢ t).image (uncurry (· ⊔ ·)) = s ⊻ t :=
image_uncurry_product _ _ _
theorem sups_assoc : s ⊻ t ⊻ u = s ⊻ (t ⊻ u) := image₂_assoc sup_assoc
theorem sups_comm : s ⊻ t = t ⊻ s := image₂_comm sup_comm
theorem sups_left_comm : s ⊻ (t ⊻ u) = t ⊻ (s ⊻ u) :=
image₂_left_comm sup_left_comm
theorem sups_right_comm : s ⊻ t ⊻ u = s ⊻ u ⊻ t :=
image₂_right_comm sup_right_comm
theorem sups_sups_sups_comm : s ⊻ t ⊻ (u ⊻ v) = s ⊻ u ⊻ (t ⊻ v) :=
image₂_image₂_image₂_comm sup_sup_sup_comm
end Sups
section Infs
variable [DecidableEq α] [DecidableEq β]
variable [SemilatticeInf α] [SemilatticeInf β] [FunLike F α β] [InfHomClass F α β]
| variable (s s₁ s₂ t t₁ t₂ u v : Finset α)
| Mathlib/Data/Finset/Sups.lean | 193 | 193 |
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Algebra.Order.Group.Indicator
import Mathlib.Analysis.Normed.Affine.AddTorsor
import Mathlib.Analysis.NormedSpace.FunctionSeries
import Mathlib.Analysis.SpecificLimits.Basic
import Mathlib.LinearAlgebra.AffineSpace.Ordered
import Mathlib.Topology.ContinuousMap.Algebra
import Mathlib.Topology.GDelta.Basic
/-!
# Urysohn's lemma
In this file we prove Urysohn's lemma `exists_continuous_zero_one_of_isClosed`: for any two disjoint
closed sets `s` and `t` in a normal topological space `X` there exists a continuous function
`f : X → ℝ` such that
* `f` equals zero on `s`;
* `f` equals one on `t`;
* `0 ≤ f x ≤ 1` for all `x`.
We also give versions in a regular locally compact space where one assumes that `s` is compact
and `t` is closed, in `exists_continuous_zero_one_of_isCompact`
and `exists_continuous_one_zero_of_isCompact` (the latter providing additionally a function with
compact support).
We write a generic proof so that it applies both to normal spaces and to regular locally
compact spaces.
## Implementation notes
Most paper sources prove Urysohn's lemma using a family of open sets indexed by dyadic rational
numbers on `[0, 1]`. There are many technical difficulties with formalizing this proof (e.g., one
needs to formalize the "dyadic induction", then prove that the resulting family of open sets is
monotone). So, we formalize a slightly different proof.
Let `Urysohns.CU` be the type of pairs `(C, U)` of a closed set `C` and an open set `U` such that
`C ⊆ U`. Since `X` is a normal topological space, for each `c : CU` there exists an open set `u`
such that `c.C ⊆ u ∧ closure u ⊆ c.U`. We define `c.left` and `c.right` to be `(c.C, u)` and
`(closure u, c.U)`, respectively. Then we define a family of functions
`Urysohns.CU.approx (c : Urysohns.CU) (n : ℕ) : X → ℝ` by recursion on `n`:
* `c.approx 0` is the indicator of `c.Uᶜ`;
* `c.approx (n + 1) x = (c.left.approx n x + c.right.approx n x) / 2`.
For each `x` this is a monotone family of functions that are equal to zero on `c.C` and are equal to
one outside of `c.U`. We also have `c.approx n x ∈ [0, 1]` for all `c`, `n`, and `x`.
Let `Urysohns.CU.lim c` be the supremum (or equivalently, the limit) of `c.approx n`. Then
properties of `Urysohns.CU.approx` immediately imply that
* `c.lim x ∈ [0, 1]` for all `x`;
* `c.lim` equals zero on `c.C` and equals one outside of `c.U`;
* `c.lim x = (c.left.lim x + c.right.lim x) / 2`.
In order to prove that `c.lim` is continuous at `x`, we prove by induction on `n : ℕ` that for `y`
in a small neighborhood of `x` we have `|c.lim y - c.lim x| ≤ (3 / 4) ^ n`. Induction base follows
from `c.lim x ∈ [0, 1]`, `c.lim y ∈ [0, 1]`. For the induction step, consider two cases:
* `x ∈ c.left.U`; then for `y` in a small neighborhood of `x` we have `y ∈ c.left.U ⊆ c.right.C`
(hence `c.right.lim x = c.right.lim y = 0`) and `|c.left.lim y - c.left.lim x| ≤ (3 / 4) ^ n`.
Then
`|c.lim y - c.lim x| = |c.left.lim y - c.left.lim x| / 2 ≤ (3 / 4) ^ n / 2 < (3 / 4) ^ (n + 1)`.
* otherwise, `x ∉ c.left.right.C`; then for `y` in a small neighborhood of `x` we have
`y ∉ c.left.right.C ⊇ c.left.left.U` (hence `c.left.left.lim x = c.left.left.lim y = 1`),
`|c.left.right.lim y - c.left.right.lim x| ≤ (3 / 4) ^ n`, and
`|c.right.lim y - c.right.lim x| ≤ (3 / 4) ^ n`. Combining these inequalities, the triangle
inequality, and the recurrence formula for `c.lim`, we get
`|c.lim x - c.lim y| ≤ (3 / 4) ^ (n + 1)`.
The actual formalization uses `midpoint ℝ x y` instead of `(x + y) / 2` because we have more API
lemmas about `midpoint`.
## Tags
Urysohn's lemma, normal topological space, locally compact topological space
-/
variable {X : Type*} [TopologicalSpace X]
open Set Filter TopologicalSpace Topology Filter
open scoped Pointwise
namespace Urysohns
/--
An auxiliary type for the proof of Urysohn's lemma: a pair of a closed set `C` and its open
neighborhood `U`, together with the assumption that `C` and `U` satisfy the property `P C U`.
The latter assumption will make it possible to prove simultaneously both versions of Urysohn's
lemma, in normal spaces (with `P` always true) and in locally compact spaces
(with `P C U = IsCompact C`). We put also in the structure the assumption that, for any such pair,
one may find an intermediate pair in between satisfying `P`,
to avoid carrying it around in the argument.
-/
structure CU {X : Type*} [TopologicalSpace X] (P : Set X → Set X → Prop) where
/-- The inner set in the inductive construction towards Urysohn's lemma -/
protected C : Set X
/-- The outer set in the inductive construction towards Urysohn's lemma -/
protected U : Set X
/-- The proof that `C` and `U` satisfy the property `P C U` -/
protected P_C_U : P C U
protected closed_C : IsClosed C
protected open_U : IsOpen U
protected subset : C ⊆ U
/-- The proof that we can divide `CU` pairs in half -/
protected hP : ∀ {c u : Set X}, IsClosed c → P c u → IsOpen u → c ⊆ u →
∃ (v : Set X), IsOpen v ∧ c ⊆ v ∧ closure v ⊆ u ∧ P c v ∧ P (closure v) u
namespace CU
variable {P : Set X → Set X → Prop}
/-- By assumption, for each `c : CU P` there exists an open set `u`
such that `c.C ⊆ u` and `closure u ⊆ c.U`. `c.left` is the pair `(c.C, u)`. -/
@[simps C]
def left (c : CU P) : CU P where
C := c.C
U := (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose
closed_C := c.closed_C
P_C_U := (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose_spec.2.2.2.1
open_U := (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose_spec.1
subset := (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose_spec.2.1
hP := c.hP
/-- By assumption, for each `c : CU P` there exists an open set `u`
such that `c.C ⊆ u` and `closure u ⊆ c.U`. `c.right` is the pair `(closure u, c.U)`. -/
@[simps U]
def right (c : CU P) : CU P where
C := closure (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose
U := c.U
closed_C := isClosed_closure
P_C_U := (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose_spec.2.2.2.2
open_U := c.open_U
subset := (c.hP c.closed_C c.P_C_U c.open_U c.subset).choose_spec.2.2.1
hP := c.hP
theorem left_U_subset_right_C (c : CU P) : c.left.U ⊆ c.right.C :=
subset_closure
theorem left_U_subset (c : CU P) : c.left.U ⊆ c.U :=
Subset.trans c.left_U_subset_right_C c.right.subset
theorem subset_right_C (c : CU P) : c.C ⊆ c.right.C :=
Subset.trans c.left.subset c.left_U_subset_right_C
/-- `n`-th approximation to a continuous function `f : X → ℝ` such that `f = 0` on `c.C` and `f = 1`
outside of `c.U`. -/
noncomputable def approx : ℕ → CU P → X → ℝ
| 0, c, x => indicator c.Uᶜ 1 x
| n + 1, c, x => midpoint ℝ (approx n c.left x) (approx n c.right x)
theorem approx_of_mem_C (c : CU P) (n : ℕ) {x : X} (hx : x ∈ c.C) : c.approx n x = 0 := by
induction n generalizing c with
| zero => exact indicator_of_not_mem (fun (hU : x ∈ c.Uᶜ) => hU <| c.subset hx) _
| succ n ihn =>
simp only [approx]
rw [ihn, ihn, midpoint_self]
exacts [c.subset_right_C hx, hx]
theorem approx_of_nmem_U (c : CU P) (n : ℕ) {x : X} (hx : x ∉ c.U) : c.approx n x = 1 := by
induction n generalizing c with
| zero =>
rw [← mem_compl_iff] at hx
exact indicator_of_mem hx _
| succ n ihn =>
simp only [approx]
rw [ihn, ihn, midpoint_self]
exacts [hx, fun hU => hx <| c.left_U_subset hU]
theorem approx_nonneg (c : CU P) (n : ℕ) (x : X) : 0 ≤ c.approx n x := by
induction n generalizing c with
| zero => exact indicator_nonneg (fun _ _ => zero_le_one) _
| succ n ihn =>
simp only [approx, midpoint_eq_smul_add, invOf_eq_inv]
refine mul_nonneg (inv_nonneg.2 zero_le_two) (add_nonneg ?_ ?_) <;> apply ihn
theorem approx_le_one (c : CU P) (n : ℕ) (x : X) : c.approx n x ≤ 1 := by
induction n generalizing c with
| zero => exact indicator_apply_le' (fun _ => le_rfl) fun _ => zero_le_one
| succ n ihn =>
simp only [approx, midpoint_eq_smul_add, invOf_eq_inv, smul_eq_mul, ← div_eq_inv_mul]
have := add_le_add (ihn (left c)) (ihn (right c))
norm_num at this
exact Iff.mpr (div_le_one zero_lt_two) this
theorem bddAbove_range_approx (c : CU P) (x : X) : BddAbove (range fun n => c.approx n x) :=
⟨1, fun _ ⟨n, hn⟩ => hn ▸ c.approx_le_one n x⟩
theorem approx_le_approx_of_U_sub_C {c₁ c₂ : CU P} (h : c₁.U ⊆ c₂.C) (n₁ n₂ : ℕ) (x : X) :
c₂.approx n₂ x ≤ c₁.approx n₁ x := by
by_cases hx : x ∈ c₁.U
· calc
approx n₂ c₂ x = 0 := approx_of_mem_C _ _ (h hx)
_ ≤ approx n₁ c₁ x := approx_nonneg _ _ _
· calc
approx n₂ c₂ x ≤ 1 := approx_le_one _ _ _
_ = approx n₁ c₁ x := (approx_of_nmem_U _ _ hx).symm
theorem approx_mem_Icc_right_left (c : CU P) (n : ℕ) (x : X) :
c.approx n x ∈ Icc (c.right.approx n x) (c.left.approx n x) := by
induction n generalizing c with
| zero =>
exact ⟨le_rfl, indicator_le_indicator_of_subset (compl_subset_compl.2 c.left_U_subset)
(fun _ => zero_le_one) _⟩
| succ n ihn =>
simp only [approx, mem_Icc]
refine ⟨midpoint_le_midpoint ?_ (ihn _).1, midpoint_le_midpoint (ihn _).2 ?_⟩ <;>
apply approx_le_approx_of_U_sub_C
exacts [subset_closure, subset_closure]
theorem approx_le_succ (c : CU P) (n : ℕ) (x : X) : c.approx n x ≤ c.approx (n + 1) x := by
induction n generalizing c with
| zero =>
simp only [approx, right_U, right_le_midpoint]
exact (approx_mem_Icc_right_left c 0 x).2
| succ n ihn =>
rw [approx, approx]
exact midpoint_le_midpoint (ihn _) (ihn _)
theorem approx_mono (c : CU P) (x : X) : Monotone fun n => c.approx n x :=
monotone_nat_of_le_succ fun n => c.approx_le_succ n x
/-- A continuous function `f : X → ℝ` such that
* `0 ≤ f x ≤ 1` for all `x`;
* `f` equals zero on `c.C` and equals one outside of `c.U`;
-/
protected noncomputable def lim (c : CU P) (x : X) : ℝ :=
⨆ n, c.approx n x
theorem tendsto_approx_atTop (c : CU P) (x : X) :
Tendsto (fun n => c.approx n x) atTop (𝓝 <| c.lim x) :=
tendsto_atTop_ciSup (c.approx_mono x) ⟨1, fun _ ⟨_, hn⟩ => hn ▸ c.approx_le_one _ _⟩
theorem lim_of_mem_C (c : CU P) (x : X) (h : x ∈ c.C) : c.lim x = 0 := by
simp only [CU.lim, approx_of_mem_C, h, ciSup_const]
theorem disjoint_C_support_lim (c : CU P) : Disjoint c.C (Function.support c.lim) :=
Function.disjoint_support_iff.mpr (fun x hx => lim_of_mem_C c x hx)
theorem lim_of_nmem_U (c : CU P) (x : X) (h : x ∉ c.U) : c.lim x = 1 := by
simp only [CU.lim, approx_of_nmem_U c _ h, ciSup_const]
theorem lim_eq_midpoint (c : CU P) (x : X) :
c.lim x = midpoint ℝ (c.left.lim x) (c.right.lim x) := by
refine tendsto_nhds_unique (c.tendsto_approx_atTop x) ((tendsto_add_atTop_iff_nat 1).1 ?_)
simp only [approx]
exact (c.left.tendsto_approx_atTop x).midpoint (c.right.tendsto_approx_atTop x)
theorem approx_le_lim (c : CU P) (x : X) (n : ℕ) : c.approx n x ≤ c.lim x :=
le_ciSup (c.bddAbove_range_approx x) _
theorem lim_nonneg (c : CU P) (x : X) : 0 ≤ c.lim x :=
(c.approx_nonneg 0 x).trans (c.approx_le_lim x 0)
theorem lim_le_one (c : CU P) (x : X) : c.lim x ≤ 1 :=
ciSup_le fun _ => c.approx_le_one _ _
theorem lim_mem_Icc (c : CU P) (x : X) : c.lim x ∈ Icc (0 : ℝ) 1 :=
⟨c.lim_nonneg x, c.lim_le_one x⟩
/-- Continuity of `Urysohns.CU.lim`. See module docstring for a sketch of the proofs. -/
theorem continuous_lim (c : CU P) : Continuous c.lim := by
obtain ⟨h0, h1234, h1⟩ : 0 < (2⁻¹ : ℝ) ∧ (2⁻¹ : ℝ) < 3 / 4 ∧ (3 / 4 : ℝ) < 1 := by norm_num
refine
continuous_iff_continuousAt.2 fun x =>
(Metric.nhds_basis_closedBall_pow (h0.trans h1234) h1).tendsto_right_iff.2 fun n _ => ?_
simp only [Metric.mem_closedBall]
induction n generalizing c with
| zero =>
filter_upwards with y
rw [pow_zero]
| exact Real.dist_le_of_mem_Icc_01 (c.lim_mem_Icc _) (c.lim_mem_Icc _)
| succ n ihn =>
by_cases hxl : x ∈ c.left.U
· filter_upwards [IsOpen.mem_nhds c.left.open_U hxl, ihn c.left] with _ hyl hyd
rw [pow_succ', c.lim_eq_midpoint, c.lim_eq_midpoint,
c.right.lim_of_mem_C _ (c.left_U_subset_right_C hyl),
c.right.lim_of_mem_C _ (c.left_U_subset_right_C hxl)]
refine (dist_midpoint_midpoint_le _ _ _ _).trans ?_
rw [dist_self, add_zero, div_eq_inv_mul]
gcongr
· replace hxl : x ∈ c.left.right.Cᶜ :=
compl_subset_compl.2 c.left.right.subset hxl
filter_upwards [IsOpen.mem_nhds (isOpen_compl_iff.2 c.left.right.closed_C) hxl,
ihn c.left.right, ihn c.right] with y hyl hydl hydr
replace hxl : x ∉ c.left.left.U :=
compl_subset_compl.2 c.left.left_U_subset_right_C hxl
replace hyl : y ∉ c.left.left.U :=
compl_subset_compl.2 c.left.left_U_subset_right_C hyl
simp only [pow_succ, c.lim_eq_midpoint, c.left.lim_eq_midpoint,
c.left.left.lim_of_nmem_U _ hxl, c.left.left.lim_of_nmem_U _ hyl]
refine (dist_midpoint_midpoint_le _ _ _ _).trans ?_
refine (div_le_div_of_nonneg_right (add_le_add_right (dist_midpoint_midpoint_le _ _ _ _) _)
zero_le_two).trans ?_
rw [dist_self, zero_add]
set r := (3 / 4 : ℝ) ^ n
calc _ ≤ (r / 2 + r) / 2 := by gcongr
_ = _ := by field_simp; ring
end CU
end Urysohns
/-- Urysohn's lemma: if `s` and `t` are two disjoint closed sets in a normal topological space `X`,
then there exists a continuous function `f : X → ℝ` such that
| Mathlib/Topology/UrysohnsLemma.lean | 278 | 312 |
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Mario Carneiro, Johannes Hölzl
-/
import Mathlib.Algebra.Order.Monoid.Unbundled.Basic
/-!
# Lemmas about `min` and `max` in an ordered monoid.
-/
open Function
variable {α β : Type*}
/-! Some lemmas about types that have an ordering and a binary operation, with no
rules relating them. -/
section CommSemigroup
variable [LinearOrder α] [CommSemigroup β]
@[to_additive]
lemma fn_min_mul_fn_max (f : α → β) (a b : α) : f (min a b) * f (max a b) = f a * f b := by
| obtain h | h := le_total a b <;> simp [h, mul_comm]
@[to_additive]
| Mathlib/Algebra/Order/Monoid/Unbundled/MinMax.lean | 25 | 27 |
/-
Copyright (c) 2022 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Yury Kudryashov, Kevin H. Wilson, Heather Macbeth
-/
import Mathlib.Order.Filter.Tendsto
/-!
# Product and coproduct filters
In this file we define `Filter.prod f g` (notation: `f ×ˢ g`) and `Filter.coprod f g`. The product
of two filters is the largest filter `l` such that `Filter.Tendsto Prod.fst l f` and
`Filter.Tendsto Prod.snd l g`.
## Implementation details
The product filter cannot be defined using the monad structure on filters. For example:
```lean
F := do {x ← seq, y ← top, return (x, y)}
G := do {y ← top, x ← seq, return (x, y)}
```
hence:
```lean
s ∈ F ↔ ∃ n, [n..∞] × univ ⊆ s
s ∈ G ↔ ∀ i:ℕ, ∃ n, [n..∞] × {i} ⊆ s
```
Now `⋃ i, [i..∞] × {i}` is in `G` but not in `F`.
As product filter we want to have `F` as result.
## Notations
* `f ×ˢ g` : `Filter.prod f g`, localized in `Filter`.
-/
open Set
open Filter
namespace Filter
variable {α β γ δ : Type*} {ι : Sort*}
section Prod
variable {s : Set α} {t : Set β} {f : Filter α} {g : Filter β}
theorem prod_mem_prod (hs : s ∈ f) (ht : t ∈ g) : s ×ˢ t ∈ f ×ˢ g :=
inter_mem_inf (preimage_mem_comap hs) (preimage_mem_comap ht)
theorem mem_prod_iff {s : Set (α × β)} {f : Filter α} {g : Filter β} :
s ∈ f ×ˢ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ×ˢ t₂ ⊆ s := by
constructor
· rintro ⟨t₁, ⟨s₁, hs₁, hts₁⟩, t₂, ⟨s₂, hs₂, hts₂⟩, rfl⟩
exact ⟨s₁, hs₁, s₂, hs₂, fun p ⟨h, h'⟩ => ⟨hts₁ h, hts₂ h'⟩⟩
· rintro ⟨t₁, ht₁, t₂, ht₂, h⟩
exact mem_inf_of_inter (preimage_mem_comap ht₁) (preimage_mem_comap ht₂) h
@[simp]
theorem compl_diagonal_mem_prod {l₁ l₂ : Filter α} : (diagonal α)ᶜ ∈ l₁ ×ˢ l₂ ↔ Disjoint l₁ l₂ := by
simp only [mem_prod_iff, Filter.disjoint_iff, prod_subset_compl_diagonal_iff_disjoint]
@[simp]
theorem prod_mem_prod_iff [f.NeBot] [g.NeBot] : s ×ˢ t ∈ f ×ˢ g ↔ s ∈ f ∧ t ∈ g :=
⟨fun h =>
let ⟨_s', hs', _t', ht', H⟩ := mem_prod_iff.1 h
(prod_subset_prod_iff.1 H).elim
(fun ⟨hs's, ht't⟩ => ⟨mem_of_superset hs' hs's, mem_of_superset ht' ht't⟩) fun h =>
h.elim (fun hs'e => absurd hs'e (nonempty_of_mem hs').ne_empty) fun ht'e =>
absurd ht'e (nonempty_of_mem ht').ne_empty,
fun h => prod_mem_prod h.1 h.2⟩
theorem mem_prod_principal {s : Set (α × β)} :
s ∈ f ×ˢ 𝓟 t ↔ { a | ∀ b ∈ t, (a, b) ∈ s } ∈ f := by
rw [← @exists_mem_subset_iff _ f, mem_prod_iff]
refine exists_congr fun u => Iff.rfl.and ⟨?_, fun h => ⟨t, mem_principal_self t, ?_⟩⟩
· rintro ⟨v, v_in, hv⟩ a a_in b b_in
exact hv (mk_mem_prod a_in <| v_in b_in)
· rintro ⟨x, y⟩ ⟨hx, hy⟩
exact h hx y hy
theorem mem_prod_top {s : Set (α × β)} :
s ∈ f ×ˢ (⊤ : Filter β) ↔ { a | ∀ b, (a, b) ∈ s } ∈ f := by
rw [← principal_univ, mem_prod_principal]
simp only [mem_univ, forall_true_left]
theorem eventually_prod_principal_iff {p : α × β → Prop} {s : Set β} :
(∀ᶠ x : α × β in f ×ˢ 𝓟 s, p x) ↔ ∀ᶠ x : α in f, ∀ y : β, y ∈ s → p (x, y) := by
rw [eventually_iff, eventually_iff, mem_prod_principal]
simp only [mem_setOf_eq]
theorem comap_prod (f : α → β × γ) (b : Filter β) (c : Filter γ) :
comap f (b ×ˢ c) = comap (Prod.fst ∘ f) b ⊓ comap (Prod.snd ∘ f) c := by
rw [prod_eq_inf, comap_inf, Filter.comap_comap, Filter.comap_comap]
theorem comap_prodMap_prod (f : α → β) (g : γ → δ) (lb : Filter β) (ld : Filter δ) :
comap (Prod.map f g) (lb ×ˢ ld) = comap f lb ×ˢ comap g ld := by
simp [prod_eq_inf, comap_comap, Function.comp_def]
theorem prod_top : f ×ˢ (⊤ : Filter β) = f.comap Prod.fst := by
rw [prod_eq_inf, comap_top, inf_top_eq]
theorem top_prod : (⊤ : Filter α) ×ˢ g = g.comap Prod.snd := by
rw [prod_eq_inf, comap_top, top_inf_eq]
theorem sup_prod (f₁ f₂ : Filter α) (g : Filter β) : (f₁ ⊔ f₂) ×ˢ g = (f₁ ×ˢ g) ⊔ (f₂ ×ˢ g) := by
simp only [prod_eq_inf, comap_sup, inf_sup_right]
theorem prod_sup (f : Filter α) (g₁ g₂ : Filter β) : f ×ˢ (g₁ ⊔ g₂) = (f ×ˢ g₁) ⊔ (f ×ˢ g₂) := by
simp only [prod_eq_inf, comap_sup, inf_sup_left]
theorem eventually_prod_iff {p : α × β → Prop} :
(∀ᶠ x in f ×ˢ g, p x) ↔
∃ pa : α → Prop, (∀ᶠ x in f, pa x) ∧ ∃ pb : β → Prop, (∀ᶠ y in g, pb y) ∧
∀ {x}, pa x → ∀ {y}, pb y → p (x, y) := by
simpa only [Set.prod_subset_iff] using @mem_prod_iff α β p f g
theorem tendsto_fst : Tendsto Prod.fst (f ×ˢ g) f :=
tendsto_inf_left tendsto_comap
theorem tendsto_snd : Tendsto Prod.snd (f ×ˢ g) g :=
tendsto_inf_right tendsto_comap
/-- If a function tends to a product `g ×ˢ h` of filters, then its first component tends to
`g`. See also `Filter.Tendsto.fst_nhds` for the special case of converging to a point in a
product of two topological spaces. -/
theorem Tendsto.fst {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) :
Tendsto (fun a ↦ (m a).1) f g :=
tendsto_fst.comp H
/-- If a function tends to a product `g ×ˢ h` of filters, then its second component tends to
`h`. See also `Filter.Tendsto.snd_nhds` for the special case of converging to a point in a
product of two topological spaces. -/
theorem Tendsto.snd {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) :
Tendsto (fun a ↦ (m a).2) f h :=
tendsto_snd.comp H
theorem Tendsto.prodMk {h : Filter γ} {m₁ : α → β} {m₂ : α → γ}
(h₁ : Tendsto m₁ f g) (h₂ : Tendsto m₂ f h) : Tendsto (fun x => (m₁ x, m₂ x)) f (g ×ˢ h) :=
tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩
@[deprecated (since := "2025-03-10")]
alias Tendsto.prod_mk := Tendsto.prodMk
theorem tendsto_prod_swap : Tendsto (Prod.swap : α × β → β × α) (f ×ˢ g) (g ×ˢ f) :=
tendsto_snd.prodMk tendsto_fst
theorem Eventually.prod_inl {la : Filter α} {p : α → Prop} (h : ∀ᶠ x in la, p x) (lb : Filter β) :
∀ᶠ x in la ×ˢ lb, p (x : α × β).1 :=
tendsto_fst.eventually h
theorem Eventually.prod_inr {lb : Filter β} {p : β → Prop} (h : ∀ᶠ x in lb, p x) (la : Filter α) :
∀ᶠ x in la ×ˢ lb, p (x : α × β).2 :=
tendsto_snd.eventually h
theorem Eventually.prod_mk {la : Filter α} {pa : α → Prop} (ha : ∀ᶠ x in la, pa x) {lb : Filter β}
{pb : β → Prop} (hb : ∀ᶠ y in lb, pb y) : ∀ᶠ p in la ×ˢ lb, pa (p : α × β).1 ∧ pb p.2 :=
(ha.prod_inl lb).and (hb.prod_inr la)
theorem EventuallyEq.prodMap {δ} {la : Filter α} {fa ga : α → γ} (ha : fa =ᶠ[la] ga)
{lb : Filter β} {fb gb : β → δ} (hb : fb =ᶠ[lb] gb) :
Prod.map fa fb =ᶠ[la ×ˢ lb] Prod.map ga gb :=
(Eventually.prod_mk ha hb).mono fun _ h => Prod.ext h.1 h.2
@[deprecated (since := "2025-03-10")]
alias EventuallyEq.prod_map := EventuallyEq.prodMap
theorem EventuallyLE.prodMap {δ} [LE γ] [LE δ] {la : Filter α} {fa ga : α → γ} (ha : fa ≤ᶠ[la] ga)
{lb : Filter β} {fb gb : β → δ} (hb : fb ≤ᶠ[lb] gb) :
Prod.map fa fb ≤ᶠ[la ×ˢ lb] Prod.map ga gb :=
Eventually.prod_mk ha hb
@[deprecated (since := "2025-03-10")]
alias EventuallyLE.prod_map := EventuallyLE.prodMap
theorem Eventually.curry {la : Filter α} {lb : Filter β} {p : α × β → Prop}
(h : ∀ᶠ x in la ×ˢ lb, p x) : ∀ᶠ x in la, ∀ᶠ y in lb, p (x, y) := by
rcases eventually_prod_iff.1 h with ⟨pa, ha, pb, hb, h⟩
exact ha.mono fun a ha => hb.mono fun b hb => h ha hb
protected lemma Frequently.uncurry {la : Filter α} {lb : Filter β} {p : α → β → Prop}
(h : ∃ᶠ x in la, ∃ᶠ y in lb, p x y) : ∃ᶠ xy in la ×ˢ lb, p xy.1 xy.2 :=
mt (fun h ↦ by simpa only [not_frequently] using h.curry) h
lemma Frequently.of_curry {la : Filter α} {lb : Filter β} {p : α × β → Prop}
(h : ∃ᶠ x in la, ∃ᶠ y in lb, p (x, y)) : ∃ᶠ xy in la ×ˢ lb, p xy :=
h.uncurry
/-- A fact that is eventually true about all pairs `l ×ˢ l` is eventually true about
all diagonal pairs `(i, i)` -/
theorem Eventually.diag_of_prod {p : α × α → Prop} (h : ∀ᶠ i in f ×ˢ f, p i) :
∀ᶠ i in f, p (i, i) := by
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
apply (ht.and hs).mono fun x hx => hst hx.1 hx.2
theorem Eventually.diag_of_prod_left {f : Filter α} {g : Filter γ} {p : (α × α) × γ → Prop} :
(∀ᶠ x in (f ×ˢ f) ×ˢ g, p x) → ∀ᶠ x : α × γ in f ×ˢ g, p ((x.1, x.1), x.2) := by
intro h
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
exact (ht.diag_of_prod.prod_mk hs).mono fun x hx => by simp only [hst hx.1 hx.2]
theorem Eventually.diag_of_prod_right {f : Filter α} {g : Filter γ} {p : α × γ × γ → Prop} :
(∀ᶠ x in f ×ˢ (g ×ˢ g), p x) → ∀ᶠ x : α × γ in f ×ˢ g, p (x.1, x.2, x.2) := by
intro h
obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h
exact (ht.prod_mk hs.diag_of_prod).mono fun x hx => by simp only [hst hx.1 hx.2]
theorem tendsto_diag : Tendsto (fun i => (i, i)) f (f ×ˢ f) :=
tendsto_iff_eventually.mpr fun _ hpr => hpr.diag_of_prod
theorem prod_iInf_left [Nonempty ι] {f : ι → Filter α} {g : Filter β} :
(⨅ i, f i) ×ˢ g = ⨅ i, f i ×ˢ g := by
simp only [prod_eq_inf, comap_iInf, iInf_inf]
theorem prod_iInf_right [Nonempty ι] {f : Filter α} {g : ι → Filter β} :
(f ×ˢ ⨅ i, g i) = ⨅ i, f ×ˢ g i := by
simp only [prod_eq_inf, comap_iInf, inf_iInf]
@[mono, gcongr]
theorem prod_mono {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) :
f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ :=
inf_le_inf (comap_mono hf) (comap_mono hg)
@[gcongr]
theorem prod_mono_left (g : Filter β) {f₁ f₂ : Filter α} (hf : f₁ ≤ f₂) : f₁ ×ˢ g ≤ f₂ ×ˢ g :=
Filter.prod_mono hf rfl.le
@[gcongr]
theorem prod_mono_right (f : Filter α) {g₁ g₂ : Filter β} (hf : g₁ ≤ g₂) : f ×ˢ g₁ ≤ f ×ˢ g₂ :=
Filter.prod_mono rfl.le hf
theorem prod_comap_comap_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x}
{f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : β₁ → α₁} {m₂ : β₂ → α₂} :
comap m₁ f₁ ×ˢ comap m₂ f₂ = comap (fun p : β₁ × β₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) := by
simp only [prod_eq_inf, comap_comap, comap_inf, Function.comp_def]
theorem prod_comm' : f ×ˢ g = comap Prod.swap (g ×ˢ f) := by
simp only [prod_eq_inf, comap_comap, Function.comp_def, inf_comm, Prod.swap, comap_inf]
theorem prod_comm : f ×ˢ g = map (fun p : β × α => (p.2, p.1)) (g ×ˢ f) := by
rw [prod_comm', ← map_swap_eq_comap_swap]
rfl
theorem mem_prod_iff_left {s : Set (α × β)} :
s ∈ f ×ˢ g ↔ ∃ t ∈ f, ∀ᶠ y in g, ∀ x ∈ t, (x, y) ∈ s := by
simp only [mem_prod_iff, prod_subset_iff]
refine exists_congr fun _ => Iff.rfl.and <| Iff.trans ?_ exists_mem_subset_iff
exact exists_congr fun _ => Iff.rfl.and forall₂_swap
theorem mem_prod_iff_right {s : Set (α × β)} :
s ∈ f ×ˢ g ↔ ∃ t ∈ g, ∀ᶠ x in f, ∀ y ∈ t, (x, y) ∈ s := by
rw [prod_comm, mem_map, mem_prod_iff_left]; rfl
@[simp]
theorem map_fst_prod (f : Filter α) (g : Filter β) [NeBot g] : map Prod.fst (f ×ˢ g) = f := by
ext s
simp only [mem_map, mem_prod_iff_left, mem_preimage, eventually_const, ← subset_def,
exists_mem_subset_iff]
@[simp]
theorem map_snd_prod (f : Filter α) (g : Filter β) [NeBot f] : map Prod.snd (f ×ˢ g) = g := by
rw [prod_comm, map_map]; apply map_fst_prod
@[simp]
theorem prod_le_prod {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} [NeBot f₁] [NeBot g₁] :
f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ ↔ f₁ ≤ f₂ ∧ g₁ ≤ g₂ :=
⟨fun h =>
⟨map_fst_prod f₁ g₁ ▸ tendsto_fst.mono_left h, map_snd_prod f₁ g₁ ▸ tendsto_snd.mono_left h⟩,
fun h => prod_mono h.1 h.2⟩
@[simp]
theorem prod_inj {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} [NeBot f₁] [NeBot g₁] :
f₁ ×ˢ g₁ = f₂ ×ˢ g₂ ↔ f₁ = f₂ ∧ g₁ = g₂ := by
refine ⟨fun h => ?_, fun h => h.1 ▸ h.2 ▸ rfl⟩
have hle : f₁ ≤ f₂ ∧ g₁ ≤ g₂ := prod_le_prod.1 h.le
haveI := neBot_of_le hle.1; haveI := neBot_of_le hle.2
exact ⟨hle.1.antisymm <| (prod_le_prod.1 h.ge).1, hle.2.antisymm <| (prod_le_prod.1 h.ge).2⟩
theorem eventually_swap_iff {p : α × β → Prop} :
(∀ᶠ x : α × β in f ×ˢ g, p x) ↔ ∀ᶠ y : β × α in g ×ˢ f, p y.swap := by
rw [prod_comm]; rfl
theorem prod_assoc (f : Filter α) (g : Filter β) (h : Filter γ) :
map (Equiv.prodAssoc α β γ) ((f ×ˢ g) ×ˢ h) = f ×ˢ (g ×ˢ h) := by
simp_rw [← comap_equiv_symm, prod_eq_inf, comap_inf, comap_comap, inf_assoc,
Function.comp_def, Equiv.prodAssoc_symm_apply]
theorem prod_assoc_symm (f : Filter α) (g : Filter β) (h : Filter γ) :
map (Equiv.prodAssoc α β γ).symm (f ×ˢ (g ×ˢ h)) = (f ×ˢ g) ×ˢ h := by
simp_rw [map_equiv_symm, prod_eq_inf, comap_inf, comap_comap, inf_assoc,
Function.comp_def, Equiv.prodAssoc_apply]
theorem tendsto_prodAssoc {h : Filter γ} :
Tendsto (Equiv.prodAssoc α β γ) ((f ×ˢ g) ×ˢ h) (f ×ˢ (g ×ˢ h)) :=
(prod_assoc f g h).le
theorem tendsto_prodAssoc_symm {h : Filter γ} :
Tendsto (Equiv.prodAssoc α β γ).symm (f ×ˢ (g ×ˢ h)) ((f ×ˢ g) ×ˢ h) :=
(prod_assoc_symm f g h).le
/-- A useful lemma when dealing with uniformities. -/
theorem map_swap4_prod {h : Filter γ} {k : Filter δ} :
map (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) ((f ×ˢ g) ×ˢ (h ×ˢ k)) =
(f ×ˢ h) ×ˢ (g ×ˢ k) := by
simp_rw [map_swap4_eq_comap, prod_eq_inf, comap_inf, comap_comap]; ac_rfl
theorem tendsto_swap4_prod {h : Filter γ} {k : Filter δ} :
Tendsto (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) ((f ×ˢ g) ×ˢ (h ×ˢ k))
((f ×ˢ h) ×ˢ (g ×ˢ k)) :=
map_swap4_prod.le
theorem prod_map_map_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x}
{f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : α₁ → β₁} {m₂ : α₂ → β₂} :
map m₁ f₁ ×ˢ map m₂ f₂ = map (fun p : α₁ × α₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) :=
le_antisymm
(fun s hs =>
let ⟨s₁, hs₁, s₂, hs₂, h⟩ := mem_prod_iff.mp hs
mem_of_superset (prod_mem_prod (image_mem_map hs₁) (image_mem_map hs₂)) <|
by rwa [prod_image_image_eq, image_subset_iff])
((tendsto_map.comp tendsto_fst).prodMk (tendsto_map.comp tendsto_snd))
theorem prod_map_map_eq' {α₁ : Type*} {α₂ : Type*} {β₁ : Type*} {β₂ : Type*} (f : α₁ → α₂)
(g : β₁ → β₂) (F : Filter α₁) (G : Filter β₁) :
map f F ×ˢ map g G = map (Prod.map f g) (F ×ˢ G) :=
prod_map_map_eq
theorem prod_map_left (f : α → β) (F : Filter α) (G : Filter γ) :
map f F ×ˢ G = map (Prod.map f id) (F ×ˢ G) := by
rw [← prod_map_map_eq', map_id]
theorem prod_map_right (f : β → γ) (F : Filter α) (G : Filter β) :
F ×ˢ map f G = map (Prod.map id f) (F ×ˢ G) := by
rw [← prod_map_map_eq', map_id]
theorem le_prod_map_fst_snd {f : Filter (α × β)} : f ≤ map Prod.fst f ×ˢ map Prod.snd f :=
le_inf le_comap_map le_comap_map
theorem Tendsto.prodMap {δ : Type*} {f : α → γ} {g : β → δ} {a : Filter α} {b : Filter β}
{c : Filter γ} {d : Filter δ} (hf : Tendsto f a c) (hg : Tendsto g b d) :
Tendsto (Prod.map f g) (a ×ˢ b) (c ×ˢ d) := by
rw [Tendsto, Prod.map_def, ← prod_map_map_eq]
exact Filter.prod_mono hf hg
@[deprecated (since := "2025-03-10")]
alias Tendsto.prod_map := Tendsto.prodMap
protected theorem map_prod (m : α × β → γ) (f : Filter α) (g : Filter β) :
map m (f ×ˢ g) = (f.map fun a b => m (a, b)).seq g := by
simp only [Filter.ext_iff, mem_map, mem_prod_iff, mem_map_seq_iff, exists_and_left]
intro s
constructor
· exact fun ⟨t, ht, s, hs, h⟩ => ⟨s, hs, t, ht, fun x hx y hy => @h ⟨x, y⟩ ⟨hx, hy⟩⟩
· exact fun ⟨s, hs, t, ht, h⟩ => ⟨t, ht, s, hs, fun ⟨x, y⟩ ⟨hx, hy⟩ => h x hx y hy⟩
theorem prod_eq : f ×ˢ g = (f.map Prod.mk).seq g := f.map_prod id g
theorem prod_inf_prod {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} :
(f₁ ×ˢ g₁) ⊓ (f₂ ×ˢ g₂) = (f₁ ⊓ f₂) ×ˢ (g₁ ⊓ g₂) := by
simp only [prod_eq_inf, comap_inf, inf_comm, inf_assoc, inf_left_comm]
theorem inf_prod {f₁ f₂ : Filter α} : (f₁ ⊓ f₂) ×ˢ g = (f₁ ×ˢ g) ⊓ (f₂ ×ˢ g) := by
rw [prod_inf_prod, inf_idem]
theorem prod_inf {g₁ g₂ : Filter β} : f ×ˢ (g₁ ⊓ g₂) = (f ×ˢ g₁) ⊓ (f ×ˢ g₂) := by
rw [prod_inf_prod, inf_idem]
@[simp]
theorem prod_principal_principal {s : Set α} {t : Set β} : 𝓟 s ×ˢ 𝓟 t = 𝓟 (s ×ˢ t) := by
simp only [prod_eq_inf, comap_principal, principal_eq_iff_eq, comap_principal, inf_principal]; rfl
@[simp]
theorem pure_prod {a : α} {f : Filter β} : pure a ×ˢ f = map (Prod.mk a) f := by
rw [prod_eq, map_pure, pure_seq_eq_map]
theorem map_pure_prod (f : α → β → γ) (a : α) (B : Filter β) :
map (Function.uncurry f) (pure a ×ˢ B) = map (f a) B := by
rw [Filter.pure_prod]; rfl
@[simp]
theorem prod_pure {b : β} : f ×ˢ pure b = map (fun a => (a, b)) f := by
rw [prod_eq, seq_pure, map_map]; rfl
theorem prod_pure_pure {a : α} {b : β} :
(pure a : Filter α) ×ˢ (pure b : Filter β) = pure (a, b) := by simp
@[simp]
theorem prod_eq_bot : f ×ˢ g = ⊥ ↔ f = ⊥ ∨ g = ⊥ := by
simp_rw [← empty_mem_iff_bot, mem_prod_iff, subset_empty_iff, prod_eq_empty_iff, ← exists_prop,
Subtype.exists', exists_or, exists_const, Subtype.exists, exists_prop, exists_eq_right]
@[simp] theorem prod_bot : f ×ˢ (⊥ : Filter β) = ⊥ := prod_eq_bot.2 <| Or.inr rfl
@[simp] theorem bot_prod : (⊥ : Filter α) ×ˢ g = ⊥ := prod_eq_bot.2 <| Or.inl rfl
theorem prod_neBot : NeBot (f ×ˢ g) ↔ NeBot f ∧ NeBot g := by
simp only [neBot_iff, Ne, prod_eq_bot, not_or]
protected theorem NeBot.prod (hf : NeBot f) (hg : NeBot g) : NeBot (f ×ˢ g) := prod_neBot.2 ⟨hf, hg⟩
instance prod.instNeBot [hf : NeBot f] [hg : NeBot g] : NeBot (f ×ˢ g) := hf.prod hg
@[simp]
lemma disjoint_prod {f' : Filter α} {g' : Filter β} :
Disjoint (f ×ˢ g) (f' ×ˢ g') ↔ Disjoint f f' ∨ Disjoint g g' := by
simp only [disjoint_iff, prod_inf_prod, prod_eq_bot]
/-- `p ∧ q` occurs frequently along the product of two filters
iff both `p` and `q` occur frequently along the corresponding filters. -/
theorem frequently_prod_and {p : α → Prop} {q : β → Prop} :
(∃ᶠ x in f ×ˢ g, p x.1 ∧ q x.2) ↔ (∃ᶠ a in f, p a) ∧ ∃ᶠ b in g, q b := by
simp only [frequently_iff_neBot, ← prod_neBot, ← prod_inf_prod, prod_principal_principal]
rfl
theorem tendsto_prod_iff {f : α × β → γ} {x : Filter α} {y : Filter β} {z : Filter γ} :
| Tendsto f (x ×ˢ y) z ↔ ∀ W ∈ z, ∃ U ∈ x, ∃ V ∈ y, ∀ x y, x ∈ U → y ∈ V → f (x, y) ∈ W := by
simp only [tendsto_def, mem_prod_iff, prod_sub_preimage_iff, exists_prop]
| Mathlib/Order/Filter/Prod.lean | 416 | 418 |
/-
Copyright (c) 2020 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison
-/
import Mathlib.Algebra.BigOperators.Group.Finset.Piecewise
import Mathlib.Algebra.Group.Ext
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.BinaryProducts
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Biproducts
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Products
import Mathlib.CategoryTheory.Preadditive.Basic
import Mathlib.Tactic.Abel
/-!
# Basic facts about biproducts in preadditive categories.
In (or between) preadditive categories,
* Any biproduct satisfies the equality
`total : ∑ j : J, biproduct.π f j ≫ biproduct.ι f j = 𝟙 (⨁ f)`,
or, in the binary case, `total : fst ≫ inl + snd ≫ inr = 𝟙 X`.
* Any (binary) `product` or (binary) `coproduct` is a (binary) `biproduct`.
* In any category (with zero morphisms), if `biprod.map f g` is an isomorphism,
then both `f` and `g` are isomorphisms.
* If `f` is a morphism `X₁ ⊞ X₂ ⟶ Y₁ ⊞ Y₂` whose `X₁ ⟶ Y₁` entry is an isomorphism,
then we can construct isomorphisms `L : X₁ ⊞ X₂ ≅ X₁ ⊞ X₂` and `R : Y₁ ⊞ Y₂ ≅ Y₁ ⊞ Y₂`
so that `L.hom ≫ g ≫ R.hom` is diagonal (with `X₁ ⟶ Y₁` component still `f`),
via Gaussian elimination.
* As a corollary of the previous two facts,
if we have an isomorphism `X₁ ⊞ X₂ ≅ Y₁ ⊞ Y₂` whose `X₁ ⟶ Y₁` entry is an isomorphism,
we can construct an isomorphism `X₂ ≅ Y₂`.
* If `f : W ⊞ X ⟶ Y ⊞ Z` is an isomorphism, either `𝟙 W = 0`,
or at least one of the component maps `W ⟶ Y` and `W ⟶ Z` is nonzero.
* If `f : ⨁ S ⟶ ⨁ T` is an isomorphism,
then every column (corresponding to a nonzero summand in the domain)
has some nonzero matrix entry.
* A functor preserves a biproduct if and only if it preserves
the corresponding product if and only if it preserves the corresponding coproduct.
There are connections between this material and the special case of the category whose morphisms are
matrices over a ring, in particular the Schur complement (see
`Mathlib.LinearAlgebra.Matrix.SchurComplement`). In particular, the declarations
`CategoryTheory.Biprod.isoElim`, `CategoryTheory.Biprod.gaussian`
and `Matrix.invertibleOfFromBlocks₁₁Invertible` are all closely related.
-/
open CategoryTheory
open CategoryTheory.Preadditive
open CategoryTheory.Limits
open CategoryTheory.Functor
open CategoryTheory.Preadditive
universe v v' u u'
noncomputable section
namespace CategoryTheory
variable {C : Type u} [Category.{v} C] [Preadditive C]
namespace Limits
section Fintype
variable {J : Type} [Fintype J]
/-- In a preadditive category, we can construct a biproduct for `f : J → C` from
any bicone `b` for `f` satisfying `total : ∑ j : J, b.π j ≫ b.ι j = 𝟙 b.X`.
(That is, such a bicone is a limit cone and a colimit cocone.)
-/
def isBilimitOfTotal {f : J → C} (b : Bicone f) (total : ∑ j : J, b.π j ≫ b.ι j = 𝟙 b.pt) :
b.IsBilimit where
isLimit :=
{ lift := fun s => ∑ j : J, s.π.app ⟨j⟩ ≫ b.ι j
uniq := fun s m h => by
erw [← Category.comp_id m, ← total, comp_sum]
apply Finset.sum_congr rfl
intro j _
have reassoced : m ≫ Bicone.π b j ≫ Bicone.ι b j = s.π.app ⟨j⟩ ≫ Bicone.ι b j := by
erw [← Category.assoc, eq_whisker (h ⟨j⟩)]
rw [reassoced]
fac := fun s j => by
classical
cases j
simp only [sum_comp, Category.assoc, Bicone.toCone_π_app, b.ι_π, comp_dite]
-- See note [dsimp, simp].
dsimp
simp }
isColimit :=
{ desc := fun s => ∑ j : J, b.π j ≫ s.ι.app ⟨j⟩
uniq := fun s m h => by
erw [← Category.id_comp m, ← total, sum_comp]
apply Finset.sum_congr rfl
intro j _
erw [Category.assoc, h ⟨j⟩]
fac := fun s j => by
classical
cases j
simp only [comp_sum, ← Category.assoc, Bicone.toCocone_ι_app, b.ι_π, dite_comp]
dsimp; simp }
theorem IsBilimit.total {f : J → C} {b : Bicone f} (i : b.IsBilimit) :
∑ j : J, b.π j ≫ b.ι j = 𝟙 b.pt :=
i.isLimit.hom_ext fun j => by
classical
cases j
simp [sum_comp, b.ι_π, comp_dite]
/-- In a preadditive category, we can construct a biproduct for `f : J → C` from
any bicone `b` for `f` satisfying `total : ∑ j : J, b.π j ≫ b.ι j = 𝟙 b.X`.
(That is, such a bicone is a limit cone and a colimit cocone.)
-/
theorem hasBiproduct_of_total {f : J → C} (b : Bicone f)
(total : ∑ j : J, b.π j ≫ b.ι j = 𝟙 b.pt) : HasBiproduct f :=
HasBiproduct.mk
{ bicone := b
isBilimit := isBilimitOfTotal b total }
/-- In a preadditive category, any finite bicone which is a limit cone is in fact a bilimit
bicone. -/
def isBilimitOfIsLimit {f : J → C} (t : Bicone f) (ht : IsLimit t.toCone) : t.IsBilimit :=
isBilimitOfTotal _ <|
ht.hom_ext fun j => by
classical
cases j
simp [sum_comp, t.ι_π, dite_comp, comp_dite]
/-- We can turn any limit cone over a pair into a bilimit bicone. -/
def biconeIsBilimitOfLimitConeOfIsLimit {f : J → C} {t : Cone (Discrete.functor f)}
(ht : IsLimit t) : (Bicone.ofLimitCone ht).IsBilimit :=
isBilimitOfIsLimit _ <| IsLimit.ofIsoLimit ht <| Cones.ext (Iso.refl _) (by simp)
/-- In a preadditive category, any finite bicone which is a colimit cocone is in fact a bilimit
bicone. -/
def isBilimitOfIsColimit {f : J → C} (t : Bicone f) (ht : IsColimit t.toCocone) : t.IsBilimit :=
isBilimitOfTotal _ <|
ht.hom_ext fun j => by
classical
cases j
simp_rw [Bicone.toCocone_ι_app, comp_sum, ← Category.assoc, t.ι_π, dite_comp]
simp
/-- We can turn any limit cone over a pair into a bilimit bicone. -/
def biconeIsBilimitOfColimitCoconeOfIsColimit {f : J → C} {t : Cocone (Discrete.functor f)}
(ht : IsColimit t) : (Bicone.ofColimitCocone ht).IsBilimit :=
isBilimitOfIsColimit _ <| IsColimit.ofIsoColimit ht <| Cocones.ext (Iso.refl _) <| by
rintro ⟨j⟩; simp
end Fintype
section Finite
variable {J : Type} [Finite J]
/-- In a preadditive category, if the product over `f : J → C` exists,
then the biproduct over `f` exists. -/
theorem HasBiproduct.of_hasProduct (f : J → C) [HasProduct f] : HasBiproduct f := by
cases nonempty_fintype J
exact HasBiproduct.mk
{ bicone := _
isBilimit := biconeIsBilimitOfLimitConeOfIsLimit (limit.isLimit _) }
/-- In a preadditive category, if the coproduct over `f : J → C` exists,
then the biproduct over `f` exists. -/
theorem HasBiproduct.of_hasCoproduct (f : J → C) [HasCoproduct f] : HasBiproduct f := by
cases nonempty_fintype J
exact HasBiproduct.mk
{ bicone := _
isBilimit := biconeIsBilimitOfColimitCoconeOfIsColimit (colimit.isColimit _) }
end Finite
/-- A preadditive category with finite products has finite biproducts. -/
theorem HasFiniteBiproducts.of_hasFiniteProducts [HasFiniteProducts C] : HasFiniteBiproducts C :=
⟨fun _ => { has_biproduct := fun _ => HasBiproduct.of_hasProduct _ }⟩
/-- A preadditive category with finite coproducts has finite biproducts. -/
theorem HasFiniteBiproducts.of_hasFiniteCoproducts [HasFiniteCoproducts C] :
HasFiniteBiproducts C :=
⟨fun _ => { has_biproduct := fun _ => HasBiproduct.of_hasCoproduct _ }⟩
section HasBiproduct
variable {J : Type} [Fintype J] {f : J → C} [HasBiproduct f]
/-- In any preadditive category, any biproduct satisfies
`∑ j : J, biproduct.π f j ≫ biproduct.ι f j = 𝟙 (⨁ f)`
-/
@[simp]
theorem biproduct.total : ∑ j : J, biproduct.π f j ≫ biproduct.ι f j = 𝟙 (⨁ f) :=
IsBilimit.total (biproduct.isBilimit _)
theorem biproduct.lift_eq {T : C} {g : ∀ j, T ⟶ f j} :
biproduct.lift g = ∑ j, g j ≫ biproduct.ι f j := by
classical
ext j
simp only [sum_comp, biproduct.ι_π, comp_dite, biproduct.lift_π, Category.assoc, comp_zero,
Finset.sum_dite_eq', Finset.mem_univ, eqToHom_refl, Category.comp_id, if_true]
theorem biproduct.desc_eq {T : C} {g : ∀ j, f j ⟶ T} :
biproduct.desc g = ∑ j, biproduct.π f j ≫ g j := by
classical
ext j
simp [comp_sum, biproduct.ι_π_assoc, dite_comp]
@[reassoc]
theorem biproduct.lift_desc {T U : C} {g : ∀ j, T ⟶ f j} {h : ∀ j, f j ⟶ U} :
biproduct.lift g ≫ biproduct.desc h = ∑ j : J, g j ≫ h j := by
classical
simp [biproduct.lift_eq, biproduct.desc_eq, comp_sum, sum_comp, biproduct.ι_π_assoc, comp_dite,
dite_comp]
theorem biproduct.map_eq [HasFiniteBiproducts C] {f g : J → C} {h : ∀ j, f j ⟶ g j} :
biproduct.map h = ∑ j : J, biproduct.π f j ≫ h j ≫ biproduct.ι g j := by
classical
ext
simp [biproduct.ι_π, biproduct.ι_π_assoc, comp_sum, sum_comp, comp_dite, dite_comp]
@[reassoc]
theorem biproduct.lift_matrix {K : Type} [Finite K] [HasFiniteBiproducts C] {f : J → C} {g : K → C}
{P} (x : ∀ j, P ⟶ f j) (m : ∀ j k, f j ⟶ g k) :
biproduct.lift x ≫ biproduct.matrix m = biproduct.lift fun k => ∑ j, x j ≫ m j k := by
ext
simp [biproduct.lift_desc]
end HasBiproduct
section HasFiniteBiproducts
variable {J K : Type} [Finite J] {f : J → C} [HasFiniteBiproducts C]
@[reassoc]
theorem biproduct.matrix_desc [Fintype K] {f : J → C} {g : K → C}
(m : ∀ j k, f j ⟶ g k) {P} (x : ∀ k, g k ⟶ P) :
biproduct.matrix m ≫ biproduct.desc x = biproduct.desc fun j => ∑ k, m j k ≫ x k := by
ext
simp [lift_desc]
variable [Finite K]
@[reassoc]
theorem biproduct.matrix_map {f : J → C} {g : K → C} {h : K → C} (m : ∀ j k, f j ⟶ g k)
(n : ∀ k, g k ⟶ h k) :
biproduct.matrix m ≫ biproduct.map n = biproduct.matrix fun j k => m j k ≫ n k := by
ext
simp
@[reassoc]
theorem biproduct.map_matrix {f : J → C} {g : J → C} {h : K → C} (m : ∀ k, f k ⟶ g k)
(n : ∀ j k, g j ⟶ h k) :
biproduct.map m ≫ biproduct.matrix n = biproduct.matrix fun j k => m j ≫ n j k := by
ext
simp
end HasFiniteBiproducts
/-- Reindex a categorical biproduct via an equivalence of the index types. -/
@[simps]
def biproduct.reindex {β γ : Type} [Finite β] (ε : β ≃ γ)
(f : γ → C) [HasBiproduct f] [HasBiproduct (f ∘ ε)] : ⨁ f ∘ ε ≅ ⨁ f where
hom := biproduct.desc fun b => biproduct.ι f (ε b)
inv := biproduct.lift fun b => biproduct.π f (ε b)
hom_inv_id := by
ext b b'
by_cases h : b' = b
· subst h; simp
· have : ε b' ≠ ε b := by simp [h]
| simp [biproduct.ι_π_ne _ h, biproduct.ι_π_ne _ this]
inv_hom_id := by
classical
cases nonempty_fintype β
ext g g'
| Mathlib/CategoryTheory/Preadditive/Biproducts.lean | 283 | 287 |
/-
Copyright (c) 2023 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz, Dagur Asgeirsson
-/
import Mathlib.Topology.Category.CompHaus.Limits
import Mathlib.Topology.Category.CompHausLike.EffectiveEpi
/-!
# Effective epimorphisms in `CompHaus`
This file proves that `EffectiveEpi`, `Epi` and `Surjective` are all equivalent in `CompHaus`.
As a consequence we deduce from the material in
`Mathlib.Topology.Category.CompHausLike.EffectiveEpi` that `CompHaus` is `Preregular`
and `Precoherent`.
We also prove that for a finite family of morphisms in `CompHaus` with fixed
target, the conditions jointly surjective, jointly epimorphic and effective epimorphic are all
equivalent.
## Projects
- Define regular categories, and show that `CompHaus` is regular.
- Define coherent categories, and show that `CompHaus` is actually coherent.
-/
universe u
open CategoryTheory Limits CompHausLike
namespace CompHaus
open List in
theorem effectiveEpi_tfae
{B X : CompHaus.{u}} (π : X ⟶ B) :
TFAE
[ EffectiveEpi π
, Epi π
, Function.Surjective π
] := by
tfae_have 1 → 2 := fun _ ↦ inferInstance
tfae_have 2 ↔ 3 := epi_iff_surjective π
tfae_have 3 → 1 := fun hπ ↦ ⟨⟨effectiveEpiStruct π hπ⟩⟩
tfae_finish
instance : Preregular CompHaus :=
preregular fun _ _ _ ↦ ((effectiveEpi_tfae _).out 0 2).mp
example : Precoherent CompHaus.{u} := inferInstance
-- TODO: prove this for `Type*`
open List in
theorem effectiveEpiFamily_tfae
{α : Type} [Finite α] {B : CompHaus.{u}}
(X : α → CompHaus.{u}) (π : (a : α) → (X a ⟶ B)) :
TFAE
[ EffectiveEpiFamily X π
, Epi (Sigma.desc π)
, ∀ b : B, ∃ (a : α) (x : X a), π a x = b
] := by
tfae_have 2 → 1
| _ => by
simpa [← effectiveEpi_desc_iff_effectiveEpiFamily, (effectiveEpi_tfae (Sigma.desc π)).out 0 1]
tfae_have 1 → 2
| _ => inferInstance
tfae_have 3 → 2
| e => by
rw [epi_iff_surjective]
intro b
obtain ⟨t, x, h⟩ := e b
| refine ⟨Sigma.ι X t x, ?_⟩
change (Sigma.ι X t ≫ Sigma.desc π) x = _
simpa using h
tfae_have 2 → 3
| e => by
rw [epi_iff_surjective] at e
let i : ∐ X ≅ finiteCoproduct X :=
(colimit.isColimit _).coconePointUniqueUpToIso (finiteCoproduct.isColimit _)
intro b
obtain ⟨t, rfl⟩ := e b
let q := i.hom t
refine ⟨q.1,q.2,?_⟩
have : t = i.inv (i.hom t) := show t = (i.hom ≫ i.inv) t by simp only [i.hom_inv_id]; rfl
rw [this]
| Mathlib/Topology/Category/CompHaus/EffectiveEpi.lean | 72 | 85 |
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.Analysis.InnerProductSpace.Continuous
import Mathlib.Analysis.Normed.Module.Dual
import Mathlib.MeasureTheory.Function.AEEqOfLIntegral
import Mathlib.MeasureTheory.Function.StronglyMeasurable.Lp
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
import Mathlib.Order.Filter.Ring
/-! # From equality of integrals to equality of functions
This file provides various statements of the general form "if two functions have the same integral
on all sets, then they are equal almost everywhere".
The different lemmas use various hypotheses on the class of functions, on the target space or on the
possible finiteness of the measure.
This file is about Bochner integrals. See the file `AEEqOfLIntegral` for Lebesgue integrals.
## Main statements
All results listed below apply to two functions `f, g`, together with two main hypotheses,
* `f` and `g` are integrable on all measurable sets with finite measure,
* for all measurable sets `s` with finite measure, `∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ`.
The conclusion is then `f =ᵐ[μ] g`. The main lemmas are:
* `ae_eq_of_forall_setIntegral_eq_of_sigmaFinite`: case of a sigma-finite measure.
* `AEFinStronglyMeasurable.ae_eq_of_forall_setIntegral_eq`: for functions which are
`AEFinStronglyMeasurable`.
* `Lp.ae_eq_of_forall_setIntegral_eq`: for elements of `Lp`, for `0 < p < ∞`.
* `Integrable.ae_eq_of_forall_setIntegral_eq`: for integrable functions.
For each of these results, we also provide a lemma about the equality of one function and 0. For
example, `Lp.ae_eq_zero_of_forall_setIntegral_eq_zero`.
Generally useful lemmas which are not related to integrals:
* `ae_eq_zero_of_forall_inner`: if for all constants `c`, `fun x => inner c (f x) =ᵐ[μ] 0` then
`f =ᵐ[μ] 0`.
* `ae_eq_zero_of_forall_dual`: if for all constants `c` in the dual space,
`fun x => c (f x) =ᵐ[μ] 0` then `f =ᵐ[μ] 0`.
-/
open MeasureTheory TopologicalSpace NormedSpace Filter
open scoped ENNReal NNReal MeasureTheory Topology
namespace MeasureTheory
section AeEqOfForall
variable {α E 𝕜 : Type*} {m : MeasurableSpace α} {μ : Measure α} [RCLike 𝕜]
theorem ae_eq_zero_of_forall_inner [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
[SecondCountableTopology E] {f : α → E} (hf : ∀ c : E, (fun x => (inner c (f x) : 𝕜)) =ᵐ[μ] 0) :
f =ᵐ[μ] 0 := by
let s := denseSeq E
have hs : DenseRange s := denseRange_denseSeq E
have hf' : ∀ᵐ x ∂μ, ∀ n : ℕ, inner (s n) (f x) = (0 : 𝕜) := ae_all_iff.mpr fun n => hf (s n)
refine hf'.mono fun x hx => ?_
rw [Pi.zero_apply, ← @inner_self_eq_zero 𝕜]
have h_closed : IsClosed {c : E | inner c (f x) = (0 : 𝕜)} :=
isClosed_eq (continuous_id.inner continuous_const) continuous_const
exact @isClosed_property ℕ E _ s (fun c => inner c (f x) = (0 : 𝕜)) hs h_closed hx _
local notation "⟪" x ", " y "⟫" => y x
variable (𝕜)
theorem ae_eq_zero_of_forall_dual_of_isSeparable [NormedAddCommGroup E] [NormedSpace 𝕜 E]
{t : Set E} (ht : TopologicalSpace.IsSeparable t) {f : α → E}
(hf : ∀ c : Dual 𝕜 E, (fun x => ⟪f x, c⟫) =ᵐ[μ] 0) (h't : ∀ᵐ x ∂μ, f x ∈ t) : f =ᵐ[μ] 0 := by
rcases ht with ⟨d, d_count, hd⟩
haveI : Encodable d := d_count.toEncodable
have : ∀ x : d, ∃ g : E →L[𝕜] 𝕜, ‖g‖ ≤ 1 ∧ g x = ‖(x : E)‖ :=
fun x => exists_dual_vector'' 𝕜 (x : E)
choose s hs using this
have A : ∀ a : E, a ∈ t → (∀ x, ⟪a, s x⟫ = (0 : 𝕜)) → a = 0 := by
intro a hat ha
contrapose! ha
have a_pos : 0 < ‖a‖ := by simp only [ha, norm_pos_iff, Ne, not_false_iff]
have a_mem : a ∈ closure d := hd hat
obtain ⟨x, hx⟩ : ∃ x : d, dist a x < ‖a‖ / 2 := by
rcases Metric.mem_closure_iff.1 a_mem (‖a‖ / 2) (half_pos a_pos) with ⟨x, h'x, hx⟩
exact ⟨⟨x, h'x⟩, hx⟩
use x
have I : ‖a‖ / 2 < ‖(x : E)‖ := by
have : ‖a‖ ≤ ‖(x : E)‖ + ‖a - x‖ := norm_le_insert' _ _
have : ‖a - x‖ < ‖a‖ / 2 := by rwa [dist_eq_norm] at hx
linarith
intro h
apply lt_irrefl ‖s x x‖
calc
‖s x x‖ = ‖s x (x - a)‖ := by simp only [h, sub_zero, ContinuousLinearMap.map_sub]
_ ≤ 1 * ‖(x : E) - a‖ := ContinuousLinearMap.le_of_opNorm_le _ (hs x).1 _
_ < ‖a‖ / 2 := by rw [one_mul]; rwa [dist_eq_norm'] at hx
_ < ‖(x : E)‖ := I
_ = ‖s x x‖ := by rw [(hs x).2, RCLike.norm_coe_norm]
have hfs : ∀ y : d, ∀ᵐ x ∂μ, ⟪f x, s y⟫ = (0 : 𝕜) := fun y => hf (s y)
have hf' : ∀ᵐ x ∂μ, ∀ y : d, ⟪f x, s y⟫ = (0 : 𝕜) := by rwa [ae_all_iff]
filter_upwards [hf', h't] with x hx h'x
exact A (f x) h'x hx
theorem ae_eq_zero_of_forall_dual [NormedAddCommGroup E] [NormedSpace 𝕜 E]
[SecondCountableTopology E] {f : α → E} (hf : ∀ c : Dual 𝕜 E, (fun x => ⟪f x, c⟫) =ᵐ[μ] 0) :
f =ᵐ[μ] 0 :=
ae_eq_zero_of_forall_dual_of_isSeparable 𝕜 (.of_separableSpace Set.univ) hf
(Eventually.of_forall fun _ => Set.mem_univ _)
variable {𝕜}
end AeEqOfForall
variable {α E : Type*} {m m0 : MeasurableSpace α} {μ : Measure α}
[NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E] {p : ℝ≥0∞}
section AeEqOfForallSetIntegralEq
section Real
variable {f : α → ℝ}
theorem ae_nonneg_of_forall_setIntegral_nonneg (hf : Integrable f μ)
(hf_zero : ∀ s, MeasurableSet s → μ s < ∞ → 0 ≤ ∫ x in s, f x ∂μ) : 0 ≤ᵐ[μ] f := by
simp_rw [EventuallyLE, Pi.zero_apply]
rw [ae_const_le_iff_forall_lt_measure_zero]
intro b hb_neg
let s := {x | f x ≤ b}
have hs : NullMeasurableSet s μ := nullMeasurableSet_le hf.1.aemeasurable aemeasurable_const
have mus : μ s < ∞ := Integrable.measure_le_lt_top hf hb_neg
have h_int_gt : (∫ x in s, f x ∂μ) ≤ b * μ.real s := by
have h_const_le : (∫ x in s, f x ∂μ) ≤ ∫ _ in s, b ∂μ := by
refine setIntegral_mono_ae_restrict hf.integrableOn (integrableOn_const.mpr (Or.inr mus)) ?_
rw [EventuallyLE, ae_restrict_iff₀ (hs.mono μ.restrict_le_self)]
exact Eventually.of_forall fun x hxs => hxs
rwa [setIntegral_const, smul_eq_mul, mul_comm] at h_const_le
contrapose! h_int_gt with H
calc
b * μ.real s < 0 := mul_neg_of_neg_of_pos hb_neg <| ENNReal.toReal_pos H mus.ne
_ ≤ ∫ x in s, f x ∂μ := by
rw [← μ.restrict_toMeasurable mus.ne]
exact hf_zero _ (measurableSet_toMeasurable ..) (by rwa [measure_toMeasurable])
theorem ae_le_of_forall_setIntegral_le {f g : α → ℝ} (hf : Integrable f μ) (hg : Integrable g μ)
(hf_le : ∀ s, MeasurableSet s → μ s < ∞ → (∫ x in s, f x ∂μ) ≤ ∫ x in s, g x ∂μ) :
f ≤ᵐ[μ] g := by
rw [← eventually_sub_nonneg]
refine ae_nonneg_of_forall_setIntegral_nonneg (hg.sub hf) fun s hs => ?_
rw [integral_sub' hg.integrableOn hf.integrableOn, sub_nonneg]
exact hf_le s hs
theorem ae_nonneg_restrict_of_forall_setIntegral_nonneg_inter {f : α → ℝ} {t : Set α}
(hf : IntegrableOn f t μ)
(hf_zero : ∀ s, MeasurableSet s → μ (s ∩ t) < ∞ → 0 ≤ ∫ x in s ∩ t, f x ∂μ) :
0 ≤ᵐ[μ.restrict t] f := by
refine ae_nonneg_of_forall_setIntegral_nonneg hf fun s hs h's => ?_
simp_rw [Measure.restrict_restrict hs]
apply hf_zero s hs
rwa [Measure.restrict_apply hs] at h's
theorem ae_nonneg_of_forall_setIntegral_nonneg_of_sigmaFinite [SigmaFinite μ] {f : α → ℝ}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s, MeasurableSet s → μ s < ∞ → 0 ≤ ∫ x in s, f x ∂μ) : 0 ≤ᵐ[μ] f := by
apply ae_of_forall_measure_lt_top_ae_restrict
intro t t_meas t_lt_top
apply ae_nonneg_restrict_of_forall_setIntegral_nonneg_inter (hf_int_finite t t_meas t_lt_top)
intro s s_meas _
exact
hf_zero _ (s_meas.inter t_meas)
(lt_of_le_of_lt (measure_mono (Set.inter_subset_right)) t_lt_top)
theorem AEFinStronglyMeasurable.ae_nonneg_of_forall_setIntegral_nonneg {f : α → ℝ}
(hf : AEFinStronglyMeasurable f μ)
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s, MeasurableSet s → μ s < ∞ → 0 ≤ ∫ x in s, f x ∂μ) : 0 ≤ᵐ[μ] f := by
let t := hf.sigmaFiniteSet
suffices 0 ≤ᵐ[μ.restrict t] f from
ae_of_ae_restrict_of_ae_restrict_compl _ this hf.ae_eq_zero_compl.symm.le
haveI : SigmaFinite (μ.restrict t) := hf.sigmaFinite_restrict
refine
ae_nonneg_of_forall_setIntegral_nonneg_of_sigmaFinite (fun s hs hμts => ?_) fun s hs hμts => ?_
· rw [IntegrableOn, Measure.restrict_restrict hs]
rw [Measure.restrict_apply hs] at hμts
exact hf_int_finite (s ∩ t) (hs.inter hf.measurableSet) hμts
· rw [Measure.restrict_restrict hs]
rw [Measure.restrict_apply hs] at hμts
exact hf_zero (s ∩ t) (hs.inter hf.measurableSet) hμts
theorem ae_nonneg_restrict_of_forall_setIntegral_nonneg {f : α → ℝ}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s, MeasurableSet s → μ s < ∞ → 0 ≤ ∫ x in s, f x ∂μ) {t : Set α}
(ht : MeasurableSet t) (hμt : μ t ≠ ∞) : 0 ≤ᵐ[μ.restrict t] f := by
refine
ae_nonneg_restrict_of_forall_setIntegral_nonneg_inter
(hf_int_finite t ht (lt_top_iff_ne_top.mpr hμt)) fun s hs _ => ?_
refine hf_zero (s ∩ t) (hs.inter ht) ?_
exact (measure_mono Set.inter_subset_right).trans_lt (lt_top_iff_ne_top.mpr hμt)
theorem ae_eq_zero_restrict_of_forall_setIntegral_eq_zero_real {f : α → ℝ}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = 0) {t : Set α}
(ht : MeasurableSet t) (hμt : μ t ≠ ∞) : f =ᵐ[μ.restrict t] 0 := by
suffices h_and : f ≤ᵐ[μ.restrict t] 0 ∧ 0 ≤ᵐ[μ.restrict t] f from
h_and.1.mp (h_and.2.mono fun x hx1 hx2 => le_antisymm hx2 hx1)
refine
⟨?_,
ae_nonneg_restrict_of_forall_setIntegral_nonneg hf_int_finite
(fun s hs hμs => (hf_zero s hs hμs).symm.le) ht hμt⟩
suffices h_neg : 0 ≤ᵐ[μ.restrict t] -f by
refine h_neg.mono fun x hx => ?_
rw [Pi.neg_apply] at hx
simpa using hx
refine
ae_nonneg_restrict_of_forall_setIntegral_nonneg (fun s hs hμs => (hf_int_finite s hs hμs).neg)
(fun s hs hμs => ?_) ht hμt
simp_rw [Pi.neg_apply]
rw [integral_neg, neg_nonneg]
exact (hf_zero s hs hμs).le
end Real
theorem ae_eq_zero_restrict_of_forall_setIntegral_eq_zero {f : α → E}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = 0) {t : Set α}
(ht : MeasurableSet t) (hμt : μ t ≠ ∞) : f =ᵐ[μ.restrict t] 0 := by
rcases (hf_int_finite t ht hμt.lt_top).aestronglyMeasurable.isSeparable_ae_range with
⟨u, u_sep, hu⟩
refine ae_eq_zero_of_forall_dual_of_isSeparable ℝ u_sep (fun c => ?_) hu
refine ae_eq_zero_restrict_of_forall_setIntegral_eq_zero_real ?_ ?_ ht hμt
· intro s hs hμs
exact ContinuousLinearMap.integrable_comp c (hf_int_finite s hs hμs)
· intro s hs hμs
rw [ContinuousLinearMap.integral_comp_comm c (hf_int_finite s hs hμs), hf_zero s hs hμs]
exact ContinuousLinearMap.map_zero _
theorem ae_eq_restrict_of_forall_setIntegral_eq {f g : α → E}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hg_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn g s μ)
(hfg_zero : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ)
{t : Set α} (ht : MeasurableSet t) (hμt : μ t ≠ ∞) : f =ᵐ[μ.restrict t] g := by
rw [← sub_ae_eq_zero]
have hfg' : ∀ s : Set α, MeasurableSet s → μ s < ∞ → (∫ x in s, (f - g) x ∂μ) = 0 := by
intro s hs hμs
rw [integral_sub' (hf_int_finite s hs hμs) (hg_int_finite s hs hμs)]
exact sub_eq_zero.mpr (hfg_zero s hs hμs)
have hfg_int : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn (f - g) s μ := fun s hs hμs =>
(hf_int_finite s hs hμs).sub (hg_int_finite s hs hμs)
exact ae_eq_zero_restrict_of_forall_setIntegral_eq_zero hfg_int hfg' ht hμt
theorem ae_eq_zero_of_forall_setIntegral_eq_of_sigmaFinite [SigmaFinite μ] {f : α → E}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = 0) : f =ᵐ[μ] 0 := by
let S := spanningSets μ
rw [← @Measure.restrict_univ _ _ μ, ← iUnion_spanningSets μ, EventuallyEq, ae_iff,
Measure.restrict_apply' (MeasurableSet.iUnion (measurableSet_spanningSets μ))]
rw [Set.inter_iUnion, measure_iUnion_null_iff]
intro n
have h_meas_n : MeasurableSet (S n) := measurableSet_spanningSets μ n
have hμn : μ (S n) < ∞ := measure_spanningSets_lt_top μ n
rw [← Measure.restrict_apply' h_meas_n]
exact ae_eq_zero_restrict_of_forall_setIntegral_eq_zero hf_int_finite hf_zero h_meas_n hμn.ne
theorem ae_eq_of_forall_setIntegral_eq_of_sigmaFinite [SigmaFinite μ] {f g : α → E}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hg_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn g s μ)
(hfg_eq : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ) :
f =ᵐ[μ] g := by
rw [← sub_ae_eq_zero]
have hfg : ∀ s : Set α, MeasurableSet s → μ s < ∞ → (∫ x in s, (f - g) x ∂μ) = 0 := by
intro s hs hμs
rw [integral_sub' (hf_int_finite s hs hμs) (hg_int_finite s hs hμs),
sub_eq_zero.mpr (hfg_eq s hs hμs)]
have hfg_int : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn (f - g) s μ := fun s hs hμs =>
(hf_int_finite s hs hμs).sub (hg_int_finite s hs hμs)
exact ae_eq_zero_of_forall_setIntegral_eq_of_sigmaFinite hfg_int hfg
theorem AEFinStronglyMeasurable.ae_eq_zero_of_forall_setIntegral_eq_zero {f : α → E}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = 0)
(hf : AEFinStronglyMeasurable f μ) : f =ᵐ[μ] 0 := by
let t := hf.sigmaFiniteSet
suffices f =ᵐ[μ.restrict t] 0 from
ae_of_ae_restrict_of_ae_restrict_compl _ this hf.ae_eq_zero_compl
haveI : SigmaFinite (μ.restrict t) := hf.sigmaFinite_restrict
refine ae_eq_zero_of_forall_setIntegral_eq_of_sigmaFinite ?_ ?_
· intro s hs hμs
rw [IntegrableOn, Measure.restrict_restrict hs]
rw [Measure.restrict_apply hs] at hμs
exact hf_int_finite _ (hs.inter hf.measurableSet) hμs
· intro s hs hμs
rw [Measure.restrict_restrict hs]
rw [Measure.restrict_apply hs] at hμs
exact hf_zero _ (hs.inter hf.measurableSet) hμs
theorem AEFinStronglyMeasurable.ae_eq_of_forall_setIntegral_eq {f g : α → E}
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hg_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn g s μ)
(hfg_eq : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ)
(hf : AEFinStronglyMeasurable f μ) (hg : AEFinStronglyMeasurable g μ) : f =ᵐ[μ] g := by
rw [← sub_ae_eq_zero]
have hfg : ∀ s : Set α, MeasurableSet s → μ s < ∞ → (∫ x in s, (f - g) x ∂μ) = 0 := by
intro s hs hμs
rw [integral_sub' (hf_int_finite s hs hμs) (hg_int_finite s hs hμs),
sub_eq_zero.mpr (hfg_eq s hs hμs)]
have hfg_int : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn (f - g) s μ := fun s hs hμs =>
(hf_int_finite s hs hμs).sub (hg_int_finite s hs hμs)
exact (hf.sub hg).ae_eq_zero_of_forall_setIntegral_eq_zero hfg_int hfg
theorem Lp.ae_eq_zero_of_forall_setIntegral_eq_zero (f : Lp E p μ) (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) (hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = 0) : f =ᵐ[μ] 0 :=
AEFinStronglyMeasurable.ae_eq_zero_of_forall_setIntegral_eq_zero hf_int_finite hf_zero
(Lp.finStronglyMeasurable _ hp_ne_zero hp_ne_top).aefinStronglyMeasurable
theorem Lp.ae_eq_of_forall_setIntegral_eq (f g : Lp E p μ) (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞)
(hf_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn f s μ)
(hg_int_finite : ∀ s, MeasurableSet s → μ s < ∞ → IntegrableOn g s μ)
(hfg : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ) :
f =ᵐ[μ] g :=
AEFinStronglyMeasurable.ae_eq_of_forall_setIntegral_eq hf_int_finite hg_int_finite hfg
(Lp.finStronglyMeasurable _ hp_ne_zero hp_ne_top).aefinStronglyMeasurable
(Lp.finStronglyMeasurable _ hp_ne_zero hp_ne_top).aefinStronglyMeasurable
theorem ae_eq_zero_of_forall_setIntegral_eq_of_finStronglyMeasurable_trim (hm : m ≤ m0) {f : α → E}
(hf_int_finite : ∀ s, MeasurableSet[m] s → μ s < ∞ → IntegrableOn f s μ)
(hf_zero : ∀ s : Set α, MeasurableSet[m] s → μ s < ∞ → ∫ x in s, f x ∂μ = 0)
(hf : FinStronglyMeasurable f (μ.trim hm)) : f =ᵐ[μ] 0 := by
obtain ⟨t, ht_meas, htf_zero, htμ⟩ := hf.exists_set_sigmaFinite
haveI : SigmaFinite ((μ.restrict t).trim hm) := by rwa [restrict_trim hm μ ht_meas] at htμ
have htf_zero : f =ᵐ[μ.restrict tᶜ] 0 := by
rw [EventuallyEq, ae_restrict_iff' (MeasurableSet.compl (hm _ ht_meas))]
exact Eventually.of_forall htf_zero
have hf_meas_m : StronglyMeasurable[m] f := hf.stronglyMeasurable
suffices f =ᵐ[μ.restrict t] 0 from
ae_of_ae_restrict_of_ae_restrict_compl _ this htf_zero
refine measure_eq_zero_of_trim_eq_zero hm ?_
refine ae_eq_zero_of_forall_setIntegral_eq_of_sigmaFinite ?_ ?_
· intro s hs hμs
unfold IntegrableOn
rw [restrict_trim hm (μ.restrict t) hs, Measure.restrict_restrict (hm s hs)]
rw [← restrict_trim hm μ ht_meas, Measure.restrict_apply hs,
trim_measurableSet_eq hm (hs.inter ht_meas)] at hμs
refine Integrable.trim hm ?_ hf_meas_m
exact hf_int_finite _ (hs.inter ht_meas) hμs
· intro s hs hμs
rw [restrict_trim hm (μ.restrict t) hs, Measure.restrict_restrict (hm s hs)]
rw [← restrict_trim hm μ ht_meas, Measure.restrict_apply hs,
trim_measurableSet_eq hm (hs.inter ht_meas)] at hμs
rw [← integral_trim hm hf_meas_m]
exact hf_zero _ (hs.inter ht_meas) hμs
theorem Integrable.ae_eq_zero_of_forall_setIntegral_eq_zero {f : α → E} (hf : Integrable f μ)
(hf_zero : ∀ s, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = 0) : f =ᵐ[μ] 0 := by
have hf_Lp : MemLp f 1 μ := memLp_one_iff_integrable.mpr hf
let f_Lp := hf_Lp.toLp f
have hf_f_Lp : f =ᵐ[μ] f_Lp := (MemLp.coeFn_toLp hf_Lp).symm
refine hf_f_Lp.trans ?_
refine Lp.ae_eq_zero_of_forall_setIntegral_eq_zero f_Lp one_ne_zero ENNReal.coe_ne_top ?_ ?_
· exact fun s _ _ => Integrable.integrableOn (L1.integrable_coeFn _)
· intro s hs hμs
rw [integral_congr_ae (ae_restrict_of_ae hf_f_Lp.symm)]
exact hf_zero s hs hμs
theorem Integrable.ae_eq_of_forall_setIntegral_eq (f g : α → E) (hf : Integrable f μ)
(hg : Integrable g μ)
(hfg : ∀ s : Set α, MeasurableSet s → μ s < ∞ → ∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ) :
f =ᵐ[μ] g := by
rw [← sub_ae_eq_zero]
have hfg' : ∀ s : Set α, MeasurableSet s → μ s < ∞ → (∫ x in s, (f - g) x ∂μ) = 0 := by
intro s hs hμs
rw [integral_sub' hf.integrableOn hg.integrableOn]
exact sub_eq_zero.mpr (hfg s hs hμs)
exact Integrable.ae_eq_zero_of_forall_setIntegral_eq_zero (hf.sub hg) hfg'
variable {β : Type*} [TopologicalSpace β] [MeasurableSpace β] [BorelSpace β]
/-- If an integrable function has zero integral on all closed sets, then it is zero
almost everywhere. -/
lemma ae_eq_zero_of_forall_setIntegral_isClosed_eq_zero {μ : Measure β} {f : β → E}
(hf : Integrable f μ) (h'f : ∀ (s : Set β), IsClosed s → ∫ x in s, f x ∂μ = 0) :
f =ᵐ[μ] 0 := by
suffices ∀ s, MeasurableSet s → ∫ x in s, f x ∂μ = 0 from
hf.ae_eq_zero_of_forall_setIntegral_eq_zero (fun s hs _ ↦ this s hs)
have A : ∀ (t : Set β), MeasurableSet t → ∫ (x : β) in t, f x ∂μ = 0
→ ∫ (x : β) in tᶜ, f x ∂μ = 0 := by
intro t t_meas ht
have I : ∫ x, f x ∂μ = 0 := by rw [← setIntegral_univ]; exact h'f _ isClosed_univ
simpa [ht, I] using integral_add_compl t_meas hf
intro s hs
induction s, hs using MeasurableSet.induction_on_open with
| isOpen U hU => exact compl_compl U ▸ A _ hU.measurableSet.compl (h'f _ hU.isClosed_compl)
| compl s hs ihs => exact A s hs ihs
| iUnion g g_disj g_meas hg => simp [integral_iUnion g_meas g_disj hf.integrableOn, hg]
/-- If an integrable function has zero integral on all compact sets in a sigma-compact space, then
it is zero almost everywhere. -/
lemma ae_eq_zero_of_forall_setIntegral_isCompact_eq_zero
[SigmaCompactSpace β] [R1Space β] {μ : Measure β} {f : β → E} (hf : Integrable f μ)
(h'f : ∀ (s : Set β), IsCompact s → ∫ x in s, f x ∂μ = 0) :
f =ᵐ[μ] 0 := by
apply ae_eq_zero_of_forall_setIntegral_isClosed_eq_zero hf (fun s hs ↦ ?_)
let t : ℕ → Set β := fun n ↦ closure (compactCovering β n) ∩ s
suffices H : Tendsto (fun n ↦ ∫ x in t n, f x ∂μ) atTop (𝓝 (∫ x in s, f x ∂μ)) by
have A : ∀ n, ∫ x in t n, f x ∂μ = 0 :=
fun n ↦ h'f _ ((isCompact_compactCovering β n).closure.inter_right hs)
simp_rw [A, tendsto_const_nhds_iff] at H
exact H.symm
have B : s = ⋃ n, t n := by
rw [← Set.iUnion_inter, iUnion_closure_compactCovering, Set.univ_inter]
rw [B]
apply tendsto_setIntegral_of_monotone
· intros n
exact (isClosed_closure.inter hs).measurableSet
· intros m n hmn
simp only [t, Set.le_iff_subset]
gcongr
· exact hf.integrableOn
/-- If a locally integrable function has zero integral on all compact sets in a sigma-compact space,
then it is zero almost everywhere. -/
lemma ae_eq_zero_of_forall_setIntegral_isCompact_eq_zero'
[SigmaCompactSpace β] [R1Space β] {μ : Measure β} {f : β → E} (hf : LocallyIntegrable f μ)
(h'f : ∀ (s : Set β), IsCompact s → ∫ x in s, f x ∂μ = 0) :
f =ᵐ[μ] 0 := by
rw [← μ.restrict_univ, ← iUnion_closure_compactCovering]
apply (ae_restrict_iUnion_iff _ _).2 (fun n ↦ ?_)
apply ae_eq_zero_of_forall_setIntegral_isCompact_eq_zero
· exact hf.integrableOn_isCompact (isCompact_compactCovering β n).closure
· intro s hs
rw [Measure.restrict_restrict' measurableSet_closure]
exact h'f _ (hs.inter_right isClosed_closure)
end AeEqOfForallSetIntegralEq
end MeasureTheory
| Mathlib/MeasureTheory/Function/AEEqOfIntegral.lean | 740 | 744 | |
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Yuyang Zhao
-/
import Mathlib.Algebra.Algebra.Tower
import Mathlib.Algebra.Polynomial.AlgebraMap
/-!
# Algebra towers for polynomial
This file proves some basic results about the algebra tower structure for the type `R[X]`.
This structure itself is provided elsewhere as `Polynomial.isScalarTower`
When you update this file, you can also try to make a corresponding update in
`RingTheory.MvPolynomial.Tower`.
-/
open Polynomial
variable (R A B : Type*)
namespace Polynomial
section Semiring
variable [CommSemiring R] [CommSemiring A] [Semiring B]
variable [Algebra R A] [Algebra A B] [Algebra R B]
variable [IsScalarTower R A B]
variable {R B}
@[simp]
theorem aeval_map_algebraMap (x : B) (p : R[X]) : aeval x (map (algebraMap R A) p) = aeval x p := by
rw [aeval_def, aeval_def, eval₂_map, IsScalarTower.algebraMap_eq R A B]
@[simp]
lemma eval_map_algebraMap (P : R[X]) (b : B) :
(map (algebraMap R B) P).eval b = aeval b P := by
rw [aeval_def, eval_map]
end Semiring
section CommSemiring
variable [CommSemiring R] [CommSemiring A] [Semiring B]
variable [Algebra R A] [Algebra A B] [Algebra R B] [IsScalarTower R A B]
variable {R A}
theorem aeval_algebraMap_apply (x : A) (p : R[X]) :
aeval (algebraMap A B x) p = algebraMap A B (aeval x p) := by
rw [aeval_def, aeval_def, hom_eval₂, ← IsScalarTower.algebraMap_eq]
@[simp]
theorem aeval_algebraMap_eq_zero_iff [NoZeroSMulDivisors A B] [Nontrivial B] (x : A) (p : R[X]) :
aeval (algebraMap A B x) p = 0 ↔ aeval x p = 0 := by
rw [aeval_algebraMap_apply, Algebra.algebraMap_eq_smul_one, smul_eq_zero,
iff_false_intro (one_ne_zero' B), or_false]
variable {B}
theorem aeval_algebraMap_eq_zero_iff_of_injective {x : A} {p : R[X]}
(h : Function.Injective (algebraMap A B)) : aeval (algebraMap A B x) p = 0 ↔ aeval x p = 0 := by
rw [aeval_algebraMap_apply, ← (algebraMap A B).map_zero, h.eq_iff]
end CommSemiring
|
end Polynomial
| Mathlib/RingTheory/Polynomial/Tower.lean | 68 | 70 |
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Algebra.Order.UpperLower
import Mathlib.Topology.Algebra.Group.Pointwise
/-!
# Topological facts about upper/lower/order-connected sets
The topological closure and interior of an upper/lower/order-connected set is an
upper/lower/order-connected set (with the notable exception of the closure of an order-connected
set).
## Implementation notes
The same lemmas are true in the additive/multiplicative worlds. To avoid code duplication, we
provide `HasUpperLowerClosure`, an ad hoc axiomatisation of the properties we need.
-/
open Function Set
open Pointwise
/-- Ad hoc class stating that the closure of an upper set is an upper set. This is used to state
lemmas that do not mention algebraic operations for both the additive and multiplicative versions
simultaneously. If you find a satisfying replacement for this typeclass, please remove it! -/
class HasUpperLowerClosure (α : Type*) [TopologicalSpace α] [Preorder α] : Prop where
isUpperSet_closure : ∀ s : Set α, IsUpperSet s → IsUpperSet (closure s)
isLowerSet_closure : ∀ s : Set α, IsLowerSet s → IsLowerSet (closure s)
isOpen_upperClosure : ∀ s : Set α, IsOpen s → IsOpen (upperClosure s : Set α)
isOpen_lowerClosure : ∀ s : Set α, IsOpen s → IsOpen (lowerClosure s : Set α)
variable {α : Type*} [TopologicalSpace α]
-- See note [lower instance priority]
@[to_additive]
instance (priority := 100) IsOrderedMonoid.to_hasUpperLowerClosure
[CommGroup α] [PartialOrder α] [IsOrderedMonoid α]
[ContinuousConstSMul α α] : HasUpperLowerClosure α where
isUpperSet_closure s h x y hxy hx :=
closure_mono (h.smul_subset <| one_le_div'.2 hxy) <| by
rw [closure_smul]
exact ⟨x, hx, div_mul_cancel _ _⟩
isLowerSet_closure s h x y hxy hx :=
closure_mono (h.smul_subset <| div_le_one'.2 hxy) <| by
rw [closure_smul]
exact ⟨x, hx, div_mul_cancel _ _⟩
isOpen_upperClosure s hs := by
rw [← mul_one s, ← mul_upperClosure]
exact hs.mul_right
isOpen_lowerClosure s hs := by
rw [← mul_one s, ← mul_lowerClosure]
exact hs.mul_right
variable [Preorder α] [HasUpperLowerClosure α] {s : Set α}
protected theorem IsUpperSet.closure : IsUpperSet s → IsUpperSet (closure s) :=
HasUpperLowerClosure.isUpperSet_closure _
protected theorem IsLowerSet.closure : IsLowerSet s → IsLowerSet (closure s) :=
HasUpperLowerClosure.isLowerSet_closure _
protected theorem IsOpen.upperClosure : IsOpen s → IsOpen (upperClosure s : Set α) :=
HasUpperLowerClosure.isOpen_upperClosure _
protected theorem IsOpen.lowerClosure : IsOpen s → IsOpen (lowerClosure s : Set α) :=
HasUpperLowerClosure.isOpen_lowerClosure _
instance : HasUpperLowerClosure αᵒᵈ where
isUpperSet_closure := @IsLowerSet.closure α _ _ _
isLowerSet_closure := @IsUpperSet.closure α _ _ _
isOpen_upperClosure := @IsOpen.lowerClosure α _ _ _
isOpen_lowerClosure := @IsOpen.upperClosure α _ _ _
/-
Note: `s.OrdConnected` does not imply `(closure s).OrdConnected`, as we can see by taking
`s := Ioo 0 1 × Ioo 1 2 ∪ Ioo 2 3 × Ioo 0 1` because then
`closure s = Icc 0 1 × Icc 1 2 ∪ Icc 2 3 × Icc 0 1` is not order-connected as
`(1, 1) ∈ closure s`, `(2, 1) ∈ closure s` but `Icc (1, 1) (2, 1) ⊈ closure s`.
`s` looks like
```
xxooooo
xxooooo
oooooxx
oooooxx
```
-/
protected theorem IsUpperSet.interior (h : IsUpperSet s) : IsUpperSet (interior s) := by
rw [← isLowerSet_compl, ← closure_compl]
exact h.compl.closure
protected theorem IsLowerSet.interior (h : IsLowerSet s) : IsLowerSet (interior s) :=
h.toDual.interior
protected theorem Set.OrdConnected.interior (h : s.OrdConnected) : (interior s).OrdConnected := by
| rw [← h.upperClosure_inter_lowerClosure, interior_inter]
exact
(upperClosure s).upper.interior.ordConnected.inter (lowerClosure s).lower.interior.ordConnected
| Mathlib/Topology/Algebra/Order/UpperLower.lean | 100 | 102 |
/-
Copyright (c) 2019 Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard
-/
import Mathlib.Data.EReal.Basic
deprecated_module (since := "2025-04-13")
| Mathlib/Data/Real/EReal.lean | 1,417 | 1,423 | |
/-
Copyright (c) 2020 Nicolò Cavalleri. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nicolò Cavalleri
-/
import Mathlib.Geometry.Manifold.ContMDiffMap
import Mathlib.Geometry.Manifold.MFDeriv.Basic
/-!
# `C^n` monoid
A `C^n` monoid is a monoid that is also a `C^n` manifold, in which multiplication is a `C^n` map
of the product manifold `G` × `G` into `G`.
In this file we define the basic structures to talk about `C^n` monoids: `ContMDiffMul` and its
additive counterpart `ContMDiffAdd`. These structures are general enough to also talk about `C^n`
semigroups.
-/
open scoped Manifold ContDiff
library_note "Design choices about smooth algebraic structures"/--
1. All `C^n` algebraic structures on `G` are `Prop`-valued classes that extend
`IsManifold I n G`. This way we save users from adding both
`[IsManifold I n G]` and `[ContMDiffMul I n G]` to the assumptions. While many API
lemmas hold true without the `IsManifold I n G` assumption, we're not aware of a
mathematically interesting monoid on a topological manifold such that (a) the space is not a
`IsManifold`; (b) the multiplication is `C^n` at `(a, b)` in the charts
`extChartAt I a`, `extChartAt I b`, `extChartAt I (a * b)`.
2. Because of `ModelProd` we can't assume, e.g., that a `LieGroup` is modelled on `𝓘(𝕜, E)`. So,
we formulate the definitions and lemmas for any model.
3. While smoothness of an operation implies its continuity, lemmas like
`continuousMul_of_contMDiffMul` can't be instances because otherwise Lean would have to search for
`ContMDiffMul I n G` with unknown `𝕜`, `E`, `H`, and `I : ModelWithCorners 𝕜 E H`. If users needs
`[ContinuousMul G]` in a proof about a `C^n` monoid, then they need to either add
`[ContinuousMul G]` as an assumption (worse) or use `haveI` in the proof (better). -/
-- See note [Design choices about smooth algebraic structures]
/-- Basic hypothesis to talk about a `C^n` (Lie) additive monoid or a `C^n` additive
semigroup. A `C^n` additive monoid over `G`, for example, is obtained by requiring both the
instances `AddMonoid G` and `ContMDiffAdd I n G`. -/
class ContMDiffAdd {𝕜 : Type*} [NontriviallyNormedField 𝕜] {H : Type*} [TopologicalSpace H]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
(I : ModelWithCorners 𝕜 E H) (n : WithTop ℕ∞)
(G : Type*) [Add G] [TopologicalSpace G] [ChartedSpace H G] : Prop
extends IsManifold I n G where
contMDiff_add : ContMDiff (I.prod I) I n fun p : G × G => p.1 + p.2
@[deprecated (since := "2025-01-09")] alias SmoothAdd := ContMDiffAdd
-- See note [Design choices about smooth algebraic structures]
/-- Basic hypothesis to talk about a `C^n` (Lie) monoid or a `C^n` semigroup.
A `C^n` monoid over `G`, for example, is obtained by requiring both the instances `Monoid G`
and `ContMDiffMul I n G`. -/
@[to_additive]
class ContMDiffMul {𝕜 : Type*} [NontriviallyNormedField 𝕜] {H : Type*} [TopologicalSpace H]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
(I : ModelWithCorners 𝕜 E H) (n : WithTop ℕ∞)
(G : Type*) [Mul G] [TopologicalSpace G] [ChartedSpace H G] : Prop
extends IsManifold I n G where
contMDiff_mul : ContMDiff (I.prod I) I n fun p : G × G => p.1 * p.2
@[deprecated (since := "2025-01-09")] alias SmoothMul := ContMDiffMul
section ContMDiffMul
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {H : Type*} [TopologicalSpace H] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {I : ModelWithCorners 𝕜 E H} {n : WithTop ℕ∞}
{G : Type*} [Mul G] [TopologicalSpace G] [ChartedSpace H G] {E' : Type*} [NormedAddCommGroup E']
[NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H'] {I' : ModelWithCorners 𝕜 E' H'}
{M : Type*} [TopologicalSpace M] [ChartedSpace H' M]
@[to_additive]
protected theorem ContMDiffMul.of_le {m n : WithTop ℕ∞} (hmn : m ≤ n)
[h : ContMDiffMul I n G] : ContMDiffMul I m G := by
have : IsManifold I m G := IsManifold.of_le hmn
exact ⟨h.contMDiff_mul.of_le hmn⟩
@[to_additive]
instance {a : WithTop ℕ∞} [ContMDiffMul I ∞ G] [h : ENat.LEInfty a] : ContMDiffMul I a G :=
ContMDiffMul.of_le h.out
@[to_additive]
instance {a : WithTop ℕ∞} [ContMDiffMul I ω G] : ContMDiffMul I a G :=
ContMDiffMul.of_le le_top
@[to_additive]
instance [ContinuousMul G] : ContMDiffMul I 0 G := by
constructor
rw [contMDiff_zero_iff]
exact continuous_mul
@[to_additive]
instance [ContMDiffMul I 2 G] : ContMDiffMul I 1 G :=
ContMDiffMul.of_le one_le_two
section
variable (I n)
@[to_additive]
theorem contMDiff_mul [ContMDiffMul I n G] : ContMDiff (I.prod I) I n fun p : G × G => p.1 * p.2 :=
ContMDiffMul.contMDiff_mul
@[deprecated (since := "2024-11-20")] alias smooth_mul := contMDiff_mul
@[deprecated (since := "2024-11-20")] alias smooth_add := contMDiff_add
include I n in
/-- If the multiplication is `C^n`, then it is continuous. This is not an instance for technical
reasons, see note [Design choices about smooth algebraic structures]. -/
@[to_additive "If the addition is `C^n`, then it is continuous. This is not an instance for
technical reasons, see note [Design choices about smooth algebraic structures]."]
theorem continuousMul_of_contMDiffMul [ContMDiffMul I n G] : ContinuousMul G :=
⟨(contMDiff_mul I n).continuous⟩
@[deprecated (since := "2025-01-09")] alias continuousMul_of_smooth := continuousMul_of_contMDiffMul
end
section
variable [ContMDiffMul I n G] {f g : M → G} {s : Set M} {x : M}
@[to_additive]
theorem ContMDiffWithinAt.mul (hf : ContMDiffWithinAt I' I n f s x)
(hg : ContMDiffWithinAt I' I n g s x) : ContMDiffWithinAt I' I n (f * g) s x :=
(contMDiff_mul I n).contMDiffAt.comp_contMDiffWithinAt x (hf.prodMk hg)
@[to_additive]
nonrec theorem ContMDiffAt.mul (hf : ContMDiffAt I' I n f x) (hg : ContMDiffAt I' I n g x) :
ContMDiffAt I' I n (f * g) x :=
hf.mul hg
@[to_additive]
theorem ContMDiffOn.mul (hf : ContMDiffOn I' I n f s) (hg : ContMDiffOn I' I n g s) :
ContMDiffOn I' I n (f * g) s := fun x hx => (hf x hx).mul (hg x hx)
@[to_additive]
theorem ContMDiff.mul (hf : ContMDiff I' I n f) (hg : ContMDiff I' I n g) :
ContMDiff I' I n (f * g) := fun x => (hf x).mul (hg x)
@[deprecated (since := "2024-11-21")] alias SmoothWithinAt.mul := ContMDiffWithinAt.mul
@[deprecated (since := "2024-11-21")] alias SmoothAt.mul := ContMDiffAt.mul
@[deprecated (since := "2024-11-21")] alias SmoothOn.mul := ContMDiffOn.mul
@[deprecated (since := "2024-11-21")] alias Smooth.mul := ContMDiff.mul
@[deprecated (since := "2024-11-21")] alias SmoothWithinAt.add := ContMDiffWithinAt.add
@[deprecated (since := "2024-11-21")] alias SmoothAt.add := ContMDiffAt.add
@[deprecated (since := "2024-11-21")] alias SmoothOn.add := ContMDiffOn.add
@[deprecated (since := "2024-11-21")] alias Smooth.add := ContMDiff.add
@[to_additive]
theorem contMDiff_mul_left {a : G} : ContMDiff I I n (a * ·) :=
contMDiff_const.mul contMDiff_id
@[deprecated (since := "2024-11-21")] alias smooth_mul_left := contMDiff_mul_left
@[deprecated (since := "2024-11-21")] alias smooth_add_left := contMDiff_add_left
@[to_additive]
theorem contMDiffAt_mul_left {a b : G} : ContMDiffAt I I n (a * ·) b :=
contMDiff_mul_left.contMDiffAt
@[to_additive]
theorem contMDiff_mul_right {a : G} : ContMDiff I I n (· * a) :=
contMDiff_id.mul contMDiff_const
@[deprecated (since := "2024-11-21")] alias smooth_mul_right := contMDiff_mul_right
@[deprecated (since := "2024-11-21")] alias smooth_add_right := contMDiff_add_right
@[to_additive]
theorem contMDiffAt_mul_right {a b : G} : ContMDiffAt I I n (· * a) b :=
contMDiff_mul_right.contMDiffAt
end
section
variable [ContMDiffMul I 1 G]
@[to_additive]
theorem mdifferentiable_mul_left {a : G} : MDifferentiable I I (a * ·) :=
contMDiff_mul_left.mdifferentiable le_rfl
@[to_additive]
theorem mdifferentiableAt_mul_left {a b : G} :
MDifferentiableAt I I (a * ·) b :=
contMDiffAt_mul_left.mdifferentiableAt le_rfl
@[to_additive]
theorem mdifferentiable_mul_right {a : G} : MDifferentiable I I (· * a) :=
contMDiff_mul_right.mdifferentiable le_rfl
@[to_additive]
theorem mdifferentiableAt_mul_right {a b : G} :
MDifferentiableAt I I (· * a) b :=
contMDiffAt_mul_right.mdifferentiableAt le_rfl
end
variable (I) (g h : G)
variable [ContMDiffMul I ∞ G]
/-- Left multiplication by `g`. It is meant to mimic the usual notation in Lie groups.
Used mostly through the notation `𝑳`.
Lemmas involving `smoothLeftMul` with the notation `𝑳` usually use `L` instead of `𝑳` in the
names. -/
def smoothLeftMul : C^∞⟮I, G; I, G⟯ :=
⟨(g * ·), contMDiff_mul_left⟩
/-- Right multiplication by `g`. It is meant to mimic the usual notation in Lie groups.
Used mostly through the notation `𝑹`.
Lemmas involving `smoothRightMul` with the notation `𝑹` usually use `R` instead of `𝑹` in the
names. -/
def smoothRightMul : C^∞⟮I, G; I, G⟯ :=
⟨(· * g), contMDiff_mul_right⟩
-- Left multiplication. The abbreviation is `MIL`.
@[inherit_doc] scoped[LieGroup] notation "𝑳" => smoothLeftMul
-- Right multiplication. The abbreviation is `MIR`.
