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/-
Copyright (c) 2022 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.Algebra.Category.ModuleCat.Abelian
import Mathlib.CategoryTheory.Limits.Shapes.Images
#align_import algebra.category.Module.images from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# The category of R-modules has images.
Note that we don't need to register any of the constructions here as instances, because we get them
from the fact that `ModuleCat R` is an abelian category.
-/
open CategoryTheory
open CategoryTheory.Limits
universe u v
namespace ModuleCat
set_option linter.uppercaseLean3 false -- `Module`
variable {R : Type u} [Ring R]
variable {G H : ModuleCat.{v} R} (f : G ⟶ H)
attribute [local ext] Subtype.ext_val
section
-- implementation details of `HasImage` for ModuleCat; use the API, not these
/-- The image of a morphism in `ModuleCat R` is just the bundling of `LinearMap.range f` -/
def image : ModuleCat R :=
ModuleCat.of R (LinearMap.range f)
#align Module.image ModuleCat.image
/-- The inclusion of `image f` into the target -/
def image.ι : image f ⟶ H :=
f.range.subtype
#align Module.image.ι ModuleCat.image.ι
instance : Mono (image.ι f) :=
ConcreteCategory.mono_of_injective (image.ι f) Subtype.val_injective
/-- The corestriction map to the image -/
def factorThruImage : G ⟶ image f :=
f.rangeRestrict
#align Module.factor_thru_image ModuleCat.factorThruImage
theorem image.fac : factorThruImage f ≫ image.ι f = f :=
rfl
#align Module.image.fac ModuleCat.image.fac
attribute [local simp] image.fac
variable {f}
/-- The universal property for the image factorisation -/
noncomputable def image.lift (F' : MonoFactorisation f) : image f ⟶ F'.I where
toFun := (fun x => F'.e (Classical.indefiniteDescription _ x.2).1 : image f → F'.I)
map_add' x y := by
apply (mono_iff_injective F'.m).1
· infer_instance
rw [LinearMap.map_add]
change (F'.e ≫ F'.m) _ = (F'.e ≫ F'.m) _ + (F'.e ≫ F'.m) _
simp_rw [F'.fac, (Classical.indefiniteDescription (fun z => f z = _) _).2]
rfl
map_smul' c x := by
apply (mono_iff_injective F'.m).1
· infer_instance
rw [LinearMap.map_smul]
change (F'.e ≫ F'.m) _ = _ • (F'.e ≫ F'.m) _
simp_rw [F'.fac, (Classical.indefiniteDescription (fun z => f z = _) _).2]
rfl
#align Module.image.lift ModuleCat.image.lift
theorem image.lift_fac (F' : MonoFactorisation f) : image.lift F' ≫ F'.m = image.ι f := by
ext x
change (F'.e ≫ F'.m) _ = _
rw [F'.fac, (Classical.indefiniteDescription _ x.2).2]
rfl
#align Module.image.lift_fac ModuleCat.image.lift_fac
end
/-- The factorisation of any morphism in `ModuleCat R` through a mono. -/
def monoFactorisation : MonoFactorisation f where
I := image f
m := image.ι f
e := factorThruImage f
#align Module.mono_factorisation ModuleCat.monoFactorisation
/-- The factorisation of any morphism in `ModuleCat R` through a mono has the universal property of
the image. -/
noncomputable def isImage : IsImage (monoFactorisation f) where
lift := image.lift
lift_fac := image.lift_fac
#align Module.is_image ModuleCat.isImage
/-- The categorical image of a morphism in `ModuleCat R` agrees with the linear algebraic range. -/
noncomputable def imageIsoRange {G H : ModuleCat.{v} R} (f : G ⟶ H) :
Limits.image f ≅ ModuleCat.of R (LinearMap.range f) :=
IsImage.isoExt (Image.isImage f) (isImage f)
#align Module.image_iso_range ModuleCat.imageIsoRange
@[simp, reassoc, elementwise]
theorem imageIsoRange_inv_image_ι {G H : ModuleCat.{v} R} (f : G ⟶ H) :
(imageIsoRange f).inv ≫ Limits.image.ι f = ModuleCat.ofHom f.range.subtype :=
IsImage.isoExt_inv_m _ _
#align Module.image_iso_range_inv_image_ι ModuleCat.imageIsoRange_inv_image_ι
@[simp, reassoc, elementwise]
| Mathlib/Algebra/Category/ModuleCat/Images.lean | 117 | 119 | theorem imageIsoRange_hom_subtype {G H : ModuleCat.{v} R} (f : G ⟶ H) :
(imageIsoRange f).hom ≫ ModuleCat.ofHom f.range.subtype = Limits.image.ι f := by |
erw [← imageIsoRange_inv_image_ι f, Iso.hom_inv_id_assoc]
|
/-
Copyright (c) 2024 Christian Merten. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Christian Merten
-/
import Mathlib.CategoryTheory.Galois.Basic
import Mathlib.RepresentationTheory.Action.Basic
import Mathlib.RepresentationTheory.Action.Concrete
import Mathlib.RepresentationTheory.Action.Limits
import Mathlib.CategoryTheory.Limits.FintypeCat
import Mathlib.CategoryTheory.Limits.Shapes.Types
import Mathlib.Logic.Equiv.TransferInstance
/-!
# Examples of Galois categories and fiber functors
We show that for a group `G` the category of finite `G`-sets is a `PreGaloisCategory` and that the
forgetful functor to `FintypeCat` is a `FiberFunctor`.
The connected finite `G`-sets are precisely the ones with transitive `G`-action.
-/
universe u v w
namespace CategoryTheory
namespace FintypeCat
open Limits Functor PreGaloisCategory
/-- Complement of the image of a morphism `f : X ⟶ Y` in `FintypeCat`. -/
noncomputable def imageComplement {X Y : FintypeCat.{u}} (f : X ⟶ Y) :
FintypeCat.{u} := by
haveI : Fintype (↑(Set.range f)ᶜ) := Fintype.ofFinite _
exact FintypeCat.of (↑(Set.range f)ᶜ)
/-- The inclusion from the complement of the image of `f : X ⟶ Y` into `Y`. -/
def imageComplementIncl {X Y : FintypeCat.{u}}
(f : X ⟶ Y) : imageComplement f ⟶ Y :=
Subtype.val
variable (G : Type u) [Group G]
/-- Given `f : X ⟶ Y` for `X Y : Action FintypeCat (MonCat.of G)`, the complement of the image
of `f` has a natural `G`-action. -/
noncomputable def Action.imageComplement {X Y : Action FintypeCat (MonCat.of G)}
(f : X ⟶ Y) : Action FintypeCat (MonCat.of G) where
V := FintypeCat.imageComplement f.hom
ρ := MonCat.ofHom <| {
toFun := fun g y ↦ Subtype.mk (Y.ρ g y.val) <| by
intro ⟨x, h⟩
apply y.property
use X.ρ g⁻¹ x
calc (X.ρ g⁻¹ ≫ f.hom) x
= (Y.ρ g⁻¹ * Y.ρ g) y.val := by rw [f.comm, FintypeCat.comp_apply, h]; rfl
_ = y.val := by rw [← map_mul, mul_left_inv, Action.ρ_one, FintypeCat.id_apply]
map_one' := by simp only [Action.ρ_one]; rfl
map_mul' := fun g h ↦ FintypeCat.hom_ext _ _ <| fun y ↦ Subtype.ext <| by
exact congrFun (MonoidHom.map_mul Y.ρ g h) y.val
}
/-- The inclusion from the complement of the image of `f : X ⟶ Y` into `Y`. -/
def Action.imageComplementIncl {X Y : Action FintypeCat (MonCat.of G)} (f : X ⟶ Y) :
Action.imageComplement G f ⟶ Y where
hom := FintypeCat.imageComplementIncl f.hom
comm _ := rfl
instance {X Y : Action FintypeCat (MonCat.of G)} (f : X ⟶ Y) :
Mono (Action.imageComplementIncl G f) := by
apply Functor.mono_of_mono_map (forget _)
apply ConcreteCategory.mono_of_injective
exact Subtype.val_injective
/-- The category of finite sets has quotients by finite groups in arbitrary universes. -/
instance [Finite G] : HasColimitsOfShape (SingleObj G) FintypeCat.{w} := by
obtain ⟨G', hg, hf, ⟨e⟩⟩ := Finite.exists_type_zero_nonempty_mulEquiv G
exact Limits.hasColimitsOfShape_of_equivalence e.toSingleObjEquiv.symm
noncomputable instance : PreservesFiniteLimits (forget (Action FintypeCat (MonCat.of G))) := by
show PreservesFiniteLimits (Action.forget FintypeCat _ ⋙ FintypeCat.incl)
apply compPreservesFiniteLimits
/-- The category of finite `G`-sets is a `PreGaloisCategory`. -/
instance : PreGaloisCategory (Action FintypeCat (MonCat.of G)) where
hasQuotientsByFiniteGroups G _ _ := inferInstance
monoInducesIsoOnDirectSummand {X Y} i h :=
⟨Action.imageComplement G i, Action.imageComplementIncl G i,
⟨isColimitOfReflects (Action.forget _ _ ⋙ FintypeCat.incl) <|
(isColimitMapCoconeBinaryCofanEquiv (forget _) i _).symm
(Types.isCoprodOfMono ((forget _).map i))⟩⟩
/-- The forgetful functor from finite `G`-sets to sets is a `FiberFunctor`. -/
noncomputable instance : FiberFunctor (Action.forget FintypeCat (MonCat.of G)) where
preservesFiniteCoproducts := ⟨fun _ _ ↦ inferInstance⟩
preservesQuotientsByFiniteGroups _ _ _ := inferInstance
reflectsIsos := ⟨fun f (h : IsIso f.hom) => inferInstance⟩
/-- The category of finite `G`-sets is a `GaloisCategory`. -/
instance : GaloisCategory (Action FintypeCat (MonCat.of G)) where
hasFiberFunctor := ⟨Action.forget FintypeCat (MonCat.of G), ⟨inferInstance⟩⟩
/-- The `G`-action on a connected finite `G`-set is transitive. -/
theorem Action.pretransitive_of_isConnected (X : Action FintypeCat (MonCat.of G))
[IsConnected X] : MulAction.IsPretransitive G X.V where
exists_smul_eq x y := by
/- We show that the `G`-orbit of `x` is a non-initial subobject of `X` and hence by
connectedness, the orbit equals `X.V`. -/
let T : Set X.V := MulAction.orbit G x
have : Fintype T := Fintype.ofFinite T
letI : MulAction G (FintypeCat.of T) := inferInstanceAs <| MulAction G ↑(MulAction.orbit G x)
let T' : Action FintypeCat (MonCat.of G) := Action.FintypeCat.ofMulAction G (FintypeCat.of T)
let i : T' ⟶ X := ⟨Subtype.val, fun _ ↦ rfl⟩
have : Mono i := ConcreteCategory.mono_of_injective _ (Subtype.val_injective)
have : IsIso i := by
apply IsConnected.noTrivialComponent T' i
apply (not_initial_iff_fiber_nonempty (Action.forget _ _) T').mpr
exact Set.Nonempty.coe_sort (MulAction.orbit_nonempty x)
have hb : Function.Bijective i.hom := by
apply (ConcreteCategory.isIso_iff_bijective i.hom).mp
exact map_isIso (forget₂ _ FintypeCat) i
obtain ⟨⟨y', ⟨g, (hg : g • x = y')⟩⟩, (hy' : y' = y)⟩ := hb.surjective y
use g
exact hg.trans hy'
/-- A nonempty `G`-set with transitive `G`-action is connected. -/
| Mathlib/CategoryTheory/Galois/Examples.lean | 127 | 145 | theorem Action.isConnected_of_transitive (X : FintypeCat) [MulAction G X]
[MulAction.IsPretransitive G X] [h : Nonempty X] :
IsConnected (Action.FintypeCat.ofMulAction G X) where
notInitial := not_initial_of_inhabited (Action.forget _ _) h.some
noTrivialComponent Y i hm hni := by |
/- We show that the induced inclusion `i.hom` of finite sets is surjective, using the
transitivity of the `G`-action. -/
obtain ⟨(y : Y.V)⟩ := (not_initial_iff_fiber_nonempty (Action.forget _ _) Y).mp hni
have : IsIso i.hom := by
refine (ConcreteCategory.isIso_iff_bijective i.hom).mpr ⟨?_, fun x' ↦ ?_⟩
· haveI : Mono i.hom := map_mono (forget₂ _ _) i
exact ConcreteCategory.injective_of_mono_of_preservesPullback i.hom
· letI x : X := i.hom y
obtain ⟨σ, hσ⟩ := MulAction.exists_smul_eq G x x'
use σ • y
show (Y.ρ σ ≫ i.hom) y = x'
rw [i.comm, FintypeCat.comp_apply]
exact hσ
apply isIso_of_reflects_iso i (Action.forget _ _)
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura
-/
import Mathlib.Data.Stream.Defs
import Mathlib.Logic.Function.Basic
import Mathlib.Init.Data.List.Basic
import Mathlib.Data.List.Basic
#align_import data.stream.init from "leanprover-community/mathlib"@"207cfac9fcd06138865b5d04f7091e46d9320432"
/-!
# Streams a.k.a. infinite lists a.k.a. infinite sequences
Porting note:
This file used to be in the core library. It was moved to `mathlib` and renamed to `init` to avoid
name clashes. -/
set_option autoImplicit true
open Nat Function Option
namespace Stream'
variable {α : Type u} {β : Type v} {δ : Type w}
instance [Inhabited α] : Inhabited (Stream' α) :=
⟨Stream'.const default⟩
protected theorem eta (s : Stream' α) : (head s::tail s) = s :=
funext fun i => by cases i <;> rfl
#align stream.eta Stream'.eta
@[ext]
protected theorem ext {s₁ s₂ : Stream' α} : (∀ n, get s₁ n = get s₂ n) → s₁ = s₂ :=
fun h => funext h
#align stream.ext Stream'.ext
@[simp]
theorem get_zero_cons (a : α) (s : Stream' α) : get (a::s) 0 = a :=
rfl
#align stream.nth_zero_cons Stream'.get_zero_cons
@[simp]
theorem head_cons (a : α) (s : Stream' α) : head (a::s) = a :=
rfl
#align stream.head_cons Stream'.head_cons
@[simp]
theorem tail_cons (a : α) (s : Stream' α) : tail (a::s) = s :=
rfl
#align stream.tail_cons Stream'.tail_cons
@[simp]
theorem get_drop (n m : Nat) (s : Stream' α) : get (drop m s) n = get s (n + m) :=
rfl
#align stream.nth_drop Stream'.get_drop
theorem tail_eq_drop (s : Stream' α) : tail s = drop 1 s :=
rfl
#align stream.tail_eq_drop Stream'.tail_eq_drop
@[simp]
theorem drop_drop (n m : Nat) (s : Stream' α) : drop n (drop m s) = drop (n + m) s := by
ext; simp [Nat.add_assoc]
#align stream.drop_drop Stream'.drop_drop
@[simp] theorem get_tail {s : Stream' α} : s.tail.get n = s.get (n + 1) := rfl
@[simp] theorem tail_drop' {s : Stream' α} : tail (drop i s) = s.drop (i+1) := by
ext; simp [Nat.add_comm, Nat.add_assoc, Nat.add_left_comm]
@[simp] theorem drop_tail' {s : Stream' α} : drop i (tail s) = s.drop (i+1) := rfl
theorem tail_drop (n : Nat) (s : Stream' α) : tail (drop n s) = drop n (tail s) := by simp
#align stream.tail_drop Stream'.tail_drop
theorem get_succ (n : Nat) (s : Stream' α) : get s (succ n) = get (tail s) n :=
rfl
#align stream.nth_succ Stream'.get_succ
@[simp]
theorem get_succ_cons (n : Nat) (s : Stream' α) (x : α) : get (x::s) n.succ = get s n :=
rfl
#align stream.nth_succ_cons Stream'.get_succ_cons
@[simp] theorem drop_zero {s : Stream' α} : s.drop 0 = s := rfl
theorem drop_succ (n : Nat) (s : Stream' α) : drop (succ n) s = drop n (tail s) :=
rfl
#align stream.drop_succ Stream'.drop_succ
theorem head_drop (a : Stream' α) (n : ℕ) : (a.drop n).head = a.get n := by simp
#align stream.head_drop Stream'.head_drop
theorem cons_injective2 : Function.Injective2 (cons : α → Stream' α → Stream' α) := fun x y s t h =>
⟨by rw [← get_zero_cons x s, h, get_zero_cons],
Stream'.ext fun n => by rw [← get_succ_cons n _ x, h, get_succ_cons]⟩
#align stream.cons_injective2 Stream'.cons_injective2
theorem cons_injective_left (s : Stream' α) : Function.Injective fun x => cons x s :=
cons_injective2.left _
#align stream.cons_injective_left Stream'.cons_injective_left
theorem cons_injective_right (x : α) : Function.Injective (cons x) :=
cons_injective2.right _
#align stream.cons_injective_right Stream'.cons_injective_right
theorem all_def (p : α → Prop) (s : Stream' α) : All p s = ∀ n, p (get s n) :=
rfl
#align stream.all_def Stream'.all_def
theorem any_def (p : α → Prop) (s : Stream' α) : Any p s = ∃ n, p (get s n) :=
rfl
#align stream.any_def Stream'.any_def
@[simp]
theorem mem_cons (a : α) (s : Stream' α) : a ∈ a::s :=
Exists.intro 0 rfl
#align stream.mem_cons Stream'.mem_cons
theorem mem_cons_of_mem {a : α} {s : Stream' α} (b : α) : a ∈ s → a ∈ b::s := fun ⟨n, h⟩ =>
Exists.intro (succ n) (by rw [get_succ, tail_cons, h])
#align stream.mem_cons_of_mem Stream'.mem_cons_of_mem
theorem eq_or_mem_of_mem_cons {a b : α} {s : Stream' α} : (a ∈ b::s) → a = b ∨ a ∈ s :=
fun ⟨n, h⟩ => by
cases' n with n'
· left
exact h
· right
rw [get_succ, tail_cons] at h
exact ⟨n', h⟩
#align stream.eq_or_mem_of_mem_cons Stream'.eq_or_mem_of_mem_cons
theorem mem_of_get_eq {n : Nat} {s : Stream' α} {a : α} : a = get s n → a ∈ s := fun h =>
Exists.intro n h
#align stream.mem_of_nth_eq Stream'.mem_of_get_eq
section Map
variable (f : α → β)
theorem drop_map (n : Nat) (s : Stream' α) : drop n (map f s) = map f (drop n s) :=
Stream'.ext fun _ => rfl
#align stream.drop_map Stream'.drop_map
@[simp]
theorem get_map (n : Nat) (s : Stream' α) : get (map f s) n = f (get s n) :=
rfl
#align stream.nth_map Stream'.get_map
theorem tail_map (s : Stream' α) : tail (map f s) = map f (tail s) := rfl
#align stream.tail_map Stream'.tail_map
@[simp]
theorem head_map (s : Stream' α) : head (map f s) = f (head s) :=
rfl
#align stream.head_map Stream'.head_map
theorem map_eq (s : Stream' α) : map f s = f (head s)::map f (tail s) := by
rw [← Stream'.eta (map f s), tail_map, head_map]
#align stream.map_eq Stream'.map_eq
theorem map_cons (a : α) (s : Stream' α) : map f (a::s) = f a::map f s := by
rw [← Stream'.eta (map f (a::s)), map_eq]; rfl
#align stream.map_cons Stream'.map_cons
@[simp]
theorem map_id (s : Stream' α) : map id s = s :=
rfl
#align stream.map_id Stream'.map_id
@[simp]
theorem map_map (g : β → δ) (f : α → β) (s : Stream' α) : map g (map f s) = map (g ∘ f) s :=
rfl
#align stream.map_map Stream'.map_map
@[simp]
theorem map_tail (s : Stream' α) : map f (tail s) = tail (map f s) :=
rfl
#align stream.map_tail Stream'.map_tail
theorem mem_map {a : α} {s : Stream' α} : a ∈ s → f a ∈ map f s := fun ⟨n, h⟩ =>
Exists.intro n (by rw [get_map, h])
#align stream.mem_map Stream'.mem_map
theorem exists_of_mem_map {f} {b : β} {s : Stream' α} : b ∈ map f s → ∃ a, a ∈ s ∧ f a = b :=
fun ⟨n, h⟩ => ⟨get s n, ⟨n, rfl⟩, h.symm⟩
#align stream.exists_of_mem_map Stream'.exists_of_mem_map
end Map
section Zip
variable (f : α → β → δ)
theorem drop_zip (n : Nat) (s₁ : Stream' α) (s₂ : Stream' β) :
drop n (zip f s₁ s₂) = zip f (drop n s₁) (drop n s₂) :=
Stream'.ext fun _ => rfl
#align stream.drop_zip Stream'.drop_zip
@[simp]
theorem get_zip (n : Nat) (s₁ : Stream' α) (s₂ : Stream' β) :
get (zip f s₁ s₂) n = f (get s₁ n) (get s₂ n) :=
rfl
#align stream.nth_zip Stream'.get_zip
theorem head_zip (s₁ : Stream' α) (s₂ : Stream' β) : head (zip f s₁ s₂) = f (head s₁) (head s₂) :=
rfl
#align stream.head_zip Stream'.head_zip
theorem tail_zip (s₁ : Stream' α) (s₂ : Stream' β) :
tail (zip f s₁ s₂) = zip f (tail s₁) (tail s₂) :=
rfl
#align stream.tail_zip Stream'.tail_zip
theorem zip_eq (s₁ : Stream' α) (s₂ : Stream' β) :
zip f s₁ s₂ = f (head s₁) (head s₂)::zip f (tail s₁) (tail s₂) := by
rw [← Stream'.eta (zip f s₁ s₂)]; rfl
#align stream.zip_eq Stream'.zip_eq
@[simp]
theorem get_enum (s : Stream' α) (n : ℕ) : get (enum s) n = (n, s.get n) :=
rfl
#align stream.nth_enum Stream'.get_enum
theorem enum_eq_zip (s : Stream' α) : enum s = zip Prod.mk nats s :=
rfl
#align stream.enum_eq_zip Stream'.enum_eq_zip
end Zip
@[simp]
theorem mem_const (a : α) : a ∈ const a :=
Exists.intro 0 rfl
#align stream.mem_const Stream'.mem_const
theorem const_eq (a : α) : const a = a::const a := by
apply Stream'.ext; intro n
cases n <;> rfl
#align stream.const_eq Stream'.const_eq
@[simp]
theorem tail_const (a : α) : tail (const a) = const a :=
suffices tail (a::const a) = const a by rwa [← const_eq] at this
rfl
#align stream.tail_const Stream'.tail_const
@[simp]
theorem map_const (f : α → β) (a : α) : map f (const a) = const (f a) :=
rfl
#align stream.map_const Stream'.map_const
@[simp]
theorem get_const (n : Nat) (a : α) : get (const a) n = a :=
rfl
#align stream.nth_const Stream'.get_const
@[simp]
theorem drop_const (n : Nat) (a : α) : drop n (const a) = const a :=
Stream'.ext fun _ => rfl
#align stream.drop_const Stream'.drop_const
@[simp]
theorem head_iterate (f : α → α) (a : α) : head (iterate f a) = a :=
rfl
#align stream.head_iterate Stream'.head_iterate
theorem get_succ_iterate' (n : Nat) (f : α → α) (a : α) :
get (iterate f a) (succ n) = f (get (iterate f a) n) := rfl
theorem tail_iterate (f : α → α) (a : α) : tail (iterate f a) = iterate f (f a) := by
ext n
rw [get_tail]
induction' n with n' ih
· rfl
· rw [get_succ_iterate', ih, get_succ_iterate']
#align stream.tail_iterate Stream'.tail_iterate
theorem iterate_eq (f : α → α) (a : α) : iterate f a = a::iterate f (f a) := by
rw [← Stream'.eta (iterate f a)]
rw [tail_iterate]; rfl
#align stream.iterate_eq Stream'.iterate_eq
@[simp]
theorem get_zero_iterate (f : α → α) (a : α) : get (iterate f a) 0 = a :=
rfl
#align stream.nth_zero_iterate Stream'.get_zero_iterate
theorem get_succ_iterate (n : Nat) (f : α → α) (a : α) :
get (iterate f a) (succ n) = get (iterate f (f a)) n := by rw [get_succ, tail_iterate]
#align stream.nth_succ_iterate Stream'.get_succ_iterate
section Bisim
variable (R : Stream' α → Stream' α → Prop)
/-- equivalence relation -/
local infixl:50 " ~ " => R
/-- Streams `s₁` and `s₂` are defined to be bisimulations if
their heads are equal and tails are bisimulations. -/
def IsBisimulation :=
∀ ⦃s₁ s₂⦄, s₁ ~ s₂ →
head s₁ = head s₂ ∧ tail s₁ ~ tail s₂
#align stream.is_bisimulation Stream'.IsBisimulation
theorem get_of_bisim (bisim : IsBisimulation R) :
∀ {s₁ s₂} (n), s₁ ~ s₂ → get s₁ n = get s₂ n ∧ drop (n + 1) s₁ ~ drop (n + 1) s₂
| _, _, 0, h => bisim h
| _, _, n + 1, h =>
match bisim h with
| ⟨_, trel⟩ => get_of_bisim bisim n trel
#align stream.nth_of_bisim Stream'.get_of_bisim
-- If two streams are bisimilar, then they are equal
theorem eq_of_bisim (bisim : IsBisimulation R) : ∀ {s₁ s₂}, s₁ ~ s₂ → s₁ = s₂ := fun r =>
Stream'.ext fun n => And.left (get_of_bisim R bisim n r)
#align stream.eq_of_bisim Stream'.eq_of_bisim
end Bisim
theorem bisim_simple (s₁ s₂ : Stream' α) :
head s₁ = head s₂ → s₁ = tail s₁ → s₂ = tail s₂ → s₁ = s₂ := fun hh ht₁ ht₂ =>
eq_of_bisim (fun s₁ s₂ => head s₁ = head s₂ ∧ s₁ = tail s₁ ∧ s₂ = tail s₂)
(fun s₁ s₂ ⟨h₁, h₂, h₃⟩ => by
constructor
· exact h₁
rw [← h₂, ← h₃]
(repeat' constructor) <;> assumption)
(And.intro hh (And.intro ht₁ ht₂))
#align stream.bisim_simple Stream'.bisim_simple
theorem coinduction {s₁ s₂ : Stream' α} :
head s₁ = head s₂ →
(∀ (β : Type u) (fr : Stream' α → β),
fr s₁ = fr s₂ → fr (tail s₁) = fr (tail s₂)) → s₁ = s₂ :=
fun hh ht =>
eq_of_bisim
(fun s₁ s₂ =>
head s₁ = head s₂ ∧
∀ (β : Type u) (fr : Stream' α → β), fr s₁ = fr s₂ → fr (tail s₁) = fr (tail s₂))
(fun s₁ s₂ h =>
have h₁ : head s₁ = head s₂ := And.left h
have h₂ : head (tail s₁) = head (tail s₂) := And.right h α (@head α) h₁
have h₃ :
∀ (β : Type u) (fr : Stream' α → β),
fr (tail s₁) = fr (tail s₂) → fr (tail (tail s₁)) = fr (tail (tail s₂)) :=
fun β fr => And.right h β fun s => fr (tail s)
And.intro h₁ (And.intro h₂ h₃))
(And.intro hh ht)
#align stream.coinduction Stream'.coinduction
@[simp]
theorem iterate_id (a : α) : iterate id a = const a :=
coinduction rfl fun β fr ch => by rw [tail_iterate, tail_const]; exact ch
#align stream.iterate_id Stream'.iterate_id
| Mathlib/Data/Stream/Init.lean | 361 | 368 | theorem map_iterate (f : α → α) (a : α) : iterate f (f a) = map f (iterate f a) := by |
funext n
induction' n with n' ih
· rfl
· unfold map iterate get
rw [map, get] at ih
rw [iterate]
exact congrArg f ih
|
/-
Copyright (c) 2022 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Joël Riou
-/
import Mathlib.CategoryTheory.CommSq
import Mathlib.CategoryTheory.Limits.Opposites
import Mathlib.CategoryTheory.Limits.Shapes.Biproducts
import Mathlib.CategoryTheory.Limits.Shapes.ZeroMorphisms
import Mathlib.CategoryTheory.Limits.Constructions.BinaryProducts
import Mathlib.CategoryTheory.Limits.Constructions.ZeroObjects
#align_import category_theory.limits.shapes.comm_sq from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Pullback and pushout squares, and bicartesian squares
We provide another API for pullbacks and pushouts.
`IsPullback fst snd f g` is the proposition that
```
P --fst--> X
| |
snd f
| |
v v
Y ---g---> Z
```
is a pullback square.
(And similarly for `IsPushout`.)
We provide the glue to go back and forth to the usual `IsLimit` API for pullbacks, and prove
`IsPullback (pullback.fst : pullback f g ⟶ X) (pullback.snd : pullback f g ⟶ Y) f g`
for the usual `pullback f g` provided by the `HasLimit` API.
We don't attempt to restate everything we know about pullbacks in this language,
but do restate the pasting lemmas.
We define bicartesian squares, and
show that the pullback and pushout squares for a biproduct are bicartesian.
-/
noncomputable section
open CategoryTheory
open CategoryTheory.Limits
universe v₁ v₂ u₁ u₂
namespace CategoryTheory
variable {C : Type u₁} [Category.{v₁} C]
attribute [simp] CommSq.mk
namespace CommSq
variable {W X Y Z : C} {f : W ⟶ X} {g : W ⟶ Y} {h : X ⟶ Z} {i : Y ⟶ Z}
/-- The (not necessarily limiting) `PullbackCone h i` implicit in the statement
that we have `CommSq f g h i`.
-/
def cone (s : CommSq f g h i) : PullbackCone h i :=
PullbackCone.mk _ _ s.w
#align category_theory.comm_sq.cone CategoryTheory.CommSq.cone
/-- The (not necessarily limiting) `PushoutCocone f g` implicit in the statement
that we have `CommSq f g h i`.
-/
def cocone (s : CommSq f g h i) : PushoutCocone f g :=
PushoutCocone.mk _ _ s.w
#align category_theory.comm_sq.cocone CategoryTheory.CommSq.cocone
@[simp]
theorem cone_fst (s : CommSq f g h i) : s.cone.fst = f :=
rfl
#align category_theory.comm_sq.cone_fst CategoryTheory.CommSq.cone_fst
@[simp]
theorem cone_snd (s : CommSq f g h i) : s.cone.snd = g :=
rfl
#align category_theory.comm_sq.cone_snd CategoryTheory.CommSq.cone_snd
@[simp]
theorem cocone_inl (s : CommSq f g h i) : s.cocone.inl = h :=
rfl
#align category_theory.comm_sq.cocone_inl CategoryTheory.CommSq.cocone_inl
@[simp]
theorem cocone_inr (s : CommSq f g h i) : s.cocone.inr = i :=
rfl
#align category_theory.comm_sq.cocone_inr CategoryTheory.CommSq.cocone_inr
/-- The pushout cocone in the opposite category associated to the cone of
a commutative square identifies to the cocone of the flipped commutative square in
the opposite category -/
def coneOp (p : CommSq f g h i) : p.cone.op ≅ p.flip.op.cocone :=
PushoutCocone.ext (Iso.refl _) (by aesop_cat) (by aesop_cat)
#align category_theory.comm_sq.cone_op CategoryTheory.CommSq.coneOp
/-- The pullback cone in the opposite category associated to the cocone of
a commutative square identifies to the cone of the flipped commutative square in
the opposite category -/
def coconeOp (p : CommSq f g h i) : p.cocone.op ≅ p.flip.op.cone :=
PullbackCone.ext (Iso.refl _) (by aesop_cat) (by aesop_cat)
#align category_theory.comm_sq.cocone_op CategoryTheory.CommSq.coconeOp
/-- The pushout cocone obtained from the pullback cone associated to a
commutative square in the opposite category identifies to the cocone associated
to the flipped square. -/
def coneUnop {W X Y Z : Cᵒᵖ} {f : W ⟶ X} {g : W ⟶ Y} {h : X ⟶ Z} {i : Y ⟶ Z} (p : CommSq f g h i) :
p.cone.unop ≅ p.flip.unop.cocone :=
PushoutCocone.ext (Iso.refl _) (by aesop_cat) (by aesop_cat)
#align category_theory.comm_sq.cone_unop CategoryTheory.CommSq.coneUnop
/-- The pullback cone obtained from the pushout cone associated to a
commutative square in the opposite category identifies to the cone associated
to the flipped square. -/
def coconeUnop {W X Y Z : Cᵒᵖ} {f : W ⟶ X} {g : W ⟶ Y} {h : X ⟶ Z} {i : Y ⟶ Z}
(p : CommSq f g h i) : p.cocone.unop ≅ p.flip.unop.cone :=
PullbackCone.ext (Iso.refl _) (by aesop_cat) (by aesop_cat)
#align category_theory.comm_sq.cocone_unop CategoryTheory.CommSq.coconeUnop
end CommSq
/-- The proposition that a square
```
P --fst--> X
| |
snd f
| |
v v
Y ---g---> Z
```
is a pullback square. (Also known as a fibered product or cartesian square.)
-/
structure IsPullback {P X Y Z : C} (fst : P ⟶ X) (snd : P ⟶ Y) (f : X ⟶ Z) (g : Y ⟶ Z) extends
CommSq fst snd f g : Prop where
/-- the pullback cone is a limit -/
isLimit' : Nonempty (IsLimit (PullbackCone.mk _ _ w))
#align category_theory.is_pullback CategoryTheory.IsPullback
/-- The proposition that a square
```
Z ---f---> X
| |
g inl
| |
v v
Y --inr--> P
```
is a pushout square. (Also known as a fiber coproduct or cocartesian square.)
-/
structure IsPushout {Z X Y P : C} (f : Z ⟶ X) (g : Z ⟶ Y) (inl : X ⟶ P) (inr : Y ⟶ P) extends
CommSq f g inl inr : Prop where
/-- the pushout cocone is a colimit -/
isColimit' : Nonempty (IsColimit (PushoutCocone.mk _ _ w))
#align category_theory.is_pushout CategoryTheory.IsPushout
section
/-- A *bicartesian* square is a commutative square
```
W ---f---> X
| |
g h
| |
v v
Y ---i---> Z
```
that is both a pullback square and a pushout square.
-/
structure BicartesianSq {W X Y Z : C} (f : W ⟶ X) (g : W ⟶ Y) (h : X ⟶ Z) (i : Y ⟶ Z) extends
IsPullback f g h i, IsPushout f g h i : Prop
#align category_theory.bicartesian_sq CategoryTheory.BicartesianSq
-- Lean should make these parent projections as `lemma`, not `def`.
attribute [nolint defLemma docBlame] BicartesianSq.toIsPullback BicartesianSq.toIsPushout
end
/-!
We begin by providing some glue between `IsPullback` and the `IsLimit` and `HasLimit` APIs.
(And similarly for `IsPushout`.)
-/
namespace IsPullback
variable {P X Y Z : C} {fst : P ⟶ X} {snd : P ⟶ Y} {f : X ⟶ Z} {g : Y ⟶ Z}
/-- The (limiting) `PullbackCone f g` implicit in the statement
that we have an `IsPullback fst snd f g`.
-/
def cone (h : IsPullback fst snd f g) : PullbackCone f g :=
h.toCommSq.cone
#align category_theory.is_pullback.cone CategoryTheory.IsPullback.cone
@[simp]
theorem cone_fst (h : IsPullback fst snd f g) : h.cone.fst = fst :=
rfl
#align category_theory.is_pullback.cone_fst CategoryTheory.IsPullback.cone_fst
@[simp]
theorem cone_snd (h : IsPullback fst snd f g) : h.cone.snd = snd :=
rfl
#align category_theory.is_pullback.cone_snd CategoryTheory.IsPullback.cone_snd
/-- The cone obtained from `IsPullback fst snd f g` is a limit cone.
-/
noncomputable def isLimit (h : IsPullback fst snd f g) : IsLimit h.cone :=
h.isLimit'.some
#align category_theory.is_pullback.is_limit CategoryTheory.IsPullback.isLimit
/-- If `c` is a limiting pullback cone, then we have an `IsPullback c.fst c.snd f g`. -/
theorem of_isLimit {c : PullbackCone f g} (h : Limits.IsLimit c) : IsPullback c.fst c.snd f g :=
{ w := c.condition
isLimit' := ⟨IsLimit.ofIsoLimit h (Limits.PullbackCone.ext (Iso.refl _)
(by aesop_cat) (by aesop_cat))⟩ }
#align category_theory.is_pullback.of_is_limit CategoryTheory.IsPullback.of_isLimit
/-- A variant of `of_isLimit` that is more useful with `apply`. -/
theorem of_isLimit' (w : CommSq fst snd f g) (h : Limits.IsLimit w.cone) :
IsPullback fst snd f g :=
of_isLimit h
#align category_theory.is_pullback.of_is_limit' CategoryTheory.IsPullback.of_isLimit'
/-- The pullback provided by `HasPullback f g` fits into an `IsPullback`. -/
theorem of_hasPullback (f : X ⟶ Z) (g : Y ⟶ Z) [HasPullback f g] :
IsPullback (pullback.fst : pullback f g ⟶ X) (pullback.snd : pullback f g ⟶ Y) f g :=
of_isLimit (limit.isLimit (cospan f g))
#align category_theory.is_pullback.of_has_pullback CategoryTheory.IsPullback.of_hasPullback
/-- If `c` is a limiting binary product cone, and we have a terminal object,
then we have `IsPullback c.fst c.snd 0 0`
(where each `0` is the unique morphism to the terminal object). -/
theorem of_is_product {c : BinaryFan X Y} (h : Limits.IsLimit c) (t : IsTerminal Z) :
IsPullback c.fst c.snd (t.from _) (t.from _) :=
of_isLimit
(isPullbackOfIsTerminalIsProduct _ _ _ _ t
(IsLimit.ofIsoLimit h
(Limits.Cones.ext (Iso.refl c.pt)
(by
rintro ⟨⟨⟩⟩ <;>
· dsimp
simp))))
#align category_theory.is_pullback.of_is_product CategoryTheory.IsPullback.of_is_product
/-- A variant of `of_is_product` that is more useful with `apply`. -/
theorem of_is_product' (h : Limits.IsLimit (BinaryFan.mk fst snd)) (t : IsTerminal Z) :
IsPullback fst snd (t.from _) (t.from _) :=
of_is_product h t
#align category_theory.is_pullback.of_is_product' CategoryTheory.IsPullback.of_is_product'
variable (X Y)
theorem of_hasBinaryProduct' [HasBinaryProduct X Y] [HasTerminal C] :
IsPullback Limits.prod.fst Limits.prod.snd (terminal.from X) (terminal.from Y) :=
of_is_product (limit.isLimit _) terminalIsTerminal
#align category_theory.is_pullback.of_has_binary_product' CategoryTheory.IsPullback.of_hasBinaryProduct'
open ZeroObject
theorem of_hasBinaryProduct [HasBinaryProduct X Y] [HasZeroObject C] [HasZeroMorphisms C] :
IsPullback Limits.prod.fst Limits.prod.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) := by
convert @of_is_product _ _ X Y 0 _ (limit.isLimit _) HasZeroObject.zeroIsTerminal
<;> apply Subsingleton.elim
#align category_theory.is_pullback.of_has_binary_product CategoryTheory.IsPullback.of_hasBinaryProduct
variable {X Y}
/-- Any object at the top left of a pullback square is
isomorphic to the pullback provided by the `HasLimit` API. -/
noncomputable def isoPullback (h : IsPullback fst snd f g) [HasPullback f g] : P ≅ pullback f g :=
(limit.isoLimitCone ⟨_, h.isLimit⟩).symm
#align category_theory.is_pullback.iso_pullback CategoryTheory.IsPullback.isoPullback
@[simp]
theorem isoPullback_hom_fst (h : IsPullback fst snd f g) [HasPullback f g] :
h.isoPullback.hom ≫ pullback.fst = fst := by
dsimp [isoPullback, cone, CommSq.cone]
simp
#align category_theory.is_pullback.iso_pullback_hom_fst CategoryTheory.IsPullback.isoPullback_hom_fst
@[simp]
theorem isoPullback_hom_snd (h : IsPullback fst snd f g) [HasPullback f g] :
h.isoPullback.hom ≫ pullback.snd = snd := by
dsimp [isoPullback, cone, CommSq.cone]
simp
#align category_theory.is_pullback.iso_pullback_hom_snd CategoryTheory.IsPullback.isoPullback_hom_snd
@[simp]
theorem isoPullback_inv_fst (h : IsPullback fst snd f g) [HasPullback f g] :
h.isoPullback.inv ≫ fst = pullback.fst := by simp [Iso.inv_comp_eq]
#align category_theory.is_pullback.iso_pullback_inv_fst CategoryTheory.IsPullback.isoPullback_inv_fst
@[simp]
theorem isoPullback_inv_snd (h : IsPullback fst snd f g) [HasPullback f g] :
h.isoPullback.inv ≫ snd = pullback.snd := by simp [Iso.inv_comp_eq]
#align category_theory.is_pullback.iso_pullback_inv_snd CategoryTheory.IsPullback.isoPullback_inv_snd
theorem of_iso_pullback (h : CommSq fst snd f g) [HasPullback f g] (i : P ≅ pullback f g)
(w₁ : i.hom ≫ pullback.fst = fst) (w₂ : i.hom ≫ pullback.snd = snd) : IsPullback fst snd f g :=
of_isLimit' h
(Limits.IsLimit.ofIsoLimit (limit.isLimit _)
(@PullbackCone.ext _ _ _ _ _ _ _ (PullbackCone.mk _ _ _) _ i w₁.symm w₂.symm).symm)
#align category_theory.is_pullback.of_iso_pullback CategoryTheory.IsPullback.of_iso_pullback
theorem of_horiz_isIso [IsIso fst] [IsIso g] (sq : CommSq fst snd f g) : IsPullback fst snd f g :=
of_isLimit' sq
(by
refine
PullbackCone.IsLimit.mk _ (fun s => s.fst ≫ inv fst) (by aesop_cat)
(fun s => ?_) (by aesop_cat)
simp only [← cancel_mono g, Category.assoc, ← sq.w, IsIso.inv_hom_id_assoc, s.condition])
#align category_theory.is_pullback.of_horiz_is_iso CategoryTheory.IsPullback.of_horiz_isIso
end IsPullback
namespace IsPushout
variable {Z X Y P : C} {f : Z ⟶ X} {g : Z ⟶ Y} {inl : X ⟶ P} {inr : Y ⟶ P}
/-- The (colimiting) `PushoutCocone f g` implicit in the statement
that we have an `IsPushout f g inl inr`.
-/
def cocone (h : IsPushout f g inl inr) : PushoutCocone f g :=
h.toCommSq.cocone
#align category_theory.is_pushout.cocone CategoryTheory.IsPushout.cocone
@[simp]
theorem cocone_inl (h : IsPushout f g inl inr) : h.cocone.inl = inl :=
rfl
#align category_theory.is_pushout.cocone_inl CategoryTheory.IsPushout.cocone_inl
@[simp]
theorem cocone_inr (h : IsPushout f g inl inr) : h.cocone.inr = inr :=
rfl
#align category_theory.is_pushout.cocone_inr CategoryTheory.IsPushout.cocone_inr
/-- The cocone obtained from `IsPushout f g inl inr` is a colimit cocone.
-/
noncomputable def isColimit (h : IsPushout f g inl inr) : IsColimit h.cocone :=
h.isColimit'.some
#align category_theory.is_pushout.is_colimit CategoryTheory.IsPushout.isColimit
/-- If `c` is a colimiting pushout cocone, then we have an `IsPushout f g c.inl c.inr`. -/
theorem of_isColimit {c : PushoutCocone f g} (h : Limits.IsColimit c) : IsPushout f g c.inl c.inr :=
{ w := c.condition
isColimit' :=
⟨IsColimit.ofIsoColimit h (Limits.PushoutCocone.ext (Iso.refl _)
(by aesop_cat) (by aesop_cat))⟩ }
#align category_theory.is_pushout.of_is_colimit CategoryTheory.IsPushout.of_isColimit
/-- A variant of `of_isColimit` that is more useful with `apply`. -/
theorem of_isColimit' (w : CommSq f g inl inr) (h : Limits.IsColimit w.cocone) :
IsPushout f g inl inr :=
of_isColimit h
#align category_theory.is_pushout.of_is_colimit' CategoryTheory.IsPushout.of_isColimit'
/-- The pushout provided by `HasPushout f g` fits into an `IsPushout`. -/
theorem of_hasPushout (f : Z ⟶ X) (g : Z ⟶ Y) [HasPushout f g] :
IsPushout f g (pushout.inl : X ⟶ pushout f g) (pushout.inr : Y ⟶ pushout f g) :=
of_isColimit (colimit.isColimit (span f g))
#align category_theory.is_pushout.of_has_pushout CategoryTheory.IsPushout.of_hasPushout
/-- If `c` is a colimiting binary coproduct cocone, and we have an initial object,
then we have `IsPushout 0 0 c.inl c.inr`
(where each `0` is the unique morphism from the initial object). -/
theorem of_is_coproduct {c : BinaryCofan X Y} (h : Limits.IsColimit c) (t : IsInitial Z) :
IsPushout (t.to _) (t.to _) c.inl c.inr :=
of_isColimit
(isPushoutOfIsInitialIsCoproduct _ _ _ _ t
(IsColimit.ofIsoColimit h
(Limits.Cocones.ext (Iso.refl c.pt)
(by
rintro ⟨⟨⟩⟩ <;>
· dsimp
simp))))
#align category_theory.is_pushout.of_is_coproduct CategoryTheory.IsPushout.of_is_coproduct
/-- A variant of `of_is_coproduct` that is more useful with `apply`. -/
theorem of_is_coproduct' (h : Limits.IsColimit (BinaryCofan.mk inl inr)) (t : IsInitial Z) :
IsPushout (t.to _) (t.to _) inl inr :=
of_is_coproduct h t
#align category_theory.is_pushout.of_is_coproduct' CategoryTheory.IsPushout.of_is_coproduct'
variable (X Y)
theorem of_hasBinaryCoproduct' [HasBinaryCoproduct X Y] [HasInitial C] :
IsPushout (initial.to _) (initial.to _) (coprod.inl : X ⟶ _) (coprod.inr : Y ⟶ _) :=
of_is_coproduct (colimit.isColimit _) initialIsInitial
#align category_theory.is_pushout.of_has_binary_coproduct' CategoryTheory.IsPushout.of_hasBinaryCoproduct'
open ZeroObject
theorem of_hasBinaryCoproduct [HasBinaryCoproduct X Y] [HasZeroObject C] [HasZeroMorphisms C] :
IsPushout (0 : 0 ⟶ X) (0 : 0 ⟶ Y) coprod.inl coprod.inr := by
convert @of_is_coproduct _ _ 0 X Y _ (colimit.isColimit _) HasZeroObject.zeroIsInitial
<;> apply Subsingleton.elim
#align category_theory.is_pushout.of_has_binary_coproduct CategoryTheory.IsPushout.of_hasBinaryCoproduct
variable {X Y}
/-- Any object at the top left of a pullback square is
isomorphic to the pullback provided by the `HasLimit` API. -/
noncomputable def isoPushout (h : IsPushout f g inl inr) [HasPushout f g] : P ≅ pushout f g :=
(colimit.isoColimitCocone ⟨_, h.isColimit⟩).symm
#align category_theory.is_pushout.iso_pushout CategoryTheory.IsPushout.isoPushout
@[simp]
theorem inl_isoPushout_inv (h : IsPushout f g inl inr) [HasPushout f g] :
pushout.inl ≫ h.isoPushout.inv = inl := by
dsimp [isoPushout, cocone, CommSq.cocone]
simp
#align category_theory.is_pushout.inl_iso_pushout_inv CategoryTheory.IsPushout.inl_isoPushout_inv
@[simp]
theorem inr_isoPushout_inv (h : IsPushout f g inl inr) [HasPushout f g] :
pushout.inr ≫ h.isoPushout.inv = inr := by
dsimp [isoPushout, cocone, CommSq.cocone]
simp
#align category_theory.is_pushout.inr_iso_pushout_inv CategoryTheory.IsPushout.inr_isoPushout_inv
@[simp]
theorem inl_isoPushout_hom (h : IsPushout f g inl inr) [HasPushout f g] :
inl ≫ h.isoPushout.hom = pushout.inl := by simp [← Iso.eq_comp_inv]
#align category_theory.is_pushout.inl_iso_pushout_hom CategoryTheory.IsPushout.inl_isoPushout_hom
@[simp]
theorem inr_isoPushout_hom (h : IsPushout f g inl inr) [HasPushout f g] :
inr ≫ h.isoPushout.hom = pushout.inr := by simp [← Iso.eq_comp_inv]
#align category_theory.is_pushout.inr_iso_pushout_hom CategoryTheory.IsPushout.inr_isoPushout_hom
theorem of_iso_pushout (h : CommSq f g inl inr) [HasPushout f g] (i : P ≅ pushout f g)
(w₁ : inl ≫ i.hom = pushout.inl) (w₂ : inr ≫ i.hom = pushout.inr) : IsPushout f g inl inr :=
of_isColimit' h
(Limits.IsColimit.ofIsoColimit (colimit.isColimit _)
(PushoutCocone.ext (s := PushoutCocone.mk ..) i w₁ w₂).symm)
#align category_theory.is_pushout.of_iso_pushout CategoryTheory.IsPushout.of_iso_pushout
end IsPushout
namespace IsPullback
variable {P X Y Z : C} {fst : P ⟶ X} {snd : P ⟶ Y} {f : X ⟶ Z} {g : Y ⟶ Z}
theorem flip (h : IsPullback fst snd f g) : IsPullback snd fst g f :=
of_isLimit (PullbackCone.flipIsLimit h.isLimit)
#align category_theory.is_pullback.flip CategoryTheory.IsPullback.flip
theorem flip_iff : IsPullback fst snd f g ↔ IsPullback snd fst g f :=
⟨flip, flip⟩
#align category_theory.is_pullback.flip_iff CategoryTheory.IsPullback.flip_iff
section
variable [HasZeroObject C] [HasZeroMorphisms C]
open ZeroObject
/-- The square with `0 : 0 ⟶ 0` on the left and `𝟙 X` on the right is a pullback square. -/
@[simp]
theorem zero_left (X : C) : IsPullback (0 : 0 ⟶ X) (0 : (0 : C) ⟶ 0) (𝟙 X) (0 : 0 ⟶ X) :=
{ w := by simp
isLimit' :=
⟨{ lift := fun s => 0
fac := fun s => by
simpa [eq_iff_true_of_subsingleton] using
@PullbackCone.equalizer_ext _ _ _ _ _ _ _ s _ 0 (𝟙 _)
(by simpa using (PullbackCone.condition s).symm) }⟩ }
#align category_theory.is_pullback.zero_left CategoryTheory.IsPullback.zero_left
/-- The square with `0 : 0 ⟶ 0` on the top and `𝟙 X` on the bottom is a pullback square. -/
@[simp]
theorem zero_top (X : C) : IsPullback (0 : (0 : C) ⟶ 0) (0 : 0 ⟶ X) (0 : 0 ⟶ X) (𝟙 X) :=
(zero_left X).flip
#align category_theory.is_pullback.zero_top CategoryTheory.IsPullback.zero_top
/-- The square with `0 : 0 ⟶ 0` on the right and `𝟙 X` on the left is a pullback square. -/
@[simp]
theorem zero_right (X : C) : IsPullback (0 : X ⟶ 0) (𝟙 X) (0 : (0 : C) ⟶ 0) (0 : X ⟶ 0) :=
of_iso_pullback (by simp) ((zeroProdIso X).symm ≪≫ (pullbackZeroZeroIso _ _).symm)
(by simp [eq_iff_true_of_subsingleton]) (by simp)
#align category_theory.is_pullback.zero_right CategoryTheory.IsPullback.zero_right
/-- The square with `0 : 0 ⟶ 0` on the bottom and `𝟙 X` on the top is a pullback square. -/
@[simp]
theorem zero_bot (X : C) : IsPullback (𝟙 X) (0 : X ⟶ 0) (0 : X ⟶ 0) (0 : (0 : C) ⟶ 0) :=
(zero_right X).flip
#align category_theory.is_pullback.zero_bot CategoryTheory.IsPullback.zero_bot
end
-- Objects here are arranged in a 3x2 grid, and indexed by their xy coordinates.
-- Morphisms are named `hᵢⱼ` for a horizontal morphism starting at `(i,j)`,
-- and `vᵢⱼ` for a vertical morphism starting at `(i,j)`.
/-- Paste two pullback squares "vertically" to obtain another pullback square. -/
theorem paste_vert {X₁₁ X₁₂ X₂₁ X₂₂ X₃₁ X₃₂ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₂₁ : X₂₁ ⟶ X₂₂}
{h₃₁ : X₃₁ ⟶ X₃₂} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₂₁ : X₂₁ ⟶ X₃₁} {v₂₂ : X₂₂ ⟶ X₃₂}
(s : IsPullback h₁₁ v₁₁ v₁₂ h₂₁) (t : IsPullback h₂₁ v₂₁ v₂₂ h₃₁) :
IsPullback h₁₁ (v₁₁ ≫ v₂₁) (v₁₂ ≫ v₂₂) h₃₁ :=
of_isLimit (bigSquareIsPullback _ _ _ _ _ _ _ s.w t.w t.isLimit s.isLimit)
#align category_theory.is_pullback.paste_vert CategoryTheory.IsPullback.paste_vert
/-- Paste two pullback squares "horizontally" to obtain another pullback square. -/
theorem paste_horiz {X₁₁ X₁₂ X₁₃ X₂₁ X₂₂ X₂₃ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₁₂ : X₁₂ ⟶ X₁₃}
{h₂₁ : X₂₁ ⟶ X₂₂} {h₂₂ : X₂₂ ⟶ X₂₃} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₁₃ : X₁₃ ⟶ X₂₃}
(s : IsPullback h₁₁ v₁₁ v₁₂ h₂₁) (t : IsPullback h₁₂ v₁₂ v₁₃ h₂₂) :
IsPullback (h₁₁ ≫ h₁₂) v₁₁ v₁₃ (h₂₁ ≫ h₂₂) :=
(paste_vert s.flip t.flip).flip
#align category_theory.is_pullback.paste_horiz CategoryTheory.IsPullback.paste_horiz
/-- Given a pullback square assembled from a commuting square on the top and
a pullback square on the bottom, the top square is a pullback square. -/
theorem of_bot {X₁₁ X₁₂ X₂₁ X₂₂ X₃₁ X₃₂ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₂₁ : X₂₁ ⟶ X₂₂} {h₃₁ : X₃₁ ⟶ X₃₂}
{v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₂₁ : X₂₁ ⟶ X₃₁} {v₂₂ : X₂₂ ⟶ X₃₂}
(s : IsPullback h₁₁ (v₁₁ ≫ v₂₁) (v₁₂ ≫ v₂₂) h₃₁) (p : h₁₁ ≫ v₁₂ = v₁₁ ≫ h₂₁)
(t : IsPullback h₂₁ v₂₁ v₂₂ h₃₁) : IsPullback h₁₁ v₁₁ v₁₂ h₂₁ :=
of_isLimit (leftSquareIsPullback _ _ _ _ _ _ _ p t.w t.isLimit s.isLimit)
#align category_theory.is_pullback.of_bot CategoryTheory.IsPullback.of_bot
/-- Given a pullback square assembled from a commuting square on the left and
a pullback square on the right, the left square is a pullback square. -/
theorem of_right {X₁₁ X₁₂ X₁₃ X₂₁ X₂₂ X₂₃ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₁₂ : X₁₂ ⟶ X₁₃} {h₂₁ : X₂₁ ⟶ X₂₂}
{h₂₂ : X₂₂ ⟶ X₂₃} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₁₃ : X₁₃ ⟶ X₂₃}
(s : IsPullback (h₁₁ ≫ h₁₂) v₁₁ v₁₃ (h₂₁ ≫ h₂₂)) (p : h₁₁ ≫ v₁₂ = v₁₁ ≫ h₂₁)
(t : IsPullback h₁₂ v₁₂ v₁₃ h₂₂) : IsPullback h₁₁ v₁₁ v₁₂ h₂₁ :=
(of_bot s.flip p.symm t.flip).flip
#align category_theory.is_pullback.of_right CategoryTheory.IsPullback.of_right
theorem paste_vert_iff {X₁₁ X₁₂ X₂₁ X₂₂ X₃₁ X₃₂ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₂₁ : X₂₁ ⟶ X₂₂}
{h₃₁ : X₃₁ ⟶ X₃₂} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₂₁ : X₂₁ ⟶ X₃₁} {v₂₂ : X₂₂ ⟶ X₃₂}
(s : IsPullback h₂₁ v₂₁ v₂₂ h₃₁) (e : h₁₁ ≫ v₁₂ = v₁₁ ≫ h₂₁) :
IsPullback h₁₁ (v₁₁ ≫ v₂₁) (v₁₂ ≫ v₂₂) h₃₁ ↔ IsPullback h₁₁ v₁₁ v₁₂ h₂₁ :=
⟨fun h => h.of_bot e s, fun h => h.paste_vert s⟩
#align category_theory.is_pullback.paste_vert_iff CategoryTheory.IsPullback.paste_vert_iff
theorem paste_horiz_iff {X₁₁ X₁₂ X₁₃ X₂₁ X₂₂ X₂₃ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₁₂ : X₁₂ ⟶ X₁₃}
{h₂₁ : X₂₁ ⟶ X₂₂} {h₂₂ : X₂₂ ⟶ X₂₃} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₁₃ : X₁₃ ⟶ X₂₃}
(s : IsPullback h₁₂ v₁₂ v₁₃ h₂₂) (e : h₁₁ ≫ v₁₂ = v₁₁ ≫ h₂₁) :
IsPullback (h₁₁ ≫ h₁₂) v₁₁ v₁₃ (h₂₁ ≫ h₂₂) ↔ IsPullback h₁₁ v₁₁ v₁₂ h₂₁ :=
⟨fun h => h.of_right e s, fun h => h.paste_horiz s⟩
#align category_theory.is_pullback.paste_horiz_iff CategoryTheory.IsPullback.paste_horiz_iff
section
variable [HasZeroObject C] [HasZeroMorphisms C]
open ZeroObject
theorem of_isBilimit {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPullback b.fst b.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) := by
convert IsPullback.of_is_product' h.isLimit HasZeroObject.zeroIsTerminal
<;> apply Subsingleton.elim
#align category_theory.is_pullback.of_is_bilimit CategoryTheory.IsPullback.of_isBilimit
@[simp]
theorem of_has_biproduct (X Y : C) [HasBinaryBiproduct X Y] :
IsPullback biprod.fst biprod.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) :=
of_isBilimit (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pullback.of_has_biproduct CategoryTheory.IsPullback.of_has_biproduct
theorem inl_snd' {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPullback b.inl (0 : X ⟶ 0) b.snd (0 : 0 ⟶ Y) := by
refine of_right ?_ (by simp) (of_isBilimit h)
simp
#align category_theory.is_pullback.inl_snd' CategoryTheory.IsPullback.inl_snd'
/-- The square
```
X --inl--> X ⊞ Y
| |
0 snd
| |
v v
0 ---0-----> Y
```
is a pullback square.
-/
@[simp]
theorem inl_snd (X Y : C) [HasBinaryBiproduct X Y] :
IsPullback biprod.inl (0 : X ⟶ 0) biprod.snd (0 : 0 ⟶ Y) :=
inl_snd' (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pullback.inl_snd CategoryTheory.IsPullback.inl_snd
theorem inr_fst' {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPullback b.inr (0 : Y ⟶ 0) b.fst (0 : 0 ⟶ X) := by
apply flip
refine of_bot ?_ (by simp) (of_isBilimit h)
simp
#align category_theory.is_pullback.inr_fst' CategoryTheory.IsPullback.inr_fst'
/-- The square
```
Y --inr--> X ⊞ Y
| |
0 fst
| |
v v
0 ---0-----> X
```
is a pullback square.
-/
@[simp]
theorem inr_fst (X Y : C) [HasBinaryBiproduct X Y] :
IsPullback biprod.inr (0 : Y ⟶ 0) biprod.fst (0 : 0 ⟶ X) :=
inr_fst' (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pullback.inr_fst CategoryTheory.IsPullback.inr_fst
theorem of_is_bilimit' {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPullback (0 : 0 ⟶ X) (0 : 0 ⟶ Y) b.inl b.inr := by
refine IsPullback.of_right ?_ (by simp) (IsPullback.inl_snd' h).flip
simp
#align category_theory.is_pullback.of_is_bilimit' CategoryTheory.IsPullback.of_is_bilimit'
theorem of_hasBinaryBiproduct (X Y : C) [HasBinaryBiproduct X Y] :
IsPullback (0 : 0 ⟶ X) (0 : 0 ⟶ Y) biprod.inl biprod.inr :=
of_is_bilimit' (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pullback.of_has_binary_biproduct CategoryTheory.IsPullback.of_hasBinaryBiproduct
instance hasPullback_biprod_fst_biprod_snd [HasBinaryBiproduct X Y] :
HasPullback (biprod.inl : X ⟶ _) (biprod.inr : Y ⟶ _) :=
HasLimit.mk ⟨_, (of_hasBinaryBiproduct X Y).isLimit⟩
#align category_theory.is_pullback.has_pullback_biprod_fst_biprod_snd CategoryTheory.IsPullback.hasPullback_biprod_fst_biprod_snd
/-- The pullback of `biprod.inl` and `biprod.inr` is the zero object. -/
def pullbackBiprodInlBiprodInr [HasBinaryBiproduct X Y] :
pullback (biprod.inl : X ⟶ _) (biprod.inr : Y ⟶ _) ≅ 0 :=
limit.isoLimitCone ⟨_, (of_hasBinaryBiproduct X Y).isLimit⟩
#align category_theory.is_pullback.pullback_biprod_inl_biprod_inr CategoryTheory.IsPullback.pullbackBiprodInlBiprodInr
end
theorem op (h : IsPullback fst snd f g) : IsPushout g.op f.op snd.op fst.op :=
IsPushout.of_isColimit
(IsColimit.ofIsoColimit (Limits.PullbackCone.isLimitEquivIsColimitOp h.flip.cone h.flip.isLimit)
h.toCommSq.flip.coneOp)
#align category_theory.is_pullback.op CategoryTheory.IsPullback.op
theorem unop {P X Y Z : Cᵒᵖ} {fst : P ⟶ X} {snd : P ⟶ Y} {f : X ⟶ Z} {g : Y ⟶ Z}
(h : IsPullback fst snd f g) : IsPushout g.unop f.unop snd.unop fst.unop :=
IsPushout.of_isColimit
(IsColimit.ofIsoColimit
(Limits.PullbackCone.isLimitEquivIsColimitUnop h.flip.cone h.flip.isLimit)
h.toCommSq.flip.coneUnop)
#align category_theory.is_pullback.unop CategoryTheory.IsPullback.unop
theorem of_vert_isIso [IsIso snd] [IsIso f] (sq : CommSq fst snd f g) : IsPullback fst snd f g :=
IsPullback.flip (of_horiz_isIso sq.flip)
#align category_theory.is_pullback.of_vert_is_iso CategoryTheory.IsPullback.of_vert_isIso
end IsPullback
namespace IsPushout
variable {Z X Y P : C} {f : Z ⟶ X} {g : Z ⟶ Y} {inl : X ⟶ P} {inr : Y ⟶ P}
theorem flip (h : IsPushout f g inl inr) : IsPushout g f inr inl :=
of_isColimit (PushoutCocone.flipIsColimit h.isColimit)
#align category_theory.is_pushout.flip CategoryTheory.IsPushout.flip
theorem flip_iff : IsPushout f g inl inr ↔ IsPushout g f inr inl :=
⟨flip, flip⟩
#align category_theory.is_pushout.flip_iff CategoryTheory.IsPushout.flip_iff
section
variable [HasZeroObject C] [HasZeroMorphisms C]
open ZeroObject
/-- The square with `0 : 0 ⟶ 0` on the right and `𝟙 X` on the left is a pushout square. -/
@[simp]
theorem zero_right (X : C) : IsPushout (0 : X ⟶ 0) (𝟙 X) (0 : (0 : C) ⟶ 0) (0 : X ⟶ 0) :=
{ w := by simp
isColimit' :=
⟨{ desc := fun s => 0
fac := fun s => by
have c :=
@PushoutCocone.coequalizer_ext _ _ _ _ _ _ _ s _ 0 (𝟙 _)
(by simp [eq_iff_true_of_subsingleton]) (by simpa using PushoutCocone.condition s)
dsimp at c
simpa using c }⟩ }
#align category_theory.is_pushout.zero_right CategoryTheory.IsPushout.zero_right
/-- The square with `0 : 0 ⟶ 0` on the bottom and `𝟙 X` on the top is a pushout square. -/
@[simp]
theorem zero_bot (X : C) : IsPushout (𝟙 X) (0 : X ⟶ 0) (0 : X ⟶ 0) (0 : (0 : C) ⟶ 0) :=
(zero_right X).flip
#align category_theory.is_pushout.zero_bot CategoryTheory.IsPushout.zero_bot
/-- The square with `0 : 0 ⟶ 0` on the right left `𝟙 X` on the right is a pushout square. -/
@[simp]
theorem zero_left (X : C) : IsPushout (0 : 0 ⟶ X) (0 : (0 : C) ⟶ 0) (𝟙 X) (0 : 0 ⟶ X) :=
of_iso_pushout (by simp) ((coprodZeroIso X).symm ≪≫ (pushoutZeroZeroIso _ _).symm) (by simp)
(by simp [eq_iff_true_of_subsingleton])
#align category_theory.is_pushout.zero_left CategoryTheory.IsPushout.zero_left
/-- The square with `0 : 0 ⟶ 0` on the top and `𝟙 X` on the bottom is a pushout square. -/
@[simp]
theorem zero_top (X : C) : IsPushout (0 : (0 : C) ⟶ 0) (0 : 0 ⟶ X) (0 : 0 ⟶ X) (𝟙 X) :=
(zero_left X).flip
#align category_theory.is_pushout.zero_top CategoryTheory.IsPushout.zero_top
end
-- Objects here are arranged in a 3x2 grid, and indexed by their xy coordinates.
-- Morphisms are named `hᵢⱼ` for a horizontal morphism starting at `(i,j)`,
-- and `vᵢⱼ` for a vertical morphism starting at `(i,j)`.
/-- Paste two pushout squares "vertically" to obtain another pushout square. -/
theorem paste_vert {X₁₁ X₁₂ X₂₁ X₂₂ X₃₁ X₃₂ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₂₁ : X₂₁ ⟶ X₂₂}
{h₃₁ : X₃₁ ⟶ X₃₂} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₂₁ : X₂₁ ⟶ X₃₁} {v₂₂ : X₂₂ ⟶ X₃₂}
(s : IsPushout h₁₁ v₁₁ v₁₂ h₂₁) (t : IsPushout h₂₁ v₂₁ v₂₂ h₃₁) :
IsPushout h₁₁ (v₁₁ ≫ v₂₁) (v₁₂ ≫ v₂₂) h₃₁ :=
of_isColimit (bigSquareIsPushout _ _ _ _ _ _ _ s.w t.w t.isColimit s.isColimit)
#align category_theory.is_pushout.paste_vert CategoryTheory.IsPushout.paste_vert
/-- Paste two pushout squares "horizontally" to obtain another pushout square. -/
theorem paste_horiz {X₁₁ X₁₂ X₁₃ X₂₁ X₂₂ X₂₃ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₁₂ : X₁₂ ⟶ X₁₃}
{h₂₁ : X₂₁ ⟶ X₂₂} {h₂₂ : X₂₂ ⟶ X₂₃} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₁₃ : X₁₃ ⟶ X₂₃}
(s : IsPushout h₁₁ v₁₁ v₁₂ h₂₁) (t : IsPushout h₁₂ v₁₂ v₁₃ h₂₂) :
IsPushout (h₁₁ ≫ h₁₂) v₁₁ v₁₃ (h₂₁ ≫ h₂₂) :=
(paste_vert s.flip t.flip).flip
#align category_theory.is_pushout.paste_horiz CategoryTheory.IsPushout.paste_horiz
/-- Given a pushout square assembled from a pushout square on the top and
a commuting square on the bottom, the bottom square is a pushout square. -/
theorem of_bot {X₁₁ X₁₂ X₂₁ X₂₂ X₃₁ X₃₂ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₂₁ : X₂₁ ⟶ X₂₂} {h₃₁ : X₃₁ ⟶ X₃₂}
{v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₂₁ : X₂₁ ⟶ X₃₁} {v₂₂ : X₂₂ ⟶ X₃₂}
(s : IsPushout h₁₁ (v₁₁ ≫ v₂₁) (v₁₂ ≫ v₂₂) h₃₁) (p : h₂₁ ≫ v₂₂ = v₂₁ ≫ h₃₁)
(t : IsPushout h₁₁ v₁₁ v₁₂ h₂₁) : IsPushout h₂₁ v₂₁ v₂₂ h₃₁ :=
of_isColimit (rightSquareIsPushout _ _ _ _ _ _ _ t.w p t.isColimit s.isColimit)
#align category_theory.is_pushout.of_bot CategoryTheory.IsPushout.of_bot
/-- Given a pushout square assembled from a pushout square on the left and
a commuting square on the right, the right square is a pushout square. -/
theorem of_right {X₁₁ X₁₂ X₁₃ X₂₁ X₂₂ X₂₃ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₁₂ : X₁₂ ⟶ X₁₃} {h₂₁ : X₂₁ ⟶ X₂₂}
{h₂₂ : X₂₂ ⟶ X₂₃} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₁₃ : X₁₃ ⟶ X₂₃}
(s : IsPushout (h₁₁ ≫ h₁₂) v₁₁ v₁₃ (h₂₁ ≫ h₂₂)) (p : h₁₂ ≫ v₁₃ = v₁₂ ≫ h₂₂)
(t : IsPushout h₁₁ v₁₁ v₁₂ h₂₁) : IsPushout h₁₂ v₁₂ v₁₃ h₂₂ :=
(of_bot s.flip p.symm t.flip).flip
#align category_theory.is_pushout.of_right CategoryTheory.IsPushout.of_right
theorem paste_vert_iff {X₁₁ X₁₂ X₂₁ X₂₂ X₃₁ X₃₂ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₂₁ : X₂₁ ⟶ X₂₂}
{h₃₁ : X₃₁ ⟶ X₃₂} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₂₁ : X₂₁ ⟶ X₃₁} {v₂₂ : X₂₂ ⟶ X₃₂}
(s : IsPushout h₁₁ v₁₁ v₁₂ h₂₁) (e : h₂₁ ≫ v₂₂ = v₂₁ ≫ h₃₁) :
IsPushout h₁₁ (v₁₁ ≫ v₂₁) (v₁₂ ≫ v₂₂) h₃₁ ↔ IsPushout h₂₁ v₂₁ v₂₂ h₃₁ :=
⟨fun h => h.of_bot e s, s.paste_vert⟩
#align category_theory.is_pushout.paste_vert_iff CategoryTheory.IsPushout.paste_vert_iff
theorem paste_horiz_iff {X₁₁ X₁₂ X₁₃ X₂₁ X₂₂ X₂₃ : C} {h₁₁ : X₁₁ ⟶ X₁₂} {h₁₂ : X₁₂ ⟶ X₁₃}
{h₂₁ : X₂₁ ⟶ X₂₂} {h₂₂ : X₂₂ ⟶ X₂₃} {v₁₁ : X₁₁ ⟶ X₂₁} {v₁₂ : X₁₂ ⟶ X₂₂} {v₁₃ : X₁₃ ⟶ X₂₃}
(s : IsPushout h₁₁ v₁₁ v₁₂ h₂₁) (e : h₁₂ ≫ v₁₃ = v₁₂ ≫ h₂₂) :
IsPushout (h₁₁ ≫ h₁₂) v₁₁ v₁₃ (h₂₁ ≫ h₂₂) ↔ IsPushout h₁₂ v₁₂ v₁₃ h₂₂ :=
⟨fun h => h.of_right e s, s.paste_horiz⟩
#align category_theory.is_pushout.paste_horiz_iff CategoryTheory.IsPushout.paste_horiz_iff
section
variable [HasZeroObject C] [HasZeroMorphisms C]
open ZeroObject
theorem of_isBilimit {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPushout (0 : 0 ⟶ X) (0 : 0 ⟶ Y) b.inl b.inr := by
convert IsPushout.of_is_coproduct' h.isColimit HasZeroObject.zeroIsInitial
<;> apply Subsingleton.elim
#align category_theory.is_pushout.of_is_bilimit CategoryTheory.IsPushout.of_isBilimit
@[simp]
theorem of_has_biproduct (X Y : C) [HasBinaryBiproduct X Y] :
IsPushout (0 : 0 ⟶ X) (0 : 0 ⟶ Y) biprod.inl biprod.inr :=
of_isBilimit (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pushout.of_has_biproduct CategoryTheory.IsPushout.of_has_biproduct
theorem inl_snd' {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPushout b.inl (0 : X ⟶ 0) b.snd (0 : 0 ⟶ Y) := by
apply flip
refine of_right ?_ (by simp) (of_isBilimit h)
simp
#align category_theory.is_pushout.inl_snd' CategoryTheory.IsPushout.inl_snd'
/-- The square
```
X --inl--> X ⊞ Y
| |
0 snd
| |
v v
0 ---0-----> Y
```
is a pushout square.
-/
theorem inl_snd (X Y : C) [HasBinaryBiproduct X Y] :
IsPushout biprod.inl (0 : X ⟶ 0) biprod.snd (0 : 0 ⟶ Y) :=
inl_snd' (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pushout.inl_snd CategoryTheory.IsPushout.inl_snd
theorem inr_fst' {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPushout b.inr (0 : Y ⟶ 0) b.fst (0 : 0 ⟶ X) := by
refine of_bot ?_ (by simp) (of_isBilimit h)
simp
#align category_theory.is_pushout.inr_fst' CategoryTheory.IsPushout.inr_fst'
/-- The square
```
Y --inr--> X ⊞ Y
| |
0 fst
| |
v v
0 ---0-----> X
```
is a pushout square.
-/
theorem inr_fst (X Y : C) [HasBinaryBiproduct X Y] :
IsPushout biprod.inr (0 : Y ⟶ 0) biprod.fst (0 : 0 ⟶ X) :=
inr_fst' (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pushout.inr_fst CategoryTheory.IsPushout.inr_fst
theorem of_is_bilimit' {b : BinaryBicone X Y} (h : b.IsBilimit) :
IsPushout b.fst b.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) := by
refine IsPushout.of_right ?_ (by simp) (IsPushout.inl_snd' h)
simp
#align category_theory.is_pushout.of_is_bilimit' CategoryTheory.IsPushout.of_is_bilimit'
theorem of_hasBinaryBiproduct (X Y : C) [HasBinaryBiproduct X Y] :
IsPushout biprod.fst biprod.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) :=
of_is_bilimit' (BinaryBiproduct.isBilimit X Y)
#align category_theory.is_pushout.of_has_binary_biproduct CategoryTheory.IsPushout.of_hasBinaryBiproduct
instance hasPushout_biprod_fst_biprod_snd [HasBinaryBiproduct X Y] :
HasPushout (biprod.fst : _ ⟶ X) (biprod.snd : _ ⟶ Y) :=
HasColimit.mk ⟨_, (of_hasBinaryBiproduct X Y).isColimit⟩
#align category_theory.is_pushout.has_pushout_biprod_fst_biprod_snd CategoryTheory.IsPushout.hasPushout_biprod_fst_biprod_snd
/-- The pushout of `biprod.fst` and `biprod.snd` is the zero object. -/
def pushoutBiprodFstBiprodSnd [HasBinaryBiproduct X Y] :
pushout (biprod.fst : _ ⟶ X) (biprod.snd : _ ⟶ Y) ≅ 0 :=
colimit.isoColimitCocone ⟨_, (of_hasBinaryBiproduct X Y).isColimit⟩
#align category_theory.is_pushout.pushout_biprod_fst_biprod_snd CategoryTheory.IsPushout.pushoutBiprodFstBiprodSnd
end
theorem op (h : IsPushout f g inl inr) : IsPullback inr.op inl.op g.op f.op :=
IsPullback.of_isLimit
(IsLimit.ofIsoLimit
(Limits.PushoutCocone.isColimitEquivIsLimitOp h.flip.cocone h.flip.isColimit)
h.toCommSq.flip.coconeOp)
#align category_theory.is_pushout.op CategoryTheory.IsPushout.op
theorem unop {Z X Y P : Cᵒᵖ} {f : Z ⟶ X} {g : Z ⟶ Y} {inl : X ⟶ P} {inr : Y ⟶ P}
(h : IsPushout f g inl inr) : IsPullback inr.unop inl.unop g.unop f.unop :=
IsPullback.of_isLimit
(IsLimit.ofIsoLimit
(Limits.PushoutCocone.isColimitEquivIsLimitUnop h.flip.cocone h.flip.isColimit)
h.toCommSq.flip.coconeUnop)
#align category_theory.is_pushout.unop CategoryTheory.IsPushout.unop
theorem of_horiz_isIso [IsIso f] [IsIso inr] (sq : CommSq f g inl inr) : IsPushout f g inl inr :=
of_isColimit' sq
(by
refine
PushoutCocone.IsColimit.mk _ (fun s => inv inr ≫ s.inr) (fun s => ?_)
(by aesop_cat) (by aesop_cat)
simp only [← cancel_epi f, s.condition, sq.w_assoc, IsIso.hom_inv_id_assoc])
#align category_theory.is_pushout.of_horiz_is_iso CategoryTheory.IsPushout.of_horiz_isIso
theorem of_vert_isIso [IsIso g] [IsIso inl] (sq : CommSq f g inl inr) : IsPushout f g inl inr :=
(of_horiz_isIso sq.flip).flip
#align category_theory.is_pushout.of_vert_is_iso CategoryTheory.IsPushout.of_vert_isIso
end IsPushout
section Equalizer
variable {X Y Z : C} {f f' : X ⟶ Y} {g g' : Y ⟶ Z}
/-- If `f : X ⟶ Y`, `g g' : Y ⟶ Z` forms a pullback square, then `f` is the equalizer of
`g` and `g'`. -/
noncomputable def IsPullback.isLimitFork (H : IsPullback f f g g') : IsLimit (Fork.ofι f H.w) := by
fapply Fork.IsLimit.mk
· exact fun s => H.isLimit.lift (PullbackCone.mk s.ι s.ι s.condition)
· exact fun s => H.isLimit.fac _ WalkingCospan.left
· intro s m e
apply PullbackCone.IsLimit.hom_ext H.isLimit <;> refine e.trans ?_ <;> symm <;>
exact H.isLimit.fac _ _
#align category_theory.is_pullback.is_limit_fork CategoryTheory.IsPullback.isLimitFork
/-- If `f f' : X ⟶ Y`, `g : Y ⟶ Z` forms a pushout square, then `g` is the coequalizer of
`f` and `f'`. -/
noncomputable def IsPushout.isLimitFork (H : IsPushout f f' g g) :
IsColimit (Cofork.ofπ g H.w) := by
fapply Cofork.IsColimit.mk
· exact fun s => H.isColimit.desc (PushoutCocone.mk s.π s.π s.condition)
· exact fun s => H.isColimit.fac _ WalkingSpan.left
· intro s m e
apply PushoutCocone.IsColimit.hom_ext H.isColimit <;> refine e.trans ?_ <;> symm <;>
exact H.isColimit.fac _ _
#align category_theory.is_pushout.is_limit_fork CategoryTheory.IsPushout.isLimitFork
end Equalizer
namespace BicartesianSq
variable {W X Y Z : C} {f : W ⟶ X} {g : W ⟶ Y} {h : X ⟶ Z} {i : Y ⟶ Z}
theorem of_isPullback_isPushout (p₁ : IsPullback f g h i) (p₂ : IsPushout f g h i) :
BicartesianSq f g h i :=
BicartesianSq.mk p₁ p₂.isColimit'
#align category_theory.bicartesian_sq.of_is_pullback_is_pushout CategoryTheory.BicartesianSq.of_isPullback_isPushout
theorem flip (p : BicartesianSq f g h i) : BicartesianSq g f i h :=
of_isPullback_isPushout p.toIsPullback.flip p.toIsPushout.flip
#align category_theory.bicartesian_sq.flip CategoryTheory.BicartesianSq.flip
variable [HasZeroObject C] [HasZeroMorphisms C]
open ZeroObject
/-- ```
X ⊞ Y --fst--> X
| |
snd 0
| |
v v
Y -----0---> 0
```
is a bicartesian square.
-/
theorem of_is_biproduct₁ {b : BinaryBicone X Y} (h : b.IsBilimit) :
BicartesianSq b.fst b.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) :=
of_isPullback_isPushout (IsPullback.of_isBilimit h) (IsPushout.of_is_bilimit' h)
#align category_theory.bicartesian_sq.of_is_biproduct₁ CategoryTheory.BicartesianSq.of_is_biproduct₁
/-- ```
0 -----0---> X
| |
0 inl
| |
v v
Y --inr--> X ⊞ Y
```
is a bicartesian square.
-/
theorem of_is_biproduct₂ {b : BinaryBicone X Y} (h : b.IsBilimit) :
BicartesianSq (0 : 0 ⟶ X) (0 : 0 ⟶ Y) b.inl b.inr :=
of_isPullback_isPushout (IsPullback.of_is_bilimit' h) (IsPushout.of_isBilimit h)
#align category_theory.bicartesian_sq.of_is_biproduct₂ CategoryTheory.BicartesianSq.of_is_biproduct₂
/-- ```
X ⊞ Y --fst--> X
| |
snd 0
| |
v v
Y -----0---> 0
```
is a bicartesian square.
-/
@[simp]
theorem of_has_biproduct₁ [HasBinaryBiproduct X Y] :
BicartesianSq biprod.fst biprod.snd (0 : X ⟶ 0) (0 : Y ⟶ 0) := by
convert of_is_biproduct₁ (BinaryBiproduct.isBilimit X Y)
#align category_theory.bicartesian_sq.of_has_biproduct₁ CategoryTheory.BicartesianSq.of_has_biproduct₁
/-- ```
0 -----0---> X
| |
0 inl
| |
v v
Y --inr--> X ⊞ Y
```
is a bicartesian square.
-/
@[simp]
theorem of_has_biproduct₂ [HasBinaryBiproduct X Y] :
BicartesianSq (0 : 0 ⟶ X) (0 : 0 ⟶ Y) biprod.inl biprod.inr := by
convert of_is_biproduct₂ (BinaryBiproduct.isBilimit X Y)
#align category_theory.bicartesian_sq.of_has_biproduct₂ CategoryTheory.BicartesianSq.of_has_biproduct₂
end BicartesianSq
section Functor
variable {D : Type u₂} [Category.{v₂} D]
variable (F : C ⥤ D) {W X Y Z : C} {f : W ⟶ X} {g : W ⟶ Y} {h : X ⟶ Z} {i : Y ⟶ Z}
theorem Functor.map_isPullback [PreservesLimit (cospan h i) F] (s : IsPullback f g h i) :
IsPullback (F.map f) (F.map g) (F.map h) (F.map i) := by
-- This is made slightly awkward because `C` and `D` have different universes,
-- and so the relevant `WalkingCospan` diagrams live in different universes too!
refine
IsPullback.of_isLimit' (F.map_commSq s.toCommSq)
(IsLimit.equivOfNatIsoOfIso (cospanCompIso F h i) _ _ (WalkingCospan.ext ?_ ?_ ?_)
(isLimitOfPreserves F s.isLimit))
· rfl
· simp
· simp
#align category_theory.functor.map_is_pullback CategoryTheory.Functor.map_isPullback
| Mathlib/CategoryTheory/Limits/Shapes/CommSq.lean | 1,011 | 1,019 | theorem Functor.map_isPushout [PreservesColimit (span f g) F] (s : IsPushout f g h i) :
IsPushout (F.map f) (F.map g) (F.map h) (F.map i) := by |
refine
IsPushout.of_isColimit' (F.map_commSq s.toCommSq)
(IsColimit.equivOfNatIsoOfIso (spanCompIso F f g) _ _ (WalkingSpan.ext ?_ ?_ ?_)
(isColimitOfPreserves F s.isColimit))
· rfl
· simp
· simp
|
/-
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
#align_import group_theory.perm.list from "leanprover-community/mathlib"@"9003f28797c0664a49e4179487267c494477d853"
/-!
# 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
#align list.form_perm List.formPerm
@[simp]
theorem formPerm_nil : formPerm ([] : List α) = 1 :=
rfl
#align list.form_perm_nil List.formPerm_nil
@[simp]
theorem formPerm_singleton (x : α) : formPerm [x] = 1 :=
rfl
#align list.form_perm_singleton List.formPerm_singleton
@[simp]
theorem formPerm_cons_cons (x y : α) (l : List α) :
formPerm (x :: y :: l) = swap x y * formPerm (y :: l) :=
prod_cons
#align list.form_perm_cons_cons List.formPerm_cons_cons
theorem formPerm_pair (x y : α) : formPerm [x, y] = swap x y :=
rfl
#align list.form_perm_pair List.formPerm_pair
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 (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
#align list.zip_with_swap_prod_support' List.zipWith_swap_prod_support'
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'
#align list.zip_with_swap_prod_support List.zipWith_swap_prod_support
| Mathlib/GroupTheory/Perm/List.lean | 95 | 97 | 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
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta
-/
import Mathlib.CategoryTheory.Sites.Sheaf
#align_import category_theory.sites.canonical from "leanprover-community/mathlib"@"9e7c80f638149bfb3504ba8ff48dfdbfc949fb1a"
/-!
# The canonical topology on a category
We define the finest (largest) Grothendieck topology for which a given presheaf `P` is a sheaf.
This is well defined since if `P` is a sheaf for a topology `J`, then it is a sheaf for any
coarser (smaller) topology. Nonetheless we define the topology explicitly by specifying its sieves:
A sieve `S` on `X` is covering for `finestTopologySingle P` iff
for any `f : Y ⟶ X`, `P` satisfies the sheaf axiom for `S.pullback f`.
Showing that this is a genuine Grothendieck topology (namely that it satisfies the transitivity
axiom) forms the bulk of this file.
This generalises to a set of presheaves, giving the topology `finestTopology Ps` which is the
finest topology for which every presheaf in `Ps` is a sheaf.
Using `Ps` as the set of representable presheaves defines the `canonicalTopology`: the finest
topology for which every representable is a sheaf.
A Grothendieck topology is called `Subcanonical` if it is smaller than the canonical topology,
equivalently it is subcanonical iff every representable presheaf is a sheaf.
## References
* https://ncatlab.org/nlab/show/canonical+topology
* https://ncatlab.org/nlab/show/subcanonical+coverage
* https://stacks.math.columbia.edu/tag/00Z9
* https://math.stackexchange.com/a/358709/
-/
universe v u
namespace CategoryTheory
open scoped Classical
open CategoryTheory Category Limits Sieve
variable {C : Type u} [Category.{v} C]
namespace Sheaf
variable {P : Cᵒᵖ ⥤ Type v}
variable {X Y : C} {S : Sieve X} {R : Presieve X}
variable (J J₂ : GrothendieckTopology C)
/--
To show `P` is a sheaf for the binding of `U` with `B`, it suffices to show that `P` is a sheaf for
`U`, that `P` is a sheaf for each sieve in `B`, and that it is separated for any pullback of any
sieve in `B`.
This is mostly an auxiliary lemma to show `isSheafFor_trans`.
Adapted from [Elephant], Lemma C2.1.7(i) with suggestions as mentioned in
https://math.stackexchange.com/a/358709/
-/
theorem isSheafFor_bind (P : Cᵒᵖ ⥤ Type v) (U : Sieve X) (B : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, U f → Sieve Y)
(hU : Presieve.IsSheafFor P (U : Presieve X))
(hB : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (hf : U f), Presieve.IsSheafFor P (B hf : Presieve Y))
(hB' : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (h : U f) ⦃Z⦄ (g : Z ⟶ Y),
Presieve.IsSeparatedFor P (((B h).pullback g) : Presieve Z)) :
Presieve.IsSheafFor P (Sieve.bind (U : Presieve X) B : Presieve X) := by
intro s hs
let y : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (hf : U f), Presieve.FamilyOfElements P (B hf : Presieve Y) :=
fun Y f hf Z g hg => s _ (Presieve.bind_comp _ _ hg)
have hy : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (hf : U f), (y hf).Compatible := by
intro Y f H Y₁ Y₂ Z g₁ g₂ f₁ f₂ hf₁ hf₂ comm
apply hs
apply reassoc_of% comm
let t : Presieve.FamilyOfElements P (U : Presieve X) :=
fun Y f hf => (hB hf).amalgamate (y hf) (hy hf)
have ht : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (hf : U f), (y hf).IsAmalgamation (t f hf) := fun Y f hf =>
(hB hf).isAmalgamation _
have hT : t.Compatible := by
rw [Presieve.compatible_iff_sieveCompatible]
intro Z W f h hf
apply (hB (U.downward_closed hf h)).isSeparatedFor.ext
intro Y l hl
apply (hB' hf (l ≫ h)).ext
intro M m hm
have : bind U B (m ≫ l ≫ h ≫ f) := by
-- Porting note: had to make explicit the parameter `((m ≫ l ≫ h) ≫ f)` and
-- using `by exact`
have : bind U B ((m ≫ l ≫ h) ≫ f) := by exact Presieve.bind_comp f hf hm
simpa using this
trans s (m ≫ l ≫ h ≫ f) this
· have := ht (U.downward_closed hf h) _ ((B _).downward_closed hl m)
rw [op_comp, FunctorToTypes.map_comp_apply] at this
rw [this]
change s _ _ = s _ _
-- Porting note: the proof was `by simp`
congr 1
simp only [assoc]
· have h : s _ _ = _ := (ht hf _ hm).symm
-- Porting note: this was done by `simp only [assoc] at`
conv_lhs at h => congr; rw [assoc, assoc]
rw [h]
simp only [op_comp, assoc, FunctorToTypes.map_comp_apply]
refine ⟨hU.amalgamate t hT, ?_, ?_⟩
· rintro Z _ ⟨Y, f, g, hg, hf, rfl⟩
rw [op_comp, FunctorToTypes.map_comp_apply, Presieve.IsSheafFor.valid_glue _ _ _ hg]
apply ht hg _ hf
· intro y hy
apply hU.isSeparatedFor.ext
intro Y f hf
apply (hB hf).isSeparatedFor.ext
intro Z g hg
rw [← FunctorToTypes.map_comp_apply, ← op_comp, hy _ (Presieve.bind_comp _ _ hg),
hU.valid_glue _ _ hf, ht hf _ hg]
#align category_theory.sheaf.is_sheaf_for_bind CategoryTheory.Sheaf.isSheafFor_bind
/-- Given two sieves `R` and `S`, to show that `P` is a sheaf for `S`, we can show:
* `P` is a sheaf for `R`
* `P` is a sheaf for the pullback of `S` along any arrow in `R`
* `P` is separated for the pullback of `R` along any arrow in `S`.
This is mostly an auxiliary lemma to construct `finestTopology`.
Adapted from [Elephant], Lemma C2.1.7(ii) with suggestions as mentioned in
https://math.stackexchange.com/a/358709
-/
theorem isSheafFor_trans (P : Cᵒᵖ ⥤ Type v) (R S : Sieve X)
(hR : Presieve.IsSheafFor P (R : Presieve X))
(hR' : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (_ : S f), Presieve.IsSeparatedFor P (R.pullback f : Presieve Y))
(hS : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄ (_ : R f), Presieve.IsSheafFor P (S.pullback f : Presieve Y)) :
Presieve.IsSheafFor P (S : Presieve X) := by
have : (bind R fun Y f _ => S.pullback f : Presieve X) ≤ S := by
rintro Z f ⟨W, f, g, hg, hf : S _, rfl⟩
apply hf
apply Presieve.isSheafFor_subsieve_aux P this
· apply isSheafFor_bind _ _ _ hR hS
intro Y f hf Z g
rw [← pullback_comp]
apply (hS (R.downward_closed hf _)).isSeparatedFor
· intro Y f hf
have : Sieve.pullback f (bind R fun T (k : T ⟶ X) (_ : R k) => pullback k S) =
R.pullback f := by
ext Z g
constructor
· rintro ⟨W, k, l, hl, _, comm⟩
rw [pullback_apply, ← comm]
simp [hl]
· intro a
refine ⟨Z, 𝟙 Z, _, a, ?_⟩
simp [hf]
rw [this]
apply hR' hf
#align category_theory.sheaf.is_sheaf_for_trans CategoryTheory.Sheaf.isSheafFor_trans
/-- Construct the finest (largest) Grothendieck topology for which the given presheaf is a sheaf.
This is a special case of https://stacks.math.columbia.edu/tag/00Z9, but following a different
proof (see the comments there).
-/
def finestTopologySingle (P : Cᵒᵖ ⥤ Type v) : GrothendieckTopology C where
sieves X S := ∀ (Y) (f : Y ⟶ X), Presieve.IsSheafFor P (S.pullback f : Presieve Y)
top_mem' X Y f := by
rw [Sieve.pullback_top]
exact Presieve.isSheafFor_top_sieve P
pullback_stable' X Y S f hS Z g := by
rw [← pullback_comp]
apply hS
transitive' X S hS R hR Z g := by
-- This is the hard part of the construction, showing that the given set of sieves satisfies
-- the transitivity axiom.
refine isSheafFor_trans P (pullback g S) _ (hS Z g) ?_ ?_
· intro Y f _
rw [← pullback_comp]
apply (hS _ _).isSeparatedFor
· intro Y f hf
have := hR hf _ (𝟙 _)
rw [pullback_id, pullback_comp] at this
apply this
#align category_theory.sheaf.finest_topology_single CategoryTheory.Sheaf.finestTopologySingle
/--
Construct the finest (largest) Grothendieck topology for which all the given presheaves are sheaves.
This is equal to the construction of <https://stacks.math.columbia.edu/tag/00Z9>.
-/
def finestTopology (Ps : Set (Cᵒᵖ ⥤ Type v)) : GrothendieckTopology C :=
sInf (finestTopologySingle '' Ps)
#align category_theory.sheaf.finest_topology CategoryTheory.Sheaf.finestTopology
/-- Check that if `P ∈ Ps`, then `P` is indeed a sheaf for the finest topology on `Ps`. -/
theorem sheaf_for_finestTopology (Ps : Set (Cᵒᵖ ⥤ Type v)) (h : P ∈ Ps) :
Presieve.IsSheaf (finestTopology Ps) P := fun X S hS => by
simpa using hS _ ⟨⟨_, _, ⟨_, h, rfl⟩, rfl⟩, rfl⟩ _ (𝟙 _)
#align category_theory.sheaf.sheaf_for_finest_topology CategoryTheory.Sheaf.sheaf_for_finestTopology
/--
Check that if each `P ∈ Ps` is a sheaf for `J`, then `J` is a subtopology of `finestTopology Ps`.
-/
| Mathlib/CategoryTheory/Sites/Canonical.lean | 197 | 202 | theorem le_finestTopology (Ps : Set (Cᵒᵖ ⥤ Type v)) (J : GrothendieckTopology C)
(hJ : ∀ P ∈ Ps, Presieve.IsSheaf J P) : J ≤ finestTopology Ps := by |
rintro X S hS _ ⟨⟨_, _, ⟨P, hP, rfl⟩, rfl⟩, rfl⟩
intro Y f
-- this can't be combined with the previous because the `subst` is applied at the end
exact hJ P hP (S.pullback f) (J.pullback_stable f hS)
|
/-
Copyright (c) 2022 Violeta Hernández Palacios. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Violeta Hernández Palacios
-/
import Mathlib.Data.Complex.Basic
import Mathlib.Data.Real.Cardinality
#align_import data.complex.cardinality from "leanprover-community/mathlib"@"1c4e18434eeb5546b212e830b2b39de6a83c473c"
/-!
# The cardinality of the complex numbers
This file shows that the complex numbers have cardinality continuum, i.e. `#ℂ = 𝔠`.
-/
-- Porting note: the lemmas `mk_complex` and `mk_univ_complex` should be in the namespace `Cardinal`
-- like their real counterparts.
open Cardinal Set
open Cardinal
/-- The cardinality of the complex numbers, as a type. -/
@[simp]
theorem mk_complex : #ℂ = 𝔠 := by
rw [mk_congr Complex.equivRealProd, mk_prod, lift_id, mk_real, continuum_mul_self]
#align mk_complex mk_complex
/-- The cardinality of the complex numbers, as a set. -/
-- @[simp] -- Porting note (#10618): simp can prove this
| Mathlib/Data/Complex/Cardinality.lean | 31 | 31 | theorem mk_univ_complex : #(Set.univ : Set ℂ) = 𝔠 := by | rw [mk_univ, mk_complex]
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Thomas Read, Andrew Yang, Dagur Asgeirsson, Joël Riou
-/
import Mathlib.CategoryTheory.Adjunction.Basic
/-!
# Uniqueness of adjoints
This file shows that adjoints are unique up to natural isomorphism.
## Main results
* `Adjunction.natTransEquiv` and `Adjunction.natIsoEquiv` If `F ⊣ G` and `F' ⊣ G'` are adjunctions,
then there are equivalences `(G ⟶ G') ≃ (F' ⟶ F)` and `(G ≅ G') ≃ (F' ≅ F)`.
Everything else is deduced from this:
* `Adjunction.leftAdjointUniq` : If `F` and `F'` are both left adjoint to `G`, then they are
naturally isomorphic.
* `Adjunction.rightAdjointUniq` : If `G` and `G'` are both right adjoint to `F`, then they are
naturally isomorphic.
-/
open CategoryTheory
variable {C D : Type*} [Category C] [Category D]
namespace CategoryTheory.Adjunction
/--
If `F ⊣ G` and `F' ⊣ G'` are adjunctions, then giving a natural transformation `G ⟶ G'` is the
same as giving a natural transformation `F' ⟶ F`.
-/
@[simps]
def natTransEquiv {F F' : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G') :
(G ⟶ G') ≃ (F' ⟶ F) where
toFun f := {
app := fun X ↦ F'.map ((adj1.unit ≫ whiskerLeft F f).app X) ≫ adj2.counit.app _
naturality := by
intro X Y g
simp only [← Category.assoc, ← Functor.map_comp]
erw [(adj1.unit ≫ (whiskerLeft F f)).naturality]
simp
}
invFun f := {
app := fun X ↦ adj2.unit.app (G.obj X) ≫ G'.map (f.app (G.obj X) ≫ adj1.counit.app X)
naturality := by
intro X Y g
erw [← adj2.unit_naturality_assoc]
simp only [← Functor.map_comp]
simp
}
left_inv f := by
ext X
simp only [Functor.comp_obj, NatTrans.comp_app, Functor.id_obj, whiskerLeft_app,
Functor.map_comp, Category.assoc, unit_naturality_assoc, right_triangle_components_assoc]
erw [← f.naturality (adj1.counit.app X), ← Category.assoc]
simp
right_inv f := by
ext
simp
@[simp]
lemma natTransEquiv_id {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) :
natTransEquiv adj adj (𝟙 _) = 𝟙 _ := by ext; simp
@[simp]
lemma natTransEquiv_id_symm {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) :
(natTransEquiv adj adj).symm (𝟙 _) = 𝟙 _ := by ext; simp
@[simp]
lemma natTransEquiv_comp {F F' F'' : C ⥤ D} {G G' G'' : D ⥤ C}
(adj1 : F ⊣ G) (adj2 : F' ⊣ G') (adj3 : F'' ⊣ G'') (f : G ⟶ G') (g : G' ⟶ G'') :
natTransEquiv adj2 adj3 g ≫ natTransEquiv adj1 adj2 f = natTransEquiv adj1 adj3 (f ≫ g) := by
apply (natTransEquiv adj1 adj3).symm.injective
ext X
simp only [natTransEquiv_symm_apply_app, Functor.comp_obj, NatTrans.comp_app,
natTransEquiv_apply_app, Functor.id_obj, whiskerLeft_app, Functor.map_comp, Category.assoc,
unit_naturality_assoc, right_triangle_components_assoc, Equiv.symm_apply_apply,
← g.naturality_assoc, ← g.naturality]
simp only [← Category.assoc, unit_naturality, Functor.comp_obj, right_triangle_components,
Category.comp_id, ← f.naturality, Category.id_comp]
@[simp]
lemma natTransEquiv_comp_symm {F F' F'' : C ⥤ D} {G G' G'' : D ⥤ C}
(adj1 : F ⊣ G) (adj2 : F' ⊣ G') (adj3 : F'' ⊣ G'') (f : F' ⟶ F) (g : F'' ⟶ F') :
(natTransEquiv adj1 adj2).symm f ≫ (natTransEquiv adj2 adj3).symm g =
(natTransEquiv adj1 adj3).symm (g ≫ f) := by
apply (natTransEquiv adj1 adj3).injective
ext
simp
/--
If `F ⊣ G` and `F' ⊣ G'` are adjunctions, then giving a natural isomorphism `G ≅ G'` is the
same as giving a natural transformation `F' ≅ F`.
-/
@[simps]
def natIsoEquiv {F F' : C ⥤ D} {G G' : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G') :
(G ≅ G') ≃ (F' ≅ F) where
toFun i := {
hom := natTransEquiv adj1 adj2 i.hom
inv := natTransEquiv adj2 adj1 i.inv
}
invFun i := {
hom := (natTransEquiv adj1 adj2).symm i.hom
inv := (natTransEquiv adj2 adj1).symm i.inv }
left_inv i := by simp
right_inv i := by simp
/-- If `F` and `F'` are both left adjoint to `G`, then they are naturally isomorphic. -/
def leftAdjointUniq {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) : F ≅ F' :=
(natIsoEquiv adj1 adj2 (Iso.refl _)).symm
#align category_theory.adjunction.left_adjoint_uniq CategoryTheory.Adjunction.leftAdjointUniq
-- Porting note (#10618): removed simp as simp can prove this
theorem homEquiv_leftAdjointUniq_hom_app {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G)
(x : C) : adj1.homEquiv _ _ ((leftAdjointUniq adj1 adj2).hom.app x) = adj2.unit.app x := by
simp [leftAdjointUniq]
#align category_theory.adjunction.hom_equiv_left_adjoint_uniq_hom_app CategoryTheory.Adjunction.homEquiv_leftAdjointUniq_hom_app
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Adjunction/Unique.lean | 123 | 127 | theorem unit_leftAdjointUniq_hom {F F' : C ⥤ D} {G : D ⥤ C} (adj1 : F ⊣ G) (adj2 : F' ⊣ G) :
adj1.unit ≫ whiskerRight (leftAdjointUniq adj1 adj2).hom G = adj2.unit := by |
ext x
rw [NatTrans.comp_app, ← homEquiv_leftAdjointUniq_hom_app adj1 adj2]
simp [← G.map_comp]
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.Order.Group.Int
import Mathlib.Algebra.Order.Ring.Nat
import Mathlib.Algebra.Ring.Rat
import Mathlib.Data.PNat.Defs
#align_import data.rat.lemmas from "leanprover-community/mathlib"@"550b58538991c8977703fdeb7c9d51a5aa27df11"
/-!
# Further lemmas for the Rational Numbers
-/
namespace Rat
open Rat
theorem num_dvd (a) {b : ℤ} (b0 : b ≠ 0) : (a /. b).num ∣ a := by
cases' e : a /. b with n d h c
rw [Rat.mk'_eq_divInt, divInt_eq_iff b0 (mod_cast h)] at e
refine Int.natAbs_dvd.1 <| Int.dvd_natAbs.1 <| Int.natCast_dvd_natCast.2 <|
c.dvd_of_dvd_mul_right ?_
have := congr_arg Int.natAbs e
simp only [Int.natAbs_mul, Int.natAbs_ofNat] at this; simp [this]
#align rat.num_dvd Rat.num_dvd
theorem den_dvd (a b : ℤ) : ((a /. b).den : ℤ) ∣ b := by
by_cases b0 : b = 0; · simp [b0]
cases' e : a /. b with n d h c
rw [mk'_eq_divInt, divInt_eq_iff b0 (ne_of_gt (Int.natCast_pos.2 (Nat.pos_of_ne_zero h)))] at e
refine Int.dvd_natAbs.1 <| Int.natCast_dvd_natCast.2 <| c.symm.dvd_of_dvd_mul_left ?_
rw [← Int.natAbs_mul, ← Int.natCast_dvd_natCast, Int.dvd_natAbs, ← e]; simp
#align rat.denom_dvd Rat.den_dvd
theorem num_den_mk {q : ℚ} {n d : ℤ} (hd : d ≠ 0) (qdf : q = n /. d) :
∃ c : ℤ, n = c * q.num ∧ d = c * q.den := by
obtain rfl | hn := eq_or_ne n 0
· simp [qdf]
have : q.num * d = n * ↑q.den := by
refine (divInt_eq_iff ?_ hd).mp ?_
· exact Int.natCast_ne_zero.mpr (Rat.den_nz _)
· rwa [num_divInt_den]
have hqdn : q.num ∣ n := by
rw [qdf]
exact Rat.num_dvd _ hd
refine ⟨n / q.num, ?_, ?_⟩
· rw [Int.ediv_mul_cancel hqdn]
· refine Int.eq_mul_div_of_mul_eq_mul_of_dvd_left ?_ hqdn this
rw [qdf]
exact Rat.num_ne_zero.2 ((divInt_ne_zero hd).mpr hn)
#align rat.num_denom_mk Rat.num_den_mk
#noalign rat.mk_pnat_num
#noalign rat.mk_pnat_denom
theorem num_mk (n d : ℤ) : (n /. d).num = d.sign * n / n.gcd d := by
have (m : ℕ) : Int.natAbs (m + 1) = m + 1 := by
rw [← Nat.cast_one, ← Nat.cast_add, Int.natAbs_cast]
rcases d with ((_ | _) | _) <;>
rw [← Int.div_eq_ediv_of_dvd] <;>
simp [divInt, mkRat, Rat.normalize, Nat.succPNat, Int.sign, Int.gcd,
Int.zero_ediv, Int.ofNat_dvd_left, Nat.gcd_dvd_left, this]
#align rat.num_mk Rat.num_mk
theorem den_mk (n d : ℤ) : (n /. d).den = if d = 0 then 1 else d.natAbs / n.gcd d := by
have (m : ℕ) : Int.natAbs (m + 1) = m + 1 := by
rw [← Nat.cast_one, ← Nat.cast_add, Int.natAbs_cast]
rcases d with ((_ | _) | _) <;>
simp [divInt, mkRat, Rat.normalize, Nat.succPNat, Int.sign, Int.gcd,
if_neg (Nat.cast_add_one_ne_zero _), this]
#align rat.denom_mk Rat.den_mk
#noalign rat.mk_pnat_denom_dvd
theorem add_den_dvd (q₁ q₂ : ℚ) : (q₁ + q₂).den ∣ q₁.den * q₂.den := by
rw [add_def, normalize_eq]
apply Nat.div_dvd_of_dvd
apply Nat.gcd_dvd_right
#align rat.add_denom_dvd Rat.add_den_dvd
theorem mul_den_dvd (q₁ q₂ : ℚ) : (q₁ * q₂).den ∣ q₁.den * q₂.den := by
rw [mul_def, normalize_eq]
apply Nat.div_dvd_of_dvd
apply Nat.gcd_dvd_right
#align rat.mul_denom_dvd Rat.mul_den_dvd
theorem mul_num (q₁ q₂ : ℚ) :
(q₁ * q₂).num = q₁.num * q₂.num / Nat.gcd (q₁.num * q₂.num).natAbs (q₁.den * q₂.den) := by
rw [mul_def, normalize_eq]
#align rat.mul_num Rat.mul_num
theorem mul_den (q₁ q₂ : ℚ) :
(q₁ * q₂).den =
q₁.den * q₂.den / Nat.gcd (q₁.num * q₂.num).natAbs (q₁.den * q₂.den) := by
rw [mul_def, normalize_eq]
#align rat.mul_denom Rat.mul_den
theorem mul_self_num (q : ℚ) : (q * q).num = q.num * q.num := by
rw [mul_num, Int.natAbs_mul, Nat.Coprime.gcd_eq_one, Int.ofNat_one, Int.ediv_one]
exact (q.reduced.mul_right q.reduced).mul (q.reduced.mul_right q.reduced)
#align rat.mul_self_num Rat.mul_self_num
theorem mul_self_den (q : ℚ) : (q * q).den = q.den * q.den := by
rw [Rat.mul_den, Int.natAbs_mul, Nat.Coprime.gcd_eq_one, Nat.div_one]
exact (q.reduced.mul_right q.reduced).mul (q.reduced.mul_right q.reduced)
#align rat.mul_self_denom Rat.mul_self_den
theorem add_num_den (q r : ℚ) :
q + r = (q.num * r.den + q.den * r.num : ℤ) /. (↑q.den * ↑r.den : ℤ) := by
have hqd : (q.den : ℤ) ≠ 0 := Int.natCast_ne_zero_iff_pos.2 q.den_pos
have hrd : (r.den : ℤ) ≠ 0 := Int.natCast_ne_zero_iff_pos.2 r.den_pos
conv_lhs => rw [← num_divInt_den q, ← num_divInt_den r, divInt_add_divInt _ _ hqd hrd]
rw [mul_comm r.num q.den]
#align rat.add_num_denom Rat.add_num_den
section Casts
theorem exists_eq_mul_div_num_and_eq_mul_div_den (n : ℤ) {d : ℤ} (d_ne_zero : d ≠ 0) :
∃ c : ℤ, n = c * ((n : ℚ) / d).num ∧ (d : ℤ) = c * ((n : ℚ) / d).den :=
haveI : (n : ℚ) / d = Rat.divInt n d := by rw [← Rat.divInt_eq_div]
Rat.num_den_mk d_ne_zero this
#align rat.exists_eq_mul_div_num_and_eq_mul_div_denom Rat.exists_eq_mul_div_num_and_eq_mul_div_den
theorem mul_num_den' (q r : ℚ) :
(q * r).num * q.den * r.den = q.num * r.num * (q * r).den := by
let s := q.num * r.num /. (q.den * r.den : ℤ)
have hs : (q.den * r.den : ℤ) ≠ 0 := Int.natCast_ne_zero_iff_pos.mpr (mul_pos q.pos r.pos)
obtain ⟨c, ⟨c_mul_num, c_mul_den⟩⟩ :=
exists_eq_mul_div_num_and_eq_mul_div_den (q.num * r.num) hs
rw [c_mul_num, mul_assoc, mul_comm]
nth_rw 1 [c_mul_den]
rw [Int.mul_assoc, Int.mul_assoc, mul_eq_mul_left_iff, or_iff_not_imp_right]
intro
have h : _ = s := divInt_mul_divInt q.num r.num (mod_cast q.den_ne_zero) (mod_cast r.den_ne_zero)
rw [num_divInt_den, num_divInt_den] at h
rw [h, mul_comm, ← Rat.eq_iff_mul_eq_mul, ← divInt_eq_div]
#align rat.mul_num_denom' Rat.mul_num_den'
theorem add_num_den' (q r : ℚ) :
(q + r).num * q.den * r.den = (q.num * r.den + r.num * q.den) * (q + r).den := by
let s := divInt (q.num * r.den + r.num * q.den) (q.den * r.den : ℤ)
have hs : (q.den * r.den : ℤ) ≠ 0 := Int.natCast_ne_zero_iff_pos.mpr (mul_pos q.pos r.pos)
obtain ⟨c, ⟨c_mul_num, c_mul_den⟩⟩ :=
exists_eq_mul_div_num_and_eq_mul_div_den (q.num * r.den + r.num * q.den) hs
rw [c_mul_num, mul_assoc, mul_comm]
nth_rw 1 [c_mul_den]
repeat rw [Int.mul_assoc]
apply mul_eq_mul_left_iff.2
rw [or_iff_not_imp_right]
intro
have h : _ = s := divInt_add_divInt q.num r.num (mod_cast q.den_ne_zero) (mod_cast r.den_ne_zero)
rw [num_divInt_den, num_divInt_den] at h
rw [h]
rw [mul_comm]
apply Rat.eq_iff_mul_eq_mul.mp
rw [← divInt_eq_div]
#align rat.add_num_denom' Rat.add_num_den'
theorem substr_num_den' (q r : ℚ) :
(q - r).num * q.den * r.den = (q.num * r.den - r.num * q.den) * (q - r).den := by
rw [sub_eq_add_neg, sub_eq_add_neg, ← neg_mul, ← num_neg_eq_neg_num, ← den_neg_eq_den r,
add_num_den' q (-r)]
#align rat.substr_num_denom' Rat.substr_num_den'
end Casts
protected theorem inv_neg (q : ℚ) : (-q)⁻¹ = -q⁻¹ := by
rw [← num_divInt_den q]
simp only [Rat.neg_divInt, Rat.inv_divInt', eq_self_iff_true, Rat.divInt_neg]
#align rat.inv_neg Rat.inv_neg
theorem num_div_eq_of_coprime {a b : ℤ} (hb0 : 0 < b) (h : Nat.Coprime a.natAbs b.natAbs) :
(a / b : ℚ).num = a := by
-- Porting note: was `lift b to ℕ using le_of_lt hb0`
rw [← Int.natAbs_of_nonneg hb0.le, ← Rat.divInt_eq_div,
← mk_eq_divInt _ _ (Int.natAbs_ne_zero.mpr hb0.ne') h]
#align rat.num_div_eq_of_coprime Rat.num_div_eq_of_coprime
theorem den_div_eq_of_coprime {a b : ℤ} (hb0 : 0 < b) (h : Nat.Coprime a.natAbs b.natAbs) :
((a / b : ℚ).den : ℤ) = b := by
-- Porting note: was `lift b to ℕ using le_of_lt hb0`
rw [← Int.natAbs_of_nonneg hb0.le, ← Rat.divInt_eq_div,
← mk_eq_divInt _ _ (Int.natAbs_ne_zero.mpr hb0.ne') h]
#align rat.denom_div_eq_of_coprime Rat.den_div_eq_of_coprime
theorem div_int_inj {a b c d : ℤ} (hb0 : 0 < b) (hd0 : 0 < d) (h1 : Nat.Coprime a.natAbs b.natAbs)
(h2 : Nat.Coprime c.natAbs d.natAbs) (h : (a : ℚ) / b = (c : ℚ) / d) : a = c ∧ b = d := by
apply And.intro
· rw [← num_div_eq_of_coprime hb0 h1, h, num_div_eq_of_coprime hd0 h2]
· rw [← den_div_eq_of_coprime hb0 h1, h, den_div_eq_of_coprime hd0 h2]
#align rat.div_int_inj Rat.div_int_inj
@[norm_cast]
theorem intCast_div_self (n : ℤ) : ((n / n : ℤ) : ℚ) = n / n := by
by_cases hn : n = 0
· subst hn
simp only [Int.cast_zero, Int.zero_div, zero_div, Int.ediv_zero]
· have : (n : ℚ) ≠ 0 := by rwa [← coe_int_inj] at hn
simp only [Int.ediv_self hn, Int.cast_one, Ne, not_false_iff, div_self this]
#align rat.coe_int_div_self Rat.intCast_div_self
@[norm_cast]
theorem natCast_div_self (n : ℕ) : ((n / n : ℕ) : ℚ) = n / n :=
intCast_div_self n
#align rat.coe_nat_div_self Rat.natCast_div_self
theorem intCast_div (a b : ℤ) (h : b ∣ a) : ((a / b : ℤ) : ℚ) = a / b := by
rcases h with ⟨c, rfl⟩
rw [mul_comm b, Int.mul_ediv_assoc c (dvd_refl b), Int.cast_mul,
intCast_div_self, Int.cast_mul, mul_div_assoc]
#align rat.coe_int_div Rat.intCast_div
theorem natCast_div (a b : ℕ) (h : b ∣ a) : ((a / b : ℕ) : ℚ) = a / b :=
intCast_div a b (Int.ofNat_dvd.mpr h)
#align rat.coe_nat_div Rat.natCast_div
theorem den_div_intCast_eq_one_iff (m n : ℤ) (hn : n ≠ 0) : ((m : ℚ) / n).den = 1 ↔ n ∣ m := by
replace hn : (n : ℚ) ≠ 0 := num_ne_zero.mp hn
constructor
· rw [Rat.den_eq_one_iff, eq_div_iff hn]
exact mod_cast (Dvd.intro_left _)
· exact (intCast_div _ _ · ▸ rfl)
#align rat.denom_div_cast_eq_one_iff Rat.den_div_intCast_eq_one_iff
theorem den_div_natCast_eq_one_iff (m n : ℕ) (hn : n ≠ 0) : ((m : ℚ) / n).den = 1 ↔ n ∣ m :=
(den_div_intCast_eq_one_iff m n (Int.ofNat_ne_zero.mpr hn)).trans Int.ofNat_dvd
-- 2024-05-11
@[deprecated] alias den_div_cast_eq_one_iff := den_div_intCast_eq_one_iff
theorem inv_intCast_num_of_pos {a : ℤ} (ha0 : 0 < a) : (a : ℚ)⁻¹.num = 1 := by
rw [← ofInt_eq_cast, ofInt, mk_eq_divInt, Rat.inv_divInt', divInt_eq_div, Nat.cast_one]
apply num_div_eq_of_coprime ha0
rw [Int.natAbs_one]
exact Nat.coprime_one_left _
#align rat.inv_coe_int_num_of_pos Rat.inv_intCast_num_of_pos
theorem inv_natCast_num_of_pos {a : ℕ} (ha0 : 0 < a) : (a : ℚ)⁻¹.num = 1 :=
inv_intCast_num_of_pos (mod_cast ha0 : 0 < (a : ℤ))
#align rat.inv_coe_nat_num_of_pos Rat.inv_natCast_num_of_pos
| Mathlib/Data/Rat/Lemmas.lean | 248 | 252 | theorem inv_intCast_den_of_pos {a : ℤ} (ha0 : 0 < a) : ((a : ℚ)⁻¹.den : ℤ) = a := by |
rw [← ofInt_eq_cast, ofInt, mk_eq_divInt, Rat.inv_divInt', divInt_eq_div, Nat.cast_one]
apply den_div_eq_of_coprime ha0
rw [Int.natAbs_one]
exact Nat.coprime_one_left _
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Wrenna Robson
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.LinearAlgebra.Vandermonde
import Mathlib.RingTheory.Polynomial.Basic
#align_import linear_algebra.lagrange from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Lagrange interpolation
## Main definitions
* In everything that follows, `s : Finset ι` is a finite set of indexes, with `v : ι → F` an
indexing of the field over some type. We call the image of v on s the interpolation nodes,
though strictly unique nodes are only defined when v is injective on s.
* `Lagrange.basisDivisor x y`, with `x y : F`. These are the normalised irreducible factors of
the Lagrange basis polynomials. They evaluate to `1` at `x` and `0` at `y` when `x` and `y`
are distinct.
* `Lagrange.basis v i` with `i : ι`: the Lagrange basis polynomial that evaluates to `1` at `v i`
and `0` at `v j` for `i ≠ j`.
* `Lagrange.interpolate v r` where `r : ι → F` is a function from the fintype to the field: the
Lagrange interpolant that evaluates to `r i` at `x i` for all `i : ι`. The `r i` are the _values_
associated with the _nodes_`x i`.
-/
open Polynomial
section PolynomialDetermination
namespace Polynomial
variable {R : Type*} [CommRing R] [IsDomain R] {f g : R[X]}
section Finset
open Function Fintype
variable (s : Finset R)
theorem eq_zero_of_degree_lt_of_eval_finset_eq_zero (degree_f_lt : f.degree < s.card)
(eval_f : ∀ x ∈ s, f.eval x = 0) : f = 0 := by
rw [← mem_degreeLT] at degree_f_lt
simp_rw [eval_eq_sum_degreeLTEquiv degree_f_lt] at eval_f
rw [← degreeLTEquiv_eq_zero_iff_eq_zero degree_f_lt]
exact
Matrix.eq_zero_of_forall_index_sum_mul_pow_eq_zero
(Injective.comp (Embedding.subtype _).inj' (equivFinOfCardEq (card_coe _)).symm.injective)
fun _ => eval_f _ (Finset.coe_mem _)
#align polynomial.eq_zero_of_degree_lt_of_eval_finset_eq_zero Polynomial.eq_zero_of_degree_lt_of_eval_finset_eq_zero
theorem eq_of_degree_sub_lt_of_eval_finset_eq (degree_fg_lt : (f - g).degree < s.card)
(eval_fg : ∀ x ∈ s, f.eval x = g.eval x) : f = g := by
rw [← sub_eq_zero]
refine eq_zero_of_degree_lt_of_eval_finset_eq_zero _ degree_fg_lt ?_
simp_rw [eval_sub, sub_eq_zero]
exact eval_fg
#align polynomial.eq_of_degree_sub_lt_of_eval_finset_eq Polynomial.eq_of_degree_sub_lt_of_eval_finset_eq
theorem eq_of_degrees_lt_of_eval_finset_eq (degree_f_lt : f.degree < s.card)
(degree_g_lt : g.degree < s.card) (eval_fg : ∀ x ∈ s, f.eval x = g.eval x) : f = g := by
rw [← mem_degreeLT] at degree_f_lt degree_g_lt
refine eq_of_degree_sub_lt_of_eval_finset_eq _ ?_ eval_fg
rw [← mem_degreeLT]; exact Submodule.sub_mem _ degree_f_lt degree_g_lt
#align polynomial.eq_of_degrees_lt_of_eval_finset_eq Polynomial.eq_of_degrees_lt_of_eval_finset_eq
/--
Two polynomials, with the same degree and leading coefficient, which have the same evaluation
on a set of distinct values with cardinality equal to the degree, are equal.
-/
theorem eq_of_degree_le_of_eval_finset_eq
(h_deg_le : f.degree ≤ s.card)
(h_deg_eq : f.degree = g.degree)
(hlc : f.leadingCoeff = g.leadingCoeff)
(h_eval : ∀ x ∈ s, f.eval x = g.eval x) :
f = g := by
rcases eq_or_ne f 0 with rfl | hf
· rwa [degree_zero, eq_comm, degree_eq_bot, eq_comm] at h_deg_eq
· exact eq_of_degree_sub_lt_of_eval_finset_eq s
(lt_of_lt_of_le (degree_sub_lt h_deg_eq hf hlc) h_deg_le) h_eval
end Finset
section Indexed
open Finset
variable {ι : Type*} {v : ι → R} (s : Finset ι)
theorem eq_zero_of_degree_lt_of_eval_index_eq_zero (hvs : Set.InjOn v s)
(degree_f_lt : f.degree < s.card) (eval_f : ∀ i ∈ s, f.eval (v i) = 0) : f = 0 := by
classical
rw [← card_image_of_injOn hvs] at degree_f_lt
refine eq_zero_of_degree_lt_of_eval_finset_eq_zero _ degree_f_lt ?_
intro x hx
rcases mem_image.mp hx with ⟨_, hj, rfl⟩
exact eval_f _ hj
#align polynomial.eq_zero_of_degree_lt_of_eval_index_eq_zero Polynomial.eq_zero_of_degree_lt_of_eval_index_eq_zero
theorem eq_of_degree_sub_lt_of_eval_index_eq (hvs : Set.InjOn v s)
(degree_fg_lt : (f - g).degree < s.card) (eval_fg : ∀ i ∈ s, f.eval (v i) = g.eval (v i)) :
f = g := by
rw [← sub_eq_zero]
refine eq_zero_of_degree_lt_of_eval_index_eq_zero _ hvs degree_fg_lt ?_
simp_rw [eval_sub, sub_eq_zero]
exact eval_fg
#align polynomial.eq_of_degree_sub_lt_of_eval_index_eq Polynomial.eq_of_degree_sub_lt_of_eval_index_eq
theorem eq_of_degrees_lt_of_eval_index_eq (hvs : Set.InjOn v s) (degree_f_lt : f.degree < s.card)
(degree_g_lt : g.degree < s.card) (eval_fg : ∀ i ∈ s, f.eval (v i) = g.eval (v i)) : f = g := by
refine eq_of_degree_sub_lt_of_eval_index_eq _ hvs ?_ eval_fg
rw [← mem_degreeLT] at degree_f_lt degree_g_lt ⊢
exact Submodule.sub_mem _ degree_f_lt degree_g_lt
#align polynomial.eq_of_degrees_lt_of_eval_index_eq Polynomial.eq_of_degrees_lt_of_eval_index_eq
theorem eq_of_degree_le_of_eval_index_eq (hvs : Set.InjOn v s)
(h_deg_le : f.degree ≤ s.card)
(h_deg_eq : f.degree = g.degree)
(hlc : f.leadingCoeff = g.leadingCoeff)
(h_eval : ∀ i ∈ s, f.eval (v i) = g.eval (v i)) : f = g := by
rcases eq_or_ne f 0 with rfl | hf
· rwa [degree_zero, eq_comm, degree_eq_bot, eq_comm] at h_deg_eq
· exact eq_of_degree_sub_lt_of_eval_index_eq s hvs
(lt_of_lt_of_le (degree_sub_lt h_deg_eq hf hlc) h_deg_le)
h_eval
end Indexed
end Polynomial
end PolynomialDetermination
noncomputable section
namespace Lagrange
open Polynomial
section BasisDivisor
variable {F : Type*} [Field F]
variable {x y : F}
/-- `basisDivisor x y` is the unique linear or constant polynomial such that
when evaluated at `x` it gives `1` and `y` it gives `0` (where when `x = y` it is identically `0`).
Such polynomials are the building blocks for the Lagrange interpolants. -/
def basisDivisor (x y : F) : F[X] :=
C (x - y)⁻¹ * (X - C y)
#align lagrange.basis_divisor Lagrange.basisDivisor
theorem basisDivisor_self : basisDivisor x x = 0 := by
simp only [basisDivisor, sub_self, inv_zero, map_zero, zero_mul]
#align lagrange.basis_divisor_self Lagrange.basisDivisor_self
theorem basisDivisor_inj (hxy : basisDivisor x y = 0) : x = y := by
simp_rw [basisDivisor, mul_eq_zero, X_sub_C_ne_zero, or_false_iff, C_eq_zero, inv_eq_zero,
sub_eq_zero] at hxy
exact hxy
#align lagrange.basis_divisor_inj Lagrange.basisDivisor_inj
@[simp]
theorem basisDivisor_eq_zero_iff : basisDivisor x y = 0 ↔ x = y :=
⟨basisDivisor_inj, fun H => H ▸ basisDivisor_self⟩
#align lagrange.basis_divisor_eq_zero_iff Lagrange.basisDivisor_eq_zero_iff
theorem basisDivisor_ne_zero_iff : basisDivisor x y ≠ 0 ↔ x ≠ y := by
rw [Ne, basisDivisor_eq_zero_iff]
#align lagrange.basis_divisor_ne_zero_iff Lagrange.basisDivisor_ne_zero_iff
theorem degree_basisDivisor_of_ne (hxy : x ≠ y) : (basisDivisor x y).degree = 1 := by
rw [basisDivisor, degree_mul, degree_X_sub_C, degree_C, zero_add]
exact inv_ne_zero (sub_ne_zero_of_ne hxy)
#align lagrange.degree_basis_divisor_of_ne Lagrange.degree_basisDivisor_of_ne
@[simp]
theorem degree_basisDivisor_self : (basisDivisor x x).degree = ⊥ := by
rw [basisDivisor_self, degree_zero]
#align lagrange.degree_basis_divisor_self Lagrange.degree_basisDivisor_self
theorem natDegree_basisDivisor_self : (basisDivisor x x).natDegree = 0 := by
rw [basisDivisor_self, natDegree_zero]
#align lagrange.nat_degree_basis_divisor_self Lagrange.natDegree_basisDivisor_self
theorem natDegree_basisDivisor_of_ne (hxy : x ≠ y) : (basisDivisor x y).natDegree = 1 :=
natDegree_eq_of_degree_eq_some (degree_basisDivisor_of_ne hxy)
#align lagrange.nat_degree_basis_divisor_of_ne Lagrange.natDegree_basisDivisor_of_ne
@[simp]
theorem eval_basisDivisor_right : eval y (basisDivisor x y) = 0 := by
simp only [basisDivisor, eval_mul, eval_C, eval_sub, eval_X, sub_self, mul_zero]
#align lagrange.eval_basis_divisor_right Lagrange.eval_basisDivisor_right
theorem eval_basisDivisor_left_of_ne (hxy : x ≠ y) : eval x (basisDivisor x y) = 1 := by
simp only [basisDivisor, eval_mul, eval_C, eval_sub, eval_X]
exact inv_mul_cancel (sub_ne_zero_of_ne hxy)
#align lagrange.eval_basis_divisor_left_of_ne Lagrange.eval_basisDivisor_left_of_ne
end BasisDivisor
section Basis
variable {F : Type*} [Field F] {ι : Type*} [DecidableEq ι]
variable {s : Finset ι} {v : ι → F} {i j : ι}
open Finset
/-- Lagrange basis polynomials indexed by `s : Finset ι`, defined at nodes `v i` for a
map `v : ι → F`. For `i, j ∈ s`, `basis s v i` evaluates to 0 at `v j` for `i ≠ j`. When
`v` is injective on `s`, `basis s v i` evaluates to 1 at `v i`. -/
protected def basis (s : Finset ι) (v : ι → F) (i : ι) : F[X] :=
∏ j ∈ s.erase i, basisDivisor (v i) (v j)
#align lagrange.basis Lagrange.basis
@[simp]
theorem basis_empty : Lagrange.basis ∅ v i = 1 :=
rfl
#align lagrange.basis_empty Lagrange.basis_empty
@[simp]
theorem basis_singleton (i : ι) : Lagrange.basis {i} v i = 1 := by
rw [Lagrange.basis, erase_singleton, prod_empty]
#align lagrange.basis_singleton Lagrange.basis_singleton
@[simp]
theorem basis_pair_left (hij : i ≠ j) : Lagrange.basis {i, j} v i = basisDivisor (v i) (v j) := by
simp only [Lagrange.basis, hij, erase_insert_eq_erase, erase_eq_of_not_mem, mem_singleton,
not_false_iff, prod_singleton]
#align lagrange.basis_pair_left Lagrange.basis_pair_left
@[simp]
theorem basis_pair_right (hij : i ≠ j) : Lagrange.basis {i, j} v j = basisDivisor (v j) (v i) := by
rw [pair_comm]
exact basis_pair_left hij.symm
#align lagrange.basis_pair_right Lagrange.basis_pair_right
theorem basis_ne_zero (hvs : Set.InjOn v s) (hi : i ∈ s) : Lagrange.basis s v i ≠ 0 := by
simp_rw [Lagrange.basis, prod_ne_zero_iff, Ne, mem_erase]
rintro j ⟨hij, hj⟩
rw [basisDivisor_eq_zero_iff, hvs.eq_iff hi hj]
exact hij.symm
#align lagrange.basis_ne_zero Lagrange.basis_ne_zero
@[simp]
theorem eval_basis_self (hvs : Set.InjOn v s) (hi : i ∈ s) :
(Lagrange.basis s v i).eval (v i) = 1 := by
rw [Lagrange.basis, eval_prod]
refine prod_eq_one fun j H => ?_
rw [eval_basisDivisor_left_of_ne]
rcases mem_erase.mp H with ⟨hij, hj⟩
exact mt (hvs hi hj) hij.symm
#align lagrange.eval_basis_self Lagrange.eval_basis_self
@[simp]
theorem eval_basis_of_ne (hij : i ≠ j) (hj : j ∈ s) : (Lagrange.basis s v i).eval (v j) = 0 := by
simp_rw [Lagrange.basis, eval_prod, prod_eq_zero_iff]
exact ⟨j, ⟨mem_erase.mpr ⟨hij.symm, hj⟩, eval_basisDivisor_right⟩⟩
#align lagrange.eval_basis_of_ne Lagrange.eval_basis_of_ne
@[simp]
| Mathlib/LinearAlgebra/Lagrange.lean | 262 | 271 | theorem natDegree_basis (hvs : Set.InjOn v s) (hi : i ∈ s) :
(Lagrange.basis s v i).natDegree = s.card - 1 := by |
have H : ∀ j, j ∈ s.erase i → basisDivisor (v i) (v j) ≠ 0 := by
simp_rw [Ne, mem_erase, basisDivisor_eq_zero_iff]
exact fun j ⟨hij₁, hj⟩ hij₂ => hij₁ (hvs hj hi hij₂.symm)
rw [← card_erase_of_mem hi, card_eq_sum_ones]
convert natDegree_prod _ _ H using 1
refine sum_congr rfl fun j hj => (natDegree_basisDivisor_of_ne ?_).symm
rw [Ne, ← basisDivisor_eq_zero_iff]
exact H _ hj
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jeremy Avigad, Yury Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Field.Defs
import Mathlib.Algebra.Order.Group.Instances
import Mathlib.Algebra.Order.Group.MinMax
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.Data.Finset.Preimage
import Mathlib.Order.Interval.Set.Disjoint
import Mathlib.Order.Interval.Set.OrderIso
import Mathlib.Order.ConditionallyCompleteLattice.Basic
import Mathlib.Order.Filter.Bases
#align_import order.filter.at_top_bot from "leanprover-community/mathlib"@"1f0096e6caa61e9c849ec2adbd227e960e9dff58"
/-!
# `Filter.atTop` and `Filter.atBot` filters on preorders, monoids and groups.
In this file we define the filters
* `Filter.atTop`: corresponds to `n → +∞`;
* `Filter.atBot`: corresponds to `n → -∞`.
Then we prove many lemmas like “if `f → +∞`, then `f ± c → +∞`”.
-/
set_option autoImplicit true
variable {ι ι' α β γ : Type*}
open Set
namespace Filter
/-- `atTop` is the filter representing the limit `→ ∞` on an ordered set.
It is generated by the collection of up-sets `{b | a ≤ b}`.
(The preorder need not have a top element for this to be well defined,
and indeed is trivial when a top element exists.) -/
def atTop [Preorder α] : Filter α :=
⨅ a, 𝓟 (Ici a)
#align filter.at_top Filter.atTop
/-- `atBot` is the filter representing the limit `→ -∞` on an ordered set.
It is generated by the collection of down-sets `{b | b ≤ a}`.
(The preorder need not have a bottom element for this to be well defined,
and indeed is trivial when a bottom element exists.) -/
def atBot [Preorder α] : Filter α :=
⨅ a, 𝓟 (Iic a)
#align filter.at_bot Filter.atBot
theorem mem_atTop [Preorder α] (a : α) : { b : α | a ≤ b } ∈ @atTop α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_top Filter.mem_atTop
theorem Ici_mem_atTop [Preorder α] (a : α) : Ici a ∈ (atTop : Filter α) :=
mem_atTop a
#align filter.Ici_mem_at_top Filter.Ici_mem_atTop
theorem Ioi_mem_atTop [Preorder α] [NoMaxOrder α] (x : α) : Ioi x ∈ (atTop : Filter α) :=
let ⟨z, hz⟩ := exists_gt x
mem_of_superset (mem_atTop z) fun _ h => lt_of_lt_of_le hz h
#align filter.Ioi_mem_at_top Filter.Ioi_mem_atTop
theorem mem_atBot [Preorder α] (a : α) : { b : α | b ≤ a } ∈ @atBot α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_bot Filter.mem_atBot
theorem Iic_mem_atBot [Preorder α] (a : α) : Iic a ∈ (atBot : Filter α) :=
mem_atBot a
#align filter.Iic_mem_at_bot Filter.Iic_mem_atBot
theorem Iio_mem_atBot [Preorder α] [NoMinOrder α] (x : α) : Iio x ∈ (atBot : Filter α) :=
let ⟨z, hz⟩ := exists_lt x
mem_of_superset (mem_atBot z) fun _ h => lt_of_le_of_lt h hz
#align filter.Iio_mem_at_bot Filter.Iio_mem_atBot
theorem disjoint_atBot_principal_Ioi [Preorder α] (x : α) : Disjoint atBot (𝓟 (Ioi x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl) (Iic_mem_atBot x) (mem_principal_self _)
#align filter.disjoint_at_bot_principal_Ioi Filter.disjoint_atBot_principal_Ioi
theorem disjoint_atTop_principal_Iio [Preorder α] (x : α) : Disjoint atTop (𝓟 (Iio x)) :=
@disjoint_atBot_principal_Ioi αᵒᵈ _ _
#align filter.disjoint_at_top_principal_Iio Filter.disjoint_atTop_principal_Iio
theorem disjoint_atTop_principal_Iic [Preorder α] [NoMaxOrder α] (x : α) :
Disjoint atTop (𝓟 (Iic x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl).symm (Ioi_mem_atTop x)
(mem_principal_self _)
#align filter.disjoint_at_top_principal_Iic Filter.disjoint_atTop_principal_Iic
theorem disjoint_atBot_principal_Ici [Preorder α] [NoMinOrder α] (x : α) :
Disjoint atBot (𝓟 (Ici x)) :=
@disjoint_atTop_principal_Iic αᵒᵈ _ _ _
#align filter.disjoint_at_bot_principal_Ici Filter.disjoint_atBot_principal_Ici
theorem disjoint_pure_atTop [Preorder α] [NoMaxOrder α] (x : α) : Disjoint (pure x) atTop :=
Disjoint.symm <| (disjoint_atTop_principal_Iic x).mono_right <| le_principal_iff.2 <|
mem_pure.2 right_mem_Iic
#align filter.disjoint_pure_at_top Filter.disjoint_pure_atTop
theorem disjoint_pure_atBot [Preorder α] [NoMinOrder α] (x : α) : Disjoint (pure x) atBot :=
@disjoint_pure_atTop αᵒᵈ _ _ _
#align filter.disjoint_pure_at_bot Filter.disjoint_pure_atBot
theorem not_tendsto_const_atTop [Preorder α] [NoMaxOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atTop :=
tendsto_const_pure.not_tendsto (disjoint_pure_atTop x)
#align filter.not_tendsto_const_at_top Filter.not_tendsto_const_atTop
theorem not_tendsto_const_atBot [Preorder α] [NoMinOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atBot :=
tendsto_const_pure.not_tendsto (disjoint_pure_atBot x)
#align filter.not_tendsto_const_at_bot Filter.not_tendsto_const_atBot
theorem disjoint_atBot_atTop [PartialOrder α] [Nontrivial α] :
Disjoint (atBot : Filter α) atTop := by
rcases exists_pair_ne α with ⟨x, y, hne⟩
by_cases hle : x ≤ y
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot x) (Ici_mem_atTop y)
exact Iic_disjoint_Ici.2 (hle.lt_of_ne hne).not_le
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot y) (Ici_mem_atTop x)
exact Iic_disjoint_Ici.2 hle
#align filter.disjoint_at_bot_at_top Filter.disjoint_atBot_atTop
theorem disjoint_atTop_atBot [PartialOrder α] [Nontrivial α] : Disjoint (atTop : Filter α) atBot :=
disjoint_atBot_atTop.symm
#align filter.disjoint_at_top_at_bot Filter.disjoint_atTop_atBot
theorem hasAntitoneBasis_atTop [Nonempty α] [Preorder α] [IsDirected α (· ≤ ·)] :
(@atTop α _).HasAntitoneBasis Ici :=
.iInf_principal fun _ _ ↦ Ici_subset_Ici.2
theorem atTop_basis [Nonempty α] [SemilatticeSup α] : (@atTop α _).HasBasis (fun _ => True) Ici :=
hasAntitoneBasis_atTop.1
#align filter.at_top_basis Filter.atTop_basis
theorem atTop_eq_generate_Ici [SemilatticeSup α] : atTop = generate (range (Ici (α := α))) := by
rcases isEmpty_or_nonempty α with hα|hα
· simp only [eq_iff_true_of_subsingleton]
· simp [(atTop_basis (α := α)).eq_generate, range]
theorem atTop_basis' [SemilatticeSup α] (a : α) : (@atTop α _).HasBasis (fun x => a ≤ x) Ici :=
⟨fun _ =>
(@atTop_basis α ⟨a⟩ _).mem_iff.trans
⟨fun ⟨x, _, hx⟩ => ⟨x ⊔ a, le_sup_right, fun _y hy => hx (le_trans le_sup_left hy)⟩,
fun ⟨x, _, hx⟩ => ⟨x, trivial, hx⟩⟩⟩
#align filter.at_top_basis' Filter.atTop_basis'
theorem atBot_basis [Nonempty α] [SemilatticeInf α] : (@atBot α _).HasBasis (fun _ => True) Iic :=
@atTop_basis αᵒᵈ _ _
#align filter.at_bot_basis Filter.atBot_basis
theorem atBot_basis' [SemilatticeInf α] (a : α) : (@atBot α _).HasBasis (fun x => x ≤ a) Iic :=
@atTop_basis' αᵒᵈ _ _
#align filter.at_bot_basis' Filter.atBot_basis'
@[instance]
theorem atTop_neBot [Nonempty α] [SemilatticeSup α] : NeBot (atTop : Filter α) :=
atTop_basis.neBot_iff.2 fun _ => nonempty_Ici
#align filter.at_top_ne_bot Filter.atTop_neBot
@[instance]
theorem atBot_neBot [Nonempty α] [SemilatticeInf α] : NeBot (atBot : Filter α) :=
@atTop_neBot αᵒᵈ _ _
#align filter.at_bot_ne_bot Filter.atBot_neBot
@[simp]
theorem mem_atTop_sets [Nonempty α] [SemilatticeSup α] {s : Set α} :
s ∈ (atTop : Filter α) ↔ ∃ a : α, ∀ b ≥ a, b ∈ s :=
atTop_basis.mem_iff.trans <| exists_congr fun _ => true_and_iff _
#align filter.mem_at_top_sets Filter.mem_atTop_sets
@[simp]
theorem mem_atBot_sets [Nonempty α] [SemilatticeInf α] {s : Set α} :
s ∈ (atBot : Filter α) ↔ ∃ a : α, ∀ b ≤ a, b ∈ s :=
@mem_atTop_sets αᵒᵈ _ _ _
#align filter.mem_at_bot_sets Filter.mem_atBot_sets
@[simp]
theorem eventually_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ b ≥ a, p b :=
mem_atTop_sets
#align filter.eventually_at_top Filter.eventually_atTop
@[simp]
theorem eventually_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ b ≤ a, p b :=
mem_atBot_sets
#align filter.eventually_at_bot Filter.eventually_atBot
theorem eventually_ge_atTop [Preorder α] (a : α) : ∀ᶠ x in atTop, a ≤ x :=
mem_atTop a
#align filter.eventually_ge_at_top Filter.eventually_ge_atTop
theorem eventually_le_atBot [Preorder α] (a : α) : ∀ᶠ x in atBot, x ≤ a :=
mem_atBot a
#align filter.eventually_le_at_bot Filter.eventually_le_atBot
theorem eventually_gt_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, a < x :=
Ioi_mem_atTop a
#align filter.eventually_gt_at_top Filter.eventually_gt_atTop
theorem eventually_ne_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, x ≠ a :=
(eventually_gt_atTop a).mono fun _ => ne_of_gt
#align filter.eventually_ne_at_top Filter.eventually_ne_atTop
protected theorem Tendsto.eventually_gt_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c < f x :=
hf.eventually (eventually_gt_atTop c)
#align filter.tendsto.eventually_gt_at_top Filter.Tendsto.eventually_gt_atTop
protected theorem Tendsto.eventually_ge_atTop [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c ≤ f x :=
hf.eventually (eventually_ge_atTop c)
#align filter.tendsto.eventually_ge_at_top Filter.Tendsto.eventually_ge_atTop
protected theorem Tendsto.eventually_ne_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atTop c)
#align filter.tendsto.eventually_ne_at_top Filter.Tendsto.eventually_ne_atTop
protected theorem Tendsto.eventually_ne_atTop' [Preorder β] [NoMaxOrder β] {f : α → β}
{l : Filter α} (hf : Tendsto f l atTop) (c : α) : ∀ᶠ x in l, x ≠ c :=
(hf.eventually_ne_atTop (f c)).mono fun _ => ne_of_apply_ne f
#align filter.tendsto.eventually_ne_at_top' Filter.Tendsto.eventually_ne_atTop'
theorem eventually_lt_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x < a :=
Iio_mem_atBot a
#align filter.eventually_lt_at_bot Filter.eventually_lt_atBot
theorem eventually_ne_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x ≠ a :=
(eventually_lt_atBot a).mono fun _ => ne_of_lt
#align filter.eventually_ne_at_bot Filter.eventually_ne_atBot
protected theorem Tendsto.eventually_lt_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x < c :=
hf.eventually (eventually_lt_atBot c)
#align filter.tendsto.eventually_lt_at_bot Filter.Tendsto.eventually_lt_atBot
protected theorem Tendsto.eventually_le_atBot [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≤ c :=
hf.eventually (eventually_le_atBot c)
#align filter.tendsto.eventually_le_at_bot Filter.Tendsto.eventually_le_atBot
protected theorem Tendsto.eventually_ne_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atBot c)
#align filter.tendsto.eventually_ne_at_bot Filter.Tendsto.eventually_ne_atBot
theorem eventually_forall_ge_atTop [Preorder α] {p : α → Prop} :
(∀ᶠ x in atTop, ∀ y, x ≤ y → p y) ↔ ∀ᶠ x in atTop, p x := by
refine ⟨fun h ↦ h.mono fun x hx ↦ hx x le_rfl, fun h ↦ ?_⟩
rcases (hasBasis_iInf_principal_finite _).eventually_iff.1 h with ⟨S, hSf, hS⟩
refine mem_iInf_of_iInter hSf (V := fun x ↦ Ici x.1) (fun _ ↦ Subset.rfl) fun x hx y hy ↦ ?_
simp only [mem_iInter] at hS hx
exact hS fun z hz ↦ le_trans (hx ⟨z, hz⟩) hy
theorem eventually_forall_le_atBot [Preorder α] {p : α → Prop} :
(∀ᶠ x in atBot, ∀ y, y ≤ x → p y) ↔ ∀ᶠ x in atBot, p x :=
eventually_forall_ge_atTop (α := αᵒᵈ)
theorem Tendsto.eventually_forall_ge_atTop {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atTop) (h_evtl : ∀ᶠ x in atTop, p x) :
∀ᶠ x in l, ∀ y, f x ≤ y → p y := by
rw [← Filter.eventually_forall_ge_atTop] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem Tendsto.eventually_forall_le_atBot {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atBot) (h_evtl : ∀ᶠ x in atBot, p x) :
∀ᶠ x in l, ∀ y, y ≤ f x → p y := by
rw [← Filter.eventually_forall_le_atBot] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem atTop_basis_Ioi [Nonempty α] [SemilatticeSup α] [NoMaxOrder α] :
(@atTop α _).HasBasis (fun _ => True) Ioi :=
atTop_basis.to_hasBasis (fun a ha => ⟨a, ha, Ioi_subset_Ici_self⟩) fun a ha =>
(exists_gt a).imp fun _b hb => ⟨ha, Ici_subset_Ioi.2 hb⟩
#align filter.at_top_basis_Ioi Filter.atTop_basis_Ioi
lemma atTop_basis_Ioi' [SemilatticeSup α] [NoMaxOrder α] (a : α) : atTop.HasBasis (a < ·) Ioi :=
have : Nonempty α := ⟨a⟩
atTop_basis_Ioi.to_hasBasis (fun b _ ↦
let ⟨c, hc⟩ := exists_gt (a ⊔ b)
⟨c, le_sup_left.trans_lt hc, Ioi_subset_Ioi <| le_sup_right.trans hc.le⟩) fun b _ ↦
⟨b, trivial, Subset.rfl⟩
theorem atTop_countable_basis [Nonempty α] [SemilatticeSup α] [Countable α] :
HasCountableBasis (atTop : Filter α) (fun _ => True) Ici :=
{ atTop_basis with countable := to_countable _ }
#align filter.at_top_countable_basis Filter.atTop_countable_basis
theorem atBot_countable_basis [Nonempty α] [SemilatticeInf α] [Countable α] :
HasCountableBasis (atBot : Filter α) (fun _ => True) Iic :=
{ atBot_basis with countable := to_countable _ }
#align filter.at_bot_countable_basis Filter.atBot_countable_basis
instance (priority := 200) atTop.isCountablyGenerated [Preorder α] [Countable α] :
(atTop : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_top.is_countably_generated Filter.atTop.isCountablyGenerated
instance (priority := 200) atBot.isCountablyGenerated [Preorder α] [Countable α] :
(atBot : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_bot.is_countably_generated Filter.atBot.isCountablyGenerated
theorem _root_.IsTop.atTop_eq [Preorder α] {a : α} (ha : IsTop a) : atTop = 𝓟 (Ici a) :=
(iInf_le _ _).antisymm <| le_iInf fun b ↦ principal_mono.2 <| Ici_subset_Ici.2 <| ha b
theorem _root_.IsBot.atBot_eq [Preorder α] {a : α} (ha : IsBot a) : atBot = 𝓟 (Iic a) :=
ha.toDual.atTop_eq
theorem OrderTop.atTop_eq (α) [PartialOrder α] [OrderTop α] : (atTop : Filter α) = pure ⊤ := by
rw [isTop_top.atTop_eq, Ici_top, principal_singleton]
#align filter.order_top.at_top_eq Filter.OrderTop.atTop_eq
theorem OrderBot.atBot_eq (α) [PartialOrder α] [OrderBot α] : (atBot : Filter α) = pure ⊥ :=
@OrderTop.atTop_eq αᵒᵈ _ _
#align filter.order_bot.at_bot_eq Filter.OrderBot.atBot_eq
@[nontriviality]
theorem Subsingleton.atTop_eq (α) [Subsingleton α] [Preorder α] : (atTop : Filter α) = ⊤ := by
refine top_unique fun s hs x => ?_
rw [atTop, ciInf_subsingleton x, mem_principal] at hs
exact hs left_mem_Ici
#align filter.subsingleton.at_top_eq Filter.Subsingleton.atTop_eq
@[nontriviality]
theorem Subsingleton.atBot_eq (α) [Subsingleton α] [Preorder α] : (atBot : Filter α) = ⊤ :=
@Subsingleton.atTop_eq αᵒᵈ _ _
#align filter.subsingleton.at_bot_eq Filter.Subsingleton.atBot_eq
theorem tendsto_atTop_pure [PartialOrder α] [OrderTop α] (f : α → β) :
Tendsto f atTop (pure <| f ⊤) :=
(OrderTop.atTop_eq α).symm ▸ tendsto_pure_pure _ _
#align filter.tendsto_at_top_pure Filter.tendsto_atTop_pure
theorem tendsto_atBot_pure [PartialOrder α] [OrderBot α] (f : α → β) :
Tendsto f atBot (pure <| f ⊥) :=
@tendsto_atTop_pure αᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_pure Filter.tendsto_atBot_pure
theorem Eventually.exists_forall_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atTop, p x) : ∃ a, ∀ b ≥ a, p b :=
eventually_atTop.mp h
#align filter.eventually.exists_forall_of_at_top Filter.Eventually.exists_forall_of_atTop
theorem Eventually.exists_forall_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atBot, p x) : ∃ a, ∀ b ≤ a, p b :=
eventually_atBot.mp h
#align filter.eventually.exists_forall_of_at_bot Filter.Eventually.exists_forall_of_atBot
lemma exists_eventually_atTop [SemilatticeSup α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atTop, r a b) ↔ ∀ᶠ a₀ in atTop, ∃ b, ∀ a ≥ a₀, r a b := by
simp_rw [eventually_atTop, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_ge_iff <| Monotone.exists fun _ _ _ hb H n hn ↦
H n (hb.trans hn)
lemma exists_eventually_atBot [SemilatticeInf α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atBot, r a b) ↔ ∀ᶠ a₀ in atBot, ∃ b, ∀ a ≤ a₀, r a b := by
simp_rw [eventually_atBot, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_le_iff <| Antitone.exists fun _ _ _ hb H n hn ↦
H n (hn.trans hb)
theorem frequently_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b ≥ a, p b :=
atTop_basis.frequently_iff.trans <| by simp
#align filter.frequently_at_top Filter.frequently_atTop
theorem frequently_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b ≤ a, p b :=
@frequently_atTop αᵒᵈ _ _ _
#align filter.frequently_at_bot Filter.frequently_atBot
theorem frequently_atTop' [SemilatticeSup α] [Nonempty α] [NoMaxOrder α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b > a, p b :=
atTop_basis_Ioi.frequently_iff.trans <| by simp
#align filter.frequently_at_top' Filter.frequently_atTop'
theorem frequently_atBot' [SemilatticeInf α] [Nonempty α] [NoMinOrder α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b < a, p b :=
@frequently_atTop' αᵒᵈ _ _ _ _
#align filter.frequently_at_bot' Filter.frequently_atBot'
theorem Frequently.forall_exists_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atTop, p x) : ∀ a, ∃ b ≥ a, p b :=
frequently_atTop.mp h
#align filter.frequently.forall_exists_of_at_top Filter.Frequently.forall_exists_of_atTop
theorem Frequently.forall_exists_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atBot, p x) : ∀ a, ∃ b ≤ a, p b :=
frequently_atBot.mp h
#align filter.frequently.forall_exists_of_at_bot Filter.Frequently.forall_exists_of_atBot
theorem map_atTop_eq [Nonempty α] [SemilatticeSup α] {f : α → β} :
atTop.map f = ⨅ a, 𝓟 (f '' { a' | a ≤ a' }) :=
(atTop_basis.map f).eq_iInf
#align filter.map_at_top_eq Filter.map_atTop_eq
theorem map_atBot_eq [Nonempty α] [SemilatticeInf α] {f : α → β} :
atBot.map f = ⨅ a, 𝓟 (f '' { a' | a' ≤ a }) :=
@map_atTop_eq αᵒᵈ _ _ _ _
#align filter.map_at_bot_eq Filter.map_atBot_eq
theorem tendsto_atTop [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atTop ↔ ∀ b, ∀ᶠ a in f, b ≤ m a := by
simp only [atTop, tendsto_iInf, tendsto_principal, mem_Ici]
#align filter.tendsto_at_top Filter.tendsto_atTop
theorem tendsto_atBot [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atBot ↔ ∀ b, ∀ᶠ a in f, m a ≤ b :=
@tendsto_atTop α βᵒᵈ _ m f
#align filter.tendsto_at_bot Filter.tendsto_atBot
theorem tendsto_atTop_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂)
(h₁ : Tendsto f₁ l atTop) : Tendsto f₂ l atTop :=
tendsto_atTop.2 fun b => by filter_upwards [tendsto_atTop.1 h₁ b, h] with x using le_trans
#align filter.tendsto_at_top_mono' Filter.tendsto_atTop_mono'
theorem tendsto_atBot_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂) :
Tendsto f₂ l atBot → Tendsto f₁ l atBot :=
@tendsto_atTop_mono' _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono' Filter.tendsto_atBot_mono'
theorem tendsto_atTop_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto f l atTop → Tendsto g l atTop :=
tendsto_atTop_mono' l <| eventually_of_forall h
#align filter.tendsto_at_top_mono Filter.tendsto_atTop_mono
theorem tendsto_atBot_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto g l atBot → Tendsto f l atBot :=
@tendsto_atTop_mono _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono Filter.tendsto_atBot_mono
lemma atTop_eq_generate_of_forall_exists_le [LinearOrder α] {s : Set α} (hs : ∀ x, ∃ y ∈ s, x ≤ y) :
(atTop : Filter α) = generate (Ici '' s) := by
rw [atTop_eq_generate_Ici]
apply le_antisymm
· rw [le_generate_iff]
rintro - ⟨y, -, rfl⟩
exact mem_generate_of_mem ⟨y, rfl⟩
· rw [le_generate_iff]
rintro - ⟨x, -, -, rfl⟩
rcases hs x with ⟨y, ys, hy⟩
have A : Ici y ∈ generate (Ici '' s) := mem_generate_of_mem (mem_image_of_mem _ ys)
have B : Ici y ⊆ Ici x := Ici_subset_Ici.2 hy
exact sets_of_superset (generate (Ici '' s)) A B
lemma atTop_eq_generate_of_not_bddAbove [LinearOrder α] {s : Set α} (hs : ¬ BddAbove s) :
(atTop : Filter α) = generate (Ici '' s) := by
refine atTop_eq_generate_of_forall_exists_le fun x ↦ ?_
obtain ⟨y, hy, hy'⟩ := not_bddAbove_iff.mp hs x
exact ⟨y, hy, hy'.le⟩
end Filter
namespace OrderIso
open Filter
variable [Preorder α] [Preorder β]
@[simp]
theorem comap_atTop (e : α ≃o β) : comap e atTop = atTop := by
simp [atTop, ← e.surjective.iInf_comp]
#align order_iso.comap_at_top OrderIso.comap_atTop
@[simp]
theorem comap_atBot (e : α ≃o β) : comap e atBot = atBot :=
e.dual.comap_atTop
#align order_iso.comap_at_bot OrderIso.comap_atBot
@[simp]
theorem map_atTop (e : α ≃o β) : map (e : α → β) atTop = atTop := by
rw [← e.comap_atTop, map_comap_of_surjective e.surjective]
#align order_iso.map_at_top OrderIso.map_atTop
@[simp]
theorem map_atBot (e : α ≃o β) : map (e : α → β) atBot = atBot :=
e.dual.map_atTop
#align order_iso.map_at_bot OrderIso.map_atBot
theorem tendsto_atTop (e : α ≃o β) : Tendsto e atTop atTop :=
e.map_atTop.le
#align order_iso.tendsto_at_top OrderIso.tendsto_atTop
theorem tendsto_atBot (e : α ≃o β) : Tendsto e atBot atBot :=
e.map_atBot.le
#align order_iso.tendsto_at_bot OrderIso.tendsto_atBot
@[simp]
theorem tendsto_atTop_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atTop ↔ Tendsto f l atTop := by
rw [← e.comap_atTop, tendsto_comap_iff, Function.comp_def]
#align order_iso.tendsto_at_top_iff OrderIso.tendsto_atTop_iff
@[simp]
theorem tendsto_atBot_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atBot ↔ Tendsto f l atBot :=
e.dual.tendsto_atTop_iff
#align order_iso.tendsto_at_bot_iff OrderIso.tendsto_atBot_iff
end OrderIso
namespace Filter
/-!
### Sequences
-/
theorem inf_map_atTop_neBot_iff [SemilatticeSup α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atTop) ↔ ∀ U ∈ F, ∀ N, ∃ n ≥ N, u n ∈ U := by
simp_rw [inf_neBot_iff_frequently_left, frequently_map, frequently_atTop]; rfl
#align filter.inf_map_at_top_ne_bot_iff Filter.inf_map_atTop_neBot_iff
theorem inf_map_atBot_neBot_iff [SemilatticeInf α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atBot) ↔ ∀ U ∈ F, ∀ N, ∃ n ≤ N, u n ∈ U :=
@inf_map_atTop_neBot_iff αᵒᵈ _ _ _ _ _
#align filter.inf_map_at_bot_ne_bot_iff Filter.inf_map_atBot_neBot_iff
theorem extraction_of_frequently_atTop' {P : ℕ → Prop} (h : ∀ N, ∃ n > N, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
choose u hu hu' using h
refine ⟨fun n => u^[n + 1] 0, strictMono_nat_of_lt_succ fun n => ?_, fun n => ?_⟩
· exact Trans.trans (hu _) (Function.iterate_succ_apply' _ _ _).symm
· simpa only [Function.iterate_succ_apply'] using hu' _
#align filter.extraction_of_frequently_at_top' Filter.extraction_of_frequently_atTop'
theorem extraction_of_frequently_atTop {P : ℕ → Prop} (h : ∃ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
rw [frequently_atTop'] at h
exact extraction_of_frequently_atTop' h
#align filter.extraction_of_frequently_at_top Filter.extraction_of_frequently_atTop
theorem extraction_of_eventually_atTop {P : ℕ → Prop} (h : ∀ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) :=
extraction_of_frequently_atTop h.frequently
#align filter.extraction_of_eventually_at_top Filter.extraction_of_eventually_atTop
theorem extraction_forall_of_frequently {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) := by
simp only [frequently_atTop'] at h
choose u hu hu' using h
use (fun n => Nat.recOn n (u 0 0) fun n v => u (n + 1) v : ℕ → ℕ)
constructor
· apply strictMono_nat_of_lt_succ
intro n
apply hu
· intro n
cases n <;> simp [hu']
#align filter.extraction_forall_of_frequently Filter.extraction_forall_of_frequently
theorem extraction_forall_of_eventually {P : ℕ → ℕ → Prop} (h : ∀ n, ∀ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_frequently fun n => (h n).frequently
#align filter.extraction_forall_of_eventually Filter.extraction_forall_of_eventually
theorem extraction_forall_of_eventually' {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ N, ∀ k ≥ N, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_eventually (by simp [eventually_atTop, h])
#align filter.extraction_forall_of_eventually' Filter.extraction_forall_of_eventually'
theorem Eventually.atTop_of_arithmetic {p : ℕ → Prop} {n : ℕ} (hn : n ≠ 0)
(hp : ∀ k < n, ∀ᶠ a in atTop, p (n * a + k)) : ∀ᶠ a in atTop, p a := by
simp only [eventually_atTop] at hp ⊢
choose! N hN using hp
refine ⟨(Finset.range n).sup (n * N ·), fun b hb => ?_⟩
rw [← Nat.div_add_mod b n]
have hlt := Nat.mod_lt b hn.bot_lt
refine hN _ hlt _ ?_
rw [ge_iff_le, Nat.le_div_iff_mul_le hn.bot_lt, mul_comm]
exact (Finset.le_sup (f := (n * N ·)) (Finset.mem_range.2 hlt)).trans hb
theorem exists_le_of_tendsto_atTop [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b ≤ u a' := by
have : Nonempty α := ⟨a⟩
have : ∀ᶠ x in atTop, a ≤ x ∧ b ≤ u x :=
(eventually_ge_atTop a).and (h.eventually <| eventually_ge_atTop b)
exact this.exists
#align filter.exists_le_of_tendsto_at_top Filter.exists_le_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_le_of_tendsto_atBot [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' ≤ b :=
@exists_le_of_tendsto_atTop _ βᵒᵈ _ _ _ h
#align filter.exists_le_of_tendsto_at_bot Filter.exists_le_of_tendsto_atBot
theorem exists_lt_of_tendsto_atTop [SemilatticeSup α] [Preorder β] [NoMaxOrder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b < u a' := by
cases' exists_gt b with b' hb'
rcases exists_le_of_tendsto_atTop h a b' with ⟨a', ha', ha''⟩
exact ⟨a', ha', lt_of_lt_of_le hb' ha''⟩
#align filter.exists_lt_of_tendsto_at_top Filter.exists_lt_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_lt_of_tendsto_atBot [SemilatticeSup α] [Preorder β] [NoMinOrder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' < b :=
@exists_lt_of_tendsto_atTop _ βᵒᵈ _ _ _ _ h
#align filter.exists_lt_of_tendsto_at_bot Filter.exists_lt_of_tendsto_atBot
/-- If `u` is a sequence which is unbounded above,
then after any point, it reaches a value strictly greater than all previous values.
-/
theorem high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β} (hu : Tendsto u atTop atTop) :
∀ N, ∃ n ≥ N, ∀ k < n, u k < u n := by
intro N
obtain ⟨k : ℕ, - : k ≤ N, hku : ∀ l ≤ N, u l ≤ u k⟩ : ∃ k ≤ N, ∀ l ≤ N, u l ≤ u k :=
exists_max_image _ u (finite_le_nat N) ⟨N, le_refl N⟩
have ex : ∃ n ≥ N, u k < u n := exists_lt_of_tendsto_atTop hu _ _
obtain ⟨n : ℕ, hnN : n ≥ N, hnk : u k < u n, hn_min : ∀ m, m < n → N ≤ m → u m ≤ u k⟩ :
∃ n ≥ N, u k < u n ∧ ∀ m, m < n → N ≤ m → u m ≤ u k := by
rcases Nat.findX ex with ⟨n, ⟨hnN, hnk⟩, hn_min⟩
push_neg at hn_min
exact ⟨n, hnN, hnk, hn_min⟩
use n, hnN
rintro (l : ℕ) (hl : l < n)
have hlk : u l ≤ u k := by
cases' (le_total l N : l ≤ N ∨ N ≤ l) with H H
· exact hku l H
· exact hn_min l hl H
calc
u l ≤ u k := hlk
_ < u n := hnk
#align filter.high_scores Filter.high_scores
-- see Note [nolint_ge]
/-- If `u` is a sequence which is unbounded below,
then after any point, it reaches a value strictly smaller than all previous values.
-/
-- @[nolint ge_or_gt] Porting note: restore attribute
theorem low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β} (hu : Tendsto u atTop atBot) :
∀ N, ∃ n ≥ N, ∀ k < n, u n < u k :=
@high_scores βᵒᵈ _ _ _ hu
#align filter.low_scores Filter.low_scores
/-- If `u` is a sequence which is unbounded above,
then it `Frequently` reaches a value strictly greater than all previous values.
-/
theorem frequently_high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ᶠ n in atTop, ∀ k < n, u k < u n := by
simpa [frequently_atTop] using high_scores hu
#align filter.frequently_high_scores Filter.frequently_high_scores
/-- If `u` is a sequence which is unbounded below,
then it `Frequently` reaches a value strictly smaller than all previous values.
-/
theorem frequently_low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atBot) : ∃ᶠ n in atTop, ∀ k < n, u n < u k :=
@frequently_high_scores βᵒᵈ _ _ _ hu
#align filter.frequently_low_scores Filter.frequently_low_scores
theorem strictMono_subseq_of_tendsto_atTop {β : Type*} [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
let ⟨φ, h, h'⟩ := extraction_of_frequently_atTop (frequently_high_scores hu)
⟨φ, h, fun _ m hnm => h' m _ (h hnm)⟩
#align filter.strict_mono_subseq_of_tendsto_at_top Filter.strictMono_subseq_of_tendsto_atTop
theorem strictMono_subseq_of_id_le {u : ℕ → ℕ} (hu : ∀ n, n ≤ u n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
strictMono_subseq_of_tendsto_atTop (tendsto_atTop_mono hu tendsto_id)
#align filter.strict_mono_subseq_of_id_le Filter.strictMono_subseq_of_id_le
theorem _root_.StrictMono.tendsto_atTop {φ : ℕ → ℕ} (h : StrictMono φ) : Tendsto φ atTop atTop :=
tendsto_atTop_mono h.id_le tendsto_id
#align strict_mono.tendsto_at_top StrictMono.tendsto_atTop
section OrderedAddCommMonoid
variable [OrderedAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_add_nonneg_left' (hf : ∀ᶠ x in l, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (hf.mono fun _ => le_add_of_nonneg_left) hg
#align filter.tendsto_at_top_add_nonneg_left' Filter.tendsto_atTop_add_nonneg_left'
theorem tendsto_atBot_add_nonpos_left' (hf : ∀ᶠ x in l, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left' Filter.tendsto_atBot_add_nonpos_left'
theorem tendsto_atTop_add_nonneg_left (hf : ∀ x, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (eventually_of_forall hf) hg
#align filter.tendsto_at_top_add_nonneg_left Filter.tendsto_atTop_add_nonneg_left
theorem tendsto_atBot_add_nonpos_left (hf : ∀ x, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left Filter.tendsto_atBot_add_nonpos_left
theorem tendsto_atTop_add_nonneg_right' (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (monotone_mem (fun _ => le_add_of_nonneg_right) hg) hf
#align filter.tendsto_at_top_add_nonneg_right' Filter.tendsto_atTop_add_nonneg_right'
theorem tendsto_atBot_add_nonpos_right' (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right' Filter.tendsto_atBot_add_nonpos_right'
theorem tendsto_atTop_add_nonneg_right (hf : Tendsto f l atTop) (hg : ∀ x, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_right' hf (eventually_of_forall hg)
#align filter.tendsto_at_top_add_nonneg_right Filter.tendsto_atTop_add_nonneg_right
theorem tendsto_atBot_add_nonpos_right (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right Filter.tendsto_atBot_add_nonpos_right
theorem tendsto_atTop_add (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (tendsto_atTop.mp hf 0) hg
#align filter.tendsto_at_top_add Filter.tendsto_atTop_add
theorem tendsto_atBot_add (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add Filter.tendsto_atBot_add
theorem Tendsto.nsmul_atTop (hf : Tendsto f l atTop) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atTop :=
tendsto_atTop.2 fun y =>
(tendsto_atTop.1 hf y).mp <|
(tendsto_atTop.1 hf 0).mono fun x h₀ hy =>
calc
y ≤ f x := hy
_ = 1 • f x := (one_nsmul _).symm
_ ≤ n • f x := nsmul_le_nsmul_left h₀ hn
#align filter.tendsto.nsmul_at_top Filter.Tendsto.nsmul_atTop
theorem Tendsto.nsmul_atBot (hf : Tendsto f l atBot) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atBot :=
@Tendsto.nsmul_atTop α βᵒᵈ _ l f hf n hn
#align filter.tendsto.nsmul_at_bot Filter.Tendsto.nsmul_atBot
#noalign filter.tendsto_bit0_at_top
#noalign filter.tendsto_bit0_at_bot
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [OrderedCancelAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_top_of_add_const_left Filter.tendsto_atTop_of_add_const_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_bot_of_add_const_left Filter.tendsto_atBot_of_add_const_left
theorem tendsto_atTop_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_top_of_add_const_right Filter.tendsto_atTop_of_add_const_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_bot_of_add_const_right Filter.tendsto_atBot_of_add_const_right
theorem tendsto_atTop_of_add_bdd_above_left' (C) (hC : ∀ᶠ x in l, f x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto g l atTop :=
tendsto_atTop_of_add_const_left C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_left' Filter.tendsto_atTop_of_add_bdd_above_left'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left' (C) (hC : ∀ᶠ x in l, C ≤ f x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto g l atBot :=
tendsto_atBot_of_add_const_left C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_left' Filter.tendsto_atBot_of_add_bdd_below_left'
theorem tendsto_atTop_of_add_bdd_above_left (C) (hC : ∀ x, f x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto g l atTop :=
tendsto_atTop_of_add_bdd_above_left' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_left Filter.tendsto_atTop_of_add_bdd_above_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left (C) (hC : ∀ x, C ≤ f x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto g l atBot :=
tendsto_atBot_of_add_bdd_below_left' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_left Filter.tendsto_atBot_of_add_bdd_below_left
theorem tendsto_atTop_of_add_bdd_above_right' (C) (hC : ∀ᶠ x in l, g x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto f l atTop :=
tendsto_atTop_of_add_const_right C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_right' Filter.tendsto_atTop_of_add_bdd_above_right'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right' (C) (hC : ∀ᶠ x in l, C ≤ g x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto f l atBot :=
tendsto_atBot_of_add_const_right C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_right' Filter.tendsto_atBot_of_add_bdd_below_right'
theorem tendsto_atTop_of_add_bdd_above_right (C) (hC : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto f l atTop :=
tendsto_atTop_of_add_bdd_above_right' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_right Filter.tendsto_atTop_of_add_bdd_above_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right (C) (hC : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto f l atBot :=
tendsto_atBot_of_add_bdd_below_right' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_right Filter.tendsto_atBot_of_add_bdd_below_right
end OrderedCancelAddCommMonoid
section OrderedGroup
variable [OrderedAddCommGroup β] (l : Filter α) {f g : α → β}
theorem tendsto_atTop_add_left_of_le' (C : β) (hf : ∀ᶠ x in l, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_left' _ _ _ l (fun x => -f x) (fun x => f x + g x) (-C) (by simpa)
(by simpa)
#align filter.tendsto_at_top_add_left_of_le' Filter.tendsto_atTop_add_left_of_le'
theorem tendsto_atBot_add_left_of_ge' (C : β) (hf : ∀ᶠ x in l, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge' Filter.tendsto_atBot_add_left_of_ge'
theorem tendsto_atTop_add_left_of_le (C : β) (hf : ∀ x, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' hf) hg
#align filter.tendsto_at_top_add_left_of_le Filter.tendsto_atTop_add_left_of_le
theorem tendsto_atBot_add_left_of_ge (C : β) (hf : ∀ x, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge Filter.tendsto_atBot_add_left_of_ge
theorem tendsto_atTop_add_right_of_le' (C : β) (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_right' _ _ _ l (fun x => f x + g x) (fun x => -g x) (-C)
(by simp [hg]) (by simp [hf])
#align filter.tendsto_at_top_add_right_of_le' Filter.tendsto_atTop_add_right_of_le'
theorem tendsto_atBot_add_right_of_ge' (C : β) (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge' Filter.tendsto_atBot_add_right_of_ge'
theorem tendsto_atTop_add_right_of_le (C : β) (hf : Tendsto f l atTop) (hg : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' hg)
#align filter.tendsto_at_top_add_right_of_le Filter.tendsto_atTop_add_right_of_le
theorem tendsto_atBot_add_right_of_ge (C : β) (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge Filter.tendsto_atBot_add_right_of_ge
theorem tendsto_atTop_add_const_left (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => C + f x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' fun _ => le_refl C) hf
#align filter.tendsto_at_top_add_const_left Filter.tendsto_atTop_add_const_left
theorem tendsto_atBot_add_const_left (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => C + f x) l atBot :=
@tendsto_atTop_add_const_left _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_left Filter.tendsto_atBot_add_const_left
theorem tendsto_atTop_add_const_right (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x + C) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' fun _ => le_refl C)
#align filter.tendsto_at_top_add_const_right Filter.tendsto_atTop_add_const_right
theorem tendsto_atBot_add_const_right (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x + C) l atBot :=
@tendsto_atTop_add_const_right _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_right Filter.tendsto_atBot_add_const_right
theorem map_neg_atBot : map (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).map_atBot
#align filter.map_neg_at_bot Filter.map_neg_atBot
theorem map_neg_atTop : map (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).map_atTop
#align filter.map_neg_at_top Filter.map_neg_atTop
theorem comap_neg_atBot : comap (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).comap_atTop
#align filter.comap_neg_at_bot Filter.comap_neg_atBot
theorem comap_neg_atTop : comap (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).comap_atBot
#align filter.comap_neg_at_top Filter.comap_neg_atTop
theorem tendsto_neg_atTop_atBot : Tendsto (Neg.neg : β → β) atTop atBot :=
(OrderIso.neg β).tendsto_atTop
#align filter.tendsto_neg_at_top_at_bot Filter.tendsto_neg_atTop_atBot
theorem tendsto_neg_atBot_atTop : Tendsto (Neg.neg : β → β) atBot atTop :=
@tendsto_neg_atTop_atBot βᵒᵈ _
#align filter.tendsto_neg_at_bot_at_top Filter.tendsto_neg_atBot_atTop
variable {l}
@[simp]
theorem tendsto_neg_atTop_iff : Tendsto (fun x => -f x) l atTop ↔ Tendsto f l atBot :=
(OrderIso.neg β).tendsto_atBot_iff
#align filter.tendsto_neg_at_top_iff Filter.tendsto_neg_atTop_iff
@[simp]
theorem tendsto_neg_atBot_iff : Tendsto (fun x => -f x) l atBot ↔ Tendsto f l atTop :=
(OrderIso.neg β).tendsto_atTop_iff
#align filter.tendsto_neg_at_bot_iff Filter.tendsto_neg_atBot_iff
end OrderedGroup
section OrderedSemiring
variable [OrderedSemiring α] {l : Filter β} {f g : β → α}
#noalign filter.tendsto_bit1_at_top
theorem Tendsto.atTop_mul_atTop (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atTop := by
refine tendsto_atTop_mono' _ ?_ hg
filter_upwards [hg.eventually (eventually_ge_atTop 0),
hf.eventually (eventually_ge_atTop 1)] with _ using le_mul_of_one_le_left
#align filter.tendsto.at_top_mul_at_top Filter.Tendsto.atTop_mul_atTop
theorem tendsto_mul_self_atTop : Tendsto (fun x : α => x * x) atTop atTop :=
tendsto_id.atTop_mul_atTop tendsto_id
#align filter.tendsto_mul_self_at_top Filter.tendsto_mul_self_atTop
/-- The monomial function `x^n` tends to `+∞` at `+∞` for any positive natural `n`.
A version for positive real powers exists as `tendsto_rpow_atTop`. -/
theorem tendsto_pow_atTop {n : ℕ} (hn : n ≠ 0) : Tendsto (fun x : α => x ^ n) atTop atTop :=
tendsto_atTop_mono' _ ((eventually_ge_atTop 1).mono fun _x hx => le_self_pow hx hn) tendsto_id
#align filter.tendsto_pow_at_top Filter.tendsto_pow_atTop
end OrderedSemiring
theorem zero_pow_eventuallyEq [MonoidWithZero α] :
(fun n : ℕ => (0 : α) ^ n) =ᶠ[atTop] fun _ => 0 :=
eventually_atTop.2 ⟨1, fun _n hn ↦ zero_pow $ Nat.one_le_iff_ne_zero.1 hn⟩
#align filter.zero_pow_eventually_eq Filter.zero_pow_eventuallyEq
section OrderedRing
variable [OrderedRing α] {l : Filter β} {f g : β → α}
theorem Tendsto.atTop_mul_atBot (hf : Tendsto f l atTop) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atBot := by
have := hf.atTop_mul_atTop <| tendsto_neg_atBot_atTop.comp hg
simpa only [(· ∘ ·), neg_mul_eq_mul_neg, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_top_mul_at_bot Filter.Tendsto.atTop_mul_atBot
theorem Tendsto.atBot_mul_atTop (hf : Tendsto f l atBot) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atBot := by
have : Tendsto (fun x => -f x * g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop hg
simpa only [(· ∘ ·), neg_mul_eq_neg_mul, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_bot_mul_at_top Filter.Tendsto.atBot_mul_atTop
theorem Tendsto.atBot_mul_atBot (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atTop := by
have : Tendsto (fun x => -f x * -g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop (tendsto_neg_atBot_atTop.comp hg)
simpa only [neg_mul_neg] using this
#align filter.tendsto.at_bot_mul_at_bot Filter.Tendsto.atBot_mul_atBot
end OrderedRing
section LinearOrderedAddCommGroup
variable [LinearOrderedAddCommGroup α]
/-- $\lim_{x\to+\infty}|x|=+\infty$ -/
theorem tendsto_abs_atTop_atTop : Tendsto (abs : α → α) atTop atTop :=
tendsto_atTop_mono le_abs_self tendsto_id
#align filter.tendsto_abs_at_top_at_top Filter.tendsto_abs_atTop_atTop
/-- $\lim_{x\to-\infty}|x|=+\infty$ -/
theorem tendsto_abs_atBot_atTop : Tendsto (abs : α → α) atBot atTop :=
tendsto_atTop_mono neg_le_abs tendsto_neg_atBot_atTop
#align filter.tendsto_abs_at_bot_at_top Filter.tendsto_abs_atBot_atTop
@[simp]
theorem comap_abs_atTop : comap (abs : α → α) atTop = atBot ⊔ atTop := by
refine
le_antisymm (((atTop_basis.comap _).le_basis_iff (atBot_basis.sup atTop_basis)).2 ?_)
(sup_le tendsto_abs_atBot_atTop.le_comap tendsto_abs_atTop_atTop.le_comap)
rintro ⟨a, b⟩ -
refine ⟨max (-a) b, trivial, fun x hx => ?_⟩
rw [mem_preimage, mem_Ici, le_abs', max_le_iff, ← min_neg_neg, le_min_iff, neg_neg] at hx
exact hx.imp And.left And.right
#align filter.comap_abs_at_top Filter.comap_abs_atTop
end LinearOrderedAddCommGroup
section LinearOrderedSemiring
variable [LinearOrderedSemiring α] {l : Filter β} {f : β → α}
theorem Tendsto.atTop_of_const_mul {c : α} (hc : 0 < c) (hf : Tendsto (fun x => c * f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (c * b)).mono
fun _x hx => le_of_mul_le_mul_left hx hc
#align filter.tendsto.at_top_of_const_mul Filter.Tendsto.atTop_of_const_mul
theorem Tendsto.atTop_of_mul_const {c : α} (hc : 0 < c) (hf : Tendsto (fun x => f x * c) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b * c)).mono
fun _x hx => le_of_mul_le_mul_right hx hc
#align filter.tendsto.at_top_of_mul_const Filter.Tendsto.atTop_of_mul_const
@[simp]
theorem tendsto_pow_atTop_iff {n : ℕ} : Tendsto (fun x : α => x ^ n) atTop atTop ↔ n ≠ 0 :=
⟨fun h hn => by simp only [hn, pow_zero, not_tendsto_const_atTop] at h, tendsto_pow_atTop⟩
#align filter.tendsto_pow_at_top_iff Filter.tendsto_pow_atTop_iff
end LinearOrderedSemiring
theorem not_tendsto_pow_atTop_atBot [LinearOrderedRing α] :
∀ {n : ℕ}, ¬Tendsto (fun x : α => x ^ n) atTop atBot
| 0 => by simp [not_tendsto_const_atBot]
| n + 1 => (tendsto_pow_atTop n.succ_ne_zero).not_tendsto disjoint_atTop_atBot
#align filter.not_tendsto_pow_at_top_at_bot Filter.not_tendsto_pow_atTop_atBot
section LinearOrderedSemifield
variable [LinearOrderedSemifield α] {l : Filter β} {f : β → α} {r c : α} {n : ℕ}
/-!
### Multiplication by constant: iff lemmas
-/
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_const_mul_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atTop :=
⟨fun h => h.atTop_of_const_mul hr, fun h =>
Tendsto.atTop_of_const_mul (inv_pos.2 hr) <| by simpa only [inv_mul_cancel_left₀ hr.ne'] ⟩
#align filter.tendsto_const_mul_at_top_of_pos Filter.tendsto_const_mul_atTop_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_mul_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_mul_const_at_top_of_pos Filter.tendsto_mul_const_atTop_of_pos
/-- If `r` is a positive constant, `x ↦ f x / r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
lemma tendsto_div_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atTop := by
simpa only [div_eq_mul_inv] using tendsto_mul_const_atTop_of_pos (inv_pos.2 hr)
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r := by
refine ⟨fun hrf => not_le.mp fun hr => ?_, fun hr => (tendsto_const_mul_atTop_of_pos hr).mpr h⟩
rcases ((h.eventually_ge_atTop 0).and (hrf.eventually_gt_atTop 0)).exists with ⟨x, hx, hrx⟩
exact (mul_nonpos_of_nonpos_of_nonneg hr hx).not_lt hrx
#align filter.tendsto_const_mul_at_top_iff_pos Filter.tendsto_const_mul_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_pos h]
#align filter.tendsto_mul_const_at_top_iff_pos Filter.tendsto_mul_const_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r := by
simp only [div_eq_mul_inv, tendsto_mul_const_atTop_iff_pos h, inv_pos]
/-- If `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the left) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.const_mul_atTop'` instead. -/
theorem Tendsto.const_mul_atTop (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_top Filter.Tendsto.const_mul_atTop
/-- If a function `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the right) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.atTop_mul_const'` instead. -/
theorem Tendsto.atTop_mul_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_pos hr).2 hf
#align filter.tendsto.at_top_mul_const Filter.Tendsto.atTop_mul_const
/-- If a function `f` tends to infinity along a filter, then `f` divided by a positive
constant also tends to infinity. -/
theorem Tendsto.atTop_div_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x / r) l atTop := by
simpa only [div_eq_mul_inv] using hf.atTop_mul_const (inv_pos.2 hr)
#align filter.tendsto.at_top_div_const Filter.Tendsto.atTop_div_const
theorem tendsto_const_mul_pow_atTop (hn : n ≠ 0) (hc : 0 < c) :
Tendsto (fun x => c * x ^ n) atTop atTop :=
Tendsto.const_mul_atTop hc (tendsto_pow_atTop hn)
#align filter.tendsto_const_mul_pow_at_top Filter.tendsto_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atTop_iff :
Tendsto (fun x => c * x ^ n) atTop atTop ↔ n ≠ 0 ∧ 0 < c := by
refine ⟨fun h => ⟨?_, ?_⟩, fun h => tendsto_const_mul_pow_atTop h.1 h.2⟩
· rintro rfl
simp only [pow_zero, not_tendsto_const_atTop] at h
· rcases ((h.eventually_gt_atTop 0).and (eventually_ge_atTop 0)).exists with ⟨k, hck, hk⟩
exact pos_of_mul_pos_left hck (pow_nonneg hk _)
#align filter.tendsto_const_mul_pow_at_top_iff Filter.tendsto_const_mul_pow_atTop_iff
lemma tendsto_zpow_atTop_atTop {n : ℤ} (hn : 0 < n) : Tendsto (fun x : α ↦ x ^ n) atTop atTop := by
lift n to ℕ+ using hn; simp
#align tendsto_zpow_at_top_at_top Filter.tendsto_zpow_atTop_atTop
end LinearOrderedSemifield
section LinearOrderedField
variable [LinearOrderedField α] {l : Filter β} {f : β → α} {r : α}
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_const_mul_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atBot := by
simpa only [← mul_neg, ← tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_const_mul_at_bot_of_pos Filter.tendsto_const_mul_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_mul_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_pos hr
#align filter.tendsto_mul_const_at_bot_of_pos Filter.tendsto_mul_const_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x / r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
lemma tendsto_div_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_pos, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_const_mul_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atBot := by
simpa only [neg_mul, tendsto_neg_atBot_iff] using tendsto_const_mul_atBot_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_top_of_neg Filter.tendsto_const_mul_atTop_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_mul_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_neg hr
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
lemma tendsto_div_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_of_neg, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_const_mul_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atTop := by
simpa only [neg_mul, tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_bot_of_neg Filter.tendsto_const_mul_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_mul_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_neg hr
#align filter.tendsto_mul_const_at_bot_of_neg Filter.tendsto_mul_const_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
lemma tendsto_div_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_neg, hr]
/-- The function `fun x ↦ r * f x` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_const_mul_atTop_iff [NeBot l] :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
rcases lt_trichotomy r 0 with (hr | rfl | hr)
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_neg]
· simp [not_tendsto_const_atTop]
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_pos]
#align filter.tendsto_const_mul_at_top_iff Filter.tendsto_const_mul_atTop_iff
/-- The function `fun x ↦ f x * r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_mul_const_atTop_iff [NeBot l] :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff]
#align filter.tendsto_mul_const_at_top_iff Filter.tendsto_mul_const_atTop_iff
/-- The function `fun x ↦ f x / r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
lemma tendsto_div_const_atTop_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff]
/-- The function `fun x ↦ r * f x` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_const_mul_atBot_iff [NeBot l] :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [← tendsto_neg_atTop_iff, ← mul_neg, tendsto_const_mul_atTop_iff, neg_neg]
#align filter.tendsto_const_mul_at_bot_iff Filter.tendsto_const_mul_atBot_iff
/-- The function `fun x ↦ f x * r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_mul_const_atBot_iff [NeBot l] :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff]
#align filter.tendsto_mul_const_at_bot_iff Filter.tendsto_mul_const_atBot_iff
/-- The function `fun x ↦ f x / r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
lemma tendsto_div_const_atBot_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff]
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ r * f x` tends to infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop ↔ r < 0 := by
simp [tendsto_const_mul_atTop_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_top_iff_neg Filter.tendsto_const_mul_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x * r` tends to infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_neg h]
#align filter.tendsto_mul_const_at_top_iff_neg Filter.tendsto_mul_const_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x / r` tends to infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atTop ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff_neg h]
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_bot_iff_pos Filter.tendsto_const_mul_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_pos h]
#align filter.tendsto_mul_const_at_bot_iff_pos Filter.tendsto_mul_const_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x / r` tends to negative infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_pos h]
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ r * f x` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot ↔ r < 0 := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atTop_atBot]
#align filter.tendsto_const_mul_at_bot_iff_neg Filter.tendsto_const_mul_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x * r` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_neg h]
#align filter.tendsto_mul_const_at_bot_iff_neg Filter.tendsto_mul_const_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x / r` tends to negative infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_neg h]
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to negative infinity. -/
theorem Tendsto.const_mul_atTop_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_top Filter.Tendsto.const_mul_atTop_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to negative infinity. -/
theorem Tendsto.atTop_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_neg hr).2 hf
#align filter.tendsto.at_top_mul_neg_const Filter.Tendsto.atTop_mul_const_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` divided by a negative constant tends to negative infinity. -/
lemma Tendsto.atTop_div_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot := (tendsto_div_const_atBot_of_neg hr).2 hf
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the left) also tends to negative infinity. -/
theorem Tendsto.const_mul_atBot (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_bot Filter.Tendsto.const_mul_atBot
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the right) also tends to negative infinity. -/
theorem Tendsto.atBot_mul_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_mul_const Filter.Tendsto.atBot_mul_const
/-- If a function `f` tends to negative infinity along a filter, then `f` divided by
a positive constant also tends to negative infinity. -/
theorem Tendsto.atBot_div_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x / r) l atBot := (tendsto_div_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_div_const Filter.Tendsto.atBot_div_const
/-- If a function `f` tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to positive infinity. -/
theorem Tendsto.const_mul_atBot_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_bot Filter.Tendsto.const_mul_atBot_of_neg
/-- If a function tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to positive infinity. -/
theorem Tendsto.atBot_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_neg hr).2 hf
#align filter.tendsto.at_bot_mul_neg_const Filter.Tendsto.atBot_mul_const_of_neg
theorem tendsto_neg_const_mul_pow_atTop {c : α} {n : ℕ} (hn : n ≠ 0) (hc : c < 0) :
Tendsto (fun x => c * x ^ n) atTop atBot :=
(tendsto_pow_atTop hn).const_mul_atTop_of_neg hc
#align filter.tendsto_neg_const_mul_pow_at_top Filter.tendsto_neg_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atBot_iff {c : α} {n : ℕ} :
Tendsto (fun x => c * x ^ n) atTop atBot ↔ n ≠ 0 ∧ c < 0 := by
simp only [← tendsto_neg_atTop_iff, ← neg_mul, tendsto_const_mul_pow_atTop_iff, neg_pos]
#align filter.tendsto_const_mul_pow_at_bot_iff Filter.tendsto_const_mul_pow_atBot_iff
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atTop := Tendsto.const_mul_atTop_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atTop_mul_neg_const := Tendsto.atTop_mul_const_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atBot := Tendsto.const_mul_atBot_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atBot_mul_neg_const := Tendsto.atBot_mul_const_of_neg
end LinearOrderedField
open Filter
theorem tendsto_atTop' [Nonempty α] [SemilatticeSup α] {f : α → β} {l : Filter β} :
Tendsto f atTop l ↔ ∀ s ∈ l, ∃ a, ∀ b ≥ a, f b ∈ s := by
simp only [tendsto_def, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top' Filter.tendsto_atTop'
theorem tendsto_atBot' [Nonempty α] [SemilatticeInf α] {f : α → β} {l : Filter β} :
Tendsto f atBot l ↔ ∀ s ∈ l, ∃ a, ∀ b ≤ a, f b ∈ s :=
@tendsto_atTop' αᵒᵈ _ _ _ _ _
#align filter.tendsto_at_bot' Filter.tendsto_atBot'
theorem tendsto_atTop_principal [Nonempty β] [SemilatticeSup β] {f : β → α} {s : Set α} :
Tendsto f atTop (𝓟 s) ↔ ∃ N, ∀ n ≥ N, f n ∈ s := by
simp_rw [tendsto_iff_comap, comap_principal, le_principal_iff, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top_principal Filter.tendsto_atTop_principal
theorem tendsto_atBot_principal [Nonempty β] [SemilatticeInf β] {f : β → α} {s : Set α} :
Tendsto f atBot (𝓟 s) ↔ ∃ N, ∀ n ≤ N, f n ∈ s :=
@tendsto_atTop_principal _ βᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_principal Filter.tendsto_atBot_principal
/-- A function `f` grows to `+∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atTop_atTop [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → b ≤ f a :=
Iff.trans tendsto_iInf <| forall_congr' fun _ => tendsto_atTop_principal
#align filter.tendsto_at_top_at_top Filter.tendsto_atTop_atTop
theorem tendsto_atTop_atBot [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → f a ≤ b :=
@tendsto_atTop_atTop α βᵒᵈ _ _ _ f
#align filter.tendsto_at_top_at_bot Filter.tendsto_atTop_atBot
theorem tendsto_atBot_atTop [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → b ≤ f a :=
@tendsto_atTop_atTop αᵒᵈ β _ _ _ f
#align filter.tendsto_at_bot_at_top Filter.tendsto_atBot_atTop
theorem tendsto_atBot_atBot [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → f a ≤ b :=
@tendsto_atTop_atTop αᵒᵈ βᵒᵈ _ _ _ f
#align filter.tendsto_at_bot_at_bot Filter.tendsto_atBot_atBot
theorem tendsto_atTop_atTop_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atTop atTop :=
tendsto_iInf.2 fun b =>
tendsto_principal.2 <|
let ⟨a, ha⟩ := h b
mem_of_superset (mem_atTop a) fun _a' ha' => le_trans ha (hf ha')
#align filter.tendsto_at_top_at_top_of_monotone Filter.tendsto_atTop_atTop_of_monotone
theorem tendsto_atTop_atBot_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atTop atBot :=
@tendsto_atTop_atTop_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atBot_atBot_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atBot atBot :=
tendsto_iInf.2 fun b => tendsto_principal.2 <|
let ⟨a, ha⟩ := h b; mem_of_superset (mem_atBot a) fun _a' ha' => le_trans (hf ha') ha
#align filter.tendsto_at_bot_at_bot_of_monotone Filter.tendsto_atBot_atBot_of_monotone
theorem tendsto_atBot_atTop_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atBot atTop :=
@tendsto_atBot_atBot_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atTop_atTop_iff_of_monotone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atTop atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
tendsto_atTop_atTop.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans h <| hf ha'⟩
#align filter.tendsto_at_top_at_top_iff_of_monotone Filter.tendsto_atTop_atTop_iff_of_monotone
theorem tendsto_atTop_atBot_iff_of_antitone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atTop atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
@tendsto_atTop_atTop_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
theorem tendsto_atBot_atBot_iff_of_monotone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atBot atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
tendsto_atBot_atBot.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans (hf ha') h⟩
#align filter.tendsto_at_bot_at_bot_iff_of_monotone Filter.tendsto_atBot_atBot_iff_of_monotone
theorem tendsto_atBot_atTop_iff_of_antitone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atBot atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
@tendsto_atBot_atBot_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
alias _root_.Monotone.tendsto_atTop_atTop := tendsto_atTop_atTop_of_monotone
#align monotone.tendsto_at_top_at_top Monotone.tendsto_atTop_atTop
alias _root_.Monotone.tendsto_atBot_atBot := tendsto_atBot_atBot_of_monotone
#align monotone.tendsto_at_bot_at_bot Monotone.tendsto_atBot_atBot
alias _root_.Monotone.tendsto_atTop_atTop_iff := tendsto_atTop_atTop_iff_of_monotone
#align monotone.tendsto_at_top_at_top_iff Monotone.tendsto_atTop_atTop_iff
alias _root_.Monotone.tendsto_atBot_atBot_iff := tendsto_atBot_atBot_iff_of_monotone
#align monotone.tendsto_at_bot_at_bot_iff Monotone.tendsto_atBot_atBot_iff
theorem comap_embedding_atTop [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) : comap e atTop = atTop :=
le_antisymm
(le_iInf fun b =>
le_principal_iff.2 <| mem_comap.2 ⟨Ici (e b), mem_atTop _, fun _ => (hm _ _).1⟩)
(tendsto_atTop_atTop_of_monotone (fun _ _ => (hm _ _).2) hu).le_comap
#align filter.comap_embedding_at_top Filter.comap_embedding_atTop
theorem comap_embedding_atBot [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) : comap e atBot = atBot :=
@comap_embedding_atTop βᵒᵈ γᵒᵈ _ _ e (Function.swap hm) hu
#align filter.comap_embedding_at_bot Filter.comap_embedding_atBot
theorem tendsto_atTop_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) :
Tendsto (e ∘ f) l atTop ↔ Tendsto f l atTop := by
rw [← comap_embedding_atTop hm hu, tendsto_comap_iff]
#align filter.tendsto_at_top_embedding Filter.tendsto_atTop_embedding
/-- A function `f` goes to `-∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atBot_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) :
Tendsto (e ∘ f) l atBot ↔ Tendsto f l atBot :=
@tendsto_atTop_embedding α βᵒᵈ γᵒᵈ _ _ f e l (Function.swap hm) hu
#align filter.tendsto_at_bot_embedding Filter.tendsto_atBot_embedding
theorem tendsto_finset_range : Tendsto Finset.range atTop atTop :=
Finset.range_mono.tendsto_atTop_atTop Finset.exists_nat_subset_range
#align filter.tendsto_finset_range Filter.tendsto_finset_range
theorem atTop_finset_eq_iInf : (atTop : Filter (Finset α)) = ⨅ x : α, 𝓟 (Ici {x}) := by
refine le_antisymm (le_iInf fun i => le_principal_iff.2 <| mem_atTop ({i} : Finset α)) ?_
refine
le_iInf fun s =>
le_principal_iff.2 <| mem_iInf_of_iInter s.finite_toSet (fun i => mem_principal_self _) ?_
simp only [subset_def, mem_iInter, SetCoe.forall, mem_Ici, Finset.le_iff_subset,
Finset.mem_singleton, Finset.subset_iff, forall_eq]
exact fun t => id
#align filter.at_top_finset_eq_infi Filter.atTop_finset_eq_iInf
/-- If `f` is a monotone sequence of `Finset`s and each `x` belongs to one of `f n`, then
`Tendsto f atTop atTop`. -/
theorem tendsto_atTop_finset_of_monotone [Preorder β] {f : β → Finset α} (h : Monotone f)
(h' : ∀ x : α, ∃ n, x ∈ f n) : Tendsto f atTop atTop := by
simp only [atTop_finset_eq_iInf, tendsto_iInf, tendsto_principal]
intro a
rcases h' a with ⟨b, hb⟩
exact (eventually_ge_atTop b).mono fun b' hb' => (Finset.singleton_subset_iff.2 hb).trans (h hb')
#align filter.tendsto_at_top_finset_of_monotone Filter.tendsto_atTop_finset_of_monotone
alias _root_.Monotone.tendsto_atTop_finset := tendsto_atTop_finset_of_monotone
#align monotone.tendsto_at_top_finset Monotone.tendsto_atTop_finset
-- Porting note: add assumption `DecidableEq β` so that the lemma applies to any instance
theorem tendsto_finset_image_atTop_atTop [DecidableEq β] {i : β → γ} {j : γ → β}
(h : Function.LeftInverse j i) : Tendsto (Finset.image j) atTop atTop :=
(Finset.image_mono j).tendsto_atTop_finset fun a =>
⟨{i a}, by simp only [Finset.image_singleton, h a, Finset.mem_singleton]⟩
#align filter.tendsto_finset_image_at_top_at_top Filter.tendsto_finset_image_atTop_atTop
theorem tendsto_finset_preimage_atTop_atTop {f : α → β} (hf : Function.Injective f) :
Tendsto (fun s : Finset β => s.preimage f (hf.injOn)) atTop atTop :=
(Finset.monotone_preimage hf).tendsto_atTop_finset fun x =>
⟨{f x}, Finset.mem_preimage.2 <| Finset.mem_singleton_self _⟩
#align filter.tendsto_finset_preimage_at_top_at_top Filter.tendsto_finset_preimage_atTop_atTop
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atTop_atTop_eq [Preorder α] [Preorder β] :
(atTop : Filter α) ×ˢ (atTop : Filter β) = (atTop : Filter (α × β)) := by
cases isEmpty_or_nonempty α
· exact Subsingleton.elim _ _
cases isEmpty_or_nonempty β
· exact Subsingleton.elim _ _
simpa [atTop, prod_iInf_left, prod_iInf_right, iInf_prod] using iInf_comm
#align filter.prod_at_top_at_top_eq Filter.prod_atTop_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atBot_atBot_eq [Preorder β₁] [Preorder β₂] :
(atBot : Filter β₁) ×ˢ (atBot : Filter β₂) = (atBot : Filter (β₁ × β₂)) :=
@prod_atTop_atTop_eq β₁ᵒᵈ β₂ᵒᵈ _ _
#align filter.prod_at_bot_at_bot_eq Filter.prod_atBot_atBot_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atTop_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atTop ×ˢ map u₂ atTop = map (Prod.map u₁ u₂) atTop := by
rw [prod_map_map_eq, prod_atTop_atTop_eq, Prod.map_def]
#align filter.prod_map_at_top_eq Filter.prod_map_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atBot_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atBot ×ˢ map u₂ atBot = map (Prod.map u₁ u₂) atBot :=
@prod_map_atTop_eq _ _ β₁ᵒᵈ β₂ᵒᵈ _ _ _ _
#align filter.prod_map_at_bot_eq Filter.prod_map_atBot_eq
theorem Tendsto.subseq_mem {F : Filter α} {V : ℕ → Set α} (h : ∀ n, V n ∈ F) {u : ℕ → α}
(hu : Tendsto u atTop F) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, u (φ n) ∈ V n :=
extraction_forall_of_eventually'
(fun n => tendsto_atTop'.mp hu _ (h n) : ∀ n, ∃ N, ∀ k ≥ N, u k ∈ V n)
#align filter.tendsto.subseq_mem Filter.Tendsto.subseq_mem
theorem tendsto_atBot_diagonal [SemilatticeInf α] : Tendsto (fun a : α => (a, a)) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_bot_diagonal Filter.tendsto_atBot_diagonal
theorem tendsto_atTop_diagonal [SemilatticeSup α] : Tendsto (fun a : α => (a, a)) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_top_diagonal Filter.tendsto_atTop_diagonal
theorem Tendsto.prod_map_prod_atBot [SemilatticeInf γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atBot) (hg : Tendsto g G atBot) :
Tendsto (Prod.map f g) (F ×ˢ G) atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_bot Filter.Tendsto.prod_map_prod_atBot
theorem Tendsto.prod_map_prod_atTop [SemilatticeSup γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atTop) (hg : Tendsto g G atTop) :
Tendsto (Prod.map f g) (F ×ˢ G) atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_top Filter.Tendsto.prod_map_prod_atTop
theorem Tendsto.prod_atBot [SemilatticeInf α] [SemilatticeInf γ] {f g : α → γ}
(hf : Tendsto f atBot atBot) (hg : Tendsto g atBot atBot) :
Tendsto (Prod.map f g) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map_prod_atBot hg
#align filter.tendsto.prod_at_bot Filter.Tendsto.prod_atBot
theorem Tendsto.prod_atTop [SemilatticeSup α] [SemilatticeSup γ] {f g : α → γ}
(hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) :
Tendsto (Prod.map f g) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map_prod_atTop hg
#align filter.tendsto.prod_at_top Filter.Tendsto.prod_atTop
| Mathlib/Order/Filter/AtTopBot.lean | 1,608 | 1,610 | theorem eventually_atBot_prod_self [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k l, k ≤ a → l ≤ a → p (k, l) := by |
simp [← prod_atBot_atBot_eq, (@atBot_basis α _ _).prod_self.eventually_iff]
|
/-
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.Calculus.TangentCone
import Mathlib.Analysis.NormedSpace.OperatorNorm.Asymptotics
#align_import analysis.calculus.fderiv.basic from "leanprover-community/mathlib"@"41bef4ae1254365bc190aee63b947674d2977f01"
/-!
# The Fréchet derivative
Let `E` and `F` be normed spaces, `f : E → F`, and `f' : E →L[𝕜] F` a
continuous 𝕜-linear map, where `𝕜` is a non-discrete normed field. Then
`HasFDerivWithinAt f f' s x`
says that `f` has derivative `f'` at `x`, where the domain of interest
is restricted to `s`. We also have
`HasFDerivAt f f' x := HasFDerivWithinAt f f' x univ`
Finally,
`HasStrictFDerivAt f f' x`
means that `f : E → F` has derivative `f' : E →L[𝕜] F` in the sense of strict differentiability,
i.e., `f y - f z - f'(y - z) = o(y - z)` as `y, z → x`. This notion is used in the inverse
function theorem, and is defined here only to avoid proving theorems like
`IsBoundedBilinearMap.hasFDerivAt` twice: first for `HasFDerivAt`, then for
`HasStrictFDerivAt`.
## Main results
In addition to the definition and basic properties of the derivative,
the folder `Analysis/Calculus/FDeriv/` contains the usual formulas
(and existence assertions) for the derivative of
* constants
* the identity
* bounded linear maps (`Linear.lean`)
* bounded bilinear maps (`Bilinear.lean`)
* sum of two functions (`Add.lean`)
* sum of finitely many functions (`Add.lean`)
* multiplication of a function by a scalar constant (`Add.lean`)
* negative of a function (`Add.lean`)
* subtraction of two functions (`Add.lean`)
* multiplication of a function by a scalar function (`Mul.lean`)
* multiplication of two scalar functions (`Mul.lean`)
* composition of functions (the chain rule) (`Comp.lean`)
* inverse function (`Mul.lean`)
(assuming that it exists; the inverse function theorem is in `../Inverse.lean`)
For most binary operations we also define `const_op` and `op_const` theorems for the cases when
the first or second argument is a constant. This makes writing chains of `HasDerivAt`'s easier,
and they more frequently lead to the desired result.
One can also interpret the derivative of a function `f : 𝕜 → E` as an element of `E` (by identifying
a linear function from `𝕜` to `E` with its value at `1`). Results on the Fréchet derivative are
translated to this more elementary point of view on the derivative in the file `Deriv.lean`. The
derivative of polynomials is handled there, as it is naturally one-dimensional.
The simplifier is set up to prove automatically that some functions are differentiable, or
differentiable at a point (but not differentiable on a set or within a set at a point, as checking
automatically that the good domains are mapped one to the other when using composition is not
something the simplifier can easily do). This means that one can write
`example (x : ℝ) : Differentiable ℝ (fun x ↦ sin (exp (3 + x^2)) - 5 * cos x) := by simp`.
If there are divisions, one needs to supply to the simplifier proofs that the denominators do
not vanish, as in
```lean
example (x : ℝ) (h : 1 + sin x ≠ 0) : DifferentiableAt ℝ (fun x ↦ exp x / (1 + sin x)) x := by
simp [h]
```
Of course, these examples only work once `exp`, `cos` and `sin` have been shown to be
differentiable, in `Analysis.SpecialFunctions.Trigonometric`.
The simplifier is not set up to compute the Fréchet derivative of maps (as these are in general
complicated multidimensional linear maps), but it will compute one-dimensional derivatives,
see `Deriv.lean`.
## Implementation details
The derivative is defined in terms of the `isLittleO` relation, but also
characterized in terms of the `Tendsto` relation.
We also introduce predicates `DifferentiableWithinAt 𝕜 f s x` (where `𝕜` is the base field,
`f` the function to be differentiated, `x` the point at which the derivative is asserted to exist,
and `s` the set along which the derivative is defined), as well as `DifferentiableAt 𝕜 f x`,
`DifferentiableOn 𝕜 f s` and `Differentiable 𝕜 f` to express the existence of a derivative.
To be able to compute with derivatives, we write `fderivWithin 𝕜 f s x` and `fderiv 𝕜 f x`
for some choice of a derivative if it exists, and the zero function otherwise. This choice only
behaves well along sets for which the derivative is unique, i.e., those for which the tangent
directions span a dense subset of the whole space. The predicates `UniqueDiffWithinAt s x` and
`UniqueDiffOn s`, defined in `TangentCone.lean` express this property. We prove that indeed
they imply the uniqueness of the derivative. This is satisfied for open subsets, and in particular
for `univ`. This uniqueness only holds when the field is non-discrete, which we request at the very
beginning: otherwise, a derivative can be defined, but it has no interesting properties whatsoever.
To make sure that the simplifier can prove automatically that functions are differentiable, we tag
many lemmas with the `simp` attribute, for instance those saying that the sum of differentiable
functions is differentiable, as well as their product, their cartesian product, and so on. A notable
exception is the chain rule: we do not mark as a simp lemma the fact that, if `f` and `g` are
differentiable, then their composition also is: `simp` would always be able to match this lemma,
by taking `f` or `g` to be the identity. Instead, for every reasonable function (say, `exp`),
we add a lemma that if `f` is differentiable then so is `(fun x ↦ exp (f x))`. This means adding
some boilerplate lemmas, but these can also be useful in their own right.
Tests for this ability of the simplifier (with more examples) are provided in
`Tests/Differentiable.lean`.
## Tags
derivative, differentiable, Fréchet, calculus
-/
open Filter Asymptotics ContinuousLinearMap Set Metric
open scoped Classical
open Topology NNReal Filter Asymptotics ENNReal
noncomputable section
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 {G' : Type*} [NormedAddCommGroup G'] [NormedSpace 𝕜 G']
/-- A function `f` has the continuous linear map `f'` as derivative along the filter `L` if
`f x' = f x + f' (x' - x) + o (x' - x)` when `x'` converges along the filter `L`. This definition
is designed to be specialized for `L = 𝓝 x` (in `HasFDerivAt`), giving rise to the usual notion
of Fréchet derivative, and for `L = 𝓝[s] x` (in `HasFDerivWithinAt`), giving rise to
the notion of Fréchet derivative along the set `s`. -/
@[mk_iff hasFDerivAtFilter_iff_isLittleO]
structure HasFDerivAtFilter (f : E → F) (f' : E →L[𝕜] F) (x : E) (L : Filter E) : Prop where
of_isLittleO :: isLittleO : (fun x' => f x' - f x - f' (x' - x)) =o[L] fun x' => x' - x
#align has_fderiv_at_filter HasFDerivAtFilter
/-- A function `f` has the continuous linear map `f'` as derivative at `x` within a set `s` if
`f x' = f x + f' (x' - x) + o (x' - x)` when `x'` tends to `x` inside `s`. -/
@[fun_prop]
def HasFDerivWithinAt (f : E → F) (f' : E →L[𝕜] F) (s : Set E) (x : E) :=
HasFDerivAtFilter f f' x (𝓝[s] x)
#align has_fderiv_within_at HasFDerivWithinAt
/-- A function `f` has the continuous linear map `f'` as derivative at `x` if
`f x' = f x + f' (x' - x) + o (x' - x)` when `x'` tends to `x`. -/
@[fun_prop]
def HasFDerivAt (f : E → F) (f' : E →L[𝕜] F) (x : E) :=
HasFDerivAtFilter f f' x (𝓝 x)
#align has_fderiv_at HasFDerivAt
/-- A function `f` has derivative `f'` at `a` in the sense of *strict differentiability*
if `f x - f y - f' (x - y) = o(x - y)` as `x, y → a`. This form of differentiability is required,
e.g., by the inverse function theorem. Any `C^1` function on a vector space over `ℝ` is strictly
differentiable but this definition works, e.g., for vector spaces over `p`-adic numbers. -/
@[fun_prop]
def HasStrictFDerivAt (f : E → F) (f' : E →L[𝕜] F) (x : E) :=
(fun p : E × E => f p.1 - f p.2 - f' (p.1 - p.2)) =o[𝓝 (x, x)] fun p : E × E => p.1 - p.2
#align has_strict_fderiv_at HasStrictFDerivAt
variable (𝕜)
/-- A function `f` is differentiable at a point `x` within a set `s` if it admits a derivative
there (possibly non-unique). -/
@[fun_prop]
def DifferentiableWithinAt (f : E → F) (s : Set E) (x : E) :=
∃ f' : E →L[𝕜] F, HasFDerivWithinAt f f' s x
#align differentiable_within_at DifferentiableWithinAt
/-- A function `f` is differentiable at a point `x` if it admits a derivative there (possibly
non-unique). -/
@[fun_prop]
def DifferentiableAt (f : E → F) (x : E) :=
∃ f' : E →L[𝕜] F, HasFDerivAt f f' x
#align differentiable_at DifferentiableAt
/-- If `f` has a derivative at `x` within `s`, then `fderivWithin 𝕜 f s x` is such a derivative.
Otherwise, it is set to `0`. If `x` is isolated in `s`, we take the derivative within `s` to
be zero for convenience. -/
irreducible_def fderivWithin (f : E → F) (s : Set E) (x : E) : E →L[𝕜] F :=
if 𝓝[s \ {x}] x = ⊥ then 0 else
if h : ∃ f', HasFDerivWithinAt f f' s x then Classical.choose h else 0
#align fderiv_within fderivWithin
/-- If `f` has a derivative at `x`, then `fderiv 𝕜 f x` is such a derivative. Otherwise, it is
set to `0`. -/
irreducible_def fderiv (f : E → F) (x : E) : E →L[𝕜] F :=
if h : ∃ f', HasFDerivAt f f' x then Classical.choose h else 0
#align fderiv fderiv
/-- `DifferentiableOn 𝕜 f s` means that `f` is differentiable within `s` at any point of `s`. -/
@[fun_prop]
def DifferentiableOn (f : E → F) (s : Set E) :=
∀ x ∈ s, DifferentiableWithinAt 𝕜 f s x
#align differentiable_on DifferentiableOn
/-- `Differentiable 𝕜 f` means that `f` is differentiable at any point. -/
@[fun_prop]
def Differentiable (f : E → F) :=
∀ x, DifferentiableAt 𝕜 f x
#align differentiable Differentiable
variable {𝕜}
variable {f f₀ f₁ g : E → F}
variable {f' f₀' f₁' g' : E →L[𝕜] F}
variable (e : E →L[𝕜] F)
variable {x : E}
variable {s t : Set E}
variable {L L₁ L₂ : Filter E}
theorem fderivWithin_zero_of_isolated (h : 𝓝[s \ {x}] x = ⊥) : fderivWithin 𝕜 f s x = 0 := by
rw [fderivWithin, if_pos h]
theorem fderivWithin_zero_of_nmem_closure (h : x ∉ closure s) : fderivWithin 𝕜 f s x = 0 := by
apply fderivWithin_zero_of_isolated
simp only [mem_closure_iff_nhdsWithin_neBot, neBot_iff, Ne, Classical.not_not] at h
rw [eq_bot_iff, ← h]
exact nhdsWithin_mono _ diff_subset
theorem fderivWithin_zero_of_not_differentiableWithinAt (h : ¬DifferentiableWithinAt 𝕜 f s x) :
fderivWithin 𝕜 f s x = 0 := by
have : ¬∃ f', HasFDerivWithinAt f f' s x := h
simp [fderivWithin, this]
#align fderiv_within_zero_of_not_differentiable_within_at fderivWithin_zero_of_not_differentiableWithinAt
theorem fderiv_zero_of_not_differentiableAt (h : ¬DifferentiableAt 𝕜 f x) : fderiv 𝕜 f x = 0 := by
have : ¬∃ f', HasFDerivAt f f' x := h
simp [fderiv, this]
#align fderiv_zero_of_not_differentiable_at fderiv_zero_of_not_differentiableAt
section DerivativeUniqueness
/- In this section, we discuss the uniqueness of the derivative.
We prove that the definitions `UniqueDiffWithinAt` and `UniqueDiffOn` indeed imply the
uniqueness of the derivative. -/
/-- If a function f has a derivative f' at x, a rescaled version of f around x converges to f',
i.e., `n (f (x + (1/n) v) - f x)` converges to `f' v`. More generally, if `c n` tends to infinity
and `c n * d n` tends to `v`, then `c n * (f (x + d n) - f x)` tends to `f' v`. This lemma expresses
this fact, for functions having a derivative within a set. Its specific formulation is useful for
tangent cone related discussions. -/
theorem HasFDerivWithinAt.lim (h : HasFDerivWithinAt f f' s x) {α : Type*} (l : Filter α)
{c : α → 𝕜} {d : α → E} {v : E} (dtop : ∀ᶠ n in l, x + d n ∈ s)
(clim : Tendsto (fun n => ‖c n‖) l atTop) (cdlim : Tendsto (fun n => c n • d n) l (𝓝 v)) :
Tendsto (fun n => c n • (f (x + d n) - f x)) l (𝓝 (f' v)) := by
have tendsto_arg : Tendsto (fun n => x + d n) l (𝓝[s] x) := by
conv in 𝓝[s] x => rw [← add_zero x]
rw [nhdsWithin, tendsto_inf]
constructor
· apply tendsto_const_nhds.add (tangentConeAt.lim_zero l clim cdlim)
· rwa [tendsto_principal]
have : (fun y => f y - f x - f' (y - x)) =o[𝓝[s] x] fun y => y - x := h.isLittleO
have : (fun n => f (x + d n) - f x - f' (x + d n - x)) =o[l] fun n => x + d n - x :=
this.comp_tendsto tendsto_arg
have : (fun n => f (x + d n) - f x - f' (d n)) =o[l] d := by simpa only [add_sub_cancel_left]
have : (fun n => c n • (f (x + d n) - f x - f' (d n))) =o[l] fun n => c n • d n :=
(isBigO_refl c l).smul_isLittleO this
have : (fun n => c n • (f (x + d n) - f x - f' (d n))) =o[l] fun _ => (1 : ℝ) :=
this.trans_isBigO (cdlim.isBigO_one ℝ)
have L1 : Tendsto (fun n => c n • (f (x + d n) - f x - f' (d n))) l (𝓝 0) :=
(isLittleO_one_iff ℝ).1 this
have L2 : Tendsto (fun n => f' (c n • d n)) l (𝓝 (f' v)) :=
Tendsto.comp f'.cont.continuousAt cdlim
have L3 :
Tendsto (fun n => c n • (f (x + d n) - f x - f' (d n)) + f' (c n • d n)) l (𝓝 (0 + f' v)) :=
L1.add L2
have :
(fun n => c n • (f (x + d n) - f x - f' (d n)) + f' (c n • d n)) = fun n =>
c n • (f (x + d n) - f x) := by
ext n
simp [smul_add, smul_sub]
rwa [this, zero_add] at L3
#align has_fderiv_within_at.lim HasFDerivWithinAt.lim
/-- If `f'` and `f₁'` are two derivatives of `f` within `s` at `x`, then they are equal on the
tangent cone to `s` at `x` -/
theorem HasFDerivWithinAt.unique_on (hf : HasFDerivWithinAt f f' s x)
(hg : HasFDerivWithinAt f f₁' s x) : EqOn f' f₁' (tangentConeAt 𝕜 s x) :=
fun _ ⟨_, _, dtop, clim, cdlim⟩ =>
tendsto_nhds_unique (hf.lim atTop dtop clim cdlim) (hg.lim atTop dtop clim cdlim)
#align has_fderiv_within_at.unique_on HasFDerivWithinAt.unique_on
/-- `UniqueDiffWithinAt` achieves its goal: it implies the uniqueness of the derivative. -/
theorem UniqueDiffWithinAt.eq (H : UniqueDiffWithinAt 𝕜 s x) (hf : HasFDerivWithinAt f f' s x)
(hg : HasFDerivWithinAt f f₁' s x) : f' = f₁' :=
ContinuousLinearMap.ext_on H.1 (hf.unique_on hg)
#align unique_diff_within_at.eq UniqueDiffWithinAt.eq
theorem UniqueDiffOn.eq (H : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (h : HasFDerivWithinAt f f' s x)
(h₁ : HasFDerivWithinAt f f₁' s x) : f' = f₁' :=
(H x hx).eq h h₁
#align unique_diff_on.eq UniqueDiffOn.eq
end DerivativeUniqueness
section FDerivProperties
/-! ### Basic properties of the derivative -/
theorem hasFDerivAtFilter_iff_tendsto :
HasFDerivAtFilter f f' x L ↔
Tendsto (fun x' => ‖x' - x‖⁻¹ * ‖f x' - f x - f' (x' - x)‖) L (𝓝 0) := by
have h : ∀ x', ‖x' - x‖ = 0 → ‖f x' - f x - f' (x' - x)‖ = 0 := fun x' hx' => by
rw [sub_eq_zero.1 (norm_eq_zero.1 hx')]
simp
rw [hasFDerivAtFilter_iff_isLittleO, ← isLittleO_norm_left, ← isLittleO_norm_right,
isLittleO_iff_tendsto h]
exact tendsto_congr fun _ => div_eq_inv_mul _ _
#align has_fderiv_at_filter_iff_tendsto hasFDerivAtFilter_iff_tendsto
theorem hasFDerivWithinAt_iff_tendsto :
HasFDerivWithinAt f f' s x ↔
Tendsto (fun x' => ‖x' - x‖⁻¹ * ‖f x' - f x - f' (x' - x)‖) (𝓝[s] x) (𝓝 0) :=
hasFDerivAtFilter_iff_tendsto
#align has_fderiv_within_at_iff_tendsto hasFDerivWithinAt_iff_tendsto
theorem hasFDerivAt_iff_tendsto :
HasFDerivAt f f' x ↔ Tendsto (fun x' => ‖x' - x‖⁻¹ * ‖f x' - f x - f' (x' - x)‖) (𝓝 x) (𝓝 0) :=
hasFDerivAtFilter_iff_tendsto
#align has_fderiv_at_iff_tendsto hasFDerivAt_iff_tendsto
theorem hasFDerivAt_iff_isLittleO_nhds_zero :
HasFDerivAt f f' x ↔ (fun h : E => f (x + h) - f x - f' h) =o[𝓝 0] fun h => h := by
rw [HasFDerivAt, hasFDerivAtFilter_iff_isLittleO, ← map_add_left_nhds_zero x, isLittleO_map]
simp [(· ∘ ·)]
#align has_fderiv_at_iff_is_o_nhds_zero hasFDerivAt_iff_isLittleO_nhds_zero
/-- Converse to the mean value inequality: if `f` is differentiable at `x₀` and `C`-lipschitz
on a neighborhood of `x₀` then its derivative at `x₀` has norm bounded by `C`. This version
only assumes that `‖f x - f x₀‖ ≤ C * ‖x - x₀‖` in a neighborhood of `x`. -/
theorem HasFDerivAt.le_of_lip' {f : E → F} {f' : E →L[𝕜] F} {x₀ : E} (hf : HasFDerivAt f f' x₀)
{C : ℝ} (hC₀ : 0 ≤ C) (hlip : ∀ᶠ x in 𝓝 x₀, ‖f x - f x₀‖ ≤ C * ‖x - x₀‖) : ‖f'‖ ≤ C := by
refine le_of_forall_pos_le_add fun ε ε0 => opNorm_le_of_nhds_zero ?_ ?_
· exact add_nonneg hC₀ ε0.le
rw [← map_add_left_nhds_zero x₀, eventually_map] at hlip
filter_upwards [isLittleO_iff.1 (hasFDerivAt_iff_isLittleO_nhds_zero.1 hf) ε0, hlip] with y hy hyC
rw [add_sub_cancel_left] at hyC
calc
‖f' y‖ ≤ ‖f (x₀ + y) - f x₀‖ + ‖f (x₀ + y) - f x₀ - f' y‖ := norm_le_insert _ _
_ ≤ C * ‖y‖ + ε * ‖y‖ := add_le_add hyC hy
_ = (C + ε) * ‖y‖ := (add_mul _ _ _).symm
#align has_fderiv_at.le_of_lip' HasFDerivAt.le_of_lip'
/-- Converse to the mean value inequality: if `f` is differentiable at `x₀` and `C`-lipschitz
on a neighborhood of `x₀` then its derivative at `x₀` has norm bounded by `C`. -/
theorem HasFDerivAt.le_of_lipschitzOn
{f : E → F} {f' : E →L[𝕜] F} {x₀ : E} (hf : HasFDerivAt f f' x₀)
{s : Set E} (hs : s ∈ 𝓝 x₀) {C : ℝ≥0} (hlip : LipschitzOnWith C f s) : ‖f'‖ ≤ C := by
refine hf.le_of_lip' C.coe_nonneg ?_
filter_upwards [hs] with x hx using hlip.norm_sub_le hx (mem_of_mem_nhds hs)
#align has_fderiv_at.le_of_lip HasFDerivAt.le_of_lipschitzOn
/-- Converse to the mean value inequality: if `f` is differentiable at `x₀` and `C`-lipschitz
then its derivative at `x₀` has norm bounded by `C`. -/
theorem HasFDerivAt.le_of_lipschitz {f : E → F} {f' : E →L[𝕜] F} {x₀ : E} (hf : HasFDerivAt f f' x₀)
{C : ℝ≥0} (hlip : LipschitzWith C f) : ‖f'‖ ≤ C :=
hf.le_of_lipschitzOn univ_mem (lipschitzOn_univ.2 hlip)
nonrec theorem HasFDerivAtFilter.mono (h : HasFDerivAtFilter f f' x L₂) (hst : L₁ ≤ L₂) :
HasFDerivAtFilter f f' x L₁ :=
.of_isLittleO <| h.isLittleO.mono hst
#align has_fderiv_at_filter.mono HasFDerivAtFilter.mono
theorem HasFDerivWithinAt.mono_of_mem (h : HasFDerivWithinAt f f' t x) (hst : t ∈ 𝓝[s] x) :
HasFDerivWithinAt f f' s x :=
h.mono <| nhdsWithin_le_iff.mpr hst
#align has_fderiv_within_at.mono_of_mem HasFDerivWithinAt.mono_of_mem
#align has_fderiv_within_at.nhds_within HasFDerivWithinAt.mono_of_mem
nonrec theorem HasFDerivWithinAt.mono (h : HasFDerivWithinAt f f' t x) (hst : s ⊆ t) :
HasFDerivWithinAt f f' s x :=
h.mono <| nhdsWithin_mono _ hst
#align has_fderiv_within_at.mono HasFDerivWithinAt.mono
theorem HasFDerivAt.hasFDerivAtFilter (h : HasFDerivAt f f' x) (hL : L ≤ 𝓝 x) :
HasFDerivAtFilter f f' x L :=
h.mono hL
#align has_fderiv_at.has_fderiv_at_filter HasFDerivAt.hasFDerivAtFilter
@[fun_prop]
theorem HasFDerivAt.hasFDerivWithinAt (h : HasFDerivAt f f' x) : HasFDerivWithinAt f f' s x :=
h.hasFDerivAtFilter inf_le_left
#align has_fderiv_at.has_fderiv_within_at HasFDerivAt.hasFDerivWithinAt
@[fun_prop]
theorem HasFDerivWithinAt.differentiableWithinAt (h : HasFDerivWithinAt f f' s x) :
DifferentiableWithinAt 𝕜 f s x :=
⟨f', h⟩
#align has_fderiv_within_at.differentiable_within_at HasFDerivWithinAt.differentiableWithinAt
@[fun_prop]
theorem HasFDerivAt.differentiableAt (h : HasFDerivAt f f' x) : DifferentiableAt 𝕜 f x :=
⟨f', h⟩
#align has_fderiv_at.differentiable_at HasFDerivAt.differentiableAt
@[simp]
theorem hasFDerivWithinAt_univ : HasFDerivWithinAt f f' univ x ↔ HasFDerivAt f f' x := by
simp only [HasFDerivWithinAt, nhdsWithin_univ]
rfl
#align has_fderiv_within_at_univ hasFDerivWithinAt_univ
alias ⟨HasFDerivWithinAt.hasFDerivAt_of_univ, _⟩ := hasFDerivWithinAt_univ
#align has_fderiv_within_at.has_fderiv_at_of_univ HasFDerivWithinAt.hasFDerivAt_of_univ
theorem hasFDerivWithinAt_of_mem_nhds (h : s ∈ 𝓝 x) :
HasFDerivWithinAt f f' s x ↔ HasFDerivAt f f' x := by
rw [HasFDerivAt, HasFDerivWithinAt, nhdsWithin_eq_nhds.mpr h]
lemma hasFDerivWithinAt_of_isOpen (h : IsOpen s) (hx : x ∈ s) :
HasFDerivWithinAt f f' s x ↔ HasFDerivAt f f' x :=
hasFDerivWithinAt_of_mem_nhds (h.mem_nhds hx)
theorem hasFDerivWithinAt_insert {y : E} :
HasFDerivWithinAt f f' (insert y s) x ↔ HasFDerivWithinAt f f' s x := by
rcases eq_or_ne x y with (rfl | h)
· simp_rw [HasFDerivWithinAt, hasFDerivAtFilter_iff_isLittleO]
apply Asymptotics.isLittleO_insert
simp only [sub_self, map_zero]
refine ⟨fun h => h.mono <| subset_insert y s, fun hf => hf.mono_of_mem ?_⟩
simp_rw [nhdsWithin_insert_of_ne h, self_mem_nhdsWithin]
#align has_fderiv_within_at_insert hasFDerivWithinAt_insert
alias ⟨HasFDerivWithinAt.of_insert, HasFDerivWithinAt.insert'⟩ := hasFDerivWithinAt_insert
#align has_fderiv_within_at.of_insert HasFDerivWithinAt.of_insert
#align has_fderiv_within_at.insert' HasFDerivWithinAt.insert'
protected theorem HasFDerivWithinAt.insert (h : HasFDerivWithinAt g g' s x) :
HasFDerivWithinAt g g' (insert x s) x :=
h.insert'
#align has_fderiv_within_at.insert HasFDerivWithinAt.insert
theorem hasFDerivWithinAt_diff_singleton (y : E) :
HasFDerivWithinAt f f' (s \ {y}) x ↔ HasFDerivWithinAt f f' s x := by
rw [← hasFDerivWithinAt_insert, insert_diff_singleton, hasFDerivWithinAt_insert]
#align has_fderiv_within_at_diff_singleton hasFDerivWithinAt_diff_singleton
theorem HasStrictFDerivAt.isBigO_sub (hf : HasStrictFDerivAt f f' x) :
(fun p : E × E => f p.1 - f p.2) =O[𝓝 (x, x)] fun p : E × E => p.1 - p.2 :=
hf.isBigO.congr_of_sub.2 (f'.isBigO_comp _ _)
set_option linter.uppercaseLean3 false in
#align has_strict_fderiv_at.is_O_sub HasStrictFDerivAt.isBigO_sub
theorem HasFDerivAtFilter.isBigO_sub (h : HasFDerivAtFilter f f' x L) :
(fun x' => f x' - f x) =O[L] fun x' => x' - x :=
h.isLittleO.isBigO.congr_of_sub.2 (f'.isBigO_sub _ _)
set_option linter.uppercaseLean3 false in
#align has_fderiv_at_filter.is_O_sub HasFDerivAtFilter.isBigO_sub
@[fun_prop]
protected theorem HasStrictFDerivAt.hasFDerivAt (hf : HasStrictFDerivAt f f' x) :
HasFDerivAt f f' x := by
rw [HasFDerivAt, hasFDerivAtFilter_iff_isLittleO, isLittleO_iff]
exact fun c hc => tendsto_id.prod_mk_nhds tendsto_const_nhds (isLittleO_iff.1 hf hc)
#align has_strict_fderiv_at.has_fderiv_at HasStrictFDerivAt.hasFDerivAt
protected theorem HasStrictFDerivAt.differentiableAt (hf : HasStrictFDerivAt f f' x) :
DifferentiableAt 𝕜 f x :=
hf.hasFDerivAt.differentiableAt
#align has_strict_fderiv_at.differentiable_at HasStrictFDerivAt.differentiableAt
/-- If `f` is strictly differentiable at `x` with derivative `f'` and `K > ‖f'‖₊`, then `f` is
`K`-Lipschitz in a neighborhood of `x`. -/
theorem HasStrictFDerivAt.exists_lipschitzOnWith_of_nnnorm_lt (hf : HasStrictFDerivAt f f' x)
(K : ℝ≥0) (hK : ‖f'‖₊ < K) : ∃ s ∈ 𝓝 x, LipschitzOnWith K f s := by
have := hf.add_isBigOWith (f'.isBigOWith_comp _ _) hK
simp only [sub_add_cancel, IsBigOWith] at this
rcases exists_nhds_square this with ⟨U, Uo, xU, hU⟩
exact
⟨U, Uo.mem_nhds xU, lipschitzOnWith_iff_norm_sub_le.2 fun x hx y hy => hU (mk_mem_prod hx hy)⟩
#align has_strict_fderiv_at.exists_lipschitz_on_with_of_nnnorm_lt HasStrictFDerivAt.exists_lipschitzOnWith_of_nnnorm_lt
/-- If `f` is strictly differentiable at `x` with derivative `f'`, then `f` is Lipschitz in a
neighborhood of `x`. See also `HasStrictFDerivAt.exists_lipschitzOnWith_of_nnnorm_lt` for a
more precise statement. -/
theorem HasStrictFDerivAt.exists_lipschitzOnWith (hf : HasStrictFDerivAt f f' x) :
∃ K, ∃ s ∈ 𝓝 x, LipschitzOnWith K f s :=
(exists_gt _).imp hf.exists_lipschitzOnWith_of_nnnorm_lt
#align has_strict_fderiv_at.exists_lipschitz_on_with HasStrictFDerivAt.exists_lipschitzOnWith
/-- Directional derivative agrees with `HasFDeriv`. -/
theorem HasFDerivAt.lim (hf : HasFDerivAt f f' x) (v : E) {α : Type*} {c : α → 𝕜} {l : Filter α}
(hc : Tendsto (fun n => ‖c n‖) l atTop) :
Tendsto (fun n => c n • (f (x + (c n)⁻¹ • v) - f x)) l (𝓝 (f' v)) := by
refine (hasFDerivWithinAt_univ.2 hf).lim _ univ_mem hc ?_
intro U hU
refine (eventually_ne_of_tendsto_norm_atTop hc (0 : 𝕜)).mono fun y hy => ?_
convert mem_of_mem_nhds hU
dsimp only
rw [← mul_smul, mul_inv_cancel hy, one_smul]
#align has_fderiv_at.lim HasFDerivAt.lim
theorem HasFDerivAt.unique (h₀ : HasFDerivAt f f₀' x) (h₁ : HasFDerivAt f f₁' x) : f₀' = f₁' := by
rw [← hasFDerivWithinAt_univ] at h₀ h₁
exact uniqueDiffWithinAt_univ.eq h₀ h₁
#align has_fderiv_at.unique HasFDerivAt.unique
theorem hasFDerivWithinAt_inter' (h : t ∈ 𝓝[s] x) :
HasFDerivWithinAt f f' (s ∩ t) x ↔ HasFDerivWithinAt f f' s x := by
simp [HasFDerivWithinAt, nhdsWithin_restrict'' s h]
#align has_fderiv_within_at_inter' hasFDerivWithinAt_inter'
theorem hasFDerivWithinAt_inter (h : t ∈ 𝓝 x) :
HasFDerivWithinAt f f' (s ∩ t) x ↔ HasFDerivWithinAt f f' s x := by
simp [HasFDerivWithinAt, nhdsWithin_restrict' s h]
#align has_fderiv_within_at_inter hasFDerivWithinAt_inter
theorem HasFDerivWithinAt.union (hs : HasFDerivWithinAt f f' s x)
(ht : HasFDerivWithinAt f f' t x) : HasFDerivWithinAt f f' (s ∪ t) x := by
simp only [HasFDerivWithinAt, nhdsWithin_union]
exact .of_isLittleO <| hs.isLittleO.sup ht.isLittleO
#align has_fderiv_within_at.union HasFDerivWithinAt.union
theorem HasFDerivWithinAt.hasFDerivAt (h : HasFDerivWithinAt f f' s x) (hs : s ∈ 𝓝 x) :
HasFDerivAt f f' x := by
rwa [← univ_inter s, hasFDerivWithinAt_inter hs, hasFDerivWithinAt_univ] at h
#align has_fderiv_within_at.has_fderiv_at HasFDerivWithinAt.hasFDerivAt
theorem DifferentiableWithinAt.differentiableAt (h : DifferentiableWithinAt 𝕜 f s x)
(hs : s ∈ 𝓝 x) : DifferentiableAt 𝕜 f x :=
h.imp fun _ hf' => hf'.hasFDerivAt hs
#align differentiable_within_at.differentiable_at DifferentiableWithinAt.differentiableAt
/-- If `x` is isolated in `s`, then `f` has any derivative at `x` within `s`,
as this statement is empty. -/
theorem HasFDerivWithinAt.of_nhdsWithin_eq_bot (h : 𝓝[s\{x}] x = ⊥) :
HasFDerivWithinAt f f' s x := by
rw [← hasFDerivWithinAt_diff_singleton x, HasFDerivWithinAt, h, hasFDerivAtFilter_iff_isLittleO]
apply isLittleO_bot
/-- If `x` is not in the closure of `s`, then `f` has any derivative at `x` within `s`,
as this statement is empty. -/
theorem hasFDerivWithinAt_of_nmem_closure (h : x ∉ closure s) : HasFDerivWithinAt f f' s x :=
.of_nhdsWithin_eq_bot <| eq_bot_mono (nhdsWithin_mono _ diff_subset) <| by
rwa [mem_closure_iff_nhdsWithin_neBot, not_neBot] at h
#align has_fderiv_within_at_of_not_mem_closure hasFDerivWithinAt_of_nmem_closure
theorem DifferentiableWithinAt.hasFDerivWithinAt (h : DifferentiableWithinAt 𝕜 f s x) :
HasFDerivWithinAt f (fderivWithin 𝕜 f s x) s x := by
by_cases H : 𝓝[s \ {x}] x = ⊥
· exact .of_nhdsWithin_eq_bot H
· unfold DifferentiableWithinAt at h
rw [fderivWithin, if_neg H, dif_pos h]
exact Classical.choose_spec h
#align differentiable_within_at.has_fderiv_within_at DifferentiableWithinAt.hasFDerivWithinAt
theorem DifferentiableAt.hasFDerivAt (h : DifferentiableAt 𝕜 f x) :
HasFDerivAt f (fderiv 𝕜 f x) x := by
dsimp only [DifferentiableAt] at h
rw [fderiv, dif_pos h]
exact Classical.choose_spec h
#align differentiable_at.has_fderiv_at DifferentiableAt.hasFDerivAt
theorem DifferentiableOn.hasFDerivAt (h : DifferentiableOn 𝕜 f s) (hs : s ∈ 𝓝 x) :
HasFDerivAt f (fderiv 𝕜 f x) x :=
((h x (mem_of_mem_nhds hs)).differentiableAt hs).hasFDerivAt
#align differentiable_on.has_fderiv_at DifferentiableOn.hasFDerivAt
theorem DifferentiableOn.differentiableAt (h : DifferentiableOn 𝕜 f s) (hs : s ∈ 𝓝 x) :
DifferentiableAt 𝕜 f x :=
(h.hasFDerivAt hs).differentiableAt
#align differentiable_on.differentiable_at DifferentiableOn.differentiableAt
theorem DifferentiableOn.eventually_differentiableAt (h : DifferentiableOn 𝕜 f s) (hs : s ∈ 𝓝 x) :
∀ᶠ y in 𝓝 x, DifferentiableAt 𝕜 f y :=
(eventually_eventually_nhds.2 hs).mono fun _ => h.differentiableAt
#align differentiable_on.eventually_differentiable_at DifferentiableOn.eventually_differentiableAt
protected theorem HasFDerivAt.fderiv (h : HasFDerivAt f f' x) : fderiv 𝕜 f x = f' := by
ext
rw [h.unique h.differentiableAt.hasFDerivAt]
#align has_fderiv_at.fderiv HasFDerivAt.fderiv
theorem fderiv_eq {f' : E → E →L[𝕜] F} (h : ∀ x, HasFDerivAt f (f' x) x) : fderiv 𝕜 f = f' :=
funext fun x => (h x).fderiv
#align fderiv_eq fderiv_eq
variable (𝕜)
/-- Converse to the mean value inequality: if `f` is `C`-lipschitz
on a neighborhood of `x₀` then its derivative at `x₀` has norm bounded by `C`. This version
only assumes that `‖f x - f x₀‖ ≤ C * ‖x - x₀‖` in a neighborhood of `x`. -/
theorem norm_fderiv_le_of_lip' {f : E → F} {x₀ : E}
{C : ℝ} (hC₀ : 0 ≤ C) (hlip : ∀ᶠ x in 𝓝 x₀, ‖f x - f x₀‖ ≤ C * ‖x - x₀‖) :
‖fderiv 𝕜 f x₀‖ ≤ C := by
by_cases hf : DifferentiableAt 𝕜 f x₀
· exact hf.hasFDerivAt.le_of_lip' hC₀ hlip
· rw [fderiv_zero_of_not_differentiableAt hf]
simp [hC₀]
/-- Converse to the mean value inequality: if `f` is `C`-lipschitz
on a neighborhood of `x₀` then its derivative at `x₀` has norm bounded by `C`.
Version using `fderiv`. -/
-- Porting note: renamed so that dot-notation makes sense
theorem norm_fderiv_le_of_lipschitzOn {f : E → F} {x₀ : E} {s : Set E} (hs : s ∈ 𝓝 x₀)
{C : ℝ≥0} (hlip : LipschitzOnWith C f s) : ‖fderiv 𝕜 f x₀‖ ≤ C := by
refine norm_fderiv_le_of_lip' 𝕜 C.coe_nonneg ?_
filter_upwards [hs] with x hx using hlip.norm_sub_le hx (mem_of_mem_nhds hs)
#align fderiv_at.le_of_lip norm_fderiv_le_of_lipschitzOn
/-- Converse to the mean value inequality: if `f` is `C`-lipschitz then
its derivative at `x₀` has norm bounded by `C`.
Version using `fderiv`. -/
theorem norm_fderiv_le_of_lipschitz {f : E → F} {x₀ : E}
{C : ℝ≥0} (hlip : LipschitzWith C f) : ‖fderiv 𝕜 f x₀‖ ≤ C :=
norm_fderiv_le_of_lipschitzOn 𝕜 univ_mem (lipschitzOn_univ.2 hlip)
variable {𝕜}
protected theorem HasFDerivWithinAt.fderivWithin (h : HasFDerivWithinAt f f' s x)
(hxs : UniqueDiffWithinAt 𝕜 s x) : fderivWithin 𝕜 f s x = f' :=
(hxs.eq h h.differentiableWithinAt.hasFDerivWithinAt).symm
#align has_fderiv_within_at.fderiv_within HasFDerivWithinAt.fderivWithin
theorem DifferentiableWithinAt.mono (h : DifferentiableWithinAt 𝕜 f t x) (st : s ⊆ t) :
DifferentiableWithinAt 𝕜 f s x := by
rcases h with ⟨f', hf'⟩
exact ⟨f', hf'.mono st⟩
#align differentiable_within_at.mono DifferentiableWithinAt.mono
theorem DifferentiableWithinAt.mono_of_mem (h : DifferentiableWithinAt 𝕜 f s x) {t : Set E}
(hst : s ∈ 𝓝[t] x) : DifferentiableWithinAt 𝕜 f t x :=
(h.hasFDerivWithinAt.mono_of_mem hst).differentiableWithinAt
#align differentiable_within_at.mono_of_mem DifferentiableWithinAt.mono_of_mem
theorem differentiableWithinAt_univ :
DifferentiableWithinAt 𝕜 f univ x ↔ DifferentiableAt 𝕜 f x := by
simp only [DifferentiableWithinAt, hasFDerivWithinAt_univ, DifferentiableAt]
#align differentiable_within_at_univ differentiableWithinAt_univ
theorem differentiableWithinAt_inter (ht : t ∈ 𝓝 x) :
DifferentiableWithinAt 𝕜 f (s ∩ t) x ↔ DifferentiableWithinAt 𝕜 f s x := by
simp only [DifferentiableWithinAt, hasFDerivWithinAt_inter ht]
#align differentiable_within_at_inter differentiableWithinAt_inter
theorem differentiableWithinAt_inter' (ht : t ∈ 𝓝[s] x) :
DifferentiableWithinAt 𝕜 f (s ∩ t) x ↔ DifferentiableWithinAt 𝕜 f s x := by
simp only [DifferentiableWithinAt, hasFDerivWithinAt_inter' ht]
#align differentiable_within_at_inter' differentiableWithinAt_inter'
theorem DifferentiableAt.differentiableWithinAt (h : DifferentiableAt 𝕜 f x) :
DifferentiableWithinAt 𝕜 f s x :=
(differentiableWithinAt_univ.2 h).mono (subset_univ _)
#align differentiable_at.differentiable_within_at DifferentiableAt.differentiableWithinAt
@[fun_prop]
theorem Differentiable.differentiableAt (h : Differentiable 𝕜 f) : DifferentiableAt 𝕜 f x :=
h x
#align differentiable.differentiable_at Differentiable.differentiableAt
protected theorem DifferentiableAt.fderivWithin (h : DifferentiableAt 𝕜 f x)
(hxs : UniqueDiffWithinAt 𝕜 s x) : fderivWithin 𝕜 f s x = fderiv 𝕜 f x :=
h.hasFDerivAt.hasFDerivWithinAt.fderivWithin hxs
#align differentiable_at.fderiv_within DifferentiableAt.fderivWithin
theorem DifferentiableOn.mono (h : DifferentiableOn 𝕜 f t) (st : s ⊆ t) : DifferentiableOn 𝕜 f s :=
fun x hx => (h x (st hx)).mono st
#align differentiable_on.mono DifferentiableOn.mono
theorem differentiableOn_univ : DifferentiableOn 𝕜 f univ ↔ Differentiable 𝕜 f := by
simp only [DifferentiableOn, Differentiable, differentiableWithinAt_univ, mem_univ,
forall_true_left]
#align differentiable_on_univ differentiableOn_univ
@[fun_prop]
theorem Differentiable.differentiableOn (h : Differentiable 𝕜 f) : DifferentiableOn 𝕜 f s :=
(differentiableOn_univ.2 h).mono (subset_univ _)
#align differentiable.differentiable_on Differentiable.differentiableOn
| Mathlib/Analysis/Calculus/FDeriv/Basic.lean | 675 | 680 | theorem differentiableOn_of_locally_differentiableOn
(h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ DifferentiableOn 𝕜 f (s ∩ u)) :
DifferentiableOn 𝕜 f s := by |
intro x xs
rcases h x xs with ⟨t, t_open, xt, ht⟩
exact (differentiableWithinAt_inter (IsOpen.mem_nhds t_open xt)).1 (ht x ⟨xs, xt⟩)
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Anne Baanen
-/
import Mathlib.LinearAlgebra.Dimension.Basic
import Mathlib.SetTheory.Cardinal.ToNat
#align_import linear_algebra.finrank from "leanprover-community/mathlib"@"347636a7a80595d55bedf6e6fbd996a3c39da69a"
/-!
# Finite dimension of vector spaces
Definition of the rank of a module, or dimension of a vector space, as a natural number.
## Main definitions
Defined is `FiniteDimensional.finrank`, the dimension of a finite dimensional space, returning a
`Nat`, as opposed to `Module.rank`, which returns a `Cardinal`. When the space has infinite
dimension, its `finrank` is by convention set to `0`.
The definition of `finrank` does not assume a `FiniteDimensional` instance, but lemmas might.
Import `LinearAlgebra.FiniteDimensional` to get access to these additional lemmas.
Formulas for the dimension are given for linear equivs, in `LinearEquiv.finrank_eq`.
## Implementation notes
Most results are deduced from the corresponding results for the general dimension (as a cardinal),
in `Dimension.lean`. Not all results have been ported yet.
You should not assume that there has been any effort to state lemmas as generally as possible.
-/
universe u v w
open Cardinal Submodule Module Function
variable {R : Type u} {M : Type v} {N : Type w}
variable [Ring R] [AddCommGroup M] [Module R M] [AddCommGroup N] [Module R N]
namespace FiniteDimensional
section Ring
/-- The rank of a module as a natural number.
Defined by convention to be `0` if the space has infinite rank.
For a vector space `M` over a field `R`, this is the same as the finite dimension
of `M` over `R`.
-/
noncomputable def finrank (R M : Type*) [Semiring R] [AddCommGroup M] [Module R M] : ℕ :=
Cardinal.toNat (Module.rank R M)
#align finite_dimensional.finrank FiniteDimensional.finrank
theorem finrank_eq_of_rank_eq {n : ℕ} (h : Module.rank R M = ↑n) : finrank R M = n := by
apply_fun toNat at h
rw [toNat_natCast] at h
exact mod_cast h
#align finite_dimensional.finrank_eq_of_rank_eq FiniteDimensional.finrank_eq_of_rank_eq
lemma rank_eq_one_iff_finrank_eq_one : Module.rank R M = 1 ↔ finrank R M = 1 :=
Cardinal.toNat_eq_one.symm
/-- This is like `rank_eq_one_iff_finrank_eq_one` but works for `2`, `3`, `4`, ... -/
lemma rank_eq_ofNat_iff_finrank_eq_ofNat (n : ℕ) [Nat.AtLeastTwo n] :
Module.rank R M = OfNat.ofNat n ↔ finrank R M = OfNat.ofNat n :=
Cardinal.toNat_eq_ofNat.symm
| Mathlib/LinearAlgebra/Dimension/Finrank.lean | 72 | 75 | theorem finrank_le_of_rank_le {n : ℕ} (h : Module.rank R M ≤ ↑n) : finrank R M ≤ n := by |
rwa [← Cardinal.toNat_le_iff_le_of_lt_aleph0, toNat_natCast] at h
· exact h.trans_lt (nat_lt_aleph0 n)
· exact nat_lt_aleph0 n
|
/-
Copyright (c) 2021 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Sébastien Gouëzel
-/
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.MeasureTheory.Group.Pointwise
import Mathlib.MeasureTheory.Measure.Lebesgue.Basic
import Mathlib.MeasureTheory.Measure.Haar.Basic
import Mathlib.MeasureTheory.Measure.Doubling
import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric
#align_import measure_theory.measure.lebesgue.eq_haar from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Relationship between the Haar and Lebesgue measures
We prove that the Haar measure and Lebesgue measure are equal on `ℝ` and on `ℝ^ι`, in
`MeasureTheory.addHaarMeasure_eq_volume` and `MeasureTheory.addHaarMeasure_eq_volume_pi`.
We deduce basic properties of any Haar measure on a finite dimensional real vector space:
* `map_linearMap_addHaar_eq_smul_addHaar`: a linear map rescales the Haar measure by the
absolute value of its determinant.
* `addHaar_preimage_linearMap` : when `f` is a linear map with nonzero determinant, the measure
of `f ⁻¹' s` is the measure of `s` multiplied by the absolute value of the inverse of the
determinant of `f`.
* `addHaar_image_linearMap` : when `f` is a linear map, the measure of `f '' s` is the
measure of `s` multiplied by the absolute value of the determinant of `f`.
* `addHaar_submodule` : a strict submodule has measure `0`.
* `addHaar_smul` : the measure of `r • s` is `|r| ^ dim * μ s`.
* `addHaar_ball`: the measure of `ball x r` is `r ^ dim * μ (ball 0 1)`.
* `addHaar_closedBall`: the measure of `closedBall x r` is `r ^ dim * μ (ball 0 1)`.
* `addHaar_sphere`: spheres have zero measure.
This makes it possible to associate a Lebesgue measure to an `n`-alternating map in dimension `n`.
This measure is called `AlternatingMap.measure`. Its main property is
`ω.measure_parallelepiped v`, stating that the associated measure of the parallelepiped spanned
by vectors `v₁, ..., vₙ` is given by `|ω v|`.
We also show that a Lebesgue density point `x` of a set `s` (with respect to closed balls) has
density one for the rescaled copies `{x} + r • t` of a given set `t` with positive measure, in
`tendsto_addHaar_inter_smul_one_of_density_one`. In particular, `s` intersects `{x} + r • t` for
small `r`, see `eventually_nonempty_inter_smul_of_density_one`.
Statements on integrals of functions with respect to an additive Haar measure can be found in
`MeasureTheory.Measure.Haar.NormedSpace`.
-/
assert_not_exists MeasureTheory.integral
open TopologicalSpace Set Filter Metric Bornology
open scoped ENNReal Pointwise Topology NNReal
/-- The interval `[0,1]` as a compact set with non-empty interior. -/
def TopologicalSpace.PositiveCompacts.Icc01 : PositiveCompacts ℝ where
carrier := Icc 0 1
isCompact' := isCompact_Icc
interior_nonempty' := by simp_rw [interior_Icc, nonempty_Ioo, zero_lt_one]
#align topological_space.positive_compacts.Icc01 TopologicalSpace.PositiveCompacts.Icc01
universe u
/-- The set `[0,1]^ι` as a compact set with non-empty interior. -/
def TopologicalSpace.PositiveCompacts.piIcc01 (ι : Type*) [Finite ι] :
PositiveCompacts (ι → ℝ) where
carrier := pi univ fun _ => Icc 0 1
isCompact' := isCompact_univ_pi fun _ => isCompact_Icc
interior_nonempty' := by
simp only [interior_pi_set, Set.toFinite, interior_Icc, univ_pi_nonempty_iff, nonempty_Ioo,
imp_true_iff, zero_lt_one]
#align topological_space.positive_compacts.pi_Icc01 TopologicalSpace.PositiveCompacts.piIcc01
/-- The parallelepiped formed from the standard basis for `ι → ℝ` is `[0,1]^ι` -/
theorem Basis.parallelepiped_basisFun (ι : Type*) [Fintype ι] :
(Pi.basisFun ℝ ι).parallelepiped = TopologicalSpace.PositiveCompacts.piIcc01 ι :=
SetLike.coe_injective <| by
refine Eq.trans ?_ ((uIcc_of_le ?_).trans (Set.pi_univ_Icc _ _).symm)
· classical convert parallelepiped_single (ι := ι) 1
· exact zero_le_one
#align basis.parallelepiped_basis_fun Basis.parallelepiped_basisFun
/-- A parallelepiped can be expressed on the standard basis. -/
theorem Basis.parallelepiped_eq_map {ι E : Type*} [Fintype ι] [NormedAddCommGroup E]
[NormedSpace ℝ E] (b : Basis ι ℝ E) :
b.parallelepiped = (PositiveCompacts.piIcc01 ι).map b.equivFun.symm
b.equivFunL.symm.continuous b.equivFunL.symm.isOpenMap := by
classical
rw [← Basis.parallelepiped_basisFun, ← Basis.parallelepiped_map]
congr with x
simp
open MeasureTheory MeasureTheory.Measure
theorem Basis.map_addHaar {ι E F : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedAddCommGroup F]
[NormedSpace ℝ E] [NormedSpace ℝ F] [MeasurableSpace E] [MeasurableSpace F] [BorelSpace E]
[BorelSpace F] [SecondCountableTopology F] [SigmaCompactSpace F]
(b : Basis ι ℝ E) (f : E ≃L[ℝ] F) :
map f b.addHaar = (b.map f.toLinearEquiv).addHaar := by
have : IsAddHaarMeasure (map f b.addHaar) :=
AddEquiv.isAddHaarMeasure_map b.addHaar f.toAddEquiv f.continuous f.symm.continuous
rw [eq_comm, Basis.addHaar_eq_iff, Measure.map_apply f.continuous.measurable
(PositiveCompacts.isCompact _).measurableSet, Basis.coe_parallelepiped, Basis.coe_map]
erw [← image_parallelepiped, f.toEquiv.preimage_image, addHaar_self]
namespace MeasureTheory
open Measure TopologicalSpace.PositiveCompacts FiniteDimensional
/-!
### The Lebesgue measure is a Haar measure on `ℝ` and on `ℝ^ι`.
-/
/-- The Haar measure equals the Lebesgue measure on `ℝ`. -/
theorem addHaarMeasure_eq_volume : addHaarMeasure Icc01 = volume := by
convert (addHaarMeasure_unique volume Icc01).symm; simp [Icc01]
#align measure_theory.add_haar_measure_eq_volume MeasureTheory.addHaarMeasure_eq_volume
/-- The Haar measure equals the Lebesgue measure on `ℝ^ι`. -/
theorem addHaarMeasure_eq_volume_pi (ι : Type*) [Fintype ι] :
addHaarMeasure (piIcc01 ι) = volume := by
convert (addHaarMeasure_unique volume (piIcc01 ι)).symm
simp only [piIcc01, volume_pi_pi fun _ => Icc (0 : ℝ) 1, PositiveCompacts.coe_mk,
Compacts.coe_mk, Finset.prod_const_one, ENNReal.ofReal_one, Real.volume_Icc, one_smul, sub_zero]
#align measure_theory.add_haar_measure_eq_volume_pi MeasureTheory.addHaarMeasure_eq_volume_pi
-- Porting note (#11215): TODO: remove this instance?
instance isAddHaarMeasure_volume_pi (ι : Type*) [Fintype ι] :
IsAddHaarMeasure (volume : Measure (ι → ℝ)) :=
inferInstance
#align measure_theory.is_add_haar_measure_volume_pi MeasureTheory.isAddHaarMeasure_volume_pi
namespace Measure
/-!
### Strict subspaces have zero measure
-/
/-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure
zero. This auxiliary lemma proves this assuming additionally that the set is bounded. -/
theorem addHaar_eq_zero_of_disjoint_translates_aux {E : Type*} [NormedAddCommGroup E]
[NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E)
[IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (sb : IsBounded s) (hu : IsBounded (range u))
(hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by
by_contra h
apply lt_irrefl ∞
calc
∞ = ∑' _ : ℕ, μ s := (ENNReal.tsum_const_eq_top_of_ne_zero h).symm
_ = ∑' n : ℕ, μ ({u n} + s) := by
congr 1; ext1 n; simp only [image_add_left, measure_preimage_add, singleton_add]
_ = μ (⋃ n, {u n} + s) := Eq.symm <| measure_iUnion hs fun n => by
simpa only [image_add_left, singleton_add] using measurable_id.const_add _ h's
_ = μ (range u + s) := by rw [← iUnion_add, iUnion_singleton_eq_range]
_ < ∞ := (hu.add sb).measure_lt_top
#align measure_theory.measure.add_haar_eq_zero_of_disjoint_translates_aux MeasureTheory.Measure.addHaar_eq_zero_of_disjoint_translates_aux
/-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure
zero. -/
theorem addHaar_eq_zero_of_disjoint_translates {E : Type*} [NormedAddCommGroup E]
[NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E)
[IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (hu : IsBounded (range u))
(hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by
suffices H : ∀ R, μ (s ∩ closedBall 0 R) = 0 by
apply le_antisymm _ (zero_le _)
calc
μ s ≤ ∑' n : ℕ, μ (s ∩ closedBall 0 n) := by
conv_lhs => rw [← iUnion_inter_closedBall_nat s 0]
exact measure_iUnion_le _
_ = 0 := by simp only [H, tsum_zero]
intro R
apply addHaar_eq_zero_of_disjoint_translates_aux μ u
(isBounded_closedBall.subset inter_subset_right) hu _ (h's.inter measurableSet_closedBall)
refine pairwise_disjoint_mono hs fun n => ?_
exact add_subset_add Subset.rfl inter_subset_left
#align measure_theory.measure.add_haar_eq_zero_of_disjoint_translates MeasureTheory.Measure.addHaar_eq_zero_of_disjoint_translates
/-- A strict vector subspace has measure zero. -/
theorem addHaar_submodule {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E]
[BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] (s : Submodule ℝ E)
(hs : s ≠ ⊤) : μ s = 0 := by
obtain ⟨x, hx⟩ : ∃ x, x ∉ s := by
simpa only [Submodule.eq_top_iff', not_exists, Ne, not_forall] using hs
obtain ⟨c, cpos, cone⟩ : ∃ c : ℝ, 0 < c ∧ c < 1 := ⟨1 / 2, by norm_num, by norm_num⟩
have A : IsBounded (range fun n : ℕ => c ^ n • x) :=
have : Tendsto (fun n : ℕ => c ^ n • x) atTop (𝓝 ((0 : ℝ) • x)) :=
(tendsto_pow_atTop_nhds_zero_of_lt_one cpos.le cone).smul_const x
isBounded_range_of_tendsto _ this
apply addHaar_eq_zero_of_disjoint_translates μ _ A _
(Submodule.closed_of_finiteDimensional s).measurableSet
intro m n hmn
simp only [Function.onFun, image_add_left, singleton_add, disjoint_left, mem_preimage,
SetLike.mem_coe]
intro y hym hyn
have A : (c ^ n - c ^ m) • x ∈ s := by
convert s.sub_mem hym hyn using 1
simp only [sub_smul, neg_sub_neg, add_sub_add_right_eq_sub]
have H : c ^ n - c ^ m ≠ 0 := by
simpa only [sub_eq_zero, Ne] using (pow_right_strictAnti cpos cone).injective.ne hmn.symm
have : x ∈ s := by
convert s.smul_mem (c ^ n - c ^ m)⁻¹ A
rw [smul_smul, inv_mul_cancel H, one_smul]
exact hx this
#align measure_theory.measure.add_haar_submodule MeasureTheory.Measure.addHaar_submodule
/-- A strict affine subspace has measure zero. -/
theorem addHaar_affineSubspace {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ]
(s : AffineSubspace ℝ E) (hs : s ≠ ⊤) : μ s = 0 := by
rcases s.eq_bot_or_nonempty with (rfl | hne)
· rw [AffineSubspace.bot_coe, measure_empty]
rw [Ne, ← AffineSubspace.direction_eq_top_iff_of_nonempty hne] at hs
rcases hne with ⟨x, hx : x ∈ s⟩
simpa only [AffineSubspace.coe_direction_eq_vsub_set_right hx, vsub_eq_sub, sub_eq_add_neg,
image_add_right, neg_neg, measure_preimage_add_right] using addHaar_submodule μ s.direction hs
#align measure_theory.measure.add_haar_affine_subspace MeasureTheory.Measure.addHaar_affineSubspace
/-!
### Applying a linear map rescales Haar measure by the determinant
We first prove this on `ι → ℝ`, using that this is already known for the product Lebesgue
measure (thanks to matrices computations). Then, we extend this to any finite-dimensional real
vector space by using a linear equiv with a space of the form `ι → ℝ`, and arguing that such a
linear equiv maps Haar measure to Haar measure.
-/
theorem map_linearMap_addHaar_pi_eq_smul_addHaar {ι : Type*} [Finite ι] {f : (ι → ℝ) →ₗ[ℝ] ι → ℝ}
(hf : LinearMap.det f ≠ 0) (μ : Measure (ι → ℝ)) [IsAddHaarMeasure μ] :
Measure.map f μ = ENNReal.ofReal (abs (LinearMap.det f)⁻¹) • μ := by
cases nonempty_fintype ι
/- We have already proved the result for the Lebesgue product measure, using matrices.
We deduce it for any Haar measure by uniqueness (up to scalar multiplication). -/
have := addHaarMeasure_unique μ (piIcc01 ι)
rw [this, addHaarMeasure_eq_volume_pi, Measure.map_smul,
Real.map_linearMap_volume_pi_eq_smul_volume_pi hf, smul_comm]
#align measure_theory.measure.map_linear_map_add_haar_pi_eq_smul_add_haar MeasureTheory.Measure.map_linearMap_addHaar_pi_eq_smul_addHaar
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
[FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {F : Type*} [NormedAddCommGroup F]
[NormedSpace ℝ F] [CompleteSpace F]
theorem map_linearMap_addHaar_eq_smul_addHaar {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) :
Measure.map f μ = ENNReal.ofReal |(LinearMap.det f)⁻¹| • μ := by
-- we reduce to the case of `E = ι → ℝ`, for which we have already proved the result using
-- matrices in `map_linearMap_addHaar_pi_eq_smul_addHaar`.
let ι := Fin (finrank ℝ E)
haveI : FiniteDimensional ℝ (ι → ℝ) := by infer_instance
have : finrank ℝ E = finrank ℝ (ι → ℝ) := by simp [ι]
have e : E ≃ₗ[ℝ] ι → ℝ := LinearEquiv.ofFinrankEq E (ι → ℝ) this
-- next line is to avoid `g` getting reduced by `simp`.
obtain ⟨g, hg⟩ : ∃ g, g = (e : E →ₗ[ℝ] ι → ℝ).comp (f.comp (e.symm : (ι → ℝ) →ₗ[ℝ] E)) := ⟨_, rfl⟩
have gdet : LinearMap.det g = LinearMap.det f := by rw [hg]; exact LinearMap.det_conj f e
rw [← gdet] at hf ⊢
have fg : f = (e.symm : (ι → ℝ) →ₗ[ℝ] E).comp (g.comp (e : E →ₗ[ℝ] ι → ℝ)) := by
ext x
simp only [LinearEquiv.coe_coe, Function.comp_apply, LinearMap.coe_comp,
LinearEquiv.symm_apply_apply, hg]
simp only [fg, LinearEquiv.coe_coe, LinearMap.coe_comp]
have Ce : Continuous e := (e : E →ₗ[ℝ] ι → ℝ).continuous_of_finiteDimensional
have Cg : Continuous g := LinearMap.continuous_of_finiteDimensional g
have Cesymm : Continuous e.symm := (e.symm : (ι → ℝ) →ₗ[ℝ] E).continuous_of_finiteDimensional
rw [← map_map Cesymm.measurable (Cg.comp Ce).measurable, ← map_map Cg.measurable Ce.measurable]
haveI : IsAddHaarMeasure (map e μ) := (e : E ≃+ (ι → ℝ)).isAddHaarMeasure_map μ Ce Cesymm
have ecomp : e.symm ∘ e = id := by
ext x; simp only [id, Function.comp_apply, LinearEquiv.symm_apply_apply]
rw [map_linearMap_addHaar_pi_eq_smul_addHaar hf (map e μ), Measure.map_smul,
map_map Cesymm.measurable Ce.measurable, ecomp, Measure.map_id]
#align measure_theory.measure.map_linear_map_add_haar_eq_smul_add_haar MeasureTheory.Measure.map_linearMap_addHaar_eq_smul_addHaar
/-- The preimage of a set `s` under a linear map `f` with nonzero determinant has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_linearMap {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s :=
calc
μ (f ⁻¹' s) = Measure.map f μ s :=
((f.equivOfDetNeZero hf).toContinuousLinearEquiv.toHomeomorph.toMeasurableEquiv.map_apply
s).symm
_ = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s := by
rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]; rfl
#align measure_theory.measure.add_haar_preimage_linear_map MeasureTheory.Measure.addHaar_preimage_linearMap
/-- The preimage of a set `s` under a continuous linear map `f` with nonzero determinant has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_continuousLinearMap {f : E →L[ℝ] E}
(hf : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal (abs (LinearMap.det (f : E →ₗ[ℝ] E))⁻¹) * μ s :=
addHaar_preimage_linearMap μ hf s
#align measure_theory.measure.add_haar_preimage_continuous_linear_map MeasureTheory.Measure.addHaar_preimage_continuousLinearMap
/-- The preimage of a set `s` under a linear equiv `f` has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_linearEquiv (f : E ≃ₗ[ℝ] E) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s := by
have A : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0 := (LinearEquiv.isUnit_det' f).ne_zero
convert addHaar_preimage_linearMap μ A s
simp only [LinearEquiv.det_coe_symm]
#align measure_theory.measure.add_haar_preimage_linear_equiv MeasureTheory.Measure.addHaar_preimage_linearEquiv
/-- The preimage of a set `s` under a continuous linear equiv `f` has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s :=
addHaar_preimage_linearEquiv μ _ s
#align measure_theory.measure.add_haar_preimage_continuous_linear_equiv MeasureTheory.Measure.addHaar_preimage_continuousLinearEquiv
/-- The image of a set `s` under a linear map `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_linearMap (f : E →ₗ[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det f| * μ s := by
rcases ne_or_eq (LinearMap.det f) 0 with (hf | hf)
· let g := (f.equivOfDetNeZero hf).toContinuousLinearEquiv
change μ (g '' s) = _
rw [ContinuousLinearEquiv.image_eq_preimage g s, addHaar_preimage_continuousLinearEquiv]
congr
· simp only [hf, zero_mul, ENNReal.ofReal_zero, abs_zero]
have : μ (LinearMap.range f) = 0 :=
addHaar_submodule μ _ (LinearMap.range_lt_top_of_det_eq_zero hf).ne
exact le_antisymm (le_trans (measure_mono (image_subset_range _ _)) this.le) (zero_le _)
#align measure_theory.measure.add_haar_image_linear_map MeasureTheory.Measure.addHaar_image_linearMap
/-- The image of a set `s` under a continuous linear map `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_continuousLinearMap (f : E →L[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s :=
addHaar_image_linearMap μ _ s
#align measure_theory.measure.add_haar_image_continuous_linear_map MeasureTheory.Measure.addHaar_image_continuousLinearMap
/-- The image of a set `s` under a continuous linear equiv `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s :=
μ.addHaar_image_linearMap (f : E →ₗ[ℝ] E) s
#align measure_theory.measure.add_haar_image_continuous_linear_equiv MeasureTheory.Measure.addHaar_image_continuousLinearEquiv
theorem LinearMap.quasiMeasurePreserving (f : E →ₗ[ℝ] E) (hf : LinearMap.det f ≠ 0) :
QuasiMeasurePreserving f μ μ := by
refine ⟨f.continuous_of_finiteDimensional.measurable, ?_⟩
rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]
exact smul_absolutelyContinuous
theorem ContinuousLinearMap.quasiMeasurePreserving (f : E →L[ℝ] E) (hf : f.det ≠ 0) :
QuasiMeasurePreserving f μ μ :=
LinearMap.quasiMeasurePreserving μ (f : E →ₗ[ℝ] E) hf
/-!
### Basic properties of Haar measures on real vector spaces
-/
theorem map_addHaar_smul {r : ℝ} (hr : r ≠ 0) :
Measure.map (r • ·) μ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) • μ := by
let f : E →ₗ[ℝ] E := r • (1 : E →ₗ[ℝ] E)
change Measure.map f μ = _
have hf : LinearMap.det f ≠ 0 := by
simp only [f, mul_one, LinearMap.det_smul, Ne, MonoidHom.map_one]
intro h
exact hr (pow_eq_zero h)
simp only [f, map_linearMap_addHaar_eq_smul_addHaar μ hf, mul_one, LinearMap.det_smul, map_one]
#align measure_theory.measure.map_add_haar_smul MeasureTheory.Measure.map_addHaar_smul
theorem quasiMeasurePreserving_smul {r : ℝ} (hr : r ≠ 0) :
QuasiMeasurePreserving (r • ·) μ μ := by
refine ⟨measurable_const_smul r, ?_⟩
rw [map_addHaar_smul μ hr]
exact smul_absolutelyContinuous
@[simp]
theorem addHaar_preimage_smul {r : ℝ} (hr : r ≠ 0) (s : Set E) :
μ ((r • ·) ⁻¹' s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) * μ s :=
calc
μ ((r • ·) ⁻¹' s) = Measure.map (r • ·) μ s :=
((Homeomorph.smul (isUnit_iff_ne_zero.2 hr).unit).toMeasurableEquiv.map_apply s).symm
_ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) * μ s := by
rw [map_addHaar_smul μ hr, coe_smul, Pi.smul_apply, smul_eq_mul]
#align measure_theory.measure.add_haar_preimage_smul MeasureTheory.Measure.addHaar_preimage_smul
/-- Rescaling a set by a factor `r` multiplies its measure by `abs (r ^ dim)`. -/
@[simp]
theorem addHaar_smul (r : ℝ) (s : Set E) :
μ (r • s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := by
rcases ne_or_eq r 0 with (h | rfl)
· rw [← preimage_smul_inv₀ h, addHaar_preimage_smul μ (inv_ne_zero h), inv_pow, inv_inv]
rcases eq_empty_or_nonempty s with (rfl | hs)
· simp only [measure_empty, mul_zero, smul_set_empty]
rw [zero_smul_set hs, ← singleton_zero]
by_cases h : finrank ℝ E = 0
· haveI : Subsingleton E := finrank_zero_iff.1 h
simp only [h, one_mul, ENNReal.ofReal_one, abs_one, Subsingleton.eq_univ_of_nonempty hs,
pow_zero, Subsingleton.eq_univ_of_nonempty (singleton_nonempty (0 : E))]
· haveI : Nontrivial E := nontrivial_of_finrank_pos (bot_lt_iff_ne_bot.2 h)
simp only [h, zero_mul, ENNReal.ofReal_zero, abs_zero, Ne, not_false_iff,
zero_pow, measure_singleton]
#align measure_theory.measure.add_haar_smul MeasureTheory.Measure.addHaar_smul
theorem addHaar_smul_of_nonneg {r : ℝ} (hr : 0 ≤ r) (s : Set E) :
μ (r • s) = ENNReal.ofReal (r ^ finrank ℝ E) * μ s := by
rw [addHaar_smul, abs_pow, abs_of_nonneg hr]
#align measure_theory.measure.add_haar_smul_of_nonneg MeasureTheory.Measure.addHaar_smul_of_nonneg
variable {μ} {s : Set E}
-- Note: We might want to rename this once we acquire the lemma corresponding to
-- `MeasurableSet.const_smul`
theorem NullMeasurableSet.const_smul (hs : NullMeasurableSet s μ) (r : ℝ) :
NullMeasurableSet (r • s) μ := by
obtain rfl | hs' := s.eq_empty_or_nonempty
· simp
obtain rfl | hr := eq_or_ne r 0
· simpa [zero_smul_set hs'] using nullMeasurableSet_singleton _
obtain ⟨t, ht, hst⟩ := hs
refine ⟨_, ht.const_smul_of_ne_zero hr, ?_⟩
rw [← measure_symmDiff_eq_zero_iff] at hst ⊢
rw [← smul_set_symmDiff₀ hr, addHaar_smul μ, hst, mul_zero]
#align measure_theory.measure.null_measurable_set.const_smul MeasureTheory.Measure.NullMeasurableSet.const_smul
variable (μ)
@[simp]
theorem addHaar_image_homothety (x : E) (r : ℝ) (s : Set E) :
μ (AffineMap.homothety x r '' s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s :=
calc
μ (AffineMap.homothety x r '' s) = μ ((fun y => y + x) '' (r • (fun y => y + -x) '' s)) := by
simp only [← image_smul, image_image, ← sub_eq_add_neg]; rfl
_ = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := by
simp only [image_add_right, measure_preimage_add_right, addHaar_smul]
#align measure_theory.measure.add_haar_image_homothety MeasureTheory.Measure.addHaar_image_homothety
/-! We don't need to state `map_addHaar_neg` here, because it has already been proved for
general Haar measures on general commutative groups. -/
/-! ### Measure of balls -/
theorem addHaar_ball_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E] [BorelSpace E]
(μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) : μ (ball x r) = μ (ball (0 : E) r) := by
have : ball (0 : E) r = (x + ·) ⁻¹' ball x r := by simp [preimage_add_ball]
rw [this, measure_preimage_add]
#align measure_theory.measure.add_haar_ball_center MeasureTheory.Measure.addHaar_ball_center
theorem addHaar_closedBall_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E]
[BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) :
μ (closedBall x r) = μ (closedBall (0 : E) r) := by
have : closedBall (0 : E) r = (x + ·) ⁻¹' closedBall x r := by simp [preimage_add_closedBall]
rw [this, measure_preimage_add]
#align measure_theory.measure.add_haar_closed_ball_center MeasureTheory.Measure.addHaar_closedBall_center
theorem addHaar_ball_mul_of_pos (x : E) {r : ℝ} (hr : 0 < r) (s : ℝ) :
μ (ball x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 s) := by
have : ball (0 : E) (r * s) = r • ball (0 : E) s := by
simp only [_root_.smul_ball hr.ne' (0 : E) s, Real.norm_eq_abs, abs_of_nonneg hr.le, smul_zero]
simp only [this, addHaar_smul, abs_of_nonneg hr.le, addHaar_ball_center, abs_pow]
#align measure_theory.measure.add_haar_ball_mul_of_pos MeasureTheory.Measure.addHaar_ball_mul_of_pos
theorem addHaar_ball_of_pos (x : E) {r : ℝ} (hr : 0 < r) :
μ (ball x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 1) := by
rw [← addHaar_ball_mul_of_pos μ x hr, mul_one]
#align measure_theory.measure.add_haar_ball_of_pos MeasureTheory.Measure.addHaar_ball_of_pos
theorem addHaar_ball_mul [Nontrivial E] (x : E) {r : ℝ} (hr : 0 ≤ r) (s : ℝ) :
μ (ball x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 s) := by
rcases hr.eq_or_lt with (rfl | h)
· simp only [zero_pow (finrank_pos (R := ℝ) (M := E)).ne', measure_empty, zero_mul,
ENNReal.ofReal_zero, ball_zero]
· exact addHaar_ball_mul_of_pos μ x h s
#align measure_theory.measure.add_haar_ball_mul MeasureTheory.Measure.addHaar_ball_mul
theorem addHaar_ball [Nontrivial E] (x : E) {r : ℝ} (hr : 0 ≤ r) :
μ (ball x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 1) := by
rw [← addHaar_ball_mul μ x hr, mul_one]
#align measure_theory.measure.add_haar_ball MeasureTheory.Measure.addHaar_ball
theorem addHaar_closedBall_mul_of_pos (x : E) {r : ℝ} (hr : 0 < r) (s : ℝ) :
μ (closedBall x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall 0 s) := by
have : closedBall (0 : E) (r * s) = r • closedBall (0 : E) s := by
simp [smul_closedBall' hr.ne' (0 : E), abs_of_nonneg hr.le]
simp only [this, addHaar_smul, abs_of_nonneg hr.le, addHaar_closedBall_center, abs_pow]
#align measure_theory.measure.add_haar_closed_ball_mul_of_pos MeasureTheory.Measure.addHaar_closedBall_mul_of_pos
theorem addHaar_closedBall_mul (x : E) {r : ℝ} (hr : 0 ≤ r) {s : ℝ} (hs : 0 ≤ s) :
μ (closedBall x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall 0 s) := by
have : closedBall (0 : E) (r * s) = r • closedBall (0 : E) s := by
simp [smul_closedBall r (0 : E) hs, abs_of_nonneg hr]
simp only [this, addHaar_smul, abs_of_nonneg hr, addHaar_closedBall_center, abs_pow]
#align measure_theory.measure.add_haar_closed_ball_mul MeasureTheory.Measure.addHaar_closedBall_mul
/-- The measure of a closed ball can be expressed in terms of the measure of the closed unit ball.
Use instead `addHaar_closedBall`, which uses the measure of the open unit ball as a standard
form. -/
theorem addHaar_closedBall' (x : E) {r : ℝ} (hr : 0 ≤ r) :
μ (closedBall x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall 0 1) := by
rw [← addHaar_closedBall_mul μ x hr zero_le_one, mul_one]
#align measure_theory.measure.add_haar_closed_ball' MeasureTheory.Measure.addHaar_closedBall'
theorem addHaar_closed_unit_ball_eq_addHaar_unit_ball :
μ (closedBall (0 : E) 1) = μ (ball 0 1) := by
apply le_antisymm _ (measure_mono ball_subset_closedBall)
have A : Tendsto
(fun r : ℝ => ENNReal.ofReal (r ^ finrank ℝ E) * μ (closedBall (0 : E) 1)) (𝓝[<] 1)
(𝓝 (ENNReal.ofReal ((1 : ℝ) ^ finrank ℝ E) * μ (closedBall (0 : E) 1))) := by
refine ENNReal.Tendsto.mul ?_ (by simp) tendsto_const_nhds (by simp)
exact ENNReal.tendsto_ofReal ((tendsto_id'.2 nhdsWithin_le_nhds).pow _)
simp only [one_pow, one_mul, ENNReal.ofReal_one] at A
refine le_of_tendsto A ?_
refine mem_nhdsWithin_Iio_iff_exists_Ioo_subset.2 ⟨(0 : ℝ), by simp, fun r hr => ?_⟩
dsimp
rw [← addHaar_closedBall' μ (0 : E) hr.1.le]
exact measure_mono (closedBall_subset_ball hr.2)
#align measure_theory.measure.add_haar_closed_unit_ball_eq_add_haar_unit_ball MeasureTheory.Measure.addHaar_closed_unit_ball_eq_addHaar_unit_ball
theorem addHaar_closedBall (x : E) {r : ℝ} (hr : 0 ≤ r) :
μ (closedBall x r) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 1) := by
rw [addHaar_closedBall' μ x hr, addHaar_closed_unit_ball_eq_addHaar_unit_ball]
#align measure_theory.measure.add_haar_closed_ball MeasureTheory.Measure.addHaar_closedBall
| Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean | 522 | 527 | theorem addHaar_closedBall_eq_addHaar_ball [Nontrivial E] (x : E) (r : ℝ) :
μ (closedBall x r) = μ (ball x r) := by |
by_cases h : r < 0
· rw [Metric.closedBall_eq_empty.mpr h, Metric.ball_eq_empty.mpr h.le]
push_neg at h
rw [addHaar_closedBall μ x h, addHaar_ball μ x h]
|
/-
Copyright (c) 2021 Benjamin Davidson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Benjamin Davidson
-/
import Mathlib.Algebra.Field.Opposite
import Mathlib.Algebra.Group.Subgroup.ZPowers
import Mathlib.Algebra.Group.Submonoid.Membership
import Mathlib.Algebra.Ring.NegOnePow
import Mathlib.Algebra.Order.Archimedean
import Mathlib.GroupTheory.Coset
#align_import algebra.periodic from "leanprover-community/mathlib"@"30413fc89f202a090a54d78e540963ed3de0056e"
/-!
# Periodicity
In this file we define and then prove facts about periodic and antiperiodic functions.
## Main definitions
* `Function.Periodic`: A function `f` is *periodic* if `∀ x, f (x + c) = f x`.
`f` is referred to as periodic with period `c` or `c`-periodic.
* `Function.Antiperiodic`: A function `f` is *antiperiodic* if `∀ x, f (x + c) = -f x`.
`f` is referred to as antiperiodic with antiperiod `c` or `c`-antiperiodic.
Note that any `c`-antiperiodic function will necessarily also be `2 • c`-periodic.
## Tags
period, periodic, periodicity, antiperiodic
-/
variable {α β γ : Type*} {f g : α → β} {c c₁ c₂ x : α}
open Set
namespace Function
/-! ### Periodicity -/
/-- A function `f` is said to be `Periodic` with period `c` if for all `x`, `f (x + c) = f x`. -/
@[simp]
def Periodic [Add α] (f : α → β) (c : α) : Prop :=
∀ x : α, f (x + c) = f x
#align function.periodic Function.Periodic
protected theorem Periodic.funext [Add α] (h : Periodic f c) : (fun x => f (x + c)) = f :=
funext h
#align function.periodic.funext Function.Periodic.funext
protected theorem Periodic.comp [Add α] (h : Periodic f c) (g : β → γ) : Periodic (g ∘ f) c := by
simp_all
#align function.periodic.comp Function.Periodic.comp
theorem Periodic.comp_addHom [Add α] [Add γ] (h : Periodic f c) (g : AddHom γ α) (g_inv : α → γ)
(hg : RightInverse g_inv g) : Periodic (f ∘ g) (g_inv c) := fun x => by
simp only [hg c, h (g x), map_add, comp_apply]
#align function.periodic.comp_add_hom Function.Periodic.comp_addHom
@[to_additive]
protected theorem Periodic.mul [Add α] [Mul β] (hf : Periodic f c) (hg : Periodic g c) :
Periodic (f * g) c := by simp_all
#align function.periodic.mul Function.Periodic.mul
#align function.periodic.add Function.Periodic.add
@[to_additive]
protected theorem Periodic.div [Add α] [Div β] (hf : Periodic f c) (hg : Periodic g c) :
Periodic (f / g) c := by simp_all
#align function.periodic.div Function.Periodic.div
#align function.periodic.sub Function.Periodic.sub
@[to_additive]
theorem _root_.List.periodic_prod [Add α] [Monoid β] (l : List (α → β))
(hl : ∀ f ∈ l, Periodic f c) : Periodic l.prod c := by
induction' l with g l ih hl
· simp
· rw [List.forall_mem_cons] at hl
simpa only [List.prod_cons] using hl.1.mul (ih hl.2)
#align list.periodic_prod List.periodic_prod
#align list.periodic_sum List.periodic_sum
@[to_additive]
theorem _root_.Multiset.periodic_prod [Add α] [CommMonoid β] (s : Multiset (α → β))
(hs : ∀ f ∈ s, Periodic f c) : Periodic s.prod c :=
(s.prod_toList ▸ s.toList.periodic_prod) fun f hf => hs f <| Multiset.mem_toList.mp hf
#align multiset.periodic_prod Multiset.periodic_prod
#align multiset.periodic_sum Multiset.periodic_sum
@[to_additive]
theorem _root_.Finset.periodic_prod [Add α] [CommMonoid β] {ι : Type*} {f : ι → α → β}
(s : Finset ι) (hs : ∀ i ∈ s, Periodic (f i) c) : Periodic (∏ i ∈ s, f i) c :=
s.prod_to_list f ▸ (s.toList.map f).periodic_prod (by simpa [-Periodic] )
#align finset.periodic_prod Finset.periodic_prod
#align finset.periodic_sum Finset.periodic_sum
@[to_additive]
protected theorem Periodic.smul [Add α] [SMul γ β] (h : Periodic f c) (a : γ) :
Periodic (a • f) c := by simp_all
#align function.periodic.smul Function.Periodic.smul
#align function.periodic.vadd Function.Periodic.vadd
protected theorem Periodic.const_smul [AddMonoid α] [Group γ] [DistribMulAction γ α]
(h : Periodic f c) (a : γ) : Periodic (fun x => f (a • x)) (a⁻¹ • c) := fun x => by
simpa only [smul_add, smul_inv_smul] using h (a • x)
#align function.periodic.const_smul Function.Periodic.const_smul
protected theorem Periodic.const_smul₀ [AddCommMonoid α] [DivisionSemiring γ] [Module γ α]
(h : Periodic f c) (a : γ) : Periodic (fun x => f (a • x)) (a⁻¹ • c) := fun x => by
by_cases ha : a = 0
· simp only [ha, zero_smul]
· simpa only [smul_add, smul_inv_smul₀ ha] using h (a • x)
#align function.periodic.const_smul₀ Function.Periodic.const_smul₀
protected theorem Periodic.const_mul [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (a * x)) (a⁻¹ * c) :=
Periodic.const_smul₀ h a
#align function.periodic.const_mul Function.Periodic.const_mul
theorem Periodic.const_inv_smul [AddMonoid α] [Group γ] [DistribMulAction γ α] (h : Periodic f c)
(a : γ) : Periodic (fun x => f (a⁻¹ • x)) (a • c) := by
simpa only [inv_inv] using h.const_smul a⁻¹
#align function.periodic.const_inv_smul Function.Periodic.const_inv_smul
theorem Periodic.const_inv_smul₀ [AddCommMonoid α] [DivisionSemiring γ] [Module γ α]
(h : Periodic f c) (a : γ) : Periodic (fun x => f (a⁻¹ • x)) (a • c) := by
simpa only [inv_inv] using h.const_smul₀ a⁻¹
#align function.periodic.const_inv_smul₀ Function.Periodic.const_inv_smul₀
theorem Periodic.const_inv_mul [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (a⁻¹ * x)) (a * c) :=
h.const_inv_smul₀ a
#align function.periodic.const_inv_mul Function.Periodic.const_inv_mul
theorem Periodic.mul_const [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x * a)) (c * a⁻¹) :=
h.const_smul₀ (MulOpposite.op a)
#align function.periodic.mul_const Function.Periodic.mul_const
theorem Periodic.mul_const' [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x * a)) (c / a) := by simpa only [div_eq_mul_inv] using h.mul_const a
#align function.periodic.mul_const' Function.Periodic.mul_const'
theorem Periodic.mul_const_inv [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x * a⁻¹)) (c * a) :=
h.const_inv_smul₀ (MulOpposite.op a)
#align function.periodic.mul_const_inv Function.Periodic.mul_const_inv
theorem Periodic.div_const [DivisionSemiring α] (h : Periodic f c) (a : α) :
Periodic (fun x => f (x / a)) (c * a) := by simpa only [div_eq_mul_inv] using h.mul_const_inv a
#align function.periodic.div_const Function.Periodic.div_const
| Mathlib/Algebra/Periodic.lean | 156 | 157 | theorem Periodic.add_period [AddSemigroup α] (h1 : Periodic f c₁) (h2 : Periodic f c₂) :
Periodic f (c₁ + c₂) := by | simp_all [← add_assoc]
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Order.Filter.Bases
import Mathlib.Order.ConditionallyCompleteLattice.Basic
#align_import order.filter.lift from "leanprover-community/mathlib"@"8631e2d5ea77f6c13054d9151d82b83069680cb1"
/-!
# Lift filters along filter and set functions
-/
open Set Classical Filter Function
namespace Filter
variable {α β γ : Type*} {ι : Sort*}
section lift
/-- A variant on `bind` using a function `g` taking a set instead of a member of `α`.
This is essentially a push-forward along a function mapping each set to a filter. -/
protected def lift (f : Filter α) (g : Set α → Filter β) :=
⨅ s ∈ f, g s
#align filter.lift Filter.lift
variable {f f₁ f₂ : Filter α} {g g₁ g₂ : Set α → Filter β}
@[simp]
theorem lift_top (g : Set α → Filter β) : (⊤ : Filter α).lift g = g univ := by simp [Filter.lift]
#align filter.lift_top Filter.lift_top
-- Porting note: use `∃ i, p i ∧ _` instead of `∃ i (hi : p i), _`
/-- If `(p : ι → Prop, s : ι → Set α)` is a basis of a filter `f`, `g` is a monotone function
`Set α → Filter γ`, and for each `i`, `(pg : β i → Prop, sg : β i → Set α)` is a basis
of the filter `g (s i)`, then
`(fun (i : ι) (x : β i) ↦ p i ∧ pg i x, fun (i : ι) (x : β i) ↦ sg i x)` is a basis
of the filter `f.lift g`.
This basis is parametrized by `i : ι` and `x : β i`, so in order to formulate this fact using
`Filter.HasBasis` one has to use `Σ i, β i` as the index type, see `Filter.HasBasis.lift`.
This lemma states the corresponding `mem_iff` statement without using a sigma type. -/
theorem HasBasis.mem_lift_iff {ι} {p : ι → Prop} {s : ι → Set α} {f : Filter α}
(hf : f.HasBasis p s) {β : ι → Type*} {pg : ∀ i, β i → Prop} {sg : ∀ i, β i → Set γ}
{g : Set α → Filter γ} (hg : ∀ i, (g <| s i).HasBasis (pg i) (sg i)) (gm : Monotone g)
{s : Set γ} : s ∈ f.lift g ↔ ∃ i, p i ∧ ∃ x, pg i x ∧ sg i x ⊆ s := by
refine (mem_biInf_of_directed ?_ ⟨univ, univ_sets _⟩).trans ?_
· intro t₁ ht₁ t₂ ht₂
exact ⟨t₁ ∩ t₂, inter_mem ht₁ ht₂, gm inter_subset_left, gm inter_subset_right⟩
· simp only [← (hg _).mem_iff]
exact hf.exists_iff fun t₁ t₂ ht H => gm ht H
#align filter.has_basis.mem_lift_iff Filter.HasBasis.mem_lift_iffₓ
/-- If `(p : ι → Prop, s : ι → Set α)` is a basis of a filter `f`, `g` is a monotone function
`Set α → Filter γ`, and for each `i`, `(pg : β i → Prop, sg : β i → Set α)` is a basis
of the filter `g (s i)`, then
`(fun (i : ι) (x : β i) ↦ p i ∧ pg i x, fun (i : ι) (x : β i) ↦ sg i x)`
is a basis of the filter `f.lift g`.
This basis is parametrized by `i : ι` and `x : β i`, so in order to formulate this fact using
`has_basis` one has to use `Σ i, β i` as the index type. See also `Filter.HasBasis.mem_lift_iff`
for the corresponding `mem_iff` statement formulated without using a sigma type. -/
theorem HasBasis.lift {ι} {p : ι → Prop} {s : ι → Set α} {f : Filter α} (hf : f.HasBasis p s)
{β : ι → Type*} {pg : ∀ i, β i → Prop} {sg : ∀ i, β i → Set γ} {g : Set α → Filter γ}
(hg : ∀ i, (g (s i)).HasBasis (pg i) (sg i)) (gm : Monotone g) :
(f.lift g).HasBasis (fun i : Σi, β i => p i.1 ∧ pg i.1 i.2) fun i : Σi, β i => sg i.1 i.2 := by
refine ⟨fun t => (hf.mem_lift_iff hg gm).trans ?_⟩
simp [Sigma.exists, and_assoc, exists_and_left]
#align filter.has_basis.lift Filter.HasBasis.lift
theorem mem_lift_sets (hg : Monotone g) {s : Set β} : s ∈ f.lift g ↔ ∃ t ∈ f, s ∈ g t :=
(f.basis_sets.mem_lift_iff (fun s => (g s).basis_sets) hg).trans <| by
simp only [id, exists_mem_subset_iff]
#align filter.mem_lift_sets Filter.mem_lift_sets
theorem sInter_lift_sets (hg : Monotone g) :
⋂₀ { s | s ∈ f.lift g } = ⋂ s ∈ f, ⋂₀ { t | t ∈ g s } := by
simp only [sInter_eq_biInter, mem_setOf_eq, Filter.mem_sets, mem_lift_sets hg, iInter_exists,
iInter_and, @iInter_comm _ (Set β)]
#align filter.sInter_lift_sets Filter.sInter_lift_sets
theorem mem_lift {s : Set β} {t : Set α} (ht : t ∈ f) (hs : s ∈ g t) : s ∈ f.lift g :=
le_principal_iff.mp <|
show f.lift g ≤ 𝓟 s from iInf_le_of_le t <| iInf_le_of_le ht <| le_principal_iff.mpr hs
#align filter.mem_lift Filter.mem_lift
theorem lift_le {f : Filter α} {g : Set α → Filter β} {h : Filter β} {s : Set α} (hs : s ∈ f)
(hg : g s ≤ h) : f.lift g ≤ h :=
iInf₂_le_of_le s hs hg
#align filter.lift_le Filter.lift_le
theorem le_lift {f : Filter α} {g : Set α → Filter β} {h : Filter β} :
h ≤ f.lift g ↔ ∀ s ∈ f, h ≤ g s :=
le_iInf₂_iff
#align filter.le_lift Filter.le_lift
theorem lift_mono (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) : f₁.lift g₁ ≤ f₂.lift g₂ :=
iInf_mono fun s => iInf_mono' fun hs => ⟨hf hs, hg s⟩
#align filter.lift_mono Filter.lift_mono
theorem lift_mono' (hg : ∀ s ∈ f, g₁ s ≤ g₂ s) : f.lift g₁ ≤ f.lift g₂ := iInf₂_mono hg
#align filter.lift_mono' Filter.lift_mono'
theorem tendsto_lift {m : γ → β} {l : Filter γ} :
Tendsto m l (f.lift g) ↔ ∀ s ∈ f, Tendsto m l (g s) := by
simp only [Filter.lift, tendsto_iInf]
#align filter.tendsto_lift Filter.tendsto_lift
theorem map_lift_eq {m : β → γ} (hg : Monotone g) : map m (f.lift g) = f.lift (map m ∘ g) :=
have : Monotone (map m ∘ g) := map_mono.comp hg
Filter.ext fun s => by
simp only [mem_lift_sets hg, mem_lift_sets this, exists_prop, mem_map, Function.comp_apply]
#align filter.map_lift_eq Filter.map_lift_eq
theorem comap_lift_eq {m : γ → β} : comap m (f.lift g) = f.lift (comap m ∘ g) := by
simp only [Filter.lift, comap_iInf]; rfl
#align filter.comap_lift_eq Filter.comap_lift_eq
theorem comap_lift_eq2 {m : β → α} {g : Set β → Filter γ} (hg : Monotone g) :
(comap m f).lift g = f.lift (g ∘ preimage m) :=
le_antisymm (le_iInf₂ fun s hs => iInf₂_le (m ⁻¹' s) ⟨s, hs, Subset.rfl⟩)
(le_iInf₂ fun _s ⟨s', hs', h_sub⟩ => iInf₂_le_of_le s' hs' <| hg h_sub)
#align filter.comap_lift_eq2 Filter.comap_lift_eq2
theorem lift_map_le {g : Set β → Filter γ} {m : α → β} : (map m f).lift g ≤ f.lift (g ∘ image m) :=
le_lift.2 fun _s hs => lift_le (image_mem_map hs) le_rfl
#align filter.lift_map_le Filter.lift_map_le
theorem map_lift_eq2 {g : Set β → Filter γ} {m : α → β} (hg : Monotone g) :
(map m f).lift g = f.lift (g ∘ image m) :=
lift_map_le.antisymm <| le_lift.2 fun _s hs => lift_le hs <| hg <| image_preimage_subset _ _
#align filter.map_lift_eq2 Filter.map_lift_eq2
theorem lift_comm {g : Filter β} {h : Set α → Set β → Filter γ} :
(f.lift fun s => g.lift (h s)) = g.lift fun t => f.lift fun s => h s t :=
le_antisymm
(le_iInf fun i => le_iInf fun hi => le_iInf fun j => le_iInf fun hj =>
iInf_le_of_le j <| iInf_le_of_le hj <| iInf_le_of_le i <| iInf_le _ hi)
(le_iInf fun i => le_iInf fun hi => le_iInf fun j => le_iInf fun hj =>
iInf_le_of_le j <| iInf_le_of_le hj <| iInf_le_of_le i <| iInf_le _ hi)
#align filter.lift_comm Filter.lift_comm
theorem lift_assoc {h : Set β → Filter γ} (hg : Monotone g) :
(f.lift g).lift h = f.lift fun s => (g s).lift h :=
le_antisymm
(le_iInf₂ fun _s hs => le_iInf₂ fun t ht =>
iInf_le_of_le t <| iInf_le _ <| (mem_lift_sets hg).mpr ⟨_, hs, ht⟩)
(le_iInf₂ fun t ht =>
let ⟨s, hs, h'⟩ := (mem_lift_sets hg).mp ht
iInf_le_of_le s <| iInf_le_of_le hs <| iInf_le_of_le t <| iInf_le _ h')
#align filter.lift_assoc Filter.lift_assoc
theorem lift_lift_same_le_lift {g : Set α → Set α → Filter β} :
(f.lift fun s => f.lift (g s)) ≤ f.lift fun s => g s s :=
le_lift.2 fun _s hs => lift_le hs <| lift_le hs le_rfl
#align filter.lift_lift_same_le_lift Filter.lift_lift_same_le_lift
theorem lift_lift_same_eq_lift {g : Set α → Set α → Filter β} (hg₁ : ∀ s, Monotone fun t => g s t)
(hg₂ : ∀ t, Monotone fun s => g s t) : (f.lift fun s => f.lift (g s)) = f.lift fun s => g s s :=
lift_lift_same_le_lift.antisymm <|
le_lift.2 fun s hs => le_lift.2 fun t ht => lift_le (inter_mem hs ht) <|
calc
g (s ∩ t) (s ∩ t) ≤ g s (s ∩ t) := hg₂ (s ∩ t) inter_subset_left
_ ≤ g s t := hg₁ s inter_subset_right
#align filter.lift_lift_same_eq_lift Filter.lift_lift_same_eq_lift
theorem lift_principal {s : Set α} (hg : Monotone g) : (𝓟 s).lift g = g s :=
(lift_le (mem_principal_self _) le_rfl).antisymm (le_lift.2 fun _t ht => hg ht)
#align filter.lift_principal Filter.lift_principal
theorem monotone_lift [Preorder γ] {f : γ → Filter α} {g : γ → Set α → Filter β} (hf : Monotone f)
(hg : Monotone g) : Monotone fun c => (f c).lift (g c) := fun _ _ h => lift_mono (hf h) (hg h)
#align filter.monotone_lift Filter.monotone_lift
theorem lift_neBot_iff (hm : Monotone g) : (NeBot (f.lift g)) ↔ ∀ s ∈ f, NeBot (g s) := by
simp only [neBot_iff, Ne, ← empty_mem_iff_bot, mem_lift_sets hm, not_exists, not_and]
#align filter.lift_ne_bot_iff Filter.lift_neBot_iff
@[simp]
theorem lift_const {f : Filter α} {g : Filter β} : (f.lift fun _ => g) = g :=
iInf_subtype'.trans iInf_const
#align filter.lift_const Filter.lift_const
@[simp]
theorem lift_inf {f : Filter α} {g h : Set α → Filter β} :
(f.lift fun x => g x ⊓ h x) = f.lift g ⊓ f.lift h := by simp only [Filter.lift, iInf_inf_eq]
#align filter.lift_inf Filter.lift_inf
@[simp]
theorem lift_principal2 {f : Filter α} : f.lift 𝓟 = f :=
le_antisymm (fun s hs => mem_lift hs (mem_principal_self s))
(le_iInf fun s => le_iInf fun hs => by simp only [hs, le_principal_iff])
#align filter.lift_principal2 Filter.lift_principal2
theorem lift_iInf_le {f : ι → Filter α} {g : Set α → Filter β} :
(iInf f).lift g ≤ ⨅ i, (f i).lift g :=
le_iInf fun _ => lift_mono (iInf_le _ _) le_rfl
#align filter.lift_infi_le Filter.lift_iInf_le
theorem lift_iInf [Nonempty ι] {f : ι → Filter α} {g : Set α → Filter β}
(hg : ∀ s t, g (s ∩ t) = g s ⊓ g t) : (iInf f).lift g = ⨅ i, (f i).lift g := by
refine lift_iInf_le.antisymm fun s => ?_
have H : ∀ t ∈ iInf f, ⨅ i, (f i).lift g ≤ g t := by
intro t ht
refine iInf_sets_induct ht ?_ fun hs ht => ?_
· inhabit ι
exact iInf₂_le_of_le default univ (iInf_le _ univ_mem)
· rw [hg]
exact le_inf (iInf₂_le_of_le _ _ <| iInf_le _ hs) ht
simp only [mem_lift_sets (Monotone.of_map_inf hg), exists_imp, and_imp]
exact fun t ht hs => H t ht hs
#align filter.lift_infi Filter.lift_iInf
theorem lift_iInf_of_directed [Nonempty ι] {f : ι → Filter α} {g : Set α → Filter β}
(hf : Directed (· ≥ ·) f) (hg : Monotone g) : (iInf f).lift g = ⨅ i, (f i).lift g :=
lift_iInf_le.antisymm fun s => by
simp only [mem_lift_sets hg, exists_imp, and_imp, mem_iInf_of_directed hf]
exact fun t i ht hs => mem_iInf_of_mem i <| mem_lift ht hs
#align filter.lift_infi_of_directed Filter.lift_iInf_of_directed
theorem lift_iInf_of_map_univ {f : ι → Filter α} {g : Set α → Filter β}
(hg : ∀ s t, g (s ∩ t) = g s ⊓ g t) (hg' : g univ = ⊤) :
(iInf f).lift g = ⨅ i, (f i).lift g := by
cases isEmpty_or_nonempty ι
· simp [iInf_of_empty, hg']
· exact lift_iInf hg
#align filter.lift_infi_of_map_univ Filter.lift_iInf_of_map_univ
end lift
section Lift'
/-- Specialize `lift` to functions `Set α → Set β`. This can be viewed as a generalization of `map`.
This is essentially a push-forward along a function mapping each set to a set. -/
protected def lift' (f : Filter α) (h : Set α → Set β) :=
f.lift (𝓟 ∘ h)
#align filter.lift' Filter.lift'
variable {f f₁ f₂ : Filter α} {h h₁ h₂ : Set α → Set β}
@[simp]
theorem lift'_top (h : Set α → Set β) : (⊤ : Filter α).lift' h = 𝓟 (h univ) :=
lift_top _
#align filter.lift'_top Filter.lift'_top
theorem mem_lift' {t : Set α} (ht : t ∈ f) : h t ∈ f.lift' h :=
le_principal_iff.mp <| show f.lift' h ≤ 𝓟 (h t) from iInf_le_of_le t <| iInf_le_of_le ht <| le_rfl
#align filter.mem_lift' Filter.mem_lift'
theorem tendsto_lift' {m : γ → β} {l : Filter γ} :
Tendsto m l (f.lift' h) ↔ ∀ s ∈ f, ∀ᶠ a in l, m a ∈ h s := by
simp only [Filter.lift', tendsto_lift, tendsto_principal, comp]
#align filter.tendsto_lift' Filter.tendsto_lift'
theorem HasBasis.lift' {ι} {p : ι → Prop} {s} (hf : f.HasBasis p s) (hh : Monotone h) :
(f.lift' h).HasBasis p (h ∘ s) :=
⟨fun t => (hf.mem_lift_iff (fun i => hasBasis_principal (h (s i)))
(monotone_principal.comp hh)).trans <| by simp only [exists_const, true_and, comp]⟩
#align filter.has_basis.lift' Filter.HasBasis.lift'
theorem mem_lift'_sets (hh : Monotone h) {s : Set β} : s ∈ f.lift' h ↔ ∃ t ∈ f, h t ⊆ s :=
mem_lift_sets <| monotone_principal.comp hh
#align filter.mem_lift'_sets Filter.mem_lift'_sets
theorem eventually_lift'_iff (hh : Monotone h) {p : β → Prop} :
(∀ᶠ y in f.lift' h, p y) ↔ ∃ t ∈ f, ∀ y ∈ h t, p y :=
mem_lift'_sets hh
#align filter.eventually_lift'_iff Filter.eventually_lift'_iff
theorem sInter_lift'_sets (hh : Monotone h) : ⋂₀ { s | s ∈ f.lift' h } = ⋂ s ∈ f, h s :=
(sInter_lift_sets (monotone_principal.comp hh)).trans <| iInter₂_congr fun _ _ => csInf_Ici
#align filter.sInter_lift'_sets Filter.sInter_lift'_sets
theorem lift'_le {f : Filter α} {g : Set α → Set β} {h : Filter β} {s : Set α} (hs : s ∈ f)
(hg : 𝓟 (g s) ≤ h) : f.lift' g ≤ h :=
lift_le hs hg
#align filter.lift'_le Filter.lift'_le
theorem lift'_mono (hf : f₁ ≤ f₂) (hh : h₁ ≤ h₂) : f₁.lift' h₁ ≤ f₂.lift' h₂ :=
lift_mono hf fun s => principal_mono.mpr <| hh s
#align filter.lift'_mono Filter.lift'_mono
theorem lift'_mono' (hh : ∀ s ∈ f, h₁ s ⊆ h₂ s) : f.lift' h₁ ≤ f.lift' h₂ :=
iInf₂_mono fun s hs => principal_mono.mpr <| hh s hs
#align filter.lift'_mono' Filter.lift'_mono'
theorem lift'_cong (hh : ∀ s ∈ f, h₁ s = h₂ s) : f.lift' h₁ = f.lift' h₂ :=
le_antisymm (lift'_mono' fun s hs => le_of_eq <| hh s hs)
(lift'_mono' fun s hs => le_of_eq <| (hh s hs).symm)
#align filter.lift'_cong Filter.lift'_cong
theorem map_lift'_eq {m : β → γ} (hh : Monotone h) : map m (f.lift' h) = f.lift' (image m ∘ h) :=
calc
map m (f.lift' h) = f.lift (map m ∘ 𝓟 ∘ h) := map_lift_eq <| monotone_principal.comp hh
_ = f.lift' (image m ∘ h) := by simp only [comp, Filter.lift', map_principal]
#align filter.map_lift'_eq Filter.map_lift'_eq
theorem lift'_map_le {g : Set β → Set γ} {m : α → β} : (map m f).lift' g ≤ f.lift' (g ∘ image m) :=
lift_map_le
#align filter.lift'_map_le Filter.lift'_map_le
theorem map_lift'_eq2 {g : Set β → Set γ} {m : α → β} (hg : Monotone g) :
(map m f).lift' g = f.lift' (g ∘ image m) :=
map_lift_eq2 <| monotone_principal.comp hg
#align filter.map_lift'_eq2 Filter.map_lift'_eq2
theorem comap_lift'_eq {m : γ → β} : comap m (f.lift' h) = f.lift' (preimage m ∘ h) := by
simp only [Filter.lift', comap_lift_eq, (· ∘ ·), comap_principal]
#align filter.comap_lift'_eq Filter.comap_lift'_eq
theorem comap_lift'_eq2 {m : β → α} {g : Set β → Set γ} (hg : Monotone g) :
(comap m f).lift' g = f.lift' (g ∘ preimage m) :=
comap_lift_eq2 <| monotone_principal.comp hg
#align filter.comap_lift'_eq2 Filter.comap_lift'_eq2
theorem lift'_principal {s : Set α} (hh : Monotone h) : (𝓟 s).lift' h = 𝓟 (h s) :=
lift_principal <| monotone_principal.comp hh
#align filter.lift'_principal Filter.lift'_principal
| Mathlib/Order/Filter/Lift.lean | 322 | 323 | theorem lift'_pure {a : α} (hh : Monotone h) : (pure a : Filter α).lift' h = 𝓟 (h {a}) := by |
rw [← principal_singleton, lift'_principal hh]
|
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Yuyang Zhao
-/
import Mathlib.Algebra.GroupWithZero.Defs
import Mathlib.Algebra.Order.Monoid.Unbundled.Defs
import Mathlib.Tactic.GCongr.Core
#align_import algebra.order.ring.lemmas from "leanprover-community/mathlib"@"44e29dbcff83ba7114a464d592b8c3743987c1e5"
/-!
# Monotonicity of multiplication by positive elements
This file defines typeclasses to reason about monotonicity of the operations
* `b ↦ a * b`, "left multiplication"
* `a ↦ a * b`, "right multiplication"
We use eight typeclasses to encode the various properties we care about for those two operations.
These typeclasses are meant to be mostly internal to this file, to set up each lemma in the
appropriate generality.
Less granular typeclasses like `OrderedAddCommMonoid`, `LinearOrderedField` should be enough for
most purposes, and the system is set up so that they imply the correct granular typeclasses here.
If those are enough for you, you may stop reading here! Else, beware that what follows is a bit
technical.
## Definitions
In all that follows, `α` is an orders which has a `0` and a multiplication. Note however that we do
not use lawfulness of this action in most of the file. Hence `*` should be considered here as a
mostly arbitrary function `α → α → α`.
We use the following four typeclasses to reason about left multiplication (`b ↦ a * b`):
* `PosMulMono`: If `a ≥ 0`, then `b₁ ≤ b₂ → a * b₁ ≤ a * b₂`.
* `PosMulStrictMono`: If `a > 0`, then `b₁ < b₂ → a * b₁ < a * b₂`.
* `PosMulReflectLT`: If `a ≥ 0`, then `a * b₁ < a * b₂ → b₁ < b₂`.
* `PosMulReflectLE`: If `a > 0`, then `a * b₁ ≤ a * b₂ → b₁ ≤ b₂`.
We use the following four typeclasses to reason about right multiplication (`a ↦ a * b`):
* `MulPosMono`: If `b ≥ 0`, then `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b`.
* `MulPosStrictMono`: If `b > 0`, then `a₁ < a₂ → a₁ * b < a₂ * b`.
* `MulPosReflectLT`: If `b ≥ 0`, then `a₁ * b < a₂ * b → a₁ < a₂`.
* `MulPosReflectLE`: If `b > 0`, then `a₁ * b ≤ a₂ * b → a₁ ≤ a₂`.
