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/- 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, Jeremy Avigad -/ import Mathlib.Data.Set.Finite.Basic import Mathlib.Data.Set.Finite.Range import Mathlib.Data.Set.Lattice import Mathlib.Topology.Defs.Filter /-! # Openness and closedness of a set This file provides lemmas relating to the predicates `IsOpen` and `IsClosed` of a set endowed with a topology. ## Implementation notes Topology in mathlib heavily uses filters (even more than in Bourbaki). See explanations in <https://leanprover-community.github.io/theories/topology.html>. ## References * [N. Bourbaki, *General Topology*][bourbaki1966] * [I. M. James, *Topologies and Uniformities*][james1999] ## Tags topological space -/ open Set Filter Topology universe u v /-- A constructor for topologies by specifying the closed sets, and showing that they satisfy the appropriate conditions. -/ def TopologicalSpace.ofClosed {X : Type u} (T : Set (Set X)) (empty_mem : ∅ ∈ T) (sInter_mem : ∀ A, A ⊆ T → ⋂₀ A ∈ T) (union_mem : ∀ A, A ∈ T → ∀ B, B ∈ T → A ∪ B ∈ T) : TopologicalSpace X where IsOpen X := Xᶜ ∈ T isOpen_univ := by simp [empty_mem] isOpen_inter s t hs ht := by simpa only [compl_inter] using union_mem sᶜ hs tᶜ ht isOpen_sUnion s hs := by simp only [Set.compl_sUnion] exact sInter_mem (compl '' s) fun z ⟨y, hy, hz⟩ => hz ▸ hs y hy section TopologicalSpace variable {X : Type u} {ι : Sort v} {α : Type*} {x : X} {s s₁ s₂ t : Set X} {p p₁ p₂ : X → Prop} lemma isOpen_mk {p h₁ h₂ h₃} : IsOpen[⟨p, h₁, h₂, h₃⟩] s ↔ p s := Iff.rfl @[ext (iff := false)] protected theorem TopologicalSpace.ext : ∀ {f g : TopologicalSpace X}, IsOpen[f] = IsOpen[g] → f = g | ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, rfl => rfl protected theorem TopologicalSpace.ext_iff {t t' : TopologicalSpace X} : t = t' ↔ ∀ s, IsOpen[t] s ↔ IsOpen[t'] s := ⟨fun h _ => h ▸ Iff.rfl, fun h => by ext; exact h _⟩ theorem isOpen_fold {t : TopologicalSpace X} : t.IsOpen s = IsOpen[t] s := rfl variable [TopologicalSpace X] theorem isOpen_iUnion {f : ι → Set X} (h : ∀ i, IsOpen (f i)) : IsOpen (⋃ i, f i) := isOpen_sUnion (forall_mem_range.2 h) theorem isOpen_biUnion {s : Set α} {f : α → Set X} (h : ∀ i ∈ s, IsOpen (f i)) : IsOpen (⋃ i ∈ s, f i) := isOpen_iUnion fun i => isOpen_iUnion fun hi => h i hi theorem IsOpen.union (h₁ : IsOpen s₁) (h₂ : IsOpen s₂) : IsOpen (s₁ ∪ s₂) := by rw [union_eq_iUnion]; exact isOpen_iUnion (Bool.forall_bool.2 ⟨h₂, h₁⟩) lemma isOpen_iff_of_cover {f : α → Set X} (ho : ∀ i, IsOpen (f i)) (hU : (⋃ i, f i) = univ) : IsOpen s ↔ ∀ i, IsOpen (f i ∩ s) := by refine ⟨fun h i ↦ (ho i).inter h, fun h ↦ ?_⟩ rw [← s.inter_univ, inter_comm, ← hU, iUnion_inter] exact isOpen_iUnion fun i ↦ h i @[simp] theorem isOpen_empty : IsOpen (∅ : Set X) := by rw [← sUnion_empty]; exact isOpen_sUnion fun a => False.elim theorem Set.Finite.isOpen_sInter {s : Set (Set X)} (hs : s.Finite) (h : ∀ t ∈ s, IsOpen t) : IsOpen (⋂₀ s) := by induction s, hs using Set.Finite.induction_on with | empty => rw [sInter_empty]; exact isOpen_univ | insert _ _ ih => simp only [sInter_insert, forall_mem_insert] at h ⊢ exact h.1.inter (ih h.2) theorem Set.Finite.isOpen_biInter {s : Set α} {f : α → Set X} (hs : s.Finite) (h : ∀ i ∈ s, IsOpen (f i)) : IsOpen (⋂ i ∈ s, f i) := sInter_image f s ▸ (hs.image _).isOpen_sInter (forall_mem_image.2 h) theorem isOpen_iInter_of_finite [Finite ι] {s : ι → Set X} (h : ∀ i, IsOpen (s i)) : IsOpen (⋂ i, s i) := (finite_range _).isOpen_sInter (forall_mem_range.2 h) theorem isOpen_biInter_finset {s : Finset α} {f : α → Set X} (h : ∀ i ∈ s, IsOpen (f i)) : IsOpen (⋂ i ∈ s, f i) := s.finite_toSet.isOpen_biInter h @[simp] theorem isOpen_const {p : Prop} : IsOpen { _x : X | p } := by by_cases p <;> simp [*] theorem IsOpen.and : IsOpen { x | p₁ x } → IsOpen { x | p₂ x } → IsOpen { x | p₁ x ∧ p₂ x } := IsOpen.inter @[simp] theorem isOpen_compl_iff : IsOpen sᶜ ↔ IsClosed s := ⟨fun h => ⟨h⟩, fun h => h.isOpen_compl⟩ theorem TopologicalSpace.ext_iff_isClosed {X} {t₁ t₂ : TopologicalSpace X} : t₁ = t₂ ↔ ∀ s, IsClosed[t₁] s ↔ IsClosed[t₂] s := by rw [TopologicalSpace.ext_iff, compl_surjective.forall] simp only [@isOpen_compl_iff _ _ t₁, @isOpen_compl_iff _ _ t₂] alias ⟨_, TopologicalSpace.ext_isClosed⟩ := TopologicalSpace.ext_iff_isClosed theorem isClosed_const {p : Prop} : IsClosed { _x : X | p } := ⟨isOpen_const (p := ¬p)⟩ @[simp] theorem isClosed_empty : IsClosed (∅ : Set X) := isClosed_const @[simp] theorem isClosed_univ : IsClosed (univ : Set X) := isClosed_const lemma IsOpen.isLocallyClosed (hs : IsOpen s) : IsLocallyClosed s := ⟨_, _, hs, isClosed_univ, (inter_univ _).symm⟩ lemma IsClosed.isLocallyClosed (hs : IsClosed s) : IsLocallyClosed s := ⟨_, _, isOpen_univ, hs, (univ_inter _).symm⟩ theorem IsClosed.union : IsClosed s₁ → IsClosed s₂ → IsClosed (s₁ ∪ s₂) := by simpa only [← isOpen_compl_iff, compl_union] using IsOpen.inter theorem isClosed_sInter {s : Set (Set X)} : (∀ t ∈ s, IsClosed t) → IsClosed (⋂₀ s) := by simpa only [← isOpen_compl_iff, compl_sInter, sUnion_image] using isOpen_biUnion theorem isClosed_iInter {f : ι → Set X} (h : ∀ i, IsClosed (f i)) : IsClosed (⋂ i, f i) := isClosed_sInter <| forall_mem_range.2 h theorem isClosed_biInter {s : Set α} {f : α → Set X} (h : ∀ i ∈ s, IsClosed (f i)) : IsClosed (⋂ i ∈ s, f i) := isClosed_iInter fun i => isClosed_iInter <| h i @[simp] theorem isClosed_compl_iff {s : Set X} : IsClosed sᶜ ↔ IsOpen s := by rw [← isOpen_compl_iff, compl_compl] alias ⟨_, IsOpen.isClosed_compl⟩ := isClosed_compl_iff theorem IsOpen.sdiff (h₁ : IsOpen s) (h₂ : IsClosed t) : IsOpen (s \ t) := IsOpen.inter h₁ h₂.isOpen_compl theorem IsClosed.inter (h₁ : IsClosed s₁) (h₂ : IsClosed s₂) : IsClosed (s₁ ∩ s₂) := by rw [← isOpen_compl_iff] at * rw [compl_inter] exact IsOpen.union h₁ h₂ theorem IsClosed.sdiff (h₁ : IsClosed s) (h₂ : IsOpen t) : IsClosed (s \ t) := IsClosed.inter h₁ (isClosed_compl_iff.mpr h₂) theorem Set.Finite.isClosed_biUnion {s : Set α} {f : α → Set X} (hs : s.Finite) (h : ∀ i ∈ s, IsClosed (f i)) : IsClosed (⋃ i ∈ s, f i) := by simp only [← isOpen_compl_iff, compl_iUnion] at * exact hs.isOpen_biInter h lemma isClosed_biUnion_finset {s : Finset α} {f : α → Set X} (h : ∀ i ∈ s, IsClosed (f i)) : IsClosed (⋃ i ∈ s, f i) := s.finite_toSet.isClosed_biUnion h theorem isClosed_iUnion_of_finite [Finite ι] {s : ι → Set X} (h : ∀ i, IsClosed (s i)) : IsClosed (⋃ i, s i) := by simp only [← isOpen_compl_iff, compl_iUnion] at * exact isOpen_iInter_of_finite h theorem isClosed_imp {p q : X → Prop} (hp : IsOpen { x | p x }) (hq : IsClosed { x | q x }) : IsClosed { x | p x → q x } := by simpa only [imp_iff_not_or] using hp.isClosed_compl.union hq theorem IsClosed.not : IsClosed { a | p a } → IsOpen { a | ¬p a } := isOpen_compl_iff.mpr /-! ### Limits of filters in topological spaces In this section we define functions that return a limit of a filter (or of a function along a filter), if it exists, and a random point otherwise. These functions are rarely used in Mathlib, most of the theorems are written using `Filter.Tendsto`. One of the reasons is that `Filter.limUnder f g = x` is not equivalent to `Filter.Tendsto g f (𝓝 x)` unless the codomain is a Hausdorff space and `g` has a limit along `f`. -/ section lim /-- If a filter `f` is majorated by some `𝓝 x`, then it is majorated by `𝓝 (Filter.lim f)`. We formulate this lemma with a `[Nonempty X]` argument of `lim` derived from `h` to make it useful for types without a `[Nonempty X]` instance. Because of the built-in proof irrelevance, Lean will unify this instance with any other instance. -/ theorem le_nhds_lim {f : Filter X} (h : ∃ x, f ≤ 𝓝 x) : f ≤ 𝓝 (@lim _ _ (nonempty_of_exists h) f) := Classical.epsilon_spec h /-- If `g` tends to some `𝓝 x` along `f`, then it tends to `𝓝 (Filter.limUnder f g)`. We formulate this lemma with a `[Nonempty X]` argument of `lim` derived from `h` to make it useful for types without a `[Nonempty X]` instance. Because of the built-in proof irrelevance, Lean will unify this instance with any other instance. -/ theorem tendsto_nhds_limUnder {f : Filter α} {g : α → X} (h : ∃ x, Tendsto g f (𝓝 x)) : Tendsto g f (𝓝 (@limUnder _ _ _ (nonempty_of_exists h) f g)) := le_nhds_lim h theorem limUnder_of_not_tendsto [hX : Nonempty X] {f : Filter α} {g : α → X} (h : ¬ ∃ x, Tendsto g f (𝓝 x)) : limUnder f g = Classical.choice hX := by simp_rw [Tendsto] at h simp_rw [limUnder, lim, Classical.epsilon, Classical.strongIndefiniteDescription, dif_neg h] end lim end TopologicalSpace
Mathlib/Topology/Basic.lean
351
359
/- Copyright (c) 2020 Kyle Miller. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kyle Miller -/ import Mathlib.Algebra.BigOperators.Ring.Finset import Mathlib.Combinatorics.SimpleGraph.Dart import Mathlib.Combinatorics.SimpleGraph.Finite import Mathlib.Data.ZMod.Basic /-! # Degree-sum formula and handshaking lemma The degree-sum formula is that the sum of the degrees of the vertices in a finite graph is equal to twice the number of edges. The handshaking lemma, a corollary, is that the number of odd-degree vertices is even. ## Main definitions - `SimpleGraph.sum_degrees_eq_twice_card_edges` is the degree-sum formula. - `SimpleGraph.even_card_odd_degree_vertices` is the handshaking lemma. - `SimpleGraph.odd_card_odd_degree_vertices_ne` is that the number of odd-degree vertices different from a given odd-degree vertex is odd. - `SimpleGraph.exists_ne_odd_degree_of_exists_odd_degree` is that the existence of an odd-degree vertex implies the existence of another one. ## Implementation notes We give a combinatorial proof by using the facts that (1) the map from darts to vertices is such that each fiber has cardinality the degree of the corresponding vertex and that (2) the map from darts to edges is 2-to-1. ## Tags simple graphs, sums, degree-sum formula, handshaking lemma -/ assert_not_exists Field TwoSidedIdeal open Finset namespace SimpleGraph universe u variable {V : Type u} (G : SimpleGraph V) section DegreeSum variable [Fintype V] [DecidableRel G.Adj] theorem dart_fst_fiber [DecidableEq V] (v : V) : ({d : G.Dart | d.fst = v} : Finset _) = univ.image (G.dartOfNeighborSet v) := by ext d simp only [mem_image, true_and, mem_filter, SetCoe.exists, mem_univ, exists_prop_of_true] constructor · rintro rfl exact ⟨_, d.adj, by ext <;> rfl⟩ · rintro ⟨e, he, rfl⟩ rfl theorem dart_fst_fiber_card_eq_degree [DecidableEq V] (v : V) : #{d : G.Dart | d.fst = v} = G.degree v := by simpa only [dart_fst_fiber, Finset.card_univ, card_neighborSet_eq_degree] using card_image_of_injective univ (G.dartOfNeighborSet_injective v)
theorem dart_card_eq_sum_degrees : Fintype.card G.Dart = ∑ v, G.degree v := by haveI := Classical.decEq V simp only [← card_univ, ← dart_fst_fiber_card_eq_degree] exact card_eq_sum_card_fiberwise (by simp)
Mathlib/Combinatorics/SimpleGraph/DegreeSum.lean
67
70
/- Copyright (c) 2020 Kevin Buzzard, Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kevin Buzzard, Bhavik Mehta -/ import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Equalizers import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Products import Mathlib.CategoryTheory.Limits.Yoneda import Mathlib.CategoryTheory.Preadditive.FunctorCategory import Mathlib.CategoryTheory.Sites.SheafOfTypes import Mathlib.CategoryTheory.Sites.EqualizerSheafCondition import Mathlib.CategoryTheory.Limits.Constructions.EpiMono /-! # Sheaves taking values in a category If C is a category with a Grothendieck topology, we define the notion of a sheaf taking values in an arbitrary category `A`. We follow the definition in https://stacks.math.columbia.edu/tag/00VR, noting that the presheaf of sets "defined above" can be seen in the comments between tags 00VQ and 00VR on the page <https://stacks.math.columbia.edu/tag/00VL>. The advantage of this definition is that we need no assumptions whatsoever on `A` other than the assumption that the morphisms in `C` and `A` live in the same universe. * An `A`-valued presheaf `P : Cᵒᵖ ⥤ A` is defined to be a sheaf (for the topology `J`) iff for every `E : A`, the type-valued presheaves of sets given by sending `U : Cᵒᵖ` to `Hom_{A}(E, P U)` are all sheaves of sets, see `CategoryTheory.Presheaf.IsSheaf`. * When `A = Type`, this recovers the basic definition of sheaves of sets, see `CategoryTheory.isSheaf_iff_isSheaf_of_type`. * A alternate definition in terms of limits, unconditionally equivalent to the original one: see `CategoryTheory.Presheaf.isSheaf_iff_isLimit`. * An alternate definition when `C` is small, has pullbacks and `A` has products is given by an equalizer condition `CategoryTheory.Presheaf.IsSheaf'`. This is equivalent to the earlier definition, shown in `CategoryTheory.Presheaf.isSheaf_iff_isSheaf'`. * When `A = Type`, this is *definitionally* equal to the equalizer condition for presieves in `CategoryTheory.Sites.SheafOfTypes`. * When `A` has limits and there is a functor `s : A ⥤ Type` which is faithful, reflects isomorphisms and preserves limits, then `P : Cᵒᵖ ⥤ A` is a sheaf iff the underlying presheaf of types `P ⋙ s : Cᵒᵖ ⥤ Type` is a sheaf (`CategoryTheory.Presheaf.isSheaf_iff_isSheaf_forget`). Cf https://stacks.math.columbia.edu/tag/0073, which is a weaker version of this statement (it's only over spaces, not sites) and https://stacks.math.columbia.edu/tag/00YR (a), which additionally assumes filtered colimits. ## Implementation notes Occasionally we need to take a limit in `A` of a collection of morphisms of `C` indexed by a collection of objects in `C`. This turns out to force the morphisms of `A` to be in a sufficiently large universe. Rather than use `UnivLE` we prove some results for a category `A'` instead, whose morphism universe of `A'` is defined to be `max u₁ v₁`, where `u₁, v₁` are the universes for `C`. Perhaps after we get better at handling universe inequalities this can be changed. -/ universe w v₁ v₂ v₃ u₁ u₂ u₃ noncomputable section namespace CategoryTheory open Opposite CategoryTheory Category Limits Sieve namespace Presheaf variable {C : Type u₁} [Category.{v₁} C] variable {A : Type u₂} [Category.{v₂} A] variable (J : GrothendieckTopology C) -- We follow https://stacks.math.columbia.edu/tag/00VL definition 00VR /-- A sheaf of A is a presheaf P : Cᵒᵖ => A such that for every E : A, the presheaf of types given by sending U : C to Hom_{A}(E, P U) is a sheaf of types. -/ @[stacks 00VR] def IsSheaf (P : Cᵒᵖ ⥤ A) : Prop := ∀ E : A, Presieve.IsSheaf J (P ⋙ coyoneda.obj (op E)) /-- Condition that a presheaf with values in a concrete category is separated for a Grothendieck topology. -/ def IsSeparated (P : Cᵒᵖ ⥤ A) {FA : A → A → Type*} {CA : A → Type*} [∀ X Y, FunLike (FA X Y) (CA X) (CA Y)] [ConcreteCategory A FA] : Prop := ∀ (X : C) (S : Sieve X) (_ : S ∈ J X) (x y : ToType (P.obj (op X))), (∀ (Y : C) (f : Y ⟶ X) (_ : S f), P.map f.op x = P.map f.op y) → x = y section LimitSheafCondition open Presieve Presieve.FamilyOfElements Limits variable (P : Cᵒᵖ ⥤ A) {X : C} (S : Sieve X) (R : Presieve X) (E : Aᵒᵖ) /-- Given a sieve `S` on `X : C`, a presheaf `P : Cᵒᵖ ⥤ A`, and an object `E` of `A`, the cones over the natural diagram `S.arrows.diagram.op ⋙ P` associated to `S` and `P` with cone point `E` are in 1-1 correspondence with sieve_compatible family of elements for the sieve `S` and the presheaf of types `Hom (E, P -)`. -/ def conesEquivSieveCompatibleFamily : (S.arrows.diagram.op ⋙ P).cones.obj E ≃ { x : FamilyOfElements (P ⋙ coyoneda.obj E) (S : Presieve X) // x.SieveCompatible } where toFun π := ⟨fun _ f h => π.app (op ⟨Over.mk f, h⟩), fun X Y f g hf => by apply (id_comp _).symm.trans dsimp exact π.naturality (Quiver.Hom.op (Over.homMk _ (by rfl)))⟩ invFun x := { app := fun f => x.1 f.unop.1.hom f.unop.2 naturality := fun f f' g => by refine Eq.trans ?_ (x.2 f.unop.1.hom g.unop.left f.unop.2) dsimp rw [id_comp] convert rfl rw [Over.w] } left_inv _ := rfl right_inv _ := rfl variable {P S E} variable {x : FamilyOfElements (P ⋙ coyoneda.obj E) S.arrows} (hx : SieveCompatible x) /-- The cone corresponding to a sieve_compatible family of elements, dot notation enabled. -/ @[simp] def _root_.CategoryTheory.Presieve.FamilyOfElements.SieveCompatible.cone : Cone (S.arrows.diagram.op ⋙ P) where pt := E.unop π := (conesEquivSieveCompatibleFamily P S E).invFun ⟨x, hx⟩ /-- Cone morphisms from the cone corresponding to a sieve_compatible family to the natural cone associated to a sieve `S` and a presheaf `P` are in 1-1 correspondence with amalgamations of the family. -/ def homEquivAmalgamation : (hx.cone ⟶ P.mapCone S.arrows.cocone.op) ≃ { t // x.IsAmalgamation t } where toFun l := ⟨l.hom, fun _ f hf => l.w (op ⟨Over.mk f, hf⟩)⟩ invFun t := ⟨t.1, fun f => t.2 f.unop.1.hom f.unop.2⟩ left_inv _ := rfl right_inv _ := rfl variable (P S) /-- Given sieve `S` and presheaf `P : Cᵒᵖ ⥤ A`, their natural associated cone is a limit cone iff `Hom (E, P -)` is a sheaf of types for the sieve `S` and all `E : A`. -/ theorem isLimit_iff_isSheafFor : Nonempty (IsLimit (P.mapCone S.arrows.cocone.op)) ↔ ∀ E : Aᵒᵖ, IsSheafFor (P ⋙ coyoneda.obj E) S.arrows := by dsimp [IsSheafFor]; simp_rw [compatible_iff_sieveCompatible] rw [((Cone.isLimitEquivIsTerminal _).trans (isTerminalEquivUnique _ _)).nonempty_congr] rw [Classical.nonempty_pi]; constructor · intro hu E x hx specialize hu hx.cone rw [(homEquivAmalgamation hx).uniqueCongr.nonempty_congr] at hu exact (unique_subtype_iff_existsUnique _).1 hu · rintro h ⟨E, π⟩ let eqv := conesEquivSieveCompatibleFamily P S (op E) rw [← eqv.left_inv π] erw [(homEquivAmalgamation (eqv π).2).uniqueCongr.nonempty_congr] rw [unique_subtype_iff_existsUnique] exact h _ _ (eqv π).2 /-- Given sieve `S` and presheaf `P : Cᵒᵖ ⥤ A`, their natural associated cone admits at most one morphism from every cone in the same category (i.e. over the same diagram), iff `Hom (E, P -)`is separated for the sieve `S` and all `E : A`. -/ theorem subsingleton_iff_isSeparatedFor : (∀ c, Subsingleton (c ⟶ P.mapCone S.arrows.cocone.op)) ↔ ∀ E : Aᵒᵖ, IsSeparatedFor (P ⋙ coyoneda.obj E) S.arrows := by constructor · intro hs E x t₁ t₂ h₁ h₂ have hx := is_compatible_of_exists_amalgamation x ⟨t₁, h₁⟩ rw [compatible_iff_sieveCompatible] at hx specialize hs hx.cone rcases hs with ⟨hs⟩ simpa only [Subtype.mk.injEq] using (show Subtype.mk t₁ h₁ = ⟨t₂, h₂⟩ from (homEquivAmalgamation hx).symm.injective (hs _ _)) · rintro h ⟨E, π⟩ let eqv := conesEquivSieveCompatibleFamily P S (op E) constructor rw [← eqv.left_inv π] intro f₁ f₂ let eqv' := homEquivAmalgamation (eqv π).2 apply eqv'.injective ext apply h _ (eqv π).1 <;> exact (eqv' _).2 /-- A presheaf `P` is a sheaf for the Grothendieck topology `J` iff for every covering sieve `S` of `J`, the natural cone associated to `P` and `S` is a limit cone. -/ theorem isSheaf_iff_isLimit : IsSheaf J P ↔ ∀ ⦃X : C⦄ (S : Sieve X), S ∈ J X → Nonempty (IsLimit (P.mapCone S.arrows.cocone.op)) := ⟨fun h _ S hS => (isLimit_iff_isSheafFor P S).2 fun E => h E.unop S hS, fun h E _ S hS => (isLimit_iff_isSheafFor P S).1 (h S hS) (op E)⟩ /-- A presheaf `P` is separated for the Grothendieck topology `J` iff for every covering sieve `S` of `J`, the natural cone associated to `P` and `S` admits at most one morphism from every cone in the same category. -/ theorem isSeparated_iff_subsingleton : (∀ E : A, Presieve.IsSeparated J (P ⋙ coyoneda.obj (op E))) ↔ ∀ ⦃X : C⦄ (S : Sieve X), S ∈ J X → ∀ c, Subsingleton (c ⟶ P.mapCone S.arrows.cocone.op) := ⟨fun h _ S hS => (subsingleton_iff_isSeparatedFor P S).2 fun E => h E.unop S hS, fun h E _ S hS => (subsingleton_iff_isSeparatedFor P S).1 (h S hS) (op E)⟩ /-- Given presieve `R` and presheaf `P : Cᵒᵖ ⥤ A`, the natural cone associated to `P` and the sieve `Sieve.generate R` generated by `R` is a limit cone iff `Hom (E, P -)` is a sheaf of types for the presieve `R` and all `E : A`. -/ theorem isLimit_iff_isSheafFor_presieve : Nonempty (IsLimit (P.mapCone (generate R).arrows.cocone.op)) ↔ ∀ E : Aᵒᵖ, IsSheafFor (P ⋙ coyoneda.obj E) R := (isLimit_iff_isSheafFor P _).trans (forall_congr' fun _ => (isSheafFor_iff_generate _).symm) /-- A presheaf `P` is a sheaf for the Grothendieck topology generated by a pretopology `K` iff for every covering presieve `R` of `K`, the natural cone associated to `P` and `Sieve.generate R` is a limit cone. -/ theorem isSheaf_iff_isLimit_pretopology [HasPullbacks C] (K : Pretopology C) : IsSheaf (K.toGrothendieck C) P ↔ ∀ ⦃X : C⦄ (R : Presieve X), R ∈ K X → Nonempty (IsLimit (P.mapCone (generate R).arrows.cocone.op)) := by dsimp [IsSheaf] simp_rw [isSheaf_pretopology] exact ⟨fun h X R hR => (isLimit_iff_isSheafFor_presieve P R).2 fun E => h E.unop R hR, fun h E X R hR => (isLimit_iff_isSheafFor_presieve P R).1 (h R hR) (op E)⟩ end LimitSheafCondition variable {J} /-- This is a wrapper around `Presieve.IsSheafFor.amalgamate` to be used below. If `P`s a sheaf, `S` is a cover of `X`, and `x` is a collection of morphisms from `E` to `P` evaluated at terms in the cover which are compatible, then we can amalgamate the `x`s to obtain a single morphism `E ⟶ P.obj (op X)`. -/ def IsSheaf.amalgamate {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) (S : J.Cover X) (x : ∀ I : S.Arrow, E ⟶ P.obj (op I.Y)) (hx : ∀ ⦃I₁ I₂ : S.Arrow⦄ (r : I₁.Relation I₂), x I₁ ≫ P.map r.g₁.op = x I₂ ≫ P.map r.g₂.op) : E ⟶ P.obj (op X) := (hP _ _ S.condition).amalgamate (fun Y f hf => x ⟨Y, f, hf⟩) fun _ _ _ _ _ _ _ h₁ h₂ w => @hx { hf := h₁, .. } { hf := h₂, .. } { w := w, .. } @[reassoc (attr := simp)] theorem IsSheaf.amalgamate_map {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) (S : J.Cover X) (x : ∀ I : S.Arrow, E ⟶ P.obj (op I.Y)) (hx : ∀ ⦃I₁ I₂ : S.Arrow⦄ (r : I₁.Relation I₂), x I₁ ≫ P.map r.g₁.op = x I₂ ≫ P.map r.g₂.op) (I : S.Arrow) : hP.amalgamate S x hx ≫ P.map I.f.op = x _ := by apply (hP _ _ S.condition).valid_glue theorem IsSheaf.hom_ext {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) (S : J.Cover X) (e₁ e₂ : E ⟶ P.obj (op X)) (h : ∀ I : S.Arrow, e₁ ≫ P.map I.f.op = e₂ ≫ P.map I.f.op) : e₁ = e₂ := (hP _ _ S.condition).isSeparatedFor.ext fun Y f hf => h ⟨Y, f, hf⟩ lemma IsSheaf.hom_ext_ofArrows {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) {I : Type*} {S : C} {X : I → C} (f : ∀ i, X i ⟶ S) (hf : Sieve.ofArrows _ f ∈ J S) {E : A} {x y : E ⟶ P.obj (op S)} (h : ∀ i, x ≫ P.map (f i).op = y ≫ P.map (f i).op) : x = y := by apply hP.hom_ext ⟨_, hf⟩ rintro ⟨Z, _, _, g, _, ⟨i⟩, rfl⟩ dsimp rw [P.map_comp, reassoc_of% (h i)] section variable {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) {I : Type*} {S : C} {X : I → C} (f : ∀ i, X i ⟶ S) (hf : Sieve.ofArrows _ f ∈ J S) {E : A} (x : ∀ i, E ⟶ P.obj (op (X i))) (hx : ∀ ⦃W : C⦄ ⦃i j : I⦄ (a : W ⟶ X i) (b : W ⟶ X j), a ≫ f i = b ≫ f j → x i ≫ P.map a.op = x j ≫ P.map b.op) include hP hf hx lemma IsSheaf.existsUnique_amalgamation_ofArrows : ∃! (g : E ⟶ P.obj (op S)), ∀ (i : I), g ≫ P.map (f i).op = x i := (Presieve.isSheafFor_arrows_iff _ _).1 ((Presieve.isSheafFor_iff_generate _).2 (hP E _ hf)) x (fun _ _ _ _ _ w => hx _ _ w) @[deprecated (since := "2024-12-17")] alias IsSheaf.exists_unique_amalgamation_ofArrows := IsSheaf.existsUnique_amalgamation_ofArrows /-- If `P : Cᵒᵖ ⥤ A` is a sheaf and `f i : X i ⟶ S` is a covering family, then a morphism `E ⟶ P.obj (op S)` can be constructed from a compatible family of morphisms `x : E ⟶ P.obj (op (X i))`. -/ def IsSheaf.amalgamateOfArrows : E ⟶ P.obj (op S) := (hP.existsUnique_amalgamation_ofArrows f hf x hx).choose @[reassoc (attr := simp)] lemma IsSheaf.amalgamateOfArrows_map (i : I) : hP.amalgamateOfArrows f hf x hx ≫ P.map (f i).op = x i := (hP.existsUnique_amalgamation_ofArrows f hf x hx).choose_spec.1 i end theorem isSheaf_of_iso_iff {P P' : Cᵒᵖ ⥤ A} (e : P ≅ P') : IsSheaf J P ↔ IsSheaf J P' := forall_congr' fun _ => ⟨Presieve.isSheaf_iso J (isoWhiskerRight e _), Presieve.isSheaf_iso J (isoWhiskerRight e.symm _)⟩ variable (J) theorem isSheaf_of_isTerminal {X : A} (hX : IsTerminal X) : Presheaf.IsSheaf J ((CategoryTheory.Functor.const _).obj X) := fun _ _ _ _ _ _ => ⟨hX.from _, fun _ _ _ => hX.hom_ext _ _, fun _ _ => hX.hom_ext _ _⟩ end Presheaf variable {C : Type u₁} [Category.{v₁} C] variable (J : GrothendieckTopology C) variable (A : Type u₂) [Category.{v₂} A] /-- The category of sheaves taking values in `A` on a grothendieck topology. -/ structure Sheaf where /-- the underlying presheaf -/ val : Cᵒᵖ ⥤ A /-- the condition that the presheaf is a sheaf -/ cond : Presheaf.IsSheaf J val namespace Sheaf variable {J A} /-- Morphisms between sheaves are just morphisms of presheaves. -/ @[ext] structure Hom (X Y : Sheaf J A) where /-- a morphism between the underlying presheaves -/ val : X.val ⟶ Y.val @[simps id_val comp_val] instance instCategorySheaf : Category (Sheaf J A) where Hom := Hom id _ := ⟨𝟙 _⟩ comp f g := ⟨f.val ≫ g.val⟩ id_comp _ := Hom.ext <| id_comp _ comp_id _ := Hom.ext <| comp_id _ assoc _ _ _ := Hom.ext <| assoc _ _ _ -- Let's make the inhabited linter happy.../sips instance (X : Sheaf J A) : Inhabited (Hom X X) := ⟨𝟙 X⟩ @[ext] lemma hom_ext {X Y : Sheaf J A} (x y : X ⟶ Y) (h : x.val = y.val) : x = y := Sheaf.Hom.ext h end Sheaf /-- The inclusion functor from sheaves to presheaves. -/ @[simps] def sheafToPresheaf : Sheaf J A ⥤ Cᵒᵖ ⥤ A where obj := Sheaf.val map f := f.val map_id _ := rfl map_comp _ _ := rfl /-- The sections of a sheaf (i.e. evaluation as a presheaf on `C`). -/ abbrev sheafSections : Cᵒᵖ ⥤ Sheaf J A ⥤ A := (sheafToPresheaf J A).flip /-- The sheaf sections functor on `X` is given by evaluation of presheaves on `X`. -/ @[simps!] def sheafSectionsNatIsoEvaluation {X : C} : (sheafSections J A).obj (op X) ≅ sheafToPresheaf J A ⋙ (evaluation _ _).obj (op X) := NatIso.ofComponents (fun _ ↦ Iso.refl _) /-- The functor `Sheaf J A ⥤ Cᵒᵖ ⥤ A` is fully faithful. -/ @[simps] def fullyFaithfulSheafToPresheaf : (sheafToPresheaf J A).FullyFaithful where preimage f := ⟨f⟩ variable {J A} in /-- The bijection `(X ⟶ Y) ≃ (X.val ⟶ Y.val)` when `X` and `Y` are sheaves. -/ abbrev Sheaf.homEquiv {X Y : Sheaf J A} : (X ⟶ Y) ≃ (X.val ⟶ Y.val) := (fullyFaithfulSheafToPresheaf J A).homEquiv instance : (sheafToPresheaf J A).Full := (fullyFaithfulSheafToPresheaf J A).full instance : (sheafToPresheaf J A).Faithful := (fullyFaithfulSheafToPresheaf J A).faithful instance : (sheafToPresheaf J A).ReflectsIsomorphisms := (fullyFaithfulSheafToPresheaf J A).reflectsIsomorphisms /-- This is stated as a lemma to prevent class search from forming a loop since a sheaf morphism is monic if and only if it is monic as a presheaf morphism (under suitable assumption). -/ theorem Sheaf.Hom.mono_of_presheaf_mono {F G : Sheaf J A} (f : F ⟶ G) [h : Mono f.1] : Mono f := (sheafToPresheaf J A).mono_of_mono_map h instance Sheaf.Hom.epi_of_presheaf_epi {F G : Sheaf J A} (f : F ⟶ G) [h : Epi f.1] : Epi f := (sheafToPresheaf J A).epi_of_epi_map h theorem isSheaf_iff_isSheaf_of_type (P : Cᵒᵖ ⥤ Type w) : Presheaf.IsSheaf J P ↔ Presieve.IsSheaf J P := by constructor · intro hP refine Presieve.isSheaf_iso J ?_ (hP PUnit) exact isoWhiskerLeft _ Coyoneda.punitIso ≪≫ P.rightUnitor · intro hP X Y S hS z hz refine ⟨fun x => (hP S hS).amalgamate (fun Z f hf => z f hf x) ?_, ?_, ?_⟩ · intro Y₁ Y₂ Z g₁ g₂ f₁ f₂ hf₁ hf₂ h exact congr_fun (hz g₁ g₂ hf₁ hf₂ h) x · intro Z f hf funext x apply Presieve.IsSheafFor.valid_glue · intro y hy funext x apply (hP S hS).isSeparatedFor.ext intro Y' f hf rw [Presieve.IsSheafFor.valid_glue _ _ _ hf, ← hy _ hf] rfl /-- The sheaf of sections guaranteed by the sheaf condition. -/ @[simps] def sheafOver {A : Type u₂} [Category.{v₂} A] {J : GrothendieckTopology C} (ℱ : Sheaf J A) (E : A) : Sheaf J (Type _) where val := ℱ.val ⋙ coyoneda.obj (op E) cond := by rw [isSheaf_iff_isSheaf_of_type] exact ℱ.cond E variable {J} in lemma Presheaf.IsSheaf.isSheafFor {P : Cᵒᵖ ⥤ Type w} (hP : Presheaf.IsSheaf J P) {X : C} (S : Sieve X) (hS : S ∈ J X) : Presieve.IsSheafFor P S.arrows := by rw [isSheaf_iff_isSheaf_of_type] at hP exact hP S hS variable {A} in lemma Presheaf.isSheaf_bot (P : Cᵒᵖ ⥤ A) : IsSheaf ⊥ P := fun _ ↦ Presieve.isSheaf_bot /-- The category of sheaves on the bottom (trivial) Grothendieck topology is equivalent to the category of presheaves. -/ @[simps] def sheafBotEquivalence : Sheaf (⊥ : GrothendieckTopology C) A ≌ Cᵒᵖ ⥤ A where functor := sheafToPresheaf _ _ inverse := { obj := fun P => ⟨P, Presheaf.isSheaf_bot P⟩ map := fun f => ⟨f⟩ } unitIso := Iso.refl _ counitIso := Iso.refl _ instance : Inhabited (Sheaf (⊥ : GrothendieckTopology C) (Type w)) := ⟨(sheafBotEquivalence _).inverse.obj ((Functor.const _).obj default)⟩
variable {J} {A} /-- If the empty sieve is a cover of `X`, then `F(X)` is terminal. -/ def Sheaf.isTerminalOfBotCover (F : Sheaf J A) (X : C) (H : ⊥ ∈ J X) :
Mathlib/CategoryTheory/Sites/Sheaf.lean
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/- Copyright (c) 2022 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.AlgebraicGeometry.Morphisms.Constructors import Mathlib.RingTheory.LocalProperties.Basic import Mathlib.RingTheory.RingHom.Locally /-! # Properties of morphisms from properties of ring homs. We provide the basic framework for talking about properties of morphisms that come from properties of ring homs. For `P` a property of ring homs, we have two ways of defining a property of scheme morphisms: Let `f : X ⟶ Y`, - `targetAffineLocally (affineAnd P)`: the preimage of an affine open `U = Spec A` is affine (`= Spec B`) and `A ⟶ B` satisfies `P`. (in `Mathlib/AlgebraicGeometry/Morphisms/AffineAnd.lean`) - `affineLocally P`: For each pair of affine open `U = Spec A ⊆ X` and `V = Spec B ⊆ f ⁻¹' U`, the ring hom `A ⟶ B` satisfies `P`. For these notions to be well defined, we require `P` be a sufficient local property. For the former, `P` should be local on the source (`RingHom.RespectsIso P`, `RingHom.LocalizationPreserves P`, `RingHom.OfLocalizationSpan`), and `targetAffineLocally (affine_and P)` will be local on the target. For the latter `P` should be local on the target (`RingHom.PropertyIsLocal P`), and `affineLocally P` will be local on both the source and the target. We also provide the following interface: ## `HasRingHomProperty` `HasRingHomProperty P Q` is a type class asserting that `P` is local at the target and the source, and for `f : Spec B ⟶ Spec A`, it is equivalent to the ring hom property `Q` on `Γ(f)`. For `HasRingHomProperty P Q` and `f : X ⟶ Y`, we provide these API lemmas: - `AlgebraicGeometry.HasRingHomProperty.iff_appLE`: `P f` if and only if `Q (f.appLE U V _)` for all affine `U : Opens Y` and `V : Opens X`. - `AlgebraicGeometry.HasRingHomProperty.iff_of_source_openCover`: If `Y` is affine, `P f ↔ ∀ i, Q ((𝒰.map i ≫ f).appTop)` for an affine open cover `𝒰` of `X`. - `AlgebraicGeometry.HasRingHomProperty.iff_of_isAffine`: If `X` and `Y` are affine, then `P f ↔ Q (f.appTop)`. - `AlgebraicGeometry.HasRingHomProperty.Spec_iff`: `P (Spec.map φ) ↔ Q φ` - `AlgebraicGeometry.HasRingHomProperty.iff_of_iSup_eq_top`: If `Y` is affine, `P f ↔ ∀ i, Q (f.appLE ⊤ (U i) _)` for a family `U` of affine opens of `X`. - `AlgebraicGeometry.HasRingHomProperty.of_isOpenImmersion`: If `f` is an open immersion then `P f`. - `AlgebraicGeometry.HasRingHomProperty.isStableUnderBaseChange`: If `Q` is stable under base change, then so is `P`. We also provide the instances `P.IsMultiplicative`, `P.IsStableUnderComposition`, `IsLocalAtTarget P`, `IsLocalAtSource P`. -/ -- Explicit universe annotations were used in this file to improve performance https://github.com/leanprover-community/mathlib4/issues/12737 universe u open CategoryTheory Opposite TopologicalSpace CategoryTheory.Limits AlgebraicGeometry namespace RingHom variable (P : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop) theorem IsStableUnderBaseChange.pullback_fst_appTop (hP : IsStableUnderBaseChange P) (hP' : RespectsIso P) {X Y S : Scheme} [IsAffine X] [IsAffine Y] [IsAffine S] (f : X ⟶ S) (g : Y ⟶ S) (H : P g.appTop.hom) : P (pullback.fst f g).appTop.hom := by -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11224): change `rw` to `erw` erw [← PreservesPullback.iso_inv_fst AffineScheme.forgetToScheme (AffineScheme.ofHom f) (AffineScheme.ofHom g)] rw [Scheme.comp_appTop, CommRingCat.hom_comp, hP'.cancel_right_isIso, AffineScheme.forgetToScheme_map] have := congr_arg Quiver.Hom.unop (PreservesPullback.iso_hom_fst AffineScheme.Γ.rightOp (AffineScheme.ofHom f) (AffineScheme.ofHom g)) simp only [AffineScheme.Γ, Functor.rightOp_obj, Functor.comp_obj, Functor.op_obj, unop_comp, AffineScheme.forgetToScheme_obj, Scheme.Γ_obj, Functor.rightOp_map, Functor.comp_map, Functor.op_map, Quiver.Hom.unop_op, AffineScheme.forgetToScheme_map, Scheme.Γ_map] at this rw [← this, CommRingCat.hom_comp, hP'.cancel_right_isIso, ← pushoutIsoUnopPullback_inl_hom, CommRingCat.hom_comp, hP'.cancel_right_isIso]
exact hP.pushout_inl _ hP' _ _ H @[deprecated (since := "2024-11-23")] alias IsStableUnderBaseChange.pullback_fst_app_top := IsStableUnderBaseChange.pullback_fst_appTop end RingHom namespace AlgebraicGeometry section affineLocally variable (P : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop) /-- For `P` a property of ring homomorphisms, `sourceAffineLocally P` holds for `f : X ⟶ Y` whenever `P` holds for the restriction of `f` on every affine open subset of `X`. -/ def sourceAffineLocally : AffineTargetMorphismProperty := fun X _ f _ =>
Mathlib/AlgebraicGeometry/Morphisms/RingHomProperties.lean
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/- Copyright (c) 2019 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.GeomSum import Mathlib.Algebra.MvPolynomial.CommRing import Mathlib.Algebra.MvPolynomial.Equiv import Mathlib.Algebra.Polynomial.BigOperators import Mathlib.RingTheory.Noetherian.Basic /-! # Ring-theoretic supplement of Algebra.Polynomial. ## Main results * `MvPolynomial.isDomain`: If a ring is an integral domain, then so is its polynomial ring over finitely many variables. * `Polynomial.isNoetherianRing`: Hilbert basis theorem, that if a ring is noetherian then so is its polynomial ring. -/ noncomputable section open Polynomial open Finset universe u v w variable {R : Type u} {S : Type*} namespace Polynomial section Semiring variable [Semiring R] instance instCharP (p : ℕ) [h : CharP R p] : CharP R[X] p := let ⟨h⟩ := h ⟨fun n => by rw [← map_natCast C, ← C_0, C_inj, h]⟩ instance instExpChar (p : ℕ) [h : ExpChar R p] : ExpChar R[X] p := by cases h; exacts [ExpChar.zero, ExpChar.prime ‹_›] variable (R) /-- The `R`-submodule of `R[X]` consisting of polynomials of degree ≤ `n`. -/ def degreeLE (n : WithBot ℕ) : Submodule R R[X] := ⨅ k : ℕ, ⨅ _ : ↑k > n, LinearMap.ker (lcoeff R k) /-- The `R`-submodule of `R[X]` consisting of polynomials of degree < `n`. -/ def degreeLT (n : ℕ) : Submodule R R[X] := ⨅ k : ℕ, ⨅ (_ : k ≥ n), LinearMap.ker (lcoeff R k) variable {R} theorem mem_degreeLE {n : WithBot ℕ} {f : R[X]} : f ∈ degreeLE R n ↔ degree f ≤ n := by simp only [degreeLE, Submodule.mem_iInf, degree_le_iff_coeff_zero, LinearMap.mem_ker]; rfl @[mono] theorem degreeLE_mono {m n : WithBot ℕ} (H : m ≤ n) : degreeLE R m ≤ degreeLE R n := fun _ hf => mem_degreeLE.2 (le_trans (mem_degreeLE.1 hf) H) theorem degreeLE_eq_span_X_pow [DecidableEq R] {n : ℕ} : degreeLE R n = Submodule.span R ↑((Finset.range (n + 1)).image fun n => (X : R[X]) ^ n) := by apply le_antisymm · intro p hp replace hp := mem_degreeLE.1 hp rw [← Polynomial.sum_monomial_eq p, Polynomial.sum] refine Submodule.sum_mem _ fun k hk => ?_ have := WithBot.coe_le_coe.1 (Finset.sup_le_iff.1 hp k hk) rw [← C_mul_X_pow_eq_monomial, C_mul'] refine Submodule.smul_mem _ _ (Submodule.subset_span <| Finset.mem_coe.2 <| Finset.mem_image.2 ⟨_, Finset.mem_range.2 (Nat.lt_succ_of_le this), rfl⟩) rw [Submodule.span_le, Finset.coe_image, Set.image_subset_iff] intro k hk apply mem_degreeLE.2 exact (degree_X_pow_le _).trans (WithBot.coe_le_coe.2 <| Nat.le_of_lt_succ <| Finset.mem_range.1 hk) theorem mem_degreeLT {n : ℕ} {f : R[X]} : f ∈ degreeLT R n ↔ degree f < n := by rw [degreeLT, Submodule.mem_iInf] conv_lhs => intro i; rw [Submodule.mem_iInf] rw [degree, Finset.max_eq_sup_coe] rw [Finset.sup_lt_iff ?_] rotate_left · apply WithBot.bot_lt_coe conv_rhs => simp only [mem_support_iff] intro b rw [Nat.cast_withBot, WithBot.coe_lt_coe, lt_iff_not_le, Ne, not_imp_not] rfl @[mono] theorem degreeLT_mono {m n : ℕ} (H : m ≤ n) : degreeLT R m ≤ degreeLT R n := fun _ hf => mem_degreeLT.2 (lt_of_lt_of_le (mem_degreeLT.1 hf) <| WithBot.coe_le_coe.2 H) theorem degreeLT_eq_span_X_pow [DecidableEq R] {n : ℕ} : degreeLT R n = Submodule.span R ↑((Finset.range n).image fun n => X ^ n : Finset R[X]) := by apply le_antisymm · intro p hp replace hp := mem_degreeLT.1 hp rw [← Polynomial.sum_monomial_eq p, Polynomial.sum] refine Submodule.sum_mem _ fun k hk => ?