@[inherit_doc] scoped[LieGroup] notation "𝑹" => smoothRightMul
open scoped LieGroup
@[simp]
theorem L_apply : (𝑳 I g) h = g * h :=
rfl
@[simp]
theorem R_apply : (𝑹 I g) h = h * g :=
rfl
@[simp]
theorem L_mul {G : Type*} [Semigroup G] [TopologicalSpace G] [ChartedSpace H G] [ContMDiffMul I ∞ G]
(g h : G) : 𝑳 I (g * h) = (𝑳 I g).comp (𝑳 I h) := by
ext
simp only [ContMDiffMap.comp_apply, L_apply, mul_assoc]
@[simp]
theorem R_mul {G : Type*} [Semigroup G] [TopologicalSpace G] [ChartedSpace H G] [ContMDiffMul I ∞ G]
(g h : G) : 𝑹 I (g * h) = (𝑹 I h).comp (𝑹 I g) := by
ext
simp only [ContMDiffMap.comp_apply, R_apply, mul_assoc]
section
variable {G' : Type*} [Monoid G'] [TopologicalSpace G'] [ChartedSpace H G'] [ContMDiffMul I ∞ G']
(g' : G')
theorem smoothLeftMul_one : (𝑳 I g') 1 = g' :=
mul_one g'
theorem smoothRightMul_one : (𝑹 I g') 1 = g' :=
one_mul g'
end
-- Instance of product
@[to_additive prod]
instance ContMDiffMul.prod {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) (G : Type*) [TopologicalSpace G] [ChartedSpace H G] [Mul G]
[ContMDiffMul I n G] {E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H' : Type*}
[TopologicalSpace H'] (I' : ModelWithCorners 𝕜 E' H') (G' : Type*) [TopologicalSpace G']
[ChartedSpace H' G'] [Mul G'] [ContMDiffMul I' n G'] : ContMDiffMul (I.prod I') n (G × G') :=
{ IsManifold.prod G G' with
contMDiff_mul :=
((contMDiff_fst.comp contMDiff_fst).mul (contMDiff_fst.comp contMDiff_snd)).prodMk
((contMDiff_snd.comp contMDiff_fst).mul (contMDiff_snd.comp contMDiff_snd)) }
end ContMDiffMul
section Monoid
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {n : WithTop ℕ∞}
{H : Type*} [TopologicalSpace H] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {I : ModelWithCorners 𝕜 E H} {G : Type*} [Monoid G]
[TopologicalSpace G] [ChartedSpace H G] [ContMDiffMul I n G] {H' : Type*} [TopologicalSpace H']
{E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {I' : ModelWithCorners 𝕜 E' H'}
{G' : Type*} [Monoid G'] [TopologicalSpace G'] [ChartedSpace H' G'] [ContMDiffMul I' n G']
@[to_additive]
theorem contMDiff_pow : ∀ i : ℕ, ContMDiff I I n fun a : G => a ^ i
| 0 => by simp only [pow_zero]; exact contMDiff_const
| k + 1 => by simpa [pow_succ] using (contMDiff_pow _).mul contMDiff_id
@[deprecated (since := "2024-11-21")] alias smooth_pow := contMDiff_pow
@[deprecated (since := "2024-11-21")] alias smooth_nsmul := contMDiff_nsmul
/-- Morphism of additive `C^n` monoids. -/
structure ContMDiffAddMonoidMorphism (I : ModelWithCorners 𝕜 E H) (I' : ModelWithCorners 𝕜 E' H')
(n : WithTop ℕ∞) (G : Type*) [TopologicalSpace G] [ChartedSpace H G] [AddMonoid G]
(G' : Type*) [TopologicalSpace G'] [ChartedSpace H' G'] [AddMonoid G']
extends G →+ G' where
contMDiff_toFun : ContMDiff I I' n toFun
@[deprecated (since := "2025-01-09")] alias SmoothAddMonoidMorphism := ContMDiffAddMonoidMorphism
/-- Morphism of `C^n` monoids. -/
@[to_additive]
structure ContMDiffMonoidMorphism (I : ModelWithCorners 𝕜 E H) (I' : ModelWithCorners 𝕜 E' H')
(n : WithTop ℕ∞) (G : Type*) [TopologicalSpace G] [ChartedSpace H G] [Monoid G] (G' : Type*)
[TopologicalSpace G'] [ChartedSpace H' G'] [Monoid G'] extends
G →* G' where
contMDiff_toFun : ContMDiff I I' n toFun
@[deprecated (since := "2025-01-09")] alias SmoothMonoidMorphism := ContMDiffMonoidMorphism
@[to_additive]
instance : One (ContMDiffMonoidMorphism I I' n G G') :=
⟨{ contMDiff_toFun := contMDiff_const
toMonoidHom := 1 }⟩
@[to_additive]
instance : Inhabited (ContMDiffMonoidMorphism I I' n G G') :=
⟨1⟩
@[to_additive]
instance : FunLike (ContMDiffMonoidMorphism I I' n G G') G G' where
coe a := a.toFun
coe_injective' f g h := by cases f; cases g; congr; exact DFunLike.ext' h
@[to_additive]
instance : MonoidHomClass (ContMDiffMonoidMorphism I I' n G G') G G' where
map_one f := f.map_one
map_mul f := f.map_mul
@[to_additive]
instance : ContinuousMapClass (ContMDiffMonoidMorphism I I' n G G') G G' where
map_continuous f := f.contMDiff_toFun.continuous
end Monoid
/-! ### Differentiability of finite point-wise sums and products
Finite point-wise products (resp. sums) of `C^n` functions `M → G` (at `x`/on `s`)
into a commutative monoid `G` are `C^n` at `x`/on `s`. -/
section CommMonoid
open Function
variable {ι 𝕜 : Type*} [NontriviallyNormedField 𝕜] {n : WithTop ℕ∞} {H : Type*} [TopologicalSpace H]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {I : ModelWithCorners 𝕜 E H}
{G : Type*} [CommMonoid G] [TopologicalSpace G] [ChartedSpace H G] [ContMDiffMul I n G]
{E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E']
{H' : Type*} [TopologicalSpace H'] {I' : ModelWithCorners 𝕜 E' H'}
{M : Type*} [TopologicalSpace M] [ChartedSpace H' M]
{s : Set M} {x x₀ : M} {t : Finset ι} {f : ι → M → G} {p : ι → Prop}
@[to_additive]
theorem ContMDiffWithinAt.prod (h : ∀ i ∈ t, ContMDiffWithinAt I' I n (f i) s x₀) :
ContMDiffWithinAt I' I n (fun x ↦ ∏ i ∈ t, f i x) s x₀ := by
classical
induction' t using Finset.induction_on with i K iK IH
· simp [contMDiffWithinAt_const]
· simp only [iK, Finset.prod_insert, not_false_iff]
exact (h _ (Finset.mem_insert_self i K)).mul (IH fun j hj ↦ h _ <| Finset.mem_insert_of_mem hj)
@[to_additive]
theorem contMDiffWithinAt_finprod (lf : LocallyFinite fun i ↦ mulSupport <| f i) {x₀ : M}
(h : ∀ i, ContMDiffWithinAt I' I n (f i) s x₀) :
ContMDiffWithinAt I' I n (fun x ↦ ∏ᶠ i, f i x) s x₀ :=
let ⟨_I, hI⟩ := finprod_eventually_eq_prod lf x₀
(ContMDiffWithinAt.prod fun i _hi ↦ h i).congr_of_eventuallyEq
(eventually_nhdsWithin_of_eventually_nhds hI) hI.self_of_nhds
@[to_additive]
theorem contMDiffWithinAt_finset_prod' (h : ∀ i ∈ t, ContMDiffWithinAt I' I n (f i) s x) :
ContMDiffWithinAt I' I n (∏ i ∈ t, f i) s x :=
Finset.prod_induction f (fun f => ContMDiffWithinAt I' I n f s x) (fun _ _ hf hg => hf.mul hg)
(contMDiffWithinAt_const (c := 1)) h
@[to_additive]
theorem contMDiffWithinAt_finset_prod (h : ∀ i ∈ t, ContMDiffWithinAt I' I n (f i) s x) :
ContMDiffWithinAt I' I n (fun x => ∏ i ∈ t, f i x) s x := by
simp only [← Finset.prod_apply]
exact contMDiffWithinAt_finset_prod' h
@[to_additive]
theorem ContMDiffAt.prod (h : ∀ i ∈ t, ContMDiffAt I' I n (f i) x₀) :
ContMDiffAt I' I n (fun x ↦ ∏ i ∈ t, f i x) x₀ := by
simp only [← contMDiffWithinAt_univ] at *
exact ContMDiffWithinAt.prod h
@[to_additive]
theorem contMDiffAt_finprod
(lf : LocallyFinite fun i ↦ mulSupport <| f i) (h : ∀ i, ContMDiffAt I' I n (f i) x₀) :
ContMDiffAt I' I n (fun x ↦ ∏ᶠ i, f i x) x₀ :=
contMDiffWithinAt_finprod lf h
@[to_additive]
theorem contMDiffAt_finset_prod' (h : ∀ i ∈ t, ContMDiffAt I' I n (f i) x) :
ContMDiffAt I' I n (∏ i ∈ t, f i) x :=
contMDiffWithinAt_finset_prod' h
@[to_additive]
theorem contMDiffAt_finset_prod (h : ∀ i ∈ t, ContMDiffAt I' I n (f i) x) :
ContMDiffAt I' I n (fun x => ∏ i ∈ t, f i x) x :=
contMDiffWithinAt_finset_prod h
@[to_additive]
theorem contMDiffOn_finprod
(lf : LocallyFinite fun i ↦ Function.mulSupport <| f i) (h : ∀ i, ContMDiffOn I' I n (f i) s) :
ContMDiffOn I' I n (fun x ↦ ∏ᶠ i, f i x) s := fun x hx ↦
contMDiffWithinAt_finprod lf fun i ↦ h i x hx
@[to_additive]
theorem contMDiffOn_finset_prod' (h : ∀ i ∈ t, ContMDiffOn I' I n (f i) s) :
ContMDiffOn I' I n (∏ i ∈ t, f i) s := fun x hx =>
contMDiffWithinAt_finset_prod' fun i hi => h i hi x hx
@[to_additive]
theorem contMDiffOn_finset_prod (h : ∀ i ∈ t, ContMDiffOn I' I n (f i) s) :
ContMDiffOn I' I n (fun x => ∏ i ∈ t, f i x) s := fun x hx =>
contMDiffWithinAt_finset_prod fun i hi => h i hi x hx
@[to_additive]
theorem ContMDiff.prod (h : ∀ i ∈ t, ContMDiff I' I n (f i)) :
ContMDiff I' I n fun x ↦ ∏ i ∈ t, f i x :=
fun x ↦ ContMDiffAt.prod fun j hj ↦ h j hj x
@[to_additive]
theorem contMDiff_finset_prod' (h : ∀ i ∈ t, ContMDiff I' I n (f i)) :
ContMDiff I' I n (∏ i ∈ t, f i) := fun x => contMDiffAt_finset_prod' fun i hi => h i hi x
@[to_additive]
theorem contMDiff_finset_prod (h : ∀ i ∈ t, ContMDiff I' I n (f i)) :
ContMDiff I' I n fun x => ∏ i ∈ t, f i x := fun x =>
contMDiffAt_finset_prod fun i hi => h i hi x
@[to_additive]
theorem contMDiff_finprod (h : ∀ i, ContMDiff I' I n (f i))
(hfin : LocallyFinite fun i => mulSupport (f i)) : ContMDiff I' I n fun x => ∏ᶠ i, f i x :=
fun x ↦ contMDiffAt_finprod hfin fun i ↦ h i x
@[to_additive]
theorem contMDiff_finprod_cond (hc : ∀ i, p i → ContMDiff I' I n (f i))
(hf : LocallyFinite fun i => mulSupport (f i)) :
ContMDiff I' I n fun x => ∏ᶠ (i) (_ : p i), f i x := by
simp only [← finprod_subtype_eq_finprod_cond]
exact contMDiff_finprod (fun i => hc i i.2) (hf.comp_injective Subtype.coe_injective)
@[deprecated (since := "2024-11-21")] alias smoothAt_finprod := contMDiffAt_finprod
@[deprecated (since := "2024-11-21")] alias smoothAt_finsum := contMDiffAt_finsum
@[deprecated (since := "2024-11-21")]
alias smoothWithinAt_finset_prod' := contMDiffWithinAt_finset_prod'
@[deprecated (since := "2024-11-21")]
alias smoothWithinAt_finset_sum' := contMDiffWithinAt_finset_sum'
@[deprecated (since := "2024-11-21")]
alias smoothWithinAt_finset_prod := contMDiffWithinAt_finset_prod
@[deprecated (since := "2024-11-21")]
alias smoothWithinAt_finset_sum := contMDiffWithinAt_finset_sum
@[deprecated (since := "2024-11-21")] alias smoothAt_finset_prod' := contMDiffAt_finset_prod'
@[deprecated (since := "2024-11-21")] alias smoothAt_finset_sum' := contMDiffAt_finset_sum'
@[deprecated (since := "2024-11-21")] alias smoothAt_finset_prod := contMDiffAt_finset_prod
@[deprecated (since := "2024-11-21")] alias smoothAt_finset_sum := contMDiffAt_finset_sum
@[deprecated (since := "2024-11-21")] alias smoothOn_finset_prod' := contMDiffOn_finset_prod'
@[deprecated (since := "2024-11-21")] alias smoothOn_finset_sum' := contMDiffOn_finset_sum'
@[deprecated (since := "2024-11-21")] alias smoothOn_finset_prod := contMDiffOn_finset_prod
@[deprecated (since := "2024-11-21")] alias smoothOn_finset_sum := contMDiffOn_finset_sum
@[deprecated (since := "2024-11-21")] alias smooth_finset_prod' := contMDiffOn_finset_prod'
@[deprecated (since := "2024-11-21")] alias smooth_finset_sum' := contMDiffOn_finset_sum'
@[deprecated (since := "2024-11-21")] alias smooth_finset_prod := contMDiff_finset_prod
@[deprecated (since := "2024-11-21")] alias smooth_finset_sum := contMDiff_finset_sum
@[deprecated (since := "2024-11-21")] alias smooth_finprod := contMDiff_finprod
@[deprecated (since := "2024-11-21")] alias smooth_finsum := contMDiff_finsum
@[deprecated (since := "2024-11-21")] alias smooth_finprod_cond := contMDiff_finprod_cond
@[deprecated (since := "2024-11-21")] alias smooth_finsum_cond := contMDiff_finsum_cond
end CommMonoid
section
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {E : Type*} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {n : WithTop ℕ∞}
instance instContMDiffAddSelf : ContMDiffAdd 𝓘(𝕜, E) n E := by
constructor
rw [← modelWithCornersSelf_prod, chartedSpaceSelf_prod]
exact contDiff_add.contMDiff
end
section DivConst
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {n : WithTop ℕ∞}
{H : Type*} [TopologicalSpace H] {E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {I : ModelWithCorners 𝕜 E H}
{G : Type*} [DivInvMonoid G] [TopologicalSpace G] [ChartedSpace H G] [ContMDiffMul I n G]
{E' : Type*} [NormedAddCommGroup E']
[NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H'] {I' : ModelWithCorners 𝕜 E' H'}
{M : Type*} [TopologicalSpace M] [ChartedSpace H' M]
variable {f : M → G} {s : Set M} {x : M} (c : G)
@[to_additive]
theorem ContMDiffWithinAt.div_const (hf : ContMDiffWithinAt I' I n f s x) :
ContMDiffWithinAt I' I n (fun x ↦ f x / c) s x := by
simpa only [div_eq_mul_inv] using hf.mul contMDiffWithinAt_const
@[to_additive]
nonrec theorem ContMDiffAt.div_const (hf : ContMDiffAt I' I n f x) :
ContMDiffAt I' I n (fun x ↦ f x / c) x :=
hf.div_const c
@[to_additive]
theorem ContMDiffOn.div_const (hf : ContMDiffOn I' I n f s) :
ContMDiffOn I' I n (fun x ↦ f x / c) s := fun x hx => (hf x hx).div_const c
@[to_additive]
theorem ContMDiff.div_const (hf : ContMDiff I' I n f) :
ContMDiff I' I n (fun x ↦ f x / c) := fun x => (hf x).div_const c
@[deprecated (since := "2024-11-21")] alias SmoothWithinAt.div_const := ContMDiffWithinAt.div_const
@[deprecated (since := "2024-11-21")] alias SmoothAt.div_const := ContMDiffAt.div_const
@[deprecated (since := "2024-11-21")] alias SmoothOn.div_const := ContMDiffOn.div_const
@[deprecated (since := "2024-11-21")] alias Smooth.div_const := ContMDiff.div_const
end DivConst
| Mathlib/Geometry/Manifold/Algebra/Monoid.lean | 536 | 538 | |
/-
Copyright (c) 2022 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis, Heather Macbeth, Johan Commelin
-/
import Mathlib.RingTheory.WittVector.Domain
import Mathlib.RingTheory.WittVector.MulCoeff
import Mathlib.RingTheory.DiscreteValuationRing.Basic
import Mathlib.Tactic.LinearCombination
/-!
# Witt vectors over a perfect ring
This file establishes that Witt vectors over a perfect field are a discrete valuation ring.
When `k` is a perfect ring, a nonzero `a : 𝕎 k` can be written as `p^m * b` for some `m : ℕ` and
`b : 𝕎 k` with nonzero 0th coefficient.
When `k` is also a field, this `b` can be chosen to be a unit of `𝕎 k`.
## Main declarations
* `WittVector.exists_eq_pow_p_mul`: the existence of this element `b` over a perfect ring
* `WittVector.exists_eq_pow_p_mul'`: the existence of this unit `b` over a perfect field
* `WittVector.isDiscreteValuationRing`: `𝕎 k` is a discrete valuation ring if `k` is a perfect field
-/
noncomputable section
namespace WittVector
variable {p : ℕ} [hp : Fact p.Prime]
local notation "𝕎" => WittVector p
section CommRing
variable {k : Type*} [CommRing k] [CharP k p]
/-- This is the `n+1`st coefficient of our inverse. -/
def succNthValUnits (n : ℕ) (a : Units k) (A : 𝕎 k) (bs : Fin (n + 1) → k) : k :=
-↑(a⁻¹ ^ p ^ (n + 1)) *
(A.coeff (n + 1) * ↑(a⁻¹ ^ p ^ (n + 1)) + nthRemainder p n (truncateFun (n + 1) A) bs)
/--
Recursively defines the sequence of coefficients for the inverse to a Witt vector whose first entry
is a unit.
-/
noncomputable def inverseCoeff (a : Units k) (A : 𝕎 k) : ℕ → k
| 0 => ↑a⁻¹
| n + 1 => succNthValUnits n a A fun i => inverseCoeff a A i.val
/--
Upgrade a Witt vector `A` whose first entry `A.coeff 0` is a unit to be, itself, a unit in `𝕎 k`.
-/
def mkUnit {a : Units k} {A : 𝕎 k} (hA : A.coeff 0 = a) : Units (𝕎 k) :=
Units.mkOfMulEqOne A (@WittVector.mk' p _ (inverseCoeff a A)) (by
ext n
induction' n with n _
· simp [WittVector.mul_coeff_zero, inverseCoeff, hA]
let H_coeff := A.coeff (n + 1) * ↑(a⁻¹ ^ p ^ (n + 1)) +
nthRemainder p n (truncateFun (n + 1) A) fun i : Fin (n + 1) => inverseCoeff a A i
have H := Units.mul_inv (a ^ p ^ (n + 1))
linear_combination (norm := skip) -H_coeff * H
have ha : (a : k) ^ p ^ (n + 1) = ↑(a ^ p ^ (n + 1)) := by norm_cast
have ha_inv : (↑a⁻¹ : k) ^ p ^ (n + 1) = ↑(a ^ p ^ (n + 1))⁻¹ := by norm_cast
simp only [nthRemainder_spec, inverseCoeff, succNthValUnits, hA,
one_coeff_eq_of_pos, Nat.succ_pos', ha_inv, ha, inv_pow]
ring!)
@[simp]
theorem coe_mkUnit {a : Units k} {A : 𝕎 k} (hA : A.coeff 0 = a) : (mkUnit hA : 𝕎 k) = A :=
rfl
end CommRing
section Field
variable {k : Type*} [Field k] [CharP k p]
theorem isUnit_of_coeff_zero_ne_zero (x : 𝕎 k) (hx : x.coeff 0 ≠ 0) : IsUnit x := by
let y : kˣ := Units.mk0 (x.coeff 0) hx
have hy : x.coeff 0 = y := rfl
exact (mkUnit hy).isUnit
variable (p)
theorem irreducible : Irreducible (p : 𝕎 k) := by
have hp : ¬IsUnit (p : 𝕎 k) := by
intro hp
simpa only [constantCoeff_apply, coeff_p_zero, not_isUnit_zero] using
(constantCoeff : WittVector p k →+* _).isUnit_map hp
refine ⟨hp, fun a b hab => ?_⟩
obtain ⟨ha0, hb0⟩ : a ≠ 0 ∧ b ≠ 0 := by
rw [← mul_ne_zero_iff]; intro h; rw [h] at hab; exact p_nonzero p k hab
obtain ⟨m, a, ha, rfl⟩ := verschiebung_nonzero ha0
obtain ⟨n, b, hb, rfl⟩ := verschiebung_nonzero hb0
cases m; · exact Or.inl (isUnit_of_coeff_zero_ne_zero a ha)
rcases n with - | n; · exact Or.inr (isUnit_of_coeff_zero_ne_zero b hb)
rw [iterate_verschiebung_mul] at hab
apply_fun fun x => coeff x 1 at hab
simp only [coeff_p_one, Nat.add_succ, add_comm _ n, Function.iterate_succ', Function.comp_apply,
verschiebung_coeff_add_one, verschiebung_coeff_zero] at hab
exact (one_ne_zero hab).elim
end Field
section PerfectRing
variable {k : Type*} [CommRing k] [CharP k p] [PerfectRing k p]
theorem exists_eq_pow_p_mul (a : 𝕎 k) (ha : a ≠ 0) :
∃ (m : ℕ) (b : 𝕎 k), b.coeff 0 ≠ 0 ∧ a = (p : 𝕎 k) ^ m * b := by
obtain ⟨m, c, hc, hcm⟩ := WittVector.verschiebung_nonzero ha
obtain ⟨b, rfl⟩ := (frobenius_bijective p k).surjective.iterate m c
rw [WittVector.iterate_frobenius_coeff] at hc
have := congr_fun (WittVector.verschiebung_frobenius_comm.comp_iterate m) b
simp only [Function.comp_apply] at this
rw [← this] at hcm
refine ⟨m, b, ?_, ?_⟩
· contrapose! hc
simp [hc, zero_pow <| pow_ne_zero _ hp.out.ne_zero]
· simp_rw [← mul_left_iterate (p : 𝕎 k) m]
convert hcm using 2
ext1 x
rw [mul_comm, ← WittVector.verschiebung_frobenius x]; rfl
end PerfectRing
section PerfectField
variable {k : Type*} [Field k] [CharP k p] [PerfectRing k p]
theorem exists_eq_pow_p_mul' (a : 𝕎 k) (ha : a ≠ 0) :
∃ (m : ℕ) (b : Units (𝕎 k)), a = (p : 𝕎 k) ^ m * b := by
obtain ⟨m, b, h₁, h₂⟩ := exists_eq_pow_p_mul a ha
let b₀ := Units.mk0 (b.coeff 0) h₁
have hb₀ : b.coeff 0 = b₀ := rfl
exact ⟨m, mkUnit hb₀, h₂⟩
/-
Note: The following lemma should be an instance, but it seems to cause some
exponential blowups in certain typeclass resolution problems.
See the following Lean4 issue as well as the zulip discussion linked there:
https://github.com/leanprover/lean4/issues/1102
-/
/-- The ring of Witt Vectors of a perfect field of positive characteristic is a DVR.
-/
theorem isDiscreteValuationRing : IsDiscreteValuationRing (𝕎 k) :=
IsDiscreteValuationRing.ofHasUnitMulPowIrreducibleFactorization (by
refine ⟨p, irreducible p, fun {x} hx => ?_⟩
obtain ⟨n, b, hb⟩ := exists_eq_pow_p_mul' x hx
exact ⟨n, b, hb.symm⟩)
end PerfectField
end WittVector
| Mathlib/RingTheory/WittVector/DiscreteValuationRing.lean | 160 | 164 | |
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Data.Set.Image
import Mathlib.Data.Set.BooleanAlgebra
/-!
# Sets in sigma types
This file defines `Set.sigma`, the indexed sum of sets.
-/
namespace Set
variable {ι ι' : Type*} {α : ι → Type*} {s s₁ s₂ : Set ι} {t t₁ t₂ : ∀ i, Set (α i)}
{u : Set (Σ i, α i)} {x : Σ i, α i} {i j : ι} {a : α i}
@[simp]
theorem range_sigmaMk (i : ι) : range (Sigma.mk i : α i → Sigma α) = Sigma.fst ⁻¹' {i} := by
apply Subset.antisymm
· rintro _ ⟨b, rfl⟩
simp
· rintro ⟨x, y⟩ (rfl | _)
exact mem_range_self y
theorem preimage_image_sigmaMk_of_ne (h : i ≠ j) (s : Set (α j)) :
Sigma.mk i ⁻¹' (Sigma.mk j '' s) = ∅ := by
ext x
| simp [h.symm]
theorem image_sigmaMk_preimage_sigmaMap_subset {β : ι' → Type*} (f : ι → ι')
(g : ∀ i, α i → β (f i)) (i : ι) (s : Set (β (f i))) :
| Mathlib/Data/Set/Sigma.lean | 31 | 34 |
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Eric Wieser
-/
import Mathlib.Algebra.Group.Fin.Tuple
import Mathlib.Data.Matrix.RowCol
import Mathlib.Data.Fin.VecNotation
import Mathlib.Tactic.FinCases
import Mathlib.Algebra.BigOperators.Fin
/-!
# Matrix and vector notation
This file includes `simp` lemmas for applying operations in `Data.Matrix.Basic` to values built out
of the matrix notation `![a, b] = vecCons a (vecCons b vecEmpty)` defined in
`Data.Fin.VecNotation`.
This also provides the new notation `!![a, b; c, d] = Matrix.of ![![a, b], ![c, d]]`.
This notation also works for empty matrices; `!![,,,] : Matrix (Fin 0) (Fin 3)` and
`!![;;;] : Matrix (Fin 3) (Fin 0)`.
## Implementation notes
The `simp` lemmas require that one of the arguments is of the form `vecCons _ _`.
This ensures `simp` works with entries only when (some) entries are already given.
In other words, this notation will only appear in the output of `simp` if it
already appears in the input.
## Notations
This file provide notation `!![a, b; c, d]` for matrices, which corresponds to
`Matrix.of ![![a, b], ![c, d]]`.
## Examples
Examples of usage can be found in the `MathlibTest/matrix.lean` file.
-/
namespace Matrix
universe u uₘ uₙ uₒ
variable {α : Type u} {o n m : ℕ} {m' : Type uₘ} {n' : Type uₙ} {o' : Type uₒ}
open Matrix
section toExpr
open Lean Qq
open Qq in
/-- `Matrix.mkLiteralQ !![a, b; c, d]` produces the term `q(!![$a, $b; $c, $d])`. -/
def mkLiteralQ {u : Level} {α : Q(Type u)} {m n : Nat} (elems : Matrix (Fin m) (Fin n) Q($α)) :
Q(Matrix (Fin $m) (Fin $n) $α) :=
let elems := PiFin.mkLiteralQ (α := q(Fin $n → $α)) fun i => PiFin.mkLiteralQ fun j => elems i j
q(Matrix.of $elems)
/-- Matrices can be reflected whenever their entries can. We insert a `Matrix.of` to
prevent immediate decay to a function. -/
protected instance toExpr [ToLevel.{u}] [ToLevel.{uₘ}] [ToLevel.{uₙ}]
[Lean.ToExpr α] [Lean.ToExpr m'] [Lean.ToExpr n'] [Lean.ToExpr (m' → n' → α)] :
Lean.ToExpr (Matrix m' n' α) :=
have eα : Q(Type $(toLevel.{u})) := toTypeExpr α
have em' : Q(Type $(toLevel.{uₘ})) := toTypeExpr m'
have en' : Q(Type $(toLevel.{uₙ})) := toTypeExpr n'
{ toTypeExpr :=
q(Matrix $eα $em' $en')
toExpr := fun M =>
have eM : Q($em' → $en' → $eα) := toExpr (show m' → n' → α from M)
q(Matrix.of $eM) }
end toExpr
section Parser
open Lean Meta Elab Term Macro TSyntax PrettyPrinter.Delaborator SubExpr
/-- Notation for m×n matrices, aka `Matrix (Fin m) (Fin n) α`.
For instance:
* `!![a, b, c; d, e, f]` is the matrix with two rows and three columns, of type
`Matrix (Fin 2) (Fin 3) α`
* `!![a, b, c]` is a row vector of type `Matrix (Fin 1) (Fin 3) α` (see also `Matrix.row`).
* `!![a; b; c]` is a column vector of type `Matrix (Fin 3) (Fin 1) α` (see also `Matrix.col`).
This notation implements some special cases:
* `![,,]`, with `n` `,`s, is a term of type `Matrix (Fin 0) (Fin n) α`
* `![;;]`, with `m` `;`s, is a term of type `Matrix (Fin m) (Fin 0) α`
* `![]` is the 0×0 matrix
Note that vector notation is provided elsewhere (by `Matrix.vecNotation`) as `![a, b, c]`.
Under the hood, `!![a, b, c; d, e, f]` is syntax for `Matrix.of ![![a, b, c], ![d, e, f]]`.
-/
syntax (name := matrixNotation)
"!![" ppRealGroup(sepBy1(ppGroup(term,+,?), ";", "; ", allowTrailingSep)) "]" : term
@[inherit_doc matrixNotation]
syntax (name := matrixNotationRx0) "!![" ";"+ "]" : term
@[inherit_doc matrixNotation]
syntax (name := matrixNotation0xC) "!![" ","* "]" : term
macro_rules
| `(!![$[$[$rows],*];*]) => do
let m := rows.size
let n := if h : 0 < m then rows[0].size else 0
let rowVecs ← rows.mapM fun row : Array Term => do
unless row.size = n do
Macro.throwErrorAt (mkNullNode row) s!"\
Rows must be of equal length; this row has {row.size} items, \
the previous rows have {n}"
`(![$row,*])
`(@Matrix.of (Fin $(quote m)) (Fin $(quote n)) _ ![$rowVecs,*])
| `(!![$[;%$semicolons]*]) => do
let emptyVec ← `(![])
let emptyVecs := semicolons.map (fun _ => emptyVec)
`(@Matrix.of (Fin $(quote semicolons.size)) (Fin 0) _ ![$emptyVecs,*])
| `(!![$[,%$commas]*]) => `(@Matrix.of (Fin 0) (Fin $(quote commas.size)) _ ![])
/-- Delaborator for the `!![]` notation. -/
@[app_delab DFunLike.coe]
def delabMatrixNotation : Delab := whenNotPPOption getPPExplicit <| whenPPOption getPPNotation <|
withOverApp 6 do
let mkApp3 (.const ``Matrix.of _) (.app (.const ``Fin _) em) (.app (.const ``Fin _) en) _ :=
(← getExpr).appFn!.appArg! | failure
let some m ← withNatValue em (pure ∘ some) | failure
let some n ← withNatValue en (pure ∘ some) | failure
withAppArg do
if m = 0 then
guard <| (← getExpr).isAppOfArity ``vecEmpty 1
let commas := .replicate n (mkAtom ",")
`(!![$[,%$commas]*])
else
if n = 0 then
let `(![$[![]%$evecs],*]) ← delab | failure
`(!![$[;%$evecs]*])
else
let `(![$[![$[$melems],*]],*]) ← delab | failure
`(!![$[$[$melems],*];*])
end Parser
variable (a b : ℕ)
/-- Use `![...]` notation for displaying a `Fin`-indexed matrix, for example:
```
#eval !![1, 2; 3, 4] + !![3, 4; 5, 6] -- !![4, 6; 8, 10]
```
-/
instance repr [Repr α] : Repr (Matrix (Fin m) (Fin n) α) where
reprPrec f _p :=
(Std.Format.bracket "!![" · "]") <|
(Std.Format.joinSep · (";" ++ Std.Format.line)) <|
(List.finRange m).map fun i =>
Std.Format.fill <| -- wrap line in a single place rather than all at once
(Std.Format.joinSep · ("," ++ Std.Format.line)) <|
(List.finRange n).map fun j => _root_.repr (f i j)
@[simp]
theorem cons_val' (v : n' → α) (B : Fin m → n' → α) (i j) :
vecCons v B i j = vecCons (v j) (fun i => B i j) i := by refine Fin.cases ?_ ?_ i <;> simp
@[simp]
theorem head_val' (B : Fin m.succ → n' → α) (j : n') : (vecHead fun i => B i j) = vecHead B j :=
rfl
@[simp]
theorem tail_val' (B : Fin m.succ → n' → α) (j : n') :
(vecTail fun i => B i j) = fun i => vecTail B i j := rfl
section DotProduct
variable [AddCommMonoid α] [Mul α]
@[simp]
theorem dotProduct_empty (v w : Fin 0 → α) : dotProduct v w = 0 :=
Finset.sum_empty
@[simp]
theorem cons_dotProduct (x : α) (v : Fin n → α) (w : Fin n.succ → α) :
dotProduct (vecCons x v) w = x * vecHead w + dotProduct v (vecTail w) := by
simp [dotProduct, Fin.sum_univ_succ, vecHead, vecTail]
@[simp]
theorem dotProduct_cons (v : Fin n.succ → α) (x : α) (w : Fin n → α) :
dotProduct v (vecCons x w) = vecHead v * x + dotProduct (vecTail v) w := by
simp [dotProduct, Fin.sum_univ_succ, vecHead, vecTail]
theorem cons_dotProduct_cons (x : α) (v : Fin n → α) (y : α) (w : Fin n → α) :
dotProduct (vecCons x v) (vecCons y w) = x * y + dotProduct v w := by simp
end DotProduct
section ColRow
variable {ι : Type*}
@[simp]
theorem replicateCol_empty (v : Fin 0 → α) : replicateCol ι v = vecEmpty :=
empty_eq _
@[deprecated (since := "2025-03-20")] alias col_empty := replicateCol_empty
@[simp]
theorem replicateCol_cons (x : α) (u : Fin m → α) :
replicateCol ι (vecCons x u) = of (vecCons (fun _ => x) (replicateCol ι u)) := by
ext i j
refine Fin.cases ?_ ?_ i <;> simp [vecHead, vecTail]
@[deprecated (since := "2025-03-20")] alias col_cons := replicateCol_cons
@[simp]
theorem replicateRow_empty : replicateRow ι (vecEmpty : Fin 0 → α) = of fun _ => vecEmpty := rfl
@[deprecated (since := "2025-03-20")] alias row_empty := replicateRow_empty
@[simp]
theorem replicateRow_cons (x : α) (u : Fin m → α) :
replicateRow ι (vecCons x u) = of fun _ => vecCons x u :=
rfl
@[deprecated (since := "2025-03-20")] alias row_cons := replicateRow_cons
end ColRow
section Transpose
@[simp]
theorem transpose_empty_rows (A : Matrix m' (Fin 0) α) : Aᵀ = of ![] :=
empty_eq _
@[simp]
theorem transpose_empty_cols (A : Matrix (Fin 0) m' α) : Aᵀ = of fun _ => ![] :=
funext fun _ => empty_eq _
@[simp]
theorem cons_transpose (v : n' → α) (A : Matrix (Fin m) n' α) :
(of (vecCons v A))ᵀ = of fun i => vecCons (v i) (Aᵀ i) := by
ext i j
refine Fin.cases ?_ ?_ j <;> simp
@[simp]
theorem head_transpose (A : Matrix m' (Fin n.succ) α) :
vecHead (of.symm Aᵀ) = vecHead ∘ of.symm A :=
rfl
@[simp]
theorem tail_transpose (A : Matrix m' (Fin n.succ) α) : vecTail (of.symm Aᵀ) = (vecTail ∘ A)ᵀ := by
ext i j
rfl
end Transpose
section Mul
variable [NonUnitalNonAssocSemiring α]
@[simp]
theorem empty_mul [Fintype n'] (A : Matrix (Fin 0) n' α) (B : Matrix n' o' α) : A * B = of ![] :=
empty_eq _
@[simp]
theorem empty_mul_empty (A : Matrix m' (Fin 0) α) (B : Matrix (Fin 0) o' α) : A * B = 0 :=
rfl
@[simp]
theorem mul_empty [Fintype n'] (A : Matrix m' n' α) (B : Matrix n' (Fin 0) α) :
A * B = of fun _ => ![] :=
funext fun _ => empty_eq _
theorem mul_val_succ [Fintype n'] (A : Matrix (Fin m.succ) n' α) (B : Matrix n' o' α) (i : Fin m)
(j : o') : (A * B) i.succ j = (of (vecTail (of.symm A)) * B) i j :=
rfl
@[simp]
theorem cons_mul [Fintype n'] (v : n' → α) (A : Fin m → n' → α) (B : Matrix n' o' α) :
of (vecCons v A) * B = of (vecCons (v ᵥ* B) (of.symm (of A * B))) := by
ext i j
refine Fin.cases ?_ ?_ i
· rfl
simp [mul_val_succ]
end Mul
section VecMul
variable [NonUnitalNonAssocSemiring α]
@[simp]
theorem empty_vecMul (v : Fin 0 → α) (B : Matrix (Fin 0) o' α) : v ᵥ* B = 0 :=
rfl
@[simp]
theorem vecMul_empty [Fintype n'] (v : n' → α) (B : Matrix n' (Fin 0) α) : v ᵥ* B = ![] :=
empty_eq _
@[simp]
theorem cons_vecMul (x : α) (v : Fin n → α) (B : Fin n.succ → o' → α) :
vecCons x v ᵥ* of B = x • vecHead B + v ᵥ* of (vecTail B) := by
ext i
simp [vecMul]
@[simp]
theorem vecMul_cons (v : Fin n.succ → α) (w : o' → α) (B : Fin n → o' → α) :
v ᵥ* of (vecCons w B) = vecHead v • w + vecTail v ᵥ* of B := by
ext i
simp [vecMul]
theorem cons_vecMul_cons (x : α) (v : Fin n → α) (w : o' → α) (B : Fin n → o' → α) :
vecCons x v ᵥ* of (vecCons w B) = x • w + v ᵥ* of B := by simp
end VecMul
section MulVec
variable [NonUnitalNonAssocSemiring α]
@[simp]
theorem empty_mulVec [Fintype n'] (A : Matrix (Fin 0) n' α) (v : n' → α) : A *ᵥ v = ![] :=
empty_eq _
@[simp]
theorem mulVec_empty (A : Matrix m' (Fin 0) α) (v : Fin 0 → α) : A *ᵥ v = 0 :=
rfl
@[simp]
theorem cons_mulVec [Fintype n'] (v : n' → α) (A : Fin m → n' → α) (w : n' → α) :
(of <| vecCons v A) *ᵥ w = vecCons (dotProduct v w) (of A *ᵥ w) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp [mulVec]
@[simp]
theorem mulVec_cons {α} [NonUnitalCommSemiring α] (A : m' → Fin n.succ → α) (x : α)
(v : Fin n → α) : (of A) *ᵥ (vecCons x v) = x • vecHead ∘ A + (of (vecTail ∘ A)) *ᵥ v := by
ext i
simp [mulVec, mul_comm]
end MulVec
section VecMulVec
variable [NonUnitalNonAssocSemiring α]
@[simp]
theorem empty_vecMulVec (v : Fin 0 → α) (w : n' → α) : vecMulVec v w = ![] :=
empty_eq _
@[simp]
theorem vecMulVec_empty (v : m' → α) (w : Fin 0 → α) : vecMulVec v w = of fun _ => ![] :=
funext fun _ => empty_eq _
@[simp]
theorem cons_vecMulVec (x : α) (v : Fin m → α) (w : n' → α) :
vecMulVec (vecCons x v) w = vecCons (x • w) (vecMulVec v w) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp [vecMulVec]
@[simp]
theorem vecMulVec_cons (v : m' → α) (x : α) (w : Fin n → α) :
vecMulVec v (vecCons x w) = of fun i => v i • vecCons x w := rfl
end VecMulVec
section SMul
variable [NonUnitalNonAssocSemiring α]
theorem smul_mat_empty {m' : Type*} (x : α) (A : Fin 0 → m' → α) : x • A = ![] :=
empty_eq _
theorem smul_mat_cons (x : α) (v : n' → α) (A : Fin m → n' → α) :
x • vecCons v A = vecCons (x • v) (x • A) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp
end SMul
section Submatrix
@[simp]
theorem submatrix_empty (A : Matrix m' n' α) (row : Fin 0 → m') (col : o' → n') :
submatrix A row col = ![] :=
empty_eq _
@[simp]
theorem submatrix_cons_row (A : Matrix m' n' α) (i : m') (row : Fin m → m') (col : o' → n') :
submatrix A (vecCons i row) col = vecCons (fun j => A i (col j)) (submatrix A row col) := by
ext i j
refine Fin.cases ?_ ?_ i <;> simp [submatrix]
/-- Updating a row then removing it is the same as removing it. -/
@[simp]
theorem submatrix_updateRow_succAbove (A : Matrix (Fin m.succ) n' α) (v : n' → α) (f : o' → n')
(i : Fin m.succ) : (A.updateRow i v).submatrix i.succAbove f = A.submatrix i.succAbove f :=
| ext fun r s => (congr_fun (updateRow_ne (Fin.succAbove_ne i r) : _ = A _) (f s) :)
/-- Updating a column then removing it is the same as removing it. -/
@[simp]
| Mathlib/Data/Matrix/Notation.lean | 396 | 399 |
/-
Copyright (c) 2022 Yaël Dillies, Sara Rousta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Sara Rousta
-/
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Interval.Set.OrderEmbedding
import Mathlib.Order.SetNotation
/-!
# Properties of unbundled upper/lower sets
This file proves results on `IsUpperSet` and `IsLowerSet`, including their interactions with
set operations, images, preimages and order duals, and properties that reflect stronger assumptions
on the underlying order (such as `PartialOrder` and `LinearOrder`).
## TODO
* Lattice structure on antichains.
* Order equivalence between upper/lower sets and antichains.
-/
open OrderDual Set
variable {α β : Type*} {ι : Sort*} {κ : ι → Sort*}
attribute [aesop norm unfold] IsUpperSet IsLowerSet
section LE
variable [LE α] {s t : Set α} {a : α}
theorem isUpperSet_empty : IsUpperSet (∅ : Set α) := fun _ _ _ => id
theorem isLowerSet_empty : IsLowerSet (∅ : Set α) := fun _ _ _ => id
theorem isUpperSet_univ : IsUpperSet (univ : Set α) := fun _ _ _ => id
theorem isLowerSet_univ : IsLowerSet (univ : Set α) := fun _ _ _ => id
theorem IsUpperSet.compl (hs : IsUpperSet s) : IsLowerSet sᶜ := fun _a _b h hb ha => hb <| hs h ha
theorem IsLowerSet.compl (hs : IsLowerSet s) : IsUpperSet sᶜ := fun _a _b h hb ha => hb <| hs h ha
@[simp]
theorem isUpperSet_compl : IsUpperSet sᶜ ↔ IsLowerSet s :=
⟨fun h => by
convert h.compl
rw [compl_compl], IsLowerSet.compl⟩
@[simp]
theorem isLowerSet_compl : IsLowerSet sᶜ ↔ IsUpperSet s :=
⟨fun h => by
convert h.compl
rw [compl_compl], IsUpperSet.compl⟩
theorem IsUpperSet.union (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∪ t) :=
fun _ _ h => Or.imp (hs h) (ht h)
theorem IsLowerSet.union (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∪ t) :=
fun _ _ h => Or.imp (hs h) (ht h)
theorem IsUpperSet.inter (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∩ t) :=
fun _ _ h => And.imp (hs h) (ht h)
theorem IsLowerSet.inter (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∩ t) :=
fun _ _ h => And.imp (hs h) (ht h)
theorem isUpperSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋃₀ S) :=
fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩
theorem isLowerSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋃₀ S) :=
fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩
theorem isUpperSet_iUnion {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋃ i, f i) :=
isUpperSet_sUnion <| forall_mem_range.2 hf
theorem isLowerSet_iUnion {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋃ i, f i) :=
isLowerSet_sUnion <| forall_mem_range.2 hf
theorem isUpperSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) :
IsUpperSet (⋃ (i) (j), f i j) :=
isUpperSet_iUnion fun i => isUpperSet_iUnion <| hf i
theorem isLowerSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) :
IsLowerSet (⋃ (i) (j), f i j) :=
isLowerSet_iUnion fun i => isLowerSet_iUnion <| hf i
theorem isUpperSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋂₀ S) :=
fun _ _ h => forall₂_imp fun s hs => hf s hs h
theorem isLowerSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋂₀ S) :=
fun _ _ h => forall₂_imp fun s hs => hf s hs h
theorem isUpperSet_iInter {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋂ i, f i) :=
isUpperSet_sInter <| forall_mem_range.2 hf
theorem isLowerSet_iInter {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋂ i, f i) :=
isLowerSet_sInter <| forall_mem_range.2 hf
theorem isUpperSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) :
IsUpperSet (⋂ (i) (j), f i j) :=
isUpperSet_iInter fun i => isUpperSet_iInter <| hf i
theorem isLowerSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) :
IsLowerSet (⋂ (i) (j), f i j) :=
isLowerSet_iInter fun i => isLowerSet_iInter <| hf i
@[simp]
theorem isLowerSet_preimage_ofDual_iff : IsLowerSet (ofDual ⁻¹' s) ↔ IsUpperSet s :=
Iff.rfl
@[simp]
theorem isUpperSet_preimage_ofDual_iff : IsUpperSet (ofDual ⁻¹' s) ↔ IsLowerSet s :=
Iff.rfl
@[simp]
theorem isLowerSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsLowerSet (toDual ⁻¹' s) ↔ IsUpperSet s :=
Iff.rfl
@[simp]
theorem isUpperSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsUpperSet (toDual ⁻¹' s) ↔ IsLowerSet s :=
Iff.rfl
alias ⟨_, IsUpperSet.toDual⟩ := isLowerSet_preimage_ofDual_iff
alias ⟨_, IsLowerSet.toDual⟩ := isUpperSet_preimage_ofDual_iff
alias ⟨_, IsUpperSet.ofDual⟩ := isLowerSet_preimage_toDual_iff
alias ⟨_, IsLowerSet.ofDual⟩ := isUpperSet_preimage_toDual_iff
lemma IsUpperSet.isLowerSet_preimage_coe (hs : IsUpperSet s) :
IsLowerSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t := by aesop
lemma IsLowerSet.isUpperSet_preimage_coe (hs : IsLowerSet s) :
IsUpperSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t := by aesop
lemma IsUpperSet.sdiff (hs : IsUpperSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t) :
IsUpperSet (s \ t) :=
fun _b _c hbc hb ↦ ⟨hs hbc hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hbc⟩
lemma IsLowerSet.sdiff (hs : IsLowerSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t) :
IsLowerSet (s \ t) :=
fun _b _c hcb hb ↦ ⟨hs hcb hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hcb⟩
lemma IsUpperSet.sdiff_of_isLowerSet (hs : IsUpperSet s) (ht : IsLowerSet t) : IsUpperSet (s \ t) :=
hs.sdiff <| by aesop
lemma IsLowerSet.sdiff_of_isUpperSet (hs : IsLowerSet s) (ht : IsUpperSet t) : IsLowerSet (s \ t) :=
hs.sdiff <| by aesop
lemma IsUpperSet.erase (hs : IsUpperSet s) (has : ∀ b ∈ s, b ≤ a → b = a) : IsUpperSet (s \ {a}) :=
hs.sdiff <| by simpa using has
lemma IsLowerSet.erase (hs : IsLowerSet s) (has : ∀ b ∈ s, a ≤ b → b = a) : IsLowerSet (s \ {a}) :=
hs.sdiff <| by simpa using has
end LE
section Preorder
variable [Preorder α] [Preorder β] {s : Set α} {p : α → Prop} (a : α)
theorem isUpperSet_Ici : IsUpperSet (Ici a) := fun _ _ => ge_trans
theorem isLowerSet_Iic : IsLowerSet (Iic a) := fun _ _ => le_trans
theorem isUpperSet_Ioi : IsUpperSet (Ioi a) := fun _ _ => flip lt_of_lt_of_le
theorem isLowerSet_Iio : IsLowerSet (Iio a) := fun _ _ => lt_of_le_of_lt
theorem isUpperSet_iff_Ici_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ici a ⊆ s := by
simp [IsUpperSet, subset_def, @forall_swap (_ ∈ s)]
theorem isLowerSet_iff_Iic_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iic a ⊆ s := by
simp [IsLowerSet, subset_def, @forall_swap (_ ∈ s)]
alias ⟨IsUpperSet.Ici_subset, _⟩ := isUpperSet_iff_Ici_subset
alias ⟨IsLowerSet.Iic_subset, _⟩ := isLowerSet_iff_Iic_subset
theorem IsUpperSet.Ioi_subset (h : IsUpperSet s) ⦃a⦄ (ha : a ∈ s) : Ioi a ⊆ s :=
Ioi_subset_Ici_self.trans <| h.Ici_subset ha
theorem IsLowerSet.Iio_subset (h : IsLowerSet s) ⦃a⦄ (ha : a ∈ s) : Iio a ⊆ s :=
h.toDual.Ioi_subset ha
theorem IsUpperSet.ordConnected (h : IsUpperSet s) : s.OrdConnected :=
⟨fun _ ha _ _ => Icc_subset_Ici_self.trans <| h.Ici_subset ha⟩
theorem IsLowerSet.ordConnected (h : IsLowerSet s) : s.OrdConnected :=
⟨fun _ _ _ hb => Icc_subset_Iic_self.trans <| h.Iic_subset hb⟩
theorem IsUpperSet.preimage (hs : IsUpperSet s) {f : β → α} (hf : Monotone f) :
IsUpperSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h
theorem IsLowerSet.preimage (hs : IsLowerSet s) {f : β → α} (hf : Monotone f) :
IsLowerSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h
theorem IsUpperSet.image (hs : IsUpperSet s) (f : α ≃o β) : IsUpperSet (f '' s : Set β) := by
change IsUpperSet ((f : α ≃ β) '' s)
rw [Set.image_equiv_eq_preimage_symm]
exact hs.preimage f.symm.monotone
theorem IsLowerSet.image (hs : IsLowerSet s) (f : α ≃o β) : IsLowerSet (f '' s : Set β) := by
change IsLowerSet ((f : α ≃ β) '' s)
rw [Set.image_equiv_eq_preimage_symm]
exact hs.preimage f.symm.monotone
theorem OrderEmbedding.image_Ici (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) :
e '' Ici a = Ici (e a) := by
rw [← e.preimage_Ici, image_preimage_eq_inter_range,
inter_eq_left.2 <| he.Ici_subset (mem_range_self _)]
theorem OrderEmbedding.image_Iic (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) :
e '' Iic a = Iic (e a) :=
e.dual.image_Ici he a
theorem OrderEmbedding.image_Ioi (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) :
e '' Ioi a = Ioi (e a) := by
rw [← e.preimage_Ioi, image_preimage_eq_inter_range,
inter_eq_left.2 <| he.Ioi_subset (mem_range_self _)]
theorem OrderEmbedding.image_Iio (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) :
e '' Iio a = Iio (e a) :=
e.dual.image_Ioi he a
@[simp]
theorem Set.monotone_mem : Monotone (· ∈ s) ↔ IsUpperSet s :=
Iff.rfl
@[simp]
theorem Set.antitone_mem : Antitone (· ∈ s) ↔ IsLowerSet s :=
forall_swap
@[simp]
theorem isUpperSet_setOf : IsUpperSet { a | p a } ↔ Monotone p :=
Iff.rfl
@[simp]
theorem isLowerSet_setOf : IsLowerSet { a | p a } ↔ Antitone p :=
forall_swap
lemma IsUpperSet.upperBounds_subset (hs : IsUpperSet s) : s.Nonempty → upperBounds s ⊆ s :=
fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha
lemma IsLowerSet.lowerBounds_subset (hs : IsLowerSet s) : s.Nonempty → lowerBounds s ⊆ s :=
fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha
section OrderTop
variable [OrderTop α]
theorem IsLowerSet.top_mem (hs : IsLowerSet s) : ⊤ ∈ s ↔ s = univ :=
⟨fun h => eq_univ_of_forall fun _ => hs le_top h, fun h => h.symm ▸ mem_univ _⟩
theorem IsUpperSet.top_mem (hs : IsUpperSet s) : ⊤ ∈ s ↔ s.Nonempty :=
⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs le_top ha⟩
theorem IsUpperSet.not_top_mem (hs : IsUpperSet s) : ⊤ ∉ s ↔ s = ∅ :=
hs.top_mem.not.trans not_nonempty_iff_eq_empty
end OrderTop
section OrderBot
variable [OrderBot α]
theorem IsUpperSet.bot_mem (hs : IsUpperSet s) : ⊥ ∈ s ↔ s = univ :=
⟨fun h => eq_univ_of_forall fun _ => hs bot_le h, fun h => h.symm ▸ mem_univ _⟩
theorem IsLowerSet.bot_mem (hs : IsLowerSet s) : ⊥ ∈ s ↔ s.Nonempty :=
⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs bot_le ha⟩
theorem IsLowerSet.not_bot_mem (hs : IsLowerSet s) : ⊥ ∉ s ↔ s = ∅ :=
hs.bot_mem.not.trans not_nonempty_iff_eq_empty
end OrderBot
section NoMaxOrder
variable [NoMaxOrder α]
theorem IsUpperSet.not_bddAbove (hs : IsUpperSet s) : s.Nonempty → ¬BddAbove s := by
rintro ⟨a, ha⟩ ⟨b, hb⟩
obtain ⟨c, hc⟩ := exists_gt b
exact hc.not_le (hb <| hs ((hb ha).trans hc.le) ha)
theorem not_bddAbove_Ici : ¬BddAbove (Ici a) :=
(isUpperSet_Ici _).not_bddAbove nonempty_Ici
theorem not_bddAbove_Ioi : ¬BddAbove (Ioi a) :=
(isUpperSet_Ioi _).not_bddAbove nonempty_Ioi
end NoMaxOrder
section NoMinOrder
variable [NoMinOrder α]
theorem IsLowerSet.not_bddBelow (hs : IsLowerSet s) : s.Nonempty → ¬BddBelow s := by
rintro ⟨a, ha⟩ ⟨b, hb⟩
obtain ⟨c, hc⟩ := exists_lt b
exact hc.not_le (hb <| hs (hc.le.trans <| hb ha) ha)
theorem not_bddBelow_Iic : ¬BddBelow (Iic a) :=
(isLowerSet_Iic _).not_bddBelow nonempty_Iic
theorem not_bddBelow_Iio : ¬BddBelow (Iio a) :=
(isLowerSet_Iio _).not_bddBelow nonempty_Iio
end NoMinOrder
end Preorder
section PartialOrder
variable [PartialOrder α] {s : Set α}
theorem isUpperSet_iff_forall_lt : IsUpperSet s ↔ ∀ ⦃a b : α⦄, a < b → a ∈ s → b ∈ s :=
forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and]
theorem isLowerSet_iff_forall_lt : IsLowerSet s ↔ ∀ ⦃a b : α⦄, b < a → a ∈ s → b ∈ s :=
forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and]
theorem isUpperSet_iff_Ioi_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ioi a ⊆ s := by
simp [isUpperSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)]
theorem isLowerSet_iff_Iio_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iio a ⊆ s := by
simp [isLowerSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)]
end PartialOrder
section LinearOrder
variable [LinearOrder α] {s t : Set α}
theorem IsUpperSet.total (hs : IsUpperSet s) (ht : IsUpperSet t) : s ⊆ t ∨ t ⊆ s := by
by_contra! h
simp_rw [Set.not_subset] at h
obtain ⟨⟨a, has, hat⟩, b, hbt, hbs⟩ := h
obtain hab | hba := le_total a b
· exact hbs (hs hab has)
· exact hat (ht hba hbt)
theorem IsLowerSet.total (hs : IsLowerSet s) (ht : IsLowerSet t) : s ⊆ t ∨ t ⊆ s :=
hs.toDual.total ht.toDual
end LinearOrder
| Mathlib/Order/UpperLower/Basic.lean | 1,719 | 1,720 | |
/-
Copyright (c) 2021 Justus Springer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Justus Springer, Andrew Yang
-/
import Mathlib.Algebra.Category.Ring.Colimits
import Mathlib.Algebra.Category.Ring.FilteredColimits
import Mathlib.Algebra.Category.Ring.Limits
import Mathlib.Algebra.Order.Group.Nat
import Mathlib.Geometry.RingedSpace.SheafedSpace
import Mathlib.Topology.Sheaves.Stalks
/-!
# Ringed spaces
We introduce the category of ringed spaces, as an alias for `SheafedSpace CommRingCat`.
The facts collected in this file are typically stated for locally ringed spaces, but never actually
make use of the locality of stalks. See for instance <https://stacks.math.columbia.edu/tag/01HZ>.
-/
universe v u
open CategoryTheory
open TopologicalSpace
open Opposite
open TopCat
open TopCat.Presheaf
namespace AlgebraicGeometry
/-- The type of Ringed spaces, as an abbreviation for `SheafedSpace CommRingCat`. -/
@[nolint checkUnivs] -- The universes appear together in the type, but separately in the value.
abbrev RingedSpace : Type max (u+1) (v+1) :=
SheafedSpace.{v+1, v, u} CommRingCat.{v}
namespace RingedSpace
open SheafedSpace
@[simp]
lemma res_zero {X : RingedSpace.{u}} {U V : TopologicalSpace.Opens X}
(hUV : U ≤ V) : (0 : X.presheaf.obj (op V)) |_ U = (0 : X.presheaf.obj (op U)) :=
RingHom.map_zero _
variable (X : RingedSpace)
instance : CoeSort RingedSpace Type* where
coe X := X.carrier
/-- If the germ of a section `f` is zero in the stalk at `x`, then `f` is zero on some neighbourhood
around `x`. -/
| lemma exists_res_eq_zero_of_germ_eq_zero (U : Opens X) (f : X.presheaf.obj (op U)) (x : U)
(h : X.presheaf.germ U x.val x.property f = 0) :
∃ (V : Opens X) (i : V ⟶ U) (_ : x.1 ∈ V), X.presheaf.map i.op f = 0 := by
have h1 : X.presheaf.germ U x.val x.property f = X.presheaf.germ U x.val x.property 0 := by simpa
obtain ⟨V, hv, i, _, (hv4 : (X.presheaf.map i.op) f = (X.presheaf.map _) 0)⟩ :=
TopCat.Presheaf.germ_eq X.presheaf x.1 x.2 x.2 f 0 h1
use V, i, hv
simpa using hv4
/--
If the germ of a section `f` is a unit in the stalk at `x`, then `f` must be a unit on some small
neighborhood around `x`.
-/
theorem isUnit_res_of_isUnit_germ (U : Opens X) (f : X.presheaf.obj (op U)) (x : X) (hx : x ∈ U)
(h : IsUnit (X.presheaf.germ U x hx f)) :
∃ (V : Opens X) (i : V ⟶ U) (_ : x ∈ V), IsUnit (X.presheaf.map i.op f) := by
obtain ⟨g', heq⟩ := h.exists_right_inv
obtain ⟨V, hxV, g, rfl⟩ := X.presheaf.germ_exist x g'
let W := U ⊓ V
have hxW : x ∈ W := ⟨hx, hxV⟩
-- Porting note: `erw` can't write into `HEq`, so this is replaced with another `HEq` in the
-- desired form
| Mathlib/Geometry/RingedSpace/Basic.lean | 58 | 79 |
/-
Copyright (c) 2022 Niels Voss. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Niels Voss
-/
import Mathlib.Algebra.Order.Archimedean.Basic
import Mathlib.FieldTheory.Finite.Basic
import Mathlib.Order.Filter.Cofinite
/-!
# Fermat Pseudoprimes
In this file we define Fermat pseudoprimes: composite numbers that pass the Fermat primality test.
A natural number `n` passes the Fermat primality test to base `b` (and is therefore deemed a
"probable prime") if `n` divides `b ^ (n - 1) - 1`. `n` is a Fermat pseudoprime to base `b` if `n`
is a composite number that passes the Fermat primality test to base `b` and is coprime with `b`.
Fermat pseudoprimes can also be seen as composite numbers for which Fermat's little theorem holds
true.
Numbers which are Fermat pseudoprimes to all bases are known as Carmichael numbers (not yet defined
in this file).
## Main Results
The main definitions for this file are
- `Nat.ProbablePrime`: A number `n` is a probable prime to base `b` if it passes the Fermat
primality test; that is, if `n` divides `b ^ (n - 1) - 1`
- `Nat.FermatPsp`: A number `n` is a pseudoprime to base `b` if it is a probable prime to base `b`,
is composite, and is coprime with `b` (this last condition is automatically true if `n` divides
`b ^ (n - 1) - 1`, but some sources include it in the definition).
Note that all composite numbers are pseudoprimes to base 0 and 1, and that the definition of
`Nat.ProbablePrime` in this file implies that all numbers are probable primes to bases 0 and 1, and
that 0 and 1 are probable primes to any base.
The main theorems are
- `Nat.exists_infinite_pseudoprimes`: there are infinite pseudoprimes to any base `b ≥ 1`
-/
namespace Nat
/--
`n` is a probable prime to base `b` if `n` passes the Fermat primality test; that is, `n` divides
`b ^ (n - 1) - 1`.
This definition implies that all numbers are probable primes to base 0 or 1, and that 0 and 1 are
probable primes to any base.
-/
def ProbablePrime (n b : ℕ) : Prop :=
n ∣ b ^ (n - 1) - 1
/--
`n` is a Fermat pseudoprime to base `b` if `n` is a probable prime to base `b` and is composite. By
this definition, all composite natural numbers are pseudoprimes to base 0 and 1. This definition
also permits `n` to be less than `b`, so that 4 is a pseudoprime to base 5, for example.
-/
def FermatPsp (n b : ℕ) : Prop :=
ProbablePrime n b ∧ ¬n.Prime ∧ 1 < n
instance decidableProbablePrime (n b : ℕ) : Decidable (ProbablePrime n b) :=
Nat.decidable_dvd _ _
instance decidablePsp (n b : ℕ) : Decidable (FermatPsp n b) :=
inferInstanceAs (Decidable (_ ∧ _))
/-- If `n` passes the Fermat primality test to base `b`, then `n` is coprime with `b`, assuming that
`n` and `b` are both positive.
-/
theorem coprime_of_probablePrime {n b : ℕ} (h : ProbablePrime n b) (h₁ : 1 ≤ n) (h₂ : 1 ≤ b) :
Nat.Coprime n b := by
by_cases h₃ : 2 ≤ n
· -- To prove that `n` is coprime with `b`, we need to show that for all prime factors of `n`,
-- we can derive a contradiction if `n` divides `b`.
apply Nat.coprime_of_dvd
-- If `k` is a prime number that divides both `n` and `b`, then we know that `n = m * k` and
-- `b = j * k` for some natural numbers `m` and `j`. We substitute these into the hypothesis.
rintro k hk ⟨m, rfl⟩ ⟨j, rfl⟩
-- Because prime numbers do not divide 1, it suffices to show that `k ∣ 1` to prove a
-- contradiction
apply Nat.Prime.not_dvd_one hk
-- Since `n` divides `b ^ (n - 1) - 1`, `k` also divides `b ^ (n - 1) - 1`
replace h := dvd_of_mul_right_dvd h
-- Because `k` divides `b ^ (n - 1) - 1`, if we can show that `k` also divides `b ^ (n - 1)`,
-- then we know `k` divides 1.
rw [Nat.dvd_add_iff_right h, Nat.sub_add_cancel (Nat.one_le_pow _ _ h₂)]
-- Since `k` divides `b`, `k` also divides any power of `b` except `b ^ 0`. Therefore, it
-- suffices to show that `n - 1` isn't zero. However, we know that `n - 1` isn't zero because we
-- assumed `2 ≤ n` when doing `by_cases`.
refine dvd_of_mul_right_dvd (dvd_pow_self (k * j) ?_)
omega
-- If `n = 1`, then it follows trivially that `n` is coprime with `b`.
· rw [show n = 1 by omega]
norm_num
theorem probablePrime_iff_modEq (n : ℕ) {b : ℕ} (h : 1 ≤ b) :
ProbablePrime n b ↔ b ^ (n - 1) ≡ 1 [MOD n] := by
have : 1 ≤ b ^ (n - 1) := one_le_pow₀ h
-- For exact mod_cast
rw [Nat.ModEq.comm]
constructor
· intro h₁
apply Nat.modEq_of_dvd
exact mod_cast h₁
· intro h₁
exact mod_cast Nat.ModEq.dvd h₁
/-- If `n` is a Fermat pseudoprime to base `b`, then `n` is coprime with `b`, assuming that `b` is
positive.
This lemma is a small wrapper based on `coprime_of_probablePrime`
-/
theorem coprime_of_fermatPsp {n b : ℕ} (h : FermatPsp n b) (h₁ : 1 ≤ b) : Nat.Coprime n b := by
rcases h with ⟨hp, _, hn₂⟩
exact coprime_of_probablePrime hp (by omega) h₁
/-- All composite numbers are Fermat pseudoprimes to base 1.
-/
theorem fermatPsp_base_one {n : ℕ} (h₁ : 1 < n) (h₂ : ¬n.Prime) : FermatPsp n 1 := by
refine ⟨show n ∣ 1 ^ (n - 1) - 1 from ?_, h₂, h₁⟩
exact show 0 = 1 ^ (n - 1) - 1 by norm_num ▸ dvd_zero n
-- Lemmas that are needed to prove statements in this file, but aren't directly related to Fermat
-- pseudoprimes
section HelperLemmas
private theorem a_id_helper {a b : ℕ} (ha : 2 ≤ a) (hb : 2 ≤ b) : 2 ≤ (a ^ b - 1) / (a - 1) := by
change 1 < _
have h₁ : a - 1 ∣ a ^ b - 1 := by simpa only [one_pow] using nat_sub_dvd_pow_sub_pow a 1 b
rw [Nat.lt_div_iff_mul_lt' h₁, mul_one, tsub_lt_tsub_iff_right (Nat.le_of_succ_le ha)]
exact lt_self_pow₀ (Nat.lt_of_succ_le ha) hb
private theorem b_id_helper {a b : ℕ} (ha : 2 ≤ a) (hb : 2 < b) : 2 ≤ (a ^ b + 1) / (a + 1) := by
rw [Nat.le_div_iff_mul_le (Nat.zero_lt_succ _)]
apply Nat.succ_le_succ
calc
2 * a + 1 ≤ a ^ 2 * a := by nlinarith
_ = a ^ 3 := by rw [Nat.pow_succ a 2]
_ ≤ a ^ b := pow_right_mono₀ (Nat.le_of_succ_le ha) hb
private theorem AB_id_helper (b p : ℕ) (_ : 2 ≤ b) (hp : Odd p) :
(b ^ p - 1) / (b - 1) * ((b ^ p + 1) / (b + 1)) = (b ^ (2 * p) - 1) / (b ^ 2 - 1) := by
have q₁ : b - 1 ∣ b ^ p - 1 := by simpa only [one_pow] using nat_sub_dvd_pow_sub_pow b 1 p
have q₂ : b + 1 ∣ b ^ p + 1 := by simpa only [one_pow] using hp.nat_add_dvd_pow_add_pow b 1
convert Nat.div_mul_div_comm q₁ q₂ using 2 <;> rw [mul_comm (_ - 1), ← Nat.sq_sub_sq]
ring_nf
/-- Used in the proof of `psp_from_prime_psp`
-/
private theorem bp_helper {b p : ℕ} (hb : 0 < b) (hp : 1 ≤ p) :
b ^ (2 * p) - 1 - (b ^ 2 - 1) = b * (b ^ (p - 1) - 1) * (b ^ p + b) :=
have hi_bsquared : 1 ≤ b ^ 2 := Nat.one_le_pow _ _ hb
calc
b ^ (2 * p) - 1 - (b ^ 2 - 1) = b ^ (2 * p) - (1 + (b ^ 2 - 1)) := by rw [Nat.sub_sub]
_ = b ^ (2 * p) - (1 + b ^ 2 - 1) := by rw [Nat.add_sub_assoc hi_bsquared]
_ = b ^ (2 * p) - b ^ 2 := by rw [Nat.add_sub_cancel_left]
_ = b ^ (p * 2) - b ^ 2 := by rw [mul_comm]
_ = (b ^ p) ^ 2 - b ^ 2 := by rw [pow_mul]
| _ = (b ^ p + b) * (b ^ p - b) := by rw [Nat.sq_sub_sq]
_ = (b ^ p - b) * (b ^ p + b) := by rw [mul_comm]
_ = (b ^ (p - 1 + 1) - b) * (b ^ p + b) := by rw [Nat.sub_add_cancel hp]
_ = (b * b ^ (p - 1) - b) * (b ^ p + b) := by rw [pow_succ']
_ = (b * b ^ (p - 1) - b * 1) * (b ^ p + b) := by rw [mul_one]
_ = b * (b ^ (p - 1) - 1) * (b ^ p + b) := by rw [Nat.mul_sub_left_distrib]
end HelperLemmas
/-- Given a prime `p` which does not divide `b * (b ^ 2 - 1)`, we can produce a number `n` which is
larger than `p` and pseudoprime to base `b`. We do this by defining
`n = ((b ^ p - 1) / (b - 1)) * ((b ^ p + 1) / (b + 1))`
The primary purpose of this definition is to help prove `exists_infinite_pseudoprimes`. For a proof
that `n` is actually pseudoprime to base `b`, see `psp_from_prime_psp`, and for a proof that `n` is
| Mathlib/NumberTheory/FermatPsp.lean | 159 | 173 |
/-
Copyright (c) 2018 Rohan Mitta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rohan Mitta, Kevin Buzzard, Alistair Tucker, Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.Order.Interval.Set.ProjIcc
import Mathlib.Topology.Algebra.Order.Field
import Mathlib.Topology.Bornology.Hom
import Mathlib.Topology.EMetricSpace.Lipschitz
import Mathlib.Topology.Maps.Proper.Basic
import Mathlib.Topology.MetricSpace.Basic
import Mathlib.Topology.MetricSpace.Bounded
/-!
# Lipschitz continuous functions
A map `f : α → β` between two (extended) metric spaces is called *Lipschitz continuous*
with constant `K ≥ 0` if for all `x, y` we have `edist (f x) (f y) ≤ K * edist x y`.
For a metric space, the latter inequality is equivalent to `dist (f x) (f y) ≤ K * dist x y`.
There is also a version asserting this inequality only for `x` and `y` in some set `s`.
Finally, `f : α → β` is called *locally Lipschitz continuous* if each `x : α` has a neighbourhood
on which `f` is Lipschitz continuous (with some constant).
In this file we specialize various facts about Lipschitz continuous maps
to the case of (pseudo) metric spaces.
## Implementation notes
The parameter `K` has type `ℝ≥0`. This way we avoid conjunction in the definition and have
coercions both to `ℝ` and `ℝ≥0∞`. Constructors whose names end with `'` take `K : ℝ` as an
argument, and return `LipschitzWith (Real.toNNReal K) f`.
-/
assert_not_exists Basis Ideal
universe u v w x
open Filter Function Set Topology NNReal ENNReal Bornology
variable {α : Type u} {β : Type v} {γ : Type w} {ι : Type x}
theorem lipschitzWith_iff_dist_le_mul [PseudoMetricSpace α] [PseudoMetricSpace β] {K : ℝ≥0}
{f : α → β} : LipschitzWith K f ↔ ∀ x y, dist (f x) (f y) ≤ K * dist x y := by
simp only [LipschitzWith, edist_nndist, dist_nndist]
norm_cast
alias ⟨LipschitzWith.dist_le_mul, LipschitzWith.of_dist_le_mul⟩ := lipschitzWith_iff_dist_le_mul
theorem lipschitzOnWith_iff_dist_le_mul [PseudoMetricSpace α] [PseudoMetricSpace β] {K : ℝ≥0}
{s : Set α} {f : α → β} :
LipschitzOnWith K f s ↔ ∀ x ∈ s, ∀ y ∈ s, dist (f x) (f y) ≤ K * dist x y := by
simp only [LipschitzOnWith, edist_nndist, dist_nndist]
norm_cast
alias ⟨LipschitzOnWith.dist_le_mul, LipschitzOnWith.of_dist_le_mul⟩ :=
lipschitzOnWith_iff_dist_le_mul
namespace LipschitzWith
section Metric
variable [PseudoMetricSpace α] [PseudoMetricSpace β] [PseudoMetricSpace γ] {K : ℝ≥0} {f : α → β}
{x y : α} {r : ℝ}
protected theorem of_dist_le' {K : ℝ} (h : ∀ x y, dist (f x) (f y) ≤ K * dist x y) :
LipschitzWith (Real.toNNReal K) f :=
of_dist_le_mul fun x y =>
le_trans (h x y) <| by gcongr; apply Real.le_coe_toNNReal
protected theorem mk_one (h : ∀ x y, dist (f x) (f y) ≤ dist x y) : LipschitzWith 1 f :=
of_dist_le_mul <| by simpa only [NNReal.coe_one, one_mul] using h
/-- For functions to `ℝ`, it suffices to prove `f x ≤ f y + K * dist x y`; this version
doesn't assume `0≤K`. -/
protected theorem of_le_add_mul' {f : α → ℝ} (K : ℝ) (h : ∀ x y, f x ≤ f y + K * dist x y) :
LipschitzWith (Real.toNNReal K) f :=
have I : ∀ x y, f x - f y ≤ K * dist x y := fun x y => sub_le_iff_le_add'.2 (h x y)
LipschitzWith.of_dist_le' fun x y => abs_sub_le_iff.2 ⟨I x y, dist_comm y x ▸ I y x⟩
/-- For functions to `ℝ`, it suffices to prove `f x ≤ f y + K * dist x y`; this version
assumes `0≤K`. -/
protected theorem of_le_add_mul {f : α → ℝ} (K : ℝ≥0) (h : ∀ x y, f x ≤ f y + K * dist x y) :
LipschitzWith K f := by simpa only [Real.toNNReal_coe] using LipschitzWith.of_le_add_mul' K h
protected theorem of_le_add {f : α → ℝ} (h : ∀ x y, f x ≤ f y + dist x y) : LipschitzWith 1 f :=
LipschitzWith.of_le_add_mul 1 <| by simpa only [NNReal.coe_one, one_mul]
protected theorem le_add_mul {f : α → ℝ} {K : ℝ≥0} (h : LipschitzWith K f) (x y) :
f x ≤ f y + K * dist x y :=
sub_le_iff_le_add'.1 <| le_trans (le_abs_self _) <| h.dist_le_mul x y
protected theorem iff_le_add_mul {f : α → ℝ} {K : ℝ≥0} :
LipschitzWith K f ↔ ∀ x y, f x ≤ f y + K * dist x y :=
⟨LipschitzWith.le_add_mul, LipschitzWith.of_le_add_mul K⟩
theorem nndist_le (hf : LipschitzWith K f) (x y : α) : nndist (f x) (f y) ≤ K * nndist x y :=
hf.dist_le_mul x y
theorem dist_le_mul_of_le (hf : LipschitzWith K f) (hr : dist x y ≤ r) : dist (f x) (f y) ≤ K * r :=
(hf.dist_le_mul x y).trans <| by gcongr
theorem mapsTo_closedBall (hf : LipschitzWith K f) (x : α) (r : ℝ) :
MapsTo f (Metric.closedBall x r) (Metric.closedBall (f x) (K * r)) := fun _y hy =>
hf.dist_le_mul_of_le hy
theorem dist_lt_mul_of_lt (hf : LipschitzWith K f) (hK : K ≠ 0) (hr : dist x y < r) :
dist (f x) (f y) < K * r :=
(hf.dist_le_mul x y).trans_lt <| (mul_lt_mul_left <| NNReal.coe_pos.2 hK.bot_lt).2 hr
theorem mapsTo_ball (hf : LipschitzWith K f) (hK : K ≠ 0) (x : α) (r : ℝ) :
MapsTo f (Metric.ball x r) (Metric.ball (f x) (K * r)) := fun _y hy =>
hf.dist_lt_mul_of_lt hK hy
/-- A Lipschitz continuous map is a locally bounded map. -/
def toLocallyBoundedMap (f : α → β) (hf : LipschitzWith K f) : LocallyBoundedMap α β :=
LocallyBoundedMap.ofMapBounded f fun _s hs =>
let ⟨C, hC⟩ := Metric.isBounded_iff.1 hs
Metric.isBounded_iff.2 ⟨K * C, forall_mem_image.2 fun _x hx => forall_mem_image.2 fun _y hy =>
hf.dist_le_mul_of_le (hC hx hy)⟩
@[simp]
theorem coe_toLocallyBoundedMap (hf : LipschitzWith K f) : ⇑(hf.toLocallyBoundedMap f) = f :=
rfl
theorem comap_cobounded_le (hf : LipschitzWith K f) :
comap f (Bornology.cobounded β) ≤ Bornology.cobounded α :=
(hf.toLocallyBoundedMap f).2
/-- The image of a bounded set under a Lipschitz map is bounded. -/
theorem isBounded_image (hf : LipschitzWith K f) {s : Set α} (hs : IsBounded s) :
IsBounded (f '' s) :=
hs.image (toLocallyBoundedMap f hf)
theorem diam_image_le (hf : LipschitzWith K f) (s : Set α) (hs : IsBounded s) :
Metric.diam (f '' s) ≤ K * Metric.diam s :=
Metric.diam_le_of_forall_dist_le (mul_nonneg K.coe_nonneg Metric.diam_nonneg) <|
forall_mem_image.2 fun _x hx =>
forall_mem_image.2 fun _y hy => hf.dist_le_mul_of_le <| Metric.dist_le_diam_of_mem hs hx hy
protected theorem dist_left (y : α) : LipschitzWith 1 (dist · y) :=
LipschitzWith.mk_one fun _ _ => dist_dist_dist_le_left _ _ _
protected theorem dist_right (x : α) : LipschitzWith 1 (dist x) :=
LipschitzWith.of_le_add fun _ _ => dist_triangle_right _ _ _
protected theorem dist : LipschitzWith 2 (Function.uncurry <| @dist α _) := by
rw [← one_add_one_eq_two]
exact LipschitzWith.uncurry LipschitzWith.dist_left LipschitzWith.dist_right
theorem dist_iterate_succ_le_geometric {f : α → α} (hf : LipschitzWith K f) (x n) :
dist (f^[n] x) (f^[n + 1] x) ≤ dist x (f x) * (K : ℝ) ^ n := by
rw [iterate_succ, mul_comm]
simpa only [NNReal.coe_pow] using (hf.iterate n).dist_le_mul x (f x)
theorem _root_.lipschitzWith_max : LipschitzWith 1 fun p : ℝ × ℝ => max p.1 p.2 :=
LipschitzWith.of_le_add fun _ _ => sub_le_iff_le_add'.1 <|
(le_abs_self _).trans (abs_max_sub_max_le_max _ _ _ _)
theorem _root_.lipschitzWith_min : LipschitzWith 1 fun p : ℝ × ℝ => min p.1 p.2 :=
LipschitzWith.of_le_add fun _ _ => sub_le_iff_le_add'.1 <|
(le_abs_self _).trans (abs_min_sub_min_le_max _ _ _ _)
lemma _root_.Real.lipschitzWith_toNNReal : LipschitzWith 1 Real.toNNReal := by
refine lipschitzWith_iff_dist_le_mul.mpr (fun x y ↦ ?_)
simpa only [NNReal.coe_one, dist_prod_same_right, one_mul, Real.dist_eq] using
lipschitzWith_iff_dist_le_mul.mp lipschitzWith_max (x, 0) (y, 0)
lemma cauchySeq_comp (hf : LipschitzWith K f) {u : ℕ → α} (hu : CauchySeq u) :
CauchySeq (f ∘ u) := by
| rcases cauchySeq_iff_le_tendsto_0.1 hu with ⟨b, b_nonneg, hb, blim⟩
refine cauchySeq_iff_le_tendsto_0.2 ⟨fun n ↦ K * b n, ?_, ?_, ?_⟩
· exact fun n ↦ mul_nonneg (by positivity) (b_nonneg n)
| Mathlib/Topology/MetricSpace/Lipschitz.lean | 170 | 172 |
/-
Copyright (c) 2023 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Data.Finset.Lattice.Fold
/-!
# Irreducible and prime elements in an order
This file defines irreducible and prime elements in an order and shows that in a well-founded
lattice every element decomposes as a supremum of irreducible elements.
An element is sup-irreducible (resp. inf-irreducible) if it isn't `⊥` and can't be written as the
supremum of any strictly smaller elements. An element is sup-prime (resp. inf-prime) if it isn't `⊥`
and is greater than the supremum of any two elements less than it.
Primality implies irreducibility in general. The converse only holds in distributive lattices.
Both hold for all (non-minimal) elements in a linear order.
## Main declarations
* `SupIrred a`: Sup-irreducibility, `a` isn't minimal and `a = b ⊔ c → a = b ∨ a = c`
* `InfIrred a`: Inf-irreducibility, `a` isn't maximal and `a = b ⊓ c → a = b ∨ a = c`
* `SupPrime a`: Sup-primality, `a` isn't minimal and `a ≤ b ⊔ c → a ≤ b ∨ a ≤ c`
* `InfIrred a`: Inf-primality, `a` isn't maximal and `a ≥ b ⊓ c → a ≥ b ∨ a ≥ c`
* `exists_supIrred_decomposition`/`exists_infIrred_decomposition`: Decomposition into irreducibles
in a well-founded semilattice.
-/
open Finset OrderDual
variable {ι α : Type*}
/-! ### Irreducible and prime elements -/
section SemilatticeSup
variable [SemilatticeSup α] {a b c : α}
/-- A sup-irreducible element is a non-bottom element which isn't the supremum of anything smaller.
-/
def SupIrred (a : α) : Prop :=
¬IsMin a ∧ ∀ ⦃b c⦄, b ⊔ c = a → b = a ∨ c = a
/-- A sup-prime element is a non-bottom element which isn't less than the supremum of anything
smaller. -/
def SupPrime (a : α) : Prop :=
¬IsMin a ∧ ∀ ⦃b c⦄, a ≤ b ⊔ c → a ≤ b ∨ a ≤ c
theorem SupIrred.not_isMin (ha : SupIrred a) : ¬IsMin a :=
ha.1
theorem SupPrime.not_isMin (ha : SupPrime a) : ¬IsMin a :=
ha.1
theorem IsMin.not_supIrred (ha : IsMin a) : ¬SupIrred a := fun h => h.1 ha
theorem IsMin.not_supPrime (ha : IsMin a) : ¬SupPrime a := fun h => h.1 ha
@[simp]
theorem not_supIrred : ¬SupIrred a ↔ IsMin a ∨ ∃ b c, b ⊔ c = a ∧ b < a ∧ c < a := by
rw [SupIrred, not_and_or]
push_neg
rw [exists₂_congr]
simp +contextual [@eq_comm _ _ a]
@[simp]
theorem not_supPrime : ¬SupPrime a ↔ IsMin a ∨ ∃ b c, a ≤ b ⊔ c ∧ ¬a ≤ b ∧ ¬a ≤ c := by
rw [SupPrime, not_and_or]; push_neg; rfl
protected theorem SupPrime.supIrred : SupPrime a → SupIrred a :=
And.imp_right fun h b c ha => by simpa [← ha] using h ha.ge
theorem SupPrime.le_sup (ha : SupPrime a) : a ≤ b ⊔ c ↔ a ≤ b ∨ a ≤ c :=
⟨fun h => ha.2 h, fun h => h.elim le_sup_of_le_left le_sup_of_le_right⟩
variable [OrderBot α] {s : Finset ι} {f : ι → α}
@[simp]
theorem not_supIrred_bot : ¬SupIrred (⊥ : α) :=
isMin_bot.not_supIrred
@[simp]
theorem not_supPrime_bot : ¬SupPrime (⊥ : α) :=
isMin_bot.not_supPrime
theorem SupIrred.ne_bot (ha : SupIrred a) : a ≠ ⊥ := by rintro rfl; exact not_supIrred_bot ha
theorem SupPrime.ne_bot (ha : SupPrime a) : a ≠ ⊥ := by rintro rfl; exact not_supPrime_bot ha
theorem SupIrred.finset_sup_eq (ha : SupIrred a) (h : s.sup f = a) : ∃ i ∈ s, f i = a := by
classical
induction' s using Finset.induction with i s _ ih
· simpa [ha.ne_bot] using h.symm
simp only [exists_prop, exists_mem_insert] at ih ⊢
rw [sup_insert] at h
exact (ha.2 h).imp_right ih
theorem SupPrime.le_finset_sup (ha : SupPrime a) : a ≤ s.sup f ↔ ∃ i ∈ s, a ≤ f i := by
classical
induction' s using Finset.induction with i s _ ih
· simp [ha.ne_bot]
· simp only [exists_prop, exists_mem_insert, sup_insert, ha.le_sup, ih]
variable [WellFoundedLT α]
/-- In a well-founded lattice, any element is the supremum of finitely many sup-irreducible
elements. This is the order-theoretic analogue of prime factorisation. -/
theorem exists_supIrred_decomposition (a : α) :
∃ s : Finset α, s.sup id = a ∧ ∀ ⦃b⦄, b ∈ s → SupIrred b := by
classical
apply WellFoundedLT.induction a _
clear a
rintro a ih
by_cases ha : SupIrred a
| · exact ⟨{a}, by simp [ha]⟩
rw [not_supIrred] at ha
obtain ha | ⟨b, c, rfl, hb, hc⟩ := ha
· exact ⟨∅, by simp [ha.eq_bot]⟩
obtain ⟨s, rfl, hs⟩ := ih _ hb
| Mathlib/Order/Irreducible.lean | 119 | 123 |
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Patrick Massot, Sébastien Gouëzel
-/
import Mathlib.MeasureTheory.Integral.IntervalIntegral.Basic
import Mathlib.MeasureTheory.Integral.IntervalIntegral.FundThmCalculus
import Mathlib.MeasureTheory.Integral.IntervalIntegral.IntegrationByParts
deprecated_module (since := "2025-04-13")
| Mathlib/MeasureTheory/Integral/IntervalIntegral.lean | 753 | 755 | |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov, Kexing Ying
-/
import Mathlib.Topology.Semicontinuous
import Mathlib.MeasureTheory.Function.AEMeasurableSequence
import Mathlib.MeasureTheory.Order.Lattice
import Mathlib.Topology.Order.Lattice
import Mathlib.MeasureTheory.Constructions.BorelSpace.Basic
/-!
# Borel sigma algebras on spaces with orders
## Main statements
* `borel_eq_generateFrom_Ixx` (where Ixx is one of {Iio, Ioi, Iic, Ici, Ico, Ioc}):
The Borel sigma algebra of a linear order topology is generated by intervals of the given kind.
* `Dense.borel_eq_generateFrom_Ico_mem`, `Dense.borel_eq_generateFrom_Ioc_mem`:
The Borel sigma algebra of a dense linear order topology is generated by intervals of a given
kind, with endpoints from dense subsets.
* `ext_of_Ico`, `ext_of_Ioc`:
A locally finite Borel measure on a second countable conditionally complete linear order is
characterized by the measures of intervals of the given kind.
* `ext_of_Iic`, `ext_of_Ici`:
A finite Borel measure on a second countable linear order is characterized by the measures of
intervals of the given kind.
* `UpperSemicontinuous.measurable`, `LowerSemicontinuous.measurable`:
Semicontinuous functions are measurable.
* `Measurable.iSup`, `Measurable.iInf`, `Measurable.sSup`, `Measurable.sInf`:
Countable supremums and infimums of measurable functions to conditionally complete linear orders
are measurable.
* `Measurable.liminf`, `Measurable.limsup`:
Countable liminfs and limsups of measurable functions to conditionally complete linear orders
are measurable.
-/
open Set Filter MeasureTheory MeasurableSpace TopologicalSpace
open scoped Topology NNReal ENNReal MeasureTheory
universe u v w x y
variable {α β γ δ : Type*} {ι : Sort y} {s t u : Set α}
section OrderTopology
variable (α)
variable [TopologicalSpace α] [SecondCountableTopology α] [LinearOrder α] [OrderTopology α]
theorem borel_eq_generateFrom_Iio : borel α = .generateFrom (range Iio) := by
refine le_antisymm ?_ (generateFrom_le ?_)
· rw [borel_eq_generateFrom_of_subbasis (@OrderTopology.topology_eq_generate_intervals α _ _ _)]
letI : MeasurableSpace α := MeasurableSpace.generateFrom (range Iio)
have H : ∀ a : α, MeasurableSet (Iio a) := fun a => GenerateMeasurable.basic _ ⟨_, rfl⟩
refine generateFrom_le ?_
rintro _ ⟨a, rfl | rfl⟩
· rcases em (∃ b, a ⋖ b) with ⟨b, hb⟩ | hcovBy
· rw [hb.Ioi_eq, ← compl_Iio]
exact (H _).compl
· rcases isOpen_biUnion_countable (Ioi a) Ioi fun _ _ ↦ isOpen_Ioi with ⟨t, hat, htc, htU⟩
have : Ioi a = ⋃ b ∈ t, Ici b := by
refine Subset.antisymm ?_ <| iUnion₂_subset fun b hb ↦ Ici_subset_Ioi.2 (hat hb)
refine Subset.trans ?_ <| iUnion₂_mono fun _ _ ↦ Ioi_subset_Ici_self
simpa [CovBy, htU, subset_def] using hcovBy
simp only [this, ← compl_Iio]
exact .biUnion htc <| fun _ _ ↦ (H _).compl
· apply H
· rw [forall_mem_range]
intro a
exact GenerateMeasurable.basic _ isOpen_Iio
theorem borel_eq_generateFrom_Ioi : borel α = .generateFrom (range Ioi) :=
@borel_eq_generateFrom_Iio αᵒᵈ _ (by infer_instance : SecondCountableTopology α) _ _
theorem borel_eq_generateFrom_Iic :
borel α = MeasurableSpace.generateFrom (range Iic) := by
rw [borel_eq_generateFrom_Ioi]
refine le_antisymm ?_ ?_
· refine MeasurableSpace.generateFrom_le fun t ht => ?_
obtain ⟨u, rfl⟩ := ht
rw [← compl_Iic]
exact (MeasurableSpace.measurableSet_generateFrom (mem_range.mpr ⟨u, rfl⟩)).compl
· refine MeasurableSpace.generateFrom_le fun t ht => ?_
obtain ⟨u, rfl⟩ := ht
rw [← compl_Ioi]
exact (MeasurableSpace.measurableSet_generateFrom (mem_range.mpr ⟨u, rfl⟩)).compl
theorem borel_eq_generateFrom_Ici : borel α = MeasurableSpace.generateFrom (range Ici) :=
@borel_eq_generateFrom_Iic αᵒᵈ _ _ _ _
end OrderTopology
section Orders
variable [TopologicalSpace α] {mα : MeasurableSpace α} [OpensMeasurableSpace α]
variable {mδ : MeasurableSpace δ}
section Preorder
variable [Preorder α] [OrderClosedTopology α] {a b x : α} {μ : Measure α}
@[simp, measurability]
theorem measurableSet_Ici : MeasurableSet (Ici a) :=
isClosed_Ici.measurableSet
theorem nullMeasurableSet_Ici : NullMeasurableSet (Ici a) μ :=
measurableSet_Ici.nullMeasurableSet
@[simp, measurability]
theorem measurableSet_Iic : MeasurableSet (Iic a) :=
isClosed_Iic.measurableSet
theorem nullMeasurableSet_Iic : NullMeasurableSet (Iic a) μ :=
measurableSet_Iic.nullMeasurableSet
@[simp, measurability]
theorem measurableSet_Icc : MeasurableSet (Icc a b) :=
isClosed_Icc.measurableSet
theorem nullMeasurableSet_Icc : NullMeasurableSet (Icc a b) μ :=
measurableSet_Icc.nullMeasurableSet
instance nhdsWithin_Ici_isMeasurablyGenerated : (𝓝[Ici b] a).IsMeasurablyGenerated :=
measurableSet_Ici.nhdsWithin_isMeasurablyGenerated _
instance nhdsWithin_Iic_isMeasurablyGenerated : (𝓝[Iic b] a).IsMeasurablyGenerated :=
measurableSet_Iic.nhdsWithin_isMeasurablyGenerated _
instance nhdsWithin_Icc_isMeasurablyGenerated : IsMeasurablyGenerated (𝓝[Icc a b] x) := by
rw [← Ici_inter_Iic, nhdsWithin_inter]
infer_instance
instance atTop_isMeasurablyGenerated : (Filter.atTop : Filter α).IsMeasurablyGenerated :=
@Filter.iInf_isMeasurablyGenerated _ _ _ _ fun a =>
(measurableSet_Ici : MeasurableSet (Ici a)).principal_isMeasurablyGenerated
instance atBot_isMeasurablyGenerated : (Filter.atBot : Filter α).IsMeasurablyGenerated :=
@Filter.iInf_isMeasurablyGenerated _ _ _ _ fun a =>
(measurableSet_Iic : MeasurableSet (Iic a)).principal_isMeasurablyGenerated
instance [R1Space α] : IsMeasurablyGenerated (cocompact α) where
exists_measurable_subset := by
intro _ hs
obtain ⟨t, ht, hts⟩ := mem_cocompact.mp hs
exact ⟨(closure t)ᶜ, ht.closure.compl_mem_cocompact, isClosed_closure.measurableSet.compl,
(compl_subset_compl.2 subset_closure).trans hts⟩
end Preorder
section PartialOrder
variable [PartialOrder α] [OrderClosedTopology α] [SecondCountableTopology α] {a b : α}
@[measurability]
theorem measurableSet_le' : MeasurableSet { p : α × α | p.1 ≤ p.2 } :=
OrderClosedTopology.isClosed_le'.measurableSet
@[measurability]
theorem measurableSet_le {f g : δ → α} (hf : Measurable f) (hg : Measurable g) :
MeasurableSet { a | f a ≤ g a } :=
hf.prodMk hg measurableSet_le'
end PartialOrder
section LinearOrder
variable [LinearOrder α] [OrderClosedTopology α] {a b x : α} {μ : Measure α}
-- we open this locale only here to avoid issues with list being treated as intervals above
open Interval
@[simp, measurability]
theorem measurableSet_Iio : MeasurableSet (Iio a) :=
isOpen_Iio.measurableSet
theorem nullMeasurableSet_Iio : NullMeasurableSet (Iio a) μ :=
measurableSet_Iio.nullMeasurableSet
@[simp, measurability]
theorem measurableSet_Ioi : MeasurableSet (Ioi a) :=
isOpen_Ioi.measurableSet
theorem nullMeasurableSet_Ioi : NullMeasurableSet (Ioi a) μ :=
measurableSet_Ioi.nullMeasurableSet
@[simp, measurability]
theorem measurableSet_Ioo : MeasurableSet (Ioo a b) :=
isOpen_Ioo.measurableSet
theorem nullMeasurableSet_Ioo : NullMeasurableSet (Ioo a b) μ :=
measurableSet_Ioo.nullMeasurableSet
@[simp, measurability]
theorem measurableSet_Ioc : MeasurableSet (Ioc a b) :=
measurableSet_Ioi.inter measurableSet_Iic
theorem nullMeasurableSet_Ioc : NullMeasurableSet (Ioc a b) μ :=
measurableSet_Ioc.nullMeasurableSet
@[simp, measurability]
theorem measurableSet_Ico : MeasurableSet (Ico a b) :=
measurableSet_Ici.inter measurableSet_Iio
theorem nullMeasurableSet_Ico : NullMeasurableSet (Ico a b) μ :=
measurableSet_Ico.nullMeasurableSet
instance nhdsWithin_Ioi_isMeasurablyGenerated : (𝓝[Ioi b] a).IsMeasurablyGenerated :=
measurableSet_Ioi.nhdsWithin_isMeasurablyGenerated _
instance nhdsWithin_Iio_isMeasurablyGenerated : (𝓝[Iio b] a).IsMeasurablyGenerated :=
measurableSet_Iio.nhdsWithin_isMeasurablyGenerated _
instance nhdsWithin_uIcc_isMeasurablyGenerated : IsMeasurablyGenerated (𝓝[[[a, b]]] x) :=
nhdsWithin_Icc_isMeasurablyGenerated
@[measurability]
theorem measurableSet_lt' [SecondCountableTopology α] : MeasurableSet { p : α × α | p.1 < p.2 } :=
(isOpen_lt continuous_fst continuous_snd).measurableSet
@[measurability]
theorem measurableSet_lt [SecondCountableTopology α] {f g : δ → α} (hf : Measurable f)
(hg : Measurable g) : MeasurableSet { a | f a < g a } :=
hf.prodMk hg measurableSet_lt'
theorem nullMeasurableSet_lt [SecondCountableTopology α] {μ : Measure δ} {f g : δ → α}
(hf : AEMeasurable f μ) (hg : AEMeasurable g μ) : NullMeasurableSet { a | f a < g a } μ :=
(hf.prodMk hg).nullMeasurable measurableSet_lt'
theorem nullMeasurableSet_lt' [SecondCountableTopology α] {μ : Measure (α × α)} :
NullMeasurableSet { p : α × α | p.1 < p.2 } μ :=
measurableSet_lt'.nullMeasurableSet
theorem nullMeasurableSet_le [SecondCountableTopology α] {μ : Measure δ}
{f g : δ → α} (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
NullMeasurableSet { a | f a ≤ g a } μ :=
(hf.prodMk hg).nullMeasurable measurableSet_le'
theorem Set.OrdConnected.measurableSet (h : OrdConnected s) : MeasurableSet s := by
let u := ⋃ (x ∈ s) (y ∈ s), Ioo x y
have huopen : IsOpen u := isOpen_biUnion fun _ _ => isOpen_biUnion fun _ _ => isOpen_Ioo
have humeas : MeasurableSet u := huopen.measurableSet
have hfinite : (s \ u).Finite := s.finite_diff_iUnion_Ioo
have : u ⊆ s := iUnion₂_subset fun x hx => iUnion₂_subset fun y hy =>
Ioo_subset_Icc_self.trans (h.out hx hy)
rw [← union_diff_cancel this]
exact humeas.union hfinite.measurableSet
theorem IsPreconnected.measurableSet (h : IsPreconnected s) : MeasurableSet s :=
h.ordConnected.measurableSet
theorem generateFrom_Ico_mem_le_borel {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderClosedTopology α] (s t : Set α) :
MeasurableSpace.generateFrom { S | ∃ l ∈ s, ∃ u ∈ t, l < u ∧ Ico l u = S }
≤ borel α := by
apply generateFrom_le
borelize α
rintro _ ⟨a, -, b, -, -, rfl⟩
exact measurableSet_Ico
theorem Dense.borel_eq_generateFrom_Ico_mem_aux {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] {s : Set α} (hd : Dense s)
(hbot : ∀ x, IsBot x → x ∈ s) (hIoo : ∀ x y : α, x < y → Ioo x y = ∅ → y ∈ s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ico l u = S } := by
set S : Set (Set α) := { S | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ico l u = S }
refine le_antisymm ?_ (generateFrom_Ico_mem_le_borel _ _)
letI : MeasurableSpace α := generateFrom S
rw [borel_eq_generateFrom_Iio]
refine generateFrom_le (forall_mem_range.2 fun a => ?_)
rcases hd.exists_countable_dense_subset_bot_top with ⟨t, hts, hc, htd, htb, -⟩
by_cases ha : ∀ b < a, (Ioo b a).Nonempty
· convert_to MeasurableSet (⋃ (l ∈ t) (u ∈ t) (_ : l < u) (_ : u ≤ a), Ico l u)
· ext y
simp only [mem_iUnion, mem_Iio, mem_Ico]
constructor
· intro hy
rcases htd.exists_le' (fun b hb => htb _ hb (hbot b hb)) y with ⟨l, hlt, hly⟩
rcases htd.exists_mem_open isOpen_Ioo (ha y hy) with ⟨u, hut, hyu, hua⟩
exact ⟨l, hlt, u, hut, hly.trans_lt hyu, hua.le, hly, hyu⟩
· rintro ⟨l, -, u, -, -, hua, -, hyu⟩
exact hyu.trans_le hua
· refine MeasurableSet.biUnion hc fun a ha => MeasurableSet.biUnion hc fun b hb => ?_
refine MeasurableSet.iUnion fun hab => MeasurableSet.iUnion fun _ => ?_
exact .basic _ ⟨a, hts ha, b, hts hb, hab, mem_singleton _⟩
· simp only [not_forall, not_nonempty_iff_eq_empty] at ha
replace ha : a ∈ s := hIoo ha.choose a ha.choose_spec.fst ha.choose_spec.snd
convert_to MeasurableSet (⋃ (l ∈ t) (_ : l < a), Ico l a)
· symm
simp only [← Ici_inter_Iio, ← iUnion_inter, inter_eq_right, subset_def, mem_iUnion,
mem_Ici, mem_Iio]
intro x hx
rcases htd.exists_le' (fun b hb => htb _ hb (hbot b hb)) x with ⟨z, hzt, hzx⟩
exact ⟨z, hzt, hzx.trans_lt hx, hzx⟩
· refine .biUnion hc fun x hx => MeasurableSet.iUnion fun hlt => ?_
exact .basic _ ⟨x, hts hx, a, ha, hlt, mem_singleton _⟩
theorem Dense.borel_eq_generateFrom_Ico_mem {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] [DenselyOrdered α] [NoMinOrder α] {s : Set α}
(hd : Dense s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ico l u = S } :=
hd.borel_eq_generateFrom_Ico_mem_aux (by simp) fun _ _ hxy H =>
((nonempty_Ioo.2 hxy).ne_empty H).elim
theorem borel_eq_generateFrom_Ico (α : Type*) [TopologicalSpace α] [SecondCountableTopology α]
[LinearOrder α] [OrderTopology α] :
borel α = .generateFrom { S : Set α | ∃ (l u : α), l < u ∧ Ico l u = S } := by
simpa only [exists_prop, mem_univ, true_and] using
(@dense_univ α _).borel_eq_generateFrom_Ico_mem_aux (fun _ _ => mem_univ _) fun _ _ _ _ =>
mem_univ _
theorem Dense.borel_eq_generateFrom_Ioc_mem_aux {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] {s : Set α} (hd : Dense s)
(hbot : ∀ x, IsTop x → x ∈ s) (hIoo : ∀ x y : α, x < y → Ioo x y = ∅ → x ∈ s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ioc l u = S } := by
convert hd.orderDual.borel_eq_generateFrom_Ico_mem_aux hbot fun x y hlt he => hIoo y x hlt _
using 2
· ext s
constructor <;> rintro ⟨l, hl, u, hu, hlt, rfl⟩
exacts [⟨u, hu, l, hl, hlt, Ico_toDual⟩, ⟨u, hu, l, hl, hlt, Ioc_toDual⟩]
· erw [Ioo_toDual]
exact he
theorem Dense.borel_eq_generateFrom_Ioc_mem {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] [DenselyOrdered α] [NoMaxOrder α] {s : Set α}
(hd : Dense s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ioc l u = S } :=
hd.borel_eq_generateFrom_Ioc_mem_aux (by simp) fun _ _ hxy H =>
((nonempty_Ioo.2 hxy).ne_empty H).elim
theorem borel_eq_generateFrom_Ioc (α : Type*) [TopologicalSpace α] [SecondCountableTopology α]
[LinearOrder α] [OrderTopology α] :
borel α = .generateFrom { S : Set α | ∃ l u, l < u ∧ Ioc l u = S } := by
simpa only [exists_prop, mem_univ, true_and] using
(@dense_univ α _).borel_eq_generateFrom_Ioc_mem_aux (fun _ _ => mem_univ _) fun _ _ _ _ =>
mem_univ _
namespace MeasureTheory.Measure
/-- Two finite measures on a Borel space are equal if they agree on all closed-open intervals. If
`α` is a conditionally complete linear order with no top element,
`MeasureTheory.Measure.ext_of_Ico` is an extensionality lemma with weaker assumptions on `μ` and
`ν`. -/
theorem ext_of_Ico_finite {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] (μ ν : Measure α)
[IsFiniteMeasure μ] (hμν : μ univ = ν univ) (h : ∀ ⦃a b⦄, a < b → μ (Ico a b) = ν (Ico a b)) :
μ = ν := by
refine
ext_of_generate_finite _ (BorelSpace.measurable_eq.trans (borel_eq_generateFrom_Ico α))
(isPiSystem_Ico (id : α → α) id) ?_ hμν
rintro - ⟨a, b, hlt, rfl⟩
exact h hlt
/-- Two finite measures on a Borel space are equal if they agree on all open-closed intervals. If
`α` is a conditionally complete linear order with no top element,
| `MeasureTheory.Measure.ext_of_Ioc` is an extensionality lemma with weaker assumptions on `μ` and
`ν`. -/
theorem ext_of_Ioc_finite {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] (μ ν : Measure α)
[IsFiniteMeasure μ] (hμν : μ univ = ν univ) (h : ∀ ⦃a b⦄, a < b → μ (Ioc a b) = ν (Ioc a b)) :
μ = ν := by
refine @ext_of_Ico_finite αᵒᵈ _ _ _ _ _ ‹_› μ ν _ hμν fun a b hab => ?_
erw [Ico_toDual (α := α)]
exact h hab
| Mathlib/MeasureTheory/Constructions/BorelSpace/Order.lean | 356 | 364 |
/-
Copyright (c) 2022 Antoine Labelle, Rémi Bottinelli. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Antoine Labelle, Rémi Bottinelli
-/
import Mathlib.Combinatorics.Quiver.Basic
import Mathlib.Combinatorics.Quiver.Path
/-!
# Rewriting arrows and paths along vertex equalities
This files defines `Hom.cast` and `Path.cast` (and associated lemmas) in order to allow
rewriting arrows and paths along equalities of their endpoints.
-/
universe v v₁ v₂ u u₁ u₂
variable {U : Type*} [Quiver.{u + 1} U]
namespace Quiver
/-!
### Rewriting arrows along equalities of vertices
-/
/-- Change the endpoints of an arrow using equalities. -/
def Hom.cast {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) : u' ⟶ v' :=
Eq.ndrec (motive := (· ⟶ v')) (Eq.ndrec e hv) hu
theorem Hom.cast_eq_cast {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) :
e.cast hu hv = _root_.cast (by {rw [hu, hv]}) e := by
subst_vars
rfl
@[simp]
theorem Hom.cast_rfl_rfl {u v : U} (e : u ⟶ v) : e.cast rfl rfl = e :=
rfl
@[simp]
theorem Hom.cast_cast {u v u' v' u'' v'' : U} (e : u ⟶ v) (hu : u = u') (hv : v = v')
(hu' : u' = u'') (hv' : v' = v'') :
(e.cast hu hv).cast hu' hv' = e.cast (hu.trans hu') (hv.trans hv') := by
subst_vars
rfl
|
theorem Hom.cast_heq {u v u' v' : U} (hu : u = u') (hv : v = v') (e : u ⟶ v) :
HEq (e.cast hu hv) e := by
subst_vars
rfl
| Mathlib/Combinatorics/Quiver/Cast.lean | 50 | 54 |
/-
Copyright (c) 2018 Michael Jendrusch. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Jendrusch, Kim Morrison, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Monoidal.Category
import Mathlib.CategoryTheory.Adjunction.FullyFaithful
import Mathlib.CategoryTheory.Products.Basic
/-!
# (Lax) monoidal functors
A lax monoidal functor `F` between monoidal categories `C` and `D`
is a functor between the underlying categories equipped with morphisms
* `ε : 𝟙_ D ⟶ F.obj (𝟙_ C)` (called the unit morphism)
* `μ X Y : (F.obj X) ⊗ (F.obj Y) ⟶ F.obj (X ⊗ Y)` (called the tensorator, or strength).
satisfying various axioms. This is implemented as a typeclass `F.LaxMonoidal`.
Similarly, we define the typeclass `F.OplaxMonoidal`. For these oplax monoidal functors,
we have similar data `η` and `δ`, but with morphisms in the opposite direction.
A monoidal functor (`F.Monoidal`) is defined here as the combination of `F.LaxMonoidal`
and `F.OplaxMonoidal`, with the additional conditions that `ε`/`η` and `μ`/`δ` are
inverse isomorphisms.
We show that the composition of (lax) monoidal functors gives a (lax) monoidal functor.
See `Mathlib.CategoryTheory.Monoidal.NaturalTransformation` for monoidal natural transformations.
We show in `Mathlib.CategoryTheory.Monoidal.Mon_` that lax monoidal functors take monoid objects
to monoid objects.
## References
See <https://stacks.math.columbia.edu/tag/0FFL>.
-/
universe v₁ v₂ v₃ v₁' u₁ u₂ u₃ u₁'
namespace CategoryTheory
open Category Functor MonoidalCategory
variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory.{v₁} C]
{D : Type u₂} [Category.{v₂} D] [MonoidalCategory.{v₂} D]
{E : Type u₃} [Category.{v₃} E] [MonoidalCategory.{v₃} E]
{C' : Type u₁'} [Category.{v₁'} C']
(F : C ⥤ D) (G : D ⥤ E)
namespace Functor
-- The direction of `left_unitality` and `right_unitality` as simp lemmas may look strange:
-- remember the rule of thumb that component indices of natural transformations
-- "weigh more" than structural maps.
-- (However by this argument `associativity` is currently stated backwards!)