## Implications
As `α` gets more and more structure, those typeclasses end up being equivalent. The commonly used
implications are:
* When `α` is a partial order:
* `PosMulStrictMono → PosMulMono`
* `MulPosStrictMono → MulPosMono`
* `PosMulReflectLE → PosMulReflectLT`
* `MulPosReflectLE → MulPosReflectLT`
* When `α` is a linear order:
* `PosMulStrictMono → PosMulReflectLE`
* `MulPosStrictMono → MulPosReflectLE` .
* When the multiplication of `α` is commutative:
* `PosMulMono → MulPosMono`
* `PosMulStrictMono → MulPosStrictMono`
* `PosMulReflectLE → MulPosReflectLE`
* `PosMulReflectLT → MulPosReflectLT`
Further, the bundled non-granular typeclasses imply the granular ones like so:
* `OrderedSemiring → PosMulMono`
* `OrderedSemiring → MulPosMono`
* `StrictOrderedSemiring → PosMulStrictMono`
* `StrictOrderedSemiring → MulPosStrictMono`
All these are registered as instances, which means that in practice you should not worry about these
implications. However, if you encounter a case where you think a statement is true but not covered
by the current implications, please bring it up on Zulip!
## Notation
The following is local notation in this file:
* `α≥0`: `{x : α // 0 ≤ x}`
* `α>0`: `{x : α // 0 < x}`
See https://leanprover.zulipchat.com/#narrow/stream/113488-general/topic/notation.20for.20positive.20elements
for a discussion about this notation, and whether to enable it globally (note that the notation is
currently global but broken, hence actually only works locally).
-/
variable (α : Type*)
set_option quotPrecheck false in
/-- Local notation for the nonnegative elements of a type `α`. TODO: actually make local. -/
notation "α≥0" => { x : α // 0 ≤ x }
set_option quotPrecheck false in
/-- Local notation for the positive elements of a type `α`. TODO: actually make local. -/
notation "α>0" => { x : α // 0 < x }
section Abbreviations
variable [Mul α] [Zero α] [Preorder α]
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the left,
namely `b₁ ≤ b₂ → a * b₁ ≤ a * b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev PosMulMono : Prop :=
CovariantClass α≥0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono PosMulMono
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the right,
namely `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev MulPosMono : Prop :=
CovariantClass α≥0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono MulPosMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the left,
namely `b₁ < b₂ → a * b₁ < a * b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev PosMulStrictMono : Prop :=
CovariantClass α>0 α (fun x y => x * y) (· < ·)
#align pos_mul_strict_mono PosMulStrictMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the right,
namely `a₁ < a₂ → a₁ * b < a₂ * b` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev MulPosStrictMono : Prop :=
CovariantClass α>0 α (fun x y => y * x) (· < ·)
#align mul_pos_strict_mono MulPosStrictMono
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the left, namely `a * b₁ < a * b₂ → b₁ < b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => x * y) (· < ·)
#align pos_mul_reflect_lt PosMulReflectLT
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the right, namely `a₁ * b < a₂ * b → a₁ < a₂` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => y * x) (· < ·)
#align mul_pos_reflect_lt MulPosReflectLT
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the left,
namely `a * b₁ ≤ a * b₂ → b₁ ≤ b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono_rev PosMulReflectLE
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the right,
namely `a₁ * b ≤ a₂ * b → a₁ ≤ a₂` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono_rev MulPosReflectLE
end Abbreviations
variable {α} {a b c d : α}
section MulZero
variable [Mul α] [Zero α]
section Preorder
variable [Preorder α]
instance PosMulMono.to_covariantClass_pos_mul_le [PosMulMono α] :
CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_mono.to_covariant_class_pos_mul_le PosMulMono.to_covariantClass_pos_mul_le
instance MulPosMono.to_covariantClass_pos_mul_le [MulPosMono α] :
CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_mono.to_covariant_class_pos_mul_le MulPosMono.to_covariantClass_pos_mul_le
instance PosMulReflectLT.to_contravariantClass_pos_mul_lt [PosMulReflectLT α] :
ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_reflect_lt.to_contravariant_class_pos_mul_lt PosMulReflectLT.to_contravariantClass_pos_mul_lt
instance MulPosReflectLT.to_contravariantClass_pos_mul_lt [MulPosReflectLT α] :
ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_reflect_lt.to_contravariant_class_pos_mul_lt MulPosReflectLT.to_contravariantClass_pos_mul_lt
@[gcongr]
theorem mul_le_mul_of_nonneg_left [PosMulMono α] (h : b ≤ c) (a0 : 0 ≤ a) : a * b ≤ a * c :=
@CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_left mul_le_mul_of_nonneg_left
@[gcongr]
theorem mul_le_mul_of_nonneg_right [MulPosMono α] (h : b ≤ c) (a0 : 0 ≤ a) : b * a ≤ c * a :=
@CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_right mul_le_mul_of_nonneg_right
@[gcongr]
theorem mul_lt_mul_of_pos_left [PosMulStrictMono α] (bc : b < c) (a0 : 0 < a) : a * b < a * c :=
@CovariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_left mul_lt_mul_of_pos_left
@[gcongr]
theorem mul_lt_mul_of_pos_right [MulPosStrictMono α] (bc : b < c) (a0 : 0 < a) : b * a < c * a :=
@CovariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_right mul_lt_mul_of_pos_right
theorem lt_of_mul_lt_mul_left [PosMulReflectLT α] (h : a * b < a * c) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_left lt_of_mul_lt_mul_left
theorem lt_of_mul_lt_mul_right [MulPosReflectLT α] (h : b * a < c * a) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_right lt_of_mul_lt_mul_right
theorem le_of_mul_le_mul_left [PosMulReflectLE α] (bc : a * b ≤ a * c) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_left le_of_mul_le_mul_left
theorem le_of_mul_le_mul_right [MulPosReflectLE α] (bc : b * a ≤ c * a) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_right le_of_mul_le_mul_right
alias lt_of_mul_lt_mul_of_nonneg_left := lt_of_mul_lt_mul_left
#align lt_of_mul_lt_mul_of_nonneg_left lt_of_mul_lt_mul_of_nonneg_left
alias lt_of_mul_lt_mul_of_nonneg_right := lt_of_mul_lt_mul_right
#align lt_of_mul_lt_mul_of_nonneg_right lt_of_mul_lt_mul_of_nonneg_right
alias le_of_mul_le_mul_of_pos_left := le_of_mul_le_mul_left
#align le_of_mul_le_mul_of_pos_left le_of_mul_le_mul_of_pos_left
alias le_of_mul_le_mul_of_pos_right := le_of_mul_le_mul_right
#align le_of_mul_le_mul_of_pos_right le_of_mul_le_mul_of_pos_right
@[simp]
theorem mul_lt_mul_left [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a * b < a * c ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_left mul_lt_mul_left
@[simp]
theorem mul_lt_mul_right [MulPosStrictMono α] [MulPosReflectLT α] (a0 : 0 < a) :
b * a < c * a ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_right mul_lt_mul_right
@[simp]
theorem mul_le_mul_left [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_left mul_le_mul_left
@[simp]
theorem mul_le_mul_right [MulPosMono α] [MulPosReflectLE α] (a0 : 0 < a) : b * a ≤ c * a ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_right mul_le_mul_right
alias mul_le_mul_iff_of_pos_left := mul_le_mul_left
alias mul_le_mul_iff_of_pos_right := mul_le_mul_right
alias mul_lt_mul_iff_of_pos_left := mul_lt_mul_left
alias mul_lt_mul_iff_of_pos_right := mul_lt_mul_right
theorem mul_lt_mul_of_pos_of_nonneg [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 ≤ d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans_le (mul_le_mul_of_nonneg_right h₁ d0)
#align mul_lt_mul_of_pos_of_nonneg mul_lt_mul_of_pos_of_nonneg
theorem mul_lt_mul_of_le_of_le' [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 ≤ c) : a * c < b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans_lt (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_le_of_le' mul_lt_mul_of_le_of_le'
theorem mul_lt_mul_of_nonneg_of_pos [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(a0 : 0 ≤ a) (d0 : 0 < d) : a * c < b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans_lt (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_nonneg_of_pos mul_lt_mul_of_nonneg_of_pos
theorem mul_lt_mul_of_le_of_lt' [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(b0 : 0 ≤ b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans_le (mul_le_mul_of_nonneg_left h₂ b0)
#align mul_lt_mul_of_le_of_lt' mul_lt_mul_of_le_of_lt'
theorem mul_lt_mul_of_pos_of_pos [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 < d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_pos_of_pos mul_lt_mul_of_pos_of_pos
theorem mul_lt_mul_of_lt_of_lt' [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_lt_of_lt' mul_lt_mul_of_lt_of_lt'
theorem mul_lt_of_mul_lt_of_nonneg_left [PosMulMono α] (h : a * b < c) (hdb : d ≤ b) (ha : 0 ≤ a) :
a * d < c :=
(mul_le_mul_of_nonneg_left hdb ha).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_left mul_lt_of_mul_lt_of_nonneg_left
theorem lt_mul_of_lt_mul_of_nonneg_left [PosMulMono α] (h : a < b * c) (hcd : c ≤ d) (hb : 0 ≤ b) :
a < b * d :=
h.trans_le <| mul_le_mul_of_nonneg_left hcd hb
#align lt_mul_of_lt_mul_of_nonneg_left lt_mul_of_lt_mul_of_nonneg_left
theorem mul_lt_of_mul_lt_of_nonneg_right [MulPosMono α] (h : a * b < c) (hda : d ≤ a) (hb : 0 ≤ b) :
d * b < c :=
(mul_le_mul_of_nonneg_right hda hb).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_right mul_lt_of_mul_lt_of_nonneg_right
theorem lt_mul_of_lt_mul_of_nonneg_right [MulPosMono α] (h : a < b * c) (hbd : b ≤ d) (hc : 0 ≤ c) :
a < d * c :=
h.trans_le <| mul_le_mul_of_nonneg_right hbd hc
#align lt_mul_of_lt_mul_of_nonneg_right lt_mul_of_lt_mul_of_nonneg_right
end Preorder
section LinearOrder
variable [LinearOrder α]
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulReflectLE [PosMulStrictMono α] :
PosMulReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosReflectLE [MulPosStrictMono α] :
MulPosReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
theorem PosMulReflectLE.toPosMulStrictMono [PosMulReflectLE α] : PosMulStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_mono_rev.to_pos_mul_strict_mono PosMulReflectLE.toPosMulStrictMono
theorem MulPosReflectLE.toMulPosStrictMono [MulPosReflectLE α] : MulPosStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_mono_rev.to_mul_pos_strict_mono MulPosReflectLE.toMulPosStrictMono
theorem posMulStrictMono_iff_posMulReflectLE : PosMulStrictMono α ↔ PosMulReflectLE α :=
⟨@PosMulStrictMono.toPosMulReflectLE _ _ _ _, @PosMulReflectLE.toPosMulStrictMono _ _ _ _⟩
#align pos_mul_strict_mono_iff_pos_mul_mono_rev posMulStrictMono_iff_posMulReflectLE
theorem mulPosStrictMono_iff_mulPosReflectLE : MulPosStrictMono α ↔ MulPosReflectLE α :=
⟨@MulPosStrictMono.toMulPosReflectLE _ _ _ _, @MulPosReflectLE.toMulPosStrictMono _ _ _ _⟩
#align mul_pos_strict_mono_iff_mul_pos_mono_rev mulPosStrictMono_iff_mulPosReflectLE
theorem PosMulReflectLT.toPosMulMono [PosMulReflectLT α] : PosMulMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_reflect_lt.to_pos_mul_mono PosMulReflectLT.toPosMulMono
theorem MulPosReflectLT.toMulPosMono [MulPosReflectLT α] : MulPosMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_reflect_lt.to_mul_pos_mono MulPosReflectLT.toMulPosMono
theorem PosMulMono.toPosMulReflectLT [PosMulMono α] : PosMulReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align pos_mul_mono.to_pos_mul_reflect_lt PosMulMono.toPosMulReflectLT
theorem MulPosMono.toMulPosReflectLT [MulPosMono α] : MulPosReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align mul_pos_mono.to_mul_pos_reflect_lt MulPosMono.toMulPosReflectLT
/- TODO: Currently, only one in four of the above are made instances; we could consider making
both directions of `covariant_le_iff_contravariant_lt` and `covariant_lt_iff_contravariant_le`
instances, then all of the above become redundant instances, but there are performance issues. -/
theorem posMulMono_iff_posMulReflectLT : PosMulMono α ↔ PosMulReflectLT α :=
⟨@PosMulMono.toPosMulReflectLT _ _ _ _, @PosMulReflectLT.toPosMulMono _ _ _ _⟩
#align pos_mul_mono_iff_pos_mul_reflect_lt posMulMono_iff_posMulReflectLT
theorem mulPosMono_iff_mulPosReflectLT : MulPosMono α ↔ MulPosReflectLT α :=
⟨@MulPosMono.toMulPosReflectLT _ _ _ _, @MulPosReflectLT.toMulPosMono _ _ _ _⟩
#align mul_pos_mono_iff_mul_pos_reflect_lt mulPosMono_iff_mulPosReflectLT
end LinearOrder
end MulZero
section MulZeroClass
variable [MulZeroClass α]
section Preorder
variable [Preorder α]
/-- Assumes left covariance. -/
theorem Left.mul_pos [PosMulStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
#align left.mul_pos Left.mul_pos
alias mul_pos := Left.mul_pos
#align mul_pos mul_pos
theorem mul_neg_of_pos_of_neg [PosMulStrictMono α] (ha : 0 < a) (hb : b < 0) : a * b < 0 := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
#align mul_neg_of_pos_of_neg mul_neg_of_pos_of_neg
@[simp]
theorem mul_pos_iff_of_pos_left [PosMulStrictMono α] [PosMulReflectLT α] (h : 0 < a) :
0 < a * b ↔ 0 < b := by simpa using mul_lt_mul_left (b := 0) h
#align zero_lt_mul_left mul_pos_iff_of_pos_left
/-- Assumes right covariance. -/
theorem Right.mul_pos [MulPosStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by
simpa only [zero_mul] using mul_lt_mul_of_pos_right ha hb
#align right.mul_pos Right.mul_pos
theorem mul_neg_of_neg_of_pos [MulPosStrictMono α] (ha : a < 0) (hb : 0 < b) : a * b < 0 := by
simpa only [zero_mul] using mul_lt_mul_of_pos_right ha hb
#align mul_neg_of_neg_of_pos mul_neg_of_neg_of_pos
@[simp]
theorem mul_pos_iff_of_pos_right [MulPosStrictMono α] [MulPosReflectLT α] (h : 0 < b) :
0 < a * b ↔ 0 < a := by simpa using mul_lt_mul_right (b := 0) h
#align zero_lt_mul_right mul_pos_iff_of_pos_right
/-- Assumes left covariance. -/
theorem Left.mul_nonneg [PosMulMono α] (ha : 0 ≤ a) (hb : 0 ≤ b) : 0 ≤ a * b := by
simpa only [mul_zero] using mul_le_mul_of_nonneg_left hb ha
#align left.mul_nonneg Left.mul_nonneg
alias mul_nonneg := Left.mul_nonneg
#align mul_nonneg mul_nonneg
theorem mul_nonpos_of_nonneg_of_nonpos [PosMulMono α] (ha : 0 ≤ a) (hb : b ≤ 0) : a * b ≤ 0 := by
simpa only [mul_zero] using mul_le_mul_of_nonneg_left hb ha
#align mul_nonpos_of_nonneg_of_nonpos mul_nonpos_of_nonneg_of_nonpos
/-- Assumes right covariance. -/
theorem Right.mul_nonneg [MulPosMono α] (ha : 0 ≤ a) (hb : 0 ≤ b) : 0 ≤ a * b := by
simpa only [zero_mul] using mul_le_mul_of_nonneg_right ha hb
#align right.mul_nonneg Right.mul_nonneg
theorem mul_nonpos_of_nonpos_of_nonneg [MulPosMono α] (ha : a ≤ 0) (hb : 0 ≤ b) : a * b ≤ 0 := by
simpa only [zero_mul] using mul_le_mul_of_nonneg_right ha hb
#align mul_nonpos_of_nonpos_of_nonneg mul_nonpos_of_nonpos_of_nonneg
theorem pos_of_mul_pos_right [PosMulReflectLT α] (h : 0 < a * b) (ha : 0 ≤ a) : 0 < b :=
lt_of_mul_lt_mul_left ((mul_zero a).symm ▸ h : a * 0 < a * b) ha
#align pos_of_mul_pos_right pos_of_mul_pos_right
theorem pos_of_mul_pos_left [MulPosReflectLT α] (h : 0 < a * b) (hb : 0 ≤ b) : 0 < a :=
lt_of_mul_lt_mul_right ((zero_mul b).symm ▸ h : 0 * b < a * b) hb
#align pos_of_mul_pos_left pos_of_mul_pos_left
theorem pos_iff_pos_of_mul_pos [PosMulReflectLT α] [MulPosReflectLT α] (hab : 0 < a * b) :
0 < a ↔ 0 < b :=
⟨pos_of_mul_pos_right hab ∘ le_of_lt, pos_of_mul_pos_left hab ∘ le_of_lt⟩
#align pos_iff_pos_of_mul_pos pos_iff_pos_of_mul_pos
theorem mul_le_mul_of_le_of_le [PosMulMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c ≤ d) (a0 : 0 ≤ a)
(d0 : 0 ≤ d) : a * c ≤ b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans <| mul_le_mul_of_nonneg_right h₁ d0
#align mul_le_mul_of_le_of_le mul_le_mul_of_le_of_le
@[gcongr]
theorem mul_le_mul [PosMulMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c ≤ d) (c0 : 0 ≤ c)
(b0 : 0 ≤ b) : a * c ≤ b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans <| mul_le_mul_of_nonneg_left h₂ b0
#align mul_le_mul mul_le_mul
theorem mul_self_le_mul_self [PosMulMono α] [MulPosMono α] (ha : 0 ≤ a) (hab : a ≤ b) :
a * a ≤ b * b :=
mul_le_mul hab hab ha <| ha.trans hab
#align mul_self_le_mul_self mul_self_le_mul_self
theorem mul_le_of_mul_le_of_nonneg_left [PosMulMono α] (h : a * b ≤ c) (hle : d ≤ b)
(a0 : 0 ≤ a) : a * d ≤ c :=
(mul_le_mul_of_nonneg_left hle a0).trans h
#align mul_le_of_mul_le_of_nonneg_left mul_le_of_mul_le_of_nonneg_left
theorem le_mul_of_le_mul_of_nonneg_left [PosMulMono α] (h : a ≤ b * c) (hle : c ≤ d)
(b0 : 0 ≤ b) : a ≤ b * d :=
h.trans (mul_le_mul_of_nonneg_left hle b0)
#align le_mul_of_le_mul_of_nonneg_left le_mul_of_le_mul_of_nonneg_left
theorem mul_le_of_mul_le_of_nonneg_right [MulPosMono α] (h : a * b ≤ c) (hle : d ≤ a)
(b0 : 0 ≤ b) : d * b ≤ c :=
(mul_le_mul_of_nonneg_right hle b0).trans h
#align mul_le_of_mul_le_of_nonneg_right mul_le_of_mul_le_of_nonneg_right
theorem le_mul_of_le_mul_of_nonneg_right [MulPosMono α] (h : a ≤ b * c) (hle : b ≤ d)
(c0 : 0 ≤ c) : a ≤ d * c :=
h.trans (mul_le_mul_of_nonneg_right hle c0)
#align le_mul_of_le_mul_of_nonneg_right le_mul_of_le_mul_of_nonneg_right
end Preorder
section PartialOrder
variable [PartialOrder α]
theorem posMulMono_iff_covariant_pos :
PosMulMono α ↔ CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨@PosMulMono.to_covariantClass_pos_mul_le _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha]
· exact @CovariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align pos_mul_mono_iff_covariant_pos posMulMono_iff_covariant_pos
theorem mulPosMono_iff_covariant_pos :
MulPosMono α ↔ CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨@MulPosMono.to_covariantClass_pos_mul_le _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha]
· exact @CovariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align mul_pos_mono_iff_covariant_pos mulPosMono_iff_covariant_pos
theorem posMulReflectLT_iff_contravariant_pos :
PosMulReflectLT α ↔ ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨@PosMulReflectLT.to_contravariantClass_pos_mul_lt _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha] at h
· exact @ContravariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align pos_mul_reflect_lt_iff_contravariant_pos posMulReflectLT_iff_contravariant_pos
theorem mulPosReflectLT_iff_contravariant_pos :
MulPosReflectLT α ↔ ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨@MulPosReflectLT.to_contravariantClass_pos_mul_lt _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha] at h
· exact @ContravariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align mul_pos_reflect_lt_iff_contravariant_pos mulPosReflectLT_iff_contravariant_pos
-- Porting note: mathlib3 proofs would look like `StrictMono.monotone <| @CovariantClass.elim ..`
-- but implicit argument handling causes that to break
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulMono [PosMulStrictMono α] : PosMulMono α :=
posMulMono_iff_covariant_pos.2 (covariantClass_le_of_lt _ _ _)
#align pos_mul_strict_mono.to_pos_mul_mono PosMulStrictMono.toPosMulMono
-- Porting note: mathlib3 proofs would look like `StrictMono.monotone <| @CovariantClass.elim ..`
-- but implicit argument handling causes that to break
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosMono [MulPosStrictMono α] : MulPosMono α :=
mulPosMono_iff_covariant_pos.2 (covariantClass_le_of_lt _ _ _)
#align mul_pos_strict_mono.to_mul_pos_mono MulPosStrictMono.toMulPosMono
-- see Note [lower instance priority]
instance (priority := 100) PosMulReflectLE.toPosMulReflectLT [PosMulReflectLE α] :
PosMulReflectLT α :=
posMulReflectLT_iff_contravariant_pos.2
⟨fun a b c h =>
(le_of_mul_le_mul_of_pos_left h.le a.2).lt_of_ne <| by
rintro rfl
simp at h⟩
#align pos_mul_mono_rev.to_pos_mul_reflect_lt PosMulReflectLE.toPosMulReflectLT
-- see Note [lower instance priority]
instance (priority := 100) MulPosReflectLE.toMulPosReflectLT [MulPosReflectLE α] :
MulPosReflectLT α :=
mulPosReflectLT_iff_contravariant_pos.2
⟨fun a b c h =>
(le_of_mul_le_mul_of_pos_right h.le a.2).lt_of_ne <| by
rintro rfl
simp at h⟩
#align mul_pos_mono_rev.to_mul_pos_reflect_lt MulPosReflectLE.toMulPosReflectLT
theorem mul_left_cancel_iff_of_pos [PosMulReflectLE α] (a0 : 0 < a) : a * b = a * c ↔ b = c :=
⟨fun h => (le_of_mul_le_mul_of_pos_left h.le a0).antisymm <|
le_of_mul_le_mul_of_pos_left h.ge a0, congr_arg _⟩
#align mul_left_cancel_iff_of_pos mul_left_cancel_iff_of_pos
theorem mul_right_cancel_iff_of_pos [MulPosReflectLE α] (b0 : 0 < b) : a * b = c * b ↔ a = c :=
⟨fun h => (le_of_mul_le_mul_of_pos_right h.le b0).antisymm <|
le_of_mul_le_mul_of_pos_right h.ge b0, congr_arg (· * b)⟩
#align mul_right_cancel_iff_of_pos mul_right_cancel_iff_of_pos
theorem mul_eq_mul_iff_eq_and_eq_of_pos [PosMulStrictMono α] [MulPosStrictMono α]
(hab : a ≤ b) (hcd : c ≤ d) (a0 : 0 < a) (d0 : 0 < d) :
a * c = b * d ↔ a = b ∧ c = d := by
refine ⟨fun h ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
simp only [eq_iff_le_not_lt, hab, hcd, true_and]
refine ⟨fun hab ↦ h.not_lt ?_, fun hcd ↦ h.not_lt ?_⟩
· exact (mul_le_mul_of_nonneg_left hcd a0.le).trans_lt (mul_lt_mul_of_pos_right hab d0)
· exact (mul_lt_mul_of_pos_left hcd a0).trans_le (mul_le_mul_of_nonneg_right hab d0.le)
#align mul_eq_mul_iff_eq_and_eq_of_pos mul_eq_mul_iff_eq_and_eq_of_pos
theorem mul_eq_mul_iff_eq_and_eq_of_pos' [PosMulStrictMono α] [MulPosStrictMono α]
(hab : a ≤ b) (hcd : c ≤ d) (b0 : 0 < b) (c0 : 0 < c) :
a * c = b * d ↔ a = b ∧ c = d := by
refine ⟨fun h ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
simp only [eq_iff_le_not_lt, hab, hcd, true_and]
refine ⟨fun hab ↦ h.not_lt ?_, fun hcd ↦ h.not_lt ?_⟩
· exact (mul_lt_mul_of_pos_right hab c0).trans_le (mul_le_mul_of_nonneg_left hcd b0.le)
· exact (mul_le_mul_of_nonneg_right hab c0.le).trans_lt (mul_lt_mul_of_pos_left hcd b0)
#align mul_eq_mul_iff_eq_and_eq_of_pos' mul_eq_mul_iff_eq_and_eq_of_pos'
end PartialOrder
section LinearOrder
variable [LinearOrder α]
theorem pos_and_pos_or_neg_and_neg_of_mul_pos [PosMulMono α] [MulPosMono α] (hab : 0 < a * b) :
0 < a ∧ 0 < b ∨ a < 0 ∧ b < 0 := by
rcases lt_trichotomy a 0 with (ha | rfl | ha)
· refine Or.inr ⟨ha, lt_imp_lt_of_le_imp_le (fun hb => ?_) hab⟩
exact mul_nonpos_of_nonpos_of_nonneg ha.le hb
· rw [zero_mul] at hab
exact hab.false.elim
· refine Or.inl ⟨ha, lt_imp_lt_of_le_imp_le (fun hb => ?_) hab⟩
exact mul_nonpos_of_nonneg_of_nonpos ha.le hb
#align pos_and_pos_or_neg_and_neg_of_mul_pos pos_and_pos_or_neg_and_neg_of_mul_pos
theorem neg_of_mul_pos_right [PosMulMono α] [MulPosMono α] (h : 0 < a * b) (ha : a ≤ 0) : b < 0 :=
((pos_and_pos_or_neg_and_neg_of_mul_pos h).resolve_left fun h => h.1.not_le ha).2
#align neg_of_mul_pos_right neg_of_mul_pos_right
theorem neg_of_mul_pos_left [PosMulMono α] [MulPosMono α] (h : 0 < a * b) (ha : b ≤ 0) : a < 0 :=
((pos_and_pos_or_neg_and_neg_of_mul_pos h).resolve_left fun h => h.2.not_le ha).1
#align neg_of_mul_pos_left neg_of_mul_pos_left
theorem neg_iff_neg_of_mul_pos [PosMulMono α] [MulPosMono α] (hab : 0 < a * b) : a < 0 ↔ b < 0 :=
⟨neg_of_mul_pos_right hab ∘ le_of_lt, neg_of_mul_pos_left hab ∘ le_of_lt⟩
#align neg_iff_neg_of_mul_pos neg_iff_neg_of_mul_pos
theorem Left.neg_of_mul_neg_left [PosMulMono α] (h : a * b < 0) (h1 : 0 ≤ a) : b < 0 :=
lt_of_not_ge fun h2 : b ≥ 0 => (Left.mul_nonneg h1 h2).not_lt h
#align left.neg_of_mul_neg_left Left.neg_of_mul_neg_left
theorem Right.neg_of_mul_neg_left [MulPosMono α] (h : a * b < 0) (h1 : 0 ≤ a) : b < 0 :=
lt_of_not_ge fun h2 : b ≥ 0 => (Right.mul_nonneg h1 h2).not_lt h
#align right.neg_of_mul_neg_left Right.neg_of_mul_neg_left
theorem Left.neg_of_mul_neg_right [PosMulMono α] (h : a * b < 0) (h1 : 0 ≤ b) : a < 0 :=
lt_of_not_ge fun h2 : a ≥ 0 => (Left.mul_nonneg h2 h1).not_lt h
#align left.neg_of_mul_neg_right Left.neg_of_mul_neg_right
theorem Right.neg_of_mul_neg_right [MulPosMono α] (h : a * b < 0) (h1 : 0 ≤ b) : a < 0 :=
lt_of_not_ge fun h2 : a ≥ 0 => (Right.mul_nonneg h2 h1).not_lt h
#align right.neg_of_mul_neg_right Right.neg_of_mul_neg_right
end LinearOrder
end MulZeroClass
section MulOneClass
variable [MulOneClass α] [Zero α]
section Preorder
variable [Preorder α]
/-! Lemmas of the form `a ≤ a * b ↔ 1 ≤ b` and `a * b ≤ a ↔ b ≤ 1`,
which assume left covariance. -/
@[simp]
lemma le_mul_iff_one_le_right [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a ≤ a * b ↔ 1 ≤ b :=
Iff.trans (by rw [mul_one]) (mul_le_mul_left a0)
#align le_mul_iff_one_le_right le_mul_iff_one_le_right
@[simp]
theorem lt_mul_iff_one_lt_right [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a < a * b ↔ 1 < b :=
Iff.trans (by rw [mul_one]) (mul_lt_mul_left a0)
#align lt_mul_iff_one_lt_right lt_mul_iff_one_lt_right
@[simp]
lemma mul_le_iff_le_one_right [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a * b ≤ a ↔ b ≤ 1 :=
Iff.trans (by rw [mul_one]) (mul_le_mul_left a0)
#align mul_le_iff_le_one_right mul_le_iff_le_one_right
@[simp]
theorem mul_lt_iff_lt_one_right [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a * b < a ↔ b < 1 :=
Iff.trans (by rw [mul_one]) (mul_lt_mul_left a0)
#align mul_lt_iff_lt_one_right mul_lt_iff_lt_one_right
/-! Lemmas of the form `a ≤ b * a ↔ 1 ≤ b` and `a * b ≤ b ↔ a ≤ 1`,
which assume right covariance. -/
@[simp]
lemma le_mul_iff_one_le_left [MulPosMono α] [MulPosReflectLE α] (a0 : 0 < a) : a ≤ b * a ↔ 1 ≤ b :=
Iff.trans (by rw [one_mul]) (mul_le_mul_right a0)
#align le_mul_iff_one_le_left le_mul_iff_one_le_left
@[simp]
theorem lt_mul_iff_one_lt_left [MulPosStrictMono α] [MulPosReflectLT α] (a0 : 0 < a) :
a < b * a ↔ 1 < b :=
Iff.trans (by rw [one_mul]) (mul_lt_mul_right a0)
#align lt_mul_iff_one_lt_left lt_mul_iff_one_lt_left
@[simp]
lemma mul_le_iff_le_one_left [MulPosMono α] [MulPosReflectLE α] (b0 : 0 < b) : a * b ≤ b ↔ a ≤ 1 :=
Iff.trans (by rw [one_mul]) (mul_le_mul_right b0)
#align mul_le_iff_le_one_left mul_le_iff_le_one_left
@[simp]
theorem mul_lt_iff_lt_one_left [MulPosStrictMono α] [MulPosReflectLT α] (b0 : 0 < b) :
a * b < b ↔ a < 1 :=
Iff.trans (by rw [one_mul]) (mul_lt_mul_right b0)
#align mul_lt_iff_lt_one_left mul_lt_iff_lt_one_left
/-! Lemmas of the form `1 ≤ b → a ≤ a * b`.
Variants with `< 0` and `≤ 0` instead of `0 <` and `0 ≤` appear in `Mathlib/Algebra/Order/Ring/Defs`
(which imports this file) as they need additional results which are not yet available here. -/
theorem mul_le_of_le_one_left [MulPosMono α] (hb : 0 ≤ b) (h : a ≤ 1) : a * b ≤ b := by
simpa only [one_mul] using mul_le_mul_of_nonneg_right h hb
#align mul_le_of_le_one_left mul_le_of_le_one_left
theorem le_mul_of_one_le_left [MulPosMono α] (hb : 0 ≤ b) (h : 1 ≤ a) : b ≤ a * b := by
simpa only [one_mul] using mul_le_mul_of_nonneg_right h hb
#align le_mul_of_one_le_left le_mul_of_one_le_left
theorem mul_le_of_le_one_right [PosMulMono α] (ha : 0 ≤ a) (h : b ≤ 1) : a * b ≤ a := by
simpa only [mul_one] using mul_le_mul_of_nonneg_left h ha
#align mul_le_of_le_one_right mul_le_of_le_one_right
theorem le_mul_of_one_le_right [PosMulMono α] (ha : 0 ≤ a) (h : 1 ≤ b) : a ≤ a * b := by
simpa only [mul_one] using mul_le_mul_of_nonneg_left h ha
#align le_mul_of_one_le_right le_mul_of_one_le_right
theorem mul_lt_of_lt_one_left [MulPosStrictMono α] (hb : 0 < b) (h : a < 1) : a * b < b := by
simpa only [one_mul] using mul_lt_mul_of_pos_right h hb
#align mul_lt_of_lt_one_left mul_lt_of_lt_one_left
theorem lt_mul_of_one_lt_left [MulPosStrictMono α] (hb : 0 < b) (h : 1 < a) : b < a * b := by
simpa only [one_mul] using mul_lt_mul_of_pos_right h hb
#align lt_mul_of_one_lt_left lt_mul_of_one_lt_left
theorem mul_lt_of_lt_one_right [PosMulStrictMono α] (ha : 0 < a) (h : b < 1) : a * b < a := by
simpa only [mul_one] using mul_lt_mul_of_pos_left h ha
#align mul_lt_of_lt_one_right mul_lt_of_lt_one_right
theorem lt_mul_of_one_lt_right [PosMulStrictMono α] (ha : 0 < a) (h : 1 < b) : a < a * b := by
simpa only [mul_one] using mul_lt_mul_of_pos_left h ha
#align lt_mul_of_one_lt_right lt_mul_of_one_lt_right
/-! Lemmas of the form `b ≤ c → a ≤ 1 → b * a ≤ c`. -/
/- Yaël: What's the point of these lemmas? They just chain an existing lemma with an assumption in
all possible ways, thereby artificially inflating the API and making the truly relevant lemmas hard
to find -/
theorem mul_le_of_le_of_le_one_of_nonneg [PosMulMono α] (h : b ≤ c) (ha : a ≤ 1) (hb : 0 ≤ b) :
b * a ≤ c :=
(mul_le_of_le_one_right hb ha).trans h
#align mul_le_of_le_of_le_one_of_nonneg mul_le_of_le_of_le_one_of_nonneg
theorem mul_lt_of_le_of_lt_one_of_pos [PosMulStrictMono α] (bc : b ≤ c) (ha : a < 1) (b0 : 0 < b) :
b * a < c :=
(mul_lt_of_lt_one_right b0 ha).trans_le bc
#align mul_lt_of_le_of_lt_one_of_pos mul_lt_of_le_of_lt_one_of_pos
theorem mul_lt_of_lt_of_le_one_of_nonneg [PosMulMono α] (h : b < c) (ha : a ≤ 1) (hb : 0 ≤ b) :
b * a < c :=
(mul_le_of_le_one_right hb ha).trans_lt h
#align mul_lt_of_lt_of_le_one_of_nonneg mul_lt_of_lt_of_le_one_of_nonneg
/-- Assumes left covariance. -/
theorem Left.mul_le_one_of_le_of_le [PosMulMono α] (ha : a ≤ 1) (hb : b ≤ 1) (a0 : 0 ≤ a) :
a * b ≤ 1 :=
mul_le_of_le_of_le_one_of_nonneg ha hb a0
#align left.mul_le_one_of_le_of_le Left.mul_le_one_of_le_of_le
/-- Assumes left covariance. -/
theorem Left.mul_lt_of_le_of_lt_one_of_pos [PosMulStrictMono α] (ha : a ≤ 1) (hb : b < 1)
(a0 : 0 < a) : a * b < 1 :=
_root_.mul_lt_of_le_of_lt_one_of_pos ha hb a0
#align left.mul_lt_of_le_of_lt_one_of_pos Left.mul_lt_of_le_of_lt_one_of_pos
/-- Assumes left covariance. -/
theorem Left.mul_lt_of_lt_of_le_one_of_nonneg [PosMulMono α] (ha : a < 1) (hb : b ≤ 1)
(a0 : 0 ≤ a) : a * b < 1 :=
_root_.mul_lt_of_lt_of_le_one_of_nonneg ha hb a0
#align left.mul_lt_of_lt_of_le_one_of_nonneg Left.mul_lt_of_lt_of_le_one_of_nonneg
theorem mul_le_of_le_of_le_one' [PosMulMono α] [MulPosMono α] (bc : b ≤ c) (ha : a ≤ 1) (a0 : 0 ≤ a)
(c0 : 0 ≤ c) : b * a ≤ c :=
(mul_le_mul_of_nonneg_right bc a0).trans <| mul_le_of_le_one_right c0 ha
#align mul_le_of_le_of_le_one' mul_le_of_le_of_le_one'
theorem mul_lt_of_lt_of_le_one' [PosMulMono α] [MulPosStrictMono α] (bc : b < c) (ha : a ≤ 1)
(a0 : 0 < a) (c0 : 0 ≤ c) : b * a < c :=
(mul_lt_mul_of_pos_right bc a0).trans_le <| mul_le_of_le_one_right c0 ha
#align mul_lt_of_lt_of_le_one' mul_lt_of_lt_of_le_one'
theorem mul_lt_of_le_of_lt_one' [PosMulStrictMono α] [MulPosMono α] (bc : b ≤ c) (ha : a < 1)
(a0 : 0 ≤ a) (c0 : 0 < c) : b * a < c :=
(mul_le_mul_of_nonneg_right bc a0).trans_lt <| mul_lt_of_lt_one_right c0 ha
#align mul_lt_of_le_of_lt_one' mul_lt_of_le_of_lt_one'
theorem mul_lt_of_lt_of_lt_one_of_pos [PosMulMono α] [MulPosStrictMono α] (bc : b < c) (ha : a ≤ 1)
(a0 : 0 < a) (c0 : 0 ≤ c) : b * a < c :=
(mul_lt_mul_of_pos_right bc a0).trans_le <| mul_le_of_le_one_right c0 ha
#align mul_lt_of_lt_of_lt_one_of_pos mul_lt_of_lt_of_lt_one_of_pos
/-! Lemmas of the form `b ≤ c → 1 ≤ a → b ≤ c * a`. -/
theorem le_mul_of_le_of_one_le_of_nonneg [PosMulMono α] (h : b ≤ c) (ha : 1 ≤ a) (hc : 0 ≤ c) :
b ≤ c * a :=
h.trans <| le_mul_of_one_le_right hc ha
#align le_mul_of_le_of_one_le_of_nonneg le_mul_of_le_of_one_le_of_nonneg
theorem lt_mul_of_le_of_one_lt_of_pos [PosMulStrictMono α] (bc : b ≤ c) (ha : 1 < a) (c0 : 0 < c) :
b < c * a :=
bc.trans_lt <| lt_mul_of_one_lt_right c0 ha
#align lt_mul_of_le_of_one_lt_of_pos lt_mul_of_le_of_one_lt_of_pos
theorem lt_mul_of_lt_of_one_le_of_nonneg [PosMulMono α] (h : b < c) (ha : 1 ≤ a) (hc : 0 ≤ c) :
b < c * a :=
h.trans_le <| le_mul_of_one_le_right hc ha
#align lt_mul_of_lt_of_one_le_of_nonneg lt_mul_of_lt_of_one_le_of_nonneg
/-- Assumes left covariance. -/
theorem Left.one_le_mul_of_le_of_le [PosMulMono α] (ha : 1 ≤ a) (hb : 1 ≤ b) (a0 : 0 ≤ a) :
1 ≤ a * b :=
le_mul_of_le_of_one_le_of_nonneg ha hb a0
#align left.one_le_mul_of_le_of_le Left.one_le_mul_of_le_of_le
/-- Assumes left covariance. -/
theorem Left.one_lt_mul_of_le_of_lt_of_pos [PosMulStrictMono α] (ha : 1 ≤ a) (hb : 1 < b)
(a0 : 0 < a) : 1 < a * b :=
lt_mul_of_le_of_one_lt_of_pos ha hb a0
#align left.one_lt_mul_of_le_of_lt_of_pos Left.one_lt_mul_of_le_of_lt_of_pos
/-- Assumes left covariance. -/
theorem Left.lt_mul_of_lt_of_one_le_of_nonneg [PosMulMono α] (ha : 1 < a) (hb : 1 ≤ b)
(a0 : 0 ≤ a) : 1 < a * b :=
_root_.lt_mul_of_lt_of_one_le_of_nonneg ha hb a0
#align left.lt_mul_of_lt_of_one_le_of_nonneg Left.lt_mul_of_lt_of_one_le_of_nonneg
theorem le_mul_of_le_of_one_le' [PosMulMono α] [MulPosMono α] (bc : b ≤ c) (ha : 1 ≤ a)
(a0 : 0 ≤ a) (b0 : 0 ≤ b) : b ≤ c * a :=
(le_mul_of_one_le_right b0 ha).trans <| mul_le_mul_of_nonneg_right bc a0
#align le_mul_of_le_of_one_le' le_mul_of_le_of_one_le'
theorem lt_mul_of_le_of_one_lt' [PosMulStrictMono α] [MulPosMono α] (bc : b ≤ c) (ha : 1 < a)
(a0 : 0 ≤ a) (b0 : 0 < b) : b < c * a :=
(lt_mul_of_one_lt_right b0 ha).trans_le <| mul_le_mul_of_nonneg_right bc a0
#align lt_mul_of_le_of_one_lt' lt_mul_of_le_of_one_lt'
theorem lt_mul_of_lt_of_one_le' [PosMulMono α] [MulPosStrictMono α] (bc : b < c) (ha : 1 ≤ a)
(a0 : 0 < a) (b0 : 0 ≤ b) : b < c * a :=
(le_mul_of_one_le_right b0 ha).trans_lt <| mul_lt_mul_of_pos_right bc a0
#align lt_mul_of_lt_of_one_le' lt_mul_of_lt_of_one_le'
theorem lt_mul_of_lt_of_one_lt_of_pos [PosMulStrictMono α] [MulPosStrictMono α] (bc : b < c)
(ha : 1 < a) (a0 : 0 < a) (b0 : 0 < b) : b < c * a :=
(lt_mul_of_one_lt_right b0 ha).trans <| mul_lt_mul_of_pos_right bc a0
#align lt_mul_of_lt_of_one_lt_of_pos lt_mul_of_lt_of_one_lt_of_pos
/-! Lemmas of the form `a ≤ 1 → b ≤ c → a * b ≤ c`. -/
theorem mul_le_of_le_one_of_le_of_nonneg [MulPosMono α] (ha : a ≤ 1) (h : b ≤ c) (hb : 0 ≤ b) :
a * b ≤ c :=
(mul_le_of_le_one_left hb ha).trans h
#align mul_le_of_le_one_of_le_of_nonneg mul_le_of_le_one_of_le_of_nonneg
theorem mul_lt_of_lt_one_of_le_of_pos [MulPosStrictMono α] (ha : a < 1) (h : b ≤ c) (hb : 0 < b) :
a * b < c :=
(mul_lt_of_lt_one_left hb ha).trans_le h
#align mul_lt_of_lt_one_of_le_of_pos mul_lt_of_lt_one_of_le_of_pos
theorem mul_lt_of_le_one_of_lt_of_nonneg [MulPosMono α] (ha : a ≤ 1) (h : b < c) (hb : 0 ≤ b) :
a * b < c :=
(mul_le_of_le_one_left hb ha).trans_lt h
#align mul_lt_of_le_one_of_lt_of_nonneg mul_lt_of_le_one_of_lt_of_nonneg
/-- Assumes right covariance. -/
theorem Right.mul_lt_one_of_lt_of_le_of_pos [MulPosStrictMono α] (ha : a < 1) (hb : b ≤ 1)
(b0 : 0 < b) : a * b < 1 :=
mul_lt_of_lt_one_of_le_of_pos ha hb b0
#align right.mul_lt_one_of_lt_of_le_of_pos Right.mul_lt_one_of_lt_of_le_of_pos
/-- Assumes right covariance. -/
theorem Right.mul_lt_one_of_le_of_lt_of_nonneg [MulPosMono α] (ha : a ≤ 1) (hb : b < 1)
(b0 : 0 ≤ b) : a * b < 1 :=
mul_lt_of_le_one_of_lt_of_nonneg ha hb b0
#align right.mul_lt_one_of_le_of_lt_of_nonneg Right.mul_lt_one_of_le_of_lt_of_nonneg
theorem mul_lt_of_lt_one_of_lt_of_pos [PosMulStrictMono α] [MulPosStrictMono α] (ha : a < 1)
(bc : b < c) (a0 : 0 < a) (c0 : 0 < c) : a * b < c :=
(mul_lt_mul_of_pos_left bc a0).trans <| mul_lt_of_lt_one_left c0 ha
#align mul_lt_of_lt_one_of_lt_of_pos mul_lt_of_lt_one_of_lt_of_pos
/-- Assumes right covariance. -/
theorem Right.mul_le_one_of_le_of_le [MulPosMono α] (ha : a ≤ 1) (hb : b ≤ 1) (b0 : 0 ≤ b) :
a * b ≤ 1 :=
mul_le_of_le_one_of_le_of_nonneg ha hb b0
#align right.mul_le_one_of_le_of_le Right.mul_le_one_of_le_of_le
theorem mul_le_of_le_one_of_le' [PosMulMono α] [MulPosMono α] (ha : a ≤ 1) (bc : b ≤ c) (a0 : 0 ≤ a)
(c0 : 0 ≤ c) : a * b ≤ c :=
(mul_le_mul_of_nonneg_left bc a0).trans <| mul_le_of_le_one_left c0 ha
#align mul_le_of_le_one_of_le' mul_le_of_le_one_of_le'
theorem mul_lt_of_lt_one_of_le' [PosMulMono α] [MulPosStrictMono α] (ha : a < 1) (bc : b ≤ c)
(a0 : 0 ≤ a) (c0 : 0 < c) : a * b < c :=
(mul_le_mul_of_nonneg_left bc a0).trans_lt <| mul_lt_of_lt_one_left c0 ha
#align mul_lt_of_lt_one_of_le' mul_lt_of_lt_one_of_le'
theorem mul_lt_of_le_one_of_lt' [PosMulStrictMono α] [MulPosMono α] (ha : a ≤ 1) (bc : b < c)
(a0 : 0 < a) (c0 : 0 ≤ c) : a * b < c :=
(mul_lt_mul_of_pos_left bc a0).trans_le <| mul_le_of_le_one_left c0 ha
#align mul_lt_of_le_one_of_lt' mul_lt_of_le_one_of_lt'
/-! Lemmas of the form `1 ≤ a → b ≤ c → b ≤ a * c`. -/
theorem lt_mul_of_one_lt_of_le_of_pos [MulPosStrictMono α] (ha : 1 < a) (h : b ≤ c) (hc : 0 < c) :
b < a * c :=
h.trans_lt <| lt_mul_of_one_lt_left hc ha
#align lt_mul_of_one_lt_of_le_of_pos lt_mul_of_one_lt_of_le_of_pos
theorem lt_mul_of_one_le_of_lt_of_nonneg [MulPosMono α] (ha : 1 ≤ a) (h : b < c) (hc : 0 ≤ c) :
b < a * c :=
h.trans_le <| le_mul_of_one_le_left hc ha
#align lt_mul_of_one_le_of_lt_of_nonneg lt_mul_of_one_le_of_lt_of_nonneg
theorem lt_mul_of_one_lt_of_lt_of_pos [MulPosStrictMono α] (ha : 1 < a) (h : b < c) (hc : 0 < c) :
b < a * c :=
h.trans <| lt_mul_of_one_lt_left hc ha
#align lt_mul_of_one_lt_of_lt_of_pos lt_mul_of_one_lt_of_lt_of_pos
/-- Assumes right covariance. -/
theorem Right.one_lt_mul_of_lt_of_le_of_pos [MulPosStrictMono α] (ha : 1 < a) (hb : 1 ≤ b)
(b0 : 0 < b) : 1 < a * b :=
lt_mul_of_one_lt_of_le_of_pos ha hb b0
#align right.one_lt_mul_of_lt_of_le_of_pos Right.one_lt_mul_of_lt_of_le_of_pos
/-- Assumes right covariance. -/
theorem Right.one_lt_mul_of_le_of_lt_of_nonneg [MulPosMono α] (ha : 1 ≤ a) (hb : 1 < b)
(b0 : 0 ≤ b) : 1 < a * b :=
lt_mul_of_one_le_of_lt_of_nonneg ha hb b0
#align right.one_lt_mul_of_le_of_lt_of_nonneg Right.one_lt_mul_of_le_of_lt_of_nonneg
/-- Assumes right covariance. -/
theorem Right.one_lt_mul_of_lt_of_lt [MulPosStrictMono α] (ha : 1 < a) (hb : 1 < b) (b0 : 0 < b) :
1 < a * b :=
lt_mul_of_one_lt_of_lt_of_pos ha hb b0
#align right.one_lt_mul_of_lt_of_lt Right.one_lt_mul_of_lt_of_lt
theorem lt_mul_of_one_lt_of_lt_of_nonneg [MulPosMono α] (ha : 1 ≤ a) (h : b < c) (hc : 0 ≤ c) :
b < a * c :=
h.trans_le <| le_mul_of_one_le_left hc ha
#align lt_mul_of_one_lt_of_lt_of_nonneg lt_mul_of_one_lt_of_lt_of_nonneg
theorem lt_of_mul_lt_of_one_le_of_nonneg_left [PosMulMono α] (h : a * b < c) (hle : 1 ≤ b)
(ha : 0 ≤ a) : a < c :=
(le_mul_of_one_le_right ha hle).trans_lt h
#align lt_of_mul_lt_of_one_le_of_nonneg_left lt_of_mul_lt_of_one_le_of_nonneg_left
theorem lt_of_lt_mul_of_le_one_of_nonneg_left [PosMulMono α] (h : a < b * c) (hc : c ≤ 1)
(hb : 0 ≤ b) : a < b :=
h.trans_le <| mul_le_of_le_one_right hb hc
#align lt_of_lt_mul_of_le_one_of_nonneg_left lt_of_lt_mul_of_le_one_of_nonneg_left
theorem lt_of_lt_mul_of_le_one_of_nonneg_right [MulPosMono α] (h : a < b * c) (hb : b ≤ 1)
(hc : 0 ≤ c) : a < c :=
h.trans_le <| mul_le_of_le_one_left hc hb
#align lt_of_lt_mul_of_le_one_of_nonneg_right lt_of_lt_mul_of_le_one_of_nonneg_right
theorem le_mul_of_one_le_of_le_of_nonneg [MulPosMono α] (ha : 1 ≤ a) (bc : b ≤ c) (c0 : 0 ≤ c) :
b ≤ a * c :=
bc.trans <| le_mul_of_one_le_left c0 ha
#align le_mul_of_one_le_of_le_of_nonneg le_mul_of_one_le_of_le_of_nonneg
/-- Assumes right covariance. -/
theorem Right.one_le_mul_of_le_of_le [MulPosMono α] (ha : 1 ≤ a) (hb : 1 ≤ b) (b0 : 0 ≤ b) :
1 ≤ a * b :=
le_mul_of_one_le_of_le_of_nonneg ha hb b0
#align right.one_le_mul_of_le_of_le Right.one_le_mul_of_le_of_le
theorem le_of_mul_le_of_one_le_of_nonneg_left [PosMulMono α] (h : a * b ≤ c) (hb : 1 ≤ b)
(ha : 0 ≤ a) : a ≤ c :=
(le_mul_of_one_le_right ha hb).trans h
#align le_of_mul_le_of_one_le_of_nonneg_left le_of_mul_le_of_one_le_of_nonneg_left
theorem le_of_le_mul_of_le_one_of_nonneg_left [PosMulMono α] (h : a ≤ b * c) (hc : c ≤ 1)
(hb : 0 ≤ b) : a ≤ b :=
h.trans <| mul_le_of_le_one_right hb hc
#align le_of_le_mul_of_le_one_of_nonneg_left le_of_le_mul_of_le_one_of_nonneg_left
theorem le_of_mul_le_of_one_le_nonneg_right [MulPosMono α] (h : a * b ≤ c) (ha : 1 ≤ a)
(hb : 0 ≤ b) : b ≤ c :=
(le_mul_of_one_le_left hb ha).trans h
#align le_of_mul_le_of_one_le_nonneg_right le_of_mul_le_of_one_le_nonneg_right
theorem le_of_le_mul_of_le_one_of_nonneg_right [MulPosMono α] (h : a ≤ b * c) (hb : b ≤ 1)
(hc : 0 ≤ c) : a ≤ c :=
h.trans <| mul_le_of_le_one_left hc hb
#align le_of_le_mul_of_le_one_of_nonneg_right le_of_le_mul_of_le_one_of_nonneg_right
end Preorder
section LinearOrder
variable [LinearOrder α]
-- Yaël: What's the point of this lemma? If we have `0 * 0 = 0`, then we can just take `b = 0`.
-- proven with `a0 : 0 ≤ a` as `exists_square_le`
theorem exists_square_le' [PosMulStrictMono α] (a0 : 0 < a) : ∃ b : α, b * b ≤ a := by
obtain ha | ha := lt_or_le a 1
· exact ⟨a, (mul_lt_of_lt_one_right a0 ha).le⟩
· exact ⟨1, by rwa [mul_one]⟩
#align exists_square_le' exists_square_le'
end LinearOrder
end MulOneClass
section CancelMonoidWithZero
variable [CancelMonoidWithZero α]
section PartialOrder
variable [PartialOrder α]
theorem PosMulMono.toPosMulStrictMono [PosMulMono α] : PosMulStrictMono α :=
⟨fun x _ _ h => (mul_le_mul_of_nonneg_left h.le x.2.le).lt_of_ne
(h.ne ∘ mul_left_cancel₀ x.2.ne')⟩
#align pos_mul_mono.to_pos_mul_strict_mono PosMulMono.toPosMulStrictMono
theorem posMulMono_iff_posMulStrictMono : PosMulMono α ↔ PosMulStrictMono α :=
⟨@PosMulMono.toPosMulStrictMono α _ _, @PosMulStrictMono.toPosMulMono α _ _⟩
#align pos_mul_mono_iff_pos_mul_strict_mono posMulMono_iff_posMulStrictMono
theorem MulPosMono.toMulPosStrictMono [MulPosMono α] : MulPosStrictMono α :=
⟨fun x _ _ h => (mul_le_mul_of_nonneg_right h.le x.2.le).lt_of_ne
(h.ne ∘ mul_right_cancel₀ x.2.ne')⟩
#align mul_pos_mono.to_mul_pos_strict_mono MulPosMono.toMulPosStrictMono
theorem mulPosMono_iff_mulPosStrictMono : MulPosMono α ↔ MulPosStrictMono α :=
⟨@MulPosMono.toMulPosStrictMono α _ _, @MulPosStrictMono.toMulPosMono α _ _⟩
#align mul_pos_mono_iff_mul_pos_strict_mono mulPosMono_iff_mulPosStrictMono
theorem PosMulReflectLT.toPosMulReflectLE [PosMulReflectLT α] : PosMulReflectLE α :=
⟨fun x _ _ h =>
h.eq_or_lt.elim (le_of_eq ∘ mul_left_cancel₀ x.2.ne.symm) fun h' =>
(lt_of_mul_lt_mul_left h' x.2.le).le⟩
#align pos_mul_reflect_lt.to_pos_mul_mono_rev PosMulReflectLT.toPosMulReflectLE
theorem posMulReflectLE_iff_posMulReflectLT : PosMulReflectLE α ↔ PosMulReflectLT α :=
⟨@PosMulReflectLE.toPosMulReflectLT α _ _, @PosMulReflectLT.toPosMulReflectLE α _ _⟩
#align pos_mul_mono_rev_iff_pos_mul_reflect_lt posMulReflectLE_iff_posMulReflectLT
theorem MulPosReflectLT.toMulPosReflectLE [MulPosReflectLT α] : MulPosReflectLE α :=
⟨fun x _ _ h => h.eq_or_lt.elim (le_of_eq ∘ mul_right_cancel₀ x.2.ne.symm) fun h' =>
(lt_of_mul_lt_mul_right h' x.2.le).le⟩
#align mul_pos_reflect_lt.to_mul_pos_mono_rev MulPosReflectLT.toMulPosReflectLE
theorem mulPosReflectLE_iff_mulPosReflectLT : MulPosReflectLE α ↔ MulPosReflectLT α :=
⟨@MulPosReflectLE.toMulPosReflectLT α _ _, @MulPosReflectLT.toMulPosReflectLE α _ _⟩
#align mul_pos_mono_rev_iff_mul_pos_reflect_lt mulPosReflectLE_iff_mulPosReflectLT
end PartialOrder
end CancelMonoidWithZero
section CommSemigroupHasZero
variable [Mul α] [IsSymmOp α α (· * ·)] [Zero α] [Preorder α]
theorem posMulStrictMono_iff_mulPosStrictMono : PosMulStrictMono α ↔ MulPosStrictMono α := by
simp only [PosMulStrictMono, MulPosStrictMono, IsSymmOp.symm_op]
#align pos_mul_strict_mono_iff_mul_pos_strict_mono posMulStrictMono_iff_mulPosStrictMono
| Mathlib/Algebra/Order/GroupWithZero/Unbundled.lean | 1,089 | 1,090 | theorem posMulReflectLT_iff_mulPosReflectLT : PosMulReflectLT α ↔ MulPosReflectLT α := by |
simp only [PosMulReflectLT, MulPosReflectLT, IsSymmOp.symm_op]
|
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Kenny Lau
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.RingTheory.MvPowerSeries.Basic
#align_import ring_theory.power_series.basic from "leanprover-community/mathlib"@"2d5739b61641ee4e7e53eca5688a08f66f2e6a60"
/-!
# Formal power series (in one variable)
This file defines (univariate) formal power series
and develops the basic properties of these objects.
A formal power series is to a polynomial like an infinite sum is to a finite sum.
Formal power series in one variable are defined from multivariate
power series as `PowerSeries R := MvPowerSeries Unit R`.
The file sets up the (semi)ring structure on univariate power series.
We provide the natural inclusion from polynomials to formal power series.
Additional results can be found in:
* `Mathlib.RingTheory.PowerSeries.Trunc`, truncation of power series;
* `Mathlib.RingTheory.PowerSeries.Inverse`, about inverses of power series,
and the fact that power series over a local ring form a local ring;
* `Mathlib.RingTheory.PowerSeries.Order`, the order of a power series at 0,
and application to the fact that power series over an integral domain
form an integral domain.
## Implementation notes
Because of its definition,
`PowerSeries R := MvPowerSeries Unit R`.
a lot of proofs and properties from the multivariate case
can be ported to the single variable case.
However, it means that formal power series are indexed by `Unit →₀ ℕ`,
which is of course canonically isomorphic to `ℕ`.
We then build some glue to treat formal power series as if they were indexed by `ℕ`.
Occasionally this leads to proofs that are uglier than expected.
-/
noncomputable section
open Finset (antidiagonal mem_antidiagonal)
/-- Formal power series over a coefficient type `R` -/
def PowerSeries (R : Type*) :=
MvPowerSeries Unit R
#align power_series PowerSeries
namespace PowerSeries
open Finsupp (single)
variable {R : Type*}
section
-- Porting note: not available in Lean 4
-- local reducible PowerSeries
/--
`R⟦X⟧` is notation for `PowerSeries R`,
the semiring of formal power series in one variable over a semiring `R`.
-/
scoped notation:9000 R "⟦X⟧" => PowerSeries R
instance [Inhabited R] : Inhabited R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Zero R] : Zero R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddMonoid R] : AddMonoid R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddGroup R] : AddGroup R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddCommMonoid R] : AddCommMonoid R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [AddCommGroup R] : AddCommGroup R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Semiring R] : Semiring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [CommSemiring R] : CommSemiring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Ring R] : Ring R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [CommRing R] : CommRing R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance [Nontrivial R] : Nontrivial R⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance {A} [Semiring R] [AddCommMonoid A] [Module R A] : Module R A⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
instance {A S} [Semiring R] [Semiring S] [AddCommMonoid A] [Module R A] [Module S A] [SMul R S]
[IsScalarTower R S A] : IsScalarTower R S A⟦X⟧ :=
Pi.isScalarTower
instance {A} [Semiring A] [CommSemiring R] [Algebra R A] : Algebra R A⟦X⟧ := by
dsimp only [PowerSeries]
infer_instance
end
section Semiring
variable (R) [Semiring R]
/-- The `n`th coefficient of a formal power series. -/
def coeff (n : ℕ) : R⟦X⟧ →ₗ[R] R :=
MvPowerSeries.coeff R (single () n)
#align power_series.coeff PowerSeries.coeff
/-- The `n`th monomial with coefficient `a` as formal power series. -/
def monomial (n : ℕ) : R →ₗ[R] R⟦X⟧ :=
MvPowerSeries.monomial R (single () n)
#align power_series.monomial PowerSeries.monomial
variable {R}
| Mathlib/RingTheory/PowerSeries/Basic.lean | 150 | 151 | theorem coeff_def {s : Unit →₀ ℕ} {n : ℕ} (h : s () = n) : coeff R n = MvPowerSeries.coeff R s := by |
erw [coeff, ← h, ← Finsupp.unique_single s]
|
/-
Copyright (c) 2019 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Isabel Longbottom, Scott Morrison
-/
import Mathlib.Algebra.Order.ZeroLEOne
import Mathlib.Data.List.InsertNth
import Mathlib.Logic.Relation
import Mathlib.Logic.Small.Defs
import Mathlib.Order.GameAdd
#align_import set_theory.game.pgame from "leanprover-community/mathlib"@"8900d545017cd21961daa2a1734bb658ef52c618"
/-!
# Combinatorial (pre-)games.
The basic theory of combinatorial games, following Conway's book `On Numbers and Games`. We
construct "pregames", define an ordering and arithmetic operations on them, then show that the
operations descend to "games", defined via the equivalence relation `p ≈ q ↔ p ≤ q ∧ q ≤ p`.
The surreal numbers will be built as a quotient of a subtype of pregames.
A pregame (`SetTheory.PGame` below) is axiomatised via an inductive type, whose sole constructor
takes two types (thought of as indexing the possible moves for the players Left and Right), and a
pair of functions out of these types to `SetTheory.PGame` (thought of as describing the resulting
game after making a move).
Combinatorial games themselves, as a quotient of pregames, are constructed in `Game.lean`.
## Conway induction
By construction, the induction principle for pregames is exactly "Conway induction". That is, to
prove some predicate `SetTheory.PGame → Prop` holds for all pregames, it suffices to prove
that for every pregame `g`, if the predicate holds for every game resulting from making a move,
then it also holds for `g`.
While it is often convenient to work "by induction" on pregames, in some situations this becomes
awkward, so we also define accessor functions `SetTheory.PGame.LeftMoves`,
`SetTheory.PGame.RightMoves`, `SetTheory.PGame.moveLeft` and `SetTheory.PGame.moveRight`.
There is a relation `PGame.Subsequent p q`, saying that
`p` can be reached by playing some non-empty sequence of moves starting from `q`, an instance
`WellFounded Subsequent`, and a local tactic `pgame_wf_tac` which is helpful for discharging proof
obligations in inductive proofs relying on this relation.
## Order properties
Pregames have both a `≤` and a `<` relation, satisfying the usual properties of a `Preorder`. The
relation `0 < x` means that `x` can always be won by Left, while `0 ≤ x` means that `x` can be won
by Left as the second player.
It turns out to be quite convenient to define various relations on top of these. We define the "less
or fuzzy" relation `x ⧏ y` as `¬ y ≤ x`, the equivalence relation `x ≈ y` as `x ≤ y ∧ y ≤ x`, and
the fuzzy relation `x ‖ y` as `x ⧏ y ∧ y ⧏ x`. If `0 ⧏ x`, then `x` can be won by Left as the
first player. If `x ≈ 0`, then `x` can be won by the second player. If `x ‖ 0`, then `x` can be won
by the first player.
Statements like `zero_le_lf`, `zero_lf_le`, etc. unfold these definitions. The theorems `le_def` and
`lf_def` give a recursive characterisation of each relation in terms of themselves two moves later.
The theorems `zero_le`, `zero_lf`, etc. also take into account that `0` has no moves.
Later, games will be defined as the quotient by the `≈` relation; that is to say, the
`Antisymmetrization` of `SetTheory.PGame`.
## Algebraic structures
We next turn to defining the operations necessary to make games into a commutative additive group.
Addition is defined for $x = \{xL | xR\}$ and $y = \{yL | yR\}$ by $x + y = \{xL + y, x + yL | xR +
y, x + yR\}$. Negation is defined by $\{xL | xR\} = \{-xR | -xL\}$.
The order structures interact in the expected way with addition, so we have
```
theorem le_iff_sub_nonneg {x y : PGame} : x ≤ y ↔ 0 ≤ y - x := sorry
theorem lt_iff_sub_pos {x y : PGame} : x < y ↔ 0 < y - x := sorry
```
We show that these operations respect the equivalence relation, and hence descend to games. At the
level of games, these operations satisfy all the laws of a commutative group. To prove the necessary
equivalence relations at the level of pregames, we introduce the notion of a `Relabelling` of a
game, and show, for example, that there is a relabelling between `x + (y + z)` and `(x + y) + z`.
## Future work
* The theory of dominated and reversible positions, and unique normal form for short games.
* Analysis of basic domineering positions.
* Hex.
* Temperature.
* The development of surreal numbers, based on this development of combinatorial games, is still
quite incomplete.
## References
The material here is all drawn from
* [Conway, *On numbers and games*][conway2001]
An interested reader may like to formalise some of the material from
* [Andreas Blass, *A game semantics for linear logic*][MR1167694]
* [André Joyal, *Remarques sur la théorie des jeux à deux personnes*][joyal1997]
-/
set_option autoImplicit true
namespace SetTheory
open Function Relation
-- We'd like to be able to use multi-character auto-implicits in this file.
set_option relaxedAutoImplicit true
/-! ### Pre-game moves -/
/-- The type of pre-games, before we have quotiented
by equivalence (`PGame.Setoid`). In ZFC, a combinatorial game is constructed from
two sets of combinatorial games that have been constructed at an earlier
stage. To do this in type theory, we say that a pre-game is built
inductively from two families of pre-games indexed over any type
in Type u. The resulting type `PGame.{u}` lives in `Type (u+1)`,
reflecting that it is a proper class in ZFC. -/
inductive PGame : Type (u + 1)
| mk : ∀ α β : Type u, (α → PGame) → (β → PGame) → PGame
#align pgame SetTheory.PGame
compile_inductive% PGame
namespace PGame
/-- The indexing type for allowable moves by Left. -/
def LeftMoves : PGame → Type u
| mk l _ _ _ => l
#align pgame.left_moves SetTheory.PGame.LeftMoves
/-- The indexing type for allowable moves by Right. -/
def RightMoves : PGame → Type u
| mk _ r _ _ => r
#align pgame.right_moves SetTheory.PGame.RightMoves
/-- The new game after Left makes an allowed move. -/
def moveLeft : ∀ g : PGame, LeftMoves g → PGame
| mk _l _ L _ => L
#align pgame.move_left SetTheory.PGame.moveLeft
/-- The new game after Right makes an allowed move. -/
def moveRight : ∀ g : PGame, RightMoves g → PGame
| mk _ _r _ R => R
#align pgame.move_right SetTheory.PGame.moveRight
@[simp]
theorem leftMoves_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).LeftMoves = xl :=
rfl
#align pgame.left_moves_mk SetTheory.PGame.leftMoves_mk
@[simp]
theorem moveLeft_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).moveLeft = xL :=
rfl
#align pgame.move_left_mk SetTheory.PGame.moveLeft_mk
@[simp]
theorem rightMoves_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).RightMoves = xr :=
rfl
#align pgame.right_moves_mk SetTheory.PGame.rightMoves_mk
@[simp]
theorem moveRight_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).moveRight = xR :=
rfl
#align pgame.move_right_mk SetTheory.PGame.moveRight_mk
-- TODO define this at the level of games, as well, and perhaps also for finsets of games.
/-- Construct a pre-game from list of pre-games describing the available moves for Left and Right.
-/
def ofLists (L R : List PGame.{u}) : PGame.{u} :=
mk (ULift (Fin L.length)) (ULift (Fin R.length)) (fun i => L.get i.down) fun j ↦ R.get j.down
#align pgame.of_lists SetTheory.PGame.ofLists
theorem leftMoves_ofLists (L R : List PGame) : (ofLists L R).LeftMoves = ULift (Fin L.length) :=
rfl
#align pgame.left_moves_of_lists SetTheory.PGame.leftMoves_ofLists
theorem rightMoves_ofLists (L R : List PGame) : (ofLists L R).RightMoves = ULift (Fin R.length) :=
rfl
#align pgame.right_moves_of_lists SetTheory.PGame.rightMoves_ofLists
/-- Converts a number into a left move for `ofLists`. -/
def toOfListsLeftMoves {L R : List PGame} : Fin L.length ≃ (ofLists L R).LeftMoves :=
((Equiv.cast (leftMoves_ofLists L R).symm).trans Equiv.ulift).symm
#align pgame.to_of_lists_left_moves SetTheory.PGame.toOfListsLeftMoves
/-- Converts a number into a right move for `ofLists`. -/
def toOfListsRightMoves {L R : List PGame} : Fin R.length ≃ (ofLists L R).RightMoves :=
((Equiv.cast (rightMoves_ofLists L R).symm).trans Equiv.ulift).symm
#align pgame.to_of_lists_right_moves SetTheory.PGame.toOfListsRightMoves
theorem ofLists_moveLeft {L R : List PGame} (i : Fin L.length) :
(ofLists L R).moveLeft (toOfListsLeftMoves i) = L.get i :=
rfl
#align pgame.of_lists_move_left SetTheory.PGame.ofLists_moveLeft
@[simp]
theorem ofLists_moveLeft' {L R : List PGame} (i : (ofLists L R).LeftMoves) :
(ofLists L R).moveLeft i = L.get (toOfListsLeftMoves.symm i) :=
rfl
#align pgame.of_lists_move_left' SetTheory.PGame.ofLists_moveLeft'
theorem ofLists_moveRight {L R : List PGame} (i : Fin R.length) :
(ofLists L R).moveRight (toOfListsRightMoves i) = R.get i :=
rfl
#align pgame.of_lists_move_right SetTheory.PGame.ofLists_moveRight
@[simp]
theorem ofLists_moveRight' {L R : List PGame} (i : (ofLists L R).RightMoves) :
(ofLists L R).moveRight i = R.get (toOfListsRightMoves.symm i) :=
rfl
#align pgame.of_lists_move_right' SetTheory.PGame.ofLists_moveRight'
/-- A variant of `PGame.recOn` expressed in terms of `PGame.moveLeft` and `PGame.moveRight`.
Both this and `PGame.recOn` describe Conway induction on games. -/
@[elab_as_elim]
def moveRecOn {C : PGame → Sort*} (x : PGame)
(IH : ∀ y : PGame, (∀ i, C (y.moveLeft i)) → (∀ j, C (y.moveRight j)) → C y) : C x :=
x.recOn fun yl yr yL yR => IH (mk yl yr yL yR)
#align pgame.move_rec_on SetTheory.PGame.moveRecOn
/-- `IsOption x y` means that `x` is either a left or right option for `y`. -/
@[mk_iff]
inductive IsOption : PGame → PGame → Prop
| moveLeft {x : PGame} (i : x.LeftMoves) : IsOption (x.moveLeft i) x
| moveRight {x : PGame} (i : x.RightMoves) : IsOption (x.moveRight i) x
#align pgame.is_option SetTheory.PGame.IsOption
theorem IsOption.mk_left {xl xr : Type u} (xL : xl → PGame) (xR : xr → PGame) (i : xl) :
(xL i).IsOption (mk xl xr xL xR) :=
@IsOption.moveLeft (mk _ _ _ _) i
#align pgame.is_option.mk_left SetTheory.PGame.IsOption.mk_left
theorem IsOption.mk_right {xl xr : Type u} (xL : xl → PGame) (xR : xr → PGame) (i : xr) :
(xR i).IsOption (mk xl xr xL xR) :=
@IsOption.moveRight (mk _ _ _ _) i
#align pgame.is_option.mk_right SetTheory.PGame.IsOption.mk_right
theorem wf_isOption : WellFounded IsOption :=
⟨fun x =>
moveRecOn x fun x IHl IHr =>
Acc.intro x fun y h => by
induction' h with _ i _ j
· exact IHl i
· exact IHr j⟩
#align pgame.wf_is_option SetTheory.PGame.wf_isOption
/-- `Subsequent x y` says that `x` can be obtained by playing some nonempty sequence of moves from
`y`. It is the transitive closure of `IsOption`. -/
def Subsequent : PGame → PGame → Prop :=
TransGen IsOption
#align pgame.subsequent SetTheory.PGame.Subsequent
instance : IsTrans _ Subsequent :=
inferInstanceAs <| IsTrans _ (TransGen _)
@[trans]
theorem Subsequent.trans {x y z} : Subsequent x y → Subsequent y z → Subsequent x z :=
TransGen.trans
#align pgame.subsequent.trans SetTheory.PGame.Subsequent.trans
theorem wf_subsequent : WellFounded Subsequent :=
wf_isOption.transGen
#align pgame.wf_subsequent SetTheory.PGame.wf_subsequent
instance : WellFoundedRelation PGame :=
⟨_, wf_subsequent⟩
@[simp]
theorem Subsequent.moveLeft {x : PGame} (i : x.LeftMoves) : Subsequent (x.moveLeft i) x :=
TransGen.single (IsOption.moveLeft i)
#align pgame.subsequent.move_left SetTheory.PGame.Subsequent.moveLeft
@[simp]
theorem Subsequent.moveRight {x : PGame} (j : x.RightMoves) : Subsequent (x.moveRight j) x :=
TransGen.single (IsOption.moveRight j)
#align pgame.subsequent.move_right SetTheory.PGame.Subsequent.moveRight
@[simp]
theorem Subsequent.mk_left {xl xr} (xL : xl → PGame) (xR : xr → PGame) (i : xl) :
Subsequent (xL i) (mk xl xr xL xR) :=
@Subsequent.moveLeft (mk _ _ _ _) i
#align pgame.subsequent.mk_left SetTheory.PGame.Subsequent.mk_left
@[simp]
theorem Subsequent.mk_right {xl xr} (xL : xl → PGame) (xR : xr → PGame) (j : xr) :
Subsequent (xR j) (mk xl xr xL xR) :=
@Subsequent.moveRight (mk _ _ _ _) j
#align pgame.subsequent.mk_right SetTheory.PGame.Subsequent.mk_right
/--
Discharges proof obligations of the form `⊢ Subsequent ..` arising in termination proofs
of definitions using well-founded recursion on `PGame`.
-/
macro "pgame_wf_tac" : tactic =>
`(tactic| solve_by_elim (config := { maxDepth := 8 })
[Prod.Lex.left, Prod.Lex.right, PSigma.Lex.left, PSigma.Lex.right,
Subsequent.moveLeft, Subsequent.moveRight, Subsequent.mk_left, Subsequent.mk_right,
Subsequent.trans] )
-- Register some consequences of pgame_wf_tac as simp-lemmas for convenience
-- (which are applied by default for WF goals)
-- This is different from mk_right from the POV of the simplifier,
-- because the unifier can't solve `xr =?= RightMoves (mk xl xr xL xR)` at reducible transparency.
@[simp]
theorem Subsequent.mk_right' (xL : xl → PGame) (xR : xr → PGame) (j : RightMoves (mk xl xr xL xR)) :
Subsequent (xR j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveRight_mk_left (xL : xl → PGame) (j) :
Subsequent ((xL i).moveRight j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveRight_mk_right (xR : xr → PGame) (j) :
Subsequent ((xR i).moveRight j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveLeft_mk_left (xL : xl → PGame) (j) :
Subsequent ((xL i).moveLeft j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveLeft_mk_right (xR : xr → PGame) (j) :
Subsequent ((xR i).moveLeft j) (mk xl xr xL xR) := by
pgame_wf_tac
-- Porting note: linter claims these lemmas don't simplify?
open Subsequent in attribute [nolint simpNF] mk_left mk_right mk_right'
moveRight_mk_left moveRight_mk_right moveLeft_mk_left moveLeft_mk_right
/-! ### Basic pre-games -/
/-- The pre-game `Zero` is defined by `0 = { | }`. -/
instance : Zero PGame :=
⟨⟨PEmpty, PEmpty, PEmpty.elim, PEmpty.elim⟩⟩
@[simp]
theorem zero_leftMoves : LeftMoves 0 = PEmpty :=
rfl
#align pgame.zero_left_moves SetTheory.PGame.zero_leftMoves
@[simp]
theorem zero_rightMoves : RightMoves 0 = PEmpty :=
rfl
#align pgame.zero_right_moves SetTheory.PGame.zero_rightMoves
instance isEmpty_zero_leftMoves : IsEmpty (LeftMoves 0) :=
instIsEmptyPEmpty
#align pgame.is_empty_zero_left_moves SetTheory.PGame.isEmpty_zero_leftMoves
instance isEmpty_zero_rightMoves : IsEmpty (RightMoves 0) :=
instIsEmptyPEmpty
#align pgame.is_empty_zero_right_moves SetTheory.PGame.isEmpty_zero_rightMoves
instance : Inhabited PGame :=
⟨0⟩
/-- The pre-game `One` is defined by `1 = { 0 | }`. -/
instance instOnePGame : One PGame :=
⟨⟨PUnit, PEmpty, fun _ => 0, PEmpty.elim⟩⟩
@[simp]
theorem one_leftMoves : LeftMoves 1 = PUnit :=
rfl
#align pgame.one_left_moves SetTheory.PGame.one_leftMoves
@[simp]
theorem one_moveLeft (x) : moveLeft 1 x = 0 :=
rfl
#align pgame.one_move_left SetTheory.PGame.one_moveLeft
@[simp]
theorem one_rightMoves : RightMoves 1 = PEmpty :=
rfl
#align pgame.one_right_moves SetTheory.PGame.one_rightMoves
instance uniqueOneLeftMoves : Unique (LeftMoves 1) :=
PUnit.unique
#align pgame.unique_one_left_moves SetTheory.PGame.uniqueOneLeftMoves
instance isEmpty_one_rightMoves : IsEmpty (RightMoves 1) :=
instIsEmptyPEmpty
#align pgame.is_empty_one_right_moves SetTheory.PGame.isEmpty_one_rightMoves
/-! ### Pre-game order relations -/
/-- The less or equal relation on pre-games.
If `0 ≤ x`, then Left can win `x` as the second player. -/
instance le : LE PGame :=
⟨Sym2.GameAdd.fix wf_isOption fun x y le =>
(∀ i, ¬le y (x.moveLeft i) (Sym2.GameAdd.snd_fst <| IsOption.moveLeft i)) ∧
∀ j, ¬le (y.moveRight j) x (Sym2.GameAdd.fst_snd <| IsOption.moveRight j)⟩
/-- The less or fuzzy relation on pre-games.
If `0 ⧏ x`, then Left can win `x` as the first player. -/
def LF (x y : PGame) : Prop :=
¬y ≤ x
#align pgame.lf SetTheory.PGame.LF
@[inherit_doc]
scoped infixl:50 " ⧏ " => PGame.LF
@[simp]
protected theorem not_le {x y : PGame} : ¬x ≤ y ↔ y ⧏ x :=
Iff.rfl
#align pgame.not_le SetTheory.PGame.not_le
@[simp]
theorem not_lf {x y : PGame} : ¬x ⧏ y ↔ y ≤ x :=
Classical.not_not
#align pgame.not_lf SetTheory.PGame.not_lf
theorem _root_.LE.le.not_gf {x y : PGame} : x ≤ y → ¬y ⧏ x :=
not_lf.2
#align has_le.le.not_gf LE.le.not_gf
theorem LF.not_ge {x y : PGame} : x ⧏ y → ¬y ≤ x :=
id
#align pgame.lf.not_ge SetTheory.PGame.LF.not_ge
/-- Definition of `x ≤ y` on pre-games, in terms of `⧏`.
The ordering here is chosen so that `And.left` refer to moves by Left, and `And.right` refer to
moves by Right. -/
theorem le_iff_forall_lf {x y : PGame} :
x ≤ y ↔ (∀ i, x.moveLeft i ⧏ y) ∧ ∀ j, x ⧏ y.moveRight j := by
unfold LE.le le
simp only
rw [Sym2.GameAdd.fix_eq]
rfl
#align pgame.le_iff_forall_lf SetTheory.PGame.le_iff_forall_lf
/-- Definition of `x ≤ y` on pre-games built using the constructor. -/
@[simp]
theorem mk_le_mk {xl xr xL xR yl yr yL yR} :
mk xl xr xL xR ≤ mk yl yr yL yR ↔ (∀ i, xL i ⧏ mk yl yr yL yR) ∧ ∀ j, mk xl xr xL xR ⧏ yR j :=
le_iff_forall_lf
#align pgame.mk_le_mk SetTheory.PGame.mk_le_mk
theorem le_of_forall_lf {x y : PGame} (h₁ : ∀ i, x.moveLeft i ⧏ y) (h₂ : ∀ j, x ⧏ y.moveRight j) :
x ≤ y :=
le_iff_forall_lf.2 ⟨h₁, h₂⟩
#align pgame.le_of_forall_lf SetTheory.PGame.le_of_forall_lf
/-- Definition of `x ⧏ y` on pre-games, in terms of `≤`.
The ordering here is chosen so that `or.inl` refer to moves by Left, and `or.inr` refer to
moves by Right. -/
theorem lf_iff_exists_le {x y : PGame} :
x ⧏ y ↔ (∃ i, x ≤ y.moveLeft i) ∨ ∃ j, x.moveRight j ≤ y := by
rw [LF, le_iff_forall_lf, not_and_or]
simp
#align pgame.lf_iff_exists_le SetTheory.PGame.lf_iff_exists_le
/-- Definition of `x ⧏ y` on pre-games built using the constructor. -/
@[simp]
theorem mk_lf_mk {xl xr xL xR yl yr yL yR} :
mk xl xr xL xR ⧏ mk yl yr yL yR ↔ (∃ i, mk xl xr xL xR ≤ yL i) ∨ ∃ j, xR j ≤ mk yl yr yL yR :=
lf_iff_exists_le
#align pgame.mk_lf_mk SetTheory.PGame.mk_lf_mk
theorem le_or_gf (x y : PGame) : x ≤ y ∨ y ⧏ x := by
rw [← PGame.not_le]
apply em
#align pgame.le_or_gf SetTheory.PGame.le_or_gf
theorem moveLeft_lf_of_le {x y : PGame} (h : x ≤ y) (i) : x.moveLeft i ⧏ y :=
(le_iff_forall_lf.1 h).1 i
#align pgame.move_left_lf_of_le SetTheory.PGame.moveLeft_lf_of_le
alias _root_.LE.le.moveLeft_lf := moveLeft_lf_of_le
#align has_le.le.move_left_lf LE.le.moveLeft_lf
theorem lf_moveRight_of_le {x y : PGame} (h : x ≤ y) (j) : x ⧏ y.moveRight j :=
(le_iff_forall_lf.1 h).2 j
#align pgame.lf_move_right_of_le SetTheory.PGame.lf_moveRight_of_le
alias _root_.LE.le.lf_moveRight := lf_moveRight_of_le
#align has_le.le.lf_move_right LE.le.lf_moveRight
theorem lf_of_moveRight_le {x y : PGame} {j} (h : x.moveRight j ≤ y) : x ⧏ y :=
lf_iff_exists_le.2 <| Or.inr ⟨j, h⟩
#align pgame.lf_of_move_right_le SetTheory.PGame.lf_of_moveRight_le
theorem lf_of_le_moveLeft {x y : PGame} {i} (h : x ≤ y.moveLeft i) : x ⧏ y :=
lf_iff_exists_le.2 <| Or.inl ⟨i, h⟩
#align pgame.lf_of_le_move_left SetTheory.PGame.lf_of_le_moveLeft
theorem lf_of_le_mk {xl xr xL xR y} : mk xl xr xL xR ≤ y → ∀ i, xL i ⧏ y :=
moveLeft_lf_of_le
#align pgame.lf_of_le_mk SetTheory.PGame.lf_of_le_mk
theorem lf_of_mk_le {x yl yr yL yR} : x ≤ mk yl yr yL yR → ∀ j, x ⧏ yR j :=
lf_moveRight_of_le
#align pgame.lf_of_mk_le SetTheory.PGame.lf_of_mk_le
theorem mk_lf_of_le {xl xr y j} (xL) {xR : xr → PGame} : xR j ≤ y → mk xl xr xL xR ⧏ y :=
@lf_of_moveRight_le (mk _ _ _ _) y j
#align pgame.mk_lf_of_le SetTheory.PGame.mk_lf_of_le
theorem lf_mk_of_le {x yl yr} {yL : yl → PGame} (yR) {i} : x ≤ yL i → x ⧏ mk yl yr yL yR :=
@lf_of_le_moveLeft x (mk _ _ _ _) i
#align pgame.lf_mk_of_le SetTheory.PGame.lf_mk_of_le
/- We prove that `x ≤ y → y ≤ z → x ≤ z` inductively, by also simultaneously proving its cyclic
reorderings. This auxiliary lemma is used during said induction. -/
private theorem le_trans_aux {x y z : PGame}
(h₁ : ∀ {i}, y ≤ z → z ≤ x.moveLeft i → y ≤ x.moveLeft i)
(h₂ : ∀ {j}, z.moveRight j ≤ x → x ≤ y → z.moveRight j ≤ y) (hxy : x ≤ y) (hyz : y ≤ z) :
x ≤ z :=
le_of_forall_lf (fun i => PGame.not_le.1 fun h => (h₁ hyz h).not_gf <| hxy.moveLeft_lf i)
fun j => PGame.not_le.1 fun h => (h₂ h hxy).not_gf <| hyz.lf_moveRight j
instance : Preorder PGame :=
{ PGame.le with
le_refl := fun x => by
induction' x with _ _ _ _ IHl IHr
exact
le_of_forall_lf (fun i => lf_of_le_moveLeft (IHl i)) fun i => lf_of_moveRight_le (IHr i)
le_trans := by
suffices
∀ {x y z : PGame},
(x ≤ y → y ≤ z → x ≤ z) ∧ (y ≤ z → z ≤ x → y ≤ x) ∧ (z ≤ x → x ≤ y → z ≤ y) from
fun x y z => this.1
intro x y z
induction' x with xl xr xL xR IHxl IHxr generalizing y z
induction' y with yl yr yL yR IHyl IHyr generalizing z
induction' z with zl zr zL zR IHzl IHzr
exact
⟨le_trans_aux (fun {i} => (IHxl i).2.1) fun {j} => (IHzr j).2.2,
le_trans_aux (fun {i} => (IHyl i).2.2) fun {j} => (IHxr j).1,
le_trans_aux (fun {i} => (IHzl i).1) fun {j} => (IHyr j).2.1⟩
lt := fun x y => x ≤ y ∧ x ⧏ y }
theorem lt_iff_le_and_lf {x y : PGame} : x < y ↔ x ≤ y ∧ x ⧏ y :=
Iff.rfl
#align pgame.lt_iff_le_and_lf SetTheory.PGame.lt_iff_le_and_lf
theorem lt_of_le_of_lf {x y : PGame} (h₁ : x ≤ y) (h₂ : x ⧏ y) : x < y :=
⟨h₁, h₂⟩
#align pgame.lt_of_le_of_lf SetTheory.PGame.lt_of_le_of_lf
theorem lf_of_lt {x y : PGame} (h : x < y) : x ⧏ y :=
h.2
#align pgame.lf_of_lt SetTheory.PGame.lf_of_lt
alias _root_.LT.lt.lf := lf_of_lt
#align has_lt.lt.lf LT.lt.lf
theorem lf_irrefl (x : PGame) : ¬x ⧏ x :=
le_rfl.not_gf
#align pgame.lf_irrefl SetTheory.PGame.lf_irrefl
instance : IsIrrefl _ (· ⧏ ·) :=
⟨lf_irrefl⟩
@[trans]
theorem lf_of_le_of_lf {x y z : PGame} (h₁ : x ≤ y) (h₂ : y ⧏ z) : x ⧏ z := by
rw [← PGame.not_le] at h₂ ⊢
exact fun h₃ => h₂ (h₃.trans h₁)
#align pgame.lf_of_le_of_lf SetTheory.PGame.lf_of_le_of_lf
-- Porting note (#10754): added instance
instance : Trans (· ≤ ·) (· ⧏ ·) (· ⧏ ·) := ⟨lf_of_le_of_lf⟩
@[trans]
theorem lf_of_lf_of_le {x y z : PGame} (h₁ : x ⧏ y) (h₂ : y ≤ z) : x ⧏ z := by
rw [← PGame.not_le] at h₁ ⊢
exact fun h₃ => h₁ (h₂.trans h₃)
#align pgame.lf_of_lf_of_le SetTheory.PGame.lf_of_lf_of_le
-- Porting note (#10754): added instance
instance : Trans (· ⧏ ·) (· ≤ ·) (· ⧏ ·) := ⟨lf_of_lf_of_le⟩
alias _root_.LE.le.trans_lf := lf_of_le_of_lf
#align has_le.le.trans_lf LE.le.trans_lf
alias LF.trans_le := lf_of_lf_of_le
#align pgame.lf.trans_le SetTheory.PGame.LF.trans_le
@[trans]
theorem lf_of_lt_of_lf {x y z : PGame} (h₁ : x < y) (h₂ : y ⧏ z) : x ⧏ z :=
h₁.le.trans_lf h₂
#align pgame.lf_of_lt_of_lf SetTheory.PGame.lf_of_lt_of_lf
@[trans]
theorem lf_of_lf_of_lt {x y z : PGame} (h₁ : x ⧏ y) (h₂ : y < z) : x ⧏ z :=
h₁.trans_le h₂.le
#align pgame.lf_of_lf_of_lt SetTheory.PGame.lf_of_lf_of_lt
alias _root_.LT.lt.trans_lf := lf_of_lt_of_lf
#align has_lt.lt.trans_lf LT.lt.trans_lf
alias LF.trans_lt := lf_of_lf_of_lt
#align pgame.lf.trans_lt SetTheory.PGame.LF.trans_lt
theorem moveLeft_lf {x : PGame} : ∀ i, x.moveLeft i ⧏ x :=
le_rfl.moveLeft_lf
#align pgame.move_left_lf SetTheory.PGame.moveLeft_lf
theorem lf_moveRight {x : PGame} : ∀ j, x ⧏ x.moveRight j :=
le_rfl.lf_moveRight
#align pgame.lf_move_right SetTheory.PGame.lf_moveRight
theorem lf_mk {xl xr} (xL : xl → PGame) (xR : xr → PGame) (i) : xL i ⧏ mk xl xr xL xR :=
@moveLeft_lf (mk _ _ _ _) i
#align pgame.lf_mk SetTheory.PGame.lf_mk
theorem mk_lf {xl xr} (xL : xl → PGame) (xR : xr → PGame) (j) : mk xl xr xL xR ⧏ xR j :=
@lf_moveRight (mk _ _ _ _) j
#align pgame.mk_lf SetTheory.PGame.mk_lf
/-- This special case of `PGame.le_of_forall_lf` is useful when dealing with surreals, where `<` is
preferred over `⧏`. -/
theorem le_of_forall_lt {x y : PGame} (h₁ : ∀ i, x.moveLeft i < y) (h₂ : ∀ j, x < y.moveRight j) :
x ≤ y :=
le_of_forall_lf (fun i => (h₁ i).lf) fun i => (h₂ i).lf
#align pgame.le_of_forall_lt SetTheory.PGame.le_of_forall_lt
/-- The definition of `x ≤ y` on pre-games, in terms of `≤` two moves later. -/
theorem le_def {x y : PGame} :
x ≤ y ↔
(∀ i, (∃ i', x.moveLeft i ≤ y.moveLeft i') ∨ ∃ j, (x.moveLeft i).moveRight j ≤ y) ∧
∀ j, (∃ i, x ≤ (y.moveRight j).moveLeft i) ∨ ∃ j', x.moveRight j' ≤ y.moveRight j := by
rw [le_iff_forall_lf]
conv =>
lhs
simp only [lf_iff_exists_le]
#align pgame.le_def SetTheory.PGame.le_def
/-- The definition of `x ⧏ y` on pre-games, in terms of `⧏` two moves later. -/
theorem lf_def {x y : PGame} :
x ⧏ y ↔
(∃ i, (∀ i', x.moveLeft i' ⧏ y.moveLeft i) ∧ ∀ j, x ⧏ (y.moveLeft i).moveRight j) ∨
∃ j, (∀ i, (x.moveRight j).moveLeft i ⧏ y) ∧ ∀ j', x.moveRight j ⧏ y.moveRight j' := by
rw [lf_iff_exists_le]
conv =>
lhs
simp only [le_iff_forall_lf]
#align pgame.lf_def SetTheory.PGame.lf_def
/-- The definition of `0 ≤ x` on pre-games, in terms of `0 ⧏`. -/
theorem zero_le_lf {x : PGame} : 0 ≤ x ↔ ∀ j, 0 ⧏ x.moveRight j := by
rw [le_iff_forall_lf]
simp
#align pgame.zero_le_lf SetTheory.PGame.zero_le_lf
/-- The definition of `x ≤ 0` on pre-games, in terms of `⧏ 0`. -/
theorem le_zero_lf {x : PGame} : x ≤ 0 ↔ ∀ i, x.moveLeft i ⧏ 0 := by
rw [le_iff_forall_lf]
simp
#align pgame.le_zero_lf SetTheory.PGame.le_zero_lf
/-- The definition of `0 ⧏ x` on pre-games, in terms of `0 ≤`. -/
theorem zero_lf_le {x : PGame} : 0 ⧏ x ↔ ∃ i, 0 ≤ x.moveLeft i := by
rw [lf_iff_exists_le]
simp
#align pgame.zero_lf_le SetTheory.PGame.zero_lf_le
/-- The definition of `x ⧏ 0` on pre-games, in terms of `≤ 0`. -/
theorem lf_zero_le {x : PGame} : x ⧏ 0 ↔ ∃ j, x.moveRight j ≤ 0 := by
rw [lf_iff_exists_le]
simp
#align pgame.lf_zero_le SetTheory.PGame.lf_zero_le
/-- The definition of `0 ≤ x` on pre-games, in terms of `0 ≤` two moves later. -/
theorem zero_le {x : PGame} : 0 ≤ x ↔ ∀ j, ∃ i, 0 ≤ (x.moveRight j).moveLeft i := by
rw [le_def]
simp
#align pgame.zero_le SetTheory.PGame.zero_le
/-- The definition of `x ≤ 0` on pre-games, in terms of `≤ 0` two moves later. -/
theorem le_zero {x : PGame} : x ≤ 0 ↔ ∀ i, ∃ j, (x.moveLeft i).moveRight j ≤ 0 := by
rw [le_def]
simp
#align pgame.le_zero SetTheory.PGame.le_zero
/-- The definition of `0 ⧏ x` on pre-games, in terms of `0 ⧏` two moves later. -/
theorem zero_lf {x : PGame} : 0 ⧏ x ↔ ∃ i, ∀ j, 0 ⧏ (x.moveLeft i).moveRight j := by
rw [lf_def]
simp
#align pgame.zero_lf SetTheory.PGame.zero_lf
/-- The definition of `x ⧏ 0` on pre-games, in terms of `⧏ 0` two moves later. -/
theorem lf_zero {x : PGame} : x ⧏ 0 ↔ ∃ j, ∀ i, (x.moveRight j).moveLeft i ⧏ 0 := by
rw [lf_def]
simp
#align pgame.lf_zero SetTheory.PGame.lf_zero
@[simp]
theorem zero_le_of_isEmpty_rightMoves (x : PGame) [IsEmpty x.RightMoves] : 0 ≤ x :=
zero_le.2 isEmptyElim
#align pgame.zero_le_of_is_empty_right_moves SetTheory.PGame.zero_le_of_isEmpty_rightMoves
@[simp]
theorem le_zero_of_isEmpty_leftMoves (x : PGame) [IsEmpty x.LeftMoves] : x ≤ 0 :=
le_zero.2 isEmptyElim
#align pgame.le_zero_of_is_empty_left_moves SetTheory.PGame.le_zero_of_isEmpty_leftMoves
/-- Given a game won by the right player when they play second, provide a response to any move by
left. -/
noncomputable def rightResponse {x : PGame} (h : x ≤ 0) (i : x.LeftMoves) :
(x.moveLeft i).RightMoves :=
Classical.choose <| (le_zero.1 h) i
#align pgame.right_response SetTheory.PGame.rightResponse
/-- Show that the response for right provided by `rightResponse` preserves the right-player-wins
condition. -/
theorem rightResponse_spec {x : PGame} (h : x ≤ 0) (i : x.LeftMoves) :
(x.moveLeft i).moveRight (rightResponse h i) ≤ 0 :=
Classical.choose_spec <| (le_zero.1 h) i
#align pgame.right_response_spec SetTheory.PGame.rightResponse_spec
/-- Given a game won by the left player when they play second, provide a response to any move by
right. -/
noncomputable def leftResponse {x : PGame} (h : 0 ≤ x) (j : x.RightMoves) :
(x.moveRight j).LeftMoves :=
Classical.choose <| (zero_le.1 h) j
#align pgame.left_response SetTheory.PGame.leftResponse
/-- Show that the response for left provided by `leftResponse` preserves the left-player-wins
condition. -/
theorem leftResponse_spec {x : PGame} (h : 0 ≤ x) (j : x.RightMoves) :
0 ≤ (x.moveRight j).moveLeft (leftResponse h j) :=
Classical.choose_spec <| (zero_le.1 h) j
#align pgame.left_response_spec SetTheory.PGame.leftResponse_spec
#noalign pgame.upper_bound
#noalign pgame.upper_bound_right_moves_empty
#noalign pgame.le_upper_bound
#noalign pgame.upper_bound_mem_upper_bounds
/-- A small family of pre-games is bounded above. -/
lemma bddAbove_range_of_small [Small.{u} ι] (f : ι → PGame.{u}) : BddAbove (Set.range f) := by
let x : PGame.{u} := ⟨Σ i, (f $ (equivShrink.{u} ι).symm i).LeftMoves, PEmpty,
fun x ↦ moveLeft _ x.2, PEmpty.elim⟩
refine ⟨x, Set.forall_mem_range.2 fun i ↦ ?_⟩
rw [← (equivShrink ι).symm_apply_apply i, le_iff_forall_lf]
simpa [x] using fun j ↦ @moveLeft_lf x ⟨equivShrink ι i, j⟩
/-- A small set of pre-games is bounded above. -/
lemma bddAbove_of_small (s : Set PGame.{u}) [Small.{u} s] : BddAbove s := by
simpa using bddAbove_range_of_small (Subtype.val : s → PGame.{u})
#align pgame.bdd_above_of_small SetTheory.PGame.bddAbove_of_small
#noalign pgame.lower_bound
#noalign pgame.lower_bound_left_moves_empty
#noalign pgame.lower_bound_le
#noalign pgame.lower_bound_mem_lower_bounds
/-- A small family of pre-games is bounded below. -/
lemma bddBelow_range_of_small [Small.{u} ι] (f : ι → PGame.{u}) : BddBelow (Set.range f) := by
let x : PGame.{u} := ⟨PEmpty, Σ i, (f $ (equivShrink.{u} ι).symm i).RightMoves, PEmpty.elim,
fun x ↦ moveRight _ x.2⟩
refine ⟨x, Set.forall_mem_range.2 fun i ↦ ?_⟩
rw [← (equivShrink ι).symm_apply_apply i, le_iff_forall_lf]
simpa [x] using fun j ↦ @lf_moveRight x ⟨equivShrink ι i, j⟩
/-- A small set of pre-games is bounded below. -/
lemma bddBelow_of_small (s : Set PGame.{u}) [Small.{u} s] : BddBelow s := by
simpa using bddBelow_range_of_small (Subtype.val : s → PGame.{u})
#align pgame.bdd_below_of_small SetTheory.PGame.bddBelow_of_small
/-- The equivalence relation on pre-games. Two pre-games `x`, `y` are equivalent if `x ≤ y` and
`y ≤ x`.
If `x ≈ 0`, then the second player can always win `x`. -/
def Equiv (x y : PGame) : Prop :=
x ≤ y ∧ y ≤ x
#align pgame.equiv SetTheory.PGame.Equiv
-- Porting note: deleted the scoped notation due to notation overloading with the setoid
-- instance and this causes the PGame.equiv docstring to not show up on hover.
instance : IsEquiv _ PGame.Equiv where
refl _ := ⟨le_rfl, le_rfl⟩
trans := fun _ _ _ ⟨xy, yx⟩ ⟨yz, zy⟩ => ⟨xy.trans yz, zy.trans yx⟩
symm _ _ := And.symm
-- Porting note: moved the setoid instance from Basic.lean to here
instance setoid : Setoid PGame :=
⟨Equiv, refl, symm, Trans.trans⟩
#align pgame.setoid SetTheory.PGame.setoid
theorem Equiv.le {x y : PGame} (h : x ≈ y) : x ≤ y :=
h.1
#align pgame.equiv.le SetTheory.PGame.Equiv.le
theorem Equiv.ge {x y : PGame} (h : x ≈ y) : y ≤ x :=
h.2
#align pgame.equiv.ge SetTheory.PGame.Equiv.ge
@[refl, simp]
theorem equiv_rfl {x : PGame} : x ≈ x :=
refl x
#align pgame.equiv_rfl SetTheory.PGame.equiv_rfl
theorem equiv_refl (x : PGame) : x ≈ x :=
refl x
#align pgame.equiv_refl SetTheory.PGame.equiv_refl
@[symm]
protected theorem Equiv.symm {x y : PGame} : (x ≈ y) → (y ≈ x) :=
symm
#align pgame.equiv.symm SetTheory.PGame.Equiv.symm
@[trans]
protected theorem Equiv.trans {x y z : PGame} : (x ≈ y) → (y ≈ z) → (x ≈ z) :=
_root_.trans
#align pgame.equiv.trans SetTheory.PGame.Equiv.trans
protected theorem equiv_comm {x y : PGame} : (x ≈ y) ↔ (y ≈ x) :=
comm
#align pgame.equiv_comm SetTheory.PGame.equiv_comm
theorem equiv_of_eq {x y : PGame} (h : x = y) : x ≈ y := by subst h; rfl
#align pgame.equiv_of_eq SetTheory.PGame.equiv_of_eq
@[trans]
theorem le_of_le_of_equiv {x y z : PGame} (h₁ : x ≤ y) (h₂ : y ≈ z) : x ≤ z :=
h₁.trans h₂.1
#align pgame.le_of_le_of_equiv SetTheory.PGame.le_of_le_of_equiv
instance : Trans
((· ≤ ·) : PGame → PGame → Prop)
((· ≈ ·) : PGame → PGame → Prop)
((· ≤ ·) : PGame → PGame → Prop) where
trans := le_of_le_of_equiv
@[trans]
theorem le_of_equiv_of_le {x y z : PGame} (h₁ : x ≈ y) : y ≤ z → x ≤ z :=
h₁.1.trans
#align pgame.le_of_equiv_of_le SetTheory.PGame.le_of_equiv_of_le
instance : Trans
((· ≈ ·) : PGame → PGame → Prop)
((· ≤ ·) : PGame → PGame → Prop)
((· ≤ ·) : PGame → PGame → Prop) where
trans := le_of_equiv_of_le
theorem LF.not_equiv {x y : PGame} (h : x ⧏ y) : ¬(x ≈ y) := fun h' => h.not_ge h'.2
#align pgame.lf.not_equiv SetTheory.PGame.LF.not_equiv
theorem LF.not_equiv' {x y : PGame} (h : x ⧏ y) : ¬(y ≈ x) := fun h' => h.not_ge h'.1
#align pgame.lf.not_equiv' SetTheory.PGame.LF.not_equiv'
theorem LF.not_gt {x y : PGame} (h : x ⧏ y) : ¬y < x := fun h' => h.not_ge h'.le
#align pgame.lf.not_gt SetTheory.PGame.LF.not_gt
theorem le_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) (h : x₁ ≤ y₁) : x₂ ≤ y₂ :=
hx.2.trans (h.trans hy.1)
#align pgame.le_congr_imp SetTheory.PGame.le_congr_imp
theorem le_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ≤ y₁ ↔ x₂ ≤ y₂ :=
⟨le_congr_imp hx hy, le_congr_imp (Equiv.symm hx) (Equiv.symm hy)⟩
#align pgame.le_congr SetTheory.PGame.le_congr
theorem le_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ ≤ y ↔ x₂ ≤ y :=
le_congr hx equiv_rfl
#align pgame.le_congr_left SetTheory.PGame.le_congr_left
theorem le_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x ≤ y₁ ↔ x ≤ y₂ :=
le_congr equiv_rfl hy
#align pgame.le_congr_right SetTheory.PGame.le_congr_right
theorem lf_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ⧏ y₁ ↔ x₂ ⧏ y₂ :=
PGame.not_le.symm.trans <| (not_congr (le_congr hy hx)).trans PGame.not_le
#align pgame.lf_congr SetTheory.PGame.lf_congr
theorem lf_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ⧏ y₁ → x₂ ⧏ y₂ :=
(lf_congr hx hy).1
#align pgame.lf_congr_imp SetTheory.PGame.lf_congr_imp
theorem lf_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ ⧏ y ↔ x₂ ⧏ y :=
lf_congr hx equiv_rfl
#align pgame.lf_congr_left SetTheory.PGame.lf_congr_left
theorem lf_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x ⧏ y₁ ↔ x ⧏ y₂ :=
lf_congr equiv_rfl hy
#align pgame.lf_congr_right SetTheory.PGame.lf_congr_right
@[trans]
theorem lf_of_lf_of_equiv {x y z : PGame} (h₁ : x ⧏ y) (h₂ : y ≈ z) : x ⧏ z :=
lf_congr_imp equiv_rfl h₂ h₁
#align pgame.lf_of_lf_of_equiv SetTheory.PGame.lf_of_lf_of_equiv
@[trans]
theorem lf_of_equiv_of_lf {x y z : PGame} (h₁ : x ≈ y) : y ⧏ z → x ⧏ z :=
lf_congr_imp (Equiv.symm h₁) equiv_rfl
#align pgame.lf_of_equiv_of_lf SetTheory.PGame.lf_of_equiv_of_lf
@[trans]
theorem lt_of_lt_of_equiv {x y z : PGame} (h₁ : x < y) (h₂ : y ≈ z) : x < z :=
h₁.trans_le h₂.1
#align pgame.lt_of_lt_of_equiv SetTheory.PGame.lt_of_lt_of_equiv
@[trans]
theorem lt_of_equiv_of_lt {x y z : PGame} (h₁ : x ≈ y) : y < z → x < z :=
h₁.1.trans_lt
#align pgame.lt_of_equiv_of_lt SetTheory.PGame.lt_of_equiv_of_lt
instance : Trans
((· ≈ ·) : PGame → PGame → Prop)
((· < ·) : PGame → PGame → Prop)
((· < ·) : PGame → PGame → Prop) where
trans := lt_of_equiv_of_lt
theorem lt_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) (h : x₁ < y₁) : x₂ < y₂ :=
hx.2.trans_lt (h.trans_le hy.1)
#align pgame.lt_congr_imp SetTheory.PGame.lt_congr_imp
theorem lt_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ < y₁ ↔ x₂ < y₂ :=
⟨lt_congr_imp hx hy, lt_congr_imp (Equiv.symm hx) (Equiv.symm hy)⟩
#align pgame.lt_congr SetTheory.PGame.lt_congr
theorem lt_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ < y ↔ x₂ < y :=
lt_congr hx equiv_rfl
#align pgame.lt_congr_left SetTheory.PGame.lt_congr_left
theorem lt_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x < y₁ ↔ x < y₂ :=
lt_congr equiv_rfl hy
#align pgame.lt_congr_right SetTheory.PGame.lt_congr_right
theorem lt_or_equiv_of_le {x y : PGame} (h : x ≤ y) : x < y ∨ (x ≈ y) :=
and_or_left.mp ⟨h, (em <| y ≤ x).symm.imp_left PGame.not_le.1⟩
#align pgame.lt_or_equiv_of_le SetTheory.PGame.lt_or_equiv_of_le
theorem lf_or_equiv_or_gf (x y : PGame) : x ⧏ y ∨ (x ≈ y) ∨ y ⧏ x := by
by_cases h : x ⧏ y
· exact Or.inl h
· right
cases' lt_or_equiv_of_le (PGame.not_lf.1 h) with h' h'
· exact Or.inr h'.lf
· exact Or.inl (Equiv.symm h')
#align pgame.lf_or_equiv_or_gf SetTheory.PGame.lf_or_equiv_or_gf
theorem equiv_congr_left {y₁ y₂ : PGame} : (y₁ ≈ y₂) ↔ ∀ x₁, (x₁ ≈ y₁) ↔ (x₁ ≈ y₂) :=
⟨fun h _ => ⟨fun h' => Equiv.trans h' h, fun h' => Equiv.trans h' (Equiv.symm h)⟩,
fun h => (h y₁).1 <| equiv_rfl⟩
#align pgame.equiv_congr_left SetTheory.PGame.equiv_congr_left
theorem equiv_congr_right {x₁ x₂ : PGame} : (x₁ ≈ x₂) ↔ ∀ y₁, (x₁ ≈ y₁) ↔ (x₂ ≈ y₁) :=
⟨fun h _ => ⟨fun h' => Equiv.trans (Equiv.symm h) h', fun h' => Equiv.trans h h'⟩,
fun h => (h x₂).2 <| equiv_rfl⟩
#align pgame.equiv_congr_right SetTheory.PGame.equiv_congr_right
theorem equiv_of_mk_equiv {x y : PGame} (L : x.LeftMoves ≃ y.LeftMoves)
(R : x.RightMoves ≃ y.RightMoves) (hl : ∀ i, x.moveLeft i ≈ y.moveLeft (L i))
(hr : ∀ j, x.moveRight j ≈ y.moveRight (R j)) : x ≈ y := by
constructor <;> rw [le_def]
· exact ⟨fun i => Or.inl ⟨_, (hl i).1⟩, fun j => Or.inr ⟨_, by simpa using (hr (R.symm j)).1⟩⟩
· exact ⟨fun i => Or.inl ⟨_, by simpa using (hl (L.symm i)).2⟩, fun j => Or.inr ⟨_, (hr j).2⟩⟩
#align pgame.equiv_of_mk_equiv SetTheory.PGame.equiv_of_mk_equiv
/-- The fuzzy, confused, or incomparable relation on pre-games.
If `x ‖ 0`, then the first player can always win `x`. -/
def Fuzzy (x y : PGame) : Prop :=
x ⧏ y ∧ y ⧏ x
#align pgame.fuzzy SetTheory.PGame.Fuzzy
@[inherit_doc]
scoped infixl:50 " ‖ " => PGame.Fuzzy
@[symm]
theorem Fuzzy.swap {x y : PGame} : x ‖ y → y ‖ x :=
And.symm
#align pgame.fuzzy.swap SetTheory.PGame.Fuzzy.swap
instance : IsSymm _ (· ‖ ·) :=
⟨fun _ _ => Fuzzy.swap⟩
theorem Fuzzy.swap_iff {x y : PGame} : x ‖ y ↔ y ‖ x :=
⟨Fuzzy.swap, Fuzzy.swap⟩
#align pgame.fuzzy.swap_iff SetTheory.PGame.Fuzzy.swap_iff
theorem fuzzy_irrefl (x : PGame) : ¬x ‖ x := fun h => lf_irrefl x h.1
#align pgame.fuzzy_irrefl SetTheory.PGame.fuzzy_irrefl
instance : IsIrrefl _ (· ‖ ·) :=
⟨fuzzy_irrefl⟩
theorem lf_iff_lt_or_fuzzy {x y : PGame} : x ⧏ y ↔ x < y ∨ x ‖ y := by
simp only [lt_iff_le_and_lf, Fuzzy, ← PGame.not_le]
tauto
#align pgame.lf_iff_lt_or_fuzzy SetTheory.PGame.lf_iff_lt_or_fuzzy
theorem lf_of_fuzzy {x y : PGame} (h : x ‖ y) : x ⧏ y :=
lf_iff_lt_or_fuzzy.2 (Or.inr h)
#align pgame.lf_of_fuzzy SetTheory.PGame.lf_of_fuzzy
alias Fuzzy.lf := lf_of_fuzzy
#align pgame.fuzzy.lf SetTheory.PGame.Fuzzy.lf
theorem lt_or_fuzzy_of_lf {x y : PGame} : x ⧏ y → x < y ∨ x ‖ y :=
lf_iff_lt_or_fuzzy.1
#align pgame.lt_or_fuzzy_of_lf SetTheory.PGame.lt_or_fuzzy_of_lf
theorem Fuzzy.not_equiv {x y : PGame} (h : x ‖ y) : ¬(x ≈ y) := fun h' => h'.1.not_gf h.2
#align pgame.fuzzy.not_equiv SetTheory.PGame.Fuzzy.not_equiv
theorem Fuzzy.not_equiv' {x y : PGame} (h : x ‖ y) : ¬(y ≈ x) := fun h' => h'.2.not_gf h.2
#align pgame.fuzzy.not_equiv' SetTheory.PGame.Fuzzy.not_equiv'
theorem not_fuzzy_of_le {x y : PGame} (h : x ≤ y) : ¬x ‖ y := fun h' => h'.2.not_ge h
#align pgame.not_fuzzy_of_le SetTheory.PGame.not_fuzzy_of_le
theorem not_fuzzy_of_ge {x y : PGame} (h : y ≤ x) : ¬x ‖ y := fun h' => h'.1.not_ge h
#align pgame.not_fuzzy_of_ge SetTheory.PGame.not_fuzzy_of_ge
theorem Equiv.not_fuzzy {x y : PGame} (h : x ≈ y) : ¬x ‖ y :=
not_fuzzy_of_le h.1
#align pgame.equiv.not_fuzzy SetTheory.PGame.Equiv.not_fuzzy
theorem Equiv.not_fuzzy' {x y : PGame} (h : x ≈ y) : ¬y ‖ x :=
not_fuzzy_of_le h.2
#align pgame.equiv.not_fuzzy' SetTheory.PGame.Equiv.not_fuzzy'
theorem fuzzy_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ‖ y₁ ↔ x₂ ‖ y₂ :=
show _ ∧ _ ↔ _ ∧ _ by rw [lf_congr hx hy, lf_congr hy hx]
#align pgame.fuzzy_congr SetTheory.PGame.fuzzy_congr
theorem fuzzy_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ‖ y₁ → x₂ ‖ y₂ :=
(fuzzy_congr hx hy).1
#align pgame.fuzzy_congr_imp SetTheory.PGame.fuzzy_congr_imp
theorem fuzzy_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ ‖ y ↔ x₂ ‖ y :=
fuzzy_congr hx equiv_rfl
#align pgame.fuzzy_congr_left SetTheory.PGame.fuzzy_congr_left
theorem fuzzy_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x ‖ y₁ ↔ x ‖ y₂ :=
fuzzy_congr equiv_rfl hy
#align pgame.fuzzy_congr_right SetTheory.PGame.fuzzy_congr_right
@[trans]
theorem fuzzy_of_fuzzy_of_equiv {x y z : PGame} (h₁ : x ‖ y) (h₂ : y ≈ z) : x ‖ z :=
(fuzzy_congr_right h₂).1 h₁
#align pgame.fuzzy_of_fuzzy_of_equiv SetTheory.PGame.fuzzy_of_fuzzy_of_equiv
@[trans]
theorem fuzzy_of_equiv_of_fuzzy {x y z : PGame} (h₁ : x ≈ y) (h₂ : y ‖ z) : x ‖ z :=
(fuzzy_congr_left h₁).2 h₂
#align pgame.fuzzy_of_equiv_of_fuzzy SetTheory.PGame.fuzzy_of_equiv_of_fuzzy
/-- Exactly one of the following is true (although we don't prove this here). -/
theorem lt_or_equiv_or_gt_or_fuzzy (x y : PGame) : x < y ∨ (x ≈ y) ∨ y < x ∨ x ‖ y := by
cases' le_or_gf x y with h₁ h₁ <;> cases' le_or_gf y x with h₂ h₂
· right
left
exact ⟨h₁, h₂⟩
· left
exact ⟨h₁, h₂⟩
· right
right
left
exact ⟨h₂, h₁⟩
· right
right
right
exact ⟨h₂, h₁⟩
#align pgame.lt_or_equiv_or_gt_or_fuzzy SetTheory.PGame.lt_or_equiv_or_gt_or_fuzzy
theorem lt_or_equiv_or_gf (x y : PGame) : x < y ∨ (x ≈ y) ∨ y ⧏ x := by
rw [lf_iff_lt_or_fuzzy, Fuzzy.swap_iff]
exact lt_or_equiv_or_gt_or_fuzzy x y
#align pgame.lt_or_equiv_or_gf SetTheory.PGame.lt_or_equiv_or_gf
/-! ### Relabellings -/
/-- `Relabelling x y` says that `x` and `y` are really the same game, just dressed up differently.
Specifically, there is a bijection between the moves for Left in `x` and in `y`, and similarly
for Right, and under these bijections we inductively have `Relabelling`s for the consequent games.
-/
inductive Relabelling : PGame.{u} → PGame.{u} → Type (u + 1)
|
mk :
∀ {x y : PGame} (L : x.LeftMoves ≃ y.LeftMoves) (R : x.RightMoves ≃ y.RightMoves),
(∀ i, Relabelling (x.moveLeft i) (y.moveLeft (L i))) →
(∀ j, Relabelling (x.moveRight j) (y.moveRight (R j))) → Relabelling x y
#align pgame.relabelling SetTheory.PGame.Relabelling
@[inherit_doc]
scoped infixl:50 " ≡r " => PGame.Relabelling
namespace Relabelling
variable {x y : PGame.{u}}
/-- A constructor for relabellings swapping the equivalences. -/
def mk' (L : y.LeftMoves ≃ x.LeftMoves) (R : y.RightMoves ≃ x.RightMoves)
(hL : ∀ i, x.moveLeft (L i) ≡r y.moveLeft i) (hR : ∀ j, x.moveRight (R j) ≡r y.moveRight j) :
x ≡r y :=
⟨L.symm, R.symm, fun i => by simpa using hL (L.symm i), fun j => by simpa using hR (R.symm j)⟩
#align pgame.relabelling.mk' SetTheory.PGame.Relabelling.mk'
/-- The equivalence between left moves of `x` and `y` given by the relabelling. -/
def leftMovesEquiv : x ≡r y → x.LeftMoves ≃ y.LeftMoves
| ⟨L,_, _,_⟩ => L
#align pgame.relabelling.left_moves_equiv SetTheory.PGame.Relabelling.leftMovesEquiv
@[simp]
theorem mk_leftMovesEquiv {x y L R hL hR} : (@Relabelling.mk x y L R hL hR).leftMovesEquiv = L :=
rfl
#align pgame.relabelling.mk_left_moves_equiv SetTheory.PGame.Relabelling.mk_leftMovesEquiv
@[simp]
theorem mk'_leftMovesEquiv {x y L R hL hR} :
(@Relabelling.mk' x y L R hL hR).leftMovesEquiv = L.symm :=
rfl
#align pgame.relabelling.mk'_left_moves_equiv SetTheory.PGame.Relabelling.mk'_leftMovesEquiv
/-- The equivalence between right moves of `x` and `y` given by the relabelling. -/
def rightMovesEquiv : x ≡r y → x.RightMoves ≃ y.RightMoves
| ⟨_, R, _, _⟩ => R
#align pgame.relabelling.right_moves_equiv SetTheory.PGame.Relabelling.rightMovesEquiv
@[simp]
theorem mk_rightMovesEquiv {x y L R hL hR} : (@Relabelling.mk x y L R hL hR).rightMovesEquiv = R :=
rfl
#align pgame.relabelling.mk_right_moves_equiv SetTheory.PGame.Relabelling.mk_rightMovesEquiv
@[simp]
theorem mk'_rightMovesEquiv {x y L R hL hR} :
(@Relabelling.mk' x y L R hL hR).rightMovesEquiv = R.symm :=
rfl
#align pgame.relabelling.mk'_right_moves_equiv SetTheory.PGame.Relabelling.mk'_rightMovesEquiv
/-- A left move of `x` is a relabelling of a left move of `y`. -/
def moveLeft : ∀ (r : x ≡r y) (i : x.LeftMoves), x.moveLeft i ≡r y.moveLeft (r.leftMovesEquiv i)
| ⟨_, _, hL, _⟩ => hL
#align pgame.relabelling.move_left SetTheory.PGame.Relabelling.moveLeft
/-- A left move of `y` is a relabelling of a left move of `x`. -/
def moveLeftSymm :
∀ (r : x ≡r y) (i : y.LeftMoves), x.moveLeft (r.leftMovesEquiv.symm i) ≡r y.moveLeft i
| ⟨L, R, hL, hR⟩, i => by simpa using hL (L.symm i)
#align pgame.relabelling.move_left_symm SetTheory.PGame.Relabelling.moveLeftSymm
/-- A right move of `x` is a relabelling of a right move of `y`. -/
def moveRight :
∀ (r : x ≡r y) (i : x.RightMoves), x.moveRight i ≡r y.moveRight (r.rightMovesEquiv i)
| ⟨_, _, _, hR⟩ => hR
#align pgame.relabelling.move_right SetTheory.PGame.Relabelling.moveRight
/-- A right move of `y` is a relabelling of a right move of `x`. -/
def moveRightSymm :
∀ (r : x ≡r y) (i : y.RightMoves), x.moveRight (r.rightMovesEquiv.symm i) ≡r y.moveRight i
| ⟨L, R, hL, hR⟩, i => by simpa using hR (R.symm i)
#align pgame.relabelling.move_right_symm SetTheory.PGame.Relabelling.moveRightSymm
/-- The identity relabelling. -/
@[refl]
def refl (x : PGame) : x ≡r x :=
⟨Equiv.refl _, Equiv.refl _, fun i => refl _, fun j => refl _⟩
termination_by x
#align pgame.relabelling.refl SetTheory.PGame.Relabelling.refl
instance (x : PGame) : Inhabited (x ≡r x) :=
⟨refl _⟩
/-- Flip a relabelling. -/
@[symm]
def symm : ∀ {x y : PGame}, x ≡r y → y ≡r x
| _, _, ⟨L, R, hL, hR⟩ => mk' L R (fun i => (hL i).symm) fun j => (hR j).symm
#align pgame.relabelling.symm SetTheory.PGame.Relabelling.symm
theorem le {x y : PGame} (r : x ≡r y) : x ≤ y :=
le_def.2
⟨fun i => Or.inl ⟨_, (r.moveLeft i).le⟩, fun j =>
Or.inr ⟨_, (r.moveRightSymm j).le⟩⟩
termination_by x
#align pgame.relabelling.le SetTheory.PGame.Relabelling.le
theorem ge {x y : PGame} (r : x ≡r y) : y ≤ x :=
r.symm.le
#align pgame.relabelling.ge SetTheory.PGame.Relabelling.ge
/-- A relabelling lets us prove equivalence of games. -/
theorem equiv (r : x ≡r y) : x ≈ y :=
⟨r.le, r.ge⟩
#align pgame.relabelling.equiv SetTheory.PGame.Relabelling.equiv
/-- Transitivity of relabelling. -/
@[trans]
def trans : ∀ {x y z : PGame}, x ≡r y → y ≡r z → x ≡r z
| _, _, _, ⟨L₁, R₁, hL₁, hR₁⟩, ⟨L₂, R₂, hL₂, hR₂⟩ =>
⟨L₁.trans L₂, R₁.trans R₂, fun i => (hL₁ i).trans (hL₂ _), fun j => (hR₁ j).trans (hR₂ _)⟩
#align pgame.relabelling.trans SetTheory.PGame.Relabelling.trans
/-- Any game without left or right moves is a relabelling of 0. -/
def isEmpty (x : PGame) [IsEmpty x.LeftMoves] [IsEmpty x.RightMoves] : x ≡r 0 :=
⟨Equiv.equivPEmpty _, Equiv.equivOfIsEmpty _ _, isEmptyElim, isEmptyElim⟩
#align pgame.relabelling.is_empty SetTheory.PGame.Relabelling.isEmpty
end Relabelling
theorem Equiv.isEmpty (x : PGame) [IsEmpty x.LeftMoves] [IsEmpty x.RightMoves] : x ≈ 0 :=
(Relabelling.isEmpty x).equiv
#align pgame.equiv.is_empty SetTheory.PGame.Equiv.isEmpty
instance {x y : PGame} : Coe (x ≡r y) (x ≈ y) :=
⟨Relabelling.equiv⟩
/-- Replace the types indexing the next moves for Left and Right by equivalent types. -/
def relabel {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves) : PGame :=
⟨xl', xr', x.moveLeft ∘ el, x.moveRight ∘ er⟩
#align pgame.relabel SetTheory.PGame.relabel
@[simp]
theorem relabel_moveLeft' {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(i : xl') : moveLeft (relabel el er) i = x.moveLeft (el i) :=
rfl
#align pgame.relabel_move_left' SetTheory.PGame.relabel_moveLeft'
theorem relabel_moveLeft {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(i : x.LeftMoves) : moveLeft (relabel el er) (el.symm i) = x.moveLeft i := by simp
#align pgame.relabel_move_left SetTheory.PGame.relabel_moveLeft
@[simp]
theorem relabel_moveRight' {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(j : xr') : moveRight (relabel el er) j = x.moveRight (er j) :=
rfl
#align pgame.relabel_move_right' SetTheory.PGame.relabel_moveRight'
theorem relabel_moveRight {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(j : x.RightMoves) : moveRight (relabel el er) (er.symm j) = x.moveRight j := by simp
#align pgame.relabel_move_right SetTheory.PGame.relabel_moveRight
/-- The game obtained by relabelling the next moves is a relabelling of the original game. -/
def relabelRelabelling {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves) :
x ≡r relabel el er :=
-- Porting note: needed to add `rfl`
Relabelling.mk' el er (fun i => by simp; rfl) (fun j => by simp; rfl)
#align pgame.relabel_relabelling SetTheory.PGame.relabelRelabelling
/-! ### Negation -/
/-- The negation of `{L | R}` is `{-R | -L}`. -/
def neg : PGame → PGame
| ⟨l, r, L, R⟩ => ⟨r, l, fun i => neg (R i), fun i => neg (L i)⟩
#align pgame.neg SetTheory.PGame.neg
instance : Neg PGame :=
⟨neg⟩
@[simp]
theorem neg_def {xl xr xL xR} : -mk xl xr xL xR = mk xr xl (fun j => -xR j) fun i => -xL i :=
rfl
#align pgame.neg_def SetTheory.PGame.neg_def
instance : InvolutiveNeg PGame :=
{ inferInstanceAs (Neg PGame) with
neg_neg := fun x => by
induction' x with xl xr xL xR ihL ihR
simp_rw [neg_def, ihL, ihR] }
instance : NegZeroClass PGame :=
{ inferInstanceAs (Zero PGame), inferInstanceAs (Neg PGame) with
neg_zero := by
dsimp [Zero.zero, Neg.neg, neg]
congr <;> funext i <;> cases i }
@[simp]
theorem neg_ofLists (L R : List PGame) :
-ofLists L R = ofLists (R.map fun x => -x) (L.map fun x => -x) := by
simp only [ofLists, neg_def, List.get_map, mk.injEq, List.length_map, true_and]
constructor
all_goals
apply hfunext
· simp
· rintro ⟨⟨a, ha⟩⟩ ⟨⟨b, hb⟩⟩ h
have :
∀ {m n} (_ : m = n) {b : ULift (Fin m)} {c : ULift (Fin n)} (_ : HEq b c),
(b.down : ℕ) = ↑c.down := by
rintro m n rfl b c
simp only [heq_eq_eq]
rintro rfl
rfl
congr 5
exact this (List.length_map _ _).symm h
#align pgame.neg_of_lists SetTheory.PGame.neg_ofLists
theorem isOption_neg {x y : PGame} : IsOption x (-y) ↔ IsOption (-x) y := by
rw [isOption_iff, isOption_iff, or_comm]
cases y;
apply or_congr <;>
· apply exists_congr
intro
rw [neg_eq_iff_eq_neg]
rfl
#align pgame.is_option_neg SetTheory.PGame.isOption_neg
@[simp]
theorem isOption_neg_neg {x y : PGame} : IsOption (-x) (-y) ↔ IsOption x y := by
rw [isOption_neg, neg_neg]
#align pgame.is_option_neg_neg SetTheory.PGame.isOption_neg_neg
theorem leftMoves_neg : ∀ x : PGame, (-x).LeftMoves = x.RightMoves
| ⟨_, _, _, _⟩ => rfl
#align pgame.left_moves_neg SetTheory.PGame.leftMoves_neg
theorem rightMoves_neg : ∀ x : PGame, (-x).RightMoves = x.LeftMoves
| ⟨_, _, _, _⟩ => rfl
#align pgame.right_moves_neg SetTheory.PGame.rightMoves_neg
/-- Turns a right move for `x` into a left move for `-x` and vice versa.
Even though these types are the same (not definitionally so), this is the preferred way to convert
between them. -/
def toLeftMovesNeg {x : PGame} : x.RightMoves ≃ (-x).LeftMoves :=
Equiv.cast (leftMoves_neg x).symm
#align pgame.to_left_moves_neg SetTheory.PGame.toLeftMovesNeg
/-- Turns a left move for `x` into a right move for `-x` and vice versa.
Even though these types are the same (not definitionally so), this is the preferred way to convert
between them. -/
def toRightMovesNeg {x : PGame} : x.LeftMoves ≃ (-x).RightMoves :=
Equiv.cast (rightMoves_neg x).symm
#align pgame.to_right_moves_neg SetTheory.PGame.toRightMovesNeg
theorem moveLeft_neg {x : PGame} (i) : (-x).moveLeft (toLeftMovesNeg i) = -x.moveRight i := by
cases x
rfl
#align pgame.move_left_neg SetTheory.PGame.moveLeft_neg
@[simp]
theorem moveLeft_neg' {x : PGame} (i) : (-x).moveLeft i = -x.moveRight (toLeftMovesNeg.symm i) := by
cases x
rfl
#align pgame.move_left_neg' SetTheory.PGame.moveLeft_neg'
theorem moveRight_neg {x : PGame} (i) : (-x).moveRight (toRightMovesNeg i) = -x.moveLeft i := by
cases x
rfl
#align pgame.move_right_neg SetTheory.PGame.moveRight_neg
@[simp]
theorem moveRight_neg' {x : PGame} (i) :
(-x).moveRight i = -x.moveLeft (toRightMovesNeg.symm i) := by
cases x
rfl
#align pgame.move_right_neg' SetTheory.PGame.moveRight_neg'
theorem moveLeft_neg_symm {x : PGame} (i) :
x.moveLeft (toRightMovesNeg.symm i) = -(-x).moveRight i := by simp
#align pgame.move_left_neg_symm SetTheory.PGame.moveLeft_neg_symm
| Mathlib/SetTheory/Game/PGame.lean | 1,356 | 1,357 | theorem moveLeft_neg_symm' {x : PGame} (i) :
x.moveLeft i = -(-x).moveRight (toRightMovesNeg i) := by | simp
|
/-
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
-/
import Mathlib.Init.Logic
import Mathlib.Init.Function
import Mathlib.Init.Algebra.Classes
import Batteries.Util.LibraryNote
import Batteries.Tactic.Lint.Basic
#align_import logic.basic from "leanprover-community/mathlib"@"3365b20c2ffa7c35e47e5209b89ba9abdddf3ffe"
#align_import init.ite_simp from "leanprover-community/lean"@"4a03bdeb31b3688c31d02d7ff8e0ff2e5d6174db"
/-!
# Basic logic properties
This file is one of the earliest imports in mathlib.
## Implementation notes
Theorems that require decidability hypotheses are in the namespace `Decidable`.
Classical versions are in the namespace `Classical`.
-/
open Function
attribute [local instance 10] Classical.propDecidable
section Miscellany
-- Porting note: the following `inline` attributes have been omitted,
-- on the assumption that this issue has been dealt with properly in Lean 4.
-- /- We add the `inline` attribute to optimize VM computation using these declarations.
-- For example, `if p ∧ q then ... else ...` will not evaluate the decidability
-- of `q` if `p` is false. -/
-- attribute [inline]
-- And.decidable Or.decidable Decidable.false Xor.decidable Iff.decidable Decidable.true
-- Implies.decidable Not.decidable Ne.decidable Bool.decidableEq Decidable.toBool
attribute [simp] cast_eq cast_heq imp_false
/-- An identity function with its main argument implicit. This will be printed as `hidden` even
if it is applied to a large term, so it can be used for elision,
as done in the `elide` and `unelide` tactics. -/
abbrev hidden {α : Sort*} {a : α} := a
#align hidden hidden
variable {α : Sort*}
instance (priority := 10) decidableEq_of_subsingleton [Subsingleton α] : DecidableEq α :=
fun a b ↦ isTrue (Subsingleton.elim a b)
#align decidable_eq_of_subsingleton decidableEq_of_subsingleton
instance [Subsingleton α] (p : α → Prop) : Subsingleton (Subtype p) :=
⟨fun ⟨x, _⟩ ⟨y, _⟩ ↦ by cases Subsingleton.elim x y; rfl⟩
#align pempty PEmpty
theorem congr_heq {α β γ : Sort _} {f : α → γ} {g : β → γ} {x : α} {y : β}
(h₁ : HEq f g) (h₂ : HEq x y) : f x = g y := by
cases h₂; cases h₁; rfl
#align congr_heq congr_heq
theorem congr_arg_heq {β : α → Sort*} (f : ∀ a, β a) :
∀ {a₁ a₂ : α}, a₁ = a₂ → HEq (f a₁) (f a₂)
| _, _, rfl => HEq.rfl
#align congr_arg_heq congr_arg_heq
theorem ULift.down_injective {α : Sort _} : Function.Injective (@ULift.down α)
| ⟨a⟩, ⟨b⟩, _ => by congr
#align ulift.down_injective ULift.down_injective
@[simp] theorem ULift.down_inj {α : Sort _} {a b : ULift α} : a.down = b.down ↔ a = b :=
⟨fun h ↦ ULift.down_injective h, fun h ↦ by rw [h]⟩
#align ulift.down_inj ULift.down_inj
theorem PLift.down_injective : Function.Injective (@PLift.down α)
| ⟨a⟩, ⟨b⟩, _ => by congr
#align plift.down_injective PLift.down_injective
@[simp] theorem PLift.down_inj {a b : PLift α} : a.down = b.down ↔ a = b :=
⟨fun h ↦ PLift.down_injective h, fun h ↦ by rw [h]⟩
#align plift.down_inj PLift.down_inj
@[simp] theorem eq_iff_eq_cancel_left {b c : α} : (∀ {a}, a = b ↔ a = c) ↔ b = c :=
⟨fun h ↦ by rw [← h], fun h a ↦ by rw [h]⟩
#align eq_iff_eq_cancel_left eq_iff_eq_cancel_left
@[simp] theorem eq_iff_eq_cancel_right {a b : α} : (∀ {c}, a = c ↔ b = c) ↔ a = b :=
⟨fun h ↦ by rw [h], fun h a ↦ by rw [h]⟩
#align eq_iff_eq_cancel_right eq_iff_eq_cancel_right
lemma ne_and_eq_iff_right {a b c : α} (h : b ≠ c) : a ≠ b ∧ a = c ↔ a = c :=
and_iff_right_of_imp (fun h2 => h2.symm ▸ h.symm)
#align ne_and_eq_iff_right ne_and_eq_iff_right
/-- Wrapper for adding elementary propositions to the type class systems.
Warning: this can easily be abused. See the rest of this docstring for details.
Certain propositions should not be treated as a class globally,
but sometimes it is very convenient to be able to use the type class system
in specific circumstances.
For example, `ZMod p` is a field if and only if `p` is a prime number.
In order to be able to find this field instance automatically by type class search,
we have to turn `p.prime` into an instance implicit assumption.
On the other hand, making `Nat.prime` a class would require a major refactoring of the library,
and it is questionable whether making `Nat.prime` a class is desirable at all.
The compromise is to add the assumption `[Fact p.prime]` to `ZMod.field`.
In particular, this class is not intended for turning the type class system
into an automated theorem prover for first order logic. -/
class Fact (p : Prop) : Prop where
/-- `Fact.out` contains the unwrapped witness for the fact represented by the instance of
`Fact p`. -/
out : p
#align fact Fact
library_note "fact non-instances"/--
In most cases, we should not have global instances of `Fact`; typeclass search only reads the head
symbol and then tries any instances, which means that adding any such instance will cause slowdowns
everywhere. We instead make them as lemmata and make them local instances as required.
-/
theorem Fact.elim {p : Prop} (h : Fact p) : p := h.1
theorem fact_iff {p : Prop} : Fact p ↔ p := ⟨fun h ↦ h.1, fun h ↦ ⟨h⟩⟩
#align fact_iff fact_iff
#align fact.elim Fact.elim
instance {p : Prop} [Decidable p] : Decidable (Fact p) :=
decidable_of_iff _ fact_iff.symm
/-- Swaps two pairs of arguments to a function. -/
abbrev Function.swap₂ {ι₁ ι₂ : Sort*} {κ₁ : ι₁ → Sort*} {κ₂ : ι₂ → Sort*}
{φ : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Sort*} (f : ∀ i₁ j₁ i₂ j₂, φ i₁ j₁ i₂ j₂)
(i₂ j₂ i₁ j₁) : φ i₁ j₁ i₂ j₂ := f i₁ j₁ i₂ j₂
#align function.swap₂ Function.swap₂
-- Porting note: these don't work as intended any more
-- /-- If `x : α . tac_name` then `x.out : α`. These are definitionally equal, but this can
-- nevertheless be useful for various reasons, e.g. to apply further projection notation or in an
-- argument to `simp`. -/
-- def autoParam'.out {α : Sort*} {n : Name} (x : autoParam' α n) : α := x
-- /-- If `x : α := d` then `x.out : α`. These are definitionally equal, but this can
-- nevertheless be useful for various reasons, e.g. to apply further projection notation or in an
-- argument to `simp`. -/
-- def optParam.out {α : Sort*} {d : α} (x : α := d) : α := x
end Miscellany
open Function
/-!
### Declarations about propositional connectives
-/
section Propositional
/-! ### Declarations about `implies` -/
instance : IsRefl Prop Iff := ⟨Iff.refl⟩
instance : IsTrans Prop Iff := ⟨fun _ _ _ ↦ Iff.trans⟩
alias Iff.imp := imp_congr
#align iff.imp Iff.imp
#align eq_true_eq_id eq_true_eq_id
#align imp_and_distrib imp_and
#align imp_iff_right imp_iff_rightₓ -- reorder implicits
#align imp_iff_not imp_iff_notₓ -- reorder implicits
-- This is a duplicate of `Classical.imp_iff_right_iff`. Deprecate?
theorem imp_iff_right_iff {a b : Prop} : (a → b ↔ b) ↔ a ∨ b := Decidable.imp_iff_right_iff
#align imp_iff_right_iff imp_iff_right_iff
-- This is a duplicate of `Classical.and_or_imp`. Deprecate?
theorem and_or_imp {a b c : Prop} : a ∧ b ∨ (a → c) ↔ a → b ∨ c := Decidable.and_or_imp
#align and_or_imp and_or_imp
/-- Provide modus tollens (`mt`) as dot notation for implications. -/
protected theorem Function.mt {a b : Prop} : (a → b) → ¬b → ¬a := mt
#align function.mt Function.mt
/-! ### Declarations about `not` -/
alias dec_em := Decidable.em
#align dec_em dec_em
theorem dec_em' (p : Prop) [Decidable p] : ¬p ∨ p := (dec_em p).symm
#align dec_em' dec_em'
alias em := Classical.em
#align em em
theorem em' (p : Prop) : ¬p ∨ p := (em p).symm
#align em' em'
theorem or_not {p : Prop} : p ∨ ¬p := em _
#align or_not or_not
theorem Decidable.eq_or_ne {α : Sort*} (x y : α) [Decidable (x = y)] : x = y ∨ x ≠ y :=
dec_em <| x = y
#align decidable.eq_or_ne Decidable.eq_or_ne
theorem Decidable.ne_or_eq {α : Sort*} (x y : α) [Decidable (x = y)] : x ≠ y ∨ x = y :=
dec_em' <| x = y
#align decidable.ne_or_eq Decidable.ne_or_eq
theorem eq_or_ne {α : Sort*} (x y : α) : x = y ∨ x ≠ y := em <| x = y
#align eq_or_ne eq_or_ne
theorem ne_or_eq {α : Sort*} (x y : α) : x ≠ y ∨ x = y := em' <| x = y
#align ne_or_eq ne_or_eq
theorem by_contradiction {p : Prop} : (¬p → False) → p := Decidable.by_contradiction
#align classical.by_contradiction by_contradiction
#align by_contradiction by_contradiction
theorem by_cases {p q : Prop} (hpq : p → q) (hnpq : ¬p → q) : q :=
if hp : p then hpq hp else hnpq hp
#align classical.by_cases by_cases
alias by_contra := by_contradiction
#align by_contra by_contra
library_note "decidable namespace"/--
In most of mathlib, we use the law of excluded middle (LEM) and the axiom of choice (AC) freely.
The `Decidable` namespace contains versions of lemmas from the root namespace that explicitly
attempt to avoid the axiom of choice, usually by adding decidability assumptions on the inputs.
You can check if a lemma uses the axiom of choice by using `#print axioms foo` and seeing if
`Classical.choice` appears in the list.
-/
library_note "decidable arguments"/--
As mathlib is primarily classical,
if the type signature of a `def` or `lemma` does not require any `Decidable` instances to state,
it is preferable not to introduce any `Decidable` instances that are needed in the proof
as arguments, but rather to use the `classical` tactic as needed.
In the other direction, when `Decidable` instances do appear in the type signature,
it is better to use explicitly introduced ones rather than allowing Lean to automatically infer
classical ones, as these may cause instance mismatch errors later.
-/
export Classical (not_not)
attribute [simp] not_not
#align not_not Classical.not_not
variable {a b : Prop}
theorem of_not_not {a : Prop} : ¬¬a → a := by_contra
#align of_not_not of_not_not
theorem not_ne_iff {α : Sort*} {a b : α} : ¬a ≠ b ↔ a = b := not_not
#align not_ne_iff not_ne_iff
theorem of_not_imp : ¬(a → b) → a := Decidable.of_not_imp
#align of_not_imp of_not_imp
alias Not.decidable_imp_symm := Decidable.not_imp_symm
#align not.decidable_imp_symm Not.decidable_imp_symm
theorem Not.imp_symm : (¬a → b) → ¬b → a := Not.decidable_imp_symm
#align not.imp_symm Not.imp_symm
theorem not_imp_comm : ¬a → b ↔ ¬b → a := Decidable.not_imp_comm
#align not_imp_comm not_imp_comm
@[simp] theorem not_imp_self : ¬a → a ↔ a := Decidable.not_imp_self
#align not_imp_self not_imp_self
theorem Imp.swap {a b : Sort*} {c : Prop} : a → b → c ↔ b → a → c := ⟨Function.swap, Function.swap⟩
#align imp.swap Imp.swap
alias Iff.not := not_congr
#align iff.not Iff.not
theorem Iff.not_left (h : a ↔ ¬b) : ¬a ↔ b := h.not.trans not_not
#align iff.not_left Iff.not_left
theorem Iff.not_right (h : ¬a ↔ b) : a ↔ ¬b := not_not.symm.trans h.not
#align iff.not_right Iff.not_right
protected lemma Iff.ne {α β : Sort*} {a b : α} {c d : β} : (a = b ↔ c = d) → (a ≠ b ↔ c ≠ d) :=
Iff.not
#align iff.ne Iff.ne
lemma Iff.ne_left {α β : Sort*} {a b : α} {c d : β} : (a = b ↔ c ≠ d) → (a ≠ b ↔ c = d) :=
Iff.not_left
#align iff.ne_left Iff.ne_left
lemma Iff.ne_right {α β : Sort*} {a b : α} {c d : β} : (a ≠ b ↔ c = d) → (a = b ↔ c ≠ d) :=
Iff.not_right
#align iff.ne_right Iff.ne_right
/-! ### Declarations about `Xor'` -/
@[simp] theorem xor_true : Xor' True = Not := by
simp (config := { unfoldPartialApp := true }) [Xor']
#align xor_true xor_true
@[simp] theorem xor_false : Xor' False = id := by ext; simp [Xor']
#align xor_false xor_false
theorem xor_comm (a b : Prop) : Xor' a b = Xor' b a := by simp [Xor', and_comm, or_comm]
#align xor_comm xor_comm
instance : Std.Commutative Xor' := ⟨xor_comm⟩
@[simp] theorem xor_self (a : Prop) : Xor' a a = False := by simp [Xor']
#align xor_self xor_self
@[simp] theorem xor_not_left : Xor' (¬a) b ↔ (a ↔ b) := by by_cases a <;> simp [*]
#align xor_not_left xor_not_left
@[simp] theorem xor_not_right : Xor' a (¬b) ↔ (a ↔ b) := by by_cases a <;> simp [*]
#align xor_not_right xor_not_right
theorem xor_not_not : Xor' (¬a) (¬b) ↔ Xor' a b := by simp [Xor', or_comm, and_comm]
#align xor_not_not xor_not_not
protected theorem Xor'.or (h : Xor' a b) : a ∨ b := h.imp And.left And.left
#align xor.or Xor'.or
/-! ### Declarations about `and` -/
alias Iff.and := and_congr
#align iff.and Iff.and
#align and_congr_left and_congr_leftₓ -- reorder implicits
#align and_congr_right' and_congr_right'ₓ -- reorder implicits
#align and.right_comm and_right_comm
#align and_and_distrib_left and_and_left
#align and_and_distrib_right and_and_right
alias ⟨And.rotate, _⟩ := and_rotate
#align and.rotate And.rotate
#align and.congr_right_iff and_congr_right_iff
#align and.congr_left_iff and_congr_left_iffₓ -- reorder implicits
theorem and_symm_right {α : Sort*} (a b : α) (p : Prop) : p ∧ a = b ↔ p ∧ b = a := by simp [eq_comm]
theorem and_symm_left {α : Sort*} (a b : α) (p : Prop) : a = b ∧ p ↔ b = a ∧ p := by simp [eq_comm]
/-! ### Declarations about `or` -/
alias Iff.or := or_congr
#align iff.or Iff.or
#align or_congr_left' or_congr_left
#align or_congr_right' or_congr_rightₓ -- reorder implicits
#align or.right_comm or_right_comm
alias ⟨Or.rotate, _⟩ := or_rotate
#align or.rotate Or.rotate
@[deprecated Or.imp]
theorem or_of_or_of_imp_of_imp {a b c d : Prop} (h₁ : a ∨ b) (h₂ : a → c) (h₃ : b → d) :
c ∨ d :=
Or.imp h₂ h₃ h₁
#align or_of_or_of_imp_of_imp or_of_or_of_imp_of_imp
@[deprecated Or.imp_left]
theorem or_of_or_of_imp_left {a c b : Prop} (h₁ : a ∨ c) (h : a → b) : b ∨ c := Or.imp_left h h₁
#align or_of_or_of_imp_left or_of_or_of_imp_left
@[deprecated Or.imp_right]
theorem or_of_or_of_imp_right {c a b : Prop} (h₁ : c ∨ a) (h : a → b) : c ∨ b := Or.imp_right h h₁
#align or_of_or_of_imp_right or_of_or_of_imp_right
theorem Or.elim3 {c d : Prop} (h : a ∨ b ∨ c) (ha : a → d) (hb : b → d) (hc : c → d) : d :=
Or.elim h ha fun h₂ ↦ Or.elim h₂ hb hc
#align or.elim3 Or.elim3
theorem Or.imp3 {d e c f : Prop} (had : a → d) (hbe : b → e) (hcf : c → f) :
a ∨ b ∨ c → d ∨ e ∨ f :=
Or.imp had <| Or.imp hbe hcf
#align or.imp3 Or.imp3
#align or_imp_distrib or_imp
export Classical (or_iff_not_imp_left or_iff_not_imp_right)
#align or_iff_not_imp_left Classical.or_iff_not_imp_left
#align or_iff_not_imp_right Classical.or_iff_not_imp_right
theorem not_or_of_imp : (a → b) → ¬a ∨ b := Decidable.not_or_of_imp
#align not_or_of_imp not_or_of_imp
-- See Note [decidable namespace]
protected theorem Decidable.or_not_of_imp [Decidable a] (h : a → b) : b ∨ ¬a :=
dite _ (Or.inl ∘ h) Or.inr
#align decidable.or_not_of_imp Decidable.or_not_of_imp
theorem or_not_of_imp : (a → b) → b ∨ ¬a := Decidable.or_not_of_imp
#align or_not_of_imp or_not_of_imp
theorem imp_iff_not_or : a → b ↔ ¬a ∨ b := Decidable.imp_iff_not_or
#align imp_iff_not_or imp_iff_not_or
theorem imp_iff_or_not {b a : Prop} : b → a ↔ a ∨ ¬b := Decidable.imp_iff_or_not
#align imp_iff_or_not imp_iff_or_not
theorem not_imp_not : ¬a → ¬b ↔ b → a := Decidable.not_imp_not
#align not_imp_not not_imp_not
theorem imp_and_neg_imp_iff (p q : Prop) : (p → q) ∧ (¬p → q) ↔ q := by simp
/-- Provide the reverse of modus tollens (`mt`) as dot notation for implications. -/
protected theorem Function.mtr : (¬a → ¬b) → b → a := not_imp_not.mp
#align function.mtr Function.mtr
#align decidable.or_congr_left Decidable.or_congr_left'
#align decidable.or_congr_right Decidable.or_congr_right'
#align decidable.or_iff_not_imp_right Decidable.or_iff_not_imp_rightₓ -- reorder implicits
#align decidable.imp_iff_or_not Decidable.imp_iff_or_notₓ -- reorder implicits
theorem or_congr_left' {c a b : Prop} (h : ¬c → (a ↔ b)) : a ∨ c ↔ b ∨ c :=
Decidable.or_congr_left' h
#align or_congr_left or_congr_left'
theorem or_congr_right' {c : Prop} (h : ¬a → (b ↔ c)) : a ∨ b ↔ a ∨ c := Decidable.or_congr_right' h
#align or_congr_right or_congr_right'ₓ -- reorder implicits
#align or_iff_left or_iff_leftₓ -- reorder implicits
/-! ### Declarations about distributivity -/
#align and_or_distrib_left and_or_left
#align or_and_distrib_right or_and_right
#align or_and_distrib_left or_and_left
#align and_or_distrib_right and_or_right
/-! Declarations about `iff` -/
alias Iff.iff := iff_congr
#align iff.iff Iff.iff
-- @[simp] -- FIXME simp ignores proof rewrites
theorem iff_mpr_iff_true_intro {P : Prop} (h : P) : Iff.mpr (iff_true_intro h) True.intro = h := rfl
#align iff_mpr_iff_true_intro iff_mpr_iff_true_intro
#align decidable.imp_or_distrib Decidable.imp_or
theorem imp_or {a b c : Prop} : a → b ∨ c ↔ (a → b) ∨ (a → c) := Decidable.imp_or
#align imp_or_distrib imp_or
#align decidable.imp_or_distrib' Decidable.imp_or'
theorem imp_or' {a : Sort*} {b c : Prop} : a → b ∨ c ↔ (a → b) ∨ (a → c) := Decidable.imp_or'
#align imp_or_distrib' imp_or'ₓ -- universes
theorem not_imp : ¬(a → b) ↔ a ∧ ¬b := Decidable.not_imp_iff_and_not
#align not_imp not_imp
theorem peirce (a b : Prop) : ((a → b) → a) → a := Decidable.peirce _ _
#align peirce peirce
theorem not_iff_not : (¬a ↔ ¬b) ↔ (a ↔ b) := Decidable.not_iff_not
#align not_iff_not not_iff_not
theorem not_iff_comm : (¬a ↔ b) ↔ (¬b ↔ a) := Decidable.not_iff_comm
#align not_iff_comm not_iff_comm
theorem not_iff : ¬(a ↔ b) ↔ (¬a ↔ b) := Decidable.not_iff
#align not_iff not_iff
theorem iff_not_comm : (a ↔ ¬b) ↔ (b ↔ ¬a) := Decidable.iff_not_comm
#align iff_not_comm iff_not_comm
theorem iff_iff_and_or_not_and_not : (a ↔ b) ↔ a ∧ b ∨ ¬a ∧ ¬b :=
Decidable.iff_iff_and_or_not_and_not
#align iff_iff_and_or_not_and_not iff_iff_and_or_not_and_not
theorem iff_iff_not_or_and_or_not : (a ↔ b) ↔ (¬a ∨ b) ∧ (a ∨ ¬b) :=
Decidable.iff_iff_not_or_and_or_not
#align iff_iff_not_or_and_or_not iff_iff_not_or_and_or_not
theorem not_and_not_right : ¬(a ∧ ¬b) ↔ a → b := Decidable.not_and_not_right
#align not_and_not_right not_and_not_right
#align decidable_of_iff decidable_of_iff
#align decidable_of_iff' decidable_of_iff'
#align decidable_of_bool decidable_of_bool
/-! ### De Morgan's laws -/
#align decidable.not_and_distrib Decidable.not_and_iff_or_not_not
#align decidable.not_and_distrib' Decidable.not_and_iff_or_not_not'
/-- One of **de Morgan's laws**: the negation of a conjunction is logically equivalent to the
disjunction of the negations. -/
theorem not_and_or : ¬(a ∧ b) ↔ ¬a ∨ ¬b := Decidable.not_and_iff_or_not_not
#align not_and_distrib not_and_or
#align not_or_distrib not_or
theorem or_iff_not_and_not : a ∨ b ↔ ¬(¬a ∧ ¬b) := Decidable.or_iff_not_and_not
#align or_iff_not_and_not or_iff_not_and_not
theorem and_iff_not_or_not : a ∧ b ↔ ¬(¬a ∨ ¬b) := Decidable.and_iff_not_or_not
#align and_iff_not_or_not and_iff_not_or_not
@[simp] theorem not_xor (P Q : Prop) : ¬Xor' P Q ↔ (P ↔ Q) := by
simp only [not_and, Xor', not_or, not_not, ← iff_iff_implies_and_implies]
#align not_xor not_xor
theorem xor_iff_not_iff (P Q : Prop) : Xor' P Q ↔ ¬ (P ↔ Q) := (not_xor P Q).not_right
#align xor_iff_not_iff xor_iff_not_iff
theorem xor_iff_iff_not : Xor' a b ↔ (a ↔ ¬b) := by simp only [← @xor_not_right a, not_not]
#align xor_iff_iff_not xor_iff_iff_not
theorem xor_iff_not_iff' : Xor' a b ↔ (¬a ↔ b) := by simp only [← @xor_not_left _ b, not_not]
#align xor_iff_not_iff' xor_iff_not_iff'
end Propositional
/-! ### Declarations about equality -/
alias Membership.mem.ne_of_not_mem := ne_of_mem_of_not_mem
alias Membership.mem.ne_of_not_mem' := ne_of_mem_of_not_mem'
#align has_mem.mem.ne_of_not_mem Membership.mem.ne_of_not_mem
#align has_mem.mem.ne_of_not_mem' Membership.mem.ne_of_not_mem'
section Equality
-- todo: change name
theorem forall_cond_comm {α} {s : α → Prop} {p : α → α → Prop} :
(∀ a, s a → ∀ b, s b → p a b) ↔ ∀ a b, s a → s b → p a b :=
⟨fun h a b ha hb ↦ h a ha b hb, fun h a ha b hb ↦ h a b ha hb⟩
#align ball_cond_comm forall_cond_comm
theorem forall_mem_comm {α β} [Membership α β] {s : β} {p : α → α → Prop} :
(∀ a (_ : a ∈ s) b (_ : b ∈ s), p a b) ↔ ∀ a b, a ∈ s → b ∈ s → p a b :=
forall_cond_comm
#align ball_mem_comm forall_mem_comm
@[deprecated (since := "2024-03-23")] alias ball_cond_comm := forall_cond_comm
@[deprecated (since := "2024-03-23")] alias ball_mem_comm := forall_mem_comm
#align ne_of_apply_ne ne_of_apply_ne
lemma ne_of_eq_of_ne {α : Sort*} {a b c : α} (h₁ : a = b) (h₂ : b ≠ c) : a ≠ c := h₁.symm ▸ h₂
lemma ne_of_ne_of_eq {α : Sort*} {a b c : α} (h₁ : a ≠ b) (h₂ : b = c) : a ≠ c := h₂ ▸ h₁
alias Eq.trans_ne := ne_of_eq_of_ne
alias Ne.trans_eq := ne_of_ne_of_eq
#align eq.trans_ne Eq.trans_ne
#align ne.trans_eq Ne.trans_eq
theorem eq_equivalence {α : Sort*} : Equivalence (@Eq α) :=
⟨Eq.refl, @Eq.symm _, @Eq.trans _⟩
#align eq_equivalence eq_equivalence
-- These were migrated to Batteries but the `@[simp]` attributes were (mysteriously?) removed.
attribute [simp] eq_mp_eq_cast eq_mpr_eq_cast
#align eq_mp_eq_cast eq_mp_eq_cast
#align eq_mpr_eq_cast eq_mpr_eq_cast
#align cast_cast cast_cast
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_refl_left {α β : Sort*} (f : α → β) {a b : α} (h : a = b) :
congr (Eq.refl f) h = congr_arg f h := rfl
#align congr_refl_left congr_refl_left
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_refl_right {α β : Sort*} {f g : α → β} (h : f = g) (a : α) :
congr h (Eq.refl a) = congr_fun h a := rfl
#align congr_refl_right congr_refl_right
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_arg_refl {α β : Sort*} (f : α → β) (a : α) :
congr_arg f (Eq.refl a) = Eq.refl (f a) :=
rfl
#align congr_arg_refl congr_arg_refl
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_fun_rfl {α β : Sort*} (f : α → β) (a : α) : congr_fun (Eq.refl f) a = Eq.refl (f a) :=
rfl
#align congr_fun_rfl congr_fun_rfl
-- @[simp] -- FIXME simp ignores proof rewrites
theorem congr_fun_congr_arg {α β γ : Sort*} (f : α → β → γ) {a a' : α} (p : a = a') (b : β) :
congr_fun (congr_arg f p) b = congr_arg (fun a ↦ f a b) p := rfl
#align congr_fun_congr_arg congr_fun_congr_arg
#align heq_of_cast_eq heq_of_cast_eq
#align cast_eq_iff_heq cast_eq_iff_heq
theorem Eq.rec_eq_cast {α : Sort _} {P : α → Sort _} {x y : α} (h : x = y) (z : P x) :
h ▸ z = cast (congr_arg P h) z := by induction h; rfl
-- Porting note (#10756): new theorem. More general version of `eqRec_heq`
theorem eqRec_heq' {α : Sort*} {a' : α} {motive : (a : α) → a' = a → Sort*}
(p : motive a' (rfl : a' = a')) {a : α} (t : a' = a) :
HEq (@Eq.rec α a' motive p a t) p := by
subst t; rfl
set_option autoImplicit true in
theorem rec_heq_of_heq {C : α → Sort*} {x : C a} {y : β} (e : a = b) (h : HEq x y) :
HEq (e ▸ x) y := by subst e; exact h
#align rec_heq_of_heq rec_heq_of_heq
set_option autoImplicit true in
theorem rec_heq_iff_heq {C : α → Sort*} {x : C a} {y : β} {e : a = b} :
HEq (e ▸ x) y ↔ HEq x y := by subst e; rfl
#align rec_heq_iff_heq rec_heq_iff_heq
set_option autoImplicit true in
theorem heq_rec_iff_heq {C : α → Sort*} {x : β} {y : C a} {e : a = b} :
HEq x (e ▸ y) ↔ HEq x y := by subst e; rfl
#align heq_rec_iff_heq heq_rec_iff_heq
#align eq.congr Eq.congr
#align eq.congr_left Eq.congr_left
#align eq.congr_right Eq.congr_right
#align congr_arg2 congr_arg₂
#align congr_fun₂ congr_fun₂
#align congr_fun₃ congr_fun₃
#align funext₂ funext₂
#align funext₃ funext₃
end Equality
/-! ### Declarations about quantifiers -/
section Quantifiers
section Dependent
variable {α : Sort*} {β : α → Sort*} {γ : ∀ a, β a → Sort*} {δ : ∀ a b, γ a b → Sort*}
{ε : ∀ a b c, δ a b c → Sort*}
theorem pi_congr {β' : α → Sort _} (h : ∀ a, β a = β' a) : (∀ a, β a) = ∀ a, β' a :=
(funext h : β = β') ▸ rfl
#align pi_congr pi_congr
-- Porting note: some higher order lemmas such as `forall₂_congr` and `exists₂_congr`
-- were moved to `Batteries`
theorem forall₂_imp {p q : ∀ a, β a → Prop} (h : ∀ a b, p a b → q a b) :
(∀ a b, p a b) → ∀ a b, q a b :=
forall_imp fun i ↦ forall_imp <| h i
#align forall₂_imp forall₂_imp
theorem forall₃_imp {p q : ∀ a b, γ a b → Prop} (h : ∀ a b c, p a b c → q a b c) :
(∀ a b c, p a b c) → ∀ a b c, q a b c :=
forall_imp fun a ↦ forall₂_imp <| h a
#align forall₃_imp forall₃_imp
theorem Exists₂.imp {p q : ∀ a, β a → Prop} (h : ∀ a b, p a b → q a b) :
(∃ a b, p a b) → ∃ a b, q a b :=
Exists.imp fun a ↦ Exists.imp <| h a
#align Exists₂.imp Exists₂.imp
theorem Exists₃.imp {p q : ∀ a b, γ a b → Prop} (h : ∀ a b c, p a b c → q a b c) :
(∃ a b c, p a b c) → ∃ a b c, q a b c :=
Exists.imp fun a ↦ Exists₂.imp <| h a
#align Exists₃.imp Exists₃.imp
end Dependent
variable {α β : Sort*} {p q : α → Prop}
#align exists_imp_exists' Exists.imp'
theorem forall_swap {p : α → β → Prop} : (∀ x y, p x y) ↔ ∀ y x, p x y := ⟨swap, swap⟩
#align forall_swap forall_swap
theorem forall₂_swap
{ι₁ ι₂ : Sort*} {κ₁ : ι₁ → Sort*} {κ₂ : ι₂ → Sort*} {p : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Prop} :
(∀ i₁ j₁ i₂ j₂, p i₁ j₁ i₂ j₂) ↔ ∀ i₂ j₂ i₁ j₁, p i₁ j₁ i₂ j₂ := ⟨swap₂, swap₂⟩
#align forall₂_swap forall₂_swap
/-- We intentionally restrict the type of `α` in this lemma so that this is a safer to use in simp
than `forall_swap`. -/
theorem imp_forall_iff {α : Type*} {p : Prop} {q : α → Prop} : (p → ∀ x, q x) ↔ ∀ x, p → q x :=
forall_swap
#align imp_forall_iff imp_forall_iff
theorem exists_swap {p : α → β → Prop} : (∃ x y, p x y) ↔ ∃ y x, p x y :=
⟨fun ⟨x, y, h⟩ ↦ ⟨y, x, h⟩, fun ⟨y, x, h⟩ ↦ ⟨x, y, h⟩⟩
#align exists_swap exists_swap
#align forall_exists_index forall_exists_index
#align exists_imp_distrib exists_imp
#align not_exists_of_forall_not not_exists_of_forall_not
#align Exists.some Exists.choose
#align Exists.some_spec Exists.choose_spec
#align decidable.not_forall Decidable.not_forall
export Classical (not_forall)
#align not_forall Classical.not_forall
#align decidable.not_forall_not Decidable.not_forall_not
theorem not_forall_not : (¬∀ x, ¬p x) ↔ ∃ x, p x := Decidable.not_forall_not
#align not_forall_not not_forall_not
#align decidable.not_exists_not Decidable.not_exists_not
export Classical (not_exists_not)
#align not_exists_not Classical.not_exists_not
lemma forall_or_exists_not (P : α → Prop) : (∀ a, P a) ∨ ∃ a, ¬ P a := by
rw [← not_forall]; exact em _
lemma exists_or_forall_not (P : α → Prop) : (∃ a, P a) ∨ ∀ a, ¬ P a := by
rw [← not_exists]; exact em _
theorem forall_imp_iff_exists_imp {α : Sort*} {p : α → Prop} {b : Prop} [ha : Nonempty α] :
(∀ x, p x) → b ↔ ∃ x, p x → b := by
let ⟨a⟩ := ha
refine ⟨fun h ↦ not_forall_not.1 fun h' ↦ ?_, fun ⟨x, hx⟩ h ↦ hx (h x)⟩
exact if hb : b then h' a fun _ ↦ hb else hb <| h fun x ↦ (_root_.not_imp.1 (h' x)).1
#align forall_imp_iff_exists_imp forall_imp_iff_exists_imp
@[mfld_simps]
theorem forall_true_iff : (α → True) ↔ True := imp_true_iff _
#align forall_true_iff forall_true_iff
-- Unfortunately this causes simp to loop sometimes, so we
-- add the 2 and 3 cases as simp lemmas instead
theorem forall_true_iff' (h : ∀ a, p a ↔ True) : (∀ a, p a) ↔ True :=
iff_true_intro fun _ ↦ of_iff_true (h _)
#align forall_true_iff' forall_true_iff'
-- This is not marked `@[simp]` because `implies_true : (α → True) = True` works
theorem forall₂_true_iff {β : α → Sort*} : (∀ a, β a → True) ↔ True := by simp
#align forall_2_true_iff forall₂_true_iff
-- This is not marked `@[simp]` because `implies_true : (α → True) = True` works
theorem forall₃_true_iff {β : α → Sort*} {γ : ∀ a, β a → Sort*} :
(∀ (a) (b : β a), γ a b → True) ↔ True := by simp
#align forall_3_true_iff forall₃_true_iff
@[simp] theorem exists_unique_iff_exists [Subsingleton α] {p : α → Prop} :
(∃! x, p x) ↔ ∃ x, p x :=
⟨fun h ↦ h.exists, Exists.imp fun x hx ↦ ⟨hx, fun y _ ↦ Subsingleton.elim y x⟩⟩
#align exists_unique_iff_exists exists_unique_iff_exists
-- forall_forall_const is no longer needed
#align exists_const exists_const
theorem exists_unique_const {b : Prop} (α : Sort*) [i : Nonempty α] [Subsingleton α] :
(∃! _ : α, b) ↔ b := by simp
#align exists_unique_const exists_unique_const
#align forall_and_distrib forall_and
#align exists_or_distrib exists_or
#align exists_and_distrib_left exists_and_left
#align exists_and_distrib_right exists_and_right
theorem Decidable.and_forall_ne [DecidableEq α] (a : α) {p : α → Prop} :
(p a ∧ ∀ b, b ≠ a → p b) ↔ ∀ b, p b := by
simp only [← @forall_eq _ p a, ← forall_and, ← or_imp, Decidable.em, forall_const]
#align decidable.and_forall_ne Decidable.and_forall_ne
theorem and_forall_ne (a : α) : (p a ∧ ∀ b, b ≠ a → p b) ↔ ∀ b, p b :=
Decidable.and_forall_ne a
#align and_forall_ne and_forall_ne
theorem Ne.ne_or_ne {x y : α} (z : α) (h : x ≠ y) : x ≠ z ∨ y ≠ z :=
not_and_or.1 <| mt (and_imp.2 (· ▸ ·)) h.symm
#align ne.ne_or_ne Ne.ne_or_ne
@[simp] theorem exists_unique_eq {a' : α} : ∃! a, a = a' := by
simp only [eq_comm, ExistsUnique, and_self, forall_eq', exists_eq']
#align exists_unique_eq exists_unique_eq
@[simp] theorem exists_unique_eq' {a' : α} : ∃! a, a' = a := by
simp only [ExistsUnique, and_self, forall_eq', exists_eq']
#align exists_unique_eq' exists_unique_eq'
@[simp]
theorem exists_apply_eq_apply' (f : α → β) (a' : α) : ∃ a, f a' = f a := ⟨a', rfl⟩
#align exists_apply_eq_apply' exists_apply_eq_apply'
@[simp]
lemma exists_apply_eq_apply2 {α β γ} {f : α → β → γ} {a : α} {b : β} : ∃ x y, f x y = f a b :=
⟨a, b, rfl⟩
@[simp]
lemma exists_apply_eq_apply2' {α β γ} {f : α → β → γ} {a : α} {b : β} : ∃ x y, f a b = f x y :=
⟨a, b, rfl⟩
@[simp]
lemma exists_apply_eq_apply3 {α β γ δ} {f : α → β → γ → δ} {a : α} {b : β} {c : γ} :
∃ x y z, f x y z = f a b c :=
⟨a, b, c, rfl⟩
@[simp]
lemma exists_apply_eq_apply3' {α β γ δ} {f : α → β → γ → δ} {a : α} {b : β} {c : γ} :
∃ x y z, f a b c = f x y z :=
⟨a, b, c, rfl⟩
-- Porting note: an alternative workaround theorem:
theorem exists_apply_eq (a : α) (b : β) : ∃ f : α → β, f a = b := ⟨fun _ ↦ b, rfl⟩
@[simp] theorem exists_exists_and_eq_and {f : α → β} {p : α → Prop} {q : β → Prop} :
(∃ b, (∃ a, p a ∧ f a = b) ∧ q b) ↔ ∃ a, p a ∧ q (f a) :=
⟨fun ⟨_, ⟨a, ha, hab⟩, hb⟩ ↦ ⟨a, ha, hab.symm ▸ hb⟩, fun ⟨a, hp, hq⟩ ↦ ⟨f a, ⟨a, hp, rfl⟩, hq⟩⟩
#align exists_exists_and_eq_and exists_exists_and_eq_and
@[simp] theorem exists_exists_eq_and {f : α → β} {p : β → Prop} :
(∃ b, (∃ a, f a = b) ∧ p b) ↔ ∃ a, p (f a) :=
⟨fun ⟨_, ⟨a, ha⟩, hb⟩ ↦ ⟨a, ha.symm ▸ hb⟩, fun ⟨a, ha⟩ ↦ ⟨f a, ⟨a, rfl⟩, ha⟩⟩
#align exists_exists_eq_and exists_exists_eq_and
@[simp] theorem exists_exists_and_exists_and_eq_and {α β γ : Type*}
{f : α → β → γ} {p : α → Prop} {q : β → Prop} {r : γ → Prop} :
(∃ c, (∃ a, p a ∧ ∃ b, q b ∧ f a b = c) ∧ r c) ↔ ∃ a, p a ∧ ∃ b, q b ∧ r (f a b) :=
⟨fun ⟨_, ⟨a, ha, b, hb, hab⟩, hc⟩ ↦ ⟨a, ha, b, hb, hab.symm ▸ hc⟩,
fun ⟨a, ha, b, hb, hab⟩ ↦ ⟨f a b, ⟨a, ha, b, hb, rfl⟩, hab⟩⟩
@[simp] theorem exists_exists_exists_and_eq {α β γ : Type*}
{f : α → β → γ} {p : γ → Prop} :
(∃ c, (∃ a, ∃ b, f a b = c) ∧ p c) ↔ ∃ a, ∃ b, p (f a b) :=
⟨fun ⟨_, ⟨a, b, hab⟩, hc⟩ ↦ ⟨a, b, hab.symm ▸ hc⟩,
fun ⟨a, b, hab⟩ ↦ ⟨f a b, ⟨a, b, rfl⟩, hab⟩⟩
@[simp] theorem exists_or_eq_left (y : α) (p : α → Prop) : ∃ x : α, x = y ∨ p x := ⟨y, .inl rfl⟩
#align exists_or_eq_left exists_or_eq_left
@[simp] theorem exists_or_eq_right (y : α) (p : α → Prop) : ∃ x : α, p x ∨ x = y := ⟨y, .inr rfl⟩
#align exists_or_eq_right exists_or_eq_right
@[simp] theorem exists_or_eq_left' (y : α) (p : α → Prop) : ∃ x : α, y = x ∨ p x := ⟨y, .inl rfl⟩
#align exists_or_eq_left' exists_or_eq_left'
@[simp] theorem exists_or_eq_right' (y : α) (p : α → Prop) : ∃ x : α, p x ∨ y = x := ⟨y, .inr rfl⟩
#align exists_or_eq_right' exists_or_eq_right'
theorem forall_apply_eq_imp_iff' {f : α → β} {p : β → Prop} :
(∀ a b, f a = b → p b) ↔ ∀ a, p (f a) := by simp
#align forall_apply_eq_imp_iff forall_apply_eq_imp_iff'
#align forall_apply_eq_imp_iff' forall_apply_eq_imp_iff
theorem forall_eq_apply_imp_iff' {f : α → β} {p : β → Prop} :
(∀ a b, b = f a → p b) ↔ ∀ a, p (f a) := by simp
#align forall_eq_apply_imp_iff forall_eq_apply_imp_iff'
#align forall_eq_apply_imp_iff' forall_eq_apply_imp_iff
#align forall_apply_eq_imp_iff₂ forall_apply_eq_imp_iff₂
@[simp] theorem exists_eq_right' {a' : α} : (∃ a, p a ∧ a' = a) ↔ p a' := by simp [@eq_comm _ a']
#align exists_eq_right' exists_eq_right'
#align exists_comm exists_comm
theorem exists₂_comm
{ι₁ ι₂ : Sort*} {κ₁ : ι₁ → Sort*} {κ₂ : ι₂ → Sort*} {p : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Prop} :
(∃ i₁ j₁ i₂ j₂, p i₁ j₁ i₂ j₂) ↔ ∃ i₂ j₂ i₁ j₁, p i₁ j₁ i₂ j₂ := by
simp only [@exists_comm (κ₁ _), @exists_comm ι₁]
#align exists₂_comm exists₂_comm
theorem And.exists {p q : Prop} {f : p ∧ q → Prop} : (∃ h, f h) ↔ ∃ hp hq, f ⟨hp, hq⟩ :=
⟨fun ⟨h, H⟩ ↦ ⟨h.1, h.2, H⟩, fun ⟨hp, hq, H⟩ ↦ ⟨⟨hp, hq⟩, H⟩⟩
#align and.exists And.exists
theorem forall_or_of_or_forall {α : Sort*} {p : α → Prop} {b : Prop} (h : b ∨ ∀ x, p x) (x : α) :
b ∨ p x :=
h.imp_right fun h₂ ↦ h₂ x
#align forall_or_of_or_forall forall_or_of_or_forall
-- See Note [decidable namespace]
protected theorem Decidable.forall_or_left {q : Prop} {p : α → Prop} [Decidable q] :
(∀ x, q ∨ p x) ↔ q ∨ ∀ x, p x :=
⟨fun h ↦ if hq : q then Or.inl hq else
Or.inr fun x ↦ (h x).resolve_left hq, forall_or_of_or_forall⟩
#align decidable.forall_or_distrib_left Decidable.forall_or_left
theorem forall_or_left {q} {p : α → Prop} : (∀ x, q ∨ p x) ↔ q ∨ ∀ x, p x :=
Decidable.forall_or_left
#align forall_or_distrib_left forall_or_left
-- See Note [decidable namespace]
protected theorem Decidable.forall_or_right {q} {p : α → Prop} [Decidable q] :
(∀ x, p x ∨ q) ↔ (∀ x, p x) ∨ q := by simp [or_comm, Decidable.forall_or_left]
#align decidable.forall_or_distrib_right Decidable.forall_or_right
theorem forall_or_right {q} {p : α → Prop} : (∀ x, p x ∨ q) ↔ (∀ x, p x) ∨ q :=
Decidable.forall_or_right
#align forall_or_distrib_right forall_or_right
theorem exists_unique_prop {p q : Prop} : (∃! _ : p, q) ↔ p ∧ q := by simp
#align exists_unique_prop exists_unique_prop
@[simp] theorem exists_unique_false : ¬∃! _ : α, False := fun ⟨_, h, _⟩ ↦ h
#align exists_unique_false exists_unique_false
theorem Exists.fst {b : Prop} {p : b → Prop} : Exists p → b
| ⟨h, _⟩ => h
#align Exists.fst Exists.fst
theorem Exists.snd {b : Prop} {p : b → Prop} : ∀ h : Exists p, p h.fst
| ⟨_, h⟩ => h
#align Exists.snd Exists.snd
theorem Prop.exists_iff {p : Prop → Prop} : (∃ h, p h) ↔ p False ∨ p True :=
⟨fun ⟨h₁, h₂⟩ ↦ by_cases (fun H : h₁ ↦ .inr <| by simpa only [H] using h₂)
(fun H ↦ .inl <| by simpa only [H] using h₂), fun h ↦ h.elim (.intro _) (.intro _)⟩
theorem Prop.forall_iff {p : Prop → Prop} : (∀ h, p h) ↔ p False ∧ p True :=
⟨fun H ↦ ⟨H _, H _⟩, fun ⟨h₁, h₂⟩ h ↦ by by_cases H : h <;> simpa only [H]⟩
theorem exists_prop_of_true {p : Prop} {q : p → Prop} (h : p) : (∃ h' : p, q h') ↔ q h :=
@exists_const (q h) p ⟨h⟩
#align exists_prop_of_true exists_prop_of_true
theorem exists_iff_of_forall {p : Prop} {q : p → Prop} (h : ∀ h, q h) : (∃ h, q h) ↔ p :=
⟨Exists.fst, fun H ↦ ⟨H, h H⟩⟩
#align exists_iff_of_forall exists_iff_of_forall
theorem exists_unique_prop_of_true {p : Prop} {q : p → Prop} (h : p) : (∃! h' : p, q h') ↔ q h :=
@exists_unique_const (q h) p ⟨h⟩ _
#align exists_unique_prop_of_true exists_unique_prop_of_true
#align forall_prop_of_false forall_prop_of_false
theorem exists_prop_of_false {p : Prop} {q : p → Prop} : ¬p → ¬∃ h' : p, q h' :=
mt Exists.fst
#align exists_prop_of_false exists_prop_of_false
@[congr]
theorem exists_prop_congr {p p' : Prop} {q q' : p → Prop} (hq : ∀ h, q h ↔ q' h) (hp : p ↔ p') :
Exists q ↔ ∃ h : p', q' (hp.2 h) :=
⟨fun ⟨_, _⟩ ↦ ⟨hp.1 ‹_›, (hq _).1 ‹_›⟩, fun ⟨_, _⟩ ↦ ⟨_, (hq _).2 ‹_›⟩⟩
#align exists_prop_congr exists_prop_congr
/-- See `IsEmpty.exists_iff` for the `False` version. -/
@[simp] theorem exists_true_left (p : True → Prop) : (∃ x, p x) ↔ p True.intro :=
exists_prop_of_true _
#align exists_true_left exists_true_left
-- Porting note: `@[congr]` commented out for now.
-- @[congr]
theorem forall_prop_congr {p p' : Prop} {q q' : p → Prop} (hq : ∀ h, q h ↔ q' h) (hp : p ↔ p') :
(∀ h, q h) ↔ ∀ h : p', q' (hp.2 h) :=
⟨fun h1 h2 ↦ (hq _).1 (h1 (hp.2 h2)), fun h1 h2 ↦ (hq _).2 (h1 (hp.1 h2))⟩
#align forall_prop_congr forall_prop_congr
-- Porting note: `@[congr]` commented out for now.
-- @[congr]
theorem forall_prop_congr' {p p' : Prop} {q q' : p → Prop} (hq : ∀ h, q h ↔ q' h) (hp : p ↔ p') :
(∀ h, q h) = ∀ h : p', q' (hp.2 h) :=
propext (forall_prop_congr hq hp)
#align forall_prop_congr' forall_prop_congr'
#align forall_congr_eq forall_congr
lemma imp_congr_eq {a b c d : Prop} (h₁ : a = c) (h₂ : b = d) : (a → b) = (c → d) :=
propext (imp_congr h₁.to_iff h₂.to_iff)
lemma imp_congr_ctx_eq {a b c d : Prop} (h₁ : a = c) (h₂ : c → b = d) : (a → b) = (c → d) :=
propext (imp_congr_ctx h₁.to_iff fun hc ↦ (h₂ hc).to_iff)
lemma eq_true_intro {a : Prop} (h : a) : a = True := propext (iff_true_intro h)
lemma eq_false_intro {a : Prop} (h : ¬a) : a = False := propext (iff_false_intro h)
-- FIXME: `alias` creates `def Iff.eq := propext` instead of `lemma Iff.eq := propext`
@[nolint defLemma] alias Iff.eq := propext
lemma iff_eq_eq {a b : Prop} : (a ↔ b) = (a = b) := propext ⟨propext, Eq.to_iff⟩
-- They were not used in Lean 3 and there are already lemmas with those names in Lean 4
#noalign eq_false
#noalign eq_true
/-- See `IsEmpty.forall_iff` for the `False` version. -/
@[simp] theorem forall_true_left (p : True → Prop) : (∀ x, p x) ↔ p True.intro :=
forall_prop_of_true _
#align forall_true_left forall_true_left
theorem ExistsUnique.elim₂ {α : Sort*} {p : α → Sort*} [∀ x, Subsingleton (p x)]
{q : ∀ (x) (_ : p x), Prop} {b : Prop} (h₂ : ∃! x, ∃! h : p x, q x h)
(h₁ : ∀ (x) (h : p x), q x h → (∀ (y) (hy : p y), q y hy → y = x) → b) : b := by
simp only [exists_unique_iff_exists] at h₂
apply h₂.elim
exact fun x ⟨hxp, hxq⟩ H ↦ h₁ x hxp hxq fun y hyp hyq ↦ H y ⟨hyp, hyq⟩
#align exists_unique.elim2 ExistsUnique.elim₂
theorem ExistsUnique.intro₂ {α : Sort*} {p : α → Sort*} [∀ x, Subsingleton (p x)]
{q : ∀ (x : α) (_ : p x), Prop} (w : α) (hp : p w) (hq : q w hp)
(H : ∀ (y) (hy : p y), q y hy → y = w) : ∃! x, ∃! hx : p x, q x hx := by
simp only [exists_unique_iff_exists]
exact ExistsUnique.intro w ⟨hp, hq⟩ fun y ⟨hyp, hyq⟩ ↦ H y hyp hyq
#align exists_unique.intro2 ExistsUnique.intro₂
theorem ExistsUnique.exists₂ {α : Sort*} {p : α → Sort*} {q : ∀ (x : α) (_ : p x), Prop}
(h : ∃! x, ∃! hx : p x, q x hx) : ∃ (x : _) (hx : p x), q x hx :=
h.exists.imp fun _ hx ↦ hx.exists
#align exists_unique.exists2 ExistsUnique.exists₂
theorem ExistsUnique.unique₂ {α : Sort*} {p : α → Sort*} [∀ x, Subsingleton (p x)]
{q : ∀ (x : α) (_ : p x), Prop} (h : ∃! x, ∃! hx : p x, q x hx) {y₁ y₂ : α}
(hpy₁ : p y₁) (hqy₁ : q y₁ hpy₁) (hpy₂ : p y₂) (hqy₂ : q y₂ hpy₂) : y₁ = y₂ := by
simp only [exists_unique_iff_exists] at h
exact h.unique ⟨hpy₁, hqy₁⟩ ⟨hpy₂, hqy₂⟩
#align exists_unique.unique2 ExistsUnique.unique₂
end Quantifiers
/-! ### Classical lemmas -/
namespace Classical
-- use shortened names to avoid conflict when classical namespace is open.
/-- Any prop `p` is decidable classically. A shorthand for `Classical.propDecidable`. -/
noncomputable def dec (p : Prop) : Decidable p := by infer_instance
#align classical.dec Classical.dec
variable {α : Sort*} {p : α → Prop}
/-- Any predicate `p` is decidable classically. -/
noncomputable def decPred (p : α → Prop) : DecidablePred p := by infer_instance
#align classical.dec_pred Classical.decPred
/-- Any relation `p` is decidable classically. -/
noncomputable def decRel (p : α → α → Prop) : DecidableRel p := by infer_instance
#align classical.dec_rel Classical.decRel
/-- Any type `α` has decidable equality classically. -/
noncomputable def decEq (α : Sort*) : DecidableEq α := by infer_instance
#align classical.dec_eq Classical.decEq
/-- Construct a function from a default value `H0`, and a function to use if there exists a value
satisfying the predicate. -/
-- @[elab_as_elim] -- FIXME
noncomputable def existsCases {α C : Sort*} {p : α → Prop} (H0 : C) (H : ∀ a, p a → C) : C :=
if h : ∃ a, p a then H (Classical.choose h) (Classical.choose_spec h) else H0
#align classical.exists_cases Classical.existsCases
theorem some_spec₂ {α : Sort*} {p : α → Prop} {h : ∃ a, p a} (q : α → Prop)
(hpq : ∀ a, p a → q a) : q (choose h) := hpq _ <| choose_spec _
#align classical.some_spec2 Classical.some_spec₂
/-- A version of `Classical.indefiniteDescription` which is definitionally equal to a pair -/
noncomputable def subtype_of_exists {α : Type*} {P : α → Prop} (h : ∃ x, P x) : { x // P x } :=
⟨Classical.choose h, Classical.choose_spec h⟩
#align classical.subtype_of_exists Classical.subtype_of_exists
/-- A version of `byContradiction` that uses types instead of propositions. -/
protected noncomputable def byContradiction' {α : Sort*} (H : ¬(α → False)) : α :=
Classical.choice <| (peirce _ False) fun h ↦ (H fun a ↦ h ⟨a⟩).elim
#align classical.by_contradiction' Classical.byContradiction'
/-- `classical.byContradiction'` is equivalent to lean's axiom `classical.choice`. -/
def choice_of_byContradiction' {α : Sort*} (contra : ¬(α → False) → α) : Nonempty α → α :=
fun H ↦ contra H.elim
#align classical.choice_of_by_contradiction' Classical.choice_of_byContradiction'
end Classical
set_option autoImplicit true in
/-- This function has the same type as `Exists.recOn`, and can be used to case on an equality,
but `Exists.recOn` can only eliminate into Prop, while this version eliminates into any universe
using the axiom of choice. -/
-- @[elab_as_elim] -- FIXME
noncomputable def Exists.classicalRecOn {p : α → Prop} (h : ∃ a, p a) {C} (H : ∀ a, p a → C) : C :=
H (Classical.choose h) (Classical.choose_spec h)
#align exists.classical_rec_on Exists.classicalRecOn
/-! ### Declarations about bounded quantifiers -/
section BoundedQuantifiers
variable {α : Sort*} {r p q : α → Prop} {P Q : ∀ x, p x → Prop} {b : Prop}
theorem bex_def : (∃ (x : _) (_ : p x), q x) ↔ ∃ x, p x ∧ q x :=
⟨fun ⟨x, px, qx⟩ ↦ ⟨x, px, qx⟩, fun ⟨x, px, qx⟩ ↦ ⟨x, px, qx⟩⟩
#align bex_def bex_def
theorem BEx.elim {b : Prop} : (∃ x h, P x h) → (∀ a h, P a h → b) → b
| ⟨a, h₁, h₂⟩, h' => h' a h₁ h₂
#align bex.elim BEx.elim
theorem BEx.intro (a : α) (h₁ : p a) (h₂ : P a h₁) : ∃ (x : _) (h : p x), P x h :=
⟨a, h₁, h₂⟩
#align bex.intro BEx.intro
#align ball_congr forall₂_congr
#align bex_congr exists₂_congr
@[deprecated exists_eq_left (since := "2024-04-06")]
theorem bex_eq_left {a : α} : (∃ (x : _) (_ : x = a), p x) ↔ p a := by
simp only [exists_prop, exists_eq_left]
#align bex_eq_left bex_eq_left
@[deprecated (since := "2024-04-06")] alias ball_congr := forall₂_congr
@[deprecated (since := "2024-04-06")] alias bex_congr := exists₂_congr
theorem BAll.imp_right (H : ∀ x h, P x h → Q x h) (h₁ : ∀ x h, P x h) (x h) : Q x h :=
H _ _ <| h₁ _ _
#align ball.imp_right BAll.imp_right
theorem BEx.imp_right (H : ∀ x h, P x h → Q x h) : (∃ x h, P x h) → ∃ x h, Q x h
| ⟨_, _, h'⟩ => ⟨_, _, H _ _ h'⟩
#align bex.imp_right BEx.imp_right
theorem BAll.imp_left (H : ∀ x, p x → q x) (h₁ : ∀ x, q x → r x) (x) (h : p x) : r x :=
h₁ _ <| H _ h
#align ball.imp_left BAll.imp_left
theorem BEx.imp_left (H : ∀ x, p x → q x) : (∃ (x : _) (_ : p x), r x) → ∃ (x : _) (_ : q x), r x
| ⟨x, hp, hr⟩ => ⟨x, H _ hp, hr⟩
#align bex.imp_left BEx.imp_left
@[deprecated id (since := "2024-03-23")]
theorem ball_of_forall (h : ∀ x, p x) (x) : p x := h x
#align ball_of_forall ball_of_forall
@[deprecated forall_imp (since := "2024-03-23")]
theorem forall_of_ball (H : ∀ x, p x) (h : ∀ x, p x → q x) (x) : q x := h x <| H x
#align forall_of_ball forall_of_ball
theorem exists_mem_of_exists (H : ∀ x, p x) : (∃ x, q x) → ∃ (x : _) (_ : p x), q x
| ⟨x, hq⟩ => ⟨x, H x, hq⟩
#align bex_of_exists exists_mem_of_exists
theorem exists_of_exists_mem : (∃ (x : _) (_ : p x), q x) → ∃ x, q x
| ⟨x, _, hq⟩ => ⟨x, hq⟩
#align exists_of_bex exists_of_exists_mem
theorem exists₂_imp : (∃ x h, P x h) → b ↔ ∀ x h, P x h → b := by simp
#align bex_imp_distrib exists₂_imp
@[deprecated (since := "2024-03-23")] alias bex_of_exists := exists_mem_of_exists
@[deprecated (since := "2024-03-23")] alias exists_of_bex := exists_of_exists_mem
@[deprecated (since := "2024-03-23")] alias bex_imp := exists₂_imp
theorem not_exists_mem : (¬∃ x h, P x h) ↔ ∀ x h, ¬P x h := exists₂_imp
#align not_bex not_exists_mem
theorem not_forall₂_of_exists₂_not : (∃ x h, ¬P x h) → ¬∀ x h, P x h
| ⟨x, h, hp⟩, al => hp <| al x h
#align not_ball_of_bex_not not_forall₂_of_exists₂_not
-- See Note [decidable namespace]
protected theorem Decidable.not_forall₂ [Decidable (∃ x h, ¬P x h)] [∀ x h, Decidable (P x h)] :
(¬∀ x h, P x h) ↔ ∃ x h, ¬P x h :=
⟨Not.decidable_imp_symm fun nx x h ↦ nx.decidable_imp_symm
fun h' ↦ ⟨x, h, h'⟩, not_forall₂_of_exists₂_not⟩
#align decidable.not_ball Decidable.not_forall₂
theorem not_forall₂ : (¬∀ x h, P x h) ↔ ∃ x h, ¬P x h := Decidable.not_forall₂
#align not_ball not_forall₂
#align ball_true_iff forall₂_true_iff
theorem forall₂_and : (∀ x h, P x h ∧ Q x h) ↔ (∀ x h, P x h) ∧ ∀ x h, Q x h :=
Iff.trans (forall_congr' fun _ ↦ forall_and) forall_and
#align ball_and_distrib forall₂_and
theorem exists_mem_or : (∃ x h, P x h ∨ Q x h) ↔ (∃ x h, P x h) ∨ ∃ x h, Q x h :=
Iff.trans (exists_congr fun _ ↦ exists_or) exists_or
#align bex_or_distrib exists_mem_or
theorem forall₂_or_left : (∀ x, p x ∨ q x → r x) ↔ (∀ x, p x → r x) ∧ ∀ x, q x → r x :=
Iff.trans (forall_congr' fun _ ↦ or_imp) forall_and
#align ball_or_left_distrib forall₂_or_left
theorem exists_mem_or_left :
(∃ (x : _) (_ : p x ∨ q x), r x) ↔ (∃ (x : _) (_ : p x), r x) ∨ ∃ (x : _) (_ : q x), r x := by
simp only [exists_prop]
exact Iff.trans (exists_congr fun x ↦ or_and_right) exists_or
#align bex_or_left_distrib exists_mem_or_left
@[deprecated (since := "2023-03-23")] alias not_ball_of_bex_not := not_forall₂_of_exists₂_not
@[deprecated (since := "2023-03-23")] alias Decidable.not_ball := Decidable.not_forall₂
@[deprecated (since := "2023-03-23")] alias not_ball := not_forall₂
@[deprecated (since := "2023-03-23")] alias ball_true_iff := forall₂_true_iff
@[deprecated (since := "2023-03-23")] alias ball_and := forall₂_and
@[deprecated (since := "2023-03-23")] alias not_bex := not_exists_mem
@[deprecated (since := "2023-03-23")] alias bex_or := exists_mem_or
@[deprecated (since := "2023-03-23")] alias ball_or_left := forall₂_or_left
@[deprecated (since := "2023-03-23")] alias bex_or_left := exists_mem_or_left
end BoundedQuantifiers
#align classical.not_ball not_ball
section ite
variable {α : Sort*} {σ : α → Sort*} {P Q R : Prop} [Decidable P] [Decidable Q]
{a b c : α} {A : P → α} {B : ¬P → α}
theorem dite_eq_iff : dite P A B = c ↔ (∃ h, A h = c) ∨ ∃ h, B h = c := by
by_cases P <;> simp [*, exists_prop_of_true, exists_prop_of_false]
#align dite_eq_iff dite_eq_iff
theorem ite_eq_iff : ite P a b = c ↔ P ∧ a = c ∨ ¬P ∧ b = c :=
dite_eq_iff.trans <| by simp only; rw [exists_prop, exists_prop]
#align ite_eq_iff ite_eq_iff
theorem eq_ite_iff : a = ite P b c ↔ P ∧ a = b ∨ ¬P ∧ a = c :=
eq_comm.trans <| ite_eq_iff.trans <| (Iff.rfl.and eq_comm).or (Iff.rfl.and eq_comm)
theorem dite_eq_iff' : dite P A B = c ↔ (∀ h, A h = c) ∧ ∀ h, B h = c :=
⟨fun he ↦ ⟨fun h ↦ (dif_pos h).symm.trans he, fun h ↦ (dif_neg h).symm.trans he⟩, fun he ↦
(em P).elim (fun h ↦ (dif_pos h).trans <| he.1 h) fun h ↦ (dif_neg h).trans <| he.2 h⟩
#align dite_eq_iff' dite_eq_iff'
theorem ite_eq_iff' : ite P a b = c ↔ (P → a = c) ∧ (¬P → b = c) := dite_eq_iff'
#align ite_eq_iff' ite_eq_iff'
#align dite_eq_left_iff dite_eq_left_iff
#align dite_eq_right_iff dite_eq_right_iff
#align ite_eq_left_iff ite_eq_left_iff
#align ite_eq_right_iff ite_eq_right_iff
theorem dite_ne_left_iff : dite P (fun _ ↦ a) B ≠ a ↔ ∃ h, a ≠ B h := by
rw [Ne, dite_eq_left_iff, not_forall]
exact exists_congr fun h ↦ by rw [ne_comm]
#align dite_ne_left_iff dite_ne_left_iff
| Mathlib/Logic/Basic.lean | 1,223 | 1,224 | theorem dite_ne_right_iff : (dite P A fun _ ↦ b) ≠ b ↔ ∃ h, A h ≠ b := by |
simp only [Ne, dite_eq_right_iff, not_forall]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Yury Kudryashov
-/
import Mathlib.Data.Rat.Sqrt
import Mathlib.Data.Real.Sqrt
import Mathlib.RingTheory.Algebraic
import Mathlib.RingTheory.Int.Basic
import Mathlib.Tactic.IntervalCases
#align_import data.real.irrational from "leanprover-community/mathlib"@"7e7aaccf9b0182576cabdde36cf1b5ad3585b70d"
/-!
# Irrational real numbers
In this file we define a predicate `Irrational` on `ℝ`, prove that the `n`-th root of an integer
number is irrational if it is not integer, and that `sqrt q` is irrational if and only if
`Rat.sqrt q * Rat.sqrt q ≠ q ∧ 0 ≤ q`.
We also provide dot-style constructors like `Irrational.add_rat`, `Irrational.rat_sub` etc.
-/
open Rat Real multiplicity
/-- A real number is irrational if it is not equal to any rational number. -/
def Irrational (x : ℝ) :=
x ∉ Set.range ((↑) : ℚ → ℝ)
#align irrational Irrational
theorem irrational_iff_ne_rational (x : ℝ) : Irrational x ↔ ∀ a b : ℤ, x ≠ a / b := by
simp only [Irrational, Rat.forall, cast_mk, not_exists, Set.mem_range, cast_intCast, cast_div,
eq_comm]
#align irrational_iff_ne_rational irrational_iff_ne_rational
/-- A transcendental real number is irrational. -/
theorem Transcendental.irrational {r : ℝ} (tr : Transcendental ℚ r) : Irrational r := by
rintro ⟨a, rfl⟩
exact tr (isAlgebraic_algebraMap a)
#align transcendental.irrational Transcendental.irrational
/-!
### Irrationality of roots of integer and rational numbers
-/
/-- If `x^n`, `n > 0`, is integer and is not the `n`-th power of an integer, then
`x` is irrational. -/
theorem irrational_nrt_of_notint_nrt {x : ℝ} (n : ℕ) (m : ℤ) (hxr : x ^ n = m)
(hv : ¬∃ y : ℤ, x = y) (hnpos : 0 < n) : Irrational x := by
rintro ⟨⟨N, D, P, C⟩, rfl⟩
rw [← cast_pow] at hxr
have c1 : ((D : ℤ) : ℝ) ≠ 0 := by
rw [Int.cast_ne_zero, Int.natCast_ne_zero]
exact P
have c2 : ((D : ℤ) : ℝ) ^ n ≠ 0 := pow_ne_zero _ c1
rw [mk'_eq_divInt, cast_pow, cast_mk, div_pow, div_eq_iff_mul_eq c2, ← Int.cast_pow,
← Int.cast_pow, ← Int.cast_mul, Int.cast_inj] at hxr
have hdivn : (D : ℤ) ^ n ∣ N ^ n := Dvd.intro_left m hxr
rw [← Int.dvd_natAbs, ← Int.natCast_pow, Int.natCast_dvd_natCast, Int.natAbs_pow,
Nat.pow_dvd_pow_iff hnpos.ne'] at hdivn
obtain rfl : D = 1 := by rw [← Nat.gcd_eq_right hdivn, C.gcd_eq_one]
refine hv ⟨N, ?_⟩
rw [mk'_eq_divInt, Int.ofNat_one, divInt_one, cast_intCast]
#align irrational_nrt_of_notint_nrt irrational_nrt_of_notint_nrt
/-- If `x^n = m` is an integer and `n` does not divide the `multiplicity p m`, then `x`
is irrational. -/
theorem irrational_nrt_of_n_not_dvd_multiplicity {x : ℝ} (n : ℕ) {m : ℤ} (hm : m ≠ 0) (p : ℕ)
[hp : Fact p.Prime] (hxr : x ^ n = m)
(hv : (multiplicity (p : ℤ) m).get (finite_int_iff.2 ⟨hp.1.ne_one, hm⟩) % n ≠ 0) :
Irrational x := by
rcases Nat.eq_zero_or_pos n with (rfl | hnpos)
· rw [eq_comm, pow_zero, ← Int.cast_one, Int.cast_inj] at hxr
simp [hxr, multiplicity.one_right (mt isUnit_iff_dvd_one.1
(mt Int.natCast_dvd_natCast.1 hp.1.not_dvd_one)), Nat.zero_mod] at hv
refine irrational_nrt_of_notint_nrt _ _ hxr ?_ hnpos
rintro ⟨y, rfl⟩
rw [← Int.cast_pow, Int.cast_inj] at hxr
subst m
have : y ≠ 0 := by rintro rfl; rw [zero_pow hnpos.ne'] at hm; exact hm rfl
erw [multiplicity.pow' (Nat.prime_iff_prime_int.1 hp.1) (finite_int_iff.2 ⟨hp.1.ne_one, this⟩),
Nat.mul_mod_right] at hv
exact hv rfl
#align irrational_nrt_of_n_not_dvd_multiplicity irrational_nrt_of_n_not_dvd_multiplicity
theorem irrational_sqrt_of_multiplicity_odd (m : ℤ) (hm : 0 < m) (p : ℕ) [hp : Fact p.Prime]
(Hpv :
(multiplicity (p : ℤ) m).get (finite_int_iff.2 ⟨hp.1.ne_one, (ne_of_lt hm).symm⟩) % 2 = 1) :
Irrational (√m) :=
@irrational_nrt_of_n_not_dvd_multiplicity _ 2 _ (Ne.symm (ne_of_lt hm)) p hp
(sq_sqrt (Int.cast_nonneg.2 <| le_of_lt hm)) (by rw [Hpv]; exact one_ne_zero)
#align irrational_sqrt_of_multiplicity_odd irrational_sqrt_of_multiplicity_odd
theorem Nat.Prime.irrational_sqrt {p : ℕ} (hp : Nat.Prime p) : Irrational (√p) :=
@irrational_sqrt_of_multiplicity_odd p (Int.natCast_pos.2 hp.pos) p ⟨hp⟩ <| by
simp [multiplicity.multiplicity_self
(mt isUnit_iff_dvd_one.1 (mt Int.natCast_dvd_natCast.1 hp.not_dvd_one))]
#align nat.prime.irrational_sqrt Nat.Prime.irrational_sqrt
/-- **Irrationality of the Square Root of 2** -/
theorem irrational_sqrt_two : Irrational (√2) := by
simpa using Nat.prime_two.irrational_sqrt
#align irrational_sqrt_two irrational_sqrt_two
theorem irrational_sqrt_rat_iff (q : ℚ) :
Irrational (√q) ↔ Rat.sqrt q * Rat.sqrt q ≠ q ∧ 0 ≤ q :=
if H1 : Rat.sqrt q * Rat.sqrt q = q then
iff_of_false
(not_not_intro
⟨Rat.sqrt q, by
rw [← H1, cast_mul, sqrt_mul_self (cast_nonneg.2 <| Rat.sqrt_nonneg q), sqrt_eq,
abs_of_nonneg (Rat.sqrt_nonneg q)]⟩)
fun h => h.1 H1
else
if H2 : 0 ≤ q then
iff_of_true
(fun ⟨r, hr⟩ =>
H1 <|
(exists_mul_self _).1
⟨r, by
rwa [eq_comm, sqrt_eq_iff_mul_self_eq (cast_nonneg.2 H2), ← cast_mul,
Rat.cast_inj] at hr
rw [← hr]
exact Real.sqrt_nonneg _⟩)
⟨H1, H2⟩
else
iff_of_false
(not_not_intro
⟨0, by
rw [cast_zero]
exact (sqrt_eq_zero_of_nonpos (Rat.cast_nonpos.2 <| le_of_not_le H2)).symm⟩)
fun h => H2 h.2
#align irrational_sqrt_rat_iff irrational_sqrt_rat_iff
instance (q : ℚ) : Decidable (Irrational (√q)) :=
decidable_of_iff' _ (irrational_sqrt_rat_iff q)
/-!
### Dot-style operations on `Irrational`
#### Coercion of a rational/integer/natural number is not irrational
-/
namespace Irrational
variable {x : ℝ}
/-!
#### Irrational number is not equal to a rational/integer/natural number
-/
theorem ne_rat (h : Irrational x) (q : ℚ) : x ≠ q := fun hq => h ⟨q, hq.symm⟩
#align irrational.ne_rat Irrational.ne_rat
theorem ne_int (h : Irrational x) (m : ℤ) : x ≠ m := by
rw [← Rat.cast_intCast]
exact h.ne_rat _
#align irrational.ne_int Irrational.ne_int
theorem ne_nat (h : Irrational x) (m : ℕ) : x ≠ m :=
h.ne_int m
#align irrational.ne_nat Irrational.ne_nat
theorem ne_zero (h : Irrational x) : x ≠ 0 := mod_cast h.ne_nat 0
#align irrational.ne_zero Irrational.ne_zero
theorem ne_one (h : Irrational x) : x ≠ 1 := by simpa only [Nat.cast_one] using h.ne_nat 1
#align irrational.ne_one Irrational.ne_one
end Irrational
@[simp]
theorem Rat.not_irrational (q : ℚ) : ¬Irrational q := fun h => h ⟨q, rfl⟩
#align rat.not_irrational Rat.not_irrational
@[simp]
theorem Int.not_irrational (m : ℤ) : ¬Irrational m := fun h => h.ne_int m rfl
#align int.not_irrational Int.not_irrational
@[simp]
theorem Nat.not_irrational (m : ℕ) : ¬Irrational m := fun h => h.ne_nat m rfl
#align nat.not_irrational Nat.not_irrational
namespace Irrational
variable (q : ℚ) {x y : ℝ}
/-!
#### Addition of rational/integer/natural numbers
-/
/-- If `x + y` is irrational, then at least one of `x` and `y` is irrational. -/
theorem add_cases : Irrational (x + y) → Irrational x ∨ Irrational y := by
delta Irrational
contrapose!
rintro ⟨⟨rx, rfl⟩, ⟨ry, rfl⟩⟩
exact ⟨rx + ry, cast_add rx ry⟩
#align irrational.add_cases Irrational.add_cases
theorem of_rat_add (h : Irrational (q + x)) : Irrational x :=
h.add_cases.resolve_left q.not_irrational
#align irrational.of_rat_add Irrational.of_rat_add
theorem rat_add (h : Irrational x) : Irrational (q + x) :=
of_rat_add (-q) <| by rwa [cast_neg, neg_add_cancel_left]
#align irrational.rat_add Irrational.rat_add
theorem of_add_rat : Irrational (x + q) → Irrational x :=
add_comm (↑q) x ▸ of_rat_add q
#align irrational.of_add_rat Irrational.of_add_rat
theorem add_rat (h : Irrational x) : Irrational (x + q) :=
add_comm (↑q) x ▸ h.rat_add q
#align irrational.add_rat Irrational.add_rat
theorem of_int_add (m : ℤ) (h : Irrational (m + x)) : Irrational x := by
rw [← cast_intCast] at h
exact h.of_rat_add m
#align irrational.of_int_add Irrational.of_int_add
theorem of_add_int (m : ℤ) (h : Irrational (x + m)) : Irrational x :=
of_int_add m <| add_comm x m ▸ h
#align irrational.of_add_int Irrational.of_add_int
theorem int_add (h : Irrational x) (m : ℤ) : Irrational (m + x) := by
rw [← cast_intCast]
exact h.rat_add m
#align irrational.int_add Irrational.int_add
theorem add_int (h : Irrational x) (m : ℤ) : Irrational (x + m) :=
add_comm (↑m) x ▸ h.int_add m
#align irrational.add_int Irrational.add_int
theorem of_nat_add (m : ℕ) (h : Irrational (m + x)) : Irrational x :=
h.of_int_add m
#align irrational.of_nat_add Irrational.of_nat_add
theorem of_add_nat (m : ℕ) (h : Irrational (x + m)) : Irrational x :=
h.of_add_int m
#align irrational.of_add_nat Irrational.of_add_nat
theorem nat_add (h : Irrational x) (m : ℕ) : Irrational (m + x) :=
h.int_add m
#align irrational.nat_add Irrational.nat_add
theorem add_nat (h : Irrational x) (m : ℕ) : Irrational (x + m) :=
h.add_int m
#align irrational.add_nat Irrational.add_nat
/-!
#### Negation
-/
theorem of_neg (h : Irrational (-x)) : Irrational x := fun ⟨q, hx⟩ => h ⟨-q, by rw [cast_neg, hx]⟩
#align irrational.of_neg Irrational.of_neg
protected theorem neg (h : Irrational x) : Irrational (-x) :=
of_neg <| by rwa [neg_neg]
#align irrational.neg Irrational.neg
/-!
#### Subtraction of rational/integer/natural numbers
-/
theorem sub_rat (h : Irrational x) : Irrational (x - q) := by
simpa only [sub_eq_add_neg, cast_neg] using h.add_rat (-q)
#align irrational.sub_rat Irrational.sub_rat
theorem rat_sub (h : Irrational x) : Irrational (q - x) := by
simpa only [sub_eq_add_neg] using h.neg.rat_add q
#align irrational.rat_sub Irrational.rat_sub
theorem of_sub_rat (h : Irrational (x - q)) : Irrational x :=
of_add_rat (-q) <| by simpa only [cast_neg, sub_eq_add_neg] using h
#align irrational.of_sub_rat Irrational.of_sub_rat
theorem of_rat_sub (h : Irrational (q - x)) : Irrational x :=
of_neg (of_rat_add q (by simpa only [sub_eq_add_neg] using h))
#align irrational.of_rat_sub Irrational.of_rat_sub
theorem sub_int (h : Irrational x) (m : ℤ) : Irrational (x - m) := by
simpa only [Rat.cast_intCast] using h.sub_rat m
#align irrational.sub_int Irrational.sub_int
theorem int_sub (h : Irrational x) (m : ℤ) : Irrational (m - x) := by
simpa only [Rat.cast_intCast] using h.rat_sub m
#align irrational.int_sub Irrational.int_sub
theorem of_sub_int (m : ℤ) (h : Irrational (x - m)) : Irrational x :=
of_sub_rat m <| by rwa [Rat.cast_intCast]
#align irrational.of_sub_int Irrational.of_sub_int
theorem of_int_sub (m : ℤ) (h : Irrational (m - x)) : Irrational x :=
of_rat_sub m <| by rwa [Rat.cast_intCast]
#align irrational.of_int_sub Irrational.of_int_sub
theorem sub_nat (h : Irrational x) (m : ℕ) : Irrational (x - m) :=
h.sub_int m
#align irrational.sub_nat Irrational.sub_nat
theorem nat_sub (h : Irrational x) (m : ℕ) : Irrational (m - x) :=
h.int_sub m
#align irrational.nat_sub Irrational.nat_sub
theorem of_sub_nat (m : ℕ) (h : Irrational (x - m)) : Irrational x :=
h.of_sub_int m
#align irrational.of_sub_nat Irrational.of_sub_nat
theorem of_nat_sub (m : ℕ) (h : Irrational (m - x)) : Irrational x :=
h.of_int_sub m
#align irrational.of_nat_sub Irrational.of_nat_sub
/-!
#### Multiplication by rational numbers
-/
theorem mul_cases : Irrational (x * y) → Irrational x ∨ Irrational y := by
delta Irrational
contrapose!
rintro ⟨⟨rx, rfl⟩, ⟨ry, rfl⟩⟩
exact ⟨rx * ry, cast_mul rx ry⟩
#align irrational.mul_cases Irrational.mul_cases
theorem of_mul_rat (h : Irrational (x * q)) : Irrational x :=
h.mul_cases.resolve_right q.not_irrational
#align irrational.of_mul_rat Irrational.of_mul_rat
theorem mul_rat (h : Irrational x) {q : ℚ} (hq : q ≠ 0) : Irrational (x * q) :=
of_mul_rat q⁻¹ <| by rwa [mul_assoc, ← cast_mul, mul_inv_cancel hq, cast_one, mul_one]
#align irrational.mul_rat Irrational.mul_rat
theorem of_rat_mul : Irrational (q * x) → Irrational x :=
mul_comm x q ▸ of_mul_rat q
#align irrational.of_rat_mul Irrational.of_rat_mul
theorem rat_mul (h : Irrational x) {q : ℚ} (hq : q ≠ 0) : Irrational (q * x) :=
mul_comm x q ▸ h.mul_rat hq
#align irrational.rat_mul Irrational.rat_mul
theorem of_mul_int (m : ℤ) (h : Irrational (x * m)) : Irrational x :=
of_mul_rat m <| by rwa [cast_intCast]
#align irrational.of_mul_int Irrational.of_mul_int
theorem of_int_mul (m : ℤ) (h : Irrational (m * x)) : Irrational x :=
of_rat_mul m <| by rwa [cast_intCast]
#align irrational.of_int_mul Irrational.of_int_mul
| Mathlib/Data/Real/Irrational.lean | 356 | 359 | theorem mul_int (h : Irrational x) {m : ℤ} (hm : m ≠ 0) : Irrational (x * m) := by |
rw [← cast_intCast]
refine h.mul_rat ?_
rwa [Int.cast_ne_zero]
|
/-
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
#align_import ring_theory.polynomial.scale_roots from "leanprover-community/mathlib"@"40ac1b258344e0c2b4568dc37bfad937ec35a727"
/-!
# 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
open 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))
#align polynomial.scale_roots Polynomial.scaleRoots
@[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 (config := { contextual := true }) [scaleRoots, coeff_monomial]
#align polynomial.coeff_scale_roots Polynomial.coeff_scaleRoots
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]
#align polynomial.coeff_scale_roots_nat_degree Polynomial.coeff_scaleRoots_natDegree
@[simp]
theorem zero_scaleRoots (s : R) : scaleRoots 0 s = 0 := by
ext
simp
#align polynomial.zero_scale_roots Polynomial.zero_scaleRoots
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
#align polynomial.scale_roots_ne_zero Polynomial.scaleRoots_ne_zero
theorem support_scaleRoots_le (p : R[X]) (s : R) : (scaleRoots p s).support ≤ p.support := by
intro
simpa using left_ne_zero_of_mul
#align polynomial.support_scale_roots_le Polynomial.support_scaleRoots_le
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)
#align polynomial.support_scale_roots_eq Polynomial.support_scaleRoots_eq
@[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
#align polynomial.degree_scale_roots Polynomial.degree_scaleRoots
@[simp]
theorem natDegree_scaleRoots (p : R[X]) (s : R) : natDegree (scaleRoots p s) = natDegree p := by
simp only [natDegree, degree_scaleRoots]
#align polynomial.nat_degree_scale_roots Polynomial.natDegree_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]
#align polynomial.monic_scale_roots_iff Polynomial.monic_scaleRoots_iff
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]
#align polynomial.map_scale_roots Polynomial.map_scaleRoots
@[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, ge_iff_le, 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 _ _
#align polynomial.scale_roots_eval₂_mul Polynomial.scaleRoots_eval₂_mul
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]
#align polynomial.scale_roots_eval₂_eq_zero Polynomial.scaleRoots_eval₂_eq_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]
#align polynomial.scale_roots_aeval_eq_zero Polynomial.scaleRoots_aeval_eq_zero
| Mathlib/RingTheory/Polynomial/ScaleRoots.lean | 170 | 177 | 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 |
set_option tactic.skipAssignedInstances false in
nontriviality S using Subsingleton.eq_zero
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
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen
-/
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.LinearAlgebra.StdBasis
import Mathlib.RingTheory.AlgebraTower
import Mathlib.Algebra.Algebra.Subalgebra.Tower
#align_import linear_algebra.matrix.to_lin from "leanprover-community/mathlib"@"0e2aab2b0d521f060f62a14d2cf2e2c54e8491d6"
/-!
# Linear maps and matrices
This file defines the maps to send matrices to a linear map,
and to send linear maps between modules with a finite bases
to matrices. This defines a linear equivalence between linear maps
between finite-dimensional vector spaces and matrices indexed by
the respective bases.
## Main definitions
In the list below, and in all this file, `R` is a commutative ring (semiring
is sometimes enough), `M` and its variations are `R`-modules, `ι`, `κ`, `n` and `m` are finite
types used for indexing.
* `LinearMap.toMatrix`: given bases `v₁ : ι → M₁` and `v₂ : κ → M₂`,
the `R`-linear equivalence from `M₁ →ₗ[R] M₂` to `Matrix κ ι R`
* `Matrix.toLin`: the inverse of `LinearMap.toMatrix`
* `LinearMap.toMatrix'`: the `R`-linear equivalence from `(m → R) →ₗ[R] (n → R)`
to `Matrix m n R` (with the standard basis on `m → R` and `n → R`)
* `Matrix.toLin'`: the inverse of `LinearMap.toMatrix'`
* `algEquivMatrix`: given a basis indexed by `n`, the `R`-algebra equivalence between
`R`-endomorphisms of `M` and `Matrix n n R`
## Issues
This file was originally written without attention to non-commutative rings,
and so mostly only works in the commutative setting. This should be fixed.
In particular, `Matrix.mulVec` gives us a linear equivalence
`Matrix m n R ≃ₗ[R] (n → R) →ₗ[Rᵐᵒᵖ] (m → R)`
while `Matrix.vecMul` gives us a linear equivalence
`Matrix m n R ≃ₗ[Rᵐᵒᵖ] (m → R) →ₗ[R] (n → R)`.
At present, the first equivalence is developed in detail but only for commutative rings
(and we omit the distinction between `Rᵐᵒᵖ` and `R`),
while the second equivalence is developed only in brief, but for not-necessarily-commutative rings.
Naming is slightly inconsistent between the two developments.
In the original (commutative) development `linear` is abbreviated to `lin`,
although this is not consistent with the rest of mathlib.
In the new (non-commutative) development `linear` is not abbreviated, and declarations use `_right`
to indicate they use the right action of matrices on vectors (via `Matrix.vecMul`).
When the two developments are made uniform, the names should be made uniform, too,
by choosing between `linear` and `lin` consistently,
and (presumably) adding `_left` where necessary.
## Tags
linear_map, matrix, linear_equiv, diagonal, det, trace
-/
noncomputable section
open LinearMap Matrix Set Submodule
section ToMatrixRight
variable {R : Type*} [Semiring R]
variable {l m n : Type*}
/-- `Matrix.vecMul M` is a linear map. -/
def Matrix.vecMulLinear [Fintype m] (M : Matrix m n R) : (m → R) →ₗ[R] n → R where
toFun x := x ᵥ* M
map_add' _ _ := funext fun _ ↦ add_dotProduct _ _ _
map_smul' _ _ := funext fun _ ↦ smul_dotProduct _ _ _
#align matrix.vec_mul_linear Matrix.vecMulLinear
@[simp] theorem Matrix.vecMulLinear_apply [Fintype m] (M : Matrix m n R) (x : m → R) :
M.vecMulLinear x = x ᵥ* M := rfl
theorem Matrix.coe_vecMulLinear [Fintype m] (M : Matrix m n R) :
(M.vecMulLinear : _ → _) = M.vecMul := rfl
variable [Fintype m] [DecidableEq m]
@[simp]
theorem Matrix.vecMul_stdBasis (M : Matrix m n R) (i j) :
(LinearMap.stdBasis R (fun _ ↦ R) i 1 ᵥ* M) j = M i j := by
have : (∑ i', (if i = i' then 1 else 0) * M i' j) = M i j := by
simp_rw [boole_mul, Finset.sum_ite_eq, Finset.mem_univ, if_true]
simp only [vecMul, dotProduct]
convert this
split_ifs with h <;> simp only [stdBasis_apply]
· rw [h, Function.update_same]
· rw [Function.update_noteq (Ne.symm h), Pi.zero_apply]
#align matrix.vec_mul_std_basis Matrix.vecMul_stdBasis
theorem range_vecMulLinear (M : Matrix m n R) :
LinearMap.range M.vecMulLinear = span R (range M) := by
letI := Classical.decEq m
simp_rw [range_eq_map, ← iSup_range_stdBasis, Submodule.map_iSup, range_eq_map, ←
Ideal.span_singleton_one, Ideal.span, Submodule.map_span, image_image, image_singleton,
Matrix.vecMulLinear_apply, iSup_span, range_eq_iUnion, iUnion_singleton_eq_range,
LinearMap.stdBasis, coe_single]
unfold vecMul
simp_rw [single_dotProduct, one_mul]
theorem Matrix.vecMul_injective_iff {R : Type*} [CommRing R] {M : Matrix m n R} :
Function.Injective M.vecMul ↔ LinearIndependent R (fun i ↦ M i) := by
rw [← coe_vecMulLinear]
simp only [← LinearMap.ker_eq_bot, Fintype.linearIndependent_iff, Submodule.eq_bot_iff,
LinearMap.mem_ker, vecMulLinear_apply]
refine ⟨fun h c h0 ↦ congr_fun <| h c ?_, fun h c h0 ↦ funext <| h c ?_⟩
· rw [← h0]
ext i
simp [vecMul, dotProduct]
· rw [← h0]
ext j
simp [vecMul, dotProduct]
/-- Linear maps `(m → R) →ₗ[R] (n → R)` are linearly equivalent over `Rᵐᵒᵖ` to `Matrix m n R`,
by having matrices act by right multiplication.
-/
def LinearMap.toMatrixRight' : ((m → R) →ₗ[R] n → R) ≃ₗ[Rᵐᵒᵖ] Matrix m n R where
toFun f i j := f (stdBasis R (fun _ ↦ R) i 1) j
invFun := Matrix.vecMulLinear
right_inv M := by
ext i j
simp only [Matrix.vecMul_stdBasis, Matrix.vecMulLinear_apply]
left_inv f := by
apply (Pi.basisFun R m).ext
intro j; ext i
simp only [Pi.basisFun_apply, Matrix.vecMul_stdBasis, Matrix.vecMulLinear_apply]
map_add' f g := by
ext i j
simp only [Pi.add_apply, LinearMap.add_apply, Matrix.add_apply]
map_smul' c f := by
ext i j
simp only [Pi.smul_apply, LinearMap.smul_apply, RingHom.id_apply, Matrix.smul_apply]
#align linear_map.to_matrix_right' LinearMap.toMatrixRight'
/-- A `Matrix m n R` is linearly equivalent over `Rᵐᵒᵖ` to a linear map `(m → R) →ₗ[R] (n → R)`,
by having matrices act by right multiplication. -/
abbrev Matrix.toLinearMapRight' : Matrix m n R ≃ₗ[Rᵐᵒᵖ] (m → R) →ₗ[R] n → R :=
LinearEquiv.symm LinearMap.toMatrixRight'
#align matrix.to_linear_map_right' Matrix.toLinearMapRight'
@[simp]
theorem Matrix.toLinearMapRight'_apply (M : Matrix m n R) (v : m → R) :
(Matrix.toLinearMapRight') M v = v ᵥ* M := rfl
#align matrix.to_linear_map_right'_apply Matrix.toLinearMapRight'_apply
@[simp]
theorem Matrix.toLinearMapRight'_mul [Fintype l] [DecidableEq l] (M : Matrix l m R)
(N : Matrix m n R) :
Matrix.toLinearMapRight' (M * N) =
(Matrix.toLinearMapRight' N).comp (Matrix.toLinearMapRight' M) :=
LinearMap.ext fun _x ↦ (vecMul_vecMul _ M N).symm
#align matrix.to_linear_map_right'_mul Matrix.toLinearMapRight'_mul
theorem Matrix.toLinearMapRight'_mul_apply [Fintype l] [DecidableEq l] (M : Matrix l m R)
(N : Matrix m n R) (x) :
Matrix.toLinearMapRight' (M * N) x =
Matrix.toLinearMapRight' N (Matrix.toLinearMapRight' M x) :=
(vecMul_vecMul _ M N).symm
#align matrix.to_linear_map_right'_mul_apply Matrix.toLinearMapRight'_mul_apply
@[simp]
theorem Matrix.toLinearMapRight'_one :
Matrix.toLinearMapRight' (1 : Matrix m m R) = LinearMap.id := by
ext
simp [LinearMap.one_apply, stdBasis_apply]
#align matrix.to_linear_map_right'_one Matrix.toLinearMapRight'_one
/-- If `M` and `M'` are each other's inverse matrices, they provide an equivalence between `n → A`
and `m → A` corresponding to `M.vecMul` and `M'.vecMul`. -/
@[simps]
def Matrix.toLinearEquivRight'OfInv [Fintype n] [DecidableEq n] {M : Matrix m n R}
{M' : Matrix n m R} (hMM' : M * M' = 1) (hM'M : M' * M = 1) : (n → R) ≃ₗ[R] m → R :=
{ LinearMap.toMatrixRight'.symm M' with
toFun := Matrix.toLinearMapRight' M'
invFun := Matrix.toLinearMapRight' M
left_inv := fun x ↦ by
rw [← Matrix.toLinearMapRight'_mul_apply, hM'M, Matrix.toLinearMapRight'_one, id_apply]
right_inv := fun x ↦ by
dsimp only -- Porting note: needed due to non-flat structures
rw [← Matrix.toLinearMapRight'_mul_apply, hMM', Matrix.toLinearMapRight'_one, id_apply] }
#align matrix.to_linear_equiv_right'_of_inv Matrix.toLinearEquivRight'OfInv
end ToMatrixRight
/-!
From this point on, we only work with commutative rings,
and fail to distinguish between `Rᵐᵒᵖ` and `R`.
This should eventually be remedied.
-/
section mulVec
variable {R : Type*} [CommSemiring R]
variable {k l m n : Type*}
/-- `Matrix.mulVec M` is a linear map. -/
def Matrix.mulVecLin [Fintype n] (M : Matrix m n R) : (n → R) →ₗ[R] m → R where
toFun := M.mulVec
map_add' _ _ := funext fun _ ↦ dotProduct_add _ _ _
map_smul' _ _ := funext fun _ ↦ dotProduct_smul _ _ _
#align matrix.mul_vec_lin Matrix.mulVecLin
theorem Matrix.coe_mulVecLin [Fintype n] (M : Matrix m n R) :
(M.mulVecLin : _ → _) = M.mulVec := rfl
@[simp]
theorem Matrix.mulVecLin_apply [Fintype n] (M : Matrix m n R) (v : n → R) :
M.mulVecLin v = M *ᵥ v :=
rfl
#align matrix.mul_vec_lin_apply Matrix.mulVecLin_apply
@[simp]
theorem Matrix.mulVecLin_zero [Fintype n] : Matrix.mulVecLin (0 : Matrix m n R) = 0 :=
LinearMap.ext zero_mulVec
#align matrix.mul_vec_lin_zero Matrix.mulVecLin_zero
@[simp]
theorem Matrix.mulVecLin_add [Fintype n] (M N : Matrix m n R) :
(M + N).mulVecLin = M.mulVecLin + N.mulVecLin :=
LinearMap.ext fun _ ↦ add_mulVec _ _ _
#align matrix.mul_vec_lin_add Matrix.mulVecLin_add
@[simp] theorem Matrix.mulVecLin_transpose [Fintype m] (M : Matrix m n R) :
Mᵀ.mulVecLin = M.vecMulLinear := by
ext; simp [mulVec_transpose]
@[simp] theorem Matrix.vecMulLinear_transpose [Fintype n] (M : Matrix m n R) :
Mᵀ.vecMulLinear = M.mulVecLin := by
ext; simp [vecMul_transpose]
theorem Matrix.mulVecLin_submatrix [Fintype n] [Fintype l] (f₁ : m → k) (e₂ : n ≃ l)
(M : Matrix k l R) :
(M.submatrix f₁ e₂).mulVecLin = funLeft R R f₁ ∘ₗ M.mulVecLin ∘ₗ funLeft _ _ e₂.symm :=
LinearMap.ext fun _ ↦ submatrix_mulVec_equiv _ _ _ _
#align matrix.mul_vec_lin_submatrix Matrix.mulVecLin_submatrix
/-- A variant of `Matrix.mulVecLin_submatrix` that keeps around `LinearEquiv`s. -/
theorem Matrix.mulVecLin_reindex [Fintype n] [Fintype l] (e₁ : k ≃ m) (e₂ : l ≃ n)
(M : Matrix k l R) :
(reindex e₁ e₂ M).mulVecLin =
↑(LinearEquiv.funCongrLeft R R e₁.symm) ∘ₗ
M.mulVecLin ∘ₗ ↑(LinearEquiv.funCongrLeft R R e₂) :=
Matrix.mulVecLin_submatrix _ _ _
#align matrix.mul_vec_lin_reindex Matrix.mulVecLin_reindex
variable [Fintype n]
@[simp]
theorem Matrix.mulVecLin_one [DecidableEq n] :
Matrix.mulVecLin (1 : Matrix n n R) = LinearMap.id := by
ext; simp [Matrix.one_apply, Pi.single_apply]
#align matrix.mul_vec_lin_one Matrix.mulVecLin_one
@[simp]
theorem Matrix.mulVecLin_mul [Fintype m] (M : Matrix l m R) (N : Matrix m n R) :
Matrix.mulVecLin (M * N) = (Matrix.mulVecLin M).comp (Matrix.mulVecLin N) :=
LinearMap.ext fun _ ↦ (mulVec_mulVec _ _ _).symm
#align matrix.mul_vec_lin_mul Matrix.mulVecLin_mul
| Mathlib/LinearAlgebra/Matrix/ToLin.lean | 272 | 274 | theorem Matrix.ker_mulVecLin_eq_bot_iff {M : Matrix m n R} :
(LinearMap.ker M.mulVecLin) = ⊥ ↔ ∀ v, M *ᵥ v = 0 → v = 0 := by |
simp only [Submodule.eq_bot_iff, LinearMap.mem_ker, Matrix.mulVecLin_apply]
|
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad
-/
import Mathlib.Algebra.Ring.Int
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.Size
#align_import data.int.bitwise from "leanprover-community/mathlib"@"0743cc5d9d86bcd1bba10f480e948a257d65056f"
#align_import init.data.int.bitwise from "leanprover-community/lean"@"855e5b74e3a52a40552e8f067169d747d48743fd"
/-!
# Bitwise operations on integers
Possibly only of archaeological significance.
## Recursors
* `Int.bitCasesOn`: Parity disjunction. Something is true/defined on `ℤ` if it's true/defined for
even and for odd values.
-/
namespace Int
/-- `div2 n = n/2`-/
def div2 : ℤ → ℤ
| (n : ℕ) => n.div2
| -[n +1] => negSucc n.div2
#align int.div2 Int.div2
/-- `bodd n` returns `true` if `n` is odd-/
def bodd : ℤ → Bool
| (n : ℕ) => n.bodd
| -[n +1] => not (n.bodd)
#align int.bodd Int.bodd
-- Porting note: `bit0, bit1` deprecated, do we need to adapt `bit`?
set_option linter.deprecated false in
/-- `bit b` appends the digit `b` to the binary representation of
its integer input. -/
def bit (b : Bool) : ℤ → ℤ :=
cond b bit1 bit0
#align int.bit Int.bit
/-- `testBit m n` returns whether the `(n+1)ˢᵗ` least significant bit is `1` or `0`-/
def testBit : ℤ → ℕ → Bool
| (m : ℕ), n => Nat.testBit m n
| -[m +1], n => !(Nat.testBit m n)
#align int.test_bit Int.testBit
/-- `Int.natBitwise` is an auxiliary definition for `Int.bitwise`. -/
def natBitwise (f : Bool → Bool → Bool) (m n : ℕ) : ℤ :=
cond (f false false) -[ Nat.bitwise (fun x y => not (f x y)) m n +1] (Nat.bitwise f m n)
#align int.nat_bitwise Int.natBitwise
/-- `Int.bitwise` applies the function `f` to pairs of bits in the same position in
the binary representations of its inputs. -/
def bitwise (f : Bool → Bool → Bool) : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => natBitwise f m n
| (m : ℕ), -[n +1] => natBitwise (fun x y => f x (not y)) m n
| -[m +1], (n : ℕ) => natBitwise (fun x y => f (not x) y) m n
| -[m +1], -[n +1] => natBitwise (fun x y => f (not x) (not y)) m n
#align int.bitwise Int.bitwise
/-- `lnot` flips all the bits in the binary representation of its input -/
def lnot : ℤ → ℤ
| (m : ℕ) => -[m +1]
| -[m +1] => m
#align int.lnot Int.lnot
/-- `lor` takes two integers and returns their bitwise `or`-/
def lor : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => m ||| n
| (m : ℕ), -[n +1] => -[Nat.ldiff n m +1]
| -[m +1], (n : ℕ) => -[Nat.ldiff m n +1]
| -[m +1], -[n +1] => -[m &&& n +1]
#align int.lor Int.lor
/-- `land` takes two integers and returns their bitwise `and`-/
def land : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => m &&& n
| (m : ℕ), -[n +1] => Nat.ldiff m n
| -[m +1], (n : ℕ) => Nat.ldiff n m
| -[m +1], -[n +1] => -[m ||| n +1]
#align int.land Int.land
-- Porting note: I don't know why `Nat.ldiff` got the prime, but I'm matching this change here
/-- `ldiff a b` performs bitwise set difference. For each corresponding
pair of bits taken as booleans, say `aᵢ` and `bᵢ`, it applies the
boolean operation `aᵢ ∧ bᵢ` to obtain the `iᵗʰ` bit of the result. -/
def ldiff : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => Nat.ldiff m n
| (m : ℕ), -[n +1] => m &&& n
| -[m +1], (n : ℕ) => -[m ||| n +1]
| -[m +1], -[n +1] => Nat.ldiff n m
#align int.ldiff Int.ldiff
-- Porting note: I don't know why `Nat.xor'` got the prime, but I'm matching this change here
/-- `xor` computes the bitwise `xor` of two natural numbers-/
protected def xor : ℤ → ℤ → ℤ
| (m : ℕ), (n : ℕ) => (m ^^^ n)
| (m : ℕ), -[n +1] => -[(m ^^^ n) +1]
| -[m +1], (n : ℕ) => -[(m ^^^ n) +1]
| -[m +1], -[n +1] => (m ^^^ n)
#align int.lxor Int.xor
/-- `m <<< n` produces an integer whose binary representation
is obtained by left-shifting the binary representation of `m` by `n` places -/
instance : ShiftLeft ℤ where
shiftLeft
| (m : ℕ), (n : ℕ) => Nat.shiftLeft' false m n
| (m : ℕ), -[n +1] => m >>> (Nat.succ n)
| -[m +1], (n : ℕ) => -[Nat.shiftLeft' true m n +1]
| -[m +1], -[n +1] => -[m >>> (Nat.succ n) +1]
#align int.shiftl ShiftLeft.shiftLeft
/-- `m >>> n` produces an integer whose binary representation
is obtained by right-shifting the binary representation of `m` by `n` places -/
instance : ShiftRight ℤ where
shiftRight m n := m <<< (-n)
#align int.shiftr ShiftRight.shiftRight
/-! ### bitwise ops -/
@[simp]
theorem bodd_zero : bodd 0 = false :=
rfl
#align int.bodd_zero Int.bodd_zero
@[simp]
theorem bodd_one : bodd 1 = true :=
rfl
#align int.bodd_one Int.bodd_one
theorem bodd_two : bodd 2 = false :=
rfl
#align int.bodd_two Int.bodd_two
@[simp, norm_cast]
theorem bodd_coe (n : ℕ) : Int.bodd n = Nat.bodd n :=
rfl
#align int.bodd_coe Int.bodd_coe
@[simp]
theorem bodd_subNatNat (m n : ℕ) : bodd (subNatNat m n) = xor m.bodd n.bodd := by
apply subNatNat_elim m n fun m n i => bodd i = xor m.bodd n.bodd <;>
intros i j <;>
simp only [Int.bodd, Int.bodd_coe, Nat.bodd_add] <;>
cases Nat.bodd i <;> simp
#align int.bodd_sub_nat_nat Int.bodd_subNatNat
@[simp]
theorem bodd_negOfNat (n : ℕ) : bodd (negOfNat n) = n.bodd := by
cases n <;> simp (config := {decide := true})
rfl
#align int.bodd_neg_of_nat Int.bodd_negOfNat
@[simp]
| Mathlib/Data/Int/Bitwise.lean | 159 | 167 | theorem bodd_neg (n : ℤ) : bodd (-n) = bodd n := by |
cases n with
| ofNat =>
rw [← negOfNat_eq, bodd_negOfNat]
simp
| negSucc n =>
rw [neg_negSucc, bodd_coe, Nat.bodd_succ]
change (!Nat.bodd n) = !(bodd n)
rw [bodd_coe]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Kenny Lau
-/
import Mathlib.Data.Finsupp.ToDFinsupp
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.LinearIndependent
#align_import linear_algebra.dfinsupp from "leanprover-community/mathlib"@"a148d797a1094ab554ad4183a4ad6f130358ef64"
/-!
# Properties of the module `Π₀ i, M i`
Given an indexed collection of `R`-modules `M i`, the `R`-module structure on `Π₀ i, M i`
is defined in `Data.DFinsupp`.
In this file we define `LinearMap` versions of various maps:
* `DFinsupp.lsingle a : M →ₗ[R] Π₀ i, M i`: `DFinsupp.single a` as a linear map;
* `DFinsupp.lmk s : (Π i : (↑s : Set ι), M i) →ₗ[R] Π₀ i, M i`: `DFinsupp.single a` as a linear map;
* `DFinsupp.lapply i : (Π₀ i, M i) →ₗ[R] M`: the map `fun f ↦ f i` as a linear map;
* `DFinsupp.lsum`: `DFinsupp.sum` or `DFinsupp.liftAddHom` as a `LinearMap`;
## Implementation notes
This file should try to mirror `LinearAlgebra.Finsupp` where possible. The API of `Finsupp` is
much more developed, but many lemmas in that file should be eligible to copy over.
## Tags
function with finite support, module, linear algebra
-/
variable {ι : Type*} {R : Type*} {S : Type*} {M : ι → Type*} {N : Type*}
namespace DFinsupp
variable [Semiring R] [∀ i, AddCommMonoid (M i)] [∀ i, Module R (M i)]
variable [AddCommMonoid N] [Module R N]
section DecidableEq
variable [DecidableEq ι]
/-- `DFinsupp.mk` as a `LinearMap`. -/
def lmk (s : Finset ι) : (∀ i : (↑s : Set ι), M i) →ₗ[R] Π₀ i, M i where
toFun := mk s
map_add' _ _ := mk_add
map_smul' c x := mk_smul c x
#align dfinsupp.lmk DFinsupp.lmk
/-- `DFinsupp.single` as a `LinearMap` -/
def lsingle (i) : M i →ₗ[R] Π₀ i, M i :=
{ DFinsupp.singleAddHom _ _ with
toFun := single i
map_smul' := single_smul }
#align dfinsupp.lsingle DFinsupp.lsingle
/-- Two `R`-linear maps from `Π₀ i, M i` which agree on each `single i x` agree everywhere. -/
theorem lhom_ext ⦃φ ψ : (Π₀ i, M i) →ₗ[R] N⦄ (h : ∀ i x, φ (single i x) = ψ (single i x)) : φ = ψ :=
LinearMap.toAddMonoidHom_injective <| addHom_ext h
#align dfinsupp.lhom_ext DFinsupp.lhom_ext
/-- Two `R`-linear maps from `Π₀ i, M i` which agree on each `single i x` agree everywhere.
See note [partially-applied ext lemmas].
After apply this lemma, if `M = R` then it suffices to verify `φ (single a 1) = ψ (single a 1)`. -/
@[ext 1100]
theorem lhom_ext' ⦃φ ψ : (Π₀ i, M i) →ₗ[R] N⦄ (h : ∀ i, φ.comp (lsingle i) = ψ.comp (lsingle i)) :
φ = ψ :=
lhom_ext fun i => LinearMap.congr_fun (h i)
#align dfinsupp.lhom_ext' DFinsupp.lhom_ext'
/-- Interpret `fun (f : Π₀ i, M i) ↦ f i` as a linear map. -/
def lapply (i : ι) : (Π₀ i, M i) →ₗ[R] M i where
toFun f := f i
map_add' f g := add_apply f g i
map_smul' c f := smul_apply c f i
#align dfinsupp.lapply DFinsupp.lapply
-- This lemma has always been bad, but the linter only noticed after lean4#2644.
@[simp, nolint simpNF]
theorem lmk_apply (s : Finset ι) (x) : (lmk s : _ →ₗ[R] Π₀ i, M i) x = mk s x :=
rfl
#align dfinsupp.lmk_apply DFinsupp.lmk_apply
@[simp]
theorem lsingle_apply (i : ι) (x : M i) : (lsingle i : (M i) →ₗ[R] _) x = single i x :=
rfl
#align dfinsupp.lsingle_apply DFinsupp.lsingle_apply
@[simp]
theorem lapply_apply (i : ι) (f : Π₀ i, M i) : (lapply i : (Π₀ i, M i) →ₗ[R] _) f = f i :=
rfl
#align dfinsupp.lapply_apply DFinsupp.lapply_apply
section Lsum
-- Porting note: Unclear how true these docstrings are in lean 4
/-- Typeclass inference can't find `DFinsupp.addCommMonoid` without help for this case.
This instance allows it to be found where it is needed on the LHS of the colon in
`DFinsupp.moduleOfLinearMap`. -/
instance addCommMonoidOfLinearMap : AddCommMonoid (Π₀ i : ι, M i →ₗ[R] N) :=
inferInstance
#align dfinsupp.add_comm_monoid_of_linear_map DFinsupp.addCommMonoidOfLinearMap
/-- Typeclass inference can't find `DFinsupp.module` without help for this case.
This is needed to define `DFinsupp.lsum` below.
The cause seems to be an inability to unify the `∀ i, AddCommMonoid (M i →ₗ[R] N)` instance that
we have with the `∀ i, Zero (M i →ₗ[R] N)` instance which appears as a parameter to the
`DFinsupp` type. -/
instance moduleOfLinearMap [Semiring S] [Module S N] [SMulCommClass R S N] :
Module S (Π₀ i : ι, M i →ₗ[R] N) :=
DFinsupp.module
#align dfinsupp.module_of_linear_map DFinsupp.moduleOfLinearMap
variable (S)
instance {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : Type*) (M₂ : Type*)
[AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂] :
EquivLike (LinearEquiv σ M M₂) M M₂ :=
inferInstance
/- Porting note: In every application of lsum that follows, the argument M needs to be explicitly
supplied, lean does not manage to gather that information itself -/
/-- The `DFinsupp` version of `Finsupp.lsum`.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used. -/
@[simps]
def lsum [Semiring S] [Module S N] [SMulCommClass R S N] :
(∀ i, M i →ₗ[R] N) ≃ₗ[S] (Π₀ i, M i) →ₗ[R] N where
toFun F :=
{ toFun := sumAddHom fun i => (F i).toAddMonoidHom
map_add' := (DFinsupp.liftAddHom fun (i : ι) => (F i).toAddMonoidHom).map_add
map_smul' := fun c f => by
dsimp
apply DFinsupp.induction f
· rw [smul_zero, AddMonoidHom.map_zero, smul_zero]
· intro a b f _ _ hf
rw [smul_add, AddMonoidHom.map_add, AddMonoidHom.map_add, smul_add, hf, ← single_smul,
sumAddHom_single, sumAddHom_single, LinearMap.toAddMonoidHom_coe,
LinearMap.map_smul] }
invFun F i := F.comp (lsingle i)
left_inv F := by
ext
simp
right_inv F := by
refine DFinsupp.lhom_ext' (fun i ↦ ?_)
ext
simp
map_add' F G := by
refine DFinsupp.lhom_ext' (fun i ↦ ?_)
ext
simp
map_smul' c F := by
refine DFinsupp.lhom_ext' (fun i ↦ ?_)
ext
simp
#align dfinsupp.lsum DFinsupp.lsum
/-- While `simp` can prove this, it is often convenient to avoid unfolding `lsum` into `sumAddHom`
with `DFinsupp.lsum_apply_apply`. -/
theorem lsum_single [Semiring S] [Module S N] [SMulCommClass R S N] (F : ∀ i, M i →ₗ[R] N) (i)
(x : M i) : lsum S (M := M) F (single i x) = F i x := by
simp
#align dfinsupp.lsum_single DFinsupp.lsum_single
end Lsum
end DecidableEq
/-! ### Bundled versions of `DFinsupp.mapRange`
The names should match the equivalent bundled `Finsupp.mapRange` definitions.
-/
section mapRange
variable {β β₁ β₂ : ι → Type*}
variable [∀ i, AddCommMonoid (β i)] [∀ i, AddCommMonoid (β₁ i)] [∀ i, AddCommMonoid (β₂ i)]
variable [∀ i, Module R (β i)] [∀ i, Module R (β₁ i)] [∀ i, Module R (β₂ i)]
theorem mapRange_smul (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) (r : R)
(hf' : ∀ i x, f i (r • x) = r • f i x) (g : Π₀ i, β₁ i) :
mapRange f hf (r • g) = r • mapRange f hf g := by
ext
simp only [mapRange_apply f, coe_smul, Pi.smul_apply, hf']
#align dfinsupp.map_range_smul DFinsupp.mapRange_smul
/-- `DFinsupp.mapRange` as a `LinearMap`. -/
@[simps! apply]
def mapRange.linearMap (f : ∀ i, β₁ i →ₗ[R] β₂ i) : (Π₀ i, β₁ i) →ₗ[R] Π₀ i, β₂ i :=
{ mapRange.addMonoidHom fun i => (f i).toAddMonoidHom with
toFun := mapRange (fun i x => f i x) fun i => (f i).map_zero
map_smul' := fun r => mapRange_smul _ (fun i => (f i).map_zero) _ fun i => (f i).map_smul r }
#align dfinsupp.map_range.linear_map DFinsupp.mapRange.linearMap
@[simp]
theorem mapRange.linearMap_id :
(mapRange.linearMap fun i => (LinearMap.id : β₂ i →ₗ[R] _)) = LinearMap.id := by
ext
simp [linearMap]
#align dfinsupp.map_range.linear_map_id DFinsupp.mapRange.linearMap_id
theorem mapRange.linearMap_comp (f : ∀ i, β₁ i →ₗ[R] β₂ i) (f₂ : ∀ i, β i →ₗ[R] β₁ i) :
(mapRange.linearMap fun i => (f i).comp (f₂ i)) =
(mapRange.linearMap f).comp (mapRange.linearMap f₂) :=
LinearMap.ext <| mapRange_comp (fun i x => f i x) (fun i x => f₂ i x)
(fun i => (f i).map_zero) (fun i => (f₂ i).map_zero) (by simp)
#align dfinsupp.map_range.linear_map_comp DFinsupp.mapRange.linearMap_comp
theorem sum_mapRange_index.linearMap [DecidableEq ι] {f : ∀ i, β₁ i →ₗ[R] β₂ i}
{h : ∀ i, β₂ i →ₗ[R] N} {l : Π₀ i, β₁ i} :
DFinsupp.lsum ℕ h (mapRange.linearMap f l) = DFinsupp.lsum ℕ (fun i => (h i).comp (f i)) l := by
classical simpa [DFinsupp.sumAddHom_apply] using sum_mapRange_index fun i => by simp
#align dfinsupp.sum_map_range_index.linear_map DFinsupp.sum_mapRange_index.linearMap
/-- `DFinsupp.mapRange.linearMap` as a `LinearEquiv`. -/
@[simps apply]
def mapRange.linearEquiv (e : ∀ i, β₁ i ≃ₗ[R] β₂ i) : (Π₀ i, β₁ i) ≃ₗ[R] Π₀ i, β₂ i :=
{ mapRange.addEquiv fun i => (e i).toAddEquiv,
mapRange.linearMap fun i => (e i).toLinearMap with
toFun := mapRange (fun i x => e i x) fun i => (e i).map_zero
invFun := mapRange (fun i x => (e i).symm x) fun i => (e i).symm.map_zero }
#align dfinsupp.map_range.linear_equiv DFinsupp.mapRange.linearEquiv
@[simp]
theorem mapRange.linearEquiv_refl :
(mapRange.linearEquiv fun i => LinearEquiv.refl R (β₁ i)) = LinearEquiv.refl _ _ :=
LinearEquiv.ext mapRange_id
#align dfinsupp.map_range.linear_equiv_refl DFinsupp.mapRange.linearEquiv_refl
theorem mapRange.linearEquiv_trans (f : ∀ i, β i ≃ₗ[R] β₁ i) (f₂ : ∀ i, β₁ i ≃ₗ[R] β₂ i) :
(mapRange.linearEquiv fun i => (f i).trans (f₂ i)) =
(mapRange.linearEquiv f).trans (mapRange.linearEquiv f₂) :=
LinearEquiv.ext <| mapRange_comp (fun i x => f₂ i x) (fun i x => f i x)
(fun i => (f₂ i).map_zero) (fun i => (f i).map_zero) (by simp)
#align dfinsupp.map_range.linear_equiv_trans DFinsupp.mapRange.linearEquiv_trans
@[simp]
theorem mapRange.linearEquiv_symm (e : ∀ i, β₁ i ≃ₗ[R] β₂ i) :
(mapRange.linearEquiv e).symm = mapRange.linearEquiv fun i => (e i).symm :=
rfl
#align dfinsupp.map_range.linear_equiv_symm DFinsupp.mapRange.linearEquiv_symm
end mapRange
section CoprodMap
variable [DecidableEq ι] [∀ x : N, Decidable (x ≠ 0)]
/-- Given a family of linear maps `f i : M i →ₗ[R] N`, we can form a linear map
`(Π₀ i, M i) →ₗ[R] N` which sends `x : Π₀ i, M i` to the sum over `i` of `f i` applied to `x i`.
This is the map coming from the universal property of `Π₀ i, M i` as the coproduct of the `M i`.
See also `LinearMap.coprod` for the binary product version. -/
def coprodMap (f : ∀ i : ι, M i →ₗ[R] N) : (Π₀ i, M i) →ₗ[R] N :=
(DFinsupp.lsum ℕ fun _ : ι => LinearMap.id) ∘ₗ DFinsupp.mapRange.linearMap f
#align dfinsupp.coprod_map DFinsupp.coprodMap
theorem coprodMap_apply (f : ∀ i : ι, M i →ₗ[R] N) (x : Π₀ i, M i) :
coprodMap f x =
DFinsupp.sum (mapRange (fun i => f i) (fun _ => LinearMap.map_zero _) x) fun _ =>
id :=
DFinsupp.sumAddHom_apply _ _
#align dfinsupp.coprod_map_apply DFinsupp.coprodMap_apply
theorem coprodMap_apply_single (f : ∀ i : ι, M i →ₗ[R] N) (i : ι) (x : M i) :
coprodMap f (single i x) = f i x := by
simp [coprodMap]
end CoprodMap
end DFinsupp
namespace Submodule
variable [Semiring R] [AddCommMonoid N] [Module R N]
open DFinsupp
section DecidableEq
variable [DecidableEq ι]
theorem dfinsupp_sum_mem {β : ι → Type*} [∀ i, Zero (β i)] [∀ (i) (x : β i), Decidable (x ≠ 0)]
(S : Submodule R N) (f : Π₀ i, β i) (g : ∀ i, β i → N) (h : ∀ c, f c ≠ 0 → g c (f c) ∈ S) :
f.sum g ∈ S :=
_root_.dfinsupp_sum_mem S f g h
#align submodule.dfinsupp_sum_mem Submodule.dfinsupp_sum_mem
theorem dfinsupp_sumAddHom_mem {β : ι → Type*} [∀ i, AddZeroClass (β i)] (S : Submodule R N)
(f : Π₀ i, β i) (g : ∀ i, β i →+ N) (h : ∀ c, f c ≠ 0 → g c (f c) ∈ S) :
DFinsupp.sumAddHom g f ∈ S :=
_root_.dfinsupp_sumAddHom_mem S f g h
#align submodule.dfinsupp_sum_add_hom_mem Submodule.dfinsupp_sumAddHom_mem
/-- The supremum of a family of submodules is equal to the range of `DFinsupp.lsum`; that is
every element in the `iSup` can be produced from taking a finite number of non-zero elements
of `p i`, coercing them to `N`, and summing them. -/
theorem iSup_eq_range_dfinsupp_lsum (p : ι → Submodule R N) :
iSup p = LinearMap.range (DFinsupp.lsum ℕ (M := fun i ↦ ↥(p i)) fun i => (p i).subtype) := by
apply le_antisymm
· apply iSup_le _
intro i y hy
simp only [LinearMap.mem_range, lsum_apply_apply]
exact ⟨DFinsupp.single i ⟨y, hy⟩, DFinsupp.sumAddHom_single _ _ _⟩
· rintro x ⟨v, rfl⟩
exact dfinsupp_sumAddHom_mem _ v _ fun i _ => (le_iSup p i : p i ≤ _) (v i).2
#align submodule.supr_eq_range_dfinsupp_lsum Submodule.iSup_eq_range_dfinsupp_lsum
/-- The bounded supremum of a family of commutative additive submonoids is equal to the range of
`DFinsupp.sumAddHom` composed with `DFinsupp.filter_add_monoid_hom`; that is, every element in the
bounded `iSup` can be produced from taking a finite number of non-zero elements from the `S i` that
satisfy `p i`, coercing them to `γ`, and summing them. -/
theorem biSup_eq_range_dfinsupp_lsum (p : ι → Prop) [DecidablePred p] (S : ι → Submodule R N) :
⨆ (i) (_ : p i), S i =
LinearMap.range
(LinearMap.comp
(DFinsupp.lsum ℕ (M := fun i ↦ ↥(S i)) (fun i => (S i).subtype))
(DFinsupp.filterLinearMap R _ p)) := by
apply le_antisymm
· refine iSup₂_le fun i hi y hy => ⟨DFinsupp.single i ⟨y, hy⟩, ?_⟩
rw [LinearMap.comp_apply, filterLinearMap_apply, filter_single_pos _ _ hi]
simp only [lsum_apply_apply, sumAddHom_single, LinearMap.toAddMonoidHom_coe, coeSubtype]
· rintro x ⟨v, rfl⟩
refine dfinsupp_sumAddHom_mem _ _ _ fun i _ => ?_
refine mem_iSup_of_mem i ?_
by_cases hp : p i
· simp [hp]
· simp [hp]
#align submodule.bsupr_eq_range_dfinsupp_lsum Submodule.biSup_eq_range_dfinsupp_lsum
/-- A characterisation of the span of a family of submodules.
See also `Submodule.mem_iSup_iff_exists_finsupp`. -/
theorem mem_iSup_iff_exists_dfinsupp (p : ι → Submodule R N) (x : N) :
x ∈ iSup p ↔
∃ f : Π₀ i, p i, DFinsupp.lsum ℕ (M := fun i ↦ ↥(p i)) (fun i => (p i).subtype) f = x :=
SetLike.ext_iff.mp (iSup_eq_range_dfinsupp_lsum p) x
#align submodule.mem_supr_iff_exists_dfinsupp Submodule.mem_iSup_iff_exists_dfinsupp
/-- A variant of `Submodule.mem_iSup_iff_exists_dfinsupp` with the RHS fully unfolded.
See also `Submodule.mem_iSup_iff_exists_finsupp`. -/
theorem mem_iSup_iff_exists_dfinsupp' (p : ι → Submodule R N) [∀ (i) (x : p i), Decidable (x ≠ 0)]
(x : N) : x ∈ iSup p ↔ ∃ f : Π₀ i, p i, (f.sum fun i xi => ↑xi) = x := by
rw [mem_iSup_iff_exists_dfinsupp]
simp_rw [DFinsupp.lsum_apply_apply, DFinsupp.sumAddHom_apply,
LinearMap.toAddMonoidHom_coe, coeSubtype]
#align submodule.mem_supr_iff_exists_dfinsupp' Submodule.mem_iSup_iff_exists_dfinsupp'
theorem mem_biSup_iff_exists_dfinsupp (p : ι → Prop) [DecidablePred p] (S : ι → Submodule R N)
(x : N) :
(x ∈ ⨆ (i) (_ : p i), S i) ↔
∃ f : Π₀ i, S i,
DFinsupp.lsum ℕ (M := fun i ↦ ↥(S i)) (fun i => (S i).subtype) (f.filter p) = x :=
SetLike.ext_iff.mp (biSup_eq_range_dfinsupp_lsum p S) x
#align submodule.mem_bsupr_iff_exists_dfinsupp Submodule.mem_biSup_iff_exists_dfinsupp
end DecidableEq
lemma mem_iSup_iff_exists_finsupp (p : ι → Submodule R N) (x : N) :
x ∈ iSup p ↔ ∃ (f : ι →₀ N), (∀ i, f i ∈ p i) ∧ (f.sum fun _i xi ↦ xi) = x := by
classical
rw [mem_iSup_iff_exists_dfinsupp']
refine ⟨fun ⟨f, hf⟩ ↦ ⟨⟨f.support, fun i ↦ (f i : N), by simp⟩, by simp, hf⟩, ?_⟩
rintro ⟨f, hf, rfl⟩
refine ⟨DFinsupp.mk f.support fun i ↦ ⟨f i, hf i⟩, Finset.sum_congr ?_ fun i hi ↦ ?_⟩
· ext; simp
· simp [Finsupp.mem_support_iff.mp hi]
theorem mem_iSup_finset_iff_exists_sum {s : Finset ι} (p : ι → Submodule R N) (a : N) :
(a ∈ ⨆ i ∈ s, p i) ↔ ∃ μ : ∀ i, p i, (∑ i ∈ s, (μ i : N)) = a := by
classical
rw [Submodule.mem_iSup_iff_exists_dfinsupp']
constructor <;> rintro ⟨μ, hμ⟩
· use fun i => ⟨μ i, (iSup_const_le : _ ≤ p i) (coe_mem <| μ i)⟩
rw [← hμ]
symm
apply Finset.sum_subset
· intro x
contrapose
intro hx
rw [mem_support_iff, not_ne_iff]
ext
rw [coe_zero, ← mem_bot R]
suffices ⊥ = ⨆ (_ : x ∈ s), p x from this.symm ▸ coe_mem (μ x)
exact (iSup_neg hx).symm
· intro x _ hx
rw [mem_support_iff, not_ne_iff] at hx
rw [hx]
rfl
· refine ⟨DFinsupp.mk s ?_, ?_⟩
· rintro ⟨i, hi⟩
refine ⟨μ i, ?_⟩
rw [iSup_pos]
· exact coe_mem _
· exact hi
simp only [DFinsupp.sum]
rw [Finset.sum_subset support_mk_subset, ← hμ]
· exact Finset.sum_congr rfl fun x hx => congr_arg Subtype.val <| mk_of_mem hx
· intro x _ hx
rw [mem_support_iff, not_ne_iff] at hx
rw [hx]
rfl
#align submodule.mem_supr_finset_iff_exists_sum Submodule.mem_iSup_finset_iff_exists_sum
end Submodule
namespace CompleteLattice
open DFinsupp
section Semiring
variable [DecidableEq ι] [Semiring R] [AddCommMonoid N] [Module R N]
/-- Independence of a family of submodules can be expressed as a quantifier over `DFinsupp`s.
This is an intermediate result used to prove
`CompleteLattice.independent_of_dfinsupp_lsum_injective` and
`CompleteLattice.Independent.dfinsupp_lsum_injective`. -/
theorem independent_iff_forall_dfinsupp (p : ι → Submodule R N) :
Independent p ↔
∀ (i) (x : p i) (v : Π₀ i : ι, ↥(p i)),
lsum ℕ (M := fun i ↦ ↥(p i)) (fun i => (p i).subtype) (erase i v) = x → x = 0 := by
simp_rw [CompleteLattice.independent_def, Submodule.disjoint_def,
Submodule.mem_biSup_iff_exists_dfinsupp, exists_imp, filter_ne_eq_erase]
refine forall_congr' fun i => Subtype.forall'.trans ?_
simp_rw [Submodule.coe_eq_zero]
#align complete_lattice.independent_iff_forall_dfinsupp CompleteLattice.independent_iff_forall_dfinsupp
/- If `DFinsupp.lsum` applied with `Submodule.subtype` is injective then the submodules are
independent. -/
theorem independent_of_dfinsupp_lsum_injective (p : ι → Submodule R N)
(h : Function.Injective (lsum ℕ (M := fun i ↦ ↥(p i)) fun i => (p i).subtype)) :
Independent p := by
rw [independent_iff_forall_dfinsupp]
intro i x v hv
replace hv : lsum ℕ (M := fun i ↦ ↥(p i)) (fun i => (p i).subtype) (erase i v) =
lsum ℕ (M := fun i ↦ ↥(p i)) (fun i => (p i).subtype) (single i x) := by
simpa only [lsum_single] using hv
have := DFunLike.ext_iff.mp (h hv) i
simpa [eq_comm] using this
#align complete_lattice.independent_of_dfinsupp_lsum_injective CompleteLattice.independent_of_dfinsupp_lsum_injective
/- If `DFinsupp.sumAddHom` applied with `AddSubmonoid.subtype` is injective then the additive
submonoids are independent. -/
theorem independent_of_dfinsupp_sumAddHom_injective (p : ι → AddSubmonoid N)
(h : Function.Injective (sumAddHom fun i => (p i).subtype)) : Independent p := by
rw [← independent_map_orderIso_iff (AddSubmonoid.toNatSubmodule : AddSubmonoid N ≃o _)]
exact independent_of_dfinsupp_lsum_injective _ h
#align complete_lattice.independent_of_dfinsupp_sum_add_hom_injective CompleteLattice.independent_of_dfinsupp_sumAddHom_injective
/-- Combining `DFinsupp.lsum` with `LinearMap.toSpanSingleton` is the same as `Finsupp.total` -/
theorem lsum_comp_mapRange_toSpanSingleton [∀ m : R, Decidable (m ≠ 0)] (p : ι → Submodule R N)
{v : ι → N} (hv : ∀ i : ι, v i ∈ p i) :
(lsum ℕ (M := fun i ↦ ↥(p i)) fun i => (p i).subtype : _ →ₗ[R] _).comp
((mapRange.linearMap fun i => LinearMap.toSpanSingleton R (↥(p i)) ⟨v i, hv i⟩ :
_ →ₗ[R] _).comp
(finsuppLequivDFinsupp R : (ι →₀ R) ≃ₗ[R] _).toLinearMap) =
Finsupp.total ι N R v := by
ext
simp
#align complete_lattice.lsum_comp_map_range_to_span_singleton CompleteLattice.lsum_comp_mapRange_toSpanSingleton
end Semiring
section Ring
variable [DecidableEq ι] [Ring R] [AddCommGroup N] [Module R N]
/- If `DFinsupp.sumAddHom` applied with `AddSubmonoid.subtype` is injective then the additive
subgroups are independent. -/
theorem independent_of_dfinsupp_sumAddHom_injective' (p : ι → AddSubgroup N)
(h : Function.Injective (sumAddHom fun i => (p i).subtype)) : Independent p := by
rw [← independent_map_orderIso_iff (AddSubgroup.toIntSubmodule : AddSubgroup N ≃o _)]
exact independent_of_dfinsupp_lsum_injective _ h
#align complete_lattice.independent_of_dfinsupp_sum_add_hom_injective' CompleteLattice.independent_of_dfinsupp_sumAddHom_injective'
/-- The canonical map out of a direct sum of a family of submodules is injective when the submodules
are `CompleteLattice.Independent`.
Note that this is not generally true for `[Semiring R]`, for instance when `A` is the
`ℕ`-submodules of the positive and negative integers.
See `Counterexamples/DirectSumIsInternal.lean` for a proof of this fact. -/
| Mathlib/LinearAlgebra/DFinsupp.lean | 495 | 511 | theorem Independent.dfinsupp_lsum_injective {p : ι → Submodule R N} (h : Independent p) :
Function.Injective (lsum ℕ (M := fun i ↦ ↥(p i)) fun i => (p i).subtype) := by |
-- simplify everything down to binders over equalities in `N`
rw [independent_iff_forall_dfinsupp] at h
suffices LinearMap.ker (lsum ℕ (M := fun i ↦ ↥(p i)) fun i => (p i).subtype) = ⊥ by
-- Lean can't find this without our help
letI thisI : AddCommGroup (Π₀ i, p i) := inferInstance
rw [LinearMap.ker_eq_bot] at this
exact this
rw [LinearMap.ker_eq_bot']
intro m hm
ext i : 1
-- split `m` into the piece at `i` and the pieces elsewhere, to match `h`
rw [DFinsupp.zero_apply, ← neg_eq_zero]
refine h i (-m i) m ?_
rwa [← erase_add_single i m, LinearMap.map_add, lsum_single, Submodule.subtype_apply,
add_eq_zero_iff_eq_neg, ← Submodule.coe_neg] at hm
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Scott Morrison
-/
import Mathlib.CategoryTheory.FinCategory.Basic
import Mathlib.CategoryTheory.Limits.Cones
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Adjunction.Basic
import Mathlib.CategoryTheory.Category.Preorder
import Mathlib.CategoryTheory.Category.ULift
import Mathlib.CategoryTheory.PEmpty
#align_import category_theory.filtered from "leanprover-community/mathlib"@"14e80e85cbca5872a329fbfd3d1f3fd64e306934"
/-!
# Filtered categories
A category is filtered if every finite diagram admits a cocone.
We give a simple characterisation of this condition as
1. for every pair of objects there exists another object "to the right",
2. for every pair of parallel morphisms there exists a morphism to the right so the compositions
are equal, and
3. there exists some object.
Filtered colimits are often better behaved than arbitrary colimits.
See `CategoryTheory/Limits/Types` for some details.
Filtered categories are nice because colimits indexed by filtered categories tend to be
easier to describe than general colimits (and more often preserved by functors).
In this file we show that any functor from a finite category to a filtered category admits a cocone:
* `cocone_nonempty [FinCategory J] [IsFiltered C] (F : J ⥤ C) : Nonempty (Cocone F)`
More generally,
for any finite collection of objects and morphisms between them in a filtered category
(even if not closed under composition) there exists some object `Z` receiving maps from all of them,
so that all the triangles (one edge from the finite set, two from morphisms to `Z`) commute.
This formulation is often more useful in practice and is available via `sup_exists`,
which takes a finset of objects, and an indexed family (indexed by source and target)
of finsets of morphisms.
We also prove the converse of `cocone_nonempty` as `of_cocone_nonempty`.
Furthermore, we give special support for two diagram categories: The `bowtie` and the `tulip`.
This is because these shapes show up in the proofs that forgetful functors of algebraic categories
(e.g. `MonCat`, `CommRingCat`, ...) preserve filtered colimits.
All of the above API, except for the `bowtie` and the `tulip`, is also provided for cofiltered
categories.
## See also
In `CategoryTheory.Limits.FilteredColimitCommutesFiniteLimit` we show that filtered colimits
commute with finite limits.
There is another characterization of filtered categories, namely that whenever `F : J ⥤ C` is a
functor from a finite category, there is `X : C` such that `Nonempty (limit (F.op ⋙ yoneda.obj X))`.
This is shown in `CategoryTheory.Limits.Filtered`.
-/
open Function
-- declare the `v`'s first; see `CategoryTheory.Category` for an explanation
universe w v v₁ u u₁ u₂
namespace CategoryTheory
variable (C : Type u) [Category.{v} C]
/-- A category `IsFilteredOrEmpty` if
1. for every pair of objects there exists another object "to the right", and
2. for every pair of parallel morphisms there exists a morphism to the right so the compositions
are equal.
-/
class IsFilteredOrEmpty : Prop where
/-- for every pair of objects there exists another object "to the right" -/
cocone_objs : ∀ X Y : C, ∃ (Z : _) (_ : X ⟶ Z) (_ : Y ⟶ Z), True
/-- for every pair of parallel morphisms there exists a morphism to the right
so the compositions are equal -/
cocone_maps : ∀ ⦃X Y : C⦄ (f g : X ⟶ Y), ∃ (Z : _) (h : Y ⟶ Z), f ≫ h = g ≫ h
#align category_theory.is_filtered_or_empty CategoryTheory.IsFilteredOrEmpty
/-- A category `IsFiltered` if
1. for every pair of objects there exists another object "to the right",
2. for every pair of parallel morphisms there exists a morphism to the right so the compositions
are equal, and
3. there exists some object.
See <https://stacks.math.columbia.edu/tag/002V>. (They also define a diagram being filtered.)
-/
class IsFiltered extends IsFilteredOrEmpty C : Prop where
/-- a filtered category must be non empty -/
[nonempty : Nonempty C]
#align category_theory.is_filtered CategoryTheory.IsFiltered
instance (priority := 100) isFilteredOrEmpty_of_semilatticeSup (α : Type u) [SemilatticeSup α] :
IsFilteredOrEmpty α where
cocone_objs X Y := ⟨X ⊔ Y, homOfLE le_sup_left, homOfLE le_sup_right, trivial⟩
cocone_maps X Y f g := ⟨Y, 𝟙 _, by
apply ULift.ext
apply Subsingleton.elim⟩
#align category_theory.is_filtered_or_empty_of_semilattice_sup CategoryTheory.isFilteredOrEmpty_of_semilatticeSup
instance (priority := 100) isFiltered_of_semilatticeSup_nonempty (α : Type u) [SemilatticeSup α]
[Nonempty α] : IsFiltered α where
#align category_theory.is_filtered_of_semilattice_sup_nonempty CategoryTheory.isFiltered_of_semilatticeSup_nonempty
instance (priority := 100) isFilteredOrEmpty_of_directed_le (α : Type u) [Preorder α]
[IsDirected α (· ≤ ·)] : IsFilteredOrEmpty α where
cocone_objs X Y :=
let ⟨Z, h1, h2⟩ := exists_ge_ge X Y
⟨Z, homOfLE h1, homOfLE h2, trivial⟩
cocone_maps X Y f g := ⟨Y, 𝟙 _, by
apply ULift.ext
apply Subsingleton.elim⟩
#align category_theory.is_filtered_or_empty_of_directed_le CategoryTheory.isFilteredOrEmpty_of_directed_le
instance (priority := 100) isFiltered_of_directed_le_nonempty (α : Type u) [Preorder α]
[IsDirected α (· ≤ ·)] [Nonempty α] : IsFiltered α where
#align category_theory.is_filtered_of_directed_le_nonempty CategoryTheory.isFiltered_of_directed_le_nonempty
-- Sanity checks
example (α : Type u) [SemilatticeSup α] [OrderBot α] : IsFiltered α := by infer_instance
example (α : Type u) [SemilatticeSup α] [OrderTop α] : IsFiltered α := by infer_instance
instance : IsFiltered (Discrete PUnit) where
cocone_objs X Y := ⟨⟨PUnit.unit⟩, ⟨⟨by trivial⟩⟩, ⟨⟨Subsingleton.elim _ _⟩⟩, trivial⟩
cocone_maps X Y f g := ⟨⟨PUnit.unit⟩, ⟨⟨by trivial⟩⟩, by
apply ULift.ext
apply Subsingleton.elim⟩
namespace IsFiltered
section AllowEmpty
variable {C}
variable [IsFilteredOrEmpty C]
-- Porting note: the following definitions were removed because the names are invalid,
-- direct references to `IsFilteredOrEmpty` have been added instead
--
-- theorem cocone_objs : ∀ X Y : C, ∃ (Z : _) (f : X ⟶ Z) (g : Y ⟶ Z), True :=
-- IsFilteredOrEmpty.cocone_objs
-- #align category_theory.is_filtered.cocone_objs CategoryTheory.IsFiltered.cocone_objs
--
--theorem cocone_maps : ∀ ⦃X Y : C⦄ (f g : X ⟶ Y), ∃ (Z : _) (h : Y ⟶ Z), f ≫ h = g ≫ h :=
-- IsFilteredOrEmpty.cocone_maps
--#align category_theory.is_filtered.cocone_maps CategoryTheory.IsFiltered.cocone_maps
/-- `max j j'` is an arbitrary choice of object to the right of both `j` and `j'`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def max (j j' : C) : C :=
(IsFilteredOrEmpty.cocone_objs j j').choose
#align category_theory.is_filtered.max CategoryTheory.IsFiltered.max
/-- `leftToMax j j'` is an arbitrary choice of morphism from `j` to `max j j'`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def leftToMax (j j' : C) : j ⟶ max j j' :=
(IsFilteredOrEmpty.cocone_objs j j').choose_spec.choose
#align category_theory.is_filtered.left_to_max CategoryTheory.IsFiltered.leftToMax
/-- `rightToMax j j'` is an arbitrary choice of morphism from `j'` to `max j j'`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def rightToMax (j j' : C) : j' ⟶ max j j' :=
(IsFilteredOrEmpty.cocone_objs j j').choose_spec.choose_spec.choose
#align category_theory.is_filtered.right_to_max CategoryTheory.IsFiltered.rightToMax
/-- `coeq f f'`, for morphisms `f f' : j ⟶ j'`, is an arbitrary choice of object
which admits a morphism `coeqHom f f' : j' ⟶ coeq f f'` such that
`coeq_condition : f ≫ coeqHom f f' = f' ≫ coeqHom f f'`.
Its existence is ensured by `IsFiltered`.
-/
noncomputable def coeq {j j' : C} (f f' : j ⟶ j') : C :=
(IsFilteredOrEmpty.cocone_maps f f').choose
#align category_theory.is_filtered.coeq CategoryTheory.IsFiltered.coeq
/-- `coeqHom f f'`, for morphisms `f f' : j ⟶ j'`, is an arbitrary choice of morphism
`coeqHom f f' : j' ⟶ coeq f f'` such that
`coeq_condition : f ≫ coeqHom f f' = f' ≫ coeqHom f f'`.
Its existence is ensured by `IsFiltered`.
-/
noncomputable def coeqHom {j j' : C} (f f' : j ⟶ j') : j' ⟶ coeq f f' :=
(IsFilteredOrEmpty.cocone_maps f f').choose_spec.choose
#align category_theory.is_filtered.coeq_hom CategoryTheory.IsFiltered.coeqHom
-- Porting note: the simp tag has been removed as the linter complained
/-- `coeq_condition f f'`, for morphisms `f f' : j ⟶ j'`, is the proof that
`f ≫ coeqHom f f' = f' ≫ coeqHom f f'`.
-/
@[reassoc]
theorem coeq_condition {j j' : C} (f f' : j ⟶ j') : f ≫ coeqHom f f' = f' ≫ coeqHom f f' :=
(IsFilteredOrEmpty.cocone_maps f f').choose_spec.choose_spec
#align category_theory.is_filtered.coeq_condition CategoryTheory.IsFiltered.coeq_condition
end AllowEmpty
end IsFiltered
namespace IsFilteredOrEmpty
open IsFiltered
variable {C}
variable [IsFilteredOrEmpty C]
variable {D : Type u₁} [Category.{v₁} D]
/-- If `C` is filtered or emtpy, and we have a functor `R : C ⥤ D` with a left adjoint, then `D` is
filtered or empty.
-/
theorem of_right_adjoint {L : D ⥤ C} {R : C ⥤ D} (h : L ⊣ R) : IsFilteredOrEmpty D :=
{ cocone_objs := fun X Y =>
⟨_, h.homEquiv _ _ (leftToMax _ _), h.homEquiv _ _ (rightToMax _ _), ⟨⟩⟩
cocone_maps := fun X Y f g =>
⟨_, h.homEquiv _ _ (coeqHom _ _), by
rw [← h.homEquiv_naturality_left, ← h.homEquiv_naturality_left, coeq_condition]⟩ }
/-- If `C` is filtered or empty, and we have a right adjoint functor `R : C ⥤ D`, then `D` is
filtered or empty. -/
theorem of_isRightAdjoint (R : C ⥤ D) [R.IsRightAdjoint] : IsFilteredOrEmpty D :=
of_right_adjoint (Adjunction.ofIsRightAdjoint R)
/-- Being filtered or empty is preserved by equivalence of categories. -/
theorem of_equivalence (h : C ≌ D) : IsFilteredOrEmpty D :=
of_right_adjoint h.symm.toAdjunction
end IsFilteredOrEmpty
namespace IsFiltered
section Nonempty
open CategoryTheory.Limits
variable {C}
variable [IsFiltered C]
/-- Any finite collection of objects in a filtered category has an object "to the right".
-/
theorem sup_objs_exists (O : Finset C) : ∃ S : C, ∀ {X}, X ∈ O → Nonempty (X ⟶ S) := by
classical
induction' O using Finset.induction with X O' nm h
· exact ⟨Classical.choice IsFiltered.nonempty, by intro; simp⟩
· obtain ⟨S', w'⟩ := h
use max X S'
rintro Y mY
obtain rfl | h := eq_or_ne Y X
· exact ⟨leftToMax _ _⟩
· exact ⟨(w' (Finset.mem_of_mem_insert_of_ne mY h)).some ≫ rightToMax _ _⟩
#align category_theory.is_filtered.sup_objs_exists CategoryTheory.IsFiltered.sup_objs_exists
variable (O : Finset C) (H : Finset (Σ' (X Y : C) (_ : X ∈ O) (_ : Y ∈ O), X ⟶ Y))
/-- Given any `Finset` of objects `{X, ...}` and
indexed collection of `Finset`s of morphisms `{f, ...}` in `C`,
there exists an object `S`, with a morphism `T X : X ⟶ S` from each `X`,
such that the triangles commute: `f ≫ T Y = T X`, for `f : X ⟶ Y` in the `Finset`.
-/
theorem sup_exists :
∃ (S : C) (T : ∀ {X : C}, X ∈ O → (X ⟶ S)),
∀ {X Y : C} (mX : X ∈ O) (mY : Y ∈ O) {f : X ⟶ Y},
(⟨X, Y, mX, mY, f⟩ : Σ' (X Y : C) (_ : X ∈ O) (_ : Y ∈ O), X ⟶ Y) ∈ H →
f ≫ T mY = T mX := by
classical
induction' H using Finset.induction with h' H' nmf h''
· obtain ⟨S, f⟩ := sup_objs_exists O
exact ⟨S, fun mX => (f mX).some, by rintro - - - - - ⟨⟩⟩
· obtain ⟨X, Y, mX, mY, f⟩ := h'
obtain ⟨S', T', w'⟩ := h''
refine ⟨coeq (f ≫ T' mY) (T' mX), fun mZ => T' mZ ≫ coeqHom (f ≫ T' mY) (T' mX), ?_⟩
intro X' Y' mX' mY' f' mf'
rw [← Category.assoc]
by_cases h : X = X' ∧ Y = Y'
· rcases h with ⟨rfl, rfl⟩
by_cases hf : f = f'
· subst hf
apply coeq_condition
· rw [@w' _ _ mX mY f']
simp only [Finset.mem_insert, PSigma.mk.injEq, heq_eq_eq, true_and] at mf'
rcases mf' with mf' | mf'
· exfalso
exact hf mf'.symm
· exact mf'
· rw [@w' _ _ mX' mY' f' _]
apply Finset.mem_of_mem_insert_of_ne mf'
contrapose! h
obtain ⟨rfl, h⟩ := h
trivial
#align category_theory.is_filtered.sup_exists CategoryTheory.IsFiltered.sup_exists
/-- An arbitrary choice of object "to the right"
of a finite collection of objects `O` and morphisms `H`,
making all the triangles commute.
-/
noncomputable def sup : C :=
(sup_exists O H).choose
#align category_theory.is_filtered.sup CategoryTheory.IsFiltered.sup
/-- The morphisms to `sup O H`.
-/
noncomputable def toSup {X : C} (m : X ∈ O) : X ⟶ sup O H :=
(sup_exists O H).choose_spec.choose m
#align category_theory.is_filtered.to_sup CategoryTheory.IsFiltered.toSup
/-- The triangles of consisting of a morphism in `H` and the maps to `sup O H` commute.
-/
theorem toSup_commutes {X Y : C} (mX : X ∈ O) (mY : Y ∈ O) {f : X ⟶ Y}
(mf : (⟨X, Y, mX, mY, f⟩ : Σ' (X Y : C) (_ : X ∈ O) (_ : Y ∈ O), X ⟶ Y) ∈ H) :
f ≫ toSup O H mY = toSup O H mX :=
(sup_exists O H).choose_spec.choose_spec mX mY mf
#align category_theory.is_filtered.to_sup_commutes CategoryTheory.IsFiltered.toSup_commutes
variable {J : Type w} [SmallCategory J] [FinCategory J]
/-- If we have `IsFiltered C`, then for any functor `F : J ⥤ C` with `FinCategory J`,
there exists a cocone over `F`.
-/
theorem cocone_nonempty (F : J ⥤ C) : Nonempty (Cocone F) := by
classical
let O := Finset.univ.image F.obj
let H : Finset (Σ' (X Y : C) (_ : X ∈ O) (_ : Y ∈ O), X ⟶ Y) :=
Finset.univ.biUnion fun X : J =>
Finset.univ.biUnion fun Y : J =>
Finset.univ.image fun f : X ⟶ Y => ⟨F.obj X, F.obj Y, by simp [O], by simp [O], F.map f⟩
obtain ⟨Z, f, w⟩ := sup_exists O H
refine ⟨⟨Z, ⟨fun X => f (by simp [O]), ?_⟩⟩⟩
intro j j' g
dsimp
simp only [Category.comp_id]
apply w
simp only [O, H, Finset.mem_biUnion, Finset.mem_univ, Finset.mem_image, PSigma.mk.injEq,
true_and, exists_and_left]
exact ⟨j, rfl, j', g, by simp⟩
#align category_theory.is_filtered.cocone_nonempty CategoryTheory.IsFiltered.cocone_nonempty
/-- An arbitrary choice of cocone over `F : J ⥤ C`, for `FinCategory J` and `IsFiltered C`.
-/
noncomputable def cocone (F : J ⥤ C) : Cocone F :=
(cocone_nonempty F).some
#align category_theory.is_filtered.cocone CategoryTheory.IsFiltered.cocone
variable {D : Type u₁} [Category.{v₁} D]
/-- If `C` is filtered, and we have a functor `R : C ⥤ D` with a left adjoint, then `D` is filtered.
-/
theorem of_right_adjoint {L : D ⥤ C} {R : C ⥤ D} (h : L ⊣ R) : IsFiltered D :=
{ IsFilteredOrEmpty.of_right_adjoint h with
nonempty := IsFiltered.nonempty.map R.obj }
#align category_theory.is_filtered.of_right_adjoint CategoryTheory.IsFiltered.of_right_adjoint
/-- If `C` is filtered, and we have a right adjoint functor `R : C ⥤ D`, then `D` is filtered. -/
theorem of_isRightAdjoint (R : C ⥤ D) [R.IsRightAdjoint] : IsFiltered D :=
of_right_adjoint (Adjunction.ofIsRightAdjoint R)
#align category_theory.is_filtered.of_is_right_adjoint CategoryTheory.IsFiltered.of_isRightAdjoint
/-- Being filtered is preserved by equivalence of categories. -/
theorem of_equivalence (h : C ≌ D) : IsFiltered D :=
of_right_adjoint h.symm.toAdjunction
#align category_theory.is_filtered.of_equivalence CategoryTheory.IsFiltered.of_equivalence
end Nonempty
section OfCocone
open CategoryTheory.Limits
/-- If every finite diagram in `C` admits a cocone, then `C` is filtered. It is sufficient to verify
this for diagrams whose shape lives in any one fixed universe. -/
theorem of_cocone_nonempty (h : ∀ {J : Type w} [SmallCategory J] [FinCategory J] (F : J ⥤ C),
Nonempty (Cocone F)) : IsFiltered C := by
have : Nonempty C := by
obtain ⟨c⟩ := h (Functor.empty _)
exact ⟨c.pt⟩
have : IsFilteredOrEmpty C := by
refine ⟨?_, ?_⟩
· intros X Y
obtain ⟨c⟩ := h (ULiftHom.down ⋙ ULift.downFunctor ⋙ pair X Y)
exact ⟨c.pt, c.ι.app ⟨⟨WalkingPair.left⟩⟩, c.ι.app ⟨⟨WalkingPair.right⟩⟩, trivial⟩
· intros X Y f g
obtain ⟨c⟩ := h (ULiftHom.down ⋙ ULift.downFunctor ⋙ parallelPair f g)
refine ⟨c.pt, c.ι.app ⟨WalkingParallelPair.one⟩, ?_⟩
have h₁ := c.ι.naturality ⟨WalkingParallelPairHom.left⟩
have h₂ := c.ι.naturality ⟨WalkingParallelPairHom.right⟩
simp_all
apply IsFiltered.mk
theorem of_hasFiniteColimits [HasFiniteColimits C] : IsFiltered C :=
of_cocone_nonempty.{v} C fun F => ⟨colimit.cocone F⟩
theorem of_isTerminal {X : C} (h : IsTerminal X) : IsFiltered C :=
of_cocone_nonempty.{v} _ fun {_} _ _ _ => ⟨⟨X, ⟨fun _ => h.from _, fun _ _ _ => h.hom_ext _ _⟩⟩⟩
instance (priority := 100) of_hasTerminal [HasTerminal C] : IsFiltered C :=
of_isTerminal _ terminalIsTerminal
/-- For every universe `w`, `C` is filtered if and only if every finite diagram in `C` with shape
in `w` admits a cocone. -/
theorem iff_cocone_nonempty : IsFiltered C ↔
∀ {J : Type w} [SmallCategory J] [FinCategory J] (F : J ⥤ C), Nonempty (Cocone F) :=
⟨fun _ _ _ _ F => cocone_nonempty F, of_cocone_nonempty C⟩
end OfCocone
section SpecialShapes
variable {C}
variable [IsFilteredOrEmpty C]
/-- `max₃ j₁ j₂ j₃` is an arbitrary choice of object to the right of `j₁`, `j₂` and `j₃`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def max₃ (j₁ j₂ j₃ : C) : C :=
max (max j₁ j₂) j₃
#align category_theory.is_filtered.max₃ CategoryTheory.IsFiltered.max₃
/-- `firstToMax₃ j₁ j₂ j₃` is an arbitrary choice of morphism from `j₁` to `max₃ j₁ j₂ j₃`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def firstToMax₃ (j₁ j₂ j₃ : C) : j₁ ⟶ max₃ j₁ j₂ j₃ :=
leftToMax j₁ j₂ ≫ leftToMax (max j₁ j₂) j₃
#align category_theory.is_filtered.first_to_max₃ CategoryTheory.IsFiltered.firstToMax₃
/-- `secondToMax₃ j₁ j₂ j₃` is an arbitrary choice of morphism from `j₂` to `max₃ j₁ j₂ j₃`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def secondToMax₃ (j₁ j₂ j₃ : C) : j₂ ⟶ max₃ j₁ j₂ j₃ :=
rightToMax j₁ j₂ ≫ leftToMax (max j₁ j₂) j₃
#align category_theory.is_filtered.second_to_max₃ CategoryTheory.IsFiltered.secondToMax₃
/-- `thirdToMax₃ j₁ j₂ j₃` is an arbitrary choice of morphism from `j₃` to `max₃ j₁ j₂ j₃`,
whose existence is ensured by `IsFiltered`.
-/
noncomputable def thirdToMax₃ (j₁ j₂ j₃ : C) : j₃ ⟶ max₃ j₁ j₂ j₃ :=
rightToMax (max j₁ j₂) j₃
#align category_theory.is_filtered.third_to_max₃ CategoryTheory.IsFiltered.thirdToMax₃
/-- `coeq₃ f g h`, for morphisms `f g h : j₁ ⟶ j₂`, is an arbitrary choice of object
which admits a morphism `coeq₃Hom f g h : j₂ ⟶ coeq₃ f g h` such that
`coeq₃_condition₁`, `coeq₃_condition₂` and `coeq₃_condition₃` are satisfied.
Its existence is ensured by `IsFiltered`.
-/
noncomputable def coeq₃ {j₁ j₂ : C} (f g h : j₁ ⟶ j₂) : C :=
coeq (coeqHom f g ≫ leftToMax (coeq f g) (coeq g h))
(coeqHom g h ≫ rightToMax (coeq f g) (coeq g h))
#align category_theory.is_filtered.coeq₃ CategoryTheory.IsFiltered.coeq₃
/-- `coeq₃Hom f g h`, for morphisms `f g h : j₁ ⟶ j₂`, is an arbitrary choice of morphism
`j₂ ⟶ coeq₃ f g h` such that `coeq₃_condition₁`, `coeq₃_condition₂` and `coeq₃_condition₃`
are satisfied. Its existence is ensured by `IsFiltered`.
-/
noncomputable def coeq₃Hom {j₁ j₂ : C} (f g h : j₁ ⟶ j₂) : j₂ ⟶ coeq₃ f g h :=
coeqHom f g ≫
leftToMax (coeq f g) (coeq g h) ≫
coeqHom (coeqHom f g ≫ leftToMax (coeq f g) (coeq g h))
(coeqHom g h ≫ rightToMax (coeq f g) (coeq g h))
#align category_theory.is_filtered.coeq₃_hom CategoryTheory.IsFiltered.coeq₃Hom
| Mathlib/CategoryTheory/Filtered/Basic.lean | 461 | 463 | theorem coeq₃_condition₁ {j₁ j₂ : C} (f g h : j₁ ⟶ j₂) :
f ≫ coeq₃Hom f g h = g ≫ coeq₃Hom f g h := by |
simp only [coeq₃Hom, ← Category.assoc, coeq_condition f g]
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta
-/
import Mathlib.CategoryTheory.Adjunction.FullyFaithful
import Mathlib.CategoryTheory.Conj
import Mathlib.CategoryTheory.Functor.ReflectsIso
#align_import category_theory.adjunction.reflective from "leanprover-community/mathlib"@"239d882c4fb58361ee8b3b39fb2091320edef10a"
/-!
# Reflective functors
Basic properties of reflective functors, especially those relating to their essential image.
Note properties of reflective functors relating to limits and colimits are included in
`CategoryTheory.Monad.Limits`.
-/
universe v₁ v₂ v₃ u₁ u₂ u₃
noncomputable section
namespace CategoryTheory
open Category Adjunction
variable {C : Type u₁} {D : Type u₂} {E : Type u₃}
variable [Category.{v₁} C] [Category.{v₂} D] [Category.{v₃} E]
/--
A functor is *reflective*, or *a reflective inclusion*, if it is fully faithful and right adjoint.
-/
class Reflective (R : D ⥤ C) extends R.Full, R.Faithful where
/-- a choice of a left adjoint to `R` -/
L : C ⥤ D
/-- `R` is a right adjoint -/
adj : L ⊣ R
#align category_theory.reflective CategoryTheory.Reflective
variable (i : D ⥤ C)
/-- The reflector `C ⥤ D` when `R : D ⥤ C` is reflective. -/
def reflector [Reflective i] : C ⥤ D := Reflective.L (R := i)
/-- The adjunction `reflector i ⊣ i` when `i` is reflective. -/
def reflectorAdjunction [Reflective i] : reflector i ⊣ i := Reflective.adj
instance [Reflective i] : i.IsRightAdjoint := ⟨_, ⟨reflectorAdjunction i⟩⟩
instance [Reflective i] : (reflector i).IsLeftAdjoint := ⟨_, ⟨reflectorAdjunction i⟩⟩
/-- A reflective functor is fully faithful. -/
def Functor.fullyFaithfulOfReflective [Reflective i] : i.FullyFaithful :=
(reflectorAdjunction i).fullyFaithfulROfIsIsoCounit
-- TODO: This holds more generally for idempotent adjunctions, not just reflective adjunctions.
/-- For a reflective functor `i` (with left adjoint `L`), with unit `η`, we have `η_iL = iL η`.
-/
theorem unit_obj_eq_map_unit [Reflective i] (X : C) :
(reflectorAdjunction i).unit.app (i.obj ((reflector i).obj X)) =
i.map ((reflector i).map ((reflectorAdjunction i).unit.app X)) := by
rw [← cancel_mono (i.map ((reflectorAdjunction i).counit.app ((reflector i).obj X))),
← i.map_comp]
simp
#align category_theory.unit_obj_eq_map_unit CategoryTheory.unit_obj_eq_map_unit
/--
When restricted to objects in `D` given by `i : D ⥤ C`, the unit is an isomorphism. In other words,
`η_iX` is an isomorphism for any `X` in `D`.
More generally this applies to objects essentially in the reflective subcategory, see
`Functor.essImage.unit_isIso`.
-/
example [Reflective i] {B : D} : IsIso ((reflectorAdjunction i).unit.app (i.obj B)) :=
inferInstance
variable {i}
/-- If `A` is essentially in the image of a reflective functor `i`, then `η_A` is an isomorphism.
This gives that the "witness" for `A` being in the essential image can instead be given as the
reflection of `A`, with the isomorphism as `η_A`.
(For any `B` in the reflective subcategory, we automatically have that `ε_B` is an iso.)
-/
theorem Functor.essImage.unit_isIso [Reflective i] {A : C} (h : A ∈ i.essImage) :
IsIso ((reflectorAdjunction i).unit.app A) := by
rwa [isIso_unit_app_iff_mem_essImage]
#align category_theory.functor.ess_image.unit_is_iso CategoryTheory.Functor.essImage.unit_isIso
/-- If `η_A` is an isomorphism, then `A` is in the essential image of `i`. -/
theorem mem_essImage_of_unit_isIso {L : C ⥤ D} (adj : L ⊣ i) (A : C)
[IsIso (adj.unit.app A)] : A ∈ i.essImage :=
⟨L.obj A, ⟨(asIso (adj.unit.app A)).symm⟩⟩
#align category_theory.mem_ess_image_of_unit_is_iso CategoryTheory.mem_essImage_of_unit_isIso
/-- If `η_A` is a split monomorphism, then `A` is in the reflective subcategory. -/
theorem mem_essImage_of_unit_isSplitMono [Reflective i] {A : C}
[IsSplitMono ((reflectorAdjunction i).unit.app A)] : A ∈ i.essImage := by
let η : 𝟭 C ⟶ reflector i ⋙ i := (reflectorAdjunction i).unit
haveI : IsIso (η.app (i.obj ((reflector i).obj A))) :=
Functor.essImage.unit_isIso ((i.obj_mem_essImage _))
have : Epi (η.app A) := by
refine @epi_of_epi _ _ _ _ _ (retraction (η.app A)) (η.app A) ?_
rw [show retraction _ ≫ η.app A = _ from η.naturality (retraction (η.app A))]
apply epi_comp (η.app (i.obj ((reflector i).obj A)))
haveI := isIso_of_epi_of_isSplitMono (η.app A)
exact mem_essImage_of_unit_isIso (reflectorAdjunction i) A
#align category_theory.mem_ess_image_of_unit_is_split_mono CategoryTheory.mem_essImage_of_unit_isSplitMono
/-- Composition of reflective functors. -/
instance Reflective.comp (F : C ⥤ D) (G : D ⥤ E) [Reflective F] [Reflective G] :
Reflective (F ⋙ G) where
L := reflector G ⋙ reflector F
adj := (reflectorAdjunction G).comp (reflectorAdjunction F)
#align category_theory.reflective.comp CategoryTheory.Reflective.comp
/-- (Implementation) Auxiliary definition for `unitCompPartialBijective`. -/
def unitCompPartialBijectiveAux [Reflective i] (A : C) (B : D) :
(A ⟶ i.obj B) ≃ (i.obj ((reflector i).obj A) ⟶ i.obj B) :=
((reflectorAdjunction i).homEquiv _ _).symm.trans
(Functor.FullyFaithful.ofFullyFaithful i).homEquiv
#align category_theory.unit_comp_partial_bijective_aux CategoryTheory.unitCompPartialBijectiveAux
/-- The description of the inverse of the bijection `unitCompPartialBijectiveAux`. -/
theorem unitCompPartialBijectiveAux_symm_apply [Reflective i] {A : C} {B : D}
(f : i.obj ((reflector i).obj A) ⟶ i.obj B) :
(unitCompPartialBijectiveAux _ _).symm f = (reflectorAdjunction i).unit.app A ≫ f := by
simp [unitCompPartialBijectiveAux]
#align category_theory.unit_comp_partial_bijective_aux_symm_apply CategoryTheory.unitCompPartialBijectiveAux_symm_apply
/-- If `i` has a reflector `L`, then the function `(i.obj (L.obj A) ⟶ B) → (A ⟶ B)` given by
precomposing with `η.app A` is a bijection provided `B` is in the essential image of `i`.
That is, the function `fun (f : i.obj (L.obj A) ⟶ B) ↦ η.app A ≫ f` is bijective,
as long as `B` is in the essential image of `i`.
This definition gives an equivalence: the key property that the inverse can be described
nicely is shown in `unitCompPartialBijective_symm_apply`.
This establishes there is a natural bijection `(A ⟶ B) ≃ (i.obj (L.obj A) ⟶ B)`. In other words,
from the point of view of objects in `D`, `A` and `i.obj (L.obj A)` look the same: specifically
that `η.app A` is an isomorphism.
-/
def unitCompPartialBijective [Reflective i] (A : C) {B : C} (hB : B ∈ i.essImage) :
(A ⟶ B) ≃ (i.obj ((reflector i).obj A) ⟶ B) :=
calc
(A ⟶ B) ≃ (A ⟶ i.obj (Functor.essImage.witness hB)) := Iso.homCongr (Iso.refl _) hB.getIso.symm
_ ≃ (i.obj _ ⟶ i.obj (Functor.essImage.witness hB)) := unitCompPartialBijectiveAux _ _
_ ≃ (i.obj ((reflector i).obj A) ⟶ B) :=
Iso.homCongr (Iso.refl _) (Functor.essImage.getIso hB)
#align category_theory.unit_comp_partial_bijective CategoryTheory.unitCompPartialBijective
@[simp]
theorem unitCompPartialBijective_symm_apply [Reflective i] (A : C) {B : C} (hB : B ∈ i.essImage)
(f) : (unitCompPartialBijective A hB).symm f = (reflectorAdjunction i).unit.app A ≫ f := by
simp [unitCompPartialBijective, unitCompPartialBijectiveAux_symm_apply]
#align category_theory.unit_comp_partial_bijective_symm_apply CategoryTheory.unitCompPartialBijective_symm_apply
| Mathlib/CategoryTheory/Adjunction/Reflective.lean | 159 | 162 | theorem unitCompPartialBijective_symm_natural [Reflective i] (A : C) {B B' : C} (h : B ⟶ B')
(hB : B ∈ i.essImage) (hB' : B' ∈ i.essImage) (f : i.obj ((reflector i).obj A) ⟶ B) :
(unitCompPartialBijective A hB').symm (f ≫ h) = (unitCompPartialBijective A hB).symm f ≫ h := by |
simp
|
/-
Copyright (c) 2024 Jz Pan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jz Pan
-/
import Mathlib.FieldTheory.SeparableClosure
import Mathlib.Algebra.CharP.IntermediateField
/-!
# Purely inseparable extension and relative perfect closure
This file contains basics about purely inseparable extensions and the relative perfect closure
of fields.
## Main definitions
- `IsPurelyInseparable`: typeclass for purely inseparable field extensions: an algebraic extension
`E / F` is purely inseparable if and only if the minimal polynomial of every element of `E ∖ F`
is not separable.
- `perfectClosure`: the relative perfect closure of `F` in `E`, it consists of the elements
`x` of `E` such that there exists a natural number `n` such that `x ^ (ringExpChar F) ^ n`
is contained in `F`, where `ringExpChar F` is the exponential characteristic of `F`.
It is also the maximal purely inseparable subextension of `E / F` (`le_perfectClosure_iff`).
## Main results
- `IsPurelyInseparable.surjective_algebraMap_of_isSeparable`,
`IsPurelyInseparable.bijective_algebraMap_of_isSeparable`,
`IntermediateField.eq_bot_of_isPurelyInseparable_of_isSeparable`:
if `E / F` is both purely inseparable and separable, then `algebraMap F E` is surjective
(hence bijective). In particular, if an intermediate field of `E / F` is both purely inseparable
and separable, then it is equal to `F`.
- `isPurelyInseparable_iff_pow_mem`: a field extension `E / F` of exponential characteristic `q` is
purely inseparable if and only if for every element `x` of `E`, there exists a natural number `n`
such that `x ^ (q ^ n)` is contained in `F`.
- `IsPurelyInseparable.trans`: if `E / F` and `K / E` are both purely inseparable extensions, then
`K / F` is also purely inseparable.
- `isPurelyInseparable_iff_natSepDegree_eq_one`: `E / F` is purely inseparable if and only if for
every element `x` of `E`, its minimal polynomial has separable degree one.
- `isPurelyInseparable_iff_minpoly_eq_X_pow_sub_C`: a field extension `E / F` of exponential
characteristic `q` is purely inseparable if and only if for every element `x` of `E`, the minimal
polynomial of `x` over `F` is of form `X ^ (q ^ n) - y` for some natural number `n` and some
element `y` of `F`.
- `isPurelyInseparable_iff_minpoly_eq_X_sub_C_pow`: a field extension `E / F` of exponential
characteristic `q` is purely inseparable if and only if for every element `x` of `E`, the minimal
polynomial of `x` over `F` is of form `(X - x) ^ (q ^ n)` for some natural number `n`.
- `isPurelyInseparable_iff_finSepDegree_eq_one`: an algebraic extension is purely inseparable
if and only if it has finite separable degree (`Field.finSepDegree`) one.
**TODO:** remove the algebraic assumption.
- `IsPurelyInseparable.normal`: a purely inseparable extension is normal.
- `separableClosure.isPurelyInseparable`: if `E / F` is algebraic, then `E` is purely inseparable
over the separable closure of `F` in `E`.
- `separableClosure_le_iff`: if `E / F` is algebraic, then an intermediate field of `E / F` contains
the separable closure of `F` in `E` if and only if `E` is purely inseparable over it.
- `eq_separableClosure_iff`: if `E / F` is algebraic, then an intermediate field of `E / F` is equal
to the separable closure of `F` in `E` if and only if it is separable over `F`, and `E`
is purely inseparable over it.
- `le_perfectClosure_iff`: an intermediate field of `E / F` is contained in the relative perfect
closure of `F` in `E` if and only if it is purely inseparable over `F`.
- `perfectClosure.perfectRing`, `perfectClosure.perfectField`: if `E` is a perfect field, then the
(relative) perfect closure `perfectClosure F E` is perfect.
- `IsPurelyInseparable.injective_comp_algebraMap`: if `E / F` is purely inseparable, then for any
reduced ring `L`, the map `(E →+* L) → (F →+* L)` induced by `algebraMap F E` is injective.
In particular, a purely inseparable field extension is an epimorphism in the category of fields.
- `IntermediateField.isPurelyInseparable_adjoin_iff_pow_mem`: if `F` is of exponential
characteristic `q`, then `F(S) / F` is a purely inseparable extension if and only if for any
`x ∈ S`, `x ^ (q ^ n)` is contained in `F` for some `n : ℕ`.
- `Field.finSepDegree_eq`: if `E / F` is algebraic, then the `Field.finSepDegree F E` is equal to
`Field.sepDegree F E` as a natural number. This means that the cardinality of `Field.Emb F E`
and the degree of `(separableClosure F E) / F` are both finite or infinite, and when they are
finite, they coincide.
- `Field.finSepDegree_mul_finInsepDegree`: the finite separable degree multiply by the finite
inseparable degree is equal to the (finite) field extension degree.
- `Field.lift_sepDegree_mul_lift_sepDegree_of_isAlgebraic`: the separable degrees satisfy the
tower law: $[E:F]_s [K:E]_s = [K:F]_s$.
- `IntermediateField.sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable`,
`IntermediateField.sepDegree_adjoin_eq_of_isAlgebraic_of_isPurelyInseparable'`:
if `K / E / F` is a field extension tower, such that `E / F` is purely inseparable, then
for any subset `S` of `K` such that `F(S) / F` is algebraic, the `E(S) / E` and `F(S) / F` have
the same separable degree. In particular, if `S` is an intermediate field of `K / F` such that
`S / F` is algebraic, the `E(S) / E` and `S / F` have the same separable degree.
- `minpoly.map_eq_of_separable_of_isPurelyInseparable`: if `K / E / F` is a field extension tower,
such that `E / F` is purely inseparable, then for any element `x` of `K` separable over `F`,
it has the same minimal polynomials over `F` and over `E`.
- `Polynomial.Separable.map_irreducible_of_isPurelyInseparable`: if `E / F` is purely inseparable,
`f` is a separable irreducible polynomial over `F`, then it is also irreducible over `E`.
## Tags
separable degree, degree, separable closure, purely inseparable
## TODO
- `IsPurelyInseparable.of_injective_comp_algebraMap`: if `L` is an algebraically closed field
containing `E`, such that the map `(E →+* L) → (F →+* L)` induced by `algebraMap F E` is
injective, then `E / F` is purely inseparable. As a corollary, epimorphisms in the category of
fields must be purely inseparable extensions. Need to use the fact that `Emb F E` is infinite
(or just not a singleton) when `E / F` is (purely) transcendental.
- Restate some intermediate result in terms of linearly disjointness.
- Prove that the inseparable degrees satisfy the tower law: $[E:F]_i [K:E]_i = [K:F]_i$.
Probably an argument using linearly disjointness is needed.
-/
open FiniteDimensional Polynomial IntermediateField Field
noncomputable section
universe u v w
variable (F : Type u) (E : Type v) [Field F] [Field E] [Algebra F E]
variable (K : Type w) [Field K] [Algebra F K]
section IsPurelyInseparable
/-- Typeclass for purely inseparable field extensions: an algebraic extension `E / F` is purely
inseparable if and only if the minimal polynomial of every element of `E ∖ F` is not separable. -/
class IsPurelyInseparable : Prop where
isIntegral : Algebra.IsIntegral F E
inseparable' (x : E) : (minpoly F x).Separable → x ∈ (algebraMap F E).range
attribute [instance] IsPurelyInseparable.isIntegral
variable {E} in
theorem IsPurelyInseparable.isIntegral' [IsPurelyInseparable F E] (x : E) : IsIntegral F x :=
Algebra.IsIntegral.isIntegral _
theorem IsPurelyInseparable.isAlgebraic [IsPurelyInseparable F E] :
Algebra.IsAlgebraic F E := inferInstance
variable {E}
theorem IsPurelyInseparable.inseparable [IsPurelyInseparable F E] :
∀ x : E, (minpoly F x).Separable → x ∈ (algebraMap F E).range :=
IsPurelyInseparable.inseparable'
variable {F K}
theorem isPurelyInseparable_iff : IsPurelyInseparable F E ↔ ∀ x : E,
IsIntegral F x ∧ ((minpoly F x).Separable → x ∈ (algebraMap F E).range) :=
⟨fun h x ↦ ⟨h.isIntegral' x, h.inseparable' x⟩, fun h ↦ ⟨⟨fun x ↦ (h x).1⟩, fun x ↦ (h x).2⟩⟩
/-- Transfer `IsPurelyInseparable` across an `AlgEquiv`. -/
theorem AlgEquiv.isPurelyInseparable (e : K ≃ₐ[F] E) [IsPurelyInseparable F K] :
IsPurelyInseparable F E := by
refine ⟨⟨fun _ ↦ by rw [← isIntegral_algEquiv e.symm]; exact IsPurelyInseparable.isIntegral' F _⟩,
fun x h ↦ ?_⟩
rw [← minpoly.algEquiv_eq e.symm] at h
simpa only [RingHom.mem_range, algebraMap_eq_apply] using IsPurelyInseparable.inseparable F _ h
theorem AlgEquiv.isPurelyInseparable_iff (e : K ≃ₐ[F] E) :
IsPurelyInseparable F K ↔ IsPurelyInseparable F E :=
⟨fun _ ↦ e.isPurelyInseparable, fun _ ↦ e.symm.isPurelyInseparable⟩
/-- If `E / F` is an algebraic extension, `F` is separably closed,
then `E / F` is purely inseparable. -/
theorem Algebra.IsAlgebraic.isPurelyInseparable_of_isSepClosed [Algebra.IsAlgebraic F E]
[IsSepClosed F] : IsPurelyInseparable F E :=
⟨inferInstance, fun x h ↦ minpoly.mem_range_of_degree_eq_one F x <|
IsSepClosed.degree_eq_one_of_irreducible F (minpoly.irreducible
(Algebra.IsIntegral.isIntegral _)) h⟩
variable (F E K)
/-- If `E / F` is both purely inseparable and separable, then `algebraMap F E` is surjective. -/
theorem IsPurelyInseparable.surjective_algebraMap_of_isSeparable
[IsPurelyInseparable F E] [IsSeparable F E] : Function.Surjective (algebraMap F E) :=
fun x ↦ IsPurelyInseparable.inseparable F x (IsSeparable.separable F x)
/-- If `E / F` is both purely inseparable and separable, then `algebraMap F E` is bijective. -/
theorem IsPurelyInseparable.bijective_algebraMap_of_isSeparable
[IsPurelyInseparable F E] [IsSeparable F E] : Function.Bijective (algebraMap F E) :=
⟨(algebraMap F E).injective, surjective_algebraMap_of_isSeparable F E⟩
variable {F E} in
/-- If an intermediate field of `E / F` is both purely inseparable and separable, then it is equal
to `F`. -/
theorem IntermediateField.eq_bot_of_isPurelyInseparable_of_isSeparable (L : IntermediateField F E)
[IsPurelyInseparable F L] [IsSeparable F L] : L = ⊥ := bot_unique fun x hx ↦ by
obtain ⟨y, hy⟩ := IsPurelyInseparable.surjective_algebraMap_of_isSeparable F L ⟨x, hx⟩
exact ⟨y, congr_arg (algebraMap L E) hy⟩
/-- If `E / F` is purely inseparable, then the separable closure of `F` in `E` is
equal to `F`. -/
theorem separableClosure.eq_bot_of_isPurelyInseparable [IsPurelyInseparable F E] :
separableClosure F E = ⊥ :=
bot_unique fun x h ↦ IsPurelyInseparable.inseparable F x (mem_separableClosure_iff.1 h)
variable {F E} in
/-- If `E / F` is an algebraic extension, then the separable closure of `F` in `E` is
equal to `F` if and only if `E / F` is purely inseparable. -/
theorem separableClosure.eq_bot_iff [Algebra.IsAlgebraic F E] :
separableClosure F E = ⊥ ↔ IsPurelyInseparable F E :=
⟨fun h ↦ isPurelyInseparable_iff.2 fun x ↦ ⟨Algebra.IsIntegral.isIntegral x, fun hs ↦ by
simpa only [h] using mem_separableClosure_iff.2 hs⟩, fun _ ↦ eq_bot_of_isPurelyInseparable F E⟩
instance isPurelyInseparable_self : IsPurelyInseparable F F :=
⟨inferInstance, fun x _ ↦ ⟨x, rfl⟩⟩
variable {E}
/-- A field extension `E / F` of exponential characteristic `q` is purely inseparable
if and only if for every element `x` of `E`, there exists a natural number `n` such that
`x ^ (q ^ n)` is contained in `F`. -/
| Mathlib/FieldTheory/PurelyInseparable.lean | 230 | 243 | theorem isPurelyInseparable_iff_pow_mem (q : ℕ) [ExpChar F q] :
IsPurelyInseparable F E ↔ ∀ x : E, ∃ n : ℕ, x ^ q ^ n ∈ (algebraMap F E).range := by |
rw [isPurelyInseparable_iff]
refine ⟨fun h x ↦ ?_, fun h x ↦ ?_⟩
· obtain ⟨g, h1, n, h2⟩ := (minpoly.irreducible (h x).1).hasSeparableContraction q
exact ⟨n, (h _).2 <| h1.of_dvd <| minpoly.dvd F _ <| by
simpa only [expand_aeval, minpoly.aeval] using congr_arg (aeval x) h2⟩
have hdeg := (minpoly.natSepDegree_eq_one_iff_pow_mem q).2 (h x)
have halg : IsIntegral F x := by_contra fun h' ↦ by
simp only [minpoly.eq_zero h', natSepDegree_zero, zero_ne_one] at hdeg
refine ⟨halg, fun hsep ↦ ?_⟩
rw [hsep.natSepDegree_eq_natDegree, ← adjoin.finrank halg,
IntermediateField.finrank_eq_one_iff] at hdeg
simpa only [hdeg] using mem_adjoin_simple_self F x
|
/-
Copyright (c) 2018 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Simon Hudon
-/
import Mathlib.Control.Functor.Multivariate
import Mathlib.Data.PFunctor.Univariate.Basic
#align_import data.pfunctor.multivariate.basic from "leanprover-community/mathlib"@"e3d9ab8faa9dea8f78155c6c27d62a621f4c152d"
/-!