_ have := WithBot.coe_lt_coe.1 ((Finset.sup_lt_iff <| WithBot.bot_lt_coe n).1 hp k hk) rw [← C_mul_X_pow_eq_monomial, C_mul'] refine Submodule.smul_mem _ _ (Submodule.subset_span <| Finset.mem_coe.2 <| Finset.mem_image.2 ⟨_, Finset.mem_range.2 this, rfl⟩) rw [Submodule.span_le, Finset.coe_image, Set.image_subset_iff] intro k hk apply mem_degreeLT.2 exact lt_of_le_of_lt (degree_X_pow_le _) (WithBot.coe_lt_coe.2 <| Finset.mem_range.1 hk) /-- The first `n` coefficients on `degreeLT n` form a linear equivalence with `Fin n → R`. -/ def degreeLTEquiv (R) [Semiring R] (n : ℕ) : degreeLT R n ≃ₗ[R] Fin n → R where toFun p n := (↑p : R[X]).coeff n invFun f := ⟨∑ i : Fin n, monomial i (f i), (degreeLT R n).sum_mem fun i _ => mem_degreeLT.mpr (lt_of_le_of_lt (degree_monomial_le i (f i)) (WithBot.coe_lt_coe.mpr i.is_lt))⟩ map_add' p q := by ext dsimp rw [coeff_add] map_smul' x p := by ext dsimp rw [coeff_smul] rfl left_inv := by rintro ⟨p, hp⟩ ext1 simp only [Submodule.coe_mk] by_cases hp0 : p = 0 · subst hp0 simp only [coeff_zero, LinearMap.map_zero, Finset.sum_const_zero] rw [mem_degreeLT, degree_eq_natDegree hp0, Nat.cast_lt] at hp conv_rhs => rw [p.as_sum_range' n hp, ← Fin.sum_univ_eq_sum_range] right_inv f := by ext i simp only [finset_sum_coeff, Submodule.coe_mk] rw [Finset.sum_eq_single i, coeff_monomial, if_pos rfl] · rintro j - hji rw [coeff_monomial, if_neg] rwa [← Fin.ext_iff] · intro h exact (h (Finset.mem_univ _)).elim theorem degreeLTEquiv_eq_zero_iff_eq_zero {n : ℕ} {p : R[X]} (hp : p ∈ degreeLT R n) : degreeLTEquiv _ _ ⟨p, hp⟩ = 0 ↔ p = 0 := by simp theorem eval_eq_sum_degreeLTEquiv {n : ℕ} {p : R[X]} (hp : p ∈ degreeLT R n) (x : R) : p.eval x = ∑ i, degreeLTEquiv _ _ ⟨p, hp⟩ i * x ^ (i : ℕ) := by simp_rw [eval_eq_sum] exact (sum_fin _ (by simp_rw [zero_mul, forall_const]) (mem_degreeLT.mp hp)).symm theorem degreeLT_succ_eq_degreeLE {n : ℕ} : degreeLT R (n + 1) = degreeLE R n := by ext x by_cases x_zero : x = 0 · simp_rw [x_zero, Submodule.zero_mem] · rw [mem_degreeLT, mem_degreeLE, ← natDegree_lt_iff_degree_lt (by rwa [ne_eq]), ← natDegree_le_iff_degree_le, Nat.lt_succ] /-- The equivalence between monic polynomials of degree `n` and polynomials of degree less than `n`, formed by adding a term `X ^ n`. -/ def monicEquivDegreeLT [Nontrivial R] (n : ℕ) : { p : R[X] // p.Monic ∧ p.natDegree = n } ≃ degreeLT R n where toFun p := ⟨p.1.eraseLead, by rcases p with ⟨p, hp, rfl⟩ simp only [mem_degreeLT] refine lt_of_lt_of_le ?_ degree_le_natDegree exact degree_eraseLead_lt (ne_zero_of_ne_zero_of_monic one_ne_zero hp)⟩ invFun := fun p => ⟨X^n + p.1, monic_X_pow_add (mem_degreeLT.1 p.2), by rw [natDegree_add_eq_left_of_degree_lt] · simp · simp [mem_degreeLT.1 p.2]⟩ left_inv := by rintro ⟨p, hp, rfl⟩ ext1 simp only conv_rhs => rw [← eraseLead_add_C_mul_X_pow p] simp [Monic.def.1 hp, add_comm] right_inv := by rintro ⟨p, hp⟩ ext1 simp only rw [eraseLead_add_of_degree_lt_left] · simp · simp [mem_degreeLT.1 hp] /-- For every polynomial `p` in the span of a set `s : Set R[X]`, there exists a polynomial of `p' ∈ s` with higher degree. See also `Polynomial.exists_degree_le_of_mem_span_of_finite`. -/ theorem exists_degree_le_of_mem_span {s : Set R[X]} {p : R[X]} (hs : s.Nonempty) (hp : p ∈ Submodule.span R s) : ∃ p' ∈ s, degree p ≤ degree p' := by by_contra! h by_cases hp_zero : p = 0 · rw [hp_zero, degree_zero] at h rcases hs with ⟨x, hx⟩ exact not_lt_bot (h x hx) · have : p ∈ degreeLT R (natDegree p) := by refine (Submodule.span_le.mpr fun p' p'_mem => ?_) hp rw [SetLike.mem_coe, mem_degreeLT, Nat.cast_withBot] exact lt_of_lt_of_le (h p' p'_mem) degree_le_natDegree rwa [mem_degreeLT, Nat.cast_withBot, degree_eq_natDegree hp_zero, Nat.cast_withBot, lt_self_iff_false] at this /-- A stronger version of `Polynomial.exists_degree_le_of_mem_span` under the assumption that the set `s : R[X]` is finite. There exists a polynomial `p' ∈ s` whose degree dominates the degree of every element of `p ∈ span R s`. -/ theorem exists_degree_le_of_mem_span_of_finite {s : Set R[X]} (s_fin : s.Finite) (hs : s.Nonempty) : ∃ p' ∈ s, ∀ (p : R[X]), p ∈ Submodule.span R s → degree p ≤ degree p' := by rcases Set.Finite.exists_maximal_wrt degree s s_fin hs with ⟨a, has, hmax⟩ refine ⟨a, has, fun p hp => ?_⟩ rcases exists_degree_le_of_mem_span hs hp with ⟨p', hp'⟩ by_cases h : degree a ≤ degree p' · rw [← hmax p' hp'.left h] at hp'; exact hp'.right · exact le_trans hp'.right (not_le.mp h).le /-- The span of every finite set of polynomials is contained in a `degreeLE n` for some `n`. -/ theorem span_le_degreeLE_of_finite {s : Set R[X]} (s_fin : s.Finite) : ∃ n : ℕ, Submodule.span R s ≤ degreeLE R n := by by_cases s_emp : s.Nonempty · rcases exists_degree_le_of_mem_span_of_finite s_fin s_emp with ⟨p', _, hp'max⟩ exact ⟨natDegree p', fun p hp => mem_degreeLE.mpr ((hp'max _ hp).trans degree_le_natDegree)⟩ · rw [Set.not_nonempty_iff_eq_empty] at s_emp rw [s_emp, Submodule.span_empty] exact ⟨0, bot_le⟩ /-- The span of every finite set of polynomials is contained in a `degreeLT n` for some `n`. -/ theorem span_of_finite_le_degreeLT {s : Set R[X]} (s_fin : s.Finite) : ∃ n : ℕ, Submodule.span R s ≤ degreeLT R n := by rcases span_le_degreeLE_of_finite s_fin with ⟨n, _⟩ exact ⟨n + 1, by rwa [degreeLT_succ_eq_degreeLE]⟩ /-- If `R` is a nontrivial ring, the polynomials `R[X]` are not finite as an `R`-module. When `R` is a field, this is equivalent to `R[X]` being an infinite-dimensional vector space over `R`. -/ theorem not_finite [Nontrivial R] : ¬ Module.Finite R R[X] := by rw [Module.finite_def, Submodule.fg_def] push_neg intro s hs contra rcases span_le_degreeLE_of_finite hs with ⟨n,hn⟩ have : ((X : R[X]) ^ (n + 1)) ∈ Polynomial.degreeLE R ↑n := by rw [contra] at hn exact hn Submodule.mem_top rw [mem_degreeLE, degree_X_pow, Nat.cast_le, add_le_iff_nonpos_right, nonpos_iff_eq_zero] at this exact one_ne_zero this theorem geom_sum_X_comp_X_add_one_eq_sum (n : ℕ) : (∑ i ∈ range n, (X : R[X]) ^ i).comp (X + 1) = (Finset.range n).sum fun i : ℕ => (n.choose (i + 1) : R[X]) * X ^ i := by ext i trans (n.choose (i + 1) : R); swap · simp only [finset_sum_coeff, ← C_eq_natCast, coeff_C_mul_X_pow] rw [Finset.sum_eq_single i, if_pos rfl] · simp +contextual only [@eq_comm _ i, if_false, eq_self_iff_true, imp_true_iff] · simp +contextual only [Nat.lt_add_one_iff, Nat.choose_eq_zero_of_lt, Nat.cast_zero, Finset.mem_range, not_lt, eq_self_iff_true, if_true, imp_true_iff] induction' n with n ih generalizing i · dsimp; simp only [zero_comp, coeff_zero, Nat.cast_zero] · simp only [geom_sum_succ', ih, add_comp, X_pow_comp, coeff_add, Nat.choose_succ_succ, Nat.cast_add, coeff_X_add_one_pow] theorem Monic.geom_sum {P : R[X]} (hP : P.Monic) (hdeg : 0 < P.natDegree) {n : ℕ} (hn : n ≠ 0) : (∑ i ∈ range n, P ^ i).Monic := by nontriviality R obtain ⟨n, rfl⟩ := Nat.exists_eq_succ_of_ne_zero hn rw [geom_sum_succ'] refine (hP.pow _).add_of_left ?_ refine lt_of_le_of_lt (degree_sum_le _ _) ?_ rw [Finset.sup_lt_iff] · simp only [Finset.mem_range, degree_eq_natDegree (hP.pow _).ne_zero] simp only [Nat.cast_lt, hP.natDegree_pow] intro k exact nsmul_lt_nsmul_left hdeg · rw [bot_lt_iff_ne_bot, Ne, degree_eq_bot] exact (hP.pow _).ne_zero theorem Monic.geom_sum' {P : R[X]} (hP : P.Monic) (hdeg : 0 < P.degree) {n : ℕ} (hn : n ≠ 0) : (∑ i ∈ range n, P ^ i).Monic := hP.geom_sum (natDegree_pos_iff_degree_pos.2 hdeg) hn theorem monic_geom_sum_X {n : ℕ} (hn : n ≠ 0) : (∑ i ∈ range n, (X : R[X]) ^ i).Monic := by nontriviality R apply monic_X.geom_sum _ hn simp only [natDegree_X, zero_lt_one] end Semiring section Ring variable [Ring R] /-- Given a polynomial, return the polynomial whose coefficients are in the ring closure of the original coefficients. -/ def restriction (p : R[X]) : Polynomial (Subring.closure (↑p.coeffs : Set R)) := ∑ i ∈ p.support, monomial i (⟨p.coeff i, letI := Classical.decEq R if H : p.coeff i = 0 then H.symm ▸ (Subring.closure _).zero_mem else Subring.subset_closure (p.coeff_mem_coeffs _ H)⟩ : Subring.closure (↑p.coeffs : Set R)) @[simp] theorem coeff_restriction {p : R[X]} {n : ℕ} : ↑(coeff (restriction p) n) = coeff p n := by classical simp only [restriction, coeff_monomial, finset_sum_coeff, mem_support_iff, Finset.sum_ite_eq', Ne, ite_not] split_ifs with h · rw [h] rfl · rfl theorem coeff_restriction' {p : R[X]} {n : ℕ} : (coeff (restriction p) n).1 = coeff p n := by simp @[simp] theorem support_restriction (p : R[X]) : support (restriction p) = support p := by ext i simp only [mem_support_iff, not_iff_not, Ne] conv_rhs => rw [← coeff_restriction] exact ⟨fun H => by rw [H, ZeroMemClass.coe_zero], fun H => Subtype.coe_injective H⟩ @[simp] theorem map_restriction {R : Type u} [CommRing R] (p : R[X]) : p.restriction.map (algebraMap _ _) = p := ext fun n => by rw [coeff_map, Algebra.algebraMap_ofSubring_apply, coeff_restriction] @[simp] theorem degree_restriction {p : R[X]} : (restriction p).degree = p.degree := by simp [degree] @[simp] theorem natDegree_restriction {p : R[X]} : (restriction p).natDegree = p.natDegree := by simp [natDegree] @[simp] theorem monic_restriction {p : R[X]} : Monic (restriction p) ↔ Monic p := by simp only [Monic, leadingCoeff, natDegree_restriction] rw [← @coeff_restriction _ _ p] exact ⟨fun H => by rw [H, OneMemClass.coe_one], fun H => Subtype.coe_injective H⟩ @[simp] theorem restriction_zero : restriction (0 : R[X]) = 0 := by simp only [restriction, Finset.sum_empty, support_zero] @[simp] theorem restriction_one : restriction (1 : R[X]) = 1 := ext fun i => Subtype.eq <| by rw [coeff_restriction', coeff_one, coeff_one]; split_ifs <;> rfl variable [Semiring S] {f : R →+* S} {x : S} theorem eval₂_restriction {p : R[X]} : eval₂ f x p = eval₂ (f.comp (Subring.subtype (Subring.closure (p.coeffs : Set R)))) x p.restriction := by simp only [eval₂_eq_sum, sum, support_restriction, ← @coeff_restriction _ _ p, RingHom.comp_apply, Subring.coe_subtype] section ToSubring variable (p : R[X]) (T : Subring R) /-- Given a polynomial `p` and a subring `T` that contains the coefficients of `p`, return the corresponding polynomial whose coefficients are in `T`. -/ def toSubring (hp : (↑p.coeffs : Set R) ⊆ T) : T[X] := ∑ i ∈ p.support, monomial i (⟨p.coeff i, letI := Classical.decEq R if H : p.coeff i = 0 then H.symm ▸ T.zero_mem else hp (p.coeff_mem_coeffs _ H)⟩ : T) variable (hp : (↑p.coeffs : Set R) ⊆ T) @[simp] theorem coeff_toSubring {n : ℕ} : ↑(coeff (toSubring p T hp) n) = coeff p n := by classical simp only [toSubring, coeff_monomial, finset_sum_coeff, mem_support_iff, Finset.sum_ite_eq', Ne, ite_not] split_ifs with h · rw [h] rfl · rfl theorem coeff_toSubring' {n : ℕ} : (coeff (toSubring p T hp) n).1 = coeff p n := by simp @[simp] theorem support_toSubring : support (toSubring p T hp) = support p := by ext i simp only [mem_support_iff, not_iff_not, Ne] conv_rhs => rw [← coeff_toSubring p T hp] exact ⟨fun H => by rw [H, ZeroMemClass.coe_zero], fun H => Subtype.coe_injective H⟩ @[simp] theorem degree_toSubring : (toSubring p T hp).degree = p.degree := by simp [degree] @[simp] theorem natDegree_toSubring : (toSubring p T hp).natDegree = p.natDegree := by simp [natDegree] @[simp] theorem monic_toSubring : Monic (toSubring p T hp) ↔ Monic p := by simp_rw [Monic, leadingCoeff, natDegree_toSubring, ← coeff_toSubring p T hp] exact ⟨fun H => by rw [H, OneMemClass.coe_one], fun H => Subtype.coe_injective H⟩ @[simp] theorem toSubring_zero : toSubring (0 : R[X]) T (by simp [coeffs]) = 0 := by ext i simp @[simp] theorem toSubring_one : toSubring (1 : R[X]) T (Set.Subset.trans coeffs_one <| Finset.singleton_subset_set_iff.2 T.one_mem) = 1 := ext fun i => Subtype.eq <| by rw [coeff_toSubring', coeff_one, coeff_one, apply_ite Subtype.val, ZeroMemClass.coe_zero, OneMemClass.coe_one] @[simp] theorem map_toSubring : (p.toSubring T hp).map (Subring.subtype T) = p := by ext n simp [coeff_map] end ToSubring variable (T : Subring R) /-- Given a polynomial whose coefficients are in some subring, return the corresponding polynomial whose coefficients are in the ambient ring. -/ def ofSubring (p : T[X]) : R[X] := ∑ i ∈ p.support, monomial i (p.coeff i : R) theorem coeff_ofSubring (p : T[X]) (n : ℕ) : coeff (ofSubring T p) n = (coeff p n : T) := by simp only [ofSubring, coeff_monomial, finset_sum_coeff, mem_support_iff, Finset.sum_ite_eq', ite_eq_right_iff, Ne, ite_not, Classical.not_not, ite_eq_left_iff] intro h rw [h, ZeroMemClass.coe_zero] @[simp] theorem coeffs_ofSubring {p : T[X]} : (↑(p.ofSubring T).coeffs : Set R) ⊆ T := by classical intro i hi simp only [coeffs, Set.mem_image, mem_support_iff, Ne, Finset.mem_coe, (Finset.coe_image)] at hi rcases hi with ⟨n, _, h'n⟩ rw [← h'n, coeff_ofSubring] exact Subtype.mem (coeff p n : T) end Ring end Polynomial namespace Ideal open Polynomial section Semiring variable [Semiring R] /-- Transport an ideal of `R[X]` to an `R`-submodule of `R[X]`. -/ def ofPolynomial (I : Ideal R[X]) : Submodule R R[X] where carrier := I.carrier zero_mem' := I.zero_mem add_mem' := I.add_mem smul_mem' c x H := by rw [← C_mul'] exact I.mul_mem_left _ H variable {I : Ideal R[X]} theorem mem_ofPolynomial (x) : x ∈ I.ofPolynomial ↔ x ∈ I := Iff.rfl variable (I) /-- Given an ideal `I` of `R[X]`, make the `R`-submodule of `I` consisting of polynomials of degree ≤ `n`. -/ def degreeLE (n : WithBot ℕ) : Submodule R R[X] := Polynomial.degreeLE R n ⊓ I.ofPolynomial /-- Given an ideal `I` of `R[X]`, make the ideal in `R` of leading coefficients of polynomials in `I` with degree ≤ `n`. -/ def leadingCoeffNth (n : ℕ) : Ideal R := (I.degreeLE n).map <| lcoeff R n /-- Given an ideal `I` in `R[X]`, make the ideal in `R` of the leading coefficients in `I`. -/ def leadingCoeff : Ideal R := ⨆ n : ℕ, I.leadingCoeffNth n end Semiring section CommSemiring variable [CommSemiring R] [Semiring S] /-- If every coefficient of a polynomial is in an ideal `I`, then so is the polynomial itself -/ theorem polynomial_mem_ideal_of_coeff_mem_ideal (I : Ideal R[X]) (p : R[X]) (hp : ∀ n : ℕ, p.coeff n ∈ I.comap (C : R →+* R[X])) : p ∈ I := sum_C_mul_X_pow_eq p ▸ Submodule.sum_mem I fun n _ => I.mul_mem_right _ (hp n) /-- The push-forward of an ideal `I` of `R` to `R[X]` via inclusion is exactly the set of polynomials whose coefficients are in `I` -/ theorem mem_map_C_iff {I : Ideal R} {f : R[X]} : f ∈ (Ideal.map (C : R →+* R[X]) I : Ideal R[X]) ↔ ∀ n : ℕ, f.coeff n ∈ I := by constructor · intro hf refine Submodule.span_induction ?_ ?_ ?_ ?_ hf · intro f hf n obtain ⟨x, hx⟩ := (Set.mem_image _ _ _).mp hf rw [← hx.right, coeff_C] by_cases h : n = 0 · simpa [h] using hx.left · simp [h] · simp · exact fun f g _ _ hf hg n => by simp [I.add_mem (hf n) (hg n)] · refine fun f g _ hg n => ?_ rw [smul_eq_mul, coeff_mul] exact I.sum_mem fun c _ => I.mul_mem_left (f.coeff c.fst) (hg c.snd) · intro hf rw [← sum_monomial_eq f] refine (I.map C : Ideal R[X]).sum_mem fun n _ => ?_ simp only [← C_mul_X_pow_eq_monomial, ne_eq] rw [mul_comm] exact (I.map C : Ideal R[X]).mul_mem_left _ (mem_map_of_mem _ (hf n)) theorem _root_.Polynomial.ker_mapRingHom (f : R →+* S) : RingHom.ker (Polynomial.mapRingHom f) = (RingHom.ker f).map (C : R →+* R[X]) := by ext simp only [RingHom.mem_ker, coe_mapRingHom] rw [mem_map_C_iff, Polynomial.ext_iff] simp [RingHom.mem_ker] variable (I : Ideal R[X]) theorem mem_leadingCoeffNth (n : ℕ) (x) : x ∈ I.leadingCoeffNth n ↔ ∃ p ∈ I, degree p ≤ n ∧ p.leadingCoeff = x := by simp only [leadingCoeffNth, degreeLE, Submodule.mem_map, lcoeff_apply, Submodule.mem_inf, mem_degreeLE] constructor · rintro ⟨p, ⟨hpdeg, hpI⟩, rfl⟩ rcases lt_or_eq_of_le hpdeg with hpdeg | hpdeg · refine ⟨0, I.zero_mem, bot_le, ?_⟩ rw [leadingCoeff_zero, eq_comm] exact coeff_eq_zero_of_degree_lt hpdeg · refine ⟨p, hpI, le_of_eq hpdeg, ?_⟩ rw [Polynomial.leadingCoeff, natDegree, hpdeg, Nat.cast_withBot, WithBot.unbotD_coe] · rintro ⟨p, hpI, hpdeg, rfl⟩ have : natDegree p + (n - natDegree p) = n := add_tsub_cancel_of_le (natDegree_le_of_degree_le hpdeg) refine ⟨p * X ^ (n - natDegree p), ⟨?_, I.mul_mem_right _ hpI⟩, ?_⟩ · apply le_trans (degree_mul_le _ _) _ apply le_trans (add_le_add degree_le_natDegree (degree_X_pow_le _)) _ rw [← Nat.cast_add, this] · rw [Polynomial.leadingCoeff, ← coeff_mul_X_pow p (n - natDegree p), this] theorem mem_leadingCoeffNth_zero (x) : x ∈ I.leadingCoeffNth 0 ↔ C x ∈ I := (mem_leadingCoeffNth _ _ _).trans ⟨fun ⟨p, hpI, hpdeg, hpx⟩ => by rwa [← hpx, Polynomial.leadingCoeff, Nat.eq_zero_of_le_zero (natDegree_le_of_degree_le hpdeg), ← eq_C_of_degree_le_zero hpdeg], fun hx => ⟨C x, hx, degree_C_le, leadingCoeff_C x⟩⟩ theorem leadingCoeffNth_mono {m n : ℕ} (H : m ≤ n) : I.leadingCoeffNth m ≤ I.leadingCoeffNth n := by intro r hr simp only [SetLike.mem_coe, mem_leadingCoeffNth] at hr ⊢ rcases hr with ⟨p, hpI, hpdeg, rfl⟩ refine ⟨p * X ^ (n - m), I.mul_mem_right _ hpI, ?_, leadingCoeff_mul_X_pow⟩ refine le_trans (degree_mul_le _ _) ?_ refine le_trans (add_le_add hpdeg (degree_X_pow_le _)) ?_ rw [← Nat.cast_add, add_tsub_cancel_of_le H] theorem mem_leadingCoeff (x) : x ∈ I.leadingCoeff ↔ ∃ p ∈ I, Polynomial.leadingCoeff p = x := by rw [leadingCoeff, Submodule.mem_iSup_of_directed] · simp only [mem_leadingCoeffNth] constructor · rintro ⟨i, p, hpI, _, rfl⟩ exact ⟨p, hpI, rfl⟩ rintro ⟨p, hpI, rfl⟩ exact ⟨natDegree p, p, hpI, degree_le_natDegree, rfl⟩ intro i j exact ⟨i + j, I.leadingCoeffNth_mono (Nat.le_add_right _ _), I.leadingCoeffNth_mono (Nat.le_add_left _ _)⟩ /-- If `I` is an ideal, and `pᵢ` is a finite family of polynomials each satisfying `∀ k, (pᵢ)ₖ ∈ Iⁿⁱ⁻ᵏ` for some `nᵢ`, then `p = ∏ pᵢ` also satisfies `∀ k, pₖ ∈ Iⁿ⁻ᵏ` with `n = ∑ nᵢ`. -/ theorem _root_.Polynomial.coeff_prod_mem_ideal_pow_tsub {ι : Type*} (s : Finset ι) (f : ι → R[X]) (I : Ideal R) (n : ι → ℕ) (h : ∀ i ∈ s, ∀ (k), (f i).coeff k ∈ I ^ (n i - k)) (k : ℕ) : (s.prod f).coeff k ∈ I ^ (s.sum n - k) := by classical induction' s using Finset.induction with a s ha hs generalizing k · rw [sum_empty, prod_empty, coeff_one, zero_tsub, pow_zero, Ideal.one_eq_top] exact Submodule.mem_top · rw [sum_insert ha, prod_insert ha, coeff_mul] apply sum_mem rintro ⟨i, j⟩ e obtain rfl : i + j = k := mem_antidiagonal.mp e apply Ideal.pow_le_pow_right add_tsub_add_le_tsub_add_tsub rw [pow_add] exact Ideal.mul_mem_mul (h _ (Finset.mem_insert.mpr <| Or.inl rfl) _) (hs (fun i hi k => h _ (Finset.mem_insert.mpr <| Or.inr hi) _) j) end CommSemiring section Ring variable [Ring R] /-- `R[X]` is never a field for any ring `R`. -/ theorem polynomial_not_isField : ¬IsField R[X] := by nontriviality R intro hR obtain ⟨p, hp⟩ := hR.mul_inv_cancel X_ne_zero have hp0 : p ≠ 0 := right_ne_zero_of_mul_eq_one hp have := degree_lt_degree_mul_X hp0 rw [← X_mul, congr_arg degree hp, degree_one, Nat.WithBot.lt_zero_iff, degree_eq_bot] at this exact hp0 this /-- The only constant in a maximal ideal over a field is `0`. -/ theorem eq_zero_of_constant_mem_of_maximal (hR : IsField R) (I : Ideal R[X]) [hI : I.IsMaximal] (x : R) (hx : C x ∈ I) : x = 0 := by refine Classical.by_contradiction fun hx0 => hI.ne_top ((eq_top_iff_one I).2 ?_) obtain ⟨y, hy⟩ := hR.mul_inv_cancel hx0 convert I.mul_mem_left (C y) hx rw [← C.map_mul, hR.mul_comm y x, hy, RingHom.map_one] end Ring section CommRing variable [CommRing R] /-- If `P` is a prime ideal of `R`, then `P.R[x]` is a prime ideal of `R[x]`. -/ theorem isPrime_map_C_iff_isPrime (P : Ideal R) : IsPrime (map (C : R →+* R[X]) P : Ideal R[X]) ↔ IsPrime P := by -- Note: the following proof avoids quotient rings -- It can be golfed substantially by using something like -- `(Quotient.isDomain_iff_prime (map C P : Ideal R[X]))` constructor · intro H have := comap_isPrime C (map C P) convert this using 1 ext x simp only [mem_comap, mem_map_C_iff] constructor · rintro h (- | n) · rwa [coeff_C_zero] · simp only [coeff_C_ne_zero (Nat.succ_ne_zero _), Submodule.zero_mem] · intro h simpa only [coeff_C_zero] using h 0 · intro h constructor · rw [Ne, eq_top_iff_one, mem_map_C_iff, not_forall] use 0 rw [coeff_one_zero, ← eq_top_iff_one] exact h.1 · intro f g simp only [mem_map_C_iff] contrapose! rintro ⟨hf, hg⟩ classical let m := Nat.find hf let n := Nat.find hg refine ⟨m + n, ?_⟩ rw [coeff_mul, ← Finset.insert_erase ((Finset.mem_antidiagonal (a := (m,n))).mpr rfl), Finset.sum_insert (Finset.not_mem_erase _ _), (P.add_mem_iff_left _).not] · apply mt h.2 rw [not_or] exact ⟨Nat.find_spec hf, Nat.find_spec hg⟩