/-- A functor `F : C ⥤ D` between monoidal categories is lax monoidal if it is
equipped with morphisms `ε : 𝟙_ D ⟶ F.obj (𝟙_ C)` and `μ X Y : F.obj X ⊗ F.obj Y ⟶ F.obj (X ⊗ Y)`,
satisfying the appropriate coherences. -/
@[ext]
class LaxMonoidal where
/-- unit morphism -/
ε' : 𝟙_ D ⟶ F.obj (𝟙_ C)
/-- tensorator -/
μ' : ∀ X Y : C, F.obj X ⊗ F.obj Y ⟶ F.obj (X ⊗ Y)
μ'_natural_left :
∀ {X Y : C} (f : X ⟶ Y) (X' : C),
F.map f ▷ F.obj X' ≫ μ' Y X' = μ' X X' ≫ F.map (f ▷ X') := by
aesop_cat
μ'_natural_right :
∀ {X Y : C} (X' : C) (f : X ⟶ Y) ,
F.obj X' ◁ F.map f ≫ μ' X' Y = μ' X' X ≫ F.map (X' ◁ f) := by
aesop_cat
/-- associativity of the tensorator -/
associativity' :
∀ X Y Z : C,
μ' X Y ▷ F.obj Z ≫ μ' (X ⊗ Y) Z ≫ F.map (α_ X Y Z).hom =
(α_ (F.obj X) (F.obj Y) (F.obj Z)).hom ≫ F.obj X ◁ μ' Y Z ≫ μ' X (Y ⊗ Z) := by
aesop_cat
-- unitality
left_unitality' :
∀ X : C, (λ_ (F.obj X)).hom = ε' ▷ F.obj X ≫ μ' (𝟙_ C) X ≫ F.map (λ_ X).hom := by
aesop_cat
right_unitality' :
∀ X : C, (ρ_ (F.obj X)).hom = F.obj X ◁ ε' ≫ μ' X (𝟙_ C) ≫ F.map (ρ_ X).hom := by
aesop_cat
namespace LaxMonoidal
section
variable [F.LaxMonoidal]
/-- the unit morphism of a lax monoidal functor -/
def ε : 𝟙_ D ⟶ F.obj (𝟙_ C) := ε'
/-- the tensorator of a lax monoidal functor -/
def μ (X Y : C) : F.obj X ⊗ F.obj Y ⟶ F.obj (X ⊗ Y) := μ' X Y
@[reassoc (attr := simp)]
lemma μ_natural_left {X Y : C} (f : X ⟶ Y) (X' : C) :
F.map f ▷ F.obj X' ≫ μ F Y X' = μ F X X' ≫ F.map (f ▷ X') := by
apply μ'_natural_left
@[reassoc (attr := simp)]
lemma μ_natural_right {X Y : C} (X' : C) (f : X ⟶ Y) :
F.obj X' ◁ F.map f ≫ μ F X' Y = μ F X' X ≫ F.map (X' ◁ f) := by
apply μ'_natural_right
@[reassoc (attr := simp)]
lemma associativity (X Y Z : C) :
μ F X Y ▷ F.obj Z ≫ μ F (X ⊗ Y) Z ≫ F.map (α_ X Y Z).hom =
(α_ (F.obj X) (F.obj Y) (F.obj Z)).hom ≫ F.obj X ◁ μ F Y Z ≫ μ F X (Y ⊗ Z) := by
apply associativity'
@[simp, reassoc]
lemma left_unitality (X : C) :
(λ_ (F.obj X)).hom = ε F ▷ F.obj X ≫ μ F (𝟙_ C) X ≫ F.map (λ_ X).hom := by
apply left_unitality'
@[simp, reassoc]
lemma right_unitality (X : C) :
(ρ_ (F.obj X)).hom = F.obj X ◁ ε F ≫ μ F X (𝟙_ C) ≫ F.map (ρ_ X).hom := by
apply right_unitality'
@[reassoc (attr := simp)]
theorem μ_natural {X Y X' Y' : C} (f : X ⟶ Y) (g : X' ⟶ Y') :
(F.map f ⊗ F.map g) ≫ μ F Y Y' = μ F X X' ≫ F.map (f ⊗ g) := by
simp [tensorHom_def]
@[reassoc (attr := simp)]
theorem left_unitality_inv (X : C) :
(λ_ (F.obj X)).inv ≫ ε F ▷ F.obj X ≫ μ F (𝟙_ C) X = F.map (λ_ X).inv := by
rw [Iso.inv_comp_eq, left_unitality, Category.assoc, Category.assoc, ← F.map_comp,
Iso.hom_inv_id, F.map_id, comp_id]
@[reassoc (attr := simp)]
theorem right_unitality_inv (X : C) :
(ρ_ (F.obj X)).inv ≫ F.obj X ◁ ε F ≫ μ F X (𝟙_ C) = F.map (ρ_ X).inv := by
rw [Iso.inv_comp_eq, right_unitality, Category.assoc, Category.assoc, ← F.map_comp,
Iso.hom_inv_id, F.map_id, comp_id]
@[reassoc (attr := simp)]
theorem associativity_inv (X Y Z : C) :
F.obj X ◁ μ F Y Z ≫ μ F X (Y ⊗ Z) ≫ F.map (α_ X Y Z).inv =
(α_ (F.obj X) (F.obj Y) (F.obj Z)).inv ≫ μ F X Y ▷ F.obj Z ≫ μ F (X ⊗ Y) Z := by
rw [Iso.eq_inv_comp, ← associativity_assoc, ← F.map_comp, Iso.hom_inv_id,
F.map_id, comp_id]
end
section
variable {F}
/- unit morphism -/
(ε' : 𝟙_ D ⟶ F.obj (𝟙_ C))
/- tensorator -/
(μ' : ∀ X Y : C, F.obj X ⊗ F.obj Y ⟶ F.obj (X ⊗ Y))
(μ'_natural :
∀ {X Y X' Y' : C} (f : X ⟶ Y) (g : X' ⟶ Y'),
(F.map f ⊗ F.map g) ≫ μ' Y Y' = μ' X X' ≫ F.map (f ⊗ g) := by
aesop_cat)
/- associativity of the tensorator -/
(associativity' :
∀ X Y Z : C,
(μ' X Y ⊗ 𝟙 (F.obj Z)) ≫ μ' (X ⊗ Y) Z ≫ F.map (α_ X Y Z).hom =
(α_ (F.obj X) (F.obj Y) (F.obj Z)).hom ≫ (𝟙 (F.obj X) ⊗ μ' Y Z) ≫ μ' X (Y ⊗ Z) := by
aesop_cat)
/- unitality -/
(left_unitality' :
∀ X : C, (λ_ (F.obj X)).hom = (ε' ⊗ 𝟙 (F.obj X)) ≫ μ' (𝟙_ C) X ≫ F.map (λ_ X).hom := by
aesop_cat)
(right_unitality' :
∀ X : C, (ρ_ (F.obj X)).hom = (𝟙 (F.obj X) ⊗ ε') ≫ μ' X (𝟙_ C) ≫ F.map (ρ_ X).hom := by
aesop_cat)
/--
A constructor for lax monoidal functors whose axioms are described by `tensorHom` instead of
`whiskerLeft` and `whiskerRight`.
-/
def ofTensorHom : F.LaxMonoidal where
ε' := ε'
μ' := μ'
μ'_natural_left := fun f X' => by
simp_rw [← tensorHom_id, ← F.map_id, μ'_natural]
μ'_natural_right := fun X' f => by
simp_rw [← id_tensorHom, ← F.map_id, μ'_natural]
associativity' := fun X Y Z => by
simp_rw [← tensorHom_id, ← id_tensorHom, associativity']
left_unitality' := fun X => by
simp_rw [← tensorHom_id, left_unitality']
right_unitality' := fun X => by
simp_rw [← id_tensorHom, right_unitality']
lemma ofTensorHom_ε :
letI := (ofTensorHom ε' μ' μ'_natural associativity' left_unitality' right_unitality')
ε F = ε' := rfl
lemma ofTensorHom_μ :
letI := (ofTensorHom ε' μ' μ'_natural associativity' left_unitality' right_unitality')
μ F = μ' := rfl
end
instance id : (𝟭 C).LaxMonoidal where
ε' := 𝟙 _
μ' _ _ := 𝟙 _
@[simp]
lemma id_ε : ε (𝟭 C) = 𝟙 _ := rfl
@[simp]
lemma id_μ (X Y : C) : μ (𝟭 C) X Y = 𝟙 _ := rfl
section
variable [F.LaxMonoidal] [G.LaxMonoidal]
instance comp : (F ⋙ G).LaxMonoidal where
ε' := ε G ≫ G.map (ε F)
μ' X Y := μ G _ _ ≫ G.map (μ F X Y)
μ'_natural_left _ _ := by
simp_rw [comp_obj, F.comp_map, μ_natural_left_assoc, assoc, ← G.map_comp, μ_natural_left]
μ'_natural_right _ _ := by
simp_rw [comp_obj, F.comp_map, μ_natural_right_assoc, assoc, ← G.map_comp, μ_natural_right]
associativity' _ _ _ := by
dsimp
simp_rw [comp_whiskerRight, assoc, μ_natural_left_assoc, MonoidalCategory.whiskerLeft_comp,
assoc, μ_natural_right_assoc, ← associativity_assoc, ← G.map_comp, associativity]
| @[simp]
lemma comp_ε : ε (F ⋙ G) = ε G ≫ G.map (ε F) := rfl
@[simp]
| Mathlib/CategoryTheory/Monoidal/Functor.lean | 231 | 234 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot
-/
import Mathlib.Order.Filter.SmallSets
import Mathlib.Topology.UniformSpace.Defs
import Mathlib.Topology.ContinuousOn
/-!
# Basic results on uniform spaces
Uniform spaces are a generalization of metric spaces and topological groups.
## Main definitions
In this file we define a complete lattice structure on the type `UniformSpace X`
of uniform structures on `X`, as well as the pullback (`UniformSpace.comap`) of uniform structures
coming from the pullback of filters.
Like distance functions, uniform structures cannot be pushed forward in general.
## Notations
Localized in `Uniformity`, we have the notation `𝓤 X` for the uniformity on a uniform space `X`,
and `○` for composition of relations, seen as terms with type `Set (X × X)`.
## References
The formalization uses the books:
* [N. Bourbaki, *General Topology*][bourbaki1966]
* [I. M. James, *Topologies and Uniformities*][james1999]
But it makes a more systematic use of the filter library.
-/
open Set Filter Topology
universe u v ua ub uc ud
/-!
### Relations, seen as `Set (α × α)`
-/
variable {α : Type ua} {β : Type ub} {γ : Type uc} {δ : Type ud} {ι : Sort*}
open Uniformity
section UniformSpace
variable [UniformSpace α]
/-- If `s ∈ 𝓤 α`, then for any natural `n`, for a subset `t` of a sufficiently small set in `𝓤 α`,
we have `t ○ t ○ ... ○ t ⊆ s` (`n` compositions). -/
theorem eventually_uniformity_iterate_comp_subset {s : Set (α × α)} (hs : s ∈ 𝓤 α) (n : ℕ) :
∀ᶠ t in (𝓤 α).smallSets, (t ○ ·)^[n] t ⊆ s := by
suffices ∀ᶠ t in (𝓤 α).smallSets, t ⊆ s ∧ (t ○ ·)^[n] t ⊆ s from (eventually_and.1 this).2
induction n generalizing s with
| zero => simpa
| succ _ ihn =>
rcases comp_mem_uniformity_sets hs with ⟨t, htU, hts⟩
refine (ihn htU).mono fun U hU => ?_
rw [Function.iterate_succ_apply']
exact
⟨hU.1.trans <| (subset_comp_self <| refl_le_uniformity htU).trans hts,
(compRel_mono hU.1 hU.2).trans hts⟩
/-- If `s ∈ 𝓤 α`, then for a subset `t` of a sufficiently small set in `𝓤 α`,
we have `t ○ t ⊆ s`. -/
theorem eventually_uniformity_comp_subset {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∀ᶠ t in (𝓤 α).smallSets, t ○ t ⊆ s :=
eventually_uniformity_iterate_comp_subset hs 1
/-!
### Balls in uniform spaces
-/
namespace UniformSpace
open UniformSpace (ball)
lemma isOpen_ball (x : α) {V : Set (α × α)} (hV : IsOpen V) : IsOpen (ball x V) :=
hV.preimage <| .prodMk_right _
lemma isClosed_ball (x : α) {V : Set (α × α)} (hV : IsClosed V) : IsClosed (ball x V) :=
hV.preimage <| .prodMk_right _
/-!
### Neighborhoods in uniform spaces
-/
theorem hasBasis_nhds_prod (x y : α) :
HasBasis (𝓝 (x, y)) (fun s => s ∈ 𝓤 α ∧ IsSymmetricRel s) fun s => ball x s ×ˢ ball y s := by
rw [nhds_prod_eq]
apply (hasBasis_nhds x).prod_same_index (hasBasis_nhds y)
rintro U V ⟨U_in, U_symm⟩ ⟨V_in, V_symm⟩
exact
⟨U ∩ V, ⟨(𝓤 α).inter_sets U_in V_in, U_symm.inter V_symm⟩, ball_inter_left x U V,
ball_inter_right y U V⟩
end UniformSpace
open UniformSpace
theorem nhds_eq_uniformity_prod {a b : α} :
𝓝 (a, b) =
(𝓤 α).lift' fun s : Set (α × α) => { y : α | (y, a) ∈ s } ×ˢ { y : α | (b, y) ∈ s } := by
rw [nhds_prod_eq, nhds_nhds_eq_uniformity_uniformity_prod, lift_lift'_same_eq_lift']
· exact fun s => monotone_const.set_prod monotone_preimage
· refine fun t => Monotone.set_prod ?_ monotone_const
exact monotone_preimage (f := fun y => (y, a))
theorem nhdset_of_mem_uniformity {d : Set (α × α)} (s : Set (α × α)) (hd : d ∈ 𝓤 α) :
∃ t : Set (α × α), IsOpen t ∧ s ⊆ t ∧
t ⊆ { p | ∃ x y, (p.1, x) ∈ d ∧ (x, y) ∈ s ∧ (y, p.2) ∈ d } := by
let cl_d := { p : α × α | ∃ x y, (p.1, x) ∈ d ∧ (x, y) ∈ s ∧ (y, p.2) ∈ d }
have : ∀ p ∈ s, ∃ t, t ⊆ cl_d ∧ IsOpen t ∧ p ∈ t := fun ⟨x, y⟩ hp =>
mem_nhds_iff.mp <|
show cl_d ∈ 𝓝 (x, y) by
rw [nhds_eq_uniformity_prod, mem_lift'_sets]
· exact ⟨d, hd, fun ⟨a, b⟩ ⟨ha, hb⟩ => ⟨x, y, ha, hp, hb⟩⟩
· exact fun _ _ h _ h' => ⟨h h'.1, h h'.2⟩
choose t ht using this
exact ⟨(⋃ p : α × α, ⋃ h : p ∈ s, t p h : Set (α × α)),
isOpen_iUnion fun p : α × α => isOpen_iUnion fun hp => (ht p hp).right.left,
fun ⟨a, b⟩ hp => by
simp only [mem_iUnion, Prod.exists]; exact ⟨a, b, hp, (ht (a, b) hp).right.right⟩,
iUnion_subset fun p => iUnion_subset fun hp => (ht p hp).left⟩
/-- Entourages are neighborhoods of the diagonal. -/
theorem nhds_le_uniformity (x : α) : 𝓝 (x, x) ≤ 𝓤 α := by
intro V V_in
rcases comp_symm_mem_uniformity_sets V_in with ⟨w, w_in, w_symm, w_sub⟩
have : ball x w ×ˢ ball x w ∈ 𝓝 (x, x) := by
rw [nhds_prod_eq]
exact prod_mem_prod (ball_mem_nhds x w_in) (ball_mem_nhds x w_in)
apply mem_of_superset this
rintro ⟨u, v⟩ ⟨u_in, v_in⟩
exact w_sub (mem_comp_of_mem_ball w_symm u_in v_in)
/-- Entourages are neighborhoods of the diagonal. -/
theorem iSup_nhds_le_uniformity : ⨆ x : α, 𝓝 (x, x) ≤ 𝓤 α :=
iSup_le nhds_le_uniformity
/-- Entourages are neighborhoods of the diagonal. -/
theorem nhdsSet_diagonal_le_uniformity : 𝓝ˢ (diagonal α) ≤ 𝓤 α :=
(nhdsSet_diagonal α).trans_le iSup_nhds_le_uniformity
section
variable (α)
theorem UniformSpace.has_seq_basis [IsCountablyGenerated <| 𝓤 α] :
∃ V : ℕ → Set (α × α), HasAntitoneBasis (𝓤 α) V ∧ ∀ n, IsSymmetricRel (V n) :=
let ⟨U, hsym, hbasis⟩ := (@UniformSpace.hasBasis_symmetric α _).exists_antitone_subbasis
⟨U, hbasis, fun n => (hsym n).2⟩
end
/-!
### Closure and interior in uniform spaces
-/
theorem closure_eq_uniformity (s : Set <| α × α) :
closure s = ⋂ V ∈ { V | V ∈ 𝓤 α ∧ IsSymmetricRel V }, V ○ s ○ V := by
ext ⟨x, y⟩
simp +contextual only
[mem_closure_iff_nhds_basis (UniformSpace.hasBasis_nhds_prod x y), mem_iInter, mem_setOf_eq,
and_imp, mem_comp_comp, exists_prop, ← mem_inter_iff, inter_comm, Set.Nonempty]
theorem uniformity_hasBasis_closed :
HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsClosed V) id := by
refine Filter.hasBasis_self.2 fun t h => ?_
rcases comp_comp_symm_mem_uniformity_sets h with ⟨w, w_in, w_symm, r⟩
refine ⟨closure w, mem_of_superset w_in subset_closure, isClosed_closure, ?_⟩
refine Subset.trans ?_ r
rw [closure_eq_uniformity]
apply iInter_subset_of_subset
apply iInter_subset
exact ⟨w_in, w_symm⟩
theorem uniformity_eq_uniformity_closure : 𝓤 α = (𝓤 α).lift' closure :=
Eq.symm <| uniformity_hasBasis_closed.lift'_closure_eq_self fun _ => And.right
theorem Filter.HasBasis.uniformity_closure {p : ι → Prop} {U : ι → Set (α × α)}
(h : (𝓤 α).HasBasis p U) : (𝓤 α).HasBasis p fun i => closure (U i) :=
(@uniformity_eq_uniformity_closure α _).symm ▸ h.lift'_closure
/-- Closed entourages form a basis of the uniformity filter. -/
theorem uniformity_hasBasis_closure : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α) closure :=
(𝓤 α).basis_sets.uniformity_closure
theorem closure_eq_inter_uniformity {t : Set (α × α)} : closure t = ⋂ d ∈ 𝓤 α, d ○ (t ○ d) :=
calc
closure t = ⋂ (V) (_ : V ∈ 𝓤 α ∧ IsSymmetricRel V), V ○ t ○ V := closure_eq_uniformity t
_ = ⋂ V ∈ 𝓤 α, V ○ t ○ V :=
Eq.symm <|
UniformSpace.hasBasis_symmetric.biInter_mem fun _ _ hV =>
compRel_mono (compRel_mono hV Subset.rfl) hV
_ = ⋂ V ∈ 𝓤 α, V ○ (t ○ V) := by simp only [compRel_assoc]
theorem uniformity_eq_uniformity_interior : 𝓤 α = (𝓤 α).lift' interior :=
le_antisymm
(le_iInf₂ fun d hd => by
let ⟨s, hs, hs_comp⟩ := comp3_mem_uniformity hd
let ⟨t, ht, hst, ht_comp⟩ := nhdset_of_mem_uniformity s hs
have : s ⊆ interior d :=
calc
s ⊆ t := hst
_ ⊆ interior d :=
ht.subset_interior_iff.mpr fun x (hx : x ∈ t) =>
let ⟨x, y, h₁, h₂, h₃⟩ := ht_comp hx
hs_comp ⟨x, h₁, y, h₂, h₃⟩
have : interior d ∈ 𝓤 α := by filter_upwards [hs] using this
simp [this])
fun _ hs => ((𝓤 α).lift' interior).sets_of_superset (mem_lift' hs) interior_subset
theorem interior_mem_uniformity {s : Set (α × α)} (hs : s ∈ 𝓤 α) : interior s ∈ 𝓤 α := by
rw [uniformity_eq_uniformity_interior]; exact mem_lift' hs
theorem mem_uniformity_isClosed {s : Set (α × α)} (h : s ∈ 𝓤 α) : ∃ t ∈ 𝓤 α, IsClosed t ∧ t ⊆ s :=
let ⟨t, ⟨ht_mem, htc⟩, hts⟩ := uniformity_hasBasis_closed.mem_iff.1 h
⟨t, ht_mem, htc, hts⟩
theorem isOpen_iff_isOpen_ball_subset {s : Set α} :
IsOpen s ↔ ∀ x ∈ s, ∃ V ∈ 𝓤 α, IsOpen V ∧ ball x V ⊆ s := by
rw [isOpen_iff_ball_subset]
constructor <;> intro h x hx
· obtain ⟨V, hV, hV'⟩ := h x hx
exact
⟨interior V, interior_mem_uniformity hV, isOpen_interior,
(ball_mono interior_subset x).trans hV'⟩
· obtain ⟨V, hV, -, hV'⟩ := h x hx
exact ⟨V, hV, hV'⟩
@[deprecated (since := "2024-11-18")] alias
isOpen_iff_open_ball_subset := isOpen_iff_isOpen_ball_subset
/-- The uniform neighborhoods of all points of a dense set cover the whole space. -/
theorem Dense.biUnion_uniformity_ball {s : Set α} {U : Set (α × α)} (hs : Dense s) (hU : U ∈ 𝓤 α) :
⋃ x ∈ s, ball x U = univ := by
refine iUnion₂_eq_univ_iff.2 fun y => ?_
rcases hs.inter_nhds_nonempty (mem_nhds_right y hU) with ⟨x, hxs, hxy : (x, y) ∈ U⟩
exact ⟨x, hxs, hxy⟩
/-- The uniform neighborhoods of all points of a dense indexed collection cover the whole space. -/
lemma DenseRange.iUnion_uniformity_ball {ι : Type*} {xs : ι → α}
(xs_dense : DenseRange xs) {U : Set (α × α)} (hU : U ∈ uniformity α) :
⋃ i, UniformSpace.ball (xs i) U = univ := by
rw [← biUnion_range (f := xs) (g := fun x ↦ UniformSpace.ball x U)]
exact Dense.biUnion_uniformity_ball xs_dense hU
/-!
### Uniformity bases
-/
/-- Open elements of `𝓤 α` form a basis of `𝓤 α`. -/
theorem uniformity_hasBasis_open : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsOpen V) id :=
hasBasis_self.2 fun s hs =>
⟨interior s, interior_mem_uniformity hs, isOpen_interior, interior_subset⟩
theorem Filter.HasBasis.mem_uniformity_iff {p : β → Prop} {s : β → Set (α × α)}
(h : (𝓤 α).HasBasis p s) {t : Set (α × α)} :
t ∈ 𝓤 α ↔ ∃ i, p i ∧ ∀ a b, (a, b) ∈ s i → (a, b) ∈ t :=
h.mem_iff.trans <| by simp only [Prod.forall, subset_def]
/-- Open elements `s : Set (α × α)` of `𝓤 α` such that `(x, y) ∈ s ↔ (y, x) ∈ s` form a basis
of `𝓤 α`. -/
theorem uniformity_hasBasis_open_symmetric :
HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsOpen V ∧ IsSymmetricRel V) id := by
simp only [← and_assoc]
refine uniformity_hasBasis_open.restrict fun s hs => ⟨symmetrizeRel s, ?_⟩
exact
⟨⟨symmetrize_mem_uniformity hs.1, IsOpen.inter hs.2 (hs.2.preimage continuous_swap)⟩,
symmetric_symmetrizeRel s, symmetrizeRel_subset_self s⟩
theorem comp_open_symm_mem_uniformity_sets {s : Set (α × α)} (hs : s ∈ 𝓤 α) :
∃ t ∈ 𝓤 α, IsOpen t ∧ IsSymmetricRel t ∧ t ○ t ⊆ s := by
obtain ⟨t, ht₁, ht₂⟩ := comp_mem_uniformity_sets hs
obtain ⟨u, ⟨hu₁, hu₂, hu₃⟩, hu₄ : u ⊆ t⟩ := uniformity_hasBasis_open_symmetric.mem_iff.mp ht₁
exact ⟨u, hu₁, hu₂, hu₃, (compRel_mono hu₄ hu₄).trans ht₂⟩
end UniformSpace
open uniformity
section Constructions
instance : PartialOrder (UniformSpace α) :=
PartialOrder.lift (fun u => 𝓤[u]) fun _ _ => UniformSpace.ext
protected theorem UniformSpace.le_def {u₁ u₂ : UniformSpace α} : u₁ ≤ u₂ ↔ 𝓤[u₁] ≤ 𝓤[u₂] := Iff.rfl
instance : InfSet (UniformSpace α) :=
⟨fun s =>
UniformSpace.ofCore
{ uniformity := ⨅ u ∈ s, 𝓤[u]
refl := le_iInf fun u => le_iInf fun _ => u.toCore.refl
symm := le_iInf₂ fun u hu =>
le_trans (map_mono <| iInf_le_of_le _ <| iInf_le _ hu) u.symm
comp := le_iInf₂ fun u hu =>
le_trans (lift'_mono (iInf_le_of_le _ <| iInf_le _ hu) <| le_rfl) u.comp }⟩
protected theorem UniformSpace.sInf_le {tt : Set (UniformSpace α)} {t : UniformSpace α}
(h : t ∈ tt) : sInf tt ≤ t :=
show ⨅ u ∈ tt, 𝓤[u] ≤ 𝓤[t] from iInf₂_le t h
protected theorem UniformSpace.le_sInf {tt : Set (UniformSpace α)} {t : UniformSpace α}
(h : ∀ t' ∈ tt, t ≤ t') : t ≤ sInf tt :=
show 𝓤[t] ≤ ⨅ u ∈ tt, 𝓤[u] from le_iInf₂ h
instance : Top (UniformSpace α) :=
⟨@UniformSpace.mk α ⊤ ⊤ le_top le_top fun x ↦ by simp only [nhds_top, comap_top]⟩
instance : Bot (UniformSpace α) :=
⟨{ toTopologicalSpace := ⊥
uniformity := 𝓟 idRel
symm := by simp [Tendsto]
comp := lift'_le (mem_principal_self _) <| principal_mono.2 id_compRel.subset
nhds_eq_comap_uniformity := fun s => by
let _ : TopologicalSpace α := ⊥; have := discreteTopology_bot α
simp [idRel] }⟩
instance : Min (UniformSpace α) :=
⟨fun u₁ u₂ =>
{ uniformity := 𝓤[u₁] ⊓ 𝓤[u₂]
symm := u₁.symm.inf u₂.symm
comp := (lift'_inf_le _ _ _).trans <| inf_le_inf u₁.comp u₂.comp
toTopologicalSpace := u₁.toTopologicalSpace ⊓ u₂.toTopologicalSpace
nhds_eq_comap_uniformity := fun _ ↦ by
rw [@nhds_inf _ u₁.toTopologicalSpace _, @nhds_eq_comap_uniformity _ u₁,
@nhds_eq_comap_uniformity _ u₂, comap_inf] }⟩
instance : CompleteLattice (UniformSpace α) :=
{ inferInstanceAs (PartialOrder (UniformSpace α)) with
sup := fun a b => sInf { x | a ≤ x ∧ b ≤ x }
le_sup_left := fun _ _ => UniformSpace.le_sInf fun _ ⟨h, _⟩ => h
le_sup_right := fun _ _ => UniformSpace.le_sInf fun _ ⟨_, h⟩ => h
sup_le := fun _ _ _ h₁ h₂ => UniformSpace.sInf_le ⟨h₁, h₂⟩
inf := (· ⊓ ·)
le_inf := fun a _ _ h₁ h₂ => show a.uniformity ≤ _ from le_inf h₁ h₂
inf_le_left := fun a _ => show _ ≤ a.uniformity from inf_le_left
inf_le_right := fun _ b => show _ ≤ b.uniformity from inf_le_right
top := ⊤
le_top := fun a => show a.uniformity ≤ ⊤ from le_top
bot := ⊥
bot_le := fun u => u.toCore.refl
sSup := fun tt => sInf { t | ∀ t' ∈ tt, t' ≤ t }
le_sSup := fun _ _ h => UniformSpace.le_sInf fun _ h' => h' _ h
sSup_le := fun _ _ h => UniformSpace.sInf_le h
sInf := sInf
le_sInf := fun _ _ hs => UniformSpace.le_sInf hs
sInf_le := fun _ _ ha => UniformSpace.sInf_le ha }
theorem iInf_uniformity {ι : Sort*} {u : ι → UniformSpace α} : 𝓤[iInf u] = ⨅ i, 𝓤[u i] :=
iInf_range
theorem inf_uniformity {u v : UniformSpace α} : 𝓤[u ⊓ v] = 𝓤[u] ⊓ 𝓤[v] := rfl
lemma bot_uniformity : 𝓤[(⊥ : UniformSpace α)] = 𝓟 idRel := rfl
lemma top_uniformity : 𝓤[(⊤ : UniformSpace α)] = ⊤ := rfl
instance inhabitedUniformSpace : Inhabited (UniformSpace α) :=
⟨⊥⟩
instance inhabitedUniformSpaceCore : Inhabited (UniformSpace.Core α) :=
⟨@UniformSpace.toCore _ default⟩
instance [Subsingleton α] : Unique (UniformSpace α) where
uniq u := bot_unique <| le_principal_iff.2 <| by
rw [idRel, ← diagonal, diagonal_eq_univ]; exact univ_mem
/-- Given `f : α → β` and a uniformity `u` on `β`, the inverse image of `u` under `f`
is the inverse image in the filter sense of the induced function `α × α → β × β`.
See note [reducible non-instances]. -/
abbrev UniformSpace.comap (f : α → β) (u : UniformSpace β) : UniformSpace α where
uniformity := 𝓤[u].comap fun p : α × α => (f p.1, f p.2)
symm := by
simp only [tendsto_comap_iff, Prod.swap, (· ∘ ·)]
exact tendsto_swap_uniformity.comp tendsto_comap
comp := le_trans
(by
rw [comap_lift'_eq, comap_lift'_eq2]
· exact lift'_mono' fun s _ ⟨a₁, a₂⟩ ⟨x, h₁, h₂⟩ => ⟨f x, h₁, h₂⟩
· exact monotone_id.compRel monotone_id)
(comap_mono u.comp)
toTopologicalSpace := u.toTopologicalSpace.induced f
nhds_eq_comap_uniformity x := by
simp only [nhds_induced, nhds_eq_comap_uniformity, comap_comap, Function.comp_def]
theorem uniformity_comap {_ : UniformSpace β} (f : α → β) :
𝓤[UniformSpace.comap f ‹_›] = comap (Prod.map f f) (𝓤 β) :=
rfl
lemma ball_preimage {f : α → β} {U : Set (β × β)} {x : α} :
UniformSpace.ball x (Prod.map f f ⁻¹' U) = f ⁻¹' UniformSpace.ball (f x) U := by
ext : 1
simp only [UniformSpace.ball, mem_preimage, Prod.map_apply]
@[simp]
theorem uniformSpace_comap_id {α : Type*} : UniformSpace.comap (id : α → α) = id := by
ext : 2
rw [uniformity_comap, Prod.map_id, comap_id]
theorem UniformSpace.comap_comap {α β γ} {uγ : UniformSpace γ} {f : α → β} {g : β → γ} :
UniformSpace.comap (g ∘ f) uγ = UniformSpace.comap f (UniformSpace.comap g uγ) := by
ext1
simp only [uniformity_comap, Filter.comap_comap, Prod.map_comp_map]
theorem UniformSpace.comap_inf {α γ} {u₁ u₂ : UniformSpace γ} {f : α → γ} :
(u₁ ⊓ u₂).comap f = u₁.comap f ⊓ u₂.comap f :=
UniformSpace.ext Filter.comap_inf
theorem UniformSpace.comap_iInf {ι α γ} {u : ι → UniformSpace γ} {f : α → γ} :
(⨅ i, u i).comap f = ⨅ i, (u i).comap f := by
ext : 1
simp [uniformity_comap, iInf_uniformity]
theorem UniformSpace.comap_mono {α γ} {f : α → γ} :
Monotone fun u : UniformSpace γ => u.comap f := fun _ _ hu =>
Filter.comap_mono hu
theorem uniformContinuous_iff {α β} {uα : UniformSpace α} {uβ : UniformSpace β} {f : α → β} :
UniformContinuous f ↔ uα ≤ uβ.comap f :=
Filter.map_le_iff_le_comap
theorem le_iff_uniformContinuous_id {u v : UniformSpace α} :
u ≤ v ↔ @UniformContinuous _ _ u v id := by
rw [uniformContinuous_iff, uniformSpace_comap_id, id]
theorem uniformContinuous_comap {f : α → β} [u : UniformSpace β] :
@UniformContinuous α β (UniformSpace.comap f u) u f :=
tendsto_comap
theorem uniformContinuous_comap' {f : γ → β} {g : α → γ} [v : UniformSpace β] [u : UniformSpace α]
(h : UniformContinuous (f ∘ g)) : @UniformContinuous α γ u (UniformSpace.comap f v) g :=
tendsto_comap_iff.2 h
namespace UniformSpace
theorem to_nhds_mono {u₁ u₂ : UniformSpace α} (h : u₁ ≤ u₂) (a : α) :
@nhds _ (@UniformSpace.toTopologicalSpace _ u₁) a ≤
@nhds _ (@UniformSpace.toTopologicalSpace _ u₂) a := by
rw [@nhds_eq_uniformity α u₁ a, @nhds_eq_uniformity α u₂ a]; exact lift'_mono h le_rfl
theorem toTopologicalSpace_mono {u₁ u₂ : UniformSpace α} (h : u₁ ≤ u₂) :
@UniformSpace.toTopologicalSpace _ u₁ ≤ @UniformSpace.toTopologicalSpace _ u₂ :=
le_of_nhds_le_nhds <| to_nhds_mono h
theorem toTopologicalSpace_comap {f : α → β} {u : UniformSpace β} :
@UniformSpace.toTopologicalSpace _ (UniformSpace.comap f u) =
TopologicalSpace.induced f (@UniformSpace.toTopologicalSpace β u) :=
rfl
lemma uniformSpace_eq_bot {u : UniformSpace α} : u = ⊥ ↔ idRel ∈ 𝓤[u] :=
le_bot_iff.symm.trans le_principal_iff
protected lemma _root_.Filter.HasBasis.uniformSpace_eq_bot {ι p} {s : ι → Set (α × α)}
{u : UniformSpace α} (h : 𝓤[u].HasBasis p s) :
u = ⊥ ↔ ∃ i, p i ∧ Pairwise fun x y : α ↦ (x, y) ∉ s i := by
simp [uniformSpace_eq_bot, h.mem_iff, subset_def, Pairwise, not_imp_not]
theorem toTopologicalSpace_bot : @UniformSpace.toTopologicalSpace α ⊥ = ⊥ := rfl
theorem toTopologicalSpace_top : @UniformSpace.toTopologicalSpace α ⊤ = ⊤ := rfl
theorem toTopologicalSpace_iInf {ι : Sort*} {u : ι → UniformSpace α} :
(iInf u).toTopologicalSpace = ⨅ i, (u i).toTopologicalSpace :=
TopologicalSpace.ext_nhds fun a ↦ by simp only [@nhds_eq_comap_uniformity _ (iInf u), nhds_iInf,
iInf_uniformity, @nhds_eq_comap_uniformity _ (u _), Filter.comap_iInf]
theorem toTopologicalSpace_sInf {s : Set (UniformSpace α)} :
(sInf s).toTopologicalSpace = ⨅ i ∈ s, @UniformSpace.toTopologicalSpace α i := by
rw [sInf_eq_iInf]
simp only [← toTopologicalSpace_iInf]
theorem toTopologicalSpace_inf {u v : UniformSpace α} :
(u ⊓ v).toTopologicalSpace = u.toTopologicalSpace ⊓ v.toTopologicalSpace :=
rfl
end UniformSpace
theorem UniformContinuous.continuous [UniformSpace α] [UniformSpace β] {f : α → β}
(hf : UniformContinuous f) : Continuous f :=
continuous_iff_le_induced.mpr <| UniformSpace.toTopologicalSpace_mono <|
uniformContinuous_iff.1 hf
/-- Uniform space structure on `ULift α`. -/
instance ULift.uniformSpace [UniformSpace α] : UniformSpace (ULift α) :=
UniformSpace.comap ULift.down ‹_›
/-- Uniform space structure on `αᵒᵈ`. -/
instance OrderDual.instUniformSpace [UniformSpace α] : UniformSpace (αᵒᵈ) :=
‹UniformSpace α›
section UniformContinuousInfi
-- TODO: add an `iff` lemma?
theorem UniformContinuous.inf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ u₃ : UniformSpace β}
(h₁ : UniformContinuous[u₁, u₂] f) (h₂ : UniformContinuous[u₁, u₃] f) :
UniformContinuous[u₁, u₂ ⊓ u₃] f :=
tendsto_inf.mpr ⟨h₁, h₂⟩
theorem UniformContinuous.inf_dom_left {f : α → β} {u₁ u₂ : UniformSpace α} {u₃ : UniformSpace β}
(hf : UniformContinuous[u₁, u₃] f) : UniformContinuous[u₁ ⊓ u₂, u₃] f :=
tendsto_inf_left hf
theorem UniformContinuous.inf_dom_right {f : α → β} {u₁ u₂ : UniformSpace α} {u₃ : UniformSpace β}
(hf : UniformContinuous[u₂, u₃] f) : UniformContinuous[u₁ ⊓ u₂, u₃] f :=
tendsto_inf_right hf
theorem uniformContinuous_sInf_dom {f : α → β} {u₁ : Set (UniformSpace α)} {u₂ : UniformSpace β}
{u : UniformSpace α} (h₁ : u ∈ u₁) (hf : UniformContinuous[u, u₂] f) :
UniformContinuous[sInf u₁, u₂] f := by
delta UniformContinuous
rw [sInf_eq_iInf', iInf_uniformity]
exact tendsto_iInf' ⟨u, h₁⟩ hf
theorem uniformContinuous_sInf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ : Set (UniformSpace β)} :
UniformContinuous[u₁, sInf u₂] f ↔ ∀ u ∈ u₂, UniformContinuous[u₁, u] f := by
delta UniformContinuous
rw [sInf_eq_iInf', iInf_uniformity, tendsto_iInf, SetCoe.forall]
theorem uniformContinuous_iInf_dom {f : α → β} {u₁ : ι → UniformSpace α} {u₂ : UniformSpace β}
{i : ι} (hf : UniformContinuous[u₁ i, u₂] f) : UniformContinuous[iInf u₁, u₂] f := by
delta UniformContinuous
rw [iInf_uniformity]
exact tendsto_iInf' i hf
theorem uniformContinuous_iInf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ : ι → UniformSpace β} :
UniformContinuous[u₁, iInf u₂] f ↔ ∀ i, UniformContinuous[u₁, u₂ i] f := by
delta UniformContinuous
rw [iInf_uniformity, tendsto_iInf]
end UniformContinuousInfi
/-- A uniform space with the discrete uniformity has the discrete topology. -/
theorem discreteTopology_of_discrete_uniformity [hα : UniformSpace α] (h : uniformity α = 𝓟 idRel) :
DiscreteTopology α :=
⟨(UniformSpace.ext h.symm : ⊥ = hα) ▸ rfl⟩
instance : UniformSpace Empty := ⊥
instance : UniformSpace PUnit := ⊥
instance : UniformSpace Bool := ⊥
instance : UniformSpace ℕ := ⊥
instance : UniformSpace ℤ := ⊥
section
variable [UniformSpace α]
open Additive Multiplicative
instance : UniformSpace (Additive α) := ‹UniformSpace α›
instance : UniformSpace (Multiplicative α) := ‹UniformSpace α›
theorem uniformContinuous_ofMul : UniformContinuous (ofMul : α → Additive α) :=
uniformContinuous_id
theorem uniformContinuous_toMul : UniformContinuous (toMul : Additive α → α) :=
uniformContinuous_id
theorem uniformContinuous_ofAdd : UniformContinuous (ofAdd : α → Multiplicative α) :=
uniformContinuous_id
theorem uniformContinuous_toAdd : UniformContinuous (toAdd : Multiplicative α → α) :=
uniformContinuous_id
theorem uniformity_additive : 𝓤 (Additive α) = (𝓤 α).map (Prod.map ofMul ofMul) := rfl
theorem uniformity_multiplicative : 𝓤 (Multiplicative α) = (𝓤 α).map (Prod.map ofAdd ofAdd) := rfl
end
instance instUniformSpaceSubtype {p : α → Prop} [t : UniformSpace α] : UniformSpace (Subtype p) :=
UniformSpace.comap Subtype.val t
theorem uniformity_subtype {p : α → Prop} [UniformSpace α] :
𝓤 (Subtype p) = comap (fun q : Subtype p × Subtype p => (q.1.1, q.2.1)) (𝓤 α) :=
rfl
theorem uniformity_setCoe {s : Set α} [UniformSpace α] :
𝓤 s = comap (Prod.map ((↑) : s → α) ((↑) : s → α)) (𝓤 α) :=
rfl
theorem map_uniformity_set_coe {s : Set α} [UniformSpace α] :
map (Prod.map (↑) (↑)) (𝓤 s) = 𝓤 α ⊓ 𝓟 (s ×ˢ s) := by
rw [uniformity_setCoe, map_comap, range_prodMap, Subtype.range_val]
theorem uniformContinuous_subtype_val {p : α → Prop} [UniformSpace α] :
UniformContinuous (Subtype.val : { a : α // p a } → α) :=
uniformContinuous_comap
theorem UniformContinuous.subtype_mk {p : α → Prop} [UniformSpace α] [UniformSpace β] {f : β → α}
(hf : UniformContinuous f) (h : ∀ x, p (f x)) :
UniformContinuous (fun x => ⟨f x, h x⟩ : β → Subtype p) :=
uniformContinuous_comap' hf
theorem uniformContinuousOn_iff_restrict [UniformSpace α] [UniformSpace β] {f : α → β} {s : Set α} :
UniformContinuousOn f s ↔ UniformContinuous (s.restrict f) := by
delta UniformContinuousOn UniformContinuous
rw [← map_uniformity_set_coe, tendsto_map'_iff]; rfl
theorem tendsto_of_uniformContinuous_subtype [UniformSpace α] [UniformSpace β] {f : α → β}
{s : Set α} {a : α} (hf : UniformContinuous fun x : s => f x.val) (ha : s ∈ 𝓝 a) :
Tendsto f (𝓝 a) (𝓝 (f a)) := by
rw [(@map_nhds_subtype_coe_eq_nhds α _ s a (mem_of_mem_nhds ha) ha).symm]
exact tendsto_map' hf.continuous.continuousAt
theorem UniformContinuousOn.continuousOn [UniformSpace α] [UniformSpace β] {f : α → β} {s : Set α}
(h : UniformContinuousOn f s) : ContinuousOn f s := by
rw [uniformContinuousOn_iff_restrict] at h
rw [continuousOn_iff_continuous_restrict]
exact h.continuous
@[to_additive]
instance [UniformSpace α] : UniformSpace αᵐᵒᵖ :=
UniformSpace.comap MulOpposite.unop ‹_›
@[to_additive]
theorem uniformity_mulOpposite [UniformSpace α] :
𝓤 αᵐᵒᵖ = comap (fun q : αᵐᵒᵖ × αᵐᵒᵖ => (q.1.unop, q.2.unop)) (𝓤 α) :=
rfl
@[to_additive (attr := simp)]
theorem comap_uniformity_mulOpposite [UniformSpace α] :
comap (fun p : α × α => (MulOpposite.op p.1, MulOpposite.op p.2)) (𝓤 αᵐᵒᵖ) = 𝓤 α := by
simpa [uniformity_mulOpposite, comap_comap, (· ∘ ·)] using comap_id
namespace MulOpposite
@[to_additive]
theorem uniformContinuous_unop [UniformSpace α] : UniformContinuous (unop : αᵐᵒᵖ → α) :=
uniformContinuous_comap
@[to_additive]
theorem uniformContinuous_op [UniformSpace α] : UniformContinuous (op : α → αᵐᵒᵖ) :=
uniformContinuous_comap' uniformContinuous_id
end MulOpposite
section Prod
open UniformSpace
/- a similar product space is possible on the function space (uniformity of pointwise convergence),
but we want to have the uniformity of uniform convergence on function spaces -/
instance instUniformSpaceProd [u₁ : UniformSpace α] [u₂ : UniformSpace β] : UniformSpace (α × β) :=
u₁.comap Prod.fst ⊓ u₂.comap Prod.snd
-- check the above produces no diamond for `simp` and typeclass search
example [UniformSpace α] [UniformSpace β] :
(instTopologicalSpaceProd : TopologicalSpace (α × β)) = UniformSpace.toTopologicalSpace := by
with_reducible_and_instances rfl
theorem uniformity_prod [UniformSpace α] [UniformSpace β] :
𝓤 (α × β) =
((𝓤 α).comap fun p : (α × β) × α × β => (p.1.1, p.2.1)) ⊓
(𝓤 β).comap fun p : (α × β) × α × β => (p.1.2, p.2.2) :=
rfl
instance [UniformSpace α] [IsCountablyGenerated (𝓤 α)]
[UniformSpace β] [IsCountablyGenerated (𝓤 β)] : IsCountablyGenerated (𝓤 (α × β)) := by
rw [uniformity_prod]
infer_instance
theorem uniformity_prod_eq_comap_prod [UniformSpace α] [UniformSpace β] :
𝓤 (α × β) =
comap (fun p : (α × β) × α × β => ((p.1.1, p.2.1), (p.1.2, p.2.2))) (𝓤 α ×ˢ 𝓤 β) := by
simp_rw [uniformity_prod, prod_eq_inf, Filter.comap_inf, Filter.comap_comap, Function.comp_def]
theorem uniformity_prod_eq_prod [UniformSpace α] [UniformSpace β] :
𝓤 (α × β) = map (fun p : (α × α) × β × β => ((p.1.1, p.2.1), (p.1.2, p.2.2))) (𝓤 α ×ˢ 𝓤 β) := by
rw [map_swap4_eq_comap, uniformity_prod_eq_comap_prod]
theorem mem_uniformity_of_uniformContinuous_invariant [UniformSpace α] [UniformSpace β]
{s : Set (β × β)} {f : α → α → β} (hf : UniformContinuous fun p : α × α => f p.1 p.2)
(hs : s ∈ 𝓤 β) : ∃ u ∈ 𝓤 α, ∀ a b c, (a, b) ∈ u → (f a c, f b c) ∈ s := by
rw [UniformContinuous, uniformity_prod_eq_prod, tendsto_map'_iff] at hf
rcases mem_prod_iff.1 (mem_map.1 <| hf hs) with ⟨u, hu, v, hv, huvt⟩
exact ⟨u, hu, fun a b c hab => @huvt ((_, _), (_, _)) ⟨hab, refl_mem_uniformity hv⟩⟩
/-- An entourage of the diagonal in `α` and an entourage in `β` yield an entourage in `α × β`
once we permute coordinates. -/
def entourageProd (u : Set (α × α)) (v : Set (β × β)) : Set ((α × β) × α × β) :=
{((a₁, b₁),(a₂, b₂)) | (a₁, a₂) ∈ u ∧ (b₁, b₂) ∈ v}
theorem mem_entourageProd {u : Set (α × α)} {v : Set (β × β)} {p : (α × β) × α × β} :
p ∈ entourageProd u v ↔ (p.1.1, p.2.1) ∈ u ∧ (p.1.2, p.2.2) ∈ v := Iff.rfl
theorem entourageProd_mem_uniformity [t₁ : UniformSpace α] [t₂ : UniformSpace β] {u : Set (α × α)}
{v : Set (β × β)} (hu : u ∈ 𝓤 α) (hv : v ∈ 𝓤 β) :
entourageProd u v ∈ 𝓤 (α × β) := by
rw [uniformity_prod]; exact inter_mem_inf (preimage_mem_comap hu) (preimage_mem_comap hv)
theorem ball_entourageProd (u : Set (α × α)) (v : Set (β × β)) (x : α × β) :
ball x (entourageProd u v) = ball x.1 u ×ˢ ball x.2 v := by
ext p; simp only [ball, entourageProd, Set.mem_setOf_eq, Set.mem_prod, Set.mem_preimage]
lemma IsSymmetricRel.entourageProd {u : Set (α × α)} {v : Set (β × β)}
(hu : IsSymmetricRel u) (hv : IsSymmetricRel v) :
IsSymmetricRel (entourageProd u v) :=
Set.ext fun _ ↦ and_congr hu.mk_mem_comm hv.mk_mem_comm
theorem Filter.HasBasis.uniformity_prod {ιa ιb : Type*} [UniformSpace α] [UniformSpace β]
{pa : ιa → Prop} {pb : ιb → Prop} {sa : ιa → Set (α × α)} {sb : ιb → Set (β × β)}
(ha : (𝓤 α).HasBasis pa sa) (hb : (𝓤 β).HasBasis pb sb) :
(𝓤 (α × β)).HasBasis (fun i : ιa × ιb ↦ pa i.1 ∧ pb i.2)
(fun i ↦ entourageProd (sa i.1) (sb i.2)) :=
(ha.comap _).inf (hb.comap _)
theorem entourageProd_subset [UniformSpace α] [UniformSpace β]
{s : Set ((α × β) × α × β)} (h : s ∈ 𝓤 (α × β)) :
∃ u ∈ 𝓤 α, ∃ v ∈ 𝓤 β, entourageProd u v ⊆ s := by
rcases (((𝓤 α).basis_sets.uniformity_prod (𝓤 β).basis_sets).mem_iff' s).1 h with ⟨w, hw⟩
use w.1, hw.1.1, w.2, hw.1.2, hw.2
theorem tendsto_prod_uniformity_fst [UniformSpace α] [UniformSpace β] :
Tendsto (fun p : (α × β) × α × β => (p.1.1, p.2.1)) (𝓤 (α × β)) (𝓤 α) :=
le_trans (map_mono inf_le_left) map_comap_le
theorem tendsto_prod_uniformity_snd [UniformSpace α] [UniformSpace β] :
Tendsto (fun p : (α × β) × α × β => (p.1.2, p.2.2)) (𝓤 (α × β)) (𝓤 β) :=
le_trans (map_mono inf_le_right) map_comap_le
theorem uniformContinuous_fst [UniformSpace α] [UniformSpace β] :
UniformContinuous fun p : α × β => p.1 :=
tendsto_prod_uniformity_fst
theorem uniformContinuous_snd [UniformSpace α] [UniformSpace β] :
UniformContinuous fun p : α × β => p.2 :=
tendsto_prod_uniformity_snd
variable [UniformSpace α] [UniformSpace β] [UniformSpace γ]
theorem UniformContinuous.prodMk {f₁ : α → β} {f₂ : α → γ} (h₁ : UniformContinuous f₁)
(h₂ : UniformContinuous f₂) : UniformContinuous fun a => (f₁ a, f₂ a) := by
rw [UniformContinuous, uniformity_prod]
exact tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩
@[deprecated (since := "2025-03-10")]
alias UniformContinuous.prod_mk := UniformContinuous.prodMk
theorem UniformContinuous.prodMk_left {f : α × β → γ} (h : UniformContinuous f) (b) :
UniformContinuous fun a => f (a, b) :=
h.comp (uniformContinuous_id.prodMk uniformContinuous_const)
@[deprecated (since := "2025-03-10")]
alias UniformContinuous.prod_mk_left := UniformContinuous.prodMk_left
theorem UniformContinuous.prodMk_right {f : α × β → γ} (h : UniformContinuous f) (a) :
UniformContinuous fun b => f (a, b) :=
h.comp (uniformContinuous_const.prodMk uniformContinuous_id)
@[deprecated (since := "2025-03-10")]
alias UniformContinuous.prod_mk_right := UniformContinuous.prodMk_right
theorem UniformContinuous.prodMap [UniformSpace δ] {f : α → γ} {g : β → δ}
(hf : UniformContinuous f) (hg : UniformContinuous g) : UniformContinuous (Prod.map f g) :=
(hf.comp uniformContinuous_fst).prodMk (hg.comp uniformContinuous_snd)
theorem toTopologicalSpace_prod {α} {β} [u : UniformSpace α] [v : UniformSpace β] :
@UniformSpace.toTopologicalSpace (α × β) instUniformSpaceProd =
@instTopologicalSpaceProd α β u.toTopologicalSpace v.toTopologicalSpace :=
rfl
/-- A version of `UniformContinuous.inf_dom_left` for binary functions -/
theorem uniformContinuous_inf_dom_left₂ {α β γ} {f : α → β → γ} {ua1 ua2 : UniformSpace α}
{ub1 ub2 : UniformSpace β} {uc1 : UniformSpace γ}
(h : by haveI := ua1; haveI := ub1; exact UniformContinuous fun p : α × β => f p.1 p.2) : by
haveI := ua1 ⊓ ua2; haveI := ub1 ⊓ ub2
exact UniformContinuous fun p : α × β => f p.1 p.2 := by
-- proof essentially copied from `continuous_inf_dom_left₂`
have ha := @UniformContinuous.inf_dom_left _ _ id ua1 ua2 ua1 (@uniformContinuous_id _ (id _))
have hb := @UniformContinuous.inf_dom_left _ _ id ub1 ub2 ub1 (@uniformContinuous_id _ (id _))
have h_unif_cont_id :=
@UniformContinuous.prodMap _ _ _ _ (ua1 ⊓ ua2) (ub1 ⊓ ub2) ua1 ub1 _ _ ha hb
exact @UniformContinuous.comp _ _ _ (id _) (id _) _ _ _ h h_unif_cont_id
/-- A version of `UniformContinuous.inf_dom_right` for binary functions -/
theorem uniformContinuous_inf_dom_right₂ {α β γ} {f : α → β → γ} {ua1 ua2 : UniformSpace α}
{ub1 ub2 : UniformSpace β} {uc1 : UniformSpace γ}
(h : by haveI := ua2; haveI := ub2; exact UniformContinuous fun p : α × β => f p.1 p.2) : by
haveI := ua1 ⊓ ua2; haveI := ub1 ⊓ ub2
exact UniformContinuous fun p : α × β => f p.1 p.2 := by
-- proof essentially copied from `continuous_inf_dom_right₂`
have ha := @UniformContinuous.inf_dom_right _ _ id ua1 ua2 ua2 (@uniformContinuous_id _ (id _))
have hb := @UniformContinuous.inf_dom_right _ _ id ub1 ub2 ub2 (@uniformContinuous_id _ (id _))
have h_unif_cont_id :=
@UniformContinuous.prodMap _ _ _ _ (ua1 ⊓ ua2) (ub1 ⊓ ub2) ua2 ub2 _ _ ha hb
exact @UniformContinuous.comp _ _ _ (id _) (id _) _ _ _ h h_unif_cont_id
/-- A version of `uniformContinuous_sInf_dom` for binary functions -/
theorem uniformContinuous_sInf_dom₂ {α β γ} {f : α → β → γ} {uas : Set (UniformSpace α)}
{ubs : Set (UniformSpace β)} {ua : UniformSpace α} {ub : UniformSpace β} {uc : UniformSpace γ}
(ha : ua ∈ uas) (hb : ub ∈ ubs) (hf : UniformContinuous fun p : α × β => f p.1 p.2) : by
haveI := sInf uas; haveI := sInf ubs
exact @UniformContinuous _ _ _ uc fun p : α × β => f p.1 p.2 := by
-- proof essentially copied from `continuous_sInf_dom`
let _ : UniformSpace (α × β) := instUniformSpaceProd
have ha := uniformContinuous_sInf_dom ha uniformContinuous_id
have hb := uniformContinuous_sInf_dom hb uniformContinuous_id
have h_unif_cont_id := @UniformContinuous.prodMap _ _ _ _ (sInf uas) (sInf ubs) ua ub _ _ ha hb
exact @UniformContinuous.comp _ _ _ (id _) (id _) _ _ _ hf h_unif_cont_id
end Prod
section
open UniformSpace Function
variable {δ' : Type*} [UniformSpace α] [UniformSpace β] [UniformSpace γ] [UniformSpace δ]
[UniformSpace δ']
local notation f " ∘₂ " g => Function.bicompr f g
/-- Uniform continuity for functions of two variables. -/
def UniformContinuous₂ (f : α → β → γ) :=
UniformContinuous (uncurry f)
theorem uniformContinuous₂_def (f : α → β → γ) :
UniformContinuous₂ f ↔ UniformContinuous (uncurry f) :=
Iff.rfl
theorem UniformContinuous₂.uniformContinuous {f : α → β → γ} (h : UniformContinuous₂ f) :
UniformContinuous (uncurry f) :=
h
theorem uniformContinuous₂_curry (f : α × β → γ) :
UniformContinuous₂ (Function.curry f) ↔ UniformContinuous f := by
rw [UniformContinuous₂, uncurry_curry]
theorem UniformContinuous₂.comp {f : α → β → γ} {g : γ → δ} (hg : UniformContinuous g)
(hf : UniformContinuous₂ f) : UniformContinuous₂ (g ∘₂ f) :=
hg.comp hf
theorem UniformContinuous₂.bicompl {f : α → β → γ} {ga : δ → α} {gb : δ' → β}
(hf : UniformContinuous₂ f) (hga : UniformContinuous ga) (hgb : UniformContinuous gb) :
UniformContinuous₂ (bicompl f ga gb) :=
hf.uniformContinuous.comp (hga.prodMap hgb)
end
theorem toTopologicalSpace_subtype [u : UniformSpace α] {p : α → Prop} :
@UniformSpace.toTopologicalSpace (Subtype p) instUniformSpaceSubtype =
@instTopologicalSpaceSubtype α p u.toTopologicalSpace :=
rfl
section Sum
variable [UniformSpace α] [UniformSpace β]
open Sum
-- Obsolete auxiliary definitions and lemmas
/-- Uniformity on a disjoint union. Entourages of the diagonal in the union are obtained
by taking independently an entourage of the diagonal in the first part, and an entourage of
the diagonal in the second part. -/
instance Sum.instUniformSpace : UniformSpace (α ⊕ β) where
uniformity := map (fun p : α × α => (inl p.1, inl p.2)) (𝓤 α) ⊔
map (fun p : β × β => (inr p.1, inr p.2)) (𝓤 β)
symm := fun _ hs ↦ ⟨symm_le_uniformity hs.1, symm_le_uniformity hs.2⟩
comp := fun s hs ↦ by
rcases comp_mem_uniformity_sets hs.1 with ⟨tα, htα, Htα⟩
rcases comp_mem_uniformity_sets hs.2 with ⟨tβ, htβ, Htβ⟩
filter_upwards [mem_lift' (union_mem_sup (image_mem_map htα) (image_mem_map htβ))]
rintro ⟨_, _⟩ ⟨z, ⟨⟨a, b⟩, hab, ⟨⟩⟩ | ⟨⟨a, b⟩, hab, ⟨⟩⟩, ⟨⟨_, c⟩, hbc, ⟨⟩⟩ | ⟨⟨_, c⟩, hbc, ⟨⟩⟩⟩
exacts [@Htα (_, _) ⟨b, hab, hbc⟩, @Htβ (_, _) ⟨b, hab, hbc⟩]
nhds_eq_comap_uniformity x := by
ext
cases x <;> simp [mem_comap', -mem_comap, nhds_inl, nhds_inr, nhds_eq_comap_uniformity,
Prod.ext_iff]
|
/-- The union of an entourage of the diagonal in each set of a disjoint union is again an entourage
of the diagonal. -/
theorem union_mem_uniformity_sum {a : Set (α × α)} (ha : a ∈ 𝓤 α) {b : Set (β × β)} (hb : b ∈ 𝓤 β) :
Prod.map inl inl '' a ∪ Prod.map inr inr '' b ∈ 𝓤 (α ⊕ β) :=
union_mem_sup (image_mem_map ha) (image_mem_map hb)
theorem Sum.uniformity : 𝓤 (α ⊕ β) = map (Prod.map inl inl) (𝓤 α) ⊔ map (Prod.map inr inr) (𝓤 β) :=
rfl
lemma uniformContinuous_inl : UniformContinuous (Sum.inl : α → α ⊕ β) := le_sup_left
lemma uniformContinuous_inr : UniformContinuous (Sum.inr : β → α ⊕ β) := le_sup_right
instance [IsCountablyGenerated (𝓤 α)] [IsCountablyGenerated (𝓤 β)] :
IsCountablyGenerated (𝓤 (α ⊕ β)) := by
rw [Sum.uniformity]
| Mathlib/Topology/UniformSpace/Basic.lean | 873 | 888 |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Limits.Shapes.IsTerminal
import Mathlib.CategoryTheory.Limits.HasLimits
/-!
# Initial and terminal objects in a category.
## References
* [Stacks: Initial and final objects](https://stacks.math.columbia.edu/tag/002B)
-/
noncomputable section
universe w w' v v₁ v₂ u u₁ u₂
open CategoryTheory
namespace CategoryTheory.Limits
variable {C : Type u₁} [Category.{v₁} C]
variable (C)
/-- A category has a terminal object if it has a limit over the empty diagram.
Use `hasTerminal_of_unique` to construct instances.
-/
abbrev HasTerminal :=
HasLimitsOfShape (Discrete.{0} PEmpty) C
/-- A category has an initial object if it has a colimit over the empty diagram.
Use `hasInitial_of_unique` to construct instances.
-/
abbrev HasInitial :=
HasColimitsOfShape (Discrete.{0} PEmpty) C
section Univ
variable (X : C) {F₁ : Discrete.{w} PEmpty ⥤ C} {F₂ : Discrete.{w'} PEmpty ⥤ C}
theorem hasTerminalChangeDiagram (h : HasLimit F₁) : HasLimit F₂ :=
⟨⟨⟨⟨limit F₁, by aesop_cat, by simp⟩,
isLimitChangeEmptyCone C (limit.isLimit F₁) _ (eqToIso rfl)⟩⟩⟩
theorem hasTerminalChangeUniverse [h : HasLimitsOfShape (Discrete.{w} PEmpty) C] :
HasLimitsOfShape (Discrete.{w'} PEmpty) C where
has_limit _ := hasTerminalChangeDiagram C (h.1 (Functor.empty C))
theorem hasInitialChangeDiagram (h : HasColimit F₁) : HasColimit F₂ :=
⟨⟨⟨⟨colimit F₁, by aesop_cat, by simp⟩,
isColimitChangeEmptyCocone C (colimit.isColimit F₁) _ (eqToIso rfl)⟩⟩⟩
theorem hasInitialChangeUniverse [h : HasColimitsOfShape (Discrete.{w} PEmpty) C] :
HasColimitsOfShape (Discrete.{w'} PEmpty) C where
has_colimit _ := hasInitialChangeDiagram C (h.1 (Functor.empty C))
end Univ
/-- An arbitrary choice of terminal object, if one exists.
You can use the notation `⊤_ C`.
This object is characterized by having a unique morphism from any object.
-/
abbrev terminal [HasTerminal C] : C :=
limit (Functor.empty.{0} C)
/-- An arbitrary choice of initial object, if one exists.
You can use the notation `⊥_ C`.
This object is characterized by having a unique morphism to any object.
-/
abbrev initial [HasInitial C] : C :=
colimit (Functor.empty.{0} C)
/-- Notation for the terminal object in `C` -/
notation "⊤_ " C:20 => terminal C
/-- Notation for the initial object in `C` -/
notation "⊥_ " C:20 => initial C
section
variable {C}
/-- We can more explicitly show that a category has a terminal object by specifying the object,
and showing there is a unique morphism to it from any other object. -/
theorem hasTerminal_of_unique (X : C) [∀ Y, Nonempty (Y ⟶ X)] [∀ Y, Subsingleton (Y ⟶ X)] :
HasTerminal C where
has_limit F := .mk ⟨_, (isTerminalEquivUnique F X).invFun fun _ ↦
⟨Classical.inhabited_of_nonempty', (Subsingleton.elim · _)⟩⟩
theorem IsTerminal.hasTerminal {X : C} (h : IsTerminal X) : HasTerminal C :=
{ has_limit := fun F => HasLimit.mk ⟨⟨X, by aesop_cat, by simp⟩,
isLimitChangeEmptyCone _ h _ (Iso.refl _)⟩ }
/-- We can more explicitly show that a category has an initial object by specifying the object,
and showing there is a unique morphism from it to any other object. -/
theorem hasInitial_of_unique (X : C) [∀ Y, Nonempty (X ⟶ Y)] [∀ Y, Subsingleton (X ⟶ Y)] :
HasInitial C where
has_colimit F := .mk ⟨_, (isInitialEquivUnique F X).invFun fun _ ↦
⟨Classical.inhabited_of_nonempty', (Subsingleton.elim · _)⟩⟩
theorem IsInitial.hasInitial {X : C} (h : IsInitial X) : HasInitial C where
has_colimit F :=
HasColimit.mk ⟨⟨X, by aesop_cat, by simp⟩, isColimitChangeEmptyCocone _ h _ (Iso.refl _)⟩
/-- The map from an object to the terminal object. -/
abbrev terminal.from [HasTerminal C] (P : C) : P ⟶ ⊤_ C :=
limit.lift (Functor.empty C) (asEmptyCone P)
/-- The map to an object from the initial object. -/
abbrev initial.to [HasInitial C] (P : C) : ⊥_ C ⟶ P :=
colimit.desc (Functor.empty C) (asEmptyCocone P)
/-- A terminal object is terminal. -/
def terminalIsTerminal [HasTerminal C] : IsTerminal (⊤_ C) where
lift _ := terminal.from _
/-- An initial object is initial. -/
def initialIsInitial [HasInitial C] : IsInitial (⊥_ C) where
desc _ := initial.to _
instance uniqueToTerminal [HasTerminal C] (P : C) : Unique (P ⟶ ⊤_ C) :=
isTerminalEquivUnique _ (⊤_ C) terminalIsTerminal P
instance uniqueFromInitial [HasInitial C] (P : C) : Unique (⊥_ C ⟶ P) :=
isInitialEquivUnique _ (⊥_ C) initialIsInitial P
@[ext] theorem terminal.hom_ext [HasTerminal C] {P : C} (f g : P ⟶ ⊤_ C) : f = g := by ext ⟨⟨⟩⟩
@[ext] theorem initial.hom_ext [HasInitial C] {P : C} (f g : ⊥_ C ⟶ P) : f = g := by ext ⟨⟨⟩⟩
@[reassoc (attr := simp)]
theorem terminal.comp_from [HasTerminal C] {P Q : C} (f : P ⟶ Q) :
f ≫ terminal.from Q = terminal.from P := by
simp [eq_iff_true_of_subsingleton]
-- `initial.to_comp_assoc` does not need the `simp` attribute.
@[simp, reassoc]
theorem initial.to_comp [HasInitial C] {P Q : C} (f : P ⟶ Q) : initial.to P ≫ f = initial.to Q := by
simp [eq_iff_true_of_subsingleton]
/-- The (unique) isomorphism between the chosen initial object and any other initial object. -/
@[simps!]
def initialIsoIsInitial [HasInitial C] {P : C} (t : IsInitial P) : ⊥_ C ≅ P :=
initialIsInitial.uniqueUpToIso t
/-- The (unique) isomorphism between the chosen terminal object and any other terminal object. -/
@[simps!]
def terminalIsoIsTerminal [HasTerminal C] {P : C} (t : IsTerminal P) : ⊤_ C ≅ P :=
terminalIsTerminal.uniqueUpToIso t
/-- Any morphism from a terminal object is split mono. -/
instance terminal.isSplitMono_from {Y : C} [HasTerminal C] (f : ⊤_ C ⟶ Y) : IsSplitMono f :=
IsTerminal.isSplitMono_from terminalIsTerminal _
/-- Any morphism to an initial object is split epi. -/
instance initial.isSplitEpi_to {Y : C} [HasInitial C] (f : Y ⟶ ⊥_ C) : IsSplitEpi f :=
IsInitial.isSplitEpi_to initialIsInitial _
instance hasInitial_op_of_hasTerminal [HasTerminal C] : HasInitial Cᵒᵖ :=
(initialOpOfTerminal terminalIsTerminal).hasInitial
instance hasTerminal_op_of_hasInitial [HasInitial C] : HasTerminal Cᵒᵖ :=
(terminalOpOfInitial initialIsInitial).hasTerminal
theorem hasTerminal_of_hasInitial_op [HasInitial Cᵒᵖ] : HasTerminal C :=
(terminalUnopOfInitial initialIsInitial).hasTerminal
theorem hasInitial_of_hasTerminal_op [HasTerminal Cᵒᵖ] : HasInitial C :=
(initialUnopOfTerminal terminalIsTerminal).hasInitial
instance {J : Type*} [Category J] {C : Type*} [Category C] [HasTerminal C] :
HasLimit ((CategoryTheory.Functor.const J).obj (⊤_ C)) :=
HasLimit.mk
{ cone :=
{ pt := ⊤_ C
π := { app := fun _ => terminal.from _ } }
isLimit := { lift := fun _ => terminal.from _ } }
/-- The limit of the constant `⊤_ C` functor is `⊤_ C`. -/
@[simps hom]
def limitConstTerminal {J : Type*} [Category J] {C : Type*} [Category C] [HasTerminal C] :
limit ((CategoryTheory.Functor.const J).obj (⊤_ C)) ≅ ⊤_ C where
hom := terminal.from _
inv :=
limit.lift ((CategoryTheory.Functor.const J).obj (⊤_ C))
{ pt := ⊤_ C
π := { app := fun _ => terminal.from _ } }
@[reassoc (attr := simp)]
theorem limitConstTerminal_inv_π {J : Type*} [Category J] {C : Type*} [Category C] [HasTerminal C]
{j : J} :
limitConstTerminal.inv ≫ limit.π ((CategoryTheory.Functor.const J).obj (⊤_ C)) j =
terminal.from _ := by aesop_cat
instance {J : Type*} [Category J] {C : Type*} [Category C] [HasInitial C] :
HasColimit ((CategoryTheory.Functor.const J).obj (⊥_ C)) :=
HasColimit.mk
{ cocone :=
{ pt := ⊥_ C
ι := { app := fun _ => initial.to _ } }
isColimit := { desc := fun _ => initial.to _ } }
/-- The colimit of the constant `⊥_ C` functor is `⊥_ C`. -/
@[simps inv]
def colimitConstInitial {J : Type*} [Category J] {C : Type*} [Category C] [HasInitial C] :
colimit ((CategoryTheory.Functor.const J).obj (⊥_ C)) ≅ ⊥_ C where
hom :=
colimit.desc ((CategoryTheory.Functor.const J).obj (⊥_ C))
{ pt := ⊥_ C
ι := { app := fun _ => initial.to _ } }
inv := initial.to _
@[reassoc (attr := simp)]
theorem ι_colimitConstInitial_hom {J : Type*} [Category J] {C : Type*} [Category C] [HasInitial C]
{j : J} :
colimit.ι ((CategoryTheory.Functor.const J).obj (⊥_ C)) j ≫ colimitConstInitial.hom =
initial.to _ := by aesop_cat
instance (priority := 100) initial.mono_from [HasInitial C] [InitialMonoClass C] (X : C)
(f : ⊥_ C ⟶ X) : Mono f :=
initialIsInitial.mono_from f
/-- To show a category is an `InitialMonoClass` it suffices to show every morphism out of the
initial object is a monomorphism. -/
theorem InitialMonoClass.of_initial [HasInitial C] (h : ∀ X : C, Mono (initial.to X)) :
InitialMonoClass C :=
InitialMonoClass.of_isInitial initialIsInitial h
/-- To show a category is an `InitialMonoClass` it suffices to show the unique morphism from the
initial object to a terminal object is a monomorphism. -/
theorem InitialMonoClass.of_terminal [HasInitial C] [HasTerminal C] (h : Mono (initial.to (⊤_ C))) :
InitialMonoClass C :=
InitialMonoClass.of_isTerminal initialIsInitial terminalIsTerminal h
section Comparison
variable {D : Type u₂} [Category.{v₂} D] (G : C ⥤ D)
/-- The comparison morphism from the image of a terminal object to the terminal object in the target
category.
This is an isomorphism iff `G` preserves terminal objects, see
`CategoryTheory.Limits.PreservesTerminal.ofIsoComparison`.
-/
def terminalComparison [HasTerminal C] [HasTerminal D] : G.obj (⊤_ C) ⟶ ⊤_ D :=
terminal.from _
-- TODO: Show this is an isomorphism if and only if `G` preserves initial objects.
/--
The comparison morphism from the initial object in the target category to the image of the initial
object.
-/
def initialComparison [HasInitial C] [HasInitial D] : ⊥_ D ⟶ G.obj (⊥_ C) :=
initial.to _
end Comparison
variable {J : Type u} [Category.{v} J]
instance hasLimit_of_domain_hasInitial [HasInitial J] {F : J ⥤ C} : HasLimit F :=
HasLimit.mk { cone := _, isLimit := limitOfDiagramInitial (initialIsInitial) F }
-- See note [dsimp, simp]
-- This is reducible to allow usage of lemmas about `cone_point_unique_up_to_iso`.
/-- For a functor `F : J ⥤ C`, if `J` has an initial object then the image of it is isomorphic
to the limit of `F`. -/
abbrev limitOfInitial (F : J ⥤ C) [HasInitial J] : limit F ≅ F.obj (⊥_ J) :=
IsLimit.conePointUniqueUpToIso (limit.isLimit _) (limitOfDiagramInitial initialIsInitial F)
instance hasLimit_of_domain_hasTerminal [HasTerminal J] {F : J ⥤ C}
[∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] : HasLimit F :=
HasLimit.mk { cone := _, isLimit := limitOfDiagramTerminal (terminalIsTerminal) F }
-- This is reducible to allow usage of lemmas about `cone_point_unique_up_to_iso`.
/-- For a functor `F : J ⥤ C`, if `J` has a terminal object and all the morphisms in the diagram
are isomorphisms, then the image of the terminal object is isomorphic to the limit of `F`. -/
abbrev limitOfTerminal (F : J ⥤ C) [HasTerminal J] [∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] :
limit F ≅ F.obj (⊤_ J) :=
IsLimit.conePointUniqueUpToIso (limit.isLimit _) (limitOfDiagramTerminal terminalIsTerminal F)
instance hasColimit_of_domain_hasTerminal [HasTerminal J] {F : J ⥤ C} : HasColimit F :=
HasColimit.mk { cocone := _, isColimit := colimitOfDiagramTerminal (terminalIsTerminal) F }
-- This is reducible to allow usage of lemmas about `cocone_point_unique_up_to_iso`.
/-- For a functor `F : J ⥤ C`, if `J` has a terminal object then the image of it is isomorphic
to the colimit of `F`. -/
abbrev colimitOfTerminal (F : J ⥤ C) [HasTerminal J] : colimit F ≅ F.obj (⊤_ J) :=
IsColimit.coconePointUniqueUpToIso (colimit.isColimit _)
(colimitOfDiagramTerminal terminalIsTerminal F)
instance hasColimit_of_domain_hasInitial [HasInitial J] {F : J ⥤ C}
[∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] : HasColimit F :=
HasColimit.mk { cocone := _, isColimit := colimitOfDiagramInitial (initialIsInitial) F }
-- This is reducible to allow usage of lemmas about `cocone_point_unique_up_to_iso`.
/-- For a functor `F : J ⥤ C`, if `J` has an initial object and all the morphisms in the diagram
are isomorphisms, then the image of the initial object is isomorphic to the colimit of `F`. -/
abbrev colimitOfInitial (F : J ⥤ C) [HasInitial J] [∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] :
colimit F ≅ F.obj (⊥_ J) :=
IsColimit.coconePointUniqueUpToIso (colimit.isColimit _)
(colimitOfDiagramInitial initialIsInitial _)
/-- If `j` is initial in the index category, then the map `limit.π F j` is an isomorphism.
-/
theorem isIso_π_of_isInitial {j : J} (I : IsInitial j) (F : J ⥤ C) [HasLimit F] :
IsIso (limit.π F j) :=
⟨⟨limit.lift _ (coneOfDiagramInitial I F), ⟨by ext; simp, by simp⟩⟩⟩
instance isIso_π_initial [HasInitial J] (F : J ⥤ C) : IsIso (limit.π F (⊥_ J)) :=
isIso_π_of_isInitial initialIsInitial F
theorem isIso_π_of_isTerminal {j : J} (I : IsTerminal j) (F : J ⥤ C) [HasLimit F]
[∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] : IsIso (limit.π F j) :=
⟨⟨limit.lift _ (coneOfDiagramTerminal I F), by ext; simp, by simp⟩⟩
instance isIso_π_terminal [HasTerminal J] (F : J ⥤ C) [∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] :
IsIso (limit.π F (⊤_ J)) :=
isIso_π_of_isTerminal terminalIsTerminal F
/-- If `j` is terminal in the index category, then the map `colimit.ι F j` is an isomorphism.
-/
theorem isIso_ι_of_isTerminal {j : J} (I : IsTerminal j) (F : J ⥤ C) [HasColimit F] :
IsIso (colimit.ι F j) :=
⟨⟨colimit.desc _ (coconeOfDiagramTerminal I F), ⟨by simp, by ext; simp⟩⟩⟩
instance isIso_ι_terminal [HasTerminal J] (F : J ⥤ C) : IsIso (colimit.ι F (⊤_ J)) :=
isIso_ι_of_isTerminal terminalIsTerminal F
theorem isIso_ι_of_isInitial {j : J} (I : IsInitial j) (F : J ⥤ C) [HasColimit F]
[∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] : IsIso (colimit.ι F j) :=
⟨⟨colimit.desc _ (coconeOfDiagramInitial I F), by
refine ⟨?_, by ext; simp⟩
dsimp; simp only [colimit.ι_desc, coconeOfDiagramInitial_pt, coconeOfDiagramInitial_ι_app,
Functor.const_obj_obj, IsInitial.to_self, Functor.map_id]
dsimp [inv]; simp only [Category.id_comp, Category.comp_id, and_self]
apply @Classical.choose_spec _ (fun x => x = 𝟙 F.obj j) _
⟩⟩
instance isIso_ι_initial [HasInitial J] (F : J ⥤ C) [∀ (i j : J) (f : i ⟶ j), IsIso (F.map f)] :
IsIso (colimit.ι F (⊥_ J)) :=
isIso_ι_of_isInitial initialIsInitial F
end
end CategoryTheory.Limits
| Mathlib/CategoryTheory/Limits/Shapes/Terminal.lean | 397 | 397 | |
/-
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.MeasurableSpace.MeasurablyGenerated
import Mathlib.MeasureTheory.Measure.NullMeasurable
import Mathlib.Order.Interval.Set.Monotone
/-!
# Measure spaces
The definition of a measure and a measure space are in `MeasureTheory.MeasureSpaceDef`, with
only a few basic properties. This file provides many more properties of these objects.
This separation allows the measurability tactic to import only the file `MeasureSpaceDef`, and to
be available in `MeasureSpace` (through `MeasurableSpace`).
Given a measurable space `α`, a measure on `α` is a function that sends measurable sets to the
extended nonnegative reals that satisfies the following conditions:
1. `μ ∅ = 0`;
2. `μ` is countably additive. This means that the measure of a countable union of pairwise disjoint
sets is equal to the measure of the individual sets.
Every measure can be canonically extended to an outer measure, so that it assigns values to
all subsets, not just the measurable subsets. On the other hand, a measure that is countably
additive on measurable sets can be restricted to measurable sets to obtain a measure.
In this file a measure is defined to be an outer measure that is countably additive on
measurable sets, with the additional assumption that the outer measure is the canonical
extension of the restricted measure.
Measures on `α` form a complete lattice, and are closed under scalar multiplication with `ℝ≥0∞`.
Given a measure, the null sets are the sets where `μ s = 0`, where `μ` denotes the corresponding
outer measure (so `s` might not be measurable). We can then define the completion of `μ` as the
measure on the least `σ`-algebra that also contains all null sets, by defining the measure to be `0`
on the null sets.
## Main statements
* `completion` is the completion of a measure to all null measurable sets.
* `Measure.ofMeasurable` and `OuterMeasure.toMeasure` are two important ways to define a measure.
## Implementation notes
Given `μ : Measure α`, `μ s` is the value of the *outer measure* applied to `s`.
This conveniently allows us to apply the measure to sets without proving that they are measurable.
We get countable subadditivity for all sets, but only countable additivity for measurable sets.
You often don't want to define a measure via its constructor.
Two ways that are sometimes more convenient:
* `Measure.ofMeasurable` is a way to define a measure by only giving its value on measurable sets
and proving the properties (1) and (2) mentioned above.
* `OuterMeasure.toMeasure` is a way of obtaining a measure from an outer measure by showing that
all measurable sets in the measurable space are Carathéodory measurable.
To prove that two measures are equal, there are multiple options:
* `ext`: two measures are equal if they are equal on all measurable sets.
* `ext_of_generateFrom_of_iUnion`: two measures are equal if they are equal on a π-system generating
the measurable sets, if the π-system contains a spanning increasing sequence of sets where the
measures take finite value (in particular the measures are σ-finite). This is a special case of
the more general `ext_of_generateFrom_of_cover`
* `ext_of_generate_finite`: two finite measures are equal if they are equal on a π-system
generating the measurable sets. This is a special case of `ext_of_generateFrom_of_iUnion` using
`C ∪ {univ}`, but is easier to work with.
A `MeasureSpace` is a class that is a measurable space with a canonical measure.
The measure is denoted `volume`.
## References
* <https://en.wikipedia.org/wiki/Measure_(mathematics)>
* <https://en.wikipedia.org/wiki/Complete_measure>
* <https://en.wikipedia.org/wiki/Almost_everywhere>
## Tags
measure, almost everywhere, measure space, completion, null set, null measurable set
-/
noncomputable section
open Set
open Filter hiding map
open Function MeasurableSpace Topology Filter ENNReal NNReal Interval MeasureTheory
open scoped symmDiff
variable {α β γ δ ι R R' : Type*}
namespace MeasureTheory
section
variable {m : MeasurableSpace α} {μ μ₁ μ₂ : Measure α} {s s₁ s₂ t : Set α}
instance ae_isMeasurablyGenerated : IsMeasurablyGenerated (ae μ) :=
⟨fun _s hs =>
let ⟨t, hst, htm, htμ⟩ := exists_measurable_superset_of_null hs
⟨tᶜ, compl_mem_ae_iff.2 htμ, htm.compl, compl_subset_comm.1 hst⟩⟩
/-- See also `MeasureTheory.ae_restrict_uIoc_iff`. -/
theorem ae_uIoc_iff [LinearOrder α] {a b : α} {P : α → Prop} :
(∀ᵐ x ∂μ, x ∈ Ι a b → P x) ↔ (∀ᵐ x ∂μ, x ∈ Ioc a b → P x) ∧ ∀ᵐ x ∂μ, x ∈ Ioc b a → P x := by
simp only [uIoc_eq_union, mem_union, or_imp, eventually_and]
theorem measure_union (hd : Disjoint s₁ s₂) (h : MeasurableSet s₂) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀ h.nullMeasurableSet hd.aedisjoint
theorem measure_union' (hd : Disjoint s₁ s₂) (h : MeasurableSet s₁) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀' h.nullMeasurableSet hd.aedisjoint
theorem measure_inter_add_diff (s : Set α) (ht : MeasurableSet t) : μ (s ∩ t) + μ (s \ t) = μ s :=
measure_inter_add_diff₀ _ ht.nullMeasurableSet
theorem measure_diff_add_inter (s : Set α) (ht : MeasurableSet t) : μ (s \ t) + μ (s ∩ t) = μ s :=
(add_comm _ _).trans (measure_inter_add_diff s ht)
theorem measure_diff_eq_top (hs : μ s = ∞) (ht : μ t ≠ ∞) : μ (s \ t) = ∞ := by
contrapose! hs
exact ((measure_mono (subset_diff_union s t)).trans_lt
((measure_union_le _ _).trans_lt (ENNReal.add_lt_top.2 ⟨hs.lt_top, ht.lt_top⟩))).ne
theorem measure_union_add_inter (s : Set α) (ht : MeasurableSet t) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [← measure_inter_add_diff (s ∪ t) ht, Set.union_inter_cancel_right, union_diff_right, ←
measure_inter_add_diff s ht]
ac_rfl
theorem measure_union_add_inter' (hs : MeasurableSet s) (t : Set α) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [union_comm, inter_comm, measure_union_add_inter t hs, add_comm]
lemma measure_symmDiff_eq (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) :
μ (s ∆ t) = μ (s \ t) + μ (t \ s) := by
simpa only [symmDiff_def, sup_eq_union]
using measure_union₀ (ht.diff hs) disjoint_sdiff_sdiff.aedisjoint
lemma measure_symmDiff_le (s t u : Set α) :
μ (s ∆ u) ≤ μ (s ∆ t) + μ (t ∆ u) :=
le_trans (μ.mono <| symmDiff_triangle s t u) (measure_union_le (s ∆ t) (t ∆ u))
theorem measure_symmDiff_eq_top (hs : μ s ≠ ∞) (ht : μ t = ∞) : μ (s ∆ t) = ∞ :=
measure_mono_top subset_union_right (measure_diff_eq_top ht hs)
theorem measure_add_measure_compl (h : MeasurableSet s) : μ s + μ sᶜ = μ univ :=
measure_add_measure_compl₀ h.nullMeasurableSet
theorem measure_biUnion₀ {s : Set β} {f : β → Set α} (hs : s.Countable)
(hd : s.Pairwise (AEDisjoint μ on f)) (h : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) := by
haveI := hs.toEncodable
rw [biUnion_eq_iUnion]
exact measure_iUnion₀ (hd.on_injective Subtype.coe_injective fun x => x.2) fun x => h x x.2
theorem measure_biUnion {s : Set β} {f : β → Set α} (hs : s.Countable) (hd : s.PairwiseDisjoint f)
(h : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) :=
measure_biUnion₀ hs hd.aedisjoint fun b hb => (h b hb).nullMeasurableSet
theorem measure_sUnion₀ {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise (AEDisjoint μ))
(h : ∀ s ∈ S, NullMeasurableSet s μ) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion₀ hs hd h]
theorem measure_sUnion {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise Disjoint)
(h : ∀ s ∈ S, MeasurableSet s) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion hs hd h]
theorem measure_biUnion_finset₀ {s : Finset ι} {f : ι → Set α}
(hd : Set.Pairwise (↑s) (AEDisjoint μ on f)) (hm : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) := by
rw [← Finset.sum_attach, Finset.attach_eq_univ, ← tsum_fintype]
exact measure_biUnion₀ s.countable_toSet hd hm
theorem measure_biUnion_finset {s : Finset ι} {f : ι → Set α} (hd : PairwiseDisjoint (↑s) f)
(hm : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) :=
measure_biUnion_finset₀ hd.aedisjoint fun b hb => (hm b hb).nullMeasurableSet
/-- The measure of an a.e. disjoint union (even uncountable) of null-measurable sets is at least
the sum of the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint₀ {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, NullMeasurableSet (As i) μ)
(As_disj : Pairwise (AEDisjoint μ on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) := by
rw [ENNReal.tsum_eq_iSup_sum, iSup_le_iff]
intro s
simp only [← measure_biUnion_finset₀ (fun _i _hi _j _hj hij => As_disj hij) fun i _ => As_mble i]
gcongr
exact iUnion_subset fun _ ↦ Subset.rfl
/-- The measure of a disjoint union (even uncountable) of measurable sets is at least the sum of
the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, MeasurableSet (As i))
(As_disj : Pairwise (Disjoint on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) :=
tsum_meas_le_meas_iUnion_of_disjoint₀ μ (fun i ↦ (As_mble i).nullMeasurableSet)
(fun _ _ h ↦ Disjoint.aedisjoint (As_disj h))
/-- If `s` is a countable set, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem tsum_measure_preimage_singleton {s : Set β} (hs : s.Countable) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑' b : s, μ (f ⁻¹' {↑b})) = μ (f ⁻¹' s) := by
rw [← Set.biUnion_preimage_singleton, measure_biUnion hs (pairwiseDisjoint_fiber f s) hf]
lemma measure_preimage_eq_zero_iff_of_countable {s : Set β} {f : α → β} (hs : s.Countable) :
μ (f ⁻¹' s) = 0 ↔ ∀ x ∈ s, μ (f ⁻¹' {x}) = 0 := by
rw [← biUnion_preimage_singleton, measure_biUnion_null_iff hs]
/-- If `s` is a `Finset`, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem sum_measure_preimage_singleton (s : Finset β) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑ b ∈ s, μ (f ⁻¹' {b})) = μ (f ⁻¹' ↑s) := by
simp only [← measure_biUnion_finset (pairwiseDisjoint_fiber f s) hf,
Finset.set_biUnion_preimage_singleton]
@[simp] lemma sum_measure_singleton {s : Finset α} [MeasurableSingletonClass α] :
∑ x ∈ s, μ {x} = μ s := by
trans ∑ x ∈ s, μ (id ⁻¹' {x})
· simp
rw [sum_measure_preimage_singleton]
· simp
· simp
theorem measure_diff_null' (h : μ (s₁ ∩ s₂) = 0) : μ (s₁ \ s₂) = μ s₁ :=
measure_congr <| diff_ae_eq_self.2 h
theorem measure_add_diff (hs : NullMeasurableSet s μ) (t : Set α) :
μ s + μ (t \ s) = μ (s ∪ t) := by
rw [← measure_union₀' hs disjoint_sdiff_right.aedisjoint, union_diff_self]
theorem measure_diff' (s : Set α) (hm : NullMeasurableSet t μ) (h_fin : μ t ≠ ∞) :
μ (s \ t) = μ (s ∪ t) - μ t :=
ENNReal.eq_sub_of_add_eq h_fin <| by rw [add_comm, measure_add_diff hm, union_comm]
theorem measure_diff (h : s₂ ⊆ s₁) (h₂ : NullMeasurableSet s₂ μ) (h_fin : μ s₂ ≠ ∞) :
μ (s₁ \ s₂) = μ s₁ - μ s₂ := by rw [measure_diff' _ h₂ h_fin, union_eq_self_of_subset_right h]
theorem le_measure_diff : μ s₁ - μ s₂ ≤ μ (s₁ \ s₂) :=
tsub_le_iff_left.2 <| (measure_le_inter_add_diff μ s₁ s₂).trans <| by
gcongr; apply inter_subset_right
/-- If the measure of the symmetric difference of two sets is finite,
then one has infinite measure if and only if the other one does. -/
theorem measure_eq_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s = ∞ ↔ μ t = ∞ := by
suffices h : ∀ u v, μ (u ∆ v) ≠ ∞ → μ u = ∞ → μ v = ∞
from ⟨h s t hμst, h t s (symmDiff_comm s t ▸ hμst)⟩
intro u v hμuv hμu
by_contra! hμv
apply hμuv
rw [Set.symmDiff_def, eq_top_iff]
calc
∞ = μ u - μ v := by rw [ENNReal.sub_eq_top_iff.2 ⟨hμu, hμv⟩]
_ ≤ μ (u \ v) := le_measure_diff
_ ≤ μ (u \ v ∪ v \ u) := measure_mono subset_union_left
/-- If the measure of the symmetric difference of two sets is finite,
then one has finite measure if and only if the other one does. -/
theorem measure_ne_top_iff_of_symmDiff (hμst : μ (s ∆ t) ≠ ∞) : μ s ≠ ∞ ↔ μ t ≠ ∞ :=
(measure_eq_top_iff_of_symmDiff hμst).ne
theorem measure_diff_lt_of_lt_add (hs : NullMeasurableSet s μ) (hst : s ⊆ t) (hs' : μ s ≠ ∞)
{ε : ℝ≥0∞} (h : μ t < μ s + ε) : μ (t \ s) < ε := by
rw [measure_diff hst hs hs']; rw [add_comm] at h
exact ENNReal.sub_lt_of_lt_add (measure_mono hst) h
theorem measure_diff_le_iff_le_add (hs : NullMeasurableSet s μ) (hst : s ⊆ t) (hs' : μ s ≠ ∞)
{ε : ℝ≥0∞} : μ (t \ s) ≤ ε ↔ μ t ≤ μ s + ε := by
rw [measure_diff hst hs hs', tsub_le_iff_left]
theorem measure_eq_measure_of_null_diff {s t : Set α} (hst : s ⊆ t) (h_nulldiff : μ (t \ s) = 0) :
μ s = μ t := measure_congr <|
EventuallyLE.antisymm (HasSubset.Subset.eventuallyLE hst) (ae_le_set.mpr h_nulldiff)
theorem measure_eq_measure_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂) (h23 : s₂ ⊆ s₃)
(h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ ∧ μ s₂ = μ s₃ := by
have le12 : μ s₁ ≤ μ s₂ := measure_mono h12
have le23 : μ s₂ ≤ μ s₃ := measure_mono h23
have key : μ s₃ ≤ μ s₁ :=
calc
μ s₃ = μ (s₃ \ s₁ ∪ s₁) := by rw [diff_union_of_subset (h12.trans h23)]
_ ≤ μ (s₃ \ s₁) + μ s₁ := measure_union_le _ _
_ = μ s₁ := by simp only [h_nulldiff, zero_add]
exact ⟨le12.antisymm (le23.trans key), le23.antisymm (key.trans le12)⟩
theorem measure_eq_measure_smaller_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂)
(h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₁ = μ s₂ :=
(measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).1
theorem measure_eq_measure_larger_of_between_null_diff {s₁ s₂ s₃ : Set α} (h12 : s₁ ⊆ s₂)
(h23 : s₂ ⊆ s₃) (h_nulldiff : μ (s₃ \ s₁) = 0) : μ s₂ = μ s₃ :=
(measure_eq_measure_of_between_null_diff h12 h23 h_nulldiff).2
lemma measure_compl₀ (h : NullMeasurableSet s μ) (hs : μ s ≠ ∞) :
μ sᶜ = μ Set.univ - μ s := by
rw [← measure_add_measure_compl₀ h, ENNReal.add_sub_cancel_left hs]
theorem measure_compl (h₁ : MeasurableSet s) (h_fin : μ s ≠ ∞) : μ sᶜ = μ univ - μ s :=
measure_compl₀ h₁.nullMeasurableSet h_fin
lemma measure_inter_conull' (ht : μ (s \ t) = 0) : μ (s ∩ t) = μ s := by
rw [← diff_compl, measure_diff_null']; rwa [← diff_eq]
lemma measure_inter_conull (ht : μ tᶜ = 0) : μ (s ∩ t) = μ s := by
rw [← diff_compl, measure_diff_null ht]
@[simp]
theorem union_ae_eq_left_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] s ↔ t ≤ᵐ[μ] s := by
rw [ae_le_set]
refine
⟨fun h => by simpa only [union_diff_left] using (ae_eq_set.mp h).1, fun h =>
eventuallyLE_antisymm_iff.mpr
⟨by rwa [ae_le_set, union_diff_left],
HasSubset.Subset.eventuallyLE subset_union_left⟩⟩
@[simp]
theorem union_ae_eq_right_iff_ae_subset : (s ∪ t : Set α) =ᵐ[μ] t ↔ s ≤ᵐ[μ] t := by
rw [union_comm, union_ae_eq_left_iff_ae_subset]
theorem ae_eq_of_ae_subset_of_measure_ge (h₁ : s ≤ᵐ[μ] t) (h₂ : μ t ≤ μ s)
(hsm : NullMeasurableSet s μ) (ht : μ t ≠ ∞) : s =ᵐ[μ] t := by
refine eventuallyLE_antisymm_iff.mpr ⟨h₁, ae_le_set.mpr ?_⟩
replace h₂ : μ t = μ s := h₂.antisymm (measure_mono_ae h₁)
replace ht : μ s ≠ ∞ := h₂ ▸ ht
rw [measure_diff' t hsm ht, measure_congr (union_ae_eq_left_iff_ae_subset.mpr h₁), h₂, tsub_self]
/-- If `s ⊆ t`, `μ t ≤ μ s`, `μ t ≠ ∞`, and `s` is measurable, then `s =ᵐ[μ] t`. -/
theorem ae_eq_of_subset_of_measure_ge (h₁ : s ⊆ t) (h₂ : μ t ≤ μ s) (hsm : NullMeasurableSet s μ)
(ht : μ t ≠ ∞) : s =ᵐ[μ] t :=
ae_eq_of_ae_subset_of_measure_ge (HasSubset.Subset.eventuallyLE h₁) h₂ hsm ht
theorem measure_iUnion_congr_of_subset {ι : Sort*} [Countable ι] {s : ι → Set α} {t : ι → Set α}
(hsub : ∀ i, s i ⊆ t i) (h_le : ∀ i, μ (t i) ≤ μ (s i)) : μ (⋃ i, s i) = μ (⋃ i, t i) := by
refine le_antisymm (by gcongr; apply hsub) ?_
rcases Classical.em (∃ i, μ (t i) = ∞) with (⟨i, hi⟩ | htop)
· calc
μ (⋃ i, t i) ≤ ∞ := le_top
_ ≤ μ (s i) := hi ▸ h_le i
_ ≤ μ (⋃ i, s i) := measure_mono <| subset_iUnion _ _
push_neg at htop
set M := toMeasurable μ
have H : ∀ b, (M (t b) ∩ M (⋃ b, s b) : Set α) =ᵐ[μ] M (t b) := by
refine fun b => ae_eq_of_subset_of_measure_ge inter_subset_left ?_ ?_ ?_
· calc
μ (M (t b)) = μ (t b) := measure_toMeasurable _
_ ≤ μ (s b) := h_le b
_ ≤ μ (M (t b) ∩ M (⋃ b, s b)) :=
measure_mono <|
subset_inter ((hsub b).trans <| subset_toMeasurable _ _)
((subset_iUnion _ _).trans <| subset_toMeasurable _ _)
· measurability
· rw [measure_toMeasurable]
exact htop b
calc
μ (⋃ b, t b) ≤ μ (⋃ b, M (t b)) := measure_mono (iUnion_mono fun b => subset_toMeasurable _ _)
_ = μ (⋃ b, M (t b) ∩ M (⋃ b, s b)) := measure_congr (EventuallyEq.countable_iUnion H).symm
_ ≤ μ (M (⋃ b, s b)) := measure_mono (iUnion_subset fun b => inter_subset_right)
_ = μ (⋃ b, s b) := measure_toMeasurable _
theorem measure_union_congr_of_subset {t₁ t₂ : Set α} (hs : s₁ ⊆ s₂) (hsμ : μ s₂ ≤ μ s₁)
(ht : t₁ ⊆ t₂) (htμ : μ t₂ ≤ μ t₁) : μ (s₁ ∪ t₁) = μ (s₂ ∪ t₂) := by
rw [union_eq_iUnion, union_eq_iUnion]
exact measure_iUnion_congr_of_subset (Bool.forall_bool.2 ⟨ht, hs⟩) (Bool.forall_bool.2 ⟨htμ, hsμ⟩)
@[simp]
theorem measure_iUnion_toMeasurable {ι : Sort*} [Countable ι] (s : ι → Set α) :
μ (⋃ i, toMeasurable μ (s i)) = μ (⋃ i, s i) :=
Eq.symm <| measure_iUnion_congr_of_subset (fun _i => subset_toMeasurable _ _) fun _i ↦
(measure_toMeasurable _).le
theorem measure_biUnion_toMeasurable {I : Set β} (hc : I.Countable) (s : β → Set α) :
μ (⋃ b ∈ I, toMeasurable μ (s b)) = μ (⋃ b ∈ I, s b) := by
haveI := hc.toEncodable
simp only [biUnion_eq_iUnion, measure_iUnion_toMeasurable]
@[simp]
theorem measure_toMeasurable_union : μ (toMeasurable μ s ∪ t) = μ (s ∪ t) :=
Eq.symm <|
measure_union_congr_of_subset (subset_toMeasurable _ _) (measure_toMeasurable _).le Subset.rfl
le_rfl
@[simp]
theorem measure_union_toMeasurable : μ (s ∪ toMeasurable μ t) = μ (s ∪ t) :=
Eq.symm <|
measure_union_congr_of_subset Subset.rfl le_rfl (subset_toMeasurable _ _)
(measure_toMeasurable _).le
theorem sum_measure_le_measure_univ {s : Finset ι} {t : ι → Set α}
(h : ∀ i ∈ s, NullMeasurableSet (t i) μ) (H : Set.Pairwise s (AEDisjoint μ on t)) :
(∑ i ∈ s, μ (t i)) ≤ μ (univ : Set α) := by
rw [← measure_biUnion_finset₀ H h]
exact measure_mono (subset_univ _)
theorem tsum_measure_le_measure_univ {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ)
(H : Pairwise (AEDisjoint μ on s)) : ∑' i, μ (s i) ≤ μ (univ : Set α) := by
rw [ENNReal.tsum_eq_iSup_sum]
exact iSup_le fun s =>
sum_measure_le_measure_univ (fun i _hi => hs i) fun i _hi j _hj hij => H hij
/-- Pigeonhole principle for measure spaces: if `∑' i, μ (s i) > μ univ`, then
one of the intersections `s i ∩ s j` is not empty. -/
theorem exists_nonempty_inter_of_measure_univ_lt_tsum_measure {m : MeasurableSpace α}
(μ : Measure α) {s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ)
(H : μ (univ : Set α) < ∑' i, μ (s i)) : ∃ i j, i ≠ j ∧ (s i ∩ s j).Nonempty := by
contrapose! H
apply tsum_measure_le_measure_univ hs
intro i j hij
exact (disjoint_iff_inter_eq_empty.mpr (H i j hij)).aedisjoint
/-- Pigeonhole principle for measure spaces: if `s` is a `Finset` and
`∑ i ∈ s, μ (t i) > μ univ`, then one of the intersections `t i ∩ t j` is not empty. -/
theorem exists_nonempty_inter_of_measure_univ_lt_sum_measure {m : MeasurableSpace α} (μ : Measure α)
{s : Finset ι} {t : ι → Set α} (h : ∀ i ∈ s, NullMeasurableSet (t i) μ)
(H : μ (univ : Set α) < ∑ i ∈ s, μ (t i)) :
∃ i ∈ s, ∃ j ∈ s, ∃ _h : i ≠ j, (t i ∩ t j).Nonempty := by
contrapose! H
apply sum_measure_le_measure_univ h
intro i hi j hj hij
exact (disjoint_iff_inter_eq_empty.mpr (H i hi j hj hij)).aedisjoint
/-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`,
then `s` intersects `t`. Version assuming that `t` is measurable. -/
theorem nonempty_inter_of_measure_lt_add {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α}
(ht : MeasurableSet t) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) :
(s ∩ t).Nonempty := by
rw [← Set.not_disjoint_iff_nonempty_inter]
contrapose! h
calc
μ s + μ t = μ (s ∪ t) := (measure_union h ht).symm
_ ≤ μ u := measure_mono (union_subset h's h't)
/-- If two sets `s` and `t` are included in a set `u`, and `μ s + μ t > μ u`,
then `s` intersects `t`. Version assuming that `s` is measurable. -/
theorem nonempty_inter_of_measure_lt_add' {m : MeasurableSpace α} (μ : Measure α) {s t u : Set α}
(hs : MeasurableSet s) (h's : s ⊆ u) (h't : t ⊆ u) (h : μ u < μ s + μ t) :
(s ∩ t).Nonempty := by
rw [add_comm] at h
rw [inter_comm]
exact nonempty_inter_of_measure_lt_add μ hs h't h's h
/-- Continuity from below:
the measure of the union of a directed sequence of (not necessarily measurable) sets
is the supremum of the measures. -/
theorem _root_.Directed.measure_iUnion [Countable ι] {s : ι → Set α} (hd : Directed (· ⊆ ·) s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) := by
-- WLOG, `ι = ℕ`
rcases Countable.exists_injective_nat ι with ⟨e, he⟩
generalize ht : Function.extend e s ⊥ = t
replace hd : Directed (· ⊆ ·) t := ht ▸ hd.extend_bot he
suffices μ (⋃ n, t n) = ⨆ n, μ (t n) by
simp only [← ht, Function.apply_extend μ, ← iSup_eq_iUnion, iSup_extend_bot he,
Function.comp_def, Pi.bot_apply, bot_eq_empty, measure_empty] at this
exact this.trans (iSup_extend_bot he _)
clear! ι
-- The `≥` inequality is trivial
refine le_antisymm ?_ (iSup_le fun i ↦ measure_mono <| subset_iUnion _ _)
-- Choose `T n ⊇ t n` of the same measure, put `Td n = disjointed T`
set T : ℕ → Set α := fun n => toMeasurable μ (t n)
set Td : ℕ → Set α := disjointed T
have hm : ∀ n, MeasurableSet (Td n) := .disjointed fun n ↦ measurableSet_toMeasurable _ _
calc
μ (⋃ n, t n) = μ (⋃ n, Td n) := by rw [iUnion_disjointed, measure_iUnion_toMeasurable]
_ ≤ ∑' n, μ (Td n) := measure_iUnion_le _
_ = ⨆ I : Finset ℕ, ∑ n ∈ I, μ (Td n) := ENNReal.tsum_eq_iSup_sum
_ ≤ ⨆ n, μ (t n) := iSup_le fun I => by
rcases hd.finset_le I with ⟨N, hN⟩
calc
(∑ n ∈ I, μ (Td n)) = μ (⋃ n ∈ I, Td n) :=
(measure_biUnion_finset ((disjoint_disjointed T).set_pairwise I) fun n _ => hm n).symm
_ ≤ μ (⋃ n ∈ I, T n) := measure_mono (iUnion₂_mono fun n _hn => disjointed_subset _ _)
_ = μ (⋃ n ∈ I, t n) := measure_biUnion_toMeasurable I.countable_toSet _
_ ≤ μ (t N) := measure_mono (iUnion₂_subset hN)
_ ≤ ⨆ n, μ (t n) := le_iSup (μ ∘ t) N
/-- Continuity from below:
the measure of the union of a monotone family of sets is equal to the supremum of their measures.