# Multivariate polynomial functors.
Multivariate polynomial functors are used for defining M-types and W-types.
They map a type vector `α` to the type `Σ a : A, B a ⟹ α`, with `A : Type` and
`B : A → TypeVec n`. They interact well with Lean's inductive definitions because
they guarantee that occurrences of `α` are positive.
-/
universe u v
open MvFunctor
/-- multivariate polynomial functors
-/
@[pp_with_univ]
structure MvPFunctor (n : ℕ) where
/-- The head type -/
A : Type u
/-- The child family of types -/
B : A → TypeVec.{u} n
#align mvpfunctor MvPFunctor
namespace MvPFunctor
open MvFunctor (LiftP LiftR)
variable {n m : ℕ} (P : MvPFunctor.{u} n)
/-- Applying `P` to an object of `Type` -/
@[coe]
def Obj (α : TypeVec.{u} n) : Type u :=
Σ a : P.A, P.B a ⟹ α
#align mvpfunctor.obj MvPFunctor.Obj
instance : CoeFun (MvPFunctor.{u} n) (fun _ => TypeVec.{u} n → Type u) where
coe := Obj
/-- Applying `P` to a morphism of `Type` -/
def map {α β : TypeVec n} (f : α ⟹ β) : P α → P β := fun ⟨a, g⟩ => ⟨a, TypeVec.comp f g⟩
#align mvpfunctor.map MvPFunctor.map
instance : Inhabited (MvPFunctor n) :=
⟨⟨default, default⟩⟩
instance Obj.inhabited {α : TypeVec n} [Inhabited P.A] [∀ i, Inhabited (α i)] :
Inhabited (P α) :=
⟨⟨default, fun _ _ => default⟩⟩
#align mvpfunctor.obj.inhabited MvPFunctor.Obj.inhabited
instance : MvFunctor.{u} P.Obj :=
⟨@MvPFunctor.map n P⟩
theorem map_eq {α β : TypeVec n} (g : α ⟹ β) (a : P.A) (f : P.B a ⟹ α) :
@MvFunctor.map _ P.Obj _ _ _ g ⟨a, f⟩ = ⟨a, g ⊚ f⟩ :=
rfl
#align mvpfunctor.map_eq MvPFunctor.map_eq
theorem id_map {α : TypeVec n} : ∀ x : P α, TypeVec.id <$$> x = x
| ⟨_, _⟩ => rfl
#align mvpfunctor.id_map MvPFunctor.id_map
theorem comp_map {α β γ : TypeVec n} (f : α ⟹ β) (g : β ⟹ γ) :
∀ x : P α, (g ⊚ f) <$$> x = g <$$> f <$$> x
| ⟨_, _⟩ => rfl
#align mvpfunctor.comp_map MvPFunctor.comp_map
instance : LawfulMvFunctor.{u} P.Obj where
id_map := @id_map _ P
comp_map := @comp_map _ P
/-- Constant functor where the input object does not affect the output -/
def const (n : ℕ) (A : Type u) : MvPFunctor n :=
{ A
B := fun _ _ => PEmpty }
#align mvpfunctor.const MvPFunctor.const
section Const
variable (n) {A : Type u} {α β : TypeVec.{u} n}
/-- Constructor for the constant functor -/
def const.mk (x : A) {α} : const n A α :=
⟨x, fun _ a => PEmpty.elim a⟩
#align mvpfunctor.const.mk MvPFunctor.const.mk
variable {n}
/-- Destructor for the constant functor -/
def const.get (x : const n A α) : A :=
x.1
#align mvpfunctor.const.get MvPFunctor.const.get
@[simp]
theorem const.get_map (f : α ⟹ β) (x : const n A α) : const.get (f <$$> x) = const.get x := by
cases x
rfl
#align mvpfunctor.const.get_map MvPFunctor.const.get_map
@[simp]
theorem const.get_mk (x : A) : const.get (const.mk n x : const n A α) = x := rfl
#align mvpfunctor.const.get_mk MvPFunctor.const.get_mk
@[simp]
theorem const.mk_get (x : const n A α) : const.mk n (const.get x) = x := by
cases x
dsimp [const.get, const.mk]
congr with (_⟨⟩)
#align mvpfunctor.const.mk_get MvPFunctor.const.mk_get
end Const
/-- Functor composition on polynomial functors -/
def comp (P : MvPFunctor.{u} n) (Q : Fin2 n → MvPFunctor.{u} m) : MvPFunctor m where
A := Σ a₂ : P.1, ∀ i, P.2 a₂ i → (Q i).1
B a i := Σ(j : _) (b : P.2 a.1 j), (Q j).2 (a.snd j b) i
#align mvpfunctor.comp MvPFunctor.comp
variable {P} {Q : Fin2 n → MvPFunctor.{u} m} {α β : TypeVec.{u} m}
/-- Constructor for functor composition -/
def comp.mk (x : P (fun i => Q i α)) : comp P Q α :=
⟨⟨x.1, fun _ a => (x.2 _ a).1⟩, fun i a => (x.snd a.fst a.snd.fst).snd i a.snd.snd⟩
#align mvpfunctor.comp.mk MvPFunctor.comp.mk
/-- Destructor for functor composition -/
def comp.get (x : comp P Q α) : P (fun i => Q i α) :=
⟨x.1.1, fun i a => ⟨x.fst.snd i a, fun (j : Fin2 m) (b : (Q i).B _ j) => x.snd j ⟨i, ⟨a, b⟩⟩⟩⟩
#align mvpfunctor.comp.get MvPFunctor.comp.get
theorem comp.get_map (f : α ⟹ β) (x : comp P Q α) :
comp.get (f <$$> x) = (fun i (x : Q i α) => f <$$> x) <$$> comp.get x := by
rfl
#align mvpfunctor.comp.get_map MvPFunctor.comp.get_map
@[simp]
theorem comp.get_mk (x : P (fun i => Q i α)) : comp.get (comp.mk x) = x := by
rfl
#align mvpfunctor.comp.get_mk MvPFunctor.comp.get_mk
@[simp]
theorem comp.mk_get (x : comp P Q α) : comp.mk (comp.get x) = x := by
rfl
#align mvpfunctor.comp.mk_get MvPFunctor.comp.mk_get
/-
lifting predicates and relations
-/
| Mathlib/Data/PFunctor/Multivariate/Basic.lean | 160 | 170 | theorem liftP_iff {α : TypeVec n} (p : ∀ ⦃i⦄, α i → Prop) (x : P α) :
LiftP p x ↔ ∃ a f, x = ⟨a, f⟩ ∧ ∀ i j, p (f i j) := by |
constructor
· rintro ⟨y, hy⟩
cases' h : y with a f
refine ⟨a, fun i j => (f i j).val, ?_, fun i j => (f i j).property⟩
rw [← hy, h, map_eq]
rfl
rintro ⟨a, f, xeq, pf⟩
use ⟨a, fun i j => ⟨f i j, pf i j⟩⟩
rw [xeq]; rfl
|
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Felix Weilacher
-/
import Mathlib.Data.Real.Cardinality
import Mathlib.Topology.MetricSpace.Perfect
import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric
import Mathlib.Topology.CountableSeparatingOn
#align_import measure_theory.constructions.polish from "leanprover-community/mathlib"@"9f55d0d4363ae59948c33864cbc52e0b12e0e8ce"
/-!
# The Borel sigma-algebra on Polish spaces
We discuss several results pertaining to the relationship between the topology and the Borel
structure on Polish spaces.
## Main definitions and results
First, we define standard Borel spaces.
* A `StandardBorelSpace α` is a typeclass for measurable spaces which arise as the Borel sets
of some Polish topology.
Next, we define the class of analytic sets and establish its basic properties.
* `MeasureTheory.AnalyticSet s`: a set in a topological space is analytic if it is the continuous
image of a Polish space. Equivalently, it is empty, or the image of `ℕ → ℕ`.
* `MeasureTheory.AnalyticSet.image_of_continuous`: a continuous image of an analytic set is
analytic.
* `MeasurableSet.analyticSet`: in a Polish space, any Borel-measurable set is analytic.
Then, we show Lusin's theorem that two disjoint analytic sets can be separated by Borel sets.
* `MeasurablySeparable s t` states that there exists a measurable set containing `s` and disjoint
from `t`.
* `AnalyticSet.measurablySeparable` shows that two disjoint analytic sets are separated by a
Borel set.
We then prove the Lusin-Souslin theorem that a continuous injective image of a Borel subset of
a Polish space is Borel. The proof of this nontrivial result relies on the above results on
analytic sets.
* `MeasurableSet.image_of_continuousOn_injOn` asserts that, if `s` is a Borel measurable set in
a Polish space, then the image of `s` under a continuous injective map is still Borel measurable.
* `Continuous.measurableEmbedding` states that a continuous injective map on a Polish space
is a measurable embedding for the Borel sigma-algebra.
* `ContinuousOn.measurableEmbedding` is the same result for a map restricted to a measurable set
on which it is continuous.
* `Measurable.measurableEmbedding` states that a measurable injective map from
a standard Borel space to a second-countable topological space is a measurable embedding.
* `isClopenable_iff_measurableSet`: in a Polish space, a set is clopenable (i.e., it can be made
open and closed by using a finer Polish topology) if and only if it is Borel-measurable.
We use this to prove several versions of the Borel isomorphism theorem.
* `PolishSpace.measurableEquivOfNotCountable` : Any two uncountable standard Borel spaces
are Borel isomorphic.
* `PolishSpace.Equiv.measurableEquiv` : Any two standard Borel spaces of the same cardinality
are Borel isomorphic.
-/
open Set Function PolishSpace PiNat TopologicalSpace Bornology Metric Filter Topology MeasureTheory
/-! ### Standard Borel Spaces -/
variable (α : Type*)
/-- A standard Borel space is a measurable space arising as the Borel sets of some Polish topology.
This is useful in situations where a space has no natural topology or
the natural topology in a space is non-Polish.
To endow a standard Borel space `α` with a compatible Polish topology, use
`letI := upgradeStandardBorel α`. One can then use `eq_borel_upgradeStandardBorel α` to
rewrite the `MeasurableSpace α` instance to `borel α t`, where `t` is the new topology. -/
class StandardBorelSpace [MeasurableSpace α] : Prop where
/-- There exists a compatible Polish topology. -/
polish : ∃ _ : TopologicalSpace α, BorelSpace α ∧ PolishSpace α
/-- A convenience class similar to `UpgradedPolishSpace`. No instance should be registered.
Instead one should use `letI := upgradeStandardBorel α`. -/
class UpgradedStandardBorel extends MeasurableSpace α, TopologicalSpace α,
BorelSpace α, PolishSpace α
/-- Use as `letI := upgradeStandardBorel α` to endow a standard Borel space `α` with
a compatible Polish topology.
Warning: following this with `borelize α` will cause an error. Instead, one can
rewrite with `eq_borel_upgradeStandardBorel α`.
TODO: fix the corresponding bug in `borelize`. -/
noncomputable
def upgradeStandardBorel [MeasurableSpace α] [h : StandardBorelSpace α] :
UpgradedStandardBorel α := by
choose τ hb hp using h.polish
constructor
/-- The `MeasurableSpace α` instance on a `StandardBorelSpace` `α` is equal to
the borel sets of `upgradeStandardBorel α`. -/
theorem eq_borel_upgradeStandardBorel [MeasurableSpace α] [StandardBorelSpace α] :
‹MeasurableSpace α› = @borel _ (upgradeStandardBorel α).toTopologicalSpace :=
@BorelSpace.measurable_eq _ (upgradeStandardBorel α).toTopologicalSpace _
(upgradeStandardBorel α).toBorelSpace
variable {α}
section
variable [MeasurableSpace α]
instance standardBorel_of_polish [τ : TopologicalSpace α]
[BorelSpace α] [PolishSpace α] : StandardBorelSpace α := by exists τ
instance countablyGenerated_of_standardBorel [StandardBorelSpace α] :
MeasurableSpace.CountablyGenerated α :=
letI := upgradeStandardBorel α
inferInstance
instance measurableSingleton_of_standardBorel [StandardBorelSpace α] : MeasurableSingletonClass α :=
letI := upgradeStandardBorel α
inferInstance
namespace StandardBorelSpace
variable {β : Type*} [MeasurableSpace β]
section instances
/-- A product of two standard Borel spaces is standard Borel. -/
instance prod [StandardBorelSpace α] [StandardBorelSpace β] : StandardBorelSpace (α × β) :=
letI := upgradeStandardBorel α
letI := upgradeStandardBorel β
inferInstance
/-- A product of countably many standard Borel spaces is standard Borel. -/
instance pi_countable {ι : Type*} [Countable ι] {α : ι → Type*} [∀ n, MeasurableSpace (α n)]
[∀ n, StandardBorelSpace (α n)] : StandardBorelSpace (∀ n, α n) :=
letI := fun n => upgradeStandardBorel (α n)
inferInstance
end instances
end StandardBorelSpace
end section
variable {ι : Type*}
namespace MeasureTheory
variable [TopologicalSpace α]
/-! ### Analytic sets -/
/-- An analytic set is a set which is the continuous image of some Polish space. There are several
equivalent characterizations of this definition. For the definition, we pick one that avoids
universe issues: a set is analytic if and only if it is a continuous image of `ℕ → ℕ` (or if it
is empty). The above more usual characterization is given
in `analyticSet_iff_exists_polishSpace_range`.
Warning: these are analytic sets in the context of descriptive set theory (which is why they are
registered in the namespace `MeasureTheory`). They have nothing to do with analytic sets in the
context of complex analysis. -/
irreducible_def AnalyticSet (s : Set α) : Prop :=
s = ∅ ∨ ∃ f : (ℕ → ℕ) → α, Continuous f ∧ range f = s
#align measure_theory.analytic_set MeasureTheory.AnalyticSet
theorem analyticSet_empty : AnalyticSet (∅ : Set α) := by
rw [AnalyticSet]
exact Or.inl rfl
#align measure_theory.analytic_set_empty MeasureTheory.analyticSet_empty
theorem analyticSet_range_of_polishSpace {β : Type*} [TopologicalSpace β] [PolishSpace β]
{f : β → α} (f_cont : Continuous f) : AnalyticSet (range f) := by
cases isEmpty_or_nonempty β
· rw [range_eq_empty]
exact analyticSet_empty
· rw [AnalyticSet]
obtain ⟨g, g_cont, hg⟩ : ∃ g : (ℕ → ℕ) → β, Continuous g ∧ Surjective g :=
exists_nat_nat_continuous_surjective β
refine Or.inr ⟨f ∘ g, f_cont.comp g_cont, ?_⟩
rw [hg.range_comp]
#align measure_theory.analytic_set_range_of_polish_space MeasureTheory.analyticSet_range_of_polishSpace
/-- The image of an open set under a continuous map is analytic. -/
theorem _root_.IsOpen.analyticSet_image {β : Type*} [TopologicalSpace β] [PolishSpace β]
{s : Set β} (hs : IsOpen s) {f : β → α} (f_cont : Continuous f) : AnalyticSet (f '' s) := by
rw [image_eq_range]
haveI : PolishSpace s := hs.polishSpace
exact analyticSet_range_of_polishSpace (f_cont.comp continuous_subtype_val)
#align is_open.analytic_set_image IsOpen.analyticSet_image
/-- A set is analytic if and only if it is the continuous image of some Polish space. -/
theorem analyticSet_iff_exists_polishSpace_range {s : Set α} :
AnalyticSet s ↔
∃ (β : Type) (h : TopologicalSpace β) (_ : @PolishSpace β h) (f : β → α),
@Continuous _ _ h _ f ∧ range f = s := by
constructor
· intro h
rw [AnalyticSet] at h
cases' h with h h
· refine ⟨Empty, inferInstance, inferInstance, Empty.elim, continuous_bot, ?_⟩
rw [h]
exact range_eq_empty _
· exact ⟨ℕ → ℕ, inferInstance, inferInstance, h⟩
· rintro ⟨β, h, h', f, f_cont, f_range⟩
rw [← f_range]
exact analyticSet_range_of_polishSpace f_cont
#align measure_theory.analytic_set_iff_exists_polish_space_range MeasureTheory.analyticSet_iff_exists_polishSpace_range
/-- The continuous image of an analytic set is analytic -/
theorem AnalyticSet.image_of_continuousOn {β : Type*} [TopologicalSpace β] {s : Set α}
(hs : AnalyticSet s) {f : α → β} (hf : ContinuousOn f s) : AnalyticSet (f '' s) := by
rcases analyticSet_iff_exists_polishSpace_range.1 hs with ⟨γ, γtop, γpolish, g, g_cont, gs⟩
have : f '' s = range (f ∘ g) := by rw [range_comp, gs]
rw [this]
apply analyticSet_range_of_polishSpace
apply hf.comp_continuous g_cont fun x => _
rw [← gs]
exact mem_range_self
#align measure_theory.analytic_set.image_of_continuous_on MeasureTheory.AnalyticSet.image_of_continuousOn
theorem AnalyticSet.image_of_continuous {β : Type*} [TopologicalSpace β] {s : Set α}
(hs : AnalyticSet s) {f : α → β} (hf : Continuous f) : AnalyticSet (f '' s) :=
hs.image_of_continuousOn hf.continuousOn
#align measure_theory.analytic_set.image_of_continuous MeasureTheory.AnalyticSet.image_of_continuous
/-- A countable intersection of analytic sets is analytic. -/
theorem AnalyticSet.iInter [hι : Nonempty ι] [Countable ι] [T2Space α] {s : ι → Set α}
(hs : ∀ n, AnalyticSet (s n)) : AnalyticSet (⋂ n, s n) := by
rcases hι with ⟨i₀⟩
/- For the proof, write each `s n` as the continuous image under a map `f n` of a
Polish space `β n`. The product space `γ = Π n, β n` is also Polish, and so is the subset
`t` of sequences `x n` for which `f n (x n)` is independent of `n`. The set `t` is Polish, and
the range of `x ↦ f 0 (x 0)` on `t` is exactly `⋂ n, s n`, so this set is analytic. -/
choose β hβ h'β f f_cont f_range using fun n =>
analyticSet_iff_exists_polishSpace_range.1 (hs n)
let γ := ∀ n, β n
let t : Set γ := ⋂ n, { x | f n (x n) = f i₀ (x i₀) }
have t_closed : IsClosed t := by
apply isClosed_iInter
intro n
exact
isClosed_eq ((f_cont n).comp (continuous_apply n)) ((f_cont i₀).comp (continuous_apply i₀))
haveI : PolishSpace t := t_closed.polishSpace
let F : t → α := fun x => f i₀ ((x : γ) i₀)
have F_cont : Continuous F := (f_cont i₀).comp ((continuous_apply i₀).comp continuous_subtype_val)
have F_range : range F = ⋂ n : ι, s n := by
apply Subset.antisymm
· rintro y ⟨x, rfl⟩
refine mem_iInter.2 fun n => ?_
have : f n ((x : γ) n) = F x := (mem_iInter.1 x.2 n : _)
rw [← this, ← f_range n]
exact mem_range_self _
· intro y hy
have A : ∀ n, ∃ x : β n, f n x = y := by
intro n
rw [← mem_range, f_range n]
exact mem_iInter.1 hy n
choose x hx using A
have xt : x ∈ t := by
refine mem_iInter.2 fun n => ?_
simp [hx]
refine ⟨⟨x, xt⟩, ?_⟩
exact hx i₀
rw [← F_range]
exact analyticSet_range_of_polishSpace F_cont
#align measure_theory.analytic_set.Inter MeasureTheory.AnalyticSet.iInter
/-- A countable union of analytic sets is analytic. -/
theorem AnalyticSet.iUnion [Countable ι] {s : ι → Set α} (hs : ∀ n, AnalyticSet (s n)) :
AnalyticSet (⋃ n, s n) := by
/- For the proof, write each `s n` as the continuous image under a map `f n` of a
Polish space `β n`. The union space `γ = Σ n, β n` is also Polish, and the map `F : γ → α` which
coincides with `f n` on `β n` sends it to `⋃ n, s n`. -/
choose β hβ h'β f f_cont f_range using fun n =>
analyticSet_iff_exists_polishSpace_range.1 (hs n)
let γ := Σn, β n
let F : γ → α := fun ⟨n, x⟩ ↦ f n x
have F_cont : Continuous F := continuous_sigma f_cont
have F_range : range F = ⋃ n, s n := by
simp only [γ, range_sigma_eq_iUnion_range, f_range]
rw [← F_range]
exact analyticSet_range_of_polishSpace F_cont
#align measure_theory.analytic_set.Union MeasureTheory.AnalyticSet.iUnion
theorem _root_.IsClosed.analyticSet [PolishSpace α] {s : Set α} (hs : IsClosed s) :
AnalyticSet s := by
haveI : PolishSpace s := hs.polishSpace
rw [← @Subtype.range_val α s]
exact analyticSet_range_of_polishSpace continuous_subtype_val
#align is_closed.analytic_set IsClosed.analyticSet
/-- Given a Borel-measurable set in a Polish space, there exists a finer Polish topology making
it clopen. This is in fact an equivalence, see `isClopenable_iff_measurableSet`. -/
theorem _root_.MeasurableSet.isClopenable [PolishSpace α] [MeasurableSpace α] [BorelSpace α]
{s : Set α} (hs : MeasurableSet s) : IsClopenable s := by
revert s
apply MeasurableSet.induction_on_open
· exact fun u hu => hu.isClopenable
· exact fun u _ h'u => h'u.compl
· exact fun f _ _ hf => IsClopenable.iUnion hf
#align measurable_set.is_clopenable MeasurableSet.isClopenable
/-- A Borel-measurable set in a Polish space is analytic. -/
theorem _root_.MeasurableSet.analyticSet {α : Type*} [t : TopologicalSpace α] [PolishSpace α]
[MeasurableSpace α] [BorelSpace α] {s : Set α} (hs : MeasurableSet s) : AnalyticSet s := by
/- For a short proof (avoiding measurable induction), one sees `s` as a closed set for a finer
topology `t'`. It is analytic for this topology. As the identity from `t'` to `t` is continuous
and the image of an analytic set is analytic, it follows that `s` is also analytic for `t`. -/
obtain ⟨t', t't, t'_polish, s_closed, _⟩ :
∃ t' : TopologicalSpace α, t' ≤ t ∧ @PolishSpace α t' ∧ IsClosed[t'] s ∧ IsOpen[t'] s :=
hs.isClopenable
have A := @IsClosed.analyticSet α t' t'_polish s s_closed
convert @AnalyticSet.image_of_continuous α t' α t s A id (continuous_id_of_le t't)
simp only [id, image_id']
#align measurable_set.analytic_set MeasurableSet.analyticSet
/-- Given a Borel-measurable function from a Polish space to a second-countable space, there exists
a finer Polish topology on the source space for which the function is continuous. -/
theorem _root_.Measurable.exists_continuous {α β : Type*} [t : TopologicalSpace α] [PolishSpace α]
[MeasurableSpace α] [BorelSpace α] [tβ : TopologicalSpace β] [MeasurableSpace β]
[OpensMeasurableSpace β] {f : α → β} [SecondCountableTopology (range f)] (hf : Measurable f) :
∃ t' : TopologicalSpace α, t' ≤ t ∧ @Continuous α β t' tβ f ∧ @PolishSpace α t' := by
obtain ⟨b, b_count, -, hb⟩ :
∃ b : Set (Set (range f)), b.Countable ∧ ∅ ∉ b ∧ IsTopologicalBasis b :=
exists_countable_basis (range f)
haveI : Countable b := b_count.to_subtype
have : ∀ s : b, IsClopenable (rangeFactorization f ⁻¹' s) := fun s ↦ by
apply MeasurableSet.isClopenable
exact hf.subtype_mk (hb.isOpen s.2).measurableSet
choose T Tt Tpolish _ Topen using this
obtain ⟨t', t'T, t't, t'_polish⟩ :
∃ t' : TopologicalSpace α, (∀ i, t' ≤ T i) ∧ t' ≤ t ∧ @PolishSpace α t' :=
exists_polishSpace_forall_le (t := t) T Tt Tpolish
refine ⟨t', t't, ?_, t'_polish⟩
have : Continuous[t', _] (rangeFactorization f) :=
hb.continuous_iff.2 fun s hs => t'T ⟨s, hs⟩ _ (Topen ⟨s, hs⟩)
exact continuous_subtype_val.comp this
#align measurable.exists_continuous Measurable.exists_continuous
/-- The image of a measurable set in a standard Borel space under a measurable map
is an analytic set. -/
theorem _root_.MeasurableSet.analyticSet_image {X Y : Type*} [MeasurableSpace X]
[StandardBorelSpace X] [TopologicalSpace Y] [MeasurableSpace Y]
[OpensMeasurableSpace Y] {f : X → Y} [SecondCountableTopology (range f)] {s : Set X}
(hs : MeasurableSet s) (hf : Measurable f) : AnalyticSet (f '' s) := by
letI := upgradeStandardBorel X
rw [eq_borel_upgradeStandardBorel X] at hs
rcases hf.exists_continuous with ⟨τ', hle, hfc, hτ'⟩
letI m' : MeasurableSpace X := @borel _ τ'
haveI b' : BorelSpace X := ⟨rfl⟩
have hle := borel_anti hle
exact (hle _ hs).analyticSet.image_of_continuous hfc
#align measurable_set.analytic_set_image MeasurableSet.analyticSet_image
/-- Preimage of an analytic set is an analytic set. -/
protected lemma AnalyticSet.preimage {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y]
[PolishSpace X] [T2Space Y] {s : Set Y} (hs : AnalyticSet s) {f : X → Y} (hf : Continuous f) :
AnalyticSet (f ⁻¹' s) := by
rcases analyticSet_iff_exists_polishSpace_range.1 hs with ⟨Z, _, _, g, hg, rfl⟩
have : IsClosed {x : X × Z | f x.1 = g x.2} := isClosed_diagonal.preimage (hf.prod_map hg)
convert this.analyticSet.image_of_continuous continuous_fst
ext x
simp [eq_comm]
/-! ### Separating sets with measurable sets -/
/-- Two sets `u` and `v` in a measurable space are measurably separable if there
exists a measurable set containing `u` and disjoint from `v`.
This is mostly interesting for Borel-separable sets. -/
def MeasurablySeparable {α : Type*} [MeasurableSpace α] (s t : Set α) : Prop :=
∃ u, s ⊆ u ∧ Disjoint t u ∧ MeasurableSet u
#align measure_theory.measurably_separable MeasureTheory.MeasurablySeparable
theorem MeasurablySeparable.iUnion [Countable ι] {α : Type*} [MeasurableSpace α] {s t : ι → Set α}
(h : ∀ m n, MeasurablySeparable (s m) (t n)) : MeasurablySeparable (⋃ n, s n) (⋃ m, t m) := by
choose u hsu htu hu using h
refine ⟨⋃ m, ⋂ n, u m n, ?_, ?_, ?_⟩
· refine iUnion_subset fun m => subset_iUnion_of_subset m ?_
exact subset_iInter fun n => hsu m n
· simp_rw [disjoint_iUnion_left, disjoint_iUnion_right]
intro n m
apply Disjoint.mono_right _ (htu m n)
apply iInter_subset
· refine MeasurableSet.iUnion fun m => ?_
exact MeasurableSet.iInter fun n => hu m n
#align measure_theory.measurably_separable.Union MeasureTheory.MeasurablySeparable.iUnion
/-- The hard part of the Lusin separation theorem saying that two disjoint analytic sets are
contained in disjoint Borel sets (see the full statement in `AnalyticSet.measurablySeparable`).
Here, we prove this when our analytic sets are the ranges of functions from `ℕ → ℕ`.
-/
theorem measurablySeparable_range_of_disjoint [T2Space α] [MeasurableSpace α]
[OpensMeasurableSpace α] {f g : (ℕ → ℕ) → α} (hf : Continuous f) (hg : Continuous g)
(h : Disjoint (range f) (range g)) : MeasurablySeparable (range f) (range g) := by
/- We follow [Kechris, *Classical Descriptive Set Theory* (Theorem 14.7)][kechris1995].
If the ranges are not Borel-separated, then one can find two cylinders of length one whose
images are not Borel-separated, and then two smaller cylinders of length two whose images are
not Borel-separated, and so on. One thus gets two sequences of cylinders, that decrease to two
points `x` and `y`. Their images are different by the disjointness assumption, hence contained
in two disjoint open sets by the T2 property. By continuity, long enough cylinders around `x`
and `y` have images which are separated by these two disjoint open sets, a contradiction.
-/
by_contra hfg
have I : ∀ n x y, ¬MeasurablySeparable (f '' cylinder x n) (g '' cylinder y n) →
∃ x' y', x' ∈ cylinder x n ∧ y' ∈ cylinder y n ∧
¬MeasurablySeparable (f '' cylinder x' (n + 1)) (g '' cylinder y' (n + 1)) := by
intro n x y
contrapose!
intro H
rw [← iUnion_cylinder_update x n, ← iUnion_cylinder_update y n, image_iUnion, image_iUnion]
refine MeasurablySeparable.iUnion fun i j => ?_
exact H _ _ (update_mem_cylinder _ _ _) (update_mem_cylinder _ _ _)
-- consider the set of pairs of cylinders of some length whose images are not Borel-separated
let A :=
{ p : ℕ × (ℕ → ℕ) × (ℕ → ℕ) //
¬MeasurablySeparable (f '' cylinder p.2.1 p.1) (g '' cylinder p.2.2 p.1) }
-- for each such pair, one can find longer cylinders whose images are not Borel-separated either
have : ∀ p : A, ∃ q : A,
q.1.1 = p.1.1 + 1 ∧ q.1.2.1 ∈ cylinder p.1.2.1 p.1.1 ∧ q.1.2.2 ∈ cylinder p.1.2.2 p.1.1 := by
rintro ⟨⟨n, x, y⟩, hp⟩
rcases I n x y hp with ⟨x', y', hx', hy', h'⟩
exact ⟨⟨⟨n + 1, x', y'⟩, h'⟩, rfl, hx', hy'⟩
choose F hFn hFx hFy using this
let p0 : A := ⟨⟨0, fun _ => 0, fun _ => 0⟩, by simp [hfg]⟩
-- construct inductively decreasing sequences of cylinders whose images are not separated
let p : ℕ → A := fun n => F^[n] p0
have prec : ∀ n, p (n + 1) = F (p n) := fun n => by simp only [p, iterate_succ', Function.comp]
-- check that at the `n`-th step we deal with cylinders of length `n`
have pn_fst : ∀ n, (p n).1.1 = n := by
intro n
induction' n with n IH
· rfl
· simp only [prec, hFn, IH]
-- check that the cylinders we construct are indeed decreasing, by checking that the coordinates
-- are stationary.
have Ix : ∀ m n, m + 1 ≤ n → (p n).1.2.1 m = (p (m + 1)).1.2.1 m := by
intro m
apply Nat.le_induction
· rfl
intro n hmn IH
have I : (F (p n)).val.snd.fst m = (p n).val.snd.fst m := by
apply hFx (p n) m
rw [pn_fst]
exact hmn
rw [prec, I, IH]
have Iy : ∀ m n, m + 1 ≤ n → (p n).1.2.2 m = (p (m + 1)).1.2.2 m := by
intro m
apply Nat.le_induction
· rfl
intro n hmn IH
have I : (F (p n)).val.snd.snd m = (p n).val.snd.snd m := by
apply hFy (p n) m
rw [pn_fst]
exact hmn
rw [prec, I, IH]
-- denote by `x` and `y` the limit points of these two sequences of cylinders.
set x : ℕ → ℕ := fun n => (p (n + 1)).1.2.1 n with hx
set y : ℕ → ℕ := fun n => (p (n + 1)).1.2.2 n with hy
-- by design, the cylinders around these points have images which are not Borel-separable.
have M : ∀ n, ¬MeasurablySeparable (f '' cylinder x n) (g '' cylinder y n) := by
intro n
convert (p n).2 using 3
· rw [pn_fst, ← mem_cylinder_iff_eq, mem_cylinder_iff]
intro i hi
rw [hx]
exact (Ix i n hi).symm
· rw [pn_fst, ← mem_cylinder_iff_eq, mem_cylinder_iff]
intro i hi
rw [hy]
exact (Iy i n hi).symm
-- consider two open sets separating `f x` and `g y`.
obtain ⟨u, v, u_open, v_open, xu, yv, huv⟩ :
∃ u v : Set α, IsOpen u ∧ IsOpen v ∧ f x ∈ u ∧ g y ∈ v ∧ Disjoint u v := by
apply t2_separation
exact disjoint_iff_forall_ne.1 h (mem_range_self _) (mem_range_self _)
letI : MetricSpace (ℕ → ℕ) := metricSpaceNatNat
obtain ⟨εx, εxpos, hεx⟩ : ∃ (εx : ℝ), εx > 0 ∧ Metric.ball x εx ⊆ f ⁻¹' u := by
apply Metric.mem_nhds_iff.1
exact hf.continuousAt.preimage_mem_nhds (u_open.mem_nhds xu)
obtain ⟨εy, εypos, hεy⟩ : ∃ (εy : ℝ), εy > 0 ∧ Metric.ball y εy ⊆ g ⁻¹' v := by
apply Metric.mem_nhds_iff.1
exact hg.continuousAt.preimage_mem_nhds (v_open.mem_nhds yv)
obtain ⟨n, hn⟩ : ∃ n : ℕ, (1 / 2 : ℝ) ^ n < min εx εy :=
exists_pow_lt_of_lt_one (lt_min εxpos εypos) (by norm_num)
-- for large enough `n`, these open sets separate the images of long cylinders around `x` and `y`
have B : MeasurablySeparable (f '' cylinder x n) (g '' cylinder y n) := by
refine ⟨u, ?_, ?_, u_open.measurableSet⟩
· rw [image_subset_iff]
apply Subset.trans _ hεx
intro z hz
rw [mem_cylinder_iff_dist_le] at hz
exact hz.trans_lt (hn.trans_le (min_le_left _ _))
· refine Disjoint.mono_left ?_ huv.symm
change g '' cylinder y n ⊆ v
rw [image_subset_iff]
apply Subset.trans _ hεy
intro z hz
rw [mem_cylinder_iff_dist_le] at hz
exact hz.trans_lt (hn.trans_le (min_le_right _ _))
-- this is a contradiction.
exact M n B
#align measure_theory.measurably_separable_range_of_disjoint MeasureTheory.measurablySeparable_range_of_disjoint
/-- The **Lusin separation theorem**: if two analytic sets are disjoint, then they are contained in
disjoint Borel sets. -/
theorem AnalyticSet.measurablySeparable [T2Space α] [MeasurableSpace α] [OpensMeasurableSpace α]
{s t : Set α} (hs : AnalyticSet s) (ht : AnalyticSet t) (h : Disjoint s t) :
MeasurablySeparable s t := by
rw [AnalyticSet] at hs ht
rcases hs with (rfl | ⟨f, f_cont, rfl⟩)
· refine ⟨∅, Subset.refl _, by simp, MeasurableSet.empty⟩
rcases ht with (rfl | ⟨g, g_cont, rfl⟩)
· exact ⟨univ, subset_univ _, by simp, MeasurableSet.univ⟩
exact measurablySeparable_range_of_disjoint f_cont g_cont h
#align measure_theory.analytic_set.measurably_separable MeasureTheory.AnalyticSet.measurablySeparable
/-- **Suslin's Theorem**: in a Hausdorff topological space, an analytic set with an analytic
complement is measurable. -/
theorem AnalyticSet.measurableSet_of_compl [T2Space α] [MeasurableSpace α] [OpensMeasurableSpace α]
{s : Set α} (hs : AnalyticSet s) (hsc : AnalyticSet sᶜ) : MeasurableSet s := by
rcases hs.measurablySeparable hsc disjoint_compl_right with ⟨u, hsu, hdu, hmu⟩
obtain rfl : s = u := hsu.antisymm (disjoint_compl_left_iff_subset.1 hdu)
exact hmu
#align measure_theory.analytic_set.measurable_set_of_compl MeasureTheory.AnalyticSet.measurableSet_of_compl
end MeasureTheory
/-!
### Measurability of preimages under measurable maps
-/
namespace Measurable
open MeasurableSpace
variable {X Y Z β : Type*} [MeasurableSpace X] [StandardBorelSpace X]
[TopologicalSpace Y] [T0Space Y] [MeasurableSpace Y] [OpensMeasurableSpace Y] [MeasurableSpace β]
[MeasurableSpace Z]
/-- If `f : X → Z` is a surjective Borel measurable map from a standard Borel space
to a countably separated measurable space, then the preimage of a set `s`
is measurable if and only if the set is measurable.
One implication is the definition of measurability, the other one heavily relies on `X` being a
standard Borel space. -/
theorem measurableSet_preimage_iff_of_surjective [CountablySeparated Z]
{f : X → Z} (hf : Measurable f) (hsurj : Surjective f) {s : Set Z} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet s := by
refine ⟨fun h => ?_, fun h => hf h⟩
rcases exists_opensMeasurableSpace_of_countablySeparated Z with ⟨τ, _, _, _⟩
apply AnalyticSet.measurableSet_of_compl
· rw [← image_preimage_eq s hsurj]
exact h.analyticSet_image hf
· rw [← image_preimage_eq sᶜ hsurj]
exact h.compl.analyticSet_image hf
#align measurable.measurable_set_preimage_iff_of_surjective Measurable.measurableSet_preimage_iff_of_surjective
theorem map_measurableSpace_eq [CountablySeparated Z]
{f : X → Z} (hf : Measurable f)
(hsurj : Surjective f) : MeasurableSpace.map f ‹MeasurableSpace X› = ‹MeasurableSpace Z› :=
MeasurableSpace.ext fun _ => hf.measurableSet_preimage_iff_of_surjective hsurj
#align measurable.map_measurable_space_eq Measurable.map_measurableSpace_eq
theorem map_measurableSpace_eq_borel [SecondCountableTopology Y] {f : X → Y} (hf : Measurable f)
(hsurj : Surjective f) : MeasurableSpace.map f ‹MeasurableSpace X› = borel Y := by
have d := hf.mono le_rfl OpensMeasurableSpace.borel_le
letI := borel Y; haveI : BorelSpace Y := ⟨rfl⟩
exact d.map_measurableSpace_eq hsurj
#align measurable.map_measurable_space_eq_borel Measurable.map_measurableSpace_eq_borel
theorem borelSpace_codomain [SecondCountableTopology Y] {f : X → Y} (hf : Measurable f)
(hsurj : Surjective f) : BorelSpace Y :=
⟨(hf.map_measurableSpace_eq hsurj).symm.trans <| hf.map_measurableSpace_eq_borel hsurj⟩
#align measurable.borel_space_codomain Measurable.borelSpace_codomain
/-- If `f : X → Z` is a Borel measurable map from a standard Borel space to a
countably separated measurable space then the preimage of a set `s` is measurable
if and only if the set is measurable in `Set.range f`. -/
theorem measurableSet_preimage_iff_preimage_val {f : X → Z} [CountablySeparated (range f)]
(hf : Measurable f) {s : Set Z} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet ((↑) ⁻¹' s : Set (range f)) :=
have hf' : Measurable (rangeFactorization f) := hf.subtype_mk
hf'.measurableSet_preimage_iff_of_surjective (s := Subtype.val ⁻¹' s) surjective_onto_range
#align measurable.measurable_set_preimage_iff_preimage_coe Measurable.measurableSet_preimage_iff_preimage_val
/-- If `f : X → Z` is a Borel measurable map from a standard Borel space to a
countably separated measurable space and the range of `f` is measurable,
then the preimage of a set `s` is measurable
if and only if the intesection with `Set.range f` is measurable. -/
theorem measurableSet_preimage_iff_inter_range {f : X → Z} [CountablySeparated (range f)]
(hf : Measurable f) (hr : MeasurableSet (range f)) {s : Set Z} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet (s ∩ range f) := by
rw [hf.measurableSet_preimage_iff_preimage_val, inter_comm,
← (MeasurableEmbedding.subtype_coe hr).measurableSet_image, Subtype.image_preimage_coe]
#align measurable.measurable_set_preimage_iff_inter_range Measurable.measurableSet_preimage_iff_inter_range
/-- If `f : X → Z` is a Borel measurable map from a standard Borel space
to a countably separated measurable space,
then for any measurable space `β` and `g : Z → β`, the composition `g ∘ f` is
measurable if and only if the restriction of `g` to the range of `f` is measurable. -/
theorem measurable_comp_iff_restrict {f : X → Z}
[CountablySeparated (range f)]
(hf : Measurable f) {g : Z → β} : Measurable (g ∘ f) ↔ Measurable (restrict (range f) g) :=
forall₂_congr fun s _ => measurableSet_preimage_iff_preimage_val hf (s := g ⁻¹' s)
#align measurable.measurable_comp_iff_restrict Measurable.measurable_comp_iff_restrict
/-- If `f : X → Z` is a surjective Borel measurable map from a standard Borel space
to a countably separated measurable space,
then for any measurable space `α` and `g : Z → α`, the composition
`g ∘ f` is measurable if and only if `g` is measurable. -/
theorem measurable_comp_iff_of_surjective [CountablySeparated Z]
{f : X → Z} (hf : Measurable f) (hsurj : Surjective f)
{g : Z → β} : Measurable (g ∘ f) ↔ Measurable g :=
forall₂_congr fun s _ => measurableSet_preimage_iff_of_surjective hf hsurj (s := g ⁻¹' s)
#align measurable.measurable_comp_iff_of_surjective Measurable.measurable_comp_iff_of_surjective
end Measurable
theorem Continuous.map_eq_borel {X Y : Type*} [TopologicalSpace X] [PolishSpace X]
[MeasurableSpace X] [BorelSpace X] [TopologicalSpace Y] [T0Space Y] [SecondCountableTopology Y]
{f : X → Y} (hf : Continuous f) (hsurj : Surjective f) :
MeasurableSpace.map f ‹MeasurableSpace X› = borel Y := by
borelize Y
exact hf.measurable.map_measurableSpace_eq hsurj
#align continuous.map_eq_borel Continuous.map_eq_borel
theorem Continuous.map_borel_eq {X Y : Type*} [TopologicalSpace X] [PolishSpace X]
[TopologicalSpace Y] [T0Space Y] [SecondCountableTopology Y] {f : X → Y} (hf : Continuous f)
(hsurj : Surjective f) : MeasurableSpace.map f (borel X) = borel Y := by
borelize X
exact hf.map_eq_borel hsurj
#align continuous.map_borel_eq Continuous.map_borel_eq
instance Quotient.borelSpace {X : Type*} [TopologicalSpace X] [PolishSpace X] [MeasurableSpace X]
[BorelSpace X] {s : Setoid X} [T0Space (Quotient s)] [SecondCountableTopology (Quotient s)] :
BorelSpace (Quotient s) :=
⟨continuous_quotient_mk'.map_eq_borel (surjective_quotient_mk' _)⟩
#align quotient.borel_space Quotient.borelSpace
/-- When the subgroup `N < G` is not necessarily `Normal`, we have a `CosetSpace` as opposed
to `QuotientGroup` (the next `instance`).
TODO: typeclass inference should normally find this, but currently doesn't.
E.g., `MeasurableSMul G (G ⧸ Γ)` fails to synthesize, even though `G ⧸ Γ` is the quotient
of `G` by the action of `Γ`; it seems unable to pick up the `BorelSpace` instance. -/
@[to_additive AddCosetSpace.borelSpace]
instance CosetSpace.borelSpace {G : Type*} [TopologicalSpace G] [PolishSpace G] [Group G]
[MeasurableSpace G] [BorelSpace G] {N : Subgroup G} [T2Space (G ⧸ N)]
[SecondCountableTopology (G ⧸ N)] : BorelSpace (G ⧸ N) := Quotient.borelSpace
@[to_additive]
instance QuotientGroup.borelSpace {G : Type*} [TopologicalSpace G] [PolishSpace G] [Group G]
[TopologicalGroup G] [MeasurableSpace G] [BorelSpace G] {N : Subgroup G} [N.Normal]
[IsClosed (N : Set G)] : BorelSpace (G ⧸ N) :=
-- Porting note: 1st and 3rd `haveI`s were not needed in Lean 3
haveI := Subgroup.t3_quotient_of_isClosed N
haveI := QuotientGroup.secondCountableTopology (Γ := N)
Quotient.borelSpace
#align quotient_group.borel_space QuotientGroup.borelSpace
#align quotient_add_group.borel_space QuotientAddGroup.borelSpace
namespace MeasureTheory
/-! ### Injective images of Borel sets -/
variable {γ : Type*}
/-- The **Lusin-Souslin theorem**: the range of a continuous injective function defined on a Polish
space is Borel-measurable. -/
theorem measurableSet_range_of_continuous_injective {β : Type*} [TopologicalSpace γ]
[PolishSpace γ] [TopologicalSpace β] [T2Space β] [MeasurableSpace β] [OpensMeasurableSpace β]
{f : γ → β} (f_cont : Continuous f) (f_inj : Injective f) :
MeasurableSet (range f) := by
/- We follow [Fremlin, *Measure Theory* (volume 4, 423I)][fremlin_vol4].
Let `b = {s i}` be a countable basis for `α`. When `s i` and `s j` are disjoint, their images
are disjoint analytic sets, hence by the separation theorem one can find a Borel-measurable set
`q i j` separating them.
Let `E i = closure (f '' s i) ∩ ⋂ j, q i j \ q j i`. It contains `f '' (s i)` and it is
measurable. Let `F n = ⋃ E i`, where the union is taken over those `i` for which `diam (s i)`
is bounded by some number `u n` tending to `0` with `n`.
We claim that `range f = ⋂ F n`, from which the measurability is obvious. The inclusion `⊆` is
straightforward. To show `⊇`, consider a point `x` in the intersection. For each `n`, it belongs
to some `E i` with `diam (s i) ≤ u n`. Pick a point `y i ∈ s i`. We claim that for such `i`
and `j`, the intersection `s i ∩ s j` is nonempty: if it were empty, then thanks to the
separating set `q i j` in the definition of `E i` one could not have `x ∈ E i ∩ E j`.
Since these two sets have small diameter, it follows that `y i` and `y j` are close.
Thus, `y` is a Cauchy sequence, converging to a limit `z`. We claim that `f z = x`, completing
the proof.
Otherwise, one could find open sets `v` and `w` separating `f z` from `x`. Then, for large `n`,
the image `f '' (s i)` would be included in `v` by continuity of `f`, so its closure would be
contained in the closure of `v`, and therefore it would be disjoint from `w`. This is a
contradiction since `x` belongs both to this closure and to `w`. -/
letI := upgradePolishSpace γ
obtain ⟨b, b_count, b_nonempty, hb⟩ :
∃ b : Set (Set γ), b.Countable ∧ ∅ ∉ b ∧ IsTopologicalBasis b := exists_countable_basis γ
haveI : Encodable b := b_count.toEncodable
let A := { p : b × b // Disjoint (p.1 : Set γ) p.2 }
-- for each pair of disjoint sets in the topological basis `b`, consider Borel sets separating
-- their images, by injectivity of `f` and the Lusin separation theorem.
have : ∀ p : A, ∃ q : Set β,
f '' (p.1.1 : Set γ) ⊆ q ∧ Disjoint (f '' (p.1.2 : Set γ)) q ∧ MeasurableSet q := by
intro p
apply
AnalyticSet.measurablySeparable ((hb.isOpen p.1.1.2).analyticSet_image f_cont)
((hb.isOpen p.1.2.2).analyticSet_image f_cont)
exact Disjoint.image p.2 f_inj.injOn (subset_univ _) (subset_univ _)
choose q hq1 hq2 q_meas using this
-- define sets `E i` and `F n` as in the proof sketch above
let E : b → Set β := fun s =>
closure (f '' s) ∩ ⋂ (t : b) (ht : Disjoint s.1 t.1), q ⟨(s, t), ht⟩ \ q ⟨(t, s), ht.symm⟩
obtain ⟨u, u_anti, u_pos, u_lim⟩ :
∃ u : ℕ → ℝ, StrictAnti u ∧ (∀ n : ℕ, 0 < u n) ∧ Tendsto u atTop (𝓝 0) :=
exists_seq_strictAnti_tendsto (0 : ℝ)
let F : ℕ → Set β := fun n => ⋃ (s : b) (_ : IsBounded s.1 ∧ diam s.1 ≤ u n), E s
-- it is enough to show that `range f = ⋂ F n`, as the latter set is obviously measurable.
suffices range f = ⋂ n, F n by
have E_meas : ∀ s : b, MeasurableSet (E s) := by
intro b
refine isClosed_closure.measurableSet.inter ?_
refine MeasurableSet.iInter fun s => ?_
exact MeasurableSet.iInter fun hs => (q_meas _).diff (q_meas _)
have F_meas : ∀ n, MeasurableSet (F n) := by
intro n
refine MeasurableSet.iUnion fun s => ?_
exact MeasurableSet.iUnion fun _ => E_meas _
rw [this]
exact MeasurableSet.iInter fun n => F_meas n
-- we check both inclusions.
apply Subset.antisymm
-- we start with the easy inclusion `range f ⊆ ⋂ F n`. One just needs to unfold the definitions.
· rintro x ⟨y, rfl⟩
refine mem_iInter.2 fun n => ?_
obtain ⟨s, sb, ys, hs⟩ : ∃ (s : Set γ), s ∈ b ∧ y ∈ s ∧ s ⊆ ball y (u n / 2) := by
apply hb.mem_nhds_iff.1
exact ball_mem_nhds _ (half_pos (u_pos n))
have diam_s : diam s ≤ u n := by
apply (diam_mono hs isBounded_ball).trans
convert diam_ball (x := y) (half_pos (u_pos n)).le
ring
refine mem_iUnion.2 ⟨⟨s, sb⟩, ?_⟩
refine mem_iUnion.2 ⟨⟨isBounded_ball.subset hs, diam_s⟩, ?_⟩
apply mem_inter (subset_closure (mem_image_of_mem _ ys))
refine mem_iInter.2 fun t => mem_iInter.2 fun ht => ⟨?_, ?_⟩
· apply hq1
exact mem_image_of_mem _ ys
· apply disjoint_left.1 (hq2 ⟨(t, ⟨s, sb⟩), ht.symm⟩)
exact mem_image_of_mem _ ys
-- Now, let us prove the harder inclusion `⋂ F n ⊆ range f`.
· intro x hx
-- pick for each `n` a good set `s n` of small diameter for which `x ∈ E (s n)`.
have C1 : ∀ n, ∃ (s : b) (_ : IsBounded s.1 ∧ diam s.1 ≤ u n), x ∈ E s := fun n => by
simpa only [F, mem_iUnion] using mem_iInter.1 hx n
choose s hs hxs using C1
have C2 : ∀ n, (s n).1.Nonempty := by
intro n
rw [nonempty_iff_ne_empty]
intro hn
have := (s n).2
rw [hn] at this
exact b_nonempty this
-- choose a point `y n ∈ s n`.
choose y hy using C2
have I : ∀ m n, ((s m).1 ∩ (s n).1).Nonempty := by
intro m n
rw [← not_disjoint_iff_nonempty_inter]
by_contra! h
have A : x ∈ q ⟨(s m, s n), h⟩ \ q ⟨(s n, s m), h.symm⟩ :=
haveI := mem_iInter.1 (hxs m).2 (s n)
(mem_iInter.1 this h : _)
have B : x ∈ q ⟨(s n, s m), h.symm⟩ \ q ⟨(s m, s n), h⟩ :=
haveI := mem_iInter.1 (hxs n).2 (s m)
(mem_iInter.1 this h.symm : _)
exact A.2 B.1
-- the points `y n` are nearby, and therefore they form a Cauchy sequence.
have cauchy_y : CauchySeq y := by
have : Tendsto (fun n => 2 * u n) atTop (𝓝 0) := by
simpa only [mul_zero] using u_lim.const_mul 2
refine cauchySeq_of_le_tendsto_0' (fun n => 2 * u n) (fun m n hmn => ?_) this
rcases I m n with ⟨z, zsm, zsn⟩
calc
dist (y m) (y n) ≤ dist (y m) z + dist z (y n) := dist_triangle _ _ _
_ ≤ u m + u n :=
(add_le_add ((dist_le_diam_of_mem (hs m).1 (hy m) zsm).trans (hs m).2)
((dist_le_diam_of_mem (hs n).1 zsn (hy n)).trans (hs n).2))
_ ≤ 2 * u m := by linarith [u_anti.antitone hmn]
haveI : Nonempty γ := ⟨y 0⟩
-- let `z` be its limit.
let z := limUnder atTop y
have y_lim : Tendsto y atTop (𝓝 z) := cauchy_y.tendsto_limUnder
suffices f z = x by
rw [← this]
exact mem_range_self _
-- assume for a contradiction that `f z ≠ x`.
by_contra! hne
-- introduce disjoint open sets `v` and `w` separating `f z` from `x`.
obtain ⟨v, w, v_open, w_open, fzv, xw, hvw⟩ := t2_separation hne
obtain ⟨δ, δpos, hδ⟩ : ∃ δ > (0 : ℝ), ball z δ ⊆ f ⁻¹' v := by
apply Metric.mem_nhds_iff.1
exact f_cont.continuousAt.preimage_mem_nhds (v_open.mem_nhds fzv)
obtain ⟨n, hn⟩ : ∃ n, u n + dist (y n) z < δ :=
haveI : Tendsto (fun n => u n + dist (y n) z) atTop (𝓝 0) := by
simpa only [add_zero] using u_lim.add (tendsto_iff_dist_tendsto_zero.1 y_lim)
((tendsto_order.1 this).2 _ δpos).exists
-- for large enough `n`, the image of `s n` is contained in `v`, by continuity of `f`.
have fsnv : f '' s n ⊆ v := by
rw [image_subset_iff]
apply Subset.trans _ hδ
intro a ha
calc
dist a z ≤ dist a (y n) + dist (y n) z := dist_triangle _ _ _
_ ≤ u n + dist (y n) z :=
(add_le_add_right ((dist_le_diam_of_mem (hs n).1 ha (hy n)).trans (hs n).2) _)
_ < δ := hn
-- as `x` belongs to the closure of `f '' (s n)`, it belongs to the closure of `v`.
have : x ∈ closure v := closure_mono fsnv (hxs n).1
-- this is a contradiction, as `x` is supposed to belong to `w`, which is disjoint from
-- the closure of `v`.
exact disjoint_left.1 (hvw.closure_left w_open) this xw
#align measure_theory.measurable_set_range_of_continuous_injective MeasureTheory.measurableSet_range_of_continuous_injective
theorem _root_.IsClosed.measurableSet_image_of_continuousOn_injOn
[TopologicalSpace γ] [PolishSpace γ] {β : Type*} [TopologicalSpace β] [T2Space β]
[MeasurableSpace β] [OpensMeasurableSpace β] {s : Set γ} (hs : IsClosed s) {f : γ → β}
(f_cont : ContinuousOn f s) (f_inj : InjOn f s) : MeasurableSet (f '' s) := by
rw [image_eq_range]
haveI : PolishSpace s := IsClosed.polishSpace hs
apply measurableSet_range_of_continuous_injective
· rwa [continuousOn_iff_continuous_restrict] at f_cont
· rwa [injOn_iff_injective] at f_inj
#align is_closed.measurable_set_image_of_continuous_on_inj_on IsClosed.measurableSet_image_of_continuousOn_injOn
variable {α β : Type*} [tβ : TopologicalSpace β] [T2Space β] [MeasurableSpace β]
[MeasurableSpace α]
{s : Set γ} {f : γ → β}
/-- The Lusin-Souslin theorem: if `s` is Borel-measurable in a Polish space, then its image under
a continuous injective map is also Borel-measurable. -/
| Mathlib/MeasureTheory/Constructions/Polish.lean | 839 | 848 | theorem _root_.MeasurableSet.image_of_continuousOn_injOn [OpensMeasurableSpace β]
[tγ : TopologicalSpace γ] [PolishSpace γ] [MeasurableSpace γ] [BorelSpace γ]
(hs : MeasurableSet s)
(f_cont : ContinuousOn f s) (f_inj : InjOn f s) : MeasurableSet (f '' s) := by |
obtain ⟨t', t't, t'_polish, s_closed, _⟩ :
∃ t' : TopologicalSpace γ, t' ≤ tγ ∧ @PolishSpace γ t' ∧ IsClosed[t'] s ∧ IsOpen[t'] s :=
hs.isClopenable
exact
@IsClosed.measurableSet_image_of_continuousOn_injOn γ t' t'_polish β _ _ _ _ s s_closed f
(f_cont.mono_dom t't) f_inj
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.MvPolynomial.Basic
#align_import data.mv_polynomial.rename from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Renaming variables of polynomials
This file establishes the `rename` operation on multivariate polynomials,
which modifies the set of variables.
## Main declarations
* `MvPolynomial.rename`
* `MvPolynomial.renameEquiv`
## Notation
As in other polynomial files, we typically use the notation:
+ `σ τ α : Type*` (indexing the variables)
+ `R S : Type*` `[CommSemiring R]` `[CommSemiring S]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `r : R` elements of the coefficient ring
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ α`
-/
noncomputable section
open Set Function Finsupp AddMonoidAlgebra
variable {σ τ α R S : Type*} [CommSemiring R] [CommSemiring S]
namespace MvPolynomial
section Rename
/-- Rename all the variables in a multivariable polynomial. -/
def rename (f : σ → τ) : MvPolynomial σ R →ₐ[R] MvPolynomial τ R :=
aeval (X ∘ f)
#align mv_polynomial.rename MvPolynomial.rename
theorem rename_C (f : σ → τ) (r : R) : rename f (C r) = C r :=
eval₂_C _ _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.rename_C MvPolynomial.rename_C
@[simp]
theorem rename_X (f : σ → τ) (i : σ) : rename f (X i : MvPolynomial σ R) = X (f i) :=
eval₂_X _ _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.rename_X MvPolynomial.rename_X
theorem map_rename (f : R →+* S) (g : σ → τ) (p : MvPolynomial σ R) :
map f (rename g p) = rename g (map f p) := by
apply MvPolynomial.induction_on p
(fun a => by simp only [map_C, rename_C])
(fun p q hp hq => by simp only [hp, hq, AlgHom.map_add, RingHom.map_add]) fun p n hp => by
simp only [hp, rename_X, map_X, RingHom.map_mul, AlgHom.map_mul]
#align mv_polynomial.map_rename MvPolynomial.map_rename
@[simp]
theorem rename_rename (f : σ → τ) (g : τ → α) (p : MvPolynomial σ R) :
rename g (rename f p) = rename (g ∘ f) p :=
show rename g (eval₂ C (X ∘ f) p) = _ by
simp only [rename, aeval_eq_eval₂Hom]
-- Porting note: the Lean 3 proof of this was very fragile and included a nonterminal `simp`.
-- Hopefully this is less prone to breaking
rw [eval₂_comp_left (eval₂Hom (algebraMap R (MvPolynomial α R)) (X ∘ g)) C (X ∘ f) p]
simp only [(· ∘ ·), eval₂Hom_X']
refine eval₂Hom_congr ?_ rfl rfl
ext1; simp only [comp_apply, RingHom.coe_comp, eval₂Hom_C]
#align mv_polynomial.rename_rename MvPolynomial.rename_rename
@[simp]
theorem rename_id (p : MvPolynomial σ R) : rename id p = p :=
eval₂_eta p
#align mv_polynomial.rename_id MvPolynomial.rename_id
theorem rename_monomial (f : σ → τ) (d : σ →₀ ℕ) (r : R) :
rename f (monomial d r) = monomial (d.mapDomain f) r := by
rw [rename, aeval_monomial, monomial_eq (s := Finsupp.mapDomain f d),
Finsupp.prod_mapDomain_index]
· rfl
· exact fun n => pow_zero _
· exact fun n i₁ i₂ => pow_add _ _ _
#align mv_polynomial.rename_monomial MvPolynomial.rename_monomial
theorem rename_eq (f : σ → τ) (p : MvPolynomial σ R) :
rename f p = Finsupp.mapDomain (Finsupp.mapDomain f) p := by
simp only [rename, aeval_def, eval₂, Finsupp.mapDomain, algebraMap_eq, comp_apply,
X_pow_eq_monomial, ← monomial_finsupp_sum_index]
rfl
#align mv_polynomial.rename_eq MvPolynomial.rename_eq
theorem rename_injective (f : σ → τ) (hf : Function.Injective f) :
Function.Injective (rename f : MvPolynomial σ R → MvPolynomial τ R) := by
have :
(rename f : MvPolynomial σ R → MvPolynomial τ R) = Finsupp.mapDomain (Finsupp.mapDomain f) :=
funext (rename_eq f)
rw [this]
exact Finsupp.mapDomain_injective (Finsupp.mapDomain_injective hf)
#align mv_polynomial.rename_injective MvPolynomial.rename_injective
section
variable {f : σ → τ} (hf : Function.Injective f)
open scoped Classical
/-- Given a function between sets of variables `f : σ → τ` that is injective with proof `hf`,
`MvPolynomial.killCompl hf` is the `AlgHom` from `R[τ]` to `R[σ]` that is left inverse to
`rename f : R[σ] → R[τ]` and sends the variables in the complement of the range of `f` to `0`. -/
def killCompl : MvPolynomial τ R →ₐ[R] MvPolynomial σ R :=
aeval fun i => if h : i ∈ Set.range f then X <| (Equiv.ofInjective f hf).symm ⟨i, h⟩ else 0
#align mv_polynomial.kill_compl MvPolynomial.killCompl
theorem killCompl_C (r : R) : killCompl hf (C r) = C r := algHom_C _ _
theorem killCompl_comp_rename : (killCompl hf).comp (rename f) = AlgHom.id R _ :=
algHom_ext fun i => by
dsimp
rw [rename, killCompl, aeval_X, comp_apply, aeval_X, dif_pos, Equiv.ofInjective_symm_apply]
#align mv_polynomial.kill_compl_comp_rename MvPolynomial.killCompl_comp_rename
@[simp]
theorem killCompl_rename_app (p : MvPolynomial σ R) : killCompl hf (rename f p) = p :=
AlgHom.congr_fun (killCompl_comp_rename hf) p
#align mv_polynomial.kill_compl_rename_app MvPolynomial.killCompl_rename_app
end
section
variable (R)
/-- `MvPolynomial.rename e` is an equivalence when `e` is. -/
@[simps apply]
def renameEquiv (f : σ ≃ τ) : MvPolynomial σ R ≃ₐ[R] MvPolynomial τ R :=
{ rename f with
toFun := rename f
invFun := rename f.symm
left_inv := fun p => by rw [rename_rename, f.symm_comp_self, rename_id]
right_inv := fun p => by rw [rename_rename, f.self_comp_symm, rename_id] }
#align mv_polynomial.rename_equiv MvPolynomial.renameEquiv
@[simp]
theorem renameEquiv_refl : renameEquiv R (Equiv.refl σ) = AlgEquiv.refl :=
AlgEquiv.ext rename_id
#align mv_polynomial.rename_equiv_refl MvPolynomial.renameEquiv_refl
@[simp]
theorem renameEquiv_symm (f : σ ≃ τ) : (renameEquiv R f).symm = renameEquiv R f.symm :=
rfl
#align mv_polynomial.rename_equiv_symm MvPolynomial.renameEquiv_symm
@[simp]
theorem renameEquiv_trans (e : σ ≃ τ) (f : τ ≃ α) :
(renameEquiv R e).trans (renameEquiv R f) = renameEquiv R (e.trans f) :=
AlgEquiv.ext (rename_rename e f)
#align mv_polynomial.rename_equiv_trans MvPolynomial.renameEquiv_trans
end
section
variable (f : R →+* S) (k : σ → τ) (g : τ → S) (p : MvPolynomial σ R)
theorem eval₂_rename : (rename k p).eval₂ f g = p.eval₂ f (g ∘ k) := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
#align mv_polynomial.eval₂_rename MvPolynomial.eval₂_rename
theorem eval_rename (g : τ → R) (p : MvPolynomial σ R) : eval g (rename k p) = eval (g ∘ k) p :=
eval₂_rename _ _ _ _
theorem eval₂Hom_rename : eval₂Hom f g (rename k p) = eval₂Hom f (g ∘ k) p :=
eval₂_rename _ _ _ _
#align mv_polynomial.eval₂_hom_rename MvPolynomial.eval₂Hom_rename
theorem aeval_rename [Algebra R S] : aeval g (rename k p) = aeval (g ∘ k) p :=
eval₂Hom_rename _ _ _ _
#align mv_polynomial.aeval_rename MvPolynomial.aeval_rename
theorem rename_eval₂ (g : τ → MvPolynomial σ R) :
rename k (p.eval₂ C (g ∘ k)) = (rename k p).eval₂ C (rename k ∘ g) := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
#align mv_polynomial.rename_eval₂ MvPolynomial.rename_eval₂
theorem rename_prod_mk_eval₂ (j : τ) (g : σ → MvPolynomial σ R) :
rename (Prod.mk j) (p.eval₂ C g) = p.eval₂ C fun x => rename (Prod.mk j) (g x) := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
#align mv_polynomial.rename_prodmk_eval₂ MvPolynomial.rename_prod_mk_eval₂
theorem eval₂_rename_prod_mk (g : σ × τ → S) (i : σ) (p : MvPolynomial τ R) :
(rename (Prod.mk i) p).eval₂ f g = eval₂ f (fun j => g (i, j)) p := by
apply MvPolynomial.induction_on p <;>
· intros
simp [*]
#align mv_polynomial.eval₂_rename_prodmk MvPolynomial.eval₂_rename_prod_mk
theorem eval_rename_prod_mk (g : σ × τ → R) (i : σ) (p : MvPolynomial τ R) :
eval g (rename (Prod.mk i) p) = eval (fun j => g (i, j)) p :=
eval₂_rename_prod_mk (RingHom.id _) _ _ _
#align mv_polynomial.eval_rename_prodmk MvPolynomial.eval_rename_prod_mk
end
/-- Every polynomial is a polynomial in finitely many variables. -/
theorem exists_finset_rename (p : MvPolynomial σ R) :
∃ (s : Finset σ) (q : MvPolynomial { x // x ∈ s } R), p = rename (↑) q := by
classical
apply induction_on p
· intro r
exact ⟨∅, C r, by rw [rename_C]⟩
· rintro p q ⟨s, p, rfl⟩ ⟨t, q, rfl⟩
refine ⟨s ∪ t, ⟨?_, ?_⟩⟩
· refine rename (Subtype.map id ?_) p + rename (Subtype.map id ?_) q <;>
simp (config := { contextual := true }) only [id, true_or_iff, or_true_iff,
Finset.mem_union, forall_true_iff]
· simp only [rename_rename, AlgHom.map_add]
rfl
· rintro p n ⟨s, p, rfl⟩
refine ⟨insert n s, ⟨?_, ?_⟩⟩
· refine rename (Subtype.map id ?_) p * X ⟨n, s.mem_insert_self n⟩
simp (config := { contextual := true }) only [id, or_true_iff, Finset.mem_insert,
forall_true_iff]
· simp only [rename_rename, rename_X, Subtype.coe_mk, AlgHom.map_mul]
rfl
#align mv_polynomial.exists_finset_rename MvPolynomial.exists_finset_rename
/-- `exists_finset_rename` for two polynomials at once: for any two polynomials `p₁`, `p₂` in a
polynomial semiring `R[σ]` of possibly infinitely many variables, `exists_finset_rename₂` yields
a finite subset `s` of `σ` such that both `p₁` and `p₂` are contained in the polynomial semiring
`R[s]` of finitely many variables. -/
theorem exists_finset_rename₂ (p₁ p₂ : MvPolynomial σ R) :
∃ (s : Finset σ) (q₁ q₂ : MvPolynomial s R), p₁ = rename (↑) q₁ ∧ p₂ = rename (↑) q₂ := by
obtain ⟨s₁, q₁, rfl⟩ := exists_finset_rename p₁
obtain ⟨s₂, q₂, rfl⟩ := exists_finset_rename p₂
classical
use s₁ ∪ s₂
use rename (Set.inclusion s₁.subset_union_left) q₁
use rename (Set.inclusion s₁.subset_union_right) q₂
constructor -- Porting note: was `<;> simp <;> rfl` but Lean couldn't infer the arguments
· -- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [rename_rename (Set.inclusion s₁.subset_union_left)]
rfl
· -- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [rename_rename (Set.inclusion s₁.subset_union_right)]
rfl
#align mv_polynomial.exists_finset_rename₂ MvPolynomial.exists_finset_rename₂
/-- Every polynomial is a polynomial in finitely many variables. -/
theorem exists_fin_rename (p : MvPolynomial σ R) :
∃ (n : ℕ) (f : Fin n → σ) (_hf : Injective f) (q : MvPolynomial (Fin n) R), p = rename f q := by
obtain ⟨s, q, rfl⟩ := exists_finset_rename p
let n := Fintype.card { x // x ∈ s }
let e := Fintype.equivFin { x // x ∈ s }
refine ⟨n, (↑) ∘ e.symm, Subtype.val_injective.comp e.symm.injective, rename e q, ?_⟩
rw [← rename_rename, rename_rename e]
simp only [Function.comp, Equiv.symm_apply_apply, rename_rename]
#align mv_polynomial.exists_fin_rename MvPolynomial.exists_fin_rename
end Rename
| Mathlib/Algebra/MvPolynomial/Rename.lean | 284 | 288 | theorem eval₂_cast_comp (f : σ → τ) (c : ℤ →+* R) (g : τ → R) (p : MvPolynomial σ ℤ) :
eval₂ c (g ∘ f) p = eval₂ c g (rename f p) := by |
apply MvPolynomial.induction_on p (fun n => by simp only [eval₂_C, rename_C])
(fun p q hp hq => by simp only [hp, hq, rename, eval₂_add, AlgHom.map_add])
fun p n hp => by simp only [eval₂_mul, hp, eval₂_X, comp_apply, map_mul, rename_X, eval₂_mul]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Topology.Algebra.InfiniteSum.Group
import Mathlib.Logic.Encodable.Lattice
/-!
# Infinite sums and products over `ℕ` and `ℤ`
This file contains lemmas about `HasSum`, `Summable`, `tsum`, `HasProd`, `Multipliable`, and `tprod`
applied to the important special cases where the domain is `ℕ` or `ℤ`. For instance, we prove the
formula `∑ i ∈ range k, f i + ∑' i, f (i + k) = ∑' i, f i`, ∈ `sum_add_tsum_nat_add`, as well as
several results relating sums and products on `ℕ` to sums and products on `ℤ`.
-/
noncomputable section
open Filter Finset Function Encodable
open scoped Topology
variable {M : Type*} [CommMonoid M] [TopologicalSpace M] {m m' : M}
variable {G : Type*} [CommGroup G] {g g' : G}
-- don't declare [TopologicalAddGroup G] here as some results require [UniformAddGroup G] instead
/-!
## Sums over `ℕ`
-/
section Nat
section Monoid
namespace HasProd
/-- If `f : ℕ → M` has product `m`, then the partial products `∏ i ∈ range n, f i` converge
to `m`. -/
@[to_additive "If `f : ℕ → M` has sum `m`, then the partial sums `∑ i ∈ range n, f i` converge
to `m`."]
theorem tendsto_prod_nat {f : ℕ → M} (h : HasProd f m) :
Tendsto (fun n ↦ ∏ i ∈ range n, f i) atTop (𝓝 m) :=
h.comp tendsto_finset_range
#align has_sum.tendsto_sum_nat HasSum.tendsto_sum_nat
/-- If `f : ℕ → M` is multipliable, then the partial products `∏ i ∈ range n, f i` converge
to `∏' i, f i`. -/
@[to_additive "If `f : ℕ → M` is summable, then the partial sums `∑ i ∈ range n, f i` converge
to `∑' i, f i`."]
theorem Multipliable.tendsto_prod_tprod_nat {f : ℕ → M} (h : Multipliable f) :
Tendsto (fun n ↦ ∏ i ∈ range n, f i) atTop (𝓝 (∏' i, f i)) :=
tendsto_prod_nat h.hasProd
section ContinuousMul
variable [ContinuousMul M]
@[to_additive]
theorem prod_range_mul {f : ℕ → M} {k : ℕ} (h : HasProd (fun n ↦ f (n + k)) m) :
HasProd f ((∏ i ∈ range k, f i) * m) := by
refine ((range k).hasProd f).mul_compl ?_
rwa [← (notMemRangeEquiv k).symm.hasProd_iff]
@[to_additive]
theorem zero_mul {f : ℕ → M} (h : HasProd (fun n ↦ f (n + 1)) m) :
HasProd f (f 0 * m) := by
simpa only [prod_range_one] using h.prod_range_mul
@[to_additive]
theorem even_mul_odd {f : ℕ → M} (he : HasProd (fun k ↦ f (2 * k)) m)
(ho : HasProd (fun k ↦ f (2 * k + 1)) m') : HasProd f (m * m') := by
have := mul_right_injective₀ (two_ne_zero' ℕ)
replace ho := ((add_left_injective 1).comp this).hasProd_range_iff.2 ho
refine (this.hasProd_range_iff.2 he).mul_isCompl ?_ ho
simpa [(· ∘ ·)] using Nat.isCompl_even_odd
#align has_sum.even_add_odd HasSum.even_add_odd
end ContinuousMul
end HasProd
namespace Multipliable
@[to_additive]
theorem hasProd_iff_tendsto_nat [T2Space M] {f : ℕ → M} (hf : Multipliable f) :
HasProd f m ↔ Tendsto (fun n : ℕ ↦ ∏ i ∈ range n, f i) atTop (𝓝 m) := by
refine ⟨fun h ↦ h.tendsto_prod_nat, fun h ↦ ?_⟩
rw [tendsto_nhds_unique h hf.hasProd.tendsto_prod_nat]
exact hf.hasProd
#align summable.has_sum_iff_tendsto_nat Summable.hasSum_iff_tendsto_nat
section ContinuousMul
variable [ContinuousMul M]
@[to_additive]
theorem comp_nat_add {f : ℕ → M} {k : ℕ} (h : Multipliable fun n ↦ f (n + k)) : Multipliable f :=
h.hasProd.prod_range_mul.multipliable
@[to_additive]
theorem even_mul_odd {f : ℕ → M} (he : Multipliable fun k ↦ f (2 * k))
(ho : Multipliable fun k ↦ f (2 * k + 1)) : Multipliable f :=
(he.hasProd.even_mul_odd ho.hasProd).multipliable
end ContinuousMul
end Multipliable
section tprod
variable [T2Space M] {α β γ : Type*}
section Encodable
variable [Encodable β]
/-- You can compute a product over an encodable type by multiplying over the natural numbers and
taking a supremum. -/
@[to_additive "You can compute a sum over an encodable type by summing over the natural numbers and
taking a supremum. This is useful for outer measures."]
theorem tprod_iSup_decode₂ [CompleteLattice α] (m : α → M) (m0 : m ⊥ = 1) (s : β → α) :
∏' i : ℕ, m (⨆ b ∈ decode₂ β i, s b) = ∏' b : β, m (s b) := by
rw [← tprod_extend_one (@encode_injective β _)]
refine tprod_congr fun n ↦ ?_
rcases em (n ∈ Set.range (encode : β → ℕ)) with ⟨a, rfl⟩ | hn
· simp [encode_injective.extend_apply]
· rw [extend_apply' _ _ _ hn]
rw [← decode₂_ne_none_iff, ne_eq, not_not] at hn
simp [hn, m0]
#align tsum_supr_decode₂ tsum_iSup_decode₂
/-- `tprod_iSup_decode₂` specialized to the complete lattice of sets. -/
@[to_additive "`tsum_iSup_decode₂` specialized to the complete lattice of sets."]
theorem tprod_iUnion_decode₂ (m : Set α → M) (m0 : m ∅ = 1) (s : β → Set α) :
∏' i, m (⋃ b ∈ decode₂ β i, s b) = ∏' b, m (s b) :=
tprod_iSup_decode₂ m m0 s
#align tsum_Union_decode₂ tsum_iUnion_decode₂
end Encodable
/-! Some properties about measure-like functions. These could also be functions defined on complete
sublattices of sets, with the property that they are countably sub-additive.
`R` will probably be instantiated with `(≤)` in all applications.
-/
section Countable
variable [Countable β]
/-- If a function is countably sub-multiplicative then it is sub-multiplicative on countable
types -/
@[to_additive "If a function is countably sub-additive then it is sub-additive on countable types"]
| Mathlib/Topology/Algebra/InfiniteSum/NatInt.lean | 155 | 160 | theorem rel_iSup_tprod [CompleteLattice α] (m : α → M) (m0 : m ⊥ = 1) (R : M → M → Prop)
(m_iSup : ∀ s : ℕ → α, R (m (⨆ i, s i)) (∏' i, m (s i))) (s : β → α) :
R (m (⨆ b : β, s b)) (∏' b : β, m (s b)) := by |
cases nonempty_encodable β
rw [← iSup_decode₂, ← tprod_iSup_decode₂ _ m0 s]
exact m_iSup _
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.Algebra.MvPolynomial.PDeriv
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Derivative
import Mathlib.Data.Nat.Choose.Sum
import Mathlib.LinearAlgebra.LinearIndependent
import Mathlib.RingTheory.Polynomial.Pochhammer
#align_import ring_theory.polynomial.bernstein from "leanprover-community/mathlib"@"bbeb185db4ccee8ed07dc48449414ebfa39cb821"
/-!
# Bernstein polynomials
The definition of the Bernstein polynomials
```
bernsteinPolynomial (R : Type*) [CommRing R] (n ν : ℕ) : R[X] :=
(choose n ν) * X^ν * (1 - X)^(n - ν)
```
and the fact that for `ν : fin (n+1)` these are linearly independent over `ℚ`.
We prove the basic identities
* `(Finset.range (n + 1)).sum (fun ν ↦ bernsteinPolynomial R n ν) = 1`
* `(Finset.range (n + 1)).sum (fun ν ↦ ν • bernsteinPolynomial R n ν) = n • X`
* `(Finset.range (n + 1)).sum (fun ν ↦ (ν * (ν-1)) • bernsteinPolynomial R n ν) = (n * (n-1)) • X^2`
## Notes
See also `Mathlib.Analysis.SpecialFunctions.Bernstein`, which defines the Bernstein approximations
of a continuous function `f : C([0,1], ℝ)`, and shows that these converge uniformly to `f`.
-/
noncomputable section
open Nat (choose)
open Polynomial (X)
open scoped Polynomial
variable (R : Type*) [CommRing R]
/-- `bernsteinPolynomial R n ν` is `(choose n ν) * X^ν * (1 - X)^(n - ν)`.
Although the coefficients are integers, it is convenient to work over an arbitrary commutative ring.
-/
def bernsteinPolynomial (n ν : ℕ) : R[X] :=
(choose n ν : R[X]) * X ^ ν * (1 - X) ^ (n - ν)
#align bernstein_polynomial bernsteinPolynomial
example : bernsteinPolynomial ℤ 3 2 = 3 * X ^ 2 - 3 * X ^ 3 := by
norm_num [bernsteinPolynomial, choose]
ring
namespace bernsteinPolynomial
theorem eq_zero_of_lt {n ν : ℕ} (h : n < ν) : bernsteinPolynomial R n ν = 0 := by
simp [bernsteinPolynomial, Nat.choose_eq_zero_of_lt h]
#align bernstein_polynomial.eq_zero_of_lt bernsteinPolynomial.eq_zero_of_lt
section
variable {R} {S : Type*} [CommRing S]
@[simp]
theorem map (f : R →+* S) (n ν : ℕ) :
(bernsteinPolynomial R n ν).map f = bernsteinPolynomial S n ν := by simp [bernsteinPolynomial]
#align bernstein_polynomial.map bernsteinPolynomial.map
end
theorem flip (n ν : ℕ) (h : ν ≤ n) :
(bernsteinPolynomial R n ν).comp (1 - X) = bernsteinPolynomial R n (n - ν) := by
simp [bernsteinPolynomial, h, tsub_tsub_assoc, mul_right_comm]
#align bernstein_polynomial.flip bernsteinPolynomial.flip
theorem flip' (n ν : ℕ) (h : ν ≤ n) :
bernsteinPolynomial R n ν = (bernsteinPolynomial R n (n - ν)).comp (1 - X) := by
simp [← flip _ _ _ h, Polynomial.comp_assoc]
#align bernstein_polynomial.flip' bernsteinPolynomial.flip'
theorem eval_at_0 (n ν : ℕ) : (bernsteinPolynomial R n ν).eval 0 = if ν = 0 then 1 else 0 := by
rw [bernsteinPolynomial]
split_ifs with h
· subst h; simp
· simp [zero_pow h]
#align bernstein_polynomial.eval_at_0 bernsteinPolynomial.eval_at_0
theorem eval_at_1 (n ν : ℕ) : (bernsteinPolynomial R n ν).eval 1 = if ν = n then 1 else 0 := by
rw [bernsteinPolynomial]
split_ifs with h
· subst h; simp
· obtain hνn | hnν := Ne.lt_or_lt h
· simp [zero_pow $ Nat.sub_ne_zero_of_lt hνn]
· simp [Nat.choose_eq_zero_of_lt hnν]
#align bernstein_polynomial.eval_at_1 bernsteinPolynomial.eval_at_1
theorem derivative_succ_aux (n ν : ℕ) :
Polynomial.derivative (bernsteinPolynomial R (n + 1) (ν + 1)) =
(n + 1) * (bernsteinPolynomial R n ν - bernsteinPolynomial R n (ν + 1)) := by
rw [bernsteinPolynomial]
suffices ((n + 1).choose (ν + 1) : R[X]) * ((↑(ν + 1 : ℕ) : R[X]) * X ^ ν) * (1 - X) ^ (n - ν) -
((n + 1).choose (ν + 1) : R[X]) * X ^ (ν + 1) * ((↑(n - ν) : R[X]) * (1 - X) ^ (n - ν - 1)) =
(↑(n + 1) : R[X]) * ((n.choose ν : R[X]) * X ^ ν * (1 - X) ^ (n - ν) -
(n.choose (ν + 1) : R[X]) * X ^ (ν + 1) * (1 - X) ^ (n - (ν + 1))) by
simpa [Polynomial.derivative_pow, ← sub_eq_add_neg, Nat.succ_sub_succ_eq_sub,
Polynomial.derivative_mul, Polynomial.derivative_natCast, zero_mul,
Nat.cast_add, algebraMap.coe_one, Polynomial.derivative_X, mul_one, zero_add,
Polynomial.derivative_sub, Polynomial.derivative_one, zero_sub, mul_neg, Nat.sub_zero,
bernsteinPolynomial, map_add, map_natCast, Nat.cast_one]
conv_rhs => rw [mul_sub]
-- We'll prove the two terms match up separately.
refine congr (congr_arg Sub.sub ?_) ?_
· simp only [← mul_assoc]
apply congr (congr_arg (· * ·) (congr (congr_arg (· * ·) _) rfl)) rfl
-- Now it's just about binomial coefficients
exact mod_cast congr_arg (fun m : ℕ => (m : R[X])) (Nat.succ_mul_choose_eq n ν).symm
· rw [← tsub_add_eq_tsub_tsub, ← mul_assoc, ← mul_assoc]; congr 1
rw [mul_comm, ← mul_assoc, ← mul_assoc]; congr 1
norm_cast
congr 1
convert (Nat.choose_mul_succ_eq n (ν + 1)).symm using 1
· -- Porting note: was
-- convert mul_comm _ _ using 2
-- simp
rw [mul_comm, Nat.succ_sub_succ_eq_sub]
· apply mul_comm
#align bernstein_polynomial.derivative_succ_aux bernsteinPolynomial.derivative_succ_aux
theorem derivative_succ (n ν : ℕ) : Polynomial.derivative (bernsteinPolynomial R n (ν + 1)) =
n * (bernsteinPolynomial R (n - 1) ν - bernsteinPolynomial R (n - 1) (ν + 1)) := by
cases n
· simp [bernsteinPolynomial]
· rw [Nat.cast_succ]; apply derivative_succ_aux
#align bernstein_polynomial.derivative_succ bernsteinPolynomial.derivative_succ
theorem derivative_zero (n : ℕ) :
Polynomial.derivative (bernsteinPolynomial R n 0) = -n * bernsteinPolynomial R (n - 1) 0 := by
simp [bernsteinPolynomial, Polynomial.derivative_pow]
#align bernstein_polynomial.derivative_zero bernsteinPolynomial.derivative_zero
theorem iterate_derivative_at_0_eq_zero_of_lt (n : ℕ) {ν k : ℕ} :
k < ν → (Polynomial.derivative^[k] (bernsteinPolynomial R n ν)).eval 0 = 0 := by
cases' ν with ν
· rintro ⟨⟩
· rw [Nat.lt_succ_iff]
induction' k with k ih generalizing n ν
· simp [eval_at_0]
· simp only [derivative_succ, Int.natCast_eq_zero, mul_eq_zero, Function.comp_apply,
Function.iterate_succ, Polynomial.iterate_derivative_sub,
Polynomial.iterate_derivative_natCast_mul, Polynomial.eval_mul, Polynomial.eval_natCast,
Polynomial.eval_sub]
intro h
apply mul_eq_zero_of_right
rw [ih _ _ (Nat.le_of_succ_le h), sub_zero]
convert ih _ _ (Nat.pred_le_pred h)
exact (Nat.succ_pred_eq_of_pos (k.succ_pos.trans_le h)).symm
#align bernstein_polynomial.iterate_derivative_at_0_eq_zero_of_lt bernsteinPolynomial.iterate_derivative_at_0_eq_zero_of_lt
@[simp]
theorem iterate_derivative_succ_at_0_eq_zero (n ν : ℕ) :
(Polynomial.derivative^[ν] (bernsteinPolynomial R n (ν + 1))).eval 0 = 0 :=
iterate_derivative_at_0_eq_zero_of_lt R n (lt_add_one ν)
#align bernstein_polynomial.iterate_derivative_succ_at_0_eq_zero bernsteinPolynomial.iterate_derivative_succ_at_0_eq_zero
open Polynomial
@[simp]
theorem iterate_derivative_at_0 (n ν : ℕ) :
(Polynomial.derivative^[ν] (bernsteinPolynomial R n ν)).eval 0 =
(ascPochhammer R ν).eval ((n - (ν - 1) : ℕ) : R) := by
by_cases h : ν ≤ n
· induction' ν with ν ih generalizing n
· simp [eval_at_0]
· have h' : ν ≤ n - 1 := le_tsub_of_add_le_right h
simp only [derivative_succ, ih (n - 1) h', iterate_derivative_succ_at_0_eq_zero,
Nat.succ_sub_succ_eq_sub, tsub_zero, sub_zero, iterate_derivative_sub,
iterate_derivative_natCast_mul, eval_one, eval_mul, eval_add, eval_sub, eval_X, eval_comp,
eval_natCast, Function.comp_apply, Function.iterate_succ, ascPochhammer_succ_left]
obtain rfl | h'' := ν.eq_zero_or_pos
· simp
· have : n - 1 - (ν - 1) = n - ν := by
rw [gt_iff_lt, ← Nat.succ_le_iff] at h''
rw [← tsub_add_eq_tsub_tsub, add_comm, tsub_add_cancel_of_le h'']
rw [this, ascPochhammer_eval_succ]
rw_mod_cast [tsub_add_cancel_of_le (h'.trans n.pred_le)]
· simp only [not_le] at h
rw [tsub_eq_zero_iff_le.mpr (Nat.le_sub_one_of_lt h), eq_zero_of_lt R h]
simp [pos_iff_ne_zero.mp (pos_of_gt h)]
#align bernstein_polynomial.iterate_derivative_at_0 bernsteinPolynomial.iterate_derivative_at_0
theorem iterate_derivative_at_0_ne_zero [CharZero R] (n ν : ℕ) (h : ν ≤ n) :
(Polynomial.derivative^[ν] (bernsteinPolynomial R n ν)).eval 0 ≠ 0 := by
simp only [Int.natCast_eq_zero, bernsteinPolynomial.iterate_derivative_at_0, Ne, Nat.cast_eq_zero]
simp only [← ascPochhammer_eval_cast]
norm_cast
apply ne_of_gt
obtain rfl | h' := Nat.eq_zero_or_pos ν
· simp
· rw [← Nat.succ_pred_eq_of_pos h'] at h
exact ascPochhammer_pos _ _ (tsub_pos_of_lt (Nat.lt_of_succ_le h))
#align bernstein_polynomial.iterate_derivative_at_0_ne_zero bernsteinPolynomial.iterate_derivative_at_0_ne_zero
/-!
Rather than redoing the work of evaluating the derivatives at 1,
we use the symmetry of the Bernstein polynomials.
-/
theorem iterate_derivative_at_1_eq_zero_of_lt (n : ℕ) {ν k : ℕ} :
k < n - ν → (Polynomial.derivative^[k] (bernsteinPolynomial R n ν)).eval 1 = 0 := by
intro w
rw [flip' _ _ _ (tsub_pos_iff_lt.mp (pos_of_gt w)).le]
simp [Polynomial.eval_comp, iterate_derivative_at_0_eq_zero_of_lt R n w]
#align bernstein_polynomial.iterate_derivative_at_1_eq_zero_of_lt bernsteinPolynomial.iterate_derivative_at_1_eq_zero_of_lt
@[simp]
theorem iterate_derivative_at_1 (n ν : ℕ) (h : ν ≤ n) :
(Polynomial.derivative^[n - ν] (bernsteinPolynomial R n ν)).eval 1 =
(-1) ^ (n - ν) * (ascPochhammer R (n - ν)).eval (ν + 1 : R) := by
rw [flip' _ _ _ h]
simp [Polynomial.eval_comp, h]
obtain rfl | h' := h.eq_or_lt
· simp
· norm_cast
congr
omega
#align bernstein_polynomial.iterate_derivative_at_1 bernsteinPolynomial.iterate_derivative_at_1
theorem iterate_derivative_at_1_ne_zero [CharZero R] (n ν : ℕ) (h : ν ≤ n) :
(Polynomial.derivative^[n - ν] (bernsteinPolynomial R n ν)).eval 1 ≠ 0 := by
rw [bernsteinPolynomial.iterate_derivative_at_1 _ _ _ h, Ne, neg_one_pow_mul_eq_zero_iff, ←
Nat.cast_succ, ← ascPochhammer_eval_cast, ← Nat.cast_zero, Nat.cast_inj]
exact (ascPochhammer_pos _ _ (Nat.succ_pos ν)).ne'
#align bernstein_polynomial.iterate_derivative_at_1_ne_zero bernsteinPolynomial.iterate_derivative_at_1_ne_zero
open Submodule
theorem linearIndependent_aux (n k : ℕ) (h : k ≤ n + 1) :
LinearIndependent ℚ fun ν : Fin k => bernsteinPolynomial ℚ n ν := by
induction' k with k ih
· apply linearIndependent_empty_type
· apply linearIndependent_fin_succ'.mpr
fconstructor
· exact ih (le_of_lt h)
· -- The actual work!
-- We show that the (n-k)-th derivative at 1 doesn't vanish,
-- but vanishes for everything in the span.
clear ih
simp only [Nat.succ_eq_add_one, add_le_add_iff_right] at h
simp only [Fin.val_last, Fin.init_def]
dsimp
apply not_mem_span_of_apply_not_mem_span_image (@Polynomial.derivative ℚ _ ^ (n - k))
-- Note: #8386 had to change `span_image` into `span_image _`
simp only [not_exists, not_and, Submodule.mem_map, Submodule.span_image _]
intro p m
apply_fun Polynomial.eval (1 : ℚ)
simp only [LinearMap.pow_apply]
-- The right hand side is nonzero,
-- so it will suffice to show the left hand side is always zero.
suffices (Polynomial.derivative^[n - k] p).eval 1 = 0 by
rw [this]
exact (iterate_derivative_at_1_ne_zero ℚ n k h).symm
refine span_induction m ?_ ?_ ?_ ?_
· simp
rintro ⟨a, w⟩; simp only [Fin.val_mk]
rw [iterate_derivative_at_1_eq_zero_of_lt ℚ n ((tsub_lt_tsub_iff_left_of_le h).mpr w)]
· simp
· intro x y hx hy; simp [hx, hy]
· intro a x h; simp [h]
#align bernstein_polynomial.linear_independent_aux bernsteinPolynomial.linearIndependent_aux
/-- The Bernstein polynomials are linearly independent.
We prove by induction that the collection of `bernsteinPolynomial n ν` for `ν = 0, ..., k`
are linearly independent.
The inductive step relies on the observation that the `(n-k)`-th derivative, evaluated at 1,
annihilates `bernsteinPolynomial n ν` for `ν < k`, but has a nonzero value at `ν = k`.
-/
theorem linearIndependent (n : ℕ) :
LinearIndependent ℚ fun ν : Fin (n + 1) => bernsteinPolynomial ℚ n ν :=
linearIndependent_aux n (n + 1) le_rfl
#align bernstein_polynomial.linear_independent bernsteinPolynomial.linearIndependent
| Mathlib/RingTheory/Polynomial/Bernstein.lean | 289 | 294 | theorem sum (n : ℕ) : (∑ ν ∈ Finset.range (n + 1), bernsteinPolynomial R n ν) = 1 :=
calc
(∑ ν ∈ Finset.range (n + 1), bernsteinPolynomial R n ν) = (X + (1 - X)) ^ n := by |
rw [add_pow]
simp only [bernsteinPolynomial, mul_comm, mul_assoc, mul_left_comm]
_ = 1 := by simp
|
/-
Copyright (c) 2020 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Computability.Halting
import Mathlib.Computability.TuringMachine
import Mathlib.Data.Num.Lemmas
import Mathlib.Tactic.DeriveFintype
#align_import computability.tm_to_partrec from "leanprover-community/mathlib"@"6155d4351090a6fad236e3d2e4e0e4e7342668e8"
/-!
# Modelling partial recursive functions using Turing machines
This file defines a simplified basis for partial recursive functions, and a `Turing.TM2` model
Turing machine for evaluating these functions. This amounts to a constructive proof that every
`Partrec` function can be evaluated by a Turing machine.
## Main definitions
* `ToPartrec.Code`: a simplified basis for partial recursive functions, valued in
`List ℕ →. List ℕ`.
* `ToPartrec.Code.eval`: semantics for a `ToPartrec.Code` program
* `PartrecToTM2.tr`: A TM2 turing machine which can evaluate `code` programs
-/
open Function (update)
open Relation
namespace Turing
/-!
## A simplified basis for partrec
This section constructs the type `Code`, which is a data type of programs with `List ℕ` input and
output, with enough expressivity to write any partial recursive function. The primitives are:
* `zero'` appends a `0` to the input. That is, `zero' v = 0 :: v`.
* `succ` returns the successor of the head of the input, defaulting to zero if there is no head:
* `succ [] = [1]`
* `succ (n :: v) = [n + 1]`
* `tail` returns the tail of the input
* `tail [] = []`
* `tail (n :: v) = v`
* `cons f fs` calls `f` and `fs` on the input and conses the results:
* `cons f fs v = (f v).head :: fs v`
* `comp f g` calls `f` on the output of `g`:
* `comp f g v = f (g v)`
* `case f g` cases on the head of the input, calling `f` or `g` depending on whether it is zero or
a successor (similar to `Nat.casesOn`).
* `case f g [] = f []`
* `case f g (0 :: v) = f v`
* `case f g (n+1 :: v) = g (n :: v)`
* `fix f` calls `f` repeatedly, using the head of the result of `f` to decide whether to call `f`
again or finish:
* `fix f v = []` if `f v = []`
* `fix f v = w` if `f v = 0 :: w`
* `fix f v = fix f w` if `f v = n+1 :: w` (the exact value of `n` is discarded)
This basis is convenient because it is closer to the Turing machine model - the key operations are
splitting and merging of lists of unknown length, while the messy `n`-ary composition operation
from the traditional basis for partial recursive functions is absent - but it retains a
compositional semantics. The first step in transitioning to Turing machines is to make a sequential
evaluator for this basis, which we take up in the next section.
-/
namespace ToPartrec
/-- The type of codes for primitive recursive functions. Unlike `Nat.Partrec.Code`, this uses a set
of operations on `List ℕ`. See `Code.eval` for a description of the behavior of the primitives. -/
inductive Code
| zero'
| succ
| tail
| cons : Code → Code → Code
| comp : Code → Code → Code
| case : Code → Code → Code
| fix : Code → Code
deriving DecidableEq, Inhabited
#align turing.to_partrec.code Turing.ToPartrec.Code
#align turing.to_partrec.code.zero' Turing.ToPartrec.Code.zero'
#align turing.to_partrec.code.succ Turing.ToPartrec.Code.succ
#align turing.to_partrec.code.tail Turing.ToPartrec.Code.tail
#align turing.to_partrec.code.cons Turing.ToPartrec.Code.cons
#align turing.to_partrec.code.comp Turing.ToPartrec.Code.comp
#align turing.to_partrec.code.case Turing.ToPartrec.Code.case
#align turing.to_partrec.code.fix Turing.ToPartrec.Code.fix
/-- The semantics of the `Code` primitives, as partial functions `List ℕ →. List ℕ`. By convention
we functions that return a single result return a singleton `[n]`, or in some cases `n :: v` where
`v` will be ignored by a subsequent function.
* `zero'` appends a `0` to the input. That is, `zero' v = 0 :: v`.
* `succ` returns the successor of the head of the input, defaulting to zero if there is no head:
* `succ [] = [1]`
* `succ (n :: v) = [n + 1]`
* `tail` returns the tail of the input
* `tail [] = []`
* `tail (n :: v) = v`
* `cons f fs` calls `f` and `fs` on the input and conses the results:
* `cons f fs v = (f v).head :: fs v`
* `comp f g` calls `f` on the output of `g`:
* `comp f g v = f (g v)`
* `case f g` cases on the head of the input, calling `f` or `g` depending on whether it is zero or
a successor (similar to `Nat.casesOn`).
* `case f g [] = f []`
* `case f g (0 :: v) = f v`
* `case f g (n+1 :: v) = g (n :: v)`
* `fix f` calls `f` repeatedly, using the head of the result of `f` to decide whether to call `f`
again or finish:
* `fix f v = []` if `f v = []`
* `fix f v = w` if `f v = 0 :: w`
* `fix f v = fix f w` if `f v = n+1 :: w` (the exact value of `n` is discarded)
-/
def Code.eval : Code → List ℕ →. List ℕ
| Code.zero' => fun v => pure (0 :: v)
| Code.succ => fun v => pure [v.headI.succ]
| Code.tail => fun v => pure v.tail
| Code.cons f fs => fun v => do
let n ← Code.eval f v
let ns ← Code.eval fs v
pure (n.headI :: ns)
| Code.comp f g => fun v => g.eval v >>= f.eval
| Code.case f g => fun v => v.headI.rec (f.eval v.tail) fun y _ => g.eval (y::v.tail)
| Code.fix f =>
PFun.fix fun v => (f.eval v).map fun v => if v.headI = 0 then Sum.inl v.tail else Sum.inr v.tail
#align turing.to_partrec.code.eval Turing.ToPartrec.Code.eval
namespace Code
/- Porting note: The equation lemma of `eval` is too strong; it simplifies terms like the LHS of
`pred_eval`. Even `eqns` can't fix this. We removed `simp` attr from `eval` and prepare new simp
lemmas for `eval`. -/
@[simp]
theorem zero'_eval : zero'.eval = fun v => pure (0 :: v) := by simp [eval]
@[simp]
theorem succ_eval : succ.eval = fun v => pure [v.headI.succ] := by simp [eval]
@[simp]
theorem tail_eval : tail.eval = fun v => pure v.tail := by simp [eval]
@[simp]
theorem cons_eval (f fs) : (cons f fs).eval = fun v => do {
let n ← Code.eval f v
let ns ← Code.eval fs v
pure (n.headI :: ns) } := by simp [eval]
@[simp]
theorem comp_eval (f g) : (comp f g).eval = fun v => g.eval v >>= f.eval := by simp [eval]
@[simp]
theorem case_eval (f g) :
(case f g).eval = fun v => v.headI.rec (f.eval v.tail) fun y _ => g.eval (y::v.tail) := by
simp [eval]
@[simp]
theorem fix_eval (f) : (fix f).eval =
PFun.fix fun v => (f.eval v).map fun v =>
if v.headI = 0 then Sum.inl v.tail else Sum.inr v.tail := by
simp [eval]
/-- `nil` is the constant nil function: `nil v = []`. -/
def nil : Code :=
tail.comp succ
#align turing.to_partrec.code.nil Turing.ToPartrec.Code.nil
@[simp]
theorem nil_eval (v) : nil.eval v = pure [] := by simp [nil]
#align turing.to_partrec.code.nil_eval Turing.ToPartrec.Code.nil_eval
/-- `id` is the identity function: `id v = v`. -/
def id : Code :=
tail.comp zero'
#align turing.to_partrec.code.id Turing.ToPartrec.Code.id
@[simp]
theorem id_eval (v) : id.eval v = pure v := by simp [id]
#align turing.to_partrec.code.id_eval Turing.ToPartrec.Code.id_eval
/-- `head` gets the head of the input list: `head [] = [0]`, `head (n :: v) = [n]`. -/
def head : Code :=
cons id nil
#align turing.to_partrec.code.head Turing.ToPartrec.Code.head
@[simp]
theorem head_eval (v) : head.eval v = pure [v.headI] := by simp [head]
#align turing.to_partrec.code.head_eval Turing.ToPartrec.Code.head_eval
/-- `zero` is the constant zero function: `zero v = [0]`. -/
def zero : Code :=
cons zero' nil
#align turing.to_partrec.code.zero Turing.ToPartrec.Code.zero
@[simp]
theorem zero_eval (v) : zero.eval v = pure [0] := by simp [zero]
#align turing.to_partrec.code.zero_eval Turing.ToPartrec.Code.zero_eval
/-- `pred` returns the predecessor of the head of the input:
`pred [] = [0]`, `pred (0 :: v) = [0]`, `pred (n+1 :: v) = [n]`. -/
def pred : Code :=
case zero head
#align turing.to_partrec.code.pred Turing.ToPartrec.Code.pred
@[simp]
theorem pred_eval (v) : pred.eval v = pure [v.headI.pred] := by
simp [pred]; cases v.headI <;> simp
#align turing.to_partrec.code.pred_eval Turing.ToPartrec.Code.pred_eval
/-- `rfind f` performs the function of the `rfind` primitive of partial recursive functions.
`rfind f v` returns the smallest `n` such that `(f (n :: v)).head = 0`.
It is implemented as:
rfind f v = pred (fix (fun (n::v) => f (n::v) :: n+1 :: v) (0 :: v))
The idea is that the initial state is `0 :: v`, and the `fix` keeps `n :: v` as its internal state;
it calls `f (n :: v)` as the exit test and `n+1 :: v` as the next state. At the end we get
`n+1 :: v` where `n` is the desired output, and `pred (n+1 :: v) = [n]` returns the result.
-/
def rfind (f : Code) : Code :=
comp pred <| comp (fix <| cons f <| cons succ tail) zero'
#align turing.to_partrec.code.rfind Turing.ToPartrec.Code.rfind
/-- `prec f g` implements the `prec` (primitive recursion) operation of partial recursive
functions. `prec f g` evaluates as:
* `prec f g [] = [f []]`
* `prec f g (0 :: v) = [f v]`
* `prec f g (n+1 :: v) = [g (n :: prec f g (n :: v) :: v)]`
It is implemented as:
G (a :: b :: IH :: v) = (b :: a+1 :: b-1 :: g (a :: IH :: v) :: v)
F (0 :: f_v :: v) = (f_v :: v)
F (n+1 :: f_v :: v) = (fix G (0 :: n :: f_v :: v)).tail.tail
prec f g (a :: v) = [(F (a :: f v :: v)).head]
Because `fix` always evaluates its body at least once, we must special case the `0` case to avoid
calling `g` more times than necessary (which could be bad if `g` diverges). If the input is
`0 :: v`, then `F (0 :: f v :: v) = (f v :: v)` so we return `[f v]`. If the input is `n+1 :: v`,
we evaluate the function from the bottom up, with initial state `0 :: n :: f v :: v`. The first
number counts up, providing arguments for the applications to `g`, while the second number counts
down, providing the exit condition (this is the initial `b` in the return value of `G`, which is
stripped by `fix`). After the `fix` is complete, the final state is `n :: 0 :: res :: v` where
`res` is the desired result, and the rest reduces this to `[res]`. -/
def prec (f g : Code) : Code :=
let G :=
cons tail <|
cons succ <|
cons (comp pred tail) <|
cons (comp g <| cons id <| comp tail tail) <| comp tail <| comp tail tail
let F := case id <| comp (comp (comp tail tail) (fix G)) zero'
cons (comp F (cons head <| cons (comp f tail) tail)) nil
#align turing.to_partrec.code.prec Turing.ToPartrec.Code.prec
attribute [-simp] Part.bind_eq_bind Part.map_eq_map Part.pure_eq_some
theorem exists_code.comp {m n} {f : Vector ℕ n →. ℕ} {g : Fin n → Vector ℕ m →. ℕ}
(hf : ∃ c : Code, ∀ v : Vector ℕ n, c.eval v.1 = pure <$> f v)
(hg : ∀ i, ∃ c : Code, ∀ v : Vector ℕ m, c.eval v.1 = pure <$> g i v) :
∃ c : Code, ∀ v : Vector ℕ m, c.eval v.1 = pure <$> ((Vector.mOfFn fun i => g i v) >>= f) := by
rsuffices ⟨cg, hg⟩ :
∃ c : Code, ∀ v : Vector ℕ m, c.eval v.1 = Subtype.val <$> Vector.mOfFn fun i => g i v
· obtain ⟨cf, hf⟩ := hf
exact
⟨cf.comp cg, fun v => by
simp [hg, hf, map_bind, seq_bind_eq, Function.comp]
rfl⟩
clear hf f; induction' n with n IH
· exact ⟨nil, fun v => by simp [Vector.mOfFn, Bind.bind]; rfl⟩
· obtain ⟨cg, hg₁⟩ := hg 0
obtain ⟨cl, hl⟩ := IH fun i => hg i.succ
exact
⟨cons cg cl, fun v => by
simp [Vector.mOfFn, hg₁, map_bind, seq_bind_eq, bind_assoc, (· ∘ ·), hl]
rfl⟩
#align turing.to_partrec.code.exists_code.comp Turing.ToPartrec.Code.exists_code.comp
theorem exists_code {n} {f : Vector ℕ n →. ℕ} (hf : Nat.Partrec' f) :
∃ c : Code, ∀ v : Vector ℕ n, c.eval v.1 = pure <$> f v := by
induction hf with
| prim hf =>
induction hf with
| zero => exact ⟨zero', fun ⟨[], _⟩ => rfl⟩
| succ => exact ⟨succ, fun ⟨[v], _⟩ => rfl⟩
| get i =>
refine Fin.succRec (fun n => ?_) (fun n i IH => ?_) i
· exact ⟨head, fun ⟨List.cons a as, _⟩ => by simp [Bind.bind]; rfl⟩
· obtain ⟨c, h⟩ := IH
exact ⟨c.comp tail, fun v => by simpa [← Vector.get_tail, Bind.bind] using h v.tail⟩
| comp g hf hg IHf IHg =>
simpa [Part.bind_eq_bind] using exists_code.comp IHf IHg
| @prec n f g _ _ IHf IHg =>
obtain ⟨cf, hf⟩ := IHf
obtain ⟨cg, hg⟩ := IHg
simp only [Part.map_eq_map, Part.map_some, PFun.coe_val] at hf hg
refine ⟨prec cf cg, fun v => ?_⟩
rw [← v.cons_head_tail]
specialize hf v.tail
replace hg := fun a b => hg (a ::ᵥ b ::ᵥ v.tail)
simp only [Vector.cons_val, Vector.tail_val] at hf hg
simp only [Part.map_eq_map, Part.map_some, Vector.cons_val, Vector.tail_cons,
Vector.head_cons, PFun.coe_val, Vector.tail_val]
simp only [← Part.pure_eq_some] at hf hg ⊢
induction' v.head with n _ <;>
simp [prec, hf, Part.bind_assoc, ← Part.bind_some_eq_map, Part.bind_some,
show ∀ x, pure x = [x] from fun _ => rfl, Bind.bind, Functor.map]
suffices ∀ a b, a + b = n →
(n.succ :: 0 ::
g (n ::ᵥ Nat.rec (f v.tail) (fun y IH => g (y ::ᵥ IH ::ᵥ v.tail)) n ::ᵥ v.tail) ::
v.val.tail : List ℕ) ∈
PFun.fix
(fun v : List ℕ => Part.bind (cg.eval (v.headI :: v.tail.tail))
(fun x => Part.some (if v.tail.headI = 0
then Sum.inl
(v.headI.succ :: v.tail.headI.pred :: x.headI :: v.tail.tail.tail : List ℕ)
else Sum.inr
(v.headI.succ :: v.tail.headI.pred :: x.headI :: v.tail.tail.tail))))
(a :: b :: Nat.rec (f v.tail) (fun y IH => g (y ::ᵥ IH ::ᵥ v.tail)) a :: v.val.tail) by
erw [Part.eq_some_iff.2 (this 0 n (zero_add n))]
simp only [List.headI, Part.bind_some, List.tail_cons]
intro a b e
induction' b with b IH generalizing a
· refine PFun.mem_fix_iff.2 (Or.inl <| Part.eq_some_iff.1 ?_)
simp only [hg, ← e, Part.bind_some, List.tail_cons, pure]
rfl
· refine PFun.mem_fix_iff.2 (Or.inr ⟨_, ?_, IH (a + 1) (by rwa [add_right_comm])⟩)
simp only [hg, eval, Part.bind_some, Nat.rec_add_one, List.tail_nil, List.tail_cons, pure]
exact Part.mem_some_iff.2 rfl
| comp g _ _ IHf IHg => exact exists_code.comp IHf IHg
| @rfind n f _ IHf =>
obtain ⟨cf, hf⟩ := IHf; refine ⟨rfind cf, fun v => ?_⟩
replace hf := fun a => hf (a ::ᵥ v)
simp only [Part.map_eq_map, Part.map_some, Vector.cons_val, PFun.coe_val,
show ∀ x, pure x = [x] from fun _ => rfl] at hf ⊢
refine Part.ext fun x => ?_
simp only [rfind, Part.bind_eq_bind, Part.pure_eq_some, Part.map_eq_map, Part.bind_some,
exists_prop, cons_eval, comp_eval, fix_eval, tail_eval, succ_eval, zero'_eval,
List.headI_nil, List.headI_cons, pred_eval, Part.map_some, false_eq_decide_iff,
Part.mem_bind_iff, List.length, Part.mem_map_iff, Nat.mem_rfind, List.tail_nil,
List.tail_cons, true_eq_decide_iff, Part.mem_some_iff, Part.map_bind]
constructor
· rintro ⟨v', h1, rfl⟩
suffices ∀ v₁ : List ℕ, v' ∈ PFun.fix
(fun v => (cf.eval v).bind fun y => Part.some <|
if y.headI = 0 then Sum.inl (v.headI.succ :: v.tail)
else Sum.inr (v.headI.succ :: v.tail)) v₁ →
∀ n, (v₁ = n :: v.val) → (∀ m < n, ¬f (m ::ᵥ v) = 0) →
∃ a : ℕ,
(f (a ::ᵥ v) = 0 ∧ ∀ {m : ℕ}, m < a → ¬f (m ::ᵥ v) = 0) ∧ [a] = [v'.headI.pred]
by exact this _ h1 0 rfl (by rintro _ ⟨⟩)
clear h1
intro v₀ h1
refine PFun.fixInduction h1 fun v₁ h2 IH => ?_
clear h1
rintro n rfl hm
have := PFun.mem_fix_iff.1 h2
simp only [hf, Part.bind_some] at this
split_ifs at this with h
· simp only [List.headI_nil, List.headI_cons, exists_false, or_false_iff, Part.mem_some_iff,
List.tail_cons, false_and_iff, Sum.inl.injEq] at this
subst this
exact ⟨_, ⟨h, @(hm)⟩, rfl⟩
· refine IH (n.succ::v.val) (by simp_all) _ rfl fun m h' => ?_
obtain h | rfl := Nat.lt_succ_iff_lt_or_eq.1 h'
exacts [hm _ h, h]
· rintro ⟨n, ⟨hn, hm⟩, rfl⟩
refine ⟨n.succ::v.1, ?_, rfl⟩
have : (n.succ::v.1 : List ℕ) ∈
PFun.fix (fun v =>
(cf.eval v).bind fun y =>
Part.some <|
if y.headI = 0 then Sum.inl (v.headI.succ :: v.tail)
else Sum.inr (v.headI.succ :: v.tail))
(n::v.val) :=
PFun.mem_fix_iff.2 (Or.inl (by simp [hf, hn]))
generalize (n.succ :: v.1 : List ℕ) = w at this ⊢
clear hn
induction' n with n IH
· exact this
refine IH (fun {m} h' => hm (Nat.lt_succ_of_lt h'))
(PFun.mem_fix_iff.2 (Or.inr ⟨_, ?_, this⟩))
simp only [hf, hm n.lt_succ_self, Part.bind_some, List.headI, eq_self_iff_true, if_false,
Part.mem_some_iff, and_self_iff, List.tail_cons]
#align turing.to_partrec.code.exists_code Turing.ToPartrec.Code.exists_code
end Code
/-!
## From compositional semantics to sequential semantics
Our initial sequential model is designed to be as similar as possible to the compositional
semantics in terms of its primitives, but it is a sequential semantics, meaning that rather than
defining an `eval c : List ℕ →. List ℕ` function for each program, defined by recursion on
programs, we have a type `Cfg` with a step function `step : Cfg → Option cfg` that provides a
deterministic evaluation order. In order to do this, we introduce the notion of a *continuation*,
which can be viewed as a `Code` with a hole in it where evaluation is currently taking place.
Continuations can be assigned a `List ℕ →. List ℕ` semantics as well, with the interpretation
being that given a `List ℕ` result returned from the code in the hole, the remainder of the
program will evaluate to a `List ℕ` final value.
The continuations are:
* `halt`: the empty continuation: the hole is the whole program, whatever is returned is the
final result. In our notation this is just `_`.
* `cons₁ fs v k`: evaluating the first part of a `cons`, that is `k (_ :: fs v)`, where `k` is the
outer continuation.
* `cons₂ ns k`: evaluating the second part of a `cons`: `k (ns.headI :: _)`. (Technically we don't
need to hold on to all of `ns` here since we are already committed to taking the head, but this
is more regular.)
* `comp f k`: evaluating the first part of a composition: `k (f _)`.
* `fix f k`: waiting for the result of `f` in a `fix f` expression:
`k (if _.headI = 0 then _.tail else fix f (_.tail))`
The type `Cfg` of evaluation states is:
* `ret k v`: we have received a result, and are now evaluating the continuation `k` with result
`v`; that is, `k v` where `k` is ready to evaluate.
* `halt v`: we are done and the result is `v`.
The main theorem of this section is that for each code `c`, the state `stepNormal c halt v` steps
to `v'` in finitely many steps if and only if `Code.eval c v = some v'`.
-/
/-- The type of continuations, built up during evaluation of a `Code` expression. -/
inductive Cont
| halt
| cons₁ : Code → List ℕ → Cont → Cont
| cons₂ : List ℕ → Cont → Cont
| comp : Code → Cont → Cont
| fix : Code → Cont → Cont
deriving Inhabited
#align turing.to_partrec.cont Turing.ToPartrec.Cont
#align turing.to_partrec.cont.halt Turing.ToPartrec.Cont.halt
#align turing.to_partrec.cont.cons₁ Turing.ToPartrec.Cont.cons₁
#align turing.to_partrec.cont.cons₂ Turing.ToPartrec.Cont.cons₂
#align turing.to_partrec.cont.comp Turing.ToPartrec.Cont.comp
#align turing.to_partrec.cont.fix Turing.ToPartrec.Cont.fix
/-- The semantics of a continuation. -/
def Cont.eval : Cont → List ℕ →. List ℕ
| Cont.halt => pure
| Cont.cons₁ fs as k => fun v => do
let ns ← Code.eval fs as
Cont.eval k (v.headI :: ns)
| Cont.cons₂ ns k => fun v => Cont.eval k (ns.headI :: v)
| Cont.comp f k => fun v => Code.eval f v >>= Cont.eval k
| Cont.fix f k => fun v => if v.headI = 0 then k.eval v.tail else f.fix.eval v.tail >>= k.eval
#align turing.to_partrec.cont.eval Turing.ToPartrec.Cont.eval
/-- The set of configurations of the machine:
* `halt v`: The machine is about to stop and `v : List ℕ` is the result.
* `ret k v`: The machine is about to pass `v : List ℕ` to continuation `k : cont`.
We don't have a state corresponding to normal evaluation because these are evaluated immediately
to a `ret` "in zero steps" using the `stepNormal` function. -/
inductive Cfg
| halt : List ℕ → Cfg
| ret : Cont → List ℕ → Cfg
deriving Inhabited
#align turing.to_partrec.cfg Turing.ToPartrec.Cfg
#align turing.to_partrec.cfg.halt Turing.ToPartrec.Cfg.halt
#align turing.to_partrec.cfg.ret Turing.ToPartrec.Cfg.ret
/-- Evaluating `c : Code` in a continuation `k : Cont` and input `v : List ℕ`. This goes by
recursion on `c`, building an augmented continuation and a value to pass to it.
* `zero' v = 0 :: v` evaluates immediately, so we return it to the parent continuation
* `succ v = [v.headI.succ]` evaluates immediately, so we return it to the parent continuation
* `tail v = v.tail` evaluates immediately, so we return it to the parent continuation
* `cons f fs v = (f v).headI :: fs v` requires two sub-evaluations, so we evaluate
`f v` in the continuation `k (_.headI :: fs v)` (called `Cont.cons₁ fs v k`)
* `comp f g v = f (g v)` requires two sub-evaluations, so we evaluate
`g v` in the continuation `k (f _)` (called `Cont.comp f k`)
* `case f g v = v.head.casesOn (f v.tail) (fun n => g (n :: v.tail))` has the information needed
to evaluate the case statement, so we do that and transition to either
`f v` or `g (n :: v.tail)`.
* `fix f v = let v' := f v; if v'.headI = 0 then k v'.tail else fix f v'.tail`
needs to first evaluate `f v`, so we do that and leave the rest for the continuation (called
`Cont.fix f k`)
-/
def stepNormal : Code → Cont → List ℕ → Cfg
| Code.zero' => fun k v => Cfg.ret k (0::v)
| Code.succ => fun k v => Cfg.ret k [v.headI.succ]
| Code.tail => fun k v => Cfg.ret k v.tail
| Code.cons f fs => fun k v => stepNormal f (Cont.cons₁ fs v k) v
| Code.comp f g => fun k v => stepNormal g (Cont.comp f k) v
| Code.case f g => fun k v =>
v.headI.rec (stepNormal f k v.tail) fun y _ => stepNormal g k (y::v.tail)
| Code.fix f => fun k v => stepNormal f (Cont.fix f k) v
#align turing.to_partrec.step_normal Turing.ToPartrec.stepNormal
/-- Evaluating a continuation `k : Cont` on input `v : List ℕ`. This is the second part of
evaluation, when we receive results from continuations built by `stepNormal`.
* `Cont.halt v = v`, so we are done and transition to the `Cfg.halt v` state
* `Cont.cons₁ fs as k v = k (v.headI :: fs as)`, so we evaluate `fs as` now with the continuation
`k (v.headI :: _)` (called `cons₂ v k`).
* `Cont.cons₂ ns k v = k (ns.headI :: v)`, where we now have everything we need to evaluate
`ns.headI :: v`, so we return it to `k`.
* `Cont.comp f k v = k (f v)`, so we call `f v` with `k` as the continuation.
* `Cont.fix f k v = k (if v.headI = 0 then k v.tail else fix f v.tail)`, where `v` is a value,
so we evaluate the if statement and either call `k` with `v.tail`, or call `fix f v` with `k` as
the continuation (which immediately calls `f` with `Cont.fix f k` as the continuation).
-/
def stepRet : Cont → List ℕ → Cfg
| Cont.halt, v => Cfg.halt v
| Cont.cons₁ fs as k, v => stepNormal fs (Cont.cons₂ v k) as
| Cont.cons₂ ns k, v => stepRet k (ns.headI :: v)
| Cont.comp f k, v => stepNormal f k v
| Cont.fix f k, v => if v.headI = 0 then stepRet k v.tail else stepNormal f (Cont.fix f k) v.tail
#align turing.to_partrec.step_ret Turing.ToPartrec.stepRet
/-- If we are not done (in `Cfg.halt` state), then we must be still stuck on a continuation, so
this main loop calls `stepRet` with the new continuation. The overall `step` function transitions
from one `Cfg` to another, only halting at the `Cfg.halt` state. -/
def step : Cfg → Option Cfg
| Cfg.halt _ => none
| Cfg.ret k v => some (stepRet k v)
#align turing.to_partrec.step Turing.ToPartrec.step
/-- In order to extract a compositional semantics from the sequential execution behavior of
configurations, we observe that continuations have a monoid structure, with `Cont.halt` as the unit
and `Cont.then` as the multiplication. `Cont.then k₁ k₂` runs `k₁` until it halts, and then takes
the result of `k₁` and passes it to `k₂`.
We will not prove it is associative (although it is), but we are instead interested in the
associativity law `k₂ (eval c k₁) = eval c (k₁.then k₂)`. This holds at both the sequential and
compositional levels, and allows us to express running a machine without the ambient continuation
and relate it to the original machine's evaluation steps. In the literature this is usually
where one uses Turing machines embedded inside other Turing machines, but this approach allows us
to avoid changing the ambient type `Cfg` in the middle of the recursion.
-/
def Cont.then : Cont → Cont → Cont
| Cont.halt => fun k' => k'
| Cont.cons₁ fs as k => fun k' => Cont.cons₁ fs as (k.then k')
| Cont.cons₂ ns k => fun k' => Cont.cons₂ ns (k.then k')
| Cont.comp f k => fun k' => Cont.comp f (k.then k')
| Cont.fix f k => fun k' => Cont.fix f (k.then k')
#align turing.to_partrec.cont.then Turing.ToPartrec.Cont.then
theorem Cont.then_eval {k k' : Cont} {v} : (k.then k').eval v = k.eval v >>= k'.eval := by
induction' k with _ _ _ _ _ _ _ _ _ k_ih _ _ k_ih generalizing v <;>
simp only [Cont.eval, Cont.then, bind_assoc, pure_bind, *]
· simp only [← k_ih]
· split_ifs <;> [rfl; simp only [← k_ih, bind_assoc]]
#align turing.to_partrec.cont.then_eval Turing.ToPartrec.Cont.then_eval
/-- The `then k` function is a "configuration homomorphism". Its operation on states is to append
`k` to the continuation of a `Cfg.ret` state, and to run `k` on `v` if we are in the `Cfg.halt v`
state. -/
def Cfg.then : Cfg → Cont → Cfg
| Cfg.halt v => fun k' => stepRet k' v
| Cfg.ret k v => fun k' => Cfg.ret (k.then k') v
#align turing.to_partrec.cfg.then Turing.ToPartrec.Cfg.then
/-- The `stepNormal` function respects the `then k'` homomorphism. Note that this is an exact
equality, not a simulation; the original and embedded machines move in lock-step until the
embedded machine reaches the halt state. -/
theorem stepNormal_then (c) (k k' : Cont) (v) :
stepNormal c (k.then k') v = (stepNormal c k v).then k' := by
induction c generalizing k v with simp only [Cont.then, stepNormal, *]
| cons c c' ih _ => rw [← ih, Cont.then]
| comp c c' _ ih' => rw [← ih', Cont.then]
| case => cases v.headI <;> simp only [Nat.rec_zero]
| fix c ih => rw [← ih, Cont.then]
| _ => simp only [Cfg.then]
#align turing.to_partrec.step_normal_then Turing.ToPartrec.stepNormal_then
/-- The `stepRet` function respects the `then k'` homomorphism. Note that this is an exact
equality, not a simulation; the original and embedded machines move in lock-step until the
embedded machine reaches the halt state. -/
theorem stepRet_then {k k' : Cont} {v} : stepRet (k.then k') v = (stepRet k v).then k' := by
induction k generalizing v with simp only [Cont.then, stepRet, *]
| cons₁ =>
rw [← stepNormal_then]
rfl
| comp =>
rw [← stepNormal_then]
| fix _ _ k_ih =>
split_ifs
· rw [← k_ih]
· rw [← stepNormal_then]
rfl
| _ => simp only [Cfg.then]
#align turing.to_partrec.step_ret_then Turing.ToPartrec.stepRet_then
/-- This is a temporary definition, because we will prove in `code_is_ok` that it always holds.
It asserts that `c` is semantically correct; that is, for any `k` and `v`,
`eval (stepNormal c k v) = eval (Cfg.ret k (Code.eval c v))`, as an equality of partial values
(so one diverges iff the other does).
In particular, we can let `k = Cont.halt`, and then this asserts that `stepNormal c Cont.halt v`
evaluates to `Cfg.halt (Code.eval c v)`. -/
def Code.Ok (c : Code) :=
∀ k v, Turing.eval step (stepNormal c k v) =
Code.eval c v >>= fun v => Turing.eval step (Cfg.ret k v)
#align turing.to_partrec.code.ok Turing.ToPartrec.Code.Ok
theorem Code.Ok.zero {c} (h : Code.Ok c) {v} :
Turing.eval step (stepNormal c Cont.halt v) = Cfg.halt <$> Code.eval c v := by
rw [h, ← bind_pure_comp]; congr; funext v
exact Part.eq_some_iff.2 (mem_eval.2 ⟨ReflTransGen.single rfl, rfl⟩)
#align turing.to_partrec.code.ok.zero Turing.ToPartrec.Code.Ok.zero
theorem stepNormal.is_ret (c k v) : ∃ k' v', stepNormal c k v = Cfg.ret k' v' := by
induction c generalizing k v with
| cons _f fs IHf _IHfs => apply IHf
| comp f _g _IHf IHg => apply IHg
| case f g IHf IHg =>
rw [stepNormal]
simp only []
cases v.headI <;> [apply IHf; apply IHg]
| fix f IHf => apply IHf
| _ => exact ⟨_, _, rfl⟩
#align turing.to_partrec.step_normal.is_ret Turing.ToPartrec.stepNormal.is_ret
theorem cont_eval_fix {f k v} (fok : Code.Ok f) :
Turing.eval step (stepNormal f (Cont.fix f k) v) =
f.fix.eval v >>= fun v => Turing.eval step (Cfg.ret k v) := by
refine Part.ext fun x => ?_
simp only [Part.bind_eq_bind, Part.mem_bind_iff]
constructor
· suffices ∀ c, x ∈ eval step c → ∀ v c', c = Cfg.then c' (Cont.fix f k) →
Reaches step (stepNormal f Cont.halt v) c' →
∃ v₁ ∈ f.eval v, ∃ v₂ ∈ if List.headI v₁ = 0 then pure v₁.tail else f.fix.eval v₁.tail,
x ∈ eval step (Cfg.ret k v₂) by
intro h
obtain ⟨v₁, hv₁, v₂, hv₂, h₃⟩ :=
this _ h _ _ (stepNormal_then _ Cont.halt _ _) ReflTransGen.refl
refine ⟨v₂, PFun.mem_fix_iff.2 ?_, h₃⟩
simp only [Part.eq_some_iff.2 hv₁, Part.map_some]
split_ifs at hv₂ ⊢
· rw [Part.mem_some_iff.1 hv₂]
exact Or.inl (Part.mem_some _)
· exact Or.inr ⟨_, Part.mem_some _, hv₂⟩
refine fun c he => evalInduction he fun y h IH => ?_
rintro v (⟨v'⟩ | ⟨k', v'⟩) rfl hr <;> rw [Cfg.then] at h IH <;> simp only [] at h IH
· have := mem_eval.2 ⟨hr, rfl⟩
rw [fok, Part.bind_eq_bind, Part.mem_bind_iff] at this
obtain ⟨v'', h₁, h₂⟩ := this
rw [reaches_eval] at h₂
swap
· exact ReflTransGen.single rfl
cases Part.mem_unique h₂ (mem_eval.2 ⟨ReflTransGen.refl, rfl⟩)
refine ⟨v', h₁, ?_⟩
rw [stepRet] at h
revert h
by_cases he : v'.headI = 0 <;> simp only [exists_prop, if_pos, if_false, he] <;> intro h
· refine ⟨_, Part.mem_some _, ?_⟩
rw [reaches_eval]
· exact h
exact ReflTransGen.single rfl
· obtain ⟨k₀, v₀, e₀⟩ := stepNormal.is_ret f Cont.halt v'.tail
have e₁ := stepNormal_then f Cont.halt (Cont.fix f k) v'.tail
rw [e₀, Cont.then, Cfg.then] at e₁
simp only [] at e₁
obtain ⟨v₁, hv₁, v₂, hv₂, h₃⟩ :=
IH (stepRet (k₀.then (Cont.fix f k)) v₀) (by rw [stepRet, if_neg he, e₁]; rfl)
v'.tail _ stepRet_then (by apply ReflTransGen.single; rw [e₀]; rfl)
refine ⟨_, PFun.mem_fix_iff.2 ?_, h₃⟩
simp only [Part.eq_some_iff.2 hv₁, Part.map_some, Part.mem_some_iff]
split_ifs at hv₂ ⊢ <;> [exact Or.inl (congr_arg Sum.inl (Part.mem_some_iff.1 hv₂));
exact Or.inr ⟨_, rfl, hv₂⟩]
· exact IH _ rfl _ _ stepRet_then (ReflTransGen.tail hr rfl)
· rintro ⟨v', he, hr⟩
rw [reaches_eval] at hr
swap
· exact ReflTransGen.single rfl
refine PFun.fixInduction he fun v (he : v' ∈ f.fix.eval v) IH => ?_
rw [fok, Part.bind_eq_bind, Part.mem_bind_iff]
obtain he | ⟨v'', he₁', _⟩ := PFun.mem_fix_iff.1 he
· obtain ⟨v', he₁, he₂⟩ := (Part.mem_map_iff _).1 he
split_ifs at he₂ with h; cases he₂
refine ⟨_, he₁, ?_⟩
rw [reaches_eval]
swap
· exact ReflTransGen.single rfl
rwa [stepRet, if_pos h]
· obtain ⟨v₁, he₁, he₂⟩ := (Part.mem_map_iff _).1 he₁'
split_ifs at he₂ with h; cases he₂
clear he₁'
refine ⟨_, he₁, ?_⟩
rw [reaches_eval]
swap
· exact ReflTransGen.single rfl
rw [stepRet, if_neg h]
exact IH v₁.tail ((Part.mem_map_iff _).2 ⟨_, he₁, if_neg h⟩)
#align turing.to_partrec.cont_eval_fix Turing.ToPartrec.cont_eval_fix
theorem code_is_ok (c) : Code.Ok c := by
induction c with (intro k v; rw [stepNormal])
| cons f fs IHf IHfs =>
rw [Code.eval, IHf]
simp only [bind_assoc, Cont.eval, pure_bind]; congr; funext v
rw [reaches_eval]; swap
· exact ReflTransGen.single rfl
rw [stepRet, IHfs]; congr; funext v'
refine Eq.trans (b := eval step (stepRet (Cont.cons₂ v k) v')) ?_ (Eq.symm ?_) <;>
exact reaches_eval (ReflTransGen.single rfl)
| comp f g IHf IHg =>
rw [Code.eval, IHg]
simp only [bind_assoc, Cont.eval, pure_bind]; congr; funext v
rw [reaches_eval]; swap
· exact ReflTransGen.single rfl
rw [stepRet, IHf]
| case f g IHf IHg =>
simp only [Code.eval]
cases v.headI <;> simp only [Nat.rec_zero, Part.bind_eq_bind] <;> [apply IHf; apply IHg]
| fix f IHf => rw [cont_eval_fix IHf]
| _ => simp only [Code.eval, pure_bind]
#align turing.to_partrec.code_is_ok Turing.ToPartrec.code_is_ok
theorem stepNormal_eval (c v) : eval step (stepNormal c Cont.halt v) = Cfg.halt <$> c.eval v :=
(code_is_ok c).zero
#align turing.to_partrec.step_normal_eval Turing.ToPartrec.stepNormal_eval
theorem stepRet_eval {k v} : eval step (stepRet k v) = Cfg.halt <$> k.eval v := by
induction k generalizing v with
| halt =>
simp only [mem_eval, Cont.eval, map_pure]
exact Part.eq_some_iff.2 (mem_eval.2 ⟨ReflTransGen.refl, rfl⟩)
| cons₁ fs as k IH =>
rw [Cont.eval, stepRet, code_is_ok]
simp only [← bind_pure_comp, bind_assoc]; congr; funext v'
rw [reaches_eval]; swap
· exact ReflTransGen.single rfl
rw [stepRet, IH, bind_pure_comp]
| cons₂ ns k IH => rw [Cont.eval, stepRet]; exact IH
| comp f k IH =>
rw [Cont.eval, stepRet, code_is_ok]
simp only [← bind_pure_comp, bind_assoc]; congr; funext v'
rw [reaches_eval]; swap
· exact ReflTransGen.single rfl
rw [IH, bind_pure_comp]
| fix f k IH =>
rw [Cont.eval, stepRet]; simp only [bind_pure_comp]
split_ifs; · exact IH
simp only [← bind_pure_comp, bind_assoc, cont_eval_fix (code_is_ok _)]
congr; funext; rw [bind_pure_comp, ← IH]
exact reaches_eval (ReflTransGen.single rfl)
#align turing.to_partrec.step_ret_eval Turing.ToPartrec.stepRet_eval
end ToPartrec
/-!
## Simulating sequentialized partial recursive functions in TM2
At this point we have a sequential model of partial recursive functions: the `Cfg` type and
`step : Cfg → Option Cfg` function from the previous section. The key feature of this model is that
it does a finite amount of computation (in fact, an amount which is statically bounded by the size
of the program) between each step, and no individual step can diverge (unlike the compositional
semantics, where every sub-part of the computation is potentially divergent). So we can utilize the
same techniques as in the other TM simulations in `Computability.TuringMachine` to prove that
each step corresponds to a finite number of steps in a lower level model. (We don't prove it here,
but in anticipation of the complexity class P, the simulation is actually polynomial-time as well.)
The target model is `Turing.TM2`, which has a fixed finite set of stacks, a bit of local storage,
with programs selected from a potentially infinite (but finitely accessible) set of program
positions, or labels `Λ`, each of which executes a finite sequence of basic stack commands.
For this program we will need four stacks, each on an alphabet `Γ'` like so:
inductive Γ' | consₗ | cons | bit0 | bit1
We represent a number as a bit sequence, lists of numbers by putting `cons` after each element, and
lists of lists of natural numbers by putting `consₗ` after each list. For example:
0 ~> []
1 ~> [bit1]
6 ~> [bit0, bit1, bit1]
[1, 2] ~> [bit1, cons, bit0, bit1, cons]
[[], [1, 2]] ~> [consₗ, bit1, cons, bit0, bit1, cons, consₗ]
The four stacks are `main`, `rev`, `aux`, `stack`. In normal mode, `main` contains the input to the
current program (a `List ℕ`) and `stack` contains data (a `List (List ℕ)`) associated to the
current continuation, and in `ret` mode `main` contains the value that is being passed to the
continuation and `stack` contains the data for the continuation. The `rev` and `aux` stacks are
usually empty; `rev` is used to store reversed data when e.g. moving a value from one stack to
another, while `aux` is used as a temporary for a `main`/`stack` swap that happens during `cons₁`
evaluation.
The only local store we need is `Option Γ'`, which stores the result of the last pop
operation. (Most of our working data are natural numbers, which are too large to fit in the local
store.)
The continuations from the previous section are data-carrying, containing all the values that have
been computed and are awaiting other arguments. In order to have only a finite number of
continuations appear in the program so that they can be used in machine states, we separate the
data part (anything with type `List ℕ`) from the `Cont` type, producing a `Cont'` type that lacks
this information. The data is kept on the `stack` stack.
Because we want to have subroutines for e.g. moving an entire stack to another place, we use an
infinite inductive type `Λ'` so that we can execute a program and then return to do something else
without having to define too many different kinds of intermediate states. (We must nevertheless
prove that only finitely many labels are accessible.) The labels are:
* `move p k₁ k₂ q`: move elements from stack `k₁` to `k₂` while `p` holds of the value being moved.
The last element, that fails `p`, is placed in neither stack but left in the local store.
At the end of the operation, `k₂` will have the elements of `k₁` in reverse order. Then do `q`.
* `clear p k q`: delete elements from stack `k` until `p` is true. Like `move`, the last element is
left in the local storage. Then do `q`.
* `copy q`: Move all elements from `rev` to both `main` and `stack` (in reverse order),
then do `q`. That is, it takes `(a, b, c, d)` to `(b.reverse ++ a, [], c, b.reverse ++ d)`.
* `push k f q`: push `f s`, where `s` is the local store, to stack `k`, then do `q`. This is a
duplicate of the `push` instruction that is part of the TM2 model, but by having a subroutine
just for this purpose we can build up programs to execute inside a `goto` statement, where we
have the flexibility to be general recursive.
* `read (f : Option Γ' → Λ')`: go to state `f s` where `s` is the local store. Again this is only
here for convenience.
* `succ q`: perform a successor operation. Assuming `[n]` is encoded on `main` before,
`[n+1]` will be on main after. This implements successor for binary natural numbers.
* `pred q₁ q₂`: perform a predecessor operation or `case` statement. If `[]` is encoded on
`main` before, then we transition to `q₁` with `[]` on main; if `(0 :: v)` is on `main` before
then `v` will be on `main` after and we transition to `q₁`; and if `(n+1 :: v)` is on `main`
before then `n :: v` will be on `main` after and we transition to `q₂`.
* `ret k`: call continuation `k`. Each continuation has its own interpretation of the data in
`stack` and sets up the data for the next continuation.
* `ret (cons₁ fs k)`: `v :: KData` on `stack` and `ns` on `main`, and the next step expects
`v` on `main` and `ns :: KData` on `stack`. So we have to do a little dance here with six
reverse-moves using the `aux` stack to perform a three-point swap, each of which involves two
reversals.
* `ret (cons₂ k)`: `ns :: KData` is on `stack` and `v` is on `main`, and we have to put
`ns.headI :: v` on `main` and `KData` on `stack`. This is done using the `head` subroutine.
* `ret (fix f k)`: This stores no data, so we just check if `main` starts with `0` and
if so, remove it and call `k`, otherwise `clear` the first value and call `f`.
* `ret halt`: the stack is empty, and `main` has the output. Do nothing and halt.
In addition to these basic states, we define some additional subroutines that are used in the
above:
* `push'`, `peek'`, `pop'` are special versions of the builtins that use the local store to supply
inputs and outputs.
* `unrev`: special case `move false rev main` to move everything from `rev` back to `main`. Used as
a cleanup operation in several functions.
* `moveExcl p k₁ k₂ q`: same as `move` but pushes the last value read back onto the source stack.
* `move₂ p k₁ k₂ q`: double `move`, so that the result comes out in the right order at the target
stack. Implemented as `moveExcl p k rev; move false rev k₂`. Assumes that neither `k₁` nor `k₂`
is `rev` and `rev` is initially empty.
* `head k q`: get the first natural number from stack `k` and reverse-move it to `rev`, then clear
the rest of the list at `k` and then `unrev` to reverse-move the head value to `main`. This is
used with `k = main` to implement regular `head`, i.e. if `v` is on `main` before then `[v.headI]`
will be on `main` after; and also with `k = stack` for the `cons` operation, which has `v` on
`main` and `ns :: KData` on `stack`, and results in `KData` on `stack` and `ns.headI :: v` on
`main`.
* `trNormal` is the main entry point, defining states that perform a given `code` computation.
It mostly just dispatches to functions written above.
The main theorem of this section is `tr_eval`, which asserts that for each that for each code `c`,
the state `init c v` steps to `halt v'` in finitely many steps if and only if
`Code.eval c v = some v'`.
-/
set_option linter.uppercaseLean3 false
namespace PartrecToTM2
section
open ToPartrec
/-- The alphabet for the stacks in the program. `bit0` and `bit1` are used to represent `ℕ` values
as lists of binary digits, `cons` is used to separate `List ℕ` values, and `consₗ` is used to
separate `List (List ℕ)` values. See the section documentation. -/
inductive Γ'
| consₗ
| cons
| bit0
| bit1
deriving DecidableEq, Inhabited, Fintype
#align turing.partrec_to_TM2.Γ' Turing.PartrecToTM2.Γ'
#align turing.partrec_to_TM2.Γ'.Cons Turing.PartrecToTM2.Γ'.consₗ
#align turing.partrec_to_TM2.Γ'.cons Turing.PartrecToTM2.Γ'.cons
#align turing.partrec_to_TM2.Γ'.bit0 Turing.PartrecToTM2.Γ'.bit0
#align turing.partrec_to_TM2.Γ'.bit1 Turing.PartrecToTM2.Γ'.bit1
/-- The four stacks used by the program. `main` is used to store the input value in `trNormal`
mode and the output value in `Λ'.ret` mode, while `stack` is used to keep all the data for the
continuations. `rev` is used to store reversed lists when transferring values between stacks, and
`aux` is only used once in `cons₁`. See the section documentation. -/
inductive K'
| main
| rev
| aux
| stack
deriving DecidableEq, Inhabited
#align turing.partrec_to_TM2.K' Turing.PartrecToTM2.K'
#align turing.partrec_to_TM2.K'.main Turing.PartrecToTM2.K'.main
#align turing.partrec_to_TM2.K'.rev Turing.PartrecToTM2.K'.rev
#align turing.partrec_to_TM2.K'.aux Turing.PartrecToTM2.K'.aux
#align turing.partrec_to_TM2.K'.stack Turing.PartrecToTM2.K'.stack
open K'
/-- Continuations as in `ToPartrec.Cont` but with the data removed. This is done because we want
the set of all continuations in the program to be finite (so that it can ultimately be encoded into
the finite state machine of a Turing machine), but a continuation can handle a potentially infinite
number of data values during execution. -/
inductive Cont'
| halt
| cons₁ : Code → Cont' → Cont'
| cons₂ : Cont' → Cont'
| comp : Code → Cont' → Cont'
| fix : Code → Cont' → Cont'
deriving DecidableEq, Inhabited
#align turing.partrec_to_TM2.cont' Turing.PartrecToTM2.Cont'
#align turing.partrec_to_TM2.cont'.halt Turing.PartrecToTM2.Cont'.halt
#align turing.partrec_to_TM2.cont'.cons₁ Turing.PartrecToTM2.Cont'.cons₁
#align turing.partrec_to_TM2.cont'.cons₂ Turing.PartrecToTM2.Cont'.cons₂
#align turing.partrec_to_TM2.cont'.comp Turing.PartrecToTM2.Cont'.comp
#align turing.partrec_to_TM2.cont'.fix Turing.PartrecToTM2.Cont'.fix
/-- The set of program positions. We make extensive use of inductive types here to let us describe
"subroutines"; for example `clear p k q` is a program that clears stack `k`, then does `q` where
`q` is another label. In order to prevent this from resulting in an infinite number of distinct
accessible states, we are careful to be non-recursive (although loops are okay). See the section
documentation for a description of all the programs. -/
inductive Λ'
| move (p : Γ' → Bool) (k₁ k₂ : K') (q : Λ')
| clear (p : Γ' → Bool) (k : K') (q : Λ')
| copy (q : Λ')
| push (k : K') (s : Option Γ' → Option Γ') (q : Λ')
| read (f : Option Γ' → Λ')
| succ (q : Λ')
| pred (q₁ q₂ : Λ')
| ret (k : Cont')
#align turing.partrec_to_TM2.Λ' Turing.PartrecToTM2.Λ'
#align turing.partrec_to_TM2.Λ'.move Turing.PartrecToTM2.Λ'.move
#align turing.partrec_to_TM2.Λ'.clear Turing.PartrecToTM2.Λ'.clear
#align turing.partrec_to_TM2.Λ'.copy Turing.PartrecToTM2.Λ'.copy
#align turing.partrec_to_TM2.Λ'.push Turing.PartrecToTM2.Λ'.push
#align turing.partrec_to_TM2.Λ'.read Turing.PartrecToTM2.Λ'.read
#align turing.partrec_to_TM2.Λ'.succ Turing.PartrecToTM2.Λ'.succ
#align turing.partrec_to_TM2.Λ'.pred Turing.PartrecToTM2.Λ'.pred
#align turing.partrec_to_TM2.Λ'.ret Turing.PartrecToTM2.Λ'.ret
-- Porting note: `Turing.PartrecToTM2.Λ'.rec` is noncomputable in Lean4, so we make it computable.
compile_inductive% Code
compile_inductive% Cont'
compile_inductive% K'
compile_inductive% Λ'
instance Λ'.instInhabited : Inhabited Λ' :=
⟨Λ'.ret Cont'.halt⟩
#align turing.partrec_to_TM2.Λ'.inhabited Turing.PartrecToTM2.Λ'.instInhabited
instance Λ'.instDecidableEq : DecidableEq Λ' := fun a b => by
induction a generalizing b <;> cases b <;> first
| apply Decidable.isFalse; rintro ⟨⟨⟩⟩; done
| exact decidable_of_iff' _ (by simp [Function.funext_iff]; rfl)
#align turing.partrec_to_TM2.Λ'.decidable_eq Turing.PartrecToTM2.Λ'.instDecidableEq
/-- The type of TM2 statements used by this machine. -/
def Stmt' :=
TM2.Stmt (fun _ : K' => Γ') Λ' (Option Γ') deriving Inhabited
#align turing.partrec_to_TM2.stmt' Turing.PartrecToTM2.Stmt'
/-- The type of TM2 configurations used by this machine. -/
def Cfg' :=
TM2.Cfg (fun _ : K' => Γ') Λ' (Option Γ') deriving Inhabited
#align turing.partrec_to_TM2.cfg' Turing.PartrecToTM2.Cfg'
open TM2.Stmt
/-- A predicate that detects the end of a natural number, either `Γ'.cons` or `Γ'.consₗ` (or
implicitly the end of the list), for use in predicate-taking functions like `move` and `clear`. -/
@[simp]
def natEnd : Γ' → Bool
| Γ'.consₗ => true
| Γ'.cons => true
| _ => false
#align turing.partrec_to_TM2.nat_end Turing.PartrecToTM2.natEnd
/-- Pop a value from the stack and place the result in local store. -/
@[simp]
def pop' (k : K') : Stmt' → Stmt' :=
pop k fun _ v => v
#align turing.partrec_to_TM2.pop' Turing.PartrecToTM2.pop'
/-- Peek a value from the stack and place the result in local store. -/
@[simp]
def peek' (k : K') : Stmt' → Stmt' :=
peek k fun _ v => v
#align turing.partrec_to_TM2.peek' Turing.PartrecToTM2.peek'
/-- Push the value in the local store to the given stack. -/
@[simp]
def push' (k : K') : Stmt' → Stmt' :=
push k fun x => x.iget
#align turing.partrec_to_TM2.push' Turing.PartrecToTM2.push'
/-- Move everything from the `rev` stack to the `main` stack (reversed). -/
def unrev :=
Λ'.move (fun _ => false) rev main
#align turing.partrec_to_TM2.unrev Turing.PartrecToTM2.unrev
/-- Move elements from `k₁` to `k₂` while `p` holds, with the last element being left on `k₁`. -/
def moveExcl (p k₁ k₂ q) :=
Λ'.move p k₁ k₂ <| Λ'.push k₁ id q
#align turing.partrec_to_TM2.move_excl Turing.PartrecToTM2.moveExcl
/-- Move elements from `k₁` to `k₂` without reversion, by performing a double move via the `rev`
stack. -/
def move₂ (p k₁ k₂ q) :=
moveExcl p k₁ rev <| Λ'.move (fun _ => false) rev k₂ q
#align turing.partrec_to_TM2.move₂ Turing.PartrecToTM2.move₂
/-- Assuming `trList v` is on the front of stack `k`, remove it, and push `v.headI` onto `main`.
See the section documentation. -/
def head (k : K') (q : Λ') : Λ' :=
Λ'.move natEnd k rev <|
(Λ'.push rev fun _ => some Γ'.cons) <|
Λ'.read fun s =>
(if s = some Γ'.consₗ then id else Λ'.clear (fun x => x = Γ'.consₗ) k) <| unrev q
#align turing.partrec_to_TM2.head Turing.PartrecToTM2.head
/-- The program that evaluates code `c` with continuation `k`. This expects an initial state where
`trList v` is on `main`, `trContStack k` is on `stack`, and `aux` and `rev` are empty.
See the section documentation for details. -/
@[simp]
def trNormal : Code → Cont' → Λ'
| Code.zero', k => (Λ'.push main fun _ => some Γ'.cons) <| Λ'.ret k
| Code.succ, k => head main <| Λ'.succ <| Λ'.ret k
| Code.tail, k => Λ'.clear natEnd main <| Λ'.ret k
| Code.cons f fs, k =>
(Λ'.push stack fun _ => some Γ'.consₗ) <|
Λ'.move (fun _ => false) main rev <| Λ'.copy <| trNormal f (Cont'.cons₁ fs k)
| Code.comp f g, k => trNormal g (Cont'.comp f k)
| Code.case f g, k => Λ'.pred (trNormal f k) (trNormal g k)
| Code.fix f, k => trNormal f (Cont'.fix f k)
#align turing.partrec_to_TM2.tr_normal Turing.PartrecToTM2.trNormal
/-- The main program. See the section documentation for details. -/
def tr : Λ' → Stmt'
| Λ'.move p k₁ k₂ q =>
pop' k₁ <|
branch (fun s => s.elim true p) (goto fun _ => q)
(push' k₂ <| goto fun _ => Λ'.move p k₁ k₂ q)
| Λ'.push k f q =>
branch (fun s => (f s).isSome) ((push k fun s => (f s).iget) <| goto fun _ => q)
(goto fun _ => q)
| Λ'.read q => goto q
| Λ'.clear p k q =>
pop' k <| branch (fun s => s.elim true p) (goto fun _ => q) (goto fun _ => Λ'.clear p k q)
| Λ'.copy q =>
pop' rev <|
branch Option.isSome (push' main <| push' stack <| goto fun _ => Λ'.copy q) (goto fun _ => q)
| Λ'.succ q =>
pop' main <|
branch (fun s => s = some Γ'.bit1) ((push rev fun _ => Γ'.bit0) <| goto fun _ => Λ'.succ q) <|
branch (fun s => s = some Γ'.cons)
((push main fun _ => Γ'.cons) <| (push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)
((push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)
| Λ'.pred q₁ q₂ =>
pop' main <|
branch (fun s => s = some Γ'.bit0)
((push rev fun _ => Γ'.bit1) <| goto fun _ => Λ'.pred q₁ q₂) <|
branch (fun s => natEnd s.iget) (goto fun _ => q₁)
(peek' main <|
branch (fun s => natEnd s.iget) (goto fun _ => unrev q₂)
((push rev fun _ => Γ'.bit0) <| goto fun _ => unrev q₂))
| Λ'.ret (Cont'.cons₁ fs k) =>
goto fun _ =>
move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k)
| Λ'.ret (Cont'.cons₂ k) => goto fun _ => head stack <| Λ'.ret k
| Λ'.ret (Cont'.comp f k) => goto fun _ => trNormal f k
| Λ'.ret (Cont'.fix f k) =>
pop' main <|
goto fun s =>
cond (natEnd s.iget) (Λ'.ret k) <| Λ'.clear natEnd main <| trNormal f (Cont'.fix f k)
| Λ'.ret Cont'.halt => (load fun _ => none) <| halt
#align turing.partrec_to_TM2.tr Turing.PartrecToTM2.tr
/- Porting note: The equation lemma of `tr` simplifies to `match` structures. To prevent this,
we replace equation lemmas of `tr`. -/
theorem tr_move (p k₁ k₂ q) : tr (Λ'.move p k₁ k₂ q) =
pop' k₁ (branch (fun s => s.elim true p) (goto fun _ => q)
(push' k₂ <| goto fun _ => Λ'.move p k₁ k₂ q)) := rfl
theorem tr_push (k f q) : tr (Λ'.push k f q) = branch (fun s => (f s).isSome)
((push k fun s => (f s).iget) <| goto fun _ => q) (goto fun _ => q) := rfl
theorem tr_read (q) : tr (Λ'.read q) = goto q := rfl
theorem tr_clear (p k q) : tr (Λ'.clear p k q) = pop' k (branch
(fun s => s.elim true p) (goto fun _ => q) (goto fun _ => Λ'.clear p k q)) := rfl
theorem tr_copy (q) : tr (Λ'.copy q) = pop' rev (branch Option.isSome
(push' main <| push' stack <| goto fun _ => Λ'.copy q) (goto fun _ => q)) := rfl
theorem tr_succ (q) : tr (Λ'.succ q) = pop' main (branch (fun s => s = some Γ'.bit1)
((push rev fun _ => Γ'.bit0) <| goto fun _ => Λ'.succ q) <|
branch (fun s => s = some Γ'.cons)
((push main fun _ => Γ'.cons) <| (push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)
((push main fun _ => Γ'.bit1) <| goto fun _ => unrev q)) := rfl
theorem tr_pred (q₁ q₂) : tr (Λ'.pred q₁ q₂) = pop' main (branch (fun s => s = some Γ'.bit0)
((push rev fun _ => Γ'.bit1) <| goto fun _ => Λ'.pred q₁ q₂) <|
branch (fun s => natEnd s.iget) (goto fun _ => q₁)
(peek' main <|
branch (fun s => natEnd s.iget) (goto fun _ => unrev q₂)
((push rev fun _ => Γ'.bit0) <| goto fun _ => unrev q₂))) := rfl
theorem tr_ret_cons₁ (fs k) : tr (Λ'.ret (Cont'.cons₁ fs k)) = goto fun _ =>
move₂ (fun _ => false) main aux <|
move₂ (fun s => s = Γ'.consₗ) stack main <|
move₂ (fun _ => false) aux stack <| trNormal fs (Cont'.cons₂ k) := rfl
theorem tr_ret_cons₂ (k) : tr (Λ'.ret (Cont'.cons₂ k)) =
goto fun _ => head stack <| Λ'.ret k := rfl
theorem tr_ret_comp (f k) : tr (Λ'.ret (Cont'.comp f k)) = goto fun _ => trNormal f k := rfl
theorem tr_ret_fix (f k) : tr (Λ'.ret (Cont'.fix f k)) = pop' main (goto fun s =>
cond (natEnd s.iget) (Λ'.ret k) <| Λ'.clear natEnd main <| trNormal f (Cont'.fix f k)) := rfl
theorem tr_ret_halt : tr (Λ'.ret Cont'.halt) = (load fun _ => none) halt := rfl
attribute
[eqns tr_move tr_push tr_read tr_clear tr_copy tr_succ tr_pred tr_ret_cons₁
tr_ret_cons₂ tr_ret_comp tr_ret_fix tr_ret_halt] tr
attribute [simp] tr
/-- Translating a `Cont` continuation to a `Cont'` continuation simply entails dropping all the
data. This data is instead encoded in `trContStack` in the configuration. -/
def trCont : Cont → Cont'
| Cont.halt => Cont'.halt
| Cont.cons₁ c _ k => Cont'.cons₁ c (trCont k)
| Cont.cons₂ _ k => Cont'.cons₂ (trCont k)
| Cont.comp c k => Cont'.comp c (trCont k)
| Cont.fix c k => Cont'.fix c (trCont k)
#align turing.partrec_to_TM2.tr_cont Turing.PartrecToTM2.trCont
/-- We use `PosNum` to define the translation of binary natural numbers. A natural number is
represented as a little-endian list of `bit0` and `bit1` elements:
1 = [bit1]
2 = [bit0, bit1]
3 = [bit1, bit1]
4 = [bit0, bit0, bit1]
In particular, this representation guarantees no trailing `bit0`'s at the end of the list. -/
def trPosNum : PosNum → List Γ'
| PosNum.one => [Γ'.bit1]
| PosNum.bit0 n => Γ'.bit0 :: trPosNum n
| PosNum.bit1 n => Γ'.bit1 :: trPosNum n
#align turing.partrec_to_TM2.tr_pos_num Turing.PartrecToTM2.trPosNum
/-- We use `Num` to define the translation of binary natural numbers. Positive numbers are
translated using `trPosNum`, and `trNum 0 = []`. So there are never any trailing `bit0`'s in
a translated `Num`.
0 = []
1 = [bit1]
2 = [bit0, bit1]
3 = [bit1, bit1]
4 = [bit0, bit0, bit1]
-/
def trNum : Num → List Γ'
| Num.zero => []
| Num.pos n => trPosNum n
#align turing.partrec_to_TM2.tr_num Turing.PartrecToTM2.trNum
/-- Because we use binary encoding, we define `trNat` in terms of `trNum`, using `Num`, which are
binary natural numbers. (We could also use `Nat.binaryRecOn`, but `Num` and `PosNum` make for
easy inductions.) -/
def trNat (n : ℕ) : List Γ' :=
trNum n
#align turing.partrec_to_TM2.tr_nat Turing.PartrecToTM2.trNat
@[simp]
theorem trNat_zero : trNat 0 = [] := by rw [trNat, Nat.cast_zero]; rfl
#align turing.partrec_to_TM2.tr_nat_zero Turing.PartrecToTM2.trNat_zero
theorem trNat_default : trNat default = [] :=
trNat_zero
#align turing.partrec_to_TM2.tr_nat_default Turing.PartrecToTM2.trNat_default
/-- Lists are translated with a `cons` after each encoded number.
For example:
[] = []
[0] = [cons]
[1] = [bit1, cons]
[6, 0] = [bit0, bit1, bit1, cons, cons]
-/
@[simp]
def trList : List ℕ → List Γ'
| [] => []
| n::ns => trNat n ++ Γ'.cons :: trList ns
#align turing.partrec_to_TM2.tr_list Turing.PartrecToTM2.trList
/-- Lists of lists are translated with a `consₗ` after each encoded list.
For example:
[] = []
[[]] = [consₗ]
[[], []] = [consₗ, consₗ]
[[0]] = [cons, consₗ]
[[1, 2], [0]] = [bit1, cons, bit0, bit1, cons, consₗ, cons, consₗ]
-/
@[simp]
def trLList : List (List ℕ) → List Γ'
| [] => []
| l::ls => trList l ++ Γ'.consₗ :: trLList ls
#align turing.partrec_to_TM2.tr_llist Turing.PartrecToTM2.trLList
/-- The data part of a continuation is a list of lists, which is encoded on the `stack` stack
using `trLList`. -/
@[simp]
def contStack : Cont → List (List ℕ)
| Cont.halt => []
| Cont.cons₁ _ ns k => ns :: contStack k
| Cont.cons₂ ns k => ns :: contStack k
| Cont.comp _ k => contStack k
| Cont.fix _ k => contStack k
#align turing.partrec_to_TM2.cont_stack Turing.PartrecToTM2.contStack
/-- The data part of a continuation is a list of lists, which is encoded on the `stack` stack
using `trLList`. -/
def trContStack (k : Cont) :=
trLList (contStack k)
#align turing.partrec_to_TM2.tr_cont_stack Turing.PartrecToTM2.trContStack
/-- This is the nondependent eliminator for `K'`, but we use it specifically here in order to
represent the stack data as four lists rather than as a function `K' → List Γ'`, because this makes
rewrites easier. The theorems `K'.elim_update_main` et. al. show how such a function is updated
after an `update` to one of the components. -/
def K'.elim (a b c d : List Γ') : K' → List Γ'
| K'.main => a
| K'.rev => b
| K'.aux => c
| K'.stack => d
#align turing.partrec_to_TM2.K'.elim Turing.PartrecToTM2.K'.elim
-- The equation lemma of `elim` simplifies to `match` structures.
theorem K'.elim_main (a b c d) : K'.elim a b c d K'.main = a := rfl
theorem K'.elim_rev (a b c d) : K'.elim a b c d K'.rev = b := rfl
theorem K'.elim_aux (a b c d) : K'.elim a b c d K'.aux = c := rfl
theorem K'.elim_stack (a b c d) : K'.elim a b c d K'.stack = d := rfl
attribute [simp] K'.elim
@[simp]
theorem K'.elim_update_main {a b c d a'} : update (K'.elim a b c d) main a' = K'.elim a' b c d := by
funext x; cases x <;> rfl
#align turing.partrec_to_TM2.K'.elim_update_main Turing.PartrecToTM2.K'.elim_update_main
@[simp]
theorem K'.elim_update_rev {a b c d b'} : update (K'.elim a b c d) rev b' = K'.elim a b' c d := by
funext x; cases x <;> rfl
#align turing.partrec_to_TM2.K'.elim_update_rev Turing.PartrecToTM2.K'.elim_update_rev
@[simp]
theorem K'.elim_update_aux {a b c d c'} : update (K'.elim a b c d) aux c' = K'.elim a b c' d := by
funext x; cases x <;> rfl
#align turing.partrec_to_TM2.K'.elim_update_aux Turing.PartrecToTM2.K'.elim_update_aux
@[simp]
theorem K'.elim_update_stack {a b c d d'} :
update (K'.elim a b c d) stack d' = K'.elim a b c d' := by funext x; cases x <;> rfl
#align turing.partrec_to_TM2.K'.elim_update_stack Turing.PartrecToTM2.K'.elim_update_stack
/-- The halting state corresponding to a `List ℕ` output value. -/
def halt (v : List ℕ) : Cfg' :=
⟨none, none, K'.elim (trList v) [] [] []⟩
#align turing.partrec_to_TM2.halt Turing.PartrecToTM2.halt
/-- The `Cfg` states map to `Cfg'` states almost one to one, except that in normal operation the
local store contains an arbitrary garbage value. To make the final theorem cleaner we explicitly
clear it in the halt state so that there is exactly one configuration corresponding to output `v`.
-/
def TrCfg : Cfg → Cfg' → Prop
| Cfg.ret k v, c' =>
∃ s, c' = ⟨some (Λ'.ret (trCont k)), s, K'.elim (trList v) [] [] (trContStack k)⟩
| Cfg.halt v, c' => c' = halt v
#align turing.partrec_to_TM2.tr_cfg Turing.PartrecToTM2.TrCfg
/-- This could be a general list definition, but it is also somewhat specialized to this
application. `splitAtPred p L` will search `L` for the first element satisfying `p`.
If it is found, say `L = l₁ ++ a :: l₂` where `a` satisfies `p` but `l₁` does not, then it returns
`(l₁, some a, l₂)`. Otherwise, if there is no such element, it returns `(L, none, [])`. -/
def splitAtPred {α} (p : α → Bool) : List α → List α × Option α × List α
| [] => ([], none, [])
| a :: as =>
cond (p a) ([], some a, as) <|
let ⟨l₁, o, l₂⟩ := splitAtPred p as
⟨a::l₁, o, l₂⟩
#align turing.partrec_to_TM2.split_at_pred Turing.PartrecToTM2.splitAtPred
theorem splitAtPred_eq {α} (p : α → Bool) :
∀ L l₁ o l₂,
(∀ x ∈ l₁, p x = false) →
Option.elim' (L = l₁ ∧ l₂ = []) (fun a => p a = true ∧ L = l₁ ++ a::l₂) o →
splitAtPred p L = (l₁, o, l₂)
| [], _, none, _, _, ⟨rfl, rfl⟩ => rfl
| [], l₁, some o, l₂, _, ⟨_, h₃⟩ => by simp at h₃
| a :: L, l₁, o, l₂, h₁, h₂ => by
rw [splitAtPred]
have IH := splitAtPred_eq p L
cases' o with o
· cases' l₁ with a' l₁ <;> rcases h₂ with ⟨⟨⟩, rfl⟩
rw [h₁ a (List.Mem.head _), cond, IH L none [] _ ⟨rfl, rfl⟩]
exact fun x h => h₁ x (List.Mem.tail _ h)
· cases' l₁ with a' l₁ <;> rcases h₂ with ⟨h₂, ⟨⟩⟩
· rw [h₂, cond]
rw [h₁ a (List.Mem.head _), cond, IH l₁ (some o) l₂ _ ⟨h₂, _⟩] <;> try rfl
exact fun x h => h₁ x (List.Mem.tail _ h)
#align turing.partrec_to_TM2.split_at_pred_eq Turing.PartrecToTM2.splitAtPred_eq
theorem splitAtPred_false {α} (L : List α) : splitAtPred (fun _ => false) L = (L, none, []) :=
splitAtPred_eq _ _ _ _ _ (fun _ _ => rfl) ⟨rfl, rfl⟩
#align turing.partrec_to_TM2.split_at_pred_ff Turing.PartrecToTM2.splitAtPred_false
theorem move_ok {p k₁ k₂ q s L₁ o L₂} {S : K' → List Γ'} (h₁ : k₁ ≠ k₂)
(e : splitAtPred p (S k₁) = (L₁, o, L₂)) :
Reaches₁ (TM2.step tr) ⟨some (Λ'.move p k₁ k₂ q), s, S⟩
⟨some q, o, update (update S k₁ L₂) k₂ (L₁.reverseAux (S k₂))⟩ := by
induction' L₁ with a L₁ IH generalizing S s
· rw [(_ : [].reverseAux _ = _), Function.update_eq_self]
swap
· rw [Function.update_noteq h₁.symm, List.reverseAux_nil]
refine TransGen.head' rfl ?_
simp only [TM2.step, Option.mem_def, TM2.stepAux, Option.elim, ne_eq]
revert e; cases' S k₁ with a Sk <;> intro e
· cases e
rfl
simp only [splitAtPred, Option.elim, List.head?, List.tail_cons, Option.iget_some] at e ⊢
revert e; cases p a <;> intro e <;>
simp only [cond_false, cond_true, Prod.mk.injEq, true_and, false_and] at e ⊢
simp only [e]
rfl
· refine TransGen.head rfl ?_
simp only [TM2.step, Option.mem_def, TM2.stepAux, Option.elim, ne_eq, List.reverseAux_cons]
cases' e₁ : S k₁ with a' Sk <;> rw [e₁, splitAtPred] at e
· cases e
cases e₂ : p a' <;> simp only [e₂, cond] at e
swap
· cases e
rcases e₃ : splitAtPred p Sk with ⟨_, _, _⟩
rw [e₃] at e
cases e
simp only [List.head?_cons, e₂, List.tail_cons, ne_eq, cond_false]
convert @IH _ (update (update S k₁ Sk) k₂ (a :: S k₂)) _ using 2 <;>
simp [Function.update_noteq, h₁, h₁.symm, e₃, List.reverseAux]
simp [Function.update_comm h₁.symm]
#align turing.partrec_to_TM2.move_ok Turing.PartrecToTM2.move_ok
theorem unrev_ok {q s} {S : K' → List Γ'} :
Reaches₁ (TM2.step tr) ⟨some (unrev q), s, S⟩
⟨some q, none, update (update S rev []) main (List.reverseAux (S rev) (S main))⟩ :=
move_ok (by decide) <| splitAtPred_false _
#align turing.partrec_to_TM2.unrev_ok Turing.PartrecToTM2.unrev_ok
| Mathlib/Computability/TMToPartrec.lean | 1,370 | 1,390 | theorem move₂_ok {p k₁ k₂ q s L₁ o L₂} {S : K' → List Γ'} (h₁ : k₁ ≠ rev ∧ k₂ ≠ rev ∧ k₁ ≠ k₂)
(h₂ : S rev = []) (e : splitAtPred p (S k₁) = (L₁, o, L₂)) :
Reaches₁ (TM2.step tr) ⟨some (move₂ p k₁ k₂ q), s, S⟩
⟨some q, none, update (update S k₁ (o.elim id List.cons L₂)) k₂ (L₁ ++ S k₂)⟩ := by |
refine (move_ok h₁.1 e).trans (TransGen.head rfl ?_)
simp only [TM2.step, Option.mem_def, TM2.stepAux, id_eq, ne_eq, Option.elim]
cases o <;> simp only [Option.elim, id]
· simp only [TM2.stepAux, Option.isSome, cond_false]
convert move_ok h₁.2.1.symm (splitAtPred_false _) using 2
simp only [Function.update_comm h₁.1, Function.update_idem]
rw [show update S rev [] = S by rw [← h₂, Function.update_eq_self]]
simp only [Function.update_noteq h₁.2.2.symm, Function.update_noteq h₁.2.1,
Function.update_noteq h₁.1.symm, List.reverseAux_eq, h₂, Function.update_same,
List.append_nil, List.reverse_reverse]
· simp only [TM2.stepAux, Option.isSome, cond_true]
convert move_ok h₁.2.1.symm (splitAtPred_false _) using 2
simp only [h₂, Function.update_comm h₁.1, List.reverseAux_eq, Function.update_same,
List.append_nil, Function.update_idem]
rw [show update S rev [] = S by rw [← h₂, Function.update_eq_self]]
simp only [Function.update_noteq h₁.1.symm, Function.update_noteq h₁.2.2.symm,
Function.update_noteq h₁.2.1, Function.update_same, List.reverse_reverse]
|
/-
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.ModelTheory.Basic
#align_import model_theory.language_map from "leanprover-community/mathlib"@"b3951c65c6e797ff162ae8b69eab0063bcfb3d73"
/-!
# Language Maps
Maps between first-order languages in the style of the
[Flypitch project](https://flypitch.github.io/), as well as several important maps between
structures.
## Main Definitions
* A `FirstOrder.Language.LHom`, denoted `L →ᴸ L'`, is a map between languages, sending the symbols
of one to symbols of the same kind and arity in the other.
* A `FirstOrder.Language.LEquiv`, denoted `L ≃ᴸ L'`, is an invertible language homomorphism.
* `FirstOrder.Language.withConstants` is defined so that if `M` is an `L.Structure` and
`A : Set M`, `L.withConstants A`, denoted `L[[A]]`, is a language which adds constant symbols for
elements of `A` to `L`.
## 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'
namespace FirstOrder
set_option linter.uppercaseLean3 false
namespace Language
open Structure Cardinal
open Cardinal
variable (L : Language.{u, v}) (L' : Language.{u', v'}) {M : Type w} [L.Structure M]
/-- A language homomorphism maps the symbols of one language to symbols of another. -/
structure LHom where
onFunction : ∀ ⦃n⦄, L.Functions n → L'.Functions n
onRelation : ∀ ⦃n⦄, L.Relations n → L'.Relations n
#align first_order.language.Lhom FirstOrder.Language.LHom
@[inherit_doc FirstOrder.Language.LHom]
infixl:10 " →ᴸ " => LHom
-- \^L
variable {L L'}
namespace LHom
/-- Defines a map between languages defined with `Language.mk₂`. -/
protected def mk₂ {c f₁ f₂ : Type u} {r₁ r₂ : Type v} (φ₀ : c → L'.Constants)
(φ₁ : f₁ → L'.Functions 1) (φ₂ : f₂ → L'.Functions 2) (φ₁' : r₁ → L'.Relations 1)
(φ₂' : r₂ → L'.Relations 2) : Language.mk₂ c f₁ f₂ r₁ r₂ →ᴸ L' :=
⟨fun n =>
Nat.casesOn n φ₀ fun n => Nat.casesOn n φ₁ fun n => Nat.casesOn n φ₂ fun _ => PEmpty.elim,
fun n =>
Nat.casesOn n PEmpty.elim fun n =>
Nat.casesOn n φ₁' fun n => Nat.casesOn n φ₂' fun _ => PEmpty.elim⟩
#align first_order.language.Lhom.mk₂ FirstOrder.Language.LHom.mk₂
variable (ϕ : L →ᴸ L')
/-- Pulls a structure back along a language map. -/
def reduct (M : Type*) [L'.Structure M] : L.Structure M where
funMap f xs := funMap (ϕ.onFunction f) xs
RelMap r xs := RelMap (ϕ.onRelation r) xs
#align first_order.language.Lhom.reduct FirstOrder.Language.LHom.reduct
/-- The identity language homomorphism. -/
@[simps]
protected def id (L : Language) : L →ᴸ L :=
⟨fun _n => id, fun _n => id⟩
#align first_order.language.Lhom.id FirstOrder.Language.LHom.id
instance : Inhabited (L →ᴸ L) :=
⟨LHom.id L⟩
/-- The inclusion of the left factor into the sum of two languages. -/
@[simps]
protected def sumInl : L →ᴸ L.sum L' :=
⟨fun _n => Sum.inl, fun _n => Sum.inl⟩
#align first_order.language.Lhom.sum_inl FirstOrder.Language.LHom.sumInl
/-- The inclusion of the right factor into the sum of two languages. -/
@[simps]
protected def sumInr : L' →ᴸ L.sum L' :=
⟨fun _n => Sum.inr, fun _n => Sum.inr⟩
#align first_order.language.Lhom.sum_inr FirstOrder.Language.LHom.sumInr
variable (L L')
/-- The inclusion of an empty language into any other language. -/
@[simps]
protected def ofIsEmpty [L.IsAlgebraic] [L.IsRelational] : L →ᴸ L' :=
⟨fun n => (IsRelational.empty_functions n).elim, fun n => (IsAlgebraic.empty_relations n).elim⟩
#align first_order.language.Lhom.of_is_empty FirstOrder.Language.LHom.ofIsEmpty
variable {L L'} {L'' : Language}
@[ext]
protected theorem funext {F G : L →ᴸ L'} (h_fun : F.onFunction = G.onFunction)
(h_rel : F.onRelation = G.onRelation) : F = G := by
cases' F with Ff Fr
cases' G with Gf Gr
simp only [mk.injEq]
exact And.intro h_fun h_rel
#align first_order.language.Lhom.funext FirstOrder.Language.LHom.funext
instance [L.IsAlgebraic] [L.IsRelational] : Unique (L →ᴸ L') :=
⟨⟨LHom.ofIsEmpty L L'⟩, fun _ => LHom.funext (Subsingleton.elim _ _) (Subsingleton.elim _ _)⟩
theorem mk₂_funext {c f₁ f₂ : Type u} {r₁ r₂ : Type v} {F G : Language.mk₂ c f₁ f₂ r₁ r₂ →ᴸ L'}
(h0 : ∀ c : (Language.mk₂ c f₁ f₂ r₁ r₂).Constants, F.onFunction c = G.onFunction c)
(h1 : ∀ f : (Language.mk₂ c f₁ f₂ r₁ r₂).Functions 1, F.onFunction f = G.onFunction f)
(h2 : ∀ f : (Language.mk₂ c f₁ f₂ r₁ r₂).Functions 2, F.onFunction f = G.onFunction f)
(h1' : ∀ r : (Language.mk₂ c f₁ f₂ r₁ r₂).Relations 1, F.onRelation r = G.onRelation r)
(h2' : ∀ r : (Language.mk₂ c f₁ f₂ r₁ r₂).Relations 2, F.onRelation r = G.onRelation r) :
F = G :=
LHom.funext
(funext fun n =>
Nat.casesOn n (funext h0) fun n =>
Nat.casesOn n (funext h1) fun n =>
Nat.casesOn n (funext h2) fun _n => funext fun f => PEmpty.elim f)
(funext fun n =>
Nat.casesOn n (funext fun r => PEmpty.elim r) fun n =>
Nat.casesOn n (funext h1') fun n =>
Nat.casesOn n (funext h2') fun _n => funext fun r => PEmpty.elim r)
#align first_order.language.Lhom.mk₂_funext FirstOrder.Language.LHom.mk₂_funext
/-- The composition of two language homomorphisms. -/
@[simps]
def comp (g : L' →ᴸ L'') (f : L →ᴸ L') : L →ᴸ L'' :=
⟨fun _n F => g.1 (f.1 F), fun _ R => g.2 (f.2 R)⟩
#align first_order.language.Lhom.comp FirstOrder.Language.LHom.comp
-- Porting note: added ᴸ to avoid clash with function composition
@[inherit_doc]
local infixl:60 " ∘ᴸ " => LHom.comp
@[simp]
theorem id_comp (F : L →ᴸ L') : LHom.id L' ∘ᴸ F = F := by
cases F
rfl
#align first_order.language.Lhom.id_comp FirstOrder.Language.LHom.id_comp
@[simp]
theorem comp_id (F : L →ᴸ L') : F ∘ᴸ LHom.id L = F := by
cases F
rfl
#align first_order.language.Lhom.comp_id FirstOrder.Language.LHom.comp_id
theorem comp_assoc {L3 : Language} (F : L'' →ᴸ L3) (G : L' →ᴸ L'') (H : L →ᴸ L') :
F ∘ᴸ G ∘ᴸ H = F ∘ᴸ (G ∘ᴸ H) :=
rfl
#align first_order.language.Lhom.comp_assoc FirstOrder.Language.LHom.comp_assoc
section SumElim
variable (ψ : L'' →ᴸ L')
/-- A language map defined on two factors of a sum. -/
@[simps]
protected def sumElim : L.sum L'' →ᴸ L' where
onFunction _n := Sum.elim (fun f => ϕ.onFunction f) fun f => ψ.onFunction f
onRelation _n := Sum.elim (fun f => ϕ.onRelation f) fun f => ψ.onRelation f
#align first_order.language.Lhom.sum_elim FirstOrder.Language.LHom.sumElim
theorem sumElim_comp_inl (ψ : L'' →ᴸ L') : ϕ.sumElim ψ ∘ᴸ LHom.sumInl = ϕ :=
LHom.funext (funext fun _ => rfl) (funext fun _ => rfl)
#align first_order.language.Lhom.sum_elim_comp_inl FirstOrder.Language.LHom.sumElim_comp_inl
theorem sumElim_comp_inr (ψ : L'' →ᴸ L') : ϕ.sumElim ψ ∘ᴸ LHom.sumInr = ψ :=
LHom.funext (funext fun _ => rfl) (funext fun _ => rfl)
#align first_order.language.Lhom.sum_elim_comp_inr FirstOrder.Language.LHom.sumElim_comp_inr
theorem sumElim_inl_inr : LHom.sumInl.sumElim LHom.sumInr = LHom.id (L.sum L') :=
LHom.funext (funext fun _ => Sum.elim_inl_inr) (funext fun _ => Sum.elim_inl_inr)
#align first_order.language.Lhom.sum_elim_inl_inr FirstOrder.Language.LHom.sumElim_inl_inr
theorem comp_sumElim {L3 : Language} (θ : L' →ᴸ L3) :
θ ∘ᴸ ϕ.sumElim ψ = (θ ∘ᴸ ϕ).sumElim (θ ∘ᴸ ψ) :=
LHom.funext (funext fun _n => Sum.comp_elim _ _ _) (funext fun _n => Sum.comp_elim _ _ _)
#align first_order.language.Lhom.comp_sum_elim FirstOrder.Language.LHom.comp_sumElim
end SumElim
section SumMap
variable {L₁ L₂ : Language} (ψ : L₁ →ᴸ L₂)
/-- The map between two sum-languages induced by maps on the two factors. -/
@[simps]
def sumMap : L.sum L₁ →ᴸ L'.sum L₂ where
onFunction _n := Sum.map (fun f => ϕ.onFunction f) fun f => ψ.onFunction f
onRelation _n := Sum.map (fun f => ϕ.onRelation f) fun f => ψ.onRelation f
#align first_order.language.Lhom.sum_map FirstOrder.Language.LHom.sumMap
@[simp]
theorem sumMap_comp_inl : ϕ.sumMap ψ ∘ᴸ LHom.sumInl = LHom.sumInl ∘ᴸ ϕ :=
LHom.funext (funext fun _ => rfl) (funext fun _ => rfl)
#align first_order.language.Lhom.sum_map_comp_inl FirstOrder.Language.LHom.sumMap_comp_inl
@[simp]
theorem sumMap_comp_inr : ϕ.sumMap ψ ∘ᴸ LHom.sumInr = LHom.sumInr ∘ᴸ ψ :=
LHom.funext (funext fun _ => rfl) (funext fun _ => rfl)
#align first_order.language.Lhom.sum_map_comp_inr FirstOrder.Language.LHom.sumMap_comp_inr
end SumMap
/-- A language homomorphism is injective when all the maps between symbol types are. -/
protected structure Injective : Prop where
onFunction {n} : Function.Injective fun f : L.Functions n => onFunction ϕ f
onRelation {n} : Function.Injective fun R : L.Relations n => onRelation ϕ R
#align first_order.language.Lhom.injective FirstOrder.Language.LHom.Injective
/-- Pulls an `L`-structure along a language map `ϕ : L →ᴸ L'`, and then expands it
to an `L'`-structure arbitrarily. -/
noncomputable def defaultExpansion (ϕ : L →ᴸ L')
[∀ (n) (f : L'.Functions n), Decidable (f ∈ Set.range fun f : L.Functions n => onFunction ϕ f)]
[∀ (n) (r : L'.Relations n), Decidable (r ∈ Set.range fun r : L.Relations n => onRelation ϕ r)]
(M : Type*) [Inhabited M] [L.Structure M] : L'.Structure M where
funMap {n} f xs :=
if h' : f ∈ Set.range fun f : L.Functions n => onFunction ϕ f then funMap h'.choose xs
else default
RelMap {n} r xs :=
if h' : r ∈ Set.range fun r : L.Relations n => onRelation ϕ r then RelMap h'.choose xs
else default
#align first_order.language.Lhom.default_expansion FirstOrder.Language.LHom.defaultExpansion
/-- A language homomorphism is an expansion on a structure if it commutes with the interpretation of
all symbols on that structure. -/
class IsExpansionOn (M : Type*) [L.Structure M] [L'.Structure M] : Prop where
map_onFunction : ∀ {n} (f : L.Functions n) (x : Fin n → M), funMap (ϕ.onFunction f) x = funMap f x
map_onRelation : ∀ {n} (R : L.Relations n) (x : Fin n → M),
RelMap (ϕ.onRelation R) x = RelMap R x
#align first_order.language.Lhom.is_expansion_on FirstOrder.Language.LHom.IsExpansionOn
@[simp]
theorem map_onFunction {M : Type*} [L.Structure M] [L'.Structure M] [ϕ.IsExpansionOn M] {n}
(f : L.Functions n) (x : Fin n → M) : funMap (ϕ.onFunction f) x = funMap f x :=
IsExpansionOn.map_onFunction f x
#align first_order.language.Lhom.map_on_function FirstOrder.Language.LHom.map_onFunction
@[simp]
theorem map_onRelation {M : Type*} [L.Structure M] [L'.Structure M] [ϕ.IsExpansionOn M] {n}
(R : L.Relations n) (x : Fin n → M) : RelMap (ϕ.onRelation R) x = RelMap R x :=
IsExpansionOn.map_onRelation R x
#align first_order.language.Lhom.map_on_relation FirstOrder.Language.LHom.map_onRelation
instance id_isExpansionOn (M : Type*) [L.Structure M] : IsExpansionOn (LHom.id L) M :=
⟨fun _ _ => rfl, fun _ _ => rfl⟩
#align first_order.language.Lhom.id_is_expansion_on FirstOrder.Language.LHom.id_isExpansionOn
instance ofIsEmpty_isExpansionOn (M : Type*) [L.Structure M] [L'.Structure M] [L.IsAlgebraic]
[L.IsRelational] : IsExpansionOn (LHom.ofIsEmpty L L') M :=
⟨fun {n} => (IsRelational.empty_functions n).elim,
fun {n} => (IsAlgebraic.empty_relations n).elim⟩
#align first_order.language.Lhom.of_is_empty_is_expansion_on FirstOrder.Language.LHom.ofIsEmpty_isExpansionOn
instance sumElim_isExpansionOn {L'' : Language} (ψ : L'' →ᴸ L') (M : Type*) [L.Structure M]
[L'.Structure M] [L''.Structure M] [ϕ.IsExpansionOn M] [ψ.IsExpansionOn M] :
(ϕ.sumElim ψ).IsExpansionOn M :=
⟨fun f _ => Sum.casesOn f (by simp) (by simp), fun R _ => Sum.casesOn R (by simp) (by simp)⟩
#align first_order.language.Lhom.sum_elim_is_expansion_on FirstOrder.Language.LHom.sumElim_isExpansionOn
instance sumMap_isExpansionOn {L₁ L₂ : Language} (ψ : L₁ →ᴸ L₂) (M : Type*) [L.Structure M]
[L'.Structure M] [L₁.Structure M] [L₂.Structure M] [ϕ.IsExpansionOn M] [ψ.IsExpansionOn M] :
(ϕ.sumMap ψ).IsExpansionOn M :=
⟨fun f _ => Sum.casesOn f (by simp) (by simp), fun R _ => Sum.casesOn R (by simp) (by simp)⟩
#align first_order.language.Lhom.sum_map_is_expansion_on FirstOrder.Language.LHom.sumMap_isExpansionOn
instance sumInl_isExpansionOn (M : Type*) [L.Structure M] [L'.Structure M] :
(LHom.sumInl : L →ᴸ L.sum L').IsExpansionOn M :=
⟨fun _f _ => rfl, fun _R _ => rfl⟩
#align first_order.language.Lhom.sum_inl_is_expansion_on FirstOrder.Language.LHom.sumInl_isExpansionOn
instance sumInr_isExpansionOn (M : Type*) [L.Structure M] [L'.Structure M] :
(LHom.sumInr : L' →ᴸ L.sum L').IsExpansionOn M :=
⟨fun _f _ => rfl, fun _R _ => rfl⟩
#align first_order.language.Lhom.sum_inr_is_expansion_on FirstOrder.Language.LHom.sumInr_isExpansionOn
@[simp]
theorem funMap_sumInl [(L.sum L').Structure M] [(LHom.sumInl : L →ᴸ L.sum L').IsExpansionOn M] {n}
{f : L.Functions n} {x : Fin n → M} : @funMap (L.sum L') M _ n (Sum.inl f) x = funMap f x :=
(LHom.sumInl : L →ᴸ L.sum L').map_onFunction f x
#align first_order.language.Lhom.fun_map_sum_inl FirstOrder.Language.LHom.funMap_sumInl
@[simp]
theorem funMap_sumInr [(L'.sum L).Structure M] [(LHom.sumInr : L →ᴸ L'.sum L).IsExpansionOn M] {n}
{f : L.Functions n} {x : Fin n → M} : @funMap (L'.sum L) M _ n (Sum.inr f) x = funMap f x :=
(LHom.sumInr : L →ᴸ L'.sum L).map_onFunction f x
#align first_order.language.Lhom.fun_map_sum_inr FirstOrder.Language.LHom.funMap_sumInr
theorem sumInl_injective : (LHom.sumInl : L →ᴸ L.sum L').Injective :=
⟨fun h => Sum.inl_injective h, fun h => Sum.inl_injective h⟩
#align first_order.language.Lhom.sum_inl_injective FirstOrder.Language.LHom.sumInl_injective
theorem sumInr_injective : (LHom.sumInr : L' →ᴸ L.sum L').Injective :=
⟨fun h => Sum.inr_injective h, fun h => Sum.inr_injective h⟩
#align first_order.language.Lhom.sum_inr_injective FirstOrder.Language.LHom.sumInr_injective
instance (priority := 100) isExpansionOn_reduct (ϕ : L →ᴸ L') (M : Type*) [L'.Structure M] :
@IsExpansionOn L L' ϕ M (ϕ.reduct M) _ :=
letI := ϕ.reduct M
⟨fun _f _ => rfl, fun _R _ => rfl⟩
#align first_order.language.Lhom.is_expansion_on_reduct FirstOrder.Language.LHom.isExpansionOn_reduct
theorem Injective.isExpansionOn_default {ϕ : L →ᴸ L'}
[∀ (n) (f : L'.Functions n), Decidable (f ∈ Set.range fun f : L.Functions n => ϕ.onFunction f)]
[∀ (n) (r : L'.Relations n), Decidable (r ∈ Set.range fun r : L.Relations n => ϕ.onRelation r)]
(h : ϕ.Injective) (M : Type*) [Inhabited M] [L.Structure M] :
@IsExpansionOn L L' ϕ M _ (ϕ.defaultExpansion M) := by
letI := ϕ.defaultExpansion M
refine ⟨fun {n} f xs => ?_, fun {n} r xs => ?_⟩
· have hf : ϕ.onFunction f ∈ Set.range fun f : L.Functions n => ϕ.onFunction f := ⟨f, rfl⟩
refine (dif_pos hf).trans ?_
rw [h.onFunction hf.choose_spec]
· have hr : ϕ.onRelation r ∈ Set.range fun r : L.Relations n => ϕ.onRelation r := ⟨r, rfl⟩
refine (dif_pos hr).trans ?_
rw [h.onRelation hr.choose_spec]
#align first_order.language.Lhom.injective.is_expansion_on_default FirstOrder.Language.LHom.Injective.isExpansionOn_default
end LHom
/-- A language equivalence maps the symbols of one language to symbols of another bijectively. -/
structure LEquiv (L L' : Language) where
toLHom : L →ᴸ L'
invLHom : L' →ᴸ L
left_inv : invLHom.comp toLHom = LHom.id L
right_inv : toLHom.comp invLHom = LHom.id L'
#align first_order.lanugage.Lequiv FirstOrder.Language.LEquiv
infixl:10 " ≃ᴸ " => LEquiv
-- \^L
namespace LEquiv
variable (L)
/-- The identity equivalence from a first-order language to itself. -/
@[simps]
protected def refl : L ≃ᴸ L :=
⟨LHom.id L, LHom.id L, LHom.comp_id _, LHom.comp_id _⟩
#align first_order.lanugage.Lequiv.refl FirstOrder.Language.LEquiv.refl
variable {L}
instance : Inhabited (L ≃ᴸ L) :=
⟨LEquiv.refl L⟩
variable {L'' : Language} (e' : L' ≃ᴸ L'') (e : L ≃ᴸ L')
/-- The inverse of an equivalence of first-order languages. -/
@[simps]
protected def symm : L' ≃ᴸ L :=
⟨e.invLHom, e.toLHom, e.right_inv, e.left_inv⟩
#align first_order.lanugage.Lequiv.symm FirstOrder.Language.LEquiv.symm
/-- The composition of equivalences of first-order languages. -/
@[simps, trans]
protected def trans (e : L ≃ᴸ L') (e' : L' ≃ᴸ L'') : L ≃ᴸ L'' :=
⟨e'.toLHom.comp e.toLHom, e.invLHom.comp e'.invLHom, by
rw [LHom.comp_assoc, ← LHom.comp_assoc e'.invLHom, e'.left_inv, LHom.id_comp, e.left_inv], by
rw [LHom.comp_assoc, ← LHom.comp_assoc e.toLHom, e.right_inv, LHom.id_comp, e'.right_inv]⟩
#align first_order.lanugage.Lequiv.trans FirstOrder.Language.LEquiv.trans
end LEquiv
section ConstantsOn
variable (α : Type u')
/-- A language with constants indexed by a type. -/
@[simp]
def constantsOn : Language.{u', 0} :=
Language.mk₂ α PEmpty PEmpty PEmpty PEmpty
#align first_order.language.constants_on FirstOrder.Language.constantsOn
variable {α}
theorem constantsOn_constants : (constantsOn α).Constants = α :=
rfl
#align first_order.language.constants_on_constants FirstOrder.Language.constantsOn_constants
instance isAlgebraic_constantsOn : IsAlgebraic (constantsOn α) :=
Language.isAlgebraic_mk₂
#align first_order.language.is_algebraic_constants_on FirstOrder.Language.isAlgebraic_constantsOn
instance isRelational_constantsOn [_ie : IsEmpty α] : IsRelational (constantsOn α) :=
Language.isRelational_mk₂
#align first_order.language.is_relational_constants_on FirstOrder.Language.isRelational_constantsOn
instance isEmpty_functions_constantsOn_succ {n : ℕ} : IsEmpty ((constantsOn α).Functions (n + 1)) :=
Nat.casesOn n (inferInstanceAs (IsEmpty PEmpty))
fun n => Nat.casesOn n (inferInstanceAs (IsEmpty PEmpty))
fun _ => (inferInstanceAs (IsEmpty PEmpty))
#align first_order.language.is_empty_functions_constants_on_succ FirstOrder.Language.isEmpty_functions_constantsOn_succ
theorem card_constantsOn : (constantsOn α).card = #α := by simp
#align first_order.language.card_constants_on FirstOrder.Language.card_constantsOn
/-- Gives a `constantsOn α` structure to a type by assigning each constant a value. -/
def constantsOn.structure (f : α → M) : (constantsOn α).Structure M :=
Structure.mk₂ f PEmpty.elim PEmpty.elim PEmpty.elim PEmpty.elim
#align first_order.language.constants_on.Structure FirstOrder.Language.constantsOn.structure
variable {β : Type v'}
/-- A map between index types induces a map between constant languages. -/
def LHom.constantsOnMap (f : α → β) : constantsOn α →ᴸ constantsOn β :=
LHom.mk₂ f PEmpty.elim PEmpty.elim PEmpty.elim PEmpty.elim
#align first_order.language.Lhom.constants_on_map FirstOrder.Language.LHom.constantsOnMap
theorem constantsOnMap_isExpansionOn {f : α → β} {fα : α → M} {fβ : β → M} (h : fβ ∘ f = fα) :
@LHom.IsExpansionOn _ _ (LHom.constantsOnMap f) M (constantsOn.structure fα)
(constantsOn.structure fβ) := by
letI := constantsOn.structure fα
letI := constantsOn.structure fβ
exact
⟨fun {n} => Nat.casesOn n (fun F _x => (congr_fun h F : _)) fun n F => isEmptyElim F, fun R =>
isEmptyElim R⟩
#align first_order.language.constants_on_map_is_expansion_on FirstOrder.Language.constantsOnMap_isExpansionOn
end ConstantsOn
section WithConstants
variable (L)
section
variable (α : Type w')
/-- Extends a language with a constant for each element of a parameter set in `M`. -/
def withConstants : Language.{max u w', v} :=
L.sum (constantsOn α)
#align first_order.language.with_constants FirstOrder.Language.withConstants
@[inherit_doc FirstOrder.Language.withConstants]
scoped[FirstOrder] notation:95 L "[[" α "]]" => Language.withConstants L α
@[simp]
theorem card_withConstants :
L[[α]].card = Cardinal.lift.{w'} L.card + Cardinal.lift.{max u v} #α := by
rw [withConstants, card_sum, card_constantsOn]
#align first_order.language.card_with_constants FirstOrder.Language.card_withConstants
/-- The language map adding constants. -/
@[simps!] -- Porting note: add `!` to `simps`
def lhomWithConstants : L →ᴸ L[[α]] :=
LHom.sumInl
#align first_order.language.Lhom_with_constants FirstOrder.Language.lhomWithConstants
theorem lhomWithConstants_injective : (L.lhomWithConstants α).Injective :=
LHom.sumInl_injective
#align first_order.language.Lhom_with_constants_injective FirstOrder.Language.lhomWithConstants_injective
variable {α}
/-- The constant symbol indexed by a particular element. -/
protected def con (a : α) : L[[α]].Constants :=
Sum.inr a
#align first_order.language.con FirstOrder.Language.con
variable {L} (α)
/-- Adds constants to a language map. -/
def LHom.addConstants {L' : Language} (φ : L →ᴸ L') : L[[α]] →ᴸ L'[[α]] :=
φ.sumMap (LHom.id _)
#align first_order.language.Lhom.add_constants FirstOrder.Language.LHom.addConstants
instance paramsStructure (A : Set α) : (constantsOn A).Structure α :=
constantsOn.structure (↑)
#align first_order.language.params_Structure FirstOrder.Language.paramsStructure
variable (L)
/-- The language map removing an empty constant set. -/
@[simps]
def LEquiv.addEmptyConstants [ie : IsEmpty α] : L ≃ᴸ L[[α]] where
toLHom := lhomWithConstants L α
invLHom := LHom.sumElim (LHom.id L) (LHom.ofIsEmpty (constantsOn α) L)
left_inv := by rw [lhomWithConstants, LHom.sumElim_comp_inl]
right_inv := by
simp only [LHom.comp_sumElim, lhomWithConstants, LHom.comp_id]
exact _root_.trans (congr rfl (Subsingleton.elim _ _)) LHom.sumElim_inl_inr
#align first_order.lanugage.Lequiv.add_empty_constants FirstOrder.Language.LEquiv.addEmptyConstants
variable {α} {β : Type*}
@[simp]
theorem withConstants_funMap_sum_inl [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{n} {f : L.Functions n} {x : Fin n → M} : @funMap (L[[α]]) M _ n (Sum.inl f) x = funMap f x :=
(lhomWithConstants L α).map_onFunction f x
#align first_order.language.with_constants_fun_map_sum_inl FirstOrder.Language.withConstants_funMap_sum_inl
@[simp]
theorem withConstants_relMap_sum_inl [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{n} {R : L.Relations n} {x : Fin n → M} : @RelMap (L[[α]]) M _ n (Sum.inl R) x = RelMap R x :=
(lhomWithConstants L α).map_onRelation R x
#align first_order.language.with_constants_rel_map_sum_inl FirstOrder.Language.withConstants_relMap_sum_inl
/-- The language map extending the constant set. -/
def lhomWithConstantsMap (f : α → β) : L[[α]] →ᴸ L[[β]] :=
LHom.sumMap (LHom.id L) (LHom.constantsOnMap f)
#align first_order.language.Lhom_with_constants_map FirstOrder.Language.lhomWithConstantsMap
@[simp]
| Mathlib/ModelTheory/LanguageMap.lean | 521 | 522 | theorem LHom.map_constants_comp_sumInl {f : α → β} :
(L.lhomWithConstantsMap f).comp LHom.sumInl = L.lhomWithConstants β := by | ext <;> rfl
|
/-
Copyright (c) 2020 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Constructions.Prod.Basic
import Mathlib.MeasureTheory.Integral.DominatedConvergence
import Mathlib.MeasureTheory.Integral.SetIntegral
#align_import measure_theory.constructions.prod.integral from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Integration with respect to the product measure
In this file we prove Fubini's theorem.
## Main results
* `MeasureTheory.integrable_prod_iff` states that a binary function is integrable iff both
* `y ↦ f (x, y)` is integrable for almost every `x`, and
* the function `x ↦ ∫ ‖f (x, y)‖ dy` is integrable.
* `MeasureTheory.integral_prod`: Fubini's theorem. It states that for an integrable function
`α × β → E` (where `E` is a second countable Banach space) we have
`∫ z, f z ∂(μ.prod ν) = ∫ x, ∫ y, f (x, y) ∂ν ∂μ`. This theorem has the same variants as
Tonelli's theorem (see `MeasureTheory.lintegral_prod`). The lemma
`MeasureTheory.Integrable.integral_prod_right` states that the inner integral of the right-hand
side is integrable.
* `MeasureTheory.integral_integral_swap_of_hasCompactSupport`: a version of Fubini theorem for
continuous functions with compact support, which does not assume that the measures are σ-finite
contrary to all the usual versions of Fubini.
## Tags
product measure, Fubini's theorem, Fubini-Tonelli theorem
-/
noncomputable section
open scoped Classical Topology ENNReal MeasureTheory
open Set Function Real ENNReal
open MeasureTheory MeasurableSpace MeasureTheory.Measure
open TopologicalSpace
open Filter hiding prod_eq map
variable {α α' β β' γ E : Type*}
variable [MeasurableSpace α] [MeasurableSpace α'] [MeasurableSpace β] [MeasurableSpace β']
variable [MeasurableSpace γ]
variable {μ μ' : Measure α} {ν ν' : Measure β} {τ : Measure γ}
variable [NormedAddCommGroup E]
/-! ### Measurability
Before we define the product measure, we can talk about the measurability of operations on binary
functions. We show that if `f` is a binary measurable function, then the function that integrates
along one of the variables (using either the Lebesgue or Bochner integral) is measurable.
-/
theorem measurableSet_integrable [SigmaFinite ν] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : MeasurableSet {x | Integrable (f x) ν} := by
simp_rw [Integrable, hf.of_uncurry_left.aestronglyMeasurable, true_and_iff]
exact measurableSet_lt (Measurable.lintegral_prod_right hf.ennnorm) measurable_const
#align measurable_set_integrable measurableSet_integrable
section
variable [NormedSpace ℝ E]
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
Fubini's theorem is measurable.
This version has `f` in curried form. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_right [SigmaFinite ν] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : StronglyMeasurable fun x => ∫ y, f x y ∂ν := by
by_cases hE : CompleteSpace E; swap; · simp [integral, hE, stronglyMeasurable_const]
borelize E
haveI : SeparableSpace (range (uncurry f) ∪ {0} : Set E) :=
hf.separableSpace_range_union_singleton
let s : ℕ → SimpleFunc (α × β) E :=
SimpleFunc.approxOn _ hf.measurable (range (uncurry f) ∪ {0}) 0 (by simp)
let s' : ℕ → α → SimpleFunc β E := fun n x => (s n).comp (Prod.mk x) measurable_prod_mk_left
let f' : ℕ → α → E := fun n => {x | Integrable (f x) ν}.indicator fun x => (s' n x).integral ν
have hf' : ∀ n, StronglyMeasurable (f' n) := by
intro n; refine StronglyMeasurable.indicator ?_ (measurableSet_integrable hf)
have : ∀ x, ((s' n x).range.filter fun x => x ≠ 0) ⊆ (s n).range := by
intro x; refine Finset.Subset.trans (Finset.filter_subset _ _) ?_; intro y
simp_rw [SimpleFunc.mem_range]; rintro ⟨z, rfl⟩; exact ⟨(x, z), rfl⟩
simp only [SimpleFunc.integral_eq_sum_of_subset (this _)]
refine Finset.stronglyMeasurable_sum _ fun x _ => ?_
refine (Measurable.ennreal_toReal ?_).stronglyMeasurable.smul_const _
simp only [s', SimpleFunc.coe_comp, preimage_comp]
apply measurable_measure_prod_mk_left
exact (s n).measurableSet_fiber x
have h2f' : Tendsto f' atTop (𝓝 fun x : α => ∫ y : β, f x y ∂ν) := by
rw [tendsto_pi_nhds]; intro x
by_cases hfx : Integrable (f x) ν
· have (n) : Integrable (s' n x) ν := by
apply (hfx.norm.add hfx.norm).mono' (s' n x).aestronglyMeasurable
filter_upwards with y
simp_rw [s', SimpleFunc.coe_comp]; exact SimpleFunc.norm_approxOn_zero_le _ _ (x, y) n
simp only [f', hfx, SimpleFunc.integral_eq_integral _ (this _), indicator_of_mem,
mem_setOf_eq]
refine
tendsto_integral_of_dominated_convergence (fun y => ‖f x y‖ + ‖f x y‖)
(fun n => (s' n x).aestronglyMeasurable) (hfx.norm.add hfx.norm) ?_ ?_
· refine fun n => eventually_of_forall fun y =>
SimpleFunc.norm_approxOn_zero_le ?_ ?_ (x, y) n
-- Porting note: Lean 3 solved the following two subgoals on its own
· exact hf.measurable
· simp
· refine eventually_of_forall fun y => SimpleFunc.tendsto_approxOn ?_ ?_ ?_
-- Porting note: Lean 3 solved the following two subgoals on its own
· exact hf.measurable.of_uncurry_left
· simp
apply subset_closure
simp [-uncurry_apply_pair]
· simp [f', hfx, integral_undef]
exact stronglyMeasurable_of_tendsto _ hf' h2f'
#align measure_theory.strongly_measurable.integral_prod_right MeasureTheory.StronglyMeasurable.integral_prod_right
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
Fubini's theorem is measurable. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_right' [SigmaFinite ν] ⦃f : α × β → E⦄
(hf : StronglyMeasurable f) : StronglyMeasurable fun x => ∫ y, f (x, y) ∂ν := by
rw [← uncurry_curry f] at hf; exact hf.integral_prod_right
#align measure_theory.strongly_measurable.integral_prod_right' MeasureTheory.StronglyMeasurable.integral_prod_right'
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Fubini's theorem is measurable.
This version has `f` in curried form. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_left [SigmaFinite μ] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : StronglyMeasurable fun y => ∫ x, f x y ∂μ :=
(hf.comp_measurable measurable_swap).integral_prod_right'
#align measure_theory.strongly_measurable.integral_prod_left MeasureTheory.StronglyMeasurable.integral_prod_left
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
the symmetric version of Fubini's theorem is measurable. -/
theorem MeasureTheory.StronglyMeasurable.integral_prod_left' [SigmaFinite μ] ⦃f : α × β → E⦄
(hf : StronglyMeasurable f) : StronglyMeasurable fun y => ∫ x, f (x, y) ∂μ :=
(hf.comp_measurable measurable_swap).integral_prod_right'
#align measure_theory.strongly_measurable.integral_prod_left' MeasureTheory.StronglyMeasurable.integral_prod_left'
end
/-! ### The product measure -/
namespace MeasureTheory
namespace Measure
variable [SigmaFinite ν]
theorem integrable_measure_prod_mk_left {s : Set (α × β)} (hs : MeasurableSet s)
(h2s : (μ.prod ν) s ≠ ∞) : Integrable (fun x => (ν (Prod.mk x ⁻¹' s)).toReal) μ := by
refine ⟨(measurable_measure_prod_mk_left hs).ennreal_toReal.aemeasurable.aestronglyMeasurable, ?_⟩
simp_rw [HasFiniteIntegral, ennnorm_eq_ofReal toReal_nonneg]
convert h2s.lt_top using 1
-- Porting note: was `simp_rw`
rw [prod_apply hs]
apply lintegral_congr_ae
filter_upwards [ae_measure_lt_top hs h2s] with x hx
rw [lt_top_iff_ne_top] at hx; simp [ofReal_toReal, hx]
#align measure_theory.measure.integrable_measure_prod_mk_left MeasureTheory.Measure.integrable_measure_prod_mk_left
end Measure
open Measure
end MeasureTheory
open MeasureTheory.Measure
section
nonrec theorem MeasureTheory.AEStronglyMeasurable.prod_swap {γ : Type*} [TopologicalSpace γ]
[SigmaFinite μ] [SigmaFinite ν] {f : β × α → γ} (hf : AEStronglyMeasurable f (ν.prod μ)) :
AEStronglyMeasurable (fun z : α × β => f z.swap) (μ.prod ν) := by
rw [← prod_swap] at hf
exact hf.comp_measurable measurable_swap
#align measure_theory.ae_strongly_measurable.prod_swap MeasureTheory.AEStronglyMeasurable.prod_swap
theorem MeasureTheory.AEStronglyMeasurable.fst {γ} [TopologicalSpace γ] [SigmaFinite ν] {f : α → γ}
(hf : AEStronglyMeasurable f μ) : AEStronglyMeasurable (fun z : α × β => f z.1) (μ.prod ν) :=
hf.comp_quasiMeasurePreserving quasiMeasurePreserving_fst
#align measure_theory.ae_strongly_measurable.fst MeasureTheory.AEStronglyMeasurable.fst
theorem MeasureTheory.AEStronglyMeasurable.snd {γ} [TopologicalSpace γ] [SigmaFinite ν] {f : β → γ}
(hf : AEStronglyMeasurable f ν) : AEStronglyMeasurable (fun z : α × β => f z.2) (μ.prod ν) :=
hf.comp_quasiMeasurePreserving quasiMeasurePreserving_snd
#align measure_theory.ae_strongly_measurable.snd MeasureTheory.AEStronglyMeasurable.snd
/-- The Bochner integral is a.e.-measurable.
This shows that the integrand of (the right-hand-side of) Fubini's theorem is a.e.-measurable. -/
theorem MeasureTheory.AEStronglyMeasurable.integral_prod_right' [SigmaFinite ν] [NormedSpace ℝ E]
⦃f : α × β → E⦄ (hf : AEStronglyMeasurable f (μ.prod ν)) :
AEStronglyMeasurable (fun x => ∫ y, f (x, y) ∂ν) μ :=
⟨fun x => ∫ y, hf.mk f (x, y) ∂ν, hf.stronglyMeasurable_mk.integral_prod_right', by
filter_upwards [ae_ae_of_ae_prod hf.ae_eq_mk] with _ hx using integral_congr_ae hx⟩
#align measure_theory.ae_strongly_measurable.integral_prod_right' MeasureTheory.AEStronglyMeasurable.integral_prod_right'
theorem MeasureTheory.AEStronglyMeasurable.prod_mk_left {γ : Type*} [SigmaFinite ν]
[TopologicalSpace γ] {f : α × β → γ} (hf : AEStronglyMeasurable f (μ.prod ν)) :
∀ᵐ x ∂μ, AEStronglyMeasurable (fun y => f (x, y)) ν := by
filter_upwards [ae_ae_of_ae_prod hf.ae_eq_mk] with x hx
exact
⟨fun y => hf.mk f (x, y), hf.stronglyMeasurable_mk.comp_measurable measurable_prod_mk_left, hx⟩
#align measure_theory.ae_strongly_measurable.prod_mk_left MeasureTheory.AEStronglyMeasurable.prod_mk_left
end
namespace MeasureTheory
variable [SigmaFinite ν]
/-! ### Integrability on a product -/
section
theorem integrable_swap_iff [SigmaFinite μ] {f : α × β → E} :
Integrable (f ∘ Prod.swap) (ν.prod μ) ↔ Integrable f (μ.prod ν) :=
measurePreserving_swap.integrable_comp_emb MeasurableEquiv.prodComm.measurableEmbedding
#align measure_theory.integrable_swap_iff MeasureTheory.integrable_swap_iff
theorem Integrable.swap [SigmaFinite μ] ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
Integrable (f ∘ Prod.swap) (ν.prod μ) :=
integrable_swap_iff.2 hf
#align measure_theory.integrable.swap MeasureTheory.Integrable.swap
theorem hasFiniteIntegral_prod_iff ⦃f : α × β → E⦄ (h1f : StronglyMeasurable f) :
HasFiniteIntegral f (μ.prod ν) ↔
(∀ᵐ x ∂μ, HasFiniteIntegral (fun y => f (x, y)) ν) ∧
HasFiniteIntegral (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ := by
simp only [HasFiniteIntegral, lintegral_prod_of_measurable _ h1f.ennnorm]
have (x) : ∀ᵐ y ∂ν, 0 ≤ ‖f (x, y)‖ := by filter_upwards with y using norm_nonneg _
simp_rw [integral_eq_lintegral_of_nonneg_ae (this _)
(h1f.norm.comp_measurable measurable_prod_mk_left).aestronglyMeasurable,
ennnorm_eq_ofReal toReal_nonneg, ofReal_norm_eq_coe_nnnorm]
-- this fact is probably too specialized to be its own lemma
have : ∀ {p q r : Prop} (_ : r → p), (r ↔ p ∧ q) ↔ p → (r ↔ q) := fun {p q r} h1 => by
rw [← and_congr_right_iff, and_iff_right_of_imp h1]
rw [this]
· intro h2f; rw [lintegral_congr_ae]
filter_upwards [h2f] with x hx
rw [ofReal_toReal]; rw [← lt_top_iff_ne_top]; exact hx
· intro h2f; refine ae_lt_top ?_ h2f.ne; exact h1f.ennnorm.lintegral_prod_right'
#align measure_theory.has_finite_integral_prod_iff MeasureTheory.hasFiniteIntegral_prod_iff
theorem hasFiniteIntegral_prod_iff' ⦃f : α × β → E⦄ (h1f : AEStronglyMeasurable f (μ.prod ν)) :
HasFiniteIntegral f (μ.prod ν) ↔
(∀ᵐ x ∂μ, HasFiniteIntegral (fun y => f (x, y)) ν) ∧
HasFiniteIntegral (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ := by
rw [hasFiniteIntegral_congr h1f.ae_eq_mk,
hasFiniteIntegral_prod_iff h1f.stronglyMeasurable_mk]
apply and_congr
· apply eventually_congr
filter_upwards [ae_ae_of_ae_prod h1f.ae_eq_mk.symm]
intro x hx
exact hasFiniteIntegral_congr hx
· apply hasFiniteIntegral_congr
filter_upwards [ae_ae_of_ae_prod h1f.ae_eq_mk.symm] with _ hx using
integral_congr_ae (EventuallyEq.fun_comp hx _)
#align measure_theory.has_finite_integral_prod_iff' MeasureTheory.hasFiniteIntegral_prod_iff'
/-- A binary function is integrable if the function `y ↦ f (x, y)` is integrable for almost every
`x` and the function `x ↦ ∫ ‖f (x, y)‖ dy` is integrable. -/
theorem integrable_prod_iff ⦃f : α × β → E⦄ (h1f : AEStronglyMeasurable f (μ.prod ν)) :
Integrable f (μ.prod ν) ↔
(∀ᵐ x ∂μ, Integrable (fun y => f (x, y)) ν) ∧ Integrable (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ := by
simp [Integrable, h1f, hasFiniteIntegral_prod_iff', h1f.norm.integral_prod_right',
h1f.prod_mk_left]
#align measure_theory.integrable_prod_iff MeasureTheory.integrable_prod_iff
/-- A binary function is integrable if the function `x ↦ f (x, y)` is integrable for almost every
`y` and the function `y ↦ ∫ ‖f (x, y)‖ dx` is integrable. -/
theorem integrable_prod_iff' [SigmaFinite μ] ⦃f : α × β → E⦄
(h1f : AEStronglyMeasurable f (μ.prod ν)) :
Integrable f (μ.prod ν) ↔
(∀ᵐ y ∂ν, Integrable (fun x => f (x, y)) μ) ∧ Integrable (fun y => ∫ x, ‖f (x, y)‖ ∂μ) ν := by
convert integrable_prod_iff h1f.prod_swap using 1
rw [funext fun _ => Function.comp_apply.symm, integrable_swap_iff]
#align measure_theory.integrable_prod_iff' MeasureTheory.integrable_prod_iff'
theorem Integrable.prod_left_ae [SigmaFinite μ] ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
∀ᵐ y ∂ν, Integrable (fun x => f (x, y)) μ :=
((integrable_prod_iff' hf.aestronglyMeasurable).mp hf).1
#align measure_theory.integrable.prod_left_ae MeasureTheory.Integrable.prod_left_ae
theorem Integrable.prod_right_ae [SigmaFinite μ] ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
∀ᵐ x ∂μ, Integrable (fun y => f (x, y)) ν :=
hf.swap.prod_left_ae
#align measure_theory.integrable.prod_right_ae MeasureTheory.Integrable.prod_right_ae
theorem Integrable.integral_norm_prod_left ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
Integrable (fun x => ∫ y, ‖f (x, y)‖ ∂ν) μ :=
((integrable_prod_iff hf.aestronglyMeasurable).mp hf).2
#align measure_theory.integrable.integral_norm_prod_left MeasureTheory.Integrable.integral_norm_prod_left
theorem Integrable.integral_norm_prod_right [SigmaFinite μ] ⦃f : α × β → E⦄
(hf : Integrable f (μ.prod ν)) : Integrable (fun y => ∫ x, ‖f (x, y)‖ ∂μ) ν :=
hf.swap.integral_norm_prod_left
#align measure_theory.integrable.integral_norm_prod_right MeasureTheory.Integrable.integral_norm_prod_right
theorem Integrable.prod_smul {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E]
{f : α → 𝕜} {g : β → E} (hf : Integrable f μ) (hg : Integrable g ν) :
Integrable (fun z : α × β => f z.1 • g z.2) (μ.prod ν) := by
refine (integrable_prod_iff ?_).2 ⟨?_, ?_⟩
· exact hf.1.fst.smul hg.1.snd
· exact eventually_of_forall fun x => hg.smul (f x)
· simpa only [norm_smul, integral_mul_left] using hf.norm.mul_const _
theorem Integrable.prod_mul {L : Type*} [RCLike L] {f : α → L} {g : β → L} (hf : Integrable f μ)
(hg : Integrable g ν) : Integrable (fun z : α × β => f z.1 * g z.2) (μ.prod ν) :=
hf.prod_smul hg
#align measure_theory.integrable_prod_mul MeasureTheory.Integrable.prod_mul
end
variable [NormedSpace ℝ E]
theorem Integrable.integral_prod_left ⦃f : α × β → E⦄ (hf : Integrable f (μ.prod ν)) :
Integrable (fun x => ∫ y, f (x, y) ∂ν) μ :=
Integrable.mono hf.integral_norm_prod_left hf.aestronglyMeasurable.integral_prod_right' <|
eventually_of_forall fun x =>
(norm_integral_le_integral_norm _).trans_eq <|
(norm_of_nonneg <|
integral_nonneg_of_ae <|
eventually_of_forall fun y => (norm_nonneg (f (x, y)) : _)).symm
#align measure_theory.integrable.integral_prod_left MeasureTheory.Integrable.integral_prod_left
theorem Integrable.integral_prod_right [SigmaFinite μ] ⦃f : α × β → E⦄
(hf : Integrable f (μ.prod ν)) : Integrable (fun y => ∫ x, f (x, y) ∂μ) ν :=
hf.swap.integral_prod_left
#align measure_theory.integrable.integral_prod_right MeasureTheory.Integrable.integral_prod_right
/-! ### The Bochner integral on a product -/
variable [SigmaFinite μ]
theorem integral_prod_swap (f : α × β → E) :
∫ z, f z.swap ∂ν.prod μ = ∫ z, f z ∂μ.prod ν :=
measurePreserving_swap.integral_comp MeasurableEquiv.prodComm.measurableEmbedding _
#align measure_theory.integral_prod_swap MeasureTheory.integral_prod_swap
variable {E' : Type*} [NormedAddCommGroup E'] [NormedSpace ℝ E']
/-! Some rules about the sum/difference of double integrals. They follow from `integral_add`, but
we separate them out as separate lemmas, because they involve quite some steps. -/
/-- Integrals commute with addition inside another integral. `F` can be any function. -/
theorem integral_fn_integral_add ⦃f g : α × β → E⦄ (F : E → E') (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, F (∫ y, f (x, y) + g (x, y) ∂ν) ∂μ) =
∫ x, F ((∫ y, f (x, y) ∂ν) + ∫ y, g (x, y) ∂ν) ∂μ := by
refine integral_congr_ae ?_
filter_upwards [hf.prod_right_ae, hg.prod_right_ae] with _ h2f h2g
simp [integral_add h2f h2g]
#align measure_theory.integral_fn_integral_add MeasureTheory.integral_fn_integral_add
/-- Integrals commute with subtraction inside another integral.
`F` can be any measurable function. -/
theorem integral_fn_integral_sub ⦃f g : α × β → E⦄ (F : E → E') (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, F (∫ y, f (x, y) - g (x, y) ∂ν) ∂μ) =
∫ x, F ((∫ y, f (x, y) ∂ν) - ∫ y, g (x, y) ∂ν) ∂μ := by
refine integral_congr_ae ?_
filter_upwards [hf.prod_right_ae, hg.prod_right_ae] with _ h2f h2g
simp [integral_sub h2f h2g]
#align measure_theory.integral_fn_integral_sub MeasureTheory.integral_fn_integral_sub
/-- Integrals commute with subtraction inside a lower Lebesgue integral.
`F` can be any function. -/
theorem lintegral_fn_integral_sub ⦃f g : α × β → E⦄ (F : E → ℝ≥0∞) (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫⁻ x, F (∫ y, f (x, y) - g (x, y) ∂ν) ∂μ) =
∫⁻ x, F ((∫ y, f (x, y) ∂ν) - ∫ y, g (x, y) ∂ν) ∂μ := by
refine lintegral_congr_ae ?_
filter_upwards [hf.prod_right_ae, hg.prod_right_ae] with _ h2f h2g
simp [integral_sub h2f h2g]
#align measure_theory.lintegral_fn_integral_sub MeasureTheory.lintegral_fn_integral_sub
/-- Double integrals commute with addition. -/
theorem integral_integral_add ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, f (x, y) + g (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) + ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
(integral_fn_integral_add id hf hg).trans <|
integral_add hf.integral_prod_left hg.integral_prod_left
#align measure_theory.integral_integral_add MeasureTheory.integral_integral_add
/-- Double integrals commute with addition. This is the version with `(f + g) (x, y)`
(instead of `f (x, y) + g (x, y)`) in the LHS. -/
theorem integral_integral_add' ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, (f + g) (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) + ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
integral_integral_add hf hg
#align measure_theory.integral_integral_add' MeasureTheory.integral_integral_add'
/-- Double integrals commute with subtraction. -/
theorem integral_integral_sub ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, f (x, y) - g (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) - ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
(integral_fn_integral_sub id hf hg).trans <|
integral_sub hf.integral_prod_left hg.integral_prod_left
#align measure_theory.integral_integral_sub MeasureTheory.integral_integral_sub
/-- Double integrals commute with subtraction. This is the version with `(f - g) (x, y)`
(instead of `f (x, y) - g (x, y)`) in the LHS. -/
theorem integral_integral_sub' ⦃f g : α × β → E⦄ (hf : Integrable f (μ.prod ν))
(hg : Integrable g (μ.prod ν)) :
(∫ x, ∫ y, (f - g) (x, y) ∂ν ∂μ) = (∫ x, ∫ y, f (x, y) ∂ν ∂μ) - ∫ x, ∫ y, g (x, y) ∂ν ∂μ :=
integral_integral_sub hf hg
#align measure_theory.integral_integral_sub' MeasureTheory.integral_integral_sub'
/-- The map that sends an L¹-function `f : α × β → E` to `∫∫f` is continuous. -/
theorem continuous_integral_integral :
Continuous fun f : α × β →₁[μ.prod ν] E => ∫ x, ∫ y, f (x, y) ∂ν ∂μ := by
rw [continuous_iff_continuousAt]; intro g
refine
tendsto_integral_of_L1 _ (L1.integrable_coeFn g).integral_prod_left
(eventually_of_forall fun h => (L1.integrable_coeFn h).integral_prod_left) ?_
simp_rw [←
lintegral_fn_integral_sub (fun x => (‖x‖₊ : ℝ≥0∞)) (L1.integrable_coeFn _)
(L1.integrable_coeFn g)]
apply tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds _ (fun i => zero_le _) _
· exact fun i => ∫⁻ x, ∫⁻ y, ‖i (x, y) - g (x, y)‖₊ ∂ν ∂μ
swap; · exact fun i => lintegral_mono fun x => ennnorm_integral_le_lintegral_ennnorm _
show
Tendsto (fun i : α × β →₁[μ.prod ν] E => ∫⁻ x, ∫⁻ y : β, ‖i (x, y) - g (x, y)‖₊ ∂ν ∂μ) (𝓝 g)
(𝓝 0)
have : ∀ i : α × β →₁[μ.prod ν] E, Measurable fun z => (‖i z - g z‖₊ : ℝ≥0∞) := fun i =>
((Lp.stronglyMeasurable i).sub (Lp.stronglyMeasurable g)).ennnorm
-- Porting note: was
-- simp_rw [← lintegral_prod_of_measurable _ (this _), ← L1.ofReal_norm_sub_eq_lintegral, ←
-- ofReal_zero]
conv =>
congr
ext
rw [← lintegral_prod_of_measurable _ (this _), ← L1.ofReal_norm_sub_eq_lintegral]
rw [← ofReal_zero]
refine (continuous_ofReal.tendsto 0).comp ?_
rw [← tendsto_iff_norm_sub_tendsto_zero]; exact tendsto_id
#align measure_theory.continuous_integral_integral MeasureTheory.continuous_integral_integral
/-- **Fubini's Theorem**: For integrable functions on `α × β`,
the Bochner integral of `f` is equal to the iterated Bochner integral.
`integrable_prod_iff` can be useful to show that the function in question in integrable.
`MeasureTheory.Integrable.integral_prod_right` is useful to show that the inner integral
of the right-hand side is integrable. -/
| Mathlib/MeasureTheory/Constructions/Prod/Integral.lean | 454 | 472 | theorem integral_prod (f : α × β → E) (hf : Integrable f (μ.prod ν)) :
∫ z, f z ∂μ.prod ν = ∫ x, ∫ y, f (x, y) ∂ν ∂μ := by |
by_cases hE : CompleteSpace E; swap; · simp only [integral, dif_neg hE]
revert f
apply Integrable.induction
· intro c s hs h2s
simp_rw [integral_indicator hs, ← indicator_comp_right, Function.comp,
integral_indicator (measurable_prod_mk_left hs), setIntegral_const, integral_smul_const,
integral_toReal (measurable_measure_prod_mk_left hs).aemeasurable
(ae_measure_lt_top hs h2s.ne)]
-- Porting note: was `simp_rw`
rw [prod_apply hs]
· rintro f g - i_f i_g hf hg
simp_rw [integral_add' i_f i_g, integral_integral_add' i_f i_g, hf, hg]
· exact isClosed_eq continuous_integral continuous_integral_integral
· rintro f g hfg - hf; convert hf using 1
· exact integral_congr_ae hfg.symm
· apply integral_congr_ae
filter_upwards [ae_ae_of_ae_prod hfg] with x hfgx using integral_congr_ae (ae_eq_symm hfgx)
|
/-
Copyright (c) 2022 Siddhartha Prasad, Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Siddhartha Prasad, Yaël Dillies
-/
import Mathlib.Algebra.Ring.Pi
import Mathlib.Algebra.Ring.Prod
import Mathlib.Algebra.Ring.InjSurj
import Mathlib.Tactic.Monotonicity.Attr
#align_import algebra.order.kleene from "leanprover-community/mathlib"@"98e83c3d541c77cdb7da20d79611a780ff8e7d90"
/-!
# Kleene Algebras
This file defines idempotent semirings and Kleene algebras, which are used extensively in the theory
of computation.
An idempotent semiring is a semiring whose addition is idempotent. An idempotent semiring is
naturally a semilattice by setting `a ≤ b` if `a + b = b`.
A Kleene algebra is an idempotent semiring equipped with an additional unary operator `∗`, the
Kleene star.
## Main declarations
* `IdemSemiring`: Idempotent semiring
* `IdemCommSemiring`: Idempotent commutative semiring
* `KleeneAlgebra`: Kleene algebra
## Notation
`a∗` is notation for `kstar a` in locale `Computability`.
## References
* [D. Kozen, *A completeness theorem for Kleene algebras and the algebra of regular events*]
[kozen1994]
* https://planetmath.org/idempotentsemiring
* https://encyclopediaofmath.org/wiki/Idempotent_semi-ring
* https://planetmath.org/kleene_algebra
## TODO
Instances for `AddOpposite`, `MulOpposite`, `ULift`, `Subsemiring`, `Subring`, `Subalgebra`.
## Tags
kleene algebra, idempotent semiring
-/
open Function
universe u
variable {α β ι : Type*} {π : ι → Type*}
/-- An idempotent semiring is a semiring with the additional property that addition is idempotent.
-/
class IdemSemiring (α : Type u) extends Semiring α, SemilatticeSup α where
protected sup := (· + ·)
protected add_eq_sup : ∀ a b : α, a + b = a ⊔ b := by
intros
rfl
/-- The bottom element of an idempotent semiring: `0` by default -/
protected bot : α := 0
protected bot_le : ∀ a, bot ≤ a
#align idem_semiring IdemSemiring
/-- An idempotent commutative semiring is a commutative semiring with the additional property that
addition is idempotent. -/
class IdemCommSemiring (α : Type u) extends CommSemiring α, IdemSemiring α
#align idem_comm_semiring IdemCommSemiring
/-- Notation typeclass for the Kleene star `∗`. -/
class KStar (α : Type*) where
/-- The Kleene star operator on a Kleene algebra -/
protected kstar : α → α
#align has_kstar KStar
@[inherit_doc] scoped[Computability] postfix:1024 "∗" => KStar.kstar
open Computability
/-- A Kleene Algebra is an idempotent semiring with an additional unary operator `kstar` (for Kleene
star) that satisfies the following properties:
* `1 + a * a∗ ≤ a∗`
* `1 + a∗ * a ≤ a∗`
* If `a * c + b ≤ c`, then `a∗ * b ≤ c`
* If `c * a + b ≤ c`, then `b * a∗ ≤ c`
-/
class KleeneAlgebra (α : Type*) extends IdemSemiring α, KStar α where
protected one_le_kstar : ∀ a : α, 1 ≤ a∗
protected mul_kstar_le_kstar : ∀ a : α, a * a∗ ≤ a∗
protected kstar_mul_le_kstar : ∀ a : α, a∗ * a ≤ a∗
protected mul_kstar_le_self : ∀ a b : α, b * a ≤ b → b * a∗ ≤ b
protected kstar_mul_le_self : ∀ a b : α, a * b ≤ b → a∗ * b ≤ b
#align kleene_algebra KleeneAlgebra
-- See note [lower instance priority]
instance (priority := 100) IdemSemiring.toOrderBot [IdemSemiring α] : OrderBot α :=
{ ‹IdemSemiring α› with }
#align idem_semiring.to_order_bot IdemSemiring.toOrderBot
-- See note [reducible non-instances]
/-- Construct an idempotent semiring from an idempotent addition. -/
abbrev IdemSemiring.ofSemiring [Semiring α] (h : ∀ a : α, a + a = a) : IdemSemiring α :=
{ ‹Semiring α› with
le := fun a b ↦ a + b = b
le_refl := h
le_trans := fun a b c hab hbc ↦ by
simp only
rw [← hbc, ← add_assoc, hab]
le_antisymm := fun a b hab hba ↦ by rwa [← hba, add_comm]
sup := (· + ·)
le_sup_left := fun a b ↦ by
simp only
rw [← add_assoc, h]
le_sup_right := fun a b ↦ by
simp only
rw [add_comm, add_assoc, h]
sup_le := fun a b c hab hbc ↦ by
simp only
rwa [add_assoc, hbc]
bot := 0
bot_le := zero_add }
#align idem_semiring.of_semiring IdemSemiring.ofSemiring
section IdemSemiring
variable [IdemSemiring α] {a b c : α}
theorem add_eq_sup (a b : α) : a + b = a ⊔ b :=
IdemSemiring.add_eq_sup _ _
#align add_eq_sup add_eq_sup
-- Porting note: This simp theorem often leads to timeout when `α` has rich structure.
-- So, this theorem should be scoped.
scoped[Computability] attribute [simp] add_eq_sup
theorem add_idem (a : α) : a + a = a := by simp
#align add_idem add_idem
theorem nsmul_eq_self : ∀ {n : ℕ} (_ : n ≠ 0) (a : α), n • a = a
| 0, h => (h rfl).elim
| 1, _ => one_nsmul
| n + 2, _ => fun a ↦ by rw [succ_nsmul, nsmul_eq_self n.succ_ne_zero, add_idem]
#align nsmul_eq_self nsmul_eq_self
theorem add_eq_left_iff_le : a + b = a ↔ b ≤ a := by simp
#align add_eq_left_iff_le add_eq_left_iff_le
| Mathlib/Algebra/Order/Kleene.lean | 154 | 154 | theorem add_eq_right_iff_le : a + b = b ↔ a ≤ b := by | simp
|
/-
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.Normed.Group.Hom
import Mathlib.Analysis.SpecialFunctions.Pow.Continuity
import Mathlib.Data.Set.Image
import Mathlib.MeasureTheory.Function.LpSeminorm.ChebyshevMarkov
import Mathlib.MeasureTheory.Function.LpSeminorm.CompareExp
import Mathlib.MeasureTheory.Function.LpSeminorm.TriangleInequality
import Mathlib.MeasureTheory.Measure.OpenPos
import Mathlib.Topology.ContinuousFunction.Compact
import Mathlib.Order.Filter.IndicatorFunction
#align_import measure_theory.function.lp_space from "leanprover-community/mathlib"@"c4015acc0a223449d44061e27ddac1835a3852b9"
/-!
# Lp space
This file provides the space `Lp E p μ` as the subtype of elements of `α →ₘ[μ] E` (see ae_eq_fun)
such that `snorm f p μ` is finite. For `1 ≤ p`, `snorm` defines a norm and `Lp` is a complete metric
space.
## Main definitions
* `Lp E p μ` : elements of `α →ₘ[μ] E` (see ae_eq_fun) such that `snorm f p μ` is finite. Defined
as an `AddSubgroup` of `α →ₘ[μ] E`.
Lipschitz functions vanishing at zero act by composition on `Lp`. We define this action, and prove
that it is continuous. In particular,
* `ContinuousLinearMap.compLp` defines the action on `Lp` of a continuous linear map.
* `Lp.posPart` is the positive part of an `Lp` function.
* `Lp.negPart` is the negative part of an `Lp` function.
When `α` is a topological space equipped with a finite Borel measure, there is a bounded linear map
from the normed space of bounded continuous functions (`α →ᵇ E`) to `Lp E p μ`. We construct this
as `BoundedContinuousFunction.toLp`.
## Notations
* `α →₁[μ] E` : the type `Lp E 1 μ`.
* `α →₂[μ] E` : the type `Lp E 2 μ`.
## Implementation
Since `Lp` is defined as an `AddSubgroup`, dot notation does not work. Use `Lp.Measurable f` to
say that the coercion of `f` to a genuine function is measurable, instead of the non-working
`f.Measurable`.
To prove that two `Lp` elements are equal, it suffices to show that their coercions to functions
coincide almost everywhere (this is registered as an `ext` rule). This can often be done using
`filter_upwards`. For instance, a proof from first principles that `f + (g + h) = (f + g) + h`
could read (in the `Lp` namespace)
```
example (f g h : Lp E p μ) : (f + g) + h = f + (g + h) := by
ext1
filter_upwards [coeFn_add (f + g) h, coeFn_add f g, coeFn_add f (g + h), coeFn_add g h]
with _ ha1 ha2 ha3 ha4
simp only [ha1, ha2, ha3, ha4, add_assoc]
```
The lemma `coeFn_add` states that the coercion of `f + g` coincides almost everywhere with the sum
of the coercions of `f` and `g`. All such lemmas use `coeFn` in their name, to distinguish the
function coercion from the coercion to almost everywhere defined functions.
-/
noncomputable section
set_option linter.uppercaseLean3 false
open TopologicalSpace MeasureTheory Filter
open scoped NNReal ENNReal Topology MeasureTheory Uniformity
variable {α E F G : Type*} {m m0 : MeasurableSpace α} {p : ℝ≥0∞} {q : ℝ} {μ ν : Measure α}
[NormedAddCommGroup E] [NormedAddCommGroup F] [NormedAddCommGroup G]
namespace MeasureTheory
/-!
### Lp space
The space of equivalence classes of measurable functions for which `snorm f p μ < ∞`.
-/
@[simp]
theorem snorm_aeeqFun {α E : Type*} [MeasurableSpace α] {μ : Measure α} [NormedAddCommGroup E]
{p : ℝ≥0∞} {f : α → E} (hf : AEStronglyMeasurable f μ) :
snorm (AEEqFun.mk f hf) p μ = snorm f p μ :=
snorm_congr_ae (AEEqFun.coeFn_mk _ _)
#align measure_theory.snorm_ae_eq_fun MeasureTheory.snorm_aeeqFun
theorem Memℒp.snorm_mk_lt_top {α E : Type*} [MeasurableSpace α] {μ : Measure α}
[NormedAddCommGroup E] {p : ℝ≥0∞} {f : α → E} (hfp : Memℒp f p μ) :
snorm (AEEqFun.mk f hfp.1) p μ < ∞ := by simp [hfp.2]
#align measure_theory.mem_ℒp.snorm_mk_lt_top MeasureTheory.Memℒp.snorm_mk_lt_top
/-- Lp space -/
def Lp {α} (E : Type*) {m : MeasurableSpace α} [NormedAddCommGroup E] (p : ℝ≥0∞)
(μ : Measure α := by volume_tac) : AddSubgroup (α →ₘ[μ] E) where
carrier := { f | snorm f p μ < ∞ }
zero_mem' := by simp [snorm_congr_ae AEEqFun.coeFn_zero, snorm_zero]
add_mem' {f g} hf hg := by
simp [snorm_congr_ae (AEEqFun.coeFn_add f g),
snorm_add_lt_top ⟨f.aestronglyMeasurable, hf⟩ ⟨g.aestronglyMeasurable, hg⟩]
neg_mem' {f} hf := by rwa [Set.mem_setOf_eq, snorm_congr_ae (AEEqFun.coeFn_neg f), snorm_neg]
#align measure_theory.Lp MeasureTheory.Lp
-- Porting note: calling the first argument `α` breaks the `(α := ·)` notation
scoped notation:25 α' " →₁[" μ "] " E => MeasureTheory.Lp (α := α') E 1 μ
scoped notation:25 α' " →₂[" μ "] " E => MeasureTheory.Lp (α := α') E 2 μ
namespace Memℒp
/-- make an element of Lp from a function verifying `Memℒp` -/
def toLp (f : α → E) (h_mem_ℒp : Memℒp f p μ) : Lp E p μ :=
⟨AEEqFun.mk f h_mem_ℒp.1, h_mem_ℒp.snorm_mk_lt_top⟩
#align measure_theory.mem_ℒp.to_Lp MeasureTheory.Memℒp.toLp
theorem coeFn_toLp {f : α → E} (hf : Memℒp f p μ) : hf.toLp f =ᵐ[μ] f :=
AEEqFun.coeFn_mk _ _
#align measure_theory.mem_ℒp.coe_fn_to_Lp MeasureTheory.Memℒp.coeFn_toLp
theorem toLp_congr {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) (hfg : f =ᵐ[μ] g) :
hf.toLp f = hg.toLp g := by simp [toLp, hfg]
#align measure_theory.mem_ℒp.to_Lp_congr MeasureTheory.Memℒp.toLp_congr
@[simp]
theorem toLp_eq_toLp_iff {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
hf.toLp f = hg.toLp g ↔ f =ᵐ[μ] g := by simp [toLp]
#align measure_theory.mem_ℒp.to_Lp_eq_to_Lp_iff MeasureTheory.Memℒp.toLp_eq_toLp_iff
@[simp]
theorem toLp_zero (h : Memℒp (0 : α → E) p μ) : h.toLp 0 = 0 :=
rfl
#align measure_theory.mem_ℒp.to_Lp_zero MeasureTheory.Memℒp.toLp_zero
theorem toLp_add {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.add hg).toLp (f + g) = hf.toLp f + hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_add MeasureTheory.Memℒp.toLp_add
theorem toLp_neg {f : α → E} (hf : Memℒp f p μ) : hf.neg.toLp (-f) = -hf.toLp f :=
rfl
#align measure_theory.mem_ℒp.to_Lp_neg MeasureTheory.Memℒp.toLp_neg
theorem toLp_sub {f g : α → E} (hf : Memℒp f p μ) (hg : Memℒp g p μ) :
(hf.sub hg).toLp (f - g) = hf.toLp f - hg.toLp g :=
rfl
#align measure_theory.mem_ℒp.to_Lp_sub MeasureTheory.Memℒp.toLp_sub
end Memℒp
namespace Lp
instance instCoeFun : CoeFun (Lp E p μ) (fun _ => α → E) :=
⟨fun f => ((f : α →ₘ[μ] E) : α → E)⟩
#align measure_theory.Lp.has_coe_to_fun MeasureTheory.Lp.instCoeFun
@[ext high]
theorem ext {f g : Lp E p μ} (h : f =ᵐ[μ] g) : f = g := by
cases f
cases g
simp only [Subtype.mk_eq_mk]
exact AEEqFun.ext h
#align measure_theory.Lp.ext MeasureTheory.Lp.ext
theorem ext_iff {f g : Lp E p μ} : f = g ↔ f =ᵐ[μ] g :=
⟨fun h => by rw [h], fun h => ext h⟩
#align measure_theory.Lp.ext_iff MeasureTheory.Lp.ext_iff
theorem mem_Lp_iff_snorm_lt_top {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ snorm f p μ < ∞ := Iff.rfl
#align measure_theory.Lp.mem_Lp_iff_snorm_lt_top MeasureTheory.Lp.mem_Lp_iff_snorm_lt_top
theorem mem_Lp_iff_memℒp {f : α →ₘ[μ] E} : f ∈ Lp E p μ ↔ Memℒp f p μ := by
simp [mem_Lp_iff_snorm_lt_top, Memℒp, f.stronglyMeasurable.aestronglyMeasurable]
#align measure_theory.Lp.mem_Lp_iff_mem_ℒp MeasureTheory.Lp.mem_Lp_iff_memℒp
protected theorem antitone [IsFiniteMeasure μ] {p q : ℝ≥0∞} (hpq : p ≤ q) : Lp E q μ ≤ Lp E p μ :=
fun f hf => (Memℒp.memℒp_of_exponent_le ⟨f.aestronglyMeasurable, hf⟩ hpq).2
#align measure_theory.Lp.antitone MeasureTheory.Lp.antitone
@[simp]
theorem coeFn_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α → E) = f :=
rfl
#align measure_theory.Lp.coe_fn_mk MeasureTheory.Lp.coeFn_mk
-- @[simp] -- Porting note (#10685): dsimp can prove this
theorem coe_mk {f : α →ₘ[μ] E} (hf : snorm f p μ < ∞) : ((⟨f, hf⟩ : Lp E p μ) : α →ₘ[μ] E) = f :=
rfl
#align measure_theory.Lp.coe_mk MeasureTheory.Lp.coe_mk
@[simp]
theorem toLp_coeFn (f : Lp E p μ) (hf : Memℒp f p μ) : hf.toLp f = f := by
cases f
simp [Memℒp.toLp]
#align measure_theory.Lp.to_Lp_coe_fn MeasureTheory.Lp.toLp_coeFn
theorem snorm_lt_top (f : Lp E p μ) : snorm f p μ < ∞ :=
f.prop
#align measure_theory.Lp.snorm_lt_top MeasureTheory.Lp.snorm_lt_top
theorem snorm_ne_top (f : Lp E p μ) : snorm f p μ ≠ ∞ :=
(snorm_lt_top f).ne
#align measure_theory.Lp.snorm_ne_top MeasureTheory.Lp.snorm_ne_top
@[measurability]
protected theorem stronglyMeasurable (f : Lp E p μ) : StronglyMeasurable f :=
f.val.stronglyMeasurable
#align measure_theory.Lp.strongly_measurable MeasureTheory.Lp.stronglyMeasurable
@[measurability]
protected theorem aestronglyMeasurable (f : Lp E p μ) : AEStronglyMeasurable f μ :=
f.val.aestronglyMeasurable
#align measure_theory.Lp.ae_strongly_measurable MeasureTheory.Lp.aestronglyMeasurable
protected theorem memℒp (f : Lp E p μ) : Memℒp f p μ :=
⟨Lp.aestronglyMeasurable f, f.prop⟩
#align measure_theory.Lp.mem_ℒp MeasureTheory.Lp.memℒp
variable (E p μ)
theorem coeFn_zero : ⇑(0 : Lp E p μ) =ᵐ[μ] 0 :=
AEEqFun.coeFn_zero
#align measure_theory.Lp.coe_fn_zero MeasureTheory.Lp.coeFn_zero
variable {E p μ}
theorem coeFn_neg (f : Lp E p μ) : ⇑(-f) =ᵐ[μ] -f :=
AEEqFun.coeFn_neg _
#align measure_theory.Lp.coe_fn_neg MeasureTheory.Lp.coeFn_neg
theorem coeFn_add (f g : Lp E p μ) : ⇑(f + g) =ᵐ[μ] f + g :=
AEEqFun.coeFn_add _ _
#align measure_theory.Lp.coe_fn_add MeasureTheory.Lp.coeFn_add
theorem coeFn_sub (f g : Lp E p μ) : ⇑(f - g) =ᵐ[μ] f - g :=
AEEqFun.coeFn_sub _ _
#align measure_theory.Lp.coe_fn_sub MeasureTheory.Lp.coeFn_sub
theorem const_mem_Lp (α) {_ : MeasurableSpace α} (μ : Measure α) (c : E) [IsFiniteMeasure μ] :
@AEEqFun.const α _ _ μ _ c ∈ Lp E p μ :=
(memℒp_const c).snorm_mk_lt_top
#align measure_theory.Lp.mem_Lp_const MeasureTheory.Lp.const_mem_Lp
instance instNorm : Norm (Lp E p μ) where norm f := ENNReal.toReal (snorm f p μ)
#align measure_theory.Lp.has_norm MeasureTheory.Lp.instNorm
-- note: we need this to be defeq to the instance from `SeminormedAddGroup.toNNNorm`, so
-- can't use `ENNReal.toNNReal (snorm f p μ)`
instance instNNNorm : NNNorm (Lp E p μ) where nnnorm f := ⟨‖f‖, ENNReal.toReal_nonneg⟩
#align measure_theory.Lp.has_nnnorm MeasureTheory.Lp.instNNNorm
instance instDist : Dist (Lp E p μ) where dist f g := ‖f - g‖
#align measure_theory.Lp.has_dist MeasureTheory.Lp.instDist
instance instEDist : EDist (Lp E p μ) where edist f g := snorm (⇑f - ⇑g) p μ
#align measure_theory.Lp.has_edist MeasureTheory.Lp.instEDist
theorem norm_def (f : Lp E p μ) : ‖f‖ = ENNReal.toReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.norm_def MeasureTheory.Lp.norm_def
theorem nnnorm_def (f : Lp E p μ) : ‖f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
rfl
#align measure_theory.Lp.nnnorm_def MeasureTheory.Lp.nnnorm_def
@[simp, norm_cast]
protected theorem coe_nnnorm (f : Lp E p μ) : (‖f‖₊ : ℝ) = ‖f‖ :=
rfl
#align measure_theory.Lp.coe_nnnorm MeasureTheory.Lp.coe_nnnorm
@[simp, norm_cast]
theorem nnnorm_coe_ennreal (f : Lp E p μ) : (‖f‖₊ : ℝ≥0∞) = snorm f p μ :=
ENNReal.coe_toNNReal <| Lp.snorm_ne_top f
@[simp]
theorem norm_toLp (f : α → E) (hf : Memℒp f p μ) : ‖hf.toLp f‖ = ENNReal.toReal (snorm f p μ) := by
erw [norm_def, snorm_congr_ae (Memℒp.coeFn_toLp hf)]
#align measure_theory.Lp.norm_to_Lp MeasureTheory.Lp.norm_toLp
@[simp]
theorem nnnorm_toLp (f : α → E) (hf : Memℒp f p μ) :
‖hf.toLp f‖₊ = ENNReal.toNNReal (snorm f p μ) :=
NNReal.eq <| norm_toLp f hf
#align measure_theory.Lp.nnnorm_to_Lp MeasureTheory.Lp.nnnorm_toLp
| Mathlib/MeasureTheory/Function/LpSpace.lean | 290 | 291 | theorem coe_nnnorm_toLp {f : α → E} (hf : Memℒp f p μ) : (‖hf.toLp f‖₊ : ℝ≥0∞) = snorm f p μ := by |
rw [nnnorm_toLp f hf, ENNReal.coe_toNNReal hf.2.ne]
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Data.Finset.Sort
import Mathlib.Data.Set.Subsingleton
#align_import combinatorics.composition from "leanprover-community/mathlib"@"92ca63f0fb391a9ca5f22d2409a6080e786d99f7"
/-!
# Compositions
A composition of a natural number `n` is a decomposition `n = i₀ + ... + i_{k-1}` of `n` into a sum
of positive integers. Combinatorially, it corresponds to a decomposition of `{0, ..., n-1}` into
non-empty blocks of consecutive integers, where the `iⱼ` are the lengths of the blocks.
This notion is closely related to that of a partition of `n`, but in a composition of `n` the
order of the `iⱼ`s matters.
We implement two different structures covering these two viewpoints on compositions. The first
one, made of a list of positive integers summing to `n`, is the main one and is called
`Composition n`. The second one is useful for combinatorial arguments (for instance to show that
the number of compositions of `n` is `2^(n-1)`). It is given by a subset of `{0, ..., n}`
containing `0` and `n`, where the elements of the subset (other than `n`) correspond to the leftmost
points of each block. The main API is built on `Composition n`, and we provide an equivalence
between the two types.
## Main functions
* `c : Composition n` is a structure, made of a list of integers which are all positive and
add up to `n`.
* `composition_card` states that the cardinality of `Composition n` is exactly
`2^(n-1)`, which is proved by constructing an equiv with `CompositionAsSet n` (see below), which
is itself in bijection with the subsets of `Fin (n-1)` (this holds even for `n = 0`, where `-` is
nat subtraction).
Let `c : Composition n` be a composition of `n`. Then
* `c.blocks` is the list of blocks in `c`.
* `c.length` is the number of blocks in the composition.
* `c.blocks_fun : Fin c.length → ℕ` is the realization of `c.blocks` as a function on
`Fin c.length`. This is the main object when using compositions to understand the composition of
analytic functions.
* `c.sizeUpTo : ℕ → ℕ` is the sum of the size of the blocks up to `i`.;
* `c.embedding i : Fin (c.blocks_fun i) → Fin n` is the increasing embedding of the `i`-th block in
`Fin n`;
* `c.index j`, for `j : Fin n`, is the index of the block containing `j`.
* `Composition.ones n` is the composition of `n` made of ones, i.e., `[1, ..., 1]`.
* `Composition.single n (hn : 0 < n)` is the composition of `n` made of a single block of size `n`.
Compositions can also be used to split lists. Let `l` be a list of length `n` and `c` a composition
of `n`.
* `l.splitWrtComposition c` is a list of lists, made of the slices of `l` corresponding to the
blocks of `c`.
* `join_splitWrtComposition` states that splitting a list and then joining it gives back the
original list.
* `joinSplitWrtComposition_join` states that joining a list of lists, and then splitting it back
according to the right composition, gives back the original list of lists.
We turn to the second viewpoint on compositions, that we realize as a finset of `Fin (n+1)`.
`c : CompositionAsSet n` is a structure made of a finset of `Fin (n+1)` called `c.boundaries`
and proofs that it contains `0` and `n`. (Taking a finset of `Fin n` containing `0` would not
make sense in the edge case `n = 0`, while the previous description works in all cases).
The elements of this set (other than `n`) correspond to leftmost points of blocks.
Thus, there is an equiv between `Composition n` and `CompositionAsSet n`. We
only construct basic API on `CompositionAsSet` (notably `c.length` and `c.blocks`) to be able
to construct this equiv, called `compositionEquiv n`. Since there is a straightforward equiv
between `CompositionAsSet n` and finsets of `{1, ..., n-1}` (obtained by removing `0` and `n`
from a `CompositionAsSet` and called `compositionAsSetEquiv n`), we deduce that
`CompositionAsSet n` and `Composition n` are both fintypes of cardinality `2^(n - 1)`
(see `compositionAsSet_card` and `composition_card`).
## Implementation details
The main motivation for this structure and its API is in the construction of the composition of
formal multilinear series, and the proof that the composition of analytic functions is analytic.
The representation of a composition as a list is very handy as lists are very flexible and already
have a well-developed API.
## Tags
Composition, partition
## References
<https://en.wikipedia.org/wiki/Composition_(combinatorics)>
-/
open List
variable {n : ℕ}
/-- A composition of `n` is a list of positive integers summing to `n`. -/
@[ext]
structure Composition (n : ℕ) where
/-- List of positive integers summing to `n`-/
blocks : List ℕ
/-- Proof of positivity for `blocks`-/
blocks_pos : ∀ {i}, i ∈ blocks → 0 < i
/-- Proof that `blocks` sums to `n`-/
blocks_sum : blocks.sum = n
#align composition Composition
/-- Combinatorial viewpoint on a composition of `n`, by seeing it as non-empty blocks of
consecutive integers in `{0, ..., n-1}`. We register every block by its left end-point, yielding
a finset containing `0`. As this does not make sense for `n = 0`, we add `n` to this finset, and
get a finset of `{0, ..., n}` containing `0` and `n`. This is the data in the structure
`CompositionAsSet n`. -/
@[ext]
structure CompositionAsSet (n : ℕ) where
/-- Combinatorial viewpoint on a composition of `n` as consecutive integers `{0, ..., n-1}`-/
boundaries : Finset (Fin n.succ)
/-- Proof that `0` is a member of `boundaries`-/
zero_mem : (0 : Fin n.succ) ∈ boundaries
/-- Last element of the composition-/
getLast_mem : Fin.last n ∈ boundaries
#align composition_as_set CompositionAsSet
instance {n : ℕ} : Inhabited (CompositionAsSet n) :=
⟨⟨Finset.univ, Finset.mem_univ _, Finset.mem_univ _⟩⟩
/-!
### Compositions
A composition of an integer `n` is a decomposition `n = i₀ + ... + i_{k-1}` of `n` into a sum of
positive integers.
-/
namespace Composition
variable (c : Composition n)
instance (n : ℕ) : ToString (Composition n) :=
⟨fun c => toString c.blocks⟩
/-- The length of a composition, i.e., the number of blocks in the composition. -/
abbrev length : ℕ :=
c.blocks.length
#align composition.length Composition.length
theorem blocks_length : c.blocks.length = c.length :=
rfl
#align composition.blocks_length Composition.blocks_length
/-- The blocks of a composition, seen as a function on `Fin c.length`. When composing analytic
functions using compositions, this is the main player. -/
def blocksFun : Fin c.length → ℕ := c.blocks.get
#align composition.blocks_fun Composition.blocksFun
theorem ofFn_blocksFun : ofFn c.blocksFun = c.blocks :=
ofFn_get _
#align composition.of_fn_blocks_fun Composition.ofFn_blocksFun
theorem sum_blocksFun : ∑ i, c.blocksFun i = n := by
conv_rhs => rw [← c.blocks_sum, ← ofFn_blocksFun, sum_ofFn]
#align composition.sum_blocks_fun Composition.sum_blocksFun
theorem blocksFun_mem_blocks (i : Fin c.length) : c.blocksFun i ∈ c.blocks :=
get_mem _ _ _
#align composition.blocks_fun_mem_blocks Composition.blocksFun_mem_blocks
@[simp]
theorem one_le_blocks {i : ℕ} (h : i ∈ c.blocks) : 1 ≤ i :=
c.blocks_pos h
#align composition.one_le_blocks Composition.one_le_blocks
@[simp]
theorem one_le_blocks' {i : ℕ} (h : i < c.length) : 1 ≤ c.blocks.get ⟨i, h⟩ :=
c.one_le_blocks (get_mem (blocks c) i h)
#align composition.one_le_blocks' Composition.one_le_blocks'
@[simp]
theorem blocks_pos' (i : ℕ) (h : i < c.length) : 0 < c.blocks.get ⟨i, h⟩ :=
c.one_le_blocks' h
#align composition.blocks_pos' Composition.blocks_pos'
theorem one_le_blocksFun (i : Fin c.length) : 1 ≤ c.blocksFun i :=
c.one_le_blocks (c.blocksFun_mem_blocks i)
#align composition.one_le_blocks_fun Composition.one_le_blocksFun
theorem length_le : c.length ≤ n := by
conv_rhs => rw [← c.blocks_sum]
exact length_le_sum_of_one_le _ fun i hi => c.one_le_blocks hi
#align composition.length_le Composition.length_le
theorem length_pos_of_pos (h : 0 < n) : 0 < c.length := by
apply length_pos_of_sum_pos
convert h
exact c.blocks_sum
#align composition.length_pos_of_pos Composition.length_pos_of_pos
/-- The sum of the sizes of the blocks in a composition up to `i`. -/
def sizeUpTo (i : ℕ) : ℕ :=
(c.blocks.take i).sum
#align composition.size_up_to Composition.sizeUpTo
@[simp]
theorem sizeUpTo_zero : c.sizeUpTo 0 = 0 := by simp [sizeUpTo]
#align composition.size_up_to_zero Composition.sizeUpTo_zero
theorem sizeUpTo_ofLength_le (i : ℕ) (h : c.length ≤ i) : c.sizeUpTo i = n := by
dsimp [sizeUpTo]
convert c.blocks_sum
exact take_all_of_le h
#align composition.size_up_to_of_length_le Composition.sizeUpTo_ofLength_le
@[simp]
theorem sizeUpTo_length : c.sizeUpTo c.length = n :=
c.sizeUpTo_ofLength_le c.length le_rfl
#align composition.size_up_to_length Composition.sizeUpTo_length
theorem sizeUpTo_le (i : ℕ) : c.sizeUpTo i ≤ n := by
conv_rhs => rw [← c.blocks_sum, ← sum_take_add_sum_drop _ i]
exact Nat.le_add_right _ _
#align composition.size_up_to_le Composition.sizeUpTo_le
theorem sizeUpTo_succ {i : ℕ} (h : i < c.length) :
c.sizeUpTo (i + 1) = c.sizeUpTo i + c.blocks.get ⟨i, h⟩ := by
simp only [sizeUpTo]
rw [sum_take_succ _ _ h]
#align composition.size_up_to_succ Composition.sizeUpTo_succ
theorem sizeUpTo_succ' (i : Fin c.length) :
c.sizeUpTo ((i : ℕ) + 1) = c.sizeUpTo i + c.blocksFun i :=
c.sizeUpTo_succ i.2
#align composition.size_up_to_succ' Composition.sizeUpTo_succ'
theorem sizeUpTo_strict_mono {i : ℕ} (h : i < c.length) : c.sizeUpTo i < c.sizeUpTo (i + 1) := by
rw [c.sizeUpTo_succ h]
simp
#align composition.size_up_to_strict_mono Composition.sizeUpTo_strict_mono
theorem monotone_sizeUpTo : Monotone c.sizeUpTo :=
monotone_sum_take _
#align composition.monotone_size_up_to Composition.monotone_sizeUpTo
/-- The `i`-th boundary of a composition, i.e., the leftmost point of the `i`-th block. We include
a virtual point at the right of the last block, to make for a nice equiv with
`CompositionAsSet n`. -/
def boundary : Fin (c.length + 1) ↪o Fin (n + 1) :=
(OrderEmbedding.ofStrictMono fun i => ⟨c.sizeUpTo i, Nat.lt_succ_of_le (c.sizeUpTo_le i)⟩) <|
Fin.strictMono_iff_lt_succ.2 fun ⟨_, hi⟩ => c.sizeUpTo_strict_mono hi
#align composition.boundary Composition.boundary
@[simp]
theorem boundary_zero : c.boundary 0 = 0 := by simp [boundary, Fin.ext_iff]
#align composition.boundary_zero Composition.boundary_zero
@[simp]
theorem boundary_last : c.boundary (Fin.last c.length) = Fin.last n := by
simp [boundary, Fin.ext_iff]
#align composition.boundary_last Composition.boundary_last
/-- The boundaries of a composition, i.e., the leftmost point of all the blocks. We include
a virtual point at the right of the last block, to make for a nice equiv with
`CompositionAsSet n`. -/
def boundaries : Finset (Fin (n + 1)) :=
Finset.univ.map c.boundary.toEmbedding
#align composition.boundaries Composition.boundaries
theorem card_boundaries_eq_succ_length : c.boundaries.card = c.length + 1 := by simp [boundaries]
#align composition.card_boundaries_eq_succ_length Composition.card_boundaries_eq_succ_length
/-- To `c : Composition n`, one can associate a `CompositionAsSet n` by registering the leftmost
point of each block, and adding a virtual point at the right of the last block. -/
def toCompositionAsSet : CompositionAsSet n where
boundaries := c.boundaries
zero_mem := by
simp only [boundaries, Finset.mem_univ, exists_prop_of_true, Finset.mem_map]
exact ⟨0, And.intro True.intro rfl⟩
getLast_mem := by
simp only [boundaries, Finset.mem_univ, exists_prop_of_true, Finset.mem_map]
exact ⟨Fin.last c.length, And.intro True.intro c.boundary_last⟩
#align composition.to_composition_as_set Composition.toCompositionAsSet
/-- The canonical increasing bijection between `Fin (c.length + 1)` and `c.boundaries` is
exactly `c.boundary`. -/
theorem orderEmbOfFin_boundaries :
c.boundaries.orderEmbOfFin c.card_boundaries_eq_succ_length = c.boundary := by
refine (Finset.orderEmbOfFin_unique' _ ?_).symm
exact fun i => (Finset.mem_map' _).2 (Finset.mem_univ _)
#align composition.order_emb_of_fin_boundaries Composition.orderEmbOfFin_boundaries
/-- Embedding the `i`-th block of a composition (identified with `Fin (c.blocks_fun i)`) into
`Fin n` at the relevant position. -/
def embedding (i : Fin c.length) : Fin (c.blocksFun i) ↪o Fin n :=
(Fin.natAddOrderEmb <| c.sizeUpTo i).trans <| Fin.castLEOrderEmb <|
calc
c.sizeUpTo i + c.blocksFun i = c.sizeUpTo (i + 1) := (c.sizeUpTo_succ _).symm
_ ≤ c.sizeUpTo c.length := monotone_sum_take _ i.2
_ = n := c.sizeUpTo_length
#align composition.embedding Composition.embedding
@[simp]
theorem coe_embedding (i : Fin c.length) (j : Fin (c.blocksFun i)) :
(c.embedding i j : ℕ) = c.sizeUpTo i + j :=
rfl
#align composition.coe_embedding Composition.coe_embedding
/-- `index_exists` asserts there is some `i` with `j < c.size_up_to (i+1)`.
In the next definition `index` we use `Nat.find` to produce the minimal such index.
-/
theorem index_exists {j : ℕ} (h : j < n) : ∃ i : ℕ, j < c.sizeUpTo (i + 1) ∧ i < c.length := by
have n_pos : 0 < n := lt_of_le_of_lt (zero_le j) h
have : 0 < c.blocks.sum := by rwa [← c.blocks_sum] at n_pos
have length_pos : 0 < c.blocks.length := length_pos_of_sum_pos (blocks c) this
refine ⟨c.length - 1, ?_, Nat.pred_lt (ne_of_gt length_pos)⟩
have : c.length - 1 + 1 = c.length := Nat.succ_pred_eq_of_pos length_pos
simp [this, h]
#align composition.index_exists Composition.index_exists
/-- `c.index j` is the index of the block in the composition `c` containing `j`. -/
def index (j : Fin n) : Fin c.length :=
⟨Nat.find (c.index_exists j.2), (Nat.find_spec (c.index_exists j.2)).2⟩
#align composition.index Composition.index
theorem lt_sizeUpTo_index_succ (j : Fin n) : (j : ℕ) < c.sizeUpTo (c.index j).succ :=
(Nat.find_spec (c.index_exists j.2)).1
#align composition.lt_size_up_to_index_succ Composition.lt_sizeUpTo_index_succ
theorem sizeUpTo_index_le (j : Fin n) : c.sizeUpTo (c.index j) ≤ j := by
by_contra H
set i := c.index j
push_neg at H
have i_pos : (0 : ℕ) < i := by
by_contra! i_pos
revert H
simp [nonpos_iff_eq_zero.1 i_pos, c.sizeUpTo_zero]
let i₁ := (i : ℕ).pred
have i₁_lt_i : i₁ < i := Nat.pred_lt (ne_of_gt i_pos)
have i₁_succ : i₁ + 1 = i := Nat.succ_pred_eq_of_pos i_pos
have := Nat.find_min (c.index_exists j.2) i₁_lt_i
simp [lt_trans i₁_lt_i (c.index j).2, i₁_succ] at this
exact Nat.lt_le_asymm H this
#align composition.size_up_to_index_le Composition.sizeUpTo_index_le
/-- Mapping an element `j` of `Fin n` to the element in the block containing it, identified with
`Fin (c.blocks_fun (c.index j))` through the canonical increasing bijection. -/
def invEmbedding (j : Fin n) : Fin (c.blocksFun (c.index j)) :=
⟨j - c.sizeUpTo (c.index j), by
rw [tsub_lt_iff_right, add_comm, ← sizeUpTo_succ']
· exact lt_sizeUpTo_index_succ _ _
· exact sizeUpTo_index_le _ _⟩
#align composition.inv_embedding Composition.invEmbedding
@[simp]
theorem coe_invEmbedding (j : Fin n) : (c.invEmbedding j : ℕ) = j - c.sizeUpTo (c.index j) :=
rfl
#align composition.coe_inv_embedding Composition.coe_invEmbedding
theorem embedding_comp_inv (j : Fin n) : c.embedding (c.index j) (c.invEmbedding j) = j := by
rw [Fin.ext_iff]
apply add_tsub_cancel_of_le (c.sizeUpTo_index_le j)
#align composition.embedding_comp_inv Composition.embedding_comp_inv
theorem mem_range_embedding_iff {j : Fin n} {i : Fin c.length} :
j ∈ Set.range (c.embedding i) ↔ c.sizeUpTo i ≤ j ∧ (j : ℕ) < c.sizeUpTo (i : ℕ).succ := by
constructor
· intro h
rcases Set.mem_range.2 h with ⟨k, hk⟩
rw [Fin.ext_iff] at hk
dsimp at hk
rw [← hk]
simp [sizeUpTo_succ', k.is_lt]
· intro h
apply Set.mem_range.2
refine ⟨⟨j - c.sizeUpTo i, ?_⟩, ?_⟩
· rw [tsub_lt_iff_left, ← sizeUpTo_succ']
· exact h.2
· exact h.1
· rw [Fin.ext_iff]
exact add_tsub_cancel_of_le h.1
#align composition.mem_range_embedding_iff Composition.mem_range_embedding_iff
/-- The embeddings of different blocks of a composition are disjoint. -/
theorem disjoint_range {i₁ i₂ : Fin c.length} (h : i₁ ≠ i₂) :
Disjoint (Set.range (c.embedding i₁)) (Set.range (c.embedding i₂)) := by
classical
wlog h' : i₁ < i₂
· exact (this c h.symm (h.lt_or_lt.resolve_left h')).symm
by_contra d
obtain ⟨x, hx₁, hx₂⟩ :
∃ x : Fin n, x ∈ Set.range (c.embedding i₁) ∧ x ∈ Set.range (c.embedding i₂) :=
Set.not_disjoint_iff.1 d
have A : (i₁ : ℕ).succ ≤ i₂ := Nat.succ_le_of_lt h'
apply lt_irrefl (x : ℕ)
calc
(x : ℕ) < c.sizeUpTo (i₁ : ℕ).succ := (c.mem_range_embedding_iff.1 hx₁).2
_ ≤ c.sizeUpTo (i₂ : ℕ) := monotone_sum_take _ A
_ ≤ x := (c.mem_range_embedding_iff.1 hx₂).1
#align composition.disjoint_range Composition.disjoint_range
theorem mem_range_embedding (j : Fin n) : j ∈ Set.range (c.embedding (c.index j)) := by
have : c.embedding (c.index j) (c.invEmbedding j) ∈ Set.range (c.embedding (c.index j)) :=
Set.mem_range_self _
rwa [c.embedding_comp_inv j] at this
#align composition.mem_range_embedding Composition.mem_range_embedding
theorem mem_range_embedding_iff' {j : Fin n} {i : Fin c.length} :
j ∈ Set.range (c.embedding i) ↔ i = c.index j := by
constructor
· rw [← not_imp_not]
intro h
exact Set.disjoint_right.1 (c.disjoint_range h) (c.mem_range_embedding j)
· intro h
rw [h]
exact c.mem_range_embedding j
#align composition.mem_range_embedding_iff' Composition.mem_range_embedding_iff'
theorem index_embedding (i : Fin c.length) (j : Fin (c.blocksFun i)) :
c.index (c.embedding i j) = i := by
symm
rw [← mem_range_embedding_iff']
apply Set.mem_range_self
#align composition.index_embedding Composition.index_embedding
theorem invEmbedding_comp (i : Fin c.length) (j : Fin (c.blocksFun i)) :
(c.invEmbedding (c.embedding i j) : ℕ) = j := by
simp_rw [coe_invEmbedding, index_embedding, coe_embedding, add_tsub_cancel_left]
#align composition.inv_embedding_comp Composition.invEmbedding_comp
/-- Equivalence between the disjoint union of the blocks (each of them seen as
`Fin (c.blocks_fun i)`) with `Fin n`. -/
def blocksFinEquiv : (Σi : Fin c.length, Fin (c.blocksFun i)) ≃ Fin n where
toFun x := c.embedding x.1 x.2
invFun j := ⟨c.index j, c.invEmbedding j⟩
left_inv x := by
rcases x with ⟨i, y⟩
dsimp
congr; · exact c.index_embedding _ _
rw [Fin.heq_ext_iff]
· exact c.invEmbedding_comp _ _
· rw [c.index_embedding]
right_inv j := c.embedding_comp_inv j
#align composition.blocks_fin_equiv Composition.blocksFinEquiv
theorem blocksFun_congr {n₁ n₂ : ℕ} (c₁ : Composition n₁) (c₂ : Composition n₂) (i₁ : Fin c₁.length)
(i₂ : Fin c₂.length) (hn : n₁ = n₂) (hc : c₁.blocks = c₂.blocks) (hi : (i₁ : ℕ) = i₂) :
c₁.blocksFun i₁ = c₂.blocksFun i₂ := by
cases hn
rw [← Composition.ext_iff] at hc
cases hc
congr
rwa [Fin.ext_iff]
#align composition.blocks_fun_congr Composition.blocksFun_congr
/-- Two compositions (possibly of different integers) coincide if and only if they have the
same sequence of blocks. -/
theorem sigma_eq_iff_blocks_eq {c : Σn, Composition n} {c' : Σn, Composition n} :
c = c' ↔ c.2.blocks = c'.2.blocks := by
refine ⟨fun H => by rw [H], fun H => ?_⟩
rcases c with ⟨n, c⟩
rcases c' with ⟨n', c'⟩
have : n = n' := by rw [← c.blocks_sum, ← c'.blocks_sum, H]
induction this
congr
ext1
exact H
#align composition.sigma_eq_iff_blocks_eq Composition.sigma_eq_iff_blocks_eq
/-! ### The composition `Composition.ones` -/
/-- The composition made of blocks all of size `1`. -/
def ones (n : ℕ) : Composition n :=
⟨replicate n (1 : ℕ), fun {i} hi => by simp [List.eq_of_mem_replicate hi], by simp⟩
#align composition.ones Composition.ones
instance {n : ℕ} : Inhabited (Composition n) :=
⟨Composition.ones n⟩
@[simp]
theorem ones_length (n : ℕ) : (ones n).length = n :=
List.length_replicate n 1
#align composition.ones_length Composition.ones_length
@[simp]
theorem ones_blocks (n : ℕ) : (ones n).blocks = replicate n (1 : ℕ) :=
rfl
#align composition.ones_blocks Composition.ones_blocks
@[simp]
theorem ones_blocksFun (n : ℕ) (i : Fin (ones n).length) : (ones n).blocksFun i = 1 := by
simp only [blocksFun, ones, blocks, i.2, List.get_replicate]
#align composition.ones_blocks_fun Composition.ones_blocksFun
@[simp]
theorem ones_sizeUpTo (n : ℕ) (i : ℕ) : (ones n).sizeUpTo i = min i n := by
simp [sizeUpTo, ones_blocks, take_replicate]
#align composition.ones_size_up_to Composition.ones_sizeUpTo
@[simp]
theorem ones_embedding (i : Fin (ones n).length) (h : 0 < (ones n).blocksFun i) :
(ones n).embedding i ⟨0, h⟩ = ⟨i, lt_of_lt_of_le i.2 (ones n).length_le⟩ := by
ext
simpa using i.2.le
#align composition.ones_embedding Composition.ones_embedding
theorem eq_ones_iff {c : Composition n} : c = ones n ↔ ∀ i ∈ c.blocks, i = 1 := by
constructor
· rintro rfl
exact fun i => eq_of_mem_replicate
· intro H
ext1
have A : c.blocks = replicate c.blocks.length 1 := eq_replicate_of_mem H
have : c.blocks.length = n := by
conv_rhs => rw [← c.blocks_sum, A]
simp
rw [A, this, ones_blocks]
#align composition.eq_ones_iff Composition.eq_ones_iff
theorem ne_ones_iff {c : Composition n} : c ≠ ones n ↔ ∃ i ∈ c.blocks, 1 < i := by
refine (not_congr eq_ones_iff).trans ?_
have : ∀ j ∈ c.blocks, j = 1 ↔ j ≤ 1 := fun j hj => by simp [le_antisymm_iff, c.one_le_blocks hj]
simp (config := { contextual := true }) [this]
#align composition.ne_ones_iff Composition.ne_ones_iff
theorem eq_ones_iff_length {c : Composition n} : c = ones n ↔ c.length = n := by
constructor
· rintro rfl
exact ones_length n
· contrapose
intro H length_n
apply lt_irrefl n
calc
n = ∑ i : Fin c.length, 1 := by simp [length_n]
_ < ∑ i : Fin c.length, c.blocksFun i := by
{
obtain ⟨i, hi, i_blocks⟩ : ∃ i ∈ c.blocks, 1 < i := ne_ones_iff.1 H
rw [← ofFn_blocksFun, mem_ofFn c.blocksFun, Set.mem_range] at hi
obtain ⟨j : Fin c.length, hj : c.blocksFun j = i⟩ := hi
rw [← hj] at i_blocks
exact Finset.sum_lt_sum (fun i _ => one_le_blocksFun c i) ⟨j, Finset.mem_univ _, i_blocks⟩
}
_ = n := c.sum_blocksFun
#align composition.eq_ones_iff_length Composition.eq_ones_iff_length
theorem eq_ones_iff_le_length {c : Composition n} : c = ones n ↔ n ≤ c.length := by
simp [eq_ones_iff_length, le_antisymm_iff, c.length_le]
#align composition.eq_ones_iff_le_length Composition.eq_ones_iff_le_length
/-! ### The composition `Composition.single` -/
/-- The composition made of a single block of size `n`. -/
def single (n : ℕ) (h : 0 < n) : Composition n :=
⟨[n], by simp [h], by simp⟩
#align composition.single Composition.single
@[simp]
theorem single_length {n : ℕ} (h : 0 < n) : (single n h).length = 1 :=
rfl
#align composition.single_length Composition.single_length
@[simp]
theorem single_blocks {n : ℕ} (h : 0 < n) : (single n h).blocks = [n] :=
rfl
#align composition.single_blocks Composition.single_blocks
@[simp]
theorem single_blocksFun {n : ℕ} (h : 0 < n) (i : Fin (single n h).length) :
(single n h).blocksFun i = n := by simp [blocksFun, single, blocks, i.2]
#align composition.single_blocks_fun Composition.single_blocksFun
@[simp]
theorem single_embedding {n : ℕ} (h : 0 < n) (i : Fin n) :
((single n h).embedding (0 : Fin 1)) i = i := by
ext
simp
#align composition.single_embedding Composition.single_embedding
theorem eq_single_iff_length {n : ℕ} (h : 0 < n) {c : Composition n} :
c = single n h ↔ c.length = 1 := by
constructor
· intro H
rw [H]
exact single_length h
· intro H
ext1
have A : c.blocks.length = 1 := H ▸ c.blocks_length
have B : c.blocks.sum = n := c.blocks_sum
rw [eq_cons_of_length_one A] at B ⊢
simpa [single_blocks] using B
#align composition.eq_single_iff_length Composition.eq_single_iff_length
theorem ne_single_iff {n : ℕ} (hn : 0 < n) {c : Composition n} :
c ≠ single n hn ↔ ∀ i, c.blocksFun i < n := by
rw [← not_iff_not]
push_neg
constructor
· rintro rfl
exact ⟨⟨0, by simp⟩, by simp⟩
· rintro ⟨i, hi⟩
rw [eq_single_iff_length]
have : ∀ j : Fin c.length, j = i := by
intro j
by_contra ji
apply lt_irrefl (∑ k, c.blocksFun k)
calc
∑ k, c.blocksFun k ≤ c.blocksFun i := by simp only [c.sum_blocksFun, hi]
_ < ∑ k, c.blocksFun k :=
Finset.single_lt_sum ji (Finset.mem_univ _) (Finset.mem_univ _) (c.one_le_blocksFun j)
fun _ _ _ => zero_le _
simpa using Fintype.card_eq_one_of_forall_eq this
#align composition.ne_single_iff Composition.ne_single_iff
end Composition
/-!
### Splitting a list
Given a list of length `n` and a composition `c` of `n`, one can split `l` into `c.length` sublists
of respective lengths `c.blocks_fun 0`, ..., `c.blocks_fun (c.length-1)`. This is inverse to the
join operation.
-/
namespace List
variable {α : Type*}
/-- Auxiliary for `List.splitWrtComposition`. -/
def splitWrtCompositionAux : List α → List ℕ → List (List α)
| _, [] => []
| l, n::ns =>
let (l₁, l₂) := l.splitAt n
l₁::splitWrtCompositionAux l₂ ns
#align list.split_wrt_composition_aux List.splitWrtCompositionAux
/-- Given a list of length `n` and a composition `[i₁, ..., iₖ]` of `n`, split `l` into a list of
`k` lists corresponding to the blocks of the composition, of respective lengths `i₁`, ..., `iₖ`.
This makes sense mostly when `n = l.length`, but this is not necessary for the definition. -/
def splitWrtComposition (l : List α) (c : Composition n) : List (List α) :=
splitWrtCompositionAux l c.blocks
#align list.split_wrt_composition List.splitWrtComposition
-- Porting note: can't refer to subeqn in Lean 4 this way, and seems to definitionally simp
--attribute [local simp] splitWrtCompositionAux.equations._eqn_1
@[local simp]
theorem splitWrtCompositionAux_cons (l : List α) (n ns) :
l.splitWrtCompositionAux (n::ns) = take n l::(drop n l).splitWrtCompositionAux ns := by
simp [splitWrtCompositionAux]
#align list.split_wrt_composition_aux_cons List.splitWrtCompositionAux_cons
theorem length_splitWrtCompositionAux (l : List α) (ns) :
length (l.splitWrtCompositionAux ns) = ns.length := by
induction ns generalizing l
· simp [splitWrtCompositionAux, *]
· simp [*]
#align list.length_split_wrt_composition_aux List.length_splitWrtCompositionAux
/-- When one splits a list along a composition `c`, the number of sublists thus created is
`c.length`. -/
@[simp]
theorem length_splitWrtComposition (l : List α) (c : Composition n) :
length (l.splitWrtComposition c) = c.length :=
length_splitWrtCompositionAux _ _
#align list.length_split_wrt_composition List.length_splitWrtComposition
theorem map_length_splitWrtCompositionAux {ns : List ℕ} :
∀ {l : List α}, ns.sum ≤ l.length → map length (l.splitWrtCompositionAux ns) = ns := by
induction' ns with n ns IH <;> intro l h <;> simp at h
· simp [splitWrtCompositionAux]
have := le_trans (Nat.le_add_right _ _) h
simp only [splitWrtCompositionAux_cons, this]; dsimp
rw [length_take, IH] <;> simp [length_drop]
· assumption
· exact le_tsub_of_add_le_left h
#align list.map_length_split_wrt_composition_aux List.map_length_splitWrtCompositionAux
/-- When one splits a list along a composition `c`, the lengths of the sublists thus created are
given by the block sizes in `c`. -/
theorem map_length_splitWrtComposition (l : List α) (c : Composition l.length) :
map length (l.splitWrtComposition c) = c.blocks :=
map_length_splitWrtCompositionAux (le_of_eq c.blocks_sum)
#align list.map_length_split_wrt_composition List.map_length_splitWrtComposition
theorem length_pos_of_mem_splitWrtComposition {l l' : List α} {c : Composition l.length}
(h : l' ∈ l.splitWrtComposition c) : 0 < length l' := by
have : l'.length ∈ (l.splitWrtComposition c).map List.length :=
List.mem_map_of_mem List.length h
rw [map_length_splitWrtComposition] at this
exact c.blocks_pos this
#align list.length_pos_of_mem_split_wrt_composition List.length_pos_of_mem_splitWrtComposition
theorem sum_take_map_length_splitWrtComposition (l : List α) (c : Composition l.length) (i : ℕ) :
(((l.splitWrtComposition c).map length).take i).sum = c.sizeUpTo i := by
congr
exact map_length_splitWrtComposition l c
#align list.sum_take_map_length_split_wrt_composition List.sum_take_map_length_splitWrtComposition
theorem get_splitWrtCompositionAux (l : List α) (ns : List ℕ) {i : ℕ} (hi) :
(l.splitWrtCompositionAux ns).get ⟨i, hi⟩ =
(l.take (ns.take (i + 1)).sum).drop (ns.take i).sum := by
induction' ns with n ns IH generalizing l i
· cases hi
cases' i with i
· rw [Nat.add_zero, List.take_zero, sum_nil]
simpa using get_mk_zero hi
· simp only [splitWrtCompositionAux, get_cons_succ, IH, take,
sum_cons, Nat.add_eq, add_zero, splitAt_eq_take_drop, drop_take, drop_drop]
rw [add_comm (sum _) n, Nat.add_sub_add_left]
#align list.nth_le_split_wrt_composition_aux List.get_splitWrtCompositionAux
/-- The `i`-th sublist in the splitting of a list `l` along a composition `c`, is the slice of `l`
between the indices `c.sizeUpTo i` and `c.sizeUpTo (i+1)`, i.e., the indices in the `i`-th
block of the composition. -/
theorem get_splitWrtComposition' (l : List α) (c : Composition n) {i : ℕ}
(hi : i < (l.splitWrtComposition c).length) :
(l.splitWrtComposition c).get ⟨i, hi⟩ = (l.take (c.sizeUpTo (i + 1))).drop (c.sizeUpTo i) :=
get_splitWrtCompositionAux _ _ _
#align list.nth_le_split_wrt_composition List.get_splitWrtComposition'
-- Porting note: restatement of `get_splitWrtComposition`
theorem get_splitWrtComposition (l : List α) (c : Composition n)
(i : Fin (l.splitWrtComposition c).length) :
get (l.splitWrtComposition c) i = (l.take (c.sizeUpTo (i + 1))).drop (c.sizeUpTo i) :=
get_splitWrtComposition' _ _ _
theorem join_splitWrtCompositionAux {ns : List ℕ} :
∀ {l : List α}, ns.sum = l.length → (l.splitWrtCompositionAux ns).join = l := by
induction' ns with n ns IH <;> intro l h <;> simp at h
· exact (length_eq_zero.1 h.symm).symm
simp only [splitWrtCompositionAux_cons]; dsimp
rw [IH]
· simp
· rw [length_drop, ← h, add_tsub_cancel_left]
#align list.join_split_wrt_composition_aux List.join_splitWrtCompositionAux
/-- If one splits a list along a composition, and then joins the sublists, one gets back the
original list. -/
@[simp]
theorem join_splitWrtComposition (l : List α) (c : Composition l.length) :
(l.splitWrtComposition c).join = l :=
join_splitWrtCompositionAux c.blocks_sum
#align list.join_split_wrt_composition List.join_splitWrtComposition
/-- If one joins a list of lists and then splits the join along the right composition, one gets
back the original list of lists. -/
@[simp]
theorem splitWrtComposition_join (L : List (List α)) (c : Composition L.join.length)
(h : map length L = c.blocks) : splitWrtComposition (join L) c = L := by
simp only [eq_self_iff_true, and_self_iff, eq_iff_join_eq, join_splitWrtComposition,
map_length_splitWrtComposition, h]
#align list.split_wrt_composition_join List.splitWrtComposition_join
end List
/-!
### Compositions as sets
Combinatorial viewpoints on compositions, seen as finite subsets of `Fin (n+1)` containing `0` and
`n`, where the points of the set (other than `n`) correspond to the leftmost points of each block.
-/
/-- Bijection between compositions of `n` and subsets of `{0, ..., n-2}`, defined by
considering the restriction of the subset to `{1, ..., n-1}` and shifting to the left by one. -/
def compositionAsSetEquiv (n : ℕ) : CompositionAsSet n ≃ Finset (Fin (n - 1)) where
toFun c :=
{ i : Fin (n - 1) |
(⟨1 + (i : ℕ), by
apply (add_lt_add_left i.is_lt 1).trans_le
rw [Nat.succ_eq_add_one, add_comm]
exact add_le_add (Nat.sub_le n 1) (le_refl 1)⟩ :
Fin n.succ) ∈
c.boundaries }.toFinset
invFun s :=
{ boundaries :=
{ i : Fin n.succ |
i = 0 ∨ i = Fin.last n ∨ ∃ (j : Fin (n - 1)) (_hj : j ∈ s), (i : ℕ) = j + 1 }.toFinset
zero_mem := by simp
getLast_mem := by simp }
left_inv := by
intro c
ext i
simp only [add_comm, Set.toFinset_setOf, Finset.mem_univ,
forall_true_left, Finset.mem_filter, true_and, exists_prop]
constructor
· rintro (rfl | rfl | ⟨j, hj1, hj2⟩)
· exact c.zero_mem
· exact c.getLast_mem
· convert hj1
· simp only [or_iff_not_imp_left]
intro i_mem i_ne_zero i_ne_last
simp? [Fin.ext_iff] at i_ne_zero i_ne_last says
simp only [Nat.succ_eq_add_one, Fin.ext_iff, Fin.val_zero, Fin.val_last]
at i_ne_zero i_ne_last
have A : (1 + (i - 1) : ℕ) = (i : ℕ) := by
rw [add_comm]
exact Nat.succ_pred_eq_of_pos (pos_iff_ne_zero.mpr i_ne_zero)
refine ⟨⟨i - 1, ?_⟩, ?_, ?_⟩
· have : (i : ℕ) < n + 1 := i.2
simp? [Nat.lt_succ_iff_lt_or_eq, i_ne_last] at this says
simp only [Nat.succ_eq_add_one, Nat.lt_succ_iff_lt_or_eq, i_ne_last, or_false] at this
exact Nat.pred_lt_pred i_ne_zero this
· convert i_mem
simp only [ge_iff_le]
rwa [add_comm]
· simp only [ge_iff_le]
symm
rwa [add_comm]
right_inv := by
intro s
ext i
have : 1 + (i : ℕ) ≠ n := by
apply ne_of_lt
convert add_lt_add_left i.is_lt 1
rw [add_comm]
apply (Nat.succ_pred_eq_of_pos _).symm
exact (zero_le i.val).trans_lt (i.2.trans_le (Nat.sub_le n 1))
simp only [add_comm, Fin.ext_iff, Fin.val_zero, Fin.val_last, exists_prop, Set.toFinset_setOf,
Finset.mem_univ, forall_true_left, Finset.mem_filter, add_eq_zero_iff, and_false,
add_left_inj, false_or, true_and]
erw [Set.mem_setOf_eq]
simp [this, false_or_iff, add_right_inj, add_eq_zero_iff, one_ne_zero, false_and_iff,
Fin.val_mk]
constructor
· intro h
cases' h with n h
· rw [add_comm] at this
contradiction
· cases' h with w h; cases' h with h₁ h₂
rw [← Fin.ext_iff] at h₂
rwa [h₂]
· intro h
apply Or.inr
use i, h
#align composition_as_set_equiv compositionAsSetEquiv
instance compositionAsSetFintype (n : ℕ) : Fintype (CompositionAsSet n) :=
Fintype.ofEquiv _ (compositionAsSetEquiv n).symm
#align composition_as_set_fintype compositionAsSetFintype
theorem compositionAsSet_card (n : ℕ) : Fintype.card (CompositionAsSet n) = 2 ^ (n - 1) := by
have : Fintype.card (Finset (Fin (n - 1))) = 2 ^ (n - 1) := by simp
rw [← this]
exact Fintype.card_congr (compositionAsSetEquiv n)
#align composition_as_set_card compositionAsSet_card
namespace CompositionAsSet
variable (c : CompositionAsSet n)
theorem boundaries_nonempty : c.boundaries.Nonempty :=
⟨0, c.zero_mem⟩
#align composition_as_set.boundaries_nonempty CompositionAsSet.boundaries_nonempty
theorem card_boundaries_pos : 0 < Finset.card c.boundaries :=
Finset.card_pos.mpr c.boundaries_nonempty
#align composition_as_set.card_boundaries_pos CompositionAsSet.card_boundaries_pos
/-- Number of blocks in a `CompositionAsSet`. -/
def length : ℕ :=
Finset.card c.boundaries - 1
#align composition_as_set.length CompositionAsSet.length
theorem card_boundaries_eq_succ_length : c.boundaries.card = c.length + 1 :=
(tsub_eq_iff_eq_add_of_le (Nat.succ_le_of_lt c.card_boundaries_pos)).mp rfl
#align composition_as_set.card_boundaries_eq_succ_length CompositionAsSet.card_boundaries_eq_succ_length
| Mathlib/Combinatorics/Enumerative/Composition.lean | 870 | 872 | theorem length_lt_card_boundaries : c.length < c.boundaries.card := by |
rw [c.card_boundaries_eq_succ_length]
exact lt_add_one _
|
/-
Copyright (c) 2023 Antoine Labelle. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Antoine Labelle
-/
import Mathlib.Combinatorics.Quiver.Cast
import Mathlib.Combinatorics.Quiver.Symmetric
#align_import combinatorics.quiver.single_obj from "leanprover-community/mathlib"@"509de852e1de55e1efa8eacfa11df0823f26f226"
/-!
# Single-object quiver
Single object quiver with a given arrows type.
## Main definitions
Given a type `α`, `SingleObj α` is the `Unit` type, whose single object is called `star α`, with
`Quiver` structure such that `star α ⟶ star α` is the type `α`.
An element `x : α` can be reinterpreted as an element of `star α ⟶ star α` using
`toHom`.
More generally, a list of elements of `a` can be reinterpreted as a path from `star α` to
itself using `pathEquivList`.
-/
namespace Quiver
/-- Type tag on `Unit` used to define single-object quivers. -/
-- Porting note: Removed `deriving Unique`.
@[nolint unusedArguments]
def SingleObj (_ : Type*) : Type :=
Unit
#align quiver.single_obj Quiver.SingleObj
-- Porting note: `deriving` from above has been moved to below.
instance {α : Type*} : Unique (SingleObj α) where
default := ⟨⟩
uniq := fun _ => rfl
namespace SingleObj
variable (α β γ : Type*)
instance : Quiver (SingleObj α) :=
⟨fun _ _ => α⟩
/-- The single object in `SingleObj α`. -/
def star : SingleObj α :=
Unit.unit
#align quiver.single_obj.star Quiver.SingleObj.star
instance : Inhabited (SingleObj α) :=
⟨star α⟩
variable {α β γ}
lemma ext {x y : SingleObj α} : x = y := Unit.ext x y
-- See note [reducible non-instances]
/-- Equip `SingleObj α` with a reverse operation. -/
abbrev hasReverse (rev : α → α) : HasReverse (SingleObj α) := ⟨rev⟩
#align quiver.single_obj.has_reverse Quiver.SingleObj.hasReverse
-- See note [reducible non-instances]
/-- Equip `SingleObj α` with an involutive reverse operation. -/
abbrev hasInvolutiveReverse (rev : α → α) (h : Function.Involutive rev) :
HasInvolutiveReverse (SingleObj α) where
toHasReverse := hasReverse rev
inv' := h
#align quiver.single_obj.has_involutive_reverse Quiver.SingleObj.hasInvolutiveReverse
/-- The type of arrows from `star α` to itself is equivalent to the original type `α`. -/
@[simps!]
def toHom : α ≃ (star α ⟶ star α) :=
Equiv.refl _
#align quiver.single_obj.to_hom Quiver.SingleObj.toHom
#align quiver.single_obj.to_hom_apply Quiver.SingleObj.toHom_apply
#align quiver.single_obj.to_hom_symm_apply Quiver.SingleObj.toHom_symm_apply
/-- Prefunctors between two `SingleObj` quivers correspond to functions between the corresponding
arrows types.
-/
@[simps]
def toPrefunctor : (α → β) ≃ SingleObj α ⥤q SingleObj β where
toFun f := ⟨id, f⟩
invFun f a := f.map (toHom a)
left_inv _ := rfl
right_inv _ := rfl
#align quiver.single_obj.to_prefunctor_symm_apply Quiver.SingleObj.toPrefunctor_symm_apply
#align quiver.single_obj.to_prefunctor_apply_map Quiver.SingleObj.toPrefunctor_apply_map
#align quiver.single_obj.to_prefunctor_apply_obj Quiver.SingleObj.toPrefunctor_apply_obj
#align quiver.single_obj.to_prefunctor Quiver.SingleObj.toPrefunctor
theorem toPrefunctor_id : toPrefunctor id = 𝟭q (SingleObj α) :=
rfl
#align quiver.single_obj.to_prefunctor_id Quiver.SingleObj.toPrefunctor_id
@[simp]
theorem toPrefunctor_symm_id : toPrefunctor.symm (𝟭q (SingleObj α)) = id :=
rfl
#align quiver.single_obj.to_prefunctor_symm_id Quiver.SingleObj.toPrefunctor_symm_id
theorem toPrefunctor_comp (f : α → β) (g : β → γ) :
toPrefunctor (g ∘ f) = toPrefunctor f ⋙q toPrefunctor g :=
rfl
#align quiver.single_obj.to_prefunctor_comp Quiver.SingleObj.toPrefunctor_comp
@[simp]
| Mathlib/Combinatorics/Quiver/SingleObj.lean | 110 | 112 | theorem toPrefunctor_symm_comp (f : SingleObj α ⥤q SingleObj β) (g : SingleObj β ⥤q SingleObj γ) :
toPrefunctor.symm (f ⋙q g) = toPrefunctor.symm g ∘ toPrefunctor.symm f := by |
simp only [Equiv.symm_apply_eq, toPrefunctor_comp, Equiv.apply_symm_apply]
|
/-
Copyright (c) 2021 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
import Mathlib.Analysis.SpecialFunctions.Complex.Circle
import Mathlib.Analysis.InnerProductSpace.l2Space
import Mathlib.MeasureTheory.Function.ContinuousMapDense
import Mathlib.MeasureTheory.Function.L2Space
import Mathlib.MeasureTheory.Group.Integral
import Mathlib.MeasureTheory.Integral.Periodic
import Mathlib.Topology.ContinuousFunction.StoneWeierstrass
import Mathlib.MeasureTheory.Integral.FundThmCalculus
#align_import analysis.fourier.add_circle from "leanprover-community/mathlib"@"8f9fea08977f7e450770933ee6abb20733b47c92"
/-!
# Fourier analysis on the additive circle
This file contains basic results on Fourier series for functions on the additive circle
`AddCircle T = ℝ / ℤ • T`.
## Main definitions
* `haarAddCircle`, Haar measure on `AddCircle T`, normalized to have total measure `1`. (Note
that this is not the same normalisation as the standard measure defined in `Integral.Periodic`,
so we do not declare it as a `MeasureSpace` instance, to avoid confusion.)
* for `n : ℤ`, `fourier n` is the monomial `fun x => exp (2 π i n x / T)`,
bundled as a continuous map from `AddCircle T` to `ℂ`.
* `fourierBasis` is the Hilbert basis of `Lp ℂ 2 haarAddCircle` given by the images of the
monomials `fourier n`.
* `fourierCoeff f n`, for `f : AddCircle T → E` (with `E` a complete normed `ℂ`-vector space), is
the `n`-th Fourier coefficient of `f`, defined as an integral over `AddCircle T`. The lemma
`fourierCoeff_eq_intervalIntegral` expresses this as an integral over `[a, a + T]` for any real
`a`.
* `fourierCoeffOn`, for `f : ℝ → E` and `a < b` reals, is the `n`-th Fourier
coefficient of the unique periodic function of period `b - a` which agrees with `f` on `(a, b]`.
The lemma `fourierCoeffOn_eq_integral` expresses this as an integral over `[a, b]`.
## Main statements
The theorem `span_fourier_closure_eq_top` states that the span of the monomials `fourier n` is
dense in `C(AddCircle T, ℂ)`, i.e. that its `Submodule.topologicalClosure` is `⊤`. This follows
from the Stone-Weierstrass theorem after checking that the span is a subalgebra, is closed under
conjugation, and separates points.
Using this and general theory on approximation of Lᵖ functions by continuous functions, we deduce
(`span_fourierLp_closure_eq_top`) that for any `1 ≤ p < ∞`, the span of the Fourier monomials is
dense in the Lᵖ space of `AddCircle T`. For `p = 2` we show (`orthonormal_fourier`) that the
monomials are also orthonormal, so they form a Hilbert basis for L², which is named as
`fourierBasis`; in particular, for `L²` functions `f`, the Fourier series of `f` converges to `f`
in the `L²` topology (`hasSum_fourier_series_L2`). Parseval's identity, `tsum_sq_fourierCoeff`, is
a direct consequence.
For continuous maps `f : AddCircle T → ℂ`, the theorem
`hasSum_fourier_series_of_summable` states that if the sequence of Fourier
coefficients of `f` is summable, then the Fourier series `∑ (i : ℤ), fourierCoeff f i * fourier i`
converges to `f` in the uniform-convergence topology of `C(AddCircle T, ℂ)`.
-/
noncomputable section
open scoped ENNReal ComplexConjugate Real
open TopologicalSpace ContinuousMap MeasureTheory MeasureTheory.Measure Algebra Submodule Set
variable {T : ℝ}
namespace AddCircle
/-! ### Measure on `AddCircle T`
In this file we use the Haar measure on `AddCircle T` normalised to have total measure 1 (which is
**not** the same as the standard measure defined in `Topology.Instances.AddCircle`). -/
variable [hT : Fact (0 < T)]
/-- Haar measure on the additive circle, normalised to have total measure 1. -/
def haarAddCircle : Measure (AddCircle T) :=
addHaarMeasure ⊤
#align add_circle.haar_add_circle AddCircle.haarAddCircle
-- Porting note: was `deriving IsAddHaarMeasure` on `haarAddCircle`
instance : IsAddHaarMeasure (@haarAddCircle T _) :=
Measure.isAddHaarMeasure_addHaarMeasure ⊤
instance : IsProbabilityMeasure (@haarAddCircle T _) :=
IsProbabilityMeasure.mk addHaarMeasure_self
theorem volume_eq_smul_haarAddCircle :
(volume : Measure (AddCircle T)) = ENNReal.ofReal T • (@haarAddCircle T _) :=
rfl
#align add_circle.volume_eq_smul_haar_add_circle AddCircle.volume_eq_smul_haarAddCircle
end AddCircle
open AddCircle
section Monomials
/-- The family of exponential monomials `fun x => exp (2 π i n x / T)`, parametrized by `n : ℤ` and
considered as bundled continuous maps from `ℝ / ℤ • T` to `ℂ`. -/
def fourier (n : ℤ) : C(AddCircle T, ℂ) where
toFun x := toCircle (n • x :)
continuous_toFun := continuous_induced_dom.comp <| continuous_toCircle.comp <| continuous_zsmul _
#align fourier fourier
@[simp]
theorem fourier_apply {n : ℤ} {x : AddCircle T} : fourier n x = toCircle (n • x :) :=
rfl
#align fourier_apply fourier_apply
-- @[simp] -- Porting note: simp normal form is `fourier_coe_apply'`
theorem fourier_coe_apply {n : ℤ} {x : ℝ} :
fourier n (x : AddCircle T) = Complex.exp (2 * π * Complex.I * n * x / T) := by
rw [fourier_apply, ← QuotientAddGroup.mk_zsmul, toCircle, Function.Periodic.lift_coe,
expMapCircle_apply, Complex.ofReal_mul, Complex.ofReal_div, Complex.ofReal_mul, zsmul_eq_mul,
Complex.ofReal_mul, Complex.ofReal_intCast]
norm_num
congr 1; ring
#align fourier_coe_apply fourier_coe_apply
@[simp]
theorem fourier_coe_apply' {n : ℤ} {x : ℝ} :
toCircle (n • (x : AddCircle T) :) = Complex.exp (2 * π * Complex.I * n * x / T) := by
rw [← fourier_apply]; exact fourier_coe_apply
-- @[simp] -- Porting note: simp normal form is `fourier_zero'`
theorem fourier_zero {x : AddCircle T} : fourier 0 x = 1 := by
induction x using QuotientAddGroup.induction_on'
simp only [fourier_coe_apply]
norm_num
#align fourier_zero fourier_zero
@[simp]
theorem fourier_zero' {x : AddCircle T} : @toCircle T 0 = (1 : ℂ) := by
have : fourier 0 x = @toCircle T 0 := by rw [fourier_apply, zero_smul]
rw [← this]; exact fourier_zero
-- @[simp] -- Porting note: simp normal form is *also* `fourier_zero'`
theorem fourier_eval_zero (n : ℤ) : fourier n (0 : AddCircle T) = 1 := by
rw [← QuotientAddGroup.mk_zero, fourier_coe_apply, Complex.ofReal_zero, mul_zero,
zero_div, Complex.exp_zero]
#align fourier_eval_zero fourier_eval_zero
-- @[simp] -- Porting note (#10618): simp can prove this
theorem fourier_one {x : AddCircle T} : fourier 1 x = toCircle x := by rw [fourier_apply, one_zsmul]
#align fourier_one fourier_one
-- @[simp] -- Porting note: simp normal form is `fourier_neg'`
theorem fourier_neg {n : ℤ} {x : AddCircle T} : fourier (-n) x = conj (fourier n x) := by
induction x using QuotientAddGroup.induction_on'
simp_rw [fourier_apply, toCircle]
rw [← QuotientAddGroup.mk_zsmul, ← QuotientAddGroup.mk_zsmul]
simp_rw [Function.Periodic.lift_coe, ← coe_inv_circle_eq_conj, ← expMapCircle_neg,
neg_smul, mul_neg]
#align fourier_neg fourier_neg
@[simp]
theorem fourier_neg' {n : ℤ} {x : AddCircle T} : @toCircle T (-(n • x)) = conj (fourier n x) := by
rw [← neg_smul, ← fourier_apply]; exact fourier_neg
-- @[simp] -- Porting note: simp normal form is `fourier_add'`
theorem fourier_add {m n : ℤ} {x : AddCircle T} : fourier (m+n) x = fourier m x * fourier n x := by
simp_rw [fourier_apply, add_zsmul, toCircle_add, coe_mul_unitSphere]
#align fourier_add fourier_add
@[simp]
theorem fourier_add' {m n : ℤ} {x : AddCircle T} :
toCircle ((m + n) • x :) = fourier m x * fourier n x := by
rw [← fourier_apply]; exact fourier_add
theorem fourier_norm [Fact (0 < T)] (n : ℤ) : ‖@fourier T n‖ = 1 := by
rw [ContinuousMap.norm_eq_iSup_norm]
have : ∀ x : AddCircle T, ‖fourier n x‖ = 1 := fun x => abs_coe_circle _
simp_rw [this]
exact @ciSup_const _ _ _ Zero.instNonempty _
#align fourier_norm fourier_norm
/-- For `n ≠ 0`, a translation by `T / 2 / n` negates the function `fourier n`. -/
theorem fourier_add_half_inv_index {n : ℤ} (hn : n ≠ 0) (hT : 0 < T) (x : AddCircle T) :
@fourier T n (x + ↑(T / 2 / n)) = -fourier n x := by
rw [fourier_apply, zsmul_add, ← QuotientAddGroup.mk_zsmul, toCircle_add, coe_mul_unitSphere]
have : (n : ℂ) ≠ 0 := by simpa using hn
have : (@toCircle T (n • (T / 2 / n) : ℝ) : ℂ) = -1 := by
rw [zsmul_eq_mul, toCircle, Function.Periodic.lift_coe, expMapCircle_apply]
replace hT := Complex.ofReal_ne_zero.mpr hT.ne'
convert Complex.exp_pi_mul_I using 3
field_simp; ring
rw [this]; simp
#align fourier_add_half_inv_index fourier_add_half_inv_index
/-- The star subalgebra of `C(AddCircle T, ℂ)` generated by `fourier n` for `n ∈ ℤ` . -/
def fourierSubalgebra : StarSubalgebra ℂ C(AddCircle T, ℂ) where
toSubalgebra := Algebra.adjoin ℂ (range fourier)
star_mem' := by
show Algebra.adjoin ℂ (range (fourier (T := T))) ≤
star (Algebra.adjoin ℂ (range (fourier (T := T))))
refine adjoin_le ?_
rintro - ⟨n, rfl⟩
exact subset_adjoin ⟨-n, ext fun _ => fourier_neg⟩
#align fourier_subalgebra fourierSubalgebra
/-- The star subalgebra of `C(AddCircle T, ℂ)` generated by `fourier n` for `n ∈ ℤ` is in fact the
linear span of these functions. -/
| Mathlib/Analysis/Fourier/AddCircle.lean | 210 | 220 | theorem fourierSubalgebra_coe :
Subalgebra.toSubmodule (@fourierSubalgebra T).toSubalgebra = span ℂ (range (@fourier T)) := by |
apply adjoin_eq_span_of_subset
refine Subset.trans ?_ Submodule.subset_span
intro x hx
refine Submonoid.closure_induction hx (fun _ => id) ⟨0, ?_⟩ ?_
· ext1 z; exact fourier_zero
· rintro _ _ ⟨m, rfl⟩ ⟨n, rfl⟩
refine ⟨m + n, ?_⟩
ext1 z
exact fourier_add
|
/-
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.Module.Hom
import Mathlib.Algebra.Module.LinearMap.End
#align_import algebra.module.equiv from "leanprover-community/mathlib"@"ea94d7cd54ad9ca6b7710032868abb7c6a104c9c"
/-!
# (Semi)linear equivalences
In this file we define
* `LinearEquiv σ M M₂`, `M ≃ₛₗ[σ] M₂`: an invertible semilinear map. Here, `σ` is a `RingHom`
from `R` to `R₂` and an `e : M ≃ₛₗ[σ] M₂` satisfies `e (c • x) = (σ c) • (e x)`. The plain
linear version, with `σ` being `RingHom.id R`, is denoted by `M ≃ₗ[R] M₂`, and the
star-linear version (with `σ` being `starRingEnd`) is denoted by `M ≃ₗ⋆[R] M₂`.
## Implementation notes
To ensure that composition works smoothly for semilinear equivalences, we use the typeclasses
`RingHomCompTriple`, `RingHomInvPair` and `RingHomSurjective` from
`Algebra/Ring/CompTypeclasses`.
The group structure on automorphisms, `LinearEquiv.automorphismGroup`, is provided elsewhere.
## TODO
* Parts of this file have not yet been generalized to semilinear maps
## Tags
linear equiv, linear equivalences, linear isomorphism, linear isomorphic
-/
open Function
universe u u' v w x y z
variable {R : Type*} {R₁ : Type*} {R₂ : Type*} {R₃ : Type*}
variable {k : Type*} {K : Type*} {S : Type*} {M : Type*} {M₁ : Type*} {M₂ : Type*} {M₃ : Type*}
variable {N₁ : Type*} {N₂ : Type*} {N₃ : Type*} {N₄ : Type*} {ι : Type*}
section
/-- A linear equivalence is an invertible linear map. -/
-- Porting note (#11215): TODO @[nolint has_nonempty_instance]
structure LinearEquiv {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : Type*) (M₂ : Type*)
[AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂] extends LinearMap σ M M₂, M ≃+ M₂
#align linear_equiv LinearEquiv
attribute [coe] LinearEquiv.toLinearMap
/-- The linear map underlying a linear equivalence. -/
add_decl_doc LinearEquiv.toLinearMap
#align linear_equiv.to_linear_map LinearEquiv.toLinearMap
/-- The additive equivalence of types underlying a linear equivalence. -/
add_decl_doc LinearEquiv.toAddEquiv
#align linear_equiv.to_add_equiv LinearEquiv.toAddEquiv
/-- The backwards directed function underlying a linear equivalence. -/
add_decl_doc LinearEquiv.invFun
/-- `LinearEquiv.invFun` is a right inverse to the linear equivalence's underlying function. -/
add_decl_doc LinearEquiv.right_inv
/-- `LinearEquiv.invFun` is a left inverse to the linear equivalence's underlying function. -/
add_decl_doc LinearEquiv.left_inv
/-- The notation `M ≃ₛₗ[σ] M₂` denotes the type of linear equivalences between `M` and `M₂` over a
ring homomorphism `σ`. -/
notation:50 M " ≃ₛₗ[" σ "] " M₂ => LinearEquiv σ M M₂
/-- The notation `M ≃ₗ [R] M₂` denotes the type of linear equivalences between `M` and `M₂` over
a plain linear map `M →ₗ M₂`. -/
notation:50 M " ≃ₗ[" R "] " M₂ => LinearEquiv (RingHom.id R) M M₂
/-- The notation `M ≃ₗ⋆[R] M₂` denotes the type of star-linear equivalences between `M` and `M₂`
over the `⋆` endomorphism of the underlying starred ring `R`. -/
notation:50 M " ≃ₗ⋆[" R "] " M₂ => LinearEquiv (starRingEnd R) M M₂
/-- `SemilinearEquivClass F σ M M₂` asserts `F` is a type of bundled `σ`-semilinear equivs
`M → M₂`.
See also `LinearEquivClass 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 SemilinearEquivClass (F : Type*) {R S : outParam Type*} [Semiring R] [Semiring S]
(σ : outParam <| R →+* S) {σ' : outParam <| S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
(M M₂ : outParam Type*) [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂]
[EquivLike F M M₂]
extends AddEquivClass F M M₂ : Prop where
/-- Applying a semilinear equivalence `f` over `σ` to `r • x` equals `σ r • f x`. -/
map_smulₛₗ : ∀ (f : F) (r : R) (x : M), f (r • x) = σ r • f x
#align semilinear_equiv_class SemilinearEquivClass
-- `R, S, σ, σ'` become metavars, but it's OK since they are outparams.
/-- `LinearEquivClass F R M M₂` asserts `F` is a type of bundled `R`-linear equivs `M → M₂`.
This is an abbreviation for `SemilinearEquivClass F (RingHom.id R) M M₂`.
-/
abbrev LinearEquivClass (F : Type*) (R M M₂ : outParam Type*) [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂] [EquivLike F M M₂] :=
SemilinearEquivClass F (RingHom.id R) M M₂
#align linear_equiv_class LinearEquivClass
end
namespace SemilinearEquivClass
variable (F : Type*) [Semiring R] [Semiring S]
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂]
variable [Module R M] [Module S M₂] {σ : R →+* S} {σ' : S →+* R}
instance (priority := 100) [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
[EquivLike F M M₂] [s : SemilinearEquivClass F σ M M₂] : SemilinearMapClass F σ M M₂ :=
{ s with }
variable {F}
/-- Reinterpret an element of a type of semilinear equivalences as a semilinear equivalence. -/
@[coe]
def semilinearEquiv [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
[EquivLike F M M₂] [SemilinearEquivClass F σ M M₂] (f : F) : M ≃ₛₗ[σ] M₂ :=
{ (f : M ≃+ M₂), (f : M →ₛₗ[σ] M₂) with }
/-- Reinterpret an element of a type of semilinear equivalences as a semilinear equivalence. -/
instance instCoeToSemilinearEquiv [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
[EquivLike F M M₂] [SemilinearEquivClass F σ M M₂] : CoeHead F (M ≃ₛₗ[σ] M₂) where
coe f := semilinearEquiv f
end SemilinearEquivClass
namespace LinearEquiv
section AddCommMonoid
variable {M₄ : Type*}
variable [Semiring R] [Semiring S]
section
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂]
variable [Module R M] [Module S M₂] {σ : R →+* S} {σ' : S →+* R}
variable [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
instance : Coe (M ≃ₛₗ[σ] M₂) (M →ₛₗ[σ] M₂) :=
⟨toLinearMap⟩
-- This exists for compatibility, previously `≃ₗ[R]` extended `≃` instead of `≃+`.