apply P.sum_mem rintro ⟨i, j⟩ hij rw [Finset.mem_erase, Finset.mem_antidiagonal] at hij simp only [Ne, Prod.mk_inj, not_and_or] at hij obtain hi | hj : i < m ∨ j < n := by omega · rw [mul_comm] apply P.mul_mem_left exact Classical.not_not.1 (Nat.find_min hf hi) · apply P.mul_mem_left exact Classical.not_not.1 (Nat.find_min hg hj)
Mathlib/RingTheory/Polynomial/Basic.lean
683
694
/- Copyright (c) 2023 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.Analysis.SpecialFunctions.Log.Deriv import Mathlib.Analysis.SpecialFunctions.Pow.Asymptotics import Mathlib.Analysis.Convex.Deriv /-! # The function `x ↦ - x * log x` The purpose of this file is to record basic analytic properties of the function `x ↦ - x * log x`, which is notably used in the theory of Shannon entropy. ## Main definitions * `negMulLog`: the function `x ↦ - x * log x` from `ℝ` to `ℝ`. -/ open scoped Topology namespace Real @[fun_prop] lemma continuous_mul_log : Continuous fun x ↦ x * log x := by rw [continuous_iff_continuousAt] intro x obtain hx | rfl := ne_or_eq x 0 · exact (continuous_id'.continuousAt).mul (continuousAt_log hx) rw [ContinuousAt, zero_mul] simp_rw [mul_comm _ (log _)] nth_rewrite 1 [← nhdsWithin_univ] have : (Set.univ : Set ℝ) = Set.Iio 0 ∪ Set.Ioi 0 ∪ {0} := by ext; simp [em] rw [this, nhdsWithin_union, nhdsWithin_union] simp only [nhdsWithin_singleton, sup_le_iff, Filter.nonpos_iff, Filter.tendsto_sup] refine ⟨⟨tendsto_log_mul_self_nhdsLT_zero, ?_⟩, ?_⟩ · simpa only [rpow_one] using tendsto_log_mul_rpow_nhdsGT_zero zero_lt_one · convert tendsto_pure_nhds (fun x ↦ log x * x) 0 simp @[fun_prop] lemma Continuous.mul_log {α : Type*} [TopologicalSpace α] {f : α → ℝ} (hf : Continuous f) :
Continuous fun a ↦ f a * log (f a) := continuous_mul_log.comp hf lemma differentiableOn_mul_log : DifferentiableOn ℝ (fun x ↦ x * log x) {0}ᶜ := differentiable_id'.differentiableOn.mul differentiableOn_log
Mathlib/Analysis/SpecialFunctions/Log/NegMulLog.lean
45
48
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot -/ import Mathlib.Order.Filter.SmallSets import Mathlib.Topology.UniformSpace.Defs import Mathlib.Topology.ContinuousOn /-! # Basic results on uniform spaces Uniform spaces are a generalization of metric spaces and topological groups. ## Main definitions In this file we define a complete lattice structure on the type `UniformSpace X` of uniform structures on `X`, as well as the pullback (`UniformSpace.comap`) of uniform structures coming from the pullback of filters. Like distance functions, uniform structures cannot be pushed forward in general. ## Notations Localized in `Uniformity`, we have the notation `𝓤 X` for the uniformity on a uniform space `X`, and `○` for composition of relations, seen as terms with type `Set (X × X)`. ## References The formalization uses the books: * [N. Bourbaki, *General Topology*][bourbaki1966] * [I. M. James, *Topologies and Uniformities*][james1999] But it makes a more systematic use of the filter library. -/ open Set Filter Topology universe u v ua ub uc ud /-! ### Relations, seen as `Set (α × α)` -/ variable {α : Type ua} {β : Type ub} {γ : Type uc} {δ : Type ud} {ι : Sort*} open Uniformity section UniformSpace variable [UniformSpace α] /-- If `s ∈ 𝓤 α`, then for any natural `n`, for a subset `t` of a sufficiently small set in `𝓤 α`, we have `t ○ t ○ ... ○ t ⊆ s` (`n` compositions). -/ theorem eventually_uniformity_iterate_comp_subset {s : Set (α × α)} (hs : s ∈ 𝓤 α) (n : ℕ) : ∀ᶠ t in (𝓤 α).smallSets, (t ○ ·)^[n] t ⊆ s := by suffices ∀ᶠ t in (𝓤 α).smallSets, t ⊆ s ∧ (t ○ ·)^[n] t ⊆ s from (eventually_and.1 this).2 induction n generalizing s with | zero => simpa | succ _ ihn => rcases comp_mem_uniformity_sets hs with ⟨t, htU, hts⟩ refine (ihn htU).mono fun U hU => ?_ rw [Function.iterate_succ_apply'] exact ⟨hU.1.trans <| (subset_comp_self <| refl_le_uniformity htU).trans hts, (compRel_mono hU.1 hU.2).trans hts⟩ /-- If `s ∈ 𝓤 α`, then for a subset `t` of a sufficiently small set in `𝓤 α`, we have `t ○ t ⊆ s`. -/ theorem eventually_uniformity_comp_subset {s : Set (α × α)} (hs : s ∈ 𝓤 α) : ∀ᶠ t in (𝓤 α).smallSets, t ○ t ⊆ s := eventually_uniformity_iterate_comp_subset hs 1 /-! ### Balls in uniform spaces -/ namespace UniformSpace open UniformSpace (ball) lemma isOpen_ball (x : α) {V : Set (α × α)} (hV : IsOpen V) : IsOpen (ball x V) := hV.preimage <| .prodMk_right _ lemma isClosed_ball (x : α) {V : Set (α × α)} (hV : IsClosed V) : IsClosed (ball x V) := hV.preimage <| .prodMk_right _ /-! ### Neighborhoods in uniform spaces -/ theorem hasBasis_nhds_prod (x y : α) : HasBasis (𝓝 (x, y)) (fun s => s ∈ 𝓤 α ∧ IsSymmetricRel s) fun s => ball x s ×ˢ ball y s := by rw [nhds_prod_eq] apply (hasBasis_nhds x).prod_same_index (hasBasis_nhds y) rintro U V ⟨U_in, U_symm⟩ ⟨V_in, V_symm⟩ exact ⟨U ∩ V, ⟨(𝓤 α).inter_sets U_in V_in, U_symm.inter V_symm⟩, ball_inter_left x U V, ball_inter_right y U V⟩ end UniformSpace open UniformSpace theorem nhds_eq_uniformity_prod {a b : α} : 𝓝 (a, b) = (𝓤 α).lift' fun s : Set (α × α) => { y : α | (y, a) ∈ s } ×ˢ { y : α | (b, y) ∈ s } := by rw [nhds_prod_eq, nhds_nhds_eq_uniformity_uniformity_prod, lift_lift'_same_eq_lift'] · exact fun s => monotone_const.set_prod monotone_preimage · refine fun t => Monotone.set_prod ?_ monotone_const exact monotone_preimage (f := fun y => (y, a)) theorem nhdset_of_mem_uniformity {d : Set (α × α)} (s : Set (α × α)) (hd : d ∈ 𝓤 α) : ∃ t : Set (α × α), IsOpen t ∧ s ⊆ t ∧ t ⊆ { p | ∃ x y, (p.1, x) ∈ d ∧ (x, y) ∈ s ∧ (y, p.2) ∈ d } := by let cl_d := { p : α × α | ∃ x y, (p.1, x) ∈ d ∧ (x, y) ∈ s ∧ (y, p.2) ∈ d } have : ∀ p ∈ s, ∃ t, t ⊆ cl_d ∧ IsOpen t ∧ p ∈ t := fun ⟨x, y⟩ hp => mem_nhds_iff.mp <| show cl_d ∈ 𝓝 (x, y) by rw [nhds_eq_uniformity_prod, mem_lift'_sets] · exact ⟨d, hd, fun ⟨a, b⟩ ⟨ha, hb⟩ => ⟨x, y, ha, hp, hb⟩⟩ · exact fun _ _ h _ h' => ⟨h h'.1, h h'.2⟩ choose t ht using this exact ⟨(⋃ p : α × α, ⋃ h : p ∈ s, t p h : Set (α × α)), isOpen_iUnion fun p : α × α => isOpen_iUnion fun hp => (ht p hp).right.left, fun ⟨a, b⟩ hp => by simp only [mem_iUnion, Prod.exists]; exact ⟨a, b, hp, (ht (a, b) hp).right.right⟩, iUnion_subset fun p => iUnion_subset fun hp => (ht p hp).left⟩ /-- Entourages are neighborhoods of the diagonal. -/ theorem nhds_le_uniformity (x : α) : 𝓝 (x, x) ≤ 𝓤 α := by intro V V_in rcases comp_symm_mem_uniformity_sets V_in with ⟨w, w_in, w_symm, w_sub⟩ have : ball x w ×ˢ ball x w ∈ 𝓝 (x, x) := by rw [nhds_prod_eq] exact prod_mem_prod (ball_mem_nhds x w_in) (ball_mem_nhds x w_in) apply mem_of_superset this rintro ⟨u, v⟩ ⟨u_in, v_in⟩ exact w_sub (mem_comp_of_mem_ball w_symm u_in v_in) /-- Entourages are neighborhoods of the diagonal. -/ theorem iSup_nhds_le_uniformity : ⨆ x : α, 𝓝 (x, x) ≤ 𝓤 α := iSup_le nhds_le_uniformity /-- Entourages are neighborhoods of the diagonal. -/ theorem nhdsSet_diagonal_le_uniformity : 𝓝ˢ (diagonal α) ≤ 𝓤 α := (nhdsSet_diagonal α).trans_le iSup_nhds_le_uniformity section variable (α) theorem UniformSpace.has_seq_basis [IsCountablyGenerated <| 𝓤 α] : ∃ V : ℕ → Set (α × α), HasAntitoneBasis (𝓤 α) V ∧ ∀ n, IsSymmetricRel (V n) := let ⟨U, hsym, hbasis⟩ := (@UniformSpace.hasBasis_symmetric α _).exists_antitone_subbasis ⟨U, hbasis, fun n => (hsym n).2⟩ end /-! ### Closure and interior in uniform spaces -/ theorem closure_eq_uniformity (s : Set <| α × α) : closure s = ⋂ V ∈ { V | V ∈ 𝓤 α ∧ IsSymmetricRel V }, V ○ s ○ V := by ext ⟨x, y⟩ simp +contextual only [mem_closure_iff_nhds_basis (UniformSpace.hasBasis_nhds_prod x y), mem_iInter, mem_setOf_eq, and_imp, mem_comp_comp, exists_prop, ← mem_inter_iff, inter_comm, Set.Nonempty] theorem uniformity_hasBasis_closed : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsClosed V) id := by refine Filter.hasBasis_self.2 fun t h => ?_ rcases comp_comp_symm_mem_uniformity_sets h with ⟨w, w_in, w_symm, r⟩ refine ⟨closure w, mem_of_superset w_in subset_closure, isClosed_closure, ?_⟩ refine Subset.trans ?_ r rw [closure_eq_uniformity] apply iInter_subset_of_subset apply iInter_subset exact ⟨w_in, w_symm⟩ theorem uniformity_eq_uniformity_closure : 𝓤 α = (𝓤 α).lift' closure := Eq.symm <| uniformity_hasBasis_closed.lift'_closure_eq_self fun _ => And.right theorem Filter.HasBasis.uniformity_closure {p : ι → Prop} {U : ι → Set (α × α)} (h : (𝓤 α).HasBasis p U) : (𝓤 α).HasBasis p fun i => closure (U i) := (@uniformity_eq_uniformity_closure α _).symm ▸ h.lift'_closure /-- Closed entourages form a basis of the uniformity filter. -/ theorem uniformity_hasBasis_closure : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α) closure := (𝓤 α).basis_sets.uniformity_closure theorem closure_eq_inter_uniformity {t : Set (α × α)} : closure t = ⋂ d ∈ 𝓤 α, d ○ (t ○ d) := calc closure t = ⋂ (V) (_ : V ∈ 𝓤 α ∧ IsSymmetricRel V), V ○ t ○ V := closure_eq_uniformity t _ = ⋂ V ∈ 𝓤 α, V ○ t ○ V := Eq.symm <| UniformSpace.hasBasis_symmetric.biInter_mem fun _ _ hV => compRel_mono (compRel_mono hV Subset.rfl) hV _ = ⋂ V ∈ 𝓤 α, V ○ (t ○ V) := by simp only [compRel_assoc] theorem uniformity_eq_uniformity_interior : 𝓤 α = (𝓤 α).lift' interior := le_antisymm (le_iInf₂ fun d hd => by let ⟨s, hs, hs_comp⟩ := comp3_mem_uniformity hd let ⟨t, ht, hst, ht_comp⟩ := nhdset_of_mem_uniformity s hs have : s ⊆ interior d := calc s ⊆ t := hst _ ⊆ interior d := ht.subset_interior_iff.mpr fun x (hx : x ∈ t) => let ⟨x, y, h₁, h₂, h₃⟩ := ht_comp hx hs_comp ⟨x, h₁, y, h₂, h₃⟩ have : interior d ∈ 𝓤 α := by filter_upwards [hs] using this simp [this]) fun _ hs => ((𝓤 α).lift' interior).sets_of_superset (mem_lift' hs) interior_subset theorem interior_mem_uniformity {s : Set (α × α)} (hs : s ∈ 𝓤 α) : interior s ∈ 𝓤 α := by rw [uniformity_eq_uniformity_interior]; exact mem_lift' hs theorem mem_uniformity_isClosed {s : Set (α × α)} (h : s ∈ 𝓤 α) : ∃ t ∈ 𝓤 α, IsClosed t ∧ t ⊆ s := let ⟨t, ⟨ht_mem, htc⟩, hts⟩ := uniformity_hasBasis_closed.mem_iff.1 h ⟨t, ht_mem, htc, hts⟩ theorem isOpen_iff_isOpen_ball_subset {s : Set α} : IsOpen s ↔ ∀ x ∈ s, ∃ V ∈ 𝓤 α, IsOpen V ∧ ball x V ⊆ s := by rw [isOpen_iff_ball_subset] constructor <;> intro h x hx · obtain ⟨V, hV, hV'⟩ := h x hx exact ⟨interior V, interior_mem_uniformity hV, isOpen_interior, (ball_mono interior_subset x).trans hV'⟩ · obtain ⟨V, hV, -, hV'⟩ := h x hx exact ⟨V, hV, hV'⟩ @[deprecated (since := "2024-11-18")] alias isOpen_iff_open_ball_subset := isOpen_iff_isOpen_ball_subset /-- The uniform neighborhoods of all points of a dense set cover the whole space. -/ theorem Dense.biUnion_uniformity_ball {s : Set α} {U : Set (α × α)} (hs : Dense s) (hU : U ∈ 𝓤 α) : ⋃ x ∈ s, ball x U = univ := by refine iUnion₂_eq_univ_iff.2 fun y => ?_ rcases hs.inter_nhds_nonempty (mem_nhds_right y hU) with ⟨x, hxs, hxy : (x, y) ∈ U⟩ exact ⟨x, hxs, hxy⟩ /-- The uniform neighborhoods of all points of a dense indexed collection cover the whole space. -/ lemma DenseRange.iUnion_uniformity_ball {ι : Type*} {xs : ι → α} (xs_dense : DenseRange xs) {U : Set (α × α)} (hU : U ∈ uniformity α) : ⋃ i, UniformSpace.ball (xs i) U = univ := by rw [← biUnion_range (f := xs) (g := fun x ↦ UniformSpace.ball x U)] exact Dense.biUnion_uniformity_ball xs_dense hU /-! ### Uniformity bases -/ /-- Open elements of `𝓤 α` form a basis of `𝓤 α`. -/ theorem uniformity_hasBasis_open : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsOpen V) id := hasBasis_self.2 fun s hs => ⟨interior s, interior_mem_uniformity hs, isOpen_interior, interior_subset⟩ theorem Filter.HasBasis.mem_uniformity_iff {p : β → Prop} {s : β → Set (α × α)} (h : (𝓤 α).HasBasis p s) {t : Set (α × α)} : t ∈ 𝓤 α ↔ ∃ i, p i ∧ ∀ a b, (a, b) ∈ s i → (a, b) ∈ t := h.mem_iff.trans <| by simp only [Prod.forall, subset_def] /-- Open elements `s : Set (α × α)` of `𝓤 α` such that `(x, y) ∈ s ↔ (y, x) ∈ s` form a basis of `𝓤 α`. -/ theorem uniformity_hasBasis_open_symmetric : HasBasis (𝓤 α) (fun V : Set (α × α) => V ∈ 𝓤 α ∧ IsOpen V ∧ IsSymmetricRel V) id := by simp only [← and_assoc] refine uniformity_hasBasis_open.restrict fun s hs => ⟨symmetrizeRel s, ?_⟩ exact ⟨⟨symmetrize_mem_uniformity hs.1, IsOpen.inter hs.2 (hs.2.preimage continuous_swap)⟩, symmetric_symmetrizeRel s, symmetrizeRel_subset_self s⟩ theorem comp_open_symm_mem_uniformity_sets {s : Set (α × α)} (hs : s ∈ 𝓤 α) : ∃ t ∈ 𝓤 α, IsOpen t ∧ IsSymmetricRel t ∧ t ○ t ⊆ s := by obtain ⟨t, ht₁, ht₂⟩ := comp_mem_uniformity_sets hs obtain ⟨u, ⟨hu₁, hu₂, hu₃⟩, hu₄ : u ⊆ t⟩ := uniformity_hasBasis_open_symmetric.mem_iff.mp ht₁ exact ⟨u, hu₁, hu₂, hu₃, (compRel_mono hu₄ hu₄).trans ht₂⟩ end UniformSpace open uniformity section Constructions instance : PartialOrder (UniformSpace α) := PartialOrder.lift (fun u => 𝓤[u]) fun _ _ => UniformSpace.ext protected theorem UniformSpace.le_def {u₁ u₂ : UniformSpace α} : u₁ ≤ u₂ ↔ 𝓤[u₁] ≤ 𝓤[u₂] := Iff.rfl instance : InfSet (UniformSpace α) := ⟨fun s => UniformSpace.ofCore { uniformity := ⨅ u ∈ s, 𝓤[u] refl := le_iInf fun u => le_iInf fun _ => u.toCore.refl symm := le_iInf₂ fun u hu => le_trans (map_mono <| iInf_le_of_le _ <| iInf_le _ hu) u.symm comp := le_iInf₂ fun u hu => le_trans (lift'_mono (iInf_le_of_le _ <| iInf_le _ hu) <| le_rfl) u.comp }⟩ protected theorem UniformSpace.sInf_le {tt : Set (UniformSpace α)} {t : UniformSpace α} (h : t ∈ tt) : sInf tt ≤ t := show ⨅ u ∈ tt, 𝓤[u] ≤ 𝓤[t] from iInf₂_le t h protected theorem UniformSpace.le_sInf {tt : Set (UniformSpace α)} {t : UniformSpace α} (h : ∀ t' ∈ tt, t ≤ t') : t ≤ sInf tt := show 𝓤[t] ≤ ⨅ u ∈ tt, 𝓤[u] from le_iInf₂ h instance : Top (UniformSpace α) := ⟨@UniformSpace.mk α ⊤ ⊤ le_top le_top fun x ↦ by simp only [nhds_top, comap_top]⟩ instance : Bot (UniformSpace α) := ⟨{ toTopologicalSpace := ⊥ uniformity := 𝓟 idRel symm := by simp [Tendsto] comp := lift'_le (mem_principal_self _) <| principal_mono.2 id_compRel.subset nhds_eq_comap_uniformity := fun s => by let _ : TopologicalSpace α := ⊥; have := discreteTopology_bot α simp [idRel] }⟩ instance : Min (UniformSpace α) := ⟨fun u₁ u₂ => { uniformity := 𝓤[u₁] ⊓ 𝓤[u₂] symm := u₁.symm.inf u₂.symm comp := (lift'_inf_le _ _ _).trans <| inf_le_inf u₁.comp u₂.comp toTopologicalSpace := u₁.toTopologicalSpace ⊓ u₂.toTopologicalSpace nhds_eq_comap_uniformity := fun _ ↦ by rw [@nhds_inf _ u₁.toTopologicalSpace _, @nhds_eq_comap_uniformity _ u₁, @nhds_eq_comap_uniformity _ u₂, comap_inf] }⟩ instance : CompleteLattice (UniformSpace α) := { inferInstanceAs (PartialOrder (UniformSpace α)) with sup := fun a b => sInf { x | a ≤ x ∧ b ≤ x } le_sup_left := fun _ _ => UniformSpace.le_sInf fun _ ⟨h, _⟩ => h le_sup_right := fun _ _ => UniformSpace.le_sInf fun _ ⟨_, h⟩ => h sup_le := fun _ _ _ h₁ h₂ => UniformSpace.sInf_le ⟨h₁, h₂⟩ inf := (· ⊓ ·) le_inf := fun a _ _ h₁ h₂ => show a.uniformity ≤ _ from le_inf h₁ h₂ inf_le_left := fun a _ => show _ ≤ a.uniformity from inf_le_left inf_le_right := fun _ b => show _ ≤ b.uniformity from inf_le_right top := ⊤ le_top := fun a => show a.uniformity ≤ ⊤ from le_top bot := ⊥ bot_le := fun u => u.toCore.refl sSup := fun tt => sInf { t | ∀ t' ∈ tt, t' ≤ t } le_sSup := fun _ _ h => UniformSpace.le_sInf fun _ h' => h' _ h sSup_le := fun _ _ h => UniformSpace.sInf_le h sInf := sInf le_sInf := fun _ _ hs => UniformSpace.le_sInf hs sInf_le := fun _ _ ha => UniformSpace.sInf_le ha } theorem iInf_uniformity {ι : Sort*} {u : ι → UniformSpace α} : 𝓤[iInf u] = ⨅ i, 𝓤[u i] := iInf_range theorem inf_uniformity {u v : UniformSpace α} : 𝓤[u ⊓ v] = 𝓤[u] ⊓ 𝓤[v] := rfl lemma bot_uniformity : 𝓤[(⊥ : UniformSpace α)] = 𝓟 idRel := rfl lemma top_uniformity : 𝓤[(⊤ : UniformSpace α)] = ⊤ := rfl instance inhabitedUniformSpace : Inhabited (UniformSpace α) := ⟨⊥⟩ instance inhabitedUniformSpaceCore : Inhabited (UniformSpace.Core α) := ⟨@UniformSpace.toCore _ default⟩ instance [Subsingleton α] : Unique (UniformSpace α) where uniq u := bot_unique <| le_principal_iff.2 <| by rw [idRel, ← diagonal, diagonal_eq_univ]; exact univ_mem /-- Given `f : α → β` and a uniformity `u` on `β`, the inverse image of `u` under `f` is the inverse image in the filter sense of the induced function `α × α → β × β`. See note [reducible non-instances]. -/ abbrev UniformSpace.comap (f : α → β) (u : UniformSpace β) : UniformSpace α where uniformity := 𝓤[u].comap fun p : α × α => (f p.1, f p.2) symm := by simp only [tendsto_comap_iff, Prod.swap, (· ∘ ·)] exact tendsto_swap_uniformity.comp tendsto_comap comp := le_trans (by rw [comap_lift'_eq, comap_lift'_eq2] · exact lift'_mono' fun s _ ⟨a₁, a₂⟩ ⟨x, h₁, h₂⟩ => ⟨f x, h₁, h₂⟩ · exact monotone_id.compRel monotone_id) (comap_mono u.comp) toTopologicalSpace := u.toTopologicalSpace.induced f nhds_eq_comap_uniformity x := by simp only [nhds_induced, nhds_eq_comap_uniformity, comap_comap, Function.comp_def] theorem uniformity_comap {_ : UniformSpace β} (f : α → β) : 𝓤[UniformSpace.comap f ‹_›] = comap (Prod.map f f) (𝓤 β) := rfl lemma ball_preimage {f : α → β} {U : Set (β × β)} {x : α} : UniformSpace.ball x (Prod.map f f ⁻¹' U) = f ⁻¹' UniformSpace.ball (f x) U := by ext : 1 simp only [UniformSpace.ball, mem_preimage, Prod.map_apply] @[simp] theorem uniformSpace_comap_id {α : Type*} : UniformSpace.comap (id : α → α) = id := by ext : 2 rw [uniformity_comap, Prod.map_id, comap_id] theorem UniformSpace.comap_comap {α β γ} {uγ : UniformSpace γ} {f : α → β} {g : β → γ} : UniformSpace.comap (g ∘ f) uγ = UniformSpace.comap f (UniformSpace.comap g uγ) := by ext1 simp only [uniformity_comap, Filter.comap_comap, Prod.map_comp_map] theorem UniformSpace.comap_inf {α γ} {u₁ u₂ : UniformSpace γ} {f : α → γ} : (u₁ ⊓ u₂).comap f = u₁.comap f ⊓ u₂.comap f := UniformSpace.ext Filter.comap_inf theorem UniformSpace.comap_iInf {ι α γ} {u : ι → UniformSpace γ} {f : α → γ} : (⨅ i, u i).comap f = ⨅ i, (u i).comap f := by ext : 1 simp [uniformity_comap, iInf_uniformity] theorem UniformSpace.comap_mono {α γ} {f : α → γ} : Monotone fun u : UniformSpace γ => u.comap f := fun _ _ hu => Filter.comap_mono hu theorem uniformContinuous_iff {α β} {uα : UniformSpace α} {uβ : UniformSpace β} {f : α → β} : UniformContinuous f ↔ uα ≤ uβ.comap f := Filter.map_le_iff_le_comap theorem le_iff_uniformContinuous_id {u v : UniformSpace α} : u ≤ v ↔ @UniformContinuous _ _ u v id := by rw [uniformContinuous_iff, uniformSpace_comap_id, id] theorem uniformContinuous_comap {f : α → β} [u : UniformSpace β] : @UniformContinuous α β (UniformSpace.comap f u) u f := tendsto_comap theorem uniformContinuous_comap' {f : γ → β} {g : α → γ} [v : UniformSpace β] [u : UniformSpace α] (h : UniformContinuous (f ∘ g)) : @UniformContinuous α γ u (UniformSpace.comap f v) g := tendsto_comap_iff.2 h namespace UniformSpace theorem to_nhds_mono {u₁ u₂ : UniformSpace α} (h : u₁ ≤ u₂) (a : α) : @nhds _ (@UniformSpace.toTopologicalSpace _ u₁) a ≤ @nhds _ (@UniformSpace.toTopologicalSpace _ u₂) a := by rw [@nhds_eq_uniformity α u₁ a, @nhds_eq_uniformity