The theorem assumes that the `atTop` filter on the index set is countably generated,
so it works for a family indexed by a countable type, as well as `ℝ`. -/
theorem _root_.Monotone.measure_iUnion [Preorder ι] [IsDirected ι (· ≤ ·)]
[(atTop : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Monotone s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) := by
cases isEmpty_or_nonempty ι with
| inl _ => simp
| inr _ =>
rcases exists_seq_monotone_tendsto_atTop_atTop ι with ⟨x, hxm, hx⟩
rw [← hs.iUnion_comp_tendsto_atTop hx, ← Monotone.iSup_comp_tendsto_atTop _ hx]
exacts [(hs.comp hxm).directed_le.measure_iUnion, fun _ _ h ↦ measure_mono (hs h)]
theorem _root_.Antitone.measure_iUnion [Preorder ι] [IsDirected ι (· ≥ ·)]
[(atBot : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Antitone s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) :=
hs.dual_left.measure_iUnion
/-- Continuity from below: the measure of the union of a sequence of
(not necessarily measurable) sets is the supremum of the measures of the partial unions. -/
theorem measure_iUnion_eq_iSup_accumulate [Preorder ι] [IsDirected ι (· ≤ ·)]
[(atTop : Filter ι).IsCountablyGenerated] {f : ι → Set α} :
μ (⋃ i, f i) = ⨆ i, μ (Accumulate f i) := by
rw [← iUnion_accumulate]
exact monotone_accumulate.measure_iUnion
theorem measure_biUnion_eq_iSup {s : ι → Set α} {t : Set ι} (ht : t.Countable)
(hd : DirectedOn ((· ⊆ ·) on s) t) : μ (⋃ i ∈ t, s i) = ⨆ i ∈ t, μ (s i) := by
haveI := ht.to_subtype
rw [biUnion_eq_iUnion, hd.directed_val.measure_iUnion, ← iSup_subtype'']
/-- **Continuity from above**:
the measure of the intersection of a directed downwards countable family of measurable sets
is the infimum of the measures. -/
theorem _root_.Directed.measure_iInter [Countable ι] {s : ι → Set α}
(h : ∀ i, NullMeasurableSet (s i) μ) (hd : Directed (· ⊇ ·) s) (hfin : ∃ i, μ (s i) ≠ ∞) :
μ (⋂ i, s i) = ⨅ i, μ (s i) := by
rcases hfin with ⟨k, hk⟩
have : ∀ t ⊆ s k, μ t ≠ ∞ := fun t ht => ne_top_of_le_ne_top hk (measure_mono ht)
rw [← ENNReal.sub_sub_cancel hk (iInf_le (fun i => μ (s i)) k), ENNReal.sub_iInf, ←
ENNReal.sub_sub_cancel hk (measure_mono (iInter_subset _ k)), ←
measure_diff (iInter_subset _ k) (.iInter h) (this _ (iInter_subset _ k)),
diff_iInter, Directed.measure_iUnion]
· congr 1
refine le_antisymm (iSup_mono' fun i => ?_) (iSup_mono fun i => le_measure_diff)
rcases hd i k with ⟨j, hji, hjk⟩
use j
rw [← measure_diff hjk (h _) (this _ hjk)]
gcongr
· exact hd.mono_comp _ fun _ _ => diff_subset_diff_right
/-- **Continuity from above**:
the measure of the intersection of a monotone family of measurable sets
indexed by a type with countably generated `atBot` filter
is equal to the infimum of the measures. -/
theorem _root_.Monotone.measure_iInter [Preorder ι] [IsDirected ι (· ≥ ·)]
[(atBot : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Monotone s)
(hsm : ∀ i, NullMeasurableSet (s i) μ) (hfin : ∃ i, μ (s i) ≠ ∞) :
μ (⋂ i, s i) = ⨅ i, μ (s i) := by
refine le_antisymm (le_iInf fun i ↦ measure_mono <| iInter_subset _ _) ?_
have := hfin.nonempty
rcases exists_seq_antitone_tendsto_atTop_atBot ι with ⟨x, hxm, hx⟩
calc
⨅ i, μ (s i) ≤ ⨅ n, μ (s (x n)) := le_iInf_comp (μ ∘ s) x
_ = μ (⋂ n, s (x n)) := by
refine .symm <| (hs.comp_antitone hxm).directed_ge.measure_iInter (fun n ↦ hsm _) ?_
rcases hfin with ⟨k, hk⟩
rcases (hx.eventually_le_atBot k).exists with ⟨n, hn⟩
exact ⟨n, ne_top_of_le_ne_top hk <| measure_mono <| hs hn⟩
_ ≤ μ (⋂ i, s i) := by
refine measure_mono <| iInter_mono' fun i ↦ ?_
rcases (hx.eventually_le_atBot i).exists with ⟨n, hn⟩
exact ⟨n, hs hn⟩
/-- **Continuity from above**:
the measure of the intersection of an antitone family of measurable sets
indexed by a type with countably generated `atTop` filter
is equal to the infimum of the measures. -/
theorem _root_.Antitone.measure_iInter [Preorder ι] [IsDirected ι (· ≤ ·)]
[(atTop : Filter ι).IsCountablyGenerated] {s : ι → Set α} (hs : Antitone s)
(hsm : ∀ i, NullMeasurableSet (s i) μ) (hfin : ∃ i, μ (s i) ≠ ∞) :
μ (⋂ i, s i) = ⨅ i, μ (s i) :=
hs.dual_left.measure_iInter hsm hfin
/-- Continuity from above: the measure of the intersection of a sequence of
measurable sets is the infimum of the measures of the partial intersections. -/
theorem measure_iInter_eq_iInf_measure_iInter_le {α ι : Type*} {_ : MeasurableSpace α}
{μ : Measure α} [Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)]
{f : ι → Set α} (h : ∀ i, NullMeasurableSet (f i) μ) (hfin : ∃ i, μ (f i) ≠ ∞) :
μ (⋂ i, f i) = ⨅ i, μ (⋂ j ≤ i, f j) := by
rw [← Antitone.measure_iInter]
· rw [iInter_comm]
exact congrArg μ <| iInter_congr fun i ↦ (biInf_const nonempty_Ici).symm
· exact fun i j h ↦ biInter_mono (Iic_subset_Iic.2 h) fun _ _ ↦ Set.Subset.rfl
· exact fun i ↦ .biInter (to_countable _) fun _ _ ↦ h _
· refine hfin.imp fun k hk ↦ ne_top_of_le_ne_top hk <| measure_mono <| iInter₂_subset k ?_
rfl
/-- Continuity from below: the measure of the union of an increasing sequence of (not necessarily
measurable) sets is the limit of the measures. -/
theorem tendsto_measure_iUnion_atTop [Preorder ι] [IsCountablyGenerated (atTop : Filter ι)]
{s : ι → Set α} (hm : Monotone s) : Tendsto (μ ∘ s) atTop (𝓝 (μ (⋃ n, s n))) := by
refine .of_neBot_imp fun h ↦ ?_
have := (atTop_neBot_iff.1 h).2
rw [hm.measure_iUnion]
exact tendsto_atTop_iSup fun n m hnm => measure_mono <| hm hnm
theorem tendsto_measure_iUnion_atBot [Preorder ι] [IsCountablyGenerated (atBot : Filter ι)]
{s : ι → Set α} (hm : Antitone s) : Tendsto (μ ∘ s) atBot (𝓝 (μ (⋃ n, s n))) :=
tendsto_measure_iUnion_atTop (ι := ιᵒᵈ) hm.dual_left
/-- Continuity from below: the measure of the union of a sequence of (not necessarily measurable)
sets is the limit of the measures of the partial unions. -/
theorem tendsto_measure_iUnion_accumulate {α ι : Type*}
[Preorder ι] [IsCountablyGenerated (atTop : Filter ι)]
{_ : MeasurableSpace α} {μ : Measure α} {f : ι → Set α} :
Tendsto (fun i ↦ μ (Accumulate f i)) atTop (𝓝 (μ (⋃ i, f i))) := by
refine .of_neBot_imp fun h ↦ ?_
have := (atTop_neBot_iff.1 h).2
rw [measure_iUnion_eq_iSup_accumulate]
exact tendsto_atTop_iSup fun i j hij ↦ by gcongr
/-- Continuity from above: the measure of the intersection of a decreasing sequence of measurable
sets is the limit of the measures. -/
theorem tendsto_measure_iInter_atTop [Preorder ι]
[IsCountablyGenerated (atTop : Filter ι)] {s : ι → Set α}
(hs : ∀ i, NullMeasurableSet (s i) μ) (hm : Antitone s) (hf : ∃ i, μ (s i) ≠ ∞) :
Tendsto (μ ∘ s) atTop (𝓝 (μ (⋂ n, s n))) := by
refine .of_neBot_imp fun h ↦ ?_
have := (atTop_neBot_iff.1 h).2
rw [hm.measure_iInter hs hf]
exact tendsto_atTop_iInf fun n m hnm => measure_mono <| hm hnm
/-- Continuity from above: the measure of the intersection of an increasing sequence of measurable
sets is the limit of the measures. -/
theorem tendsto_measure_iInter_atBot [Preorder ι] [IsCountablyGenerated (atBot : Filter ι)]
{s : ι → Set α} (hs : ∀ i, NullMeasurableSet (s i) μ) (hm : Monotone s)
(hf : ∃ i, μ (s i) ≠ ∞) : Tendsto (μ ∘ s) atBot (𝓝 (μ (⋂ n, s n))) :=
tendsto_measure_iInter_atTop (ι := ιᵒᵈ) hs hm.dual_left hf
/-- Continuity from above: the measure of the intersection of a sequence of measurable
sets such that one has finite measure is the limit of the measures of the partial intersections. -/
theorem tendsto_measure_iInter_le {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α}
[Countable ι] [Preorder ι] {f : ι → Set α} (hm : ∀ i, NullMeasurableSet (f i) μ)
(hf : ∃ i, μ (f i) ≠ ∞) :
Tendsto (fun i ↦ μ (⋂ j ≤ i, f j)) atTop (𝓝 (μ (⋂ i, f i))) := by
refine .of_neBot_imp fun hne ↦ ?_
cases atTop_neBot_iff.mp hne
rw [measure_iInter_eq_iInf_measure_iInter_le hm hf]
exact tendsto_atTop_iInf
fun i j hij ↦ measure_mono <| biInter_subset_biInter_left fun k hki ↦ le_trans hki hij
/-- Some version of continuity of a measure in the empty set using the intersection along a set of
sets. -/
theorem exists_measure_iInter_lt {α ι : Type*} {_ : MeasurableSpace α} {μ : Measure α}
[SemilatticeSup ι] [Countable ι] {f : ι → Set α}
(hm : ∀ i, NullMeasurableSet (f i) μ) {ε : ℝ≥0∞} (hε : 0 < ε) (hfin : ∃ i, μ (f i) ≠ ∞)
(hfem : ⋂ n, f n = ∅) : ∃ m, μ (⋂ n ≤ m, f n) < ε := by
let F m := μ (⋂ n ≤ m, f n)
have hFAnti : Antitone F :=
fun i j hij => measure_mono (biInter_subset_biInter_left fun k hki => le_trans hki hij)
suffices Filter.Tendsto F Filter.atTop (𝓝 0) by
rw [@ENNReal.tendsto_atTop_zero_iff_lt_of_antitone
_ (nonempty_of_exists hfin) _ _ hFAnti] at this
exact this ε hε
have hzero : μ (⋂ n, f n) = 0 := by
simp only [hfem, measure_empty]
rw [← hzero]
exact tendsto_measure_iInter_le hm hfin
/-- The measure of the intersection of a decreasing sequence of measurable
sets indexed by a linear order with first countable topology is the limit of the measures. -/
theorem tendsto_measure_biInter_gt {ι : Type*} [LinearOrder ι] [TopologicalSpace ι]
[OrderTopology ι] [DenselyOrdered ι] [FirstCountableTopology ι] {s : ι → Set α}
{a : ι} (hs : ∀ r > a, NullMeasurableSet (s r) μ) (hm : ∀ i j, a < i → i ≤ j → s i ⊆ s j)
(hf : ∃ r > a, μ (s r) ≠ ∞) : Tendsto (μ ∘ s) (𝓝[Ioi a] a) (𝓝 (μ (⋂ r > a, s r))) := by
have : (atBot : Filter (Ioi a)).IsCountablyGenerated := by
rw [← comap_coe_Ioi_nhdsGT]
infer_instance
simp_rw [← map_coe_Ioi_atBot, tendsto_map'_iff, ← mem_Ioi, biInter_eq_iInter]
apply tendsto_measure_iInter_atBot
· rwa [Subtype.forall]
· exact fun i j h ↦ hm i j i.2 h
· simpa only [Subtype.exists, exists_prop]
theorem measure_if {x : β} {t : Set β} {s : Set α} [Decidable (x ∈ t)] :
μ (if x ∈ t then s else ∅) = indicator t (fun _ => μ s) x := by split_ifs with h <;> simp [h]
end
section OuterMeasure
variable [ms : MeasurableSpace α] {s t : Set α}
/-- Obtain a measure by giving an outer measure where all sets in the σ-algebra are
Carathéodory measurable. -/
def OuterMeasure.toMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) : Measure α :=
Measure.ofMeasurable (fun s _ => m s) m.empty fun _f hf hd =>
m.iUnion_eq_of_caratheodory (fun i => h _ (hf i)) hd
theorem le_toOuterMeasure_caratheodory (μ : Measure α) : ms ≤ μ.toOuterMeasure.caratheodory :=
fun _s hs _t => (measure_inter_add_diff _ hs).symm
@[simp]
theorem toMeasure_toOuterMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) :
(m.toMeasure h).toOuterMeasure = m.trim :=
rfl
@[simp]
theorem toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α}
(hs : MeasurableSet s) : m.toMeasure h s = m s :=
m.trim_eq hs
theorem le_toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) (s : Set α) :
m s ≤ m.toMeasure h s :=
m.le_trim s
theorem toMeasure_apply₀ (m : OuterMeasure α) (h : ms ≤ m.caratheodory) {s : Set α}
(hs : NullMeasurableSet s (m.toMeasure h)) : m.toMeasure h s = m s := by
refine le_antisymm ?_ (le_toMeasure_apply _ _ _)
rcases hs.exists_measurable_subset_ae_eq with ⟨t, hts, htm, heq⟩
calc
m.toMeasure h s = m.toMeasure h t := measure_congr heq.symm
_ = m t := toMeasure_apply m h htm
_ ≤ m s := m.mono hts
@[simp]
theorem toOuterMeasure_toMeasure {μ : Measure α} :
μ.toOuterMeasure.toMeasure (le_toOuterMeasure_caratheodory _) = μ :=
Measure.ext fun _s => μ.toOuterMeasure.trim_eq
@[simp]
theorem boundedBy_measure (μ : Measure α) : OuterMeasure.boundedBy μ = μ.toOuterMeasure :=
μ.toOuterMeasure.boundedBy_eq_self
end OuterMeasure
section
variable {m0 : MeasurableSpace α} {mβ : MeasurableSpace β} [MeasurableSpace γ]
variable {μ μ₁ μ₂ μ₃ ν ν' ν₁ ν₂ : Measure α} {s s' t : Set α}
namespace Measure
/-- If `u` is a superset of `t` with the same (finite) measure (both sets possibly non-measurable),
then for any measurable set `s` one also has `μ (t ∩ s) = μ (u ∩ s)`. -/
theorem measure_inter_eq_of_measure_eq {s t u : Set α} (hs : MeasurableSet s) (h : μ t = μ u)
(htu : t ⊆ u) (ht_ne_top : μ t ≠ ∞) : μ (t ∩ s) = μ (u ∩ s) := by
rw [h] at ht_ne_top
refine le_antisymm (by gcongr) ?_
have A : μ (u ∩ s) + μ (u \ s) ≤ μ (t ∩ s) + μ (u \ s) :=
calc
μ (u ∩ s) + μ (u \ s) = μ u := measure_inter_add_diff _ hs
_ = μ t := h.symm
_ = μ (t ∩ s) + μ (t \ s) := (measure_inter_add_diff _ hs).symm
_ ≤ μ (t ∩ s) + μ (u \ s) := by gcongr
have B : μ (u \ s) ≠ ∞ := (lt_of_le_of_lt (measure_mono diff_subset) ht_ne_top.lt_top).ne
exact ENNReal.le_of_add_le_add_right B A
/-- The measurable superset `toMeasurable μ t` of `t` (which has the same measure as `t`)
satisfies, for any measurable set `s`, the equality `μ (toMeasurable μ t ∩ s) = μ (u ∩ s)`.
Here, we require that the measure of `t` is finite. The conclusion holds without this assumption
when the measure is s-finite (for example when it is σ-finite),
see `measure_toMeasurable_inter_of_sFinite`. -/
theorem measure_toMeasurable_inter {s t : Set α} (hs : MeasurableSet s) (ht : μ t ≠ ∞) :
μ (toMeasurable μ t ∩ s) = μ (t ∩ s) :=
(measure_inter_eq_of_measure_eq hs (measure_toMeasurable t).symm (subset_toMeasurable μ t)
ht).symm
/-! ### The `ℝ≥0∞`-module of measures -/
instance instZero {_ : MeasurableSpace α} : Zero (Measure α) :=
⟨{ toOuterMeasure := 0
m_iUnion := fun _f _hf _hd => tsum_zero.symm
trim_le := OuterMeasure.trim_zero.le }⟩
@[simp]
theorem zero_toOuterMeasure {_m : MeasurableSpace α} : (0 : Measure α).toOuterMeasure = 0 :=
rfl
@[simp, norm_cast]
theorem coe_zero {_m : MeasurableSpace α} : ⇑(0 : Measure α) = 0 :=
rfl
@[simp] lemma _root_.MeasureTheory.OuterMeasure.toMeasure_zero
[ms : MeasurableSpace α] (h : ms ≤ (0 : OuterMeasure α).caratheodory) :
(0 : OuterMeasure α).toMeasure h = 0 := by
ext s hs
simp [hs]
@[simp] lemma _root_.MeasureTheory.OuterMeasure.toMeasure_eq_zero {ms : MeasurableSpace α}
{μ : OuterMeasure α} (h : ms ≤ μ.caratheodory) : μ.toMeasure h = 0 ↔ μ = 0 where
mp hμ := by ext s; exact le_bot_iff.1 <| (le_toMeasure_apply _ _ _).trans_eq congr($hμ s)
mpr := by rintro rfl; simp
@[nontriviality]
lemma apply_eq_zero_of_isEmpty [IsEmpty α] {_ : MeasurableSpace α} (μ : Measure α) (s : Set α) :
μ s = 0 := by
rw [eq_empty_of_isEmpty s, measure_empty]
instance instSubsingleton [IsEmpty α] {m : MeasurableSpace α} : Subsingleton (Measure α) :=
⟨fun μ ν => by ext1 s _; rw [apply_eq_zero_of_isEmpty, apply_eq_zero_of_isEmpty]⟩
theorem eq_zero_of_isEmpty [IsEmpty α] {_m : MeasurableSpace α} (μ : Measure α) : μ = 0 :=
Subsingleton.elim μ 0
instance instInhabited {_ : MeasurableSpace α} : Inhabited (Measure α) :=
⟨0⟩
instance instAdd {_ : MeasurableSpace α} : Add (Measure α) :=
⟨fun μ₁ μ₂ =>
{ toOuterMeasure := μ₁.toOuterMeasure + μ₂.toOuterMeasure
m_iUnion := fun s hs hd =>
show μ₁ (⋃ i, s i) + μ₂ (⋃ i, s i) = ∑' i, (μ₁ (s i) + μ₂ (s i)) by
rw [ENNReal.tsum_add, measure_iUnion hd hs, measure_iUnion hd hs]
trim_le := by rw [OuterMeasure.trim_add, μ₁.trimmed, μ₂.trimmed] }⟩
@[simp]
theorem add_toOuterMeasure {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) :
(μ₁ + μ₂).toOuterMeasure = μ₁.toOuterMeasure + μ₂.toOuterMeasure :=
rfl
@[simp, norm_cast]
theorem coe_add {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) : ⇑(μ₁ + μ₂) = μ₁ + μ₂ :=
rfl
theorem add_apply {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) (s : Set α) :
(μ₁ + μ₂) s = μ₁ s + μ₂ s :=
rfl
section SMul
variable [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
variable [SMul R' ℝ≥0∞] [IsScalarTower R' ℝ≥0∞ ℝ≥0∞]
instance instSMul {_ : MeasurableSpace α} : SMul R (Measure α) :=
⟨fun c μ =>
{ toOuterMeasure := c • μ.toOuterMeasure
m_iUnion := fun s hs hd => by
simp only [OuterMeasure.smul_apply, coe_toOuterMeasure, ENNReal.tsum_const_smul,
measure_iUnion hd hs]
trim_le := by rw [OuterMeasure.trim_smul, μ.trimmed] }⟩
@[simp]
theorem smul_toOuterMeasure {_m : MeasurableSpace α} (c : R) (μ : Measure α) :
(c • μ).toOuterMeasure = c • μ.toOuterMeasure :=
rfl
@[simp, norm_cast]
theorem coe_smul {_m : MeasurableSpace α} (c : R) (μ : Measure α) : ⇑(c • μ) = c • ⇑μ :=
rfl
@[simp]
theorem smul_apply {_m : MeasurableSpace α} (c : R) (μ : Measure α) (s : Set α) :
(c • μ) s = c • μ s :=
rfl
instance instSMulCommClass [SMulCommClass R R' ℝ≥0∞] {_ : MeasurableSpace α} :
SMulCommClass R R' (Measure α) :=
⟨fun _ _ _ => ext fun _ _ => smul_comm _ _ _⟩
instance instIsScalarTower [SMul R R'] [IsScalarTower R R' ℝ≥0∞] {_ : MeasurableSpace α} :
IsScalarTower R R' (Measure α) :=
⟨fun _ _ _ => ext fun _ _ => smul_assoc _ _ _⟩
instance instIsCentralScalar [SMul Rᵐᵒᵖ ℝ≥0∞] [IsCentralScalar R ℝ≥0∞] {_ : MeasurableSpace α} :
IsCentralScalar R (Measure α) :=
⟨fun _ _ => ext fun _ _ => op_smul_eq_smul _ _⟩
end SMul
instance instNoZeroSMulDivisors [Zero R] [SMulWithZero R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
[NoZeroSMulDivisors R ℝ≥0∞] : NoZeroSMulDivisors R (Measure α) where
eq_zero_or_eq_zero_of_smul_eq_zero h := by simpa [Ne, ext_iff', forall_or_left] using h
instance instMulAction [Monoid R] [MulAction R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
{_ : MeasurableSpace α} : MulAction R (Measure α) :=
Injective.mulAction _ toOuterMeasure_injective smul_toOuterMeasure
instance instAddCommMonoid {_ : MeasurableSpace α} : AddCommMonoid (Measure α) :=
toOuterMeasure_injective.addCommMonoid toOuterMeasure zero_toOuterMeasure add_toOuterMeasure
fun _ _ => smul_toOuterMeasure _ _
/-- Coercion to function as an additive monoid homomorphism. -/
def coeAddHom {_ : MeasurableSpace α} : Measure α →+ Set α → ℝ≥0∞ where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
@[simp]
theorem coeAddHom_apply {_ : MeasurableSpace α} (μ : Measure α) : coeAddHom μ = ⇑μ := rfl
@[simp]
theorem coe_finset_sum {_m : MeasurableSpace α} (I : Finset ι) (μ : ι → Measure α) :
⇑(∑ i ∈ I, μ i) = ∑ i ∈ I, ⇑(μ i) := map_sum coeAddHom μ I
theorem finset_sum_apply {m : MeasurableSpace α} (I : Finset ι) (μ : ι → Measure α) (s : Set α) :
(∑ i ∈ I, μ i) s = ∑ i ∈ I, μ i s := by rw [coe_finset_sum, Finset.sum_apply]
instance instDistribMulAction [Monoid R] [DistribMulAction R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
{_ : MeasurableSpace α} : DistribMulAction R (Measure α) :=
Injective.distribMulAction ⟨⟨toOuterMeasure, zero_toOuterMeasure⟩, add_toOuterMeasure⟩
toOuterMeasure_injective smul_toOuterMeasure
instance instModule [Semiring R] [Module R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
{_ : MeasurableSpace α} : Module R (Measure α) :=
Injective.module R ⟨⟨toOuterMeasure, zero_toOuterMeasure⟩, add_toOuterMeasure⟩
toOuterMeasure_injective smul_toOuterMeasure
@[simp]
theorem coe_nnreal_smul_apply {_m : MeasurableSpace α} (c : ℝ≥0) (μ : Measure α) (s : Set α) :
(c • μ) s = c * μ s :=
rfl
@[simp]
theorem nnreal_smul_coe_apply {_m : MeasurableSpace α} (c : ℝ≥0) (μ : Measure α) (s : Set α) :
c • μ s = c * μ s := by
rfl
theorem ae_smul_measure {p : α → Prop} [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
(h : ∀ᵐ x ∂μ, p x) (c : R) : ∀ᵐ x ∂c • μ, p x :=
ae_iff.2 <| by rw [smul_apply, ae_iff.1 h, ← smul_one_smul ℝ≥0∞, smul_zero]
theorem ae_smul_measure_le [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞] (c : R) :
ae (c • μ) ≤ ae μ := fun _ h ↦ ae_smul_measure h c
section SMulWithZero
variable {R : Type*} [Zero R] [SMulWithZero R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
[NoZeroSMulDivisors R ℝ≥0∞] {c : R} {p : α → Prop}
lemma ae_smul_measure_iff (hc : c ≠ 0) {μ : Measure α} : (∀ᵐ x ∂c • μ, p x) ↔ ∀ᵐ x ∂μ, p x := by
simp [ae_iff, hc]
@[simp] lemma ae_smul_measure_eq (hc : c ≠ 0) (μ : Measure α) : ae (c • μ) = ae μ := by
ext; exact ae_smul_measure_iff hc
end SMulWithZero
theorem measure_eq_left_of_subset_of_measure_add_eq {s t : Set α} (h : (μ + ν) t ≠ ∞) (h' : s ⊆ t)
(h'' : (μ + ν) s = (μ + ν) t) : μ s = μ t := by
refine le_antisymm (measure_mono h') ?_
have : μ t + ν t ≤ μ s + ν t :=
calc
μ t + ν t = μ s + ν s := h''.symm
_ ≤ μ s + ν t := by gcongr
apply ENNReal.le_of_add_le_add_right _ this
exact ne_top_of_le_ne_top h (le_add_left le_rfl)
theorem measure_eq_right_of_subset_of_measure_add_eq {s t : Set α} (h : (μ + ν) t ≠ ∞) (h' : s ⊆ t)
(h'' : (μ + ν) s = (μ + ν) t) : ν s = ν t := by
rw [add_comm] at h'' h
exact measure_eq_left_of_subset_of_measure_add_eq h h' h''
theorem measure_toMeasurable_add_inter_left {s t : Set α} (hs : MeasurableSet s)
(ht : (μ + ν) t ≠ ∞) : μ (toMeasurable (μ + ν) t ∩ s) = μ (t ∩ s) := by
refine (measure_inter_eq_of_measure_eq hs ?_ (subset_toMeasurable _ _) ?_).symm
· refine
measure_eq_left_of_subset_of_measure_add_eq ?_ (subset_toMeasurable _ _)
(measure_toMeasurable t).symm
rwa [measure_toMeasurable t]
· simp only [not_or, ENNReal.add_eq_top, Pi.add_apply, Ne, coe_add] at ht
exact ht.1
theorem measure_toMeasurable_add_inter_right {s t : Set α} (hs : MeasurableSet s)
(ht : (μ + ν) t ≠ ∞) : ν (toMeasurable (μ + ν) t ∩ s) = ν (t ∩ s) := by
rw [add_comm] at ht ⊢
exact measure_toMeasurable_add_inter_left hs ht
/-! ### The complete lattice of measures -/
/-- Measures are partially ordered. -/
instance instPartialOrder {_ : MeasurableSpace α} : PartialOrder (Measure α) where
le m₁ m₂ := ∀ s, m₁ s ≤ m₂ s
le_refl _ _ := le_rfl
le_trans _ _ _ h₁ h₂ s := le_trans (h₁ s) (h₂ s)
le_antisymm _ _ h₁ h₂ := ext fun s _ => le_antisymm (h₁ s) (h₂ s)
theorem toOuterMeasure_le : μ₁.toOuterMeasure ≤ μ₂.toOuterMeasure ↔ μ₁ ≤ μ₂ := .rfl
theorem le_iff : μ₁ ≤ μ₂ ↔ ∀ s, MeasurableSet s → μ₁ s ≤ μ₂ s := outerMeasure_le_iff
theorem le_intro (h : ∀ s, MeasurableSet s → s.Nonempty → μ₁ s ≤ μ₂ s) : μ₁ ≤ μ₂ :=
le_iff.2 fun s hs ↦ s.eq_empty_or_nonempty.elim (by rintro rfl; simp) (h s hs)
theorem le_iff' : μ₁ ≤ μ₂ ↔ ∀ s, μ₁ s ≤ μ₂ s := .rfl
theorem lt_iff : μ < ν ↔ μ ≤ ν ∧ ∃ s, MeasurableSet s ∧ μ s < ν s :=
lt_iff_le_not_le.trans <|
and_congr Iff.rfl <| by simp only [le_iff, not_forall, not_le, exists_prop]
theorem lt_iff' : μ < ν ↔ μ ≤ ν ∧ ∃ s, μ s < ν s :=
lt_iff_le_not_le.trans <| and_congr Iff.rfl <| by simp only [le_iff', not_forall, not_le]
instance instAddLeftMono {_ : MeasurableSpace α} : AddLeftMono (Measure α) :=
⟨fun _ν _μ₁ _μ₂ hμ s => add_le_add_left (hμ s) _⟩
protected theorem le_add_left (h : μ ≤ ν) : μ ≤ ν' + ν := fun s => le_add_left (h s)
protected theorem le_add_right (h : μ ≤ ν) : μ ≤ ν + ν' := fun s => le_add_right (h s)
section sInf
variable {m : Set (Measure α)}
theorem sInf_caratheodory (s : Set α) (hs : MeasurableSet s) :
MeasurableSet[(sInf (toOuterMeasure '' m)).caratheodory] s := by
rw [OuterMeasure.sInf_eq_boundedBy_sInfGen]
refine OuterMeasure.boundedBy_caratheodory fun t => ?_
simp only [OuterMeasure.sInfGen, le_iInf_iff, forall_mem_image, measure_eq_iInf t,
coe_toOuterMeasure]
intro μ hμ u htu _hu
have hm : ∀ {s t}, s ⊆ t → OuterMeasure.sInfGen (toOuterMeasure '' m) s ≤ μ t := by
intro s t hst
rw [OuterMeasure.sInfGen_def, iInf_image]
exact iInf₂_le_of_le μ hμ <| measure_mono hst
rw [← measure_inter_add_diff u hs]
exact add_le_add (hm <| inter_subset_inter_left _ htu) (hm <| diff_subset_diff_left htu)
instance {_ : MeasurableSpace α} : InfSet (Measure α) :=
⟨fun m => (sInf (toOuterMeasure '' m)).toMeasure <| sInf_caratheodory⟩
theorem sInf_apply (hs : MeasurableSet s) : sInf m s = sInf (toOuterMeasure '' m) s :=
toMeasure_apply _ _ hs
private theorem measure_sInf_le (h : μ ∈ m) : sInf m ≤ μ :=
have : sInf (toOuterMeasure '' m) ≤ μ.toOuterMeasure := sInf_le (mem_image_of_mem _ h)
le_iff.2 fun s hs => by rw [sInf_apply hs]; exact this s
private theorem measure_le_sInf (h : ∀ μ' ∈ m, μ ≤ μ') : μ ≤ sInf m :=
have : μ.toOuterMeasure ≤ sInf (toOuterMeasure '' m) :=
le_sInf <| forall_mem_image.2 fun _ hμ ↦ toOuterMeasure_le.2 <| h _ hμ
le_iff.2 fun s hs => by rw [sInf_apply hs]; exact this s
instance instCompleteSemilatticeInf {_ : MeasurableSpace α} : CompleteSemilatticeInf (Measure α) :=
{ (by infer_instance : PartialOrder (Measure α)),
(by infer_instance : InfSet (Measure α)) with
sInf_le := fun _s _a => measure_sInf_le
le_sInf := fun _s _a => measure_le_sInf }
instance instCompleteLattice {_ : MeasurableSpace α} : CompleteLattice (Measure α) :=
{ completeLatticeOfCompleteSemilatticeInf (Measure α) with
top :=
{ toOuterMeasure := ⊤,
m_iUnion := by
intro f _ _
refine (measure_iUnion_le _).antisymm ?_
if hne : (⋃ i, f i).Nonempty then
rw [OuterMeasure.top_apply hne]
exact le_top
else
simp_all [Set.not_nonempty_iff_eq_empty]
trim_le := le_top },
le_top := fun _ => toOuterMeasure_le.mp le_top
bot := 0
bot_le := fun _a _s => bot_le }
end sInf
lemma inf_apply {s : Set α} (hs : MeasurableSet s) :
(μ ⊓ ν) s = sInf {m | ∃ t, m = μ (t ∩ s) + ν (tᶜ ∩ s)} := by
-- `(μ ⊓ ν) s` is defined as `⊓ (t : ℕ → Set α) (ht : s ⊆ ⋃ n, t n), ∑' n, μ (t n) ⊓ ν (t n)`
rw [← sInf_pair, Measure.sInf_apply hs, OuterMeasure.sInf_apply
(image_nonempty.2 <| insert_nonempty μ {ν})]
refine le_antisymm (le_sInf fun m ⟨t, ht₁⟩ ↦ ?_) (le_iInf₂ fun t' ht' ↦ ?_)
· subst ht₁
-- We first show `(μ ⊓ ν) s ≤ μ (t ∩ s) + ν (tᶜ ∩ s)` for any `t : Set α`
-- For this, define the sequence `t' : ℕ → Set α` where `t' 0 = t ∩ s`, `t' 1 = tᶜ ∩ s` and
-- `∅` otherwise. Then, we have by construction
-- `(μ ⊓ ν) s ≤ ∑' n, μ (t' n) ⊓ ν (t' n) ≤ μ (t' 0) + ν (t' 1) = μ (t ∩ s) + ν (tᶜ ∩ s)`.
set t' : ℕ → Set α := fun n ↦ if n = 0 then t ∩ s else if n = 1 then tᶜ ∩ s else ∅ with ht'
refine (iInf₂_le t' fun x hx ↦ ?_).trans ?_
· by_cases hxt : x ∈ t
· refine mem_iUnion.2 ⟨0, ?_⟩
simp [hx, hxt]
· refine mem_iUnion.2 ⟨1, ?_⟩
simp [hx, hxt]
· simp only [iInf_image, coe_toOuterMeasure, iInf_pair]
rw [tsum_eq_add_tsum_ite 0, tsum_eq_add_tsum_ite 1, if_neg zero_ne_one.symm,
ENNReal.summable.tsum_eq_zero_iff.2 _, add_zero]
· exact add_le_add (inf_le_left.trans <| by simp [ht']) (inf_le_right.trans <| by simp [ht'])
· simp only [ite_eq_left_iff]
intro n hn₁ hn₀
simp only [ht', if_neg hn₀, if_neg hn₁, measure_empty, iInf_pair, le_refl, inf_of_le_left]
· simp only [iInf_image, coe_toOuterMeasure, iInf_pair]
-- Conversely, fixing `t' : ℕ → Set α` such that `s ⊆ ⋃ n, t' n`, we construct `t : Set α`
-- for which `μ (t ∩ s) + ν (tᶜ ∩ s) ≤ ∑' n, μ (t' n) ⊓ ν (t' n)`.
-- Denoting `I := {n | μ (t' n) ≤ ν (t' n)}`, we set `t = ⋃ n ∈ I, t' n`.
-- Clearly `μ (t ∩ s) ≤ ∑' n ∈ I, μ (t' n)` and `ν (tᶜ ∩ s) ≤ ∑' n ∉ I, ν (t' n)`, so
-- `μ (t ∩ s) + ν (tᶜ ∩ s) ≤ ∑' n ∈ I, μ (t' n) + ∑' n ∉ I, ν (t' n)`
-- where the RHS equals `∑' n, μ (t' n) ⊓ ν (t' n)` by the choice of `I`.
set t := ⋃ n ∈ {k : ℕ | μ (t' k) ≤ ν (t' k)}, t' n with ht
suffices hadd : μ (t ∩ s) + ν (tᶜ ∩ s) ≤ ∑' n, μ (t' n) ⊓ ν (t' n) by
exact le_trans (sInf_le ⟨t, rfl⟩) hadd
have hle₁ : μ (t ∩ s) ≤ ∑' (n : {k | μ (t' k) ≤ ν (t' k)}), μ (t' n) :=
(measure_mono inter_subset_left).trans <| measure_biUnion_le _ (to_countable _) _
have hcap : tᶜ ∩ s ⊆ ⋃ n ∈ {k | ν (t' k) < μ (t' k)}, t' n := by
simp_rw [ht, compl_iUnion]
refine fun x ⟨hx₁, hx₂⟩ ↦ mem_iUnion₂.2 ?_
obtain ⟨i, hi⟩ := mem_iUnion.1 <| ht' hx₂
refine ⟨i, ?_, hi⟩
by_contra h
simp only [mem_setOf_eq, not_lt] at h
exact mem_iInter₂.1 hx₁ i h hi
have hle₂ : ν (tᶜ ∩ s) ≤ ∑' (n : {k | ν (t' k) < μ (t' k)}), ν (t' n) :=
(measure_mono hcap).trans (measure_biUnion_le ν (to_countable {k | ν (t' k) < μ (t' k)}) _)
refine (add_le_add hle₁ hle₂).trans ?_
have heq : {k | μ (t' k) ≤ ν (t' k)} ∪ {k | ν (t' k) < μ (t' k)} = univ := by
ext k; simp [le_or_lt]
conv in ∑' (n : ℕ), μ (t' n) ⊓ ν (t' n) => rw [← tsum_univ, ← heq]
rw [ENNReal.summable.tsum_union_disjoint (f := fun n ↦ μ (t' n) ⊓ ν (t' n)) ?_ ENNReal.summable]
· refine add_le_add (tsum_congr ?_).le (tsum_congr ?_).le
· rw [Subtype.forall]
intro n hn; simpa
· rw [Subtype.forall]
intro n hn
rw [mem_setOf_eq] at hn
simp [le_of_lt hn]
· rw [Set.disjoint_iff]
rintro k ⟨hk₁, hk₂⟩
rw [mem_setOf_eq] at hk₁ hk₂
exact False.elim <| hk₂.not_le hk₁
@[simp]
theorem _root_.MeasureTheory.OuterMeasure.toMeasure_top :
(⊤ : OuterMeasure α).toMeasure (by rw [OuterMeasure.top_caratheodory]; exact le_top) =
(⊤ : Measure α) :=
toOuterMeasure_toMeasure (μ := ⊤)
@[simp]
theorem toOuterMeasure_top {_ : MeasurableSpace α} :
(⊤ : Measure α).toOuterMeasure = (⊤ : OuterMeasure α) :=
rfl
@[simp]
theorem top_add : ⊤ + μ = ⊤ :=
top_unique <| Measure.le_add_right le_rfl
@[simp]
theorem add_top : μ + ⊤ = ⊤ :=
top_unique <| Measure.le_add_left le_rfl
protected theorem zero_le {_m0 : MeasurableSpace α} (μ : Measure α) : 0 ≤ μ :=
bot_le
theorem nonpos_iff_eq_zero' : μ ≤ 0 ↔ μ = 0 :=
μ.zero_le.le_iff_eq
@[simp]
theorem measure_univ_eq_zero : μ univ = 0 ↔ μ = 0 :=
⟨fun h => bot_unique fun s => (h ▸ measure_mono (subset_univ s) : μ s ≤ 0), fun h =>
h.symm ▸ rfl⟩
theorem measure_univ_ne_zero : μ univ ≠ 0 ↔ μ ≠ 0 :=
measure_univ_eq_zero.not
instance [NeZero μ] : NeZero (μ univ) := ⟨measure_univ_ne_zero.2 <| NeZero.ne μ⟩
@[simp]
theorem measure_univ_pos : 0 < μ univ ↔ μ ≠ 0 :=
pos_iff_ne_zero.trans measure_univ_ne_zero
lemma nonempty_of_neZero (μ : Measure α) [NeZero μ] : Nonempty α :=
(isEmpty_or_nonempty α).resolve_left fun h ↦ by
simpa [eq_empty_of_isEmpty] using NeZero.ne (μ univ)
section Sum
variable {f : ι → Measure α}
/-- Sum of an indexed family of measures. -/
noncomputable def sum (f : ι → Measure α) : Measure α :=
(OuterMeasure.sum fun i => (f i).toOuterMeasure).toMeasure <|
le_trans (le_iInf fun _ => le_toOuterMeasure_caratheodory _)
(OuterMeasure.le_sum_caratheodory _)
theorem le_sum_apply (f : ι → Measure α) (s : Set α) : ∑' i, f i s ≤ sum f s :=
le_toMeasure_apply _ _ _
@[simp]
theorem sum_apply (f : ι → Measure α) {s : Set α} (hs : MeasurableSet s) :
sum f s = ∑' i, f i s :=
toMeasure_apply _ _ hs
theorem sum_apply₀ (f : ι → Measure α) {s : Set α} (hs : NullMeasurableSet s (sum f)) :
sum f s = ∑' i, f i s := by
apply le_antisymm ?_ (le_sum_apply _ _)
rcases hs.exists_measurable_subset_ae_eq with ⟨t, ts, t_meas, ht⟩
calc
sum f s = sum f t := measure_congr ht.symm
_ = ∑' i, f i t := sum_apply _ t_meas
_ ≤ ∑' i, f i s := ENNReal.tsum_le_tsum fun i ↦ measure_mono ts
/-! For the next theorem, the countability assumption is necessary. For a counterexample, consider
an uncountable space, with a distinguished point `x₀`, and the sigma-algebra made of countable sets
not containing `x₀`, and their complements. All points but `x₀` are measurable.
Consider the sum of the Dirac masses at points different from `x₀`, and `s = {x₀}`. For any Dirac
mass `δ_x`, we have `δ_x (x₀) = 0`, so `∑' x, δ_x (x₀) = 0`. On the other hand, the measure
`sum δ_x` gives mass one to each point different from `x₀`, so it gives infinite mass to any
measurable set containing `x₀` (as such a set is uncountable), and by outer regularity one gets
`sum δ_x {x₀} = ∞`.
-/
theorem sum_apply_of_countable [Countable ι] (f : ι → Measure α) (s : Set α) :
sum f s = ∑' i, f i s := by
apply le_antisymm ?_ (le_sum_apply _ _)
rcases exists_measurable_superset_forall_eq f s with ⟨t, hst, htm, ht⟩
calc
sum f s ≤ sum f t := measure_mono hst
_ = ∑' i, f i t := sum_apply _ htm
_ = ∑' i, f i s := by simp [ht]
theorem le_sum (μ : ι → Measure α) (i : ι) : μ i ≤ sum μ :=
le_iff.2 fun s hs ↦ by simpa only [sum_apply μ hs] using ENNReal.le_tsum i
@[simp]
theorem sum_apply_eq_zero [Countable ι] {μ : ι → Measure α} {s : Set α} :
sum μ s = 0 ↔ ∀ i, μ i s = 0 := by
simp [sum_apply_of_countable]
theorem sum_apply_eq_zero' {μ : ι → Measure α} {s : Set α} (hs : MeasurableSet s) :
sum μ s = 0 ↔ ∀ i, μ i s = 0 := by simp [hs]
@[simp] lemma sum_eq_zero : sum f = 0 ↔ ∀ i, f i = 0 := by
simp +contextual [Measure.ext_iff, forall_swap (α := ι)]
@[simp]
lemma sum_zero : Measure.sum (fun (_ : ι) ↦ (0 : Measure α)) = 0 := by
ext s hs
simp [Measure.sum_apply _ hs]
theorem sum_sum {ι' : Type*} (μ : ι → ι' → Measure α) :
(sum fun n => sum (μ n)) = sum (fun (p : ι × ι') ↦ μ p.1 p.2) := by
ext1 s hs
simp [sum_apply _ hs, ENNReal.tsum_prod']
theorem sum_comm {ι' : Type*} (μ : ι → ι' → Measure α) :
(sum fun n => sum (μ n)) = sum fun m => sum fun n => μ n m := by
ext1 s hs
simp_rw [sum_apply _ hs]
rw [ENNReal.tsum_comm]
theorem ae_sum_iff [Countable ι] {μ : ι → Measure α} {p : α → Prop} :
(∀ᵐ x ∂sum μ, p x) ↔ ∀ i, ∀ᵐ x ∂μ i, p x :=
sum_apply_eq_zero
theorem ae_sum_iff' {μ : ι → Measure α} {p : α → Prop} (h : MeasurableSet { x | p x }) :
(∀ᵐ x ∂sum μ, p x) ↔ ∀ i, ∀ᵐ x ∂μ i, p x :=
sum_apply_eq_zero' h.compl
@[simp]
theorem sum_fintype [Fintype ι] (μ : ι → Measure α) : sum μ = ∑ i, μ i := by
ext1 s hs
simp only [sum_apply, finset_sum_apply, hs, tsum_fintype]
theorem sum_coe_finset (s : Finset ι) (μ : ι → Measure α) :
(sum fun i : s => μ i) = ∑ i ∈ s, μ i := by rw [sum_fintype, Finset.sum_coe_sort s μ]
@[simp]
theorem ae_sum_eq [Countable ι] (μ : ι → Measure α) : ae (sum μ) = ⨆ i, ae (μ i) :=
Filter.ext fun _ => ae_sum_iff.trans mem_iSup.symm
theorem sum_bool (f : Bool → Measure α) : sum f = f true + f false := by
rw [sum_fintype, Fintype.sum_bool]
theorem sum_cond (μ ν : Measure α) : (sum fun b => cond b μ ν) = μ + ν :=
sum_bool _
@[simp]
theorem sum_of_isEmpty [IsEmpty ι] (μ : ι → Measure α) : sum μ = 0 := by
rw [← measure_univ_eq_zero, sum_apply _ MeasurableSet.univ, tsum_empty]
theorem sum_add_sum_compl (s : Set ι) (μ : ι → Measure α) :
((sum fun i : s => μ i) + sum fun i : ↥sᶜ => μ i) = sum μ := by
ext1 t ht
simp only [add_apply, sum_apply _ ht]
exact ENNReal.summable.tsum_add_tsum_compl (f := fun i => μ i t) ENNReal.summable
theorem sum_congr {μ ν : ℕ → Measure α} (h : ∀ n, μ n = ν n) : sum μ = sum ν :=
congr_arg sum (funext h)
theorem sum_add_sum {ι : Type*} (μ ν : ι → Measure α) : sum μ + sum ν = sum fun n => μ n + ν n := by
ext1 s hs
simp only [add_apply, sum_apply _ hs, Pi.add_apply, coe_add,
ENNReal.summable.tsum_add ENNReal.summable]
@[simp] lemma sum_comp_equiv {ι ι' : Type*} (e : ι' ≃ ι) (m : ι → Measure α) :
sum (m ∘ e) = sum m := by
ext s hs
simpa [hs, sum_apply] using e.tsum_eq (fun n ↦ m n s)
@[simp] lemma sum_extend_zero {ι ι' : Type*} {f : ι → ι'} (hf : Injective f) (m : ι → Measure α) :
sum (Function.extend f m 0) = sum m := by
ext s hs
simp [*, Function.apply_extend (fun μ : Measure α ↦ μ s)]
end Sum
/-! ### The `cofinite` filter -/
/-- The filter of sets `s` such that `sᶜ` has finite measure. -/
def cofinite {m0 : MeasurableSpace α} (μ : Measure α) : Filter α :=
comk (μ · < ∞) (by simp) (fun _ ht _ hs ↦ (measure_mono hs).trans_lt ht) fun s hs t ht ↦
(measure_union_le s t).trans_lt <| ENNReal.add_lt_top.2 ⟨hs, ht⟩
theorem mem_cofinite : s ∈ μ.cofinite ↔ μ sᶜ < ∞ :=
Iff.rfl
theorem compl_mem_cofinite : sᶜ ∈ μ.cofinite ↔ μ s < ∞ := by rw [mem_cofinite, compl_compl]
theorem eventually_cofinite {p : α → Prop} : (∀ᶠ x in μ.cofinite, p x) ↔ μ { x | ¬p x } < ∞ :=
Iff.rfl
instance cofinite.instIsMeasurablyGenerated : IsMeasurablyGenerated μ.cofinite where
exists_measurable_subset s hs := by
refine ⟨(toMeasurable μ sᶜ)ᶜ, ?_, (measurableSet_toMeasurable _ _).compl, ?_⟩
· rwa [compl_mem_cofinite, measure_toMeasurable]
· rw [compl_subset_comm]
apply subset_toMeasurable
end Measure
open Measure
open MeasureTheory
protected theorem _root_.AEMeasurable.nullMeasurable {f : α → β} (h : AEMeasurable f μ) :
NullMeasurable f μ :=
let ⟨_g, hgm, hg⟩ := h; hgm.nullMeasurable.congr hg.symm
lemma _root_.AEMeasurable.nullMeasurableSet_preimage {f : α → β} {s : Set β}
(hf : AEMeasurable f μ) (hs : MeasurableSet s) : NullMeasurableSet (f ⁻¹' s) μ :=
hf.nullMeasurable hs
@[simp]
theorem ae_eq_bot : ae μ = ⊥ ↔ μ = 0 := by
rw [← empty_mem_iff_bot, mem_ae_iff, compl_empty, measure_univ_eq_zero]
@[simp]
theorem ae_neBot : (ae μ).NeBot ↔ μ ≠ 0 :=
neBot_iff.trans (not_congr ae_eq_bot)
instance Measure.ae.neBot [NeZero μ] : (ae μ).NeBot := ae_neBot.2 <| NeZero.ne μ
@[simp]
theorem ae_zero {_m0 : MeasurableSpace α} : ae (0 : Measure α) = ⊥ :=
ae_eq_bot.2 rfl
section Intervals
theorem biSup_measure_Iic [Preorder α] {s : Set α} (hsc : s.Countable)
(hst : ∀ x : α, ∃ y ∈ s, x ≤ y) (hdir : DirectedOn (· ≤ ·) s) :
⨆ x ∈ s, μ (Iic x) = μ univ := by
rw [← measure_biUnion_eq_iSup hsc]
· congr
simp only [← bex_def] at hst
exact iUnion₂_eq_univ_iff.2 hst
· exact directedOn_iff_directed.2 (hdir.directed_val.mono_comp _ fun x y => Iic_subset_Iic.2)
theorem tendsto_measure_Ico_atTop [Preorder α] [NoMaxOrder α]
[(atTop : Filter α).IsCountablyGenerated] (μ : Measure α) (a : α) :
Tendsto (fun x => μ (Ico a x)) atTop (𝓝 (μ (Ici a))) := by
rw [← iUnion_Ico_right]
exact tendsto_measure_iUnion_atTop (antitone_const.Ico monotone_id)
theorem tendsto_measure_Ioc_atBot [Preorder α] [NoMinOrder α]
[(atBot : Filter α).IsCountablyGenerated] (μ : Measure α) (a : α) :
Tendsto (fun x => μ (Ioc x a)) atBot (𝓝 (μ (Iic a))) := by
rw [← iUnion_Ioc_left]
exact tendsto_measure_iUnion_atBot (monotone_id.Ioc antitone_const)
theorem tendsto_measure_Iic_atTop [Preorder α] [(atTop : Filter α).IsCountablyGenerated]
(μ : Measure α) : Tendsto (fun x => μ (Iic x)) atTop (𝓝 (μ univ)) := by
rw [← iUnion_Iic]
exact tendsto_measure_iUnion_atTop monotone_Iic
theorem tendsto_measure_Ici_atBot [Preorder α] [(atBot : Filter α).IsCountablyGenerated]
(μ : Measure α) : Tendsto (fun x => μ (Ici x)) atBot (𝓝 (μ univ)) :=
tendsto_measure_Iic_atTop (α := αᵒᵈ) μ
variable [PartialOrder α] {a b : α}
theorem Iio_ae_eq_Iic' (ha : μ {a} = 0) : Iio a =ᵐ[μ] Iic a := by
rw [← Iic_diff_right, diff_ae_eq_self, measure_mono_null Set.inter_subset_right ha]
theorem Ioi_ae_eq_Ici' (ha : μ {a} = 0) : Ioi a =ᵐ[μ] Ici a :=
Iio_ae_eq_Iic' (α := αᵒᵈ) ha
theorem Ioo_ae_eq_Ioc' (hb : μ {b} = 0) : Ioo a b =ᵐ[μ] Ioc a b :=
(ae_eq_refl _).inter (Iio_ae_eq_Iic' hb)
theorem Ioc_ae_eq_Icc' (ha : μ {a} = 0) : Ioc a b =ᵐ[μ] Icc a b :=
(Ioi_ae_eq_Ici' ha).inter (ae_eq_refl _)
theorem Ioo_ae_eq_Ico' (ha : μ {a} = 0) : Ioo a b =ᵐ[μ] Ico a b :=
(Ioi_ae_eq_Ici' ha).inter (ae_eq_refl _)
theorem Ioo_ae_eq_Icc' (ha : μ {a} = 0) (hb : μ {b} = 0) : Ioo a b =ᵐ[μ] Icc a b :=
(Ioi_ae_eq_Ici' ha).inter (Iio_ae_eq_Iic' hb)
theorem Ico_ae_eq_Icc' (hb : μ {b} = 0) : Ico a b =ᵐ[μ] Icc a b :=
(ae_eq_refl _).inter (Iio_ae_eq_Iic' hb)
theorem Ico_ae_eq_Ioc' (ha : μ {a} = 0) (hb : μ {b} = 0) : Ico a b =ᵐ[μ] Ioc a b :=
(Ioo_ae_eq_Ico' ha).symm.trans (Ioo_ae_eq_Ioc' hb)
end Intervals
end
end MeasureTheory
end
| Mathlib/MeasureTheory/Measure/MeasureSpace.lean | 2,116 | 2,117 | |
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Data.Nat.Choose.Basic
import Mathlib.Data.Nat.Factorial.Cast
/-!
# Cast of binomial coefficients
This file allows calculating the binomial coefficient `a.choose b` as an element of a division ring
of characteristic `0`.
-/
open Nat
variable (K : Type*)
namespace Nat
section DivisionSemiring
variable [DivisionSemiring K] [CharZero K]
| theorem cast_choose {a b : ℕ} (h : a ≤ b) : (b.choose a : K) = b ! / (a ! * (b - a)!) := by
have : ∀ {n : ℕ}, (n ! : K) ≠ 0 := Nat.cast_ne_zero.2 (factorial_ne_zero _)
rw [eq_div_iff_mul_eq (mul_ne_zero this this)]
rw_mod_cast [← mul_assoc, choose_mul_factorial_mul_factorial h]
| Mathlib/Data/Nat/Choose/Cast.lean | 25 | 28 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Morenikeji Neri
-/
import Mathlib.Algebra.EuclideanDomain.Basic
import Mathlib.Algebra.EuclideanDomain.Field
import Mathlib.Algebra.GCDMonoid.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.RingTheory.Ideal.Nonunits
import Mathlib.RingTheory.Noetherian.UniqueFactorizationDomain
/-!
# Principal ideal rings, principal ideal domains, and Bézout rings
A principal ideal ring (PIR) is a ring in which all left ideals are principal. A
principal ideal domain (PID) is an integral domain which is a principal ideal ring.
The definition of `IsPrincipalIdealRing` can be found in `Mathlib.RingTheory.Ideal.Span`.
# Main definitions
Note that for principal ideal domains, one should use
`[IsDomain R] [IsPrincipalIdealRing R]`. There is no explicit definition of a PID.
Theorems about PID's are in the `PrincipalIdealRing` namespace.
- `IsBezout`: the predicate saying that every finitely generated left ideal is principal.
- `generator`: a generator of a principal ideal (or more generally submodule)
- `to_uniqueFactorizationMonoid`: a PID is a unique factorization domain
# Main results
- `Ideal.IsPrime.to_maximal_ideal`: a non-zero prime ideal in a PID is maximal.
- `EuclideanDomain.to_principal_ideal_domain` : a Euclidean domain is a PID.
- `IsBezout.nonemptyGCDMonoid`: Every Bézout domain is a GCD domain.
-/
universe u v
variable {R : Type u} {M : Type v}
open Set Function
open Submodule
section
variable [Semiring R] [AddCommGroup M] [Module R M]
instance bot_isPrincipal : (⊥ : Submodule R M).IsPrincipal :=
⟨⟨0, by simp⟩⟩
instance top_isPrincipal : (⊤ : Submodule R R).IsPrincipal :=
⟨⟨1, Ideal.span_singleton_one.symm⟩⟩
variable (R)
/-- A Bézout ring is a ring whose finitely generated ideals are principal. -/
class IsBezout : Prop where
/-- Any finitely generated ideal is principal. -/
isPrincipal_of_FG : ∀ I : Ideal R, I.FG → I.IsPrincipal
instance (priority := 100) IsBezout.of_isPrincipalIdealRing [IsPrincipalIdealRing R] : IsBezout R :=
⟨fun I _ => IsPrincipalIdealRing.principal I⟩
instance (priority := 100) DivisionRing.isPrincipalIdealRing (K : Type u) [DivisionRing K] :
IsPrincipalIdealRing K where
principal S := by
rcases Ideal.eq_bot_or_top S with (rfl | rfl)
· apply bot_isPrincipal
· apply top_isPrincipal
end
namespace Submodule.IsPrincipal
variable [AddCommMonoid M]
section Semiring
variable [Semiring R] [Module R M]
/-- `generator I`, if `I` is a principal submodule, is an `x ∈ M` such that `span R {x} = I` -/
noncomputable def generator (S : Submodule R M) [S.IsPrincipal] : M :=
Classical.choose (principal S)
theorem span_singleton_generator (S : Submodule R M) [S.IsPrincipal] : span R {generator S} = S :=
Eq.symm (Classical.choose_spec (principal S))
@[simp]
theorem _root_.Ideal.span_singleton_generator (I : Ideal R) [I.IsPrincipal] :
Ideal.span ({generator I} : Set R) = I :=
Eq.symm (Classical.choose_spec (principal I))
@[simp]
theorem generator_mem (S : Submodule R M) [S.IsPrincipal] : generator S ∈ S := by
have : generator S ∈ span R {generator S} := subset_span (mem_singleton _)
convert this
exact span_singleton_generator S |>.symm
theorem mem_iff_eq_smul_generator (S : Submodule R M) [S.IsPrincipal] {x : M} :
x ∈ S ↔ ∃ s : R, x = s • generator S := by
simp_rw [@eq_comm _ x, ← mem_span_singleton, span_singleton_generator]
theorem eq_bot_iff_generator_eq_zero (S : Submodule R M) [S.IsPrincipal] :
S = ⊥ ↔ generator S = 0 := by rw [← @span_singleton_eq_bot R M, span_singleton_generator]
protected lemma fg {S : Submodule R M} (h : S.IsPrincipal) : S.FG :=
⟨{h.generator}, by simp only [Finset.coe_singleton, span_singleton_generator]⟩
-- See note [lower instance priority]
instance (priority := 100) _root_.PrincipalIdealRing.isNoetherianRing [IsPrincipalIdealRing R] :
IsNoetherianRing R where
noetherian S := (IsPrincipalIdealRing.principal S).fg
-- See note [lower instance priority]
instance (priority := 100) _root_.IsPrincipalIdealRing.of_isNoetherianRing_of_isBezout
[IsNoetherianRing R] [IsBezout R] : IsPrincipalIdealRing R where
principal S := IsBezout.isPrincipal_of_FG S (IsNoetherian.noetherian S)
end Semiring
section CommRing
variable [CommRing R] [Module R M]
theorem associated_generator_span_self [IsPrincipalIdealRing R] [IsDomain R] (r : R) :
Associated (generator <| Ideal.span {r}) r := by
rw [← Ideal.span_singleton_eq_span_singleton]
exact Ideal.span_singleton_generator _
theorem mem_iff_generator_dvd (S : Ideal R) [S.IsPrincipal] {x : R} : x ∈ S ↔ generator S ∣ x :=
(mem_iff_eq_smul_generator S).trans (exists_congr fun a => by simp only [mul_comm, smul_eq_mul])
theorem prime_generator_of_isPrime (S : Ideal R) [S.IsPrincipal] [is_prime : S.IsPrime]
(ne_bot : S ≠ ⊥) : Prime (generator S) :=
⟨fun h => ne_bot ((eq_bot_iff_generator_eq_zero S).2 h), fun h =>
is_prime.ne_top (S.eq_top_of_isUnit_mem (generator_mem S) h), fun _ _ => by
simpa only [← mem_iff_generator_dvd S] using is_prime.2⟩
-- Note that the converse may not hold if `ϕ` is not injective.
theorem generator_map_dvd_of_mem {N : Submodule R M} (ϕ : M →ₗ[R] R) [(N.map ϕ).IsPrincipal] {x : M}
(hx : x ∈ N) : generator (N.map ϕ) ∣ ϕ x := by
rw [← mem_iff_generator_dvd, Submodule.mem_map]
exact ⟨x, hx, rfl⟩
-- Note that the converse may not hold if `ϕ` is not injective.
theorem generator_submoduleImage_dvd_of_mem {N O : Submodule R M} (hNO : N ≤ O) (ϕ : O →ₗ[R] R)
[(ϕ.submoduleImage N).IsPrincipal] {x : M} (hx : x ∈ N) :
generator (ϕ.submoduleImage N) ∣ ϕ ⟨x, hNO hx⟩ := by
rw [← mem_iff_generator_dvd, LinearMap.mem_submoduleImage_of_le hNO]
exact ⟨x, hx, rfl⟩
end CommRing
end Submodule.IsPrincipal
namespace IsBezout
section
variable [Ring R]
instance span_pair_isPrincipal [IsBezout R] (x y : R) : (Ideal.span {x, y}).IsPrincipal := by
classical exact isPrincipal_of_FG (Ideal.span {x, y}) ⟨{x, y}, by simp⟩
variable (x y : R) [(Ideal.span {x, y}).IsPrincipal]
/-- A choice of gcd of two elements in a Bézout domain.
Note that the choice is usually not unique. -/
noncomputable def gcd : R := Submodule.IsPrincipal.generator (Ideal.span {x, y})
theorem span_gcd : Ideal.span {gcd x y} = Ideal.span {x, y} :=
Ideal.span_singleton_generator _
end
variable [CommRing R] (x y z : R) [(Ideal.span {x, y}).IsPrincipal]
theorem gcd_dvd_left : gcd x y ∣ x :=
(Submodule.IsPrincipal.mem_iff_generator_dvd _).mp (Ideal.subset_span (by simp))
theorem gcd_dvd_right : gcd x y ∣ y :=
(Submodule.IsPrincipal.mem_iff_generator_dvd _).mp (Ideal.subset_span (by simp))
variable {x y z} in
theorem dvd_gcd (hx : z ∣ x) (hy : z ∣ y) : z ∣ gcd x y := by
rw [← Ideal.span_singleton_le_span_singleton] at hx hy ⊢
rw [span_gcd, Ideal.span_insert, sup_le_iff]
exact ⟨hx, hy⟩
theorem gcd_eq_sum : ∃ a b : R, a * x + b * y = gcd x y :=
Ideal.mem_span_pair.mp (by rw [← span_gcd]; apply Ideal.subset_span; simp)
variable {x y}
theorem _root_.IsRelPrime.isCoprime (h : IsRelPrime x y) : IsCoprime x y := by
rw [← Ideal.isCoprime_span_singleton_iff, Ideal.isCoprime_iff_sup_eq, ← Ideal.span_union,
Set.singleton_union, ← span_gcd, Ideal.span_singleton_eq_top]
exact h (gcd_dvd_left x y) (gcd_dvd_right x y)
theorem _root_.isRelPrime_iff_isCoprime : IsRelPrime x y ↔ IsCoprime x y :=
⟨IsRelPrime.isCoprime, IsCoprime.isRelPrime⟩
variable (R)
/-- Any Bézout domain is a GCD domain. This is not an instance since `GCDMonoid` contains data,
and this might not be how we would like to construct it. -/
noncomputable def toGCDDomain [IsBezout R] [IsDomain R] [DecidableEq R] : GCDMonoid R :=
gcdMonoidOfGCD (gcd · ·) (gcd_dvd_left · ·) (gcd_dvd_right · ·) dvd_gcd
instance nonemptyGCDMonoid [IsBezout R] [IsDomain R] : Nonempty (GCDMonoid R) := by
classical exact ⟨toGCDDomain R⟩
theorem associated_gcd_gcd [IsDomain R] [GCDMonoid R] :
Associated (IsBezout.gcd x y) (GCDMonoid.gcd x y) :=
gcd_greatest_associated (gcd_dvd_left _ _ ) (gcd_dvd_right _ _) (fun _ => dvd_gcd)
end IsBezout
namespace IsPrime
open Submodule.IsPrincipal Ideal
-- TODO -- for a non-ID one could perhaps prove that if p < q are prime then q maximal;
-- 0 isn't prime in a non-ID PIR but the Krull dimension is still <= 1.
-- The below result follows from this, but we could also use the below result to
-- prove this (quotient out by p).
theorem to_maximal_ideal [CommRing R] [IsDomain R] [IsPrincipalIdealRing R] {S : Ideal R}
[hpi : IsPrime S] (hS : S ≠ ⊥) : IsMaximal S :=
isMaximal_iff.2
⟨(ne_top_iff_one S).1 hpi.1, by
intro T x hST hxS hxT
obtain ⟨z, hz⟩ := (mem_iff_generator_dvd _).1 (hST <| generator_mem S)
cases hpi.mem_or_mem (show generator T * z ∈ S from hz ▸ generator_mem S) with
| inl h =>
have hTS : T ≤ S := by
rwa [← T.span_singleton_generator, Ideal.span_le, singleton_subset_iff]
exact (hxS <| hTS hxT).elim
| inr h =>
obtain ⟨y, hy⟩ := (mem_iff_generator_dvd _).1 h
have : generator S ≠ 0 := mt (eq_bot_iff_generator_eq_zero _).2 hS
rw [← mul_one (generator S), hy, mul_left_comm, mul_right_inj' this] at hz
exact hz.symm ▸ T.mul_mem_right _ (generator_mem T)⟩
end IsPrime
section
open EuclideanDomain
variable [EuclideanDomain R]
theorem mod_mem_iff {S : Ideal R} {x y : R} (hy : y ∈ S) : x % y ∈ S ↔ x ∈ S :=
⟨fun hxy => div_add_mod x y ▸ S.add_mem (S.mul_mem_right _ hy) hxy, fun hx =>
(mod_eq_sub_mul_div x y).symm ▸ S.sub_mem hx (S.mul_mem_right _ hy)⟩
-- see Note [lower instance priority]
instance (priority := 100) EuclideanDomain.to_principal_ideal_domain : IsPrincipalIdealRing R where
principal S := by classical exact
⟨if h : { x : R | x ∈ S ∧ x ≠ 0 }.Nonempty then
have wf : WellFounded (EuclideanDomain.r : R → R → Prop) := EuclideanDomain.r_wellFounded
have hmin : WellFounded.min wf { x : R | x ∈ S ∧ x ≠ 0 } h ∈ S ∧
WellFounded.min wf { x : R | x ∈ S ∧ x ≠ 0 } h ≠ 0 :=
WellFounded.min_mem wf { x : R | x ∈ S ∧ x ≠ 0 } h
⟨WellFounded.min wf { x : R | x ∈ S ∧ x ≠ 0 } h,
Submodule.ext fun x => ⟨fun hx =>
div_add_mod x (WellFounded.min wf { x : R | x ∈ S ∧ x ≠ 0 } h) ▸
(Ideal.mem_span_singleton.2 <| dvd_add (dvd_mul_right _ _) <| by
have : x % WellFounded.min wf { x : R | x ∈ S ∧ x ≠ 0 } h ∉
{ x : R | x ∈ S ∧ x ≠ 0 } :=
fun h₁ => WellFounded.not_lt_min wf _ h h₁ (mod_lt x hmin.2)
have : x % WellFounded.min wf { x : R | x ∈ S ∧ x ≠ 0 } h = 0 := by
simp only [not_and_or, Set.mem_setOf_eq, not_ne_iff] at this
exact this.neg_resolve_left <| (mod_mem_iff hmin.1).2 hx
simp [*]),
fun hx =>
let ⟨y, hy⟩ := Ideal.mem_span_singleton.1 hx
hy.symm ▸ S.mul_mem_right _ hmin.1⟩⟩
else ⟨0, Submodule.ext fun a => by
rw [← @Submodule.bot_coe R R _ _ _, span_eq, Submodule.mem_bot]
exact ⟨fun haS => by_contra fun ha0 => h ⟨a, ⟨haS, ha0⟩⟩,
fun h₁ => h₁.symm ▸ S.zero_mem⟩⟩⟩
end
theorem IsField.isPrincipalIdealRing {R : Type*} [Ring R] (h : IsField R) :
IsPrincipalIdealRing R :=
@EuclideanDomain.to_principal_ideal_domain R (@Field.toEuclideanDomain R h.toField)
namespace PrincipalIdealRing
open IsPrincipalIdealRing
theorem isMaximal_of_irreducible [CommSemiring R] [IsPrincipalIdealRing R] {p : R}
(hp : Irreducible p) : Ideal.IsMaximal (span R ({p} : Set R)) :=
⟨⟨mt Ideal.span_singleton_eq_top.1 hp.1, fun I hI => by
rcases principal I with ⟨a, rfl⟩
rw [Ideal.submodule_span_eq, Ideal.span_singleton_eq_top]
rcases Ideal.span_singleton_le_span_singleton.1 (le_of_lt hI) with ⟨b, rfl⟩
refine (of_irreducible_mul hp).resolve_right (mt (fun hb => ?_) (not_le_of_lt hI))
rw [Ideal.submodule_span_eq, Ideal.submodule_span_eq,
Ideal.span_singleton_le_span_singleton, IsUnit.mul_right_dvd hb]⟩⟩
variable [CommRing R] [IsDomain R] [IsPrincipalIdealRing R]
section
open scoped Classical in
/-- `factors a` is a multiset of irreducible elements whose product is `a`, up to units -/
noncomputable def factors (a : R) : Multiset R :=
if h : a = 0 then ∅ else Classical.choose (WfDvdMonoid.exists_factors a h)
theorem factors_spec (a : R) (h : a ≠ 0) :
(∀ b ∈ factors a, Irreducible b) ∧ Associated (factors a).prod a := by
unfold factors; rw [dif_neg h]
exact Classical.choose_spec (WfDvdMonoid.exists_factors a h)
theorem ne_zero_of_mem_factors {R : Type v} [CommRing R] [IsDomain R] [IsPrincipalIdealRing R]
{a b : R} (ha : a ≠ 0) (hb : b ∈ factors a) : b ≠ 0 :=
Irreducible.ne_zero ((factors_spec a ha).1 b hb)
theorem mem_submonoid_of_factors_subset_of_units_subset (s : Submonoid R) {a : R} (ha : a ≠ 0)
(hfac : ∀ b ∈ factors a, b ∈ s) (hunit : ∀ c : Rˣ, (c : R) ∈ s) : a ∈ s := by
rcases (factors_spec a ha).2 with ⟨c, hc⟩
rw [← hc]
exact mul_mem (multiset_prod_mem _ hfac) (hunit _)
/-- If a `RingHom` maps all units and all factors of an element `a` into a submonoid `s`, then it
also maps `a` into that submonoid. -/
theorem ringHom_mem_submonoid_of_factors_subset_of_units_subset {R S : Type*} [CommRing R]
[IsDomain R] [IsPrincipalIdealRing R] [NonAssocSemiring S] (f : R →+* S) (s : Submonoid S)
(a : R) (ha : a ≠ 0) (h : ∀ b ∈ factors a, f b ∈ s) (hf : ∀ c : Rˣ, f c ∈ s) : f a ∈ s :=
mem_submonoid_of_factors_subset_of_units_subset (s.comap f.toMonoidHom) ha h hf
-- see Note [lower instance priority]
/-- A principal ideal domain has unique factorization -/
instance (priority := 100) to_uniqueFactorizationMonoid : UniqueFactorizationMonoid R :=
{ (IsNoetherianRing.wfDvdMonoid : WfDvdMonoid R) with
irreducible_iff_prime := irreducible_iff_prime }
end
end PrincipalIdealRing
section Surjective
open Submodule
variable {S N F : Type*} [Ring R] [AddCommGroup M] [AddCommGroup N] [Ring S]
variable [Module R M] [Module R N] [FunLike F R S] [RingHomClass F R S]
theorem Submodule.IsPrincipal.map (f : M →ₗ[R] N) {S : Submodule R M}
(hI : IsPrincipal S) : IsPrincipal (map f S) :=
⟨⟨f (IsPrincipal.generator S), by
rw [← Set.image_singleton, ← map_span, span_singleton_generator]⟩⟩
theorem Submodule.IsPrincipal.of_comap (f : M →ₗ[R] N) (hf : Function.Surjective f)
(S : Submodule R N) [hI : IsPrincipal (S.comap f)] : IsPrincipal S := by
rw [← Submodule.map_comap_eq_of_surjective hf S]
exact hI.map f
theorem Submodule.IsPrincipal.map_ringHom (f : F) {I : Ideal R}
(hI : IsPrincipal I) : IsPrincipal (Ideal.map f I) :=
⟨⟨f (IsPrincipal.generator I), by
rw [Ideal.submodule_span_eq, ← Set.image_singleton, ← Ideal.map_span,
Ideal.span_singleton_generator]⟩⟩
theorem Ideal.IsPrincipal.of_comap (f : F) (hf : Function.Surjective f) (I : Ideal S)
[hI : IsPrincipal (I.comap f)] : IsPrincipal I := by
rw [← map_comap_of_surjective f hf I]
exact hI.map_ringHom f
/-- The surjective image of a principal ideal ring is again a principal ideal ring. -/
theorem IsPrincipalIdealRing.of_surjective [IsPrincipalIdealRing R] (f : F)
(hf : Function.Surjective f) : IsPrincipalIdealRing S :=
⟨fun I => Ideal.IsPrincipal.of_comap f hf I⟩
end Surjective
section
open Ideal
variable [CommRing R]
section Bezout
variable [IsBezout R]
theorem isCoprime_of_dvd (x y : R) (nonzero : ¬(x = 0 ∧ y = 0))
(H : ∀ z ∈ nonunits R, z ≠ 0 → z ∣ x → ¬z ∣ y) : IsCoprime x y :=
(isRelPrime_of_no_nonunits_factors nonzero H).isCoprime
theorem dvd_or_isCoprime (x y : R) (h : Irreducible x) : x ∣ y ∨ IsCoprime x y :=
h.dvd_or_isRelPrime.imp_right IsRelPrime.isCoprime
|
@[deprecated (since := "2025-01-23")] alias dvd_or_coprime := dvd_or_isCoprime
/-- See also `Irreducible.isRelPrime_iff_not_dvd`. -/
theorem Irreducible.coprime_iff_not_dvd {p n : R} (hp : Irreducible p) :
| Mathlib/RingTheory/PrincipalIdealDomain.lean | 399 | 403 |
/-
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.Lemmas
import Mathlib.Analysis.Convex.PartitionOfUnity
/-!
# 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
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]
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)
/-- 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)
/-- 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 | 87 | 93 |
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Sébastien Gouëzel
-/
import Mathlib.Analysis.NormedSpace.IndicatorFunction
import Mathlib.Data.Fintype.Order
import Mathlib.MeasureTheory.Function.AEEqFun
import Mathlib.MeasureTheory.Function.LpSeminorm.Defs
import Mathlib.MeasureTheory.Function.SpecialFunctions.Basic
import Mathlib.MeasureTheory.Integral.Lebesgue.Countable
import Mathlib.MeasureTheory.Integral.Lebesgue.Sub
/-!
# Basic theorems about ℒp space
-/
noncomputable section
open TopologicalSpace MeasureTheory Filter
open scoped NNReal ENNReal Topology ComplexConjugate
variable {α ε ε' E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G] [ENorm ε] [ENorm ε']
namespace MeasureTheory
section Lp
section Top
theorem MemLp.eLpNorm_lt_top [TopologicalSpace ε] {f : α → ε} (hfp : MemLp f p μ) :
eLpNorm f p μ < ∞ :=
hfp.2
@[deprecated (since := "2025-02-21")]
alias Memℒp.eLpNorm_lt_top := MemLp.eLpNorm_lt_top
theorem MemLp.eLpNorm_ne_top [TopologicalSpace ε] {f : α → ε} (hfp : MemLp f p μ) :
eLpNorm f p μ ≠ ∞ :=
ne_of_lt hfp.2
@[deprecated (since := "2025-02-21")]
alias Memℒp.eLpNorm_ne_top := MemLp.eLpNorm_ne_top
theorem lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top {f : α → ε} (hq0_lt : 0 < q)
(hfq : eLpNorm' f q μ < ∞) : ∫⁻ a, ‖f a‖ₑ ^ q ∂μ < ∞ := by
rw [lintegral_rpow_enorm_eq_rpow_eLpNorm' hq0_lt]
exact ENNReal.rpow_lt_top_of_nonneg (le_of_lt hq0_lt) (ne_of_lt hfq)
@[deprecated (since := "2025-01-17")]
alias lintegral_rpow_nnnorm_lt_top_of_eLpNorm'_lt_top' :=
lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top
theorem lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top {f : α → ε} (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) (hfp : eLpNorm f p μ < ∞) : ∫⁻ a, ‖f a‖ₑ ^ p.toReal ∂μ < ∞ := by
apply lintegral_rpow_enorm_lt_top_of_eLpNorm'_lt_top
· exact ENNReal.toReal_pos hp_ne_zero hp_ne_top
· simpa [eLpNorm_eq_eLpNorm' hp_ne_zero hp_ne_top] using hfp
@[deprecated (since := "2025-01-17")]
alias lintegral_rpow_nnnorm_lt_top_of_eLpNorm_lt_top :=
lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top
theorem eLpNorm_lt_top_iff_lintegral_rpow_enorm_lt_top {f : α → ε} (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) : eLpNorm f p μ < ∞ ↔ ∫⁻ a, (‖f a‖ₑ) ^ p.toReal ∂μ < ∞ :=
⟨lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top hp_ne_zero hp_ne_top, by
intro h
have hp' := ENNReal.toReal_pos hp_ne_zero hp_ne_top
have : 0 < 1 / p.toReal := div_pos zero_lt_one hp'
simpa [eLpNorm_eq_lintegral_rpow_enorm hp_ne_zero hp_ne_top] using
ENNReal.rpow_lt_top_of_nonneg (le_of_lt this) (ne_of_lt h)⟩
@[deprecated (since := "2025-02-04")] alias
eLpNorm_lt_top_iff_lintegral_rpow_nnnorm_lt_top := eLpNorm_lt_top_iff_lintegral_rpow_enorm_lt_top
end Top
section Zero
@[simp]
theorem eLpNorm'_exponent_zero {f : α → ε} : eLpNorm' f 0 μ = 1 := by
rw [eLpNorm', div_zero, ENNReal.rpow_zero]
@[simp]
theorem eLpNorm_exponent_zero {f : α → ε} : eLpNorm f 0 μ = 0 := by simp [eLpNorm]
@[simp]
theorem memLp_zero_iff_aestronglyMeasurable [TopologicalSpace ε] {f : α → ε} :
MemLp f 0 μ ↔ AEStronglyMeasurable f μ := by simp [MemLp, eLpNorm_exponent_zero]
@[deprecated (since := "2025-02-21")]
alias memℒp_zero_iff_aestronglyMeasurable := memLp_zero_iff_aestronglyMeasurable
section ENormedAddMonoid
variable {ε : Type*} [TopologicalSpace ε] [ENormedAddMonoid ε]
@[simp]
theorem eLpNorm'_zero (hp0_lt : 0 < q) : eLpNorm' (0 : α → ε) q μ = 0 := by
simp [eLpNorm'_eq_lintegral_enorm, hp0_lt]
@[simp]
theorem eLpNorm'_zero' (hq0_ne : q ≠ 0) (hμ : μ ≠ 0) : eLpNorm' (0 : α → ε) q μ = 0 := by
rcases le_or_lt 0 q with hq0 | hq_neg
· exact eLpNorm'_zero (lt_of_le_of_ne hq0 hq0_ne.symm)
· simp [eLpNorm'_eq_lintegral_enorm, ENNReal.rpow_eq_zero_iff, hμ, hq_neg]
@[simp]
theorem eLpNormEssSup_zero : eLpNormEssSup (0 : α → ε) μ = 0 := by
simp [eLpNormEssSup, ← bot_eq_zero', essSup_const_bot]
@[simp]
theorem eLpNorm_zero : eLpNorm (0 : α → ε) p μ = 0 := by
by_cases h0 : p = 0
· simp [h0]
by_cases h_top : p = ∞
· simp only [h_top, eLpNorm_exponent_top, eLpNormEssSup_zero]
rw [← Ne] at h0
simp [eLpNorm_eq_eLpNorm' h0 h_top, ENNReal.toReal_pos h0 h_top]
@[simp]
theorem eLpNorm_zero' : eLpNorm (fun _ : α => (0 : ε)) p μ = 0 := eLpNorm_zero
@[simp] lemma MemLp.zero : MemLp (0 : α → ε) p μ :=
⟨aestronglyMeasurable_zero, by rw [eLpNorm_zero]; exact ENNReal.coe_lt_top⟩
@[simp] lemma MemLp.zero' : MemLp (fun _ : α => (0 : ε)) p μ := MemLp.zero
@[deprecated (since := "2025-02-21")]
alias Memℒp.zero' := MemLp.zero'
@[deprecated (since := "2025-01-21")] alias zero_memℒp := MemLp.zero
@[deprecated (since := "2025-01-21")] alias zero_mem_ℒp := MemLp.zero'
variable [MeasurableSpace α]
theorem eLpNorm'_measure_zero_of_pos {f : α → ε} (hq_pos : 0 < q) :
eLpNorm' f q (0 : Measure α) = 0 := by simp [eLpNorm', hq_pos]
theorem eLpNorm'_measure_zero_of_exponent_zero {f : α → ε} : eLpNorm' f 0 (0 : Measure α) = 1 := by
simp [eLpNorm']
theorem eLpNorm'_measure_zero_of_neg {f : α → ε} (hq_neg : q < 0) :
eLpNorm' f q (0 : Measure α) = ∞ := by simp [eLpNorm', hq_neg]
end ENormedAddMonoid
@[simp]
theorem eLpNormEssSup_measure_zero {f : α → ε} : eLpNormEssSup f (0 : Measure α) = 0 := by
simp [eLpNormEssSup]
@[simp]
theorem eLpNorm_measure_zero {f : α → ε} : eLpNorm f p (0 : Measure α) = 0 := by
by_cases h0 : p = 0
· simp [h0]
by_cases h_top : p = ∞
· simp [h_top]
rw [← Ne] at h0
simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm', ENNReal.toReal_pos h0 h_top]
section ContinuousENorm
variable {ε : Type*} [TopologicalSpace ε] [ContinuousENorm ε]
@[simp] lemma memLp_measure_zero {f : α → ε} : MemLp f p (0 : Measure α) := by
simp [MemLp]
@[deprecated (since := "2025-02-21")]
alias memℒp_measure_zero := memLp_measure_zero
end ContinuousENorm
end Zero
section Neg
@[simp]
theorem eLpNorm'_neg (f : α → F) (q : ℝ) (μ : Measure α) : eLpNorm' (-f) q μ = eLpNorm' f q μ := by
simp [eLpNorm'_eq_lintegral_enorm]
@[simp]
theorem eLpNorm_neg (f : α → F) (p : ℝ≥0∞) (μ : Measure α) : eLpNorm (-f) p μ = eLpNorm f p μ := by
by_cases h0 : p = 0
· simp [h0]
by_cases h_top : p = ∞
· simp [h_top, eLpNormEssSup_eq_essSup_enorm]
simp [eLpNorm_eq_eLpNorm' h0 h_top]
lemma eLpNorm_sub_comm (f g : α → E) (p : ℝ≥0∞) (μ : Measure α) :
eLpNorm (f - g) p μ = eLpNorm (g - f) p μ := by simp [← eLpNorm_neg (f := f - g)]
theorem MemLp.neg {f : α → E} (hf : MemLp f p μ) : MemLp (-f) p μ :=
⟨AEStronglyMeasurable.neg hf.1, by simp [hf.right]⟩
@[deprecated (since := "2025-02-21")]
alias Memℒp.neg := MemLp.neg
theorem memLp_neg_iff {f : α → E} : MemLp (-f) p μ ↔ MemLp f p μ :=
⟨fun h => neg_neg f ▸ h.neg, MemLp.neg⟩
@[deprecated (since := "2025-02-21")]
alias memℒp_neg_iff := memLp_neg_iff
end Neg
section Const
variable {ε' ε'' : Type*} [TopologicalSpace ε'] [ContinuousENorm ε']
[TopologicalSpace ε''] [ENormedAddMonoid ε'']
theorem eLpNorm'_const (c : ε) (hq_pos : 0 < q) :
eLpNorm' (fun _ : α => c) q μ = ‖c‖ₑ * μ Set.univ ^ (1 / q) := by
rw [eLpNorm'_eq_lintegral_enorm, lintegral_const,
ENNReal.mul_rpow_of_nonneg _ _ (by simp [hq_pos.le] : 0 ≤ 1 / q)]
congr
rw [← ENNReal.rpow_mul]
suffices hq_cancel : q * (1 / q) = 1 by rw [hq_cancel, ENNReal.rpow_one]
rw [one_div, mul_inv_cancel₀ (ne_of_lt hq_pos).symm]
-- Generalising this to ENormedAddMonoid requires a case analysis whether ‖c‖ₑ = ⊤,
-- and will happen in a future PR.
theorem eLpNorm'_const' [IsFiniteMeasure μ] (c : F) (hc_ne_zero : c ≠ 0) (hq_ne_zero : q ≠ 0) :
eLpNorm' (fun _ : α => c) q μ = ‖c‖ₑ * μ Set.univ ^ (1 / q) := by
rw [eLpNorm'_eq_lintegral_enorm, lintegral_const,
ENNReal.mul_rpow_of_ne_top _ (measure_ne_top μ Set.univ)]
· congr
rw [← ENNReal.rpow_mul]
suffices hp_cancel : q * (1 / q) = 1 by rw [hp_cancel, ENNReal.rpow_one]
rw [one_div, mul_inv_cancel₀ hq_ne_zero]
· rw [Ne, ENNReal.rpow_eq_top_iff, not_or, not_and_or, not_and_or]
simp [hc_ne_zero]
theorem eLpNormEssSup_const (c : ε) (hμ : μ ≠ 0) : eLpNormEssSup (fun _ : α => c) μ = ‖c‖ₑ := by
rw [eLpNormEssSup_eq_essSup_enorm, essSup_const _ hμ]
theorem eLpNorm'_const_of_isProbabilityMeasure (c : ε) (hq_pos : 0 < q) [IsProbabilityMeasure μ] :
eLpNorm' (fun _ : α => c) q μ = ‖c‖ₑ := by simp [eLpNorm'_const c hq_pos, measure_univ]
theorem eLpNorm_const (c : ε) (h0 : p ≠ 0) (hμ : μ ≠ 0) :
eLpNorm (fun _ : α => c) p μ = ‖c‖ₑ * μ Set.univ ^ (1 / ENNReal.toReal p) := by
by_cases h_top : p = ∞
· simp [h_top, eLpNormEssSup_const c hμ]
simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm'_const, ENNReal.toReal_pos h0 h_top]
theorem eLpNorm_const' (c : ε) (h0 : p ≠ 0) (h_top : p ≠ ∞) :
eLpNorm (fun _ : α => c) p μ = ‖c‖ₑ * μ Set.univ ^ (1 / ENNReal.toReal p) := by
simp [eLpNorm_eq_eLpNorm' h0 h_top, eLpNorm'_const, ENNReal.toReal_pos h0 h_top]
-- NB. If ‖c‖ₑ = ∞ and μ is finite, this claim is false: the right has side is true,
-- but the left hand side is false (as the norm is infinite).
theorem eLpNorm_const_lt_top_iff_enorm {c : ε''} (hc' : ‖c‖ₑ ≠ ∞)
{p : ℝ≥0∞} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
eLpNorm (fun _ : α ↦ c) p μ < ∞ ↔ c = 0 ∨ μ Set.univ < ∞ := by
have hp : 0 < p.toReal := ENNReal.toReal_pos hp_ne_zero hp_ne_top
by_cases hμ : μ = 0
· simp only [hμ, Measure.coe_zero, Pi.zero_apply, or_true, ENNReal.zero_lt_top,
eLpNorm_measure_zero]
by_cases hc : c = 0
· simp only [hc, true_or, eq_self_iff_true, ENNReal.zero_lt_top, eLpNorm_zero']
rw [eLpNorm_const' c hp_ne_zero hp_ne_top]
obtain hμ_top | hμ_ne_top := eq_or_ne (μ .univ) ∞
· simp [hc, hμ_top, hp]
rw [ENNReal.mul_lt_top_iff]
simpa [hμ, hc, hμ_ne_top, hμ_ne_top.lt_top, hc, hc'.lt_top] using
ENNReal.rpow_lt_top_of_nonneg (inv_nonneg.mpr hp.le) hμ_ne_top
theorem eLpNorm_const_lt_top_iff {p : ℝ≥0∞} {c : F} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
eLpNorm (fun _ : α => c) p μ < ∞ ↔ c = 0 ∨ μ Set.univ < ∞ :=
eLpNorm_const_lt_top_iff_enorm enorm_ne_top hp_ne_zero hp_ne_top
theorem memLp_const_enorm {c : ε'} (hc : ‖c‖ₑ ≠ ⊤) [IsFiniteMeasure μ] :
MemLp (fun _ : α ↦ c) p μ := by
refine ⟨aestronglyMeasurable_const, ?_⟩
by_cases h0 : p = 0
· simp [h0]
by_cases hμ : μ = 0
· simp [hμ]
rw [eLpNorm_const c h0 hμ]
exact ENNReal.mul_lt_top hc.lt_top (ENNReal.rpow_lt_top_of_nonneg (by simp)
(measure_ne_top μ Set.univ))
theorem memLp_const (c : E) [IsFiniteMeasure μ] : MemLp (fun _ : α => c) p μ :=
memLp_const_enorm enorm_ne_top
@[deprecated (since := "2025-02-21")]
alias memℒp_const := memLp_const
theorem memLp_top_const_enorm {c : ε'} (hc : ‖c‖ₑ ≠ ⊤) :
MemLp (fun _ : α ↦ c) ∞ μ :=
⟨aestronglyMeasurable_const, by by_cases h : μ = 0 <;> simp [eLpNorm_const _, h, hc.lt_top]⟩
theorem memLp_top_const (c : E) : MemLp (fun _ : α => c) ∞ μ :=
memLp_top_const_enorm enorm_ne_top
@[deprecated (since := "2025-02-21")]
alias memℒp_top_const := memLp_top_const
theorem memLp_const_iff_enorm
{p : ℝ≥0∞} {c : ε''} (hc : ‖c‖ₑ ≠ ⊤) (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
MemLp (fun _ : α ↦ c) p μ ↔ c = 0 ∨ μ Set.univ < ∞ := by
simp_all [MemLp, aestronglyMeasurable_const,
eLpNorm_const_lt_top_iff_enorm hc hp_ne_zero hp_ne_top]
theorem memLp_const_iff {p : ℝ≥0∞} {c : E} (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) :
MemLp (fun _ : α => c) p μ ↔ c = 0 ∨ μ Set.univ < ∞ :=
memLp_const_iff_enorm enorm_ne_top hp_ne_zero hp_ne_top
@[deprecated (since := "2025-02-21")]
alias memℒp_const_iff := memLp_const_iff
end Const
variable {f : α → F}
lemma eLpNorm'_mono_enorm_ae {f : α → ε} {g : α → ε'} (hq : 0 ≤ q) (h : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm' f q μ ≤ eLpNorm' g q μ := by
simp only [eLpNorm'_eq_lintegral_enorm]
gcongr ?_ ^ (1/q)
refine lintegral_mono_ae (h.mono fun x hx => ?_)
gcongr
lemma eLpNorm'_mono_nnnorm_ae {f : α → F} {g : α → G} (hq : 0 ≤ q) (h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNorm' f q μ ≤ eLpNorm' g q μ := by
simp only [eLpNorm'_eq_lintegral_enorm]
gcongr ?_ ^ (1/q)
refine lintegral_mono_ae (h.mono fun x hx => ?_)
dsimp [enorm]
gcongr
theorem eLpNorm'_mono_ae {f : α → F} {g : α → G} (hq : 0 ≤ q) (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
eLpNorm' f q μ ≤ eLpNorm' g q μ :=
eLpNorm'_mono_enorm_ae hq (by simpa only [enorm_le_iff_norm_le] using h)
theorem eLpNorm'_congr_enorm_ae {f g : α → ε} (hfg : ∀ᵐ x ∂μ, ‖f x‖ₑ = ‖g x‖ₑ) :
eLpNorm' f q μ = eLpNorm' g q μ := by
have : (‖f ·‖ₑ ^ q) =ᵐ[μ] (‖g ·‖ₑ ^ q) := hfg.mono fun x hx ↦ by simp [hx]
simp only [eLpNorm'_eq_lintegral_enorm, lintegral_congr_ae this]
theorem eLpNorm'_congr_nnnorm_ae {f g : α → F} (hfg : ∀ᵐ x ∂μ, ‖f x‖₊ = ‖g x‖₊) :
eLpNorm' f q μ = eLpNorm' g q μ := by
have : (‖f ·‖ₑ ^ q) =ᵐ[μ] (‖g ·‖ₑ ^ q) := hfg.mono fun x hx ↦ by simp [enorm, hx]
simp only [eLpNorm'_eq_lintegral_enorm, lintegral_congr_ae this]
theorem eLpNorm'_congr_norm_ae {f g : α → F} (hfg : ∀ᵐ x ∂μ, ‖f x‖ = ‖g x‖) :
eLpNorm' f q μ = eLpNorm' g q μ :=
eLpNorm'_congr_nnnorm_ae <| hfg.mono fun _x hx => NNReal.eq hx
theorem eLpNorm'_congr_ae {f g : α → ε} (hfg : f =ᵐ[μ] g) : eLpNorm' f q μ = eLpNorm' g q μ :=
eLpNorm'_congr_enorm_ae (hfg.fun_comp _)
theorem eLpNormEssSup_congr_ae {f g : α → ε} (hfg : f =ᵐ[μ] g) :
eLpNormEssSup f μ = eLpNormEssSup g μ :=
essSup_congr_ae (hfg.fun_comp enorm)
theorem eLpNormEssSup_mono_enorm_ae {f g : α → ε} (hfg : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNormEssSup f μ ≤ eLpNormEssSup g μ :=
essSup_mono_ae <| hfg
theorem eLpNormEssSup_mono_nnnorm_ae {f g : α → F} (hfg : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNormEssSup f μ ≤ eLpNormEssSup g μ :=
essSup_mono_ae <| hfg.mono fun _x hx => ENNReal.coe_le_coe.mpr hx
theorem eLpNorm_mono_enorm_ae {f : α → ε} {g : α → ε'} (h : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm f p μ ≤ eLpNorm g p μ := by
simp only [eLpNorm]
split_ifs
· exact le_rfl
· exact essSup_mono_ae h
· exact eLpNorm'_mono_enorm_ae ENNReal.toReal_nonneg h
theorem eLpNorm_mono_nnnorm_ae {f : α → F} {g : α → G} (h : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNorm f p μ ≤ eLpNorm g p μ := by
simp only [eLpNorm]
split_ifs
· exact le_rfl
· exact essSup_mono_ae (h.mono fun x hx => ENNReal.coe_le_coe.mpr hx)
· exact eLpNorm'_mono_nnnorm_ae ENNReal.toReal_nonneg h
theorem eLpNorm_mono_ae {f : α → F} {g : α → G} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_enorm_ae (by simpa only [enorm_le_iff_norm_le] using h)
theorem eLpNorm_mono_ae' {ε' : Type*} [ENorm ε']
{f : α → ε} {g : α → ε'} (h : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_enorm_ae (by simpa only [enorm_le_iff_norm_le] using h)
theorem eLpNorm_mono_ae_real {f : α → F} {g : α → ℝ} (h : ∀ᵐ x ∂μ, ‖f x‖ ≤ g x) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_ae <| h.mono fun _x hx =>
hx.trans ((le_abs_self _).trans (Real.norm_eq_abs _).symm.le)
theorem eLpNorm_mono_enorm {f : α → ε} {g : α → ε'} (h : ∀ x, ‖f x‖ₑ ≤ ‖g x‖ₑ) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_enorm_ae (Eventually.of_forall h)
theorem eLpNorm_mono_nnnorm {f : α → F} {g : α → G} (h : ∀ x, ‖f x‖₊ ≤ ‖g x‖₊) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_nnnorm_ae (Eventually.of_forall h)
theorem eLpNorm_mono {f : α → F} {g : α → G} (h : ∀ x, ‖f x‖ ≤ ‖g x‖) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_ae (Eventually.of_forall h)
theorem eLpNorm_mono_real {f : α → F} {g : α → ℝ} (h : ∀ x, ‖f x‖ ≤ g x) :
eLpNorm f p μ ≤ eLpNorm g p μ :=
eLpNorm_mono_ae_real (Eventually.of_forall h)
theorem eLpNormEssSup_le_of_ae_enorm_bound {f : α → ε} {C : ℝ≥0∞} (hfC : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ C) :
eLpNormEssSup f μ ≤ C :=
essSup_le_of_ae_le C hfC
theorem eLpNormEssSup_le_of_ae_nnnorm_bound {f : α → F} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) :
eLpNormEssSup f μ ≤ C :=
essSup_le_of_ae_le (C : ℝ≥0∞) <| hfC.mono fun _x hx => ENNReal.coe_le_coe.mpr hx
theorem eLpNormEssSup_le_of_ae_bound {f : α → F} {C : ℝ} (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
eLpNormEssSup f μ ≤ ENNReal.ofReal C :=
eLpNormEssSup_le_of_ae_nnnorm_bound <| hfC.mono fun _x hx => hx.trans C.le_coe_toNNReal
theorem eLpNormEssSup_lt_top_of_ae_enorm_bound {f : α → ε} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ C) :
eLpNormEssSup f μ < ∞ :=
(eLpNormEssSup_le_of_ae_enorm_bound hfC).trans_lt ENNReal.coe_lt_top
theorem eLpNormEssSup_lt_top_of_ae_nnnorm_bound {f : α → F} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) :
eLpNormEssSup f μ < ∞ :=
(eLpNormEssSup_le_of_ae_nnnorm_bound hfC).trans_lt ENNReal.coe_lt_top
theorem eLpNormEssSup_lt_top_of_ae_bound {f : α → F} {C : ℝ} (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
eLpNormEssSup f μ < ∞ :=
(eLpNormEssSup_le_of_ae_bound hfC).trans_lt ENNReal.ofReal_lt_top
theorem eLpNorm_le_of_ae_enorm_bound {ε} [TopologicalSpace ε] [ENormedAddMonoid ε]
{f : α → ε} {C : ℝ≥0∞} (hfC : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ C) :
eLpNorm f p μ ≤ C • μ Set.univ ^ p.toReal⁻¹ := by
rcases eq_zero_or_neZero μ with rfl | hμ
· simp
by_cases hp : p = 0
· simp [hp]
have : ∀ᵐ x ∂μ, ‖f x‖ₑ ≤ ‖C‖ₑ := hfC.mono fun x hx ↦ hx.trans (Preorder.le_refl C)
refine (eLpNorm_mono_enorm_ae this).trans_eq ?_
rw [eLpNorm_const _ hp (NeZero.ne μ), one_div, enorm_eq_self, smul_eq_mul]
theorem eLpNorm_le_of_ae_nnnorm_bound {f : α → F} {C : ℝ≥0} (hfC : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ C) :
eLpNorm f p μ ≤ C • μ Set.univ ^ p.toReal⁻¹ := by
rcases eq_zero_or_neZero μ with rfl | hμ
· simp
by_cases hp : p = 0
· simp [hp]
have : ∀ᵐ x ∂μ, ‖f x‖₊ ≤ ‖(C : ℝ)‖₊ := hfC.mono fun x hx => hx.trans_eq C.nnnorm_eq.symm
refine (eLpNorm_mono_ae this).trans_eq ?_
rw [eLpNorm_const _ hp (NeZero.ne μ), C.enorm_eq, one_div, ENNReal.smul_def, smul_eq_mul]
theorem eLpNorm_le_of_ae_bound {f : α → F} {C : ℝ} (hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) :
eLpNorm f p μ ≤ μ Set.univ ^ p.toReal⁻¹ * ENNReal.ofReal C := by
rw [← mul_comm]
exact eLpNorm_le_of_ae_nnnorm_bound (hfC.mono fun x hx => hx.trans C.le_coe_toNNReal)
theorem eLpNorm_congr_enorm_ae {f : α → ε} {g : α → ε'} (hfg : ∀ᵐ x ∂μ, ‖f x‖ₑ = ‖g x‖ₑ) :
eLpNorm f p μ = eLpNorm g p μ :=
le_antisymm (eLpNorm_mono_enorm_ae <| EventuallyEq.le hfg)
(eLpNorm_mono_enorm_ae <| (EventuallyEq.symm hfg).le)
theorem eLpNorm_congr_nnnorm_ae {f : α → F} {g : α → G} (hfg : ∀ᵐ x ∂μ, ‖f x‖₊ = ‖g x‖₊) :
eLpNorm f p μ = eLpNorm g p μ :=
le_antisymm (eLpNorm_mono_nnnorm_ae <| EventuallyEq.le hfg)
(eLpNorm_mono_nnnorm_ae <| (EventuallyEq.symm hfg).le)
theorem eLpNorm_congr_norm_ae {f : α → F} {g : α → G} (hfg : ∀ᵐ x ∂μ, ‖f x‖ = ‖g x‖) :
eLpNorm f p μ = eLpNorm g p μ :=
eLpNorm_congr_nnnorm_ae <| hfg.mono fun _x hx => NNReal.eq hx
open scoped symmDiff in
theorem eLpNorm_indicator_sub_indicator (s t : Set α) (f : α → E) :
eLpNorm (s.indicator f - t.indicator f) p μ = eLpNorm ((s ∆ t).indicator f) p μ :=
eLpNorm_congr_norm_ae <| ae_of_all _ fun x ↦ by simp [Set.apply_indicator_symmDiff norm_neg]
@[simp]
theorem eLpNorm'_norm {f : α → F} : eLpNorm' (fun a => ‖f a‖) q μ = eLpNorm' f q μ := by
simp [eLpNorm'_eq_lintegral_enorm]
@[simp]
theorem eLpNorm'_enorm {f : α → ε} : eLpNorm' (fun a => ‖f a‖ₑ) q μ = eLpNorm' f q μ := by
simp [eLpNorm'_eq_lintegral_enorm]
@[simp]
theorem eLpNorm_norm (f : α → F) : eLpNorm (fun x => ‖f x‖) p μ = eLpNorm f p μ :=
eLpNorm_congr_norm_ae <| Eventually.of_forall fun _ => norm_norm _
@[simp]
theorem eLpNorm_enorm (f : α → ε) : eLpNorm (fun x ↦ ‖f x‖ₑ) p μ = eLpNorm f p μ :=
eLpNorm_congr_enorm_ae <| Eventually.of_forall fun _ => enorm_enorm _
theorem eLpNorm'_norm_rpow (f : α → F) (p q : ℝ) (hq_pos : 0 < q) :
eLpNorm' (fun x => ‖f x‖ ^ q) p μ = eLpNorm' f (p * q) μ ^ q := by
simp_rw [eLpNorm', ← ENNReal.rpow_mul, ← one_div_mul_one_div, one_div,
mul_assoc, inv_mul_cancel₀ hq_pos.ne.symm, mul_one, ← ofReal_norm_eq_enorm,
Real.norm_eq_abs, abs_eq_self.mpr (Real.rpow_nonneg (norm_nonneg _) _), mul_comm p,
← ENNReal.ofReal_rpow_of_nonneg (norm_nonneg _) hq_pos.le, ENNReal.rpow_mul]
theorem eLpNorm_norm_rpow (f : α → F) (hq_pos : 0 < q) :
eLpNorm (fun x => ‖f x‖ ^ q) p μ = eLpNorm f (p * ENNReal.ofReal q) μ ^ q := by
by_cases h0 : p = 0
· simp [h0, ENNReal.zero_rpow_of_pos hq_pos]
by_cases hp_top : p = ∞
· simp only [hp_top, eLpNorm_exponent_top, ENNReal.top_mul', hq_pos.not_le,
ENNReal.ofReal_eq_zero, if_false, eLpNorm_exponent_top, eLpNormEssSup_eq_essSup_enorm]
have h_rpow : essSup (‖‖f ·‖ ^ q‖ₑ) μ = essSup (‖f ·‖ₑ ^ q) μ := by
congr
ext1 x
conv_rhs => rw [← enorm_norm]
rw [← Real.enorm_rpow_of_nonneg (norm_nonneg _) hq_pos.le]
rw [h_rpow]
have h_rpow_mono := ENNReal.strictMono_rpow_of_pos hq_pos
have h_rpow_surj := (ENNReal.rpow_left_bijective hq_pos.ne.symm).2
let iso := h_rpow_mono.orderIsoOfSurjective _ h_rpow_surj
exact (iso.essSup_apply (fun x => ‖f x‖ₑ) μ).symm
rw [eLpNorm_eq_eLpNorm' h0 hp_top, eLpNorm_eq_eLpNorm' _ _]
swap
· refine mul_ne_zero h0 ?_
rwa [Ne, ENNReal.ofReal_eq_zero, not_le]
swap; · exact ENNReal.mul_ne_top hp_top ENNReal.ofReal_ne_top
rw [ENNReal.toReal_mul, ENNReal.toReal_ofReal hq_pos.le]
exact eLpNorm'_norm_rpow f p.toReal q hq_pos
theorem eLpNorm_congr_ae {f g : α → ε} (hfg : f =ᵐ[μ] g) : eLpNorm f p μ = eLpNorm g p μ :=
eLpNorm_congr_enorm_ae <| hfg.mono fun _x hx => hx ▸ rfl
theorem memLp_congr_ae [TopologicalSpace ε] {f g : α → ε} (hfg : f =ᵐ[μ] g) :
MemLp f p μ ↔ MemLp g p μ := by
simp only [MemLp, eLpNorm_congr_ae hfg, aestronglyMeasurable_congr hfg]
@[deprecated (since := "2025-02-21")]
alias memℒp_congr_ae := memLp_congr_ae
theorem MemLp.ae_eq [TopologicalSpace ε] {f g : α → ε} (hfg : f =ᵐ[μ] g) (hf_Lp : MemLp f p μ) :
MemLp g p μ :=
(memLp_congr_ae hfg).1 hf_Lp
@[deprecated (since := "2025-02-21")]
alias Memℒp.ae_eq := MemLp.ae_eq
theorem MemLp.of_le {f : α → E} {g : α → F} (hg : MemLp g p μ) (hf : AEStronglyMeasurable f μ)
(hfg : ∀ᵐ x ∂μ, ‖f x‖ ≤ ‖g x‖) : MemLp f p μ :=
⟨hf, (eLpNorm_mono_ae hfg).trans_lt hg.eLpNorm_lt_top⟩
@[deprecated (since := "2025-02-21")] alias Memℒp.of_le := MemLp.of_le
alias MemLp.mono := MemLp.of_le
@[deprecated (since := "2025-02-21")] alias Memℒp.mono := MemLp.mono
theorem MemLp.mono' {f : α → E} {g : α → ℝ} (hg : MemLp g p μ) (hf : AEStronglyMeasurable f μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ ≤ g a) : MemLp f p μ :=
hg.mono hf <| h.mono fun _x hx => le_trans hx (le_abs_self _)
@[deprecated (since := "2025-02-21")]
alias Memℒp.mono' := MemLp.mono'
theorem MemLp.congr_norm {f : α → E} {g : α → F} (hf : MemLp f p μ) (hg : AEStronglyMeasurable g μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : MemLp g p μ :=
hf.mono hg <| EventuallyEq.le <| EventuallyEq.symm h
@[deprecated (since := "2025-02-21")]
alias Memℒp.congr_norm := MemLp.congr_norm
theorem memLp_congr_norm {f : α → E} {g : α → F} (hf : AEStronglyMeasurable f μ)
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : MemLp f p μ ↔ MemLp g p μ :=
⟨fun h2f => h2f.congr_norm hg h, fun h2g => h2g.congr_norm hf <| EventuallyEq.symm h⟩
@[deprecated (since := "2025-02-21")]
alias memℒp_congr_norm := memLp_congr_norm
theorem memLp_top_of_bound {f : α → E} (hf : AEStronglyMeasurable f μ) (C : ℝ)
(hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) : MemLp f ∞ μ :=
⟨hf, by
rw [eLpNorm_exponent_top]
exact eLpNormEssSup_lt_top_of_ae_bound hfC⟩
@[deprecated (since := "2025-02-21")]
alias memℒp_top_of_bound := memLp_top_of_bound
theorem MemLp.of_bound [IsFiniteMeasure μ] {f : α → E} (hf : AEStronglyMeasurable f μ) (C : ℝ)
(hfC : ∀ᵐ x ∂μ, ‖f x‖ ≤ C) : MemLp f p μ :=
(memLp_const C).of_le hf (hfC.mono fun _x hx => le_trans hx (le_abs_self _))
@[deprecated (since := "2025-02-21")]
alias Memℒp.of_bound := MemLp.of_bound
theorem memLp_of_bounded [IsFiniteMeasure μ]
{a b : ℝ} {f : α → ℝ} (h : ∀ᵐ x ∂μ, f x ∈ Set.Icc a b)
(hX : AEStronglyMeasurable f μ) (p : ENNReal) : MemLp f p μ :=
have ha : ∀ᵐ x ∂μ, a ≤ f x := h.mono fun ω h => h.1
have hb : ∀ᵐ x ∂μ, f x ≤ b := h.mono fun ω h => h.2
(memLp_const (max |a| |b|)).mono' hX (by filter_upwards [ha, hb] with x using abs_le_max_abs_abs)
@[deprecated (since := "2025-02-21")]
alias memℒp_of_bounded := memLp_of_bounded
@[gcongr, mono]
theorem eLpNorm'_mono_measure (f : α → ε) (hμν : ν ≤ μ) (hq : 0 ≤ q) :
eLpNorm' f q ν ≤ eLpNorm' f q μ := by
simp_rw [eLpNorm']
gcongr
exact lintegral_mono' hμν le_rfl
@[gcongr, mono]
theorem eLpNormEssSup_mono_measure (f : α → ε) (hμν : ν ≪ μ) :
eLpNormEssSup f ν ≤ eLpNormEssSup f μ := by
simp_rw [eLpNormEssSup]
exact essSup_mono_measure hμν
@[gcongr, mono]
theorem eLpNorm_mono_measure (f : α → ε) (hμν : ν ≤ μ) : eLpNorm f p ν ≤ eLpNorm f p μ := by
by_cases hp0 : p = 0
· simp [hp0]
by_cases hp_top : p = ∞
· simp [hp_top, eLpNormEssSup_mono_measure f (Measure.absolutelyContinuous_of_le hμν)]
simp_rw [eLpNorm_eq_eLpNorm' hp0 hp_top]
exact eLpNorm'_mono_measure f hμν ENNReal.toReal_nonneg
theorem MemLp.mono_measure [TopologicalSpace ε] {f : α → ε} (hμν : ν ≤ μ) (hf : MemLp f p μ) :
MemLp f p ν :=
⟨hf.1.mono_measure hμν, (eLpNorm_mono_measure f hμν).trans_lt hf.2⟩
@[deprecated (since := "2025-02-21")]
alias Memℒp.mono_measure := MemLp.mono_measure
section Indicator
variable {ε : Type*} [TopologicalSpace ε] [ENormedAddMonoid ε]
{c : ε} {hf : AEStronglyMeasurable f μ} {s : Set α}
lemma eLpNorm_indicator_eq_eLpNorm_restrict {f : α → ε} {s : Set α} (hs : MeasurableSet s) :
eLpNorm (s.indicator f) p μ = eLpNorm f p (μ.restrict s) := by
by_cases hp_zero : p = 0
· simp only [hp_zero, eLpNorm_exponent_zero]
by_cases hp_top : p = ∞
· simp_rw [hp_top, eLpNorm_exponent_top, eLpNormEssSup_eq_essSup_enorm,
enorm_indicator_eq_indicator_enorm, ENNReal.essSup_indicator_eq_essSup_restrict hs]
simp_rw [eLpNorm_eq_lintegral_rpow_enorm hp_zero hp_top]
suffices (∫⁻ x, (‖s.indicator f x‖ₑ) ^ p.toReal ∂μ) =
∫⁻ x in s, ‖f x‖ₑ ^ p.toReal ∂μ by rw [this]
rw [← lintegral_indicator hs]
congr
simp_rw [enorm_indicator_eq_indicator_enorm]
rw [eq_comm, ← Function.comp_def (fun x : ℝ≥0∞ => x ^ p.toReal), Set.indicator_comp_of_zero,
Function.comp_def]
simp [ENNReal.toReal_pos hp_zero hp_top]
@[deprecated (since := "2025-01-07")]
alias eLpNorm_indicator_eq_restrict := eLpNorm_indicator_eq_eLpNorm_restrict
lemma eLpNormEssSup_indicator_eq_eLpNormEssSup_restrict (hs : MeasurableSet s) :
eLpNormEssSup (s.indicator f) μ = eLpNormEssSup f (μ.restrict s) := by
simp_rw [← eLpNorm_exponent_top, eLpNorm_indicator_eq_eLpNorm_restrict hs]
lemma eLpNorm_restrict_le (f : α → ε') (p : ℝ≥0∞) (μ : Measure α) (s : Set α) :
eLpNorm f p (μ.restrict s) ≤ eLpNorm f p μ :=
eLpNorm_mono_measure f Measure.restrict_le_self
lemma eLpNorm_indicator_le (f : α → ε) :
eLpNorm (s.indicator f) p μ ≤ eLpNorm f p μ := by
refine eLpNorm_mono_ae' <| .of_forall fun x ↦ ?_
| rw [enorm_indicator_eq_indicator_enorm]
exact s.indicator_le_self _ x
lemma eLpNormEssSup_indicator_le (s : Set α) (f : α → ε) :
eLpNormEssSup (s.indicator f) μ ≤ eLpNormEssSup f μ := by
refine essSup_mono_ae (Eventually.of_forall fun x => ?_)
simp_rw [enorm_indicator_eq_indicator_enorm]
exact Set.indicator_le_self s _ x
| Mathlib/MeasureTheory/Function/LpSeminorm/Basic.lean | 667 | 674 |
/-
Copyright (c) 2021 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Algebra.Polynomial.Degree.CardPowDegree
import Mathlib.Analysis.SpecialFunctions.Pow.Real
import Mathlib.NumberTheory.ClassNumber.AdmissibleAbsoluteValue
import Mathlib.RingTheory.LocalRing.Basic
/-!
# Admissible absolute values on polynomials
This file defines an admissible absolute value `Polynomial.cardPowDegreeIsAdmissible` which we
use to show the class number of the ring of integers of a function field is finite.