/-- The equivalence of types underlying a linear equivalence. -/
def toEquiv : (M ≃ₛₗ[σ] M₂) → M ≃ M₂ := fun f => f.toAddEquiv.toEquiv
#align linear_equiv.to_equiv LinearEquiv.toEquiv
theorem toEquiv_injective : Function.Injective (toEquiv : (M ≃ₛₗ[σ] M₂) → M ≃ M₂) :=
fun ⟨⟨⟨_, _⟩, _⟩, _, _, _⟩ ⟨⟨⟨_, _⟩, _⟩, _, _, _⟩ h =>
(LinearEquiv.mk.injEq _ _ _ _ _ _ _ _).mpr
⟨LinearMap.ext (congr_fun (Equiv.mk.inj h).1), (Equiv.mk.inj h).2⟩
#align linear_equiv.to_equiv_injective LinearEquiv.toEquiv_injective
@[simp]
theorem toEquiv_inj {e₁ e₂ : M ≃ₛₗ[σ] M₂} : e₁.toEquiv = e₂.toEquiv ↔ e₁ = e₂ :=
toEquiv_injective.eq_iff
#align linear_equiv.to_equiv_inj LinearEquiv.toEquiv_inj
theorem toLinearMap_injective : Injective (toLinearMap : (M ≃ₛₗ[σ] M₂) → M →ₛₗ[σ] M₂) :=
fun _ _ H => toEquiv_injective <| Equiv.ext <| LinearMap.congr_fun H
#align linear_equiv.to_linear_map_injective LinearEquiv.toLinearMap_injective
@[simp, norm_cast]
theorem toLinearMap_inj {e₁ e₂ : M ≃ₛₗ[σ] M₂} : (↑e₁ : M →ₛₗ[σ] M₂) = e₂ ↔ e₁ = e₂ :=
toLinearMap_injective.eq_iff
#align linear_equiv.to_linear_map_inj LinearEquiv.toLinearMap_inj
instance : EquivLike (M ≃ₛₗ[σ] M₂) M M₂ where
inv := LinearEquiv.invFun
coe_injective' _ _ h _ := toLinearMap_injective (DFunLike.coe_injective h)
left_inv := LinearEquiv.left_inv
right_inv := LinearEquiv.right_inv
/-- Helper instance for when inference gets stuck on following the normal chain
`EquivLike → FunLike`.
TODO: this instance doesn't appear to be necessary: remove it (after benchmarking?)
-/
instance : FunLike (M ≃ₛₗ[σ] M₂) M M₂ where
coe := DFunLike.coe
coe_injective' := DFunLike.coe_injective
instance : SemilinearEquivClass (M ≃ₛₗ[σ] M₂) σ M M₂ where
map_add := (·.map_add') --map_add' Porting note (#11215): TODO why did I need to change this?
map_smulₛₗ := (·.map_smul') --map_smul' Porting note (#11215): TODO why did I need to change this?
-- Porting note: moved to a lower line since there is no shortcut `CoeFun` instance any more
@[simp]
theorem coe_mk {to_fun inv_fun map_add map_smul left_inv right_inv} :
(⟨⟨⟨to_fun, map_add⟩, map_smul⟩, inv_fun, left_inv, right_inv⟩ : M ≃ₛₗ[σ] M₂) = to_fun := rfl
#align linear_equiv.coe_mk LinearEquiv.coe_mk
theorem coe_injective : @Injective (M ≃ₛₗ[σ] M₂) (M → M₂) CoeFun.coe :=
DFunLike.coe_injective
#align linear_equiv.coe_injective LinearEquiv.coe_injective
end
section
variable [Semiring R₁] [Semiring R₂] [Semiring R₃]
variable [AddCommMonoid M] [AddCommMonoid M₁] [AddCommMonoid M₂]
variable [AddCommMonoid M₃] [AddCommMonoid M₄]
variable [AddCommMonoid N₁] [AddCommMonoid N₂]
variable {module_M : Module R M} {module_S_M₂ : Module S M₂} {σ : R →+* S} {σ' : S →+* R}
variable {re₁ : RingHomInvPair σ σ'} {re₂ : RingHomInvPair σ' σ}
variable (e e' : M ≃ₛₗ[σ] M₂)
@[simp, norm_cast]
theorem coe_coe : ⇑(e : M →ₛₗ[σ] M₂) = e :=
rfl
#align linear_equiv.coe_coe LinearEquiv.coe_coe
@[simp]
theorem coe_toEquiv : ⇑(e.toEquiv) = e :=
rfl
#align linear_equiv.coe_to_equiv LinearEquiv.coe_toEquiv
@[simp]
theorem coe_toLinearMap : ⇑e.toLinearMap = e :=
rfl
#align linear_equiv.coe_to_linear_map LinearEquiv.coe_toLinearMap
-- Porting note: no longer a `simp`
theorem toFun_eq_coe : e.toFun = e := rfl
#align linear_equiv.to_fun_eq_coe LinearEquiv.toFun_eq_coe
section
variable {e e'}
@[ext]
theorem ext (h : ∀ x, e x = e' x) : e = e' :=
DFunLike.ext _ _ h
#align linear_equiv.ext LinearEquiv.ext
theorem ext_iff : e = e' ↔ ∀ x, e x = e' x :=
DFunLike.ext_iff
#align linear_equiv.ext_iff LinearEquiv.ext_iff
protected theorem congr_arg {x x'} : x = x' → e x = e x' :=
DFunLike.congr_arg e
#align linear_equiv.congr_arg LinearEquiv.congr_arg
protected theorem congr_fun (h : e = e') (x : M) : e x = e' x :=
DFunLike.congr_fun h x
#align linear_equiv.congr_fun LinearEquiv.congr_fun
end
section
variable (M R)
/-- The identity map is a linear equivalence. -/
@[refl]
def refl [Module R M] : M ≃ₗ[R] M :=
{ LinearMap.id, Equiv.refl M with }
#align linear_equiv.refl LinearEquiv.refl
end
@[simp]
theorem refl_apply [Module R M] (x : M) : refl R M x = x :=
rfl
#align linear_equiv.refl_apply LinearEquiv.refl_apply
/-- Linear equivalences are symmetric. -/
@[symm]
def symm (e : M ≃ₛₗ[σ] M₂) : M₂ ≃ₛₗ[σ'] M :=
{ e.toLinearMap.inverse e.invFun e.left_inv e.right_inv,
e.toEquiv.symm with
toFun := e.toLinearMap.inverse e.invFun e.left_inv e.right_inv
invFun := e.toEquiv.symm.invFun
map_smul' := fun r x => by dsimp only; rw [map_smulₛₗ] }
#align linear_equiv.symm LinearEquiv.symm
-- Porting note: this is new
/-- See Note [custom simps projection] -/
def Simps.apply {R : Type*} {S : Type*} [Semiring R] [Semiring S]
{σ : R →+* S} {σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
{M : Type*} {M₂ : Type*} [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂]
(e : M ≃ₛₗ[σ] M₂) : M → M₂ :=
e
#align linear_equiv.simps.apply LinearEquiv.Simps.apply
/-- See Note [custom simps projection] -/
def Simps.symm_apply {R : Type*} {S : Type*} [Semiring R] [Semiring S]
{σ : R →+* S} {σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
{M : Type*} {M₂ : Type*} [AddCommMonoid M] [AddCommMonoid M₂] [Module R M] [Module S M₂]
(e : M ≃ₛₗ[σ] M₂) : M₂ → M :=
e.symm
#align linear_equiv.simps.symm_apply LinearEquiv.Simps.symm_apply
initialize_simps_projections LinearEquiv (toFun → apply, invFun → symm_apply)
@[simp]
theorem invFun_eq_symm : e.invFun = e.symm :=
rfl
#align linear_equiv.inv_fun_eq_symm LinearEquiv.invFun_eq_symm
@[simp]
theorem coe_toEquiv_symm : e.toEquiv.symm = e.symm :=
rfl
#align linear_equiv.coe_to_equiv_symm LinearEquiv.coe_toEquiv_symm
variable {module_M₁ : Module R₁ M₁} {module_M₂ : Module R₂ M₂} {module_M₃ : Module R₃ M₃}
variable {module_N₁ : Module R₁ N₁} {module_N₂ : Module R₁ N₂}
variable {σ₁₂ : R₁ →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R₁ →+* R₃}
variable {σ₂₁ : R₂ →+* R₁} {σ₃₂ : R₃ →+* R₂} {σ₃₁ : R₃ →+* R₁}
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
variable [RingHomCompTriple σ₃₂ σ₂₁ σ₃₁]
variable {re₁₂ : RingHomInvPair σ₁₂ σ₂₁} {re₂₃ : RingHomInvPair σ₂₃ σ₃₂}
variable [RingHomInvPair σ₁₃ σ₃₁] {re₂₁ : RingHomInvPair σ₂₁ σ₁₂}
variable {re₃₂ : RingHomInvPair σ₃₂ σ₂₃} [RingHomInvPair σ₃₁ σ₁₃]
variable (e₁₂ : M₁ ≃ₛₗ[σ₁₂] M₂) (e₂₃ : M₂ ≃ₛₗ[σ₂₃] M₃)
-- Porting note: Lean 4 aggressively removes unused variables declared using `variable`, so
-- we have to list all the variables explicitly here in order to match the Lean 3 signature.
set_option linter.unusedVariables false in
/-- Linear equivalences are transitive. -/
-- Note: the `RingHomCompTriple σ₃₂ σ₂₁ σ₃₁` is unused, but is convenient to carry around
-- implicitly for lemmas like `LinearEquiv.self_trans_symm`.
@[trans, nolint unusedArguments]
def trans
[RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [RingHomCompTriple σ₃₂ σ₂₁ σ₃₁]
{re₁₂ : RingHomInvPair σ₁₂ σ₂₁} {re₂₃ : RingHomInvPair σ₂₃ σ₃₂}
[RingHomInvPair σ₁₃ σ₃₁] {re₂₁ : RingHomInvPair σ₂₁ σ₁₂}
{re₃₂ : RingHomInvPair σ₃₂ σ₂₃} [RingHomInvPair σ₃₁ σ₁₃]
(e₁₂ : M₁ ≃ₛₗ[σ₁₂] M₂) (e₂₃ : M₂ ≃ₛₗ[σ₂₃] M₃) : M₁ ≃ₛₗ[σ₁₃] M₃ :=
{ e₂₃.toLinearMap.comp e₁₂.toLinearMap, e₁₂.toEquiv.trans e₂₃.toEquiv with }
#align linear_equiv.trans LinearEquiv.trans
/-- The notation `e₁ ≪≫ₗ e₂` denotes the composition of the linear equivalences `e₁` and `e₂`. -/
notation3:80 (name := transNotation) e₁:80 " ≪≫ₗ " e₂:81 =>
@LinearEquiv.trans _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ (RingHom.id _) (RingHom.id _) (RingHom.id _)
(RingHom.id _) (RingHom.id _) (RingHom.id _) RingHomCompTriple.ids RingHomCompTriple.ids
RingHomInvPair.ids RingHomInvPair.ids RingHomInvPair.ids RingHomInvPair.ids RingHomInvPair.ids
RingHomInvPair.ids e₁ e₂
variable {e₁₂} {e₂₃}
@[simp]
theorem coe_toAddEquiv : e.toAddEquiv = e :=
rfl
#align linear_equiv.coe_to_add_equiv LinearEquiv.coe_toAddEquiv
/-- The two paths coercion can take to an `AddMonoidHom` are equivalent -/
theorem toAddMonoidHom_commutes : e.toLinearMap.toAddMonoidHom = e.toAddEquiv.toAddMonoidHom :=
rfl
#align linear_equiv.to_add_monoid_hom_commutes LinearEquiv.toAddMonoidHom_commutes
@[simp]
theorem trans_apply (c : M₁) : (e₁₂.trans e₂₃ : M₁ ≃ₛₗ[σ₁₃] M₃) c = e₂₃ (e₁₂ c) :=
rfl
#align linear_equiv.trans_apply LinearEquiv.trans_apply
theorem coe_trans :
(e₁₂.trans e₂₃ : M₁ →ₛₗ[σ₁₃] M₃) = (e₂₃ : M₂ →ₛₗ[σ₂₃] M₃).comp (e₁₂ : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align linear_equiv.coe_trans LinearEquiv.coe_trans
@[simp]
theorem apply_symm_apply (c : M₂) : e (e.symm c) = c :=
e.right_inv c
#align linear_equiv.apply_symm_apply LinearEquiv.apply_symm_apply
@[simp]
theorem symm_apply_apply (b : M) : e.symm (e b) = b :=
e.left_inv b
#align linear_equiv.symm_apply_apply LinearEquiv.symm_apply_apply
@[simp]
theorem trans_symm : (e₁₂.trans e₂₃ : M₁ ≃ₛₗ[σ₁₃] M₃).symm = e₂₃.symm.trans e₁₂.symm :=
rfl
#align linear_equiv.trans_symm LinearEquiv.trans_symm
theorem symm_trans_apply (c : M₃) :
(e₁₂.trans e₂₃ : M₁ ≃ₛₗ[σ₁₃] M₃).symm c = e₁₂.symm (e₂₃.symm c) :=
rfl
#align linear_equiv.symm_trans_apply LinearEquiv.symm_trans_apply
@[simp]
theorem trans_refl : e.trans (refl S M₂) = e :=
toEquiv_injective e.toEquiv.trans_refl
#align linear_equiv.trans_refl LinearEquiv.trans_refl
@[simp]
theorem refl_trans : (refl R M).trans e = e :=
toEquiv_injective e.toEquiv.refl_trans
#align linear_equiv.refl_trans LinearEquiv.refl_trans
theorem symm_apply_eq {x y} : e.symm x = y ↔ x = e y :=
e.toEquiv.symm_apply_eq
#align linear_equiv.symm_apply_eq LinearEquiv.symm_apply_eq
theorem eq_symm_apply {x y} : y = e.symm x ↔ e y = x :=
e.toEquiv.eq_symm_apply
#align linear_equiv.eq_symm_apply LinearEquiv.eq_symm_apply
theorem eq_comp_symm {α : Type*} (f : M₂ → α) (g : M₁ → α) : f = g ∘ e₁₂.symm ↔ f ∘ e₁₂ = g :=
e₁₂.toEquiv.eq_comp_symm f g
#align linear_equiv.eq_comp_symm LinearEquiv.eq_comp_symm
theorem comp_symm_eq {α : Type*} (f : M₂ → α) (g : M₁ → α) : g ∘ e₁₂.symm = f ↔ g = f ∘ e₁₂ :=
e₁₂.toEquiv.comp_symm_eq f g
#align linear_equiv.comp_symm_eq LinearEquiv.comp_symm_eq
theorem eq_symm_comp {α : Type*} (f : α → M₁) (g : α → M₂) : f = e₁₂.symm ∘ g ↔ e₁₂ ∘ f = g :=
e₁₂.toEquiv.eq_symm_comp f g
#align linear_equiv.eq_symm_comp LinearEquiv.eq_symm_comp
theorem symm_comp_eq {α : Type*} (f : α → M₁) (g : α → M₂) : e₁₂.symm ∘ g = f ↔ g = e₁₂ ∘ f :=
e₁₂.toEquiv.symm_comp_eq f g
#align linear_equiv.symm_comp_eq LinearEquiv.symm_comp_eq
variable [RingHomCompTriple σ₂₁ σ₁₃ σ₂₃] [RingHomCompTriple σ₃₁ σ₁₂ σ₃₂]
theorem eq_comp_toLinearMap_symm (f : M₂ →ₛₗ[σ₂₃] M₃) (g : M₁ →ₛₗ[σ₁₃] M₃) :
f = g.comp e₁₂.symm.toLinearMap ↔ f.comp e₁₂.toLinearMap = g := by
constructor <;> intro H <;> ext
· simp [H, e₁₂.toEquiv.eq_comp_symm f g]
· simp [← H, ← e₁₂.toEquiv.eq_comp_symm f g]
#align linear_equiv.eq_comp_to_linear_map_symm LinearEquiv.eq_comp_toLinearMap_symm
theorem comp_toLinearMap_symm_eq (f : M₂ →ₛₗ[σ₂₃] M₃) (g : M₁ →ₛₗ[σ₁₃] M₃) :
g.comp e₁₂.symm.toLinearMap = f ↔ g = f.comp e₁₂.toLinearMap := by
constructor <;> intro H <;> ext
· simp [← H, ← e₁₂.toEquiv.comp_symm_eq f g]
· simp [H, e₁₂.toEquiv.comp_symm_eq f g]
#align linear_equiv.comp_to_linear_map_symm_eq LinearEquiv.comp_toLinearMap_symm_eq
| Mathlib/Algebra/Module/Equiv.lean | 447 | 451 | theorem eq_toLinearMap_symm_comp (f : M₃ →ₛₗ[σ₃₁] M₁) (g : M₃ →ₛₗ[σ₃₂] M₂) :
f = e₁₂.symm.toLinearMap.comp g ↔ e₁₂.toLinearMap.comp f = g := by |
constructor <;> intro H <;> ext
· simp [H, e₁₂.toEquiv.eq_symm_comp f g]
· simp [← H, ← e₁₂.toEquiv.eq_symm_comp f g]
|
/-
Copyright (c) 2024 Lawrence Wu. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Lawrence Wu
-/
import Mathlib.MeasureTheory.Group.Measure
import Mathlib.MeasureTheory.Integral.IntegrableOn
import Mathlib.MeasureTheory.Function.LocallyIntegrable
/-!
# Bounding of integrals by asymptotics
We establish integrability of `f` from `f = O(g)`.
## Main results
* `Asymptotics.IsBigO.integrableAtFilter`: If `f = O[l] g` on measurably generated `l`,
`f` is strongly measurable at `l`, and `g` is integrable at `l`, then `f` is integrable at `l`.
* `MeasureTheory.LocallyIntegrable.integrable_of_isBigO_cocompact`: If `f` is locally integrable,
and `f =O[cocompact] g` for some `g` integrable at `cocompact`, then `f` is integrable.
* `MeasureTheory.LocallyIntegrable.integrable_of_isBigO_atBot_atTop`: If `f` is locally integrable,
and `f =O[atBot] g`, `f =O[atTop] g'` for some `g`, `g'` integrable `atBot` and `atTop`
respectively, then `f` is integrable.
* `MeasureTheory.LocallyIntegrable.integrable_of_isBigO_atTop_of_norm_isNegInvariant`:
If `f` is locally integrable, `‖f(-x)‖ = ‖f(x)‖`, and `f =O[atTop] g` for some
`g` integrable `atTop`, then `f` is integrable.
-/
open Asymptotics MeasureTheory Set Filter
variable {α E F : Type*} [MeasurableSpace α] [NormedAddCommGroup E] [NormedAddCommGroup F]
{f : α → E} {g : α → F} {a b : α} {μ : Measure α} {l : Filter α}
/-- If `f = O[l] g` on measurably generated `l`, `f` is strongly measurable at `l`,
and `g` is integrable at `l`, then `f` is integrable at `l`. -/
theorem _root_.Asymptotics.IsBigO.integrableAtFilter [IsMeasurablyGenerated l]
(hf : f =O[l] g) (hfm : StronglyMeasurableAtFilter f l μ) (hg : IntegrableAtFilter g l μ) :
IntegrableAtFilter f l μ := by
obtain ⟨C, hC⟩ := hf.bound
obtain ⟨s, hsl, hsm, hfg, hf, hg⟩ :=
(hC.smallSets.and <| hfm.eventually.and hg.eventually).exists_measurable_mem_of_smallSets
refine ⟨s, hsl, (hg.norm.const_mul C).mono hf ?_⟩
refine (ae_restrict_mem hsm).mono fun x hx ↦ ?_
exact (hfg x hx).trans (le_abs_self _)
/-- Variant of `MeasureTheory.Integrable.mono` taking `f =O[⊤] (g)` instead of `‖f(x)‖ ≤ ‖g(x)‖` -/
theorem _root_.Asymptotics.IsBigO.integrable (hfm : AEStronglyMeasurable f μ)
(hf : f =O[⊤] g) (hg : Integrable g μ) : Integrable f μ := by
rewrite [← integrableAtFilter_top] at *
exact hf.integrableAtFilter ⟨univ, univ_mem, hfm.restrict⟩ hg
variable [TopologicalSpace α] [SecondCountableTopology α]
namespace MeasureTheory
/-- If `f` is locally integrable, and `f =O[cocompact] g` for some `g` integrable at `cocompact`,
then `f` is integrable. -/
theorem LocallyIntegrable.integrable_of_isBigO_cocompact [IsMeasurablyGenerated (cocompact α)]
(hf : LocallyIntegrable f μ) (ho : f =O[cocompact α] g)
(hg : IntegrableAtFilter g (cocompact α) μ) : Integrable f μ := by
refine integrable_iff_integrableAtFilter_cocompact.mpr ⟨ho.integrableAtFilter ?_ hg, hf⟩
exact hf.aestronglyMeasurable.stronglyMeasurableAtFilter
section LinearOrder
variable [LinearOrder α] [CompactIccSpace α] {g' : α → F}
/-- If `f` is locally integrable, and `f =O[atBot] g`, `f =O[atTop] g'` for some
`g`, `g'` integrable at `atBot` and `atTop` respectively, then `f` is integrable. -/
theorem LocallyIntegrable.integrable_of_isBigO_atBot_atTop
[IsMeasurablyGenerated (atBot (α := α))] [IsMeasurablyGenerated (atTop (α := α))]
(hf : LocallyIntegrable f μ)
(ho : f =O[atBot] g) (hg : IntegrableAtFilter g atBot μ)
(ho' : f =O[atTop] g') (hg' : IntegrableAtFilter g' atTop μ) : Integrable f μ := by
refine integrable_iff_integrableAtFilter_atBot_atTop.mpr
⟨⟨ho.integrableAtFilter ?_ hg, ho'.integrableAtFilter ?_ hg'⟩, hf⟩
all_goals exact hf.aestronglyMeasurable.stronglyMeasurableAtFilter
/-- If `f` is locally integrable on `(∞, a]`, and `f =O[atBot] g`, for some
`g` integrable at `atBot`, then `f` is integrable on `(∞, a]`. -/
theorem LocallyIntegrableOn.integrableOn_of_isBigO_atBot [IsMeasurablyGenerated (atBot (α := α))]
(hf : LocallyIntegrableOn f (Iic a) μ) (ho : f =O[atBot] g)
(hg : IntegrableAtFilter g atBot μ) : IntegrableOn f (Iic a) μ := by
refine integrableOn_Iic_iff_integrableAtFilter_atBot.mpr ⟨ho.integrableAtFilter ?_ hg, hf⟩
exact ⟨Iic a, Iic_mem_atBot a, hf.aestronglyMeasurable⟩
/-- If `f` is locally integrable on `[a, ∞)`, and `f =O[atTop] g`, for some
`g` integrable at `atTop`, then `f` is integrable on `[a, ∞)`. -/
theorem LocallyIntegrableOn.integrableOn_of_isBigO_atTop [IsMeasurablyGenerated (atTop (α := α))]
(hf : LocallyIntegrableOn f (Ici a) μ) (ho : f =O[atTop] g)
(hg : IntegrableAtFilter g atTop μ) : IntegrableOn f (Ici a) μ := by
refine integrableOn_Ici_iff_integrableAtFilter_atTop.mpr ⟨ho.integrableAtFilter ?_ hg, hf⟩
exact ⟨Ici a, Ici_mem_atTop a, hf.aestronglyMeasurable⟩
/-- If `f` is locally integrable, `f` has a top element, and `f =O[atBot] g`, for some
`g` integrable at `atBot`, then `f` is integrable. -/
theorem LocallyIntegrable.integrable_of_isBigO_atBot [IsMeasurablyGenerated (atBot (α := α))]
[OrderTop α] (hf : LocallyIntegrable f μ) (ho : f =O[atBot] g)
(hg : IntegrableAtFilter g atBot μ) : Integrable f μ := by
refine integrable_iff_integrableAtFilter_atBot.mpr ⟨ho.integrableAtFilter ?_ hg, hf⟩
exact hf.aestronglyMeasurable.stronglyMeasurableAtFilter
/-- If `f` is locally integrable, `f` has a bottom element, and `f =O[atTop] g`, for some
`g` integrable at `atTop`, then `f` is integrable. -/
theorem LocallyIntegrable.integrable_of_isBigO_atTop [IsMeasurablyGenerated (atTop (α := α))]
[OrderBot α] (hf : LocallyIntegrable f μ) (ho : f =O[atTop] g)
(hg : IntegrableAtFilter g atTop μ) : Integrable f μ := by
refine integrable_iff_integrableAtFilter_atTop.mpr ⟨ho.integrableAtFilter ?_ hg, hf⟩
exact hf.aestronglyMeasurable.stronglyMeasurableAtFilter
end LinearOrder
section LinearOrderedAddCommGroup
variable [LinearOrderedAddCommGroup α] [CompactIccSpace α]
/-- If `f` is locally integrable, `‖f(-x)‖ = ‖f(x)‖`, and `f =O[atTop] g`, for some
`g` integrable at `atTop`, then `f` is integrable. -/
| Mathlib/MeasureTheory/Integral/Asymptotics.lean | 119 | 132 | theorem LocallyIntegrable.integrable_of_isBigO_atTop_of_norm_isNegInvariant
[IsMeasurablyGenerated (atTop (α := α))] [MeasurableNeg α] [μ.IsNegInvariant]
(hf : LocallyIntegrable f μ) (hsymm : norm ∘ f =ᵐ[μ] norm ∘ f ∘ Neg.neg) (ho : f =O[atTop] g)
(hg : IntegrableAtFilter g atTop μ) : Integrable f μ := by |
have h_int := (hf.locallyIntegrableOn (Ici 0)).integrableOn_of_isBigO_atTop ho hg
rw [← integrableOn_univ, ← Iic_union_Ici_of_le le_rfl, integrableOn_union]
refine ⟨?_, h_int⟩
have h_map_neg : (μ.restrict (Ici 0)).map Neg.neg = μ.restrict (Iic 0) := by
conv => rhs; rw [← Measure.map_neg_eq_self μ, measurableEmbedding_neg.restrict_map]
simp
rw [IntegrableOn, ← h_map_neg, measurableEmbedding_neg.integrable_map_iff]
refine h_int.congr' ?_ hsymm.restrict
refine AEStronglyMeasurable.comp_aemeasurable ?_ measurable_neg.aemeasurable
exact h_map_neg ▸ hf.aestronglyMeasurable.restrict
|
/-
Copyright (c) 2019 Calle Sönne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Calle Sönne
-/
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Basic
import Mathlib.Analysis.Normed.Group.AddCircle
import Mathlib.Algebra.CharZero.Quotient
import Mathlib.Topology.Instances.Sign
#align_import analysis.special_functions.trigonometric.angle from "leanprover-community/mathlib"@"213b0cff7bc5ab6696ee07cceec80829ce42efec"
/-!
# The type of angles
In this file we define `Real.Angle` to be the quotient group `ℝ/2πℤ` and prove a few simple lemmas
about trigonometric functions and angles.
-/
open Real
noncomputable section
namespace Real
-- Porting note: can't derive `NormedAddCommGroup, Inhabited`
/-- The type of angles -/
def Angle : Type :=
AddCircle (2 * π)
#align real.angle Real.Angle
namespace Angle
-- Porting note (#10754): added due to missing instances due to no deriving
instance : NormedAddCommGroup Angle :=
inferInstanceAs (NormedAddCommGroup (AddCircle (2 * π)))
-- Porting note (#10754): added due to missing instances due to no deriving
instance : Inhabited Angle :=
inferInstanceAs (Inhabited (AddCircle (2 * π)))
-- Porting note (#10754): added due to missing instances due to no deriving
-- also, without this, a plain `QuotientAddGroup.mk`
-- causes coerced terms to be of type `ℝ ⧸ AddSubgroup.zmultiples (2 * π)`
/-- The canonical map from `ℝ` to the quotient `Angle`. -/
@[coe]
protected def coe (r : ℝ) : Angle := QuotientAddGroup.mk r
instance : Coe ℝ Angle := ⟨Angle.coe⟩
instance : CircularOrder Real.Angle :=
QuotientAddGroup.circularOrder (hp' := ⟨by norm_num [pi_pos]⟩)
@[continuity]
theorem continuous_coe : Continuous ((↑) : ℝ → Angle) :=
continuous_quotient_mk'
#align real.angle.continuous_coe Real.Angle.continuous_coe
/-- Coercion `ℝ → Angle` as an additive homomorphism. -/
def coeHom : ℝ →+ Angle :=
QuotientAddGroup.mk' _
#align real.angle.coe_hom Real.Angle.coeHom
@[simp]
theorem coe_coeHom : (coeHom : ℝ → Angle) = ((↑) : ℝ → Angle) :=
rfl
#align real.angle.coe_coe_hom Real.Angle.coe_coeHom
/-- An induction principle to deduce results for `Angle` from those for `ℝ`, used with
`induction θ using Real.Angle.induction_on`. -/
@[elab_as_elim]
protected theorem induction_on {p : Angle → Prop} (θ : Angle) (h : ∀ x : ℝ, p x) : p θ :=
Quotient.inductionOn' θ h
#align real.angle.induction_on Real.Angle.induction_on
@[simp]
theorem coe_zero : ↑(0 : ℝ) = (0 : Angle) :=
rfl
#align real.angle.coe_zero Real.Angle.coe_zero
@[simp]
theorem coe_add (x y : ℝ) : ↑(x + y : ℝ) = (↑x + ↑y : Angle) :=
rfl
#align real.angle.coe_add Real.Angle.coe_add
@[simp]
theorem coe_neg (x : ℝ) : ↑(-x : ℝ) = -(↑x : Angle) :=
rfl
#align real.angle.coe_neg Real.Angle.coe_neg
@[simp]
theorem coe_sub (x y : ℝ) : ↑(x - y : ℝ) = (↑x - ↑y : Angle) :=
rfl
#align real.angle.coe_sub Real.Angle.coe_sub
theorem coe_nsmul (n : ℕ) (x : ℝ) : ↑(n • x : ℝ) = n • (↑x : Angle) :=
rfl
#align real.angle.coe_nsmul Real.Angle.coe_nsmul
theorem coe_zsmul (z : ℤ) (x : ℝ) : ↑(z • x : ℝ) = z • (↑x : Angle) :=
rfl
#align real.angle.coe_zsmul Real.Angle.coe_zsmul
@[simp, norm_cast]
theorem natCast_mul_eq_nsmul (x : ℝ) (n : ℕ) : ↑((n : ℝ) * x) = n • (↑x : Angle) := by
simpa only [nsmul_eq_mul] using coeHom.map_nsmul x n
#align real.angle.coe_nat_mul_eq_nsmul Real.Angle.natCast_mul_eq_nsmul
@[simp, norm_cast]
theorem intCast_mul_eq_zsmul (x : ℝ) (n : ℤ) : ↑((n : ℝ) * x : ℝ) = n • (↑x : Angle) := by
simpa only [zsmul_eq_mul] using coeHom.map_zsmul x n
#align real.angle.coe_int_mul_eq_zsmul Real.Angle.intCast_mul_eq_zsmul
@[deprecated (since := "2024-05-25")] alias coe_nat_mul_eq_nsmul := natCast_mul_eq_nsmul
@[deprecated (since := "2024-05-25")] alias coe_int_mul_eq_zsmul := intCast_mul_eq_zsmul
theorem angle_eq_iff_two_pi_dvd_sub {ψ θ : ℝ} : (θ : Angle) = ψ ↔ ∃ k : ℤ, θ - ψ = 2 * π * k := by
simp only [QuotientAddGroup.eq, AddSubgroup.zmultiples_eq_closure,
AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm]
-- Porting note: added `rw`, `simp [Angle.coe, QuotientAddGroup.eq]` doesn't fire otherwise
rw [Angle.coe, Angle.coe, QuotientAddGroup.eq]
simp only [AddSubgroup.zmultiples_eq_closure,
AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm]
#align real.angle.angle_eq_iff_two_pi_dvd_sub Real.Angle.angle_eq_iff_two_pi_dvd_sub
@[simp]
theorem coe_two_pi : ↑(2 * π : ℝ) = (0 : Angle) :=
angle_eq_iff_two_pi_dvd_sub.2 ⟨1, by rw [sub_zero, Int.cast_one, mul_one]⟩
#align real.angle.coe_two_pi Real.Angle.coe_two_pi
@[simp]
theorem neg_coe_pi : -(π : Angle) = π := by
rw [← coe_neg, angle_eq_iff_two_pi_dvd_sub]
use -1
simp [two_mul, sub_eq_add_neg]
#align real.angle.neg_coe_pi Real.Angle.neg_coe_pi
@[simp]
theorem two_nsmul_coe_div_two (θ : ℝ) : (2 : ℕ) • (↑(θ / 2) : Angle) = θ := by
rw [← coe_nsmul, two_nsmul, add_halves]
#align real.angle.two_nsmul_coe_div_two Real.Angle.two_nsmul_coe_div_two
@[simp]
theorem two_zsmul_coe_div_two (θ : ℝ) : (2 : ℤ) • (↑(θ / 2) : Angle) = θ := by
rw [← coe_zsmul, two_zsmul, add_halves]
#align real.angle.two_zsmul_coe_div_two Real.Angle.two_zsmul_coe_div_two
-- Porting note (#10618): @[simp] can prove it
theorem two_nsmul_neg_pi_div_two : (2 : ℕ) • (↑(-π / 2) : Angle) = π := by
rw [two_nsmul_coe_div_two, coe_neg, neg_coe_pi]
#align real.angle.two_nsmul_neg_pi_div_two Real.Angle.two_nsmul_neg_pi_div_two
-- Porting note (#10618): @[simp] can prove it
theorem two_zsmul_neg_pi_div_two : (2 : ℤ) • (↑(-π / 2) : Angle) = π := by
rw [two_zsmul, ← two_nsmul, two_nsmul_neg_pi_div_two]
#align real.angle.two_zsmul_neg_pi_div_two Real.Angle.two_zsmul_neg_pi_div_two
theorem sub_coe_pi_eq_add_coe_pi (θ : Angle) : θ - π = θ + π := by
rw [sub_eq_add_neg, neg_coe_pi]
#align real.angle.sub_coe_pi_eq_add_coe_pi Real.Angle.sub_coe_pi_eq_add_coe_pi
@[simp]
theorem two_nsmul_coe_pi : (2 : ℕ) • (π : Angle) = 0 := by simp [← natCast_mul_eq_nsmul]
#align real.angle.two_nsmul_coe_pi Real.Angle.two_nsmul_coe_pi
@[simp]
theorem two_zsmul_coe_pi : (2 : ℤ) • (π : Angle) = 0 := by simp [← intCast_mul_eq_zsmul]
#align real.angle.two_zsmul_coe_pi Real.Angle.two_zsmul_coe_pi
@[simp]
theorem coe_pi_add_coe_pi : (π : Real.Angle) + π = 0 := by rw [← two_nsmul, two_nsmul_coe_pi]
#align real.angle.coe_pi_add_coe_pi Real.Angle.coe_pi_add_coe_pi
theorem zsmul_eq_iff {ψ θ : Angle} {z : ℤ} (hz : z ≠ 0) :
z • ψ = z • θ ↔ ∃ k : Fin z.natAbs, ψ = θ + (k : ℕ) • (2 * π / z : ℝ) :=
QuotientAddGroup.zmultiples_zsmul_eq_zsmul_iff hz
#align real.angle.zsmul_eq_iff Real.Angle.zsmul_eq_iff
theorem nsmul_eq_iff {ψ θ : Angle} {n : ℕ} (hz : n ≠ 0) :
n • ψ = n • θ ↔ ∃ k : Fin n, ψ = θ + (k : ℕ) • (2 * π / n : ℝ) :=
QuotientAddGroup.zmultiples_nsmul_eq_nsmul_iff hz
#align real.angle.nsmul_eq_iff Real.Angle.nsmul_eq_iff
theorem two_zsmul_eq_iff {ψ θ : Angle} : (2 : ℤ) • ψ = (2 : ℤ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by
-- Porting note: no `Int.natAbs_bit0` anymore
have : Int.natAbs 2 = 2 := rfl
rw [zsmul_eq_iff two_ne_zero, this, Fin.exists_fin_two, Fin.val_zero,
Fin.val_one, zero_smul, add_zero, one_smul, Int.cast_two,
mul_div_cancel_left₀ (_ : ℝ) two_ne_zero]
#align real.angle.two_zsmul_eq_iff Real.Angle.two_zsmul_eq_iff
theorem two_nsmul_eq_iff {ψ θ : Angle} : (2 : ℕ) • ψ = (2 : ℕ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by
simp_rw [← natCast_zsmul, Nat.cast_ofNat, two_zsmul_eq_iff]
#align real.angle.two_nsmul_eq_iff Real.Angle.two_nsmul_eq_iff
theorem two_nsmul_eq_zero_iff {θ : Angle} : (2 : ℕ) • θ = 0 ↔ θ = 0 ∨ θ = π := by
convert two_nsmul_eq_iff <;> simp
#align real.angle.two_nsmul_eq_zero_iff Real.Angle.two_nsmul_eq_zero_iff
theorem two_nsmul_ne_zero_iff {θ : Angle} : (2 : ℕ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← two_nsmul_eq_zero_iff]
#align real.angle.two_nsmul_ne_zero_iff Real.Angle.two_nsmul_ne_zero_iff
theorem two_zsmul_eq_zero_iff {θ : Angle} : (2 : ℤ) • θ = 0 ↔ θ = 0 ∨ θ = π := by
simp_rw [two_zsmul, ← two_nsmul, two_nsmul_eq_zero_iff]
#align real.angle.two_zsmul_eq_zero_iff Real.Angle.two_zsmul_eq_zero_iff
theorem two_zsmul_ne_zero_iff {θ : Angle} : (2 : ℤ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← two_zsmul_eq_zero_iff]
#align real.angle.two_zsmul_ne_zero_iff Real.Angle.two_zsmul_ne_zero_iff
theorem eq_neg_self_iff {θ : Angle} : θ = -θ ↔ θ = 0 ∨ θ = π := by
rw [← add_eq_zero_iff_eq_neg, ← two_nsmul, two_nsmul_eq_zero_iff]
#align real.angle.eq_neg_self_iff Real.Angle.eq_neg_self_iff
theorem ne_neg_self_iff {θ : Angle} : θ ≠ -θ ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← eq_neg_self_iff.not]
#align real.angle.ne_neg_self_iff Real.Angle.ne_neg_self_iff
theorem neg_eq_self_iff {θ : Angle} : -θ = θ ↔ θ = 0 ∨ θ = π := by rw [eq_comm, eq_neg_self_iff]
#align real.angle.neg_eq_self_iff Real.Angle.neg_eq_self_iff
theorem neg_ne_self_iff {θ : Angle} : -θ ≠ θ ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← neg_eq_self_iff.not]
#align real.angle.neg_ne_self_iff Real.Angle.neg_ne_self_iff
theorem two_nsmul_eq_pi_iff {θ : Angle} : (2 : ℕ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
have h : (π : Angle) = ((2 : ℕ) • (π / 2 : ℝ) :) := by rw [two_nsmul, add_halves]
nth_rw 1 [h]
rw [coe_nsmul, two_nsmul_eq_iff]
-- Porting note: `congr` didn't simplify the goal of iff of `Or`s
convert Iff.rfl
rw [add_comm, ← coe_add, ← sub_eq_zero, ← coe_sub, neg_div, ← neg_sub, sub_neg_eq_add, add_assoc,
add_halves, ← two_mul, coe_neg, coe_two_pi, neg_zero]
#align real.angle.two_nsmul_eq_pi_iff Real.Angle.two_nsmul_eq_pi_iff
theorem two_zsmul_eq_pi_iff {θ : Angle} : (2 : ℤ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
rw [two_zsmul, ← two_nsmul, two_nsmul_eq_pi_iff]
#align real.angle.two_zsmul_eq_pi_iff Real.Angle.two_zsmul_eq_pi_iff
theorem cos_eq_iff_coe_eq_or_eq_neg {θ ψ : ℝ} :
cos θ = cos ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) = -ψ := by
constructor
· intro Hcos
rw [← sub_eq_zero, cos_sub_cos, mul_eq_zero, mul_eq_zero, neg_eq_zero,
eq_false (two_ne_zero' ℝ), false_or_iff, sin_eq_zero_iff, sin_eq_zero_iff] at Hcos
rcases Hcos with (⟨n, hn⟩ | ⟨n, hn⟩)
· right
rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), ← sub_eq_iff_eq_add] at hn
rw [← hn, coe_sub, eq_neg_iff_add_eq_zero, sub_add_cancel, mul_assoc, intCast_mul_eq_zsmul,
mul_comm, coe_two_pi, zsmul_zero]
· left
rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), eq_sub_iff_add_eq] at hn
rw [← hn, coe_add, mul_assoc, intCast_mul_eq_zsmul, mul_comm, coe_two_pi, zsmul_zero,
zero_add]
· rw [angle_eq_iff_two_pi_dvd_sub, ← coe_neg, angle_eq_iff_two_pi_dvd_sub]
rintro (⟨k, H⟩ | ⟨k, H⟩)
· rw [← sub_eq_zero, cos_sub_cos, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ),
mul_comm π _, sin_int_mul_pi, mul_zero]
rw [← sub_eq_zero, cos_sub_cos, ← sub_neg_eq_add, H, mul_assoc 2 π k,
mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero,
zero_mul]
#align real.angle.cos_eq_iff_coe_eq_or_eq_neg Real.Angle.cos_eq_iff_coe_eq_or_eq_neg
theorem sin_eq_iff_coe_eq_or_add_eq_pi {θ ψ : ℝ} :
sin θ = sin ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) + ψ = π := by
constructor
· intro Hsin
rw [← cos_pi_div_two_sub, ← cos_pi_div_two_sub] at Hsin
cases' cos_eq_iff_coe_eq_or_eq_neg.mp Hsin with h h
· left
rw [coe_sub, coe_sub] at h
exact sub_right_inj.1 h
right
rw [coe_sub, coe_sub, eq_neg_iff_add_eq_zero, add_sub, sub_add_eq_add_sub, ← coe_add,
add_halves, sub_sub, sub_eq_zero] at h
exact h.symm
· rw [angle_eq_iff_two_pi_dvd_sub, ← eq_sub_iff_add_eq, ← coe_sub, angle_eq_iff_two_pi_dvd_sub]
rintro (⟨k, H⟩ | ⟨k, H⟩)
· rw [← sub_eq_zero, sin_sub_sin, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ),
mul_comm π _, sin_int_mul_pi, mul_zero, zero_mul]
have H' : θ + ψ = 2 * k * π + π := by
rwa [← sub_add, sub_add_eq_add_sub, sub_eq_iff_eq_add, mul_assoc, mul_comm π _, ←
mul_assoc] at H
rw [← sub_eq_zero, sin_sub_sin, H', add_div, mul_assoc 2 _ π,
mul_div_cancel_left₀ _ (two_ne_zero' ℝ), cos_add_pi_div_two, sin_int_mul_pi, neg_zero,
mul_zero]
#align real.angle.sin_eq_iff_coe_eq_or_add_eq_pi Real.Angle.sin_eq_iff_coe_eq_or_add_eq_pi
theorem cos_sin_inj {θ ψ : ℝ} (Hcos : cos θ = cos ψ) (Hsin : sin θ = sin ψ) : (θ : Angle) = ψ := by
cases' cos_eq_iff_coe_eq_or_eq_neg.mp Hcos with hc hc; · exact hc
cases' sin_eq_iff_coe_eq_or_add_eq_pi.mp Hsin with hs hs; · exact hs
rw [eq_neg_iff_add_eq_zero, hs] at hc
obtain ⟨n, hn⟩ : ∃ n, n • _ = _ := QuotientAddGroup.leftRel_apply.mp (Quotient.exact' hc)
rw [← neg_one_mul, add_zero, ← sub_eq_zero, zsmul_eq_mul, ← mul_assoc, ← sub_mul, mul_eq_zero,
eq_false (ne_of_gt pi_pos), or_false_iff, sub_neg_eq_add, ← Int.cast_zero, ← Int.cast_one,
← Int.cast_ofNat, ← Int.cast_mul, ← Int.cast_add, Int.cast_inj] at hn
have : (n * 2 + 1) % (2 : ℤ) = 0 % (2 : ℤ) := congr_arg (· % (2 : ℤ)) hn
rw [add_comm, Int.add_mul_emod_self] at this
exact absurd this one_ne_zero
#align real.angle.cos_sin_inj Real.Angle.cos_sin_inj
/-- The sine of a `Real.Angle`. -/
def sin (θ : Angle) : ℝ :=
sin_periodic.lift θ
#align real.angle.sin Real.Angle.sin
@[simp]
theorem sin_coe (x : ℝ) : sin (x : Angle) = Real.sin x :=
rfl
#align real.angle.sin_coe Real.Angle.sin_coe
@[continuity]
theorem continuous_sin : Continuous sin :=
Real.continuous_sin.quotient_liftOn' _
#align real.angle.continuous_sin Real.Angle.continuous_sin
/-- The cosine of a `Real.Angle`. -/
def cos (θ : Angle) : ℝ :=
cos_periodic.lift θ
#align real.angle.cos Real.Angle.cos
@[simp]
theorem cos_coe (x : ℝ) : cos (x : Angle) = Real.cos x :=
rfl
#align real.angle.cos_coe Real.Angle.cos_coe
@[continuity]
theorem continuous_cos : Continuous cos :=
Real.continuous_cos.quotient_liftOn' _
#align real.angle.continuous_cos Real.Angle.continuous_cos
theorem cos_eq_real_cos_iff_eq_or_eq_neg {θ : Angle} {ψ : ℝ} :
cos θ = Real.cos ψ ↔ θ = ψ ∨ θ = -ψ := by
induction θ using Real.Angle.induction_on
exact cos_eq_iff_coe_eq_or_eq_neg
#align real.angle.cos_eq_real_cos_iff_eq_or_eq_neg Real.Angle.cos_eq_real_cos_iff_eq_or_eq_neg
theorem cos_eq_iff_eq_or_eq_neg {θ ψ : Angle} : cos θ = cos ψ ↔ θ = ψ ∨ θ = -ψ := by
induction ψ using Real.Angle.induction_on
exact cos_eq_real_cos_iff_eq_or_eq_neg
#align real.angle.cos_eq_iff_eq_or_eq_neg Real.Angle.cos_eq_iff_eq_or_eq_neg
theorem sin_eq_real_sin_iff_eq_or_add_eq_pi {θ : Angle} {ψ : ℝ} :
sin θ = Real.sin ψ ↔ θ = ψ ∨ θ + ψ = π := by
induction θ using Real.Angle.induction_on
exact sin_eq_iff_coe_eq_or_add_eq_pi
#align real.angle.sin_eq_real_sin_iff_eq_or_add_eq_pi Real.Angle.sin_eq_real_sin_iff_eq_or_add_eq_pi
theorem sin_eq_iff_eq_or_add_eq_pi {θ ψ : Angle} : sin θ = sin ψ ↔ θ = ψ ∨ θ + ψ = π := by
induction ψ using Real.Angle.induction_on
exact sin_eq_real_sin_iff_eq_or_add_eq_pi
#align real.angle.sin_eq_iff_eq_or_add_eq_pi Real.Angle.sin_eq_iff_eq_or_add_eq_pi
@[simp]
theorem sin_zero : sin (0 : Angle) = 0 := by rw [← coe_zero, sin_coe, Real.sin_zero]
#align real.angle.sin_zero Real.Angle.sin_zero
-- Porting note (#10618): @[simp] can prove it
theorem sin_coe_pi : sin (π : Angle) = 0 := by rw [sin_coe, Real.sin_pi]
#align real.angle.sin_coe_pi Real.Angle.sin_coe_pi
theorem sin_eq_zero_iff {θ : Angle} : sin θ = 0 ↔ θ = 0 ∨ θ = π := by
nth_rw 1 [← sin_zero]
rw [sin_eq_iff_eq_or_add_eq_pi]
simp
#align real.angle.sin_eq_zero_iff Real.Angle.sin_eq_zero_iff
theorem sin_ne_zero_iff {θ : Angle} : sin θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← sin_eq_zero_iff]
#align real.angle.sin_ne_zero_iff Real.Angle.sin_ne_zero_iff
@[simp]
theorem sin_neg (θ : Angle) : sin (-θ) = -sin θ := by
induction θ using Real.Angle.induction_on
exact Real.sin_neg _
#align real.angle.sin_neg Real.Angle.sin_neg
theorem sin_antiperiodic : Function.Antiperiodic sin (π : Angle) := by
intro θ
induction θ using Real.Angle.induction_on
exact Real.sin_antiperiodic _
#align real.angle.sin_antiperiodic Real.Angle.sin_antiperiodic
@[simp]
theorem sin_add_pi (θ : Angle) : sin (θ + π) = -sin θ :=
sin_antiperiodic θ
#align real.angle.sin_add_pi Real.Angle.sin_add_pi
@[simp]
theorem sin_sub_pi (θ : Angle) : sin (θ - π) = -sin θ :=
sin_antiperiodic.sub_eq θ
#align real.angle.sin_sub_pi Real.Angle.sin_sub_pi
@[simp]
theorem cos_zero : cos (0 : Angle) = 1 := by rw [← coe_zero, cos_coe, Real.cos_zero]
#align real.angle.cos_zero Real.Angle.cos_zero
-- Porting note (#10618): @[simp] can prove it
theorem cos_coe_pi : cos (π : Angle) = -1 := by rw [cos_coe, Real.cos_pi]
#align real.angle.cos_coe_pi Real.Angle.cos_coe_pi
@[simp]
theorem cos_neg (θ : Angle) : cos (-θ) = cos θ := by
induction θ using Real.Angle.induction_on
exact Real.cos_neg _
#align real.angle.cos_neg Real.Angle.cos_neg
theorem cos_antiperiodic : Function.Antiperiodic cos (π : Angle) := by
intro θ
induction θ using Real.Angle.induction_on
exact Real.cos_antiperiodic _
#align real.angle.cos_antiperiodic Real.Angle.cos_antiperiodic
@[simp]
theorem cos_add_pi (θ : Angle) : cos (θ + π) = -cos θ :=
cos_antiperiodic θ
#align real.angle.cos_add_pi Real.Angle.cos_add_pi
@[simp]
theorem cos_sub_pi (θ : Angle) : cos (θ - π) = -cos θ :=
cos_antiperiodic.sub_eq θ
#align real.angle.cos_sub_pi Real.Angle.cos_sub_pi
theorem cos_eq_zero_iff {θ : Angle} : cos θ = 0 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
rw [← cos_pi_div_two, ← cos_coe, cos_eq_iff_eq_or_eq_neg, ← coe_neg, ← neg_div]
#align real.angle.cos_eq_zero_iff Real.Angle.cos_eq_zero_iff
theorem sin_add (θ₁ θ₂ : Real.Angle) : sin (θ₁ + θ₂) = sin θ₁ * cos θ₂ + cos θ₁ * sin θ₂ := by
induction θ₁ using Real.Angle.induction_on
induction θ₂ using Real.Angle.induction_on
exact Real.sin_add _ _
#align real.angle.sin_add Real.Angle.sin_add
theorem cos_add (θ₁ θ₂ : Real.Angle) : cos (θ₁ + θ₂) = cos θ₁ * cos θ₂ - sin θ₁ * sin θ₂ := by
induction θ₂ using Real.Angle.induction_on
induction θ₁ using Real.Angle.induction_on
exact Real.cos_add _ _
#align real.angle.cos_add Real.Angle.cos_add
@[simp]
theorem cos_sq_add_sin_sq (θ : Real.Angle) : cos θ ^ 2 + sin θ ^ 2 = 1 := by
induction θ using Real.Angle.induction_on
exact Real.cos_sq_add_sin_sq _
#align real.angle.cos_sq_add_sin_sq Real.Angle.cos_sq_add_sin_sq
theorem sin_add_pi_div_two (θ : Angle) : sin (θ + ↑(π / 2)) = cos θ := by
induction θ using Real.Angle.induction_on
exact Real.sin_add_pi_div_two _
#align real.angle.sin_add_pi_div_two Real.Angle.sin_add_pi_div_two
theorem sin_sub_pi_div_two (θ : Angle) : sin (θ - ↑(π / 2)) = -cos θ := by
induction θ using Real.Angle.induction_on
exact Real.sin_sub_pi_div_two _
#align real.angle.sin_sub_pi_div_two Real.Angle.sin_sub_pi_div_two
theorem sin_pi_div_two_sub (θ : Angle) : sin (↑(π / 2) - θ) = cos θ := by
induction θ using Real.Angle.induction_on
exact Real.sin_pi_div_two_sub _
#align real.angle.sin_pi_div_two_sub Real.Angle.sin_pi_div_two_sub
theorem cos_add_pi_div_two (θ : Angle) : cos (θ + ↑(π / 2)) = -sin θ := by
induction θ using Real.Angle.induction_on
exact Real.cos_add_pi_div_two _
#align real.angle.cos_add_pi_div_two Real.Angle.cos_add_pi_div_two
theorem cos_sub_pi_div_two (θ : Angle) : cos (θ - ↑(π / 2)) = sin θ := by
induction θ using Real.Angle.induction_on
exact Real.cos_sub_pi_div_two _
#align real.angle.cos_sub_pi_div_two Real.Angle.cos_sub_pi_div_two
theorem cos_pi_div_two_sub (θ : Angle) : cos (↑(π / 2) - θ) = sin θ := by
induction θ using Real.Angle.induction_on
exact Real.cos_pi_div_two_sub _
#align real.angle.cos_pi_div_two_sub Real.Angle.cos_pi_div_two_sub
theorem abs_sin_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) :
|sin θ| = |sin ψ| := by
rw [two_nsmul_eq_iff] at h
rcases h with (rfl | rfl)
· rfl
· rw [sin_add_pi, abs_neg]
#align real.angle.abs_sin_eq_of_two_nsmul_eq Real.Angle.abs_sin_eq_of_two_nsmul_eq
theorem abs_sin_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) :
|sin θ| = |sin ψ| := by
simp_rw [two_zsmul, ← two_nsmul] at h
exact abs_sin_eq_of_two_nsmul_eq h
#align real.angle.abs_sin_eq_of_two_zsmul_eq Real.Angle.abs_sin_eq_of_two_zsmul_eq
theorem abs_cos_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) :
|cos θ| = |cos ψ| := by
rw [two_nsmul_eq_iff] at h
rcases h with (rfl | rfl)
· rfl
· rw [cos_add_pi, abs_neg]
#align real.angle.abs_cos_eq_of_two_nsmul_eq Real.Angle.abs_cos_eq_of_two_nsmul_eq
theorem abs_cos_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) :
|cos θ| = |cos ψ| := by
simp_rw [two_zsmul, ← two_nsmul] at h
exact abs_cos_eq_of_two_nsmul_eq h
#align real.angle.abs_cos_eq_of_two_zsmul_eq Real.Angle.abs_cos_eq_of_two_zsmul_eq
@[simp]
theorem coe_toIcoMod (θ ψ : ℝ) : ↑(toIcoMod two_pi_pos ψ θ) = (θ : Angle) := by
rw [angle_eq_iff_two_pi_dvd_sub]
refine ⟨-toIcoDiv two_pi_pos ψ θ, ?_⟩
rw [toIcoMod_sub_self, zsmul_eq_mul, mul_comm]
#align real.angle.coe_to_Ico_mod Real.Angle.coe_toIcoMod
@[simp]
theorem coe_toIocMod (θ ψ : ℝ) : ↑(toIocMod two_pi_pos ψ θ) = (θ : Angle) := by
rw [angle_eq_iff_two_pi_dvd_sub]
refine ⟨-toIocDiv two_pi_pos ψ θ, ?_⟩
rw [toIocMod_sub_self, zsmul_eq_mul, mul_comm]
#align real.angle.coe_to_Ioc_mod Real.Angle.coe_toIocMod
/-- Convert a `Real.Angle` to a real number in the interval `Ioc (-π) π`. -/
def toReal (θ : Angle) : ℝ :=
(toIocMod_periodic two_pi_pos (-π)).lift θ
#align real.angle.to_real Real.Angle.toReal
theorem toReal_coe (θ : ℝ) : (θ : Angle).toReal = toIocMod two_pi_pos (-π) θ :=
rfl
#align real.angle.to_real_coe Real.Angle.toReal_coe
theorem toReal_coe_eq_self_iff {θ : ℝ} : (θ : Angle).toReal = θ ↔ -π < θ ∧ θ ≤ π := by
rw [toReal_coe, toIocMod_eq_self two_pi_pos]
ring_nf
rfl
#align real.angle.to_real_coe_eq_self_iff Real.Angle.toReal_coe_eq_self_iff
theorem toReal_coe_eq_self_iff_mem_Ioc {θ : ℝ} : (θ : Angle).toReal = θ ↔ θ ∈ Set.Ioc (-π) π := by
rw [toReal_coe_eq_self_iff, ← Set.mem_Ioc]
#align real.angle.to_real_coe_eq_self_iff_mem_Ioc Real.Angle.toReal_coe_eq_self_iff_mem_Ioc
theorem toReal_injective : Function.Injective toReal := by
intro θ ψ h
induction θ using Real.Angle.induction_on
induction ψ using Real.Angle.induction_on
simpa [toReal_coe, toIocMod_eq_toIocMod, zsmul_eq_mul, mul_comm _ (2 * π), ←
angle_eq_iff_two_pi_dvd_sub, eq_comm] using h
#align real.angle.to_real_injective Real.Angle.toReal_injective
@[simp]
theorem toReal_inj {θ ψ : Angle} : θ.toReal = ψ.toReal ↔ θ = ψ :=
toReal_injective.eq_iff
#align real.angle.to_real_inj Real.Angle.toReal_inj
@[simp]
theorem coe_toReal (θ : Angle) : (θ.toReal : Angle) = θ := by
induction θ using Real.Angle.induction_on
exact coe_toIocMod _ _
#align real.angle.coe_to_real Real.Angle.coe_toReal
theorem neg_pi_lt_toReal (θ : Angle) : -π < θ.toReal := by
induction θ using Real.Angle.induction_on
exact left_lt_toIocMod _ _ _
#align real.angle.neg_pi_lt_to_real Real.Angle.neg_pi_lt_toReal
theorem toReal_le_pi (θ : Angle) : θ.toReal ≤ π := by
induction θ using Real.Angle.induction_on
convert toIocMod_le_right two_pi_pos _ _
ring
#align real.angle.to_real_le_pi Real.Angle.toReal_le_pi
theorem abs_toReal_le_pi (θ : Angle) : |θ.toReal| ≤ π :=
abs_le.2 ⟨(neg_pi_lt_toReal _).le, toReal_le_pi _⟩
#align real.angle.abs_to_real_le_pi Real.Angle.abs_toReal_le_pi
theorem toReal_mem_Ioc (θ : Angle) : θ.toReal ∈ Set.Ioc (-π) π :=
⟨neg_pi_lt_toReal _, toReal_le_pi _⟩
#align real.angle.to_real_mem_Ioc Real.Angle.toReal_mem_Ioc
@[simp]
theorem toIocMod_toReal (θ : Angle) : toIocMod two_pi_pos (-π) θ.toReal = θ.toReal := by
induction θ using Real.Angle.induction_on
rw [toReal_coe]
exact toIocMod_toIocMod _ _ _ _
#align real.angle.to_Ioc_mod_to_real Real.Angle.toIocMod_toReal
@[simp]
theorem toReal_zero : (0 : Angle).toReal = 0 := by
rw [← coe_zero, toReal_coe_eq_self_iff]
exact ⟨Left.neg_neg_iff.2 Real.pi_pos, Real.pi_pos.le⟩
#align real.angle.to_real_zero Real.Angle.toReal_zero
@[simp]
theorem toReal_eq_zero_iff {θ : Angle} : θ.toReal = 0 ↔ θ = 0 := by
nth_rw 1 [← toReal_zero]
exact toReal_inj
#align real.angle.to_real_eq_zero_iff Real.Angle.toReal_eq_zero_iff
@[simp]
theorem toReal_pi : (π : Angle).toReal = π := by
rw [toReal_coe_eq_self_iff]
exact ⟨Left.neg_lt_self Real.pi_pos, le_refl _⟩
#align real.angle.to_real_pi Real.Angle.toReal_pi
@[simp]
theorem toReal_eq_pi_iff {θ : Angle} : θ.toReal = π ↔ θ = π := by rw [← toReal_inj, toReal_pi]
#align real.angle.to_real_eq_pi_iff Real.Angle.toReal_eq_pi_iff
theorem pi_ne_zero : (π : Angle) ≠ 0 := by
rw [← toReal_injective.ne_iff, toReal_pi, toReal_zero]
exact Real.pi_ne_zero
#align real.angle.pi_ne_zero Real.Angle.pi_ne_zero
@[simp]
theorem toReal_pi_div_two : ((π / 2 : ℝ) : Angle).toReal = π / 2 :=
toReal_coe_eq_self_iff.2 <| by constructor <;> linarith [pi_pos]
#align real.angle.to_real_pi_div_two Real.Angle.toReal_pi_div_two
@[simp]
theorem toReal_eq_pi_div_two_iff {θ : Angle} : θ.toReal = π / 2 ↔ θ = (π / 2 : ℝ) := by
rw [← toReal_inj, toReal_pi_div_two]
#align real.angle.to_real_eq_pi_div_two_iff Real.Angle.toReal_eq_pi_div_two_iff
@[simp]
theorem toReal_neg_pi_div_two : ((-π / 2 : ℝ) : Angle).toReal = -π / 2 :=
toReal_coe_eq_self_iff.2 <| by constructor <;> linarith [pi_pos]
#align real.angle.to_real_neg_pi_div_two Real.Angle.toReal_neg_pi_div_two
@[simp]
theorem toReal_eq_neg_pi_div_two_iff {θ : Angle} : θ.toReal = -π / 2 ↔ θ = (-π / 2 : ℝ) := by
rw [← toReal_inj, toReal_neg_pi_div_two]
#align real.angle.to_real_eq_neg_pi_div_two_iff Real.Angle.toReal_eq_neg_pi_div_two_iff
theorem pi_div_two_ne_zero : ((π / 2 : ℝ) : Angle) ≠ 0 := by
rw [← toReal_injective.ne_iff, toReal_pi_div_two, toReal_zero]
exact div_ne_zero Real.pi_ne_zero two_ne_zero
#align real.angle.pi_div_two_ne_zero Real.Angle.pi_div_two_ne_zero
theorem neg_pi_div_two_ne_zero : ((-π / 2 : ℝ) : Angle) ≠ 0 := by
rw [← toReal_injective.ne_iff, toReal_neg_pi_div_two, toReal_zero]
exact div_ne_zero (neg_ne_zero.2 Real.pi_ne_zero) two_ne_zero
#align real.angle.neg_pi_div_two_ne_zero Real.Angle.neg_pi_div_two_ne_zero
theorem abs_toReal_coe_eq_self_iff {θ : ℝ} : |(θ : Angle).toReal| = θ ↔ 0 ≤ θ ∧ θ ≤ π :=
⟨fun h => h ▸ ⟨abs_nonneg _, abs_toReal_le_pi _⟩, fun h =>
(toReal_coe_eq_self_iff.2 ⟨(Left.neg_neg_iff.2 Real.pi_pos).trans_le h.1, h.2⟩).symm ▸
abs_eq_self.2 h.1⟩
#align real.angle.abs_to_real_coe_eq_self_iff Real.Angle.abs_toReal_coe_eq_self_iff
theorem abs_toReal_neg_coe_eq_self_iff {θ : ℝ} : |(-θ : Angle).toReal| = θ ↔ 0 ≤ θ ∧ θ ≤ π := by
refine ⟨fun h => h ▸ ⟨abs_nonneg _, abs_toReal_le_pi _⟩, fun h => ?_⟩
by_cases hnegpi : θ = π; · simp [hnegpi, Real.pi_pos.le]
rw [← coe_neg,
toReal_coe_eq_self_iff.2
⟨neg_lt_neg (lt_of_le_of_ne h.2 hnegpi), (neg_nonpos.2 h.1).trans Real.pi_pos.le⟩,
abs_neg, abs_eq_self.2 h.1]
#align real.angle.abs_to_real_neg_coe_eq_self_iff Real.Angle.abs_toReal_neg_coe_eq_self_iff
theorem abs_toReal_eq_pi_div_two_iff {θ : Angle} :
|θ.toReal| = π / 2 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by
rw [abs_eq (div_nonneg Real.pi_pos.le two_pos.le), ← neg_div, toReal_eq_pi_div_two_iff,
toReal_eq_neg_pi_div_two_iff]
#align real.angle.abs_to_real_eq_pi_div_two_iff Real.Angle.abs_toReal_eq_pi_div_two_iff
theorem nsmul_toReal_eq_mul {n : ℕ} (h : n ≠ 0) {θ : Angle} :
(n • θ).toReal = n * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / n) (π / n) := by
nth_rw 1 [← coe_toReal θ]
have h' : 0 < (n : ℝ) := mod_cast Nat.pos_of_ne_zero h
rw [← coe_nsmul, nsmul_eq_mul, toReal_coe_eq_self_iff, Set.mem_Ioc, div_lt_iff' h',
le_div_iff' h']
#align real.angle.nsmul_to_real_eq_mul Real.Angle.nsmul_toReal_eq_mul
theorem two_nsmul_toReal_eq_two_mul {θ : Angle} :
((2 : ℕ) • θ).toReal = 2 * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / 2) (π / 2) :=
mod_cast nsmul_toReal_eq_mul two_ne_zero
#align real.angle.two_nsmul_to_real_eq_two_mul Real.Angle.two_nsmul_toReal_eq_two_mul
theorem two_zsmul_toReal_eq_two_mul {θ : Angle} :
((2 : ℤ) • θ).toReal = 2 * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / 2) (π / 2) := by
rw [two_zsmul, ← two_nsmul, two_nsmul_toReal_eq_two_mul]
#align real.angle.two_zsmul_to_real_eq_two_mul Real.Angle.two_zsmul_toReal_eq_two_mul
theorem toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff {θ : ℝ} {k : ℤ} :
(θ : Angle).toReal = θ - 2 * k * π ↔ θ ∈ Set.Ioc ((2 * k - 1 : ℝ) * π) ((2 * k + 1) * π) := by
rw [← sub_zero (θ : Angle), ← zsmul_zero k, ← coe_two_pi, ← coe_zsmul, ← coe_sub, zsmul_eq_mul, ←
mul_assoc, mul_comm (k : ℝ), toReal_coe_eq_self_iff, Set.mem_Ioc]
exact ⟨fun h => ⟨by linarith, by linarith⟩, fun h => ⟨by linarith, by linarith⟩⟩
#align real.angle.to_real_coe_eq_self_sub_two_mul_int_mul_pi_iff Real.Angle.toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff
theorem toReal_coe_eq_self_sub_two_pi_iff {θ : ℝ} :
(θ : Angle).toReal = θ - 2 * π ↔ θ ∈ Set.Ioc π (3 * π) := by
convert @toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff θ 1 <;> norm_num
#align real.angle.to_real_coe_eq_self_sub_two_pi_iff Real.Angle.toReal_coe_eq_self_sub_two_pi_iff
theorem toReal_coe_eq_self_add_two_pi_iff {θ : ℝ} :
(θ : Angle).toReal = θ + 2 * π ↔ θ ∈ Set.Ioc (-3 * π) (-π) := by
convert @toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff θ (-1) using 2 <;>
set_option tactic.skipAssignedInstances false in norm_num
#align real.angle.to_real_coe_eq_self_add_two_pi_iff Real.Angle.toReal_coe_eq_self_add_two_pi_iff
theorem two_nsmul_toReal_eq_two_mul_sub_two_pi {θ : Angle} :
((2 : ℕ) • θ).toReal = 2 * θ.toReal - 2 * π ↔ π / 2 < θ.toReal := by
nth_rw 1 [← coe_toReal θ]
rw [← coe_nsmul, two_nsmul, ← two_mul, toReal_coe_eq_self_sub_two_pi_iff, Set.mem_Ioc]
exact
⟨fun h => by linarith, fun h =>
⟨(div_lt_iff' (zero_lt_two' ℝ)).1 h, by linarith [pi_pos, toReal_le_pi θ]⟩⟩
#align real.angle.two_nsmul_to_real_eq_two_mul_sub_two_pi Real.Angle.two_nsmul_toReal_eq_two_mul_sub_two_pi
theorem two_zsmul_toReal_eq_two_mul_sub_two_pi {θ : Angle} :
((2 : ℤ) • θ).toReal = 2 * θ.toReal - 2 * π ↔ π / 2 < θ.toReal := by
rw [two_zsmul, ← two_nsmul, two_nsmul_toReal_eq_two_mul_sub_two_pi]
#align real.angle.two_zsmul_to_real_eq_two_mul_sub_two_pi Real.Angle.two_zsmul_toReal_eq_two_mul_sub_two_pi
theorem two_nsmul_toReal_eq_two_mul_add_two_pi {θ : Angle} :
((2 : ℕ) • θ).toReal = 2 * θ.toReal + 2 * π ↔ θ.toReal ≤ -π / 2 := by
nth_rw 1 [← coe_toReal θ]
rw [← coe_nsmul, two_nsmul, ← two_mul, toReal_coe_eq_self_add_two_pi_iff, Set.mem_Ioc]
refine
⟨fun h => by linarith, fun h =>
⟨by linarith [pi_pos, neg_pi_lt_toReal θ], (le_div_iff' (zero_lt_two' ℝ)).1 h⟩⟩
#align real.angle.two_nsmul_to_real_eq_two_mul_add_two_pi Real.Angle.two_nsmul_toReal_eq_two_mul_add_two_pi
theorem two_zsmul_toReal_eq_two_mul_add_two_pi {θ : Angle} :
((2 : ℤ) • θ).toReal = 2 * θ.toReal + 2 * π ↔ θ.toReal ≤ -π / 2 := by
rw [two_zsmul, ← two_nsmul, two_nsmul_toReal_eq_two_mul_add_two_pi]
#align real.angle.two_zsmul_to_real_eq_two_mul_add_two_pi Real.Angle.two_zsmul_toReal_eq_two_mul_add_two_pi
@[simp]
theorem sin_toReal (θ : Angle) : Real.sin θ.toReal = sin θ := by
conv_rhs => rw [← coe_toReal θ, sin_coe]
#align real.angle.sin_to_real Real.Angle.sin_toReal
@[simp]
theorem cos_toReal (θ : Angle) : Real.cos θ.toReal = cos θ := by
conv_rhs => rw [← coe_toReal θ, cos_coe]
#align real.angle.cos_to_real Real.Angle.cos_toReal
theorem cos_nonneg_iff_abs_toReal_le_pi_div_two {θ : Angle} : 0 ≤ cos θ ↔ |θ.toReal| ≤ π / 2 := by
nth_rw 1 [← coe_toReal θ]
rw [abs_le, cos_coe]
refine ⟨fun h => ?_, cos_nonneg_of_mem_Icc⟩
by_contra hn
rw [not_and_or, not_le, not_le] at hn
refine (not_lt.2 h) ?_
rcases hn with (hn | hn)
· rw [← Real.cos_neg]
refine cos_neg_of_pi_div_two_lt_of_lt (by linarith) ?_
linarith [neg_pi_lt_toReal θ]
· refine cos_neg_of_pi_div_two_lt_of_lt hn ?_
linarith [toReal_le_pi θ]
#align real.angle.cos_nonneg_iff_abs_to_real_le_pi_div_two Real.Angle.cos_nonneg_iff_abs_toReal_le_pi_div_two
theorem cos_pos_iff_abs_toReal_lt_pi_div_two {θ : Angle} : 0 < cos θ ↔ |θ.toReal| < π / 2 := by
rw [lt_iff_le_and_ne, lt_iff_le_and_ne, cos_nonneg_iff_abs_toReal_le_pi_div_two, ←
and_congr_right]
rintro -
rw [Ne, Ne, not_iff_not, @eq_comm ℝ 0, abs_toReal_eq_pi_div_two_iff, cos_eq_zero_iff]
#align real.angle.cos_pos_iff_abs_to_real_lt_pi_div_two Real.Angle.cos_pos_iff_abs_toReal_lt_pi_div_two
theorem cos_neg_iff_pi_div_two_lt_abs_toReal {θ : Angle} : cos θ < 0 ↔ π / 2 < |θ.toReal| := by
rw [← not_le, ← not_le, not_iff_not, cos_nonneg_iff_abs_toReal_le_pi_div_two]
#align real.angle.cos_neg_iff_pi_div_two_lt_abs_to_real Real.Angle.cos_neg_iff_pi_div_two_lt_abs_toReal
theorem abs_cos_eq_abs_sin_of_two_nsmul_add_two_nsmul_eq_pi {θ ψ : Angle}
(h : (2 : ℕ) • θ + (2 : ℕ) • ψ = π) : |cos θ| = |sin ψ| := by
rw [← eq_sub_iff_add_eq, ← two_nsmul_coe_div_two, ← nsmul_sub, two_nsmul_eq_iff] at h
rcases h with (rfl | rfl) <;> simp [cos_pi_div_two_sub]
#align real.angle.abs_cos_eq_abs_sin_of_two_nsmul_add_two_nsmul_eq_pi Real.Angle.abs_cos_eq_abs_sin_of_two_nsmul_add_two_nsmul_eq_pi
theorem abs_cos_eq_abs_sin_of_two_zsmul_add_two_zsmul_eq_pi {θ ψ : Angle}
(h : (2 : ℤ) • θ + (2 : ℤ) • ψ = π) : |cos θ| = |sin ψ| := by
simp_rw [two_zsmul, ← two_nsmul] at h
exact abs_cos_eq_abs_sin_of_two_nsmul_add_two_nsmul_eq_pi h
#align real.angle.abs_cos_eq_abs_sin_of_two_zsmul_add_two_zsmul_eq_pi Real.Angle.abs_cos_eq_abs_sin_of_two_zsmul_add_two_zsmul_eq_pi
/-- The tangent of a `Real.Angle`. -/
def tan (θ : Angle) : ℝ :=
sin θ / cos θ
#align real.angle.tan Real.Angle.tan
theorem tan_eq_sin_div_cos (θ : Angle) : tan θ = sin θ / cos θ :=
rfl
#align real.angle.tan_eq_sin_div_cos Real.Angle.tan_eq_sin_div_cos
@[simp]
theorem tan_coe (x : ℝ) : tan (x : Angle) = Real.tan x := by
rw [tan, sin_coe, cos_coe, Real.tan_eq_sin_div_cos]
#align real.angle.tan_coe Real.Angle.tan_coe
@[simp]
theorem tan_zero : tan (0 : Angle) = 0 := by rw [← coe_zero, tan_coe, Real.tan_zero]
#align real.angle.tan_zero Real.Angle.tan_zero
-- Porting note (#10618): @[simp] can now prove it
theorem tan_coe_pi : tan (π : Angle) = 0 := by rw [tan_coe, Real.tan_pi]
#align real.angle.tan_coe_pi Real.Angle.tan_coe_pi
theorem tan_periodic : Function.Periodic tan (π : Angle) := by
intro θ
induction θ using Real.Angle.induction_on
rw [← coe_add, tan_coe, tan_coe]
exact Real.tan_periodic _
#align real.angle.tan_periodic Real.Angle.tan_periodic
@[simp]
theorem tan_add_pi (θ : Angle) : tan (θ + π) = tan θ :=
tan_periodic θ
#align real.angle.tan_add_pi Real.Angle.tan_add_pi
@[simp]
theorem tan_sub_pi (θ : Angle) : tan (θ - π) = tan θ :=
tan_periodic.sub_eq θ
#align real.angle.tan_sub_pi Real.Angle.tan_sub_pi
@[simp]
theorem tan_toReal (θ : Angle) : Real.tan θ.toReal = tan θ := by
conv_rhs => rw [← coe_toReal θ, tan_coe]
#align real.angle.tan_to_real Real.Angle.tan_toReal
theorem tan_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) : tan θ = tan ψ := by
rw [two_nsmul_eq_iff] at h
rcases h with (rfl | rfl)
· rfl
· exact tan_add_pi _
#align real.angle.tan_eq_of_two_nsmul_eq Real.Angle.tan_eq_of_two_nsmul_eq
theorem tan_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) : tan θ = tan ψ := by
simp_rw [two_zsmul, ← two_nsmul] at h
exact tan_eq_of_two_nsmul_eq h
#align real.angle.tan_eq_of_two_zsmul_eq Real.Angle.tan_eq_of_two_zsmul_eq
theorem tan_eq_inv_of_two_nsmul_add_two_nsmul_eq_pi {θ ψ : Angle}
(h : (2 : ℕ) • θ + (2 : ℕ) • ψ = π) : tan ψ = (tan θ)⁻¹ := by
induction θ using Real.Angle.induction_on
induction ψ using Real.Angle.induction_on
rw [← smul_add, ← coe_add, ← coe_nsmul, two_nsmul, ← two_mul, angle_eq_iff_two_pi_dvd_sub] at h
rcases h with ⟨k, h⟩
rw [sub_eq_iff_eq_add, ← mul_inv_cancel_left₀ two_ne_zero π, mul_assoc, ← mul_add,
mul_right_inj' (two_ne_zero' ℝ), ← eq_sub_iff_add_eq', mul_inv_cancel_left₀ two_ne_zero π,
inv_mul_eq_div, mul_comm] at h
rw [tan_coe, tan_coe, ← tan_pi_div_two_sub, h, add_sub_assoc, add_comm]
exact Real.tan_periodic.int_mul _ _
#align real.angle.tan_eq_inv_of_two_nsmul_add_two_nsmul_eq_pi Real.Angle.tan_eq_inv_of_two_nsmul_add_two_nsmul_eq_pi
theorem tan_eq_inv_of_two_zsmul_add_two_zsmul_eq_pi {θ ψ : Angle}
(h : (2 : ℤ) • θ + (2 : ℤ) • ψ = π) : tan ψ = (tan θ)⁻¹ := by
simp_rw [two_zsmul, ← two_nsmul] at h
exact tan_eq_inv_of_two_nsmul_add_two_nsmul_eq_pi h
#align real.angle.tan_eq_inv_of_two_zsmul_add_two_zsmul_eq_pi Real.Angle.tan_eq_inv_of_two_zsmul_add_two_zsmul_eq_pi
/-- The sign of a `Real.Angle` is `0` if the angle is `0` or `π`, `1` if the angle is strictly
between `0` and `π` and `-1` is the angle is strictly between `-π` and `0`. It is defined as the
sign of the sine of the angle. -/
def sign (θ : Angle) : SignType :=
SignType.sign (sin θ)
#align real.angle.sign Real.Angle.sign
@[simp]
theorem sign_zero : (0 : Angle).sign = 0 := by
rw [sign, sin_zero, _root_.sign_zero]
#align real.angle.sign_zero Real.Angle.sign_zero
@[simp]
theorem sign_coe_pi : (π : Angle).sign = 0 := by rw [sign, sin_coe_pi, _root_.sign_zero]
#align real.angle.sign_coe_pi Real.Angle.sign_coe_pi
@[simp]
theorem sign_neg (θ : Angle) : (-θ).sign = -θ.sign := by
simp_rw [sign, sin_neg, Left.sign_neg]
#align real.angle.sign_neg Real.Angle.sign_neg
theorem sign_antiperiodic : Function.Antiperiodic sign (π : Angle) := fun θ => by
rw [sign, sign, sin_add_pi, Left.sign_neg]
#align real.angle.sign_antiperiodic Real.Angle.sign_antiperiodic
@[simp]
theorem sign_add_pi (θ : Angle) : (θ + π).sign = -θ.sign :=
sign_antiperiodic θ
#align real.angle.sign_add_pi Real.Angle.sign_add_pi
@[simp]
theorem sign_pi_add (θ : Angle) : ((π : Angle) + θ).sign = -θ.sign := by rw [add_comm, sign_add_pi]
#align real.angle.sign_pi_add Real.Angle.sign_pi_add
@[simp]
theorem sign_sub_pi (θ : Angle) : (θ - π).sign = -θ.sign :=
sign_antiperiodic.sub_eq θ
#align real.angle.sign_sub_pi Real.Angle.sign_sub_pi
@[simp]
theorem sign_pi_sub (θ : Angle) : ((π : Angle) - θ).sign = θ.sign := by
simp [sign_antiperiodic.sub_eq']
#align real.angle.sign_pi_sub Real.Angle.sign_pi_sub
theorem sign_eq_zero_iff {θ : Angle} : θ.sign = 0 ↔ θ = 0 ∨ θ = π := by
rw [sign, _root_.sign_eq_zero_iff, sin_eq_zero_iff]
#align real.angle.sign_eq_zero_iff Real.Angle.sign_eq_zero_iff
theorem sign_ne_zero_iff {θ : Angle} : θ.sign ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by
rw [← not_or, ← sign_eq_zero_iff]
#align real.angle.sign_ne_zero_iff Real.Angle.sign_ne_zero_iff
theorem toReal_neg_iff_sign_neg {θ : Angle} : θ.toReal < 0 ↔ θ.sign = -1 := by
rw [sign, ← sin_toReal, sign_eq_neg_one_iff]
rcases lt_trichotomy θ.toReal 0 with (h | h | h)
· exact ⟨fun _ => Real.sin_neg_of_neg_of_neg_pi_lt h (neg_pi_lt_toReal θ), fun _ => h⟩
· simp [h]
· exact
⟨fun hn => False.elim (h.asymm hn), fun hn =>
False.elim (hn.not_le (sin_nonneg_of_nonneg_of_le_pi h.le (toReal_le_pi θ)))⟩
#align real.angle.to_real_neg_iff_sign_neg Real.Angle.toReal_neg_iff_sign_neg
theorem toReal_nonneg_iff_sign_nonneg {θ : Angle} : 0 ≤ θ.toReal ↔ 0 ≤ θ.sign := by
rcases lt_trichotomy θ.toReal 0 with (h | h | h)
· refine ⟨fun hn => False.elim (h.not_le hn), fun hn => ?_⟩
rw [toReal_neg_iff_sign_neg.1 h] at hn
exact False.elim (hn.not_lt (by decide))
· simp [h, sign, ← sin_toReal]
· refine ⟨fun _ => ?_, fun _ => h.le⟩
rw [sign, ← sin_toReal, sign_nonneg_iff]
exact sin_nonneg_of_nonneg_of_le_pi h.le (toReal_le_pi θ)
#align real.angle.to_real_nonneg_iff_sign_nonneg Real.Angle.toReal_nonneg_iff_sign_nonneg
@[simp]
| Mathlib/Analysis/SpecialFunctions/Trigonometric/Angle.lean | 924 | 930 | theorem sign_toReal {θ : Angle} (h : θ ≠ π) : SignType.sign θ.toReal = θ.sign := by |
rcases lt_trichotomy θ.toReal 0 with (ht | ht | ht)
· simp [ht, toReal_neg_iff_sign_neg.1 ht]
· simp [sign, ht, ← sin_toReal]
· rw [sign, ← sin_toReal, sign_pos ht,
sign_pos
(sin_pos_of_pos_of_lt_pi ht ((toReal_le_pi θ).lt_of_ne (toReal_eq_pi_iff.not.2 h)))]
|
/-
Copyright (c) 2019 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Eric Wieser
-/
import Mathlib.Data.Matrix.Basic
/-!
# Row and column matrices
This file provides results about row and column matrices
## Main definitions
* `Matrix.row r : Matrix Unit n α`: a matrix with a single row
* `Matrix.col c : Matrix m Unit α`: a matrix with a single column
* `Matrix.updateRow M i r`: update the `i`th row of `M` to `r`
* `Matrix.updateCol M j c`: update the `j`th column of `M` to `c`
-/
variable {l m n o : Type*}
universe u v w
variable {R : Type*} {α : Type v} {β : Type w}
namespace Matrix
/-- `Matrix.col u` is the column matrix whose entries are given by `u`. -/
def col (w : m → α) : Matrix m Unit α :=
of fun x _ => w x
#align matrix.col Matrix.col
-- TODO: set as an equation lemma for `col`, see mathlib4#3024
@[simp]
theorem col_apply (w : m → α) (i j) : col w i j = w i :=
rfl
#align matrix.col_apply Matrix.col_apply
/-- `Matrix.row u` is the row matrix whose entries are given by `u`. -/
def row (v : n → α) : Matrix Unit n α :=
of fun _ y => v y
#align matrix.row Matrix.row
-- TODO: set as an equation lemma for `row`, see mathlib4#3024
@[simp]
theorem row_apply (v : n → α) (i j) : row v i j = v j :=
rfl
#align matrix.row_apply Matrix.row_apply
theorem col_injective : Function.Injective (col : (m → α) → _) :=
fun _x _y h => funext fun i => congr_fun₂ h i ()
@[simp] theorem col_inj {v w : m → α} : col v = col w ↔ v = w := col_injective.eq_iff
@[simp] theorem col_zero [Zero α] : col (0 : m → α) = 0 := rfl
@[simp] theorem col_eq_zero [Zero α] (v : m → α) : col v = 0 ↔ v = 0 := col_inj
@[simp]
theorem col_add [Add α] (v w : m → α) : col (v + w) = col v + col w := by
ext
rfl
#align matrix.col_add Matrix.col_add
@[simp]
theorem col_smul [SMul R α] (x : R) (v : m → α) : col (x • v) = x • col v := by
ext
rfl
#align matrix.col_smul Matrix.col_smul
theorem row_injective : Function.Injective (row : (n → α) → _) :=
fun _x _y h => funext fun j => congr_fun₂ h () j
@[simp] theorem row_inj {v w : n → α} : row v = row w ↔ v = w := row_injective.eq_iff
@[simp] theorem row_zero [Zero α] : row (0 : n → α) = 0 := rfl
@[simp] theorem row_eq_zero [Zero α] (v : n → α) : row v = 0 ↔ v = 0 := row_inj
@[simp]
theorem row_add [Add α] (v w : m → α) : row (v + w) = row v + row w := by
ext
rfl
#align matrix.row_add Matrix.row_add
@[simp]
theorem row_smul [SMul R α] (x : R) (v : m → α) : row (x • v) = x • row v := by
ext
rfl
#align matrix.row_smul Matrix.row_smul
@[simp]
theorem transpose_col (v : m → α) : (Matrix.col v)ᵀ = Matrix.row v := by
ext
rfl
#align matrix.transpose_col Matrix.transpose_col
@[simp]
theorem transpose_row (v : m → α) : (Matrix.row v)ᵀ = Matrix.col v := by
ext
rfl
#align matrix.transpose_row Matrix.transpose_row
@[simp]
theorem conjTranspose_col [Star α] (v : m → α) : (col v)ᴴ = row (star v) := by
ext
rfl
#align matrix.conj_transpose_col Matrix.conjTranspose_col
@[simp]
theorem conjTranspose_row [Star α] (v : m → α) : (row v)ᴴ = col (star v) := by
ext
rfl
#align matrix.conj_transpose_row Matrix.conjTranspose_row
theorem row_vecMul [Fintype m] [NonUnitalNonAssocSemiring α] (M : Matrix m n α) (v : m → α) :
Matrix.row (v ᵥ* M) = Matrix.row v * M := by
ext
rfl
#align matrix.row_vec_mul Matrix.row_vecMul
theorem col_vecMul [Fintype m] [NonUnitalNonAssocSemiring α] (M : Matrix m n α) (v : m → α) :
Matrix.col (v ᵥ* M) = (Matrix.row v * M)ᵀ := by
ext
rfl
#align matrix.col_vec_mul Matrix.col_vecMul
theorem col_mulVec [Fintype n] [NonUnitalNonAssocSemiring α] (M : Matrix m n α) (v : n → α) :
Matrix.col (M *ᵥ v) = M * Matrix.col v := by
ext
rfl
#align matrix.col_mul_vec Matrix.col_mulVec
theorem row_mulVec [Fintype n] [NonUnitalNonAssocSemiring α] (M : Matrix m n α) (v : n → α) :
Matrix.row (M *ᵥ v) = (M * Matrix.col v)ᵀ := by
ext
rfl
#align matrix.row_mul_vec Matrix.row_mulVec
@[simp]
theorem row_mul_col_apply [Fintype m] [Mul α] [AddCommMonoid α] (v w : m → α) (i j) :
(row v * col w) i j = v ⬝ᵥ w :=
rfl
#align matrix.row_mul_col_apply Matrix.row_mul_col_apply
@[simp]
theorem diag_col_mul_row [Mul α] [AddCommMonoid α] (a b : n → α) :
diag (col a * row b) = a * b := by
ext
simp [Matrix.mul_apply, col, row]
#align matrix.diag_col_mul_row Matrix.diag_col_mul_row
theorem vecMulVec_eq [Mul α] [AddCommMonoid α] (w : m → α) (v : n → α) :
vecMulVec w v = col w * row v := by
ext
simp only [vecMulVec, mul_apply, Fintype.univ_punit, Finset.sum_singleton]
rfl
#align matrix.vec_mul_vec_eq Matrix.vecMulVec_eq
/-! ### Updating rows and columns -/
/-- Update, i.e. replace the `i`th row of matrix `A` with the values in `b`. -/
def updateRow [DecidableEq m] (M : Matrix m n α) (i : m) (b : n → α) : Matrix m n α :=
of <| Function.update M i b
#align matrix.update_row Matrix.updateRow
/-- Update, i.e. replace the `j`th column of matrix `A` with the values in `b`. -/
def updateColumn [DecidableEq n] (M : Matrix m n α) (j : n) (b : m → α) : Matrix m n α :=
of fun i => Function.update (M i) j (b i)
#align matrix.update_column Matrix.updateColumn
variable {M : Matrix m n α} {i : m} {j : n} {b : n → α} {c : m → α}
@[simp]
theorem updateRow_self [DecidableEq m] : updateRow M i b i = b :=
-- Porting note: (implicit arg) added `(β := _)`
Function.update_same (β := fun _ => (n → α)) i b M
#align matrix.update_row_self Matrix.updateRow_self
@[simp]
theorem updateColumn_self [DecidableEq n] : updateColumn M j c i j = c i :=
-- Porting note: (implicit arg) added `(β := _)`
Function.update_same (β := fun _ => α) j (c i) (M i)
#align matrix.update_column_self Matrix.updateColumn_self
@[simp]
theorem updateRow_ne [DecidableEq m] {i' : m} (i_ne : i' ≠ i) : updateRow M i b i' = M i' :=
-- Porting note: (implicit arg) added `(β := _)`
Function.update_noteq (β := fun _ => (n → α)) i_ne b M
#align matrix.update_row_ne Matrix.updateRow_ne
@[simp]
theorem updateColumn_ne [DecidableEq n] {j' : n} (j_ne : j' ≠ j) :
updateColumn M j c i j' = M i j' :=
-- Porting note: (implicit arg) added `(β := _)`
Function.update_noteq (β := fun _ => α) j_ne (c i) (M i)
#align matrix.update_column_ne Matrix.updateColumn_ne
theorem updateRow_apply [DecidableEq m] {i' : m} :
updateRow M i b i' j = if i' = i then b j else M i' j := by
by_cases h : i' = i
· rw [h, updateRow_self, if_pos rfl]
· rw [updateRow_ne h, if_neg h]
#align matrix.update_row_apply Matrix.updateRow_apply
theorem updateColumn_apply [DecidableEq n] {j' : n} :
updateColumn M j c i j' = if j' = j then c i else M i j' := by
by_cases h : j' = j
· rw [h, updateColumn_self, if_pos rfl]
· rw [updateColumn_ne h, if_neg h]
#align matrix.update_column_apply Matrix.updateColumn_apply
@[simp]
theorem updateColumn_subsingleton [Subsingleton n] (A : Matrix m n R) (i : n) (b : m → R) :
A.updateColumn i b = (col b).submatrix id (Function.const n ()) := by
ext x y
simp [updateColumn_apply, Subsingleton.elim i y]
#align matrix.update_column_subsingleton Matrix.updateColumn_subsingleton
@[simp]
theorem updateRow_subsingleton [Subsingleton m] (A : Matrix m n R) (i : m) (b : n → R) :
A.updateRow i b = (row b).submatrix (Function.const m ()) id := by
ext x y
simp [updateColumn_apply, Subsingleton.elim i x]
#align matrix.update_row_subsingleton Matrix.updateRow_subsingleton
theorem map_updateRow [DecidableEq m] (f : α → β) :
map (updateRow M i b) f = updateRow (M.map f) i (f ∘ b) := by
ext
rw [updateRow_apply, map_apply, map_apply, updateRow_apply]
exact apply_ite f _ _ _
#align matrix.map_update_row Matrix.map_updateRow
theorem map_updateColumn [DecidableEq n] (f : α → β) :
map (updateColumn M j c) f = updateColumn (M.map f) j (f ∘ c) := by
ext
rw [updateColumn_apply, map_apply, map_apply, updateColumn_apply]
exact apply_ite f _ _ _
#align matrix.map_update_column Matrix.map_updateColumn
theorem updateRow_transpose [DecidableEq n] : updateRow Mᵀ j c = (updateColumn M j c)ᵀ := by
ext
rw [transpose_apply, updateRow_apply, updateColumn_apply]
rfl
#align matrix.update_row_transpose Matrix.updateRow_transpose
theorem updateColumn_transpose [DecidableEq m] : updateColumn Mᵀ i b = (updateRow M i b)ᵀ := by
ext
rw [transpose_apply, updateRow_apply, updateColumn_apply]
rfl
#align matrix.update_column_transpose Matrix.updateColumn_transpose
theorem updateRow_conjTranspose [DecidableEq n] [Star α] :
updateRow Mᴴ j (star c) = (updateColumn M j c)ᴴ := by
rw [conjTranspose, conjTranspose, transpose_map, transpose_map, updateRow_transpose,
map_updateColumn]
rfl
#align matrix.update_row_conj_transpose Matrix.updateRow_conjTranspose
theorem updateColumn_conjTranspose [DecidableEq m] [Star α] :
updateColumn Mᴴ i (star b) = (updateRow M i b)ᴴ := by
rw [conjTranspose, conjTranspose, transpose_map, transpose_map, updateColumn_transpose,
map_updateRow]
rfl
#align matrix.update_column_conj_transpose Matrix.updateColumn_conjTranspose
@[simp]
theorem updateRow_eq_self [DecidableEq m] (A : Matrix m n α) (i : m) : A.updateRow i (A i) = A :=
Function.update_eq_self i A
#align matrix.update_row_eq_self Matrix.updateRow_eq_self
@[simp]
theorem updateColumn_eq_self [DecidableEq n] (A : Matrix m n α) (i : n) :
(A.updateColumn i fun j => A j i) = A :=
funext fun j => Function.update_eq_self i (A j)
#align matrix.update_column_eq_self Matrix.updateColumn_eq_self
theorem diagonal_updateColumn_single [DecidableEq n] [Zero α] (v : n → α) (i : n) (x : α) :
(diagonal v).updateColumn i (Pi.single i x) = diagonal (Function.update v i x) := by
ext j k
obtain rfl | hjk := eq_or_ne j k
· rw [diagonal_apply_eq]
obtain rfl | hji := eq_or_ne j i
· rw [updateColumn_self, Pi.single_eq_same, Function.update_same]
· rw [updateColumn_ne hji, diagonal_apply_eq, Function.update_noteq hji]
· rw [diagonal_apply_ne _ hjk]
obtain rfl | hki := eq_or_ne k i
· rw [updateColumn_self, Pi.single_eq_of_ne hjk]
· rw [updateColumn_ne hki, diagonal_apply_ne _ hjk]
#align matrix.diagonal_update_column_single Matrix.diagonal_updateColumn_single
theorem diagonal_updateRow_single [DecidableEq n] [Zero α] (v : n → α) (i : n) (x : α) :
(diagonal v).updateRow i (Pi.single i x) = diagonal (Function.update v i x) := by
rw [← diagonal_transpose, updateRow_transpose, diagonal_updateColumn_single, diagonal_transpose]
#align matrix.diagonal_update_row_single Matrix.diagonal_updateRow_single
/-! Updating rows and columns commutes in the obvious way with reindexing the matrix. -/
| Mathlib/Data/Matrix/RowCol.lean | 301 | 305 | theorem updateRow_submatrix_equiv [DecidableEq l] [DecidableEq m] (A : Matrix m n α) (i : l)
(r : o → α) (e : l ≃ m) (f : o ≃ n) :
updateRow (A.submatrix e f) i r = (A.updateRow (e i) fun j => r (f.symm j)).submatrix e f := by |
ext i' j
simp only [submatrix_apply, updateRow_apply, Equiv.apply_eq_iff_eq, Equiv.symm_apply_apply]
|
/-
Copyright (c) 2020 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Alex Meiburg
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.Polynomial.Degree.Lemmas
#align_import data.polynomial.erase_lead from "leanprover-community/mathlib"@"fa256f00ce018e7b40e1dc756e403c86680bf448"
/-!
# Erase the leading term of a univariate polynomial
## Definition
* `eraseLead f`: the polynomial `f - leading term of f`
`eraseLead` serves as reduction step in an induction, shaving off one monomial from a polynomial.
The definition is set up so that it does not mention subtraction in the definition,
and thus works for polynomials over semirings as well as rings.
-/
noncomputable section
open Polynomial
open Polynomial Finset
namespace Polynomial
variable {R : Type*} [Semiring R] {f : R[X]}
/-- `eraseLead f` for a polynomial `f` is the polynomial obtained by
subtracting from `f` the leading term of `f`. -/
def eraseLead (f : R[X]) : R[X] :=
Polynomial.erase f.natDegree f
#align polynomial.erase_lead Polynomial.eraseLead
section EraseLead
theorem eraseLead_support (f : R[X]) : f.eraseLead.support = f.support.erase f.natDegree := by
simp only [eraseLead, support_erase]
#align polynomial.erase_lead_support Polynomial.eraseLead_support
theorem eraseLead_coeff (i : ℕ) :
f.eraseLead.coeff i = if i = f.natDegree then 0 else f.coeff i := by
simp only [eraseLead, coeff_erase]
#align polynomial.erase_lead_coeff Polynomial.eraseLead_coeff
@[simp]
theorem eraseLead_coeff_natDegree : f.eraseLead.coeff f.natDegree = 0 := by simp [eraseLead_coeff]
#align polynomial.erase_lead_coeff_nat_degree Polynomial.eraseLead_coeff_natDegree
theorem eraseLead_coeff_of_ne (i : ℕ) (hi : i ≠ f.natDegree) : f.eraseLead.coeff i = f.coeff i := by
simp [eraseLead_coeff, hi]
#align polynomial.erase_lead_coeff_of_ne Polynomial.eraseLead_coeff_of_ne
@[simp]
theorem eraseLead_zero : eraseLead (0 : R[X]) = 0 := by simp only [eraseLead, erase_zero]
#align polynomial.erase_lead_zero Polynomial.eraseLead_zero
@[simp]
theorem eraseLead_add_monomial_natDegree_leadingCoeff (f : R[X]) :
f.eraseLead + monomial f.natDegree f.leadingCoeff = f :=
(add_comm _ _).trans (f.monomial_add_erase _)
#align polynomial.erase_lead_add_monomial_nat_degree_leading_coeff Polynomial.eraseLead_add_monomial_natDegree_leadingCoeff
@[simp]
theorem eraseLead_add_C_mul_X_pow (f : R[X]) :
f.eraseLead + C f.leadingCoeff * X ^ f.natDegree = f := by
rw [C_mul_X_pow_eq_monomial, eraseLead_add_monomial_natDegree_leadingCoeff]
set_option linter.uppercaseLean3 false in
#align polynomial.erase_lead_add_C_mul_X_pow Polynomial.eraseLead_add_C_mul_X_pow
@[simp]
theorem self_sub_monomial_natDegree_leadingCoeff {R : Type*} [Ring R] (f : R[X]) :
f - monomial f.natDegree f.leadingCoeff = f.eraseLead :=
(eq_sub_iff_add_eq.mpr (eraseLead_add_monomial_natDegree_leadingCoeff f)).symm
#align polynomial.self_sub_monomial_nat_degree_leading_coeff Polynomial.self_sub_monomial_natDegree_leadingCoeff
@[simp]
theorem self_sub_C_mul_X_pow {R : Type*} [Ring R] (f : R[X]) :
f - C f.leadingCoeff * X ^ f.natDegree = f.eraseLead := by
rw [C_mul_X_pow_eq_monomial, self_sub_monomial_natDegree_leadingCoeff]
set_option linter.uppercaseLean3 false in
#align polynomial.self_sub_C_mul_X_pow Polynomial.self_sub_C_mul_X_pow
theorem eraseLead_ne_zero (f0 : 2 ≤ f.support.card) : eraseLead f ≠ 0 := by
rw [Ne, ← card_support_eq_zero, eraseLead_support]
exact
(zero_lt_one.trans_le <| (tsub_le_tsub_right f0 1).trans Finset.pred_card_le_card_erase).ne.symm
#align polynomial.erase_lead_ne_zero Polynomial.eraseLead_ne_zero
theorem lt_natDegree_of_mem_eraseLead_support {a : ℕ} (h : a ∈ (eraseLead f).support) :
a < f.natDegree := by
rw [eraseLead_support, mem_erase] at h
exact (le_natDegree_of_mem_supp a h.2).lt_of_ne h.1
#align polynomial.lt_nat_degree_of_mem_erase_lead_support Polynomial.lt_natDegree_of_mem_eraseLead_support
theorem ne_natDegree_of_mem_eraseLead_support {a : ℕ} (h : a ∈ (eraseLead f).support) :
a ≠ f.natDegree :=
(lt_natDegree_of_mem_eraseLead_support h).ne
#align polynomial.ne_nat_degree_of_mem_erase_lead_support Polynomial.ne_natDegree_of_mem_eraseLead_support
theorem natDegree_not_mem_eraseLead_support : f.natDegree ∉ (eraseLead f).support := fun h =>
ne_natDegree_of_mem_eraseLead_support h rfl
#align polynomial.nat_degree_not_mem_erase_lead_support Polynomial.natDegree_not_mem_eraseLead_support
theorem eraseLead_support_card_lt (h : f ≠ 0) : (eraseLead f).support.card < f.support.card := by
rw [eraseLead_support]
exact card_lt_card (erase_ssubset <| natDegree_mem_support_of_nonzero h)
#align polynomial.erase_lead_support_card_lt Polynomial.eraseLead_support_card_lt
theorem card_support_eraseLead_add_one (h : f ≠ 0) :
f.eraseLead.support.card + 1 = f.support.card := by
set c := f.support.card with hc
cases h₁ : c
case zero =>
by_contra
exact h (card_support_eq_zero.mp h₁)
case succ =>
rw [eraseLead_support, card_erase_of_mem (natDegree_mem_support_of_nonzero h), ← hc, h₁]
rfl
@[simp]
theorem card_support_eraseLead : f.eraseLead.support.card = f.support.card - 1 := by
by_cases hf : f = 0
· rw [hf, eraseLead_zero, support_zero, card_empty]
· rw [← card_support_eraseLead_add_one hf, add_tsub_cancel_right]
theorem card_support_eraseLead' {c : ℕ} (fc : f.support.card = c + 1) :
f.eraseLead.support.card = c := by
rw [card_support_eraseLead, fc, add_tsub_cancel_right]
#align polynomial.erase_lead_card_support' Polynomial.card_support_eraseLead'
theorem card_support_eq_one_of_eraseLead_eq_zero (h₀ : f ≠ 0) (h₁ : f.eraseLead = 0) :
f.support.card = 1 :=
(card_support_eq_zero.mpr h₁ ▸ card_support_eraseLead_add_one h₀).symm
theorem card_support_le_one_of_eraseLead_eq_zero (h : f.eraseLead = 0) : f.support.card ≤ 1 := by
by_cases hpz : f = 0
case pos => simp [hpz]
case neg => exact le_of_eq (card_support_eq_one_of_eraseLead_eq_zero hpz h)
@[simp]
theorem eraseLead_monomial (i : ℕ) (r : R) : eraseLead (monomial i r) = 0 := by
classical
by_cases hr : r = 0
· subst r
simp only [monomial_zero_right, eraseLead_zero]
· rw [eraseLead, natDegree_monomial, if_neg hr, erase_monomial]
#align polynomial.erase_lead_monomial Polynomial.eraseLead_monomial
@[simp]
theorem eraseLead_C (r : R) : eraseLead (C r) = 0 :=
eraseLead_monomial _ _
set_option linter.uppercaseLean3 false in
#align polynomial.erase_lead_C Polynomial.eraseLead_C
@[simp]
theorem eraseLead_X : eraseLead (X : R[X]) = 0 :=
eraseLead_monomial _ _
set_option linter.uppercaseLean3 false in
#align polynomial.erase_lead_X Polynomial.eraseLead_X
@[simp]
theorem eraseLead_X_pow (n : ℕ) : eraseLead (X ^ n : R[X]) = 0 := by
rw [X_pow_eq_monomial, eraseLead_monomial]
set_option linter.uppercaseLean3 false in
#align polynomial.erase_lead_X_pow Polynomial.eraseLead_X_pow
@[simp]
theorem eraseLead_C_mul_X_pow (r : R) (n : ℕ) : eraseLead (C r * X ^ n) = 0 := by
rw [C_mul_X_pow_eq_monomial, eraseLead_monomial]
set_option linter.uppercaseLean3 false in
#align polynomial.erase_lead_C_mul_X_pow Polynomial.eraseLead_C_mul_X_pow
@[simp] lemma eraseLead_C_mul_X (r : R) : eraseLead (C r * X) = 0 := by
simpa using eraseLead_C_mul_X_pow _ 1
theorem eraseLead_add_of_natDegree_lt_left {p q : R[X]} (pq : q.natDegree < p.natDegree) :
(p + q).eraseLead = p.eraseLead + q := by
ext n
by_cases nd : n = p.natDegree
· rw [nd, eraseLead_coeff, if_pos (natDegree_add_eq_left_of_natDegree_lt pq).symm]
simpa using (coeff_eq_zero_of_natDegree_lt pq).symm
· rw [eraseLead_coeff, coeff_add, coeff_add, eraseLead_coeff, if_neg, if_neg nd]
rintro rfl
exact nd (natDegree_add_eq_left_of_natDegree_lt pq)
#align polynomial.erase_lead_add_of_nat_degree_lt_left Polynomial.eraseLead_add_of_natDegree_lt_left
theorem eraseLead_add_of_natDegree_lt_right {p q : R[X]} (pq : p.natDegree < q.natDegree) :
(p + q).eraseLead = p + q.eraseLead := by
ext n
by_cases nd : n = q.natDegree
· rw [nd, eraseLead_coeff, if_pos (natDegree_add_eq_right_of_natDegree_lt pq).symm]
simpa using (coeff_eq_zero_of_natDegree_lt pq).symm
· rw [eraseLead_coeff, coeff_add, coeff_add, eraseLead_coeff, if_neg, if_neg nd]
rintro rfl
exact nd (natDegree_add_eq_right_of_natDegree_lt pq)
#align polynomial.erase_lead_add_of_nat_degree_lt_right Polynomial.eraseLead_add_of_natDegree_lt_right
theorem eraseLead_degree_le : (eraseLead f).degree ≤ f.degree :=
f.degree_erase_le _
#align polynomial.erase_lead_degree_le Polynomial.eraseLead_degree_le
theorem eraseLead_natDegree_le_aux : (eraseLead f).natDegree ≤ f.natDegree :=
natDegree_le_natDegree eraseLead_degree_le
#align polynomial.erase_lead_nat_degree_le_aux Polynomial.eraseLead_natDegree_le_aux
theorem eraseLead_natDegree_lt (f0 : 2 ≤ f.support.card) : (eraseLead f).natDegree < f.natDegree :=
lt_of_le_of_ne eraseLead_natDegree_le_aux <|
ne_natDegree_of_mem_eraseLead_support <|
natDegree_mem_support_of_nonzero <| eraseLead_ne_zero f0
#align polynomial.erase_lead_nat_degree_lt Polynomial.eraseLead_natDegree_lt
| Mathlib/Algebra/Polynomial/EraseLead.lean | 218 | 221 | theorem natDegree_pos_of_eraseLead_ne_zero (h : f.eraseLead ≠ 0) : 0 < f.natDegree := by |
by_contra h₂
rw [eq_C_of_natDegree_eq_zero (Nat.eq_zero_of_not_pos h₂)] at h
simp at h
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker, Johan Commelin
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.BigOperators
import Mathlib.Algebra.Polynomial.Degree.Lemmas
import Mathlib.Algebra.Polynomial.Div
#align_import data.polynomial.ring_division from "leanprover-community/mathlib"@"8efcf8022aac8e01df8d302dcebdbc25d6a886c8"
/-!
# Theory of univariate polynomials
We prove basic results about univariate polynomials.
-/
noncomputable section
open Polynomial
open Finset
namespace Polynomial
universe u v w z
variable {R : Type u} {S : Type v} {T : Type w} {a b : R} {n : ℕ}
section CommRing
variable [CommRing R] {p q : R[X]}
section
variable [Semiring S]
theorem natDegree_pos_of_aeval_root [Algebra R S] {p : R[X]} (hp : p ≠ 0) {z : S}
(hz : aeval z p = 0) (inj : ∀ x : R, algebraMap R S x = 0 → x = 0) : 0 < p.natDegree :=
natDegree_pos_of_eval₂_root hp (algebraMap R S) hz inj
#align polynomial.nat_degree_pos_of_aeval_root Polynomial.natDegree_pos_of_aeval_root
theorem degree_pos_of_aeval_root [Algebra R S] {p : R[X]} (hp : p ≠ 0) {z : S} (hz : aeval z p = 0)
(inj : ∀ x : R, algebraMap R S x = 0 → x = 0) : 0 < p.degree :=
natDegree_pos_iff_degree_pos.mp (natDegree_pos_of_aeval_root hp hz inj)
#align polynomial.degree_pos_of_aeval_root Polynomial.degree_pos_of_aeval_root
theorem modByMonic_eq_of_dvd_sub (hq : q.Monic) {p₁ p₂ : R[X]} (h : q ∣ p₁ - p₂) :
p₁ %ₘ q = p₂ %ₘ q := by
nontriviality R
obtain ⟨f, sub_eq⟩ := h
refine (div_modByMonic_unique (p₂ /ₘ q + f) _ hq ⟨?_, degree_modByMonic_lt _ hq⟩).2
rw [sub_eq_iff_eq_add.mp sub_eq, mul_add, ← add_assoc, modByMonic_add_div _ hq, add_comm]
#align polynomial.mod_by_monic_eq_of_dvd_sub Polynomial.modByMonic_eq_of_dvd_sub
theorem add_modByMonic (p₁ p₂ : R[X]) : (p₁ + p₂) %ₘ q = p₁ %ₘ q + p₂ %ₘ q := by
by_cases hq : q.Monic
· cases' subsingleton_or_nontrivial R with hR hR
· simp only [eq_iff_true_of_subsingleton]
· exact
(div_modByMonic_unique (p₁ /ₘ q + p₂ /ₘ q) _ hq
⟨by
rw [mul_add, add_left_comm, add_assoc, modByMonic_add_div _ hq, ← add_assoc,
add_comm (q * _), modByMonic_add_div _ hq],
(degree_add_le _ _).trans_lt
(max_lt (degree_modByMonic_lt _ hq) (degree_modByMonic_lt _ hq))⟩).2
· simp_rw [modByMonic_eq_of_not_monic _ hq]
#align polynomial.add_mod_by_monic Polynomial.add_modByMonic
theorem smul_modByMonic (c : R) (p : R[X]) : c • p %ₘ q = c • (p %ₘ q) := by
by_cases hq : q.Monic
· cases' subsingleton_or_nontrivial R with hR hR
· simp only [eq_iff_true_of_subsingleton]
· exact
(div_modByMonic_unique (c • (p /ₘ q)) (c • (p %ₘ q)) hq
⟨by rw [mul_smul_comm, ← smul_add, modByMonic_add_div p hq],
(degree_smul_le _ _).trans_lt (degree_modByMonic_lt _ hq)⟩).2
· simp_rw [modByMonic_eq_of_not_monic _ hq]
#align polynomial.smul_mod_by_monic Polynomial.smul_modByMonic
/-- `_ %ₘ q` as an `R`-linear map. -/
@[simps]
def modByMonicHom (q : R[X]) : R[X] →ₗ[R] R[X] where
toFun p := p %ₘ q
map_add' := add_modByMonic
map_smul' := smul_modByMonic
#align polynomial.mod_by_monic_hom Polynomial.modByMonicHom
theorem neg_modByMonic (p mod : R[X]) : (-p) %ₘ mod = - (p %ₘ mod) :=
(modByMonicHom mod).map_neg p
theorem sub_modByMonic (a b mod : R[X]) : (a - b) %ₘ mod = a %ₘ mod - b %ₘ mod :=
(modByMonicHom mod).map_sub a b
end
section
variable [Ring S]
theorem aeval_modByMonic_eq_self_of_root [Algebra R S] {p q : R[X]} (hq : q.Monic) {x : S}
(hx : aeval x q = 0) : aeval x (p %ₘ q) = aeval x p := by
--`eval₂_modByMonic_eq_self_of_root` doesn't work here as it needs commutativity
rw [modByMonic_eq_sub_mul_div p hq, _root_.map_sub, _root_.map_mul, hx, zero_mul,
sub_zero]
#align polynomial.aeval_mod_by_monic_eq_self_of_root Polynomial.aeval_modByMonic_eq_self_of_root
end
end CommRing
section NoZeroDivisors
variable [Semiring R] [NoZeroDivisors R] {p q : R[X]}
instance : NoZeroDivisors R[X] where
eq_zero_or_eq_zero_of_mul_eq_zero h := by
rw [← leadingCoeff_eq_zero, ← leadingCoeff_eq_zero]
refine eq_zero_or_eq_zero_of_mul_eq_zero ?_
rw [← leadingCoeff_zero, ← leadingCoeff_mul, h]
theorem natDegree_mul (hp : p ≠ 0) (hq : q ≠ 0) : (p*q).natDegree = p.natDegree + q.natDegree := by
rw [← Nat.cast_inj (R := WithBot ℕ), ← degree_eq_natDegree (mul_ne_zero hp hq),
Nat.cast_add, ← degree_eq_natDegree hp, ← degree_eq_natDegree hq, degree_mul]
#align polynomial.nat_degree_mul Polynomial.natDegree_mul
theorem trailingDegree_mul : (p * q).trailingDegree = p.trailingDegree + q.trailingDegree := by
by_cases hp : p = 0
· rw [hp, zero_mul, trailingDegree_zero, top_add]
by_cases hq : q = 0
· rw [hq, mul_zero, trailingDegree_zero, add_top]
· rw [trailingDegree_eq_natTrailingDegree hp, trailingDegree_eq_natTrailingDegree hq,
trailingDegree_eq_natTrailingDegree (mul_ne_zero hp hq), natTrailingDegree_mul hp hq]
apply WithTop.coe_add
#align polynomial.trailing_degree_mul Polynomial.trailingDegree_mul
@[simp]
| Mathlib/Algebra/Polynomial/RingDivision.lean | 140 | 145 | theorem natDegree_pow (p : R[X]) (n : ℕ) : natDegree (p ^ n) = n * natDegree p := by |
classical
obtain rfl | hp := eq_or_ne p 0
· obtain rfl | hn := eq_or_ne n 0 <;> simp [*]
exact natDegree_pow' $ by
rw [← leadingCoeff_pow, Ne, leadingCoeff_eq_zero]; exact pow_ne_zero _ hp
|
/-
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.Algebra.ModEq
import Mathlib.Algebra.Module.Defs
import Mathlib.Algebra.Order.Archimedean
import Mathlib.Algebra.Periodic
import Mathlib.Data.Int.SuccPred
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.Order.Circular
import Mathlib.Data.List.TFAE
import Mathlib.Data.Set.Lattice
#align_import algebra.order.to_interval_mod from "leanprover-community/mathlib"@"213b0cff7bc5ab6696ee07cceec80829ce42efec"
/-!
# Reducing to an interval modulo its length
This file defines operations that reduce a number (in an `Archimedean`
`LinearOrderedAddCommGroup`) to a number in a given interval, modulo the length of that
interval.
## Main definitions
* `toIcoDiv hp a b` (where `hp : 0 < p`): The unique integer such that this multiple of `p`,
subtracted from `b`, is in `Ico a (a + p)`.
* `toIcoMod hp a b` (where `hp : 0 < p`): Reduce `b` to the interval `Ico a (a + p)`.
* `toIocDiv hp a b` (where `hp : 0 < p`): The unique integer such that this multiple of `p`,
subtracted from `b`, is in `Ioc a (a + p)`.
* `toIocMod hp a b` (where `hp : 0 < p`): Reduce `b` to the interval `Ioc a (a + p)`.
-/
noncomputable section
section LinearOrderedAddCommGroup
variable {α : Type*} [LinearOrderedAddCommGroup α] [hα : Archimedean α] {p : α} (hp : 0 < p)
{a b c : α} {n : ℤ}
/--
The unique integer such that this multiple of `p`, subtracted from `b`, is in `Ico a (a + p)`. -/
def toIcoDiv (a b : α) : ℤ :=
(existsUnique_sub_zsmul_mem_Ico hp b a).choose
#align to_Ico_div toIcoDiv
theorem sub_toIcoDiv_zsmul_mem_Ico (a b : α) : b - toIcoDiv hp a b • p ∈ Set.Ico a (a + p) :=
(existsUnique_sub_zsmul_mem_Ico hp b a).choose_spec.1
#align sub_to_Ico_div_zsmul_mem_Ico sub_toIcoDiv_zsmul_mem_Ico
theorem toIcoDiv_eq_of_sub_zsmul_mem_Ico (h : b - n • p ∈ Set.Ico a (a + p)) :
toIcoDiv hp a b = n :=
((existsUnique_sub_zsmul_mem_Ico hp b a).choose_spec.2 _ h).symm
#align to_Ico_div_eq_of_sub_zsmul_mem_Ico toIcoDiv_eq_of_sub_zsmul_mem_Ico
/--
The unique integer such that this multiple of `p`, subtracted from `b`, is in `Ioc a (a + p)`. -/
def toIocDiv (a b : α) : ℤ :=
(existsUnique_sub_zsmul_mem_Ioc hp b a).choose
#align to_Ioc_div toIocDiv
theorem sub_toIocDiv_zsmul_mem_Ioc (a b : α) : b - toIocDiv hp a b • p ∈ Set.Ioc a (a + p) :=
(existsUnique_sub_zsmul_mem_Ioc hp b a).choose_spec.1
#align sub_to_Ioc_div_zsmul_mem_Ioc sub_toIocDiv_zsmul_mem_Ioc
theorem toIocDiv_eq_of_sub_zsmul_mem_Ioc (h : b - n • p ∈ Set.Ioc a (a + p)) :
toIocDiv hp a b = n :=
((existsUnique_sub_zsmul_mem_Ioc hp b a).choose_spec.2 _ h).symm
#align to_Ioc_div_eq_of_sub_zsmul_mem_Ioc toIocDiv_eq_of_sub_zsmul_mem_Ioc
/-- Reduce `b` to the interval `Ico a (a + p)`. -/
def toIcoMod (a b : α) : α :=
b - toIcoDiv hp a b • p
#align to_Ico_mod toIcoMod
/-- Reduce `b` to the interval `Ioc a (a + p)`. -/
def toIocMod (a b : α) : α :=
b - toIocDiv hp a b • p
#align to_Ioc_mod toIocMod
theorem toIcoMod_mem_Ico (a b : α) : toIcoMod hp a b ∈ Set.Ico a (a + p) :=
sub_toIcoDiv_zsmul_mem_Ico hp a b
#align to_Ico_mod_mem_Ico toIcoMod_mem_Ico
theorem toIcoMod_mem_Ico' (b : α) : toIcoMod hp 0 b ∈ Set.Ico 0 p := by
convert toIcoMod_mem_Ico hp 0 b
exact (zero_add p).symm
#align to_Ico_mod_mem_Ico' toIcoMod_mem_Ico'
theorem toIocMod_mem_Ioc (a b : α) : toIocMod hp a b ∈ Set.Ioc a (a + p) :=
sub_toIocDiv_zsmul_mem_Ioc hp a b
#align to_Ioc_mod_mem_Ioc toIocMod_mem_Ioc
theorem left_le_toIcoMod (a b : α) : a ≤ toIcoMod hp a b :=
(Set.mem_Ico.1 (toIcoMod_mem_Ico hp a b)).1
#align left_le_to_Ico_mod left_le_toIcoMod
theorem left_lt_toIocMod (a b : α) : a < toIocMod hp a b :=
(Set.mem_Ioc.1 (toIocMod_mem_Ioc hp a b)).1
#align left_lt_to_Ioc_mod left_lt_toIocMod
theorem toIcoMod_lt_right (a b : α) : toIcoMod hp a b < a + p :=
(Set.mem_Ico.1 (toIcoMod_mem_Ico hp a b)).2
#align to_Ico_mod_lt_right toIcoMod_lt_right
theorem toIocMod_le_right (a b : α) : toIocMod hp a b ≤ a + p :=
(Set.mem_Ioc.1 (toIocMod_mem_Ioc hp a b)).2
#align to_Ioc_mod_le_right toIocMod_le_right
@[simp]
theorem self_sub_toIcoDiv_zsmul (a b : α) : b - toIcoDiv hp a b • p = toIcoMod hp a b :=
rfl
#align self_sub_to_Ico_div_zsmul self_sub_toIcoDiv_zsmul
@[simp]
theorem self_sub_toIocDiv_zsmul (a b : α) : b - toIocDiv hp a b • p = toIocMod hp a b :=
rfl
#align self_sub_to_Ioc_div_zsmul self_sub_toIocDiv_zsmul
@[simp]
theorem toIcoDiv_zsmul_sub_self (a b : α) : toIcoDiv hp a b • p - b = -toIcoMod hp a b := by
rw [toIcoMod, neg_sub]
#align to_Ico_div_zsmul_sub_self toIcoDiv_zsmul_sub_self
@[simp]
theorem toIocDiv_zsmul_sub_self (a b : α) : toIocDiv hp a b • p - b = -toIocMod hp a b := by
rw [toIocMod, neg_sub]
#align to_Ioc_div_zsmul_sub_self toIocDiv_zsmul_sub_self
@[simp]
theorem toIcoMod_sub_self (a b : α) : toIcoMod hp a b - b = -toIcoDiv hp a b • p := by
rw [toIcoMod, sub_sub_cancel_left, neg_smul]
#align to_Ico_mod_sub_self toIcoMod_sub_self
@[simp]
theorem toIocMod_sub_self (a b : α) : toIocMod hp a b - b = -toIocDiv hp a b • p := by
rw [toIocMod, sub_sub_cancel_left, neg_smul]
#align to_Ioc_mod_sub_self toIocMod_sub_self
@[simp]
theorem self_sub_toIcoMod (a b : α) : b - toIcoMod hp a b = toIcoDiv hp a b • p := by
rw [toIcoMod, sub_sub_cancel]
#align self_sub_to_Ico_mod self_sub_toIcoMod
@[simp]
theorem self_sub_toIocMod (a b : α) : b - toIocMod hp a b = toIocDiv hp a b • p := by
rw [toIocMod, sub_sub_cancel]
#align self_sub_to_Ioc_mod self_sub_toIocMod
@[simp]
theorem toIcoMod_add_toIcoDiv_zsmul (a b : α) : toIcoMod hp a b + toIcoDiv hp a b • p = b := by
rw [toIcoMod, sub_add_cancel]
#align to_Ico_mod_add_to_Ico_div_zsmul toIcoMod_add_toIcoDiv_zsmul
@[simp]
theorem toIocMod_add_toIocDiv_zsmul (a b : α) : toIocMod hp a b + toIocDiv hp a b • p = b := by
rw [toIocMod, sub_add_cancel]
#align to_Ioc_mod_add_to_Ioc_div_zsmul toIocMod_add_toIocDiv_zsmul
@[simp]
theorem toIcoDiv_zsmul_sub_toIcoMod (a b : α) : toIcoDiv hp a b • p + toIcoMod hp a b = b := by
rw [add_comm, toIcoMod_add_toIcoDiv_zsmul]
#align to_Ico_div_zsmul_sub_to_Ico_mod toIcoDiv_zsmul_sub_toIcoMod
@[simp]
theorem toIocDiv_zsmul_sub_toIocMod (a b : α) : toIocDiv hp a b • p + toIocMod hp a b = b := by
rw [add_comm, toIocMod_add_toIocDiv_zsmul]
#align to_Ioc_div_zsmul_sub_to_Ioc_mod toIocDiv_zsmul_sub_toIocMod
theorem toIcoMod_eq_iff : toIcoMod hp a b = c ↔ c ∈ Set.Ico a (a + p) ∧ ∃ z : ℤ, b = c + z • p := by
refine
⟨fun h =>
⟨h ▸ toIcoMod_mem_Ico hp a b, toIcoDiv hp a b, h ▸ (toIcoMod_add_toIcoDiv_zsmul _ _ _).symm⟩,
?_⟩
simp_rw [← @sub_eq_iff_eq_add]
rintro ⟨hc, n, rfl⟩
rw [← toIcoDiv_eq_of_sub_zsmul_mem_Ico hp hc, toIcoMod]
#align to_Ico_mod_eq_iff toIcoMod_eq_iff
theorem toIocMod_eq_iff : toIocMod hp a b = c ↔ c ∈ Set.Ioc a (a + p) ∧ ∃ z : ℤ, b = c + z • p := by
refine
⟨fun h =>
⟨h ▸ toIocMod_mem_Ioc hp a b, toIocDiv hp a b, h ▸ (toIocMod_add_toIocDiv_zsmul hp _ _).symm⟩,
?_⟩
simp_rw [← @sub_eq_iff_eq_add]
rintro ⟨hc, n, rfl⟩
rw [← toIocDiv_eq_of_sub_zsmul_mem_Ioc hp hc, toIocMod]
#align to_Ioc_mod_eq_iff toIocMod_eq_iff
@[simp]
theorem toIcoDiv_apply_left (a : α) : toIcoDiv hp a a = 0 :=
toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by simp [hp]
#align to_Ico_div_apply_left toIcoDiv_apply_left
@[simp]
theorem toIocDiv_apply_left (a : α) : toIocDiv hp a a = -1 :=
toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by simp [hp]
#align to_Ioc_div_apply_left toIocDiv_apply_left
@[simp]
theorem toIcoMod_apply_left (a : α) : toIcoMod hp a a = a := by
rw [toIcoMod_eq_iff hp, Set.left_mem_Ico]
exact ⟨lt_add_of_pos_right _ hp, 0, by simp⟩
#align to_Ico_mod_apply_left toIcoMod_apply_left
@[simp]
theorem toIocMod_apply_left (a : α) : toIocMod hp a a = a + p := by
rw [toIocMod_eq_iff hp, Set.right_mem_Ioc]
exact ⟨lt_add_of_pos_right _ hp, -1, by simp⟩
#align to_Ioc_mod_apply_left toIocMod_apply_left
theorem toIcoDiv_apply_right (a : α) : toIcoDiv hp a (a + p) = 1 :=
toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by simp [hp]
#align to_Ico_div_apply_right toIcoDiv_apply_right
theorem toIocDiv_apply_right (a : α) : toIocDiv hp a (a + p) = 0 :=
toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by simp [hp]
#align to_Ioc_div_apply_right toIocDiv_apply_right
theorem toIcoMod_apply_right (a : α) : toIcoMod hp a (a + p) = a := by
rw [toIcoMod_eq_iff hp, Set.left_mem_Ico]
exact ⟨lt_add_of_pos_right _ hp, 1, by simp⟩
#align to_Ico_mod_apply_right toIcoMod_apply_right
theorem toIocMod_apply_right (a : α) : toIocMod hp a (a + p) = a + p := by
rw [toIocMod_eq_iff hp, Set.right_mem_Ioc]
exact ⟨lt_add_of_pos_right _ hp, 0, by simp⟩
#align to_Ioc_mod_apply_right toIocMod_apply_right
@[simp]
theorem toIcoDiv_add_zsmul (a b : α) (m : ℤ) : toIcoDiv hp a (b + m • p) = toIcoDiv hp a b + m :=
toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by
simpa only [add_smul, add_sub_add_right_eq_sub] using sub_toIcoDiv_zsmul_mem_Ico hp a b
#align to_Ico_div_add_zsmul toIcoDiv_add_zsmul
@[simp]
theorem toIcoDiv_add_zsmul' (a b : α) (m : ℤ) :
toIcoDiv hp (a + m • p) b = toIcoDiv hp a b - m := by
refine toIcoDiv_eq_of_sub_zsmul_mem_Ico _ ?_
rw [sub_smul, ← sub_add, add_right_comm]
simpa using sub_toIcoDiv_zsmul_mem_Ico hp a b
#align to_Ico_div_add_zsmul' toIcoDiv_add_zsmul'
@[simp]
theorem toIocDiv_add_zsmul (a b : α) (m : ℤ) : toIocDiv hp a (b + m • p) = toIocDiv hp a b + m :=
toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by
simpa only [add_smul, add_sub_add_right_eq_sub] using sub_toIocDiv_zsmul_mem_Ioc hp a b
#align to_Ioc_div_add_zsmul toIocDiv_add_zsmul
@[simp]
theorem toIocDiv_add_zsmul' (a b : α) (m : ℤ) :
toIocDiv hp (a + m • p) b = toIocDiv hp a b - m := by
refine toIocDiv_eq_of_sub_zsmul_mem_Ioc _ ?_
rw [sub_smul, ← sub_add, add_right_comm]
simpa using sub_toIocDiv_zsmul_mem_Ioc hp a b
#align to_Ioc_div_add_zsmul' toIocDiv_add_zsmul'
@[simp]
theorem toIcoDiv_zsmul_add (a b : α) (m : ℤ) : toIcoDiv hp a (m • p + b) = m + toIcoDiv hp a b := by
rw [add_comm, toIcoDiv_add_zsmul, add_comm]
#align to_Ico_div_zsmul_add toIcoDiv_zsmul_add
/-! Note we omit `toIcoDiv_zsmul_add'` as `-m + toIcoDiv hp a b` is not very convenient. -/
@[simp]
theorem toIocDiv_zsmul_add (a b : α) (m : ℤ) : toIocDiv hp a (m • p + b) = m + toIocDiv hp a b := by
rw [add_comm, toIocDiv_add_zsmul, add_comm]
#align to_Ioc_div_zsmul_add toIocDiv_zsmul_add
/-! Note we omit `toIocDiv_zsmul_add'` as `-m + toIocDiv hp a b` is not very convenient. -/
@[simp]
theorem toIcoDiv_sub_zsmul (a b : α) (m : ℤ) : toIcoDiv hp a (b - m • p) = toIcoDiv hp a b - m := by
rw [sub_eq_add_neg, ← neg_smul, toIcoDiv_add_zsmul, sub_eq_add_neg]
#align to_Ico_div_sub_zsmul toIcoDiv_sub_zsmul
@[simp]
theorem toIcoDiv_sub_zsmul' (a b : α) (m : ℤ) :
toIcoDiv hp (a - m • p) b = toIcoDiv hp a b + m := by
rw [sub_eq_add_neg, ← neg_smul, toIcoDiv_add_zsmul', sub_neg_eq_add]
#align to_Ico_div_sub_zsmul' toIcoDiv_sub_zsmul'
@[simp]
theorem toIocDiv_sub_zsmul (a b : α) (m : ℤ) : toIocDiv hp a (b - m • p) = toIocDiv hp a b - m := by
rw [sub_eq_add_neg, ← neg_smul, toIocDiv_add_zsmul, sub_eq_add_neg]
#align to_Ioc_div_sub_zsmul toIocDiv_sub_zsmul
@[simp]
theorem toIocDiv_sub_zsmul' (a b : α) (m : ℤ) :
toIocDiv hp (a - m • p) b = toIocDiv hp a b + m := by
rw [sub_eq_add_neg, ← neg_smul, toIocDiv_add_zsmul', sub_neg_eq_add]
#align to_Ioc_div_sub_zsmul' toIocDiv_sub_zsmul'
@[simp]
theorem toIcoDiv_add_right (a b : α) : toIcoDiv hp a (b + p) = toIcoDiv hp a b + 1 := by
simpa only [one_zsmul] using toIcoDiv_add_zsmul hp a b 1
#align to_Ico_div_add_right toIcoDiv_add_right
@[simp]
| Mathlib/Algebra/Order/ToIntervalMod.lean | 304 | 305 | theorem toIcoDiv_add_right' (a b : α) : toIcoDiv hp (a + p) b = toIcoDiv hp a b - 1 := by |
simpa only [one_zsmul] using toIcoDiv_add_zsmul' hp a b 1
|
/-
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.Algebra.Order.Ring.WithTop
import Mathlib.Algebra.Order.Sub.WithTop
import Mathlib.Data.Real.NNReal
import Mathlib.Order.Interval.Set.WithBotTop
#align_import data.real.ennreal from "leanprover-community/mathlib"@"c14c8fcde993801fca8946b0d80131a1a81d1520"
/-!
# Extended non-negative reals
We define `ENNReal = ℝ≥0∞ := WithTop ℝ≥0` to be the type of extended nonnegative real numbers,
i.e., the interval `[0, +∞]`. This type is used as the codomain of a `MeasureTheory.Measure`,
and of the extended distance `edist` in an `EMetricSpace`.
In this file we set up many of the instances on `ℝ≥0∞`, and provide relationships between `ℝ≥0∞` and
`ℝ≥0`, and between `ℝ≥0∞` and `ℝ`. In particular, we provide a coercion from `ℝ≥0` to `ℝ≥0∞` as well
as functions `ENNReal.toNNReal`, `ENNReal.ofReal` and `ENNReal.toReal`, all of which take the value
zero wherever they cannot be the identity. Also included is the relationship between `ℝ≥0∞` and `ℕ`.
The interaction of these functions, especially `ENNReal.ofReal` and `ENNReal.toReal`, with the
algebraic and lattice structure can be found in `Data.ENNReal.Real`.
This file proves many of the order properties of `ℝ≥0∞`, with the exception of the ways those relate
to the algebraic structure, which are included in `Data.ENNReal.Operations`.
This file also defines inversion and division: this includes `Inv` and `Div` instances on `ℝ≥0∞`
making it into a `DivInvOneMonoid`.
As a consequence of being a `DivInvOneMonoid`, `ℝ≥0∞` inherits a power operation with integer
exponent: this and other properties is shown in `Data.ENNReal.Inv`.
## Main definitions
* `ℝ≥0∞`: the extended nonnegative real numbers `[0, ∞]`; defined as `WithTop ℝ≥0`; it is
equipped with the following structures:
- coercion from `ℝ≥0` defined in the natural way;
- the natural structure of a complete dense linear order: `↑p ≤ ↑q ↔ p ≤ q` and `∀ a, a ≤ ∞`;
- `a + b` is defined so that `↑p + ↑q = ↑(p + q)` for `(p q : ℝ≥0)` and `a + ∞ = ∞ + a = ∞`;
- `a * b` is defined so that `↑p * ↑q = ↑(p * q)` for `(p q : ℝ≥0)`, `0 * ∞ = ∞ * 0 = 0`, and
`a * ∞ = ∞ * a = ∞` for `a ≠ 0`;
- `a - b` is defined as the minimal `d` such that `a ≤ d + b`; this way we have
`↑p - ↑q = ↑(p - q)`, `∞ - ↑p = ∞`, `↑p - ∞ = ∞ - ∞ = 0`; note that there is no negation, only
subtraction;
The addition and multiplication defined this way together with `0 = ↑0` and `1 = ↑1` turn
`ℝ≥0∞` into a canonically ordered commutative semiring of characteristic zero.
- `a⁻¹` is defined as `Inf {b | 1 ≤ a * b}`. This way we have `(↑p)⁻¹ = ↑(p⁻¹)` for
`p : ℝ≥0`, `p ≠ 0`, `0⁻¹ = ∞`, and `∞⁻¹ = 0`.
- `a / b` is defined as `a * b⁻¹`.
This inversion and division include `Inv` and `Div` instances on `ℝ≥0∞`,
making it into a `DivInvOneMonoid`. Further properties of these are shown in `Data.ENNReal.Inv`.
* Coercions to/from other types:
- coercion `ℝ≥0 → ℝ≥0∞` is defined as `Coe`, so one can use `(p : ℝ≥0)` in a context that
expects `a : ℝ≥0∞`, and Lean will apply `coe` automatically;
- `ENNReal.toNNReal` sends `↑p` to `p` and `∞` to `0`;
- `ENNReal.toReal := coe ∘ ENNReal.toNNReal` sends `↑p`, `p : ℝ≥0` to `(↑p : ℝ)` and `∞` to `0`;
- `ENNReal.ofReal := coe ∘ Real.toNNReal` sends `x : ℝ` to `↑⟨max x 0, _⟩`
- `ENNReal.neTopEquivNNReal` is an equivalence between `{a : ℝ≥0∞ // a ≠ 0}` and `ℝ≥0`.
## Implementation notes
We define a `CanLift ℝ≥0∞ ℝ≥0` instance, so one of the ways to prove theorems about an `ℝ≥0∞`
number `a` is to consider the cases `a = ∞` and `a ≠ ∞`, and use the tactic `lift a to ℝ≥0 using ha`
in the second case. This instance is even more useful if one already has `ha : a ≠ ∞` in the
context, or if we have `(f : α → ℝ≥0∞) (hf : ∀ x, f x ≠ ∞)`.
## Notations
* `ℝ≥0∞`: the type of the extended nonnegative real numbers;
* `ℝ≥0`: the type of nonnegative real numbers `[0, ∞)`; defined in `Data.Real.NNReal`;
* `∞`: a localized notation in `ENNReal` for `⊤ : ℝ≥0∞`.
-/
open Function Set NNReal
variable {α : Type*}
/-- The extended nonnegative real numbers. This is usually denoted [0, ∞],
and is relevant as the codomain of a measure. -/
def ENNReal := WithTop ℝ≥0
deriving Zero, AddCommMonoidWithOne, SemilatticeSup, DistribLattice, Nontrivial
#align ennreal ENNReal
@[inherit_doc]
scoped[ENNReal] notation "ℝ≥0∞" => ENNReal
/-- Notation for infinity as an `ENNReal` number. -/
scoped[ENNReal] notation "∞" => (⊤ : ENNReal)
namespace ENNReal
instance : OrderBot ℝ≥0∞ := inferInstanceAs (OrderBot (WithTop ℝ≥0))
instance : BoundedOrder ℝ≥0∞ := inferInstanceAs (BoundedOrder (WithTop ℝ≥0))
instance : CharZero ℝ≥0∞ := inferInstanceAs (CharZero (WithTop ℝ≥0))
noncomputable instance : CanonicallyOrderedCommSemiring ℝ≥0∞ :=
inferInstanceAs (CanonicallyOrderedCommSemiring (WithTop ℝ≥0))
noncomputable instance : CompleteLinearOrder ℝ≥0∞ :=
inferInstanceAs (CompleteLinearOrder (WithTop ℝ≥0))
instance : DenselyOrdered ℝ≥0∞ := inferInstanceAs (DenselyOrdered (WithTop ℝ≥0))
noncomputable instance : CanonicallyLinearOrderedAddCommMonoid ℝ≥0∞ :=
inferInstanceAs (CanonicallyLinearOrderedAddCommMonoid (WithTop ℝ≥0))
noncomputable instance instSub : Sub ℝ≥0∞ := inferInstanceAs (Sub (WithTop ℝ≥0))
noncomputable instance : OrderedSub ℝ≥0∞ := inferInstanceAs (OrderedSub (WithTop ℝ≥0))
noncomputable instance : LinearOrderedAddCommMonoidWithTop ℝ≥0∞ :=
inferInstanceAs (LinearOrderedAddCommMonoidWithTop (WithTop ℝ≥0))
-- Porting note: rfc: redefine using pattern matching?
noncomputable instance : Inv ℝ≥0∞ := ⟨fun a => sInf { b | 1 ≤ a * b }⟩
noncomputable instance : DivInvMonoid ℝ≥0∞ where
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0}
-- Porting note: are these 2 instances still required in Lean 4?
instance covariantClass_mul_le : CovariantClass ℝ≥0∞ ℝ≥0∞ (· * ·) (· ≤ ·) := inferInstance
#align ennreal.covariant_class_mul_le ENNReal.covariantClass_mul_le
instance covariantClass_add_le : CovariantClass ℝ≥0∞ ℝ≥0∞ (· + ·) (· ≤ ·) := inferInstance
#align ennreal.covariant_class_add_le ENNReal.covariantClass_add_le
-- Porting note (#11215): TODO: add a `WithTop` instance and use it here
noncomputable instance : LinearOrderedCommMonoidWithZero ℝ≥0∞ :=
{ inferInstanceAs (LinearOrderedAddCommMonoidWithTop ℝ≥0∞),
inferInstanceAs (CommSemiring ℝ≥0∞) with
mul_le_mul_left := fun _ _ => mul_le_mul_left'
zero_le_one := zero_le 1 }
noncomputable instance : Unique (AddUnits ℝ≥0∞) where
default := 0
uniq a := AddUnits.ext <| le_zero_iff.1 <| by rw [← a.add_neg]; exact le_self_add
instance : Inhabited ℝ≥0∞ := ⟨0⟩
/-- Coercion from `ℝ≥0` to `ℝ≥0∞`. -/
@[coe, match_pattern] def ofNNReal : ℝ≥0 → ℝ≥0∞ := WithTop.some
instance : Coe ℝ≥0 ℝ≥0∞ := ⟨ofNNReal⟩
/-- A version of `WithTop.recTopCoe` that uses `ENNReal.ofNNReal`. -/
@[elab_as_elim, induction_eliminator, cases_eliminator]
def recTopCoe {C : ℝ≥0∞ → Sort*} (top : C ∞) (coe : ∀ x : ℝ≥0, C x) (x : ℝ≥0∞) : C x :=
WithTop.recTopCoe top coe x
instance canLift : CanLift ℝ≥0∞ ℝ≥0 ofNNReal (· ≠ ∞) := WithTop.canLift
#align ennreal.can_lift ENNReal.canLift
@[simp] theorem none_eq_top : (none : ℝ≥0∞) = ∞ := rfl
#align ennreal.none_eq_top ENNReal.none_eq_top
@[simp] theorem some_eq_coe (a : ℝ≥0) : (Option.some a : ℝ≥0∞) = (↑a : ℝ≥0∞) := rfl
#align ennreal.some_eq_coe ENNReal.some_eq_coe
@[simp] theorem some_eq_coe' (a : ℝ≥0) : (WithTop.some a : ℝ≥0∞) = (↑a : ℝ≥0∞) := rfl
lemma coe_injective : Injective ((↑) : ℝ≥0 → ℝ≥0∞) := WithTop.coe_injective
@[simp, norm_cast] lemma coe_inj : (p : ℝ≥0∞) = q ↔ p = q := coe_injective.eq_iff
#align ennreal.coe_eq_coe ENNReal.coe_inj
lemma coe_ne_coe : (p : ℝ≥0∞) ≠ q ↔ p ≠ q := coe_inj.not
theorem range_coe' : range ofNNReal = Iio ∞ := WithTop.range_coe
theorem range_coe : range ofNNReal = {∞}ᶜ := (isCompl_range_some_none ℝ≥0).symm.compl_eq.symm
/-- `toNNReal x` returns `x` if it is real, otherwise 0. -/
protected def toNNReal : ℝ≥0∞ → ℝ≥0 := WithTop.untop' 0
#align ennreal.to_nnreal ENNReal.toNNReal
/-- `toReal x` returns `x` if it is real, `0` otherwise. -/
protected def toReal (a : ℝ≥0∞) : Real := a.toNNReal
#align ennreal.to_real ENNReal.toReal
/-- `ofReal x` returns `x` if it is nonnegative, `0` otherwise. -/
protected noncomputable def ofReal (r : Real) : ℝ≥0∞ := r.toNNReal
#align ennreal.of_real ENNReal.ofReal
@[simp, norm_cast]
theorem toNNReal_coe : (r : ℝ≥0∞).toNNReal = r := rfl
#align ennreal.to_nnreal_coe ENNReal.toNNReal_coe
@[simp]
theorem coe_toNNReal : ∀ {a : ℝ≥0∞}, a ≠ ∞ → ↑a.toNNReal = a
| ofNNReal _, _ => rfl
| ⊤, h => (h rfl).elim
#align ennreal.coe_to_nnreal ENNReal.coe_toNNReal
@[simp]
theorem ofReal_toReal {a : ℝ≥0∞} (h : a ≠ ∞) : ENNReal.ofReal a.toReal = a := by
simp [ENNReal.toReal, ENNReal.ofReal, h]
#align ennreal.of_real_to_real ENNReal.ofReal_toReal
@[simp]
theorem toReal_ofReal {r : ℝ} (h : 0 ≤ r) : (ENNReal.ofReal r).toReal = r :=
max_eq_left h
#align ennreal.to_real_of_real ENNReal.toReal_ofReal
theorem toReal_ofReal' {r : ℝ} : (ENNReal.ofReal r).toReal = max r 0 := rfl
#align ennreal.to_real_of_real' ENNReal.toReal_ofReal'
theorem coe_toNNReal_le_self : ∀ {a : ℝ≥0∞}, ↑a.toNNReal ≤ a
| ofNNReal r => by rw [toNNReal_coe]
| ⊤ => le_top
#align ennreal.coe_to_nnreal_le_self ENNReal.coe_toNNReal_le_self
theorem coe_nnreal_eq (r : ℝ≥0) : (r : ℝ≥0∞) = ENNReal.ofReal r := by
rw [ENNReal.ofReal, Real.toNNReal_coe]
#align ennreal.coe_nnreal_eq ENNReal.coe_nnreal_eq
theorem ofReal_eq_coe_nnreal {x : ℝ} (h : 0 ≤ x) :
ENNReal.ofReal x = ofNNReal ⟨x, h⟩ :=
(coe_nnreal_eq ⟨x, h⟩).symm
#align ennreal.of_real_eq_coe_nnreal ENNReal.ofReal_eq_coe_nnreal
@[simp] theorem ofReal_coe_nnreal : ENNReal.ofReal p = p := (coe_nnreal_eq p).symm
#align ennreal.of_real_coe_nnreal ENNReal.ofReal_coe_nnreal
@[simp, norm_cast] theorem coe_zero : ↑(0 : ℝ≥0) = (0 : ℝ≥0∞) := rfl
#align ennreal.coe_zero ENNReal.coe_zero
@[simp, norm_cast] theorem coe_one : ↑(1 : ℝ≥0) = (1 : ℝ≥0∞) := rfl
#align ennreal.coe_one ENNReal.coe_one
@[simp] theorem toReal_nonneg {a : ℝ≥0∞} : 0 ≤ a.toReal := a.toNNReal.2
#align ennreal.to_real_nonneg ENNReal.toReal_nonneg
@[simp] theorem top_toNNReal : ∞.toNNReal = 0 := rfl
#align ennreal.top_to_nnreal ENNReal.top_toNNReal
@[simp] theorem top_toReal : ∞.toReal = 0 := rfl
#align ennreal.top_to_real ENNReal.top_toReal
@[simp] theorem one_toReal : (1 : ℝ≥0∞).toReal = 1 := rfl
#align ennreal.one_to_real ENNReal.one_toReal
@[simp] theorem one_toNNReal : (1 : ℝ≥0∞).toNNReal = 1 := rfl
#align ennreal.one_to_nnreal ENNReal.one_toNNReal
@[simp] theorem coe_toReal (r : ℝ≥0) : (r : ℝ≥0∞).toReal = r := rfl
#align ennreal.coe_to_real ENNReal.coe_toReal
@[simp] theorem zero_toNNReal : (0 : ℝ≥0∞).toNNReal = 0 := rfl
#align ennreal.zero_to_nnreal ENNReal.zero_toNNReal
@[simp] theorem zero_toReal : (0 : ℝ≥0∞).toReal = 0 := rfl
#align ennreal.zero_to_real ENNReal.zero_toReal
@[simp] theorem ofReal_zero : ENNReal.ofReal (0 : ℝ) = 0 := by simp [ENNReal.ofReal]
#align ennreal.of_real_zero ENNReal.ofReal_zero
@[simp] theorem ofReal_one : ENNReal.ofReal (1 : ℝ) = (1 : ℝ≥0∞) := by simp [ENNReal.ofReal]
#align ennreal.of_real_one ENNReal.ofReal_one
theorem ofReal_toReal_le {a : ℝ≥0∞} : ENNReal.ofReal a.toReal ≤ a :=
if ha : a = ∞ then ha.symm ▸ le_top else le_of_eq (ofReal_toReal ha)
#align ennreal.of_real_to_real_le ENNReal.ofReal_toReal_le
theorem forall_ennreal {p : ℝ≥0∞ → Prop} : (∀ a, p a) ↔ (∀ r : ℝ≥0, p r) ∧ p ∞ :=
Option.forall.trans and_comm
#align ennreal.forall_ennreal ENNReal.forall_ennreal
theorem forall_ne_top {p : ℝ≥0∞ → Prop} : (∀ a, a ≠ ∞ → p a) ↔ ∀ r : ℝ≥0, p r :=
Option.ball_ne_none
#align ennreal.forall_ne_top ENNReal.forall_ne_top
theorem exists_ne_top {p : ℝ≥0∞ → Prop} : (∃ a ≠ ∞, p a) ↔ ∃ r : ℝ≥0, p r :=
Option.exists_ne_none
#align ennreal.exists_ne_top ENNReal.exists_ne_top
theorem toNNReal_eq_zero_iff (x : ℝ≥0∞) : x.toNNReal = 0 ↔ x = 0 ∨ x = ∞ :=
WithTop.untop'_eq_self_iff
#align ennreal.to_nnreal_eq_zero_iff ENNReal.toNNReal_eq_zero_iff
theorem toReal_eq_zero_iff (x : ℝ≥0∞) : x.toReal = 0 ↔ x = 0 ∨ x = ∞ := by
simp [ENNReal.toReal, toNNReal_eq_zero_iff]
#align ennreal.to_real_eq_zero_iff ENNReal.toReal_eq_zero_iff
theorem toNNReal_ne_zero : a.toNNReal ≠ 0 ↔ a ≠ 0 ∧ a ≠ ∞ :=
a.toNNReal_eq_zero_iff.not.trans not_or
#align ennreal.to_nnreal_ne_zero ENNReal.toNNReal_ne_zero
theorem toReal_ne_zero : a.toReal ≠ 0 ↔ a ≠ 0 ∧ a ≠ ∞ :=
a.toReal_eq_zero_iff.not.trans not_or
#align ennreal.to_real_ne_zero ENNReal.toReal_ne_zero
theorem toNNReal_eq_one_iff (x : ℝ≥0∞) : x.toNNReal = 1 ↔ x = 1 :=
WithTop.untop'_eq_iff.trans <| by simp
#align ennreal.to_nnreal_eq_one_iff ENNReal.toNNReal_eq_one_iff
theorem toReal_eq_one_iff (x : ℝ≥0∞) : x.toReal = 1 ↔ x = 1 := by
rw [ENNReal.toReal, NNReal.coe_eq_one, ENNReal.toNNReal_eq_one_iff]
#align ennreal.to_real_eq_one_iff ENNReal.toReal_eq_one_iff
theorem toNNReal_ne_one : a.toNNReal ≠ 1 ↔ a ≠ 1 :=
a.toNNReal_eq_one_iff.not
#align ennreal.to_nnreal_ne_one ENNReal.toNNReal_ne_one
theorem toReal_ne_one : a.toReal ≠ 1 ↔ a ≠ 1 :=
a.toReal_eq_one_iff.not
#align ennreal.to_real_ne_one ENNReal.toReal_ne_one
@[simp] theorem coe_ne_top : (r : ℝ≥0∞) ≠ ∞ := WithTop.coe_ne_top
#align ennreal.coe_ne_top ENNReal.coe_ne_top
@[simp] theorem top_ne_coe : ∞ ≠ (r : ℝ≥0∞) := WithTop.top_ne_coe
#align ennreal.top_ne_coe ENNReal.top_ne_coe
@[simp] theorem coe_lt_top : (r : ℝ≥0∞) < ∞ := WithTop.coe_lt_top r
#align ennreal.coe_lt_top ENNReal.coe_lt_top
@[simp] theorem ofReal_ne_top {r : ℝ} : ENNReal.ofReal r ≠ ∞ := coe_ne_top
#align ennreal.of_real_ne_top ENNReal.ofReal_ne_top
@[simp] theorem ofReal_lt_top {r : ℝ} : ENNReal.ofReal r < ∞ := coe_lt_top
#align ennreal.of_real_lt_top ENNReal.ofReal_lt_top
@[simp] theorem top_ne_ofReal {r : ℝ} : ∞ ≠ ENNReal.ofReal r := top_ne_coe
#align ennreal.top_ne_of_real ENNReal.top_ne_ofReal
@[simp]
theorem ofReal_toReal_eq_iff : ENNReal.ofReal a.toReal = a ↔ a ≠ ⊤ :=
⟨fun h => by
rw [← h]
exact ofReal_ne_top, ofReal_toReal⟩
#align ennreal.of_real_to_real_eq_iff ENNReal.ofReal_toReal_eq_iff
@[simp]
theorem toReal_ofReal_eq_iff {a : ℝ} : (ENNReal.ofReal a).toReal = a ↔ 0 ≤ a :=
⟨fun h => by
rw [← h]
exact toReal_nonneg, toReal_ofReal⟩
#align ennreal.to_real_of_real_eq_iff ENNReal.toReal_ofReal_eq_iff
@[simp] theorem zero_ne_top : 0 ≠ ∞ := coe_ne_top
#align ennreal.zero_ne_top ENNReal.zero_ne_top
@[simp] theorem top_ne_zero : ∞ ≠ 0 := top_ne_coe
#align ennreal.top_ne_zero ENNReal.top_ne_zero
@[simp] theorem one_ne_top : 1 ≠ ∞ := coe_ne_top
#align ennreal.one_ne_top ENNReal.one_ne_top
@[simp] theorem top_ne_one : ∞ ≠ 1 := top_ne_coe
#align ennreal.top_ne_one ENNReal.top_ne_one
@[simp] theorem zero_lt_top : 0 < ∞ := coe_lt_top
@[simp, norm_cast] theorem coe_le_coe : (↑r : ℝ≥0∞) ≤ ↑q ↔ r ≤ q := WithTop.coe_le_coe
#align ennreal.coe_le_coe ENNReal.coe_le_coe
@[simp, norm_cast] theorem coe_lt_coe : (↑r : ℝ≥0∞) < ↑q ↔ r < q := WithTop.coe_lt_coe
#align ennreal.coe_lt_coe ENNReal.coe_lt_coe
-- Needed until `@[gcongr]` accepts iff statements
alias ⟨_, coe_le_coe_of_le⟩ := coe_le_coe
attribute [gcongr] ENNReal.coe_le_coe_of_le
-- Needed until `@[gcongr]` accepts iff statements
alias ⟨_, coe_lt_coe_of_lt⟩ := coe_lt_coe
attribute [gcongr] ENNReal.coe_lt_coe_of_lt
theorem coe_mono : Monotone ofNNReal := fun _ _ => coe_le_coe.2
#align ennreal.coe_mono ENNReal.coe_mono
theorem coe_strictMono : StrictMono ofNNReal := fun _ _ => coe_lt_coe.2
@[simp, norm_cast] theorem coe_eq_zero : (↑r : ℝ≥0∞) = 0 ↔ r = 0 := coe_inj
#align ennreal.coe_eq_zero ENNReal.coe_eq_zero
@[simp, norm_cast] theorem zero_eq_coe : 0 = (↑r : ℝ≥0∞) ↔ 0 = r := coe_inj
#align ennreal.zero_eq_coe ENNReal.zero_eq_coe
@[simp, norm_cast] theorem coe_eq_one : (↑r : ℝ≥0∞) = 1 ↔ r = 1 := coe_inj
#align ennreal.coe_eq_one ENNReal.coe_eq_one
@[simp, norm_cast] theorem one_eq_coe : 1 = (↑r : ℝ≥0∞) ↔ 1 = r := coe_inj
#align ennreal.one_eq_coe ENNReal.one_eq_coe
@[simp, norm_cast] theorem coe_pos : 0 < (r : ℝ≥0∞) ↔ 0 < r := coe_lt_coe
#align ennreal.coe_pos ENNReal.coe_pos
theorem coe_ne_zero : (r : ℝ≥0∞) ≠ 0 ↔ r ≠ 0 := coe_eq_zero.not
#align ennreal.coe_ne_zero ENNReal.coe_ne_zero
lemma coe_ne_one : (r : ℝ≥0∞) ≠ 1 ↔ r ≠ 1 := coe_eq_one.not
@[simp, norm_cast] lemma coe_add (x y : ℝ≥0) : (↑(x + y) : ℝ≥0∞) = x + y := rfl
#align ennreal.coe_add ENNReal.coe_add
@[simp, norm_cast] lemma coe_mul (x y : ℝ≥0) : (↑(x * y) : ℝ≥0∞) = x * y := rfl
#align ennreal.coe_mul ENNReal.coe_mul
@[norm_cast] lemma coe_nsmul (n : ℕ) (x : ℝ≥0) : (↑(n • x) : ℝ≥0∞) = n • x := rfl
@[simp, norm_cast] lemma coe_pow (x : ℝ≥0) (n : ℕ) : (↑(x ^ n) : ℝ≥0∞) = x ^ n := rfl
#noalign ennreal.coe_bit0
#noalign ennreal.coe_bit1
-- See note [no_index around OfNat.ofNat]
@[simp, norm_cast] -- Porting note (#10756): new theorem
theorem coe_ofNat (n : ℕ) [n.AtLeastTwo] :
((no_index (OfNat.ofNat n) : ℝ≥0) : ℝ≥0∞) = OfNat.ofNat n := rfl
-- Porting note (#11215): TODO: add lemmas about `OfNat.ofNat` and `<`/`≤`
theorem coe_two : ((2 : ℝ≥0) : ℝ≥0∞) = 2 := rfl
#align ennreal.coe_two ENNReal.coe_two
theorem toNNReal_eq_toNNReal_iff (x y : ℝ≥0∞) :
x.toNNReal = y.toNNReal ↔ x = y ∨ x = 0 ∧ y = ⊤ ∨ x = ⊤ ∧ y = 0 :=
WithTop.untop'_eq_untop'_iff
#align ennreal.to_nnreal_eq_to_nnreal_iff ENNReal.toNNReal_eq_toNNReal_iff
| Mathlib/Data/ENNReal/Basic.lean | 438 | 440 | theorem toReal_eq_toReal_iff (x y : ℝ≥0∞) :
x.toReal = y.toReal ↔ x = y ∨ x = 0 ∧ y = ⊤ ∨ x = ⊤ ∧ y = 0 := by |
simp only [ENNReal.toReal, NNReal.coe_inj, toNNReal_eq_toNNReal_iff]
|
/-
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.Data.Set.Function
import Mathlib.Logic.Equiv.Defs
import Mathlib.Tactic.Core
import Mathlib.Tactic.Attr.Core
#align_import logic.equiv.local_equiv from "leanprover-community/mathlib"@"48fb5b5280e7c81672afc9524185ae994553ebf4"
/-!
# Partial equivalences
This files defines equivalences between subsets of given types.
An element `e` of `PartialEquiv α β` is made of two maps `e.toFun` and `e.invFun` respectively
from α to β and from β to α (just like equivs), which are inverse to each other on the subsets
`e.source` and `e.target` of respectively α and β.
They are designed in particular to define charts on manifolds.
The main functionality is `e.trans f`, which composes the two partial equivalences by restricting
the source and target to the maximal set where the composition makes sense.
As for equivs, we register a coercion to functions and use it in our simp normal form: we write
`e x` and `e.symm y` instead of `e.toFun x` and `e.invFun y`.
## Main definitions
* `Equiv.toPartialEquiv`: associating a partial equiv to an equiv, with source = target = univ
* `PartialEquiv.symm`: the inverse of a partial equivalence
* `PartialEquiv.trans`: the composition of two partial equivalences
* `PartialEquiv.refl`: the identity partial equivalence
* `PartialEquiv.ofSet`: the identity on a set `s`
* `EqOnSource`: equivalence relation describing the "right" notion of equality for partial
equivalences (see below in implementation notes)
## Implementation notes
There are at least three possible implementations of partial equivalences:
* equivs on subtypes
* pairs of functions taking values in `Option α` and `Option β`, equal to none where the partial
equivalence is not defined
* pairs of functions defined everywhere, keeping the source and target as additional data
Each of these implementations has pros and cons.
* When dealing with subtypes, one still need to define additional API for composition and
restriction of domains. Checking that one always belongs to the right subtype makes things very
tedious, and leads quickly to DTT hell (as the subtype `u ∩ v` is not the "same" as `v ∩ u`, for
instance).
* With option-valued functions, the composition is very neat (it is just the usual composition, and
the domain is restricted automatically). These are implemented in `PEquiv.lean`. For manifolds,
where one wants to discuss thoroughly the smoothness of the maps, this creates however a lot of
overhead as one would need to extend all classes of smoothness to option-valued maps.
* The `PartialEquiv` version as explained above is easier to use for manifolds. The drawback is that
there is extra useless data (the values of `toFun` and `invFun` outside of `source` and `target`).
In particular, the equality notion between partial equivs is not "the right one", i.e., coinciding
source and target and equality there. Moreover, there are no partial equivs in this sense between
an empty type and a nonempty type. Since empty types are not that useful, and since one almost never
needs to talk about equal partial equivs, this is not an issue in practice.
Still, we introduce an equivalence relation `EqOnSource` that captures this right notion of
equality, and show that many properties are invariant under this equivalence relation.
### 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 Lean Meta Elab Tactic
/-! Implementation of the `mfld_set_tac` tactic for working with the domains of partially-defined
functions (`PartialEquiv`, `PartialHomeomorph`, etc).
This is in a separate file from `Mathlib.Logic.Equiv.MfldSimpsAttr` because attributes need a new
file to become functional.
-/
/-- Common `@[simps]` configuration options used for manifold-related declarations. -/
def mfld_cfg : Simps.Config where
attrs := [`mfld_simps]
fullyApplied := false
#align mfld_cfg mfld_cfg
namespace Tactic.MfldSetTac
/-- A very basic tactic to show that sets showing up in manifolds coincide or are included
in one another. -/
elab (name := mfldSetTac) "mfld_set_tac" : tactic => withMainContext do
let g ← getMainGoal
let goalTy := (← instantiateMVars (← g.getDecl).type).getAppFnArgs
match goalTy with
| (``Eq, #[_ty, _e₁, _e₂]) =>
evalTactic (← `(tactic| (
apply Set.ext; intro my_y
constructor <;>
· intro h_my_y
try simp only [*, mfld_simps] at h_my_y
try simp only [*, mfld_simps])))
| (``Subset, #[_ty, _inst, _e₁, _e₂]) =>
evalTactic (← `(tactic| (
intro my_y h_my_y
try simp only [*, mfld_simps] at h_my_y
try simp only [*, mfld_simps])))
| _ => throwError "goal should be an equality or an inclusion"
attribute [mfld_simps] and_true eq_self_iff_true Function.comp_apply
end Tactic.MfldSetTac
open Function Set
variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*}
/-- Local equivalence between subsets `source` and `target` of `α` and `β` respectively. The
(global) maps `toFun : α → β` and `invFun : β → α` map `source` to `target` and conversely, and are
inverse to each other there. The values of `toFun` outside of `source` and of `invFun` outside of
`target` are irrelevant. -/
structure PartialEquiv (α : Type*) (β : Type*) where
/-- The global function which has a partial inverse. Its value outside of the `source` subset is
irrelevant. -/
toFun : α → β
/-- The partial inverse to `toFun`. Its value outside of the `target` subset is irrelevant. -/
invFun : β → α
/-- The domain of the partial equivalence. -/
source : Set α
/-- The codomain of the partial equivalence. -/
target : Set β
/-- The proposition that elements of `source` are mapped to elements of `target`. -/
map_source' : ∀ ⦃x⦄, x ∈ source → toFun x ∈ target
/-- The proposition that elements of `target` are mapped to elements of `source`. -/
map_target' : ∀ ⦃x⦄, x ∈ target → invFun x ∈ source
/-- The proposition that `invFun` is a left-inverse of `toFun` on `source`. -/
left_inv' : ∀ ⦃x⦄, x ∈ source → invFun (toFun x) = x
/-- The proposition that `invFun` is a right-inverse of `toFun` on `target`. -/
right_inv' : ∀ ⦃x⦄, x ∈ target → toFun (invFun x) = x
#align local_equiv PartialEquiv
attribute [coe] PartialEquiv.toFun
namespace PartialEquiv
variable (e : PartialEquiv α β) (e' : PartialEquiv β γ)
instance [Inhabited α] [Inhabited β] : Inhabited (PartialEquiv α β) :=
⟨⟨const α default, const β default, ∅, ∅, mapsTo_empty _ _, mapsTo_empty _ _, eqOn_empty _ _,
eqOn_empty _ _⟩⟩
/-- The inverse of a partial equivalence -/
@[symm]
protected def symm : PartialEquiv β α where
toFun := e.invFun
invFun := e.toFun
source := e.target
target := e.source
map_source' := e.map_target'
map_target' := e.map_source'
left_inv' := e.right_inv'
right_inv' := e.left_inv'
#align local_equiv.symm PartialEquiv.symm
instance : CoeFun (PartialEquiv α β) fun _ => α → β :=
⟨PartialEquiv.toFun⟩
/-- See Note [custom simps projection] -/
def Simps.symm_apply (e : PartialEquiv α β) : β → α :=
e.symm
#align local_equiv.simps.symm_apply PartialEquiv.Simps.symm_apply
initialize_simps_projections PartialEquiv (toFun → apply, invFun → symm_apply)
-- Porting note: this can be proven with `dsimp only`
-- @[simp, mfld_simps]
-- theorem coe_mk (f : α → β) (g s t ml mr il ir) :
-- (PartialEquiv.mk f g s t ml mr il ir : α → β) = f := by dsimp only
-- #align local_equiv.coe_mk PartialEquiv.coe_mk
#noalign local_equiv.coe_mk
@[simp, mfld_simps]
theorem coe_symm_mk (f : α → β) (g s t ml mr il ir) :
((PartialEquiv.mk f g s t ml mr il ir).symm : β → α) = g :=
rfl
#align local_equiv.coe_symm_mk PartialEquiv.coe_symm_mk
-- Porting note: this is now a syntactic tautology
-- @[simp, mfld_simps]
-- theorem toFun_as_coe : e.toFun = e := rfl
-- #align local_equiv.to_fun_as_coe PartialEquiv.toFun_as_coe
#noalign local_equiv.to_fun_as_coe
@[simp, mfld_simps]
theorem invFun_as_coe : e.invFun = e.symm :=
rfl
#align local_equiv.inv_fun_as_coe PartialEquiv.invFun_as_coe
@[simp, mfld_simps]
theorem map_source {x : α} (h : x ∈ e.source) : e x ∈ e.target :=
e.map_source' h
#align local_equiv.map_source PartialEquiv.map_source
/-- Variant of `e.map_source` and `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 : β} (h : x ∈ e.target) : e.symm x ∈ e.source :=
e.map_target' h
#align local_equiv.map_target PartialEquiv.map_target
@[simp, mfld_simps]
theorem left_inv {x : α} (h : x ∈ e.source) : e.symm (e x) = x :=
e.left_inv' h
#align local_equiv.left_inv PartialEquiv.left_inv
@[simp, mfld_simps]
theorem right_inv {x : β} (h : x ∈ e.target) : e (e.symm x) = x :=
e.right_inv' h
#align local_equiv.right_inv PartialEquiv.right_inv
theorem eq_symm_apply {x : α} {y : β} (hx : x ∈ e.source) (hy : y ∈ e.target) :
x = e.symm y ↔ e x = y :=
⟨fun h => by rw [← e.right_inv hy, h], fun h => by rw [← e.left_inv hx, h]⟩
#align local_equiv.eq_symm_apply PartialEquiv.eq_symm_apply
protected theorem mapsTo : MapsTo e e.source e.target := fun _ => e.map_source
#align local_equiv.maps_to PartialEquiv.mapsTo
theorem symm_mapsTo : MapsTo e.symm e.target e.source :=
e.symm.mapsTo
#align local_equiv.symm_maps_to PartialEquiv.symm_mapsTo
protected theorem leftInvOn : LeftInvOn e.symm e e.source := fun _ => e.left_inv
#align local_equiv.left_inv_on PartialEquiv.leftInvOn
protected theorem rightInvOn : RightInvOn e.symm e e.target := fun _ => e.right_inv
#align local_equiv.right_inv_on PartialEquiv.rightInvOn
protected theorem invOn : InvOn e.symm e e.source e.target :=
⟨e.leftInvOn, e.rightInvOn⟩
#align local_equiv.inv_on PartialEquiv.invOn
protected theorem injOn : InjOn e e.source :=
e.leftInvOn.injOn
#align local_equiv.inj_on PartialEquiv.injOn
protected theorem bijOn : BijOn e e.source e.target :=
e.invOn.bijOn e.mapsTo e.symm_mapsTo
#align local_equiv.bij_on PartialEquiv.bijOn
protected theorem surjOn : SurjOn e e.source e.target :=
e.bijOn.surjOn
#align local_equiv.surj_on PartialEquiv.surjOn
/-- Interpret an `Equiv` as a `PartialEquiv` by restricting it to `s` in the domain
and to `t` in the codomain. -/
@[simps (config := .asFn)]
def _root_.Equiv.toPartialEquivOfImageEq (e : α ≃ β) (s : Set α) (t : Set β) (h : e '' s = t) :
PartialEquiv α β where
toFun := e
invFun := e.symm
source := s
target := t
map_source' x hx := h ▸ mem_image_of_mem _ hx
map_target' x hx := by
subst t
rcases hx with ⟨x, hx, rfl⟩
rwa [e.symm_apply_apply]
left_inv' x _ := e.symm_apply_apply x
right_inv' x _ := e.apply_symm_apply x
/-- Associate a `PartialEquiv` to an `Equiv`. -/
@[simps! (config := mfld_cfg)]
def _root_.Equiv.toPartialEquiv (e : α ≃ β) : PartialEquiv α β :=
e.toPartialEquivOfImageEq univ univ <| by rw [image_univ, e.surjective.range_eq]
#align equiv.to_local_equiv Equiv.toPartialEquiv
#align equiv.to_local_equiv_symm_apply Equiv.toPartialEquiv_symm_apply
#align equiv.to_local_equiv_target Equiv.toPartialEquiv_target
#align equiv.to_local_equiv_apply Equiv.toPartialEquiv_apply
#align equiv.to_local_equiv_source Equiv.toPartialEquiv_source
instance inhabitedOfEmpty [IsEmpty α] [IsEmpty β] : Inhabited (PartialEquiv α β) :=
⟨((Equiv.equivEmpty α).trans (Equiv.equivEmpty β).symm).toPartialEquiv⟩
#align local_equiv.inhabited_of_empty PartialEquiv.inhabitedOfEmpty
/-- Create a copy of a `PartialEquiv` providing better definitional equalities. -/
@[simps (config := .asFn)]
def copy (e : PartialEquiv α β) (f : α → β) (hf : ⇑e = f) (g : β → α) (hg : ⇑e.symm = g) (s : Set α)
(hs : e.source = s) (t : Set β) (ht : e.target = t) :
PartialEquiv α β where
toFun := f
invFun := g
source := s
target := t
map_source' _ := ht ▸ hs ▸ hf ▸ e.map_source
map_target' _ := hs ▸ ht ▸ hg ▸ e.map_target
left_inv' _ := hs ▸ hf ▸ hg ▸ e.left_inv
right_inv' _ := ht ▸ hf ▸ hg ▸ e.right_inv
#align local_equiv.copy PartialEquiv.copy
#align local_equiv.copy_source PartialEquiv.copy_source
#align local_equiv.copy_apply PartialEquiv.copy_apply
#align local_equiv.copy_symm_apply PartialEquiv.copy_symm_apply
#align local_equiv.copy_target PartialEquiv.copy_target
theorem copy_eq (e : PartialEquiv α β) (f : α → β) (hf : ⇑e = f) (g : β → α) (hg : ⇑e.symm = g)
(s : Set α) (hs : e.source = s) (t : Set β) (ht : e.target = t) :
e.copy f hf g hg s hs t ht = e := by
substs f g s t
cases e
rfl
#align local_equiv.copy_eq PartialEquiv.copy_eq
/-- Associate to a `PartialEquiv` an `Equiv` between the source and the target. -/
protected def toEquiv : e.source ≃ e.target where
toFun x := ⟨e x, e.map_source x.mem⟩
invFun y := ⟨e.symm y, e.map_target y.mem⟩
left_inv := fun ⟨_, hx⟩ => Subtype.eq <| e.left_inv hx
right_inv := fun ⟨_, hy⟩ => Subtype.eq <| e.right_inv hy
#align local_equiv.to_equiv PartialEquiv.toEquiv
@[simp, mfld_simps]
theorem symm_source : e.symm.source = e.target :=
rfl
#align local_equiv.symm_source PartialEquiv.symm_source
@[simp, mfld_simps]
theorem symm_target : e.symm.target = e.source :=
rfl
#align local_equiv.symm_target PartialEquiv.symm_target
@[simp, mfld_simps]
theorem symm_symm : e.symm.symm = e := by
cases e
rfl
#align local_equiv.symm_symm PartialEquiv.symm_symm
theorem symm_bijective :
Function.Bijective (PartialEquiv.symm : PartialEquiv α β → PartialEquiv β α) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
theorem image_source_eq_target : e '' e.source = e.target :=
e.bijOn.image_eq
#align local_equiv.image_source_eq_target PartialEquiv.image_source_eq_target
theorem forall_mem_target {p : β → Prop} : (∀ y ∈ e.target, p y) ↔ ∀ x ∈ e.source, p (e x) := by
rw [← image_source_eq_target, forall_mem_image]
#align local_equiv.forall_mem_target PartialEquiv.forall_mem_target
theorem exists_mem_target {p : β → Prop} : (∃ y ∈ e.target, p y) ↔ ∃ x ∈ e.source, p (e x) := by
rw [← image_source_eq_target, exists_mem_image]
#align local_equiv.exists_mem_target PartialEquiv.exists_mem_target
/-- We say that `t : Set β` is an image of `s : Set α` under a partial equivalence if
any of the following equivalent conditions hold:
* `e '' (e.source ∩ s) = e.target ∩ t`;
* `e.source ∩ e ⁻¹ t = e.source ∩ s`;
* `∀ x ∈ e.source, e x ∈ t ↔ x ∈ s` (this one is used in the definition).
-/
def IsImage (s : Set α) (t : Set β) : Prop :=
∀ ⦃x⦄, x ∈ e.source → (e x ∈ t ↔ x ∈ s)
#align local_equiv.is_image PartialEquiv.IsImage
namespace IsImage
variable {e} {s : Set α} {t : Set β} {x : α} {y : β}
theorem apply_mem_iff (h : e.IsImage s t) (hx : x ∈ e.source) : e x ∈ t ↔ x ∈ s :=
h hx
#align local_equiv.is_image.apply_mem_iff PartialEquiv.IsImage.apply_mem_iff
theorem symm_apply_mem_iff (h : e.IsImage s t) : ∀ ⦃y⦄, y ∈ e.target → (e.symm y ∈ s ↔ y ∈ t) :=
e.forall_mem_target.mpr fun x hx => by rw [e.left_inv hx, h hx]
#align local_equiv.is_image.symm_apply_mem_iff PartialEquiv.IsImage.symm_apply_mem_iff
protected theorem symm (h : e.IsImage s t) : e.symm.IsImage t s :=
h.symm_apply_mem_iff
#align local_equiv.is_image.symm PartialEquiv.IsImage.symm
@[simp]
theorem symm_iff : e.symm.IsImage t s ↔ e.IsImage s t :=
⟨fun h => h.symm, fun h => h.symm⟩
#align local_equiv.is_image.symm_iff PartialEquiv.IsImage.symm_iff
protected theorem mapsTo (h : e.IsImage s t) : MapsTo e (e.source ∩ s) (e.target ∩ t) :=
fun _ hx => ⟨e.mapsTo hx.1, (h hx.1).2 hx.2⟩
#align local_equiv.is_image.maps_to PartialEquiv.IsImage.mapsTo
theorem symm_mapsTo (h : e.IsImage s t) : MapsTo e.symm (e.target ∩ t) (e.source ∩ s) :=
h.symm.mapsTo
#align local_equiv.is_image.symm_maps_to PartialEquiv.IsImage.symm_mapsTo
/-- Restrict a `PartialEquiv` to a pair of corresponding sets. -/
@[simps (config := .asFn)]
def restr (h : e.IsImage s t) : PartialEquiv α β where
toFun := e
invFun := e.symm
source := e.source ∩ s
target := e.target ∩ t
map_source' := h.mapsTo
map_target' := h.symm_mapsTo
left_inv' := e.leftInvOn.mono inter_subset_left
right_inv' := e.rightInvOn.mono inter_subset_left
#align local_equiv.is_image.restr PartialEquiv.IsImage.restr
#align local_equiv.is_image.restr_apply PartialEquiv.IsImage.restr_apply
#align local_equiv.is_image.restr_source PartialEquiv.IsImage.restr_source
#align local_equiv.is_image.restr_target PartialEquiv.IsImage.restr_target
#align local_equiv.is_image.restr_symm_apply PartialEquiv.IsImage.restr_symm_apply
theorem image_eq (h : e.IsImage s t) : e '' (e.source ∩ s) = e.target ∩ t :=
h.restr.image_source_eq_target
#align local_equiv.is_image.image_eq PartialEquiv.IsImage.image_eq
theorem symm_image_eq (h : e.IsImage s t) : e.symm '' (e.target ∩ t) = e.source ∩ s :=
h.symm.image_eq
#align local_equiv.is_image.symm_image_eq PartialEquiv.IsImage.symm_image_eq
| Mathlib/Logic/Equiv/PartialEquiv.lean | 418 | 419 | theorem iff_preimage_eq : e.IsImage s t ↔ e.source ∩ e ⁻¹' t = e.source ∩ s := by |
simp only [IsImage, ext_iff, mem_inter_iff, mem_preimage, and_congr_right_iff]
|
/-
Copyright (c) 2014 Parikshit Khanna. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Parikshit Khanna, Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Mario Carneiro
-/
import Mathlib.Data.List.Join
#align_import data.list.permutation from "leanprover-community/mathlib"@"dd71334db81d0bd444af1ee339a29298bef40734"
/-!
# Permutations of a list
In this file we prove properties about `List.Permutations`, a list of all permutations of a list. It
is defined in `Data.List.Defs`.
## Order of the permutations
Designed for performance, the order in which the permutations appear in `List.Permutations` is
rather intricate and not very amenable to induction. That's why we also provide `List.Permutations'`
as a less efficient but more straightforward way of listing permutations.
### `List.Permutations`
TODO. In the meantime, you can try decrypting the docstrings.
### `List.Permutations'`
The list of partitions is built by recursion. The permutations of `[]` are `[[]]`. Then, the
permutations of `a :: l` are obtained by taking all permutations of `l` in order and adding `a` in
all positions. Hence, to build `[0, 1, 2, 3].permutations'`, it does
* `[[]]`
* `[[3]]`
* `[[2, 3], [3, 2]]]`
* `[[1, 2, 3], [2, 1, 3], [2, 3, 1], [1, 3, 2], [3, 1, 2], [3, 2, 1]]`
* `[[0, 1, 2, 3], [1, 0, 2, 3], [1, 2, 0, 3], [1, 2, 3, 0],`
`[0, 2, 1, 3], [2, 0, 1, 3], [2, 1, 0, 3], [2, 1, 3, 0],`
`[0, 2, 3, 1], [2, 0, 3, 1], [2, 3, 0, 1], [2, 3, 1, 0],`
`[0, 1, 3, 2], [1, 0, 3, 2], [1, 3, 0, 2], [1, 3, 2, 0],`
`[0, 3, 1, 2], [3, 0, 1, 2], [3, 1, 0, 2], [3, 1, 2, 0],`
`[0, 3, 2, 1], [3, 0, 2, 1], [3, 2, 0, 1], [3, 2, 1, 0]]`
## TODO
Show that `l.Nodup → l.permutations.Nodup`. See `Data.Fintype.List`.
-/
-- Make sure we don't import algebra
assert_not_exists Monoid
open Nat
variable {α β : Type*}
namespace List
theorem permutationsAux2_fst (t : α) (ts : List α) (r : List β) :
∀ (ys : List α) (f : List α → β), (permutationsAux2 t ts r ys f).1 = ys ++ ts
| [], f => rfl
| y :: ys, f => by simp [permutationsAux2, permutationsAux2_fst t _ _ ys]
#align list.permutations_aux2_fst List.permutationsAux2_fst
@[simp]
theorem permutationsAux2_snd_nil (t : α) (ts : List α) (r : List β) (f : List α → β) :
(permutationsAux2 t ts r [] f).2 = r :=
rfl
#align list.permutations_aux2_snd_nil List.permutationsAux2_snd_nil
@[simp]
theorem permutationsAux2_snd_cons (t : α) (ts : List α) (r : List β) (y : α) (ys : List α)
(f : List α → β) :
(permutationsAux2 t ts r (y :: ys) f).2 =
f (t :: y :: ys ++ ts) :: (permutationsAux2 t ts r ys fun x : List α => f (y :: x)).2 := by
simp [permutationsAux2, permutationsAux2_fst t _ _ ys]
#align list.permutations_aux2_snd_cons List.permutationsAux2_snd_cons
/-- The `r` argument to `permutationsAux2` is the same as appending. -/
| Mathlib/Data/List/Permutation.lean | 77 | 79 | theorem permutationsAux2_append (t : α) (ts : List α) (r : List β) (ys : List α) (f : List α → β) :
(permutationsAux2 t ts nil ys f).2 ++ r = (permutationsAux2 t ts r ys f).2 := by |
induction ys generalizing f <;> simp [*]
|
/-
Copyright (c) 2017 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Logic.Relation
import Mathlib.Data.Option.Basic
import Mathlib.Data.Seq.Seq
#align_import data.seq.wseq from "leanprover-community/mathlib"@"a7e36e48519ab281320c4d192da6a7b348ce40ad"
/-!
# Partially defined possibly infinite lists
This file provides a `WSeq α` type representing partially defined possibly infinite lists
(referred here as weak sequences).
-/
namespace Stream'
open Function
universe u v w
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
/-- Weak sequences.
While the `Seq` structure allows for lists which may not be finite,
a weak sequence also allows the computation of each element to
involve an indeterminate amount of computation, including possibly
an infinite loop. This is represented as a regular `Seq` interspersed
with `none` elements to indicate that computation is ongoing.
This model is appropriate for Haskell style lazy lists, and is closed
under most interesting computation patterns on infinite lists,
but conversely it is difficult to extract elements from it. -/
def WSeq (α) :=
Seq (Option α)
#align stream.wseq Stream'.WSeq
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
namespace WSeq
variable {α : Type u} {β : Type v} {γ : Type w}
/-- Turn a sequence into a weak sequence -/
@[coe]
def ofSeq : Seq α → WSeq α :=
(· <$> ·) some
#align stream.wseq.of_seq Stream'.WSeq.ofSeq
/-- Turn a list into a weak sequence -/
@[coe]
def ofList (l : List α) : WSeq α :=
ofSeq l
#align stream.wseq.of_list Stream'.WSeq.ofList
/-- Turn a stream into a weak sequence -/
@[coe]
def ofStream (l : Stream' α) : WSeq α :=
ofSeq l
#align stream.wseq.of_stream Stream'.WSeq.ofStream
instance coeSeq : Coe (Seq α) (WSeq α) :=
⟨ofSeq⟩
#align stream.wseq.coe_seq Stream'.WSeq.coeSeq
instance coeList : Coe (List α) (WSeq α) :=
⟨ofList⟩
#align stream.wseq.coe_list Stream'.WSeq.coeList
instance coeStream : Coe (Stream' α) (WSeq α) :=
⟨ofStream⟩
#align stream.wseq.coe_stream Stream'.WSeq.coeStream
/-- The empty weak sequence -/
def nil : WSeq α :=
Seq.nil
#align stream.wseq.nil Stream'.WSeq.nil
instance inhabited : Inhabited (WSeq α) :=
⟨nil⟩
#align stream.wseq.inhabited Stream'.WSeq.inhabited
/-- Prepend an element to a weak sequence -/
def cons (a : α) : WSeq α → WSeq α :=
Seq.cons (some a)
#align stream.wseq.cons Stream'.WSeq.cons
/-- Compute for one tick, without producing any elements -/
def think : WSeq α → WSeq α :=
Seq.cons none
#align stream.wseq.think Stream'.WSeq.think
/-- Destruct a weak sequence, to (eventually possibly) produce either
`none` for `nil` or `some (a, s)` if an element is produced. -/
def destruct : WSeq α → Computation (Option (α × WSeq α)) :=
Computation.corec fun s =>
match Seq.destruct s with
| none => Sum.inl none
| some (none, s') => Sum.inr s'
| some (some a, s') => Sum.inl (some (a, s'))
#align stream.wseq.destruct Stream'.WSeq.destruct
/-- Recursion principle for weak sequences, compare with `List.recOn`. -/
def recOn {C : WSeq α → Sort v} (s : WSeq α) (h1 : C nil) (h2 : ∀ x s, C (cons x s))
(h3 : ∀ s, C (think s)) : C s :=
Seq.recOn s h1 fun o => Option.recOn o h3 h2
#align stream.wseq.rec_on Stream'.WSeq.recOn
/-- membership for weak sequences-/
protected def Mem (a : α) (s : WSeq α) :=
Seq.Mem (some a) s
#align stream.wseq.mem Stream'.WSeq.Mem
instance membership : Membership α (WSeq α) :=
⟨WSeq.Mem⟩
#align stream.wseq.has_mem Stream'.WSeq.membership
theorem not_mem_nil (a : α) : a ∉ @nil α :=
Seq.not_mem_nil (some a)
#align stream.wseq.not_mem_nil Stream'.WSeq.not_mem_nil
/-- Get the head of a weak sequence. This involves a possibly
infinite computation. -/
def head (s : WSeq α) : Computation (Option α) :=
Computation.map (Prod.fst <$> ·) (destruct s)
#align stream.wseq.head Stream'.WSeq.head
/-- Encode a computation yielding a weak sequence into additional
`think` constructors in a weak sequence -/
def flatten : Computation (WSeq α) → WSeq α :=
Seq.corec fun c =>
match Computation.destruct c with
| Sum.inl s => Seq.omap (return ·) (Seq.destruct s)
| Sum.inr c' => some (none, c')
#align stream.wseq.flatten Stream'.WSeq.flatten
/-- Get the tail of a weak sequence. This doesn't need a `Computation`
wrapper, unlike `head`, because `flatten` allows us to hide this
in the construction of the weak sequence itself. -/
def tail (s : WSeq α) : WSeq α :=
flatten <| (fun o => Option.recOn o nil Prod.snd) <$> destruct s
#align stream.wseq.tail Stream'.WSeq.tail
/-- drop the first `n` elements from `s`. -/
def drop (s : WSeq α) : ℕ → WSeq α
| 0 => s
| n + 1 => tail (drop s n)
#align stream.wseq.drop Stream'.WSeq.drop
/-- Get the nth element of `s`. -/
def get? (s : WSeq α) (n : ℕ) : Computation (Option α) :=
head (drop s n)
#align stream.wseq.nth Stream'.WSeq.get?
/-- Convert `s` to a list (if it is finite and completes in finite time). -/
def toList (s : WSeq α) : Computation (List α) :=
@Computation.corec (List α) (List α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s'))
([], s)
#align stream.wseq.to_list Stream'.WSeq.toList
/-- Get the length of `s` (if it is finite and completes in finite time). -/
def length (s : WSeq α) : Computation ℕ :=
@Computation.corec ℕ (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s with
| none => Sum.inl n
| some (none, s') => Sum.inr (n, s')
| some (some _, s') => Sum.inr (n + 1, s'))
(0, s)
#align stream.wseq.length Stream'.WSeq.length
/-- A weak sequence is finite if `toList s` terminates. Equivalently,
it is a finite number of `think` and `cons` applied to `nil`. -/
class IsFinite (s : WSeq α) : Prop where
out : (toList s).Terminates
#align stream.wseq.is_finite Stream'.WSeq.IsFinite
instance toList_terminates (s : WSeq α) [h : IsFinite s] : (toList s).Terminates :=
h.out
#align stream.wseq.to_list_terminates Stream'.WSeq.toList_terminates
/-- Get the list corresponding to a finite weak sequence. -/
def get (s : WSeq α) [IsFinite s] : List α :=
(toList s).get
#align stream.wseq.get Stream'.WSeq.get
/-- A weak sequence is *productive* if it never stalls forever - there are
always a finite number of `think`s between `cons` constructors.
The sequence itself is allowed to be infinite though. -/
class Productive (s : WSeq α) : Prop where
get?_terminates : ∀ n, (get? s n).Terminates
#align stream.wseq.productive Stream'.WSeq.Productive
#align stream.wseq.productive.nth_terminates Stream'.WSeq.Productive.get?_terminates
theorem productive_iff (s : WSeq α) : Productive s ↔ ∀ n, (get? s n).Terminates :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align stream.wseq.productive_iff Stream'.WSeq.productive_iff
instance get?_terminates (s : WSeq α) [h : Productive s] : ∀ n, (get? s n).Terminates :=
h.get?_terminates
#align stream.wseq.nth_terminates Stream'.WSeq.get?_terminates
instance head_terminates (s : WSeq α) [Productive s] : (head s).Terminates :=
s.get?_terminates 0
#align stream.wseq.head_terminates Stream'.WSeq.head_terminates
/-- Replace the `n`th element of `s` with `a`. -/
def updateNth (s : WSeq α) (n : ℕ) (a : α) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (some a, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.update_nth Stream'.WSeq.updateNth
/-- Remove the `n`th element of `s`. -/
def removeNth (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (none, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.remove_nth Stream'.WSeq.removeNth
/-- Map the elements of `s` over `f`, removing any values that yield `none`. -/
def filterMap (f : α → Option β) : WSeq α → WSeq β :=
Seq.corec fun s =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, s')
| some (some a, s') => some (f a, s')
#align stream.wseq.filter_map Stream'.WSeq.filterMap
/-- Select the elements of `s` that satisfy `p`. -/
def filter (p : α → Prop) [DecidablePred p] : WSeq α → WSeq α :=
filterMap fun a => if p a then some a else none
#align stream.wseq.filter Stream'.WSeq.filter
-- example of infinite list manipulations
/-- Get the first element of `s` satisfying `p`. -/
def find (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation (Option α) :=
head <| filter p s
#align stream.wseq.find Stream'.WSeq.find
/-- Zip a function over two weak sequences -/
def zipWith (f : α → β → γ) (s1 : WSeq α) (s2 : WSeq β) : WSeq γ :=
@Seq.corec (Option γ) (WSeq α × WSeq β)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some _, _), some (none, s2') => some (none, s1, s2')
| some (none, s1'), some (some _, _) => some (none, s1', s2)
| some (some a1, s1'), some (some a2, s2') => some (some (f a1 a2), s1', s2')
| _, _ => none)
(s1, s2)
#align stream.wseq.zip_with Stream'.WSeq.zipWith
/-- Zip two weak sequences into a single sequence of pairs -/
def zip : WSeq α → WSeq β → WSeq (α × β) :=
zipWith Prod.mk
#align stream.wseq.zip Stream'.WSeq.zip
/-- Get the list of indexes of elements of `s` satisfying `p` -/
def findIndexes (p : α → Prop) [DecidablePred p] (s : WSeq α) : WSeq ℕ :=
(zip s (Stream'.nats : WSeq ℕ)).filterMap fun ⟨a, n⟩ => if p a then some n else none
#align stream.wseq.find_indexes Stream'.WSeq.findIndexes
/-- Get the index of the first element of `s` satisfying `p` -/
def findIndex (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation ℕ :=
(fun o => Option.getD o 0) <$> head (findIndexes p s)
#align stream.wseq.find_index Stream'.WSeq.findIndex
/-- Get the index of the first occurrence of `a` in `s` -/
def indexOf [DecidableEq α] (a : α) : WSeq α → Computation ℕ :=
findIndex (Eq a)
#align stream.wseq.index_of Stream'.WSeq.indexOf
/-- Get the indexes of occurrences of `a` in `s` -/
def indexesOf [DecidableEq α] (a : α) : WSeq α → WSeq ℕ :=
findIndexes (Eq a)
#align stream.wseq.indexes_of Stream'.WSeq.indexesOf
/-- `union s1 s2` is a weak sequence which interleaves `s1` and `s2` in
some order (nondeterministically). -/
def union (s1 s2 : WSeq α) : WSeq α :=
@Seq.corec (Option α) (WSeq α × WSeq α)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| none, none => none
| some (a1, s1'), none => some (a1, s1', nil)
| none, some (a2, s2') => some (a2, nil, s2')
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some a1, s1'), some (none, s2') => some (some a1, s1', s2')
| some (none, s1'), some (some a2, s2') => some (some a2, s1', s2')
| some (some a1, s1'), some (some a2, s2') => some (some a1, cons a2 s1', s2'))
(s1, s2)
#align stream.wseq.union Stream'.WSeq.union
/-- Returns `true` if `s` is `nil` and `false` if `s` has an element -/
def isEmpty (s : WSeq α) : Computation Bool :=
Computation.map Option.isNone <| head s
#align stream.wseq.is_empty Stream'.WSeq.isEmpty
/-- Calculate one step of computation -/
def compute (s : WSeq α) : WSeq α :=
match Seq.destruct s with
| some (none, s') => s'
| _ => s
#align stream.wseq.compute Stream'.WSeq.compute
/-- Get the first `n` elements of a weak sequence -/
def take (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match n, Seq.destruct s with
| 0, _ => none
| _ + 1, none => none
| m + 1, some (none, s') => some (none, m + 1, s')
| m + 1, some (some a, s') => some (some a, m, s'))
(n, s)
#align stream.wseq.take Stream'.WSeq.take
/-- Split the sequence at position `n` into a finite initial segment
and the weak sequence tail -/
def splitAt (s : WSeq α) (n : ℕ) : Computation (List α × WSeq α) :=
@Computation.corec (List α × WSeq α) (ℕ × List α × WSeq α)
(fun ⟨n, l, s⟩ =>
match n, Seq.destruct s with
| 0, _ => Sum.inl (l.reverse, s)
| _ + 1, none => Sum.inl (l.reverse, s)
| _ + 1, some (none, s') => Sum.inr (n, l, s')
| m + 1, some (some a, s') => Sum.inr (m, a::l, s'))
(n, [], s)
#align stream.wseq.split_at Stream'.WSeq.splitAt
/-- Returns `true` if any element of `s` satisfies `p` -/
def any (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl false
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inl true else Sum.inr s')
s
#align stream.wseq.any Stream'.WSeq.any
/-- Returns `true` if every element of `s` satisfies `p` -/
def all (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl true
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inr s' else Sum.inl false)
s
#align stream.wseq.all Stream'.WSeq.all
/-- Apply a function to the elements of the sequence to produce a sequence
of partial results. (There is no `scanr` because this would require
working from the end of the sequence, which may not exist.) -/
def scanl (f : α → β → α) (a : α) (s : WSeq β) : WSeq α :=
cons a <|
@Seq.corec (Option α) (α × WSeq β)
(fun ⟨a, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, a, s')
| some (some b, s') =>
let a' := f a b
some (some a', a', s'))
(a, s)
#align stream.wseq.scanl Stream'.WSeq.scanl
/-- Get the weak sequence of initial segments of the input sequence -/
def inits (s : WSeq α) : WSeq (List α) :=
cons [] <|
@Seq.corec (Option (List α)) (Batteries.DList α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, l, s')
| some (some a, s') =>
let l' := l.push a
some (some l'.toList, l', s'))
(Batteries.DList.empty, s)
#align stream.wseq.inits Stream'.WSeq.inits
/-- Like take, but does not wait for a result. Calculates `n` steps of
computation and returns the sequence computed so far -/
def collect (s : WSeq α) (n : ℕ) : List α :=
(Seq.take n s).filterMap id
#align stream.wseq.collect Stream'.WSeq.collect
/-- Append two weak sequences. As with `Seq.append`, this may not use
the second sequence if the first one takes forever to compute -/
def append : WSeq α → WSeq α → WSeq α :=
Seq.append
#align stream.wseq.append Stream'.WSeq.append
/-- Map a function over a weak sequence -/
def map (f : α → β) : WSeq α → WSeq β :=
Seq.map (Option.map f)
#align stream.wseq.map Stream'.WSeq.map
/-- Flatten a sequence of weak sequences. (Note that this allows
empty sequences, unlike `Seq.join`.) -/
def join (S : WSeq (WSeq α)) : WSeq α :=
Seq.join
((fun o : Option (WSeq α) =>
match o with
| none => Seq1.ret none
| some s => (none, s)) <$>
S)
#align stream.wseq.join Stream'.WSeq.join
/-- Monadic bind operator for weak sequences -/
def bind (s : WSeq α) (f : α → WSeq β) : WSeq β :=
join (map f s)
#align stream.wseq.bind Stream'.WSeq.bind
/-- lift a relation to a relation over weak sequences -/
@[simp]
def LiftRelO (R : α → β → Prop) (C : WSeq α → WSeq β → Prop) :
Option (α × WSeq α) → Option (β × WSeq β) → Prop
| none, none => True
| some (a, s), some (b, t) => R a b ∧ C s t
| _, _ => False
#align stream.wseq.lift_rel_o Stream'.WSeq.LiftRelO
theorem LiftRelO.imp {R S : α → β → Prop} {C D : WSeq α → WSeq β → Prop} (H1 : ∀ a b, R a b → S a b)
(H2 : ∀ s t, C s t → D s t) : ∀ {o p}, LiftRelO R C o p → LiftRelO S D o p
| none, none, _ => trivial
| some (_, _), some (_, _), h => And.imp (H1 _ _) (H2 _ _) h
| none, some _, h => False.elim h
| some (_, _), none, h => False.elim h
#align stream.wseq.lift_rel_o.imp Stream'.WSeq.LiftRelO.imp
theorem LiftRelO.imp_right (R : α → β → Prop) {C D : WSeq α → WSeq β → Prop}
(H : ∀ s t, C s t → D s t) {o p} : LiftRelO R C o p → LiftRelO R D o p :=
LiftRelO.imp (fun _ _ => id) H
#align stream.wseq.lift_rel_o.imp_right Stream'.WSeq.LiftRelO.imp_right
/-- Definition of bisimilarity for weak sequences-/
@[simp]
def BisimO (R : WSeq α → WSeq α → Prop) : Option (α × WSeq α) → Option (α × WSeq α) → Prop :=
LiftRelO (· = ·) R
#align stream.wseq.bisim_o Stream'.WSeq.BisimO
theorem BisimO.imp {R S : WSeq α → WSeq α → Prop} (H : ∀ s t, R s t → S s t) {o p} :
BisimO R o p → BisimO S o p :=
LiftRelO.imp_right _ H
#align stream.wseq.bisim_o.imp Stream'.WSeq.BisimO.imp
/-- Two weak sequences are `LiftRel R` related if they are either both empty,
or they are both nonempty and the heads are `R` related and the tails are
`LiftRel R` related. (This is a coinductive definition.) -/
def LiftRel (R : α → β → Prop) (s : WSeq α) (t : WSeq β) : Prop :=
∃ C : WSeq α → WSeq β → Prop,
C s t ∧ ∀ {s t}, C s t → Computation.LiftRel (LiftRelO R C) (destruct s) (destruct t)
#align stream.wseq.lift_rel Stream'.WSeq.LiftRel
/-- If two sequences are equivalent, then they have the same values and
the same computational behavior (i.e. if one loops forever then so does
the other), although they may differ in the number of `think`s needed to
arrive at the answer. -/
def Equiv : WSeq α → WSeq α → Prop :=
LiftRel (· = ·)
#align stream.wseq.equiv Stream'.WSeq.Equiv
theorem liftRel_destruct {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t → Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t)
| ⟨R, h1, h2⟩ => by
refine Computation.LiftRel.imp ?_ _ _ (h2 h1)
apply LiftRelO.imp_right
exact fun s' t' h' => ⟨R, h', @h2⟩
#align stream.wseq.lift_rel_destruct Stream'.WSeq.liftRel_destruct
theorem liftRel_destruct_iff {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t ↔ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) :=
⟨liftRel_destruct, fun h =>
⟨fun s t =>
LiftRel R s t ∨ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t),
Or.inr h, fun {s t} h => by
have h : Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) := by
cases' h with h h
· exact liftRel_destruct h
· assumption
apply Computation.LiftRel.imp _ _ _ h
intro a b
apply LiftRelO.imp_right
intro s t
apply Or.inl⟩⟩
#align stream.wseq.lift_rel_destruct_iff Stream'.WSeq.liftRel_destruct_iff
-- Porting note: To avoid ambiguous notation, `~` became `~ʷ`.
infixl:50 " ~ʷ " => Equiv
theorem destruct_congr {s t : WSeq α} :
s ~ʷ t → Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct
#align stream.wseq.destruct_congr Stream'.WSeq.destruct_congr
theorem destruct_congr_iff {s t : WSeq α} :
s ~ʷ t ↔ Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct_iff
#align stream.wseq.destruct_congr_iff Stream'.WSeq.destruct_congr_iff
theorem LiftRel.refl (R : α → α → Prop) (H : Reflexive R) : Reflexive (LiftRel R) := fun s => by
refine ⟨(· = ·), rfl, fun {s t} (h : s = t) => ?_⟩
rw [← h]
apply Computation.LiftRel.refl
intro a
cases' a with a
· simp
· cases a
simp only [LiftRelO, and_true]
apply H
#align stream.wseq.lift_rel.refl Stream'.WSeq.LiftRel.refl
theorem LiftRelO.swap (R : α → β → Prop) (C) :
swap (LiftRelO R C) = LiftRelO (swap R) (swap C) := by
funext x y
rcases x with ⟨⟩ | ⟨hx, jx⟩ <;> rcases y with ⟨⟩ | ⟨hy, jy⟩ <;> rfl
#align stream.wseq.lift_rel_o.swap Stream'.WSeq.LiftRelO.swap
theorem LiftRel.swap_lem {R : α → β → Prop} {s1 s2} (h : LiftRel R s1 s2) :
LiftRel (swap R) s2 s1 := by
refine ⟨swap (LiftRel R), h, fun {s t} (h : LiftRel R t s) => ?_⟩
rw [← LiftRelO.swap, Computation.LiftRel.swap]
apply liftRel_destruct h
#align stream.wseq.lift_rel.swap_lem Stream'.WSeq.LiftRel.swap_lem
theorem LiftRel.swap (R : α → β → Prop) : swap (LiftRel R) = LiftRel (swap R) :=
funext fun _ => funext fun _ => propext ⟨LiftRel.swap_lem, LiftRel.swap_lem⟩
#align stream.wseq.lift_rel.swap Stream'.WSeq.LiftRel.swap
theorem LiftRel.symm (R : α → α → Prop) (H : Symmetric R) : Symmetric (LiftRel R) :=
fun s1 s2 (h : Function.swap (LiftRel R) s2 s1) => by rwa [LiftRel.swap, H.swap_eq] at h
#align stream.wseq.lift_rel.symm Stream'.WSeq.LiftRel.symm
theorem LiftRel.trans (R : α → α → Prop) (H : Transitive R) : Transitive (LiftRel R) :=
fun s t u h1 h2 => by
refine ⟨fun s u => ∃ t, LiftRel R s t ∧ LiftRel R t u, ⟨t, h1, h2⟩, fun {s u} h => ?_⟩
rcases h with ⟨t, h1, h2⟩
have h1 := liftRel_destruct h1
have h2 := liftRel_destruct h2
refine
Computation.liftRel_def.2
⟨(Computation.terminates_of_liftRel h1).trans (Computation.terminates_of_liftRel h2),
fun {a c} ha hc => ?_⟩
rcases h1.left ha with ⟨b, hb, t1⟩
have t2 := Computation.rel_of_liftRel h2 hb hc
cases' a with a <;> cases' c with c
· trivial
· cases b
· cases t2
· cases t1
· cases a
cases' b with b
· cases t1
· cases b
cases t2
· cases' a with a s
cases' b with b
· cases t1
cases' b with b t
cases' c with c u
cases' t1 with ab st
cases' t2 with bc tu
exact ⟨H ab bc, t, st, tu⟩
#align stream.wseq.lift_rel.trans Stream'.WSeq.LiftRel.trans
theorem LiftRel.equiv (R : α → α → Prop) : Equivalence R → Equivalence (LiftRel R)
| ⟨refl, symm, trans⟩ => ⟨LiftRel.refl R refl, @(LiftRel.symm R @symm), @(LiftRel.trans R @trans)⟩
#align stream.wseq.lift_rel.equiv Stream'.WSeq.LiftRel.equiv
@[refl]
theorem Equiv.refl : ∀ s : WSeq α, s ~ʷ s :=
LiftRel.refl (· = ·) Eq.refl
#align stream.wseq.equiv.refl Stream'.WSeq.Equiv.refl
@[symm]
theorem Equiv.symm : ∀ {s t : WSeq α}, s ~ʷ t → t ~ʷ s :=
@(LiftRel.symm (· = ·) (@Eq.symm _))
#align stream.wseq.equiv.symm Stream'.WSeq.Equiv.symm
@[trans]
theorem Equiv.trans : ∀ {s t u : WSeq α}, s ~ʷ t → t ~ʷ u → s ~ʷ u :=
@(LiftRel.trans (· = ·) (@Eq.trans _))
#align stream.wseq.equiv.trans Stream'.WSeq.Equiv.trans
theorem Equiv.equivalence : Equivalence (@Equiv α) :=
⟨@Equiv.refl _, @Equiv.symm _, @Equiv.trans _⟩
#align stream.wseq.equiv.equivalence Stream'.WSeq.Equiv.equivalence
open Computation
@[simp]
theorem destruct_nil : destruct (nil : WSeq α) = Computation.pure none :=
Computation.destruct_eq_pure rfl
#align stream.wseq.destruct_nil Stream'.WSeq.destruct_nil
@[simp]
theorem destruct_cons (a : α) (s) : destruct (cons a s) = Computation.pure (some (a, s)) :=
Computation.destruct_eq_pure <| by simp [destruct, cons, Computation.rmap]
#align stream.wseq.destruct_cons Stream'.WSeq.destruct_cons
@[simp]
theorem destruct_think (s : WSeq α) : destruct (think s) = (destruct s).think :=
Computation.destruct_eq_think <| by simp [destruct, think, Computation.rmap]
#align stream.wseq.destruct_think Stream'.WSeq.destruct_think
@[simp]
theorem seq_destruct_nil : Seq.destruct (nil : WSeq α) = none :=
Seq.destruct_nil
#align stream.wseq.seq_destruct_nil Stream'.WSeq.seq_destruct_nil
@[simp]
theorem seq_destruct_cons (a : α) (s) : Seq.destruct (cons a s) = some (some a, s) :=
Seq.destruct_cons _ _
#align stream.wseq.seq_destruct_cons Stream'.WSeq.seq_destruct_cons
@[simp]
theorem seq_destruct_think (s : WSeq α) : Seq.destruct (think s) = some (none, s) :=
Seq.destruct_cons _ _
#align stream.wseq.seq_destruct_think Stream'.WSeq.seq_destruct_think
@[simp]
theorem head_nil : head (nil : WSeq α) = Computation.pure none := by simp [head]
#align stream.wseq.head_nil Stream'.WSeq.head_nil
@[simp]
theorem head_cons (a : α) (s) : head (cons a s) = Computation.pure (some a) := by simp [head]
#align stream.wseq.head_cons Stream'.WSeq.head_cons
@[simp]
theorem head_think (s : WSeq α) : head (think s) = (head s).think := by simp [head]
#align stream.wseq.head_think Stream'.WSeq.head_think
@[simp]
theorem flatten_pure (s : WSeq α) : flatten (Computation.pure s) = s := by
refine Seq.eq_of_bisim (fun s1 s2 => flatten (Computation.pure s2) = s1) ?_ rfl
intro s' s h
rw [← h]
simp only [Seq.BisimO, flatten, Seq.omap, pure_def, Seq.corec_eq, destruct_pure]
cases Seq.destruct s with
| none => simp
| some val =>
cases' val with o s'
simp
#align stream.wseq.flatten_ret Stream'.WSeq.flatten_pure
@[simp]
theorem flatten_think (c : Computation (WSeq α)) : flatten c.think = think (flatten c) :=
Seq.destruct_eq_cons <| by simp [flatten, think]
#align stream.wseq.flatten_think Stream'.WSeq.flatten_think
@[simp]
theorem destruct_flatten (c : Computation (WSeq α)) : destruct (flatten c) = c >>= destruct := by
refine
Computation.eq_of_bisim
(fun c1 c2 => c1 = c2 ∨ ∃ c, c1 = destruct (flatten c) ∧ c2 = Computation.bind c destruct) ?_
(Or.inr ⟨c, rfl, rfl⟩)
intro c1 c2 h
exact
match c1, c2, h with
| c, _, Or.inl rfl => by cases c.destruct <;> simp
| _, _, Or.inr ⟨c, rfl, rfl⟩ => by
induction' c using Computation.recOn with a c' <;> simp
· cases (destruct a).destruct <;> simp
· exact Or.inr ⟨c', rfl, rfl⟩
#align stream.wseq.destruct_flatten Stream'.WSeq.destruct_flatten
theorem head_terminates_iff (s : WSeq α) : Terminates (head s) ↔ Terminates (destruct s) :=
terminates_map_iff _ (destruct s)
#align stream.wseq.head_terminates_iff Stream'.WSeq.head_terminates_iff
@[simp]
theorem tail_nil : tail (nil : WSeq α) = nil := by simp [tail]
#align stream.wseq.tail_nil Stream'.WSeq.tail_nil
@[simp]
theorem tail_cons (a : α) (s) : tail (cons a s) = s := by simp [tail]
#align stream.wseq.tail_cons Stream'.WSeq.tail_cons
@[simp]
theorem tail_think (s : WSeq α) : tail (think s) = (tail s).think := by simp [tail]
#align stream.wseq.tail_think Stream'.WSeq.tail_think
@[simp]
theorem dropn_nil (n) : drop (nil : WSeq α) n = nil := by induction n <;> simp [*, drop]
#align stream.wseq.dropn_nil Stream'.WSeq.dropn_nil
@[simp]
theorem dropn_cons (a : α) (s) (n) : drop (cons a s) (n + 1) = drop s n := by
induction n with
| zero => simp [drop]
| succ n n_ih =>
-- porting note (#10745): was `simp [*, drop]`.
simp [drop, ← n_ih]
#align stream.wseq.dropn_cons Stream'.WSeq.dropn_cons
@[simp]
theorem dropn_think (s : WSeq α) (n) : drop (think s) n = (drop s n).think := by
induction n <;> simp [*, drop]
#align stream.wseq.dropn_think Stream'.WSeq.dropn_think
theorem dropn_add (s : WSeq α) (m) : ∀ n, drop s (m + n) = drop (drop s m) n
| 0 => rfl
| n + 1 => congr_arg tail (dropn_add s m n)
#align stream.wseq.dropn_add Stream'.WSeq.dropn_add
theorem dropn_tail (s : WSeq α) (n) : drop (tail s) n = drop s (n + 1) := by
rw [Nat.add_comm]
symm
apply dropn_add
#align stream.wseq.dropn_tail Stream'.WSeq.dropn_tail
theorem get?_add (s : WSeq α) (m n) : get? s (m + n) = get? (drop s m) n :=
congr_arg head (dropn_add _ _ _)
#align stream.wseq.nth_add Stream'.WSeq.get?_add
theorem get?_tail (s : WSeq α) (n) : get? (tail s) n = get? s (n + 1) :=
congr_arg head (dropn_tail _ _)
#align stream.wseq.nth_tail Stream'.WSeq.get?_tail
@[simp]
theorem join_nil : join nil = (nil : WSeq α) :=
Seq.join_nil
#align stream.wseq.join_nil Stream'.WSeq.join_nil
@[simp]
theorem join_think (S : WSeq (WSeq α)) : join (think S) = think (join S) := by
simp only [join, think]
dsimp only [(· <$> ·)]
simp [join, Seq1.ret]
#align stream.wseq.join_think Stream'.WSeq.join_think
@[simp]
theorem join_cons (s : WSeq α) (S) : join (cons s S) = think (append s (join S)) := by
simp only [join, think]
dsimp only [(· <$> ·)]
simp [join, cons, append]
#align stream.wseq.join_cons Stream'.WSeq.join_cons
@[simp]
theorem nil_append (s : WSeq α) : append nil s = s :=
Seq.nil_append _
#align stream.wseq.nil_append Stream'.WSeq.nil_append
@[simp]
theorem cons_append (a : α) (s t) : append (cons a s) t = cons a (append s t) :=
Seq.cons_append _ _ _
#align stream.wseq.cons_append Stream'.WSeq.cons_append
@[simp]
theorem think_append (s t : WSeq α) : append (think s) t = think (append s t) :=
Seq.cons_append _ _ _
#align stream.wseq.think_append Stream'.WSeq.think_append
@[simp]
theorem append_nil (s : WSeq α) : append s nil = s :=
Seq.append_nil _
#align stream.wseq.append_nil Stream'.WSeq.append_nil
@[simp]
theorem append_assoc (s t u : WSeq α) : append (append s t) u = append s (append t u) :=
Seq.append_assoc _ _ _
#align stream.wseq.append_assoc Stream'.WSeq.append_assoc
/-- auxiliary definition of tail over weak sequences-/
@[simp]
def tail.aux : Option (α × WSeq α) → Computation (Option (α × WSeq α))
| none => Computation.pure none
| some (_, s) => destruct s
#align stream.wseq.tail.aux Stream'.WSeq.tail.aux
theorem destruct_tail (s : WSeq α) : destruct (tail s) = destruct s >>= tail.aux := by
simp only [tail, destruct_flatten, tail.aux]; rw [← bind_pure_comp, LawfulMonad.bind_assoc]
apply congr_arg; ext1 (_ | ⟨a, s⟩) <;> apply (@pure_bind Computation _ _ _ _ _ _).trans _ <;> simp
#align stream.wseq.destruct_tail Stream'.WSeq.destruct_tail
/-- auxiliary definition of drop over weak sequences-/
@[simp]
def drop.aux : ℕ → Option (α × WSeq α) → Computation (Option (α × WSeq α))
| 0 => Computation.pure
| n + 1 => fun a => tail.aux a >>= drop.aux n
#align stream.wseq.drop.aux Stream'.WSeq.drop.aux
theorem drop.aux_none : ∀ n, @drop.aux α n none = Computation.pure none
| 0 => rfl
| n + 1 =>
show Computation.bind (Computation.pure none) (drop.aux n) = Computation.pure none by
rw [ret_bind, drop.aux_none n]
#align stream.wseq.drop.aux_none Stream'.WSeq.drop.aux_none
theorem destruct_dropn : ∀ (s : WSeq α) (n), destruct (drop s n) = destruct s >>= drop.aux n
| s, 0 => (bind_pure' _).symm
| s, n + 1 => by
rw [← dropn_tail, destruct_dropn _ n, destruct_tail, LawfulMonad.bind_assoc]
rfl
#align stream.wseq.destruct_dropn Stream'.WSeq.destruct_dropn
theorem head_terminates_of_head_tail_terminates (s : WSeq α) [T : Terminates (head (tail s))] :
Terminates (head s) :=
(head_terminates_iff _).2 <| by
rcases (head_terminates_iff _).1 T with ⟨⟨a, h⟩⟩
simp? [tail] at h says simp only [tail, destruct_flatten] at h
rcases exists_of_mem_bind h with ⟨s', h1, _⟩
unfold Functor.map at h1
exact
let ⟨t, h3, _⟩ := Computation.exists_of_mem_map h1
Computation.terminates_of_mem h3
#align stream.wseq.head_terminates_of_head_tail_terminates Stream'.WSeq.head_terminates_of_head_tail_terminates
theorem destruct_some_of_destruct_tail_some {s : WSeq α} {a} (h : some a ∈ destruct (tail s)) :
∃ a', some a' ∈ destruct s := by
unfold tail Functor.map at h; simp only [destruct_flatten] at h
rcases exists_of_mem_bind h with ⟨t, tm, td⟩; clear h
rcases Computation.exists_of_mem_map tm with ⟨t', ht', ht2⟩; clear tm
cases' t' with t' <;> rw [← ht2] at td <;> simp only [destruct_nil] at td
· have := mem_unique td (ret_mem _)
contradiction
· exact ⟨_, ht'⟩
#align stream.wseq.destruct_some_of_destruct_tail_some Stream'.WSeq.destruct_some_of_destruct_tail_some
theorem head_some_of_head_tail_some {s : WSeq α} {a} (h : some a ∈ head (tail s)) :
∃ a', some a' ∈ head s := by
unfold head at h
rcases Computation.exists_of_mem_map h with ⟨o, md, e⟩; clear h
cases' o with o <;> [injection e; injection e with h']; clear h'
cases' destruct_some_of_destruct_tail_some md with a am
exact ⟨_, Computation.mem_map (@Prod.fst α (WSeq α) <$> ·) am⟩
#align stream.wseq.head_some_of_head_tail_some Stream'.WSeq.head_some_of_head_tail_some
theorem head_some_of_get?_some {s : WSeq α} {a n} (h : some a ∈ get? s n) :
∃ a', some a' ∈ head s := by
induction n generalizing a with
| zero => exact ⟨_, h⟩
| succ n IH =>
let ⟨a', h'⟩ := head_some_of_head_tail_some h
exact IH h'
#align stream.wseq.head_some_of_nth_some Stream'.WSeq.head_some_of_get?_some
instance productive_tail (s : WSeq α) [Productive s] : Productive (tail s) :=
⟨fun n => by rw [get?_tail]; infer_instance⟩
#align stream.wseq.productive_tail Stream'.WSeq.productive_tail
instance productive_dropn (s : WSeq α) [Productive s] (n) : Productive (drop s n) :=
⟨fun m => by rw [← get?_add]; infer_instance⟩
#align stream.wseq.productive_dropn Stream'.WSeq.productive_dropn
/-- Given a productive weak sequence, we can collapse all the `think`s to
produce a sequence. -/
def toSeq (s : WSeq α) [Productive s] : Seq α :=
⟨fun n => (get? s n).get,
fun {n} h => by
cases e : Computation.get (get? s (n + 1))
· assumption
have := Computation.mem_of_get_eq _ e
simp? [get?] at this h says simp only [get?] at this h
cases' head_some_of_head_tail_some this with a' h'
have := mem_unique h' (@Computation.mem_of_get_eq _ _ _ _ h)
contradiction⟩
#align stream.wseq.to_seq Stream'.WSeq.toSeq
theorem get?_terminates_le {s : WSeq α} {m n} (h : m ≤ n) :
Terminates (get? s n) → Terminates (get? s m) := by
induction' h with m' _ IH
exacts [id, fun T => IH (@head_terminates_of_head_tail_terminates _ _ T)]
#align stream.wseq.nth_terminates_le Stream'.WSeq.get?_terminates_le
theorem head_terminates_of_get?_terminates {s : WSeq α} {n} :
Terminates (get? s n) → Terminates (head s) :=
get?_terminates_le (Nat.zero_le n)
#align stream.wseq.head_terminates_of_nth_terminates Stream'.WSeq.head_terminates_of_get?_terminates
theorem destruct_terminates_of_get?_terminates {s : WSeq α} {n} (T : Terminates (get? s n)) :
Terminates (destruct s) :=
(head_terminates_iff _).1 <| head_terminates_of_get?_terminates T
#align stream.wseq.destruct_terminates_of_nth_terminates Stream'.WSeq.destruct_terminates_of_get?_terminates
theorem mem_rec_on {C : WSeq α → Prop} {a s} (M : a ∈ s) (h1 : ∀ b s', a = b ∨ C s' → C (cons b s'))
(h2 : ∀ s, C s → C (think s)) : C s := by
apply Seq.mem_rec_on M
intro o s' h; cases' o with b
· apply h2
cases h
· contradiction
· assumption
· apply h1
apply Or.imp_left _ h
intro h
injection h
#align stream.wseq.mem_rec_on Stream'.WSeq.mem_rec_on
@[simp]
theorem mem_think (s : WSeq α) (a) : a ∈ think s ↔ a ∈ s := by
cases' s with f al
change (some (some a) ∈ some none::f) ↔ some (some a) ∈ f
constructor <;> intro h
· apply (Stream'.eq_or_mem_of_mem_cons h).resolve_left
intro
injections
· apply Stream'.mem_cons_of_mem _ h
#align stream.wseq.mem_think Stream'.WSeq.mem_think
theorem eq_or_mem_iff_mem {s : WSeq α} {a a' s'} :
some (a', s') ∈ destruct s → (a ∈ s ↔ a = a' ∨ a ∈ s') := by
generalize e : destruct s = c; intro h
revert s
apply Computation.memRecOn h <;> [skip; intro c IH] <;> intro s <;>
induction' s using WSeq.recOn with x s s <;>
intro m <;>
have := congr_arg Computation.destruct m <;>
simp at this
· cases' this with i1 i2
rw [i1, i2]
cases' s' with f al
dsimp only [cons, (· ∈ ·), WSeq.Mem, Seq.Mem, Seq.cons]
have h_a_eq_a' : a = a' ↔ some (some a) = some (some a') := by simp
rw [h_a_eq_a']
refine ⟨Stream'.eq_or_mem_of_mem_cons, fun o => ?_⟩
· cases' o with e m
· rw [e]
apply Stream'.mem_cons
· exact Stream'.mem_cons_of_mem _ m
· simp [IH this]
#align stream.wseq.eq_or_mem_iff_mem Stream'.WSeq.eq_or_mem_iff_mem
@[simp]
theorem mem_cons_iff (s : WSeq α) (b) {a} : a ∈ cons b s ↔ a = b ∨ a ∈ s :=
eq_or_mem_iff_mem <| by simp [ret_mem]
#align stream.wseq.mem_cons_iff Stream'.WSeq.mem_cons_iff
theorem mem_cons_of_mem {s : WSeq α} (b) {a} (h : a ∈ s) : a ∈ cons b s :=
(mem_cons_iff _ _).2 (Or.inr h)
#align stream.wseq.mem_cons_of_mem Stream'.WSeq.mem_cons_of_mem
theorem mem_cons (s : WSeq α) (a) : a ∈ cons a s :=
(mem_cons_iff _ _).2 (Or.inl rfl)
#align stream.wseq.mem_cons Stream'.WSeq.mem_cons
theorem mem_of_mem_tail {s : WSeq α} {a} : a ∈ tail s → a ∈ s := by
intro h; have := h; cases' h with n e; revert s; simp only [Stream'.get]
induction' n with n IH <;> intro s <;> induction' s using WSeq.recOn with x s s <;>
simp <;> intro m e <;>
injections
· exact Or.inr m
· exact Or.inr m
· apply IH m
rw [e]
cases tail s
rfl
#align stream.wseq.mem_of_mem_tail Stream'.WSeq.mem_of_mem_tail
theorem mem_of_mem_dropn {s : WSeq α} {a} : ∀ {n}, a ∈ drop s n → a ∈ s
| 0, h => h
| n + 1, h => @mem_of_mem_dropn s a n (mem_of_mem_tail h)
#align stream.wseq.mem_of_mem_dropn Stream'.WSeq.mem_of_mem_dropn
theorem get?_mem {s : WSeq α} {a n} : some a ∈ get? s n → a ∈ s := by
revert s; induction' n with n IH <;> intro s h
· -- Porting note: This line is required to infer metavariables in
-- `Computation.exists_of_mem_map`.
dsimp only [get?, head] at h
rcases Computation.exists_of_mem_map h with ⟨o, h1, h2⟩
cases' o with o
· injection h2
injection h2 with h'
cases' o with a' s'
exact (eq_or_mem_iff_mem h1).2 (Or.inl h'.symm)
· have := @IH (tail s)
rw [get?_tail] at this
exact mem_of_mem_tail (this h)
#align stream.wseq.nth_mem Stream'.WSeq.get?_mem
theorem exists_get?_of_mem {s : WSeq α} {a} (h : a ∈ s) : ∃ n, some a ∈ get? s n := by
apply mem_rec_on h
· intro a' s' h
cases' h with h h
· exists 0
simp only [get?, drop, head_cons]
rw [h]
apply ret_mem
· cases' h with n h
exists n + 1
-- porting note (#10745): was `simp [get?]`.
simpa [get?]
· intro s' h
cases' h with n h
exists n
simp only [get?, dropn_think, head_think]
apply think_mem h
#align stream.wseq.exists_nth_of_mem Stream'.WSeq.exists_get?_of_mem
theorem exists_dropn_of_mem {s : WSeq α} {a} (h : a ∈ s) :
∃ n s', some (a, s') ∈ destruct (drop s n) :=
let ⟨n, h⟩ := exists_get?_of_mem h
⟨n, by
rcases (head_terminates_iff _).1 ⟨⟨_, h⟩⟩ with ⟨⟨o, om⟩⟩
have := Computation.mem_unique (Computation.mem_map _ om) h
cases' o with o
· injection this
injection this with i
cases' o with a' s'
dsimp at i
rw [i] at om
exact ⟨_, om⟩⟩
#align stream.wseq.exists_dropn_of_mem Stream'.WSeq.exists_dropn_of_mem
theorem liftRel_dropn_destruct {R : α → β → Prop} {s t} (H : LiftRel R s t) :
∀ n, Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct (drop s n)) (destruct (drop t n))
| 0 => liftRel_destruct H
| n + 1 => by
simp only [LiftRelO, drop, Nat.add_eq, Nat.add_zero, destruct_tail, tail.aux]
apply liftRel_bind
· apply liftRel_dropn_destruct H n
exact fun {a b} o =>
match a, b, o with
| none, none, _ => by
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
| some (a, s), some (b, t), ⟨_, h2⟩ => by simpa [tail.aux] using liftRel_destruct h2
#align stream.wseq.lift_rel_dropn_destruct Stream'.WSeq.liftRel_dropn_destruct
theorem exists_of_liftRel_left {R : α → β → Prop} {s t} (H : LiftRel R s t) {a} (h : a ∈ s) :
∃ b, b ∈ t ∧ R a b := by
let ⟨n, h⟩ := exists_get?_of_mem h
-- Porting note: This line is required to infer metavariables in
-- `Computation.exists_of_mem_map`.
dsimp only [get?, head] at h
let ⟨some (_, s'), sd, rfl⟩ := Computation.exists_of_mem_map h
let ⟨some (b, t'), td, ⟨ab, _⟩⟩ := (liftRel_dropn_destruct H n).left sd
exact ⟨b, get?_mem (Computation.mem_map (Prod.fst.{v, v} <$> ·) td), ab⟩
#align stream.wseq.exists_of_lift_rel_left Stream'.WSeq.exists_of_liftRel_left
theorem exists_of_liftRel_right {R : α → β → Prop} {s t} (H : LiftRel R s t) {b} (h : b ∈ t) :
∃ a, a ∈ s ∧ R a b := by rw [← LiftRel.swap] at H; exact exists_of_liftRel_left H h
#align stream.wseq.exists_of_lift_rel_right Stream'.WSeq.exists_of_liftRel_right
theorem head_terminates_of_mem {s : WSeq α} {a} (h : a ∈ s) : Terminates (head s) :=
let ⟨_, h⟩ := exists_get?_of_mem h
head_terminates_of_get?_terminates ⟨⟨_, h⟩⟩
#align stream.wseq.head_terminates_of_mem Stream'.WSeq.head_terminates_of_mem
theorem of_mem_append {s₁ s₂ : WSeq α} {a : α} : a ∈ append s₁ s₂ → a ∈ s₁ ∨ a ∈ s₂ :=
Seq.of_mem_append
#align stream.wseq.of_mem_append Stream'.WSeq.of_mem_append
theorem mem_append_left {s₁ s₂ : WSeq α} {a : α} : a ∈ s₁ → a ∈ append s₁ s₂ :=
Seq.mem_append_left
#align stream.wseq.mem_append_left Stream'.WSeq.mem_append_left
theorem exists_of_mem_map {f} {b : β} : ∀ {s : WSeq α}, b ∈ map f s → ∃ a, a ∈ s ∧ f a = b
| ⟨g, al⟩, h => by
let ⟨o, om, oe⟩ := Seq.exists_of_mem_map h
cases' o with a
· injection oe
injection oe with h'
exact ⟨a, om, h'⟩
#align stream.wseq.exists_of_mem_map Stream'.WSeq.exists_of_mem_map
@[simp]
theorem liftRel_nil (R : α → β → Prop) : LiftRel R nil nil := by
rw [liftRel_destruct_iff]
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
#align stream.wseq.lift_rel_nil Stream'.WSeq.liftRel_nil
@[simp]
theorem liftRel_cons (R : α → β → Prop) (a b s t) :
LiftRel R (cons a s) (cons b t) ↔ R a b ∧ LiftRel R s t := by
rw [liftRel_destruct_iff]
-- Porting note: These 2 theorems should be excluded.
simp [-liftRel_pure_left, -liftRel_pure_right]
#align stream.wseq.lift_rel_cons Stream'.WSeq.liftRel_cons
@[simp]
theorem liftRel_think_left (R : α → β → Prop) (s t) : LiftRel R (think s) t ↔ LiftRel R s t := by
rw [liftRel_destruct_iff, liftRel_destruct_iff]; simp
#align stream.wseq.lift_rel_think_left Stream'.WSeq.liftRel_think_left
@[simp]
theorem liftRel_think_right (R : α → β → Prop) (s t) : LiftRel R s (think t) ↔ LiftRel R s t := by
rw [liftRel_destruct_iff, liftRel_destruct_iff]; simp
#align stream.wseq.lift_rel_think_right Stream'.WSeq.liftRel_think_right
theorem cons_congr {s t : WSeq α} (a : α) (h : s ~ʷ t) : cons a s ~ʷ cons a t := by
unfold Equiv; simpa using h
#align stream.wseq.cons_congr Stream'.WSeq.cons_congr
theorem think_equiv (s : WSeq α) : think s ~ʷ s := by unfold Equiv; simpa using Equiv.refl _
#align stream.wseq.think_equiv Stream'.WSeq.think_equiv
theorem think_congr {s t : WSeq α} (h : s ~ʷ t) : think s ~ʷ think t := by
unfold Equiv; simpa using h
#align stream.wseq.think_congr Stream'.WSeq.think_congr
theorem head_congr : ∀ {s t : WSeq α}, s ~ʷ t → head s ~ head t := by
suffices ∀ {s t : WSeq α}, s ~ʷ t → ∀ {o}, o ∈ head s → o ∈ head t from fun s t h o =>
⟨this h, this h.symm⟩
intro s t h o ho
rcases @Computation.exists_of_mem_map _ _ _ _ (destruct s) ho with ⟨ds, dsm, dse⟩
rw [← dse]
cases' destruct_congr h with l r
rcases l dsm with ⟨dt, dtm, dst⟩
cases' ds with a <;> cases' dt with b
· apply Computation.mem_map _ dtm
· cases b
cases dst
· cases a
cases dst
· cases' a with a s'
cases' b with b t'
rw [dst.left]
exact @Computation.mem_map _ _ (@Functor.map _ _ (α × WSeq α) _ Prod.fst)
(some (b, t')) (destruct t) dtm
#align stream.wseq.head_congr Stream'.WSeq.head_congr
theorem flatten_equiv {c : Computation (WSeq α)} {s} (h : s ∈ c) : flatten c ~ʷ s := by
apply Computation.memRecOn h
· simp [Equiv.refl]
· intro s'
apply Equiv.trans
simp [think_equiv]
#align stream.wseq.flatten_equiv Stream'.WSeq.flatten_equiv
theorem liftRel_flatten {R : α → β → Prop} {c1 : Computation (WSeq α)} {c2 : Computation (WSeq β)}
(h : c1.LiftRel (LiftRel R) c2) : LiftRel R (flatten c1) (flatten c2) :=
let S s t := ∃ c1 c2, s = flatten c1 ∧ t = flatten c2 ∧ Computation.LiftRel (LiftRel R) c1 c2
⟨S, ⟨c1, c2, rfl, rfl, h⟩, fun {s t} h =>
match s, t, h with
| _, _, ⟨c1, c2, rfl, rfl, h⟩ => by
simp only [destruct_flatten]; apply liftRel_bind _ _ h
intro a b ab; apply Computation.LiftRel.imp _ _ _ (liftRel_destruct ab)
intro a b; apply LiftRelO.imp_right
intro s t h; refine ⟨Computation.pure s, Computation.pure t, ?_, ?_, ?_⟩ <;>
-- Porting note: These 2 theorems should be excluded.
simp [h, -liftRel_pure_left, -liftRel_pure_right]⟩
#align stream.wseq.lift_rel_flatten Stream'.WSeq.liftRel_flatten
theorem flatten_congr {c1 c2 : Computation (WSeq α)} :
Computation.LiftRel Equiv c1 c2 → flatten c1 ~ʷ flatten c2 :=
liftRel_flatten
#align stream.wseq.flatten_congr Stream'.WSeq.flatten_congr
theorem tail_congr {s t : WSeq α} (h : s ~ʷ t) : tail s ~ʷ tail t := by
apply flatten_congr
dsimp only [(· <$> ·)]; rw [← Computation.bind_pure, ← Computation.bind_pure]
apply liftRel_bind _ _ (destruct_congr h)
intro a b h; simp only [comp_apply, liftRel_pure]
cases' a with a <;> cases' b with b
· trivial
· cases h
· cases a
cases h
· cases' a with a s'
cases' b with b t'
exact h.right
#align stream.wseq.tail_congr Stream'.WSeq.tail_congr
theorem dropn_congr {s t : WSeq α} (h : s ~ʷ t) (n) : drop s n ~ʷ drop t n := by
induction n <;> simp [*, tail_congr, drop]
#align stream.wseq.dropn_congr Stream'.WSeq.dropn_congr
theorem get?_congr {s t : WSeq α} (h : s ~ʷ t) (n) : get? s n ~ get? t n :=
head_congr (dropn_congr h _)
#align stream.wseq.nth_congr Stream'.WSeq.get?_congr
theorem mem_congr {s t : WSeq α} (h : s ~ʷ t) (a) : a ∈ s ↔ a ∈ t :=
suffices ∀ {s t : WSeq α}, s ~ʷ t → a ∈ s → a ∈ t from ⟨this h, this h.symm⟩
fun {_ _} h as =>
let ⟨_, hn⟩ := exists_get?_of_mem as
get?_mem ((get?_congr h _ _).1 hn)
#align stream.wseq.mem_congr Stream'.WSeq.mem_congr
theorem productive_congr {s t : WSeq α} (h : s ~ʷ t) : Productive s ↔ Productive t := by
simp only [productive_iff]; exact forall_congr' fun n => terminates_congr <| get?_congr h _
#align stream.wseq.productive_congr Stream'.WSeq.productive_congr
theorem Equiv.ext {s t : WSeq α} (h : ∀ n, get? s n ~ get? t n) : s ~ʷ t :=
⟨fun s t => ∀ n, get? s n ~ get? t n, h, fun {s t} h => by
refine liftRel_def.2 ⟨?_, ?_⟩
· rw [← head_terminates_iff, ← head_terminates_iff]
exact terminates_congr (h 0)
· intro a b ma mb
cases' a with a <;> cases' b with b
· trivial
· injection mem_unique (Computation.mem_map _ ma) ((h 0 _).2 (Computation.mem_map _ mb))
· injection mem_unique (Computation.mem_map _ ma) ((h 0 _).2 (Computation.mem_map _ mb))
· cases' a with a s'
cases' b with b t'
injection mem_unique (Computation.mem_map _ ma) ((h 0 _).2 (Computation.mem_map _ mb)) with
ab
refine ⟨ab, fun n => ?_⟩
refine
(get?_congr (flatten_equiv (Computation.mem_map _ ma)) n).symm.trans
((?_ : get? (tail s) n ~ get? (tail t) n).trans
(get?_congr (flatten_equiv (Computation.mem_map _ mb)) n))
rw [get?_tail, get?_tail]
apply h⟩
#align stream.wseq.equiv.ext Stream'.WSeq.Equiv.ext
theorem length_eq_map (s : WSeq α) : length s = Computation.map List.length (toList s) := by
refine
Computation.eq_of_bisim
(fun c1 c2 =>
∃ (l : List α) (s : WSeq α),
c1 = Computation.corec (fun ⟨n, s⟩ =>
match Seq.destruct s with
| none => Sum.inl n
| some (none, s') => Sum.inr (n, s')
| some (some _, s') => Sum.inr (n + 1, s')) (l.length, s) ∧
c2 = Computation.map List.length (Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l, s)))
?_ ⟨[], s, rfl, rfl⟩
intro s1 s2 h; rcases h with ⟨l, s, h⟩; rw [h.left, h.right]
induction' s using WSeq.recOn with a s s <;> simp [toList, nil, cons, think, length]
· refine ⟨a::l, s, ?_, ?_⟩ <;> simp
· refine ⟨l, s, ?_, ?_⟩ <;> simp
#align stream.wseq.length_eq_map Stream'.WSeq.length_eq_map
@[simp]
theorem ofList_nil : ofList [] = (nil : WSeq α) :=
rfl
#align stream.wseq.of_list_nil Stream'.WSeq.ofList_nil
@[simp]
theorem ofList_cons (a : α) (l) : ofList (a::l) = cons a (ofList l) :=
show Seq.map some (Seq.ofList (a::l)) = Seq.cons (some a) (Seq.map some (Seq.ofList l)) by simp
#align stream.wseq.of_list_cons Stream'.WSeq.ofList_cons
@[simp]
theorem toList'_nil (l : List α) :
Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l, nil) = Computation.pure l.reverse :=
destruct_eq_pure rfl
#align stream.wseq.to_list'_nil Stream'.WSeq.toList'_nil
@[simp]
theorem toList'_cons (l : List α) (s : WSeq α) (a : α) :
Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l, cons a s) =
(Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (a::l, s)).think :=
destruct_eq_think <| by simp [toList, cons]
#align stream.wseq.to_list'_cons Stream'.WSeq.toList'_cons
@[simp]
theorem toList'_think (l : List α) (s : WSeq α) :
Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l, think s) =
(Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l, s)).think :=
destruct_eq_think <| by simp [toList, think]
#align stream.wseq.to_list'_think Stream'.WSeq.toList'_think
| Mathlib/Data/Seq/WSeq.lean | 1,303 | 1,327 | theorem toList'_map (l : List α) (s : WSeq α) :
Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a :: l, s')) (l, s) = (l.reverse ++ ·) <$> toList s := by |
refine
Computation.eq_of_bisim
(fun c1 c2 =>
∃ (l' : List α) (s : WSeq α),
c1 = Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l' ++ l, s) ∧
c2 = Computation.map (l.reverse ++ ·) (Computation.corec (fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s')) (l', s)))
?_ ⟨[], s, rfl, rfl⟩
intro s1 s2 h; rcases h with ⟨l', s, h⟩; rw [h.left, h.right]
induction' s using WSeq.recOn with a s s <;> simp [toList, nil, cons, think, length]
· refine ⟨a::l', s, ?_, ?_⟩ <;> simp
· refine ⟨l', s, ?_, ?_⟩ <;> simp
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.ContMDiff.Defs
/-!
## Basic properties of smooth functions between manifolds
In this file, we show that standard operations on smooth maps between smooth manifolds are smooth:
* `ContMDiffOn.comp` gives the invariance of the `Cⁿ` property under composition
* `contMDiff_id` gives the smoothness of the identity
* `contMDiff_const` gives the smoothness of constant functions
* `contMDiff_inclusion` shows that the inclusion between open sets of a topological space is smooth
* `contMDiff_openEmbedding` shows that if `M` has a `ChartedSpace` structure induced by an open
embedding `e : M → H`, then `e` is smooth.
## Tags
chain rule, manifolds, higher derivative
-/
open Set Filter Function
open scoped Topology Manifold
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
-- declare a smooth manifold `M` over the pair `(E, H)`.
{E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) {M : Type*} [TopologicalSpace M] [ChartedSpace H M]
[SmoothManifoldWithCorners I M]
-- declare a smooth manifold `M'` over the pair `(E', H')`.
{E' : Type*}
[NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H']
(I' : ModelWithCorners 𝕜 E' H') {M' : Type*} [TopologicalSpace M'] [ChartedSpace H' M']
[SmoothManifoldWithCorners I' M']
-- declare a manifold `M''` over the pair `(E'', H'')`.
{E'' : Type*}
[NormedAddCommGroup E''] [NormedSpace 𝕜 E''] {H'' : Type*} [TopologicalSpace H'']
{I'' : ModelWithCorners 𝕜 E'' H''} {M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M'']
-- declare functions, sets, points and smoothness indices
{e : PartialHomeomorph M H}
{e' : PartialHomeomorph M' H'} {f f₁ : M → M'} {s s₁ t : Set M} {x : M} {m n : ℕ∞}
variable {I I'}
/-! ### Smoothness of the composition of smooth functions between manifolds -/
section Composition
/-- The composition of `C^n` functions within domains at points is `C^n`. -/
theorem ContMDiffWithinAt.comp {t : Set M'} {g : M' → M''} (x : M)
(hg : ContMDiffWithinAt I' I'' n g t (f x)) (hf : ContMDiffWithinAt I I' n f s x)
(st : MapsTo f s t) : ContMDiffWithinAt I I'' n (g ∘ f) s x := by
rw [contMDiffWithinAt_iff] at hg hf ⊢
refine ⟨hg.1.comp hf.1 st, ?_⟩
set e := extChartAt I x
set e' := extChartAt I' (f x)
have : e' (f x) = (writtenInExtChartAt I I' x f) (e x) := by simp only [e, e', mfld_simps]
rw [this] at hg
have A : ∀ᶠ y in 𝓝[e.symm ⁻¹' s ∩ range I] e x, f (e.symm y) ∈ t ∧ f (e.symm y) ∈ e'.source := by
simp only [e, ← map_extChartAt_nhdsWithin, eventually_map]
filter_upwards [hf.1.tendsto (extChartAt_source_mem_nhds I' (f x)),
inter_mem_nhdsWithin s (extChartAt_source_mem_nhds I x)]
rintro x' (hfx' : f x' ∈ e'.source) ⟨hx's, hx'⟩
simp only [e.map_source hx', true_and_iff, e.left_inv hx', st hx's, *]
refine ((hg.2.comp _ (hf.2.mono inter_subset_right) inter_subset_left).mono_of_mem
(inter_mem ?_ self_mem_nhdsWithin)).congr_of_eventuallyEq ?_ ?_
· filter_upwards [A]
rintro x' ⟨ht, hfx'⟩
simp only [*, mem_preimage, writtenInExtChartAt, (· ∘ ·), mem_inter_iff, e'.left_inv,
true_and_iff]
exact mem_range_self _
· filter_upwards [A]
rintro x' ⟨-, hfx'⟩
simp only [*, (· ∘ ·), writtenInExtChartAt, e'.left_inv]
· simp only [e, e', writtenInExtChartAt, (· ∘ ·), mem_extChartAt_source, e.left_inv, e'.left_inv]
#align cont_mdiff_within_at.comp ContMDiffWithinAt.comp
/-- See note [comp_of_eq lemmas] -/
theorem ContMDiffWithinAt.comp_of_eq {t : Set M'} {g : M' → M''} {x : M} {y : M'}
(hg : ContMDiffWithinAt I' I'' n g t y) (hf : ContMDiffWithinAt I I' n f s x)
(st : MapsTo f s t) (hx : f x = y) : ContMDiffWithinAt I I'' n (g ∘ f) s x := by
subst hx; exact hg.comp x hf st
#align cont_mdiff_within_at.comp_of_eq ContMDiffWithinAt.comp_of_eq
/-- The composition of `C^∞` functions within domains at points is `C^∞`. -/
nonrec theorem SmoothWithinAt.comp {t : Set M'} {g : M' → M''} (x : M)
(hg : SmoothWithinAt I' I'' g t (f x)) (hf : SmoothWithinAt I I' f s x) (st : MapsTo f s t) :
SmoothWithinAt I I'' (g ∘ f) s x :=
hg.comp x hf st
#align smooth_within_at.comp SmoothWithinAt.comp
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContMDiffOn.comp {t : Set M'} {g : M' → M''} (hg : ContMDiffOn I' I'' n g t)
(hf : ContMDiffOn I I' n f s) (st : s ⊆ f ⁻¹' t) : ContMDiffOn I I'' n (g ∘ f) s := fun x hx =>
(hg _ (st hx)).comp x (hf x hx) st
#align cont_mdiff_on.comp ContMDiffOn.comp
/-- The composition of `C^∞` functions on domains is `C^∞`. -/
nonrec theorem SmoothOn.comp {t : Set M'} {g : M' → M''} (hg : SmoothOn I' I'' g t)
(hf : SmoothOn I I' f s) (st : s ⊆ f ⁻¹' t) : SmoothOn I I'' (g ∘ f) s :=
hg.comp hf st
#align smooth_on.comp SmoothOn.comp
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContMDiffOn.comp' {t : Set M'} {g : M' → M''} (hg : ContMDiffOn I' I'' n g t)
(hf : ContMDiffOn I I' n f s) : ContMDiffOn I I'' n (g ∘ f) (s ∩ f ⁻¹' t) :=
hg.comp (hf.mono inter_subset_left) inter_subset_right
#align cont_mdiff_on.comp' ContMDiffOn.comp'
/-- The composition of `C^∞` functions is `C^∞`. -/
nonrec theorem SmoothOn.comp' {t : Set M'} {g : M' → M''} (hg : SmoothOn I' I'' g t)
(hf : SmoothOn I I' f s) : SmoothOn I I'' (g ∘ f) (s ∩ f ⁻¹' t) :=
hg.comp' hf
#align smooth_on.comp' SmoothOn.comp'
/-- The composition of `C^n` functions is `C^n`. -/
theorem ContMDiff.comp {g : M' → M''} (hg : ContMDiff I' I'' n g) (hf : ContMDiff I I' n f) :
ContMDiff I I'' n (g ∘ f) := by
rw [← contMDiffOn_univ] at hf hg ⊢
exact hg.comp hf subset_preimage_univ
#align cont_mdiff.comp ContMDiff.comp
/-- The composition of `C^∞` functions is `C^∞`. -/
nonrec theorem Smooth.comp {g : M' → M''} (hg : Smooth I' I'' g) (hf : Smooth I I' f) :
Smooth I I'' (g ∘ f) :=
hg.comp hf
#align smooth.comp Smooth.comp
/-- The composition of `C^n` functions within domains at points is `C^n`. -/
theorem ContMDiffWithinAt.comp' {t : Set M'} {g : M' → M''} (x : M)
(hg : ContMDiffWithinAt I' I'' n g t (f x)) (hf : ContMDiffWithinAt I I' n f s x) :
ContMDiffWithinAt I I'' n (g ∘ f) (s ∩ f ⁻¹' t) x :=
hg.comp x (hf.mono inter_subset_left) inter_subset_right
#align cont_mdiff_within_at.comp' ContMDiffWithinAt.comp'
/-- The composition of `C^∞` functions within domains at points is `C^∞`. -/
nonrec theorem SmoothWithinAt.comp' {t : Set M'} {g : M' → M''} (x : M)
(hg : SmoothWithinAt I' I'' g t (f x)) (hf : SmoothWithinAt I I' f s x) :
SmoothWithinAt I I'' (g ∘ f) (s ∩ f ⁻¹' t) x :=
hg.comp' x hf
#align smooth_within_at.comp' SmoothWithinAt.comp'
/-- `g ∘ f` is `C^n` within `s` at `x` if `g` is `C^n` at `f x` and
`f` is `C^n` within `s` at `x`. -/
theorem ContMDiffAt.comp_contMDiffWithinAt {g : M' → M''} (x : M)
(hg : ContMDiffAt I' I'' n g (f x)) (hf : ContMDiffWithinAt I I' n f s x) :
ContMDiffWithinAt I I'' n (g ∘ f) s x :=
hg.comp x hf (mapsTo_univ _ _)
#align cont_mdiff_at.comp_cont_mdiff_within_at ContMDiffAt.comp_contMDiffWithinAt
/-- `g ∘ f` is `C^∞` within `s` at `x` if `g` is `C^∞` at `f x` and
`f` is `C^∞` within `s` at `x`. -/
theorem SmoothAt.comp_smoothWithinAt {g : M' → M''} (x : M) (hg : SmoothAt I' I'' g (f x))
(hf : SmoothWithinAt I I' f s x) : SmoothWithinAt I I'' (g ∘ f) s x :=
hg.comp_contMDiffWithinAt x hf
#align smooth_at.comp_smooth_within_at SmoothAt.comp_smoothWithinAt
/-- The composition of `C^n` functions at points is `C^n`. -/
nonrec theorem ContMDiffAt.comp {g : M' → M''} (x : M) (hg : ContMDiffAt I' I'' n g (f x))
(hf : ContMDiffAt I I' n f x) : ContMDiffAt I I'' n (g ∘ f) x :=
hg.comp x hf (mapsTo_univ _ _)
#align cont_mdiff_at.comp ContMDiffAt.comp
/-- See note [comp_of_eq lemmas] -/
theorem ContMDiffAt.comp_of_eq {g : M' → M''} {x : M} {y : M'} (hg : ContMDiffAt I' I'' n g y)
(hf : ContMDiffAt I I' n f x) (hx : f x = y) : ContMDiffAt I I'' n (g ∘ f) x := by
subst hx; exact hg.comp x hf
#align cont_mdiff_at.comp_of_eq ContMDiffAt.comp_of_eq
/-- The composition of `C^∞` functions at points is `C^∞`. -/
nonrec theorem SmoothAt.comp {g : M' → M''} (x : M) (hg : SmoothAt I' I'' g (f x))
(hf : SmoothAt I I' f x) : SmoothAt I I'' (g ∘ f) x :=
hg.comp x hf
#align smooth_at.comp SmoothAt.comp
theorem ContMDiff.comp_contMDiffOn {f : M → M'} {g : M' → M''} {s : Set M}
(hg : ContMDiff I' I'' n g) (hf : ContMDiffOn I I' n f s) : ContMDiffOn I I'' n (g ∘ f) s :=
hg.contMDiffOn.comp hf Set.subset_preimage_univ
#align cont_mdiff.comp_cont_mdiff_on ContMDiff.comp_contMDiffOn
theorem Smooth.comp_smoothOn {f : M → M'} {g : M' → M''} {s : Set M} (hg : Smooth I' I'' g)
(hf : SmoothOn I I' f s) : SmoothOn I I'' (g ∘ f) s :=
hg.smoothOn.comp hf Set.subset_preimage_univ
#align smooth.comp_smooth_on Smooth.comp_smoothOn
theorem ContMDiffOn.comp_contMDiff {t : Set M'} {g : M' → M''} (hg : ContMDiffOn I' I'' n g t)
(hf : ContMDiff I I' n f) (ht : ∀ x, f x ∈ t) : ContMDiff I I'' n (g ∘ f) :=
contMDiffOn_univ.mp <| hg.comp hf.contMDiffOn fun x _ => ht x
#align cont_mdiff_on.comp_cont_mdiff ContMDiffOn.comp_contMDiff
theorem SmoothOn.comp_smooth {t : Set M'} {g : M' → M''} (hg : SmoothOn I' I'' g t)
(hf : Smooth I I' f) (ht : ∀ x, f x ∈ t) : Smooth I I'' (g ∘ f) :=
hg.comp_contMDiff hf ht
#align smooth_on.comp_smooth SmoothOn.comp_smooth
end Composition
/-! ### The identity is smooth -/
section id
theorem contMDiff_id : ContMDiff I I n (id : M → M) :=
ContMDiff.of_le
((contDiffWithinAt_localInvariantProp I I ∞).liftProp_id (contDiffWithinAtProp_id I)) le_top
#align cont_mdiff_id contMDiff_id
theorem smooth_id : Smooth I I (id : M → M) :=
contMDiff_id
#align smooth_id smooth_id
theorem contMDiffOn_id : ContMDiffOn I I n (id : M → M) s :=
contMDiff_id.contMDiffOn
#align cont_mdiff_on_id contMDiffOn_id
theorem smoothOn_id : SmoothOn I I (id : M → M) s :=
contMDiffOn_id
#align smooth_on_id smoothOn_id
theorem contMDiffAt_id : ContMDiffAt I I n (id : M → M) x :=
contMDiff_id.contMDiffAt
#align cont_mdiff_at_id contMDiffAt_id
theorem smoothAt_id : SmoothAt I I (id : M → M) x :=
contMDiffAt_id
#align smooth_at_id smoothAt_id
theorem contMDiffWithinAt_id : ContMDiffWithinAt I I n (id : M → M) s x :=
contMDiffAt_id.contMDiffWithinAt
#align cont_mdiff_within_at_id contMDiffWithinAt_id
theorem smoothWithinAt_id : SmoothWithinAt I I (id : M → M) s x :=
contMDiffWithinAt_id
#align smooth_within_at_id smoothWithinAt_id
end id
/-! ### Constants are smooth -/
section id
variable {c : M'}
theorem contMDiff_const : ContMDiff I I' n fun _ : M => c := by
intro x
refine ⟨continuousWithinAt_const, ?_⟩
simp only [ContDiffWithinAtProp, (· ∘ ·)]
exact contDiffWithinAt_const
#align cont_mdiff_const contMDiff_const
@[to_additive]
theorem contMDiff_one [One M'] : ContMDiff I I' n (1 : M → M') := by
simp only [Pi.one_def, contMDiff_const]
#align cont_mdiff_one contMDiff_one
#align cont_mdiff_zero contMDiff_zero
theorem smooth_const : Smooth I I' fun _ : M => c :=
contMDiff_const
#align smooth_const smooth_const
@[to_additive]
| Mathlib/Geometry/Manifold/ContMDiff/Basic.lean | 262 | 262 | theorem smooth_one [One M'] : Smooth I I' (1 : M → M') := by | simp only [Pi.one_def, smooth_const]
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johan Commelin
-/
import Mathlib.Analysis.Analytic.Basic
import Mathlib.Combinatorics.Enumerative.Composition
#align_import analysis.analytic.composition from "leanprover-community/mathlib"@"ce11c3c2a285bbe6937e26d9792fda4e51f3fe1a"
/-!
# Composition of analytic functions
In this file we prove that the composition of analytic functions is analytic.
The argument is the following. Assume `g z = ∑' qₙ (z, ..., z)` and `f y = ∑' pₖ (y, ..., y)`. Then
`g (f y) = ∑' qₙ (∑' pₖ (y, ..., y), ..., ∑' pₖ (y, ..., y))
= ∑' qₙ (p_{i₁} (y, ..., y), ..., p_{iₙ} (y, ..., y))`.
For each `n` and `i₁, ..., iₙ`, define a `i₁ + ... + iₙ` multilinear function mapping
`(y₀, ..., y_{i₁ + ... + iₙ - 1})` to
`qₙ (p_{i₁} (y₀, ..., y_{i₁-1}), p_{i₂} (y_{i₁}, ..., y_{i₁ + i₂ - 1}), ..., p_{iₙ} (....)))`.
Then `g ∘ f` is obtained by summing all these multilinear functions.
To formalize this, we use compositions of an integer `N`, i.e., its decompositions into
a sum `i₁ + ... + iₙ` of positive integers. Given such a composition `c` and two formal
multilinear series `q` and `p`, let `q.comp_along_composition p c` be the above multilinear
function. Then the `N`-th coefficient in the power series expansion of `g ∘ f` is the sum of these
terms over all `c : composition N`.
To complete the proof, we need to show that this power series has a positive radius of convergence.
This follows from the fact that `composition N` has cardinality `2^(N-1)` and estimates on
the norm of `qₙ` and `pₖ`, which give summability. We also need to show that it indeed converges to
`g ∘ f`. For this, we note that the composition of partial sums converges to `g ∘ f`, and that it
corresponds to a part of the whole sum, on a subset that increases to the whole space. By
summability of the norms, this implies the overall convergence.
## Main results
* `q.comp p` is the formal composition of the formal multilinear series `q` and `p`.
* `HasFPowerSeriesAt.comp` states that if two functions `g` and `f` admit power series expansions
`q` and `p`, then `g ∘ f` admits a power series expansion given by `q.comp p`.
* `AnalyticAt.comp` states that the composition of analytic functions is analytic.
* `FormalMultilinearSeries.comp_assoc` states that composition is associative on formal
multilinear series.
## Implementation details
The main technical difficulty is to write down things. In particular, we need to define precisely
`q.comp_along_composition p c` and to show that it is indeed a continuous multilinear
function. This requires a whole interface built on the class `Composition`. Once this is set,
the main difficulty is to reorder the sums, writing the composition of the partial sums as a sum
over some subset of `Σ n, composition n`. We need to check that the reordering is a bijection,
running over difficulties due to the dependent nature of the types under consideration, that are
controlled thanks to the interface for `Composition`.
The associativity of composition on formal multilinear series is a nontrivial result: it does not
follow from the associativity of composition of analytic functions, as there is no uniqueness for
the formal multilinear series representing a function (and also, it holds even when the radius of
convergence of the series is `0`). Instead, we give a direct proof, which amounts to reordering
double sums in a careful way. The change of variables is a canonical (combinatorial) bijection
`Composition.sigmaEquivSigmaPi` between `(Σ (a : composition n), composition a.length)` and
`(Σ (c : composition n), Π (i : fin c.length), composition (c.blocks_fun i))`, and is described
in more details below in the paragraph on associativity.
-/
noncomputable section
variable {𝕜 : Type*} {E F G H : Type*}
open Filter List
open scoped Topology Classical NNReal ENNReal
section Topological
variable [CommRing 𝕜] [AddCommGroup E] [AddCommGroup F] [AddCommGroup G]
variable [Module 𝕜 E] [Module 𝕜 F] [Module 𝕜 G]
variable [TopologicalSpace E] [TopologicalSpace F] [TopologicalSpace G]
/-! ### Composing formal multilinear series -/
namespace FormalMultilinearSeries
variable [TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
variable [TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
variable [TopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
/-!
In this paragraph, we define the composition of formal multilinear series, by summing over all
possible compositions of `n`.
-/
/-- Given a formal multilinear series `p`, a composition `c` of `n` and the index `i` of a
block of `c`, we may define a function on `fin n → E` by picking the variables in the `i`-th block
of `n`, and applying the corresponding coefficient of `p` to these variables. This function is
called `p.apply_composition c v i` for `v : fin n → E` and `i : fin c.length`. -/
def applyComposition (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (c : Composition n) :
(Fin n → E) → Fin c.length → F := fun v i => p (c.blocksFun i) (v ∘ c.embedding i)
#align formal_multilinear_series.apply_composition FormalMultilinearSeries.applyComposition
theorem applyComposition_ones (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
p.applyComposition (Composition.ones n) = fun v i =>
p 1 fun _ => v (Fin.castLE (Composition.length_le _) i) := by
funext v i
apply p.congr (Composition.ones_blocksFun _ _)
intro j hjn hj1
obtain rfl : j = 0 := by omega
refine congr_arg v ?_
rw [Fin.ext_iff, Fin.coe_castLE, Composition.ones_embedding, Fin.val_mk]
#align formal_multilinear_series.apply_composition_ones FormalMultilinearSeries.applyComposition_ones
theorem applyComposition_single (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (hn : 0 < n)
(v : Fin n → E) : p.applyComposition (Composition.single n hn) v = fun _j => p n v := by
ext j
refine p.congr (by simp) fun i hi1 hi2 => ?_
dsimp
congr 1
convert Composition.single_embedding hn ⟨i, hi2⟩ using 1
cases' j with j_val j_property
have : j_val = 0 := le_bot_iff.1 (Nat.lt_succ_iff.1 j_property)
congr!
simp
#align formal_multilinear_series.apply_composition_single FormalMultilinearSeries.applyComposition_single
@[simp]
theorem removeZero_applyComposition (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ}
(c : Composition n) : p.removeZero.applyComposition c = p.applyComposition c := by
ext v i
simp [applyComposition, zero_lt_one.trans_le (c.one_le_blocksFun i), removeZero_of_pos]
#align formal_multilinear_series.remove_zero_apply_composition FormalMultilinearSeries.removeZero_applyComposition
/-- Technical lemma stating how `p.apply_composition` commutes with updating variables. This
will be the key point to show that functions constructed from `apply_composition` retain
multilinearity. -/
theorem applyComposition_update (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (c : Composition n)
(j : Fin n) (v : Fin n → E) (z : E) :
p.applyComposition c (Function.update v j z) =
Function.update (p.applyComposition c v) (c.index j)
(p (c.blocksFun (c.index j))
(Function.update (v ∘ c.embedding (c.index j)) (c.invEmbedding j) z)) := by
ext k
by_cases h : k = c.index j
· rw [h]
let r : Fin (c.blocksFun (c.index j)) → Fin n := c.embedding (c.index j)
simp only [Function.update_same]
change p (c.blocksFun (c.index j)) (Function.update v j z ∘ r) = _
let j' := c.invEmbedding j
suffices B : Function.update v j z ∘ r = Function.update (v ∘ r) j' z by rw [B]
suffices C : Function.update v (r j') z ∘ r = Function.update (v ∘ r) j' z by
convert C; exact (c.embedding_comp_inv j).symm
exact Function.update_comp_eq_of_injective _ (c.embedding _).injective _ _
· simp only [h, Function.update_eq_self, Function.update_noteq, Ne, not_false_iff]
let r : Fin (c.blocksFun k) → Fin n := c.embedding k
change p (c.blocksFun k) (Function.update v j z ∘ r) = p (c.blocksFun k) (v ∘ r)
suffices B : Function.update v j z ∘ r = v ∘ r by rw [B]
apply Function.update_comp_eq_of_not_mem_range
rwa [c.mem_range_embedding_iff']
#align formal_multilinear_series.apply_composition_update FormalMultilinearSeries.applyComposition_update
@[simp]
theorem compContinuousLinearMap_applyComposition {n : ℕ} (p : FormalMultilinearSeries 𝕜 F G)
(f : E →L[𝕜] F) (c : Composition n) (v : Fin n → E) :
(p.compContinuousLinearMap f).applyComposition c v = p.applyComposition c (f ∘ v) := by
simp (config := {unfoldPartialApp := true}) [applyComposition]; rfl
#align formal_multilinear_series.comp_continuous_linear_map_apply_composition FormalMultilinearSeries.compContinuousLinearMap_applyComposition
end FormalMultilinearSeries
namespace ContinuousMultilinearMap
open FormalMultilinearSeries
variable [TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
variable [TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p`, a composition `c` of `n` and a continuous multilinear
map `f` in `c.length` variables, one may form a continuous multilinear map in `n` variables by
applying the right coefficient of `p` to each block of the composition, and then applying `f` to
the resulting vector. It is called `f.comp_along_composition p c`. -/
def compAlongComposition {n : ℕ} (p : FormalMultilinearSeries 𝕜 E F) (c : Composition n)
(f : ContinuousMultilinearMap 𝕜 (fun _i : Fin c.length => F) G) :
ContinuousMultilinearMap 𝕜 (fun _i : Fin n => E) G where
toFun v := f (p.applyComposition c v)
map_add' v i x y := by
cases Subsingleton.elim ‹_› (instDecidableEqFin _)
simp only [applyComposition_update, ContinuousMultilinearMap.map_add]
map_smul' v i c x := by
cases Subsingleton.elim ‹_› (instDecidableEqFin _)
simp only [applyComposition_update, ContinuousMultilinearMap.map_smul]
cont :=
f.cont.comp <|
continuous_pi fun i => (coe_continuous _).comp <| continuous_pi fun j => continuous_apply _
#align continuous_multilinear_map.comp_along_composition ContinuousMultilinearMap.compAlongComposition
@[simp]
theorem compAlongComposition_apply {n : ℕ} (p : FormalMultilinearSeries 𝕜 E F) (c : Composition n)
(f : ContinuousMultilinearMap 𝕜 (fun _i : Fin c.length => F) G) (v : Fin n → E) :
(f.compAlongComposition p c) v = f (p.applyComposition c v) :=
rfl
#align continuous_multilinear_map.comp_along_composition_apply ContinuousMultilinearMap.compAlongComposition_apply
end ContinuousMultilinearMap
namespace FormalMultilinearSeries
variable [TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
variable [TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
variable [TopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
/-- Given two formal multilinear series `q` and `p` and a composition `c` of `n`, one may
form a continuous multilinear map in `n` variables by applying the right coefficient of `p` to each
block of the composition, and then applying `q c.length` to the resulting vector. It is
called `q.comp_along_composition p c`. -/
def compAlongComposition {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) :
ContinuousMultilinearMap 𝕜 (fun _i : Fin n => E) G :=
(q c.length).compAlongComposition p c
#align formal_multilinear_series.comp_along_composition FormalMultilinearSeries.compAlongComposition
@[simp]
theorem compAlongComposition_apply {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) (v : Fin n → E) :
(q.compAlongComposition p c) v = q c.length (p.applyComposition c v) :=
rfl
#align formal_multilinear_series.comp_along_composition_apply FormalMultilinearSeries.compAlongComposition_apply
/-- Formal composition of two formal multilinear series. The `n`-th coefficient in the composition
is defined to be the sum of `q.comp_along_composition p c` over all compositions of
`n`. In other words, this term (as a multilinear function applied to `v_0, ..., v_{n-1}`) is
`∑'_{k} ∑'_{i₁ + ... + iₖ = n} qₖ (p_{i_1} (...), ..., p_{i_k} (...))`, where one puts all variables
`v_0, ..., v_{n-1}` in increasing order in the dots.
In general, the composition `q ∘ p` only makes sense when the constant coefficient of `p` vanishes.
We give a general formula but which ignores the value of `p 0` instead.
-/
protected def comp (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F) :
FormalMultilinearSeries 𝕜 E G := fun n => ∑ c : Composition n, q.compAlongComposition p c
#align formal_multilinear_series.comp FormalMultilinearSeries.comp
/-- The `0`-th coefficient of `q.comp p` is `q 0`. Since these maps are multilinear maps in zero
variables, but on different spaces, we can not state this directly, so we state it when applied to
arbitrary vectors (which have to be the zero vector). -/
theorem comp_coeff_zero (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(v : Fin 0 → E) (v' : Fin 0 → F) : (q.comp p) 0 v = q 0 v' := by
let c : Composition 0 := Composition.ones 0
dsimp [FormalMultilinearSeries.comp]
have : {c} = (Finset.univ : Finset (Composition 0)) := by
apply Finset.eq_of_subset_of_card_le <;> simp [Finset.card_univ, composition_card 0]
rw [← this, Finset.sum_singleton, compAlongComposition_apply]
symm; congr! -- Porting note: needed the stronger `congr!`!
#align formal_multilinear_series.comp_coeff_zero FormalMultilinearSeries.comp_coeff_zero
@[simp]
theorem comp_coeff_zero' (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(v : Fin 0 → E) : (q.comp p) 0 v = q 0 fun _i => 0 :=
q.comp_coeff_zero p v _
#align formal_multilinear_series.comp_coeff_zero' FormalMultilinearSeries.comp_coeff_zero'
/-- The `0`-th coefficient of `q.comp p` is `q 0`. When `p` goes from `E` to `E`, this can be
expressed as a direct equality -/
theorem comp_coeff_zero'' (q : FormalMultilinearSeries 𝕜 E F) (p : FormalMultilinearSeries 𝕜 E E) :
(q.comp p) 0 = q 0 := by ext v; exact q.comp_coeff_zero p _ _
#align formal_multilinear_series.comp_coeff_zero'' FormalMultilinearSeries.comp_coeff_zero''
/-- The first coefficient of a composition of formal multilinear series is the composition of the
first coefficients seen as continuous linear maps. -/
theorem comp_coeff_one (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(v : Fin 1 → E) : (q.comp p) 1 v = q 1 fun _i => p 1 v := by
have : {Composition.ones 1} = (Finset.univ : Finset (Composition 1)) :=
Finset.eq_univ_of_card _ (by simp [composition_card])
simp only [FormalMultilinearSeries.comp, compAlongComposition_apply, ← this,
Finset.sum_singleton]
refine q.congr (by simp) fun i hi1 hi2 => ?_
simp only [applyComposition_ones]
exact p.congr rfl fun j _hj1 hj2 => by congr! -- Porting note: needed the stronger `congr!`
#align formal_multilinear_series.comp_coeff_one FormalMultilinearSeries.comp_coeff_one
/-- Only `0`-th coefficient of `q.comp p` depends on `q 0`. -/
theorem removeZero_comp_of_pos (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (hn : 0 < n) :
q.removeZero.comp p n = q.comp p n := by
ext v
simp only [FormalMultilinearSeries.comp, compAlongComposition,
ContinuousMultilinearMap.compAlongComposition_apply, ContinuousMultilinearMap.sum_apply]
refine Finset.sum_congr rfl fun c _hc => ?_
rw [removeZero_of_pos _ (c.length_pos_of_pos hn)]
#align formal_multilinear_series.remove_zero_comp_of_pos FormalMultilinearSeries.removeZero_comp_of_pos
@[simp]
theorem comp_removeZero (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F) :
q.comp p.removeZero = q.comp p := by ext n; simp [FormalMultilinearSeries.comp]
#align formal_multilinear_series.comp_remove_zero FormalMultilinearSeries.comp_removeZero
end FormalMultilinearSeries
end Topological
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G] [NormedAddCommGroup H]
[NormedSpace 𝕜 H]
namespace FormalMultilinearSeries
/-- The norm of `f.comp_along_composition p c` is controlled by the product of
the norms of the relevant bits of `f` and `p`. -/
theorem compAlongComposition_bound {n : ℕ} (p : FormalMultilinearSeries 𝕜 E F) (c : Composition n)
(f : ContinuousMultilinearMap 𝕜 (fun _i : Fin c.length => F) G) (v : Fin n → E) :
‖f.compAlongComposition p c v‖ ≤ (‖f‖ * ∏ i, ‖p (c.blocksFun i)‖) * ∏ i : Fin n, ‖v i‖ :=
calc
‖f.compAlongComposition p c v‖ = ‖f (p.applyComposition c v)‖ := rfl
_ ≤ ‖f‖ * ∏ i, ‖p.applyComposition c v i‖ := ContinuousMultilinearMap.le_opNorm _ _
_ ≤ ‖f‖ * ∏ i, ‖p (c.blocksFun i)‖ * ∏ j : Fin (c.blocksFun i), ‖(v ∘ c.embedding i) j‖ := by
apply mul_le_mul_of_nonneg_left _ (norm_nonneg _)
refine Finset.prod_le_prod (fun i _hi => norm_nonneg _) fun i _hi => ?_
apply ContinuousMultilinearMap.le_opNorm
_ = (‖f‖ * ∏ i, ‖p (c.blocksFun i)‖) *
∏ i, ∏ j : Fin (c.blocksFun i), ‖(v ∘ c.embedding i) j‖ := by
rw [Finset.prod_mul_distrib, mul_assoc]
_ = (‖f‖ * ∏ i, ‖p (c.blocksFun i)‖) * ∏ i : Fin n, ‖v i‖ := by
rw [← c.blocksFinEquiv.prod_comp, ← Finset.univ_sigma_univ, Finset.prod_sigma]
congr
#align formal_multilinear_series.comp_along_composition_bound FormalMultilinearSeries.compAlongComposition_bound
/-- The norm of `q.comp_along_composition p c` is controlled by the product of
the norms of the relevant bits of `q` and `p`. -/
theorem compAlongComposition_norm {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) :
‖q.compAlongComposition p c‖ ≤ ‖q c.length‖ * ∏ i, ‖p (c.blocksFun i)‖ :=
ContinuousMultilinearMap.opNorm_le_bound _ (by positivity) (compAlongComposition_bound _ _ _)
#align formal_multilinear_series.comp_along_composition_norm FormalMultilinearSeries.compAlongComposition_norm
theorem compAlongComposition_nnnorm {n : ℕ} (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (c : Composition n) :
‖q.compAlongComposition p c‖₊ ≤ ‖q c.length‖₊ * ∏ i, ‖p (c.blocksFun i)‖₊ := by
rw [← NNReal.coe_le_coe]; push_cast; exact q.compAlongComposition_norm p c
#align formal_multilinear_series.comp_along_composition_nnnorm FormalMultilinearSeries.compAlongComposition_nnnorm
/-!
### The identity formal power series
We will now define the identity power series, and show that it is a neutral element for left and
right composition.
-/
section
variable (𝕜 E)
/-- The identity formal multilinear series, with all coefficients equal to `0` except for `n = 1`
where it is (the continuous multilinear version of) the identity. -/
def id : FormalMultilinearSeries 𝕜 E E
| 0 => 0
| 1 => (continuousMultilinearCurryFin1 𝕜 E E).symm (ContinuousLinearMap.id 𝕜 E)
| _ => 0
#align formal_multilinear_series.id FormalMultilinearSeries.id
/-- The first coefficient of `id 𝕜 E` is the identity. -/
@[simp]
theorem id_apply_one (v : Fin 1 → E) : (FormalMultilinearSeries.id 𝕜 E) 1 v = v 0 :=
rfl
#align formal_multilinear_series.id_apply_one FormalMultilinearSeries.id_apply_one
/-- The `n`th coefficient of `id 𝕜 E` is the identity when `n = 1`. We state this in a dependent
way, as it will often appear in this form. -/
theorem id_apply_one' {n : ℕ} (h : n = 1) (v : Fin n → E) :
(id 𝕜 E) n v = v ⟨0, h.symm ▸ zero_lt_one⟩ := by
subst n
apply id_apply_one
#align formal_multilinear_series.id_apply_one' FormalMultilinearSeries.id_apply_one'
/-- For `n ≠ 1`, the `n`-th coefficient of `id 𝕜 E` is zero, by definition. -/
@[simp]
theorem id_apply_ne_one {n : ℕ} (h : n ≠ 1) : (FormalMultilinearSeries.id 𝕜 E) n = 0 := by
cases' n with n
· rfl
· cases n
· contradiction
· rfl
#align formal_multilinear_series.id_apply_ne_one FormalMultilinearSeries.id_apply_ne_one
end
@[simp]
theorem comp_id (p : FormalMultilinearSeries 𝕜 E F) : p.comp (id 𝕜 E) = p := by
ext1 n
dsimp [FormalMultilinearSeries.comp]
rw [Finset.sum_eq_single (Composition.ones n)]
· show compAlongComposition p (id 𝕜 E) (Composition.ones n) = p n
ext v
rw [compAlongComposition_apply]
apply p.congr (Composition.ones_length n)
intros
rw [applyComposition_ones]
refine congr_arg v ?_
rw [Fin.ext_iff, Fin.coe_castLE, Fin.val_mk]
· show
∀ b : Composition n,
b ∈ Finset.univ → b ≠ Composition.ones n → compAlongComposition p (id 𝕜 E) b = 0
intro b _ hb
obtain ⟨k, hk, lt_k⟩ : ∃ (k : ℕ), k ∈ Composition.blocks b ∧ 1 < k :=
Composition.ne_ones_iff.1 hb
obtain ⟨i, hi⟩ : ∃ (i : Fin b.blocks.length), b.blocks.get i = k :=
List.get_of_mem hk
let j : Fin b.length := ⟨i.val, b.blocks_length ▸ i.prop⟩
have A : 1 < b.blocksFun j := by convert lt_k
ext v
rw [compAlongComposition_apply, ContinuousMultilinearMap.zero_apply]
apply ContinuousMultilinearMap.map_coord_zero _ j
dsimp [applyComposition]
rw [id_apply_ne_one _ _ (ne_of_gt A)]
rfl
· simp
#align formal_multilinear_series.comp_id FormalMultilinearSeries.comp_id
@[simp]
theorem id_comp (p : FormalMultilinearSeries 𝕜 E F) (h : p 0 = 0) : (id 𝕜 F).comp p = p := by
ext1 n
by_cases hn : n = 0
· rw [hn, h]
ext v
rw [comp_coeff_zero', id_apply_ne_one _ _ zero_ne_one]
rfl
· dsimp [FormalMultilinearSeries.comp]
have n_pos : 0 < n := bot_lt_iff_ne_bot.mpr hn
rw [Finset.sum_eq_single (Composition.single n n_pos)]
· show compAlongComposition (id 𝕜 F) p (Composition.single n n_pos) = p n
ext v
rw [compAlongComposition_apply, id_apply_one' _ _ (Composition.single_length n_pos)]
dsimp [applyComposition]
refine p.congr rfl fun i him hin => congr_arg v <| ?_
ext; simp
· show
∀ b : Composition n,
b ∈ Finset.univ → b ≠ Composition.single n n_pos → compAlongComposition (id 𝕜 F) p b = 0
intro b _ hb
have A : b.length ≠ 1 := by simpa [Composition.eq_single_iff_length] using hb
ext v
rw [compAlongComposition_apply, id_apply_ne_one _ _ A]
rfl
· simp
#align formal_multilinear_series.id_comp FormalMultilinearSeries.id_comp
/-! ### Summability properties of the composition of formal power series-/
section
/-- If two formal multilinear series have positive radius of convergence, then the terms appearing
in the definition of their composition are also summable (when multiplied by a suitable positive
geometric term). -/
theorem comp_summable_nnreal (q : FormalMultilinearSeries 𝕜 F G) (p : FormalMultilinearSeries 𝕜 E F)
(hq : 0 < q.radius) (hp : 0 < p.radius) :
∃ r > (0 : ℝ≥0),
Summable fun i : Σ n, Composition n => ‖q.compAlongComposition p i.2‖₊ * r ^ i.1 := by
/- This follows from the fact that the growth rate of `‖qₙ‖` and `‖pₙ‖` is at most geometric,
giving a geometric bound on each `‖q.comp_along_composition p op‖`, together with the
fact that there are `2^(n-1)` compositions of `n`, giving at most a geometric loss. -/
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 (lt_min zero_lt_one hq) with ⟨rq, rq_pos, hrq⟩
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 (lt_min zero_lt_one hp) with ⟨rp, rp_pos, hrp⟩
simp only [lt_min_iff, ENNReal.coe_lt_one_iff, ENNReal.coe_pos] at hrp hrq rp_pos rq_pos
obtain ⟨Cq, _hCq0, hCq⟩ : ∃ Cq > 0, ∀ n, ‖q n‖₊ * rq ^ n ≤ Cq :=
q.nnnorm_mul_pow_le_of_lt_radius hrq.2
obtain ⟨Cp, hCp1, hCp⟩ : ∃ Cp ≥ 1, ∀ n, ‖p n‖₊ * rp ^ n ≤ Cp := by
rcases p.nnnorm_mul_pow_le_of_lt_radius hrp.2 with ⟨Cp, -, hCp⟩
exact ⟨max Cp 1, le_max_right _ _, fun n => (hCp n).trans (le_max_left _ _)⟩
let r0 : ℝ≥0 := (4 * Cp)⁻¹
have r0_pos : 0 < r0 := inv_pos.2 (mul_pos zero_lt_four (zero_lt_one.trans_le hCp1))
set r : ℝ≥0 := rp * rq * r0
have r_pos : 0 < r := mul_pos (mul_pos rp_pos rq_pos) r0_pos
have I :
∀ i : Σ n : ℕ, Composition n, ‖q.compAlongComposition p i.2‖₊ * r ^ i.1 ≤ Cq / 4 ^ i.1 := by
rintro ⟨n, c⟩
have A := calc
‖q c.length‖₊ * rq ^ n ≤ ‖q c.length‖₊ * rq ^ c.length :=
mul_le_mul' le_rfl (pow_le_pow_of_le_one rq.2 hrq.1.le c.length_le)
_ ≤ Cq := hCq _
have B := calc
(∏ i, ‖p (c.blocksFun i)‖₊) * rp ^ n = ∏ i, ‖p (c.blocksFun i)‖₊ * rp ^ c.blocksFun i := by
simp only [Finset.prod_mul_distrib, Finset.prod_pow_eq_pow_sum, c.sum_blocksFun]
_ ≤ ∏ _i : Fin c.length, Cp := Finset.prod_le_prod' fun i _ => hCp _
_ = Cp ^ c.length := by simp
_ ≤ Cp ^ n := pow_le_pow_right hCp1 c.length_le
calc
‖q.compAlongComposition p c‖₊ * r ^ n ≤
(‖q c.length‖₊ * ∏ i, ‖p (c.blocksFun i)‖₊) * r ^ n :=
mul_le_mul' (q.compAlongComposition_nnnorm p c) le_rfl
_ = ‖q c.length‖₊ * rq ^ n * ((∏ i, ‖p (c.blocksFun i)‖₊) * rp ^ n) * r0 ^ n := by
simp only [mul_pow]; ring
_ ≤ Cq * Cp ^ n * r0 ^ n := mul_le_mul' (mul_le_mul' A B) le_rfl
_ = Cq / 4 ^ n := by
simp only [r0]
field_simp [mul_pow, (zero_lt_one.trans_le hCp1).ne']
ring
refine ⟨r, r_pos, NNReal.summable_of_le I ?_⟩
simp_rw [div_eq_mul_inv]
refine Summable.mul_left _ ?_
have : ∀ n : ℕ, HasSum (fun c : Composition n => (4 ^ n : ℝ≥0)⁻¹) (2 ^ (n - 1) / 4 ^ n) := by
intro n
convert hasSum_fintype fun c : Composition n => (4 ^ n : ℝ≥0)⁻¹
simp [Finset.card_univ, composition_card, div_eq_mul_inv]
refine NNReal.summable_sigma.2 ⟨fun n => (this n).summable, (NNReal.summable_nat_add_iff 1).1 ?_⟩
convert (NNReal.summable_geometric (NNReal.div_lt_one_of_lt one_lt_two)).mul_left (1 / 4) using 1
ext1 n
rw [(this _).tsum_eq, add_tsub_cancel_right]
field_simp [← mul_assoc, pow_succ, mul_pow, show (4 : ℝ≥0) = 2 * 2 by norm_num,
mul_right_comm]
#align formal_multilinear_series.comp_summable_nnreal FormalMultilinearSeries.comp_summable_nnreal
end
/-- Bounding below the radius of the composition of two formal multilinear series assuming
summability over all compositions. -/
| Mathlib/Analysis/Analytic/Composition.lean | 520 | 533 | theorem le_comp_radius_of_summable (q : FormalMultilinearSeries 𝕜 F G)
(p : FormalMultilinearSeries 𝕜 E F) (r : ℝ≥0)
(hr : Summable fun i : Σ n, Composition n => ‖q.compAlongComposition p i.2‖₊ * r ^ i.1) :
(r : ℝ≥0∞) ≤ (q.comp p).radius := by |
refine
le_radius_of_bound_nnreal _
(∑' i : Σ n, Composition n, ‖compAlongComposition q p i.snd‖₊ * r ^ i.fst) fun n => ?_
calc
‖FormalMultilinearSeries.comp q p n‖₊ * r ^ n ≤
∑' c : Composition n, ‖compAlongComposition q p c‖₊ * r ^ n := by
rw [tsum_fintype, ← Finset.sum_mul]
exact mul_le_mul' (nnnorm_sum_le _ _) le_rfl
_ ≤ ∑' i : Σ n : ℕ, Composition n, ‖compAlongComposition q p i.snd‖₊ * r ^ i.fst :=
NNReal.tsum_comp_le_tsum_of_inj hr sigma_mk_injective
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Data.Set.Image
import Mathlib.Order.SuccPred.Relation
import Mathlib.Topology.Clopen
import Mathlib.Topology.Irreducible
#align_import topology.connected from "leanprover-community/mathlib"@"d101e93197bb5f6ea89bd7ba386b7f7dff1f3903"
/-!
# Connected subsets of topological spaces
In this file we define connected subsets of a topological spaces and various other properties and
classes related to connectivity.
## Main definitions
We define the following properties for sets in a topological space:
* `IsConnected`: a nonempty set that has no non-trivial open partition.
See also the section below in the module doc.
* `connectedComponent` is the connected component of an element in the space.
We also have a class stating that the whole space satisfies that property: `ConnectedSpace`
## On the definition of connected sets/spaces
In informal mathematics, connected spaces are assumed to be nonempty.
We formalise the predicate without that assumption as `IsPreconnected`.
In other words, the only difference is whether the empty space counts as connected.
There are good reasons to consider the empty space to be “too simple to be simple”
See also https://ncatlab.org/nlab/show/too+simple+to+be+simple,
and in particular
https://ncatlab.org/nlab/show/too+simple+to+be+simple#relationship_to_biased_definitions.