α u₂ a]; exact lift'_mono h le_rfl theorem toTopologicalSpace_mono {u₁ u₂ : UniformSpace α} (h : u₁ ≤ u₂) : @UniformSpace.toTopologicalSpace _ u₁ ≤ @UniformSpace.toTopologicalSpace _ u₂ := le_of_nhds_le_nhds <| to_nhds_mono h theorem toTopologicalSpace_comap {f : α → β} {u : UniformSpace β} : @UniformSpace.toTopologicalSpace _ (UniformSpace.comap f u) = TopologicalSpace.induced f (@UniformSpace.toTopologicalSpace β u) := rfl lemma uniformSpace_eq_bot {u : UniformSpace α} : u = ⊥ ↔ idRel ∈ 𝓤[u] := le_bot_iff.symm.trans le_principal_iff protected lemma _root_.Filter.HasBasis.uniformSpace_eq_bot {ι p} {s : ι → Set (α × α)} {u : UniformSpace α} (h : 𝓤[u].HasBasis p s) : u = ⊥ ↔ ∃ i, p i ∧ Pairwise fun x y : α ↦ (x, y) ∉ s i := by simp [uniformSpace_eq_bot, h.mem_iff, subset_def, Pairwise, not_imp_not] theorem toTopologicalSpace_bot : @UniformSpace.toTopologicalSpace α ⊥ = ⊥ := rfl theorem toTopologicalSpace_top : @UniformSpace.toTopologicalSpace α ⊤ = ⊤ := rfl theorem toTopologicalSpace_iInf {ι : Sort*} {u : ι → UniformSpace α} : (iInf u).toTopologicalSpace = ⨅ i, (u i).toTopologicalSpace := TopologicalSpace.ext_nhds fun a ↦ by simp only [@nhds_eq_comap_uniformity _ (iInf u), nhds_iInf, iInf_uniformity, @nhds_eq_comap_uniformity _ (u _), Filter.comap_iInf] theorem toTopologicalSpace_sInf {s : Set (UniformSpace α)} : (sInf s).toTopologicalSpace = ⨅ i ∈ s, @UniformSpace.toTopologicalSpace α i := by rw [sInf_eq_iInf] simp only [← toTopologicalSpace_iInf] theorem toTopologicalSpace_inf {u v : UniformSpace α} : (u ⊓ v).toTopologicalSpace = u.toTopologicalSpace ⊓ v.toTopologicalSpace := rfl end UniformSpace theorem UniformContinuous.continuous [UniformSpace α] [UniformSpace β] {f : α → β} (hf : UniformContinuous f) : Continuous f := continuous_iff_le_induced.mpr <| UniformSpace.toTopologicalSpace_mono <| uniformContinuous_iff.1 hf /-- Uniform space structure on `ULift α`. -/ instance ULift.uniformSpace [UniformSpace α] : UniformSpace (ULift α) := UniformSpace.comap ULift.down ‹_› /-- Uniform space structure on `αᵒᵈ`. -/ instance OrderDual.instUniformSpace [UniformSpace α] : UniformSpace (αᵒᵈ) := ‹UniformSpace α› section UniformContinuousInfi -- TODO: add an `iff` lemma? theorem UniformContinuous.inf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ u₃ : UniformSpace β} (h₁ : UniformContinuous[u₁, u₂] f) (h₂ : UniformContinuous[u₁, u₃] f) : UniformContinuous[u₁, u₂ ⊓ u₃] f := tendsto_inf.mpr ⟨h₁, h₂⟩ theorem UniformContinuous.inf_dom_left {f : α → β} {u₁ u₂ : UniformSpace α} {u₃ : UniformSpace β} (hf : UniformContinuous[u₁, u₃] f) : UniformContinuous[u₁ ⊓ u₂, u₃] f := tendsto_inf_left hf theorem UniformContinuous.inf_dom_right {f : α → β} {u₁ u₂ : UniformSpace α} {u₃ : UniformSpace β} (hf : UniformContinuous[u₂, u₃] f) : UniformContinuous[u₁ ⊓ u₂, u₃] f := tendsto_inf_right hf theorem uniformContinuous_sInf_dom {f : α → β} {u₁ : Set (UniformSpace α)} {u₂ : UniformSpace β} {u : UniformSpace α} (h₁ : u ∈ u₁) (hf : UniformContinuous[u, u₂] f) : UniformContinuous[sInf u₁, u₂] f := by delta UniformContinuous rw [sInf_eq_iInf', iInf_uniformity] exact tendsto_iInf' ⟨u, h₁⟩ hf theorem uniformContinuous_sInf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ : Set (UniformSpace β)} : UniformContinuous[u₁, sInf u₂] f ↔ ∀ u ∈ u₂, UniformContinuous[u₁, u] f := by delta UniformContinuous rw [sInf_eq_iInf', iInf_uniformity, tendsto_iInf, SetCoe.forall] theorem uniformContinuous_iInf_dom {f : α → β} {u₁ : ι → UniformSpace α} {u₂ : UniformSpace β} {i : ι} (hf : UniformContinuous[u₁ i, u₂] f) : UniformContinuous[iInf u₁, u₂] f := by delta UniformContinuous rw [iInf_uniformity] exact tendsto_iInf' i hf theorem uniformContinuous_iInf_rng {f : α → β} {u₁ : UniformSpace α} {u₂ : ι → UniformSpace β} : UniformContinuous[u₁, iInf u₂] f ↔ ∀ i, UniformContinuous[u₁, u₂ i] f := by delta UniformContinuous rw [iInf_uniformity, tendsto_iInf] end UniformContinuousInfi /-- A uniform space with the discrete uniformity has the discrete topology. -/ theorem discreteTopology_of_discrete_uniformity [hα : UniformSpace α] (h : uniformity α = 𝓟 idRel) : DiscreteTopology α := ⟨(UniformSpace.ext h.symm : ⊥ = hα) ▸ rfl⟩ instance : UniformSpace Empty := ⊥ instance : UniformSpace PUnit := ⊥ instance : UniformSpace Bool := ⊥ instance : UniformSpace ℕ := ⊥ instance : UniformSpace ℤ := ⊥ section variable [UniformSpace α] open Additive Multiplicative instance : UniformSpace (Additive α) := ‹UniformSpace α› instance : UniformSpace (Multiplicative α) := ‹UniformSpace α› theorem uniformContinuous_ofMul : UniformContinuous (ofMul : α → Additive α) := uniformContinuous_id theorem uniformContinuous_toMul : UniformContinuous (toMul : Additive α → α) := uniformContinuous_id theorem uniformContinuous_ofAdd : UniformContinuous (ofAdd : α → Multiplicative α) := uniformContinuous_id theorem uniformContinuous_toAdd : UniformContinuous (toAdd : Multiplicative α → α) := uniformContinuous_id theorem uniformity_additive : 𝓤 (Additive α) = (𝓤 α).map (Prod.map ofMul ofMul) := rfl theorem uniformity_multiplicative : 𝓤 (Multiplicative α) = (𝓤 α).map (Prod.map ofAdd ofAdd) := rfl end instance instUniformSpaceSubtype {p : α → Prop} [t : UniformSpace α] : UniformSpace (Subtype p) := UniformSpace.comap Subtype.val t theorem uniformity_subtype {p : α → Prop} [UniformSpace α] : 𝓤 (Subtype p) = comap (fun q : Subtype p × Subtype p => (q.1.1, q.2.1)) (𝓤 α) := rfl theorem uniformity_setCoe {s : Set α} [UniformSpace α] : 𝓤 s = comap (Prod.map ((↑) : s → α) ((↑) : s → α)) (𝓤 α) := rfl theorem map_uniformity_set_coe {s : Set α} [UniformSpace α] : map (Prod.map (↑) (↑)) (𝓤 s) = 𝓤 α ⊓ 𝓟 (s ×ˢ s) := by rw [uniformity_setCoe, map_comap, range_prodMap, Subtype.range_val] theorem uniformContinuous_subtype_val {p : α → Prop} [UniformSpace α] : UniformContinuous (Subtype.val : { a : α // p a } → α) := uniformContinuous_comap theorem UniformContinuous.subtype_mk {p : α → Prop} [UniformSpace α] [UniformSpace β] {f : β → α} (hf : UniformContinuous f) (h : ∀ x, p (f x)) : UniformContinuous (fun x => ⟨f x, h x⟩ : β → Subtype p) := uniformContinuous_comap' hf theorem uniformContinuousOn_iff_restrict [UniformSpace α] [UniformSpace β] {f : α → β} {s : Set α} : UniformContinuousOn f s ↔ UniformContinuous (s.restrict f) := by delta UniformContinuousOn UniformContinuous rw [← map_uniformity_set_coe, tendsto_map'_iff]; rfl theorem tendsto_of_uniformContinuous_subtype [UniformSpace α] [UniformSpace β] {f : α → β} {s : Set α} {a : α} (hf : UniformContinuous fun x : s => f x.val) (ha : s ∈ 𝓝 a) : Tendsto f (𝓝 a) (𝓝 (f a)) := by rw [(@map_nhds_subtype_coe_eq_nhds α _ s a (mem_of_mem_nhds ha) ha).symm] exact tendsto_map' hf.continuous.continuousAt theorem UniformContinuousOn.continuousOn [UniformSpace α] [UniformSpace β] {f : α → β} {s : Set α} (h : UniformContinuousOn f s) : ContinuousOn f s := by rw [uniformContinuousOn_iff_restrict] at h rw [continuousOn_iff_continuous_restrict] exact h.continuous @[to_additive] instance [UniformSpace α] : UniformSpace αᵐᵒᵖ := UniformSpace.comap MulOpposite.unop ‹_› @[to_additive] theorem uniformity_mulOpposite [UniformSpace α] : 𝓤 αᵐᵒᵖ = comap (fun q : αᵐᵒᵖ × αᵐᵒᵖ => (q.1.unop, q.2.unop)) (𝓤 α) := rfl @[to_additive (attr := simp)] theorem comap_uniformity_mulOpposite [UniformSpace α] : comap (fun p : α × α => (MulOpposite.op p.1, MulOpposite.op p.2)) (𝓤 αᵐᵒᵖ) = 𝓤 α := by simpa [uniformity_mulOpposite, comap_comap, (· ∘ ·)] using comap_id namespace MulOpposite @[to_additive] theorem uniformContinuous_unop [UniformSpace α] : UniformContinuous (unop : αᵐᵒᵖ → α) := uniformContinuous_comap @[to_additive] theorem uniformContinuous_op [UniformSpace α] : UniformContinuous (op : α → αᵐᵒᵖ) := uniformContinuous_comap' uniformContinuous_id end MulOpposite section Prod open UniformSpace /- a similar product space is possible on the function space (uniformity of pointwise convergence), but we want to have the uniformity of uniform convergence on function spaces -/ instance instUniformSpaceProd [u₁ : UniformSpace α] [u₂ : UniformSpace β] : UniformSpace (α × β) := u₁.comap Prod.fst ⊓ u₂.comap Prod.snd -- check the above produces no diamond for `simp` and typeclass search example [UniformSpace α] [UniformSpace β] : (instTopologicalSpaceProd : TopologicalSpace (α × β)) = UniformSpace.toTopologicalSpace := by with_reducible_and_instances rfl theorem uniformity_prod [UniformSpace α] [UniformSpace β] : 𝓤 (α × β) = ((𝓤 α).comap fun p : (α × β) × α × β => (p.1.1, p.2.1)) ⊓ (𝓤 β).comap fun p : (α × β) × α × β => (p.1.2, p.2.2) := rfl instance [UniformSpace α] [IsCountablyGenerated (𝓤 α)] [UniformSpace β] [IsCountablyGenerated (𝓤 β)] : IsCountablyGenerated (𝓤 (α × β)) := by rw [uniformity_prod] infer_instance theorem uniformity_prod_eq_comap_prod [UniformSpace α] [UniformSpace β] : 𝓤 (α × β) = comap (fun p : (α × β) × α × β => ((p.1.1, p.2.1), (p.1.2, p.2.2))) (𝓤 α ×ˢ 𝓤 β) := by simp_rw [uniformity_prod, prod_eq_inf, Filter.comap_inf, Filter.comap_comap, Function.comp_def] theorem uniformity_prod_eq_prod [UniformSpace α] [UniformSpace β] : 𝓤 (α × β) = map (fun p : (α × α) × β × β => ((p.1.1, p.2.1), (p.1.2, p.2.2))) (𝓤 α ×ˢ 𝓤 β) := by rw [map_swap4_eq_comap, uniformity_prod_eq_comap_prod] theorem mem_uniformity_of_uniformContinuous_invariant [UniformSpace α] [UniformSpace β] {s : Set (β × β)} {f : α → α → β} (hf : UniformContinuous fun p : α × α => f p.1 p.2) (hs : s ∈ 𝓤 β) : ∃ u ∈ 𝓤 α, ∀ a b c, (a, b) ∈ u → (f a c, f b c) ∈ s := by rw [UniformContinuous, uniformity_prod_eq_prod, tendsto_map'_iff] at hf rcases mem_prod_iff.1 (mem_map.1 <| hf hs) with ⟨u, hu, v, hv, huvt⟩ exact ⟨u, hu, fun a b c hab => @huvt ((_, _), (_, _)) ⟨hab, refl_mem_uniformity hv⟩⟩ /-- An entourage of the diagonal in `α` and an entourage in `β` yield an entourage in `α × β` once we permute coordinates. -/ def entourageProd (u : Set (α × α)) (v : Set (β × β)) : Set ((α × β) × α × β) := {((a₁, b₁),(a₂, b₂)) | (a₁, a₂) ∈ u ∧ (b₁, b₂) ∈ v} theorem mem_entourageProd {u : Set (α × α)} {v : Set (β × β)} {p : (α × β) × α × β} : p ∈ entourageProd u v ↔ (p.1.1, p.2.1) ∈ u ∧ (p.1.2, p.2.2) ∈ v := Iff.rfl theorem entourageProd_mem_uniformity [t₁ : UniformSpace α] [t₂ : UniformSpace β] {u : Set (α × α)} {v : Set (β × β)} (hu : u ∈ 𝓤 α) (hv : v ∈ 𝓤 β) : entourageProd u v ∈ 𝓤 (α × β) := by rw [uniformity_prod]; exact inter_mem_inf (preimage_mem_comap hu) (preimage_mem_comap hv) theorem ball_entourageProd (u : Set (α × α)) (v : Set (β × β)) (x : α × β) : ball x (entourageProd u v) = ball x.1 u ×ˢ ball x.2 v := by ext p; simp only [ball, entourageProd, Set.mem_setOf_eq, Set.mem_prod, Set.mem_preimage] lemma IsSymmetricRel.entourageProd {u : Set (α × α)} {v : Set (β × β)} (hu : IsSymmetricRel u) (hv : IsSymmetricRel v) : IsSymmetricRel (entourageProd u v) := Set.ext fun _ ↦ and_congr hu.mk_mem_comm hv.mk_mem_comm theorem Filter.HasBasis.uniformity_prod {ιa ιb : Type*} [UniformSpace α] [UniformSpace β] {pa : ιa → Prop} {pb : ιb → Prop} {sa : ιa → Set (α × α)} {sb : ιb → Set (β × β)} (ha : (𝓤 α).HasBasis pa sa) (hb : (𝓤 β).HasBasis pb sb) : (𝓤 (α × β)).HasBasis (fun i : ιa × ιb ↦ pa i.1 ∧ pb i.2) (fun i ↦ entourageProd (sa i.1) (sb i.2)) := (ha.comap _).inf (hb.comap _) theorem entourageProd_subset [UniformSpace α] [UniformSpace β] {s : Set ((α × β) × α × β)} (h : s ∈ 𝓤 (α × β)) : ∃ u ∈ 𝓤 α, ∃ v ∈ 𝓤 β, entourageProd u v ⊆ s := by rcases (((𝓤 α).basis_sets.uniformity_prod (𝓤 β).basis_sets).mem_iff' s).1 h with ⟨w, hw⟩ use w.1, hw.1.1, w.2, hw.1.2, hw.2 theorem tendsto_prod_uniformity_fst [UniformSpace α] [UniformSpace β] : Tendsto (fun p : (α × β) × α × β => (p.1.1, p.2.1)) (𝓤 (α × β)) (𝓤 α) := le_trans (map_mono inf_le_left) map_comap_le theorem tendsto_prod_uniformity_snd [UniformSpace α] [UniformSpace β] : Tendsto (fun p : (α × β) × α × β => (p.1.2, p.2.2)) (𝓤 (α × β)) (𝓤 β) := le_trans (map_mono inf_le_right) map_comap_le theorem uniformContinuous_fst [UniformSpace α] [UniformSpace β] : UniformContinuous fun p : α × β => p.1 := tendsto_prod_uniformity_fst theorem uniformContinuous_snd [UniformSpace α] [UniformSpace β] : UniformContinuous fun p : α × β => p.2 := tendsto_prod_uniformity_snd variable [UniformSpace α] [UniformSpace β] [UniformSpace γ] theorem UniformContinuous.prodMk {f₁ : α → β} {f₂ : α → γ} (h₁ : UniformContinuous f₁) (h₂ : UniformContinuous f₂) : UniformContinuous fun a => (f₁ a, f₂ a) := by rw [UniformContinuous, uniformity_prod] exact tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩ @[deprecated (since := "2025-03-10")] alias UniformContinuous.prod_mk := UniformContinuous.prodMk theorem UniformContinuous.prodMk_left {f : α × β → γ} (h : UniformContinuous f) (b) : UniformContinuous fun a => f (a, b) := h.comp (uniformContinuous_id.prodMk uniformContinuous_const) @[deprecated (since := "2025-03-10")] alias UniformContinuous.prod_mk_left := UniformContinuous.prodMk_left theorem UniformContinuous.prodMk_right {f : α × β → γ} (h : UniformContinuous f) (a) : UniformContinuous fun b => f (a, b) := h.comp (uniformContinuous_const.prodMk uniformContinuous_id) @[deprecated (since := "2025-03-10")] alias UniformContinuous.prod_mk_right := UniformContinuous.prodMk_right theorem UniformContinuous.prodMap [UniformSpace δ] {f : α → γ} {g : β → δ} (hf : UniformContinuous f) (hg : UniformContinuous g) : UniformContinuous (Prod.map f g) := (hf.comp uniformContinuous_fst).prodMk (hg.comp uniformContinuous_snd) theorem toTopologicalSpace_prod {α} {β} [u : UniformSpace α] [v : UniformSpace β] : @UniformSpace.toTopologicalSpace (α × β) instUniformSpaceProd = @instTopologicalSpaceProd α β u.toTopologicalSpace v.toTopologicalSpace := rfl /-- A version of `UniformContinuous.inf_dom_left` for binary functions -/ theorem uniformContinuous_inf_dom_left₂ {α β γ} {f : α → β → γ} {ua1 ua2 : UniformSpace α} {ub1 ub2 : UniformSpace β} {uc1 : UniformSpace γ} (h : by haveI := ua1; haveI := ub1; exact UniformContinuous fun p : α × β => f p.1 p.2) : by haveI := ua1 ⊓ ua2; haveI := ub1 ⊓ ub2 exact UniformContinuous fun p : α × β => f p.1 p.2 := by -- proof essentially copied from `continuous_inf_dom_left₂` have ha := @UniformContinuous.inf_dom_left _ _ id ua1 ua2 ua1 (@uniformContinuous_id _ (id _)) have hb := @UniformContinuous.inf_dom_left _ _ id ub1 ub2 ub1 (@uniformContinuous_id _ (id _)) have h_unif_cont_id := @UniformContinuous.prodMap _ _ _ _ (ua1 ⊓ ua2) (ub1 ⊓ ub2) ua1 ub1 _ _ ha hb exact @UniformContinuous.comp _ _ _ (id _) (id _) _ _ _ h h_unif_cont_id /-- A version of `UniformContinuous.inf_dom_right` for binary functions -/ theorem uniformContinuous_inf_dom_right₂ {α β γ} {f : α → β → γ} {ua1 ua2 : UniformSpace α} {ub1 ub2 : UniformSpace β} {uc1 : UniformSpace γ} (h : by haveI := ua2; haveI := ub2; exact UniformContinuous fun p : α × β => f p.1 p.2) : by haveI := ua1 ⊓ ua2; haveI := ub1 ⊓ ub2 exact UniformContinuous fun p : α × β => f p.1 p.2 := by -- proof essentially copied from `continuous_inf_dom_right₂` have ha := @UniformContinuous.inf_dom_right _ _ id ua1 ua2 ua2 (@uniformContinuous_id _ (id _)) have hb := @UniformContinuous.inf_dom_right _ _ id ub1 ub2 ub2 (@uniformContinuous_id _ (id _)) have h_unif_cont_id := @UniformContinuous.prodMap _ _ _ _ (ua1 ⊓ ua2) (ub1 ⊓ ub2) ua2 ub2 _ _ ha hb exact @UniformContinuous.comp _ _ _ (id _) (id _) _ _ _ h h_unif_cont_id /-- A version of `uniformContinuous_sInf_dom` for binary functions -/ theorem uniformContinuous_sInf_dom₂ {α β γ} {f : α → β → γ} {uas : Set (UniformSpace α)} {ubs : Set (UniformSpace β)} {ua : UniformSpace α} {ub : UniformSpace β} {uc : UniformSpace γ} (ha : ua ∈ uas) (hb : ub ∈ ubs) (hf : UniformContinuous fun p : α × β => f p.1 p.2) : by haveI := sInf uas; haveI := sInf ubs exact @UniformContinuous _ _ _ uc fun p : α × β => f p.1 p.2 := by -- proof essentially copied from `continuous_sInf_dom` let _ : UniformSpace (α × β) := instUniformSpaceProd have ha := uniformContinuous_sInf_dom ha uniformContinuous_id have hb := uniformContinuous_sInf_dom hb uniformContinuous_id have h_unif_cont_id := @UniformContinuous.prodMap _ _ _ _ (sInf uas) (sInf ubs) ua ub _ _ ha hb exact @UniformContinuous.comp _ _ _ (id _) (id _) _ _ _ hf h_unif_cont_id end Prod section open UniformSpace Function variable {δ' : Type*} [UniformSpace α] [UniformSpace β] [UniformSpace γ] [UniformSpace δ] [UniformSpace δ'] local notation f " ∘₂ " g => Function.bicompr f g /-- Uniform continuity for functions of two variables. -/ def UniformContinuous₂ (f : α → β → γ) := UniformContinuous (uncurry f) theorem uniformContinuous₂_def (f : α → β → γ) : UniformContinuous₂ f ↔ UniformContinuous (uncurry f) := Iff.rfl theorem UniformContinuous₂.uniformContinuous {f : α → β → γ} (h : UniformContinuous₂ f) : UniformContinuous (uncurry f) := h theorem uniformContinuous₂_curry (f : α × β → γ) : UniformContinuous₂ (Function.curry f) ↔ UniformContinuous f := by rw [UniformContinuous₂, uncurry_curry] theorem UniformContinuous₂.comp {f : α → β → γ} {g : γ → δ} (hg : UniformContinuous g) (hf : UniformContinuous₂ f) : UniformContinuous₂ (g ∘₂ f) := hg.comp hf theorem UniformContinuous₂.bicompl {f : α → β → γ} {ga : δ → α} {gb : δ' → β} (hf : UniformContinuous₂ f) (hga : UniformContinuous ga) (hgb : UniformContinuous gb) : UniformContinuous₂ (bicompl f ga gb) := hf.uniformContinuous.comp (hga.prodMap hgb) end theorem toTopologicalSpace_subtype [u : UniformSpace α] {p : α → Prop} : @UniformSpace.toTopologicalSpace (Subtype p) instUniformSpaceSubtype = @instTopologicalSpaceSubtype α p u.toTopologicalSpace := rfl section Sum variable [UniformSpace α] [UniformSpace β] open Sum -- Obsolete auxiliary definitions and lemmas /-- Uniformity on a disjoint union. Entourages of the diagonal in the union are obtained by taking independently an entourage of the diagonal in the first part, and an entourage of the diagonal in the second part. -/ instance Sum.instUniformSpace : UniformSpace (α ⊕ β) where uniformity := map (fun p : α × α => (inl p.1, inl p.2)) (𝓤 α) ⊔ map (fun p : β × β => (inr p.1, inr p.2)) (𝓤 β) symm := fun _ hs ↦ ⟨symm_le_uniformity hs.1, symm_le_uniformity hs.2⟩ comp := fun s hs ↦ by rcases comp_mem_uniformity_sets hs.1 with ⟨tα, htα, Htα⟩ rcases comp_mem_uniformity_sets hs.2 with ⟨tβ, htβ, Htβ⟩ filter_upwards [mem_lift' (union_mem_sup (image_mem_map htα) (image_mem_map htβ))] rintro ⟨_, _⟩ ⟨z, ⟨⟨a, b⟩, hab, ⟨⟩⟩ | ⟨⟨a, b⟩, hab, ⟨⟩⟩, ⟨⟨_, c⟩, hbc, ⟨⟩⟩ | ⟨⟨_, c⟩, hbc, ⟨⟩⟩⟩ exacts [@Htα (_, _) ⟨b, hab, hbc⟩, @Htβ (_, _) ⟨b, hab, hbc⟩] nhds_eq_comap_uniformity x := by ext cases x <;> simp [mem_comap', -mem_comap, nhds_inl, nhds_inr, nhds_eq_comap_uniformity, Prod.ext_iff] /-- The union of an entourage of the diagonal in each set of a disjoint union is again an entourage of the diagonal. -/ theorem union_mem_uniformity_sum {a : Set (α × α)} (ha : a ∈ 𝓤 α) {b : Set (β × β)} (hb : b ∈ 𝓤 β) : Prod.map inl inl '' a ∪ Prod.map inr inr '' b ∈ 𝓤 (α ⊕ β) := union_mem_sup (image_mem_map ha) (image_mem_map hb) theorem Sum.uniformity : 𝓤 (α ⊕ β) = map (Prod.map inl inl) (𝓤 α) ⊔ map (Prod.map inr inr) (𝓤 β) := rfl lemma