## Main results
* `Polynomial.cardPowDegreeIsAdmissible` shows `cardPowDegree`,
mapping `p : Polynomial 𝔽_q` to `q ^ degree p`, is admissible
-/
namespace Polynomial
open AbsoluteValue Real
variable {Fq : Type*} [Fintype Fq]
/-- If `A` is a family of enough low-degree polynomials over a finite semiring, there is a
pair of equal elements in `A`. -/
theorem exists_eq_polynomial [Semiring Fq] {d : ℕ} {m : ℕ} (hm : Fintype.card Fq ^ d ≤ m)
(b : Fq[X]) (hb : natDegree b ≤ d) (A : Fin m.succ → Fq[X])
(hA : ∀ i, degree (A i) < degree b) : ∃ i₀ i₁, i₀ ≠ i₁ ∧ A i₁ = A i₀ := by
-- Since there are > q^d elements of A, and only q^d choices for the highest `d` coefficients,
-- there must be two elements of A with the same coefficients at
-- `0`, ... `degree b - 1` ≤ `d - 1`.
-- In other words, the following map is not injective:
set f : Fin m.succ → Fin d → Fq := fun i j => (A i).coeff j
have : Fintype.card (Fin d → Fq) < Fintype.card (Fin m.succ) := by
simpa using lt_of_le_of_lt hm (Nat.lt_succ_self m)
-- Therefore, the differences have all coefficients higher than `deg b - d` equal.
obtain ⟨i₀, i₁, i_ne, i_eq⟩ := Fintype.exists_ne_map_eq_of_card_lt f this
use i₀, i₁, i_ne
ext j
-- The coefficients higher than `deg b` are the same because they are equal to 0.
by_cases hbj : degree b ≤ j
· rw [coeff_eq_zero_of_degree_lt (lt_of_lt_of_le (hA _) hbj),
coeff_eq_zero_of_degree_lt (lt_of_lt_of_le (hA _) hbj)]
-- So we only need to look for the coefficients between `0` and `deg b`.
rw [not_le] at hbj
apply congr_fun i_eq.symm ⟨j, _⟩
exact lt_of_lt_of_le (coe_lt_degree.mp hbj) hb
/-- If `A` is a family of enough low-degree polynomials over a finite ring,
there is a pair of elements in `A` (with different indices but not necessarily
distinct), such that their difference has small degree. -/
theorem exists_approx_polynomial_aux [Ring Fq] {d : ℕ} {m : ℕ} (hm : Fintype.card Fq ^ d ≤ m)
(b : Fq[X]) (A : Fin m.succ → Fq[X]) (hA : ∀ i, degree (A i) < degree b) :
∃ i₀ i₁, i₀ ≠ i₁ ∧ degree (A i₁ - A i₀) < ↑(natDegree b - d) := by
have hb : b ≠ 0 := by
rintro rfl
specialize hA 0
rw [degree_zero] at hA
exact not_lt_of_le bot_le hA
-- Since there are > q^d elements of A, and only q^d choices for the highest `d` coefficients,
-- there must be two elements of A with the same coefficients at
-- `degree b - 1`, ... `degree b - d`.
-- In other words, the following map is not injective:
set f : Fin m.succ → Fin d → Fq := fun i j => (A i).coeff (natDegree b - j.succ)
have : Fintype.card (Fin d → Fq) < Fintype.card (Fin m.succ) := by
simpa using lt_of_le_of_lt hm (Nat.lt_succ_self m)
-- Therefore, the differences have all coefficients higher than `deg b - d` equal.
obtain ⟨i₀, i₁, i_ne, i_eq⟩ := Fintype.exists_ne_map_eq_of_card_lt f this
use i₀, i₁, i_ne
refine (degree_lt_iff_coeff_zero _ _).mpr fun j hj => ?_
-- The coefficients higher than `deg b` are the same because they are equal to 0.
by_cases hbj : degree b ≤ j
· refine coeff_eq_zero_of_degree_lt (lt_of_lt_of_le ?_ hbj)
exact lt_of_le_of_lt (degree_sub_le _ _) (max_lt (hA _) (hA _))
-- So we only need to look for the coefficients between `deg b - d` and `deg b`.
rw [coeff_sub, sub_eq_zero]
rw [not_le, degree_eq_natDegree hb] at hbj
have hbj : j < natDegree b := (@WithBot.coe_lt_coe _ _ _).mp hbj
have hj : natDegree b - j.succ < d := by
by_cases hd : natDegree b < d
· exact lt_of_le_of_lt tsub_le_self hd
· rw [not_lt] at hd
have := lt_of_le_of_lt hj (Nat.lt_succ_self j)
rwa [tsub_lt_iff_tsub_lt hd hbj] at this
have : j = b.natDegree - (natDegree b - j.succ).succ := by
rw [← Nat.succ_sub hbj, Nat.succ_sub_succ, tsub_tsub_cancel_of_le hbj.le]
convert congr_fun i_eq.symm ⟨natDegree b - j.succ, hj⟩
variable [Field Fq]
/-- If `A` is a family of enough low-degree polynomials over a finite field,
there is a pair of elements in `A` (with different indices but not necessarily
distinct), such that the difference of their remainders is close together. -/
theorem exists_approx_polynomial {b : Fq[X]} (hb : b ≠ 0) {ε : ℝ} (hε : 0 < ε)
(A : Fin (Fintype.card Fq ^ ⌈-log ε / log (Fintype.card Fq)⌉₊).succ → Fq[X]) :
∃ i₀ i₁, i₀ ≠ i₁ ∧ (cardPowDegree (A i₁ % b - A i₀ % b) : ℝ) < cardPowDegree b • ε := by
have hbε : 0 < cardPowDegree b • ε := by
rw [Algebra.smul_def, eq_intCast]
exact mul_pos (Int.cast_pos.mpr (AbsoluteValue.pos _ hb)) hε
have one_lt_q : 1 < Fintype.card Fq := Fintype.one_lt_card
have one_lt_q' : (1 : ℝ) < Fintype.card Fq := by assumption_mod_cast
have q_pos : 0 < Fintype.card Fq := by omega
have q_pos' : (0 : ℝ) < Fintype.card Fq := by assumption_mod_cast
-- If `b` is already small enough, then the remainders are equal and we are done.
by_cases le_b : b.natDegree ≤ ⌈-log ε / log (Fintype.card Fq)⌉₊
· obtain ⟨i₀, i₁, i_ne, mod_eq⟩ :=
exists_eq_polynomial le_rfl b le_b (fun i => A i % b) fun i => EuclideanDomain.mod_lt (A i) hb
refine ⟨i₀, i₁, i_ne, ?_⟩
rwa [mod_eq, sub_self, map_zero, Int.cast_zero]
-- Otherwise, it suffices to choose two elements whose difference is of small enough degree.
rw [not_le] at le_b
obtain ⟨i₀, i₁, i_ne, deg_lt⟩ := exists_approx_polynomial_aux le_rfl b (fun i => A i % b) fun i =>
EuclideanDomain.mod_lt (A i) hb
use i₀, i₁, i_ne
-- Again, if the remainders are equal we are done.
by_cases h : A i₁ % b = A i₀ % b
· rwa [h, sub_self, map_zero, Int.cast_zero]
have h' : A i₁ % b - A i₀ % b ≠ 0 := mt sub_eq_zero.mp h
-- If the remainders are not equal, we'll show their difference is of small degree.
-- In particular, we'll show the degree is less than the following:
suffices (natDegree (A i₁ % b - A i₀ % b) : ℝ) < b.natDegree + log ε / log (Fintype.card Fq) by
rwa [← Real.log_lt_log_iff (Int.cast_pos.mpr (cardPowDegree.pos h')) hbε,
cardPowDegree_nonzero _ h', cardPowDegree_nonzero _ hb, Algebra.smul_def, eq_intCast,
Int.cast_pow, Int.cast_natCast, Int.cast_pow, Int.cast_natCast,
log_mul (pow_ne_zero _ q_pos'.ne') hε.ne', ← rpow_natCast, ← rpow_natCast, log_rpow q_pos',
log_rpow q_pos', ← lt_div_iff₀ (log_pos one_lt_q'), add_div,
mul_div_cancel_right₀ _ (log_pos one_lt_q').ne']
-- And that result follows from manipulating the result from `exists_approx_polynomial_aux`
-- to turn the `-⌈-stuff⌉₊` into `+ stuff`.
apply lt_of_lt_of_le (Nat.cast_lt.mpr (WithBot.coe_lt_coe.mp _)) _
swap
· convert deg_lt
rw [degree_eq_natDegree h']; rfl
rw [← sub_neg_eq_add, neg_div]
refine le_trans ?_ (sub_le_sub_left (Nat.le_ceil _) (b.natDegree : ℝ))
rw [← neg_div]
exact le_of_eq (Nat.cast_sub le_b.le)
/-- If `x` is close to `y` and `y` is close to `z`, then `x` and `z` are at least as close. -/
theorem cardPowDegree_anti_archimedean {x y z : Fq[X]} {a : ℤ} (hxy : cardPowDegree (x - y) < a)
(hyz : cardPowDegree (y - z) < a) : cardPowDegree (x - z) < a := by
have ha : 0 < a := lt_of_le_of_lt (AbsoluteValue.nonneg _ _) hxy
by_cases hxy' : x = y
· rwa [hxy']
by_cases hyz' : y = z
· rwa [← hyz']
by_cases hxz' : x = z
· rwa [hxz', sub_self, map_zero]
rw [← Ne, ← sub_ne_zero] at hxy' hyz' hxz'
refine lt_of_le_of_lt ?_ (max_lt hxy hyz)
rw [cardPowDegree_nonzero _ hxz', cardPowDegree_nonzero _ hxy',
cardPowDegree_nonzero _ hyz']
have : (1 : ℤ) ≤ Fintype.card Fq := mod_cast (@Fintype.one_lt_card Fq _ _).le
simp only [Int.cast_pow, Int.cast_natCast, le_max_iff]
refine Or.imp (pow_le_pow_right₀ this) (pow_le_pow_right₀ this) ?_
rw [natDegree_le_iff_degree_le, natDegree_le_iff_degree_le, ← le_max_iff, ←
degree_eq_natDegree hxy', ← degree_eq_natDegree hyz']
convert degree_add_le (x - y) (y - z) using 2
exact (sub_add_sub_cancel _ _ _).symm
/-- A slightly stronger version of `exists_partition` on which we perform induction on `n`:
for all `ε > 0`, we can partition the remainders of any family of polynomials `A`
into equivalence classes, where the equivalence(!) relation is "closer than `ε`". -/
theorem exists_partition_polynomial_aux (n : ℕ) {ε : ℝ} (hε : 0 < ε) {b : Fq[X]} (hb : b ≠ 0)
(A : Fin n → Fq[X]) : ∃ t : Fin n → Fin (Fintype.card Fq ^ ⌈-log ε / log (Fintype.card Fq)⌉₊),
∀ i₀ i₁ : Fin n, t i₀ = t i₁ ↔
(cardPowDegree (A i₁ % b - A i₀ % b) : ℝ) < cardPowDegree b • ε := by
have hbε : 0 < cardPowDegree b • ε := by
rw [Algebra.smul_def, eq_intCast]
exact mul_pos (Int.cast_pos.mpr (AbsoluteValue.pos _ hb)) hε
-- We go by induction on the size `A`.
induction n with | zero => refine ⟨finZeroElim, finZeroElim⟩ | succ n ih =>
-- Show `anti_archimedean` also holds for real distances.
have anti_archim' : ∀ {i j k} {ε : ℝ},
(cardPowDegree (A i % b - A j % b) : ℝ) < ε →
(cardPowDegree (A j % b - A k % b) : ℝ) < ε →
(cardPowDegree (A i % b - A k % b) : ℝ) < ε := by
intro i j k ε
simp_rw [← Int.lt_ceil]
exact cardPowDegree_anti_archimedean
obtain ⟨t', ht'⟩ := ih (Fin.tail A)
-- We got rid of `A 0`, so determine the index `j` of the partition we'll re-add it to.
rsuffices ⟨j, hj⟩ :
∃ j, ∀ i, t' i = j ↔ (cardPowDegree (A 0 % b - A i.succ % b) : ℝ) < cardPowDegree b • ε
· refine ⟨Fin.cons j t', fun i₀ i₁ => ?_⟩
refine Fin.cases ?_ (fun i₀ => ?_) i₀ <;> refine Fin.cases ?_ (fun i₁ => ?_) i₁
· simpa using hbε
· rw [Fin.cons_succ, Fin.cons_zero, eq_comm, AbsoluteValue.map_sub]
exact hj i₁
· rw [Fin.cons_succ, Fin.cons_zero]
exact hj i₀
· rw [Fin.cons_succ, Fin.cons_succ]
exact ht' i₀ i₁
-- `exists_approx_polynomial` guarantees that we can insert `A 0` into some partition `j`,
-- but not that `j` is uniquely defined (which is needed to keep the induction going).
obtain ⟨j, hj⟩ : ∃ j, ∀ i : Fin n,
t' i = j → (cardPowDegree (A 0 % b - A i.succ % b) : ℝ) < cardPowDegree b • ε := by
by_contra! hg
obtain ⟨j₀, j₁, j_ne, approx⟩ := exists_approx_polynomial hb hε
(Fin.cons (A 0) fun j => A (Fin.succ (Classical.choose (hg j))))
revert j_ne approx
refine Fin.cases ?_ (fun j₀ => ?_) j₀ <;>
refine Fin.cases (fun j_ne approx => ?_) (fun j₁ j_ne approx => ?_) j₁
· exact absurd rfl j_ne
· rw [Fin.cons_succ, Fin.cons_zero, ← not_le, AbsoluteValue.map_sub] at approx
have := (Classical.choose_spec (hg j₁)).2
contradiction
· rw [Fin.cons_succ, Fin.cons_zero, ← not_le] at approx
have := (Classical.choose_spec (hg j₀)).2
contradiction
· rw [Fin.cons_succ, Fin.cons_succ] at approx
rw [Ne, Fin.succ_inj] at j_ne
have : j₀ = j₁ := (Classical.choose_spec (hg j₀)).1.symm.trans
(((ht' (Classical.choose (hg j₀)) (Classical.choose (hg j₁))).mpr approx).trans
(Classical.choose_spec (hg j₁)).1)
contradiction
-- However, if one of those partitions `j` is inhabited by some `i`, then this `j` works.
by_cases exists_nonempty_j : ∃ j, (∃ i, t' i = j) ∧
∀ i, t' i = j → (cardPowDegree (A 0 % b - A i.succ % b) : ℝ) < cardPowDegree b • ε
· obtain ⟨j, ⟨i, hi⟩, hj⟩ := exists_nonempty_j
refine ⟨j, fun i' => ⟨hj i', fun hi' => _root_.trans ((ht' _ _).mpr ?_) hi⟩⟩
apply anti_archim' _ hi'
rw [AbsoluteValue.map_sub]
exact hj _ hi
-- And otherwise, we can just take any `j`, since those are empty.
refine ⟨j, fun i => ⟨hj i, fun hi => ?_⟩⟩
have := exists_nonempty_j ⟨t' i, ⟨i, rfl⟩, fun i' hi' => anti_archim' hi ((ht' _ _).mp hi')⟩
contradiction
/-- For all `ε > 0`, we can partition the remainders of any family of polynomials `A`
into classes, where all remainders in a class are close together. -/
theorem exists_partition_polynomial (n : ℕ) {ε : ℝ} (hε : 0 < ε) {b : Fq[X]} (hb : b ≠ 0)
(A : Fin n → Fq[X]) : ∃ t : Fin n → Fin (Fintype.card Fq ^ ⌈-log ε / log (Fintype.card Fq)⌉₊),
∀ i₀ i₁ : Fin n, t i₀ = t i₁ →
(cardPowDegree (A i₁ % b - A i₀ % b) : ℝ) < cardPowDegree b • ε := by
obtain ⟨t, ht⟩ := exists_partition_polynomial_aux n hε hb A
exact ⟨t, fun i₀ i₁ hi => (ht i₀ i₁).mp hi⟩
/-- `fun p => Fintype.card Fq ^ degree p` is an admissible absolute value.
We set `q ^ degree 0 = 0`. -/
noncomputable def cardPowDegreeIsAdmissible :
| IsAdmissible (cardPowDegree : AbsoluteValue Fq[X] ℤ) :=
{ @cardPowDegree_isEuclidean Fq _
_ with
card := fun ε => Fintype.card Fq ^ ⌈-log ε / log (Fintype.card Fq)⌉₊
exists_partition' := fun n _ hε _ hb => exists_partition_polynomial n hε hb }
| Mathlib/NumberTheory/ClassNumber/AdmissibleCardPowDegree.lean | 248 | 253 |
/-
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.Card
import Mathlib.Data.Fintype.Basic
/-!
# Cardinalities of finite types
This file defines the cardinality `Fintype.card α` as the number of elements in `(univ : Finset α)`.
We also include some elementary results on the values of `Fintype.card` on specific types.
## Main declarations
* `Fintype.card α`: Cardinality of a fintype. Equal to `Finset.univ.card`.
* `Finite.surjective_of_injective`: an injective function from a finite type to
itself is also surjective.
-/
assert_not_exists Monoid
open Function
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
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 :=
Multiset.card_pmap _ _ _
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 := by
rw [← subtype_card s H]
congr!
@[simp]
theorem card_ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) :
@Fintype.card p (ofFinset s H) = #s :=
Fintype.subtype_card s H
theorem card_of_finset' {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) [Fintype p] :
Fintype.card p = #s := by rw [← card_ofFinset s H]; congr!
end Fintype
namespace Fintype
theorem ofEquiv_card [Fintype α] (f : α ≃ β) : @card β (ofEquiv α f) = card α :=
Multiset.card_map _ _
theorem card_congr {α β} [Fintype α] [Fintype β] (f : α ≃ β) : card α = card β := by
rw [← ofEquiv_card f]; congr!
@[congr]
theorem card_congr' {α β} [Fintype α] [Fintype β] (h : α = β) : card α = card β :=
card_congr (by rw [h])
/-- 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`. -/
theorem card_ofSubsingleton (a : α) [Subsingleton α] : @Fintype.card _ (ofSubsingleton a) = 1 :=
rfl
@[simp]
theorem card_unique [Unique α] [h : Fintype α] : Fintype.card α = 1 :=
Subsingleton.elim (ofSubsingleton default) h ▸ card_ofSubsingleton _
/-- Note: this lemma is specifically about `Fintype.ofIsEmpty`. For a statement about
arbitrary `Fintype` instances, use `Fintype.card_eq_zero`. -/
theorem card_ofIsEmpty [IsEmpty α] : @Fintype.card α Fintype.ofIsEmpty = 0 :=
rfl
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
end Set
@[simp]
theorem Finset.card_univ [Fintype α] : #(univ : Finset α) = Fintype.card α := rfl
theorem Finset.eq_univ_of_card [Fintype α] (s : Finset α) (hs : #s = Fintype.card α) :
s = univ :=
eq_of_subset_of_card_le (subset_univ _) <| by rw [hs, Finset.card_univ]
theorem Finset.card_eq_iff_eq_univ [Fintype α] (s : Finset α) : #s = Fintype.card α ↔ s = univ :=
⟨s.eq_univ_of_card, by
rintro rfl
exact Finset.card_univ⟩
theorem Finset.card_le_univ [Fintype α] (s : Finset α) : #s ≤ Fintype.card α :=
card_le_card (subset_univ s)
theorem Finset.card_lt_univ_of_not_mem [Fintype α] {s : Finset α} {x : α} (hx : x ∉ s) :
#s < Fintype.card α :=
card_lt_card ⟨subset_univ s, not_forall.2 ⟨x, fun hx' => hx (hx' <| mem_univ x)⟩⟩
theorem Finset.card_lt_iff_ne_univ [Fintype α] (s : Finset α) :
#s < Fintype.card α ↔ s ≠ Finset.univ :=
s.card_le_univ.lt_iff_ne.trans (not_congr s.card_eq_iff_eq_univ)
theorem Finset.card_compl_lt_iff_nonempty [Fintype α] [DecidableEq α] (s : Finset α) :
#sᶜ < Fintype.card α ↔ s.Nonempty :=
sᶜ.card_lt_iff_ne_univ.trans s.compl_ne_univ_iff_nonempty
theorem Finset.card_univ_diff [DecidableEq α] [Fintype α] (s : Finset α) :
#(univ \ s) = Fintype.card α - #s :=
Finset.card_sdiff (subset_univ s)
theorem Finset.card_compl [DecidableEq α] [Fintype α] (s : Finset α) : #sᶜ = Fintype.card α - #s :=
Finset.card_univ_diff s
@[simp]
theorem Finset.card_add_card_compl [DecidableEq α] [Fintype α] (s : Finset α) :
#s + #sᶜ = 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 + #s = Fintype.card α := by
rw [Nat.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]
theorem Fintype.card_subtype_eq (y : α) [Fintype { x // x = y }] :
Fintype.card { x // x = y } = 1 :=
Fintype.card_unique
theorem Fintype.card_subtype_eq' (y : α) [Fintype { x // y = x }] :
Fintype.card { x // y = x } = 1 :=
Fintype.card_unique
theorem Fintype.card_empty : Fintype.card Empty = 0 :=
rfl
theorem Fintype.card_pempty : Fintype.card PEmpty = 0 :=
rfl
theorem Fintype.card_unit : Fintype.card Unit = 1 :=
rfl
@[simp]
theorem Fintype.card_punit : Fintype.card PUnit = 1 :=
rfl
@[simp]
theorem Fintype.card_bool : Fintype.card Bool = 2 :=
rfl
@[simp]
theorem Fintype.card_ulift (α : Type*) [Fintype α] : Fintype.card (ULift α) = Fintype.card α :=
Fintype.ofEquiv_card _
@[simp]
theorem Fintype.card_plift (α : Type*) [Fintype α] : Fintype.card (PLift α) = Fintype.card α :=
Fintype.ofEquiv_card _
@[simp]
theorem Fintype.card_orderDual (α : Type*) [Fintype α] : Fintype.card αᵒᵈ = Fintype.card α :=
rfl
@[simp]
theorem Fintype.card_lex (α : Type*) [Fintype α] : Fintype.card (Lex α) = Fintype.card α :=
rfl
-- Note: The extra hypothesis `h` is there so that the rewrite lemma applies,
-- no matter what instance of `Fintype (Set.univ : Set α)` is used.
@[simp]
theorem Fintype.card_setUniv [Fintype α] {h : Fintype (Set.univ : Set α)} :
Fintype.card (Set.univ : Set α) = Fintype.card α := by
apply Fintype.card_of_finset'
simp
@[simp]
theorem Fintype.card_subtype_true [Fintype α] {h : Fintype {_a : α // True}} :
@Fintype.card {_a // True} h = Fintype.card α := by
apply Fintype.card_of_subtype
simp
/-- 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 (α ⊕ β)] : Fintype α :=
Fintype.ofInjective (Sum.inl : α → α ⊕ β) Sum.inl_injective
/-- 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 (α ⊕ β)] : Fintype β :=
Fintype.ofInjective (Sum.inr : β → α ⊕ β) Sum.inr_injective
theorem Finite.exists_univ_list (α) [Finite α] : ∃ l : List α, l.Nodup ∧ ∀ x : α, x ∈ l := by
cases nonempty_fintype α
obtain ⟨l, e⟩ := Quotient.exists_rep (@univ α _).1
have := And.intro (@univ α _).2 (@mem_univ_val α _)
exact ⟨_, by rwa [← e] at this⟩
theorem List.Nodup.length_le_card {α : Type*} [Fintype α] {l : List α} (h : l.Nodup) :
l.length ≤ Fintype.card α := by
classical exact List.toFinset_card_of_nodup h ▸ l.toFinset.card_le_univ
namespace Fintype
variable [Fintype α] [Fintype β]
theorem card_le_of_injective (f : α → β) (hf : Function.Injective f) : card α ≤ card β :=
Finset.card_le_card_of_injOn f (fun _ _ => Finset.mem_univ _) fun _ _ _ _ h => hf h
theorem card_le_of_embedding (f : α ↪ β) : card α ≤ card β :=
card_le_of_injective f f.2
theorem card_lt_of_injective_of_not_mem (f : α → β) (h : Function.Injective f) {b : β}
(w : b ∉ Set.range f) : card α < card β :=
calc
card α = (univ.map ⟨f, h⟩).card := (card_map _).symm
_ < card β :=
Finset.card_lt_univ_of_not_mem (x := b) <| by
rwa [← mem_coe, coe_map, coe_univ, Set.image_univ]
theorem card_lt_of_injective_not_surjective (f : α → β) (h : Function.Injective f)
(h' : ¬Function.Surjective f) : card α < card β :=
let ⟨_y, hy⟩ := not_forall.1 h'
card_lt_of_injective_of_not_mem f h hy
theorem card_le_of_surjective (f : α → β) (h : Function.Surjective f) : card β ≤ card α :=
card_le_of_injective _ (Function.injective_surjInv h)
theorem card_range_le {α β : Type*} (f : α → β) [Fintype α] [Fintype (Set.range f)] :
Fintype.card (Set.range f) ≤ Fintype.card α :=
Fintype.card_le_of_surjective (fun a => ⟨f a, by simp⟩) fun ⟨_, a, ha⟩ => ⟨a, by simpa using ha⟩
theorem card_range {α β F : Type*} [FunLike F α β] [EmbeddingLike F α β] (f : F) [Fintype α]
[Fintype (Set.range f)] : Fintype.card (Set.range f) = Fintype.card α :=
Eq.symm <| Fintype.card_congr <| Equiv.ofInjective _ <| EmbeddingLike.injective f
theorem card_eq_zero_iff : card α = 0 ↔ IsEmpty α := by
rw [card, Finset.card_eq_zero, univ_eq_empty_iff]
@[simp] theorem card_eq_zero [IsEmpty α] : card α = 0 :=
card_eq_zero_iff.2 ‹_›
alias card_of_isEmpty := card_eq_zero
/-- A `Fintype` with cardinality zero is equivalent to `Empty`. -/
def cardEqZeroEquivEquivEmpty : card α = 0 ≃ (α ≃ Empty) :=
(Equiv.ofIff card_eq_zero_iff).trans (Equiv.equivEmptyEquiv α).symm
theorem card_pos_iff : 0 < card α ↔ Nonempty α :=
Nat.pos_iff_ne_zero.trans <| not_iff_comm.mp <| not_nonempty_iff.trans card_eq_zero_iff.symm
theorem card_pos [h : Nonempty α] : 0 < card α :=
card_pos_iff.mpr h
@[simp]
theorem card_ne_zero [Nonempty α] : card α ≠ 0 :=
_root_.ne_of_gt card_pos
instance [Nonempty α] : NeZero (card α) := ⟨card_ne_zero⟩
theorem existsUnique_iff_card_one {α} [Fintype α] (p : α → Prop) [DecidablePred p] :
(∃! a : α, p a) ↔ #{x | p x} = 1 := by
rw [Finset.card_eq_one]
refine exists_congr fun x => ?_
simp only [forall_true_left, Subset.antisymm_iff, subset_singleton_iff', singleton_subset_iff,
true_and, and_comm, mem_univ, mem_filter]
@[deprecated (since := "2024-12-17")] alias exists_unique_iff_card_one := existsUnique_iff_card_one
nonrec theorem two_lt_card_iff : 2 < card α ↔ ∃ a b c : α, a ≠ b ∧ a ≠ c ∧ b ≠ c := by
simp_rw [← Finset.card_univ, two_lt_card_iff, mem_univ, true_and]
theorem card_of_bijective {f : α → β} (hf : Bijective f) : card α = card β :=
card_congr (Equiv.ofBijective f hf)
end Fintype
namespace Finite
variable [Finite α]
theorem surjective_of_injective {f : α → α} (hinj : Injective f) : Surjective f := by
intro x
have := Classical.propDecidable
cases nonempty_fintype α
have h₁ : image f univ = univ :=
eq_of_subset_of_card_le (subset_univ _)
((card_image_of_injective univ hinj).symm ▸ le_rfl)
have h₂ : x ∈ image f univ := h₁.symm ▸ mem_univ x
obtain ⟨y, h⟩ := mem_image.1 h₂
exact ⟨y, h.2⟩
theorem injective_iff_surjective {f : α → α} : Injective f ↔ Surjective f :=
⟨surjective_of_injective, fun hsurj =>
HasLeftInverse.injective ⟨surjInv hsurj, leftInverse_of_surjective_of_rightInverse
(surjective_of_injective (injective_surjInv _))
(rightInverse_surjInv _)⟩⟩
theorem injective_iff_bijective {f : α → α} : Injective f ↔ Bijective f := by
simp [Bijective, injective_iff_surjective]
theorem surjective_iff_bijective {f : α → α} : Surjective f ↔ Bijective f := by
simp [Bijective, injective_iff_surjective]
theorem injective_iff_surjective_of_equiv {f : α → β} (e : α ≃ β) : Injective f ↔ Surjective f :=
have : Injective (e.symm ∘ f) ↔ Surjective (e.symm ∘ f) := injective_iff_surjective
⟨fun hinj => by
simpa [Function.comp] using e.surjective.comp (this.1 (e.symm.injective.comp hinj)),
fun hsurj => by
simpa [Function.comp] using e.injective.comp (this.2 (e.symm.surjective.comp hsurj))⟩
alias ⟨_root_.Function.Injective.bijective_of_finite, _⟩ := injective_iff_bijective
alias ⟨_root_.Function.Surjective.bijective_of_finite, _⟩ := surjective_iff_bijective
|
alias ⟨_root_.Function.Injective.surjective_of_fintype,
_root_.Function.Surjective.injective_of_fintype⟩ :=
injective_iff_surjective_of_equiv
| Mathlib/Data/Fintype/Card.lean | 334 | 337 |
/-
Copyright (c) 2024 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.Lie.Engel
import Mathlib.Algebra.Lie.Normalizer
import Mathlib.Algebra.Lie.OfAssociative
import Mathlib.Algebra.Lie.Subalgebra
import Mathlib.Data.Finset.NatAntidiagonal
/-!
# Engel subalgebras
This file defines Engel subalgebras of a Lie algebra and provides basic related properties.
The Engel subalgebra `LieSubalgebra.Engel R x` consists of
all `y : L` such that `(ad R L x)^n` kills `y` for some `n`.
## Main results
Engel subalgebras are self-normalizing (`LieSubalgebra.normalizer_engel`),
and minimal ones are nilpotent (TODO), hence Cartan subalgebras.
* `LieSubalgebra.normalizer_eq_self_of_engel_le`:
Lie subalgebras containing an Engel subalgebra are self-normalizing,
provided the ambient Lie algebra is Artinian.
* `LieSubalgebra.isNilpotent_of_forall_le_engel`:
A Lie subalgebra of a Noetherian Lie algebra is nilpotent
if it is contained in the Engel subalgebra of all its elements.
-/
open LieAlgebra LieModule
variable {R L M : Type*} [CommRing R] [LieRing L] [LieAlgebra R L]
[AddCommGroup M] [Module R M] [LieRingModule L M] [LieModule R L M]
namespace LieSubalgebra
variable (R)
/-- The Engel subalgebra `Engel R x` consists of
all `y : L` such that `(ad R L x)^n` kills `y` for some `n`.
Engel subalgebras are self-normalizing (`LieSubalgebra.normalizer_engel`),
and minimal ones are nilpotent, hence Cartan subalgebras. -/
@[simps!]
def engel (x : L) : LieSubalgebra R L :=
{ (ad R L x).maxGenEigenspace 0 with
lie_mem' := by
simp only [AddSubsemigroup.mem_carrier, AddSubmonoid.mem_toSubsemigroup,
Submodule.mem_toAddSubmonoid, Module.End.mem_maxGenEigenspace, zero_smul,
sub_zero, forall_exists_index]
intro y z m hm n hn
refine ⟨m + n, ?_⟩
rw [ad_pow_lie]
apply Finset.sum_eq_zero
intro ij hij
obtain (h|h) : m ≤ ij.1 ∨ n ≤ ij.2 := by rw [Finset.mem_antidiagonal] at hij; omega
all_goals simp [Module.End.pow_map_zero_of_le h, hm, hn] }
lemma mem_engel_iff (x y : L) :
y ∈ engel R x ↔ ∃ n : ℕ, ((ad R L x) ^ n) y = 0 :=
(Module.End.mem_maxGenEigenspace _ _ _).trans <| by simp only [zero_smul, sub_zero]
| lemma self_mem_engel (x : L) : x ∈ engel R x := by
simp only [mem_engel_iff]
exact ⟨1, by simp⟩
| Mathlib/Algebra/Lie/EngelSubalgebra.lean | 66 | 68 |
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Algebra.Squarefree.Basic
import Mathlib.FieldTheory.IntermediateField.Basic
import Mathlib.FieldTheory.Minpoly.Field
import Mathlib.RingTheory.Polynomial.Content
import Mathlib.RingTheory.PowerBasis
import Mathlib.Data.ENat.Lattice
/-!
# Separable polynomials
We define a polynomial to be separable if it is coprime with its derivative. We prove basic
properties about separable polynomials here.
## Main definitions
* `Polynomial.Separable f`: a polynomial `f` is separable iff it is coprime with its derivative.
* `IsSeparable K x`: an element `x` is separable over `K` iff the minimal polynomial of `x`
over `K` is separable.
* `Algebra.IsSeparable K L`: `L` is separable over `K` iff every element in `L` is separable
over `K`.
-/
universe u v w
open Polynomial Finset
namespace Polynomial
section CommSemiring
variable {R : Type u} [CommSemiring R] {S : Type v} [CommSemiring S]
/-- A polynomial is separable iff it is coprime with its derivative. -/
@[stacks 09H1 "first part"]
def Separable (f : R[X]) : Prop :=
IsCoprime f (derivative f)
theorem separable_def (f : R[X]) : f.Separable ↔ IsCoprime f (derivative f) :=
Iff.rfl
theorem separable_def' (f : R[X]) : f.Separable ↔ ∃ a b : R[X], a * f + b * (derivative f) = 1 :=
Iff.rfl
theorem not_separable_zero [Nontrivial R] : ¬Separable (0 : R[X]) := by
rintro ⟨x, y, h⟩
simp only [derivative_zero, mul_zero, add_zero, zero_ne_one] at h
theorem Separable.ne_zero [Nontrivial R] {f : R[X]} (h : f.Separable) : f ≠ 0 :=
(not_separable_zero <| · ▸ h)
@[simp]
theorem separable_one : (1 : R[X]).Separable :=
isCoprime_one_left
@[nontriviality]
theorem separable_of_subsingleton [Subsingleton R] (f : R[X]) : f.Separable := by
simp [Separable, IsCoprime, eq_iff_true_of_subsingleton]
theorem separable_X_add_C (a : R) : (X + C a).Separable := by
rw [separable_def, derivative_add, derivative_X, derivative_C, add_zero]
exact isCoprime_one_right
theorem separable_X : (X : R[X]).Separable := by
rw [separable_def, derivative_X]
exact isCoprime_one_right
theorem separable_C (r : R) : (C r).Separable ↔ IsUnit r := by
rw [separable_def, derivative_C, isCoprime_zero_right, isUnit_C]
theorem Separable.of_mul_left {f g : R[X]} (h : (f * g).Separable) : f.Separable := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_left (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_mul_right {f g : R[X]} (h : (f * g).Separable) : g.Separable := by
rw [mul_comm] at h
exact h.of_mul_left
theorem Separable.of_dvd {f g : R[X]} (hf : f.Separable) (hfg : g ∣ f) : g.Separable := by
rcases hfg with ⟨f', rfl⟩
exact Separable.of_mul_left hf
theorem separable_gcd_left {F : Type*} [Field F] [DecidableEq F[X]]
{f : F[X]} (hf : f.Separable) (g : F[X]) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hf (EuclideanDomain.gcd_dvd_left f g)
theorem separable_gcd_right {F : Type*} [Field F] [DecidableEq F[X]]
{g : F[X]} (f : F[X]) (hg : g.Separable) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hg (EuclideanDomain.gcd_dvd_right f g)
theorem Separable.isCoprime {f g : R[X]} (h : (f * g).Separable) : IsCoprime f g := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_right (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_pow' {f : R[X]} :
∀ {n : ℕ} (_h : (f ^ n).Separable), IsUnit f ∨ f.Separable ∧ n = 1 ∨ n = 0
| 0 => fun _h => Or.inr <| Or.inr rfl
| 1 => fun h => Or.inr <| Or.inl ⟨pow_one f ▸ h, rfl⟩
| n + 2 => fun h => by
rw [pow_succ, pow_succ] at h
exact Or.inl (isCoprime_self.1 h.isCoprime.of_mul_left_right)
theorem Separable.of_pow {f : R[X]} (hf : ¬IsUnit f) {n : ℕ} (hn : n ≠ 0)
(hfs : (f ^ n).Separable) : f.Separable ∧ n = 1 :=
(hfs.of_pow'.resolve_left hf).resolve_right hn
theorem Separable.map {p : R[X]} (h : p.Separable) {f : R →+* S} : (p.map f).Separable :=
let ⟨a, b, H⟩ := h
⟨a.map f, b.map f, by
rw [derivative_map, ← Polynomial.map_mul, ← Polynomial.map_mul, ← Polynomial.map_add, H,
Polynomial.map_one]⟩
theorem _root_.Associated.separable {f g : R[X]}
(ha : Associated f g) (h : f.Separable) : g.Separable := by
obtain ⟨⟨u, v, h1, h2⟩, ha⟩ := ha
obtain ⟨a, b, h⟩ := h
refine ⟨a * v + b * derivative v, b * v, ?_⟩
replace h := congr($h * $(h1))
have h3 := congr(derivative $(h1))
simp only [← ha, derivative_mul, derivative_one] at h3 ⊢
calc
_ = (a * f + b * derivative f) * (u * v)
+ (b * f) * (derivative u * v + u * derivative v) := by ring1
_ = 1 := by rw [h, h3]; ring1
theorem _root_.Associated.separable_iff {f g : R[X]}
(ha : Associated f g) : f.Separable ↔ g.Separable := ⟨ha.separable, ha.symm.separable⟩
theorem Separable.mul_unit {f g : R[X]} (hf : f.Separable) (hg : IsUnit g) : (f * g).Separable :=
(associated_mul_unit_right f g hg).separable hf
theorem Separable.unit_mul {f g : R[X]} (hf : IsUnit f) (hg : g.Separable) : (f * g).Separable :=
(associated_unit_mul_right g f hf).separable hg
theorem Separable.eval₂_derivative_ne_zero [Nontrivial S] (f : R →+* S) {p : R[X]}
(h : p.Separable) {x : S} (hx : p.eval₂ f x = 0) :
(derivative p).eval₂ f x ≠ 0 := by
intro hx'
obtain ⟨a, b, e⟩ := h
apply_fun Polynomial.eval₂ f x at e
simp only [eval₂_add, eval₂_mul, hx, mul_zero, hx', add_zero, eval₂_one, zero_ne_one] at e
theorem Separable.aeval_derivative_ne_zero [Nontrivial S] [Algebra R S] {p : R[X]}
(h : p.Separable) {x : S} (hx : aeval x p = 0) :
aeval x (derivative p) ≠ 0 :=
h.eval₂_derivative_ne_zero (algebraMap R S) hx
variable (p q : ℕ)
theorem isUnit_of_self_mul_dvd_separable {p q : R[X]} (hp : p.Separable) (hq : q * q ∣ p) :
IsUnit q := by
obtain ⟨p, rfl⟩ := hq
apply isCoprime_self.mp
have : IsCoprime (q * (q * p))
(q * (derivative q * p + derivative q * p + q * derivative p)) := by
simp only [← mul_assoc, mul_add]
dsimp only [Separable] at hp
convert hp using 1
rw [derivative_mul, derivative_mul]
ring
exact IsCoprime.of_mul_right_left (IsCoprime.of_mul_left_left this)
theorem emultiplicity_le_one_of_separable {p q : R[X]} (hq : ¬IsUnit q) (hsep : Separable p) :
emultiplicity q p ≤ 1 := by
contrapose! hq
apply isUnit_of_self_mul_dvd_separable hsep
rw [← sq]
apply pow_dvd_of_le_emultiplicity
exact Order.add_one_le_of_lt hq
/-- A separable polynomial is square-free.
See `PerfectField.separable_iff_squarefree` for the converse when the coefficients are a perfect
field. -/
theorem Separable.squarefree {p : R[X]} (hsep : Separable p) : Squarefree p := by
classical
rw [squarefree_iff_emultiplicity_le_one p]
exact fun f => or_iff_not_imp_right.mpr fun hunit => emultiplicity_le_one_of_separable hunit hsep
end CommSemiring
section CommRing
variable {R : Type u} [CommRing R]
theorem separable_X_sub_C {x : R} : Separable (X - C x) := by
simpa only [sub_eq_add_neg, C_neg] using separable_X_add_C (-x)
theorem Separable.mul {f g : R[X]} (hf : f.Separable) (hg : g.Separable) (h : IsCoprime f g) :
(f * g).Separable := by
rw [separable_def, derivative_mul]
exact
((hf.mul_right h).add_mul_left_right _).mul_left ((h.symm.mul_right hg).mul_add_right_right _)
theorem separable_prod' {ι : Sort _} {f : ι → R[X]} {s : Finset ι} :
(∀ x ∈ s, ∀ y ∈ s, x ≠ y → IsCoprime (f x) (f y)) →
(∀ x ∈ s, (f x).Separable) → (∏ x ∈ s, f x).Separable := by
classical
exact Finset.induction_on s (fun _ _ => separable_one) fun a s has ih h1 h2 => by
simp_rw [Finset.forall_mem_insert, forall_and] at h1 h2; rw [prod_insert has]
exact
h2.1.mul (ih h1.2.2 h2.2)
(IsCoprime.prod_right fun i his => h1.1.2 i his <| Ne.symm <| ne_of_mem_of_not_mem his has)
open scoped Function in -- required for scoped `on` notation
theorem separable_prod {ι : Sort _} [Fintype ι] {f : ι → R[X]} (h1 : Pairwise (IsCoprime on f))
(h2 : ∀ x, (f x).Separable) : (∏ x, f x).Separable :=
separable_prod' (fun _x _hx _y _hy hxy => h1 hxy) fun x _hx => h2 x
theorem Separable.inj_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} {f : ι → R} {s : Finset ι}
(hfs : (∏ i ∈ s, (X - C (f i))).Separable) {x y : ι} (hx : x ∈ s) (hy : y ∈ s)
(hfxy : f x = f y) : x = y := by
classical
by_contra hxy
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase_of_ne_of_mem (Ne.symm hxy) hy), prod_insert (not_mem_erase _ _), ←
mul_assoc, hfxy, ← sq] at hfs
cases (hfs.of_mul_left.of_pow (not_isUnit_X_sub_C _) two_ne_zero).2
theorem Separable.injective_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} [Fintype ι] {f : ι → R}
(hfs : (∏ i, (X - C (f i))).Separable) : Function.Injective f := fun _x _y hfxy =>
hfs.inj_of_prod_X_sub_C (mem_univ _) (mem_univ _) hfxy
theorem nodup_of_separable_prod [Nontrivial R] {s : Multiset R}
(hs : Separable (Multiset.map (fun a => X - C a) s).prod) : s.Nodup := by
rw [Multiset.nodup_iff_ne_cons_cons]
rintro a t rfl
refine not_isUnit_X_sub_C a (isUnit_of_self_mul_dvd_separable hs ?_)
simpa only [Multiset.map_cons, Multiset.prod_cons] using mul_dvd_mul_left _ (dvd_mul_right _ _)
| /-- If `IsUnit n` in a `CommRing R`, then `X ^ n - u` is separable for any unit `u`. -/
theorem separable_X_pow_sub_C_unit {n : ℕ} (u : Rˣ) (hn : IsUnit (n : R)) :
Separable (X ^ n - C (u : R)) := by
nontriviality R
rcases n.eq_zero_or_pos with (rfl | hpos)
· simp at hn
apply (separable_def' (X ^ n - C (u : R))).2
obtain ⟨n', hn'⟩ := hn.exists_left_inv
| Mathlib/FieldTheory/Separable.lean | 242 | 249 |
/-
Copyright (c) 2022 Frédéric Dupuis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Frédéric Dupuis
-/
import Mathlib.Topology.Algebra.Module.WeakDual
import Mathlib.Algebra.Algebra.Spectrum.Basic
import Mathlib.Topology.ContinuousMap.Algebra
import Mathlib.Data.Set.Lattice
/-!
# Character space of a topological algebra
The character space of a topological algebra is the subset of elements of the weak dual that
are also algebra homomorphisms. This space is used in the Gelfand transform, which gives an
isomorphism between a commutative C⋆-algebra and continuous functions on the character space
of the algebra. This, in turn, is used to construct the continuous functional calculus on
C⋆-algebras.
## Implementation notes
We define `WeakDual.characterSpace 𝕜 A` as a subset of the weak dual, which automatically puts the
correct topology on the space. We then define `WeakDual.CharacterSpace.toAlgHom` which provides the
algebra homomorphism corresponding to any element. We also provide `WeakDual.CharacterSpace.toCLM`
which provides the element as a continuous linear map. (Even though `WeakDual 𝕜 A` is a type copy of
`A →L[𝕜] 𝕜`, this is often more convenient.)
## Tags
character space, Gelfand transform, functional calculus
-/
namespace WeakDual
/-- The character space of a topological algebra is the subset of elements of the weak dual that
are also algebra homomorphisms. -/
def characterSpace (𝕜 : Type*) (A : Type*) [CommSemiring 𝕜] [TopologicalSpace 𝕜] [ContinuousAdd 𝕜]
[ContinuousConstSMul 𝕜 𝕜] [NonUnitalNonAssocSemiring A] [TopologicalSpace A] [Module 𝕜 A] :=
{φ : WeakDual 𝕜 A | φ ≠ 0 ∧ ∀ x y : A, φ (x * y) = φ x * φ y}
variable {𝕜 : Type*} {A : Type*}
-- Even though the capitalization of the namespace differs, it doesn't matter
-- because there is no dot notation since `characterSpace` is only a type via `CoeSort`.
namespace CharacterSpace
section NonUnitalNonAssocSemiring
variable [CommSemiring 𝕜] [TopologicalSpace 𝕜] [ContinuousAdd 𝕜] [ContinuousConstSMul 𝕜 𝕜]
[NonUnitalNonAssocSemiring A] [TopologicalSpace A] [Module 𝕜 A]
instance instFunLike : FunLike (characterSpace 𝕜 A) A 𝕜 where
coe φ := ((φ : WeakDual 𝕜 A) : A → 𝕜)
coe_injective' φ ψ h := by ext1; apply DFunLike.ext; exact congr_fun h
/-- Elements of the character space are continuous linear maps. -/
instance instContinuousLinearMapClass : ContinuousLinearMapClass (characterSpace 𝕜 A) 𝕜 A 𝕜 where
map_smulₛₗ φ := (φ : WeakDual 𝕜 A).map_smul
map_add φ := (φ : WeakDual 𝕜 A).map_add
map_continuous φ := (φ : WeakDual 𝕜 A).cont
-- Porting note: moved because Lean 4 doesn't see the `DFunLike` instance on `characterSpace 𝕜 A`
-- until the `ContinuousLinearMapClass` instance is declared
@[simp, norm_cast]
protected theorem coe_coe (φ : characterSpace 𝕜 A) : ⇑(φ : WeakDual 𝕜 A) = (φ : A → 𝕜) :=
rfl
@[ext]
theorem ext {φ ψ : characterSpace 𝕜 A} (h : ∀ x, φ x = ψ x) : φ = ψ :=
DFunLike.ext _ _ h
/-- An element of the character space, as a continuous linear map. -/
def toCLM (φ : characterSpace 𝕜 A) : A →L[𝕜] 𝕜 :=
(φ : WeakDual 𝕜 A)
@[simp]
theorem coe_toCLM (φ : characterSpace 𝕜 A) : ⇑(toCLM φ) = φ :=
rfl
/-- Elements of the character space are non-unital algebra homomorphisms. -/
instance instNonUnitalAlgHomClass : NonUnitalAlgHomClass (characterSpace 𝕜 A) 𝕜 A 𝕜 :=
{ CharacterSpace.instContinuousLinearMapClass with
map_smulₛₗ := fun φ => map_smul φ
map_zero := fun φ => map_zero φ
map_mul := fun φ => φ.prop.2 }
/-- An element of the character space, as a non-unital algebra homomorphism. -/
def toNonUnitalAlgHom (φ : characterSpace 𝕜 A) : A →ₙₐ[𝕜] 𝕜 where
toFun := (φ : A → 𝕜)
map_mul' := map_mul φ
map_smul' := map_smul φ
map_zero' := map_zero φ
map_add' := map_add φ
@[simp]
theorem coe_toNonUnitalAlgHom (φ : characterSpace 𝕜 A) : ⇑(toNonUnitalAlgHom φ) = φ :=
rfl
instance instIsEmpty [Subsingleton A] : IsEmpty (characterSpace 𝕜 A) :=
⟨fun φ => φ.prop.1 <|
ContinuousLinearMap.ext fun x => by
rw [show x = 0 from Subsingleton.elim x 0, map_zero, map_zero] ⟩
variable (𝕜 A)
theorem union_zero :
characterSpace 𝕜 A ∪ {0} = {φ : WeakDual 𝕜 A | ∀ x y : A, φ (x * y) = φ x * φ y} :=
le_antisymm (by
rintro φ (hφ | rfl)
· exact hφ.2
· exact fun _ _ => by exact (zero_mul (0 : 𝕜)).symm)
fun φ hφ => Or.elim (em <| φ = 0) Or.inr fun h₀ => Or.inl ⟨h₀, hφ⟩
/-- The `characterSpace 𝕜 A` along with `0` is always a closed set in `WeakDual 𝕜 A`. -/
| theorem union_zero_isClosed [T2Space 𝕜] [ContinuousMul 𝕜] :
IsClosed (characterSpace 𝕜 A ∪ {0}) := by
simp only [union_zero, Set.setOf_forall]
exact
isClosed_iInter fun x =>
isClosed_iInter fun y =>
isClosed_eq (eval_continuous _) <| (eval_continuous _).mul (eval_continuous _)
| Mathlib/Topology/Algebra/Module/CharacterSpace.lean | 118 | 124 |
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Integral.FinMeasAdditive
/-!
# Extension of a linear function from indicators to L1
Given `T : Set α → E →L[ℝ] F` with `DominatedFinMeasAdditive μ T C`, we construct an extension
of `T` to integrable simple functions, which are finite sums of indicators of measurable sets
with finite measure, then to integrable functions, which are limits of integrable simple functions.
The main result is a continuous linear map `(α →₁[μ] E) →L[ℝ] F`.
This extension process is used to define the Bochner integral
in the `Mathlib.MeasureTheory.Integral.Bochner.Basic` file
and the conditional expectation of an integrable function
in `Mathlib.MeasureTheory.Function.ConditionalExpectation.CondexpL1`.
## Main definitions
- `setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F`: the extension of `T`
from indicators to L1.
- `setToFun μ T (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F`: a version of the
extension which applies to functions (with value 0 if the function is not integrable).
## Properties
For most properties of `setToFun`, we provide two lemmas. One version uses hypotheses valid on
all sets, like `T = T'`, and a second version which uses a primed name uses hypotheses on
measurable sets with finite measure, like `∀ s, MeasurableSet s → μ s < ∞ → T s = T' s`.
The lemmas listed here don't show all hypotheses. Refer to the actual lemmas for details.
Linearity:
- `setToFun_zero_left : setToFun μ 0 hT f = 0`
- `setToFun_add_left : setToFun μ (T + T') _ f = setToFun μ T hT f + setToFun μ T' hT' f`
- `setToFun_smul_left : setToFun μ (fun s ↦ c • (T s)) (hT.smul c) f = c • setToFun μ T hT f`
- `setToFun_zero : setToFun μ T hT (0 : α → E) = 0`
- `setToFun_neg : setToFun μ T hT (-f) = - setToFun μ T hT f`
If `f` and `g` are integrable:
- `setToFun_add : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g`
- `setToFun_sub : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g`
If `T` is verifies `∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x`:
- `setToFun_smul : setToFun μ T hT (c • f) = c • setToFun μ T hT f`
Other:
- `setToFun_congr_ae (h : f =ᵐ[μ] g) : setToFun μ T hT f = setToFun μ T hT g`
- `setToFun_measure_zero (h : μ = 0) : setToFun μ T hT f = 0`
If the space is also an ordered additive group with an order closed topology and `T` is such that
`0 ≤ T s x` for `0 ≤ x`, we also prove order-related properties:
- `setToFun_mono_left (h : ∀ s x, T s x ≤ T' s x) : setToFun μ T hT f ≤ setToFun μ T' hT' f`
- `setToFun_nonneg (hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f`
- `setToFun_mono (hfg : f ≤ᵐ[μ] g) : setToFun μ T hT f ≤ setToFun μ T hT g`
-/
noncomputable section
open scoped Topology NNReal
open Set Filter TopologicalSpace ENNReal
namespace MeasureTheory
variable {α E F F' G 𝕜 : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [NormedAddCommGroup F'] [NormedSpace ℝ F']
[NormedAddCommGroup G] {m : MeasurableSpace α} {μ : Measure α}
namespace L1
open AEEqFun Lp.simpleFunc Lp
namespace SimpleFunc
theorem norm_eq_sum_mul (f : α →₁ₛ[μ] G) :
‖f‖ = ∑ x ∈ (toSimpleFunc f).range, μ.real (toSimpleFunc f ⁻¹' {x}) * ‖x‖ := by
rw [norm_toSimpleFunc, eLpNorm_one_eq_lintegral_enorm]
have h_eq := SimpleFunc.map_apply (‖·‖ₑ) (toSimpleFunc f)
simp_rw [← h_eq, measureReal_def]
rw [SimpleFunc.lintegral_eq_lintegral, SimpleFunc.map_lintegral, ENNReal.toReal_sum]
· congr
ext1 x
rw [ENNReal.toReal_mul, mul_comm, ← ofReal_norm_eq_enorm,
ENNReal.toReal_ofReal (norm_nonneg _)]
· intro x _
by_cases hx0 : x = 0
· rw [hx0]; simp
· exact
ENNReal.mul_ne_top ENNReal.coe_ne_top
(SimpleFunc.measure_preimage_lt_top_of_integrable _ (SimpleFunc.integrable f) hx0).ne
section SetToL1S
variable [NormedField 𝕜] [NormedSpace 𝕜 E]
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
/-- Extend `Set α → (E →L[ℝ] F')` to `(α →₁ₛ[μ] E) → F'`. -/
def setToL1S (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : F :=
(toSimpleFunc f).setToSimpleFunc T
theorem setToL1S_eq_setToSimpleFunc (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S T f = (toSimpleFunc f).setToSimpleFunc T :=
rfl
@[simp]
theorem setToL1S_zero_left (f : α →₁ₛ[μ] E) : setToL1S (0 : Set α → E →L[ℝ] F) f = 0 :=
SimpleFunc.setToSimpleFunc_zero _
theorem setToL1S_zero_left' {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) : setToL1S T f = 0 :=
SimpleFunc.setToSimpleFunc_zero' h_zero _ (SimpleFunc.integrable f)
theorem setToL1S_congr (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) :
setToL1S T f = setToL1S T g :=
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) h
theorem setToL1S_congr_left (T T' : Set α → E →L[ℝ] F)
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁ₛ[μ] E) :
setToL1S T f = setToL1S T' f :=
SimpleFunc.setToSimpleFunc_congr_left T T' h (simpleFunc.toSimpleFunc f) (SimpleFunc.integrable f)
/-- `setToL1S` does not change if we replace the measure `μ` by `μ'` with `μ ≪ μ'`. The statement
uses two functions `f` and `f'` because they have to belong to different types, but morally these
are the same function (we have `f =ᵐ[μ] f'`). -/
theorem setToL1S_congr_measure {μ' : Measure α} (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hμ : μ ≪ μ')
(f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E) (h : (f : α → E) =ᵐ[μ] f') :
setToL1S T f = setToL1S T f' := by
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) ?_
refine (toSimpleFunc_eq_toFun f).trans ?_
suffices (f' : α → E) =ᵐ[μ] simpleFunc.toSimpleFunc f' from h.trans this
have goal' : (f' : α → E) =ᵐ[μ'] simpleFunc.toSimpleFunc f' := (toSimpleFunc_eq_toFun f').symm
exact hμ.ae_eq goal'
theorem setToL1S_add_left (T T' : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S (T + T') f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left T T'
theorem setToL1S_add_left' (T T' T'' : Set α → E →L[ℝ] F)
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1S T'' f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left' T T' T'' h_add (SimpleFunc.integrable f)
theorem setToL1S_smul_left (T : Set α → E →L[ℝ] F) (c : ℝ) (f : α →₁ₛ[μ] E) :
setToL1S (fun s => c • T s) f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left T c _
theorem setToL1S_smul_left' (T T' : Set α → E →L[ℝ] F) (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1S T' f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left' T T' c h_smul (SimpleFunc.integrable f)
theorem setToL1S_add (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f + g) = setToL1S T f + setToL1S T g := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_add T h_add (SimpleFunc.integrable f)
(SimpleFunc.integrable g)]
exact
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _)
(add_toSimpleFunc f g)
theorem setToL1S_neg {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f : α →₁ₛ[μ] E) : setToL1S T (-f) = -setToL1S T f := by
simp_rw [setToL1S]
have : simpleFunc.toSimpleFunc (-f) =ᵐ[μ] ⇑(-simpleFunc.toSimpleFunc f) :=
neg_toSimpleFunc f
rw [SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) this]
exact SimpleFunc.setToSimpleFunc_neg T h_add (SimpleFunc.integrable f)
theorem setToL1S_sub {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f - g) = setToL1S T f - setToL1S T g := by
rw [sub_eq_add_neg, setToL1S_add T h_zero h_add, setToL1S_neg h_zero h_add, sub_eq_add_neg]
theorem setToL1S_smul_real (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (c : ℝ)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul_real T h_add c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
theorem setToL1S_smul {E} [NormedAddCommGroup E] [NormedSpace ℝ E] [NormedSpace 𝕜 E]
[DistribSMul 𝕜 F] (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul T h_add h_smul c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
theorem norm_setToL1S_le (T : Set α → E →L[ℝ] F) {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * μ.real s) (f : α →₁ₛ[μ] E) :
‖setToL1S T f‖ ≤ C * ‖f‖ := by
rw [setToL1S, norm_eq_sum_mul f]
exact
SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm _
(SimpleFunc.integrable f)
theorem setToL1S_indicatorConst {T : Set α → E →L[ℝ] F} {s : Set α}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T)
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
have h_empty : T ∅ = 0 := h_zero _ MeasurableSet.empty measure_empty
rw [setToL1S_eq_setToSimpleFunc]
refine Eq.trans ?_ (SimpleFunc.setToSimpleFunc_indicator T h_empty hs x)
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact toSimpleFunc_indicatorConst hs hμs.ne x
theorem setToL1S_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) = T univ x :=
setToL1S_indicatorConst h_zero h_add MeasurableSet.univ (measure_lt_top _ _) x
section Order
variable {G'' G' : Type*}
[NormedAddCommGroup G'] [PartialOrder G'] [IsOrderedAddMonoid G'] [NormedSpace ℝ G']
[NormedAddCommGroup G''] [PartialOrder G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G'']
{T : Set α → G'' →L[ℝ] G'}
theorem setToL1S_mono_left {T T' : Set α → E →L[ℝ] G''} (hTT' : ∀ s x, T s x ≤ T' s x)
(f : α →₁ₛ[μ] E) : setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
theorem setToL1S_mono_left' {T T' : Set α → E →L[ℝ] G''}
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
omit [IsOrderedAddMonoid G''] in
theorem setToL1S_nonneg (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G''}
(hf : 0 ≤ f) : 0 ≤ setToL1S T f := by
simp_rw [setToL1S]
obtain ⟨f', hf', hff'⟩ := exists_simpleFunc_nonneg_ae_eq hf
replace hff' : simpleFunc.toSimpleFunc f =ᵐ[μ] f' :=
(Lp.simpleFunc.toSimpleFunc_eq_toFun f).trans hff'
rw [SimpleFunc.setToSimpleFunc_congr _ h_zero h_add (SimpleFunc.integrable _) hff']
exact
SimpleFunc.setToSimpleFunc_nonneg' T hT_nonneg _ hf' ((SimpleFunc.integrable f).congr hff')
theorem setToL1S_mono (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G''}
(hfg : f ≤ g) : setToL1S T f ≤ setToL1S T g := by
rw [← sub_nonneg] at hfg ⊢
rw [← setToL1S_sub h_zero h_add]
exact setToL1S_nonneg h_zero h_add hT_nonneg hfg
end Order
variable [NormedSpace 𝕜 F]
variable (α E μ 𝕜)
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[𝕜] F`. -/
def setToL1SCLM' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁ₛ[μ] E) →L[𝕜] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul T (fun _ => hT.eq_zero_of_measure_zero) hT.1 h_smul⟩
C fun f => norm_setToL1S_le T hT.2 f
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[ℝ] F`. -/
def setToL1SCLM {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
(α →₁ₛ[μ] E) →L[ℝ] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul_real T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩
C fun f => norm_setToL1S_le T hT.2 f
variable {α E μ 𝕜}
variable {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
@[simp]
theorem setToL1SCLM_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left _
theorem setToL1SCLM_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left' h_zero f
theorem setToL1SCLM_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' (fun _ _ _ => by rw [h]) f
theorem setToL1SCLM_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' h f
theorem setToL1SCLM_congr_measure {μ' : Measure α} (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (hμ : μ ≪ μ') (f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E)
(h : (f : α → E) =ᵐ[μ] f') : setToL1SCLM α E μ hT f = setToL1SCLM α E μ' hT' f' :=
setToL1S_congr_measure T (fun _ => hT.eq_zero_of_measure_zero) hT.1 hμ _ _ h
theorem setToL1SCLM_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.add hT') f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left T T' f
theorem setToL1SCLM_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT'' f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left' T T' T'' h_add f
theorem setToL1SCLM_smul_left (c : ℝ) (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.smul c) f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left T c f
theorem setToL1SCLM_smul_left' (c : ℝ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C')
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT' f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left' T T' c h_smul f
theorem norm_setToL1SCLM_le {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hC : 0 ≤ C) : ‖setToL1SCLM α E μ hT‖ ≤ C :=
LinearMap.mkContinuous_norm_le _ hC _
theorem norm_setToL1SCLM_le' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1SCLM α E μ hT‖ ≤ max C 0 :=
LinearMap.mkContinuous_norm_le' _ _
theorem setToL1SCLM_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F} {C : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1SCLM α E μ hT (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) =
T univ x :=
setToL1S_const (fun _ => hT.eq_zero_of_measure_zero) hT.1 x
section Order
variable {G' G'' : Type*}
[NormedAddCommGroup G''] [PartialOrder G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G'']
[NormedAddCommGroup G'] [PartialOrder G'] [IsOrderedAddMonoid G'] [NormedSpace ℝ G']
theorem setToL1SCLM_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
theorem setToL1SCLM_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
omit [IsOrderedAddMonoid G'] in
theorem setToL1SCLM_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1SCLM α G' μ hT f :=
setToL1S_nonneg (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hf
theorem setToL1SCLM_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G'}
(hfg : f ≤ g) : setToL1SCLM α G' μ hT f ≤ setToL1SCLM α G' μ hT g :=
setToL1S_mono (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hfg
end Order
end SetToL1S
end SimpleFunc
open SimpleFunc
section SetToL1
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
variable (𝕜) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F] [CompleteSpace F]
{T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
/-- Extend `Set α → (E →L[ℝ] F)` to `(α →₁[μ] E) →L[𝕜] F`. -/
def setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁[μ] E) →L[𝕜] F :=
(setToL1SCLM' α E 𝕜 μ hT h_smul).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top)
simpleFunc.isUniformInducing
variable {𝕜}
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁[μ] E) →L[ℝ] F`. -/
def setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F :=
(setToL1SCLM α E μ hT).extend (coeToLp α E ℝ) (simpleFunc.denseRange one_ne_top)
simpleFunc.isUniformInducing
theorem setToL1_eq_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1 hT f = setToL1SCLM α E μ hT f :=
uniformly_extend_of_ind simpleFunc.isUniformInducing (simpleFunc.denseRange one_ne_top)
(setToL1SCLM α E μ hT).uniformContinuous _
theorem setToL1_eq_setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (f : α →₁[μ] E) :
setToL1 hT f = setToL1' 𝕜 hT h_smul f :=
rfl
@[simp]
theorem setToL1_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left hT f, ContinuousLinearMap.zero_comp, ContinuousLinearMap.zero_apply]
theorem setToL1_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left' hT h_zero f, ContinuousLinearMap.zero_comp,
ContinuousLinearMap.zero_apply]
theorem setToL1_congr_left (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T')
(f : α →₁[μ] E) : setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM]
exact setToL1SCLM_congr_left hT' hT h.symm f
theorem setToL1_congr_left' (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁[μ] E) :
setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM]
exact (setToL1SCLM_congr_left' hT hT' h f).symm
theorem setToL1_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁[μ] E) :
setToL1 (hT.add hT') f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 (hT.add hT') = setToL1 hT + setToL1 hT' by
rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.add hT')) _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ (hT.add hT') f by
rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM, setToL1SCLM_add_left hT hT']
theorem setToL1_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁[μ] E) :
setToL1 hT'' f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 hT'' = setToL1 hT + setToL1 hT' by rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT'') _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ hT'' f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM,
setToL1SCLM_add_left' hT hT' hT'' h_add]
theorem setToL1_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α →₁[μ] E) :
setToL1 (hT.smul c) f = c • setToL1 hT f := by
suffices setToL1 (hT.smul c) = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.smul c)) _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ (hT.smul c) f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left c hT]
theorem setToL1_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁[μ] E) :
setToL1 hT' f = c • setToL1 hT f := by
suffices setToL1 hT' = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT') _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ hT' f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left' c hT hT' h_smul]
theorem setToL1_smul (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α →₁[μ] E) :
setToL1 hT (c • f) = c • setToL1 hT f := by
rw [setToL1_eq_setToL1' hT h_smul, setToL1_eq_setToL1' hT h_smul]
exact ContinuousLinearMap.map_smul _ _ _
theorem setToL1_simpleFunc_indicatorConst (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1 hT (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
rw [setToL1_eq_setToL1SCLM]
exact setToL1S_indicatorConst (fun s => hT.eq_zero_of_measure_zero) hT.1 hs hμs x
theorem setToL1_indicatorConstLp (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToL1 hT (indicatorConstLp 1 hs hμs x) = T s x := by
rw [← Lp.simpleFunc.coe_indicatorConst hs hμs x]
exact setToL1_simpleFunc_indicatorConst hT hs hμs.lt_top x
theorem setToL1_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1 hT (indicatorConstLp 1 MeasurableSet.univ (measure_ne_top _ _) x) = T univ x :=
setToL1_indicatorConstLp hT MeasurableSet.univ (measure_ne_top _ _) x
section Order
variable {G' G'' : Type*}
[NormedAddCommGroup G''] [PartialOrder G''] [OrderClosedTopology G''] [IsOrderedAddMonoid G'']
[NormedSpace ℝ G''] [CompleteSpace G'']
[NormedAddCommGroup G'] [PartialOrder G'] [NormedSpace ℝ G']
theorem setToL1_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁[μ] E) :
setToL1 hT f ≤ setToL1 hT' f := by
induction f using Lp.induction (hp_ne_top := one_ne_top) with
| @indicatorConst c s hs hμs =>
rw [setToL1_simpleFunc_indicatorConst hT hs hμs, setToL1_simpleFunc_indicatorConst hT' hs hμs]
exact hTT' s hs hμs c
| @add f g hf hg _ hf_le hg_le =>
rw [(setToL1 hT).map_add, (setToL1 hT').map_add]
exact add_le_add hf_le hg_le
| isClosed => exact isClosed_le (setToL1 hT).continuous (setToL1 hT').continuous
theorem setToL1_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToL1 hT f ≤ setToL1 hT' f :=
setToL1_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
theorem setToL1_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1 hT f := by
suffices ∀ f : { g : α →₁[μ] G' // 0 ≤ g }, 0 ≤ setToL1 hT f from
this (⟨f, hf⟩ : { g : α →₁[μ] G' // 0 ≤ g })
refine fun g =>
@isClosed_property { g : α →₁ₛ[μ] G' // 0 ≤ g } { g : α →₁[μ] G' // 0 ≤ g } _ _
(fun g => 0 ≤ setToL1 hT g)
(denseRange_coeSimpleFuncNonnegToLpNonneg 1 μ G' one_ne_top) ?_ ?_ g
· exact isClosed_le continuous_zero ((setToL1 hT).continuous.comp continuous_induced_dom)
· intro g
have : (coeSimpleFuncNonnegToLpNonneg 1 μ G' g : α →₁[μ] G') = (g : α →₁ₛ[μ] G') := rfl
rw [this, setToL1_eq_setToL1SCLM]
exact setToL1S_nonneg (fun s => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg g.2
theorem setToL1_mono [IsOrderedAddMonoid G']
{T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁[μ] G'}
(hfg : f ≤ g) : setToL1 hT f ≤ setToL1 hT g := by
rw [← sub_nonneg] at hfg ⊢
rw [← (setToL1 hT).map_sub]
exact setToL1_nonneg hT hT_nonneg hfg
end Order
theorem norm_setToL1_le_norm_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1 hT‖ ≤ ‖setToL1SCLM α E μ hT‖ :=
calc
‖setToL1 hT‖ ≤ (1 : ℝ≥0) * ‖setToL1SCLM α E μ hT‖ := by
refine
ContinuousLinearMap.opNorm_extend_le (setToL1SCLM α E μ hT) (coeToLp α E ℝ)
(simpleFunc.denseRange one_ne_top) fun x => le_of_eq ?_
rw [NNReal.coe_one, one_mul]
simp [coeToLp]
_ = ‖setToL1SCLM α E μ hT‖ := by rw [NNReal.coe_one, one_mul]
theorem norm_setToL1_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C)
(f : α →₁[μ] E) : ‖setToL1 hT f‖ ≤ C * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ C * ‖f‖ := mul_le_mul (norm_setToL1SCLM_le hT hC) le_rfl (norm_nonneg _) hC
theorem norm_setToL1_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
‖setToL1 hT f‖ ≤ max C 0 * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ max C 0 * ‖f‖ :=
mul_le_mul (norm_setToL1SCLM_le' hT) le_rfl (norm_nonneg _) (le_max_right _ _)
theorem norm_setToL1_le (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : ‖setToL1 hT‖ ≤ C :=
ContinuousLinearMap.opNorm_le_bound _ hC (norm_setToL1_le_mul_norm hT hC)
theorem norm_setToL1_le' (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1 hT‖ ≤ max C 0 :=
ContinuousLinearMap.opNorm_le_bound _ (le_max_right _ _) (norm_setToL1_le_mul_norm' hT)
theorem setToL1_lipschitz (hT : DominatedFinMeasAdditive μ T C) :
LipschitzWith (Real.toNNReal C) (setToL1 hT) :=
(setToL1 hT).lipschitz.weaken (norm_setToL1_le' hT)
/-- If `fs i → f` in `L1`, then `setToL1 hT (fs i) → setToL1 hT f`. -/
theorem tendsto_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) {ι}
(fs : ι → α →₁[μ] E) {l : Filter ι} (hfs : Tendsto fs l (𝓝 f)) :
Tendsto (fun i => setToL1 hT (fs i)) l (𝓝 <| setToL1 hT f) :=
((setToL1 hT).continuous.tendsto _).comp hfs
end SetToL1
end L1
section Function
variable [CompleteSpace F] {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} {f g : α → E}
variable (μ T)
open Classical in
/-- Extend `T : Set α → E →L[ℝ] F` to `(α → E) → F` (for integrable functions `α → E`). We set it to
0 if the function is not integrable. -/
def setToFun (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F :=
if hf : Integrable f μ then L1.setToL1 hT (hf.toL1 f) else 0
variable {μ T}
theorem setToFun_eq (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT f = L1.setToL1 hT (hf.toL1 f) :=
dif_pos hf
theorem L1.setToFun_eq_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
setToFun μ T hT f = L1.setToL1 hT f := by
rw [setToFun_eq hT (L1.integrable_coeFn f), Integrable.toL1_coeFn]
theorem setToFun_undef (hT : DominatedFinMeasAdditive μ T C) (hf : ¬Integrable f μ) :
setToFun μ T hT f = 0 :=
dif_neg hf
theorem setToFun_non_aestronglyMeasurable (hT : DominatedFinMeasAdditive μ T C)
(hf : ¬AEStronglyMeasurable f μ) : setToFun μ T hT f = 0 :=
setToFun_undef hT (not_and_of_not_left _ hf)
@[deprecated (since := "2025-04-09")]
alias setToFun_non_aEStronglyMeasurable := setToFun_non_aestronglyMeasurable
theorem setToFun_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α → E) :
setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
theorem setToFun_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α → E) : setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left' T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
theorem setToFun_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α → E) :
setToFun μ (T + T') (hT.add hT') f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left hT hT']
· simp_rw [setToFun_undef _ hf, add_zero]
theorem setToFun_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α → E) :
setToFun μ T'' hT'' f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left' hT hT' hT'' h_add]
· simp_rw [setToFun_undef _ hf, add_zero]
theorem setToFun_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α → E) :
setToFun μ (fun s => c • T s) (hT.smul c) f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left hT c]
· simp_rw [setToFun_undef _ hf, smul_zero]
theorem setToFun_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α → E) :
setToFun μ T' hT' f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left' hT hT' c h_smul]
· simp_rw [setToFun_undef _ hf, smul_zero]
@[simp]
theorem setToFun_zero (hT : DominatedFinMeasAdditive μ T C) : setToFun μ T hT (0 : α → E) = 0 := by
rw [Pi.zero_def, setToFun_eq hT (integrable_zero _ _ _)]
simp only [← Pi.zero_def]
rw [Integrable.toL1_zero, ContinuousLinearMap.map_zero]
@[simp]
theorem setToFun_zero_left {hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C} :
setToFun μ 0 hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left hT _
· exact setToFun_undef hT hf
theorem setToFun_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) : setToFun μ T hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left' hT h_zero _
· exact setToFun_undef hT hf
theorem setToFun_add (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g := by
rw [setToFun_eq hT (hf.add hg), setToFun_eq hT hf, setToFun_eq hT hg, Integrable.toL1_add,
(L1.setToL1 hT).map_add]
theorem setToFun_finset_sum' (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι)
{f : ι → α → E} (hf : ∀ i ∈ s, Integrable (f i) μ) :
setToFun μ T hT (∑ i ∈ s, f i) = ∑ i ∈ s, setToFun μ T hT (f i) := by
classical
revert hf
refine Finset.induction_on s ?_ ?_
· intro _
simp only [setToFun_zero, Finset.sum_empty]
· intro i s his ih hf
simp only [his, Finset.sum_insert, not_false_iff]
rw [setToFun_add hT (hf i (Finset.mem_insert_self i s)) _]
· rw [ih fun i hi => hf i (Finset.mem_insert_of_mem hi)]
· convert integrable_finset_sum s fun i hi => hf i (Finset.mem_insert_of_mem hi) with x
simp
theorem setToFun_finset_sum (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι) {f : ι → α → E}
(hf : ∀ i ∈ s, Integrable (f i) μ) :
(setToFun μ T hT fun a => ∑ i ∈ s, f i a) = ∑ i ∈ s, setToFun μ T hT (f i) := by
convert setToFun_finset_sum' hT s hf with a; simp
theorem setToFun_neg (hT : DominatedFinMeasAdditive μ T C) (f : α → E) :
setToFun μ T hT (-f) = -setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT hf.neg, Integrable.toL1_neg,
(L1.setToL1 hT).map_neg]
· rw [setToFun_undef hT hf, setToFun_undef hT, neg_zero]
rwa [← integrable_neg_iff] at hf
theorem setToFun_sub (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g := by
rw [sub_eq_add_neg, sub_eq_add_neg, setToFun_add hT hf hg.neg, setToFun_neg hT g]
theorem setToFun_smul [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F]
(hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α → E) : setToFun μ T hT (c • f) = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT, Integrable.toL1_smul',
L1.setToL1_smul hT h_smul c _]
· by_cases hr : c = 0
· rw [hr]; simp
· have hf' : ¬Integrable (c • f) μ := by rwa [integrable_smul_iff hr f]
rw [setToFun_undef hT hf, setToFun_undef hT hf', smul_zero]
theorem setToFun_congr_ae (hT : DominatedFinMeasAdditive μ T C) (h : f =ᵐ[μ] g) :
setToFun μ T hT f = setToFun μ T hT g := by
by_cases hfi : Integrable f μ
· have hgi : Integrable g μ := hfi.congr h
rw [setToFun_eq hT hfi, setToFun_eq hT hgi, (Integrable.toL1_eq_toL1_iff f g hfi hgi).2 h]
· have hgi : ¬Integrable g μ := by rw [integrable_congr h] at hfi; exact hfi
rw [setToFun_undef hT hfi, setToFun_undef hT hgi]
theorem setToFun_measure_zero (hT : DominatedFinMeasAdditive μ T C) (h : μ = 0) :
setToFun μ T hT f = 0 := by
have : f =ᵐ[μ] 0 := by simp [h, EventuallyEq]
rw [setToFun_congr_ae hT this, setToFun_zero]
theorem setToFun_measure_zero' (hT : DominatedFinMeasAdditive μ T C)
(h : ∀ s, MeasurableSet s → μ s < ∞ → μ s = 0) : setToFun μ T hT f = 0 :=
setToFun_zero_left' hT fun s hs hμs => hT.eq_zero_of_measure_zero hs (h s hs hμs)
theorem setToFun_toL1 (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT (hf.toL1 f) = setToFun μ T hT f :=
setToFun_congr_ae hT hf.coeFn_toL1
theorem setToFun_indicator_const (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToFun μ T hT (s.indicator fun _ => x) = T s x := by
rw [setToFun_congr_ae hT (@indicatorConstLp_coeFn _ _ _ 1 _ _ _ hs hμs x).symm]
rw [L1.setToFun_eq_setToL1 hT]
exact L1.setToL1_indicatorConstLp hT hs hμs x
theorem setToFun_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
(setToFun μ T hT fun _ => x) = T univ x := by
have : (fun _ : α => x) = Set.indicator univ fun _ => x := (indicator_univ _).symm
rw [this]
exact setToFun_indicator_const hT MeasurableSet.univ (measure_ne_top _ _) x
section Order
variable {G' G'' : Type*}
[NormedAddCommGroup G''] [PartialOrder G''] [OrderClosedTopology G''] [IsOrderedAddMonoid G'']
[NormedSpace ℝ G''] [CompleteSpace G'']
[NormedAddCommGroup G'] [PartialOrder G'] [NormedSpace ℝ G']
theorem setToFun_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α → E) :
setToFun μ T hT f ≤ setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf]; exact L1.setToL1_mono_left' hT hT' hTT' _
· simp_rw [setToFun_undef _ hf, le_rfl]
theorem setToFun_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToFun μ T hT f ≤ setToFun μ T' hT' f :=
setToFun_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
theorem setToFun_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α → G'}
(hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f := by
by_cases hfi : Integrable f μ
· simp_rw [setToFun_eq _ hfi]
refine L1.setToL1_nonneg hT hT_nonneg ?_
rw [← Lp.coeFn_le]
have h0 := Lp.coeFn_zero G' 1 μ
have h := Integrable.coeFn_toL1 hfi
filter_upwards [h0, h, hf] with _ h0a ha hfa
rw [h0a, ha]
exact hfa
· simp_rw [setToFun_undef _ hfi, le_rfl]
theorem setToFun_mono [IsOrderedAddMonoid G']
{T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α → G'}
(hf : Integrable f μ) (hg : Integrable g μ) (hfg : f ≤ᵐ[μ] g) :
setToFun μ T hT f ≤ setToFun μ T hT g := by
rw [← sub_nonneg, ← setToFun_sub hT hg hf]
refine setToFun_nonneg hT hT_nonneg (hfg.mono fun a ha => ?_)
rw [Pi.sub_apply, Pi.zero_apply, sub_nonneg]
exact ha
end Order
@[continuity]
theorem continuous_setToFun (hT : DominatedFinMeasAdditive μ T C) :
Continuous fun f : α →₁[μ] E => setToFun μ T hT f := by
simp_rw [L1.setToFun_eq_setToL1 hT]; exact ContinuousLinearMap.continuous _
/-- If `F i → f` in `L1`, then `setToFun μ T hT (F i) → setToFun μ T hT f`. -/
theorem tendsto_setToFun_of_L1 (hT : DominatedFinMeasAdditive μ T C) {ι} (f : α → E)
(hfi : Integrable f μ) {fs : ι → α → E} {l : Filter ι} (hfsi : ∀ᶠ i in l, Integrable (fs i) μ)
(hfs : Tendsto (fun i => ∫⁻ x, ‖fs i x - f x‖ₑ ∂μ) l (𝓝 0)) :
Tendsto (fun i => setToFun μ T hT (fs i)) l (𝓝 <| setToFun μ T hT f) := by
classical
let f_lp := hfi.toL1 f
let F_lp i := if hFi : Integrable (fs i) μ then hFi.toL1 (fs i) else 0
have tendsto_L1 : Tendsto F_lp l (𝓝 f_lp) := by
rw [Lp.tendsto_Lp_iff_tendsto_eLpNorm']
simp_rw [eLpNorm_one_eq_lintegral_enorm, Pi.sub_apply]
refine (tendsto_congr' ?_).mp hfs
filter_upwards [hfsi] with i hi
refine lintegral_congr_ae ?_
filter_upwards [hi.coeFn_toL1, hfi.coeFn_toL1] with x hxi hxf
simp_rw [F_lp, dif_pos hi, hxi, f_lp, hxf]
suffices Tendsto (fun i => setToFun μ T hT (F_lp i)) l (𝓝 (setToFun μ T hT f)) by
refine (tendsto_congr' ?_).mp this
filter_upwards [hfsi] with i hi
suffices h_ae_eq : F_lp i =ᵐ[μ] fs i from setToFun_congr_ae hT h_ae_eq
simp_rw [F_lp, dif_pos hi]
exact hi.coeFn_toL1
rw [setToFun_congr_ae hT hfi.coeFn_toL1.symm]
exact ((continuous_setToFun hT).tendsto f_lp).comp tendsto_L1
theorem tendsto_setToFun_approxOn_of_measurable (hT : DominatedFinMeasAdditive μ T C)
[MeasurableSpace E] [BorelSpace E] {f : α → E} {s : Set E} [SeparableSpace s]
(hfi : Integrable f μ) (hfm : Measurable f) (hs : ∀ᵐ x ∂μ, f x ∈ closure s) {y₀ : E}
(h₀ : y₀ ∈ s) (h₀i : Integrable (fun _ => y₀) μ) :
Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f hfm s y₀ h₀ n)) atTop
(𝓝 <| setToFun μ T hT f) :=
tendsto_setToFun_of_L1 hT _ hfi
(Eventually.of_forall (SimpleFunc.integrable_approxOn hfm hfi h₀ h₀i))
(SimpleFunc.tendsto_approxOn_L1_enorm hfm _ hs (hfi.sub h₀i).2)
theorem tendsto_setToFun_approxOn_of_measurable_of_range_subset
(hT : DominatedFinMeasAdditive μ T C) [MeasurableSpace E] [BorelSpace E] {f : α → E}
(fmeas : Measurable f) (hf : Integrable f μ) (s : Set E) [SeparableSpace s]
(hs : range f ∪ {0} ⊆ s) :
Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f fmeas s 0 (hs <| by simp) n)) atTop
(𝓝 <| setToFun μ T hT f) := by
refine tendsto_setToFun_approxOn_of_measurable hT hf fmeas ?_ _ (integrable_zero _ _ _)
exact Eventually.of_forall fun x => subset_closure (hs (Set.mem_union_left _ (mem_range_self _)))
/-- Auxiliary lemma for `setToFun_congr_measure`: the function sending `f : α →₁[μ] G` to
`f : α →₁[μ'] G` is continuous when `μ' ≤ c' • μ` for `c' ≠ ∞`. -/
theorem continuous_L1_toL1 {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞) (hμ'_le : μ' ≤ c' • μ) :
Continuous fun f : α →₁[μ] G =>
(Integrable.of_measure_le_smul hc' hμ'_le (L1.integrable_coeFn f)).toL1 f := by
by_cases hc'0 : c' = 0
· have hμ'0 : μ' = 0 := by rw [← Measure.nonpos_iff_eq_zero']; refine hμ'_le.trans ?_; simp [hc'0]
have h_im_zero :
(fun f : α →₁[μ] G =>
(Integrable.of_measure_le_smul hc' hμ'_le (L1.integrable_coeFn f)).toL1 f) =
0 := by
ext1 f; ext1; simp_rw [hμ'0]; simp only [ae_zero, EventuallyEq, eventually_bot]
rw [h_im_zero]
exact continuous_zero
rw [Metric.continuous_iff]
intro f ε hε_pos
use ε / 2 / c'.toReal
refine ⟨div_pos (half_pos hε_pos) (toReal_pos hc'0 hc'), ?_⟩
intro g hfg
rw [Lp.dist_def] at hfg ⊢
let h_int := fun f' : α →₁[μ] G => (L1.integrable_coeFn f').of_measure_le_smul hc' hμ'_le
have :
eLpNorm (⇑(Integrable.toL1 g (h_int g)) - ⇑(Integrable.toL1 f (h_int f))) 1 μ' =
eLpNorm (⇑g - ⇑f) 1 μ' :=
eLpNorm_congr_ae ((Integrable.coeFn_toL1 _).sub (Integrable.coeFn_toL1 _))
rw [this]
have h_eLpNorm_ne_top : eLpNorm (⇑g - ⇑f) 1 μ ≠ ∞ := by
rw [← eLpNorm_congr_ae (Lp.coeFn_sub _ _)]; exact Lp.eLpNorm_ne_top _
calc
(eLpNorm (⇑g - ⇑f) 1 μ').toReal ≤ (c' * eLpNorm (⇑g - ⇑f) 1 μ).toReal := by
refine toReal_mono (ENNReal.mul_ne_top hc' h_eLpNorm_ne_top) ?_
refine (eLpNorm_mono_measure (⇑g - ⇑f) hμ'_le).trans_eq ?_
rw [eLpNorm_smul_measure_of_ne_zero hc'0, smul_eq_mul]
simp
_ = c'.toReal * (eLpNorm (⇑g - ⇑f) 1 μ).toReal := toReal_mul
_ ≤ c'.toReal * (ε / 2 / c'.toReal) := by gcongr
_ = ε / 2 := by
refine mul_div_cancel₀ (ε / 2) ?_; rw [Ne, toReal_eq_zero_iff]; simp [hc', hc'0]
_ < ε := half_lt_self hε_pos
theorem setToFun_congr_measure_of_integrable {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞)
(hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) (hfμ : Integrable f μ) :
setToFun μ T hT f = setToFun μ' T hT' f := by
-- integrability for `μ` implies integrability for `μ'`.
have h_int : ∀ g : α → E, Integrable g μ → Integrable g μ' := fun g hg =>
Integrable.of_measure_le_smul hc' hμ'_le hg
-- We use `Integrable.induction`
apply hfμ.induction (P := fun f => setToFun μ T hT f = setToFun μ' T hT' f)
· intro c s hs hμs
have hμ's : μ' s ≠ ∞ := by
refine ((hμ'_le s).trans_lt ?_).ne
rw [Measure.smul_apply, smul_eq_mul]
exact ENNReal.mul_lt_top hc'.lt_top hμs
rw [setToFun_indicator_const hT hs hμs.ne, setToFun_indicator_const hT' hs hμ's]
· intro f₂ g₂ _ hf₂ hg₂ h_eq_f h_eq_g
rw [setToFun_add hT hf₂ hg₂, setToFun_add hT' (h_int f₂ hf₂) (h_int g₂ hg₂), h_eq_f, h_eq_g]
· refine isClosed_eq (continuous_setToFun hT) ?_
have :
(fun f : α →₁[μ] E => setToFun μ' T hT' f) = fun f : α →₁[μ] E =>
setToFun μ' T hT' ((h_int f (L1.integrable_coeFn f)).toL1 f) := by
ext1 f; exact setToFun_congr_ae hT' (Integrable.coeFn_toL1 _).symm
rw [this]
exact (continuous_setToFun hT').comp (continuous_L1_toL1 c' hc' hμ'_le)
· intro f₂ g₂ hfg _ hf_eq
have hfg' : f₂ =ᵐ[μ'] g₂ := (Measure.absolutelyContinuous_of_le_smul hμ'_le).ae_eq hfg
rw [← setToFun_congr_ae hT hfg, hf_eq, setToFun_congr_ae hT' hfg']
theorem setToFun_congr_measure {μ' : Measure α} (c c' : ℝ≥0∞) (hc : c ≠ ∞) (hc' : c' ≠ ∞)
(hμ_le : μ ≤ c • μ') (hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) :
setToFun μ T hT f = setToFun μ' T hT' f := by
by_cases hf : Integrable f μ
· exact setToFun_congr_measure_of_integrable c' hc' hμ'_le hT hT' f hf
· -- if `f` is not integrable, both `setToFun` are 0.
have h_int : ∀ g : α → E, ¬Integrable g μ → ¬Integrable g μ' := fun g =>
mt fun h => h.of_measure_le_smul hc hμ_le
simp_rw [setToFun_undef _ hf, setToFun_undef _ (h_int f hf)]
theorem setToFun_congr_measure_of_add_right {μ' : Measure α}
(hT_add : DominatedFinMeasAdditive (μ + μ') T C') (hT : DominatedFinMeasAdditive μ T C)
(f : α → E) (hf : Integrable f (μ + μ')) :
setToFun (μ + μ') T hT_add f = setToFun μ T hT f := by
refine setToFun_congr_measure_of_integrable 1 one_ne_top ?_ hT_add hT f hf
rw [one_smul]
nth_rw 1 [← add_zero μ]
exact add_le_add le_rfl bot_le
theorem setToFun_congr_measure_of_add_left {μ' : Measure α}
(hT_add : DominatedFinMeasAdditive (μ + μ') T C') (hT : DominatedFinMeasAdditive μ' T C)
(f : α → E) (hf : Integrable f (μ + μ')) :
setToFun (μ + μ') T hT_add f = setToFun μ' T hT f := by
refine setToFun_congr_measure_of_integrable 1 one_ne_top ?_ hT_add hT f hf
rw [one_smul]
nth_rw 1 [← zero_add μ']
exact add_le_add_right bot_le μ'
theorem setToFun_top_smul_measure (hT : DominatedFinMeasAdditive (∞ • μ) T C) (f : α → E) :
setToFun (∞ • μ) T hT f = 0 := by
refine setToFun_measure_zero' hT fun s _ hμs => ?_
rw [lt_top_iff_ne_top] at hμs
simp only [true_and, Measure.smul_apply, ENNReal.mul_eq_top, eq_self_iff_true,
top_ne_zero, Ne, not_false_iff, not_or, Classical.not_not, smul_eq_mul] at hμs
simp only [hμs.right, Measure.smul_apply, mul_zero, smul_eq_mul]
theorem setToFun_congr_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞)
(hT : DominatedFinMeasAdditive μ T C) (hT_smul : DominatedFinMeasAdditive (c • μ) T C')
(f : α → E) : setToFun μ T hT f = setToFun (c • μ) T hT_smul f := by
by_cases hc0 : c = 0
· simp [hc0] at hT_smul
have h : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0 := fun s hs _ => hT_smul.eq_zero hs
rw [setToFun_zero_left' _ h, setToFun_measure_zero]
simp [hc0]
refine setToFun_congr_measure c⁻¹ c ?_ hc_ne_top (le_of_eq ?_) le_rfl hT hT_smul f
· simp [hc0]
· rw [smul_smul, ENNReal.inv_mul_cancel hc0 hc_ne_top, one_smul]
theorem norm_setToFun_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E)
(hC : 0 ≤ C) : ‖setToFun μ T hT f‖ ≤ C * ‖f‖ := by
rw [L1.setToFun_eq_setToL1]; exact L1.norm_setToL1_le_mul_norm hT hC f
theorem norm_setToFun_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
‖setToFun μ T hT f‖ ≤ max C 0 * ‖f‖ := by
rw [L1.setToFun_eq_setToL1]; exact L1.norm_setToL1_le_mul_norm' hT f
theorem norm_setToFun_le (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) (hC : 0 ≤ C) :
‖setToFun μ T hT f‖ ≤ C * ‖hf.toL1 f‖ := by
rw [setToFun_eq hT hf]; exact L1.norm_setToL1_le_mul_norm hT hC _
theorem norm_setToFun_le' (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
‖setToFun μ T hT f‖ ≤ max C 0 * ‖hf.toL1 f‖ := by
rw [setToFun_eq hT hf]; exact L1.norm_setToL1_le_mul_norm' hT _
/-- Lebesgue dominated convergence theorem provides sufficient conditions under which almost
everywhere convergence of a sequence of functions implies the convergence of their image by
`setToFun`.
We could weaken the condition `bound_integrable` to require `HasFiniteIntegral bound μ` instead
(i.e. not requiring that `bound` is measurable), but in all applications proving integrability
is easier. -/
theorem tendsto_setToFun_of_dominated_convergence (hT : DominatedFinMeasAdditive μ T C)
{fs : ℕ → α → E} {f : α → E} (bound : α → ℝ)
(fs_measurable : ∀ n, AEStronglyMeasurable (fs n) μ) (bound_integrable : Integrable bound μ)
(h_bound : ∀ n, ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => fs n a) atTop (𝓝 (f a))) :
Tendsto (fun n => setToFun μ T hT (fs n)) atTop (𝓝 <| setToFun μ T hT f) := by
-- `f` is a.e.-measurable, since it is the a.e.-pointwise limit of a.e.-measurable functions.
have f_measurable : AEStronglyMeasurable f μ :=
aestronglyMeasurable_of_tendsto_ae _ fs_measurable h_lim
-- all functions we consider are integrable
have fs_int : ∀ n, Integrable (fs n) μ := fun n =>
bound_integrable.mono' (fs_measurable n) (h_bound _)
have f_int : Integrable f μ :=
⟨f_measurable,
hasFiniteIntegral_of_dominated_convergence bound_integrable.hasFiniteIntegral h_bound
h_lim⟩
-- it suffices to prove the result for the corresponding L1 functions
suffices
Tendsto (fun n => L1.setToL1 hT ((fs_int n).toL1 (fs n))) atTop
(𝓝 (L1.setToL1 hT (f_int.toL1 f))) by
convert this with n
· exact setToFun_eq hT (fs_int n)
· exact setToFun_eq hT f_int
-- the convergence of setToL1 follows from the convergence of the L1 functions
refine L1.tendsto_setToL1 hT _ _ ?_
-- up to some rewriting, what we need to prove is `h_lim`
rw [tendsto_iff_norm_sub_tendsto_zero]
have lintegral_norm_tendsto_zero :
Tendsto (fun n => ENNReal.toReal <| ∫⁻ a, ENNReal.ofReal ‖fs n a - f a‖ ∂μ) atTop (𝓝 0) :=
(tendsto_toReal zero_ne_top).comp
(tendsto_lintegral_norm_of_dominated_convergence fs_measurable
bound_integrable.hasFiniteIntegral h_bound h_lim)
convert lintegral_norm_tendsto_zero with n
rw [L1.norm_def]
congr 1
refine lintegral_congr_ae ?_
rw [← Integrable.toL1_sub]
refine ((fs_int n).sub f_int).coeFn_toL1.mono fun x hx => ?_
dsimp only
rw [hx, ofReal_norm_eq_enorm, Pi.sub_apply]
/-- Lebesgue dominated convergence theorem for filters with a countable basis -/
theorem tendsto_setToFun_filter_of_dominated_convergence (hT : DominatedFinMeasAdditive μ T C) {ι}
{l : Filter ι} [l.IsCountablyGenerated] {fs : ι → α → E} {f : α → E} (bound : α → ℝ)
(hfs_meas : ∀ᶠ n in l, AEStronglyMeasurable (fs n) μ)
(h_bound : ∀ᶠ n in l, ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => fs n a) l (𝓝 (f a))) :
Tendsto (fun n => setToFun μ T hT (fs n)) l (𝓝 <| setToFun μ T hT f) := by
rw [tendsto_iff_seq_tendsto]
intro x xl
have hxl : ∀ s ∈ l, ∃ a, ∀ b ≥ a, x b ∈ s := by rwa [tendsto_atTop'] at xl
have h :
{ x : ι | (fun n => AEStronglyMeasurable (fs n) μ) x } ∩
{ x : ι | (fun n => ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) x } ∈ l :=
inter_mem hfs_meas h_bound
obtain ⟨k, h⟩ := hxl _ h
rw [← tendsto_add_atTop_iff_nat k]
refine tendsto_setToFun_of_dominated_convergence hT bound ?_ bound_integrable ?_ ?_
· exact fun n => (h _ (self_le_add_left _ _)).1
| · exact fun n => (h _ (self_le_add_left _ _)).2
· filter_upwards [h_lim]
refine fun a h_lin => @Tendsto.comp _ _ _ (fun n => x (n + k)) (fun n => fs n a) _ _ _ h_lin ?_
rwa [tendsto_add_atTop_iff_nat]
variable {X : Type*} [TopologicalSpace X] [FirstCountableTopology X]
theorem continuousWithinAt_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C)
{fs : X → α → E} {x₀ : X} {bound : α → ℝ} {s : Set X}
(hfs_meas : ∀ᶠ x in 𝓝[s] x₀, AEStronglyMeasurable (fs x) μ)
| Mathlib/MeasureTheory/Integral/SetToL1.lean | 1,077 | 1,086 |
/-
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, Kim Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Degree.Domain
import Mathlib.Algebra.Polynomial.Degree.Support
import Mathlib.Algebra.Polynomial.Eval.Coeff
import Mathlib.GroupTheory.GroupAction.Ring
/-!
# The derivative map on polynomials
## Main definitions
* `Polynomial.derivative`: The formal derivative of polynomials, expressed as a linear map.
* `Polynomial.derivativeFinsupp`: Iterated derivatives as a finite support function.
-/
noncomputable section
open Finset
open Polynomial
open scoped Nat
namespace Polynomial
universe u v w y z
variable {R : Type u} {S : Type v} {T : Type w} {ι : Type y} {A : Type z} {a b : R} {n : ℕ}
section Derivative
section Semiring
variable [Semiring R]
/-- `derivative p` is the formal derivative of the polynomial `p` -/
def derivative : R[X] →ₗ[R] R[X] where
toFun p := p.sum fun n a => C (a * n) * X ^ (n - 1)
map_add' p q := by
rw [sum_add_index] <;>
simp only [add_mul, forall_const, RingHom.map_add, eq_self_iff_true, zero_mul,
RingHom.map_zero]
map_smul' a p := by
dsimp; rw [sum_smul_index] <;>
simp only [mul_sum, ← C_mul', mul_assoc, coeff_C_mul, RingHom.map_mul, forall_const, zero_mul,
RingHom.map_zero, sum]
theorem derivative_apply (p : R[X]) : derivative p = p.sum fun n a => C (a * n) * X ^ (n - 1) :=
rfl
theorem coeff_derivative (p : R[X]) (n : ℕ) :
coeff (derivative p) n = coeff p (n + 1) * (n + 1) := by
rw [derivative_apply]
simp only [coeff_X_pow, coeff_sum, coeff_C_mul]
rw [sum, Finset.sum_eq_single (n + 1)]
· simp only [Nat.add_succ_sub_one, add_zero, mul_one, if_true, eq_self_iff_true]; norm_cast
· intro b
cases b
· intros
rw [Nat.cast_zero, mul_zero, zero_mul]
· intro _ H
rw [Nat.add_one_sub_one, if_neg (mt (congr_arg Nat.succ) H.symm), mul_zero]
· rw [if_pos (add_tsub_cancel_right n 1).symm, mul_one, Nat.cast_add, Nat.cast_one,
mem_support_iff]
intro h
push_neg at h
simp [h]
@[simp]
theorem derivative_zero : derivative (0 : R[X]) = 0 :=
derivative.map_zero
theorem iterate_derivative_zero {k : ℕ} : derivative^[k] (0 : R[X]) = 0 :=
iterate_map_zero derivative k
theorem derivative_monomial (a : R) (n : ℕ) :
derivative (monomial n a) = monomial (n - 1) (a * n) := by
rw [derivative_apply, sum_monomial_index, C_mul_X_pow_eq_monomial]
simp
@[simp]
theorem derivative_monomial_succ (a : R) (n : ℕ) :
derivative (monomial (n + 1) a) = monomial n (a * (n + 1)) := by
rw [derivative_monomial, add_tsub_cancel_right, Nat.cast_add, Nat.cast_one]
theorem derivative_C_mul_X (a : R) : derivative (C a * X) = C a := by
simp [C_mul_X_eq_monomial, derivative_monomial, Nat.cast_one, mul_one]
theorem derivative_C_mul_X_pow (a : R) (n : ℕ) :
derivative (C a * X ^ n) = C (a * n) * X ^ (n - 1) := by
rw [C_mul_X_pow_eq_monomial, C_mul_X_pow_eq_monomial, derivative_monomial]
theorem derivative_C_mul_X_sq (a : R) : derivative (C a * X ^ 2) = C (a * 2) * X := by
rw [derivative_C_mul_X_pow, Nat.cast_two, pow_one]
theorem derivative_X_pow (n : ℕ) : derivative (X ^ n : R[X]) = C (n : R) * X ^ (n - 1) := by
convert derivative_C_mul_X_pow (1 : R) n <;> simp
@[simp]
theorem derivative_X_pow_succ (n : ℕ) :
derivative (X ^ (n + 1) : R[X]) = C (n + 1 : R) * X ^ n := by
simp [derivative_X_pow]
theorem derivative_X_sq : derivative (X ^ 2 : R[X]) = C 2 * X := by
rw [derivative_X_pow, Nat.cast_two, pow_one]
@[simp]
theorem derivative_C {a : R} : derivative (C a) = 0 := by simp [derivative_apply]
theorem derivative_of_natDegree_zero {p : R[X]} (hp : p.natDegree = 0) : derivative p = 0 := by
rw [eq_C_of_natDegree_eq_zero hp, derivative_C]
@[simp]
theorem derivative_X : derivative (X : R[X]) = 1 :=
(derivative_monomial _ _).trans <| by simp
@[simp]
theorem derivative_one : derivative (1 : R[X]) = 0 :=
derivative_C
@[simp]
theorem derivative_add {f g : R[X]} : derivative (f + g) = derivative f + derivative g :=
derivative.map_add f g
theorem derivative_X_add_C (c : R) : derivative (X + C c) = 1 := by
rw [derivative_add, derivative_X, derivative_C, add_zero]
theorem derivative_sum {s : Finset ι} {f : ι → R[X]} :
derivative (∑ b ∈ s, f b) = ∑ b ∈ s, derivative (f b) :=
map_sum ..
theorem iterate_derivative_sum (k : ℕ) (s : Finset ι) (f : ι → R[X]) :
derivative^[k] (∑ b ∈ s, f b) = ∑ b ∈ s, derivative^[k] (f b) := by
simp_rw [← Module.End.pow_apply, map_sum]
theorem derivative_smul {S : Type*} [SMulZeroClass S R] [IsScalarTower S R R] (s : S)
(p : R[X]) : derivative (s • p) = s • derivative p :=
derivative.map_smul_of_tower s p
@[simp]
theorem iterate_derivative_smul {S : Type*} [SMulZeroClass S R] [IsScalarTower S R R]
(s : S) (p : R[X]) (k : ℕ) : derivative^[k] (s • p) = s • derivative^[k] p := by
induction k generalizing p with
| zero => simp
| succ k ih => simp [ih]
@[simp]
theorem iterate_derivative_C_mul (a : R) (p : R[X]) (k : ℕ) :
derivative^[k] (C a * p) = C a * derivative^[k] p := by
simp_rw [← smul_eq_C_mul, iterate_derivative_smul]
theorem derivative_C_mul (a : R) (p : R[X]) :
derivative (C a * p) = C a * derivative p := iterate_derivative_C_mul _ _ 1
theorem of_mem_support_derivative {p : R[X]} {n : ℕ} (h : n ∈ p.derivative.support) :
n + 1 ∈ p.support :=
mem_support_iff.2 fun h1 : p.coeff (n + 1) = 0 =>
mem_support_iff.1 h <| show p.derivative.coeff n = 0 by rw [coeff_derivative, h1, zero_mul]
theorem degree_derivative_lt {p : R[X]} (hp : p ≠ 0) : p.derivative.degree < p.degree :=
(Finset.sup_lt_iff <| bot_lt_iff_ne_bot.2 <| mt degree_eq_bot.1 hp).2 fun n hp =>
lt_of_lt_of_le (WithBot.coe_lt_coe.2 n.lt_succ_self) <|
Finset.le_sup <| of_mem_support_derivative hp
theorem degree_derivative_le {p : R[X]} : p.derivative.degree ≤ p.degree :=
letI := Classical.decEq R
if H : p = 0 then le_of_eq <| by rw [H, derivative_zero] else (degree_derivative_lt H).le
theorem natDegree_derivative_lt {p : R[X]} (hp : p.natDegree ≠ 0) :
p.derivative.natDegree < p.natDegree := by
rcases eq_or_ne (derivative p) 0 with hp' | hp'
· rw [hp', Polynomial.natDegree_zero]
exact hp.bot_lt
· rw [natDegree_lt_natDegree_iff hp']
exact degree_derivative_lt fun h => hp (h.symm ▸ natDegree_zero)
theorem natDegree_derivative_le (p : R[X]) : p.derivative.natDegree ≤ p.natDegree - 1 := by
by_cases p0 : p.natDegree = 0
· simp [p0, derivative_of_natDegree_zero]
· exact Nat.le_sub_one_of_lt (natDegree_derivative_lt p0)
theorem natDegree_iterate_derivative (p : R[X]) (k : ℕ) :
(derivative^[k] p).natDegree ≤ p.natDegree - k := by
induction k with
| zero => rw [Function.iterate_zero_apply, Nat.sub_zero]
| succ d hd =>
rw [Function.iterate_succ_apply', Nat.sub_succ']
exact (natDegree_derivative_le _).trans <| Nat.sub_le_sub_right hd 1
@[simp]
theorem derivative_natCast {n : ℕ} : derivative (n : R[X]) = 0 := by
rw [← map_natCast C n]
exact derivative_C
@[simp]
theorem derivative_ofNat (n : ℕ) [n.AtLeastTwo] :
derivative (ofNat(n) : R[X]) = 0 :=
derivative_natCast
theorem iterate_derivative_eq_zero {p : R[X]} {x : ℕ} (hx : p.natDegree < x) :
Polynomial.derivative^[x] p = 0 := by
induction' h : p.natDegree using Nat.strong_induction_on with _ ih generalizing p x
subst h
obtain ⟨t, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (pos_of_gt hx).ne'
rw [Function.iterate_succ_apply]
by_cases hp : p.natDegree = 0
· rw [derivative_of_natDegree_zero hp, iterate_derivative_zero]
have := natDegree_derivative_lt hp
exact ih _ this (this.trans_le <| Nat.le_of_lt_succ hx) rfl
@[simp]
theorem iterate_derivative_C {k} (h : 0 < k) : derivative^[k] (C a : R[X]) = 0 :=
iterate_derivative_eq_zero <| (natDegree_C _).trans_lt h
@[simp]
theorem iterate_derivative_one {k} (h : 0 < k) : derivative^[k] (1 : R[X]) = 0 :=
iterate_derivative_C h
@[simp]
theorem iterate_derivative_X {k} (h : 1 < k) : derivative^[k] (X : R[X]) = 0 :=
iterate_derivative_eq_zero <| natDegree_X_le.trans_lt h
theorem natDegree_eq_zero_of_derivative_eq_zero [NoZeroSMulDivisors ℕ R] {f : R[X]}
(h : derivative f = 0) : f.natDegree = 0 := by
rcases eq_or_ne f 0 with (rfl | hf)
· exact natDegree_zero
rw [natDegree_eq_zero_iff_degree_le_zero]
by_contra! f_nat_degree_pos
rw [← natDegree_pos_iff_degree_pos] at f_nat_degree_pos
let m := f.natDegree - 1
have hm : m + 1 = f.natDegree := tsub_add_cancel_of_le f_nat_degree_pos
have h2 := coeff_derivative f m
rw [Polynomial.ext_iff] at h
rw [h m, coeff_zero, ← Nat.cast_add_one, ← nsmul_eq_mul', eq_comm, smul_eq_zero] at h2
replace h2 := h2.resolve_left m.succ_ne_zero
rw [hm, ← leadingCoeff, leadingCoeff_eq_zero] at h2
exact hf h2
theorem eq_C_of_derivative_eq_zero [NoZeroSMulDivisors ℕ R] {f : R[X]} (h : derivative f = 0) :
f = C (f.coeff 0) :=
eq_C_of_natDegree_eq_zero <| natDegree_eq_zero_of_derivative_eq_zero h
@[simp]
theorem derivative_mul {f g : R[X]} : derivative (f * g) = derivative f * g + f * derivative g := by
induction f using Polynomial.induction_on' with
| add => simp only [add_mul, map_add, add_assoc, add_left_comm, *]
| monomial m a => ?_
induction g using Polynomial.induction_on' with
| add => simp only [mul_add, map_add, add_assoc, add_left_comm, *]
| monomial n b => ?_
simp only [monomial_mul_monomial, derivative_monomial]
simp only [mul_assoc, (Nat.cast_commute _ _).eq, Nat.cast_add, mul_add, map_add]
cases m with
| zero => simp only [zero_add, Nat.cast_zero, mul_zero, map_zero]
| succ m =>
cases n with
| zero => simp only [add_zero, Nat.cast_zero, mul_zero, map_zero]
| succ n =>
simp only [Nat.add_succ_sub_one, add_tsub_cancel_right]
rw [add_assoc, add_comm n 1]
theorem derivative_eval (p : R[X]) (x : R) :
p.derivative.eval x = p.sum fun n a => a * n * x ^ (n - 1) := by
simp_rw [derivative_apply, eval_sum, eval_mul_X_pow, eval_C]
@[simp]
theorem derivative_map [Semiring S] (p : R[X]) (f : R →+* S) :
derivative (p.map f) = p.derivative.map f := by
let n := max p.natDegree (map f p).natDegree
rw [derivative_apply, derivative_apply]
rw [sum_over_range' _ _ (n + 1) ((le_max_left _ _).trans_lt (lt_add_one _))]
on_goal 1 => rw [sum_over_range' _ _ (n + 1) ((le_max_right _ _).trans_lt (lt_add_one _))]
· simp only [Polynomial.map_sum, Polynomial.map_mul, Polynomial.map_C, map_mul, coeff_map,
map_natCast, Polynomial.map_natCast, Polynomial.map_pow, map_X]
all_goals intro n; rw [zero_mul, C_0, zero_mul]
@[simp]
theorem iterate_derivative_map [Semiring S] (p : R[X]) (f : R →+* S) (k : ℕ) :
Polynomial.derivative^[k] (p.map f) = (Polynomial.derivative^[k] p).map f := by
induction' k with k ih generalizing p
· simp
· simp only [ih, Function.iterate_succ, Polynomial.derivative_map, Function.comp_apply]
theorem derivative_natCast_mul {n : ℕ} {f : R[X]} :
derivative ((n : R[X]) * f) = n * derivative f := by
simp
@[simp]
theorem iterate_derivative_natCast_mul {n k : ℕ} {f : R[X]} :
derivative^[k] ((n : R[X]) * f) = n * derivative^[k] f := by
induction' k with k ih generalizing f <;> simp [*]
theorem mem_support_derivative [NoZeroSMulDivisors ℕ R] (p : R[X]) (n : ℕ) :
n ∈ (derivative p).support ↔ n + 1 ∈ p.support := by
suffices ¬p.coeff (n + 1) * (n + 1 : ℕ) = 0 ↔ coeff p (n + 1) ≠ 0 by
simpa only [mem_support_iff, coeff_derivative, Ne, Nat.cast_succ]
rw [← nsmul_eq_mul', smul_eq_zero]
simp only [Nat.succ_ne_zero, false_or]
@[simp]
theorem degree_derivative_eq [NoZeroSMulDivisors ℕ R] (p : R[X]) (hp : 0 < natDegree p) :
degree (derivative p) = (natDegree p - 1 : ℕ) := by
apply le_antisymm
· rw [derivative_apply]
apply le_trans (degree_sum_le _ _) (Finset.sup_le _)
intro n hn
apply le_trans (degree_C_mul_X_pow_le _ _) (WithBot.coe_le_coe.2 (tsub_le_tsub_right _ _))
apply le_natDegree_of_mem_supp _ hn
· refine le_sup ?_
rw [mem_support_derivative, tsub_add_cancel_of_le, mem_support_iff]
· rw [coeff_natDegree, Ne, leadingCoeff_eq_zero]
intro h
rw [h, natDegree_zero] at hp
exact hp.false
exact hp
theorem coeff_iterate_derivative {k} (p : R[X]) (m : ℕ) :
(derivative^[k] p).coeff m = (m + k).descFactorial k • p.coeff (m + k) := by
induction k generalizing m with
| zero => simp
| succ k ih =>
calc
(derivative^[k + 1] p).coeff m
_ = Nat.descFactorial (Nat.succ (m + k)) k • p.coeff (m + k.succ) * (m + 1) := by
rw [Function.iterate_succ_apply', coeff_derivative, ih m.succ, Nat.succ_add, Nat.add_succ]
_ = ((m + 1) * Nat.descFactorial (Nat.succ (m + k)) k) • p.coeff (m + k.succ) := by
rw [← Nat.cast_add_one, ← nsmul_eq_mul', smul_smul]
_ = Nat.descFactorial (m.succ + k) k.succ • p.coeff (m + k.succ) := by
rw [← Nat.succ_add, Nat.descFactorial_succ, add_tsub_cancel_right]
_ = Nat.descFactorial (m + k.succ) k.succ • p.coeff (m + k.succ) := by
rw [Nat.succ_add_eq_add_succ]
theorem iterate_derivative_eq_sum (p : R[X]) (k : ℕ) :
derivative^[k] p =
∑ x ∈ (derivative^[k] p).support, C ((x + k).descFactorial k • p.coeff (x + k)) * X ^ x := by
conv_lhs => rw [(derivative^[k] p).as_sum_support_C_mul_X_pow]
refine sum_congr rfl fun i _ ↦ ?_
rw [coeff_iterate_derivative, Nat.descFactorial_eq_factorial_mul_choose]
theorem iterate_derivative_eq_factorial_smul_sum (p : R[X]) (k : ℕ) :
derivative^[k] p = k ! •
∑ x ∈ (derivative^[k] p).support, C ((x + k).choose k • p.coeff (x + k)) * X ^ x := by
conv_lhs => rw [iterate_derivative_eq_sum]
rw [smul_sum]
refine sum_congr rfl fun i _ ↦ ?_
rw [← smul_mul_assoc, smul_C, smul_smul, Nat.descFactorial_eq_factorial_mul_choose]
theorem iterate_derivative_mul {n} (p q : R[X]) :
derivative^[n] (p * q) =
∑ k ∈ range n.succ, (n.choose k • (derivative^[n - k] p * derivative^[k] q)) := by
induction n with
| zero =>
simp [Finset.range]
| succ n IH =>
calc
derivative^[n + 1] (p * q) =
derivative (∑ k ∈ range n.succ,
n.choose k • (derivative^[n - k] p * derivative^[k] q)) := by
rw [Function.iterate_succ_apply', IH]
_ = (∑ k ∈ range n.succ,
n.choose k • (derivative^[n - k + 1] p * derivative^[k] q)) +
∑ k ∈ range n.succ,
n.choose k • (derivative^[n - k] p * derivative^[k + 1] q) := by
simp_rw [derivative_sum, derivative_smul, derivative_mul, Function.iterate_succ_apply',
smul_add, sum_add_distrib]
_ = (∑ k ∈ range n.succ,
n.choose k.succ • (derivative^[n - k] p * derivative^[k + 1] q)) +
1 • (derivative^[n + 1] p * derivative^[0] q) +
∑ k ∈ range n.succ, n.choose k • (derivative^[n - k] p * derivative^[k + 1] q) :=
?_
_ = ((∑ k ∈ range n.succ, n.choose k • (derivative^[n - k] p * derivative^[k + 1] q)) +
∑ k ∈ range n.succ,
n.choose k.succ • (derivative^[n - k] p * derivative^[k + 1] q)) +
1 • (derivative^[n + 1] p * derivative^[0] q) := by
rw [add_comm, add_assoc]
_ = (∑ i ∈ range n.succ,
(n + 1).choose (i + 1) • (derivative^[n + 1 - (i + 1)] p * derivative^[i + 1] q)) +
1 • (derivative^[n + 1] p * derivative^[0] q) := by
simp_rw [Nat.choose_succ_succ, Nat.succ_sub_succ, add_smul, sum_add_distrib]
_ = ∑ k ∈ range n.succ.succ,
n.succ.choose k • (derivative^[n.succ - k] p * derivative^[k] q) := by
rw [sum_range_succ' _ n.succ, Nat.choose_zero_right, tsub_zero]
congr
refine (sum_range_succ' _ _).trans (congr_arg₂ (· + ·) ?_ ?_)
· rw [sum_range_succ, Nat.choose_succ_self, zero_smul, add_zero]
refine sum_congr rfl fun k hk => ?_
rw [mem_range] at hk
congr
omega
· rw [Nat.choose_zero_right, tsub_zero]
/--
Iterated derivatives as a finite support function.