-/
open Set Function Topology TopologicalSpace Relation
open scoped Classical
universe u v
variable {α : Type u} {β : Type v} {ι : Type*} {π : ι → Type*} [TopologicalSpace α]
{s t u v : Set α}
section Preconnected
/-- A preconnected set is one where there is no non-trivial open partition. -/
def IsPreconnected (s : Set α) : Prop :=
∀ u v : Set α, IsOpen u → IsOpen v → s ⊆ u ∪ v → (s ∩ u).Nonempty → (s ∩ v).Nonempty →
(s ∩ (u ∩ v)).Nonempty
#align is_preconnected IsPreconnected
/-- A connected set is one that is nonempty and where there is no non-trivial open partition. -/
def IsConnected (s : Set α) : Prop :=
s.Nonempty ∧ IsPreconnected s
#align is_connected IsConnected
theorem IsConnected.nonempty {s : Set α} (h : IsConnected s) : s.Nonempty :=
h.1
#align is_connected.nonempty IsConnected.nonempty
theorem IsConnected.isPreconnected {s : Set α} (h : IsConnected s) : IsPreconnected s :=
h.2
#align is_connected.is_preconnected IsConnected.isPreconnected
theorem IsPreirreducible.isPreconnected {s : Set α} (H : IsPreirreducible s) : IsPreconnected s :=
fun _ _ hu hv _ => H _ _ hu hv
#align is_preirreducible.is_preconnected IsPreirreducible.isPreconnected
theorem IsIrreducible.isConnected {s : Set α} (H : IsIrreducible s) : IsConnected s :=
⟨H.nonempty, H.isPreirreducible.isPreconnected⟩
#align is_irreducible.is_connected IsIrreducible.isConnected
theorem isPreconnected_empty : IsPreconnected (∅ : Set α) :=
isPreirreducible_empty.isPreconnected
#align is_preconnected_empty isPreconnected_empty
theorem isConnected_singleton {x} : IsConnected ({x} : Set α) :=
isIrreducible_singleton.isConnected
#align is_connected_singleton isConnected_singleton
theorem isPreconnected_singleton {x} : IsPreconnected ({x} : Set α) :=
isConnected_singleton.isPreconnected
#align is_preconnected_singleton isPreconnected_singleton
theorem Set.Subsingleton.isPreconnected {s : Set α} (hs : s.Subsingleton) : IsPreconnected s :=
hs.induction_on isPreconnected_empty fun _ => isPreconnected_singleton
#align set.subsingleton.is_preconnected Set.Subsingleton.isPreconnected
/-- If any point of a set is joined to a fixed point by a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall {s : Set α} (x : α)
(H : ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) : IsPreconnected s := by
rintro u v hu hv hs ⟨z, zs, zu⟩ ⟨y, ys, yv⟩
have xs : x ∈ s := by
rcases H y ys with ⟨t, ts, xt, -, -⟩
exact ts xt
-- Porting note (#11215): TODO: use `wlog xu : x ∈ u := hs xs using u v y z, v u z y`
cases hs xs with
| inl xu =>
rcases H y ys with ⟨t, ts, xt, yt, ht⟩
have := ht u v hu hv (ts.trans hs) ⟨x, xt, xu⟩ ⟨y, yt, yv⟩
exact this.imp fun z hz => ⟨ts hz.1, hz.2⟩
| inr xv =>
rcases H z zs with ⟨t, ts, xt, zt, ht⟩
have := ht v u hv hu (ts.trans <| by rwa [union_comm]) ⟨x, xt, xv⟩ ⟨z, zt, zu⟩
exact this.imp fun _ h => ⟨ts h.1, h.2.2, h.2.1⟩
#align is_preconnected_of_forall isPreconnected_of_forall
/-- If any two points of a set are contained in a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall_pair {s : Set α}
(H : ∀ x ∈ s, ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) :
IsPreconnected s := by
rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩)
exacts [isPreconnected_empty, isPreconnected_of_forall x fun y => H x hx y]
#align is_preconnected_of_forall_pair isPreconnected_of_forall_pair
/-- A union of a family of preconnected sets with a common point is preconnected as well. -/
theorem isPreconnected_sUnion (x : α) (c : Set (Set α)) (H1 : ∀ s ∈ c, x ∈ s)
(H2 : ∀ s ∈ c, IsPreconnected s) : IsPreconnected (⋃₀ c) := by
apply isPreconnected_of_forall x
rintro y ⟨s, sc, ys⟩
exact ⟨s, subset_sUnion_of_mem sc, H1 s sc, ys, H2 s sc⟩
#align is_preconnected_sUnion isPreconnected_sUnion
theorem isPreconnected_iUnion {ι : Sort*} {s : ι → Set α} (h₁ : (⋂ i, s i).Nonempty)
(h₂ : ∀ i, IsPreconnected (s i)) : IsPreconnected (⋃ i, s i) :=
Exists.elim h₁ fun f hf => isPreconnected_sUnion f _ hf (forall_mem_range.2 h₂)
#align is_preconnected_Union isPreconnected_iUnion
theorem IsPreconnected.union (x : α) {s t : Set α} (H1 : x ∈ s) (H2 : x ∈ t) (H3 : IsPreconnected s)
(H4 : IsPreconnected t) : IsPreconnected (s ∪ t) :=
sUnion_pair s t ▸ isPreconnected_sUnion x {s, t} (by rintro r (rfl | rfl | h) <;> assumption)
(by rintro r (rfl | rfl | h) <;> assumption)
#align is_preconnected.union IsPreconnected.union
theorem IsPreconnected.union' {s t : Set α} (H : (s ∩ t).Nonempty) (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ∪ t) := by
rcases H with ⟨x, hxs, hxt⟩
exact hs.union x hxs hxt ht
#align is_preconnected.union' IsPreconnected.union'
theorem IsConnected.union {s t : Set α} (H : (s ∩ t).Nonempty) (Hs : IsConnected s)
(Ht : IsConnected t) : IsConnected (s ∪ t) := by
rcases H with ⟨x, hx⟩
refine ⟨⟨x, mem_union_left t (mem_of_mem_inter_left hx)⟩, ?_⟩
exact Hs.isPreconnected.union x (mem_of_mem_inter_left hx) (mem_of_mem_inter_right hx)
Ht.isPreconnected
#align is_connected.union IsConnected.union
/-- The directed sUnion of a set S of preconnected subsets is preconnected. -/
theorem IsPreconnected.sUnion_directed {S : Set (Set α)} (K : DirectedOn (· ⊆ ·) S)
(H : ∀ s ∈ S, IsPreconnected s) : IsPreconnected (⋃₀ S) := by
rintro u v hu hv Huv ⟨a, ⟨s, hsS, has⟩, hau⟩ ⟨b, ⟨t, htS, hbt⟩, hbv⟩
obtain ⟨r, hrS, hsr, htr⟩ : ∃ r ∈ S, s ⊆ r ∧ t ⊆ r := K s hsS t htS
have Hnuv : (r ∩ (u ∩ v)).Nonempty :=
H _ hrS u v hu hv ((subset_sUnion_of_mem hrS).trans Huv) ⟨a, hsr has, hau⟩ ⟨b, htr hbt, hbv⟩
have Kruv : r ∩ (u ∩ v) ⊆ ⋃₀ S ∩ (u ∩ v) := inter_subset_inter_left _ (subset_sUnion_of_mem hrS)
exact Hnuv.mono Kruv
#align is_preconnected.sUnion_directed IsPreconnected.sUnion_directed
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsPreconnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(H : ∀ i ∈ t, IsPreconnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsPreconnected (⋃ n ∈ t, s n) := by
let R := fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t
have P : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen R i j →
∃ p, p ⊆ t ∧ i ∈ p ∧ j ∈ p ∧ IsPreconnected (⋃ j ∈ p, s j) := fun i hi j hj h => by
induction h with
| refl =>
refine ⟨{i}, singleton_subset_iff.mpr hi, mem_singleton i, mem_singleton i, ?_⟩
rw [biUnion_singleton]
exact H i hi
| @tail j k _ hjk ih =>
obtain ⟨p, hpt, hip, hjp, hp⟩ := ih hjk.2
refine ⟨insert k p, insert_subset_iff.mpr ⟨hj, hpt⟩, mem_insert_of_mem k hip,
mem_insert k p, ?_⟩
rw [biUnion_insert]
refine (H k hj).union' (hjk.1.mono ?_) hp
rw [inter_comm]
exact inter_subset_inter_right _ (subset_biUnion_of_mem hjp)
refine isPreconnected_of_forall_pair ?_
intro x hx y hy
obtain ⟨i : ι, hi : i ∈ t, hxi : x ∈ s i⟩ := mem_iUnion₂.1 hx
obtain ⟨j : ι, hj : j ∈ t, hyj : y ∈ s j⟩ := mem_iUnion₂.1 hy
obtain ⟨p, hpt, hip, hjp, hp⟩ := P i hi j hj (K i hi j hj)
exact ⟨⋃ j ∈ p, s j, biUnion_subset_biUnion_left hpt, mem_biUnion hip hxi,
mem_biUnion hjp hyj, hp⟩
#align is_preconnected.bUnion_of_refl_trans_gen IsPreconnected.biUnion_of_reflTransGen
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsConnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(ht : t.Nonempty) (H : ∀ i ∈ t, IsConnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨ht.some, ht.some_mem, (H _ ht.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_reflTransGen (fun i hi => (H i hi).isPreconnected) K⟩
#align is_connected.bUnion_of_refl_trans_gen IsConnected.biUnion_of_reflTransGen
/-- Preconnectedness of the iUnion of a family of preconnected sets
indexed by the vertices of a preconnected graph,
where two vertices are joined when the corresponding sets intersect. -/
theorem IsPreconnected.iUnion_of_reflTransGen {ι : Type*} {s : ι → Set α}
(H : ∀ i, IsPreconnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) :
IsPreconnected (⋃ n, s n) := by
rw [← biUnion_univ]
exact IsPreconnected.biUnion_of_reflTransGen (fun i _ => H i) fun i _ j _ => by
simpa [mem_univ] using K i j
#align is_preconnected.Union_of_refl_trans_gen IsPreconnected.iUnion_of_reflTransGen
theorem IsConnected.iUnion_of_reflTransGen {ι : Type*} [Nonempty ι] {s : ι → Set α}
(H : ∀ i, IsConnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) : IsConnected (⋃ n, s n) :=
⟨nonempty_iUnion.2 <| Nonempty.elim ‹_› fun i : ι => ⟨i, (H _).nonempty⟩,
IsPreconnected.iUnion_of_reflTransGen (fun i => (H i).isPreconnected) K⟩
#align is_connected.Union_of_refl_trans_gen IsConnected.iUnion_of_reflTransGen
section SuccOrder
open Order
variable [LinearOrder β] [SuccOrder β] [IsSuccArchimedean β]
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.iUnion_of_chain {s : β → Set α} (H : ∀ n, IsPreconnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsPreconnected (⋃ n, s n) :=
IsPreconnected.iUnion_of_reflTransGen H fun i j =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
#align is_preconnected.Union_of_chain IsPreconnected.iUnion_of_chain
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is connected. -/
theorem IsConnected.iUnion_of_chain [Nonempty β] {s : β → Set α} (H : ∀ n, IsConnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n, s n) :=
IsConnected.iUnion_of_reflTransGen H fun i j =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
#align is_connected.Union_of_chain IsConnected.iUnion_of_chain
/-- The iUnion of preconnected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.biUnion_of_chain {s : β → Set α} {t : Set β} (ht : OrdConnected t)
(H : ∀ n ∈ t, IsPreconnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) :
IsPreconnected (⋃ n ∈ t, s n) := by
have h1 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → k ∈ t := fun hi hj hk =>
ht.out hi hj (Ico_subset_Icc_self hk)
have h2 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → succ k ∈ t := fun hi hj hk =>
ht.out hi hj ⟨hk.1.trans <| le_succ _, succ_le_of_lt hk.2⟩
have h3 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → (s k ∩ s (succ k)).Nonempty :=
fun hi hj hk => K _ (h1 hi hj hk) (h2 hi hj hk)
refine IsPreconnected.biUnion_of_reflTransGen H fun i hi j hj => ?_
exact reflTransGen_of_succ _ (fun k hk => ⟨h3 hi hj hk, h1 hi hj hk⟩) fun k hk =>
⟨by rw [inter_comm]; exact h3 hj hi hk, h2 hj hi hk⟩
#align is_preconnected.bUnion_of_chain IsPreconnected.biUnion_of_chain
/-- The iUnion of connected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsConnected.biUnion_of_chain {s : β → Set α} {t : Set β} (hnt : t.Nonempty)
(ht : OrdConnected t) (H : ∀ n ∈ t, IsConnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨hnt.some, hnt.some_mem, (H _ hnt.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_chain ht (fun i hi => (H i hi).isPreconnected) K⟩
#align is_connected.bUnion_of_chain IsConnected.biUnion_of_chain
end SuccOrder
/-- Theorem of bark and tree: if a set is within a preconnected set and its closure, then it is
preconnected as well. See also `IsConnected.subset_closure`. -/
protected theorem IsPreconnected.subset_closure {s : Set α} {t : Set α} (H : IsPreconnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsPreconnected t :=
fun u v hu hv htuv ⟨_y, hyt, hyu⟩ ⟨_z, hzt, hzv⟩ =>
let ⟨p, hpu, hps⟩ := mem_closure_iff.1 (Ktcs hyt) u hu hyu
let ⟨q, hqv, hqs⟩ := mem_closure_iff.1 (Ktcs hzt) v hv hzv
let ⟨r, hrs, hruv⟩ := H u v hu hv (Subset.trans Kst htuv) ⟨p, hps, hpu⟩ ⟨q, hqs, hqv⟩
⟨r, Kst hrs, hruv⟩
#align is_preconnected.subset_closure IsPreconnected.subset_closure
/-- Theorem of bark and tree: if a set is within a connected set and its closure, then it is
connected as well. See also `IsPreconnected.subset_closure`. -/
protected theorem IsConnected.subset_closure {s : Set α} {t : Set α} (H : IsConnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsConnected t :=
⟨Nonempty.mono Kst H.left, IsPreconnected.subset_closure H.right Kst Ktcs⟩
#align is_connected.subset_closure IsConnected.subset_closure
/-- The closure of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.closure {s : Set α} (H : IsPreconnected s) :
IsPreconnected (closure s) :=
IsPreconnected.subset_closure H subset_closure Subset.rfl
#align is_preconnected.closure IsPreconnected.closure
/-- The closure of a connected set is connected as well. -/
protected theorem IsConnected.closure {s : Set α} (H : IsConnected s) : IsConnected (closure s) :=
IsConnected.subset_closure H subset_closure <| Subset.rfl
#align is_connected.closure IsConnected.closure
/-- The image of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.image [TopologicalSpace β] {s : Set α} (H : IsPreconnected s)
(f : α → β) (hf : ContinuousOn f s) : IsPreconnected (f '' s) := by
-- Unfold/destruct definitions in hypotheses
rintro u v hu hv huv ⟨_, ⟨x, xs, rfl⟩, xu⟩ ⟨_, ⟨y, ys, rfl⟩, yv⟩
rcases continuousOn_iff'.1 hf u hu with ⟨u', hu', u'_eq⟩
rcases continuousOn_iff'.1 hf v hv with ⟨v', hv', v'_eq⟩
-- Reformulate `huv : f '' s ⊆ u ∪ v` in terms of `u'` and `v'`
replace huv : s ⊆ u' ∪ v' := by
rw [image_subset_iff, preimage_union] at huv
replace huv := subset_inter huv Subset.rfl
rw [union_inter_distrib_right, u'_eq, v'_eq, ← union_inter_distrib_right] at huv
exact (subset_inter_iff.1 huv).1
-- Now `s ⊆ u' ∪ v'`, so we can apply `‹IsPreconnected s›`
obtain ⟨z, hz⟩ : (s ∩ (u' ∩ v')).Nonempty := by
refine H u' v' hu' hv' huv ⟨x, ?_⟩ ⟨y, ?_⟩ <;> rw [inter_comm]
exacts [u'_eq ▸ ⟨xu, xs⟩, v'_eq ▸ ⟨yv, ys⟩]
rw [← inter_self s, inter_assoc, inter_left_comm s u', ← inter_assoc, inter_comm s, inter_comm s,
← u'_eq, ← v'_eq] at hz
exact ⟨f z, ⟨z, hz.1.2, rfl⟩, hz.1.1, hz.2.1⟩
#align is_preconnected.image IsPreconnected.image
/-- The image of a connected set is connected as well. -/
protected theorem IsConnected.image [TopologicalSpace β] {s : Set α} (H : IsConnected s) (f : α → β)
(hf : ContinuousOn f s) : IsConnected (f '' s) :=
⟨image_nonempty.mpr H.nonempty, H.isPreconnected.image f hf⟩
#align is_connected.image IsConnected.image
theorem isPreconnected_closed_iff {s : Set α} :
IsPreconnected s ↔ ∀ t t', IsClosed t → IsClosed t' →
s ⊆ t ∪ t' → (s ∩ t).Nonempty → (s ∩ t').Nonempty → (s ∩ (t ∩ t')).Nonempty :=
⟨by
rintro h t t' ht ht' htt' ⟨x, xs, xt⟩ ⟨y, ys, yt'⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xt' : x ∉ t' := (h' xs).resolve_left (absurd xt)
have yt : y ∉ t := (h' ys).resolve_right (absurd yt')
have := h _ _ ht.isOpen_compl ht'.isOpen_compl h' ⟨y, ys, yt⟩ ⟨x, xs, xt'⟩
rw [← compl_union] at this
exact this.ne_empty htt'.disjoint_compl_right.inter_eq,
by
rintro h u v hu hv huv ⟨x, xs, xu⟩ ⟨y, ys, yv⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xv : x ∉ v := (h' xs).elim (absurd xu) id
have yu : y ∉ u := (h' ys).elim id (absurd yv)
have := h _ _ hu.isClosed_compl hv.isClosed_compl h' ⟨y, ys, yu⟩ ⟨x, xs, xv⟩
rw [← compl_union] at this
exact this.ne_empty huv.disjoint_compl_right.inter_eq⟩
#align is_preconnected_closed_iff isPreconnected_closed_iff
theorem Inducing.isPreconnected_image [TopologicalSpace β] {s : Set α} {f : α → β}
(hf : Inducing f) : IsPreconnected (f '' s) ↔ IsPreconnected s := by
refine ⟨fun h => ?_, fun h => h.image _ hf.continuous.continuousOn⟩
rintro u v hu' hv' huv ⟨x, hxs, hxu⟩ ⟨y, hys, hyv⟩
rcases hf.isOpen_iff.1 hu' with ⟨u, hu, rfl⟩
rcases hf.isOpen_iff.1 hv' with ⟨v, hv, rfl⟩
replace huv : f '' s ⊆ u ∪ v := by rwa [image_subset_iff]
rcases h u v hu hv huv ⟨f x, mem_image_of_mem _ hxs, hxu⟩ ⟨f y, mem_image_of_mem _ hys, hyv⟩ with
⟨_, ⟨z, hzs, rfl⟩, hzuv⟩
exact ⟨z, hzs, hzuv⟩
#align inducing.is_preconnected_image Inducing.isPreconnected_image
/- TODO: The following lemmas about connection of preimages hold more generally for strict maps
(the quotient and subspace topologies of the image agree) whose fibers are preconnected. -/
theorem IsPreconnected.preimage_of_isOpenMap [TopologicalSpace β] {f : α → β} {s : Set β}
(hs : IsPreconnected s) (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsPreconnected (f ⁻¹' s) := fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by
refine hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
#align is_preconnected.preimage_of_open_map IsPreconnected.preimage_of_isOpenMap
theorem IsPreconnected.preimage_of_isClosedMap [TopologicalSpace β] {s : Set β}
(hs : IsPreconnected s) {f : α → β} (hinj : Function.Injective f) (hf : IsClosedMap f)
(hsf : s ⊆ range f) : IsPreconnected (f ⁻¹' s) :=
isPreconnected_closed_iff.2 fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by
refine isPreconnected_closed_iff.1 hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
#align is_preconnected.preimage_of_closed_map IsPreconnected.preimage_of_isClosedMap
theorem IsConnected.preimage_of_isOpenMap [TopologicalSpace β] {s : Set β} (hs : IsConnected s)
{f : α → β} (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsConnected (f ⁻¹' s) :=
⟨hs.nonempty.preimage' hsf, hs.isPreconnected.preimage_of_isOpenMap hinj hf hsf⟩
#align is_connected.preimage_of_open_map IsConnected.preimage_of_isOpenMap
theorem IsConnected.preimage_of_isClosedMap [TopologicalSpace β] {s : Set β} (hs : IsConnected s)
{f : α → β} (hinj : Function.Injective f) (hf : IsClosedMap f) (hsf : s ⊆ range f) :
IsConnected (f ⁻¹' s) :=
⟨hs.nonempty.preimage' hsf, hs.isPreconnected.preimage_of_isClosedMap hinj hf hsf⟩
#align is_connected.preimage_of_closed_map IsConnected.preimage_of_isClosedMap
theorem IsPreconnected.subset_or_subset (hu : IsOpen u) (hv : IsOpen v) (huv : Disjoint u v)
(hsuv : s ⊆ u ∪ v) (hs : IsPreconnected s) : s ⊆ u ∨ s ⊆ v := by
specialize hs u v hu hv hsuv
obtain hsu | hsu := (s ∩ u).eq_empty_or_nonempty
· exact Or.inr ((Set.disjoint_iff_inter_eq_empty.2 hsu).subset_right_of_subset_union hsuv)
· replace hs := mt (hs hsu)
simp_rw [Set.not_nonempty_iff_eq_empty, ← Set.disjoint_iff_inter_eq_empty,
disjoint_iff_inter_eq_empty.1 huv] at hs
exact Or.inl ((hs s.disjoint_empty).subset_left_of_subset_union hsuv)
#align is_preconnected.subset_or_subset IsPreconnected.subset_or_subset
theorem IsPreconnected.subset_left_of_subset_union (hu : IsOpen u) (hv : IsOpen v)
(huv : Disjoint u v) (hsuv : s ⊆ u ∪ v) (hsu : (s ∩ u).Nonempty) (hs : IsPreconnected s) :
s ⊆ u :=
Disjoint.subset_left_of_subset_union hsuv
(by
by_contra hsv
rw [not_disjoint_iff_nonempty_inter] at hsv
obtain ⟨x, _, hx⟩ := hs u v hu hv hsuv hsu hsv
exact Set.disjoint_iff.1 huv hx)
#align is_preconnected.subset_left_of_subset_union IsPreconnected.subset_left_of_subset_union
theorem IsPreconnected.subset_right_of_subset_union (hu : IsOpen u) (hv : IsOpen v)
(huv : Disjoint u v) (hsuv : s ⊆ u ∪ v) (hsv : (s ∩ v).Nonempty) (hs : IsPreconnected s) :
s ⊆ v :=
hs.subset_left_of_subset_union hv hu huv.symm (union_comm u v ▸ hsuv) hsv
#align is_preconnected.subset_right_of_subset_union IsPreconnected.subset_right_of_subset_union
-- Porting note: moved up
/-- Preconnected sets are either contained in or disjoint to any given clopen set. -/
theorem IsPreconnected.subset_isClopen {s t : Set α} (hs : IsPreconnected s) (ht : IsClopen t)
(hne : (s ∩ t).Nonempty) : s ⊆ t :=
hs.subset_left_of_subset_union ht.isOpen ht.compl.isOpen disjoint_compl_right (by simp) hne
#align is_preconnected.subset_clopen IsPreconnected.subset_isClopen
/-- If a preconnected set `s` intersects an open set `u`, and limit points of `u` inside `s` are
contained in `u`, then the whole set `s` is contained in `u`. -/
theorem IsPreconnected.subset_of_closure_inter_subset (hs : IsPreconnected s) (hu : IsOpen u)
(h'u : (s ∩ u).Nonempty) (h : closure u ∩ s ⊆ u) : s ⊆ u := by
have A : s ⊆ u ∪ (closure u)ᶜ := by
intro x hx
by_cases xu : x ∈ u
· exact Or.inl xu
· right
intro h'x
exact xu (h (mem_inter h'x hx))
apply hs.subset_left_of_subset_union hu isClosed_closure.isOpen_compl _ A h'u
exact disjoint_compl_right.mono_right (compl_subset_compl.2 subset_closure)
#align is_preconnected.subset_of_closure_inter_subset IsPreconnected.subset_of_closure_inter_subset
theorem IsPreconnected.prod [TopologicalSpace β] {s : Set α} {t : Set β} (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ×ˢ t) := by
apply isPreconnected_of_forall_pair
rintro ⟨a₁, b₁⟩ ⟨ha₁, hb₁⟩ ⟨a₂, b₂⟩ ⟨ha₂, hb₂⟩
refine ⟨Prod.mk a₁ '' t ∪ flip Prod.mk b₂ '' s, ?_, .inl ⟨b₁, hb₁, rfl⟩, .inr ⟨a₂, ha₂, rfl⟩, ?_⟩
· rintro _ (⟨y, hy, rfl⟩ | ⟨x, hx, rfl⟩)
exacts [⟨ha₁, hy⟩, ⟨hx, hb₂⟩]
· exact (ht.image _ (Continuous.Prod.mk _).continuousOn).union (a₁, b₂) ⟨b₂, hb₂, rfl⟩
⟨a₁, ha₁, rfl⟩ (hs.image _ (continuous_id.prod_mk continuous_const).continuousOn)
#align is_preconnected.prod IsPreconnected.prod
theorem IsConnected.prod [TopologicalSpace β] {s : Set α} {t : Set β} (hs : IsConnected s)
(ht : IsConnected t) : IsConnected (s ×ˢ t) :=
⟨hs.1.prod ht.1, hs.2.prod ht.2⟩
#align is_connected.prod IsConnected.prod
theorem isPreconnected_univ_pi [∀ i, TopologicalSpace (π i)] {s : ∀ i, Set (π i)}
(hs : ∀ i, IsPreconnected (s i)) : IsPreconnected (pi univ s) := by
rintro u v uo vo hsuv ⟨f, hfs, hfu⟩ ⟨g, hgs, hgv⟩
rcases exists_finset_piecewise_mem_of_mem_nhds (uo.mem_nhds hfu) g with ⟨I, hI⟩
induction' I using Finset.induction_on with i I _ ihI
· refine ⟨g, hgs, ⟨?_, hgv⟩⟩
simpa using hI
· rw [Finset.piecewise_insert] at hI
have := I.piecewise_mem_set_pi hfs hgs
refine (hsuv this).elim ihI fun h => ?_
set S := update (I.piecewise f g) i '' s i
have hsub : S ⊆ pi univ s := by
refine image_subset_iff.2 fun z hz => ?_
rwa [update_preimage_univ_pi]
exact fun j _ => this j trivial
have hconn : IsPreconnected S :=
(hs i).image _ (continuous_const.update i continuous_id).continuousOn
have hSu : (S ∩ u).Nonempty := ⟨_, mem_image_of_mem _ (hfs _ trivial), hI⟩
have hSv : (S ∩ v).Nonempty := ⟨_, ⟨_, this _ trivial, update_eq_self _ _⟩, h⟩
refine (hconn u v uo vo (hsub.trans hsuv) hSu hSv).mono ?_
exact inter_subset_inter_left _ hsub
#align is_preconnected_univ_pi isPreconnected_univ_pi
@[simp]
theorem isConnected_univ_pi [∀ i, TopologicalSpace (π i)] {s : ∀ i, Set (π i)} :
IsConnected (pi univ s) ↔ ∀ i, IsConnected (s i) := by
simp only [IsConnected, ← univ_pi_nonempty_iff, forall_and, and_congr_right_iff]
refine fun hne => ⟨fun hc i => ?_, isPreconnected_univ_pi⟩
rw [← eval_image_univ_pi hne]
exact hc.image _ (continuous_apply _).continuousOn
#align is_connected_univ_pi isConnected_univ_pi
theorem Sigma.isConnected_iff [∀ i, TopologicalSpace (π i)] {s : Set (Σi, π i)} :
IsConnected s ↔ ∃ i t, IsConnected t ∧ s = Sigma.mk i '' t := by
refine ⟨fun hs => ?_, ?_⟩
· obtain ⟨⟨i, x⟩, hx⟩ := hs.nonempty
have : s ⊆ range (Sigma.mk i) :=
hs.isPreconnected.subset_isClopen isClopen_range_sigmaMk ⟨⟨i, x⟩, hx, x, rfl⟩
exact ⟨i, Sigma.mk i ⁻¹' s, hs.preimage_of_isOpenMap sigma_mk_injective isOpenMap_sigmaMk this,
(Set.image_preimage_eq_of_subset this).symm⟩
· rintro ⟨i, t, ht, rfl⟩
exact ht.image _ continuous_sigmaMk.continuousOn
#align sigma.is_connected_iff Sigma.isConnected_iff
theorem Sigma.isPreconnected_iff [hι : Nonempty ι] [∀ i, TopologicalSpace (π i)]
{s : Set (Σi, π i)} : IsPreconnected s ↔ ∃ i t, IsPreconnected t ∧ s = Sigma.mk i '' t := by
refine ⟨fun hs => ?_, ?_⟩
· obtain rfl | h := s.eq_empty_or_nonempty
· exact ⟨Classical.choice hι, ∅, isPreconnected_empty, (Set.image_empty _).symm⟩
· obtain ⟨a, t, ht, rfl⟩ := Sigma.isConnected_iff.1 ⟨h, hs⟩
exact ⟨a, t, ht.isPreconnected, rfl⟩
· rintro ⟨a, t, ht, rfl⟩
exact ht.image _ continuous_sigmaMk.continuousOn
#align sigma.is_preconnected_iff Sigma.isPreconnected_iff
theorem Sum.isConnected_iff [TopologicalSpace β] {s : Set (Sum α β)} :
IsConnected s ↔
(∃ t, IsConnected t ∧ s = Sum.inl '' t) ∨ ∃ t, IsConnected t ∧ s = Sum.inr '' t := by
refine ⟨fun hs => ?_, ?_⟩
· obtain ⟨x | x, hx⟩ := hs.nonempty
· have h : s ⊆ range Sum.inl :=
hs.isPreconnected.subset_isClopen isClopen_range_inl ⟨.inl x, hx, x, rfl⟩
refine Or.inl ⟨Sum.inl ⁻¹' s, ?_, ?_⟩
· exact hs.preimage_of_isOpenMap Sum.inl_injective isOpenMap_inl h
· exact (image_preimage_eq_of_subset h).symm
· have h : s ⊆ range Sum.inr :=
hs.isPreconnected.subset_isClopen isClopen_range_inr ⟨.inr x, hx, x, rfl⟩
refine Or.inr ⟨Sum.inr ⁻¹' s, ?_, ?_⟩
· exact hs.preimage_of_isOpenMap Sum.inr_injective isOpenMap_inr h
· exact (image_preimage_eq_of_subset h).symm
· rintro (⟨t, ht, rfl⟩ | ⟨t, ht, rfl⟩)
· exact ht.image _ continuous_inl.continuousOn
· exact ht.image _ continuous_inr.continuousOn
#align sum.is_connected_iff Sum.isConnected_iff
theorem Sum.isPreconnected_iff [TopologicalSpace β] {s : Set (Sum α β)} :
IsPreconnected s ↔
(∃ t, IsPreconnected t ∧ s = Sum.inl '' t) ∨ ∃ t, IsPreconnected t ∧ s = Sum.inr '' t := by
refine ⟨fun hs => ?_, ?_⟩
· obtain rfl | h := s.eq_empty_or_nonempty
· exact Or.inl ⟨∅, isPreconnected_empty, (Set.image_empty _).symm⟩
obtain ⟨t, ht, rfl⟩ | ⟨t, ht, rfl⟩ := Sum.isConnected_iff.1 ⟨h, hs⟩
· exact Or.inl ⟨t, ht.isPreconnected, rfl⟩
· exact Or.inr ⟨t, ht.isPreconnected, rfl⟩
· rintro (⟨t, ht, rfl⟩ | ⟨t, ht, rfl⟩)
· exact ht.image _ continuous_inl.continuousOn
· exact ht.image _ continuous_inr.continuousOn
#align sum.is_preconnected_iff Sum.isPreconnected_iff
/-- The connected component of a point is the maximal connected set
that contains this point. -/
def connectedComponent (x : α) : Set α :=
⋃₀ { s : Set α | IsPreconnected s ∧ x ∈ s }
#align connected_component connectedComponent
/-- Given a set `F` in a topological space `α` and a point `x : α`, the connected
component of `x` in `F` is the connected component of `x` in the subtype `F` seen as
a set in `α`. This definition does not make sense if `x` is not in `F` so we return the
empty set in this case. -/
def connectedComponentIn (F : Set α) (x : α) : Set α :=
if h : x ∈ F then (↑) '' connectedComponent (⟨x, h⟩ : F) else ∅
#align connected_component_in connectedComponentIn
theorem connectedComponentIn_eq_image {F : Set α} {x : α} (h : x ∈ F) :
connectedComponentIn F x = (↑) '' connectedComponent (⟨x, h⟩ : F) :=
dif_pos h
#align connected_component_in_eq_image connectedComponentIn_eq_image
theorem connectedComponentIn_eq_empty {F : Set α} {x : α} (h : x ∉ F) :
connectedComponentIn F x = ∅ :=
dif_neg h
#align connected_component_in_eq_empty connectedComponentIn_eq_empty
theorem mem_connectedComponent {x : α} : x ∈ connectedComponent x :=
mem_sUnion_of_mem (mem_singleton x) ⟨isPreconnected_singleton, mem_singleton x⟩
#align mem_connected_component mem_connectedComponent
theorem mem_connectedComponentIn {x : α} {F : Set α} (hx : x ∈ F) :
x ∈ connectedComponentIn F x := by
simp [connectedComponentIn_eq_image hx, mem_connectedComponent, hx]
#align mem_connected_component_in mem_connectedComponentIn
theorem connectedComponent_nonempty {x : α} : (connectedComponent x).Nonempty :=
⟨x, mem_connectedComponent⟩
#align connected_component_nonempty connectedComponent_nonempty
theorem connectedComponentIn_nonempty_iff {x : α} {F : Set α} :
(connectedComponentIn F x).Nonempty ↔ x ∈ F := by
rw [connectedComponentIn]
split_ifs <;> simp [connectedComponent_nonempty, *]
#align connected_component_in_nonempty_iff connectedComponentIn_nonempty_iff
theorem connectedComponentIn_subset (F : Set α) (x : α) : connectedComponentIn F x ⊆ F := by
rw [connectedComponentIn]
split_ifs <;> simp
#align connected_component_in_subset connectedComponentIn_subset
theorem isPreconnected_connectedComponent {x : α} : IsPreconnected (connectedComponent x) :=
isPreconnected_sUnion x _ (fun _ => And.right) fun _ => And.left
#align is_preconnected_connected_component isPreconnected_connectedComponent
theorem isPreconnected_connectedComponentIn {x : α} {F : Set α} :
IsPreconnected (connectedComponentIn F x) := by
rw [connectedComponentIn]; split_ifs
· exact inducing_subtype_val.isPreconnected_image.mpr isPreconnected_connectedComponent
· exact isPreconnected_empty
#align is_preconnected_connected_component_in isPreconnected_connectedComponentIn
theorem isConnected_connectedComponent {x : α} : IsConnected (connectedComponent x) :=
⟨⟨x, mem_connectedComponent⟩, isPreconnected_connectedComponent⟩
#align is_connected_connected_component isConnected_connectedComponent
theorem isConnected_connectedComponentIn_iff {x : α} {F : Set α} :
IsConnected (connectedComponentIn F x) ↔ x ∈ F := by
simp_rw [← connectedComponentIn_nonempty_iff, IsConnected, isPreconnected_connectedComponentIn,
and_true_iff]
#align is_connected_connected_component_in_iff isConnected_connectedComponentIn_iff
theorem IsPreconnected.subset_connectedComponent {x : α} {s : Set α} (H1 : IsPreconnected s)
(H2 : x ∈ s) : s ⊆ connectedComponent x := fun _z hz => mem_sUnion_of_mem hz ⟨H1, H2⟩
#align is_preconnected.subset_connected_component IsPreconnected.subset_connectedComponent
theorem IsPreconnected.subset_connectedComponentIn {x : α} {F : Set α} (hs : IsPreconnected s)
(hxs : x ∈ s) (hsF : s ⊆ F) : s ⊆ connectedComponentIn F x := by
have : IsPreconnected (((↑) : F → α) ⁻¹' s) := by
refine inducing_subtype_val.isPreconnected_image.mp ?_
rwa [Subtype.image_preimage_coe, inter_eq_right.mpr hsF]
have h2xs : (⟨x, hsF hxs⟩ : F) ∈ (↑) ⁻¹' s := by
rw [mem_preimage]
exact hxs
have := this.subset_connectedComponent h2xs
rw [connectedComponentIn_eq_image (hsF hxs)]
refine Subset.trans ?_ (image_subset _ this)
rw [Subtype.image_preimage_coe, inter_eq_right.mpr hsF]
#align is_preconnected.subset_connected_component_in IsPreconnected.subset_connectedComponentIn
theorem IsConnected.subset_connectedComponent {x : α} {s : Set α} (H1 : IsConnected s)
(H2 : x ∈ s) : s ⊆ connectedComponent x :=
H1.2.subset_connectedComponent H2
#align is_connected.subset_connected_component IsConnected.subset_connectedComponent
theorem IsPreconnected.connectedComponentIn {x : α} {F : Set α} (h : IsPreconnected F)
(hx : x ∈ F) : connectedComponentIn F x = F :=
(connectedComponentIn_subset F x).antisymm (h.subset_connectedComponentIn hx subset_rfl)
#align is_preconnected.connected_component_in IsPreconnected.connectedComponentIn
theorem connectedComponent_eq {x y : α} (h : y ∈ connectedComponent x) :
connectedComponent x = connectedComponent y :=
eq_of_subset_of_subset (isConnected_connectedComponent.subset_connectedComponent h)
(isConnected_connectedComponent.subset_connectedComponent
(Set.mem_of_mem_of_subset mem_connectedComponent
(isConnected_connectedComponent.subset_connectedComponent h)))
#align connected_component_eq connectedComponent_eq
theorem connectedComponent_eq_iff_mem {x y : α} :
connectedComponent x = connectedComponent y ↔ x ∈ connectedComponent y :=
⟨fun h => h ▸ mem_connectedComponent, fun h => (connectedComponent_eq h).symm⟩
#align connected_component_eq_iff_mem connectedComponent_eq_iff_mem
theorem connectedComponentIn_eq {x y : α} {F : Set α} (h : y ∈ connectedComponentIn F x) :
connectedComponentIn F x = connectedComponentIn F y := by
have hx : x ∈ F := connectedComponentIn_nonempty_iff.mp ⟨y, h⟩
simp_rw [connectedComponentIn_eq_image hx] at h ⊢
obtain ⟨⟨y, hy⟩, h2y, rfl⟩ := h
simp_rw [connectedComponentIn_eq_image hy, connectedComponent_eq h2y]
#align connected_component_in_eq connectedComponentIn_eq
theorem connectedComponentIn_univ (x : α) : connectedComponentIn univ x = connectedComponent x :=
subset_antisymm
(isPreconnected_connectedComponentIn.subset_connectedComponent <|
mem_connectedComponentIn trivial)
(isPreconnected_connectedComponent.subset_connectedComponentIn mem_connectedComponent <|
subset_univ _)
#align connected_component_in_univ connectedComponentIn_univ
theorem connectedComponent_disjoint {x y : α} (h : connectedComponent x ≠ connectedComponent y) :
Disjoint (connectedComponent x) (connectedComponent y) :=
Set.disjoint_left.2 fun _ h1 h2 =>
h ((connectedComponent_eq h1).trans (connectedComponent_eq h2).symm)
#align connected_component_disjoint connectedComponent_disjoint
theorem isClosed_connectedComponent {x : α} : IsClosed (connectedComponent x) :=
closure_subset_iff_isClosed.1 <|
isConnected_connectedComponent.closure.subset_connectedComponent <|
subset_closure mem_connectedComponent
#align is_closed_connected_component isClosed_connectedComponent
theorem Continuous.image_connectedComponent_subset [TopologicalSpace β] {f : α → β}
(h : Continuous f) (a : α) : f '' connectedComponent a ⊆ connectedComponent (f a) :=
(isConnected_connectedComponent.image f h.continuousOn).subset_connectedComponent
((mem_image f (connectedComponent a) (f a)).2 ⟨a, mem_connectedComponent, rfl⟩)
#align continuous.image_connected_component_subset Continuous.image_connectedComponent_subset
theorem Continuous.image_connectedComponentIn_subset [TopologicalSpace β] {f : α → β} {s : Set α}
{a : α} (hf : Continuous f) (hx : a ∈ s) :
f '' connectedComponentIn s a ⊆ connectedComponentIn (f '' s) (f a) :=
(isPreconnected_connectedComponentIn.image _ hf.continuousOn).subset_connectedComponentIn
(mem_image_of_mem _ <| mem_connectedComponentIn hx)
(image_subset _ <| connectedComponentIn_subset _ _)
theorem Continuous.mapsTo_connectedComponent [TopologicalSpace β] {f : α → β} (h : Continuous f)
(a : α) : MapsTo f (connectedComponent a) (connectedComponent (f a)) :=
mapsTo'.2 <| h.image_connectedComponent_subset a
#align continuous.maps_to_connected_component Continuous.mapsTo_connectedComponent
theorem Continuous.mapsTo_connectedComponentIn [TopologicalSpace β] {f : α → β} {s : Set α}
(h : Continuous f) {a : α} (hx : a ∈ s) :
MapsTo f (connectedComponentIn s a) (connectedComponentIn (f '' s) (f a)) :=
mapsTo'.2 <| image_connectedComponentIn_subset h hx
theorem irreducibleComponent_subset_connectedComponent {x : α} :
irreducibleComponent x ⊆ connectedComponent x :=
isIrreducible_irreducibleComponent.isConnected.subset_connectedComponent mem_irreducibleComponent
#align irreducible_component_subset_connected_component irreducibleComponent_subset_connectedComponent
@[mono]
theorem connectedComponentIn_mono (x : α) {F G : Set α} (h : F ⊆ G) :
connectedComponentIn F x ⊆ connectedComponentIn G x := by
by_cases hx : x ∈ F
· rw [connectedComponentIn_eq_image hx, connectedComponentIn_eq_image (h hx), ←
show ((↑) : G → α) ∘ inclusion h = (↑) from rfl, image_comp]
exact image_subset _ ((continuous_inclusion h).image_connectedComponent_subset ⟨x, hx⟩)
· rw [connectedComponentIn_eq_empty hx]
exact Set.empty_subset _
#align connected_component_in_mono connectedComponentIn_mono
/-- A preconnected space is one where there is no non-trivial open partition. -/
class PreconnectedSpace (α : Type u) [TopologicalSpace α] : Prop where
/-- The universal set `Set.univ` in a preconnected space is a preconnected set. -/
isPreconnected_univ : IsPreconnected (univ : Set α)
#align preconnected_space PreconnectedSpace
export PreconnectedSpace (isPreconnected_univ)
/-- A connected space is a nonempty one where there is no non-trivial open partition. -/
class ConnectedSpace (α : Type u) [TopologicalSpace α] extends PreconnectedSpace α : Prop where
/-- A connected space is nonempty. -/
toNonempty : Nonempty α
#align connected_space ConnectedSpace
attribute [instance 50] ConnectedSpace.toNonempty -- see Note [lower instance priority]
-- see Note [lower instance priority]
theorem isConnected_univ [ConnectedSpace α] : IsConnected (univ : Set α) :=
⟨univ_nonempty, isPreconnected_univ⟩
#align is_connected_univ isConnected_univ
lemma preconnectedSpace_iff_univ : PreconnectedSpace α ↔ IsPreconnected (univ : Set α) :=
⟨fun h ↦ h.1, fun h ↦ ⟨h⟩⟩
lemma connectedSpace_iff_univ : ConnectedSpace α ↔ IsConnected (univ : Set α) :=
⟨fun h ↦ ⟨univ_nonempty, h.1.1⟩,
fun h ↦ ConnectedSpace.mk (toPreconnectedSpace := ⟨h.2⟩) ⟨h.1.some⟩⟩
theorem isPreconnected_range [TopologicalSpace β] [PreconnectedSpace α] {f : α → β}
(h : Continuous f) : IsPreconnected (range f) :=
@image_univ _ _ f ▸ isPreconnected_univ.image _ h.continuousOn
#align is_preconnected_range isPreconnected_range
theorem isConnected_range [TopologicalSpace β] [ConnectedSpace α] {f : α → β} (h : Continuous f) :
IsConnected (range f) :=
⟨range_nonempty f, isPreconnected_range h⟩
#align is_connected_range isConnected_range
theorem Function.Surjective.connectedSpace [ConnectedSpace α] [TopologicalSpace β]
{f : α → β} (hf : Surjective f) (hf' : Continuous f) : ConnectedSpace β := by
rw [connectedSpace_iff_univ, ← hf.range_eq]
exact isConnected_range hf'
instance Quotient.instConnectedSpace {s : Setoid α} [ConnectedSpace α] :
ConnectedSpace (Quotient s) :=
(surjective_quotient_mk' _).connectedSpace continuous_coinduced_rng
theorem DenseRange.preconnectedSpace [TopologicalSpace β] [PreconnectedSpace α] {f : α → β}
(hf : DenseRange f) (hc : Continuous f) : PreconnectedSpace β :=
⟨hf.closure_eq ▸ (isPreconnected_range hc).closure⟩
#align dense_range.preconnected_space DenseRange.preconnectedSpace
theorem connectedSpace_iff_connectedComponent :
ConnectedSpace α ↔ ∃ x : α, connectedComponent x = univ := by
constructor
· rintro ⟨⟨x⟩⟩
exact
⟨x, eq_univ_of_univ_subset <| isPreconnected_univ.subset_connectedComponent (mem_univ x)⟩
· rintro ⟨x, h⟩
haveI : PreconnectedSpace α :=
⟨by rw [← h]; exact isPreconnected_connectedComponent⟩
exact ⟨⟨x⟩⟩
#align connected_space_iff_connected_component connectedSpace_iff_connectedComponent
theorem preconnectedSpace_iff_connectedComponent :
PreconnectedSpace α ↔ ∀ x : α, connectedComponent x = univ := by
constructor
· intro h x
exact eq_univ_of_univ_subset <| isPreconnected_univ.subset_connectedComponent (mem_univ x)
· intro h
cases' isEmpty_or_nonempty α with hα hα
· exact ⟨by rw [univ_eq_empty_iff.mpr hα]; exact isPreconnected_empty⟩
· exact ⟨by rw [← h (Classical.choice hα)]; exact isPreconnected_connectedComponent⟩
#align preconnected_space_iff_connected_component preconnectedSpace_iff_connectedComponent
@[simp]
theorem PreconnectedSpace.connectedComponent_eq_univ {X : Type*} [TopologicalSpace X]
[h : PreconnectedSpace X] (x : X) : connectedComponent x = univ :=
preconnectedSpace_iff_connectedComponent.mp h x
#align preconnected_space.connected_component_eq_univ PreconnectedSpace.connectedComponent_eq_univ
instance [TopologicalSpace β] [PreconnectedSpace α] [PreconnectedSpace β] :
PreconnectedSpace (α × β) :=
⟨by
rw [← univ_prod_univ]
exact isPreconnected_univ.prod isPreconnected_univ⟩
instance [TopologicalSpace β] [ConnectedSpace α] [ConnectedSpace β] : ConnectedSpace (α × β) :=
⟨inferInstance⟩
instance [∀ i, TopologicalSpace (π i)] [∀ i, PreconnectedSpace (π i)] :
PreconnectedSpace (∀ i, π i) :=
⟨by rw [← pi_univ univ]; exact isPreconnected_univ_pi fun i => isPreconnected_univ⟩
instance [∀ i, TopologicalSpace (π i)] [∀ i, ConnectedSpace (π i)] : ConnectedSpace (∀ i, π i) :=
⟨inferInstance⟩
-- see Note [lower instance priority]
instance (priority := 100) PreirreducibleSpace.preconnectedSpace (α : Type u) [TopologicalSpace α]
[PreirreducibleSpace α] : PreconnectedSpace α :=
⟨isPreirreducible_univ.isPreconnected⟩
#align preirreducible_space.preconnected_space PreirreducibleSpace.preconnectedSpace
-- see Note [lower instance priority]
instance (priority := 100) IrreducibleSpace.connectedSpace (α : Type u) [TopologicalSpace α]
[IrreducibleSpace α] : ConnectedSpace α where toNonempty := IrreducibleSpace.toNonempty
#align irreducible_space.connected_space IrreducibleSpace.connectedSpace
/-- A continuous map from a connected space to a disjoint union `Σ i, π i` can be lifted to one of
the components `π i`. See also `ContinuousMap.exists_lift_sigma` for a version with bundled
`ContinuousMap`s. -/
theorem Continuous.exists_lift_sigma [ConnectedSpace α] [∀ i, TopologicalSpace (π i)]
{f : α → Σ i, π i} (hf : Continuous f) :
∃ (i : ι) (g : α → π i), Continuous g ∧ f = Sigma.mk i ∘ g := by
obtain ⟨i, hi⟩ : ∃ i, range f ⊆ range (.mk i) := by
rcases Sigma.isConnected_iff.1 (isConnected_range hf) with ⟨i, s, -, hs⟩
exact ⟨i, hs.trans_subset (image_subset_range _ _)⟩
rcases range_subset_range_iff_exists_comp.1 hi with ⟨g, rfl⟩
refine ⟨i, g, ?_, rfl⟩
rwa [← embedding_sigmaMk.continuous_iff] at hf
theorem nonempty_inter [PreconnectedSpace α] {s t : Set α} :
IsOpen s → IsOpen t → s ∪ t = univ → s.Nonempty → t.Nonempty → (s ∩ t).Nonempty := by
simpa only [univ_inter, univ_subset_iff] using @PreconnectedSpace.isPreconnected_univ α _ _ s t
#align nonempty_inter nonempty_inter
theorem isClopen_iff [PreconnectedSpace α] {s : Set α} : IsClopen s ↔ s = ∅ ∨ s = univ :=
⟨fun hs =>
by_contradiction fun h =>
have h1 : s ≠ ∅ ∧ sᶜ ≠ ∅ :=
⟨mt Or.inl h,
mt (fun h2 => Or.inr <| (by rw [← compl_compl s, h2, compl_empty] : s = univ)) h⟩
let ⟨_, h2, h3⟩ :=
nonempty_inter hs.2 hs.1.isOpen_compl (union_compl_self s) (nonempty_iff_ne_empty.2 h1.1)
(nonempty_iff_ne_empty.2 h1.2)
h3 h2,
by rintro (rfl | rfl) <;> [exact isClopen_empty; exact isClopen_univ]⟩
#align is_clopen_iff isClopen_iff
theorem IsClopen.eq_univ [PreconnectedSpace α] {s : Set α} (h' : IsClopen s) (h : s.Nonempty) :
s = univ :=
(isClopen_iff.mp h').resolve_left h.ne_empty
#align is_clopen.eq_univ IsClopen.eq_univ
section disjoint_subsets
variable [PreconnectedSpace α]
{s : ι → Set α} (h_nonempty : ∀ i, (s i).Nonempty) (h_disj : Pairwise (Disjoint on s))
/-- In a preconnected space, any disjoint family of non-empty clopen subsets has at most one
element. -/
lemma subsingleton_of_disjoint_isClopen
(h_clopen : ∀ i, IsClopen (s i)) :
Subsingleton ι := by
replace h_nonempty : ∀ i, s i ≠ ∅ := by intro i; rw [← nonempty_iff_ne_empty]; exact h_nonempty i
rw [← not_nontrivial_iff_subsingleton]
by_contra contra
obtain ⟨i, j, h_ne⟩ := contra
replace h_ne : s i ∩ s j = ∅ := by
simpa only [← bot_eq_empty, eq_bot_iff, ← inf_eq_inter, ← disjoint_iff_inf_le] using h_disj h_ne
cases' isClopen_iff.mp (h_clopen i) with hi hi
· exact h_nonempty i hi
· rw [hi, univ_inter] at h_ne
exact h_nonempty j h_ne
/-- In a preconnected space, any disjoint cover by non-empty open subsets has at most one
element. -/
lemma subsingleton_of_disjoint_isOpen_iUnion_eq_univ
(h_open : ∀ i, IsOpen (s i)) (h_Union : ⋃ i, s i = univ) :
Subsingleton ι := by
refine subsingleton_of_disjoint_isClopen h_nonempty h_disj (fun i ↦ ⟨?_, h_open i⟩)
rw [← isOpen_compl_iff, compl_eq_univ_diff, ← h_Union, iUnion_diff]
refine isOpen_iUnion (fun j ↦ ?_)
rcases eq_or_ne i j with rfl | h_ne
· simp
· simpa only [(h_disj h_ne.symm).sdiff_eq_left] using h_open j
/-- In a preconnected space, any finite disjoint cover by non-empty closed subsets has at most one
element. -/
lemma subsingleton_of_disjoint_isClosed_iUnion_eq_univ [Finite ι]
(h_closed : ∀ i, IsClosed (s i)) (h_Union : ⋃ i, s i = univ) :
Subsingleton ι := by
refine subsingleton_of_disjoint_isClopen h_nonempty h_disj (fun i ↦ ⟨h_closed i, ?_⟩)
rw [← isClosed_compl_iff, compl_eq_univ_diff, ← h_Union, iUnion_diff]
refine isClosed_iUnion_of_finite (fun j ↦ ?_)
rcases eq_or_ne i j with rfl | h_ne
· simp
· simpa only [(h_disj h_ne.symm).sdiff_eq_left] using h_closed j
end disjoint_subsets
theorem frontier_eq_empty_iff [PreconnectedSpace α] {s : Set α} :
frontier s = ∅ ↔ s = ∅ ∨ s = univ :=
isClopen_iff_frontier_eq_empty.symm.trans isClopen_iff
#align frontier_eq_empty_iff frontier_eq_empty_iff
theorem nonempty_frontier_iff [PreconnectedSpace α] {s : Set α} :
(frontier s).Nonempty ↔ s.Nonempty ∧ s ≠ univ := by
simp only [nonempty_iff_ne_empty, Ne, frontier_eq_empty_iff, not_or]
#align nonempty_frontier_iff nonempty_frontier_iff
theorem Subtype.preconnectedSpace {s : Set α} (h : IsPreconnected s) : PreconnectedSpace s where
isPreconnected_univ := by
rwa [← inducing_subtype_val.isPreconnected_image, image_univ, Subtype.range_val]
#align subtype.preconnected_space Subtype.preconnectedSpace
theorem Subtype.connectedSpace {s : Set α} (h : IsConnected s) : ConnectedSpace s where
toPreconnectedSpace := Subtype.preconnectedSpace h.isPreconnected
toNonempty := h.nonempty.to_subtype
#align subtype.connected_space Subtype.connectedSpace
theorem isPreconnected_iff_preconnectedSpace {s : Set α} : IsPreconnected s ↔ PreconnectedSpace s :=
⟨Subtype.preconnectedSpace, fun h => by
simpa using isPreconnected_univ.image ((↑) : s → α) continuous_subtype_val.continuousOn⟩
#align is_preconnected_iff_preconnected_space isPreconnected_iff_preconnectedSpace
theorem isConnected_iff_connectedSpace {s : Set α} : IsConnected s ↔ ConnectedSpace s :=
⟨Subtype.connectedSpace, fun h =>
⟨nonempty_subtype.mp h.2, isPreconnected_iff_preconnectedSpace.mpr h.1⟩⟩
#align is_connected_iff_connected_space isConnected_iff_connectedSpace
/-- In a preconnected space, given a transitive relation `P`, if `P x y` and `P y x` are true
for `y` close enough to `x`, then `P x y` holds for all `x, y`. This is a version of the fact
that, if an equivalence relation has open classes, then it has a single equivalence class. -/
lemma PreconnectedSpace.induction₂' [PreconnectedSpace α] (P : α → α → Prop)
(h : ∀ x, ∀ᶠ y in 𝓝 x, P x y ∧ P y x) (h' : Transitive P) (x y : α) :
P x y := by
let u := {z | P x z}
have A : IsClosed u := by
apply isClosed_iff_nhds.2 (fun z hz ↦ ?_)
rcases hz _ (h z) with ⟨t, ht, h't⟩
exact h' h't ht.2
have B : IsOpen u := by
apply isOpen_iff_mem_nhds.2 (fun z hz ↦ ?_)
filter_upwards [h z] with t ht
exact h' hz ht.1
have C : u.Nonempty := ⟨x, (mem_of_mem_nhds (h x)).1⟩
have D : u = Set.univ := IsClopen.eq_univ ⟨A, B⟩ C
show y ∈ u
simp [D]
/-- In a preconnected space, if a symmetric transitive relation `P x y` is true for `y` close
enough to `x`, then it holds for all `x, y`. This is a version of the fact that, if an equivalence
relation has open classes, then it has a single equivalence class. -/
lemma PreconnectedSpace.induction₂ [PreconnectedSpace α] (P : α → α → Prop)
(h : ∀ x, ∀ᶠ y in 𝓝 x, P x y) (h' : Transitive P) (h'' : Symmetric P) (x y : α) :
P x y := by
refine PreconnectedSpace.induction₂' P (fun z ↦ ?_) h' x y
filter_upwards [h z] with a ha
exact ⟨ha, h'' ha⟩
/-- In a preconnected set, given a transitive relation `P`, if `P x y` and `P y x` are true
for `y` close enough to `x`, then `P x y` holds for all `x, y`. This is a version of the fact
that, if an equivalence relation has open classes, then it has a single equivalence class. -/
lemma IsPreconnected.induction₂' {s : Set α} (hs : IsPreconnected s) (P : α → α → Prop)
(h : ∀ x ∈ s, ∀ᶠ y in 𝓝[s] x, P x y ∧ P y x)
(h' : ∀ x y z, x ∈ s → y ∈ s → z ∈ s → P x y → P y z → P x z)
{x y : α} (hx : x ∈ s) (hy : y ∈ s) : P x y := by
let Q : s → s → Prop := fun a b ↦ P a b
show Q ⟨x, hx⟩ ⟨y, hy⟩
have : PreconnectedSpace s := Subtype.preconnectedSpace hs
apply PreconnectedSpace.induction₂'
· rintro ⟨x, hx⟩
have Z := h x hx
rwa [nhdsWithin_eq_map_subtype_coe] at Z
· rintro ⟨a, ha⟩ ⟨b, hb⟩ ⟨c, hc⟩ hab hbc
exact h' a b c ha hb hc hab hbc
/-- In a preconnected set, if a symmetric transitive relation `P x y` is true for `y` close
enough to `x`, then it holds for all `x, y`. This is a version of the fact that, if an equivalence
relation has open classes, then it has a single equivalence class. -/
lemma IsPreconnected.induction₂ {s : Set α} (hs : IsPreconnected s) (P : α → α → Prop)
(h : ∀ x ∈ s, ∀ᶠ y in 𝓝[s] x, P x y)
(h' : ∀ x y z, x ∈ s → y ∈ s → z ∈ s → P x y → P y z → P x z)
(h'' : ∀ x y, x ∈ s → y ∈ s → P x y → P y x)
{x y : α} (hx : x ∈ s) (hy : y ∈ s) : P x y := by
apply hs.induction₂' P (fun z hz ↦ ?_) h' hx hy
filter_upwards [h z hz, self_mem_nhdsWithin] with a ha h'a
exact ⟨ha, h'' z a hz h'a ha⟩
/-- A set `s` is preconnected if and only if for every cover by two open sets that are disjoint on
`s`, it is contained in one of the two covering sets. -/
theorem isPreconnected_iff_subset_of_disjoint {s : Set α} :
IsPreconnected s ↔
∀ u v, IsOpen u → IsOpen v → s ⊆ u ∪ v → s ∩ (u ∩ v) = ∅ → s ⊆ u ∨ s ⊆ v := by
constructor <;> intro h
· intro u v hu hv hs huv
specialize h u v hu hv hs
contrapose! huv
simp [not_subset] at huv
rcases huv with ⟨⟨x, hxs, hxu⟩, ⟨y, hys, hyv⟩⟩
have hxv : x ∈ v := or_iff_not_imp_left.mp (hs hxs) hxu
have hyu : y ∈ u := or_iff_not_imp_right.mp (hs hys) hyv
exact h ⟨y, hys, hyu⟩ ⟨x, hxs, hxv⟩
· intro u v hu hv hs hsu hsv
by_contra H
specialize h u v hu hv hs (Set.not_nonempty_iff_eq_empty.mp H)
apply H
cases' h with h h
· rcases hsv with ⟨x, hxs, hxv⟩
exact ⟨x, hxs, ⟨h hxs, hxv⟩⟩
· rcases hsu with ⟨x, hxs, hxu⟩
exact ⟨x, hxs, ⟨hxu, h hxs⟩⟩
#align is_preconnected_iff_subset_of_disjoint isPreconnected_iff_subset_of_disjoint
/-- A set `s` is connected if and only if
for every cover by a finite collection of open sets that are pairwise disjoint on `s`,
it is contained in one of the members of the collection. -/
theorem isConnected_iff_sUnion_disjoint_open {s : Set α} :
IsConnected s ↔
∀ U : Finset (Set α), (∀ u v : Set α, u ∈ U → v ∈ U → (s ∩ (u ∩ v)).Nonempty → u = v) →
(∀ u ∈ U, IsOpen u) → (s ⊆ ⋃₀ ↑U) → ∃ u ∈ U, s ⊆ u := by
rw [IsConnected, isPreconnected_iff_subset_of_disjoint]
refine ⟨fun ⟨hne, h⟩ U hU hUo hsU => ?_, fun h => ⟨?_, fun u v hu hv hs hsuv => ?_⟩⟩
· induction U using Finset.induction_on with
| empty => exact absurd (by simpa using hsU) hne.not_subset_empty
| @insert u U uU IH =>
simp only [← forall_cond_comm, Finset.forall_mem_insert, Finset.exists_mem_insert,
Finset.coe_insert, sUnion_insert, implies_true, true_and] at *
refine (h _ hUo.1 (⋃₀ ↑U) (isOpen_sUnion hUo.2) hsU ?_).imp_right ?_
· refine subset_empty_iff.1 fun x ⟨hxs, hxu, v, hvU, hxv⟩ => ?_
exact ne_of_mem_of_not_mem hvU uU (hU.1 v hvU ⟨x, hxs, hxu, hxv⟩).symm
· exact IH (fun u hu => (hU.2 u hu).2) hUo.2
· simpa [subset_empty_iff, nonempty_iff_ne_empty] using h ∅
· rw [← not_nonempty_iff_eq_empty] at hsuv
have := hsuv; rw [inter_comm u] at this
simpa [*, or_imp, forall_and] using h {u, v}
#align is_connected_iff_sUnion_disjoint_open isConnected_iff_sUnion_disjoint_open
-- Porting note: `IsPreconnected.subset_isClopen` moved up from here
/-- Preconnected sets are either contained in or disjoint to any given clopen set. -/
theorem disjoint_or_subset_of_isClopen {s t : Set α} (hs : IsPreconnected s) (ht : IsClopen t) :
Disjoint s t ∨ s ⊆ t :=
(disjoint_or_nonempty_inter s t).imp_right <| hs.subset_isClopen ht
#align disjoint_or_subset_of_clopen disjoint_or_subset_of_isClopen
/-- A set `s` is preconnected if and only if
for every cover by two closed sets that are disjoint on `s`,
it is contained in one of the two covering sets. -/
theorem isPreconnected_iff_subset_of_disjoint_closed :
IsPreconnected s ↔
∀ u v, IsClosed u → IsClosed v → s ⊆ u ∪ v → s ∩ (u ∩ v) = ∅ → s ⊆ u ∨ s ⊆ v := by
constructor <;> intro h
· intro u v hu hv hs huv
rw [isPreconnected_closed_iff] at h
specialize h u v hu hv hs
contrapose! huv
simp [not_subset] at huv
rcases huv with ⟨⟨x, hxs, hxu⟩, ⟨y, hys, hyv⟩⟩
have hxv : x ∈ v := or_iff_not_imp_left.mp (hs hxs) hxu
have hyu : y ∈ u := or_iff_not_imp_right.mp (hs hys) hyv
exact h ⟨y, hys, hyu⟩ ⟨x, hxs, hxv⟩
· rw [isPreconnected_closed_iff]
intro u v hu hv hs hsu hsv
by_contra H
specialize h u v hu hv hs (Set.not_nonempty_iff_eq_empty.mp H)
apply H
cases' h with h h
· rcases hsv with ⟨x, hxs, hxv⟩
exact ⟨x, hxs, ⟨h hxs, hxv⟩⟩
· rcases hsu with ⟨x, hxs, hxu⟩
exact ⟨x, hxs, ⟨hxu, h hxs⟩⟩
#align is_preconnected_iff_subset_of_disjoint_closed isPreconnected_iff_subset_of_disjoint_closed
/-- A closed set `s` is preconnected if and only if for every cover by two closed sets that are
disjoint, it is contained in one of the two covering sets. -/
| Mathlib/Topology/Connected/Basic.lean | 1,112 | 1,124 | theorem isPreconnected_iff_subset_of_fully_disjoint_closed {s : Set α} (hs : IsClosed s) :
IsPreconnected s ↔
∀ u v, IsClosed u → IsClosed v → s ⊆ u ∪ v → Disjoint u v → s ⊆ u ∨ s ⊆ v := by |
refine isPreconnected_iff_subset_of_disjoint_closed.trans ⟨?_, ?_⟩ <;> intro H u v hu hv hss huv
· apply H u v hu hv hss
rw [huv.inter_eq, inter_empty]
have H1 := H (u ∩ s) (v ∩ s)
rw [subset_inter_iff, subset_inter_iff] at H1
simp only [Subset.refl, and_true] at H1
apply H1 (hu.inter hs) (hv.inter hs)
· rw [← union_inter_distrib_right]
exact subset_inter hss Subset.rfl
· rwa [disjoint_iff_inter_eq_empty, ← inter_inter_distrib_right, inter_comm]
|
/-
Copyright (c) 2019 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Lu-Ming Zhang
-/
import Mathlib.Data.Matrix.Invertible
import Mathlib.LinearAlgebra.Matrix.Adjugate
import Mathlib.LinearAlgebra.FiniteDimensional
#align_import linear_algebra.matrix.nonsingular_inverse from "leanprover-community/mathlib"@"722b3b152ddd5e0cf21c0a29787c76596cb6b422"
/-!
# Nonsingular inverses
In this file, we define an inverse for square matrices of invertible determinant.
For matrices that are not square or not of full rank, there is a more general notion of
pseudoinverses which we do not consider here.
The definition of inverse used in this file is the adjugate divided by the determinant.
We show that dividing the adjugate by `det A` (if possible), giving a matrix `A⁻¹` (`nonsing_inv`),
will result in a multiplicative inverse to `A`.
Note that there are at least three different inverses in mathlib:
* `A⁻¹` (`Inv.inv`): alone, this satisfies no properties, although it is usually used in
conjunction with `Group` or `GroupWithZero`. On matrices, this is defined to be zero when no
inverse exists.
* `⅟A` (`invOf`): this is only available in the presence of `[Invertible A]`, which guarantees an
inverse exists.
* `Ring.inverse A`: this is defined on any `MonoidWithZero`, and just like `⁻¹` on matrices, is
defined to be zero when no inverse exists.
We start by working with `Invertible`, and show the main results:
* `Matrix.invertibleOfDetInvertible`
* `Matrix.detInvertibleOfInvertible`
* `Matrix.isUnit_iff_isUnit_det`
* `Matrix.mul_eq_one_comm`
After this we define `Matrix.inv` and show it matches `⅟A` and `Ring.inverse A`.
The rest of the results in the file are then about `A⁻¹`
## References
* https://en.wikipedia.org/wiki/Cramer's_rule#Finding_inverse_matrix
## Tags
matrix inverse, cramer, cramer's rule, adjugate
-/
namespace Matrix
universe u u' v
variable {l : Type*} {m : Type u} {n : Type u'} {α : Type v}
open Matrix Equiv Equiv.Perm Finset
/-! ### Matrices are `Invertible` iff their determinants are -/
section Invertible
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
/-- If `A.det` has a constructive inverse, produce one for `A`. -/
def invertibleOfDetInvertible [Invertible A.det] : Invertible A where
invOf := ⅟ A.det • A.adjugate
mul_invOf_self := by
rw [mul_smul_comm, mul_adjugate, smul_smul, invOf_mul_self, one_smul]
invOf_mul_self := by
rw [smul_mul_assoc, adjugate_mul, smul_smul, invOf_mul_self, one_smul]
#align matrix.invertible_of_det_invertible Matrix.invertibleOfDetInvertible
theorem invOf_eq [Invertible A.det] [Invertible A] : ⅟ A = ⅟ A.det • A.adjugate := by
letI := invertibleOfDetInvertible A
convert (rfl : ⅟ A = _)
#align matrix.inv_of_eq Matrix.invOf_eq
/-- `A.det` is invertible if `A` has a left inverse. -/
def detInvertibleOfLeftInverse (h : B * A = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [mul_comm, ← det_mul, h, det_one]
invOf_mul_self := by rw [← det_mul, h, det_one]
#align matrix.det_invertible_of_left_inverse Matrix.detInvertibleOfLeftInverse
/-- `A.det` is invertible if `A` has a right inverse. -/
def detInvertibleOfRightInverse (h : A * B = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [← det_mul, h, det_one]
invOf_mul_self := by rw [mul_comm, ← det_mul, h, det_one]
#align matrix.det_invertible_of_right_inverse Matrix.detInvertibleOfRightInverse
/-- If `A` has a constructive inverse, produce one for `A.det`. -/
def detInvertibleOfInvertible [Invertible A] : Invertible A.det :=
detInvertibleOfLeftInverse A (⅟ A) (invOf_mul_self _)
#align matrix.det_invertible_of_invertible Matrix.detInvertibleOfInvertible
theorem det_invOf [Invertible A] [Invertible A.det] : (⅟ A).det = ⅟ A.det := by
letI := detInvertibleOfInvertible A
convert (rfl : _ = ⅟ A.det)
#align matrix.det_inv_of Matrix.det_invOf
/-- Together `Matrix.detInvertibleOfInvertible` and `Matrix.invertibleOfDetInvertible` form an
equivalence, although both sides of the equiv are subsingleton anyway. -/
@[simps]
def invertibleEquivDetInvertible : Invertible A ≃ Invertible A.det where
toFun := @detInvertibleOfInvertible _ _ _ _ _ A
invFun := @invertibleOfDetInvertible _ _ _ _ _ A
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
#align matrix.invertible_equiv_det_invertible Matrix.invertibleEquivDetInvertible
variable {A B}
theorem mul_eq_one_comm : A * B = 1 ↔ B * A = 1 :=
suffices ∀ A B : Matrix n n α, A * B = 1 → B * A = 1 from ⟨this A B, this B A⟩
fun A B h => by
letI : Invertible B.det := detInvertibleOfLeftInverse _ _ h
letI : Invertible B := invertibleOfDetInvertible B
calc
B * A = B * A * (B * ⅟ B) := by rw [mul_invOf_self, Matrix.mul_one]
_ = B * (A * B * ⅟ B) := by simp only [Matrix.mul_assoc]
_ = B * ⅟ B := by rw [h, Matrix.one_mul]
_ = 1 := mul_invOf_self B
#align matrix.mul_eq_one_comm Matrix.mul_eq_one_comm
variable (A B)
/-- We can construct an instance of invertible A if A has a left inverse. -/
def invertibleOfLeftInverse (h : B * A = 1) : Invertible A :=
⟨B, h, mul_eq_one_comm.mp h⟩
#align matrix.invertible_of_left_inverse Matrix.invertibleOfLeftInverse
/-- We can construct an instance of invertible A if A has a right inverse. -/
def invertibleOfRightInverse (h : A * B = 1) : Invertible A :=
⟨B, mul_eq_one_comm.mp h, h⟩
#align matrix.invertible_of_right_inverse Matrix.invertibleOfRightInverse
/-- Given a proof that `A.det` has a constructive inverse, lift `A` to `(Matrix n n α)ˣ`-/
def unitOfDetInvertible [Invertible A.det] : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ A (invertibleOfDetInvertible A)
#align matrix.unit_of_det_invertible Matrix.unitOfDetInvertible
/-- When lowered to a prop, `Matrix.invertibleEquivDetInvertible` forms an `iff`. -/
theorem isUnit_iff_isUnit_det : IsUnit A ↔ IsUnit A.det := by
simp only [← nonempty_invertible_iff_isUnit, (invertibleEquivDetInvertible A).nonempty_congr]
#align matrix.is_unit_iff_is_unit_det Matrix.isUnit_iff_isUnit_det
@[simp]
theorem isUnits_det_units (A : (Matrix n n α)ˣ) : IsUnit (A : Matrix n n α).det :=
isUnit_iff_isUnit_det _ |>.mp A.isUnit
/-! #### Variants of the statements above with `IsUnit`-/
theorem isUnit_det_of_invertible [Invertible A] : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfInvertible A)
#align matrix.is_unit_det_of_invertible Matrix.isUnit_det_of_invertible
variable {A B}
theorem isUnit_of_left_inverse (h : B * A = 1) : IsUnit A :=
⟨⟨A, B, mul_eq_one_comm.mp h, h⟩, rfl⟩
#align matrix.is_unit_of_left_inverse Matrix.isUnit_of_left_inverse
theorem exists_left_inverse_iff_isUnit : (∃ B, B * A = 1) ↔ IsUnit A :=
⟨fun ⟨_, h⟩ ↦ isUnit_of_left_inverse h, fun h ↦ have := h.invertible; ⟨⅟A, invOf_mul_self' A⟩⟩
theorem isUnit_of_right_inverse (h : A * B = 1) : IsUnit A :=
⟨⟨A, B, h, mul_eq_one_comm.mp h⟩, rfl⟩
#align matrix.is_unit_of_right_inverse Matrix.isUnit_of_right_inverse
theorem exists_right_inverse_iff_isUnit : (∃ B, A * B = 1) ↔ IsUnit A :=
⟨fun ⟨_, h⟩ ↦ isUnit_of_right_inverse h, fun h ↦ have := h.invertible; ⟨⅟A, mul_invOf_self' A⟩⟩
theorem isUnit_det_of_left_inverse (h : B * A = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfLeftInverse _ _ h)
#align matrix.is_unit_det_of_left_inverse Matrix.isUnit_det_of_left_inverse
theorem isUnit_det_of_right_inverse (h : A * B = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfRightInverse _ _ h)
#align matrix.is_unit_det_of_right_inverse Matrix.isUnit_det_of_right_inverse
theorem det_ne_zero_of_left_inverse [Nontrivial α] (h : B * A = 1) : A.det ≠ 0 :=
(isUnit_det_of_left_inverse h).ne_zero
#align matrix.det_ne_zero_of_left_inverse Matrix.det_ne_zero_of_left_inverse
theorem det_ne_zero_of_right_inverse [Nontrivial α] (h : A * B = 1) : A.det ≠ 0 :=
(isUnit_det_of_right_inverse h).ne_zero
#align matrix.det_ne_zero_of_right_inverse Matrix.det_ne_zero_of_right_inverse
end Invertible
section Inv
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem isUnit_det_transpose (h : IsUnit A.det) : IsUnit Aᵀ.det := by
rw [det_transpose]
exact h
#align matrix.is_unit_det_transpose Matrix.isUnit_det_transpose
/-! ### A noncomputable `Inv` instance -/
/-- The inverse of a square matrix, when it is invertible (and zero otherwise). -/
noncomputable instance inv : Inv (Matrix n n α) :=
⟨fun A => Ring.inverse A.det • A.adjugate⟩
theorem inv_def (A : Matrix n n α) : A⁻¹ = Ring.inverse A.det • A.adjugate :=
rfl
#align matrix.inv_def Matrix.inv_def
theorem nonsing_inv_apply_not_isUnit (h : ¬IsUnit A.det) : A⁻¹ = 0 := by
rw [inv_def, Ring.inverse_non_unit _ h, zero_smul]
#align matrix.nonsing_inv_apply_not_is_unit Matrix.nonsing_inv_apply_not_isUnit
theorem nonsing_inv_apply (h : IsUnit A.det) : A⁻¹ = (↑h.unit⁻¹ : α) • A.adjugate := by
rw [inv_def, ← Ring.inverse_unit h.unit, IsUnit.unit_spec]
#align matrix.nonsing_inv_apply Matrix.nonsing_inv_apply
/-- The nonsingular inverse is the same as `invOf` when `A` is invertible. -/
@[simp]
theorem invOf_eq_nonsing_inv [Invertible A] : ⅟ A = A⁻¹ := by
letI := detInvertibleOfInvertible A
rw [inv_def, Ring.inverse_invertible, invOf_eq]
#align matrix.inv_of_eq_nonsing_inv Matrix.invOf_eq_nonsing_inv
/-- Coercing the result of `Units.instInv` is the same as coercing first and applying the
nonsingular inverse. -/
@[simp, norm_cast]
theorem coe_units_inv (A : (Matrix n n α)ˣ) : ↑A⁻¹ = (A⁻¹ : Matrix n n α) := by
letI := A.invertible
rw [← invOf_eq_nonsing_inv, invOf_units]
#align matrix.coe_units_inv Matrix.coe_units_inv
/-- The nonsingular inverse is the same as the general `Ring.inverse`. -/
theorem nonsing_inv_eq_ring_inverse : A⁻¹ = Ring.inverse A := by
by_cases h_det : IsUnit A.det
· cases (A.isUnit_iff_isUnit_det.mpr h_det).nonempty_invertible
rw [← invOf_eq_nonsing_inv, Ring.inverse_invertible]
· have h := mt A.isUnit_iff_isUnit_det.mp h_det
rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit A h_det]
#align matrix.nonsing_inv_eq_ring_inverse Matrix.nonsing_inv_eq_ring_inverse
theorem transpose_nonsing_inv : A⁻¹ᵀ = Aᵀ⁻¹ := by
rw [inv_def, inv_def, transpose_smul, det_transpose, adjugate_transpose]
#align matrix.transpose_nonsing_inv Matrix.transpose_nonsing_inv
theorem conjTranspose_nonsing_inv [StarRing α] : A⁻¹ᴴ = Aᴴ⁻¹ := by
rw [inv_def, inv_def, conjTranspose_smul, det_conjTranspose, adjugate_conjTranspose,
Ring.inverse_star]
#align matrix.conj_transpose_nonsing_inv Matrix.conjTranspose_nonsing_inv
/-- The `nonsing_inv` of `A` is a right inverse. -/
@[simp]
theorem mul_nonsing_inv (h : IsUnit A.det) : A * A⁻¹ = 1 := by
cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, mul_invOf_self]
#align matrix.mul_nonsing_inv Matrix.mul_nonsing_inv
/-- The `nonsing_inv` of `A` is a left inverse. -/
@[simp]
theorem nonsing_inv_mul (h : IsUnit A.det) : A⁻¹ * A = 1 := by
cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, invOf_mul_self]
#align matrix.nonsing_inv_mul Matrix.nonsing_inv_mul
instance [Invertible A] : Invertible A⁻¹ := by
rw [← invOf_eq_nonsing_inv]
infer_instance
@[simp]
theorem inv_inv_of_invertible [Invertible A] : A⁻¹⁻¹ = A := by
simp only [← invOf_eq_nonsing_inv, invOf_invOf]
#align matrix.inv_inv_of_invertible Matrix.inv_inv_of_invertible
@[simp]
theorem mul_nonsing_inv_cancel_right (B : Matrix m n α) (h : IsUnit A.det) : B * A * A⁻¹ = B := by
simp [Matrix.mul_assoc, mul_nonsing_inv A h]
#align matrix.mul_nonsing_inv_cancel_right Matrix.mul_nonsing_inv_cancel_right
@[simp]
theorem mul_nonsing_inv_cancel_left (B : Matrix n m α) (h : IsUnit A.det) : A * (A⁻¹ * B) = B := by
simp [← Matrix.mul_assoc, mul_nonsing_inv A h]
#align matrix.mul_nonsing_inv_cancel_left Matrix.mul_nonsing_inv_cancel_left
@[simp]
theorem nonsing_inv_mul_cancel_right (B : Matrix m n α) (h : IsUnit A.det) : B * A⁻¹ * A = B := by
simp [Matrix.mul_assoc, nonsing_inv_mul A h]
#align matrix.nonsing_inv_mul_cancel_right Matrix.nonsing_inv_mul_cancel_right
@[simp]
theorem nonsing_inv_mul_cancel_left (B : Matrix n m α) (h : IsUnit A.det) : A⁻¹ * (A * B) = B := by
simp [← Matrix.mul_assoc, nonsing_inv_mul A h]
#align matrix.nonsing_inv_mul_cancel_left Matrix.nonsing_inv_mul_cancel_left
@[simp]
theorem mul_inv_of_invertible [Invertible A] : A * A⁻¹ = 1 :=
mul_nonsing_inv A (isUnit_det_of_invertible A)
#align matrix.mul_inv_of_invertible Matrix.mul_inv_of_invertible
@[simp]
theorem inv_mul_of_invertible [Invertible A] : A⁻¹ * A = 1 :=
nonsing_inv_mul A (isUnit_det_of_invertible A)
#align matrix.inv_mul_of_invertible Matrix.inv_mul_of_invertible
@[simp]
theorem mul_inv_cancel_right_of_invertible (B : Matrix m n α) [Invertible A] : B * A * A⁻¹ = B :=
mul_nonsing_inv_cancel_right A B (isUnit_det_of_invertible A)
#align matrix.mul_inv_cancel_right_of_invertible Matrix.mul_inv_cancel_right_of_invertible
@[simp]
theorem mul_inv_cancel_left_of_invertible (B : Matrix n m α) [Invertible A] : A * (A⁻¹ * B) = B :=
mul_nonsing_inv_cancel_left A B (isUnit_det_of_invertible A)
#align matrix.mul_inv_cancel_left_of_invertible Matrix.mul_inv_cancel_left_of_invertible
@[simp]
theorem inv_mul_cancel_right_of_invertible (B : Matrix m n α) [Invertible A] : B * A⁻¹ * A = B :=
nonsing_inv_mul_cancel_right A B (isUnit_det_of_invertible A)
#align matrix.inv_mul_cancel_right_of_invertible Matrix.inv_mul_cancel_right_of_invertible
@[simp]
theorem inv_mul_cancel_left_of_invertible (B : Matrix n m α) [Invertible A] : A⁻¹ * (A * B) = B :=
nonsing_inv_mul_cancel_left A B (isUnit_det_of_invertible A)
#align matrix.inv_mul_cancel_left_of_invertible Matrix.inv_mul_cancel_left_of_invertible
theorem inv_mul_eq_iff_eq_mul_of_invertible (A B C : Matrix n n α) [Invertible A] :
A⁻¹ * B = C ↔ B = A * C :=
⟨fun h => by rw [← h, mul_inv_cancel_left_of_invertible],
fun h => by rw [h, inv_mul_cancel_left_of_invertible]⟩
#align matrix.inv_mul_eq_iff_eq_mul_of_invertible Matrix.inv_mul_eq_iff_eq_mul_of_invertible
theorem mul_inv_eq_iff_eq_mul_of_invertible (A B C : Matrix n n α) [Invertible A] :
B * A⁻¹ = C ↔ B = C * A :=
⟨fun h => by rw [← h, inv_mul_cancel_right_of_invertible],
fun h => by rw [h, mul_inv_cancel_right_of_invertible]⟩
#align matrix.mul_inv_eq_iff_eq_mul_of_invertible Matrix.mul_inv_eq_iff_eq_mul_of_invertible
lemma mul_right_injective_of_invertible [Invertible A] :
Function.Injective (fun (x : Matrix n m α) => A * x) :=
fun _ _ h => by simpa only [inv_mul_cancel_left_of_invertible] using congr_arg (A⁻¹ * ·) h
lemma mul_left_injective_of_invertible [Invertible A] :
Function.Injective (fun (x : Matrix m n α) => x * A) :=
fun a x hax => by simpa only [mul_inv_cancel_right_of_invertible] using congr_arg (· * A⁻¹) hax
lemma mul_right_inj_of_invertible [Invertible A] {x y : Matrix n m α} : A * x = A * y ↔ x = y :=
(mul_right_injective_of_invertible A).eq_iff
lemma mul_left_inj_of_invertible [Invertible A] {x y : Matrix m n α} : x * A = y * A ↔ x = y :=
(mul_left_injective_of_invertible A).eq_iff
end Inv
section InjectiveMul
variable [Fintype n] [Fintype m] [DecidableEq m] [CommRing α]
variable [Fintype l] [DecidableEq l]
lemma mul_left_injective_of_inv (A : Matrix m n α) (B : Matrix n m α) (h : A * B = 1) :
Function.Injective (fun x : Matrix l m α => x * A) := fun _ _ g => by
simpa only [Matrix.mul_assoc, Matrix.mul_one, h] using congr_arg (· * B) g
lemma mul_right_injective_of_inv (A : Matrix m n α) (B : Matrix n m α) (h : A * B = 1) :
Function.Injective (fun x : Matrix m l α => B * x) :=
fun _ _ g => by simpa only [← Matrix.mul_assoc, Matrix.one_mul, h] using congr_arg (A * ·) g
end InjectiveMul
section vecMul
variable [DecidableEq m] [DecidableEq n]
section Semiring
variable {R : Type*} [Semiring R]
theorem vecMul_surjective_iff_exists_left_inverse [Fintype m] [Finite n] {A : Matrix m n R} :
Function.Surjective A.vecMul ↔ ∃ B : Matrix n m R, B * A = 1 := by
cases nonempty_fintype n
refine ⟨fun h ↦ ?_, fun ⟨B, hBA⟩ y ↦ ⟨y ᵥ* B, by simp [hBA]⟩⟩
choose rows hrows using (h <| Pi.single · 1)
refine ⟨Matrix.of rows, Matrix.ext fun i j => ?_⟩
rw [mul_apply_eq_vecMul, one_eq_pi_single, ← hrows]
rfl
theorem mulVec_surjective_iff_exists_right_inverse [Finite m] [Fintype n] {A : Matrix m n R} :
Function.Surjective A.mulVec ↔ ∃ B : Matrix n m R, A * B = 1 := by
cases nonempty_fintype m
refine ⟨fun h ↦ ?_, fun ⟨B, hBA⟩ y ↦ ⟨B *ᵥ y, by simp [hBA]⟩⟩
choose cols hcols using (h <| Pi.single · 1)
refine ⟨(Matrix.of cols)ᵀ, Matrix.ext fun i j ↦ ?_⟩
rw [one_eq_pi_single, Pi.single_comm, ← hcols j]
rfl
end Semiring
variable {R K : Type*} [CommRing R] [Field K] [Fintype m]
theorem vecMul_surjective_iff_isUnit {A : Matrix m m R} :
Function.Surjective A.vecMul ↔ IsUnit A := by
rw [vecMul_surjective_iff_exists_left_inverse, exists_left_inverse_iff_isUnit]
theorem mulVec_surjective_iff_isUnit {A : Matrix m m R} :
Function.Surjective A.mulVec ↔ IsUnit A := by
rw [mulVec_surjective_iff_exists_right_inverse, exists_right_inverse_iff_isUnit]
theorem vecMul_injective_iff_isUnit {A : Matrix m m K} :
Function.Injective A.vecMul ↔ IsUnit A := by
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· rw [← vecMul_surjective_iff_isUnit]
exact LinearMap.surjective_of_injective (f := A.vecMulLinear) h
change Function.Injective A.vecMulLinear
rw [← LinearMap.ker_eq_bot, LinearMap.ker_eq_bot']
intro c hc
replace h := h.invertible
simpa using congr_arg A⁻¹.vecMulLinear hc
theorem mulVec_injective_iff_isUnit {A : Matrix m m K} :
Function.Injective A.mulVec ↔ IsUnit A := by
rw [← isUnit_transpose, ← vecMul_injective_iff_isUnit]
simp_rw [vecMul_transpose]
theorem linearIndependent_rows_iff_isUnit {A : Matrix m m K} :
LinearIndependent K (fun i ↦ A i) ↔ IsUnit A := by
rw [← transpose_transpose A, ← mulVec_injective_iff, ← coe_mulVecLin, mulVecLin_transpose,
transpose_transpose, ← vecMul_injective_iff_isUnit, coe_vecMulLinear]
theorem linearIndependent_cols_iff_isUnit {A : Matrix m m K} :
LinearIndependent K (fun i ↦ Aᵀ i) ↔ IsUnit A := by
rw [← transpose_transpose A, isUnit_transpose, linearIndependent_rows_iff_isUnit,
transpose_transpose]
theorem vecMul_surjective_of_invertible (A : Matrix m m R) [Invertible A] :
Function.Surjective A.vecMul :=
vecMul_surjective_iff_isUnit.2 <| isUnit_of_invertible A
theorem mulVec_surjective_of_invertible (A : Matrix m m R) [Invertible A] :
Function.Surjective A.mulVec :=
mulVec_surjective_iff_isUnit.2 <| isUnit_of_invertible A
theorem vecMul_injective_of_invertible (A : Matrix m m K) [Invertible A] :
Function.Injective A.vecMul :=
vecMul_injective_iff_isUnit.2 <| isUnit_of_invertible A
theorem mulVec_injective_of_invertible (A : Matrix m m K) [Invertible A] :
Function.Injective A.mulVec :=
mulVec_injective_iff_isUnit.2 <| isUnit_of_invertible A
theorem linearIndependent_rows_of_invertible (A : Matrix m m K) [Invertible A] :
LinearIndependent K (fun i ↦ A i) :=
linearIndependent_rows_iff_isUnit.2 <| isUnit_of_invertible A
theorem linearIndependent_cols_of_invertible (A : Matrix m m K) [Invertible A] :
LinearIndependent K (fun i ↦ Aᵀ i) :=
linearIndependent_cols_iff_isUnit.2 <| isUnit_of_invertible A
end vecMul
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem nonsing_inv_cancel_or_zero : A⁻¹ * A = 1 ∧ A * A⁻¹ = 1 ∨ A⁻¹ = 0 := by
by_cases h : IsUnit A.det
· exact Or.inl ⟨nonsing_inv_mul _ h, mul_nonsing_inv _ h⟩
· exact Or.inr (nonsing_inv_apply_not_isUnit _ h)
#align matrix.nonsing_inv_cancel_or_zero Matrix.nonsing_inv_cancel_or_zero
theorem det_nonsing_inv_mul_det (h : IsUnit A.det) : A⁻¹.det * A.det = 1 := by
rw [← det_mul, A.nonsing_inv_mul h, det_one]
#align matrix.det_nonsing_inv_mul_det Matrix.det_nonsing_inv_mul_det
@[simp]
theorem det_nonsing_inv : A⁻¹.det = Ring.inverse A.det := by
by_cases h : IsUnit A.det
· cases h.nonempty_invertible
letI := invertibleOfDetInvertible A
rw [Ring.inverse_invertible, ← invOf_eq_nonsing_inv, det_invOf]
cases isEmpty_or_nonempty n
· rw [det_isEmpty, det_isEmpty, Ring.inverse_one]
· rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit _ h, det_zero ‹_›]
#align matrix.det_nonsing_inv Matrix.det_nonsing_inv
theorem isUnit_nonsing_inv_det (h : IsUnit A.det) : IsUnit A⁻¹.det :=
isUnit_of_mul_eq_one _ _ (A.det_nonsing_inv_mul_det h)
#align matrix.is_unit_nonsing_inv_det Matrix.isUnit_nonsing_inv_det
@[simp]
theorem nonsing_inv_nonsing_inv (h : IsUnit A.det) : A⁻¹⁻¹ = A :=
calc
A⁻¹⁻¹ = 1 * A⁻¹⁻¹ := by rw [Matrix.one_mul]
_ = A * A⁻¹ * A⁻¹⁻¹ := by rw [A.mul_nonsing_inv h]
_ = A := by
rw [Matrix.mul_assoc, A⁻¹.mul_nonsing_inv (A.isUnit_nonsing_inv_det h), Matrix.mul_one]
#align matrix.nonsing_inv_nonsing_inv Matrix.nonsing_inv_nonsing_inv
theorem isUnit_nonsing_inv_det_iff {A : Matrix n n α} : IsUnit A⁻¹.det ↔ IsUnit A.det := by
rw [Matrix.det_nonsing_inv, isUnit_ring_inverse]
#align matrix.is_unit_nonsing_inv_det_iff Matrix.isUnit_nonsing_inv_det_iff
-- `IsUnit.invertible` lifts the proposition `IsUnit A` to a constructive inverse of `A`.
/-- A version of `Matrix.invertibleOfDetInvertible` with the inverse defeq to `A⁻¹` that is
therefore noncomputable. -/
noncomputable def invertibleOfIsUnitDet (h : IsUnit A.det) : Invertible A :=
⟨A⁻¹, nonsing_inv_mul A h, mul_nonsing_inv A h⟩
#align matrix.invertible_of_is_unit_det Matrix.invertibleOfIsUnitDet
/-- A version of `Matrix.unitOfDetInvertible` with the inverse defeq to `A⁻¹` that is therefore
noncomputable. -/
noncomputable def nonsingInvUnit (h : IsUnit A.det) : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ _ (invertibleOfIsUnitDet A h)
#align matrix.nonsing_inv_unit Matrix.nonsingInvUnit
theorem unitOfDetInvertible_eq_nonsingInvUnit [Invertible A.det] :
unitOfDetInvertible A = nonsingInvUnit A (isUnit_of_invertible _) := by
ext
rfl
#align matrix.unit_of_det_invertible_eq_nonsing_inv_unit Matrix.unitOfDetInvertible_eq_nonsingInvUnit
variable {A} {B}
/-- If matrix A is left invertible, then its inverse equals its left inverse. -/
theorem inv_eq_left_inv (h : B * A = 1) : A⁻¹ = B :=
letI := invertibleOfLeftInverse _ _ h
invOf_eq_nonsing_inv A ▸ invOf_eq_left_inv h
#align matrix.inv_eq_left_inv Matrix.inv_eq_left_inv
/-- If matrix A is right invertible, then its inverse equals its right inverse. -/
theorem inv_eq_right_inv (h : A * B = 1) : A⁻¹ = B :=
inv_eq_left_inv (mul_eq_one_comm.2 h)
#align matrix.inv_eq_right_inv Matrix.inv_eq_right_inv
section InvEqInv
variable {C : Matrix n n α}
/-- The left inverse of matrix A is unique when existing. -/
| Mathlib/LinearAlgebra/Matrix/NonsingularInverse.lean | 546 | 547 | theorem left_inv_eq_left_inv (h : B * A = 1) (g : C * A = 1) : B = C := by |
rw [← inv_eq_left_inv h, ← inv_eq_left_inv g]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Basic
import Mathlib.Data.Nat.SuccPred
#align_import set_theory.ordinal.arithmetic from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Ordinal arithmetic
Ordinals have an addition (corresponding to disjoint union) that turns them into an additive
monoid, and a multiplication (corresponding to the lexicographic order on the product) that turns
them into a monoid. One can also define correspondingly a subtraction, a division, a successor
function, a power function and a logarithm function.
We also define limit ordinals and prove the basic induction principle on ordinals separating
successor ordinals and limit ordinals, in `limitRecOn`.
## Main definitions and results
* `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that
every element of `o₁` is smaller than every element of `o₂`.
* `o₁ - o₂` is the unique ordinal `o` such that `o₂ + o = o₁`, when `o₂ ≤ o₁`.
* `o₁ * o₂` is the lexicographic order on `o₂ × o₁`.
* `o₁ / o₂` is the ordinal `o` such that `o₁ = o₂ * o + o'` with `o' < o₂`. We also define the
divisibility predicate, and a modulo operation.
* `Order.succ o = o + 1` is the successor of `o`.
* `pred o` if the predecessor of `o`. If `o` is not a successor, we set `pred o = o`.
We discuss the properties of casts of natural numbers of and of `ω` with respect to these
operations.
Some properties of the operations are also used to discuss general tools on ordinals:
* `IsLimit o`: an ordinal is a limit ordinal if it is neither `0` nor a successor.
* `limitRecOn` is the main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals.
* `IsNormal`: a function `f : Ordinal → Ordinal` satisfies `IsNormal` if it is strictly increasing
and order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`.
* `enumOrd`: enumerates an unbounded set of ordinals by the ordinals themselves.
* `sup`, `lsub`: the supremum / least strict upper bound of an indexed family of ordinals in
`Type u`, as an ordinal in `Type u`.
* `bsup`, `blsub`: the supremum / least strict upper bound of a set of ordinals indexed by ordinals
less than a given ordinal `o`.
Various other basic arithmetic results are given in `Principal.lean` instead.
-/
assert_not_exists Field
assert_not_exists Module
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal Ordinal
universe u v w
namespace Ordinal
variable {α : Type*} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Further properties of addition on ordinals -/
@[simp]
theorem lift_add (a b : Ordinal.{v}) : lift.{u} (a + b) = lift.{u} a + lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.sumLexCongr (RelIso.preimage Equiv.ulift _) (RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_add Ordinal.lift_add
@[simp]
theorem lift_succ (a : Ordinal.{v}) : lift.{u} (succ a) = succ (lift.{u} a) := by
rw [← add_one_eq_succ, lift_add, lift_one]
rfl
#align ordinal.lift_succ Ordinal.lift_succ
instance add_contravariantClass_le : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· ≤ ·) :=
⟨fun a b c =>
inductionOn a fun α r hr =>
inductionOn b fun β₁ s₁ hs₁ =>
inductionOn c fun β₂ s₂ hs₂ ⟨f⟩ =>
⟨have fl : ∀ a, f (Sum.inl a) = Sum.inl a := fun a => by
simpa only [InitialSeg.trans_apply, InitialSeg.leAdd_apply] using
@InitialSeg.eq _ _ _ _ _
((InitialSeg.leAdd r s₁).trans f) (InitialSeg.leAdd r s₂) a
have : ∀ b, { b' // f (Sum.inr b) = Sum.inr b' } := by
intro b; cases e : f (Sum.inr b)
· rw [← fl] at e
have := f.inj' e
contradiction
· exact ⟨_, rfl⟩
let g (b) := (this b).1
have fr : ∀ b, f (Sum.inr b) = Sum.inr (g b) := fun b => (this b).2
⟨⟨⟨g, fun x y h => by
injection f.inj' (by rw [fr, fr, h] : f (Sum.inr x) = f (Sum.inr y))⟩,
@fun a b => by
-- Porting note:
-- `relEmbedding.coe_fn_to_embedding` & `initial_seg.coe_fn_to_rel_embedding`
-- → `InitialSeg.coe_coe_fn`
simpa only [Sum.lex_inr_inr, fr, InitialSeg.coe_coe_fn, Embedding.coeFn_mk] using
@RelEmbedding.map_rel_iff _ _ _ _ f.toRelEmbedding (Sum.inr a) (Sum.inr b)⟩,
fun a b H => by
rcases f.init (by rw [fr] <;> exact Sum.lex_inr_inr.2 H) with ⟨a' | a', h⟩
· rw [fl] at h
cases h
· rw [fr] at h
exact ⟨a', Sum.inr.inj h⟩⟩⟩⟩
#align ordinal.add_contravariant_class_le Ordinal.add_contravariantClass_le
theorem add_left_cancel (a) {b c : Ordinal} : a + b = a + c ↔ b = c := by
simp only [le_antisymm_iff, add_le_add_iff_left]
#align ordinal.add_left_cancel Ordinal.add_left_cancel
private theorem add_lt_add_iff_left' (a) {b c : Ordinal} : a + b < a + c ↔ b < c := by
rw [← not_le, ← not_le, add_le_add_iff_left]
instance add_covariantClass_lt : CovariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).2⟩
#align ordinal.add_covariant_class_lt Ordinal.add_covariantClass_lt
instance add_contravariantClass_lt : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).1⟩
#align ordinal.add_contravariant_class_lt Ordinal.add_contravariantClass_lt
instance add_swap_contravariantClass_lt :
ContravariantClass Ordinal.{u} Ordinal.{u} (swap (· + ·)) (· < ·) :=
⟨fun _a _b _c => lt_imp_lt_of_le_imp_le fun h => add_le_add_right h _⟩
#align ordinal.add_swap_contravariant_class_lt Ordinal.add_swap_contravariantClass_lt
theorem add_le_add_iff_right {a b : Ordinal} : ∀ n : ℕ, a + n ≤ b + n ↔ a ≤ b
| 0 => by simp
| n + 1 => by
simp only [natCast_succ, add_succ, add_succ, succ_le_succ_iff, add_le_add_iff_right]
#align ordinal.add_le_add_iff_right Ordinal.add_le_add_iff_right
theorem add_right_cancel {a b : Ordinal} (n : ℕ) : a + n = b + n ↔ a = b := by
simp only [le_antisymm_iff, add_le_add_iff_right]
#align ordinal.add_right_cancel Ordinal.add_right_cancel
theorem add_eq_zero_iff {a b : Ordinal} : a + b = 0 ↔ a = 0 ∧ b = 0 :=
inductionOn a fun α r _ =>
inductionOn b fun β s _ => by
simp_rw [← type_sum_lex, type_eq_zero_iff_isEmpty]
exact isEmpty_sum
#align ordinal.add_eq_zero_iff Ordinal.add_eq_zero_iff
theorem left_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : a = 0 :=
(add_eq_zero_iff.1 h).1
#align ordinal.left_eq_zero_of_add_eq_zero Ordinal.left_eq_zero_of_add_eq_zero
theorem right_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : b = 0 :=
(add_eq_zero_iff.1 h).2
#align ordinal.right_eq_zero_of_add_eq_zero Ordinal.right_eq_zero_of_add_eq_zero
/-! ### The predecessor of an ordinal -/
/-- The ordinal predecessor of `o` is `o'` if `o = succ o'`,
and `o` otherwise. -/
def pred (o : Ordinal) : Ordinal :=
if h : ∃ a, o = succ a then Classical.choose h else o
#align ordinal.pred Ordinal.pred
@[simp]
theorem pred_succ (o) : pred (succ o) = o := by
have h : ∃ a, succ o = succ a := ⟨_, rfl⟩;
simpa only [pred, dif_pos h] using (succ_injective <| Classical.choose_spec h).symm
#align ordinal.pred_succ Ordinal.pred_succ
theorem pred_le_self (o) : pred o ≤ o :=
if h : ∃ a, o = succ a then by
let ⟨a, e⟩ := h
rw [e, pred_succ]; exact le_succ a
else by rw [pred, dif_neg h]
#align ordinal.pred_le_self Ordinal.pred_le_self
theorem pred_eq_iff_not_succ {o} : pred o = o ↔ ¬∃ a, o = succ a :=
⟨fun e ⟨a, e'⟩ => by rw [e', pred_succ] at e; exact (lt_succ a).ne e, fun h => dif_neg h⟩
#align ordinal.pred_eq_iff_not_succ Ordinal.pred_eq_iff_not_succ
theorem pred_eq_iff_not_succ' {o} : pred o = o ↔ ∀ a, o ≠ succ a := by
simpa using pred_eq_iff_not_succ
#align ordinal.pred_eq_iff_not_succ' Ordinal.pred_eq_iff_not_succ'
theorem pred_lt_iff_is_succ {o} : pred o < o ↔ ∃ a, o = succ a :=
Iff.trans (by simp only [le_antisymm_iff, pred_le_self, true_and_iff, not_le])
(iff_not_comm.1 pred_eq_iff_not_succ).symm
#align ordinal.pred_lt_iff_is_succ Ordinal.pred_lt_iff_is_succ
@[simp]
theorem pred_zero : pred 0 = 0 :=
pred_eq_iff_not_succ'.2 fun a => (succ_ne_zero a).symm
#align ordinal.pred_zero Ordinal.pred_zero
theorem succ_pred_iff_is_succ {o} : succ (pred o) = o ↔ ∃ a, o = succ a :=
⟨fun e => ⟨_, e.symm⟩, fun ⟨a, e⟩ => by simp only [e, pred_succ]⟩
#align ordinal.succ_pred_iff_is_succ Ordinal.succ_pred_iff_is_succ
theorem succ_lt_of_not_succ {o b : Ordinal} (h : ¬∃ a, o = succ a) : succ b < o ↔ b < o :=
⟨(lt_succ b).trans, fun l => lt_of_le_of_ne (succ_le_of_lt l) fun e => h ⟨_, e.symm⟩⟩
#align ordinal.succ_lt_of_not_succ Ordinal.succ_lt_of_not_succ
theorem lt_pred {a b} : a < pred b ↔ succ a < b :=
if h : ∃ a, b = succ a then by
let ⟨c, e⟩ := h
rw [e, pred_succ, succ_lt_succ_iff]
else by simp only [pred, dif_neg h, succ_lt_of_not_succ h]
#align ordinal.lt_pred Ordinal.lt_pred
theorem pred_le {a b} : pred a ≤ b ↔ a ≤ succ b :=
le_iff_le_iff_lt_iff_lt.2 lt_pred
#align ordinal.pred_le Ordinal.pred_le
@[simp]
theorem lift_is_succ {o : Ordinal.{v}} : (∃ a, lift.{u} o = succ a) ↔ ∃ a, o = succ a :=
⟨fun ⟨a, h⟩ =>
let ⟨b, e⟩ := lift_down <| show a ≤ lift.{u} o from le_of_lt <| h.symm ▸ lt_succ a
⟨b, lift_inj.1 <| by rw [h, ← e, lift_succ]⟩,
fun ⟨a, h⟩ => ⟨lift.{u} a, by simp only [h, lift_succ]⟩⟩
#align ordinal.lift_is_succ Ordinal.lift_is_succ
@[simp]
theorem lift_pred (o : Ordinal.{v}) : lift.{u} (pred o) = pred (lift.{u} o) :=
if h : ∃ a, o = succ a then by cases' h with a e; simp only [e, pred_succ, lift_succ]
else by rw [pred_eq_iff_not_succ.2 h, pred_eq_iff_not_succ.2 (mt lift_is_succ.1 h)]
#align ordinal.lift_pred Ordinal.lift_pred
/-! ### Limit ordinals -/
/-- A limit ordinal is an ordinal which is not zero and not a successor. -/
def IsLimit (o : Ordinal) : Prop :=
o ≠ 0 ∧ ∀ a < o, succ a < o
#align ordinal.is_limit Ordinal.IsLimit
theorem IsLimit.isSuccLimit {o} (h : IsLimit o) : IsSuccLimit o := isSuccLimit_iff_succ_lt.mpr h.2
theorem IsLimit.succ_lt {o a : Ordinal} (h : IsLimit o) : a < o → succ a < o :=
h.2 a
#align ordinal.is_limit.succ_lt Ordinal.IsLimit.succ_lt
theorem isSuccLimit_zero : IsSuccLimit (0 : Ordinal) := isSuccLimit_bot
theorem not_zero_isLimit : ¬IsLimit 0
| ⟨h, _⟩ => h rfl
#align ordinal.not_zero_is_limit Ordinal.not_zero_isLimit
theorem not_succ_isLimit (o) : ¬IsLimit (succ o)
| ⟨_, h⟩ => lt_irrefl _ (h _ (lt_succ o))
#align ordinal.not_succ_is_limit Ordinal.not_succ_isLimit
theorem not_succ_of_isLimit {o} (h : IsLimit o) : ¬∃ a, o = succ a
| ⟨a, e⟩ => not_succ_isLimit a (e ▸ h)
#align ordinal.not_succ_of_is_limit Ordinal.not_succ_of_isLimit
theorem succ_lt_of_isLimit {o a : Ordinal} (h : IsLimit o) : succ a < o ↔ a < o :=
⟨(lt_succ a).trans, h.2 _⟩
#align ordinal.succ_lt_of_is_limit Ordinal.succ_lt_of_isLimit
theorem le_succ_of_isLimit {o} (h : IsLimit o) {a} : o ≤ succ a ↔ o ≤ a :=
le_iff_le_iff_lt_iff_lt.2 <| succ_lt_of_isLimit h
#align ordinal.le_succ_of_is_limit Ordinal.le_succ_of_isLimit
theorem limit_le {o} (h : IsLimit o) {a} : o ≤ a ↔ ∀ x < o, x ≤ a :=
⟨fun h _x l => l.le.trans h, fun H =>
(le_succ_of_isLimit h).1 <| le_of_not_lt fun hn => not_lt_of_le (H _ hn) (lt_succ a)⟩
#align ordinal.limit_le Ordinal.limit_le
theorem lt_limit {o} (h : IsLimit o) {a} : a < o ↔ ∃ x < o, a < x := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@limit_le _ h a)
#align ordinal.lt_limit Ordinal.lt_limit
@[simp]
theorem lift_isLimit (o) : IsLimit (lift o) ↔ IsLimit o :=
and_congr (not_congr <| by simpa only [lift_zero] using @lift_inj o 0)
⟨fun H a h => lift_lt.1 <| by simpa only [lift_succ] using H _ (lift_lt.2 h), fun H a h => by
obtain ⟨a', rfl⟩ := lift_down h.le
rw [← lift_succ, lift_lt]
exact H a' (lift_lt.1 h)⟩
#align ordinal.lift_is_limit Ordinal.lift_isLimit
theorem IsLimit.pos {o : Ordinal} (h : IsLimit o) : 0 < o :=
lt_of_le_of_ne (Ordinal.zero_le _) h.1.symm
#align ordinal.is_limit.pos Ordinal.IsLimit.pos
theorem IsLimit.one_lt {o : Ordinal} (h : IsLimit o) : 1 < o := by
simpa only [succ_zero] using h.2 _ h.pos
#align ordinal.is_limit.one_lt Ordinal.IsLimit.one_lt
theorem IsLimit.nat_lt {o : Ordinal} (h : IsLimit o) : ∀ n : ℕ, (n : Ordinal) < o
| 0 => h.pos
| n + 1 => h.2 _ (IsLimit.nat_lt h n)
#align ordinal.is_limit.nat_lt Ordinal.IsLimit.nat_lt
theorem zero_or_succ_or_limit (o : Ordinal) : o = 0 ∨ (∃ a, o = succ a) ∨ IsLimit o :=
if o0 : o = 0 then Or.inl o0
else
if h : ∃ a, o = succ a then Or.inr (Or.inl h)
else Or.inr <| Or.inr ⟨o0, fun _a => (succ_lt_of_not_succ h).2⟩
#align ordinal.zero_or_succ_or_limit Ordinal.zero_or_succ_or_limit
/-- Main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals. -/
@[elab_as_elim]
def limitRecOn {C : Ordinal → Sort*} (o : Ordinal) (H₁ : C 0) (H₂ : ∀ o, C o → C (succ o))
(H₃ : ∀ o, IsLimit o → (∀ o' < o, C o') → C o) : C o :=
SuccOrder.limitRecOn o (fun o _ ↦ H₂ o) fun o hl ↦
if h : o = 0 then fun _ ↦ h ▸ H₁ else H₃ o ⟨h, fun _ ↦ hl.succ_lt⟩
#align ordinal.limit_rec_on Ordinal.limitRecOn
@[simp]
theorem limitRecOn_zero {C} (H₁ H₂ H₃) : @limitRecOn C 0 H₁ H₂ H₃ = H₁ := by
rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ isSuccLimit_zero, dif_pos rfl]
#align ordinal.limit_rec_on_zero Ordinal.limitRecOn_zero
@[simp]
theorem limitRecOn_succ {C} (o H₁ H₂ H₃) :
@limitRecOn C (succ o) H₁ H₂ H₃ = H₂ o (@limitRecOn C o H₁ H₂ H₃) := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_succ _ _ (not_isMax _)]
#align ordinal.limit_rec_on_succ Ordinal.limitRecOn_succ
@[simp]
theorem limitRecOn_limit {C} (o H₁ H₂ H₃ h) :
@limitRecOn C o H₁ H₂ H₃ = H₃ o h fun x _h => @limitRecOn C x H₁ H₂ H₃ := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ h.isSuccLimit, dif_neg h.1]
#align ordinal.limit_rec_on_limit Ordinal.limitRecOn_limit
instance orderTopOutSucc (o : Ordinal) : OrderTop (succ o).out.α :=
@OrderTop.mk _ _ (Top.mk _) le_enum_succ
#align ordinal.order_top_out_succ Ordinal.orderTopOutSucc
theorem enum_succ_eq_top {o : Ordinal} :
enum (· < ·) o
(by
rw [type_lt]
exact lt_succ o) =
(⊤ : (succ o).out.α) :=
rfl
#align ordinal.enum_succ_eq_top Ordinal.enum_succ_eq_top
theorem has_succ_of_type_succ_lt {α} {r : α → α → Prop} [wo : IsWellOrder α r]
(h : ∀ a < type r, succ a < type r) (x : α) : ∃ y, r x y := by
use enum r (succ (typein r x)) (h _ (typein_lt_type r x))
convert (enum_lt_enum (typein_lt_type r x)
(h _ (typein_lt_type r x))).mpr (lt_succ _); rw [enum_typein]
#align ordinal.has_succ_of_type_succ_lt Ordinal.has_succ_of_type_succ_lt
theorem out_no_max_of_succ_lt {o : Ordinal} (ho : ∀ a < o, succ a < o) : NoMaxOrder o.out.α :=
⟨has_succ_of_type_succ_lt (by rwa [type_lt])⟩
#align ordinal.out_no_max_of_succ_lt Ordinal.out_no_max_of_succ_lt
theorem bounded_singleton {r : α → α → Prop} [IsWellOrder α r] (hr : (type r).IsLimit) (x) :
Bounded r {x} := by
refine ⟨enum r (succ (typein r x)) (hr.2 _ (typein_lt_type r x)), ?_⟩
intro b hb
rw [mem_singleton_iff.1 hb]
nth_rw 1 [← enum_typein r x]
rw [@enum_lt_enum _ r]
apply lt_succ
#align ordinal.bounded_singleton Ordinal.bounded_singleton
-- Porting note: `· < ·` requires a type ascription for an `IsWellOrder` instance.
theorem type_subrel_lt (o : Ordinal.{u}) :
type (Subrel ((· < ·) : Ordinal → Ordinal → Prop) { o' : Ordinal | o' < o })
= Ordinal.lift.{u + 1} o := by
refine Quotient.inductionOn o ?_
rintro ⟨α, r, wo⟩; apply Quotient.sound
-- Porting note: `symm; refine' [term]` → `refine' [term].symm`
constructor; refine ((RelIso.preimage Equiv.ulift r).trans (enumIso r).symm).symm
#align ordinal.type_subrel_lt Ordinal.type_subrel_lt
theorem mk_initialSeg (o : Ordinal.{u}) :
#{ o' : Ordinal | o' < o } = Cardinal.lift.{u + 1} o.card := by
rw [lift_card, ← type_subrel_lt, card_type]
#align ordinal.mk_initial_seg Ordinal.mk_initialSeg
/-! ### Normal ordinal functions -/
/-- A normal ordinal function is a strictly increasing function which is
order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`. -/
def IsNormal (f : Ordinal → Ordinal) : Prop :=
(∀ o, f o < f (succ o)) ∧ ∀ o, IsLimit o → ∀ a, f o ≤ a ↔ ∀ b < o, f b ≤ a
#align ordinal.is_normal Ordinal.IsNormal
theorem IsNormal.limit_le {f} (H : IsNormal f) :
∀ {o}, IsLimit o → ∀ {a}, f o ≤ a ↔ ∀ b < o, f b ≤ a :=
@H.2
#align ordinal.is_normal.limit_le Ordinal.IsNormal.limit_le
theorem IsNormal.limit_lt {f} (H : IsNormal f) {o} (h : IsLimit o) {a} :
a < f o ↔ ∃ b < o, a < f b :=
not_iff_not.1 <| by simpa only [exists_prop, not_exists, not_and, not_lt] using H.2 _ h a
#align ordinal.is_normal.limit_lt Ordinal.IsNormal.limit_lt
theorem IsNormal.strictMono {f} (H : IsNormal f) : StrictMono f := fun a b =>
limitRecOn b (Not.elim (not_lt_of_le <| Ordinal.zero_le _))
(fun _b IH h =>
(lt_or_eq_of_le (le_of_lt_succ h)).elim (fun h => (IH h).trans (H.1 _)) fun e => e ▸ H.1 _)
fun _b l _IH h => lt_of_lt_of_le (H.1 a) ((H.2 _ l _).1 le_rfl _ (l.2 _ h))
#align ordinal.is_normal.strict_mono Ordinal.IsNormal.strictMono
theorem IsNormal.monotone {f} (H : IsNormal f) : Monotone f :=
H.strictMono.monotone
#align ordinal.is_normal.monotone Ordinal.IsNormal.monotone
theorem isNormal_iff_strictMono_limit (f : Ordinal → Ordinal) :
IsNormal f ↔ StrictMono f ∧ ∀ o, IsLimit o → ∀ a, (∀ b < o, f b ≤ a) → f o ≤ a :=
⟨fun hf => ⟨hf.strictMono, fun a ha c => (hf.2 a ha c).2⟩, fun ⟨hs, hl⟩ =>
⟨fun a => hs (lt_succ a), fun a ha c =>
⟨fun hac _b hba => ((hs hba).trans_le hac).le, hl a ha c⟩⟩⟩
#align ordinal.is_normal_iff_strict_mono_limit Ordinal.isNormal_iff_strictMono_limit
theorem IsNormal.lt_iff {f} (H : IsNormal f) {a b} : f a < f b ↔ a < b :=
StrictMono.lt_iff_lt <| H.strictMono
#align ordinal.is_normal.lt_iff Ordinal.IsNormal.lt_iff
theorem IsNormal.le_iff {f} (H : IsNormal f) {a b} : f a ≤ f b ↔ a ≤ b :=
le_iff_le_iff_lt_iff_lt.2 H.lt_iff
#align ordinal.is_normal.le_iff Ordinal.IsNormal.le_iff
theorem IsNormal.inj {f} (H : IsNormal f) {a b} : f a = f b ↔ a = b := by
simp only [le_antisymm_iff, H.le_iff]
#align ordinal.is_normal.inj Ordinal.IsNormal.inj
theorem IsNormal.self_le {f} (H : IsNormal f) (a) : a ≤ f a :=
lt_wf.self_le_of_strictMono H.strictMono a
#align ordinal.is_normal.self_le Ordinal.IsNormal.self_le
theorem IsNormal.le_set {f o} (H : IsNormal f) (p : Set Ordinal) (p0 : p.Nonempty) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f a ≤ o :=
⟨fun h a pa => (H.le_iff.2 ((H₂ _).1 le_rfl _ pa)).trans h, fun h => by
-- Porting note: `refine'` didn't work well so `induction` is used
induction b using limitRecOn with
| H₁ =>
cases' p0 with x px
have := Ordinal.le_zero.1 ((H₂ _).1 (Ordinal.zero_le _) _ px)
rw [this] at px
exact h _ px
| H₂ S _ =>
rcases not_forall₂.1 (mt (H₂ S).2 <| (lt_succ S).not_le) with ⟨a, h₁, h₂⟩
exact (H.le_iff.2 <| succ_le_of_lt <| not_le.1 h₂).trans (h _ h₁)
| H₃ S L _ =>
refine (H.2 _ L _).2 fun a h' => ?_
rcases not_forall₂.1 (mt (H₂ a).2 h'.not_le) with ⟨b, h₁, h₂⟩
exact (H.le_iff.2 <| (not_le.1 h₂).le).trans (h _ h₁)⟩
#align ordinal.is_normal.le_set Ordinal.IsNormal.le_set
theorem IsNormal.le_set' {f o} (H : IsNormal f) (p : Set α) (p0 : p.Nonempty) (g : α → Ordinal) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, g a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f (g a) ≤ o := by
simpa [H₂] using H.le_set (g '' p) (p0.image g) b
#align ordinal.is_normal.le_set' Ordinal.IsNormal.le_set'
theorem IsNormal.refl : IsNormal id :=
⟨lt_succ, fun _o l _a => Ordinal.limit_le l⟩
#align ordinal.is_normal.refl Ordinal.IsNormal.refl
theorem IsNormal.trans {f g} (H₁ : IsNormal f) (H₂ : IsNormal g) : IsNormal (f ∘ g) :=
⟨fun _x => H₁.lt_iff.2 (H₂.1 _), fun o l _a =>
H₁.le_set' (· < o) ⟨0, l.pos⟩ g _ fun _c => H₂.2 _ l _⟩
#align ordinal.is_normal.trans Ordinal.IsNormal.trans
theorem IsNormal.isLimit {f} (H : IsNormal f) {o} (l : IsLimit o) : IsLimit (f o) :=
⟨ne_of_gt <| (Ordinal.zero_le _).trans_lt <| H.lt_iff.2 l.pos, fun _ h =>
let ⟨_b, h₁, h₂⟩ := (H.limit_lt l).1 h
(succ_le_of_lt h₂).trans_lt (H.lt_iff.2 h₁)⟩
#align ordinal.is_normal.is_limit Ordinal.IsNormal.isLimit
theorem IsNormal.le_iff_eq {f} (H : IsNormal f) {a} : f a ≤ a ↔ f a = a :=
(H.self_le a).le_iff_eq
#align ordinal.is_normal.le_iff_eq Ordinal.IsNormal.le_iff_eq
theorem add_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a + b ≤ c ↔ ∀ b' < b, a + b' ≤ c :=
⟨fun h b' l => (add_le_add_left l.le _).trans h, fun H =>
le_of_not_lt <| by
-- Porting note: `induction` tactics are required because of the parser bug.
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
intro l
suffices ∀ x : β, Sum.Lex r s (Sum.inr x) (enum _ _ l) by
-- Porting note: `revert` & `intro` is required because `cases'` doesn't replace
-- `enum _ _ l` in `this`.
revert this; cases' enum _ _ l with x x <;> intro this
· cases this (enum s 0 h.pos)
· exact irrefl _ (this _)
intro x
rw [← typein_lt_typein (Sum.Lex r s), typein_enum]
have := H _ (h.2 _ (typein_lt_type s x))
rw [add_succ, succ_le_iff] at this
refine
(RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨a | b, h⟩
· exact Sum.inl a
· exact Sum.inr ⟨b, by cases h; assumption⟩
· rcases a with ⟨a | a, h₁⟩ <;> rcases b with ⟨b | b, h₂⟩ <;> cases h₁ <;> cases h₂ <;>
rintro ⟨⟩ <;> constructor <;> assumption⟩
#align ordinal.add_le_of_limit Ordinal.add_le_of_limit
theorem add_isNormal (a : Ordinal) : IsNormal (a + ·) :=
⟨fun b => (add_lt_add_iff_left a).2 (lt_succ b), fun _b l _c => add_le_of_limit l⟩
#align ordinal.add_is_normal Ordinal.add_isNormal
theorem add_isLimit (a) {b} : IsLimit b → IsLimit (a + b) :=
(add_isNormal a).isLimit
#align ordinal.add_is_limit Ordinal.add_isLimit
alias IsLimit.add := add_isLimit
#align ordinal.is_limit.add Ordinal.IsLimit.add
/-! ### Subtraction on ordinals-/
/-- The set in the definition of subtraction is nonempty. -/
theorem sub_nonempty {a b : Ordinal} : { o | a ≤ b + o }.Nonempty :=
⟨a, le_add_left _ _⟩
#align ordinal.sub_nonempty Ordinal.sub_nonempty
/-- `a - b` is the unique ordinal satisfying `b + (a - b) = a` when `b ≤ a`. -/
instance sub : Sub Ordinal :=
⟨fun a b => sInf { o | a ≤ b + o }⟩
theorem le_add_sub (a b : Ordinal) : a ≤ b + (a - b) :=
csInf_mem sub_nonempty
#align ordinal.le_add_sub Ordinal.le_add_sub
theorem sub_le {a b c : Ordinal} : a - b ≤ c ↔ a ≤ b + c :=
⟨fun h => (le_add_sub a b).trans (add_le_add_left h _), fun h => csInf_le' h⟩
#align ordinal.sub_le Ordinal.sub_le
theorem lt_sub {a b c : Ordinal} : a < b - c ↔ c + a < b :=
lt_iff_lt_of_le_iff_le sub_le
#align ordinal.lt_sub Ordinal.lt_sub
theorem add_sub_cancel (a b : Ordinal) : a + b - a = b :=
le_antisymm (sub_le.2 <| le_rfl) ((add_le_add_iff_left a).1 <| le_add_sub _ _)
#align ordinal.add_sub_cancel Ordinal.add_sub_cancel
theorem sub_eq_of_add_eq {a b c : Ordinal} (h : a + b = c) : c - a = b :=
h ▸ add_sub_cancel _ _
#align ordinal.sub_eq_of_add_eq Ordinal.sub_eq_of_add_eq
theorem sub_le_self (a b : Ordinal) : a - b ≤ a :=
sub_le.2 <| le_add_left _ _
#align ordinal.sub_le_self Ordinal.sub_le_self
protected theorem add_sub_cancel_of_le {a b : Ordinal} (h : b ≤ a) : b + (a - b) = a :=
(le_add_sub a b).antisymm'
(by
rcases zero_or_succ_or_limit (a - b) with (e | ⟨c, e⟩ | l)
· simp only [e, add_zero, h]
· rw [e, add_succ, succ_le_iff, ← lt_sub, e]
exact lt_succ c
· exact (add_le_of_limit l).2 fun c l => (lt_sub.1 l).le)
#align ordinal.add_sub_cancel_of_le Ordinal.add_sub_cancel_of_le
theorem le_sub_of_le {a b c : Ordinal} (h : b ≤ a) : c ≤ a - b ↔ b + c ≤ a := by
rw [← add_le_add_iff_left b, Ordinal.add_sub_cancel_of_le h]
#align ordinal.le_sub_of_le Ordinal.le_sub_of_le
theorem sub_lt_of_le {a b c : Ordinal} (h : b ≤ a) : a - b < c ↔ a < b + c :=
lt_iff_lt_of_le_iff_le (le_sub_of_le h)
#align ordinal.sub_lt_of_le Ordinal.sub_lt_of_le
instance existsAddOfLE : ExistsAddOfLE Ordinal :=
⟨fun h => ⟨_, (Ordinal.add_sub_cancel_of_le h).symm⟩⟩
@[simp]
theorem sub_zero (a : Ordinal) : a - 0 = a := by simpa only [zero_add] using add_sub_cancel 0 a
#align ordinal.sub_zero Ordinal.sub_zero
@[simp]
theorem zero_sub (a : Ordinal) : 0 - a = 0 := by rw [← Ordinal.le_zero]; apply sub_le_self
#align ordinal.zero_sub Ordinal.zero_sub
@[simp]
theorem sub_self (a : Ordinal) : a - a = 0 := by simpa only [add_zero] using add_sub_cancel a 0
#align ordinal.sub_self Ordinal.sub_self
protected theorem sub_eq_zero_iff_le {a b : Ordinal} : a - b = 0 ↔ a ≤ b :=
⟨fun h => by simpa only [h, add_zero] using le_add_sub a b, fun h => by
rwa [← Ordinal.le_zero, sub_le, add_zero]⟩
#align ordinal.sub_eq_zero_iff_le Ordinal.sub_eq_zero_iff_le
theorem sub_sub (a b c : Ordinal) : a - b - c = a - (b + c) :=
eq_of_forall_ge_iff fun d => by rw [sub_le, sub_le, sub_le, add_assoc]
#align ordinal.sub_sub Ordinal.sub_sub
@[simp]
theorem add_sub_add_cancel (a b c : Ordinal) : a + b - (a + c) = b - c := by
rw [← sub_sub, add_sub_cancel]
#align ordinal.add_sub_add_cancel Ordinal.add_sub_add_cancel
theorem sub_isLimit {a b} (l : IsLimit a) (h : b < a) : IsLimit (a - b) :=
⟨ne_of_gt <| lt_sub.2 <| by rwa [add_zero], fun c h => by
rw [lt_sub, add_succ]; exact l.2 _ (lt_sub.1 h)⟩
#align ordinal.sub_is_limit Ordinal.sub_isLimit
-- @[simp] -- Porting note (#10618): simp can prove this
theorem one_add_omega : 1 + ω = ω := by
refine le_antisymm ?_ (le_add_left _ _)
rw [omega, ← lift_one.{_, 0}, ← lift_add, lift_le, ← type_unit, ← type_sum_lex]
refine ⟨RelEmbedding.collapse (RelEmbedding.ofMonotone ?_ ?_)⟩
· apply Sum.rec
· exact fun _ => 0
· exact Nat.succ
· intro a b
cases a <;> cases b <;> intro H <;> cases' H with _ _ H _ _ H <;>
[exact H.elim; exact Nat.succ_pos _; exact Nat.succ_lt_succ H]
#align ordinal.one_add_omega Ordinal.one_add_omega
@[simp]
theorem one_add_of_omega_le {o} (h : ω ≤ o) : 1 + o = o := by
rw [← Ordinal.add_sub_cancel_of_le h, ← add_assoc, one_add_omega]
#align ordinal.one_add_of_omega_le Ordinal.one_add_of_omega_le
/-! ### Multiplication of ordinals-/
/-- The multiplication of ordinals `o₁` and `o₂` is the (well founded) lexicographic order on
`o₂ × o₁`. -/
instance monoid : Monoid Ordinal.{u} where
mul a b :=
Quotient.liftOn₂ a b
(fun ⟨α, r, wo⟩ ⟨β, s, wo'⟩ => ⟦⟨β × α, Prod.Lex s r, inferInstance⟩⟧ :
WellOrder → WellOrder → Ordinal)
fun ⟨α₁, r₁, o₁⟩ ⟨α₂, r₂, o₂⟩ ⟨β₁, s₁, p₁⟩ ⟨β₂, s₂, p₂⟩ ⟨f⟩ ⟨g⟩ =>
Quot.sound ⟨RelIso.prodLexCongr g f⟩
one := 1
mul_assoc a b c :=
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Eq.symm <|
Quotient.sound
⟨⟨prodAssoc _ _ _, @fun a b => by
rcases a with ⟨⟨a₁, a₂⟩, a₃⟩
rcases b with ⟨⟨b₁, b₂⟩, b₃⟩
simp [Prod.lex_def, and_or_left, or_assoc, and_assoc]⟩⟩
mul_one a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨punitProd _, @fun a b => by
rcases a with ⟨⟨⟨⟩⟩, a⟩; rcases b with ⟨⟨⟨⟩⟩, b⟩
simp only [Prod.lex_def, EmptyRelation, false_or_iff]
simp only [eq_self_iff_true, true_and_iff]
rfl⟩⟩
one_mul a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨prodPUnit _, @fun a b => by
rcases a with ⟨a, ⟨⟨⟩⟩⟩; rcases b with ⟨b, ⟨⟨⟩⟩⟩
simp only [Prod.lex_def, EmptyRelation, and_false_iff, or_false_iff]
rfl⟩⟩
@[simp]
theorem type_prod_lex {α β : Type u} (r : α → α → Prop) (s : β → β → Prop) [IsWellOrder α r]
[IsWellOrder β s] : type (Prod.Lex s r) = type r * type s :=
rfl
#align ordinal.type_prod_lex Ordinal.type_prod_lex
private theorem mul_eq_zero' {a b : Ordinal} : a * b = 0 ↔ a = 0 ∨ b = 0 :=
inductionOn a fun α _ _ =>
inductionOn b fun β _ _ => by
simp_rw [← type_prod_lex, type_eq_zero_iff_isEmpty]
rw [or_comm]
exact isEmpty_prod
instance monoidWithZero : MonoidWithZero Ordinal :=
{ Ordinal.monoid with
zero := 0
mul_zero := fun _a => mul_eq_zero'.2 <| Or.inr rfl
zero_mul := fun _a => mul_eq_zero'.2 <| Or.inl rfl }
instance noZeroDivisors : NoZeroDivisors Ordinal :=
⟨fun {_ _} => mul_eq_zero'.1⟩
@[simp]
theorem lift_mul (a b : Ordinal.{v}) : lift.{u} (a * b) = lift.{u} a * lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.prodLexCongr (RelIso.preimage Equiv.ulift _)
(RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_mul Ordinal.lift_mul
@[simp]
theorem card_mul (a b) : card (a * b) = card a * card b :=
Quotient.inductionOn₂ a b fun ⟨α, _r, _⟩ ⟨β, _s, _⟩ => mul_comm #β #α
#align ordinal.card_mul Ordinal.card_mul
instance leftDistribClass : LeftDistribClass Ordinal.{u} :=
⟨fun a b c =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Quotient.sound
⟨⟨sumProdDistrib _ _ _, by
rintro ⟨a₁ | a₁, a₂⟩ ⟨b₁ | b₁, b₂⟩ <;>
simp only [Prod.lex_def, Sum.lex_inl_inl, Sum.Lex.sep, Sum.lex_inr_inl,
Sum.lex_inr_inr, sumProdDistrib_apply_left, sumProdDistrib_apply_right] <;>
-- Porting note: `Sum.inr.inj_iff` is required.
simp only [Sum.inl.inj_iff, Sum.inr.inj_iff,
true_or_iff, false_and_iff, false_or_iff]⟩⟩⟩
theorem mul_succ (a b : Ordinal) : a * succ b = a * b + a :=
mul_add_one a b
#align ordinal.mul_succ Ordinal.mul_succ
instance mul_covariantClass_le : CovariantClass Ordinal.{u} Ordinal.{u} (· * ·) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : α × γ => (f a.1, a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ (f.toRelEmbedding.map_rel_iff.2 h')
· exact Prod.Lex.right _ h'⟩
#align ordinal.mul_covariant_class_le Ordinal.mul_covariantClass_le
instance mul_swap_covariantClass_le :
CovariantClass Ordinal.{u} Ordinal.{u} (swap (· * ·)) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : γ × α => (a.1, f a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ h'
· exact Prod.Lex.right _ (f.toRelEmbedding.map_rel_iff.2 h')⟩
#align ordinal.mul_swap_covariant_class_le Ordinal.mul_swap_covariantClass_le
theorem le_mul_left (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ a * b := by
convert mul_le_mul_left' (one_le_iff_pos.2 hb) a
rw [mul_one a]
#align ordinal.le_mul_left Ordinal.le_mul_left
theorem le_mul_right (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ b * a := by
convert mul_le_mul_right' (one_le_iff_pos.2 hb) a
rw [one_mul a]
#align ordinal.le_mul_right Ordinal.le_mul_right
private theorem mul_le_of_limit_aux {α β r s} [IsWellOrder α r] [IsWellOrder β s] {c}
(h : IsLimit (type s)) (H : ∀ b' < type s, type r * b' ≤ c) (l : c < type r * type s) :
False := by
suffices ∀ a b, Prod.Lex s r (b, a) (enum _ _ l) by
cases' enum _ _ l with b a
exact irrefl _ (this _ _)
intro a b
rw [← typein_lt_typein (Prod.Lex s r), typein_enum]
have := H _ (h.2 _ (typein_lt_type s b))
rw [mul_succ] at this
have := ((add_lt_add_iff_left _).2 (typein_lt_type _ a)).trans_le this
refine (RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨⟨b', a'⟩, h⟩
by_cases e : b = b'
· refine Sum.inr ⟨a', ?_⟩
subst e
cases' h with _ _ _ _ h _ _ _ h
· exact (irrefl _ h).elim
· exact h
· refine Sum.inl (⟨b', ?_⟩, a')
cases' h with _ _ _ _ h _ _ _ h
· exact h
· exact (e rfl).elim
· rcases a with ⟨⟨b₁, a₁⟩, h₁⟩
rcases b with ⟨⟨b₂, a₂⟩, h₂⟩
intro h
by_cases e₁ : b = b₁ <;> by_cases e₂ : b = b₂
· substs b₁ b₂
simpa only [subrel_val, Prod.lex_def, @irrefl _ s _ b, true_and_iff, false_or_iff,
eq_self_iff_true, dif_pos, Sum.lex_inr_inr] using h
· subst b₁
simp only [subrel_val, Prod.lex_def, e₂, Prod.lex_def, dif_pos, subrel_val, eq_self_iff_true,
or_false_iff, dif_neg, not_false_iff, Sum.lex_inr_inl, false_and_iff] at h ⊢
cases' h₂ with _ _ _ _ h₂_h h₂_h <;> [exact asymm h h₂_h; exact e₂ rfl]
-- Porting note: `cc` hadn't ported yet.
· simp [e₂, dif_neg e₁, show b₂ ≠ b₁ from e₂ ▸ e₁]
· simpa only [dif_neg e₁, dif_neg e₂, Prod.lex_def, subrel_val, Subtype.mk_eq_mk,
Sum.lex_inl_inl] using h
theorem mul_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a * b ≤ c ↔ ∀ b' < b, a * b' ≤ c :=
⟨fun h b' l => (mul_le_mul_left' l.le _).trans h, fun H =>
-- Porting note: `induction` tactics are required because of the parser bug.
le_of_not_lt <| by
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
exact mul_le_of_limit_aux h H⟩
#align ordinal.mul_le_of_limit Ordinal.mul_le_of_limit
theorem mul_isNormal {a : Ordinal} (h : 0 < a) : IsNormal (a * ·) :=
-- Porting note(#12129): additional beta reduction needed
⟨fun b => by
beta_reduce
rw [mul_succ]
simpa only [add_zero] using (add_lt_add_iff_left (a * b)).2 h,
fun b l c => mul_le_of_limit l⟩
#align ordinal.mul_is_normal Ordinal.mul_isNormal
theorem lt_mul_of_limit {a b c : Ordinal} (h : IsLimit c) : a < b * c ↔ ∃ c' < c, a < b * c' := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@mul_le_of_limit b c a h)
#align ordinal.lt_mul_of_limit Ordinal.lt_mul_of_limit
theorem mul_lt_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b < a * c ↔ b < c :=
(mul_isNormal a0).lt_iff
#align ordinal.mul_lt_mul_iff_left Ordinal.mul_lt_mul_iff_left
theorem mul_le_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
(mul_isNormal a0).le_iff
#align ordinal.mul_le_mul_iff_left Ordinal.mul_le_mul_iff_left
theorem mul_lt_mul_of_pos_left {a b c : Ordinal} (h : a < b) (c0 : 0 < c) : c * a < c * b :=
(mul_lt_mul_iff_left c0).2 h
#align ordinal.mul_lt_mul_of_pos_left Ordinal.mul_lt_mul_of_pos_left
theorem mul_pos {a b : Ordinal} (h₁ : 0 < a) (h₂ : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left h₂ h₁
#align ordinal.mul_pos Ordinal.mul_pos
theorem mul_ne_zero {a b : Ordinal} : a ≠ 0 → b ≠ 0 → a * b ≠ 0 := by
simpa only [Ordinal.pos_iff_ne_zero] using mul_pos
#align ordinal.mul_ne_zero Ordinal.mul_ne_zero
theorem le_of_mul_le_mul_left {a b c : Ordinal} (h : c * a ≤ c * b) (h0 : 0 < c) : a ≤ b :=
le_imp_le_of_lt_imp_lt (fun h' => mul_lt_mul_of_pos_left h' h0) h
#align ordinal.le_of_mul_le_mul_left Ordinal.le_of_mul_le_mul_left
theorem mul_right_inj {a b c : Ordinal} (a0 : 0 < a) : a * b = a * c ↔ b = c :=
(mul_isNormal a0).inj
#align ordinal.mul_right_inj Ordinal.mul_right_inj
theorem mul_isLimit {a b : Ordinal} (a0 : 0 < a) : IsLimit b → IsLimit (a * b) :=
(mul_isNormal a0).isLimit
#align ordinal.mul_is_limit Ordinal.mul_isLimit
theorem mul_isLimit_left {a b : Ordinal} (l : IsLimit a) (b0 : 0 < b) : IsLimit (a * b) := by
rcases zero_or_succ_or_limit b with (rfl | ⟨b, rfl⟩ | lb)
· exact b0.false.elim
· rw [mul_succ]
exact add_isLimit _ l
· exact mul_isLimit l.pos lb
#align ordinal.mul_is_limit_left Ordinal.mul_isLimit_left
theorem smul_eq_mul : ∀ (n : ℕ) (a : Ordinal), n • a = a * n
| 0, a => by rw [zero_nsmul, Nat.cast_zero, mul_zero]
| n + 1, a => by rw [succ_nsmul, Nat.cast_add, mul_add, Nat.cast_one, mul_one, smul_eq_mul n]
#align ordinal.smul_eq_mul Ordinal.smul_eq_mul
/-! ### Division on ordinals -/
/-- The set in the definition of division is nonempty. -/
theorem div_nonempty {a b : Ordinal} (h : b ≠ 0) : { o | a < b * succ o }.Nonempty :=
⟨a, (succ_le_iff (a := a) (b := b * succ a)).1 <| by
simpa only [succ_zero, one_mul] using
mul_le_mul_right' (succ_le_of_lt (Ordinal.pos_iff_ne_zero.2 h)) (succ a)⟩
#align ordinal.div_nonempty Ordinal.div_nonempty
/-- `a / b` is the unique ordinal `o` satisfying `a = b * o + o'` with `o' < b`. -/
instance div : Div Ordinal :=
⟨fun a b => if _h : b = 0 then 0 else sInf { o | a < b * succ o }⟩
@[simp]
theorem div_zero (a : Ordinal) : a / 0 = 0 :=
dif_pos rfl
#align ordinal.div_zero Ordinal.div_zero
theorem div_def (a) {b : Ordinal} (h : b ≠ 0) : a / b = sInf { o | a < b * succ o } :=
dif_neg h
#align ordinal.div_def Ordinal.div_def
theorem lt_mul_succ_div (a) {b : Ordinal} (h : b ≠ 0) : a < b * succ (a / b) := by
rw [div_def a h]; exact csInf_mem (div_nonempty h)
#align ordinal.lt_mul_succ_div Ordinal.lt_mul_succ_div
theorem lt_mul_div_add (a) {b : Ordinal} (h : b ≠ 0) : a < b * (a / b) + b := by
simpa only [mul_succ] using lt_mul_succ_div a h
#align ordinal.lt_mul_div_add Ordinal.lt_mul_div_add
theorem div_le {a b c : Ordinal} (b0 : b ≠ 0) : a / b ≤ c ↔ a < b * succ c :=
⟨fun h => (lt_mul_succ_div a b0).trans_le (mul_le_mul_left' (succ_le_succ_iff.2 h) _), fun h => by
rw [div_def a b0]; exact csInf_le' h⟩
#align ordinal.div_le Ordinal.div_le
theorem lt_div {a b c : Ordinal} (h : c ≠ 0) : a < b / c ↔ c * succ a ≤ b := by
rw [← not_le, div_le h, not_lt]
#align ordinal.lt_div Ordinal.lt_div
theorem div_pos {b c : Ordinal} (h : c ≠ 0) : 0 < b / c ↔ c ≤ b := by simp [lt_div h]
#align ordinal.div_pos Ordinal.div_pos
theorem le_div {a b c : Ordinal} (c0 : c ≠ 0) : a ≤ b / c ↔ c * a ≤ b := by
induction a using limitRecOn with
| H₁ => simp only [mul_zero, Ordinal.zero_le]
| H₂ _ _ => rw [succ_le_iff, lt_div c0]
| H₃ _ h₁ h₂ =>
revert h₁ h₂
simp (config := { contextual := true }) only [mul_le_of_limit, limit_le, iff_self_iff,
forall_true_iff]
#align ordinal.le_div Ordinal.le_div
theorem div_lt {a b c : Ordinal} (b0 : b ≠ 0) : a / b < c ↔ a < b * c :=
lt_iff_lt_of_le_iff_le <| le_div b0
#align ordinal.div_lt Ordinal.div_lt
theorem div_le_of_le_mul {a b c : Ordinal} (h : a ≤ b * c) : a / b ≤ c :=
if b0 : b = 0 then by simp only [b0, div_zero, Ordinal.zero_le]
else
(div_le b0).2 <| h.trans_lt <| mul_lt_mul_of_pos_left (lt_succ c) (Ordinal.pos_iff_ne_zero.2 b0)
#align ordinal.div_le_of_le_mul Ordinal.div_le_of_le_mul
theorem mul_lt_of_lt_div {a b c : Ordinal} : a < b / c → c * a < b :=
lt_imp_lt_of_le_imp_le div_le_of_le_mul
#align ordinal.mul_lt_of_lt_div Ordinal.mul_lt_of_lt_div
@[simp]
theorem zero_div (a : Ordinal) : 0 / a = 0 :=
Ordinal.le_zero.1 <| div_le_of_le_mul <| Ordinal.zero_le _
#align ordinal.zero_div Ordinal.zero_div
theorem mul_div_le (a b : Ordinal) : b * (a / b) ≤ a :=
if b0 : b = 0 then by simp only [b0, zero_mul, Ordinal.zero_le] else (le_div b0).1 le_rfl
#align ordinal.mul_div_le Ordinal.mul_div_le
theorem mul_add_div (a) {b : Ordinal} (b0 : b ≠ 0) (c) : (b * a + c) / b = a + c / b := by
apply le_antisymm
· apply (div_le b0).2
rw [mul_succ, mul_add, add_assoc, add_lt_add_iff_left]
apply lt_mul_div_add _ b0
· rw [le_div b0, mul_add, add_le_add_iff_left]
apply mul_div_le
#align ordinal.mul_add_div Ordinal.mul_add_div
theorem div_eq_zero_of_lt {a b : Ordinal} (h : a < b) : a / b = 0 := by
rw [← Ordinal.le_zero, div_le <| Ordinal.pos_iff_ne_zero.1 <| (Ordinal.zero_le _).trans_lt h]
simpa only [succ_zero, mul_one] using h
#align ordinal.div_eq_zero_of_lt Ordinal.div_eq_zero_of_lt
@[simp]
theorem mul_div_cancel (a) {b : Ordinal} (b0 : b ≠ 0) : b * a / b = a := by
simpa only [add_zero, zero_div] using mul_add_div a b0 0
#align ordinal.mul_div_cancel Ordinal.mul_div_cancel
@[simp]
theorem div_one (a : Ordinal) : a / 1 = a := by
simpa only [one_mul] using mul_div_cancel a Ordinal.one_ne_zero
#align ordinal.div_one Ordinal.div_one
@[simp]
theorem div_self {a : Ordinal} (h : a ≠ 0) : a / a = 1 := by
simpa only [mul_one] using mul_div_cancel 1 h
#align ordinal.div_self Ordinal.div_self
theorem mul_sub (a b c : Ordinal) : a * (b - c) = a * b - a * c :=
if a0 : a = 0 then by simp only [a0, zero_mul, sub_self]
else
eq_of_forall_ge_iff fun d => by rw [sub_le, ← le_div a0, sub_le, ← le_div a0, mul_add_div _ a0]
#align ordinal.mul_sub Ordinal.mul_sub
theorem isLimit_add_iff {a b} : IsLimit (a + b) ↔ IsLimit b ∨ b = 0 ∧ IsLimit a := by
constructor <;> intro h
· by_cases h' : b = 0
· rw [h', add_zero] at h
right
exact ⟨h', h⟩
left
rw [← add_sub_cancel a b]
apply sub_isLimit h
suffices a + 0 < a + b by simpa only [add_zero] using this
rwa [add_lt_add_iff_left, Ordinal.pos_iff_ne_zero]
rcases h with (h | ⟨rfl, h⟩)
· exact add_isLimit a h
· simpa only [add_zero]
#align ordinal.is_limit_add_iff Ordinal.isLimit_add_iff
theorem dvd_add_iff : ∀ {a b c : Ordinal}, a ∣ b → (a ∣ b + c ↔ a ∣ c)
| a, _, c, ⟨b, rfl⟩ =>
⟨fun ⟨d, e⟩ => ⟨d - b, by rw [mul_sub, ← e, add_sub_cancel]⟩, fun ⟨d, e⟩ => by
rw [e, ← mul_add]
apply dvd_mul_right⟩
#align ordinal.dvd_add_iff Ordinal.dvd_add_iff
theorem div_mul_cancel : ∀ {a b : Ordinal}, a ≠ 0 → a ∣ b → a * (b / a) = b
| a, _, a0, ⟨b, rfl⟩ => by rw [mul_div_cancel _ a0]
#align ordinal.div_mul_cancel Ordinal.div_mul_cancel
theorem le_of_dvd : ∀ {a b : Ordinal}, b ≠ 0 → a ∣ b → a ≤ b
-- Porting note: `⟨b, rfl⟩ => by` → `⟨b, e⟩ => by subst e`
| a, _, b0, ⟨b, e⟩ => by
subst e
-- Porting note: `Ne` is required.
simpa only [mul_one] using
mul_le_mul_left'
(one_le_iff_ne_zero.2 fun h : b = 0 => by
simp only [h, mul_zero, Ne, not_true_eq_false] at b0) a
#align ordinal.le_of_dvd Ordinal.le_of_dvd
theorem dvd_antisymm {a b : Ordinal} (h₁ : a ∣ b) (h₂ : b ∣ a) : a = b :=
if a0 : a = 0 then by subst a; exact (eq_zero_of_zero_dvd h₁).symm
else
if b0 : b = 0 then by subst b; exact eq_zero_of_zero_dvd h₂
else (le_of_dvd b0 h₁).antisymm (le_of_dvd a0 h₂)
#align ordinal.dvd_antisymm Ordinal.dvd_antisymm
instance isAntisymm : IsAntisymm Ordinal (· ∣ ·) :=
⟨@dvd_antisymm⟩
/-- `a % b` is the unique ordinal `o'` satisfying
`a = b * o + o'` with `o' < b`. -/
instance mod : Mod Ordinal :=
⟨fun a b => a - b * (a / b)⟩
theorem mod_def (a b : Ordinal) : a % b = a - b * (a / b) :=
rfl
#align ordinal.mod_def Ordinal.mod_def
theorem mod_le (a b : Ordinal) : a % b ≤ a :=
sub_le_self a _
#align ordinal.mod_le Ordinal.mod_le
@[simp]
theorem mod_zero (a : Ordinal) : a % 0 = a := by simp only [mod_def, div_zero, zero_mul, sub_zero]
#align ordinal.mod_zero Ordinal.mod_zero
theorem mod_eq_of_lt {a b : Ordinal} (h : a < b) : a % b = a := by
simp only [mod_def, div_eq_zero_of_lt h, mul_zero, sub_zero]
#align ordinal.mod_eq_of_lt Ordinal.mod_eq_of_lt
@[simp]
theorem zero_mod (b : Ordinal) : 0 % b = 0 := by simp only [mod_def, zero_div, mul_zero, sub_self]
#align ordinal.zero_mod Ordinal.zero_mod
theorem div_add_mod (a b : Ordinal) : b * (a / b) + a % b = a :=
Ordinal.add_sub_cancel_of_le <| mul_div_le _ _
#align ordinal.div_add_mod Ordinal.div_add_mod
theorem mod_lt (a) {b : Ordinal} (h : b ≠ 0) : a % b < b :=
(add_lt_add_iff_left (b * (a / b))).1 <| by rw [div_add_mod]; exact lt_mul_div_add a h
#align ordinal.mod_lt Ordinal.mod_lt
@[simp]
theorem mod_self (a : Ordinal) : a % a = 0 :=
if a0 : a = 0 then by simp only [a0, zero_mod]
else by simp only [mod_def, div_self a0, mul_one, sub_self]
#align ordinal.mod_self Ordinal.mod_self
@[simp]
theorem mod_one (a : Ordinal) : a % 1 = 0 := by simp only [mod_def, div_one, one_mul, sub_self]
#align ordinal.mod_one Ordinal.mod_one
theorem dvd_of_mod_eq_zero {a b : Ordinal} (H : a % b = 0) : b ∣ a :=
⟨a / b, by simpa [H] using (div_add_mod a b).symm⟩
#align ordinal.dvd_of_mod_eq_zero Ordinal.dvd_of_mod_eq_zero
theorem mod_eq_zero_of_dvd {a b : Ordinal} (H : b ∣ a) : a % b = 0 := by
rcases H with ⟨c, rfl⟩
rcases eq_or_ne b 0 with (rfl | hb)
· simp
· simp [mod_def, hb]
#align ordinal.mod_eq_zero_of_dvd Ordinal.mod_eq_zero_of_dvd
theorem dvd_iff_mod_eq_zero {a b : Ordinal} : b ∣ a ↔ a % b = 0 :=
⟨mod_eq_zero_of_dvd, dvd_of_mod_eq_zero⟩
#align ordinal.dvd_iff_mod_eq_zero Ordinal.dvd_iff_mod_eq_zero
@[simp]
theorem mul_add_mod_self (x y z : Ordinal) : (x * y + z) % x = z % x := by
rcases eq_or_ne x 0 with rfl | hx
· simp
· rwa [mod_def, mul_add_div, mul_add, ← sub_sub, add_sub_cancel, mod_def]
#align ordinal.mul_add_mod_self Ordinal.mul_add_mod_self
@[simp]
theorem mul_mod (x y : Ordinal) : x * y % x = 0 := by
simpa using mul_add_mod_self x y 0
#align ordinal.mul_mod Ordinal.mul_mod
theorem mod_mod_of_dvd (a : Ordinal) {b c : Ordinal} (h : c ∣ b) : a % b % c = a % c := by
nth_rw 2 [← div_add_mod a b]
rcases h with ⟨d, rfl⟩
rw [mul_assoc, mul_add_mod_self]
#align ordinal.mod_mod_of_dvd Ordinal.mod_mod_of_dvd
@[simp]
theorem mod_mod (a b : Ordinal) : a % b % b = a % b :=
mod_mod_of_dvd a dvd_rfl
#align ordinal.mod_mod Ordinal.mod_mod
/-! ### Families of ordinals
There are two kinds of indexed families that naturally arise when dealing with ordinals: those
indexed by some type in the appropriate universe, and those indexed by ordinals less than another.
The following API allows one to convert from one kind of family to the other.
In many cases, this makes it easy to prove claims about one kind of family via the corresponding
claim on the other. -/
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a specified
well-ordering. -/
def bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
∀ a < type r, α := fun a ha => f (enum r a ha)
#align ordinal.bfamily_of_family' Ordinal.bfamilyOfFamily'
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a well-ordering
given by the axiom of choice. -/
def bfamilyOfFamily {ι : Type u} : (ι → α) → ∀ a < type (@WellOrderingRel ι), α :=
bfamilyOfFamily' WellOrderingRel
#align ordinal.bfamily_of_family Ordinal.bfamilyOfFamily
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a specified
well-ordering. -/
def familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, α) : ι → α := fun i =>
f (typein r i)
(by
rw [← ho]
exact typein_lt_type r i)
#align ordinal.family_of_bfamily' Ordinal.familyOfBFamily'
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a well-ordering
given by the axiom of choice. -/
def familyOfBFamily (o : Ordinal) (f : ∀ a < o, α) : o.out.α → α :=
familyOfBFamily' (· < ·) (type_lt o) f
#align ordinal.family_of_bfamily Ordinal.familyOfBFamily
@[simp]
theorem bfamilyOfFamily'_typein {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) (i) :
bfamilyOfFamily' r f (typein r i) (typein_lt_type r i) = f i := by
simp only [bfamilyOfFamily', enum_typein]
#align ordinal.bfamily_of_family'_typein Ordinal.bfamilyOfFamily'_typein
@[simp]
theorem bfamilyOfFamily_typein {ι} (f : ι → α) (i) :
bfamilyOfFamily f (typein _ i) (typein_lt_type _ i) = f i :=
bfamilyOfFamily'_typein _ f i
#align ordinal.bfamily_of_family_typein Ordinal.bfamilyOfFamily_typein
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily'_enum {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (i hi) :
familyOfBFamily' r ho f (enum r i (by rwa [ho])) = f i hi := by
simp only [familyOfBFamily', typein_enum]
#align ordinal.family_of_bfamily'_enum Ordinal.familyOfBFamily'_enum
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily_enum (o : Ordinal) (f : ∀ a < o, α) (i hi) :
familyOfBFamily o f
(enum (· < ·) i
(by
convert hi
exact type_lt _)) =
f i hi :=
familyOfBFamily'_enum _ (type_lt o) f _ _
#align ordinal.family_of_bfamily_enum Ordinal.familyOfBFamily_enum
/-- The range of a family indexed by ordinals. -/
def brange (o : Ordinal) (f : ∀ a < o, α) : Set α :=
{ a | ∃ i hi, f i hi = a }
#align ordinal.brange Ordinal.brange
theorem mem_brange {o : Ordinal} {f : ∀ a < o, α} {a} : a ∈ brange o f ↔ ∃ i hi, f i hi = a :=
Iff.rfl
#align ordinal.mem_brange Ordinal.mem_brange
theorem mem_brange_self {o} (f : ∀ a < o, α) (i hi) : f i hi ∈ brange o f :=
⟨i, hi, rfl⟩
#align ordinal.mem_brange_self Ordinal.mem_brange_self
@[simp]
theorem range_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) : range (familyOfBFamily' r ho f) = brange o f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨b, rfl⟩
apply mem_brange_self
· rintro ⟨i, hi, rfl⟩
exact ⟨_, familyOfBFamily'_enum _ _ _ _ _⟩
#align ordinal.range_family_of_bfamily' Ordinal.range_familyOfBFamily'
@[simp]
theorem range_familyOfBFamily {o} (f : ∀ a < o, α) : range (familyOfBFamily o f) = brange o f :=
range_familyOfBFamily' _ _ f
#align ordinal.range_family_of_bfamily Ordinal.range_familyOfBFamily
@[simp]
theorem brange_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
brange _ (bfamilyOfFamily' r f) = range f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨i, hi, rfl⟩
apply mem_range_self
· rintro ⟨b, rfl⟩
exact ⟨_, _, bfamilyOfFamily'_typein _ _ _⟩
#align ordinal.brange_bfamily_of_family' Ordinal.brange_bfamilyOfFamily'
@[simp]
theorem brange_bfamilyOfFamily {ι : Type u} (f : ι → α) : brange _ (bfamilyOfFamily f) = range f :=
brange_bfamilyOfFamily' _ _
#align ordinal.brange_bfamily_of_family Ordinal.brange_bfamilyOfFamily
@[simp]
theorem brange_const {o : Ordinal} (ho : o ≠ 0) {c : α} : (brange o fun _ _ => c) = {c} := by
rw [← range_familyOfBFamily]
exact @Set.range_const _ o.out.α (out_nonempty_iff_ne_zero.2 ho) c
#align ordinal.brange_const Ordinal.brange_const
theorem comp_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α)
(g : α → β) : (fun i hi => g (bfamilyOfFamily' r f i hi)) = bfamilyOfFamily' r (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family' Ordinal.comp_bfamilyOfFamily'
theorem comp_bfamilyOfFamily {ι : Type u} (f : ι → α) (g : α → β) :
(fun i hi => g (bfamilyOfFamily f i hi)) = bfamilyOfFamily (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family Ordinal.comp_bfamilyOfFamily
theorem comp_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily' r ho f = familyOfBFamily' r ho fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily' Ordinal.comp_familyOfBFamily'
theorem comp_familyOfBFamily {o} (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily o f = familyOfBFamily o fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily Ordinal.comp_familyOfBFamily
/-! ### Supremum of a family of ordinals -/
-- Porting note: Universes should be specified in `sup`s.
/-- The supremum of a family of ordinals -/
def sup {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal.{max u v} :=
iSup f
#align ordinal.sup Ordinal.sup
@[simp]
theorem sSup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : sSup (Set.range f) = sup.{_, v} f :=
rfl
#align ordinal.Sup_eq_sup Ordinal.sSup_eq_sup
/-- The range of an indexed ordinal function, whose outputs live in a higher universe than the
inputs, is always bounded above. See `Ordinal.lsub` for an explicit bound. -/
theorem bddAbove_range {ι : Type u} (f : ι → Ordinal.{max u v}) : BddAbove (Set.range f) :=
⟨(iSup (succ ∘ card ∘ f)).ord, by
rintro a ⟨i, rfl⟩
exact le_of_lt (Cardinal.lt_ord.2 ((lt_succ _).trans_le
(le_ciSup (Cardinal.bddAbove_range.{_, v} _) _)))⟩
#align ordinal.bdd_above_range Ordinal.bddAbove_range
theorem le_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : ∀ i, f i ≤ sup.{_, v} f := fun i =>
le_csSup (bddAbove_range.{_, v} f) (mem_range_self i)
#align ordinal.le_sup Ordinal.le_sup
theorem sup_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : sup.{_, v} f ≤ a ↔ ∀ i, f i ≤ a :=
(csSup_le_iff' (bddAbove_range.{_, v} f)).trans (by simp)
#align ordinal.sup_le_iff Ordinal.sup_le_iff
theorem sup_le {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : (∀ i, f i ≤ a) → sup.{_, v} f ≤ a :=
sup_le_iff.2
#align ordinal.sup_le Ordinal.sup_le
theorem lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : a < sup.{_, v} f ↔ ∃ i, a < f i := by
simpa only [not_forall, not_le] using not_congr (@sup_le_iff.{_, v} _ f a)
#align ordinal.lt_sup Ordinal.lt_sup
theorem ne_sup_iff_lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} :
(∀ i, f i ≠ sup.{_, v} f) ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun hf _ => lt_of_le_of_ne (le_sup _ _) (hf _), fun hf _ => ne_of_lt (hf _)⟩
#align ordinal.ne_sup_iff_lt_sup Ordinal.ne_sup_iff_lt_sup
theorem sup_not_succ_of_ne_sup {ι : Type u} {f : ι → Ordinal.{max u v}}
(hf : ∀ i, f i ≠ sup.{_, v} f) {a} (hao : a < sup.{_, v} f) : succ a < sup.{_, v} f := by
by_contra! hoa
exact
hao.not_le (sup_le fun i => le_of_lt_succ <| (lt_of_le_of_ne (le_sup _ _) (hf i)).trans_le hoa)
#align ordinal.sup_not_succ_of_ne_sup Ordinal.sup_not_succ_of_ne_sup
@[simp]
theorem sup_eq_zero_iff {ι : Type u} {f : ι → Ordinal.{max u v}} :
sup.{_, v} f = 0 ↔ ∀ i, f i = 0 := by
refine
⟨fun h i => ?_, fun h =>
le_antisymm (sup_le fun i => Ordinal.le_zero.2 (h i)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_sup f i
#align ordinal.sup_eq_zero_iff Ordinal.sup_eq_zero_iff
theorem IsNormal.sup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f) {ι : Type u}
(g : ι → Ordinal.{max u v}) [Nonempty ι] : f (sup.{_, v} g) = sup.{_, w} (f ∘ g) :=
eq_of_forall_ge_iff fun a => by
rw [sup_le_iff]; simp only [comp]; rw [H.le_set' Set.univ Set.univ_nonempty g] <;>
simp [sup_le_iff]
#align ordinal.is_normal.sup Ordinal.IsNormal.sup
@[simp]
theorem sup_empty {ι} [IsEmpty ι] (f : ι → Ordinal) : sup f = 0 :=
ciSup_of_empty f
#align ordinal.sup_empty Ordinal.sup_empty
@[simp]
theorem sup_const {ι} [_hι : Nonempty ι] (o : Ordinal) : (sup fun _ : ι => o) = o :=
ciSup_const
#align ordinal.sup_const Ordinal.sup_const
@[simp]
theorem sup_unique {ι} [Unique ι] (f : ι → Ordinal) : sup f = f default :=
ciSup_unique
#align ordinal.sup_unique Ordinal.sup_unique
theorem sup_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : sup.{u, max v w} f ≤ sup.{v, max u w} g :=
sup_le fun i =>
match h (mem_range_self i) with
| ⟨_j, hj⟩ => hj ▸ le_sup _ _
#align ordinal.sup_le_of_range_subset Ordinal.sup_le_of_range_subset
theorem sup_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : sup.{u, max v w} f = sup.{v, max u w} g :=
(sup_le_of_range_subset.{u, v, w} h.le).antisymm (sup_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.sup_eq_of_range_eq Ordinal.sup_eq_of_range_eq
@[simp]
theorem sup_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
sup.{max u v, w} f =
max (sup.{u, max v w} fun a => f (Sum.inl a)) (sup.{v, max u w} fun b => f (Sum.inr b)) := by
apply (sup_le_iff.2 _).antisymm (max_le_iff.2 ⟨_, _⟩)
· rintro (i | i)
· exact le_max_of_le_left (le_sup _ i)
· exact le_max_of_le_right (le_sup _ i)
all_goals
apply sup_le_of_range_subset.{_, max u v, w}
rintro i ⟨a, rfl⟩
apply mem_range_self
#align ordinal.sup_sum Ordinal.sup_sum
theorem unbounded_range_of_sup_ge {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β → α)
(h : type r ≤ sup.{u, u} (typein r ∘ f)) : Unbounded r (range f) :=
(not_bounded_iff _).1 fun ⟨x, hx⟩ =>
not_lt_of_le h <|
lt_of_le_of_lt
(sup_le fun y => le_of_lt <| (typein_lt_typein r).2 <| hx _ <| mem_range_self y)
(typein_lt_type r x)
#align ordinal.unbounded_range_of_sup_ge Ordinal.unbounded_range_of_sup_ge
theorem le_sup_shrink_equiv {s : Set Ordinal.{u}} (hs : Small.{u} s) (a) (ha : a ∈ s) :
a ≤ sup.{u, u} fun x => ((@equivShrink s hs).symm x).val := by
convert le_sup.{u, u} (fun x => ((@equivShrink s hs).symm x).val) ((@equivShrink s hs) ⟨a, ha⟩)
rw [symm_apply_apply]
#align ordinal.le_sup_shrink_equiv Ordinal.le_sup_shrink_equiv
instance small_Iio (o : Ordinal.{u}) : Small.{u} (Set.Iio o) :=
let f : o.out.α → Set.Iio o :=
fun x => ⟨typein ((· < ·) : o.out.α → o.out.α → Prop) x, typein_lt_self x⟩
let hf : Surjective f := fun b =>
⟨enum (· < ·) b.val
(by
rw [type_lt]
exact b.prop),
Subtype.ext (typein_enum _ _)⟩
small_of_surjective hf
#align ordinal.small_Iio Ordinal.small_Iio
instance small_Iic (o : Ordinal.{u}) : Small.{u} (Set.Iic o) := by
rw [← Iio_succ]
infer_instance
#align ordinal.small_Iic Ordinal.small_Iic
theorem bddAbove_iff_small {s : Set Ordinal.{u}} : BddAbove s ↔ Small.{u} s :=
⟨fun ⟨a, h⟩ => small_subset <| show s ⊆ Iic a from fun _x hx => h hx, fun h =>
⟨sup.{u, u} fun x => ((@equivShrink s h).symm x).val, le_sup_shrink_equiv h⟩⟩
#align ordinal.bdd_above_iff_small Ordinal.bddAbove_iff_small
theorem bddAbove_of_small (s : Set Ordinal.{u}) [h : Small.{u} s] : BddAbove s :=
bddAbove_iff_small.2 h
#align ordinal.bdd_above_of_small Ordinal.bddAbove_of_small
theorem sup_eq_sSup {s : Set Ordinal.{u}} (hs : Small.{u} s) :
(sup.{u, u} fun x => (@equivShrink s hs).symm x) = sSup s :=
let hs' := bddAbove_iff_small.2 hs
((csSup_le_iff' hs').2 (le_sup_shrink_equiv hs)).antisymm'
(sup_le fun _x => le_csSup hs' (Subtype.mem _))
#align ordinal.sup_eq_Sup Ordinal.sup_eq_sSup
theorem sSup_ord {s : Set Cardinal.{u}} (hs : BddAbove s) : (sSup s).ord = sSup (ord '' s) :=
eq_of_forall_ge_iff fun a => by
rw [csSup_le_iff'
(bddAbove_iff_small.2 (@small_image _ _ _ s (Cardinal.bddAbove_iff_small.1 hs))),
ord_le, csSup_le_iff' hs]
simp [ord_le]
#align ordinal.Sup_ord Ordinal.sSup_ord
theorem iSup_ord {ι} {f : ι → Cardinal} (hf : BddAbove (range f)) :
(iSup f).ord = ⨆ i, (f i).ord := by
unfold iSup
convert sSup_ord hf
-- Porting note: `change` is required.
conv_lhs => change range (ord ∘ f)
rw [range_comp]
#align ordinal.supr_ord Ordinal.iSup_ord
private theorem sup_le_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop)
[IsWellOrder ι r] [IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) ≤ sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_le fun i => by
cases'
typein_surj r'
(by
rw [ho', ← ho]
exact typein_lt_type r i) with
j hj
simp_rw [familyOfBFamily', ← hj]
apply le_sup
theorem sup_eq_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o : Ordinal.{u}} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) = sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_eq_of_range_eq.{u, u, v} (by simp)
#align ordinal.sup_eq_sup Ordinal.sup_eq_sup
/-- The supremum of a family of ordinals indexed by the set of ordinals less than some
`o : Ordinal.{u}`. This is a special case of `sup` over the family provided by
`familyOfBFamily`. -/
def bsup (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
sup.{_, v} (familyOfBFamily o f)
#align ordinal.bsup Ordinal.bsup
@[simp]
theorem sup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily o f) = bsup.{_, v} o f :=
rfl
#align ordinal.sup_eq_bsup Ordinal.sup_eq_bsup
@[simp]
theorem sup_eq_bsup' {o : Ordinal.{u}} {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : sup.{_, v} (familyOfBFamily' r ho f) = bsup.{_, v} o f :=
sup_eq_sup r _ ho _ f
#align ordinal.sup_eq_bsup' Ordinal.sup_eq_bsup'
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem sSup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sSup (brange o f) = bsup.{_, v} o f := by
congr
rw [range_familyOfBFamily]
#align ordinal.Sup_eq_bsup Ordinal.sSup_eq_bsup
@[simp]
theorem bsup_eq_sup' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = sup.{_, v} f := by
simp (config := { unfoldPartialApp := true }) only [← sup_eq_bsup' r, enum_typein,
familyOfBFamily', bfamilyOfFamily']
#align ordinal.bsup_eq_sup' Ordinal.bsup_eq_sup'
theorem bsup_eq_bsup {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = bsup.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [bsup_eq_sup', bsup_eq_sup']
#align ordinal.bsup_eq_bsup Ordinal.bsup_eq_bsup
@[simp]
theorem bsup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily f) = sup.{_, v} f :=
bsup_eq_sup' _ f
#align ordinal.bsup_eq_sup Ordinal.bsup_eq_sup
@[congr]
theorem bsup_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
bsup.{_, v} o₁ f = bsup.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.bsup_congr Ordinal.bsup_congr
theorem bsup_le_iff {o f a} : bsup.{u, v} o f ≤ a ↔ ∀ i h, f i h ≤ a :=
sup_le_iff.trans
⟨fun h i hi => by
rw [← familyOfBFamily_enum o f]
exact h _, fun h i => h _ _⟩
#align ordinal.bsup_le_iff Ordinal.bsup_le_iff
theorem bsup_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} :
(∀ i h, f i h ≤ a) → bsup.{u, v} o f ≤ a :=
bsup_le_iff.2
#align ordinal.bsup_le Ordinal.bsup_le
theorem le_bsup {o} (f : ∀ a < o, Ordinal) (i h) : f i h ≤ bsup o f :=
bsup_le_iff.1 le_rfl _ _
#align ordinal.le_bsup Ordinal.le_bsup
theorem lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) {a} :
a < bsup.{_, v} o f ↔ ∃ i hi, a < f i hi := by
simpa only [not_forall, not_le] using not_congr (@bsup_le_iff.{_, v} _ f a)
#align ordinal.lt_bsup Ordinal.lt_bsup
theorem IsNormal.bsup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f)
{o : Ordinal.{u}} :
∀ (g : ∀ a < o, Ordinal), o ≠ 0 → f (bsup.{_, v} o g) = bsup.{_, w} o fun a h => f (g a h) :=
inductionOn o fun α r _ g h => by
haveI := type_ne_zero_iff_nonempty.1 h
rw [← sup_eq_bsup' r, IsNormal.sup.{_, v, w} H, ← sup_eq_bsup' r] <;> rfl
#align ordinal.is_normal.bsup Ordinal.IsNormal.bsup
theorem lt_bsup_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} :
(∀ i h, f i h ≠ bsup.{_, v} o f) ↔ ∀ i h, f i h < bsup.{_, v} o f :=
⟨fun hf _ _ => lt_of_le_of_ne (le_bsup _ _ _) (hf _ _), fun hf _ _ => ne_of_lt (hf _ _)⟩
#align ordinal.lt_bsup_of_ne_bsup Ordinal.lt_bsup_of_ne_bsup
theorem bsup_not_succ_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}}
(hf : ∀ {i : Ordinal} (h : i < o), f i h ≠ bsup.{_, v} o f) (a) :
a < bsup.{_, v} o f → succ a < bsup.{_, v} o f := by
rw [← sup_eq_bsup] at *
exact sup_not_succ_of_ne_sup fun i => hf _
#align ordinal.bsup_not_succ_of_ne_bsup Ordinal.bsup_not_succ_of_ne_bsup
@[simp]
theorem bsup_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : bsup o f = 0 ↔ ∀ i hi, f i hi = 0 := by
refine
⟨fun h i hi => ?_, fun h =>
le_antisymm (bsup_le fun i hi => Ordinal.le_zero.2 (h i hi)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_bsup f i hi
#align ordinal.bsup_eq_zero_iff Ordinal.bsup_eq_zero_iff
theorem lt_bsup_of_limit {o : Ordinal} {f : ∀ a < o, Ordinal}
(hf : ∀ {a a'} (ha : a < o) (ha' : a' < o), a < a' → f a ha < f a' ha')
(ho : ∀ a < o, succ a < o) (i h) : f i h < bsup o f :=
(hf _ _ <| lt_succ i).trans_le (le_bsup f (succ i) <| ho _ h)
#align ordinal.lt_bsup_of_limit Ordinal.lt_bsup_of_limit
theorem bsup_succ_of_mono {o : Ordinal} {f : ∀ a < succ o, Ordinal}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : bsup _ f = f o (lt_succ o) :=
le_antisymm (bsup_le fun _i hi => hf _ _ <| le_of_lt_succ hi) (le_bsup _ _ _)
#align ordinal.bsup_succ_of_mono Ordinal.bsup_succ_of_mono
@[simp]
theorem bsup_zero (f : ∀ a < (0 : Ordinal), Ordinal) : bsup 0 f = 0 :=
bsup_eq_zero_iff.2 fun i hi => (Ordinal.not_lt_zero i hi).elim
#align ordinal.bsup_zero Ordinal.bsup_zero
theorem bsup_const {o : Ordinal.{u}} (ho : o ≠ 0) (a : Ordinal.{max u v}) :
(bsup.{_, v} o fun _ _ => a) = a :=
le_antisymm (bsup_le fun _ _ => le_rfl) (le_bsup _ 0 (Ordinal.pos_iff_ne_zero.2 ho))
#align ordinal.bsup_const Ordinal.bsup_const
@[simp]
theorem bsup_one (f : ∀ a < (1 : Ordinal), Ordinal) : bsup 1 f = f 0 zero_lt_one := by
simp_rw [← sup_eq_bsup, sup_unique, familyOfBFamily, familyOfBFamily', typein_one_out]
#align ordinal.bsup_one Ordinal.bsup_one
theorem bsup_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : bsup.{u, max v w} o f ≤ bsup.{v, max u w} o' g :=
bsup_le fun i hi => by
obtain ⟨j, hj, hj'⟩ := h ⟨i, hi, rfl⟩
rw [← hj']
apply le_bsup
#align ordinal.bsup_le_of_brange_subset Ordinal.bsup_le_of_brange_subset
theorem bsup_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f = brange o' g) : bsup.{u, max v w} o f = bsup.{v, max u w} o' g :=
(bsup_le_of_brange_subset.{u, v, w} h.le).antisymm (bsup_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.bsup_eq_of_brange_eq Ordinal.bsup_eq_of_brange_eq
/-- The least strict upper bound of a family of ordinals. -/
def lsub {ι} (f : ι → Ordinal) : Ordinal :=
sup (succ ∘ f)
#align ordinal.lsub Ordinal.lsub
@[simp]
theorem sup_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} (succ ∘ f) = lsub.{_, v} f :=
rfl
#align ordinal.sup_eq_lsub Ordinal.sup_eq_lsub
theorem lsub_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
lsub.{_, v} f ≤ a ↔ ∀ i, f i < a := by
convert sup_le_iff.{_, v} (f := succ ∘ f) (a := a) using 2
-- Porting note: `comp_apply` is required.
simp only [comp_apply, succ_le_iff]
#align ordinal.lsub_le_iff Ordinal.lsub_le_iff
theorem lsub_le {ι} {f : ι → Ordinal} {a} : (∀ i, f i < a) → lsub f ≤ a :=
lsub_le_iff.2
#align ordinal.lsub_le Ordinal.lsub_le
theorem lt_lsub {ι} (f : ι → Ordinal) (i) : f i < lsub f :=
succ_le_iff.1 (le_sup _ i)
#align ordinal.lt_lsub Ordinal.lt_lsub
theorem lt_lsub_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
a < lsub.{_, v} f ↔ ∃ i, a ≤ f i := by
simpa only [not_forall, not_lt, not_le] using not_congr (@lsub_le_iff.{_, v} _ f a)
#align ordinal.lt_lsub_iff Ordinal.lt_lsub_iff
theorem sup_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) : sup.{_, v} f ≤ lsub.{_, v} f :=
sup_le fun i => (lt_lsub f i).le
#align ordinal.sup_le_lsub Ordinal.sup_le_lsub
theorem lsub_le_sup_succ {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f ≤ succ (sup.{_, v} f) :=
lsub_le fun i => lt_succ_iff.2 (le_sup f i)
#align ordinal.lsub_le_sup_succ Ordinal.lsub_le_sup_succ
theorem sup_eq_lsub_or_sup_succ_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ∨ succ (sup.{_, v} f) = lsub.{_, v} f := by
cases' eq_or_lt_of_le (sup_le_lsub.{_, v} f) with h h
· exact Or.inl h
· exact Or.inr ((succ_le_of_lt h).antisymm (lsub_le_sup_succ f))
#align ordinal.sup_eq_lsub_or_sup_succ_eq_lsub Ordinal.sup_eq_lsub_or_sup_succ_eq_lsub
theorem sup_succ_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
succ (sup.{_, v} f) ≤ lsub.{_, v} f ↔ ∃ i, f i = sup.{_, v} f := by
refine ⟨fun h => ?_, ?_⟩
· by_contra! hf
exact (succ_le_iff.1 h).ne ((sup_le_lsub f).antisymm (lsub_le (ne_sup_iff_lt_sup.1 hf)))
rintro ⟨_, hf⟩
rw [succ_le_iff, ← hf]
exact lt_lsub _ _
#align ordinal.sup_succ_le_lsub Ordinal.sup_succ_le_lsub
theorem sup_succ_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
succ (sup.{_, v} f) = lsub.{_, v} f ↔ ∃ i, f i = sup.{_, v} f :=
(lsub_le_sup_succ f).le_iff_eq.symm.trans (sup_succ_le_lsub f)
#align ordinal.sup_succ_eq_lsub Ordinal.sup_succ_eq_lsub
theorem sup_eq_lsub_iff_succ {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ↔ ∀ a < lsub.{_, v} f, succ a < lsub.{_, v} f := by
refine ⟨fun h => ?_, fun hf => le_antisymm (sup_le_lsub f) (lsub_le fun i => ?_)⟩
· rw [← h]
exact fun a => sup_not_succ_of_ne_sup fun i => (lsub_le_iff.1 (le_of_eq h.symm) i).ne
by_contra! hle
have heq := (sup_succ_eq_lsub f).2 ⟨i, le_antisymm (le_sup _ _) hle⟩
have :=
hf _
(by
rw [← heq]
exact lt_succ (sup f))
rw [heq] at this
exact this.false
#align ordinal.sup_eq_lsub_iff_succ Ordinal.sup_eq_lsub_iff_succ
theorem sup_eq_lsub_iff_lt_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun h i => by
rw [h]
apply lt_lsub, fun h => le_antisymm (sup_le_lsub f) (lsub_le h)⟩
#align ordinal.sup_eq_lsub_iff_lt_sup Ordinal.sup_eq_lsub_iff_lt_sup
@[simp]
theorem lsub_empty {ι} [h : IsEmpty ι] (f : ι → Ordinal) : lsub f = 0 := by
rw [← Ordinal.le_zero, lsub_le_iff]
exact h.elim
#align ordinal.lsub_empty Ordinal.lsub_empty
theorem lsub_pos {ι : Type u} [h : Nonempty ι] (f : ι → Ordinal.{max u v}) : 0 < lsub.{_, v} f :=
h.elim fun i => (Ordinal.zero_le _).trans_lt (lt_lsub f i)
#align ordinal.lsub_pos Ordinal.lsub_pos
@[simp]
theorem lsub_eq_zero_iff {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f = 0 ↔ IsEmpty ι := by
refine ⟨fun h => ⟨fun i => ?_⟩, fun h => @lsub_empty _ h _⟩
have := @lsub_pos.{_, v} _ ⟨i⟩ f
rw [h] at this
exact this.false
#align ordinal.lsub_eq_zero_iff Ordinal.lsub_eq_zero_iff
@[simp]
theorem lsub_const {ι} [Nonempty ι] (o : Ordinal) : (lsub fun _ : ι => o) = succ o :=
sup_const (succ o)
#align ordinal.lsub_const Ordinal.lsub_const
@[simp]
theorem lsub_unique {ι} [Unique ι] (f : ι → Ordinal) : lsub f = succ (f default) :=
sup_unique _
#align ordinal.lsub_unique Ordinal.lsub_unique
theorem lsub_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : lsub.{u, max v w} f ≤ lsub.{v, max u w} g :=
sup_le_of_range_subset.{u, v, w} (by convert Set.image_subset succ h <;> apply Set.range_comp)
#align ordinal.lsub_le_of_range_subset Ordinal.lsub_le_of_range_subset
theorem lsub_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : lsub.{u, max v w} f = lsub.{v, max u w} g :=
(lsub_le_of_range_subset.{u, v, w} h.le).antisymm (lsub_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.lsub_eq_of_range_eq Ordinal.lsub_eq_of_range_eq
@[simp]
theorem lsub_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
lsub.{max u v, w} f =
max (lsub.{u, max v w} fun a => f (Sum.inl a)) (lsub.{v, max u w} fun b => f (Sum.inr b)) :=
sup_sum _
#align ordinal.lsub_sum Ordinal.lsub_sum
theorem lsub_not_mem_range {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f ∉ Set.range f := fun ⟨i, h⟩ =>
h.not_lt (lt_lsub f i)
#align ordinal.lsub_not_mem_range Ordinal.lsub_not_mem_range
theorem nonempty_compl_range {ι : Type u} (f : ι → Ordinal.{max u v}) : (Set.range f)ᶜ.Nonempty :=
⟨_, lsub_not_mem_range.{_, v} f⟩
#align ordinal.nonempty_compl_range Ordinal.nonempty_compl_range
@[simp]
theorem lsub_typein (o : Ordinal) : lsub.{u, u} (typein ((· < ·) : o.out.α → o.out.α → Prop)) = o :=
(lsub_le.{u, u} typein_lt_self).antisymm
(by
by_contra! h
-- Porting note: `nth_rw` → `conv_rhs` & `rw`
conv_rhs at h => rw [← type_lt o]
simpa [typein_enum] using lt_lsub.{u, u} (typein (· < ·)) (enum (· < ·) _ h))
#align ordinal.lsub_typein Ordinal.lsub_typein
theorem sup_typein_limit {o : Ordinal} (ho : ∀ a, a < o → succ a < o) :
sup.{u, u} (typein ((· < ·) : o.out.α → o.out.α → Prop)) = o := by
-- Porting note: `rwa` → `rw` & `assumption`
rw [(sup_eq_lsub_iff_succ.{u, u} (typein (· < ·))).2] <;> rw [lsub_typein o]; assumption
#align ordinal.sup_typein_limit Ordinal.sup_typein_limit
@[simp]
theorem sup_typein_succ {o : Ordinal} :
sup.{u, u} (typein ((· < ·) : (succ o).out.α → (succ o).out.α → Prop)) = o := by
cases'
sup_eq_lsub_or_sup_succ_eq_lsub.{u, u}
(typein ((· < ·) : (succ o).out.α → (succ o).out.α → Prop)) with
h h
· rw [sup_eq_lsub_iff_succ] at h
simp only [lsub_typein] at h
exact (h o (lt_succ o)).false.elim
rw [← succ_eq_succ_iff, h]
apply lsub_typein
#align ordinal.sup_typein_succ Ordinal.sup_typein_succ
/-- The least strict upper bound of a family of ordinals indexed by the set of ordinals less than
some `o : Ordinal.{u}`.
This is to `lsub` as `bsup` is to `sup`. -/
def blsub (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
bsup.{_, v} o fun a ha => succ (f a ha)
#align ordinal.blsub Ordinal.blsub
@[simp]
theorem bsup_eq_blsub (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) :
(bsup.{_, v} o fun a ha => succ (f a ha)) = blsub.{_, v} o f :=
rfl
#align ordinal.bsup_eq_blsub Ordinal.bsup_eq_blsub
theorem lsub_eq_blsub' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : lsub.{_, v} (familyOfBFamily' r ho f) = blsub.{_, v} o f :=
sup_eq_bsup'.{_, v} r ho fun a ha => succ (f a ha)
#align ordinal.lsub_eq_blsub' Ordinal.lsub_eq_blsub'
theorem lsub_eq_lsub {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
lsub.{_, v} (familyOfBFamily' r ho f) = lsub.{_, v} (familyOfBFamily' r' ho' f) := by
rw [lsub_eq_blsub', lsub_eq_blsub']
#align ordinal.lsub_eq_lsub Ordinal.lsub_eq_lsub
@[simp]
theorem lsub_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
lsub.{_, v} (familyOfBFamily o f) = blsub.{_, v} o f :=
lsub_eq_blsub' _ _ _
#align ordinal.lsub_eq_blsub Ordinal.lsub_eq_blsub
@[simp]
theorem blsub_eq_lsub' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r]
(f : ι → Ordinal.{max u v}) : blsub.{_, v} _ (bfamilyOfFamily' r f) = lsub.{_, v} f :=
bsup_eq_sup'.{_, v} r (succ ∘ f)
#align ordinal.blsub_eq_lsub' Ordinal.blsub_eq_lsub'
theorem blsub_eq_blsub {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
blsub.{_, v} _ (bfamilyOfFamily' r f) = blsub.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [blsub_eq_lsub', blsub_eq_lsub']
#align ordinal.blsub_eq_blsub Ordinal.blsub_eq_blsub
@[simp]
theorem blsub_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
blsub.{_, v} _ (bfamilyOfFamily f) = lsub.{_, v} f :=
blsub_eq_lsub' _ _
#align ordinal.blsub_eq_lsub Ordinal.blsub_eq_lsub
@[congr]
theorem blsub_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
blsub.{_, v} o₁ f = blsub.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.blsub_congr Ordinal.blsub_congr
theorem blsub_le_iff {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} {a} :
blsub.{_, v} o f ≤ a ↔ ∀ i h, f i h < a := by
convert bsup_le_iff.{_, v} (f := fun a ha => succ (f a ha)) (a := a) using 2
simp_rw [succ_le_iff]
#align ordinal.blsub_le_iff Ordinal.blsub_le_iff
theorem blsub_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} : (∀ i h, f i h < a) → blsub o f ≤ a :=
blsub_le_iff.2
#align ordinal.blsub_le Ordinal.blsub_le
theorem lt_blsub {o} (f : ∀ a < o, Ordinal) (i h) : f i h < blsub o f :=
blsub_le_iff.1 le_rfl _ _
#align ordinal.lt_blsub Ordinal.lt_blsub
theorem lt_blsub_iff {o : Ordinal.{u}} {f : ∀ b < o, Ordinal.{max u v}} {a} :
a < blsub.{_, v} o f ↔ ∃ i hi, a ≤ f i hi := by
simpa only [not_forall, not_lt, not_le] using not_congr (@blsub_le_iff.{_, v} _ f a)
#align ordinal.lt_blsub_iff Ordinal.lt_blsub_iff
theorem bsup_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f ≤ blsub.{_, v} o f :=
bsup_le fun i h => (lt_blsub f i h).le
#align ordinal.bsup_le_blsub Ordinal.bsup_le_blsub
theorem blsub_le_bsup_succ {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
blsub.{_, v} o f ≤ succ (bsup.{_, v} o f) :=
blsub_le fun i h => lt_succ_iff.2 (le_bsup f i h)
#align ordinal.blsub_le_bsup_succ Ordinal.blsub_le_bsup_succ
theorem bsup_eq_blsub_or_succ_bsup_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ∨ succ (bsup.{_, v} o f) = blsub.{_, v} o f := by
rw [← sup_eq_bsup, ← lsub_eq_blsub]
exact sup_eq_lsub_or_sup_succ_eq_lsub _
#align ordinal.bsup_eq_blsub_or_succ_bsup_eq_blsub Ordinal.bsup_eq_blsub_or_succ_bsup_eq_blsub
theorem bsup_succ_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
succ (bsup.{_, v} o f) ≤ blsub.{_, v} o f ↔ ∃ i hi, f i hi = bsup.{_, v} o f := by
refine ⟨fun h => ?_, ?_⟩
· by_contra! hf
exact
ne_of_lt (succ_le_iff.1 h)
(le_antisymm (bsup_le_blsub f) (blsub_le (lt_bsup_of_ne_bsup.1 hf)))
rintro ⟨_, _, hf⟩
rw [succ_le_iff, ← hf]
exact lt_blsub _ _ _
#align ordinal.bsup_succ_le_blsub Ordinal.bsup_succ_le_blsub
theorem bsup_succ_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
succ (bsup.{_, v} o f) = blsub.{_, v} o f ↔ ∃ i hi, f i hi = bsup.{_, v} o f :=
(blsub_le_bsup_succ f).le_iff_eq.symm.trans (bsup_succ_le_blsub f)
#align ordinal.bsup_succ_eq_blsub Ordinal.bsup_succ_eq_blsub
theorem bsup_eq_blsub_iff_succ {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ↔ ∀ a < blsub.{_, v} o f, succ a < blsub.{_, v} o f := by
rw [← sup_eq_bsup, ← lsub_eq_blsub]
apply sup_eq_lsub_iff_succ
#align ordinal.bsup_eq_blsub_iff_succ Ordinal.bsup_eq_blsub_iff_succ
theorem bsup_eq_blsub_iff_lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ↔ ∀ i hi, f i hi < bsup.{_, v} o f :=
⟨fun h i => by
rw [h]
apply lt_blsub, fun h => le_antisymm (bsup_le_blsub f) (blsub_le h)⟩
#align ordinal.bsup_eq_blsub_iff_lt_bsup Ordinal.bsup_eq_blsub_iff_lt_bsup
theorem bsup_eq_blsub_of_lt_succ_limit {o : Ordinal.{u}} (ho : IsLimit o)
{f : ∀ a < o, Ordinal.{max u v}} (hf : ∀ a ha, f a ha < f (succ a) (ho.2 a ha)) :
bsup.{_, v} o f = blsub.{_, v} o f := by
rw [bsup_eq_blsub_iff_lt_bsup]
exact fun i hi => (hf i hi).trans_le (le_bsup f _ _)
#align ordinal.bsup_eq_blsub_of_lt_succ_limit Ordinal.bsup_eq_blsub_of_lt_succ_limit
theorem blsub_succ_of_mono {o : Ordinal.{u}} {f : ∀ a < succ o, Ordinal.{max u v}}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : blsub.{_, v} _ f = succ (f o (lt_succ o)) :=
bsup_succ_of_mono fun {_ _} hi hj h => succ_le_succ (hf hi hj h)
#align ordinal.blsub_succ_of_mono Ordinal.blsub_succ_of_mono
@[simp]
theorem blsub_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : blsub o f = 0 ↔ o = 0 := by
rw [← lsub_eq_blsub, lsub_eq_zero_iff]
exact out_empty_iff_eq_zero
#align ordinal.blsub_eq_zero_iff Ordinal.blsub_eq_zero_iff
-- Porting note: `rwa` → `rw`
@[simp]
theorem blsub_zero (f : ∀ a < (0 : Ordinal), Ordinal) : blsub 0 f = 0 := by rw [blsub_eq_zero_iff]
#align ordinal.blsub_zero Ordinal.blsub_zero
theorem blsub_pos {o : Ordinal} (ho : 0 < o) (f : ∀ a < o, Ordinal) : 0 < blsub o f :=
(Ordinal.zero_le _).trans_lt (lt_blsub f 0 ho)
#align ordinal.blsub_pos Ordinal.blsub_pos
theorem blsub_type {α : Type u} (r : α → α → Prop) [IsWellOrder α r]
(f : ∀ a < type r, Ordinal.{max u v}) :
blsub.{_, v} (type r) f = lsub.{_, v} fun a => f (typein r a) (typein_lt_type _ _) :=
eq_of_forall_ge_iff fun o => by
rw [blsub_le_iff, lsub_le_iff];
exact ⟨fun H b => H _ _, fun H i h => by simpa only [typein_enum] using H (enum r i h)⟩
#align ordinal.blsub_type Ordinal.blsub_type
theorem blsub_const {o : Ordinal} (ho : o ≠ 0) (a : Ordinal) :
(blsub.{u, v} o fun _ _ => a) = succ a :=
bsup_const.{u, v} ho (succ a)
#align ordinal.blsub_const Ordinal.blsub_const
@[simp]
theorem blsub_one (f : ∀ a < (1 : Ordinal), Ordinal) : blsub 1 f = succ (f 0 zero_lt_one) :=
bsup_one _
#align ordinal.blsub_one Ordinal.blsub_one
@[simp]
theorem blsub_id : ∀ o, (blsub.{u, u} o fun x _ => x) = o :=
lsub_typein
#align ordinal.blsub_id Ordinal.blsub_id
theorem bsup_id_limit {o : Ordinal} : (∀ a < o, succ a < o) → (bsup.{u, u} o fun x _ => x) = o :=
sup_typein_limit
#align ordinal.bsup_id_limit Ordinal.bsup_id_limit
@[simp]
theorem bsup_id_succ (o) : (bsup.{u, u} (succ o) fun x _ => x) = o :=
sup_typein_succ
#align ordinal.bsup_id_succ Ordinal.bsup_id_succ
theorem blsub_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : blsub.{u, max v w} o f ≤ blsub.{v, max u w} o' g :=
bsup_le_of_brange_subset.{u, v, w} fun a ⟨b, hb, hb'⟩ => by
obtain ⟨c, hc, hc'⟩ := h ⟨b, hb, rfl⟩
simp_rw [← hc'] at hb'
exact ⟨c, hc, hb'⟩
#align ordinal.blsub_le_of_brange_subset Ordinal.blsub_le_of_brange_subset
theorem blsub_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : { o | ∃ i hi, f i hi = o } = { o | ∃ i hi, g i hi = o }) :
blsub.{u, max v w} o f = blsub.{v, max u w} o' g :=
(blsub_le_of_brange_subset.{u, v, w} h.le).antisymm (blsub_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.blsub_eq_of_brange_eq Ordinal.blsub_eq_of_brange_eq
theorem bsup_comp {o o' : Ordinal.{max u v}} {f : ∀ a < o, Ordinal.{max u v w}}
(hf : ∀ {i j} (hi) (hj), i ≤ j → f i hi ≤ f j hj) {g : ∀ a < o', Ordinal.{max u v}}
(hg : blsub.{_, u} o' g = o) :
(bsup.{_, w} o' fun a ha => f (g a ha) (by rw [← hg]; apply lt_blsub)) = bsup.{_, w} o f := by
apply le_antisymm <;> refine bsup_le fun i hi => ?_
· apply le_bsup
· rw [← hg, lt_blsub_iff] at hi
rcases hi with ⟨j, hj, hj'⟩
exact (hf _ _ hj').trans (le_bsup _ _ _)
#align ordinal.bsup_comp Ordinal.bsup_comp
theorem blsub_comp {o o' : Ordinal.{max u v}} {f : ∀ a < o, Ordinal.{max u v w}}
(hf : ∀ {i j} (hi) (hj), i ≤ j → f i hi ≤ f j hj) {g : ∀ a < o', Ordinal.{max u v}}
(hg : blsub.{_, u} o' g = o) :
(blsub.{_, w} o' fun a ha => f (g a ha) (by rw [← hg]; apply lt_blsub)) = blsub.{_, w} o f :=
@bsup_comp.{u, v, w} o _ (fun a ha => succ (f a ha))
(fun {_ _} _ _ h => succ_le_succ_iff.2 (hf _ _ h)) g hg
#align ordinal.blsub_comp Ordinal.blsub_comp
theorem IsNormal.bsup_eq {f : Ordinal.{u} → Ordinal.{max u v}} (H : IsNormal f) {o : Ordinal.{u}}
(h : IsLimit o) : (Ordinal.bsup.{_, v} o fun x _ => f x) = f o := by
rw [← IsNormal.bsup.{u, u, v} H (fun x _ => x) h.1, bsup_id_limit h.2]
#align ordinal.is_normal.bsup_eq Ordinal.IsNormal.bsup_eq
theorem IsNormal.blsub_eq {f : Ordinal.{u} → Ordinal.{max u v}} (H : IsNormal f) {o : Ordinal.{u}}
(h : IsLimit o) : (blsub.{_, v} o fun x _ => f x) = f o := by
rw [← IsNormal.bsup_eq.{u, v} H h, bsup_eq_blsub_of_lt_succ_limit h]
exact fun a _ => H.1 a
#align ordinal.is_normal.blsub_eq Ordinal.IsNormal.blsub_eq
theorem isNormal_iff_lt_succ_and_bsup_eq {f : Ordinal.{u} → Ordinal.{max u v}} :
IsNormal f ↔ (∀ a, f a < f (succ a)) ∧ ∀ o, IsLimit o → (bsup.{_, v} o fun x _ => f x) = f o :=
⟨fun h => ⟨h.1, @IsNormal.bsup_eq f h⟩, fun ⟨h₁, h₂⟩ =>
⟨h₁, fun o ho a => by
rw [← h₂ o ho]
exact bsup_le_iff⟩⟩
#align ordinal.is_normal_iff_lt_succ_and_bsup_eq Ordinal.isNormal_iff_lt_succ_and_bsup_eq
theorem isNormal_iff_lt_succ_and_blsub_eq {f : Ordinal.{u} → Ordinal.{max u v}} :
IsNormal f ↔ (∀ a, f a < f (succ a)) ∧
∀ o, IsLimit o → (blsub.{_, v} o fun x _ => f x) = f o := by
rw [isNormal_iff_lt_succ_and_bsup_eq.{u, v}, and_congr_right_iff]
intro h
constructor <;> intro H o ho <;> have := H o ho <;>
rwa [← bsup_eq_blsub_of_lt_succ_limit ho fun a _ => h a] at *
#align ordinal.is_normal_iff_lt_succ_and_blsub_eq Ordinal.isNormal_iff_lt_succ_and_blsub_eq
theorem IsNormal.eq_iff_zero_and_succ {f g : Ordinal.{u} → Ordinal.{u}} (hf : IsNormal f)
(hg : IsNormal g) : f = g ↔ f 0 = g 0 ∧ ∀ a, f a = g a → f (succ a) = g (succ a) :=
⟨fun h => by simp [h], fun ⟨h₁, h₂⟩ =>
funext fun a => by
induction' a using limitRecOn with _ _ _ ho H
any_goals solve_by_elim
rw [← IsNormal.bsup_eq.{u, u} hf ho, ← IsNormal.bsup_eq.{u, u} hg ho]
congr
ext b hb
exact H b hb⟩
#align ordinal.is_normal.eq_iff_zero_and_succ Ordinal.IsNormal.eq_iff_zero_and_succ
/-- A two-argument version of `Ordinal.blsub`.
We don't develop a full API for this, since it's only used in a handful of existence results. -/
def blsub₂ (o₁ o₂ : Ordinal) (op : {a : Ordinal} → (a < o₁) → {b : Ordinal} → (b < o₂) → Ordinal) :
Ordinal :=
lsub (fun x : o₁.out.α × o₂.out.α => op (typein_lt_self x.1) (typein_lt_self x.2))
#align ordinal.blsub₂ Ordinal.blsub₂
theorem lt_blsub₂ {o₁ o₂ : Ordinal}
(op : {a : Ordinal} → (a < o₁) → {b : Ordinal} → (b < o₂) → Ordinal) {a b : Ordinal}
(ha : a < o₁) (hb : b < o₂) : op ha hb < blsub₂ o₁ o₂ op := by
convert lt_lsub _ (Prod.mk (enum (· < ·) a (by rwa [type_lt]))
(enum (· < ·) b (by rwa [type_lt])))
simp only [typein_enum]
#align ordinal.lt_blsub₂ Ordinal.lt_blsub₂
/-! ### Minimum excluded ordinals -/
/-- The minimum excluded ordinal in a family of ordinals. -/
def mex {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal :=
sInf (Set.range f)ᶜ
#align ordinal.mex Ordinal.mex
theorem mex_not_mem_range {ι : Type u} (f : ι → Ordinal.{max u v}) : mex.{_, v} f ∉ Set.range f :=
csInf_mem (nonempty_compl_range.{_, v} f)
#align ordinal.mex_not_mem_range Ordinal.mex_not_mem_range
theorem le_mex_of_forall {ι : Type u} {f : ι → Ordinal.{max u v}} {a : Ordinal}
(H : ∀ b < a, ∃ i, f i = b) : a ≤ mex.{_, v} f := by
by_contra! h
exact mex_not_mem_range f (H _ h)
#align ordinal.le_mex_of_forall Ordinal.le_mex_of_forall
theorem ne_mex {ι : Type u} (f : ι → Ordinal.{max u v}) : ∀ i, f i ≠ mex.{_, v} f := by
simpa using mex_not_mem_range.{_, v} f
#align ordinal.ne_mex Ordinal.ne_mex
theorem mex_le_of_ne {ι} {f : ι → Ordinal} {a} (ha : ∀ i, f i ≠ a) : mex f ≤ a :=
csInf_le' (by simp [ha])
#align ordinal.mex_le_of_ne Ordinal.mex_le_of_ne
theorem exists_of_lt_mex {ι} {f : ι → Ordinal} {a} (ha : a < mex f) : ∃ i, f i = a := by
by_contra! ha'
exact ha.not_le (mex_le_of_ne ha')
#align ordinal.exists_of_lt_mex Ordinal.exists_of_lt_mex
theorem mex_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) : mex.{_, v} f ≤ lsub.{_, v} f :=
csInf_le' (lsub_not_mem_range f)
#align ordinal.mex_le_lsub Ordinal.mex_le_lsub
theorem mex_monotone {α β : Type u} {f : α → Ordinal.{max u v}} {g : β → Ordinal.{max u v}}
(h : Set.range f ⊆ Set.range g) : mex.{_, v} f ≤ mex.{_, v} g := by
refine mex_le_of_ne fun i hi => ?_
cases' h ⟨i, rfl⟩ with j hj
rw [← hj] at hi
exact ne_mex g j hi
#align ordinal.mex_monotone Ordinal.mex_monotone
theorem mex_lt_ord_succ_mk {ι : Type u} (f : ι → Ordinal.{u}) :
mex.{_, u} f < (succ #ι).ord := by
by_contra! h
apply (lt_succ #ι).not_le
have H := fun a => exists_of_lt_mex ((typein_lt_self a).trans_le h)
let g : (succ #ι).ord.out.α → ι := fun a => Classical.choose (H a)
have hg : Injective g := fun a b h' => by
have Hf : ∀ x, f (g x) =
typein ((· < ·) : (succ #ι).ord.out.α → (succ #ι).ord.out.α → Prop) x :=
fun a => Classical.choose_spec (H a)
apply_fun f at h'
rwa [Hf, Hf, typein_inj] at h'
convert Cardinal.mk_le_of_injective hg
rw [Cardinal.mk_ord_out (succ #ι)]
#align ordinal.mex_lt_ord_succ_mk Ordinal.mex_lt_ord_succ_mk
/-- The minimum excluded ordinal of a family of ordinals indexed by the set of ordinals less than
some `o : Ordinal.{u}`. This is a special case of `mex` over the family provided by
`familyOfBFamily`.
This is to `mex` as `bsup` is to `sup`. -/
def bmex (o : Ordinal) (f : ∀ a < o, Ordinal) : Ordinal :=
mex (familyOfBFamily o f)
#align ordinal.bmex Ordinal.bmex
theorem bmex_not_mem_brange {o : Ordinal} (f : ∀ a < o, Ordinal) : bmex o f ∉ brange o f := by
rw [← range_familyOfBFamily]
apply mex_not_mem_range
#align ordinal.bmex_not_mem_brange Ordinal.bmex_not_mem_brange
theorem le_bmex_of_forall {o : Ordinal} (f : ∀ a < o, Ordinal) {a : Ordinal}
(H : ∀ b < a, ∃ i hi, f i hi = b) : a ≤ bmex o f := by
by_contra! h
exact bmex_not_mem_brange f (H _ h)
#align ordinal.le_bmex_of_forall Ordinal.le_bmex_of_forall
theorem ne_bmex {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) {i} (hi) :
f i hi ≠ bmex.{_, v} o f := by
convert (config := {transparency := .default})
ne_mex.{_, v} (familyOfBFamily o f) (enum (· < ·) i (by rwa [type_lt])) using 2
-- Porting note: `familyOfBFamily_enum` → `typein_enum`
rw [typein_enum]
#align ordinal.ne_bmex Ordinal.ne_bmex
theorem bmex_le_of_ne {o : Ordinal} {f : ∀ a < o, Ordinal} {a} (ha : ∀ i hi, f i hi ≠ a) :
bmex o f ≤ a :=
mex_le_of_ne fun _i => ha _ _
#align ordinal.bmex_le_of_ne Ordinal.bmex_le_of_ne
theorem exists_of_lt_bmex {o : Ordinal} {f : ∀ a < o, Ordinal} {a} (ha : a < bmex o f) :
∃ i hi, f i hi = a := by
cases' exists_of_lt_mex ha with i hi
exact ⟨_, typein_lt_self i, hi⟩
#align ordinal.exists_of_lt_bmex Ordinal.exists_of_lt_bmex
theorem bmex_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bmex.{_, v} o f ≤ blsub.{_, v} o f :=
mex_le_lsub _
#align ordinal.bmex_le_blsub Ordinal.bmex_le_blsub
theorem bmex_monotone {o o' : Ordinal.{u}}
{f : ∀ a < o, Ordinal.{max u v}} {g : ∀ a < o', Ordinal.{max u v}}
(h : brange o f ⊆ brange o' g) : bmex.{_, v} o f ≤ bmex.{_, v} o' g :=
mex_monotone (by rwa [range_familyOfBFamily, range_familyOfBFamily])
#align ordinal.bmex_monotone Ordinal.bmex_monotone
theorem bmex_lt_ord_succ_card {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{u}) :
bmex.{_, u} o f < (succ o.card).ord := by
rw [← mk_ordinal_out]
exact mex_lt_ord_succ_mk (familyOfBFamily o f)
#align ordinal.bmex_lt_ord_succ_card Ordinal.bmex_lt_ord_succ_card
end Ordinal
/-! ### Results about injectivity and surjectivity -/
theorem not_surjective_of_ordinal {α : Type u} (f : α → Ordinal.{u}) : ¬Surjective f := fun h =>
Ordinal.lsub_not_mem_range.{u, u} f (h _)
#align not_surjective_of_ordinal not_surjective_of_ordinal
theorem not_injective_of_ordinal {α : Type u} (f : Ordinal.{u} → α) : ¬Injective f := fun h =>
not_surjective_of_ordinal _ (invFun_surjective h)
#align not_injective_of_ordinal not_injective_of_ordinal
theorem not_surjective_of_ordinal_of_small {α : Type v} [Small.{u} α] (f : α → Ordinal.{u}) :
¬Surjective f := fun h => not_surjective_of_ordinal _ (h.comp (equivShrink _).symm.surjective)
#align not_surjective_of_ordinal_of_small not_surjective_of_ordinal_of_small
theorem not_injective_of_ordinal_of_small {α : Type v} [Small.{u} α] (f : Ordinal.{u} → α) :
¬Injective f := fun h => not_injective_of_ordinal _ ((equivShrink _).injective.comp h)
#align not_injective_of_ordinal_of_small not_injective_of_ordinal_of_small
/-- The type of ordinals in universe `u` is not `Small.{u}`. This is the type-theoretic analog of
the Burali-Forti paradox. -/
theorem not_small_ordinal : ¬Small.{u} Ordinal.{max u v} := fun h =>
@not_injective_of_ordinal_of_small _ h _ fun _a _b => Ordinal.lift_inj.{v, u}.1
#align not_small_ordinal not_small_ordinal
/-! ### Enumerating unbounded sets of ordinals with ordinals -/
namespace Ordinal
section
/-- Enumerator function for an unbounded set of ordinals. -/
def enumOrd (S : Set Ordinal.{u}) : Ordinal → Ordinal :=
lt_wf.fix fun o f => sInf (S ∩ Set.Ici (blsub.{u, u} o f))
#align ordinal.enum_ord Ordinal.enumOrd
variable {S : Set Ordinal.{u}}
/-- The equation that characterizes `enumOrd` definitionally. This isn't the nicest expression to
work with, so consider using `enumOrd_def` instead. -/
theorem enumOrd_def' (o) :
enumOrd S o = sInf (S ∩ Set.Ici (blsub.{u, u} o fun a _ => enumOrd S a)) :=
lt_wf.fix_eq _ _
#align ordinal.enum_ord_def' Ordinal.enumOrd_def'
/-- The set in `enumOrd_def'` is nonempty. -/
theorem enumOrd_def'_nonempty (hS : Unbounded (· < ·) S) (a) : (S ∩ Set.Ici a).Nonempty :=
let ⟨b, hb, hb'⟩ := hS a
⟨b, hb, le_of_not_gt hb'⟩
#align ordinal.enum_ord_def'_nonempty Ordinal.enumOrd_def'_nonempty
private theorem enumOrd_mem_aux (hS : Unbounded (· < ·) S) (o) :
enumOrd S o ∈ S ∩ Set.Ici (blsub.{u, u} o fun c _ => enumOrd S c) := by
rw [enumOrd_def']
exact csInf_mem (enumOrd_def'_nonempty hS _)
theorem enumOrd_mem (hS : Unbounded (· < ·) S) (o) : enumOrd S o ∈ S :=
(enumOrd_mem_aux hS o).left
#align ordinal.enum_ord_mem Ordinal.enumOrd_mem
theorem blsub_le_enumOrd (hS : Unbounded (· < ·) S) (o) :
(blsub.{u, u} o fun c _ => enumOrd S c) ≤ enumOrd S o :=
(enumOrd_mem_aux hS o).right
#align ordinal.blsub_le_enum_ord Ordinal.blsub_le_enumOrd
theorem enumOrd_strictMono (hS : Unbounded (· < ·) S) : StrictMono (enumOrd S) := fun _ _ h =>
(lt_blsub.{u, u} _ _ h).trans_le (blsub_le_enumOrd hS _)
#align ordinal.enum_ord_strict_mono Ordinal.enumOrd_strictMono
/-- A more workable definition for `enumOrd`. -/
theorem enumOrd_def (o) : enumOrd S o = sInf (S ∩ { b | ∀ c, c < o → enumOrd S c < b }) := by
rw [enumOrd_def']
congr; ext
exact ⟨fun h a hao => (lt_blsub.{u, u} _ _ hao).trans_le h, blsub_le⟩
#align ordinal.enum_ord_def Ordinal.enumOrd_def
/-- The set in `enumOrd_def` is nonempty. -/
theorem enumOrd_def_nonempty (hS : Unbounded (· < ·) S) {o} :
{ x | x ∈ S ∧ ∀ c, c < o → enumOrd S c < x }.Nonempty :=
⟨_, enumOrd_mem hS o, fun _ b => enumOrd_strictMono hS b⟩
#align ordinal.enum_ord_def_nonempty Ordinal.enumOrd_def_nonempty
@[simp]
theorem enumOrd_range {f : Ordinal → Ordinal} (hf : StrictMono f) : enumOrd (range f) = f :=
funext fun o => by
apply Ordinal.induction o
intro a H
rw [enumOrd_def a]
have Hfa : f a ∈ range f ∩ { b | ∀ c, c < a → enumOrd (range f) c < b } :=
⟨mem_range_self a, fun b hb => by
rw [H b hb]
exact hf hb⟩
refine (csInf_le' Hfa).antisymm ((le_csInf_iff'' ⟨_, Hfa⟩).2 ?_)
rintro _ ⟨⟨c, rfl⟩, hc : ∀ b < a, enumOrd (range f) b < f c⟩
rw [hf.le_iff_le]
contrapose! hc
exact ⟨c, hc, (H c hc).ge⟩
#align ordinal.enum_ord_range Ordinal.enumOrd_range
@[simp]
theorem enumOrd_univ : enumOrd Set.univ = id := by
rw [← range_id]
exact enumOrd_range strictMono_id
#align ordinal.enum_ord_univ Ordinal.enumOrd_univ
@[simp]
theorem enumOrd_zero : enumOrd S 0 = sInf S := by
rw [enumOrd_def]
simp [Ordinal.not_lt_zero]
#align ordinal.enum_ord_zero Ordinal.enumOrd_zero
theorem enumOrd_succ_le {a b} (hS : Unbounded (· < ·) S) (ha : a ∈ S) (hb : enumOrd S b < a) :
enumOrd S (succ b) ≤ a := by
rw [enumOrd_def]
exact
csInf_le' ⟨ha, fun c hc => ((enumOrd_strictMono hS).monotone (le_of_lt_succ hc)).trans_lt hb⟩
#align ordinal.enum_ord_succ_le Ordinal.enumOrd_succ_le
theorem enumOrd_le_of_subset {S T : Set Ordinal} (hS : Unbounded (· < ·) S) (hST : S ⊆ T) (a) :
enumOrd T a ≤ enumOrd S a := by
apply Ordinal.induction a
intro b H
rw [enumOrd_def]
exact csInf_le' ⟨hST (enumOrd_mem hS b), fun c h => (H c h).trans_lt (enumOrd_strictMono hS h)⟩
#align ordinal.enum_ord_le_of_subset Ordinal.enumOrd_le_of_subset
theorem enumOrd_surjective (hS : Unbounded (· < ·) S) : ∀ s ∈ S, ∃ a, enumOrd S a = s := fun s hs =>
⟨sSup { a | enumOrd S a ≤ s }, by
apply le_antisymm
· rw [enumOrd_def]
refine csInf_le' ⟨hs, fun a ha => ?_⟩
have : enumOrd S 0 ≤ s := by
rw [enumOrd_zero]
exact csInf_le' hs
-- Porting note: `flip` is required to infer a metavariable.
rcases flip exists_lt_of_lt_csSup ha ⟨0, this⟩ with ⟨b, hb, hab⟩
exact (enumOrd_strictMono hS hab).trans_le hb
· by_contra! h
exact
(le_csSup ⟨s, fun a => (lt_wf.self_le_of_strictMono (enumOrd_strictMono hS) a).trans⟩
(enumOrd_succ_le hS hs h)).not_lt
(lt_succ _)⟩
#align ordinal.enum_ord_surjective Ordinal.enumOrd_surjective
/-- An order isomorphism between an unbounded set of ordinals and the ordinals. -/
def enumOrdOrderIso (hS : Unbounded (· < ·) S) : Ordinal ≃o S :=
StrictMono.orderIsoOfSurjective (fun o => ⟨_, enumOrd_mem hS o⟩) (enumOrd_strictMono hS) fun s =>
let ⟨a, ha⟩ := enumOrd_surjective hS s s.prop
⟨a, Subtype.eq ha⟩
#align ordinal.enum_ord_order_iso Ordinal.enumOrdOrderIso
theorem range_enumOrd (hS : Unbounded (· < ·) S) : range (enumOrd S) = S := by
rw [range_eq_iff]
exact ⟨enumOrd_mem hS, enumOrd_surjective hS⟩
#align ordinal.range_enum_ord Ordinal.range_enumOrd
/-- A characterization of `enumOrd`: it is the unique strict monotonic function with range `S`. -/
theorem eq_enumOrd (f : Ordinal → Ordinal) (hS : Unbounded (· < ·) S) :
StrictMono f ∧ range f = S ↔ f = enumOrd S := by
constructor
· rintro ⟨h₁, h₂⟩
rwa [← lt_wf.eq_strictMono_iff_eq_range h₁ (enumOrd_strictMono hS), range_enumOrd hS]
· rintro rfl
exact ⟨enumOrd_strictMono hS, range_enumOrd hS⟩
#align ordinal.eq_enum_ord Ordinal.eq_enumOrd
end
/-! ### Casting naturals into ordinals, compatibility with operations -/
@[simp]
theorem one_add_natCast (m : ℕ) : 1 + (m : Ordinal) = succ m := by
rw [← Nat.cast_one, ← Nat.cast_add, add_comm]
rfl
#align ordinal.one_add_nat_cast Ordinal.one_add_natCast
@[deprecated (since := "2024-04-17")]
alias one_add_nat_cast := one_add_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem one_add_ofNat (m : ℕ) [m.AtLeastTwo] :
1 + (no_index (OfNat.ofNat m : Ordinal)) = Order.succ (OfNat.ofNat m : Ordinal) :=
one_add_natCast m
@[simp, norm_cast]
theorem natCast_mul (m : ℕ) : ∀ n : ℕ, ((m * n : ℕ) : Ordinal) = m * n
| 0 => by simp
| n + 1 => by rw [Nat.mul_succ, Nat.cast_add, natCast_mul m n, Nat.cast_succ, mul_add_one]
#align ordinal.nat_cast_mul Ordinal.natCast_mul
@[deprecated (since := "2024-04-17")]
alias nat_cast_mul := natCast_mul
/-- Alias of `Nat.cast_le`, specialized to `Ordinal` --/
theorem natCast_le {m n : ℕ} : (m : Ordinal) ≤ n ↔ m ≤ n := by
rw [← Cardinal.ord_nat, ← Cardinal.ord_nat, Cardinal.ord_le_ord, Cardinal.natCast_le]
#align ordinal.nat_cast_le Ordinal.natCast_le
@[deprecated (since := "2024-04-17")]
alias nat_cast_le := natCast_le
/-- Alias of `Nat.cast_inj`, specialized to `Ordinal` --/
theorem natCast_inj {m n : ℕ} : (m : Ordinal) = n ↔ m = n := by
simp only [le_antisymm_iff, natCast_le]
#align ordinal.nat_cast_inj Ordinal.natCast_inj
@[deprecated (since := "2024-04-17")]
alias nat_cast_inj := natCast_inj
instance charZero : CharZero Ordinal where
cast_injective _ _ := natCast_inj.mp
/-- Alias of `Nat.cast_lt`, specialized to `Ordinal` --/
theorem natCast_lt {m n : ℕ} : (m : Ordinal) < n ↔ m < n := Nat.cast_lt
#align ordinal.nat_cast_lt Ordinal.natCast_lt
@[deprecated (since := "2024-04-17")]
alias nat_cast_lt := natCast_lt
/-- Alias of `Nat.cast_eq_zero`, specialized to `Ordinal` --/
theorem natCast_eq_zero {n : ℕ} : (n : Ordinal) = 0 ↔ n = 0 := Nat.cast_eq_zero
#align ordinal.nat_cast_eq_zero Ordinal.natCast_eq_zero
@[deprecated (since := "2024-04-17")]
alias nat_cast_eq_zero := natCast_eq_zero
/-- Alias of `Nat.cast_eq_zero`, specialized to `Ordinal` --/
theorem natCast_ne_zero {n : ℕ} : (n : Ordinal) ≠ 0 ↔ n ≠ 0 := Nat.cast_ne_zero
#align ordinal.nat_cast_ne_zero Ordinal.natCast_ne_zero
@[deprecated (since := "2024-04-17")]
alias nat_cast_ne_zero := natCast_ne_zero
/-- Alias of `Nat.cast_pos'`, specialized to `Ordinal` --/
theorem natCast_pos {n : ℕ} : (0 : Ordinal) < n ↔ 0 < n := Nat.cast_pos'
#align ordinal.nat_cast_pos Ordinal.natCast_pos
@[deprecated (since := "2024-04-17")]
alias nat_cast_pos := natCast_pos
@[simp, norm_cast]
theorem natCast_sub (m n : ℕ) : ((m - n : ℕ) : Ordinal) = m - n := by
rcases le_total m n with h | h
· rw [tsub_eq_zero_iff_le.2 h, Ordinal.sub_eq_zero_iff_le.2 (natCast_le.2 h)]
rfl
· apply (add_left_cancel n).1
rw [← Nat.cast_add, add_tsub_cancel_of_le h, Ordinal.add_sub_cancel_of_le (natCast_le.2 h)]
#align ordinal.nat_cast_sub Ordinal.natCast_sub
@[deprecated (since := "2024-04-17")]
alias nat_cast_sub := natCast_sub
@[simp, norm_cast]
theorem natCast_div (m n : ℕ) : ((m / n : ℕ) : Ordinal) = m / n := by
rcases eq_or_ne n 0 with (rfl | hn)
· simp
· have hn' := natCast_ne_zero.2 hn
apply le_antisymm
· rw [le_div hn', ← natCast_mul, natCast_le, mul_comm]
apply Nat.div_mul_le_self
· rw [div_le hn', ← add_one_eq_succ, ← Nat.cast_succ, ← natCast_mul, natCast_lt, mul_comm, ←
Nat.div_lt_iff_lt_mul (Nat.pos_of_ne_zero hn)]
apply Nat.lt_succ_self
#align ordinal.nat_cast_div Ordinal.natCast_div
@[deprecated (since := "2024-04-17")]
alias nat_cast_div := natCast_div
@[simp, norm_cast]
theorem natCast_mod (m n : ℕ) : ((m % n : ℕ) : Ordinal) = m % n := by
rw [← add_left_cancel, div_add_mod, ← natCast_div, ← natCast_mul, ← Nat.cast_add,
Nat.div_add_mod]
#align ordinal.nat_cast_mod Ordinal.natCast_mod
@[deprecated (since := "2024-04-17")]
alias nat_cast_mod := natCast_mod
@[simp]
theorem lift_natCast : ∀ n : ℕ, lift.{u, v} n = n
| 0 => by simp
| n + 1 => by simp [lift_natCast n]
#align ordinal.lift_nat_cast Ordinal.lift_natCast
@[deprecated (since := "2024-04-17")]
alias lift_nat_cast := lift_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem lift_ofNat (n : ℕ) [n.AtLeastTwo] :
lift.{u, v} (no_index (OfNat.ofNat n)) = OfNat.ofNat n :=
lift_natCast n
end Ordinal
/-! ### Properties of `omega` -/
namespace Cardinal
open Ordinal
@[simp]
theorem ord_aleph0 : ord.{u} ℵ₀ = ω :=
le_antisymm (ord_le.2 <| le_rfl) <|
le_of_forall_lt fun o h => by
rcases Ordinal.lt_lift_iff.1 h with ⟨o, rfl, h'⟩
rw [lt_ord, ← lift_card, lift_lt_aleph0, ← typein_enum (· < ·) h']
exact lt_aleph0_iff_fintype.2 ⟨Set.fintypeLTNat _⟩
#align cardinal.ord_aleph_0 Cardinal.ord_aleph0
@[simp]
theorem add_one_of_aleph0_le {c} (h : ℵ₀ ≤ c) : c + 1 = c := by
rw [add_comm, ← card_ord c, ← card_one, ← card_add, one_add_of_omega_le]
rwa [← ord_aleph0, ord_le_ord]
#align cardinal.add_one_of_aleph_0_le Cardinal.add_one_of_aleph0_le
end Cardinal
namespace Ordinal
theorem lt_add_of_limit {a b c : Ordinal.{u}} (h : IsLimit c) :
a < b + c ↔ ∃ c' < c, a < b + c' := by
-- Porting note: `bex_def` is required.
rw [← IsNormal.bsup_eq.{u, u} (add_isNormal b) h, lt_bsup, bex_def]
#align ordinal.lt_add_of_limit Ordinal.lt_add_of_limit
theorem lt_omega {o : Ordinal} : o < ω ↔ ∃ n : ℕ, o = n := by
simp_rw [← Cardinal.ord_aleph0, Cardinal.lt_ord, lt_aleph0, card_eq_nat]
#align ordinal.lt_omega Ordinal.lt_omega
theorem nat_lt_omega (n : ℕ) : ↑n < ω :=
lt_omega.2 ⟨_, rfl⟩
#align ordinal.nat_lt_omega Ordinal.nat_lt_omega
theorem omega_pos : 0 < ω :=
nat_lt_omega 0
#align ordinal.omega_pos Ordinal.omega_pos
theorem omega_ne_zero : ω ≠ 0 :=
omega_pos.ne'
#align ordinal.omega_ne_zero Ordinal.omega_ne_zero
theorem one_lt_omega : 1 < ω := by simpa only [Nat.cast_one] using nat_lt_omega 1
#align ordinal.one_lt_omega Ordinal.one_lt_omega
theorem omega_isLimit : IsLimit ω :=
⟨omega_ne_zero, fun o h => by
let ⟨n, e⟩ := lt_omega.1 h
rw [e]; exact nat_lt_omega (n + 1)⟩
#align ordinal.omega_is_limit Ordinal.omega_isLimit
theorem omega_le {o : Ordinal} : ω ≤ o ↔ ∀ n : ℕ, ↑n ≤ o :=
⟨fun h n => (nat_lt_omega _).le.trans h, fun H =>
le_of_forall_lt fun a h => by
let ⟨n, e⟩ := lt_omega.1 h
rw [e, ← succ_le_iff]; exact H (n + 1)⟩
#align ordinal.omega_le Ordinal.omega_le
@[simp]
theorem sup_natCast : sup Nat.cast = ω :=
(sup_le fun n => (nat_lt_omega n).le).antisymm <| omega_le.2 <| le_sup _
#align ordinal.sup_nat_cast Ordinal.sup_natCast
@[deprecated (since := "2024-04-17")]
alias sup_nat_cast := sup_natCast
theorem nat_lt_limit {o} (h : IsLimit o) : ∀ n : ℕ, ↑n < o
| 0 => lt_of_le_of_ne (Ordinal.zero_le o) h.1.symm
| n + 1 => h.2 _ (nat_lt_limit h n)
#align ordinal.nat_lt_limit Ordinal.nat_lt_limit
theorem omega_le_of_isLimit {o} (h : IsLimit o) : ω ≤ o :=
omega_le.2 fun n => le_of_lt <| nat_lt_limit h n
#align ordinal.omega_le_of_is_limit Ordinal.omega_le_of_isLimit
| Mathlib/SetTheory/Ordinal/Arithmetic.lean | 2,508 | 2,521 | theorem isLimit_iff_omega_dvd {a : Ordinal} : IsLimit a ↔ a ≠ 0 ∧ ω ∣ a := by |
refine ⟨fun l => ⟨l.1, ⟨a / ω, le_antisymm ?_ (mul_div_le _ _)⟩⟩, fun h => ?_⟩
· refine (limit_le l).2 fun x hx => le_of_lt ?_
rw [← div_lt omega_ne_zero, ← succ_le_iff, le_div omega_ne_zero, mul_succ,
add_le_of_limit omega_isLimit]
intro b hb
rcases lt_omega.1 hb with ⟨n, rfl⟩
exact
(add_le_add_right (mul_div_le _ _) _).trans
(lt_sub.1 <| nat_lt_limit (sub_isLimit l hx) _).le
· rcases h with ⟨a0, b, rfl⟩
refine mul_isLimit_left omega_isLimit (Ordinal.pos_iff_ne_zero.2 <| mt ?_ a0)
intro e
simp only [e, mul_zero]
|
/-
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.Algebra.BigOperators.Finprod
import Mathlib.Order.Filter.Pointwise
import Mathlib.Topology.Algebra.MulAction
import Mathlib.Algebra.BigOperators.Pi
import Mathlib.Topology.ContinuousFunction.Basic
import Mathlib.Algebra.Group.ULift
#align_import topology.algebra.monoid from "leanprover-community/mathlib"@"1ac8d4304efba9d03fa720d06516fac845aa5353"
/-!
# Theory of topological monoids
In this file we define mixin classes `ContinuousMul` and `ContinuousAdd`. While in many
applications the underlying type is a monoid (multiplicative or additive), we do not require this in
the definitions.
-/
universe u v
open scoped Classical
open Set Filter TopologicalSpace
open scoped Classical
open Topology Pointwise
variable {ι α M N X : Type*} [TopologicalSpace X]
@[to_additive (attr := continuity, fun_prop)]
theorem continuous_one [TopologicalSpace M] [One M] : Continuous (1 : X → M) :=
@continuous_const _ _ _ _ 1
#align continuous_one continuous_one
#align continuous_zero continuous_zero
/-- Basic hypothesis to talk about a topological additive monoid or a topological additive
semigroup. A topological additive monoid over `M`, for example, is obtained by requiring both the
instances `AddMonoid M` and `ContinuousAdd M`.
Continuity in only the left/right argument can be stated using
`ContinuousConstVAdd α α`/`ContinuousConstVAdd αᵐᵒᵖ α`. -/
class ContinuousAdd (M : Type u) [TopologicalSpace M] [Add M] : Prop where
continuous_add : Continuous fun p : M × M => p.1 + p.2
#align has_continuous_add ContinuousAdd
/-- Basic hypothesis to talk about a topological monoid or a topological semigroup.
A topological monoid over `M`, for example, is obtained by requiring both the instances `Monoid M`
and `ContinuousMul M`.
Continuity in only the left/right argument can be stated using
`ContinuousConstSMul α α`/`ContinuousConstSMul αᵐᵒᵖ α`. -/
@[to_additive]
class ContinuousMul (M : Type u) [TopologicalSpace M] [Mul M] : Prop where
continuous_mul : Continuous fun p : M × M => p.1 * p.2
#align has_continuous_mul ContinuousMul
section ContinuousMul
variable [TopologicalSpace M] [Mul M] [ContinuousMul M]
@[to_additive]
instance : ContinuousMul Mᵒᵈ :=
‹ContinuousMul M›
@[to_additive (attr := continuity)]
theorem continuous_mul : Continuous fun p : M × M => p.1 * p.2 :=
ContinuousMul.continuous_mul
#align continuous_mul continuous_mul
#align continuous_add continuous_add
@[to_additive]
instance : ContinuousMul (ULift.{u} M) := by
constructor
apply continuous_uLift_up.comp
exact continuous_mul.comp₂ (continuous_uLift_down.comp continuous_fst)
(continuous_uLift_down.comp continuous_snd)
@[to_additive]
instance ContinuousMul.to_continuousSMul : ContinuousSMul M M :=
⟨continuous_mul⟩
#align has_continuous_mul.to_has_continuous_smul ContinuousMul.to_continuousSMul
#align has_continuous_add.to_has_continuous_vadd ContinuousAdd.to_continuousVAdd
@[to_additive]
instance ContinuousMul.to_continuousSMul_op : ContinuousSMul Mᵐᵒᵖ M :=
⟨show Continuous ((fun p : M × M => p.1 * p.2) ∘ Prod.swap ∘ Prod.map MulOpposite.unop id) from
continuous_mul.comp <|
continuous_swap.comp <| Continuous.prod_map MulOpposite.continuous_unop continuous_id⟩
#align has_continuous_mul.to_has_continuous_smul_op ContinuousMul.to_continuousSMul_op
#align has_continuous_add.to_has_continuous_vadd_op ContinuousAdd.to_continuousVAdd_op
@[to_additive (attr := continuity, fun_prop)]
theorem Continuous.mul {f g : X → M} (hf : Continuous f) (hg : Continuous g) :
Continuous fun x => f x * g x :=
continuous_mul.comp (hf.prod_mk hg : _)
#align continuous.mul Continuous.mul
#align continuous.add Continuous.add
@[to_additive (attr := continuity)]
theorem continuous_mul_left (a : M) : Continuous fun b : M => a * b :=
continuous_const.mul continuous_id
#align continuous_mul_left continuous_mul_left
#align continuous_add_left continuous_add_left
@[to_additive (attr := continuity)]
theorem continuous_mul_right (a : M) : Continuous fun b : M => b * a :=
continuous_id.mul continuous_const
#align continuous_mul_right continuous_mul_right
#align continuous_add_right continuous_add_right
@[to_additive (attr := fun_prop)]
theorem ContinuousOn.mul {f g : X → M} {s : Set X} (hf : ContinuousOn f s) (hg : ContinuousOn g s) :
ContinuousOn (fun x => f x * g x) s :=
(continuous_mul.comp_continuousOn (hf.prod hg) : _)
#align continuous_on.mul ContinuousOn.mul
#align continuous_on.add ContinuousOn.add
@[to_additive]
theorem tendsto_mul {a b : M} : Tendsto (fun p : M × M => p.fst * p.snd) (𝓝 (a, b)) (𝓝 (a * b)) :=
continuous_iff_continuousAt.mp ContinuousMul.continuous_mul (a, b)
#align tendsto_mul tendsto_mul
#align tendsto_add tendsto_add
@[to_additive]
theorem Filter.Tendsto.mul {f g : α → M} {x : Filter α} {a b : M} (hf : Tendsto f x (𝓝 a))
(hg : Tendsto g x (𝓝 b)) : Tendsto (fun x => f x * g x) x (𝓝 (a * b)) :=
tendsto_mul.comp (hf.prod_mk_nhds hg)
#align filter.tendsto.mul Filter.Tendsto.mul
#align filter.tendsto.add Filter.Tendsto.add
@[to_additive]
theorem Filter.Tendsto.const_mul (b : M) {c : M} {f : α → M} {l : Filter α}
(h : Tendsto (fun k : α => f k) l (𝓝 c)) : Tendsto (fun k : α => b * f k) l (𝓝 (b * c)) :=
tendsto_const_nhds.mul h
#align filter.tendsto.const_mul Filter.Tendsto.const_mul
#align filter.tendsto.const_add Filter.Tendsto.const_add
@[to_additive]
theorem Filter.Tendsto.mul_const (b : M) {c : M} {f : α → M} {l : Filter α}
(h : Tendsto (fun k : α => f k) l (𝓝 c)) : Tendsto (fun k : α => f k * b) l (𝓝 (c * b)) :=
h.mul tendsto_const_nhds
#align filter.tendsto.mul_const Filter.Tendsto.mul_const
#align filter.tendsto.add_const Filter.Tendsto.add_const
@[to_additive]
theorem le_nhds_mul (a b : M) : 𝓝 a * 𝓝 b ≤ 𝓝 (a * b) := by
rw [← map₂_mul, ← map_uncurry_prod, ← nhds_prod_eq]
exact continuous_mul.tendsto _
#align le_nhds_mul le_nhds_mul
#align le_nhds_add le_nhds_add
@[to_additive (attr := simp)]
theorem nhds_one_mul_nhds {M} [MulOneClass M] [TopologicalSpace M] [ContinuousMul M] (a : M) :
𝓝 (1 : M) * 𝓝 a = 𝓝 a :=
((le_nhds_mul _ _).trans_eq <| congr_arg _ (one_mul a)).antisymm <|
le_mul_of_one_le_left' <| pure_le_nhds 1
#align nhds_one_mul_nhds nhds_one_mul_nhds
#align nhds_zero_add_nhds nhds_zero_add_nhds
@[to_additive (attr := simp)]
theorem nhds_mul_nhds_one {M} [MulOneClass M] [TopologicalSpace M] [ContinuousMul M] (a : M) :
𝓝 a * 𝓝 1 = 𝓝 a :=
((le_nhds_mul _ _).trans_eq <| congr_arg _ (mul_one a)).antisymm <|
le_mul_of_one_le_right' <| pure_le_nhds 1
#align nhds_mul_nhds_one nhds_mul_nhds_one
#align nhds_add_nhds_zero nhds_add_nhds_zero
section tendsto_nhds
variable {𝕜 : Type*} [Preorder 𝕜] [Zero 𝕜] [Mul 𝕜] [TopologicalSpace 𝕜] [ContinuousMul 𝕜]
{l : Filter α} {f : α → 𝕜} {b c : 𝕜} (hb : 0 < b)
theorem Filter.TendstoNhdsWithinIoi.const_mul [PosMulStrictMono 𝕜] [PosMulReflectLT 𝕜]
(h : Tendsto f l (𝓝[>] c)) : Tendsto (fun a => b * f a) l (𝓝[>] (b * c)) :=
tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _
((tendsto_nhds_of_tendsto_nhdsWithin h).const_mul b) <|
(tendsto_nhdsWithin_iff.mp h).2.mono fun _ => (mul_lt_mul_left hb).mpr
#align filter.tendsto_nhds_within_Ioi.const_mul Filter.TendstoNhdsWithinIoi.const_mul
theorem Filter.TendstoNhdsWithinIio.const_mul [PosMulStrictMono 𝕜] [PosMulReflectLT 𝕜]
(h : Tendsto f l (𝓝[<] c)) : Tendsto (fun a => b * f a) l (𝓝[<] (b * c)) :=
tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _
((tendsto_nhds_of_tendsto_nhdsWithin h).const_mul b) <|
(tendsto_nhdsWithin_iff.mp h).2.mono fun _ => (mul_lt_mul_left hb).mpr
#align filter.tendsto_nhds_within_Iio.const_mul Filter.TendstoNhdsWithinIio.const_mul
theorem Filter.TendstoNhdsWithinIoi.mul_const [MulPosStrictMono 𝕜] [MulPosReflectLT 𝕜]
(h : Tendsto f l (𝓝[>] c)) : Tendsto (fun a => f a * b) l (𝓝[>] (c * b)) :=
tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _
((tendsto_nhds_of_tendsto_nhdsWithin h).mul_const b) <|
(tendsto_nhdsWithin_iff.mp h).2.mono fun _ => (mul_lt_mul_right hb).mpr
#align filter.tendsto_nhds_within_Ioi.mul_const Filter.TendstoNhdsWithinIoi.mul_const
theorem Filter.TendstoNhdsWithinIio.mul_const [MulPosStrictMono 𝕜] [MulPosReflectLT 𝕜]
(h : Tendsto f l (𝓝[<] c)) : Tendsto (fun a => f a * b) l (𝓝[<] (c * b)) :=
tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _
((tendsto_nhds_of_tendsto_nhdsWithin h).mul_const b) <|
(tendsto_nhdsWithin_iff.mp h).2.mono fun _ => (mul_lt_mul_right hb).mpr
#align filter.tendsto_nhds_within_Iio.mul_const Filter.TendstoNhdsWithinIio.mul_const
end tendsto_nhds
@[to_additive]
protected theorem Specializes.mul {a b c d : M} (hab : a ⤳ b) (hcd : c ⤳ d) : (a * c) ⤳ (b * d) :=
hab.smul hcd
@[to_additive]
protected theorem Inseparable.mul {a b c d : M} (hab : Inseparable a b) (hcd : Inseparable c d) :
Inseparable (a * c) (b * d) :=
hab.smul hcd
@[to_additive]
protected theorem Specializes.pow {M : Type*} [Monoid M] [TopologicalSpace M] [ContinuousMul M]
{a b : M} (h : a ⤳ b) (n : ℕ) : (a ^ n) ⤳ (b ^ n) :=
Nat.recOn n (by simp only [pow_zero, specializes_rfl]) fun _ ihn ↦ by
simpa only [pow_succ] using ihn.mul h
@[to_additive]
protected theorem Inseparable.pow {M : Type*} [Monoid M] [TopologicalSpace M] [ContinuousMul M]
{a b : M} (h : Inseparable a b) (n : ℕ) : Inseparable (a ^ n) (b ^ n) :=
(h.specializes.pow n).antisymm (h.specializes'.pow n)
/-- Construct a unit from limits of units and their inverses. -/
@[to_additive (attr := simps)
"Construct an additive unit from limits of additive units and their negatives."]
def Filter.Tendsto.units [TopologicalSpace N] [Monoid N] [ContinuousMul N] [T2Space N]
{f : ι → Nˣ} {r₁ r₂ : N} {l : Filter ι} [l.NeBot] (h₁ : Tendsto (fun x => ↑(f x)) l (𝓝 r₁))
(h₂ : Tendsto (fun x => ↑(f x)⁻¹) l (𝓝 r₂)) : Nˣ where
val := r₁
inv := r₂
val_inv := by
symm
simpa using h₁.mul h₂
inv_val := by
symm
simpa using h₂.mul h₁
#align filter.tendsto.units Filter.Tendsto.units
#align filter.tendsto.add_units Filter.Tendsto.addUnits
@[to_additive (attr := fun_prop)]
theorem ContinuousAt.mul {f g : X → M} {x : X} (hf : ContinuousAt f x) (hg : ContinuousAt g x) :
ContinuousAt (fun x => f x * g x) x :=
Filter.Tendsto.mul hf hg
#align continuous_at.mul ContinuousAt.mul
#align continuous_at.add ContinuousAt.add
@[to_additive]
theorem ContinuousWithinAt.mul {f g : X → M} {s : Set X} {x : X} (hf : ContinuousWithinAt f s x)
(hg : ContinuousWithinAt g s x) : ContinuousWithinAt (fun x => f x * g x) s x :=
Filter.Tendsto.mul hf hg
#align continuous_within_at.mul ContinuousWithinAt.mul
#align continuous_within_at.add ContinuousWithinAt.add
@[to_additive]
instance Prod.continuousMul [TopologicalSpace N] [Mul N] [ContinuousMul N] :
ContinuousMul (M × N) :=
⟨(continuous_fst.fst'.mul continuous_fst.snd').prod_mk
(continuous_snd.fst'.mul continuous_snd.snd')⟩
@[to_additive]
instance Pi.continuousMul {C : ι → Type*} [∀ i, TopologicalSpace (C i)] [∀ i, Mul (C i)]
[∀ i, ContinuousMul (C i)] : ContinuousMul (∀ i, C i) where
continuous_mul :=
continuous_pi fun i => (continuous_apply i).fst'.mul (continuous_apply i).snd'
#align pi.has_continuous_mul Pi.continuousMul
#align pi.has_continuous_add Pi.continuousAdd
/-- A version of `Pi.continuousMul` for non-dependent functions. It is needed because sometimes
Lean 3 fails to use `Pi.continuousMul` for non-dependent functions. -/
@[to_additive "A version of `Pi.continuousAdd` for non-dependent functions. It is needed
because sometimes Lean fails to use `Pi.continuousAdd` for non-dependent functions."]
instance Pi.continuousMul' : ContinuousMul (ι → M) :=
Pi.continuousMul
#align pi.has_continuous_mul' Pi.continuousMul'
#align pi.has_continuous_add' Pi.continuousAdd'
@[to_additive]
instance (priority := 100) continuousMul_of_discreteTopology [TopologicalSpace N] [Mul N]
[DiscreteTopology N] : ContinuousMul N :=
⟨continuous_of_discreteTopology⟩
#align has_continuous_mul_of_discrete_topology continuousMul_of_discreteTopology
#align has_continuous_add_of_discrete_topology continuousAdd_of_discreteTopology
open Filter
open Function
@[to_additive]
theorem ContinuousMul.of_nhds_one {M : Type u} [Monoid M] [TopologicalSpace M]
(hmul : Tendsto (uncurry ((· * ·) : M → M → M)) (𝓝 1 ×ˢ 𝓝 1) <| 𝓝 1)
(hleft : ∀ x₀ : M, 𝓝 x₀ = map (fun x => x₀ * x) (𝓝 1))
(hright : ∀ x₀ : M, 𝓝 x₀ = map (fun x => x * x₀) (𝓝 1)) : ContinuousMul M :=
⟨by
rw [continuous_iff_continuousAt]
rintro ⟨x₀, y₀⟩
have key : (fun p : M × M => x₀ * p.1 * (p.2 * y₀)) =
((fun x => x₀ * x) ∘ fun x => x * y₀) ∘ uncurry (· * ·) := by
ext p
simp [uncurry, mul_assoc]
have key₂ : ((fun x => x₀ * x) ∘ fun x => y₀ * x) = fun x => x₀ * y₀ * x := by
ext x
simp [mul_assoc]
calc
map (uncurry (· * ·)) (𝓝 (x₀, y₀)) = map (uncurry (· * ·)) (𝓝 x₀ ×ˢ 𝓝 y₀) := by
rw [nhds_prod_eq]
_ = map (fun p : M × M => x₀ * p.1 * (p.2 * y₀)) (𝓝 1 ×ˢ 𝓝 1) := by
-- Porting note: `rw` was able to prove this
-- Now it fails with `failed to rewrite using equation theorems for 'Function.uncurry'`
-- and `failed to rewrite using equation theorems for 'Function.comp'`.
-- Removing those two lemmas, the `rw` would succeed, but then needs a `rfl`.
simp (config := { unfoldPartialApp := true }) only [uncurry]
simp_rw [hleft x₀, hright y₀, prod_map_map_eq, Filter.map_map, Function.comp_def]
_ = map ((fun x => x₀ * x) ∘ fun x => x * y₀) (map (uncurry (· * ·)) (𝓝 1 ×ˢ 𝓝 1)) := by
rw [key, ← Filter.map_map]
_ ≤ map ((fun x : M => x₀ * x) ∘ fun x => x * y₀) (𝓝 1) := map_mono hmul
_ = 𝓝 (x₀ * y₀) := by
rw [← Filter.map_map, ← hright, hleft y₀, Filter.map_map, key₂, ← hleft]⟩
#align has_continuous_mul.of_nhds_one ContinuousMul.of_nhds_one
#align has_continuous_add.of_nhds_zero ContinuousAdd.of_nhds_zero
@[to_additive]
| Mathlib/Topology/Algebra/Monoid.lean | 326 | 331 | theorem continuousMul_of_comm_of_nhds_one (M : Type u) [CommMonoid M] [TopologicalSpace M]
(hmul : Tendsto (uncurry ((· * ·) : M → M → M)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1))
(hleft : ∀ x₀ : M, 𝓝 x₀ = map (fun x => x₀ * x) (𝓝 1)) : ContinuousMul M := by |
apply ContinuousMul.of_nhds_one hmul hleft
intro x₀
simp_rw [mul_comm, hleft x₀]
|
/-
Copyright (c) 2022 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Analysis.InnerProductSpace.Adjoint
#align_import analysis.inner_product_space.positive from "leanprover-community/mathlib"@"caa58cbf5bfb7f81ccbaca4e8b8ac4bc2b39cc1c"
/-!
# Positive operators
In this file we define positive operators in a Hilbert space. We follow Bourbaki's choice
of requiring self adjointness in the definition.
## Main definitions
* `IsPositive` : a continuous linear map is positive if it is self adjoint and
`∀ x, 0 ≤ re ⟪T x, x⟫`
## Main statements
* `ContinuousLinearMap.IsPositive.conj_adjoint` : if `T : E →L[𝕜] E` is positive,
then for any `S : E →L[𝕜] F`, `S ∘L T ∘L S†` is also positive.
* `ContinuousLinearMap.isPositive_iff_complex` : in a ***complex*** Hilbert space,
checking that `⟪T x, x⟫` is a nonnegative real number for all `x` suffices to prove that
`T` is positive
## References
* [Bourbaki, *Topological Vector Spaces*][bourbaki1987]
## Tags
Positive operator
-/
open InnerProductSpace RCLike ContinuousLinearMap
open scoped InnerProduct ComplexConjugate
namespace ContinuousLinearMap
variable {𝕜 E F : Type*} [RCLike 𝕜]
variable [NormedAddCommGroup E] [NormedAddCommGroup F]
variable [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 F]
variable [CompleteSpace E] [CompleteSpace F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
/-- A continuous linear endomorphism `T` of a Hilbert space is **positive** if it is self adjoint
and `∀ x, 0 ≤ re ⟪T x, x⟫`. -/
def IsPositive (T : E →L[𝕜] E) : Prop :=
IsSelfAdjoint T ∧ ∀ x, 0 ≤ T.reApplyInnerSelf x
#align continuous_linear_map.is_positive ContinuousLinearMap.IsPositive
theorem IsPositive.isSelfAdjoint {T : E →L[𝕜] E} (hT : IsPositive T) : IsSelfAdjoint T :=
hT.1
#align continuous_linear_map.is_positive.is_self_adjoint ContinuousLinearMap.IsPositive.isSelfAdjoint
theorem IsPositive.inner_nonneg_left {T : E →L[𝕜] E} (hT : IsPositive T) (x : E) :
0 ≤ re ⟪T x, x⟫ :=
hT.2 x
#align continuous_linear_map.is_positive.inner_nonneg_left ContinuousLinearMap.IsPositive.inner_nonneg_left
| Mathlib/Analysis/InnerProductSpace/Positive.lean | 67 | 68 | theorem IsPositive.inner_nonneg_right {T : E →L[𝕜] E} (hT : IsPositive T) (x : E) :
0 ≤ re ⟪x, T x⟫ := by | rw [inner_re_symm]; exact hT.inner_nonneg_left x
|
/-
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.Logic.Function.Basic
import Mathlib.Logic.Relator
import Mathlib.Init.Data.Quot
import Mathlib.Tactic.Cases
import Mathlib.Tactic.Use
import Mathlib.Tactic.MkIffOfInductiveProp
import Mathlib.Tactic.SimpRw
#align_import logic.relation from "leanprover-community/mathlib"@"3365b20c2ffa7c35e47e5209b89ba9abdddf3ffe"
/-!
# Relation closures
This file defines the reflexive, transitive, and reflexive transitive closures of relations.
It also proves some basic results on definitions such as `EqvGen`.
Note that this is about unbundled relations, that is terms of types of the form `α → β → Prop`. For
the bundled version, see `Rel`.
## Definitions
* `Relation.ReflGen`: Reflexive closure. `ReflGen r` relates everything `r` related, plus for all
`a` it relates `a` with itself. So `ReflGen r a b ↔ r a b ∨ a = b`.
* `Relation.TransGen`: Transitive closure. `TransGen r` relates everything `r` related
transitively. So `TransGen r a b ↔ ∃ x₀ ... xₙ, r a x₀ ∧ r x₀ x₁ ∧ ... ∧ r xₙ b`.
* `Relation.ReflTransGen`: Reflexive transitive closure. `ReflTransGen r` relates everything
`r` related transitively, plus for all `a` it relates `a` with itself. So
`ReflTransGen r a b ↔ (∃ x₀ ... xₙ, r a x₀ ∧ r x₀ x₁ ∧ ... ∧ r xₙ b) ∨ a = b`. It is the same as
the reflexive closure of the transitive closure, or the transitive closure of the reflexive
closure. In terms of rewriting systems, this means that `a` can be rewritten to `b` in a number of
rewrites.
* `Relation.Comp`: Relation composition. We provide notation `∘r`. For `r : α → β → Prop` and
`s : β → γ → Prop`, `r ∘r s`relates `a : α` and `c : γ` iff there exists `b : β` that's related to
both.
* `Relation.Map`: Image of a relation under a pair of maps. For `r : α → β → Prop`, `f : α → γ`,
`g : β → δ`, `Map r f g` is the relation `γ → δ → Prop` relating `f a` and `g b` for all `a`, `b`
related by `r`.
* `Relation.Join`: Join of a relation. For `r : α → α → Prop`, `Join r a b ↔ ∃ c, r a c ∧ r b c`. In
terms of rewriting systems, this means that `a` and `b` can be rewritten to the same term.
-/
open Function
variable {α β γ δ ε ζ : Type*}
section NeImp
variable {r : α → α → Prop}
theorem IsRefl.reflexive [IsRefl α r] : Reflexive r := fun x ↦ IsRefl.refl x
#align is_refl.reflexive IsRefl.reflexive
/-- To show a reflexive relation `r : α → α → Prop` holds over `x y : α`,
it suffices to show it holds when `x ≠ y`. -/
theorem Reflexive.rel_of_ne_imp (h : Reflexive r) {x y : α} (hr : x ≠ y → r x y) : r x y := by
by_cases hxy : x = y
· exact hxy ▸ h x
· exact hr hxy
#align reflexive.rel_of_ne_imp Reflexive.rel_of_ne_imp
/-- If a reflexive relation `r : α → α → Prop` holds over `x y : α`,
then it holds whether or not `x ≠ y`. -/
theorem Reflexive.ne_imp_iff (h : Reflexive r) {x y : α} : x ≠ y → r x y ↔ r x y :=
⟨h.rel_of_ne_imp, fun hr _ ↦ hr⟩
#align reflexive.ne_imp_iff Reflexive.ne_imp_iff
/-- If a reflexive relation `r : α → α → Prop` holds over `x y : α`,
then it holds whether or not `x ≠ y`. Unlike `Reflexive.ne_imp_iff`, this uses `[IsRefl α r]`. -/
theorem reflexive_ne_imp_iff [IsRefl α r] {x y : α} : x ≠ y → r x y ↔ r x y :=
IsRefl.reflexive.ne_imp_iff
#align reflexive_ne_imp_iff reflexive_ne_imp_iff
protected theorem Symmetric.iff (H : Symmetric r) (x y : α) : r x y ↔ r y x :=
⟨fun h ↦ H h, fun h ↦ H h⟩
#align symmetric.iff Symmetric.iff
theorem Symmetric.flip_eq (h : Symmetric r) : flip r = r :=
funext₂ fun _ _ ↦ propext <| h.iff _ _
#align symmetric.flip_eq Symmetric.flip_eq
theorem Symmetric.swap_eq : Symmetric r → swap r = r :=
Symmetric.flip_eq
#align symmetric.swap_eq Symmetric.swap_eq
theorem flip_eq_iff : flip r = r ↔ Symmetric r :=
⟨fun h _ _ ↦ (congr_fun₂ h _ _).mp, Symmetric.flip_eq⟩
#align flip_eq_iff flip_eq_iff
theorem swap_eq_iff : swap r = r ↔ Symmetric r :=
flip_eq_iff
#align swap_eq_iff swap_eq_iff
end NeImp
section Comap
variable {r : β → β → Prop}
theorem Reflexive.comap (h : Reflexive r) (f : α → β) : Reflexive (r on f) := fun a ↦ h (f a)
#align reflexive.comap Reflexive.comap
theorem Symmetric.comap (h : Symmetric r) (f : α → β) : Symmetric (r on f) := fun _ _ hab ↦ h hab
#align symmetric.comap Symmetric.comap
theorem Transitive.comap (h : Transitive r) (f : α → β) : Transitive (r on f) :=
fun _ _ _ hab hbc ↦ h hab hbc
#align transitive.comap Transitive.comap
theorem Equivalence.comap (h : Equivalence r) (f : α → β) : Equivalence (r on f) :=
⟨h.reflexive.comap f, @(h.symmetric.comap f), @(h.transitive.comap f)⟩
#align equivalence.comap Equivalence.comap
end Comap
namespace Relation
section Comp
variable {r : α → β → Prop} {p : β → γ → Prop} {q : γ → δ → Prop}
/-- The composition of two relations, yielding a new relation. The result
relates a term of `α` and a term of `γ` if there is an intermediate
term of `β` related to both.
-/
def Comp (r : α → β → Prop) (p : β → γ → Prop) (a : α) (c : γ) : Prop :=
∃ b, r a b ∧ p b c
#align relation.comp Relation.Comp
@[inherit_doc]
local infixr:80 " ∘r " => Relation.Comp
theorem comp_eq : r ∘r (· = ·) = r :=
funext fun _ ↦ funext fun b ↦ propext <|
Iff.intro (fun ⟨_, h, Eq⟩ ↦ Eq ▸ h) fun h ↦ ⟨b, h, rfl⟩
#align relation.comp_eq Relation.comp_eq
theorem eq_comp : (· = ·) ∘r r = r :=
funext fun a ↦ funext fun _ ↦ propext <|
Iff.intro (fun ⟨_, Eq, h⟩ ↦ Eq.symm ▸ h) fun h ↦ ⟨a, rfl, h⟩
#align relation.eq_comp Relation.eq_comp
theorem iff_comp {r : Prop → α → Prop} : (· ↔ ·) ∘r r = r := by
have : (· ↔ ·) = (· = ·) := by funext a b; exact iff_eq_eq
rw [this, eq_comp]
#align relation.iff_comp Relation.iff_comp
theorem comp_iff {r : α → Prop → Prop} : r ∘r (· ↔ ·) = r := by
have : (· ↔ ·) = (· = ·) := by funext a b; exact iff_eq_eq
rw [this, comp_eq]
#align relation.comp_iff Relation.comp_iff
theorem comp_assoc : (r ∘r p) ∘r q = r ∘r p ∘r q := by
funext a d
apply propext
constructor
· exact fun ⟨c, ⟨b, hab, hbc⟩, hcd⟩ ↦ ⟨b, hab, c, hbc, hcd⟩
· exact fun ⟨b, hab, c, hbc, hcd⟩ ↦ ⟨c, ⟨b, hab, hbc⟩, hcd⟩
#align relation.comp_assoc Relation.comp_assoc
theorem flip_comp : flip (r ∘r p) = flip p ∘r flip r := by
funext c a
apply propext
constructor
· exact fun ⟨b, hab, hbc⟩ ↦ ⟨b, hbc, hab⟩
· exact fun ⟨b, hbc, hab⟩ ↦ ⟨b, hab, hbc⟩
#align relation.flip_comp Relation.flip_comp
end Comp
section Fibration
variable (rα : α → α → Prop) (rβ : β → β → Prop) (f : α → β)
/-- A function `f : α → β` is a fibration between the relation `rα` and `rβ` if for all
`a : α` and `b : β`, whenever `b : β` and `f a` are related by `rβ`, `b` is the image
of some `a' : α` under `f`, and `a'` and `a` are related by `rα`. -/
def Fibration :=
∀ ⦃a b⦄, rβ b (f a) → ∃ a', rα a' a ∧ f a' = b
#align relation.fibration Relation.Fibration
variable {rα rβ}
/-- If `f : α → β` is a fibration between relations `rα` and `rβ`, and `a : α` is
accessible under `rα`, then `f a` is accessible under `rβ`. -/
theorem _root_.Acc.of_fibration (fib : Fibration rα rβ f) {a} (ha : Acc rα a) : Acc rβ (f a) := by
induction' ha with a _ ih
refine Acc.intro (f a) fun b hr ↦ ?_
obtain ⟨a', hr', rfl⟩ := fib hr
exact ih a' hr'
#align acc.of_fibration Acc.of_fibration
theorem _root_.Acc.of_downward_closed (dc : ∀ {a b}, rβ b (f a) → ∃ c, f c = b) (a : α)
(ha : Acc (InvImage rβ f) a) : Acc rβ (f a) :=
ha.of_fibration f fun a _ h ↦
let ⟨a', he⟩ := dc h
-- Porting note: Lean 3 did not need the motive
⟨a', he.substr (p := fun x ↦ rβ x (f a)) h, he⟩
#align acc.of_downward_closed Acc.of_downward_closed
end Fibration
section Map
variable {r : α → β → Prop} {f : α → γ} {g : β → δ} {c : γ} {d : δ}
/-- The map of a relation `r` through a pair of functions pushes the
relation to the codomains of the functions. The resulting relation is
defined by having pairs of terms related if they have preimages
related by `r`.
-/
protected def Map (r : α → β → Prop) (f : α → γ) (g : β → δ) : γ → δ → Prop := fun c d ↦
∃ a b, r a b ∧ f a = c ∧ g b = d
#align relation.map Relation.Map
lemma map_apply : Relation.Map r f g c d ↔ ∃ a b, r a b ∧ f a = c ∧ g b = d := Iff.rfl
#align relation.map_apply Relation.map_apply
@[simp] lemma map_map (r : α → β → Prop) (f₁ : α → γ) (g₁ : β → δ) (f₂ : γ → ε) (g₂ : δ → ζ) :
Relation.Map (Relation.Map r f₁ g₁) f₂ g₂ = Relation.Map r (f₂ ∘ f₁) (g₂ ∘ g₁) := by
ext a b
simp_rw [Relation.Map, Function.comp_apply, ← exists_and_right, @exists_comm γ, @exists_comm δ]
refine exists₂_congr fun a b ↦ ⟨?_, fun h ↦ ⟨_, _, ⟨⟨h.1, rfl, rfl⟩, h.2⟩⟩⟩
rintro ⟨_, _, ⟨hab, rfl, rfl⟩, h⟩
exact ⟨hab, h⟩
#align relation.map_map Relation.map_map
@[simp]
lemma map_apply_apply (hf : Injective f) (hg : Injective g) (r : α → β → Prop) (a : α) (b : β) :
Relation.Map r f g (f a) (g b) ↔ r a b := by simp [Relation.Map, hf.eq_iff, hg.eq_iff]
@[simp] lemma map_id_id (r : α → β → Prop) : Relation.Map r id id = r := by ext; simp [Relation.Map]
#align relation.map_id_id Relation.map_id_id
instance [Decidable (∃ a b, r a b ∧ f a = c ∧ g b = d)] : Decidable (Relation.Map r f g c d) :=
‹Decidable _›
end Map
variable {r : α → α → Prop} {a b c d : α}
/-- `ReflTransGen r`: reflexive transitive closure of `r` -/
@[mk_iff ReflTransGen.cases_tail_iff]
inductive ReflTransGen (r : α → α → Prop) (a : α) : α → Prop
| refl : ReflTransGen r a a
| tail {b c} : ReflTransGen r a b → r b c → ReflTransGen r a c
#align relation.refl_trans_gen Relation.ReflTransGen
#align relation.refl_trans_gen.cases_tail_iff Relation.ReflTransGen.cases_tail_iff
attribute [refl] ReflTransGen.refl
/-- `ReflGen r`: reflexive closure of `r` -/
@[mk_iff]
inductive ReflGen (r : α → α → Prop) (a : α) : α → Prop
| refl : ReflGen r a a
| single {b} : r a b → ReflGen r a b
#align relation.refl_gen Relation.ReflGen
#align relation.refl_gen_iff Relation.reflGen_iff
/-- `TransGen r`: transitive closure of `r` -/
@[mk_iff]
inductive TransGen (r : α → α → Prop) (a : α) : α → Prop
| single {b} : r a b → TransGen r a b
| tail {b c} : TransGen r a b → r b c → TransGen r a c
#align relation.trans_gen Relation.TransGen
#align relation.trans_gen_iff Relation.transGen_iff
attribute [refl] ReflGen.refl
namespace ReflGen
theorem to_reflTransGen : ∀ {a b}, ReflGen r a b → ReflTransGen r a b
| a, _, refl => by rfl
| a, b, single h => ReflTransGen.tail ReflTransGen.refl h
#align relation.refl_gen.to_refl_trans_gen Relation.ReflGen.to_reflTransGen
theorem mono {p : α → α → Prop} (hp : ∀ a b, r a b → p a b) : ∀ {a b}, ReflGen r a b → ReflGen p a b
| a, _, ReflGen.refl => by rfl
| a, b, single h => single (hp a b h)
#align relation.refl_gen.mono Relation.ReflGen.mono
instance : IsRefl α (ReflGen r) :=
⟨@refl α r⟩
end ReflGen
namespace ReflTransGen
@[trans]
theorem trans (hab : ReflTransGen r a b) (hbc : ReflTransGen r b c) : ReflTransGen r a c := by
induction hbc with
| refl => assumption
| tail _ hcd hac => exact hac.tail hcd
#align relation.refl_trans_gen.trans Relation.ReflTransGen.trans
theorem single (hab : r a b) : ReflTransGen r a b :=
refl.tail hab
#align relation.refl_trans_gen.single Relation.ReflTransGen.single
theorem head (hab : r a b) (hbc : ReflTransGen r b c) : ReflTransGen r a c := by
induction hbc with
| refl => exact refl.tail hab
| tail _ hcd hac => exact hac.tail hcd
#align relation.refl_trans_gen.head Relation.ReflTransGen.head
theorem symmetric (h : Symmetric r) : Symmetric (ReflTransGen r) := by
intro x y h
induction' h with z w _ b c
· rfl
· apply Relation.ReflTransGen.head (h b) c
#align relation.refl_trans_gen.symmetric Relation.ReflTransGen.symmetric
theorem cases_tail : ReflTransGen r a b → b = a ∨ ∃ c, ReflTransGen r a c ∧ r c b :=
(cases_tail_iff r a b).1
#align relation.refl_trans_gen.cases_tail Relation.ReflTransGen.cases_tail
@[elab_as_elim]
theorem head_induction_on {P : ∀ a : α, ReflTransGen r a b → Prop} {a : α} (h : ReflTransGen r a b)
(refl : P b refl)
(head : ∀ {a c} (h' : r a c) (h : ReflTransGen r c b), P c h → P a (h.head h')) : P a h := by
induction h with
| refl => exact refl
| @tail b c _ hbc ih =>
apply ih
· exact head hbc _ refl
· exact fun h1 h2 ↦ head h1 (h2.tail hbc)
#align relation.refl_trans_gen.head_induction_on Relation.ReflTransGen.head_induction_on
@[elab_as_elim]
theorem trans_induction_on {P : ∀ {a b : α}, ReflTransGen r a b → Prop} {a b : α}
(h : ReflTransGen r a b) (ih₁ : ∀ a, @P a a refl) (ih₂ : ∀ {a b} (h : r a b), P (single h))
(ih₃ : ∀ {a b c} (h₁ : ReflTransGen r a b) (h₂ : ReflTransGen r b c), P h₁ → P h₂ →
P (h₁.trans h₂)) : P h := by
induction h with
| refl => exact ih₁ a
| tail hab hbc ih => exact ih₃ hab (single hbc) ih (ih₂ hbc)
#align relation.refl_trans_gen.trans_induction_on Relation.ReflTransGen.trans_induction_on
theorem cases_head (h : ReflTransGen r a b) : a = b ∨ ∃ c, r a c ∧ ReflTransGen r c b := by
induction h using Relation.ReflTransGen.head_induction_on
· left
rfl
· right
exact ⟨_, by assumption, by assumption⟩;
#align relation.refl_trans_gen.cases_head Relation.ReflTransGen.cases_head
theorem cases_head_iff : ReflTransGen r a b ↔ a = b ∨ ∃ c, r a c ∧ ReflTransGen r c b := by
use cases_head
rintro (rfl | ⟨c, hac, hcb⟩)
· rfl
· exact head hac hcb
#align relation.refl_trans_gen.cases_head_iff Relation.ReflTransGen.cases_head_iff
theorem total_of_right_unique (U : Relator.RightUnique r) (ab : ReflTransGen r a b)
(ac : ReflTransGen r a c) : ReflTransGen r b c ∨ ReflTransGen r c b := by
induction' ab with b d _ bd IH
· exact Or.inl ac
· rcases IH with (IH | IH)
· rcases cases_head IH with (rfl | ⟨e, be, ec⟩)
· exact Or.inr (single bd)
· cases U bd be
exact Or.inl ec
· exact Or.inr (IH.tail bd)
#align relation.refl_trans_gen.total_of_right_unique Relation.ReflTransGen.total_of_right_unique
end ReflTransGen
namespace TransGen
theorem to_reflTransGen {a b} (h : TransGen r a b) : ReflTransGen r a b := by
induction' h with b h b c _ bc ab
· exact ReflTransGen.single h
· exact ReflTransGen.tail ab bc
-- Porting note: in Lean 3 this function was called `to_refl` which seems wrong.
#align relation.trans_gen.to_refl Relation.TransGen.to_reflTransGen
theorem trans_left (hab : TransGen r a b) (hbc : ReflTransGen r b c) : TransGen r a c := by
induction hbc with
| refl => assumption
| tail _ hcd hac => exact hac.tail hcd
#align relation.trans_gen.trans_left Relation.TransGen.trans_left
instance : Trans (TransGen r) (ReflTransGen r) (TransGen r) :=
⟨trans_left⟩
@[trans]
theorem trans (hab : TransGen r a b) (hbc : TransGen r b c) : TransGen r a c :=
trans_left hab hbc.to_reflTransGen
#align relation.trans_gen.trans Relation.TransGen.trans
instance : Trans (TransGen r) (TransGen r) (TransGen r) :=
⟨trans⟩
theorem head' (hab : r a b) (hbc : ReflTransGen r b c) : TransGen r a c :=
trans_left (single hab) hbc
#align relation.trans_gen.head' Relation.TransGen.head'
theorem tail' (hab : ReflTransGen r a b) (hbc : r b c) : TransGen r a c := by
induction hab generalizing c with
| refl => exact single hbc
| tail _ hdb IH => exact tail (IH hdb) hbc
#align relation.trans_gen.tail' Relation.TransGen.tail'
theorem head (hab : r a b) (hbc : TransGen r b c) : TransGen r a c :=
head' hab hbc.to_reflTransGen
#align relation.trans_gen.head Relation.TransGen.head
@[elab_as_elim]
theorem head_induction_on {P : ∀ a : α, TransGen r a b → Prop} {a : α} (h : TransGen r a b)
(base : ∀ {a} (h : r a b), P a (single h))
(ih : ∀ {a c} (h' : r a c) (h : TransGen r c b), P c h → P a (h.head h')) : P a h := by
induction h with
| single h => exact base h
| @tail b c _ hbc h_ih =>
apply h_ih
· exact fun h ↦ ih h (single hbc) (base hbc)
· exact fun hab hbc ↦ ih hab _
#align relation.trans_gen.head_induction_on Relation.TransGen.head_induction_on
@[elab_as_elim]
theorem trans_induction_on {P : ∀ {a b : α}, TransGen r a b → Prop} {a b : α} (h : TransGen r a b)
(base : ∀ {a b} (h : r a b), P (single h))
(ih : ∀ {a b c} (h₁ : TransGen r a b) (h₂ : TransGen r b c), P h₁ → P h₂ → P (h₁.trans h₂)) :
P h := by
induction h with
| single h => exact base h
| tail hab hbc h_ih => exact ih hab (single hbc) h_ih (base hbc)
#align relation.trans_gen.trans_induction_on Relation.TransGen.trans_induction_on
theorem trans_right (hab : ReflTransGen r a b) (hbc : TransGen r b c) : TransGen r a c := by
induction hbc with
| single hbc => exact tail' hab hbc
| tail _ hcd hac => exact hac.tail hcd
#align relation.trans_gen.trans_right Relation.TransGen.trans_right
instance : Trans (ReflTransGen r) (TransGen r) (TransGen r) :=
⟨trans_right⟩
theorem tail'_iff : TransGen r a c ↔ ∃ b, ReflTransGen r a b ∧ r b c := by
refine ⟨fun h ↦ ?_, fun ⟨b, hab, hbc⟩ ↦ tail' hab hbc⟩
cases' h with _ hac b _ hab hbc
· exact ⟨_, by rfl, hac⟩
· exact ⟨_, hab.to_reflTransGen, hbc⟩
#align relation.trans_gen.tail'_iff Relation.TransGen.tail'_iff
theorem head'_iff : TransGen r a c ↔ ∃ b, r a b ∧ ReflTransGen r b c := by
refine ⟨fun h ↦ ?_, fun ⟨b, hab, hbc⟩ ↦ head' hab hbc⟩
induction h with
| single hac => exact ⟨_, hac, by rfl⟩
| tail _ hbc IH =>
rcases IH with ⟨d, had, hdb⟩
exact ⟨_, had, hdb.tail hbc⟩
#align relation.trans_gen.head'_iff Relation.TransGen.head'_iff
end TransGen
theorem _root_.Acc.TransGen (h : Acc r a) : Acc (TransGen r) a := by
induction' h with x _ H
refine Acc.intro x fun y hy ↦ ?_
cases' hy with _ hyx z _ hyz hzx
exacts [H y hyx, (H z hzx).inv hyz]
#align acc.trans_gen Acc.TransGen
theorem _root_.acc_transGen_iff : Acc (TransGen r) a ↔ Acc r a :=
⟨Subrelation.accessible TransGen.single, Acc.TransGen⟩
#align acc_trans_gen_iff acc_transGen_iff
theorem _root_.WellFounded.transGen (h : WellFounded r) : WellFounded (TransGen r) :=
⟨fun a ↦ (h.apply a).TransGen⟩
#align well_founded.trans_gen WellFounded.transGen
section reflGen
lemma reflGen_eq_self (hr : Reflexive r) : ReflGen r = r := by
ext x y
simpa only [reflGen_iff, or_iff_right_iff_imp] using fun h ↦ h ▸ hr y
lemma reflexive_reflGen : Reflexive (ReflGen r) := fun _ ↦ .refl
lemma reflGen_minimal {r' : α → α → Prop} (hr' : Reflexive r') (h : ∀ x y, r x y → r' x y) {x y : α}
(hxy : ReflGen r x y) : r' x y := by
simpa [reflGen_eq_self hr'] using ReflGen.mono h hxy
end reflGen
section TransGen
theorem transGen_eq_self (trans : Transitive r) : TransGen r = r :=
funext fun a ↦ funext fun b ↦ propext <|
⟨fun h ↦ by
induction h with
| single hc => exact hc
| tail _ hcd hac => exact trans hac hcd, TransGen.single⟩
#align relation.trans_gen_eq_self Relation.transGen_eq_self
theorem transitive_transGen : Transitive (TransGen r) := fun _ _ _ ↦ TransGen.trans
#align relation.transitive_trans_gen Relation.transitive_transGen
instance : IsTrans α (TransGen r) :=
⟨@TransGen.trans α r⟩
theorem transGen_idem : TransGen (TransGen r) = TransGen r :=
transGen_eq_self transitive_transGen
#align relation.trans_gen_idem Relation.transGen_idem
theorem TransGen.lift {p : β → β → Prop} {a b : α} (f : α → β) (h : ∀ a b, r a b → p (f a) (f b))
(hab : TransGen r a b) : TransGen p (f a) (f b) := by
induction hab with
| single hac => exact TransGen.single (h a _ hac)
| tail _ hcd hac => exact TransGen.tail hac (h _ _ hcd)
#align relation.trans_gen.lift Relation.TransGen.lift
theorem TransGen.lift' {p : β → β → Prop} {a b : α} (f : α → β)
(h : ∀ a b, r a b → TransGen p (f a) (f b)) (hab : TransGen r a b) :
TransGen p (f a) (f b) := by
simpa [transGen_idem] using hab.lift f h
#align relation.trans_gen.lift' Relation.TransGen.lift'
theorem TransGen.closed {p : α → α → Prop} :
(∀ a b, r a b → TransGen p a b) → TransGen r a b → TransGen p a b :=
TransGen.lift' id
#align relation.trans_gen.closed Relation.TransGen.closed
theorem TransGen.mono {p : α → α → Prop} :
(∀ a b, r a b → p a b) → TransGen r a b → TransGen p a b :=
TransGen.lift id
#align relation.trans_gen.mono Relation.TransGen.mono
lemma transGen_minimal {r' : α → α → Prop} (hr' : Transitive r') (h : ∀ x y, r x y → r' x y)
{x y : α} (hxy : TransGen r x y) : r' x y := by
simpa [transGen_eq_self hr'] using TransGen.mono h hxy
theorem TransGen.swap (h : TransGen r b a) : TransGen (swap r) a b := by
induction' h with b h b c _ hbc ih
· exact TransGen.single h
· exact ih.head hbc
#align relation.trans_gen.swap Relation.TransGen.swap
theorem transGen_swap : TransGen (swap r) a b ↔ TransGen r b a :=
⟨TransGen.swap, TransGen.swap⟩
#align relation.trans_gen_swap Relation.transGen_swap
end TransGen
section ReflTransGen
open ReflTransGen
theorem reflTransGen_iff_eq (h : ∀ b, ¬r a b) : ReflTransGen r a b ↔ b = a := by
rw [cases_head_iff]; simp [h, eq_comm]
#align relation.refl_trans_gen_iff_eq Relation.reflTransGen_iff_eq
| Mathlib/Logic/Relation.lean | 559 | 566 | theorem reflTransGen_iff_eq_or_transGen : ReflTransGen r a b ↔ b = a ∨ TransGen r a b := by |
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· cases' h with c _ hac hcb
· exact Or.inl rfl
· exact Or.inr (TransGen.tail' hac hcb)
· rcases h with (rfl | h)
· rfl
· exact h.to_reflTransGen
|
/-
Copyright (c) 2019 Neil Strickland. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Neil Strickland
-/
import Mathlib.Algebra.BigOperators.Group.Multiset
import Mathlib.Data.PNat.Prime
import Mathlib.Data.Nat.Factors
import Mathlib.Data.Multiset.Sort
#align_import data.pnat.factors from "leanprover-community/mathlib"@"e3d9ab8faa9dea8f78155c6c27d62a621f4c152d"
/-!
# Prime factors of nonzero naturals
This file defines the factorization of a nonzero natural number `n` as a multiset of primes,
the multiplicity of `p` in this factors multiset being the p-adic valuation of `n`.
## Main declarations
* `PrimeMultiset`: Type of multisets of prime numbers.
* `FactorMultiset n`: Multiset of prime factors of `n`.
-/
-- Porting note: `deriving` contained Inhabited, CanonicallyOrderedAddCommMonoid, DistribLattice,
-- SemilatticeSup, OrderBot, Sub, OrderedSub
/-- The type of multisets of prime numbers. Unique factorization
gives an equivalence between this set and ℕ+, as we will formalize
below. -/
def PrimeMultiset :=
Multiset Nat.Primes deriving Inhabited, CanonicallyOrderedAddCommMonoid, DistribLattice,
SemilatticeSup, Sub
#align prime_multiset PrimeMultiset
instance : OrderBot PrimeMultiset where
bot_le := by simp only [bot_le, forall_const]
instance : OrderedSub PrimeMultiset where
tsub_le_iff_right _ _ _ := Multiset.sub_le_iff_le_add
namespace PrimeMultiset
-- `@[derive]` doesn't work for `meta` instances
unsafe instance : Repr PrimeMultiset := by delta PrimeMultiset; infer_instance
/-- The multiset consisting of a single prime -/
def ofPrime (p : Nat.Primes) : PrimeMultiset :=
({p} : Multiset Nat.Primes)
#align prime_multiset.of_prime PrimeMultiset.ofPrime
theorem card_ofPrime (p : Nat.Primes) : Multiset.card (ofPrime p) = 1 :=
rfl
#align prime_multiset.card_of_prime PrimeMultiset.card_ofPrime
/-- We can forget the primality property and regard a multiset
of primes as just a multiset of positive integers, or a multiset
of natural numbers. In the opposite direction, if we have a
multiset of positive integers or natural numbers, together with
a proof that all the elements are prime, then we can regard it
as a multiset of primes. The next block of results records
obvious properties of these coercions.
-/
def toNatMultiset : PrimeMultiset → Multiset ℕ := fun v => v.map Coe.coe
#align prime_multiset.to_nat_multiset PrimeMultiset.toNatMultiset
instance coeNat : Coe PrimeMultiset (Multiset ℕ) :=
⟨toNatMultiset⟩
#align prime_multiset.coe_nat PrimeMultiset.coeNat
/-- `PrimeMultiset.coe`, the coercion from a multiset of primes to a multiset of
naturals, promoted to an `AddMonoidHom`. -/
def coeNatMonoidHom : PrimeMultiset →+ Multiset ℕ :=
{ Multiset.mapAddMonoidHom Coe.coe with toFun := Coe.coe }
#align prime_multiset.coe_nat_monoid_hom PrimeMultiset.coeNatMonoidHom
@[simp]
theorem coe_coeNatMonoidHom : (coeNatMonoidHom : PrimeMultiset → Multiset ℕ) = Coe.coe :=
rfl
#align prime_multiset.coe_coe_nat_monoid_hom PrimeMultiset.coe_coeNatMonoidHom
theorem coeNat_injective : Function.Injective (Coe.coe : PrimeMultiset → Multiset ℕ) :=
Multiset.map_injective Nat.Primes.coe_nat_injective
#align prime_multiset.coe_nat_injective PrimeMultiset.coeNat_injective
theorem coeNat_ofPrime (p : Nat.Primes) : (ofPrime p : Multiset ℕ) = {(p : ℕ)} :=
rfl
#align prime_multiset.coe_nat_of_prime PrimeMultiset.coeNat_ofPrime
theorem coeNat_prime (v : PrimeMultiset) (p : ℕ) (h : p ∈ (v : Multiset ℕ)) : p.Prime := by
rcases Multiset.mem_map.mp h with ⟨⟨_, hp'⟩, ⟨_, h_eq⟩⟩
exact h_eq ▸ hp'
#align prime_multiset.coe_nat_prime PrimeMultiset.coeNat_prime
/-- Converts a `PrimeMultiset` to a `Multiset ℕ+`. -/
def toPNatMultiset : PrimeMultiset → Multiset ℕ+ := fun v => v.map Coe.coe
#align prime_multiset.to_pnat_multiset PrimeMultiset.toPNatMultiset
instance coePNat : Coe PrimeMultiset (Multiset ℕ+) :=
⟨toPNatMultiset⟩
#align prime_multiset.coe_pnat PrimeMultiset.coePNat
/-- `coePNat`, the coercion from a multiset of primes to a multiset of positive
naturals, regarded as an `AddMonoidHom`. -/
def coePNatMonoidHom : PrimeMultiset →+ Multiset ℕ+ :=
{ Multiset.mapAddMonoidHom Coe.coe with toFun := Coe.coe }
#align prime_multiset.coe_pnat_monoid_hom PrimeMultiset.coePNatMonoidHom
@[simp]
theorem coe_coePNatMonoidHom : (coePNatMonoidHom : PrimeMultiset → Multiset ℕ+) = Coe.coe :=
rfl
#align prime_multiset.coe_coe_pnat_monoid_hom PrimeMultiset.coe_coePNatMonoidHom
theorem coePNat_injective : Function.Injective (Coe.coe : PrimeMultiset → Multiset ℕ+) :=
Multiset.map_injective Nat.Primes.coe_pnat_injective
#align prime_multiset.coe_pnat_injective PrimeMultiset.coePNat_injective
theorem coePNat_ofPrime (p : Nat.Primes) : (ofPrime p : Multiset ℕ+) = {(p : ℕ+)} :=
rfl
#align prime_multiset.coe_pnat_of_prime PrimeMultiset.coePNat_ofPrime
theorem coePNat_prime (v : PrimeMultiset) (p : ℕ+) (h : p ∈ (v : Multiset ℕ+)) : p.Prime := by
rcases Multiset.mem_map.mp h with ⟨⟨_, hp'⟩, ⟨_, h_eq⟩⟩
exact h_eq ▸ hp'
#align prime_multiset.coe_pnat_prime PrimeMultiset.coePNat_prime
instance coeMultisetPNatNat : Coe (Multiset ℕ+) (Multiset ℕ) :=
⟨fun v => v.map Coe.coe⟩
#align prime_multiset.coe_multiset_pnat_nat PrimeMultiset.coeMultisetPNatNat
theorem coePNat_nat (v : PrimeMultiset) : ((v : Multiset ℕ+) : Multiset ℕ) = (v : Multiset ℕ) := by
change (v.map (Coe.coe : Nat.Primes → ℕ+)).map Subtype.val = v.map Subtype.val
rw [Multiset.map_map]
congr
#align prime_multiset.coe_pnat_nat PrimeMultiset.coePNat_nat
/-- The product of a `PrimeMultiset`, as a `ℕ+`. -/
def prod (v : PrimeMultiset) : ℕ+ :=
(v : Multiset PNat).prod
#align prime_multiset.prod PrimeMultiset.prod
theorem coe_prod (v : PrimeMultiset) : (v.prod : ℕ) = (v : Multiset ℕ).prod := by
let h : (v.prod : ℕ) = ((v.map Coe.coe).map Coe.coe).prod :=
PNat.coeMonoidHom.map_multiset_prod v.toPNatMultiset
rw [Multiset.map_map] at h
have : (Coe.coe : ℕ+ → ℕ) ∘ (Coe.coe : Nat.Primes → ℕ+) = Coe.coe := funext fun p => rfl
rw [this] at h; exact h
#align prime_multiset.coe_prod PrimeMultiset.coe_prod
theorem prod_ofPrime (p : Nat.Primes) : (ofPrime p).prod = (p : ℕ+) :=
Multiset.prod_singleton _
#align prime_multiset.prod_of_prime PrimeMultiset.prod_ofPrime
/-- If a `Multiset ℕ` consists only of primes, it can be recast as a `PrimeMultiset`. -/
def ofNatMultiset (v : Multiset ℕ) (h : ∀ p : ℕ, p ∈ v → p.Prime) : PrimeMultiset :=
@Multiset.pmap ℕ Nat.Primes Nat.Prime (fun p hp => ⟨p, hp⟩) v h
#align prime_multiset.of_nat_multiset PrimeMultiset.ofNatMultiset
theorem to_ofNatMultiset (v : Multiset ℕ) (h) : (ofNatMultiset v h : Multiset ℕ) = v := by
dsimp [ofNatMultiset, toNatMultiset]
have : (fun p h => (Coe.coe : Nat.Primes → ℕ) ⟨p, h⟩) = fun p _ => id p := by
funext p h
rfl
rw [Multiset.map_pmap, this, Multiset.pmap_eq_map, Multiset.map_id]
#align prime_multiset.to_of_nat_multiset PrimeMultiset.to_ofNatMultiset
theorem prod_ofNatMultiset (v : Multiset ℕ) (h) :
((ofNatMultiset v h).prod : ℕ) = (v.prod : ℕ) := by rw [coe_prod, to_ofNatMultiset]
#align prime_multiset.prod_of_nat_multiset PrimeMultiset.prod_ofNatMultiset
/-- If a `Multiset ℕ+` consists only of primes, it can be recast as a `PrimeMultiset`. -/
def ofPNatMultiset (v : Multiset ℕ+) (h : ∀ p : ℕ+, p ∈ v → p.Prime) : PrimeMultiset :=
@Multiset.pmap ℕ+ Nat.Primes PNat.Prime (fun p hp => ⟨(p : ℕ), hp⟩) v h
#align prime_multiset.of_pnat_multiset PrimeMultiset.ofPNatMultiset
theorem to_ofPNatMultiset (v : Multiset ℕ+) (h) : (ofPNatMultiset v h : Multiset ℕ+) = v := by
dsimp [ofPNatMultiset, toPNatMultiset]
have : (fun (p : ℕ+) (h : p.Prime) => (Coe.coe : Nat.Primes → ℕ+) ⟨p, h⟩) = fun p _ => id p := by
funext p h
apply Subtype.eq
rfl
rw [Multiset.map_pmap, this, Multiset.pmap_eq_map, Multiset.map_id]
#align prime_multiset.to_of_pnat_multiset PrimeMultiset.to_ofPNatMultiset
theorem prod_ofPNatMultiset (v : Multiset ℕ+) (h) : ((ofPNatMultiset v h).prod : ℕ+) = v.prod := by
dsimp [prod]
rw [to_ofPNatMultiset]
#align prime_multiset.prod_of_pnat_multiset PrimeMultiset.prod_ofPNatMultiset
/-- Lists can be coerced to multisets; here we have some results
about how this interacts with our constructions on multisets. -/
def ofNatList (l : List ℕ) (h : ∀ p : ℕ, p ∈ l → p.Prime) : PrimeMultiset :=
ofNatMultiset (l : Multiset ℕ) h
#align prime_multiset.of_nat_list PrimeMultiset.ofNatList
| Mathlib/Data/PNat/Factors.lean | 195 | 198 | theorem prod_ofNatList (l : List ℕ) (h) : ((ofNatList l h).prod : ℕ) = l.prod := by |
have := prod_ofNatMultiset (l : Multiset ℕ) h
rw [Multiset.prod_coe] at this
exact this
|
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.LinearAlgebra.AffineSpace.Independent
import Mathlib.LinearAlgebra.Basis
#align_import linear_algebra.affine_space.basis from "leanprover-community/mathlib"@"2de9c37fa71dde2f1c6feff19876dd6a7b1519f0"
/-!
# Affine bases and barycentric coordinates
Suppose `P` is an affine space modelled on the module `V` over the ring `k`, and `p : ι → P` is an
affine-independent family of points spanning `P`. Given this data, each point `q : P` may be written
uniquely as an affine combination: `q = w₀ p₀ + w₁ p₁ + ⋯` for some (finitely-supported) weights
`wᵢ`. For each `i : ι`, we thus have an affine map `P →ᵃ[k] k`, namely `q ↦ wᵢ`. This family of
maps is known as the family of barycentric coordinates. It is defined in this file.
## The construction
Fixing `i : ι`, and allowing `j : ι` to range over the values `j ≠ i`, we obtain a basis `bᵢ` of `V`
defined by `bᵢ j = p j -ᵥ p i`. Let `fᵢ j : V →ₗ[k] k` be the corresponding dual basis and let
`fᵢ = ∑ j, fᵢ j : V →ₗ[k] k` be the corresponding "sum of all coordinates" form. Then the `i`th
barycentric coordinate of `q : P` is `1 - fᵢ (q -ᵥ p i)`.
## Main definitions
* `AffineBasis`: a structure representing an affine basis of an affine space.
* `AffineBasis.coord`: the map `P →ᵃ[k] k` corresponding to `i : ι`.
* `AffineBasis.coord_apply_eq`: the behaviour of `AffineBasis.coord i` on `p i`.
* `AffineBasis.coord_apply_ne`: the behaviour of `AffineBasis.coord i` on `p j` when `j ≠ i`.
* `AffineBasis.coord_apply`: the behaviour of `AffineBasis.coord i` on `p j` for general `j`.
* `AffineBasis.coord_apply_combination`: the characterisation of `AffineBasis.coord i` in terms
of affine combinations, i.e., `AffineBasis.coord i (w₀ p₀ + w₁ p₁ + ⋯) = wᵢ`.
## TODO
* Construct the affine equivalence between `P` and `{ f : ι →₀ k | f.sum = 1 }`.
-/
open Affine
open Set
universe u₁ u₂ u₃ u₄
/-- An affine basis is a family of affine-independent points whose span is the top subspace. -/
structure AffineBasis (ι : Type u₁) (k : Type u₂) {V : Type u₃} (P : Type u₄) [AddCommGroup V]
[AffineSpace V P] [Ring k] [Module k V] where
protected toFun : ι → P
protected ind' : AffineIndependent k toFun
protected tot' : affineSpan k (range toFun) = ⊤
#align affine_basis AffineBasis
variable {ι ι' k V P : Type*} [AddCommGroup V] [AffineSpace V P]
namespace AffineBasis
section Ring
variable [Ring k] [Module k V] (b : AffineBasis ι k P) {s : Finset ι} {i j : ι} (e : ι ≃ ι')
/-- The unique point in a single-point space is the simplest example of an affine basis. -/
instance : Inhabited (AffineBasis PUnit k PUnit) :=
⟨⟨id, affineIndependent_of_subsingleton k id, by simp⟩⟩
instance instFunLike : FunLike (AffineBasis ι k P) ι P where
coe := AffineBasis.toFun
coe_injective' f g h := by cases f; cases g; congr
#align affine_basis.fun_like AffineBasis.instFunLike
@[ext]
theorem ext {b₁ b₂ : AffineBasis ι k P} (h : (b₁ : ι → P) = b₂) : b₁ = b₂ :=
DFunLike.coe_injective h
#align affine_basis.ext AffineBasis.ext
theorem ind : AffineIndependent k b :=
b.ind'
#align affine_basis.ind AffineBasis.ind
theorem tot : affineSpan k (range b) = ⊤ :=
b.tot'
#align affine_basis.tot AffineBasis.tot
protected theorem nonempty : Nonempty ι :=
not_isEmpty_iff.mp fun hι => by
simpa only [@range_eq_empty _ _ hι, AffineSubspace.span_empty, bot_ne_top] using b.tot
#align affine_basis.nonempty AffineBasis.nonempty
/-- Composition of an affine basis and an equivalence of index types. -/
def reindex (e : ι ≃ ι') : AffineBasis ι' k P :=
⟨b ∘ e.symm, b.ind.comp_embedding e.symm.toEmbedding, by
rw [e.symm.surjective.range_comp]
exact b.3⟩
#align affine_basis.reindex AffineBasis.reindex
@[simp, norm_cast]
theorem coe_reindex : ⇑(b.reindex e) = b ∘ e.symm :=
rfl
#align affine_basis.coe_reindex AffineBasis.coe_reindex
@[simp]
theorem reindex_apply (i' : ι') : b.reindex e i' = b (e.symm i') :=
rfl
#align affine_basis.reindex_apply AffineBasis.reindex_apply
@[simp]
theorem reindex_refl : b.reindex (Equiv.refl _) = b :=
ext rfl
#align affine_basis.reindex_refl AffineBasis.reindex_refl
/-- Given an affine basis for an affine space `P`, if we single out one member of the family, we
obtain a linear basis for the model space `V`.
The linear basis corresponding to the singled-out member `i : ι` is indexed by `{j : ι // j ≠ i}`
and its `j`th element is `b j -ᵥ b i`. (See `basisOf_apply`.) -/
noncomputable def basisOf (i : ι) : Basis { j : ι // j ≠ i } k V :=
Basis.mk ((affineIndependent_iff_linearIndependent_vsub k b i).mp b.ind)
(by
suffices
Submodule.span k (range fun j : { x // x ≠ i } => b ↑j -ᵥ b i) = vectorSpan k (range b) by
rw [this, ← direction_affineSpan, b.tot, AffineSubspace.direction_top]
conv_rhs => rw [← image_univ]
rw [vectorSpan_image_eq_span_vsub_set_right_ne k b (mem_univ i)]
congr
ext v
simp)
#align affine_basis.basis_of AffineBasis.basisOf
@[simp]
theorem basisOf_apply (i : ι) (j : { j : ι // j ≠ i }) : b.basisOf i j = b ↑j -ᵥ b i := by
simp [basisOf]
#align affine_basis.basis_of_apply AffineBasis.basisOf_apply
@[simp]
theorem basisOf_reindex (i : ι') :
(b.reindex e).basisOf i =
(b.basisOf <| e.symm i).reindex (e.subtypeEquiv fun _ => e.eq_symm_apply.not) := by
ext j
simp
#align affine_basis.basis_of_reindex AffineBasis.basisOf_reindex
/-- The `i`th barycentric coordinate of a point. -/
noncomputable def coord (i : ι) : P →ᵃ[k] k where
toFun q := 1 - (b.basisOf i).sumCoords (q -ᵥ b i)
linear := -(b.basisOf i).sumCoords
map_vadd' q v := by
dsimp only
rw [vadd_vsub_assoc, LinearMap.map_add, vadd_eq_add, LinearMap.neg_apply,
sub_add_eq_sub_sub_swap, add_comm, sub_eq_add_neg]
#align affine_basis.coord AffineBasis.coord
@[simp]
theorem linear_eq_sumCoords (i : ι) : (b.coord i).linear = -(b.basisOf i).sumCoords :=
rfl
#align affine_basis.linear_eq_sum_coords AffineBasis.linear_eq_sumCoords
@[simp]
theorem coord_reindex (i : ι') : (b.reindex e).coord i = b.coord (e.symm i) := by
ext
classical simp [AffineBasis.coord]
#align affine_basis.coord_reindex AffineBasis.coord_reindex
@[simp]
| Mathlib/LinearAlgebra/AffineSpace/Basis.lean | 168 | 170 | theorem coord_apply_eq (i : ι) : b.coord i (b i) = 1 := by |
simp only [coord, Basis.coe_sumCoords, LinearEquiv.map_zero, LinearEquiv.coe_coe, sub_zero,
AffineMap.coe_mk, Finsupp.sum_zero_index, vsub_self]
|
/-
Copyright (c) 2022 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Roblot
-/
import Mathlib.MeasureTheory.Group.GeometryOfNumbers
import Mathlib.MeasureTheory.Measure.Lebesgue.VolumeOfBalls
import Mathlib.NumberTheory.NumberField.CanonicalEmbedding.Basic
#align_import number_theory.number_field.canonical_embedding from "leanprover-community/mathlib"@"60da01b41bbe4206f05d34fd70c8dd7498717a30"
/-!
# Convex Bodies
The file contains the definitions of several convex bodies lying in the space `ℝ^r₁ × ℂ^r₂`
associated to a number field of signature `K` and proves several existence theorems by applying
*Minkowski Convex Body Theorem* to those.
## Main definitions and results
* `NumberField.mixedEmbedding.convexBodyLT`: The set of points `x` such that `‖x w‖ < f w` for all
infinite places `w` with `f : InfinitePlace K → ℝ≥0`.
* `NumberField.mixedEmbedding.convexBodySum`: The set of points `x` such that
`∑ w real, ‖x w‖ + 2 * ∑ w complex, ‖x w‖ ≤ B`
* `NumberField.mixedEmbedding.exists_ne_zero_mem_ideal_lt`: Let `I` be a fractional ideal of `K`.
Assume that `f` is such that `minkowskiBound K I < volume (convexBodyLT K f)`, then there exists a
nonzero algebraic number `a` in `I` such that `w a < f w` for all infinite places `w`.
* `NumberField.mixedEmbedding.exists_ne_zero_mem_ideal_of_norm_le`: Let `I` be a fractional ideal
of `K`. Assume that `B` is such that `minkowskiBound K I < volume (convexBodySum K B)` (see
`convexBodySum_volume` for the computation of this volume), then there exists a nonzero algebraic
number `a` in `I` such that `|Norm a| < (B / d) ^ d` where `d` is the degree of `K`.
## Tags
number field, infinite places
-/
variable (K : Type*) [Field K]
namespace NumberField.mixedEmbedding
open NumberField NumberField.InfinitePlace FiniteDimensional
/-- The space `ℝ^r₁ × ℂ^r₂` with `(r₁, r₂)` the signature of `K`. -/
local notation "E" K =>
({w : InfinitePlace K // IsReal w} → ℝ) × ({w : InfinitePlace K // IsComplex w} → ℂ)
section convexBodyLT
open Metric NNReal
variable (f : InfinitePlace K → ℝ≥0)
/-- The convex body defined by `f`: the set of points `x : E` such that `‖x w‖ < f w` for all
infinite places `w`. -/
abbrev convexBodyLT : Set (E K) :=
(Set.univ.pi (fun w : { w : InfinitePlace K // IsReal w } => ball 0 (f w))) ×ˢ
(Set.univ.pi (fun w : { w : InfinitePlace K // IsComplex w } => ball 0 (f w)))
theorem convexBodyLT_mem {x : K} :
mixedEmbedding K x ∈ (convexBodyLT K f) ↔ ∀ w : InfinitePlace K, w x < f w := by
simp_rw [mixedEmbedding, RingHom.prod_apply, Set.mem_prod, Set.mem_pi, Set.mem_univ,
forall_true_left, mem_ball_zero_iff, Pi.ringHom_apply, ← Complex.norm_real,
embedding_of_isReal_apply, Subtype.forall, ← forall₂_or_left, ← not_isReal_iff_isComplex, em,
forall_true_left, norm_embedding_eq]
theorem convexBodyLT_neg_mem (x : E K) (hx : x ∈ (convexBodyLT K f)) :
-x ∈ (convexBodyLT K f) := by
simp only [Set.mem_prod, Prod.fst_neg, Set.mem_pi, Set.mem_univ, Pi.neg_apply,
mem_ball_zero_iff, norm_neg, Real.norm_eq_abs, forall_true_left, Subtype.forall,
Prod.snd_neg, Complex.norm_eq_abs] at hx ⊢
exact hx
theorem convexBodyLT_convex : Convex ℝ (convexBodyLT K f) :=
Convex.prod (convex_pi (fun _ _ => convex_ball _ _)) (convex_pi (fun _ _ => convex_ball _ _))
open Fintype MeasureTheory MeasureTheory.Measure ENNReal
open scoped Classical
variable [NumberField K]
instance : IsAddHaarMeasure (volume : Measure (E K)) := prod.instIsAddHaarMeasure volume volume
instance : NoAtoms (volume : Measure (E K)) := by
obtain ⟨w⟩ := (inferInstance : Nonempty (InfinitePlace K))
by_cases hw : IsReal w
· exact @prod.instNoAtoms_fst _ _ _ _ volume volume _ (pi_noAtoms ⟨w, hw⟩)
· exact @prod.instNoAtoms_snd _ _ _ _ volume volume _
(pi_noAtoms ⟨w, not_isReal_iff_isComplex.mp hw⟩)
/-- The fudge factor that appears in the formula for the volume of `convexBodyLT`. -/
noncomputable abbrev convexBodyLTFactor : ℝ≥0 :=
(2 : ℝ≥0) ^ NrRealPlaces K * NNReal.pi ^ NrComplexPlaces K
theorem convexBodyLTFactor_ne_zero : convexBodyLTFactor K ≠ 0 :=
mul_ne_zero (pow_ne_zero _ two_ne_zero) (pow_ne_zero _ pi_ne_zero)
theorem one_le_convexBodyLTFactor : 1 ≤ convexBodyLTFactor K :=
one_le_mul₀ (one_le_pow_of_one_le one_le_two _)
(one_le_pow_of_one_le (le_trans one_le_two Real.two_le_pi) _)
/-- The volume of `(ConvexBodyLt K f)` where `convexBodyLT K f` is the set of points `x`
such that `‖x w‖ < f w` for all infinite places `w`. -/
theorem convexBodyLT_volume :
volume (convexBodyLT K f) = (convexBodyLTFactor K) * ∏ w, (f w) ^ (mult w) := by
calc
_ = (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (2 * (f x.val))) *
∏ x : {w // InfinitePlace.IsComplex w}, ENNReal.ofReal (f x.val) ^ 2 * NNReal.pi := by
simp_rw [volume_eq_prod, prod_prod, volume_pi, pi_pi, Real.volume_ball, Complex.volume_ball]
_ = ((2:ℝ≥0) ^ NrRealPlaces K * (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (f x.val)))
* ((∏ x : {w // IsComplex w}, ENNReal.ofReal (f x.val) ^ 2) *
NNReal.pi ^ NrComplexPlaces K) := by
simp_rw [ofReal_mul (by norm_num : 0 ≤ (2 : ℝ)), Finset.prod_mul_distrib, Finset.prod_const,
Finset.card_univ, ofReal_ofNat, ofReal_coe_nnreal, coe_ofNat]
_ = (convexBodyLTFactor K) * ((∏ x : {w // InfinitePlace.IsReal w}, .ofReal (f x.val)) *
(∏ x : {w // IsComplex w}, ENNReal.ofReal (f x.val) ^ 2)) := by
simp_rw [convexBodyLTFactor, coe_mul, ENNReal.coe_pow]
ring
_ = (convexBodyLTFactor K) * ∏ w, (f w) ^ (mult w) := by
simp_rw [mult, pow_ite, pow_one, Finset.prod_ite, ofReal_coe_nnreal, not_isReal_iff_isComplex,
coe_mul, coe_finset_prod, ENNReal.coe_pow]
congr 2
· refine (Finset.prod_subtype (Finset.univ.filter _) ?_ (fun w => (f w : ℝ≥0∞))).symm
exact fun _ => by simp only [Finset.mem_univ, forall_true_left, Finset.mem_filter, true_and]
· refine (Finset.prod_subtype (Finset.univ.filter _) ?_ (fun w => (f w : ℝ≥0∞) ^ 2)).symm
exact fun _ => by simp only [Finset.mem_univ, forall_true_left, Finset.mem_filter, true_and]
variable {f}
/-- This is a technical result: quite often, we want to impose conditions at all infinite places
but one and choose the value at the remaining place so that we can apply
`exists_ne_zero_mem_ringOfIntegers_lt`. -/
theorem adjust_f {w₁ : InfinitePlace K} (B : ℝ≥0) (hf : ∀ w, w ≠ w₁ → f w ≠ 0) :
∃ g : InfinitePlace K → ℝ≥0, (∀ w, w ≠ w₁ → g w = f w) ∧ ∏ w, (g w) ^ mult w = B := by
let S := ∏ w ∈ Finset.univ.erase w₁, (f w) ^ mult w
refine ⟨Function.update f w₁ ((B * S⁻¹) ^ (mult w₁ : ℝ)⁻¹), ?_, ?_⟩
· exact fun w hw => Function.update_noteq hw _ f
· rw [← Finset.mul_prod_erase Finset.univ _ (Finset.mem_univ w₁), Function.update_same,
Finset.prod_congr rfl fun w hw => by rw [Function.update_noteq (Finset.ne_of_mem_erase hw)],
← NNReal.rpow_natCast, ← NNReal.rpow_mul, inv_mul_cancel, NNReal.rpow_one, mul_assoc,
inv_mul_cancel, mul_one]
· rw [Finset.prod_ne_zero_iff]
exact fun w hw => pow_ne_zero _ (hf w (Finset.ne_of_mem_erase hw))
· rw [mult]; split_ifs <;> norm_num
end convexBodyLT
section convexBodyLT'
open Metric ENNReal NNReal
open scoped Classical
variable (f : InfinitePlace K → ℝ≥0) (w₀ : {w : InfinitePlace K // IsComplex w})
/-- A version of `convexBodyLT` with an additional condition at a fixed complex place. This is
needed to ensure the element constructed is not real, see for example
`exists_primitive_element_lt_of_isComplex`.
-/
abbrev convexBodyLT' : Set (E K) :=
(Set.univ.pi (fun w : { w : InfinitePlace K // IsReal w } ↦ ball 0 (f w))) ×ˢ
(Set.univ.pi (fun w : { w : InfinitePlace K // IsComplex w } ↦
if w = w₀ then {x | |x.re| < 1 ∧ |x.im| < (f w : ℝ) ^ 2} else ball 0 (f w)))
theorem convexBodyLT'_mem {x : K} :
mixedEmbedding K x ∈ convexBodyLT' K f w₀ ↔
(∀ w : InfinitePlace K, w ≠ w₀ → w x < f w) ∧
|(w₀.val.embedding x).re| < 1 ∧ |(w₀.val.embedding x).im| < (f w₀: ℝ) ^ 2 := by
simp_rw [mixedEmbedding, RingHom.prod_apply, Set.mem_prod, Set.mem_pi, Set.mem_univ,
forall_true_left, Pi.ringHom_apply, apply_ite, mem_ball_zero_iff, ← Complex.norm_real,
embedding_of_isReal_apply, norm_embedding_eq, Subtype.forall, Set.mem_setOf_eq]
refine ⟨fun ⟨h₁, h₂⟩ ↦ ⟨fun w h_ne ↦ ?_, ?_⟩, fun ⟨h₁, h₂⟩ ↦ ⟨fun w hw ↦ ?_, fun w hw ↦ ?_⟩⟩
· by_cases hw : IsReal w
· exact norm_embedding_eq w _ ▸ h₁ w hw
· specialize h₂ w (not_isReal_iff_isComplex.mp hw)
rwa [if_neg (by exact Subtype.coe_ne_coe.1 h_ne)] at h₂
· simpa [if_true] using h₂ w₀.val w₀.prop
· exact h₁ w (ne_of_isReal_isComplex hw w₀.prop)
· by_cases h_ne : w = w₀
· simpa [h_ne]
· rw [if_neg (by exact Subtype.coe_ne_coe.1 h_ne)]
exact h₁ w h_ne
theorem convexBodyLT'_neg_mem (x : E K) (hx : x ∈ convexBodyLT' K f w₀) :
-x ∈ convexBodyLT' K f w₀ := by
simp [Set.mem_prod, Prod.fst_neg, Set.mem_pi, Set.mem_univ, Pi.neg_apply,
mem_ball_zero_iff, norm_neg, Real.norm_eq_abs, forall_true_left, Subtype.forall,
Prod.snd_neg, Complex.norm_eq_abs] at hx ⊢
convert hx using 3
split_ifs <;> simp
theorem convexBodyLT'_convex : Convex ℝ (convexBodyLT' K f w₀) := by
refine Convex.prod (convex_pi (fun _ _ => convex_ball _ _)) (convex_pi (fun _ _ => ?_))
split_ifs
· simp_rw [abs_lt]
refine Convex.inter ((convex_halfspace_re_gt _).inter (convex_halfspace_re_lt _))
((convex_halfspace_im_gt _).inter (convex_halfspace_im_lt _))
· exact convex_ball _ _
open MeasureTheory MeasureTheory.Measure
open scoped Classical
variable [NumberField K]
/-- The fudge factor that appears in the formula for the volume of `convexBodyLT'`. -/
noncomputable abbrev convexBodyLT'Factor : ℝ≥0 :=
(2 : ℝ≥0) ^ (NrRealPlaces K + 2) * NNReal.pi ^ (NrComplexPlaces K - 1)
theorem convexBodyLT'Factor_ne_zero : convexBodyLT'Factor K ≠ 0 :=
mul_ne_zero (pow_ne_zero _ two_ne_zero) (pow_ne_zero _ pi_ne_zero)
theorem one_le_convexBodyLT'Factor : 1 ≤ convexBodyLT'Factor K :=
one_le_mul₀ (one_le_pow_of_one_le one_le_two _)
(one_le_pow_of_one_le (le_trans one_le_two Real.two_le_pi) _)
theorem convexBodyLT'_volume :
volume (convexBodyLT' K f w₀) = convexBodyLT'Factor K * ∏ w, (f w) ^ (mult w) := by
have vol_box : ∀ B : ℝ≥0, volume {x : ℂ | |x.re| < 1 ∧ |x.im| < B^2} = 4*B^2 := by
intro B
rw [← (Complex.volume_preserving_equiv_real_prod.symm).measure_preimage]
· simp_rw [Set.preimage_setOf_eq, Complex.measurableEquivRealProd_symm_apply]
rw [show {a : ℝ × ℝ | |a.1| < 1 ∧ |a.2| < B ^ 2} =
Set.Ioo (-1:ℝ) (1:ℝ) ×ˢ Set.Ioo (- (B:ℝ) ^ 2) ((B:ℝ) ^ 2) by
ext; simp_rw [Set.mem_setOf_eq, Set.mem_prod, Set.mem_Ioo, abs_lt]]
simp_rw [volume_eq_prod, prod_prod, Real.volume_Ioo, sub_neg_eq_add, one_add_one_eq_two,
← two_mul, ofReal_mul zero_le_two, ofReal_pow (coe_nonneg B), ofReal_ofNat,
ofReal_coe_nnreal, ← mul_assoc, show (2:ℝ≥0∞) * 2 = 4 by norm_num]
· refine MeasurableSet.inter ?_ ?_
· exact measurableSet_lt (measurable_norm.comp Complex.measurable_re) measurable_const
· exact measurableSet_lt (measurable_norm.comp Complex.measurable_im) measurable_const
calc
_ = (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (2 * (f x.val))) *
((∏ x ∈ Finset.univ.erase w₀, ENNReal.ofReal (f x.val) ^ 2 * pi) *
(4 * (f w₀) ^ 2)) := by
simp_rw [volume_eq_prod, prod_prod, volume_pi, pi_pi, Real.volume_ball]
rw [← Finset.prod_erase_mul _ _ (Finset.mem_univ w₀)]
congr 2
· refine Finset.prod_congr rfl (fun w' hw' ↦ ?_)
rw [if_neg (Finset.ne_of_mem_erase hw'), Complex.volume_ball]
· simpa only [ite_true] using vol_box (f w₀)
_ = ((2 : ℝ≥0) ^ NrRealPlaces K *
(∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (f x.val))) *
((∏ x ∈ Finset.univ.erase w₀, ENNReal.ofReal (f x.val) ^ 2) *
↑pi ^ (NrComplexPlaces K - 1) * (4 * (f w₀) ^ 2)) := by
simp_rw [ofReal_mul (by norm_num : 0 ≤ (2 : ℝ)), Finset.prod_mul_distrib, Finset.prod_const,
Finset.card_erase_of_mem (Finset.mem_univ _), Finset.card_univ, ofReal_ofNat,
ofReal_coe_nnreal, coe_ofNat]
_ = convexBodyLT'Factor K * (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (f x.val))
* (∏ x : {w // IsComplex w}, ENNReal.ofReal (f x.val) ^ 2) := by
rw [show (4 : ℝ≥0∞) = (2 : ℝ≥0) ^ 2 by norm_num, convexBodyLT'Factor, pow_add,
← Finset.prod_erase_mul _ _ (Finset.mem_univ w₀), ofReal_coe_nnreal]
simp_rw [coe_mul, ENNReal.coe_pow]
ring
_ = convexBodyLT'Factor K * ∏ w, (f w) ^ (mult w) := by
simp_rw [mult, pow_ite, pow_one, Finset.prod_ite, ofReal_coe_nnreal, not_isReal_iff_isComplex,
coe_mul, coe_finset_prod, ENNReal.coe_pow, mul_assoc]
congr 3
· refine (Finset.prod_subtype (Finset.univ.filter _) ?_ (fun w => (f w : ℝ≥0∞))).symm
exact fun _ => by simp only [Finset.mem_univ, forall_true_left, Finset.mem_filter, true_and]
· refine (Finset.prod_subtype (Finset.univ.filter _) ?_ (fun w => (f w : ℝ≥0∞) ^ 2)).symm
exact fun _ => by simp only [Finset.mem_univ, forall_true_left, Finset.mem_filter, true_and]
end convexBodyLT'
section convexBodySum
open ENNReal MeasureTheory Fintype
open scoped Real Classical NNReal
variable [NumberField K] (B : ℝ)
variable {K}
/-- The function that sends `x : ({w // IsReal w} → ℝ) × ({w // IsComplex w} → ℂ)` to
`∑ w, ‖x.1 w‖ + 2 * ∑ w, ‖x.2 w‖`. It defines a norm and it used to define `convexBodySum`. -/
noncomputable abbrev convexBodySumFun (x : E K) : ℝ := ∑ w, mult w * normAtPlace w x
theorem convexBodySumFun_apply (x : E K) :
convexBodySumFun x = ∑ w, mult w * normAtPlace w x := rfl
theorem convexBodySumFun_apply' (x : E K) :
convexBodySumFun x = ∑ w, ‖x.1 w‖ + 2 * ∑ w, ‖x.2 w‖ := by
simp_rw [convexBodySumFun_apply, ← Finset.sum_add_sum_compl {w | IsReal w}.toFinset,
Set.toFinset_setOf, Finset.compl_filter, not_isReal_iff_isComplex, ← Finset.subtype_univ,
← Finset.univ.sum_subtype_eq_sum_filter, Finset.mul_sum]
congr
· ext w
rw [mult, if_pos w.prop, normAtPlace_apply_isReal, Nat.cast_one, one_mul]
· ext w
rw [mult, if_neg (not_isReal_iff_isComplex.mpr w.prop), normAtPlace_apply_isComplex,
Nat.cast_ofNat]
theorem convexBodySumFun_nonneg (x : E K) :
0 ≤ convexBodySumFun x :=
Finset.sum_nonneg (fun _ _ => mul_nonneg (Nat.cast_pos.mpr mult_pos).le (normAtPlace_nonneg _ _))
theorem convexBodySumFun_neg (x : E K) :
convexBodySumFun (- x) = convexBodySumFun x := by
simp_rw [convexBodySumFun, normAtPlace_neg]
theorem convexBodySumFun_add_le (x y : E K) :
convexBodySumFun (x + y) ≤ convexBodySumFun x + convexBodySumFun y := by
simp_rw [convexBodySumFun, ← Finset.sum_add_distrib, ← mul_add]
exact Finset.sum_le_sum
fun _ _ ↦ mul_le_mul_of_nonneg_left (normAtPlace_add_le _ x y) (Nat.cast_pos.mpr mult_pos).le
theorem convexBodySumFun_smul (c : ℝ) (x : E K) :
convexBodySumFun (c • x) = |c| * convexBodySumFun x := by
simp_rw [convexBodySumFun, normAtPlace_smul, ← mul_assoc, mul_comm, Finset.mul_sum, mul_assoc]
| Mathlib/NumberTheory/NumberField/CanonicalEmbedding/ConvexBody.lean | 316 | 324 | theorem convexBodySumFun_eq_zero_iff (x : E K) :
convexBodySumFun x = 0 ↔ x = 0 := by |
rw [← normAtPlace_eq_zero, convexBodySumFun, Finset.sum_eq_zero_iff_of_nonneg fun _ _ =>
mul_nonneg (Nat.cast_pos.mpr mult_pos).le (normAtPlace_nonneg _ _)]
conv =>
enter [1, w, hw]
rw [mul_left_mem_nonZeroDivisors_eq_zero_iff
(mem_nonZeroDivisors_iff_ne_zero.mpr <| Nat.cast_ne_zero.mpr mult_ne_zero)]
simp_rw [Finset.mem_univ, true_implies]
|
/-
Copyright (c) 2020 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.LinearAlgebra.Isomorphisms
import Mathlib.Algebra.Category.ModuleCat.Kernels
import Mathlib.Algebra.Category.ModuleCat.Limits
import Mathlib.CategoryTheory.Abelian.Exact
#align_import algebra.category.Module.abelian from "leanprover-community/mathlib"@"09f981f72d43749f1fa072deade828d9c1e185bb"
/-!
# The category of left R-modules is abelian.
Additionally, two linear maps are exact in the categorical sense iff `range f = ker g`.
-/
open CategoryTheory
open CategoryTheory.Limits
noncomputable section
universe w v u
namespace ModuleCat
variable {R : Type u} [Ring R] {M N : ModuleCat.{v} R} (f : M ⟶ N)
/-- In the category of modules, every monomorphism is normal. -/
def normalMono (hf : Mono f) : NormalMono f where
Z := of R (N ⧸ LinearMap.range f)
g := f.range.mkQ
w := LinearMap.range_mkQ_comp _
isLimit :=
/- The following [invalid Lean code](https://github.com/leanprover-community/lean/issues/341)
might help you understand what's going on here:
```
calc
M ≃ₗ[R] f.ker.quotient : (submodule.quot_equiv_of_eq_bot _ (ker_eq_bot_of_mono _)).symm
... ≃ₗ[R] f.range : linear_map.quot_ker_equiv_range f
... ≃ₗ[R] r.range.mkq.ker : linear_equiv.of_eq _ _ (submodule.ker_mkq _).symm
```
-/
IsKernel.isoKernel _ _ (kernelIsLimit _)
(LinearEquiv.toModuleIso'
((Submodule.quotEquivOfEqBot _ (ker_eq_bot_of_mono _)).symm ≪≫ₗ
(LinearMap.quotKerEquivRange f ≪≫ₗ
LinearEquiv.ofEq _ _ (Submodule.ker_mkQ _).symm))) <| by ext; rfl
set_option linter.uppercaseLean3 false in
#align Module.normal_mono ModuleCat.normalMono
/-- In the category of modules, every epimorphism is normal. -/
def normalEpi (hf : Epi f) : NormalEpi f where
W := of R (LinearMap.ker f)
g := (LinearMap.ker f).subtype
w := LinearMap.comp_ker_subtype _
isColimit :=
/- The following invalid Lean code might help you understand what's going on here:
```
calc f.ker.subtype.range.quotient
≃ₗ[R] f.ker.quotient : submodule.quot_equiv_of_eq _ _ (submodule.range_subtype _)
... ≃ₗ[R] f.range : linear_map.quot_ker_equiv_range f
... ≃ₗ[R] N : linear_equiv.of_top _ (range_eq_top_of_epi _)
```
-/
IsCokernel.cokernelIso _ _ (cokernelIsColimit _)
(LinearEquiv.toModuleIso'
(Submodule.quotEquivOfEq _ _ (Submodule.range_subtype _) ≪≫ₗ
LinearMap.quotKerEquivRange f ≪≫ₗ
LinearEquiv.ofTop _ (range_eq_top_of_epi _))) <| by ext; rfl
set_option linter.uppercaseLean3 false in
#align Module.normal_epi ModuleCat.normalEpi
/-- The category of R-modules is abelian. -/
instance abelian : Abelian (ModuleCat.{v} R) where
has_cokernels := hasCokernels_moduleCat
normalMonoOfMono := normalMono
normalEpiOfEpi := normalEpi
set_option linter.uppercaseLean3 false in
#align Module.abelian ModuleCat.abelian
section ReflectsLimits
-- Porting note: added to make the following definitions work
instance : HasLimitsOfSize.{v,v} (ModuleCatMax.{v, w} R) :=
ModuleCat.hasLimitsOfSize.{v, max v w, _, v}
/- We need to put this in this weird spot because we need to know that the category of modules
is balanced. -/
instance forgetReflectsLimitsOfSize :
ReflectsLimitsOfSize.{v, v} (forget (ModuleCatMax.{v, w} R)) :=
reflectsLimitsOfReflectsIsomorphisms
set_option linter.uppercaseLean3 false in
#align Module.forget_reflects_limits_of_size ModuleCat.forgetReflectsLimitsOfSize
instance forget₂ReflectsLimitsOfSize :
ReflectsLimitsOfSize.{v, v} (forget₂ (ModuleCatMax.{v, w} R) AddCommGroupCat.{max v w}) :=
reflectsLimitsOfReflectsIsomorphisms
set_option linter.uppercaseLean3 false in
#align Module.forget₂_reflects_limits_of_size ModuleCat.forget₂ReflectsLimitsOfSize
instance forgetReflectsLimits : ReflectsLimits (forget (ModuleCat.{v} R)) :=
ModuleCat.forgetReflectsLimitsOfSize.{v, v}
set_option linter.uppercaseLean3 false in
#align Module.forget_reflects_limits ModuleCat.forgetReflectsLimits
instance forget₂ReflectsLimits : ReflectsLimits (forget₂ (ModuleCat.{v} R) AddCommGroupCat.{v}) :=
ModuleCat.forget₂ReflectsLimitsOfSize.{v, v}
set_option linter.uppercaseLean3 false in
#align Module.forget₂_reflects_limits ModuleCat.forget₂ReflectsLimits
end ReflectsLimits
variable {O : ModuleCat.{v} R} (g : N ⟶ O)
open LinearMap
attribute [local instance] Preadditive.hasEqualizers_of_hasKernels
| Mathlib/Algebra/Category/ModuleCat/Abelian.lean | 123 | 127 | theorem exact_iff : Exact f g ↔ LinearMap.range f = LinearMap.ker g := by |
rw [abelian.exact_iff' f g (kernelIsLimit _) (cokernelIsColimit _)]
exact
⟨fun h => le_antisymm (range_le_ker_iff.2 h.1) (ker_le_range_iff.2 h.2), fun h =>
⟨range_le_ker_iff.1 <| le_of_eq h, ker_le_range_iff.1 <| le_of_eq h.symm⟩⟩
|
/-
Copyright (c) 2014 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Ring.Cast
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.PSub
import Mathlib.Data.Nat.Size
import Mathlib.Data.Num.Bitwise
#align_import data.num.lemmas from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Properties of the binary representation of integers
-/
/-
Porting note:
`bit0` and `bit1` are deprecated because it is mainly used to represent number literal in Lean3 but
not in Lean4 anymore. However, this file uses them for encoding numbers so this linter is
unnecessary.
-/
set_option linter.deprecated false
-- Porting note: Required for the notation `-[n+1]`.
open Int Function
attribute [local simp] add_assoc
namespace PosNum
variable {α : Type*}
@[simp, norm_cast]
theorem cast_one [One α] [Add α] : ((1 : PosNum) : α) = 1 :=
rfl
#align pos_num.cast_one PosNum.cast_one
@[simp]
theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 :=
rfl
#align pos_num.cast_one' PosNum.cast_one'
@[simp, norm_cast]
theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = _root_.bit0 (n : α) :=
rfl
#align pos_num.cast_bit0 PosNum.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = _root_.bit1 (n : α) :=
rfl
#align pos_num.cast_bit1 PosNum.cast_bit1
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n
| 1 => Nat.cast_one
| bit0 p => (Nat.cast_bit0 _).trans <| congr_arg _root_.bit0 p.cast_to_nat
| bit1 p => (Nat.cast_bit1 _).trans <| congr_arg _root_.bit1 p.cast_to_nat
#align pos_num.cast_to_nat PosNum.cast_to_nat
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
#align pos_num.to_nat_to_int PosNum.to_nat_to_int
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] (n : PosNum) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
#align pos_num.cast_to_int PosNum.cast_to_int
theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1
| 1 => rfl
| bit0 p => rfl
| bit1 p =>
(congr_arg _root_.bit0 (succ_to_nat p)).trans <|
show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm]
#align pos_num.succ_to_nat PosNum.succ_to_nat
theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl
#align pos_num.one_add PosNum.one_add
theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl
#align pos_num.add_one PosNum.add_one
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : PosNum) : ℕ) = m + n
| 1, b => by rw [one_add b, succ_to_nat, add_comm, cast_one]
| a, 1 => by rw [add_one a, succ_to_nat, cast_one]
| bit0 a, bit0 b => (congr_arg _root_.bit0 (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _
| bit0 a, bit1 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + (b + b + 1) by simp [add_left_comm]
| bit1 a, bit0 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + 1 + (b + b) by simp [add_comm, add_left_comm]
| bit1 a, bit1 b =>
show (succ (a + b) + succ (a + b) : ℕ) = a + a + 1 + (b + b + 1) by
rw [succ_to_nat, add_to_nat a b]; simp [add_left_comm]
#align pos_num.add_to_nat PosNum.add_to_nat
theorem add_succ : ∀ m n : PosNum, m + succ n = succ (m + n)
| 1, b => by simp [one_add]
| bit0 a, 1 => congr_arg bit0 (add_one a)
| bit1 a, 1 => congr_arg bit1 (add_one a)
| bit0 a, bit0 b => rfl
| bit0 a, bit1 b => congr_arg bit0 (add_succ a b)
| bit1 a, bit0 b => rfl
| bit1 a, bit1 b => congr_arg bit1 (add_succ a b)
#align pos_num.add_succ PosNum.add_succ
theorem bit0_of_bit0 : ∀ n, _root_.bit0 n = bit0 n
| 1 => rfl
| bit0 p => congr_arg bit0 (bit0_of_bit0 p)
| bit1 p => show bit0 (succ (_root_.bit0 p)) = _ by rw [bit0_of_bit0 p, succ]
#align pos_num.bit0_of_bit0 PosNum.bit0_of_bit0
theorem bit1_of_bit1 (n : PosNum) : _root_.bit1 n = bit1 n :=
show _root_.bit0 n + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ]
#align pos_num.bit1_of_bit1 PosNum.bit1_of_bit1
@[norm_cast]
theorem mul_to_nat (m) : ∀ n, ((m * n : PosNum) : ℕ) = m * n
| 1 => (mul_one _).symm
| bit0 p => show (↑(m * p) + ↑(m * p) : ℕ) = ↑m * (p + p) by rw [mul_to_nat m p, left_distrib]
| bit1 p =>
(add_to_nat (bit0 (m * p)) m).trans <|
show (↑(m * p) + ↑(m * p) + ↑m : ℕ) = ↑m * (p + p) + m by rw [mul_to_nat m p, left_distrib]
#align pos_num.mul_to_nat PosNum.mul_to_nat
theorem to_nat_pos : ∀ n : PosNum, 0 < (n : ℕ)
| 1 => Nat.zero_lt_one
| bit0 p =>
let h := to_nat_pos p
add_pos h h
| bit1 _p => Nat.succ_pos _
#align pos_num.to_nat_pos PosNum.to_nat_pos
theorem cmp_to_nat_lemma {m n : PosNum} : (m : ℕ) < n → (bit1 m : ℕ) < bit0 n :=
show (m : ℕ) < n → (m + m + 1 + 1 : ℕ) ≤ n + n by
intro h; rw [Nat.add_right_comm m m 1, add_assoc]; exact Nat.add_le_add h h
#align pos_num.cmp_to_nat_lemma PosNum.cmp_to_nat_lemma
theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by
induction' m with m IH m IH <;> intro n <;> cases' n with n n <;> unfold cmp <;>
try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl
#align pos_num.cmp_swap PosNum.cmp_swap
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 1, 1 => rfl
| bit0 a, 1 =>
let h : (1 : ℕ) ≤ a := to_nat_pos a
Nat.add_le_add h h
| bit1 a, 1 => Nat.succ_lt_succ <| to_nat_pos <| bit0 a
| 1, bit0 b =>
let h : (1 : ℕ) ≤ b := to_nat_pos b
Nat.add_le_add h h
| 1, bit1 b => Nat.succ_lt_succ <| to_nat_pos <| bit0 b
| bit0 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.add_lt_add this this
· rw [this]
· exact Nat.add_lt_add this this
| bit0 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
· rw [this]
apply Nat.lt_succ_self
· exact cmp_to_nat_lemma this
| bit1 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact cmp_to_nat_lemma this
· rw [this]
apply Nat.lt_succ_self
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
| bit1 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
· rw [this]
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
#align pos_num.cmp_to_nat PosNum.cmp_to_nat
@[norm_cast]
theorem lt_to_nat {m n : PosNum} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
#align pos_num.lt_to_nat PosNum.lt_to_nat
@[norm_cast]
theorem le_to_nat {m n : PosNum} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
#align pos_num.le_to_nat PosNum.le_to_nat
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem add_zero (n : Num) : n + 0 = n := by cases n <;> rfl
#align num.add_zero Num.add_zero
theorem zero_add (n : Num) : 0 + n = n := by cases n <;> rfl
#align num.zero_add Num.zero_add
theorem add_one : ∀ n : Num, n + 1 = succ n
| 0 => rfl
| pos p => by cases p <;> rfl
#align num.add_one Num.add_one
theorem add_succ : ∀ m n : Num, m + succ n = succ (m + n)
| 0, n => by simp [zero_add]
| pos p, 0 => show pos (p + 1) = succ (pos p + 0) by rw [PosNum.add_one, add_zero, succ, succ']
| pos p, pos q => congr_arg pos (PosNum.add_succ _ _)
#align num.add_succ Num.add_succ
theorem bit0_of_bit0 : ∀ n : Num, bit0 n = n.bit0
| 0 => rfl
| pos p => congr_arg pos p.bit0_of_bit0
#align num.bit0_of_bit0 Num.bit0_of_bit0
theorem bit1_of_bit1 : ∀ n : Num, bit1 n = n.bit1
| 0 => rfl
| pos p => congr_arg pos p.bit1_of_bit1
#align num.bit1_of_bit1 Num.bit1_of_bit1
@[simp]
theorem ofNat'_zero : Num.ofNat' 0 = 0 := by simp [Num.ofNat']
#align num.of_nat'_zero Num.ofNat'_zero
theorem ofNat'_bit (b n) : ofNat' (Nat.bit b n) = cond b Num.bit1 Num.bit0 (ofNat' n) :=
Nat.binaryRec_eq rfl _ _
#align num.of_nat'_bit Num.ofNat'_bit
@[simp]
| Mathlib/Data/Num/Lemmas.lean | 246 | 246 | theorem ofNat'_one : Num.ofNat' 1 = 1 := by | erw [ofNat'_bit true 0, cond, ofNat'_zero]; rfl
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Johan Commelin, Mario Carneiro
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.MvPolynomial.Rename
import Mathlib.Algebra.MvPolynomial.Degrees
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Data.Finsupp.Fin
import Mathlib.Logic.Equiv.Fin
#align_import data.mv_polynomial.equiv from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Equivalences between polynomial rings
This file establishes a number of equivalences between polynomial rings,
based on equivalences between the underlying types.
## Notation
As in other polynomial files, we typically use the notation:
+ `σ : Type*` (indexing the variables)
+ `R : Type*` `[CommSemiring R]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `a : R`
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ R`
## Tags
equivalence, isomorphism, morphism, ring hom, hom
-/
noncomputable section
open Polynomial Set Function Finsupp AddMonoidAlgebra
universe u v w x
variable {R : Type u} {S₁ : Type v} {S₂ : Type w} {S₃ : Type x}
namespace MvPolynomial
variable {σ : Type*} {a a' a₁ a₂ : R} {e : ℕ} {s : σ →₀ ℕ}
section Equiv
variable (R) [CommSemiring R]
/-- The ring isomorphism between multivariable polynomials in a single variable and
polynomials over the ground ring.
-/
@[simps]
def pUnitAlgEquiv : MvPolynomial PUnit R ≃ₐ[R] R[X] where
toFun := eval₂ Polynomial.C fun _ => Polynomial.X
invFun := Polynomial.eval₂ MvPolynomial.C (X PUnit.unit)
left_inv := by
let f : R[X] →+* MvPolynomial PUnit R := Polynomial.eval₂RingHom MvPolynomial.C (X PUnit.unit)
let g : MvPolynomial PUnit R →+* R[X] := eval₂Hom Polynomial.C fun _ => Polynomial.X
show ∀ p, f.comp g p = p
apply is_id
· ext a
dsimp [f, g]
rw [eval₂_C, Polynomial.eval₂_C]
· rintro ⟨⟩
dsimp [f, g]
rw [eval₂_X, Polynomial.eval₂_X]
right_inv p :=
Polynomial.induction_on p (fun a => by rw [Polynomial.eval₂_C, MvPolynomial.eval₂_C])
(fun p q hp hq => by rw [Polynomial.eval₂_add, MvPolynomial.eval₂_add, hp, hq]) fun p n _ => by
rw [Polynomial.eval₂_mul, Polynomial.eval₂_pow, Polynomial.eval₂_X, Polynomial.eval₂_C,
eval₂_mul, eval₂_C, eval₂_pow, eval₂_X]
map_mul' _ _ := eval₂_mul _ _
map_add' _ _ := eval₂_add _ _
commutes' _ := eval₂_C _ _ _
#align mv_polynomial.punit_alg_equiv MvPolynomial.pUnitAlgEquiv
section Map
variable {R} (σ)
/-- If `e : A ≃+* B` is an isomorphism of rings, then so is `map e`. -/
@[simps apply]
def mapEquiv [CommSemiring S₁] [CommSemiring S₂] (e : S₁ ≃+* S₂) :
MvPolynomial σ S₁ ≃+* MvPolynomial σ S₂ :=
{ map (e : S₁ →+* S₂) with
toFun := map (e : S₁ →+* S₂)
invFun := map (e.symm : S₂ →+* S₁)
left_inv := map_leftInverse e.left_inv
right_inv := map_rightInverse e.right_inv }
#align mv_polynomial.map_equiv MvPolynomial.mapEquiv
@[simp]
theorem mapEquiv_refl : mapEquiv σ (RingEquiv.refl R) = RingEquiv.refl _ :=
RingEquiv.ext map_id
#align mv_polynomial.map_equiv_refl MvPolynomial.mapEquiv_refl
@[simp]
theorem mapEquiv_symm [CommSemiring S₁] [CommSemiring S₂] (e : S₁ ≃+* S₂) :
(mapEquiv σ e).symm = mapEquiv σ e.symm :=
rfl
#align mv_polynomial.map_equiv_symm MvPolynomial.mapEquiv_symm
@[simp]
theorem mapEquiv_trans [CommSemiring S₁] [CommSemiring S₂] [CommSemiring S₃] (e : S₁ ≃+* S₂)
(f : S₂ ≃+* S₃) : (mapEquiv σ e).trans (mapEquiv σ f) = mapEquiv σ (e.trans f) :=
RingEquiv.ext fun p => by
simp only [RingEquiv.coe_trans, comp_apply, mapEquiv_apply, RingEquiv.coe_ringHom_trans,
map_map]
#align mv_polynomial.map_equiv_trans MvPolynomial.mapEquiv_trans
variable {A₁ A₂ A₃ : Type*} [CommSemiring A₁] [CommSemiring A₂] [CommSemiring A₃]
variable [Algebra R A₁] [Algebra R A₂] [Algebra R A₃]
/-- If `e : A ≃ₐ[R] B` is an isomorphism of `R`-algebras, then so is `map e`. -/
@[simps apply]
def mapAlgEquiv (e : A₁ ≃ₐ[R] A₂) : MvPolynomial σ A₁ ≃ₐ[R] MvPolynomial σ A₂ :=
{ mapAlgHom (e : A₁ →ₐ[R] A₂), mapEquiv σ (e : A₁ ≃+* A₂) with toFun := map (e : A₁ →+* A₂) }
#align mv_polynomial.map_alg_equiv MvPolynomial.mapAlgEquiv
@[simp]
theorem mapAlgEquiv_refl : mapAlgEquiv σ (AlgEquiv.refl : A₁ ≃ₐ[R] A₁) = AlgEquiv.refl :=
AlgEquiv.ext map_id
#align mv_polynomial.map_alg_equiv_refl MvPolynomial.mapAlgEquiv_refl
@[simp]
theorem mapAlgEquiv_symm (e : A₁ ≃ₐ[R] A₂) : (mapAlgEquiv σ e).symm = mapAlgEquiv σ e.symm :=
rfl
#align mv_polynomial.map_alg_equiv_symm MvPolynomial.mapAlgEquiv_symm
@[simp]
theorem mapAlgEquiv_trans (e : A₁ ≃ₐ[R] A₂) (f : A₂ ≃ₐ[R] A₃) :
(mapAlgEquiv σ e).trans (mapAlgEquiv σ f) = mapAlgEquiv σ (e.trans f) := by
ext
simp only [AlgEquiv.trans_apply, mapAlgEquiv_apply, map_map]
rfl
#align mv_polynomial.map_alg_equiv_trans MvPolynomial.mapAlgEquiv_trans
end Map
section
variable (S₁ S₂ S₃)
/-- The function from multivariable polynomials in a sum of two types,
to multivariable polynomials in one of the types,
with coefficients in multivariable polynomials in the other type.
See `sumRingEquiv` for the ring isomorphism.