uniformContinuous_inl : UniformContinuous (Sum.inl : α → α ⊕ β) := le_sup_left lemma uniformContinuous_inr : UniformContinuous (Sum.inr : β → α ⊕ β) := le_sup_right instance [IsCountablyGenerated (𝓤 α)] [IsCountablyGenerated (𝓤 β)] : IsCountablyGenerated (𝓤 (α ⊕ β)) := by rw [Sum.uniformity] infer_instance end Sum end Constructions /-! ### Expressing continuity properties in uniform spaces We reformulate the various continuity properties of functions taking values in a uniform space in terms of the uniformity in the target. Since the same lemmas (essentially with the same names) also exist for metric spaces and emetric spaces (reformulating things in terms of the distance or the edistance in the target), we put them in a namespace `Uniform` here. In the metric and emetric space setting, there are also similar lemmas where one assumes that both the source and the target are metric spaces, reformulating things in terms of the distance on both sides. These lemmas are generally written without primes, and the versions where only the target is a metric space is primed. We follow the same convention here, thus giving lemmas with primes. -/ namespace Uniform variable [UniformSpace α] theorem tendsto_nhds_right {f : Filter β} {u : β → α} {a : α} : Tendsto u f (𝓝 a) ↔ Tendsto (fun x => (a, u x)) f (𝓤 α) := by rw [nhds_eq_comap_uniformity, tendsto_comap_iff]; rfl theorem tendsto_nhds_left {f : Filter β} {u : β → α} {a : α} : Tendsto u f (𝓝 a) ↔ Tendsto (fun x => (u x, a)) f (𝓤 α) := by rw [nhds_eq_comap_uniformity', tendsto_comap_iff]; rfl theorem continuousAt_iff'_right [TopologicalSpace β] {f : β → α} {b : β} : ContinuousAt f b ↔ Tendsto (fun x => (f b, f x)) (𝓝 b) (𝓤 α) := by rw [ContinuousAt, tendsto_nhds_right] theorem continuousAt_iff'_left [TopologicalSpace β] {f : β → α} {b : β} : ContinuousAt f b ↔ Tendsto (fun x => (f x, f b)) (𝓝 b) (𝓤 α) := by rw [ContinuousAt, tendsto_nhds_left] theorem continuousAt_iff_prod [TopologicalSpace β] {f : β → α} {b : β} : ContinuousAt f b ↔ Tendsto (fun x : β × β => (f x.1, f x.2)) (𝓝 (b, b)) (𝓤 α) := ⟨fun H => le_trans (H.prodMap' H) (nhds_le_uniformity _), fun H => continuousAt_iff'_left.2 <| H.comp <| tendsto_id.prodMk_nhds tendsto_const_nhds⟩ theorem continuousWithinAt_iff'_right [TopologicalSpace β] {f : β → α} {b : β} {s : Set β} : ContinuousWithinAt f s b ↔ Tendsto (fun x => (f b, f x)) (𝓝[s] b) (𝓤 α) := by rw [ContinuousWithinAt, tendsto_nhds_right] theorem continuousWithinAt_iff'_left [TopologicalSpace β] {f : β → α} {b : β} {s : Set β} : ContinuousWithinAt f s b ↔ Tendsto (fun x => (f x, f b)) (𝓝[s] b) (𝓤 α) := by rw [ContinuousWithinAt, tendsto_nhds_left] theorem continuousOn_iff'_right [TopologicalSpace β] {f : β → α} {s : Set β} : ContinuousOn f s ↔ ∀ b ∈ s, Tendsto (fun x => (f b, f x)) (𝓝[s] b) (𝓤 α) := by simp [ContinuousOn, continuousWithinAt_iff'_right] theorem continuousOn_iff'_left [TopologicalSpace β] {f : β → α} {s : Set β} : ContinuousOn f s ↔ ∀ b ∈ s, Tendsto (fun x => (f x, f b)) (𝓝[s] b) (𝓤 α) := by simp [ContinuousOn, continuousWithinAt_iff'_left] theorem continuous_iff'_right [TopologicalSpace β] {f : β → α} : Continuous f ↔ ∀ b, Tendsto (fun x => (f b, f x)) (𝓝 b) (𝓤 α) := continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds_right theorem continuous_iff'_left [TopologicalSpace β] {f : β → α} : Continuous f ↔ ∀ b, Tendsto (fun x => (f x, f b)) (𝓝 b) (𝓤 α) := continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds_left /-- Consider two functions `f` and `g` which coincide on a set `s` and are continuous there. Then there is an open neighborhood of `s` on which `f` and `g` are uniformly close. -/ lemma exists_is_open_mem_uniformity_of_forall_mem_eq [TopologicalSpace β] {r : Set (α × α)} {s : Set β} {f g : β → α} (hf : ∀ x ∈ s, ContinuousAt f x) (hg : ∀ x ∈ s, ContinuousAt g x) (hfg : s.EqOn f g) (hr : r ∈ 𝓤 α) : ∃ t, IsOpen t ∧ s ⊆ t ∧ ∀ x ∈ t, (f x, g x) ∈ r := by have A : ∀ x ∈ s, ∃ t, IsOpen t ∧ x ∈ t ∧ ∀ z ∈ t, (f z, g z) ∈ r := by intro x hx obtain ⟨t, ht, htsymm, htr⟩ := comp_symm_mem_uniformity_sets hr have A : {z | (f x, f z) ∈ t} ∈ 𝓝 x := (hf x hx).preimage_mem_nhds (mem_nhds_left (f x) ht) have B : {z | (g x, g z) ∈ t} ∈ 𝓝 x := (hg x hx).preimage_mem_nhds (mem_nhds_left (g x) ht) rcases _root_.mem_nhds_iff.1 (inter_mem A B) with ⟨u, hu, u_open, xu⟩ refine ⟨u, u_open, xu, fun y hy ↦ ?_⟩ have I1 : (f y, f x) ∈ t := (htsymm.mk_mem_comm).2 (hu hy).1 have I2 : (g x, g y) ∈ t := (hu hy).2 rw [hfg hx] at I1 exact htr (prodMk_mem_compRel I1 I2) choose! t t_open xt ht using A refine ⟨⋃ x ∈ s, t x, isOpen_biUnion t_open, fun x hx ↦ mem_biUnion hx (xt x hx), ?_⟩ rintro x hx simp only [mem_iUnion, exists_prop] at hx rcases hx with ⟨y, ys, hy⟩ exact ht y ys x hy end Uniform theorem Filter.Tendsto.congr_uniformity {α β} [UniformSpace β] {f g : α → β} {l : Filter α} {b : β} (hf : Tendsto f l (𝓝 b)) (hg : Tendsto (fun x => (f x, g x)) l (𝓤 β)) : Tendsto g l (𝓝 b) := Uniform.tendsto_nhds_right.2 <| (Uniform.tendsto_nhds_right.1 hf).uniformity_trans hg theorem Uniform.tendsto_congr {α β} [UniformSpace β] {f g : α → β} {l : Filter α} {b : β} (hfg : Tendsto (fun x => (f x, g x)) l (𝓤 β)) : Tendsto f l (𝓝 b) ↔ Tendsto g l (𝓝 b) := ⟨fun h => h.congr_uniformity hfg, fun h => h.congr_uniformity hfg.uniformity_symm⟩
Mathlib/Topology/UniformSpace/Basic.lean
1,960
1,962
/- 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 /-! # 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 /-- The type of angles -/ def Angle : Type := AddCircle (2 * π) -- The `NormedAddCommGroup, Inhabited` instances should be constructed by a deriving handler. -- https://github.com/leanprover-community/mathlib4/issues/380 namespace Angle instance : NormedAddCommGroup Angle := inferInstanceAs (NormedAddCommGroup (AddCircle (2 * π))) instance : Inhabited Angle := inferInstanceAs (Inhabited (AddCircle (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' /-- Coercion `ℝ → Angle` as an additive homomorphism. -/ def coeHom : ℝ →+ Angle := QuotientAddGroup.mk' _ @[simp] theorem coe_coeHom : (coeHom : ℝ → Angle) = ((↑) : ℝ → Angle) := rfl /-- 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 @[simp] theorem coe_zero : ↑(0 : ℝ) = (0 : Angle) := rfl @[simp] theorem coe_add (x y : ℝ) : ↑(x + y : ℝ) = (↑x + ↑y : Angle) := rfl @[simp] theorem coe_neg (x : ℝ) : ↑(-x : ℝ) = -(↑x : Angle) := rfl @[simp] theorem coe_sub (x y : ℝ) : ↑(x - y : ℝ) = (↑x - ↑y : Angle) := rfl theorem coe_nsmul (n : ℕ) (x : ℝ) : ↑(n • x : ℝ) = n • (↑x : Angle) := rfl theorem coe_zsmul (z : ℤ) (x : ℝ) : ↑(z • x : ℝ) = z • (↑x : Angle) := rfl theorem coe_eq_zero_iff {x : ℝ} : (x : Angle) = 0 ↔ ∃ n : ℤ, n • (2 * π) = x := AddCircle.coe_eq_zero_iff (2 * π) @[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 @[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 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] 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]
@[simp] theorem coe_two_pi : ↑(2 * π : ℝ) = (0 : Angle) :=
Mathlib/Analysis/SpecialFunctions/Trigonometric/Angle.lean
107
108
/- 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.Option import Mathlib.Analysis.BoxIntegral.Box.Basic import Mathlib.Data.Set.Pairwise.Lattice /-! # Partitions of rectangular boxes in `ℝⁿ` In this file we define (pre)partitions of rectangular boxes in `ℝⁿ`. A partition of a box `I` in `ℝⁿ` (see `BoxIntegral.Prepartition` and `BoxIntegral.Prepartition.IsPartition`) is a finite set of pairwise disjoint boxes such that their union is exactly `I`. We use `boxes : Finset (Box ι)` to store the set of boxes. Many lemmas about box integrals deal with pairwise disjoint collections of subboxes, so we define a structure `BoxIntegral.Prepartition (I : BoxIntegral.Box ι)` that stores a collection of boxes such that * each box `J ∈ boxes` is a subbox of `I`; * the boxes are pairwise disjoint as sets in `ℝⁿ`. Then we define a predicate `BoxIntegral.Prepartition.IsPartition`; `π.IsPartition` means that the boxes of `π` actually cover the whole `I`. We also define some operations on prepartitions: * `BoxIntegral.Prepartition.biUnion`: split each box of a partition into smaller boxes; * `BoxIntegral.Prepartition.restrict`: restrict a partition to a smaller box. We also define a `SemilatticeInf` structure on `BoxIntegral.Prepartition I` for all `I : BoxIntegral.Box ι`. ## Tags rectangular box, partition -/ open Set Finset Function open scoped NNReal noncomputable section namespace BoxIntegral variable {ι : Type*} /-- A prepartition of `I : BoxIntegral.Box ι` is a finite set of pairwise disjoint subboxes of `I`. -/ structure Prepartition (I : Box ι) where /-- The underlying set of boxes -/ boxes : Finset (Box ι) /-- Each box is a sub-box of `I` -/ le_of_mem' : ∀ J ∈ boxes, J ≤ I /-- The boxes in a prepartition are pairwise disjoint. -/ pairwiseDisjoint : Set.Pairwise (↑boxes) (Disjoint on ((↑) : Box ι → Set (ι → ℝ))) namespace Prepartition variable {I J J₁ J₂ : Box ι} (π : Prepartition I) {π₁ π₂ : Prepartition I} {x : ι → ℝ} instance : Membership (Box ι) (Prepartition I) := ⟨fun π J => J ∈ π.boxes⟩ @[simp] theorem mem_boxes : J ∈ π.boxes ↔ J ∈ π := Iff.rfl @[simp] theorem mem_mk {s h₁ h₂} : J ∈ (mk s h₁ h₂ : Prepartition I) ↔ J ∈ s := Iff.rfl theorem disjoint_coe_of_mem (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (h : J₁ ≠ J₂) : Disjoint (J₁ : Set (ι → ℝ)) J₂ := π.pairwiseDisjoint h₁ h₂ h theorem eq_of_mem_of_mem (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (hx₁ : x ∈ J₁) (hx₂ : x ∈ J₂) : J₁ = J₂ := by_contra fun H => (π.disjoint_coe_of_mem h₁ h₂ H).le_bot ⟨hx₁, hx₂⟩ theorem eq_of_le_of_le (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (hle₁ : J ≤ J₁) (hle₂ : J ≤ J₂) : J₁ = J₂ := π.eq_of_mem_of_mem h₁ h₂ (hle₁ J.upper_mem) (hle₂ J.upper_mem) theorem eq_of_le (h₁ : J₁ ∈ π) (h₂ : J₂ ∈ π) (hle : J₁ ≤ J₂) : J₁ = J₂ := π.eq_of_le_of_le h₁ h₂ le_rfl hle theorem le_of_mem (hJ : J ∈ π) : J ≤ I := π.le_of_mem' J hJ theorem lower_le_lower (hJ : J ∈ π) : I.lower ≤ J.lower := Box.antitone_lower (π.le_of_mem hJ) theorem upper_le_upper (hJ : J ∈ π) : J.upper ≤ I.upper := Box.monotone_upper (π.le_of_mem hJ) theorem injective_boxes : Function.Injective (boxes : Prepartition I → Finset (Box ι)) := by rintro ⟨s₁, h₁, h₁'⟩ ⟨s₂, h₂, h₂'⟩ (rfl : s₁ = s₂) rfl @[ext] theorem ext (h : ∀ J, J ∈ π₁ ↔ J ∈ π₂) : π₁ = π₂ := injective_boxes <| Finset.ext h /-- The singleton prepartition `{J}`, `J ≤ I`. -/ @[simps] def single (I J : Box ι) (h : J ≤ I) : Prepartition I := ⟨{J}, by simpa, by simp⟩ @[simp] theorem mem_single {J'} (h : J ≤ I) : J' ∈ single I J h ↔ J' = J := mem_singleton /-- We say that `π ≤ π'` if each box of `π` is a subbox of some box of `π'`. -/ instance : LE (Prepartition I) := ⟨fun π π' => ∀ ⦃I⦄, I ∈ π → ∃ I' ∈ π', I ≤ I'⟩ instance partialOrder : PartialOrder (Prepartition I) where le := (· ≤ ·) le_refl _ I hI := ⟨I, hI, le_rfl⟩ le_trans _ _ _ h₁₂ h₂₃ _ hI₁ := let ⟨_, hI₂, hI₁₂⟩ := h₁₂ hI₁ let ⟨I₃, hI₃, hI₂₃⟩ := h₂₃ hI₂ ⟨I₃, hI₃, hI₁₂.trans hI₂₃⟩ le_antisymm := by suffices ∀ {π₁ π₂ : Prepartition I}, π₁ ≤ π₂ → π₂ ≤ π₁ → π₁.boxes ⊆ π₂.boxes from fun π₁ π₂ h₁ h₂ => injective_boxes (Subset.antisymm (this h₁ h₂) (this h₂ h₁)) intro π₁ π₂ h₁ h₂ J hJ rcases h₁ hJ with ⟨J', hJ', hle⟩; rcases h₂ hJ' with ⟨J'', hJ'', hle'⟩ obtain rfl : J = J'' := π₁.eq_of_le hJ hJ'' (hle.trans hle') obtain rfl : J' = J := le_antisymm ‹_› ‹_› assumption instance : OrderTop (Prepartition I) where top := single I I le_rfl le_top π _ hJ := ⟨I, by simp, π.le_of_mem hJ⟩ instance : OrderBot (Prepartition I) where bot := ⟨∅, fun _ hJ => (Finset.not_mem_empty _ hJ).elim, fun _ hJ => (Set.not_mem_empty _ <| Finset.coe_empty ▸ hJ).elim⟩ bot_le _ _ hJ := (Finset.not_mem_empty _ hJ).elim instance : Inhabited (Prepartition I) := ⟨⊤⟩ theorem le_def : π₁ ≤ π₂ ↔ ∀ J ∈ π₁, ∃ J' ∈ π₂, J ≤ J' := Iff.rfl @[simp] theorem mem_top : J ∈ (⊤ : Prepartition I) ↔ J = I := mem_singleton @[simp] theorem top_boxes : (⊤ : Prepartition I).boxes = {I} := rfl @[simp] theorem not_mem_bot : J ∉ (⊥ : Prepartition I) := Finset.not_mem_empty _ @[simp] theorem bot_boxes : (⊥ : Prepartition I).boxes = ∅ := rfl /-- An auxiliary lemma used to prove that the same point can't belong to more than `2 ^ Fintype.card ι` closed boxes of a prepartition. -/ theorem injOn_setOf_mem_Icc_setOf_lower_eq (x : ι → ℝ) : InjOn (fun J : Box ι => { i | J.lower i = x i }) { J | J ∈ π ∧ x ∈ Box.Icc J } := by rintro J₁ ⟨h₁, hx₁⟩ J₂ ⟨h₂, hx₂⟩ (H : { i | J₁.lower i = x i } = { i | J₂.lower i = x i }) suffices ∀ i, (Ioc (J₁.lower i) (J₁.upper i) ∩ Ioc (J₂.lower i) (J₂.upper i)).Nonempty by choose y hy₁ hy₂ using this exact π.eq_of_mem_of_mem h₁ h₂ hy₁ hy₂ intro i simp only [Set.ext_iff, mem_setOf] at H rcases (hx₁.1 i).eq_or_lt with hi₁ | hi₁ · have hi₂ : J₂.lower i = x i := (H _).1 hi₁ have H₁ : x i < J₁.upper i := by simpa only [hi₁] using J₁.lower_lt_upper i have H₂ : x i < J₂.upper i := by simpa only [hi₂] using J₂.lower_lt_upper i rw [Set.Ioc_inter_Ioc, hi₁, hi₂, sup_idem, Set.nonempty_Ioc] exact lt_min H₁ H₂ · have hi₂ : J₂.lower i < x i := (hx₂.1 i).lt_of_ne (mt (H _).2 hi₁.ne) exact ⟨x i, ⟨hi₁, hx₁.2 i⟩, ⟨hi₂, hx₂.2 i⟩⟩ open scoped Classical in /-- The set of boxes of a prepartition that contain `x` in their closures has cardinality at most `2 ^ Fintype.card ι`. -/ theorem card_filter_mem_Icc_le [Fintype ι] (x : ι → ℝ) : #{J ∈ π.boxes | x ∈ Box.Icc J} ≤ 2 ^ Fintype.card ι := by rw [← Fintype.card_set] refine Finset.card_le_card_of_injOn (fun J : Box ι => { i | J.lower i = x i }) (fun _ _ => Finset.mem_univ _) ?_ simpa using π.injOn_setOf_mem_Icc_setOf_lower_eq x /-- Given a prepartition `π : BoxIntegral.Prepartition I`, `π.iUnion` is the part of `I` covered by the boxes of `π`. -/ protected def iUnion : Set (ι → ℝ) := ⋃ J ∈ π, ↑J theorem iUnion_def : π.iUnion = ⋃ J ∈ π, ↑J := rfl theorem iUnion_def' : π.iUnion = ⋃ J ∈ π.boxes, ↑J := rfl -- Porting note: Previous proof was `:= Set.mem_iUnion₂` @[simp] theorem mem_iUnion : x ∈ π.iUnion ↔ ∃ J ∈ π, x ∈ J := by convert Set.mem_iUnion₂ rw [Box.mem_coe, exists_prop] @[simp] theorem iUnion_single (h : J ≤ I) : (single I J h).iUnion = J := by simp [iUnion_def] @[simp] theorem iUnion_top : (⊤ : Prepartition I).iUnion = I := by simp [Prepartition.iUnion] @[simp] theorem iUnion_eq_empty : π₁.iUnion = ∅ ↔ π₁ = ⊥ := by simp [← injective_boxes.eq_iff, Finset.ext_iff, Prepartition.iUnion, imp_false] @[simp] theorem iUnion_bot : (⊥ : Prepartition I).iUnion = ∅ := iUnion_eq_empty.2 rfl theorem subset_iUnion (h : J ∈ π) : ↑J ⊆ π.iUnion := subset_biUnion_of_mem h theorem iUnion_subset : π.iUnion ⊆ I := iUnion₂_subset π.le_of_mem' @[mono] theorem iUnion_mono (h : π₁ ≤ π₂) : π₁.iUnion ⊆ π₂.iUnion := fun _ hx => let ⟨_, hJ₁, hx⟩ := π₁.mem_iUnion.1 hx let ⟨J₂, hJ₂, hle⟩ := h hJ₁ π₂.mem_iUnion.2 ⟨J₂, hJ₂, hle hx⟩ theorem disjoint_boxes_of_disjoint_iUnion (h : Disjoint π₁.iUnion π₂.iUnion) : Disjoint π₁.boxes π₂.boxes := Finset.disjoint_left.2 fun J h₁ h₂ => Disjoint.le_bot (h.mono (π₁.subset_iUnion h₁) (π₂.subset_iUnion h₂)) ⟨J.upper_mem, J.upper_mem⟩ theorem le_iff_nonempty_imp_le_and_iUnion_subset : π₁ ≤ π₂ ↔ (∀ J ∈ π₁, ∀ J' ∈ π₂, (J ∩ J' : Set (ι → ℝ)).Nonempty → J ≤ J') ∧ π₁.iUnion ⊆ π₂.iUnion := by constructor · refine fun H => ⟨fun J hJ J' hJ' Hne => ?_, iUnion_mono H⟩ rcases H hJ with ⟨J'', hJ'', Hle⟩ rcases Hne with ⟨x, hx, hx'⟩ rwa [π₂.eq_of_mem_of_mem hJ' hJ'' hx' (Hle hx)] · rintro ⟨H, HU⟩ J hJ simp only [Set.subset_def, mem_iUnion] at HU rcases HU J.upper ⟨J, hJ, J.upper_mem⟩ with ⟨J₂, hJ₂, hx⟩ exact ⟨J₂, hJ₂, H _ hJ _ hJ₂ ⟨_, J.upper_mem, hx⟩⟩ theorem eq_of_boxes_subset_iUnion_superset (h₁ : π₁.boxes ⊆ π₂.boxes) (h₂ : π₂.iUnion ⊆ π₁.iUnion) : π₁ = π₂ := le_antisymm (fun J hJ => ⟨J, h₁ hJ, le_rfl⟩) <| le_iff_nonempty_imp_le_and_iUnion_subset.2 ⟨fun _ hJ₁ _ hJ₂ Hne => (π₂.eq_of_mem_of_mem hJ₁ (h₁ hJ₂) Hne.choose_spec.1 Hne.choose_spec.2).le, h₂⟩ open scoped Classical in /-- Given a prepartition `π` of a box `I` and a collection of prepartitions `πi J` of all boxes `J ∈ π`, returns the prepartition of `I` into the union of the boxes of all `πi J`. Though we only use the values of `πi` on the boxes of `π`, we require `πi` to be a globally defined function. -/ @[simps] def biUnion (πi : ∀ J : Box ι, Prepartition J) : Prepartition I where boxes := π.boxes.biUnion fun J => (πi J).boxes le_of_mem' J hJ := by simp only [Finset.mem_biUnion, exists_prop, mem_boxes] at hJ rcases hJ with ⟨J', hJ', hJ⟩ exact ((πi J').le_of_mem hJ).trans (π.le_of_mem hJ') pairwiseDisjoint := by simp only [Set.Pairwise, Finset.mem_coe, Finset.mem_biUnion] rintro J₁' ⟨J₁, hJ₁, hJ₁'⟩ J₂' ⟨J₂, hJ₂, hJ₂'⟩ Hne rw [Function.onFun, Set.disjoint_left]
rintro x hx₁ hx₂; apply Hne obtain rfl : J₁ = J₂ := π.eq_of_mem_of_mem hJ₁ hJ₂ ((πi J₁).le_of_mem hJ₁' hx₁) ((πi J₂).le_of_mem hJ₂' hx₂) exact (πi J₁).eq_of_mem_of_mem hJ₁' hJ₂' hx₁ hx₂ variable {πi πi₁ πi₂ : ∀ J : Box ι, Prepartition J} @[simp] theorem mem_biUnion : J ∈ π.biUnion πi ↔ ∃ J' ∈ π, J ∈ πi J' := by simp [biUnion] theorem biUnion_le (πi : ∀ J, Prepartition J) : π.biUnion πi ≤ π := fun _ hJ => let ⟨J', hJ', hJ⟩ := π.mem_biUnion.1 hJ
Mathlib/Analysis/BoxIntegral/Partition/Basic.lean
270