-/
@[simps! apply_toFun]
noncomputable def derivativeFinsupp : R[X] →ₗ[R] ℕ →₀ R[X] where
toFun p := .onFinset (range (p.natDegree + 1)) (derivative^[·] p) fun i ↦ by
contrapose; simp_all [iterate_derivative_eq_zero, Nat.succ_le]
map_add' _ _ := by ext; simp
map_smul' _ _ := by ext; simp
@[simp]
theorem support_derivativeFinsupp_subset_range {p : R[X]} {n : ℕ} (h : p.natDegree < n) :
(derivativeFinsupp p).support ⊆ range n := by
dsimp [derivativeFinsupp]
exact Finsupp.support_onFinset_subset.trans (Finset.range_subset.mpr h)
@[simp]
theorem derivativeFinsupp_C (r : R) : derivativeFinsupp (C r : R[X]) = .single 0 (C r) := by
ext i : 1
match i with
| 0 => simp
| i + 1 => simp
@[simp]
theorem derivativeFinsupp_one : derivativeFinsupp (1 : R[X]) = .single 0 1 := by
simpa using derivativeFinsupp_C (1 : R)
@[simp]
theorem derivativeFinsupp_X : derivativeFinsupp (X : R[X]) = .single 0 X + .single 1 1 := by
ext i : 1
match i with
| 0 => simp
| 1 => simp
| (n + 2) => simp
theorem derivativeFinsupp_map [Semiring S] (p : R[X]) (f : R →+* S) :
derivativeFinsupp (p.map f) = (derivativeFinsupp p).mapRange (·.map f) (by simp) := by
ext i : 1
simp
theorem derivativeFinsupp_derivative (p : R[X]) :
derivativeFinsupp (derivative p) =
(derivativeFinsupp p).comapDomain Nat.succ Nat.succ_injective.injOn := by
ext i : 1
simp
end Semiring
section CommSemiring
variable [CommSemiring R]
theorem derivative_pow_succ (p : R[X]) (n : ℕ) :
derivative (p ^ (n + 1)) = C (n + 1 : R) * p ^ n * derivative p :=
Nat.recOn n (by simp) fun n ih => by
rw [pow_succ, derivative_mul, ih, Nat.add_one, mul_right_comm, C_add,
add_mul, add_mul, pow_succ, ← mul_assoc, C_1, one_mul]; simp [add_mul]
theorem derivative_pow (p : R[X]) (n : ℕ) :
derivative (p ^ n) = C (n : R) * p ^ (n - 1) * derivative p :=
Nat.casesOn n (by rw [pow_zero, derivative_one, Nat.cast_zero, C_0, zero_mul, zero_mul]) fun n =>
by rw [p.derivative_pow_succ n, Nat.add_one_sub_one, n.cast_succ]
theorem derivative_sq (p : R[X]) : derivative (p ^ 2) = C 2 * p * derivative p := by
rw [derivative_pow_succ, Nat.cast_one, one_add_one_eq_two, pow_one]
theorem pow_sub_one_dvd_derivative_of_pow_dvd {p q : R[X]} {n : ℕ}
(dvd : q ^ n ∣ p) : q ^ (n - 1) ∣ derivative p := by
obtain ⟨r, rfl⟩ := dvd
rw [derivative_mul, derivative_pow]
exact (((dvd_mul_left _ _).mul_right _).mul_right _).add ((pow_dvd_pow q n.pred_le).mul_right _)
theorem pow_sub_dvd_iterate_derivative_of_pow_dvd {p q : R[X]} {n : ℕ} (m : ℕ)
(dvd : q ^ n ∣ p) : q ^ (n - m) ∣ derivative^[m] p := by
induction m generalizing p with
| zero => simpa
| succ m ih =>
rw [Nat.sub_succ, Function.iterate_succ']
exact pow_sub_one_dvd_derivative_of_pow_dvd (ih dvd)
theorem pow_sub_dvd_iterate_derivative_pow (p : R[X]) (n m : ℕ) :
p ^ (n - m) ∣ derivative^[m] (p ^ n) := pow_sub_dvd_iterate_derivative_of_pow_dvd m dvd_rfl
theorem dvd_iterate_derivative_pow (f : R[X]) (n : ℕ) {m : ℕ} (c : R) (hm : m ≠ 0) :
(n : R) ∣ eval c (derivative^[m] (f ^ n)) := by
obtain ⟨m, rfl⟩ := Nat.exists_eq_succ_of_ne_zero hm
rw [Function.iterate_succ_apply, derivative_pow, mul_assoc, C_eq_natCast,
iterate_derivative_natCast_mul, eval_mul, eval_natCast]
exact dvd_mul_right _ _
theorem iterate_derivative_X_pow_eq_natCast_mul (n k : ℕ) :
derivative^[k] (X ^ n : R[X]) = ↑(Nat.descFactorial n k : R[X]) * X ^ (n - k) := by
induction k with
| zero =>
rw [Function.iterate_zero_apply, tsub_zero, Nat.descFactorial_zero, Nat.cast_one, one_mul]
| succ k ih =>
rw [Function.iterate_succ_apply', ih, derivative_natCast_mul, derivative_X_pow, C_eq_natCast,
Nat.descFactorial_succ, Nat.sub_sub, Nat.cast_mul]
simp [mul_comm, mul_assoc, mul_left_comm]
theorem iterate_derivative_X_pow_eq_C_mul (n k : ℕ) :
derivative^[k] (X ^ n : R[X]) = C (Nat.descFactorial n k : R) * X ^ (n - k) := by
rw [iterate_derivative_X_pow_eq_natCast_mul n k, C_eq_natCast]
theorem iterate_derivative_X_pow_eq_smul (n : ℕ) (k : ℕ) :
derivative^[k] (X ^ n : R[X]) = (Nat.descFactorial n k : R) • X ^ (n - k) := by
rw [iterate_derivative_X_pow_eq_C_mul n k, smul_eq_C_mul]
theorem derivative_X_add_C_pow (c : R) (m : ℕ) :
derivative ((X + C c) ^ m) = C (m : R) * (X + C c) ^ (m - 1) := by
rw [derivative_pow, derivative_X_add_C, mul_one]
theorem derivative_X_add_C_sq (c : R) : derivative ((X + C c) ^ 2) = C 2 * (X + C c) := by
rw [derivative_sq, derivative_X_add_C, mul_one]
theorem iterate_derivative_X_add_pow (n k : ℕ) (c : R) :
derivative^[k] ((X + C c) ^ n) = Nat.descFactorial n k • (X + C c) ^ (n - k) := by
induction k with
| zero => simp
| succ k IH =>
rw [Nat.sub_succ', Function.iterate_succ_apply', IH, derivative_smul,
derivative_X_add_C_pow, map_natCast, Nat.descFactorial_succ, nsmul_eq_mul, nsmul_eq_mul,
Nat.cast_mul]
ring
theorem derivative_comp (p q : R[X]) :
derivative (p.comp q) = derivative q * p.derivative.comp q := by
induction p using Polynomial.induction_on'
· simp [*, mul_add]
· simp only [derivative_pow, derivative_mul, monomial_comp, derivative_monomial, derivative_C,
zero_mul, C_eq_natCast, zero_add, RingHom.map_mul]
ring
/-- Chain rule for formal derivative of polynomials. -/
theorem derivative_eval₂_C (p q : R[X]) :
derivative (p.eval₂ C q) = p.derivative.eval₂ C q * derivative q :=
Polynomial.induction_on p (fun r => by rw [eval₂_C, derivative_C, eval₂_zero, zero_mul])
(fun p₁ p₂ ih₁ ih₂ => by
rw [eval₂_add, derivative_add, ih₁, ih₂, derivative_add, eval₂_add, add_mul])
fun n r ih => by
rw [pow_succ, ← mul_assoc, eval₂_mul, eval₂_X, derivative_mul, ih, @derivative_mul _ _ _ X,
derivative_X, mul_one, eval₂_add, @eval₂_mul _ _ _ _ X, eval₂_X, add_mul, mul_right_comm]
theorem derivative_prod [DecidableEq ι] {s : Multiset ι} {f : ι → R[X]} :
derivative (Multiset.map f s).prod =
(Multiset.map (fun i => (Multiset.map f (s.erase i)).prod * derivative (f i)) s).sum := by
refine Multiset.induction_on s (by simp) fun i s h => ?_
rw [Multiset.map_cons, Multiset.prod_cons, derivative_mul, Multiset.map_cons _ i s,
Multiset.sum_cons, Multiset.erase_cons_head, mul_comm (derivative (f i))]
congr
rw [h, ← AddMonoidHom.coe_mulLeft, (AddMonoidHom.mulLeft (f i)).map_multiset_sum _,
AddMonoidHom.coe_mulLeft]
simp only [Function.comp_apply, Multiset.map_map]
refine congr_arg _ (Multiset.map_congr rfl fun j hj => ?_)
rw [← mul_assoc, ← Multiset.prod_cons, ← Multiset.map_cons]
by_cases hij : i = j
· simp [hij, ← Multiset.prod_cons, ← Multiset.map_cons, Multiset.cons_erase hj]
· simp [hij]
end CommSemiring
section Ring
variable [Ring R]
@[simp]
theorem derivative_neg (f : R[X]) : derivative (-f) = -derivative f :=
LinearMap.map_neg derivative f
theorem iterate_derivative_neg {f : R[X]} {k : ℕ} : derivative^[k] (-f) = -derivative^[k] f :=
iterate_map_neg derivative k f
@[simp]
theorem derivative_sub {f g : R[X]} : derivative (f - g) = derivative f - derivative g :=
LinearMap.map_sub derivative f g
theorem derivative_X_sub_C (c : R) : derivative (X - C c) = 1 := by
rw [derivative_sub, derivative_X, derivative_C, sub_zero]
theorem iterate_derivative_sub {k : ℕ} {f g : R[X]} :
derivative^[k] (f - g) = derivative^[k] f - derivative^[k] g :=
iterate_map_sub derivative k f g
@[simp]
theorem derivative_intCast {n : ℤ} : derivative (n : R[X]) = 0 := by
rw [← C_eq_intCast n]
exact derivative_C
theorem derivative_intCast_mul {n : ℤ} {f : R[X]} : derivative ((n : R[X]) * f) =
n * derivative f := by
simp
@[simp]
theorem iterate_derivative_intCast_mul {n : ℤ} {k : ℕ} {f : R[X]} :
derivative^[k] ((n : R[X]) * f) = n * derivative^[k] f := by
induction' k with k ih generalizing f <;> simp [*]
end Ring
section CommRing
variable [CommRing R]
theorem derivative_comp_one_sub_X (p : R[X]) :
derivative (p.comp (1 - X)) = -p.derivative.comp (1 - X) := by simp [derivative_comp]
@[simp]
theorem iterate_derivative_comp_one_sub_X (p : R[X]) (k : ℕ) :
derivative^[k] (p.comp (1 - X)) = (-1) ^ k * (derivative^[k] p).comp (1 - X) := by
induction' k with k ih generalizing p
· simp
· simp [ih (derivative p), iterate_derivative_neg, derivative_comp, pow_succ]
theorem eval_multiset_prod_X_sub_C_derivative [DecidableEq R]
{S : Multiset R} {r : R} (hr : r ∈ S) :
eval r (derivative (Multiset.map (fun a => X - C a) S).prod) =
(Multiset.map (fun a => r - a) (S.erase r)).prod := by
nth_rw 1 [← Multiset.cons_erase hr]
have := (evalRingHom r).map_multiset_prod (Multiset.map (fun a => X - C a) (S.erase r))
simpa using this
theorem derivative_X_sub_C_pow (c : R) (m : ℕ) :
derivative ((X - C c) ^ m) = C (m : R) * (X - C c) ^ (m - 1) := by
rw [derivative_pow, derivative_X_sub_C, mul_one]
theorem derivative_X_sub_C_sq (c : R) : derivative ((X - C c) ^ 2) = C 2 * (X - C c) := by
rw [derivative_sq, derivative_X_sub_C, mul_one]
theorem iterate_derivative_X_sub_pow (n k : ℕ) (c : R) :
derivative^[k] ((X - C c) ^ n) = n.descFactorial k • (X - C c) ^ (n - k) := by
rw [sub_eq_add_neg, ← C_neg, iterate_derivative_X_add_pow]
theorem iterate_derivative_X_sub_pow_self (n : ℕ) (c : R) :
derivative^[n] ((X - C c) ^ n) = n.factorial := by
rw [iterate_derivative_X_sub_pow, n.sub_self, pow_zero, nsmul_one, n.descFactorial_self]
end CommRing
section NoZeroDivisors
variable [Semiring R] [NoZeroDivisors R]
@[simp]
theorem dvd_derivative_iff {P : R[X]} : P ∣ derivative P ↔ derivative P = 0 where
mp h := by
by_cases hP : P = 0
· simp only [hP, derivative_zero]
exact eq_zero_of_dvd_of_degree_lt h (degree_derivative_lt hP)
mpr h := by simp [h]
end NoZeroDivisors
section CommSemiringNoZeroDivisors
variable [CommSemiring R] [NoZeroDivisors R]
theorem derivative_pow_eq_zero {n : ℕ} (chn : (n : R) ≠ 0) {a : R[X]} :
derivative (a ^ n) = 0 ↔ derivative a = 0 := by
nontriviality R
rw [← C_ne_zero, C_eq_natCast] at chn
simp +contextual [derivative_pow, or_imp, chn]
end CommSemiringNoZeroDivisors
end Derivative
end Polynomial
| Mathlib/Algebra/Polynomial/Derivative.lean | 675 | 677 | |
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomotopyCategory.HomComplex
import Mathlib.Algebra.Homology.HomotopyCategory.Shift
/-! Shifting cochains
Let `C` be a preadditive category. Given two cochain complexes (indexed by `ℤ`),
the type of cochains `HomComplex.Cochain K L n` of degree `n` was introduced
in `Mathlib.Algebra.Homology.HomotopyCategory.HomComplex`. In this file, we
study how these cochains behave with respect to the shift on the complexes `K`
and `L`.
When `n`, `a`, `n'` are integers such that `h : n' + a = n`,
we obtain `rightShiftAddEquiv K L n a n' h : Cochain K L n ≃+ Cochain K (L⟦a⟧) n'`.
This definition does not involve signs, but the analogous definition
of `leftShiftAddEquiv K L n a n' h' : Cochain K L n ≃+ Cochain (K⟦a⟧) L n'`
when `h' : n + a = n'` does involve signs, as we follow the conventions
appearing in the introduction of
[Brian Conrad's book *Grothendieck duality and base change*][conrad2000].
## References
* [Brian Conrad, Grothendieck duality and base change][conrad2000]
-/
assert_not_exists TwoSidedIdeal
open CategoryTheory Category Limits Preadditive
universe v u
variable {C : Type u} [Category.{v} C] [Preadditive C] {R : Type*} [Ring R] [Linear R C]
{K L M : CochainComplex C ℤ} {n : ℤ}
namespace CochainComplex.HomComplex
namespace Cochain
variable (γ γ₁ γ₂ : Cochain K L n)
/-- The map `Cochain K L n → Cochain K (L⟦a⟧) n'` when `n' + a = n`. -/
def rightShift (a n' : ℤ) (hn' : n' + a = n) : Cochain K (L⟦a⟧) n' :=
Cochain.mk (fun p q hpq => γ.v p (p + n) rfl ≫
(L.shiftFunctorObjXIso a q (p + n) (by omega)).inv)
lemma rightShift_v (a n' : ℤ) (hn' : n' + a = n) (p q : ℤ) (hpq : p + n' = q)
(p' : ℤ) (hp' : p + n = p') :
(γ.rightShift a n' hn').v p q hpq = γ.v p p' hp' ≫
(L.shiftFunctorObjXIso a q p' (by rw [← hp', ← hpq, ← hn', add_assoc])).inv := by
subst hp'
dsimp only [rightShift]
simp only [mk_v]
/-- The map `Cochain K L n → Cochain (K⟦a⟧) L n'` when `n + a = n'`. -/
def leftShift (a n' : ℤ) (hn' : n + a = n') : Cochain (K⟦a⟧) L n' :=
Cochain.mk (fun p q hpq => (a * n' + ((a * (a-1))/2)).negOnePow •
(K.shiftFunctorObjXIso a p (p + a) rfl).hom ≫ γ.v (p+a) q (by omega))
lemma leftShift_v (a n' : ℤ) (hn' : n + a = n') (p q : ℤ) (hpq : p + n' = q)
(p' : ℤ) (hp' : p' + n = q) :
(γ.leftShift a n' hn').v p q hpq = (a * n' + ((a * (a - 1))/2)).negOnePow •
(K.shiftFunctorObjXIso a p p'
(by rw [← add_left_inj n, hp', add_assoc, add_comm a, hn', hpq])).hom ≫ γ.v p' q hp' := by
obtain rfl : p' = p + a := by omega
dsimp only [leftShift]
simp only [mk_v]
/-- The map `Cochain K (L⟦a⟧) n' → Cochain K L n` when `n' + a = n`. -/
def rightUnshift {n' a : ℤ} (γ : Cochain K (L⟦a⟧) n') (n : ℤ) (hn : n' + a = n) :
Cochain K L n :=
Cochain.mk (fun p q hpq => γ.v p (p + n') rfl ≫
(L.shiftFunctorObjXIso a (p + n') q (by rw [← hpq, add_assoc, hn])).hom)
lemma rightUnshift_v {n' a : ℤ} (γ : Cochain K (L⟦a⟧) n') (n : ℤ) (hn : n' + a = n)
(p q : ℤ) (hpq : p + n = q) (p' : ℤ) (hp' : p + n' = p') :
(γ.rightUnshift n hn).v p q hpq = γ.v p p' hp' ≫
(L.shiftFunctorObjXIso a p' q (by rw [← hpq, ← hn, ← add_assoc, hp'])).hom := by
subst hp'
dsimp only [rightUnshift]
simp only [mk_v]
/-- The map `Cochain (K⟦a⟧) L n' → Cochain K L n` when `n + a = n'`. -/
def leftUnshift {n' a : ℤ} (γ : Cochain (K⟦a⟧) L n') (n : ℤ) (hn : n + a = n') :
Cochain K L n :=
Cochain.mk (fun p q hpq => (a * n' + ((a * (a-1))/2)).negOnePow •
(K.shiftFunctorObjXIso a (p - a) p (by omega)).inv ≫ γ.v (p-a) q (by omega))
lemma leftUnshift_v {n' a : ℤ} (γ : Cochain (K⟦a⟧) L n') (n : ℤ) (hn : n + a = n')
(p q : ℤ) (hpq : p + n = q) (p' : ℤ) (hp' : p' + n' = q) :
(γ.leftUnshift n hn).v p q hpq = (a * n' + ((a * (a-1))/2)).negOnePow •
(K.shiftFunctorObjXIso a p' p (by omega)).inv ≫ γ.v p' q (by omega) := by
obtain rfl : p' = p - a := by omega
rfl
/-- The map `Cochain K L n → Cochain (K⟦a⟧) (L⟦a⟧) n`. -/
def shift (a : ℤ) : Cochain (K⟦a⟧) (L⟦a⟧) n :=
Cochain.mk (fun p q hpq => (K.shiftFunctorObjXIso a p _ rfl).hom ≫
γ.v (p + a) (q + a) (by omega) ≫ (L.shiftFunctorObjXIso a q _ rfl).inv)
lemma shift_v (a : ℤ) (p q : ℤ) (hpq : p + n = q) (p' q' : ℤ)
(hp' : p' = p + a) (hq' : q' = q + a) :
(γ.shift a).v p q hpq = (K.shiftFunctorObjXIso a p p' hp').hom ≫
γ.v p' q' (by rw [hp', hq', ← hpq, add_assoc, add_comm a, add_assoc]) ≫
(L.shiftFunctorObjXIso a q q' hq').inv := by
subst hp' hq'
rfl
lemma shift_v' (a : ℤ) (p q : ℤ) (hpq : p + n = q) :
(γ.shift a).v p q hpq = γ.v (p + a) (q + a) (by omega) := by
simp only [shift_v γ a p q hpq _ _ rfl rfl, shiftFunctor_obj_X, shiftFunctorObjXIso,
HomologicalComplex.XIsoOfEq_rfl, Iso.refl_hom, Iso.refl_inv, comp_id, id_comp]
@[simp]
lemma rightUnshift_rightShift (a n' : ℤ) (hn' : n' + a = n) :
(γ.rightShift a n' hn').rightUnshift n hn' = γ := by
ext p q hpq
simp only [rightUnshift_v _ n hn' p q hpq (p + n') rfl,
γ.rightShift_v _ _ hn' p (p + n') rfl q hpq,
shiftFunctorObjXIso, assoc, Iso.inv_hom_id, comp_id]
@[simp]
lemma rightShift_rightUnshift {a n' : ℤ} (γ : Cochain K (L⟦a⟧) n') (n : ℤ) (hn' : n' + a = n) :
(γ.rightUnshift n hn').rightShift a n' hn' = γ := by
ext p q hpq
simp only [(γ.rightUnshift n hn').rightShift_v a n' hn' p q hpq (p + n) rfl,
γ.rightUnshift_v n hn' p (p + n) rfl q hpq,
shiftFunctorObjXIso, assoc, Iso.hom_inv_id, comp_id]
@[simp]
lemma leftUnshift_leftShift (a n' : ℤ) (hn' : n + a = n') :
(γ.leftShift a n' hn').leftUnshift n hn' = γ := by
ext p q hpq
rw [(γ.leftShift a n' hn').leftUnshift_v n hn' p q hpq (q-n') (by omega),
γ.leftShift_v a n' hn' (q-n') q (by omega) p hpq, Linear.comp_units_smul,
Iso.inv_hom_id_assoc, smul_smul, Int.units_mul_self, one_smul]
@[simp]
lemma leftShift_leftUnshift {a n' : ℤ} (γ : Cochain (K⟦a⟧) L n') (n : ℤ) (hn' : n + a = n') :
(γ.leftUnshift n hn').leftShift a n' hn' = γ := by
ext p q hpq
rw [(γ.leftUnshift n hn').leftShift_v a n' hn' p q hpq (q-n) (by omega),
γ.leftUnshift_v n hn' (q-n) q (by omega) p hpq, Linear.comp_units_smul, smul_smul,
Iso.hom_inv_id_assoc, Int.units_mul_self, one_smul]
@[simp]
lemma rightShift_add (a n' : ℤ) (hn' : n' + a = n) :
(γ₁ + γ₂).rightShift a n' hn' = γ₁.rightShift a n' hn' + γ₂.rightShift a n' hn' := by
ext p q hpq
dsimp
simp only [rightShift_v _ a n' hn' p q hpq _ rfl, add_v, add_comp]
@[simp]
lemma leftShift_add (a n' : ℤ) (hn' : n + a = n') :
(γ₁ + γ₂).leftShift a n' hn' = γ₁.leftShift a n' hn' + γ₂.leftShift a n' hn' := by
ext p q hpq
dsimp
simp only [leftShift_v _ a n' hn' p q hpq (p + a) (by omega), add_v, comp_add, smul_add]
@[simp]
lemma shift_add (a : ℤ) :
(γ₁ + γ₂).shift a = γ₁.shift a + γ₂.shift a := by
ext p q hpq
dsimp
simp only [shift_v', add_v]
variable (K L)
/-- The additive equivalence `Cochain K L n ≃+ Cochain K L⟦a⟧ n'` when `n' + a = n`. -/
@[simps]
def rightShiftAddEquiv (n a n' : ℤ) (hn' : n' + a = n) :
Cochain K L n ≃+ Cochain K (L⟦a⟧) n' where
toFun γ := γ.rightShift a n' hn'
invFun γ := γ.rightUnshift n hn'
left_inv γ := by simp only [rightUnshift_rightShift]
right_inv γ := by simp only [rightShift_rightUnshift]
map_add' γ γ' := by simp only [rightShift_add]
/-- The additive equivalence `Cochain K L n ≃+ Cochain (K⟦a⟧) L n'` when `n + a = n'`. -/
@[simps]
def leftShiftAddEquiv (n a n' : ℤ) (hn' : n + a = n') :
Cochain K L n ≃+ Cochain (K⟦a⟧) L n' where
toFun γ := γ.leftShift a n' hn'
invFun γ := γ.leftUnshift n hn'
left_inv γ := by simp only [leftUnshift_leftShift]
right_inv γ := by simp only [leftShift_leftUnshift]
map_add' γ γ' := by simp only [leftShift_add]
/-- The additive map `Cochain K L n →+ Cochain (K⟦a⟧) (L⟦a⟧) n`. -/
@[simps!]
def shiftAddHom (n a : ℤ) : Cochain K L n →+ Cochain (K⟦a⟧) (L⟦a⟧) n :=
AddMonoidHom.mk' (fun γ => γ.shift a) (by intros; dsimp; simp only [shift_add])
variable (n)
@[simp]
lemma rightShift_zero (a n' : ℤ) (hn' : n' + a = n) :
(0 : Cochain K L n).rightShift a n' hn' = 0 := by
change rightShiftAddEquiv K L n a n' hn' 0 = 0
apply map_zero
@[simp]
lemma rightUnshift_zero (a n' : ℤ) (hn' : n' + a = n) :
(0 : Cochain K (L⟦a⟧) n').rightUnshift n hn' = 0 := by
change (rightShiftAddEquiv K L n a n' hn').symm 0 = 0
apply map_zero
@[simp]
lemma leftShift_zero (a n' : ℤ) (hn' : n + a = n') :
(0 : Cochain K L n).leftShift a n' hn' = 0 := by
change leftShiftAddEquiv K L n a n' hn' 0 = 0
apply map_zero
@[simp]
lemma leftUnshift_zero (a n' : ℤ) (hn' : n + a = n') :
(0 : Cochain (K⟦a⟧) L n').leftUnshift n hn' = 0 := by
change (leftShiftAddEquiv K L n a n' hn').symm 0 = 0
apply map_zero
@[simp]
lemma shift_zero (a : ℤ) :
(0 : Cochain K L n).shift a = 0 := by
change shiftAddHom K L n a 0 = 0
apply map_zero
variable {K L n}
@[simp]
lemma rightShift_neg (a n' : ℤ) (hn' : n' + a = n) :
(-γ).rightShift a n' hn' = -γ.rightShift a n' hn' := by
change rightShiftAddEquiv K L n a n' hn' (-γ) = _
apply map_neg
@[simp]
lemma rightUnshift_neg {n' a : ℤ} (γ : Cochain K (L⟦a⟧) n') (n : ℤ) (hn : n' + a = n) :
(-γ).rightUnshift n hn = -γ.rightUnshift n hn := by
change (rightShiftAddEquiv K L n a n' hn).symm (-γ) = _
apply map_neg
@[simp]
lemma leftShift_neg (a n' : ℤ) (hn' : n + a = n') :
(-γ).leftShift a n' hn' = -γ.leftShift a n' hn' := by
change leftShiftAddEquiv K L n a n' hn' (-γ) = _
apply map_neg
@[simp]
lemma leftUnshift_neg {n' a : ℤ} (γ : Cochain (K⟦a⟧) L n') (n : ℤ) (hn : n + a = n') :
(-γ).leftUnshift n hn = -γ.leftUnshift n hn := by
| change (leftShiftAddEquiv K L n a n' hn).symm (-γ) = _
apply map_neg
@[simp]
lemma shift_neg (a : ℤ) :
| Mathlib/Algebra/Homology/HomotopyCategory/HomComplexShift.lean | 252 | 256 |
/-
Copyright (c) 2022 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Andrew Yang
-/
import Mathlib.AlgebraicGeometry.ProjectiveSpectrum.StructureSheaf
import Mathlib.AlgebraicGeometry.GammaSpecAdjunction
import Mathlib.RingTheory.GradedAlgebra.Radical
/-!
# Proj as a scheme
This file is to prove that `Proj` is a scheme.
## Notation
* `Proj` : `Proj` as a locally ringed space
* `Proj.T` : the underlying topological space of `Proj`
* `Proj| U` : `Proj` restricted to some open set `U`
* `Proj.T| U` : the underlying topological space of `Proj` restricted to open set `U`
* `pbo f` : basic open set at `f` in `Proj`
* `Spec` : `Spec` as a locally ringed space
* `Spec.T` : the underlying topological space of `Spec`
* `sbo g` : basic open set at `g` in `Spec`
* `A⁰_x` : the degree zero part of localized ring `Aₓ`
## Implementation
In `AlgebraicGeometry/ProjectiveSpectrum/StructureSheaf.lean`, we have given `Proj` a
structure sheaf so that `Proj` is a locally ringed space. In this file we will prove that `Proj`
equipped with this structure sheaf is a scheme. We achieve this by using an affine cover by basic
open sets in `Proj`, more specifically:
1. We prove that `Proj` can be covered by basic open sets at homogeneous element of positive degree.
2. We prove that for any homogeneous element `f : A` of positive degree `m`, `Proj.T | (pbo f)` is
homeomorphic to `Spec.T A⁰_f`:
- forward direction `toSpec`:
for any `x : pbo f`, i.e. a relevant homogeneous prime ideal `x`, send it to
`A⁰_f ∩ span {g / 1 | g ∈ x}` (see `ProjIsoSpecTopComponent.IoSpec.carrier`). This ideal is
prime, the proof is in `ProjIsoSpecTopComponent.ToSpec.toFun`. The fact that this function
is continuous is found in `ProjIsoSpecTopComponent.toSpec`
- backward direction `fromSpec`:
for any `q : Spec A⁰_f`, we send it to `{a | ∀ i, aᵢᵐ/fⁱ ∈ q}`; we need this to be a
homogeneous prime ideal that is relevant.
* This is in fact an ideal, the proof can be found in
`ProjIsoSpecTopComponent.FromSpec.carrier.asIdeal`;
* This ideal is also homogeneous, the proof can be found in
`ProjIsoSpecTopComponent.FromSpec.carrier.asIdeal.homogeneous`;
* This ideal is relevant, the proof can be found in
`ProjIsoSpecTopComponent.FromSpec.carrier.relevant`;
* This ideal is prime, the proof can be found in
`ProjIsoSpecTopComponent.FromSpec.carrier.asIdeal.prime`.
Hence we have a well defined function `Spec.T A⁰_f → Proj.T | (pbo f)`, this function is called
`ProjIsoSpecTopComponent.FromSpec.toFun`. But to prove the continuity of this function, we need
to prove `fromSpec ∘ toSpec` and `toSpec ∘ fromSpec` are both identities; these are achieved in
`ProjIsoSpecTopComponent.fromSpec_toSpec` and `ProjIsoSpecTopComponent.toSpec_fromSpec`.
3. Then we construct a morphism of locally ringed spaces `α : Proj| (pbo f) ⟶ Spec.T A⁰_f` as the
following: by the Gamma-Spec adjunction, it is sufficient to construct a ring map
`A⁰_f → Γ(Proj, pbo f)` from the ring of homogeneous localization of `A` away from `f` to the
local sections of structure sheaf of projective spectrum on the basic open set around `f`.
The map `A⁰_f → Γ(Proj, pbo f)` is constructed in `awayToΓ` and is defined by sending
`s ∈ A⁰_f` to the section `x ↦ s` on `pbo f`.
## Main Definitions and Statements
For a homogeneous element `f` of degree `m`
* `ProjIsoSpecTopComponent.toSpec`: the continuous map between `Proj.T| pbo f` and `Spec.T A⁰_f`
defined by sending `x : Proj| (pbo f)` to `A⁰_f ∩ span {g / 1 | g ∈ x}`. We also denote this map
as `ψ`.
* `ProjIsoSpecTopComponent.ToSpec.preimage_eq`: for any `a: A`, if `a/f^m` has degree zero,
then the preimage of `sbo a/f^m` under `toSpec f` is `pbo f ∩ pbo a`.
If we further assume `m` is positive
* `ProjIsoSpecTopComponent.fromSpec`: the continuous map between `Spec.T A⁰_f` and `Proj.T| pbo f`
defined by sending `q` to `{a | aᵢᵐ/fⁱ ∈ q}` where `aᵢ` is the `i`-th coordinate of `a`.
We also denote this map as `φ`
* `projIsoSpecTopComponent`: the homeomorphism `Proj.T| pbo f ≅ Spec.T A⁰_f` obtained by `φ` and
`ψ`.
* `ProjectiveSpectrum.Proj.toSpec`: the morphism of locally ringed spaces between `Proj| pbo f`
and `Spec A⁰_f` corresponding to the ring map `A⁰_f → Γ(Proj, pbo f)` under the Gamma-Spec
adjunction defined by sending `s` to the section `x ↦ s` on `pbo f`.
Finally,
* `AlgebraicGeometry.Proj`: for any `ℕ`-graded ring `A`, `Proj A` is locally affine, hence is a
scheme.
## Reference
* [Robin Hartshorne, *Algebraic Geometry*][Har77]: Chapter II.2 Proposition 2.5
-/
noncomputable section
namespace AlgebraicGeometry
open scoped DirectSum Pointwise
open DirectSum SetLike.GradedMonoid Localization
open Finset hiding mk_zero
variable {R A : Type*}
variable [CommRing R] [CommRing A] [Algebra R A]
variable (𝒜 : ℕ → Submodule R A)
variable [GradedAlgebra 𝒜]
open TopCat TopologicalSpace
open CategoryTheory Opposite
open ProjectiveSpectrum.StructureSheaf
-- Porting note: currently require lack of hygiene to use in variable declarations
-- maybe all make into notation3?
set_option hygiene false
/-- `Proj` as a locally ringed space -/
local notation3 "Proj" => Proj.toLocallyRingedSpace 𝒜
/-- The underlying topological space of `Proj` -/
local notation3 "Proj.T" => PresheafedSpace.carrier <| SheafedSpace.toPresheafedSpace
<| LocallyRingedSpace.toSheafedSpace <| Proj.toLocallyRingedSpace 𝒜
/-- `Proj` restrict to some open set -/
macro "Proj| " U:term : term =>
`((Proj.toLocallyRingedSpace 𝒜).restrict
(Opens.isOpenEmbedding (X := Proj.T) ($U : Opens Proj.T)))
/-- the underlying topological space of `Proj` restricted to some open set -/
local notation "Proj.T| " U => PresheafedSpace.carrier <| SheafedSpace.toPresheafedSpace
<| LocallyRingedSpace.toSheafedSpace
<| (LocallyRingedSpace.restrict Proj (Opens.isOpenEmbedding (X := Proj.T) (U : Opens Proj.T)))
/-- basic open sets in `Proj` -/
local notation "pbo " x => ProjectiveSpectrum.basicOpen 𝒜 x
/-- basic open sets in `Spec` -/
local notation "sbo " f => PrimeSpectrum.basicOpen f
/-- `Spec` as a locally ringed space -/
local notation3 "Spec " ring => Spec.locallyRingedSpaceObj (CommRingCat.of ring)
/-- the underlying topological space of `Spec` -/
local notation "Spec.T " ring =>
(Spec.locallyRingedSpaceObj (CommRingCat.of ring)).toSheafedSpace.toPresheafedSpace.1
local notation3 "A⁰_ " f => HomogeneousLocalization.Away 𝒜 f
namespace ProjIsoSpecTopComponent
/-
This section is to construct the homeomorphism between `Proj` restricted at basic open set at
a homogeneous element `x` and `Spec A⁰ₓ` where `A⁰ₓ` is the degree zero part of the localized
ring `Aₓ`.
-/
namespace ToSpec
open Ideal
-- This section is to construct the forward direction :
-- So for any `x` in `Proj| (pbo f)`, we need some point in `Spec A⁰_f`, i.e. a prime ideal,
-- and we need this correspondence to be continuous in their Zariski topology.
variable {𝒜}
variable {f : A} {m : ℕ} (x : Proj| (pbo f))
/--
For any `x` in `Proj| (pbo f)`, the corresponding ideal in `Spec A⁰_f`. This fact that this ideal
is prime is proven in `TopComponent.Forward.toFun`. -/
def carrier : Ideal (A⁰_ f) :=
Ideal.comap (algebraMap (A⁰_ f) (Away f))
(x.val.asHomogeneousIdeal.toIdeal.map (algebraMap A (Away f)))
@[simp]
theorem mk_mem_carrier (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) :
HomogeneousLocalization.mk z ∈ carrier x ↔ z.num.1 ∈ x.1.asHomogeneousIdeal := by
rw [carrier, Ideal.mem_comap, HomogeneousLocalization.algebraMap_apply,
HomogeneousLocalization.val_mk, Localization.mk_eq_mk', IsLocalization.mk'_eq_mul_mk'_one,
mul_comm, Ideal.unit_mul_mem_iff_mem, ← Ideal.mem_comap,
IsLocalization.comap_map_of_isPrime_disjoint (.powers f)]
· rfl
· infer_instance
· exact (disjoint_powers_iff_not_mem _ (Ideal.IsPrime.isRadical inferInstance)).mpr x.2
· exact isUnit_of_invertible _
theorem isPrime_carrier : Ideal.IsPrime (carrier x) := by
refine Ideal.IsPrime.comap _ (hK := ?_)
exact IsLocalization.isPrime_of_isPrime_disjoint
(Submonoid.powers f) _ _ inferInstance
((disjoint_powers_iff_not_mem _ (Ideal.IsPrime.isRadical inferInstance)).mpr x.2)
variable (f)
/-- The function between the basic open set `D(f)` in `Proj` to the corresponding basic open set in
`Spec A⁰_f`. This is bundled into a continuous map in `TopComponent.forward`.
-/
@[simps -isSimp]
def toFun (x : Proj.T| pbo f) : Spec.T A⁰_ f :=
⟨carrier x, isPrime_carrier x⟩
/-
The preimage of basic open set `D(a/f^n)` in `Spec A⁰_f` under the forward map from `Proj A` to
`Spec A⁰_f` is the basic open set `D(a) ∩ D(f)` in `Proj A`. This lemma is used to prove that the
forward map is continuous.
-/
theorem preimage_basicOpen (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) :
toFun f ⁻¹' (sbo (HomogeneousLocalization.mk z) : Set (PrimeSpectrum (A⁰_ f))) =
Subtype.val ⁻¹' (pbo z.num.1 : Set (ProjectiveSpectrum 𝒜)) :=
Set.ext fun y ↦ (mk_mem_carrier y z).not
end ToSpec
section
/-- The continuous function from the basic open set `D(f)` in `Proj`
to the corresponding basic open set in `Spec A⁰_f`. -/
@[simps! -isSimp hom_apply_asIdeal]
def toSpec (f : A) : (Proj.T| pbo f) ⟶ Spec.T A⁰_ f :=
TopCat.ofHom
{ toFun := ToSpec.toFun f
continuous_toFun := by
rw [PrimeSpectrum.isTopologicalBasis_basic_opens.continuous_iff]
rintro _ ⟨x, rfl⟩
obtain ⟨x, rfl⟩ := Quotient.mk''_surjective x
rw [ToSpec.preimage_basicOpen]
exact (pbo x.num).2.preimage continuous_subtype_val }
variable {𝒜} in
lemma toSpec_preimage_basicOpen {f} (z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) :
toSpec 𝒜 f ⁻¹' (sbo (HomogeneousLocalization.mk z) : Set (PrimeSpectrum (A⁰_ f))) =
Subtype.val ⁻¹' (pbo z.num.1 : Set (ProjectiveSpectrum 𝒜)) :=
ToSpec.preimage_basicOpen f z
end
namespace FromSpec
open GradedAlgebra SetLike
open Finset hiding mk_zero
open HomogeneousLocalization
variable {𝒜}
variable {f : A} {m : ℕ} (f_deg : f ∈ 𝒜 m)
open Lean Meta Elab Tactic
macro "mem_tac_aux" : tactic =>
`(tactic| first | exact pow_mem_graded _ (Submodule.coe_mem _) | exact natCast_mem_graded _ _ |
exact pow_mem_graded _ f_deg)
macro "mem_tac" : tactic =>
`(tactic| first | mem_tac_aux |
repeat (all_goals (apply SetLike.GradedMonoid.toGradedMul.mul_mem)); mem_tac_aux)
/-- The function from `Spec A⁰_f` to `Proj|D(f)` is defined by `q ↦ {a | aᵢᵐ/fⁱ ∈ q}`, i.e. sending
`q` a prime ideal in `A⁰_f` to the homogeneous prime relevant ideal containing only and all the
elements `a : A` such that for every `i`, the degree 0 element formed by dividing the `m`-th power
of the `i`-th projection of `a` by the `i`-th power of the degree-`m` homogeneous element `f`,
lies in `q`.
The set `{a | aᵢᵐ/fⁱ ∈ q}`
* is an ideal, as proved in `carrier.asIdeal`;
* is homogeneous, as proved in `carrier.asHomogeneousIdeal`;
* is prime, as proved in `carrier.asIdeal.prime`;
* is relevant, as proved in `carrier.relevant`.
-/
def carrier (f_deg : f ∈ 𝒜 m) (q : Spec.T A⁰_ f) : Set A :=
{a | ∀ i, (HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ m, by rw [← smul_eq_mul]; mem_tac⟩,
⟨f ^ i, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.1}
theorem mem_carrier_iff (q : Spec.T A⁰_ f) (a : A) :
a ∈ carrier f_deg q ↔ ∀ i, (HomogeneousLocalization.mk ⟨m * i, ⟨proj 𝒜 i a ^ m, by
rw [← smul_eq_mul]; mem_tac⟩,
⟨f ^ i, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.1 :=
Iff.rfl
theorem mem_carrier_iff' (q : Spec.T A⁰_ f) (a : A) :
a ∈ carrier f_deg q ↔
∀ i, (Localization.mk (proj 𝒜 i a ^ m) ⟨f ^ i, ⟨i, rfl⟩⟩ : Localization.Away f) ∈
algebraMap (HomogeneousLocalization.Away 𝒜 f) (Localization.Away f) '' { s | s ∈ q.1 } :=
(mem_carrier_iff f_deg q a).trans
(by
constructor <;> intro h i <;> specialize h i
· rw [Set.mem_image]; refine ⟨_, h, rfl⟩
· rw [Set.mem_image] at h; rcases h with ⟨x, h, hx⟩
change x ∈ q.asIdeal at h
convert h
rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk]
dsimp only [Subtype.coe_mk]; rw [← hx]; rfl)
theorem mem_carrier_iff_of_mem (hm : 0 < m) (q : Spec.T A⁰_ f) (a : A) {n} (hn : a ∈ 𝒜 n) :
a ∈ carrier f_deg q ↔
(HomogeneousLocalization.mk ⟨m * n, ⟨a ^ m, pow_mem_graded m hn⟩,
⟨f ^ n, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.asIdeal := by
trans (HomogeneousLocalization.mk ⟨m * n, ⟨proj 𝒜 n a ^ m, by rw [← smul_eq_mul]; mem_tac⟩,
⟨f ^ n, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.asIdeal
· refine ⟨fun h ↦ h n, fun h i ↦ if hi : i = n then hi ▸ h else ?_⟩
convert zero_mem q.asIdeal
apply HomogeneousLocalization.val_injective
simp only [proj_apply, decompose_of_mem_ne _ hn (Ne.symm hi), zero_pow hm.ne',
HomogeneousLocalization.val_mk, Localization.mk_zero, HomogeneousLocalization.val_zero]
· simp only [proj_apply, decompose_of_mem_same _ hn]
theorem mem_carrier_iff_of_mem_mul (hm : 0 < m)
(q : Spec.T A⁰_ f) (a : A) {n} (hn : a ∈ 𝒜 (n * m)) :
a ∈ carrier f_deg q ↔ (HomogeneousLocalization.mk ⟨m * n, ⟨a, mul_comm n m ▸ hn⟩,
⟨f ^ n, by rw [mul_comm]; mem_tac⟩, ⟨_, rfl⟩⟩ : A⁰_ f) ∈ q.asIdeal := by
rw [mem_carrier_iff_of_mem f_deg hm q a hn, iff_iff_eq, eq_comm,
← Ideal.IsPrime.pow_mem_iff_mem (α := A⁰_ f) inferInstance m hm]
congr 1
apply HomogeneousLocalization.val_injective
simp only [HomogeneousLocalization.val_mk, HomogeneousLocalization.val_pow,
Localization.mk_pow, pow_mul]
rfl
theorem num_mem_carrier_iff (hm : 0 < m) (q : Spec.T A⁰_ f)
(z : HomogeneousLocalization.NumDenSameDeg 𝒜 (.powers f)) :
z.num.1 ∈ carrier f_deg q ↔ HomogeneousLocalization.mk z ∈ q.asIdeal := by
obtain ⟨n, hn : f ^ n = _⟩ := z.den_mem
have : f ^ n ≠ 0 := fun e ↦ by
have := HomogeneousLocalization.subsingleton 𝒜 (x := .powers f) ⟨n, e⟩
exact IsEmpty.elim (inferInstanceAs (IsEmpty (PrimeSpectrum (A⁰_ f)))) q
convert mem_carrier_iff_of_mem_mul f_deg hm q z.num.1 (n := n) ?_ using 2
· apply HomogeneousLocalization.val_injective; simp only [hn, HomogeneousLocalization.val_mk]
· have := degree_eq_of_mem_mem 𝒜 (SetLike.pow_mem_graded n f_deg) (hn.symm ▸ z.den.2) this
rw [← smul_eq_mul, this]; exact z.num.2
theorem carrier.add_mem (q : Spec.T A⁰_ f) {a b : A} (ha : a ∈ carrier f_deg q)
(hb : b ∈ carrier f_deg q) : a + b ∈ carrier f_deg q := by
refine fun i => (q.2.mem_or_mem ?_).elim id id
change (HomogeneousLocalization.mk ⟨_, _, _, _⟩ : A⁰_ f) ∈ q.1; dsimp only [Subtype.coe_mk]
simp_rw [← pow_add, map_add, add_pow, mul_comm, ← nsmul_eq_mul]
let g : ℕ → A⁰_ f := fun j => (m + m).choose j •
if h2 : m + m < j then (0 : A⁰_ f)
else
-- Porting note: inlining `l`, `r` causes a "can't synth HMul A⁰_ f A⁰_ f ?" error
if h1 : j ≤ m then
letI l : A⁰_ f := HomogeneousLocalization.mk
⟨m * i, ⟨proj 𝒜 i a ^ j * proj 𝒜 i b ^ (m - j), ?_⟩,
⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩
letI r : A⁰_ f := (HomogeneousLocalization.mk
⟨m * i, ⟨proj 𝒜 i b ^ m, by rw [← smul_eq_mul]; mem_tac⟩,
⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩)
l * r
else
letI l : A⁰_ f := HomogeneousLocalization.mk
⟨m * i, ⟨proj 𝒜 i a ^ m, by rw [← smul_eq_mul]; mem_tac⟩,
⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩
letI r : A⁰_ f := HomogeneousLocalization.mk
⟨m * i, ⟨proj 𝒜 i a ^ (j - m) * proj 𝒜 i b ^ (m + m - j), ?_⟩,
⟨_, by rw [mul_comm]; mem_tac⟩, ⟨i, rfl⟩⟩
l * r
rotate_left
· rw [(_ : m * i = _)]
apply GradedMonoid.toGradedMul.mul_mem <;> mem_tac_aux
rw [← add_smul, Nat.add_sub_of_le h1]; rfl
· rw [(_ : m * i = _)]
apply GradedMonoid.toGradedMul.mul_mem (i := (j-m) • i) (j := (m + m - j) • i) <;> mem_tac_aux
rw [← add_smul]; congr; zify [le_of_not_lt h2, le_of_not_le h1]; abel
convert_to ∑ i ∈ range (m + m + 1), g i ∈ q.1; swap
· refine q.1.sum_mem fun j _ => nsmul_mem ?_ _; split_ifs
exacts [q.1.zero_mem, q.1.mul_mem_left _ (hb i), q.1.mul_mem_right _ (ha i)]
rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk]
change _ = (algebraMap (HomogeneousLocalization.Away 𝒜 f) (Localization.Away f)) _
dsimp only [Subtype.coe_mk]; rw [map_sum, mk_sum]
apply Finset.sum_congr rfl fun j hj => _
intro j hj
change _ = HomogeneousLocalization.val _
rw [HomogeneousLocalization.val_smul]
split_ifs with h2 h1
· exact ((Finset.mem_range.1 hj).not_le h2).elim
all_goals simp only [HomogeneousLocalization.val_mul, HomogeneousLocalization.val_zero,
HomogeneousLocalization.val_mk, Subtype.coe_mk, Localization.mk_mul, ← smul_mk]; congr 2
· dsimp; rw [mul_assoc, ← pow_add, add_comm (m - j), Nat.add_sub_assoc h1]
· simp_rw [pow_add]; rfl
· dsimp; rw [← mul_assoc, ← pow_add, Nat.add_sub_of_le (le_of_not_le h1)]
· simp_rw [pow_add]; rfl
variable (hm : 0 < m) (q : Spec.T A⁰_ f)
include hm
theorem carrier.zero_mem : (0 : A) ∈ carrier f_deg q := fun i => by
convert Submodule.zero_mem q.1 using 1
rw [HomogeneousLocalization.ext_iff_val, HomogeneousLocalization.val_mk,
HomogeneousLocalization.val_zero]; simp_rw [map_zero, zero_pow hm.ne']
convert Localization.mk_zero (S := Submonoid.powers f) _ using 1
theorem carrier.smul_mem (c x : A) (hx : x ∈ carrier f_deg q) : c • x ∈ carrier f_deg q := by
revert c
refine DirectSum.Decomposition.inductionOn 𝒜 ?_ ?_ ?_
· rw [zero_smul]; exact carrier.zero_mem f_deg hm _
| · rintro n ⟨a, ha⟩ i
simp_rw [proj_apply, smul_eq_mul, coe_decompose_mul_of_left_mem 𝒜 i ha]
let product : A⁰_ f :=
(HomogeneousLocalization.mk
⟨_, ⟨a ^ m, pow_mem_graded m ha⟩, ⟨_, ?_⟩, ⟨n, rfl⟩⟩ : A⁰_ f) *
| Mathlib/AlgebraicGeometry/ProjectiveSpectrum/Scheme.lean | 392 | 396 |
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Devon Tuma
-/
import Mathlib.Algebra.GroupWithZero.NonZeroDivisors
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.RingTheory.Coprime.Basic
import Mathlib.Tactic.AdaptationNote
/-!
# Scaling the roots of a polynomial
This file defines `scaleRoots p s` for a polynomial `p` in one variable and a ring element `s` to
be the polynomial with root `r * s` for each root `r` of `p` and proves some basic results about it.
-/
variable {R S A K : Type*}
namespace Polynomial
section Semiring
variable [Semiring R] [Semiring S]
/-- `scaleRoots p s` is a polynomial with root `r * s` for each root `r` of `p`. -/
noncomputable def scaleRoots (p : R[X]) (s : R) : R[X] :=
∑ i ∈ p.support, monomial i (p.coeff i * s ^ (p.natDegree - i))
@[simp]
theorem coeff_scaleRoots (p : R[X]) (s : R) (i : ℕ) :
(scaleRoots p s).coeff i = coeff p i * s ^ (p.natDegree - i) := by
simp +contextual [scaleRoots, coeff_monomial]
theorem coeff_scaleRoots_natDegree (p : R[X]) (s : R) :
(scaleRoots p s).coeff p.natDegree = p.leadingCoeff := by
rw [leadingCoeff, coeff_scaleRoots, tsub_self, pow_zero, mul_one]
@[simp]
theorem zero_scaleRoots (s : R) : scaleRoots 0 s = 0 := by
ext
simp
theorem scaleRoots_ne_zero {p : R[X]} (hp : p ≠ 0) (s : R) : scaleRoots p s ≠ 0 := by
intro h
have : p.coeff p.natDegree ≠ 0 := mt leadingCoeff_eq_zero.mp hp
have : (scaleRoots p s).coeff p.natDegree = 0 :=
congr_fun (congr_arg (coeff : R[X] → ℕ → R) h) p.natDegree
rw [coeff_scaleRoots_natDegree] at this
contradiction
theorem support_scaleRoots_le (p : R[X]) (s : R) : (scaleRoots p s).support ≤ p.support := by
intro
simpa using left_ne_zero_of_mul
theorem support_scaleRoots_eq (p : R[X]) {s : R} (hs : s ∈ nonZeroDivisors R) :
(scaleRoots p s).support = p.support :=
le_antisymm (support_scaleRoots_le p s)
(by intro i
simp only [coeff_scaleRoots, Polynomial.mem_support_iff]
intro p_ne_zero ps_zero
have := pow_mem hs (p.natDegree - i) _ ps_zero
contradiction)
@[simp]
theorem degree_scaleRoots (p : R[X]) {s : R} : degree (scaleRoots p s) = degree p := by
haveI := Classical.propDecidable
by_cases hp : p = 0
· rw [hp, zero_scaleRoots]
refine le_antisymm (Finset.sup_mono (support_scaleRoots_le p s)) (degree_le_degree ?_)
rw [coeff_scaleRoots_natDegree]
intro h
have := leadingCoeff_eq_zero.mp h
contradiction
@[simp]
theorem natDegree_scaleRoots (p : R[X]) (s : R) : natDegree (scaleRoots p s) = natDegree p := by
simp only [natDegree, degree_scaleRoots]
theorem monic_scaleRoots_iff {p : R[X]} (s : R) : Monic (scaleRoots p s) ↔ Monic p := by
simp only [Monic, leadingCoeff, natDegree_scaleRoots, coeff_scaleRoots_natDegree]
theorem map_scaleRoots (p : R[X]) (x : R) (f : R →+* S) (h : f p.leadingCoeff ≠ 0) :
(p.scaleRoots x).map f = (p.map f).scaleRoots (f x) := by
ext
simp [Polynomial.natDegree_map_of_leadingCoeff_ne_zero _ h]
@[simp]
lemma scaleRoots_C (r c : R) : (C c).scaleRoots r = C c := by
ext; simp
@[simp]
lemma scaleRoots_one (p : R[X]) :
p.scaleRoots 1 = p := by ext; simp
@[simp]
lemma scaleRoots_zero (p : R[X]) :
p.scaleRoots 0 = p.leadingCoeff • X ^ p.natDegree := by
ext n
simp only [coeff_scaleRoots, ne_eq, tsub_eq_zero_iff_le, not_le, zero_pow_eq, mul_ite,
mul_one, mul_zero, coeff_smul, coeff_X_pow, smul_eq_mul]
split_ifs with h₁ h₂ h₂
· subst h₂; rfl
· exact coeff_eq_zero_of_natDegree_lt (lt_of_le_of_ne h₁ (Ne.symm h₂))
· exact (h₁ h₂.ge).elim
· rfl
@[simp]
lemma one_scaleRoots (r : R) :
(1 : R[X]).scaleRoots r = 1 := by ext; simp
end Semiring
section CommSemiring
variable [Semiring S] [CommSemiring R] [Semiring A] [Field K]
theorem scaleRoots_eval₂_mul_of_commute {p : S[X]} (f : S →+* A) (a : A) (s : S)
(hsa : Commute (f s) a) (hf : ∀ s₁ s₂, Commute (f s₁) (f s₂)) :
eval₂ f (f s * a) (scaleRoots p s) = f s ^ p.natDegree * eval₂ f a p := by
calc
_ = (scaleRoots p s).support.sum fun i =>
f (coeff p i * s ^ (p.natDegree - i)) * (f s * a) ^ i := by
simp [eval₂_eq_sum, sum_def]
_ = p.support.sum fun i => f (coeff p i * s ^ (p.natDegree - i)) * (f s * a) ^ i :=
(Finset.sum_subset (support_scaleRoots_le p s) fun i _hi hi' => by
let this : coeff p i * s ^ (p.natDegree - i) = 0 := by simpa using hi'
simp [this])
_ = p.support.sum fun i : ℕ => f (p.coeff i) * f s ^ (p.natDegree - i + i) * a ^ i :=
(Finset.sum_congr rfl fun i _hi => by
simp_rw [f.map_mul, f.map_pow, pow_add, hsa.mul_pow, mul_assoc])
_ = p.support.sum fun i : ℕ => f s ^ p.natDegree * (f (p.coeff i) * a ^ i) :=
Finset.sum_congr rfl fun i hi => by
rw [mul_assoc, ← map_pow, (hf _ _).left_comm, map_pow, tsub_add_cancel_of_le]
exact le_natDegree_of_ne_zero (Polynomial.mem_support_iff.mp hi)
_ = f s ^ p.natDegree * eval₂ f a p := by simp [← Finset.mul_sum, eval₂_eq_sum, sum_def]
theorem scaleRoots_eval₂_mul {p : S[X]} (f : S →+* R) (r : R) (s : S) :
eval₂ f (f s * r) (scaleRoots p s) = f s ^ p.natDegree * eval₂ f r p :=
scaleRoots_eval₂_mul_of_commute f r s (mul_comm _ _) fun _ _ ↦ mul_comm _ _
theorem scaleRoots_eval₂_eq_zero {p : S[X]} (f : S →+* R) {r : R} {s : S} (hr : eval₂ f r p = 0) :
eval₂ f (f s * r) (scaleRoots p s) = 0 := by rw [scaleRoots_eval₂_mul, hr, mul_zero]
theorem scaleRoots_aeval_eq_zero [Algebra R A] {p : R[X]} {a : A} {r : R} (ha : aeval a p = 0) :
aeval (algebraMap R A r * a) (scaleRoots p r) = 0 := by
rw [aeval_def, scaleRoots_eval₂_mul_of_commute, ← aeval_def, ha, mul_zero]
· apply Algebra.commutes
· intros; rw [Commute, SemiconjBy, ← map_mul, ← map_mul, mul_comm]
theorem scaleRoots_eval₂_eq_zero_of_eval₂_div_eq_zero {p : S[X]} {f : S →+* K}
(hf : Function.Injective f) {r s : S} (hr : eval₂ f (f r / f s) p = 0)
(hs : s ∈ nonZeroDivisors S) : eval₂ f (f r) (scaleRoots p s) = 0 := by
-- if we don't specify the type with `(_ : S)`, the proof is much slower
nontriviality S using Subsingleton.eq_zero (_ : S)
convert @scaleRoots_eval₂_eq_zero _ _ _ _ p f _ s hr
rw [← mul_div_assoc, mul_comm, mul_div_cancel_right₀]
| exact map_ne_zero_of_mem_nonZeroDivisors _ hf hs
| Mathlib/RingTheory/Polynomial/ScaleRoots.lean | 159 | 160 |
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Algebra.Order.Group.Nat
import Mathlib.Data.List.Rotate
import Mathlib.GroupTheory.Perm.Support
/-!
# Permutations from a list
A list `l : List α` can be interpreted as an `Equiv.Perm α` where each element in the list
is permuted to the next one, defined as `formPerm`. When we have that `Nodup l`,
we prove that `Equiv.Perm.support (formPerm l) = l.toFinset`, and that
`formPerm l` is rotationally invariant, in `formPerm_rotate`.
When there are duplicate elements in `l`, how and in what arrangement with respect to the other
elements they appear in the list determines the formed permutation.
This is because `List.formPerm` is implemented as a product of `Equiv.swap`s.
That means that presence of a sublist of two adjacent duplicates like `[..., x, x, ...]`
will produce the same permutation as if the adjacent duplicates were not present.
The `List.formPerm` definition is meant to primarily be used with `Nodup l`, so that
the resulting permutation is cyclic (if `l` has at least two elements).
The presence of duplicates in a particular placement can lead `List.formPerm` to produce a
nontrivial permutation that is noncyclic.
-/
namespace List
variable {α β : Type*}
section FormPerm
variable [DecidableEq α] (l : List α)
open Equiv Equiv.Perm
/-- A list `l : List α` can be interpreted as an `Equiv.Perm α` where each element in the list
is permuted to the next one, defined as `formPerm`. When we have that `Nodup l`,
we prove that `Equiv.Perm.support (formPerm l) = l.toFinset`, and that
`formPerm l` is rotationally invariant, in `formPerm_rotate`.
-/
def formPerm : Equiv.Perm α :=
(zipWith Equiv.swap l l.tail).prod
@[simp]
theorem formPerm_nil : formPerm ([] : List α) = 1 :=
rfl
@[simp]
theorem formPerm_singleton (x : α) : formPerm [x] = 1 :=
rfl
@[simp]
theorem formPerm_cons_cons (x y : α) (l : List α) :
formPerm (x :: y :: l) = swap x y * formPerm (y :: l) :=
prod_cons
theorem formPerm_pair (x y : α) : formPerm [x, y] = swap x y :=
rfl
theorem mem_or_mem_of_zipWith_swap_prod_ne : ∀ {l l' : List α} {x : α},
(zipWith swap l l').prod x ≠ x → x ∈ l ∨ x ∈ l'
| [], _, _ => by simp
| _, [], _ => by simp
| a::l, b::l', x => fun hx ↦
if h : (zipWith swap l l').prod x = x then
(eq_or_eq_of_swap_apply_ne_self (a := a) (b := b) (x := x) (by simpa [h] using hx)).imp
(by rintro rfl; exact .head _) (by rintro rfl; exact .head _)
else
(mem_or_mem_of_zipWith_swap_prod_ne h).imp (.tail _) (.tail _)
theorem zipWith_swap_prod_support' (l l' : List α) :
{ x | (zipWith swap l l').prod x ≠ x } ≤ l.toFinset ⊔ l'.toFinset := fun _ h ↦ by
simpa using mem_or_mem_of_zipWith_swap_prod_ne h
theorem zipWith_swap_prod_support [Fintype α] (l l' : List α) :
(zipWith swap l l').prod.support ≤ l.toFinset ⊔ l'.toFinset := by
intro x hx
have hx' : x ∈ { x | (zipWith swap l l').prod x ≠ x } := by simpa using hx
simpa using zipWith_swap_prod_support' _ _ hx'
theorem support_formPerm_le' : { x | formPerm l x ≠ x } ≤ l.toFinset := by
refine (zipWith_swap_prod_support' l l.tail).trans ?_
simpa [Finset.subset_iff] using tail_subset l
theorem support_formPerm_le [Fintype α] : support (formPerm l) ≤ l.toFinset := by
intro x hx
have hx' : x ∈ { x | formPerm l x ≠ x } := by simpa using hx
simpa using support_formPerm_le' _ hx'
variable {l} {x : α}
theorem mem_of_formPerm_apply_ne (h : l.formPerm x ≠ x) : x ∈ l := by
simpa [or_iff_left_of_imp mem_of_mem_tail] using mem_or_mem_of_zipWith_swap_prod_ne h
theorem formPerm_apply_of_not_mem (h : x ∉ l) : formPerm l x = x :=
not_imp_comm.1 mem_of_formPerm_apply_ne h
theorem formPerm_apply_mem_of_mem (h : x ∈ l) : formPerm l x ∈ l := by
rcases l with - | ⟨y, l⟩
· simp at h
induction' l with z l IH generalizing x y
· simpa using h
· by_cases hx : x ∈ z :: l
· rw [formPerm_cons_cons, mul_apply, swap_apply_def]
split_ifs
· simp [IH _ hx]
· simp
· simp [*]
· replace h : x = y := Or.resolve_right (mem_cons.1 h) hx
simp [formPerm_apply_of_not_mem hx, ← h]
theorem mem_of_formPerm_apply_mem (h : l.formPerm x ∈ l) : x ∈ l := by
contrapose h
rwa [formPerm_apply_of_not_mem h]
@[simp]
theorem formPerm_mem_iff_mem : l.formPerm x ∈ l ↔ x ∈ l :=
⟨l.mem_of_formPerm_apply_mem, l.formPerm_apply_mem_of_mem⟩
@[simp]
theorem formPerm_cons_concat_apply_last (x y : α) (xs : List α) :
formPerm (x :: (xs ++ [y])) y = x := by
induction' xs with z xs IH generalizing x y
· simp
· simp [IH]
@[simp]
theorem formPerm_apply_getLast (x : α) (xs : List α) :
formPerm (x :: xs) ((x :: xs).getLast (cons_ne_nil x xs)) = x := by
induction' xs using List.reverseRecOn with xs y _ generalizing x <;> simp
@[simp]
theorem formPerm_apply_getElem_length (x : α) (xs : List α) :
formPerm (x :: xs) (x :: xs)[xs.length] = x := by
rw [getElem_cons_length rfl, formPerm_apply_getLast]
theorem formPerm_apply_head (x y : α) (xs : List α) (h : Nodup (x :: y :: xs)) :
formPerm (x :: y :: xs) x = y := by simp [formPerm_apply_of_not_mem h.not_mem]
theorem formPerm_apply_getElem_zero (l : List α) (h : Nodup l) (hl : 1 < l.length) :
formPerm l l[0] = l[1] := by
rcases l with (_ | ⟨x, _ | ⟨y, tl⟩⟩)
· simp at hl
· simp at hl
· rw [getElem_cons_zero, formPerm_apply_head _ _ _ h, getElem_cons_succ, getElem_cons_zero]
variable (l)
theorem formPerm_eq_head_iff_eq_getLast (x y : α) :
formPerm (y :: l) x = y ↔ x = getLast (y :: l) (cons_ne_nil _ _) :=
Iff.trans (by rw [formPerm_apply_getLast]) (formPerm (y :: l)).injective.eq_iff
theorem formPerm_apply_lt_getElem (xs : List α) (h : Nodup xs) (n : ℕ) (hn : n + 1 < xs.length) :
formPerm xs xs[n] = xs[n + 1] := by
induction' n with n IH generalizing xs
· simpa using formPerm_apply_getElem_zero _ h _
· rcases xs with (_ | ⟨x, _ | ⟨y, l⟩⟩)
· simp at hn
· rw [formPerm_singleton, getElem_singleton, getElem_singleton, one_apply]
· specialize IH (y :: l) h.of_cons _
· simpa [Nat.succ_lt_succ_iff] using hn
simp only [swap_apply_eq_iff, coe_mul, formPerm_cons_cons, Function.comp]
simp only [getElem_cons_succ] at *
rw [← IH, swap_apply_of_ne_of_ne] <;>
· intro hx
rw [← hx, IH] at h
simp [getElem_mem] at h
theorem formPerm_apply_getElem (xs : List α) (w : Nodup xs) (i : ℕ) (h : i < xs.length) :
formPerm xs xs[i] =
xs[(i + 1) % xs.length]'(Nat.mod_lt _ (i.zero_le.trans_lt h)) := by
rcases xs with - | ⟨x, xs⟩
· simp at h
· have : i ≤ xs.length := by
refine Nat.le_of_lt_succ ?_
simpa using h
rcases this.eq_or_lt with (rfl | hn')
· simp
· rw [formPerm_apply_lt_getElem (x :: xs) w _ (Nat.succ_lt_succ hn')]
congr
rw [Nat.mod_eq_of_lt]; simpa [Nat.succ_eq_add_one]
theorem support_formPerm_of_nodup' (l : List α) (h : Nodup l) (h' : ∀ x : α, l ≠ [x]) :
{ x | formPerm l x ≠ x } = l.toFinset := by
apply _root_.le_antisymm
· exact support_formPerm_le' l
· intro x hx
simp only [Finset.mem_coe, mem_toFinset] at hx
obtain ⟨n, hn, rfl⟩ := getElem_of_mem hx
rw [Set.mem_setOf_eq, formPerm_apply_getElem _ h]
intro H
rw [nodup_iff_injective_get, Function.Injective] at h
specialize h H
rcases (Nat.succ_le_of_lt hn).eq_or_lt with hn' | hn'
· simp only [← hn', Nat.mod_self] at h
refine not_exists.mpr h' ?_
rw [← length_eq_one_iff, ← hn', (Fin.mk.inj_iff.mp h).symm]
· simp [Nat.mod_eq_of_lt hn'] at h
theorem support_formPerm_of_nodup [Fintype α] (l : List α) (h : Nodup l) (h' : ∀ x : α, l ≠ [x]) :
support (formPerm l) = l.toFinset := by
rw [← Finset.coe_inj]
convert support_formPerm_of_nodup' _ h h'
simp [Set.ext_iff]
theorem formPerm_rotate_one (l : List α) (h : Nodup l) : formPerm (l.rotate 1) = formPerm l := by
have h' : Nodup (l.rotate 1) := by simpa using h
ext x
by_cases hx : x ∈ l.rotate 1
· obtain ⟨k, hk, rfl⟩ := getElem_of_mem hx
rw [formPerm_apply_getElem _ h', getElem_rotate l, getElem_rotate l, formPerm_apply_getElem _ h]
simp
· rw [formPerm_apply_of_not_mem hx, formPerm_apply_of_not_mem]
simpa using hx
theorem formPerm_rotate (l : List α) (h : Nodup l) (n : ℕ) :
formPerm (l.rotate n) = formPerm l := by
induction n with
| zero => simp
| succ n hn =>
rw [← rotate_rotate, formPerm_rotate_one, hn]
rwa [IsRotated.nodup_iff]
exact IsRotated.forall l n
theorem formPerm_eq_of_isRotated {l l' : List α} (hd : Nodup l) (h : l ~r l') :
formPerm l = formPerm l' := by
obtain ⟨n, rfl⟩ := h
exact (formPerm_rotate l hd n).symm
theorem formPerm_append_pair : ∀ (l : List α) (a b : α),
formPerm (l ++ [a, b]) = formPerm (l ++ [a]) * swap a b
| [], _, _ => rfl
| [_], _, _ => rfl
| x::y::l, a, b => by
simpa [mul_assoc] using formPerm_append_pair (y::l) a b
theorem formPerm_reverse : ∀ l : List α, formPerm l.reverse = (formPerm l)⁻¹
| [] => rfl
| [_] => rfl
| a::b::l => by
simp [formPerm_append_pair, swap_comm, ← formPerm_reverse (b::l)]
theorem formPerm_pow_apply_getElem (l : List α) (w : Nodup l) (n : ℕ) (i : ℕ) (h : i < l.length) :
(formPerm l ^ n) l[i] =
l[(i + n) % l.length]'(Nat.mod_lt _ (i.zero_le.trans_lt h)) := by
induction n with
| zero => simp [Nat.mod_eq_of_lt h]
| succ n hn =>
simp [pow_succ', mul_apply, hn, formPerm_apply_getElem _ w, Nat.succ_eq_add_one,
← Nat.add_assoc]
theorem formPerm_pow_apply_head (x : α) (l : List α) (h : Nodup (x :: l)) (n : ℕ) :
(formPerm (x :: l) ^ n) x =
(x :: l)[(n % (x :: l).length)]'(Nat.mod_lt _ (Nat.zero_lt_succ _)) := by
convert formPerm_pow_apply_getElem _ h n 0 (Nat.succ_pos _)
simp
theorem formPerm_ext_iff {x y x' y' : α} {l l' : List α} (hd : Nodup (x :: y :: l))
(hd' : Nodup (x' :: y' :: l')) :
formPerm (x :: y :: l) = formPerm (x' :: y' :: l') ↔ (x :: y :: l) ~r (x' :: y' :: l') := by
refine ⟨fun h => ?_, fun hr => formPerm_eq_of_isRotated hd hr⟩
rw [Equiv.Perm.ext_iff] at h
have hx : x' ∈ x :: y :: l := by
have : x' ∈ { z | formPerm (x :: y :: l) z ≠ z } := by
rw [Set.mem_setOf_eq, h x', formPerm_apply_head _ _ _ hd']
simp only [mem_cons, nodup_cons] at hd'
push_neg at hd'
exact hd'.left.left.symm
simpa using support_formPerm_le' _ this
| obtain ⟨⟨n, hn⟩, hx'⟩ := get_of_mem hx
have hl : (x :: y :: l).length = (x' :: y' :: l').length := by
rw [← dedup_eq_self.mpr hd, ← dedup_eq_self.mpr hd', ← card_toFinset, ← card_toFinset]
refine congr_arg Finset.card ?_
rw [← Finset.coe_inj, ← support_formPerm_of_nodup' _ hd (by simp), ←
| Mathlib/GroupTheory/Perm/List.lean | 275 | 279 |
/-
Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel
-/
import Mathlib.Data.ENNReal.Real
import Mathlib.Tactic.Bound.Attribute
import Mathlib.Topology.Bornology.Basic
import Mathlib.Topology.EMetricSpace.Defs
import Mathlib.Topology.UniformSpace.Basic
/-!
## Pseudo-metric spaces
This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the
condition `dist x y = 0 → x = y`.
Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform
spaces and topological spaces. For example: open and closed sets, compactness, completeness,
continuity and uniform continuity.
## Main definitions
* `Dist α`: Endows a space `α` with a function `dist a b`.
* `PseudoMetricSpace α`: A space endowed with a distance function, which can
be zero even if the two elements are non-equal.
* `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`.
* `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded.
* `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`.
Additional useful definitions:
* `nndist a b`: `dist` as a function to the non-negative reals.
* `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`.
* `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`.
TODO (anyone): Add "Main results" section.
## Tags
pseudo_metric, dist
-/
assert_not_exists compactSpace_uniformity
open Set Filter TopologicalSpace Bornology
open scoped ENNReal NNReal Uniformity Topology
universe u v w
variable {α : Type u} {β : Type v} {X ι : Type*}
theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε :=
⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩
/-- Construct a uniform structure from a distance function and metric space axioms -/
def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0)
(dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α :=
.ofFun dist dist_self dist_comm dist_triangle ofDist_aux
/-- Construct a bornology from a distance function and metric space axioms. -/
abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x)
(dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α :=
Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C }
⟨0, fun _ hx _ => hx.elim⟩ (fun _ ⟨c, hc⟩ _ h => ⟨c, fun _ hx _ hy => hc (h hx) (h hy)⟩)
(fun s hs t ht => by
rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩
· rwa [empty_union]
rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩
· rwa [union_empty]
rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C
· refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩
simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb)
rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩
refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim
(fun hz => (hs hx hz).trans (le_max_left _ _))
(fun hz => (dist_triangle x y z).trans <|
(add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩)
fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩
/-- The distance function (given an ambient metric space on `α`), which returns
a nonnegative real number `dist x y` given `x y : α`. -/
@[ext]
class Dist (α : Type*) where
/-- Distance between two points -/
dist : α → α → ℝ
export Dist (dist)
-- the uniform structure and the emetric space structure are embedded in the metric space structure
-- to avoid instance diamond issues. See Note [forgetful inheritance].
/-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/
private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y :=
have : 0 ≤ 2 * dist x y :=
calc 0 = dist x x := (dist_self _).symm
_ ≤ dist x y + dist y x := dist_triangle _ _ _
_ = 2 * dist x y := by rw [two_mul, dist_comm]
nonneg_of_mul_nonneg_right this two_pos
/-- A pseudometric space is a type endowed with a `ℝ`-valued distance `dist` satisfying
reflexivity `dist x x = 0`, commutativity `dist x y = dist y x`, and the triangle inequality
`dist x z ≤ dist x y + dist y z`.
Note that we do not require `dist x y = 0 → x = y`. See metric spaces (`MetricSpace`) for the
similar class with that stronger assumption.
Any pseudometric space is a topological space and a uniform space (see `TopologicalSpace`,
`UniformSpace`), where the topology and uniformity come from the metric.
Note that a T1 pseudometric space is just a metric space.
We make the uniformity/topology part of the data instead of deriving it from the metric. This eg
ensures that we do not get a diamond when doing
`[PseudoMetricSpace α] [PseudoMetricSpace β] : TopologicalSpace (α × β)`:
The product metric and product topology agree, but not definitionally so.
See Note [forgetful inheritance]. -/
class PseudoMetricSpace (α : Type u) : Type u extends Dist α where
dist_self : ∀ x : α, dist x x = 0
dist_comm : ∀ x y : α, dist x y = dist y x
dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z
/-- Extended distance between two points -/
edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩
edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y) := by
intros x y; exact ENNReal.coe_nnreal_eq _
toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle
uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl
toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets : (Bornology.cobounded α).sets =
{ s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl
/-- Two pseudo metric space structures with the same distance function coincide. -/
@[ext]
theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α}
(h : m.toDist = m'.toDist) : m = m' := by
let d := m.toDist
obtain ⟨_, _, _, _, hed, _, hU, _, hB⟩ := m
let d' := m'.toDist
obtain ⟨_, _, _, _, hed', _, hU', _, hB'⟩ := m'
obtain rfl : d = d' := h
congr
· ext x y : 2
rw [hed, hed']
· exact UniformSpace.ext (hU.trans hU'.symm)
· ext : 2
rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB']
variable [PseudoMetricSpace α]
attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology
-- see Note [lower instance priority]
instance (priority := 200) PseudoMetricSpace.toEDist : EDist α :=
⟨PseudoMetricSpace.edist⟩
/-- Construct a pseudo-metric space structure whose underlying topological space structure
(definitionally) agrees which a pre-existing topology which is compatible with a given distance
function. -/
def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ)
(dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x)
(dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z)
(H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) :
PseudoMetricSpace α :=
{ dist := dist
dist_self := dist_self
dist_comm := dist_comm
dist_triangle := dist_triangle
toUniformSpace :=
(UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <|
TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦
((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle
UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm
uniformity_dist := rfl
toBornology := Bornology.ofDist dist dist_comm dist_triangle
cobounded_sets := rfl }
@[simp]
theorem dist_self (x : α) : dist x x = 0 :=
PseudoMetricSpace.dist_self x
theorem dist_comm (x y : α) : dist x y = dist y x :=
PseudoMetricSpace.dist_comm x y
theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) :=
PseudoMetricSpace.edist_dist x y
@[bound]
theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z :=
PseudoMetricSpace.dist_triangle x y z
theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by
rw [dist_comm z]; apply dist_triangle
theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by
rw [dist_comm y]; apply dist_triangle
theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w :=
calc
dist x w ≤ dist x z + dist z w := dist_triangle x z w
_ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _
theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) :
dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by
rw [add_left_comm, dist_comm x₁, ← add_assoc]
apply dist_triangle4
theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) :
dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by
rw [add_right_comm, dist_comm y₁]
apply dist_triangle4
theorem dist_triangle8 (a b c d e f g h : α) : dist a h ≤ dist a b + dist b c + dist c d
+ dist d e + dist e f + dist f g + dist g h := by
apply le_trans (dist_triangle4 a f g h)
apply add_le_add_right (add_le_add_right _ (dist f g)) (dist g h)
apply le_trans (dist_triangle4 a d e f)
apply add_le_add_right (add_le_add_right _ (dist d e)) (dist e f)
exact dist_triangle4 a b c d
theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _
theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y :=
abs_sub_le_iff.2
⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩
@[bound]
theorem dist_nonneg {x y : α} : 0 ≤ dist x y :=
dist_nonneg' dist dist_self dist_comm dist_triangle
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
/-- Extension for the `positivity` tactic: distances are nonnegative. -/
@[positivity Dist.dist _ _]
def evalDist : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) =>
let _inst ← synthInstanceQ q(PseudoMetricSpace $β)
assertInstancesCommute
pure (.nonnegative q(dist_nonneg))
| _, _, _ => throwError "not dist"
end Mathlib.Meta.Positivity
example {x y : α} : 0 ≤ dist x y := by positivity
@[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg
/-- A version of `Dist` that takes value in `ℝ≥0`. -/
class NNDist (α : Type*) where
/-- Nonnegative distance between two points -/
nndist : α → α → ℝ≥0
export NNDist (nndist)
-- see Note [lower instance priority]
/-- Distance as a nonnegative real number. -/
instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α :=
⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩
/-- Express `dist` in terms of `nndist` -/
theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl
@[simp, norm_cast]
theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl
/-- Express `edist` in terms of `nndist` -/
theorem edist_nndist (x y : α) : edist x y = nndist x y := by
rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal]
/-- Express `nndist` in terms of `edist` -/
theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by
simp [edist_nndist]
@[simp, norm_cast]
theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y :=
(edist_nndist x y).symm
@[simp, norm_cast]
theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by
rw [edist_nndist, ENNReal.coe_lt_coe]
@[simp, norm_cast]
theorem edist_le_coe {x y : α} {c : ℝ≥0} : edist x y ≤ c ↔ nndist x y ≤ c := by
rw [edist_nndist, ENNReal.coe_le_coe]
/-- In a pseudometric space, the extended distance is always finite -/
theorem edist_lt_top {α : Type*} [PseudoMetricSpace α] (x y : α) : edist x y < ⊤ :=
(edist_dist x y).symm ▸ ENNReal.ofReal_lt_top
/-- In a pseudometric space, the extended distance is always finite -/
theorem edist_ne_top (x y : α) : edist x y ≠ ⊤ :=
(edist_lt_top x y).ne
/-- `nndist x x` vanishes -/
@[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a)
@[simp, norm_cast]
theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c :=
Iff.rfl
@[simp, norm_cast]
theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c :=
Iff.rfl
@[simp]
theorem edist_lt_ofReal {x y : α} {r : ℝ} : edist x y < ENNReal.ofReal r ↔ dist x y < r := by
rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg]
@[simp]
theorem edist_le_ofReal {x y : α} {r : ℝ} (hr : 0 ≤ r) :
edist x y ≤ ENNReal.ofReal r ↔ dist x y ≤ r := by
rw [edist_dist, ENNReal.ofReal_le_ofReal_iff hr]
/-- Express `nndist` in terms of `dist` -/
theorem nndist_dist (x y : α) : nndist x y = Real.toNNReal (dist x y) := by
rw [dist_nndist, Real.toNNReal_coe]
theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y
/-- Triangle inequality for the nonnegative distance -/
theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z :=
dist_triangle _ _ _
theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y :=
dist_triangle_left _ _ _
theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z :=
dist_triangle_right _ _ _
/-- Express `dist` in terms of `edist` -/
theorem dist_edist (x y : α) : dist x y = (edist x y).toReal := by
rw [edist_dist, ENNReal.toReal_ofReal dist_nonneg]
namespace Metric
-- instantiate pseudometric space as a topology
variable {x y z : α} {δ ε ε₁ ε₂ : ℝ} {s : Set α}
/-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/
def ball (x : α) (ε : ℝ) : Set α :=
{ y | dist y x < ε }
@[simp]
theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε :=
Iff.rfl
theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball]
theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε :=
dist_nonneg.trans_lt hy
theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by
rwa [mem_ball, dist_self]
@[simp]
theorem nonempty_ball : (ball x ε).Nonempty ↔ 0 < ε :=
⟨fun ⟨_x, hx⟩ => pos_of_mem_ball hx, fun h => ⟨x, mem_ball_self h⟩⟩
@[simp]
theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt]
@[simp]
theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty]
/-- If a point belongs to an open ball, then there is a strictly smaller radius whose ball also
contains it.
See also `exists_lt_subset_ball`. -/
theorem exists_lt_mem_ball_of_mem_ball (h : x ∈ ball y ε) : ∃ ε' < ε, x ∈ ball y ε' := by
simp only [mem_ball] at h ⊢
exact ⟨(dist x y + ε) / 2, by linarith, by linarith⟩
theorem ball_eq_ball (ε : ℝ) (x : α) :
UniformSpace.ball x { p | dist p.2 p.1 < ε } = Metric.ball x ε :=
rfl
theorem ball_eq_ball' (ε : ℝ) (x : α) :
UniformSpace.ball x { p | dist p.1 p.2 < ε } = Metric.ball x ε := by
ext
simp [dist_comm, UniformSpace.ball]
@[simp]
theorem iUnion_ball_nat (x : α) : ⋃ n : ℕ, ball x n = univ :=
iUnion_eq_univ_iff.2 fun y => exists_nat_gt (dist y x)
@[simp]
theorem iUnion_ball_nat_succ (x : α) : ⋃ n : ℕ, ball x (n + 1) = univ :=
iUnion_eq_univ_iff.2 fun y => (exists_nat_gt (dist y x)).imp fun _ h => h.trans (lt_add_one _)
/-- `closedBall x ε` is the set of all points `y` with `dist y x ≤ ε` -/
def closedBall (x : α) (ε : ℝ) :=
{ y | dist y x ≤ ε }
@[simp] theorem mem_closedBall : y ∈ closedBall x ε ↔ dist y x ≤ ε := Iff.rfl
theorem mem_closedBall' : y ∈ closedBall x ε ↔ dist x y ≤ ε := by rw [dist_comm, mem_closedBall]
/-- `sphere x ε` is the set of all points `y` with `dist y x = ε` -/
def sphere (x : α) (ε : ℝ) := { y | dist y x = ε }
@[simp] theorem mem_sphere : y ∈ sphere x ε ↔ dist y x = ε := Iff.rfl
theorem mem_sphere' : y ∈ sphere x ε ↔ dist x y = ε := by rw [dist_comm, mem_sphere]
theorem ne_of_mem_sphere (h : y ∈ sphere x ε) (hε : ε ≠ 0) : y ≠ x :=
ne_of_mem_of_not_mem h <| by simpa using hε.symm
theorem nonneg_of_mem_sphere (hy : y ∈ sphere x ε) : 0 ≤ ε :=
dist_nonneg.trans_eq hy
@[simp]
theorem sphere_eq_empty_of_neg (hε : ε < 0) : sphere x ε = ∅ :=
Set.eq_empty_iff_forall_not_mem.mpr fun _y hy => (nonneg_of_mem_sphere hy).not_lt hε
theorem sphere_eq_empty_of_subsingleton [Subsingleton α] (hε : ε ≠ 0) : sphere x ε = ∅ :=
Set.eq_empty_iff_forall_not_mem.mpr fun _ h => ne_of_mem_sphere h hε (Subsingleton.elim _ _)
instance sphere_isEmpty_of_subsingleton [Subsingleton α] [NeZero ε] : IsEmpty (sphere x ε) := by
rw [sphere_eq_empty_of_subsingleton (NeZero.ne ε)]; infer_instance
theorem closedBall_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 ≤ ε) :
closedBall x ε = {x} := by
ext x'
simpa [Subsingleton.allEq x x']
theorem ball_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 < ε) : ball x ε = {x} := by
ext x'
simpa [Subsingleton.allEq x x']
theorem mem_closedBall_self (h : 0 ≤ ε) : x ∈ closedBall x ε := by
rwa [mem_closedBall, dist_self]
@[simp]
theorem nonempty_closedBall : (closedBall x ε).Nonempty ↔ 0 ≤ ε :=
⟨fun ⟨_x, hx⟩ => dist_nonneg.trans hx, fun h => ⟨x, mem_closedBall_self h⟩⟩
@[simp]
theorem closedBall_eq_empty : closedBall x ε = ∅ ↔ ε < 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_closedBall, not_le]
/-- Closed balls and spheres coincide when the radius is non-positive -/
theorem closedBall_eq_sphere_of_nonpos (hε : ε ≤ 0) : closedBall x ε = sphere x ε :=
Set.ext fun _ => (hε.trans dist_nonneg).le_iff_eq
theorem ball_subset_closedBall : ball x ε ⊆ closedBall x ε := fun _y hy =>
mem_closedBall.2 (le_of_lt hy)
theorem sphere_subset_closedBall : sphere x ε ⊆ closedBall x ε := fun _ => le_of_eq
lemma sphere_subset_ball {r R : ℝ} (h : r < R) : sphere x r ⊆ ball x R := fun _x hx ↦
(mem_sphere.1 hx).trans_lt h
theorem closedBall_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (closedBall x δ) (ball y ε) :=
Set.disjoint_left.mpr fun _a ha1 ha2 =>
(h.trans <| dist_triangle_left _ _ _).not_lt <| add_lt_add_of_le_of_lt ha1 ha2
theorem ball_disjoint_closedBall (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (closedBall y ε) :=
(closedBall_disjoint_ball <| by rwa [add_comm, dist_comm]).symm
theorem ball_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (ball y ε) :=
(closedBall_disjoint_ball h).mono_left ball_subset_closedBall
theorem closedBall_disjoint_closedBall (h : δ + ε < dist x y) :
Disjoint (closedBall x δ) (closedBall y ε) :=
Set.disjoint_left.mpr fun _a ha1 ha2 =>
h.not_le <| (dist_triangle_left _ _ _).trans <| add_le_add ha1 ha2
theorem sphere_disjoint_ball : Disjoint (sphere x ε) (ball x ε) :=
Set.disjoint_left.mpr fun _y hy₁ hy₂ => absurd hy₁ <| ne_of_lt hy₂
@[simp]
theorem ball_union_sphere : ball x ε ∪ sphere x ε = closedBall x ε :=
Set.ext fun _y => (@le_iff_lt_or_eq ℝ _ _ _).symm
@[simp]
theorem sphere_union_ball : sphere x ε ∪ ball x ε = closedBall x ε := by
rw [union_comm, ball_union_sphere]
@[simp]
theorem closedBall_diff_sphere : closedBall x ε \ sphere x ε = ball x ε := by
rw [← ball_union_sphere, Set.union_diff_cancel_right sphere_disjoint_ball.symm.le_bot]
@[simp]
theorem closedBall_diff_ball : closedBall x ε \ ball x ε = sphere x ε := by
rw [← ball_union_sphere, Set.union_diff_cancel_left sphere_disjoint_ball.symm.le_bot]
theorem mem_ball_comm : x ∈ ball y ε ↔ y ∈ ball x ε := by rw [mem_ball', mem_ball]
theorem mem_closedBall_comm : x ∈ closedBall y ε ↔ y ∈ closedBall x ε := by
rw [mem_closedBall', mem_closedBall]
theorem mem_sphere_comm : x ∈ sphere y ε ↔ y ∈ sphere x ε := by rw [mem_sphere', mem_sphere]
@[gcongr]
theorem ball_subset_ball (h : ε₁ ≤ ε₂) : ball x ε₁ ⊆ ball x ε₂ := fun _y yx =>
lt_of_lt_of_le (mem_ball.1 yx) h
theorem closedBall_eq_bInter_ball : closedBall x ε = ⋂ δ > ε, ball x δ := by
ext y; rw [mem_closedBall, ← forall_lt_iff_le', mem_iInter₂]; rfl
theorem ball_subset_ball' (h : ε₁ + dist x y ≤ ε₂) : ball x ε₁ ⊆ ball y ε₂ := fun z hz =>
calc
dist z y ≤ dist z x + dist x y := dist_triangle _ _ _
_ < ε₁ + dist x y := add_lt_add_right (mem_ball.1 hz) _
_ ≤ ε₂ := h
@[gcongr]
theorem closedBall_subset_closedBall (h : ε₁ ≤ ε₂) : closedBall x ε₁ ⊆ closedBall x ε₂ :=
fun _y (yx : _ ≤ ε₁) => le_trans yx h
theorem closedBall_subset_closedBall' (h : ε₁ + dist x y ≤ ε₂) :
closedBall x ε₁ ⊆ closedBall y ε₂ := fun z hz =>
calc
dist z y ≤ dist z x + dist x y := dist_triangle _ _ _
_ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _
_ ≤ ε₂ := h
theorem closedBall_subset_ball (h : ε₁ < ε₂) : closedBall x ε₁ ⊆ ball x ε₂ :=
fun y (yh : dist y x ≤ ε₁) => lt_of_le_of_lt yh h
theorem closedBall_subset_ball' (h : ε₁ + dist x y < ε₂) :
closedBall x ε₁ ⊆ ball y ε₂ := fun z hz =>
calc
dist z y ≤ dist z x + dist x y := dist_triangle _ _ _
_ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _
_ < ε₂ := h
theorem dist_le_add_of_nonempty_closedBall_inter_closedBall
(h : (closedBall x ε₁ ∩ closedBall y ε₂).Nonempty) : dist x y ≤ ε₁ + ε₂ :=
let ⟨z, hz⟩ := h
calc
dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _
_ ≤ ε₁ + ε₂ := add_le_add hz.1 hz.2
theorem dist_lt_add_of_nonempty_closedBall_inter_ball (h : (closedBall x ε₁ ∩ ball y ε₂).Nonempty) :
dist x y < ε₁ + ε₂ :=
let ⟨z, hz⟩ := h
calc
dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _
_ < ε₁ + ε₂ := add_lt_add_of_le_of_lt hz.1 hz.2
theorem dist_lt_add_of_nonempty_ball_inter_closedBall (h : (ball x ε₁ ∩ closedBall y ε₂).Nonempty) :
dist x y < ε₁ + ε₂ := by
rw [inter_comm] at h
rw [add_comm, dist_comm]
exact dist_lt_add_of_nonempty_closedBall_inter_ball h
theorem dist_lt_add_of_nonempty_ball_inter_ball (h : (ball x ε₁ ∩ ball y ε₂).Nonempty) :
dist x y < ε₁ + ε₂ :=
dist_lt_add_of_nonempty_closedBall_inter_ball <|
h.mono (inter_subset_inter ball_subset_closedBall Subset.rfl)
@[simp]
theorem iUnion_closedBall_nat (x : α) : ⋃ n : ℕ, closedBall x n = univ :=
iUnion_eq_univ_iff.2 fun y => exists_nat_ge (dist y x)
theorem iUnion_inter_closedBall_nat (s : Set α) (x : α) : ⋃ n : ℕ, s ∩ closedBall x n = s := by
rw [← inter_iUnion, iUnion_closedBall_nat, inter_univ]
theorem ball_subset (h : dist x y ≤ ε₂ - ε₁) : ball x ε₁ ⊆ ball y ε₂ := fun z zx => by
rw [← add_sub_cancel ε₁ ε₂]
exact lt_of_le_of_lt (dist_triangle z x y) (add_lt_add_of_lt_of_le zx h)
theorem ball_half_subset (y) (h : y ∈ ball x (ε / 2)) : ball y (ε / 2) ⊆ ball x ε :=
ball_subset <| by rw [sub_self_div_two]; exact le_of_lt h
theorem exists_ball_subset_ball (h : y ∈ ball x ε) : ∃ ε' > 0, ball y ε' ⊆ ball x ε :=
⟨_, sub_pos.2 h, ball_subset <| by rw [sub_sub_self]⟩
/-- If a property holds for all points in closed balls of arbitrarily large radii, then it holds for
all points. -/
theorem forall_of_forall_mem_closedBall (p : α → Prop) (x : α)
(H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ closedBall x R, p y) (y : α) : p y := by
obtain ⟨R, hR, h⟩ : ∃ R ≥ dist y x, ∀ z : α, z ∈ closedBall x R → p z :=
frequently_iff.1 H (Ici_mem_atTop (dist y x))
exact h _ hR
/-- If a property holds for all points in balls of arbitrarily large radii, then it holds for all
points. -/
theorem forall_of_forall_mem_ball (p : α → Prop) (x : α)
(H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ ball x R, p y) (y : α) : p y := by
obtain ⟨R, hR, h⟩ : ∃ R > dist y x, ∀ z : α, z ∈ ball x R → p z :=
frequently_iff.1 H (Ioi_mem_atTop (dist y x))
exact h _ hR
theorem isBounded_iff {s : Set α} :
IsBounded s ↔ ∃ C : ℝ, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := by
rw [isBounded_def, ← Filter.mem_sets, @PseudoMetricSpace.cobounded_sets α, mem_setOf_eq,
compl_compl]
theorem isBounded_iff_eventually {s : Set α} :
IsBounded s ↔ ∀ᶠ C in atTop, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C :=
isBounded_iff.trans
⟨fun ⟨C, h⟩ => eventually_atTop.2 ⟨C, fun _C' hC' _x hx _y hy => (h hx hy).trans hC'⟩,
Eventually.exists⟩
theorem isBounded_iff_exists_ge {s : Set α} (c : ℝ) :
IsBounded s ↔ ∃ C, c ≤ C ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C :=
⟨fun h => ((eventually_ge_atTop c).and (isBounded_iff_eventually.1 h)).exists, fun h =>
isBounded_iff.2 <| h.imp fun _ => And.right⟩
theorem isBounded_iff_nndist {s : Set α} :
IsBounded s ↔ ∃ C : ℝ≥0, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → nndist x y ≤ C := by
simp only [isBounded_iff_exists_ge 0, NNReal.exists, ← NNReal.coe_le_coe, ← dist_nndist,
NNReal.coe_mk, exists_prop]
theorem toUniformSpace_eq :
‹PseudoMetricSpace α›.toUniformSpace = .ofDist dist dist_self dist_comm dist_triangle :=
UniformSpace.ext PseudoMetricSpace.uniformity_dist
theorem uniformity_basis_dist :
(𝓤 α).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { p : α × α | dist p.1 p.2 < ε } := by
rw [toUniformSpace_eq]
exact UniformSpace.hasBasis_ofFun (exists_gt _) _ _ _ _ _
/-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers
accumulating to zero, then `f i`-neighborhoods of the diagonal form a basis of `𝓤 α`.
For specific bases see `uniformity_basis_dist`, `uniformity_basis_dist_inv_nat_succ`,
and `uniformity_basis_dist_inv_nat_pos`. -/
protected theorem mk_uniformity_basis {β : Type*} {p : β → Prop} {f : β → ℝ}
(hf₀ : ∀ i, p i → 0 < f i) (hf : ∀ ⦃ε⦄, 0 < ε → ∃ i, p i ∧ f i ≤ ε) :
(𝓤 α).HasBasis p fun i => { p : α × α | dist p.1 p.2 < f i } := by
refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩
constructor
· rintro ⟨ε, ε₀, hε⟩
rcases hf ε₀ with ⟨i, hi, H⟩
exact ⟨i, hi, fun x (hx : _ < _) => hε <| lt_of_lt_of_le hx H⟩
· exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, H⟩
theorem uniformity_basis_dist_rat :
(𝓤 α).HasBasis (fun r : ℚ => 0 < r) fun r => { p : α × α | dist p.1 p.2 < r } :=
Metric.mk_uniformity_basis (fun _ => Rat.cast_pos.2) fun _ε hε =>
let ⟨r, hr0, hrε⟩ := exists_rat_btwn hε
⟨r, Rat.cast_pos.1 hr0, hrε.le⟩
theorem uniformity_basis_dist_inv_nat_succ :
(𝓤 α).HasBasis (fun _ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / (↑n + 1) } :=
Metric.mk_uniformity_basis (fun n _ => div_pos zero_lt_one <| Nat.cast_add_one_pos n) fun _ε ε0 =>
(exists_nat_one_div_lt ε0).imp fun _n hn => ⟨trivial, le_of_lt hn⟩
theorem uniformity_basis_dist_inv_nat_pos :
(𝓤 α).HasBasis (fun n : ℕ => 0 < n) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / ↑n } :=
Metric.mk_uniformity_basis (fun _ hn => div_pos zero_lt_one <| Nat.cast_pos.2 hn) fun _ ε0 =>
let ⟨n, hn⟩ := exists_nat_one_div_lt ε0
⟨n + 1, Nat.succ_pos n, mod_cast hn.le⟩
theorem uniformity_basis_dist_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < r ^ n } :=
Metric.mk_uniformity_basis (fun _ _ => pow_pos h0 _) fun _ε ε0 =>
let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1
⟨n, trivial, hn.le⟩
theorem uniformity_basis_dist_lt {R : ℝ} (hR : 0 < R) :
(𝓤 α).HasBasis (fun r : ℝ => 0 < r ∧ r < R) fun r => { p : α × α | dist p.1 p.2 < r } :=
Metric.mk_uniformity_basis (fun _ => And.left) fun r hr =>
⟨min r (R / 2), ⟨lt_min hr (half_pos hR), min_lt_iff.2 <| Or.inr (half_lt_self hR)⟩,
min_le_left _ _⟩
/-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers
accumulating to zero, then closed neighborhoods of the diagonal of sizes `{f i | p i}`
form a basis of `𝓤 α`.
Currently we have only one specific basis `uniformity_basis_dist_le` based on this constructor.