-/
def sumToIter : MvPolynomial (Sum S₁ S₂) R →+* MvPolynomial S₁ (MvPolynomial S₂ R) :=
eval₂Hom (C.comp C) fun bc => Sum.recOn bc X (C ∘ X)
#align mv_polynomial.sum_to_iter MvPolynomial.sumToIter
@[simp]
theorem sumToIter_C (a : R) : sumToIter R S₁ S₂ (C a) = C (C a) :=
eval₂_C _ _ a
set_option linter.uppercaseLean3 false in
#align mv_polynomial.sum_to_iter_C MvPolynomial.sumToIter_C
@[simp]
theorem sumToIter_Xl (b : S₁) : sumToIter R S₁ S₂ (X (Sum.inl b)) = X b :=
eval₂_X _ _ (Sum.inl b)
set_option linter.uppercaseLean3 false in
#align mv_polynomial.sum_to_iter_Xl MvPolynomial.sumToIter_Xl
@[simp]
theorem sumToIter_Xr (c : S₂) : sumToIter R S₁ S₂ (X (Sum.inr c)) = C (X c) :=
eval₂_X _ _ (Sum.inr c)
set_option linter.uppercaseLean3 false in
#align mv_polynomial.sum_to_iter_Xr MvPolynomial.sumToIter_Xr
/-- The function from multivariable polynomials in one type,
with coefficients in multivariable polynomials in another type,
to multivariable polynomials in the sum of the two types.
See `sumRingEquiv` for the ring isomorphism.
-/
def iterToSum : MvPolynomial S₁ (MvPolynomial S₂ R) →+* MvPolynomial (Sum S₁ S₂) R :=
eval₂Hom (eval₂Hom C (X ∘ Sum.inr)) (X ∘ Sum.inl)
#align mv_polynomial.iter_to_sum MvPolynomial.iterToSum
@[simp]
theorem iterToSum_C_C (a : R) : iterToSum R S₁ S₂ (C (C a)) = C a :=
Eq.trans (eval₂_C _ _ (C a)) (eval₂_C _ _ _)
set_option linter.uppercaseLean3 false in
#align mv_polynomial.iter_to_sum_C_C MvPolynomial.iterToSum_C_C
@[simp]
theorem iterToSum_X (b : S₁) : iterToSum R S₁ S₂ (X b) = X (Sum.inl b) :=
eval₂_X _ _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.iter_to_sum_X MvPolynomial.iterToSum_X
@[simp]
theorem iterToSum_C_X (c : S₂) : iterToSum R S₁ S₂ (C (X c)) = X (Sum.inr c) :=
Eq.trans (eval₂_C _ _ (X c)) (eval₂_X _ _ _)
set_option linter.uppercaseLean3 false in
#align mv_polynomial.iter_to_sum_C_X MvPolynomial.iterToSum_C_X
variable (σ)
/-- The algebra isomorphism between multivariable polynomials in no variables
and the ground ring. -/
@[simps!]
def isEmptyAlgEquiv [he : IsEmpty σ] : MvPolynomial σ R ≃ₐ[R] R :=
AlgEquiv.ofAlgHom (aeval (IsEmpty.elim he)) (Algebra.ofId _ _)
(by ext)
(by
ext i m
exact IsEmpty.elim' he i)
#align mv_polynomial.is_empty_alg_equiv MvPolynomial.isEmptyAlgEquiv
/-- The ring isomorphism between multivariable polynomials in no variables
and the ground ring. -/
@[simps!]
def isEmptyRingEquiv [IsEmpty σ] : MvPolynomial σ R ≃+* R :=
(isEmptyAlgEquiv R σ).toRingEquiv
#align mv_polynomial.is_empty_ring_equiv MvPolynomial.isEmptyRingEquiv
variable {σ}
/-- A helper function for `sumRingEquiv`. -/
@[simps]
def mvPolynomialEquivMvPolynomial [CommSemiring S₃] (f : MvPolynomial S₁ R →+* MvPolynomial S₂ S₃)
(g : MvPolynomial S₂ S₃ →+* MvPolynomial S₁ R) (hfgC : (f.comp g).comp C = C)
(hfgX : ∀ n, f (g (X n)) = X n) (hgfC : (g.comp f).comp C = C) (hgfX : ∀ n, g (f (X n)) = X n) :
MvPolynomial S₁ R ≃+* MvPolynomial S₂ S₃ where
toFun := f
invFun := g
left_inv := is_id (RingHom.comp _ _) hgfC hgfX
right_inv := is_id (RingHom.comp _ _) hfgC hfgX
map_mul' := f.map_mul
map_add' := f.map_add
#align mv_polynomial.mv_polynomial_equiv_mv_polynomial MvPolynomial.mvPolynomialEquivMvPolynomial
/-- The ring isomorphism between multivariable polynomials in a sum of two types,
and multivariable polynomials in one of the types,
with coefficients in multivariable polynomials in the other type.
-/
def sumRingEquiv : MvPolynomial (Sum S₁ S₂) R ≃+* MvPolynomial S₁ (MvPolynomial S₂ R) := by
apply mvPolynomialEquivMvPolynomial R (Sum S₁ S₂) _ _ (sumToIter R S₁ S₂) (iterToSum R S₁ S₂)
· refine RingHom.ext (hom_eq_hom _ _ ?hC ?hX)
case hC => ext1; simp only [RingHom.comp_apply, iterToSum_C_C, sumToIter_C]
case hX => intro; simp only [RingHom.comp_apply, iterToSum_C_X, sumToIter_Xr]
· simp [iterToSum_X, sumToIter_Xl]
· ext1; simp only [RingHom.comp_apply, sumToIter_C, iterToSum_C_C]
· rintro ⟨⟩ <;> simp only [sumToIter_Xl, iterToSum_X, sumToIter_Xr, iterToSum_C_X]
#align mv_polynomial.sum_ring_equiv MvPolynomial.sumRingEquiv
/-- The algebra isomorphism between multivariable polynomials in a sum of two types,
and multivariable polynomials in one of the types,
with coefficients in multivariable polynomials in the other type.
-/
@[simps!]
def sumAlgEquiv : MvPolynomial (Sum S₁ S₂) R ≃ₐ[R] MvPolynomial S₁ (MvPolynomial S₂ R) :=
{ sumRingEquiv R S₁ S₂ with
commutes' := by
intro r
have A : algebraMap R (MvPolynomial S₁ (MvPolynomial S₂ R)) r = (C (C r) : _) := rfl
have B : algebraMap R (MvPolynomial (Sum S₁ S₂) R) r = C r := rfl
simp only [sumRingEquiv, mvPolynomialEquivMvPolynomial, Equiv.toFun_as_coe,
Equiv.coe_fn_mk, B, sumToIter_C, A] }
#align mv_polynomial.sum_alg_equiv MvPolynomial.sumAlgEquiv
section
-- this speeds up typeclass search in the lemma below
attribute [local instance] IsScalarTower.right
/-- The algebra isomorphism between multivariable polynomials in `Option S₁` and
polynomials with coefficients in `MvPolynomial S₁ R`.
-/
@[simps!]
def optionEquivLeft : MvPolynomial (Option S₁) R ≃ₐ[R] Polynomial (MvPolynomial S₁ R) :=
AlgEquiv.ofAlgHom (MvPolynomial.aeval fun o => o.elim Polynomial.X fun s => Polynomial.C (X s))
(Polynomial.aevalTower (MvPolynomial.rename some) (X none))
(by ext : 2 <;> simp) (by ext i : 2; cases i <;> simp)
#align mv_polynomial.option_equiv_left MvPolynomial.optionEquivLeft
lemma optionEquivLeft_X_some (x : S₁) : optionEquivLeft R S₁ (X (some x)) = Polynomial.C (X x) := by
simp only [optionEquivLeft_apply, aeval_X]
lemma optionEquivLeft_X_none : optionEquivLeft R S₁ (X none) = Polynomial.X := by
simp only [optionEquivLeft_apply, aeval_X]
lemma optionEquivLeft_C (r : R) : optionEquivLeft R S₁ (C r) = Polynomial.C (C r) := by
simp only [optionEquivLeft_apply, aeval_C, Polynomial.algebraMap_apply, algebraMap_eq]
end
/-- The algebra isomorphism between multivariable polynomials in `Option S₁` and
multivariable polynomials with coefficients in polynomials.
-/
@[simps!]
def optionEquivRight : MvPolynomial (Option S₁) R ≃ₐ[R] MvPolynomial S₁ R[X] :=
AlgEquiv.ofAlgHom (MvPolynomial.aeval fun o => o.elim (C Polynomial.X) X)
(MvPolynomial.aevalTower (Polynomial.aeval (X none)) fun i => X (Option.some i))
(by
ext : 2 <;>
simp only [MvPolynomial.algebraMap_eq, Option.elim, AlgHom.coe_comp, AlgHom.id_comp,
IsScalarTower.coe_toAlgHom', comp_apply, aevalTower_C, Polynomial.aeval_X, aeval_X,
Option.elim', aevalTower_X, AlgHom.coe_id, id, eq_self_iff_true, imp_true_iff])
(by
ext ⟨i⟩ : 2 <;>
simp only [Option.elim, AlgHom.coe_comp, comp_apply, aeval_X, aevalTower_C,
Polynomial.aeval_X, AlgHom.coe_id, id, aevalTower_X])
#align mv_polynomial.option_equiv_right MvPolynomial.optionEquivRight
lemma optionEquivRight_X_some (x : S₁) : optionEquivRight R S₁ (X (some x)) = X x := by
simp only [optionEquivRight_apply, aeval_X]
lemma optionEquivRight_X_none : optionEquivRight R S₁ (X none) = C Polynomial.X := by
simp only [optionEquivRight_apply, aeval_X]
lemma optionEquivRight_C (r : R) : optionEquivRight R S₁ (C r) = C (Polynomial.C r) := by
simp only [optionEquivRight_apply, aeval_C, algebraMap_apply, Polynomial.algebraMap_eq]
variable (n : ℕ)
/-- The algebra isomorphism between multivariable polynomials in `Fin (n + 1)` and
polynomials over multivariable polynomials in `Fin n`.
-/
def finSuccEquiv : MvPolynomial (Fin (n + 1)) R ≃ₐ[R] Polynomial (MvPolynomial (Fin n) R) :=
(renameEquiv R (_root_.finSuccEquiv n)).trans (optionEquivLeft R (Fin n))
#align mv_polynomial.fin_succ_equiv MvPolynomial.finSuccEquiv
theorem finSuccEquiv_eq :
(finSuccEquiv R n : MvPolynomial (Fin (n + 1)) R →+* Polynomial (MvPolynomial (Fin n) R)) =
eval₂Hom (Polynomial.C.comp (C : R →+* MvPolynomial (Fin n) R)) fun i : Fin (n + 1) =>
Fin.cases Polynomial.X (fun k => Polynomial.C (X k)) i := by
ext i : 2
· simp only [finSuccEquiv, optionEquivLeft_apply, aeval_C, AlgEquiv.coe_trans, RingHom.coe_coe,
coe_eval₂Hom, comp_apply, renameEquiv_apply, eval₂_C, RingHom.coe_comp, rename_C]
rfl
· refine Fin.cases ?_ ?_ i <;> simp [finSuccEquiv]
#align mv_polynomial.fin_succ_equiv_eq MvPolynomial.finSuccEquiv_eq
@[simp]
theorem finSuccEquiv_apply (p : MvPolynomial (Fin (n + 1)) R) :
finSuccEquiv R n p =
eval₂Hom (Polynomial.C.comp (C : R →+* MvPolynomial (Fin n) R))
(fun i : Fin (n + 1) => Fin.cases Polynomial.X (fun k => Polynomial.C (X k)) i) p := by
rw [← finSuccEquiv_eq, RingHom.coe_coe]
#align mv_polynomial.fin_succ_equiv_apply MvPolynomial.finSuccEquiv_apply
theorem finSuccEquiv_comp_C_eq_C {R : Type u} [CommSemiring R] (n : ℕ) :
(↑(MvPolynomial.finSuccEquiv R n).symm : Polynomial (MvPolynomial (Fin n) R) →+* _).comp
(Polynomial.C.comp MvPolynomial.C) =
(MvPolynomial.C : R →+* MvPolynomial (Fin n.succ) R) := by
refine RingHom.ext fun x => ?_
rw [RingHom.comp_apply]
refine
(MvPolynomial.finSuccEquiv R n).injective
(Trans.trans ((MvPolynomial.finSuccEquiv R n).apply_symm_apply _) ?_)
simp only [MvPolynomial.finSuccEquiv_apply, MvPolynomial.eval₂Hom_C]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.fin_succ_equiv_comp_C_eq_C MvPolynomial.finSuccEquiv_comp_C_eq_C
variable {n} {R}
theorem finSuccEquiv_X_zero : finSuccEquiv R n (X 0) = Polynomial.X := by simp
set_option linter.uppercaseLean3 false in
#align mv_polynomial.fin_succ_equiv_X_zero MvPolynomial.finSuccEquiv_X_zero
| Mathlib/Algebra/MvPolynomial/Equiv.lean | 377 | 378 | theorem finSuccEquiv_X_succ {j : Fin n} : finSuccEquiv R n (X j.succ) = Polynomial.C (X j) := by |
simp
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Computability.Partrec
import Mathlib.Data.Option.Basic
#align_import computability.partrec_code from "leanprover-community/mathlib"@"6155d4351090a6fad236e3d2e4e0e4e7342668e8"
/-!
# Gödel Numbering for Partial Recursive Functions.
This file defines `Nat.Partrec.Code`, an inductive datatype describing code for partial
recursive functions on ℕ. It defines an encoding for these codes, and proves that the constructors
are primitive recursive with respect to the encoding.
It also defines the evaluation of these codes as partial functions using `PFun`, and proves that a
function is partially recursive (as defined by `Nat.Partrec`) if and only if it is the evaluation
of some code.
## Main Definitions
* `Nat.Partrec.Code`: Inductive datatype for partial recursive codes.
* `Nat.Partrec.Code.encodeCode`: A (computable) encoding of codes as natural numbers.
* `Nat.Partrec.Code.ofNatCode`: The inverse of this encoding.
* `Nat.Partrec.Code.eval`: The interpretation of a `Nat.Partrec.Code` as a partial function.
## Main Results
* `Nat.Partrec.Code.rec_prim`: Recursion on `Nat.Partrec.Code` is primitive recursive.
* `Nat.Partrec.Code.rec_computable`: Recursion on `Nat.Partrec.Code` is computable.
* `Nat.Partrec.Code.smn`: The $S_n^m$ theorem.
* `Nat.Partrec.Code.exists_code`: Partial recursiveness is equivalent to being the eval of a code.
* `Nat.Partrec.Code.evaln_prim`: `evaln` is primitive recursive.
* `Nat.Partrec.Code.fixed_point`: Roger's fixed point theorem.
## References
* [Mario Carneiro, *Formalizing computability theory via partial recursive functions*][carneiro2019]
-/
open Encodable Denumerable
namespace Nat.Partrec
theorem rfind' {f} (hf : Nat.Partrec f) :
Nat.Partrec
(Nat.unpaired fun a m =>
(Nat.rfind fun n => (fun m => m = 0) <$> f (Nat.pair a (n + m))).map (· + m)) :=
Partrec₂.unpaired'.2 <| by
refine
Partrec.map
((@Partrec₂.unpaired' fun a b : ℕ =>
Nat.rfind fun n => (fun m => m = 0) <$> f (Nat.pair a (n + b))).1
?_)
(Primrec.nat_add.comp Primrec.snd <| Primrec.snd.comp Primrec.fst).to_comp.to₂
have : Nat.Partrec (fun a => Nat.rfind (fun n => (fun m => decide (m = 0)) <$>
Nat.unpaired (fun a b => f (Nat.pair (Nat.unpair a).1 (b + (Nat.unpair a).2)))
(Nat.pair a n))) :=
rfind
(Partrec₂.unpaired'.2
((Partrec.nat_iff.2 hf).comp
(Primrec₂.pair.comp (Primrec.fst.comp <| Primrec.unpair.comp Primrec.fst)
(Primrec.nat_add.comp Primrec.snd
(Primrec.snd.comp <| Primrec.unpair.comp Primrec.fst))).to_comp))
simp at this; exact this
#align nat.partrec.rfind' Nat.Partrec.rfind'
/-- Code for partial recursive functions from ℕ to ℕ.
See `Nat.Partrec.Code.eval` for the interpretation of these constructors.
-/
inductive Code : Type
| zero : Code
| succ : Code
| left : Code
| right : Code
| pair : Code → Code → Code
| comp : Code → Code → Code
| prec : Code → Code → Code
| rfind' : Code → Code
#align nat.partrec.code Nat.Partrec.Code
-- Porting note: `Nat.Partrec.Code.recOn` is noncomputable in Lean4, so we make it computable.
compile_inductive% Code
end Nat.Partrec
namespace Nat.Partrec.Code
instance instInhabited : Inhabited Code :=
⟨zero⟩
#align nat.partrec.code.inhabited Nat.Partrec.Code.instInhabited
/-- Returns a code for the constant function outputting a particular natural. -/
protected def const : ℕ → Code
| 0 => zero
| n + 1 => comp succ (Code.const n)
#align nat.partrec.code.const Nat.Partrec.Code.const
theorem const_inj : ∀ {n₁ n₂}, Nat.Partrec.Code.const n₁ = Nat.Partrec.Code.const n₂ → n₁ = n₂
| 0, 0, _ => by simp
| n₁ + 1, n₂ + 1, h => by
dsimp [Nat.Partrec.Code.const] at h
injection h with h₁ h₂
simp only [const_inj h₂]
#align nat.partrec.code.const_inj Nat.Partrec.Code.const_inj
/-- A code for the identity function. -/
protected def id : Code :=
pair left right
#align nat.partrec.code.id Nat.Partrec.Code.id
/-- Given a code `c` taking a pair as input, returns a code using `n` as the first argument to `c`.
-/
def curry (c : Code) (n : ℕ) : Code :=
comp c (pair (Code.const n) Code.id)
#align nat.partrec.code.curry Nat.Partrec.Code.curry
-- Porting note: `bit0` and `bit1` are deprecated.
/-- An encoding of a `Nat.Partrec.Code` as a ℕ. -/
def encodeCode : Code → ℕ
| zero => 0
| succ => 1
| left => 2
| right => 3
| pair cf cg => 2 * (2 * Nat.pair (encodeCode cf) (encodeCode cg)) + 4
| comp cf cg => 2 * (2 * Nat.pair (encodeCode cf) (encodeCode cg) + 1) + 4
| prec cf cg => (2 * (2 * Nat.pair (encodeCode cf) (encodeCode cg)) + 1) + 4
| rfind' cf => (2 * (2 * encodeCode cf + 1) + 1) + 4
#align nat.partrec.code.encode_code Nat.Partrec.Code.encodeCode
/--
A decoder for `Nat.Partrec.Code.encodeCode`, taking any ℕ to the `Nat.Partrec.Code` it represents.
-/
def ofNatCode : ℕ → Code
| 0 => zero
| 1 => succ
| 2 => left
| 3 => right
| n + 4 =>
let m := n.div2.div2
have hm : m < n + 4 := by
simp only [m, div2_val]
exact
lt_of_le_of_lt (le_trans (Nat.div_le_self _ _) (Nat.div_le_self _ _))
(Nat.succ_le_succ (Nat.le_add_right _ _))
have _m1 : m.unpair.1 < n + 4 := lt_of_le_of_lt m.unpair_left_le hm
have _m2 : m.unpair.2 < n + 4 := lt_of_le_of_lt m.unpair_right_le hm
match n.bodd, n.div2.bodd with
| false, false => pair (ofNatCode m.unpair.1) (ofNatCode m.unpair.2)
| false, true => comp (ofNatCode m.unpair.1) (ofNatCode m.unpair.2)
| true , false => prec (ofNatCode m.unpair.1) (ofNatCode m.unpair.2)
| true , true => rfind' (ofNatCode m)
#align nat.partrec.code.of_nat_code Nat.Partrec.Code.ofNatCode
/-- Proof that `Nat.Partrec.Code.ofNatCode` is the inverse of `Nat.Partrec.Code.encodeCode`-/
private theorem encode_ofNatCode : ∀ n, encodeCode (ofNatCode n) = n
| 0 => by simp [ofNatCode, encodeCode]
| 1 => by simp [ofNatCode, encodeCode]
| 2 => by simp [ofNatCode, encodeCode]
| 3 => by simp [ofNatCode, encodeCode]
| n + 4 => by
let m := n.div2.div2
have hm : m < n + 4 := by
simp only [m, div2_val]
exact
lt_of_le_of_lt (le_trans (Nat.div_le_self _ _) (Nat.div_le_self _ _))
(Nat.succ_le_succ (Nat.le_add_right _ _))
have _m1 : m.unpair.1 < n + 4 := lt_of_le_of_lt m.unpair_left_le hm
have _m2 : m.unpair.2 < n + 4 := lt_of_le_of_lt m.unpair_right_le hm
have IH := encode_ofNatCode m
have IH1 := encode_ofNatCode m.unpair.1
have IH2 := encode_ofNatCode m.unpair.2
conv_rhs => rw [← Nat.bit_decomp n, ← Nat.bit_decomp n.div2]
simp only [ofNatCode.eq_5]
cases n.bodd <;> cases n.div2.bodd <;>
simp [encodeCode, ofNatCode, IH, IH1, IH2, Nat.bit_val]
instance instDenumerable : Denumerable Code :=
mk'
⟨encodeCode, ofNatCode, fun c => by
induction c <;> try {rfl} <;> simp [encodeCode, ofNatCode, Nat.div2_val, *],
encode_ofNatCode⟩
#align nat.partrec.code.denumerable Nat.Partrec.Code.instDenumerable
theorem encodeCode_eq : encode = encodeCode :=
rfl
#align nat.partrec.code.encode_code_eq Nat.Partrec.Code.encodeCode_eq
theorem ofNatCode_eq : ofNat Code = ofNatCode :=
rfl
#align nat.partrec.code.of_nat_code_eq Nat.Partrec.Code.ofNatCode_eq
theorem encode_lt_pair (cf cg) :
encode cf < encode (pair cf cg) ∧ encode cg < encode (pair cf cg) := by
simp only [encodeCode_eq, encodeCode]
have := Nat.mul_le_mul_right (Nat.pair cf.encodeCode cg.encodeCode) (by decide : 1 ≤ 2 * 2)
rw [one_mul, mul_assoc] at this
have := lt_of_le_of_lt this (lt_add_of_pos_right _ (by decide : 0 < 4))
exact ⟨lt_of_le_of_lt (Nat.left_le_pair _ _) this, lt_of_le_of_lt (Nat.right_le_pair _ _) this⟩
#align nat.partrec.code.encode_lt_pair Nat.Partrec.Code.encode_lt_pair
theorem encode_lt_comp (cf cg) :
encode cf < encode (comp cf cg) ∧ encode cg < encode (comp cf cg) := by
have : encode (pair cf cg) < encode (comp cf cg) := by simp [encodeCode_eq, encodeCode]
exact (encode_lt_pair cf cg).imp (fun h => lt_trans h this) fun h => lt_trans h this
#align nat.partrec.code.encode_lt_comp Nat.Partrec.Code.encode_lt_comp
theorem encode_lt_prec (cf cg) :
encode cf < encode (prec cf cg) ∧ encode cg < encode (prec cf cg) := by
have : encode (pair cf cg) < encode (prec cf cg) := by simp [encodeCode_eq, encodeCode]
exact (encode_lt_pair cf cg).imp (fun h => lt_trans h this) fun h => lt_trans h this
#align nat.partrec.code.encode_lt_prec Nat.Partrec.Code.encode_lt_prec
theorem encode_lt_rfind' (cf) : encode cf < encode (rfind' cf) := by
simp only [encodeCode_eq, encodeCode]
have := Nat.mul_le_mul_right cf.encodeCode (by decide : 1 ≤ 2 * 2)
rw [one_mul, mul_assoc] at this
refine lt_of_le_of_lt (le_trans this ?_) (lt_add_of_pos_right _ (by decide : 0 < 4))
exact le_of_lt (Nat.lt_succ_of_le <| Nat.mul_le_mul_left _ <| le_of_lt <|
Nat.lt_succ_of_le <| Nat.mul_le_mul_left _ <| le_rfl)
#align nat.partrec.code.encode_lt_rfind' Nat.Partrec.Code.encode_lt_rfind'
end Nat.Partrec.Code
-- Porting note: Opening `Primrec` inside `namespace Nat.Partrec.Code` causes it to resolve
-- to `Nat.Partrec`. Needs `open _root_.Partrec` support
section
open Primrec
namespace Nat.Partrec.Code
theorem pair_prim : Primrec₂ pair :=
Primrec₂.ofNat_iff.2 <|
Primrec₂.encode_iff.1 <|
nat_add.comp
(nat_double.comp <|
nat_double.comp <|
Primrec₂.natPair.comp (encode_iff.2 <| (Primrec.ofNat Code).comp fst)
(encode_iff.2 <| (Primrec.ofNat Code).comp snd))
(Primrec₂.const 4)
#align nat.partrec.code.pair_prim Nat.Partrec.Code.pair_prim
theorem comp_prim : Primrec₂ comp :=
Primrec₂.ofNat_iff.2 <|
Primrec₂.encode_iff.1 <|
nat_add.comp
(nat_double.comp <|
nat_double_succ.comp <|
Primrec₂.natPair.comp (encode_iff.2 <| (Primrec.ofNat Code).comp fst)
(encode_iff.2 <| (Primrec.ofNat Code).comp snd))
(Primrec₂.const 4)
#align nat.partrec.code.comp_prim Nat.Partrec.Code.comp_prim
theorem prec_prim : Primrec₂ prec :=
Primrec₂.ofNat_iff.2 <|
Primrec₂.encode_iff.1 <|
nat_add.comp
(nat_double_succ.comp <|
nat_double.comp <|
Primrec₂.natPair.comp (encode_iff.2 <| (Primrec.ofNat Code).comp fst)
(encode_iff.2 <| (Primrec.ofNat Code).comp snd))
(Primrec₂.const 4)
#align nat.partrec.code.prec_prim Nat.Partrec.Code.prec_prim
theorem rfind_prim : Primrec rfind' :=
ofNat_iff.2 <|
encode_iff.1 <|
nat_add.comp
(nat_double_succ.comp <| nat_double_succ.comp <|
encode_iff.2 <| Primrec.ofNat Code)
(const 4)
#align nat.partrec.code.rfind_prim Nat.Partrec.Code.rfind_prim
theorem rec_prim' {α σ} [Primcodable α] [Primcodable σ] {c : α → Code} (hc : Primrec c) {z : α → σ}
(hz : Primrec z) {s : α → σ} (hs : Primrec s) {l : α → σ} (hl : Primrec l) {r : α → σ}
(hr : Primrec r) {pr : α → Code × Code × σ × σ → σ} (hpr : Primrec₂ pr)
{co : α → Code × Code × σ × σ → σ} (hco : Primrec₂ co) {pc : α → Code × Code × σ × σ → σ}
(hpc : Primrec₂ pc) {rf : α → Code × σ → σ} (hrf : Primrec₂ rf) :
let PR (a) cf cg hf hg := pr a (cf, cg, hf, hg)
let CO (a) cf cg hf hg := co a (cf, cg, hf, hg)
let PC (a) cf cg hf hg := pc a (cf, cg, hf, hg)
let RF (a) cf hf := rf a (cf, hf)
let F (a : α) (c : Code) : σ :=
Nat.Partrec.Code.recOn c (z a) (s a) (l a) (r a) (PR a) (CO a) (PC a) (RF a)
Primrec (fun a => F a (c a) : α → σ) := by
intros _ _ _ _ F
let G₁ : (α × List σ) × ℕ × ℕ → Option σ := fun p =>
letI a := p.1.1; letI IH := p.1.2; letI n := p.2.1; letI m := p.2.2
(IH.get? m).bind fun s =>
(IH.get? m.unpair.1).bind fun s₁ =>
(IH.get? m.unpair.2).map fun s₂ =>
cond n.bodd
(cond n.div2.bodd (rf a (ofNat Code m, s))
(pc a (ofNat Code m.unpair.1, ofNat Code m.unpair.2, s₁, s₂)))
(cond n.div2.bodd (co a (ofNat Code m.unpair.1, ofNat Code m.unpair.2, s₁, s₂))
(pr a (ofNat Code m.unpair.1, ofNat Code m.unpair.2, s₁, s₂)))
have : Primrec G₁ :=
option_bind (list_get?.comp (snd.comp fst) (snd.comp snd)) <| .mk <|
option_bind ((list_get?.comp (snd.comp fst)
(fst.comp <| Primrec.unpair.comp (snd.comp snd))).comp fst) <| .mk <|
option_map ((list_get?.comp (snd.comp fst)
(snd.comp <| Primrec.unpair.comp (snd.comp snd))).comp <| fst.comp fst) <| .mk <|
have a := fst.comp (fst.comp <| fst.comp <| fst.comp fst)
have n := fst.comp (snd.comp <| fst.comp <| fst.comp fst)
have m := snd.comp (snd.comp <| fst.comp <| fst.comp fst)
have m₁ := fst.comp (Primrec.unpair.comp m)
have m₂ := snd.comp (Primrec.unpair.comp m)
have s := snd.comp (fst.comp fst)
have s₁ := snd.comp fst
have s₂ := snd
(nat_bodd.comp n).cond
((nat_bodd.comp <| nat_div2.comp n).cond
(hrf.comp a (((Primrec.ofNat Code).comp m).pair s))
(hpc.comp a (((Primrec.ofNat Code).comp m₁).pair <|
((Primrec.ofNat Code).comp m₂).pair <| s₁.pair s₂)))
(Primrec.cond (nat_bodd.comp <| nat_div2.comp n)
(hco.comp a (((Primrec.ofNat Code).comp m₁).pair <|
((Primrec.ofNat Code).comp m₂).pair <| s₁.pair s₂))
(hpr.comp a (((Primrec.ofNat Code).comp m₁).pair <|
((Primrec.ofNat Code).comp m₂).pair <| s₁.pair s₂)))
let G : α → List σ → Option σ := fun a IH =>
IH.length.casesOn (some (z a)) fun n =>
n.casesOn (some (s a)) fun n =>
n.casesOn (some (l a)) fun n =>
n.casesOn (some (r a)) fun n =>
G₁ ((a, IH), n, n.div2.div2)
have : Primrec₂ G := .mk <|
nat_casesOn (list_length.comp snd) (option_some_iff.2 (hz.comp fst)) <| .mk <|
nat_casesOn snd (option_some_iff.2 (hs.comp (fst.comp fst))) <| .mk <|
nat_casesOn snd (option_some_iff.2 (hl.comp (fst.comp <| fst.comp fst))) <| .mk <|
nat_casesOn snd (option_some_iff.2 (hr.comp (fst.comp <| fst.comp <| fst.comp fst))) <| .mk <|
this.comp <|
((fst.pair snd).comp <| fst.comp <| fst.comp <| fst.comp <| fst).pair <|
snd.pair <| nat_div2.comp <| nat_div2.comp snd
refine (nat_strong_rec (fun a n => F a (ofNat Code n)) this.to₂ fun a n => ?_)
|>.comp .id (encode_iff.2 hc) |>.of_eq fun a => by simp
simp
iterate 4 cases' n with n; · simp [ofNatCode_eq, ofNatCode]; rfl
simp only [G]; rw [List.length_map, List.length_range]
let m := n.div2.div2
show G₁ ((a, (List.range (n + 4)).map fun n => F a (ofNat Code n)), n, m)
= some (F a (ofNat Code (n + 4)))
have hm : m < n + 4 := by
simp only [m, div2_val]
exact lt_of_le_of_lt
(le_trans (Nat.div_le_self ..) (Nat.div_le_self ..))
(Nat.succ_le_succ (Nat.le_add_right ..))
have m1 : m.unpair.1 < n + 4 := lt_of_le_of_lt m.unpair_left_le hm
have m2 : m.unpair.2 < n + 4 := lt_of_le_of_lt m.unpair_right_le hm
simp [G₁]; simp [m, List.get?_map, List.get?_range, hm, m1, m2]
rw [show ofNat Code (n + 4) = ofNatCode (n + 4) from rfl]
simp [ofNatCode]
cases n.bodd <;> cases n.div2.bodd <;> rfl
#align nat.partrec.code.rec_prim' Nat.Partrec.Code.rec_prim'
/-- Recursion on `Nat.Partrec.Code` is primitive recursive. -/
theorem rec_prim {α σ} [Primcodable α] [Primcodable σ] {c : α → Code} (hc : Primrec c) {z : α → σ}
(hz : Primrec z) {s : α → σ} (hs : Primrec s) {l : α → σ} (hl : Primrec l) {r : α → σ}
(hr : Primrec r) {pr : α → Code → Code → σ → σ → σ}
(hpr : Primrec fun a : α × Code × Code × σ × σ => pr a.1 a.2.1 a.2.2.1 a.2.2.2.1 a.2.2.2.2)
{co : α → Code → Code → σ → σ → σ}
(hco : Primrec fun a : α × Code × Code × σ × σ => co a.1 a.2.1 a.2.2.1 a.2.2.2.1 a.2.2.2.2)
{pc : α → Code → Code → σ → σ → σ}
(hpc : Primrec fun a : α × Code × Code × σ × σ => pc a.1 a.2.1 a.2.2.1 a.2.2.2.1 a.2.2.2.2)
{rf : α → Code → σ → σ} (hrf : Primrec fun a : α × Code × σ => rf a.1 a.2.1 a.2.2) :
let F (a : α) (c : Code) : σ :=
Nat.Partrec.Code.recOn c (z a) (s a) (l a) (r a) (pr a) (co a) (pc a) (rf a)
Primrec fun a => F a (c a) :=
rec_prim' hc hz hs hl hr
(pr := fun a b => pr a b.1 b.2.1 b.2.2.1 b.2.2.2) (.mk hpr)
(co := fun a b => co a b.1 b.2.1 b.2.2.1 b.2.2.2) (.mk hco)
(pc := fun a b => pc a b.1 b.2.1 b.2.2.1 b.2.2.2) (.mk hpc)
(rf := fun a b => rf a b.1 b.2) (.mk hrf)
#align nat.partrec.code.rec_prim Nat.Partrec.Code.rec_prim
end Nat.Partrec.Code
end
namespace Nat.Partrec.Code
section
open Computable
/-- Recursion on `Nat.Partrec.Code` is computable. -/
theorem rec_computable {α σ} [Primcodable α] [Primcodable σ] {c : α → Code} (hc : Computable c)
{z : α → σ} (hz : Computable z) {s : α → σ} (hs : Computable s) {l : α → σ} (hl : Computable l)
{r : α → σ} (hr : Computable r) {pr : α → Code × Code × σ × σ → σ} (hpr : Computable₂ pr)
{co : α → Code × Code × σ × σ → σ} (hco : Computable₂ co) {pc : α → Code × Code × σ × σ → σ}
(hpc : Computable₂ pc) {rf : α → Code × σ → σ} (hrf : Computable₂ rf) :
let PR (a) cf cg hf hg := pr a (cf, cg, hf, hg)
let CO (a) cf cg hf hg := co a (cf, cg, hf, hg)
let PC (a) cf cg hf hg := pc a (cf, cg, hf, hg)
let RF (a) cf hf := rf a (cf, hf)
let F (a : α) (c : Code) : σ :=
Nat.Partrec.Code.recOn c (z a) (s a) (l a) (r a) (PR a) (CO a) (PC a) (RF a)
Computable fun a => F a (c a) := by
-- TODO(Mario): less copy-paste from previous proof
intros _ _ _ _ F
let G₁ : (α × List σ) × ℕ × ℕ → Option σ := fun p =>
letI a := p.1.1; letI IH := p.1.2; letI n := p.2.1; letI m := p.2.2
(IH.get? m).bind fun s =>
(IH.get? m.unpair.1).bind fun s₁ =>
(IH.get? m.unpair.2).map fun s₂ =>
cond n.bodd
(cond n.div2.bodd (rf a (ofNat Code m, s))
(pc a (ofNat Code m.unpair.1, ofNat Code m.unpair.2, s₁, s₂)))
(cond n.div2.bodd (co a (ofNat Code m.unpair.1, ofNat Code m.unpair.2, s₁, s₂))
(pr a (ofNat Code m.unpair.1, ofNat Code m.unpair.2, s₁, s₂)))
have : Computable G₁ := by
refine option_bind (list_get?.comp (snd.comp fst) (snd.comp snd)) <| .mk ?_
refine option_bind ((list_get?.comp (snd.comp fst)
(fst.comp <| Computable.unpair.comp (snd.comp snd))).comp fst) <| .mk ?_
refine option_map ((list_get?.comp (snd.comp fst)
(snd.comp <| Computable.unpair.comp (snd.comp snd))).comp <| fst.comp fst) <| .mk ?_
exact
have a := fst.comp (fst.comp <| fst.comp <| fst.comp fst)
have n := fst.comp (snd.comp <| fst.comp <| fst.comp fst)
have m := snd.comp (snd.comp <| fst.comp <| fst.comp fst)
have m₁ := fst.comp (Computable.unpair.comp m)
have m₂ := snd.comp (Computable.unpair.comp m)
have s := snd.comp (fst.comp fst)
have s₁ := snd.comp fst
have s₂ := snd
(nat_bodd.comp n).cond
((nat_bodd.comp <| nat_div2.comp n).cond
(hrf.comp a (((Computable.ofNat Code).comp m).pair s))
(hpc.comp a (((Computable.ofNat Code).comp m₁).pair <|
((Computable.ofNat Code).comp m₂).pair <| s₁.pair s₂)))
(Computable.cond (nat_bodd.comp <| nat_div2.comp n)
(hco.comp a (((Computable.ofNat Code).comp m₁).pair <|
((Computable.ofNat Code).comp m₂).pair <| s₁.pair s₂))
(hpr.comp a (((Computable.ofNat Code).comp m₁).pair <|
((Computable.ofNat Code).comp m₂).pair <| s₁.pair s₂)))
let G : α → List σ → Option σ := fun a IH =>
IH.length.casesOn (some (z a)) fun n =>
n.casesOn (some (s a)) fun n =>
n.casesOn (some (l a)) fun n =>
n.casesOn (some (r a)) fun n =>
G₁ ((a, IH), n, n.div2.div2)
have : Computable₂ G := .mk <|
nat_casesOn (list_length.comp snd) (option_some_iff.2 (hz.comp fst)) <| .mk <|
nat_casesOn snd (option_some_iff.2 (hs.comp (fst.comp fst))) <| .mk <|
nat_casesOn snd (option_some_iff.2 (hl.comp (fst.comp <| fst.comp fst))) <| .mk <|
nat_casesOn snd (option_some_iff.2 (hr.comp (fst.comp <| fst.comp <| fst.comp fst))) <| .mk <|
this.comp <|
((fst.pair snd).comp <| fst.comp <| fst.comp <| fst.comp <| fst).pair <|
snd.pair <| nat_div2.comp <| nat_div2.comp snd
refine (nat_strong_rec (fun a n => F a (ofNat Code n)) this.to₂ fun a n => ?_)
|>.comp .id (encode_iff.2 hc) |>.of_eq fun a => by simp
simp
iterate 4 cases' n with n; · simp [ofNatCode_eq, ofNatCode]; rfl
simp only [G]; rw [List.length_map, List.length_range]
let m := n.div2.div2
show G₁ ((a, (List.range (n + 4)).map fun n => F a (ofNat Code n)), n, m)
= some (F a (ofNat Code (n + 4)))
have hm : m < n + 4 := by
simp only [m, div2_val]
exact lt_of_le_of_lt
(le_trans (Nat.div_le_self ..) (Nat.div_le_self ..))
(Nat.succ_le_succ (Nat.le_add_right ..))
have m1 : m.unpair.1 < n + 4 := lt_of_le_of_lt m.unpair_left_le hm
have m2 : m.unpair.2 < n + 4 := lt_of_le_of_lt m.unpair_right_le hm
simp [G₁]; simp [m, List.get?_map, List.get?_range, hm, m1, m2]
rw [show ofNat Code (n + 4) = ofNatCode (n + 4) from rfl]
simp [ofNatCode]
cases n.bodd <;> cases n.div2.bodd <;> rfl
#align nat.partrec.code.rec_computable Nat.Partrec.Code.rec_computable
end
/-- The interpretation of a `Nat.Partrec.Code` as a partial function.
* `Nat.Partrec.Code.zero`: The constant zero function.
* `Nat.Partrec.Code.succ`: The successor function.
* `Nat.Partrec.Code.left`: Left unpairing of a pair of ℕ (encoded by `Nat.pair`)
* `Nat.Partrec.Code.right`: Right unpairing of a pair of ℕ (encoded by `Nat.pair`)
* `Nat.Partrec.Code.pair`: Pairs the outputs of argument codes using `Nat.pair`.
* `Nat.Partrec.Code.comp`: Composition of two argument codes.
* `Nat.Partrec.Code.prec`: Primitive recursion. Given an argument of the form `Nat.pair a n`:
* If `n = 0`, returns `eval cf a`.
* If `n = succ k`, returns `eval cg (pair a (pair k (eval (prec cf cg) (pair a k))))`
* `Nat.Partrec.Code.rfind'`: Minimization. For `f` an argument of the form `Nat.pair a m`,
`rfind' f m` returns the least `a` such that `f a m = 0`, if one exists and `f b m` terminates
for `b < a`
-/
def eval : Code → ℕ →. ℕ
| zero => pure 0
| succ => Nat.succ
| left => ↑fun n : ℕ => n.unpair.1
| right => ↑fun n : ℕ => n.unpair.2
| pair cf cg => fun n => Nat.pair <$> eval cf n <*> eval cg n
| comp cf cg => fun n => eval cg n >>= eval cf
| prec cf cg =>
Nat.unpaired fun a n =>
n.rec (eval cf a) fun y IH => do
let i ← IH
eval cg (Nat.pair a (Nat.pair y i))
| rfind' cf =>
Nat.unpaired fun a m =>
(Nat.rfind fun n => (fun m => m = 0) <$> eval cf (Nat.pair a (n + m))).map (· + m)
#align nat.partrec.code.eval Nat.Partrec.Code.eval
/-- Helper lemma for the evaluation of `prec` in the base case. -/
@[simp]
theorem eval_prec_zero (cf cg : Code) (a : ℕ) : eval (prec cf cg) (Nat.pair a 0) = eval cf a := by
rw [eval, Nat.unpaired, Nat.unpair_pair]
simp (config := { Lean.Meta.Simp.neutralConfig with proj := true }) only []
rw [Nat.rec_zero]
#align nat.partrec.code.eval_prec_zero Nat.Partrec.Code.eval_prec_zero
/-- Helper lemma for the evaluation of `prec` in the recursive case. -/
| Mathlib/Computability/PartrecCode.lean | 514 | 518 | theorem eval_prec_succ (cf cg : Code) (a k : ℕ) :
eval (prec cf cg) (Nat.pair a (Nat.succ k)) =
do {let ih ← eval (prec cf cg) (Nat.pair a k); eval cg (Nat.pair a (Nat.pair k ih))} := by |
rw [eval, Nat.unpaired, Part.bind_eq_bind, Nat.unpair_pair]
simp
|
/-
Copyright (c) 2022 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll
-/
import Mathlib.Analysis.SpecialFunctions.Integrals
import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar
import Mathlib.MeasureTheory.Integral.Layercake
#align_import analysis.special_functions.japanese_bracket from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Japanese Bracket
In this file, we show that Japanese bracket $(1 + \|x\|^2)^{1/2}$ can be estimated from above
and below by $1 + \|x\|$.
The functions $(1 + \|x\|^2)^{-r/2}$ and $(1 + |x|)^{-r}$ are integrable provided that `r` is larger
than the dimension.
## Main statements
* `integrable_one_add_norm`: the function $(1 + |x|)^{-r}$ is integrable
* `integrable_jap` the Japanese bracket is integrable
-/
noncomputable section
open scoped NNReal Filter Topology ENNReal
open Asymptotics Filter Set Real MeasureTheory FiniteDimensional
variable {E : Type*} [NormedAddCommGroup E]
theorem sqrt_one_add_norm_sq_le (x : E) : √((1 : ℝ) + ‖x‖ ^ 2) ≤ 1 + ‖x‖ := by
rw [sqrt_le_left (by positivity)]
simp [add_sq]
#align sqrt_one_add_norm_sq_le sqrt_one_add_norm_sq_le
theorem one_add_norm_le_sqrt_two_mul_sqrt (x : E) :
(1 : ℝ) + ‖x‖ ≤ √2 * √(1 + ‖x‖ ^ 2) := by
rw [← sqrt_mul zero_le_two]
have := sq_nonneg (‖x‖ - 1)
apply le_sqrt_of_sq_le
linarith
#align one_add_norm_le_sqrt_two_mul_sqrt one_add_norm_le_sqrt_two_mul_sqrt
theorem rpow_neg_one_add_norm_sq_le {r : ℝ} (x : E) (hr : 0 < r) :
((1 : ℝ) + ‖x‖ ^ 2) ^ (-r / 2) ≤ (2 : ℝ) ^ (r / 2) * (1 + ‖x‖) ^ (-r) :=
calc
((1 : ℝ) + ‖x‖ ^ 2) ^ (-r / 2)
= (2 : ℝ) ^ (r / 2) * ((√2 * √((1 : ℝ) + ‖x‖ ^ 2)) ^ r)⁻¹ := by
rw [rpow_div_two_eq_sqrt, rpow_div_two_eq_sqrt, mul_rpow, mul_inv, rpow_neg,
mul_inv_cancel_left₀] <;> positivity
_ ≤ (2 : ℝ) ^ (r / 2) * ((1 + ‖x‖) ^ r)⁻¹ := by
gcongr
apply one_add_norm_le_sqrt_two_mul_sqrt
_ = (2 : ℝ) ^ (r / 2) * (1 + ‖x‖) ^ (-r) := by rw [rpow_neg]; positivity
#align rpow_neg_one_add_norm_sq_le rpow_neg_one_add_norm_sq_le
| Mathlib/Analysis/SpecialFunctions/JapaneseBracket.lean | 62 | 65 | theorem le_rpow_one_add_norm_iff_norm_le {r t : ℝ} (hr : 0 < r) (ht : 0 < t) (x : E) :
t ≤ (1 + ‖x‖) ^ (-r) ↔ ‖x‖ ≤ t ^ (-r⁻¹) - 1 := by |
rw [le_sub_iff_add_le', neg_inv]
exact (Real.le_rpow_inv_iff_of_neg (by positivity) ht (neg_lt_zero.mpr hr)).symm
|
/-
Copyright (c) 2021 Eric Rodriguez. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Rodriguez
-/
import Mathlib.RingTheory.Polynomial.Cyclotomic.Roots
import Mathlib.Tactic.ByContra
import Mathlib.Topology.Algebra.Polynomial
import Mathlib.NumberTheory.Padics.PadicVal
import Mathlib.Analysis.Complex.Arg
#align_import ring_theory.polynomial.cyclotomic.eval from "leanprover-community/mathlib"@"5bfbcca0a7ffdd21cf1682e59106d6c942434a32"
/-!
# Evaluating cyclotomic polynomials
This file states some results about evaluating cyclotomic polynomials in various different ways.
## Main definitions
* `Polynomial.eval(₂)_one_cyclotomic_prime(_pow)`: `eval 1 (cyclotomic p^k R) = p`.
* `Polynomial.eval_one_cyclotomic_not_prime_pow`: Otherwise, `eval 1 (cyclotomic n R) = 1`.
* `Polynomial.cyclotomic_pos` : `∀ x, 0 < eval x (cyclotomic n R)` if `2 < n`.
-/
namespace Polynomial
open Finset Nat
@[simp]
theorem eval_one_cyclotomic_prime {R : Type*} [CommRing R] {p : ℕ} [hn : Fact p.Prime] :
eval 1 (cyclotomic p R) = p := by
simp only [cyclotomic_prime, eval_X, one_pow, Finset.sum_const, eval_pow, eval_finset_sum,
Finset.card_range, smul_one_eq_cast]
#align polynomial.eval_one_cyclotomic_prime Polynomial.eval_one_cyclotomic_prime
-- @[simp] -- Porting note (#10618): simp already proves this
| Mathlib/RingTheory/Polynomial/Cyclotomic/Eval.lean | 36 | 37 | theorem eval₂_one_cyclotomic_prime {R S : Type*} [CommRing R] [Semiring S] (f : R →+* S) {p : ℕ}
[Fact p.Prime] : eval₂ f 1 (cyclotomic p R) = p := by | simp
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Fintype.Option
import Mathlib.Data.Fintype.Prod
import Mathlib.Data.Fintype.Pi
import Mathlib.Data.Vector.Basic
import Mathlib.Data.PFun
import Mathlib.Logic.Function.Iterate
import Mathlib.Order.Basic
import Mathlib.Tactic.ApplyFun
#align_import computability.turing_machine from "leanprover-community/mathlib"@"4c19a16e4b705bf135cf9a80ac18fcc99c438514"
/-!
# Turing machines
This file defines a sequence of simple machine languages, starting with Turing machines and working
up to more complex languages based on Wang B-machines.
## Naming conventions
Each model of computation in this file shares a naming convention for the elements of a model of
computation. These are the parameters for the language:
* `Γ` is the alphabet on the tape.
* `Λ` is the set of labels, or internal machine states.
* `σ` is the type of internal memory, not on the tape. This does not exist in the TM0 model, and
later models achieve this by mixing it into `Λ`.
* `K` is used in the TM2 model, which has multiple stacks, and denotes the number of such stacks.
All of these variables denote "essentially finite" types, but for technical reasons it is
convenient to allow them to be infinite anyway. When using an infinite type, we will be interested
to prove that only finitely many values of the type are ever interacted with.
Given these parameters, there are a few common structures for the model that arise:
* `Stmt` is the set of all actions that can be performed in one step. For the TM0 model this set is
finite, and for later models it is an infinite inductive type representing "possible program
texts".
* `Cfg` is the set of instantaneous configurations, that is, the state of the machine together with
its environment.
* `Machine` is the set of all machines in the model. Usually this is approximately a function
`Λ → Stmt`, although different models have different ways of halting and other actions.
* `step : Cfg → Option Cfg` is the function that describes how the state evolves over one step.
If `step c = none`, then `c` is a terminal state, and the result of the computation is read off
from `c`. Because of the type of `step`, these models are all deterministic by construction.
* `init : Input → Cfg` sets up the initial state. The type `Input` depends on the model;
in most cases it is `List Γ`.
* `eval : Machine → Input → Part Output`, given a machine `M` and input `i`, starts from
`init i`, runs `step` until it reaches an output, and then applies a function `Cfg → Output` to
the final state to obtain the result. The type `Output` depends on the model.
* `Supports : Machine → Finset Λ → Prop` asserts that a machine `M` starts in `S : Finset Λ`, and
can only ever jump to other states inside `S`. This implies that the behavior of `M` on any input
cannot depend on its values outside `S`. We use this to allow `Λ` to be an infinite set when
convenient, and prove that only finitely many of these states are actually accessible. This
formalizes "essentially finite" mentioned above.
-/
assert_not_exists MonoidWithZero
open Relation
open Nat (iterate)
open Function (update iterate_succ iterate_succ_apply iterate_succ' iterate_succ_apply'
iterate_zero_apply)
namespace Turing
/-- The `BlankExtends` partial order holds of `l₁` and `l₂` if `l₂` is obtained by adding
blanks (`default : Γ`) to the end of `l₁`. -/
def BlankExtends {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) : Prop :=
∃ n, l₂ = l₁ ++ List.replicate n default
#align turing.blank_extends Turing.BlankExtends
@[refl]
theorem BlankExtends.refl {Γ} [Inhabited Γ] (l : List Γ) : BlankExtends l l :=
⟨0, by simp⟩
#align turing.blank_extends.refl Turing.BlankExtends.refl
@[trans]
theorem BlankExtends.trans {Γ} [Inhabited Γ] {l₁ l₂ l₃ : List Γ} :
BlankExtends l₁ l₂ → BlankExtends l₂ l₃ → BlankExtends l₁ l₃ := by
rintro ⟨i, rfl⟩ ⟨j, rfl⟩
exact ⟨i + j, by simp [List.replicate_add]⟩
#align turing.blank_extends.trans Turing.BlankExtends.trans
theorem BlankExtends.below_of_le {Γ} [Inhabited Γ] {l l₁ l₂ : List Γ} :
BlankExtends l l₁ → BlankExtends l l₂ → l₁.length ≤ l₂.length → BlankExtends l₁ l₂ := by
rintro ⟨i, rfl⟩ ⟨j, rfl⟩ h; use j - i
simp only [List.length_append, Nat.add_le_add_iff_left, List.length_replicate] at h
simp only [← List.replicate_add, Nat.add_sub_cancel' h, List.append_assoc]
#align turing.blank_extends.below_of_le Turing.BlankExtends.below_of_le
/-- Any two extensions by blank `l₁,l₂` of `l` have a common join (which can be taken to be the
longer of `l₁` and `l₂`). -/
def BlankExtends.above {Γ} [Inhabited Γ] {l l₁ l₂ : List Γ} (h₁ : BlankExtends l l₁)
(h₂ : BlankExtends l l₂) : { l' // BlankExtends l₁ l' ∧ BlankExtends l₂ l' } :=
if h : l₁.length ≤ l₂.length then ⟨l₂, h₁.below_of_le h₂ h, BlankExtends.refl _⟩
else ⟨l₁, BlankExtends.refl _, h₂.below_of_le h₁ (le_of_not_ge h)⟩
#align turing.blank_extends.above Turing.BlankExtends.above
theorem BlankExtends.above_of_le {Γ} [Inhabited Γ] {l l₁ l₂ : List Γ} :
BlankExtends l₁ l → BlankExtends l₂ l → l₁.length ≤ l₂.length → BlankExtends l₁ l₂ := by
rintro ⟨i, rfl⟩ ⟨j, e⟩ h; use i - j
refine List.append_cancel_right (e.symm.trans ?_)
rw [List.append_assoc, ← List.replicate_add, Nat.sub_add_cancel]
apply_fun List.length at e
simp only [List.length_append, List.length_replicate] at e
rwa [← Nat.add_le_add_iff_left, e, Nat.add_le_add_iff_right]
#align turing.blank_extends.above_of_le Turing.BlankExtends.above_of_le
/-- `BlankRel` is the symmetric closure of `BlankExtends`, turning it into an equivalence
relation. Two lists are related by `BlankRel` if one extends the other by blanks. -/
def BlankRel {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) : Prop :=
BlankExtends l₁ l₂ ∨ BlankExtends l₂ l₁
#align turing.blank_rel Turing.BlankRel
@[refl]
theorem BlankRel.refl {Γ} [Inhabited Γ] (l : List Γ) : BlankRel l l :=
Or.inl (BlankExtends.refl _)
#align turing.blank_rel.refl Turing.BlankRel.refl
@[symm]
theorem BlankRel.symm {Γ} [Inhabited Γ] {l₁ l₂ : List Γ} : BlankRel l₁ l₂ → BlankRel l₂ l₁ :=
Or.symm
#align turing.blank_rel.symm Turing.BlankRel.symm
@[trans]
theorem BlankRel.trans {Γ} [Inhabited Γ] {l₁ l₂ l₃ : List Γ} :
BlankRel l₁ l₂ → BlankRel l₂ l₃ → BlankRel l₁ l₃ := by
rintro (h₁ | h₁) (h₂ | h₂)
· exact Or.inl (h₁.trans h₂)
· rcases le_total l₁.length l₃.length with h | h
· exact Or.inl (h₁.above_of_le h₂ h)
· exact Or.inr (h₂.above_of_le h₁ h)
· rcases le_total l₁.length l₃.length with h | h
· exact Or.inl (h₁.below_of_le h₂ h)
· exact Or.inr (h₂.below_of_le h₁ h)
· exact Or.inr (h₂.trans h₁)
#align turing.blank_rel.trans Turing.BlankRel.trans
/-- Given two `BlankRel` lists, there exists (constructively) a common join. -/
def BlankRel.above {Γ} [Inhabited Γ] {l₁ l₂ : List Γ} (h : BlankRel l₁ l₂) :
{ l // BlankExtends l₁ l ∧ BlankExtends l₂ l } := by
refine
if hl : l₁.length ≤ l₂.length then ⟨l₂, Or.elim h id fun h' ↦ ?_, BlankExtends.refl _⟩
else ⟨l₁, BlankExtends.refl _, Or.elim h (fun h' ↦ ?_) id⟩
· exact (BlankExtends.refl _).above_of_le h' hl
· exact (BlankExtends.refl _).above_of_le h' (le_of_not_ge hl)
#align turing.blank_rel.above Turing.BlankRel.above
/-- Given two `BlankRel` lists, there exists (constructively) a common meet. -/
def BlankRel.below {Γ} [Inhabited Γ] {l₁ l₂ : List Γ} (h : BlankRel l₁ l₂) :
{ l // BlankExtends l l₁ ∧ BlankExtends l l₂ } := by
refine
if hl : l₁.length ≤ l₂.length then ⟨l₁, BlankExtends.refl _, Or.elim h id fun h' ↦ ?_⟩
else ⟨l₂, Or.elim h (fun h' ↦ ?_) id, BlankExtends.refl _⟩
· exact (BlankExtends.refl _).above_of_le h' hl
· exact (BlankExtends.refl _).above_of_le h' (le_of_not_ge hl)
#align turing.blank_rel.below Turing.BlankRel.below
theorem BlankRel.equivalence (Γ) [Inhabited Γ] : Equivalence (@BlankRel Γ _) :=
⟨BlankRel.refl, @BlankRel.symm _ _, @BlankRel.trans _ _⟩
#align turing.blank_rel.equivalence Turing.BlankRel.equivalence
/-- Construct a setoid instance for `BlankRel`. -/
def BlankRel.setoid (Γ) [Inhabited Γ] : Setoid (List Γ) :=
⟨_, BlankRel.equivalence _⟩
#align turing.blank_rel.setoid Turing.BlankRel.setoid
/-- A `ListBlank Γ` is a quotient of `List Γ` by extension by blanks at the end. This is used to
represent half-tapes of a Turing machine, so that we can pretend that the list continues
infinitely with blanks. -/
def ListBlank (Γ) [Inhabited Γ] :=
Quotient (BlankRel.setoid Γ)
#align turing.list_blank Turing.ListBlank
instance ListBlank.inhabited {Γ} [Inhabited Γ] : Inhabited (ListBlank Γ) :=
⟨Quotient.mk'' []⟩
#align turing.list_blank.inhabited Turing.ListBlank.inhabited
instance ListBlank.hasEmptyc {Γ} [Inhabited Γ] : EmptyCollection (ListBlank Γ) :=
⟨Quotient.mk'' []⟩
#align turing.list_blank.has_emptyc Turing.ListBlank.hasEmptyc
/-- A modified version of `Quotient.liftOn'` specialized for `ListBlank`, with the stronger
precondition `BlankExtends` instead of `BlankRel`. -/
-- Porting note: Removed `@[elab_as_elim]`
protected abbrev ListBlank.liftOn {Γ} [Inhabited Γ] {α} (l : ListBlank Γ) (f : List Γ → α)
(H : ∀ a b, BlankExtends a b → f a = f b) : α :=
l.liftOn' f <| by rintro a b (h | h) <;> [exact H _ _ h; exact (H _ _ h).symm]
#align turing.list_blank.lift_on Turing.ListBlank.liftOn
/-- The quotient map turning a `List` into a `ListBlank`. -/
def ListBlank.mk {Γ} [Inhabited Γ] : List Γ → ListBlank Γ :=
Quotient.mk''
#align turing.list_blank.mk Turing.ListBlank.mk
@[elab_as_elim]
protected theorem ListBlank.induction_on {Γ} [Inhabited Γ] {p : ListBlank Γ → Prop}
(q : ListBlank Γ) (h : ∀ a, p (ListBlank.mk a)) : p q :=
Quotient.inductionOn' q h
#align turing.list_blank.induction_on Turing.ListBlank.induction_on
/-- The head of a `ListBlank` is well defined. -/
def ListBlank.head {Γ} [Inhabited Γ] (l : ListBlank Γ) : Γ := by
apply l.liftOn List.headI
rintro a _ ⟨i, rfl⟩
cases a
· cases i <;> rfl
rfl
#align turing.list_blank.head Turing.ListBlank.head
@[simp]
theorem ListBlank.head_mk {Γ} [Inhabited Γ] (l : List Γ) :
ListBlank.head (ListBlank.mk l) = l.headI :=
rfl
#align turing.list_blank.head_mk Turing.ListBlank.head_mk
/-- The tail of a `ListBlank` is well defined (up to the tail of blanks). -/
def ListBlank.tail {Γ} [Inhabited Γ] (l : ListBlank Γ) : ListBlank Γ := by
apply l.liftOn (fun l ↦ ListBlank.mk l.tail)
rintro a _ ⟨i, rfl⟩
refine Quotient.sound' (Or.inl ?_)
cases a
· cases' i with i <;> [exact ⟨0, rfl⟩; exact ⟨i, rfl⟩]
exact ⟨i, rfl⟩
#align turing.list_blank.tail Turing.ListBlank.tail
@[simp]
theorem ListBlank.tail_mk {Γ} [Inhabited Γ] (l : List Γ) :
ListBlank.tail (ListBlank.mk l) = ListBlank.mk l.tail :=
rfl
#align turing.list_blank.tail_mk Turing.ListBlank.tail_mk
/-- We can cons an element onto a `ListBlank`. -/
def ListBlank.cons {Γ} [Inhabited Γ] (a : Γ) (l : ListBlank Γ) : ListBlank Γ := by
apply l.liftOn (fun l ↦ ListBlank.mk (List.cons a l))
rintro _ _ ⟨i, rfl⟩
exact Quotient.sound' (Or.inl ⟨i, rfl⟩)
#align turing.list_blank.cons Turing.ListBlank.cons
@[simp]
theorem ListBlank.cons_mk {Γ} [Inhabited Γ] (a : Γ) (l : List Γ) :
ListBlank.cons a (ListBlank.mk l) = ListBlank.mk (a :: l) :=
rfl
#align turing.list_blank.cons_mk Turing.ListBlank.cons_mk
@[simp]
theorem ListBlank.head_cons {Γ} [Inhabited Γ] (a : Γ) : ∀ l : ListBlank Γ, (l.cons a).head = a :=
Quotient.ind' fun _ ↦ rfl
#align turing.list_blank.head_cons Turing.ListBlank.head_cons
@[simp]
theorem ListBlank.tail_cons {Γ} [Inhabited Γ] (a : Γ) : ∀ l : ListBlank Γ, (l.cons a).tail = l :=
Quotient.ind' fun _ ↦ rfl
#align turing.list_blank.tail_cons Turing.ListBlank.tail_cons
/-- The `cons` and `head`/`tail` functions are mutually inverse, unlike in the case of `List` where
this only holds for nonempty lists. -/
@[simp]
theorem ListBlank.cons_head_tail {Γ} [Inhabited Γ] : ∀ l : ListBlank Γ, l.tail.cons l.head = l := by
apply Quotient.ind'
refine fun l ↦ Quotient.sound' (Or.inr ?_)
cases l
· exact ⟨1, rfl⟩
· rfl
#align turing.list_blank.cons_head_tail Turing.ListBlank.cons_head_tail
/-- The `cons` and `head`/`tail` functions are mutually inverse, unlike in the case of `List` where
this only holds for nonempty lists. -/
theorem ListBlank.exists_cons {Γ} [Inhabited Γ] (l : ListBlank Γ) :
∃ a l', l = ListBlank.cons a l' :=
⟨_, _, (ListBlank.cons_head_tail _).symm⟩
#align turing.list_blank.exists_cons Turing.ListBlank.exists_cons
/-- The n-th element of a `ListBlank` is well defined for all `n : ℕ`, unlike in a `List`. -/
def ListBlank.nth {Γ} [Inhabited Γ] (l : ListBlank Γ) (n : ℕ) : Γ := by
apply l.liftOn (fun l ↦ List.getI l n)
rintro l _ ⟨i, rfl⟩
cases' lt_or_le n _ with h h
· rw [List.getI_append _ _ _ h]
rw [List.getI_eq_default _ h]
rcases le_or_lt _ n with h₂ | h₂
· rw [List.getI_eq_default _ h₂]
rw [List.getI_eq_get _ h₂, List.get_append_right' h, List.get_replicate]
#align turing.list_blank.nth Turing.ListBlank.nth
@[simp]
theorem ListBlank.nth_mk {Γ} [Inhabited Γ] (l : List Γ) (n : ℕ) :
(ListBlank.mk l).nth n = l.getI n :=
rfl
#align turing.list_blank.nth_mk Turing.ListBlank.nth_mk
@[simp]
theorem ListBlank.nth_zero {Γ} [Inhabited Γ] (l : ListBlank Γ) : l.nth 0 = l.head := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l.tail fun l ↦ rfl
#align turing.list_blank.nth_zero Turing.ListBlank.nth_zero
@[simp]
theorem ListBlank.nth_succ {Γ} [Inhabited Γ] (l : ListBlank Γ) (n : ℕ) :
l.nth (n + 1) = l.tail.nth n := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l.tail fun l ↦ rfl
#align turing.list_blank.nth_succ Turing.ListBlank.nth_succ
@[ext]
theorem ListBlank.ext {Γ} [i : Inhabited Γ] {L₁ L₂ : ListBlank Γ} :
(∀ i, L₁.nth i = L₂.nth i) → L₁ = L₂ := by
refine ListBlank.induction_on L₁ fun l₁ ↦ ListBlank.induction_on L₂ fun l₂ H ↦ ?_
wlog h : l₁.length ≤ l₂.length
· cases le_total l₁.length l₂.length <;> [skip; symm] <;> apply this <;> try assumption
intro
rw [H]
refine Quotient.sound' (Or.inl ⟨l₂.length - l₁.length, ?_⟩)
refine List.ext_get ?_ fun i h h₂ ↦ Eq.symm ?_
· simp only [Nat.add_sub_cancel' h, List.length_append, List.length_replicate]
simp only [ListBlank.nth_mk] at H
cases' lt_or_le i l₁.length with h' h'
· simp only [List.get_append _ h', List.get?_eq_get h, List.get?_eq_get h',
← List.getI_eq_get _ h, ← List.getI_eq_get _ h', H]
· simp only [List.get_append_right' h', List.get_replicate, List.get?_eq_get h,
List.get?_len_le h', ← List.getI_eq_default _ h', H, List.getI_eq_get _ h]
#align turing.list_blank.ext Turing.ListBlank.ext
/-- Apply a function to a value stored at the nth position of the list. -/
@[simp]
def ListBlank.modifyNth {Γ} [Inhabited Γ] (f : Γ → Γ) : ℕ → ListBlank Γ → ListBlank Γ
| 0, L => L.tail.cons (f L.head)
| n + 1, L => (L.tail.modifyNth f n).cons L.head
#align turing.list_blank.modify_nth Turing.ListBlank.modifyNth
theorem ListBlank.nth_modifyNth {Γ} [Inhabited Γ] (f : Γ → Γ) (n i) (L : ListBlank Γ) :
(L.modifyNth f n).nth i = if i = n then f (L.nth i) else L.nth i := by
induction' n with n IH generalizing i L
· cases i <;> simp only [ListBlank.nth_zero, if_true, ListBlank.head_cons, ListBlank.modifyNth,
ListBlank.nth_succ, if_false, ListBlank.tail_cons, Nat.zero_eq]
· cases i
· rw [if_neg (Nat.succ_ne_zero _).symm]
simp only [ListBlank.nth_zero, ListBlank.head_cons, ListBlank.modifyNth, Nat.zero_eq]
· simp only [IH, ListBlank.modifyNth, ListBlank.nth_succ, ListBlank.tail_cons, Nat.succ.injEq]
#align turing.list_blank.nth_modify_nth Turing.ListBlank.nth_modifyNth
/-- A pointed map of `Inhabited` types is a map that sends one default value to the other. -/
structure PointedMap.{u, v} (Γ : Type u) (Γ' : Type v) [Inhabited Γ] [Inhabited Γ'] :
Type max u v where
/-- The map underlying this instance. -/
f : Γ → Γ'
map_pt' : f default = default
#align turing.pointed_map Turing.PointedMap
instance {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] : Inhabited (PointedMap Γ Γ') :=
⟨⟨default, rfl⟩⟩
instance {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] : CoeFun (PointedMap Γ Γ') fun _ ↦ Γ → Γ' :=
⟨PointedMap.f⟩
-- @[simp] -- Porting note (#10685): dsimp can prove this
theorem PointedMap.mk_val {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : Γ → Γ') (pt) :
(PointedMap.mk f pt : Γ → Γ') = f :=
rfl
#align turing.pointed_map.mk_val Turing.PointedMap.mk_val
@[simp]
theorem PointedMap.map_pt {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') :
f default = default :=
PointedMap.map_pt' _
#align turing.pointed_map.map_pt Turing.PointedMap.map_pt
@[simp]
theorem PointedMap.headI_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : List Γ) : (l.map f).headI = f l.headI := by
cases l <;> [exact (PointedMap.map_pt f).symm; rfl]
#align turing.pointed_map.head_map Turing.PointedMap.headI_map
/-- The `map` function on lists is well defined on `ListBlank`s provided that the map is
pointed. -/
def ListBlank.map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (l : ListBlank Γ) :
ListBlank Γ' := by
apply l.liftOn (fun l ↦ ListBlank.mk (List.map f l))
rintro l _ ⟨i, rfl⟩; refine Quotient.sound' (Or.inl ⟨i, ?_⟩)
simp only [PointedMap.map_pt, List.map_append, List.map_replicate]
#align turing.list_blank.map Turing.ListBlank.map
@[simp]
theorem ListBlank.map_mk {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (l : List Γ) :
(ListBlank.mk l).map f = ListBlank.mk (l.map f) :=
rfl
#align turing.list_blank.map_mk Turing.ListBlank.map_mk
@[simp]
theorem ListBlank.head_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) : (l.map f).head = f l.head := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l fun a ↦ rfl
#align turing.list_blank.head_map Turing.ListBlank.head_map
@[simp]
theorem ListBlank.tail_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) : (l.map f).tail = l.tail.map f := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l fun a ↦ rfl
#align turing.list_blank.tail_map Turing.ListBlank.tail_map
@[simp]
theorem ListBlank.map_cons {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) (a : Γ) : (l.cons a).map f = (l.map f).cons (f a) := by
refine (ListBlank.cons_head_tail _).symm.trans ?_
simp only [ListBlank.head_map, ListBlank.head_cons, ListBlank.tail_map, ListBlank.tail_cons]
#align turing.list_blank.map_cons Turing.ListBlank.map_cons
@[simp]
theorem ListBlank.nth_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) (n : ℕ) : (l.map f).nth n = f (l.nth n) := by
refine l.inductionOn fun l ↦ ?_
-- Porting note: Added `suffices` to get `simp` to work.
suffices ((mk l).map f).nth n = f ((mk l).nth n) by exact this
simp only [List.get?_map, ListBlank.map_mk, ListBlank.nth_mk, List.getI_eq_iget_get?]
cases l.get? n
· exact f.2.symm
· rfl
#align turing.list_blank.nth_map Turing.ListBlank.nth_map
/-- The `i`-th projection as a pointed map. -/
def proj {ι : Type*} {Γ : ι → Type*} [∀ i, Inhabited (Γ i)] (i : ι) :
PointedMap (∀ i, Γ i) (Γ i) :=
⟨fun a ↦ a i, rfl⟩
#align turing.proj Turing.proj
theorem proj_map_nth {ι : Type*} {Γ : ι → Type*} [∀ i, Inhabited (Γ i)] (i : ι) (L n) :
(ListBlank.map (@proj ι Γ _ i) L).nth n = L.nth n i := by
rw [ListBlank.nth_map]; rfl
#align turing.proj_map_nth Turing.proj_map_nth
theorem ListBlank.map_modifyNth {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (F : PointedMap Γ Γ')
(f : Γ → Γ) (f' : Γ' → Γ') (H : ∀ x, F (f x) = f' (F x)) (n) (L : ListBlank Γ) :
(L.modifyNth f n).map F = (L.map F).modifyNth f' n := by
induction' n with n IH generalizing L <;>
simp only [*, ListBlank.head_map, ListBlank.modifyNth, ListBlank.map_cons, ListBlank.tail_map]
#align turing.list_blank.map_modify_nth Turing.ListBlank.map_modifyNth
/-- Append a list on the left side of a `ListBlank`. -/
@[simp]
def ListBlank.append {Γ} [Inhabited Γ] : List Γ → ListBlank Γ → ListBlank Γ
| [], L => L
| a :: l, L => ListBlank.cons a (ListBlank.append l L)
#align turing.list_blank.append Turing.ListBlank.append
@[simp]
theorem ListBlank.append_mk {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) :
ListBlank.append l₁ (ListBlank.mk l₂) = ListBlank.mk (l₁ ++ l₂) := by
induction l₁ <;>
simp only [*, ListBlank.append, List.nil_append, List.cons_append, ListBlank.cons_mk]
#align turing.list_blank.append_mk Turing.ListBlank.append_mk
theorem ListBlank.append_assoc {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) (l₃ : ListBlank Γ) :
ListBlank.append (l₁ ++ l₂) l₃ = ListBlank.append l₁ (ListBlank.append l₂ l₃) := by
refine l₃.inductionOn fun l ↦ ?_
-- Porting note: Added `suffices` to get `simp` to work.
suffices append (l₁ ++ l₂) (mk l) = append l₁ (append l₂ (mk l)) by exact this
simp only [ListBlank.append_mk, List.append_assoc]
#align turing.list_blank.append_assoc Turing.ListBlank.append_assoc
/-- The `bind` function on lists is well defined on `ListBlank`s provided that the default element
is sent to a sequence of default elements. -/
def ListBlank.bind {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (l : ListBlank Γ) (f : Γ → List Γ')
(hf : ∃ n, f default = List.replicate n default) : ListBlank Γ' := by
apply l.liftOn (fun l ↦ ListBlank.mk (List.bind l f))
rintro l _ ⟨i, rfl⟩; cases' hf with n e; refine Quotient.sound' (Or.inl ⟨i * n, ?_⟩)
rw [List.append_bind, mul_comm]; congr
induction' i with i IH
· rfl
simp only [IH, e, List.replicate_add, Nat.mul_succ, add_comm, List.replicate_succ, List.cons_bind]
#align turing.list_blank.bind Turing.ListBlank.bind
@[simp]
theorem ListBlank.bind_mk {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (l : List Γ) (f : Γ → List Γ') (hf) :
(ListBlank.mk l).bind f hf = ListBlank.mk (l.bind f) :=
rfl
#align turing.list_blank.bind_mk Turing.ListBlank.bind_mk
@[simp]
theorem ListBlank.cons_bind {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (a : Γ) (l : ListBlank Γ)
(f : Γ → List Γ') (hf) : (l.cons a).bind f hf = (l.bind f hf).append (f a) := by
refine l.inductionOn fun l ↦ ?_
-- Porting note: Added `suffices` to get `simp` to work.
suffices ((mk l).cons a).bind f hf = ((mk l).bind f hf).append (f a) by exact this
simp only [ListBlank.append_mk, ListBlank.bind_mk, ListBlank.cons_mk, List.cons_bind]
#align turing.list_blank.cons_bind Turing.ListBlank.cons_bind
/-- The tape of a Turing machine is composed of a head element (which we imagine to be the
current position of the head), together with two `ListBlank`s denoting the portions of the tape
going off to the left and right. When the Turing machine moves right, an element is pulled from the
right side and becomes the new head, while the head element is `cons`ed onto the left side. -/
structure Tape (Γ : Type*) [Inhabited Γ] where
/-- The current position of the head. -/
head : Γ
/-- The portion of the tape going off to the left. -/
left : ListBlank Γ
/-- The portion of the tape going off to the right. -/
right : ListBlank Γ
#align turing.tape Turing.Tape
instance Tape.inhabited {Γ} [Inhabited Γ] : Inhabited (Tape Γ) :=
⟨by constructor <;> apply default⟩
#align turing.tape.inhabited Turing.Tape.inhabited
/-- A direction for the Turing machine `move` command, either
left or right. -/
inductive Dir
| left
| right
deriving DecidableEq, Inhabited
#align turing.dir Turing.Dir
/-- The "inclusive" left side of the tape, including both `left` and `head`. -/
def Tape.left₀ {Γ} [Inhabited Γ] (T : Tape Γ) : ListBlank Γ :=
T.left.cons T.head
#align turing.tape.left₀ Turing.Tape.left₀
/-- The "inclusive" right side of the tape, including both `right` and `head`. -/
def Tape.right₀ {Γ} [Inhabited Γ] (T : Tape Γ) : ListBlank Γ :=
T.right.cons T.head
#align turing.tape.right₀ Turing.Tape.right₀
/-- Move the tape in response to a motion of the Turing machine. Note that `T.move Dir.left` makes
`T.left` smaller; the Turing machine is moving left and the tape is moving right. -/
def Tape.move {Γ} [Inhabited Γ] : Dir → Tape Γ → Tape Γ
| Dir.left, ⟨a, L, R⟩ => ⟨L.head, L.tail, R.cons a⟩
| Dir.right, ⟨a, L, R⟩ => ⟨R.head, L.cons a, R.tail⟩
#align turing.tape.move Turing.Tape.move
@[simp]
theorem Tape.move_left_right {Γ} [Inhabited Γ] (T : Tape Γ) :
(T.move Dir.left).move Dir.right = T := by
cases T; simp [Tape.move]
#align turing.tape.move_left_right Turing.Tape.move_left_right
@[simp]
theorem Tape.move_right_left {Γ} [Inhabited Γ] (T : Tape Γ) :
(T.move Dir.right).move Dir.left = T := by
cases T; simp [Tape.move]
#align turing.tape.move_right_left Turing.Tape.move_right_left
/-- Construct a tape from a left side and an inclusive right side. -/
def Tape.mk' {Γ} [Inhabited Γ] (L R : ListBlank Γ) : Tape Γ :=
⟨R.head, L, R.tail⟩
#align turing.tape.mk' Turing.Tape.mk'
@[simp]
theorem Tape.mk'_left {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).left = L :=
rfl
#align turing.tape.mk'_left Turing.Tape.mk'_left
@[simp]
theorem Tape.mk'_head {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).head = R.head :=
rfl
#align turing.tape.mk'_head Turing.Tape.mk'_head
@[simp]
theorem Tape.mk'_right {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).right = R.tail :=
rfl
#align turing.tape.mk'_right Turing.Tape.mk'_right
@[simp]
theorem Tape.mk'_right₀ {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).right₀ = R :=
ListBlank.cons_head_tail _
#align turing.tape.mk'_right₀ Turing.Tape.mk'_right₀
@[simp]
theorem Tape.mk'_left_right₀ {Γ} [Inhabited Γ] (T : Tape Γ) : Tape.mk' T.left T.right₀ = T := by
cases T
simp only [Tape.right₀, Tape.mk', ListBlank.head_cons, ListBlank.tail_cons, eq_self_iff_true,
and_self_iff]
#align turing.tape.mk'_left_right₀ Turing.Tape.mk'_left_right₀
theorem Tape.exists_mk' {Γ} [Inhabited Γ] (T : Tape Γ) : ∃ L R, T = Tape.mk' L R :=
⟨_, _, (Tape.mk'_left_right₀ _).symm⟩
#align turing.tape.exists_mk' Turing.Tape.exists_mk'
@[simp]
theorem Tape.move_left_mk' {Γ} [Inhabited Γ] (L R : ListBlank Γ) :
(Tape.mk' L R).move Dir.left = Tape.mk' L.tail (R.cons L.head) := by
simp only [Tape.move, Tape.mk', ListBlank.head_cons, eq_self_iff_true, ListBlank.cons_head_tail,
and_self_iff, ListBlank.tail_cons]
#align turing.tape.move_left_mk' Turing.Tape.move_left_mk'
@[simp]
theorem Tape.move_right_mk' {Γ} [Inhabited Γ] (L R : ListBlank Γ) :
(Tape.mk' L R).move Dir.right = Tape.mk' (L.cons R.head) R.tail := by
simp only [Tape.move, Tape.mk', ListBlank.head_cons, eq_self_iff_true, ListBlank.cons_head_tail,
and_self_iff, ListBlank.tail_cons]
#align turing.tape.move_right_mk' Turing.Tape.move_right_mk'
/-- Construct a tape from a left side and an inclusive right side. -/
def Tape.mk₂ {Γ} [Inhabited Γ] (L R : List Γ) : Tape Γ :=
Tape.mk' (ListBlank.mk L) (ListBlank.mk R)
#align turing.tape.mk₂ Turing.Tape.mk₂
/-- Construct a tape from a list, with the head of the list at the TM head and the rest going
to the right. -/
def Tape.mk₁ {Γ} [Inhabited Γ] (l : List Γ) : Tape Γ :=
Tape.mk₂ [] l
#align turing.tape.mk₁ Turing.Tape.mk₁
/-- The `nth` function of a tape is integer-valued, with index `0` being the head, negative indexes
on the left and positive indexes on the right. (Picture a number line.) -/
def Tape.nth {Γ} [Inhabited Γ] (T : Tape Γ) : ℤ → Γ
| 0 => T.head
| (n + 1 : ℕ) => T.right.nth n
| -(n + 1 : ℕ) => T.left.nth n
#align turing.tape.nth Turing.Tape.nth
@[simp]
theorem Tape.nth_zero {Γ} [Inhabited Γ] (T : Tape Γ) : T.nth 0 = T.1 :=
rfl
#align turing.tape.nth_zero Turing.Tape.nth_zero
theorem Tape.right₀_nth {Γ} [Inhabited Γ] (T : Tape Γ) (n : ℕ) : T.right₀.nth n = T.nth n := by
cases n <;> simp only [Tape.nth, Tape.right₀, Int.ofNat_zero, ListBlank.nth_zero,
ListBlank.nth_succ, ListBlank.head_cons, ListBlank.tail_cons, Nat.zero_eq]
#align turing.tape.right₀_nth Turing.Tape.right₀_nth
@[simp]
theorem Tape.mk'_nth_nat {Γ} [Inhabited Γ] (L R : ListBlank Γ) (n : ℕ) :
(Tape.mk' L R).nth n = R.nth n := by
rw [← Tape.right₀_nth, Tape.mk'_right₀]
#align turing.tape.mk'_nth_nat Turing.Tape.mk'_nth_nat
@[simp]
theorem Tape.move_left_nth {Γ} [Inhabited Γ] :
∀ (T : Tape Γ) (i : ℤ), (T.move Dir.left).nth i = T.nth (i - 1)
| ⟨_, L, _⟩, -(n + 1 : ℕ) => (ListBlank.nth_succ _ _).symm
| ⟨_, L, _⟩, 0 => (ListBlank.nth_zero _).symm
| ⟨a, L, R⟩, 1 => (ListBlank.nth_zero _).trans (ListBlank.head_cons _ _)
| ⟨a, L, R⟩, (n + 1 : ℕ) + 1 => by
rw [add_sub_cancel_right]
change (R.cons a).nth (n + 1) = R.nth n
rw [ListBlank.nth_succ, ListBlank.tail_cons]
#align turing.tape.move_left_nth Turing.Tape.move_left_nth
@[simp]
theorem Tape.move_right_nth {Γ} [Inhabited Γ] (T : Tape Γ) (i : ℤ) :
(T.move Dir.right).nth i = T.nth (i + 1) := by
conv => rhs; rw [← T.move_right_left]
rw [Tape.move_left_nth, add_sub_cancel_right]
#align turing.tape.move_right_nth Turing.Tape.move_right_nth
@[simp]
theorem Tape.move_right_n_head {Γ} [Inhabited Γ] (T : Tape Γ) (i : ℕ) :
((Tape.move Dir.right)^[i] T).head = T.nth i := by
induction i generalizing T
· rfl
· simp only [*, Tape.move_right_nth, Int.ofNat_succ, iterate_succ, Function.comp_apply]
#align turing.tape.move_right_n_head Turing.Tape.move_right_n_head
/-- Replace the current value of the head on the tape. -/
def Tape.write {Γ} [Inhabited Γ] (b : Γ) (T : Tape Γ) : Tape Γ :=
{ T with head := b }
#align turing.tape.write Turing.Tape.write
@[simp]
theorem Tape.write_self {Γ} [Inhabited Γ] : ∀ T : Tape Γ, T.write T.1 = T := by
rintro ⟨⟩; rfl
#align turing.tape.write_self Turing.Tape.write_self
@[simp]
theorem Tape.write_nth {Γ} [Inhabited Γ] (b : Γ) :
∀ (T : Tape Γ) {i : ℤ}, (T.write b).nth i = if i = 0 then b else T.nth i
| _, 0 => rfl
| _, (_ + 1 : ℕ) => rfl
| _, -(_ + 1 : ℕ) => rfl
#align turing.tape.write_nth Turing.Tape.write_nth
@[simp]
theorem Tape.write_mk' {Γ} [Inhabited Γ] (a b : Γ) (L R : ListBlank Γ) :
(Tape.mk' L (R.cons a)).write b = Tape.mk' L (R.cons b) := by
simp only [Tape.write, Tape.mk', ListBlank.head_cons, ListBlank.tail_cons, eq_self_iff_true,
and_self_iff]
#align turing.tape.write_mk' Turing.Tape.write_mk'
/-- Apply a pointed map to a tape to change the alphabet. -/
def Tape.map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (T : Tape Γ) : Tape Γ' :=
⟨f T.1, T.2.map f, T.3.map f⟩
#align turing.tape.map Turing.Tape.map
@[simp]
theorem Tape.map_fst {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') :
∀ T : Tape Γ, (T.map f).1 = f T.1 := by
rintro ⟨⟩; rfl
#align turing.tape.map_fst Turing.Tape.map_fst
@[simp]
theorem Tape.map_write {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (b : Γ) :
∀ T : Tape Γ, (T.write b).map f = (T.map f).write (f b) := by
rintro ⟨⟩; rfl
#align turing.tape.map_write Turing.Tape.map_write
-- Porting note: `simpNF` complains about LHS does not simplify when using the simp lemma on
-- itself, but it does indeed.
@[simp, nolint simpNF]
theorem Tape.write_move_right_n {Γ} [Inhabited Γ] (f : Γ → Γ) (L R : ListBlank Γ) (n : ℕ) :
((Tape.move Dir.right)^[n] (Tape.mk' L R)).write (f (R.nth n)) =
(Tape.move Dir.right)^[n] (Tape.mk' L (R.modifyNth f n)) := by
induction' n with n IH generalizing L R
· simp only [ListBlank.nth_zero, ListBlank.modifyNth, iterate_zero_apply, Nat.zero_eq]
rw [← Tape.write_mk', ListBlank.cons_head_tail]
simp only [ListBlank.head_cons, ListBlank.nth_succ, ListBlank.modifyNth, Tape.move_right_mk',
ListBlank.tail_cons, iterate_succ_apply, IH]
#align turing.tape.write_move_right_n Turing.Tape.write_move_right_n
theorem Tape.map_move {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (T : Tape Γ) (d) :
(T.move d).map f = (T.map f).move d := by
cases T
cases d <;> simp only [Tape.move, Tape.map, ListBlank.head_map, eq_self_iff_true,
ListBlank.map_cons, and_self_iff, ListBlank.tail_map]
#align turing.tape.map_move Turing.Tape.map_move
theorem Tape.map_mk' {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (L R : ListBlank Γ) :
(Tape.mk' L R).map f = Tape.mk' (L.map f) (R.map f) := by
simp only [Tape.mk', Tape.map, ListBlank.head_map, eq_self_iff_true, and_self_iff,
ListBlank.tail_map]
#align turing.tape.map_mk' Turing.Tape.map_mk'
theorem Tape.map_mk₂ {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (L R : List Γ) :
(Tape.mk₂ L R).map f = Tape.mk₂ (L.map f) (R.map f) := by
simp only [Tape.mk₂, Tape.map_mk', ListBlank.map_mk]
#align turing.tape.map_mk₂ Turing.Tape.map_mk₂
theorem Tape.map_mk₁ {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (l : List Γ) :
(Tape.mk₁ l).map f = Tape.mk₁ (l.map f) :=
Tape.map_mk₂ _ _ _
#align turing.tape.map_mk₁ Turing.Tape.map_mk₁
/-- Run a state transition function `σ → Option σ` "to completion". The return value is the last
state returned before a `none` result. If the state transition function always returns `some`,
then the computation diverges, returning `Part.none`. -/
def eval {σ} (f : σ → Option σ) : σ → Part σ :=
PFun.fix fun s ↦ Part.some <| (f s).elim (Sum.inl s) Sum.inr
#align turing.eval Turing.eval
/-- The reflexive transitive closure of a state transition function. `Reaches f a b` means
there is a finite sequence of steps `f a = some a₁`, `f a₁ = some a₂`, ... such that `aₙ = b`.
This relation permits zero steps of the state transition function. -/
def Reaches {σ} (f : σ → Option σ) : σ → σ → Prop :=
ReflTransGen fun a b ↦ b ∈ f a
#align turing.reaches Turing.Reaches
/-- The transitive closure of a state transition function. `Reaches₁ f a b` means there is a
nonempty finite sequence of steps `f a = some a₁`, `f a₁ = some a₂`, ... such that `aₙ = b`.
This relation does not permit zero steps of the state transition function. -/
def Reaches₁ {σ} (f : σ → Option σ) : σ → σ → Prop :=
TransGen fun a b ↦ b ∈ f a
#align turing.reaches₁ Turing.Reaches₁
theorem reaches₁_eq {σ} {f : σ → Option σ} {a b c} (h : f a = f b) :
Reaches₁ f a c ↔ Reaches₁ f b c :=
TransGen.head'_iff.trans (TransGen.head'_iff.trans <| by rw [h]).symm
#align turing.reaches₁_eq Turing.reaches₁_eq
theorem reaches_total {σ} {f : σ → Option σ} {a b c} (hab : Reaches f a b) (hac : Reaches f a c) :
Reaches f b c ∨ Reaches f c b :=
ReflTransGen.total_of_right_unique (fun _ _ _ ↦ Option.mem_unique) hab hac
#align turing.reaches_total Turing.reaches_total
theorem reaches₁_fwd {σ} {f : σ → Option σ} {a b c} (h₁ : Reaches₁ f a c) (h₂ : b ∈ f a) :
Reaches f b c := by
rcases TransGen.head'_iff.1 h₁ with ⟨b', hab, hbc⟩
cases Option.mem_unique hab h₂; exact hbc
#align turing.reaches₁_fwd Turing.reaches₁_fwd
/-- A variation on `Reaches`. `Reaches₀ f a b` holds if whenever `Reaches₁ f b c` then
`Reaches₁ f a c`. This is a weaker property than `Reaches` and is useful for replacing states with
equivalent states without taking a step. -/
def Reaches₀ {σ} (f : σ → Option σ) (a b : σ) : Prop :=
∀ c, Reaches₁ f b c → Reaches₁ f a c
#align turing.reaches₀ Turing.Reaches₀
theorem Reaches₀.trans {σ} {f : σ → Option σ} {a b c : σ} (h₁ : Reaches₀ f a b)
(h₂ : Reaches₀ f b c) : Reaches₀ f a c
| _, h₃ => h₁ _ (h₂ _ h₃)
#align turing.reaches₀.trans Turing.Reaches₀.trans
@[refl]
theorem Reaches₀.refl {σ} {f : σ → Option σ} (a : σ) : Reaches₀ f a a
| _, h => h
#align turing.reaches₀.refl Turing.Reaches₀.refl
theorem Reaches₀.single {σ} {f : σ → Option σ} {a b : σ} (h : b ∈ f a) : Reaches₀ f a b
| _, h₂ => h₂.head h
#align turing.reaches₀.single Turing.Reaches₀.single
theorem Reaches₀.head {σ} {f : σ → Option σ} {a b c : σ} (h : b ∈ f a) (h₂ : Reaches₀ f b c) :
Reaches₀ f a c :=
(Reaches₀.single h).trans h₂
#align turing.reaches₀.head Turing.Reaches₀.head
theorem Reaches₀.tail {σ} {f : σ → Option σ} {a b c : σ} (h₁ : Reaches₀ f a b) (h : c ∈ f b) :
Reaches₀ f a c :=
h₁.trans (Reaches₀.single h)
#align turing.reaches₀.tail Turing.Reaches₀.tail
theorem reaches₀_eq {σ} {f : σ → Option σ} {a b} (e : f a = f b) : Reaches₀ f a b
| _, h => (reaches₁_eq e).2 h
#align turing.reaches₀_eq Turing.reaches₀_eq
theorem Reaches₁.to₀ {σ} {f : σ → Option σ} {a b : σ} (h : Reaches₁ f a b) : Reaches₀ f a b
| _, h₂ => h.trans h₂
#align turing.reaches₁.to₀ Turing.Reaches₁.to₀
theorem Reaches.to₀ {σ} {f : σ → Option σ} {a b : σ} (h : Reaches f a b) : Reaches₀ f a b
| _, h₂ => h₂.trans_right h
#align turing.reaches.to₀ Turing.Reaches.to₀
theorem Reaches₀.tail' {σ} {f : σ → Option σ} {a b c : σ} (h : Reaches₀ f a b) (h₂ : c ∈ f b) :
Reaches₁ f a c :=
h _ (TransGen.single h₂)
#align turing.reaches₀.tail' Turing.Reaches₀.tail'
/-- (co-)Induction principle for `eval`. If a property `C` holds of any point `a` evaluating to `b`
which is either terminal (meaning `a = b`) or where the next point also satisfies `C`, then it
holds of any point where `eval f a` evaluates to `b`. This formalizes the notion that if
`eval f a` evaluates to `b` then it reaches terminal state `b` in finitely many steps. -/
@[elab_as_elim]
def evalInduction {σ} {f : σ → Option σ} {b : σ} {C : σ → Sort*} {a : σ}
(h : b ∈ eval f a) (H : ∀ a, b ∈ eval f a → (∀ a', f a = some a' → C a') → C a) : C a :=
PFun.fixInduction h fun a' ha' h' ↦
H _ ha' fun b' e ↦ h' _ <| Part.mem_some_iff.2 <| by rw [e]; rfl
#align turing.eval_induction Turing.evalInduction
theorem mem_eval {σ} {f : σ → Option σ} {a b} : b ∈ eval f a ↔ Reaches f a b ∧ f b = none := by
refine ⟨fun h ↦ ?_, fun ⟨h₁, h₂⟩ ↦ ?_⟩
· -- Porting note: Explicitly specify `c`.
refine @evalInduction _ _ _ (fun a ↦ Reaches f a b ∧ f b = none) _ h fun a h IH ↦ ?_
cases' e : f a with a'
· rw [Part.mem_unique h
(PFun.mem_fix_iff.2 <| Or.inl <| Part.mem_some_iff.2 <| by rw [e] <;> rfl)]
exact ⟨ReflTransGen.refl, e⟩
· rcases PFun.mem_fix_iff.1 h with (h | ⟨_, h, _⟩) <;> rw [e] at h <;>
cases Part.mem_some_iff.1 h
cases' IH a' e with h₁ h₂
exact ⟨ReflTransGen.head e h₁, h₂⟩
· refine ReflTransGen.head_induction_on h₁ ?_ fun h _ IH ↦ ?_
· refine PFun.mem_fix_iff.2 (Or.inl ?_)
rw [h₂]
apply Part.mem_some
· refine PFun.mem_fix_iff.2 (Or.inr ⟨_, ?_, IH⟩)
rw [h]
apply Part.mem_some
#align turing.mem_eval Turing.mem_eval
theorem eval_maximal₁ {σ} {f : σ → Option σ} {a b} (h : b ∈ eval f a) (c) : ¬Reaches₁ f b c
| bc => by
let ⟨_, b0⟩ := mem_eval.1 h
let ⟨b', h', _⟩ := TransGen.head'_iff.1 bc
cases b0.symm.trans h'
#align turing.eval_maximal₁ Turing.eval_maximal₁
theorem eval_maximal {σ} {f : σ → Option σ} {a b} (h : b ∈ eval f a) {c} : Reaches f b c ↔ c = b :=
let ⟨_, b0⟩ := mem_eval.1 h
reflTransGen_iff_eq fun b' h' ↦ by cases b0.symm.trans h'
#align turing.eval_maximal Turing.eval_maximal
theorem reaches_eval {σ} {f : σ → Option σ} {a b} (ab : Reaches f a b) : eval f a = eval f b := by
refine Part.ext fun _ ↦ ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· have ⟨ac, c0⟩ := mem_eval.1 h
exact mem_eval.2 ⟨(or_iff_left_of_imp fun cb ↦ (eval_maximal h).1 cb ▸ ReflTransGen.refl).1
(reaches_total ab ac), c0⟩
· have ⟨bc, c0⟩ := mem_eval.1 h
exact mem_eval.2 ⟨ab.trans bc, c0⟩
#align turing.reaches_eval Turing.reaches_eval
/-- Given a relation `tr : σ₁ → σ₂ → Prop` between state spaces, and state transition functions
`f₁ : σ₁ → Option σ₁` and `f₂ : σ₂ → Option σ₂`, `Respects f₁ f₂ tr` means that if `tr a₁ a₂` holds
initially and `f₁` takes a step to `a₂` then `f₂` will take one or more steps before reaching a
state `b₂` satisfying `tr a₂ b₂`, and if `f₁ a₁` terminates then `f₂ a₂` also terminates.
Such a relation `tr` is also known as a refinement. -/
def Respects {σ₁ σ₂} (f₁ : σ₁ → Option σ₁) (f₂ : σ₂ → Option σ₂) (tr : σ₁ → σ₂ → Prop) :=
∀ ⦃a₁ a₂⦄, tr a₁ a₂ → (match f₁ a₁ with
| some b₁ => ∃ b₂, tr b₁ b₂ ∧ Reaches₁ f₂ a₂ b₂
| none => f₂ a₂ = none : Prop)
#align turing.respects Turing.Respects
theorem tr_reaches₁ {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) {b₁} (ab : Reaches₁ f₁ a₁ b₁) : ∃ b₂, tr b₁ b₂ ∧ Reaches₁ f₂ a₂ b₂ := by
induction' ab with c₁ ac c₁ d₁ _ cd IH
· have := H aa
rwa [show f₁ a₁ = _ from ac] at this
· rcases IH with ⟨c₂, cc, ac₂⟩
have := H cc
rw [show f₁ c₁ = _ from cd] at this
rcases this with ⟨d₂, dd, cd₂⟩
exact ⟨_, dd, ac₂.trans cd₂⟩
#align turing.tr_reaches₁ Turing.tr_reaches₁
theorem tr_reaches {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) {b₁} (ab : Reaches f₁ a₁ b₁) : ∃ b₂, tr b₁ b₂ ∧ Reaches f₂ a₂ b₂ := by
rcases reflTransGen_iff_eq_or_transGen.1 ab with (rfl | ab)
· exact ⟨_, aa, ReflTransGen.refl⟩
· have ⟨b₂, bb, h⟩ := tr_reaches₁ H aa ab
exact ⟨b₂, bb, h.to_reflTransGen⟩
#align turing.tr_reaches Turing.tr_reaches
theorem tr_reaches_rev {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) {b₂} (ab : Reaches f₂ a₂ b₂) :
∃ c₁ c₂, Reaches f₂ b₂ c₂ ∧ tr c₁ c₂ ∧ Reaches f₁ a₁ c₁ := by
induction' ab with c₂ d₂ _ cd IH
· exact ⟨_, _, ReflTransGen.refl, aa, ReflTransGen.refl⟩
· rcases IH with ⟨e₁, e₂, ce, ee, ae⟩
rcases ReflTransGen.cases_head ce with (rfl | ⟨d', cd', de⟩)
· have := H ee
revert this
cases' eg : f₁ e₁ with g₁ <;> simp only [Respects, and_imp, exists_imp]
· intro c0
cases cd.symm.trans c0
· intro g₂ gg cg
rcases TransGen.head'_iff.1 cg with ⟨d', cd', dg⟩
cases Option.mem_unique cd cd'
exact ⟨_, _, dg, gg, ae.tail eg⟩
· cases Option.mem_unique cd cd'
exact ⟨_, _, de, ee, ae⟩
#align turing.tr_reaches_rev Turing.tr_reaches_rev
theorem tr_eval {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ b₁ a₂}
(aa : tr a₁ a₂) (ab : b₁ ∈ eval f₁ a₁) : ∃ b₂, tr b₁ b₂ ∧ b₂ ∈ eval f₂ a₂ := by
cases' mem_eval.1 ab with ab b0
rcases tr_reaches H aa ab with ⟨b₂, bb, ab⟩
refine ⟨_, bb, mem_eval.2 ⟨ab, ?_⟩⟩
have := H bb; rwa [b0] at this
#align turing.tr_eval Turing.tr_eval
theorem tr_eval_rev {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ b₂ a₂}
(aa : tr a₁ a₂) (ab : b₂ ∈ eval f₂ a₂) : ∃ b₁, tr b₁ b₂ ∧ b₁ ∈ eval f₁ a₁ := by
cases' mem_eval.1 ab with ab b0
rcases tr_reaches_rev H aa ab with ⟨c₁, c₂, bc, cc, ac⟩
cases (reflTransGen_iff_eq (Option.eq_none_iff_forall_not_mem.1 b0)).1 bc
refine ⟨_, cc, mem_eval.2 ⟨ac, ?_⟩⟩
have := H cc
cases' hfc : f₁ c₁ with d₁
· rfl
rw [hfc] at this
rcases this with ⟨d₂, _, bd⟩
rcases TransGen.head'_iff.1 bd with ⟨e, h, _⟩
cases b0.symm.trans h
#align turing.tr_eval_rev Turing.tr_eval_rev
theorem tr_eval_dom {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) : (eval f₂ a₂).Dom ↔ (eval f₁ a₁).Dom :=
⟨fun h ↦
let ⟨_, _, h, _⟩ := tr_eval_rev H aa ⟨h, rfl⟩
h,
fun h ↦
let ⟨_, _, h, _⟩ := tr_eval H aa ⟨h, rfl⟩
h⟩
#align turing.tr_eval_dom Turing.tr_eval_dom
/-- A simpler version of `Respects` when the state transition relation `tr` is a function. -/
def FRespects {σ₁ σ₂} (f₂ : σ₂ → Option σ₂) (tr : σ₁ → σ₂) (a₂ : σ₂) : Option σ₁ → Prop
| some b₁ => Reaches₁ f₂ a₂ (tr b₁)
| none => f₂ a₂ = none
#align turing.frespects Turing.FRespects
theorem frespects_eq {σ₁ σ₂} {f₂ : σ₂ → Option σ₂} {tr : σ₁ → σ₂} {a₂ b₂} (h : f₂ a₂ = f₂ b₂) :
∀ {b₁}, FRespects f₂ tr a₂ b₁ ↔ FRespects f₂ tr b₂ b₁
| some b₁ => reaches₁_eq h
| none => by unfold FRespects; rw [h]
#align turing.frespects_eq Turing.frespects_eq
theorem fun_respects {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂} :
(Respects f₁ f₂ fun a b ↦ tr a = b) ↔ ∀ ⦃a₁⦄, FRespects f₂ tr (tr a₁) (f₁ a₁) :=
forall_congr' fun a₁ ↦ by
cases f₁ a₁ <;> simp only [FRespects, Respects, exists_eq_left', forall_eq']
#align turing.fun_respects Turing.fun_respects
theorem tr_eval' {σ₁ σ₂} (f₁ : σ₁ → Option σ₁) (f₂ : σ₂ → Option σ₂) (tr : σ₁ → σ₂)
(H : Respects f₁ f₂ fun a b ↦ tr a = b) (a₁) : eval f₂ (tr a₁) = tr <$> eval f₁ a₁ :=
Part.ext fun b₂ ↦
⟨fun h ↦
let ⟨b₁, bb, hb⟩ := tr_eval_rev H rfl h
(Part.mem_map_iff _).2 ⟨b₁, hb, bb⟩,
fun h ↦ by
rcases (Part.mem_map_iff _).1 h with ⟨b₁, ab, bb⟩
rcases tr_eval H rfl ab with ⟨_, rfl, h⟩
rwa [bb] at h⟩
#align turing.tr_eval' Turing.tr_eval'
/-!
## The TM0 model
A TM0 Turing machine is essentially a Post-Turing machine, adapted for type theory.
A Post-Turing machine with symbol type `Γ` and label type `Λ` is a function
`Λ → Γ → Option (Λ × Stmt)`, where a `Stmt` can be either `move left`, `move right` or `write a`
for `a : Γ`. The machine works over a "tape", a doubly-infinite sequence of elements of `Γ`, and
an instantaneous configuration, `Cfg`, is a label `q : Λ` indicating the current internal state of
the machine, and a `Tape Γ` (which is essentially `ℤ →₀ Γ`). The evolution is described by the
`step` function:
* If `M q T.head = none`, then the machine halts.
* If `M q T.head = some (q', s)`, then the machine performs action `s : Stmt` and then transitions
to state `q'`.
The initial state takes a `List Γ` and produces a `Tape Γ` where the head of the list is the head
of the tape and the rest of the list extends to the right, with the left side all blank. The final
state takes the entire right side of the tape right or equal to the current position of the
machine. (This is actually a `ListBlank Γ`, not a `List Γ`, because we don't know, at this level
of generality, where the output ends. If equality to `default : Γ` is decidable we can trim the list
to remove the infinite tail of blanks.)
-/
namespace TM0
set_option linter.uppercaseLean3 false -- for "TM0"
section
-- type of tape symbols
variable (Γ : Type*) [Inhabited Γ]
-- type of "labels" or TM states
variable (Λ : Type*) [Inhabited Λ]
/-- A Turing machine "statement" is just a command to either move
left or right, or write a symbol on the tape. -/
inductive Stmt
| move : Dir → Stmt
| write : Γ → Stmt
#align turing.TM0.stmt Turing.TM0.Stmt
local notation "Stmt₀" => Stmt Γ -- Porting note (#10750): added this to clean up types.
instance Stmt.inhabited : Inhabited Stmt₀ :=
⟨Stmt.write default⟩
#align turing.TM0.stmt.inhabited Turing.TM0.Stmt.inhabited
/-- A Post-Turing machine with symbol type `Γ` and label type `Λ`
is a function which, given the current state `q : Λ` and
the tape head `a : Γ`, either halts (returns `none`) or returns
a new state `q' : Λ` and a `Stmt` describing what to do,
either a move left or right, or a write command.
Both `Λ` and `Γ` are required to be inhabited; the default value
for `Γ` is the "blank" tape value, and the default value of `Λ` is
the initial state. -/
@[nolint unusedArguments] -- this is a deliberate addition, see comment
def Machine [Inhabited Λ] :=
Λ → Γ → Option (Λ × Stmt₀)
#align turing.TM0.machine Turing.TM0.Machine
local notation "Machine₀" => Machine Γ Λ -- Porting note (#10750): added this to clean up types.
instance Machine.inhabited : Inhabited Machine₀ := by
unfold Machine; infer_instance
#align turing.TM0.machine.inhabited Turing.TM0.Machine.inhabited
/-- The configuration state of a Turing machine during operation
consists of a label (machine state), and a tape.
The tape is represented in the form `(a, L, R)`, meaning the tape looks like `L.rev ++ [a] ++ R`
with the machine currently reading the `a`. The lists are
automatically extended with blanks as the machine moves around. -/
structure Cfg where
/-- The current machine state. -/
q : Λ
/-- The current state of the tape: current symbol, left and right parts. -/
Tape : Tape Γ
#align turing.TM0.cfg Turing.TM0.Cfg
local notation "Cfg₀" => Cfg Γ Λ -- Porting note (#10750): added this to clean up types.
instance Cfg.inhabited : Inhabited Cfg₀ :=
⟨⟨default, default⟩⟩
#align turing.TM0.cfg.inhabited Turing.TM0.Cfg.inhabited
variable {Γ Λ}
/-- Execution semantics of the Turing machine. -/
def step (M : Machine₀) : Cfg₀ → Option Cfg₀ :=
fun ⟨q, T⟩ ↦ (M q T.1).map fun ⟨q', a⟩ ↦ ⟨q', match a with
| Stmt.move d => T.move d
| Stmt.write a => T.write a⟩
#align turing.TM0.step Turing.TM0.step
/-- The statement `Reaches M s₁ s₂` means that `s₂` is obtained
starting from `s₁` after a finite number of steps from `s₂`. -/
def Reaches (M : Machine₀) : Cfg₀ → Cfg₀ → Prop :=
ReflTransGen fun a b ↦ b ∈ step M a
#align turing.TM0.reaches Turing.TM0.Reaches
/-- The initial configuration. -/
def init (l : List Γ) : Cfg₀ :=
⟨default, Tape.mk₁ l⟩
#align turing.TM0.init Turing.TM0.init
/-- Evaluate a Turing machine on initial input to a final state,
if it terminates. -/
def eval (M : Machine₀) (l : List Γ) : Part (ListBlank Γ) :=
(Turing.eval (step M) (init l)).map fun c ↦ c.Tape.right₀
#align turing.TM0.eval Turing.TM0.eval
/-- The raw definition of a Turing machine does not require that
`Γ` and `Λ` are finite, and in practice we will be interested
in the infinite `Λ` case. We recover instead a notion of
"effectively finite" Turing machines, which only make use of a
finite subset of their states. We say that a set `S ⊆ Λ`
supports a Turing machine `M` if `S` is closed under the
transition function and contains the initial state. -/
def Supports (M : Machine₀) (S : Set Λ) :=
default ∈ S ∧ ∀ {q a q' s}, (q', s) ∈ M q a → q ∈ S → q' ∈ S
#align turing.TM0.supports Turing.TM0.Supports
theorem step_supports (M : Machine₀) {S : Set Λ} (ss : Supports M S) :
∀ {c c' : Cfg₀}, c' ∈ step M c → c.q ∈ S → c'.q ∈ S := by
intro ⟨q, T⟩ c' h₁ h₂
rcases Option.map_eq_some'.1 h₁ with ⟨⟨q', a⟩, h, rfl⟩
exact ss.2 h h₂
#align turing.TM0.step_supports Turing.TM0.step_supports
theorem univ_supports (M : Machine₀) : Supports M Set.univ := by
constructor <;> intros <;> apply Set.mem_univ
#align turing.TM0.univ_supports Turing.TM0.univ_supports
end
section
variable {Γ : Type*} [Inhabited Γ]
variable {Γ' : Type*} [Inhabited Γ']
variable {Λ : Type*} [Inhabited Λ]
variable {Λ' : Type*} [Inhabited Λ']
/-- Map a TM statement across a function. This does nothing to move statements and maps the write
values. -/
def Stmt.map (f : PointedMap Γ Γ') : Stmt Γ → Stmt Γ'
| Stmt.move d => Stmt.move d
| Stmt.write a => Stmt.write (f a)
#align turing.TM0.stmt.map Turing.TM0.Stmt.map
/-- Map a configuration across a function, given `f : Γ → Γ'` a map of the alphabets and
`g : Λ → Λ'` a map of the machine states. -/
def Cfg.map (f : PointedMap Γ Γ') (g : Λ → Λ') : Cfg Γ Λ → Cfg Γ' Λ'
| ⟨q, T⟩ => ⟨g q, T.map f⟩
#align turing.TM0.cfg.map Turing.TM0.Cfg.map
variable (M : Machine Γ Λ) (f₁ : PointedMap Γ Γ') (f₂ : PointedMap Γ' Γ) (g₁ : Λ → Λ') (g₂ : Λ' → Λ)
/-- Because the state transition function uses the alphabet and machine states in both the input
and output, to map a machine from one alphabet and machine state space to another we need functions
in both directions, essentially an `Equiv` without the laws. -/
def Machine.map : Machine Γ' Λ'
| q, l => (M (g₂ q) (f₂ l)).map (Prod.map g₁ (Stmt.map f₁))
#align turing.TM0.machine.map Turing.TM0.Machine.map
theorem Machine.map_step {S : Set Λ} (f₂₁ : Function.RightInverse f₁ f₂)
(g₂₁ : ∀ q ∈ S, g₂ (g₁ q) = q) :
∀ c : Cfg Γ Λ,
c.q ∈ S → (step M c).map (Cfg.map f₁ g₁) = step (M.map f₁ f₂ g₁ g₂) (Cfg.map f₁ g₁ c)
| ⟨q, T⟩, h => by
unfold step Machine.map Cfg.map
simp only [Turing.Tape.map_fst, g₂₁ q h, f₂₁ _]
rcases M q T.1 with (_ | ⟨q', d | a⟩); · rfl
· simp only [step, Cfg.map, Option.map_some', Tape.map_move f₁]
rfl
· simp only [step, Cfg.map, Option.map_some', Tape.map_write]
rfl
#align turing.TM0.machine.map_step Turing.TM0.Machine.map_step
theorem map_init (g₁ : PointedMap Λ Λ') (l : List Γ) : (init l).map f₁ g₁ = init (l.map f₁) :=
congr (congr_arg Cfg.mk g₁.map_pt) (Tape.map_mk₁ _ _)
#align turing.TM0.map_init Turing.TM0.map_init
theorem Machine.map_respects (g₁ : PointedMap Λ Λ') (g₂ : Λ' → Λ) {S} (ss : Supports M S)
(f₂₁ : Function.RightInverse f₁ f₂) (g₂₁ : ∀ q ∈ S, g₂ (g₁ q) = q) :
Respects (step M) (step (M.map f₁ f₂ g₁ g₂)) fun a b ↦ a.q ∈ S ∧ Cfg.map f₁ g₁ a = b := by
intro c _ ⟨cs, rfl⟩
cases e : step M c
· rw [← M.map_step f₁ f₂ g₁ g₂ f₂₁ g₂₁ _ cs, e]
rfl
· refine ⟨_, ⟨step_supports M ss e cs, rfl⟩, TransGen.single ?_⟩
rw [← M.map_step f₁ f₂ g₁ g₂ f₂₁ g₂₁ _ cs, e]
rfl
#align turing.TM0.machine.map_respects Turing.TM0.Machine.map_respects
end
end TM0
/-!
## The TM1 model
The TM1 model is a simplification and extension of TM0 (Post-Turing model) in the direction of
Wang B-machines. The machine's internal state is extended with a (finite) store `σ` of variables
that may be accessed and updated at any time.
A machine is given by a `Λ` indexed set of procedures or functions. Each function has a body which
is a `Stmt`. Most of the regular commands are allowed to use the current value `a` of the local
variables and the value `T.head` on the tape to calculate what to write or how to change local
state, but the statements themselves have a fixed structure. The `Stmt`s can be as follows:
* `move d q`: move left or right, and then do `q`
* `write (f : Γ → σ → Γ) q`: write `f a T.head` to the tape, then do `q`
* `load (f : Γ → σ → σ) q`: change the internal state to `f a T.head`
* `branch (f : Γ → σ → Bool) qtrue qfalse`: If `f a T.head` is true, do `qtrue`, else `qfalse`
* `goto (f : Γ → σ → Λ)`: Go to label `f a T.head`
* `halt`: Transition to the halting state, which halts on the following step
Note that here most statements do not have labels; `goto` commands can only go to a new function.
Only the `goto` and `halt` statements actually take a step; the rest is done by recursion on
statements and so take 0 steps. (There is a uniform bound on how many statements can be executed
before the next `goto`, so this is an `O(1)` speedup with the constant depending on the machine.)
The `halt` command has a one step stutter before actually halting so that any changes made before
the halt have a chance to be "committed", since the `eval` relation uses the final configuration
before the halt as the output, and `move` and `write` etc. take 0 steps in this model.
-/
namespace TM1
set_option linter.uppercaseLean3 false -- for "TM1"
section
variable (Γ : Type*) [Inhabited Γ]
-- Type of tape symbols
variable (Λ : Type*)
-- Type of function labels
variable (σ : Type*)
-- Type of variable settings
/-- The TM1 model is a simplification and extension of TM0
(Post-Turing model) in the direction of Wang B-machines. The machine's
internal state is extended with a (finite) store `σ` of variables
that may be accessed and updated at any time.
A machine is given by a `Λ` indexed set of procedures or functions.
Each function has a body which is a `Stmt`, which can either be a
`move` or `write` command, a `branch` (if statement based on the
current tape value), a `load` (set the variable value),
a `goto` (call another function), or `halt`. Note that here
most statements do not have labels; `goto` commands can only
go to a new function. All commands have access to the variable value
and current tape value. -/
inductive Stmt
| move : Dir → Stmt → Stmt
| write : (Γ → σ → Γ) → Stmt → Stmt
| load : (Γ → σ → σ) → Stmt → Stmt
| branch : (Γ → σ → Bool) → Stmt → Stmt → Stmt
| goto : (Γ → σ → Λ) → Stmt
| halt : Stmt
#align turing.TM1.stmt Turing.TM1.Stmt
local notation "Stmt₁" => Stmt Γ Λ σ -- Porting note (#10750): added this to clean up types.
open Stmt
instance Stmt.inhabited : Inhabited Stmt₁ :=
⟨halt⟩
#align turing.TM1.stmt.inhabited Turing.TM1.Stmt.inhabited
/-- The configuration of a TM1 machine is given by the currently
evaluating statement, the variable store value, and the tape. -/
structure Cfg where
/-- The statement (if any) which is currently evaluated -/
l : Option Λ
/-- The current value of the variable store -/
var : σ
/-- The current state of the tape -/
Tape : Tape Γ
#align turing.TM1.cfg Turing.TM1.Cfg
local notation "Cfg₁" => Cfg Γ Λ σ -- Porting note (#10750): added this to clean up types.
instance Cfg.inhabited [Inhabited σ] : Inhabited Cfg₁ :=
⟨⟨default, default, default⟩⟩
#align turing.TM1.cfg.inhabited Turing.TM1.Cfg.inhabited
variable {Γ Λ σ}
/-- The semantics of TM1 evaluation. -/
def stepAux : Stmt₁ → σ → Tape Γ → Cfg₁
| move d q, v, T => stepAux q v (T.move d)
| write a q, v, T => stepAux q v (T.write (a T.1 v))
| load s q, v, T => stepAux q (s T.1 v) T
| branch p q₁ q₂, v, T => cond (p T.1 v) (stepAux q₁ v T) (stepAux q₂ v T)
| goto l, v, T => ⟨some (l T.1 v), v, T⟩
| halt, v, T => ⟨none, v, T⟩
#align turing.TM1.step_aux Turing.TM1.stepAux
/-- The state transition function. -/
def step (M : Λ → Stmt₁) : Cfg₁ → Option Cfg₁
| ⟨none, _, _⟩ => none
| ⟨some l, v, T⟩ => some (stepAux (M l) v T)
#align turing.TM1.step Turing.TM1.step
/-- A set `S` of labels supports the statement `q` if all the `goto`
statements in `q` refer only to other functions in `S`. -/
def SupportsStmt (S : Finset Λ) : Stmt₁ → Prop
| move _ q => SupportsStmt S q
| write _ q => SupportsStmt S q
| load _ q => SupportsStmt S q
| branch _ q₁ q₂ => SupportsStmt S q₁ ∧ SupportsStmt S q₂
| goto l => ∀ a v, l a v ∈ S
| halt => True
#align turing.TM1.supports_stmt Turing.TM1.SupportsStmt
open scoped Classical
/-- The subterm closure of a statement. -/
noncomputable def stmts₁ : Stmt₁ → Finset Stmt₁
| Q@(move _ q) => insert Q (stmts₁ q)
| Q@(write _ q) => insert Q (stmts₁ q)
| Q@(load _ q) => insert Q (stmts₁ q)
| Q@(branch _ q₁ q₂) => insert Q (stmts₁ q₁ ∪ stmts₁ q₂)
| Q => {Q}
#align turing.TM1.stmts₁ Turing.TM1.stmts₁
theorem stmts₁_self {q : Stmt₁} : q ∈ stmts₁ q := by
cases q <;> simp only [stmts₁, Finset.mem_insert_self, Finset.mem_singleton_self]
#align turing.TM1.stmts₁_self Turing.TM1.stmts₁_self
theorem stmts₁_trans {q₁ q₂ : Stmt₁} : q₁ ∈ stmts₁ q₂ → stmts₁ q₁ ⊆ stmts₁ q₂ := by
intro h₁₂ q₀ h₀₁
induction q₂ with (
simp only [stmts₁] at h₁₂ ⊢
simp only [Finset.mem_insert, Finset.mem_union, Finset.mem_singleton] at h₁₂)
| branch p q₁ q₂ IH₁ IH₂ =>
rcases h₁₂ with (rfl | h₁₂ | h₁₂)
· unfold stmts₁ at h₀₁
exact h₀₁
· exact Finset.mem_insert_of_mem (Finset.mem_union_left _ <| IH₁ h₁₂)
· exact Finset.mem_insert_of_mem (Finset.mem_union_right _ <| IH₂ h₁₂)
| goto l => subst h₁₂; exact h₀₁
| halt => subst h₁₂; exact h₀₁
| _ _ q IH =>
rcases h₁₂ with rfl | h₁₂
· exact h₀₁
· exact Finset.mem_insert_of_mem (IH h₁₂)
#align turing.TM1.stmts₁_trans Turing.TM1.stmts₁_trans
theorem stmts₁_supportsStmt_mono {S : Finset Λ} {q₁ q₂ : Stmt₁} (h : q₁ ∈ stmts₁ q₂)
(hs : SupportsStmt S q₂) : SupportsStmt S q₁ := by
induction q₂ with
simp only [stmts₁, SupportsStmt, Finset.mem_insert, Finset.mem_union, Finset.mem_singleton]
at h hs
| branch p q₁ q₂ IH₁ IH₂ => rcases h with (rfl | h | h); exacts [hs, IH₁ h hs.1, IH₂ h hs.2]
| goto l => subst h; exact hs
| halt => subst h; trivial
| _ _ q IH => rcases h with (rfl | h) <;> [exact hs; exact IH h hs]
#align turing.TM1.stmts₁_supports_stmt_mono Turing.TM1.stmts₁_supportsStmt_mono
/-- The set of all statements in a Turing machine, plus one extra value `none` representing the
halt state. This is used in the TM1 to TM0 reduction. -/
noncomputable def stmts (M : Λ → Stmt₁) (S : Finset Λ) : Finset (Option Stmt₁) :=
Finset.insertNone (S.biUnion fun q ↦ stmts₁ (M q))
#align turing.TM1.stmts Turing.TM1.stmts
theorem stmts_trans {M : Λ → Stmt₁} {S : Finset Λ} {q₁ q₂ : Stmt₁} (h₁ : q₁ ∈ stmts₁ q₂) :
some q₂ ∈ stmts M S → some q₁ ∈ stmts M S := by
simp only [stmts, Finset.mem_insertNone, Finset.mem_biUnion, Option.mem_def, Option.some.injEq,
forall_eq', exists_imp, and_imp]
exact fun l ls h₂ ↦ ⟨_, ls, stmts₁_trans h₂ h₁⟩
#align turing.TM1.stmts_trans Turing.TM1.stmts_trans
variable [Inhabited Λ]
/-- A set `S` of labels supports machine `M` if all the `goto`
statements in the functions in `S` refer only to other functions
in `S`. -/
def Supports (M : Λ → Stmt₁) (S : Finset Λ) :=
default ∈ S ∧ ∀ q ∈ S, SupportsStmt S (M q)
#align turing.TM1.supports Turing.TM1.Supports
theorem stmts_supportsStmt {M : Λ → Stmt₁} {S : Finset Λ} {q : Stmt₁} (ss : Supports M S) :
some q ∈ stmts M S → SupportsStmt S q := by
simp only [stmts, Finset.mem_insertNone, Finset.mem_biUnion, Option.mem_def, Option.some.injEq,
forall_eq', exists_imp, and_imp]
exact fun l ls h ↦ stmts₁_supportsStmt_mono h (ss.2 _ ls)
#align turing.TM1.stmts_supports_stmt Turing.TM1.stmts_supportsStmt
theorem step_supports (M : Λ → Stmt₁) {S : Finset Λ} (ss : Supports M S) :
∀ {c c' : Cfg₁}, c' ∈ step M c → c.l ∈ Finset.insertNone S → c'.l ∈ Finset.insertNone S
| ⟨some l₁, v, T⟩, c', h₁, h₂ => by
replace h₂ := ss.2 _ (Finset.some_mem_insertNone.1 h₂)
simp only [step, Option.mem_def, Option.some.injEq] at h₁; subst c'
revert h₂; induction M l₁ generalizing v T with intro hs
| branch p q₁' q₂' IH₁ IH₂ =>
unfold stepAux; cases p T.1 v
· exact IH₂ _ _ hs.2
· exact IH₁ _ _ hs.1
| goto => exact Finset.some_mem_insertNone.2 (hs _ _)
| halt => apply Multiset.mem_cons_self
| _ _ q IH => exact IH _ _ hs
#align turing.TM1.step_supports Turing.TM1.step_supports
variable [Inhabited σ]
/-- The initial state, given a finite input that is placed on the tape starting at the TM head and
going to the right. -/
def init (l : List Γ) : Cfg₁ :=
⟨some default, default, Tape.mk₁ l⟩
#align turing.TM1.init Turing.TM1.init
/-- Evaluate a TM to completion, resulting in an output list on the tape (with an indeterminate
number of blanks on the end). -/
def eval (M : Λ → Stmt₁) (l : List Γ) : Part (ListBlank Γ) :=
(Turing.eval (step M) (init l)).map fun c ↦ c.Tape.right₀
#align turing.TM1.eval Turing.TM1.eval
end
end TM1
/-!
## TM1 emulator in TM0
To prove that TM1 computable functions are TM0 computable, we need to reduce each TM1 program to a
TM0 program. So suppose a TM1 program is given. We take the following:
* The alphabet `Γ` is the same for both TM1 and TM0
* The set of states `Λ'` is defined to be `Option Stmt₁ × σ`, that is, a TM1 statement or `none`
representing halt, and the possible settings of the internal variables.
Note that this is an infinite set, because `Stmt₁` is infinite. This is okay because we assume
that from the initial TM1 state, only finitely many other labels are reachable, and there are
only finitely many statements that appear in all of these functions.
Even though `Stmt₁` contains a statement called `halt`, we must separate it from `none`
(`some halt` steps to `none` and `none` actually halts) because there is a one step stutter in the
TM1 semantics.
-/
namespace TM1to0
set_option linter.uppercaseLean3 false -- for "TM1to0"
section
variable {Γ : Type*} [Inhabited Γ]
variable {Λ : Type*} [Inhabited Λ]
variable {σ : Type*} [Inhabited σ]
local notation "Stmt₁" => TM1.Stmt Γ Λ σ
local notation "Cfg₁" => TM1.Cfg Γ Λ σ
local notation "Stmt₀" => TM0.Stmt Γ
variable (M : Λ → TM1.Stmt Γ Λ σ) -- Porting note: Unfolded `Stmt₁`.
-- Porting note: `Inhabited`s are not necessary, but `M` is necessary.
set_option linter.unusedVariables false in
/-- The base machine state space is a pair of an `Option Stmt₁` representing the current program
to be executed, or `none` for the halt state, and a `σ` which is the local state (stored in the TM,
not the tape). Because there are an infinite number of programs, this state space is infinite, but
for a finitely supported TM1 machine and a finite type `σ`, only finitely many of these states are
reachable. -/
@[nolint unusedArguments] -- We need the M assumption
def Λ' (M : Λ → TM1.Stmt Γ Λ σ) :=
Option Stmt₁ × σ
#align turing.TM1to0.Λ' Turing.TM1to0.Λ'
local notation "Λ'₁₀" => Λ' M -- Porting note (#10750): added this to clean up types.
instance : Inhabited Λ'₁₀ :=
⟨(some (M default), default)⟩
open TM0.Stmt
/-- The core TM1 → TM0 translation function. Here `s` is the current value on the tape, and the
`Stmt₁` is the TM1 statement to translate, with local state `v : σ`. We evaluate all regular
instructions recursively until we reach either a `move` or `write` command, or a `goto`; in the
latter case we emit a dummy `write s` step and transition to the new target location. -/
def trAux (s : Γ) : Stmt₁ → σ → Λ'₁₀ × Stmt₀
| TM1.Stmt.move d q, v => ((some q, v), move d)
| TM1.Stmt.write a q, v => ((some q, v), write (a s v))
| TM1.Stmt.load a q, v => trAux s q (a s v)
| TM1.Stmt.branch p q₁ q₂, v => cond (p s v) (trAux s q₁ v) (trAux s q₂ v)
| TM1.Stmt.goto l, v => ((some (M (l s v)), v), write s)
| TM1.Stmt.halt, v => ((none, v), write s)
#align turing.TM1to0.tr_aux Turing.TM1to0.trAux
local notation "Cfg₁₀" => TM0.Cfg Γ Λ'₁₀
/-- The translated TM0 machine (given the TM1 machine input). -/
def tr : TM0.Machine Γ Λ'₁₀
| (none, _), _ => none
| (some q, v), s => some (trAux M s q v)
#align turing.TM1to0.tr Turing.TM1to0.tr
/-- Translate configurations from TM1 to TM0. -/
def trCfg : Cfg₁ → Cfg₁₀
| ⟨l, v, T⟩ => ⟨(l.map M, v), T⟩
#align turing.TM1to0.tr_cfg Turing.TM1to0.trCfg
theorem tr_respects :
Respects (TM1.step M) (TM0.step (tr M)) fun (c₁ : Cfg₁) (c₂ : Cfg₁₀) ↦ trCfg M c₁ = c₂ :=
fun_respects.2 fun ⟨l₁, v, T⟩ ↦ by
cases' l₁ with l₁; · exact rfl
simp only [trCfg, TM1.step, FRespects, Option.map]
induction M l₁ generalizing v T with
| move _ _ IH => exact TransGen.head rfl (IH _ _)
| write _ _ IH => exact TransGen.head rfl (IH _ _)
| load _ _ IH => exact (reaches₁_eq (by rfl)).2 (IH _ _)
| branch p _ _ IH₁ IH₂ =>
unfold TM1.stepAux; cases e : p T.1 v
· exact (reaches₁_eq (by simp only [TM0.step, tr, trAux, e]; rfl)).2 (IH₂ _ _)
· exact (reaches₁_eq (by simp only [TM0.step, tr, trAux, e]; rfl)).2 (IH₁ _ _)
| _ =>
exact TransGen.single (congr_arg some (congr (congr_arg TM0.Cfg.mk rfl) (Tape.write_self T)))
#align turing.TM1to0.tr_respects Turing.TM1to0.tr_respects
theorem tr_eval (l : List Γ) : TM0.eval (tr M) l = TM1.eval M l :=
(congr_arg _ (tr_eval' _ _ _ (tr_respects M) ⟨some _, _, _⟩)).trans
(by
rw [Part.map_eq_map, Part.map_map, TM1.eval]
congr with ⟨⟩)
#align turing.TM1to0.tr_eval Turing.TM1to0.tr_eval
variable [Fintype σ]
/-- Given a finite set of accessible `Λ` machine states, there is a finite set of accessible
machine states in the target (even though the type `Λ'` is infinite). -/
noncomputable def trStmts (S : Finset Λ) : Finset Λ'₁₀ :=
(TM1.stmts M S) ×ˢ Finset.univ
#align turing.TM1to0.tr_stmts Turing.TM1to0.trStmts
open scoped Classical
attribute [local simp] TM1.stmts₁_self
theorem tr_supports {S : Finset Λ} (ss : TM1.Supports M S) :
TM0.Supports (tr M) ↑(trStmts M S) := by
constructor
· apply Finset.mem_product.2
constructor
· simp only [default, TM1.stmts, Finset.mem_insertNone, Option.mem_def, Option.some_inj,
forall_eq', Finset.mem_biUnion]
exact ⟨_, ss.1, TM1.stmts₁_self⟩
· apply Finset.mem_univ
· intro q a q' s h₁ h₂
rcases q with ⟨_ | q, v⟩; · cases h₁
cases' q' with q' v'
simp only [trStmts, Finset.mem_coe] at h₂ ⊢
rw [Finset.mem_product] at h₂ ⊢
simp only [Finset.mem_univ, and_true_iff] at h₂ ⊢
cases q'; · exact Multiset.mem_cons_self _ _
simp only [tr, Option.mem_def] at h₁
have := TM1.stmts_supportsStmt ss h₂
revert this; induction q generalizing v with intro hs
| move d q =>
cases h₁; refine TM1.stmts_trans ?_ h₂
unfold TM1.stmts₁
exact Finset.mem_insert_of_mem TM1.stmts₁_self
| write b q =>
cases h₁; refine TM1.stmts_trans ?_ h₂
unfold TM1.stmts₁
exact Finset.mem_insert_of_mem TM1.stmts₁_self
| load b q IH =>
refine IH _ (TM1.stmts_trans ?_ h₂) h₁ hs
unfold TM1.stmts₁
exact Finset.mem_insert_of_mem TM1.stmts₁_self
| branch p q₁ q₂ IH₁ IH₂ =>
cases h : p a v <;> rw [trAux, h] at h₁
· refine IH₂ _ (TM1.stmts_trans ?_ h₂) h₁ hs.2
unfold TM1.stmts₁
exact Finset.mem_insert_of_mem (Finset.mem_union_right _ TM1.stmts₁_self)
· refine IH₁ _ (TM1.stmts_trans ?_ h₂) h₁ hs.1
unfold TM1.stmts₁
exact Finset.mem_insert_of_mem (Finset.mem_union_left _ TM1.stmts₁_self)
| goto l =>
cases h₁
exact Finset.some_mem_insertNone.2 (Finset.mem_biUnion.2 ⟨_, hs _ _, TM1.stmts₁_self⟩)
| halt => cases h₁
#align turing.TM1to0.tr_supports Turing.TM1to0.tr_supports
end
end TM1to0
/-!
## TM1(Γ) emulator in TM1(Bool)
The most parsimonious Turing machine model that is still Turing complete is `TM0` with `Γ = Bool`.
Because our construction in the previous section reducing `TM1` to `TM0` doesn't change the
alphabet, we can do the alphabet reduction on `TM1` instead of `TM0` directly.
The basic idea is to use a bijection between `Γ` and a subset of `Vector Bool n`, where `n` is a
fixed constant. Each tape element is represented as a block of `n` bools. Whenever the machine
wants to read a symbol from the tape, it traverses over the block, performing `n` `branch`
instructions to each any of the `2^n` results.
For the `write` instruction, we have to use a `goto` because we need to follow a different code
path depending on the local state, which is not available in the TM1 model, so instead we jump to
a label computed using the read value and the local state, which performs the writing and returns
to normal execution.
Emulation overhead is `O(1)`. If not for the above `write` behavior it would be 1-1 because we are
exploiting the 0-step behavior of regular commands to avoid taking steps, but there are
nevertheless a bounded number of `write` calls between `goto` statements because TM1 statements are
finitely long.
-/
namespace TM1to1
set_option linter.uppercaseLean3 false -- for "TM1to1"
open TM1
section
variable {Γ : Type*} [Inhabited Γ]
theorem exists_enc_dec [Finite Γ] : ∃ (n : ℕ) (enc : Γ → Vector Bool n) (dec : Vector Bool n → Γ),
enc default = Vector.replicate n false ∧ ∀ a, dec (enc a) = a := by
rcases Finite.exists_equiv_fin Γ with ⟨n, ⟨e⟩⟩
letI : DecidableEq Γ := e.decidableEq
let G : Fin n ↪ Fin n → Bool :=
⟨fun a b ↦ a = b, fun a b h ↦
Bool.of_decide_true <| (congr_fun h b).trans <| Bool.decide_true rfl⟩
let H := (e.toEmbedding.trans G).trans (Equiv.vectorEquivFin _ _).symm.toEmbedding
let enc := H.setValue default (Vector.replicate n false)
exact ⟨_, enc, Function.invFun enc, H.setValue_eq _ _, Function.leftInverse_invFun enc.2⟩
#align turing.TM1to1.exists_enc_dec Turing.TM1to1.exists_enc_dec
variable {Λ : Type*} [Inhabited Λ]
variable {σ : Type*} [Inhabited σ]
local notation "Stmt₁" => Stmt Γ Λ σ
local notation "Cfg₁" => Cfg Γ Λ σ
/-- The configuration state of the TM. -/
inductive Λ'
| normal : Λ → Λ'
| write : Γ → Stmt₁ → Λ'
#align turing.TM1to1.Λ' Turing.TM1to1.Λ'
local notation "Λ'₁" => @Λ' Γ Λ σ -- Porting note (#10750): added this to clean up types.
instance : Inhabited Λ'₁ :=
⟨Λ'.normal default⟩
local notation "Stmt'₁" => Stmt Bool Λ'₁ σ
local notation "Cfg'₁" => Cfg Bool Λ'₁ σ
/-- Read a vector of length `n` from the tape. -/
def readAux : ∀ n, (Vector Bool n → Stmt'₁) → Stmt'₁
| 0, f => f Vector.nil
| i + 1, f =>
Stmt.branch (fun a _ ↦ a) (Stmt.move Dir.right <| readAux i fun v ↦ f (true ::ᵥ v))
(Stmt.move Dir.right <| readAux i fun v ↦ f (false ::ᵥ v))
#align turing.TM1to1.read_aux Turing.TM1to1.readAux
variable {n : ℕ} (enc : Γ → Vector Bool n) (dec : Vector Bool n → Γ)
/-- A move left or right corresponds to `n` moves across the super-cell. -/
def move (d : Dir) (q : Stmt'₁) : Stmt'₁ :=
(Stmt.move d)^[n] q
#align turing.TM1to1.move Turing.TM1to1.move
local notation "moveₙ" => @move Γ Λ σ n -- Porting note (#10750): added this to clean up types.
/-- To read a symbol from the tape, we use `readAux` to traverse the symbol,
then return to the original position with `n` moves to the left. -/
def read (f : Γ → Stmt'₁) : Stmt'₁ :=
readAux n fun v ↦ moveₙ Dir.left <| f (dec v)
#align turing.TM1to1.read Turing.TM1to1.read
/-- Write a list of bools on the tape. -/
def write : List Bool → Stmt'₁ → Stmt'₁
| [], q => q
| a :: l, q => (Stmt.write fun _ _ ↦ a) <| Stmt.move Dir.right <| write l q
#align turing.TM1to1.write Turing.TM1to1.write
/-- Translate a normal instruction. For the `write` command, we use a `goto` indirection so that
we can access the current value of the tape. -/
def trNormal : Stmt₁ → Stmt'₁
| Stmt.move d q => moveₙ d <| trNormal q
| Stmt.write f q => read dec fun a ↦ Stmt.goto fun _ s ↦ Λ'.write (f a s) q
| Stmt.load f q => read dec fun a ↦ (Stmt.load fun _ s ↦ f a s) <| trNormal q
| Stmt.branch p q₁ q₂ =>
read dec fun a ↦ Stmt.branch (fun _ s ↦ p a s) (trNormal q₁) (trNormal q₂)
| Stmt.goto l => read dec fun a ↦ Stmt.goto fun _ s ↦ Λ'.normal (l a s)
| Stmt.halt => Stmt.halt
#align turing.TM1to1.tr_normal Turing.TM1to1.trNormal
theorem stepAux_move (d : Dir) (q : Stmt'₁) (v : σ) (T : Tape Bool) :
stepAux (moveₙ d q) v T = stepAux q v ((Tape.move d)^[n] T) := by
suffices ∀ i, stepAux ((Stmt.move d)^[i] q) v T = stepAux q v ((Tape.move d)^[i] T) from this n
intro i; induction' i with i IH generalizing T; · rfl
rw [iterate_succ', iterate_succ]
simp only [stepAux, Function.comp_apply]
rw [IH]
#align turing.TM1to1.step_aux_move Turing.TM1to1.stepAux_move
theorem supportsStmt_move {S : Finset Λ'₁} {d : Dir} {q : Stmt'₁} :
SupportsStmt S (moveₙ d q) = SupportsStmt S q := by
suffices ∀ {i}, SupportsStmt S ((Stmt.move d)^[i] q) = _ from this
intro i; induction i generalizing q <;> simp only [*, iterate]; rfl
#align turing.TM1to1.supports_stmt_move Turing.TM1to1.supportsStmt_move
theorem supportsStmt_write {S : Finset Λ'₁} {l : List Bool} {q : Stmt'₁} :
SupportsStmt S (write l q) = SupportsStmt S q := by
induction' l with _ l IH <;> simp only [write, SupportsStmt, *]
#align turing.TM1to1.supports_stmt_write Turing.TM1to1.supportsStmt_write
theorem supportsStmt_read {S : Finset Λ'₁} :
∀ {f : Γ → Stmt'₁}, (∀ a, SupportsStmt S (f a)) → SupportsStmt S (read dec f) :=
suffices
∀ (i) (f : Vector Bool i → Stmt'₁), (∀ v, SupportsStmt S (f v)) → SupportsStmt S (readAux i f)
from fun hf ↦ this n _ (by intro; simp only [supportsStmt_move, hf])
fun i f hf ↦ by
induction' i with i IH; · exact hf _
constructor <;> apply IH <;> intro <;> apply hf
#align turing.TM1to1.supports_stmt_read Turing.TM1to1.supportsStmt_read
variable (enc0 : enc default = Vector.replicate n false)
section
variable {enc}
/-- The low level tape corresponding to the given tape over alphabet `Γ`. -/
def trTape' (L R : ListBlank Γ) : Tape Bool := by
refine
Tape.mk' (L.bind (fun x ↦ (enc x).toList.reverse) ⟨n, ?_⟩)
(R.bind (fun x ↦ (enc x).toList) ⟨n, ?_⟩) <;>
simp only [enc0, Vector.replicate, List.reverse_replicate, Bool.default_bool, Vector.toList_mk]
#align turing.TM1to1.tr_tape' Turing.TM1to1.trTape'
/-- The low level tape corresponding to the given tape over alphabet `Γ`. -/
def trTape (T : Tape Γ) : Tape Bool :=
trTape' enc0 T.left T.right₀
#align turing.TM1to1.tr_tape Turing.TM1to1.trTape
theorem trTape_mk' (L R : ListBlank Γ) : trTape enc0 (Tape.mk' L R) = trTape' enc0 L R := by
simp only [trTape, Tape.mk'_left, Tape.mk'_right₀]
#align turing.TM1to1.tr_tape_mk' Turing.TM1to1.trTape_mk'
end
variable (M : Λ → TM1.Stmt Γ Λ σ) -- Porting note: Unfolded `Stmt₁`.
/-- The top level program. -/
def tr : Λ'₁ → Stmt'₁
| Λ'.normal l => trNormal dec (M l)
| Λ'.write a q => write (enc a).toList <| moveₙ Dir.left <| trNormal dec q
#align turing.TM1to1.tr Turing.TM1to1.tr
/-- The machine configuration translation. -/
def trCfg : Cfg₁ → Cfg'₁
| ⟨l, v, T⟩ => ⟨l.map Λ'.normal, v, trTape enc0 T⟩
#align turing.TM1to1.tr_cfg Turing.TM1to1.trCfg
variable {enc}
theorem trTape'_move_left (L R : ListBlank Γ) :
(Tape.move Dir.left)^[n] (trTape' enc0 L R) = trTape' enc0 L.tail (R.cons L.head) := by
obtain ⟨a, L, rfl⟩ := L.exists_cons
simp only [trTape', ListBlank.cons_bind, ListBlank.head_cons, ListBlank.tail_cons]
suffices ∀ {L' R' l₁ l₂} (_ : Vector.toList (enc a) = List.reverseAux l₁ l₂),
(Tape.move Dir.left)^[l₁.length]
(Tape.mk' (ListBlank.append l₁ L') (ListBlank.append l₂ R')) =
Tape.mk' L' (ListBlank.append (Vector.toList (enc a)) R') by
simpa only [List.length_reverse, Vector.toList_length] using this (List.reverse_reverse _).symm
intro _ _ l₁ l₂ e
induction' l₁ with b l₁ IH generalizing l₂
· cases e
rfl
simp only [List.length, List.cons_append, iterate_succ_apply]
convert IH e
simp only [ListBlank.tail_cons, ListBlank.append, Tape.move_left_mk', ListBlank.head_cons]
#align turing.TM1to1.tr_tape'_move_left Turing.TM1to1.trTape'_move_left
theorem trTape'_move_right (L R : ListBlank Γ) :
(Tape.move Dir.right)^[n] (trTape' enc0 L R) = trTape' enc0 (L.cons R.head) R.tail := by
suffices ∀ i L, (Tape.move Dir.right)^[i] ((Tape.move Dir.left)^[i] L) = L by
refine (Eq.symm ?_).trans (this n _)
simp only [trTape'_move_left, ListBlank.cons_head_tail, ListBlank.head_cons,
ListBlank.tail_cons]
intro i _
induction' i with i IH
· rfl
rw [iterate_succ_apply, iterate_succ_apply', Tape.move_left_right, IH]
#align turing.TM1to1.tr_tape'_move_right Turing.TM1to1.trTape'_move_right
theorem stepAux_write (q : Stmt'₁) (v : σ) (a b : Γ) (L R : ListBlank Γ) :
stepAux (write (enc a).toList q) v (trTape' enc0 L (ListBlank.cons b R)) =
stepAux q v (trTape' enc0 (ListBlank.cons a L) R) := by
simp only [trTape', ListBlank.cons_bind]
suffices ∀ {L' R'} (l₁ l₂ l₂' : List Bool) (_ : l₂'.length = l₂.length),
stepAux (write l₂ q) v (Tape.mk' (ListBlank.append l₁ L') (ListBlank.append l₂' R')) =
stepAux q v (Tape.mk' (L'.append (List.reverseAux l₂ l₁)) R') by
exact this [] _ _ ((enc b).2.trans (enc a).2.symm)
clear a b L R
intro L' R' l₁ l₂ l₂' e
induction' l₂ with a l₂ IH generalizing l₁ l₂'
· cases List.length_eq_zero.1 e
rfl
cases' l₂' with b l₂' <;> simp only [List.length_nil, List.length_cons, Nat.succ_inj'] at e
rw [List.reverseAux, ← IH (a :: l₁) l₂' e]
simp only [stepAux, ListBlank.append, Tape.write_mk', Tape.move_right_mk', ListBlank.head_cons,
ListBlank.tail_cons]
#align turing.TM1to1.step_aux_write Turing.TM1to1.stepAux_write
variable (encdec : ∀ a, dec (enc a) = a)
theorem stepAux_read (f : Γ → Stmt'₁) (v : σ) (L R : ListBlank Γ) :
stepAux (read dec f) v (trTape' enc0 L R) = stepAux (f R.head) v (trTape' enc0 L R) := by
suffices ∀ f, stepAux (readAux n f) v (trTape' enc0 L R) =
stepAux (f (enc R.head)) v (trTape' enc0 (L.cons R.head) R.tail) by
rw [read, this, stepAux_move, encdec, trTape'_move_left enc0]
simp only [ListBlank.head_cons, ListBlank.cons_head_tail, ListBlank.tail_cons]
obtain ⟨a, R, rfl⟩ := R.exists_cons
simp only [ListBlank.head_cons, ListBlank.tail_cons, trTape', ListBlank.cons_bind,
ListBlank.append_assoc]
suffices ∀ i f L' R' l₁ l₂ h,
stepAux (readAux i f) v (Tape.mk' (ListBlank.append l₁ L') (ListBlank.append l₂ R')) =
stepAux (f ⟨l₂, h⟩) v (Tape.mk' (ListBlank.append (l₂.reverseAux l₁) L') R') by
intro f
-- Porting note: Here was `change`.
exact this n f (L.bind (fun x => (enc x).1.reverse) _)
(R.bind (fun x => (enc x).1) _) [] _ (enc a).2
clear f L a R
intro i f L' R' l₁ l₂ _
subst i
induction' l₂ with a l₂ IH generalizing l₁
· rfl
trans
stepAux (readAux l₂.length fun v ↦ f (a ::ᵥ v)) v
(Tape.mk' ((L'.append l₁).cons a) (R'.append l₂))
· dsimp [readAux, stepAux]
simp only [ListBlank.head_cons, Tape.move_right_mk', ListBlank.tail_cons]
cases a <;> rfl
rw [← ListBlank.append, IH]
rfl
#align turing.TM1to1.step_aux_read Turing.TM1to1.stepAux_read
theorem tr_respects {enc₀} :
Respects (step M) (step (tr enc dec M)) fun c₁ c₂ ↦ trCfg enc enc₀ c₁ = c₂ :=
fun_respects.2 fun ⟨l₁, v, T⟩ ↦ by
obtain ⟨L, R, rfl⟩ := T.exists_mk'
cases' l₁ with l₁
· exact rfl
suffices ∀ q R, Reaches (step (tr enc dec M)) (stepAux (trNormal dec q) v (trTape' enc0 L R))
(trCfg enc enc0 (stepAux q v (Tape.mk' L R))) by
refine TransGen.head' rfl ?_
rw [trTape_mk']
exact this _ R
clear R l₁
intro q R
induction q generalizing v L R with
| move d q IH =>
cases d <;>
simp only [trNormal, iterate, stepAux_move, stepAux, ListBlank.head_cons,
Tape.move_left_mk', ListBlank.cons_head_tail, ListBlank.tail_cons,
trTape'_move_left enc0, trTape'_move_right enc0] <;>
apply IH
| write f q IH =>
simp only [trNormal, stepAux_read dec enc0 encdec, stepAux]
refine ReflTransGen.head rfl ?_
obtain ⟨a, R, rfl⟩ := R.exists_cons
rw [tr, Tape.mk'_head, stepAux_write, ListBlank.head_cons, stepAux_move,
trTape'_move_left enc0, ListBlank.head_cons, ListBlank.tail_cons, Tape.write_mk']
apply IH
| load a q IH =>
simp only [trNormal, stepAux_read dec enc0 encdec]
apply IH
| branch p q₁ q₂ IH₁ IH₂ =>
simp only [trNormal, stepAux_read dec enc0 encdec, stepAux, Tape.mk'_head]
cases p R.head v <;> [apply IH₂; apply IH₁]
| goto l =>
simp only [trNormal, stepAux_read dec enc0 encdec, stepAux, trCfg, trTape_mk']
apply ReflTransGen.refl
| halt =>
simp only [trNormal, stepAux, trCfg, stepAux_move, trTape'_move_left enc0,
trTape'_move_right enc0, trTape_mk']
apply ReflTransGen.refl
#align turing.TM1to1.tr_respects Turing.TM1to1.tr_respects
open scoped Classical
variable [Fintype Γ]
/-- The set of accessible `Λ'.write` machine states. -/
noncomputable def writes : Stmt₁ → Finset Λ'₁
| Stmt.move _ q => writes q
| Stmt.write _ q => (Finset.univ.image fun a ↦ Λ'.write a q) ∪ writes q
| Stmt.load _ q => writes q
| Stmt.branch _ q₁ q₂ => writes q₁ ∪ writes q₂
| Stmt.goto _ => ∅
| Stmt.halt => ∅
#align turing.TM1to1.writes Turing.TM1to1.writes
/-- The set of accessible machine states, assuming that the input machine is supported on `S`,
are the normal states embedded from `S`, plus all write states accessible from these states. -/
noncomputable def trSupp (S : Finset Λ) : Finset Λ'₁ :=
S.biUnion fun l ↦ insert (Λ'.normal l) (writes (M l))
#align turing.TM1to1.tr_supp Turing.TM1to1.trSupp
theorem tr_supports {S : Finset Λ} (ss : Supports M S) : Supports (tr enc dec M) (trSupp M S) :=
⟨Finset.mem_biUnion.2 ⟨_, ss.1, Finset.mem_insert_self _ _⟩, fun q h ↦ by
suffices ∀ q, SupportsStmt S q → (∀ q' ∈ writes q, q' ∈ trSupp M S) →
SupportsStmt (trSupp M S) (trNormal dec q) ∧
∀ q' ∈ writes q, SupportsStmt (trSupp M S) (tr enc dec M q') by
rcases Finset.mem_biUnion.1 h with ⟨l, hl, h⟩
have :=
this _ (ss.2 _ hl) fun q' hq ↦ Finset.mem_biUnion.2 ⟨_, hl, Finset.mem_insert_of_mem hq⟩
rcases Finset.mem_insert.1 h with (rfl | h)
exacts [this.1, this.2 _ h]
intro q hs hw
induction q with
| move d q IH =>
unfold writes at hw ⊢
replace IH := IH hs hw; refine ⟨?_, IH.2⟩
cases d <;> simp only [trNormal, iterate, supportsStmt_move, IH]
| write f q IH =>
unfold writes at hw ⊢
simp only [Finset.mem_image, Finset.mem_union, Finset.mem_univ, exists_prop, true_and_iff]
at hw ⊢
replace IH := IH hs fun q hq ↦ hw q (Or.inr hq)
refine ⟨supportsStmt_read _ fun a _ s ↦ hw _ (Or.inl ⟨_, rfl⟩), fun q' hq ↦ ?_⟩
rcases hq with (⟨a, q₂, rfl⟩ | hq)
· simp only [tr, supportsStmt_write, supportsStmt_move, IH.1]
· exact IH.2 _ hq
| load a q IH =>
unfold writes at hw ⊢
replace IH := IH hs hw
exact ⟨supportsStmt_read _ fun _ ↦ IH.1, IH.2⟩
| branch p q₁ q₂ IH₁ IH₂ =>
unfold writes at hw ⊢
simp only [Finset.mem_union] at hw ⊢
replace IH₁ := IH₁ hs.1 fun q hq ↦ hw q (Or.inl hq)
replace IH₂ := IH₂ hs.2 fun q hq ↦ hw q (Or.inr hq)
exact ⟨supportsStmt_read _ fun _ ↦ ⟨IH₁.1, IH₂.1⟩, fun q ↦ Or.rec (IH₁.2 _) (IH₂.2 _)⟩
| goto l =>
simp only [writes, Finset.not_mem_empty]; refine ⟨?_, fun _ ↦ False.elim⟩
refine supportsStmt_read _ fun a _ s ↦ ?_
exact Finset.mem_biUnion.2 ⟨_, hs _ _, Finset.mem_insert_self _ _⟩
| halt =>
simp only [writes, Finset.not_mem_empty]; refine ⟨?_, fun _ ↦ False.elim⟩
simp only [SupportsStmt, supportsStmt_move, trNormal]⟩
#align turing.TM1to1.tr_supports Turing.TM1to1.tr_supports
end
end TM1to1
/-!
## TM0 emulator in TM1
To establish that TM0 and TM1 are equivalent computational models, we must also have a TM0 emulator
in TM1. The main complication here is that TM0 allows an action to depend on the value at the head
and local state, while TM1 doesn't (in order to have more programming language-like semantics).
So we use a computed `goto` to go to a state that performs the desired action and then returns to
normal execution.
One issue with this is that the `halt` instruction is supposed to halt immediately, not take a step
to a halting state. To resolve this we do a check for `halt` first, then `goto` (with an
unreachable branch).
-/
namespace TM0to1
set_option linter.uppercaseLean3 false -- for "TM0to1"
section
variable {Γ : Type*} [Inhabited Γ]
variable {Λ : Type*} [Inhabited Λ]
/-- The machine states for a TM1 emulating a TM0 machine. States of the TM0 machine are embedded
as `normal q` states, but the actual operation is split into two parts, a jump to `act s q`
followed by the action and a jump to the next `normal` state. -/
inductive Λ'
| normal : Λ → Λ'
| act : TM0.Stmt Γ → Λ → Λ'
#align turing.TM0to1.Λ' Turing.TM0to1.Λ'
local notation "Λ'₁" => @Λ' Γ Λ -- Porting note (#10750): added this to clean up types.
instance : Inhabited Λ'₁ :=
⟨Λ'.normal default⟩
local notation "Cfg₀" => TM0.Cfg Γ Λ
local notation "Stmt₁" => TM1.Stmt Γ Λ'₁ Unit
local notation "Cfg₁" => TM1.Cfg Γ Λ'₁ Unit
variable (M : TM0.Machine Γ Λ)
open TM1.Stmt
/-- The program. -/
def tr : Λ'₁ → Stmt₁
| Λ'.normal q =>
branch (fun a _ ↦ (M q a).isNone) halt <|
goto fun a _ ↦ match M q a with
| none => default -- unreachable
| some (q', s) => Λ'.act s q'
| Λ'.act (TM0.Stmt.move d) q => move d <| goto fun _ _ ↦ Λ'.normal q
| Λ'.act (TM0.Stmt.write a) q => (write fun _ _ ↦ a) <| goto fun _ _ ↦ Λ'.normal q
#align turing.TM0to1.tr Turing.TM0to1.tr
/-- The configuration translation. -/
def trCfg : Cfg₀ → Cfg₁
| ⟨q, T⟩ => ⟨cond (M q T.1).isSome (some (Λ'.normal q)) none, (), T⟩
#align turing.TM0to1.tr_cfg Turing.TM0to1.trCfg
theorem tr_respects : Respects (TM0.step M) (TM1.step (tr M)) fun a b ↦ trCfg M a = b :=
fun_respects.2 fun ⟨q, T⟩ ↦ by
cases' e : M q T.1 with val
· simp only [TM0.step, trCfg, e]; exact Eq.refl none
cases' val with q' s
simp only [FRespects, TM0.step, trCfg, e, Option.isSome, cond, Option.map_some']
revert e -- Porting note: Added this so that `e` doesn't get into the `match`.
have : TM1.step (tr M) ⟨some (Λ'.act s q'), (), T⟩ = some ⟨some (Λ'.normal q'), (), match s with
| TM0.Stmt.move d => T.move d
| TM0.Stmt.write a => T.write a⟩ := by
cases' s with d a <;> rfl
intro e
refine TransGen.head ?_ (TransGen.head' this ?_)
· simp only [TM1.step, TM1.stepAux]
rw [e]
rfl
cases e' : M q' _
· apply ReflTransGen.single
simp only [TM1.step, TM1.stepAux]
rw [e']
rfl
· rfl
#align turing.TM0to1.tr_respects Turing.TM0to1.tr_respects
end
end TM0to1
/-!
## The TM2 model
The TM2 model removes the tape entirely from the TM1 model, replacing it with an arbitrary (finite)
collection of stacks, each with elements of different types (the alphabet of stack `k : K` is
`Γ k`). The statements are:
* `push k (f : σ → Γ k) q` puts `f a` on the `k`-th stack, then does `q`.
* `pop k (f : σ → Option (Γ k) → σ) q` changes the state to `f a (S k).head`, where `S k` is the
value of the `k`-th stack, and removes this element from the stack, then does `q`.
* `peek k (f : σ → Option (Γ k) → σ) q` changes the state to `f a (S k).head`, where `S k` is the
value of the `k`-th stack, then does `q`.
* `load (f : σ → σ) q` reads nothing but applies `f` to the internal state, then does `q`.
* `branch (f : σ → Bool) qtrue qfalse` does `qtrue` or `qfalse` according to `f a`.
* `goto (f : σ → Λ)` jumps to label `f a`.
* `halt` halts on the next step.
The configuration is a tuple `(l, var, stk)` where `l : Option Λ` is the current label to run or
`none` for the halting state, `var : σ` is the (finite) internal state, and `stk : ∀ k, List (Γ k)`
is the collection of stacks. (Note that unlike the `TM0` and `TM1` models, these are not
`ListBlank`s, they have definite ends that can be detected by the `pop` command.)
Given a designated stack `k` and a value `L : List (Γ k)`, the initial configuration has all the
stacks empty except the designated "input" stack; in `eval` this designated stack also functions
as the output stack.
-/
namespace TM2
set_option linter.uppercaseLean3 false -- for "TM2"
section
variable {K : Type*} [DecidableEq K]
-- Index type of stacks
variable (Γ : K → Type*)
-- Type of stack elements
variable (Λ : Type*)
-- Type of function labels
variable (σ : Type*)
-- Type of variable settings
/-- The TM2 model removes the tape entirely from the TM1 model,
replacing it with an arbitrary (finite) collection of stacks.
The operation `push` puts an element on one of the stacks,
and `pop` removes an element from a stack (and modifying the
internal state based on the result). `peek` modifies the
internal state but does not remove an element. -/
inductive Stmt
| push : ∀ k, (σ → Γ k) → Stmt → Stmt
| peek : ∀ k, (σ → Option (Γ k) → σ) → Stmt → Stmt
| pop : ∀ k, (σ → Option (Γ k) → σ) → Stmt → Stmt
| load : (σ → σ) → Stmt → Stmt
| branch : (σ → Bool) → Stmt → Stmt → Stmt
| goto : (σ → Λ) → Stmt
| halt : Stmt
#align turing.TM2.stmt Turing.TM2.Stmt
local notation "Stmt₂" => Stmt Γ Λ σ -- Porting note (#10750): added this to clean up types.
open Stmt
instance Stmt.inhabited : Inhabited Stmt₂ :=
⟨halt⟩
#align turing.TM2.stmt.inhabited Turing.TM2.Stmt.inhabited
/-- A configuration in the TM2 model is a label (or `none` for the halt state), the state of
local variables, and the stacks. (Note that the stacks are not `ListBlank`s, they have a definite
size.) -/
structure Cfg where
/-- The current label to run (or `none` for the halting state) -/
l : Option Λ
/-- The internal state -/
var : σ
/-- The (finite) collection of internal stacks -/
stk : ∀ k, List (Γ k)
#align turing.TM2.cfg Turing.TM2.Cfg
local notation "Cfg₂" => Cfg Γ Λ σ -- Porting note (#10750): added this to clean up types.
instance Cfg.inhabited [Inhabited σ] : Inhabited Cfg₂ :=
⟨⟨default, default, default⟩⟩
#align turing.TM2.cfg.inhabited Turing.TM2.Cfg.inhabited
variable {Γ Λ σ}
/-- The step function for the TM2 model. -/
@[simp]
def stepAux : Stmt₂ → σ → (∀ k, List (Γ k)) → Cfg₂
| push k f q, v, S => stepAux q v (update S k (f v :: S k))
| peek k f q, v, S => stepAux q (f v (S k).head?) S
| pop k f q, v, S => stepAux q (f v (S k).head?) (update S k (S k).tail)
| load a q, v, S => stepAux q (a v) S
| branch f q₁ q₂, v, S => cond (f v) (stepAux q₁ v S) (stepAux q₂ v S)
| goto f, v, S => ⟨some (f v), v, S⟩
| halt, v, S => ⟨none, v, S⟩
#align turing.TM2.step_aux Turing.TM2.stepAux
/-- The step function for the TM2 model. -/
@[simp]
def step (M : Λ → Stmt₂) : Cfg₂ → Option Cfg₂
| ⟨none, _, _⟩ => none
| ⟨some l, v, S⟩ => some (stepAux (M l) v S)
#align turing.TM2.step Turing.TM2.step
/-- The (reflexive) reachability relation for the TM2 model. -/
def Reaches (M : Λ → Stmt₂) : Cfg₂ → Cfg₂ → Prop :=
ReflTransGen fun a b ↦ b ∈ step M a
#align turing.TM2.reaches Turing.TM2.Reaches
/-- Given a set `S` of states, `SupportsStmt S q` means that `q` only jumps to states in `S`. -/
def SupportsStmt (S : Finset Λ) : Stmt₂ → Prop
| push _ _ q => SupportsStmt S q
| peek _ _ q => SupportsStmt S q
| pop _ _ q => SupportsStmt S q
| load _ q => SupportsStmt S q
| branch _ q₁ q₂ => SupportsStmt S q₁ ∧ SupportsStmt S q₂
| goto l => ∀ v, l v ∈ S
| halt => True
#align turing.TM2.supports_stmt Turing.TM2.SupportsStmt
open scoped Classical
/-- The set of subtree statements in a statement. -/
noncomputable def stmts₁ : Stmt₂ → Finset Stmt₂
| Q@(push _ _ q) => insert Q (stmts₁ q)
| Q@(peek _ _ q) => insert Q (stmts₁ q)
| Q@(pop _ _ q) => insert Q (stmts₁ q)
| Q@(load _ q) => insert Q (stmts₁ q)
| Q@(branch _ q₁ q₂) => insert Q (stmts₁ q₁ ∪ stmts₁ q₂)
| Q@(goto _) => {Q}
| Q@halt => {Q}
#align turing.TM2.stmts₁ Turing.TM2.stmts₁
theorem stmts₁_self {q : Stmt₂} : q ∈ stmts₁ q := by
cases q <;> simp only [Finset.mem_insert_self, Finset.mem_singleton_self, stmts₁]
#align turing.TM2.stmts₁_self Turing.TM2.stmts₁_self
theorem stmts₁_trans {q₁ q₂ : Stmt₂} : q₁ ∈ stmts₁ q₂ → stmts₁ q₁ ⊆ stmts₁ q₂ := by
intro h₁₂ q₀ h₀₁
induction q₂ with (
simp only [stmts₁] at h₁₂ ⊢
simp only [Finset.mem_insert, Finset.mem_singleton, Finset.mem_union] at h₁₂)
| branch f q₁ q₂ IH₁ IH₂ =>
rcases h₁₂ with (rfl | h₁₂ | h₁₂)
· unfold stmts₁ at h₀₁
exact h₀₁
· exact Finset.mem_insert_of_mem (Finset.mem_union_left _ (IH₁ h₁₂))
· exact Finset.mem_insert_of_mem (Finset.mem_union_right _ (IH₂ h₁₂))
| goto l => subst h₁₂; exact h₀₁
| halt => subst h₁₂; exact h₀₁
| load _ q IH | _ _ _ q IH =>
rcases h₁₂ with (rfl | h₁₂)
· unfold stmts₁ at h₀₁
exact h₀₁
· exact Finset.mem_insert_of_mem (IH h₁₂)
#align turing.TM2.stmts₁_trans Turing.TM2.stmts₁_trans
theorem stmts₁_supportsStmt_mono {S : Finset Λ} {q₁ q₂ : Stmt₂} (h : q₁ ∈ stmts₁ q₂)
(hs : SupportsStmt S q₂) : SupportsStmt S q₁ := by
induction q₂ with
simp only [stmts₁, SupportsStmt, Finset.mem_insert, Finset.mem_union, Finset.mem_singleton]
at h hs
| branch f q₁ q₂ IH₁ IH₂ => rcases h with (rfl | h | h); exacts [hs, IH₁ h hs.1, IH₂ h hs.2]
| goto l => subst h; exact hs
| halt => subst h; trivial
| load _ _ IH | _ _ _ _ IH => rcases h with (rfl | h) <;> [exact hs; exact IH h hs]
#align turing.TM2.stmts₁_supports_stmt_mono Turing.TM2.stmts₁_supportsStmt_mono
/-- The set of statements accessible from initial set `S` of labels. -/
noncomputable def stmts (M : Λ → Stmt₂) (S : Finset Λ) : Finset (Option Stmt₂) :=
Finset.insertNone (S.biUnion fun q ↦ stmts₁ (M q))
#align turing.TM2.stmts Turing.TM2.stmts
theorem stmts_trans {M : Λ → Stmt₂} {S : Finset Λ} {q₁ q₂ : Stmt₂} (h₁ : q₁ ∈ stmts₁ q₂) :
some q₂ ∈ stmts M S → some q₁ ∈ stmts M S := by
simp only [stmts, Finset.mem_insertNone, Finset.mem_biUnion, Option.mem_def, Option.some.injEq,
forall_eq', exists_imp, and_imp]
exact fun l ls h₂ ↦ ⟨_, ls, stmts₁_trans h₂ h₁⟩
#align turing.TM2.stmts_trans Turing.TM2.stmts_trans
variable [Inhabited Λ]
/-- Given a TM2 machine `M` and a set `S` of states, `Supports M S` means that all states in
`S` jump only to other states in `S`. -/
def Supports (M : Λ → Stmt₂) (S : Finset Λ) :=
default ∈ S ∧ ∀ q ∈ S, SupportsStmt S (M q)
#align turing.TM2.supports Turing.TM2.Supports
theorem stmts_supportsStmt {M : Λ → Stmt₂} {S : Finset Λ} {q : Stmt₂} (ss : Supports M S) :
some q ∈ stmts M S → SupportsStmt S q := by
simp only [stmts, Finset.mem_insertNone, Finset.mem_biUnion, Option.mem_def, Option.some.injEq,
forall_eq', exists_imp, and_imp]
exact fun l ls h ↦ stmts₁_supportsStmt_mono h (ss.2 _ ls)
#align turing.TM2.stmts_supports_stmt Turing.TM2.stmts_supportsStmt
theorem step_supports (M : Λ → Stmt₂) {S : Finset Λ} (ss : Supports M S) :
∀ {c c' : Cfg₂}, c' ∈ step M c → c.l ∈ Finset.insertNone S → c'.l ∈ Finset.insertNone S
| ⟨some l₁, v, T⟩, c', h₁, h₂ => by
replace h₂ := ss.2 _ (Finset.some_mem_insertNone.1 h₂)
simp only [step, Option.mem_def, Option.some.injEq] at h₁; subst c'
revert h₂; induction M l₁ generalizing v T with intro hs
| branch p q₁' q₂' IH₁ IH₂ =>
unfold stepAux; cases p v
· exact IH₂ _ _ hs.2
· exact IH₁ _ _ hs.1
| goto => exact Finset.some_mem_insertNone.2 (hs _)
| halt => apply Multiset.mem_cons_self
| load _ _ IH | _ _ _ _ IH => exact IH _ _ hs
#align turing.TM2.step_supports Turing.TM2.step_supports
variable [Inhabited σ]
/-- The initial state of the TM2 model. The input is provided on a designated stack. -/
def init (k : K) (L : List (Γ k)) : Cfg₂ :=
⟨some default, default, update (fun _ ↦ []) k L⟩
#align turing.TM2.init Turing.TM2.init
/-- Evaluates a TM2 program to completion, with the output on the same stack as the input. -/
def eval (M : Λ → Stmt₂) (k : K) (L : List (Γ k)) : Part (List (Γ k)) :=
(Turing.eval (step M) (init k L)).map fun c ↦ c.stk k
#align turing.TM2.eval Turing.TM2.eval
end
end TM2
/-!
## TM2 emulator in TM1
To prove that TM2 computable functions are TM1 computable, we need to reduce each TM2 program to a
TM1 program. So suppose a TM2 program is given. This program has to maintain a whole collection of
stacks, but we have only one tape, so we must "multiplex" them all together. Pictorially, if stack
1 contains `[a, b]` and stack 2 contains `[c, d, e, f]` then the tape looks like this:
```
bottom: ... | _ | T | _ | _ | _ | _ | ...
stack 1: ... | _ | b | a | _ | _ | _ | ...
stack 2: ... | _ | f | e | d | c | _ | ...
```
where a tape element is a vertical slice through the diagram. Here the alphabet is
`Γ' := Bool × ∀ k, Option (Γ k)`, where:
* `bottom : Bool` is marked only in one place, the initial position of the TM, and represents the
tail of all stacks. It is never modified.
* `stk k : Option (Γ k)` is the value of the `k`-th stack, if in range, otherwise `none` (which is
the blank value). Note that the head of the stack is at the far end; this is so that push and pop
don't have to do any shifting.
In "resting" position, the TM is sitting at the position marked `bottom`. For non-stack actions,
it operates in place, but for the stack actions `push`, `peek`, and `pop`, it must shuttle to the
end of the appropriate stack, make its changes, and then return to the bottom. So the states are:
* `normal (l : Λ)`: waiting at `bottom` to execute function `l`
* `go k (s : StAct k) (q : Stmt₂)`: travelling to the right to get to the end of stack `k` in
order to perform stack action `s`, and later continue with executing `q`
* `ret (q : Stmt₂)`: travelling to the left after having performed a stack action, and executing
`q` once we arrive
Because of the shuttling, emulation overhead is `O(n)`, where `n` is the current maximum of the
length of all stacks. Therefore a program that takes `k` steps to run in TM2 takes `O((m+k)k)`
steps to run when emulated in TM1, where `m` is the length of the input.
-/
namespace TM2to1
set_option linter.uppercaseLean3 false -- for "TM2to1"
-- A displaced lemma proved in unnecessary generality
theorem stk_nth_val {K : Type*} {Γ : K → Type*} {L : ListBlank (∀ k, Option (Γ k))} {k S} (n)
(hL : ListBlank.map (proj k) L = ListBlank.mk (List.map some S).reverse) :
L.nth n k = S.reverse.get? n := by
rw [← proj_map_nth, hL, ← List.map_reverse, ListBlank.nth_mk, List.getI_eq_iget_get?,
List.get?_map]
cases S.reverse.get? n <;> rfl
#align turing.TM2to1.stk_nth_val Turing.TM2to1.stk_nth_val
section
variable {K : Type*} [DecidableEq K]
variable {Γ : K → Type*}
variable {Λ : Type*} [Inhabited Λ]
variable {σ : Type*} [Inhabited σ]
local notation "Stmt₂" => TM2.Stmt Γ Λ σ
local notation "Cfg₂" => TM2.Cfg Γ Λ σ
-- Porting note: `DecidableEq K` is not necessary.
/-- The alphabet of the TM2 simulator on TM1 is a marker for the stack bottom,
plus a vector of stack elements for each stack, or none if the stack does not extend this far. -/
def Γ' :=
Bool × ∀ k, Option (Γ k)
#align turing.TM2to1.Γ' Turing.TM2to1.Γ'
local notation "Γ'₂₁" => @Γ' K Γ -- Porting note (#10750): added this to clean up types.
instance Γ'.inhabited : Inhabited Γ'₂₁ :=
⟨⟨false, fun _ ↦ none⟩⟩
#align turing.TM2to1.Γ'.inhabited Turing.TM2to1.Γ'.inhabited
instance Γ'.fintype [Fintype K] [∀ k, Fintype (Γ k)] : Fintype Γ'₂₁ :=
instFintypeProd _ _
#align turing.TM2to1.Γ'.fintype Turing.TM2to1.Γ'.fintype
/-- The bottom marker is fixed throughout the calculation, so we use the `addBottom` function
to express the program state in terms of a tape with only the stacks themselves. -/
def addBottom (L : ListBlank (∀ k, Option (Γ k))) : ListBlank Γ'₂₁ :=
ListBlank.cons (true, L.head) (L.tail.map ⟨Prod.mk false, rfl⟩)
#align turing.TM2to1.add_bottom Turing.TM2to1.addBottom
theorem addBottom_map (L : ListBlank (∀ k, Option (Γ k))) :
(addBottom L).map ⟨Prod.snd, by rfl⟩ = L := by
simp only [addBottom, ListBlank.map_cons]
convert ListBlank.cons_head_tail L
generalize ListBlank.tail L = L'
refine L'.induction_on fun l ↦ ?_; simp
#align turing.TM2to1.add_bottom_map Turing.TM2to1.addBottom_map
theorem addBottom_modifyNth (f : (∀ k, Option (Γ k)) → ∀ k, Option (Γ k))
(L : ListBlank (∀ k, Option (Γ k))) (n : ℕ) :
(addBottom L).modifyNth (fun a ↦ (a.1, f a.2)) n = addBottom (L.modifyNth f n) := by
cases n <;>
simp only [addBottom, ListBlank.head_cons, ListBlank.modifyNth, ListBlank.tail_cons]
congr; symm; apply ListBlank.map_modifyNth; intro; rfl
#align turing.TM2to1.add_bottom_modify_nth Turing.TM2to1.addBottom_modifyNth
| Mathlib/Computability/TuringMachine.lean | 2,382 | 2,384 | theorem addBottom_nth_snd (L : ListBlank (∀ k, Option (Γ k))) (n : ℕ) :
((addBottom L).nth n).2 = L.nth n := by |
conv => rhs; rw [← addBottom_map L, ListBlank.nth_map]
|
/-
Copyright (c) 2014 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Ring.Cast
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.PSub
import Mathlib.Data.Nat.Size
import Mathlib.Data.Num.Bitwise
#align_import data.num.lemmas from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Properties of the binary representation of integers
-/
/-
Porting note:
`bit0` and `bit1` are deprecated because it is mainly used to represent number literal in Lean3 but
not in Lean4 anymore. However, this file uses them for encoding numbers so this linter is
unnecessary.
-/
set_option linter.deprecated false
-- Porting note: Required for the notation `-[n+1]`.
open Int Function
attribute [local simp] add_assoc
namespace PosNum
variable {α : Type*}
@[simp, norm_cast]
theorem cast_one [One α] [Add α] : ((1 : PosNum) : α) = 1 :=
rfl
#align pos_num.cast_one PosNum.cast_one
@[simp]
theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 :=
rfl
#align pos_num.cast_one' PosNum.cast_one'
@[simp, norm_cast]
theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = _root_.bit0 (n : α) :=
rfl
#align pos_num.cast_bit0 PosNum.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = _root_.bit1 (n : α) :=
rfl
#align pos_num.cast_bit1 PosNum.cast_bit1
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n
| 1 => Nat.cast_one
| bit0 p => (Nat.cast_bit0 _).trans <| congr_arg _root_.bit0 p.cast_to_nat
| bit1 p => (Nat.cast_bit1 _).trans <| congr_arg _root_.bit1 p.cast_to_nat
#align pos_num.cast_to_nat PosNum.cast_to_nat
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
#align pos_num.to_nat_to_int PosNum.to_nat_to_int
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] (n : PosNum) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
#align pos_num.cast_to_int PosNum.cast_to_int
theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1
| 1 => rfl
| bit0 p => rfl
| bit1 p =>
(congr_arg _root_.bit0 (succ_to_nat p)).trans <|
show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm]
#align pos_num.succ_to_nat PosNum.succ_to_nat
theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl
#align pos_num.one_add PosNum.one_add
theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl
#align pos_num.add_one PosNum.add_one
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : PosNum) : ℕ) = m + n
| 1, b => by rw [one_add b, succ_to_nat, add_comm, cast_one]
| a, 1 => by rw [add_one a, succ_to_nat, cast_one]
| bit0 a, bit0 b => (congr_arg _root_.bit0 (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _
| bit0 a, bit1 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + (b + b + 1) by simp [add_left_comm]
| bit1 a, bit0 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + 1 + (b + b) by simp [add_comm, add_left_comm]
| bit1 a, bit1 b =>
show (succ (a + b) + succ (a + b) : ℕ) = a + a + 1 + (b + b + 1) by
rw [succ_to_nat, add_to_nat a b]; simp [add_left_comm]
#align pos_num.add_to_nat PosNum.add_to_nat
theorem add_succ : ∀ m n : PosNum, m + succ n = succ (m + n)
| 1, b => by simp [one_add]
| bit0 a, 1 => congr_arg bit0 (add_one a)
| bit1 a, 1 => congr_arg bit1 (add_one a)
| bit0 a, bit0 b => rfl
| bit0 a, bit1 b => congr_arg bit0 (add_succ a b)
| bit1 a, bit0 b => rfl
| bit1 a, bit1 b => congr_arg bit1 (add_succ a b)
#align pos_num.add_succ PosNum.add_succ
theorem bit0_of_bit0 : ∀ n, _root_.bit0 n = bit0 n
| 1 => rfl
| bit0 p => congr_arg bit0 (bit0_of_bit0 p)
| bit1 p => show bit0 (succ (_root_.bit0 p)) = _ by rw [bit0_of_bit0 p, succ]
#align pos_num.bit0_of_bit0 PosNum.bit0_of_bit0
theorem bit1_of_bit1 (n : PosNum) : _root_.bit1 n = bit1 n :=
show _root_.bit0 n + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ]
#align pos_num.bit1_of_bit1 PosNum.bit1_of_bit1
@[norm_cast]
theorem mul_to_nat (m) : ∀ n, ((m * n : PosNum) : ℕ) = m * n
| 1 => (mul_one _).symm
| bit0 p => show (↑(m * p) + ↑(m * p) : ℕ) = ↑m * (p + p) by rw [mul_to_nat m p, left_distrib]
| bit1 p =>
(add_to_nat (bit0 (m * p)) m).trans <|
show (↑(m * p) + ↑(m * p) + ↑m : ℕ) = ↑m * (p + p) + m by rw [mul_to_nat m p, left_distrib]
#align pos_num.mul_to_nat PosNum.mul_to_nat
theorem to_nat_pos : ∀ n : PosNum, 0 < (n : ℕ)
| 1 => Nat.zero_lt_one
| bit0 p =>
let h := to_nat_pos p
add_pos h h
| bit1 _p => Nat.succ_pos _
#align pos_num.to_nat_pos PosNum.to_nat_pos
theorem cmp_to_nat_lemma {m n : PosNum} : (m : ℕ) < n → (bit1 m : ℕ) < bit0 n :=
show (m : ℕ) < n → (m + m + 1 + 1 : ℕ) ≤ n + n by
intro h; rw [Nat.add_right_comm m m 1, add_assoc]; exact Nat.add_le_add h h
#align pos_num.cmp_to_nat_lemma PosNum.cmp_to_nat_lemma
theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by
induction' m with m IH m IH <;> intro n <;> cases' n with n n <;> unfold cmp <;>
try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl
#align pos_num.cmp_swap PosNum.cmp_swap
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 1, 1 => rfl
| bit0 a, 1 =>
let h : (1 : ℕ) ≤ a := to_nat_pos a
Nat.add_le_add h h
| bit1 a, 1 => Nat.succ_lt_succ <| to_nat_pos <| bit0 a
| 1, bit0 b =>
let h : (1 : ℕ) ≤ b := to_nat_pos b
Nat.add_le_add h h
| 1, bit1 b => Nat.succ_lt_succ <| to_nat_pos <| bit0 b
| bit0 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.add_lt_add this this
· rw [this]
· exact Nat.add_lt_add this this
| bit0 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
· rw [this]
apply Nat.lt_succ_self
· exact cmp_to_nat_lemma this
| bit1 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact cmp_to_nat_lemma this
· rw [this]
apply Nat.lt_succ_self
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
| bit1 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
· rw [this]
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
#align pos_num.cmp_to_nat PosNum.cmp_to_nat
@[norm_cast]
theorem lt_to_nat {m n : PosNum} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
#align pos_num.lt_to_nat PosNum.lt_to_nat
@[norm_cast]
theorem le_to_nat {m n : PosNum} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
#align pos_num.le_to_nat PosNum.le_to_nat
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem add_zero (n : Num) : n + 0 = n := by cases n <;> rfl
#align num.add_zero Num.add_zero
theorem zero_add (n : Num) : 0 + n = n := by cases n <;> rfl
#align num.zero_add Num.zero_add
theorem add_one : ∀ n : Num, n + 1 = succ n
| 0 => rfl
| pos p => by cases p <;> rfl
#align num.add_one Num.add_one
theorem add_succ : ∀ m n : Num, m + succ n = succ (m + n)
| 0, n => by simp [zero_add]
| pos p, 0 => show pos (p + 1) = succ (pos p + 0) by rw [PosNum.add_one, add_zero, succ, succ']
| pos p, pos q => congr_arg pos (PosNum.add_succ _ _)
#align num.add_succ Num.add_succ
theorem bit0_of_bit0 : ∀ n : Num, bit0 n = n.bit0
| 0 => rfl
| pos p => congr_arg pos p.bit0_of_bit0
#align num.bit0_of_bit0 Num.bit0_of_bit0
theorem bit1_of_bit1 : ∀ n : Num, bit1 n = n.bit1
| 0 => rfl
| pos p => congr_arg pos p.bit1_of_bit1
#align num.bit1_of_bit1 Num.bit1_of_bit1
@[simp]
theorem ofNat'_zero : Num.ofNat' 0 = 0 := by simp [Num.ofNat']
#align num.of_nat'_zero Num.ofNat'_zero
theorem ofNat'_bit (b n) : ofNat' (Nat.bit b n) = cond b Num.bit1 Num.bit0 (ofNat' n) :=
Nat.binaryRec_eq rfl _ _
#align num.of_nat'_bit Num.ofNat'_bit
@[simp]
theorem ofNat'_one : Num.ofNat' 1 = 1 := by erw [ofNat'_bit true 0, cond, ofNat'_zero]; rfl
#align num.of_nat'_one Num.ofNat'_one
theorem bit1_succ : ∀ n : Num, n.bit1.succ = n.succ.bit0
| 0 => rfl
| pos _n => rfl
#align num.bit1_succ Num.bit1_succ
theorem ofNat'_succ : ∀ {n}, ofNat' (n + 1) = ofNat' n + 1 :=
@(Nat.binaryRec (by simp [zero_add]) fun b n ih => by
cases b
· erw [ofNat'_bit true n, ofNat'_bit]
simp only [← bit1_of_bit1, ← bit0_of_bit0, cond, _root_.bit1]
-- Porting note: `cc` was not ported yet so `exact Nat.add_left_comm n 1 1` is used.
· erw [show n.bit true + 1 = (n + 1).bit false by
simpa [Nat.bit, _root_.bit1, _root_.bit0] using Nat.add_left_comm n 1 1,
ofNat'_bit, ofNat'_bit, ih]
simp only [cond, add_one, bit1_succ])
#align num.of_nat'_succ Num.ofNat'_succ
@[simp]
theorem add_ofNat' (m n) : Num.ofNat' (m + n) = Num.ofNat' m + Num.ofNat' n := by
induction n
· simp only [Nat.add_zero, ofNat'_zero, add_zero]
· simp only [Nat.add_succ, Nat.add_zero, ofNat'_succ, add_one, add_succ, *]
#align num.add_of_nat' Num.add_ofNat'
@[simp, norm_cast]
theorem cast_zero [Zero α] [One α] [Add α] : ((0 : Num) : α) = 0 :=
rfl
#align num.cast_zero Num.cast_zero
@[simp]
theorem cast_zero' [Zero α] [One α] [Add α] : (Num.zero : α) = 0 :=
rfl
#align num.cast_zero' Num.cast_zero'
@[simp, norm_cast]
theorem cast_one [Zero α] [One α] [Add α] : ((1 : Num) : α) = 1 :=
rfl
#align num.cast_one Num.cast_one
@[simp]
theorem cast_pos [Zero α] [One α] [Add α] (n : PosNum) : (Num.pos n : α) = n :=
rfl
#align num.cast_pos Num.cast_pos
theorem succ'_to_nat : ∀ n, (succ' n : ℕ) = n + 1
| 0 => (Nat.zero_add _).symm
| pos _p => PosNum.succ_to_nat _
#align num.succ'_to_nat Num.succ'_to_nat
theorem succ_to_nat (n) : (succ n : ℕ) = n + 1 :=
succ'_to_nat n
#align num.succ_to_nat Num.succ_to_nat
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : Num, ((n : ℕ) : α) = n
| 0 => Nat.cast_zero
| pos p => p.cast_to_nat
#align num.cast_to_nat Num.cast_to_nat
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : Num) : ℕ) = m + n
| 0, 0 => rfl
| 0, pos _q => (Nat.zero_add _).symm
| pos _p, 0 => rfl
| pos _p, pos _q => PosNum.add_to_nat _ _
#align num.add_to_nat Num.add_to_nat
@[norm_cast]
theorem mul_to_nat : ∀ m n, ((m * n : Num) : ℕ) = m * n
| 0, 0 => rfl
| 0, pos _q => (zero_mul _).symm
| pos _p, 0 => rfl
| pos _p, pos _q => PosNum.mul_to_nat _ _
#align num.mul_to_nat Num.mul_to_nat
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 0, 0 => rfl
| 0, pos b => to_nat_pos _
| pos a, 0 => to_nat_pos _
| pos a, pos b => by
have := PosNum.cmp_to_nat a b; revert this; dsimp [cmp]; cases PosNum.cmp a b
exacts [id, congr_arg pos, id]
#align num.cmp_to_nat Num.cmp_to_nat
@[norm_cast]
theorem lt_to_nat {m n : Num} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
#align num.lt_to_nat Num.lt_to_nat
@[norm_cast]
theorem le_to_nat {m n : Num} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
#align num.le_to_nat Num.le_to_nat
end Num
namespace PosNum
@[simp]
theorem of_to_nat' : ∀ n : PosNum, Num.ofNat' (n : ℕ) = Num.pos n
| 1 => by erw [@Num.ofNat'_bit true 0, Num.ofNat'_zero]; rfl
| bit0 p => by erw [@Num.ofNat'_bit false, of_to_nat' p]; rfl
| bit1 p => by erw [@Num.ofNat'_bit true, of_to_nat' p]; rfl
#align pos_num.of_to_nat' PosNum.of_to_nat'
end PosNum
namespace Num
@[simp, norm_cast]
theorem of_to_nat' : ∀ n : Num, Num.ofNat' (n : ℕ) = n
| 0 => ofNat'_zero
| pos p => p.of_to_nat'
#align num.of_to_nat' Num.of_to_nat'
lemma toNat_injective : Injective (castNum : Num → ℕ) := LeftInverse.injective of_to_nat'
@[norm_cast]
theorem to_nat_inj {m n : Num} : (m : ℕ) = n ↔ m = n := toNat_injective.eq_iff
#align num.to_nat_inj Num.to_nat_inj
/-- This tactic tries to turn an (in)equality about `Num`s to one about `Nat`s by rewriting.
```lean
example (n : Num) (m : Num) : n ≤ n + m := by
transfer_rw
exact Nat.le_add_right _ _
```
-/
scoped macro (name := transfer_rw) "transfer_rw" : tactic => `(tactic|
(repeat first | rw [← to_nat_inj] | rw [← lt_to_nat] | rw [← le_to_nat]
repeat first | rw [add_to_nat] | rw [mul_to_nat] | rw [cast_one] | rw [cast_zero]))
/--
This tactic tries to prove (in)equalities about `Num`s by transferring them to the `Nat` world and
then trying to call `simp`.
```lean
example (n : Num) (m : Num) : n ≤ n + m := by transfer
```
-/
scoped macro (name := transfer) "transfer" : tactic => `(tactic|
(intros; transfer_rw; try simp))
instance addMonoid : AddMonoid Num where
add := (· + ·)
zero := 0
zero_add := zero_add
add_zero := add_zero
add_assoc := by transfer
nsmul := nsmulRec
#align num.add_monoid Num.addMonoid
instance addMonoidWithOne : AddMonoidWithOne Num :=
{ Num.addMonoid with
natCast := Num.ofNat'
one := 1
natCast_zero := ofNat'_zero
natCast_succ := fun _ => ofNat'_succ }
#align num.add_monoid_with_one Num.addMonoidWithOne
instance commSemiring : CommSemiring Num where
__ := Num.addMonoid
__ := Num.addMonoidWithOne
mul := (· * ·)
npow := @npowRec Num ⟨1⟩ ⟨(· * ·)⟩
mul_zero _ := by rw [← to_nat_inj, mul_to_nat, cast_zero, mul_zero]
zero_mul _ := by rw [← to_nat_inj, mul_to_nat, cast_zero, zero_mul]
mul_one _ := by rw [← to_nat_inj, mul_to_nat, cast_one, mul_one]
one_mul _ := by rw [← to_nat_inj, mul_to_nat, cast_one, one_mul]
add_comm _ _ := by simp_rw [← to_nat_inj, add_to_nat, add_comm]
mul_comm _ _ := by simp_rw [← to_nat_inj, mul_to_nat, mul_comm]
mul_assoc _ _ _ := by simp_rw [← to_nat_inj, mul_to_nat, mul_assoc]
left_distrib _ _ _ := by simp only [← to_nat_inj, mul_to_nat, add_to_nat, mul_add]
right_distrib _ _ _ := by simp only [← to_nat_inj, mul_to_nat, add_to_nat, add_mul]
#align num.comm_semiring Num.commSemiring
instance orderedCancelAddCommMonoid : OrderedCancelAddCommMonoid Num where
le := (· ≤ ·)
lt := (· < ·)
lt_iff_le_not_le a b := by simp only [← lt_to_nat, ← le_to_nat, lt_iff_le_not_le]
le_refl := by transfer
le_trans a b c := by transfer_rw; apply le_trans
le_antisymm a b := by transfer_rw; apply le_antisymm
add_le_add_left a b h c := by revert h; transfer_rw; exact fun h => add_le_add_left h c
le_of_add_le_add_left a b c := by transfer_rw; apply le_of_add_le_add_left
#align num.ordered_cancel_add_comm_monoid Num.orderedCancelAddCommMonoid
instance linearOrderedSemiring : LinearOrderedSemiring Num :=
{ Num.commSemiring,
Num.orderedCancelAddCommMonoid with
le_total := by
intro a b
transfer_rw
apply le_total
zero_le_one := by decide
mul_lt_mul_of_pos_left := by
intro a b c
transfer_rw
apply mul_lt_mul_of_pos_left
mul_lt_mul_of_pos_right := by
intro a b c
transfer_rw
apply mul_lt_mul_of_pos_right
decidableLT := Num.decidableLT
decidableLE := Num.decidableLE
-- This is relying on an automatically generated instance name,
-- generated in a `deriving` handler.
-- See https://github.com/leanprover/lean4/issues/2343
decidableEq := instDecidableEqNum
exists_pair_ne := ⟨0, 1, by decide⟩ }
#align num.linear_ordered_semiring Num.linearOrderedSemiring
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem add_of_nat (m n) : ((m + n : ℕ) : Num) = m + n :=
add_ofNat' _ _
#align num.add_of_nat Num.add_of_nat
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem to_nat_to_int (n : Num) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
#align num.to_nat_to_int Num.to_nat_to_int
@[simp, norm_cast]
theorem cast_to_int {α} [AddGroupWithOne α] (n : Num) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
#align num.cast_to_int Num.cast_to_int
theorem to_of_nat : ∀ n : ℕ, ((n : Num) : ℕ) = n
| 0 => by rw [Nat.cast_zero, cast_zero]
| n + 1 => by rw [Nat.cast_succ, add_one, succ_to_nat, to_of_nat n]
#align num.to_of_nat Num.to_of_nat
@[simp, norm_cast]
theorem of_natCast {α} [AddMonoidWithOne α] (n : ℕ) : ((n : Num) : α) = n := by
rw [← cast_to_nat, to_of_nat]
#align num.of_nat_cast Num.of_natCast
@[deprecated (since := "2024-04-17")]
alias of_nat_cast := of_natCast
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem of_nat_inj {m n : ℕ} : (m : Num) = n ↔ m = n :=
⟨fun h => Function.LeftInverse.injective to_of_nat h, congr_arg _⟩
#align num.of_nat_inj Num.of_nat_inj
-- Porting note: The priority should be `high`er than `cast_to_nat`.
@[simp high, norm_cast]
theorem of_to_nat : ∀ n : Num, ((n : ℕ) : Num) = n :=
of_to_nat'
#align num.of_to_nat Num.of_to_nat
@[norm_cast]
theorem dvd_to_nat (m n : Num) : (m : ℕ) ∣ n ↔ m ∣ n :=
⟨fun ⟨k, e⟩ => ⟨k, by rw [← of_to_nat n, e]; simp⟩, fun ⟨k, e⟩ => ⟨k, by simp [e, mul_to_nat]⟩⟩
#align num.dvd_to_nat Num.dvd_to_nat
end Num
namespace PosNum
variable {α : Type*}
open Num
-- Porting note: The priority should be `high`er than `cast_to_nat`.
@[simp high, norm_cast]
theorem of_to_nat : ∀ n : PosNum, ((n : ℕ) : Num) = Num.pos n :=
of_to_nat'
#align pos_num.of_to_nat PosNum.of_to_nat
@[norm_cast]
theorem to_nat_inj {m n : PosNum} : (m : ℕ) = n ↔ m = n :=
⟨fun h => Num.pos.inj <| by rw [← PosNum.of_to_nat, ← PosNum.of_to_nat, h], congr_arg _⟩
#align pos_num.to_nat_inj PosNum.to_nat_inj
theorem pred'_to_nat : ∀ n, (pred' n : ℕ) = Nat.pred n
| 1 => rfl
| bit0 n =>
have : Nat.succ ↑(pred' n) = ↑n := by
rw [pred'_to_nat n, Nat.succ_pred_eq_of_pos (to_nat_pos n)]
match (motive :=
∀ k : Num, Nat.succ ↑k = ↑n → ↑(Num.casesOn k 1 bit1 : PosNum) = Nat.pred (_root_.bit0 n))
pred' n, this with
| 0, (h : ((1 : Num) : ℕ) = n) => by rw [← to_nat_inj.1 h]; rfl
| Num.pos p, (h : Nat.succ ↑p = n) => by rw [← h]; exact (Nat.succ_add p p).symm
| bit1 n => rfl
#align pos_num.pred'_to_nat PosNum.pred'_to_nat
@[simp]
theorem pred'_succ' (n) : pred' (succ' n) = n :=
Num.to_nat_inj.1 <| by rw [pred'_to_nat, succ'_to_nat, Nat.add_one, Nat.pred_succ]
#align pos_num.pred'_succ' PosNum.pred'_succ'
@[simp]
theorem succ'_pred' (n) : succ' (pred' n) = n :=
to_nat_inj.1 <| by
rw [succ'_to_nat, pred'_to_nat, Nat.add_one, Nat.succ_pred_eq_of_pos (to_nat_pos _)]
#align pos_num.succ'_pred' PosNum.succ'_pred'
instance dvd : Dvd PosNum :=
⟨fun m n => pos m ∣ pos n⟩
#align pos_num.has_dvd PosNum.dvd
@[norm_cast]
theorem dvd_to_nat {m n : PosNum} : (m : ℕ) ∣ n ↔ m ∣ n :=
Num.dvd_to_nat (pos m) (pos n)
#align pos_num.dvd_to_nat PosNum.dvd_to_nat
theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n
| 1 => Nat.size_one.symm
| bit0 n => by
rw [size, succ_to_nat, size_to_nat n, cast_bit0, Nat.size_bit0 <| ne_of_gt <| to_nat_pos n]
| bit1 n => by rw [size, succ_to_nat, size_to_nat n, cast_bit1, Nat.size_bit1]
#align pos_num.size_to_nat PosNum.size_to_nat
theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n
| 1 => rfl
| bit0 n => by rw [size, succ_to_nat, natSize, size_eq_natSize n]
| bit1 n => by rw [size, succ_to_nat, natSize, size_eq_natSize n]
#align pos_num.size_eq_nat_size PosNum.size_eq_natSize
theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat]
#align pos_num.nat_size_to_nat PosNum.natSize_to_nat
theorem natSize_pos (n) : 0 < natSize n := by cases n <;> apply Nat.succ_pos
#align pos_num.nat_size_pos PosNum.natSize_pos
/-- This tactic tries to turn an (in)equality about `PosNum`s to one about `Nat`s by rewriting.
```lean
example (n : PosNum) (m : PosNum) : n ≤ n + m := by
transfer_rw
exact Nat.le_add_right _ _
```
-/
scoped macro (name := transfer_rw) "transfer_rw" : tactic => `(tactic|
(repeat first | rw [← to_nat_inj] | rw [← lt_to_nat] | rw [← le_to_nat]
repeat first | rw [add_to_nat] | rw [mul_to_nat] | rw [cast_one] | rw [cast_zero]))
/--
This tactic tries to prove (in)equalities about `PosNum`s by transferring them to the `Nat` world
and then trying to call `simp`.
```lean
example (n : PosNum) (m : PosNum) : n ≤ n + m := by transfer
```
-/
scoped macro (name := transfer) "transfer" : tactic => `(tactic|
(intros; transfer_rw; try simp [add_comm, add_left_comm, mul_comm, mul_left_comm]))
instance addCommSemigroup : AddCommSemigroup PosNum where
add := (· + ·)
add_assoc := by transfer
add_comm := by transfer
#align pos_num.add_comm_semigroup PosNum.addCommSemigroup
instance commMonoid : CommMonoid PosNum where
mul := (· * ·)
one := (1 : PosNum)
npow := @npowRec PosNum ⟨1⟩ ⟨(· * ·)⟩
mul_assoc := by transfer
one_mul := by transfer
mul_one := by transfer
mul_comm := by transfer
#align pos_num.comm_monoid PosNum.commMonoid
instance distrib : Distrib PosNum where
add := (· + ·)
mul := (· * ·)
left_distrib := by transfer; simp [mul_add]
right_distrib := by transfer; simp [mul_add, mul_comm]
#align pos_num.distrib PosNum.distrib
instance linearOrder : LinearOrder PosNum where
lt := (· < ·)
lt_iff_le_not_le := by
intro a b
transfer_rw
apply lt_iff_le_not_le
le := (· ≤ ·)
le_refl := by transfer
le_trans := by
intro a b c
transfer_rw
apply le_trans
le_antisymm := by
intro a b
transfer_rw
apply le_antisymm
le_total := by
intro a b
transfer_rw
apply le_total
decidableLT := by infer_instance
decidableLE := by infer_instance
decidableEq := by infer_instance
#align pos_num.linear_order PosNum.linearOrder
@[simp]
theorem cast_to_num (n : PosNum) : ↑n = Num.pos n := by rw [← cast_to_nat, ← of_to_nat n]
#align pos_num.cast_to_num PosNum.cast_to_num
@[simp, norm_cast]
theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> rfl
#align pos_num.bit_to_nat PosNum.bit_to_nat
@[simp, norm_cast]
theorem cast_add [AddMonoidWithOne α] (m n) : ((m + n : PosNum) : α) = m + n := by
rw [← cast_to_nat, add_to_nat, Nat.cast_add, cast_to_nat, cast_to_nat]
#align pos_num.cast_add PosNum.cast_add
@[simp 500, norm_cast]
theorem cast_succ [AddMonoidWithOne α] (n : PosNum) : (succ n : α) = n + 1 := by
rw [← add_one, cast_add, cast_one]
#align pos_num.cast_succ PosNum.cast_succ
@[simp, norm_cast]
theorem cast_inj [AddMonoidWithOne α] [CharZero α] {m n : PosNum} : (m : α) = n ↔ m = n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_inj, to_nat_inj]
#align pos_num.cast_inj PosNum.cast_inj
@[simp]
theorem one_le_cast [LinearOrderedSemiring α] (n : PosNum) : (1 : α) ≤ n := by
rw [← cast_to_nat, ← Nat.cast_one, Nat.cast_le (α := α)]; apply to_nat_pos
#align pos_num.one_le_cast PosNum.one_le_cast
@[simp]
theorem cast_pos [LinearOrderedSemiring α] (n : PosNum) : 0 < (n : α) :=
lt_of_lt_of_le zero_lt_one (one_le_cast n)
#align pos_num.cast_pos PosNum.cast_pos
@[simp, norm_cast]
theorem cast_mul [Semiring α] (m n) : ((m * n : PosNum) : α) = m * n := by
rw [← cast_to_nat, mul_to_nat, Nat.cast_mul, cast_to_nat, cast_to_nat]
#align pos_num.cast_mul PosNum.cast_mul
@[simp]
theorem cmp_eq (m n) : cmp m n = Ordering.eq ↔ m = n := by
have := cmp_to_nat m n
-- Porting note: `cases` didn't rewrite at `this`, so `revert` & `intro` are required.
revert this; cases cmp m n <;> intro this <;> simp at this ⊢ <;> try { exact this } <;>
simp [show m ≠ n from fun e => by rw [e] at this;exact lt_irrefl _ this]
#align pos_num.cmp_eq PosNum.cmp_eq
@[simp, norm_cast]
theorem cast_lt [LinearOrderedSemiring α] {m n : PosNum} : (m : α) < n ↔ m < n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_lt (α := α), lt_to_nat]
#align pos_num.cast_lt PosNum.cast_lt
@[simp, norm_cast]
theorem cast_le [LinearOrderedSemiring α] {m n : PosNum} : (m : α) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr cast_lt
#align pos_num.cast_le PosNum.cast_le
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> cases n <;> rfl
#align num.bit_to_nat Num.bit_to_nat
theorem cast_succ' [AddMonoidWithOne α] (n) : (succ' n : α) = n + 1 := by
rw [← PosNum.cast_to_nat, succ'_to_nat, Nat.cast_add_one, cast_to_nat]
#align num.cast_succ' Num.cast_succ'
theorem cast_succ [AddMonoidWithOne α] (n) : (succ n : α) = n + 1 :=
cast_succ' n
#align num.cast_succ Num.cast_succ
@[simp, norm_cast]
theorem cast_add [Semiring α] (m n) : ((m + n : Num) : α) = m + n := by
rw [← cast_to_nat, add_to_nat, Nat.cast_add, cast_to_nat, cast_to_nat]
#align num.cast_add Num.cast_add
@[simp, norm_cast]
theorem cast_bit0 [Semiring α] (n : Num) : (n.bit0 : α) = _root_.bit0 (n : α) := by
rw [← bit0_of_bit0, _root_.bit0, cast_add]; rfl
#align num.cast_bit0 Num.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [Semiring α] (n : Num) : (n.bit1 : α) = _root_.bit1 (n : α) := by
rw [← bit1_of_bit1, _root_.bit1, bit0_of_bit0, cast_add, cast_bit0]; rfl
#align num.cast_bit1 Num.cast_bit1
@[simp, norm_cast]
theorem cast_mul [Semiring α] : ∀ m n, ((m * n : Num) : α) = m * n
| 0, 0 => (zero_mul _).symm
| 0, pos _q => (zero_mul _).symm
| pos _p, 0 => (mul_zero _).symm
| pos _p, pos _q => PosNum.cast_mul _ _
#align num.cast_mul Num.cast_mul
theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n
| 0 => Nat.size_zero.symm
| pos p => p.size_to_nat
#align num.size_to_nat Num.size_to_nat
theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n
| 0 => rfl
| pos p => p.size_eq_natSize
#align num.size_eq_nat_size Num.size_eq_natSize
theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat]
#align num.nat_size_to_nat Num.natSize_to_nat
@[simp 999]
theorem ofNat'_eq : ∀ n, Num.ofNat' n = n :=
Nat.binaryRec (by simp) fun b n IH => by
rw [ofNat'] at IH ⊢
rw [Nat.binaryRec_eq, IH]
-- Porting note: `Nat.cast_bit0` & `Nat.cast_bit1` are not `simp` theorems anymore.
· cases b <;> simp [Nat.bit, bit0_of_bit0, bit1_of_bit1, Nat.cast_bit0, Nat.cast_bit1]
· rfl
#align num.of_nat'_eq Num.ofNat'_eq
theorem zneg_toZNum (n : Num) : -n.toZNum = n.toZNumNeg := by cases n <;> rfl
#align num.zneg_to_znum Num.zneg_toZNum
theorem zneg_toZNumNeg (n : Num) : -n.toZNumNeg = n.toZNum := by cases n <;> rfl
#align num.zneg_to_znum_neg Num.zneg_toZNumNeg
theorem toZNum_inj {m n : Num} : m.toZNum = n.toZNum ↔ m = n :=
⟨fun h => by cases m <;> cases n <;> cases h <;> rfl, congr_arg _⟩
#align num.to_znum_inj Num.toZNum_inj
@[simp]
theorem cast_toZNum [Zero α] [One α] [Add α] [Neg α] : ∀ n : Num, (n.toZNum : α) = n
| 0 => rfl
| Num.pos _p => rfl
#align num.cast_to_znum Num.cast_toZNum
@[simp]
theorem cast_toZNumNeg [AddGroup α] [One α] : ∀ n : Num, (n.toZNumNeg : α) = -n
| 0 => neg_zero.symm
| Num.pos _p => rfl
#align num.cast_to_znum_neg Num.cast_toZNumNeg
@[simp]
theorem add_toZNum (m n : Num) : Num.toZNum (m + n) = m.toZNum + n.toZNum := by
cases m <;> cases n <;> rfl
#align num.add_to_znum Num.add_toZNum
end Num
namespace PosNum
open Num
theorem pred_to_nat {n : PosNum} (h : 1 < n) : (pred n : ℕ) = Nat.pred n := by
unfold pred
cases e : pred' n
· have : (1 : ℕ) ≤ Nat.pred n := Nat.pred_le_pred ((@cast_lt ℕ _ _ _).2 h)
rw [← pred'_to_nat, e] at this
exact absurd this (by decide)
· rw [← pred'_to_nat, e]
rfl
#align pos_num.pred_to_nat PosNum.pred_to_nat
theorem sub'_one (a : PosNum) : sub' a 1 = (pred' a).toZNum := by cases a <;> rfl
#align pos_num.sub'_one PosNum.sub'_one
theorem one_sub' (a : PosNum) : sub' 1 a = (pred' a).toZNumNeg := by cases a <;> rfl
#align pos_num.one_sub' PosNum.one_sub'
theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt :=
Iff.rfl
#align pos_num.lt_iff_cmp PosNum.lt_iff_cmp
theorem le_iff_cmp {m n} : m ≤ n ↔ cmp m n ≠ Ordering.gt :=
not_congr <| lt_iff_cmp.trans <| by rw [← cmp_swap]; cases cmp m n <;> decide
#align pos_num.le_iff_cmp PosNum.le_iff_cmp
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem pred_to_nat : ∀ n : Num, (pred n : ℕ) = Nat.pred n
| 0 => rfl
| pos p => by rw [pred, PosNum.pred'_to_nat]; rfl
#align num.pred_to_nat Num.pred_to_nat
theorem ppred_to_nat : ∀ n : Num, (↑) <$> ppred n = Nat.ppred n
| 0 => rfl
| pos p => by
rw [ppred, Option.map_some, Nat.ppred_eq_some.2]
rw [PosNum.pred'_to_nat, Nat.succ_pred_eq_of_pos (PosNum.to_nat_pos _)]
rfl
#align num.ppred_to_nat Num.ppred_to_nat
theorem cmp_swap (m n) : (cmp m n).swap = cmp n m := by
cases m <;> cases n <;> try { rfl }; apply PosNum.cmp_swap
#align num.cmp_swap Num.cmp_swap
theorem cmp_eq (m n) : cmp m n = Ordering.eq ↔ m = n := by
have := cmp_to_nat m n
-- Porting note: `cases` didn't rewrite at `this`, so `revert` & `intro` are required.
revert this; cases cmp m n <;> intro this <;> simp at this ⊢ <;> try { exact this } <;>
simp [show m ≠ n from fun e => by rw [e] at this; exact lt_irrefl _ this]
#align num.cmp_eq Num.cmp_eq
@[simp, norm_cast]
theorem cast_lt [LinearOrderedSemiring α] {m n : Num} : (m : α) < n ↔ m < n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_lt (α := α), lt_to_nat]
#align num.cast_lt Num.cast_lt
@[simp, norm_cast]
theorem cast_le [LinearOrderedSemiring α] {m n : Num} : (m : α) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr cast_lt
#align num.cast_le Num.cast_le
@[simp, norm_cast]
theorem cast_inj [LinearOrderedSemiring α] {m n : Num} : (m : α) = n ↔ m = n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_inj, to_nat_inj]
#align num.cast_inj Num.cast_inj
theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt :=
Iff.rfl
#align num.lt_iff_cmp Num.lt_iff_cmp
theorem le_iff_cmp {m n} : m ≤ n ↔ cmp m n ≠ Ordering.gt :=
not_congr <| lt_iff_cmp.trans <| by rw [← cmp_swap]; cases cmp m n <;> decide
#align num.le_iff_cmp Num.le_iff_cmp
theorem castNum_eq_bitwise {f : Num → Num → Num} {g : Bool → Bool → Bool}
(p : PosNum → PosNum → Num)
(gff : g false false = false) (f00 : f 0 0 = 0)
(f0n : ∀ n, f 0 (pos n) = cond (g false true) (pos n) 0)
(fn0 : ∀ n, f (pos n) 0 = cond (g true false) (pos n) 0)
(fnn : ∀ m n, f (pos m) (pos n) = p m n) (p11 : p 1 1 = cond (g true true) 1 0)
(p1b : ∀ b n, p 1 (PosNum.bit b n) = bit (g true b) (cond (g false true) (pos n) 0))
(pb1 : ∀ a m, p (PosNum.bit a m) 1 = bit (g a true) (cond (g true false) (pos m) 0))
(pbb : ∀ a b m n, p (PosNum.bit a m) (PosNum.bit b n) = bit (g a b) (p m n)) :
∀ m n : Num, (f m n : ℕ) = Nat.bitwise g m n := by
intros m n
cases' m with m <;> cases' n with n <;>
try simp only [show zero = 0 from rfl, show ((0 : Num) : ℕ) = 0 from rfl]
· rw [f00, Nat.bitwise_zero]; rfl
· rw [f0n, Nat.bitwise_zero_left]
cases g false true <;> rfl
· rw [fn0, Nat.bitwise_zero_right]
cases g true false <;> rfl
· rw [fnn]
have : ∀ (b) (n : PosNum), (cond b (↑n) 0 : ℕ) = ↑(cond b (pos n) 0 : Num) := by
intros b _; cases b <;> rfl
induction' m with m IH m IH generalizing n <;> cases' n with n n
any_goals simp only [show one = 1 from rfl, show pos 1 = 1 from rfl,
show PosNum.bit0 = PosNum.bit false from rfl, show PosNum.bit1 = PosNum.bit true from rfl,
show ((1 : Num) : ℕ) = Nat.bit true 0 from rfl]
all_goals
repeat
rw [show ∀ b n, (pos (PosNum.bit b n) : ℕ) = Nat.bit b ↑n by
intros b _; cases b <;> rfl]
rw [Nat.bitwise_bit gff]
any_goals rw [Nat.bitwise_zero, p11]; cases g true true <;> rfl
any_goals rw [Nat.bitwise_zero_left, ← Bool.cond_eq_ite, this, ← bit_to_nat, p1b]
any_goals rw [Nat.bitwise_zero_right, ← Bool.cond_eq_ite, this, ← bit_to_nat, pb1]
all_goals
rw [← show ∀ n : PosNum, ↑(p m n) = Nat.bitwise g ↑m ↑n from IH]
rw [← bit_to_nat, pbb]
#align num.bitwise_to_nat Num.castNum_eq_bitwise
@[simp, norm_cast]
theorem castNum_or : ∀ m n : Num, ↑(m ||| n) = (↑m ||| ↑n : ℕ) := by
-- Porting note: A name of an implicit local hypothesis is not available so
-- `cases_type*` is used.
apply castNum_eq_bitwise fun x y => pos (PosNum.lor x y) <;>
intros <;> (try cases_type* Bool) <;> rfl
#align num.lor_to_nat Num.castNum_or
@[simp, norm_cast]
theorem castNum_and : ∀ m n : Num, ↑(m &&& n) = (↑m &&& ↑n : ℕ) := by
apply castNum_eq_bitwise PosNum.land <;> intros <;> (try cases_type* Bool) <;> rfl
#align num.land_to_nat Num.castNum_and
@[simp, norm_cast]
theorem castNum_ldiff : ∀ m n : Num, (ldiff m n : ℕ) = Nat.ldiff m n := by
apply castNum_eq_bitwise PosNum.ldiff <;> intros <;> (try cases_type* Bool) <;> rfl
#align num.ldiff_to_nat Num.castNum_ldiff
@[simp, norm_cast]
theorem castNum_xor : ∀ m n : Num, ↑(m ^^^ n) = (↑m ^^^ ↑n : ℕ) := by
apply castNum_eq_bitwise PosNum.lxor <;> intros <;> (try cases_type* Bool) <;> rfl
#align num.lxor_to_nat Num.castNum_ldiff
@[simp, norm_cast]
theorem castNum_shiftLeft (m : Num) (n : Nat) : ↑(m <<< n) = (m : ℕ) <<< (n : ℕ) := by
cases m <;> dsimp only [← shiftl_eq_shiftLeft, shiftl]
· symm
apply Nat.zero_shiftLeft
simp only [cast_pos]
induction' n with n IH
· rfl
simp [PosNum.shiftl_succ_eq_bit0_shiftl, Nat.shiftLeft_succ, IH,
Nat.bit0_val, pow_succ, ← mul_assoc, mul_comm,
-shiftl_eq_shiftLeft, -PosNum.shiftl_eq_shiftLeft, shiftl]
#align num.shiftl_to_nat Num.castNum_shiftLeft
@[simp, norm_cast]
theorem castNum_shiftRight (m : Num) (n : Nat) : ↑(m >>> n) = (m : ℕ) >>> (n : ℕ) := by
cases' m with m <;> dsimp only [← shiftr_eq_shiftRight, shiftr];
· symm
apply Nat.zero_shiftRight
induction' n with n IH generalizing m
· cases m <;> rfl
cases' m with m m <;> dsimp only [PosNum.shiftr, ← PosNum.shiftr_eq_shiftRight]
· rw [Nat.shiftRight_eq_div_pow]
symm
apply Nat.div_eq_of_lt
simp
· trans
· apply IH
change Nat.shiftRight m n = Nat.shiftRight (_root_.bit1 m) (n + 1)
rw [add_comm n 1, @Nat.shiftRight_eq _ (1 + n), Nat.shiftRight_add]
apply congr_arg fun x => Nat.shiftRight x n
simp [Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val]
· trans
· apply IH
change Nat.shiftRight m n = Nat.shiftRight (_root_.bit0 m) (n + 1)
rw [add_comm n 1, @Nat.shiftRight_eq _ (1 + n), Nat.shiftRight_add]
apply congr_arg fun x => Nat.shiftRight x n
simp [Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val]
#align num.shiftr_to_nat Num.castNum_shiftRight
@[simp]
theorem castNum_testBit (m n) : testBit m n = Nat.testBit m n := by
-- Porting note: `unfold` → `dsimp only`
cases m with dsimp only [testBit]
| zero =>
rw [show (Num.zero : Nat) = 0 from rfl, Nat.zero_testBit]
| pos m =>
rw [cast_pos]
induction' n with n IH generalizing m <;> cases' m with m m
<;> dsimp only [PosNum.testBit, Nat.zero_eq]
· rfl
· rw [PosNum.cast_bit1, ← Nat.bit_true, Nat.testBit_bit_zero]
· rw [PosNum.cast_bit0, ← Nat.bit_false, Nat.testBit_bit_zero]
· simp
· rw [PosNum.cast_bit1, ← Nat.bit_true, Nat.testBit_bit_succ, IH]
· rw [PosNum.cast_bit0, ← Nat.bit_false, Nat.testBit_bit_succ, IH]
#align num.test_bit_to_nat Num.castNum_testBit
end Num
namespace ZNum
variable {α : Type*}
open PosNum
@[simp, norm_cast]
theorem cast_zero [Zero α] [One α] [Add α] [Neg α] : ((0 : ZNum) : α) = 0 :=
rfl
#align znum.cast_zero ZNum.cast_zero
@[simp]
theorem cast_zero' [Zero α] [One α] [Add α] [Neg α] : (ZNum.zero : α) = 0 :=
rfl
#align znum.cast_zero' ZNum.cast_zero'
@[simp, norm_cast]
theorem cast_one [Zero α] [One α] [Add α] [Neg α] : ((1 : ZNum) : α) = 1 :=
rfl
#align znum.cast_one ZNum.cast_one
@[simp]
theorem cast_pos [Zero α] [One α] [Add α] [Neg α] (n : PosNum) : (pos n : α) = n :=
rfl
#align znum.cast_pos ZNum.cast_pos
@[simp]
theorem cast_neg [Zero α] [One α] [Add α] [Neg α] (n : PosNum) : (neg n : α) = -n :=
rfl
#align znum.cast_neg ZNum.cast_neg
@[simp, norm_cast]
theorem cast_zneg [AddGroup α] [One α] : ∀ n, ((-n : ZNum) : α) = -n
| 0 => neg_zero.symm
| pos _p => rfl
| neg _p => (neg_neg _).symm
#align znum.cast_zneg ZNum.cast_zneg
theorem neg_zero : (-0 : ZNum) = 0 :=
rfl
#align znum.neg_zero ZNum.neg_zero
theorem zneg_pos (n : PosNum) : -pos n = neg n :=
rfl
#align znum.zneg_pos ZNum.zneg_pos
theorem zneg_neg (n : PosNum) : -neg n = pos n :=
rfl
#align znum.zneg_neg ZNum.zneg_neg
theorem zneg_zneg (n : ZNum) : - -n = n := by cases n <;> rfl
#align znum.zneg_zneg ZNum.zneg_zneg
theorem zneg_bit1 (n : ZNum) : -n.bit1 = (-n).bitm1 := by cases n <;> rfl
#align znum.zneg_bit1 ZNum.zneg_bit1
theorem zneg_bitm1 (n : ZNum) : -n.bitm1 = (-n).bit1 := by cases n <;> rfl
#align znum.zneg_bitm1 ZNum.zneg_bitm1
theorem zneg_succ (n : ZNum) : -n.succ = (-n).pred := by
cases n <;> try { rfl }; rw [succ, Num.zneg_toZNumNeg]; rfl
#align znum.zneg_succ ZNum.zneg_succ
theorem zneg_pred (n : ZNum) : -n.pred = (-n).succ := by
rw [← zneg_zneg (succ (-n)), zneg_succ, zneg_zneg]
#align znum.zneg_pred ZNum.zneg_pred
@[simp]
theorem abs_to_nat : ∀ n, (abs n : ℕ) = Int.natAbs n
| 0 => rfl
| pos p => congr_arg Int.natAbs p.to_nat_to_int
| neg p => show Int.natAbs ((p : ℕ) : ℤ) = Int.natAbs (-p) by rw [p.to_nat_to_int, Int.natAbs_neg]
#align znum.abs_to_nat ZNum.abs_to_nat
@[simp]
theorem abs_toZNum : ∀ n : Num, abs n.toZNum = n
| 0 => rfl
| Num.pos _p => rfl
#align znum.abs_to_znum ZNum.abs_toZNum
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] : ∀ n : ZNum, ((n : ℤ) : α) = n
| 0 => by rw [cast_zero, cast_zero, Int.cast_zero]
| pos p => by rw [cast_pos, cast_pos, PosNum.cast_to_int]
| neg p => by rw [cast_neg, cast_neg, Int.cast_neg, PosNum.cast_to_int]
#align znum.cast_to_int ZNum.cast_to_int
theorem bit0_of_bit0 : ∀ n : ZNum, bit0 n = n.bit0
| 0 => rfl
| pos a => congr_arg pos a.bit0_of_bit0
| neg a => congr_arg neg a.bit0_of_bit0
#align znum.bit0_of_bit0 ZNum.bit0_of_bit0
theorem bit1_of_bit1 : ∀ n : ZNum, bit1 n = n.bit1
| 0 => rfl
| pos a => congr_arg pos a.bit1_of_bit1
| neg a => show PosNum.sub' 1 (_root_.bit0 a) = _ by rw [PosNum.one_sub', a.bit0_of_bit0]; rfl
#align znum.bit1_of_bit1 ZNum.bit1_of_bit1
@[simp, norm_cast]
theorem cast_bit0 [AddGroupWithOne α] : ∀ n : ZNum, (n.bit0 : α) = bit0 (n : α)
| 0 => (add_zero _).symm
| pos p => by rw [ZNum.bit0, cast_pos, cast_pos]; rfl
| neg p => by
rw [ZNum.bit0, cast_neg, cast_neg, PosNum.cast_bit0, _root_.bit0, _root_.bit0, neg_add_rev]
#align znum.cast_bit0 ZNum.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [AddGroupWithOne α] : ∀ n : ZNum, (n.bit1 : α) = bit1 (n : α)
| 0 => by simp [ZNum.bit1, _root_.bit1, _root_.bit0]
| pos p => by rw [ZNum.bit1, cast_pos, cast_pos]; rfl
| neg p => by
rw [ZNum.bit1, cast_neg, cast_neg]
cases' e : pred' p with a <;>
have ep : p = _ := (succ'_pred' p).symm.trans (congr_arg Num.succ' e)
· conv at ep => change p = 1
subst p
simp [_root_.bit1, _root_.bit0]
-- Porting note: `rw [Num.succ']` yields a `match` pattern.
· dsimp only [Num.succ'] at ep
subst p
have : (↑(-↑a : ℤ) : α) = -1 + ↑(-↑a + 1 : ℤ) := by simp [add_comm (- ↑a : ℤ) 1]
simpa [_root_.bit1, _root_.bit0] using this
#align znum.cast_bit1 ZNum.cast_bit1
@[simp]
theorem cast_bitm1 [AddGroupWithOne α] (n : ZNum) : (n.bitm1 : α) = bit0 (n : α) - 1 := by
conv =>
lhs
rw [← zneg_zneg n]
rw [← zneg_bit1, cast_zneg, cast_bit1]
have : ((-1 + n + n : ℤ) : α) = (n + n + -1 : ℤ) := by simp [add_comm, add_left_comm]
simpa [_root_.bit1, _root_.bit0, sub_eq_add_neg] using this
#align znum.cast_bitm1 ZNum.cast_bitm1
| Mathlib/Data/Num/Lemmas.lean | 1,138 | 1,138 | theorem add_zero (n : ZNum) : n + 0 = n := by | cases n <;> rfl
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Complex
import Qq
#align_import analysis.special_functions.pow.real from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-! # Power function on `ℝ`
We construct the power functions `x ^ y`, where `x` and `y` are real numbers.
-/
noncomputable section
open scoped Classical
open Real ComplexConjugate
open Finset Set
/-
## Definitions
-/
namespace Real
variable {x y z : ℝ}
/-- The real power function `x ^ y`, defined as the real part of the complex power function.
For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`, one sets `0 ^ 0=1` and `0 ^ y=0` for
`y ≠ 0`. For `x < 0`, the definition is somewhat arbitrary as it depends on the choice of a complex
determination of the logarithm. With our conventions, it is equal to `exp (y log x) cos (π y)`. -/
noncomputable def rpow (x y : ℝ) :=
((x : ℂ) ^ (y : ℂ)).re
#align real.rpow Real.rpow
noncomputable instance : Pow ℝ ℝ := ⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x y : ℝ) : rpow x y = x ^ y := rfl
#align real.rpow_eq_pow Real.rpow_eq_pow
theorem rpow_def (x y : ℝ) : x ^ y = ((x : ℂ) ^ (y : ℂ)).re := rfl
#align real.rpow_def Real.rpow_def
theorem rpow_def_of_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) := by
simp only [rpow_def, Complex.cpow_def]; split_ifs <;>
simp_all [(Complex.ofReal_log hx).symm, -Complex.ofReal_mul, -RCLike.ofReal_mul,
(Complex.ofReal_mul _ _).symm, Complex.exp_ofReal_re, Complex.ofReal_eq_zero]
#align real.rpow_def_of_nonneg Real.rpow_def_of_nonneg
theorem rpow_def_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : x ^ y = exp (log x * y) := by
rw [rpow_def_of_nonneg (le_of_lt hx), if_neg (ne_of_gt hx)]
#align real.rpow_def_of_pos Real.rpow_def_of_pos
theorem exp_mul (x y : ℝ) : exp (x * y) = exp x ^ y := by rw [rpow_def_of_pos (exp_pos _), log_exp]
#align real.exp_mul Real.exp_mul
@[simp, norm_cast]
theorem rpow_intCast (x : ℝ) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by
simp only [rpow_def, ← Complex.ofReal_zpow, Complex.cpow_intCast, Complex.ofReal_intCast,
Complex.ofReal_re]
#align real.rpow_int_cast Real.rpow_intCast
@[deprecated (since := "2024-04-17")]
alias rpow_int_cast := rpow_intCast
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by simpa using rpow_intCast x n
#align real.rpow_nat_cast Real.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
theorem exp_one_rpow (x : ℝ) : exp 1 ^ x = exp x := by rw [← exp_mul, one_mul]
#align real.exp_one_rpow Real.exp_one_rpow
@[simp] lemma exp_one_pow (n : ℕ) : exp 1 ^ n = exp n := by rw [← rpow_natCast, exp_one_rpow]
theorem rpow_eq_zero_iff_of_nonneg (hx : 0 ≤ x) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [rpow_def_of_nonneg hx]
split_ifs <;> simp [*, exp_ne_zero]
#align real.rpow_eq_zero_iff_of_nonneg Real.rpow_eq_zero_iff_of_nonneg
@[simp]
lemma rpow_eq_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y = 0 ↔ x = 0 := by
simp [rpow_eq_zero_iff_of_nonneg, *]
@[simp]
lemma rpow_ne_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y ≠ 0 ↔ x ≠ 0 :=
Real.rpow_eq_zero hx hy |>.not
open Real
theorem rpow_def_of_neg {x : ℝ} (hx : x < 0) (y : ℝ) : x ^ y = exp (log x * y) * cos (y * π) := by
rw [rpow_def, Complex.cpow_def, if_neg]
· have : Complex.log x * y = ↑(log (-x) * y) + ↑(y * π) * Complex.I := by
simp only [Complex.log, abs_of_neg hx, Complex.arg_ofReal_of_neg hx, Complex.abs_ofReal,
Complex.ofReal_mul]
ring
rw [this, Complex.exp_add_mul_I, ← Complex.ofReal_exp, ← Complex.ofReal_cos, ←
Complex.ofReal_sin, mul_add, ← Complex.ofReal_mul, ← mul_assoc, ← Complex.ofReal_mul,
Complex.add_re, Complex.ofReal_re, Complex.mul_re, Complex.I_re, Complex.ofReal_im,
Real.log_neg_eq_log]
ring
· rw [Complex.ofReal_eq_zero]
exact ne_of_lt hx
#align real.rpow_def_of_neg Real.rpow_def_of_neg
theorem rpow_def_of_nonpos {x : ℝ} (hx : x ≤ 0) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) * cos (y * π) := by
split_ifs with h <;> simp [rpow_def, *]; exact rpow_def_of_neg (lt_of_le_of_ne hx h) _
#align real.rpow_def_of_nonpos Real.rpow_def_of_nonpos
theorem rpow_pos_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : 0 < x ^ y := by
rw [rpow_def_of_pos hx]; apply exp_pos
#align real.rpow_pos_of_pos Real.rpow_pos_of_pos
@[simp]
| Mathlib/Analysis/SpecialFunctions/Pow/Real.lean | 125 | 125 | theorem rpow_zero (x : ℝ) : x ^ (0 : ℝ) = 1 := by | simp [rpow_def]
|
/-
Copyright (c) 2022 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Dynamics.Ergodic.AddCircle
import Mathlib.MeasureTheory.Covering.LiminfLimsup
#align_import number_theory.well_approximable from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Well-approximable numbers and Gallagher's ergodic theorem
Gallagher's ergodic theorem is a result in metric number theory. It thus belongs to that branch of
mathematics concerning arithmetic properties of real numbers which hold almost eveywhere with
respect to the Lebesgue measure.
Gallagher's theorem concerns the approximation of real numbers by rational numbers. The input is a
sequence of distances `δ₁, δ₂, ...`, and the theorem concerns the set of real numbers `x` for which
there is an infinity of solutions to:
$$
|x - m/n| < δₙ,
$$
where the rational number `m/n` is in lowest terms. The result is that for any `δ`, this set is
either almost all `x` or almost no `x`.
This result was proved by Gallagher in 1959
[P. Gallagher, *Approximation by reduced fractions*](Gallagher1961). It is formalised here as
`AddCircle.addWellApproximable_ae_empty_or_univ` except with `x` belonging to the circle `ℝ ⧸ ℤ`
since this turns out to be more natural.
Given a particular `δ`, the Duffin-Schaeffer conjecture (now a theorem) gives a criterion for
deciding which of the two cases in the conclusion of Gallagher's theorem actually occurs. It was
proved by Koukoulopoulos and Maynard in 2019
[D. Koukoulopoulos, J. Maynard, *On the Duffin-Schaeffer conjecture*](KoukoulopoulosMaynard2020).
We do *not* include a formalisation of the Koukoulopoulos-Maynard result here.
## Main definitions and results:
* `approxOrderOf`: in a seminormed group `A`, given `n : ℕ` and `δ : ℝ`, `approxOrderOf A n δ`
is the set of elements within a distance `δ` of a point of order `n`.
* `wellApproximable`: in a seminormed group `A`, given a sequence of distances `δ₁, δ₂, ...`,
`wellApproximable A δ` is the limsup as `n → ∞` of the sets `approxOrderOf A n δₙ`. Thus, it
is the set of points that lie in infinitely many of the sets `approxOrderOf A n δₙ`.
* `AddCircle.addWellApproximable_ae_empty_or_univ`: *Gallagher's ergodic theorem* says that for
the (additive) circle `𝕊`, for any sequence of distances `δ`, the set
`addWellApproximable 𝕊 δ` is almost empty or almost full.
* `NormedAddCommGroup.exists_norm_nsmul_le`: a general version of Dirichlet's approximation theorem
* `AddCircle.exists_norm_nsmul_le`: Dirichlet's approximation theorem
## TODO:
The hypothesis `hδ` in `AddCircle.addWellApproximable_ae_empty_or_univ` can be dropped.
An elementary (non-measure-theoretic) argument shows that if `¬ hδ` holds then
`addWellApproximable 𝕊 δ = univ` (provided `δ` is non-negative).
Use `AddCircle.exists_norm_nsmul_le` to prove:
`addWellApproximable 𝕊 (fun n ↦ 1 / n^2) = { ξ | ¬ IsOfFinAddOrder ξ }`
(which is equivalent to `Real.infinite_rat_abs_sub_lt_one_div_den_sq_iff_irrational`).
-/
open Set Filter Function Metric MeasureTheory
open scoped MeasureTheory Topology Pointwise
/-- In a seminormed group `A`, given `n : ℕ` and `δ : ℝ`, `approxOrderOf A n δ` is the set of
elements within a distance `δ` of a point of order `n`. -/
@[to_additive "In a seminormed additive group `A`, given `n : ℕ` and `δ : ℝ`,
`approxAddOrderOf A n δ` is the set of elements within a distance `δ` of a point of order `n`."]
def approxOrderOf (A : Type*) [SeminormedGroup A] (n : ℕ) (δ : ℝ) : Set A :=
thickening δ {y | orderOf y = n}
#align approx_order_of approxOrderOf
#align approx_add_order_of approxAddOrderOf
@[to_additive mem_approx_add_orderOf_iff]
theorem mem_approxOrderOf_iff {A : Type*} [SeminormedGroup A] {n : ℕ} {δ : ℝ} {a : A} :
a ∈ approxOrderOf A n δ ↔ ∃ b : A, orderOf b = n ∧ a ∈ ball b δ := by
simp only [approxOrderOf, thickening_eq_biUnion_ball, mem_iUnion₂, mem_setOf_eq, exists_prop]
#align mem_approx_order_of_iff mem_approxOrderOf_iff
#align mem_approx_add_order_of_iff mem_approx_add_orderOf_iff
/-- In a seminormed group `A`, given a sequence of distances `δ₁, δ₂, ...`, `wellApproximable A δ`
is the limsup as `n → ∞` of the sets `approxOrderOf A n δₙ`. Thus, it is the set of points that
lie in infinitely many of the sets `approxOrderOf A n δₙ`. -/
@[to_additive addWellApproximable "In a seminormed additive group `A`, given a sequence of
distances `δ₁, δ₂, ...`, `addWellApproximable A δ` is the limsup as `n → ∞` of the sets
`approxAddOrderOf A n δₙ`. Thus, it is the set of points that lie in infinitely many of the sets
`approxAddOrderOf A n δₙ`."]
def wellApproximable (A : Type*) [SeminormedGroup A] (δ : ℕ → ℝ) : Set A :=
blimsup (fun n => approxOrderOf A n (δ n)) atTop fun n => 0 < n
#align well_approximable wellApproximable
#align add_well_approximable addWellApproximable
@[to_additive mem_add_wellApproximable_iff]
theorem mem_wellApproximable_iff {A : Type*} [SeminormedGroup A] {δ : ℕ → ℝ} {a : A} :
a ∈ wellApproximable A δ ↔
a ∈ blimsup (fun n => approxOrderOf A n (δ n)) atTop fun n => 0 < n :=
Iff.rfl
#align mem_well_approximable_iff mem_wellApproximable_iff
#align mem_add_well_approximable_iff mem_add_wellApproximable_iff
namespace approxOrderOf
variable {A : Type*} [SeminormedCommGroup A] {a : A} {m n : ℕ} (δ : ℝ)
@[to_additive]
theorem image_pow_subset_of_coprime (hm : 0 < m) (hmn : n.Coprime m) :
(fun (y : A) => y ^ m) '' approxOrderOf A n δ ⊆ approxOrderOf A n (m * δ) := by
rintro - ⟨a, ha, rfl⟩
obtain ⟨b, hb, hab⟩ := mem_approxOrderOf_iff.mp ha
replace hb : b ^ m ∈ {u : A | orderOf u = n} := by
rw [← hb] at hmn ⊢; exact hmn.orderOf_pow
apply ball_subset_thickening hb ((m : ℝ) • δ)
convert pow_mem_ball hm hab using 1
simp only [nsmul_eq_mul, Algebra.id.smul_eq_mul]
#align approx_order_of.image_pow_subset_of_coprime approxOrderOf.image_pow_subset_of_coprime
#align approx_add_order_of.image_nsmul_subset_of_coprime approxAddOrderOf.image_nsmul_subset_of_coprime
@[to_additive]
theorem image_pow_subset (n : ℕ) (hm : 0 < m) :
(fun (y : A) => y ^ m) '' approxOrderOf A (n * m) δ ⊆ approxOrderOf A n (m * δ) := by
rintro - ⟨a, ha, rfl⟩
obtain ⟨b, hb : orderOf b = n * m, hab : a ∈ ball b δ⟩ := mem_approxOrderOf_iff.mp ha
replace hb : b ^ m ∈ {y : A | orderOf y = n} := by
rw [mem_setOf_eq, orderOf_pow' b hm.ne', hb, Nat.gcd_mul_left_left, n.mul_div_cancel hm]
apply ball_subset_thickening hb (m * δ)
convert pow_mem_ball hm hab using 1
simp only [nsmul_eq_mul]
#align approx_order_of.image_pow_subset approxOrderOf.image_pow_subset
#align approx_add_order_of.image_nsmul_subset approxAddOrderOf.image_nsmul_subset
@[to_additive]
theorem smul_subset_of_coprime (han : (orderOf a).Coprime n) :
a • approxOrderOf A n δ ⊆ approxOrderOf A (orderOf a * n) δ := by
simp_rw [approxOrderOf, thickening_eq_biUnion_ball, ← image_smul, image_iUnion₂, image_smul,
smul_ball'', smul_eq_mul, mem_setOf_eq]
refine iUnion₂_subset_iff.mpr fun b hb c hc => ?_
simp only [mem_iUnion, exists_prop]
refine ⟨a * b, ?_, hc⟩
rw [← hb] at han ⊢
exact (Commute.all a b).orderOf_mul_eq_mul_orderOf_of_coprime han
#align approx_order_of.smul_subset_of_coprime approxOrderOf.smul_subset_of_coprime
#align approx_add_order_of.vadd_subset_of_coprime approxAddOrderOf.vadd_subset_of_coprime
@[to_additive vadd_eq_of_mul_dvd]
| Mathlib/NumberTheory/WellApproximable.lean | 147 | 166 | theorem smul_eq_of_mul_dvd (hn : 0 < n) (han : orderOf a ^ 2 ∣ n) :
a • approxOrderOf A n δ = approxOrderOf A n δ := by |
simp_rw [approxOrderOf, thickening_eq_biUnion_ball, ← image_smul, image_iUnion₂, image_smul,
smul_ball'', smul_eq_mul, mem_setOf_eq]
replace han : ∀ {b : A}, orderOf b = n → orderOf (a * b) = n := by
intro b hb
rw [← hb] at han hn
rw [sq] at han
rwa [(Commute.all a b).orderOf_mul_eq_right_of_forall_prime_mul_dvd (orderOf_pos_iff.mp hn)
fun p _ hp' => dvd_trans (mul_dvd_mul_right hp' <| orderOf a) han]
let f : {b : A | orderOf b = n} → {b : A | orderOf b = n} := fun b => ⟨a * b, han b.property⟩
have hf : Surjective f := by
rintro ⟨b, hb⟩
refine ⟨⟨a⁻¹ * b, ?_⟩, ?_⟩
· rw [mem_setOf_eq, ← orderOf_inv, mul_inv_rev, inv_inv, mul_comm]
apply han
simpa
· simp only [f, Subtype.mk_eq_mk, Subtype.coe_mk, mul_inv_cancel_left]
simpa only [mem_setOf_eq, Subtype.coe_mk, iUnion_coe_set] using
hf.iUnion_comp fun b => ball (b : A) δ
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Kevin Buzzard, Yury Kudryashov
-/
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.LinearAlgebra.Span
#align_import linear_algebra.quotient from "leanprover-community/mathlib"@"48085f140e684306f9e7da907cd5932056d1aded"
/-!
# Quotients by submodules
* If `p` is a submodule of `M`, `M ⧸ p` is the quotient of `M` with respect to `p`:
that is, elements of `M` are identified if their difference is in `p`. This is itself a module.
-/
-- For most of this file we work over a noncommutative ring
section Ring
namespace Submodule
variable {R M : Type*} {r : R} {x y : M} [Ring R] [AddCommGroup M] [Module R M]
variable (p p' : Submodule R M)
open LinearMap QuotientAddGroup
/-- The equivalence relation associated to a submodule `p`, defined by `x ≈ y` iff `-x + y ∈ p`.
Note this is equivalent to `y - x ∈ p`, but defined this way to be defeq to the `AddSubgroup`
version, where commutativity can't be assumed. -/
def quotientRel : Setoid M :=
QuotientAddGroup.leftRel p.toAddSubgroup
#align submodule.quotient_rel Submodule.quotientRel
theorem quotientRel_r_def {x y : M} : @Setoid.r _ p.quotientRel x y ↔ x - y ∈ p :=
Iff.trans
(by
rw [leftRel_apply, sub_eq_add_neg, neg_add, neg_neg]
rfl)
neg_mem_iff
#align submodule.quotient_rel_r_def Submodule.quotientRel_r_def
/-- The quotient of a module `M` by a submodule `p ⊆ M`. -/
instance hasQuotient : HasQuotient M (Submodule R M) :=
⟨fun p => Quotient (quotientRel p)⟩
#align submodule.has_quotient Submodule.hasQuotient
namespace Quotient
/-- Map associating to an element of `M` the corresponding element of `M/p`,
when `p` is a submodule of `M`. -/
def mk {p : Submodule R M} : M → M ⧸ p :=
Quotient.mk''
#align submodule.quotient.mk Submodule.Quotient.mk
/- porting note: here and throughout elaboration is sped up *tremendously* (in some cases even
avoiding timeouts) by providing type ascriptions to `mk` (or `mk x`) and its variants. Lean 3
didn't need this help. -/
@[simp]
theorem mk'_eq_mk' {p : Submodule R M} (x : M) :
@Quotient.mk' _ (quotientRel p) x = (mk : M → M ⧸ p) x :=
rfl
#align submodule.quotient.mk_eq_mk Submodule.Quotient.mk'_eq_mk'
@[simp]
theorem mk''_eq_mk {p : Submodule R M} (x : M) : (Quotient.mk'' x : M ⧸ p) = (mk : M → M ⧸ p) x :=
rfl
#align submodule.quotient.mk'_eq_mk Submodule.Quotient.mk''_eq_mk
@[simp]
theorem quot_mk_eq_mk {p : Submodule R M} (x : M) : (Quot.mk _ x : M ⧸ p) = (mk : M → M ⧸ p) x :=
rfl
#align submodule.quotient.quot_mk_eq_mk Submodule.Quotient.quot_mk_eq_mk
protected theorem eq' {x y : M} : (mk x : M ⧸ p) = (mk : M → M ⧸ p) y ↔ -x + y ∈ p :=
QuotientAddGroup.eq
#align submodule.quotient.eq' Submodule.Quotient.eq'
protected theorem eq {x y : M} : (mk x : M ⧸ p) = (mk y : M ⧸ p) ↔ x - y ∈ p :=
(Submodule.Quotient.eq' p).trans (leftRel_apply.symm.trans p.quotientRel_r_def)
#align submodule.quotient.eq Submodule.Quotient.eq
instance : Zero (M ⧸ p) where
-- Use Quotient.mk'' instead of mk here because mk is not reducible.
-- This would lead to non-defeq diamonds.
-- See also the same comment at the One instance for Con.
zero := Quotient.mk'' 0
instance : Inhabited (M ⧸ p) :=
⟨0⟩
@[simp]
theorem mk_zero : mk 0 = (0 : M ⧸ p) :=
rfl
#align submodule.quotient.mk_zero Submodule.Quotient.mk_zero
@[simp]
theorem mk_eq_zero : (mk x : M ⧸ p) = 0 ↔ x ∈ p := by simpa using (Quotient.eq' p : mk x = 0 ↔ _)
#align submodule.quotient.mk_eq_zero Submodule.Quotient.mk_eq_zero
instance addCommGroup : AddCommGroup (M ⧸ p) :=
QuotientAddGroup.Quotient.addCommGroup p.toAddSubgroup
#align submodule.quotient.add_comm_group Submodule.Quotient.addCommGroup
@[simp]
theorem mk_add : (mk (x + y) : M ⧸ p) = (mk x : M ⧸ p) + (mk y : M ⧸ p) :=
rfl
#align submodule.quotient.mk_add Submodule.Quotient.mk_add
@[simp]
theorem mk_neg : (mk (-x) : M ⧸ p) = -(mk x : M ⧸ p) :=
rfl
#align submodule.quotient.mk_neg Submodule.Quotient.mk_neg
@[simp]
theorem mk_sub : (mk (x - y) : M ⧸ p) = (mk x : M ⧸ p) - (mk y : M ⧸ p) :=
rfl
#align submodule.quotient.mk_sub Submodule.Quotient.mk_sub
section SMul
variable {S : Type*} [SMul S R] [SMul S M] [IsScalarTower S R M] (P : Submodule R M)
instance instSMul' : SMul S (M ⧸ P) :=
⟨fun a =>
Quotient.map' (a • ·) fun x y h =>
leftRel_apply.mpr <| by simpa using Submodule.smul_mem P (a • (1 : R)) (leftRel_apply.mp h)⟩
#align submodule.quotient.has_smul' Submodule.Quotient.instSMul'
-- Porting note: should this be marked as a `@[default_instance]`?
/-- Shortcut to help the elaborator in the common case. -/
instance instSMul : SMul R (M ⧸ P) :=
Quotient.instSMul' P
#align submodule.quotient.has_smul Submodule.Quotient.instSMul
@[simp]
theorem mk_smul (r : S) (x : M) : (mk (r • x) : M ⧸ p) = r • mk x :=
rfl
#align submodule.quotient.mk_smul Submodule.Quotient.mk_smul
instance smulCommClass (T : Type*) [SMul T R] [SMul T M] [IsScalarTower T R M]
[SMulCommClass S T M] : SMulCommClass S T (M ⧸ P) where
smul_comm _x _y := Quotient.ind' fun _z => congr_arg mk (smul_comm _ _ _)
#align submodule.quotient.smul_comm_class Submodule.Quotient.smulCommClass
instance isScalarTower (T : Type*) [SMul T R] [SMul T M] [IsScalarTower T R M] [SMul S T]
[IsScalarTower S T M] : IsScalarTower S T (M ⧸ P) where
smul_assoc _x _y := Quotient.ind' fun _z => congr_arg mk (smul_assoc _ _ _)
#align submodule.quotient.is_scalar_tower Submodule.Quotient.isScalarTower
instance isCentralScalar [SMul Sᵐᵒᵖ R] [SMul Sᵐᵒᵖ M] [IsScalarTower Sᵐᵒᵖ R M]
[IsCentralScalar S M] : IsCentralScalar S (M ⧸ P) where
op_smul_eq_smul _x := Quotient.ind' fun _z => congr_arg mk <| op_smul_eq_smul _ _
#align submodule.quotient.is_central_scalar Submodule.Quotient.isCentralScalar
end SMul
section Module
variable {S : Type*}
-- Performance of `Function.Surjective.mulAction` is worse since it has to unify data to apply
-- TODO: leanprover-community/mathlib4#7432
instance mulAction' [Monoid S] [SMul S R] [MulAction S M] [IsScalarTower S R M]
(P : Submodule R M) : MulAction S (M ⧸ P) :=
{ Function.Surjective.mulAction mk (surjective_quot_mk _) <| Submodule.Quotient.mk_smul P with
toSMul := instSMul' _ }
#align submodule.quotient.mul_action' Submodule.Quotient.mulAction'
-- Porting note: should this be marked as a `@[default_instance]`?
instance mulAction (P : Submodule R M) : MulAction R (M ⧸ P) :=
Quotient.mulAction' P
#align submodule.quotient.mul_action Submodule.Quotient.mulAction
instance smulZeroClass' [SMul S R] [SMulZeroClass S M] [IsScalarTower S R M] (P : Submodule R M) :
SMulZeroClass S (M ⧸ P) :=
ZeroHom.smulZeroClass ⟨mk, mk_zero _⟩ <| Submodule.Quotient.mk_smul P
#align submodule.quotient.smul_zero_class' Submodule.Quotient.smulZeroClass'
-- Porting note: should this be marked as a `@[default_instance]`?
instance smulZeroClass (P : Submodule R M) : SMulZeroClass R (M ⧸ P) :=
Quotient.smulZeroClass' P
#align submodule.quotient.smul_zero_class Submodule.Quotient.smulZeroClass
-- Performance of `Function.Surjective.distribSMul` is worse since it has to unify data to apply
-- TODO: leanprover-community/mathlib4#7432
instance distribSMul' [SMul S R] [DistribSMul S M] [IsScalarTower S R M] (P : Submodule R M) :
DistribSMul S (M ⧸ P) :=
{ Function.Surjective.distribSMul {toFun := mk, map_zero' := rfl, map_add' := fun _ _ => rfl}
(surjective_quot_mk _) (Submodule.Quotient.mk_smul P) with
toSMulZeroClass := smulZeroClass' _ }
#align submodule.quotient.distrib_smul' Submodule.Quotient.distribSMul'
-- Porting note: should this be marked as a `@[default_instance]`?
instance distribSMul (P : Submodule R M) : DistribSMul R (M ⧸ P) :=
Quotient.distribSMul' P
#align submodule.quotient.distrib_smul Submodule.Quotient.distribSMul
-- Performance of `Function.Surjective.distribMulAction` is worse since it has to unify data
-- TODO: leanprover-community/mathlib4#7432
instance distribMulAction' [Monoid S] [SMul S R] [DistribMulAction S M] [IsScalarTower S R M]
(P : Submodule R M) : DistribMulAction S (M ⧸ P) :=
{ Function.Surjective.distribMulAction {toFun := mk, map_zero' := rfl, map_add' := fun _ _ => rfl}
(surjective_quot_mk _) (Submodule.Quotient.mk_smul P) with
toMulAction := mulAction' _ }
#align submodule.quotient.distrib_mul_action' Submodule.Quotient.distribMulAction'
-- Porting note: should this be marked as a `@[default_instance]`?
instance distribMulAction (P : Submodule R M) : DistribMulAction R (M ⧸ P) :=
Quotient.distribMulAction' P
#align submodule.quotient.distrib_mul_action Submodule.Quotient.distribMulAction
-- Performance of `Function.Surjective.module` is worse since it has to unify data to apply
-- TODO: leanprover-community/mathlib4#7432
instance module' [Semiring S] [SMul S R] [Module S M] [IsScalarTower S R M] (P : Submodule R M) :
Module S (M ⧸ P) :=
{ Function.Surjective.module _ {toFun := mk, map_zero' := by rfl, map_add' := fun _ _ => by rfl}
(surjective_quot_mk _) (Submodule.Quotient.mk_smul P) with
toDistribMulAction := distribMulAction' _ }
#align submodule.quotient.module' Submodule.Quotient.module'
-- Porting note: should this be marked as a `@[default_instance]`?
instance module (P : Submodule R M) : Module R (M ⧸ P) :=
Quotient.module' P
#align submodule.quotient.module Submodule.Quotient.module
variable (S)
/-- The quotient of `P` as an `S`-submodule is the same as the quotient of `P` as an `R`-submodule,
where `P : Submodule R M`.
-/
def restrictScalarsEquiv [Ring S] [SMul S R] [Module S M] [IsScalarTower S R M]
(P : Submodule R M) : (M ⧸ P.restrictScalars S) ≃ₗ[S] M ⧸ P :=
{ Quotient.congrRight fun _ _ => Iff.rfl with
map_add' := fun x y => Quotient.inductionOn₂' x y fun _x' _y' => rfl
map_smul' := fun _c x => Quotient.inductionOn' x fun _x' => rfl }
#align submodule.quotient.restrict_scalars_equiv Submodule.Quotient.restrictScalarsEquiv
@[simp]
theorem restrictScalarsEquiv_mk [Ring S] [SMul S R] [Module S M] [IsScalarTower S R M]
(P : Submodule R M) (x : M) :
restrictScalarsEquiv S P (mk x : M ⧸ P) = (mk x : M ⧸ P) :=
rfl
#align submodule.quotient.restrict_scalars_equiv_mk Submodule.Quotient.restrictScalarsEquiv_mk
@[simp]
theorem restrictScalarsEquiv_symm_mk [Ring S] [SMul S R] [Module S M] [IsScalarTower S R M]
(P : Submodule R M) (x : M) :
(restrictScalarsEquiv S P).symm ((mk : M → M ⧸ P) x) = (mk : M → M ⧸ P) x :=
rfl
#align submodule.quotient.restrict_scalars_equiv_symm_mk Submodule.Quotient.restrictScalarsEquiv_symm_mk
end Module
theorem mk_surjective : Function.Surjective (@mk _ _ _ _ _ p) := by
rintro ⟨x⟩
exact ⟨x, rfl⟩
#align submodule.quotient.mk_surjective Submodule.Quotient.mk_surjective
theorem nontrivial_of_lt_top (h : p < ⊤) : Nontrivial (M ⧸ p) := by
obtain ⟨x, _, not_mem_s⟩ := SetLike.exists_of_lt h
refine ⟨⟨mk x, 0, ?_⟩⟩
simpa using not_mem_s
#align submodule.quotient.nontrivial_of_lt_top Submodule.Quotient.nontrivial_of_lt_top
end Quotient
instance QuotientBot.infinite [Infinite M] : Infinite (M ⧸ (⊥ : Submodule R M)) :=
Infinite.of_injective Submodule.Quotient.mk fun _x _y h =>
sub_eq_zero.mp <| (Submodule.Quotient.eq ⊥).mp h
#align submodule.quotient_bot.infinite Submodule.QuotientBot.infinite
instance QuotientTop.unique : Unique (M ⧸ (⊤ : Submodule R M)) where
default := 0
uniq x := Quotient.inductionOn' x fun _x => (Submodule.Quotient.eq ⊤).mpr Submodule.mem_top
#align submodule.quotient_top.unique Submodule.QuotientTop.unique
instance QuotientTop.fintype : Fintype (M ⧸ (⊤ : Submodule R M)) :=
Fintype.ofSubsingleton 0
#align submodule.quotient_top.fintype Submodule.QuotientTop.fintype
variable {p}
theorem subsingleton_quotient_iff_eq_top : Subsingleton (M ⧸ p) ↔ p = ⊤ := by
constructor
· rintro h
refine eq_top_iff.mpr fun x _ => ?_
have : x - 0 ∈ p := (Submodule.Quotient.eq p).mp (Subsingleton.elim _ _)
rwa [sub_zero] at this
· rintro rfl
infer_instance
#align submodule.subsingleton_quotient_iff_eq_top Submodule.subsingleton_quotient_iff_eq_top
theorem unique_quotient_iff_eq_top : Nonempty (Unique (M ⧸ p)) ↔ p = ⊤ :=
⟨fun ⟨h⟩ => subsingleton_quotient_iff_eq_top.mp (@Unique.instSubsingleton _ h),
by rintro rfl; exact ⟨QuotientTop.unique⟩⟩
#align submodule.unique_quotient_iff_eq_top Submodule.unique_quotient_iff_eq_top
variable (p)
noncomputable instance Quotient.fintype [Fintype M] (S : Submodule R M) : Fintype (M ⧸ S) :=
@_root_.Quotient.fintype _ _ _ fun _ _ => Classical.dec _
#align submodule.quotient.fintype Submodule.Quotient.fintype
theorem card_eq_card_quotient_mul_card [Fintype M] (S : Submodule R M) [DecidablePred (· ∈ S)] :
Fintype.card M = Fintype.card S * Fintype.card (M ⧸ S) := by
rw [mul_comm, ← Fintype.card_prod]
exact Fintype.card_congr AddSubgroup.addGroupEquivQuotientProdAddSubgroup
#align submodule.card_eq_card_quotient_mul_card Submodule.card_eq_card_quotient_mul_card
section
variable {M₂ : Type*} [AddCommGroup M₂] [Module R M₂]
theorem quot_hom_ext (f g : (M ⧸ p) →ₗ[R] M₂) (h : ∀ x : M, f (Quotient.mk x) = g (Quotient.mk x)) :
f = g :=
LinearMap.ext fun x => Quotient.inductionOn' x h
#align submodule.quot_hom_ext Submodule.quot_hom_ext
/-- The map from a module `M` to the quotient of `M` by a submodule `p` as a linear map. -/
def mkQ : M →ₗ[R] M ⧸ p where
toFun := Quotient.mk
map_add' := by simp
map_smul' := by simp
#align submodule.mkq Submodule.mkQ
@[simp]
theorem mkQ_apply (x : M) : p.mkQ x = (Quotient.mk x : M ⧸ p) :=
rfl
#align submodule.mkq_apply Submodule.mkQ_apply
| Mathlib/LinearAlgebra/Quotient.lean | 334 | 335 | theorem mkQ_surjective (A : Submodule R M) : Function.Surjective A.mkQ := by |
rintro ⟨x⟩; exact ⟨x, rfl⟩
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Data.Fin.VecNotation
import Mathlib.Logic.Embedding.Set
#align_import logic.equiv.fin from "leanprover-community/mathlib"@"bd835ef554f37ef9b804f0903089211f89cb370b"
/-!
# Equivalences for `Fin n`
-/
assert_not_exists MonoidWithZero
universe u
variable {m n : ℕ}
/-- Equivalence between `Fin 0` and `Empty`. -/
def finZeroEquiv : Fin 0 ≃ Empty :=
Equiv.equivEmpty _
#align fin_zero_equiv finZeroEquiv
/-- Equivalence between `Fin 0` and `PEmpty`. -/
def finZeroEquiv' : Fin 0 ≃ PEmpty.{u} :=
Equiv.equivPEmpty _
#align fin_zero_equiv' finZeroEquiv'
/-- Equivalence between `Fin 1` and `Unit`. -/
def finOneEquiv : Fin 1 ≃ Unit :=
Equiv.equivPUnit _
#align fin_one_equiv finOneEquiv
/-- Equivalence between `Fin 2` and `Bool`. -/
def finTwoEquiv : Fin 2 ≃ Bool where
toFun := ![false, true]
invFun b := b.casesOn 0 1
left_inv := Fin.forall_fin_two.2 <| by simp
right_inv := Bool.forall_bool.2 <| by simp
#align fin_two_equiv finTwoEquiv
/-- `Π i : Fin 2, α i` is equivalent to `α 0 × α 1`. See also `finTwoArrowEquiv` for a
non-dependent version and `prodEquivPiFinTwo` for a version with inputs `α β : Type u`. -/
@[simps (config := .asFn)]
def piFinTwoEquiv (α : Fin 2 → Type u) : (∀ i, α i) ≃ α 0 × α 1 where
toFun f := (f 0, f 1)
invFun p := Fin.cons p.1 <| Fin.cons p.2 finZeroElim
left_inv _ := funext <| Fin.forall_fin_two.2 ⟨rfl, rfl⟩
right_inv := fun _ => rfl
#align pi_fin_two_equiv piFinTwoEquiv
#align pi_fin_two_equiv_symm_apply piFinTwoEquiv_symm_apply
#align pi_fin_two_equiv_apply piFinTwoEquiv_apply
theorem Fin.preimage_apply_01_prod {α : Fin 2 → Type u} (s : Set (α 0)) (t : Set (α 1)) :
(fun f : ∀ i, α i => (f 0, f 1)) ⁻¹' s ×ˢ t =
Set.pi Set.univ (Fin.cons s <| Fin.cons t finZeroElim) := by
ext f
simp [Fin.forall_fin_two]
#align fin.preimage_apply_01_prod Fin.preimage_apply_01_prod
theorem Fin.preimage_apply_01_prod' {α : Type u} (s t : Set α) :
(fun f : Fin 2 → α => (f 0, f 1)) ⁻¹' s ×ˢ t = Set.pi Set.univ ![s, t] :=
@Fin.preimage_apply_01_prod (fun _ => α) s t
#align fin.preimage_apply_01_prod' Fin.preimage_apply_01_prod'
/-- A product space `α × β` is equivalent to the space `Π i : Fin 2, γ i`, where
`γ = Fin.cons α (Fin.cons β finZeroElim)`. See also `piFinTwoEquiv` and
`finTwoArrowEquiv`. -/
@[simps! (config := .asFn)]
def prodEquivPiFinTwo (α β : Type u) : α × β ≃ ∀ i : Fin 2, ![α, β] i :=
(piFinTwoEquiv (Fin.cons α (Fin.cons β finZeroElim))).symm
#align prod_equiv_pi_fin_two prodEquivPiFinTwo
#align prod_equiv_pi_fin_two_apply prodEquivPiFinTwo_apply
#align prod_equiv_pi_fin_two_symm_apply prodEquivPiFinTwo_symm_apply
/-- The space of functions `Fin 2 → α` is equivalent to `α × α`. See also `piFinTwoEquiv` and
`prodEquivPiFinTwo`. -/
@[simps (config := .asFn)]
def finTwoArrowEquiv (α : Type*) : (Fin 2 → α) ≃ α × α :=
{ piFinTwoEquiv fun _ => α with invFun := fun x => ![x.1, x.2] }
#align fin_two_arrow_equiv finTwoArrowEquiv
#align fin_two_arrow_equiv_symm_apply finTwoArrowEquiv_symm_apply
#align fin_two_arrow_equiv_apply finTwoArrowEquiv_apply
/-- `Π i : Fin 2, α i` is order equivalent to `α 0 × α 1`. See also `OrderIso.finTwoArrowEquiv`
for a non-dependent version. -/
def OrderIso.piFinTwoIso (α : Fin 2 → Type u) [∀ i, Preorder (α i)] : (∀ i, α i) ≃o α 0 × α 1 where
toEquiv := piFinTwoEquiv α
map_rel_iff' := Iff.symm Fin.forall_fin_two
#align order_iso.pi_fin_two_iso OrderIso.piFinTwoIso
/-- The space of functions `Fin 2 → α` is order equivalent to `α × α`. See also
`OrderIso.piFinTwoIso`. -/
def OrderIso.finTwoArrowIso (α : Type*) [Preorder α] : (Fin 2 → α) ≃o α × α :=
{ OrderIso.piFinTwoIso fun _ => α with toEquiv := finTwoArrowEquiv α }
#align order_iso.fin_two_arrow_iso OrderIso.finTwoArrowIso
/-- An equivalence that removes `i` and maps it to `none`.
This is a version of `Fin.predAbove` that produces `Option (Fin n)` instead of
mapping both `i.cast_succ` and `i.succ` to `i`. -/
def finSuccEquiv' (i : Fin (n + 1)) : Fin (n + 1) ≃ Option (Fin n) where
toFun := i.insertNth none some
invFun x := x.casesOn' i (Fin.succAbove i)
left_inv x := Fin.succAboveCases i (by simp) (fun j => by simp) x
right_inv x := by cases x <;> dsimp <;> simp
#align fin_succ_equiv' finSuccEquiv'
@[simp]
theorem finSuccEquiv'_at (i : Fin (n + 1)) : (finSuccEquiv' i) i = none := by
simp [finSuccEquiv']
#align fin_succ_equiv'_at finSuccEquiv'_at
@[simp]
theorem finSuccEquiv'_succAbove (i : Fin (n + 1)) (j : Fin n) :
finSuccEquiv' i (i.succAbove j) = some j :=
@Fin.insertNth_apply_succAbove n (fun _ => Option (Fin n)) i _ _ _
#align fin_succ_equiv'_succ_above finSuccEquiv'_succAbove
theorem finSuccEquiv'_below {i : Fin (n + 1)} {m : Fin n} (h : Fin.castSucc m < i) :
(finSuccEquiv' i) (Fin.castSucc m) = m := by
rw [← Fin.succAbove_of_castSucc_lt _ _ h, finSuccEquiv'_succAbove]
#align fin_succ_equiv'_below finSuccEquiv'_below
theorem finSuccEquiv'_above {i : Fin (n + 1)} {m : Fin n} (h : i ≤ Fin.castSucc m) :
(finSuccEquiv' i) m.succ = some m := by
rw [← Fin.succAbove_of_le_castSucc _ _ h, finSuccEquiv'_succAbove]
#align fin_succ_equiv'_above finSuccEquiv'_above
@[simp]
theorem finSuccEquiv'_symm_none (i : Fin (n + 1)) : (finSuccEquiv' i).symm none = i :=
rfl
#align fin_succ_equiv'_symm_none finSuccEquiv'_symm_none
@[simp]
theorem finSuccEquiv'_symm_some (i : Fin (n + 1)) (j : Fin n) :
(finSuccEquiv' i).symm (some j) = i.succAbove j :=
rfl
#align fin_succ_equiv'_symm_some finSuccEquiv'_symm_some
theorem finSuccEquiv'_symm_some_below {i : Fin (n + 1)} {m : Fin n} (h : Fin.castSucc m < i) :
(finSuccEquiv' i).symm (some m) = Fin.castSucc m :=
Fin.succAbove_of_castSucc_lt i m h
#align fin_succ_equiv'_symm_some_below finSuccEquiv'_symm_some_below
theorem finSuccEquiv'_symm_some_above {i : Fin (n + 1)} {m : Fin n} (h : i ≤ Fin.castSucc m) :
(finSuccEquiv' i).symm (some m) = m.succ :=
Fin.succAbove_of_le_castSucc i m h
#align fin_succ_equiv'_symm_some_above finSuccEquiv'_symm_some_above
theorem finSuccEquiv'_symm_coe_below {i : Fin (n + 1)} {m : Fin n} (h : Fin.castSucc m < i) :
(finSuccEquiv' i).symm m = Fin.castSucc m :=
finSuccEquiv'_symm_some_below h
#align fin_succ_equiv'_symm_coe_below finSuccEquiv'_symm_coe_below
theorem finSuccEquiv'_symm_coe_above {i : Fin (n + 1)} {m : Fin n} (h : i ≤ Fin.castSucc m) :
(finSuccEquiv' i).symm m = m.succ :=
finSuccEquiv'_symm_some_above h
#align fin_succ_equiv'_symm_coe_above finSuccEquiv'_symm_coe_above
/-- Equivalence between `Fin (n + 1)` and `Option (Fin n)`.
This is a version of `Fin.pred` that produces `Option (Fin n)` instead of
requiring a proof that the input is not `0`. -/
def finSuccEquiv (n : ℕ) : Fin (n + 1) ≃ Option (Fin n) :=
finSuccEquiv' 0
#align fin_succ_equiv finSuccEquiv
@[simp]
theorem finSuccEquiv_zero : (finSuccEquiv n) 0 = none :=
rfl
#align fin_succ_equiv_zero finSuccEquiv_zero
@[simp]
theorem finSuccEquiv_succ (m : Fin n) : (finSuccEquiv n) m.succ = some m :=
finSuccEquiv'_above (Fin.zero_le _)
#align fin_succ_equiv_succ finSuccEquiv_succ
@[simp]
theorem finSuccEquiv_symm_none : (finSuccEquiv n).symm none = 0 :=
finSuccEquiv'_symm_none _
#align fin_succ_equiv_symm_none finSuccEquiv_symm_none
@[simp]
theorem finSuccEquiv_symm_some (m : Fin n) : (finSuccEquiv n).symm (some m) = m.succ :=
congr_fun Fin.succAbove_zero m
#align fin_succ_equiv_symm_some finSuccEquiv_symm_some
#align fin_succ_equiv_symm_coe finSuccEquiv_symm_some
/-- The equiv version of `Fin.predAbove_zero`. -/
theorem finSuccEquiv'_zero : finSuccEquiv' (0 : Fin (n + 1)) = finSuccEquiv n :=
rfl
#align fin_succ_equiv'_zero finSuccEquiv'_zero
theorem finSuccEquiv'_last_apply_castSucc (i : Fin n) :
finSuccEquiv' (Fin.last n) (Fin.castSucc i) = i := by
rw [← Fin.succAbove_last, finSuccEquiv'_succAbove]
theorem finSuccEquiv'_last_apply {i : Fin (n + 1)} (h : i ≠ Fin.last n) :
finSuccEquiv' (Fin.last n) i = Fin.castLT i (Fin.val_lt_last h) := by
rcases Fin.exists_castSucc_eq.2 h with ⟨i, rfl⟩
rw [finSuccEquiv'_last_apply_castSucc]
rfl
#align fin_succ_equiv'_last_apply finSuccEquiv'_last_apply
theorem finSuccEquiv'_ne_last_apply {i j : Fin (n + 1)} (hi : i ≠ Fin.last n) (hj : j ≠ i) :
finSuccEquiv' i j = (i.castLT (Fin.val_lt_last hi)).predAbove j := by
rcases Fin.exists_succAbove_eq hj with ⟨j, rfl⟩
rcases Fin.exists_castSucc_eq.2 hi with ⟨i, rfl⟩
simp
#align fin_succ_equiv'_ne_last_apply finSuccEquiv'_ne_last_apply
/-- `Fin.succAbove` as an order isomorphism between `Fin n` and `{x : Fin (n + 1) // x ≠ p}`. -/
def finSuccAboveEquiv (p : Fin (n + 1)) : Fin n ≃o { x : Fin (n + 1) // x ≠ p } :=
{ Equiv.optionSubtype p ⟨(finSuccEquiv' p).symm, rfl⟩ with
map_rel_iff' := p.succAboveOrderEmb.map_rel_iff' }
#align fin_succ_above_equiv finSuccAboveEquiv
theorem finSuccAboveEquiv_apply (p : Fin (n + 1)) (i : Fin n) :
finSuccAboveEquiv p i = ⟨p.succAbove i, p.succAbove_ne i⟩ :=
rfl
#align fin_succ_above_equiv_apply finSuccAboveEquiv_apply
theorem finSuccAboveEquiv_symm_apply_last (x : { x : Fin (n + 1) // x ≠ Fin.last n }) :
(finSuccAboveEquiv (Fin.last n)).symm x = Fin.castLT x.1 (Fin.val_lt_last x.2) := by
rw [← Option.some_inj]
simpa [finSuccAboveEquiv, OrderIso.symm] using finSuccEquiv'_last_apply x.property
#align fin_succ_above_equiv_symm_apply_last finSuccAboveEquiv_symm_apply_last
theorem finSuccAboveEquiv_symm_apply_ne_last {p : Fin (n + 1)} (h : p ≠ Fin.last n)
(x : { x : Fin (n + 1) // x ≠ p }) :
(finSuccAboveEquiv p).symm x = (p.castLT (Fin.val_lt_last h)).predAbove x := by
rw [← Option.some_inj]
simpa [finSuccAboveEquiv, OrderIso.symm] using finSuccEquiv'_ne_last_apply h x.property
#align fin_succ_above_equiv_symm_apply_ne_last finSuccAboveEquiv_symm_apply_ne_last
/-- `Equiv` between `Fin (n + 1)` and `Option (Fin n)` sending `Fin.last n` to `none` -/
def finSuccEquivLast : Fin (n + 1) ≃ Option (Fin n) :=
finSuccEquiv' (Fin.last n)
#align fin_succ_equiv_last finSuccEquivLast
@[simp]
theorem finSuccEquivLast_castSucc (i : Fin n) : finSuccEquivLast (Fin.castSucc i) = some i :=
finSuccEquiv'_below i.2
#align fin_succ_equiv_last_cast_succ finSuccEquivLast_castSucc
@[simp]
theorem finSuccEquivLast_last : finSuccEquivLast (Fin.last n) = none := by
simp [finSuccEquivLast]
#align fin_succ_equiv_last_last finSuccEquivLast_last
@[simp]
theorem finSuccEquivLast_symm_some (i : Fin n) :
finSuccEquivLast.symm (some i) = Fin.castSucc i :=
finSuccEquiv'_symm_some_below i.2
#align fin_succ_equiv_last_symm_some finSuccEquivLast_symm_some
#align fin_succ_equiv_last_symm_coe finSuccEquivLast_symm_some
@[simp] theorem finSuccEquivLast_symm_none : finSuccEquivLast.symm none = Fin.last n :=
finSuccEquiv'_symm_none _
#align fin_succ_equiv_last_symm_none finSuccEquivLast_symm_none
/-- Equivalence between `Π j : Fin (n + 1), α j` and `α i × Π j : Fin n, α (Fin.succAbove i j)`. -/
@[simps (config := .asFn)]
def Equiv.piFinSuccAbove (α : Fin (n + 1) → Type u) (i : Fin (n + 1)) :
(∀ j, α j) ≃ α i × ∀ j, α (i.succAbove j) where
toFun f := i.extractNth f
invFun f := i.insertNth f.1 f.2
left_inv f := by simp
right_inv f := by simp
#align equiv.pi_fin_succ_above_equiv Equiv.piFinSuccAbove
#align equiv.pi_fin_succ_above_equiv_apply Equiv.piFinSuccAbove_apply
#align equiv.pi_fin_succ_above_equiv_symm_apply Equiv.piFinSuccAbove_symm_apply
/-- Order isomorphism between `Π j : Fin (n + 1), α j` and
`α i × Π j : Fin n, α (Fin.succAbove i j)`. -/
def OrderIso.piFinSuccAboveIso (α : Fin (n + 1) → Type u) [∀ i, LE (α i)]
(i : Fin (n + 1)) : (∀ j, α j) ≃o α i × ∀ j, α (i.succAbove j) where
toEquiv := Equiv.piFinSuccAbove α i
map_rel_iff' := Iff.symm i.forall_iff_succAbove
#align order_iso.pi_fin_succ_above_iso OrderIso.piFinSuccAboveIso
/-- Equivalence between `Fin (n + 1) → β` and `β × (Fin n → β)`. -/
@[simps! (config := .asFn)]
def Equiv.piFinSucc (n : ℕ) (β : Type u) : (Fin (n + 1) → β) ≃ β × (Fin n → β) :=
Equiv.piFinSuccAbove (fun _ => β) 0
#align equiv.pi_fin_succ Equiv.piFinSucc
#align equiv.pi_fin_succ_apply Equiv.piFinSucc_apply
#align equiv.pi_fin_succ_symm_apply Equiv.piFinSucc_symm_apply
/-- An embedding `e : Fin (n+1) ↪ ι` corresponds to an embedding `f : Fin n ↪ ι` (corresponding
the last `n` coordinates of `e`) together with a value not taken by `f` (corresponding to `e 0`). -/
def Equiv.embeddingFinSucc (n : ℕ) (ι : Type*) :
(Fin (n+1) ↪ ι) ≃ (Σ (e : Fin n ↪ ι), {i // i ∉ Set.range e}) :=
((finSuccEquiv n).embeddingCongr (Equiv.refl ι)).trans
(Function.Embedding.optionEmbeddingEquiv (Fin n) ι)
@[simp] lemma Equiv.embeddingFinSucc_fst {n : ℕ} {ι : Type*} (e : Fin (n+1) ↪ ι) :
((Equiv.embeddingFinSucc n ι e).1 : Fin n → ι) = e ∘ Fin.succ := rfl
@[simp] lemma Equiv.embeddingFinSucc_snd {n : ℕ} {ι : Type*} (e : Fin (n+1) ↪ ι) :
((Equiv.embeddingFinSucc n ι e).2 : ι) = e 0 := rfl
@[simp] lemma Equiv.coe_embeddingFinSucc_symm {n : ℕ} {ι : Type*}
(f : Σ (e : Fin n ↪ ι), {i // i ∉ Set.range e}) :
((Equiv.embeddingFinSucc n ι).symm f : Fin (n + 1) → ι) = Fin.cons f.2.1 f.1 := by
ext i
exact Fin.cases rfl (fun j ↦ rfl) i
/-- Equivalence between `Fin (n + 1) → β` and `β × (Fin n → β)` which separates out the last
element of the tuple. -/
@[simps! (config := .asFn)]
def Equiv.piFinCastSucc (n : ℕ) (β : Type u) : (Fin (n + 1) → β) ≃ β × (Fin n → β) :=
Equiv.piFinSuccAbove (fun _ => β) (.last _)
/-- Equivalence between `Fin m ⊕ Fin n` and `Fin (m + n)` -/
def finSumFinEquiv : Sum (Fin m) (Fin n) ≃ Fin (m + n) where
toFun := Sum.elim (Fin.castAdd n) (Fin.natAdd m)
invFun i := @Fin.addCases m n (fun _ => Sum (Fin m) (Fin n)) Sum.inl Sum.inr i
left_inv x := by cases' x with y y <;> dsimp <;> simp
right_inv x := by refine Fin.addCases (fun i => ?_) (fun i => ?_) x <;> simp
#align fin_sum_fin_equiv finSumFinEquiv
@[simp]
theorem finSumFinEquiv_apply_left (i : Fin m) :
(finSumFinEquiv (Sum.inl i) : Fin (m + n)) = Fin.castAdd n i :=
rfl
#align fin_sum_fin_equiv_apply_left finSumFinEquiv_apply_left
@[simp]
theorem finSumFinEquiv_apply_right (i : Fin n) :
(finSumFinEquiv (Sum.inr i) : Fin (m + n)) = Fin.natAdd m i :=
rfl
#align fin_sum_fin_equiv_apply_right finSumFinEquiv_apply_right
@[simp]
theorem finSumFinEquiv_symm_apply_castAdd (x : Fin m) :
finSumFinEquiv.symm (Fin.castAdd n x) = Sum.inl x :=
finSumFinEquiv.symm_apply_apply (Sum.inl x)
#align fin_sum_fin_equiv_symm_apply_cast_add finSumFinEquiv_symm_apply_castAdd
@[simp]
theorem finSumFinEquiv_symm_apply_natAdd (x : Fin n) :
finSumFinEquiv.symm (Fin.natAdd m x) = Sum.inr x :=
finSumFinEquiv.symm_apply_apply (Sum.inr x)
#align fin_sum_fin_equiv_symm_apply_nat_add finSumFinEquiv_symm_apply_natAdd
@[simp]
theorem finSumFinEquiv_symm_last : finSumFinEquiv.symm (Fin.last n) = Sum.inr 0 :=
finSumFinEquiv_symm_apply_natAdd 0
#align fin_sum_fin_equiv_symm_last finSumFinEquiv_symm_last
/-- The equivalence between `Fin (m + n)` and `Fin (n + m)` which rotates by `n`. -/
def finAddFlip : Fin (m + n) ≃ Fin (n + m) :=
(finSumFinEquiv.symm.trans (Equiv.sumComm _ _)).trans finSumFinEquiv
#align fin_add_flip finAddFlip
@[simp]
theorem finAddFlip_apply_castAdd (k : Fin m) (n : ℕ) :
finAddFlip (Fin.castAdd n k) = Fin.natAdd n k := by simp [finAddFlip]
#align fin_add_flip_apply_cast_add finAddFlip_apply_castAdd
@[simp]
theorem finAddFlip_apply_natAdd (k : Fin n) (m : ℕ) :
finAddFlip (Fin.natAdd m k) = Fin.castAdd m k := by simp [finAddFlip]
#align fin_add_flip_apply_nat_add finAddFlip_apply_natAdd
@[simp]
theorem finAddFlip_apply_mk_left {k : ℕ} (h : k < m) (hk : k < m + n := Nat.lt_add_right n h)
(hnk : n + k < n + m := Nat.add_lt_add_left h n) :
finAddFlip (⟨k, hk⟩ : Fin (m + n)) = ⟨n + k, hnk⟩ := by
convert finAddFlip_apply_castAdd ⟨k, h⟩ n
#align fin_add_flip_apply_mk_left finAddFlip_apply_mk_left
@[simp]
theorem finAddFlip_apply_mk_right {k : ℕ} (h₁ : m ≤ k) (h₂ : k < m + n) :
finAddFlip (⟨k, h₂⟩ : Fin (m + n)) = ⟨k - m, by omega⟩ := by
convert @finAddFlip_apply_natAdd n ⟨k - m, by omega⟩ m
simp [Nat.add_sub_cancel' h₁]
#align fin_add_flip_apply_mk_right finAddFlip_apply_mk_right
/-- Rotate `Fin n` one step to the right. -/
def finRotate : ∀ n, Equiv.Perm (Fin n)
| 0 => Equiv.refl _
| n + 1 => finAddFlip.trans (finCongr (Nat.add_comm 1 n))
#align fin_rotate finRotate
@[simp] lemma finRotate_zero : finRotate 0 = Equiv.refl _ := rfl
#align fin_rotate_zero finRotate_zero
lemma finRotate_succ (n : ℕ) :
finRotate (n + 1) = finAddFlip.trans (finCongr (Nat.add_comm 1 n)) := rfl
theorem finRotate_of_lt {k : ℕ} (h : k < n) :
finRotate (n + 1) ⟨k, h.trans_le n.le_succ⟩ = ⟨k + 1, Nat.succ_lt_succ h⟩ := by
ext
dsimp [finRotate_succ]
simp [finAddFlip_apply_mk_left h, Nat.add_comm]
#align fin_rotate_of_lt finRotate_of_lt
theorem finRotate_last' : finRotate (n + 1) ⟨n, by omega⟩ = ⟨0, Nat.zero_lt_succ _⟩ := by
dsimp [finRotate_succ]
rw [finAddFlip_apply_mk_right le_rfl]
simp
#align fin_rotate_last' finRotate_last'
theorem finRotate_last : finRotate (n + 1) (Fin.last _) = 0 :=
finRotate_last'
#align fin_rotate_last finRotate_last
theorem Fin.snoc_eq_cons_rotate {α : Type*} (v : Fin n → α) (a : α) :
@Fin.snoc _ (fun _ => α) v a = fun i => @Fin.cons _ (fun _ => α) a v (finRotate _ i) := by
ext ⟨i, h⟩
by_cases h' : i < n
· rw [finRotate_of_lt h', Fin.snoc, Fin.cons, dif_pos h']
rfl
· have h'' : n = i := by
simp only [not_lt] at h'
exact (Nat.eq_of_le_of_lt_succ h' h).symm
subst h''
rw [finRotate_last', Fin.snoc, Fin.cons, dif_neg (lt_irrefl _)]
rfl
#align fin.snoc_eq_cons_rotate Fin.snoc_eq_cons_rotate
@[simp]
theorem finRotate_one : finRotate 1 = Equiv.refl _ :=
Subsingleton.elim _ _
#align fin_rotate_one finRotate_one
@[simp] theorem finRotate_succ_apply (i : Fin (n + 1)) : finRotate (n + 1) i = i + 1 := by
cases n
· exact @Subsingleton.elim (Fin 1) _ _ _
rcases i.le_last.eq_or_lt with (rfl | h)
· simp [finRotate_last]
· cases i
simp only [Fin.lt_iff_val_lt_val, Fin.val_last, Fin.val_mk] at h
simp [finRotate_of_lt h, Fin.ext_iff, Fin.add_def, Nat.mod_eq_of_lt (Nat.succ_lt_succ h)]
#align fin_rotate_succ_apply finRotate_succ_apply
-- Porting note: was a @[simp]
theorem finRotate_apply_zero : finRotate n.succ 0 = 1 := by
rw [finRotate_succ_apply, Fin.zero_add]
#align fin_rotate_apply_zero finRotate_apply_zero
theorem coe_finRotate_of_ne_last {i : Fin n.succ} (h : i ≠ Fin.last n) :
(finRotate (n + 1) i : ℕ) = i + 1 := by
rw [finRotate_succ_apply]
have : (i : ℕ) < n := Fin.val_lt_last h
exact Fin.val_add_one_of_lt this
#align coe_fin_rotate_of_ne_last coe_finRotate_of_ne_last
| Mathlib/Logic/Equiv/Fin.lean | 452 | 454 | theorem coe_finRotate (i : Fin n.succ) :
(finRotate n.succ i : ℕ) = if i = Fin.last n then (0 : ℕ) else i + 1 := by |
rw [finRotate_succ_apply, Fin.val_add_one i]
|
/-
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.ModelTheory.Ultraproducts
import Mathlib.ModelTheory.Bundled
import Mathlib.ModelTheory.Skolem
#align_import model_theory.satisfiability from "leanprover-community/mathlib"@"d565b3df44619c1498326936be16f1a935df0728"
/-!
# First-Order Satisfiability
This file deals with the satisfiability of first-order theories, as well as equivalence over them.
## Main Definitions
* `FirstOrder.Language.Theory.IsSatisfiable`: `T.IsSatisfiable` indicates that `T` has a nonempty
model.
* `FirstOrder.Language.Theory.IsFinitelySatisfiable`: `T.IsFinitelySatisfiable` indicates that
every finite subset of `T` is satisfiable.
* `FirstOrder.Language.Theory.IsComplete`: `T.IsComplete` indicates that `T` is satisfiable and
models each sentence or its negation.
* `FirstOrder.Language.Theory.SemanticallyEquivalent`: `T.SemanticallyEquivalent φ ψ` indicates
that `φ` and `ψ` are equivalent formulas or sentences in models of `T`.
* `Cardinal.Categorical`: A theory is `κ`-categorical if all models of size `κ` are isomorphic.
## Main Results
* The Compactness Theorem, `FirstOrder.Language.Theory.isSatisfiable_iff_isFinitelySatisfiable`,
shows that a theory is satisfiable iff it is finitely satisfiable.
* `FirstOrder.Language.completeTheory.isComplete`: The complete theory of a structure is
complete.
* `FirstOrder.Language.Theory.exists_large_model_of_infinite_model` shows that any theory with an
infinite model has arbitrarily large models.
* `FirstOrder.Language.Theory.exists_elementaryEmbedding_card_eq`: The Upward Löwenheim–Skolem
Theorem: If `κ` is a cardinal greater than the cardinalities of `L` and an infinite `L`-structure
`M`, then `M` has an elementary extension of cardinality `κ`.
## Implementation Details
* Satisfiability of an `L.Theory` `T` is defined in the minimal universe containing all the symbols
of `L`. By Löwenheim-Skolem, this is equivalent to satisfiability in any universe.
-/
set_option linter.uppercaseLean3 false
universe u v w w'
open Cardinal CategoryTheory
open Cardinal FirstOrder
namespace FirstOrder
namespace Language
variable {L : Language.{u, v}} {T : L.Theory} {α : Type w} {n : ℕ}
namespace Theory
variable (T)
/-- A theory is satisfiable if a structure models it. -/
def IsSatisfiable : Prop :=
Nonempty (ModelType.{u, v, max u v} T)
#align first_order.language.Theory.is_satisfiable FirstOrder.Language.Theory.IsSatisfiable
/-- A theory is finitely satisfiable if all of its finite subtheories are satisfiable. -/
def IsFinitelySatisfiable : Prop :=
∀ T0 : Finset L.Sentence, (T0 : L.Theory) ⊆ T → IsSatisfiable (T0 : L.Theory)
#align first_order.language.Theory.is_finitely_satisfiable FirstOrder.Language.Theory.IsFinitelySatisfiable
variable {T} {T' : L.Theory}
theorem Model.isSatisfiable (M : Type w) [Nonempty M] [L.Structure M] [M ⊨ T] :
T.IsSatisfiable :=
⟨((⊥ : Substructure _ (ModelType.of T M)).elementarySkolem₁Reduct.toModel T).shrink⟩
#align first_order.language.Theory.model.is_satisfiable FirstOrder.Language.Theory.Model.isSatisfiable
theorem IsSatisfiable.mono (h : T'.IsSatisfiable) (hs : T ⊆ T') : T.IsSatisfiable :=
⟨(Theory.Model.mono (ModelType.is_model h.some) hs).bundled⟩
#align first_order.language.Theory.is_satisfiable.mono FirstOrder.Language.Theory.IsSatisfiable.mono
theorem isSatisfiable_empty (L : Language.{u, v}) : IsSatisfiable (∅ : L.Theory) :=
⟨default⟩
#align first_order.language.Theory.is_satisfiable_empty FirstOrder.Language.Theory.isSatisfiable_empty
theorem isSatisfiable_of_isSatisfiable_onTheory {L' : Language.{w, w'}} (φ : L →ᴸ L')
(h : (φ.onTheory T).IsSatisfiable) : T.IsSatisfiable :=
Model.isSatisfiable (h.some.reduct φ)
#align first_order.language.Theory.is_satisfiable_of_is_satisfiable_on_Theory FirstOrder.Language.Theory.isSatisfiable_of_isSatisfiable_onTheory
theorem isSatisfiable_onTheory_iff {L' : Language.{w, w'}} {φ : L →ᴸ L'} (h : φ.Injective) :
(φ.onTheory T).IsSatisfiable ↔ T.IsSatisfiable := by
classical
refine ⟨isSatisfiable_of_isSatisfiable_onTheory φ, fun h' => ?_⟩
haveI : Inhabited h'.some := Classical.inhabited_of_nonempty'
exact Model.isSatisfiable (h'.some.defaultExpansion h)
#align first_order.language.Theory.is_satisfiable_on_Theory_iff FirstOrder.Language.Theory.isSatisfiable_onTheory_iff
theorem IsSatisfiable.isFinitelySatisfiable (h : T.IsSatisfiable) : T.IsFinitelySatisfiable :=
fun _ => h.mono
#align first_order.language.Theory.is_satisfiable.is_finitely_satisfiable FirstOrder.Language.Theory.IsSatisfiable.isFinitelySatisfiable
/-- The **Compactness Theorem of first-order logic**: A theory is satisfiable if and only if it is
finitely satisfiable. -/
theorem isSatisfiable_iff_isFinitelySatisfiable {T : L.Theory} :
T.IsSatisfiable ↔ T.IsFinitelySatisfiable :=
⟨Theory.IsSatisfiable.isFinitelySatisfiable, fun h => by
classical
set M : Finset T → Type max u v := fun T0 : Finset T =>
(h (T0.map (Function.Embedding.subtype fun x => x ∈ T)) T0.map_subtype_subset).some.Carrier
let M' := Filter.Product (Ultrafilter.of (Filter.atTop : Filter (Finset T))) M
have h' : M' ⊨ T := by
refine ⟨fun φ hφ => ?_⟩
rw [Ultraproduct.sentence_realize]
refine
Filter.Eventually.filter_mono (Ultrafilter.of_le _)
(Filter.eventually_atTop.2
⟨{⟨φ, hφ⟩}, fun s h' =>
Theory.realize_sentence_of_mem (s.map (Function.Embedding.subtype fun x => x ∈ T))
?_⟩)
simp only [Finset.coe_map, Function.Embedding.coe_subtype, Set.mem_image, Finset.mem_coe,
Subtype.exists, Subtype.coe_mk, exists_and_right, exists_eq_right]
exact ⟨hφ, h' (Finset.mem_singleton_self _)⟩
exact ⟨ModelType.of T M'⟩⟩
#align first_order.language.Theory.is_satisfiable_iff_is_finitely_satisfiable FirstOrder.Language.Theory.isSatisfiable_iff_isFinitelySatisfiable
theorem isSatisfiable_directed_union_iff {ι : Type*} [Nonempty ι] {T : ι → L.Theory}
(h : Directed (· ⊆ ·) T) : Theory.IsSatisfiable (⋃ i, T i) ↔ ∀ i, (T i).IsSatisfiable := by
refine ⟨fun h' i => h'.mono (Set.subset_iUnion _ _), fun h' => ?_⟩
rw [isSatisfiable_iff_isFinitelySatisfiable, IsFinitelySatisfiable]
intro T0 hT0
obtain ⟨i, hi⟩ := h.exists_mem_subset_of_finset_subset_biUnion hT0
exact (h' i).mono hi
#align first_order.language.Theory.is_satisfiable_directed_union_iff FirstOrder.Language.Theory.isSatisfiable_directed_union_iff
theorem isSatisfiable_union_distinctConstantsTheory_of_card_le (T : L.Theory) (s : Set α)
(M : Type w') [Nonempty M] [L.Structure M] [M ⊨ T]
(h : Cardinal.lift.{w'} #s ≤ Cardinal.lift.{w} #M) :
((L.lhomWithConstants α).onTheory T ∪ L.distinctConstantsTheory s).IsSatisfiable := by
haveI : Inhabited M := Classical.inhabited_of_nonempty inferInstance
rw [Cardinal.lift_mk_le'] at h
letI : (constantsOn α).Structure M := constantsOn.structure (Function.extend (↑) h.some default)
have : M ⊨ (L.lhomWithConstants α).onTheory T ∪ L.distinctConstantsTheory s := by
refine ((LHom.onTheory_model _ _).2 inferInstance).union ?_
rw [model_distinctConstantsTheory]
refine fun a as b bs ab => ?_
rw [← Subtype.coe_mk a as, ← Subtype.coe_mk b bs, ← Subtype.ext_iff]
exact
h.some.injective
((Subtype.coe_injective.extend_apply h.some default ⟨a, as⟩).symm.trans
(ab.trans (Subtype.coe_injective.extend_apply h.some default ⟨b, bs⟩)))
exact Model.isSatisfiable M
#align first_order.language.Theory.is_satisfiable_union_distinct_constants_theory_of_card_le FirstOrder.Language.Theory.isSatisfiable_union_distinctConstantsTheory_of_card_le
theorem isSatisfiable_union_distinctConstantsTheory_of_infinite (T : L.Theory) (s : Set α)
(M : Type w') [L.Structure M] [M ⊨ T] [Infinite M] :
((L.lhomWithConstants α).onTheory T ∪ L.distinctConstantsTheory s).IsSatisfiable := by
classical
rw [distinctConstantsTheory_eq_iUnion, Set.union_iUnion, isSatisfiable_directed_union_iff]
· exact fun t =>
isSatisfiable_union_distinctConstantsTheory_of_card_le T _ M
((lift_le_aleph0.2 (finset_card_lt_aleph0 _).le).trans
(aleph0_le_lift.2 (aleph0_le_mk M)))
· apply Monotone.directed_le
refine monotone_const.union (monotone_distinctConstantsTheory.comp ?_)
simp only [Finset.coe_map, Function.Embedding.coe_subtype]
exact Monotone.comp (g := Set.image ((↑) : s → α)) (f := ((↑) : Finset s → Set s))
Set.monotone_image fun _ _ => Finset.coe_subset.2
#align first_order.language.Theory.is_satisfiable_union_distinct_constants_theory_of_infinite FirstOrder.Language.Theory.isSatisfiable_union_distinctConstantsTheory_of_infinite
/-- Any theory with an infinite model has arbitrarily large models. -/
theorem exists_large_model_of_infinite_model (T : L.Theory) (κ : Cardinal.{w}) (M : Type w')
[L.Structure M] [M ⊨ T] [Infinite M] :
∃ N : ModelType.{_, _, max u v w} T, Cardinal.lift.{max u v w} κ ≤ #N := by
obtain ⟨N⟩ :=
isSatisfiable_union_distinctConstantsTheory_of_infinite T (Set.univ : Set κ.out) M
refine ⟨(N.is_model.mono Set.subset_union_left).bundled.reduct _, ?_⟩
haveI : N ⊨ distinctConstantsTheory _ _ := N.is_model.mono Set.subset_union_right
rw [ModelType.reduct_Carrier, coe_of]
refine _root_.trans (lift_le.2 (le_of_eq (Cardinal.mk_out κ).symm)) ?_
rw [← mk_univ]
refine
(card_le_of_model_distinctConstantsTheory L Set.univ N).trans (lift_le.{max u v w}.1 ?_)
rw [lift_lift]
#align first_order.language.Theory.exists_large_model_of_infinite_model FirstOrder.Language.Theory.exists_large_model_of_infinite_model
theorem isSatisfiable_iUnion_iff_isSatisfiable_iUnion_finset {ι : Type*} (T : ι → L.Theory) :
IsSatisfiable (⋃ i, T i) ↔ ∀ s : Finset ι, IsSatisfiable (⋃ i ∈ s, T i) := by
classical
refine
⟨fun h s => h.mono (Set.iUnion_mono fun _ => Set.iUnion_subset_iff.2 fun _ => refl _),
fun h => ?_⟩
rw [isSatisfiable_iff_isFinitelySatisfiable]
intro s hs
rw [Set.iUnion_eq_iUnion_finset] at hs
obtain ⟨t, ht⟩ := Directed.exists_mem_subset_of_finset_subset_biUnion (by
exact Monotone.directed_le fun t1 t2 (h : ∀ ⦃x⦄, x ∈ t1 → x ∈ t2) =>
Set.iUnion_mono fun _ => Set.iUnion_mono' fun h1 => ⟨h h1, refl _⟩) hs
exact (h t).mono ht
#align first_order.language.Theory.is_satisfiable_Union_iff_is_satisfiable_Union_finset FirstOrder.Language.Theory.isSatisfiable_iUnion_iff_isSatisfiable_iUnion_finset
end Theory
variable (L)
/-- A version of The Downward Löwenheim–Skolem theorem where the structure `N` elementarily embeds
into `M`, but is not by type a substructure of `M`, and thus can be chosen to belong to the universe
of the cardinal `κ`.
-/
theorem exists_elementaryEmbedding_card_eq_of_le (M : Type w') [L.Structure M] [Nonempty M]
(κ : Cardinal.{w}) (h1 : ℵ₀ ≤ κ) (h2 : lift.{w} L.card ≤ Cardinal.lift.{max u v} κ)
(h3 : lift.{w'} κ ≤ Cardinal.lift.{w} #M) :
∃ N : Bundled L.Structure, Nonempty (N ↪ₑ[L] M) ∧ #N = κ := by
obtain ⟨S, _, hS⟩ := exists_elementarySubstructure_card_eq L ∅ κ h1 (by simp) h2 h3
have : Small.{w} S := by
rw [← lift_inj.{_, w + 1}, lift_lift, lift_lift] at hS
exact small_iff_lift_mk_lt_univ.2 (lt_of_eq_of_lt hS κ.lift_lt_univ')
refine
⟨(equivShrink S).bundledInduced L,
⟨S.subtype.comp (Equiv.bundledInducedEquiv L _).symm.toElementaryEmbedding⟩,
lift_inj.1 (_root_.trans ?_ hS)⟩
simp only [Equiv.bundledInduced_α, lift_mk_shrink']
#align first_order.language.exists_elementary_embedding_card_eq_of_le FirstOrder.Language.exists_elementaryEmbedding_card_eq_of_le
section
-- Porting note: This instance interrupts synthesizing instances.
attribute [-instance] FirstOrder.Language.withConstants_expansion
/-- The **Upward Löwenheim–Skolem Theorem**: If `κ` is a cardinal greater than the cardinalities of
`L` and an infinite `L`-structure `M`, then `M` has an elementary extension of cardinality `κ`. -/
theorem exists_elementaryEmbedding_card_eq_of_ge (M : Type w') [L.Structure M] [iM : Infinite M]
(κ : Cardinal.{w}) (h1 : Cardinal.lift.{w} L.card ≤ Cardinal.lift.{max u v} κ)
(h2 : Cardinal.lift.{w} #M ≤ Cardinal.lift.{w'} κ) :
∃ N : Bundled L.Structure, Nonempty (M ↪ₑ[L] N) ∧ #N = κ := by
obtain ⟨N0, hN0⟩ := (L.elementaryDiagram M).exists_large_model_of_infinite_model κ M
rw [← lift_le.{max u v}, lift_lift, lift_lift] at h2
obtain ⟨N, ⟨NN0⟩, hN⟩ :=
exists_elementaryEmbedding_card_eq_of_le (L[[M]]) N0 κ
(aleph0_le_lift.1 ((aleph0_le_lift.2 (aleph0_le_mk M)).trans h2))
(by
simp only [card_withConstants, lift_add, lift_lift]
rw [add_comm, add_eq_max (aleph0_le_lift.2 (infinite_iff.1 iM)), max_le_iff]
rw [← lift_le.{w'}, lift_lift, lift_lift] at h1
exact ⟨h2, h1⟩)
(hN0.trans (by rw [← lift_umax', lift_id]))
letI := (lhomWithConstants L M).reduct N
haveI h : N ⊨ L.elementaryDiagram M :=
(NN0.theory_model_iff (L.elementaryDiagram M)).2 inferInstance
refine ⟨Bundled.of N, ⟨?_⟩, hN⟩
apply ElementaryEmbedding.ofModelsElementaryDiagram L M N
#align first_order.language.exists_elementary_embedding_card_eq_of_ge FirstOrder.Language.exists_elementaryEmbedding_card_eq_of_ge
end
/-- The Löwenheim–Skolem Theorem: If `κ` is a cardinal greater than the cardinalities of `L`
and an infinite `L`-structure `M`, then there is an elementary embedding in the appropriate
direction between then `M` and a structure of cardinality `κ`. -/
theorem exists_elementaryEmbedding_card_eq (M : Type w') [L.Structure M] [iM : Infinite M]
(κ : Cardinal.{w}) (h1 : ℵ₀ ≤ κ) (h2 : lift.{w} L.card ≤ Cardinal.lift.{max u v} κ) :
∃ N : Bundled L.Structure, (Nonempty (N ↪ₑ[L] M) ∨ Nonempty (M ↪ₑ[L] N)) ∧ #N = κ := by
cases le_or_gt (lift.{w'} κ) (Cardinal.lift.{w} #M) with
| inl h =>
obtain ⟨N, hN1, hN2⟩ := exists_elementaryEmbedding_card_eq_of_le L M κ h1 h2 h
exact ⟨N, Or.inl hN1, hN2⟩
| inr h =>
obtain ⟨N, hN1, hN2⟩ := exists_elementaryEmbedding_card_eq_of_ge L M κ h2 (le_of_lt h)
exact ⟨N, Or.inr hN1, hN2⟩
#align first_order.language.exists_elementary_embedding_card_eq FirstOrder.Language.exists_elementaryEmbedding_card_eq
/-- A consequence of the Löwenheim–Skolem Theorem: If `κ` is a cardinal greater than the
cardinalities of `L` and an infinite `L`-structure `M`, then there is a structure of cardinality `κ`
elementarily equivalent to `M`. -/
theorem exists_elementarilyEquivalent_card_eq (M : Type w') [L.Structure M] [Infinite M]
(κ : Cardinal.{w}) (h1 : ℵ₀ ≤ κ) (h2 : lift.{w} L.card ≤ Cardinal.lift.{max u v} κ) :
∃ N : CategoryTheory.Bundled L.Structure, (M ≅[L] N) ∧ #N = κ := by
obtain ⟨N, NM | MN, hNκ⟩ := exists_elementaryEmbedding_card_eq L M κ h1 h2
· exact ⟨N, NM.some.elementarilyEquivalent.symm, hNκ⟩
· exact ⟨N, MN.some.elementarilyEquivalent, hNκ⟩
#align first_order.language.exists_elementarily_equivalent_card_eq FirstOrder.Language.exists_elementarilyEquivalent_card_eq
variable {L}
namespace Theory
theorem exists_model_card_eq (h : ∃ M : ModelType.{u, v, max u v} T, Infinite M) (κ : Cardinal.{w})
(h1 : ℵ₀ ≤ κ) (h2 : Cardinal.lift.{w} L.card ≤ Cardinal.lift.{max u v} κ) :
∃ N : ModelType.{u, v, w} T, #N = κ := by
cases h with
| intro M MI =>
haveI := MI
obtain ⟨N, hN, rfl⟩ := exists_elementarilyEquivalent_card_eq L M κ h1 h2
haveI : Nonempty N := hN.nonempty
exact ⟨hN.theory_model.bundled, rfl⟩
#align first_order.language.Theory.exists_model_card_eq FirstOrder.Language.Theory.exists_model_card_eq
variable (T)
/-- A theory models a (bounded) formula when any of its nonempty models realizes that formula on all
inputs. -/
def ModelsBoundedFormula (φ : L.BoundedFormula α n) : Prop :=
∀ (M : ModelType.{u, v, max u v} T) (v : α → M) (xs : Fin n → M), φ.Realize v xs
#align first_order.language.Theory.models_bounded_formula FirstOrder.Language.Theory.ModelsBoundedFormula
-- Porting note: In Lean3 it was `⊨` but ambiguous.
@[inherit_doc FirstOrder.Language.Theory.ModelsBoundedFormula]
infixl:51 " ⊨ᵇ " => ModelsBoundedFormula -- input using \|= or \vDash, but not using \models
variable {T}
theorem models_formula_iff {φ : L.Formula α} :
T ⊨ᵇ φ ↔ ∀ (M : ModelType.{u, v, max u v} T) (v : α → M), φ.Realize v :=
forall_congr' fun _ => forall_congr' fun _ => Unique.forall_iff
#align first_order.language.Theory.models_formula_iff FirstOrder.Language.Theory.models_formula_iff
theorem models_sentence_iff {φ : L.Sentence} : T ⊨ᵇ φ ↔ ∀ M : ModelType.{u, v, max u v} T, M ⊨ φ :=
models_formula_iff.trans (forall_congr' fun _ => Unique.forall_iff)
#align first_order.language.Theory.models_sentence_iff FirstOrder.Language.Theory.models_sentence_iff
theorem models_sentence_of_mem {φ : L.Sentence} (h : φ ∈ T) : T ⊨ᵇ φ :=
models_sentence_iff.2 fun _ => realize_sentence_of_mem T h
#align first_order.language.Theory.models_sentence_of_mem FirstOrder.Language.Theory.models_sentence_of_mem
theorem models_iff_not_satisfiable (φ : L.Sentence) : T ⊨ᵇ φ ↔ ¬IsSatisfiable (T ∪ {φ.not}) := by
rw [models_sentence_iff, IsSatisfiable]
refine
⟨fun h1 h2 =>
(Sentence.realize_not _).1
(realize_sentence_of_mem (T ∪ {Formula.not φ})
(Set.subset_union_right (Set.mem_singleton _)))
(h1 (h2.some.subtheoryModel Set.subset_union_left)),
fun h M => ?_⟩
contrapose! h
rw [← Sentence.realize_not] at h
refine
⟨{ Carrier := M
is_model := ⟨fun ψ hψ => hψ.elim (realize_sentence_of_mem _) fun h' => ?_⟩ }⟩
rw [Set.mem_singleton_iff.1 h']
exact h
#align first_order.language.Theory.models_iff_not_satisfiable FirstOrder.Language.Theory.models_iff_not_satisfiable
theorem ModelsBoundedFormula.realize_sentence {φ : L.Sentence} (h : T ⊨ᵇ φ) (M : Type*)
[L.Structure M] [M ⊨ T] [Nonempty M] : M ⊨ φ := by
rw [models_iff_not_satisfiable] at h
contrapose! h
have : M ⊨ T ∪ {Formula.not φ} := by
simp only [Set.union_singleton, model_iff, Set.mem_insert_iff, forall_eq_or_imp,
Sentence.realize_not]
rw [← model_iff]
exact ⟨h, inferInstance⟩
exact Model.isSatisfiable M
#align first_order.language.Theory.models_bounded_formula.realize_sentence FirstOrder.Language.Theory.ModelsBoundedFormula.realize_sentence
theorem models_of_models_theory {T' : L.Theory}
(h : ∀ φ : L.Sentence, φ ∈ T' → T ⊨ᵇ φ)
{φ : L.Formula α} (hφ : T' ⊨ᵇ φ) : T ⊨ᵇ φ := by
simp only [models_sentence_iff] at h
intro M
have hM : M ⊨ T' := T'.model_iff.2 (fun ψ hψ => h ψ hψ M)
let M' : ModelType T' := ⟨M⟩
exact hφ M'
/-- An alternative statement of the Compactness Theorem. A formula `φ` is modeled by a
theory iff there is a finite subset `T0` of the theory such that `φ` is modeled by `T0` -/
theorem models_iff_finset_models {φ : L.Sentence} :
T ⊨ᵇ φ ↔ ∃ T0 : Finset L.Sentence, (T0 : L.Theory) ⊆ T ∧ (T0 : L.Theory) ⊨ᵇ φ := by
simp only [models_iff_not_satisfiable]
rw [← not_iff_not, not_not, isSatisfiable_iff_isFinitelySatisfiable, IsFinitelySatisfiable]
push_neg
letI := Classical.decEq (Sentence L)
constructor
· intro h T0 hT0
simpa using h (T0 ∪ {Formula.not φ})
(by
simp only [Finset.coe_union, Finset.coe_singleton]
exact Set.union_subset_union hT0 (Set.Subset.refl _))
· intro h T0 hT0
exact IsSatisfiable.mono (h (T0.erase (Formula.not φ))
(by simpa using hT0)) (by simp)
/-- A theory is complete when it is satisfiable and models each sentence or its negation. -/
def IsComplete (T : L.Theory) : Prop :=
T.IsSatisfiable ∧ ∀ φ : L.Sentence, T ⊨ᵇ φ ∨ T ⊨ᵇ φ.not
#align first_order.language.Theory.is_complete FirstOrder.Language.Theory.IsComplete
namespace IsComplete
| Mathlib/ModelTheory/Satisfiability.lean | 389 | 399 | theorem models_not_iff (h : T.IsComplete) (φ : L.Sentence) : T ⊨ᵇ φ.not ↔ ¬T ⊨ᵇ φ := by |
cases' h.2 φ with hφ hφn
· simp only [hφ, not_true, iff_false_iff]
rw [models_sentence_iff, not_forall]
refine ⟨h.1.some, ?_⟩
simp only [Sentence.realize_not, Classical.not_not]
exact models_sentence_iff.1 hφ _
· simp only [hφn, true_iff_iff]
intro hφ
rw [models_sentence_iff] at *
exact hφn h.1.some (hφ _)
|
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Kexing Ying
-/
import Mathlib.Probability.Notation
import Mathlib.Probability.Integration
import Mathlib.MeasureTheory.Function.L2Space
#align_import probability.variance from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Variance of random variables
We define the variance of a real-valued random variable as `Var[X] = 𝔼[(X - 𝔼[X])^2]` (in the
`ProbabilityTheory` locale).
## Main definitions
* `ProbabilityTheory.evariance`: the variance of a real-valued random variable as an extended
non-negative real.
* `ProbabilityTheory.variance`: the variance of a real-valued random variable as a real number.
## Main results
* `ProbabilityTheory.variance_le_expectation_sq`: the inequality `Var[X] ≤ 𝔼[X^2]`.
* `ProbabilityTheory.meas_ge_le_variance_div_sq`: Chebyshev's inequality, i.e.,
`ℙ {ω | c ≤ |X ω - 𝔼[X]|} ≤ ENNReal.ofReal (Var[X] / c ^ 2)`.
* `ProbabilityTheory.meas_ge_le_evariance_div_sq`: Chebyshev's inequality formulated with
`evariance` without requiring the random variables to be L².
* `ProbabilityTheory.IndepFun.variance_add`: the variance of the sum of two independent
random variables is the sum of the variances.
* `ProbabilityTheory.IndepFun.variance_sum`: the variance of a finite sum of pairwise
independent random variables is the sum of the variances.
-/
open MeasureTheory Filter Finset
noncomputable section
open scoped MeasureTheory ProbabilityTheory ENNReal NNReal
namespace ProbabilityTheory
-- Porting note: this lemma replaces `ENNReal.toReal_bit0`, which does not exist in Lean 4
private lemma coe_two : ENNReal.toReal 2 = (2 : ℝ) := rfl
-- Porting note: Consider if `evariance` or `eVariance` is better. Also,
-- consider `eVariationOn` in `Mathlib.Analysis.BoundedVariation`.