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/- Copyright (c) 2015 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro -/ import Mathlib.Data.Finset.Attach import Mathlib.Data.Finset.Disjoint import Mathlib.Data.Finset.Erase import Mathlib.Data.Finset.Filter import Mathlib.Data.Finset.Range import Mathlib.Data.Finset.SDiff import Mathlib.Data.Multiset.Basic import Mathlib.Logic.Equiv.Set import Mathlib.Order.Directed import Mathlib.Order.Interval.Set.Defs import Mathlib.Data.Set.SymmDiff /-! # Basic lemmas on finite sets This file contains lemmas on the interaction of various definitions on the `Finset` type. For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`. ## Main declarations ### Main definitions * `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate. ### Equivalences between finsets * The `Mathlib/Logic/Equiv/Defs.lean` file describes a general type of equivalence, so look in there for any lemmas. There is some API for rewriting sums and products from `s` to `t` given that `s ≃ t`. TODO: examples ## Tags finite sets, finset -/ -- Assert that we define `Finset` without the material on `List.sublists`. -- Note that we cannot use `List.sublists` itself as that is defined very early. assert_not_exists List.sublistsLen Multiset.powerset CompleteLattice Monoid open Multiset Subtype Function universe u variable {α : Type*} {β : Type*} {γ : Type*} namespace Finset -- TODO: these should be global attributes, but this will require fixing other files attribute [local trans] Subset.trans Superset.trans set_option linter.deprecated false in @[deprecated "Deprecated without replacement." (since := "2025-02-07")] theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) : SizeOf.sizeOf x < SizeOf.sizeOf s := by cases s dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf] rw [Nat.add_comm] refine lt_trans ?_ (Nat.lt_succ_self _) exact Multiset.sizeOf_lt_sizeOf_of_mem hx /-! ### Lattice structure -/ section Lattice variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α} /-! #### union -/ @[simp] theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t := ext fun a => by simp @[simp] theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by simp only [disjoint_left, mem_union, or_imp, forall_and] @[simp] theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by simp only [disjoint_right, mem_union, or_imp, forall_and] /-! #### inter -/ theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty := not_disjoint_iff.trans <| by simp [Finset.Nonempty] alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by rw [← not_disjoint_iff_nonempty_inter] exact em _ omit [DecidableEq α] in theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) : Disjoint s t ↔ s = ∅ := disjoint_of_le_iff_left_eq_bot h lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} : s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _), not_disjoint_iff_nonempty_inter] end Lattice instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le /-! ### erase -/ section Erase variable [DecidableEq α] {s t u v : Finset α} {a b : α} @[simp] theorem erase_empty (a : α) : erase ∅ a = ∅ := rfl protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty := (hs.exists_ne a).imp <| by aesop @[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)] refine ⟨?_, fun hs ↦ hs.exists_ne a⟩ rintro ⟨b, hb, hba⟩ exact ⟨_, hb, _, ha, hba⟩ @[simp] theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by ext x simp @[simp] theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a := ext fun x => by simp +contextual only [mem_erase, mem_insert, and_congr_right_iff, false_or, iff_self, imp_true_iff] theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by rw [erase_insert_eq_erase, erase_eq_of_not_mem h] theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) : erase (insert a s) b = insert a (erase s b) := ext fun x => by have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h simp only [mem_erase, mem_insert, and_or_left, this] theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) : erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by simp only [cons_eq_insert, erase_insert_of_ne hb] @[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s := ext fun x => by simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and] apply or_iff_right_of_imp rintro rfl exact h lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by aesop lemma insert_erase_invOn : Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} := ⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩ theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s := calc s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _ _ = _ := insert_erase h theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩ obtain ⟨a, ht, hs⟩ := not_subset.1 h.2 exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩ theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s := ssubset_iff_exists_subset_erase.2 ⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩ theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h] theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp] exact forall_congr' fun x => forall_swap theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s := subset_insert_iff.1 <| Subset.rfl theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) := subset_insert_iff.2 <| Subset.rfl theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by rw [subset_insert_iff, erase_eq_of_not_mem h] theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by rw [← subset_insert_iff, insert_eq_of_mem h] theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a := fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h] end Erase lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) : ∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by classical obtain ⟨a, ha, b, hb, hab⟩ := hs have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩ refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;> simp [insert_erase this, insert_erase ha, *] /-! ### sdiff -/ section Sdiff variable [DecidableEq α] {s t u v : Finset α} {a b : α} lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by ext; aesop -- TODO: Do we want to delete this lemma and `Finset.disjUnion_singleton`, -- or instead add `Finset.union_singleton`/`Finset.singleton_union`? theorem sdiff_singleton_eq_erase (a : α) (s : Finset α) : s \ {a} = erase s a := by ext rw [mem_erase, mem_sdiff, mem_singleton, and_comm] -- This lemma matches `Finset.insert_eq` in functionality. theorem erase_eq (s : Finset α) (a : α) : s.erase a = s \ {a} := (sdiff_singleton_eq_erase _ _).symm theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by simp_rw [erase_eq, disjoint_sdiff_comm] lemma disjoint_insert_erase (ha : a ∉ t) : Disjoint (s.erase a) (insert a t) ↔ Disjoint s t := by rw [disjoint_erase_comm, erase_insert ha] lemma disjoint_erase_insert (ha : a ∉ s) : Disjoint (insert a s) (t.erase a) ↔ Disjoint s t := by rw [← disjoint_erase_comm, erase_insert ha] theorem disjoint_of_erase_left (ha : a ∉ t) (hst : Disjoint (s.erase a) t) : Disjoint s t := by rw [← erase_insert ha, ← disjoint_erase_comm, disjoint_insert_right] exact ⟨not_mem_erase _ _, hst⟩ theorem disjoint_of_erase_right (ha : a ∉ s) (hst : Disjoint s (t.erase a)) : Disjoint s t := by rw [← erase_insert ha, disjoint_erase_comm, disjoint_insert_left] exact ⟨not_mem_erase _ _, hst⟩ theorem inter_erase (a : α) (s t : Finset α) : s ∩ t.erase a = (s ∩ t).erase a := by simp only [erase_eq, inter_sdiff_assoc] @[simp] theorem erase_inter (a : α) (s t : Finset α) : s.erase a ∩ t = (s ∩ t).erase a := by simpa only [inter_comm t] using inter_erase a t s theorem erase_sdiff_comm (s t : Finset α) (a : α) : s.erase a \ t = (s \ t).erase a := by simp_rw [erase_eq, sdiff_right_comm] theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by rw [erase_inter, inter_erase] theorem erase_union_distrib (s t : Finset α) (a : α) : (s ∪ t).erase a = s.erase a ∪ t.erase a := by simp_rw [erase_eq, union_sdiff_distrib] theorem insert_inter_distrib (s t : Finset α) (a : α) : insert a (s ∩ t) = insert a s ∩ insert a t := by simp_rw [insert_eq, union_inter_distrib_left] theorem erase_sdiff_distrib (s t : Finset α) (a : α) : (s \ t).erase a = s.erase a \ t.erase a := by simp_rw [erase_eq, sdiff_sdiff, sup_sdiff_eq_sup le_rfl, sup_comm] theorem erase_union_of_mem (ha : a ∈ t) (s : Finset α) : s.erase a ∪ t = s ∪ t := by rw [← insert_erase (mem_union_right s ha), erase_union_distrib, ← union_insert, insert_erase ha] theorem union_erase_of_mem (ha : a ∈ s) (t : Finset α) : s ∪ t.erase a = s ∪ t := by rw [← insert_erase (mem_union_left t ha), erase_union_distrib, ← insert_union, insert_erase ha] theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)] theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib, inter_comm] theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) : insert x (s \ insert x t) = s \ t := by rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)] theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq, union_comm] theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq] theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff] --TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra` theorem sdiff_disjoint : Disjoint (t \ s) s := disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2 theorem disjoint_sdiff : Disjoint s (t \ s) := sdiff_disjoint.symm theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) := disjoint_of_subset_right inter_subset_right sdiff_disjoint end Sdiff /-! ### attach -/ @[simp] theorem attach_empty : attach (∅ : Finset α) = ∅ := rfl @[simp] theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by simp [Finset.Nonempty] @[aesop safe apply (rule_sets := [finsetNonempty])] protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff @[simp] theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by simp [eq_empty_iff_forall_not_mem] /-! ### filter -/ section Filter variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α} theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by classical ext x simp only [mem_singleton, forall_eq, mem_filter] split_ifs with h <;> by_cases h' : x = a <;> simp [h, h'] theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) : filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) := eq_of_veq <| Multiset.filter_cons_of_pos s.val hp theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) : filter p (cons a s ha) = filter p s := eq_of_veq <| Multiset.filter_cons_of_neg s.val hp theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] : Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by constructor <;> simp +contextual [disjoint_left] theorem disjoint_filter_filter' (s t : Finset α) {p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) : Disjoint (s.filter p) (t.filter q) := by simp_rw [disjoint_left, mem_filter] rintro a ⟨_, hp⟩ ⟨_, hq⟩ rw [Pi.disjoint_iff] at h simpa [hp, hq] using h a theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] : Disjoint (s.filter p) (t.filter fun a => ¬p a) := disjoint_filter_filter' s t disjoint_compl_right theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) : filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) := eq_of_veq <| Multiset.filter_add _ _ _ theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) : filter p (cons a s ha) = if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by split_ifs with h · rw [filter_cons_of_pos _ _ _ ha h] · rw [filter_cons_of_neg _ _ _ ha h] section variable [DecidableEq α] theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p := ext fun _ => by simp only [mem_filter, mem_union, or_and_right] theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x := ext fun x => by simp [mem_filter, mem_union, ← and_or_left] theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] : (s.filter fun i => i ∈ t) = s ∩ t := ext fun i => by simp [mem_filter, mem_inter] theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by ext simp [mem_filter, mem_inter, and_assoc] theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by ext simp only [mem_inter, mem_filter, and_right_comm] theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by rw [inter_comm, filter_inter, inter_comm] theorem filter_insert (a : α) (s : Finset α) : filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by ext x split_ifs with h <;> by_cases h' : x = a <;> simp [h, h'] theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by ext x simp only [and_assoc, mem_filter, iff_self, mem_erase] theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q := ext fun _ => by simp [mem_filter, mem_union, and_or_left] theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q := ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc] theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p := ext fun a => by simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or, Bool.not_eq_true, and_or_left, and_not_self, or_false] lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] : s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)] theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ := ext fun _ => by simp [mem_sdiff, mem_filter] theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) : ∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by classical refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩ · simp [filter_union_right, em] · intro x simp · intro x simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp] intro hx hx₂ exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩ -- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing -- on, e.g. `x ∈ s.filter (Eq b)`. /-- After filtering out everything that does not equal a given value, at most that value remains. This is equivalent to `filter_eq'` with the equality the other way. -/ theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) : s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by split_ifs with h · ext simp only [mem_filter, mem_singleton, decide_eq_true_eq] refine ⟨fun h => h.2.symm, ?_⟩ rintro rfl exact ⟨h, rfl⟩ · ext simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq] rintro m rfl exact h m /-- After filtering out everything that does not equal a given value, at most that value remains. This is equivalent to `filter_eq` with the equality the other way. -/ theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ := _root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b) theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => b ≠ a) = s.erase b := by ext simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not] tauto theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b := _root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b) theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) : s.filter p ∪ s.filter q = s := (filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) : (s.filter p ∪ s.filter fun a => ¬p a) = s := filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p end end Filter /-! ### range -/ section Range open Nat variable {n m l : ℕ} @[simp] theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by convert filter_eq (range n) m using 2 · ext rw [eq_comm] · simp end Range end Finset /-! ### dedup on list and multiset -/ namespace Multiset variable [DecidableEq α] {s t : Multiset α} @[simp] theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t := Finset.ext <| by simp @[simp] theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t := Finset.ext <| by simp @[simp] theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by ext; simp @[simp] theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 := Finset.val_inj.symm.trans Multiset.dedup_eq_zero @[simp] theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty] @[aesop safe apply (rule_sets := [finsetNonempty])] protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty @[simp] theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] : Multiset.toFinset (s.filter p) = s.toFinset.filter p := by ext; simp end Multiset namespace List variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β} {s : Finset α} {t : Set β} {t' : Finset β} @[simp] theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by ext simp @[simp] theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by ext simp @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff @[simp] theorem toFinset_filter (s : List α) (p : α → Bool) : (s.filter p).toFinset = s.toFinset.filter (p ·) := by ext; simp [List.mem_filter] end List namespace Finset section ToList @[simp] theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ := Multiset.toList_eq_nil.trans val_eq_zero theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp @[simp] theorem toList_empty : (∅ : Finset α).toList = [] := toList_eq_nil.mpr rfl theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] := mt toList_eq_nil.mp hs.ne_empty theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty := mt empty_toList.mp hs.ne_empty end ToList /-! ### choose -/ section Choose variable (p : α → Prop) [DecidablePred p] (l : Finset α) /-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of `l` satisfying `p` this unique element, as an element of the corresponding subtype. -/ def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } := Multiset.chooseX p l.val hp /-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of `l` satisfying `p` this unique element, as an element of the ambient type. -/ def choose (hp : ∃! a, a ∈ l ∧ p a) : α := chooseX p l hp theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) := (chooseX p l hp).property theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l := (choose_spec _ _ _).1 theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) := (choose_spec _ _ _).2 end Choose end Finset namespace Equiv variable [DecidableEq α] {s t : Finset α} open Finset /-- The disjoint union of finsets is a sum -/ def Finset.union (s t : Finset α) (h : Disjoint s t) : s ⊕ t ≃ (s ∪ t : Finset α) := Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm @[simp] theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) : Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ := rfl @[simp] theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) : Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ := rfl /-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/ def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) : ((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i := let e := Equiv.Finset.union s t h sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e) /-- A finset is equivalent to its coercion as a set. -/ def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where toFun a := ⟨a.1, mem_coe.2 a.2⟩ invFun a := ⟨a.1, mem_coe.1 a.2⟩ left_inv := fun _ ↦ rfl right_inv := fun _ ↦ rfl end Equiv namespace Multiset variable [DecidableEq α] @[simp] lemma toFinset_replicate (n : ℕ) (a : α) : (replicate n a).toFinset = if n = 0 then ∅ else {a} := by ext x simp only [mem_toFinset, Finset.mem_singleton, mem_replicate] split_ifs with hn <;> simp [hn] end Multiset
Mathlib/Data/Finset/Basic.lean
2,770
2,772