More can be easily added if needed in the future. -/
protected theorem mk_uniformity_basis_le {β : Type*} {p : β → Prop} {f : β → ℝ}
(hf₀ : ∀ x, p x → 0 < f x) (hf : ∀ ε, 0 < ε → ∃ x, p x ∧ f x ≤ ε) :
(𝓤 α).HasBasis p fun x => { p : α × α | dist p.1 p.2 ≤ f x } := by
refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩
constructor
· rintro ⟨ε, ε₀, hε⟩
rcases exists_between ε₀ with ⟨ε', hε'⟩
rcases hf ε' hε'.1 with ⟨i, hi, H⟩
exact ⟨i, hi, fun x (hx : _ ≤ _) => hε <| lt_of_le_of_lt (le_trans hx H) hε'.2⟩
· exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, fun x (hx : _ < _) => H (mem_setOf.2 hx.le)⟩
/-- Constant size closed neighborhoods of the diagonal form a basis
of the uniformity filter. -/
theorem uniformity_basis_dist_le :
(𝓤 α).HasBasis ((0 : ℝ) < ·) fun ε => { p : α × α | dist p.1 p.2 ≤ ε } :=
Metric.mk_uniformity_basis_le (fun _ => id) fun ε ε₀ => ⟨ε, ε₀, le_refl ε⟩
theorem uniformity_basis_dist_le_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 ≤ r ^ n } :=
Metric.mk_uniformity_basis_le (fun _ _ => pow_pos h0 _) fun _ε ε0 =>
let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1
⟨n, trivial, hn.le⟩
theorem mem_uniformity_dist {s : Set (α × α)} :
s ∈ 𝓤 α ↔ ∃ ε > 0, ∀ ⦃a b : α⦄, dist a b < ε → (a, b) ∈ s :=
uniformity_basis_dist.mem_uniformity_iff
/-- A constant size neighborhood of the diagonal is an entourage. -/
theorem dist_mem_uniformity {ε : ℝ} (ε0 : 0 < ε) : { p : α × α | dist p.1 p.2 < ε } ∈ 𝓤 α :=
mem_uniformity_dist.2 ⟨ε, ε0, fun _ _ ↦ id⟩
theorem uniformContinuous_iff [PseudoMetricSpace β] {f : α → β} :
UniformContinuous f ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃a b : α⦄, dist a b < δ → dist (f a) (f b) < ε :=
uniformity_basis_dist.uniformContinuous_iff uniformity_basis_dist
theorem uniformContinuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} :
UniformContinuousOn f s ↔
∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y < δ → dist (f x) (f y) < ε :=
Metric.uniformity_basis_dist.uniformContinuousOn_iff Metric.uniformity_basis_dist
theorem uniformContinuousOn_iff_le [PseudoMetricSpace β] {f : α → β} {s : Set α} :
UniformContinuousOn f s ↔
∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y ≤ δ → dist (f x) (f y) ≤ ε :=
Metric.uniformity_basis_dist_le.uniformContinuousOn_iff Metric.uniformity_basis_dist_le
theorem nhds_basis_ball : (𝓝 x).HasBasis (0 < ·) (ball x) :=
nhds_basis_uniformity uniformity_basis_dist
theorem mem_nhds_iff : s ∈ 𝓝 x ↔ ∃ ε > 0, ball x ε ⊆ s :=
nhds_basis_ball.mem_iff
theorem eventually_nhds_iff {p : α → Prop} :
(∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ ⦃y⦄, dist y x < ε → p y :=
mem_nhds_iff
theorem eventually_nhds_iff_ball {p : α → Prop} :
(∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ y ∈ ball x ε, p y :=
mem_nhds_iff
/-- A version of `Filter.eventually_prod_iff` where the first filter consists of neighborhoods
in a pseudo-metric space. -/
theorem eventually_nhds_prod_iff {f : Filter ι} {x₀ : α} {p : α × ι → Prop} :
(∀ᶠ x in 𝓝 x₀ ×ˢ f, p x) ↔ ∃ ε > (0 : ℝ), ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧
∀ ⦃x⦄, dist x x₀ < ε → ∀ ⦃i⦄, pa i → p (x, i) := by
refine (nhds_basis_ball.prod f.basis_sets).eventually_iff.trans ?_
simp only [Prod.exists, forall_prod_set, id, mem_ball, and_assoc, exists_and_left, and_imp]
rfl
/-- A version of `Filter.eventually_prod_iff` where the second filter consists of neighborhoods
in a pseudo-metric space. -/
theorem eventually_prod_nhds_iff {f : Filter ι} {x₀ : α} {p : ι × α → Prop} :
(∀ᶠ x in f ×ˢ 𝓝 x₀, p x) ↔ ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧
∃ ε > 0, ∀ ⦃i⦄, pa i → ∀ ⦃x⦄, dist x x₀ < ε → p (i, x) := by
rw [eventually_swap_iff, Metric.eventually_nhds_prod_iff]
constructor <;>
· rintro ⟨a1, a2, a3, a4, a5⟩
exact ⟨a3, a4, a1, a2, fun _ b1 b2 b3 => a5 b3 b1⟩
theorem nhds_basis_closedBall : (𝓝 x).HasBasis (fun ε : ℝ => 0 < ε) (closedBall x) :=
nhds_basis_uniformity uniformity_basis_dist_le
theorem nhds_basis_ball_inv_nat_succ :
(𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (1 / (↑n + 1)) :=
nhds_basis_uniformity uniformity_basis_dist_inv_nat_succ
theorem nhds_basis_ball_inv_nat_pos :
(𝓝 x).HasBasis (fun n => 0 < n) fun n : ℕ => ball x (1 / ↑n) :=
nhds_basis_uniformity uniformity_basis_dist_inv_nat_pos
theorem nhds_basis_ball_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (r ^ n) :=
nhds_basis_uniformity (uniformity_basis_dist_pow h0 h1)
theorem nhds_basis_closedBall_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) :
(𝓝 x).HasBasis (fun _ => True) fun n : ℕ => closedBall x (r ^ n) :=
nhds_basis_uniformity (uniformity_basis_dist_le_pow h0 h1)
theorem isOpen_iff : IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ball x ε ⊆ s := by
simp only [isOpen_iff_mem_nhds, mem_nhds_iff]
@[simp] theorem isOpen_ball : IsOpen (ball x ε) :=
isOpen_iff.2 fun _ => exists_ball_subset_ball
theorem ball_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : ball x ε ∈ 𝓝 x :=
isOpen_ball.mem_nhds (mem_ball_self ε0)
theorem closedBall_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : closedBall x ε ∈ 𝓝 x :=
mem_of_superset (ball_mem_nhds x ε0) ball_subset_closedBall
theorem closedBall_mem_nhds_of_mem {x c : α} {ε : ℝ} (h : x ∈ ball c ε) : closedBall c ε ∈ 𝓝 x :=
mem_of_superset (isOpen_ball.mem_nhds h) ball_subset_closedBall
theorem nhdsWithin_basis_ball {s : Set α} :
(𝓝[s] x).HasBasis (fun ε : ℝ => 0 < ε) fun ε => ball x ε ∩ s :=
nhdsWithin_hasBasis nhds_basis_ball s
theorem mem_nhdsWithin_iff {t : Set α} : s ∈ 𝓝[t] x ↔ ∃ ε > 0, ball x ε ∩ t ⊆ s :=
nhdsWithin_basis_ball.mem_iff
theorem tendsto_nhdsWithin_nhdsWithin [PseudoMetricSpace β] {t : Set β} {f : α → β} {a b} :
Tendsto f (𝓝[s] a) (𝓝[t] b) ↔
∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → f x ∈ t ∧ dist (f x) b < ε :=
(nhdsWithin_basis_ball.tendsto_iff nhdsWithin_basis_ball).trans <| by
simp only [inter_comm _ s, inter_comm _ t, mem_inter_iff, and_imp, gt_iff_lt, mem_ball]
theorem tendsto_nhdsWithin_nhds [PseudoMetricSpace β] {f : α → β} {a b} :
Tendsto f (𝓝[s] a) (𝓝 b) ↔
∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → dist (f x) b < ε := by
rw [← nhdsWithin_univ b, tendsto_nhdsWithin_nhdsWithin]
simp only [mem_univ, true_and]
theorem tendsto_nhds_nhds [PseudoMetricSpace β] {f : α → β} {a b} :
Tendsto f (𝓝 a) (𝓝 b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, dist x a < δ → dist (f x) b < ε :=
nhds_basis_ball.tendsto_iff nhds_basis_ball
theorem continuousAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} :
ContinuousAt f a ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, dist x a < δ → dist (f x) (f a) < ε := by
rw [ContinuousAt, tendsto_nhds_nhds]
theorem continuousWithinAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} {s : Set α} :
ContinuousWithinAt f s a ↔
∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → dist (f x) (f a) < ε := by
rw [ContinuousWithinAt, tendsto_nhdsWithin_nhds]
theorem continuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} :
ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∃ δ > 0, ∀ a ∈ s, dist a b < δ → dist (f a) (f b) < ε := by
simp [ContinuousOn, continuousWithinAt_iff]
theorem continuous_iff [PseudoMetricSpace β] {f : α → β} :
Continuous f ↔ ∀ b, ∀ ε > 0, ∃ δ > 0, ∀ a, dist a b < δ → dist (f a) (f b) < ε :=
continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds_nhds
theorem tendsto_nhds {f : Filter β} {u : β → α} {a : α} :
Tendsto u f (𝓝 a) ↔ ∀ ε > 0, ∀ᶠ x in f, dist (u x) a < ε :=
nhds_basis_ball.tendsto_right_iff
theorem continuousAt_iff' [TopologicalSpace β] {f : β → α} {b : β} :
ContinuousAt f b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝 b, dist (f x) (f b) < ε := by
rw [ContinuousAt, tendsto_nhds]
theorem continuousWithinAt_iff' [TopologicalSpace β] {f : β → α} {b : β} {s : Set β} :
ContinuousWithinAt f s b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by
rw [ContinuousWithinAt, tendsto_nhds]
theorem continuousOn_iff' [TopologicalSpace β] {f : β → α} {s : Set β} :
ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by
simp [ContinuousOn, continuousWithinAt_iff']
theorem continuous_iff' [TopologicalSpace β] {f : β → α} :
Continuous f ↔ ∀ (a), ∀ ε > 0, ∀ᶠ x in 𝓝 a, dist (f x) (f a) < ε :=
continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds
theorem tendsto_atTop [Nonempty β] [SemilatticeSup β] {u : β → α} {a : α} :
Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n ≥ N, dist (u n) a < ε :=
(atTop_basis.tendsto_iff nhds_basis_ball).trans <| by
simp only [true_and, mem_ball, mem_Ici]
/-- A variant of `tendsto_atTop` that
uses `∃ N, ∀ n > N, ...` rather than `∃ N, ∀ n ≥ N, ...`
-/
theorem tendsto_atTop' [Nonempty β] [SemilatticeSup β] [NoMaxOrder β] {u : β → α} {a : α} :
Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n > N, dist (u n) a < ε :=
(atTop_basis_Ioi.tendsto_iff nhds_basis_ball).trans <| by
simp only [true_and, gt_iff_lt, mem_Ioi, mem_ball]
theorem isOpen_singleton_iff {α : Type*} [PseudoMetricSpace α] {x : α} :
IsOpen ({x} : Set α) ↔ ∃ ε > 0, ∀ y, dist y x < ε → y = x := by
simp [isOpen_iff, subset_singleton_iff, mem_ball]
theorem _root_.Dense.exists_dist_lt {s : Set α} (hs : Dense s) (x : α) {ε : ℝ} (hε : 0 < ε) :
∃ y ∈ s, dist x y < ε := by
have : (ball x ε).Nonempty := by simp [hε]
simpa only [mem_ball'] using hs.exists_mem_open isOpen_ball this
nonrec theorem _root_.DenseRange.exists_dist_lt {β : Type*} {f : β → α} (hf : DenseRange f) (x : α)
{ε : ℝ} (hε : 0 < ε) : ∃ y, dist x (f y) < ε :=
exists_range_iff.1 (hf.exists_dist_lt x hε)
/-- (Pseudo) metric space has discrete `UniformSpace` structure
iff the distances between distinct points are uniformly bounded away from zero. -/
protected lemma uniformSpace_eq_bot :
‹PseudoMetricSpace α›.toUniformSpace = ⊥ ↔
∃ r : ℝ, 0 < r ∧ Pairwise (r ≤ dist · · : α → α → Prop) := by
simp only [uniformity_basis_dist.uniformSpace_eq_bot, mem_setOf_eq, not_lt]
end Metric
open Metric
/-- If the distances between distinct points in a (pseudo) metric space
are uniformly bounded away from zero, then the space has discrete topology. -/
lemma DiscreteTopology.of_forall_le_dist {α} [PseudoMetricSpace α] {r : ℝ} (hpos : 0 < r)
(hr : Pairwise (r ≤ dist · · : α → α → Prop)) : DiscreteTopology α :=
⟨by rw [Metric.uniformSpace_eq_bot.2 ⟨r, hpos, hr⟩, UniformSpace.toTopologicalSpace_bot]⟩
/- Instantiate a pseudometric space as a pseudoemetric space. Before we can state the instance,
we need to show that the uniform structure coming from the edistance and the
distance coincide. -/
theorem Metric.uniformity_edist_aux {α} (d : α → α → ℝ≥0) :
⨅ ε > (0 : ℝ), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } =
⨅ ε > (0 : ℝ≥0∞), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } := by
simp only [le_antisymm_iff, le_iInf_iff, le_principal_iff]
refine ⟨fun ε hε => ?_, fun ε hε => ?_⟩
· rcases ENNReal.lt_iff_exists_nnreal_btwn.1 hε with ⟨ε', ε'0, ε'ε⟩
refine mem_iInf_of_mem (ε' : ℝ) (mem_iInf_of_mem (ENNReal.coe_pos.1 ε'0) ?_)
exact fun x hx => lt_trans (ENNReal.coe_lt_coe.2 hx) ε'ε
· lift ε to ℝ≥0 using le_of_lt hε
refine mem_iInf_of_mem (ε : ℝ≥0∞) (mem_iInf_of_mem (ENNReal.coe_pos.2 hε) ?_)
exact fun _ => ENNReal.coe_lt_coe.1
theorem Metric.uniformity_edist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | edist p.1 p.2 < ε } := by
simp only [PseudoMetricSpace.uniformity_dist, dist_nndist, edist_nndist,
Metric.uniformity_edist_aux]
-- see Note [lower instance priority]
/-- A pseudometric space induces a pseudoemetric space -/
instance (priority := 100) PseudoMetricSpace.toPseudoEMetricSpace : PseudoEMetricSpace α :=
{ ‹PseudoMetricSpace α› with
edist_self := by simp [edist_dist]
edist_comm := fun _ _ => by simp only [edist_dist, dist_comm]
edist_triangle := fun x y z => by
simp only [edist_dist, ← ENNReal.ofReal_add, dist_nonneg]
rw [ENNReal.ofReal_le_ofReal_iff _]
· exact dist_triangle _ _ _
· simpa using add_le_add (dist_nonneg : 0 ≤ dist x y) dist_nonneg
uniformity_edist := Metric.uniformity_edist }
/-- In a pseudometric space, an open ball of infinite radius is the whole space -/
theorem Metric.eball_top_eq_univ (x : α) : EMetric.ball x ∞ = Set.univ :=
Set.eq_univ_iff_forall.mpr fun y => edist_lt_top y x
/-- Balls defined using the distance or the edistance coincide -/
@[simp]
theorem Metric.emetric_ball {x : α} {ε : ℝ} : EMetric.ball x (ENNReal.ofReal ε) = ball x ε := by
ext y
simp only [EMetric.mem_ball, mem_ball, edist_dist]
exact ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg
/-- Balls defined using the distance or the edistance coincide -/
@[simp]
theorem Metric.emetric_ball_nnreal {x : α} {ε : ℝ≥0} : EMetric.ball x ε = ball x ε := by
rw [← Metric.emetric_ball]
simp
/-- Closed balls defined using the distance or the edistance coincide -/
theorem Metric.emetric_closedBall {x : α} {ε : ℝ} (h : 0 ≤ ε) :
EMetric.closedBall x (ENNReal.ofReal ε) = closedBall x ε := by
ext y; simp [edist_le_ofReal h]
/-- Closed balls defined using the distance or the edistance coincide -/
@[simp]
theorem Metric.emetric_closedBall_nnreal {x : α} {ε : ℝ≥0} :
EMetric.closedBall x ε = closedBall x ε := by
rw [← Metric.emetric_closedBall ε.coe_nonneg, ENNReal.ofReal_coe_nnreal]
@[simp]
theorem Metric.emetric_ball_top (x : α) : EMetric.ball x ⊤ = univ :=
eq_univ_of_forall fun _ => edist_lt_top _ _
/-- Build a new pseudometric space from an old one where the bundled uniform structure is provably
(but typically non-definitionaly) equal to some given uniform structure.
See Note [forgetful inheritance].
See Note [reducible non-instances].
-/
abbrev PseudoMetricSpace.replaceUniformity {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : PseudoMetricSpace α :=
{ m with
toUniformSpace := U
uniformity_dist := H.trans PseudoMetricSpace.uniformity_dist }
theorem PseudoMetricSpace.replaceUniformity_eq {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : m.replaceUniformity H = m := by
ext
rfl
-- ensure that the bornology is unchanged when replacing the uniformity.
example {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) :
(PseudoMetricSpace.replaceUniformity m H).toBornology = m.toBornology := by
with_reducible_and_instances rfl
/-- Build a new pseudo metric space from an old one where the bundled topological structure is
provably (but typically non-definitionaly) equal to some given topological structure.
See Note [forgetful inheritance].
See Note [reducible non-instances].
-/
abbrev PseudoMetricSpace.replaceTopology {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ)
(H : U = m.toUniformSpace.toTopologicalSpace) : PseudoMetricSpace γ :=
@PseudoMetricSpace.replaceUniformity γ (m.toUniformSpace.replaceTopology H) m rfl
theorem PseudoMetricSpace.replaceTopology_eq {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ)
(H : U = m.toUniformSpace.toTopologicalSpace) : m.replaceTopology H = m := by
ext
rfl
/-- One gets a pseudometric space from an emetric space if the edistance
is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the
uniformity are defeq in the pseudometric space and the pseudoemetric space. In this definition, the
distance is given separately, to be able to prescribe some expression which is not defeq to the
push-forward of the edistance to reals. See note [reducible non-instances]. -/
abbrev PseudoEMetricSpace.toPseudoMetricSpaceOfDist {α : Type u} [e : PseudoEMetricSpace α]
(dist : α → α → ℝ) (edist_ne_top : ∀ x y : α, edist x y ≠ ⊤)
(h : ∀ x y, dist x y = ENNReal.toReal (edist x y)) : PseudoMetricSpace α where
dist := dist
dist_self x := by simp [h]
dist_comm x y := by simp [h, edist_comm]
dist_triangle x y z := by
simp only [h]
exact ENNReal.toReal_le_add (edist_triangle _ _ _) (edist_ne_top _ _) (edist_ne_top _ _)
edist := edist
edist_dist _ _ := by simp only [h, ENNReal.ofReal_toReal (edist_ne_top _ _)]
toUniformSpace := e.toUniformSpace
uniformity_dist := e.uniformity_edist.trans <| by
simpa only [ENNReal.coe_toNNReal (edist_ne_top _ _), h]
using (Metric.uniformity_edist_aux fun x y : α => (edist x y).toNNReal).symm
/-- One gets a pseudometric space from an emetric space if the edistance
is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the
uniformity are defeq in the pseudometric space and the emetric space. -/
abbrev PseudoEMetricSpace.toPseudoMetricSpace {α : Type u} [PseudoEMetricSpace α]
(h : ∀ x y : α, edist x y ≠ ⊤) : PseudoMetricSpace α :=
PseudoEMetricSpace.toPseudoMetricSpaceOfDist (fun x y => ENNReal.toReal (edist x y)) h fun _ _ =>
rfl
/-- Build a new pseudometric space from an old one where the bundled bornology structure is provably
(but typically non-definitionaly) equal to some given bornology structure.
See Note [forgetful inheritance].
See Note [reducible non-instances].
-/
abbrev PseudoMetricSpace.replaceBornology {α} [B : Bornology α] (m : PseudoMetricSpace α)
(H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) :
PseudoMetricSpace α :=
{ m with
toBornology := B
cobounded_sets := Set.ext <| compl_surjective.forall.2 fun s =>
(H s).trans <| by rw [isBounded_iff, mem_setOf_eq, compl_compl] }
theorem PseudoMetricSpace.replaceBornology_eq {α} [m : PseudoMetricSpace α] [B : Bornology α]
(H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) :
PseudoMetricSpace.replaceBornology _ H = m := by
ext
rfl
-- ensure that the uniformity is unchanged when replacing the bornology.
example {α} [B : Bornology α] (m : PseudoMetricSpace α)
(H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) :
(PseudoMetricSpace.replaceBornology m H).toUniformSpace = m.toUniformSpace := by
with_reducible_and_instances rfl
section Real
/-- Instantiate the reals as a pseudometric space. -/
instance Real.pseudoMetricSpace : PseudoMetricSpace ℝ where
dist x y := |x - y|
dist_self := by simp [abs_zero]
dist_comm _ _ := abs_sub_comm _ _
dist_triangle _ _ _ := abs_sub_le _ _ _
theorem Real.dist_eq (x y : ℝ) : dist x y = |x - y| := rfl
theorem Real.nndist_eq (x y : ℝ) : nndist x y = Real.nnabs (x - y) := rfl
theorem Real.nndist_eq' (x y : ℝ) : nndist x y = Real.nnabs (y - x) :=
nndist_comm _ _
theorem Real.dist_0_eq_abs (x : ℝ) : dist x 0 = |x| := by simp [Real.dist_eq]
theorem Real.sub_le_dist (x y : ℝ) : x - y ≤ dist x y := by
rw [Real.dist_eq, le_abs]
exact Or.inl (le_refl _)
theorem Real.ball_eq_Ioo (x r : ℝ) : ball x r = Ioo (x - r) (x + r) :=
Set.ext fun y => by
rw [mem_ball, dist_comm, Real.dist_eq, abs_sub_lt_iff, mem_Ioo, ← sub_lt_iff_lt_add',
sub_lt_comm]
theorem Real.closedBall_eq_Icc {x r : ℝ} : closedBall x r = Icc (x - r) (x + r) := by
| ext y
rw [mem_closedBall, dist_comm, Real.dist_eq, abs_sub_le_iff, mem_Icc, ← sub_le_iff_le_add',
sub_le_comm]
| Mathlib/Topology/MetricSpace/Pseudo/Defs.lean | 1,067 | 1,069 |
/-
Copyright (c) 2022 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Data.Set.Finite.Lemmas
import Mathlib.ModelTheory.Substructures
/-!
# Finitely Generated First-Order Structures
This file defines what it means for a first-order (sub)structure to be finitely or countably
generated, similarly to other finitely-generated objects in the algebra library.
## Main Definitions
- `FirstOrder.Language.Substructure.FG` indicates that a substructure is finitely generated.
- `FirstOrder.Language.Structure.FG` indicates that a structure is finitely generated.
- `FirstOrder.Language.Substructure.CG` indicates that a substructure is countably generated.
- `FirstOrder.Language.Structure.CG` indicates that a structure is countably generated.
## TODO
Develop a more unified definition of finite generation using the theory of closure operators, or use
this definition of finite generation to define the others.
-/
open FirstOrder Set
namespace FirstOrder
namespace Language
open Structure
variable {L : Language} {M : Type*} [L.Structure M]
namespace Substructure
/-- A substructure of `M` is finitely generated if it is the closure of a finite subset of `M`. -/
def FG (N : L.Substructure M) : Prop :=
∃ S : Finset M, closure L S = N
|
theorem fg_def {N : L.Substructure M} : N.FG ↔ ∃ S : Set M, S.Finite ∧ closure L S = N :=
⟨fun ⟨t, h⟩ => ⟨_, Finset.finite_toSet t, h⟩, by
rintro ⟨t', h, rfl⟩
rcases Finite.exists_finset_coe h with ⟨t, rfl⟩
| Mathlib/ModelTheory/FinitelyGenerated.lean | 45 | 49 |
/-
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.MeanValue
/-!
# Extending differentiability to the boundary
We investigate how differentiable functions inside a set extend to differentiable functions
on the boundary. For this, it suffices that the function and its derivative admit limits there.
A general version of this statement is given in `hasFDerivWithinAt_closure_of_tendsto_fderiv`.
One-dimensional versions, in which one wants to obtain differentiability at the left endpoint or
the right endpoint of an interval, are given in `hasDerivWithinAt_Ici_of_tendsto_deriv` and
`hasDerivWithinAt_Iic_of_tendsto_deriv`. These versions are formulated in terms of the
one-dimensional derivative `deriv ℝ f`.
-/
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] {F : Type*} [NormedAddCommGroup F]
[NormedSpace ℝ F]
open Filter Set Metric ContinuousLinearMap
open scoped Topology
/-- If a function `f` is differentiable in a convex open set and continuous on its closure, and its
derivative converges to a limit `f'` at a point on the boundary, then `f` is differentiable there
with derivative `f'`. -/
theorem hasFDerivWithinAt_closure_of_tendsto_fderiv {f : E → F} {s : Set E} {x : E} {f' : E →L[ℝ] F}
(f_diff : DifferentiableOn ℝ f s) (s_conv : Convex ℝ s) (s_open : IsOpen s)
(f_cont : ∀ y ∈ closure s, ContinuousWithinAt f s y)
(h : Tendsto (fun y => fderiv ℝ f y) (𝓝[s] x) (𝓝 f')) :
HasFDerivWithinAt f f' (closure s) x := by
classical
-- one can assume without loss of generality that `x` belongs to the closure of `s`, as the
-- statement is empty otherwise
by_cases hx : x ∉ closure s
· rw [← closure_closure] at hx; exact HasFDerivWithinAt.of_not_mem_closure hx
push_neg at hx
rw [HasFDerivWithinAt, hasFDerivAtFilter_iff_isLittleO, Asymptotics.isLittleO_iff]
/- One needs to show that `‖f y - f x - f' (y - x)‖ ≤ ε ‖y - x‖` for `y` close to `x` in
`closure s`, where `ε` is an arbitrary positive constant. By continuity of the functions, it
suffices to prove this for nearby points inside `s`. In a neighborhood of `x`, the derivative
of `f` is arbitrarily close to `f'` by assumption. The mean value inequality completes the
proof. -/
intro ε ε_pos
obtain ⟨δ, δ_pos, hδ⟩ : ∃ δ > 0, ∀ y ∈ s, dist y x < δ → ‖fderiv ℝ f y - f'‖ < ε := by
simpa [dist_zero_right] using tendsto_nhdsWithin_nhds.1 h ε ε_pos
set B := ball x δ
suffices ∀ y ∈ B ∩ closure s, ‖f y - f x - (f' y - f' x)‖ ≤ ε * ‖y - x‖ from
mem_nhdsWithin_iff.2 ⟨δ, δ_pos, fun y hy => by simpa using this y hy⟩
suffices
∀ p : E × E,
p ∈ closure ((B ∩ s) ×ˢ (B ∩ s)) → ‖f p.2 - f p.1 - (f' p.2 - f' p.1)‖ ≤ ε * ‖p.2 - p.1‖ by
rw [closure_prod_eq] at this
intro y y_in
apply this ⟨x, y⟩
have : B ∩ closure s ⊆ closure (B ∩ s) := isOpen_ball.inter_closure
exact ⟨this ⟨mem_ball_self δ_pos, hx⟩, this y_in⟩
have key : ∀ p : E × E, p ∈ (B ∩ s) ×ˢ (B ∩ s) →
‖f p.2 - f p.1 - (f' p.2 - f' p.1)‖ ≤ ε * ‖p.2 - p.1‖ := by
rintro ⟨u, v⟩ ⟨u_in, v_in⟩
have conv : Convex ℝ (B ∩ s) := (convex_ball _ _).inter s_conv
have diff : DifferentiableOn ℝ f (B ∩ s) := f_diff.mono inter_subset_right
have bound : ∀ z ∈ B ∩ s, ‖fderivWithin ℝ f (B ∩ s) z - f'‖ ≤ ε := by
intro z z_in
have h := hδ z
have : fderivWithin ℝ f (B ∩ s) z = fderiv ℝ f z := by
have op : IsOpen (B ∩ s) := isOpen_ball.inter s_open
rw [DifferentiableAt.fderivWithin _ (op.uniqueDiffOn z z_in)]
exact (diff z z_in).differentiableAt (IsOpen.mem_nhds op z_in)
rw [← this] at h
exact le_of_lt (h z_in.2 z_in.1)
simpa using conv.norm_image_sub_le_of_norm_fderivWithin_le' diff bound u_in v_in
rintro ⟨u, v⟩ uv_in
have f_cont' : ∀ y ∈ closure s, ContinuousWithinAt (f - ⇑f') s y := by
intro y y_in
exact Tendsto.sub (f_cont y y_in) f'.cont.continuousWithinAt
refine ContinuousWithinAt.closure_le uv_in ?_ ?_ key
all_goals
-- common start for both continuity proofs
have : (B ∩ s) ×ˢ (B ∩ s) ⊆ s ×ˢ s := by gcongr <;> exact inter_subset_right
obtain ⟨u_in, v_in⟩ : u ∈ closure s ∧ v ∈ closure s := by
simpa [closure_prod_eq] using closure_mono this uv_in
apply ContinuousWithinAt.mono _ this
simp only [ContinuousWithinAt]
· rw [nhdsWithin_prod_eq]
have : ∀ u v, f v - f u - (f' v - f' u) = f v - f' v - (f u - f' u) := by intros; abel
simp only [this]
exact
Tendsto.comp continuous_norm.continuousAt
((Tendsto.comp (f_cont' v v_in) tendsto_snd).sub <|
Tendsto.comp (f_cont' u u_in) tendsto_fst)
· apply tendsto_nhdsWithin_of_tendsto_nhds
rw [nhds_prod_eq]
exact
tendsto_const_nhds.mul
(Tendsto.comp continuous_norm.continuousAt <| tendsto_snd.sub tendsto_fst)
/-- If a function is differentiable on the right of a point `a : ℝ`, continuous at `a`, and
its derivative also converges at `a`, then `f` is differentiable on the right at `a`. -/
theorem hasDerivWithinAt_Ici_of_tendsto_deriv {s : Set ℝ} {e : E} {a : ℝ} {f : ℝ → E}
(f_diff : DifferentiableOn ℝ f s) (f_lim : ContinuousWithinAt f s a) (hs : s ∈ 𝓝[>] a)
(f_lim' : Tendsto (fun x => deriv f x) (𝓝[>] a) (𝓝 e)) : HasDerivWithinAt f e (Ici a) a := by
/- This is a specialization of `hasFDerivWithinAt_closure_of_tendsto_fderiv`. To be in the
setting of this theorem, we need to work on an open interval with closure contained in
`s ∪ {a}`, that we call `t = (a, b)`. Then, we check all the assumptions of this theorem and
we apply it. -/
obtain ⟨b, ab : a < b, sab : Ioc a b ⊆ s⟩ := mem_nhdsGT_iff_exists_Ioc_subset.1 hs
let t := Ioo a b
have ts : t ⊆ s := Subset.trans Ioo_subset_Ioc_self sab
have t_diff : DifferentiableOn ℝ f t := f_diff.mono ts
have t_conv : Convex ℝ t := convex_Ioo a b
have t_open : IsOpen t := isOpen_Ioo
have t_closure : closure t = Icc a b := closure_Ioo ab.ne
have t_cont : ∀ y ∈ closure t, ContinuousWithinAt f t y := by
rw [t_closure]
intro y hy
by_cases h : y = a
· rw [h]; exact f_lim.mono ts
· have : y ∈ s := sab ⟨lt_of_le_of_ne hy.1 (Ne.symm h), hy.2⟩
exact (f_diff.continuousOn y this).mono ts
have t_diff' : Tendsto (fun x => fderiv ℝ f x) (𝓝[t] a) (𝓝 (smulRight (1 : ℝ →L[ℝ] ℝ) e)) := by
simp only [deriv_fderiv.symm]
exact Tendsto.comp
(isBoundedBilinearMap_smulRight : IsBoundedBilinearMap ℝ _).continuous_right.continuousAt
(tendsto_nhdsWithin_mono_left Ioo_subset_Ioi_self f_lim')
-- now we can apply `hasFDerivWithinAt_closure_of_tendsto_fderiv`
have : HasDerivWithinAt f e (Icc a b) a := by
rw [hasDerivWithinAt_iff_hasFDerivWithinAt, ← t_closure]
exact hasFDerivWithinAt_closure_of_tendsto_fderiv t_diff t_conv t_open t_cont t_diff'
exact this.mono_of_mem_nhdsWithin (Icc_mem_nhdsGE ab)
/-- If a function is differentiable on the left of a point `a : ℝ`, continuous at `a`, and
its derivative also converges at `a`, then `f` is differentiable on the left at `a`. -/
theorem hasDerivWithinAt_Iic_of_tendsto_deriv {s : Set ℝ} {e : E} {a : ℝ}
{f : ℝ → E} (f_diff : DifferentiableOn ℝ f s) (f_lim : ContinuousWithinAt f s a)
(hs : s ∈ 𝓝[<] a) (f_lim' : Tendsto (fun x => deriv f x) (𝓝[<] a) (𝓝 e)) :
HasDerivWithinAt f e (Iic a) a := by
/- This is a specialization of `hasFDerivWithinAt_closure_of_tendsto_fderiv`. To be in the
setting of this theorem, we need to work on an open interval with closure contained in
`s ∪ {a}`, that we call `t = (b, a)`. Then, we check all the assumptions of this theorem and we
apply it. -/
obtain ⟨b, ba, sab⟩ : ∃ b ∈ Iio a, Ico b a ⊆ s := mem_nhdsLT_iff_exists_Ico_subset.1 hs
let t := Ioo b a
have ts : t ⊆ s := Subset.trans Ioo_subset_Ico_self sab
have t_diff : DifferentiableOn ℝ f t := f_diff.mono ts
have t_conv : Convex ℝ t := convex_Ioo b a
have t_open : IsOpen t := isOpen_Ioo
have t_closure : closure t = Icc b a := closure_Ioo (ne_of_lt ba)
have t_cont : ∀ y ∈ closure t, ContinuousWithinAt f t y := by
rw [t_closure]
intro y hy
by_cases h : y = a
· rw [h]; exact f_lim.mono ts
· have : y ∈ s := sab ⟨hy.1, lt_of_le_of_ne hy.2 h⟩
exact (f_diff.continuousOn y this).mono ts
have t_diff' : Tendsto (fun x => fderiv ℝ f x) (𝓝[t] a) (𝓝 (smulRight (1 : ℝ →L[ℝ] ℝ) e)) := by
simp only [deriv_fderiv.symm]
exact Tendsto.comp
(isBoundedBilinearMap_smulRight : IsBoundedBilinearMap ℝ _).continuous_right.continuousAt
(tendsto_nhdsWithin_mono_left Ioo_subset_Iio_self f_lim')
-- now we can apply `hasFDerivWithinAt_closure_of_tendsto_fderiv`
have : HasDerivWithinAt f e (Icc b a) a := by
rw [hasDerivWithinAt_iff_hasFDerivWithinAt, ← t_closure]
exact hasFDerivWithinAt_closure_of_tendsto_fderiv t_diff t_conv t_open t_cont t_diff'
exact this.mono_of_mem_nhdsWithin (Icc_mem_nhdsLE ba)
/-- If a real function `f` has a derivative `g` everywhere but at a point, and `f` and `g` are
continuous at this point, then `g` is also the derivative of `f` at this point. -/
theorem hasDerivAt_of_hasDerivAt_of_ne {f g : ℝ → E} {x : ℝ}
(f_diff : ∀ y ≠ x, HasDerivAt f (g y) y) (hf : ContinuousAt f x)
(hg : ContinuousAt g x) : HasDerivAt f (g x) x := by
have A : HasDerivWithinAt f (g x) (Ici x) x := by
have diff : DifferentiableOn ℝ f (Ioi x) := fun y hy =>
(f_diff y (ne_of_gt hy)).differentiableAt.differentiableWithinAt
-- next line is the nontrivial bit of this proof, appealing to differentiability
-- extension results.
apply
hasDerivWithinAt_Ici_of_tendsto_deriv diff hf.continuousWithinAt
self_mem_nhdsWithin
have : Tendsto g (𝓝[>] x) (𝓝 (g x)) := tendsto_inf_left hg
apply this.congr' _
apply mem_of_superset self_mem_nhdsWithin fun y hy => _
intros y hy
exact (f_diff y (ne_of_gt hy)).deriv.symm
have B : HasDerivWithinAt f (g x) (Iic x) x := by
have diff : DifferentiableOn ℝ f (Iio x) := fun y hy =>
(f_diff y (ne_of_lt hy)).differentiableAt.differentiableWithinAt
-- next line is the nontrivial bit of this proof, appealing to differentiability
-- extension results.
apply
hasDerivWithinAt_Iic_of_tendsto_deriv diff hf.continuousWithinAt
self_mem_nhdsWithin
have : Tendsto g (𝓝[<] x) (𝓝 (g x)) := tendsto_inf_left hg
apply this.congr' _
apply mem_of_superset self_mem_nhdsWithin fun y hy => _
intros y hy
exact (f_diff y (ne_of_lt hy)).deriv.symm
simpa using B.union A
/-- If a real function `f` has a derivative `g` everywhere but at a point, and `f` and `g` are
continuous at this point, then `g` is the derivative of `f` everywhere. -/
theorem hasDerivAt_of_hasDerivAt_of_ne' {f g : ℝ → E} {x : ℝ}
(f_diff : ∀ y ≠ x, HasDerivAt f (g y) y) (hf : ContinuousAt f x)
(hg : ContinuousAt g x) (y : ℝ) : HasDerivAt f (g y) y := by
rcases eq_or_ne y x with (rfl | hne)
· exact hasDerivAt_of_hasDerivAt_of_ne f_diff hf hg
| · exact f_diff y hne
| Mathlib/Analysis/Calculus/FDeriv/Extend.lean | 212 | 217 |
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Algebra.Group.Embedding
import Mathlib.Order.Interval.Multiset
/-!
# Finite intervals of naturals
This file proves that `ℕ` is a `LocallyFiniteOrder` and calculates the cardinality of its
intervals as finsets and fintypes.
## TODO
Some lemmas can be generalized using `OrderedGroup`, `CanonicallyOrderedMul` or `SuccOrder`
and subsequently be moved upstream to `Order.Interval.Finset`.
-/
assert_not_exists Ring
open Finset Nat
variable (a b c : ℕ)
namespace Nat
instance instLocallyFiniteOrder : LocallyFiniteOrder ℕ where
finsetIcc a b := ⟨List.range' a (b + 1 - a), List.nodup_range'⟩
finsetIco a b := ⟨List.range' a (b - a), List.nodup_range'⟩
finsetIoc a b := ⟨List.range' (a + 1) (b - a), List.nodup_range'⟩
finsetIoo a b := ⟨List.range' (a + 1) (b - a - 1), List.nodup_range'⟩
finset_mem_Icc a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
finset_mem_Ico a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
finset_mem_Ioc a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
finset_mem_Ioo a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
theorem Icc_eq_range' : Icc a b = ⟨List.range' a (b + 1 - a), List.nodup_range'⟩ :=
rfl
theorem Ico_eq_range' : Ico a b = ⟨List.range' a (b - a), List.nodup_range'⟩ :=
rfl
theorem Ioc_eq_range' : Ioc a b = ⟨List.range' (a + 1) (b - a), List.nodup_range'⟩ :=
rfl
theorem Ioo_eq_range' : Ioo a b = ⟨List.range' (a + 1) (b - a - 1), List.nodup_range'⟩ :=
rfl
theorem uIcc_eq_range' :
uIcc a b = ⟨List.range' (min a b) (max a b + 1 - min a b), List.nodup_range'⟩ := rfl
theorem Iio_eq_range : Iio = range := by
ext b x
rw [mem_Iio, mem_range]
@[simp]
theorem Ico_zero_eq_range : Ico 0 = range := by rw [← Nat.bot_eq_zero, ← Iio_eq_Ico, Iio_eq_range]
lemma range_eq_Icc_zero_sub_one (n : ℕ) (hn : n ≠ 0) : range n = Icc 0 (n - 1) := by
ext b
simp_all only [mem_Icc, zero_le, true_and, mem_range]
exact lt_iff_le_pred (zero_lt_of_ne_zero hn)
theorem _root_.Finset.range_eq_Ico : range = Ico 0 :=
Ico_zero_eq_range.symm
theorem range_succ_eq_Icc_zero (n : ℕ) : range (n + 1) = Icc 0 n := by
rw [range_eq_Icc_zero_sub_one _ (Nat.add_one_ne_zero _), Nat.add_sub_cancel_right]
@[simp] lemma card_Icc : #(Icc a b) = b + 1 - a := List.length_range' ..
@[simp] lemma card_Ico : #(Ico a b) = b - a := List.length_range' ..
@[simp] lemma card_Ioc : #(Ioc a b) = b - a := List.length_range' ..
@[simp] lemma card_Ioo : #(Ioo a b) = b - a - 1 := List.length_range' ..
@[simp]
theorem card_uIcc : #(uIcc a b) = (b - a : ℤ).natAbs + 1 :=
(card_Icc _ _).trans <| by rw [← Int.natCast_inj, Int.ofNat_sub] <;> omega
@[simp]
lemma card_Iic : #(Iic b) = b + 1 := by rw [Iic_eq_Icc, card_Icc, Nat.bot_eq_zero, Nat.sub_zero]
@[simp]
theorem card_Iio : #(Iio b) = b := by rw [Iio_eq_Ico, card_Ico, Nat.bot_eq_zero, Nat.sub_zero]
@[deprecated Fintype.card_Icc (since := "2025-03-28")]
theorem card_fintypeIcc : Fintype.card (Set.Icc a b) = b + 1 - a := by simp
@[deprecated Fintype.card_Ico (since := "2025-03-28")]
theorem card_fintypeIco : Fintype.card (Set.Ico a b) = b - a := by simp
@[deprecated Fintype.card_Ioc (since := "2025-03-28")]
theorem card_fintypeIoc : Fintype.card (Set.Ioc a b) = b - a := by simp
@[deprecated Fintype.card_Ioo (since := "2025-03-28")]
theorem card_fintypeIoo : Fintype.card (Set.Ioo a b) = b - a - 1 := by simp
@[deprecated Fintype.card_Iic (since := "2025-03-28")]
theorem card_fintypeIic : Fintype.card (Set.Iic b) = b + 1 := by simp
@[deprecated Fintype.card_Iio (since := "2025-03-28")]
theorem card_fintypeIio : Fintype.card (Set.Iio b) = b := by simp
-- TODO@Yaël: Generalize all the following lemmas to `SuccOrder`
theorem Icc_succ_left : Icc a.succ b = Ioc a b := by
ext x
rw [mem_Icc, mem_Ioc, succ_le_iff]
theorem Ico_succ_right : Ico a b.succ = Icc a b := by
ext x
rw [mem_Ico, mem_Icc, Nat.lt_succ_iff]
theorem Ico_succ_left : Ico a.succ b = Ioo a b := by
ext x
rw [mem_Ico, mem_Ioo, succ_le_iff]
theorem Icc_pred_right {b : ℕ} (h : 0 < b) : Icc a (b - 1) = Ico a b := by
ext x
rw [mem_Icc, mem_Ico, lt_iff_le_pred h]
theorem Ico_succ_succ : Ico a.succ b.succ = Ioc a b := by
ext x
rw [mem_Ico, mem_Ioc, succ_le_iff, Nat.lt_succ_iff]
@[simp]
theorem Ico_succ_singleton : Ico a (a + 1) = {a} := by rw [Ico_succ_right, Icc_self]
@[simp]
theorem Ico_pred_singleton {a : ℕ} (h : 0 < a) : Ico (a - 1) a = {a - 1} := by
rw [← Icc_pred_right _ h, Icc_self]
@[simp]
theorem Ioc_succ_singleton : Ioc b (b + 1) = {b + 1} := by rw [← Nat.Icc_succ_left, Icc_self]
variable {a b c}
lemma mem_Ioc_succ : a ∈ Ioc b (b + 1) ↔ a = b + 1 := by simp
lemma mem_Ioc_succ' (a : Ioc b (b + 1)) : a = ⟨b + 1, mem_Ioc.2 (by omega)⟩ :=
Subtype.val_inj.1 (mem_Ioc_succ.1 a.2)
theorem Ico_succ_right_eq_insert_Ico (h : a ≤ b) : Ico a (b + 1) = insert b (Ico a b) := by
| rw [Ico_succ_right, ← Ico_insert_right h]
| Mathlib/Order/Interval/Finset/Nat.lean | 144 | 144 |
/-
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.Probability.ConditionalProbability
import Mathlib.Probability.Kernel.Basic
import Mathlib.Probability.Kernel.Composition.MeasureComp
import Mathlib.Tactic.Peel
import Mathlib.MeasureTheory.MeasurableSpace.Pi
/-!
# 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 ambient 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 Set 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 (m := 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 (m := 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 η : Kernel α Ω} {μ : Measure α}
{π : ι → Set (Set Ω)} {s : ι → Set Ω} {S : Finset ι} {f : ∀ x : ι, Ω → β x}
{s1 s2 : Set (Set Ω)}
@[simp] lemma iIndepSets_zero_right : iIndepSets π κ 0 := by simp [iIndepSets]
@[simp] lemma indepSets_zero_right : IndepSets s1 s2 κ 0 := by simp [IndepSets]
@[simp] lemma indepSets_zero_left : IndepSets s1 s2 (0 : Kernel α Ω) μ := by simp [IndepSets]
@[simp] lemma iIndep_zero_right : iIndep m κ 0 := by simp [iIndep]
@[simp] lemma indep_zero_right {m₁ m₂ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : Kernel α Ω} : Indep m₁ m₂ κ 0 := by simp [Indep]
@[simp] lemma indep_zero_left {m₁ m₂ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω} :
Indep m₁ m₂ (0 : Kernel α Ω) μ := by simp [Indep]
@[simp] lemma iIndepSet_zero_right : iIndepSet s κ 0 := by simp [iIndepSet]
@[simp] lemma indepSet_zero_right {s t : Set Ω} : IndepSet s t κ 0 := by simp [IndepSet]
@[simp] lemma indepSet_zero_left {s t : Set Ω} : IndepSet s t (0 : Kernel α Ω) μ := by
simp [IndepSet]
@[simp] lemma iIndepFun_zero_right {β : ι → Type*} {m : ∀ x : ι, MeasurableSpace (β x)}
{f : ∀ x : ι, Ω → β x} : iIndepFun f κ 0 := by simp [iIndepFun]
@[simp] lemma indepFun_zero_right {β γ} [MeasurableSpace β] [MeasurableSpace γ]
{f : Ω → β} {g : Ω → γ} : IndepFun f g κ 0 := by simp [IndepFun]
@[simp] lemma indepFun_zero_left {β γ} [MeasurableSpace β] [MeasurableSpace γ]
{f : Ω → β} {g : Ω → γ} : IndepFun f g (0 : Kernel α Ω) μ := by simp [IndepFun]
lemma iIndepSets_congr (h : κ =ᵐ[μ] η) : iIndepSets π κ μ ↔ iIndepSets π η μ := by
peel 3
refine ⟨fun h' ↦ ?_, fun h' ↦ ?_⟩ <;>
· filter_upwards [h, h'] with a ha h'a
simpa [ha] using h'a
alias ⟨iIndepSets.congr, _⟩ := iIndepSets_congr
lemma indepSets_congr (h : κ =ᵐ[μ] η) : IndepSets s1 s2 κ μ ↔ IndepSets s1 s2 η μ := by
peel 4
refine ⟨fun h' ↦ ?_, fun h' ↦ ?_⟩ <;>
· filter_upwards [h, h'] with a ha h'a
simpa [ha] using h'a
alias ⟨IndepSets.congr, _⟩ := indepSets_congr
lemma iIndep_congr (h : κ =ᵐ[μ] η) : iIndep m κ μ ↔ iIndep m η μ :=
iIndepSets_congr h
alias ⟨iIndep.congr, _⟩ := iIndep_congr
lemma indep_congr {m₁ m₂ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ η : Kernel α Ω} (h : κ =ᵐ[μ] η) : Indep m₁ m₂ κ μ ↔ Indep m₁ m₂ η μ :=
indepSets_congr h
alias ⟨Indep.congr, _⟩ := indep_congr
lemma iIndepSet_congr (h : κ =ᵐ[μ] η) : iIndepSet s κ μ ↔ iIndepSet s η μ :=
iIndep_congr h
alias ⟨iIndepSet.congr, _⟩ := iIndepSet_congr
lemma indepSet_congr {s t : Set Ω} (h : κ =ᵐ[μ] η) : IndepSet s t κ μ ↔ IndepSet s t η μ :=
indep_congr h
alias ⟨indepSet.congr, _⟩ := indepSet_congr
lemma iIndepFun_congr {β : ι → Type*} {m : ∀ x : ι, MeasurableSpace (β x)}
{f : ∀ x : ι, Ω → β x} (h : κ =ᵐ[μ] η) : iIndepFun f κ μ ↔ iIndepFun f η μ :=
iIndep_congr h
alias ⟨iIndepFun.congr, _⟩ := iIndepFun_congr
lemma indepFun_congr {β γ} [MeasurableSpace β] [MeasurableSpace γ]
{f : Ω → β} {g : Ω → γ} (h : κ =ᵐ[μ] η) : IndepFun f g κ μ ↔ IndepFun f g η μ :=
indep_congr h
alias ⟨IndepFun.congr, _⟩ := indepFun_congr
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.ae_isProbabilityMeasure (h : iIndepSets π κ μ) :
∀ᵐ a ∂μ, IsProbabilityMeasure (κ a) := by
filter_upwards [h.meas_biInter ∅ (f := fun _ ↦ Set.univ) (by simp)] with a ha
exact ⟨by simpa using ha⟩
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.ae_isProbabilityMeasure (h : iIndep m κ μ) :
∀ᵐ a ∂μ, IsProbabilityMeasure (κ a) :=
h.iIndepSets'.ae_isProbabilityMeasure
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]
@[nontriviality, simp]
lemma iIndepSets.of_subsingleton [Subsingleton ι] {m : ι → Set (Set Ω)} {κ : Kernel α Ω}
[IsMarkovKernel κ] : iIndepSets m κ μ := by
rintro s f hf
obtain rfl | ⟨i, rfl⟩ : s = ∅ ∨ ∃ i, s = {i} := by
simpa using (subsingleton_of_subsingleton (s := s.toSet)).eq_empty_or_singleton
all_goals simp
@[nontriviality, simp]
lemma iIndep.of_subsingleton [Subsingleton ι] {m : ι → MeasurableSpace Ω} {κ : Kernel α Ω}
[IsMarkovKernel κ] : iIndep m κ μ := by simp [iIndep]
@[nontriviality, simp]
lemma iIndepFun.of_subsingleton [Subsingleton ι] {β : ι → Type*} {m : ∀ i, MeasurableSpace (β i)}
{f : ∀ i, Ω → β i} [IsMarkovKernel κ] : iIndepFun f κ μ := by
simp [iIndepFun]
protected lemma iIndepFun.iIndep (hf : iIndepFun f κ μ) :
iIndep (fun x ↦ (mβ x).comap (f x)) κ μ := hf
lemma iIndepFun.ae_isProbabilityMeasure (h : iIndepFun f κ μ) :
∀ᵐ a ∂μ, IsProbabilityMeasure (κ a) :=
h.iIndep.ae_isProbabilityMeasure
lemma iIndepFun.meas_biInter (hf : iIndepFun 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 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} [IsZeroOrMarkovKernel κ] :
Indep m' ⊥ κ μ := by
intros s t _ ht
rw [Set.mem_setOf_eq, MeasurableSpace.measurableSet_bot_iff] at ht
rcases eq_zero_or_isMarkovKernel κ with rfl| h
· simp
refine Filter.Eventually.of_forall (fun a ↦ ?_)
rcases 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} [IsZeroOrMarkovKernel κ] :
Indep ⊥ m' κ μ := (indep_bot_right m').symm
theorem indepSet_empty_right {_mΩ : MeasurableSpace Ω}
{κ : Kernel α Ω} {μ : Measure α} [IsZeroOrMarkovKernel 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} [IsZeroOrMarkovKernel 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
rcases (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
obtain ⟨n, ht1⟩ := 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; obtain ⟨n, h⟩ := 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
rcases 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 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} [IsZeroOrMarkovKernel 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
rcases eq_zero_or_isMarkovKernel κ with rfl | h
· simp
induction t2, ht2m using induction_on_inter hpm2 hp2 with
| empty => simp
| basic u hu => exact hyp t1 u ht1 hu
| compl u hu ihu =>
filter_upwards [ihu] with a ha
rw [← Set.diff_eq, ← Set.diff_self_inter,
measure_diff inter_subset_left (ht1m.inter (h2 _ hu)).nullMeasurableSet (measure_ne_top _ _),
ha, measure_compl (h2 _ hu) (measure_ne_top _ _), measure_univ, ENNReal.mul_sub, mul_one]
exact fun _ _ ↦ measure_ne_top _ _
| iUnion f hfd hfm ihf =>
rw [← ae_all_iff] at ihf
filter_upwards [ihf] with a ha
rw [inter_iUnion, measure_iUnion, measure_iUnion hfd fun i ↦ h2 _ (hfm i)]
· simp only [ENNReal.tsum_mul_left, ha]
· exact hfd.mono fun i j h ↦ (h.inter_left' _).inter_right' _
· exact fun i ↦ .inter ht1m (h2 _ <| hfm 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}
[IsZeroOrMarkovKernel 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
rcases eq_zero_or_isMarkovKernel κ with rfl | h
· simp
intros t1 t2 ht1 ht2
induction t1, ht1 using induction_on_inter hpm1 hp1 with
| empty =>
simp only [Set.empty_inter, measure_empty, zero_mul, eq_self_iff_true, Filter.eventually_true]
| basic t ht =>
refine IndepSets.indep_aux h2 hp2 hpm2 hyp ht (h1 _ ?_) ht2
rw [hpm1]
exact measurableSet_generateFrom ht
| compl t ht iht =>
filter_upwards [iht] 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)).nullMeasurableSet
(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]
| iUnion 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} [IsZeroOrMarkovKernel 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 {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
rcases 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, h_indep.ae_isProbabilityMeasure]
with a h_P_inter ha1 ha2 h'
have h_μg : ∀ n, κ a (g n) = (ite (n ∈ p1) (κ a (f1 n)) 1) * (ite (n ∈ p2) (κ a (f2 n)) 1) := by
intro n
dsimp only [g]
split_ifs with h1 h2
· exact absurd rfl (Set.disjoint_iff_forall_ne.mp hST (hp1 h1) (hp2 h2))
all_goals simp only [measure_univ, one_mul, mul_one, Set.inter_univ, Set.univ_inter]
simp_rw [h_P_inter, h_μg, Finset.prod_mul_distrib,
Finset.prod_ite_mem (p1 ∪ p2) p1 (fun x ↦ κ a (f1 x)), Finset.union_inter_cancel_left,
Finset.prod_ite_mem (p1 ∪ p2) p2 (fun x => κ a (f2 x)), Finset.union_inter_cancel_right, ht1_eq,
← ha1, ht2_eq, ← ha2]
theorem iIndepSet.indep_generateFrom_of_disjoint {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
classical
rcases eq_or_ne μ 0 with rfl | hμ
· simp
obtain ⟨η, η_eq, hη⟩ : ∃ (η : Kernel α Ω), κ =ᵐ[μ] η ∧ IsMarkovKernel η :=
exists_ae_eq_isMarkovKernel hs.ae_isProbabilityMeasure hμ
apply Indep.congr (Filter.EventuallyEq.symm η_eq)
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 _) _
· exact indepSets_piiUnionInter_of_disjoint (iIndep.iIndepSets (fun n => rfl) (hs.congr η_eq)) hST
theorem indep_iSup_of_disjoint {m : ι → MeasurableSpace Ω}
(h_le : ∀ i, m i ≤ _mΩ) (h_indep : iIndep m κ μ) {S T : Set ι} (hST : Disjoint S T) :
Indep (⨆ i ∈ S, m i) (⨆ i ∈ T, m i) κ μ := by
classical
rcases eq_or_ne μ 0 with rfl | hμ
· simp
obtain ⟨η, η_eq, hη⟩ : ∃ (η : Kernel α Ω), κ =ᵐ[μ] η ∧ IsMarkovKernel η :=
exists_ae_eq_isMarkovKernel h_indep.ae_isProbabilityMeasure hμ
apply Indep.congr (Filter.EventuallyEq.symm η_eq)
refine
IndepSets.indep (iSup₂_le fun i _ => h_le i) (iSup₂_le fun i _ => h_le i) ?_ ?_
(generateFrom_piiUnionInter_measurableSet m S).symm
(generateFrom_piiUnionInter_measurableSet m T).symm ?_
· exact isPiSystem_piiUnionInter _ (fun n => @isPiSystem_measurableSet Ω (m n)) _
· exact isPiSystem_piiUnionInter _ (fun n => @isPiSystem_measurableSet Ω (m n)) _
· exact indepSets_piiUnionInter_of_disjoint (h_indep.congr η_eq) hST
theorem indep_iSup_of_directed_le {Ω} {m : ι → MeasurableSpace Ω} {m' m0 : MeasurableSpace Ω}
{κ : Kernel α Ω} {μ : Measure α} [IsZeroOrMarkovKernel κ] (h_indep : ∀ i, Indep (m i) m' κ μ)
(h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0) (hm : Directed (· ≤ ·) m) :
Indep (⨆ i, m i) m' κ μ := by
let p : ι → Set (Set Ω) := fun n => { t | MeasurableSet[m n] t }
have hp : ∀ n, IsPiSystem (p n) := fun n => @isPiSystem_measurableSet Ω (m n)
have h_gen_n : ∀ n, m n = generateFrom (p n) := fun n =>
(@generateFrom_measurableSet Ω (m n)).symm
have hp_supr_pi : IsPiSystem (⋃ n, p n) := isPiSystem_iUnion_of_directed_le p hp hm
let p' := { t : Set Ω | MeasurableSet[m'] t }
have hp'_pi : IsPiSystem p' := @isPiSystem_measurableSet Ω m'
have h_gen' : m' = generateFrom p' := (@generateFrom_measurableSet Ω m').symm
-- the π-systems defined are independent
have h_pi_system_indep : IndepSets (⋃ n, p n) p' κ μ := by
refine IndepSets.iUnion ?_
conv at h_indep =>
intro i
rw [h_gen_n i, h_gen']
exact fun n => (h_indep n).indepSets
-- now go from π-systems to σ-algebras
refine IndepSets.indep (iSup_le h_le) h_le' hp_supr_pi hp'_pi ?_ h_gen' h_pi_system_indep
exact (generateFrom_iUnion_measurableSet _).symm
theorem iIndepSet.indep_generateFrom_lt [Preorder ι] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (i : ι) :
Indep (generateFrom {s i}) (generateFrom { t | ∃ j < i, s j = t }) κ μ := by
convert iIndepSet.indep_generateFrom_of_disjoint hsm hs {i} { j | j < i }
(Set.disjoint_singleton_left.mpr (lt_irrefl _)) using 1
simp only [Set.mem_singleton_iff, exists_prop, exists_eq_left, Set.setOf_eq_eq_singleton']
theorem iIndepSet.indep_generateFrom_le [Preorder ι] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (i : ι) {k : ι} (hk : i < k) :
Indep (generateFrom {s k}) (generateFrom { t | ∃ j ≤ i, s j = t }) κ μ := by
convert iIndepSet.indep_generateFrom_of_disjoint hsm hs {k} { j | j ≤ i }
(Set.disjoint_singleton_left.mpr hk.not_le) using 1
simp only [Set.mem_singleton_iff, exists_prop, exists_eq_left, Set.setOf_eq_eq_singleton']
theorem iIndepSet.indep_generateFrom_le_nat {s : ℕ → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (n : ℕ) :
Indep (generateFrom {s (n + 1)}) (generateFrom { t | ∃ k ≤ n, s k = t }) κ μ :=
iIndepSet.indep_generateFrom_le hsm hs _ n.lt_succ_self
theorem indep_iSup_of_monotone [SemilatticeSup ι] {Ω} {m : ι → MeasurableSpace Ω}
{m' m0 : MeasurableSpace Ω} {κ : Kernel α Ω} {μ : Measure α} [IsZeroOrMarkovKernel κ]
(h_indep : ∀ i, Indep (m i) m' κ μ) (h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0)
(hm : Monotone m) :
Indep (⨆ i, m i) m' κ μ :=
indep_iSup_of_directed_le h_indep h_le h_le' (Monotone.directed_le hm)
theorem indep_iSup_of_antitone [SemilatticeInf ι] {Ω} {m : ι → MeasurableSpace Ω}
{m' m0 : MeasurableSpace Ω} {κ : Kernel α Ω} {μ : Measure α} [IsZeroOrMarkovKernel κ]
(h_indep : ∀ i, Indep (m i) m' κ μ) (h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0)
(hm : Antitone m) :
Indep (⨆ i, m i) m' κ μ :=
indep_iSup_of_directed_le h_indep h_le h_le' hm.directed_le
theorem iIndepSets.piiUnionInter_of_not_mem {π : ι → Set (Set Ω)} {a : ι} {S : Finset ι}
(hp_ind : iIndepSets π κ μ) (haS : a ∉ S) :
IndepSets (piiUnionInter π S) (π a) κ μ := by
rintro t1 t2 ⟨s, hs_mem, ft1, hft1_mem, ht1_eq⟩ ht2_mem_pia
rw [Finset.coe_subset] at hs_mem
classical
let f := fun n => ite (n = a) t2 (ite (n ∈ s) (ft1 n) Set.univ)
have h_f_mem : ∀ n ∈ insert a s, f n ∈ π n := by
intro n hn_mem_insert
dsimp only [f]
rcases Finset.mem_insert.mp hn_mem_insert with hn_mem | hn_mem
· simp [hn_mem, ht2_mem_pia]
· have hn_ne_a : n ≠ a := by rintro rfl; exact haS (hs_mem hn_mem)
simp [hn_ne_a, hn_mem, hft1_mem n hn_mem]
have h_f_mem_pi : ∀ n ∈ s, f n ∈ π n := fun x hxS => h_f_mem x (by simp [hxS])
have h_t1 : t1 = ⋂ n ∈ s, f n := by
suffices h_forall : ∀ n ∈ s, f n = ft1 n by
rw [ht1_eq]
ext x
simp_rw [Set.mem_iInter]
conv => lhs; intro i hns; rw [← h_forall i hns]
intro n hnS
have hn_ne_a : n ≠ a := by rintro rfl; exact haS (hs_mem hnS)
simp_rw [f, if_pos hnS, if_neg hn_ne_a]
have h_μ_t1 : ∀ᵐ a' ∂μ, κ a' t1 = ∏ n ∈ s, κ a' (f n) := by
filter_upwards [hp_ind s h_f_mem_pi] with a' ha'
rw [h_t1, ← ha']
have h_t2 : t2 = f a := by simp [f]
have h_μ_inter : ∀ᵐ a' ∂μ, κ a' (t1 ∩ t2) = ∏ n ∈ insert a s, κ a' (f n) := by
have h_t1_inter_t2 : t1 ∩ t2 = ⋂ n ∈ insert a s, f n := by
rw [h_t1, h_t2, Finset.set_biInter_insert, Set.inter_comm]
filter_upwards [hp_ind (insert a s) h_f_mem] with a' ha'
rw [h_t1_inter_t2, ← ha']
have has : a ∉ s := fun has_mem => haS (hs_mem has_mem)
filter_upwards [h_μ_t1, h_μ_inter] with a' ha1 ha2
rw [ha2, Finset.prod_insert has, h_t2, mul_comm, ha1]
/-- The measurable space structures generated by independent pi-systems are independent. -/
theorem iIndepSets.iIndep (m : ι → MeasurableSpace Ω)
(h_le : ∀ i, m i ≤ _mΩ) (π : ι → Set (Set Ω)) (h_pi : ∀ n, IsPiSystem (π n))
(h_generate : ∀ i, m i = generateFrom (π i)) (h_ind : iIndepSets π κ μ) :
iIndep m κ μ := by
classical
rcases eq_or_ne μ 0 with rfl | hμ
· simp
obtain ⟨η, η_eq, hη⟩ : ∃ (η : Kernel α Ω), κ =ᵐ[μ] η ∧ IsMarkovKernel η :=
exists_ae_eq_isMarkovKernel h_ind.ae_isProbabilityMeasure hμ
apply iIndep.congr (Filter.EventuallyEq.symm η_eq)
intro s f
refine Finset.induction ?_ ?_ s
· simp only [Finset.not_mem_empty, Set.mem_setOf_eq, IsEmpty.forall_iff, implies_true,
Set.iInter_of_empty, Set.iInter_univ, measure_univ, Finset.prod_empty,
Filter.eventually_true, forall_true_left]
· intro a S ha_notin_S h_rec hf_m
have hf_m_S : ∀ x ∈ S, MeasurableSet[m x] (f x) := fun x hx => hf_m x (by simp [hx])
let p := piiUnionInter π S
set m_p := generateFrom p with hS_eq_generate
have h_indep : Indep m_p (m a) η μ := by
have hp : IsPiSystem p := isPiSystem_piiUnionInter π h_pi S
have h_le' : ∀ i, generateFrom (π i) ≤ _mΩ := fun i ↦ (h_generate i).symm.trans_le (h_le i)
have hm_p : m_p ≤ _mΩ := generateFrom_piiUnionInter_le π h_le' S
exact IndepSets.indep hm_p (h_le a) hp (h_pi a) hS_eq_generate (h_generate a)
(iIndepSets.piiUnionInter_of_not_mem (h_ind.congr η_eq) ha_notin_S)
have h := h_indep.symm (f a) (⋂ n ∈ S, f n) (hf_m a (Finset.mem_insert_self a S)) ?_
· filter_upwards [h_rec hf_m_S, h] with a' ha' h'
rwa [Finset.set_biInter_insert, Finset.prod_insert ha_notin_S, ← ha']
· have h_le_p : ∀ i ∈ S, m i ≤ m_p := by
intros n hn
rw [hS_eq_generate, h_generate n]
exact le_generateFrom_piiUnionInter (S : Set ι) hn
have h_S_f : ∀ i ∈ S, MeasurableSet[m_p] (f i) :=
fun i hi ↦ (h_le_p i hi) (f i) (hf_m_S i hi)
exact S.measurableSet_biInter h_S_f
end FromPiSystemsToMeasurableSpaces
section IndepSet
/-! ### Independence of measurable sets
We prove the following equivalences on `IndepSet`, for measurable sets `s, t`.
* `IndepSet s t κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t`,
* `IndepSet s t κ μ ↔ IndepSets {s} {t} κ μ`.
-/
variable {_mα : MeasurableSpace α}
theorem iIndepSet_iff_iIndepSets_singleton {_mΩ : MeasurableSpace Ω} {κ : Kernel α Ω}
{μ : Measure α} {f : ι → Set Ω} (hf : ∀ i, MeasurableSet (f i)) :
iIndepSet f κ μ ↔ iIndepSets (fun i ↦ {f i}) κ μ :=
⟨iIndep.iIndepSets fun _ ↦ rfl,
iIndepSets.iIndep _ (fun i ↦ generateFrom_le <| by rintro t (rfl : t = _); exact hf _) _
(fun _ ↦ IsPiSystem.singleton _) fun _ ↦ rfl⟩
theorem iIndepSet.meas_biInter {_mΩ : MeasurableSpace Ω} {κ : Kernel α Ω}
{μ : Measure α} {f : ι → Set Ω} (h : iIndepSet f κ μ) (s : Finset ι) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i) :=
iIndep.iIndepSets (fun _ ↦ rfl) h _ (by simp)
theorem iIndepSet_iff_meas_biInter {_mΩ : MeasurableSpace Ω} {κ : Kernel α Ω}
{μ : Measure α} {f : ι → Set Ω} (hf : ∀ i, MeasurableSet (f i)) :
iIndepSet f κ μ ↔ ∀ s, ∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i) :=
(iIndepSet_iff_iIndepSets_singleton hf).trans iIndepSets_singleton_iff
theorem iIndepSets.iIndepSet_of_mem {_mΩ : MeasurableSpace Ω} {κ : Kernel α Ω}
{μ : Measure α} {π : ι → Set (Set Ω)} {f : ι → Set Ω}
(hfπ : ∀ i, f i ∈ π i) (hf : ∀ i, MeasurableSet (f i)) (hπ : iIndepSets π κ μ) :
iIndepSet f κ μ :=
(iIndepSet_iff_meas_biInter hf).2 fun _t ↦ hπ.meas_biInter _ fun _i _ ↦ hfπ _
variable {s t : Set Ω} (S T : Set (Set Ω))
theorem indepSet_iff_indepSets_singleton {m0 : MeasurableSpace Ω} (hs_meas : MeasurableSet s)
(ht_meas : MeasurableSet t) (κ : Kernel α Ω) (μ : Measure α)
[IsZeroOrMarkovKernel κ] :
IndepSet s t κ μ ↔ IndepSets {s} {t} κ μ :=
⟨Indep.indepSets, fun h =>
IndepSets.indep
(generateFrom_le fun u hu => by rwa [Set.mem_singleton_iff.mp hu])
(generateFrom_le fun u hu => by rwa [Set.mem_singleton_iff.mp hu])
(IsPiSystem.singleton s) (IsPiSystem.singleton t) rfl rfl h⟩
theorem indepSet_iff_measure_inter_eq_mul {_m0 : MeasurableSpace Ω} (hs_meas : MeasurableSet s)
(ht_meas : MeasurableSet t) (κ : Kernel α Ω) (μ : Measure α)
[IsZeroOrMarkovKernel κ] :
IndepSet s t κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t :=
| (indepSet_iff_indepSets_singleton hs_meas ht_meas κ μ).trans indepSets_singleton_iff
theorem IndepSet.measure_inter_eq_mul {_m0 : MeasurableSpace Ω} (κ : Kernel α Ω) (μ : Measure α)
(h : IndepSet s t κ μ) : ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t :=
Indep.indepSets h _ _ (by simp) (by simp)
theorem IndepSets.indepSet_of_mem {_m0 : MeasurableSpace Ω} (hs : s ∈ S) (ht : t ∈ T)
| Mathlib/Probability/Independence/Kernel.lean | 823 | 829 |
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Robert Y. Lewis
-/
import Mathlib.FieldTheory.Finite.Polynomial
import Mathlib.NumberTheory.Basic
import Mathlib.RingTheory.WittVector.WittPolynomial
/-!
# Witt structure polynomials
In this file we prove the main theorem that makes the whole theory of Witt vectors work.
Briefly, consider a polynomial `Φ : MvPolynomial idx ℤ` over the integers,
with polynomials variables indexed by an arbitrary type `idx`.
Then there exists a unique family of polynomials `φ : ℕ → MvPolynomial (idx × ℕ) Φ`
such that for all `n : ℕ` we have (`wittStructureInt_existsUnique`)
```
bind₁ φ (wittPolynomial p ℤ n) = bind₁ (fun i ↦ (rename (prod.mk i) (wittPolynomial p ℤ n))) Φ
```
In other words: evaluating the `n`-th Witt polynomial on the family `φ`
is the same as evaluating `Φ` on the (appropriately renamed) `n`-th Witt polynomials.
N.b.: As far as we know, these polynomials do not have a name in the literature,
so we have decided to call them the “Witt structure polynomials”. See `wittStructureInt`.
## Special cases
With the main result of this file in place, we apply it to certain special polynomials.
For example, by taking `Φ = X tt + X ff` resp. `Φ = X tt * X ff`
we obtain families of polynomials `witt_add` resp. `witt_mul`
(with type `ℕ → MvPolynomial (Bool × ℕ) ℤ`) that will be used in later files to define the
addition and multiplication on the ring of Witt vectors.
## Outline of the proof
The proof of `wittStructureInt_existsUnique` is rather technical, and takes up most of this file.
We start by proving the analogous version for polynomials with rational coefficients,
instead of integer coefficients.
In this case, the solution is rather easy,
since the Witt polynomials form a faithful change of coordinates
in the polynomial ring `MvPolynomial ℕ ℚ`.
We therefore obtain a family of polynomials `wittStructureRat Φ`
for every `Φ : MvPolynomial idx ℚ`.
If `Φ` has integer coefficients, then the polynomials `wittStructureRat Φ n` do so as well.
Proving this claim is the essential core of this file, and culminates in
`map_wittStructureInt`, which proves that upon mapping the coefficients
of `wittStructureInt Φ n` from the integers to the rationals,
one obtains `wittStructureRat Φ n`.
Ultimately, the proof of `map_wittStructureInt` relies on
```
dvd_sub_pow_of_dvd_sub {R : Type*} [CommRing R] {p : ℕ} {a b : R} :
(p : R) ∣ a - b → ∀ (k : ℕ), (p : R) ^ (k + 1) ∣ a ^ p ^ k - b ^ p ^ k
```
## Main results
* `wittStructureRat Φ`: the family of polynomials `ℕ → MvPolynomial (idx × ℕ) ℚ`
associated with `Φ : MvPolynomial idx ℚ` and satisfying the property explained above.
* `wittStructureRat_prop`: the proof that `wittStructureRat` indeed satisfies the property.
* `wittStructureInt Φ`: the family of polynomials `ℕ → MvPolynomial (idx × ℕ) ℤ`
associated with `Φ : MvPolynomial idx ℤ` and satisfying the property explained above.
* `map_wittStructureInt`: the proof that the integral polynomials `with_structure_int Φ`
are equal to `wittStructureRat Φ` when mapped to polynomials with rational coefficients.
* `wittStructureInt_prop`: the proof that `wittStructureInt` indeed satisfies the property.
* Five families of polynomials that will be used to define the ring structure
on the ring of Witt vectors:
- `WittVector.wittZero`
- `WittVector.wittOne`
- `WittVector.wittAdd`
- `WittVector.wittMul`
- `WittVector.wittNeg`
(We also define `WittVector.wittSub`, and later we will prove that it describes subtraction,
which is defined as `fun a b ↦ a + -b`. See `WittVector.sub_coeff` for this proof.)
## References
* [Hazewinkel, *Witt Vectors*][Haze09]
* [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21]
-/
open MvPolynomial Set
open Finset (range)
open Finsupp (single)
-- This lemma reduces a bundled morphism to a "mere" function,
-- and consequently the simplifier cannot use a lot of powerful simp-lemmas.
-- We disable this locally, and probably it should be disabled globally in mathlib.
attribute [-simp] coe_eval₂Hom
variable {p : ℕ} {R : Type*} {idx : Type*} [CommRing R]
open scoped Witt
section PPrime
variable (p)
variable [hp : Fact p.Prime]
-- Notation with ring of coefficients explicit
set_option quotPrecheck false in
@[inherit_doc]
scoped[Witt] notation "W_" => wittPolynomial p
-- Notation with ring of coefficients implicit
set_option quotPrecheck false in
@[inherit_doc]
scoped[Witt] notation "W" => wittPolynomial p _
/-- `wittStructureRat Φ` is a family of polynomials `ℕ → MvPolynomial (idx × ℕ) ℚ`
that are uniquely characterised by the property that
```
bind₁ (wittStructureRat p Φ) (wittPolynomial p ℚ n) =
bind₁ (fun i ↦ (rename (prod.mk i) (wittPolynomial p ℚ n))) Φ
```
In other words: evaluating the `n`-th Witt polynomial on the family `wittStructureRat Φ`
is the same as evaluating `Φ` on the (appropriately renamed) `n`-th Witt polynomials.
See `wittStructureRat_prop` for this property,
and `wittStructureRat_existsUnique` for the fact that `wittStructureRat`
gives the unique family of polynomials with this property.
These polynomials turn out to have integral coefficients,
but it requires some effort to show this.
See `wittStructureInt` for the version with integral coefficients,
and `map_wittStructureInt` for the fact that it is equal to `wittStructureRat`
when mapped to polynomials over the rationals. -/
noncomputable def wittStructureRat (Φ : MvPolynomial idx ℚ) (n : ℕ) : MvPolynomial (idx × ℕ) ℚ :=
bind₁ (fun k => bind₁ (fun i => rename (Prod.mk i) (W_ ℚ k)) Φ) (xInTermsOfW p ℚ n)
theorem wittStructureRat_prop (Φ : MvPolynomial idx ℚ) (n : ℕ) :
bind₁ (wittStructureRat p Φ) (W_ ℚ n) = bind₁ (fun i => rename (Prod.mk i) (W_ ℚ n)) Φ :=
calc
bind₁ (wittStructureRat p Φ) (W_ ℚ n) =
bind₁ (fun k => bind₁ (fun i => (rename (Prod.mk i)) (W_ ℚ k)) Φ)
(bind₁ (xInTermsOfW p ℚ) (W_ ℚ n)) := by
rw [bind₁_bind₁]; exact eval₂Hom_congr (RingHom.ext_rat _ _) rfl rfl
_ = bind₁ (fun i => rename (Prod.mk i) (W_ ℚ n)) Φ := by
rw [bind₁_xInTermsOfW_wittPolynomial p _ n, bind₁_X_right]
theorem wittStructureRat_existsUnique (Φ : MvPolynomial idx ℚ) :
∃! φ : ℕ → MvPolynomial (idx × ℕ) ℚ,
∀ n : ℕ, bind₁ φ (W_ ℚ n) = bind₁ (fun i => rename (Prod.mk i) (W_ ℚ n)) Φ := by
refine ⟨wittStructureRat p Φ, ?_, ?_⟩
· intro n; apply wittStructureRat_prop
· intro φ H
funext n
rw [show φ n = bind₁ φ (bind₁ (W_ ℚ) (xInTermsOfW p ℚ n)) by
rw [bind₁_wittPolynomial_xInTermsOfW p, bind₁_X_right]]
rw [bind₁_bind₁]
exact eval₂Hom_congr (RingHom.ext_rat _ _) (funext H) rfl
theorem wittStructureRat_rec_aux (Φ : MvPolynomial idx ℚ) (n : ℕ) :
wittStructureRat p Φ n * C ((p : ℚ) ^ n) =
bind₁ (fun b => rename (fun i => (b, i)) (W_ ℚ n)) Φ -
∑ i ∈ range n, C ((p : ℚ) ^ i) * wittStructureRat p Φ i ^ p ^ (n - i) := by
have := xInTermsOfW_aux p ℚ n
replace := congr_arg (bind₁ fun k : ℕ => bind₁ (fun i => rename (Prod.mk i) (W_ ℚ k)) Φ) this
rw [map_mul, bind₁_C_right] at this
rw [wittStructureRat, this]; clear this
conv_lhs => simp only [map_sub, bind₁_X_right]
rw [sub_right_inj]
simp only [map_sum, map_mul, bind₁_C_right, map_pow]
rfl
/-- Write `wittStructureRat p φ n` in terms of `wittStructureRat p φ i` for `i < n`. -/
theorem wittStructureRat_rec (Φ : MvPolynomial idx ℚ) (n : ℕ) :
wittStructureRat p Φ n =
C (1 / (p : ℚ) ^ n) *
(bind₁ (fun b => rename (fun i => (b, i)) (W_ ℚ n)) Φ -
∑ i ∈ range n, C ((p : ℚ) ^ i) * wittStructureRat p Φ i ^ p ^ (n - i)) := by
calc
wittStructureRat p Φ n = C (1 / (p : ℚ) ^ n) * (wittStructureRat p Φ n * C ((p : ℚ) ^ n)) := ?_
_ = _ := by rw [wittStructureRat_rec_aux]
rw [mul_left_comm, ← C_mul, div_mul_cancel₀, C_1, mul_one]
exact pow_ne_zero _ (Nat.cast_ne_zero.2 hp.1.ne_zero)
/-- `wittStructureInt Φ` is a family of polynomials `ℕ → MvPolynomial (idx × ℕ) ℤ`
that are uniquely characterised by the property that
```
bind₁ (wittStructureInt p Φ) (wittPolynomial p ℤ n) =
bind₁ (fun i ↦ (rename (prod.mk i) (wittPolynomial p ℤ n))) Φ
```
In other words: evaluating the `n`-th Witt polynomial on the family `wittStructureInt Φ`
is the same as evaluating `Φ` on the (appropriately renamed) `n`-th Witt polynomials.
See `wittStructureInt_prop` for this property,
and `wittStructureInt_existsUnique` for the fact that `wittStructureInt`
gives the unique family of polynomials with this property. -/
noncomputable def wittStructureInt (Φ : MvPolynomial idx ℤ) (n : ℕ) : MvPolynomial (idx × ℕ) ℤ :=
Finsupp.mapRange Rat.num (Rat.num_intCast 0) (wittStructureRat p (map (Int.castRingHom ℚ) Φ) n)
variable {p}
theorem bind₁_rename_expand_wittPolynomial (Φ : MvPolynomial idx ℤ) (n : ℕ)
(IH :
∀ m : ℕ,
m < n + 1 →
map (Int.castRingHom ℚ) (wittStructureInt p Φ m) =
wittStructureRat p (map (Int.castRingHom ℚ) Φ) m) :
bind₁ (fun b => rename (fun i => (b, i)) (expand p (W_ ℤ n))) Φ =
bind₁ (fun i => expand p (wittStructureInt p Φ i)) (W_ ℤ n) := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [map_bind₁, map_rename, map_expand, rename_expand, map_wittPolynomial]
have key := (wittStructureRat_prop p (map (Int.castRingHom ℚ) Φ) n).symm
apply_fun expand p at key
simp only [expand_bind₁] at key
rw [key]; clear key
apply eval₂Hom_congr' rfl _ rfl
rintro i hi -
rw [wittPolynomial_vars, Finset.mem_range] at hi
simp only [IH i hi]
theorem C_p_pow_dvd_bind₁_rename_wittPolynomial_sub_sum (Φ : MvPolynomial idx ℤ) (n : ℕ)
(IH :
∀ m : ℕ,
m < n →
map (Int.castRingHom ℚ) (wittStructureInt p Φ m) =
wittStructureRat p (map (Int.castRingHom ℚ) Φ) m) :
(C ((p ^ n :) : ℤ) : MvPolynomial (idx × ℕ) ℤ) ∣
bind₁ (fun b : idx => rename (fun i => (b, i)) (wittPolynomial p ℤ n)) Φ -
∑ i ∈ range n, C ((p : ℤ) ^ i) * wittStructureInt p Φ i ^ p ^ (n - i) := by
rcases n with - | n
· simp only [isUnit_one, Int.ofNat_zero, Int.natCast_succ, zero_add, pow_zero, C_1, IsUnit.dvd,
Nat.cast_one]
-- prepare a useful equation for rewriting
have key := bind₁_rename_expand_wittPolynomial Φ n IH
apply_fun map (Int.castRingHom (ZMod (p ^ (n + 1)))) at key
conv_lhs at key => simp only [map_bind₁, map_rename, map_expand, map_wittPolynomial]
-- clean up and massage
rw [C_dvd_iff_zmod, RingHom.map_sub, sub_eq_zero, map_bind₁]
simp only [map_rename, map_wittPolynomial, wittPolynomial_zmod_self]
rw [key]; clear key IH
rw [bind₁, aeval_wittPolynomial, map_sum, map_sum, Finset.sum_congr rfl]
intro k hk
rw [Finset.mem_range, Nat.lt_succ_iff] at hk
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11083): was much slower
-- simp only [← sub_eq_zero, ← RingHom.map_sub, ← C_dvd_iff_zmod, C_eq_coe_nat, ← mul_sub, ←
-- Nat.cast_pow]
rw [← sub_eq_zero, ← RingHom.map_sub, ← C_dvd_iff_zmod, C_eq_coe_nat, ← Nat.cast_pow,
← Nat.cast_pow, C_eq_coe_nat, ← mul_sub]
have : p ^ (n + 1) = p ^ k * p ^ (n - k + 1) := by
rw [← pow_add, ← add_assoc]; congr 2; rw [add_comm, ← tsub_eq_iff_eq_add_of_le hk]
rw [this]
rw [Nat.cast_mul, Nat.cast_pow, Nat.cast_pow]
apply mul_dvd_mul_left ((p : MvPolynomial (idx × ℕ) ℤ) ^ k)
rw [show p ^ (n + 1 - k) = p * p ^ (n - k) by rw [← pow_succ', ← tsub_add_eq_add_tsub hk]]
rw [pow_mul]
-- the machine!
apply dvd_sub_pow_of_dvd_sub
rw [← C_eq_coe_nat, C_dvd_iff_zmod, RingHom.map_sub, sub_eq_zero, map_expand, RingHom.map_pow,
MvPolynomial.expand_zmod]
variable (p)
@[simp]
theorem map_wittStructureInt (Φ : MvPolynomial idx ℤ) (n : ℕ) :
map (Int.castRingHom ℚ) (wittStructureInt p Φ n) =
wittStructureRat p (map (Int.castRingHom ℚ) Φ) n := by
induction n using Nat.strong_induction_on with | h n IH => ?_
rw [wittStructureInt, map_mapRange_eq_iff, Int.coe_castRingHom]
intro c
rw [wittStructureRat_rec, coeff_C_mul, mul_comm, mul_div_assoc', mul_one]
have sum_induction_steps :
map (Int.castRingHom ℚ)
(∑ i ∈ range n, C ((p : ℤ) ^ i) * wittStructureInt p Φ i ^ p ^ (n - i)) =
∑ i ∈ range n,
| C ((p : ℚ) ^ i) * wittStructureRat p (map (Int.castRingHom ℚ) Φ) i ^ p ^ (n - i) := by
rw [map_sum]
apply Finset.sum_congr rfl
intro i hi
rw [Finset.mem_range] at hi
simp only [IH i hi, RingHom.map_mul, RingHom.map_pow, map_C]
rfl
simp only [← sum_induction_steps, ← map_wittPolynomial p (Int.castRingHom ℚ), ← map_rename, ←
map_bind₁, ← RingHom.map_sub, coeff_map]
rw [show (p : ℚ) ^ n = ((↑(p ^ n) : ℤ) : ℚ) by norm_cast]
rw [← Rat.den_eq_one_iff, eq_intCast, Rat.den_div_intCast_eq_one_iff]
swap; · exact mod_cast pow_ne_zero n hp.1.ne_zero
revert c; rw [← C_dvd_iff_dvd_coeff]
exact C_p_pow_dvd_bind₁_rename_wittPolynomial_sub_sum Φ n IH
theorem wittStructureInt_prop (Φ : MvPolynomial idx ℤ) (n) :
bind₁ (wittStructureInt p Φ) (wittPolynomial p ℤ n) =
bind₁ (fun i => rename (Prod.mk i) (W_ ℤ n)) Φ := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
have := wittStructureRat_prop p (map (Int.castRingHom ℚ) Φ) n
simpa only [map_bind₁, ← eval₂Hom_map_hom, eval₂Hom_C_left, map_rename, map_wittPolynomial,
AlgHom.coe_toRingHom, map_wittStructureInt]
theorem eq_wittStructureInt (Φ : MvPolynomial idx ℤ) (φ : ℕ → MvPolynomial (idx × ℕ) ℤ)
(h : ∀ n, bind₁ φ (wittPolynomial p ℤ n) = bind₁ (fun i => rename (Prod.mk i) (W_ ℤ n)) Φ) :
| Mathlib/RingTheory/WittVector/StructurePolynomial.lean | 275 | 299 |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar
import Mathlib.MeasureTheory.Covering.Besicovitch
import Mathlib.Tactic.AdaptationNote
import Mathlib.Algebra.EuclideanDomain.Basic
/-!
# Satellite configurations for Besicovitch covering lemma in vector spaces
The Besicovitch covering theorem ensures that, in a nice metric space, there exists a number `N`
such that, from any family of balls with bounded radii, one can extract `N` families, each made of
disjoint balls, covering together all the centers of the initial family.
A key tool in the proof of this theorem is the notion of a satellite configuration, i.e., a family
of `N + 1` balls, where the first `N` balls all intersect the last one, but none of them contains
the center of another one and their radii are controlled. This is a technical notion, but it shows
up naturally in the proof of the Besicovitch theorem (which goes through a greedy algorithm): to
ensure that in the end one needs at most `N` families of balls, the crucial property of the
underlying metric space is that there should be no satellite configuration of `N + 1` points.
This file is devoted to the study of this property in vector spaces: we prove the main result
of [Füredi and Loeb, On the best constant for the Besicovitch covering theorem][furedi-loeb1994],
which shows that the optimal such `N` in a vector space coincides with the maximal number
of points one can put inside the unit ball of radius `2` under the condition that their distances
are bounded below by `1`.
In particular, this number is bounded by `5 ^ dim` by a straightforward measure argument.
## Main definitions and results
* `multiplicity E` is the maximal number of points one can put inside the unit ball
of radius `2` in the vector space `E`, under the condition that their distances
are bounded below by `1`.
* `multiplicity_le E` shows that `multiplicity E ≤ 5 ^ (dim E)`.
* `good_τ E` is a constant `> 1`, but close enough to `1` that satellite configurations
with this parameter `τ` are not worst than for `τ = 1`.
* `isEmpty_satelliteConfig_multiplicity` is the main theorem, saying that there are
no satellite configurations of `(multiplicity E) + 1` points, for the parameter `goodτ E`.
-/
universe u
open Metric Set Module MeasureTheory Filter Fin
open scoped ENNReal Topology
noncomputable section
namespace Besicovitch
variable {E : Type*} [NormedAddCommGroup E]
namespace SatelliteConfig
variable [NormedSpace ℝ E] {N : ℕ} {τ : ℝ} (a : SatelliteConfig E N τ)
/-- Rescaling a satellite configuration in a vector space, to put the basepoint at `0` and the base
radius at `1`. -/
def centerAndRescale : SatelliteConfig E N τ where
c i := (a.r (last N))⁻¹ • (a.c i - a.c (last N))
r i := (a.r (last N))⁻¹ * a.r i
rpos i := by positivity
h i j hij := by
simp (disch := positivity) only [dist_smul₀, dist_sub_right, mul_left_comm τ,
Real.norm_of_nonneg]
rcases a.h hij with (⟨H₁, H₂⟩ | ⟨H₁, H₂⟩) <;> [left; right] <;> constructor <;> gcongr
hlast i hi := by
simp (disch := positivity) only [dist_smul₀, dist_sub_right, mul_left_comm τ,
Real.norm_of_nonneg]
have ⟨H₁, H₂⟩ := a.hlast i hi
constructor <;> gcongr
inter i hi := by
simp (disch := positivity) only [dist_smul₀, ← mul_add, dist_sub_right, Real.norm_of_nonneg]
gcongr
exact a.inter i hi
theorem centerAndRescale_center : a.centerAndRescale.c (last N) = 0 := by
simp [SatelliteConfig.centerAndRescale]
theorem centerAndRescale_radius {N : ℕ} {τ : ℝ} (a : SatelliteConfig E N τ) :
a.centerAndRescale.r (last N) = 1 := by
simp [SatelliteConfig.centerAndRescale, inv_mul_cancel₀ (a.rpos _).ne']
end SatelliteConfig
/-! ### Disjoint balls of radius close to `1` in the radius `2` ball. -/
/-- The maximum cardinality of a `1`-separated set in the ball of radius `2`. This is also the
optimal number of families in the Besicovitch covering theorem. -/
def multiplicity (E : Type*) [NormedAddCommGroup E] :=
sSup {N | ∃ s : Finset E, s.card = N ∧ (∀ c ∈ s, ‖c‖ ≤ 2) ∧ ∀ c ∈ s, ∀ d ∈ s, c ≠ d → 1 ≤ ‖c - d‖}
section
variable [NormedSpace ℝ E] [FiniteDimensional ℝ E]
open scoped Function in -- required for scoped `on` notation
/-- Any `1`-separated set in the ball of radius `2` has cardinality at most `5 ^ dim`. This is
useful to show that the supremum in the definition of `Besicovitch.multiplicity E` is
well behaved. -/
theorem card_le_of_separated (s : Finset E) (hs : ∀ c ∈ s, ‖c‖ ≤ 2)
(h : ∀ c ∈ s, ∀ d ∈ s, c ≠ d → 1 ≤ ‖c - d‖) : s.card ≤ 5 ^ finrank ℝ E := by
/- We consider balls of radius `1/2` around the points in `s`. They are disjoint, and all
contained in the ball of radius `5/2`. A volume argument gives `s.card * (1/2)^dim ≤ (5/2)^dim`,
| i.e., `s.card ≤ 5^dim`. -/
borelize E
let μ : Measure E := Measure.addHaar
let δ : ℝ := (1 : ℝ) / 2
let ρ : ℝ := (5 : ℝ) / 2
have ρpos : 0 < ρ := by norm_num
set A := ⋃ c ∈ s, ball (c : E) δ with hA
have D : Set.Pairwise (s : Set E) (Disjoint on fun c => ball (c : E) δ) := by
rintro c hc d hd hcd
apply ball_disjoint_ball
rw [dist_eq_norm]
convert h c hc d hd hcd
norm_num
have A_subset : A ⊆ ball (0 : E) ρ := by
refine iUnion₂_subset fun x hx => ?_
apply ball_subset_ball'
calc
δ + dist x 0 ≤ δ + 2 := by rw [dist_zero_right]; exact add_le_add le_rfl (hs x hx)
_ = 5 / 2 := by norm_num
have I :
(s.card : ℝ≥0∞) * ENNReal.ofReal (δ ^ finrank ℝ E) * μ (ball 0 1) ≤
ENNReal.ofReal (ρ ^ finrank ℝ E) * μ (ball 0 1) :=
calc
(s.card : ℝ≥0∞) * ENNReal.ofReal (δ ^ finrank ℝ E) * μ (ball 0 1) = μ A := by
rw [hA, measure_biUnion_finset D fun c _ => measurableSet_ball]
have I : 0 < δ := by norm_num
simp only [div_pow, μ.addHaar_ball_of_pos _ I]
simp only [one_div, one_pow, Finset.sum_const, nsmul_eq_mul, mul_assoc]
_ ≤ μ (ball (0 : E) ρ) := measure_mono A_subset
_ = ENNReal.ofReal (ρ ^ finrank ℝ E) * μ (ball 0 1) := by
simp only [μ.addHaar_ball_of_pos _ ρpos]
have J : (s.card : ℝ≥0∞) * ENNReal.ofReal (δ ^ finrank ℝ E) ≤ ENNReal.ofReal (ρ ^ finrank ℝ E) :=
(ENNReal.mul_le_mul_right (measure_ball_pos _ _ zero_lt_one).ne' measure_ball_lt_top.ne).1 I
have K : (s.card : ℝ) ≤ (5 : ℝ) ^ finrank ℝ E := by
have := ENNReal.toReal_le_of_le_ofReal (pow_nonneg ρpos.le _) J
simpa [ρ, δ, div_eq_mul_inv, mul_pow] using this
exact mod_cast K
theorem multiplicity_le : multiplicity E ≤ 5 ^ finrank ℝ E := by
apply csSup_le
· refine ⟨0, ⟨∅, by simp⟩⟩
| Mathlib/MeasureTheory/Covering/BesicovitchVectorSpace.lean | 110 | 150 |
/-
Copyright (c) 2021 Julian Kuelshammer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Julian Kuelshammer
-/
import Mathlib.Algebra.CharP.Algebra
import Mathlib.Algebra.CharP.Invertible
import Mathlib.Algebra.CharP.Lemmas
import Mathlib.Algebra.EuclideanDomain.Field
import Mathlib.Algebra.Field.ZMod
import Mathlib.Algebra.Polynomial.Roots
import Mathlib.RingTheory.Polynomial.Chebyshev
/-!
# Dickson polynomials
The (generalised) Dickson polynomials are a family of polynomials indexed by `ℕ × ℕ`,
with coefficients in a commutative ring `R` depending on an element `a∈R`. More precisely, the
they satisfy the recursion `dickson k a (n + 2) = X * (dickson k a n + 1) - a * (dickson k a n)`
with starting values `dickson k a 0 = 3 - k` and `dickson k a 1 = X`. In the literature,
`dickson k a n` is called the `n`-th Dickson polynomial of the `k`-th kind associated to the
parameter `a : R`. They are closely related to the Chebyshev polynomials in the case that `a=1`.
When `a=0` they are just the family of monomials `X ^ n`.
## Main definition
* `Polynomial.dickson`: the generalised Dickson polynomials.
## Main statements
* `Polynomial.dickson_one_one_mul`, the `(m * n)`-th Dickson polynomial of the first kind for
parameter `1 : R` is the composition of the `m`-th and `n`-th Dickson polynomials of the first
kind for `1 : R`.
* `Polynomial.dickson_one_one_charP`, for a prime number `p`, the `p`-th Dickson polynomial of the
first kind associated to parameter `1 : R` is congruent to `X ^ p` modulo `p`.
## References
* [R. Lidl, G. L. Mullen and G. Turnwald, _Dickson polynomials_][MR1237403]
## TODO
* Redefine `dickson` in terms of `LinearRecurrence`.
* Show that `dickson 2 1` is equal to the characteristic polynomial of the adjacency matrix of a
type A Dynkin diagram.
* Prove that the adjacency matrices of simply laced Dynkin diagrams are precisely the adjacency
matrices of simple connected graphs which annihilate `dickson 2 1`.
-/
noncomputable section
namespace Polynomial
variable {R S : Type*} [CommRing R] [CommRing S] (k : ℕ) (a : R)
/-- `dickson` is the `n`-th (generalised) Dickson polynomial of the `k`-th kind associated to the
element `a ∈ R`. -/
noncomputable def dickson : ℕ → R[X]
| 0 => 3 - k
| 1 => X
| n + 2 => X * dickson (n + 1) - C a * dickson n
@[simp]
theorem dickson_zero : dickson k a 0 = 3 - k :=
rfl
@[simp]
theorem dickson_one : dickson k a 1 = X :=
rfl
theorem dickson_two : dickson k a 2 = X ^ 2 - C a * (3 - k : R[X]) := by
simp only [dickson, sq]
@[simp]
theorem dickson_add_two (n : ℕ) :
dickson k a (n + 2) = X * dickson k a (n + 1) - C a * dickson k a n := by rw [dickson]
theorem dickson_of_two_le {n : ℕ} (h : 2 ≤ n) :
dickson k a n = X * dickson k a (n - 1) - C a * dickson k a (n - 2) := by
obtain ⟨n, rfl⟩ := Nat.exists_eq_add_of_le h
rw [add_comm]
exact dickson_add_two k a n
variable {k a}
theorem map_dickson (f : R →+* S) : ∀ n : ℕ, map f (dickson k a n) = dickson k (f a) n
| 0 => by
simp_rw [dickson_zero, Polynomial.map_sub, Polynomial.map_natCast, Polynomial.map_ofNat]
| 1 => by simp only [dickson_one, map_X]
| n + 2 => by
simp only [dickson_add_two, Polynomial.map_sub, Polynomial.map_mul, map_X, map_C]
rw [map_dickson f n, map_dickson f (n + 1)]
@[simp]
theorem dickson_two_zero : ∀ n : ℕ, dickson 2 (0 : R) n = X ^ n
| 0 => by
simp only [dickson_zero, pow_zero]
norm_num
| 1 => by simp only [dickson_one, pow_one]
| n + 2 => by
simp only [dickson_add_two, C_0, zero_mul, sub_zero]
rw [dickson_two_zero (n + 1), pow_add X (n + 1) 1, mul_comm, pow_one]
| section Dickson
/-!
### A Lambda structure on `ℤ[X]`
Mathlib doesn't currently know what a Lambda ring is.
But once it does, we can endow `ℤ[X]` with a Lambda structure
| Mathlib/RingTheory/Polynomial/Dickson.lean | 105 | 112 |
/-
Copyright (c) 2019 Jean Lo. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jean Lo, Yaël Dillies, Moritz Doll
-/
import Mathlib.Algebra.Order.Pi
import Mathlib.Analysis.Convex.Function
import Mathlib.Analysis.LocallyConvex.Basic
import Mathlib.Data.Real.Pointwise
/-!
# Seminorms
This file defines seminorms.
A seminorm is a function to the reals which is positive-semidefinite, absolutely homogeneous, and
subadditive. They are closely related to convex sets, and a topological vector space is locally
convex if and only if its topology is induced by a family of seminorms.
## Main declarations
For a module over a normed ring:
* `Seminorm`: A function to the reals that is positive-semidefinite, absolutely homogeneous, and
subadditive.
* `normSeminorm 𝕜 E`: The norm on `E` as a seminorm.
## References
* [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966]
## Tags
seminorm, locally convex, LCTVS
-/
assert_not_exists balancedCore
open NormedField Set Filter
open scoped NNReal Pointwise Topology Uniformity
variable {R R' 𝕜 𝕜₂ 𝕜₃ 𝕝 E E₂ E₃ F ι : Type*}
/-- A seminorm on a module over a normed ring is a function to the reals that is positive
semidefinite, positive homogeneous, and subadditive. -/
structure Seminorm (𝕜 : Type*) (E : Type*) [SeminormedRing 𝕜] [AddGroup E] [SMul 𝕜 E] extends
AddGroupSeminorm E where
/-- The seminorm of a scalar multiplication is the product of the absolute value of the scalar
and the original seminorm. -/
smul' : ∀ (a : 𝕜) (x : E), toFun (a • x) = ‖a‖ * toFun x
attribute [nolint docBlame] Seminorm.toAddGroupSeminorm
/-- `SeminormClass F 𝕜 E` states that `F` is a type of seminorms on the `𝕜`-module `E`.
You should extend this class when you extend `Seminorm`. -/
class SeminormClass (F : Type*) (𝕜 E : outParam Type*) [SeminormedRing 𝕜] [AddGroup E]
[SMul 𝕜 E] [FunLike F E ℝ] : Prop extends AddGroupSeminormClass F E ℝ where
/-- The seminorm of a scalar multiplication is the product of the absolute value of the scalar
and the original seminorm. -/
map_smul_eq_mul (f : F) (a : 𝕜) (x : E) : f (a • x) = ‖a‖ * f x
export SeminormClass (map_smul_eq_mul)
section Of
/-- Alternative constructor for a `Seminorm` on an `AddCommGroup E` that is a module over a
`SeminormedRing 𝕜`. -/
def Seminorm.of [SeminormedRing 𝕜] [AddCommGroup E] [Module 𝕜 E] (f : E → ℝ)
(add_le : ∀ x y : E, f (x + y) ≤ f x + f y) (smul : ∀ (a : 𝕜) (x : E), f (a • x) = ‖a‖ * f x) :
Seminorm 𝕜 E where
toFun := f
map_zero' := by rw [← zero_smul 𝕜 (0 : E), smul, norm_zero, zero_mul]
add_le' := add_le
smul' := smul
neg' x := by rw [← neg_one_smul 𝕜, smul, norm_neg, ← smul, one_smul]
/-- Alternative constructor for a `Seminorm` over a normed field `𝕜` that only assumes `f 0 = 0`
and an inequality for the scalar multiplication. -/
def Seminorm.ofSMulLE [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] (f : E → ℝ) (map_zero : f 0 = 0)
(add_le : ∀ x y, f (x + y) ≤ f x + f y) (smul_le : ∀ (r : 𝕜) (x), f (r • x) ≤ ‖r‖ * f x) :
Seminorm 𝕜 E :=
Seminorm.of f add_le fun r x => by
refine le_antisymm (smul_le r x) ?_
by_cases h : r = 0
· simp [h, map_zero]
rw [← mul_le_mul_left (inv_pos.mpr (norm_pos_iff.mpr h))]
rw [inv_mul_cancel_left₀ (norm_ne_zero_iff.mpr h)]
specialize smul_le r⁻¹ (r • x)
rw [norm_inv] at smul_le
convert smul_le
simp [h]
end Of
namespace Seminorm
section SeminormedRing
variable [SeminormedRing 𝕜]
section AddGroup
variable [AddGroup E]
section SMul
variable [SMul 𝕜 E]
instance instFunLike : FunLike (Seminorm 𝕜 E) E ℝ where
coe f := f.toFun
coe_injective' f g h := by
rcases f with ⟨⟨_⟩⟩
rcases g with ⟨⟨_⟩⟩
congr
instance instSeminormClass : SeminormClass (Seminorm 𝕜 E) 𝕜 E where
map_zero f := f.map_zero'
map_add_le_add f := f.add_le'
map_neg_eq_map f := f.neg'
map_smul_eq_mul f := f.smul'
@[ext]
theorem ext {p q : Seminorm 𝕜 E} (h : ∀ x, (p : E → ℝ) x = q x) : p = q :=
DFunLike.ext p q h
instance instZero : Zero (Seminorm 𝕜 E) :=
⟨{ AddGroupSeminorm.instZeroAddGroupSeminorm.zero with
smul' := fun _ _ => (mul_zero _).symm }⟩
@[simp]
theorem coe_zero : ⇑(0 : Seminorm 𝕜 E) = 0 :=
rfl
@[simp]
theorem zero_apply (x : E) : (0 : Seminorm 𝕜 E) x = 0 :=
rfl
instance : Inhabited (Seminorm 𝕜 E) :=
⟨0⟩
variable (p : Seminorm 𝕜 E) (x : E) (r : ℝ)
/-- Any action on `ℝ` which factors through `ℝ≥0` applies to a seminorm. -/
instance instSMul [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] : SMul R (Seminorm 𝕜 E) where
smul r p :=
{ r • p.toAddGroupSeminorm with
toFun := fun x => r • p x
smul' := fun _ _ => by
simp only [← smul_one_smul ℝ≥0 r (_ : ℝ), NNReal.smul_def, smul_eq_mul]
rw [map_smul_eq_mul, mul_left_comm] }
instance [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] [SMul R' ℝ] [SMul R' ℝ≥0]
[IsScalarTower R' ℝ≥0 ℝ] [SMul R R'] [IsScalarTower R R' ℝ] :
IsScalarTower R R' (Seminorm 𝕜 E) where
smul_assoc r a p := ext fun x => smul_assoc r a (p x)
theorem coe_smul [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p : Seminorm 𝕜 E) :
⇑(r • p) = r • ⇑p :=
rfl
@[simp]
theorem smul_apply [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p : Seminorm 𝕜 E)
(x : E) : (r • p) x = r • p x :=
rfl
instance instAdd : Add (Seminorm 𝕜 E) where
add p q :=
{ p.toAddGroupSeminorm + q.toAddGroupSeminorm with
toFun := fun x => p x + q x
smul' := fun a x => by simp only [map_smul_eq_mul, map_smul_eq_mul, mul_add] }
theorem coe_add (p q : Seminorm 𝕜 E) : ⇑(p + q) = p + q :=
rfl
@[simp]
theorem add_apply (p q : Seminorm 𝕜 E) (x : E) : (p + q) x = p x + q x :=
rfl
instance instAddMonoid : AddMonoid (Seminorm 𝕜 E) :=
DFunLike.coe_injective.addMonoid _ rfl coe_add fun _ _ => by rfl
instance instAddCommMonoid : AddCommMonoid (Seminorm 𝕜 E) :=
DFunLike.coe_injective.addCommMonoid _ rfl coe_add fun _ _ => by rfl
instance instPartialOrder : PartialOrder (Seminorm 𝕜 E) :=
PartialOrder.lift _ DFunLike.coe_injective
instance instIsOrderedCancelAddMonoid : IsOrderedCancelAddMonoid (Seminorm 𝕜 E) :=
DFunLike.coe_injective.isOrderedCancelAddMonoid _ rfl coe_add fun _ _ => rfl
instance instMulAction [Monoid R] [MulAction R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] :
MulAction R (Seminorm 𝕜 E) :=
DFunLike.coe_injective.mulAction _ (by intros; rfl)
variable (𝕜 E)
/-- `coeFn` as an `AddMonoidHom`. Helper definition for showing that `Seminorm 𝕜 E` is a module. -/
@[simps]
def coeFnAddMonoidHom : AddMonoidHom (Seminorm 𝕜 E) (E → ℝ) where
toFun := (↑)
map_zero' := coe_zero
map_add' := coe_add
theorem coeFnAddMonoidHom_injective : Function.Injective (coeFnAddMonoidHom 𝕜 E) :=
show @Function.Injective (Seminorm 𝕜 E) (E → ℝ) (↑) from DFunLike.coe_injective
variable {𝕜 E}
instance instDistribMulAction [Monoid R] [DistribMulAction R ℝ] [SMul R ℝ≥0]
[IsScalarTower R ℝ≥0 ℝ] : DistribMulAction R (Seminorm 𝕜 E) :=
(coeFnAddMonoidHom_injective 𝕜 E).distribMulAction _ (by intros; rfl)
instance instModule [Semiring R] [Module R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] :
Module R (Seminorm 𝕜 E) :=
(coeFnAddMonoidHom_injective 𝕜 E).module R _ (by intros; rfl)
instance instSup : Max (Seminorm 𝕜 E) where
max p q :=
{ p.toAddGroupSeminorm ⊔ q.toAddGroupSeminorm with
toFun := p ⊔ q
smul' := fun x v =>
(congr_arg₂ max (map_smul_eq_mul p x v) (map_smul_eq_mul q x v)).trans <|
(mul_max_of_nonneg _ _ <| norm_nonneg x).symm }
@[simp]
theorem coe_sup (p q : Seminorm 𝕜 E) : ⇑(p ⊔ q) = (p : E → ℝ) ⊔ (q : E → ℝ) :=
rfl
theorem sup_apply (p q : Seminorm 𝕜 E) (x : E) : (p ⊔ q) x = p x ⊔ q x :=
rfl
theorem smul_sup [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p q : Seminorm 𝕜 E) :
r • (p ⊔ q) = r • p ⊔ r • q :=
have real.smul_max : ∀ x y : ℝ, r • max x y = max (r • x) (r • y) := fun x y => by
simpa only [← smul_eq_mul, ← NNReal.smul_def, smul_one_smul ℝ≥0 r (_ : ℝ)] using
mul_max_of_nonneg x y (r • (1 : ℝ≥0) : ℝ≥0).coe_nonneg
ext fun _ => real.smul_max _ _
@[simp, norm_cast]
theorem coe_le_coe {p q : Seminorm 𝕜 E} : (p : E → ℝ) ≤ q ↔ p ≤ q :=
Iff.rfl
@[simp, norm_cast]
theorem coe_lt_coe {p q : Seminorm 𝕜 E} : (p : E → ℝ) < q ↔ p < q :=
Iff.rfl
theorem le_def {p q : Seminorm 𝕜 E} : p ≤ q ↔ ∀ x, p x ≤ q x :=
Iff.rfl
theorem lt_def {p q : Seminorm 𝕜 E} : p < q ↔ p ≤ q ∧ ∃ x, p x < q x :=
@Pi.lt_def _ _ _ p q
instance instSemilatticeSup : SemilatticeSup (Seminorm 𝕜 E) :=
Function.Injective.semilatticeSup _ DFunLike.coe_injective coe_sup
end SMul
end AddGroup
section Module
variable [SeminormedRing 𝕜₂] [SeminormedRing 𝕜₃]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
variable {σ₂₃ : 𝕜₂ →+* 𝕜₃} [RingHomIsometric σ₂₃]
variable {σ₁₃ : 𝕜 →+* 𝕜₃} [RingHomIsometric σ₁₃]
variable [AddCommGroup E] [AddCommGroup E₂] [AddCommGroup E₃]
variable [Module 𝕜 E] [Module 𝕜₂ E₂] [Module 𝕜₃ E₃]
variable [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ]
/-- Composition of a seminorm with a linear map is a seminorm. -/
def comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) : Seminorm 𝕜 E :=
{ p.toAddGroupSeminorm.comp f.toAddMonoidHom with
toFun := fun x => p (f x)
-- Porting note: the `simp only` below used to be part of the `rw`.