/-- The `ℝ≥0∞`-valued variance of a real-valued random variable defined as the Lebesgue integral of
`(X - 𝔼[X])^2`. -/
def evariance {Ω : Type*} {_ : MeasurableSpace Ω} (X : Ω → ℝ) (μ : Measure Ω) : ℝ≥0∞ :=
∫⁻ ω, (‖X ω - μ[X]‖₊ : ℝ≥0∞) ^ 2 ∂μ
#align probability_theory.evariance ProbabilityTheory.evariance
/-- The `ℝ`-valued variance of a real-valued random variable defined by applying `ENNReal.toReal`
to `evariance`. -/
def variance {Ω : Type*} {_ : MeasurableSpace Ω} (X : Ω → ℝ) (μ : Measure Ω) : ℝ :=
(evariance X μ).toReal
#align probability_theory.variance ProbabilityTheory.variance
variable {Ω : Type*} {m : MeasurableSpace Ω} {X : Ω → ℝ} {μ : Measure Ω}
theorem _root_.MeasureTheory.Memℒp.evariance_lt_top [IsFiniteMeasure μ] (hX : Memℒp X 2 μ) :
evariance X μ < ∞ := by
have := ENNReal.pow_lt_top (hX.sub <| memℒp_const <| μ[X]).2 2
rw [snorm_eq_lintegral_rpow_nnnorm two_ne_zero ENNReal.two_ne_top, ← ENNReal.rpow_two] at this
simp only [coe_two, Pi.sub_apply, ENNReal.one_toReal, one_div] at this
rw [← ENNReal.rpow_mul, inv_mul_cancel (two_ne_zero : (2 : ℝ) ≠ 0), ENNReal.rpow_one] at this
simp_rw [ENNReal.rpow_two] at this
exact this
#align measure_theory.mem_ℒp.evariance_lt_top MeasureTheory.Memℒp.evariance_lt_top
theorem evariance_eq_top [IsFiniteMeasure μ] (hXm : AEStronglyMeasurable X μ) (hX : ¬Memℒp X 2 μ) :
evariance X μ = ∞ := by
by_contra h
rw [← Ne, ← lt_top_iff_ne_top] at h
have : Memℒp (fun ω => X ω - μ[X]) 2 μ := by
refine ⟨hXm.sub aestronglyMeasurable_const, ?_⟩
rw [snorm_eq_lintegral_rpow_nnnorm two_ne_zero ENNReal.two_ne_top]
simp only [coe_two, ENNReal.one_toReal, ENNReal.rpow_two, Ne]
exact ENNReal.rpow_lt_top_of_nonneg (by linarith) h.ne
refine hX ?_
-- Porting note: `μ[X]` without whitespace is ambiguous as it could be GetElem,
-- and `convert` cannot disambiguate based on typeclass inference failure.
convert this.add (memℒp_const <| μ [X])
ext ω
rw [Pi.add_apply, sub_add_cancel]
#align probability_theory.evariance_eq_top ProbabilityTheory.evariance_eq_top
theorem evariance_lt_top_iff_memℒp [IsFiniteMeasure μ] (hX : AEStronglyMeasurable X μ) :
evariance X μ < ∞ ↔ Memℒp X 2 μ := by
refine ⟨?_, MeasureTheory.Memℒp.evariance_lt_top⟩
contrapose
rw [not_lt, top_le_iff]
exact evariance_eq_top hX
#align probability_theory.evariance_lt_top_iff_mem_ℒp ProbabilityTheory.evariance_lt_top_iff_memℒp
theorem _root_.MeasureTheory.Memℒp.ofReal_variance_eq [IsFiniteMeasure μ] (hX : Memℒp X 2 μ) :
ENNReal.ofReal (variance X μ) = evariance X μ := by
rw [variance, ENNReal.ofReal_toReal]
exact hX.evariance_lt_top.ne
#align measure_theory.mem_ℒp.of_real_variance_eq MeasureTheory.Memℒp.ofReal_variance_eq
theorem evariance_eq_lintegral_ofReal (X : Ω → ℝ) (μ : Measure Ω) :
evariance X μ = ∫⁻ ω, ENNReal.ofReal ((X ω - μ[X]) ^ 2) ∂μ := by
rw [evariance]
congr
ext1 ω
rw [pow_two, ← ENNReal.coe_mul, ← nnnorm_mul, ← pow_two]
congr
exact (Real.toNNReal_eq_nnnorm_of_nonneg <| sq_nonneg _).symm
#align probability_theory.evariance_eq_lintegral_of_real ProbabilityTheory.evariance_eq_lintegral_ofReal
theorem _root_.MeasureTheory.Memℒp.variance_eq_of_integral_eq_zero (hX : Memℒp X 2 μ)
(hXint : μ[X] = 0) : variance X μ = μ[X ^ (2 : Nat)] := by
rw [variance, evariance_eq_lintegral_ofReal, ← ofReal_integral_eq_lintegral_ofReal,
ENNReal.toReal_ofReal (by positivity)] <;>
simp_rw [hXint, sub_zero]
· rfl
· convert hX.integrable_norm_rpow two_ne_zero ENNReal.two_ne_top with ω
simp only [Pi.sub_apply, Real.norm_eq_abs, coe_two, ENNReal.one_toReal,
Real.rpow_two, sq_abs, abs_pow]
· exact ae_of_all _ fun ω => pow_two_nonneg _
#align measure_theory.mem_ℒp.variance_eq_of_integral_eq_zero MeasureTheory.Memℒp.variance_eq_of_integral_eq_zero
theorem _root_.MeasureTheory.Memℒp.variance_eq [IsFiniteMeasure μ] (hX : Memℒp X 2 μ) :
variance X μ = μ[(X - fun _ => μ[X] :) ^ (2 : Nat)] := by
rw [variance, evariance_eq_lintegral_ofReal, ← ofReal_integral_eq_lintegral_ofReal,
ENNReal.toReal_ofReal (by positivity)]
· rfl
· -- Porting note: `μ[X]` without whitespace is ambiguous as it could be GetElem,
-- and `convert` cannot disambiguate based on typeclass inference failure.
convert (hX.sub <| memℒp_const (μ [X])).integrable_norm_rpow two_ne_zero ENNReal.two_ne_top
with ω
simp only [Pi.sub_apply, Real.norm_eq_abs, coe_two, ENNReal.one_toReal,
Real.rpow_two, sq_abs, abs_pow]
· exact ae_of_all _ fun ω => pow_two_nonneg _
#align measure_theory.mem_ℒp.variance_eq MeasureTheory.Memℒp.variance_eq
@[simp]
theorem evariance_zero : evariance 0 μ = 0 := by simp [evariance]
#align probability_theory.evariance_zero ProbabilityTheory.evariance_zero
theorem evariance_eq_zero_iff (hX : AEMeasurable X μ) :
evariance X μ = 0 ↔ X =ᵐ[μ] fun _ => μ[X] := by
rw [evariance, lintegral_eq_zero_iff']
constructor <;> intro hX <;> filter_upwards [hX] with ω hω
· simpa only [Pi.zero_apply, sq_eq_zero_iff, ENNReal.coe_eq_zero, nnnorm_eq_zero, sub_eq_zero]
using hω
· rw [hω]
simp
· exact (hX.sub_const _).ennnorm.pow_const _ -- TODO `measurability` and `fun_prop` fail
#align probability_theory.evariance_eq_zero_iff ProbabilityTheory.evariance_eq_zero_iff
theorem evariance_mul (c : ℝ) (X : Ω → ℝ) (μ : Measure Ω) :
evariance (fun ω => c * X ω) μ = ENNReal.ofReal (c ^ 2) * evariance X μ := by
rw [evariance, evariance, ← lintegral_const_mul' _ _ ENNReal.ofReal_lt_top.ne]
congr
ext1 ω
rw [ENNReal.ofReal, ← ENNReal.coe_pow, ← ENNReal.coe_pow, ← ENNReal.coe_mul]
congr
rw [← sq_abs, ← Real.rpow_two, Real.toNNReal_rpow_of_nonneg (abs_nonneg _), NNReal.rpow_two,
← mul_pow, Real.toNNReal_mul_nnnorm _ (abs_nonneg _)]
conv_rhs => rw [← nnnorm_norm, norm_mul, norm_abs_eq_norm, ← norm_mul, nnnorm_norm, mul_sub]
congr
rw [mul_comm]
simp_rw [← smul_eq_mul, ← integral_smul_const, smul_eq_mul, mul_comm]
#align probability_theory.evariance_mul ProbabilityTheory.evariance_mul
scoped notation "eVar[" X "]" => ProbabilityTheory.evariance X MeasureTheory.MeasureSpace.volume
@[simp]
theorem variance_zero (μ : Measure Ω) : variance 0 μ = 0 := by
simp only [variance, evariance_zero, ENNReal.zero_toReal]
#align probability_theory.variance_zero ProbabilityTheory.variance_zero
theorem variance_nonneg (X : Ω → ℝ) (μ : Measure Ω) : 0 ≤ variance X μ :=
ENNReal.toReal_nonneg
#align probability_theory.variance_nonneg ProbabilityTheory.variance_nonneg
theorem variance_mul (c : ℝ) (X : Ω → ℝ) (μ : Measure Ω) :
variance (fun ω => c * X ω) μ = c ^ 2 * variance X μ := by
rw [variance, evariance_mul, ENNReal.toReal_mul, ENNReal.toReal_ofReal (sq_nonneg _)]
rfl
#align probability_theory.variance_mul ProbabilityTheory.variance_mul
theorem variance_smul (c : ℝ) (X : Ω → ℝ) (μ : Measure Ω) :
variance (c • X) μ = c ^ 2 * variance X μ :=
variance_mul c X μ
#align probability_theory.variance_smul ProbabilityTheory.variance_smul
theorem variance_smul' {A : Type*} [CommSemiring A] [Algebra A ℝ] (c : A) (X : Ω → ℝ)
(μ : Measure Ω) : variance (c • X) μ = c ^ 2 • variance X μ := by
convert variance_smul (algebraMap A ℝ c) X μ using 1
· congr; simp only [algebraMap_smul]
· simp only [Algebra.smul_def, map_pow]
#align probability_theory.variance_smul' ProbabilityTheory.variance_smul'
scoped notation "Var[" X "]" => ProbabilityTheory.variance X MeasureTheory.MeasureSpace.volume
variable [MeasureSpace Ω]
theorem variance_def' [@IsProbabilityMeasure Ω _ ℙ] {X : Ω → ℝ} (hX : Memℒp X 2) :
Var[X] = 𝔼[X ^ 2] - 𝔼[X] ^ 2 := by
rw [hX.variance_eq, sub_sq', integral_sub', integral_add']; rotate_left
· exact hX.integrable_sq
· convert @integrable_const Ω ℝ (_) ℙ _ _ (𝔼[X] ^ 2)
· apply hX.integrable_sq.add
convert @integrable_const Ω ℝ (_) ℙ _ _ (𝔼[X] ^ 2)
· exact ((hX.integrable one_le_two).const_mul 2).mul_const' _
simp only [Pi.pow_apply, integral_const, measure_univ, ENNReal.one_toReal, smul_eq_mul, one_mul,
Pi.mul_apply, Pi.ofNat_apply, Nat.cast_ofNat, integral_mul_right, integral_mul_left]
ring
#align probability_theory.variance_def' ProbabilityTheory.variance_def'
theorem variance_le_expectation_sq [@IsProbabilityMeasure Ω _ ℙ] {X : Ω → ℝ}
(hm : AEStronglyMeasurable X ℙ) : Var[X] ≤ 𝔼[X ^ 2] := by
by_cases hX : Memℒp X 2
· rw [variance_def' hX]
simp only [sq_nonneg, sub_le_self_iff]
rw [variance, evariance_eq_lintegral_ofReal, ← integral_eq_lintegral_of_nonneg_ae]
· by_cases hint : Integrable X; swap
· simp only [integral_undef hint, Pi.pow_apply, Pi.sub_apply, sub_zero]
exact le_rfl
· rw [integral_undef]
· exact integral_nonneg fun a => sq_nonneg _
intro h
have A : Memℒp (X - fun ω : Ω => 𝔼[X]) 2 ℙ :=
(memℒp_two_iff_integrable_sq (hint.aestronglyMeasurable.sub aestronglyMeasurable_const)).2 h
have B : Memℒp (fun _ : Ω => 𝔼[X]) 2 ℙ := memℒp_const _
apply hX
convert A.add B
simp
· exact eventually_of_forall fun x => sq_nonneg _
· exact (AEMeasurable.pow_const (hm.aemeasurable.sub_const _) _).aestronglyMeasurable
#align probability_theory.variance_le_expectation_sq ProbabilityTheory.variance_le_expectation_sq
theorem evariance_def' [@IsProbabilityMeasure Ω _ ℙ] {X : Ω → ℝ} (hX : AEStronglyMeasurable X ℙ) :
eVar[X] = (∫⁻ ω, (‖X ω‖₊ ^ 2 :)) - ENNReal.ofReal (𝔼[X] ^ 2) := by
by_cases hℒ : Memℒp X 2
· rw [← hℒ.ofReal_variance_eq, variance_def' hℒ, ENNReal.ofReal_sub _ (sq_nonneg _)]
congr
rw [lintegral_coe_eq_integral]
· congr 2 with ω
simp only [Pi.pow_apply, NNReal.coe_pow, coe_nnnorm, Real.norm_eq_abs, Even.pow_abs even_two]
· exact hℒ.abs.integrable_sq
· symm
rw [evariance_eq_top hX hℒ, ENNReal.sub_eq_top_iff]
refine ⟨?_, ENNReal.ofReal_ne_top⟩
rw [Memℒp, not_and] at hℒ
specialize hℒ hX
simp only [snorm_eq_lintegral_rpow_nnnorm two_ne_zero ENNReal.two_ne_top, not_lt, top_le_iff,
coe_two, one_div, ENNReal.rpow_eq_top_iff, inv_lt_zero, inv_pos, and_true_iff,
or_iff_not_imp_left, not_and_or, zero_lt_two] at hℒ
exact mod_cast hℒ fun _ => zero_le_two
#align probability_theory.evariance_def' ProbabilityTheory.evariance_def'
/-- **Chebyshev's inequality** for `ℝ≥0∞`-valued variance. -/
theorem meas_ge_le_evariance_div_sq {X : Ω → ℝ} (hX : AEStronglyMeasurable X ℙ) {c : ℝ≥0}
(hc : c ≠ 0) : ℙ {ω | ↑c ≤ |X ω - 𝔼[X]|} ≤ eVar[X] / c ^ 2 := by
have A : (c : ℝ≥0∞) ≠ 0 := by rwa [Ne, ENNReal.coe_eq_zero]
have B : AEStronglyMeasurable (fun _ : Ω => 𝔼[X]) ℙ := aestronglyMeasurable_const
convert meas_ge_le_mul_pow_snorm ℙ two_ne_zero ENNReal.two_ne_top (hX.sub B) A using 1
· congr
simp only [Pi.sub_apply, ENNReal.coe_le_coe, ← Real.norm_eq_abs, ← coe_nnnorm,
NNReal.coe_le_coe, ENNReal.ofReal_coe_nnreal]
· rw [snorm_eq_lintegral_rpow_nnnorm two_ne_zero ENNReal.two_ne_top]
simp only [show ENNReal.ofNNReal (c ^ 2) = (ENNReal.ofNNReal c) ^ 2 by norm_cast, coe_two,
one_div, Pi.sub_apply]
rw [div_eq_mul_inv, ENNReal.inv_pow, mul_comm, ENNReal.rpow_two]
congr
simp_rw [← ENNReal.rpow_mul, inv_mul_cancel (two_ne_zero : (2 : ℝ) ≠ 0), ENNReal.rpow_two,
ENNReal.rpow_one, evariance]
#align probability_theory.meas_ge_le_evariance_div_sq ProbabilityTheory.meas_ge_le_evariance_div_sq
/-- **Chebyshev's inequality**: one can control the deviation probability of a real random variable
from its expectation in terms of the variance. -/
| Mathlib/Probability/Variance.lean | 280 | 286 | theorem meas_ge_le_variance_div_sq [@IsFiniteMeasure Ω _ ℙ] {X : Ω → ℝ} (hX : Memℒp X 2) {c : ℝ}
(hc : 0 < c) : ℙ {ω | c ≤ |X ω - 𝔼[X]|} ≤ ENNReal.ofReal (Var[X] / c ^ 2) := by |
rw [ENNReal.ofReal_div_of_pos (sq_pos_of_ne_zero hc.ne.symm), hX.ofReal_variance_eq]
convert @meas_ge_le_evariance_div_sq _ _ _ hX.1 c.toNNReal (by simp [hc]) using 1
· simp only [Real.coe_toNNReal', max_le_iff, abs_nonneg, and_true_iff]
· rw [ENNReal.ofReal_pow hc.le]
rfl
|
/-
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.Topology.EMetricSpace.Basic
import Mathlib.Topology.Bornology.Constructions
import Mathlib.Data.Set.Pointwise.Interval
import Mathlib.Topology.Order.DenselyOrdered
/-!
## 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
-/
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
#align uniform_space_of_dist UniformSpace.ofDist
-- Porting note: dropped the `dist_self` argument
/-- 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 x hx y => hx.elim⟩ (fun s ⟨c, hc⟩ t h => ⟨c, fun x hx y 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⟩
#align bornology.of_dist Bornology.ofDistₓ
/-- 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
dist : α → α → ℝ
#align has_dist Dist
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
#noalign pseudo_metric_space.edist_dist_tac -- Porting note (#11215): TODO: restore
/-- Pseudo metric and Metric spaces
A pseudo metric space is endowed with a distance for which the requirement `d(x,y)=0 → x = y` might
not hold. A metric space is a pseudo metric space such that `d(x,y)=0 → x = y`.
Each pseudo metric space induces a canonical `UniformSpace` and hence a canonical
`TopologicalSpace` This is enforced in the type class definition, by extending the `UniformSpace`
structure. When instantiating a `PseudoMetricSpace` structure, the uniformity fields are not
necessary, they will be filled in by default. In the same way, each (pseudo) metric space induces a
(pseudo) emetric space structure. It is included in the structure, but filled in by default.
-/
class PseudoMetricSpace (α : Type u) extends Dist α : Type u 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
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)
-- Porting note (#11215): TODO: add := by _
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
#align pseudo_metric_space PseudoMetricSpace
/-- 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
cases' m with d _ _ _ ed hed U hU B hB
cases' m' with d' _ _ _ ed' hed' U' hU' B' hB'
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']
#align pseudo_metric_space.ext PseudoMetricSpace.ext
variable [PseudoMetricSpace α]
attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology
-- see Note [lower instance priority]
instance (priority := 200) PseudoMetricSpace.toEDist : EDist α :=
⟨PseudoMetricSpace.edist⟩
#align pseudo_metric_space.to_has_edist PseudoMetricSpace.toEDist
/-- 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
edist_dist := fun x y => by exact ENNReal.coe_nnreal_eq _
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 }
#align pseudo_metric_space.of_dist_topology PseudoMetricSpace.ofDistTopology
@[simp]
theorem dist_self (x : α) : dist x x = 0 :=
PseudoMetricSpace.dist_self x
#align dist_self dist_self
theorem dist_comm (x y : α) : dist x y = dist y x :=
PseudoMetricSpace.dist_comm x y
#align dist_comm dist_comm
theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) :=
PseudoMetricSpace.edist_dist x y
#align edist_dist edist_dist
theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z :=
PseudoMetricSpace.dist_triangle x y z
#align dist_triangle dist_triangle
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
#align dist_triangle_left dist_triangle_left
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
#align dist_triangle_right dist_triangle_right
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) _
#align dist_triangle4 dist_triangle4
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
#align dist_triangle4_left dist_triangle4_left
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
#align dist_triangle4_right dist_triangle4_right
/-- The triangle (polygon) inequality for sequences of points; `Finset.Ico` version. -/
theorem dist_le_Ico_sum_dist (f : ℕ → α) {m n} (h : m ≤ n) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, dist (f i) (f (i + 1)) := by
induction n, h using Nat.le_induction with
| base => rw [Finset.Ico_self, Finset.sum_empty, dist_self]
| succ n hle ihn =>
calc
dist (f m) (f (n + 1)) ≤ dist (f m) (f n) + dist (f n) (f (n + 1)) := dist_triangle _ _ _
_ ≤ (∑ i ∈ Finset.Ico m n, _) + _ := add_le_add ihn le_rfl
_ = ∑ i ∈ Finset.Ico m (n + 1), _ := by
{ rw [Nat.Ico_succ_right_eq_insert_Ico hle, Finset.sum_insert, add_comm]; simp }
#align dist_le_Ico_sum_dist dist_le_Ico_sum_dist
/-- The triangle (polygon) inequality for sequences of points; `Finset.range` version. -/
theorem dist_le_range_sum_dist (f : ℕ → α) (n : ℕ) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, dist (f i) (f (i + 1)) :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_dist f (Nat.zero_le n)
#align dist_le_range_sum_dist dist_le_range_sum_dist
/-- A version of `dist_le_Ico_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_Ico_sum_of_dist_le {f : ℕ → α} {m n} (hmn : m ≤ n) {d : ℕ → ℝ}
(hd : ∀ {k}, m ≤ k → k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f m) (f n) ≤ ∑ i ∈ Finset.Ico m n, d i :=
le_trans (dist_le_Ico_sum_dist f hmn) <|
Finset.sum_le_sum fun _k hk => hd (Finset.mem_Ico.1 hk).1 (Finset.mem_Ico.1 hk).2
#align dist_le_Ico_sum_of_dist_le dist_le_Ico_sum_of_dist_le
/-- A version of `dist_le_range_sum_dist` with each intermediate distance replaced
with an upper estimate. -/
theorem dist_le_range_sum_of_dist_le {f : ℕ → α} (n : ℕ) {d : ℕ → ℝ}
(hd : ∀ {k}, k < n → dist (f k) (f (k + 1)) ≤ d k) :
dist (f 0) (f n) ≤ ∑ i ∈ Finset.range n, d i :=
Nat.Ico_zero_eq_range ▸ dist_le_Ico_sum_of_dist_le (zero_le n) fun _ => hd
#align dist_le_range_sum_of_dist_le dist_le_range_sum_of_dist_le
theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _
#align swap_dist swap_dist
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 _ _ _)⟩
#align abs_dist_sub_le abs_dist_sub_le
theorem dist_nonneg {x y : α} : 0 ≤ dist x y :=
dist_nonneg' dist dist_self dist_comm dist_triangle
#align dist_nonneg dist_nonneg
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
#align abs_dist abs_dist
/-- A version of `Dist` that takes value in `ℝ≥0`. -/
class NNDist (α : Type*) where
nndist : α → α → ℝ≥0
#align has_nndist NNDist
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⟩⟩
#align pseudo_metric_space.to_has_nndist PseudoMetricSpace.toNNDist
/-- Express `dist` in terms of `nndist`-/
theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl
#align dist_nndist dist_nndist
@[simp, norm_cast]
theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl
#align coe_nndist coe_nndist
/-- 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]
#align edist_nndist edist_nndist
/-- Express `nndist` in terms of `edist`-/
theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by
simp [edist_nndist]
#align nndist_edist nndist_edist
@[simp, norm_cast]
theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y :=
(edist_nndist x y).symm
#align coe_nnreal_ennreal_nndist coe_nnreal_ennreal_nndist
@[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]
#align edist_lt_coe edist_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]
#align edist_le_coe edist_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
#align edist_lt_top edist_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
#align edist_ne_top edist_ne_top
/-- `nndist x x` vanishes-/
@[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a)
#align nndist_self nndist_self
-- Porting note: `dist_nndist` and `coe_nndist` moved up
@[simp, norm_cast]
theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c :=
Iff.rfl
#align dist_lt_coe dist_lt_coe
@[simp, norm_cast]
theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c :=
Iff.rfl
#align dist_le_coe dist_le_coe
@[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]
#align edist_lt_of_real edist_lt_ofReal
@[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]
#align edist_le_of_real edist_le_ofReal
/-- 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]
#align nndist_dist nndist_dist
theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y
#align nndist_comm nndist_comm
/-- Triangle inequality for the nonnegative distance-/
theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z :=
dist_triangle _ _ _
#align nndist_triangle nndist_triangle
theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y :=
dist_triangle_left _ _ _
#align nndist_triangle_left nndist_triangle_left
theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z :=
dist_triangle_right _ _ _
#align nndist_triangle_right nndist_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]
#align dist_edist dist_edist
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 }
#align metric.ball Metric.ball
@[simp]
theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε :=
Iff.rfl
#align metric.mem_ball Metric.mem_ball
theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball]
#align metric.mem_ball' Metric.mem_ball'
theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε :=
dist_nonneg.trans_lt hy
#align metric.pos_of_mem_ball Metric.pos_of_mem_ball
theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by
rwa [mem_ball, dist_self]
#align metric.mem_ball_self Metric.mem_ball_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⟩⟩
#align metric.nonempty_ball Metric.nonempty_ball
@[simp]
theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt]
#align metric.ball_eq_empty Metric.ball_eq_empty
@[simp]
theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty]
#align metric.ball_zero Metric.ball_zero
/-- 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⟩
#align metric.exists_lt_mem_ball_of_mem_ball Metric.exists_lt_mem_ball_of_mem_ball
theorem ball_eq_ball (ε : ℝ) (x : α) :
UniformSpace.ball x { p | dist p.2 p.1 < ε } = Metric.ball x ε :=
rfl
#align metric.ball_eq_ball Metric.ball_eq_ball
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]
#align metric.ball_eq_ball' Metric.ball_eq_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)
#align metric.Union_ball_nat Metric.iUnion_ball_nat
@[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 _)
#align metric.Union_ball_nat_succ Metric.iUnion_ball_nat_succ
/-- `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 }
#align metric.closed_ball Metric.closedBall
@[simp] theorem mem_closedBall : y ∈ closedBall x ε ↔ dist y x ≤ ε := Iff.rfl
#align metric.mem_closed_ball Metric.mem_closedBall
theorem mem_closedBall' : y ∈ closedBall x ε ↔ dist x y ≤ ε := by rw [dist_comm, mem_closedBall]
#align metric.mem_closed_ball' Metric.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 }
#align metric.sphere Metric.sphere
@[simp] theorem mem_sphere : y ∈ sphere x ε ↔ dist y x = ε := Iff.rfl
#align metric.mem_sphere Metric.mem_sphere
theorem mem_sphere' : y ∈ sphere x ε ↔ dist x y = ε := by rw [dist_comm, mem_sphere]
#align metric.mem_sphere' Metric.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
#align metric.ne_of_mem_sphere Metric.ne_of_mem_sphere
theorem nonneg_of_mem_sphere (hy : y ∈ sphere x ε) : 0 ≤ ε :=
dist_nonneg.trans_eq hy
#align metric.nonneg_of_mem_sphere Metric.nonneg_of_mem_sphere
@[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
#align metric.sphere_eq_empty_of_neg Metric.sphere_eq_empty_of_neg
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 _ _)
#align metric.sphere_eq_empty_of_subsingleton Metric.sphere_eq_empty_of_subsingleton
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
#align metric.sphere_is_empty_of_subsingleton Metric.sphere_isEmpty_of_subsingleton
theorem mem_closedBall_self (h : 0 ≤ ε) : x ∈ closedBall x ε := by
rwa [mem_closedBall, dist_self]
#align metric.mem_closed_ball_self Metric.mem_closedBall_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⟩⟩
#align metric.nonempty_closed_ball Metric.nonempty_closedBall
@[simp]
theorem closedBall_eq_empty : closedBall x ε = ∅ ↔ ε < 0 := by
rw [← not_nonempty_iff_eq_empty, nonempty_closedBall, not_le]
#align metric.closed_ball_eq_empty Metric.closedBall_eq_empty
/-- 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
#align metric.closed_ball_eq_sphere_of_nonpos Metric.closedBall_eq_sphere_of_nonpos
theorem ball_subset_closedBall : ball x ε ⊆ closedBall x ε := fun _y hy =>
mem_closedBall.2 (le_of_lt hy)
#align metric.ball_subset_closed_ball Metric.ball_subset_closedBall
theorem sphere_subset_closedBall : sphere x ε ⊆ closedBall x ε := fun _ => le_of_eq
#align metric.sphere_subset_closed_ball Metric.sphere_subset_closedBall
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
#align metric.closed_ball_disjoint_ball Metric.closedBall_disjoint_ball
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
#align metric.ball_disjoint_closed_ball Metric.ball_disjoint_closedBall
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
#align metric.ball_disjoint_ball Metric.ball_disjoint_ball
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
#align metric.closed_ball_disjoint_closed_ball Metric.closedBall_disjoint_closedBall
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
#align metric.sphere_disjoint_ball Metric.sphere_disjoint_ball
@[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
#align metric.ball_union_sphere Metric.ball_union_sphere
@[simp]
theorem sphere_union_ball : sphere x ε ∪ ball x ε = closedBall x ε := by
rw [union_comm, ball_union_sphere]
#align metric.sphere_union_ball Metric.sphere_union_ball
@[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]
#align metric.closed_ball_diff_sphere Metric.closedBall_diff_sphere
@[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]
#align metric.closed_ball_diff_ball Metric.closedBall_diff_ball
theorem mem_ball_comm : x ∈ ball y ε ↔ y ∈ ball x ε := by rw [mem_ball', mem_ball]
#align metric.mem_ball_comm Metric.mem_ball_comm
theorem mem_closedBall_comm : x ∈ closedBall y ε ↔ y ∈ closedBall x ε := by
rw [mem_closedBall', mem_closedBall]
#align metric.mem_closed_ball_comm Metric.mem_closedBall_comm
theorem mem_sphere_comm : x ∈ sphere y ε ↔ y ∈ sphere x ε := by rw [mem_sphere', mem_sphere]
#align metric.mem_sphere_comm Metric.mem_sphere_comm
@[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
#align metric.ball_subset_ball Metric.ball_subset_ball
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
#align metric.closed_ball_eq_bInter_ball Metric.closedBall_eq_bInter_ball
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
#align metric.ball_subset_ball' Metric.ball_subset_ball'
@[gcongr]
theorem closedBall_subset_closedBall (h : ε₁ ≤ ε₂) : closedBall x ε₁ ⊆ closedBall x ε₂ :=
fun _y (yx : _ ≤ ε₁) => le_trans yx h
#align metric.closed_ball_subset_closed_ball Metric.closedBall_subset_closedBall
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
#align metric.closed_ball_subset_closed_ball' Metric.closedBall_subset_closedBall'
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
#align metric.closed_ball_subset_ball Metric.closedBall_subset_ball
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
#align metric.closed_ball_subset_ball' Metric.closedBall_subset_ball'
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
#align metric.dist_le_add_of_nonempty_closed_ball_inter_closed_ball Metric.dist_le_add_of_nonempty_closedBall_inter_closedBall
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
#align metric.dist_lt_add_of_nonempty_closed_ball_inter_ball Metric.dist_lt_add_of_nonempty_closedBall_inter_ball
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
#align metric.dist_lt_add_of_nonempty_ball_inter_closed_ball Metric.dist_lt_add_of_nonempty_ball_inter_closedBall
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)
#align metric.dist_lt_add_of_nonempty_ball_inter_ball Metric.dist_lt_add_of_nonempty_ball_inter_ball
@[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)
#align metric.Union_closed_ball_nat Metric.iUnion_closedBall_nat
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]
#align metric.Union_inter_closed_ball_nat Metric.iUnion_inter_closedBall_nat
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)
#align metric.ball_subset Metric.ball_subset
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
#align metric.ball_half_subset Metric.ball_half_subset
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]⟩
#align metric.exists_ball_subset_ball Metric.exists_ball_subset_ball
/-- 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
#align metric.forall_of_forall_mem_closed_ball Metric.forall_of_forall_mem_closedBall
/-- 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
#align metric.forall_of_forall_mem_ball Metric.forall_of_forall_mem_ball
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]
#align metric.is_bounded_iff Metric.isBounded_iff
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⟩
#align metric.is_bounded_iff_eventually Metric.isBounded_iff_eventually
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⟩
#align metric.is_bounded_iff_exists_ge Metric.isBounded_iff_exists_ge
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]
#align metric.is_bounded_iff_nndist Metric.isBounded_iff_nndist
theorem toUniformSpace_eq :
‹PseudoMetricSpace α›.toUniformSpace = .ofDist dist dist_self dist_comm dist_triangle :=
UniformSpace.ext PseudoMetricSpace.uniformity_dist
#align metric.to_uniform_space_eq Metric.toUniformSpace_eq
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 _) _ _ _ _ _
#align metric.uniformity_basis_dist Metric.uniformity_basis_dist
/-- 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⟩
#align metric.mk_uniformity_basis Metric.mk_uniformity_basis
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⟩
#align metric.uniformity_basis_dist_rat Metric.uniformity_basis_dist_rat
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⟩
#align metric.uniformity_basis_dist_inv_nat_succ Metric.uniformity_basis_dist_inv_nat_succ
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⟩
#align metric.uniformity_basis_dist_inv_nat_pos Metric.uniformity_basis_dist_inv_nat_pos
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⟩
#align metric.uniformity_basis_dist_pow Metric.uniformity_basis_dist_pow
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 _ _⟩
#align metric.uniformity_basis_dist_lt Metric.uniformity_basis_dist_lt
/-- 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)⟩
#align metric.mk_uniformity_basis_le Metric.mk_uniformity_basis_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⟩
#align metric.uniformity_basis_dist_le Metric.uniformity_basis_dist_le
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⟩
#align metric.uniformity_basis_dist_le_pow Metric.uniformity_basis_dist_le_pow
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
#align metric.mem_uniformity_dist Metric.mem_uniformity_dist
/-- 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, id⟩
#align metric.dist_mem_uniformity Metric.dist_mem_uniformity
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
#align metric.uniform_continuous_iff Metric.uniformContinuous_iff
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
#align metric.uniform_continuous_on_iff Metric.uniformContinuousOn_iff
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
#align metric.uniform_continuous_on_iff_le Metric.uniformContinuousOn_iff_le
nonrec theorem uniformInducing_iff [PseudoMetricSpace β] {f : α → β} :
UniformInducing f ↔ UniformContinuous f ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ :=
uniformInducing_iff'.trans <| Iff.rfl.and <|
((uniformity_basis_dist.comap _).le_basis_iff uniformity_basis_dist).trans <| by
simp only [subset_def, Prod.forall, gt_iff_lt, preimage_setOf_eq, Prod.map_apply, mem_setOf]
nonrec theorem uniformEmbedding_iff [PseudoMetricSpace β] {f : α → β} :
UniformEmbedding f ↔ Function.Injective f ∧ UniformContinuous f ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ := by
rw [uniformEmbedding_iff, and_comm, uniformInducing_iff]
#align metric.uniform_embedding_iff Metric.uniformEmbedding_iff
/-- If a map between pseudometric spaces is a uniform embedding then the distance between `f x`
and `f y` is controlled in terms of the distance between `x` and `y`. -/
theorem controlled_of_uniformEmbedding [PseudoMetricSpace β] {f : α → β} (h : UniformEmbedding f) :
(∀ ε > 0, ∃ δ > 0, ∀ {a b : α}, dist a b < δ → dist (f a) (f b) < ε) ∧
∀ δ > 0, ∃ ε > 0, ∀ {a b : α}, dist (f a) (f b) < ε → dist a b < δ :=
⟨uniformContinuous_iff.1 h.uniformContinuous, (uniformEmbedding_iff.1 h).2.2⟩
#align metric.controlled_of_uniform_embedding Metric.controlled_of_uniformEmbedding
theorem totallyBounded_iff {s : Set α} :
TotallyBounded s ↔ ∀ ε > 0, ∃ t : Set α, t.Finite ∧ s ⊆ ⋃ y ∈ t, ball y ε :=
uniformity_basis_dist.totallyBounded_iff
#align metric.totally_bounded_iff Metric.totallyBounded_iff
/-- A pseudometric space is totally bounded if one can reconstruct up to any ε>0 any element of the
space from finitely many data. -/
theorem totallyBounded_of_finite_discretization {s : Set α}
(H : ∀ ε > (0 : ℝ),
∃ (β : Type u) (_ : Fintype β) (F : s → β), ∀ x y, F x = F y → dist (x : α) y < ε) :
TotallyBounded s := by
rcases s.eq_empty_or_nonempty with hs | hs
· rw [hs]
exact totallyBounded_empty
rcases hs with ⟨x0, hx0⟩
haveI : Inhabited s := ⟨⟨x0, hx0⟩⟩
refine totallyBounded_iff.2 fun ε ε0 => ?_
rcases H ε ε0 with ⟨β, fβ, F, hF⟩
let Finv := Function.invFun F
refine ⟨range (Subtype.val ∘ Finv), finite_range _, fun x xs => ?_⟩
let x' := Finv (F ⟨x, xs⟩)
have : F x' = F ⟨x, xs⟩ := Function.invFun_eq ⟨⟨x, xs⟩, rfl⟩
simp only [Set.mem_iUnion, Set.mem_range]
exact ⟨_, ⟨F ⟨x, xs⟩, rfl⟩, hF _ _ this.symm⟩
#align metric.totally_bounded_of_finite_discretization Metric.totallyBounded_of_finite_discretization
theorem finite_approx_of_totallyBounded {s : Set α} (hs : TotallyBounded s) :
∀ ε > 0, ∃ t, t ⊆ s ∧ Set.Finite t ∧ s ⊆ ⋃ y ∈ t, ball y ε := by
intro ε ε_pos
rw [totallyBounded_iff_subset] at hs
exact hs _ (dist_mem_uniformity ε_pos)
#align metric.finite_approx_of_totally_bounded Metric.finite_approx_of_totallyBounded
/-- Expressing uniform convergence using `dist` -/
theorem tendstoUniformlyOnFilter_iff {F : ι → β → α} {f : β → α} {p : Filter ι} {p' : Filter β} :
TendstoUniformlyOnFilter F f p p' ↔
∀ ε > 0, ∀ᶠ n : ι × β in p ×ˢ p', dist (f n.snd) (F n.fst n.snd) < ε := by
refine ⟨fun H ε hε => H _ (dist_mem_uniformity hε), fun H u hu => ?_⟩
rcases mem_uniformity_dist.1 hu with ⟨ε, εpos, hε⟩
exact (H ε εpos).mono fun n hn => hε hn
#align metric.tendsto_uniformly_on_filter_iff Metric.tendstoUniformlyOnFilter_iff
/-- Expressing locally uniform convergence on a set using `dist`. -/
theorem tendstoLocallyUniformlyOn_iff [TopologicalSpace β] {F : ι → β → α} {f : β → α}
{p : Filter ι} {s : Set β} :
TendstoLocallyUniformlyOn F f p s ↔
∀ ε > 0, ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, ∀ᶠ n in p, ∀ y ∈ t, dist (f y) (F n y) < ε := by
refine ⟨fun H ε hε => H _ (dist_mem_uniformity hε), fun H u hu x hx => ?_⟩
rcases mem_uniformity_dist.1 hu with ⟨ε, εpos, hε⟩
rcases H ε εpos x hx with ⟨t, ht, Ht⟩
exact ⟨t, ht, Ht.mono fun n hs x hx => hε (hs x hx)⟩
#align metric.tendsto_locally_uniformly_on_iff Metric.tendstoLocallyUniformlyOn_iff
/-- Expressing uniform convergence on a set using `dist`. -/
theorem tendstoUniformlyOn_iff {F : ι → β → α} {f : β → α} {p : Filter ι} {s : Set β} :
TendstoUniformlyOn F f p s ↔ ∀ ε > 0, ∀ᶠ n in p, ∀ x ∈ s, dist (f x) (F n x) < ε := by
refine ⟨fun H ε hε => H _ (dist_mem_uniformity hε), fun H u hu => ?_⟩
rcases mem_uniformity_dist.1 hu with ⟨ε, εpos, hε⟩
exact (H ε εpos).mono fun n hs x hx => hε (hs x hx)
#align metric.tendsto_uniformly_on_iff Metric.tendstoUniformlyOn_iff
/-- Expressing locally uniform convergence using `dist`. -/
theorem tendstoLocallyUniformly_iff [TopologicalSpace β] {F : ι → β → α} {f : β → α}
{p : Filter ι} :
TendstoLocallyUniformly F f p ↔
∀ ε > 0, ∀ x : β, ∃ t ∈ 𝓝 x, ∀ᶠ n in p, ∀ y ∈ t, dist (f y) (F n y) < ε := by
simp only [← tendstoLocallyUniformlyOn_univ, tendstoLocallyUniformlyOn_iff, nhdsWithin_univ,
mem_univ, forall_const, exists_prop]
#align metric.tendsto_locally_uniformly_iff Metric.tendstoLocallyUniformly_iff
/-- Expressing uniform convergence using `dist`. -/
theorem tendstoUniformly_iff {F : ι → β → α} {f : β → α} {p : Filter ι} :
TendstoUniformly F f p ↔ ∀ ε > 0, ∀ᶠ n in p, ∀ x, dist (f x) (F n x) < ε := by
rw [← tendstoUniformlyOn_univ, tendstoUniformlyOn_iff]
simp
#align metric.tendsto_uniformly_iff Metric.tendstoUniformly_iff
protected theorem cauchy_iff {f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ ε > 0, ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, dist x y < ε :=
uniformity_basis_dist.cauchy_iff
#align metric.cauchy_iff Metric.cauchy_iff
theorem nhds_basis_ball : (𝓝 x).HasBasis (0 < ·) (ball x) :=
nhds_basis_uniformity uniformity_basis_dist
#align metric.nhds_basis_ball Metric.nhds_basis_ball
theorem mem_nhds_iff : s ∈ 𝓝 x ↔ ∃ ε > 0, ball x ε ⊆ s :=
nhds_basis_ball.mem_iff
#align metric.mem_nhds_iff Metric.mem_nhds_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
#align metric.eventually_nhds_iff Metric.eventually_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
#align metric.eventually_nhds_iff_ball Metric.eventually_nhds_iff_ball
/-- 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
#align metric.eventually_nhds_prod_iff Metric.eventually_nhds_prod_iff
/-- 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⟩
#align metric.eventually_prod_nhds_iff Metric.eventually_prod_nhds_iff
theorem nhds_basis_closedBall : (𝓝 x).HasBasis (fun ε : ℝ => 0 < ε) (closedBall x) :=
nhds_basis_uniformity uniformity_basis_dist_le
#align metric.nhds_basis_closed_ball Metric.nhds_basis_closedBall
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
#align metric.nhds_basis_ball_inv_nat_succ Metric.nhds_basis_ball_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
#align metric.nhds_basis_ball_inv_nat_pos Metric.nhds_basis_ball_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)
#align metric.nhds_basis_ball_pow Metric.nhds_basis_ball_pow
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)
#align metric.nhds_basis_closed_ball_pow Metric.nhds_basis_closedBall_pow
theorem isOpen_iff : IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ball x ε ⊆ s := by
simp only [isOpen_iff_mem_nhds, mem_nhds_iff]
#align metric.is_open_iff Metric.isOpen_iff
theorem isOpen_ball : IsOpen (ball x ε) :=
isOpen_iff.2 fun _ => exists_ball_subset_ball
#align metric.is_open_ball Metric.isOpen_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)
#align metric.ball_mem_nhds Metric.ball_mem_nhds
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
#align metric.closed_ball_mem_nhds Metric.closedBall_mem_nhds
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
#align metric.closed_ball_mem_nhds_of_mem Metric.closedBall_mem_nhds_of_mem
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
#align metric.nhds_within_basis_ball Metric.nhdsWithin_basis_ball
theorem mem_nhdsWithin_iff {t : Set α} : s ∈ 𝓝[t] x ↔ ∃ ε > 0, ball x ε ∩ t ⊆ s :=
nhdsWithin_basis_ball.mem_iff
#align metric.mem_nhds_within_iff Metric.mem_nhdsWithin_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]
#align metric.tendsto_nhds_within_nhds_within Metric.tendsto_nhdsWithin_nhdsWithin
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_iff]
#align metric.tendsto_nhds_within_nhds Metric.tendsto_nhdsWithin_nhds
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
#align metric.tendsto_nhds_nhds Metric.tendsto_nhds_nhds
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]
#align metric.continuous_at_iff Metric.continuousAt_iff
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]
#align metric.continuous_within_at_iff Metric.continuousWithinAt_iff
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]
#align metric.continuous_on_iff Metric.continuousOn_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
#align metric.continuous_iff Metric.continuous_iff
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
#align metric.tendsto_nhds Metric.tendsto_nhds
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]
#align metric.continuous_at_iff' Metric.continuousAt_iff'
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]
#align metric.continuous_within_at_iff' Metric.continuousWithinAt_iff'
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']
#align metric.continuous_on_iff' Metric.continuousOn_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
#align metric.continuous_iff' Metric.continuous_iff'
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]
#align metric.tendsto_at_top Metric.tendsto_atTop
/-- 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]
#align metric.tendsto_at_top' Metric.tendsto_atTop'
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]
#align metric.is_open_singleton_iff Metric.isOpen_singleton_iff
/-- Given a point `x` in a discrete subset `s` of a pseudometric space, there is an open ball
centered at `x` and intersecting `s` only at `x`. -/
theorem exists_ball_inter_eq_singleton_of_mem_discrete [DiscreteTopology s] {x : α} (hx : x ∈ s) :
∃ ε > 0, Metric.ball x ε ∩ s = {x} :=
nhds_basis_ball.exists_inter_eq_singleton_of_mem_discrete hx
#align metric.exists_ball_inter_eq_singleton_of_mem_discrete Metric.exists_ball_inter_eq_singleton_of_mem_discrete
/-- Given a point `x` in a discrete subset `s` of a pseudometric space, there is a closed ball
of positive radius centered at `x` and intersecting `s` only at `x`. -/
theorem exists_closedBall_inter_eq_singleton_of_discrete [DiscreteTopology s] {x : α} (hx : x ∈ s) :
∃ ε > 0, Metric.closedBall x ε ∩ s = {x} :=
nhds_basis_closedBall.exists_inter_eq_singleton_of_mem_discrete hx
#align metric.exists_closed_ball_inter_eq_singleton_of_discrete Metric.exists_closedBall_inter_eq_singleton_of_discrete
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
#align dense.exists_dist_lt Dense.exists_dist_lt
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)
#align dense_range.exists_dist_lt DenseRange.exists_dist_lt
end Metric
open Metric
/- 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. -/
-- Porting note (#10756): new theorem
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]
#align metric.uniformity_edist Metric.uniformity_edist
-- 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 }
#align pseudo_metric_space.to_pseudo_emetric_space PseudoMetricSpace.toPseudoEMetricSpace
/-- Expressing the uniformity in terms of `edist` -/
@[deprecated _root_.uniformity_basis_edist]
protected theorem Metric.uniformity_basis_edist :
(𝓤 α).HasBasis (fun ε : ℝ≥0∞ => 0 < ε) fun ε => { p | edist p.1 p.2 < ε } :=
uniformity_basis_edist
#align pseudo_metric.uniformity_basis_edist Metric.uniformity_basis_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
#align metric.eball_top_eq_univ Metric.eball_top_eq_univ
/-- 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
#align metric.emetric_ball Metric.emetric_ball
/-- 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
#align metric.emetric_ball_nnreal Metric.emetric_ball_nnreal
/-- 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]
#align metric.emetric_closed_ball Metric.emetric_closedBall
/-- 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]
#align metric.emetric_closed_ball_nnreal Metric.emetric_closedBall_nnreal
@[simp]
theorem Metric.emetric_ball_top (x : α) : EMetric.ball x ⊤ = univ :=
eq_univ_of_forall fun _ => edist_lt_top _ _
#align metric.emetric_ball_top Metric.emetric_ball_top
theorem Metric.inseparable_iff {x y : α} : Inseparable x y ↔ dist x y = 0 := by
rw [EMetric.inseparable_iff, edist_nndist, dist_nndist, ENNReal.coe_eq_zero, NNReal.coe_eq_zero]
#align metric.inseparable_iff Metric.inseparable_iff
/-- 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].
-/
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 }
#align pseudo_metric_space.replace_uniformity PseudoMetricSpace.replaceUniformity
theorem PseudoMetricSpace.replaceUniformity_eq {α} [U : UniformSpace α] (m : PseudoMetricSpace α)
(H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : m.replaceUniformity H = m := by
ext
rfl
#align pseudo_metric_space.replace_uniformity_eq PseudoMetricSpace.replaceUniformity_eq
-- 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 := 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].
-/
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
#align pseudo_metric_space.replace_topology PseudoMetricSpace.replaceTopology
theorem PseudoMetricSpace.replaceTopology_eq {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ)
(H : U = m.toUniformSpace.toTopologicalSpace) : m.replaceTopology H = m := by
ext
rfl
#align pseudo_metric_space.replace_topology_eq PseudoMetricSpace.replaceTopology_eq
/-- 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
#align pseudo_emetric_space.to_pseudo_metric_space_of_dist PseudoEMetricSpace.toPseudoMetricSpaceOfDist
/-- 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
#align pseudo_emetric_space.to_pseudo_metric_space PseudoEMetricSpace.toPseudoMetricSpace
/-- 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].
-/
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] }
#align pseudo_metric_space.replace_bornology PseudoMetricSpace.replaceBornology
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
#align pseudo_metric_space.replace_bornology_eq PseudoMetricSpace.replaceBornology_eq
-- 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 := 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 x y := abs_sub_comm _ _
dist_triangle x y z := abs_sub_le _ _ _
edist_dist := fun x y => by exact ENNReal.coe_nnreal_eq _
#align real.pseudo_metric_space Real.pseudoMetricSpace
theorem Real.dist_eq (x y : ℝ) : dist x y = |x - y| := rfl
#align real.dist_eq Real.dist_eq
theorem Real.nndist_eq (x y : ℝ) : nndist x y = Real.nnabs (x - y) := rfl
#align real.nndist_eq Real.nndist_eq
theorem Real.nndist_eq' (x y : ℝ) : nndist x y = Real.nnabs (y - x) :=
nndist_comm _ _
#align real.nndist_eq' Real.nndist_eq'
theorem Real.dist_0_eq_abs (x : ℝ) : dist x 0 = |x| := by simp [Real.dist_eq]
#align real.dist_0_eq_abs Real.dist_0_eq_abs
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.dist_left_le_of_mem_uIcc {x y z : ℝ} (h : y ∈ uIcc x z) : dist x y ≤ dist x z := by
simpa only [dist_comm x] using abs_sub_left_of_mem_uIcc h
#align real.dist_left_le_of_mem_uIcc Real.dist_left_le_of_mem_uIcc
theorem Real.dist_right_le_of_mem_uIcc {x y z : ℝ} (h : y ∈ uIcc x z) : dist y z ≤ dist x z := by
simpa only [dist_comm _ z] using abs_sub_right_of_mem_uIcc h
#align real.dist_right_le_of_mem_uIcc Real.dist_right_le_of_mem_uIcc
theorem Real.dist_le_of_mem_uIcc {x y x' y' : ℝ} (hx : x ∈ uIcc x' y') (hy : y ∈ uIcc x' y') :
dist x y ≤ dist x' y' :=
abs_sub_le_of_uIcc_subset_uIcc <| uIcc_subset_uIcc (by rwa [uIcc_comm]) (by rwa [uIcc_comm])
#align real.dist_le_of_mem_uIcc Real.dist_le_of_mem_uIcc
theorem Real.dist_le_of_mem_Icc {x y x' y' : ℝ} (hx : x ∈ Icc x' y') (hy : y ∈ Icc x' y') :
dist x y ≤ y' - x' := by
simpa only [Real.dist_eq, abs_of_nonpos (sub_nonpos.2 <| hx.1.trans hx.2), neg_sub] using
Real.dist_le_of_mem_uIcc (Icc_subset_uIcc hx) (Icc_subset_uIcc hy)
#align real.dist_le_of_mem_Icc Real.dist_le_of_mem_Icc
theorem Real.dist_le_of_mem_Icc_01 {x y : ℝ} (hx : x ∈ Icc (0 : ℝ) 1) (hy : y ∈ Icc (0 : ℝ) 1) :
dist x y ≤ 1 := by simpa only [sub_zero] using Real.dist_le_of_mem_Icc hx hy
#align real.dist_le_of_mem_Icc_01 Real.dist_le_of_mem_Icc_01
instance : OrderTopology ℝ :=
orderTopology_of_nhds_abs fun x => by
simp only [nhds_basis_ball.eq_biInf, ball, Real.dist_eq, abs_sub_comm]
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]
#align real.ball_eq_Ioo Real.ball_eq_Ioo
| Mathlib/Topology/MetricSpace/PseudoMetric.lean | 1,393 | 1,396 | 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]
|
/-
Copyright (c) 2018 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Scott Morrison, Floris van Doorn
-/
import Mathlib.CategoryTheory.Limits.IsLimit
import Mathlib.CategoryTheory.Category.ULift
import Mathlib.CategoryTheory.EssentiallySmall
import Mathlib.Logic.Equiv.Basic
#align_import category_theory.limits.has_limits from "leanprover-community/mathlib"@"2738d2ca56cbc63be80c3bd48e9ed90ad94e947d"
/-!
# Existence of limits and colimits
In `CategoryTheory.Limits.IsLimit` we defined `IsLimit c`,
the data showing that a cone `c` is a limit cone.
The two main structures defined in this file are:
* `LimitCone F`, which consists of a choice of cone for `F` and the fact it is a limit cone, and
* `HasLimit F`, asserting the mere existence of some limit cone for `F`.
`HasLimit` is a propositional typeclass
(it's important that it is a proposition merely asserting the existence of a limit,
as otherwise we would have non-defeq problems from incompatible instances).
While `HasLimit` only asserts the existence of a limit cone,
we happily use the axiom of choice in mathlib,
so there are convenience functions all depending on `HasLimit F`:
* `limit F : C`, producing some limit object (of course all such are isomorphic)
* `limit.π F j : limit F ⟶ F.obj j`, the morphisms out of the limit,
* `limit.lift F c : c.pt ⟶ limit F`, the universal morphism from any other `c : Cone F`, etc.
Key to using the `HasLimit` interface is that there is an `@[ext]` lemma stating that
to check `f = g`, for `f g : Z ⟶ limit F`, it suffices to check `f ≫ limit.π F j = g ≫ limit.π F j`
for every `j`.
This, combined with `@[simp]` lemmas, makes it possible to prove many easy facts about limits using
automation (e.g. `tidy`).
There are abbreviations `HasLimitsOfShape J C` and `HasLimits C`
asserting the existence of classes of limits.
Later more are introduced, for finite limits, special shapes of limits, etc.
Ideally, many results about limits should be stated first in terms of `IsLimit`,
and then a result in terms of `HasLimit` derived from this.
At this point, however, this is far from uniformly achieved in mathlib ---
often statements are only written in terms of `HasLimit`.
## Implementation
At present we simply say everything twice, in order to handle both limits and colimits.
It would be highly desirable to have some automation support,
e.g. a `@[dualize]` attribute that behaves similarly to `@[to_additive]`.
## References
* [Stacks: Limits and colimits](https://stacks.math.columbia.edu/tag/002D)
-/
noncomputable section
open CategoryTheory CategoryTheory.Category CategoryTheory.Functor Opposite
namespace CategoryTheory.Limits
-- morphism levels before object levels. See note [CategoryTheory universes].
universe v₁ u₁ v₂ u₂ v₃ u₃ v v' v'' u u' u''
variable {J : Type u₁} [Category.{v₁} J] {K : Type u₂} [Category.{v₂} K]
variable {C : Type u} [Category.{v} C]
variable {F : J ⥤ C}
section Limit
/-- `LimitCone F` contains a cone over `F` together with the information that it is a limit. -/
-- @[nolint has_nonempty_instance] -- Porting note(#5171): removed; linter not ported yet
structure LimitCone (F : J ⥤ C) where
/-- The cone itself -/
cone : Cone F
/-- The proof that is the limit cone -/
isLimit : IsLimit cone
#align category_theory.limits.limit_cone CategoryTheory.Limits.LimitCone
#align category_theory.limits.limit_cone.is_limit CategoryTheory.Limits.LimitCone.isLimit
/-- `HasLimit F` represents the mere existence of a limit for `F`. -/
class HasLimit (F : J ⥤ C) : Prop where mk' ::
/-- There is some limit cone for `F` -/
exists_limit : Nonempty (LimitCone F)
#align category_theory.limits.has_limit CategoryTheory.Limits.HasLimit
theorem HasLimit.mk {F : J ⥤ C} (d : LimitCone F) : HasLimit F :=
⟨Nonempty.intro d⟩
#align category_theory.limits.has_limit.mk CategoryTheory.Limits.HasLimit.mk
/-- Use the axiom of choice to extract explicit `LimitCone F` from `HasLimit F`. -/
def getLimitCone (F : J ⥤ C) [HasLimit F] : LimitCone F :=
Classical.choice <| HasLimit.exists_limit
#align category_theory.limits.get_limit_cone CategoryTheory.Limits.getLimitCone
variable (J C)
/-- `C` has limits of shape `J` if there exists a limit for every functor `F : J ⥤ C`. -/
class HasLimitsOfShape : Prop where
/-- All functors `F : J ⥤ C` from `J` have limits -/
has_limit : ∀ F : J ⥤ C, HasLimit F := by infer_instance
#align category_theory.limits.has_limits_of_shape CategoryTheory.Limits.HasLimitsOfShape
/-- `C` has all limits of size `v₁ u₁` (`HasLimitsOfSize.{v₁ u₁} C`)
if it has limits of every shape `J : Type u₁` with `[Category.{v₁} J]`.
-/
@[pp_with_univ]
class HasLimitsOfSize (C : Type u) [Category.{v} C] : Prop where
/-- All functors `F : J ⥤ C` from all small `J` have limits -/
has_limits_of_shape : ∀ (J : Type u₁) [Category.{v₁} J], HasLimitsOfShape J C := by
infer_instance
#align category_theory.limits.has_limits_of_size CategoryTheory.Limits.HasLimitsOfSize
/-- `C` has all (small) limits if it has limits of every shape that is as big as its hom-sets. -/
abbrev HasLimits (C : Type u) [Category.{v} C] : Prop :=
HasLimitsOfSize.{v, v} C
#align category_theory.limits.has_limits CategoryTheory.Limits.HasLimits
theorem HasLimits.has_limits_of_shape {C : Type u} [Category.{v} C] [HasLimits C] (J : Type v)
[Category.{v} J] : HasLimitsOfShape J C :=
HasLimitsOfSize.has_limits_of_shape J
#align category_theory.limits.has_limits.has_limits_of_shape CategoryTheory.Limits.HasLimits.has_limits_of_shape
variable {J C}
-- see Note [lower instance priority]
instance (priority := 100) hasLimitOfHasLimitsOfShape {J : Type u₁} [Category.{v₁} J]
[HasLimitsOfShape J C] (F : J ⥤ C) : HasLimit F :=
HasLimitsOfShape.has_limit F
#align category_theory.limits.has_limit_of_has_limits_of_shape CategoryTheory.Limits.hasLimitOfHasLimitsOfShape
-- see Note [lower instance priority]
instance (priority := 100) hasLimitsOfShapeOfHasLimits {J : Type u₁} [Category.{v₁} J]
[HasLimitsOfSize.{v₁, u₁} C] : HasLimitsOfShape J C :=
HasLimitsOfSize.has_limits_of_shape J
#align category_theory.limits.has_limits_of_shape_of_has_limits CategoryTheory.Limits.hasLimitsOfShapeOfHasLimits
-- Interface to the `HasLimit` class.
/-- An arbitrary choice of limit cone for a functor. -/
def limit.cone (F : J ⥤ C) [HasLimit F] : Cone F :=
(getLimitCone F).cone
#align category_theory.limits.limit.cone CategoryTheory.Limits.limit.cone
/-- An arbitrary choice of limit object of a functor. -/
def limit (F : J ⥤ C) [HasLimit F] :=
(limit.cone F).pt
#align category_theory.limits.limit CategoryTheory.Limits.limit
/-- The projection from the limit object to a value of the functor. -/
def limit.π (F : J ⥤ C) [HasLimit F] (j : J) : limit F ⟶ F.obj j :=
(limit.cone F).π.app j
#align category_theory.limits.limit.π CategoryTheory.Limits.limit.π
@[simp]
theorem limit.cone_x {F : J ⥤ C} [HasLimit F] : (limit.cone F).pt = limit F :=
rfl
set_option linter.uppercaseLean3 false in
#align category_theory.limits.limit.cone_X CategoryTheory.Limits.limit.cone_x
@[simp]
theorem limit.cone_π {F : J ⥤ C} [HasLimit F] : (limit.cone F).π.app = limit.π _ :=
rfl
#align category_theory.limits.limit.cone_π CategoryTheory.Limits.limit.cone_π
@[reassoc (attr := simp)]
theorem limit.w (F : J ⥤ C) [HasLimit F] {j j' : J} (f : j ⟶ j') :
limit.π F j ≫ F.map f = limit.π F j' :=
(limit.cone F).w f
#align category_theory.limits.limit.w CategoryTheory.Limits.limit.w
/-- Evidence that the arbitrary choice of cone provided by `limit.cone F` is a limit cone. -/
def limit.isLimit (F : J ⥤ C) [HasLimit F] : IsLimit (limit.cone F) :=
(getLimitCone F).isLimit
#align category_theory.limits.limit.is_limit CategoryTheory.Limits.limit.isLimit
/-- The morphism from the cone point of any other cone to the limit object. -/
def limit.lift (F : J ⥤ C) [HasLimit F] (c : Cone F) : c.pt ⟶ limit F :=
(limit.isLimit F).lift c
#align category_theory.limits.limit.lift CategoryTheory.Limits.limit.lift
@[simp]
theorem limit.isLimit_lift {F : J ⥤ C} [HasLimit F] (c : Cone F) :
(limit.isLimit F).lift c = limit.lift F c :=
rfl
#align category_theory.limits.limit.is_limit_lift CategoryTheory.Limits.limit.isLimit_lift
@[reassoc (attr := simp)]
theorem limit.lift_π {F : J ⥤ C} [HasLimit F] (c : Cone F) (j : J) :
limit.lift F c ≫ limit.π F j = c.π.app j :=
IsLimit.fac _ c j
#align category_theory.limits.limit.lift_π CategoryTheory.Limits.limit.lift_π
/-- Functoriality of limits.
Usually this morphism should be accessed through `lim.map`,
but may be needed separately when you have specified limits for the source and target functors,
but not necessarily for all functors of shape `J`.
-/
def limMap {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) : limit F ⟶ limit G :=
IsLimit.map _ (limit.isLimit G) α
#align category_theory.limits.lim_map CategoryTheory.Limits.limMap
@[reassoc (attr := simp)]
theorem limMap_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) (j : J) :
limMap α ≫ limit.π G j = limit.π F j ≫ α.app j :=
limit.lift_π _ j
#align category_theory.limits.lim_map_π CategoryTheory.Limits.limMap_π
/-- The cone morphism from any cone to the arbitrary choice of limit cone. -/
def limit.coneMorphism {F : J ⥤ C} [HasLimit F] (c : Cone F) : c ⟶ limit.cone F :=
(limit.isLimit F).liftConeMorphism c
#align category_theory.limits.limit.cone_morphism CategoryTheory.Limits.limit.coneMorphism
@[simp]
theorem limit.coneMorphism_hom {F : J ⥤ C} [HasLimit F] (c : Cone F) :
(limit.coneMorphism c).hom = limit.lift F c :=
rfl
#align category_theory.limits.limit.cone_morphism_hom CategoryTheory.Limits.limit.coneMorphism_hom
| Mathlib/CategoryTheory/Limits/HasLimits.lean | 224 | 225 | theorem limit.coneMorphism_π {F : J ⥤ C} [HasLimit F] (c : Cone F) (j : J) :
(limit.coneMorphism c).hom ≫ limit.π F j = c.π.app j := by | simp
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Basic
import Mathlib.Data.Nat.SuccPred
#align_import set_theory.ordinal.arithmetic from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Ordinal arithmetic
Ordinals have an addition (corresponding to disjoint union) that turns them into an additive
monoid, and a multiplication (corresponding to the lexicographic order on the product) that turns
them into a monoid. One can also define correspondingly a subtraction, a division, a successor
function, a power function and a logarithm function.
We also define limit ordinals and prove the basic induction principle on ordinals separating
successor ordinals and limit ordinals, in `limitRecOn`.
## Main definitions and results
* `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that
every element of `o₁` is smaller than every element of `o₂`.
* `o₁ - o₂` is the unique ordinal `o` such that `o₂ + o = o₁`, when `o₂ ≤ o₁`.
* `o₁ * o₂` is the lexicographic order on `o₂ × o₁`.
* `o₁ / o₂` is the ordinal `o` such that `o₁ = o₂ * o + o'` with `o' < o₂`. We also define the
divisibility predicate, and a modulo operation.
* `Order.succ o = o + 1` is the successor of `o`.
* `pred o` if the predecessor of `o`. If `o` is not a successor, we set `pred o = o`.
We discuss the properties of casts of natural numbers of and of `ω` with respect to these
operations.
Some properties of the operations are also used to discuss general tools on ordinals:
* `IsLimit o`: an ordinal is a limit ordinal if it is neither `0` nor a successor.
* `limitRecOn` is the main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals.
* `IsNormal`: a function `f : Ordinal → Ordinal` satisfies `IsNormal` if it is strictly increasing
and order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`.
* `enumOrd`: enumerates an unbounded set of ordinals by the ordinals themselves.
* `sup`, `lsub`: the supremum / least strict upper bound of an indexed family of ordinals in
`Type u`, as an ordinal in `Type u`.
* `bsup`, `blsub`: the supremum / least strict upper bound of a set of ordinals indexed by ordinals
less than a given ordinal `o`.
Various other basic arithmetic results are given in `Principal.lean` instead.
-/
assert_not_exists Field
assert_not_exists Module
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal Ordinal
universe u v w
namespace Ordinal
variable {α : Type*} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Further properties of addition on ordinals -/
@[simp]
theorem lift_add (a b : Ordinal.{v}) : lift.{u} (a + b) = lift.{u} a + lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.sumLexCongr (RelIso.preimage Equiv.ulift _) (RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_add Ordinal.lift_add
@[simp]
theorem lift_succ (a : Ordinal.{v}) : lift.{u} (succ a) = succ (lift.{u} a) := by
rw [← add_one_eq_succ, lift_add, lift_one]
rfl
#align ordinal.lift_succ Ordinal.lift_succ
instance add_contravariantClass_le : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· ≤ ·) :=
⟨fun a b c =>
inductionOn a fun α r hr =>
inductionOn b fun β₁ s₁ hs₁ =>
inductionOn c fun β₂ s₂ hs₂ ⟨f⟩ =>
⟨have fl : ∀ a, f (Sum.inl a) = Sum.inl a := fun a => by
simpa only [InitialSeg.trans_apply, InitialSeg.leAdd_apply] using
@InitialSeg.eq _ _ _ _ _
((InitialSeg.leAdd r s₁).trans f) (InitialSeg.leAdd r s₂) a
have : ∀ b, { b' // f (Sum.inr b) = Sum.inr b' } := by
intro b; cases e : f (Sum.inr b)
· rw [← fl] at e
have := f.inj' e
contradiction
· exact ⟨_, rfl⟩
let g (b) := (this b).1
have fr : ∀ b, f (Sum.inr b) = Sum.inr (g b) := fun b => (this b).2
⟨⟨⟨g, fun x y h => by
injection f.inj' (by rw [fr, fr, h] : f (Sum.inr x) = f (Sum.inr y))⟩,
@fun a b => by
-- Porting note:
-- `relEmbedding.coe_fn_to_embedding` & `initial_seg.coe_fn_to_rel_embedding`
-- → `InitialSeg.coe_coe_fn`
simpa only [Sum.lex_inr_inr, fr, InitialSeg.coe_coe_fn, Embedding.coeFn_mk] using
@RelEmbedding.map_rel_iff _ _ _ _ f.toRelEmbedding (Sum.inr a) (Sum.inr b)⟩,
fun a b H => by
rcases f.init (by rw [fr] <;> exact Sum.lex_inr_inr.2 H) with ⟨a' | a', h⟩
· rw [fl] at h
cases h
· rw [fr] at h
exact ⟨a', Sum.inr.inj h⟩⟩⟩⟩
#align ordinal.add_contravariant_class_le Ordinal.add_contravariantClass_le
theorem add_left_cancel (a) {b c : Ordinal} : a + b = a + c ↔ b = c := by
simp only [le_antisymm_iff, add_le_add_iff_left]
#align ordinal.add_left_cancel Ordinal.add_left_cancel
private theorem add_lt_add_iff_left' (a) {b c : Ordinal} : a + b < a + c ↔ b < c := by
rw [← not_le, ← not_le, add_le_add_iff_left]
instance add_covariantClass_lt : CovariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).2⟩
#align ordinal.add_covariant_class_lt Ordinal.add_covariantClass_lt
instance add_contravariantClass_lt : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).1⟩
#align ordinal.add_contravariant_class_lt Ordinal.add_contravariantClass_lt
instance add_swap_contravariantClass_lt :
ContravariantClass Ordinal.{u} Ordinal.{u} (swap (· + ·)) (· < ·) :=
⟨fun _a _b _c => lt_imp_lt_of_le_imp_le fun h => add_le_add_right h _⟩
#align ordinal.add_swap_contravariant_class_lt Ordinal.add_swap_contravariantClass_lt
theorem add_le_add_iff_right {a b : Ordinal} : ∀ n : ℕ, a + n ≤ b + n ↔ a ≤ b
| 0 => by simp
| n + 1 => by
simp only [natCast_succ, add_succ, add_succ, succ_le_succ_iff, add_le_add_iff_right]
#align ordinal.add_le_add_iff_right Ordinal.add_le_add_iff_right
theorem add_right_cancel {a b : Ordinal} (n : ℕ) : a + n = b + n ↔ a = b := by
simp only [le_antisymm_iff, add_le_add_iff_right]
#align ordinal.add_right_cancel Ordinal.add_right_cancel
theorem add_eq_zero_iff {a b : Ordinal} : a + b = 0 ↔ a = 0 ∧ b = 0 :=
inductionOn a fun α r _ =>
inductionOn b fun β s _ => by
simp_rw [← type_sum_lex, type_eq_zero_iff_isEmpty]
exact isEmpty_sum
#align ordinal.add_eq_zero_iff Ordinal.add_eq_zero_iff
theorem left_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : a = 0 :=
(add_eq_zero_iff.1 h).1
#align ordinal.left_eq_zero_of_add_eq_zero Ordinal.left_eq_zero_of_add_eq_zero
theorem right_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : b = 0 :=
(add_eq_zero_iff.1 h).2
#align ordinal.right_eq_zero_of_add_eq_zero Ordinal.right_eq_zero_of_add_eq_zero
/-! ### The predecessor of an ordinal -/
/-- The ordinal predecessor of `o` is `o'` if `o = succ o'`,
and `o` otherwise. -/
def pred (o : Ordinal) : Ordinal :=
if h : ∃ a, o = succ a then Classical.choose h else o
#align ordinal.pred Ordinal.pred
@[simp]
theorem pred_succ (o) : pred (succ o) = o := by
have h : ∃ a, succ o = succ a := ⟨_, rfl⟩;
simpa only [pred, dif_pos h] using (succ_injective <| Classical.choose_spec h).symm
#align ordinal.pred_succ Ordinal.pred_succ
theorem pred_le_self (o) : pred o ≤ o :=
if h : ∃ a, o = succ a then by
let ⟨a, e⟩ := h
rw [e, pred_succ]; exact le_succ a
else by rw [pred, dif_neg h]
#align ordinal.pred_le_self Ordinal.pred_le_self
theorem pred_eq_iff_not_succ {o} : pred o = o ↔ ¬∃ a, o = succ a :=
⟨fun e ⟨a, e'⟩ => by rw [e', pred_succ] at e; exact (lt_succ a).ne e, fun h => dif_neg h⟩
#align ordinal.pred_eq_iff_not_succ Ordinal.pred_eq_iff_not_succ
theorem pred_eq_iff_not_succ' {o} : pred o = o ↔ ∀ a, o ≠ succ a := by
simpa using pred_eq_iff_not_succ
#align ordinal.pred_eq_iff_not_succ' Ordinal.pred_eq_iff_not_succ'
theorem pred_lt_iff_is_succ {o} : pred o < o ↔ ∃ a, o = succ a :=
Iff.trans (by simp only [le_antisymm_iff, pred_le_self, true_and_iff, not_le])
(iff_not_comm.1 pred_eq_iff_not_succ).symm
#align ordinal.pred_lt_iff_is_succ Ordinal.pred_lt_iff_is_succ
@[simp]
theorem pred_zero : pred 0 = 0 :=
pred_eq_iff_not_succ'.2 fun a => (succ_ne_zero a).symm
#align ordinal.pred_zero Ordinal.pred_zero
theorem succ_pred_iff_is_succ {o} : succ (pred o) = o ↔ ∃ a, o = succ a :=
⟨fun e => ⟨_, e.symm⟩, fun ⟨a, e⟩ => by simp only [e, pred_succ]⟩
#align ordinal.succ_pred_iff_is_succ Ordinal.succ_pred_iff_is_succ
theorem succ_lt_of_not_succ {o b : Ordinal} (h : ¬∃ a, o = succ a) : succ b < o ↔ b < o :=
⟨(lt_succ b).trans, fun l => lt_of_le_of_ne (succ_le_of_lt l) fun e => h ⟨_, e.symm⟩⟩
#align ordinal.succ_lt_of_not_succ Ordinal.succ_lt_of_not_succ
theorem lt_pred {a b} : a < pred b ↔ succ a < b :=
if h : ∃ a, b = succ a then by
let ⟨c, e⟩ := h
rw [e, pred_succ, succ_lt_succ_iff]
else by simp only [pred, dif_neg h, succ_lt_of_not_succ h]
#align ordinal.lt_pred Ordinal.lt_pred
theorem pred_le {a b} : pred a ≤ b ↔ a ≤ succ b :=
le_iff_le_iff_lt_iff_lt.2 lt_pred
#align ordinal.pred_le Ordinal.pred_le
@[simp]
theorem lift_is_succ {o : Ordinal.{v}} : (∃ a, lift.{u} o = succ a) ↔ ∃ a, o = succ a :=
⟨fun ⟨a, h⟩ =>
let ⟨b, e⟩ := lift_down <| show a ≤ lift.{u} o from le_of_lt <| h.symm ▸ lt_succ a
⟨b, lift_inj.1 <| by rw [h, ← e, lift_succ]⟩,
fun ⟨a, h⟩ => ⟨lift.{u} a, by simp only [h, lift_succ]⟩⟩
#align ordinal.lift_is_succ Ordinal.lift_is_succ
@[simp]
theorem lift_pred (o : Ordinal.{v}) : lift.{u} (pred o) = pred (lift.{u} o) :=
if h : ∃ a, o = succ a then by cases' h with a e; simp only [e, pred_succ, lift_succ]
else by rw [pred_eq_iff_not_succ.2 h, pred_eq_iff_not_succ.2 (mt lift_is_succ.1 h)]
#align ordinal.lift_pred Ordinal.lift_pred
/-! ### Limit ordinals -/
/-- A limit ordinal is an ordinal which is not zero and not a successor. -/
def IsLimit (o : Ordinal) : Prop :=
o ≠ 0 ∧ ∀ a < o, succ a < o
#align ordinal.is_limit Ordinal.IsLimit
theorem IsLimit.isSuccLimit {o} (h : IsLimit o) : IsSuccLimit o := isSuccLimit_iff_succ_lt.mpr h.2
theorem IsLimit.succ_lt {o a : Ordinal} (h : IsLimit o) : a < o → succ a < o :=
h.2 a
#align ordinal.is_limit.succ_lt Ordinal.IsLimit.succ_lt
theorem isSuccLimit_zero : IsSuccLimit (0 : Ordinal) := isSuccLimit_bot
theorem not_zero_isLimit : ¬IsLimit 0
| ⟨h, _⟩ => h rfl
#align ordinal.not_zero_is_limit Ordinal.not_zero_isLimit
theorem not_succ_isLimit (o) : ¬IsLimit (succ o)
| ⟨_, h⟩ => lt_irrefl _ (h _ (lt_succ o))
#align ordinal.not_succ_is_limit Ordinal.not_succ_isLimit
theorem not_succ_of_isLimit {o} (h : IsLimit o) : ¬∃ a, o = succ a
| ⟨a, e⟩ => not_succ_isLimit a (e ▸ h)
#align ordinal.not_succ_of_is_limit Ordinal.not_succ_of_isLimit
theorem succ_lt_of_isLimit {o a : Ordinal} (h : IsLimit o) : succ a < o ↔ a < o :=
⟨(lt_succ a).trans, h.2 _⟩
#align ordinal.succ_lt_of_is_limit Ordinal.succ_lt_of_isLimit
theorem le_succ_of_isLimit {o} (h : IsLimit o) {a} : o ≤ succ a ↔ o ≤ a :=
le_iff_le_iff_lt_iff_lt.2 <| succ_lt_of_isLimit h
#align ordinal.le_succ_of_is_limit Ordinal.le_succ_of_isLimit
theorem limit_le {o} (h : IsLimit o) {a} : o ≤ a ↔ ∀ x < o, x ≤ a :=
⟨fun h _x l => l.le.trans h, fun H =>
(le_succ_of_isLimit h).1 <| le_of_not_lt fun hn => not_lt_of_le (H _ hn) (lt_succ a)⟩
#align ordinal.limit_le Ordinal.limit_le
theorem lt_limit {o} (h : IsLimit o) {a} : a < o ↔ ∃ x < o, a < x := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@limit_le _ h a)
#align ordinal.lt_limit Ordinal.lt_limit
@[simp]
theorem lift_isLimit (o) : IsLimit (lift o) ↔ IsLimit o :=
and_congr (not_congr <| by simpa only [lift_zero] using @lift_inj o 0)
⟨fun H a h => lift_lt.1 <| by simpa only [lift_succ] using H _ (lift_lt.2 h), fun H a h => by
obtain ⟨a', rfl⟩ := lift_down h.le
rw [← lift_succ, lift_lt]
exact H a' (lift_lt.1 h)⟩
#align ordinal.lift_is_limit Ordinal.lift_isLimit
theorem IsLimit.pos {o : Ordinal} (h : IsLimit o) : 0 < o :=
lt_of_le_of_ne (Ordinal.zero_le _) h.1.symm
#align ordinal.is_limit.pos Ordinal.IsLimit.pos
theorem IsLimit.one_lt {o : Ordinal} (h : IsLimit o) : 1 < o := by
simpa only [succ_zero] using h.2 _ h.pos
#align ordinal.is_limit.one_lt Ordinal.IsLimit.one_lt
theorem IsLimit.nat_lt {o : Ordinal} (h : IsLimit o) : ∀ n : ℕ, (n : Ordinal) < o
| 0 => h.pos
| n + 1 => h.2 _ (IsLimit.nat_lt h n)
#align ordinal.is_limit.nat_lt Ordinal.IsLimit.nat_lt
theorem zero_or_succ_or_limit (o : Ordinal) : o = 0 ∨ (∃ a, o = succ a) ∨ IsLimit o :=
if o0 : o = 0 then Or.inl o0
else
if h : ∃ a, o = succ a then Or.inr (Or.inl h)
else Or.inr <| Or.inr ⟨o0, fun _a => (succ_lt_of_not_succ h).2⟩
#align ordinal.zero_or_succ_or_limit Ordinal.zero_or_succ_or_limit
/-- Main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals. -/
@[elab_as_elim]
def limitRecOn {C : Ordinal → Sort*} (o : Ordinal) (H₁ : C 0) (H₂ : ∀ o, C o → C (succ o))
(H₃ : ∀ o, IsLimit o → (∀ o' < o, C o') → C o) : C o :=
SuccOrder.limitRecOn o (fun o _ ↦ H₂ o) fun o hl ↦
if h : o = 0 then fun _ ↦ h ▸ H₁ else H₃ o ⟨h, fun _ ↦ hl.succ_lt⟩
#align ordinal.limit_rec_on Ordinal.limitRecOn
@[simp]
theorem limitRecOn_zero {C} (H₁ H₂ H₃) : @limitRecOn C 0 H₁ H₂ H₃ = H₁ := by
rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ isSuccLimit_zero, dif_pos rfl]
#align ordinal.limit_rec_on_zero Ordinal.limitRecOn_zero
@[simp]
theorem limitRecOn_succ {C} (o H₁ H₂ H₃) :
@limitRecOn C (succ o) H₁ H₂ H₃ = H₂ o (@limitRecOn C o H₁ H₂ H₃) := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_succ _ _ (not_isMax _)]
#align ordinal.limit_rec_on_succ Ordinal.limitRecOn_succ
@[simp]
theorem limitRecOn_limit {C} (o H₁ H₂ H₃ h) :
@limitRecOn C o H₁ H₂ H₃ = H₃ o h fun x _h => @limitRecOn C x H₁ H₂ H₃ := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ h.isSuccLimit, dif_neg h.1]
#align ordinal.limit_rec_on_limit Ordinal.limitRecOn_limit
instance orderTopOutSucc (o : Ordinal) : OrderTop (succ o).out.α :=
@OrderTop.mk _ _ (Top.mk _) le_enum_succ
#align ordinal.order_top_out_succ Ordinal.orderTopOutSucc
theorem enum_succ_eq_top {o : Ordinal} :
enum (· < ·) o
(by
rw [type_lt]
exact lt_succ o) =
(⊤ : (succ o).out.α) :=
rfl
#align ordinal.enum_succ_eq_top Ordinal.enum_succ_eq_top
theorem has_succ_of_type_succ_lt {α} {r : α → α → Prop} [wo : IsWellOrder α r]
(h : ∀ a < type r, succ a < type r) (x : α) : ∃ y, r x y := by
use enum r (succ (typein r x)) (h _ (typein_lt_type r x))
convert (enum_lt_enum (typein_lt_type r x)
(h _ (typein_lt_type r x))).mpr (lt_succ _); rw [enum_typein]
#align ordinal.has_succ_of_type_succ_lt Ordinal.has_succ_of_type_succ_lt
theorem out_no_max_of_succ_lt {o : Ordinal} (ho : ∀ a < o, succ a < o) : NoMaxOrder o.out.α :=
⟨has_succ_of_type_succ_lt (by rwa [type_lt])⟩
#align ordinal.out_no_max_of_succ_lt Ordinal.out_no_max_of_succ_lt
theorem bounded_singleton {r : α → α → Prop} [IsWellOrder α r] (hr : (type r).IsLimit) (x) :
Bounded r {x} := by
refine ⟨enum r (succ (typein r x)) (hr.2 _ (typein_lt_type r x)), ?_⟩
intro b hb
rw [mem_singleton_iff.1 hb]
nth_rw 1 [← enum_typein r x]
rw [@enum_lt_enum _ r]
apply lt_succ
#align ordinal.bounded_singleton Ordinal.bounded_singleton
-- Porting note: `· < ·` requires a type ascription for an `IsWellOrder` instance.
theorem type_subrel_lt (o : Ordinal.{u}) :
type (Subrel ((· < ·) : Ordinal → Ordinal → Prop) { o' : Ordinal | o' < o })
= Ordinal.lift.{u + 1} o := by
refine Quotient.inductionOn o ?_
rintro ⟨α, r, wo⟩; apply Quotient.sound
-- Porting note: `symm; refine' [term]` → `refine' [term].symm`
constructor; refine ((RelIso.preimage Equiv.ulift r).trans (enumIso r).symm).symm
#align ordinal.type_subrel_lt Ordinal.type_subrel_lt
theorem mk_initialSeg (o : Ordinal.{u}) :
#{ o' : Ordinal | o' < o } = Cardinal.lift.{u + 1} o.card := by
rw [lift_card, ← type_subrel_lt, card_type]
#align ordinal.mk_initial_seg Ordinal.mk_initialSeg
/-! ### Normal ordinal functions -/
/-- A normal ordinal function is a strictly increasing function which is
order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`. -/
def IsNormal (f : Ordinal → Ordinal) : Prop :=
(∀ o, f o < f (succ o)) ∧ ∀ o, IsLimit o → ∀ a, f o ≤ a ↔ ∀ b < o, f b ≤ a
#align ordinal.is_normal Ordinal.IsNormal
theorem IsNormal.limit_le {f} (H : IsNormal f) :
∀ {o}, IsLimit o → ∀ {a}, f o ≤ a ↔ ∀ b < o, f b ≤ a :=
@H.2
#align ordinal.is_normal.limit_le Ordinal.IsNormal.limit_le
theorem IsNormal.limit_lt {f} (H : IsNormal f) {o} (h : IsLimit o) {a} :
a < f o ↔ ∃ b < o, a < f b :=
not_iff_not.1 <| by simpa only [exists_prop, not_exists, not_and, not_lt] using H.2 _ h a
#align ordinal.is_normal.limit_lt Ordinal.IsNormal.limit_lt
theorem IsNormal.strictMono {f} (H : IsNormal f) : StrictMono f := fun a b =>
limitRecOn b (Not.elim (not_lt_of_le <| Ordinal.zero_le _))
(fun _b IH h =>
(lt_or_eq_of_le (le_of_lt_succ h)).elim (fun h => (IH h).trans (H.1 _)) fun e => e ▸ H.1 _)
fun _b l _IH h => lt_of_lt_of_le (H.1 a) ((H.2 _ l _).1 le_rfl _ (l.2 _ h))
#align ordinal.is_normal.strict_mono Ordinal.IsNormal.strictMono
theorem IsNormal.monotone {f} (H : IsNormal f) : Monotone f :=
H.strictMono.monotone
#align ordinal.is_normal.monotone Ordinal.IsNormal.monotone
theorem isNormal_iff_strictMono_limit (f : Ordinal → Ordinal) :
IsNormal f ↔ StrictMono f ∧ ∀ o, IsLimit o → ∀ a, (∀ b < o, f b ≤ a) → f o ≤ a :=
⟨fun hf => ⟨hf.strictMono, fun a ha c => (hf.2 a ha c).2⟩, fun ⟨hs, hl⟩ =>
⟨fun a => hs (lt_succ a), fun a ha c =>
⟨fun hac _b hba => ((hs hba).trans_le hac).le, hl a ha c⟩⟩⟩
#align ordinal.is_normal_iff_strict_mono_limit Ordinal.isNormal_iff_strictMono_limit
theorem IsNormal.lt_iff {f} (H : IsNormal f) {a b} : f a < f b ↔ a < b :=
StrictMono.lt_iff_lt <| H.strictMono
#align ordinal.is_normal.lt_iff Ordinal.IsNormal.lt_iff
theorem IsNormal.le_iff {f} (H : IsNormal f) {a b} : f a ≤ f b ↔ a ≤ b :=
le_iff_le_iff_lt_iff_lt.2 H.lt_iff
#align ordinal.is_normal.le_iff Ordinal.IsNormal.le_iff
theorem IsNormal.inj {f} (H : IsNormal f) {a b} : f a = f b ↔ a = b := by
simp only [le_antisymm_iff, H.le_iff]
#align ordinal.is_normal.inj Ordinal.IsNormal.inj
theorem IsNormal.self_le {f} (H : IsNormal f) (a) : a ≤ f a :=
lt_wf.self_le_of_strictMono H.strictMono a
#align ordinal.is_normal.self_le Ordinal.IsNormal.self_le
theorem IsNormal.le_set {f o} (H : IsNormal f) (p : Set Ordinal) (p0 : p.Nonempty) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f a ≤ o :=
⟨fun h a pa => (H.le_iff.2 ((H₂ _).1 le_rfl _ pa)).trans h, fun h => by
-- Porting note: `refine'` didn't work well so `induction` is used
induction b using limitRecOn with
| H₁ =>
cases' p0 with x px
have := Ordinal.le_zero.1 ((H₂ _).1 (Ordinal.zero_le _) _ px)
rw [this] at px
exact h _ px
| H₂ S _ =>
rcases not_forall₂.1 (mt (H₂ S).2 <| (lt_succ S).not_le) with ⟨a, h₁, h₂⟩
exact (H.le_iff.2 <| succ_le_of_lt <| not_le.1 h₂).trans (h _ h₁)
| H₃ S L _ =>
refine (H.2 _ L _).2 fun a h' => ?_
rcases not_forall₂.1 (mt (H₂ a).2 h'.not_le) with ⟨b, h₁, h₂⟩
exact (H.le_iff.2 <| (not_le.1 h₂).le).trans (h _ h₁)⟩
#align ordinal.is_normal.le_set Ordinal.IsNormal.le_set
theorem IsNormal.le_set' {f o} (H : IsNormal f) (p : Set α) (p0 : p.Nonempty) (g : α → Ordinal) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, g a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f (g a) ≤ o := by
simpa [H₂] using H.le_set (g '' p) (p0.image g) b
#align ordinal.is_normal.le_set' Ordinal.IsNormal.le_set'
theorem IsNormal.refl : IsNormal id :=
⟨lt_succ, fun _o l _a => Ordinal.limit_le l⟩
#align ordinal.is_normal.refl Ordinal.IsNormal.refl
theorem IsNormal.trans {f g} (H₁ : IsNormal f) (H₂ : IsNormal g) : IsNormal (f ∘ g) :=
⟨fun _x => H₁.lt_iff.2 (H₂.1 _), fun o l _a =>
H₁.le_set' (· < o) ⟨0, l.pos⟩ g _ fun _c => H₂.2 _ l _⟩
#align ordinal.is_normal.trans Ordinal.IsNormal.trans
theorem IsNormal.isLimit {f} (H : IsNormal f) {o} (l : IsLimit o) : IsLimit (f o) :=
⟨ne_of_gt <| (Ordinal.zero_le _).trans_lt <| H.lt_iff.2 l.pos, fun _ h =>
let ⟨_b, h₁, h₂⟩ := (H.limit_lt l).1 h
(succ_le_of_lt h₂).trans_lt (H.lt_iff.2 h₁)⟩
#align ordinal.is_normal.is_limit Ordinal.IsNormal.isLimit
theorem IsNormal.le_iff_eq {f} (H : IsNormal f) {a} : f a ≤ a ↔ f a = a :=
(H.self_le a).le_iff_eq
#align ordinal.is_normal.le_iff_eq Ordinal.IsNormal.le_iff_eq
theorem add_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a + b ≤ c ↔ ∀ b' < b, a + b' ≤ c :=
⟨fun h b' l => (add_le_add_left l.le _).trans h, fun H =>
le_of_not_lt <| by
-- Porting note: `induction` tactics are required because of the parser bug.
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
intro l
suffices ∀ x : β, Sum.Lex r s (Sum.inr x) (enum _ _ l) by
-- Porting note: `revert` & `intro` is required because `cases'` doesn't replace
-- `enum _ _ l` in `this`.
revert this; cases' enum _ _ l with x x <;> intro this
· cases this (enum s 0 h.pos)
· exact irrefl _ (this _)
intro x
rw [← typein_lt_typein (Sum.Lex r s), typein_enum]
have := H _ (h.2 _ (typein_lt_type s x))
rw [add_succ, succ_le_iff] at this
refine
(RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨a | b, h⟩
· exact Sum.inl a
· exact Sum.inr ⟨b, by cases h; assumption⟩
· rcases a with ⟨a | a, h₁⟩ <;> rcases b with ⟨b | b, h₂⟩ <;> cases h₁ <;> cases h₂ <;>
rintro ⟨⟩ <;> constructor <;> assumption⟩
#align ordinal.add_le_of_limit Ordinal.add_le_of_limit
theorem add_isNormal (a : Ordinal) : IsNormal (a + ·) :=
⟨fun b => (add_lt_add_iff_left a).2 (lt_succ b), fun _b l _c => add_le_of_limit l⟩
#align ordinal.add_is_normal Ordinal.add_isNormal
theorem add_isLimit (a) {b} : IsLimit b → IsLimit (a + b) :=
(add_isNormal a).isLimit
#align ordinal.add_is_limit Ordinal.add_isLimit
alias IsLimit.add := add_isLimit
#align ordinal.is_limit.add Ordinal.IsLimit.add
/-! ### Subtraction on ordinals-/
/-- The set in the definition of subtraction is nonempty. -/
theorem sub_nonempty {a b : Ordinal} : { o | a ≤ b + o }.Nonempty :=
⟨a, le_add_left _ _⟩
#align ordinal.sub_nonempty Ordinal.sub_nonempty
/-- `a - b` is the unique ordinal satisfying `b + (a - b) = a` when `b ≤ a`. -/
instance sub : Sub Ordinal :=
⟨fun a b => sInf { o | a ≤ b + o }⟩
theorem le_add_sub (a b : Ordinal) : a ≤ b + (a - b) :=
csInf_mem sub_nonempty
#align ordinal.le_add_sub Ordinal.le_add_sub
theorem sub_le {a b c : Ordinal} : a - b ≤ c ↔ a ≤ b + c :=
⟨fun h => (le_add_sub a b).trans (add_le_add_left h _), fun h => csInf_le' h⟩
#align ordinal.sub_le Ordinal.sub_le
theorem lt_sub {a b c : Ordinal} : a < b - c ↔ c + a < b :=
lt_iff_lt_of_le_iff_le sub_le
#align ordinal.lt_sub Ordinal.lt_sub
theorem add_sub_cancel (a b : Ordinal) : a + b - a = b :=
le_antisymm (sub_le.2 <| le_rfl) ((add_le_add_iff_left a).1 <| le_add_sub _ _)
#align ordinal.add_sub_cancel Ordinal.add_sub_cancel
theorem sub_eq_of_add_eq {a b c : Ordinal} (h : a + b = c) : c - a = b :=
h ▸ add_sub_cancel _ _
#align ordinal.sub_eq_of_add_eq Ordinal.sub_eq_of_add_eq
theorem sub_le_self (a b : Ordinal) : a - b ≤ a :=
sub_le.2 <| le_add_left _ _
#align ordinal.sub_le_self Ordinal.sub_le_self
protected theorem add_sub_cancel_of_le {a b : Ordinal} (h : b ≤ a) : b + (a - b) = a :=
(le_add_sub a b).antisymm'
(by
rcases zero_or_succ_or_limit (a - b) with (e | ⟨c, e⟩ | l)
· simp only [e, add_zero, h]
· rw [e, add_succ, succ_le_iff, ← lt_sub, e]
exact lt_succ c
· exact (add_le_of_limit l).2 fun c l => (lt_sub.1 l).le)
#align ordinal.add_sub_cancel_of_le Ordinal.add_sub_cancel_of_le
theorem le_sub_of_le {a b c : Ordinal} (h : b ≤ a) : c ≤ a - b ↔ b + c ≤ a := by
rw [← add_le_add_iff_left b, Ordinal.add_sub_cancel_of_le h]
#align ordinal.le_sub_of_le Ordinal.le_sub_of_le
theorem sub_lt_of_le {a b c : Ordinal} (h : b ≤ a) : a - b < c ↔ a < b + c :=
lt_iff_lt_of_le_iff_le (le_sub_of_le h)
#align ordinal.sub_lt_of_le Ordinal.sub_lt_of_le
instance existsAddOfLE : ExistsAddOfLE Ordinal :=
⟨fun h => ⟨_, (Ordinal.add_sub_cancel_of_le h).symm⟩⟩
@[simp]
theorem sub_zero (a : Ordinal) : a - 0 = a := by simpa only [zero_add] using add_sub_cancel 0 a
#align ordinal.sub_zero Ordinal.sub_zero
@[simp]
theorem zero_sub (a : Ordinal) : 0 - a = 0 := by rw [← Ordinal.le_zero]; apply sub_le_self
#align ordinal.zero_sub Ordinal.zero_sub
@[simp]
theorem sub_self (a : Ordinal) : a - a = 0 := by simpa only [add_zero] using add_sub_cancel a 0
#align ordinal.sub_self Ordinal.sub_self
protected theorem sub_eq_zero_iff_le {a b : Ordinal} : a - b = 0 ↔ a ≤ b :=
⟨fun h => by simpa only [h, add_zero] using le_add_sub a b, fun h => by
rwa [← Ordinal.le_zero, sub_le, add_zero]⟩
#align ordinal.sub_eq_zero_iff_le Ordinal.sub_eq_zero_iff_le
theorem sub_sub (a b c : Ordinal) : a - b - c = a - (b + c) :=
eq_of_forall_ge_iff fun d => by rw [sub_le, sub_le, sub_le, add_assoc]
#align ordinal.sub_sub Ordinal.sub_sub
@[simp]
theorem add_sub_add_cancel (a b c : Ordinal) : a + b - (a + c) = b - c := by
rw [← sub_sub, add_sub_cancel]
#align ordinal.add_sub_add_cancel Ordinal.add_sub_add_cancel
theorem sub_isLimit {a b} (l : IsLimit a) (h : b < a) : IsLimit (a - b) :=
⟨ne_of_gt <| lt_sub.2 <| by rwa [add_zero], fun c h => by
rw [lt_sub, add_succ]; exact l.2 _ (lt_sub.1 h)⟩
#align ordinal.sub_is_limit Ordinal.sub_isLimit
-- @[simp] -- Porting note (#10618): simp can prove this
theorem one_add_omega : 1 + ω = ω := by
refine le_antisymm ?_ (le_add_left _ _)
rw [omega, ← lift_one.{_, 0}, ← lift_add, lift_le, ← type_unit, ← type_sum_lex]
refine ⟨RelEmbedding.collapse (RelEmbedding.ofMonotone ?_ ?_)⟩
· apply Sum.rec
· exact fun _ => 0
· exact Nat.succ
· intro a b
cases a <;> cases b <;> intro H <;> cases' H with _ _ H _ _ H <;>
[exact H.elim; exact Nat.succ_pos _; exact Nat.succ_lt_succ H]
#align ordinal.one_add_omega Ordinal.one_add_omega
@[simp]
theorem one_add_of_omega_le {o} (h : ω ≤ o) : 1 + o = o := by
rw [← Ordinal.add_sub_cancel_of_le h, ← add_assoc, one_add_omega]
#align ordinal.one_add_of_omega_le Ordinal.one_add_of_omega_le
/-! ### Multiplication of ordinals-/
/-- The multiplication of ordinals `o₁` and `o₂` is the (well founded) lexicographic order on
`o₂ × o₁`. -/
instance monoid : Monoid Ordinal.{u} where
mul a b :=
Quotient.liftOn₂ a b
(fun ⟨α, r, wo⟩ ⟨β, s, wo'⟩ => ⟦⟨β × α, Prod.Lex s r, inferInstance⟩⟧ :
WellOrder → WellOrder → Ordinal)
fun ⟨α₁, r₁, o₁⟩ ⟨α₂, r₂, o₂⟩ ⟨β₁, s₁, p₁⟩ ⟨β₂, s₂, p₂⟩ ⟨f⟩ ⟨g⟩ =>
Quot.sound ⟨RelIso.prodLexCongr g f⟩
one := 1
mul_assoc a b c :=
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Eq.symm <|
Quotient.sound
⟨⟨prodAssoc _ _ _, @fun a b => by
rcases a with ⟨⟨a₁, a₂⟩, a₃⟩
rcases b with ⟨⟨b₁, b₂⟩, b₃⟩
simp [Prod.lex_def, and_or_left, or_assoc, and_assoc]⟩⟩
mul_one a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨punitProd _, @fun a b => by
rcases a with ⟨⟨⟨⟩⟩, a⟩; rcases b with ⟨⟨⟨⟩⟩, b⟩
simp only [Prod.lex_def, EmptyRelation, false_or_iff]
simp only [eq_self_iff_true, true_and_iff]
rfl⟩⟩
one_mul a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨prodPUnit _, @fun a b => by
rcases a with ⟨a, ⟨⟨⟩⟩⟩; rcases b with ⟨b, ⟨⟨⟩⟩⟩
simp only [Prod.lex_def, EmptyRelation, and_false_iff, or_false_iff]
rfl⟩⟩
@[simp]
theorem type_prod_lex {α β : Type u} (r : α → α → Prop) (s : β → β → Prop) [IsWellOrder α r]
[IsWellOrder β s] : type (Prod.Lex s r) = type r * type s :=
rfl
#align ordinal.type_prod_lex Ordinal.type_prod_lex
private theorem mul_eq_zero' {a b : Ordinal} : a * b = 0 ↔ a = 0 ∨ b = 0 :=
inductionOn a fun α _ _ =>
inductionOn b fun β _ _ => by
simp_rw [← type_prod_lex, type_eq_zero_iff_isEmpty]
rw [or_comm]
exact isEmpty_prod
instance monoidWithZero : MonoidWithZero Ordinal :=
{ Ordinal.monoid with
zero := 0
mul_zero := fun _a => mul_eq_zero'.2 <| Or.inr rfl
zero_mul := fun _a => mul_eq_zero'.2 <| Or.inl rfl }
instance noZeroDivisors : NoZeroDivisors Ordinal :=
⟨fun {_ _} => mul_eq_zero'.1⟩
@[simp]
theorem lift_mul (a b : Ordinal.{v}) : lift.{u} (a * b) = lift.{u} a * lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.prodLexCongr (RelIso.preimage Equiv.ulift _)
(RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_mul Ordinal.lift_mul
@[simp]
theorem card_mul (a b) : card (a * b) = card a * card b :=
Quotient.inductionOn₂ a b fun ⟨α, _r, _⟩ ⟨β, _s, _⟩ => mul_comm #β #α
#align ordinal.card_mul Ordinal.card_mul
instance leftDistribClass : LeftDistribClass Ordinal.{u} :=
⟨fun a b c =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Quotient.sound
⟨⟨sumProdDistrib _ _ _, by
rintro ⟨a₁ | a₁, a₂⟩ ⟨b₁ | b₁, b₂⟩ <;>
simp only [Prod.lex_def, Sum.lex_inl_inl, Sum.Lex.sep, Sum.lex_inr_inl,
Sum.lex_inr_inr, sumProdDistrib_apply_left, sumProdDistrib_apply_right] <;>
-- Porting note: `Sum.inr.inj_iff` is required.
simp only [Sum.inl.inj_iff, Sum.inr.inj_iff,
true_or_iff, false_and_iff, false_or_iff]⟩⟩⟩
theorem mul_succ (a b : Ordinal) : a * succ b = a * b + a :=
mul_add_one a b
#align ordinal.mul_succ Ordinal.mul_succ
instance mul_covariantClass_le : CovariantClass Ordinal.{u} Ordinal.{u} (· * ·) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : α × γ => (f a.1, a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ (f.toRelEmbedding.map_rel_iff.2 h')
· exact Prod.Lex.right _ h'⟩
#align ordinal.mul_covariant_class_le Ordinal.mul_covariantClass_le
instance mul_swap_covariantClass_le :
CovariantClass Ordinal.{u} Ordinal.{u} (swap (· * ·)) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : γ × α => (a.1, f a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ h'
· exact Prod.Lex.right _ (f.toRelEmbedding.map_rel_iff.2 h')⟩
#align ordinal.mul_swap_covariant_class_le Ordinal.mul_swap_covariantClass_le
theorem le_mul_left (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ a * b := by
convert mul_le_mul_left' (one_le_iff_pos.2 hb) a
rw [mul_one a]
#align ordinal.le_mul_left Ordinal.le_mul_left
theorem le_mul_right (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ b * a := by
convert mul_le_mul_right' (one_le_iff_pos.2 hb) a
rw [one_mul a]
#align ordinal.le_mul_right Ordinal.le_mul_right
private theorem mul_le_of_limit_aux {α β r s} [IsWellOrder α r] [IsWellOrder β s] {c}
(h : IsLimit (type s)) (H : ∀ b' < type s, type r * b' ≤ c) (l : c < type r * type s) :
False := by
suffices ∀ a b, Prod.Lex s r (b, a) (enum _ _ l) by
cases' enum _ _ l with b a
exact irrefl _ (this _ _)
intro a b
rw [← typein_lt_typein (Prod.Lex s r), typein_enum]
have := H _ (h.2 _ (typein_lt_type s b))
rw [mul_succ] at this
have := ((add_lt_add_iff_left _).2 (typein_lt_type _ a)).trans_le this
refine (RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨⟨b', a'⟩, h⟩
by_cases e : b = b'
· refine Sum.inr ⟨a', ?_⟩
subst e
cases' h with _ _ _ _ h _ _ _ h
· exact (irrefl _ h).elim
· exact h
· refine Sum.inl (⟨b', ?_⟩, a')
cases' h with _ _ _ _ h _ _ _ h
· exact h
· exact (e rfl).elim
· rcases a with ⟨⟨b₁, a₁⟩, h₁⟩
rcases b with ⟨⟨b₂, a₂⟩, h₂⟩
intro h
by_cases e₁ : b = b₁ <;> by_cases e₂ : b = b₂
· substs b₁ b₂
simpa only [subrel_val, Prod.lex_def, @irrefl _ s _ b, true_and_iff, false_or_iff,
eq_self_iff_true, dif_pos, Sum.lex_inr_inr] using h
· subst b₁
simp only [subrel_val, Prod.lex_def, e₂, Prod.lex_def, dif_pos, subrel_val, eq_self_iff_true,
or_false_iff, dif_neg, not_false_iff, Sum.lex_inr_inl, false_and_iff] at h ⊢
cases' h₂ with _ _ _ _ h₂_h h₂_h <;> [exact asymm h h₂_h; exact e₂ rfl]
-- Porting note: `cc` hadn't ported yet.
· simp [e₂, dif_neg e₁, show b₂ ≠ b₁ from e₂ ▸ e₁]
· simpa only [dif_neg e₁, dif_neg e₂, Prod.lex_def, subrel_val, Subtype.mk_eq_mk,
Sum.lex_inl_inl] using h
theorem mul_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a * b ≤ c ↔ ∀ b' < b, a * b' ≤ c :=
⟨fun h b' l => (mul_le_mul_left' l.le _).trans h, fun H =>
-- Porting note: `induction` tactics are required because of the parser bug.
le_of_not_lt <| by
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
exact mul_le_of_limit_aux h H⟩
#align ordinal.mul_le_of_limit Ordinal.mul_le_of_limit
theorem mul_isNormal {a : Ordinal} (h : 0 < a) : IsNormal (a * ·) :=
-- Porting note(#12129): additional beta reduction needed
⟨fun b => by
beta_reduce
rw [mul_succ]
simpa only [add_zero] using (add_lt_add_iff_left (a * b)).2 h,
fun b l c => mul_le_of_limit l⟩
#align ordinal.mul_is_normal Ordinal.mul_isNormal
theorem lt_mul_of_limit {a b c : Ordinal} (h : IsLimit c) : a < b * c ↔ ∃ c' < c, a < b * c' := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@mul_le_of_limit b c a h)
#align ordinal.lt_mul_of_limit Ordinal.lt_mul_of_limit
theorem mul_lt_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b < a * c ↔ b < c :=
(mul_isNormal a0).lt_iff
#align ordinal.mul_lt_mul_iff_left Ordinal.mul_lt_mul_iff_left
theorem mul_le_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
(mul_isNormal a0).le_iff
#align ordinal.mul_le_mul_iff_left Ordinal.mul_le_mul_iff_left
theorem mul_lt_mul_of_pos_left {a b c : Ordinal} (h : a < b) (c0 : 0 < c) : c * a < c * b :=
(mul_lt_mul_iff_left c0).2 h
#align ordinal.mul_lt_mul_of_pos_left Ordinal.mul_lt_mul_of_pos_left
theorem mul_pos {a b : Ordinal} (h₁ : 0 < a) (h₂ : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left h₂ h₁
#align ordinal.mul_pos Ordinal.mul_pos
theorem mul_ne_zero {a b : Ordinal} : a ≠ 0 → b ≠ 0 → a * b ≠ 0 := by
simpa only [Ordinal.pos_iff_ne_zero] using mul_pos
#align ordinal.mul_ne_zero Ordinal.mul_ne_zero
theorem le_of_mul_le_mul_left {a b c : Ordinal} (h : c * a ≤ c * b) (h0 : 0 < c) : a ≤ b :=
le_imp_le_of_lt_imp_lt (fun h' => mul_lt_mul_of_pos_left h' h0) h
#align ordinal.le_of_mul_le_mul_left Ordinal.le_of_mul_le_mul_left
theorem mul_right_inj {a b c : Ordinal} (a0 : 0 < a) : a * b = a * c ↔ b = c :=
(mul_isNormal a0).inj
#align ordinal.mul_right_inj Ordinal.mul_right_inj
theorem mul_isLimit {a b : Ordinal} (a0 : 0 < a) : IsLimit b → IsLimit (a * b) :=
(mul_isNormal a0).isLimit
#align ordinal.mul_is_limit Ordinal.mul_isLimit
theorem mul_isLimit_left {a b : Ordinal} (l : IsLimit a) (b0 : 0 < b) : IsLimit (a * b) := by
rcases zero_or_succ_or_limit b with (rfl | ⟨b, rfl⟩ | lb)
· exact b0.false.elim
· rw [mul_succ]
exact add_isLimit _ l
· exact mul_isLimit l.pos lb
#align ordinal.mul_is_limit_left Ordinal.mul_isLimit_left
theorem smul_eq_mul : ∀ (n : ℕ) (a : Ordinal), n • a = a * n
| 0, a => by rw [zero_nsmul, Nat.cast_zero, mul_zero]
| n + 1, a => by rw [succ_nsmul, Nat.cast_add, mul_add, Nat.cast_one, mul_one, smul_eq_mul n]
#align ordinal.smul_eq_mul Ordinal.smul_eq_mul
/-! ### Division on ordinals -/
/-- The set in the definition of division is nonempty. -/
theorem div_nonempty {a b : Ordinal} (h : b ≠ 0) : { o | a < b * succ o }.Nonempty :=
⟨a, (succ_le_iff (a := a) (b := b * succ a)).1 <| by
simpa only [succ_zero, one_mul] using
mul_le_mul_right' (succ_le_of_lt (Ordinal.pos_iff_ne_zero.2 h)) (succ a)⟩
#align ordinal.div_nonempty Ordinal.div_nonempty
/-- `a / b` is the unique ordinal `o` satisfying `a = b * o + o'` with `o' < b`. -/
instance div : Div Ordinal :=
⟨fun a b => if _h : b = 0 then 0 else sInf { o | a < b * succ o }⟩
@[simp]
theorem div_zero (a : Ordinal) : a / 0 = 0 :=
dif_pos rfl
#align ordinal.div_zero Ordinal.div_zero
theorem div_def (a) {b : Ordinal} (h : b ≠ 0) : a / b = sInf { o | a < b * succ o } :=
dif_neg h
#align ordinal.div_def Ordinal.div_def
theorem lt_mul_succ_div (a) {b : Ordinal} (h : b ≠ 0) : a < b * succ (a / b) := by
rw [div_def a h]; exact csInf_mem (div_nonempty h)
#align ordinal.lt_mul_succ_div Ordinal.lt_mul_succ_div
theorem lt_mul_div_add (a) {b : Ordinal} (h : b ≠ 0) : a < b * (a / b) + b := by
simpa only [mul_succ] using lt_mul_succ_div a h
#align ordinal.lt_mul_div_add Ordinal.lt_mul_div_add
theorem div_le {a b c : Ordinal} (b0 : b ≠ 0) : a / b ≤ c ↔ a < b * succ c :=
⟨fun h => (lt_mul_succ_div a b0).trans_le (mul_le_mul_left' (succ_le_succ_iff.2 h) _), fun h => by
rw [div_def a b0]; exact csInf_le' h⟩
#align ordinal.div_le Ordinal.div_le
theorem lt_div {a b c : Ordinal} (h : c ≠ 0) : a < b / c ↔ c * succ a ≤ b := by
rw [← not_le, div_le h, not_lt]
#align ordinal.lt_div Ordinal.lt_div
theorem div_pos {b c : Ordinal} (h : c ≠ 0) : 0 < b / c ↔ c ≤ b := by simp [lt_div h]
#align ordinal.div_pos Ordinal.div_pos
theorem le_div {a b c : Ordinal} (c0 : c ≠ 0) : a ≤ b / c ↔ c * a ≤ b := by
induction a using limitRecOn with
| H₁ => simp only [mul_zero, Ordinal.zero_le]
| H₂ _ _ => rw [succ_le_iff, lt_div c0]
| H₃ _ h₁ h₂ =>
revert h₁ h₂
simp (config := { contextual := true }) only [mul_le_of_limit, limit_le, iff_self_iff,
forall_true_iff]
#align ordinal.le_div Ordinal.le_div
theorem div_lt {a b c : Ordinal} (b0 : b ≠ 0) : a / b < c ↔ a < b * c :=
lt_iff_lt_of_le_iff_le <| le_div b0
#align ordinal.div_lt Ordinal.div_lt
theorem div_le_of_le_mul {a b c : Ordinal} (h : a ≤ b * c) : a / b ≤ c :=
if b0 : b = 0 then by simp only [b0, div_zero, Ordinal.zero_le]
else
(div_le b0).2 <| h.trans_lt <| mul_lt_mul_of_pos_left (lt_succ c) (Ordinal.pos_iff_ne_zero.2 b0)
#align ordinal.div_le_of_le_mul Ordinal.div_le_of_le_mul
theorem mul_lt_of_lt_div {a b c : Ordinal} : a < b / c → c * a < b :=
lt_imp_lt_of_le_imp_le div_le_of_le_mul
#align ordinal.mul_lt_of_lt_div Ordinal.mul_lt_of_lt_div
@[simp]
theorem zero_div (a : Ordinal) : 0 / a = 0 :=
Ordinal.le_zero.1 <| div_le_of_le_mul <| Ordinal.zero_le _
#align ordinal.zero_div Ordinal.zero_div
theorem mul_div_le (a b : Ordinal) : b * (a / b) ≤ a :=
if b0 : b = 0 then by simp only [b0, zero_mul, Ordinal.zero_le] else (le_div b0).1 le_rfl
#align ordinal.mul_div_le Ordinal.mul_div_le
theorem mul_add_div (a) {b : Ordinal} (b0 : b ≠ 0) (c) : (b * a + c) / b = a + c / b := by
apply le_antisymm
· apply (div_le b0).2
rw [mul_succ, mul_add, add_assoc, add_lt_add_iff_left]
apply lt_mul_div_add _ b0
· rw [le_div b0, mul_add, add_le_add_iff_left]
apply mul_div_le
#align ordinal.mul_add_div Ordinal.mul_add_div
theorem div_eq_zero_of_lt {a b : Ordinal} (h : a < b) : a / b = 0 := by
rw [← Ordinal.le_zero, div_le <| Ordinal.pos_iff_ne_zero.1 <| (Ordinal.zero_le _).trans_lt h]
simpa only [succ_zero, mul_one] using h
#align ordinal.div_eq_zero_of_lt Ordinal.div_eq_zero_of_lt
@[simp]
theorem mul_div_cancel (a) {b : Ordinal} (b0 : b ≠ 0) : b * a / b = a := by
simpa only [add_zero, zero_div] using mul_add_div a b0 0
#align ordinal.mul_div_cancel Ordinal.mul_div_cancel
@[simp]
theorem div_one (a : Ordinal) : a / 1 = a := by
simpa only [one_mul] using mul_div_cancel a Ordinal.one_ne_zero
#align ordinal.div_one Ordinal.div_one
@[simp]
theorem div_self {a : Ordinal} (h : a ≠ 0) : a / a = 1 := by
simpa only [mul_one] using mul_div_cancel 1 h
#align ordinal.div_self Ordinal.div_self
theorem mul_sub (a b c : Ordinal) : a * (b - c) = a * b - a * c :=
if a0 : a = 0 then by simp only [a0, zero_mul, sub_self]
else
eq_of_forall_ge_iff fun d => by rw [sub_le, ← le_div a0, sub_le, ← le_div a0, mul_add_div _ a0]
#align ordinal.mul_sub Ordinal.mul_sub
theorem isLimit_add_iff {a b} : IsLimit (a + b) ↔ IsLimit b ∨ b = 0 ∧ IsLimit a := by
constructor <;> intro h
· by_cases h' : b = 0
· rw [h', add_zero] at h
right
exact ⟨h', h⟩
left
rw [← add_sub_cancel a b]
apply sub_isLimit h
suffices a + 0 < a + b by simpa only [add_zero] using this
rwa [add_lt_add_iff_left, Ordinal.pos_iff_ne_zero]
rcases h with (h | ⟨rfl, h⟩)
· exact add_isLimit a h
· simpa only [add_zero]
#align ordinal.is_limit_add_iff Ordinal.isLimit_add_iff
theorem dvd_add_iff : ∀ {a b c : Ordinal}, a ∣ b → (a ∣ b + c ↔ a ∣ c)
| a, _, c, ⟨b, rfl⟩ =>
⟨fun ⟨d, e⟩ => ⟨d - b, by rw [mul_sub, ← e, add_sub_cancel]⟩, fun ⟨d, e⟩ => by
rw [e, ← mul_add]
apply dvd_mul_right⟩
#align ordinal.dvd_add_iff Ordinal.dvd_add_iff
theorem div_mul_cancel : ∀ {a b : Ordinal}, a ≠ 0 → a ∣ b → a * (b / a) = b
| a, _, a0, ⟨b, rfl⟩ => by rw [mul_div_cancel _ a0]
#align ordinal.div_mul_cancel Ordinal.div_mul_cancel
theorem le_of_dvd : ∀ {a b : Ordinal}, b ≠ 0 → a ∣ b → a ≤ b
-- Porting note: `⟨b, rfl⟩ => by` → `⟨b, e⟩ => by subst e`
| a, _, b0, ⟨b, e⟩ => by
subst e
-- Porting note: `Ne` is required.
simpa only [mul_one] using
mul_le_mul_left'
(one_le_iff_ne_zero.2 fun h : b = 0 => by
simp only [h, mul_zero, Ne, not_true_eq_false] at b0) a
#align ordinal.le_of_dvd Ordinal.le_of_dvd
theorem dvd_antisymm {a b : Ordinal} (h₁ : a ∣ b) (h₂ : b ∣ a) : a = b :=
if a0 : a = 0 then by subst a; exact (eq_zero_of_zero_dvd h₁).symm
else
if b0 : b = 0 then by subst b; exact eq_zero_of_zero_dvd h₂
else (le_of_dvd b0 h₁).antisymm (le_of_dvd a0 h₂)
#align ordinal.dvd_antisymm Ordinal.dvd_antisymm
instance isAntisymm : IsAntisymm Ordinal (· ∣ ·) :=
⟨@dvd_antisymm⟩
/-- `a % b` is the unique ordinal `o'` satisfying
`a = b * o + o'` with `o' < b`. -/
instance mod : Mod Ordinal :=
⟨fun a b => a - b * (a / b)⟩
theorem mod_def (a b : Ordinal) : a % b = a - b * (a / b) :=
rfl
#align ordinal.mod_def Ordinal.mod_def
theorem mod_le (a b : Ordinal) : a % b ≤ a :=
sub_le_self a _
#align ordinal.mod_le Ordinal.mod_le
@[simp]
theorem mod_zero (a : Ordinal) : a % 0 = a := by simp only [mod_def, div_zero, zero_mul, sub_zero]
#align ordinal.mod_zero Ordinal.mod_zero
theorem mod_eq_of_lt {a b : Ordinal} (h : a < b) : a % b = a := by
simp only [mod_def, div_eq_zero_of_lt h, mul_zero, sub_zero]
#align ordinal.mod_eq_of_lt Ordinal.mod_eq_of_lt
@[simp]
theorem zero_mod (b : Ordinal) : 0 % b = 0 := by simp only [mod_def, zero_div, mul_zero, sub_self]
#align ordinal.zero_mod Ordinal.zero_mod
theorem div_add_mod (a b : Ordinal) : b * (a / b) + a % b = a :=
Ordinal.add_sub_cancel_of_le <| mul_div_le _ _
#align ordinal.div_add_mod Ordinal.div_add_mod
theorem mod_lt (a) {b : Ordinal} (h : b ≠ 0) : a % b < b :=
(add_lt_add_iff_left (b * (a / b))).1 <| by rw [div_add_mod]; exact lt_mul_div_add a h
#align ordinal.mod_lt Ordinal.mod_lt
@[simp]
theorem mod_self (a : Ordinal) : a % a = 0 :=
if a0 : a = 0 then by simp only [a0, zero_mod]
else by simp only [mod_def, div_self a0, mul_one, sub_self]
#align ordinal.mod_self Ordinal.mod_self
@[simp]
theorem mod_one (a : Ordinal) : a % 1 = 0 := by simp only [mod_def, div_one, one_mul, sub_self]
#align ordinal.mod_one Ordinal.mod_one
theorem dvd_of_mod_eq_zero {a b : Ordinal} (H : a % b = 0) : b ∣ a :=
⟨a / b, by simpa [H] using (div_add_mod a b).symm⟩
#align ordinal.dvd_of_mod_eq_zero Ordinal.dvd_of_mod_eq_zero
theorem mod_eq_zero_of_dvd {a b : Ordinal} (H : b ∣ a) : a % b = 0 := by
rcases H with ⟨c, rfl⟩
rcases eq_or_ne b 0 with (rfl | hb)
· simp
· simp [mod_def, hb]
#align ordinal.mod_eq_zero_of_dvd Ordinal.mod_eq_zero_of_dvd
theorem dvd_iff_mod_eq_zero {a b : Ordinal} : b ∣ a ↔ a % b = 0 :=
⟨mod_eq_zero_of_dvd, dvd_of_mod_eq_zero⟩
#align ordinal.dvd_iff_mod_eq_zero Ordinal.dvd_iff_mod_eq_zero
@[simp]
theorem mul_add_mod_self (x y z : Ordinal) : (x * y + z) % x = z % x := by
rcases eq_or_ne x 0 with rfl | hx
· simp
· rwa [mod_def, mul_add_div, mul_add, ← sub_sub, add_sub_cancel, mod_def]
#align ordinal.mul_add_mod_self Ordinal.mul_add_mod_self
@[simp]
theorem mul_mod (x y : Ordinal) : x * y % x = 0 := by
simpa using mul_add_mod_self x y 0
#align ordinal.mul_mod Ordinal.mul_mod
theorem mod_mod_of_dvd (a : Ordinal) {b c : Ordinal} (h : c ∣ b) : a % b % c = a % c := by
nth_rw 2 [← div_add_mod a b]
rcases h with ⟨d, rfl⟩
rw [mul_assoc, mul_add_mod_self]
#align ordinal.mod_mod_of_dvd Ordinal.mod_mod_of_dvd
@[simp]
theorem mod_mod (a b : Ordinal) : a % b % b = a % b :=
mod_mod_of_dvd a dvd_rfl
#align ordinal.mod_mod Ordinal.mod_mod
/-! ### Families of ordinals
There are two kinds of indexed families that naturally arise when dealing with ordinals: those
indexed by some type in the appropriate universe, and those indexed by ordinals less than another.
The following API allows one to convert from one kind of family to the other.
In many cases, this makes it easy to prove claims about one kind of family via the corresponding
claim on the other. -/
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a specified
well-ordering. -/
def bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
∀ a < type r, α := fun a ha => f (enum r a ha)
#align ordinal.bfamily_of_family' Ordinal.bfamilyOfFamily'
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a well-ordering
given by the axiom of choice. -/
def bfamilyOfFamily {ι : Type u} : (ι → α) → ∀ a < type (@WellOrderingRel ι), α :=
bfamilyOfFamily' WellOrderingRel
#align ordinal.bfamily_of_family Ordinal.bfamilyOfFamily
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a specified
well-ordering. -/
def familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, α) : ι → α := fun i =>
f (typein r i)
(by
rw [← ho]
exact typein_lt_type r i)
#align ordinal.family_of_bfamily' Ordinal.familyOfBFamily'
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a well-ordering
given by the axiom of choice. -/
def familyOfBFamily (o : Ordinal) (f : ∀ a < o, α) : o.out.α → α :=
familyOfBFamily' (· < ·) (type_lt o) f
#align ordinal.family_of_bfamily Ordinal.familyOfBFamily
@[simp]
theorem bfamilyOfFamily'_typein {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) (i) :
bfamilyOfFamily' r f (typein r i) (typein_lt_type r i) = f i := by
simp only [bfamilyOfFamily', enum_typein]
#align ordinal.bfamily_of_family'_typein Ordinal.bfamilyOfFamily'_typein
@[simp]
theorem bfamilyOfFamily_typein {ι} (f : ι → α) (i) :
bfamilyOfFamily f (typein _ i) (typein_lt_type _ i) = f i :=
bfamilyOfFamily'_typein _ f i
#align ordinal.bfamily_of_family_typein Ordinal.bfamilyOfFamily_typein
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily'_enum {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (i hi) :
familyOfBFamily' r ho f (enum r i (by rwa [ho])) = f i hi := by
simp only [familyOfBFamily', typein_enum]
#align ordinal.family_of_bfamily'_enum Ordinal.familyOfBFamily'_enum
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily_enum (o : Ordinal) (f : ∀ a < o, α) (i hi) :
familyOfBFamily o f
(enum (· < ·) i
(by
convert hi
exact type_lt _)) =
f i hi :=
familyOfBFamily'_enum _ (type_lt o) f _ _
#align ordinal.family_of_bfamily_enum Ordinal.familyOfBFamily_enum
/-- The range of a family indexed by ordinals. -/
def brange (o : Ordinal) (f : ∀ a < o, α) : Set α :=
{ a | ∃ i hi, f i hi = a }
#align ordinal.brange Ordinal.brange
theorem mem_brange {o : Ordinal} {f : ∀ a < o, α} {a} : a ∈ brange o f ↔ ∃ i hi, f i hi = a :=
Iff.rfl
#align ordinal.mem_brange Ordinal.mem_brange
theorem mem_brange_self {o} (f : ∀ a < o, α) (i hi) : f i hi ∈ brange o f :=
⟨i, hi, rfl⟩
#align ordinal.mem_brange_self Ordinal.mem_brange_self
@[simp]
theorem range_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) : range (familyOfBFamily' r ho f) = brange o f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨b, rfl⟩
apply mem_brange_self
· rintro ⟨i, hi, rfl⟩
exact ⟨_, familyOfBFamily'_enum _ _ _ _ _⟩
#align ordinal.range_family_of_bfamily' Ordinal.range_familyOfBFamily'
@[simp]
theorem range_familyOfBFamily {o} (f : ∀ a < o, α) : range (familyOfBFamily o f) = brange o f :=
range_familyOfBFamily' _ _ f
#align ordinal.range_family_of_bfamily Ordinal.range_familyOfBFamily
@[simp]
theorem brange_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
brange _ (bfamilyOfFamily' r f) = range f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨i, hi, rfl⟩
apply mem_range_self
· rintro ⟨b, rfl⟩
exact ⟨_, _, bfamilyOfFamily'_typein _ _ _⟩
#align ordinal.brange_bfamily_of_family' Ordinal.brange_bfamilyOfFamily'
@[simp]
theorem brange_bfamilyOfFamily {ι : Type u} (f : ι → α) : brange _ (bfamilyOfFamily f) = range f :=
brange_bfamilyOfFamily' _ _
#align ordinal.brange_bfamily_of_family Ordinal.brange_bfamilyOfFamily
@[simp]
theorem brange_const {o : Ordinal} (ho : o ≠ 0) {c : α} : (brange o fun _ _ => c) = {c} := by
rw [← range_familyOfBFamily]
exact @Set.range_const _ o.out.α (out_nonempty_iff_ne_zero.2 ho) c
#align ordinal.brange_const Ordinal.brange_const
theorem comp_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α)
(g : α → β) : (fun i hi => g (bfamilyOfFamily' r f i hi)) = bfamilyOfFamily' r (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family' Ordinal.comp_bfamilyOfFamily'
theorem comp_bfamilyOfFamily {ι : Type u} (f : ι → α) (g : α → β) :
(fun i hi => g (bfamilyOfFamily f i hi)) = bfamilyOfFamily (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family Ordinal.comp_bfamilyOfFamily
theorem comp_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily' r ho f = familyOfBFamily' r ho fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily' Ordinal.comp_familyOfBFamily'
theorem comp_familyOfBFamily {o} (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily o f = familyOfBFamily o fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily Ordinal.comp_familyOfBFamily
/-! ### Supremum of a family of ordinals -/
-- Porting note: Universes should be specified in `sup`s.
/-- The supremum of a family of ordinals -/
def sup {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal.{max u v} :=
iSup f
#align ordinal.sup Ordinal.sup
@[simp]
theorem sSup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : sSup (Set.range f) = sup.{_, v} f :=
rfl
#align ordinal.Sup_eq_sup Ordinal.sSup_eq_sup
/-- The range of an indexed ordinal function, whose outputs live in a higher universe than the
inputs, is always bounded above. See `Ordinal.lsub` for an explicit bound. -/
theorem bddAbove_range {ι : Type u} (f : ι → Ordinal.{max u v}) : BddAbove (Set.range f) :=
⟨(iSup (succ ∘ card ∘ f)).ord, by
rintro a ⟨i, rfl⟩
exact le_of_lt (Cardinal.lt_ord.2 ((lt_succ _).trans_le
(le_ciSup (Cardinal.bddAbove_range.{_, v} _) _)))⟩
#align ordinal.bdd_above_range Ordinal.bddAbove_range
theorem le_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : ∀ i, f i ≤ sup.{_, v} f := fun i =>
le_csSup (bddAbove_range.{_, v} f) (mem_range_self i)
#align ordinal.le_sup Ordinal.le_sup
theorem sup_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : sup.{_, v} f ≤ a ↔ ∀ i, f i ≤ a :=
(csSup_le_iff' (bddAbove_range.{_, v} f)).trans (by simp)
#align ordinal.sup_le_iff Ordinal.sup_le_iff
theorem sup_le {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : (∀ i, f i ≤ a) → sup.{_, v} f ≤ a :=
sup_le_iff.2
#align ordinal.sup_le Ordinal.sup_le
theorem lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : a < sup.{_, v} f ↔ ∃ i, a < f i := by
simpa only [not_forall, not_le] using not_congr (@sup_le_iff.{_, v} _ f a)
#align ordinal.lt_sup Ordinal.lt_sup
theorem ne_sup_iff_lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} :
(∀ i, f i ≠ sup.{_, v} f) ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun hf _ => lt_of_le_of_ne (le_sup _ _) (hf _), fun hf _ => ne_of_lt (hf _)⟩
#align ordinal.ne_sup_iff_lt_sup Ordinal.ne_sup_iff_lt_sup
theorem sup_not_succ_of_ne_sup {ι : Type u} {f : ι → Ordinal.{max u v}}
(hf : ∀ i, f i ≠ sup.{_, v} f) {a} (hao : a < sup.{_, v} f) : succ a < sup.{_, v} f := by
by_contra! hoa
exact
hao.not_le (sup_le fun i => le_of_lt_succ <| (lt_of_le_of_ne (le_sup _ _) (hf i)).trans_le hoa)
#align ordinal.sup_not_succ_of_ne_sup Ordinal.sup_not_succ_of_ne_sup
@[simp]
theorem sup_eq_zero_iff {ι : Type u} {f : ι → Ordinal.{max u v}} :
sup.{_, v} f = 0 ↔ ∀ i, f i = 0 := by
refine
⟨fun h i => ?_, fun h =>
le_antisymm (sup_le fun i => Ordinal.le_zero.2 (h i)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_sup f i
#align ordinal.sup_eq_zero_iff Ordinal.sup_eq_zero_iff
theorem IsNormal.sup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f) {ι : Type u}
(g : ι → Ordinal.{max u v}) [Nonempty ι] : f (sup.{_, v} g) = sup.{_, w} (f ∘ g) :=
eq_of_forall_ge_iff fun a => by
rw [sup_le_iff]; simp only [comp]; rw [H.le_set' Set.univ Set.univ_nonempty g] <;>
simp [sup_le_iff]
#align ordinal.is_normal.sup Ordinal.IsNormal.sup
@[simp]
theorem sup_empty {ι} [IsEmpty ι] (f : ι → Ordinal) : sup f = 0 :=
ciSup_of_empty f
#align ordinal.sup_empty Ordinal.sup_empty
@[simp]
theorem sup_const {ι} [_hι : Nonempty ι] (o : Ordinal) : (sup fun _ : ι => o) = o :=
ciSup_const
#align ordinal.sup_const Ordinal.sup_const
@[simp]
theorem sup_unique {ι} [Unique ι] (f : ι → Ordinal) : sup f = f default :=
ciSup_unique
#align ordinal.sup_unique Ordinal.sup_unique
theorem sup_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : sup.{u, max v w} f ≤ sup.{v, max u w} g :=
sup_le fun i =>
match h (mem_range_self i) with
| ⟨_j, hj⟩ => hj ▸ le_sup _ _
#align ordinal.sup_le_of_range_subset Ordinal.sup_le_of_range_subset
theorem sup_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : sup.{u, max v w} f = sup.{v, max u w} g :=
(sup_le_of_range_subset.{u, v, w} h.le).antisymm (sup_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.sup_eq_of_range_eq Ordinal.sup_eq_of_range_eq
@[simp]
theorem sup_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
sup.{max u v, w} f =
max (sup.{u, max v w} fun a => f (Sum.inl a)) (sup.{v, max u w} fun b => f (Sum.inr b)) := by
apply (sup_le_iff.2 _).antisymm (max_le_iff.2 ⟨_, _⟩)
· rintro (i | i)
· exact le_max_of_le_left (le_sup _ i)
· exact le_max_of_le_right (le_sup _ i)
all_goals
apply sup_le_of_range_subset.{_, max u v, w}
rintro i ⟨a, rfl⟩
apply mem_range_self
#align ordinal.sup_sum Ordinal.sup_sum
theorem unbounded_range_of_sup_ge {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β → α)
(h : type r ≤ sup.{u, u} (typein r ∘ f)) : Unbounded r (range f) :=
(not_bounded_iff _).1 fun ⟨x, hx⟩ =>
not_lt_of_le h <|
lt_of_le_of_lt
(sup_le fun y => le_of_lt <| (typein_lt_typein r).2 <| hx _ <| mem_range_self y)
(typein_lt_type r x)
#align ordinal.unbounded_range_of_sup_ge Ordinal.unbounded_range_of_sup_ge
theorem le_sup_shrink_equiv {s : Set Ordinal.{u}} (hs : Small.{u} s) (a) (ha : a ∈ s) :
a ≤ sup.{u, u} fun x => ((@equivShrink s hs).symm x).val := by
convert le_sup.{u, u} (fun x => ((@equivShrink s hs).symm x).val) ((@equivShrink s hs) ⟨a, ha⟩)
rw [symm_apply_apply]
#align ordinal.le_sup_shrink_equiv Ordinal.le_sup_shrink_equiv
instance small_Iio (o : Ordinal.{u}) : Small.{u} (Set.Iio o) :=
let f : o.out.α → Set.Iio o :=
fun x => ⟨typein ((· < ·) : o.out.α → o.out.α → Prop) x, typein_lt_self x⟩
let hf : Surjective f := fun b =>
⟨enum (· < ·) b.val
(by
rw [type_lt]
exact b.prop),
Subtype.ext (typein_enum _ _)⟩
small_of_surjective hf
#align ordinal.small_Iio Ordinal.small_Iio
instance small_Iic (o : Ordinal.{u}) : Small.{u} (Set.Iic o) := by
rw [← Iio_succ]
infer_instance
#align ordinal.small_Iic Ordinal.small_Iic
theorem bddAbove_iff_small {s : Set Ordinal.{u}} : BddAbove s ↔ Small.{u} s :=
⟨fun ⟨a, h⟩ => small_subset <| show s ⊆ Iic a from fun _x hx => h hx, fun h =>
⟨sup.{u, u} fun x => ((@equivShrink s h).symm x).val, le_sup_shrink_equiv h⟩⟩
#align ordinal.bdd_above_iff_small Ordinal.bddAbove_iff_small
theorem bddAbove_of_small (s : Set Ordinal.{u}) [h : Small.{u} s] : BddAbove s :=
bddAbove_iff_small.2 h
#align ordinal.bdd_above_of_small Ordinal.bddAbove_of_small
theorem sup_eq_sSup {s : Set Ordinal.{u}} (hs : Small.{u} s) :
(sup.{u, u} fun x => (@equivShrink s hs).symm x) = sSup s :=
let hs' := bddAbove_iff_small.2 hs
((csSup_le_iff' hs').2 (le_sup_shrink_equiv hs)).antisymm'
(sup_le fun _x => le_csSup hs' (Subtype.mem _))
#align ordinal.sup_eq_Sup Ordinal.sup_eq_sSup
theorem sSup_ord {s : Set Cardinal.{u}} (hs : BddAbove s) : (sSup s).ord = sSup (ord '' s) :=
eq_of_forall_ge_iff fun a => by
rw [csSup_le_iff'
(bddAbove_iff_small.2 (@small_image _ _ _ s (Cardinal.bddAbove_iff_small.1 hs))),
ord_le, csSup_le_iff' hs]
simp [ord_le]
#align ordinal.Sup_ord Ordinal.sSup_ord
theorem iSup_ord {ι} {f : ι → Cardinal} (hf : BddAbove (range f)) :
(iSup f).ord = ⨆ i, (f i).ord := by
unfold iSup
convert sSup_ord hf
-- Porting note: `change` is required.
conv_lhs => change range (ord ∘ f)
rw [range_comp]
#align ordinal.supr_ord Ordinal.iSup_ord
private theorem sup_le_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop)
[IsWellOrder ι r] [IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) ≤ sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_le fun i => by
cases'
typein_surj r'
(by
rw [ho', ← ho]
exact typein_lt_type r i) with
j hj
simp_rw [familyOfBFamily', ← hj]
apply le_sup
theorem sup_eq_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o : Ordinal.{u}} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) = sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_eq_of_range_eq.{u, u, v} (by simp)
#align ordinal.sup_eq_sup Ordinal.sup_eq_sup
/-- The supremum of a family of ordinals indexed by the set of ordinals less than some
`o : Ordinal.{u}`. This is a special case of `sup` over the family provided by
`familyOfBFamily`. -/
def bsup (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
sup.{_, v} (familyOfBFamily o f)
#align ordinal.bsup Ordinal.bsup
@[simp]
theorem sup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily o f) = bsup.{_, v} o f :=
rfl
#align ordinal.sup_eq_bsup Ordinal.sup_eq_bsup
@[simp]
theorem sup_eq_bsup' {o : Ordinal.{u}} {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : sup.{_, v} (familyOfBFamily' r ho f) = bsup.{_, v} o f :=
sup_eq_sup r _ ho _ f
#align ordinal.sup_eq_bsup' Ordinal.sup_eq_bsup'
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem sSup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sSup (brange o f) = bsup.{_, v} o f := by
congr
rw [range_familyOfBFamily]
#align ordinal.Sup_eq_bsup Ordinal.sSup_eq_bsup
@[simp]
theorem bsup_eq_sup' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = sup.{_, v} f := by
simp (config := { unfoldPartialApp := true }) only [← sup_eq_bsup' r, enum_typein,
familyOfBFamily', bfamilyOfFamily']
#align ordinal.bsup_eq_sup' Ordinal.bsup_eq_sup'
theorem bsup_eq_bsup {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = bsup.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [bsup_eq_sup', bsup_eq_sup']
#align ordinal.bsup_eq_bsup Ordinal.bsup_eq_bsup
@[simp]
theorem bsup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily f) = sup.{_, v} f :=
bsup_eq_sup' _ f
#align ordinal.bsup_eq_sup Ordinal.bsup_eq_sup
@[congr]
theorem bsup_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
bsup.{_, v} o₁ f = bsup.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.bsup_congr Ordinal.bsup_congr
theorem bsup_le_iff {o f a} : bsup.{u, v} o f ≤ a ↔ ∀ i h, f i h ≤ a :=
sup_le_iff.trans
⟨fun h i hi => by
rw [← familyOfBFamily_enum o f]
exact h _, fun h i => h _ _⟩
#align ordinal.bsup_le_iff Ordinal.bsup_le_iff
theorem bsup_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} :
(∀ i h, f i h ≤ a) → bsup.{u, v} o f ≤ a :=
bsup_le_iff.2
#align ordinal.bsup_le Ordinal.bsup_le
theorem le_bsup {o} (f : ∀ a < o, Ordinal) (i h) : f i h ≤ bsup o f :=
bsup_le_iff.1 le_rfl _ _
#align ordinal.le_bsup Ordinal.le_bsup
theorem lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) {a} :
a < bsup.{_, v} o f ↔ ∃ i hi, a < f i hi := by
simpa only [not_forall, not_le] using not_congr (@bsup_le_iff.{_, v} _ f a)
#align ordinal.lt_bsup Ordinal.lt_bsup
theorem IsNormal.bsup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f)
{o : Ordinal.{u}} :
∀ (g : ∀ a < o, Ordinal), o ≠ 0 → f (bsup.{_, v} o g) = bsup.{_, w} o fun a h => f (g a h) :=
inductionOn o fun α r _ g h => by
haveI := type_ne_zero_iff_nonempty.1 h
rw [← sup_eq_bsup' r, IsNormal.sup.{_, v, w} H, ← sup_eq_bsup' r] <;> rfl
#align ordinal.is_normal.bsup Ordinal.IsNormal.bsup
theorem lt_bsup_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} :
(∀ i h, f i h ≠ bsup.{_, v} o f) ↔ ∀ i h, f i h < bsup.{_, v} o f :=
⟨fun hf _ _ => lt_of_le_of_ne (le_bsup _ _ _) (hf _ _), fun hf _ _ => ne_of_lt (hf _ _)⟩
#align ordinal.lt_bsup_of_ne_bsup Ordinal.lt_bsup_of_ne_bsup
theorem bsup_not_succ_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}}
(hf : ∀ {i : Ordinal} (h : i < o), f i h ≠ bsup.{_, v} o f) (a) :
a < bsup.{_, v} o f → succ a < bsup.{_, v} o f := by
rw [← sup_eq_bsup] at *
exact sup_not_succ_of_ne_sup fun i => hf _
#align ordinal.bsup_not_succ_of_ne_bsup Ordinal.bsup_not_succ_of_ne_bsup
@[simp]
theorem bsup_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : bsup o f = 0 ↔ ∀ i hi, f i hi = 0 := by
refine
⟨fun h i hi => ?_, fun h =>
le_antisymm (bsup_le fun i hi => Ordinal.le_zero.2 (h i hi)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_bsup f i hi
#align ordinal.bsup_eq_zero_iff Ordinal.bsup_eq_zero_iff
theorem lt_bsup_of_limit {o : Ordinal} {f : ∀ a < o, Ordinal}
(hf : ∀ {a a'} (ha : a < o) (ha' : a' < o), a < a' → f a ha < f a' ha')
(ho : ∀ a < o, succ a < o) (i h) : f i h < bsup o f :=
(hf _ _ <| lt_succ i).trans_le (le_bsup f (succ i) <| ho _ h)
#align ordinal.lt_bsup_of_limit Ordinal.lt_bsup_of_limit
theorem bsup_succ_of_mono {o : Ordinal} {f : ∀ a < succ o, Ordinal}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : bsup _ f = f o (lt_succ o) :=
le_antisymm (bsup_le fun _i hi => hf _ _ <| le_of_lt_succ hi) (le_bsup _ _ _)
#align ordinal.bsup_succ_of_mono Ordinal.bsup_succ_of_mono
@[simp]
theorem bsup_zero (f : ∀ a < (0 : Ordinal), Ordinal) : bsup 0 f = 0 :=
bsup_eq_zero_iff.2 fun i hi => (Ordinal.not_lt_zero i hi).elim
#align ordinal.bsup_zero Ordinal.bsup_zero
theorem bsup_const {o : Ordinal.{u}} (ho : o ≠ 0) (a : Ordinal.{max u v}) :
(bsup.{_, v} o fun _ _ => a) = a :=
le_antisymm (bsup_le fun _ _ => le_rfl) (le_bsup _ 0 (Ordinal.pos_iff_ne_zero.2 ho))
#align ordinal.bsup_const Ordinal.bsup_const
@[simp]
theorem bsup_one (f : ∀ a < (1 : Ordinal), Ordinal) : bsup 1 f = f 0 zero_lt_one := by
simp_rw [← sup_eq_bsup, sup_unique, familyOfBFamily, familyOfBFamily', typein_one_out]
#align ordinal.bsup_one Ordinal.bsup_one
theorem bsup_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : bsup.{u, max v w} o f ≤ bsup.{v, max u w} o' g :=
bsup_le fun i hi => by
obtain ⟨j, hj, hj'⟩ := h ⟨i, hi, rfl⟩
rw [← hj']
apply le_bsup
#align ordinal.bsup_le_of_brange_subset Ordinal.bsup_le_of_brange_subset
theorem bsup_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f = brange o' g) : bsup.{u, max v w} o f = bsup.{v, max u w} o' g :=
(bsup_le_of_brange_subset.{u, v, w} h.le).antisymm (bsup_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.bsup_eq_of_brange_eq Ordinal.bsup_eq_of_brange_eq
/-- The least strict upper bound of a family of ordinals. -/
def lsub {ι} (f : ι → Ordinal) : Ordinal :=
sup (succ ∘ f)
#align ordinal.lsub Ordinal.lsub
@[simp]
theorem sup_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} (succ ∘ f) = lsub.{_, v} f :=
rfl
#align ordinal.sup_eq_lsub Ordinal.sup_eq_lsub
theorem lsub_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
lsub.{_, v} f ≤ a ↔ ∀ i, f i < a := by
convert sup_le_iff.{_, v} (f := succ ∘ f) (a := a) using 2
-- Porting note: `comp_apply` is required.
simp only [comp_apply, succ_le_iff]
#align ordinal.lsub_le_iff Ordinal.lsub_le_iff
theorem lsub_le {ι} {f : ι → Ordinal} {a} : (∀ i, f i < a) → lsub f ≤ a :=
lsub_le_iff.2
#align ordinal.lsub_le Ordinal.lsub_le
theorem lt_lsub {ι} (f : ι → Ordinal) (i) : f i < lsub f :=
succ_le_iff.1 (le_sup _ i)
#align ordinal.lt_lsub Ordinal.lt_lsub
theorem lt_lsub_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
a < lsub.{_, v} f ↔ ∃ i, a ≤ f i := by
simpa only [not_forall, not_lt, not_le] using not_congr (@lsub_le_iff.{_, v} _ f a)
#align ordinal.lt_lsub_iff Ordinal.lt_lsub_iff
theorem sup_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) : sup.{_, v} f ≤ lsub.{_, v} f :=
sup_le fun i => (lt_lsub f i).le
#align ordinal.sup_le_lsub Ordinal.sup_le_lsub
theorem lsub_le_sup_succ {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f ≤ succ (sup.{_, v} f) :=
lsub_le fun i => lt_succ_iff.2 (le_sup f i)
#align ordinal.lsub_le_sup_succ Ordinal.lsub_le_sup_succ
theorem sup_eq_lsub_or_sup_succ_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ∨ succ (sup.{_, v} f) = lsub.{_, v} f := by
cases' eq_or_lt_of_le (sup_le_lsub.{_, v} f) with h h
· exact Or.inl h
· exact Or.inr ((succ_le_of_lt h).antisymm (lsub_le_sup_succ f))
#align ordinal.sup_eq_lsub_or_sup_succ_eq_lsub Ordinal.sup_eq_lsub_or_sup_succ_eq_lsub
theorem sup_succ_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
succ (sup.{_, v} f) ≤ lsub.{_, v} f ↔ ∃ i, f i = sup.{_, v} f := by
refine ⟨fun h => ?_, ?_⟩
· by_contra! hf
exact (succ_le_iff.1 h).ne ((sup_le_lsub f).antisymm (lsub_le (ne_sup_iff_lt_sup.1 hf)))
rintro ⟨_, hf⟩
rw [succ_le_iff, ← hf]
exact lt_lsub _ _
#align ordinal.sup_succ_le_lsub Ordinal.sup_succ_le_lsub
theorem sup_succ_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
succ (sup.{_, v} f) = lsub.{_, v} f ↔ ∃ i, f i = sup.{_, v} f :=
(lsub_le_sup_succ f).le_iff_eq.symm.trans (sup_succ_le_lsub f)
#align ordinal.sup_succ_eq_lsub Ordinal.sup_succ_eq_lsub
theorem sup_eq_lsub_iff_succ {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ↔ ∀ a < lsub.{_, v} f, succ a < lsub.{_, v} f := by
refine ⟨fun h => ?_, fun hf => le_antisymm (sup_le_lsub f) (lsub_le fun i => ?_)⟩
· rw [← h]
exact fun a => sup_not_succ_of_ne_sup fun i => (lsub_le_iff.1 (le_of_eq h.symm) i).ne
by_contra! hle
have heq := (sup_succ_eq_lsub f).2 ⟨i, le_antisymm (le_sup _ _) hle⟩
have :=
hf _
(by
rw [← heq]
exact lt_succ (sup f))
rw [heq] at this
exact this.false
#align ordinal.sup_eq_lsub_iff_succ Ordinal.sup_eq_lsub_iff_succ
theorem sup_eq_lsub_iff_lt_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun h i => by
rw [h]
apply lt_lsub, fun h => le_antisymm (sup_le_lsub f) (lsub_le h)⟩
#align ordinal.sup_eq_lsub_iff_lt_sup Ordinal.sup_eq_lsub_iff_lt_sup
@[simp]
theorem lsub_empty {ι} [h : IsEmpty ι] (f : ι → Ordinal) : lsub f = 0 := by
rw [← Ordinal.le_zero, lsub_le_iff]
exact h.elim
#align ordinal.lsub_empty Ordinal.lsub_empty
theorem lsub_pos {ι : Type u} [h : Nonempty ι] (f : ι → Ordinal.{max u v}) : 0 < lsub.{_, v} f :=
h.elim fun i => (Ordinal.zero_le _).trans_lt (lt_lsub f i)
#align ordinal.lsub_pos Ordinal.lsub_pos
@[simp]
theorem lsub_eq_zero_iff {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f = 0 ↔ IsEmpty ι := by
refine ⟨fun h => ⟨fun i => ?_⟩, fun h => @lsub_empty _ h _⟩
have := @lsub_pos.{_, v} _ ⟨i⟩ f
rw [h] at this
exact this.false
#align ordinal.lsub_eq_zero_iff Ordinal.lsub_eq_zero_iff
@[simp]
theorem lsub_const {ι} [Nonempty ι] (o : Ordinal) : (lsub fun _ : ι => o) = succ o :=
sup_const (succ o)
#align ordinal.lsub_const Ordinal.lsub_const
@[simp]
theorem lsub_unique {ι} [Unique ι] (f : ι → Ordinal) : lsub f = succ (f default) :=
sup_unique _
#align ordinal.lsub_unique Ordinal.lsub_unique
theorem lsub_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : lsub.{u, max v w} f ≤ lsub.{v, max u w} g :=
sup_le_of_range_subset.{u, v, w} (by convert Set.image_subset succ h <;> apply Set.range_comp)
#align ordinal.lsub_le_of_range_subset Ordinal.lsub_le_of_range_subset
theorem lsub_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : lsub.{u, max v w} f = lsub.{v, max u w} g :=
(lsub_le_of_range_subset.{u, v, w} h.le).antisymm (lsub_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.lsub_eq_of_range_eq Ordinal.lsub_eq_of_range_eq
@[simp]
theorem lsub_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
lsub.{max u v, w} f =
max (lsub.{u, max v w} fun a => f (Sum.inl a)) (lsub.{v, max u w} fun b => f (Sum.inr b)) :=
sup_sum _
#align ordinal.lsub_sum Ordinal.lsub_sum
theorem lsub_not_mem_range {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f ∉ Set.range f := fun ⟨i, h⟩ =>
h.not_lt (lt_lsub f i)
#align ordinal.lsub_not_mem_range Ordinal.lsub_not_mem_range
theorem nonempty_compl_range {ι : Type u} (f : ι → Ordinal.{max u v}) : (Set.range f)ᶜ.Nonempty :=
⟨_, lsub_not_mem_range.{_, v} f⟩
#align ordinal.nonempty_compl_range Ordinal.nonempty_compl_range
@[simp]
theorem lsub_typein (o : Ordinal) : lsub.{u, u} (typein ((· < ·) : o.out.α → o.out.α → Prop)) = o :=
(lsub_le.{u, u} typein_lt_self).antisymm
(by
by_contra! h
-- Porting note: `nth_rw` → `conv_rhs` & `rw`
conv_rhs at h => rw [← type_lt o]
simpa [typein_enum] using lt_lsub.{u, u} (typein (· < ·)) (enum (· < ·) _ h))
#align ordinal.lsub_typein Ordinal.lsub_typein
theorem sup_typein_limit {o : Ordinal} (ho : ∀ a, a < o → succ a < o) :
sup.{u, u} (typein ((· < ·) : o.out.α → o.out.α → Prop)) = o := by
-- Porting note: `rwa` → `rw` & `assumption`
rw [(sup_eq_lsub_iff_succ.{u, u} (typein (· < ·))).2] <;> rw [lsub_typein o]; assumption
#align ordinal.sup_typein_limit Ordinal.sup_typein_limit
@[simp]
theorem sup_typein_succ {o : Ordinal} :
sup.{u, u} (typein ((· < ·) : (succ o).out.α → (succ o).out.α → Prop)) = o := by
cases'
sup_eq_lsub_or_sup_succ_eq_lsub.{u, u}
(typein ((· < ·) : (succ o).out.α → (succ o).out.α → Prop)) with
h h
· rw [sup_eq_lsub_iff_succ] at h
simp only [lsub_typein] at h
exact (h o (lt_succ o)).false.elim
rw [← succ_eq_succ_iff, h]
apply lsub_typein
#align ordinal.sup_typein_succ Ordinal.sup_typein_succ
/-- The least strict upper bound of a family of ordinals indexed by the set of ordinals less than
some `o : Ordinal.{u}`.
This is to `lsub` as `bsup` is to `sup`. -/
def blsub (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
bsup.{_, v} o fun a ha => succ (f a ha)
#align ordinal.blsub Ordinal.blsub
@[simp]
theorem bsup_eq_blsub (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) :
(bsup.{_, v} o fun a ha => succ (f a ha)) = blsub.{_, v} o f :=
rfl
#align ordinal.bsup_eq_blsub Ordinal.bsup_eq_blsub
theorem lsub_eq_blsub' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : lsub.{_, v} (familyOfBFamily' r ho f) = blsub.{_, v} o f :=
sup_eq_bsup'.{_, v} r ho fun a ha => succ (f a ha)
#align ordinal.lsub_eq_blsub' Ordinal.lsub_eq_blsub'
theorem lsub_eq_lsub {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
lsub.{_, v} (familyOfBFamily' r ho f) = lsub.{_, v} (familyOfBFamily' r' ho' f) := by
rw [lsub_eq_blsub', lsub_eq_blsub']
#align ordinal.lsub_eq_lsub Ordinal.lsub_eq_lsub
@[simp]
theorem lsub_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
lsub.{_, v} (familyOfBFamily o f) = blsub.{_, v} o f :=
lsub_eq_blsub' _ _ _
#align ordinal.lsub_eq_blsub Ordinal.lsub_eq_blsub
@[simp]
theorem blsub_eq_lsub' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r]
(f : ι → Ordinal.{max u v}) : blsub.{_, v} _ (bfamilyOfFamily' r f) = lsub.{_, v} f :=
bsup_eq_sup'.{_, v} r (succ ∘ f)
#align ordinal.blsub_eq_lsub' Ordinal.blsub_eq_lsub'
theorem blsub_eq_blsub {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
blsub.{_, v} _ (bfamilyOfFamily' r f) = blsub.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [blsub_eq_lsub', blsub_eq_lsub']
#align ordinal.blsub_eq_blsub Ordinal.blsub_eq_blsub
@[simp]
theorem blsub_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
blsub.{_, v} _ (bfamilyOfFamily f) = lsub.{_, v} f :=
blsub_eq_lsub' _ _
#align ordinal.blsub_eq_lsub Ordinal.blsub_eq_lsub
@[congr]
theorem blsub_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
blsub.{_, v} o₁ f = blsub.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.blsub_congr Ordinal.blsub_congr
theorem blsub_le_iff {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} {a} :
blsub.{_, v} o f ≤ a ↔ ∀ i h, f i h < a := by
convert bsup_le_iff.{_, v} (f := fun a ha => succ (f a ha)) (a := a) using 2
simp_rw [succ_le_iff]
#align ordinal.blsub_le_iff Ordinal.blsub_le_iff
theorem blsub_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} : (∀ i h, f i h < a) → blsub o f ≤ a :=
blsub_le_iff.2
#align ordinal.blsub_le Ordinal.blsub_le
theorem lt_blsub {o} (f : ∀ a < o, Ordinal) (i h) : f i h < blsub o f :=
blsub_le_iff.1 le_rfl _ _
#align ordinal.lt_blsub Ordinal.lt_blsub
theorem lt_blsub_iff {o : Ordinal.{u}} {f : ∀ b < o, Ordinal.{max u v}} {a} :
a < blsub.{_, v} o f ↔ ∃ i hi, a ≤ f i hi := by
simpa only [not_forall, not_lt, not_le] using not_congr (@blsub_le_iff.{_, v} _ f a)
#align ordinal.lt_blsub_iff Ordinal.lt_blsub_iff
theorem bsup_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f ≤ blsub.{_, v} o f :=
bsup_le fun i h => (lt_blsub f i h).le
#align ordinal.bsup_le_blsub Ordinal.bsup_le_blsub
theorem blsub_le_bsup_succ {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
blsub.{_, v} o f ≤ succ (bsup.{_, v} o f) :=
blsub_le fun i h => lt_succ_iff.2 (le_bsup f i h)
#align ordinal.blsub_le_bsup_succ Ordinal.blsub_le_bsup_succ
theorem bsup_eq_blsub_or_succ_bsup_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ∨ succ (bsup.{_, v} o f) = blsub.{_, v} o f := by
rw [← sup_eq_bsup, ← lsub_eq_blsub]
exact sup_eq_lsub_or_sup_succ_eq_lsub _
#align ordinal.bsup_eq_blsub_or_succ_bsup_eq_blsub Ordinal.bsup_eq_blsub_or_succ_bsup_eq_blsub
theorem bsup_succ_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
succ (bsup.{_, v} o f) ≤ blsub.{_, v} o f ↔ ∃ i hi, f i hi = bsup.{_, v} o f := by
refine ⟨fun h => ?_, ?_⟩
· by_contra! hf
exact
ne_of_lt (succ_le_iff.1 h)
(le_antisymm (bsup_le_blsub f) (blsub_le (lt_bsup_of_ne_bsup.1 hf)))
rintro ⟨_, _, hf⟩
rw [succ_le_iff, ← hf]
exact lt_blsub _ _ _
#align ordinal.bsup_succ_le_blsub Ordinal.bsup_succ_le_blsub
theorem bsup_succ_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
succ (bsup.{_, v} o f) = blsub.{_, v} o f ↔ ∃ i hi, f i hi = bsup.{_, v} o f :=
(blsub_le_bsup_succ f).le_iff_eq.symm.trans (bsup_succ_le_blsub f)
#align ordinal.bsup_succ_eq_blsub Ordinal.bsup_succ_eq_blsub
theorem bsup_eq_blsub_iff_succ {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ↔ ∀ a < blsub.{_, v} o f, succ a < blsub.{_, v} o f := by
rw [← sup_eq_bsup, ← lsub_eq_blsub]
apply sup_eq_lsub_iff_succ
#align ordinal.bsup_eq_blsub_iff_succ Ordinal.bsup_eq_blsub_iff_succ
theorem bsup_eq_blsub_iff_lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ↔ ∀ i hi, f i hi < bsup.{_, v} o f :=
⟨fun h i => by
rw [h]
apply lt_blsub, fun h => le_antisymm (bsup_le_blsub f) (blsub_le h)⟩
#align ordinal.bsup_eq_blsub_iff_lt_bsup Ordinal.bsup_eq_blsub_iff_lt_bsup
theorem bsup_eq_blsub_of_lt_succ_limit {o : Ordinal.{u}} (ho : IsLimit o)
{f : ∀ a < o, Ordinal.{max u v}} (hf : ∀ a ha, f a ha < f (succ a) (ho.2 a ha)) :
bsup.{_, v} o f = blsub.{_, v} o f := by
rw [bsup_eq_blsub_iff_lt_bsup]
exact fun i hi => (hf i hi).trans_le (le_bsup f _ _)
#align ordinal.bsup_eq_blsub_of_lt_succ_limit Ordinal.bsup_eq_blsub_of_lt_succ_limit
theorem blsub_succ_of_mono {o : Ordinal.{u}} {f : ∀ a < succ o, Ordinal.{max u v}}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : blsub.{_, v} _ f = succ (f o (lt_succ o)) :=
bsup_succ_of_mono fun {_ _} hi hj h => succ_le_succ (hf hi hj h)
#align ordinal.blsub_succ_of_mono Ordinal.blsub_succ_of_mono
@[simp]
theorem blsub_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : blsub o f = 0 ↔ o = 0 := by
rw [← lsub_eq_blsub, lsub_eq_zero_iff]
exact out_empty_iff_eq_zero
#align ordinal.blsub_eq_zero_iff Ordinal.blsub_eq_zero_iff
-- Porting note: `rwa` → `rw`
@[simp]
theorem blsub_zero (f : ∀ a < (0 : Ordinal), Ordinal) : blsub 0 f = 0 := by rw [blsub_eq_zero_iff]
#align ordinal.blsub_zero Ordinal.blsub_zero
theorem blsub_pos {o : Ordinal} (ho : 0 < o) (f : ∀ a < o, Ordinal) : 0 < blsub o f :=
(Ordinal.zero_le _).trans_lt (lt_blsub f 0 ho)
#align ordinal.blsub_pos Ordinal.blsub_pos
theorem blsub_type {α : Type u} (r : α → α → Prop) [IsWellOrder α r]
(f : ∀ a < type r, Ordinal.{max u v}) :
blsub.{_, v} (type r) f = lsub.{_, v} fun a => f (typein r a) (typein_lt_type _ _) :=
eq_of_forall_ge_iff fun o => by
rw [blsub_le_iff, lsub_le_iff];
exact ⟨fun H b => H _ _, fun H i h => by simpa only [typein_enum] using H (enum r i h)⟩
#align ordinal.blsub_type Ordinal.blsub_type
theorem blsub_const {o : Ordinal} (ho : o ≠ 0) (a : Ordinal) :
(blsub.{u, v} o fun _ _ => a) = succ a :=
bsup_const.{u, v} ho (succ a)
#align ordinal.blsub_const Ordinal.blsub_const
@[simp]
theorem blsub_one (f : ∀ a < (1 : Ordinal), Ordinal) : blsub 1 f = succ (f 0 zero_lt_one) :=
bsup_one _
#align ordinal.blsub_one Ordinal.blsub_one
@[simp]
theorem blsub_id : ∀ o, (blsub.{u, u} o fun x _ => x) = o :=
lsub_typein
#align ordinal.blsub_id Ordinal.blsub_id
theorem bsup_id_limit {o : Ordinal} : (∀ a < o, succ a < o) → (bsup.{u, u} o fun x _ => x) = o :=
sup_typein_limit
#align ordinal.bsup_id_limit Ordinal.bsup_id_limit
@[simp]
theorem bsup_id_succ (o) : (bsup.{u, u} (succ o) fun x _ => x) = o :=
sup_typein_succ
#align ordinal.bsup_id_succ Ordinal.bsup_id_succ
theorem blsub_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : blsub.{u, max v w} o f ≤ blsub.{v, max u w} o' g :=
bsup_le_of_brange_subset.{u, v, w} fun a ⟨b, hb, hb'⟩ => by
obtain ⟨c, hc, hc'⟩ := h ⟨b, hb, rfl⟩
simp_rw [← hc'] at hb'
exact ⟨c, hc, hb'⟩
#align ordinal.blsub_le_of_brange_subset Ordinal.blsub_le_of_brange_subset
theorem blsub_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : { o | ∃ i hi, f i hi = o } = { o | ∃ i hi, g i hi = o }) :
blsub.{u, max v w} o f = blsub.{v, max u w} o' g :=
(blsub_le_of_brange_subset.{u, v, w} h.le).antisymm (blsub_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.blsub_eq_of_brange_eq Ordinal.blsub_eq_of_brange_eq
theorem bsup_comp {o o' : Ordinal.{max u v}} {f : ∀ a < o, Ordinal.{max u v w}}
(hf : ∀ {i j} (hi) (hj), i ≤ j → f i hi ≤ f j hj) {g : ∀ a < o', Ordinal.{max u v}}
(hg : blsub.{_, u} o' g = o) :
(bsup.{_, w} o' fun a ha => f (g a ha) (by rw [← hg]; apply lt_blsub)) = bsup.{_, w} o f := by
apply le_antisymm <;> refine bsup_le fun i hi => ?_
· apply le_bsup
· rw [← hg, lt_blsub_iff] at hi
rcases hi with ⟨j, hj, hj'⟩
exact (hf _ _ hj').trans (le_bsup _ _ _)
#align ordinal.bsup_comp Ordinal.bsup_comp
theorem blsub_comp {o o' : Ordinal.{max u v}} {f : ∀ a < o, Ordinal.{max u v w}}
(hf : ∀ {i j} (hi) (hj), i ≤ j → f i hi ≤ f j hj) {g : ∀ a < o', Ordinal.{max u v}}
(hg : blsub.{_, u} o' g = o) :
(blsub.{_, w} o' fun a ha => f (g a ha) (by rw [← hg]; apply lt_blsub)) = blsub.{_, w} o f :=
@bsup_comp.{u, v, w} o _ (fun a ha => succ (f a ha))
(fun {_ _} _ _ h => succ_le_succ_iff.2 (hf _ _ h)) g hg
#align ordinal.blsub_comp Ordinal.blsub_comp
theorem IsNormal.bsup_eq {f : Ordinal.{u} → Ordinal.{max u v}} (H : IsNormal f) {o : Ordinal.{u}}
(h : IsLimit o) : (Ordinal.bsup.{_, v} o fun x _ => f x) = f o := by
rw [← IsNormal.bsup.{u, u, v} H (fun x _ => x) h.1, bsup_id_limit h.2]
#align ordinal.is_normal.bsup_eq Ordinal.IsNormal.bsup_eq
theorem IsNormal.blsub_eq {f : Ordinal.{u} → Ordinal.{max u v}} (H : IsNormal f) {o : Ordinal.{u}}
(h : IsLimit o) : (blsub.{_, v} o fun x _ => f x) = f o := by
rw [← IsNormal.bsup_eq.{u, v} H h, bsup_eq_blsub_of_lt_succ_limit h]
exact fun a _ => H.1 a
#align ordinal.is_normal.blsub_eq Ordinal.IsNormal.blsub_eq
theorem isNormal_iff_lt_succ_and_bsup_eq {f : Ordinal.{u} → Ordinal.{max u v}} :
IsNormal f ↔ (∀ a, f a < f (succ a)) ∧ ∀ o, IsLimit o → (bsup.{_, v} o fun x _ => f x) = f o :=
⟨fun h => ⟨h.1, @IsNormal.bsup_eq f h⟩, fun ⟨h₁, h₂⟩ =>
⟨h₁, fun o ho a => by
rw [← h₂ o ho]
exact bsup_le_iff⟩⟩
#align ordinal.is_normal_iff_lt_succ_and_bsup_eq Ordinal.isNormal_iff_lt_succ_and_bsup_eq
theorem isNormal_iff_lt_succ_and_blsub_eq {f : Ordinal.{u} → Ordinal.{max u v}} :
IsNormal f ↔ (∀ a, f a < f (succ a)) ∧
∀ o, IsLimit o → (blsub.{_, v} o fun x _ => f x) = f o := by
rw [isNormal_iff_lt_succ_and_bsup_eq.{u, v}, and_congr_right_iff]
intro h
constructor <;> intro H o ho <;> have := H o ho <;>
rwa [← bsup_eq_blsub_of_lt_succ_limit ho fun a _ => h a] at *
#align ordinal.is_normal_iff_lt_succ_and_blsub_eq Ordinal.isNormal_iff_lt_succ_and_blsub_eq
theorem IsNormal.eq_iff_zero_and_succ {f g : Ordinal.{u} → Ordinal.{u}} (hf : IsNormal f)
(hg : IsNormal g) : f = g ↔ f 0 = g 0 ∧ ∀ a, f a = g a → f (succ a) = g (succ a) :=
⟨fun h => by simp [h], fun ⟨h₁, h₂⟩ =>
funext fun a => by
induction' a using limitRecOn with _ _ _ ho H
any_goals solve_by_elim
rw [← IsNormal.bsup_eq.{u, u} hf ho, ← IsNormal.bsup_eq.{u, u} hg ho]
congr
ext b hb
exact H b hb⟩
#align ordinal.is_normal.eq_iff_zero_and_succ Ordinal.IsNormal.eq_iff_zero_and_succ
/-- A two-argument version of `Ordinal.blsub`.
We don't develop a full API for this, since it's only used in a handful of existence results. -/
def blsub₂ (o₁ o₂ : Ordinal) (op : {a : Ordinal} → (a < o₁) → {b : Ordinal} → (b < o₂) → Ordinal) :
Ordinal :=
lsub (fun x : o₁.out.α × o₂.out.α => op (typein_lt_self x.1) (typein_lt_self x.2))
#align ordinal.blsub₂ Ordinal.blsub₂
theorem lt_blsub₂ {o₁ o₂ : Ordinal}
(op : {a : Ordinal} → (a < o₁) → {b : Ordinal} → (b < o₂) → Ordinal) {a b : Ordinal}
(ha : a < o₁) (hb : b < o₂) : op ha hb < blsub₂ o₁ o₂ op := by
convert lt_lsub _ (Prod.mk (enum (· < ·) a (by rwa [type_lt]))
(enum (· < ·) b (by rwa [type_lt])))
simp only [typein_enum]
#align ordinal.lt_blsub₂ Ordinal.lt_blsub₂
/-! ### Minimum excluded ordinals -/
/-- The minimum excluded ordinal in a family of ordinals. -/
def mex {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal :=
sInf (Set.range f)ᶜ
#align ordinal.mex Ordinal.mex
theorem mex_not_mem_range {ι : Type u} (f : ι → Ordinal.{max u v}) : mex.{_, v} f ∉ Set.range f :=
csInf_mem (nonempty_compl_range.{_, v} f)
#align ordinal.mex_not_mem_range Ordinal.mex_not_mem_range
theorem le_mex_of_forall {ι : Type u} {f : ι → Ordinal.{max u v}} {a : Ordinal}
(H : ∀ b < a, ∃ i, f i = b) : a ≤ mex.{_, v} f := by
by_contra! h
exact mex_not_mem_range f (H _ h)
#align ordinal.le_mex_of_forall Ordinal.le_mex_of_forall
theorem ne_mex {ι : Type u} (f : ι → Ordinal.{max u v}) : ∀ i, f i ≠ mex.{_, v} f := by
simpa using mex_not_mem_range.{_, v} f
#align ordinal.ne_mex Ordinal.ne_mex
theorem mex_le_of_ne {ι} {f : ι → Ordinal} {a} (ha : ∀ i, f i ≠ a) : mex f ≤ a :=
csInf_le' (by simp [ha])
#align ordinal.mex_le_of_ne Ordinal.mex_le_of_ne
theorem exists_of_lt_mex {ι} {f : ι → Ordinal} {a} (ha : a < mex f) : ∃ i, f i = a := by
by_contra! ha'
exact ha.not_le (mex_le_of_ne ha')
#align ordinal.exists_of_lt_mex Ordinal.exists_of_lt_mex
theorem mex_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) : mex.{_, v} f ≤ lsub.{_, v} f :=
csInf_le' (lsub_not_mem_range f)
#align ordinal.mex_le_lsub Ordinal.mex_le_lsub
theorem mex_monotone {α β : Type u} {f : α → Ordinal.{max u v}} {g : β → Ordinal.{max u v}}
(h : Set.range f ⊆ Set.range g) : mex.{_, v} f ≤ mex.{_, v} g := by
refine mex_le_of_ne fun i hi => ?_
cases' h ⟨i, rfl⟩ with j hj
rw [← hj] at hi
exact ne_mex g j hi
#align ordinal.mex_monotone Ordinal.mex_monotone
theorem mex_lt_ord_succ_mk {ι : Type u} (f : ι → Ordinal.{u}) :
mex.{_, u} f < (succ #ι).ord := by
by_contra! h
apply (lt_succ #ι).not_le
have H := fun a => exists_of_lt_mex ((typein_lt_self a).trans_le h)
let g : (succ #ι).ord.out.α → ι := fun a => Classical.choose (H a)
have hg : Injective g := fun a b h' => by
have Hf : ∀ x, f (g x) =
typein ((· < ·) : (succ #ι).ord.out.α → (succ #ι).ord.out.α → Prop) x :=
fun a => Classical.choose_spec (H a)
apply_fun f at h'
rwa [Hf, Hf, typein_inj] at h'
convert Cardinal.mk_le_of_injective hg
rw [Cardinal.mk_ord_out (succ #ι)]
#align ordinal.mex_lt_ord_succ_mk Ordinal.mex_lt_ord_succ_mk
/-- The minimum excluded ordinal of a family of ordinals indexed by the set of ordinals less than
some `o : Ordinal.{u}`. This is a special case of `mex` over the family provided by
`familyOfBFamily`.
This is to `mex` as `bsup` is to `sup`. -/
def bmex (o : Ordinal) (f : ∀ a < o, Ordinal) : Ordinal :=
mex (familyOfBFamily o f)
#align ordinal.bmex Ordinal.bmex
theorem bmex_not_mem_brange {o : Ordinal} (f : ∀ a < o, Ordinal) : bmex o f ∉ brange o f := by
rw [← range_familyOfBFamily]
apply mex_not_mem_range
#align ordinal.bmex_not_mem_brange Ordinal.bmex_not_mem_brange
| Mathlib/SetTheory/Ordinal/Arithmetic.lean | 2,086 | 2,089 | theorem le_bmex_of_forall {o : Ordinal} (f : ∀ a < o, Ordinal) {a : Ordinal}
(H : ∀ b < a, ∃ i hi, f i hi = b) : a ≤ bmex o f := by |
by_contra! h
exact bmex_not_mem_brange f (H _ h)
|
/-
Copyright (c) 2014 Parikshit Khanna. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Parikshit Khanna, Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Mario Carneiro
-/
import Mathlib.Data.Nat.Defs
import Mathlib.Data.Option.Basic
import Mathlib.Data.List.Defs
import Mathlib.Init.Data.List.Basic
import Mathlib.Init.Data.List.Instances
import Mathlib.Init.Data.List.Lemmas
import Mathlib.Logic.Unique
import Mathlib.Order.Basic
import Mathlib.Tactic.Common
#align_import data.list.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Basic properties of lists
-/
assert_not_exists Set.range
assert_not_exists GroupWithZero
assert_not_exists Ring
open Function
open Nat hiding one_pos
namespace List
universe u v w
variable {ι : Type*} {α : Type u} {β : Type v} {γ : Type w} {l₁ l₂ : List α}
-- Porting note: Delete this attribute
-- attribute [inline] List.head!
/-- There is only one list of an empty type -/
instance uniqueOfIsEmpty [IsEmpty α] : Unique (List α) :=
{ instInhabitedList with
uniq := fun l =>
match l with
| [] => rfl
| a :: _ => isEmptyElim a }
#align list.unique_of_is_empty List.uniqueOfIsEmpty
instance : Std.LawfulIdentity (α := List α) Append.append [] where
left_id := nil_append
right_id := append_nil
instance : Std.Associative (α := List α) Append.append where
assoc := append_assoc
#align list.cons_ne_nil List.cons_ne_nil
#align list.cons_ne_self List.cons_ne_self
#align list.head_eq_of_cons_eq List.head_eq_of_cons_eqₓ -- implicits order
#align list.tail_eq_of_cons_eq List.tail_eq_of_cons_eqₓ -- implicits order
@[simp] theorem cons_injective {a : α} : Injective (cons a) := fun _ _ => tail_eq_of_cons_eq
#align list.cons_injective List.cons_injective
#align list.cons_inj List.cons_inj
#align list.cons_eq_cons List.cons_eq_cons
theorem singleton_injective : Injective fun a : α => [a] := fun _ _ h => (cons_eq_cons.1 h).1
#align list.singleton_injective List.singleton_injective
theorem singleton_inj {a b : α} : [a] = [b] ↔ a = b :=
singleton_injective.eq_iff
#align list.singleton_inj List.singleton_inj
#align list.exists_cons_of_ne_nil List.exists_cons_of_ne_nil
theorem set_of_mem_cons (l : List α) (a : α) : { x | x ∈ a :: l } = insert a { x | x ∈ l } :=
Set.ext fun _ => mem_cons
#align list.set_of_mem_cons List.set_of_mem_cons
/-! ### mem -/
#align list.mem_singleton_self List.mem_singleton_self
#align list.eq_of_mem_singleton List.eq_of_mem_singleton
#align list.mem_singleton List.mem_singleton
#align list.mem_of_mem_cons_of_mem List.mem_of_mem_cons_of_mem
theorem _root_.Decidable.List.eq_or_ne_mem_of_mem [DecidableEq α]
{a b : α} {l : List α} (h : a ∈ b :: l) : a = b ∨ a ≠ b ∧ a ∈ l := by
by_cases hab : a = b
· exact Or.inl hab
· exact ((List.mem_cons.1 h).elim Or.inl (fun h => Or.inr ⟨hab, h⟩))
#align decidable.list.eq_or_ne_mem_of_mem Decidable.List.eq_or_ne_mem_of_mem
#align list.eq_or_ne_mem_of_mem List.eq_or_ne_mem_of_mem
#align list.not_mem_append List.not_mem_append
#align list.ne_nil_of_mem List.ne_nil_of_mem
lemma mem_pair {a b c : α} : a ∈ [b, c] ↔ a = b ∨ a = c := by
rw [mem_cons, mem_singleton]
@[deprecated (since := "2024-03-23")] alias mem_split := append_of_mem
#align list.mem_split List.append_of_mem
#align list.mem_of_ne_of_mem List.mem_of_ne_of_mem
#align list.ne_of_not_mem_cons List.ne_of_not_mem_cons
#align list.not_mem_of_not_mem_cons List.not_mem_of_not_mem_cons
#align list.not_mem_cons_of_ne_of_not_mem List.not_mem_cons_of_ne_of_not_mem
#align list.ne_and_not_mem_of_not_mem_cons List.ne_and_not_mem_of_not_mem_cons
#align list.mem_map List.mem_map
#align list.exists_of_mem_map List.exists_of_mem_map
#align list.mem_map_of_mem List.mem_map_of_memₓ -- implicits order
-- The simpNF linter says that the LHS can be simplified via `List.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem mem_map_of_injective {f : α → β} (H : Injective f) {a : α} {l : List α} :
f a ∈ map f l ↔ a ∈ l :=
⟨fun m => let ⟨_, m', e⟩ := exists_of_mem_map m; H e ▸ m', mem_map_of_mem _⟩
#align list.mem_map_of_injective List.mem_map_of_injective
@[simp]
theorem _root_.Function.Involutive.exists_mem_and_apply_eq_iff {f : α → α}
(hf : Function.Involutive f) (x : α) (l : List α) : (∃ y : α, y ∈ l ∧ f y = x) ↔ f x ∈ l :=
⟨by rintro ⟨y, h, rfl⟩; rwa [hf y], fun h => ⟨f x, h, hf _⟩⟩
#align function.involutive.exists_mem_and_apply_eq_iff Function.Involutive.exists_mem_and_apply_eq_iff
theorem mem_map_of_involutive {f : α → α} (hf : Involutive f) {a : α} {l : List α} :
a ∈ map f l ↔ f a ∈ l := by rw [mem_map, hf.exists_mem_and_apply_eq_iff]
#align list.mem_map_of_involutive List.mem_map_of_involutive
#align list.forall_mem_map_iff List.forall_mem_map_iffₓ -- universe order
#align list.map_eq_nil List.map_eq_nilₓ -- universe order
attribute [simp] List.mem_join
#align list.mem_join List.mem_join
#align list.exists_of_mem_join List.exists_of_mem_join
#align list.mem_join_of_mem List.mem_join_of_memₓ -- implicits order
attribute [simp] List.mem_bind
#align list.mem_bind List.mem_bindₓ -- implicits order
-- Porting note: bExists in Lean3, And in Lean4
#align list.exists_of_mem_bind List.exists_of_mem_bindₓ -- implicits order
#align list.mem_bind_of_mem List.mem_bind_of_memₓ -- implicits order
#align list.bind_map List.bind_mapₓ -- implicits order
theorem map_bind (g : β → List γ) (f : α → β) :
∀ l : List α, (List.map f l).bind g = l.bind fun a => g (f a)
| [] => rfl
| a :: l => by simp only [cons_bind, map_cons, map_bind _ _ l]
#align list.map_bind List.map_bind
/-! ### length -/
#align list.length_eq_zero List.length_eq_zero
#align list.length_singleton List.length_singleton
#align list.length_pos_of_mem List.length_pos_of_mem
#align list.exists_mem_of_length_pos List.exists_mem_of_length_pos
#align list.length_pos_iff_exists_mem List.length_pos_iff_exists_mem
alias ⟨ne_nil_of_length_pos, length_pos_of_ne_nil⟩ := length_pos
#align list.ne_nil_of_length_pos List.ne_nil_of_length_pos
#align list.length_pos_of_ne_nil List.length_pos_of_ne_nil
theorem length_pos_iff_ne_nil {l : List α} : 0 < length l ↔ l ≠ [] :=
⟨ne_nil_of_length_pos, length_pos_of_ne_nil⟩
#align list.length_pos_iff_ne_nil List.length_pos_iff_ne_nil
#align list.exists_mem_of_ne_nil List.exists_mem_of_ne_nil
#align list.length_eq_one List.length_eq_one
theorem exists_of_length_succ {n} : ∀ l : List α, l.length = n + 1 → ∃ h t, l = h :: t
| [], H => absurd H.symm <| succ_ne_zero n
| h :: t, _ => ⟨h, t, rfl⟩
#align list.exists_of_length_succ List.exists_of_length_succ
@[simp] lemma length_injective_iff : Injective (List.length : List α → ℕ) ↔ Subsingleton α := by
constructor
· intro h; refine ⟨fun x y => ?_⟩; (suffices [x] = [y] by simpa using this); apply h; rfl
· intros hα l1 l2 hl
induction l1 generalizing l2 <;> cases l2
· rfl
· cases hl
· cases hl
· next ih _ _ =>
congr
· exact Subsingleton.elim _ _
· apply ih; simpa using hl
#align list.length_injective_iff List.length_injective_iff
@[simp default+1] -- Porting note: this used to be just @[simp]
lemma length_injective [Subsingleton α] : Injective (length : List α → ℕ) :=
length_injective_iff.mpr inferInstance
#align list.length_injective List.length_injective
theorem length_eq_two {l : List α} : l.length = 2 ↔ ∃ a b, l = [a, b] :=
⟨fun _ => let [a, b] := l; ⟨a, b, rfl⟩, fun ⟨_, _, e⟩ => e ▸ rfl⟩
#align list.length_eq_two List.length_eq_two
theorem length_eq_three {l : List α} : l.length = 3 ↔ ∃ a b c, l = [a, b, c] :=
⟨fun _ => let [a, b, c] := l; ⟨a, b, c, rfl⟩, fun ⟨_, _, _, e⟩ => e ▸ rfl⟩
#align list.length_eq_three List.length_eq_three
#align list.sublist.length_le List.Sublist.length_le
/-! ### set-theoretic notation of lists -/
-- ADHOC Porting note: instance from Lean3 core
instance instSingletonList : Singleton α (List α) := ⟨fun x => [x]⟩
#align list.has_singleton List.instSingletonList
-- ADHOC Porting note: instance from Lean3 core
instance [DecidableEq α] : Insert α (List α) := ⟨List.insert⟩
-- ADHOC Porting note: instance from Lean3 core
instance [DecidableEq α] : LawfulSingleton α (List α) :=
{ insert_emptyc_eq := fun x =>
show (if x ∈ ([] : List α) then [] else [x]) = [x] from if_neg (not_mem_nil _) }
#align list.empty_eq List.empty_eq
theorem singleton_eq (x : α) : ({x} : List α) = [x] :=
rfl
#align list.singleton_eq List.singleton_eq
theorem insert_neg [DecidableEq α] {x : α} {l : List α} (h : x ∉ l) :
Insert.insert x l = x :: l :=
insert_of_not_mem h
#align list.insert_neg List.insert_neg
theorem insert_pos [DecidableEq α] {x : α} {l : List α} (h : x ∈ l) : Insert.insert x l = l :=
insert_of_mem h
#align list.insert_pos List.insert_pos
theorem doubleton_eq [DecidableEq α] {x y : α} (h : x ≠ y) : ({x, y} : List α) = [x, y] := by
rw [insert_neg, singleton_eq]
rwa [singleton_eq, mem_singleton]
#align list.doubleton_eq List.doubleton_eq
/-! ### bounded quantifiers over lists -/
#align list.forall_mem_nil List.forall_mem_nil
#align list.forall_mem_cons List.forall_mem_cons
theorem forall_mem_of_forall_mem_cons {p : α → Prop} {a : α} {l : List α} (h : ∀ x ∈ a :: l, p x) :
∀ x ∈ l, p x := (forall_mem_cons.1 h).2
#align list.forall_mem_of_forall_mem_cons List.forall_mem_of_forall_mem_cons
#align list.forall_mem_singleton List.forall_mem_singleton
#align list.forall_mem_append List.forall_mem_append
#align list.not_exists_mem_nil List.not_exists_mem_nilₓ -- bExists change
-- Porting note: bExists in Lean3 and And in Lean4
theorem exists_mem_cons_of {p : α → Prop} {a : α} (l : List α) (h : p a) : ∃ x ∈ a :: l, p x :=
⟨a, mem_cons_self _ _, h⟩
#align list.exists_mem_cons_of List.exists_mem_cons_ofₓ -- bExists change
-- Porting note: bExists in Lean3 and And in Lean4
theorem exists_mem_cons_of_exists {p : α → Prop} {a : α} {l : List α} : (∃ x ∈ l, p x) →
∃ x ∈ a :: l, p x :=
fun ⟨x, xl, px⟩ => ⟨x, mem_cons_of_mem _ xl, px⟩
#align list.exists_mem_cons_of_exists List.exists_mem_cons_of_existsₓ -- bExists change
-- Porting note: bExists in Lean3 and And in Lean4
theorem or_exists_of_exists_mem_cons {p : α → Prop} {a : α} {l : List α} : (∃ x ∈ a :: l, p x) →
p a ∨ ∃ x ∈ l, p x :=
fun ⟨x, xal, px⟩ =>
Or.elim (eq_or_mem_of_mem_cons xal) (fun h : x = a => by rw [← h]; left; exact px)
fun h : x ∈ l => Or.inr ⟨x, h, px⟩
#align list.or_exists_of_exists_mem_cons List.or_exists_of_exists_mem_consₓ -- bExists change
theorem exists_mem_cons_iff (p : α → Prop) (a : α) (l : List α) :
(∃ x ∈ a :: l, p x) ↔ p a ∨ ∃ x ∈ l, p x :=
Iff.intro or_exists_of_exists_mem_cons fun h =>
Or.elim h (exists_mem_cons_of l) exists_mem_cons_of_exists
#align list.exists_mem_cons_iff List.exists_mem_cons_iff
/-! ### list subset -/
instance : IsTrans (List α) Subset where
trans := fun _ _ _ => List.Subset.trans
#align list.subset_def List.subset_def
#align list.subset_append_of_subset_left List.subset_append_of_subset_left
#align list.subset_append_of_subset_right List.subset_append_of_subset_right
#align list.cons_subset List.cons_subset
theorem cons_subset_of_subset_of_mem {a : α} {l m : List α}
(ainm : a ∈ m) (lsubm : l ⊆ m) : a::l ⊆ m :=
cons_subset.2 ⟨ainm, lsubm⟩
#align list.cons_subset_of_subset_of_mem List.cons_subset_of_subset_of_mem
theorem append_subset_of_subset_of_subset {l₁ l₂ l : List α} (l₁subl : l₁ ⊆ l) (l₂subl : l₂ ⊆ l) :
l₁ ++ l₂ ⊆ l :=
fun _ h ↦ (mem_append.1 h).elim (@l₁subl _) (@l₂subl _)
#align list.append_subset_of_subset_of_subset List.append_subset_of_subset_of_subset
-- Porting note: in Batteries
#align list.append_subset_iff List.append_subset
alias ⟨eq_nil_of_subset_nil, _⟩ := subset_nil
#align list.eq_nil_of_subset_nil List.eq_nil_of_subset_nil
#align list.eq_nil_iff_forall_not_mem List.eq_nil_iff_forall_not_mem
#align list.map_subset List.map_subset
theorem map_subset_iff {l₁ l₂ : List α} (f : α → β) (h : Injective f) :
map f l₁ ⊆ map f l₂ ↔ l₁ ⊆ l₂ := by
refine ⟨?_, map_subset f⟩; intro h2 x hx
rcases mem_map.1 (h2 (mem_map_of_mem f hx)) with ⟨x', hx', hxx'⟩
cases h hxx'; exact hx'
#align list.map_subset_iff List.map_subset_iff
/-! ### append -/
theorem append_eq_has_append {L₁ L₂ : List α} : List.append L₁ L₂ = L₁ ++ L₂ :=
rfl
#align list.append_eq_has_append List.append_eq_has_append
#align list.singleton_append List.singleton_append
#align list.append_ne_nil_of_ne_nil_left List.append_ne_nil_of_ne_nil_left
#align list.append_ne_nil_of_ne_nil_right List.append_ne_nil_of_ne_nil_right
#align list.append_eq_nil List.append_eq_nil
-- Porting note: in Batteries
#align list.nil_eq_append_iff List.nil_eq_append
@[deprecated (since := "2024-03-24")] alias append_eq_cons_iff := append_eq_cons
#align list.append_eq_cons_iff List.append_eq_cons
@[deprecated (since := "2024-03-24")] alias cons_eq_append_iff := cons_eq_append
#align list.cons_eq_append_iff List.cons_eq_append
#align list.append_eq_append_iff List.append_eq_append_iff
#align list.take_append_drop List.take_append_drop
#align list.append_inj List.append_inj
#align list.append_inj_right List.append_inj_rightₓ -- implicits order
#align list.append_inj_left List.append_inj_leftₓ -- implicits order
#align list.append_inj' List.append_inj'ₓ -- implicits order
#align list.append_inj_right' List.append_inj_right'ₓ -- implicits order
#align list.append_inj_left' List.append_inj_left'ₓ -- implicits order
@[deprecated (since := "2024-01-18")] alias append_left_cancel := append_cancel_left
#align list.append_left_cancel List.append_cancel_left
@[deprecated (since := "2024-01-18")] alias append_right_cancel := append_cancel_right
#align list.append_right_cancel List.append_cancel_right
@[simp] theorem append_left_eq_self {x y : List α} : x ++ y = y ↔ x = [] := by
rw [← append_left_inj (s₁ := x), nil_append]
@[simp] theorem self_eq_append_left {x y : List α} : y = x ++ y ↔ x = [] := by
rw [eq_comm, append_left_eq_self]
@[simp] theorem append_right_eq_self {x y : List α} : x ++ y = x ↔ y = [] := by
rw [← append_right_inj (t₁ := y), append_nil]
@[simp] theorem self_eq_append_right {x y : List α} : x = x ++ y ↔ y = [] := by
rw [eq_comm, append_right_eq_self]
theorem append_right_injective (s : List α) : Injective fun t ↦ s ++ t :=
fun _ _ ↦ append_cancel_left
#align list.append_right_injective List.append_right_injective
#align list.append_right_inj List.append_right_inj
theorem append_left_injective (t : List α) : Injective fun s ↦ s ++ t :=
fun _ _ ↦ append_cancel_right
#align list.append_left_injective List.append_left_injective
#align list.append_left_inj List.append_left_inj
#align list.map_eq_append_split List.map_eq_append_split
/-! ### replicate -/
@[simp] lemma replicate_zero (a : α) : replicate 0 a = [] := rfl
#align list.replicate_zero List.replicate_zero
attribute [simp] replicate_succ
#align list.replicate_succ List.replicate_succ
lemma replicate_one (a : α) : replicate 1 a = [a] := rfl
#align list.replicate_one List.replicate_one
#align list.length_replicate List.length_replicate
#align list.mem_replicate List.mem_replicate
#align list.eq_of_mem_replicate List.eq_of_mem_replicate
theorem eq_replicate_length {a : α} : ∀ {l : List α}, l = replicate l.length a ↔ ∀ b ∈ l, b = a
| [] => by simp
| (b :: l) => by simp [eq_replicate_length]
#align list.eq_replicate_length List.eq_replicate_length
#align list.eq_replicate_of_mem List.eq_replicate_of_mem
#align list.eq_replicate List.eq_replicate
theorem replicate_add (m n) (a : α) : replicate (m + n) a = replicate m a ++ replicate n a := by
induction m <;> simp [*, succ_add, replicate]
#align list.replicate_add List.replicate_add
theorem replicate_succ' (n) (a : α) : replicate (n + 1) a = replicate n a ++ [a] :=
replicate_add n 1 a
#align list.replicate_succ' List.replicate_succ'
theorem replicate_subset_singleton (n) (a : α) : replicate n a ⊆ [a] := fun _ h =>
mem_singleton.2 (eq_of_mem_replicate h)
#align list.replicate_subset_singleton List.replicate_subset_singleton
theorem subset_singleton_iff {a : α} {L : List α} : L ⊆ [a] ↔ ∃ n, L = replicate n a := by
simp only [eq_replicate, subset_def, mem_singleton, exists_eq_left']
#align list.subset_singleton_iff List.subset_singleton_iff
@[simp] theorem map_replicate (f : α → β) (n) (a : α) :
map f (replicate n a) = replicate n (f a) := by
induction n <;> [rfl; simp only [*, replicate, map]]
#align list.map_replicate List.map_replicate
@[simp] theorem tail_replicate (a : α) (n) :
tail (replicate n a) = replicate (n - 1) a := by cases n <;> rfl
#align list.tail_replicate List.tail_replicate
@[simp] theorem join_replicate_nil (n : ℕ) : join (replicate n []) = @nil α := by
induction n <;> [rfl; simp only [*, replicate, join, append_nil]]
#align list.join_replicate_nil List.join_replicate_nil
theorem replicate_right_injective {n : ℕ} (hn : n ≠ 0) : Injective (@replicate α n) :=
fun _ _ h => (eq_replicate.1 h).2 _ <| mem_replicate.2 ⟨hn, rfl⟩
#align list.replicate_right_injective List.replicate_right_injective
theorem replicate_right_inj {a b : α} {n : ℕ} (hn : n ≠ 0) :
replicate n a = replicate n b ↔ a = b :=
(replicate_right_injective hn).eq_iff
#align list.replicate_right_inj List.replicate_right_inj
@[simp] theorem replicate_right_inj' {a b : α} : ∀ {n},
replicate n a = replicate n b ↔ n = 0 ∨ a = b
| 0 => by simp
| n + 1 => (replicate_right_inj n.succ_ne_zero).trans <| by simp only [n.succ_ne_zero, false_or]
#align list.replicate_right_inj' List.replicate_right_inj'
theorem replicate_left_injective (a : α) : Injective (replicate · a) :=
LeftInverse.injective (length_replicate · a)
#align list.replicate_left_injective List.replicate_left_injective
@[simp] theorem replicate_left_inj {a : α} {n m : ℕ} : replicate n a = replicate m a ↔ n = m :=
(replicate_left_injective a).eq_iff
#align list.replicate_left_inj List.replicate_left_inj
@[simp] theorem head_replicate (n : ℕ) (a : α) (h) : head (replicate n a) h = a := by
cases n <;> simp at h ⊢
/-! ### pure -/
theorem mem_pure (x y : α) : x ∈ (pure y : List α) ↔ x = y := by simp
#align list.mem_pure List.mem_pure
/-! ### bind -/
@[simp]
theorem bind_eq_bind {α β} (f : α → List β) (l : List α) : l >>= f = l.bind f :=
rfl
#align list.bind_eq_bind List.bind_eq_bind
#align list.bind_append List.append_bind
/-! ### concat -/
#align list.concat_nil List.concat_nil
#align list.concat_cons List.concat_cons
#align list.concat_eq_append List.concat_eq_append
#align list.init_eq_of_concat_eq List.init_eq_of_concat_eq
#align list.last_eq_of_concat_eq List.last_eq_of_concat_eq
#align list.concat_ne_nil List.concat_ne_nil
#align list.concat_append List.concat_append
#align list.length_concat List.length_concat
#align list.append_concat List.append_concat
/-! ### reverse -/
#align list.reverse_nil List.reverse_nil
#align list.reverse_core List.reverseAux
-- Porting note: Do we need this?
attribute [local simp] reverseAux
#align list.reverse_cons List.reverse_cons
#align list.reverse_core_eq List.reverseAux_eq
theorem reverse_cons' (a : α) (l : List α) : reverse (a :: l) = concat (reverse l) a := by
simp only [reverse_cons, concat_eq_append]
#align list.reverse_cons' List.reverse_cons'
theorem reverse_concat' (l : List α) (a : α) : (l ++ [a]).reverse = a :: l.reverse := by
rw [reverse_append]; rfl
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem reverse_singleton (a : α) : reverse [a] = [a] :=
rfl
#align list.reverse_singleton List.reverse_singleton
#align list.reverse_append List.reverse_append
#align list.reverse_concat List.reverse_concat
#align list.reverse_reverse List.reverse_reverse
@[simp]
theorem reverse_involutive : Involutive (@reverse α) :=
reverse_reverse
#align list.reverse_involutive List.reverse_involutive
@[simp]
theorem reverse_injective : Injective (@reverse α) :=
reverse_involutive.injective
#align list.reverse_injective List.reverse_injective
theorem reverse_surjective : Surjective (@reverse α) :=
reverse_involutive.surjective
#align list.reverse_surjective List.reverse_surjective
theorem reverse_bijective : Bijective (@reverse α) :=
reverse_involutive.bijective
#align list.reverse_bijective List.reverse_bijective
@[simp]
theorem reverse_inj {l₁ l₂ : List α} : reverse l₁ = reverse l₂ ↔ l₁ = l₂ :=
reverse_injective.eq_iff
#align list.reverse_inj List.reverse_inj
theorem reverse_eq_iff {l l' : List α} : l.reverse = l' ↔ l = l'.reverse :=
reverse_involutive.eq_iff
#align list.reverse_eq_iff List.reverse_eq_iff
#align list.reverse_eq_nil List.reverse_eq_nil_iff
theorem concat_eq_reverse_cons (a : α) (l : List α) : concat l a = reverse (a :: reverse l) := by
simp only [concat_eq_append, reverse_cons, reverse_reverse]
#align list.concat_eq_reverse_cons List.concat_eq_reverse_cons
#align list.length_reverse List.length_reverse
-- Porting note: This one was @[simp] in mathlib 3,
-- but Lean contains a competing simp lemma reverse_map.
-- For now we remove @[simp] to avoid simplification loops.
-- TODO: Change Lean lemma to match mathlib 3?
theorem map_reverse (f : α → β) (l : List α) : map f (reverse l) = reverse (map f l) :=
(reverse_map f l).symm
#align list.map_reverse List.map_reverse
theorem map_reverseAux (f : α → β) (l₁ l₂ : List α) :
map f (reverseAux l₁ l₂) = reverseAux (map f l₁) (map f l₂) := by
simp only [reverseAux_eq, map_append, map_reverse]
#align list.map_reverse_core List.map_reverseAux
#align list.mem_reverse List.mem_reverse
@[simp] theorem reverse_replicate (n) (a : α) : reverse (replicate n a) = replicate n a :=
eq_replicate.2
⟨by rw [length_reverse, length_replicate],
fun b h => eq_of_mem_replicate (mem_reverse.1 h)⟩
#align list.reverse_replicate List.reverse_replicate
/-! ### empty -/
-- Porting note: this does not work as desired
-- attribute [simp] List.isEmpty
theorem isEmpty_iff_eq_nil {l : List α} : l.isEmpty ↔ l = [] := by cases l <;> simp [isEmpty]
#align list.empty_iff_eq_nil List.isEmpty_iff_eq_nil
/-! ### dropLast -/
#align list.length_init List.length_dropLast
/-! ### getLast -/
@[simp]
theorem getLast_cons {a : α} {l : List α} :
∀ h : l ≠ nil, getLast (a :: l) (cons_ne_nil a l) = getLast l h := by
induction l <;> intros
· contradiction
· rfl
#align list.last_cons List.getLast_cons
theorem getLast_append_singleton {a : α} (l : List α) :
getLast (l ++ [a]) (append_ne_nil_of_ne_nil_right l _ (cons_ne_nil a _)) = a := by
simp only [getLast_append]
#align list.last_append_singleton List.getLast_append_singleton
-- Porting note: name should be fixed upstream
theorem getLast_append' (l₁ l₂ : List α) (h : l₂ ≠ []) :
getLast (l₁ ++ l₂) (append_ne_nil_of_ne_nil_right l₁ l₂ h) = getLast l₂ h := by
induction' l₁ with _ _ ih
· simp
· simp only [cons_append]
rw [List.getLast_cons]
exact ih
#align list.last_append List.getLast_append'
theorem getLast_concat' {a : α} (l : List α) : getLast (concat l a) (concat_ne_nil a l) = a :=
getLast_concat ..
#align list.last_concat List.getLast_concat'
@[simp]
theorem getLast_singleton' (a : α) : getLast [a] (cons_ne_nil a []) = a := rfl
#align list.last_singleton List.getLast_singleton'
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem getLast_cons_cons (a₁ a₂ : α) (l : List α) :
getLast (a₁ :: a₂ :: l) (cons_ne_nil _ _) = getLast (a₂ :: l) (cons_ne_nil a₂ l) :=
rfl
#align list.last_cons_cons List.getLast_cons_cons
theorem dropLast_append_getLast : ∀ {l : List α} (h : l ≠ []), dropLast l ++ [getLast l h] = l
| [], h => absurd rfl h
| [a], h => rfl
| a :: b :: l, h => by
rw [dropLast_cons₂, cons_append, getLast_cons (cons_ne_nil _ _)]
congr
exact dropLast_append_getLast (cons_ne_nil b l)
#align list.init_append_last List.dropLast_append_getLast
theorem getLast_congr {l₁ l₂ : List α} (h₁ : l₁ ≠ []) (h₂ : l₂ ≠ []) (h₃ : l₁ = l₂) :
getLast l₁ h₁ = getLast l₂ h₂ := by subst l₁; rfl
#align list.last_congr List.getLast_congr
#align list.last_mem List.getLast_mem
theorem getLast_replicate_succ (m : ℕ) (a : α) :
(replicate (m + 1) a).getLast (ne_nil_of_length_eq_succ (length_replicate _ _)) = a := by
simp only [replicate_succ']
exact getLast_append_singleton _
#align list.last_replicate_succ List.getLast_replicate_succ
/-! ### getLast? -/
-- Porting note: Moved earlier in file, for use in subsequent lemmas.
@[simp]
theorem getLast?_cons_cons (a b : α) (l : List α) :
getLast? (a :: b :: l) = getLast? (b :: l) := rfl
@[simp]
theorem getLast?_isNone : ∀ {l : List α}, (getLast? l).isNone ↔ l = []
| [] => by simp
| [a] => by simp
| a :: b :: l => by simp [@getLast?_isNone (b :: l)]
#align list.last'_is_none List.getLast?_isNone
@[simp]
theorem getLast?_isSome : ∀ {l : List α}, l.getLast?.isSome ↔ l ≠ []
| [] => by simp
| [a] => by simp
| a :: b :: l => by simp [@getLast?_isSome (b :: l)]
#align list.last'_is_some List.getLast?_isSome
theorem mem_getLast?_eq_getLast : ∀ {l : List α} {x : α}, x ∈ l.getLast? → ∃ h, x = getLast l h
| [], x, hx => False.elim <| by simp at hx
| [a], x, hx =>
have : a = x := by simpa using hx
this ▸ ⟨cons_ne_nil a [], rfl⟩
| a :: b :: l, x, hx => by
rw [getLast?_cons_cons] at hx
rcases mem_getLast?_eq_getLast hx with ⟨_, h₂⟩
use cons_ne_nil _ _
assumption
#align list.mem_last'_eq_last List.mem_getLast?_eq_getLast
theorem getLast?_eq_getLast_of_ne_nil : ∀ {l : List α} (h : l ≠ []), l.getLast? = some (l.getLast h)
| [], h => (h rfl).elim
| [_], _ => rfl
| _ :: b :: l, _ => @getLast?_eq_getLast_of_ne_nil (b :: l) (cons_ne_nil _ _)
#align list.last'_eq_last_of_ne_nil List.getLast?_eq_getLast_of_ne_nil
theorem mem_getLast?_cons {x y : α} : ∀ {l : List α}, x ∈ l.getLast? → x ∈ (y :: l).getLast?
| [], _ => by contradiction
| _ :: _, h => h
#align list.mem_last'_cons List.mem_getLast?_cons
theorem mem_of_mem_getLast? {l : List α} {a : α} (ha : a ∈ l.getLast?) : a ∈ l :=
let ⟨_, h₂⟩ := mem_getLast?_eq_getLast ha
h₂.symm ▸ getLast_mem _
#align list.mem_of_mem_last' List.mem_of_mem_getLast?
theorem dropLast_append_getLast? : ∀ {l : List α}, ∀ a ∈ l.getLast?, dropLast l ++ [a] = l
| [], a, ha => (Option.not_mem_none a ha).elim
| [a], _, rfl => rfl
| a :: b :: l, c, hc => by
rw [getLast?_cons_cons] at hc
rw [dropLast_cons₂, cons_append, dropLast_append_getLast? _ hc]
#align list.init_append_last' List.dropLast_append_getLast?
theorem getLastI_eq_getLast? [Inhabited α] : ∀ l : List α, l.getLastI = l.getLast?.iget
| [] => by simp [getLastI, Inhabited.default]
| [a] => rfl
| [a, b] => rfl
| [a, b, c] => rfl
| _ :: _ :: c :: l => by simp [getLastI, getLastI_eq_getLast? (c :: l)]
#align list.ilast_eq_last' List.getLastI_eq_getLast?
@[simp]
theorem getLast?_append_cons :
∀ (l₁ : List α) (a : α) (l₂ : List α), getLast? (l₁ ++ a :: l₂) = getLast? (a :: l₂)
| [], a, l₂ => rfl
| [b], a, l₂ => rfl
| b :: c :: l₁, a, l₂ => by rw [cons_append, cons_append, getLast?_cons_cons,
← cons_append, getLast?_append_cons (c :: l₁)]
#align list.last'_append_cons List.getLast?_append_cons
#align list.last'_cons_cons List.getLast?_cons_cons
theorem getLast?_append_of_ne_nil (l₁ : List α) :
∀ {l₂ : List α} (_ : l₂ ≠ []), getLast? (l₁ ++ l₂) = getLast? l₂
| [], hl₂ => by contradiction
| b :: l₂, _ => getLast?_append_cons l₁ b l₂
#align list.last'_append_of_ne_nil List.getLast?_append_of_ne_nil
theorem getLast?_append {l₁ l₂ : List α} {x : α} (h : x ∈ l₂.getLast?) :
x ∈ (l₁ ++ l₂).getLast? := by
cases l₂
· contradiction
· rw [List.getLast?_append_cons]
exact h
#align list.last'_append List.getLast?_append
/-! ### head(!?) and tail -/
@[simp]
theorem head!_nil [Inhabited α] : ([] : List α).head! = default := rfl
@[simp] theorem head_cons_tail (x : List α) (h : x ≠ []) : x.head h :: x.tail = x := by
cases x <;> simp at h ⊢
theorem head!_eq_head? [Inhabited α] (l : List α) : head! l = (head? l).iget := by cases l <;> rfl
#align list.head_eq_head' List.head!_eq_head?
theorem surjective_head! [Inhabited α] : Surjective (@head! α _) := fun x => ⟨[x], rfl⟩
#align list.surjective_head List.surjective_head!
theorem surjective_head? : Surjective (@head? α) :=
Option.forall.2 ⟨⟨[], rfl⟩, fun x => ⟨[x], rfl⟩⟩
#align list.surjective_head' List.surjective_head?
theorem surjective_tail : Surjective (@tail α)
| [] => ⟨[], rfl⟩
| a :: l => ⟨a :: a :: l, rfl⟩
#align list.surjective_tail List.surjective_tail
theorem eq_cons_of_mem_head? {x : α} : ∀ {l : List α}, x ∈ l.head? → l = x :: tail l
| [], h => (Option.not_mem_none _ h).elim
| a :: l, h => by
simp only [head?, Option.mem_def, Option.some_inj] at h
exact h ▸ rfl
#align list.eq_cons_of_mem_head' List.eq_cons_of_mem_head?
theorem mem_of_mem_head? {x : α} {l : List α} (h : x ∈ l.head?) : x ∈ l :=
(eq_cons_of_mem_head? h).symm ▸ mem_cons_self _ _
#align list.mem_of_mem_head' List.mem_of_mem_head?
@[simp] theorem head!_cons [Inhabited α] (a : α) (l : List α) : head! (a :: l) = a := rfl
#align list.head_cons List.head!_cons
#align list.tail_nil List.tail_nil
#align list.tail_cons List.tail_cons
@[simp]
theorem head!_append [Inhabited α] (t : List α) {s : List α} (h : s ≠ []) :
head! (s ++ t) = head! s := by
induction s
· contradiction
· rfl
#align list.head_append List.head!_append
theorem head?_append {s t : List α} {x : α} (h : x ∈ s.head?) : x ∈ (s ++ t).head? := by
cases s
· contradiction
· exact h
#align list.head'_append List.head?_append
theorem head?_append_of_ne_nil :
∀ (l₁ : List α) {l₂ : List α} (_ : l₁ ≠ []), head? (l₁ ++ l₂) = head? l₁
| _ :: _, _, _ => rfl
#align list.head'_append_of_ne_nil List.head?_append_of_ne_nil
theorem tail_append_singleton_of_ne_nil {a : α} {l : List α} (h : l ≠ nil) :
tail (l ++ [a]) = tail l ++ [a] := by
induction l
· contradiction
· rw [tail, cons_append, tail]
#align list.tail_append_singleton_of_ne_nil List.tail_append_singleton_of_ne_nil
theorem cons_head?_tail : ∀ {l : List α} {a : α}, a ∈ head? l → a :: tail l = l
| [], a, h => by contradiction
| b :: l, a, h => by
simp? at h says simp only [head?_cons, Option.mem_def, Option.some.injEq] at h
simp [h]
#align list.cons_head'_tail List.cons_head?_tail
theorem head!_mem_head? [Inhabited α] : ∀ {l : List α}, l ≠ [] → head! l ∈ head? l
| [], h => by contradiction
| a :: l, _ => rfl
#align list.head_mem_head' List.head!_mem_head?
theorem cons_head!_tail [Inhabited α] {l : List α} (h : l ≠ []) : head! l :: tail l = l :=
cons_head?_tail (head!_mem_head? h)
#align list.cons_head_tail List.cons_head!_tail
theorem head!_mem_self [Inhabited α] {l : List α} (h : l ≠ nil) : l.head! ∈ l := by
have h' := mem_cons_self l.head! l.tail
rwa [cons_head!_tail h] at h'
#align list.head_mem_self List.head!_mem_self
theorem head_mem {l : List α} : ∀ (h : l ≠ nil), l.head h ∈ l := by
cases l <;> simp
@[simp]
theorem head?_map (f : α → β) (l) : head? (map f l) = (head? l).map f := by cases l <;> rfl
#align list.head'_map List.head?_map
theorem tail_append_of_ne_nil (l l' : List α) (h : l ≠ []) : (l ++ l').tail = l.tail ++ l' := by
cases l
· contradiction
· simp
#align list.tail_append_of_ne_nil List.tail_append_of_ne_nil
#align list.nth_le_eq_iff List.get_eq_iff
theorem get_eq_get? (l : List α) (i : Fin l.length) :
l.get i = (l.get? i).get (by simp [get?_eq_get]) := by
simp [get_eq_iff]
#align list.some_nth_le_eq List.get?_eq_get
section deprecated
set_option linter.deprecated false -- TODO(Mario): make replacements for theorems in this section
/-- nth element of a list `l` given `n < l.length`. -/
@[deprecated get (since := "2023-01-05")]
def nthLe (l : List α) (n) (h : n < l.length) : α := get l ⟨n, h⟩
#align list.nth_le List.nthLe
@[simp] theorem nthLe_tail (l : List α) (i) (h : i < l.tail.length)
(h' : i + 1 < l.length := (by simp only [length_tail] at h; omega)) :
l.tail.nthLe i h = l.nthLe (i + 1) h' := by
cases l <;> [cases h; rfl]
#align list.nth_le_tail List.nthLe_tail
theorem nthLe_cons_aux {l : List α} {a : α} {n} (hn : n ≠ 0) (h : n < (a :: l).length) :
n - 1 < l.length := by
contrapose! h
rw [length_cons]
omega
#align list.nth_le_cons_aux List.nthLe_cons_aux
| Mathlib/Data/List/Basic.lean | 892 | 901 | theorem nthLe_cons {l : List α} {a : α} {n} (hl) :
(a :: l).nthLe n hl = if hn : n = 0 then a else l.nthLe (n - 1) (nthLe_cons_aux hn hl) := by |
split_ifs with h
· simp [nthLe, h]
cases l
· rw [length_singleton, Nat.lt_succ_iff] at hl
omega
cases n
· contradiction
rfl
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Algebra.GroupWithZero.Units.Lemmas
import Mathlib.Data.Rat.Cast.Defs
#align_import data.rat.cast from "leanprover-community/mathlib"@"acebd8d49928f6ed8920e502a6c90674e75bd441"
/-!
# Casts of rational numbers into characteristic zero fields (or division rings).
-/
variable {F ι α β : Type*}
namespace Rat
open Rat
section WithDivRing
variable [DivisionRing α]
@[simp, norm_cast]
theorem cast_inj [CharZero α] : ∀ {m n : ℚ}, (m : α) = n ↔ m = n
| ⟨n₁, d₁, d₁0, c₁⟩, ⟨n₂, d₂, d₂0, c₂⟩ => by
refine ⟨fun h => ?_, congr_arg _⟩
have d₁a : (d₁ : α) ≠ 0 := Nat.cast_ne_zero.2 d₁0
have d₂a : (d₂ : α) ≠ 0 := Nat.cast_ne_zero.2 d₂0
rw [mk'_eq_divInt, mk'_eq_divInt] at h ⊢
rw [cast_divInt_of_ne_zero, cast_divInt_of_ne_zero] at h <;> simp [d₁0, d₂0] at h ⊢
rwa [eq_div_iff_mul_eq d₂a, division_def, mul_assoc, (d₁.cast_commute (d₂ : α)).inv_left₀.eq, ←
mul_assoc, ← division_def, eq_comm, eq_div_iff_mul_eq d₁a, eq_comm, ← Int.cast_natCast d₁, ←
Int.cast_mul, ← Int.cast_natCast d₂, ← Int.cast_mul, Int.cast_inj, ← mkRat_eq_iff d₁0 d₂0]
at h
#align rat.cast_inj Rat.cast_inj
theorem cast_injective [CharZero α] : Function.Injective ((↑) : ℚ → α)
| _, _ => cast_inj.1
#align rat.cast_injective Rat.cast_injective
@[simp]
| Mathlib/Data/Rat/Cast/CharZero.lean | 46 | 46 | theorem cast_eq_zero [CharZero α] {n : ℚ} : (n : α) = 0 ↔ n = 0 := by | rw [← cast_zero, cast_inj]
|
/-
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.Calculus.FDeriv.Bilinear
#align_import analysis.calculus.fderiv.mul from "leanprover-community/mathlib"@"d608fc5d4e69d4cc21885913fb573a88b0deb521"
/-!
# 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 scoped Classical
open Filter Asymptotics ContinuousLinearMap Set Metric Topology NNReal ENNReal
noncomputable section
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 {G' : Type*} [NormedAddCommGroup G'] [NormedSpace 𝕜 G']
variable {f f₀ f₁ g : E → F}
variable {f' f₀' f₁' g' : E →L[𝕜] F}
variable (e : E →L[𝕜] F)
variable {x : E}
variable {s t : Set E}
variable {L L₁ L₂ : Filter 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}
@[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 :=
(isBoundedBilinearMap_comp.hasStrictFDerivAt (c x, d x)).comp x <| hc.prod hd
#align has_strict_fderiv_at.clm_comp HasStrictFDerivAt.clm_comp
@[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 :=
(isBoundedBilinearMap_comp.hasFDerivAt (c x, d x)).comp_hasFDerivWithinAt x <| hc.prod hd
#align has_fderiv_within_at.clm_comp HasFDerivWithinAt.clm_comp
@[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 :=
(isBoundedBilinearMap_comp.hasFDerivAt (c x, d x)).comp x <| hc.prod hd
#align has_fderiv_at.clm_comp HasFDerivAt.clm_comp
@[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
#align differentiable_within_at.clm_comp DifferentiableWithinAt.clm_comp
@[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
#align differentiable_at.clm_comp DifferentiableAt.clm_comp
@[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)
#align differentiable_on.clm_comp DifferentiableOn.clm_comp
@[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)
#align differentiable.clm_comp Differentiable.clm_comp
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
#align fderiv_within_clm_comp fderivWithin_clm_comp
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
#align fderiv_clm_comp fderiv_clm_comp
@[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.prod hu)
#align has_strict_fderiv_at.clm_apply HasStrictFDerivAt.clm_apply
@[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 :=
(isBoundedBilinearMap_apply.hasFDerivAt (c x, u x)).comp_hasFDerivWithinAt x (hc.prod hu)
#align has_fderiv_within_at.clm_apply HasFDerivWithinAt.clm_apply
@[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 :=
(isBoundedBilinearMap_apply.hasFDerivAt (c x, u x)).comp x (hc.prod hu)
#align has_fderiv_at.clm_apply HasFDerivAt.clm_apply
@[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
#align differentiable_within_at.clm_apply DifferentiableWithinAt.clm_apply
@[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
#align differentiable_at.clm_apply DifferentiableAt.clm_apply
@[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)
#align differentiable_on.clm_apply DifferentiableOn.clm_apply
@[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)
#align differentiable.clm_apply Differentiable.clm_apply
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
#align fderiv_within_clm_apply fderivWithin_clm_apply
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
#align fderiv_clm_apply fderiv_clm_apply
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`. -/
| Mathlib/Analysis/Calculus/FDeriv/Mul.lean | 230 | 233 | 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]
|
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Yuyang Zhao
-/
import Mathlib.Algebra.GroupWithZero.Defs
import Mathlib.Algebra.Order.Monoid.Unbundled.Defs
import Mathlib.Tactic.GCongr.Core
#align_import algebra.order.ring.lemmas from "leanprover-community/mathlib"@"44e29dbcff83ba7114a464d592b8c3743987c1e5"
/-!
# Monotonicity of multiplication by positive elements
This file defines typeclasses to reason about monotonicity of the operations
* `b ↦ a * b`, "left multiplication"
* `a ↦ a * b`, "right multiplication"
We use eight typeclasses to encode the various properties we care about for those two operations.
These typeclasses are meant to be mostly internal to this file, to set up each lemma in the
appropriate generality.
Less granular typeclasses like `OrderedAddCommMonoid`, `LinearOrderedField` should be enough for
most purposes, and the system is set up so that they imply the correct granular typeclasses here.
If those are enough for you, you may stop reading here! Else, beware that what follows is a bit
technical.
## Definitions
In all that follows, `α` is an orders which has a `0` and a multiplication. Note however that we do
not use lawfulness of this action in most of the file. Hence `*` should be considered here as a
mostly arbitrary function `α → α → α`.
We use the following four typeclasses to reason about left multiplication (`b ↦ a * b`):
* `PosMulMono`: If `a ≥ 0`, then `b₁ ≤ b₂ → a * b₁ ≤ a * b₂`.
* `PosMulStrictMono`: If `a > 0`, then `b₁ < b₂ → a * b₁ < a * b₂`.
* `PosMulReflectLT`: If `a ≥ 0`, then `a * b₁ < a * b₂ → b₁ < b₂`.
* `PosMulReflectLE`: If `a > 0`, then `a * b₁ ≤ a * b₂ → b₁ ≤ b₂`.
We use the following four typeclasses to reason about right multiplication (`a ↦ a * b`):
* `MulPosMono`: If `b ≥ 0`, then `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b`.
* `MulPosStrictMono`: If `b > 0`, then `a₁ < a₂ → a₁ * b < a₂ * b`.
* `MulPosReflectLT`: If `b ≥ 0`, then `a₁ * b < a₂ * b → a₁ < a₂`.
* `MulPosReflectLE`: If `b > 0`, then `a₁ * b ≤ a₂ * b → a₁ ≤ a₂`.
## Implications
As `α` gets more and more structure, those typeclasses end up being equivalent. The commonly used
implications are:
* When `α` is a partial order:
* `PosMulStrictMono → PosMulMono`
* `MulPosStrictMono → MulPosMono`
* `PosMulReflectLE → PosMulReflectLT`
* `MulPosReflectLE → MulPosReflectLT`
* When `α` is a linear order:
* `PosMulStrictMono → PosMulReflectLE`
* `MulPosStrictMono → MulPosReflectLE` .
* When the multiplication of `α` is commutative:
* `PosMulMono → MulPosMono`
* `PosMulStrictMono → MulPosStrictMono`
* `PosMulReflectLE → MulPosReflectLE`
* `PosMulReflectLT → MulPosReflectLT`
Further, the bundled non-granular typeclasses imply the granular ones like so:
* `OrderedSemiring → PosMulMono`
* `OrderedSemiring → MulPosMono`
* `StrictOrderedSemiring → PosMulStrictMono`
* `StrictOrderedSemiring → MulPosStrictMono`
All these are registered as instances, which means that in practice you should not worry about these
implications. However, if you encounter a case where you think a statement is true but not covered
by the current implications, please bring it up on Zulip!
## Notation
The following is local notation in this file:
* `α≥0`: `{x : α // 0 ≤ x}`
* `α>0`: `{x : α // 0 < x}`
See https://leanprover.zulipchat.com/#narrow/stream/113488-general/topic/notation.20for.20positive.20elements
for a discussion about this notation, and whether to enable it globally (note that the notation is
currently global but broken, hence actually only works locally).
-/
variable (α : Type*)
set_option quotPrecheck false in
/-- Local notation for the nonnegative elements of a type `α`. TODO: actually make local. -/
notation "α≥0" => { x : α // 0 ≤ x }
set_option quotPrecheck false in
/-- Local notation for the positive elements of a type `α`. TODO: actually make local. -/
notation "α>0" => { x : α // 0 < x }
section Abbreviations
variable [Mul α] [Zero α] [Preorder α]
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the left,
namely `b₁ ≤ b₂ → a * b₁ ≤ a * b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev PosMulMono : Prop :=
CovariantClass α≥0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono PosMulMono
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the right,
namely `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev MulPosMono : Prop :=
CovariantClass α≥0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono MulPosMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the left,
namely `b₁ < b₂ → a * b₁ < a * b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev PosMulStrictMono : Prop :=
CovariantClass α>0 α (fun x y => x * y) (· < ·)
#align pos_mul_strict_mono PosMulStrictMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the right,
namely `a₁ < a₂ → a₁ * b < a₂ * b` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev MulPosStrictMono : Prop :=
CovariantClass α>0 α (fun x y => y * x) (· < ·)
#align mul_pos_strict_mono MulPosStrictMono
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the left, namely `a * b₁ < a * b₂ → b₁ < b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => x * y) (· < ·)
#align pos_mul_reflect_lt PosMulReflectLT
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the right, namely `a₁ * b < a₂ * b → a₁ < a₂` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => y * x) (· < ·)
#align mul_pos_reflect_lt MulPosReflectLT
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the left,
namely `a * b₁ ≤ a * b₂ → b₁ ≤ b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono_rev PosMulReflectLE
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the right,
namely `a₁ * b ≤ a₂ * b → a₁ ≤ a₂` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono_rev MulPosReflectLE
end Abbreviations
variable {α} {a b c d : α}
section MulZero
variable [Mul α] [Zero α]
section Preorder
variable [Preorder α]
instance PosMulMono.to_covariantClass_pos_mul_le [PosMulMono α] :
CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_mono.to_covariant_class_pos_mul_le PosMulMono.to_covariantClass_pos_mul_le
instance MulPosMono.to_covariantClass_pos_mul_le [MulPosMono α] :
CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_mono.to_covariant_class_pos_mul_le MulPosMono.to_covariantClass_pos_mul_le
instance PosMulReflectLT.to_contravariantClass_pos_mul_lt [PosMulReflectLT α] :
ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_reflect_lt.to_contravariant_class_pos_mul_lt PosMulReflectLT.to_contravariantClass_pos_mul_lt
instance MulPosReflectLT.to_contravariantClass_pos_mul_lt [MulPosReflectLT α] :
ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_reflect_lt.to_contravariant_class_pos_mul_lt MulPosReflectLT.to_contravariantClass_pos_mul_lt
@[gcongr]
theorem mul_le_mul_of_nonneg_left [PosMulMono α] (h : b ≤ c) (a0 : 0 ≤ a) : a * b ≤ a * c :=
@CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_left mul_le_mul_of_nonneg_left
@[gcongr]
theorem mul_le_mul_of_nonneg_right [MulPosMono α] (h : b ≤ c) (a0 : 0 ≤ a) : b * a ≤ c * a :=
@CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_right mul_le_mul_of_nonneg_right
@[gcongr]
theorem mul_lt_mul_of_pos_left [PosMulStrictMono α] (bc : b < c) (a0 : 0 < a) : a * b < a * c :=
@CovariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_left mul_lt_mul_of_pos_left
@[gcongr]
theorem mul_lt_mul_of_pos_right [MulPosStrictMono α] (bc : b < c) (a0 : 0 < a) : b * a < c * a :=
@CovariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_right mul_lt_mul_of_pos_right
theorem lt_of_mul_lt_mul_left [PosMulReflectLT α] (h : a * b < a * c) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_left lt_of_mul_lt_mul_left
theorem lt_of_mul_lt_mul_right [MulPosReflectLT α] (h : b * a < c * a) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_right lt_of_mul_lt_mul_right
theorem le_of_mul_le_mul_left [PosMulReflectLE α] (bc : a * b ≤ a * c) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_left le_of_mul_le_mul_left
theorem le_of_mul_le_mul_right [MulPosReflectLE α] (bc : b * a ≤ c * a) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_right le_of_mul_le_mul_right
alias lt_of_mul_lt_mul_of_nonneg_left := lt_of_mul_lt_mul_left
#align lt_of_mul_lt_mul_of_nonneg_left lt_of_mul_lt_mul_of_nonneg_left
alias lt_of_mul_lt_mul_of_nonneg_right := lt_of_mul_lt_mul_right
#align lt_of_mul_lt_mul_of_nonneg_right lt_of_mul_lt_mul_of_nonneg_right
alias le_of_mul_le_mul_of_pos_left := le_of_mul_le_mul_left
#align le_of_mul_le_mul_of_pos_left le_of_mul_le_mul_of_pos_left
alias le_of_mul_le_mul_of_pos_right := le_of_mul_le_mul_right
#align le_of_mul_le_mul_of_pos_right le_of_mul_le_mul_of_pos_right
@[simp]
theorem mul_lt_mul_left [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a * b < a * c ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_left mul_lt_mul_left
@[simp]
theorem mul_lt_mul_right [MulPosStrictMono α] [MulPosReflectLT α] (a0 : 0 < a) :
b * a < c * a ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_right mul_lt_mul_right
@[simp]
theorem mul_le_mul_left [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_left mul_le_mul_left
@[simp]
theorem mul_le_mul_right [MulPosMono α] [MulPosReflectLE α] (a0 : 0 < a) : b * a ≤ c * a ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_right mul_le_mul_right
alias mul_le_mul_iff_of_pos_left := mul_le_mul_left
alias mul_le_mul_iff_of_pos_right := mul_le_mul_right
alias mul_lt_mul_iff_of_pos_left := mul_lt_mul_left
alias mul_lt_mul_iff_of_pos_right := mul_lt_mul_right
theorem mul_lt_mul_of_pos_of_nonneg [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 ≤ d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans_le (mul_le_mul_of_nonneg_right h₁ d0)
#align mul_lt_mul_of_pos_of_nonneg mul_lt_mul_of_pos_of_nonneg
theorem mul_lt_mul_of_le_of_le' [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 ≤ c) : a * c < b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans_lt (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_le_of_le' mul_lt_mul_of_le_of_le'
theorem mul_lt_mul_of_nonneg_of_pos [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(a0 : 0 ≤ a) (d0 : 0 < d) : a * c < b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans_lt (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_nonneg_of_pos mul_lt_mul_of_nonneg_of_pos
theorem mul_lt_mul_of_le_of_lt' [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(b0 : 0 ≤ b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans_le (mul_le_mul_of_nonneg_left h₂ b0)
#align mul_lt_mul_of_le_of_lt' mul_lt_mul_of_le_of_lt'
theorem mul_lt_mul_of_pos_of_pos [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 < d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_pos_of_pos mul_lt_mul_of_pos_of_pos
theorem mul_lt_mul_of_lt_of_lt' [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_lt_of_lt' mul_lt_mul_of_lt_of_lt'
theorem mul_lt_of_mul_lt_of_nonneg_left [PosMulMono α] (h : a * b < c) (hdb : d ≤ b) (ha : 0 ≤ a) :
a * d < c :=
(mul_le_mul_of_nonneg_left hdb ha).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_left mul_lt_of_mul_lt_of_nonneg_left
theorem lt_mul_of_lt_mul_of_nonneg_left [PosMulMono α] (h : a < b * c) (hcd : c ≤ d) (hb : 0 ≤ b) :
a < b * d :=
h.trans_le <| mul_le_mul_of_nonneg_left hcd hb
#align lt_mul_of_lt_mul_of_nonneg_left lt_mul_of_lt_mul_of_nonneg_left
theorem mul_lt_of_mul_lt_of_nonneg_right [MulPosMono α] (h : a * b < c) (hda : d ≤ a) (hb : 0 ≤ b) :
d * b < c :=
(mul_le_mul_of_nonneg_right hda hb).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_right mul_lt_of_mul_lt_of_nonneg_right
theorem lt_mul_of_lt_mul_of_nonneg_right [MulPosMono α] (h : a < b * c) (hbd : b ≤ d) (hc : 0 ≤ c) :
a < d * c :=
h.trans_le <| mul_le_mul_of_nonneg_right hbd hc
#align lt_mul_of_lt_mul_of_nonneg_right lt_mul_of_lt_mul_of_nonneg_right
end Preorder
section LinearOrder
variable [LinearOrder α]
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulReflectLE [PosMulStrictMono α] :
PosMulReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosReflectLE [MulPosStrictMono α] :
MulPosReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
theorem PosMulReflectLE.toPosMulStrictMono [PosMulReflectLE α] : PosMulStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_mono_rev.to_pos_mul_strict_mono PosMulReflectLE.toPosMulStrictMono
theorem MulPosReflectLE.toMulPosStrictMono [MulPosReflectLE α] : MulPosStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_mono_rev.to_mul_pos_strict_mono MulPosReflectLE.toMulPosStrictMono
theorem posMulStrictMono_iff_posMulReflectLE : PosMulStrictMono α ↔ PosMulReflectLE α :=
⟨@PosMulStrictMono.toPosMulReflectLE _ _ _ _, @PosMulReflectLE.toPosMulStrictMono _ _ _ _⟩
#align pos_mul_strict_mono_iff_pos_mul_mono_rev posMulStrictMono_iff_posMulReflectLE
theorem mulPosStrictMono_iff_mulPosReflectLE : MulPosStrictMono α ↔ MulPosReflectLE α :=
⟨@MulPosStrictMono.toMulPosReflectLE _ _ _ _, @MulPosReflectLE.toMulPosStrictMono _ _ _ _⟩
#align mul_pos_strict_mono_iff_mul_pos_mono_rev mulPosStrictMono_iff_mulPosReflectLE
theorem PosMulReflectLT.toPosMulMono [PosMulReflectLT α] : PosMulMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_reflect_lt.to_pos_mul_mono PosMulReflectLT.toPosMulMono
theorem MulPosReflectLT.toMulPosMono [MulPosReflectLT α] : MulPosMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_reflect_lt.to_mul_pos_mono MulPosReflectLT.toMulPosMono
theorem PosMulMono.toPosMulReflectLT [PosMulMono α] : PosMulReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align pos_mul_mono.to_pos_mul_reflect_lt PosMulMono.toPosMulReflectLT
theorem MulPosMono.toMulPosReflectLT [MulPosMono α] : MulPosReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align mul_pos_mono.to_mul_pos_reflect_lt MulPosMono.toMulPosReflectLT
/- TODO: Currently, only one in four of the above are made instances; we could consider making
both directions of `covariant_le_iff_contravariant_lt` and `covariant_lt_iff_contravariant_le`
instances, then all of the above become redundant instances, but there are performance issues. -/
theorem posMulMono_iff_posMulReflectLT : PosMulMono α ↔ PosMulReflectLT α :=
⟨@PosMulMono.toPosMulReflectLT _ _ _ _, @PosMulReflectLT.toPosMulMono _ _ _ _⟩
#align pos_mul_mono_iff_pos_mul_reflect_lt posMulMono_iff_posMulReflectLT
theorem mulPosMono_iff_mulPosReflectLT : MulPosMono α ↔ MulPosReflectLT α :=
⟨@MulPosMono.toMulPosReflectLT _ _ _ _, @MulPosReflectLT.toMulPosMono _ _ _ _⟩
#align mul_pos_mono_iff_mul_pos_reflect_lt mulPosMono_iff_mulPosReflectLT
end LinearOrder
end MulZero
section MulZeroClass
variable [MulZeroClass α]
section Preorder
variable [Preorder α]
/-- Assumes left covariance. -/
| Mathlib/Algebra/Order/GroupWithZero/Unbundled.lean | 402 | 403 | theorem Left.mul_pos [PosMulStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by |
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
|
/-
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.BigOperators.Finprod
import Mathlib.SetTheory.Ordinal.Basic
import Mathlib.Topology.ContinuousFunction.Algebra
import Mathlib.Topology.Compactness.Paracompact
import Mathlib.Topology.ShrinkingLemma
import Mathlib.Topology.UrysohnsLemma
#align_import topology.partition_of_unity from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Continuous partition of unity
In this file we define `PartitionOfUnity (ι X : Type*) [TopologicalSpace X] (s : Set X := univ)`
to be a continuous partition of unity on `s` indexed by `ι`. More precisely,
`f : PartitionOfUnity ι X s` is a collection of continuous functions `f i : C(X, ℝ)`, `i : ι`,
such that
* the supports of `f i` form a locally finite family of sets;
* each `f i` is nonnegative;
* `∑ᶠ i, f i x = 1` for all `x ∈ s`;
* `∑ᶠ i, f i x ≤ 1` for all `x : X`.
In the case `s = univ` the last assumption follows from the previous one but it is convenient to
have this assumption in the case `s ≠ univ`.
We also define a bump function covering,
`BumpCovering (ι X : Type*) [TopologicalSpace X] (s : Set X := univ)`, to be a collection of
functions `f i : C(X, ℝ)`, `i : ι`, such that
* the supports of `f i` form a locally finite family of sets;
* each `f i` is nonnegative;
* for each `x ∈ s` there exists `i : ι` such that `f i y = 1` in a neighborhood of `x`.
The term is motivated by the smooth case.
If `f` is a bump function covering indexed by a linearly ordered type, then
`g i x = f i x * ∏ᶠ j < i, (1 - f j x)` is a partition of unity, see
`BumpCovering.toPartitionOfUnity`. Note that only finitely many terms `1 - f j x` are not equal
to one, so this product is well-defined.
Note that `g i x = ∏ᶠ j ≤ i, (1 - f j x) - ∏ᶠ j < i, (1 - f j x)`, so most terms in the sum
`∑ᶠ i, g i x` cancel, and we get `∑ᶠ i, g i x = 1 - ∏ᶠ i, (1 - f i x)`, and the latter product
equals zero because one of `f i x` is equal to one.
We say that a partition of unity or a bump function covering `f` is *subordinate* to a family of
sets `U i`, `i : ι`, if the closure of the support of each `f i` is included in `U i`. We use
Urysohn's Lemma to prove that a locally finite open covering of a normal topological space admits a
subordinate bump function covering (hence, a subordinate partition of unity), see
`BumpCovering.exists_isSubordinate_of_locallyFinite`. If `X` is a paracompact space, then any
open covering admits a locally finite refinement, hence it admits a subordinate bump function
covering and a subordinate partition of unity, see `BumpCovering.exists_isSubordinate`.
We also provide two slightly more general versions of these lemmas,
`BumpCovering.exists_isSubordinate_of_locallyFinite_of_prop` and
`BumpCovering.exists_isSubordinate_of_prop`, to be used later in the construction of a smooth
partition of unity.
## Implementation notes
Most (if not all) books only define a partition of unity of the whole space. However, quite a few
proofs only deal with `f i` such that `tsupport (f i)` meets a specific closed subset, and
it is easier to formalize these proofs if we don't have other functions right away.
We use `WellOrderingRel j i` instead of `j < i` in the definition of
`BumpCovering.toPartitionOfUnity` to avoid a `[LinearOrder ι]` assumption. While
`WellOrderingRel j i` is a well order, not only a strict linear order, we never use this property.
## Tags
partition of unity, bump function, Urysohn's lemma, normal space, paracompact space
-/
universe u v
open Function Set Filter
open scoped Classical
open Topology
noncomputable section
/-- A continuous partition of unity on a set `s : Set X` is a collection of continuous functions
`f i` such that
* the supports of `f i` form a locally finite family of sets, i.e., for every point `x : X` there
exists a neighborhood `U ∋ x` such that all but finitely many functions `f i` are zero on `U`;
* the functions `f i` are nonnegative;
* the sum `∑ᶠ i, f i x` is equal to one for every `x ∈ s` and is less than or equal to one
otherwise.
If `X` is a normal paracompact space, then `PartitionOfUnity.exists_isSubordinate` guarantees
that for every open covering `U : Set (Set X)` of `s` there exists a partition of unity that is
subordinate to `U`.
-/
structure PartitionOfUnity (ι X : Type*) [TopologicalSpace X] (s : Set X := univ) where
toFun : ι → C(X, ℝ)
locallyFinite' : LocallyFinite fun i => support (toFun i)
nonneg' : 0 ≤ toFun
sum_eq_one' : ∀ x ∈ s, ∑ᶠ i, toFun i x = 1
sum_le_one' : ∀ x, ∑ᶠ i, toFun i x ≤ 1
#align partition_of_unity PartitionOfUnity
/-- A `BumpCovering ι X s` is an indexed family of functions `f i`, `i : ι`, such that
* the supports of `f i` form a locally finite family of sets, i.e., for every point `x : X` there
exists a neighborhood `U ∋ x` such that all but finitely many functions `f i` are zero on `U`;
* for all `i`, `x` we have `0 ≤ f i x ≤ 1`;
* each point `x ∈ s` belongs to the interior of `{x | f i x = 1}` for some `i`.
One of the main use cases for a `BumpCovering` is to define a `PartitionOfUnity`, see
`BumpCovering.toPartitionOfUnity`, but some proofs can directly use a `BumpCovering` instead of
a `PartitionOfUnity`.
If `X` is a normal paracompact space, then `BumpCovering.exists_isSubordinate` guarantees that for
every open covering `U : Set (Set X)` of `s` there exists a `BumpCovering` of `s` that is
subordinate to `U`.
-/
structure BumpCovering (ι X : Type*) [TopologicalSpace X] (s : Set X := univ) where
toFun : ι → C(X, ℝ)
locallyFinite' : LocallyFinite fun i => support (toFun i)
nonneg' : 0 ≤ toFun
le_one' : toFun ≤ 1
eventuallyEq_one' : ∀ x ∈ s, ∃ i, toFun i =ᶠ[𝓝 x] 1
#align bump_covering BumpCovering
variable {ι : Type u} {X : Type v} [TopologicalSpace X]
namespace PartitionOfUnity
variable {E : Type*} [AddCommMonoid E] [SMulWithZero ℝ E] [TopologicalSpace E] [ContinuousSMul ℝ E]
{s : Set X} (f : PartitionOfUnity ι X s)
instance : FunLike (PartitionOfUnity ι X s) ι C(X, ℝ) where
coe := toFun
coe_injective' := fun f g h ↦ by cases f; cases g; congr
protected theorem locallyFinite : LocallyFinite fun i => support (f i) :=
f.locallyFinite'
#align partition_of_unity.locally_finite PartitionOfUnity.locallyFinite
theorem locallyFinite_tsupport : LocallyFinite fun i => tsupport (f i) :=
f.locallyFinite.closure
#align partition_of_unity.locally_finite_tsupport PartitionOfUnity.locallyFinite_tsupport
theorem nonneg (i : ι) (x : X) : 0 ≤ f i x :=
f.nonneg' i x
#align partition_of_unity.nonneg PartitionOfUnity.nonneg
theorem sum_eq_one {x : X} (hx : x ∈ s) : ∑ᶠ i, f i x = 1 :=
f.sum_eq_one' x hx
#align partition_of_unity.sum_eq_one PartitionOfUnity.sum_eq_one
/-- If `f` is a partition of unity on `s`, then for every `x ∈ s` there exists an index `i` such
that `0 < f i x`. -/
theorem exists_pos {x : X} (hx : x ∈ s) : ∃ i, 0 < f i x := by
have H := f.sum_eq_one hx
contrapose! H
simpa only [fun i => (H i).antisymm (f.nonneg i x), finsum_zero] using zero_ne_one
#align partition_of_unity.exists_pos PartitionOfUnity.exists_pos
theorem sum_le_one (x : X) : ∑ᶠ i, f i x ≤ 1 :=
f.sum_le_one' x
#align partition_of_unity.sum_le_one PartitionOfUnity.sum_le_one
theorem sum_nonneg (x : X) : 0 ≤ ∑ᶠ i, f i x :=
finsum_nonneg fun i => f.nonneg i x
#align partition_of_unity.sum_nonneg PartitionOfUnity.sum_nonneg
theorem le_one (i : ι) (x : X) : f i x ≤ 1 :=
(single_le_finsum i (f.locallyFinite.point_finite x) fun j => f.nonneg j x).trans (f.sum_le_one x)
#align partition_of_unity.le_one PartitionOfUnity.le_one
section finsupport
variable {s : Set X} (ρ : PartitionOfUnity ι X s) (x₀ : X)
/-- The support of a partition of unity at a point `x₀` as a `Finset`.
This is the set of `i : ι` such that `x₀ ∈ support f i`, i.e. `f i ≠ x₀`. -/
def finsupport : Finset ι := (ρ.locallyFinite.point_finite x₀).toFinset
@[simp]
theorem mem_finsupport (x₀ : X) {i} :
i ∈ ρ.finsupport x₀ ↔ i ∈ support fun i ↦ ρ i x₀ := by
simp only [finsupport, mem_support, Finite.mem_toFinset, mem_setOf_eq]
@[simp]
theorem coe_finsupport (x₀ : X) :
(ρ.finsupport x₀ : Set ι) = support fun i ↦ ρ i x₀ := by
ext
rw [Finset.mem_coe, mem_finsupport]
variable {x₀ : X}
theorem sum_finsupport (hx₀ : x₀ ∈ s) : ∑ i ∈ ρ.finsupport x₀, ρ i x₀ = 1 := by
rw [← ρ.sum_eq_one hx₀, finsum_eq_sum_of_support_subset _ (ρ.coe_finsupport x₀).superset]
theorem sum_finsupport' (hx₀ : x₀ ∈ s) {I : Finset ι} (hI : ρ.finsupport x₀ ⊆ I) :
∑ i ∈ I, ρ i x₀ = 1 := by
classical
rw [← Finset.sum_sdiff hI, ρ.sum_finsupport hx₀]
suffices ∑ i ∈ I \ ρ.finsupport x₀, (ρ i) x₀ = ∑ i ∈ I \ ρ.finsupport x₀, 0 by
rw [this, add_left_eq_self, Finset.sum_const_zero]
apply Finset.sum_congr rfl
rintro x hx
simp only [Finset.mem_sdiff, ρ.mem_finsupport, mem_support, Classical.not_not] at hx
exact hx.2
theorem sum_finsupport_smul_eq_finsum {M : Type*} [AddCommGroup M] [Module ℝ M] (φ : ι → X → M) :
∑ i ∈ ρ.finsupport x₀, ρ i x₀ • φ i x₀ = ∑ᶠ i, ρ i x₀ • φ i x₀ := by
apply (finsum_eq_sum_of_support_subset _ _).symm
have : (fun i ↦ (ρ i) x₀ • φ i x₀) = (fun i ↦ (ρ i) x₀) • (fun i ↦ φ i x₀) :=
funext fun _ => (Pi.smul_apply' _ _ _).symm
rw [ρ.coe_finsupport x₀, this, support_smul]
exact inter_subset_left
end finsupport
section fintsupport -- partitions of unity have locally finite `tsupport`
variable {s : Set X} (ρ : PartitionOfUnity ι X s) (x₀ : X)
/-- The `tsupport`s of a partition of unity are locally finite. -/
theorem finite_tsupport : {i | x₀ ∈ tsupport (ρ i)}.Finite := by
rcases ρ.locallyFinite x₀ with ⟨t, t_in, ht⟩
apply ht.subset
rintro i hi
simp only [inter_comm]
exact mem_closure_iff_nhds.mp hi t t_in
/-- The tsupport of a partition of unity at a point `x₀` as a `Finset`.
This is the set of `i : ι` such that `x₀ ∈ tsupport f i`. -/
def fintsupport (x₀ : X) : Finset ι :=
(ρ.finite_tsupport x₀).toFinset
theorem mem_fintsupport_iff (i : ι) : i ∈ ρ.fintsupport x₀ ↔ x₀ ∈ tsupport (ρ i) :=
Finite.mem_toFinset _
theorem eventually_fintsupport_subset :
∀ᶠ y in 𝓝 x₀, ρ.fintsupport y ⊆ ρ.fintsupport x₀ := by
apply (ρ.locallyFinite.closure.eventually_subset (fun _ ↦ isClosed_closure) x₀).mono
intro y hy z hz
rw [PartitionOfUnity.mem_fintsupport_iff] at *
exact hy hz
theorem finsupport_subset_fintsupport : ρ.finsupport x₀ ⊆ ρ.fintsupport x₀ := fun i hi ↦ by
rw [ρ.mem_fintsupport_iff]
apply subset_closure
exact (ρ.mem_finsupport x₀).mp hi
theorem eventually_finsupport_subset : ∀ᶠ y in 𝓝 x₀, ρ.finsupport y ⊆ ρ.fintsupport x₀ :=
(ρ.eventually_fintsupport_subset x₀).mono
fun y hy ↦ (ρ.finsupport_subset_fintsupport y).trans hy
end fintsupport
/-- If `f` is a partition of unity on `s : Set X` and `g : X → E` is continuous at every point of
the topological support of some `f i`, then `fun x ↦ f i x • g x` is continuous on the whole space.
-/
theorem continuous_smul {g : X → E} {i : ι} (hg : ∀ x ∈ tsupport (f i), ContinuousAt g x) :
Continuous fun x => f i x • g x :=
continuous_of_tsupport fun x hx =>
((f i).continuousAt x).smul <| hg x <| tsupport_smul_subset_left _ _ hx
#align partition_of_unity.continuous_smul PartitionOfUnity.continuous_smul
/-- If `f` is a partition of unity on a set `s : Set X` and `g : ι → X → E` is a family of functions
such that each `g i` is continuous at every point of the topological support of `f i`, then the sum
`fun x ↦ ∑ᶠ i, f i x • g i x` is continuous on the whole space. -/
theorem continuous_finsum_smul [ContinuousAdd E] {g : ι → X → E}
(hg : ∀ (i), ∀ x ∈ tsupport (f i), ContinuousAt (g i) x) :
Continuous fun x => ∑ᶠ i, f i x • g i x :=
(continuous_finsum fun i => f.continuous_smul (hg i)) <|
f.locallyFinite.subset fun _ => support_smul_subset_left _ _
#align partition_of_unity.continuous_finsum_smul PartitionOfUnity.continuous_finsum_smul
/-- A partition of unity `f i` is subordinate to a family of sets `U i` indexed by the same type if
for each `i` the closure of the support of `f i` is a subset of `U i`. -/
def IsSubordinate (U : ι → Set X) : Prop :=
∀ i, tsupport (f i) ⊆ U i
#align partition_of_unity.is_subordinate PartitionOfUnity.IsSubordinate
variable {f}
theorem exists_finset_nhd' {s : Set X} (ρ : PartitionOfUnity ι X s) (x₀ : X) :
∃ I : Finset ι, (∀ᶠ x in 𝓝[s] x₀, ∑ i ∈ I, ρ i x = 1) ∧
∀ᶠ x in 𝓝 x₀, support (ρ · x) ⊆ I := by
rcases ρ.locallyFinite.exists_finset_support x₀ with ⟨I, hI⟩
refine ⟨I, eventually_nhdsWithin_iff.mpr (hI.mono fun x hx x_in ↦ ?_), hI⟩
have : ∑ᶠ i : ι, ρ i x = ∑ i ∈ I, ρ i x := finsum_eq_sum_of_support_subset _ hx
rwa [eq_comm, ρ.sum_eq_one x_in] at this
theorem exists_finset_nhd (ρ : PartitionOfUnity ι X univ) (x₀ : X) :
∃ I : Finset ι, ∀ᶠ x in 𝓝 x₀, ∑ i ∈ I, ρ i x = 1 ∧ support (ρ · x) ⊆ I := by
rcases ρ.exists_finset_nhd' x₀ with ⟨I, H⟩
use I
rwa [nhdsWithin_univ, ← eventually_and] at H
theorem exists_finset_nhd_support_subset {U : ι → Set X} (hso : f.IsSubordinate U)
(ho : ∀ i, IsOpen (U i)) (x : X) :
∃ is : Finset ι, ∃ n ∈ 𝓝 x, n ⊆ ⋂ i ∈ is, U i ∧ ∀ z ∈ n, (support (f · z)) ⊆ is :=
f.locallyFinite.exists_finset_nhd_support_subset hso ho x
#align partition_of_unity.exists_finset_nhd_support_subset PartitionOfUnity.exists_finset_nhd_support_subset
/-- If `f` is a partition of unity that is subordinate to a family of open sets `U i` and
`g : ι → X → E` is a family of functions such that each `g i` is continuous on `U i`, then the sum
`fun x ↦ ∑ᶠ i, f i x • g i x` is a continuous function. -/
theorem IsSubordinate.continuous_finsum_smul [ContinuousAdd E] {U : ι → Set X}
(ho : ∀ i, IsOpen (U i)) (hf : f.IsSubordinate U) {g : ι → X → E}
(hg : ∀ i, ContinuousOn (g i) (U i)) : Continuous fun x => ∑ᶠ i, f i x • g i x :=
f.continuous_finsum_smul fun i _ hx => (hg i).continuousAt <| (ho i).mem_nhds <| hf i hx
#align partition_of_unity.is_subordinate.continuous_finsum_smul PartitionOfUnity.IsSubordinate.continuous_finsum_smul
end PartitionOfUnity
namespace BumpCovering
variable {s : Set X} (f : BumpCovering ι X s)
instance : FunLike (BumpCovering ι X s) ι C(X, ℝ) where
coe := toFun
coe_injective' := fun f g h ↦ by cases f; cases g; congr
protected theorem locallyFinite : LocallyFinite fun i => support (f i) :=
f.locallyFinite'
#align bump_covering.locally_finite BumpCovering.locallyFinite
theorem locallyFinite_tsupport : LocallyFinite fun i => tsupport (f i) :=
f.locallyFinite.closure
#align bump_covering.locally_finite_tsupport BumpCovering.locallyFinite_tsupport
protected theorem point_finite (x : X) : { i | f i x ≠ 0 }.Finite :=
f.locallyFinite.point_finite x
#align bump_covering.point_finite BumpCovering.point_finite
theorem nonneg (i : ι) (x : X) : 0 ≤ f i x :=
f.nonneg' i x
#align bump_covering.nonneg BumpCovering.nonneg
theorem le_one (i : ι) (x : X) : f i x ≤ 1 :=
f.le_one' i x
#align bump_covering.le_one BumpCovering.le_one
/-- A `BumpCovering` that consists of a single function, uniformly equal to one, defined as an
example for `Inhabited` instance. -/
protected def single (i : ι) (s : Set X) : BumpCovering ι X s where
toFun := Pi.single i 1
locallyFinite' x := by
refine ⟨univ, univ_mem, (finite_singleton i).subset ?_⟩
rintro j ⟨x, hx, -⟩
contrapose! hx
rw [mem_singleton_iff] at hx
simp [hx]
nonneg' := le_update_iff.2 ⟨fun x => zero_le_one, fun _ _ => le_rfl⟩
le_one' := update_le_iff.2 ⟨le_rfl, fun _ _ _ => zero_le_one⟩
eventuallyEq_one' x _ := ⟨i, by rw [Pi.single_eq_same, ContinuousMap.coe_one]⟩
#align bump_covering.single BumpCovering.single
@[simp]
theorem coe_single (i : ι) (s : Set X) : ⇑(BumpCovering.single i s) = Pi.single i 1 := rfl
#align bump_covering.coe_single BumpCovering.coe_single
instance [Inhabited ι] : Inhabited (BumpCovering ι X s) :=
⟨BumpCovering.single default s⟩
/-- A collection of bump functions `f i` is subordinate to a family of sets `U i` indexed by the
same type if for each `i` the closure of the support of `f i` is a subset of `U i`. -/
def IsSubordinate (f : BumpCovering ι X s) (U : ι → Set X) : Prop :=
∀ i, tsupport (f i) ⊆ U i
#align bump_covering.is_subordinate BumpCovering.IsSubordinate
theorem IsSubordinate.mono {f : BumpCovering ι X s} {U V : ι → Set X} (hU : f.IsSubordinate U)
(hV : ∀ i, U i ⊆ V i) : f.IsSubordinate V :=
fun i => Subset.trans (hU i) (hV i)
#align bump_covering.is_subordinate.mono BumpCovering.IsSubordinate.mono
/-- If `X` is a normal topological space and `U i`, `i : ι`, is a locally finite open covering of a
closed set `s`, then there exists a `BumpCovering ι X s` that is subordinate to `U`. If `X` is a
paracompact space, then the assumption `hf : LocallyFinite U` can be omitted, see
`BumpCovering.exists_isSubordinate`. This version assumes that `p : (X → ℝ) → Prop` is a predicate
that satisfies Urysohn's lemma, and provides a `BumpCovering` such that each function of the
covering satisfies `p`. -/
theorem exists_isSubordinate_of_locallyFinite_of_prop [NormalSpace X] (p : (X → ℝ) → Prop)
(h01 : ∀ s t, IsClosed s → IsClosed t → Disjoint s t →
∃ f : C(X, ℝ), p f ∧ EqOn f 0 s ∧ EqOn f 1 t ∧ ∀ x, f x ∈ Icc (0 : ℝ) 1)
(hs : IsClosed s) (U : ι → Set X) (ho : ∀ i, IsOpen (U i)) (hf : LocallyFinite U)
(hU : s ⊆ ⋃ i, U i) : ∃ f : BumpCovering ι X s, (∀ i, p (f i)) ∧ f.IsSubordinate U := by
rcases exists_subset_iUnion_closure_subset hs ho (fun x _ => hf.point_finite x) hU with
⟨V, hsV, hVo, hVU⟩
have hVU' : ∀ i, V i ⊆ U i := fun i => Subset.trans subset_closure (hVU i)
rcases exists_subset_iUnion_closure_subset hs hVo (fun x _ => (hf.subset hVU').point_finite x)
hsV with
⟨W, hsW, hWo, hWV⟩
choose f hfp hf0 hf1 hf01 using fun i =>
h01 _ _ (isClosed_compl_iff.2 <| hVo i) isClosed_closure
(disjoint_right.2 fun x hx => Classical.not_not.2 (hWV i hx))
have hsupp : ∀ i, support (f i) ⊆ V i := fun i => support_subset_iff'.2 (hf0 i)
refine ⟨⟨f, hf.subset fun i => Subset.trans (hsupp i) (hVU' i), fun i x => (hf01 i x).1,
fun i x => (hf01 i x).2, fun x hx => ?_⟩,
hfp, fun i => Subset.trans (closure_mono (hsupp i)) (hVU i)⟩
rcases mem_iUnion.1 (hsW hx) with ⟨i, hi⟩
exact ⟨i, ((hf1 i).mono subset_closure).eventuallyEq_of_mem ((hWo i).mem_nhds hi)⟩
#align bump_covering.exists_is_subordinate_of_locally_finite_of_prop BumpCovering.exists_isSubordinate_of_locallyFinite_of_prop
/-- If `X` is a normal topological space and `U i`, `i : ι`, is a locally finite open covering of a
closed set `s`, then there exists a `BumpCovering ι X s` that is subordinate to `U`. If `X` is a
paracompact space, then the assumption `hf : LocallyFinite U` can be omitted, see
`BumpCovering.exists_isSubordinate`. -/
theorem exists_isSubordinate_of_locallyFinite [NormalSpace X] (hs : IsClosed s) (U : ι → Set X)
(ho : ∀ i, IsOpen (U i)) (hf : LocallyFinite U) (hU : s ⊆ ⋃ i, U i) :
∃ f : BumpCovering ι X s, f.IsSubordinate U :=
let ⟨f, _, hfU⟩ :=
exists_isSubordinate_of_locallyFinite_of_prop (fun _ => True)
(fun _ _ hs ht hd =>
(exists_continuous_zero_one_of_isClosed hs ht hd).imp fun _ hf => ⟨trivial, hf⟩)
hs U ho hf hU
⟨f, hfU⟩
#align bump_covering.exists_is_subordinate_of_locally_finite BumpCovering.exists_isSubordinate_of_locallyFinite
/-- If `X` is a paracompact normal topological space and `U` is an open covering of a closed set
`s`, then there exists a `BumpCovering ι X s` that is subordinate to `U`. This version assumes that
`p : (X → ℝ) → Prop` is a predicate that satisfies Urysohn's lemma, and provides a
`BumpCovering` such that each function of the covering satisfies `p`. -/
theorem exists_isSubordinate_of_prop [NormalSpace X] [ParacompactSpace X] (p : (X → ℝ) → Prop)
(h01 : ∀ s t, IsClosed s → IsClosed t → Disjoint s t →
∃ f : C(X, ℝ), p f ∧ EqOn f 0 s ∧ EqOn f 1 t ∧ ∀ x, f x ∈ Icc (0 : ℝ) 1)
(hs : IsClosed s) (U : ι → Set X) (ho : ∀ i, IsOpen (U i)) (hU : s ⊆ ⋃ i, U i) :
∃ f : BumpCovering ι X s, (∀ i, p (f i)) ∧ f.IsSubordinate U := by
rcases precise_refinement_set hs _ ho hU with ⟨V, hVo, hsV, hVf, hVU⟩
rcases exists_isSubordinate_of_locallyFinite_of_prop p h01 hs V hVo hVf hsV with ⟨f, hfp, hf⟩
exact ⟨f, hfp, hf.mono hVU⟩
#align bump_covering.exists_is_subordinate_of_prop BumpCovering.exists_isSubordinate_of_prop
/-- If `X` is a paracompact normal topological space and `U` is an open covering of a closed set
`s`, then there exists a `BumpCovering ι X s` that is subordinate to `U`. -/
theorem exists_isSubordinate [NormalSpace X] [ParacompactSpace X] (hs : IsClosed s) (U : ι → Set X)
(ho : ∀ i, IsOpen (U i)) (hU : s ⊆ ⋃ i, U i) : ∃ f : BumpCovering ι X s, f.IsSubordinate U := by
rcases precise_refinement_set hs _ ho hU with ⟨V, hVo, hsV, hVf, hVU⟩
rcases exists_isSubordinate_of_locallyFinite hs V hVo hVf hsV with ⟨f, hf⟩
exact ⟨f, hf.mono hVU⟩
#align bump_covering.exists_is_subordinate BumpCovering.exists_isSubordinate
/-- Index of a bump function such that `fs i =ᶠ[𝓝 x] 1`. -/
def ind (x : X) (hx : x ∈ s) : ι :=
(f.eventuallyEq_one' x hx).choose
#align bump_covering.ind BumpCovering.ind
theorem eventuallyEq_one (x : X) (hx : x ∈ s) : f (f.ind x hx) =ᶠ[𝓝 x] 1 :=
(f.eventuallyEq_one' x hx).choose_spec
#align bump_covering.eventually_eq_one BumpCovering.eventuallyEq_one
theorem ind_apply (x : X) (hx : x ∈ s) : f (f.ind x hx) x = 1 :=
(f.eventuallyEq_one x hx).eq_of_nhds
#align bump_covering.ind_apply BumpCovering.ind_apply
/-- Partition of unity defined by a `BumpCovering`. We use this auxiliary definition to prove some
properties of the new family of functions before bundling it into a `PartitionOfUnity`. Do not use
this definition, use `BumpCovering.toPartitionOfUnity` instead.
The partition of unity is given by the formula `g i x = f i x * ∏ᶠ j < i, (1 - f j x)`. In other
words, `g i x = ∏ᶠ j < i, (1 - f j x) - ∏ᶠ j ≤ i, (1 - f j x)`, so
`∑ᶠ i, g i x = 1 - ∏ᶠ j, (1 - f j x)`. If `x ∈ s`, then one of `f j x` equals one, hence the product
of `1 - f j x` vanishes, and `∑ᶠ i, g i x = 1`.
In order to avoid an assumption `LinearOrder ι`, we use `WellOrderingRel` instead of `(<)`. -/
def toPOUFun (i : ι) (x : X) : ℝ :=
f i x * ∏ᶠ (j) (_ : WellOrderingRel j i), (1 - f j x)
#align bump_covering.to_pou_fun BumpCovering.toPOUFun
| Mathlib/Topology/PartitionOfUnity.lean | 474 | 475 | theorem toPOUFun_zero_of_zero {i : ι} {x : X} (h : f i x = 0) : f.toPOUFun i x = 0 := by |
rw [toPOUFun, h, zero_mul]
|
/-
Copyright (c) 2021 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker, Eric Wieser
-/
import Mathlib.Analysis.Analytic.Basic
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Normed.Field.InfiniteSum
import Mathlib.Data.Nat.Choose.Cast
import Mathlib.Data.Finset.NoncommProd
import Mathlib.Topology.Algebra.Algebra
#align_import analysis.normed_space.exponential from "leanprover-community/mathlib"@"62748956a1ece9b26b33243e2e3a2852176666f5"
/-!
# Exponential in a Banach algebra
In this file, we define `exp 𝕂 : 𝔸 → 𝔸`, the exponential map in a topological algebra `𝔸` over a
field `𝕂`.
While for most interesting results we need `𝔸` to be normed algebra, we do not require this in the
definition in order to make `exp` independent of a particular choice of norm. The definition also
does not require that `𝔸` be complete, but we need to assume it for most results.
We then prove some basic results, but we avoid importing derivatives here to minimize dependencies.
Results involving derivatives and comparisons with `Real.exp` and `Complex.exp` can be found in
`Analysis.SpecialFunctions.Exponential`.
## Main results
We prove most result for an arbitrary field `𝕂`, and then specialize to `𝕂 = ℝ` or `𝕂 = ℂ`.
### General case
- `NormedSpace.exp_add_of_commute_of_mem_ball` : if `𝕂` has characteristic zero,
then given two commuting elements `x` and `y` in the disk of convergence, we have
`exp 𝕂 (x+y) = (exp 𝕂 x) * (exp 𝕂 y)`
- `NormedSpace.exp_add_of_mem_ball` : if `𝕂` has characteristic zero and `𝔸` is commutative,
then given two elements `x` and `y` in the disk of convergence, we have
`exp 𝕂 (x+y) = (exp 𝕂 x) * (exp 𝕂 y)`
- `NormedSpace.exp_neg_of_mem_ball` : if `𝕂` has characteristic zero and `𝔸` is a division ring,
then given an element `x` in the disk of convergence, we have `exp 𝕂 (-x) = (exp 𝕂 x)⁻¹`.
### `𝕂 = ℝ` or `𝕂 = ℂ`
- `expSeries_radius_eq_top` : the `FormalMultilinearSeries` defining `exp 𝕂` has infinite
radius of convergence
- `NormedSpace.exp_add_of_commute` : given two commuting elements `x` and `y`, we have
`exp 𝕂 (x+y) = (exp 𝕂 x) * (exp 𝕂 y)`
- `NormedSpace.exp_add` : if `𝔸` is commutative, then we have `exp 𝕂 (x+y) = (exp 𝕂 x) * (exp 𝕂 y)`
for any `x` and `y`
- `NormedSpace.exp_neg` : if `𝔸` is a division ring, then we have `exp 𝕂 (-x) = (exp 𝕂 x)⁻¹`.
- `exp_sum_of_commute` : the analogous result to `NormedSpace.exp_add_of_commute` for `Finset.sum`.
- `exp_sum` : the analogous result to `NormedSpace.exp_add` for `Finset.sum`.
- `NormedSpace.exp_nsmul` : repeated addition in the domain corresponds to
repeated multiplication in the codomain.
- `NormedSpace.exp_zsmul` : repeated addition in the domain corresponds to
repeated multiplication in the codomain.
### Other useful compatibility results
- `NormedSpace.exp_eq_exp` : if `𝔸` is a normed algebra over two fields `𝕂` and `𝕂'`,
then `exp 𝕂 = exp 𝕂' 𝔸`
### Notes
We put nearly all the statements in this file in the `NormedSpace` namespace,
to avoid collisions with the `Real` or `Complex` namespaces.
As of 2023-11-16 due to bad instances in Mathlib
```
import Mathlib
open Real
#time example (x : ℝ) : 0 < exp x := exp_pos _ -- 250ms
#time example (x : ℝ) : 0 < Real.exp x := exp_pos _ -- 2ms
```
This is because `exp x` tries the `NormedSpace.exp` function defined here,
and generates a slow coercion search from `Real` to `Type`, to fit the first argument here.
We will resolve this slow coercion separately,
but we want to move `exp` out of the root namespace in any case to avoid this ambiguity.
In the long term is may be possible to replace `Real.exp` and `Complex.exp` with this one.
-/
namespace NormedSpace
open Filter RCLike ContinuousMultilinearMap NormedField Asymptotics
open scoped Nat Topology ENNReal
section TopologicalAlgebra
variable (𝕂 𝔸 : Type*) [Field 𝕂] [Ring 𝔸] [Algebra 𝕂 𝔸] [TopologicalSpace 𝔸] [TopologicalRing 𝔸]
/-- `expSeries 𝕂 𝔸` is the `FormalMultilinearSeries` whose `n`-th term is the map
`(xᵢ) : 𝔸ⁿ ↦ (1/n! : 𝕂) • ∏ xᵢ`. Its sum is the exponential map `exp 𝕂 : 𝔸 → 𝔸`. -/
def expSeries : FormalMultilinearSeries 𝕂 𝔸 𝔸 := fun n =>
(n !⁻¹ : 𝕂) • ContinuousMultilinearMap.mkPiAlgebraFin 𝕂 n 𝔸
#align exp_series NormedSpace.expSeries
variable {𝔸}
/-- `exp 𝕂 : 𝔸 → 𝔸` is the exponential map determined by the action of `𝕂` on `𝔸`.
It is defined as the sum of the `FormalMultilinearSeries` `expSeries 𝕂 𝔸`.
Note that when `𝔸 = Matrix n n 𝕂`, this is the **Matrix Exponential**; see
[`Analysis.NormedSpace.MatrixExponential`](./MatrixExponential) for lemmas specific to that
case. -/
noncomputable def exp (x : 𝔸) : 𝔸 :=
(expSeries 𝕂 𝔸).sum x
#align exp NormedSpace.exp
variable {𝕂}
theorem expSeries_apply_eq (x : 𝔸) (n : ℕ) :
(expSeries 𝕂 𝔸 n fun _ => x) = (n !⁻¹ : 𝕂) • x ^ n := by simp [expSeries]
#align exp_series_apply_eq NormedSpace.expSeries_apply_eq
theorem expSeries_apply_eq' (x : 𝔸) :
(fun n => expSeries 𝕂 𝔸 n fun _ => x) = fun n => (n !⁻¹ : 𝕂) • x ^ n :=
funext (expSeries_apply_eq x)
#align exp_series_apply_eq' NormedSpace.expSeries_apply_eq'
theorem expSeries_sum_eq (x : 𝔸) : (expSeries 𝕂 𝔸).sum x = ∑' n : ℕ, (n !⁻¹ : 𝕂) • x ^ n :=
tsum_congr fun n => expSeries_apply_eq x n
#align exp_series_sum_eq NormedSpace.expSeries_sum_eq
theorem exp_eq_tsum : exp 𝕂 = fun x : 𝔸 => ∑' n : ℕ, (n !⁻¹ : 𝕂) • x ^ n :=
funext expSeries_sum_eq
#align exp_eq_tsum NormedSpace.exp_eq_tsum
theorem expSeries_apply_zero (n : ℕ) :
(expSeries 𝕂 𝔸 n fun _ => (0 : 𝔸)) = Pi.single (f := fun _ => 𝔸) 0 1 n := by
rw [expSeries_apply_eq]
cases' n with n
· rw [pow_zero, Nat.factorial_zero, Nat.cast_one, inv_one, one_smul, Pi.single_eq_same]
· rw [zero_pow (Nat.succ_ne_zero _), smul_zero, Pi.single_eq_of_ne n.succ_ne_zero]
#align exp_series_apply_zero NormedSpace.expSeries_apply_zero
@[simp]
theorem exp_zero : exp 𝕂 (0 : 𝔸) = 1 := by
simp_rw [exp_eq_tsum, ← expSeries_apply_eq, expSeries_apply_zero, tsum_pi_single]
#align exp_zero NormedSpace.exp_zero
@[simp]
theorem exp_op [T2Space 𝔸] (x : 𝔸) : exp 𝕂 (MulOpposite.op x) = MulOpposite.op (exp 𝕂 x) := by
simp_rw [exp, expSeries_sum_eq, ← MulOpposite.op_pow, ← MulOpposite.op_smul, tsum_op]
#align exp_op NormedSpace.exp_op
@[simp]
theorem exp_unop [T2Space 𝔸] (x : 𝔸ᵐᵒᵖ) :
exp 𝕂 (MulOpposite.unop x) = MulOpposite.unop (exp 𝕂 x) := by
simp_rw [exp, expSeries_sum_eq, ← MulOpposite.unop_pow, ← MulOpposite.unop_smul, tsum_unop]
#align exp_unop NormedSpace.exp_unop
theorem star_exp [T2Space 𝔸] [StarRing 𝔸] [ContinuousStar 𝔸] (x : 𝔸) :
star (exp 𝕂 x) = exp 𝕂 (star x) := by
simp_rw [exp_eq_tsum, ← star_pow, ← star_inv_natCast_smul, ← tsum_star]
#align star_exp NormedSpace.star_exp
variable (𝕂)
theorem _root_.IsSelfAdjoint.exp [T2Space 𝔸] [StarRing 𝔸] [ContinuousStar 𝔸] {x : 𝔸}
(h : IsSelfAdjoint x) : IsSelfAdjoint (exp 𝕂 x) :=
(star_exp x).trans <| h.symm ▸ rfl
#align is_self_adjoint.exp IsSelfAdjoint.exp
theorem _root_.Commute.exp_right [T2Space 𝔸] {x y : 𝔸} (h : Commute x y) :
Commute x (exp 𝕂 y) := by
rw [exp_eq_tsum]
exact Commute.tsum_right x fun n => (h.pow_right n).smul_right _
#align commute.exp_right Commute.exp_right
theorem _root_.Commute.exp_left [T2Space 𝔸] {x y : 𝔸} (h : Commute x y) : Commute (exp 𝕂 x) y :=
(h.symm.exp_right 𝕂).symm
#align commute.exp_left Commute.exp_left
theorem _root_.Commute.exp [T2Space 𝔸] {x y : 𝔸} (h : Commute x y) : Commute (exp 𝕂 x) (exp 𝕂 y) :=
(h.exp_left _).exp_right _
#align commute.exp Commute.exp
end TopologicalAlgebra
section TopologicalDivisionAlgebra
variable {𝕂 𝔸 : Type*} [Field 𝕂] [DivisionRing 𝔸] [Algebra 𝕂 𝔸] [TopologicalSpace 𝔸]
[TopologicalRing 𝔸]
theorem expSeries_apply_eq_div (x : 𝔸) (n : ℕ) : (expSeries 𝕂 𝔸 n fun _ => x) = x ^ n / n ! := by
rw [div_eq_mul_inv, ← (Nat.cast_commute n ! (x ^ n)).inv_left₀.eq, ← smul_eq_mul,
expSeries_apply_eq, inv_natCast_smul_eq 𝕂 𝔸]
#align exp_series_apply_eq_div NormedSpace.expSeries_apply_eq_div
theorem expSeries_apply_eq_div' (x : 𝔸) :
(fun n => expSeries 𝕂 𝔸 n fun _ => x) = fun n => x ^ n / n ! :=
funext (expSeries_apply_eq_div x)
#align exp_series_apply_eq_div' NormedSpace.expSeries_apply_eq_div'
theorem expSeries_sum_eq_div (x : 𝔸) : (expSeries 𝕂 𝔸).sum x = ∑' n : ℕ, x ^ n / n ! :=
tsum_congr (expSeries_apply_eq_div x)
#align exp_series_sum_eq_div NormedSpace.expSeries_sum_eq_div
theorem exp_eq_tsum_div : exp 𝕂 = fun x : 𝔸 => ∑' n : ℕ, x ^ n / n ! :=
funext expSeries_sum_eq_div
#align exp_eq_tsum_div NormedSpace.exp_eq_tsum_div
end TopologicalDivisionAlgebra
section Normed
section AnyFieldAnyAlgebra
variable {𝕂 𝔸 𝔹 : Type*} [NontriviallyNormedField 𝕂]
variable [NormedRing 𝔸] [NormedRing 𝔹] [NormedAlgebra 𝕂 𝔸] [NormedAlgebra 𝕂 𝔹]
theorem norm_expSeries_summable_of_mem_ball (x : 𝔸)
(hx : x ∈ EMetric.ball (0 : 𝔸) (expSeries 𝕂 𝔸).radius) :
Summable fun n => ‖expSeries 𝕂 𝔸 n fun _ => x‖ :=
(expSeries 𝕂 𝔸).summable_norm_apply hx
#align norm_exp_series_summable_of_mem_ball NormedSpace.norm_expSeries_summable_of_mem_ball
| Mathlib/Analysis/NormedSpace/Exponential.lean | 226 | 231 | theorem norm_expSeries_summable_of_mem_ball' (x : 𝔸)
(hx : x ∈ EMetric.ball (0 : 𝔸) (expSeries 𝕂 𝔸).radius) :
Summable fun n => ‖(n !⁻¹ : 𝕂) • x ^ n‖ := by |
change Summable (norm ∘ _)
rw [← expSeries_apply_eq']
exact norm_expSeries_summable_of_mem_ball x hx
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou
-/
import Mathlib.MeasureTheory.Function.LpOrder
#align_import measure_theory.function.l1_space from "leanprover-community/mathlib"@"ccdbfb6e5614667af5aa3ab2d50885e0ef44a46f"
/-!
# Integrable functions and `L¹` space
In the first part of this file, the predicate `Integrable` is defined and basic properties of
integrable functions are proved.
Such a predicate is already available under the name `Memℒp 1`. We give a direct definition which
is easier to use, and show that it is equivalent to `Memℒp 1`
In the second part, we establish an API between `Integrable` and the space `L¹` of equivalence
classes of integrable functions, already defined as a special case of `L^p` spaces for `p = 1`.
## Notation
* `α →₁[μ] β` is the type of `L¹` space, where `α` is a `MeasureSpace` and `β` is a
`NormedAddCommGroup` with a `SecondCountableTopology`. `f : α →ₘ β` is a "function" in `L¹`.
In comments, `[f]` is also used to denote an `L¹` function.
`₁` can be typed as `\1`.
## Main definitions
* Let `f : α → β` be a function, where `α` is a `MeasureSpace` and `β` a `NormedAddCommGroup`.
Then `HasFiniteIntegral f` means `(∫⁻ a, ‖f a‖₊) < ∞`.
* If `β` is moreover a `MeasurableSpace` then `f` is called `Integrable` if
`f` is `Measurable` and `HasFiniteIntegral f` holds.
## Implementation notes
To prove something for an arbitrary integrable function, a useful theorem is
`Integrable.induction` in the file `SetIntegral`.
## Tags
integrable, function space, l1
-/
noncomputable section
open scoped Classical
open Topology ENNReal MeasureTheory NNReal
open Set Filter TopologicalSpace ENNReal EMetric MeasureTheory
variable {α β γ δ : Type*} {m : MeasurableSpace α} {μ ν : Measure α} [MeasurableSpace δ]
variable [NormedAddCommGroup β]
variable [NormedAddCommGroup γ]
namespace MeasureTheory
/-! ### Some results about the Lebesgue integral involving a normed group -/
theorem lintegral_nnnorm_eq_lintegral_edist (f : α → β) :
∫⁻ a, ‖f a‖₊ ∂μ = ∫⁻ a, edist (f a) 0 ∂μ := by simp only [edist_eq_coe_nnnorm]
#align measure_theory.lintegral_nnnorm_eq_lintegral_edist MeasureTheory.lintegral_nnnorm_eq_lintegral_edist
theorem lintegral_norm_eq_lintegral_edist (f : α → β) :
∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ = ∫⁻ a, edist (f a) 0 ∂μ := by
simp only [ofReal_norm_eq_coe_nnnorm, edist_eq_coe_nnnorm]
#align measure_theory.lintegral_norm_eq_lintegral_edist MeasureTheory.lintegral_norm_eq_lintegral_edist
theorem lintegral_edist_triangle {f g h : α → β} (hf : AEStronglyMeasurable f μ)
(hh : AEStronglyMeasurable h μ) :
(∫⁻ a, edist (f a) (g a) ∂μ) ≤ (∫⁻ a, edist (f a) (h a) ∂μ) + ∫⁻ a, edist (g a) (h a) ∂μ := by
rw [← lintegral_add_left' (hf.edist hh)]
refine lintegral_mono fun a => ?_
apply edist_triangle_right
#align measure_theory.lintegral_edist_triangle MeasureTheory.lintegral_edist_triangle
theorem lintegral_nnnorm_zero : (∫⁻ _ : α, ‖(0 : β)‖₊ ∂μ) = 0 := by simp
#align measure_theory.lintegral_nnnorm_zero MeasureTheory.lintegral_nnnorm_zero
theorem lintegral_nnnorm_add_left {f : α → β} (hf : AEStronglyMeasurable f μ) (g : α → γ) :
∫⁻ a, ‖f a‖₊ + ‖g a‖₊ ∂μ = (∫⁻ a, ‖f a‖₊ ∂μ) + ∫⁻ a, ‖g a‖₊ ∂μ :=
lintegral_add_left' hf.ennnorm _
#align measure_theory.lintegral_nnnorm_add_left MeasureTheory.lintegral_nnnorm_add_left
theorem lintegral_nnnorm_add_right (f : α → β) {g : α → γ} (hg : AEStronglyMeasurable g μ) :
∫⁻ a, ‖f a‖₊ + ‖g a‖₊ ∂μ = (∫⁻ a, ‖f a‖₊ ∂μ) + ∫⁻ a, ‖g a‖₊ ∂μ :=
lintegral_add_right' _ hg.ennnorm
#align measure_theory.lintegral_nnnorm_add_right MeasureTheory.lintegral_nnnorm_add_right
theorem lintegral_nnnorm_neg {f : α → β} : (∫⁻ a, ‖(-f) a‖₊ ∂μ) = ∫⁻ a, ‖f a‖₊ ∂μ := by
simp only [Pi.neg_apply, nnnorm_neg]
#align measure_theory.lintegral_nnnorm_neg MeasureTheory.lintegral_nnnorm_neg
/-! ### The predicate `HasFiniteIntegral` -/
/-- `HasFiniteIntegral f μ` means that the integral `∫⁻ a, ‖f a‖ ∂μ` is finite.
`HasFiniteIntegral f` means `HasFiniteIntegral f volume`. -/
def HasFiniteIntegral {_ : MeasurableSpace α} (f : α → β) (μ : Measure α := by volume_tac) : Prop :=
(∫⁻ a, ‖f a‖₊ ∂μ) < ∞
#align measure_theory.has_finite_integral MeasureTheory.HasFiniteIntegral
theorem hasFiniteIntegral_def {_ : MeasurableSpace α} (f : α → β) (μ : Measure α) :
HasFiniteIntegral f μ ↔ ((∫⁻ a, ‖f a‖₊ ∂μ) < ∞) :=
Iff.rfl
theorem hasFiniteIntegral_iff_norm (f : α → β) :
HasFiniteIntegral f μ ↔ (∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) < ∞ := by
simp only [HasFiniteIntegral, ofReal_norm_eq_coe_nnnorm]
#align measure_theory.has_finite_integral_iff_norm MeasureTheory.hasFiniteIntegral_iff_norm
theorem hasFiniteIntegral_iff_edist (f : α → β) :
HasFiniteIntegral f μ ↔ (∫⁻ a, edist (f a) 0 ∂μ) < ∞ := by
simp only [hasFiniteIntegral_iff_norm, edist_dist, dist_zero_right]
#align measure_theory.has_finite_integral_iff_edist MeasureTheory.hasFiniteIntegral_iff_edist
theorem hasFiniteIntegral_iff_ofReal {f : α → ℝ} (h : 0 ≤ᵐ[μ] f) :
HasFiniteIntegral f μ ↔ (∫⁻ a, ENNReal.ofReal (f a) ∂μ) < ∞ := by
rw [HasFiniteIntegral, lintegral_nnnorm_eq_of_ae_nonneg h]
#align measure_theory.has_finite_integral_iff_of_real MeasureTheory.hasFiniteIntegral_iff_ofReal
theorem hasFiniteIntegral_iff_ofNNReal {f : α → ℝ≥0} :
HasFiniteIntegral (fun x => (f x : ℝ)) μ ↔ (∫⁻ a, f a ∂μ) < ∞ := by
simp [hasFiniteIntegral_iff_norm]
#align measure_theory.has_finite_integral_iff_of_nnreal MeasureTheory.hasFiniteIntegral_iff_ofNNReal
theorem HasFiniteIntegral.mono {f : α → β} {g : α → γ} (hg : HasFiniteIntegral g μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ ≤ ‖g a‖) : HasFiniteIntegral f μ := by
simp only [hasFiniteIntegral_iff_norm] at *
calc
(∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) ≤ ∫⁻ a : α, ENNReal.ofReal ‖g a‖ ∂μ :=
lintegral_mono_ae (h.mono fun a h => ofReal_le_ofReal h)
_ < ∞ := hg
#align measure_theory.has_finite_integral.mono MeasureTheory.HasFiniteIntegral.mono
theorem HasFiniteIntegral.mono' {f : α → β} {g : α → ℝ} (hg : HasFiniteIntegral g μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ ≤ g a) : HasFiniteIntegral f μ :=
hg.mono <| h.mono fun _x hx => le_trans hx (le_abs_self _)
#align measure_theory.has_finite_integral.mono' MeasureTheory.HasFiniteIntegral.mono'
theorem HasFiniteIntegral.congr' {f : α → β} {g : α → γ} (hf : HasFiniteIntegral f μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : HasFiniteIntegral g μ :=
hf.mono <| EventuallyEq.le <| EventuallyEq.symm h
#align measure_theory.has_finite_integral.congr' MeasureTheory.HasFiniteIntegral.congr'
theorem hasFiniteIntegral_congr' {f : α → β} {g : α → γ} (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) :
HasFiniteIntegral f μ ↔ HasFiniteIntegral g μ :=
⟨fun hf => hf.congr' h, fun hg => hg.congr' <| EventuallyEq.symm h⟩
#align measure_theory.has_finite_integral_congr' MeasureTheory.hasFiniteIntegral_congr'
theorem HasFiniteIntegral.congr {f g : α → β} (hf : HasFiniteIntegral f μ) (h : f =ᵐ[μ] g) :
HasFiniteIntegral g μ :=
hf.congr' <| h.fun_comp norm
#align measure_theory.has_finite_integral.congr MeasureTheory.HasFiniteIntegral.congr
theorem hasFiniteIntegral_congr {f g : α → β} (h : f =ᵐ[μ] g) :
HasFiniteIntegral f μ ↔ HasFiniteIntegral g μ :=
hasFiniteIntegral_congr' <| h.fun_comp norm
#align measure_theory.has_finite_integral_congr MeasureTheory.hasFiniteIntegral_congr
theorem hasFiniteIntegral_const_iff {c : β} :
HasFiniteIntegral (fun _ : α => c) μ ↔ c = 0 ∨ μ univ < ∞ := by
simp [HasFiniteIntegral, lintegral_const, lt_top_iff_ne_top, ENNReal.mul_eq_top,
or_iff_not_imp_left]
#align measure_theory.has_finite_integral_const_iff MeasureTheory.hasFiniteIntegral_const_iff
theorem hasFiniteIntegral_const [IsFiniteMeasure μ] (c : β) :
HasFiniteIntegral (fun _ : α => c) μ :=
hasFiniteIntegral_const_iff.2 (Or.inr <| measure_lt_top _ _)
#align measure_theory.has_finite_integral_const MeasureTheory.hasFiniteIntegral_const
theorem hasFiniteIntegral_of_bounded [IsFiniteMeasure μ] {f : α → β} {C : ℝ}
(hC : ∀ᵐ a ∂μ, ‖f a‖ ≤ C) : HasFiniteIntegral f μ :=
(hasFiniteIntegral_const C).mono' hC
#align measure_theory.has_finite_integral_of_bounded MeasureTheory.hasFiniteIntegral_of_bounded
theorem HasFiniteIntegral.of_finite [Finite α] [IsFiniteMeasure μ] {f : α → β} :
HasFiniteIntegral f μ :=
let ⟨_⟩ := nonempty_fintype α
hasFiniteIntegral_of_bounded <| ae_of_all μ <| norm_le_pi_norm f
@[deprecated (since := "2024-02-05")]
alias hasFiniteIntegral_of_fintype := HasFiniteIntegral.of_finite
theorem HasFiniteIntegral.mono_measure {f : α → β} (h : HasFiniteIntegral f ν) (hμ : μ ≤ ν) :
HasFiniteIntegral f μ :=
lt_of_le_of_lt (lintegral_mono' hμ le_rfl) h
#align measure_theory.has_finite_integral.mono_measure MeasureTheory.HasFiniteIntegral.mono_measure
theorem HasFiniteIntegral.add_measure {f : α → β} (hμ : HasFiniteIntegral f μ)
(hν : HasFiniteIntegral f ν) : HasFiniteIntegral f (μ + ν) := by
simp only [HasFiniteIntegral, lintegral_add_measure] at *
exact add_lt_top.2 ⟨hμ, hν⟩
#align measure_theory.has_finite_integral.add_measure MeasureTheory.HasFiniteIntegral.add_measure
theorem HasFiniteIntegral.left_of_add_measure {f : α → β} (h : HasFiniteIntegral f (μ + ν)) :
HasFiniteIntegral f μ :=
h.mono_measure <| Measure.le_add_right <| le_rfl
#align measure_theory.has_finite_integral.left_of_add_measure MeasureTheory.HasFiniteIntegral.left_of_add_measure
theorem HasFiniteIntegral.right_of_add_measure {f : α → β} (h : HasFiniteIntegral f (μ + ν)) :
HasFiniteIntegral f ν :=
h.mono_measure <| Measure.le_add_left <| le_rfl
#align measure_theory.has_finite_integral.right_of_add_measure MeasureTheory.HasFiniteIntegral.right_of_add_measure
@[simp]
theorem hasFiniteIntegral_add_measure {f : α → β} :
HasFiniteIntegral f (μ + ν) ↔ HasFiniteIntegral f μ ∧ HasFiniteIntegral f ν :=
⟨fun h => ⟨h.left_of_add_measure, h.right_of_add_measure⟩, fun h => h.1.add_measure h.2⟩
#align measure_theory.has_finite_integral_add_measure MeasureTheory.hasFiniteIntegral_add_measure
theorem HasFiniteIntegral.smul_measure {f : α → β} (h : HasFiniteIntegral f μ) {c : ℝ≥0∞}
(hc : c ≠ ∞) : HasFiniteIntegral f (c • μ) := by
simp only [HasFiniteIntegral, lintegral_smul_measure] at *
exact mul_lt_top hc h.ne
#align measure_theory.has_finite_integral.smul_measure MeasureTheory.HasFiniteIntegral.smul_measure
@[simp]
theorem hasFiniteIntegral_zero_measure {m : MeasurableSpace α} (f : α → β) :
HasFiniteIntegral f (0 : Measure α) := by
simp only [HasFiniteIntegral, lintegral_zero_measure, zero_lt_top]
#align measure_theory.has_finite_integral_zero_measure MeasureTheory.hasFiniteIntegral_zero_measure
variable (α β μ)
@[simp]
theorem hasFiniteIntegral_zero : HasFiniteIntegral (fun _ : α => (0 : β)) μ := by
simp [HasFiniteIntegral]
#align measure_theory.has_finite_integral_zero MeasureTheory.hasFiniteIntegral_zero
variable {α β μ}
theorem HasFiniteIntegral.neg {f : α → β} (hfi : HasFiniteIntegral f μ) :
HasFiniteIntegral (-f) μ := by simpa [HasFiniteIntegral] using hfi
#align measure_theory.has_finite_integral.neg MeasureTheory.HasFiniteIntegral.neg
@[simp]
theorem hasFiniteIntegral_neg_iff {f : α → β} : HasFiniteIntegral (-f) μ ↔ HasFiniteIntegral f μ :=
⟨fun h => neg_neg f ▸ h.neg, HasFiniteIntegral.neg⟩
#align measure_theory.has_finite_integral_neg_iff MeasureTheory.hasFiniteIntegral_neg_iff
theorem HasFiniteIntegral.norm {f : α → β} (hfi : HasFiniteIntegral f μ) :
HasFiniteIntegral (fun a => ‖f a‖) μ := by
have eq : (fun a => (nnnorm ‖f a‖ : ℝ≥0∞)) = fun a => (‖f a‖₊ : ℝ≥0∞) := by
funext
rw [nnnorm_norm]
rwa [HasFiniteIntegral, eq]
#align measure_theory.has_finite_integral.norm MeasureTheory.HasFiniteIntegral.norm
theorem hasFiniteIntegral_norm_iff (f : α → β) :
HasFiniteIntegral (fun a => ‖f a‖) μ ↔ HasFiniteIntegral f μ :=
hasFiniteIntegral_congr' <| eventually_of_forall fun x => norm_norm (f x)
#align measure_theory.has_finite_integral_norm_iff MeasureTheory.hasFiniteIntegral_norm_iff
theorem hasFiniteIntegral_toReal_of_lintegral_ne_top {f : α → ℝ≥0∞} (hf : (∫⁻ x, f x ∂μ) ≠ ∞) :
HasFiniteIntegral (fun x => (f x).toReal) μ := by
have :
∀ x, (‖(f x).toReal‖₊ : ℝ≥0∞) = ENNReal.ofNNReal ⟨(f x).toReal, ENNReal.toReal_nonneg⟩ := by
intro x
rw [Real.nnnorm_of_nonneg]
simp_rw [HasFiniteIntegral, this]
refine lt_of_le_of_lt (lintegral_mono fun x => ?_) (lt_top_iff_ne_top.2 hf)
by_cases hfx : f x = ∞
· simp [hfx]
· lift f x to ℝ≥0 using hfx with fx h
simp [← h, ← NNReal.coe_le_coe]
#align measure_theory.has_finite_integral_to_real_of_lintegral_ne_top MeasureTheory.hasFiniteIntegral_toReal_of_lintegral_ne_top
theorem isFiniteMeasure_withDensity_ofReal {f : α → ℝ} (hfi : HasFiniteIntegral f μ) :
IsFiniteMeasure (μ.withDensity fun x => ENNReal.ofReal <| f x) := by
refine isFiniteMeasure_withDensity ((lintegral_mono fun x => ?_).trans_lt hfi).ne
exact Real.ofReal_le_ennnorm (f x)
#align measure_theory.is_finite_measure_with_density_of_real MeasureTheory.isFiniteMeasure_withDensity_ofReal
section DominatedConvergence
variable {F : ℕ → α → β} {f : α → β} {bound : α → ℝ}
theorem all_ae_ofReal_F_le_bound (h : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a) :
∀ n, ∀ᵐ a ∂μ, ENNReal.ofReal ‖F n a‖ ≤ ENNReal.ofReal (bound a) := fun n =>
(h n).mono fun _ h => ENNReal.ofReal_le_ofReal h
set_option linter.uppercaseLean3 false in
#align measure_theory.all_ae_of_real_F_le_bound MeasureTheory.all_ae_ofReal_F_le_bound
theorem all_ae_tendsto_ofReal_norm (h : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop <| 𝓝 <| f a) :
∀ᵐ a ∂μ, Tendsto (fun n => ENNReal.ofReal ‖F n a‖) atTop <| 𝓝 <| ENNReal.ofReal ‖f a‖ :=
h.mono fun _ h => tendsto_ofReal <| Tendsto.comp (Continuous.tendsto continuous_norm _) h
#align measure_theory.all_ae_tendsto_of_real_norm MeasureTheory.all_ae_tendsto_ofReal_norm
theorem all_ae_ofReal_f_le_bound (h_bound : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) :
∀ᵐ a ∂μ, ENNReal.ofReal ‖f a‖ ≤ ENNReal.ofReal (bound a) := by
have F_le_bound := all_ae_ofReal_F_le_bound h_bound
rw [← ae_all_iff] at F_le_bound
apply F_le_bound.mp ((all_ae_tendsto_ofReal_norm h_lim).mono _)
intro a tendsto_norm F_le_bound
exact le_of_tendsto' tendsto_norm F_le_bound
#align measure_theory.all_ae_of_real_f_le_bound MeasureTheory.all_ae_ofReal_f_le_bound
theorem hasFiniteIntegral_of_dominated_convergence {F : ℕ → α → β} {f : α → β} {bound : α → ℝ}
(bound_hasFiniteIntegral : HasFiniteIntegral bound μ)
(h_bound : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) : HasFiniteIntegral f μ := by
/- `‖F n a‖ ≤ bound a` and `‖F n a‖ --> ‖f a‖` implies `‖f a‖ ≤ bound a`,
and so `∫ ‖f‖ ≤ ∫ bound < ∞` since `bound` is has_finite_integral -/
rw [hasFiniteIntegral_iff_norm]
calc
(∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) ≤ ∫⁻ a, ENNReal.ofReal (bound a) ∂μ :=
lintegral_mono_ae <| all_ae_ofReal_f_le_bound h_bound h_lim
_ < ∞ := by
rw [← hasFiniteIntegral_iff_ofReal]
· exact bound_hasFiniteIntegral
exact (h_bound 0).mono fun a h => le_trans (norm_nonneg _) h
#align measure_theory.has_finite_integral_of_dominated_convergence MeasureTheory.hasFiniteIntegral_of_dominated_convergence
theorem tendsto_lintegral_norm_of_dominated_convergence {F : ℕ → α → β} {f : α → β} {bound : α → ℝ}
(F_measurable : ∀ n, AEStronglyMeasurable (F n) μ)
(bound_hasFiniteIntegral : HasFiniteIntegral bound μ)
(h_bound : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) :
Tendsto (fun n => ∫⁻ a, ENNReal.ofReal ‖F n a - f a‖ ∂μ) atTop (𝓝 0) := by
have f_measurable : AEStronglyMeasurable f μ :=
aestronglyMeasurable_of_tendsto_ae _ F_measurable h_lim
let b a := 2 * ENNReal.ofReal (bound a)
/- `‖F n a‖ ≤ bound a` and `F n a --> f a` implies `‖f a‖ ≤ bound a`, and thus by the
triangle inequality, have `‖F n a - f a‖ ≤ 2 * (bound a)`. -/
have hb : ∀ n, ∀ᵐ a ∂μ, ENNReal.ofReal ‖F n a - f a‖ ≤ b a := by
intro n
filter_upwards [all_ae_ofReal_F_le_bound h_bound n,
all_ae_ofReal_f_le_bound h_bound h_lim] with a h₁ h₂
calc
ENNReal.ofReal ‖F n a - f a‖ ≤ ENNReal.ofReal ‖F n a‖ + ENNReal.ofReal ‖f a‖ := by
rw [← ENNReal.ofReal_add]
· apply ofReal_le_ofReal
apply norm_sub_le
· exact norm_nonneg _
· exact norm_nonneg _
_ ≤ ENNReal.ofReal (bound a) + ENNReal.ofReal (bound a) := add_le_add h₁ h₂
_ = b a := by rw [← two_mul]
-- On the other hand, `F n a --> f a` implies that `‖F n a - f a‖ --> 0`
have h : ∀ᵐ a ∂μ, Tendsto (fun n => ENNReal.ofReal ‖F n a - f a‖) atTop (𝓝 0) := by
rw [← ENNReal.ofReal_zero]
refine h_lim.mono fun a h => (continuous_ofReal.tendsto _).comp ?_
rwa [← tendsto_iff_norm_sub_tendsto_zero]
/- Therefore, by the dominated convergence theorem for nonnegative integration, have
` ∫ ‖f a - F n a‖ --> 0 ` -/
suffices Tendsto (fun n => ∫⁻ a, ENNReal.ofReal ‖F n a - f a‖ ∂μ) atTop (𝓝 (∫⁻ _ : α, 0 ∂μ)) by
rwa [lintegral_zero] at this
-- Using the dominated convergence theorem.
refine tendsto_lintegral_of_dominated_convergence' _ ?_ hb ?_ ?_
-- Show `fun a => ‖f a - F n a‖` is almost everywhere measurable for all `n`
· exact fun n =>
measurable_ofReal.comp_aemeasurable ((F_measurable n).sub f_measurable).norm.aemeasurable
-- Show `2 * bound` `HasFiniteIntegral`
· rw [hasFiniteIntegral_iff_ofReal] at bound_hasFiniteIntegral
· calc
∫⁻ a, b a ∂μ = 2 * ∫⁻ a, ENNReal.ofReal (bound a) ∂μ := by
rw [lintegral_const_mul']
exact coe_ne_top
_ ≠ ∞ := mul_ne_top coe_ne_top bound_hasFiniteIntegral.ne
filter_upwards [h_bound 0] with _ h using le_trans (norm_nonneg _) h
-- Show `‖f a - F n a‖ --> 0`
· exact h
#align measure_theory.tendsto_lintegral_norm_of_dominated_convergence MeasureTheory.tendsto_lintegral_norm_of_dominated_convergence
end DominatedConvergence
section PosPart
/-! Lemmas used for defining the positive part of an `L¹` function -/
theorem HasFiniteIntegral.max_zero {f : α → ℝ} (hf : HasFiniteIntegral f μ) :
HasFiniteIntegral (fun a => max (f a) 0) μ :=
hf.mono <| eventually_of_forall fun x => by simp [abs_le, le_abs_self]
#align measure_theory.has_finite_integral.max_zero MeasureTheory.HasFiniteIntegral.max_zero
theorem HasFiniteIntegral.min_zero {f : α → ℝ} (hf : HasFiniteIntegral f μ) :
HasFiniteIntegral (fun a => min (f a) 0) μ :=
hf.mono <| eventually_of_forall fun x => by simpa [abs_le] using neg_abs_le _
#align measure_theory.has_finite_integral.min_zero MeasureTheory.HasFiniteIntegral.min_zero
end PosPart
section NormedSpace
variable {𝕜 : Type*}
theorem HasFiniteIntegral.smul [NormedAddCommGroup 𝕜] [SMulZeroClass 𝕜 β] [BoundedSMul 𝕜 β] (c : 𝕜)
{f : α → β} : HasFiniteIntegral f μ → HasFiniteIntegral (c • f) μ := by
simp only [HasFiniteIntegral]; intro hfi
calc
(∫⁻ a : α, ‖c • f a‖₊ ∂μ) ≤ ∫⁻ a : α, ‖c‖₊ * ‖f a‖₊ ∂μ := by
refine lintegral_mono ?_
intro i
-- After leanprover/lean4#2734, we need to do beta reduction `exact mod_cast`
beta_reduce
exact mod_cast (nnnorm_smul_le c (f i))
_ < ∞ := by
rw [lintegral_const_mul']
exacts [mul_lt_top coe_ne_top hfi.ne, coe_ne_top]
#align measure_theory.has_finite_integral.smul MeasureTheory.HasFiniteIntegral.smul
theorem hasFiniteIntegral_smul_iff [NormedRing 𝕜] [MulActionWithZero 𝕜 β] [BoundedSMul 𝕜 β] {c : 𝕜}
(hc : IsUnit c) (f : α → β) : HasFiniteIntegral (c • f) μ ↔ HasFiniteIntegral f μ := by
obtain ⟨c, rfl⟩ := hc
constructor
· intro h
simpa only [smul_smul, Units.inv_mul, one_smul] using h.smul ((c⁻¹ : 𝕜ˣ) : 𝕜)
exact HasFiniteIntegral.smul _
#align measure_theory.has_finite_integral_smul_iff MeasureTheory.hasFiniteIntegral_smul_iff
theorem HasFiniteIntegral.const_mul [NormedRing 𝕜] {f : α → 𝕜} (h : HasFiniteIntegral f μ) (c : 𝕜) :
HasFiniteIntegral (fun x => c * f x) μ :=
h.smul c
#align measure_theory.has_finite_integral.const_mul MeasureTheory.HasFiniteIntegral.const_mul
theorem HasFiniteIntegral.mul_const [NormedRing 𝕜] {f : α → 𝕜} (h : HasFiniteIntegral f μ) (c : 𝕜) :
HasFiniteIntegral (fun x => f x * c) μ :=
h.smul (MulOpposite.op c)
#align measure_theory.has_finite_integral.mul_const MeasureTheory.HasFiniteIntegral.mul_const
end NormedSpace
/-! ### The predicate `Integrable` -/
-- variable [MeasurableSpace β] [MeasurableSpace γ] [MeasurableSpace δ]
/-- `Integrable f μ` means that `f` is measurable and that the integral `∫⁻ a, ‖f a‖ ∂μ` is finite.