-- I'm not sure why this change was needed, and am worried by it!
-- Note: https://github.com/leanprover-community/mathlib4/pull/8386 had to change `map_smulₛₗ` to `map_smulₛₗ _`
smul' := fun _ _ => by simp only [map_smulₛₗ _]; rw [map_smul_eq_mul, RingHomIsometric.is_iso] }
theorem coe_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) : ⇑(p.comp f) = p ∘ f :=
rfl
@[simp]
theorem comp_apply (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (x : E) : (p.comp f) x = p (f x) :=
rfl
@[simp]
theorem comp_id (p : Seminorm 𝕜 E) : p.comp LinearMap.id = p :=
ext fun _ => rfl
@[simp]
theorem comp_zero (p : Seminorm 𝕜₂ E₂) : p.comp (0 : E →ₛₗ[σ₁₂] E₂) = 0 :=
ext fun _ => map_zero p
@[simp]
theorem zero_comp (f : E →ₛₗ[σ₁₂] E₂) : (0 : Seminorm 𝕜₂ E₂).comp f = 0 :=
ext fun _ => rfl
theorem comp_comp [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] (p : Seminorm 𝕜₃ E₃) (g : E₂ →ₛₗ[σ₂₃] E₃)
(f : E →ₛₗ[σ₁₂] E₂) : p.comp (g.comp f) = (p.comp g).comp f :=
ext fun _ => rfl
theorem add_comp (p q : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) :
(p + q).comp f = p.comp f + q.comp f :=
ext fun _ => rfl
theorem comp_add_le (p : Seminorm 𝕜₂ E₂) (f g : E →ₛₗ[σ₁₂] E₂) :
p.comp (f + g) ≤ p.comp f + p.comp g := fun _ => map_add_le_add p _ _
theorem smul_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (c : R) :
(c • p).comp f = c • p.comp f :=
ext fun _ => rfl
theorem comp_mono {p q : Seminorm 𝕜₂ E₂} (f : E →ₛₗ[σ₁₂] E₂) (hp : p ≤ q) : p.comp f ≤ q.comp f :=
fun _ => hp _
/-- The composition as an `AddMonoidHom`. -/
@[simps]
def pullback (f : E →ₛₗ[σ₁₂] E₂) : Seminorm 𝕜₂ E₂ →+ Seminorm 𝕜 E where
toFun := fun p => p.comp f
map_zero' := zero_comp f
map_add' := fun p q => add_comp p q f
instance instOrderBot : OrderBot (Seminorm 𝕜 E) where
bot := 0
bot_le := apply_nonneg
@[simp]
theorem coe_bot : ⇑(⊥ : Seminorm 𝕜 E) = 0 :=
rfl
theorem bot_eq_zero : (⊥ : Seminorm 𝕜 E) = 0 :=
rfl
theorem smul_le_smul {p q : Seminorm 𝕜 E} {a b : ℝ≥0} (hpq : p ≤ q) (hab : a ≤ b) :
a • p ≤ b • q := by
simp_rw [le_def]
intro x
exact mul_le_mul hab (hpq x) (apply_nonneg p x) (NNReal.coe_nonneg b)
theorem finset_sup_apply (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) :
s.sup p x = ↑(s.sup fun i => ⟨p i x, apply_nonneg (p i) x⟩ : ℝ≥0) := by
induction' s using Finset.cons_induction_on with a s ha ih
· rw [Finset.sup_empty, Finset.sup_empty, coe_bot, _root_.bot_eq_zero, Pi.zero_apply]
norm_cast
· rw [Finset.sup_cons, Finset.sup_cons, coe_sup, Pi.sup_apply, NNReal.coe_max, NNReal.coe_mk, ih]
theorem exists_apply_eq_finset_sup (p : ι → Seminorm 𝕜 E) {s : Finset ι} (hs : s.Nonempty) (x : E) :
∃ i ∈ s, s.sup p x = p i x := by
rcases Finset.exists_mem_eq_sup s hs (fun i ↦ (⟨p i x, apply_nonneg _ _⟩ : ℝ≥0)) with ⟨i, hi, hix⟩
rw [finset_sup_apply]
exact ⟨i, hi, congr_arg _ hix⟩
theorem zero_or_exists_apply_eq_finset_sup (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) :
s.sup p x = 0 ∨ ∃ i ∈ s, s.sup p x = p i x := by
rcases Finset.eq_empty_or_nonempty s with (rfl|hs)
· left; rfl
· right; exact exists_apply_eq_finset_sup p hs x
theorem finset_sup_smul (p : ι → Seminorm 𝕜 E) (s : Finset ι) (C : ℝ≥0) :
s.sup (C • p) = C • s.sup p := by
ext x
rw [smul_apply, finset_sup_apply, finset_sup_apply]
symm
exact congr_arg ((↑) : ℝ≥0 → ℝ) (NNReal.mul_finset_sup C s (fun i ↦ ⟨p i x, apply_nonneg _ _⟩))
theorem finset_sup_le_sum (p : ι → Seminorm 𝕜 E) (s : Finset ι) : s.sup p ≤ ∑ i ∈ s, p i := by
classical
refine Finset.sup_le_iff.mpr ?_
intro i hi
rw [Finset.sum_eq_sum_diff_singleton_add hi, le_add_iff_nonneg_left]
exact bot_le
theorem finset_sup_apply_le {p : ι → Seminorm 𝕜 E} {s : Finset ι} {x : E} {a : ℝ} (ha : 0 ≤ a)
(h : ∀ i, i ∈ s → p i x ≤ a) : s.sup p x ≤ a := by
lift a to ℝ≥0 using ha
rw [finset_sup_apply, NNReal.coe_le_coe]
exact Finset.sup_le h
theorem le_finset_sup_apply {p : ι → Seminorm 𝕜 E} {s : Finset ι} {x : E} {i : ι}
(hi : i ∈ s) : p i x ≤ s.sup p x :=
(Finset.le_sup hi : p i ≤ s.sup p) x
theorem finset_sup_apply_lt {p : ι → Seminorm 𝕜 E} {s : Finset ι} {x : E} {a : ℝ} (ha : 0 < a)
(h : ∀ i, i ∈ s → p i x < a) : s.sup p x < a := by
lift a to ℝ≥0 using ha.le
rw [finset_sup_apply, NNReal.coe_lt_coe, Finset.sup_lt_iff]
· exact h
· exact NNReal.coe_pos.mpr ha
theorem norm_sub_map_le_sub (p : Seminorm 𝕜 E) (x y : E) : ‖p x - p y‖ ≤ p (x - y) :=
abs_sub_map_le_sub p x y
end Module
end SeminormedRing
section SeminormedCommRing
variable [SeminormedRing 𝕜] [SeminormedCommRing 𝕜₂]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
variable [AddCommGroup E] [AddCommGroup E₂] [Module 𝕜 E] [Module 𝕜₂ E₂]
theorem comp_smul (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (c : 𝕜₂) :
p.comp (c • f) = ‖c‖₊ • p.comp f :=
ext fun _ => by
rw [comp_apply, smul_apply, LinearMap.smul_apply, map_smul_eq_mul, NNReal.smul_def, coe_nnnorm,
smul_eq_mul, comp_apply]
theorem comp_smul_apply (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (c : 𝕜₂) (x : E) :
p.comp (c • f) x = ‖c‖ * p (f x) :=
map_smul_eq_mul p _ _
end SeminormedCommRing
section NormedField
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] {p q : Seminorm 𝕜 E} {x : E}
/-- Auxiliary lemma to show that the infimum of seminorms is well-defined. -/
theorem bddBelow_range_add : BddBelow (range fun u => p u + q (x - u)) :=
⟨0, by
rintro _ ⟨x, rfl⟩
dsimp; positivity⟩
noncomputable instance instInf : Min (Seminorm 𝕜 E) where
min p q :=
{ p.toAddGroupSeminorm ⊓ q.toAddGroupSeminorm with
toFun := fun x => ⨅ u : E, p u + q (x - u)
smul' := by
intro a x
obtain rfl | ha := eq_or_ne a 0
· rw [norm_zero, zero_mul, zero_smul]
refine
ciInf_eq_of_forall_ge_of_forall_gt_exists_lt
(fun i => by positivity)
fun x hx => ⟨0, by rwa [map_zero, sub_zero, map_zero, add_zero]⟩
simp_rw [Real.mul_iInf_of_nonneg (norm_nonneg a), mul_add, ← map_smul_eq_mul p, ←
map_smul_eq_mul q, smul_sub]
refine
Function.Surjective.iInf_congr ((a⁻¹ • ·) : E → E)
(fun u => ⟨a • u, inv_smul_smul₀ ha u⟩) fun u => ?_
rw [smul_inv_smul₀ ha] }
@[simp]
theorem inf_apply (p q : Seminorm 𝕜 E) (x : E) : (p ⊓ q) x = ⨅ u : E, p u + q (x - u) :=
rfl
noncomputable instance instLattice : Lattice (Seminorm 𝕜 E) :=
{ Seminorm.instSemilatticeSup with
inf := (· ⊓ ·)
inf_le_left := fun p q x =>
ciInf_le_of_le bddBelow_range_add x <| by
simp only [sub_self, map_zero, add_zero]; rfl
inf_le_right := fun p q x =>
ciInf_le_of_le bddBelow_range_add 0 <| by
simp only [sub_self, map_zero, zero_add, sub_zero]; rfl
le_inf := fun a _ _ hab hac _ =>
le_ciInf fun _ => (le_map_add_map_sub a _ _).trans <| add_le_add (hab _) (hac _) }
theorem smul_inf [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p q : Seminorm 𝕜 E) :
r • (p ⊓ q) = r • p ⊓ r • q := by
ext
simp_rw [smul_apply, inf_apply, smul_apply, ← smul_one_smul ℝ≥0 r (_ : ℝ), NNReal.smul_def,
smul_eq_mul, Real.mul_iInf_of_nonneg (NNReal.coe_nonneg _), mul_add]
section Classical
open Classical in
/-- We define the supremum of an arbitrary subset of `Seminorm 𝕜 E` as follows:
* if `s` is `BddAbove` *as a set of functions `E → ℝ`* (that is, if `s` is pointwise bounded
above), we take the pointwise supremum of all elements of `s`, and we prove that it is indeed a
seminorm.
* otherwise, we take the zero seminorm `⊥`.
There are two things worth mentioning here:
* First, it is not trivial at first that `s` being bounded above *by a function* implies
being bounded above *as a seminorm*. We show this in `Seminorm.bddAbove_iff` by using
that the `Sup s` as defined here is then a bounding seminorm for `s`. So it is important to make
the case disjunction on `BddAbove ((↑) '' s : Set (E → ℝ))` and not `BddAbove s`.
* Since the pointwise `Sup` already gives `0` at points where a family of functions is
not bounded above, one could hope that just using the pointwise `Sup` would work here, without the
need for an additional case disjunction. As discussed on Zulip, this doesn't work because this can
give a function which does *not* satisfy the seminorm axioms (typically sub-additivity).
-/
noncomputable instance instSupSet : SupSet (Seminorm 𝕜 E) where
sSup s :=
if h : BddAbove ((↑) '' s : Set (E → ℝ)) then
{ toFun := ⨆ p : s, ((p : Seminorm 𝕜 E) : E → ℝ)
map_zero' := by
rw [iSup_apply, ← @Real.iSup_const_zero s]
congr!
rename_i _ _ _ i
exact map_zero i.1
add_le' := fun x y => by
rcases h with ⟨q, hq⟩
obtain rfl | h := s.eq_empty_or_nonempty
· simp [Real.iSup_of_isEmpty]
haveI : Nonempty ↑s := h.coe_sort
simp only [iSup_apply]
refine ciSup_le fun i =>
((i : Seminorm 𝕜 E).add_le' x y).trans <| add_le_add
-- Porting note: `f` is provided to force `Subtype.val` to appear.
-- A type ascription on `_` would have also worked, but would have been more verbose.
(le_ciSup (f := fun i => (Subtype.val i : Seminorm 𝕜 E).toFun x) ⟨q x, ?_⟩ i)
(le_ciSup (f := fun i => (Subtype.val i : Seminorm 𝕜 E).toFun y) ⟨q y, ?_⟩ i)
<;> rw [mem_upperBounds, forall_mem_range]
<;> exact fun j => hq (mem_image_of_mem _ j.2) _
neg' := fun x => by
simp only [iSup_apply]
congr! 2
rename_i _ _ _ i
exact i.1.neg' _
smul' := fun a x => by
simp only [iSup_apply]
rw [← smul_eq_mul,
Real.smul_iSup_of_nonneg (norm_nonneg a) fun i : s => (i : Seminorm 𝕜 E) x]
congr!
rename_i _ _ _ i
exact i.1.smul' a x }
else ⊥
protected theorem coe_sSup_eq' {s : Set <| Seminorm 𝕜 E}
(hs : BddAbove ((↑) '' s : Set (E → ℝ))) : ↑(sSup s) = ⨆ p : s, ((p : Seminorm 𝕜 E) : E → ℝ) :=
congr_arg _ (dif_pos hs)
protected theorem bddAbove_iff {s : Set <| Seminorm 𝕜 E} :
BddAbove s ↔ BddAbove ((↑) '' s : Set (E → ℝ)) :=
⟨fun ⟨q, hq⟩ => ⟨q, forall_mem_image.2 fun _ hp => hq hp⟩, fun H =>
⟨sSup s, fun p hp x => by
dsimp
rw [Seminorm.coe_sSup_eq' H, iSup_apply]
rcases H with ⟨q, hq⟩
exact
le_ciSup ⟨q x, forall_mem_range.mpr fun i : s => hq (mem_image_of_mem _ i.2) x⟩ ⟨p, hp⟩⟩⟩
protected theorem bddAbove_range_iff {ι : Sort*} {p : ι → Seminorm 𝕜 E} :
BddAbove (range p) ↔ ∀ x, BddAbove (range fun i ↦ p i x) := by
rw [Seminorm.bddAbove_iff, ← range_comp, bddAbove_range_pi]; rfl
protected theorem coe_sSup_eq {s : Set <| Seminorm 𝕜 E} (hs : BddAbove s) :
↑(sSup s) = ⨆ p : s, ((p : Seminorm 𝕜 E) : E → ℝ) :=
Seminorm.coe_sSup_eq' (Seminorm.bddAbove_iff.mp hs)
protected theorem coe_iSup_eq {ι : Sort*} {p : ι → Seminorm 𝕜 E} (hp : BddAbove (range p)) :
↑(⨆ i, p i) = ⨆ i, ((p i : Seminorm 𝕜 E) : E → ℝ) := by
rw [← sSup_range, Seminorm.coe_sSup_eq hp]
exact iSup_range' (fun p : Seminorm 𝕜 E => (p : E → ℝ)) p
protected theorem sSup_apply {s : Set (Seminorm 𝕜 E)} (hp : BddAbove s) {x : E} :
(sSup s) x = ⨆ p : s, (p : E → ℝ) x := by
rw [Seminorm.coe_sSup_eq hp, iSup_apply]
protected theorem iSup_apply {ι : Sort*} {p : ι → Seminorm 𝕜 E}
(hp : BddAbove (range p)) {x : E} : (⨆ i, p i) x = ⨆ i, p i x := by
rw [Seminorm.coe_iSup_eq hp, iSup_apply]
protected theorem sSup_empty : sSup (∅ : Set (Seminorm 𝕜 E)) = ⊥ := by
ext
rw [Seminorm.sSup_apply bddAbove_empty, Real.iSup_of_isEmpty]
rfl
private theorem isLUB_sSup (s : Set (Seminorm 𝕜 E)) (hs₁ : BddAbove s) (hs₂ : s.Nonempty) :
IsLUB s (sSup s) := by
refine ⟨fun p hp x => ?_, fun p hp x => ?_⟩ <;> haveI : Nonempty ↑s := hs₂.coe_sort <;>
dsimp <;> rw [Seminorm.coe_sSup_eq hs₁, iSup_apply]
· rcases hs₁ with ⟨q, hq⟩
exact le_ciSup ⟨q x, forall_mem_range.mpr fun i : s => hq i.2 x⟩ ⟨p, hp⟩
· exact ciSup_le fun q => hp q.2 x
/-- `Seminorm 𝕜 E` is a conditionally complete lattice.
Note that, while `inf`, `sup` and `sSup` have good definitional properties (corresponding to
the instances given here for `Inf`, `Sup` and `SupSet` respectively), `sInf s` is just
defined as the supremum of the lower bounds of `s`, which is not really useful in practice. If you
need to use `sInf` on seminorms, then you should probably provide a more workable definition first,
but this is unlikely to happen so we keep the "bad" definition for now. -/
noncomputable instance instConditionallyCompleteLattice :
ConditionallyCompleteLattice (Seminorm 𝕜 E) :=
conditionallyCompleteLatticeOfLatticeOfsSup (Seminorm 𝕜 E) Seminorm.isLUB_sSup
end Classical
end NormedField
/-! ### Seminorm ball -/
section SeminormedRing
variable [SeminormedRing 𝕜]
section AddCommGroup
variable [AddCommGroup E]
section SMul
variable [SMul 𝕜 E] (p : Seminorm 𝕜 E)
/-- The ball of radius `r` at `x` with respect to seminorm `p` is the set of elements `y` with
`p (y - x) < r`. -/
def ball (x : E) (r : ℝ) :=
{ y : E | p (y - x) < r }
/-- The closed ball of radius `r` at `x` with respect to seminorm `p` is the set of elements `y`
with `p (y - x) ≤ r`. -/
def closedBall (x : E) (r : ℝ) :=
{ y : E | p (y - x) ≤ r }
variable {x y : E} {r : ℝ}
@[simp]
theorem mem_ball : y ∈ ball p x r ↔ p (y - x) < r :=
Iff.rfl
@[simp]
theorem mem_closedBall : y ∈ closedBall p x r ↔ p (y - x) ≤ r :=
Iff.rfl
theorem mem_ball_self (hr : 0 < r) : x ∈ ball p x r := by simp [hr]
theorem mem_closedBall_self (hr : 0 ≤ r) : x ∈ closedBall p x r := by simp [hr]
theorem mem_ball_zero : y ∈ ball p 0 r ↔ p y < r := by rw [mem_ball, sub_zero]
theorem mem_closedBall_zero : y ∈ closedBall p 0 r ↔ p y ≤ r := by rw [mem_closedBall, sub_zero]
theorem ball_zero_eq : ball p 0 r = { y : E | p y < r } :=
Set.ext fun _ => p.mem_ball_zero
theorem closedBall_zero_eq : closedBall p 0 r = { y : E | p y ≤ r } :=
Set.ext fun _ => p.mem_closedBall_zero
theorem ball_subset_closedBall (x r) : ball p x r ⊆ closedBall p x r := fun _ h =>
(mem_closedBall _).mpr ((mem_ball _).mp h).le
theorem closedBall_eq_biInter_ball (x r) : closedBall p x r = ⋂ ρ > r, ball p x ρ := by
ext y; simp_rw [mem_closedBall, mem_iInter₂, mem_ball, ← forall_lt_iff_le']
@[simp]
theorem ball_zero' (x : E) (hr : 0 < r) : ball (0 : Seminorm 𝕜 E) x r = Set.univ := by
rw [Set.eq_univ_iff_forall, ball]
simp [hr]
@[simp]
theorem closedBall_zero' (x : E) (hr : 0 < r) : closedBall (0 : Seminorm 𝕜 E) x r = Set.univ :=
eq_univ_of_subset (ball_subset_closedBall _ _ _) (ball_zero' x hr)
theorem ball_smul (p : Seminorm 𝕜 E) {c : NNReal} (hc : 0 < c) (r : ℝ) (x : E) :
(c • p).ball x r = p.ball x (r / c) := by
ext
rw [mem_ball, mem_ball, smul_apply, NNReal.smul_def, smul_eq_mul, mul_comm,
lt_div_iff₀ (NNReal.coe_pos.mpr hc)]
theorem closedBall_smul (p : Seminorm 𝕜 E) {c : NNReal} (hc : 0 < c) (r : ℝ) (x : E) :
(c • p).closedBall x r = p.closedBall x (r / c) := by
ext
rw [mem_closedBall, mem_closedBall, smul_apply, NNReal.smul_def, smul_eq_mul, mul_comm,
le_div_iff₀ (NNReal.coe_pos.mpr hc)]
theorem ball_sup (p : Seminorm 𝕜 E) (q : Seminorm 𝕜 E) (e : E) (r : ℝ) :
ball (p ⊔ q) e r = ball p e r ∩ ball q e r := by
simp_rw [ball, ← Set.setOf_and, coe_sup, Pi.sup_apply, sup_lt_iff]
theorem closedBall_sup (p : Seminorm 𝕜 E) (q : Seminorm 𝕜 E) (e : E) (r : ℝ) :
closedBall (p ⊔ q) e r = closedBall p e r ∩ closedBall q e r := by
simp_rw [closedBall, ← Set.setOf_and, coe_sup, Pi.sup_apply, sup_le_iff]
theorem ball_finset_sup' (p : ι → Seminorm 𝕜 E) (s : Finset ι) (H : s.Nonempty) (e : E) (r : ℝ) :
ball (s.sup' H p) e r = s.inf' H fun i => ball (p i) e r := by
induction H using Finset.Nonempty.cons_induction with
| singleton => simp
| cons _ _ _ hs ih =>
rw [Finset.sup'_cons hs, Finset.inf'_cons hs, ball_sup]
-- Porting note: `rw` can't use `inf_eq_inter` here, but `simp` can?
simp only [inf_eq_inter, ih]
theorem closedBall_finset_sup' (p : ι → Seminorm 𝕜 E) (s : Finset ι) (H : s.Nonempty) (e : E)
(r : ℝ) : closedBall (s.sup' H p) e r = s.inf' H fun i => closedBall (p i) e r := by
induction H using Finset.Nonempty.cons_induction with
| singleton => simp
| cons _ _ _ hs ih =>
rw [Finset.sup'_cons hs, Finset.inf'_cons hs, closedBall_sup]
-- Porting note: `rw` can't use `inf_eq_inter` here, but `simp` can?
simp only [inf_eq_inter, ih]
theorem ball_mono {p : Seminorm 𝕜 E} {r₁ r₂ : ℝ} (h : r₁ ≤ r₂) : p.ball x r₁ ⊆ p.ball x r₂ :=
fun _ (hx : _ < _) => hx.trans_le h
theorem closedBall_mono {p : Seminorm 𝕜 E} {r₁ r₂ : ℝ} (h : r₁ ≤ r₂) :
p.closedBall x r₁ ⊆ p.closedBall x r₂ := fun _ (hx : _ ≤ _) => hx.trans h
theorem ball_antitone {p q : Seminorm 𝕜 E} (h : q ≤ p) : p.ball x r ⊆ q.ball x r := fun _ =>
(h _).trans_lt
theorem closedBall_antitone {p q : Seminorm 𝕜 E} (h : q ≤ p) :
p.closedBall x r ⊆ q.closedBall x r := fun _ => (h _).trans
theorem ball_add_ball_subset (p : Seminorm 𝕜 E) (r₁ r₂ : ℝ) (x₁ x₂ : E) :
p.ball (x₁ : E) r₁ + p.ball (x₂ : E) r₂ ⊆ p.ball (x₁ + x₂) (r₁ + r₂) := by
rintro x ⟨y₁, hy₁, y₂, hy₂, rfl⟩
rw [mem_ball, add_sub_add_comm]
exact (map_add_le_add p _ _).trans_lt (add_lt_add hy₁ hy₂)
theorem closedBall_add_closedBall_subset (p : Seminorm 𝕜 E) (r₁ r₂ : ℝ) (x₁ x₂ : E) :
p.closedBall (x₁ : E) r₁ + p.closedBall (x₂ : E) r₂ ⊆ p.closedBall (x₁ + x₂) (r₁ + r₂) := by
rintro x ⟨y₁, hy₁, y₂, hy₂, rfl⟩
rw [mem_closedBall, add_sub_add_comm]
exact (map_add_le_add p _ _).trans (add_le_add hy₁ hy₂)
theorem sub_mem_ball (p : Seminorm 𝕜 E) (x₁ x₂ y : E) (r : ℝ) :
x₁ - x₂ ∈ p.ball y r ↔ x₁ ∈ p.ball (x₂ + y) r := by simp_rw [mem_ball, sub_sub]
theorem sub_mem_closedBall (p : Seminorm 𝕜 E) (x₁ x₂ y : E) (r : ℝ) :
x₁ - x₂ ∈ p.closedBall y r ↔ x₁ ∈ p.closedBall (x₂ + y) r := by
simp_rw [mem_closedBall, sub_sub]
/-- The image of a ball under addition with a singleton is another ball. -/
theorem vadd_ball (p : Seminorm 𝕜 E) : x +ᵥ p.ball y r = p.ball (x +ᵥ y) r :=
letI := AddGroupSeminorm.toSeminormedAddCommGroup p.toAddGroupSeminorm
Metric.vadd_ball x y r
/-- The image of a closed ball under addition with a singleton is another closed ball. -/
theorem vadd_closedBall (p : Seminorm 𝕜 E) : x +ᵥ p.closedBall y r = p.closedBall (x +ᵥ y) r :=
letI := AddGroupSeminorm.toSeminormedAddCommGroup p.toAddGroupSeminorm
Metric.vadd_closedBall x y r
end SMul
section Module
variable [Module 𝕜 E]
variable [SeminormedRing 𝕜₂] [AddCommGroup E₂] [Module 𝕜₂ E₂]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
theorem ball_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (x : E) (r : ℝ) :
(p.comp f).ball x r = f ⁻¹' p.ball (f x) r := by
ext
simp_rw [ball, mem_preimage, comp_apply, Set.mem_setOf_eq, map_sub]
theorem closedBall_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (x : E) (r : ℝ) :
(p.comp f).closedBall x r = f ⁻¹' p.closedBall (f x) r := by
ext
simp_rw [closedBall, mem_preimage, comp_apply, Set.mem_setOf_eq, map_sub]
variable (p : Seminorm 𝕜 E)
theorem preimage_metric_ball {r : ℝ} : p ⁻¹' Metric.ball 0 r = { x | p x < r } := by
ext x
simp only [mem_setOf, mem_preimage, mem_ball_zero_iff, Real.norm_of_nonneg (apply_nonneg p _)]
theorem preimage_metric_closedBall {r : ℝ} : p ⁻¹' Metric.closedBall 0 r = { x | p x ≤ r } := by
ext x
simp only [mem_setOf, mem_preimage, mem_closedBall_zero_iff,
Real.norm_of_nonneg (apply_nonneg p _)]
theorem ball_zero_eq_preimage_ball {r : ℝ} : p.ball 0 r = p ⁻¹' Metric.ball 0 r := by
rw [ball_zero_eq, preimage_metric_ball]
theorem closedBall_zero_eq_preimage_closedBall {r : ℝ} :
p.closedBall 0 r = p ⁻¹' Metric.closedBall 0 r := by
rw [closedBall_zero_eq, preimage_metric_closedBall]
@[simp]
theorem ball_bot {r : ℝ} (x : E) (hr : 0 < r) : ball (⊥ : Seminorm 𝕜 E) x r = Set.univ :=
ball_zero' x hr
@[simp]
theorem closedBall_bot {r : ℝ} (x : E) (hr : 0 < r) :
closedBall (⊥ : Seminorm 𝕜 E) x r = Set.univ :=
closedBall_zero' x hr
/-- Seminorm-balls at the origin are balanced. -/
theorem balanced_ball_zero (r : ℝ) : Balanced 𝕜 (ball p 0 r) := by
rintro a ha x ⟨y, hy, hx⟩
rw [mem_ball_zero, ← hx, map_smul_eq_mul]
calc
_ ≤ p y := mul_le_of_le_one_left (apply_nonneg p _) ha
_ < r := by rwa [mem_ball_zero] at hy
/-- Closed seminorm-balls at the origin are balanced. -/
theorem balanced_closedBall_zero (r : ℝ) : Balanced 𝕜 (closedBall p 0 r) := by
rintro a ha x ⟨y, hy, hx⟩
rw [mem_closedBall_zero, ← hx, map_smul_eq_mul]
calc
_ ≤ p y := mul_le_of_le_one_left (apply_nonneg p _) ha
_ ≤ r := by rwa [mem_closedBall_zero] at hy
theorem ball_finset_sup_eq_iInter (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ}
(hr : 0 < r) : ball (s.sup p) x r = ⋂ i ∈ s, ball (p i) x r := by
lift r to NNReal using hr.le
simp_rw [ball, iInter_setOf, finset_sup_apply, NNReal.coe_lt_coe,
Finset.sup_lt_iff (show ⊥ < r from hr), ← NNReal.coe_lt_coe, NNReal.coe_mk]
theorem closedBall_finset_sup_eq_iInter (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ}
(hr : 0 ≤ r) : closedBall (s.sup p) x r = ⋂ i ∈ s, closedBall (p i) x r := by
lift r to NNReal using hr
simp_rw [closedBall, iInter_setOf, finset_sup_apply, NNReal.coe_le_coe, Finset.sup_le_iff, ←
NNReal.coe_le_coe, NNReal.coe_mk]
theorem ball_finset_sup (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ} (hr : 0 < r) :
ball (s.sup p) x r = s.inf fun i => ball (p i) x r := by
rw [Finset.inf_eq_iInf]
exact ball_finset_sup_eq_iInter _ _ _ hr
theorem closedBall_finset_sup (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ} (hr : 0 ≤ r) :
closedBall (s.sup p) x r = s.inf fun i => closedBall (p i) x r := by
rw [Finset.inf_eq_iInf]
exact closedBall_finset_sup_eq_iInter _ _ _ hr
@[simp]
theorem ball_eq_emptyset (p : Seminorm 𝕜 E) {x : E} {r : ℝ} (hr : r ≤ 0) : p.ball x r = ∅ := by
ext
rw [Seminorm.mem_ball, Set.mem_empty_iff_false, iff_false, not_lt]
exact hr.trans (apply_nonneg p _)
@[simp]
theorem closedBall_eq_emptyset (p : Seminorm 𝕜 E) {x : E} {r : ℝ} (hr : r < 0) :
| p.closedBall x r = ∅ := by
ext
rw [Seminorm.mem_closedBall, Set.mem_empty_iff_false, iff_false, not_le]
exact hr.trans_le (apply_nonneg _ _)
| Mathlib/Analysis/Seminorm.lean | 820 | 823 |
/-
Copyright (c) 2017 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis, Keeley Hoek
-/
import Mathlib.Algebra.NeZero
import Mathlib.Data.Int.DivMod
import Mathlib.Logic.Embedding.Basic
import Mathlib.Logic.Equiv.Set
import Mathlib.Tactic.Common
import Mathlib.Tactic.Attr.Register
/-!
# The finite type with `n` elements
`Fin n` is the type whose elements are natural numbers smaller than `n`.
This file expands on the development in the core library.
## Main definitions
### Induction principles
* `finZeroElim` : Elimination principle for the empty set `Fin 0`, generalizes `Fin.elim0`.
Further definitions and eliminators can be found in `Init.Data.Fin.Lemmas`
### Embeddings and isomorphisms
* `Fin.valEmbedding` : coercion to natural numbers as an `Embedding`;
* `Fin.succEmb` : `Fin.succ` as an `Embedding`;
* `Fin.castLEEmb h` : `Fin.castLE` as an `Embedding`, embed `Fin n` into `Fin m`, `h : n ≤ m`;
* `finCongr` : `Fin.cast` as an `Equiv`, equivalence between `Fin n` and `Fin m` when `n = m`;
* `Fin.castAddEmb m` : `Fin.castAdd` as an `Embedding`, embed `Fin n` into `Fin (n+m)`;
* `Fin.castSuccEmb` : `Fin.castSucc` as an `Embedding`, embed `Fin n` into `Fin (n+1)`;
* `Fin.addNatEmb m i` : `Fin.addNat` as an `Embedding`, add `m` on `i` on the right,
generalizes `Fin.succ`;
* `Fin.natAddEmb n i` : `Fin.natAdd` as an `Embedding`, adds `n` on `i` on the left;
### Other casts
* `Fin.divNat i` : divides `i : Fin (m * n)` by `n`;
* `Fin.modNat i` : takes the mod of `i : Fin (m * n)` by `n`;
-/
assert_not_exists Monoid Finset
open Fin Nat Function
attribute [simp] Fin.succ_ne_zero Fin.castSucc_lt_last
/-- Elimination principle for the empty set `Fin 0`, dependent version. -/
def finZeroElim {α : Fin 0 → Sort*} (x : Fin 0) : α x :=
x.elim0
namespace Fin
@[simp] theorem mk_eq_one {n a : Nat} {ha : a < n + 2} :
(⟨a, ha⟩ : Fin (n + 2)) = 1 ↔ a = 1 :=
mk.inj_iff
@[simp] theorem one_eq_mk {n a : Nat} {ha : a < n + 2} :
1 = (⟨a, ha⟩ : Fin (n + 2)) ↔ a = 1 := by
simp [eq_comm]
instance {n : ℕ} : CanLift ℕ (Fin n) Fin.val (· < n) where
prf k hk := ⟨⟨k, hk⟩, rfl⟩
/-- A dependent variant of `Fin.elim0`. -/
def rec0 {α : Fin 0 → Sort*} (i : Fin 0) : α i := absurd i.2 (Nat.not_lt_zero _)
variable {n m : ℕ}
--variable {a b : Fin n} -- this *really* breaks stuff
theorem val_injective : Function.Injective (@Fin.val n) :=
@Fin.eq_of_val_eq n
/-- If you actually have an element of `Fin n`, then the `n` is always positive -/
lemma size_positive : Fin n → 0 < n := Fin.pos
lemma size_positive' [Nonempty (Fin n)] : 0 < n :=
‹Nonempty (Fin n)›.elim Fin.pos
protected theorem prop (a : Fin n) : a.val < n :=
a.2
lemma lt_last_iff_ne_last {a : Fin (n + 1)} : a < last n ↔ a ≠ last n := by
simp [Fin.lt_iff_le_and_ne, le_last]
lemma ne_zero_of_lt {a b : Fin (n + 1)} (hab : a < b) : b ≠ 0 :=
Fin.ne_of_gt <| Fin.lt_of_le_of_lt a.zero_le hab
lemma ne_last_of_lt {a b : Fin (n + 1)} (hab : a < b) : a ≠ last n :=
Fin.ne_of_lt <| Fin.lt_of_lt_of_le hab b.le_last
/-- Equivalence between `Fin n` and `{ i // i < n }`. -/
@[simps apply symm_apply]
def equivSubtype : Fin n ≃ { i // i < n } where
toFun a := ⟨a.1, a.2⟩
invFun a := ⟨a.1, a.2⟩
left_inv := fun ⟨_, _⟩ => rfl
right_inv := fun ⟨_, _⟩ => rfl
section coe
/-!
### coercions and constructions
-/
theorem val_eq_val (a b : Fin n) : (a : ℕ) = b ↔ a = b :=
Fin.ext_iff.symm
theorem ne_iff_vne (a b : Fin n) : a ≠ b ↔ a.1 ≠ b.1 :=
Fin.ext_iff.not
theorem mk_eq_mk {a h a' h'} : @mk n a h = @mk n a' h' ↔ a = a' :=
Fin.ext_iff
-- syntactic tautologies now
/-- Assume `k = l`. If two functions defined on `Fin k` and `Fin l` are equal on each element,
then they coincide (in the heq sense). -/
protected theorem heq_fun_iff {α : Sort*} {k l : ℕ} (h : k = l) {f : Fin k → α} {g : Fin l → α} :
HEq f g ↔ ∀ i : Fin k, f i = g ⟨(i : ℕ), h ▸ i.2⟩ := by
subst h
simp [funext_iff]
/-- Assume `k = l` and `k' = l'`.
If two functions `Fin k → Fin k' → α` and `Fin l → Fin l' → α` are equal on each pair,
then they coincide (in the heq sense). -/
protected theorem heq_fun₂_iff {α : Sort*} {k l k' l' : ℕ} (h : k = l) (h' : k' = l')
{f : Fin k → Fin k' → α} {g : Fin l → Fin l' → α} :
HEq f g ↔ ∀ (i : Fin k) (j : Fin k'), f i j = g ⟨(i : ℕ), h ▸ i.2⟩ ⟨(j : ℕ), h' ▸ j.2⟩ := by
subst h
subst h'
simp [funext_iff]
/-- Two elements of `Fin k` and `Fin l` are heq iff their values in `ℕ` coincide. This requires
`k = l`. For the left implication without this assumption, see `val_eq_val_of_heq`. -/
protected theorem heq_ext_iff {k l : ℕ} (h : k = l) {i : Fin k} {j : Fin l} :
HEq i j ↔ (i : ℕ) = (j : ℕ) := by
subst h
simp [val_eq_val]
end coe
section Order
/-!
### order
-/
theorem le_iff_val_le_val {a b : Fin n} : a ≤ b ↔ (a : ℕ) ≤ b :=
Iff.rfl
/-- `a < b` as natural numbers if and only if `a < b` in `Fin n`. -/
@[norm_cast, simp]
theorem val_fin_lt {n : ℕ} {a b : Fin n} : (a : ℕ) < (b : ℕ) ↔ a < b :=
Iff.rfl
/-- `a ≤ b` as natural numbers if and only if `a ≤ b` in `Fin n`. -/
@[norm_cast, simp]
theorem val_fin_le {n : ℕ} {a b : Fin n} : (a : ℕ) ≤ (b : ℕ) ↔ a ≤ b :=
Iff.rfl
theorem min_val {a : Fin n} : min (a : ℕ) n = a := by simp
theorem max_val {a : Fin n} : max (a : ℕ) n = n := by simp
/-- The inclusion map `Fin n → ℕ` is an embedding. -/
@[simps -fullyApplied apply]
def valEmbedding : Fin n ↪ ℕ :=
⟨val, val_injective⟩
@[simp]
theorem equivSubtype_symm_trans_valEmbedding :
equivSubtype.symm.toEmbedding.trans valEmbedding = Embedding.subtype (· < n) :=
rfl
/-- Use the ordering on `Fin n` for checking recursive definitions.
For example, the following definition is not accepted by the termination checker,
unless we declare the `WellFoundedRelation` instance:
```lean
def factorial {n : ℕ} : Fin n → ℕ
| ⟨0, _⟩ := 1
| ⟨i + 1, hi⟩ := (i + 1) * factorial ⟨i, i.lt_succ_self.trans hi⟩
```
-/
instance {n : ℕ} : WellFoundedRelation (Fin n) :=
measure (val : Fin n → ℕ)
@[deprecated (since := "2025-02-24")]
alias val_zero' := val_zero
/-- `Fin.mk_zero` in `Lean` only applies in `Fin (n + 1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem mk_zero' (n : ℕ) [NeZero n] : (⟨0, pos_of_neZero n⟩ : Fin n) = 0 := rfl
/--
The `Fin.zero_le` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
protected theorem zero_le' [NeZero n] (a : Fin n) : 0 ≤ a :=
Nat.zero_le a.val
@[simp, norm_cast]
theorem val_eq_zero_iff [NeZero n] {a : Fin n} : a.val = 0 ↔ a = 0 := by
rw [Fin.ext_iff, val_zero]
theorem val_ne_zero_iff [NeZero n] {a : Fin n} : a.val ≠ 0 ↔ a ≠ 0 :=
val_eq_zero_iff.not
@[simp, norm_cast]
theorem val_pos_iff [NeZero n] {a : Fin n} : 0 < a.val ↔ 0 < a := by
rw [← val_fin_lt, val_zero]
/--
The `Fin.pos_iff_ne_zero` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
theorem pos_iff_ne_zero' [NeZero n] (a : Fin n) : 0 < a ↔ a ≠ 0 := by
rw [← val_pos_iff, Nat.pos_iff_ne_zero, val_ne_zero_iff]
@[simp] lemma cast_eq_self (a : Fin n) : a.cast rfl = a := rfl
@[simp] theorem cast_eq_zero {k l : ℕ} [NeZero k] [NeZero l]
(h : k = l) (x : Fin k) : Fin.cast h x = 0 ↔ x = 0 := by
simp [← val_eq_zero_iff]
lemma cast_injective {k l : ℕ} (h : k = l) : Injective (Fin.cast h) :=
fun a b hab ↦ by simpa [← val_eq_val] using hab
theorem last_pos' [NeZero n] : 0 < last n := n.pos_of_neZero
theorem one_lt_last [NeZero n] : 1 < last (n + 1) := by
rw [lt_iff_val_lt_val, val_one, val_last, Nat.lt_add_left_iff_pos, Nat.pos_iff_ne_zero]
exact NeZero.ne n
end Order
/-! ### Coercions to `ℤ` and the `fin_omega` tactic. -/
open Int
theorem coe_int_sub_eq_ite {n : Nat} (u v : Fin n) :
((u - v : Fin n) : Int) = if v ≤ u then (u - v : Int) else (u - v : Int) + n := by
rw [Fin.sub_def]
split
· rw [natCast_emod, Int.emod_eq_sub_self_emod, Int.emod_eq_of_lt] <;> omega
· rw [natCast_emod, Int.emod_eq_of_lt] <;> omega
theorem coe_int_sub_eq_mod {n : Nat} (u v : Fin n) :
((u - v : Fin n) : Int) = ((u : Int) - (v : Int)) % n := by
rw [coe_int_sub_eq_ite]
split
· rw [Int.emod_eq_of_lt] <;> omega
· rw [Int.emod_eq_add_self_emod, Int.emod_eq_of_lt] <;> omega
theorem coe_int_add_eq_ite {n : Nat} (u v : Fin n) :
((u + v : Fin n) : Int) = if (u + v : ℕ) < n then (u + v : Int) else (u + v : Int) - n := by
rw [Fin.add_def]
split
· rw [natCast_emod, Int.emod_eq_of_lt] <;> omega
· rw [natCast_emod, Int.emod_eq_sub_self_emod, Int.emod_eq_of_lt] <;> omega
theorem coe_int_add_eq_mod {n : Nat} (u v : Fin n) :
((u + v : Fin n) : Int) = ((u : Int) + (v : Int)) % n := by
rw [coe_int_add_eq_ite]
split
· rw [Int.emod_eq_of_lt] <;> omega
· rw [Int.emod_eq_sub_self_emod, Int.emod_eq_of_lt] <;> omega
-- Write `a + b` as `if (a + b : ℕ) < n then (a + b : ℤ) else (a + b : ℤ) - n` and
-- similarly `a - b` as `if (b : ℕ) ≤ a then (a - b : ℤ) else (a - b : ℤ) + n`.
attribute [fin_omega] coe_int_sub_eq_ite coe_int_add_eq_ite
-- Rewrite inequalities in `Fin` to inequalities in `ℕ`
attribute [fin_omega] Fin.lt_iff_val_lt_val Fin.le_iff_val_le_val
-- Rewrite `1 : Fin (n + 2)` to `1 : ℤ`
attribute [fin_omega] val_one
/--
Preprocessor for `omega` to handle inequalities in `Fin`.
Note that this involves a lot of case splitting, so may be slow.
-/
-- Further adjustment to the simp set can probably make this more powerful.
-- Please experiment and PR updates!
macro "fin_omega" : tactic => `(tactic|
{ try simp only [fin_omega, ← Int.ofNat_lt, ← Int.ofNat_le] at *
omega })
section Add
/-!
### addition, numerals, and coercion from Nat
-/
@[simp]
theorem val_one' (n : ℕ) [NeZero n] : ((1 : Fin n) : ℕ) = 1 % n :=
rfl
@[deprecated val_one' (since := "2025-03-10")]
theorem val_one'' {n : ℕ} : ((1 : Fin (n + 1)) : ℕ) = 1 % (n + 1) :=
rfl
instance nontrivial {n : ℕ} : Nontrivial (Fin (n + 2)) where
exists_pair_ne := ⟨0, 1, (ne_iff_vne 0 1).mpr (by simp [val_one, val_zero])⟩
theorem nontrivial_iff_two_le : Nontrivial (Fin n) ↔ 2 ≤ n := by
rcases n with (_ | _ | n) <;>
simp [Fin.nontrivial, not_nontrivial, Nat.succ_le_iff]
section Monoid
instance inhabitedFinOneAdd (n : ℕ) : Inhabited (Fin (1 + n)) :=
haveI : NeZero (1 + n) := by rw [Nat.add_comm]; infer_instance
inferInstance
@[simp]
theorem default_eq_zero (n : ℕ) [NeZero n] : (default : Fin n) = 0 :=
rfl
instance instNatCast [NeZero n] : NatCast (Fin n) where
natCast i := Fin.ofNat' n i
lemma natCast_def [NeZero n] (a : ℕ) : (a : Fin n) = ⟨a % n, mod_lt _ n.pos_of_neZero⟩ := rfl
end Monoid
theorem val_add_eq_ite {n : ℕ} (a b : Fin n) :
(↑(a + b) : ℕ) = if n ≤ a + b then a + b - n else a + b := by
rw [Fin.val_add, Nat.add_mod_eq_ite, Nat.mod_eq_of_lt (show ↑a < n from a.2),
Nat.mod_eq_of_lt (show ↑b < n from b.2)]
theorem val_add_eq_of_add_lt {n : ℕ} {a b : Fin n} (huv : a.val + b.val < n) :
(a + b).val = a.val + b.val := by
rw [val_add]
simp [Nat.mod_eq_of_lt huv]
lemma intCast_val_sub_eq_sub_add_ite {n : ℕ} (a b : Fin n) :
((a - b).val : ℤ) = a.val - b.val + if b ≤ a then 0 else n := by
split <;> fin_omega
lemma one_le_of_ne_zero {n : ℕ} [NeZero n] {k : Fin n} (hk : k ≠ 0) : 1 ≤ k := by
obtain ⟨n, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (NeZero.ne n)
cases n with
| zero => simp only [Nat.reduceAdd, Fin.isValue, Fin.zero_le]
| succ n => rwa [Fin.le_iff_val_le_val, Fin.val_one, Nat.one_le_iff_ne_zero, val_ne_zero_iff]
lemma val_sub_one_of_ne_zero [NeZero n] {i : Fin n} (hi : i ≠ 0) : (i - 1).val = i - 1 := by
obtain ⟨n, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (NeZero.ne n)
rw [Fin.sub_val_of_le (one_le_of_ne_zero hi), Fin.val_one', Nat.mod_eq_of_lt
(Nat.succ_le_iff.mpr (nontrivial_iff_two_le.mp <| nontrivial_of_ne i 0 hi))]
section OfNatCoe
@[simp]
theorem ofNat'_eq_cast (n : ℕ) [NeZero n] (a : ℕ) : Fin.ofNat' n a = a :=
rfl
@[simp] lemma val_natCast (a n : ℕ) [NeZero n] : (a : Fin n).val = a % n := rfl
/-- Converting an in-range number to `Fin (n + 1)` produces a result
whose value is the original number. -/
theorem val_cast_of_lt {n : ℕ} [NeZero n] {a : ℕ} (h : a < n) : (a : Fin n).val = a :=
Nat.mod_eq_of_lt h
/-- If `n` is non-zero, converting the value of a `Fin n` to `Fin n` results
in the same value. -/
@[simp, norm_cast] theorem cast_val_eq_self {n : ℕ} [NeZero n] (a : Fin n) : (a.val : Fin n) = a :=
Fin.ext <| val_cast_of_lt a.isLt
-- This is a special case of `CharP.cast_eq_zero` that doesn't require typeclass search
@[simp high] lemma natCast_self (n : ℕ) [NeZero n] : (n : Fin n) = 0 := by ext; simp
@[simp] lemma natCast_eq_zero {a n : ℕ} [NeZero n] : (a : Fin n) = 0 ↔ n ∣ a := by
simp [Fin.ext_iff, Nat.dvd_iff_mod_eq_zero]
@[simp]
theorem natCast_eq_last (n) : (n : Fin (n + 1)) = Fin.last n := by ext; simp
theorem le_val_last (i : Fin (n + 1)) : i ≤ n := by
rw [Fin.natCast_eq_last]
exact Fin.le_last i
variable {a b : ℕ}
lemma natCast_le_natCast (han : a ≤ n) (hbn : b ≤ n) : (a : Fin (n + 1)) ≤ b ↔ a ≤ b := by
rw [← Nat.lt_succ_iff] at han hbn
simp [le_iff_val_le_val, -val_fin_le, Nat.mod_eq_of_lt, han, hbn]
lemma natCast_lt_natCast (han : a ≤ n) (hbn : b ≤ n) : (a : Fin (n + 1)) < b ↔ a < b := by
rw [← Nat.lt_succ_iff] at han hbn; simp [lt_iff_val_lt_val, Nat.mod_eq_of_lt, han, hbn]
lemma natCast_mono (hbn : b ≤ n) (hab : a ≤ b) : (a : Fin (n + 1)) ≤ b :=
(natCast_le_natCast (hab.trans hbn) hbn).2 hab
lemma natCast_strictMono (hbn : b ≤ n) (hab : a < b) : (a : Fin (n + 1)) < b :=
(natCast_lt_natCast (hab.le.trans hbn) hbn).2 hab
end OfNatCoe
end Add
section Succ
/-!
### succ and casts into larger Fin types
-/
lemma succ_injective (n : ℕ) : Injective (@Fin.succ n) := fun a b ↦ by simp [Fin.ext_iff]
/-- `Fin.succ` as an `Embedding` -/
def succEmb (n : ℕ) : Fin n ↪ Fin (n + 1) where
toFun := succ
inj' := succ_injective _
@[simp]
theorem coe_succEmb : ⇑(succEmb n) = Fin.succ :=
rfl
@[deprecated (since := "2025-04-12")]
alias val_succEmb := coe_succEmb
@[simp]
theorem exists_succ_eq {x : Fin (n + 1)} : (∃ y, Fin.succ y = x) ↔ x ≠ 0 :=
⟨fun ⟨_, hy⟩ => hy ▸ succ_ne_zero _, x.cases (fun h => h.irrefl.elim) (fun _ _ => ⟨_, rfl⟩)⟩
theorem exists_succ_eq_of_ne_zero {x : Fin (n + 1)} (h : x ≠ 0) :
∃ y, Fin.succ y = x := exists_succ_eq.mpr h
@[simp]
theorem succ_zero_eq_one' [NeZero n] : Fin.succ (0 : Fin n) = 1 := by
cases n
· exact (NeZero.ne 0 rfl).elim
· rfl
theorem one_pos' [NeZero n] : (0 : Fin (n + 1)) < 1 := succ_zero_eq_one' (n := n) ▸ succ_pos _
theorem zero_ne_one' [NeZero n] : (0 : Fin (n + 1)) ≠ 1 := Fin.ne_of_lt one_pos'
/--
The `Fin.succ_one_eq_two` in `Lean` only applies in `Fin (n+2)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem succ_one_eq_two' [NeZero n] : Fin.succ (1 : Fin (n + 1)) = 2 := by
cases n
· exact (NeZero.ne 0 rfl).elim
· rfl
-- Version of `succ_one_eq_two` to be used by `dsimp`.
-- Note the `'` swapped around due to a move to std4.
/--
The `Fin.le_zero_iff` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem le_zero_iff' {n : ℕ} [NeZero n] {k : Fin n} : k ≤ 0 ↔ k = 0 :=
⟨fun h => Fin.ext <| by rw [Nat.eq_zero_of_le_zero h]; rfl, by rintro rfl; exact Nat.le_refl _⟩
-- TODO: Move to Batteries
@[simp] lemma castLE_inj {hmn : m ≤ n} {a b : Fin m} : castLE hmn a = castLE hmn b ↔ a = b := by
simp [Fin.ext_iff]
@[simp] lemma castAdd_inj {a b : Fin m} : castAdd n a = castAdd n b ↔ a = b := by simp [Fin.ext_iff]
attribute [simp] castSucc_inj
lemma castLE_injective (hmn : m ≤ n) : Injective (castLE hmn) :=
fun _ _ hab ↦ Fin.ext (congr_arg val hab :)
lemma castAdd_injective (m n : ℕ) : Injective (@Fin.castAdd m n) := castLE_injective _
lemma castSucc_injective (n : ℕ) : Injective (@Fin.castSucc n) := castAdd_injective _ _
/-- `Fin.castLE` as an `Embedding`, `castLEEmb h i` embeds `i` into a larger `Fin` type. -/
@[simps apply]
def castLEEmb (h : n ≤ m) : Fin n ↪ Fin m where
toFun := castLE h
inj' := castLE_injective _
@[simp, norm_cast] lemma coe_castLEEmb {m n} (hmn : m ≤ n) : castLEEmb hmn = castLE hmn := rfl
/- The next proof can be golfed a lot using `Fintype.card`.
It is written this way to define `ENat.card` and `Nat.card` without a `Fintype` dependency
(not done yet). -/
lemma nonempty_embedding_iff : Nonempty (Fin n ↪ Fin m) ↔ n ≤ m := by
refine ⟨fun h ↦ ?_, fun h ↦ ⟨castLEEmb h⟩⟩
induction n generalizing m with
| zero => exact m.zero_le
| succ n ihn =>
obtain ⟨e⟩ := h
rcases exists_eq_succ_of_ne_zero (pos_iff_nonempty.2 (Nonempty.map e inferInstance)).ne'
with ⟨m, rfl⟩
refine Nat.succ_le_succ <| ihn ⟨?_⟩
refine ⟨fun i ↦ (e.setValue 0 0 i.succ).pred (mt e.setValue_eq_iff.1 i.succ_ne_zero),
fun i j h ↦ ?_⟩
simpa only [pred_inj, EmbeddingLike.apply_eq_iff_eq, succ_inj] using h
lemma equiv_iff_eq : Nonempty (Fin m ≃ Fin n) ↔ m = n :=
⟨fun ⟨e⟩ ↦ le_antisymm (nonempty_embedding_iff.1 ⟨e⟩) (nonempty_embedding_iff.1 ⟨e.symm⟩),
fun h ↦ h ▸ ⟨.refl _⟩⟩
@[simp] lemma castLE_castSucc {n m} (i : Fin n) (h : n + 1 ≤ m) :
i.castSucc.castLE h = i.castLE (Nat.le_of_succ_le h) :=
rfl
@[simp] lemma castLE_comp_castSucc {n m} (h : n + 1 ≤ m) :
Fin.castLE h ∘ Fin.castSucc = Fin.castLE (Nat.le_of_succ_le h) :=
rfl
@[simp] lemma castLE_rfl (n : ℕ) : Fin.castLE (le_refl n) = id :=
rfl
@[simp]
theorem range_castLE {n k : ℕ} (h : n ≤ k) : Set.range (castLE h) = { i : Fin k | (i : ℕ) < n } :=
Set.ext fun x => ⟨fun ⟨y, hy⟩ => hy ▸ y.2, fun hx => ⟨⟨x, hx⟩, rfl⟩⟩
@[simp]
theorem coe_of_injective_castLE_symm {n k : ℕ} (h : n ≤ k) (i : Fin k) (hi) :
((Equiv.ofInjective _ (castLE_injective h)).symm ⟨i, hi⟩ : ℕ) = i := by
rw [← coe_castLE h]
exact congr_arg Fin.val (Equiv.apply_ofInjective_symm _ _)
theorem leftInverse_cast (eq : n = m) : LeftInverse (Fin.cast eq.symm) (Fin.cast eq) :=
fun _ => rfl
theorem rightInverse_cast (eq : n = m) : RightInverse (Fin.cast eq.symm) (Fin.cast eq) :=
fun _ => rfl
@[simp]
theorem cast_inj (eq : n = m) {a b : Fin n} : a.cast eq = b.cast eq ↔ a = b := by
simp [← val_inj]
@[simp]
theorem cast_lt_cast (eq : n = m) {a b : Fin n} : a.cast eq < b.cast eq ↔ a < b :=
Iff.rfl
@[simp]
theorem cast_le_cast (eq : n = m) {a b : Fin n} : a.cast eq ≤ b.cast eq ↔ a ≤ b :=
Iff.rfl
/-- The 'identity' equivalence between `Fin m` and `Fin n` when `m = n`. -/
@[simps]
def _root_.finCongr (eq : n = m) : Fin n ≃ Fin m where
toFun := Fin.cast eq
invFun := Fin.cast eq.symm
left_inv := leftInverse_cast eq
right_inv := rightInverse_cast eq
@[simp] lemma _root_.finCongr_apply_mk (h : m = n) (k : ℕ) (hk : k < m) :
finCongr h ⟨k, hk⟩ = ⟨k, h ▸ hk⟩ := rfl
@[simp]
lemma _root_.finCongr_refl (h : n = n := rfl) : finCongr h = Equiv.refl (Fin n) := by ext; simp
@[simp] lemma _root_.finCongr_symm (h : m = n) : (finCongr h).symm = finCongr h.symm := rfl
@[simp] lemma _root_.finCongr_apply_coe (h : m = n) (k : Fin m) : (finCongr h k : ℕ) = k := rfl
lemma _root_.finCongr_symm_apply_coe (h : m = n) (k : Fin n) : ((finCongr h).symm k : ℕ) = k := rfl
/-- While in many cases `finCongr` is better than `Equiv.cast`/`cast`, sometimes we want to apply
a generic theorem about `cast`. -/
lemma _root_.finCongr_eq_equivCast (h : n = m) : finCongr h = .cast (h ▸ rfl) := by subst h; simp
/-- While in many cases `Fin.cast` is better than `Equiv.cast`/`cast`, sometimes we want to apply
a generic theorem about `cast`. -/
theorem cast_eq_cast (h : n = m) : (Fin.cast h : Fin n → Fin m) = _root_.cast (h ▸ rfl) := by
subst h
ext
rfl
/-- `Fin.castAdd` as an `Embedding`, `castAddEmb m i` embeds `i : Fin n` in `Fin (n+m)`.
See also `Fin.natAddEmb` and `Fin.addNatEmb`. -/
def castAddEmb (m) : Fin n ↪ Fin (n + m) := castLEEmb (le_add_right n m)
@[simp]
lemma coe_castAddEmb (m) : (castAddEmb m : Fin n → Fin (n + m)) = castAdd m := rfl
lemma castAddEmb_apply (m) (i : Fin n) : castAddEmb m i = castAdd m i := rfl
/-- `Fin.castSucc` as an `Embedding`, `castSuccEmb i` embeds `i : Fin n` in `Fin (n+1)`. -/
def castSuccEmb : Fin n ↪ Fin (n + 1) := castAddEmb _
@[simp, norm_cast] lemma coe_castSuccEmb : (castSuccEmb : Fin n → Fin (n + 1)) = Fin.castSucc := rfl
lemma castSuccEmb_apply (i : Fin n) : castSuccEmb i = i.castSucc := rfl
theorem castSucc_le_succ {n} (i : Fin n) : i.castSucc ≤ i.succ := Nat.le_succ i
@[simp] theorem castSucc_le_castSucc_iff {a b : Fin n} : castSucc a ≤ castSucc b ↔ a ≤ b := .rfl
@[simp] theorem succ_le_castSucc_iff {a b : Fin n} : succ a ≤ castSucc b ↔ a < b := by
rw [le_castSucc_iff, succ_lt_succ_iff]
@[simp] theorem castSucc_lt_succ_iff {a b : Fin n} : castSucc a < succ b ↔ a ≤ b := by
rw [castSucc_lt_iff_succ_le, succ_le_succ_iff]
theorem le_of_castSucc_lt_of_succ_lt {a b : Fin (n + 1)} {i : Fin n}
(hl : castSucc i < a) (hu : b < succ i) : b < a := by
simp [Fin.lt_def, -val_fin_lt] at *; omega
theorem castSucc_lt_or_lt_succ (p : Fin (n + 1)) (i : Fin n) : castSucc i < p ∨ p < i.succ := by
simp [Fin.lt_def, -val_fin_lt]; omega
theorem succ_le_or_le_castSucc (p : Fin (n + 1)) (i : Fin n) : succ i ≤ p ∨ p ≤ i.castSucc := by
rw [le_castSucc_iff, ← castSucc_lt_iff_succ_le]
exact p.castSucc_lt_or_lt_succ i
theorem eq_castSucc_of_ne_last {x : Fin (n + 1)} (h : x ≠ (last _)) :
∃ y, Fin.castSucc y = x := exists_castSucc_eq.mpr h
@[deprecated (since := "2025-02-06")]
alias exists_castSucc_eq_of_ne_last := eq_castSucc_of_ne_last
theorem forall_fin_succ' {P : Fin (n + 1) → Prop} :
(∀ i, P i) ↔ (∀ i : Fin n, P i.castSucc) ∧ P (.last _) :=
⟨fun H => ⟨fun _ => H _, H _⟩, fun ⟨H0, H1⟩ i => Fin.lastCases H1 H0 i⟩
-- to match `Fin.eq_zero_or_eq_succ`
theorem eq_castSucc_or_eq_last {n : Nat} (i : Fin (n + 1)) :
(∃ j : Fin n, i = j.castSucc) ∨ i = last n := i.lastCases (Or.inr rfl) (Or.inl ⟨·, rfl⟩)
@[simp]
theorem castSucc_ne_last {n : ℕ} (i : Fin n) : i.castSucc ≠ .last n :=
Fin.ne_of_lt i.castSucc_lt_last
theorem exists_fin_succ' {P : Fin (n + 1) → Prop} :
(∃ i, P i) ↔ (∃ i : Fin n, P i.castSucc) ∨ P (.last _) :=
⟨fun ⟨i, h⟩ => Fin.lastCases Or.inr (fun i hi => Or.inl ⟨i, hi⟩) i h,
fun h => h.elim (fun ⟨i, hi⟩ => ⟨i.castSucc, hi⟩) (fun h => ⟨.last _, h⟩)⟩
/--
The `Fin.castSucc_zero` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem castSucc_zero' [NeZero n] : castSucc (0 : Fin n) = 0 := rfl
@[simp]
theorem castSucc_pos_iff [NeZero n] {i : Fin n} : 0 < castSucc i ↔ 0 < i := by simp [← val_pos_iff]
/-- `castSucc i` is positive when `i` is positive.
The `Fin.castSucc_pos` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis. -/
alias ⟨_, castSucc_pos'⟩ := castSucc_pos_iff
/--
The `Fin.castSucc_eq_zero_iff` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem castSucc_eq_zero_iff' [NeZero n] (a : Fin n) : castSucc a = 0 ↔ a = 0 :=
Fin.ext_iff.trans <| (Fin.ext_iff.trans <| by simp).symm
/--
The `Fin.castSucc_ne_zero_iff` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
theorem castSucc_ne_zero_iff' [NeZero n] (a : Fin n) : castSucc a ≠ 0 ↔ a ≠ 0 :=
not_iff_not.mpr <| castSucc_eq_zero_iff' a
theorem castSucc_ne_zero_of_lt {p i : Fin n} (h : p < i) : castSucc i ≠ 0 := by
cases n
· exact i.elim0
· rw [castSucc_ne_zero_iff', Ne, Fin.ext_iff]
exact ((zero_le _).trans_lt h).ne'
theorem succ_ne_last_iff (a : Fin (n + 1)) : succ a ≠ last (n + 1) ↔ a ≠ last n :=
not_iff_not.mpr <| succ_eq_last_succ
theorem succ_ne_last_of_lt {p i : Fin n} (h : i < p) : succ i ≠ last n := by
cases n
· exact i.elim0
· rw [succ_ne_last_iff, Ne, Fin.ext_iff]
exact ((le_last _).trans_lt' h).ne
@[norm_cast, simp]
theorem coe_eq_castSucc {a : Fin n} : (a : Fin (n + 1)) = castSucc a := by
ext
exact val_cast_of_lt (Nat.lt.step a.is_lt)
theorem coe_succ_lt_iff_lt {n : ℕ} {j k : Fin n} : (j : Fin <| n + 1) < k ↔ j < k := by
simp only [coe_eq_castSucc, castSucc_lt_castSucc_iff]
@[simp]
theorem range_castSucc {n : ℕ} : Set.range (castSucc : Fin n → Fin n.succ) =
({ i | (i : ℕ) < n } : Set (Fin n.succ)) := range_castLE (by omega)
@[simp]
theorem coe_of_injective_castSucc_symm {n : ℕ} (i : Fin n.succ) (hi) :
((Equiv.ofInjective castSucc (castSucc_injective _)).symm ⟨i, hi⟩ : ℕ) = i := by
rw [← coe_castSucc]
exact congr_arg val (Equiv.apply_ofInjective_symm _ _)
/-- `Fin.addNat` as an `Embedding`, `addNatEmb m i` adds `m` to `i`, generalizes `Fin.succ`. -/
@[simps! apply]
def addNatEmb (m) : Fin n ↪ Fin (n + m) where
toFun := (addNat · m)
inj' a b := by simp [Fin.ext_iff]
/-- `Fin.natAdd` as an `Embedding`, `natAddEmb n i` adds `n` to `i` "on the left". -/
@[simps! apply]
def natAddEmb (n) {m} : Fin m ↪ Fin (n + m) where
toFun := natAdd n
inj' a b := by simp [Fin.ext_iff]
theorem castSucc_castAdd (i : Fin n) : castSucc (castAdd m i) = castAdd (m + 1) i := rfl
theorem castSucc_natAdd (i : Fin m) : castSucc (natAdd n i) = natAdd n (castSucc i) := rfl
theorem succ_castAdd (i : Fin n) : succ (castAdd m i) =
if h : i.succ = last _ then natAdd n (0 : Fin (m + 1))
else castAdd (m + 1) ⟨i.1 + 1, lt_of_le_of_ne i.2 (Fin.val_ne_iff.mpr h)⟩ := by
split_ifs with h
exacts [Fin.ext (congr_arg Fin.val h :), rfl]
theorem succ_natAdd (i : Fin m) : succ (natAdd n i) = natAdd n (succ i) := rfl
end Succ
section Pred
/-!
### pred
-/
theorem pred_one' [NeZero n] (h := (zero_ne_one' (n := n)).symm) :
Fin.pred (1 : Fin (n + 1)) h = 0 := by
simp_rw [Fin.ext_iff, coe_pred, val_one', val_zero, Nat.sub_eq_zero_iff_le, Nat.mod_le]
theorem pred_last (h := Fin.ext_iff.not.2 last_pos'.ne') :
pred (last (n + 1)) h = last n := by simp_rw [← succ_last, pred_succ]
theorem pred_lt_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : pred i hi < j ↔ i < succ j := by
rw [← succ_lt_succ_iff, succ_pred]
theorem lt_pred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : j < pred i hi ↔ succ j < i := by
rw [← succ_lt_succ_iff, succ_pred]
theorem pred_le_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : pred i hi ≤ j ↔ i ≤ succ j := by
rw [← succ_le_succ_iff, succ_pred]
theorem le_pred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : j ≤ pred i hi ↔ succ j ≤ i := by
rw [← succ_le_succ_iff, succ_pred]
theorem castSucc_pred_eq_pred_castSucc {a : Fin (n + 1)} (ha : a ≠ 0)
(ha' := castSucc_ne_zero_iff.mpr ha) :
(a.pred ha).castSucc = (castSucc a).pred ha' := rfl
theorem castSucc_pred_add_one_eq {a : Fin (n + 1)} (ha : a ≠ 0) :
(a.pred ha).castSucc + 1 = a := by
cases a using cases
· exact (ha rfl).elim
· rw [pred_succ, coeSucc_eq_succ]
theorem le_pred_castSucc_iff {a b : Fin (n + 1)} (ha : castSucc a ≠ 0) :
b ≤ (castSucc a).pred ha ↔ b < a := by
rw [le_pred_iff, succ_le_castSucc_iff]
theorem pred_castSucc_lt_iff {a b : Fin (n + 1)} (ha : castSucc a ≠ 0) :
(castSucc a).pred ha < b ↔ a ≤ b := by
rw [pred_lt_iff, castSucc_lt_succ_iff]
theorem pred_castSucc_lt {a : Fin (n + 1)} (ha : castSucc a ≠ 0) :
(castSucc a).pred ha < a := by rw [pred_castSucc_lt_iff, le_def]
theorem le_castSucc_pred_iff {a b : Fin (n + 1)} (ha : a ≠ 0) :
b ≤ castSucc (a.pred ha) ↔ b < a := by
rw [castSucc_pred_eq_pred_castSucc, le_pred_castSucc_iff]
theorem castSucc_pred_lt_iff {a b : Fin (n + 1)} (ha : a ≠ 0) :
castSucc (a.pred ha) < b ↔ a ≤ b := by
rw [castSucc_pred_eq_pred_castSucc, pred_castSucc_lt_iff]
theorem castSucc_pred_lt {a : Fin (n + 1)} (ha : a ≠ 0) :
castSucc (a.pred ha) < a := by rw [castSucc_pred_lt_iff, le_def]
end Pred
section CastPred
/-- `castPred i` sends `i : Fin (n + 1)` to `Fin n` as long as i ≠ last n. -/
@[inline] def castPred (i : Fin (n + 1)) (h : i ≠ last n) : Fin n := castLT i (val_lt_last h)
@[simp]
lemma castLT_eq_castPred (i : Fin (n + 1)) (h : i < last _) (h' := Fin.ext_iff.not.2 h.ne) :
castLT i h = castPred i h' := rfl
@[simp]
lemma coe_castPred (i : Fin (n + 1)) (h : i ≠ last _) : (castPred i h : ℕ) = i := rfl
@[simp]
theorem castPred_castSucc {i : Fin n} (h' := Fin.ext_iff.not.2 (castSucc_lt_last i).ne) :
castPred (castSucc i) h' = i := rfl
@[simp]
theorem castSucc_castPred (i : Fin (n + 1)) (h : i ≠ last n) :
castSucc (i.castPred h) = i := by
rcases exists_castSucc_eq.mpr h with ⟨y, rfl⟩
rw [castPred_castSucc]
theorem castPred_eq_iff_eq_castSucc (i : Fin (n + 1)) (hi : i ≠ last _) (j : Fin n) :
castPred i hi = j ↔ i = castSucc j :=
⟨fun h => by rw [← h, castSucc_castPred], fun h => by simp_rw [h, castPred_castSucc]⟩
@[simp]
theorem castPred_mk (i : ℕ) (h₁ : i < n) (h₂ := h₁.trans (Nat.lt_succ_self _))
(h₃ : ⟨i, h₂⟩ ≠ last _ := (ne_iff_vne _ _).mpr (val_last _ ▸ h₁.ne)) :
castPred ⟨i, h₂⟩ h₃ = ⟨i, h₁⟩ := rfl
@[simp]
theorem castPred_le_castPred_iff {i j : Fin (n + 1)} {hi : i ≠ last n} {hj : j ≠ last n} :
castPred i hi ≤ castPred j hj ↔ i ≤ j := Iff.rfl
/-- A version of the right-to-left implication of `castPred_le_castPred_iff`
that deduces `i ≠ last n` from `i ≤ j` and `j ≠ last n`. -/
@[gcongr]
theorem castPred_le_castPred {i j : Fin (n + 1)} (h : i ≤ j) (hj : j ≠ last n) :
castPred i (by rw [← lt_last_iff_ne_last] at hj ⊢; exact Fin.lt_of_le_of_lt h hj) ≤
castPred j hj :=
h
@[simp]
theorem castPred_lt_castPred_iff {i j : Fin (n + 1)} {hi : i ≠ last n} {hj : j ≠ last n} :
castPred i hi < castPred j hj ↔ i < j := Iff.rfl
/-- A version of the right-to-left implication of `castPred_lt_castPred_iff`
that deduces `i ≠ last n` from `i < j`. -/
@[gcongr]
theorem castPred_lt_castPred {i j : Fin (n + 1)} (h : i < j) (hj : j ≠ last n) :
castPred i (ne_last_of_lt h) < castPred j hj := h
theorem castPred_lt_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) :
castPred i hi < j ↔ i < castSucc j := by
rw [← castSucc_lt_castSucc_iff, castSucc_castPred]
theorem lt_castPred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) :
j < castPred i hi ↔ castSucc j < i := by
rw [← castSucc_lt_castSucc_iff, castSucc_castPred]
theorem castPred_le_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) :
castPred i hi ≤ j ↔ i ≤ castSucc j := by
rw [← castSucc_le_castSucc_iff, castSucc_castPred]
theorem le_castPred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) :
j ≤ castPred i hi ↔ castSucc j ≤ i := by
rw [← castSucc_le_castSucc_iff, castSucc_castPred]
@[simp]
theorem castPred_inj {i j : Fin (n + 1)} {hi : i ≠ last n} {hj : j ≠ last n} :
castPred i hi = castPred j hj ↔ i = j := by
simp_rw [Fin.ext_iff, le_antisymm_iff, ← le_def, castPred_le_castPred_iff]
theorem castPred_zero' [NeZero n] (h := Fin.ext_iff.not.2 last_pos'.ne) :
castPred (0 : Fin (n + 1)) h = 0 := rfl
theorem castPred_zero (h := Fin.ext_iff.not.2 last_pos.ne) :
castPred (0 : Fin (n + 2)) h = 0 := rfl
@[simp]
theorem castPred_eq_zero [NeZero n] {i : Fin (n + 1)} (h : i ≠ last n) :
Fin.castPred i h = 0 ↔ i = 0 := by
rw [← castPred_zero', castPred_inj]
@[simp]
theorem castPred_one [NeZero n] (h := Fin.ext_iff.not.2 one_lt_last.ne) :
castPred (1 : Fin (n + 2)) h = 1 := by
cases n
· exact subsingleton_one.elim _ 1
· rfl
theorem succ_castPred_eq_castPred_succ {a : Fin (n + 1)} (ha : a ≠ last n)
(ha' := a.succ_ne_last_iff.mpr ha) :
(a.castPred ha).succ = (succ a).castPred ha' := rfl
theorem succ_castPred_eq_add_one {a : Fin (n + 1)} (ha : a ≠ last n) :
(a.castPred ha).succ = a + 1 := by
cases a using lastCases
· exact (ha rfl).elim
· rw [castPred_castSucc, coeSucc_eq_succ]
theorem castpred_succ_le_iff {a b : Fin (n + 1)} (ha : succ a ≠ last (n + 1)) :
(succ a).castPred ha ≤ b ↔ a < b := by
rw [castPred_le_iff, succ_le_castSucc_iff]
theorem lt_castPred_succ_iff {a b : Fin (n + 1)} (ha : succ a ≠ last (n + 1)) :
b < (succ a).castPred ha ↔ b ≤ a := by
rw [lt_castPred_iff, castSucc_lt_succ_iff]
theorem lt_castPred_succ {a : Fin (n + 1)} (ha : succ a ≠ last (n + 1)) :
a < (succ a).castPred ha := by rw [lt_castPred_succ_iff, le_def]
theorem succ_castPred_le_iff {a b : Fin (n + 1)} (ha : a ≠ last n) :
succ (a.castPred ha) ≤ b ↔ a < b := by
rw [succ_castPred_eq_castPred_succ ha, castpred_succ_le_iff]
theorem lt_succ_castPred_iff {a b : Fin (n + 1)} (ha : a ≠ last n) :
b < succ (a.castPred ha) ↔ b ≤ a := by
rw [succ_castPred_eq_castPred_succ ha, lt_castPred_succ_iff]
theorem lt_succ_castPred {a : Fin (n + 1)} (ha : a ≠ last n) :
a < succ (a.castPred ha) := by rw [lt_succ_castPred_iff, le_def]
theorem castPred_le_pred_iff {a b : Fin (n + 1)} (ha : a ≠ last n) (hb : b ≠ 0) :
castPred a ha ≤ pred b hb ↔ a < b := by
rw [le_pred_iff, succ_castPred_le_iff]
theorem pred_lt_castPred_iff {a b : Fin (n + 1)} (ha : a ≠ 0) (hb : b ≠ last n) :
pred a ha < castPred b hb ↔ a ≤ b := by
rw [lt_castPred_iff, castSucc_pred_lt_iff ha]
theorem pred_lt_castPred {a : Fin (n + 1)} (h₁ : a ≠ 0) (h₂ : a ≠ last n) :
pred a h₁ < castPred a h₂ := by
rw [pred_lt_castPred_iff, le_def]
end CastPred
section SuccAbove
variable {p : Fin (n + 1)} {i j : Fin n}
/-- `succAbove p i` embeds `Fin n` into `Fin (n + 1)` with a hole around `p`. -/
def succAbove (p : Fin (n + 1)) (i : Fin n) : Fin (n + 1) :=
if castSucc i < p then i.castSucc else i.succ
/-- Embedding `i : Fin n` into `Fin (n + 1)` with a hole around `p : Fin (n + 1)`
embeds `i` by `castSucc` when the resulting `i.castSucc < p`. -/
lemma succAbove_of_castSucc_lt (p : Fin (n + 1)) (i : Fin n) (h : castSucc i < p) :
p.succAbove i = castSucc i := if_pos h
lemma succAbove_of_succ_le (p : Fin (n + 1)) (i : Fin n) (h : succ i ≤ p) :
p.succAbove i = castSucc i :=
succAbove_of_castSucc_lt _ _ (castSucc_lt_iff_succ_le.mpr h)
/-- Embedding `i : Fin n` into `Fin (n + 1)` with a hole around `p : Fin (n + 1)`
embeds `i` by `succ` when the resulting `p < i.succ`. -/
lemma succAbove_of_le_castSucc (p : Fin (n + 1)) (i : Fin n) (h : p ≤ castSucc i) :
p.succAbove i = i.succ := if_neg (Fin.not_lt.2 h)
lemma succAbove_of_lt_succ (p : Fin (n + 1)) (i : Fin n) (h : p < succ i) :
p.succAbove i = succ i := succAbove_of_le_castSucc _ _ (le_castSucc_iff.mpr h)
lemma succAbove_succ_of_lt (p i : Fin n) (h : p < i) : succAbove p.succ i = i.succ :=
succAbove_of_lt_succ _ _ (succ_lt_succ_iff.mpr h)
lemma succAbove_succ_of_le (p i : Fin n) (h : i ≤ p) : succAbove p.succ i = i.castSucc :=
succAbove_of_succ_le _ _ (succ_le_succ_iff.mpr h)
@[simp] lemma succAbove_succ_self (j : Fin n) : j.succ.succAbove j = j.castSucc :=
succAbove_succ_of_le _ _ Fin.le_rfl
lemma succAbove_castSucc_of_lt (p i : Fin n) (h : i < p) : succAbove p.castSucc i = i.castSucc :=
succAbove_of_castSucc_lt _ _ (castSucc_lt_castSucc_iff.2 h)
lemma succAbove_castSucc_of_le (p i : Fin n) (h : p ≤ i) : succAbove p.castSucc i = i.succ :=
succAbove_of_le_castSucc _ _ (castSucc_le_castSucc_iff.2 h)
@[simp] lemma succAbove_castSucc_self (j : Fin n) : succAbove j.castSucc j = j.succ :=
succAbove_castSucc_of_le _ _ Fin.le_rfl
lemma succAbove_pred_of_lt (p i : Fin (n + 1)) (h : p < i)
(hi := Fin.ne_of_gt <| Fin.lt_of_le_of_lt p.zero_le h) : succAbove p (i.pred hi) = i := by
rw [succAbove_of_lt_succ _ _ (succ_pred _ _ ▸ h), succ_pred]
lemma succAbove_pred_of_le (p i : Fin (n + 1)) (h : i ≤ p) (hi : i ≠ 0) :
succAbove p (i.pred hi) = (i.pred hi).castSucc := succAbove_of_succ_le _ _ (succ_pred _ _ ▸ h)
@[simp] lemma succAbove_pred_self (p : Fin (n + 1)) (h : p ≠ 0) :
succAbove p (p.pred h) = (p.pred h).castSucc := succAbove_pred_of_le _ _ Fin.le_rfl h
lemma succAbove_castPred_of_lt (p i : Fin (n + 1)) (h : i < p)
(hi := Fin.ne_of_lt <| Nat.lt_of_lt_of_le h p.le_last) : succAbove p (i.castPred hi) = i := by
rw [succAbove_of_castSucc_lt _ _ (castSucc_castPred _ _ ▸ h), castSucc_castPred]
lemma succAbove_castPred_of_le (p i : Fin (n + 1)) (h : p ≤ i) (hi : i ≠ last n) :
succAbove p (i.castPred hi) = (i.castPred hi).succ :=
succAbove_of_le_castSucc _ _ (castSucc_castPred _ _ ▸ h)
lemma succAbove_castPred_self (p : Fin (n + 1)) (h : p ≠ last n) :
succAbove p (p.castPred h) = (p.castPred h).succ := succAbove_castPred_of_le _ _ Fin.le_rfl h
/-- Embedding `i : Fin n` into `Fin (n + 1)` with a hole around `p : Fin (n + 1)`
never results in `p` itself -/
@[simp]
lemma succAbove_ne (p : Fin (n + 1)) (i : Fin n) : p.succAbove i ≠ p := by
rcases p.castSucc_lt_or_lt_succ i with (h | h)
· rw [succAbove_of_castSucc_lt _ _ h]
exact Fin.ne_of_lt h
· rw [succAbove_of_lt_succ _ _ h]
exact Fin.ne_of_gt h
@[simp]
lemma ne_succAbove (p : Fin (n + 1)) (i : Fin n) : p ≠ p.succAbove i := (succAbove_ne _ _).symm
/-- Given a fixed pivot `p : Fin (n + 1)`, `p.succAbove` is injective. -/
lemma succAbove_right_injective : Injective p.succAbove := by
rintro i j hij
unfold succAbove at hij
split_ifs at hij with hi hj hj
· exact castSucc_injective _ hij
· rw [hij] at hi
cases hj <| Nat.lt_trans j.castSucc_lt_succ hi
· rw [← hij] at hj
cases hi <| Nat.lt_trans i.castSucc_lt_succ hj
· exact succ_injective _ hij
/-- Given a fixed pivot `p : Fin (n + 1)`, `p.succAbove` is injective. -/
lemma succAbove_right_inj : p.succAbove i = p.succAbove j ↔ i = j :=
succAbove_right_injective.eq_iff
/-- `Fin.succAbove p` as an `Embedding`. -/
@[simps!]
def succAboveEmb (p : Fin (n + 1)) : Fin n ↪ Fin (n + 1) := ⟨p.succAbove, succAbove_right_injective⟩
@[simp, norm_cast] lemma coe_succAboveEmb (p : Fin (n + 1)) : p.succAboveEmb = p.succAbove := rfl
@[simp]
lemma succAbove_ne_zero_zero [NeZero n] {a : Fin (n + 1)} (ha : a ≠ 0) : a.succAbove 0 = 0 := by
rw [Fin.succAbove_of_castSucc_lt]
· exact castSucc_zero'
· exact Fin.pos_iff_ne_zero.2 ha
lemma succAbove_eq_zero_iff [NeZero n] {a : Fin (n + 1)} {b : Fin n} (ha : a ≠ 0) :
a.succAbove b = 0 ↔ b = 0 := by
rw [← succAbove_ne_zero_zero ha, succAbove_right_inj]
lemma succAbove_ne_zero [NeZero n] {a : Fin (n + 1)} {b : Fin n} (ha : a ≠ 0) (hb : b ≠ 0) :
a.succAbove b ≠ 0 := mt (succAbove_eq_zero_iff ha).mp hb
/-- Embedding `Fin n` into `Fin (n + 1)` with a hole around zero embeds by `succ`. -/
@[simp] lemma succAbove_zero : succAbove (0 : Fin (n + 1)) = Fin.succ := rfl
lemma succAbove_zero_apply (i : Fin n) : succAbove 0 i = succ i := by rw [succAbove_zero]
@[simp] lemma succAbove_ne_last_last {a : Fin (n + 2)} (h : a ≠ last (n + 1)) :
a.succAbove (last n) = last (n + 1) := by
rw [succAbove_of_lt_succ _ _ (succ_last _ ▸ lt_last_iff_ne_last.2 h), succ_last]
lemma succAbove_eq_last_iff {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ last _) :
a.succAbove b = last _ ↔ b = last _ := by
rw [← succAbove_ne_last_last ha, succAbove_right_inj]
lemma succAbove_ne_last {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ last _) (hb : b ≠ last _) :
a.succAbove b ≠ last _ := mt (succAbove_eq_last_iff ha).mp hb
/-- Embedding `Fin n` into `Fin (n + 1)` with a hole around `last n` embeds by `castSucc`. -/
@[simp] lemma succAbove_last : succAbove (last n) = castSucc := by
ext; simp only [succAbove_of_castSucc_lt, castSucc_lt_last]
lemma succAbove_last_apply (i : Fin n) : succAbove (last n) i = castSucc i := by rw [succAbove_last]
/-- Embedding `i : Fin n` into `Fin (n + 1)` using a pivot `p` that is greater
results in a value that is less than `p`. -/
lemma succAbove_lt_iff_castSucc_lt (p : Fin (n + 1)) (i : Fin n) :
p.succAbove i < p ↔ castSucc i < p := by
rcases castSucc_lt_or_lt_succ p i with H | H
· rwa [iff_true_right H, succAbove_of_castSucc_lt _ _ H]
· rw [castSucc_lt_iff_succ_le, iff_false_right (Fin.not_le.2 H), succAbove_of_lt_succ _ _ H]
exact Fin.not_lt.2 <| Fin.le_of_lt H
lemma succAbove_lt_iff_succ_le (p : Fin (n + 1)) (i : Fin n) :
p.succAbove i < p ↔ succ i ≤ p := by
rw [succAbove_lt_iff_castSucc_lt, castSucc_lt_iff_succ_le]
/-- Embedding `i : Fin n` into `Fin (n + 1)` using a pivot `p` that is lesser
results in a value that is greater than `p`. -/
lemma lt_succAbove_iff_le_castSucc (p : Fin (n + 1)) (i : Fin n) :
p < p.succAbove i ↔ p ≤ castSucc i := by
rcases castSucc_lt_or_lt_succ p i with H | H
· rw [iff_false_right (Fin.not_le.2 H), succAbove_of_castSucc_lt _ _ H]
exact Fin.not_lt.2 <| Fin.le_of_lt H
· rwa [succAbove_of_lt_succ _ _ H, iff_true_left H, le_castSucc_iff]
lemma lt_succAbove_iff_lt_castSucc (p : Fin (n + 1)) (i : Fin n) :
p < p.succAbove i ↔ p < succ i := by rw [lt_succAbove_iff_le_castSucc, le_castSucc_iff]
/-- Embedding a positive `Fin n` results in a positive `Fin (n + 1)` -/
lemma succAbove_pos [NeZero n] (p : Fin (n + 1)) (i : Fin n) (h : 0 < i) : 0 < p.succAbove i := by
by_cases H : castSucc i < p
· simpa [succAbove_of_castSucc_lt _ _ H] using castSucc_pos' h
· simp [succAbove_of_le_castSucc _ _ (Fin.not_lt.1 H)]
lemma castPred_succAbove (x : Fin n) (y : Fin (n + 1)) (h : castSucc x < y)
(h' := Fin.ne_last_of_lt <| (succAbove_lt_iff_castSucc_lt ..).2 h) :
(y.succAbove x).castPred h' = x := by
rw [castPred_eq_iff_eq_castSucc, succAbove_of_castSucc_lt _ _ h]
lemma pred_succAbove (x : Fin n) (y : Fin (n + 1)) (h : y ≤ castSucc x)
(h' := Fin.ne_zero_of_lt <| (lt_succAbove_iff_le_castSucc ..).2 h) :
(y.succAbove x).pred h' = x := by simp only [succAbove_of_le_castSucc _ _ h, pred_succ]
lemma exists_succAbove_eq {x y : Fin (n + 1)} (h : x ≠ y) : ∃ z, y.succAbove z = x := by
obtain hxy | hyx := Fin.lt_or_lt_of_ne h
exacts [⟨_, succAbove_castPred_of_lt _ _ hxy⟩, ⟨_, succAbove_pred_of_lt _ _ hyx⟩]
@[simp] lemma exists_succAbove_eq_iff {x y : Fin (n + 1)} : (∃ z, x.succAbove z = y) ↔ y ≠ x :=
⟨by rintro ⟨y, rfl⟩; exact succAbove_ne _ _, exists_succAbove_eq⟩
/-- The range of `p.succAbove` is everything except `p`. -/
@[simp] lemma range_succAbove (p : Fin (n + 1)) : Set.range p.succAbove = {p}ᶜ :=
Set.ext fun _ => exists_succAbove_eq_iff
@[simp] lemma range_succ (n : ℕ) : Set.range (Fin.succ : Fin n → Fin (n + 1)) = {0}ᶜ := by
rw [← succAbove_zero]; exact range_succAbove (0 : Fin (n + 1))
/-- `succAbove` is injective at the pivot -/
lemma succAbove_left_injective : Injective (@succAbove n) := fun _ _ h => by
simpa [range_succAbove] using congr_arg (fun f : Fin n → Fin (n + 1) => (Set.range f)ᶜ) h
/-- `succAbove` is injective at the pivot -/
@[simp] lemma succAbove_left_inj {x y : Fin (n + 1)} : x.succAbove = y.succAbove ↔ x = y :=
succAbove_left_injective.eq_iff
@[simp] lemma zero_succAbove {n : ℕ} (i : Fin n) : (0 : Fin (n + 1)).succAbove i = i.succ := rfl
lemma succ_succAbove_zero {n : ℕ} [NeZero n] (i : Fin n) : succAbove i.succ 0 = 0 := by simp
/-- `succ` commutes with `succAbove`. -/
@[simp] lemma succ_succAbove_succ {n : ℕ} (i : Fin (n + 1)) (j : Fin n) :
i.succ.succAbove j.succ = (i.succAbove j).succ := by
obtain h | h := i.lt_or_le (succ j)
· rw [succAbove_of_lt_succ _ _ h, succAbove_succ_of_lt _ _ h]
· rwa [succAbove_of_castSucc_lt _ _ h, succAbove_succ_of_le, succ_castSucc]
/-- `castSucc` commutes with `succAbove`. -/
@[simp]
lemma castSucc_succAbove_castSucc {n : ℕ} {i : Fin (n + 1)} {j : Fin n} :
i.castSucc.succAbove j.castSucc = (i.succAbove j).castSucc := by
rcases i.le_or_lt (castSucc j) with (h | h)
· rw [succAbove_of_le_castSucc _ _ h, succAbove_castSucc_of_le _ _ h, succ_castSucc]
· rw [succAbove_of_castSucc_lt _ _ h, succAbove_castSucc_of_lt _ _ h]
/-- `pred` commutes with `succAbove`. -/
lemma pred_succAbove_pred {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ 0) (hb : b ≠ 0)
(hk := succAbove_ne_zero ha hb) :
(a.pred ha).succAbove (b.pred hb) = (a.succAbove b).pred hk := by
simp_rw [← succ_inj (b := pred (succAbove a b) hk), ← succ_succAbove_succ, succ_pred]
/-- `castPred` commutes with `succAbove`. -/
lemma castPred_succAbove_castPred {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ last (n + 1))
(hb : b ≠ last n) (hk := succAbove_ne_last ha hb) :
(a.castPred ha).succAbove (b.castPred hb) = (a.succAbove b).castPred hk := by
simp_rw [← castSucc_inj (b := (a.succAbove b).castPred hk), ← castSucc_succAbove_castSucc,
castSucc_castPred]
lemma one_succAbove_zero {n : ℕ} : (1 : Fin (n + 2)).succAbove 0 = 0 := by
rfl
/-- By moving `succ` to the outside of this expression, we create opportunities for further
simplification using `succAbove_zero` or `succ_succAbove_zero`. -/
@[simp] lemma succ_succAbove_one {n : ℕ} [NeZero n] (i : Fin (n + 1)) :
i.succ.succAbove 1 = (i.succAbove 0).succ := by
rw [← succ_zero_eq_one']; convert succ_succAbove_succ i 0
@[simp] lemma one_succAbove_succ {n : ℕ} (j : Fin n) :
(1 : Fin (n + 2)).succAbove j.succ = j.succ.succ := by
have := succ_succAbove_succ 0 j; rwa [succ_zero_eq_one, zero_succAbove] at this
@[simp] lemma one_succAbove_one {n : ℕ} : (1 : Fin (n + 3)).succAbove 1 = 2 := by
simpa only [succ_zero_eq_one, val_zero, zero_succAbove, succ_one_eq_two]
using succ_succAbove_succ (0 : Fin (n + 2)) (0 : Fin (n + 2))
end SuccAbove
section PredAbove
/-- `predAbove p i` surjects `i : Fin (n+1)` into `Fin n` by subtracting one if `p < i`. -/
def predAbove (p : Fin n) (i : Fin (n + 1)) : Fin n :=
if h : castSucc p < i
then pred i (Fin.ne_zero_of_lt h)
else castPred i (Fin.ne_of_lt <| Fin.lt_of_le_of_lt (Fin.not_lt.1 h) (castSucc_lt_last _))
lemma predAbove_of_le_castSucc (p : Fin n) (i : Fin (n + 1)) (h : i ≤ castSucc p)
(hi := Fin.ne_of_lt <| Fin.lt_of_le_of_lt h <| castSucc_lt_last _) :
p.predAbove i = i.castPred hi := dif_neg <| Fin.not_lt.2 h
lemma predAbove_of_lt_succ (p : Fin n) (i : Fin (n + 1)) (h : i < succ p)
(hi := Fin.ne_last_of_lt h) : p.predAbove i = i.castPred hi :=
predAbove_of_le_castSucc _ _ (le_castSucc_iff.mpr h)
lemma predAbove_of_castSucc_lt (p : Fin n) (i : Fin (n + 1)) (h : castSucc p < i)
(hi := Fin.ne_zero_of_lt h) : p.predAbove i = i.pred hi := dif_pos h
lemma predAbove_of_succ_le (p : Fin n) (i : Fin (n + 1)) (h : succ p ≤ i)
(hi := Fin.ne_of_gt <| Fin.lt_of_lt_of_le (succ_pos _) h) :
p.predAbove i = i.pred hi := predAbove_of_castSucc_lt _ _ (castSucc_lt_iff_succ_le.mpr h)
lemma predAbove_succ_of_lt (p i : Fin n) (h : i < p) (hi := succ_ne_last_of_lt h) :
p.predAbove (succ i) = (i.succ).castPred hi := by
rw [predAbove_of_lt_succ _ _ (succ_lt_succ_iff.mpr h)]
lemma predAbove_succ_of_le (p i : Fin n) (h : p ≤ i) : p.predAbove (succ i) = i := by
rw [predAbove_of_succ_le _ _ (succ_le_succ_iff.mpr h), pred_succ]
@[simp] lemma predAbove_succ_self (p : Fin n) : p.predAbove (succ p) = p :=
predAbove_succ_of_le _ _ Fin.le_rfl
lemma predAbove_castSucc_of_lt (p i : Fin n) (h : p < i) (hi := castSucc_ne_zero_of_lt h) :
p.predAbove (castSucc i) = i.castSucc.pred hi := by
rw [predAbove_of_castSucc_lt _ _ (castSucc_lt_castSucc_iff.2 h)]
lemma predAbove_castSucc_of_le (p i : Fin n) (h : i ≤ p) : p.predAbove (castSucc i) = i := by
rw [predAbove_of_le_castSucc _ _ (castSucc_le_castSucc_iff.mpr h), castPred_castSucc]
@[simp] lemma predAbove_castSucc_self (p : Fin n) : p.predAbove (castSucc p) = p :=
predAbove_castSucc_of_le _ _ Fin.le_rfl
lemma predAbove_pred_of_lt (p i : Fin (n + 1)) (h : i < p) (hp := Fin.ne_zero_of_lt h)
(hi := Fin.ne_last_of_lt h) : (pred p hp).predAbove i = castPred i hi := by
rw [predAbove_of_lt_succ _ _ (succ_pred _ _ ▸ h)]
lemma predAbove_pred_of_le (p i : Fin (n + 1)) (h : p ≤ i) (hp : p ≠ 0)
(hi := Fin.ne_of_gt <| Fin.lt_of_lt_of_le (Fin.pos_iff_ne_zero.2 hp) h) :
(pred p hp).predAbove i = pred i hi := by rw [predAbove_of_succ_le _ _ (succ_pred _ _ ▸ h)]
lemma predAbove_pred_self (p : Fin (n + 1)) (hp : p ≠ 0) : (pred p hp).predAbove p = pred p hp :=
predAbove_pred_of_le _ _ Fin.le_rfl hp
lemma predAbove_castPred_of_lt (p i : Fin (n + 1)) (h : p < i) (hp := Fin.ne_last_of_lt h)
(hi := Fin.ne_zero_of_lt h) : (castPred p hp).predAbove i = pred i hi := by
rw [predAbove_of_castSucc_lt _ _ (castSucc_castPred _ _ ▸ h)]
lemma predAbove_castPred_of_le (p i : Fin (n + 1)) (h : i ≤ p) (hp : p ≠ last n)
(hi := Fin.ne_of_lt <| Fin.lt_of_le_of_lt h <| Fin.lt_last_iff_ne_last.2 hp) :
(castPred p hp).predAbove i = castPred i hi := by
rw [predAbove_of_le_castSucc _ _ (castSucc_castPred _ _ ▸ h)]
lemma predAbove_castPred_self (p : Fin (n + 1)) (hp : p ≠ last n) :
(castPred p hp).predAbove p = castPred p hp := predAbove_castPred_of_le _ _ Fin.le_rfl hp
@[simp] lemma predAbove_right_zero [NeZero n] {i : Fin n} : predAbove (i : Fin n) 0 = 0 := by
cases n
· exact i.elim0
· rw [predAbove_of_le_castSucc _ _ (zero_le _), castPred_zero]
lemma predAbove_zero_succ [NeZero n] {i : Fin n} : predAbove 0 i.succ = i := by
rw [predAbove_succ_of_le _ _ (Fin.zero_le' _)]
@[simp]
lemma succ_predAbove_zero [NeZero n] {j : Fin (n + 1)} (h : j ≠ 0) : succ (predAbove 0 j) = j := by
rcases exists_succ_eq_of_ne_zero h with ⟨k, rfl⟩
rw [predAbove_zero_succ]
@[simp] lemma predAbove_zero_of_ne_zero [NeZero n] {i : Fin (n + 1)} (hi : i ≠ 0) :
predAbove 0 i = i.pred hi := by
obtain ⟨y, rfl⟩ := exists_succ_eq.2 hi; exact predAbove_zero_succ
lemma predAbove_zero [NeZero n] {i : Fin (n + 1)} :
predAbove (0 : Fin n) i = if hi : i = 0 then 0 else i.pred hi := by
split_ifs with hi
· rw [hi, predAbove_right_zero]
· rw [predAbove_zero_of_ne_zero hi]
@[simp] lemma predAbove_right_last {i : Fin (n + 1)} : predAbove i (last (n + 1)) = last n := by
rw [predAbove_of_castSucc_lt _ _ (castSucc_lt_last _), pred_last]
lemma predAbove_last_castSucc {i : Fin (n + 1)} : predAbove (last n) (i.castSucc) = i := by
rw [predAbove_of_le_castSucc _ _ (castSucc_le_castSucc_iff.mpr (le_last _)), castPred_castSucc]
@[simp] lemma predAbove_last_of_ne_last {i : Fin (n + 2)} (hi : i ≠ last (n + 1)) :
predAbove (last n) i = castPred i hi := by
rw [← exists_castSucc_eq] at hi
rcases hi with ⟨y, rfl⟩
exact predAbove_last_castSucc
lemma predAbove_last_apply {i : Fin (n + 2)} :
predAbove (last n) i = if hi : i = last _ then last _ else i.castPred hi := by
split_ifs with hi
· rw [hi, predAbove_right_last]
· rw [predAbove_last_of_ne_last hi]
/-- Sending `Fin (n+1)` to `Fin n` by subtracting one from anything above `p`
then back to `Fin (n+1)` with a gap around `p` is the identity away from `p`. -/
@[simp]
lemma succAbove_predAbove {p : Fin n} {i : Fin (n + 1)} (h : i ≠ castSucc p) :
p.castSucc.succAbove (p.predAbove i) = i := by
obtain h | h := Fin.lt_or_lt_of_ne h
· rw [predAbove_of_le_castSucc _ _ (Fin.le_of_lt h), succAbove_castPred_of_lt _ _ h]
· rw [predAbove_of_castSucc_lt _ _ h, succAbove_pred_of_lt _ _ h]
/-- Sending `Fin (n+1)` to `Fin n` by subtracting one from anything above `p`
then back to `Fin (n+1)` with a gap around `p.succ` is the identity away from `p.succ`. -/
@[simp]
lemma succ_succAbove_predAbove {n : ℕ} {p : Fin n} {i : Fin (n + 1)} (h : i ≠ p.succ) :
p.succ.succAbove (p.predAbove i) = i := by
obtain h | h := Fin.lt_or_lt_of_ne h
· rw [predAbove_of_le_castSucc _ _ (le_castSucc_iff.2 h),
succAbove_castPred_of_lt _ _ h]
· rw [predAbove_of_castSucc_lt _ _ (Fin.lt_of_le_of_lt (p.castSucc_le_succ) h),
succAbove_pred_of_lt _ _ h]
/-- Sending `Fin n` into `Fin (n + 1)` with a gap at `p`
then back to `Fin n` by subtracting one from anything above `p` is the identity. -/
@[simp]
lemma predAbove_succAbove (p : Fin n) (i : Fin n) : p.predAbove ((castSucc p).succAbove i) = i := by
obtain h | h := p.le_or_lt i
· rw [succAbove_castSucc_of_le _ _ h, predAbove_succ_of_le _ _ h]
· rw [succAbove_castSucc_of_lt _ _ h, predAbove_castSucc_of_le _ _ <| Fin.le_of_lt h]
/-- `succ` commutes with `predAbove`. -/
@[simp] lemma succ_predAbove_succ (a : Fin n) (b : Fin (n + 1)) :
a.succ.predAbove b.succ = (a.predAbove b).succ := by
obtain h | h := Fin.le_or_lt (succ a) b
· rw [predAbove_of_castSucc_lt _ _ h, predAbove_succ_of_le _ _ h, succ_pred]
· rw [predAbove_of_lt_succ _ _ h, predAbove_succ_of_lt _ _ h, succ_castPred_eq_castPred_succ]
/-- `castSucc` commutes with `predAbove`. -/
@[simp] lemma castSucc_predAbove_castSucc {n : ℕ} (a : Fin n) (b : Fin (n + 1)) :
a.castSucc.predAbove b.castSucc = (a.predAbove b).castSucc := by
obtain h | h := a.castSucc.lt_or_le b
· rw [predAbove_of_castSucc_lt _ _ h, predAbove_castSucc_of_lt _ _ h,
castSucc_pred_eq_pred_castSucc]
· rw [predAbove_of_le_castSucc _ _ h, predAbove_castSucc_of_le _ _ h, castSucc_castPred]
end PredAbove
section DivMod
/-- Compute `i / n`, where `n` is a `Nat` and inferred the type of `i`. -/
def divNat (i : Fin (m * n)) : Fin m :=
⟨i / n, Nat.div_lt_of_lt_mul <| Nat.mul_comm m n ▸ i.prop⟩
@[simp]
theorem coe_divNat (i : Fin (m * n)) : (i.divNat : ℕ) = i / n :=
rfl
/-- Compute `i % n`, where `n` is a `Nat` and inferred the type of `i`. -/
def modNat (i : Fin (m * n)) : Fin n := ⟨i % n, Nat.mod_lt _ <| Nat.pos_of_mul_pos_left i.pos⟩
@[simp]
theorem coe_modNat (i : Fin (m * n)) : (i.modNat : ℕ) = i % n :=
rfl
theorem modNat_rev (i : Fin (m * n)) : i.rev.modNat = i.modNat.rev := by
ext
have H₁ : i % n + 1 ≤ n := i.modNat.is_lt
have H₂ : i / n < m := i.divNat.is_lt
simp only [coe_modNat, val_rev]
calc
(m * n - (i + 1)) % n = (m * n - ((i / n) * n + i % n + 1)) % n := by rw [Nat.div_add_mod']
_ = ((m - i / n - 1) * n + (n - (i % n + 1))) % n := by
rw [Nat.mul_sub_right_distrib, Nat.one_mul, Nat.sub_add_sub_cancel _ H₁,
Nat.mul_sub_right_distrib, Nat.sub_sub, Nat.add_assoc]
exact Nat.le_mul_of_pos_left _ <| Nat.le_sub_of_add_le' H₂
_ = n - (i % n + 1) := by
rw [Nat.mul_comm, Nat.mul_add_mod, Nat.mod_eq_of_lt]; exact i.modNat.rev.is_lt
end DivMod
section Rec
/-!
### recursion and induction principles
-/
end Rec
open scoped Relator in
theorem liftFun_iff_succ {α : Type*} (r : α → α → Prop) [IsTrans α r] {f : Fin (n + 1) → α} :
((· < ·) ⇒ r) f f ↔ ∀ i : Fin n, r (f (castSucc i)) (f i.succ) := by
constructor
· intro H i
exact H i.castSucc_lt_succ
· refine fun H i => Fin.induction (fun h ↦ ?_) ?_
· simp [le_def] at h
· intro j ihj hij
rw [← le_castSucc_iff] at hij
obtain hij | hij := (le_def.1 hij).eq_or_lt
· obtain rfl := Fin.ext hij
exact H _
· exact _root_.trans (ihj hij) (H j)
section AddGroup
open Nat Int
/-- Negation on `Fin n` -/
instance neg (n : ℕ) : Neg (Fin n) :=
⟨fun a => ⟨(n - a) % n, Nat.mod_lt _ a.pos⟩⟩
theorem neg_def (a : Fin n) : -a = ⟨(n - a) % n, Nat.mod_lt _ a.pos⟩ := rfl
protected theorem coe_neg (a : Fin n) : ((-a : Fin n) : ℕ) = (n - a) % n :=
rfl
theorem eq_zero (n : Fin 1) : n = 0 := Subsingleton.elim _ _
lemma eq_one_of_ne_zero (i : Fin 2) (hi : i ≠ 0) : i = 1 := by fin_omega
@[deprecated (since := "2025-04-27")]
alias eq_one_of_neq_zero := eq_one_of_ne_zero
@[simp]
theorem coe_neg_one : ↑(-1 : Fin (n + 1)) = n := by
cases n
· simp
rw [Fin.coe_neg, Fin.val_one, Nat.add_one_sub_one, Nat.mod_eq_of_lt]
constructor
theorem last_sub (i : Fin (n + 1)) : last n - i = Fin.rev i :=
Fin.ext <| by rw [coe_sub_iff_le.2 i.le_last, val_last, val_rev, Nat.succ_sub_succ_eq_sub]
theorem add_one_le_of_lt {n : ℕ} {a b : Fin (n + 1)} (h : a < b) : a + 1 ≤ b := by
cases n <;> fin_omega
theorem exists_eq_add_of_le {n : ℕ} {a b : Fin n} (h : a ≤ b) : ∃ k ≤ b, b = a + k := by
obtain ⟨k, hk⟩ : ∃ k : ℕ, (b : ℕ) = a + k := Nat.exists_eq_add_of_le h
have hkb : k ≤ b := by omega
refine ⟨⟨k, hkb.trans_lt b.is_lt⟩, hkb, ?_⟩
simp [Fin.ext_iff, Fin.val_add, ← hk, Nat.mod_eq_of_lt b.is_lt]
theorem exists_eq_add_of_lt {n : ℕ} {a b : Fin (n + 1)} (h : a < b) :
∃ k < b, k + 1 ≤ b ∧ b = a + k + 1 := by
cases n
· omega
obtain ⟨k, hk⟩ : ∃ k : ℕ, (b : ℕ) = a + k + 1 := Nat.exists_eq_add_of_lt h
have hkb : k < b := by omega
refine ⟨⟨k, hkb.trans b.is_lt⟩, hkb, by fin_omega, ?_⟩
simp [Fin.ext_iff, Fin.val_add, ← hk, Nat.mod_eq_of_lt b.is_lt]
lemma pos_of_ne_zero {n : ℕ} {a : Fin (n + 1)} (h : a ≠ 0) :
0 < a :=
Nat.pos_of_ne_zero (val_ne_of_ne h)
lemma sub_succ_le_sub_of_le {n : ℕ} {u v : Fin (n + 2)} (h : u < v) : v - (u + 1) < v - u := by
fin_omega
end AddGroup
@[simp]
theorem coe_natCast_eq_mod (m n : ℕ) [NeZero m] :
((n : Fin m) : ℕ) = n % m :=
rfl
theorem coe_ofNat_eq_mod (m n : ℕ) [NeZero m] :
((ofNat(n) : Fin m) : ℕ) = ofNat(n) % m :=
rfl
section Mul
/-!
### mul
-/
protected theorem mul_one' [NeZero n] (k : Fin n) : k * 1 = k := by
rcases n with - | n
· simp [eq_iff_true_of_subsingleton]
cases n
· simp [fin_one_eq_zero]
simp [Fin.ext_iff, mul_def, mod_eq_of_lt (is_lt k)]
protected theorem one_mul' [NeZero n] (k : Fin n) : (1 : Fin n) * k = k := by
rw [Fin.mul_comm, Fin.mul_one']
protected theorem mul_zero' [NeZero n] (k : Fin n) : k * 0 = 0 := by simp [Fin.ext_iff, mul_def]
protected theorem zero_mul' [NeZero n] (k : Fin n) : (0 : Fin n) * k = 0 := by
simp [Fin.ext_iff, mul_def]
end Mul
end Fin
| Mathlib/Data/Fin/Basic.lean | 1,540 | 1,546 |
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