`Integrable f` means `Integrable f volume`. -/
def Integrable {α} {_ : MeasurableSpace α} (f : α → β) (μ : Measure α := by volume_tac) : Prop :=
AEStronglyMeasurable f μ ∧ HasFiniteIntegral f μ
#align measure_theory.integrable MeasureTheory.Integrable
theorem memℒp_one_iff_integrable {f : α → β} : Memℒp f 1 μ ↔ Integrable f μ := by
simp_rw [Integrable, HasFiniteIntegral, Memℒp, snorm_one_eq_lintegral_nnnorm]
#align measure_theory.mem_ℒp_one_iff_integrable MeasureTheory.memℒp_one_iff_integrable
theorem Integrable.aestronglyMeasurable {f : α → β} (hf : Integrable f μ) :
AEStronglyMeasurable f μ :=
hf.1
#align measure_theory.integrable.ae_strongly_measurable MeasureTheory.Integrable.aestronglyMeasurable
theorem Integrable.aemeasurable [MeasurableSpace β] [BorelSpace β] {f : α → β}
(hf : Integrable f μ) : AEMeasurable f μ :=
hf.aestronglyMeasurable.aemeasurable
#align measure_theory.integrable.ae_measurable MeasureTheory.Integrable.aemeasurable
theorem Integrable.hasFiniteIntegral {f : α → β} (hf : Integrable f μ) : HasFiniteIntegral f μ :=
hf.2
#align measure_theory.integrable.has_finite_integral MeasureTheory.Integrable.hasFiniteIntegral
theorem Integrable.mono {f : α → β} {g : α → γ} (hg : Integrable g μ)
(hf : AEStronglyMeasurable f μ) (h : ∀ᵐ a ∂μ, ‖f a‖ ≤ ‖g a‖) : Integrable f μ :=
⟨hf, hg.hasFiniteIntegral.mono h⟩
#align measure_theory.integrable.mono MeasureTheory.Integrable.mono
theorem Integrable.mono' {f : α → β} {g : α → ℝ} (hg : Integrable g μ)
(hf : AEStronglyMeasurable f μ) (h : ∀ᵐ a ∂μ, ‖f a‖ ≤ g a) : Integrable f μ :=
⟨hf, hg.hasFiniteIntegral.mono' h⟩
#align measure_theory.integrable.mono' MeasureTheory.Integrable.mono'
theorem Integrable.congr' {f : α → β} {g : α → γ} (hf : Integrable f μ)
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : Integrable g μ :=
⟨hg, hf.hasFiniteIntegral.congr' h⟩
#align measure_theory.integrable.congr' MeasureTheory.Integrable.congr'
theorem integrable_congr' {f : α → β} {g : α → γ} (hf : AEStronglyMeasurable f μ)
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) :
Integrable f μ ↔ Integrable g μ :=
⟨fun h2f => h2f.congr' hg h, fun h2g => h2g.congr' hf <| EventuallyEq.symm h⟩
#align measure_theory.integrable_congr' MeasureTheory.integrable_congr'
theorem Integrable.congr {f g : α → β} (hf : Integrable f μ) (h : f =ᵐ[μ] g) : Integrable g μ :=
⟨hf.1.congr h, hf.2.congr h⟩
#align measure_theory.integrable.congr MeasureTheory.Integrable.congr
theorem integrable_congr {f g : α → β} (h : f =ᵐ[μ] g) : Integrable f μ ↔ Integrable g μ :=
⟨fun hf => hf.congr h, fun hg => hg.congr h.symm⟩
#align measure_theory.integrable_congr MeasureTheory.integrable_congr
theorem integrable_const_iff {c : β} : Integrable (fun _ : α => c) μ ↔ c = 0 ∨ μ univ < ∞ := by
have : AEStronglyMeasurable (fun _ : α => c) μ := aestronglyMeasurable_const
rw [Integrable, and_iff_right this, hasFiniteIntegral_const_iff]
#align measure_theory.integrable_const_iff MeasureTheory.integrable_const_iff
@[simp]
theorem integrable_const [IsFiniteMeasure μ] (c : β) : Integrable (fun _ : α => c) μ :=
integrable_const_iff.2 <| Or.inr <| measure_lt_top _ _
#align measure_theory.integrable_const MeasureTheory.integrable_const
@[simp]
theorem Integrable.of_finite [Finite α] [MeasurableSpace α] [MeasurableSingletonClass α]
(μ : Measure α) [IsFiniteMeasure μ] (f : α → β) : Integrable (fun a ↦ f a) μ :=
⟨(StronglyMeasurable.of_finite f).aestronglyMeasurable, .of_finite⟩
@[deprecated (since := "2024-02-05")] alias integrable_of_fintype := Integrable.of_finite
theorem Memℒp.integrable_norm_rpow {f : α → β} {p : ℝ≥0∞} (hf : Memℒp f p μ) (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) : Integrable (fun x : α => ‖f x‖ ^ p.toReal) μ := by
rw [← memℒp_one_iff_integrable]
exact hf.norm_rpow hp_ne_zero hp_ne_top
#align measure_theory.mem_ℒp.integrable_norm_rpow MeasureTheory.Memℒp.integrable_norm_rpow
theorem Memℒp.integrable_norm_rpow' [IsFiniteMeasure μ] {f : α → β} {p : ℝ≥0∞} (hf : Memℒp f p μ) :
Integrable (fun x : α => ‖f x‖ ^ p.toReal) μ := by
by_cases h_zero : p = 0
· simp [h_zero, integrable_const]
by_cases h_top : p = ∞
· simp [h_top, integrable_const]
exact hf.integrable_norm_rpow h_zero h_top
#align measure_theory.mem_ℒp.integrable_norm_rpow' MeasureTheory.Memℒp.integrable_norm_rpow'
theorem Integrable.mono_measure {f : α → β} (h : Integrable f ν) (hμ : μ ≤ ν) : Integrable f μ :=
⟨h.aestronglyMeasurable.mono_measure hμ, h.hasFiniteIntegral.mono_measure hμ⟩
#align measure_theory.integrable.mono_measure MeasureTheory.Integrable.mono_measure
theorem Integrable.of_measure_le_smul {μ' : Measure α} (c : ℝ≥0∞) (hc : c ≠ ∞) (hμ'_le : μ' ≤ c • μ)
{f : α → β} (hf : Integrable f μ) : Integrable f μ' := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.of_measure_le_smul c hc hμ'_le
#align measure_theory.integrable.of_measure_le_smul MeasureTheory.Integrable.of_measure_le_smul
theorem Integrable.add_measure {f : α → β} (hμ : Integrable f μ) (hν : Integrable f ν) :
Integrable f (μ + ν) := by
simp_rw [← memℒp_one_iff_integrable] at hμ hν ⊢
refine ⟨hμ.aestronglyMeasurable.add_measure hν.aestronglyMeasurable, ?_⟩
rw [snorm_one_add_measure, ENNReal.add_lt_top]
exact ⟨hμ.snorm_lt_top, hν.snorm_lt_top⟩
#align measure_theory.integrable.add_measure MeasureTheory.Integrable.add_measure
theorem Integrable.left_of_add_measure {f : α → β} (h : Integrable f (μ + ν)) : Integrable f μ := by
rw [← memℒp_one_iff_integrable] at h ⊢
exact h.left_of_add_measure
#align measure_theory.integrable.left_of_add_measure MeasureTheory.Integrable.left_of_add_measure
theorem Integrable.right_of_add_measure {f : α → β} (h : Integrable f (μ + ν)) :
Integrable f ν := by
rw [← memℒp_one_iff_integrable] at h ⊢
exact h.right_of_add_measure
#align measure_theory.integrable.right_of_add_measure MeasureTheory.Integrable.right_of_add_measure
@[simp]
theorem integrable_add_measure {f : α → β} :
Integrable f (μ + ν) ↔ Integrable f μ ∧ Integrable f ν :=
⟨fun h => ⟨h.left_of_add_measure, h.right_of_add_measure⟩, fun h => h.1.add_measure h.2⟩
#align measure_theory.integrable_add_measure MeasureTheory.integrable_add_measure
@[simp]
theorem integrable_zero_measure {_ : MeasurableSpace α} {f : α → β} :
Integrable f (0 : Measure α) :=
⟨aestronglyMeasurable_zero_measure f, hasFiniteIntegral_zero_measure f⟩
#align measure_theory.integrable_zero_measure MeasureTheory.integrable_zero_measure
theorem integrable_finset_sum_measure {ι} {m : MeasurableSpace α} {f : α → β} {μ : ι → Measure α}
{s : Finset ι} : Integrable f (∑ i ∈ s, μ i) ↔ ∀ i ∈ s, Integrable f (μ i) := by
induction s using Finset.induction_on <;> simp [*]
#align measure_theory.integrable_finset_sum_measure MeasureTheory.integrable_finset_sum_measure
theorem Integrable.smul_measure {f : α → β} (h : Integrable f μ) {c : ℝ≥0∞} (hc : c ≠ ∞) :
Integrable f (c • μ) := by
rw [← memℒp_one_iff_integrable] at h ⊢
exact h.smul_measure hc
#align measure_theory.integrable.smul_measure MeasureTheory.Integrable.smul_measure
theorem Integrable.smul_measure_nnreal {f : α → β} (h : Integrable f μ) {c : ℝ≥0} :
Integrable f (c • μ) := by
apply h.smul_measure
simp
theorem integrable_smul_measure {f : α → β} {c : ℝ≥0∞} (h₁ : c ≠ 0) (h₂ : c ≠ ∞) :
Integrable f (c • μ) ↔ Integrable f μ :=
⟨fun h => by
simpa only [smul_smul, ENNReal.inv_mul_cancel h₁ h₂, one_smul] using
h.smul_measure (ENNReal.inv_ne_top.2 h₁),
fun h => h.smul_measure h₂⟩
#align measure_theory.integrable_smul_measure MeasureTheory.integrable_smul_measure
theorem integrable_inv_smul_measure {f : α → β} {c : ℝ≥0∞} (h₁ : c ≠ 0) (h₂ : c ≠ ∞) :
Integrable f (c⁻¹ • μ) ↔ Integrable f μ :=
integrable_smul_measure (by simpa using h₂) (by simpa using h₁)
#align measure_theory.integrable_inv_smul_measure MeasureTheory.integrable_inv_smul_measure
theorem Integrable.to_average {f : α → β} (h : Integrable f μ) : Integrable f ((μ univ)⁻¹ • μ) := by
rcases eq_or_ne μ 0 with (rfl | hne)
· rwa [smul_zero]
· apply h.smul_measure
simpa
#align measure_theory.integrable.to_average MeasureTheory.Integrable.to_average
theorem integrable_average [IsFiniteMeasure μ] {f : α → β} :
Integrable f ((μ univ)⁻¹ • μ) ↔ Integrable f μ :=
(eq_or_ne μ 0).by_cases (fun h => by simp [h]) fun h =>
integrable_smul_measure (ENNReal.inv_ne_zero.2 <| measure_ne_top _ _)
(ENNReal.inv_ne_top.2 <| mt Measure.measure_univ_eq_zero.1 h)
#align measure_theory.integrable_average MeasureTheory.integrable_average
theorem integrable_map_measure {f : α → δ} {g : δ → β}
(hg : AEStronglyMeasurable g (Measure.map f μ)) (hf : AEMeasurable f μ) :
Integrable g (Measure.map f μ) ↔ Integrable (g ∘ f) μ := by
simp_rw [← memℒp_one_iff_integrable]
exact memℒp_map_measure_iff hg hf
#align measure_theory.integrable_map_measure MeasureTheory.integrable_map_measure
theorem Integrable.comp_aemeasurable {f : α → δ} {g : δ → β} (hg : Integrable g (Measure.map f μ))
(hf : AEMeasurable f μ) : Integrable (g ∘ f) μ :=
(integrable_map_measure hg.aestronglyMeasurable hf).mp hg
#align measure_theory.integrable.comp_ae_measurable MeasureTheory.Integrable.comp_aemeasurable
theorem Integrable.comp_measurable {f : α → δ} {g : δ → β} (hg : Integrable g (Measure.map f μ))
(hf : Measurable f) : Integrable (g ∘ f) μ :=
hg.comp_aemeasurable hf.aemeasurable
#align measure_theory.integrable.comp_measurable MeasureTheory.Integrable.comp_measurable
theorem _root_.MeasurableEmbedding.integrable_map_iff {f : α → δ} (hf : MeasurableEmbedding f)
{g : δ → β} : Integrable g (Measure.map f μ) ↔ Integrable (g ∘ f) μ := by
simp_rw [← memℒp_one_iff_integrable]
exact hf.memℒp_map_measure_iff
#align measurable_embedding.integrable_map_iff MeasurableEmbedding.integrable_map_iff
theorem integrable_map_equiv (f : α ≃ᵐ δ) (g : δ → β) :
Integrable g (Measure.map f μ) ↔ Integrable (g ∘ f) μ := by
simp_rw [← memℒp_one_iff_integrable]
exact f.memℒp_map_measure_iff
#align measure_theory.integrable_map_equiv MeasureTheory.integrable_map_equiv
theorem MeasurePreserving.integrable_comp {ν : Measure δ} {g : δ → β} {f : α → δ}
(hf : MeasurePreserving f μ ν) (hg : AEStronglyMeasurable g ν) :
Integrable (g ∘ f) μ ↔ Integrable g ν := by
rw [← hf.map_eq] at hg ⊢
exact (integrable_map_measure hg hf.measurable.aemeasurable).symm
#align measure_theory.measure_preserving.integrable_comp MeasureTheory.MeasurePreserving.integrable_comp
theorem MeasurePreserving.integrable_comp_emb {f : α → δ} {ν} (h₁ : MeasurePreserving f μ ν)
(h₂ : MeasurableEmbedding f) {g : δ → β} : Integrable (g ∘ f) μ ↔ Integrable g ν :=
h₁.map_eq ▸ Iff.symm h₂.integrable_map_iff
#align measure_theory.measure_preserving.integrable_comp_emb MeasureTheory.MeasurePreserving.integrable_comp_emb
theorem lintegral_edist_lt_top {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
(∫⁻ a, edist (f a) (g a) ∂μ) < ∞ :=
lt_of_le_of_lt (lintegral_edist_triangle hf.aestronglyMeasurable aestronglyMeasurable_zero)
(ENNReal.add_lt_top.2 <| by
simp_rw [Pi.zero_apply, ← hasFiniteIntegral_iff_edist]
exact ⟨hf.hasFiniteIntegral, hg.hasFiniteIntegral⟩)
#align measure_theory.lintegral_edist_lt_top MeasureTheory.lintegral_edist_lt_top
variable (α β μ)
@[simp]
theorem integrable_zero : Integrable (fun _ => (0 : β)) μ := by
simp [Integrable, aestronglyMeasurable_const]
#align measure_theory.integrable_zero MeasureTheory.integrable_zero
variable {α β μ}
theorem Integrable.add' {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
HasFiniteIntegral (f + g) μ :=
calc
(∫⁻ a, ‖f a + g a‖₊ ∂μ) ≤ ∫⁻ a, ‖f a‖₊ + ‖g a‖₊ ∂μ :=
lintegral_mono fun a => by
-- After leanprover/lean4#2734, we need to do beta reduction before `exact mod_cast`
beta_reduce
exact mod_cast nnnorm_add_le _ _
_ = _ := lintegral_nnnorm_add_left hf.aestronglyMeasurable _
_ < ∞ := add_lt_top.2 ⟨hf.hasFiniteIntegral, hg.hasFiniteIntegral⟩
#align measure_theory.integrable.add' MeasureTheory.Integrable.add'
theorem Integrable.add {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
Integrable (f + g) μ :=
⟨hf.aestronglyMeasurable.add hg.aestronglyMeasurable, hf.add' hg⟩
#align measure_theory.integrable.add MeasureTheory.Integrable.add
theorem integrable_finset_sum' {ι} (s : Finset ι) {f : ι → α → β}
(hf : ∀ i ∈ s, Integrable (f i) μ) : Integrable (∑ i ∈ s, f i) μ :=
Finset.sum_induction f (fun g => Integrable g μ) (fun _ _ => Integrable.add)
(integrable_zero _ _ _) hf
#align measure_theory.integrable_finset_sum' MeasureTheory.integrable_finset_sum'
theorem integrable_finset_sum {ι} (s : Finset ι) {f : ι → α → β}
(hf : ∀ i ∈ s, Integrable (f i) μ) : Integrable (fun a => ∑ i ∈ s, f i a) μ := by
simpa only [← Finset.sum_apply] using integrable_finset_sum' s hf
#align measure_theory.integrable_finset_sum MeasureTheory.integrable_finset_sum
theorem Integrable.neg {f : α → β} (hf : Integrable f μ) : Integrable (-f) μ :=
⟨hf.aestronglyMeasurable.neg, hf.hasFiniteIntegral.neg⟩
#align measure_theory.integrable.neg MeasureTheory.Integrable.neg
@[simp]
theorem integrable_neg_iff {f : α → β} : Integrable (-f) μ ↔ Integrable f μ :=
⟨fun h => neg_neg f ▸ h.neg, Integrable.neg⟩
#align measure_theory.integrable_neg_iff MeasureTheory.integrable_neg_iff
@[simp]
lemma integrable_add_iff_integrable_right {f g : α → β} (hf : Integrable f μ) :
Integrable (f + g) μ ↔ Integrable g μ :=
⟨fun h ↦ show g = f + g + (-f) by simp only [add_neg_cancel_comm] ▸ h.add hf.neg,
fun h ↦ hf.add h⟩
@[simp]
lemma integrable_add_iff_integrable_left {f g : α → β} (hf : Integrable f μ) :
Integrable (g + f) μ ↔ Integrable g μ := by
rw [add_comm, integrable_add_iff_integrable_right hf]
lemma integrable_left_of_integrable_add_of_nonneg {f g : α → ℝ}
(h_meas : AEStronglyMeasurable f μ) (hf : 0 ≤ᵐ[μ] f) (hg : 0 ≤ᵐ[μ] g)
(h_int : Integrable (f + g) μ) : Integrable f μ := by
refine h_int.mono' h_meas ?_
filter_upwards [hf, hg] with a haf hag
exact (Real.norm_of_nonneg haf).symm ▸ (le_add_iff_nonneg_right _).mpr hag
lemma integrable_right_of_integrable_add_of_nonneg {f g : α → ℝ}
(h_meas : AEStronglyMeasurable f μ) (hf : 0 ≤ᵐ[μ] f) (hg : 0 ≤ᵐ[μ] g)
(h_int : Integrable (f + g) μ) : Integrable g μ :=
integrable_left_of_integrable_add_of_nonneg
((AEStronglyMeasurable.add_iff_right h_meas).mp h_int.aestronglyMeasurable)
hg hf (add_comm f g ▸ h_int)
lemma integrable_add_iff_of_nonneg {f g : α → ℝ} (h_meas : AEStronglyMeasurable f μ)
(hf : 0 ≤ᵐ[μ] f) (hg : 0 ≤ᵐ[μ] g) :
Integrable (f + g) μ ↔ Integrable f μ ∧ Integrable g μ :=
⟨fun h ↦ ⟨integrable_left_of_integrable_add_of_nonneg h_meas hf hg h,
integrable_right_of_integrable_add_of_nonneg h_meas hf hg h⟩, fun ⟨hf, hg⟩ ↦ hf.add hg⟩
lemma integrable_add_iff_of_nonpos {f g : α → ℝ} (h_meas : AEStronglyMeasurable f μ)
(hf : f ≤ᵐ[μ] 0) (hg : g ≤ᵐ[μ] 0) :
Integrable (f + g) μ ↔ Integrable f μ ∧ Integrable g μ := by
rw [← integrable_neg_iff, ← integrable_neg_iff (f := f), ← integrable_neg_iff (f := g), neg_add]
exact integrable_add_iff_of_nonneg h_meas.neg (hf.mono (fun _ ↦ neg_nonneg_of_nonpos))
(hg.mono (fun _ ↦ neg_nonneg_of_nonpos))
@[simp]
lemma integrable_add_const_iff [IsFiniteMeasure μ] {f : α → β} {c : β} :
Integrable (fun x ↦ f x + c) μ ↔ Integrable f μ :=
integrable_add_iff_integrable_left (integrable_const _)
@[simp]
lemma integrable_const_add_iff [IsFiniteMeasure μ] {f : α → β} {c : β} :
Integrable (fun x ↦ c + f x) μ ↔ Integrable f μ :=
integrable_add_iff_integrable_right (integrable_const _)
theorem Integrable.sub {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
Integrable (f - g) μ := by simpa only [sub_eq_add_neg] using hf.add hg.neg
#align measure_theory.integrable.sub MeasureTheory.Integrable.sub
theorem Integrable.norm {f : α → β} (hf : Integrable f μ) : Integrable (fun a => ‖f a‖) μ :=
⟨hf.aestronglyMeasurable.norm, hf.hasFiniteIntegral.norm⟩
#align measure_theory.integrable.norm MeasureTheory.Integrable.norm
theorem Integrable.inf {β} [NormedLatticeAddCommGroup β] {f g : α → β} (hf : Integrable f μ)
(hg : Integrable g μ) : Integrable (f ⊓ g) μ := by
rw [← memℒp_one_iff_integrable] at hf hg ⊢
exact hf.inf hg
#align measure_theory.integrable.inf MeasureTheory.Integrable.inf
theorem Integrable.sup {β} [NormedLatticeAddCommGroup β] {f g : α → β} (hf : Integrable f μ)
(hg : Integrable g μ) : Integrable (f ⊔ g) μ := by
rw [← memℒp_one_iff_integrable] at hf hg ⊢
exact hf.sup hg
#align measure_theory.integrable.sup MeasureTheory.Integrable.sup
theorem Integrable.abs {β} [NormedLatticeAddCommGroup β] {f : α → β} (hf : Integrable f μ) :
Integrable (fun a => |f a|) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.abs
#align measure_theory.integrable.abs MeasureTheory.Integrable.abs
theorem Integrable.bdd_mul {F : Type*} [NormedDivisionRing F] {f g : α → F} (hint : Integrable g μ)
(hm : AEStronglyMeasurable f μ) (hfbdd : ∃ C, ∀ x, ‖f x‖ ≤ C) :
Integrable (fun x => f x * g x) μ := by
cases' isEmpty_or_nonempty α with hα hα
· rw [μ.eq_zero_of_isEmpty]
exact integrable_zero_measure
· refine ⟨hm.mul hint.1, ?_⟩
obtain ⟨C, hC⟩ := hfbdd
have hCnonneg : 0 ≤ C := le_trans (norm_nonneg _) (hC hα.some)
have : (fun x => ‖f x * g x‖₊) ≤ fun x => ⟨C, hCnonneg⟩ * ‖g x‖₊ := by
intro x
simp only [nnnorm_mul]
exact mul_le_mul_of_nonneg_right (hC x) (zero_le _)
refine lt_of_le_of_lt (lintegral_mono_nnreal this) ?_
simp only [ENNReal.coe_mul]
rw [lintegral_const_mul' _ _ ENNReal.coe_ne_top]
exact ENNReal.mul_lt_top ENNReal.coe_ne_top (ne_of_lt hint.2)
#align measure_theory.integrable.bdd_mul MeasureTheory.Integrable.bdd_mul
/-- **Hölder's inequality for integrable functions**: the scalar multiplication of an integrable
vector-valued function by a scalar function with finite essential supremum is integrable. -/
theorem Integrable.essSup_smul {𝕜 : Type*} [NormedField 𝕜] [NormedSpace 𝕜 β] {f : α → β}
(hf : Integrable f μ) {g : α → 𝕜} (g_aestronglyMeasurable : AEStronglyMeasurable g μ)
(ess_sup_g : essSup (fun x => (‖g x‖₊ : ℝ≥0∞)) μ ≠ ∞) :
Integrable (fun x : α => g x • f x) μ := by
rw [← memℒp_one_iff_integrable] at *
refine ⟨g_aestronglyMeasurable.smul hf.1, ?_⟩
have h : (1 : ℝ≥0∞) / 1 = 1 / ∞ + 1 / 1 := by norm_num
have hg' : snorm g ∞ μ ≠ ∞ := by rwa [snorm_exponent_top]
calc
snorm (fun x : α => g x • f x) 1 μ ≤ _ := by
simpa using MeasureTheory.snorm_smul_le_mul_snorm hf.1 g_aestronglyMeasurable h
_ < ∞ := ENNReal.mul_lt_top hg' hf.2.ne
#align measure_theory.integrable.ess_sup_smul MeasureTheory.Integrable.essSup_smul
/-- Hölder's inequality for integrable functions: the scalar multiplication of an integrable
scalar-valued function by a vector-value function with finite essential supremum is integrable. -/
theorem Integrable.smul_essSup {𝕜 : Type*} [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β]
{f : α → 𝕜} (hf : Integrable f μ) {g : α → β}
(g_aestronglyMeasurable : AEStronglyMeasurable g μ)
(ess_sup_g : essSup (fun x => (‖g x‖₊ : ℝ≥0∞)) μ ≠ ∞) :
Integrable (fun x : α => f x • g x) μ := by
rw [← memℒp_one_iff_integrable] at *
refine ⟨hf.1.smul g_aestronglyMeasurable, ?_⟩
have h : (1 : ℝ≥0∞) / 1 = 1 / 1 + 1 / ∞ := by norm_num
have hg' : snorm g ∞ μ ≠ ∞ := by rwa [snorm_exponent_top]
calc
snorm (fun x : α => f x • g x) 1 μ ≤ _ := by
simpa using MeasureTheory.snorm_smul_le_mul_snorm g_aestronglyMeasurable hf.1 h
_ < ∞ := ENNReal.mul_lt_top hf.2.ne hg'
#align measure_theory.integrable.smul_ess_sup MeasureTheory.Integrable.smul_essSup
theorem integrable_norm_iff {f : α → β} (hf : AEStronglyMeasurable f μ) :
Integrable (fun a => ‖f a‖) μ ↔ Integrable f μ := by
simp_rw [Integrable, and_iff_right hf, and_iff_right hf.norm, hasFiniteIntegral_norm_iff]
#align measure_theory.integrable_norm_iff MeasureTheory.integrable_norm_iff
theorem integrable_of_norm_sub_le {f₀ f₁ : α → β} {g : α → ℝ} (hf₁_m : AEStronglyMeasurable f₁ μ)
(hf₀_i : Integrable f₀ μ) (hg_i : Integrable g μ) (h : ∀ᵐ a ∂μ, ‖f₀ a - f₁ a‖ ≤ g a) :
Integrable f₁ μ :=
haveI : ∀ᵐ a ∂μ, ‖f₁ a‖ ≤ ‖f₀ a‖ + g a := by
apply h.mono
intro a ha
calc
‖f₁ a‖ ≤ ‖f₀ a‖ + ‖f₀ a - f₁ a‖ := norm_le_insert _ _
_ ≤ ‖f₀ a‖ + g a := add_le_add_left ha _
Integrable.mono' (hf₀_i.norm.add hg_i) hf₁_m this
#align measure_theory.integrable_of_norm_sub_le MeasureTheory.integrable_of_norm_sub_le
theorem Integrable.prod_mk {f : α → β} {g : α → γ} (hf : Integrable f μ) (hg : Integrable g μ) :
Integrable (fun x => (f x, g x)) μ :=
⟨hf.aestronglyMeasurable.prod_mk hg.aestronglyMeasurable,
(hf.norm.add' hg.norm).mono <|
eventually_of_forall fun x =>
calc
max ‖f x‖ ‖g x‖ ≤ ‖f x‖ + ‖g x‖ := max_le_add_of_nonneg (norm_nonneg _) (norm_nonneg _)
_ ≤ ‖‖f x‖ + ‖g x‖‖ := le_abs_self _⟩
#align measure_theory.integrable.prod_mk MeasureTheory.Integrable.prod_mk
theorem Memℒp.integrable {q : ℝ≥0∞} (hq1 : 1 ≤ q) {f : α → β} [IsFiniteMeasure μ]
(hfq : Memℒp f q μ) : Integrable f μ :=
memℒp_one_iff_integrable.mp (hfq.memℒp_of_exponent_le hq1)
#align measure_theory.mem_ℒp.integrable MeasureTheory.Memℒp.integrable
/-- A non-quantitative version of Markov inequality for integrable functions: the measure of points
where `‖f x‖ ≥ ε` is finite for all positive `ε`. -/
theorem Integrable.measure_norm_ge_lt_top {f : α → β} (hf : Integrable f μ) {ε : ℝ} (hε : 0 < ε) :
μ { x | ε ≤ ‖f x‖ } < ∞ := by
rw [show { x | ε ≤ ‖f x‖ } = { x | ENNReal.ofReal ε ≤ ‖f x‖₊ } by
simp only [ENNReal.ofReal, Real.toNNReal_le_iff_le_coe, ENNReal.coe_le_coe, coe_nnnorm]]
refine (meas_ge_le_mul_pow_snorm μ one_ne_zero ENNReal.one_ne_top hf.1 ?_).trans_lt ?_
· simpa only [Ne, ENNReal.ofReal_eq_zero, not_le] using hε
apply ENNReal.mul_lt_top
· simpa only [ENNReal.one_toReal, ENNReal.rpow_one, Ne, ENNReal.inv_eq_top,
ENNReal.ofReal_eq_zero, not_le] using hε
simpa only [ENNReal.one_toReal, ENNReal.rpow_one] using
(memℒp_one_iff_integrable.2 hf).snorm_ne_top
#align measure_theory.integrable.measure_ge_lt_top MeasureTheory.Integrable.measure_norm_ge_lt_top
/-- A non-quantitative version of Markov inequality for integrable functions: the measure of points
where `‖f x‖ > ε` is finite for all positive `ε`. -/
lemma Integrable.measure_norm_gt_lt_top {f : α → β} (hf : Integrable f μ) {ε : ℝ} (hε : 0 < ε) :
μ {x | ε < ‖f x‖} < ∞ :=
lt_of_le_of_lt (measure_mono (fun _ h ↦ (Set.mem_setOf_eq ▸ h).le)) (hf.measure_norm_ge_lt_top hε)
/-- If `f` is `ℝ`-valued and integrable, then for any `c > 0` the set `{x | f x ≥ c}` has finite
measure. -/
lemma Integrable.measure_ge_lt_top {f : α → ℝ} (hf : Integrable f μ) {ε : ℝ} (ε_pos : 0 < ε) :
μ {a : α | ε ≤ f a} < ∞ := by
refine lt_of_le_of_lt (measure_mono ?_) (hf.measure_norm_ge_lt_top ε_pos)
intro x hx
simp only [Real.norm_eq_abs, Set.mem_setOf_eq] at hx ⊢
exact hx.trans (le_abs_self _)
/-- If `f` is `ℝ`-valued and integrable, then for any `c < 0` the set `{x | f x ≤ c}` has finite
measure. -/
lemma Integrable.measure_le_lt_top {f : α → ℝ} (hf : Integrable f μ) {c : ℝ} (c_neg : c < 0) :
μ {a : α | f a ≤ c} < ∞ := by
refine lt_of_le_of_lt (measure_mono ?_) (hf.measure_norm_ge_lt_top (show 0 < -c by linarith))
intro x hx
simp only [Real.norm_eq_abs, Set.mem_setOf_eq] at hx ⊢
exact (show -c ≤ - f x by linarith).trans (neg_le_abs _)
/-- If `f` is `ℝ`-valued and integrable, then for any `c > 0` the set `{x | f x > c}` has finite
measure. -/
lemma Integrable.measure_gt_lt_top {f : α → ℝ} (hf : Integrable f μ) {ε : ℝ} (ε_pos : 0 < ε) :
μ {a : α | ε < f a} < ∞ :=
lt_of_le_of_lt (measure_mono (fun _ hx ↦ (Set.mem_setOf_eq ▸ hx).le))
(Integrable.measure_ge_lt_top hf ε_pos)
/-- If `f` is `ℝ`-valued and integrable, then for any `c < 0` the set `{x | f x < c}` has finite
measure. -/
lemma Integrable.measure_lt_lt_top {f : α → ℝ} (hf : Integrable f μ) {c : ℝ} (c_neg : c < 0) :
μ {a : α | f a < c} < ∞ :=
lt_of_le_of_lt (measure_mono (fun _ hx ↦ (Set.mem_setOf_eq ▸ hx).le))
(Integrable.measure_le_lt_top hf c_neg)
theorem LipschitzWith.integrable_comp_iff_of_antilipschitz {K K'} {f : α → β} {g : β → γ}
(hg : LipschitzWith K g) (hg' : AntilipschitzWith K' g) (g0 : g 0 = 0) :
Integrable (g ∘ f) μ ↔ Integrable f μ := by
simp [← memℒp_one_iff_integrable, hg.memℒp_comp_iff_of_antilipschitz hg' g0]
#align measure_theory.lipschitz_with.integrable_comp_iff_of_antilipschitz MeasureTheory.LipschitzWith.integrable_comp_iff_of_antilipschitz
theorem Integrable.real_toNNReal {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun x => ((f x).toNNReal : ℝ)) μ := by
refine
⟨hf.aestronglyMeasurable.aemeasurable.real_toNNReal.coe_nnreal_real.aestronglyMeasurable, ?_⟩
rw [hasFiniteIntegral_iff_norm]
refine lt_of_le_of_lt ?_ ((hasFiniteIntegral_iff_norm _).1 hf.hasFiniteIntegral)
apply lintegral_mono
intro x
simp [ENNReal.ofReal_le_ofReal, abs_le, le_abs_self]
#align measure_theory.integrable.real_to_nnreal MeasureTheory.Integrable.real_toNNReal
theorem ofReal_toReal_ae_eq {f : α → ℝ≥0∞} (hf : ∀ᵐ x ∂μ, f x < ∞) :
(fun x => ENNReal.ofReal (f x).toReal) =ᵐ[μ] f := by
filter_upwards [hf]
intro x hx
simp only [hx.ne, ofReal_toReal, Ne, not_false_iff]
#align measure_theory.of_real_to_real_ae_eq MeasureTheory.ofReal_toReal_ae_eq
theorem coe_toNNReal_ae_eq {f : α → ℝ≥0∞} (hf : ∀ᵐ x ∂μ, f x < ∞) :
(fun x => ((f x).toNNReal : ℝ≥0∞)) =ᵐ[μ] f := by
filter_upwards [hf]
intro x hx
simp only [hx.ne, Ne, not_false_iff, coe_toNNReal]
#align measure_theory.coe_to_nnreal_ae_eq MeasureTheory.coe_toNNReal_ae_eq
section
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
theorem integrable_withDensity_iff_integrable_coe_smul {f : α → ℝ≥0} (hf : Measurable f)
{g : α → E} :
Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => (f x : ℝ) • g x) μ := by
by_cases H : AEStronglyMeasurable (fun x : α => (f x : ℝ) • g x) μ
· simp only [Integrable, aestronglyMeasurable_withDensity_iff hf, HasFiniteIntegral, H,
true_and_iff]
rw [lintegral_withDensity_eq_lintegral_mul₀' hf.coe_nnreal_ennreal.aemeasurable]
· rw [iff_iff_eq]
congr
ext1 x
simp only [nnnorm_smul, NNReal.nnnorm_eq, coe_mul, Pi.mul_apply]
· rw [aemeasurable_withDensity_ennreal_iff hf]
convert H.ennnorm using 1
ext1 x
simp only [nnnorm_smul, NNReal.nnnorm_eq, coe_mul]
· simp only [Integrable, aestronglyMeasurable_withDensity_iff hf, H, false_and_iff]
#align measure_theory.integrable_with_density_iff_integrable_coe_smul MeasureTheory.integrable_withDensity_iff_integrable_coe_smul
theorem integrable_withDensity_iff_integrable_smul {f : α → ℝ≥0} (hf : Measurable f) {g : α → E} :
Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => f x • g x) μ :=
integrable_withDensity_iff_integrable_coe_smul hf
#align measure_theory.integrable_with_density_iff_integrable_smul MeasureTheory.integrable_withDensity_iff_integrable_smul
theorem integrable_withDensity_iff_integrable_smul' {f : α → ℝ≥0∞} (hf : Measurable f)
(hflt : ∀ᵐ x ∂μ, f x < ∞) {g : α → E} :
Integrable g (μ.withDensity f) ↔ Integrable (fun x => (f x).toReal • g x) μ := by
rw [← withDensity_congr_ae (coe_toNNReal_ae_eq hflt),
integrable_withDensity_iff_integrable_smul]
· simp_rw [NNReal.smul_def, ENNReal.toReal]
· exact hf.ennreal_toNNReal
#align measure_theory.integrable_with_density_iff_integrable_smul' MeasureTheory.integrable_withDensity_iff_integrable_smul'
theorem integrable_withDensity_iff_integrable_coe_smul₀ {f : α → ℝ≥0} (hf : AEMeasurable f μ)
{g : α → E} :
Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => (f x : ℝ) • g x) μ :=
calc
Integrable g (μ.withDensity fun x => f x) ↔
Integrable g (μ.withDensity fun x => (hf.mk f x : ℝ≥0)) := by
suffices (fun x => (f x : ℝ≥0∞)) =ᵐ[μ] (fun x => (hf.mk f x : ℝ≥0)) by
rw [withDensity_congr_ae this]
filter_upwards [hf.ae_eq_mk] with x hx
simp [hx]
_ ↔ Integrable (fun x => ((hf.mk f x : ℝ≥0) : ℝ) • g x) μ :=
integrable_withDensity_iff_integrable_coe_smul hf.measurable_mk
_ ↔ Integrable (fun x => (f x : ℝ) • g x) μ := by
apply integrable_congr
filter_upwards [hf.ae_eq_mk] with x hx
simp [hx]
#align measure_theory.integrable_with_density_iff_integrable_coe_smul₀ MeasureTheory.integrable_withDensity_iff_integrable_coe_smul₀
theorem integrable_withDensity_iff_integrable_smul₀ {f : α → ℝ≥0} (hf : AEMeasurable f μ)
{g : α → E} : Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => f x • g x) μ :=
integrable_withDensity_iff_integrable_coe_smul₀ hf
#align measure_theory.integrable_with_density_iff_integrable_smul₀ MeasureTheory.integrable_withDensity_iff_integrable_smul₀
end
theorem integrable_withDensity_iff {f : α → ℝ≥0∞} (hf : Measurable f) (hflt : ∀ᵐ x ∂μ, f x < ∞)
{g : α → ℝ} : Integrable g (μ.withDensity f) ↔ Integrable (fun x => g x * (f x).toReal) μ := by
have : (fun x => g x * (f x).toReal) = fun x => (f x).toReal • g x := by simp [mul_comm]
rw [this]
exact integrable_withDensity_iff_integrable_smul' hf hflt
#align measure_theory.integrable_with_density_iff MeasureTheory.integrable_withDensity_iff
section
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
theorem memℒ1_smul_of_L1_withDensity {f : α → ℝ≥0} (f_meas : Measurable f)
(u : Lp E 1 (μ.withDensity fun x => f x)) : Memℒp (fun x => f x • u x) 1 μ :=
memℒp_one_iff_integrable.2 <|
(integrable_withDensity_iff_integrable_smul f_meas).1 <| memℒp_one_iff_integrable.1 (Lp.memℒp u)
set_option linter.uppercaseLean3 false in
#align measure_theory.mem_ℒ1_smul_of_L1_with_density MeasureTheory.memℒ1_smul_of_L1_withDensity
variable (μ)
/-- The map `u ↦ f • u` is an isometry between the `L^1` spaces for `μ.withDensity f` and `μ`. -/
noncomputable def withDensitySMulLI {f : α → ℝ≥0} (f_meas : Measurable f) :
Lp E 1 (μ.withDensity fun x => f x) →ₗᵢ[ℝ] Lp E 1 μ where
toFun u := (memℒ1_smul_of_L1_withDensity f_meas u).toLp _
map_add' := by
intro u v
ext1
filter_upwards [(memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp,
(memℒ1_smul_of_L1_withDensity f_meas v).coeFn_toLp,
(memℒ1_smul_of_L1_withDensity f_meas (u + v)).coeFn_toLp,
Lp.coeFn_add ((memℒ1_smul_of_L1_withDensity f_meas u).toLp _)
((memℒ1_smul_of_L1_withDensity f_meas v).toLp _),
(ae_withDensity_iff f_meas.coe_nnreal_ennreal).1 (Lp.coeFn_add u v)]
intro x hu hv huv h' h''
rw [huv, h', Pi.add_apply, hu, hv]
rcases eq_or_ne (f x) 0 with (hx | hx)
· simp only [hx, zero_smul, add_zero]
· rw [h'' _, Pi.add_apply, smul_add]
simpa only [Ne, ENNReal.coe_eq_zero] using hx
map_smul' := by
intro r u
ext1
filter_upwards [(ae_withDensity_iff f_meas.coe_nnreal_ennreal).1 (Lp.coeFn_smul r u),
(memℒ1_smul_of_L1_withDensity f_meas (r • u)).coeFn_toLp,
Lp.coeFn_smul r ((memℒ1_smul_of_L1_withDensity f_meas u).toLp _),
(memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp]
intro x h h' h'' h'''
rw [RingHom.id_apply, h', h'', Pi.smul_apply, h''']
rcases eq_or_ne (f x) 0 with (hx | hx)
· simp only [hx, zero_smul, smul_zero]
· rw [h _, smul_comm, Pi.smul_apply]
simpa only [Ne, ENNReal.coe_eq_zero] using hx
norm_map' := by
intro u
-- Porting note: Lean can't infer types of `AddHom.coe_mk`.
simp only [snorm, LinearMap.coe_mk,
AddHom.coe_mk (M := Lp E 1 (μ.withDensity fun x => f x)) (N := Lp E 1 μ), Lp.norm_toLp,
one_ne_zero, ENNReal.one_ne_top, ENNReal.one_toReal, if_false, snorm', ENNReal.rpow_one,
_root_.div_one, Lp.norm_def]
rw [lintegral_withDensity_eq_lintegral_mul_non_measurable _ f_meas.coe_nnreal_ennreal
(Filter.eventually_of_forall fun x => ENNReal.coe_lt_top)]
congr 1
apply lintegral_congr_ae
filter_upwards [(memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp] with x hx
rw [hx, Pi.mul_apply]
change (‖(f x : ℝ) • u x‖₊ : ℝ≥0∞) = (f x : ℝ≥0∞) * (‖u x‖₊ : ℝ≥0∞)
simp only [nnnorm_smul, NNReal.nnnorm_eq, ENNReal.coe_mul]
#align measure_theory.with_density_smul_li MeasureTheory.withDensitySMulLI
@[simp]
theorem withDensitySMulLI_apply {f : α → ℝ≥0} (f_meas : Measurable f)
(u : Lp E 1 (μ.withDensity fun x => f x)) :
withDensitySMulLI μ (E := E) f_meas u =
(memℒ1_smul_of_L1_withDensity f_meas u).toLp fun x => f x • u x :=
rfl
#align measure_theory.with_density_smul_li_apply MeasureTheory.withDensitySMulLI_apply
end
theorem mem_ℒ1_toReal_of_lintegral_ne_top {f : α → ℝ≥0∞} (hfm : AEMeasurable f μ)
(hfi : (∫⁻ x, f x ∂μ) ≠ ∞) : Memℒp (fun x => (f x).toReal) 1 μ := by
rw [Memℒp, snorm_one_eq_lintegral_nnnorm]
exact
⟨(AEMeasurable.ennreal_toReal hfm).aestronglyMeasurable,
hasFiniteIntegral_toReal_of_lintegral_ne_top hfi⟩
#align measure_theory.mem_ℒ1_to_real_of_lintegral_ne_top MeasureTheory.mem_ℒ1_toReal_of_lintegral_ne_top
theorem integrable_toReal_of_lintegral_ne_top {f : α → ℝ≥0∞} (hfm : AEMeasurable f μ)
(hfi : (∫⁻ x, f x ∂μ) ≠ ∞) : Integrable (fun x => (f x).toReal) μ :=
memℒp_one_iff_integrable.1 <| mem_ℒ1_toReal_of_lintegral_ne_top hfm hfi
#align measure_theory.integrable_to_real_of_lintegral_ne_top MeasureTheory.integrable_toReal_of_lintegral_ne_top
section PosPart
/-! ### Lemmas used for defining the positive part of an `L¹` function -/
theorem Integrable.pos_part {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun a => max (f a) 0) μ :=
⟨(hf.aestronglyMeasurable.aemeasurable.max aemeasurable_const).aestronglyMeasurable,
hf.hasFiniteIntegral.max_zero⟩
#align measure_theory.integrable.pos_part MeasureTheory.Integrable.pos_part
theorem Integrable.neg_part {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun a => max (-f a) 0) μ :=
hf.neg.pos_part
#align measure_theory.integrable.neg_part MeasureTheory.Integrable.neg_part
end PosPart
section BoundedSMul
variable {𝕜 : Type*}
theorem Integrable.smul [NormedAddCommGroup 𝕜] [SMulZeroClass 𝕜 β] [BoundedSMul 𝕜 β] (c : 𝕜)
{f : α → β} (hf : Integrable f μ) : Integrable (c • f) μ :=
⟨hf.aestronglyMeasurable.const_smul c, hf.hasFiniteIntegral.smul c⟩
#align measure_theory.integrable.smul MeasureTheory.Integrable.smul
theorem _root_.IsUnit.integrable_smul_iff [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β] {c : 𝕜}
(hc : IsUnit c) (f : α → β) : Integrable (c • f) μ ↔ Integrable f μ :=
and_congr hc.aestronglyMeasurable_const_smul_iff (hasFiniteIntegral_smul_iff hc f)
#align measure_theory.is_unit.integrable_smul_iff IsUnit.integrable_smul_iff
theorem integrable_smul_iff [NormedDivisionRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β] {c : 𝕜}
(hc : c ≠ 0) (f : α → β) : Integrable (c • f) μ ↔ Integrable f μ :=
(IsUnit.mk0 _ hc).integrable_smul_iff f
#align measure_theory.integrable_smul_iff MeasureTheory.integrable_smul_iff
variable [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β]
theorem Integrable.smul_of_top_right {f : α → β} {φ : α → 𝕜} (hf : Integrable f μ)
(hφ : Memℒp φ ∞ μ) : Integrable (φ • f) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact Memℒp.smul_of_top_right hf hφ
#align measure_theory.integrable.smul_of_top_right MeasureTheory.Integrable.smul_of_top_right
theorem Integrable.smul_of_top_left {f : α → β} {φ : α → 𝕜} (hφ : Integrable φ μ)
(hf : Memℒp f ∞ μ) : Integrable (φ • f) μ := by
rw [← memℒp_one_iff_integrable] at hφ ⊢
exact Memℒp.smul_of_top_left hf hφ
#align measure_theory.integrable.smul_of_top_left MeasureTheory.Integrable.smul_of_top_left
theorem Integrable.smul_const {f : α → 𝕜} (hf : Integrable f μ) (c : β) :
Integrable (fun x => f x • c) μ :=
hf.smul_of_top_left (memℒp_top_const c)
#align measure_theory.integrable.smul_const MeasureTheory.Integrable.smul_const
end BoundedSMul
section NormedSpaceOverCompleteField
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [CompleteSpace 𝕜]
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
theorem integrable_smul_const {f : α → 𝕜} {c : E} (hc : c ≠ 0) :
Integrable (fun x => f x • c) μ ↔ Integrable f μ := by
simp_rw [Integrable, aestronglyMeasurable_smul_const_iff (f := f) hc, and_congr_right_iff,
HasFiniteIntegral, nnnorm_smul, ENNReal.coe_mul]
intro _; rw [lintegral_mul_const' _ _ ENNReal.coe_ne_top, ENNReal.mul_lt_top_iff]
have : ∀ x : ℝ≥0∞, x = 0 → x < ∞ := by simp
simp [hc, or_iff_left_of_imp (this _)]
#align measure_theory.integrable_smul_const MeasureTheory.integrable_smul_const
end NormedSpaceOverCompleteField
section NormedRing
variable {𝕜 : Type*} [NormedRing 𝕜] {f : α → 𝕜}
theorem Integrable.const_mul {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (fun x => c * f x) μ :=
h.smul c
#align measure_theory.integrable.const_mul MeasureTheory.Integrable.const_mul
theorem Integrable.const_mul' {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable ((fun _ : α => c) * f) μ :=
Integrable.const_mul h c
#align measure_theory.integrable.const_mul' MeasureTheory.Integrable.const_mul'
theorem Integrable.mul_const {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (fun x => f x * c) μ :=
h.smul (MulOpposite.op c)
#align measure_theory.integrable.mul_const MeasureTheory.Integrable.mul_const
theorem Integrable.mul_const' {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (f * fun _ : α => c) μ :=
Integrable.mul_const h c
#align measure_theory.integrable.mul_const' MeasureTheory.Integrable.mul_const'
theorem integrable_const_mul_iff {c : 𝕜} (hc : IsUnit c) (f : α → 𝕜) :
Integrable (fun x => c * f x) μ ↔ Integrable f μ :=
hc.integrable_smul_iff f
#align measure_theory.integrable_const_mul_iff MeasureTheory.integrable_const_mul_iff
theorem integrable_mul_const_iff {c : 𝕜} (hc : IsUnit c) (f : α → 𝕜) :
Integrable (fun x => f x * c) μ ↔ Integrable f μ :=
hc.op.integrable_smul_iff f
#align measure_theory.integrable_mul_const_iff MeasureTheory.integrable_mul_const_iff
theorem Integrable.bdd_mul' {f g : α → 𝕜} {c : ℝ} (hg : Integrable g μ)
(hf : AEStronglyMeasurable f μ) (hf_bound : ∀ᵐ x ∂μ, ‖f x‖ ≤ c) :
Integrable (fun x => f x * g x) μ := by
refine Integrable.mono' (hg.norm.smul c) (hf.mul hg.1) ?_
filter_upwards [hf_bound] with x hx
rw [Pi.smul_apply, smul_eq_mul]
exact (norm_mul_le _ _).trans (mul_le_mul_of_nonneg_right hx (norm_nonneg _))
#align measure_theory.integrable.bdd_mul' MeasureTheory.Integrable.bdd_mul'
end NormedRing
section NormedDivisionRing
variable {𝕜 : Type*} [NormedDivisionRing 𝕜] {f : α → 𝕜}
theorem Integrable.div_const {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (fun x => f x / c) μ := by simp_rw [div_eq_mul_inv, h.mul_const]
#align measure_theory.integrable.div_const MeasureTheory.Integrable.div_const
end NormedDivisionRing
section RCLike
variable {𝕜 : Type*} [RCLike 𝕜] {f : α → 𝕜}
theorem Integrable.ofReal {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun x => (f x : 𝕜)) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.ofReal
#align measure_theory.integrable.of_real MeasureTheory.Integrable.ofReal
theorem Integrable.re_im_iff :
Integrable (fun x => RCLike.re (f x)) μ ∧ Integrable (fun x => RCLike.im (f x)) μ ↔
Integrable f μ := by
simp_rw [← memℒp_one_iff_integrable]
exact memℒp_re_im_iff
#align measure_theory.integrable.re_im_iff MeasureTheory.Integrable.re_im_iff
theorem Integrable.re (hf : Integrable f μ) : Integrable (fun x => RCLike.re (f x)) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.re
#align measure_theory.integrable.re MeasureTheory.Integrable.re
theorem Integrable.im (hf : Integrable f μ) : Integrable (fun x => RCLike.im (f x)) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.im
#align measure_theory.integrable.im MeasureTheory.Integrable.im
end RCLike
section Trim
variable {H : Type*} [NormedAddCommGroup H] {m0 : MeasurableSpace α} {μ' : Measure α} {f : α → H}
theorem Integrable.trim (hm : m ≤ m0) (hf_int : Integrable f μ') (hf : StronglyMeasurable[m] f) :
Integrable f (μ'.trim hm) := by
refine ⟨hf.aestronglyMeasurable, ?_⟩
rw [HasFiniteIntegral, lintegral_trim hm _]
· exact hf_int.2
· exact @StronglyMeasurable.ennnorm _ m _ _ f hf
#align measure_theory.integrable.trim MeasureTheory.Integrable.trim
theorem integrable_of_integrable_trim (hm : m ≤ m0) (hf_int : Integrable f (μ'.trim hm)) :
Integrable f μ' := by
obtain ⟨hf_meas_ae, hf⟩ := hf_int
refine ⟨aestronglyMeasurable_of_aestronglyMeasurable_trim hm hf_meas_ae, ?_⟩
rw [HasFiniteIntegral] at hf ⊢
rwa [lintegral_trim_ae hm _] at hf
exact AEStronglyMeasurable.ennnorm hf_meas_ae
#align measure_theory.integrable_of_integrable_trim MeasureTheory.integrable_of_integrable_trim
end Trim
section SigmaFinite
variable {E : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E]
theorem integrable_of_forall_fin_meas_le' {μ : Measure α} (hm : m ≤ m0) [SigmaFinite (μ.trim hm)]
(C : ℝ≥0∞) (hC : C < ∞) {f : α → E} (hf_meas : AEStronglyMeasurable f μ)
(hf : ∀ s, MeasurableSet[m] s → μ s ≠ ∞ → (∫⁻ x in s, ‖f x‖₊ ∂μ) ≤ C) : Integrable f μ :=
⟨hf_meas, (lintegral_le_of_forall_fin_meas_le' hm C hf_meas.ennnorm hf).trans_lt hC⟩
#align measure_theory.integrable_of_forall_fin_meas_le' MeasureTheory.integrable_of_forall_fin_meas_le'
theorem integrable_of_forall_fin_meas_le [SigmaFinite μ] (C : ℝ≥0∞) (hC : C < ∞) {f : α → E}
(hf_meas : AEStronglyMeasurable f μ)
(hf : ∀ s : Set α, MeasurableSet[m] s → μ s ≠ ∞ → (∫⁻ x in s, ‖f x‖₊ ∂μ) ≤ C) :
Integrable f μ :=
@integrable_of_forall_fin_meas_le' _ m _ m _ _ _ (by rwa [@trim_eq_self _ m]) C hC _ hf_meas hf
#align measure_theory.integrable_of_forall_fin_meas_le MeasureTheory.integrable_of_forall_fin_meas_le
end SigmaFinite
/-! ### The predicate `Integrable` on measurable functions modulo a.e.-equality -/
namespace AEEqFun
section
/-- A class of almost everywhere equal functions is `Integrable` if its function representative
is integrable. -/
def Integrable (f : α →ₘ[μ] β) : Prop :=
MeasureTheory.Integrable f μ
#align measure_theory.ae_eq_fun.integrable MeasureTheory.AEEqFun.Integrable
theorem integrable_mk {f : α → β} (hf : AEStronglyMeasurable f μ) :
Integrable (mk f hf : α →ₘ[μ] β) ↔ MeasureTheory.Integrable f μ := by
simp only [Integrable]
apply integrable_congr
exact coeFn_mk f hf
#align measure_theory.ae_eq_fun.integrable_mk MeasureTheory.AEEqFun.integrable_mk
theorem integrable_coeFn {f : α →ₘ[μ] β} : MeasureTheory.Integrable f μ ↔ Integrable f := by
rw [← integrable_mk, mk_coeFn]
#align measure_theory.ae_eq_fun.integrable_coe_fn MeasureTheory.AEEqFun.integrable_coeFn
theorem integrable_zero : Integrable (0 : α →ₘ[μ] β) :=
(MeasureTheory.integrable_zero α β μ).congr (coeFn_mk _ _).symm
#align measure_theory.ae_eq_fun.integrable_zero MeasureTheory.AEEqFun.integrable_zero
end
section
theorem Integrable.neg {f : α →ₘ[μ] β} : Integrable f → Integrable (-f) :=
induction_on f fun _f hfm hfi => (integrable_mk _).2 ((integrable_mk hfm).1 hfi).neg
#align measure_theory.ae_eq_fun.integrable.neg MeasureTheory.AEEqFun.Integrable.neg
section
theorem integrable_iff_mem_L1 {f : α →ₘ[μ] β} : Integrable f ↔ f ∈ (α →₁[μ] β) := by
rw [← integrable_coeFn, ← memℒp_one_iff_integrable, Lp.mem_Lp_iff_memℒp]
set_option linter.uppercaseLean3 false in
#align measure_theory.ae_eq_fun.integrable_iff_mem_L1 MeasureTheory.AEEqFun.integrable_iff_mem_L1
theorem Integrable.add {f g : α →ₘ[μ] β} : Integrable f → Integrable g → Integrable (f + g) := by
refine induction_on₂ f g fun f hf g hg hfi hgi => ?_
simp only [integrable_mk, mk_add_mk] at hfi hgi ⊢
exact hfi.add hgi
#align measure_theory.ae_eq_fun.integrable.add MeasureTheory.AEEqFun.Integrable.add
theorem Integrable.sub {f g : α →ₘ[μ] β} (hf : Integrable f) (hg : Integrable g) :
Integrable (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add hg.neg
#align measure_theory.ae_eq_fun.integrable.sub MeasureTheory.AEEqFun.Integrable.sub
end
section BoundedSMul
variable {𝕜 : Type*} [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β]
theorem Integrable.smul {c : 𝕜} {f : α →ₘ[μ] β} : Integrable f → Integrable (c • f) :=
induction_on f fun _f hfm hfi => (integrable_mk _).2 <|
by simpa using ((integrable_mk hfm).1 hfi).smul c
#align measure_theory.ae_eq_fun.integrable.smul MeasureTheory.AEEqFun.Integrable.smul
end BoundedSMul
end
end AEEqFun
namespace L1
set_option linter.uppercaseLean3 false
theorem integrable_coeFn (f : α →₁[μ] β) : Integrable f μ := by
rw [← memℒp_one_iff_integrable]
exact Lp.memℒp f
#align measure_theory.L1.integrable_coe_fn MeasureTheory.L1.integrable_coeFn
theorem hasFiniteIntegral_coeFn (f : α →₁[μ] β) : HasFiniteIntegral f μ :=
(integrable_coeFn f).hasFiniteIntegral
#align measure_theory.L1.has_finite_integral_coe_fn MeasureTheory.L1.hasFiniteIntegral_coeFn
theorem stronglyMeasurable_coeFn (f : α →₁[μ] β) : StronglyMeasurable f :=
Lp.stronglyMeasurable f
#align measure_theory.L1.strongly_measurable_coe_fn MeasureTheory.L1.stronglyMeasurable_coeFn
theorem measurable_coeFn [MeasurableSpace β] [BorelSpace β] (f : α →₁[μ] β) : Measurable f :=
(Lp.stronglyMeasurable f).measurable
#align measure_theory.L1.measurable_coe_fn MeasureTheory.L1.measurable_coeFn
theorem aestronglyMeasurable_coeFn (f : α →₁[μ] β) : AEStronglyMeasurable f μ :=
Lp.aestronglyMeasurable f
#align measure_theory.L1.ae_strongly_measurable_coe_fn MeasureTheory.L1.aestronglyMeasurable_coeFn
theorem aemeasurable_coeFn [MeasurableSpace β] [BorelSpace β] (f : α →₁[μ] β) : AEMeasurable f μ :=
(Lp.stronglyMeasurable f).measurable.aemeasurable
#align measure_theory.L1.ae_measurable_coe_fn MeasureTheory.L1.aemeasurable_coeFn
| Mathlib/MeasureTheory/Function/L1Space.lean | 1,394 | 1,397 | theorem edist_def (f g : α →₁[μ] β) : edist f g = ∫⁻ a, edist (f a) (g a) ∂μ := by |
simp only [Lp.edist_def, snorm, one_ne_zero, snorm', Pi.sub_apply, one_toReal, ENNReal.rpow_one,
ne_eq, not_false_eq_true, div_self, ite_false]
simp [edist_eq_coe_nnnorm_sub]
|
/-
Copyright (c) 2022 Wrenna Robson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Wrenna Robson
-/
import Mathlib.Topology.MetricSpace.Basic
#align_import topology.metric_space.infsep from "leanprover-community/mathlib"@"5316314b553dcf8c6716541851517c1a9715e22b"
/-!
# Infimum separation
This file defines the extended infimum separation of a set. This is approximately dual to the
diameter of a set, but where the extended diameter of a set is the supremum of the extended distance
between elements of the set, the extended infimum separation is the infimum of the (extended)
distance between *distinct* elements in the set.
We also define the infimum separation as the cast of the extended infimum separation to the reals.
This is the infimum of the distance between distinct elements of the set when in a pseudometric
space.
All lemmas and definitions are in the `Set` namespace to give access to dot notation.
## Main definitions
* `Set.einfsep`: Extended infimum separation of a set.
* `Set.infsep`: Infimum separation of a set (when in a pseudometric space).
!-/
variable {α β : Type*}
namespace Set
section Einfsep
open ENNReal
open Function
/-- The "extended infimum separation" of a set with an edist function. -/
noncomputable def einfsep [EDist α] (s : Set α) : ℝ≥0∞ :=
⨅ (x ∈ s) (y ∈ s) (_ : x ≠ y), edist x y
#align set.einfsep Set.einfsep
section EDist
variable [EDist α] {x y : α} {s t : Set α}
theorem le_einfsep_iff {d} :
d ≤ s.einfsep ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ edist x y := by
simp_rw [einfsep, le_iInf_iff]
#align set.le_einfsep_iff Set.le_einfsep_iff
theorem einfsep_zero : s.einfsep = 0 ↔ ∀ C > 0, ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < C := by
simp_rw [einfsep, ← _root_.bot_eq_zero, iInf_eq_bot, iInf_lt_iff, exists_prop]
#align set.einfsep_zero Set.einfsep_zero
theorem einfsep_pos : 0 < s.einfsep ↔ ∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y := by
rw [pos_iff_ne_zero, Ne, einfsep_zero]
simp only [not_forall, not_exists, not_lt, exists_prop, not_and]
#align set.einfsep_pos Set.einfsep_pos
theorem einfsep_top :
s.einfsep = ∞ ↔ ∀ x ∈ s, ∀ y ∈ s, x ≠ y → edist x y = ∞ := by
simp_rw [einfsep, iInf_eq_top]
#align set.einfsep_top Set.einfsep_top
theorem einfsep_lt_top :
s.einfsep < ∞ ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < ∞ := by
simp_rw [einfsep, iInf_lt_iff, exists_prop]
#align set.einfsep_lt_top Set.einfsep_lt_top
theorem einfsep_ne_top :
s.einfsep ≠ ∞ ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y ≠ ∞ := by
simp_rw [← lt_top_iff_ne_top, einfsep_lt_top]
#align set.einfsep_ne_top Set.einfsep_ne_top
theorem einfsep_lt_iff {d} :
s.einfsep < d ↔ ∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ edist x y < d := by
simp_rw [einfsep, iInf_lt_iff, exists_prop]
#align set.einfsep_lt_iff Set.einfsep_lt_iff
theorem nontrivial_of_einfsep_lt_top (hs : s.einfsep < ∞) : s.Nontrivial := by
rcases einfsep_lt_top.1 hs with ⟨_, hx, _, hy, hxy, _⟩
exact ⟨_, hx, _, hy, hxy⟩
#align set.nontrivial_of_einfsep_lt_top Set.nontrivial_of_einfsep_lt_top
theorem nontrivial_of_einfsep_ne_top (hs : s.einfsep ≠ ∞) : s.Nontrivial :=
nontrivial_of_einfsep_lt_top (lt_top_iff_ne_top.mpr hs)
#align set.nontrivial_of_einfsep_ne_top Set.nontrivial_of_einfsep_ne_top
theorem Subsingleton.einfsep (hs : s.Subsingleton) : s.einfsep = ∞ := by
rw [einfsep_top]
exact fun _ hx _ hy hxy => (hxy <| hs hx hy).elim
#align set.subsingleton.einfsep Set.Subsingleton.einfsep
theorem le_einfsep_image_iff {d} {f : β → α} {s : Set β} : d ≤ einfsep (f '' s)
↔ ∀ x ∈ s, ∀ y ∈ s, f x ≠ f y → d ≤ edist (f x) (f y) := by
simp_rw [le_einfsep_iff, forall_mem_image]
#align set.le_einfsep_image_iff Set.le_einfsep_image_iff
theorem le_edist_of_le_einfsep {d x} (hx : x ∈ s) {y} (hy : y ∈ s) (hxy : x ≠ y)
(hd : d ≤ s.einfsep) : d ≤ edist x y :=
le_einfsep_iff.1 hd x hx y hy hxy
#align set.le_edist_of_le_einfsep Set.le_edist_of_le_einfsep
theorem einfsep_le_edist_of_mem {x} (hx : x ∈ s) {y} (hy : y ∈ s) (hxy : x ≠ y) :
s.einfsep ≤ edist x y :=
le_edist_of_le_einfsep hx hy hxy le_rfl
#align set.einfsep_le_edist_of_mem Set.einfsep_le_edist_of_mem
theorem einfsep_le_of_mem_of_edist_le {d x} (hx : x ∈ s) {y} (hy : y ∈ s) (hxy : x ≠ y)
(hxy' : edist x y ≤ d) : s.einfsep ≤ d :=
le_trans (einfsep_le_edist_of_mem hx hy hxy) hxy'
#align set.einfsep_le_of_mem_of_edist_le Set.einfsep_le_of_mem_of_edist_le
theorem le_einfsep {d} (h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ edist x y) : d ≤ s.einfsep :=
le_einfsep_iff.2 h
#align set.le_einfsep Set.le_einfsep
@[simp]
theorem einfsep_empty : (∅ : Set α).einfsep = ∞ :=
subsingleton_empty.einfsep
#align set.einfsep_empty Set.einfsep_empty
@[simp]
theorem einfsep_singleton : ({x} : Set α).einfsep = ∞ :=
subsingleton_singleton.einfsep
#align set.einfsep_singleton Set.einfsep_singleton
theorem einfsep_iUnion_mem_option {ι : Type*} (o : Option ι) (s : ι → Set α) :
(⋃ i ∈ o, s i).einfsep = ⨅ i ∈ o, (s i).einfsep := by cases o <;> simp
#align set.einfsep_Union_mem_option Set.einfsep_iUnion_mem_option
theorem einfsep_anti (hst : s ⊆ t) : t.einfsep ≤ s.einfsep :=
le_einfsep fun _x hx _y hy => einfsep_le_edist_of_mem (hst hx) (hst hy)
#align set.einfsep_anti Set.einfsep_anti
theorem einfsep_insert_le : (insert x s).einfsep ≤ ⨅ (y ∈ s) (_ : x ≠ y), edist x y := by
simp_rw [le_iInf_iff]
exact fun _ hy hxy => einfsep_le_edist_of_mem (mem_insert _ _) (mem_insert_of_mem _ hy) hxy
#align set.einfsep_insert_le Set.einfsep_insert_le
theorem le_einfsep_pair : edist x y ⊓ edist y x ≤ ({x, y} : Set α).einfsep := by
simp_rw [le_einfsep_iff, inf_le_iff, mem_insert_iff, mem_singleton_iff]
rintro a (rfl | rfl) b (rfl | rfl) hab <;> (try simp only [le_refl, true_or, or_true]) <;>
contradiction
#align set.le_einfsep_pair Set.le_einfsep_pair
theorem einfsep_pair_le_left (hxy : x ≠ y) : ({x, y} : Set α).einfsep ≤ edist x y :=
einfsep_le_edist_of_mem (mem_insert _ _) (mem_insert_of_mem _ (mem_singleton _)) hxy
#align set.einfsep_pair_le_left Set.einfsep_pair_le_left
theorem einfsep_pair_le_right (hxy : x ≠ y) : ({x, y} : Set α).einfsep ≤ edist y x := by
rw [pair_comm]; exact einfsep_pair_le_left hxy.symm
#align set.einfsep_pair_le_right Set.einfsep_pair_le_right
theorem einfsep_pair_eq_inf (hxy : x ≠ y) : ({x, y} : Set α).einfsep = edist x y ⊓ edist y x :=
le_antisymm (le_inf (einfsep_pair_le_left hxy) (einfsep_pair_le_right hxy)) le_einfsep_pair
#align set.einfsep_pair_eq_inf Set.einfsep_pair_eq_inf
theorem einfsep_eq_iInf : s.einfsep = ⨅ d : s.offDiag, (uncurry edist) (d : α × α) := by
refine eq_of_forall_le_iff fun _ => ?_
simp_rw [le_einfsep_iff, le_iInf_iff, imp_forall_iff, SetCoe.forall, mem_offDiag,
Prod.forall, uncurry_apply_pair, and_imp]
#align set.einfsep_eq_infi Set.einfsep_eq_iInf
theorem einfsep_of_fintype [DecidableEq α] [Fintype s] :
s.einfsep = s.offDiag.toFinset.inf (uncurry edist) := by
refine eq_of_forall_le_iff fun _ => ?_
simp_rw [le_einfsep_iff, imp_forall_iff, Finset.le_inf_iff, mem_toFinset, mem_offDiag,
Prod.forall, uncurry_apply_pair, and_imp]
#align set.einfsep_of_fintype Set.einfsep_of_fintype
theorem Finite.einfsep (hs : s.Finite) : s.einfsep = hs.offDiag.toFinset.inf (uncurry edist) := by
refine eq_of_forall_le_iff fun _ => ?_
simp_rw [le_einfsep_iff, imp_forall_iff, Finset.le_inf_iff, Finite.mem_toFinset, mem_offDiag,
Prod.forall, uncurry_apply_pair, and_imp]
#align set.finite.einfsep Set.Finite.einfsep
theorem Finset.coe_einfsep [DecidableEq α] {s : Finset α} :
(s : Set α).einfsep = s.offDiag.inf (uncurry edist) := by
simp_rw [einfsep_of_fintype, ← Finset.coe_offDiag, Finset.toFinset_coe]
#align set.finset.coe_einfsep Set.Finset.coe_einfsep
theorem Nontrivial.einfsep_exists_of_finite [Finite s] (hs : s.Nontrivial) :
∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ s.einfsep = edist x y := by
classical
cases nonempty_fintype s
simp_rw [einfsep_of_fintype]
rcases Finset.exists_mem_eq_inf s.offDiag.toFinset (by simpa) (uncurry edist) with ⟨w, hxy, hed⟩
simp_rw [mem_toFinset] at hxy
exact ⟨w.fst, hxy.1, w.snd, hxy.2.1, hxy.2.2, hed⟩
#align set.nontrivial.einfsep_exists_of_finite Set.Nontrivial.einfsep_exists_of_finite
theorem Finite.einfsep_exists_of_nontrivial (hsf : s.Finite) (hs : s.Nontrivial) :
∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ s.einfsep = edist x y :=
letI := hsf.fintype
hs.einfsep_exists_of_finite
#align set.finite.einfsep_exists_of_nontrivial Set.Finite.einfsep_exists_of_nontrivial
end EDist
section PseudoEMetricSpace
variable [PseudoEMetricSpace α] {x y z : α} {s t : Set α}
theorem einfsep_pair (hxy : x ≠ y) : ({x, y} : Set α).einfsep = edist x y := by
nth_rw 1 [← min_self (edist x y)]
convert einfsep_pair_eq_inf hxy using 2
rw [edist_comm]
#align set.einfsep_pair Set.einfsep_pair
theorem einfsep_insert : einfsep (insert x s) =
(⨅ (y ∈ s) (_ : x ≠ y), edist x y) ⊓ s.einfsep := by
refine le_antisymm (le_min einfsep_insert_le (einfsep_anti (subset_insert _ _))) ?_
simp_rw [le_einfsep_iff, inf_le_iff, mem_insert_iff]
rintro y (rfl | hy) z (rfl | hz) hyz
· exact False.elim (hyz rfl)
· exact Or.inl (iInf_le_of_le _ (iInf₂_le hz hyz))
· rw [edist_comm]
exact Or.inl (iInf_le_of_le _ (iInf₂_le hy hyz.symm))
· exact Or.inr (einfsep_le_edist_of_mem hy hz hyz)
#align set.einfsep_insert Set.einfsep_insert
theorem einfsep_triple (hxy : x ≠ y) (hyz : y ≠ z) (hxz : x ≠ z) :
einfsep ({x, y, z} : Set α) = edist x y ⊓ edist x z ⊓ edist y z := by
simp_rw [einfsep_insert, iInf_insert, iInf_singleton, einfsep_singleton, inf_top_eq,
ciInf_pos hxy, ciInf_pos hyz, ciInf_pos hxz]
#align set.einfsep_triple Set.einfsep_triple
theorem le_einfsep_pi_of_le {π : β → Type*} [Fintype β] [∀ b, PseudoEMetricSpace (π b)]
{s : ∀ b : β, Set (π b)} {c : ℝ≥0∞} (h : ∀ b, c ≤ einfsep (s b)) :
c ≤ einfsep (Set.pi univ s) := by
refine le_einfsep fun x hx y hy hxy => ?_
rw [mem_univ_pi] at hx hy
rcases Function.ne_iff.mp hxy with ⟨i, hi⟩
exact le_trans (le_einfsep_iff.1 (h i) _ (hx _) _ (hy _) hi) (edist_le_pi_edist _ _ i)
#align set.le_einfsep_pi_of_le Set.le_einfsep_pi_of_le
end PseudoEMetricSpace
section PseudoMetricSpace
variable [PseudoMetricSpace α] {s : Set α}
theorem subsingleton_of_einfsep_eq_top (hs : s.einfsep = ∞) : s.Subsingleton := by
rw [einfsep_top] at hs
exact fun _ hx _ hy => of_not_not fun hxy => edist_ne_top _ _ (hs _ hx _ hy hxy)
#align set.subsingleton_of_einfsep_eq_top Set.subsingleton_of_einfsep_eq_top
theorem einfsep_eq_top_iff : s.einfsep = ∞ ↔ s.Subsingleton :=
⟨subsingleton_of_einfsep_eq_top, Subsingleton.einfsep⟩
#align set.einfsep_eq_top_iff Set.einfsep_eq_top_iff
theorem Nontrivial.einfsep_ne_top (hs : s.Nontrivial) : s.einfsep ≠ ∞ := by
contrapose! hs
rw [not_nontrivial_iff]
exact subsingleton_of_einfsep_eq_top hs
#align set.nontrivial.einfsep_ne_top Set.Nontrivial.einfsep_ne_top
theorem Nontrivial.einfsep_lt_top (hs : s.Nontrivial) : s.einfsep < ∞ := by
rw [lt_top_iff_ne_top]
exact hs.einfsep_ne_top
#align set.nontrivial.einfsep_lt_top Set.Nontrivial.einfsep_lt_top
theorem einfsep_lt_top_iff : s.einfsep < ∞ ↔ s.Nontrivial :=
⟨nontrivial_of_einfsep_lt_top, Nontrivial.einfsep_lt_top⟩
#align set.einfsep_lt_top_iff Set.einfsep_lt_top_iff
theorem einfsep_ne_top_iff : s.einfsep ≠ ∞ ↔ s.Nontrivial :=
⟨nontrivial_of_einfsep_ne_top, Nontrivial.einfsep_ne_top⟩
#align set.einfsep_ne_top_iff Set.einfsep_ne_top_iff
theorem le_einfsep_of_forall_dist_le {d} (h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → d ≤ dist x y) :
ENNReal.ofReal d ≤ s.einfsep :=
le_einfsep fun x hx y hy hxy => (edist_dist x y).symm ▸ ENNReal.ofReal_le_ofReal (h x hx y hy hxy)
#align set.le_einfsep_of_forall_dist_le Set.le_einfsep_of_forall_dist_le
end PseudoMetricSpace
section EMetricSpace
variable [EMetricSpace α] {x y z : α} {s t : Set α} {C : ℝ≥0∞} {sC : Set ℝ≥0∞}
theorem einfsep_pos_of_finite [Finite s] : 0 < s.einfsep := by
cases nonempty_fintype s
by_cases hs : s.Nontrivial
· rcases hs.einfsep_exists_of_finite with ⟨x, _hx, y, _hy, hxy, hxy'⟩
exact hxy'.symm ▸ edist_pos.2 hxy
· rw [not_nontrivial_iff] at hs
exact hs.einfsep.symm ▸ WithTop.zero_lt_top
#align set.einfsep_pos_of_finite Set.einfsep_pos_of_finite
theorem relatively_discrete_of_finite [Finite s] :
∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y := by
rw [← einfsep_pos]
exact einfsep_pos_of_finite
#align set.relatively_discrete_of_finite Set.relatively_discrete_of_finite
theorem Finite.einfsep_pos (hs : s.Finite) : 0 < s.einfsep :=
letI := hs.fintype
einfsep_pos_of_finite
#align set.finite.einfsep_pos Set.Finite.einfsep_pos
theorem Finite.relatively_discrete (hs : s.Finite) :
∃ C > 0, ∀ x ∈ s, ∀ y ∈ s, x ≠ y → C ≤ edist x y :=
letI := hs.fintype
relatively_discrete_of_finite
#align set.finite.relatively_discrete Set.Finite.relatively_discrete
end EMetricSpace
end Einfsep
section Infsep
open ENNReal
open Set Function
/-- The "infimum separation" of a set with an edist function. -/
noncomputable def infsep [EDist α] (s : Set α) : ℝ :=
ENNReal.toReal s.einfsep
#align set.infsep Set.infsep
section EDist
variable [EDist α] {x y : α} {s : Set α}
theorem infsep_zero : s.infsep = 0 ↔ s.einfsep = 0 ∨ s.einfsep = ∞ := by
rw [infsep, ENNReal.toReal_eq_zero_iff]
#align set.infsep_zero Set.infsep_zero
theorem infsep_nonneg : 0 ≤ s.infsep :=
ENNReal.toReal_nonneg
#align set.infsep_nonneg Set.infsep_nonneg
theorem infsep_pos : 0 < s.infsep ↔ 0 < s.einfsep ∧ s.einfsep < ∞ := by
simp_rw [infsep, ENNReal.toReal_pos_iff]
#align set.infsep_pos Set.infsep_pos
theorem Subsingleton.infsep_zero (hs : s.Subsingleton) : s.infsep = 0 :=
Set.infsep_zero.mpr <| Or.inr hs.einfsep
#align set.subsingleton.infsep_zero Set.Subsingleton.infsep_zero
| Mathlib/Topology/MetricSpace/Infsep.lean | 348 | 351 | theorem nontrivial_of_infsep_pos (hs : 0 < s.infsep) : s.Nontrivial := by |
contrapose hs
rw [not_nontrivial_iff] at hs
exact hs.infsep_zero ▸ lt_irrefl _
|
/-
Copyright (c) 2021 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Eric Wieser
-/
import Mathlib.LinearAlgebra.Matrix.DotProduct
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.Matrix.Diagonal
#align_import data.matrix.rank from "leanprover-community/mathlib"@"17219820a8aa8abe85adf5dfde19af1dd1bd8ae7"
/-!
# Rank of matrices
The rank of a matrix `A` is defined to be the rank of range of the linear map corresponding to `A`.
This definition does not depend on the choice of basis, see `Matrix.rank_eq_finrank_range_toLin`.
## Main declarations
* `Matrix.rank`: the rank of a matrix
## TODO
* Do a better job of generalizing over `ℚ`, `ℝ`, and `ℂ` in `Matrix.rank_transpose` and
`Matrix.rank_conjTranspose`. See
[this Zulip thread](https://leanprover.zulipchat.com/#narrow/stream/116395-maths/topic/row.20rank.20equals.20column.20rank/near/350462992).
-/
open Matrix
namespace Matrix
open FiniteDimensional
variable {l m n o R : Type*} [Fintype n] [Fintype o]
section CommRing
variable [CommRing R]
/-- The rank of a matrix is the rank of its image. -/
noncomputable def rank (A : Matrix m n R) : ℕ :=
finrank R <| LinearMap.range A.mulVecLin
#align matrix.rank Matrix.rank
@[simp]
theorem rank_one [StrongRankCondition R] [DecidableEq n] :
rank (1 : Matrix n n R) = Fintype.card n := by
rw [rank, mulVecLin_one, LinearMap.range_id, finrank_top, finrank_pi]
#align matrix.rank_one Matrix.rank_one
@[simp]
theorem rank_zero [Nontrivial R] : rank (0 : Matrix m n R) = 0 := by
rw [rank, mulVecLin_zero, LinearMap.range_zero, finrank_bot]
#align matrix.rank_zero Matrix.rank_zero
theorem rank_le_card_width [StrongRankCondition R] (A : Matrix m n R) :
A.rank ≤ Fintype.card n := by
haveI : Module.Finite R (n → R) := Module.Finite.pi
haveI : Module.Free R (n → R) := Module.Free.pi _ _
exact A.mulVecLin.finrank_range_le.trans_eq (finrank_pi _)
#align matrix.rank_le_card_width Matrix.rank_le_card_width
theorem rank_le_width [StrongRankCondition R] {m n : ℕ} (A : Matrix (Fin m) (Fin n) R) :
A.rank ≤ n :=
A.rank_le_card_width.trans <| (Fintype.card_fin n).le
#align matrix.rank_le_width Matrix.rank_le_width
theorem rank_mul_le_left [StrongRankCondition R] (A : Matrix m n R) (B : Matrix n o R) :
(A * B).rank ≤ A.rank := by
rw [rank, rank, mulVecLin_mul]
exact Cardinal.toNat_le_toNat (LinearMap.rank_comp_le_left _ _) (rank_lt_aleph0 _ _)
#align matrix.rank_mul_le_left Matrix.rank_mul_le_left
theorem rank_mul_le_right [StrongRankCondition R] (A : Matrix m n R) (B : Matrix n o R) :
(A * B).rank ≤ B.rank := by
rw [rank, rank, mulVecLin_mul]
exact finrank_le_finrank_of_rank_le_rank (LinearMap.lift_rank_comp_le_right _ _)
(rank_lt_aleph0 _ _)
#align matrix.rank_mul_le_right Matrix.rank_mul_le_right
theorem rank_mul_le [StrongRankCondition R] (A : Matrix m n R) (B : Matrix n o R) :
(A * B).rank ≤ min A.rank B.rank :=
le_min (rank_mul_le_left _ _) (rank_mul_le_right _ _)
#align matrix.rank_mul_le Matrix.rank_mul_le
theorem rank_unit [StrongRankCondition R] [DecidableEq n] (A : (Matrix n n R)ˣ) :
(A : Matrix n n R).rank = Fintype.card n := by
apply le_antisymm (rank_le_card_width (A : Matrix n n R)) _
have := rank_mul_le_left (A : Matrix n n R) (↑A⁻¹ : Matrix n n R)
rwa [← Units.val_mul, mul_inv_self, Units.val_one, rank_one] at this
#align matrix.rank_unit Matrix.rank_unit
theorem rank_of_isUnit [StrongRankCondition R] [DecidableEq n] (A : Matrix n n R) (h : IsUnit A) :
A.rank = Fintype.card n := by
obtain ⟨A, rfl⟩ := h
exact rank_unit A
#align matrix.rank_of_is_unit Matrix.rank_of_isUnit
/-- Right multiplying by an invertible matrix does not change the rank -/
@[simp]
lemma rank_mul_eq_left_of_isUnit_det [DecidableEq n]
(A : Matrix n n R) (B : Matrix m n R) (hA : IsUnit A.det) :
(B * A).rank = B.rank := by
suffices Function.Surjective A.mulVecLin by
rw [rank, mulVecLin_mul, LinearMap.range_comp_of_range_eq_top _
(LinearMap.range_eq_top.mpr this), ← rank]
intro v
exact ⟨(A⁻¹).mulVecLin v, by simp [mul_nonsing_inv _ hA]⟩
/-- Left multiplying by an invertible matrix does not change the rank -/
@[simp]
lemma rank_mul_eq_right_of_isUnit_det [Fintype m] [DecidableEq m]
(A : Matrix m m R) (B : Matrix m n R) (hA : IsUnit A.det) :
(A * B).rank = B.rank := by
let b : Basis m R (m → R) := Pi.basisFun R m
replace hA : IsUnit (LinearMap.toMatrix b b A.mulVecLin).det := by
convert hA; rw [← LinearEquiv.eq_symm_apply]; rfl
have hAB : mulVecLin (A * B) = (LinearEquiv.ofIsUnitDet hA).comp (mulVecLin B) := by ext; simp
rw [rank, rank, hAB, LinearMap.range_comp, LinearEquiv.finrank_map_eq]
/-- Taking a subset of the rows and permuting the columns reduces the rank. -/
theorem rank_submatrix_le [StrongRankCondition R] [Fintype m] (f : n → m) (e : n ≃ m)
(A : Matrix m m R) : rank (A.submatrix f e) ≤ rank A := by
rw [rank, rank, mulVecLin_submatrix, LinearMap.range_comp, LinearMap.range_comp,
show LinearMap.funLeft R R e.symm = LinearEquiv.funCongrLeft R R e.symm from rfl,
LinearEquiv.range, Submodule.map_top]
exact Submodule.finrank_map_le _ _
#align matrix.rank_submatrix_le Matrix.rank_submatrix_le
theorem rank_reindex [Fintype m] (e₁ e₂ : m ≃ n) (A : Matrix m m R) :
rank (reindex e₁ e₂ A) = rank A := by
rw [rank, rank, mulVecLin_reindex, LinearMap.range_comp, LinearMap.range_comp,
LinearEquiv.range, Submodule.map_top, LinearEquiv.finrank_map_eq]
#align matrix.rank_reindex Matrix.rank_reindex
@[simp]
theorem rank_submatrix [Fintype m] (A : Matrix m m R) (e₁ e₂ : n ≃ m) :
rank (A.submatrix e₁ e₂) = rank A := by
simpa only [reindex_apply] using rank_reindex e₁.symm e₂.symm A
#align matrix.rank_submatrix Matrix.rank_submatrix
theorem rank_eq_finrank_range_toLin [Finite m] [DecidableEq n] {M₁ M₂ : Type*} [AddCommGroup M₁]
[AddCommGroup M₂] [Module R M₁] [Module R M₂] (A : Matrix m n R) (v₁ : Basis m R M₁)
(v₂ : Basis n R M₂) : A.rank = finrank R (LinearMap.range (toLin v₂ v₁ A)) := by
cases nonempty_fintype m
let e₁ := (Pi.basisFun R m).equiv v₁ (Equiv.refl _)
let e₂ := (Pi.basisFun R n).equiv v₂ (Equiv.refl _)
have range_e₂ : LinearMap.range e₂ = ⊤ := by
rw [LinearMap.range_eq_top]
exact e₂.surjective
refine LinearEquiv.finrank_eq (e₁.ofSubmodules _ _ ?_)
rw [← LinearMap.range_comp, ← LinearMap.range_comp_of_range_eq_top (toLin v₂ v₁ A) range_e₂]
congr 1
apply LinearMap.pi_ext'
rintro i
apply LinearMap.ext_ring
have aux₁ := toLin_self (Pi.basisFun R n) (Pi.basisFun R m) A i
have aux₂ := Basis.equiv_apply (Pi.basisFun R n) i v₂
rw [toLin_eq_toLin', toLin'_apply'] at aux₁
rw [Pi.basisFun_apply, LinearMap.coe_stdBasis] at aux₁ aux₂
simp only [e₁, e₁, LinearMap.comp_apply, LinearEquiv.coe_coe, Equiv.refl_apply, aux₁, aux₂,
LinearMap.coe_single, toLin_self, map_sum, LinearEquiv.map_smul, Basis.equiv_apply]
#align matrix.rank_eq_finrank_range_to_lin Matrix.rank_eq_finrank_range_toLin
theorem rank_le_card_height [Fintype m] [StrongRankCondition R] (A : Matrix m n R) :
A.rank ≤ Fintype.card m := by
haveI : Module.Finite R (m → R) := Module.Finite.pi
haveI : Module.Free R (m → R) := Module.Free.pi _ _
exact (Submodule.finrank_le _).trans (finrank_pi R).le
#align matrix.rank_le_card_height Matrix.rank_le_card_height
theorem rank_le_height [StrongRankCondition R] {m n : ℕ} (A : Matrix (Fin m) (Fin n) R) :
A.rank ≤ m :=
A.rank_le_card_height.trans <| (Fintype.card_fin m).le
#align matrix.rank_le_height Matrix.rank_le_height
/-- The rank of a matrix is the rank of the space spanned by its columns. -/
| Mathlib/Data/Matrix/Rank.lean | 181 | 182 | theorem rank_eq_finrank_span_cols (A : Matrix m n R) :
A.rank = finrank R (Submodule.span R (Set.range Aᵀ)) := by | rw [rank, Matrix.range_mulVecLin]
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.BigOperators.Group.List
import Mathlib.Algebra.Group.Prod
import Mathlib.Data.Multiset.Basic
#align_import algebra.big_operators.multiset.basic from "leanprover-community/mathlib"@"6c5f73fd6f6cc83122788a80a27cdd54663609f4"
/-!
# Sums and products over multisets
In this file we define products and sums indexed by multisets. This is later used to define products
and sums indexed by finite sets.
## Main declarations
* `Multiset.prod`: `s.prod f` is the product of `f i` over all `i ∈ s`. Not to be mistaken with
the cartesian product `Multiset.product`.
* `Multiset.sum`: `s.sum f` is the sum of `f i` over all `i ∈ s`.
-/
assert_not_exists MonoidWithZero
variable {F ι α β γ : Type*}
namespace Multiset
section CommMonoid
variable [CommMonoid α] [CommMonoid β] {s t : Multiset α} {a : α} {m : Multiset ι} {f g : ι → α}
/-- Product of a multiset given a commutative monoid structure on `α`.
`prod {a, b, c} = a * b * c` -/
@[to_additive
"Sum of a multiset given a commutative additive monoid structure on `α`.
`sum {a, b, c} = a + b + c`"]
def prod : Multiset α → α :=
foldr (· * ·) (fun x y z => by simp [mul_left_comm]) 1
#align multiset.prod Multiset.prod
#align multiset.sum Multiset.sum
@[to_additive]
theorem prod_eq_foldr (s : Multiset α) :
prod s = foldr (· * ·) (fun x y z => by simp [mul_left_comm]) 1 s :=
rfl
#align multiset.prod_eq_foldr Multiset.prod_eq_foldr
#align multiset.sum_eq_foldr Multiset.sum_eq_foldr
@[to_additive]
theorem prod_eq_foldl (s : Multiset α) :
prod s = foldl (· * ·) (fun x y z => by simp [mul_right_comm]) 1 s :=
(foldr_swap _ _ _ _).trans (by simp [mul_comm])
#align multiset.prod_eq_foldl Multiset.prod_eq_foldl
#align multiset.sum_eq_foldl Multiset.sum_eq_foldl
@[to_additive (attr := simp, norm_cast)]
theorem prod_coe (l : List α) : prod ↑l = l.prod :=
prod_eq_foldl _
#align multiset.coe_prod Multiset.prod_coe
#align multiset.coe_sum Multiset.sum_coe
@[to_additive (attr := simp)]
theorem prod_toList (s : Multiset α) : s.toList.prod = s.prod := by
conv_rhs => rw [← coe_toList s]
rw [prod_coe]
#align multiset.prod_to_list Multiset.prod_toList
#align multiset.sum_to_list Multiset.sum_toList
@[to_additive (attr := simp)]
theorem prod_zero : @prod α _ 0 = 1 :=
rfl
#align multiset.prod_zero Multiset.prod_zero
#align multiset.sum_zero Multiset.sum_zero
@[to_additive (attr := simp)]
theorem prod_cons (a : α) (s) : prod (a ::ₘ s) = a * prod s :=
foldr_cons _ _ _ _ _
#align multiset.prod_cons Multiset.prod_cons
#align multiset.sum_cons Multiset.sum_cons
@[to_additive (attr := simp)]
theorem prod_erase [DecidableEq α] (h : a ∈ s) : a * (s.erase a).prod = s.prod := by
rw [← s.coe_toList, coe_erase, prod_coe, prod_coe, List.prod_erase (mem_toList.2 h)]
#align multiset.prod_erase Multiset.prod_erase
#align multiset.sum_erase Multiset.sum_erase
@[to_additive (attr := simp)]
theorem prod_map_erase [DecidableEq ι] {a : ι} (h : a ∈ m) :
f a * ((m.erase a).map f).prod = (m.map f).prod := by
rw [← m.coe_toList, coe_erase, map_coe, map_coe, prod_coe, prod_coe,
List.prod_map_erase f (mem_toList.2 h)]
#align multiset.prod_map_erase Multiset.prod_map_erase
#align multiset.sum_map_erase Multiset.sum_map_erase
@[to_additive (attr := simp)]
theorem prod_singleton (a : α) : prod {a} = a := by
simp only [mul_one, prod_cons, ← cons_zero, eq_self_iff_true, prod_zero]
#align multiset.prod_singleton Multiset.prod_singleton
#align multiset.sum_singleton Multiset.sum_singleton
@[to_additive]
theorem prod_pair (a b : α) : ({a, b} : Multiset α).prod = a * b := by
rw [insert_eq_cons, prod_cons, prod_singleton]
#align multiset.prod_pair Multiset.prod_pair
#align multiset.sum_pair Multiset.sum_pair
@[to_additive (attr := simp)]
theorem prod_add (s t : Multiset α) : prod (s + t) = prod s * prod t :=
Quotient.inductionOn₂ s t fun l₁ l₂ => by simp
#align multiset.prod_add Multiset.prod_add
#align multiset.sum_add Multiset.sum_add
@[to_additive]
theorem prod_nsmul (m : Multiset α) : ∀ n : ℕ, (n • m).prod = m.prod ^ n
| 0 => by
rw [zero_nsmul, pow_zero]
rfl
| n + 1 => by rw [add_nsmul, one_nsmul, pow_add, pow_one, prod_add, prod_nsmul m n]
#align multiset.prod_nsmul Multiset.prod_nsmul
@[to_additive]
theorem prod_filter_mul_prod_filter_not (p) [DecidablePred p] :
(s.filter p).prod * (s.filter (fun a ↦ ¬ p a)).prod = s.prod := by
rw [← prod_add, filter_add_not]
@[to_additive (attr := simp)]
theorem prod_replicate (n : ℕ) (a : α) : (replicate n a).prod = a ^ n := by
simp [replicate, List.prod_replicate]
#align multiset.prod_replicate Multiset.prod_replicate
#align multiset.sum_replicate Multiset.sum_replicate
@[to_additive]
theorem prod_map_eq_pow_single [DecidableEq ι] (i : ι)
(hf : ∀ i' ≠ i, i' ∈ m → f i' = 1) : (m.map f).prod = f i ^ m.count i := by
induction' m using Quotient.inductionOn with l
simp [List.prod_map_eq_pow_single i f hf]
#align multiset.prod_map_eq_pow_single Multiset.prod_map_eq_pow_single
#align multiset.sum_map_eq_nsmul_single Multiset.sum_map_eq_nsmul_single
@[to_additive]
theorem prod_eq_pow_single [DecidableEq α] (a : α) (h : ∀ a' ≠ a, a' ∈ s → a' = 1) :
s.prod = a ^ s.count a := by
induction' s using Quotient.inductionOn with l
simp [List.prod_eq_pow_single a h]
#align multiset.prod_eq_pow_single Multiset.prod_eq_pow_single
#align multiset.sum_eq_nsmul_single Multiset.sum_eq_nsmul_single
@[to_additive]
lemma prod_eq_one (h : ∀ x ∈ s, x = (1 : α)) : s.prod = 1 := by
induction' s using Quotient.inductionOn with l; simp [List.prod_eq_one h]
#align multiset.prod_eq_one Multiset.prod_eq_one
#align multiset.sum_eq_zero Multiset.sum_eq_zero
@[to_additive]
theorem pow_count [DecidableEq α] (a : α) : a ^ s.count a = (s.filter (Eq a)).prod := by
rw [filter_eq, prod_replicate]
#align multiset.pow_count Multiset.pow_count
#align multiset.nsmul_count Multiset.nsmul_count
@[to_additive]
theorem prod_hom [CommMonoid β] (s : Multiset α) {F : Type*} [FunLike F α β]
[MonoidHomClass F α β] (f : F) :
(s.map f).prod = f s.prod :=
Quotient.inductionOn s fun l => by simp only [l.prod_hom f, quot_mk_to_coe, map_coe, prod_coe]
#align multiset.prod_hom Multiset.prod_hom
#align multiset.sum_hom Multiset.sum_hom
@[to_additive]
theorem prod_hom' [CommMonoid β] (s : Multiset ι) {F : Type*} [FunLike F α β]
[MonoidHomClass F α β] (f : F)
(g : ι → α) : (s.map fun i => f <| g i).prod = f (s.map g).prod := by
convert (s.map g).prod_hom f
exact (map_map _ _ _).symm
#align multiset.prod_hom' Multiset.prod_hom'
#align multiset.sum_hom' Multiset.sum_hom'
@[to_additive]
theorem prod_hom₂ [CommMonoid β] [CommMonoid γ] (s : Multiset ι) (f : α → β → γ)
(hf : ∀ a b c d, f (a * b) (c * d) = f a c * f b d) (hf' : f 1 1 = 1) (f₁ : ι → α)
(f₂ : ι → β) : (s.map fun i => f (f₁ i) (f₂ i)).prod = f (s.map f₁).prod (s.map f₂).prod :=
Quotient.inductionOn s fun l => by
simp only [l.prod_hom₂ f hf hf', quot_mk_to_coe, map_coe, prod_coe]
#align multiset.prod_hom₂ Multiset.prod_hom₂
#align multiset.sum_hom₂ Multiset.sum_hom₂
@[to_additive]
theorem prod_hom_rel [CommMonoid β] (s : Multiset ι) {r : α → β → Prop} {f : ι → α} {g : ι → β}
(h₁ : r 1 1) (h₂ : ∀ ⦃a b c⦄, r b c → r (f a * b) (g a * c)) :
r (s.map f).prod (s.map g).prod :=
Quotient.inductionOn s fun l => by
simp only [l.prod_hom_rel h₁ h₂, quot_mk_to_coe, map_coe, prod_coe]
#align multiset.prod_hom_rel Multiset.prod_hom_rel
#align multiset.sum_hom_rel Multiset.sum_hom_rel
@[to_additive]
theorem prod_map_one : prod (m.map fun _ => (1 : α)) = 1 := by
rw [map_const', prod_replicate, one_pow]
#align multiset.prod_map_one Multiset.prod_map_one
#align multiset.sum_map_zero Multiset.sum_map_zero
@[to_additive (attr := simp)]
theorem prod_map_mul : (m.map fun i => f i * g i).prod = (m.map f).prod * (m.map g).prod :=
m.prod_hom₂ (· * ·) mul_mul_mul_comm (mul_one _) _ _
#align multiset.prod_map_mul Multiset.prod_map_mul
#align multiset.sum_map_add Multiset.sum_map_add
@[to_additive]
theorem prod_map_pow {n : ℕ} : (m.map fun i => f i ^ n).prod = (m.map f).prod ^ n :=
m.prod_hom' (powMonoidHom n : α →* α) f
#align multiset.prod_map_pow Multiset.prod_map_pow
#align multiset.sum_map_nsmul Multiset.sum_map_nsmul
@[to_additive]
theorem prod_map_prod_map (m : Multiset β) (n : Multiset γ) {f : β → γ → α} :
prod (m.map fun a => prod <| n.map fun b => f a b) =
prod (n.map fun b => prod <| m.map fun a => f a b) :=
Multiset.induction_on m (by simp) fun a m ih => by simp [ih]
#align multiset.prod_map_prod_map Multiset.prod_map_prod_map
#align multiset.sum_map_sum_map Multiset.sum_map_sum_map
@[to_additive]
theorem prod_induction (p : α → Prop) (s : Multiset α) (p_mul : ∀ a b, p a → p b → p (a * b))
(p_one : p 1) (p_s : ∀ a ∈ s, p a) : p s.prod := by
rw [prod_eq_foldr]
exact foldr_induction (· * ·) (fun x y z => by simp [mul_left_comm]) 1 p s p_mul p_one p_s
#align multiset.prod_induction Multiset.prod_induction
#align multiset.sum_induction Multiset.sum_induction
@[to_additive]
theorem prod_induction_nonempty (p : α → Prop) (p_mul : ∀ a b, p a → p b → p (a * b)) (hs : s ≠ ∅)
(p_s : ∀ a ∈ s, p a) : p s.prod := by
-- Porting note: used to be `refine' Multiset.induction _ _`
induction' s using Multiset.induction_on with a s hsa
· simp at hs
rw [prod_cons]
by_cases hs_empty : s = ∅
· simp [hs_empty, p_s a]
have hps : ∀ x, x ∈ s → p x := fun x hxs => p_s x (mem_cons_of_mem hxs)
exact p_mul a s.prod (p_s a (mem_cons_self a s)) (hsa hs_empty hps)
#align multiset.prod_induction_nonempty Multiset.prod_induction_nonempty
#align multiset.sum_induction_nonempty Multiset.sum_induction_nonempty
| Mathlib/Algebra/BigOperators/Group/Multiset.lean | 246 | 248 | theorem prod_dvd_prod_of_le (h : s ≤ t) : s.prod ∣ t.prod := by |
obtain ⟨z, rfl⟩ := exists_add_of_le h
simp only [prod_add, dvd_mul_right]
|
/-
Copyright (c) 2022 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz, Amelia Livingston
-/
import Mathlib.Algebra.Homology.Additive
import Mathlib.CategoryTheory.Abelian.Pseudoelements
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Images
#align_import category_theory.abelian.homology from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
The object `homology' f g w`, where `w : f ≫ g = 0`, can be identified with either a
cokernel or a kernel. The isomorphism with a cokernel is `homology'IsoCokernelLift`, which
was obtained elsewhere. In the case of an abelian category, this file shows the isomorphism
with a kernel as well.
We use these isomorphisms to obtain the analogous api for `homology'`:
- `homology'.ι` is the map from `homology' f g w` into the cokernel of `f`.
- `homology'.π'` is the map from `kernel g` to `homology' f g w`.
- `homology'.desc'` constructs a morphism from `homology' f g w`, when it is viewed as a cokernel.
- `homology'.lift` constructs a morphism to `homology' f g w`, when it is viewed as a kernel.
- Various small lemmas are proved as well, mimicking the API for (co)kernels.
With these definitions and lemmas, the isomorphisms between homology and a (co)kernel need not
be used directly.
Note: As part of the homology refactor, it is planned to remove the definitions in this file,
because it can be replaced by the content of `Algebra.Homology.ShortComplex.Homology`.
-/
open CategoryTheory.Limits
open CategoryTheory
noncomputable section
universe v u
variable {A : Type u} [Category.{v} A] [Abelian A]
variable {X Y Z : A} (f : X ⟶ Y) (g : Y ⟶ Z) (w : f ≫ g = 0)
namespace CategoryTheory.Abelian
/-- The cokernel of `kernel.lift g f w`. This is isomorphic to `homology f g w`.
See `homologyIsoCokernelLift`. -/
abbrev homologyC : A :=
cokernel (kernel.lift g f w)
#align category_theory.abelian.homology_c CategoryTheory.Abelian.homologyC
/-- The kernel of `cokernel.desc f g w`. This is isomorphic to `homology f g w`.
See `homologyIsoKernelDesc`. -/
abbrev homologyK : A :=
kernel (cokernel.desc f g w)
#align category_theory.abelian.homology_k CategoryTheory.Abelian.homologyK
/-- The canonical map from `homologyC` to `homologyK`.
This is an isomorphism, and it is used in obtaining the API for `homology f g w`
in the bottom of this file. -/
abbrev homologyCToK : homologyC f g w ⟶ homologyK f g w :=
cokernel.desc _ (kernel.lift _ (kernel.ι _ ≫ cokernel.π _) (by simp)) (by ext; simp)
#align category_theory.abelian.homology_c_to_k CategoryTheory.Abelian.homologyCToK
attribute [local instance] Pseudoelement.homToFun Pseudoelement.hasZero
instance : Mono (homologyCToK f g w) := by
apply Pseudoelement.mono_of_zero_of_map_zero
intro a ha
obtain ⟨a, rfl⟩ := Pseudoelement.pseudo_surjective_of_epi (cokernel.π (kernel.lift g f w)) a
apply_fun kernel.ι (cokernel.desc f g w) at ha
simp only [← Pseudoelement.comp_apply, cokernel.π_desc, kernel.lift_ι,
Pseudoelement.apply_zero] at ha
simp only [Pseudoelement.comp_apply] at ha
obtain ⟨b, hb⟩ : ∃ b, f b = _ := (Pseudoelement.pseudo_exact_of_exact (exact_cokernel f)).2 _ ha
rsuffices ⟨c, rfl⟩ : ∃ c, kernel.lift g f w c = a
· simp [← Pseudoelement.comp_apply]
use b
apply_fun kernel.ι g
swap; · apply Pseudoelement.pseudo_injective_of_mono
simpa [← Pseudoelement.comp_apply]
instance : Epi (homologyCToK f g w) := by
apply Pseudoelement.epi_of_pseudo_surjective
intro a
let b := kernel.ι (cokernel.desc f g w) a
obtain ⟨c, hc⟩ : ∃ c, cokernel.π f c = b := by
apply Pseudoelement.pseudo_surjective_of_epi (cokernel.π f)
have : g c = 0 := by
rw [show g = cokernel.π f ≫ cokernel.desc f g w by simp, Pseudoelement.comp_apply, hc]
simp [b, ← Pseudoelement.comp_apply]
obtain ⟨d, hd⟩ : ∃ d, kernel.ι g d = c := by
apply (Pseudoelement.pseudo_exact_of_exact exact_kernel_ι).2 _ this
use cokernel.π (kernel.lift g f w) d
apply_fun kernel.ι (cokernel.desc f g w)
swap
· apply Pseudoelement.pseudo_injective_of_mono
simp only [← Pseudoelement.comp_apply, cokernel.π_desc, kernel.lift_ι]
simp only [Pseudoelement.comp_apply, hd, hc]
instance (w : f ≫ g = 0) : IsIso (homologyCToK f g w) :=
isIso_of_mono_of_epi _
end CategoryTheory.Abelian
/-- The homology associated to `f` and `g` is isomorphic to a kernel. -/
def homology'IsoKernelDesc : homology' f g w ≅ kernel (cokernel.desc f g w) :=
homology'IsoCokernelLift _ _ _ ≪≫ asIso (CategoryTheory.Abelian.homologyCToK _ _ _)
#align homology_iso_kernel_desc homology'IsoKernelDesc
namespace homology'
-- `homology'.π` is taken
/-- The canonical map from the kernel of `g` to the homology of `f` and `g`. -/
def π' : kernel g ⟶ homology' f g w :=
cokernel.π _ ≫ (homology'IsoCokernelLift _ _ _).inv
#align homology.π' homology'.π'
/-- The canonical map from the homology of `f` and `g` to the cokernel of `f`. -/
def ι : homology' f g w ⟶ cokernel f :=
(homology'IsoKernelDesc _ _ _).hom ≫ kernel.ι _
#align homology.ι homology'.ι
/-- Obtain a morphism from the homology, given a morphism from the kernel. -/
def desc' {W : A} (e : kernel g ⟶ W) (he : kernel.lift g f w ≫ e = 0) : homology' f g w ⟶ W :=
(homology'IsoCokernelLift _ _ _).hom ≫ cokernel.desc _ e he
#align homology.desc' homology'.desc'
/-- Obtain a morphism to the homology, given a morphism to the kernel. -/
def lift {W : A} (e : W ⟶ cokernel f) (he : e ≫ cokernel.desc f g w = 0) : W ⟶ homology' f g w :=
kernel.lift _ e he ≫ (homology'IsoKernelDesc _ _ _).inv
#align homology.lift homology'.lift
@[reassoc (attr := simp)]
theorem π'_desc' {W : A} (e : kernel g ⟶ W) (he : kernel.lift g f w ≫ e = 0) :
π' f g w ≫ desc' f g w e he = e := by
dsimp [π', desc']
simp
#align homology.π'_desc' homology'.π'_desc'
@[reassoc (attr := simp)]
theorem lift_ι {W : A} (e : W ⟶ cokernel f) (he : e ≫ cokernel.desc f g w = 0) :
lift f g w e he ≫ ι _ _ _ = e := by
dsimp [ι, lift]
simp
#align homology.lift_ι homology'.lift_ι
@[reassoc (attr := simp)]
theorem condition_π' : kernel.lift g f w ≫ π' f g w = 0 := by
dsimp [π']
simp
#align homology.condition_π' homology'.condition_π'
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Abelian/Homology.lean | 157 | 159 | theorem condition_ι : ι f g w ≫ cokernel.desc f g w = 0 := by |
dsimp [ι]
simp
|
/-
Copyright (c) 2017 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Scott Morrison, Mario Carneiro, Andrew Yang
-/
import Mathlib.Topology.Category.TopCat.EpiMono
import Mathlib.Topology.Category.TopCat.Limits.Basic
import Mathlib.CategoryTheory.Limits.Shapes.Products
import Mathlib.CategoryTheory.Limits.ConcreteCategory
import Mathlib.Data.Set.Subsingleton
import Mathlib.Tactic.CategoryTheory.Elementwise
#align_import topology.category.Top.limits.products from "leanprover-community/mathlib"@"178a32653e369dce2da68dc6b2694e385d484ef1"
/-!
# Products and coproducts in the category of topological spaces
-/
-- Porting note: every ML3 decl has an uppercase letter
set_option linter.uppercaseLean3 false
open TopologicalSpace
open CategoryTheory
open CategoryTheory.Limits
universe v u w
noncomputable section
namespace TopCat
variable {J : Type v} [SmallCategory J]
/-- The projection from the product as a bundled continuous map. -/
abbrev piπ {ι : Type v} (α : ι → TopCat.{max v u}) (i : ι) : TopCat.of (∀ i, α i) ⟶ α i :=
⟨fun f => f i, continuous_apply i⟩
#align Top.pi_π TopCat.piπ
/-- The explicit fan of a family of topological spaces given by the pi type. -/
@[simps! pt π_app]
def piFan {ι : Type v} (α : ι → TopCat.{max v u}) : Fan α :=
Fan.mk (TopCat.of (∀ i, α i)) (piπ.{v,u} α)
#align Top.pi_fan TopCat.piFan
/-- The constructed fan is indeed a limit -/
def piFanIsLimit {ι : Type v} (α : ι → TopCat.{max v u}) : IsLimit (piFan α) where
lift S :=
{ toFun := fun s i => S.π.app ⟨i⟩ s
continuous_toFun := continuous_pi (fun i => (S.π.app ⟨i⟩).2) }
uniq := by
intro S m h
apply ContinuousMap.ext; intro x
funext i
set_option tactic.skipAssignedInstances false in
dsimp
rw [ContinuousMap.coe_mk, ← h ⟨i⟩]
rfl
fac s j := rfl
#align Top.pi_fan_is_limit TopCat.piFanIsLimit
/-- The product is homeomorphic to the product of the underlying spaces,
equipped with the product topology.
-/
def piIsoPi {ι : Type v} (α : ι → TopCat.{max v u}) : ∏ᶜ α ≅ TopCat.of (∀ i, α i) :=
(limit.isLimit _).conePointUniqueUpToIso (piFanIsLimit.{v, u} α)
-- Specifying the universes in `piFanIsLimit` wasn't necessary when we had `TopCatMax`
#align Top.pi_iso_pi TopCat.piIsoPi
@[reassoc (attr := simp)]
theorem piIsoPi_inv_π {ι : Type v} (α : ι → TopCat.{max v u}) (i : ι) :
(piIsoPi α).inv ≫ Pi.π α i = piπ α i := by simp [piIsoPi]
#align Top.pi_iso_pi_inv_π TopCat.piIsoPi_inv_π
theorem piIsoPi_inv_π_apply {ι : Type v} (α : ι → TopCat.{max v u}) (i : ι) (x : ∀ i, α i) :
(Pi.π α i : _) ((piIsoPi α).inv x) = x i :=
ConcreteCategory.congr_hom (piIsoPi_inv_π α i) x
#align Top.pi_iso_pi_inv_π_apply TopCat.piIsoPi_inv_π_apply
-- Porting note: needing the type ascription on `∏ᶜ α : TopCat.{max v u}` is unfortunate.
| Mathlib/Topology/Category/TopCat/Limits/Products.lean | 82 | 86 | theorem piIsoPi_hom_apply {ι : Type v} (α : ι → TopCat.{max v u}) (i : ι)
(x : (∏ᶜ α : TopCat.{max v u})) : (piIsoPi α).hom x i = (Pi.π α i : _) x := by |
have := piIsoPi_inv_π α i
rw [Iso.inv_comp_eq] at this
exact ConcreteCategory.congr_hom this x
|
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Yury Kudriashov, Yaël Dillies
-/
import Mathlib.Algebra.Order.Module.OrderedSMul
import Mathlib.Analysis.Convex.Star
import Mathlib.LinearAlgebra.AffineSpace.AffineSubspace
#align_import analysis.convex.basic from "leanprover-community/mathlib"@"92bd7b1ffeb306a89f450bee126ddd8a284c259d"
/-!
# Convex sets and functions in vector spaces
In a 𝕜-vector space, we define the following objects and properties.
* `Convex 𝕜 s`: A set `s` is convex if for any two points `x y ∈ s` it includes `segment 𝕜 x y`.
* `stdSimplex 𝕜 ι`: The standard simplex in `ι → 𝕜` (currently requires `Fintype ι`). It is the
intersection of the positive quadrant with the hyperplane `s.sum = 1`.
We also provide various equivalent versions of the definitions above, prove that some specific sets
are convex.
## TODO
Generalize all this file to affine spaces.
-/
variable {𝕜 E F β : Type*}
open LinearMap Set
open scoped Convex Pointwise
/-! ### Convexity of sets -/
section OrderedSemiring
variable [OrderedSemiring 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [AddCommMonoid F]
section SMul
variable (𝕜) [SMul 𝕜 E] [SMul 𝕜 F] (s : Set E) {x : E}
/-- Convexity of sets. -/
def Convex : Prop :=
∀ ⦃x : E⦄, x ∈ s → StarConvex 𝕜 x s
#align convex Convex
variable {𝕜 s}
theorem Convex.starConvex (hs : Convex 𝕜 s) (hx : x ∈ s) : StarConvex 𝕜 x s :=
hs hx
#align convex.star_convex Convex.starConvex
theorem convex_iff_segment_subset : Convex 𝕜 s ↔ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → [x -[𝕜] y] ⊆ s :=
forall₂_congr fun _ _ => starConvex_iff_segment_subset
#align convex_iff_segment_subset convex_iff_segment_subset
theorem Convex.segment_subset (h : Convex 𝕜 s) {x y : E} (hx : x ∈ s) (hy : y ∈ s) :
[x -[𝕜] y] ⊆ s :=
convex_iff_segment_subset.1 h hx hy
#align convex.segment_subset Convex.segment_subset
theorem Convex.openSegment_subset (h : Convex 𝕜 s) {x y : E} (hx : x ∈ s) (hy : y ∈ s) :
openSegment 𝕜 x y ⊆ s :=
(openSegment_subset_segment 𝕜 x y).trans (h.segment_subset hx hy)
#align convex.open_segment_subset Convex.openSegment_subset
/-- Alternative definition of set convexity, in terms of pointwise set operations. -/
theorem convex_iff_pointwise_add_subset :
Convex 𝕜 s ↔ ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 → a • s + b • s ⊆ s :=
Iff.intro
(by
rintro hA a b ha hb hab w ⟨au, ⟨u, hu, rfl⟩, bv, ⟨v, hv, rfl⟩, rfl⟩
exact hA hu hv ha hb hab)
fun h x hx y hy a b ha hb hab => (h ha hb hab) (Set.add_mem_add ⟨_, hx, rfl⟩ ⟨_, hy, rfl⟩)
#align convex_iff_pointwise_add_subset convex_iff_pointwise_add_subset
alias ⟨Convex.set_combo_subset, _⟩ := convex_iff_pointwise_add_subset
#align convex.set_combo_subset Convex.set_combo_subset
theorem convex_empty : Convex 𝕜 (∅ : Set E) := fun _ => False.elim
#align convex_empty convex_empty
theorem convex_univ : Convex 𝕜 (Set.univ : Set E) := fun _ _ => starConvex_univ _
#align convex_univ convex_univ
theorem Convex.inter {t : Set E} (hs : Convex 𝕜 s) (ht : Convex 𝕜 t) : Convex 𝕜 (s ∩ t) :=
fun _ hx => (hs hx.1).inter (ht hx.2)
#align convex.inter Convex.inter
theorem convex_sInter {S : Set (Set E)} (h : ∀ s ∈ S, Convex 𝕜 s) : Convex 𝕜 (⋂₀ S) := fun _ hx =>
starConvex_sInter fun _ hs => h _ hs <| hx _ hs
#align convex_sInter convex_sInter
theorem convex_iInter {ι : Sort*} {s : ι → Set E} (h : ∀ i, Convex 𝕜 (s i)) :
Convex 𝕜 (⋂ i, s i) :=
sInter_range s ▸ convex_sInter <| forall_mem_range.2 h
#align convex_Inter convex_iInter
theorem convex_iInter₂ {ι : Sort*} {κ : ι → Sort*} {s : ∀ i, κ i → Set E}
(h : ∀ i j, Convex 𝕜 (s i j)) : Convex 𝕜 (⋂ (i) (j), s i j) :=
convex_iInter fun i => convex_iInter <| h i
#align convex_Inter₂ convex_iInter₂
theorem Convex.prod {s : Set E} {t : Set F} (hs : Convex 𝕜 s) (ht : Convex 𝕜 t) :
Convex 𝕜 (s ×ˢ t) := fun _ hx => (hs hx.1).prod (ht hx.2)
#align convex.prod Convex.prod
theorem convex_pi {ι : Type*} {E : ι → Type*} [∀ i, AddCommMonoid (E i)] [∀ i, SMul 𝕜 (E i)]
{s : Set ι} {t : ∀ i, Set (E i)} (ht : ∀ ⦃i⦄, i ∈ s → Convex 𝕜 (t i)) : Convex 𝕜 (s.pi t) :=
fun _ hx => starConvex_pi fun _ hi => ht hi <| hx _ hi
#align convex_pi convex_pi
| Mathlib/Analysis/Convex/Basic.lean | 121 | 128 | theorem Directed.convex_iUnion {ι : Sort*} {s : ι → Set E} (hdir : Directed (· ⊆ ·) s)
(hc : ∀ ⦃i : ι⦄, Convex 𝕜 (s i)) : Convex 𝕜 (⋃ i, s i) := by |
rintro x hx y hy a b ha hb hab
rw [mem_iUnion] at hx hy ⊢
obtain ⟨i, hx⟩ := hx
obtain ⟨j, hy⟩ := hy
obtain ⟨k, hik, hjk⟩ := hdir i j
exact ⟨k, hc (hik hx) (hjk hy) ha hb hab⟩
|
/-
Copyright (c) 2022 Jakob von Raumer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jakob von Raumer
-/
import Mathlib.CategoryTheory.Abelian.Exact
import Mathlib.CategoryTheory.Preadditive.Injective
import Mathlib.CategoryTheory.Preadditive.Yoneda.Limits
import Mathlib.CategoryTheory.Preadditive.Yoneda.Injective
#align_import category_theory.abelian.injective from "leanprover-community/mathlib"@"f8d8465c3c392a93b9ed226956e26dee00975946"
/-!
# Injective objects in abelian categories
* Objects in an abelian categories are injective if and only if the preadditive Yoneda functor
on them preserves finite colimits.
-/
noncomputable section
open CategoryTheory
open CategoryTheory.Limits
open CategoryTheory.Injective
open Opposite
universe v u
namespace CategoryTheory
variable {C : Type u} [Category.{v} C] [Abelian C]
/-- The preadditive Yoneda functor on `J` preserves colimits if `J` is injective. -/
def preservesFiniteColimitsPreadditiveYonedaObjOfInjective (J : C) [hP : Injective J] :
PreservesFiniteColimits (preadditiveYonedaObj J) := by
letI := (injective_iff_preservesEpimorphisms_preadditive_yoneda_obj' J).mp hP
apply Functor.preservesFiniteColimitsOfPreservesEpisAndKernels
#align category_theory.preserves_finite_colimits_preadditive_yoneda_obj_of_injective CategoryTheory.preservesFiniteColimitsPreadditiveYonedaObjOfInjective
/-- An object is injective if its preadditive Yoneda functor preserves finite colimits. -/
| Mathlib/CategoryTheory/Abelian/Injective.lean | 45 | 48 | theorem injective_of_preservesFiniteColimits_preadditiveYonedaObj (J : C)
[hP : PreservesFiniteColimits (preadditiveYonedaObj J)] : Injective J := by |
rw [injective_iff_preservesEpimorphisms_preadditive_yoneda_obj']
infer_instance
|
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Probability.Martingale.Convergence
import Mathlib.Probability.Martingale.OptionalStopping
import Mathlib.Probability.Martingale.Centering
#align_import probability.martingale.borel_cantelli from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Generalized Borel-Cantelli lemma
This file proves Lévy's generalized Borel-Cantelli lemma which is a generalization of the
Borel-Cantelli lemmas. With this generalization, one can easily deduce the Borel-Cantelli lemmas
by choosing appropriate filtrations. This file also contains the one sided martingale bound which
is required to prove the generalized Borel-Cantelli.
**Note**: the usual Borel-Cantelli lemmas are not in this file. See
`MeasureTheory.measure_limsup_eq_zero` for the first (which does not depend on the results here),
and `ProbabilityTheory.measure_limsup_eq_one` for the second (which does).
## Main results
- `MeasureTheory.Submartingale.bddAbove_iff_exists_tendsto`: the one sided martingale bound: given
a submartingale `f` with uniformly bounded differences, the set for which `f` converges is almost
everywhere equal to the set for which it is bounded.
- `MeasureTheory.ae_mem_limsup_atTop_iff`: Lévy's generalized Borel-Cantelli:
given a filtration `ℱ` and a sequence of sets `s` such that `s n ∈ ℱ n` for all `n`,
`limsup atTop s` is almost everywhere equal to the set for which `∑ ℙ[s (n + 1)∣ℱ n] = ∞`.
-/
open Filter
open scoped NNReal ENNReal MeasureTheory ProbabilityTheory BigOperators Topology
namespace MeasureTheory
variable {Ω : Type*} {m0 : MeasurableSpace Ω} {μ : Measure Ω} {ℱ : Filtration ℕ m0} {f : ℕ → Ω → ℝ}
{ω : Ω}
/-!
### One sided martingale bound
-/
-- TODO: `leastGE` should be defined taking values in `WithTop ℕ` once the `stoppedProcess`
-- refactor is complete
/-- `leastGE f r n` is the stopping time corresponding to the first time `f ≥ r`. -/
noncomputable def leastGE (f : ℕ → Ω → ℝ) (r : ℝ) (n : ℕ) :=
hitting f (Set.Ici r) 0 n
#align measure_theory.least_ge MeasureTheory.leastGE
theorem Adapted.isStoppingTime_leastGE (r : ℝ) (n : ℕ) (hf : Adapted ℱ f) :
IsStoppingTime ℱ (leastGE f r n) :=
hitting_isStoppingTime hf measurableSet_Ici
#align measure_theory.adapted.is_stopping_time_least_ge MeasureTheory.Adapted.isStoppingTime_leastGE
theorem leastGE_le {i : ℕ} {r : ℝ} (ω : Ω) : leastGE f r i ω ≤ i :=
hitting_le ω
#align measure_theory.least_ge_le MeasureTheory.leastGE_le
-- The following four lemmas shows `leastGE` behaves like a stopped process. Ideally we should
-- define `leastGE` as a stopping time and take its stopped process. However, we can't do that
-- with our current definition since a stopping time takes only finite indicies. An upcomming
-- refactor should hopefully make it possible to have stopping times taking infinity as a value
theorem leastGE_mono {n m : ℕ} (hnm : n ≤ m) (r : ℝ) (ω : Ω) : leastGE f r n ω ≤ leastGE f r m ω :=
hitting_mono hnm
#align measure_theory.least_ge_mono MeasureTheory.leastGE_mono
theorem leastGE_eq_min (π : Ω → ℕ) (r : ℝ) (ω : Ω) {n : ℕ} (hπn : ∀ ω, π ω ≤ n) :
leastGE f r (π ω) ω = min (π ω) (leastGE f r n ω) := by
classical
refine le_antisymm (le_min (leastGE_le _) (leastGE_mono (hπn ω) r ω)) ?_
by_cases hle : π ω ≤ leastGE f r n ω
· rw [min_eq_left hle, leastGE]
by_cases h : ∃ j ∈ Set.Icc 0 (π ω), f j ω ∈ Set.Ici r
· refine hle.trans (Eq.le ?_)
rw [leastGE, ← hitting_eq_hitting_of_exists (hπn ω) h]
· simp only [hitting, if_neg h, le_rfl]
· rw [min_eq_right (not_le.1 hle).le, leastGE, leastGE, ←
hitting_eq_hitting_of_exists (hπn ω) _]
rw [not_le, leastGE, hitting_lt_iff _ (hπn ω)] at hle
exact
let ⟨j, hj₁, hj₂⟩ := hle
⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩
#align measure_theory.least_ge_eq_min MeasureTheory.leastGE_eq_min
theorem stoppedValue_stoppedValue_leastGE (f : ℕ → Ω → ℝ) (π : Ω → ℕ) (r : ℝ) {n : ℕ}
(hπn : ∀ ω, π ω ≤ n) : stoppedValue (fun i => stoppedValue f (leastGE f r i)) π =
stoppedValue (stoppedProcess f (leastGE f r n)) π := by
ext1 ω
simp (config := { unfoldPartialApp := true }) only [stoppedProcess, stoppedValue]
rw [leastGE_eq_min _ _ _ hπn]
#align measure_theory.stopped_value_stopped_value_least_ge MeasureTheory.stoppedValue_stoppedValue_leastGE
theorem Submartingale.stoppedValue_leastGE [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) (r : ℝ) :
Submartingale (fun i => stoppedValue f (leastGE f r i)) ℱ μ := by
rw [submartingale_iff_expected_stoppedValue_mono]
· intro σ π hσ hπ hσ_le_π hπ_bdd
obtain ⟨n, hπ_le_n⟩ := hπ_bdd
simp_rw [stoppedValue_stoppedValue_leastGE f σ r fun i => (hσ_le_π i).trans (hπ_le_n i)]
simp_rw [stoppedValue_stoppedValue_leastGE f π r hπ_le_n]
refine hf.expected_stoppedValue_mono ?_ ?_ ?_ fun ω => (min_le_left _ _).trans (hπ_le_n ω)
· exact hσ.min (hf.adapted.isStoppingTime_leastGE _ _)
· exact hπ.min (hf.adapted.isStoppingTime_leastGE _ _)
· exact fun ω => min_le_min (hσ_le_π ω) le_rfl
· exact fun i => stronglyMeasurable_stoppedValue_of_le hf.adapted.progMeasurable_of_discrete
(hf.adapted.isStoppingTime_leastGE _ _) leastGE_le
· exact fun i => integrable_stoppedValue _ (hf.adapted.isStoppingTime_leastGE _ _) hf.integrable
leastGE_le
#align measure_theory.submartingale.stopped_value_least_ge MeasureTheory.Submartingale.stoppedValue_leastGE
variable {r : ℝ} {R : ℝ≥0}
theorem norm_stoppedValue_leastGE_le (hr : 0 ≤ r) (hf0 : f 0 = 0)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) (i : ℕ) :
∀ᵐ ω ∂μ, stoppedValue f (leastGE f r i) ω ≤ r + R := by
filter_upwards [hbdd] with ω hbddω
change f (leastGE f r i ω) ω ≤ r + R
by_cases heq : leastGE f r i ω = 0
· rw [heq, hf0, Pi.zero_apply]
exact add_nonneg hr R.coe_nonneg
· obtain ⟨k, hk⟩ := Nat.exists_eq_succ_of_ne_zero heq
rw [hk, add_comm, ← sub_le_iff_le_add]
have := not_mem_of_lt_hitting (hk.symm ▸ k.lt_succ_self : k < leastGE f r i ω) (zero_le _)
simp only [Set.mem_union, Set.mem_Iic, Set.mem_Ici, not_or, not_le] at this
exact (sub_lt_sub_left this _).le.trans ((le_abs_self _).trans (hbddω _))
#align measure_theory.norm_stopped_value_least_ge_le MeasureTheory.norm_stoppedValue_leastGE_le
theorem Submartingale.stoppedValue_leastGE_snorm_le [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hr : 0 ≤ r) (hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) (i : ℕ) :
snorm (stoppedValue f (leastGE f r i)) 1 μ ≤ 2 * μ Set.univ * ENNReal.ofReal (r + R) := by
refine snorm_one_le_of_le' ((hf.stoppedValue_leastGE r).integrable _) ?_
(norm_stoppedValue_leastGE_le hr hf0 hbdd i)
rw [← integral_univ]
refine le_trans ?_ ((hf.stoppedValue_leastGE r).setIntegral_le (zero_le _) MeasurableSet.univ)
simp_rw [stoppedValue, leastGE, hitting_of_le le_rfl, hf0, integral_zero', le_rfl]
#align measure_theory.submartingale.stopped_value_least_ge_snorm_le MeasureTheory.Submartingale.stoppedValue_leastGE_snorm_le
theorem Submartingale.stoppedValue_leastGE_snorm_le' [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hr : 0 ≤ r) (hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) (i : ℕ) :
snorm (stoppedValue f (leastGE f r i)) 1 μ ≤
ENNReal.toNNReal (2 * μ Set.univ * ENNReal.ofReal (r + R)) := by
refine (hf.stoppedValue_leastGE_snorm_le hr hf0 hbdd i).trans ?_
simp [ENNReal.coe_toNNReal (measure_ne_top μ _), ENNReal.coe_toNNReal]
#align measure_theory.submartingale.stopped_value_least_ge_snorm_le' MeasureTheory.Submartingale.stoppedValue_leastGE_snorm_le'
/-- This lemma is superseded by `Submartingale.bddAbove_iff_exists_tendsto`. -/
theorem Submartingale.exists_tendsto_of_abs_bddAbove_aux [IsFiniteMeasure μ]
(hf : Submartingale f ℱ μ) (hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) → ∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c) := by
have ht :
∀ᵐ ω ∂μ, ∀ i : ℕ, ∃ c, Tendsto (fun n => stoppedValue f (leastGE f i n) ω) atTop (𝓝 c) := by
rw [ae_all_iff]
exact fun i => Submartingale.exists_ae_tendsto_of_bdd (hf.stoppedValue_leastGE i)
(hf.stoppedValue_leastGE_snorm_le' i.cast_nonneg hf0 hbdd)
filter_upwards [ht] with ω hω hωb
rw [BddAbove] at hωb
obtain ⟨i, hi⟩ := exists_nat_gt hωb.some
have hib : ∀ n, f n ω < i := by
intro n
exact lt_of_le_of_lt ((mem_upperBounds.1 hωb.some_mem) _ ⟨n, rfl⟩) hi
have heq : ∀ n, stoppedValue f (leastGE f i n) ω = f n ω := by
intro n
rw [leastGE]; unfold hitting; rw [stoppedValue]
rw [if_neg]
simp only [Set.mem_Icc, Set.mem_union, Set.mem_Ici]
push_neg
exact fun j _ => hib j
simp only [← heq, hω i]
#align measure_theory.submartingale.exists_tendsto_of_abs_bdd_above_aux MeasureTheory.Submartingale.exists_tendsto_of_abs_bddAbove_aux
theorem Submartingale.bddAbove_iff_exists_tendsto_aux [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hf0 : f 0 = 0) (hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) ↔ ∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c) := by
filter_upwards [hf.exists_tendsto_of_abs_bddAbove_aux hf0 hbdd] with ω hω using
⟨hω, fun ⟨c, hc⟩ => hc.bddAbove_range⟩
#align measure_theory.submartingale.bdd_above_iff_exists_tendsto_aux MeasureTheory.Submartingale.bddAbove_iff_exists_tendsto_aux
/-- One sided martingale bound: If `f` is a submartingale which has uniformly bounded differences,
then for almost every `ω`, `f n ω` is bounded above (in `n`) if and only if it converges. -/
theorem Submartingale.bddAbove_iff_exists_tendsto [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) ↔ ∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c) := by
set g : ℕ → Ω → ℝ := fun n ω => f n ω - f 0 ω
have hg : Submartingale g ℱ μ :=
hf.sub_martingale (martingale_const_fun _ _ (hf.adapted 0) (hf.integrable 0))
have hg0 : g 0 = 0 := by
ext ω
simp only [g, sub_self, Pi.zero_apply]
have hgbdd : ∀ᵐ ω ∂μ, ∀ i : ℕ, |g (i + 1) ω - g i ω| ≤ ↑R := by
simpa only [g, sub_sub_sub_cancel_right]
filter_upwards [hg.bddAbove_iff_exists_tendsto_aux hg0 hgbdd] with ω hω
convert hω using 1
· refine ⟨fun h => ?_, fun h => ?_⟩ <;> obtain ⟨b, hb⟩ := h <;>
refine ⟨b + |f 0 ω|, fun y hy => ?_⟩ <;> obtain ⟨n, rfl⟩ := hy
· simp_rw [g, sub_eq_add_neg]
exact add_le_add (hb ⟨n, rfl⟩) (neg_le_abs _)
· exact sub_le_iff_le_add.1 (le_trans (sub_le_sub_left (le_abs_self _) _) (hb ⟨n, rfl⟩))
· refine ⟨fun h => ?_, fun h => ?_⟩ <;> obtain ⟨c, hc⟩ := h
· exact ⟨c - f 0 ω, hc.sub_const _⟩
· refine ⟨c + f 0 ω, ?_⟩
have := hc.add_const (f 0 ω)
simpa only [g, sub_add_cancel]
#align measure_theory.submartingale.bdd_above_iff_exists_tendsto MeasureTheory.Submartingale.bddAbove_iff_exists_tendsto
/-!
### Lévy's generalization of the Borel-Cantelli lemma
Lévy's generalization of the Borel-Cantelli lemma states that: given a natural number indexed
filtration $(\mathcal{F}_n)$, and a sequence of sets $(s_n)$ such that for all
$n$, $s_n \in \mathcal{F}_n$, $limsup_n s_n$ is almost everywhere equal to the set for which
$\sum_n \mathbb{P}[s_n \mid \mathcal{F}_n] = \infty$.
The proof strategy follows by constructing a martingale satisfying the one sided martingale bound.
In particular, we define
$$
f_n := \sum_{k < n} \mathbf{1}_{s_{n + 1}} - \mathbb{P}[s_{n + 1} \mid \mathcal{F}_n].
$$
Then, as a martingale is both a sub and a super-martingale, the set for which it is unbounded from
above must agree with the set for which it is unbounded from below almost everywhere. Thus, it
can only converge to $\pm \infty$ with probability 0. Thus, by considering
$$
\limsup_n s_n = \{\sum_n \mathbf{1}_{s_n} = \infty\}
$$
almost everywhere, the result follows.
-/
theorem Martingale.bddAbove_range_iff_bddBelow_range [IsFiniteMeasure μ] (hf : Martingale f ℱ μ)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, BddAbove (Set.range fun n => f n ω) ↔ BddBelow (Set.range fun n => f n ω) := by
have hbdd' : ∀ᵐ ω ∂μ, ∀ i, |(-f) (i + 1) ω - (-f) i ω| ≤ R := by
filter_upwards [hbdd] with ω hω i
erw [← abs_neg, neg_sub, sub_neg_eq_add, neg_add_eq_sub]
exact hω i
have hup := hf.submartingale.bddAbove_iff_exists_tendsto hbdd
have hdown := hf.neg.submartingale.bddAbove_iff_exists_tendsto hbdd'
filter_upwards [hup, hdown] with ω hω₁ hω₂
have : (∃ c, Tendsto (fun n => f n ω) atTop (𝓝 c)) ↔
∃ c, Tendsto (fun n => (-f) n ω) atTop (𝓝 c) := by
constructor <;> rintro ⟨c, hc⟩
· exact ⟨-c, hc.neg⟩
· refine ⟨-c, ?_⟩
convert hc.neg
simp only [neg_neg, Pi.neg_apply]
rw [hω₁, this, ← hω₂]
constructor <;> rintro ⟨c, hc⟩ <;> refine ⟨-c, fun ω hω => ?_⟩
· rw [mem_upperBounds] at hc
refine neg_le.2 (hc _ ?_)
simpa only [Pi.neg_apply, Set.mem_range, neg_inj]
· rw [mem_lowerBounds] at hc
simp_rw [Set.mem_range, Pi.neg_apply, neg_eq_iff_eq_neg] at hω
refine le_neg.1 (hc _ ?_)
simpa only [Set.mem_range]
#align measure_theory.martingale.bdd_above_range_iff_bdd_below_range MeasureTheory.Martingale.bddAbove_range_iff_bddBelow_range
theorem Martingale.ae_not_tendsto_atTop_atTop [IsFiniteMeasure μ] (hf : Martingale f ℱ μ)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, ¬Tendsto (fun n => f n ω) atTop atTop := by
filter_upwards [hf.bddAbove_range_iff_bddBelow_range hbdd] with ω hω htop using
unbounded_of_tendsto_atTop htop (hω.2 <| bddBelow_range_of_tendsto_atTop_atTop htop)
#align measure_theory.martingale.ae_not_tendsto_at_top_at_top MeasureTheory.Martingale.ae_not_tendsto_atTop_atTop
theorem Martingale.ae_not_tendsto_atTop_atBot [IsFiniteMeasure μ] (hf : Martingale f ℱ μ)
(hbdd : ∀ᵐ ω ∂μ, ∀ i, |f (i + 1) ω - f i ω| ≤ R) :
∀ᵐ ω ∂μ, ¬Tendsto (fun n => f n ω) atTop atBot := by
filter_upwards [hf.bddAbove_range_iff_bddBelow_range hbdd] with ω hω htop using
unbounded_of_tendsto_atBot htop (hω.1 <| bddAbove_range_of_tendsto_atTop_atBot htop)
#align measure_theory.martingale.ae_not_tendsto_at_top_at_bot MeasureTheory.Martingale.ae_not_tendsto_atTop_atBot
namespace BorelCantelli
/-- Auxiliary definition required to prove Lévy's generalization of the Borel-Cantelli lemmas for
which we will take the martingale part. -/
noncomputable def process (s : ℕ → Set Ω) (n : ℕ) : Ω → ℝ :=
∑ k ∈ Finset.range n, (s (k + 1)).indicator 1
#align measure_theory.borel_cantelli.process MeasureTheory.BorelCantelli.process
variable {s : ℕ → Set Ω}
theorem process_zero : process s 0 = 0 := by rw [process, Finset.range_zero, Finset.sum_empty]
#align measure_theory.borel_cantelli.process_zero MeasureTheory.BorelCantelli.process_zero
theorem adapted_process (hs : ∀ n, MeasurableSet[ℱ n] (s n)) : Adapted ℱ (process s) := fun _ =>
Finset.stronglyMeasurable_sum' _ fun _ hk =>
stronglyMeasurable_one.indicator <| ℱ.mono (Finset.mem_range.1 hk) _ <| hs _
#align measure_theory.borel_cantelli.adapted_process MeasureTheory.BorelCantelli.adapted_process
theorem martingalePart_process_ae_eq (ℱ : Filtration ℕ m0) (μ : Measure Ω) (s : ℕ → Set Ω) (n : ℕ) :
martingalePart (process s) ℱ μ n =
∑ k ∈ Finset.range n, ((s (k + 1)).indicator 1 - μ[(s (k + 1)).indicator 1|ℱ k]) := by
simp only [martingalePart_eq_sum, process_zero, zero_add]
refine Finset.sum_congr rfl fun k _ => ?_
simp only [process, Finset.sum_range_succ_sub_sum]
#align measure_theory.borel_cantelli.martingale_part_process_ae_eq MeasureTheory.BorelCantelli.martingalePart_process_ae_eq
| Mathlib/Probability/Martingale/BorelCantelli.lean | 303 | 308 | theorem predictablePart_process_ae_eq (ℱ : Filtration ℕ m0) (μ : Measure Ω) (s : ℕ → Set Ω)
(n : ℕ) : predictablePart (process s) ℱ μ n =
∑ k ∈ Finset.range n, μ[(s (k + 1)).indicator (1 : Ω → ℝ)|ℱ k] := by |
have := martingalePart_process_ae_eq ℱ μ s n
simp_rw [martingalePart, process, Finset.sum_sub_distrib] at this
exact sub_right_injective this
|
/-
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.Measure.NullMeasurable
import Mathlib.MeasureTheory.MeasurableSpace.Basic
import Mathlib.Topology.Algebra.Order.LiminfLimsup
#align_import measure_theory.measure.measure_space from "leanprover-community/mathlib"@"343e80208d29d2d15f8050b929aa50fe4ce71b55"
/-!
# 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
open scoped Classical symmDiff
open Topology Filter ENNReal NNReal Interval MeasureTheory
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⟩⟩
#align measure_theory.ae_is_measurably_generated MeasureTheory.ae_isMeasurablyGenerated
/-- 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]
#align measure_theory.ae_uIoc_iff MeasureTheory.ae_uIoc_iff
theorem measure_union (hd : Disjoint s₁ s₂) (h : MeasurableSet s₂) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀ h.nullMeasurableSet hd.aedisjoint
#align measure_theory.measure_union MeasureTheory.measure_union
theorem measure_union' (hd : Disjoint s₁ s₂) (h : MeasurableSet s₁) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀' h.nullMeasurableSet hd.aedisjoint
#align measure_theory.measure_union' MeasureTheory.measure_union'
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
#align measure_theory.measure_inter_add_diff MeasureTheory.measure_inter_add_diff
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)
#align measure_theory.measure_diff_add_inter MeasureTheory.measure_diff_add_inter
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
#align measure_theory.measure_union_add_inter MeasureTheory.measure_union_add_inter
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]
#align measure_theory.measure_union_add_inter' MeasureTheory.measure_union_add_inter'
lemma measure_symmDiff_eq (hs : MeasurableSet s) (ht : MeasurableSet t) :
μ (s ∆ t) = μ (s \ t) + μ (t \ s) := by
simpa only [symmDiff_def, sup_eq_union] using measure_union disjoint_sdiff_sdiff (ht.diff hs)
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_add_measure_compl (h : MeasurableSet s) : μ s + μ sᶜ = μ univ :=
measure_add_measure_compl₀ h.nullMeasurableSet
#align measure_theory.measure_add_measure_compl MeasureTheory.measure_add_measure_compl
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
#align measure_theory.measure_bUnion₀ MeasureTheory.measure_biUnion₀
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
#align measure_theory.measure_bUnion MeasureTheory.measure_biUnion
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]
#align measure_theory.measure_sUnion₀ MeasureTheory.measure_sUnion₀
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]
#align measure_theory.measure_sUnion MeasureTheory.measure_sUnion
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
#align measure_theory.measure_bUnion_finset₀ MeasureTheory.measure_biUnion_finset₀
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
#align measure_theory.measure_bUnion_finset MeasureTheory.measure_biUnion_finset
/-- 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))
#align measure_theory.tsum_meas_le_meas_Union_of_disjoint MeasureTheory.tsum_meas_le_meas_iUnion_of_disjoint
/-- 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]
#align measure_theory.tsum_measure_preimage_singleton MeasureTheory.tsum_measure_preimage_singleton
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]
#align measure_theory.sum_measure_preimage_singleton MeasureTheory.sum_measure_preimage_singleton
theorem measure_diff_null' (h : μ (s₁ ∩ s₂) = 0) : μ (s₁ \ s₂) = μ s₁ :=
measure_congr <| diff_ae_eq_self.2 h
#align measure_theory.measure_diff_null' MeasureTheory.measure_diff_null'
theorem measure_add_diff (hs : MeasurableSet s) (t : Set α) : μ s + μ (t \ s) = μ (s ∪ t) := by
rw [← measure_union' disjoint_sdiff_right hs, union_diff_self]
#align measure_theory.measure_add_diff MeasureTheory.measure_add_diff
theorem measure_diff' (s : Set α) (hm : MeasurableSet t) (h_fin : μ t ≠ ∞) :
μ (s \ t) = μ (s ∪ t) - μ t :=
Eq.symm <| ENNReal.sub_eq_of_add_eq h_fin <| by rw [add_comm, measure_add_diff hm, union_comm]
#align measure_theory.measure_diff' MeasureTheory.measure_diff'
theorem measure_diff (h : s₂ ⊆ s₁) (h₂ : MeasurableSet s₂) (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]
#align measure_theory.measure_diff MeasureTheory.measure_diff
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
#align measure_theory.le_measure_diff MeasureTheory.le_measure_diff
/-- 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 := (WithTop.sub_eq_top_iff.2 ⟨hμu, hμv⟩).symm
_ ≤ 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 : MeasurableSet s) (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
#align measure_theory.measure_diff_lt_of_lt_add MeasureTheory.measure_diff_lt_of_lt_add
theorem measure_diff_le_iff_le_add (hs : MeasurableSet s) (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]
#align measure_theory.measure_diff_le_iff_le_add MeasureTheory.measure_diff_le_iff_le_add
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)
#align measure_theory.measure_eq_measure_of_null_diff MeasureTheory.measure_eq_measure_of_null_diff
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)⟩
#align measure_theory.measure_eq_measure_of_between_null_diff MeasureTheory.measure_eq_measure_of_between_null_diff
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
#align measure_theory.measure_eq_measure_smaller_of_between_null_diff MeasureTheory.measure_eq_measure_smaller_of_between_null_diff
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
#align measure_theory.measure_eq_measure_larger_of_between_null_diff MeasureTheory.measure_eq_measure_larger_of_between_null_diff
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
#align measure_theory.measure_compl MeasureTheory.measure_compl
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⟩⟩
#align measure_theory.union_ae_eq_left_iff_ae_subset MeasureTheory.union_ae_eq_left_iff_ae_subset
@[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]
#align measure_theory.union_ae_eq_right_iff_ae_subset MeasureTheory.union_ae_eq_right_iff_ae_subset
theorem ae_eq_of_ae_subset_of_measure_ge (h₁ : s ≤ᵐ[μ] t) (h₂ : μ t ≤ μ s) (hsm : MeasurableSet s)
(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]
#align measure_theory.ae_eq_of_ae_subset_of_measure_ge MeasureTheory.ae_eq_of_ae_subset_of_measure_ge
/-- 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 : MeasurableSet s)
(ht : μ t ≠ ∞) : s =ᵐ[μ] t :=
ae_eq_of_ae_subset_of_measure_ge (HasSubset.Subset.eventuallyLE h₁) h₂ hsm ht
#align measure_theory.ae_eq_of_subset_of_measure_ge MeasureTheory.ae_eq_of_subset_of_measure_ge
theorem measure_iUnion_congr_of_subset [Countable β] {s : β → Set α} {t : β → Set α}
(hsub : ∀ b, s b ⊆ t b) (h_le : ∀ b, μ (t b) ≤ μ (s b)) : μ (⋃ b, s b) = μ (⋃ b, t b) := by
rcases Classical.em (∃ b, μ (t b) = ∞) with (⟨b, hb⟩ | htop)
· calc
μ (⋃ b, s b) = ∞ := top_unique (hb ▸ (h_le b).trans <| measure_mono <| subset_iUnion _ _)
_ = μ (⋃ b, t b) := Eq.symm <| top_unique <| hb ▸ measure_mono (subset_iUnion _ _)
push_neg at htop
refine le_antisymm (measure_mono (iUnion_mono hsub)) ?_
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 _ _)
· exact (measurableSet_toMeasurable _ _).inter (measurableSet_toMeasurable _ _)
· 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 _
#align measure_theory.measure_Union_congr_of_subset MeasureTheory.measure_iUnion_congr_of_subset
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⟩)
#align measure_theory.measure_union_congr_of_subset MeasureTheory.measure_union_congr_of_subset
@[simp]
theorem measure_iUnion_toMeasurable [Countable β] (s : β → Set α) :
μ (⋃ b, toMeasurable μ (s b)) = μ (⋃ b, s b) :=
Eq.symm <|
measure_iUnion_congr_of_subset (fun _b => subset_toMeasurable _ _) fun _b =>
(measure_toMeasurable _).le
#align measure_theory.measure_Union_to_measurable MeasureTheory.measure_iUnion_toMeasurable
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]
#align measure_theory.measure_bUnion_to_measurable MeasureTheory.measure_biUnion_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
#align measure_theory.measure_to_measurable_union MeasureTheory.measure_toMeasurable_union
@[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
#align measure_theory.measure_union_to_measurable MeasureTheory.measure_union_toMeasurable
theorem sum_measure_le_measure_univ {s : Finset ι} {t : ι → Set α}
(h : ∀ i ∈ s, MeasurableSet (t i)) (H : Set.PairwiseDisjoint (↑s) t) :
(∑ i ∈ s, μ (t i)) ≤ μ (univ : Set α) := by
rw [← measure_biUnion_finset H h]
exact measure_mono (subset_univ _)
#align measure_theory.sum_measure_le_measure_univ MeasureTheory.sum_measure_le_measure_univ
theorem tsum_measure_le_measure_univ {s : ι → Set α} (hs : ∀ i, MeasurableSet (s i))
(H : Pairwise (Disjoint 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
#align measure_theory.tsum_measure_le_measure_univ MeasureTheory.tsum_measure_le_measure_univ
/-- 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, MeasurableSet (s i))
(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)
#align measure_theory.exists_nonempty_inter_of_measure_univ_lt_tsum_measure MeasureTheory.exists_nonempty_inter_of_measure_univ_lt_tsum_measure
/-- 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, MeasurableSet (t i))
(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)
#align measure_theory.exists_nonempty_inter_of_measure_univ_lt_sum_measure MeasureTheory.exists_nonempty_inter_of_measure_univ_lt_sum_measure
/-- 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)
#align measure_theory.nonempty_inter_of_measure_lt_add MeasureTheory.nonempty_inter_of_measure_lt_add
/-- 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
#align measure_theory.nonempty_inter_of_measure_lt_add' MeasureTheory.nonempty_inter_of_measure_lt_add'
/-- Continuity from below: the measure of the union of a directed sequence of (not necessarily
-measurable) sets is the supremum of the measures. -/
theorem measure_iUnion_eq_iSup [Countable ι] {s : ι → Set α} (hd : Directed (· ⊆ ·) s) :
μ (⋃ i, s i) = ⨆ i, μ (s i) := by
cases nonempty_encodable ι
-- WLOG, `ι = ℕ`
generalize ht : Function.extend Encodable.encode s ⊥ = t
replace hd : Directed (· ⊆ ·) t := ht ▸ hd.extend_bot Encodable.encode_injective
suffices μ (⋃ n, t n) = ⨆ n, μ (t n) by
simp only [← ht, Function.apply_extend μ, ← iSup_eq_iUnion,
iSup_extend_bot Encodable.encode_injective, (· ∘ ·), Pi.bot_apply, bot_eq_empty,
measure_empty] at this
exact this.trans (iSup_extend_bot Encodable.encode_injective _)
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) :=
MeasurableSet.disjointed fun n => measurableSet_toMeasurable _ _
calc
μ (⋃ n, t n) ≤ μ (⋃ n, T n) := measure_mono (iUnion_mono fun i => subset_toMeasurable _ _)
_ = μ (⋃ n, Td n) := by rw [iUnion_disjointed]
_ ≤ ∑' 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
#align measure_theory.measure_Union_eq_supr MeasureTheory.measure_iUnion_eq_iSup
/-- 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' {α ι : Type*} [MeasurableSpace α] {μ : Measure α}
[Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)]
{f : ι → Set α} : μ (⋃ i, f i) = ⨆ i, μ (Accumulate f i) := by
have hd : Directed (· ⊆ ·) (Accumulate f) := by
intro i j
rcases directed_of (· ≤ ·) i j with ⟨k, rik, rjk⟩
exact ⟨k, biUnion_subset_biUnion_left fun l rli ↦ le_trans rli rik,
biUnion_subset_biUnion_left fun l rlj ↦ le_trans rlj rjk⟩
rw [← iUnion_accumulate]
exact measure_iUnion_eq_iSup hd
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.toEncodable
rw [biUnion_eq_iUnion, measure_iUnion_eq_iSup hd.directed_val, ← iSup_subtype'']
#align measure_theory.measure_bUnion_eq_supr MeasureTheory.measure_biUnion_eq_iSup
/-- Continuity from above: the measure of the intersection of a decreasing sequence of measurable
sets is the infimum of the measures. -/
theorem measure_iInter_eq_iInf [Countable ι] {s : ι → Set α} (h : ∀ i, MeasurableSet (s i))
(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 _ k), ENNReal.sub_iInf, ←
ENNReal.sub_sub_cancel hk (measure_mono (iInter_subset _ k)), ←
measure_diff (iInter_subset _ k) (MeasurableSet.iInter h) (this _ (iInter_subset _ k)),
diff_iInter, measure_iUnion_eq_iSup]
· congr 1
refine le_antisymm (iSup_mono' fun i => ?_) (iSup_mono fun i => ?_)
· rcases hd i k with ⟨j, hji, hjk⟩
use j
rw [← measure_diff hjk (h _) (this _ hjk)]
gcongr
· rw [tsub_le_iff_right, ← measure_union, Set.union_comm]
· exact measure_mono (diff_subset_iff.1 Subset.rfl)
· apply disjoint_sdiff_left
· apply h i
· exact hd.mono_comp _ fun _ _ => diff_subset_diff_right
#align measure_theory.measure_Inter_eq_infi MeasureTheory.measure_iInter_eq_iInf
/-- 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' {α ι : Type*} [MeasurableSpace α] {μ : Measure α}
[Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)]
{f : ι → Set α} (h : ∀ i, MeasurableSet (f i)) (hfin : ∃ i, μ (f i) ≠ ∞) :
μ (⋂ i, f i) = ⨅ i, μ (⋂ j ≤ i, f j) := by
let s := fun i ↦ ⋂ j ≤ i, f j
have iInter_eq : ⋂ i, f i = ⋂ i, s i := by
ext x; simp [s]; constructor
· exact fun h _ j _ ↦ h j
· intro h i
rcases directed_of (· ≤ ·) i i with ⟨j, rij, -⟩
exact h j i rij
have ms : ∀ i, MeasurableSet (s i) :=
fun i ↦ MeasurableSet.biInter (countable_univ.mono <| subset_univ _) fun i _ ↦ h i
have hd : Directed (· ⊇ ·) s := by
intro i j
rcases directed_of (· ≤ ·) i j with ⟨k, rik, rjk⟩
exact ⟨k, biInter_subset_biInter_left fun j rji ↦ le_trans rji rik,
biInter_subset_biInter_left fun i rij ↦ le_trans rij rjk⟩
have hfin' : ∃ i, μ (s i) ≠ ∞ := by
rcases hfin with ⟨i, hi⟩
rcases directed_of (· ≤ ·) i i with ⟨j, rij, -⟩
exact ⟨j, ne_top_of_le_ne_top hi <| measure_mono <| biInter_subset_of_mem rij⟩
exact iInter_eq ▸ measure_iInter_eq_iInf ms hd hfin'
/-- 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 [Preorder ι] [IsDirected ι (· ≤ ·)] [Countable ι]
{s : ι → Set α} (hm : Monotone s) : Tendsto (μ ∘ s) atTop (𝓝 (μ (⋃ n, s n))) := by
rw [measure_iUnion_eq_iSup hm.directed_le]
exact tendsto_atTop_iSup fun n m hnm => measure_mono <| hm hnm
#align measure_theory.tendsto_measure_Union MeasureTheory.tendsto_measure_iUnion
/-- 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' {α ι : Type*} [MeasurableSpace α] {μ : Measure α} [Countable ι]
[Preorder ι] [IsDirected ι (· ≤ ·)] {f : ι → Set α} :
Tendsto (fun i ↦ μ (Accumulate f i)) atTop (𝓝 (μ (⋃ i, f i))) := by
rw [measure_iUnion_eq_iSup']
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 [Countable ι] [Preorder ι] [IsDirected ι (· ≤ ·)] {s : ι → Set α}
(hs : ∀ n, MeasurableSet (s n)) (hm : Antitone s) (hf : ∃ i, μ (s i) ≠ ∞) :
Tendsto (μ ∘ s) atTop (𝓝 (μ (⋂ n, s n))) := by
rw [measure_iInter_eq_iInf hs hm.directed_ge hf]
exact tendsto_atTop_iInf fun n m hnm => measure_mono <| hm hnm
#align measure_theory.tendsto_measure_Inter MeasureTheory.tendsto_measure_iInter
/-- 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' {α ι : Type*} [MeasurableSpace α] {μ : Measure α} [Countable ι]
[Preorder ι] [IsDirected ι (· ≤ ·)] {f : ι → Set α} (hm : ∀ i, MeasurableSet (f i))
(hf : ∃ i, μ (f i) ≠ ∞) :
Tendsto (fun i ↦ μ (⋂ j ∈ {j | j ≤ i}, f j)) atTop (𝓝 (μ (⋂ i, f i))) := by
rw [measure_iInter_eq_iInf' hm hf]
exact tendsto_atTop_iInf
fun i j hij ↦ measure_mono <| biInter_subset_biInter_left fun k hki ↦ le_trans hki hij
/-- 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, MeasurableSet (s r)) (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
refine tendsto_order.2 ⟨fun l hl => ?_, fun L hL => ?_⟩
· filter_upwards [self_mem_nhdsWithin (s := Ioi a)] with r hr using hl.trans_le
(measure_mono (biInter_subset_of_mem hr))
obtain ⟨u, u_anti, u_pos, u_lim⟩ :
∃ u : ℕ → ι, StrictAnti u ∧ (∀ n : ℕ, a < u n) ∧ Tendsto u atTop (𝓝 a) := by
rcases hf with ⟨r, ar, _⟩
rcases exists_seq_strictAnti_tendsto' ar with ⟨w, w_anti, w_mem, w_lim⟩
exact ⟨w, w_anti, fun n => (w_mem n).1, w_lim⟩
have A : Tendsto (μ ∘ s ∘ u) atTop (𝓝 (μ (⋂ n, s (u n)))) := by
refine tendsto_measure_iInter (fun n => hs _ (u_pos n)) ?_ ?_
· intro m n hmn
exact hm _ _ (u_pos n) (u_anti.antitone hmn)
· rcases hf with ⟨r, rpos, hr⟩
obtain ⟨n, hn⟩ : ∃ n : ℕ, u n < r := ((tendsto_order.1 u_lim).2 r rpos).exists
refine ⟨n, ne_of_lt (lt_of_le_of_lt ?_ hr.lt_top)⟩
exact measure_mono (hm _ _ (u_pos n) hn.le)
have B : ⋂ n, s (u n) = ⋂ r > a, s r := by
apply Subset.antisymm
· simp only [subset_iInter_iff, gt_iff_lt]
intro r rpos
obtain ⟨n, hn⟩ : ∃ n, u n < r := ((tendsto_order.1 u_lim).2 _ rpos).exists
exact Subset.trans (iInter_subset _ n) (hm (u n) r (u_pos n) hn.le)
· simp only [subset_iInter_iff, gt_iff_lt]
intro n
apply biInter_subset_of_mem
exact u_pos n
rw [B] at A
obtain ⟨n, hn⟩ : ∃ n, μ (s (u n)) < L := ((tendsto_order.1 A).2 _ hL).exists
have : Ioc a (u n) ∈ 𝓝[>] a := Ioc_mem_nhdsWithin_Ioi ⟨le_rfl, u_pos n⟩
filter_upwards [this] with r hr using lt_of_le_of_lt (measure_mono (hm _ _ hr.1 hr.2)) hn
#align measure_theory.tendsto_measure_bInter_gt MeasureTheory.tendsto_measure_biInter_gt
/-- One direction of the **Borel-Cantelli lemma** (sometimes called the "*first* Borel-Cantelli
lemma"): if (sᵢ) is a sequence of sets such that `∑ μ sᵢ` is finite, then the limit superior of the
`sᵢ` is a null set.
Note: for the *second* Borel-Cantelli lemma (applying to independent sets in a probability space),
see `ProbabilityTheory.measure_limsup_eq_one`. -/
theorem measure_limsup_eq_zero {s : ℕ → Set α} (hs : (∑' i, μ (s i)) ≠ ∞) :
μ (limsup s atTop) = 0 := by
-- First we replace the sequence `sₙ` with a sequence of measurable sets `tₙ ⊇ sₙ` of the same
-- measure.
set t : ℕ → Set α := fun n => toMeasurable μ (s n)
have ht : (∑' i, μ (t i)) ≠ ∞ := by simpa only [t, measure_toMeasurable] using hs
suffices μ (limsup t atTop) = 0 by
have A : s ≤ t := fun n => subset_toMeasurable μ (s n)
-- TODO default args fail
exact measure_mono_null (limsup_le_limsup (eventually_of_forall (Pi.le_def.mp A))) this
-- Next we unfold `limsup` for sets and replace equality with an inequality
simp only [limsup_eq_iInf_iSup_of_nat', Set.iInf_eq_iInter, Set.iSup_eq_iUnion, ←
nonpos_iff_eq_zero]
-- Finally, we estimate `μ (⋃ i, t (i + n))` by `∑ i', μ (t (i + n))`
refine
le_of_tendsto_of_tendsto'
(tendsto_measure_iInter
(fun i => MeasurableSet.iUnion fun b => measurableSet_toMeasurable _ _) ?_
⟨0, ne_top_of_le_ne_top ht (measure_iUnion_le t)⟩)
(ENNReal.tendsto_sum_nat_add (μ ∘ t) ht) fun n => measure_iUnion_le _
intro n m hnm x
simp only [Set.mem_iUnion]
exact fun ⟨i, hi⟩ => ⟨i + (m - n), by simpa only [add_assoc, tsub_add_cancel_of_le hnm] using hi⟩
#align measure_theory.measure_limsup_eq_zero MeasureTheory.measure_limsup_eq_zero
theorem measure_liminf_eq_zero {s : ℕ → Set α} (h : (∑' i, μ (s i)) ≠ ∞) :
μ (liminf s atTop) = 0 := by
rw [← le_zero_iff]
have : liminf s atTop ≤ limsup s atTop := liminf_le_limsup
exact (μ.mono this).trans (by simp [measure_limsup_eq_zero h])
#align measure_theory.measure_liminf_eq_zero MeasureTheory.measure_liminf_eq_zero
-- Need to specify `α := Set α` below because of diamond; see #19041
theorem limsup_ae_eq_of_forall_ae_eq (s : ℕ → Set α) {t : Set α}
(h : ∀ n, s n =ᵐ[μ] t) : limsup (α := Set α) s atTop =ᵐ[μ] t := by
simp_rw [ae_eq_set] at h ⊢
constructor
· rw [atTop.limsup_sdiff s t]
apply measure_limsup_eq_zero
simp [h]
· rw [atTop.sdiff_limsup s t]
apply measure_liminf_eq_zero
simp [h]
#align measure_theory.limsup_ae_eq_of_forall_ae_eq MeasureTheory.limsup_ae_eq_of_forall_ae_eq
-- Need to specify `α := Set α` above because of diamond; see #19041
theorem liminf_ae_eq_of_forall_ae_eq (s : ℕ → Set α) {t : Set α}
(h : ∀ n, s n =ᵐ[μ] t) : liminf (α := Set α) s atTop =ᵐ[μ] t := by
simp_rw [ae_eq_set] at h ⊢
constructor
· rw [atTop.liminf_sdiff s t]
apply measure_liminf_eq_zero
simp [h]
· rw [atTop.sdiff_liminf s t]
apply measure_limsup_eq_zero
simp [h]
#align measure_theory.liminf_ae_eq_of_forall_ae_eq MeasureTheory.liminf_ae_eq_of_forall_ae_eq
theorem measure_if {x : β} {t : Set β} {s : Set α} :
μ (if x ∈ t then s else ∅) = indicator t (fun _ => μ s) x := by split_ifs with h <;> simp [h]
#align measure_theory.measure_if MeasureTheory.measure_if
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
#align measure_theory.outer_measure.to_measure MeasureTheory.OuterMeasure.toMeasure
theorem le_toOuterMeasure_caratheodory (μ : Measure α) : ms ≤ μ.toOuterMeasure.caratheodory :=
fun _s hs _t => (measure_inter_add_diff _ hs).symm
#align measure_theory.le_to_outer_measure_caratheodory MeasureTheory.le_toOuterMeasure_caratheodory
@[simp]
theorem toMeasure_toOuterMeasure (m : OuterMeasure α) (h : ms ≤ m.caratheodory) :
(m.toMeasure h).toOuterMeasure = m.trim :=
rfl
#align measure_theory.to_measure_to_outer_measure MeasureTheory.toMeasure_toOuterMeasure
@[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
#align measure_theory.to_measure_apply MeasureTheory.toMeasure_apply
theorem le_toMeasure_apply (m : OuterMeasure α) (h : ms ≤ m.caratheodory) (s : Set α) :
m s ≤ m.toMeasure h s :=
m.le_trim s
#align measure_theory.le_to_measure_apply MeasureTheory.le_toMeasure_apply
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
#align measure_theory.to_measure_apply₀ MeasureTheory.toMeasure_apply₀
@[simp]
theorem toOuterMeasure_toMeasure {μ : Measure α} :
μ.toOuterMeasure.toMeasure (le_toOuterMeasure_caratheodory _) = μ :=
Measure.ext fun _s => μ.toOuterMeasure.trim_eq
#align measure_theory.to_outer_measure_to_measure MeasureTheory.toOuterMeasure_toMeasure
@[simp]
theorem boundedBy_measure (μ : Measure α) : OuterMeasure.boundedBy μ = μ.toOuterMeasure :=
μ.toOuterMeasure.boundedBy_eq_self
#align measure_theory.bounded_by_measure MeasureTheory.boundedBy_measure
end OuterMeasure
section
/- Porting note: These variables are wrapped by an anonymous section because they interrupt
synthesizing instances in `MeasureSpace` section. -/
variable {m0 : MeasurableSpace α} [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
#align measure_theory.measure.measure_inter_eq_of_measure_eq MeasureTheory.Measure.measure_inter_eq_of_measure_eq
/-- 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
#align measure_theory.measure.measure_to_measurable_inter MeasureTheory.Measure.measure_toMeasurable_inter
/-! ### 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 }⟩
#align measure_theory.measure.has_zero MeasureTheory.Measure.instZero
@[simp]
theorem zero_toOuterMeasure {_m : MeasurableSpace α} : (0 : Measure α).toOuterMeasure = 0 :=
rfl
#align measure_theory.measure.zero_to_outer_measure MeasureTheory.Measure.zero_toOuterMeasure
@[simp, norm_cast]
theorem coe_zero {_m : MeasurableSpace α} : ⇑(0 : Measure α) = 0 :=
rfl
#align measure_theory.measure.coe_zero MeasureTheory.Measure.coe_zero
@[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]⟩
#align measure_theory.measure.subsingleton MeasureTheory.Measure.instSubsingleton
theorem eq_zero_of_isEmpty [IsEmpty α] {_m : MeasurableSpace α} (μ : Measure α) : μ = 0 :=
Subsingleton.elim μ 0
#align measure_theory.measure.eq_zero_of_is_empty MeasureTheory.Measure.eq_zero_of_isEmpty
instance instInhabited [MeasurableSpace α] : Inhabited (Measure α) :=
⟨0⟩
#align measure_theory.measure.inhabited MeasureTheory.Measure.instInhabited
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] }⟩
#align measure_theory.measure.has_add MeasureTheory.Measure.instAdd
@[simp]
theorem add_toOuterMeasure {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) :
(μ₁ + μ₂).toOuterMeasure = μ₁.toOuterMeasure + μ₂.toOuterMeasure :=
rfl
#align measure_theory.measure.add_to_outer_measure MeasureTheory.Measure.add_toOuterMeasure
@[simp, norm_cast]
theorem coe_add {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) : ⇑(μ₁ + μ₂) = μ₁ + μ₂ :=
rfl
#align measure_theory.measure.coe_add MeasureTheory.Measure.coe_add
theorem add_apply {_m : MeasurableSpace α} (μ₁ μ₂ : Measure α) (s : Set α) :
(μ₁ + μ₂) s = μ₁ s + μ₂ s :=
rfl
#align measure_theory.measure.add_apply MeasureTheory.Measure.add_apply
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] }⟩
#align measure_theory.measure.has_smul MeasureTheory.Measure.instSMul
@[simp]
theorem smul_toOuterMeasure {_m : MeasurableSpace α} (c : R) (μ : Measure α) :
(c • μ).toOuterMeasure = c • μ.toOuterMeasure :=
rfl
#align measure_theory.measure.smul_to_outer_measure MeasureTheory.Measure.smul_toOuterMeasure
@[simp, norm_cast]
theorem coe_smul {_m : MeasurableSpace α} (c : R) (μ : Measure α) : ⇑(c • μ) = c • ⇑μ :=
rfl
#align measure_theory.measure.coe_smul MeasureTheory.Measure.coe_smul
@[simp]
theorem smul_apply {_m : MeasurableSpace α} (c : R) (μ : Measure α) (s : Set α) :
(c • μ) s = c • μ s :=
rfl
#align measure_theory.measure.smul_apply MeasureTheory.Measure.smul_apply
instance instSMulCommClass [SMulCommClass R R' ℝ≥0∞] [MeasurableSpace α] :
SMulCommClass R R' (Measure α) :=
⟨fun _ _ _ => ext fun _ _ => smul_comm _ _ _⟩
#align measure_theory.measure.smul_comm_class MeasureTheory.Measure.instSMulCommClass
instance instIsScalarTower [SMul R R'] [IsScalarTower R R' ℝ≥0∞] [MeasurableSpace α] :
IsScalarTower R R' (Measure α) :=
⟨fun _ _ _ => ext fun _ _ => smul_assoc _ _ _⟩
#align measure_theory.measure.is_scalar_tower MeasureTheory.Measure.instIsScalarTower
instance instIsCentralScalar [SMul Rᵐᵒᵖ ℝ≥0∞] [IsCentralScalar R ℝ≥0∞] [MeasurableSpace α] :
IsCentralScalar R (Measure α) :=
⟨fun _ _ => ext fun _ _ => op_smul_eq_smul _ _⟩
#align measure_theory.measure.is_central_scalar MeasureTheory.Measure.instIsCentralScalar
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
#align measure_theory.measure.mul_action MeasureTheory.Measure.instMulAction
instance instAddCommMonoid [MeasurableSpace α] : AddCommMonoid (Measure α) :=
toOuterMeasure_injective.addCommMonoid toOuterMeasure zero_toOuterMeasure add_toOuterMeasure
fun _ _ => smul_toOuterMeasure _ _
#align measure_theory.measure.add_comm_monoid MeasureTheory.Measure.instAddCommMonoid
/-- 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
#align measure_theory.measure.coe_add_hom MeasureTheory.Measure.coeAddHom
@[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
#align measure_theory.measure.coe_finset_sum MeasureTheory.Measure.coe_finset_sum
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]
#align measure_theory.measure.finset_sum_apply MeasureTheory.Measure.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
#align measure_theory.measure.distrib_mul_action MeasureTheory.Measure.instDistribMulAction
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
#align measure_theory.measure.module MeasureTheory.Measure.instModule
@[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
#align measure_theory.measure.coe_nnreal_smul_apply MeasureTheory.Measure.coe_nnreal_smul_apply
@[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_iff {p : α → Prop} {c : ℝ≥0∞} (hc : c ≠ 0) :
(∀ᵐ x ∂c • μ, p x) ↔ ∀ᵐ x ∂μ, p x := by
simp only [ae_iff, Algebra.id.smul_eq_mul, smul_apply, or_iff_right_iff_imp, mul_eq_zero]
simp only [IsEmpty.forall_iff, hc]
#align measure_theory.measure.ae_smul_measure_iff MeasureTheory.Measure.ae_smul_measure_iff
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)
#align measure_theory.measure.measure_eq_left_of_subset_of_measure_add_eq MeasureTheory.Measure.measure_eq_left_of_subset_of_measure_add_eq
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''
#align measure_theory.measure.measure_eq_right_of_subset_of_measure_add_eq MeasureTheory.Measure.measure_eq_right_of_subset_of_measure_add_eq
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
#align measure_theory.measure.measure_to_measurable_add_inter_left MeasureTheory.Measure.measure_toMeasurable_add_inter_left
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
#align measure_theory.measure.measure_to_measurable_add_inter_right MeasureTheory.Measure.measure_toMeasurable_add_inter_right
/-! ### 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 m s := le_rfl
le_trans m₁ m₂ m₃ h₁ h₂ s := le_trans (h₁ s) (h₂ s)
le_antisymm m₁ m₂ h₁ h₂ := ext fun s _ => le_antisymm (h₁ s) (h₂ s)
#align measure_theory.measure.partial_order MeasureTheory.Measure.instPartialOrder
theorem toOuterMeasure_le : μ₁.toOuterMeasure ≤ μ₂.toOuterMeasure ↔ μ₁ ≤ μ₂ := .rfl
#align measure_theory.measure.to_outer_measure_le MeasureTheory.Measure.toOuterMeasure_le
theorem le_iff : μ₁ ≤ μ₂ ↔ ∀ s, MeasurableSet s → μ₁ s ≤ μ₂ s := outerMeasure_le_iff
#align measure_theory.measure.le_iff MeasureTheory.Measure.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
#align measure_theory.measure.le_iff' MeasureTheory.Measure.le_iff'
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]
#align measure_theory.measure.lt_iff MeasureTheory.Measure.lt_iff
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]
#align measure_theory.measure.lt_iff' MeasureTheory.Measure.lt_iff'
instance covariantAddLE [MeasurableSpace α] :
CovariantClass (Measure α) (Measure α) (· + ·) (· ≤ ·) :=
⟨fun _ν _μ₁ _μ₂ hμ s => add_le_add_left (hμ s) _⟩
#align measure_theory.measure.covariant_add_le MeasureTheory.Measure.covariantAddLE
protected theorem le_add_left (h : μ ≤ ν) : μ ≤ ν' + ν := fun s => le_add_left (h s)
#align measure_theory.measure.le_add_left MeasureTheory.Measure.le_add_left
protected theorem le_add_right (h : μ ≤ ν) : μ ≤ ν + ν' := fun s => le_add_right (h s)
#align measure_theory.measure.le_add_right MeasureTheory.Measure.le_add_right
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)
#align measure_theory.measure.Inf_caratheodory MeasureTheory.Measure.sInf_caratheodory
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
#align measure_theory.measure.Inf_apply MeasureTheory.Measure.sInf_apply
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 μ 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 }
#align measure_theory.measure.complete_semilattice_Inf MeasureTheory.Measure.instCompleteSemilatticeInf
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 μ => toOuterMeasure_le.mp le_top
bot := 0
bot_le := fun _a _s => bot_le }
#align measure_theory.measure.complete_lattice MeasureTheory.Measure.instCompleteLattice
end sInf
@[simp]
theorem _root_.MeasureTheory.OuterMeasure.toMeasure_top :
(⊤ : OuterMeasure α).toMeasure (by rw [OuterMeasure.top_caratheodory]; exact le_top) =
(⊤ : Measure α) :=
toOuterMeasure_toMeasure (μ := ⊤)
#align measure_theory.outer_measure.to_measure_top MeasureTheory.OuterMeasure.toMeasure_top
@[simp]
theorem toOuterMeasure_top [MeasurableSpace α] :
(⊤ : Measure α).toOuterMeasure = (⊤ : OuterMeasure α) :=
rfl
#align measure_theory.measure.to_outer_measure_top MeasureTheory.Measure.toOuterMeasure_top
@[simp]
theorem top_add : ⊤ + μ = ⊤ :=
top_unique <| Measure.le_add_right le_rfl
#align measure_theory.measure.top_add MeasureTheory.Measure.top_add
@[simp]
theorem add_top : μ + ⊤ = ⊤ :=
top_unique <| Measure.le_add_left le_rfl
#align measure_theory.measure.add_top MeasureTheory.Measure.add_top
protected theorem zero_le {_m0 : MeasurableSpace α} (μ : Measure α) : 0 ≤ μ :=
bot_le
#align measure_theory.measure.zero_le MeasureTheory.Measure.zero_le
theorem nonpos_iff_eq_zero' : μ ≤ 0 ↔ μ = 0 :=
μ.zero_le.le_iff_eq
#align measure_theory.measure.nonpos_iff_eq_zero' MeasureTheory.Measure.nonpos_iff_eq_zero'
@[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⟩
#align measure_theory.measure.measure_univ_eq_zero MeasureTheory.Measure.measure_univ_eq_zero
theorem measure_univ_ne_zero : μ univ ≠ 0 ↔ μ ≠ 0 :=
measure_univ_eq_zero.not
#align measure_theory.measure.measure_univ_ne_zero MeasureTheory.Measure.measure_univ_ne_zero
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
#align measure_theory.measure.measure_univ_pos MeasureTheory.Measure.measure_univ_pos
/-! ### Pushforward and pullback -/
/-- Lift a linear map between `OuterMeasure` spaces such that for each measure `μ` every measurable
set is caratheodory-measurable w.r.t. `f μ` to a linear map between `Measure` spaces. -/
def liftLinear {m0 : MeasurableSpace α} (f : OuterMeasure α →ₗ[ℝ≥0∞] OuterMeasure β)
(hf : ∀ μ : Measure α, ‹_› ≤ (f μ.toOuterMeasure).caratheodory) :
Measure α →ₗ[ℝ≥0∞] Measure β where
toFun μ := (f μ.toOuterMeasure).toMeasure (hf μ)
map_add' μ₁ μ₂ := ext fun s hs => by
simp only [map_add, coe_add, Pi.add_apply, toMeasure_apply, add_toOuterMeasure,
OuterMeasure.coe_add, hs]
map_smul' c μ := ext fun s hs => by
simp only [LinearMap.map_smulₛₗ, coe_smul, Pi.smul_apply,
toMeasure_apply, smul_toOuterMeasure (R := ℝ≥0∞), OuterMeasure.coe_smul (R := ℝ≥0∞),
smul_apply, hs]
#align measure_theory.measure.lift_linear MeasureTheory.Measure.liftLinear
lemma liftLinear_apply₀ {f : OuterMeasure α →ₗ[ℝ≥0∞] OuterMeasure β} (hf) {s : Set β}
(hs : NullMeasurableSet s (liftLinear f hf μ)) : liftLinear f hf μ s = f μ.toOuterMeasure s :=
toMeasure_apply₀ _ (hf μ) hs
@[simp]
theorem liftLinear_apply {f : OuterMeasure α →ₗ[ℝ≥0∞] OuterMeasure β} (hf) {s : Set β}
(hs : MeasurableSet s) : liftLinear f hf μ s = f μ.toOuterMeasure s :=
toMeasure_apply _ (hf μ) hs
#align measure_theory.measure.lift_linear_apply MeasureTheory.Measure.liftLinear_apply
theorem le_liftLinear_apply {f : OuterMeasure α →ₗ[ℝ≥0∞] OuterMeasure β} (hf) (s : Set β) :
f μ.toOuterMeasure s ≤ liftLinear f hf μ s :=
le_toMeasure_apply _ (hf μ) s
#align measure_theory.measure.le_lift_linear_apply MeasureTheory.Measure.le_liftLinear_apply
/-- The pushforward of a measure as a linear map. It is defined to be `0` if `f` is not
a measurable function. -/
def mapₗ [MeasurableSpace α] (f : α → β) : Measure α →ₗ[ℝ≥0∞] Measure β :=
if hf : Measurable f then
liftLinear (OuterMeasure.map f) fun μ _s hs t =>
le_toOuterMeasure_caratheodory μ _ (hf hs) (f ⁻¹' t)
else 0
#align measure_theory.measure.mapₗ MeasureTheory.Measure.mapₗ
theorem mapₗ_congr {f g : α → β} (hf : Measurable f) (hg : Measurable g) (h : f =ᵐ[μ] g) :
mapₗ f μ = mapₗ g μ := by
ext1 s hs
simpa only [mapₗ, hf, hg, hs, dif_pos, liftLinear_apply, OuterMeasure.map_apply]
using measure_congr (h.preimage s)
#align measure_theory.measure.mapₗ_congr MeasureTheory.Measure.mapₗ_congr
/-- The pushforward of a measure. It is defined to be `0` if `f` is not an almost everywhere
measurable function. -/
irreducible_def map [MeasurableSpace α] (f : α → β) (μ : Measure α) : Measure β :=
if hf : AEMeasurable f μ then mapₗ (hf.mk f) μ else 0
#align measure_theory.measure.map MeasureTheory.Measure.map
theorem mapₗ_mk_apply_of_aemeasurable {f : α → β} (hf : AEMeasurable f μ) :
mapₗ (hf.mk f) μ = map f μ := by simp [map, hf]
#align measure_theory.measure.mapₗ_mk_apply_of_ae_measurable MeasureTheory.Measure.mapₗ_mk_apply_of_aemeasurable
theorem mapₗ_apply_of_measurable {f : α → β} (hf : Measurable f) (μ : Measure α) :
mapₗ f μ = map f μ := by
simp only [← mapₗ_mk_apply_of_aemeasurable hf.aemeasurable]
exact mapₗ_congr hf hf.aemeasurable.measurable_mk hf.aemeasurable.ae_eq_mk
#align measure_theory.measure.mapₗ_apply_of_measurable MeasureTheory.Measure.mapₗ_apply_of_measurable
@[simp]
theorem map_add (μ ν : Measure α) {f : α → β} (hf : Measurable f) :
(μ + ν).map f = μ.map f + ν.map f := by simp [← mapₗ_apply_of_measurable hf]
#align measure_theory.measure.map_add MeasureTheory.Measure.map_add
@[simp]
theorem map_zero (f : α → β) : (0 : Measure α).map f = 0 := by
by_cases hf : AEMeasurable f (0 : Measure α) <;> simp [map, hf]
#align measure_theory.measure.map_zero MeasureTheory.Measure.map_zero
@[simp]
theorem map_of_not_aemeasurable {f : α → β} {μ : Measure α} (hf : ¬AEMeasurable f μ) :
μ.map f = 0 := by simp [map, hf]
#align measure_theory.measure.map_of_not_ae_measurable MeasureTheory.Measure.map_of_not_aemeasurable
theorem map_congr {f g : α → β} (h : f =ᵐ[μ] g) : Measure.map f μ = Measure.map g μ := by
by_cases hf : AEMeasurable f μ
· have hg : AEMeasurable g μ := hf.congr h
simp only [← mapₗ_mk_apply_of_aemeasurable hf, ← mapₗ_mk_apply_of_aemeasurable hg]
exact
mapₗ_congr hf.measurable_mk hg.measurable_mk (hf.ae_eq_mk.symm.trans (h.trans hg.ae_eq_mk))
· have hg : ¬AEMeasurable g μ := by simpa [← aemeasurable_congr h] using hf
simp [map_of_not_aemeasurable, hf, hg]
#align measure_theory.measure.map_congr MeasureTheory.Measure.map_congr
@[simp]
protected theorem map_smul (c : ℝ≥0∞) (μ : Measure α) (f : α → β) :
(c • μ).map f = c • μ.map f := by
rcases eq_or_ne c 0 with (rfl | hc); · simp
by_cases hf : AEMeasurable f μ
· have hfc : AEMeasurable f (c • μ) :=
⟨hf.mk f, hf.measurable_mk, (ae_smul_measure_iff hc).2 hf.ae_eq_mk⟩
simp only [← mapₗ_mk_apply_of_aemeasurable hf, ← mapₗ_mk_apply_of_aemeasurable hfc,
LinearMap.map_smulₛₗ, RingHom.id_apply]
congr 1
apply mapₗ_congr hfc.measurable_mk hf.measurable_mk
exact EventuallyEq.trans ((ae_smul_measure_iff hc).1 hfc.ae_eq_mk.symm) hf.ae_eq_mk
· have hfc : ¬AEMeasurable f (c • μ) := by
intro hfc
exact hf ⟨hfc.mk f, hfc.measurable_mk, (ae_smul_measure_iff hc).1 hfc.ae_eq_mk⟩
simp [map_of_not_aemeasurable hf, map_of_not_aemeasurable hfc]
#align measure_theory.measure.map_smul MeasureTheory.Measure.map_smul
@[simp]
protected theorem map_smul_nnreal (c : ℝ≥0) (μ : Measure α) (f : α → β) :
(c • μ).map f = c • μ.map f :=
μ.map_smul (c : ℝ≥0∞) f
#align measure_theory.measure.map_smul_nnreal MeasureTheory.Measure.map_smul_nnreal
variable {f : α → β}
lemma map_apply₀ {f : α → β} (hf : AEMeasurable f μ) {s : Set β}
(hs : NullMeasurableSet s (map f μ)) : μ.map f s = μ (f ⁻¹' s) := by
rw [map, dif_pos hf, mapₗ, dif_pos hf.measurable_mk] at hs ⊢
rw [liftLinear_apply₀ _ hs, measure_congr (hf.ae_eq_mk.preimage s)]
rfl
/-- We can evaluate the pushforward on measurable sets. For non-measurable sets, see
`MeasureTheory.Measure.le_map_apply` and `MeasurableEquiv.map_apply`. -/
@[simp]
theorem map_apply_of_aemeasurable (hf : AEMeasurable f μ) {s : Set β} (hs : MeasurableSet s) :
μ.map f s = μ (f ⁻¹' s) := map_apply₀ hf hs.nullMeasurableSet
#align measure_theory.measure.map_apply_of_ae_measurable MeasureTheory.Measure.map_apply_of_aemeasurable
@[simp]
theorem map_apply (hf : Measurable f) {s : Set β} (hs : MeasurableSet s) :
μ.map f s = μ (f ⁻¹' s) :=
map_apply_of_aemeasurable hf.aemeasurable hs
#align measure_theory.measure.map_apply MeasureTheory.Measure.map_apply
theorem map_toOuterMeasure (hf : AEMeasurable f μ) :
(μ.map f).toOuterMeasure = (OuterMeasure.map f μ.toOuterMeasure).trim := by
rw [← trimmed, OuterMeasure.trim_eq_trim_iff]
intro s hs
simp [hf, hs]
#align measure_theory.measure.map_to_outer_measure MeasureTheory.Measure.map_toOuterMeasure
@[simp] lemma map_eq_zero_iff (hf : AEMeasurable f μ) : μ.map f = 0 ↔ μ = 0 := by
simp_rw [← measure_univ_eq_zero, map_apply_of_aemeasurable hf .univ, preimage_univ]
@[simp] lemma mapₗ_eq_zero_iff (hf : Measurable f) : Measure.mapₗ f μ = 0 ↔ μ = 0 := by
rw [mapₗ_apply_of_measurable hf, map_eq_zero_iff hf.aemeasurable]
lemma map_ne_zero_iff (hf : AEMeasurable f μ) : μ.map f ≠ 0 ↔ μ ≠ 0 := (map_eq_zero_iff hf).not
lemma mapₗ_ne_zero_iff (hf : Measurable f) : Measure.mapₗ f μ ≠ 0 ↔ μ ≠ 0 :=
(mapₗ_eq_zero_iff hf).not
@[simp]
theorem map_id : map id μ = μ :=
ext fun _ => map_apply measurable_id
#align measure_theory.measure.map_id MeasureTheory.Measure.map_id
@[simp]
theorem map_id' : map (fun x => x) μ = μ :=
map_id
#align measure_theory.measure.map_id' MeasureTheory.Measure.map_id'
theorem map_map {g : β → γ} {f : α → β} (hg : Measurable g) (hf : Measurable f) :
(μ.map f).map g = μ.map (g ∘ f) :=
ext fun s hs => by simp [hf, hg, hs, hg hs, hg.comp hf, ← preimage_comp]
#align measure_theory.measure.map_map MeasureTheory.Measure.map_map
@[mono]
theorem map_mono {f : α → β} (h : μ ≤ ν) (hf : Measurable f) : μ.map f ≤ ν.map f :=
le_iff.2 fun s hs ↦ by simp [hf.aemeasurable, hs, h _]
#align measure_theory.measure.map_mono MeasureTheory.Measure.map_mono
/-- Even if `s` is not measurable, we can bound `map f μ s` from below.
See also `MeasurableEquiv.map_apply`. -/
theorem le_map_apply {f : α → β} (hf : AEMeasurable f μ) (s : Set β) : μ (f ⁻¹' s) ≤ μ.map f s :=
calc
μ (f ⁻¹' s) ≤ μ (f ⁻¹' toMeasurable (μ.map f) s) := by gcongr; apply subset_toMeasurable
_ = μ.map f (toMeasurable (μ.map f) s) :=
(map_apply_of_aemeasurable hf <| measurableSet_toMeasurable _ _).symm
_ = μ.map f s := measure_toMeasurable _
#align measure_theory.measure.le_map_apply MeasureTheory.Measure.le_map_apply
theorem le_map_apply_image {f : α → β} (hf : AEMeasurable f μ) (s : Set α) :
μ s ≤ μ.map f (f '' s) :=
(measure_mono (subset_preimage_image f s)).trans (le_map_apply hf _)
/-- Even if `s` is not measurable, `map f μ s = 0` implies that `μ (f ⁻¹' s) = 0`. -/
theorem preimage_null_of_map_null {f : α → β} (hf : AEMeasurable f μ) {s : Set β}
(hs : μ.map f s = 0) : μ (f ⁻¹' s) = 0 :=
nonpos_iff_eq_zero.mp <| (le_map_apply hf s).trans_eq hs
#align measure_theory.measure.preimage_null_of_map_null MeasureTheory.Measure.preimage_null_of_map_null
theorem tendsto_ae_map {f : α → β} (hf : AEMeasurable f μ) : Tendsto f (ae μ) (ae (μ.map f)) :=
fun _ hs => preimage_null_of_map_null hf hs
#align measure_theory.measure.tendsto_ae_map MeasureTheory.Measure.tendsto_ae_map
/-- Pullback of a `Measure` as a linear map. If `f` sends each measurable set to a measurable
set, then for each measurable set `s` we have `comapₗ f μ s = μ (f '' s)`.
If the linearity is not needed, please use `comap` instead, which works for a larger class of
functions. -/
def comapₗ [MeasurableSpace α] (f : α → β) : Measure β →ₗ[ℝ≥0∞] Measure α :=
if hf : Injective f ∧ ∀ s, MeasurableSet s → MeasurableSet (f '' s) then
liftLinear (OuterMeasure.comap f) fun μ s hs t => by
simp only [OuterMeasure.comap_apply, image_inter hf.1, image_diff hf.1]
apply le_toOuterMeasure_caratheodory
exact hf.2 s hs
else 0
#align measure_theory.measure.comapₗ MeasureTheory.Measure.comapₗ
theorem comapₗ_apply {β} [MeasurableSpace α] {mβ : MeasurableSpace β} (f : α → β)
(hfi : Injective f) (hf : ∀ s, MeasurableSet s → MeasurableSet (f '' s)) (μ : Measure β)
(hs : MeasurableSet s) : comapₗ f μ s = μ (f '' s) := by
rw [comapₗ, dif_pos, liftLinear_apply _ hs, OuterMeasure.comap_apply, coe_toOuterMeasure]
exact ⟨hfi, hf⟩
#align measure_theory.measure.comapₗ_apply MeasureTheory.Measure.comapₗ_apply
/-- Pullback of a `Measure`. If `f` sends each measurable set to a null-measurable set,
then for each measurable set `s` we have `comap f μ s = μ (f '' s)`. -/
def comap [MeasurableSpace α] (f : α → β) (μ : Measure β) : Measure α :=
if hf : Injective f ∧ ∀ s, MeasurableSet s → NullMeasurableSet (f '' s) μ then
(OuterMeasure.comap f μ.toOuterMeasure).toMeasure fun s hs t => by
simp only [OuterMeasure.comap_apply, image_inter hf.1, image_diff hf.1]
exact (measure_inter_add_diff₀ _ (hf.2 s hs)).symm
else 0
#align measure_theory.measure.comap MeasureTheory.Measure.comap
theorem comap_apply₀ [MeasurableSpace α] (f : α → β) (μ : Measure β) (hfi : Injective f)
(hf : ∀ s, MeasurableSet s → NullMeasurableSet (f '' s) μ)
(hs : NullMeasurableSet s (comap f μ)) : comap f μ s = μ (f '' s) := by
rw [comap, dif_pos (And.intro hfi hf)] at hs ⊢
rw [toMeasure_apply₀ _ _ hs, OuterMeasure.comap_apply, coe_toOuterMeasure]
#align measure_theory.measure.comap_apply₀ MeasureTheory.Measure.comap_apply₀
theorem le_comap_apply {β} [MeasurableSpace α] {mβ : MeasurableSpace β} (f : α → β) (μ : Measure β)
(hfi : Injective f) (hf : ∀ s, MeasurableSet s → NullMeasurableSet (f '' s) μ) (s : Set α) :
μ (f '' s) ≤ comap f μ s := by
rw [comap, dif_pos (And.intro hfi hf)]
exact le_toMeasure_apply _ _ _
#align measure_theory.measure.le_comap_apply MeasureTheory.Measure.le_comap_apply
theorem comap_apply {β} [MeasurableSpace α] {_mβ : MeasurableSpace β} (f : α → β)
(hfi : Injective f) (hf : ∀ s, MeasurableSet s → MeasurableSet (f '' s)) (μ : Measure β)
(hs : MeasurableSet s) : comap f μ s = μ (f '' s) :=
comap_apply₀ f μ hfi (fun s hs => (hf s hs).nullMeasurableSet) hs.nullMeasurableSet
#align measure_theory.measure.comap_apply MeasureTheory.Measure.comap_apply
theorem comapₗ_eq_comap {β} [MeasurableSpace α] {_mβ : MeasurableSpace β} (f : α → β)
(hfi : Injective f) (hf : ∀ s, MeasurableSet s → MeasurableSet (f '' s)) (μ : Measure β)
(hs : MeasurableSet s) : comapₗ f μ s = comap f μ s :=
(comapₗ_apply f hfi hf μ hs).trans (comap_apply f hfi hf μ hs).symm
#align measure_theory.measure.comapₗ_eq_comap MeasureTheory.Measure.comapₗ_eq_comap
theorem measure_image_eq_zero_of_comap_eq_zero {β} [MeasurableSpace α] {_mβ : MeasurableSpace β}
(f : α → β) (μ : Measure β) (hfi : Injective f)
(hf : ∀ s, MeasurableSet s → NullMeasurableSet (f '' s) μ) {s : Set α} (hs : comap f μ s = 0) :
μ (f '' s) = 0 :=
le_antisymm ((le_comap_apply f μ hfi hf s).trans hs.le) (zero_le _)
#align measure_theory.measure.measure_image_eq_zero_of_comap_eq_zero MeasureTheory.Measure.measure_image_eq_zero_of_comap_eq_zero
theorem ae_eq_image_of_ae_eq_comap {β} [MeasurableSpace α] {mβ : MeasurableSpace β} (f : α → β)
(μ : Measure β) (hfi : Injective f) (hf : ∀ s, MeasurableSet s → NullMeasurableSet (f '' s) μ)
{s t : Set α} (hst : s =ᵐ[comap f μ] t) : f '' s =ᵐ[μ] f '' t := by
rw [EventuallyEq, ae_iff] at hst ⊢
have h_eq_α : { a : α | ¬s a = t a } = s \ t ∪ t \ s := by
ext1 x
simp only [eq_iff_iff, mem_setOf_eq, mem_union, mem_diff]
tauto
have h_eq_β : { a : β | ¬(f '' s) a = (f '' t) a } = f '' s \ f '' t ∪ f '' t \ f '' s := by
ext1 x
simp only [eq_iff_iff, mem_setOf_eq, mem_union, mem_diff]
tauto
rw [← Set.image_diff hfi, ← Set.image_diff hfi, ← Set.image_union] at h_eq_β
rw [h_eq_β]
rw [h_eq_α] at hst
exact measure_image_eq_zero_of_comap_eq_zero f μ hfi hf hst
#align measure_theory.measure.ae_eq_image_of_ae_eq_comap MeasureTheory.Measure.ae_eq_image_of_ae_eq_comap
theorem NullMeasurableSet.image {β} [MeasurableSpace α] {mβ : MeasurableSpace β} (f : α → β)
(μ : Measure β) (hfi : Injective f) (hf : ∀ s, MeasurableSet s → NullMeasurableSet (f '' s) μ)
{s : Set α} (hs : NullMeasurableSet s (μ.comap f)) : NullMeasurableSet (f '' s) μ := by
refine ⟨toMeasurable μ (f '' toMeasurable (μ.comap f) s), measurableSet_toMeasurable _ _, ?_⟩
refine EventuallyEq.trans ?_ (NullMeasurableSet.toMeasurable_ae_eq ?_).symm
swap
· exact hf _ (measurableSet_toMeasurable _ _)
have h : toMeasurable (comap f μ) s =ᵐ[comap f μ] s :=
NullMeasurableSet.toMeasurable_ae_eq hs
exact ae_eq_image_of_ae_eq_comap f μ hfi hf h.symm
#align measure_theory.measure.null_measurable_set.image MeasureTheory.Measure.NullMeasurableSet.image
theorem comap_preimage {β} [MeasurableSpace α] {mβ : MeasurableSpace β} (f : α → β) (μ : Measure β)
{s : Set β} (hf : Injective f) (hf' : Measurable f)
(h : ∀ t, MeasurableSet t → NullMeasurableSet (f '' t) μ) (hs : MeasurableSet s) :
μ.comap f (f ⁻¹' s) = μ (s ∩ range f) := by
rw [comap_apply₀ _ _ hf h (hf' hs).nullMeasurableSet, image_preimage_eq_inter_range]
#align measure_theory.measure.comap_preimage MeasureTheory.Measure.comap_preimage
section Sum
/-- 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 _)
#align measure_theory.measure.sum MeasureTheory.Measure.sum
theorem le_sum_apply (f : ι → Measure α) (s : Set α) : ∑' i, f i s ≤ sum f s :=
le_toMeasure_apply _ _ _
#align measure_theory.measure.le_sum_apply MeasureTheory.Measure.le_sum_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
#align measure_theory.measure.sum_apply MeasureTheory.Measure.sum_apply
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 get `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
#align measure_theory.measure.le_sum MeasureTheory.Measure.le_sum
@[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]
#align measure_theory.measure.sum_apply_eq_zero MeasureTheory.Measure.sum_apply_eq_zero
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]
#align measure_theory.measure.sum_apply_eq_zero' MeasureTheory.Measure.sum_apply_eq_zero'
@[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]
#align measure_theory.measure.sum_comm MeasureTheory.Measure.sum_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
#align measure_theory.measure.ae_sum_iff MeasureTheory.Measure.ae_sum_iff
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
#align measure_theory.measure.ae_sum_iff' MeasureTheory.Measure.ae_sum_iff'
@[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]
#align measure_theory.measure.sum_fintype MeasureTheory.Measure.sum_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]
#align measure_theory.measure.sum_coe_finset MeasureTheory.Measure.sum_coe_finset
@[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
#align measure_theory.measure.ae_sum_eq MeasureTheory.Measure.ae_sum_eq
theorem sum_bool (f : Bool → Measure α) : sum f = f true + f false := by
rw [sum_fintype, Fintype.sum_bool]
#align measure_theory.measure.sum_bool MeasureTheory.Measure.sum_bool
theorem sum_cond (μ ν : Measure α) : (sum fun b => cond b μ ν) = μ + ν :=
sum_bool _
#align measure_theory.measure.sum_cond MeasureTheory.Measure.sum_cond
@[simp]
theorem sum_of_empty [IsEmpty ι] (μ : ι → Measure α) : sum μ = 0 := by
rw [← measure_univ_eq_zero, sum_apply _ MeasurableSet.univ, tsum_empty]
#align measure_theory.measure.sum_of_empty MeasureTheory.Measure.sum_of_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 tsum_add_tsum_compl (f := fun i => μ i t) ENNReal.summable ENNReal.summable
#align measure_theory.measure.sum_add_sum_compl MeasureTheory.Measure.sum_add_sum_compl
theorem sum_congr {μ ν : ℕ → Measure α} (h : ∀ n, μ n = ν n) : sum μ = sum ν :=
congr_arg sum (funext h)
#align measure_theory.measure.sum_congr MeasureTheory.Measure.sum_congr
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,
tsum_add ENNReal.summable ENNReal.summable]
#align measure_theory.measure.sum_add_sum MeasureTheory.Measure.sum_add_sum
@[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
/-! ### Absolute continuity -/
/-- We say that `μ` is absolutely continuous with respect to `ν`, or that `μ` is dominated by `ν`,
if `ν(A) = 0` implies that `μ(A) = 0`. -/
def AbsolutelyContinuous {_m0 : MeasurableSpace α} (μ ν : Measure α) : Prop :=
∀ ⦃s : Set α⦄, ν s = 0 → μ s = 0
#align measure_theory.measure.absolutely_continuous MeasureTheory.Measure.AbsolutelyContinuous
@[inherit_doc MeasureTheory.Measure.AbsolutelyContinuous]
scoped[MeasureTheory] infixl:50 " ≪ " => MeasureTheory.Measure.AbsolutelyContinuous
theorem absolutelyContinuous_of_le (h : μ ≤ ν) : μ ≪ ν := fun s hs =>
nonpos_iff_eq_zero.1 <| hs ▸ le_iff'.1 h s
#align measure_theory.measure.absolutely_continuous_of_le MeasureTheory.Measure.absolutelyContinuous_of_le
alias _root_.LE.le.absolutelyContinuous := absolutelyContinuous_of_le
#align has_le.le.absolutely_continuous LE.le.absolutelyContinuous
theorem absolutelyContinuous_of_eq (h : μ = ν) : μ ≪ ν :=
h.le.absolutelyContinuous
#align measure_theory.measure.absolutely_continuous_of_eq MeasureTheory.Measure.absolutelyContinuous_of_eq
alias _root_.Eq.absolutelyContinuous := absolutelyContinuous_of_eq
#align eq.absolutely_continuous Eq.absolutelyContinuous
namespace AbsolutelyContinuous
theorem mk (h : ∀ ⦃s : Set α⦄, MeasurableSet s → ν s = 0 → μ s = 0) : μ ≪ ν := by
intro s hs
rcases exists_measurable_superset_of_null hs with ⟨t, h1t, h2t, h3t⟩
exact measure_mono_null h1t (h h2t h3t)
#align measure_theory.measure.absolutely_continuous.mk MeasureTheory.Measure.AbsolutelyContinuous.mk
@[refl]
protected theorem refl {_m0 : MeasurableSpace α} (μ : Measure α) : μ ≪ μ :=
rfl.absolutelyContinuous
#align measure_theory.measure.absolutely_continuous.refl MeasureTheory.Measure.AbsolutelyContinuous.refl
protected theorem rfl : μ ≪ μ := fun _s hs => hs
#align measure_theory.measure.absolutely_continuous.rfl MeasureTheory.Measure.AbsolutelyContinuous.rfl
instance instIsRefl [MeasurableSpace α] : IsRefl (Measure α) (· ≪ ·) :=
⟨fun _ => AbsolutelyContinuous.rfl⟩
#align measure_theory.measure.absolutely_continuous.is_refl MeasureTheory.Measure.AbsolutelyContinuous.instIsRefl
@[simp]
protected lemma zero (μ : Measure α) : 0 ≪ μ := fun s _ ↦ by simp
@[trans]
protected theorem trans (h1 : μ₁ ≪ μ₂) (h2 : μ₂ ≪ μ₃) : μ₁ ≪ μ₃ := fun _s hs => h1 <| h2 hs
#align measure_theory.measure.absolutely_continuous.trans MeasureTheory.Measure.AbsolutelyContinuous.trans
@[mono]
protected theorem map (h : μ ≪ ν) {f : α → β} (hf : Measurable f) : μ.map f ≪ ν.map f :=
AbsolutelyContinuous.mk fun s hs => by simpa [hf, hs] using @h _
#align measure_theory.measure.absolutely_continuous.map MeasureTheory.Measure.AbsolutelyContinuous.map
protected theorem smul [Monoid R] [DistribMulAction R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
(h : μ ≪ ν) (c : R) : c • μ ≪ ν := fun s hνs => by
simp only [h hνs, smul_eq_mul, smul_apply, smul_zero]
#align measure_theory.measure.absolutely_continuous.smul MeasureTheory.Measure.AbsolutelyContinuous.smul
protected lemma add (h1 : μ₁ ≪ ν) (h2 : μ₂ ≪ ν') : μ₁ + μ₂ ≪ ν + ν' := by
intro s hs
simp only [coe_add, Pi.add_apply, add_eq_zero] at hs ⊢
exact ⟨h1 hs.1, h2 hs.2⟩
lemma add_left_iff {μ₁ μ₂ ν : Measure α} :
μ₁ + μ₂ ≪ ν ↔ μ₁ ≪ ν ∧ μ₂ ≪ ν := by
refine ⟨fun h ↦ ?_, fun h ↦ (h.1.add h.2).trans ?_⟩
· have : ∀ s, ν s = 0 → μ₁ s = 0 ∧ μ₂ s = 0 := by intro s hs0; simpa using h hs0
exact ⟨fun s hs0 ↦ (this s hs0).1, fun s hs0 ↦ (this s hs0).2⟩
· have : ν + ν = 2 • ν := by ext; simp [two_mul]
rw [this]
exact AbsolutelyContinuous.rfl.smul 2
lemma add_right (h1 : μ ≪ ν) (ν' : Measure α) : μ ≪ ν + ν' := by
intro s hs
simp only [coe_add, Pi.add_apply, add_eq_zero] at hs ⊢
exact h1 hs.1
end AbsolutelyContinuous
@[simp]
lemma absolutelyContinuous_zero_iff : μ ≪ 0 ↔ μ = 0 :=
⟨fun h ↦ measure_univ_eq_zero.mp (h rfl), fun h ↦ h.symm ▸ AbsolutelyContinuous.zero _⟩
alias absolutelyContinuous_refl := AbsolutelyContinuous.refl
alias absolutelyContinuous_rfl := AbsolutelyContinuous.rfl
lemma absolutelyContinuous_sum_left {μs : ι → Measure α} (hμs : ∀ i, μs i ≪ ν) :
Measure.sum μs ≪ ν :=
AbsolutelyContinuous.mk fun s hs hs0 ↦ by simp [sum_apply _ hs, fun i ↦ hμs i hs0]
lemma absolutelyContinuous_sum_right {μs : ι → Measure α} (i : ι) (hνμ : ν ≪ μs i) :
ν ≪ Measure.sum μs := by
refine AbsolutelyContinuous.mk fun s hs hs0 ↦ ?_
simp only [sum_apply _ hs, ENNReal.tsum_eq_zero] at hs0
exact hνμ (hs0 i)
theorem absolutelyContinuous_of_le_smul {μ' : Measure α} {c : ℝ≥0∞} (hμ'_le : μ' ≤ c • μ) :
μ' ≪ μ :=
(Measure.absolutelyContinuous_of_le hμ'_le).trans (Measure.AbsolutelyContinuous.rfl.smul c)
#align measure_theory.measure.absolutely_continuous_of_le_smul MeasureTheory.Measure.absolutelyContinuous_of_le_smul
lemma smul_absolutelyContinuous {c : ℝ≥0∞} : c • μ ≪ μ := absolutelyContinuous_of_le_smul le_rfl
lemma absolutelyContinuous_smul {c : ℝ≥0∞} (hc : c ≠ 0) : μ ≪ c • μ := by
simp [AbsolutelyContinuous, hc]
theorem ae_le_iff_absolutelyContinuous : ae μ ≤ ae ν ↔ μ ≪ ν :=
⟨fun h s => by
rw [measure_zero_iff_ae_nmem, measure_zero_iff_ae_nmem]
exact fun hs => h hs, fun h s hs => h hs⟩
#align measure_theory.measure.ae_le_iff_absolutely_continuous MeasureTheory.Measure.ae_le_iff_absolutelyContinuous
alias ⟨_root_.LE.le.absolutelyContinuous_of_ae, AbsolutelyContinuous.ae_le⟩ :=
ae_le_iff_absolutelyContinuous
#align has_le.le.absolutely_continuous_of_ae LE.le.absolutelyContinuous_of_ae
#align measure_theory.measure.absolutely_continuous.ae_le MeasureTheory.Measure.AbsolutelyContinuous.ae_le
alias ae_mono' := AbsolutelyContinuous.ae_le
#align measure_theory.measure.ae_mono' MeasureTheory.Measure.ae_mono'
theorem AbsolutelyContinuous.ae_eq (h : μ ≪ ν) {f g : α → δ} (h' : f =ᵐ[ν] g) : f =ᵐ[μ] g :=
h.ae_le h'
#align measure_theory.measure.absolutely_continuous.ae_eq MeasureTheory.Measure.AbsolutelyContinuous.ae_eq
protected theorem _root_.MeasureTheory.AEDisjoint.of_absolutelyContinuous
(h : AEDisjoint μ s t) {ν : Measure α} (h' : ν ≪ μ) :
AEDisjoint ν s t := h' h
protected theorem _root_.MeasureTheory.AEDisjoint.of_le
(h : AEDisjoint μ s t) {ν : Measure α} (h' : ν ≤ μ) :
AEDisjoint ν s t :=
h.of_absolutelyContinuous (Measure.absolutelyContinuous_of_le h')
/-! ### Quasi measure preserving maps (a.k.a. non-singular maps) -/
/-- A map `f : α → β` is said to be *quasi measure preserving* (a.k.a. non-singular) w.r.t. measures
`μa` and `μb` if it is measurable and `μb s = 0` implies `μa (f ⁻¹' s) = 0`. -/
structure QuasiMeasurePreserving {m0 : MeasurableSpace α} (f : α → β)
(μa : Measure α := by volume_tac)
(μb : Measure β := by volume_tac) : Prop where
protected measurable : Measurable f
protected absolutelyContinuous : μa.map f ≪ μb
#align measure_theory.measure.quasi_measure_preserving MeasureTheory.Measure.QuasiMeasurePreserving
#align measure_theory.measure.quasi_measure_preserving.measurable MeasureTheory.Measure.QuasiMeasurePreserving.measurable
#align measure_theory.measure.quasi_measure_preserving.absolutely_continuous MeasureTheory.Measure.QuasiMeasurePreserving.absolutelyContinuous
namespace QuasiMeasurePreserving
protected theorem id {_m0 : MeasurableSpace α} (μ : Measure α) : QuasiMeasurePreserving id μ μ :=
⟨measurable_id, map_id.absolutelyContinuous⟩
#align measure_theory.measure.quasi_measure_preserving.id MeasureTheory.Measure.QuasiMeasurePreserving.id
variable {μa μa' : Measure α} {μb μb' : Measure β} {μc : Measure γ} {f : α → β}
protected theorem _root_.Measurable.quasiMeasurePreserving
{_m0 : MeasurableSpace α} (hf : Measurable f) (μ : Measure α) :
QuasiMeasurePreserving f μ (μ.map f) :=
⟨hf, AbsolutelyContinuous.rfl⟩
#align measurable.quasi_measure_preserving Measurable.quasiMeasurePreserving
theorem mono_left (h : QuasiMeasurePreserving f μa μb) (ha : μa' ≪ μa) :
QuasiMeasurePreserving f μa' μb :=
⟨h.1, (ha.map h.1).trans h.2⟩
#align measure_theory.measure.quasi_measure_preserving.mono_left MeasureTheory.Measure.QuasiMeasurePreserving.mono_left
theorem mono_right (h : QuasiMeasurePreserving f μa μb) (ha : μb ≪ μb') :
QuasiMeasurePreserving f μa μb' :=
⟨h.1, h.2.trans ha⟩
#align measure_theory.measure.quasi_measure_preserving.mono_right MeasureTheory.Measure.QuasiMeasurePreserving.mono_right
@[mono]
theorem mono (ha : μa' ≪ μa) (hb : μb ≪ μb') (h : QuasiMeasurePreserving f μa μb) :
QuasiMeasurePreserving f μa' μb' :=
(h.mono_left ha).mono_right hb
#align measure_theory.measure.quasi_measure_preserving.mono MeasureTheory.Measure.QuasiMeasurePreserving.mono
protected theorem comp {g : β → γ} {f : α → β} (hg : QuasiMeasurePreserving g μb μc)
(hf : QuasiMeasurePreserving f μa μb) : QuasiMeasurePreserving (g ∘ f) μa μc :=
⟨hg.measurable.comp hf.measurable, by
rw [← map_map hg.1 hf.1]
exact (hf.2.map hg.1).trans hg.2⟩
#align measure_theory.measure.quasi_measure_preserving.comp MeasureTheory.Measure.QuasiMeasurePreserving.comp
protected theorem iterate {f : α → α} (hf : QuasiMeasurePreserving f μa μa) :
∀ n, QuasiMeasurePreserving f^[n] μa μa
| 0 => QuasiMeasurePreserving.id μa
| n + 1 => (hf.iterate n).comp hf
#align measure_theory.measure.quasi_measure_preserving.iterate MeasureTheory.Measure.QuasiMeasurePreserving.iterate
protected theorem aemeasurable (hf : QuasiMeasurePreserving f μa μb) : AEMeasurable f μa :=
hf.1.aemeasurable
#align measure_theory.measure.quasi_measure_preserving.ae_measurable MeasureTheory.Measure.QuasiMeasurePreserving.aemeasurable
theorem ae_map_le (h : QuasiMeasurePreserving f μa μb) : ae (μa.map f) ≤ ae μb :=
h.2.ae_le
#align measure_theory.measure.quasi_measure_preserving.ae_map_le MeasureTheory.Measure.QuasiMeasurePreserving.ae_map_le
theorem tendsto_ae (h : QuasiMeasurePreserving f μa μb) : Tendsto f (ae μa) (ae μb) :=
(tendsto_ae_map h.aemeasurable).mono_right h.ae_map_le
#align measure_theory.measure.quasi_measure_preserving.tendsto_ae MeasureTheory.Measure.QuasiMeasurePreserving.tendsto_ae
theorem ae (h : QuasiMeasurePreserving f μa μb) {p : β → Prop} (hg : ∀ᵐ x ∂μb, p x) :
∀ᵐ x ∂μa, p (f x) :=
h.tendsto_ae hg
#align measure_theory.measure.quasi_measure_preserving.ae MeasureTheory.Measure.QuasiMeasurePreserving.ae
theorem ae_eq (h : QuasiMeasurePreserving f μa μb) {g₁ g₂ : β → δ} (hg : g₁ =ᵐ[μb] g₂) :
g₁ ∘ f =ᵐ[μa] g₂ ∘ f :=
h.ae hg
#align measure_theory.measure.quasi_measure_preserving.ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.ae_eq
theorem preimage_null (h : QuasiMeasurePreserving f μa μb) {s : Set β} (hs : μb s = 0) :
μa (f ⁻¹' s) = 0 :=
preimage_null_of_map_null h.aemeasurable (h.2 hs)
#align measure_theory.measure.quasi_measure_preserving.preimage_null MeasureTheory.Measure.QuasiMeasurePreserving.preimage_null
theorem preimage_mono_ae {s t : Set β} (hf : QuasiMeasurePreserving f μa μb) (h : s ≤ᵐ[μb] t) :
f ⁻¹' s ≤ᵐ[μa] f ⁻¹' t :=
eventually_map.mp <|
Eventually.filter_mono (tendsto_ae_map hf.aemeasurable) (Eventually.filter_mono hf.ae_map_le h)
#align measure_theory.measure.quasi_measure_preserving.preimage_mono_ae MeasureTheory.Measure.QuasiMeasurePreserving.preimage_mono_ae
theorem preimage_ae_eq {s t : Set β} (hf : QuasiMeasurePreserving f μa μb) (h : s =ᵐ[μb] t) :
f ⁻¹' s =ᵐ[μa] f ⁻¹' t :=
EventuallyLE.antisymm (hf.preimage_mono_ae h.le) (hf.preimage_mono_ae h.symm.le)
#align measure_theory.measure.quasi_measure_preserving.preimage_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.preimage_ae_eq
theorem preimage_iterate_ae_eq {s : Set α} {f : α → α} (hf : QuasiMeasurePreserving f μ μ) (k : ℕ)
(hs : f ⁻¹' s =ᵐ[μ] s) : f^[k] ⁻¹' s =ᵐ[μ] s := by
induction' k with k ih; · rfl
rw [iterate_succ, preimage_comp]
exact EventuallyEq.trans (hf.preimage_ae_eq ih) hs
#align measure_theory.measure.quasi_measure_preserving.preimage_iterate_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.preimage_iterate_ae_eq
theorem image_zpow_ae_eq {s : Set α} {e : α ≃ α} (he : QuasiMeasurePreserving e μ μ)
(he' : QuasiMeasurePreserving e.symm μ μ) (k : ℤ) (hs : e '' s =ᵐ[μ] s) :
(⇑(e ^ k)) '' s =ᵐ[μ] s := by
rw [Equiv.image_eq_preimage]
obtain ⟨k, rfl | rfl⟩ := k.eq_nat_or_neg
· replace hs : (⇑e⁻¹) ⁻¹' s =ᵐ[μ] s := by rwa [Equiv.image_eq_preimage] at hs
replace he' : (⇑e⁻¹)^[k] ⁻¹' s =ᵐ[μ] s := he'.preimage_iterate_ae_eq k hs
rwa [Equiv.Perm.iterate_eq_pow e⁻¹ k, inv_pow e k] at he'
· rw [zpow_neg, zpow_natCast]
replace hs : e ⁻¹' s =ᵐ[μ] s := by
convert he.preimage_ae_eq hs.symm
rw [Equiv.preimage_image]
replace he : (⇑e)^[k] ⁻¹' s =ᵐ[μ] s := he.preimage_iterate_ae_eq k hs
rwa [Equiv.Perm.iterate_eq_pow e k] at he
#align measure_theory.measure.quasi_measure_preserving.image_zpow_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.image_zpow_ae_eq
-- Need to specify `α := Set α` below because of diamond; see #19041
theorem limsup_preimage_iterate_ae_eq {f : α → α} (hf : QuasiMeasurePreserving f μ μ)
(hs : f ⁻¹' s =ᵐ[μ] s) : limsup (α := Set α) (fun n => (preimage f)^[n] s) atTop =ᵐ[μ] s :=
haveI : ∀ n, (preimage f)^[n] s =ᵐ[μ] s := by
intro n
induction' n with n ih
· rfl
simpa only [iterate_succ', comp_apply] using ae_eq_trans (hf.ae_eq ih) hs
(limsup_ae_eq_of_forall_ae_eq (fun n => (preimage f)^[n] s) this).trans (ae_eq_refl _)
#align measure_theory.measure.quasi_measure_preserving.limsup_preimage_iterate_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.limsup_preimage_iterate_ae_eq
-- Need to specify `α := Set α` below because of diamond; see #19041
theorem liminf_preimage_iterate_ae_eq {f : α → α} (hf : QuasiMeasurePreserving f μ μ)
(hs : f ⁻¹' s =ᵐ[μ] s) : liminf (α := Set α) (fun n => (preimage f)^[n] s) atTop =ᵐ[μ] s := by
rw [← ae_eq_set_compl_compl, @Filter.liminf_compl (Set α)]
rw [← ae_eq_set_compl_compl, ← preimage_compl] at hs
convert hf.limsup_preimage_iterate_ae_eq hs
ext1 n
simp only [← Set.preimage_iterate_eq, comp_apply, preimage_compl]
#align measure_theory.measure.quasi_measure_preserving.liminf_preimage_iterate_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.liminf_preimage_iterate_ae_eq
/-- By replacing a measurable set that is almost invariant with the `limsup` of its preimages, we
obtain a measurable set that is almost equal and strictly invariant.
(The `liminf` would work just as well.) -/
theorem exists_preimage_eq_of_preimage_ae {f : α → α} (h : QuasiMeasurePreserving f μ μ)
(hs : MeasurableSet s) (hs' : f ⁻¹' s =ᵐ[μ] s) :
∃ t : Set α, MeasurableSet t ∧ t =ᵐ[μ] s ∧ f ⁻¹' t = t :=
⟨limsup (fun n => (preimage f)^[n] s) atTop,
MeasurableSet.measurableSet_limsup fun n =>
preimage_iterate_eq ▸ h.measurable.iterate n hs,
h.limsup_preimage_iterate_ae_eq hs',
Filter.CompleteLatticeHom.apply_limsup_iterate (CompleteLatticeHom.setPreimage f) s⟩
#align measure_theory.measure.quasi_measure_preserving.exists_preimage_eq_of_preimage_ae MeasureTheory.Measure.QuasiMeasurePreserving.exists_preimage_eq_of_preimage_ae
open Pointwise
@[to_additive]
theorem smul_ae_eq_of_ae_eq {G α : Type*} [Group G] [MulAction G α] [MeasurableSpace α]
{s t : Set α} {μ : Measure α} (g : G)
(h_qmp : QuasiMeasurePreserving (g⁻¹ • · : α → α) μ μ)
(h_ae_eq : s =ᵐ[μ] t) : (g • s : Set α) =ᵐ[μ] (g • t : Set α) := by
simpa only [← preimage_smul_inv] using h_qmp.ae_eq h_ae_eq
#align measure_theory.measure.quasi_measure_preserving.smul_ae_eq_of_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.smul_ae_eq_of_ae_eq
#align measure_theory.measure.quasi_measure_preserving.vadd_ae_eq_of_ae_eq MeasureTheory.Measure.QuasiMeasurePreserving.vadd_ae_eq_of_ae_eq
end QuasiMeasurePreserving
section Pointwise
open Pointwise
@[to_additive]
theorem pairwise_aedisjoint_of_aedisjoint_forall_ne_one {G α : Type*} [Group G] [MulAction G α]
[MeasurableSpace α] {μ : Measure α} {s : Set α}
(h_ae_disjoint : ∀ g ≠ (1 : G), AEDisjoint μ (g • s) s)
(h_qmp : ∀ g : G, QuasiMeasurePreserving (g • ·) μ μ) :
Pairwise (AEDisjoint μ on fun g : G => g • s) := by
intro g₁ g₂ hg
let g := g₂⁻¹ * g₁
replace hg : g ≠ 1 := by
rw [Ne, inv_mul_eq_one]
exact hg.symm
have : (g₂⁻¹ • ·) ⁻¹' (g • s ∩ s) = g₁ • s ∩ g₂ • s := by
rw [preimage_eq_iff_eq_image (MulAction.bijective g₂⁻¹), image_smul, smul_set_inter, smul_smul,
smul_smul, inv_mul_self, one_smul]
change μ (g₁ • s ∩ g₂ • s) = 0
exact this ▸ (h_qmp g₂⁻¹).preimage_null (h_ae_disjoint g hg)
#align measure_theory.measure.pairwise_ae_disjoint_of_ae_disjoint_forall_ne_one MeasureTheory.Measure.pairwise_aedisjoint_of_aedisjoint_forall_ne_one
#align measure_theory.measure.pairwise_ae_disjoint_of_ae_disjoint_forall_ne_zero MeasureTheory.Measure.pairwise_aedisjoint_of_aedisjoint_forall_ne_zero
end Pointwise
/-! ### 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 t ht s 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⟩
#align measure_theory.measure.cofinite MeasureTheory.Measure.cofinite
theorem mem_cofinite : s ∈ μ.cofinite ↔ μ sᶜ < ∞ :=
Iff.rfl
#align measure_theory.measure.mem_cofinite MeasureTheory.Measure.mem_cofinite
theorem compl_mem_cofinite : sᶜ ∈ μ.cofinite ↔ μ s < ∞ := by rw [mem_cofinite, compl_compl]
#align measure_theory.measure.compl_mem_cofinite MeasureTheory.Measure.compl_mem_cofinite
theorem eventually_cofinite {p : α → Prop} : (∀ᶠ x in μ.cofinite, p x) ↔ μ { x | ¬p x } < ∞ :=
Iff.rfl
#align measure_theory.measure.eventually_cofinite MeasureTheory.Measure.eventually_cofinite
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
#align ae_measurable.null_measurable AEMeasurable.nullMeasurable
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
/-- The preimage of a null measurable set under a (quasi) measure preserving map is a null
measurable set. -/
theorem NullMeasurableSet.preimage {ν : Measure β} {f : α → β} {t : Set β}
(ht : NullMeasurableSet t ν) (hf : QuasiMeasurePreserving f μ ν) :
NullMeasurableSet (f ⁻¹' t) μ :=
⟨f ⁻¹' toMeasurable ν t, hf.measurable (measurableSet_toMeasurable _ _),
hf.ae_eq ht.toMeasurable_ae_eq.symm⟩
#align measure_theory.null_measurable_set.preimage MeasureTheory.NullMeasurableSet.preimage
theorem NullMeasurableSet.mono_ac (h : NullMeasurableSet s μ) (hle : ν ≪ μ) :
NullMeasurableSet s ν :=
h.preimage <| (QuasiMeasurePreserving.id μ).mono_left hle
#align measure_theory.null_measurable_set.mono_ac MeasureTheory.NullMeasurableSet.mono_ac
theorem NullMeasurableSet.mono (h : NullMeasurableSet s μ) (hle : ν ≤ μ) : NullMeasurableSet s ν :=
h.mono_ac hle.absolutelyContinuous
#align measure_theory.null_measurable_set.mono MeasureTheory.NullMeasurableSet.mono
theorem AEDisjoint.preimage {ν : Measure β} {f : α → β} {s t : Set β} (ht : AEDisjoint ν s t)
(hf : QuasiMeasurePreserving f μ ν) : AEDisjoint μ (f ⁻¹' s) (f ⁻¹' t) :=
hf.preimage_null ht
#align measure_theory.ae_disjoint.preimage MeasureTheory.AEDisjoint.preimage
@[simp]
theorem ae_eq_bot : ae μ = ⊥ ↔ μ = 0 := by
rw [← empty_mem_iff_bot, mem_ae_iff, compl_empty, measure_univ_eq_zero]
#align measure_theory.ae_eq_bot MeasureTheory.ae_eq_bot
@[simp]
theorem ae_neBot : (ae μ).NeBot ↔ μ ≠ 0 :=
neBot_iff.trans (not_congr ae_eq_bot)
#align measure_theory.ae_ne_bot MeasureTheory.ae_neBot
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
#align measure_theory.ae_zero MeasureTheory.ae_zero
@[mono]
theorem ae_mono (h : μ ≤ ν) : ae μ ≤ ae ν :=
h.absolutelyContinuous.ae_le
#align measure_theory.ae_mono MeasureTheory.ae_mono
theorem mem_ae_map_iff {f : α → β} (hf : AEMeasurable f μ) {s : Set β} (hs : MeasurableSet s) :
s ∈ ae (μ.map f) ↔ f ⁻¹' s ∈ ae μ := by
simp only [mem_ae_iff, map_apply_of_aemeasurable hf hs.compl, preimage_compl]
#align measure_theory.mem_ae_map_iff MeasureTheory.mem_ae_map_iff
theorem mem_ae_of_mem_ae_map {f : α → β} (hf : AEMeasurable f μ) {s : Set β}
(hs : s ∈ ae (μ.map f)) : f ⁻¹' s ∈ ae μ :=
(tendsto_ae_map hf).eventually hs
#align measure_theory.mem_ae_of_mem_ae_map MeasureTheory.mem_ae_of_mem_ae_map
theorem ae_map_iff {f : α → β} (hf : AEMeasurable f μ) {p : β → Prop}
(hp : MeasurableSet { x | p x }) : (∀ᵐ y ∂μ.map f, p y) ↔ ∀ᵐ x ∂μ, p (f x) :=
mem_ae_map_iff hf hp
#align measure_theory.ae_map_iff MeasureTheory.ae_map_iff
theorem ae_of_ae_map {f : α → β} (hf : AEMeasurable f μ) {p : β → Prop} (h : ∀ᵐ y ∂μ.map f, p y) :
∀ᵐ x ∂μ, p (f x) :=
mem_ae_of_mem_ae_map hf h
#align measure_theory.ae_of_ae_map MeasureTheory.ae_of_ae_map
| Mathlib/MeasureTheory/Measure/MeasureSpace.lean | 2,027 | 2,033 | theorem ae_map_mem_range {m0 : MeasurableSpace α} (f : α → β) (hf : MeasurableSet (range f))
(μ : Measure α) : ∀ᵐ x ∂μ.map f, x ∈ range f := by |
by_cases h : AEMeasurable f μ
· change range f ∈ ae (μ.map f)
rw [mem_ae_map_iff h hf]
filter_upwards using mem_range_self
· simp [map_of_not_aemeasurable h]
|
/-
Copyright (c) 2022 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.AlgebraicTopology.DoldKan.Decomposition
import Mathlib.Tactic.FinCases
#align_import algebraic_topology.dold_kan.degeneracies from "leanprover-community/mathlib"@"32a7e535287f9c73f2e4d2aef306a39190f0b504"
/-!
# Behaviour of P_infty with respect to degeneracies
For any `X : SimplicialObject C` where `C` is an abelian category,
the projector `PInfty : K[X] ⟶ K[X]` is supposed to be the projection
on the normalized subcomplex, parallel to the degenerate subcomplex, i.e.
the subcomplex generated by the images of all `X.σ i`.
In this file, we obtain `degeneracy_comp_P_infty` which states that
if `X : SimplicialObject C` with `C` a preadditive category,
`θ : [n] ⟶ Δ'` is a non injective map in `SimplexCategory`, then
`X.map θ.op ≫ P_infty.f n = 0`. It follows from the more precise
statement vanishing statement `σ_comp_P_eq_zero` for the `P q`.
(See `Equivalence.lean` for the general strategy of proof of the Dold-Kan equivalence.)
-/
open CategoryTheory CategoryTheory.Category CategoryTheory.Limits
CategoryTheory.Preadditive Simplicial
namespace AlgebraicTopology
namespace DoldKan
variable {C : Type*} [Category C] [Preadditive C]
theorem HigherFacesVanish.comp_σ {Y : C} {X : SimplicialObject C} {n b q : ℕ} {φ : Y ⟶ X _[n + 1]}
(v : HigherFacesVanish q φ) (hnbq : n + 1 = b + q) :
HigherFacesVanish q
(φ ≫
X.σ ⟨b, by
simp only [hnbq, Nat.lt_add_one_iff, le_add_iff_nonneg_right, zero_le]⟩) :=
fun j hj => by
rw [assoc, SimplicialObject.δ_comp_σ_of_gt', Fin.pred_succ, v.comp_δ_eq_zero_assoc _ _ hj,
zero_comp]
· dsimp
rw [Fin.lt_iff_val_lt_val, Fin.val_succ]
linarith
· intro hj'
simp only [hnbq, add_comm b, add_assoc, hj', Fin.val_zero, zero_add, add_le_iff_nonpos_right,
nonpos_iff_eq_zero, add_eq_zero, false_and] at hj
#align algebraic_topology.dold_kan.higher_faces_vanish.comp_σ AlgebraicTopology.DoldKan.HigherFacesVanish.comp_σ
theorem σ_comp_P_eq_zero (X : SimplicialObject C) {n q : ℕ} (i : Fin (n + 1)) (hi : n + 1 ≤ i + q) :
X.σ i ≫ (P q).f (n + 1) = 0 := by
revert i hi
induction' q with q hq
· intro i (hi : n + 1 ≤ i)
exfalso
linarith [Fin.is_lt i]
· intro i (hi : n + 1 ≤ i + q + 1)
by_cases h : n + 1 ≤ (i : ℕ) + q
· rw [P_succ, HomologicalComplex.comp_f, ← assoc, hq i h, zero_comp]
· replace hi : n = i + q := by
obtain ⟨j, hj⟩ := le_iff_exists_add.mp hi
rw [← Nat.lt_succ_iff, Nat.succ_eq_add_one, hj, not_lt, add_le_iff_nonpos_right,
nonpos_iff_eq_zero] at h
rw [← add_left_inj 1, hj, self_eq_add_right, h]
rcases n with _|n
· fin_cases i
dsimp at h hi
rw [show q = 0 by omega]
change X.σ 0 ≫ (P 1).f 1 = 0
simp only [P_succ, HomologicalComplex.add_f_apply, comp_add,
HomologicalComplex.id_f, AlternatingFaceMapComplex.obj_d_eq, Hσ,
HomologicalComplex.comp_f, Homotopy.nullHomotopicMap'_f (c_mk 2 1 rfl) (c_mk 1 0 rfl),
comp_id]
erw [hσ'_eq' (zero_add 0).symm, hσ'_eq' (add_zero 1).symm, comp_id, Fin.sum_univ_two,
Fin.sum_univ_succ, Fin.sum_univ_two]
simp only [Fin.val_zero, pow_zero, pow_one, pow_add, one_smul, neg_smul, Fin.mk_one,
Fin.val_succ, Fin.val_one, Fin.succ_one_eq_two, P_zero, HomologicalComplex.id_f,
Fin.val_two, pow_two, mul_neg, one_mul, neg_mul, neg_neg, id_comp, add_comp,
comp_add, Fin.mk_zero, neg_comp, comp_neg, Fin.succ_zero_eq_one]
erw [SimplicialObject.δ_comp_σ_self, SimplicialObject.δ_comp_σ_self_assoc,
SimplicialObject.δ_comp_σ_succ, comp_id,
SimplicialObject.δ_comp_σ_of_le X
(show (0 : Fin 2) ≤ Fin.castSucc 0 by rw [Fin.castSucc_zero]),
SimplicialObject.δ_comp_σ_self_assoc, SimplicialObject.δ_comp_σ_succ_assoc]
simp only [add_right_neg, add_zero, zero_add]
· rw [← id_comp (X.σ i), ← (P_add_Q_f q n.succ : _ = 𝟙 (X.obj _)), add_comp, add_comp,
P_succ]
have v : HigherFacesVanish q ((P q).f n.succ ≫ X.σ i) :=
(HigherFacesVanish.of_P q n).comp_σ hi
erw [← assoc, v.comp_P_eq_self, HomologicalComplex.add_f_apply, Preadditive.comp_add,
comp_id, v.comp_Hσ_eq hi, assoc, SimplicialObject.δ_comp_σ_succ_assoc, Fin.eta,
decomposition_Q n q, sum_comp, sum_comp, Finset.sum_eq_zero, add_zero, add_neg_eq_zero]
intro j hj
simp only [true_and_iff, Finset.mem_univ, Finset.mem_filter] at hj
simp only [Nat.succ_eq_add_one] at hi
obtain ⟨k, hk⟩ := Nat.le.dest (Nat.lt_succ_iff.mp (Fin.is_lt j))
rw [add_comm] at hk
have hi' : i = Fin.castSucc ⟨i, by omega⟩ := by
ext
simp only [Fin.castSucc_mk, Fin.eta]
have eq := hq j.rev.succ (by
simp only [← hk, Fin.rev_eq j hk.symm, Nat.succ_eq_add_one, Fin.succ_mk, Fin.val_mk]
omega)
rw [HomologicalComplex.comp_f, assoc, assoc, assoc, hi',
SimplicialObject.σ_comp_σ_assoc, reassoc_of% eq, zero_comp, comp_zero, comp_zero,
comp_zero]
simp only [Fin.rev_eq j hk.symm, Fin.le_iff_val_le_val, Fin.val_mk]
omega
set_option linter.uppercaseLean3 false in
#align algebraic_topology.dold_kan.σ_comp_P_eq_zero AlgebraicTopology.DoldKan.σ_comp_P_eq_zero
@[reassoc (attr := simp)]
theorem σ_comp_PInfty (X : SimplicialObject C) {n : ℕ} (i : Fin (n + 1)) :
X.σ i ≫ PInfty.f (n + 1) = 0 := by
rw [PInfty_f, σ_comp_P_eq_zero X i]
simp only [le_add_iff_nonneg_left, zero_le]
set_option linter.uppercaseLean3 false in
#align algebraic_topology.dold_kan.σ_comp_P_infty AlgebraicTopology.DoldKan.σ_comp_PInfty
@[reassoc]
| Mathlib/AlgebraicTopology/DoldKan/Degeneracies.lean | 128 | 140 | theorem degeneracy_comp_PInfty (X : SimplicialObject C) (n : ℕ) {Δ' : SimplexCategory}
(θ : ([n] : SimplexCategory) ⟶ Δ') (hθ : ¬Mono θ) : X.map θ.op ≫ PInfty.f n = 0 := by |
rw [SimplexCategory.mono_iff_injective] at hθ
cases n
· exfalso
apply hθ
intro x y h
fin_cases x
fin_cases y
rfl
· obtain ⟨i, α, h⟩ := SimplexCategory.eq_σ_comp_of_not_injective θ hθ
rw [h, op_comp, X.map_comp, assoc, show X.map (SimplexCategory.σ i).op = X.σ i by rfl,
σ_comp_PInfty, comp_zero]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Constructions
import Mathlib.Topology.ContinuousOn
#align_import topology.bases from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Bases of topologies. Countability axioms.
A topological basis on a topological space `t` is a collection of sets,
such that all open sets can be generated as unions of these sets, without the need to take
finite intersections of them. This file introduces a framework for dealing with these collections,
and also what more we can say under certain countability conditions on bases,
which are referred to as first- and second-countable.
We also briefly cover the theory of separable spaces, which are those with a countable, dense
subset. If a space is second-countable, and also has a countably generated uniformity filter
(for example, if `t` is a metric space), it will automatically be separable (and indeed, these
conditions are equivalent in this case).
## Main definitions
* `TopologicalSpace.IsTopologicalBasis s`: The topological space `t` has basis `s`.
* `TopologicalSpace.SeparableSpace α`: The topological space `t` has a countable, dense subset.
* `TopologicalSpace.IsSeparable s`: The set `s` is contained in the closure of a countable set.
* `FirstCountableTopology α`: A topology in which `𝓝 x` is countably generated for
every `x`.
* `SecondCountableTopology α`: A topology which has a topological basis which is
countable.
## Main results
* `TopologicalSpace.FirstCountableTopology.tendsto_subseq`: In a first-countable space,
cluster points are limits of subsequences.
* `TopologicalSpace.SecondCountableTopology.isOpen_iUnion_countable`: In a second-countable space,
the union of arbitrarily-many open sets is equal to a sub-union of only countably many of these
sets.
* `TopologicalSpace.SecondCountableTopology.countable_cover_nhds`: Consider `f : α → Set α` with the
property that `f x ∈ 𝓝 x` for all `x`. Then there is some countable set `s` whose image covers
the space.
## Implementation Notes
For our applications we are interested that there exists a countable basis, but we do not need the
concrete basis itself. This allows us to declare these type classes as `Prop` to use them as mixins.
### TODO:
More fine grained instances for `FirstCountableTopology`,
`TopologicalSpace.SeparableSpace`, and more.
-/
open Set Filter Function Topology
noncomputable section
namespace TopologicalSpace
universe u
variable {α : Type u} {β : Type*} [t : TopologicalSpace α] {B : Set (Set α)} {s : Set α}
/-- A topological basis is one that satisfies the necessary conditions so that
it suffices to take unions of the basis sets to get a topology (without taking
finite intersections as well). -/
structure IsTopologicalBasis (s : Set (Set α)) : Prop where
/-- For every point `x`, the set of `t ∈ s` such that `x ∈ t` is directed downwards. -/
exists_subset_inter : ∀ t₁ ∈ s, ∀ t₂ ∈ s, ∀ x ∈ t₁ ∩ t₂, ∃ t₃ ∈ s, x ∈ t₃ ∧ t₃ ⊆ t₁ ∩ t₂
/-- The sets from `s` cover the whole space. -/
sUnion_eq : ⋃₀ s = univ
/-- The topology is generated by sets from `s`. -/
eq_generateFrom : t = generateFrom s
#align topological_space.is_topological_basis TopologicalSpace.IsTopologicalBasis
theorem IsTopologicalBasis.insert_empty {s : Set (Set α)} (h : IsTopologicalBasis s) :
IsTopologicalBasis (insert ∅ s) := by
refine ⟨?_, by rw [sUnion_insert, empty_union, h.sUnion_eq], ?_⟩
· rintro t₁ (rfl | h₁) t₂ (rfl | h₂) x ⟨hx₁, hx₂⟩
· cases hx₁
· cases hx₁
· cases hx₂
· obtain ⟨t₃, h₃, hs⟩ := h.exists_subset_inter _ h₁ _ h₂ x ⟨hx₁, hx₂⟩
exact ⟨t₃, .inr h₃, hs⟩
· rw [h.eq_generateFrom]
refine le_antisymm (le_generateFrom fun t => ?_) (generateFrom_anti <| subset_insert ∅ s)
rintro (rfl | ht)
· exact @isOpen_empty _ (generateFrom s)
· exact .basic t ht
#align topological_space.is_topological_basis.insert_empty TopologicalSpace.IsTopologicalBasis.insert_empty
theorem IsTopologicalBasis.diff_empty {s : Set (Set α)} (h : IsTopologicalBasis s) :
IsTopologicalBasis (s \ {∅}) := by
refine ⟨?_, by rw [sUnion_diff_singleton_empty, h.sUnion_eq], ?_⟩
· rintro t₁ ⟨h₁, -⟩ t₂ ⟨h₂, -⟩ x hx
obtain ⟨t₃, h₃, hs⟩ := h.exists_subset_inter _ h₁ _ h₂ x hx
exact ⟨t₃, ⟨h₃, Nonempty.ne_empty ⟨x, hs.1⟩⟩, hs⟩
· rw [h.eq_generateFrom]
refine le_antisymm (generateFrom_anti diff_subset) (le_generateFrom fun t ht => ?_)
obtain rfl | he := eq_or_ne t ∅
· exact @isOpen_empty _ (generateFrom _)
· exact .basic t ⟨ht, he⟩
#align topological_space.is_topological_basis.diff_empty TopologicalSpace.IsTopologicalBasis.diff_empty
/-- If a family of sets `s` generates the topology, then intersections of finite
subcollections of `s` form a topological basis. -/
theorem isTopologicalBasis_of_subbasis {s : Set (Set α)} (hs : t = generateFrom s) :
IsTopologicalBasis ((fun f => ⋂₀ f) '' { f : Set (Set α) | f.Finite ∧ f ⊆ s }) := by
subst t; letI := generateFrom s
refine ⟨?_, ?_, le_antisymm (le_generateFrom ?_) <| generateFrom_anti fun t ht => ?_⟩
· rintro _ ⟨t₁, ⟨hft₁, ht₁b⟩, rfl⟩ _ ⟨t₂, ⟨hft₂, ht₂b⟩, rfl⟩ x h
exact ⟨_, ⟨_, ⟨hft₁.union hft₂, union_subset ht₁b ht₂b⟩, sInter_union t₁ t₂⟩, h, Subset.rfl⟩
· rw [sUnion_image, iUnion₂_eq_univ_iff]
exact fun x => ⟨∅, ⟨finite_empty, empty_subset _⟩, sInter_empty.substr <| mem_univ x⟩
· rintro _ ⟨t, ⟨hft, htb⟩, rfl⟩
exact hft.isOpen_sInter fun s hs ↦ GenerateOpen.basic _ <| htb hs
· rw [← sInter_singleton t]
exact ⟨{t}, ⟨finite_singleton t, singleton_subset_iff.2 ht⟩, rfl⟩
#align topological_space.is_topological_basis_of_subbasis TopologicalSpace.isTopologicalBasis_of_subbasis
theorem IsTopologicalBasis.of_hasBasis_nhds {s : Set (Set α)}
(h_nhds : ∀ a, (𝓝 a).HasBasis (fun t ↦ t ∈ s ∧ a ∈ t) id) : IsTopologicalBasis s where
exists_subset_inter t₁ ht₁ t₂ ht₂ x hx := by
simpa only [and_assoc, (h_nhds x).mem_iff]
using (inter_mem ((h_nhds _).mem_of_mem ⟨ht₁, hx.1⟩) ((h_nhds _).mem_of_mem ⟨ht₂, hx.2⟩))
sUnion_eq := sUnion_eq_univ_iff.2 fun x ↦ (h_nhds x).ex_mem
eq_generateFrom := ext_nhds fun x ↦ by
simpa only [nhds_generateFrom, and_comm] using (h_nhds x).eq_biInf
/-- If a family of open sets `s` is such that every open neighbourhood contains some
member of `s`, then `s` is a topological basis. -/
theorem isTopologicalBasis_of_isOpen_of_nhds {s : Set (Set α)} (h_open : ∀ u ∈ s, IsOpen u)
(h_nhds : ∀ (a : α) (u : Set α), a ∈ u → IsOpen u → ∃ v ∈ s, a ∈ v ∧ v ⊆ u) :
IsTopologicalBasis s :=
.of_hasBasis_nhds <| fun a ↦
(nhds_basis_opens a).to_hasBasis' (by simpa [and_assoc] using h_nhds a)
fun t ⟨hts, hat⟩ ↦ (h_open _ hts).mem_nhds hat
#align topological_space.is_topological_basis_of_open_of_nhds TopologicalSpace.isTopologicalBasis_of_isOpen_of_nhds
/-- A set `s` is in the neighbourhood of `a` iff there is some basis set `t`, which
contains `a` and is itself contained in `s`. -/
theorem IsTopologicalBasis.mem_nhds_iff {a : α} {s : Set α} {b : Set (Set α)}
(hb : IsTopologicalBasis b) : s ∈ 𝓝 a ↔ ∃ t ∈ b, a ∈ t ∧ t ⊆ s := by
change s ∈ (𝓝 a).sets ↔ ∃ t ∈ b, a ∈ t ∧ t ⊆ s
rw [hb.eq_generateFrom, nhds_generateFrom, biInf_sets_eq]
· simp [and_assoc, and_left_comm]
· rintro s ⟨hs₁, hs₂⟩ t ⟨ht₁, ht₂⟩
let ⟨u, hu₁, hu₂, hu₃⟩ := hb.1 _ hs₂ _ ht₂ _ ⟨hs₁, ht₁⟩
exact ⟨u, ⟨hu₂, hu₁⟩, le_principal_iff.2 (hu₃.trans inter_subset_left),
le_principal_iff.2 (hu₃.trans inter_subset_right)⟩
· rcases eq_univ_iff_forall.1 hb.sUnion_eq a with ⟨i, h1, h2⟩
exact ⟨i, h2, h1⟩
#align topological_space.is_topological_basis.mem_nhds_iff TopologicalSpace.IsTopologicalBasis.mem_nhds_iff
theorem IsTopologicalBasis.isOpen_iff {s : Set α} {b : Set (Set α)} (hb : IsTopologicalBasis b) :
IsOpen s ↔ ∀ a ∈ s, ∃ t ∈ b, a ∈ t ∧ t ⊆ s := by simp [isOpen_iff_mem_nhds, hb.mem_nhds_iff]
#align topological_space.is_topological_basis.is_open_iff TopologicalSpace.IsTopologicalBasis.isOpen_iff
theorem IsTopologicalBasis.nhds_hasBasis {b : Set (Set α)} (hb : IsTopologicalBasis b) {a : α} :
(𝓝 a).HasBasis (fun t : Set α => t ∈ b ∧ a ∈ t) fun t => t :=
⟨fun s => hb.mem_nhds_iff.trans <| by simp only [and_assoc]⟩
#align topological_space.is_topological_basis.nhds_has_basis TopologicalSpace.IsTopologicalBasis.nhds_hasBasis
protected theorem IsTopologicalBasis.isOpen {s : Set α} {b : Set (Set α)}
(hb : IsTopologicalBasis b) (hs : s ∈ b) : IsOpen s := by
rw [hb.eq_generateFrom]
exact .basic s hs
#align topological_space.is_topological_basis.is_open TopologicalSpace.IsTopologicalBasis.isOpen
protected theorem IsTopologicalBasis.mem_nhds {a : α} {s : Set α} {b : Set (Set α)}
(hb : IsTopologicalBasis b) (hs : s ∈ b) (ha : a ∈ s) : s ∈ 𝓝 a :=
(hb.isOpen hs).mem_nhds ha
#align topological_space.is_topological_basis.mem_nhds TopologicalSpace.IsTopologicalBasis.mem_nhds
theorem IsTopologicalBasis.exists_subset_of_mem_open {b : Set (Set α)} (hb : IsTopologicalBasis b)
{a : α} {u : Set α} (au : a ∈ u) (ou : IsOpen u) : ∃ v ∈ b, a ∈ v ∧ v ⊆ u :=
hb.mem_nhds_iff.1 <| IsOpen.mem_nhds ou au
#align topological_space.is_topological_basis.exists_subset_of_mem_open TopologicalSpace.IsTopologicalBasis.exists_subset_of_mem_open
/-- Any open set is the union of the basis sets contained in it. -/
theorem IsTopologicalBasis.open_eq_sUnion' {B : Set (Set α)} (hB : IsTopologicalBasis B) {u : Set α}
(ou : IsOpen u) : u = ⋃₀ { s ∈ B | s ⊆ u } :=
ext fun _a =>
⟨fun ha =>
let ⟨b, hb, ab, bu⟩ := hB.exists_subset_of_mem_open ha ou
⟨b, ⟨hb, bu⟩, ab⟩,
fun ⟨_b, ⟨_, bu⟩, ab⟩ => bu ab⟩
#align topological_space.is_topological_basis.open_eq_sUnion' TopologicalSpace.IsTopologicalBasis.open_eq_sUnion'
theorem IsTopologicalBasis.open_eq_sUnion {B : Set (Set α)} (hB : IsTopologicalBasis B) {u : Set α}
(ou : IsOpen u) : ∃ S ⊆ B, u = ⋃₀ S :=
⟨{ s ∈ B | s ⊆ u }, fun _ h => h.1, hB.open_eq_sUnion' ou⟩
#align topological_space.is_topological_basis.open_eq_sUnion TopologicalSpace.IsTopologicalBasis.open_eq_sUnion
theorem IsTopologicalBasis.open_iff_eq_sUnion {B : Set (Set α)} (hB : IsTopologicalBasis B)
{u : Set α} : IsOpen u ↔ ∃ S ⊆ B, u = ⋃₀ S :=
⟨hB.open_eq_sUnion, fun ⟨_S, hSB, hu⟩ => hu.symm ▸ isOpen_sUnion fun _s hs => hB.isOpen (hSB hs)⟩
#align topological_space.is_topological_basis.open_iff_eq_sUnion TopologicalSpace.IsTopologicalBasis.open_iff_eq_sUnion
theorem IsTopologicalBasis.open_eq_iUnion {B : Set (Set α)} (hB : IsTopologicalBasis B) {u : Set α}
(ou : IsOpen u) : ∃ (β : Type u) (f : β → Set α), (u = ⋃ i, f i) ∧ ∀ i, f i ∈ B :=
⟨↥({ s ∈ B | s ⊆ u }), (↑), by
rw [← sUnion_eq_iUnion]
apply hB.open_eq_sUnion' ou, fun s => And.left s.2⟩
#align topological_space.is_topological_basis.open_eq_Union TopologicalSpace.IsTopologicalBasis.open_eq_iUnion
lemma IsTopologicalBasis.subset_of_forall_subset {t : Set α} (hB : IsTopologicalBasis B)
(hs : IsOpen s) (h : ∀ U ∈ B, U ⊆ s → U ⊆ t) : s ⊆ t := by
rw [hB.open_eq_sUnion' hs]; simpa [sUnion_subset_iff]
lemma IsTopologicalBasis.eq_of_forall_subset_iff {t : Set α} (hB : IsTopologicalBasis B)
(hs : IsOpen s) (ht : IsOpen t) (h : ∀ U ∈ B, U ⊆ s ↔ U ⊆ t) : s = t := by
rw [hB.open_eq_sUnion' hs, hB.open_eq_sUnion' ht]
exact congr_arg _ (Set.ext fun U ↦ and_congr_right <| h _)
/-- A point `a` is in the closure of `s` iff all basis sets containing `a` intersect `s`. -/
theorem IsTopologicalBasis.mem_closure_iff {b : Set (Set α)} (hb : IsTopologicalBasis b) {s : Set α}
{a : α} : a ∈ closure s ↔ ∀ o ∈ b, a ∈ o → (o ∩ s).Nonempty :=
(mem_closure_iff_nhds_basis' hb.nhds_hasBasis).trans <| by simp only [and_imp]
#align topological_space.is_topological_basis.mem_closure_iff TopologicalSpace.IsTopologicalBasis.mem_closure_iff
/-- A set is dense iff it has non-trivial intersection with all basis sets. -/
theorem IsTopologicalBasis.dense_iff {b : Set (Set α)} (hb : IsTopologicalBasis b) {s : Set α} :
Dense s ↔ ∀ o ∈ b, Set.Nonempty o → (o ∩ s).Nonempty := by
simp only [Dense, hb.mem_closure_iff]
exact ⟨fun h o hb ⟨a, ha⟩ => h a o hb ha, fun h a o hb ha => h o hb ⟨a, ha⟩⟩
#align topological_space.is_topological_basis.dense_iff TopologicalSpace.IsTopologicalBasis.dense_iff
theorem IsTopologicalBasis.isOpenMap_iff {β} [TopologicalSpace β] {B : Set (Set α)}
(hB : IsTopologicalBasis B) {f : α → β} : IsOpenMap f ↔ ∀ s ∈ B, IsOpen (f '' s) := by
refine ⟨fun H o ho => H _ (hB.isOpen ho), fun hf o ho => ?_⟩
rw [hB.open_eq_sUnion' ho, sUnion_eq_iUnion, image_iUnion]
exact isOpen_iUnion fun s => hf s s.2.1
#align topological_space.is_topological_basis.is_open_map_iff TopologicalSpace.IsTopologicalBasis.isOpenMap_iff
theorem IsTopologicalBasis.exists_nonempty_subset {B : Set (Set α)} (hb : IsTopologicalBasis B)
{u : Set α} (hu : u.Nonempty) (ou : IsOpen u) : ∃ v ∈ B, Set.Nonempty v ∧ v ⊆ u :=
let ⟨x, hx⟩ := hu
let ⟨v, vB, xv, vu⟩ := hb.exists_subset_of_mem_open hx ou
⟨v, vB, ⟨x, xv⟩, vu⟩
#align topological_space.is_topological_basis.exists_nonempty_subset TopologicalSpace.IsTopologicalBasis.exists_nonempty_subset
theorem isTopologicalBasis_opens : IsTopologicalBasis { U : Set α | IsOpen U } :=
isTopologicalBasis_of_isOpen_of_nhds (by tauto) (by tauto)
#align topological_space.is_topological_basis_opens TopologicalSpace.isTopologicalBasis_opens
protected theorem IsTopologicalBasis.inducing {β} [TopologicalSpace β] {f : α → β} {T : Set (Set β)}
(hf : Inducing f) (h : IsTopologicalBasis T) : IsTopologicalBasis ((preimage f) '' T) :=
.of_hasBasis_nhds fun a ↦ by
convert (hf.basis_nhds (h.nhds_hasBasis (a := f a))).to_image_id with s
aesop
#align topological_space.is_topological_basis.inducing TopologicalSpace.IsTopologicalBasis.inducing
protected theorem IsTopologicalBasis.induced [s : TopologicalSpace β] (f : α → β)
{T : Set (Set β)} (h : IsTopologicalBasis T) :
IsTopologicalBasis (t := induced f s) ((preimage f) '' T) :=
h.inducing (t := induced f s) (inducing_induced f)
protected theorem IsTopologicalBasis.inf {t₁ t₂ : TopologicalSpace β} {B₁ B₂ : Set (Set β)}
(h₁ : IsTopologicalBasis (t := t₁) B₁) (h₂ : IsTopologicalBasis (t := t₂) B₂) :
IsTopologicalBasis (t := t₁ ⊓ t₂) (image2 (· ∩ ·) B₁ B₂) := by
refine .of_hasBasis_nhds (t := ?_) fun a ↦ ?_
rw [nhds_inf (t₁ := t₁)]
convert ((h₁.nhds_hasBasis (t := t₁)).inf (h₂.nhds_hasBasis (t := t₂))).to_image_id
aesop
theorem IsTopologicalBasis.inf_induced {γ} [s : TopologicalSpace β] {B₁ : Set (Set α)}
{B₂ : Set (Set β)} (h₁ : IsTopologicalBasis B₁) (h₂ : IsTopologicalBasis B₂) (f₁ : γ → α)
(f₂ : γ → β) :
IsTopologicalBasis (t := induced f₁ t ⊓ induced f₂ s) (image2 (f₁ ⁻¹' · ∩ f₂ ⁻¹' ·) B₁ B₂) := by
simpa only [image2_image_left, image2_image_right] using (h₁.induced f₁).inf (h₂.induced f₂)
protected theorem IsTopologicalBasis.prod {β} [TopologicalSpace β] {B₁ : Set (Set α)}
{B₂ : Set (Set β)} (h₁ : IsTopologicalBasis B₁) (h₂ : IsTopologicalBasis B₂) :
IsTopologicalBasis (image2 (· ×ˢ ·) B₁ B₂) :=
h₁.inf_induced h₂ Prod.fst Prod.snd
#align topological_space.is_topological_basis.prod TopologicalSpace.IsTopologicalBasis.prod
theorem isTopologicalBasis_of_cover {ι} {U : ι → Set α} (Uo : ∀ i, IsOpen (U i))
(Uc : ⋃ i, U i = univ) {b : ∀ i, Set (Set (U i))} (hb : ∀ i, IsTopologicalBasis (b i)) :
IsTopologicalBasis (⋃ i : ι, image ((↑) : U i → α) '' b i) := by
refine isTopologicalBasis_of_isOpen_of_nhds (fun u hu => ?_) ?_
· simp only [mem_iUnion, mem_image] at hu
rcases hu with ⟨i, s, sb, rfl⟩
exact (Uo i).isOpenMap_subtype_val _ ((hb i).isOpen sb)
· intro a u ha uo
rcases iUnion_eq_univ_iff.1 Uc a with ⟨i, hi⟩
lift a to ↥(U i) using hi
rcases (hb i).exists_subset_of_mem_open ha (uo.preimage continuous_subtype_val) with
⟨v, hvb, hav, hvu⟩
exact ⟨(↑) '' v, mem_iUnion.2 ⟨i, mem_image_of_mem _ hvb⟩, mem_image_of_mem _ hav,
image_subset_iff.2 hvu⟩
#align topological_space.is_topological_basis_of_cover TopologicalSpace.isTopologicalBasis_of_cover
protected theorem IsTopologicalBasis.continuous_iff {β : Type*} [TopologicalSpace β]
{B : Set (Set β)} (hB : IsTopologicalBasis B) {f : α → β} :
Continuous f ↔ ∀ s ∈ B, IsOpen (f ⁻¹' s) := by
rw [hB.eq_generateFrom, continuous_generateFrom_iff]
@[deprecated]
protected theorem IsTopologicalBasis.continuous {β : Type*} [TopologicalSpace β] {B : Set (Set β)}
(hB : IsTopologicalBasis B) (f : α → β) (hf : ∀ s ∈ B, IsOpen (f ⁻¹' s)) : Continuous f :=
hB.continuous_iff.2 hf
#align topological_space.is_topological_basis.continuous TopologicalSpace.IsTopologicalBasis.continuous
variable (α)
/-- A separable space is one with a countable dense subset, available through
`TopologicalSpace.exists_countable_dense`. If `α` is also known to be nonempty, then
`TopologicalSpace.denseSeq` provides a sequence `ℕ → α` with dense range, see
`TopologicalSpace.denseRange_denseSeq`.
If `α` is a uniform space with countably generated uniformity filter (e.g., an `EMetricSpace`), then
this condition is equivalent to `SecondCountableTopology α`. In this case the
latter should be used as a typeclass argument in theorems because Lean can automatically deduce
`TopologicalSpace.SeparableSpace` from `SecondCountableTopology` but it can't
deduce `SecondCountableTopology` from `TopologicalSpace.SeparableSpace`.
Porting note (#11215): TODO: the previous paragraph describes the state of the art in Lean 3.
We can have instance cycles in Lean 4 but we might want to
postpone adding them till after the port. -/
@[mk_iff] class SeparableSpace : Prop where
/-- There exists a countable dense set. -/
exists_countable_dense : ∃ s : Set α, s.Countable ∧ Dense s
#align topological_space.separable_space TopologicalSpace.SeparableSpace
theorem exists_countable_dense [SeparableSpace α] : ∃ s : Set α, s.Countable ∧ Dense s :=
SeparableSpace.exists_countable_dense
#align topological_space.exists_countable_dense TopologicalSpace.exists_countable_dense
/-- A nonempty separable space admits a sequence with dense range. Instead of running `cases` on the
conclusion of this lemma, you might want to use `TopologicalSpace.denseSeq` and
`TopologicalSpace.denseRange_denseSeq`.
If `α` might be empty, then `TopologicalSpace.exists_countable_dense` is the main way to use
separability of `α`. -/
theorem exists_dense_seq [SeparableSpace α] [Nonempty α] : ∃ u : ℕ → α, DenseRange u := by
obtain ⟨s : Set α, hs, s_dense⟩ := exists_countable_dense α
cases' Set.countable_iff_exists_subset_range.mp hs with u hu
exact ⟨u, s_dense.mono hu⟩
#align topological_space.exists_dense_seq TopologicalSpace.exists_dense_seq
/-- A dense sequence in a non-empty separable topological space.
If `α` might be empty, then `TopologicalSpace.exists_countable_dense` is the main way to use
separability of `α`. -/
def denseSeq [SeparableSpace α] [Nonempty α] : ℕ → α :=
Classical.choose (exists_dense_seq α)
#align topological_space.dense_seq TopologicalSpace.denseSeq
/-- The sequence `TopologicalSpace.denseSeq α` has dense range. -/
@[simp]
theorem denseRange_denseSeq [SeparableSpace α] [Nonempty α] : DenseRange (denseSeq α) :=
Classical.choose_spec (exists_dense_seq α)
#align topological_space.dense_range_dense_seq TopologicalSpace.denseRange_denseSeq
variable {α}
instance (priority := 100) Countable.to_separableSpace [Countable α] : SeparableSpace α where
exists_countable_dense := ⟨Set.univ, Set.countable_univ, dense_univ⟩
#align topological_space.countable.to_separable_space TopologicalSpace.Countable.to_separableSpace
/-- If `f` has a dense range and its domain is countable, then its codomain is a separable space.
See also `DenseRange.separableSpace`. -/
theorem SeparableSpace.of_denseRange {ι : Sort _} [Countable ι] (u : ι → α) (hu : DenseRange u) :
SeparableSpace α :=
⟨⟨range u, countable_range u, hu⟩⟩
#align topological_space.separable_space_of_dense_range TopologicalSpace.SeparableSpace.of_denseRange
alias _root_.DenseRange.separableSpace' := SeparableSpace.of_denseRange
/-- If `α` is a separable space and `f : α → β` is a continuous map with dense range, then `β` is
a separable space as well. E.g., the completion of a separable uniform space is separable. -/
protected theorem _root_.DenseRange.separableSpace [SeparableSpace α] [TopologicalSpace β]
{f : α → β} (h : DenseRange f) (h' : Continuous f) : SeparableSpace β :=
let ⟨s, s_cnt, s_dense⟩ := exists_countable_dense α
⟨⟨f '' s, Countable.image s_cnt f, h.dense_image h' s_dense⟩⟩
#align dense_range.separable_space DenseRange.separableSpace
theorem _root_.QuotientMap.separableSpace [SeparableSpace α] [TopologicalSpace β] {f : α → β}
(hf : QuotientMap f) : SeparableSpace β :=
hf.surjective.denseRange.separableSpace hf.continuous
/-- The product of two separable spaces is a separable space. -/
instance [TopologicalSpace β] [SeparableSpace α] [SeparableSpace β] : SeparableSpace (α × β) := by
rcases exists_countable_dense α with ⟨s, hsc, hsd⟩
rcases exists_countable_dense β with ⟨t, htc, htd⟩
exact ⟨⟨s ×ˢ t, hsc.prod htc, hsd.prod htd⟩⟩
/-- The product of a countable family of separable spaces is a separable space. -/
instance {ι : Type*} {X : ι → Type*} [∀ i, TopologicalSpace (X i)] [∀ i, SeparableSpace (X i)]
[Countable ι] : SeparableSpace (∀ i, X i) := by
choose t htc htd using (exists_countable_dense <| X ·)
haveI := fun i ↦ (htc i).to_subtype
nontriviality ∀ i, X i; inhabit ∀ i, X i
classical
set f : (Σ I : Finset ι, ∀ i : I, t i) → ∀ i, X i := fun ⟨I, g⟩ i ↦
if hi : i ∈ I then g ⟨i, hi⟩ else (default : ∀ i, X i) i
refine ⟨⟨range f, countable_range f, dense_iff_inter_open.2 fun U hU ⟨g, hg⟩ ↦ ?_⟩⟩
rcases isOpen_pi_iff.1 hU g hg with ⟨I, u, huo, huU⟩
have : ∀ i : I, ∃ y ∈ t i, y ∈ u i := fun i ↦
(htd i).exists_mem_open (huo i i.2).1 ⟨_, (huo i i.2).2⟩
choose y hyt hyu using this
lift y to ∀ i : I, t i using hyt
refine ⟨f ⟨I, y⟩, huU fun i (hi : i ∈ I) ↦ ?_, mem_range_self _⟩
simp only [f, dif_pos hi]
exact hyu _
instance [SeparableSpace α] {r : α → α → Prop} : SeparableSpace (Quot r) :=
quotientMap_quot_mk.separableSpace
instance [SeparableSpace α] {s : Setoid α} : SeparableSpace (Quotient s) :=
quotientMap_quot_mk.separableSpace
/-- A topological space with discrete topology is separable iff it is countable. -/
theorem separableSpace_iff_countable [DiscreteTopology α] : SeparableSpace α ↔ Countable α := by
simp [separableSpace_iff, countable_univ_iff]
/-- In a separable space, a family of nonempty disjoint open sets is countable. -/
theorem _root_.Pairwise.countable_of_isOpen_disjoint [SeparableSpace α] {ι : Type*}
{s : ι → Set α} (hd : Pairwise (Disjoint on s)) (ho : ∀ i, IsOpen (s i))
(hne : ∀ i, (s i).Nonempty) : Countable ι := by
rcases exists_countable_dense α with ⟨u, u_countable, u_dense⟩
choose f hfu hfs using fun i ↦ u_dense.exists_mem_open (ho i) (hne i)
have f_inj : Injective f := fun i j hij ↦
hd.eq <| not_disjoint_iff.2 ⟨f i, hfs i, hij.symm ▸ hfs j⟩
have := u_countable.to_subtype
exact (f_inj.codRestrict hfu).countable
/-- In a separable space, a family of nonempty disjoint open sets is countable. -/
theorem _root_.Set.PairwiseDisjoint.countable_of_isOpen [SeparableSpace α] {ι : Type*}
{s : ι → Set α} {a : Set ι} (h : a.PairwiseDisjoint s) (ho : ∀ i ∈ a, IsOpen (s i))
(hne : ∀ i ∈ a, (s i).Nonempty) : a.Countable :=
(h.subtype _ _).countable_of_isOpen_disjoint (Subtype.forall.2 ho) (Subtype.forall.2 hne)
#align set.pairwise_disjoint.countable_of_is_open Set.PairwiseDisjoint.countable_of_isOpen
/-- In a separable space, a family of disjoint sets with nonempty interiors is countable. -/
theorem _root_.Set.PairwiseDisjoint.countable_of_nonempty_interior [SeparableSpace α] {ι : Type*}
{s : ι → Set α} {a : Set ι} (h : a.PairwiseDisjoint s)
(ha : ∀ i ∈ a, (interior (s i)).Nonempty) : a.Countable :=
(h.mono fun _ => interior_subset).countable_of_isOpen (fun _ _ => isOpen_interior) ha
#align set.pairwise_disjoint.countable_of_nonempty_interior Set.PairwiseDisjoint.countable_of_nonempty_interior
/-- A set `s` in a topological space is separable if it is contained in the closure of a countable
set `c`. Beware that this definition does not require that `c` is contained in `s` (to express the
latter, use `TopologicalSpace.SeparableSpace s` or
`TopologicalSpace.IsSeparable (univ : Set s))`. In metric spaces, the two definitions are
equivalent, see `TopologicalSpace.IsSeparable.separableSpace`. -/
def IsSeparable (s : Set α) :=
∃ c : Set α, c.Countable ∧ s ⊆ closure c
#align topological_space.is_separable TopologicalSpace.IsSeparable
theorem IsSeparable.mono {s u : Set α} (hs : IsSeparable s) (hu : u ⊆ s) : IsSeparable u := by
rcases hs with ⟨c, c_count, hs⟩
exact ⟨c, c_count, hu.trans hs⟩
#align topological_space.is_separable.mono TopologicalSpace.IsSeparable.mono
theorem IsSeparable.iUnion {ι : Sort*} [Countable ι] {s : ι → Set α}
(hs : ∀ i, IsSeparable (s i)) : IsSeparable (⋃ i, s i) := by
choose c hc h'c using hs
refine ⟨⋃ i, c i, countable_iUnion hc, iUnion_subset_iff.2 fun i => ?_⟩
exact (h'c i).trans (closure_mono (subset_iUnion _ i))
#align topological_space.is_separable_Union TopologicalSpace.IsSeparable.iUnion
@[simp]
theorem isSeparable_iUnion {ι : Sort*} [Countable ι] {s : ι → Set α} :
IsSeparable (⋃ i, s i) ↔ ∀ i, IsSeparable (s i) :=
⟨fun h i ↦ h.mono <| subset_iUnion s i, .iUnion⟩
@[simp]
theorem isSeparable_union {s t : Set α} : IsSeparable (s ∪ t) ↔ IsSeparable s ∧ IsSeparable t := by
simp [union_eq_iUnion, and_comm]
theorem IsSeparable.union {s u : Set α} (hs : IsSeparable s) (hu : IsSeparable u) :
IsSeparable (s ∪ u) :=
isSeparable_union.2 ⟨hs, hu⟩
#align topological_space.is_separable.union TopologicalSpace.IsSeparable.union
@[simp]
theorem isSeparable_closure : IsSeparable (closure s) ↔ IsSeparable s := by
simp only [IsSeparable, isClosed_closure.closure_subset_iff]
protected alias ⟨_, IsSeparable.closure⟩ := isSeparable_closure
#align topological_space.is_separable.closure TopologicalSpace.IsSeparable.closure
theorem _root_.Set.Countable.isSeparable {s : Set α} (hs : s.Countable) : IsSeparable s :=
⟨s, hs, subset_closure⟩
#align set.countable.is_separable Set.Countable.isSeparable
theorem _root_.Set.Finite.isSeparable {s : Set α} (hs : s.Finite) : IsSeparable s :=
hs.countable.isSeparable
#align set.finite.is_separable Set.Finite.isSeparable
theorem IsSeparable.univ_pi {ι : Type*} [Countable ι] {X : ι → Type*} {s : ∀ i, Set (X i)}
[∀ i, TopologicalSpace (X i)] (h : ∀ i, IsSeparable (s i)) :
IsSeparable (univ.pi s) := by
classical
rcases eq_empty_or_nonempty (univ.pi s) with he | ⟨f₀, -⟩
· rw [he]
exact countable_empty.isSeparable
· choose c c_count hc using h
haveI := fun i ↦ (c_count i).to_subtype
set g : (I : Finset ι) × ((i : I) → c i) → (i : ι) → X i := fun ⟨I, f⟩ i ↦
if hi : i ∈ I then f ⟨i, hi⟩ else f₀ i
refine ⟨range g, countable_range g, fun f hf ↦ mem_closure_iff.2 fun o ho hfo ↦ ?_⟩
rcases isOpen_pi_iff.1 ho f hfo with ⟨I, u, huo, hI⟩
rsuffices ⟨f, hf⟩ : ∃ f : (i : I) → c i, g ⟨I, f⟩ ∈ Set.pi I u
· exact ⟨g ⟨I, f⟩, hI hf, mem_range_self _⟩
suffices H : ∀ i ∈ I, (u i ∩ c i).Nonempty by
choose f hfu hfc using H
refine ⟨fun i ↦ ⟨f i i.2, hfc i i.2⟩, fun i (hi : i ∈ I) ↦ ?_⟩
simpa only [g, dif_pos hi] using hfu i hi
intro i hi
exact mem_closure_iff.1 (hc i <| hf _ trivial) _ (huo i hi).1 (huo i hi).2
lemma isSeparable_pi {ι : Type*} [Countable ι] {α : ι → Type*} {s : ∀ i, Set (α i)}
[∀ i, TopologicalSpace (α i)] (h : ∀ i, IsSeparable (s i)) :
IsSeparable {f : ∀ i, α i | ∀ i, f i ∈ s i} := by
simpa only [← mem_univ_pi] using IsSeparable.univ_pi h
lemma IsSeparable.prod {β : Type*} [TopologicalSpace β]
{s : Set α} {t : Set β} (hs : IsSeparable s) (ht : IsSeparable t) :
IsSeparable (s ×ˢ t) := by
rcases hs with ⟨cs, cs_count, hcs⟩
rcases ht with ⟨ct, ct_count, hct⟩
refine ⟨cs ×ˢ ct, cs_count.prod ct_count, ?_⟩
rw [closure_prod_eq]
gcongr
theorem IsSeparable.image {β : Type*} [TopologicalSpace β] {s : Set α} (hs : IsSeparable s)
{f : α → β} (hf : Continuous f) : IsSeparable (f '' s) := by
rcases hs with ⟨c, c_count, hc⟩
refine ⟨f '' c, c_count.image _, ?_⟩
rw [image_subset_iff]
exact hc.trans (closure_subset_preimage_closure_image hf)
#align topological_space.is_separable.image TopologicalSpace.IsSeparable.image
theorem _root_.Dense.isSeparable_iff (hs : Dense s) :
IsSeparable s ↔ SeparableSpace α := by
simp_rw [IsSeparable, separableSpace_iff, dense_iff_closure_eq, ← univ_subset_iff,
← hs.closure_eq, isClosed_closure.closure_subset_iff]
theorem isSeparable_univ_iff : IsSeparable (univ : Set α) ↔ SeparableSpace α :=
dense_univ.isSeparable_iff
#align topological_space.is_separable_univ_iff TopologicalSpace.isSeparable_univ_iff
theorem isSeparable_range [TopologicalSpace β] [SeparableSpace α] {f : α → β} (hf : Continuous f) :
IsSeparable (range f) :=
image_univ (f := f) ▸ (isSeparable_univ_iff.2 ‹_›).image hf
theorem IsSeparable.of_subtype (s : Set α) [SeparableSpace s] : IsSeparable s := by
simpa using isSeparable_range (continuous_subtype_val (p := (· ∈ s)))
#align topological_space.is_separable_of_separable_space_subtype TopologicalSpace.IsSeparable.of_subtype
@[deprecated (since := "2024-02-05")]
alias isSeparable_of_separableSpace_subtype := IsSeparable.of_subtype
theorem IsSeparable.of_separableSpace [h : SeparableSpace α] (s : Set α) : IsSeparable s :=
IsSeparable.mono (isSeparable_univ_iff.2 h) (subset_univ _)
#align topological_space.is_separable_of_separable_space TopologicalSpace.IsSeparable.of_separableSpace
@[deprecated (since := "2024-02-05")]
alias isSeparable_of_separableSpace := IsSeparable.of_separableSpace
end TopologicalSpace
open TopologicalSpace
protected theorem IsTopologicalBasis.iInf {β : Type*} {ι : Type*} {t : ι → TopologicalSpace β}
{T : ι → Set (Set β)} (h_basis : ∀ i, IsTopologicalBasis (t := t i) (T i)) :
IsTopologicalBasis (t := ⨅ i, t i)
{ S | ∃ (U : ι → Set β) (F : Finset ι), (∀ i, i ∈ F → U i ∈ T i) ∧ S = ⋂ i ∈ F, U i } := by
let _ := ⨅ i, t i
refine isTopologicalBasis_of_isOpen_of_nhds ?_ ?_
· rintro - ⟨U, F, hU, rfl⟩
refine isOpen_biInter_finset fun i hi ↦
(h_basis i).isOpen (t := t i) (hU i hi) |>.mono (iInf_le _ _)
· intro a u ha hu
rcases (nhds_iInf (t := t) (a := a)).symm ▸ hasBasis_iInf'
(fun i ↦ (h_basis i).nhds_hasBasis (t := t i)) |>.mem_iff.1 (hu.mem_nhds ha)
with ⟨⟨F, U⟩, ⟨hF, hU⟩, hUu⟩
refine ⟨_, ⟨U, hF.toFinset, ?_, rfl⟩, ?_, ?_⟩ <;> simp only [Finite.mem_toFinset, mem_iInter]
· exact fun i hi ↦ (hU i hi).1
· exact fun i hi ↦ (hU i hi).2
· exact hUu
theorem IsTopologicalBasis.iInf_induced {β : Type*} {ι : Type*} {X : ι → Type*}
[t : Π i, TopologicalSpace (X i)] {T : Π i, Set (Set (X i))}
(cond : ∀ i, IsTopologicalBasis (T i)) (f : Π i, β → X i) :
IsTopologicalBasis (t := ⨅ i, induced (f i) (t i))
{ S | ∃ (U : ∀ i, Set (X i)) (F : Finset ι),
(∀ i, i ∈ F → U i ∈ T i) ∧ S = ⋂ (i) (_ : i ∈ F), f i ⁻¹' U i } := by
convert IsTopologicalBasis.iInf (fun i ↦ (cond i).induced (f i)) with S
constructor <;> rintro ⟨U, F, hUT, hSU⟩
· exact ⟨fun i ↦ (f i) ⁻¹' (U i), F, fun i hi ↦ mem_image_of_mem _ (hUT i hi), hSU⟩
· choose! U' hU' hUU' using hUT
exact ⟨U', F, hU', hSU ▸ (.symm <| iInter₂_congr hUU')⟩
#align is_topological_basis_infi IsTopologicalBasis.iInf_induced
theorem isTopologicalBasis_pi {ι : Type*} {X : ι → Type*} [∀ i, TopologicalSpace (X i)]
{T : ∀ i, Set (Set (X i))} (cond : ∀ i, IsTopologicalBasis (T i)) :
IsTopologicalBasis { S | ∃ (U : ∀ i, Set (X i)) (F : Finset ι),
(∀ i, i ∈ F → U i ∈ T i) ∧ S = (F : Set ι).pi U } := by
simpa only [Set.pi_def] using IsTopologicalBasis.iInf_induced cond eval
#align is_topological_basis_pi isTopologicalBasis_pi
theorem isTopologicalBasis_singletons (α : Type*) [TopologicalSpace α] [DiscreteTopology α] :
IsTopologicalBasis { s | ∃ x : α, (s : Set α) = {x} } :=
isTopologicalBasis_of_isOpen_of_nhds (fun _ _ => isOpen_discrete _) fun x _ hx _ =>
⟨{x}, ⟨x, rfl⟩, mem_singleton x, singleton_subset_iff.2 hx⟩
#align is_topological_basis_singletons isTopologicalBasis_singletons
theorem isTopologicalBasis_subtype
{α : Type*} [TopologicalSpace α] {B : Set (Set α)}
(h : TopologicalSpace.IsTopologicalBasis B) (p : α → Prop) :
IsTopologicalBasis (Set.preimage (Subtype.val (p := p)) '' B) :=
h.inducing ⟨rfl⟩
-- Porting note: moved `DenseRange.separableSpace` up
theorem Dense.exists_countable_dense_subset {α : Type*} [TopologicalSpace α] {s : Set α}
[SeparableSpace s] (hs : Dense s) : ∃ t ⊆ s, t.Countable ∧ Dense t :=
let ⟨t, htc, htd⟩ := exists_countable_dense s
⟨(↑) '' t, Subtype.coe_image_subset s t, htc.image Subtype.val,
hs.denseRange_val.dense_image continuous_subtype_val htd⟩
#align dense.exists_countable_dense_subset Dense.exists_countable_dense_subsetₓ
/-- Let `s` be a dense set in a topological space `α` with partial order structure. If `s` is a
separable space (e.g., if `α` has a second countable topology), then there exists a countable
dense subset `t ⊆ s` such that `t` contains bottom/top element of `α` when they exist and belong
to `s`. For a dense subset containing neither bot nor top elements, see
`Dense.exists_countable_dense_subset_no_bot_top`. -/
theorem Dense.exists_countable_dense_subset_bot_top {α : Type*} [TopologicalSpace α]
[PartialOrder α] {s : Set α} [SeparableSpace s] (hs : Dense s) :
∃ t ⊆ s, t.Countable ∧ Dense t ∧ (∀ x, IsBot x → x ∈ s → x ∈ t) ∧
∀ x, IsTop x → x ∈ s → x ∈ t := by
rcases hs.exists_countable_dense_subset with ⟨t, hts, htc, htd⟩
refine ⟨(t ∪ ({ x | IsBot x } ∪ { x | IsTop x })) ∩ s, ?_, ?_, ?_, ?_, ?_⟩
exacts [inter_subset_right,
(htc.union ((countable_isBot α).union (countable_isTop α))).mono inter_subset_left,
htd.mono (subset_inter subset_union_left hts), fun x hx hxs => ⟨Or.inr <| Or.inl hx, hxs⟩,
fun x hx hxs => ⟨Or.inr <| Or.inr hx, hxs⟩]
#align dense.exists_countable_dense_subset_bot_top Dense.exists_countable_dense_subset_bot_top
instance separableSpace_univ {α : Type*} [TopologicalSpace α] [SeparableSpace α] :
SeparableSpace (univ : Set α) :=
(Equiv.Set.univ α).symm.surjective.denseRange.separableSpace (continuous_id.subtype_mk _)
#align separable_space_univ separableSpace_univ
/-- If `α` is a separable topological space with a partial order, then there exists a countable
dense set `s : Set α` that contains those of both bottom and top elements of `α` that actually
exist. For a dense set containing neither bot nor top elements, see
`exists_countable_dense_no_bot_top`. -/
theorem exists_countable_dense_bot_top (α : Type*) [TopologicalSpace α] [SeparableSpace α]
[PartialOrder α] :
∃ s : Set α, s.Countable ∧ Dense s ∧ (∀ x, IsBot x → x ∈ s) ∧ ∀ x, IsTop x → x ∈ s := by
simpa using dense_univ.exists_countable_dense_subset_bot_top
#align exists_countable_dense_bot_top exists_countable_dense_bot_top
namespace TopologicalSpace
universe u
variable (α : Type u) [t : TopologicalSpace α]
/-- A first-countable space is one in which every point has a
countable neighborhood basis. -/
class _root_.FirstCountableTopology : Prop where
/-- The filter `𝓝 a` is countably generated for all points `a`. -/
nhds_generated_countable : ∀ a : α, (𝓝 a).IsCountablyGenerated
#align topological_space.first_countable_topology FirstCountableTopology
attribute [instance] FirstCountableTopology.nhds_generated_countable
/-- If `β` is a first-countable space, then its induced topology via `f` on `α` is also
first-countable. -/
theorem firstCountableTopology_induced (α β : Type*) [t : TopologicalSpace β]
[FirstCountableTopology β] (f : α → β) : @FirstCountableTopology α (t.induced f) :=
let _ := t.induced f;
⟨fun x ↦ nhds_induced f x ▸ inferInstance⟩
variable {α}
instance Subtype.firstCountableTopology (s : Set α) [FirstCountableTopology α] :
FirstCountableTopology s :=
firstCountableTopology_induced s α (↑)
protected theorem _root_.Inducing.firstCountableTopology {β : Type*}
[TopologicalSpace β] [FirstCountableTopology β] {f : α → β} (hf : Inducing f) :
FirstCountableTopology α := by
rw [hf.1]
exact firstCountableTopology_induced α β f
protected theorem _root_.Embedding.firstCountableTopology {β : Type*}
[TopologicalSpace β] [FirstCountableTopology β] {f : α → β} (hf : Embedding f) :
FirstCountableTopology α :=
hf.1.firstCountableTopology
namespace FirstCountableTopology
/-- In a first-countable space, a cluster point `x` of a sequence
is the limit of some subsequence. -/
theorem tendsto_subseq [FirstCountableTopology α] {u : ℕ → α} {x : α}
(hx : MapClusterPt x atTop u) : ∃ ψ : ℕ → ℕ, StrictMono ψ ∧ Tendsto (u ∘ ψ) atTop (𝓝 x) :=
subseq_tendsto_of_neBot hx
#align topological_space.first_countable_topology.tendsto_subseq TopologicalSpace.FirstCountableTopology.tendsto_subseq
end FirstCountableTopology
instance {β} [TopologicalSpace β] [FirstCountableTopology α] [FirstCountableTopology β] :
FirstCountableTopology (α × β) :=
⟨fun ⟨x, y⟩ => by rw [nhds_prod_eq]; infer_instance⟩
section Pi
instance {ι : Type*} {π : ι → Type*} [Countable ι] [∀ i, TopologicalSpace (π i)]
[∀ i, FirstCountableTopology (π i)] : FirstCountableTopology (∀ i, π i) :=
⟨fun f => by rw [nhds_pi]; infer_instance⟩
end Pi
instance isCountablyGenerated_nhdsWithin (x : α) [IsCountablyGenerated (𝓝 x)] (s : Set α) :
IsCountablyGenerated (𝓝[s] x) :=
Inf.isCountablyGenerated _ _
#align topological_space.is_countably_generated_nhds_within TopologicalSpace.isCountablyGenerated_nhdsWithin
variable (α)
/-- A second-countable space is one with a countable basis. -/
class _root_.SecondCountableTopology : Prop where
/-- There exists a countable set of sets that generates the topology. -/
is_open_generated_countable : ∃ b : Set (Set α), b.Countable ∧ t = TopologicalSpace.generateFrom b
#align topological_space.second_countable_topology SecondCountableTopology
variable {α}
protected theorem IsTopologicalBasis.secondCountableTopology {b : Set (Set α)}
(hb : IsTopologicalBasis b) (hc : b.Countable) : SecondCountableTopology α :=
⟨⟨b, hc, hb.eq_generateFrom⟩⟩
#align topological_space.is_topological_basis.second_countable_topology TopologicalSpace.IsTopologicalBasis.secondCountableTopology
lemma SecondCountableTopology.mk' {b : Set (Set α)} (hc : b.Countable) :
@SecondCountableTopology α (generateFrom b) :=
@SecondCountableTopology.mk α (generateFrom b) ⟨b, hc, rfl⟩
instance _root_.Finite.toSecondCountableTopology [Finite α] : SecondCountableTopology α where
is_open_generated_countable :=
⟨_, {U | IsOpen U}.to_countable, TopologicalSpace.isTopologicalBasis_opens.eq_generateFrom⟩
variable (α)
theorem exists_countable_basis [SecondCountableTopology α] :
∃ b : Set (Set α), b.Countable ∧ ∅ ∉ b ∧ IsTopologicalBasis b := by
obtain ⟨b, hb₁, hb₂⟩ := @SecondCountableTopology.is_open_generated_countable α _ _
refine ⟨_, ?_, not_mem_diff_of_mem ?_, (isTopologicalBasis_of_subbasis hb₂).diff_empty⟩
exacts [((countable_setOf_finite_subset hb₁).image _).mono diff_subset, rfl]
#align topological_space.exists_countable_basis TopologicalSpace.exists_countable_basis
/-- A countable topological basis of `α`. -/
def countableBasis [SecondCountableTopology α] : Set (Set α) :=
(exists_countable_basis α).choose
#align topological_space.countable_basis TopologicalSpace.countableBasis
theorem countable_countableBasis [SecondCountableTopology α] : (countableBasis α).Countable :=
(exists_countable_basis α).choose_spec.1
#align topological_space.countable_countable_basis TopologicalSpace.countable_countableBasis
instance encodableCountableBasis [SecondCountableTopology α] : Encodable (countableBasis α) :=
(countable_countableBasis α).toEncodable
#align topological_space.encodable_countable_basis TopologicalSpace.encodableCountableBasis
theorem empty_nmem_countableBasis [SecondCountableTopology α] : ∅ ∉ countableBasis α :=
(exists_countable_basis α).choose_spec.2.1
#align topological_space.empty_nmem_countable_basis TopologicalSpace.empty_nmem_countableBasis
theorem isBasis_countableBasis [SecondCountableTopology α] :
IsTopologicalBasis (countableBasis α) :=
(exists_countable_basis α).choose_spec.2.2
#align topological_space.is_basis_countable_basis TopologicalSpace.isBasis_countableBasis
theorem eq_generateFrom_countableBasis [SecondCountableTopology α] :
‹TopologicalSpace α› = generateFrom (countableBasis α) :=
(isBasis_countableBasis α).eq_generateFrom
#align topological_space.eq_generate_from_countable_basis TopologicalSpace.eq_generateFrom_countableBasis
variable {α}
theorem isOpen_of_mem_countableBasis [SecondCountableTopology α] {s : Set α}
(hs : s ∈ countableBasis α) : IsOpen s :=
(isBasis_countableBasis α).isOpen hs
#align topological_space.is_open_of_mem_countable_basis TopologicalSpace.isOpen_of_mem_countableBasis
theorem nonempty_of_mem_countableBasis [SecondCountableTopology α] {s : Set α}
(hs : s ∈ countableBasis α) : s.Nonempty :=
nonempty_iff_ne_empty.2 <| ne_of_mem_of_not_mem hs <| empty_nmem_countableBasis α
#align topological_space.nonempty_of_mem_countable_basis TopologicalSpace.nonempty_of_mem_countableBasis
variable (α)
-- see Note [lower instance priority]
instance (priority := 100) SecondCountableTopology.to_firstCountableTopology
[SecondCountableTopology α] : FirstCountableTopology α :=
⟨fun _ => HasCountableBasis.isCountablyGenerated <|
⟨(isBasis_countableBasis α).nhds_hasBasis,
(countable_countableBasis α).mono inter_subset_left⟩⟩
#align topological_space.second_countable_topology.to_first_countable_topology TopologicalSpace.SecondCountableTopology.to_firstCountableTopology
/-- If `β` is a second-countable space, then its induced topology via
`f` on `α` is also second-countable. -/
theorem secondCountableTopology_induced (β) [t : TopologicalSpace β] [SecondCountableTopology β]
(f : α → β) : @SecondCountableTopology α (t.induced f) := by
rcases @SecondCountableTopology.is_open_generated_countable β _ _ with ⟨b, hb, eq⟩
letI := t.induced f
refine { is_open_generated_countable := ⟨preimage f '' b, hb.image _, ?_⟩ }
rw [eq, induced_generateFrom_eq]
#align topological_space.second_countable_topology_induced TopologicalSpace.secondCountableTopology_induced
variable {α}
instance Subtype.secondCountableTopology (s : Set α) [SecondCountableTopology α] :
SecondCountableTopology s :=
secondCountableTopology_induced s α (↑)
#align topological_space.subtype.second_countable_topology TopologicalSpace.Subtype.secondCountableTopology
lemma secondCountableTopology_iInf {ι} [Countable ι] {t : ι → TopologicalSpace α}
(ht : ∀ i, @SecondCountableTopology α (t i)) : @SecondCountableTopology α (⨅ i, t i) := by
rw [funext fun i => @eq_generateFrom_countableBasis α (t i) (ht i), ← generateFrom_iUnion]
exact SecondCountableTopology.mk' <|
countable_iUnion fun i => @countable_countableBasis _ (t i) (ht i)
-- TODO: more fine grained instances for `FirstCountableTopology`, `SeparableSpace`, `T2Space`, ...
instance {β : Type*} [TopologicalSpace β] [SecondCountableTopology α] [SecondCountableTopology β] :
SecondCountableTopology (α × β) :=
((isBasis_countableBasis α).prod (isBasis_countableBasis β)).secondCountableTopology <|
(countable_countableBasis α).image2 (countable_countableBasis β) _
instance {ι : Type*} {π : ι → Type*} [Countable ι] [∀ a, TopologicalSpace (π a)]
[∀ a, SecondCountableTopology (π a)] : SecondCountableTopology (∀ a, π a) :=
secondCountableTopology_iInf fun _ => secondCountableTopology_induced _ _ _
-- see Note [lower instance priority]
instance (priority := 100) SecondCountableTopology.to_separableSpace [SecondCountableTopology α] :
SeparableSpace α := by
choose p hp using fun s : countableBasis α => nonempty_of_mem_countableBasis s.2
exact
⟨⟨range p, countable_range _,
(isBasis_countableBasis α).dense_iff.2 fun o ho _ => ⟨p ⟨o, ho⟩, hp _, mem_range_self _⟩⟩⟩
#align topological_space.second_countable_topology.to_separable_space TopologicalSpace.SecondCountableTopology.to_separableSpace
/-- A countable open cover induces a second-countable topology if all open covers
are themselves second countable. -/
theorem secondCountableTopology_of_countable_cover {ι} [Countable ι] {U : ι → Set α}
[∀ i, SecondCountableTopology (U i)] (Uo : ∀ i, IsOpen (U i)) (hc : ⋃ i, U i = univ) :
SecondCountableTopology α :=
haveI : IsTopologicalBasis (⋃ i, image ((↑) : U i → α) '' countableBasis (U i)) :=
isTopologicalBasis_of_cover Uo hc fun i => isBasis_countableBasis (U i)
this.secondCountableTopology (countable_iUnion fun _ => (countable_countableBasis _).image _)
#align topological_space.second_countable_topology_of_countable_cover TopologicalSpace.secondCountableTopology_of_countable_cover
/-- In a second-countable space, an open set, given as a union of open sets,
is equal to the union of countably many of those sets.
In particular, any open covering of `α` has a countable subcover: α is a Lindelöf space. -/
| Mathlib/Topology/Bases.lean | 864 | 872 | theorem isOpen_iUnion_countable [SecondCountableTopology α] {ι} (s : ι → Set α)
(H : ∀ i, IsOpen (s i)) : ∃ T : Set ι, T.Countable ∧ ⋃ i ∈ T, s i = ⋃ i, s i := by |
let B := { b ∈ countableBasis α | ∃ i, b ⊆ s i }
choose f hf using fun b : B => b.2.2
haveI : Countable B := ((countable_countableBasis α).mono (sep_subset _ _)).to_subtype
refine ⟨_, countable_range f, (iUnion₂_subset_iUnion _ _).antisymm (sUnion_subset ?_)⟩
rintro _ ⟨i, rfl⟩ x xs
rcases (isBasis_countableBasis α).exists_subset_of_mem_open xs (H _) with ⟨b, hb, xb, bs⟩
exact ⟨_, ⟨_, rfl⟩, _, ⟨⟨⟨_, hb, _, bs⟩, rfl⟩, rfl⟩, hf _ xb⟩
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn
-/
import Mathlib.Algebra.Star.Basic
import Mathlib.Algebra.Order.CauSeq.Completion
#align_import data.real.basic from "leanprover-community/mathlib"@"cb42593171ba005beaaf4549fcfe0dece9ada4c9"
/-!
# Real numbers from Cauchy sequences
This file defines `ℝ` as the type of equivalence classes of Cauchy sequences of rational numbers.
This choice is motivated by how easy it is to prove that `ℝ` is a commutative ring, by simply
lifting everything to `ℚ`.
The facts that the real numbers are an Archimedean floor ring,
and a conditionally complete linear order,
have been deferred to the file `Mathlib/Data/Real/Archimedean.lean`,
in order to keep the imports here simple.
-/
assert_not_exists Finset
assert_not_exists Module
assert_not_exists Submonoid
assert_not_exists FloorRing
/-- The type `ℝ` of real numbers constructed as equivalence classes of Cauchy sequences of rational
numbers. -/
structure Real where ofCauchy ::
/-- The underlying Cauchy completion -/
cauchy : CauSeq.Completion.Cauchy (abs : ℚ → ℚ)
#align real Real
@[inherit_doc]
notation "ℝ" => Real
-- Porting note: unknown attribute
-- attribute [pp_using_anonymous_constructor] Real
namespace CauSeq.Completion
-- this can't go in `Data.Real.CauSeqCompletion` as the structure on `ℚ` isn't available
@[simp]
theorem ofRat_rat {abv : ℚ → ℚ} [IsAbsoluteValue abv] (q : ℚ) :
ofRat (q : ℚ) = (q : Cauchy abv) :=
rfl
#align cau_seq.completion.of_rat_rat CauSeq.Completion.ofRat_rat
end CauSeq.Completion
namespace Real
open CauSeq CauSeq.Completion
variable {x y : ℝ}
theorem ext_cauchy_iff : ∀ {x y : Real}, x = y ↔ x.cauchy = y.cauchy
| ⟨a⟩, ⟨b⟩ => by rw [ofCauchy.injEq]
#align real.ext_cauchy_iff Real.ext_cauchy_iff
theorem ext_cauchy {x y : Real} : x.cauchy = y.cauchy → x = y :=
ext_cauchy_iff.2
#align real.ext_cauchy Real.ext_cauchy
/-- The real numbers are isomorphic to the quotient of Cauchy sequences on the rationals. -/
def equivCauchy : ℝ ≃ CauSeq.Completion.Cauchy (abs : ℚ → ℚ) :=
⟨Real.cauchy, Real.ofCauchy, fun ⟨_⟩ => rfl, fun _ => rfl⟩
set_option linter.uppercaseLean3 false in
#align real.equiv_Cauchy Real.equivCauchy
-- irreducible doesn't work for instances: https://github.com/leanprover-community/lean/issues/511
private irreducible_def zero : ℝ :=
⟨0⟩
private irreducible_def one : ℝ :=
⟨1⟩
private irreducible_def add : ℝ → ℝ → ℝ
| ⟨a⟩, ⟨b⟩ => ⟨a + b⟩
private irreducible_def neg : ℝ → ℝ
| ⟨a⟩ => ⟨-a⟩
private irreducible_def mul : ℝ → ℝ → ℝ
| ⟨a⟩, ⟨b⟩ => ⟨a * b⟩
private noncomputable irreducible_def inv' : ℝ → ℝ
| ⟨a⟩ => ⟨a⁻¹⟩
instance : Zero ℝ :=
⟨zero⟩
instance : One ℝ :=
⟨one⟩
instance : Add ℝ :=
⟨add⟩
instance : Neg ℝ :=
⟨neg⟩
instance : Mul ℝ :=
⟨mul⟩
instance : Sub ℝ :=
⟨fun a b => a + -b⟩
noncomputable instance : Inv ℝ :=
⟨inv'⟩
theorem ofCauchy_zero : (⟨0⟩ : ℝ) = 0 :=
zero_def.symm
#align real.of_cauchy_zero Real.ofCauchy_zero
theorem ofCauchy_one : (⟨1⟩ : ℝ) = 1 :=
one_def.symm
#align real.of_cauchy_one Real.ofCauchy_one
theorem ofCauchy_add (a b) : (⟨a + b⟩ : ℝ) = ⟨a⟩ + ⟨b⟩ :=
(add_def _ _).symm
#align real.of_cauchy_add Real.ofCauchy_add
theorem ofCauchy_neg (a) : (⟨-a⟩ : ℝ) = -⟨a⟩ :=
(neg_def _).symm
#align real.of_cauchy_neg Real.ofCauchy_neg
theorem ofCauchy_sub (a b) : (⟨a - b⟩ : ℝ) = ⟨a⟩ - ⟨b⟩ := by
rw [sub_eq_add_neg, ofCauchy_add, ofCauchy_neg]
rfl
#align real.of_cauchy_sub Real.ofCauchy_sub
theorem ofCauchy_mul (a b) : (⟨a * b⟩ : ℝ) = ⟨a⟩ * ⟨b⟩ :=
(mul_def _ _).symm
#align real.of_cauchy_mul Real.ofCauchy_mul
theorem ofCauchy_inv {f} : (⟨f⁻¹⟩ : ℝ) = ⟨f⟩⁻¹ :=
show _ = inv' _ by rw [inv']
#align real.of_cauchy_inv Real.ofCauchy_inv
theorem cauchy_zero : (0 : ℝ).cauchy = 0 :=
show zero.cauchy = 0 by rw [zero_def]
#align real.cauchy_zero Real.cauchy_zero
theorem cauchy_one : (1 : ℝ).cauchy = 1 :=
show one.cauchy = 1 by rw [one_def]
#align real.cauchy_one Real.cauchy_one
theorem cauchy_add : ∀ a b, (a + b : ℝ).cauchy = a.cauchy + b.cauchy
| ⟨a⟩, ⟨b⟩ => show (add _ _).cauchy = _ by rw [add_def]
#align real.cauchy_add Real.cauchy_add
theorem cauchy_neg : ∀ a, (-a : ℝ).cauchy = -a.cauchy
| ⟨a⟩ => show (neg _).cauchy = _ by rw [neg_def]
#align real.cauchy_neg Real.cauchy_neg
theorem cauchy_mul : ∀ a b, (a * b : ℝ).cauchy = a.cauchy * b.cauchy
| ⟨a⟩, ⟨b⟩ => show (mul _ _).cauchy = _ by rw [mul_def]
#align real.cauchy_mul Real.cauchy_mul
theorem cauchy_sub : ∀ a b, (a - b : ℝ).cauchy = a.cauchy - b.cauchy
| ⟨a⟩, ⟨b⟩ => by
rw [sub_eq_add_neg, ← cauchy_neg, ← cauchy_add]
rfl
#align real.cauchy_sub Real.cauchy_sub
theorem cauchy_inv : ∀ f, (f⁻¹ : ℝ).cauchy = f.cauchy⁻¹
| ⟨f⟩ => show (inv' _).cauchy = _ by rw [inv']
#align real.cauchy_inv Real.cauchy_inv
instance instNatCast : NatCast ℝ where natCast n := ⟨n⟩
instance instIntCast : IntCast ℝ where intCast z := ⟨z⟩
instance instNNRatCast : NNRatCast ℝ where nnratCast q := ⟨q⟩
instance instRatCast : RatCast ℝ where ratCast q := ⟨q⟩
lemma ofCauchy_natCast (n : ℕ) : (⟨n⟩ : ℝ) = n := rfl
lemma ofCauchy_intCast (z : ℤ) : (⟨z⟩ : ℝ) = z := rfl
lemma ofCauchy_nnratCast (q : ℚ≥0) : (⟨q⟩ : ℝ) = q := rfl
lemma ofCauchy_ratCast (q : ℚ) : (⟨q⟩ : ℝ) = q := rfl
#align real.of_cauchy_nat_cast Real.ofCauchy_natCast
#align real.of_cauchy_int_cast Real.ofCauchy_intCast
#align real.of_cauchy_rat_cast Real.ofCauchy_ratCast
lemma cauchy_natCast (n : ℕ) : (n : ℝ).cauchy = n := rfl
lemma cauchy_intCast (z : ℤ) : (z : ℝ).cauchy = z := rfl
lemma cauchy_nnratCast (q : ℚ≥0) : (q : ℝ).cauchy = q := rfl
lemma cauchy_ratCast (q : ℚ) : (q : ℝ).cauchy = q := rfl
#align real.cauchy_nat_cast Real.cauchy_natCast
#align real.cauchy_int_cast Real.cauchy_intCast
#align real.cauchy_rat_cast Real.cauchy_ratCast
instance commRing : CommRing ℝ where
natCast n := ⟨n⟩
intCast z := ⟨z⟩
zero := (0 : ℝ)
one := (1 : ℝ)
mul := (· * ·)
add := (· + ·)
neg := @Neg.neg ℝ _
sub := @Sub.sub ℝ _
npow := @npowRec ℝ ⟨1⟩ ⟨(· * ·)⟩
nsmul := @nsmulRec ℝ ⟨0⟩ ⟨(· + ·)⟩
zsmul := @zsmulRec ℝ ⟨0⟩ ⟨(· + ·)⟩ ⟨@Neg.neg ℝ _⟩ (@nsmulRec ℝ ⟨0⟩ ⟨(· + ·)⟩)
add_zero a := by apply ext_cauchy; simp [cauchy_add, cauchy_zero]
zero_add a := by apply ext_cauchy; simp [cauchy_add, cauchy_zero]
add_comm a b := by apply ext_cauchy; simp only [cauchy_add, add_comm]
add_assoc a b c := by apply ext_cauchy; simp only [cauchy_add, add_assoc]
mul_zero a := by apply ext_cauchy; simp [cauchy_mul, cauchy_zero]
zero_mul a := by apply ext_cauchy; simp [cauchy_mul, cauchy_zero]
mul_one a := by apply ext_cauchy; simp [cauchy_mul, cauchy_one]
one_mul a := by apply ext_cauchy; simp [cauchy_mul, cauchy_one]
mul_comm a b := by apply ext_cauchy; simp only [cauchy_mul, mul_comm]
mul_assoc a b c := by apply ext_cauchy; simp only [cauchy_mul, mul_assoc]
left_distrib a b c := by apply ext_cauchy; simp only [cauchy_add, cauchy_mul, mul_add]
right_distrib a b c := by apply ext_cauchy; simp only [cauchy_add, cauchy_mul, add_mul]
add_left_neg a := by apply ext_cauchy; simp [cauchy_add, cauchy_neg, cauchy_zero]
natCast_zero := by apply ext_cauchy; simp [cauchy_zero]
natCast_succ n := by apply ext_cauchy; simp [cauchy_one, cauchy_add]
intCast_negSucc z := by apply ext_cauchy; simp [cauchy_neg, cauchy_natCast]
/-- `Real.equivCauchy` as a ring equivalence. -/
@[simps]
def ringEquivCauchy : ℝ ≃+* CauSeq.Completion.Cauchy (abs : ℚ → ℚ) :=
{ equivCauchy with
toFun := cauchy
invFun := ofCauchy
map_add' := cauchy_add
map_mul' := cauchy_mul }
set_option linter.uppercaseLean3 false in
#align real.ring_equiv_Cauchy Real.ringEquivCauchy
set_option linter.uppercaseLean3 false in
#align real.ring_equiv_Cauchy_apply Real.ringEquivCauchy_apply
set_option linter.uppercaseLean3 false in
#align real.ring_equiv_Cauchy_symm_apply_cauchy Real.ringEquivCauchy_symm_apply_cauchy
/-! Extra instances to short-circuit type class resolution.
These short-circuits have an additional property of ensuring that a computable path is found; if
`Field ℝ` is found first, then decaying it to these typeclasses would result in a `noncomputable`
version of them. -/
instance instRing : Ring ℝ := by infer_instance
instance : CommSemiring ℝ := by infer_instance
instance semiring : Semiring ℝ := by infer_instance
instance : CommMonoidWithZero ℝ := by infer_instance
instance : MonoidWithZero ℝ := by infer_instance
instance : AddCommGroup ℝ := by infer_instance
instance : AddGroup ℝ := by infer_instance
instance : AddCommMonoid ℝ := by infer_instance
instance : AddMonoid ℝ := by infer_instance
instance : AddLeftCancelSemigroup ℝ := by infer_instance
instance : AddRightCancelSemigroup ℝ := by infer_instance
instance : AddCommSemigroup ℝ := by infer_instance
instance : AddSemigroup ℝ := by infer_instance
instance : CommMonoid ℝ := by infer_instance
instance : Monoid ℝ := by infer_instance
instance : CommSemigroup ℝ := by infer_instance
instance : Semigroup ℝ := by infer_instance
instance : Inhabited ℝ :=
⟨0⟩
/-- The real numbers are a `*`-ring, with the trivial `*`-structure. -/
instance : StarRing ℝ :=
starRingOfComm
instance : TrivialStar ℝ :=
⟨fun _ => rfl⟩
/-- Make a real number from a Cauchy sequence of rationals (by taking the equivalence class). -/
def mk (x : CauSeq ℚ abs) : ℝ :=
⟨CauSeq.Completion.mk x⟩
#align real.mk Real.mk
theorem mk_eq {f g : CauSeq ℚ abs} : mk f = mk g ↔ f ≈ g :=
ext_cauchy_iff.trans CauSeq.Completion.mk_eq
#align real.mk_eq Real.mk_eq
private irreducible_def lt : ℝ → ℝ → Prop
| ⟨x⟩, ⟨y⟩ =>
(Quotient.liftOn₂ x y (· < ·)) fun _ _ _ _ hf hg =>
propext <|
⟨fun h => lt_of_eq_of_lt (Setoid.symm hf) (lt_of_lt_of_eq h hg), fun h =>
lt_of_eq_of_lt hf (lt_of_lt_of_eq h (Setoid.symm hg))⟩
instance : LT ℝ :=
⟨lt⟩
theorem lt_cauchy {f g} : (⟨⟦f⟧⟩ : ℝ) < ⟨⟦g⟧⟩ ↔ f < g :=
show lt _ _ ↔ _ by rw [lt_def]; rfl
#align real.lt_cauchy Real.lt_cauchy
@[simp]
theorem mk_lt {f g : CauSeq ℚ abs} : mk f < mk g ↔ f < g :=
lt_cauchy
#align real.mk_lt Real.mk_lt
theorem mk_zero : mk 0 = 0 := by rw [← ofCauchy_zero]; rfl
#align real.mk_zero Real.mk_zero
theorem mk_one : mk 1 = 1 := by rw [← ofCauchy_one]; rfl
#align real.mk_one Real.mk_one
theorem mk_add {f g : CauSeq ℚ abs} : mk (f + g) = mk f + mk g := by simp [mk, ← ofCauchy_add]
#align real.mk_add Real.mk_add
theorem mk_mul {f g : CauSeq ℚ abs} : mk (f * g) = mk f * mk g := by simp [mk, ← ofCauchy_mul]
#align real.mk_mul Real.mk_mul
theorem mk_neg {f : CauSeq ℚ abs} : mk (-f) = -mk f := by simp [mk, ← ofCauchy_neg]
#align real.mk_neg Real.mk_neg
@[simp]
theorem mk_pos {f : CauSeq ℚ abs} : 0 < mk f ↔ Pos f := by
rw [← mk_zero, mk_lt]
exact iff_of_eq (congr_arg Pos (sub_zero f))
#align real.mk_pos Real.mk_pos
private irreducible_def le (x y : ℝ) : Prop :=
x < y ∨ x = y
instance : LE ℝ :=
⟨le⟩
private theorem le_def' {x y : ℝ} : x ≤ y ↔ x < y ∨ x = y :=
show le _ _ ↔ _ by rw [le_def]
@[simp]
theorem mk_le {f g : CauSeq ℚ abs} : mk f ≤ mk g ↔ f ≤ g := by
simp only [le_def', mk_lt, mk_eq]; rfl
#align real.mk_le Real.mk_le
@[elab_as_elim]
protected theorem ind_mk {C : Real → Prop} (x : Real) (h : ∀ y, C (mk y)) : C x := by
cases' x with x
induction' x using Quot.induction_on with x
exact h x
#align real.ind_mk Real.ind_mk
| Mathlib/Data/Real/Basic.lean | 358 | 363 | theorem add_lt_add_iff_left {a b : ℝ} (c : ℝ) : c + a < c + b ↔ a < b := by |
induction a using Real.ind_mk
induction b using Real.ind_mk
induction c using Real.ind_mk
simp only [mk_lt, ← mk_add]
show Pos _ ↔ Pos _; rw [add_sub_add_left_eq_sub]
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Markus Himmel
-/
import Mathlib.CategoryTheory.Limits.Shapes.Equalizers
import Mathlib.CategoryTheory.Limits.Shapes.Pullbacks
import Mathlib.CategoryTheory.Limits.Shapes.StrongEpi
import Mathlib.CategoryTheory.MorphismProperty.Factorization
#align_import category_theory.limits.shapes.images from "leanprover-community/mathlib"@"563aed347eb59dc4181cb732cda0d124d736eaa3"
/-!
# Categorical images
We define the categorical image of `f` as a factorisation `f = e ≫ m` through a monomorphism `m`,
so that `m` factors through the `m'` in any other such factorisation.
## Main definitions
* A `MonoFactorisation` is a factorisation `f = e ≫ m`, where `m` is a monomorphism
* `IsImage F` means that a given mono factorisation `F` has the universal property of the image.
* `HasImage f` means that there is some image factorization for the morphism `f : X ⟶ Y`.
* In this case, `image f` is some image object (selected with choice), `image.ι f : image f ⟶ Y`
is the monomorphism `m` of the factorisation and `factorThruImage f : X ⟶ image f` is the
morphism `e`.
* `HasImages C` means that every morphism in `C` has an image.
* Let `f : X ⟶ Y` and `g : P ⟶ Q` be morphisms in `C`, which we will represent as objects of the
arrow category `arrow C`. Then `sq : f ⟶ g` is a commutative square in `C`. If `f` and `g` have
images, then `HasImageMap sq` represents the fact that there is a morphism
`i : image f ⟶ image g` making the diagram
X ----→ image f ----→ Y
| | |
| | |
↓ ↓ ↓
P ----→ image g ----→ Q
commute, where the top row is the image factorisation of `f`, the bottom row is the image
factorisation of `g`, and the outer rectangle is the commutative square `sq`.
* If a category `HasImages`, then `HasImageMaps` means that every commutative square admits an
image map.
* If a category `HasImages`, then `HasStrongEpiImages` means that the morphism to the image is
always a strong epimorphism.
## Main statements
* When `C` has equalizers, the morphism `e` appearing in an image factorisation is an epimorphism.
* When `C` has strong epi images, then these images admit image maps.
## Future work
* TODO: coimages, and abelian categories.
* TODO: connect this with existing working in the group theory and ring theory libraries.
-/
noncomputable section
universe v u
open CategoryTheory
open CategoryTheory.Limits.WalkingParallelPair
namespace CategoryTheory.Limits
variable {C : Type u} [Category.{v} C]
variable {X Y : C} (f : X ⟶ Y)
/-- A factorisation of a morphism `f = e ≫ m`, with `m` monic. -/
structure MonoFactorisation (f : X ⟶ Y) where
I : C -- Porting note: violates naming conventions but can't think a better replacement
m : I ⟶ Y
[m_mono : Mono m]
e : X ⟶ I
fac : e ≫ m = f := by aesop_cat
#align category_theory.limits.mono_factorisation CategoryTheory.Limits.MonoFactorisation
#align category_theory.limits.mono_factorisation.fac' CategoryTheory.Limits.MonoFactorisation.fac
attribute [inherit_doc MonoFactorisation] MonoFactorisation.I MonoFactorisation.m
MonoFactorisation.m_mono MonoFactorisation.e MonoFactorisation.fac
attribute [reassoc (attr := simp)] MonoFactorisation.fac
attribute [instance] MonoFactorisation.m_mono
attribute [instance] MonoFactorisation.m_mono
namespace MonoFactorisation
/-- The obvious factorisation of a monomorphism through itself. -/
def self [Mono f] : MonoFactorisation f where
I := X
m := f
e := 𝟙 X
#align category_theory.limits.mono_factorisation.self CategoryTheory.Limits.MonoFactorisation.self
-- I'm not sure we really need this, but the linter says that an inhabited instance
-- ought to exist...
instance [Mono f] : Inhabited (MonoFactorisation f) := ⟨self f⟩
variable {f}
/-- The morphism `m` in a factorisation `f = e ≫ m` through a monomorphism is uniquely
determined. -/
@[ext]
theorem ext {F F' : MonoFactorisation f} (hI : F.I = F'.I)
(hm : F.m = eqToHom hI ≫ F'.m) : F = F' := by
cases' F with _ Fm _ _ Ffac; cases' F' with _ Fm' _ _ Ffac'
cases' hI
simp? at hm says simp only [eqToHom_refl, Category.id_comp] at hm
congr
apply (cancel_mono Fm).1
rw [Ffac, hm, Ffac']
#align category_theory.limits.mono_factorisation.ext CategoryTheory.Limits.MonoFactorisation.ext
/-- Any mono factorisation of `f` gives a mono factorisation of `f ≫ g` when `g` is a mono. -/
@[simps]
def compMono (F : MonoFactorisation f) {Y' : C} (g : Y ⟶ Y') [Mono g] :
MonoFactorisation (f ≫ g) where
I := F.I
m := F.m ≫ g
m_mono := mono_comp _ _
e := F.e
#align category_theory.limits.mono_factorisation.comp_mono CategoryTheory.Limits.MonoFactorisation.compMono
/-- A mono factorisation of `f ≫ g`, where `g` is an isomorphism,
gives a mono factorisation of `f`. -/
@[simps]
def ofCompIso {Y' : C} {g : Y ⟶ Y'} [IsIso g] (F : MonoFactorisation (f ≫ g)) :
MonoFactorisation f where
I := F.I
m := F.m ≫ inv g
m_mono := mono_comp _ _
e := F.e
#align category_theory.limits.mono_factorisation.of_comp_iso CategoryTheory.Limits.MonoFactorisation.ofCompIso
/-- Any mono factorisation of `f` gives a mono factorisation of `g ≫ f`. -/
@[simps]
def isoComp (F : MonoFactorisation f) {X' : C} (g : X' ⟶ X) : MonoFactorisation (g ≫ f) where
I := F.I
m := F.m
e := g ≫ F.e
#align category_theory.limits.mono_factorisation.iso_comp CategoryTheory.Limits.MonoFactorisation.isoComp
/-- A mono factorisation of `g ≫ f`, where `g` is an isomorphism,
gives a mono factorisation of `f`. -/
@[simps]
def ofIsoComp {X' : C} (g : X' ⟶ X) [IsIso g] (F : MonoFactorisation (g ≫ f)) :
MonoFactorisation f where
I := F.I
m := F.m
e := inv g ≫ F.e
#align category_theory.limits.mono_factorisation.of_iso_comp CategoryTheory.Limits.MonoFactorisation.ofIsoComp
/-- If `f` and `g` are isomorphic arrows, then a mono factorisation of `f`
gives a mono factorisation of `g` -/
@[simps]
def ofArrowIso {f g : Arrow C} (F : MonoFactorisation f.hom) (sq : f ⟶ g) [IsIso sq] :
MonoFactorisation g.hom where
I := F.I
m := F.m ≫ sq.right
e := inv sq.left ≫ F.e
m_mono := mono_comp _ _
fac := by simp only [fac_assoc, Arrow.w, IsIso.inv_comp_eq, Category.assoc]
#align category_theory.limits.mono_factorisation.of_arrow_iso CategoryTheory.Limits.MonoFactorisation.ofArrowIso
end MonoFactorisation
variable {f}
/-- Data exhibiting that a given factorisation through a mono is initial. -/
structure IsImage (F : MonoFactorisation f) where
lift : ∀ F' : MonoFactorisation f, F.I ⟶ F'.I
lift_fac : ∀ F' : MonoFactorisation f, lift F' ≫ F'.m = F.m := by aesop_cat
#align category_theory.limits.is_image CategoryTheory.Limits.IsImage
#align category_theory.limits.is_image.lift_fac' CategoryTheory.Limits.IsImage.lift_fac
attribute [inherit_doc IsImage] IsImage.lift IsImage.lift_fac
attribute [reassoc (attr := simp)] IsImage.lift_fac
namespace IsImage
@[reassoc (attr := simp)]
theorem fac_lift {F : MonoFactorisation f} (hF : IsImage F) (F' : MonoFactorisation f) :
F.e ≫ hF.lift F' = F'.e :=
(cancel_mono F'.m).1 <| by simp
#align category_theory.limits.is_image.fac_lift CategoryTheory.Limits.IsImage.fac_lift
variable (f)
/-- The trivial factorisation of a monomorphism satisfies the universal property. -/
@[simps]
def self [Mono f] : IsImage (MonoFactorisation.self f) where lift F' := F'.e
#align category_theory.limits.is_image.self CategoryTheory.Limits.IsImage.self
instance [Mono f] : Inhabited (IsImage (MonoFactorisation.self f)) :=
⟨self f⟩
variable {f}
-- TODO this is another good candidate for a future `UniqueUpToCanonicalIso`.
/-- Two factorisations through monomorphisms satisfying the universal property
must factor through isomorphic objects. -/
@[simps]
def isoExt {F F' : MonoFactorisation f} (hF : IsImage F) (hF' : IsImage F') :
F.I ≅ F'.I where
hom := hF.lift F'
inv := hF'.lift F
hom_inv_id := (cancel_mono F.m).1 (by simp)
inv_hom_id := (cancel_mono F'.m).1 (by simp)
#align category_theory.limits.is_image.iso_ext CategoryTheory.Limits.IsImage.isoExt
variable {F F' : MonoFactorisation f} (hF : IsImage F) (hF' : IsImage F')
| Mathlib/CategoryTheory/Limits/Shapes/Images.lean | 218 | 218 | theorem isoExt_hom_m : (isoExt hF hF').hom ≫ F'.m = F.m := by | simp
|
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