/- Copyright (c) 2022 Pim Otte. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kyle Miller, Pim Otte -/ import Mathlib.Algebra.BigOperators.Fin import Mathlib.Algebra.Order.Antidiag.Pi import Mathlib.Data.Nat.Choose.Sum import Mathlib.Data.Nat.Factorial.BigOperators import Mathlib.Data.Nat.Factorial.DoubleFactorial import Mathlib.Data.Fin.VecNotation import Mathlib.Data.Finset.Sym import Mathlib.Data.Finsupp.Multiset /-! # Multinomial This file defines the multinomial coefficient and several small lemma's for manipulating it. ## Main declarations - `Nat.multinomial`: the multinomial coefficient ## Main results - `Finset.sum_pow`: The expansion of `(s.sum x) ^ n` using multinomial coefficients -/ open Finset open scoped Nat namespace Nat variable {α : Type*} (s : Finset α) (f : α → ℕ) {a b : α} (n : ℕ) /-- The multinomial coefficient. Gives the number of strings consisting of symbols from `s`, where `c ∈ s` appears with multiplicity `f c`. Defined as `(∑ i ∈ s, f i)! / ∏ i ∈ s, (f i)!`. -/ def multinomial : ℕ := (∑ i ∈ s, f i)! / ∏ i ∈ s, (f i)! theorem multinomial_pos : 0 < multinomial s f := Nat.div_pos (le_of_dvd (factorial_pos _) (prod_factorial_dvd_factorial_sum s f)) (prod_factorial_pos s f) theorem multinomial_spec : (∏ i ∈ s, (f i)!) * multinomial s f = (∑ i ∈ s, f i)! := Nat.mul_div_cancel' (prod_factorial_dvd_factorial_sum s f) @[simp] lemma multinomial_empty : multinomial ∅ f = 1 := by simp [multinomial] variable {s f} lemma multinomial_cons (ha : a ∉ s) (f : α → ℕ) : multinomial (s.cons a ha) f = (f a + ∑ i ∈ s, f i).choose (f a) * multinomial s f := by rw [multinomial, Nat.div_eq_iff_eq_mul_left _ (prod_factorial_dvd_factorial_sum _ _), prod_cons, multinomial, mul_assoc, mul_left_comm _ (f a)!, Nat.div_mul_cancel (prod_factorial_dvd_factorial_sum _ _), ← mul_assoc, Nat.choose_symm_add, Nat.add_choose_mul_factorial_mul_factorial, Finset.sum_cons] positivity lemma multinomial_insert [DecidableEq α] (ha : a ∉ s) (f : α → ℕ) : multinomial (insert a s) f = (f a + ∑ i ∈ s, f i).choose (f a) * multinomial s f := by rw [← cons_eq_insert _ _ ha, multinomial_cons] @[simp] lemma multinomial_singleton (a : α) (f : α → ℕ) : multinomial {a} f = 1 := by rw [← cons_empty, multinomial_cons]; simp @[simp] theorem multinomial_insert_one [DecidableEq α] (h : a ∉ s) (h₁ : f a = 1) : multinomial (insert a s) f = (s.sum f).succ * multinomial s f := by simp only [multinomial] rw [Finset.sum_insert h, Finset.prod_insert h, h₁, add_comm, ← succ_eq_add_one, factorial_succ] simp only [factorial, succ_eq_add_one, zero_add, mul_one, one_mul] rw [Nat.mul_div_assoc _ (prod_factorial_dvd_factorial_sum _ _)] theorem multinomial_congr {f g : α → ℕ} (h : ∀ a ∈ s, f a = g a) : multinomial s f = multinomial s g := by simp only [multinomial]; congr 1 · rw [Finset.sum_congr rfl h] · exact Finset.prod_congr rfl fun a ha => by rw [h a ha] /-! ### Connection to binomial coefficients When `Nat.multinomial` is applied to a `Finset` of two elements `{a, b}`, the result a binomial coefficient. We use `binomial` in the names of lemmas that involves `Nat.multinomial {a, b}`. -/ theorem binomial_eq [DecidableEq α] (h : a ≠ b) : multinomial {a, b} f = (f a + f b)! / ((f a)! * (f b)!) := by simp [multinomial, Finset.sum_pair h, Finset.prod_pair h] theorem binomial_eq_choose [DecidableEq α] (h : a ≠ b) : multinomial {a, b} f = (f a + f b).choose (f a) := by simp [binomial_eq h, choose_eq_factorial_div_factorial (Nat.le_add_right _ _)] theorem binomial_spec [DecidableEq α] (hab : a ≠ b) : (f a)! * (f b)! * multinomial {a, b} f = (f a + f b)! := by simpa [Finset.sum_pair hab, Finset.prod_pair hab] using multinomial_spec {a, b} f @[simp] theorem binomial_one [DecidableEq α] (h : a ≠ b) (h₁ : f a = 1) : multinomial {a, b} f = (f b).succ := by simp [multinomial_insert_one (Finset.not_mem_singleton.mpr h) h₁] theorem binomial_succ_succ [DecidableEq α] (h : a ≠ b) : multinomial {a, b} (Function.update (Function.update f a (f a).succ) b (f b).succ) = multinomial {a, b} (Function.update f a (f a).succ) + multinomial {a, b} (Function.update f b (f b).succ) := by simp only [binomial_eq_choose, Function.update_apply, h, Ne, ite_true, ite_false, not_false_eq_true] rw [if_neg h.symm] rw [add_succ, choose_succ_succ, succ_add_eq_add_succ] ring theorem succ_mul_binomial [DecidableEq α] (h : a ≠ b) : (f a + f b).succ * multinomial {a, b} f = (f a).succ * multinomial {a, b} (Function.update f a (f a).succ) := by rw [binomial_eq_choose h, binomial_eq_choose h, mul_comm (f a).succ, Function.update_self,
Function.update_of_ne h.symm] rw [succ_mul_choose_eq (f a + f b) (f a), succ_add (f a) (f b)] /-! ### Simple cases -/ theorem multinomial_univ_two (a b : ℕ) : multinomial Finset.univ ![a, b] = (a + b)! / (a ! * b !) := by rw [multinomial, Fin.sum_univ_two, Fin.prod_univ_two]
Mathlib/Data/Nat/Choose/Multinomial.lean
123
131
/- Copyright (c) 2024 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémy Degenne -/ import Mathlib.Probability.Kernel.Composition.MapComap import Mathlib.Probability.Martingale.Convergence import Mathlib.Probability.Process.PartitionFiltration /-! # Kernel density Let `κ : Kernel α (γ × β)` and `ν : Kernel α γ` be two finite kernels with `Kernel.fst κ ≤ ν`, where `γ` has a countably generated σ-algebra (true in particular for standard Borel spaces). We build a function `density κ ν : α → γ → Set β → ℝ` jointly measurable in the first two arguments such that for all `a : α` and all measurable sets `s : Set β` and `A : Set γ`, `∫ x in A, density κ ν a x s ∂(ν a) = (κ a).real (A ×ˢ s)`. There are two main applications of this construction. * Disintegration of kernels: for `κ : Kernel α (γ × β)`, we want to build a kernel `η : Kernel (α × γ) β` such that `κ = fst κ ⊗ₖ η`. For `β = ℝ`, we can use the density of `κ` with respect to `fst κ` for intervals to build a kernel cumulative distribution function for `η`. The construction can then be extended to `β` standard Borel. * Radon-Nikodym theorem for kernels: for `κ ν : Kernel α γ`, we can use the density to build a Radon-Nikodym derivative of `κ` with respect to `ν`. We don't need `β` here but we can apply the density construction to `β = Unit`. The derivative construction will use `density` but will not be exactly equal to it because we will want to remove the `fst κ ≤ ν` assumption. ## Main definitions * `ProbabilityTheory.Kernel.density`: for `κ : Kernel α (γ × β)` and `ν : Kernel α γ` two finite kernels, `Kernel.density κ ν` is a function `α → γ → Set β → ℝ`. ## Main statements * `ProbabilityTheory.Kernel.setIntegral_density`: for all measurable sets `A : Set γ` and `s : Set β`, `∫ x in A, Kernel.density κ ν a x s ∂(ν a) = (κ a).real (A ×ˢ s)`. * `ProbabilityTheory.Kernel.measurable_density`: the function `p : α × γ ↦ Kernel.density κ ν p.1 p.2 s` is measurable. ## Construction of the density If we were interested only in a fixed `a : α`, then we could use the Radon-Nikodym derivative to build the density function `density κ ν`, as follows. ``` def density' (κ : Kernel α (γ × β)) (ν : kernel a γ) (a : α) (x : γ) (s : Set β) : ℝ := (((κ a).restrict (univ ×ˢ s)).fst.rnDeriv (ν a) x).toReal ``` However, we can't turn those functions for each `a` into a measurable function of the pair `(a, x)`. In order to obtain measurability through countability, we use the fact that the measurable space `γ` is countably generated. For each `n : ℕ`, we define (in the file `Mathlib.Probability.Process.PartitionFiltration`) a finite partition of `γ`, such that those partitions are finer as `n` grows, and the σ-algebra generated by the union of all partitions is the σ-algebra of `γ`. For `x : γ`, `countablePartitionSet n x` denotes the set in the partition such that `x ∈ countablePartitionSet n x`. For a given `n`, the function `densityProcess κ ν n : α → γ → Set β → ℝ` defined by `fun a x s ↦ (κ a (countablePartitionSet n x ×ˢ s) / ν a (countablePartitionSet n x)).toReal` has the desired property that `∫ x in A, densityProcess κ ν n a x s ∂(ν a) = (κ a (A ×ˢ s)).toReal` for all `A` in the σ-algebra generated by the partition at scale `n` and is measurable in `(a, x)`. `countableFiltration γ` is the filtration of those σ-algebras for all `n : ℕ`. The functions `densityProcess κ ν n` described here are a bounded `ν`-martingale for the filtration `countableFiltration γ`. By Doob's martingale L1 convergence theorem, that martingale converges to a limit, which has a product-measurable version and satisfies the integral equality for all `A` in `⨆ n, countableFiltration γ n`. Finally, the partitions were chosen such that that supremum is equal to the σ-algebra on `γ`, hence the equality holds for all measurable sets. We have obtained the desired density function. ## References The construction of the density process in this file follows the proof of Theorem 9.27 in [O. Kallenberg, Foundations of modern probability][kallenberg2021], adapted to use a countably generated hypothesis instead of specializing to `ℝ`. -/ open MeasureTheory Set Filter MeasurableSpace open scoped NNReal ENNReal MeasureTheory Topology ProbabilityTheory namespace ProbabilityTheory.Kernel variable {α β γ : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {mγ : MeasurableSpace γ} [CountablyGenerated γ] {κ : Kernel α (γ × β)} {ν : Kernel α γ} section DensityProcess /-- An `ℕ`-indexed martingale that is a density for `κ` with respect to `ν` on the sets in `countablePartition γ n`. Used to define its limit `ProbabilityTheory.Kernel.density`, which is a density for those kernels for all measurable sets. -/ noncomputable def densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (x : γ) (s : Set β) : ℝ := (κ a (countablePartitionSet n x ×ˢ s) / ν a (countablePartitionSet n x)).toReal lemma densityProcess_def (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (s : Set β) : (fun t ↦ densityProcess κ ν n a t s) = fun t ↦ (κ a (countablePartitionSet n t ×ˢ s) / ν a (countablePartitionSet n t)).toReal := rfl lemma measurable_densityProcess_countableFiltration_aux (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (hs : MeasurableSet s) : Measurable[mα.prod (countableFiltration γ n)] (fun (p : α × γ) ↦ κ p.1 (countablePartitionSet n p.2 ×ˢ s) / ν p.1 (countablePartitionSet n p.2)) := by change Measurable[mα.prod (countableFiltration γ n)] ((fun (p : α × countablePartition γ n) ↦ κ p.1 (↑p.2 ×ˢ s) / ν p.1 p.2) ∘ (fun (p : α × γ) ↦ (p.1, ⟨countablePartitionSet n p.2, countablePartitionSet_mem n p.2⟩))) have h1 : @Measurable _ _ (mα.prod ⊤) _ (fun p : α × countablePartition γ n ↦ κ p.1 (↑p.2 ×ˢ s) / ν p.1 p.2) := by refine Measurable.div ?_ ?_ · refine measurable_from_prod_countable (fun t ↦ ?_) exact Kernel.measurable_coe _ ((measurableSet_countablePartition _ t.prop).prod hs) · refine measurable_from_prod_countable ?_ rintro ⟨t, ht⟩ exact Kernel.measurable_coe _ (measurableSet_countablePartition _ ht) refine h1.comp (measurable_fst.prodMk ?_) change @Measurable (α × γ) (countablePartition γ n) (mα.prod (countableFiltration γ n)) ⊤ ((fun c ↦ ⟨countablePartitionSet n c, countablePartitionSet_mem n c⟩) ∘ (fun p : α × γ ↦ p.2)) exact (measurable_countablePartitionSet_subtype n ⊤).comp measurable_snd lemma measurable_densityProcess_aux (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun (p : α × γ) ↦ κ p.1 (countablePartitionSet n p.2 ×ˢ s) / ν p.1 (countablePartitionSet n p.2)) := by refine Measurable.mono (measurable_densityProcess_countableFiltration_aux κ ν n hs) ?_ le_rfl exact sup_le_sup le_rfl (comap_mono ((countableFiltration γ).le _)) lemma measurable_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun (p : α × γ) ↦ densityProcess κ ν n p.1 p.2 s) := (measurable_densityProcess_aux κ ν n hs).ennreal_toReal -- The following two lemmas also work without the `( :)`, but they are slow. lemma measurable_densityProcess_left (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (x : γ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun a ↦ densityProcess κ ν n a x s) := ((measurable_densityProcess κ ν n hs).comp (measurable_id.prodMk measurable_const):) lemma measurable_densityProcess_right (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) {s : Set β} (a : α) (hs : MeasurableSet s) : Measurable (fun x ↦ densityProcess κ ν n a x s) := ((measurable_densityProcess κ ν n hs).comp (measurable_const.prodMk measurable_id):) lemma measurable_countableFiltration_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : Measurable[countableFiltration γ n] (fun x ↦ densityProcess κ ν n a x s) := by refine @Measurable.ennreal_toReal _ (countableFiltration γ n) _ ?_ exact (measurable_densityProcess_countableFiltration_aux κ ν n hs).comp measurable_prodMk_left lemma stronglyMeasurable_countableFiltration_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : StronglyMeasurable[countableFiltration γ n] (fun x ↦ densityProcess κ ν n a x s) := (measurable_countableFiltration_densityProcess κ ν n a hs).stronglyMeasurable lemma adapted_densityProcess (κ : Kernel α (γ × β)) (ν : Kernel α γ) (a : α) {s : Set β} (hs : MeasurableSet s) : Adapted (countableFiltration γ) (fun n x ↦ densityProcess κ ν n a x s) := fun n ↦ stronglyMeasurable_countableFiltration_densityProcess κ ν n a hs lemma densityProcess_nonneg (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (x : γ) (s : Set β) : 0 ≤ densityProcess κ ν n a x s := ENNReal.toReal_nonneg lemma meas_countablePartitionSet_le_of_fst_le (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : κ a (countablePartitionSet n x ×ˢ s) ≤ ν a (countablePartitionSet n x) := by calc κ a (countablePartitionSet n x ×ˢ s) ≤ fst κ a (countablePartitionSet n x) := by rw [fst_apply' _ _ (measurableSet_countablePartitionSet _ _)] refine measure_mono (fun x ↦ ?_) simp only [mem_prod, mem_setOf_eq, and_imp] exact fun h _ ↦ h _ ≤ ν a (countablePartitionSet n x) := hκν a _ lemma densityProcess_le_one (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : densityProcess κ ν n a x s ≤ 1 := by refine ENNReal.toReal_le_of_le_ofReal zero_le_one (ENNReal.div_le_of_le_mul ?_) rw [ENNReal.ofReal_one, one_mul] exact meas_countablePartitionSet_le_of_fst_le hκν n a x s lemma eLpNorm_densityProcess_le (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (s : Set β) : eLpNorm (fun x ↦ densityProcess κ ν n a x s) 1 (ν a) ≤ ν a univ := by refine (eLpNorm_le_of_ae_bound (C := 1) (ae_of_all _ (fun x ↦ ?_))).trans ?_ · simp only [Real.norm_eq_abs, abs_of_nonneg (densityProcess_nonneg κ ν n a x s), densityProcess_le_one hκν n a x s] · simp lemma integrable_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : Integrable (fun x ↦ densityProcess κ ν n a x s) (ν a) := by rw [← memLp_one_iff_integrable] refine ⟨Measurable.aestronglyMeasurable ?_, ?_⟩ · exact measurable_densityProcess_right κ ν n a hs · exact (eLpNorm_densityProcess_le hκν n a s).trans_lt (measure_lt_top _ _) lemma setIntegral_densityProcess_of_mem (hκν : fst κ ≤ ν) [hν : IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) {u : Set γ} (hu : u ∈ countablePartition γ n) : ∫ x in u, densityProcess κ ν n a x s ∂(ν a) = (κ a).real (u ×ˢ s) := by have : IsFiniteKernel κ := isFiniteKernel_of_isFiniteKernel_fst (h := isFiniteKernel_of_le hκν) have hu_meas : MeasurableSet u := measurableSet_countablePartition n hu simp_rw [densityProcess] rw [integral_toReal] rotate_left · refine Measurable.aemeasurable ?_ change Measurable ((fun (p : α × _) ↦ κ p.1 (countablePartitionSet n p.2 ×ˢ s) / ν p.1 (countablePartitionSet n p.2)) ∘ (fun x ↦ (a, x))) exact (measurable_densityProcess_aux κ ν n hs).comp measurable_prodMk_left · refine ae_of_all _ (fun x ↦ ?_) by_cases h0 : ν a (countablePartitionSet n x) = 0 · suffices κ a (countablePartitionSet n x ×ˢ s) = 0 by simp [h0, this] have h0' : fst κ a (countablePartitionSet n x) = 0 := le_antisymm ((hκν a _).trans h0.le) zero_le' rw [fst_apply' _ _ (measurableSet_countablePartitionSet _ _)] at h0' refine measure_mono_null (fun x ↦ ?_) h0' simp only [mem_prod, mem_setOf_eq, and_imp] exact fun h _ ↦ h · exact ENNReal.div_lt_top (measure_ne_top _ _) h0 congr have : ∫⁻ x in u, κ a (countablePartitionSet n x ×ˢ s) / ν a (countablePartitionSet n x) ∂(ν a) = ∫⁻ _ in u, κ a (u ×ˢ s) / ν a u ∂(ν a) := by refine setLIntegral_congr_fun hu_meas (ae_of_all _ (fun t ht ↦ ?_)) rw [countablePartitionSet_of_mem hu ht] rw [this] simp only [MeasureTheory.lintegral_const, MeasurableSet.univ, Measure.restrict_apply, univ_inter] by_cases h0 : ν a u = 0 · simp only [h0, mul_zero] have h0' : fst κ a u = 0 := le_antisymm ((hκν a _).trans h0.le) zero_le' rw [fst_apply' _ _ hu_meas] at h0' refine (measure_mono_null ?_ h0').symm intro p simp only [mem_prod, mem_setOf_eq, and_imp] exact fun h _ ↦ h rw [div_eq_mul_inv, mul_assoc, ENNReal.inv_mul_cancel h0, mul_one] exact measure_ne_top _ _ open scoped Function in -- required for scoped `on` notation lemma setIntegral_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) {A : Set γ} (hA : MeasurableSet[countableFiltration γ n] A) : ∫ x in A, densityProcess κ ν n a x s ∂(ν a) = (κ a).real (A ×ˢ s) := by have : IsFiniteKernel κ := isFiniteKernel_of_isFiniteKernel_fst (h := isFiniteKernel_of_le hκν) obtain ⟨S, hS_subset, rfl⟩ := (measurableSet_generateFrom_countablePartition_iff _ _).mp hA simp_rw [sUnion_eq_iUnion] have h_disj : Pairwise (Disjoint on fun i : S ↦ (i : Set γ)) := by intro u v huv #adaptation_note /-- nightly-2024-03-16 Previously `Function.onFun` unfolded in the following `simp only`, but now needs a `rw`. This may be a bug: a no import minimization may be required. simp only [Finset.coe_sort_coe, Function.onFun] -/ rw [Function.onFun] refine disjoint_countablePartition (hS_subset (by simp)) (hS_subset (by simp)) ?_ rwa [ne_eq, ← Subtype.ext_iff] rw [integral_iUnion, iUnion_prod_const, measureReal_def, measure_iUnion, ENNReal.tsum_toReal_eq (fun _ ↦ measure_ne_top _ _)] · congr with u rw [setIntegral_densityProcess_of_mem hκν _ _ hs (hS_subset (by simp))] rfl · intro u v huv simp only [Finset.coe_sort_coe, Set.disjoint_prod, disjoint_self, bot_eq_empty] exact Or.inl (h_disj huv) · exact fun _ ↦ (measurableSet_countablePartition n (hS_subset (by simp))).prod hs · exact fun _ ↦ measurableSet_countablePartition n (hS_subset (by simp)) · exact h_disj · exact (integrable_densityProcess hκν _ _ hs).integrableOn lemma integral_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (n : ℕ) (a : α) {s : Set β} (hs : MeasurableSet s) : ∫ x, densityProcess κ ν n a x s ∂(ν a) = (κ a).real (univ ×ˢ s) := by rw [← setIntegral_univ, setIntegral_densityProcess hκν _ _ hs MeasurableSet.univ] lemma setIntegral_densityProcess_of_le (hκν : fst κ ≤ ν) [IsFiniteKernel ν] {n m : ℕ} (hnm : n ≤ m) (a : α) {s : Set β} (hs : MeasurableSet s) {A : Set γ} (hA : MeasurableSet[countableFiltration γ n] A) : ∫ x in A, densityProcess κ ν m a x s ∂(ν a) = (κ a).real (A ×ˢ s) := setIntegral_densityProcess hκν m a hs ((countableFiltration γ).mono hnm A hA) lemma condExp_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] {i j : ℕ} (hij : i ≤ j) (a : α) {s : Set β} (hs : MeasurableSet s) : (ν a)[fun x ↦ densityProcess κ ν j a x s | countableFiltration γ i] =ᵐ[ν a] fun x ↦ densityProcess κ ν i a x s := by refine (ae_eq_condExp_of_forall_setIntegral_eq ?_ ?_ ?_ ?_ ?_).symm · exact integrable_densityProcess hκν j a hs · exact fun _ _ _ ↦ (integrable_densityProcess hκν _ _ hs).integrableOn · intro x hx _ rw [setIntegral_densityProcess hκν i a hs hx, setIntegral_densityProcess_of_le hκν hij a hs hx] · exact StronglyMeasurable.aestronglyMeasurable (stronglyMeasurable_countableFiltration_densityProcess κ ν i a hs) @[deprecated (since := "2025-01-21")] alias condexp_densityProcess := condExp_densityProcess lemma martingale_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : Martingale (fun n x ↦ densityProcess κ ν n a x s) (countableFiltration γ) (ν a) := ⟨adapted_densityProcess κ ν a hs, fun _ _ h ↦ condExp_densityProcess hκν h a hs⟩ lemma densityProcess_mono_set (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) {s s' : Set β} (h : s ⊆ s') : densityProcess κ ν n a x s ≤ densityProcess κ ν n a x s' := by unfold densityProcess obtain h₀ | h₀ := eq_or_ne (ν a (countablePartitionSet n x)) 0 · simp [h₀] · gcongr simp only [ne_eq, ENNReal.div_eq_top, h₀, and_false, false_or, not_and, not_not] exact eq_top_mono (meas_countablePartitionSet_le_of_fst_le hκν n a x s') lemma densityProcess_mono_kernel_left {κ' : Kernel α (γ × β)} (hκκ' : κ ≤ κ') (hκ'ν : fst κ' ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : densityProcess κ ν n a x s ≤ densityProcess κ' ν n a x s := by unfold densityProcess by_cases h0 : ν a (countablePartitionSet n x) = 0 · rw [h0, ENNReal.toReal_div, ENNReal.toReal_div] simp have h_le : κ' a (countablePartitionSet n x ×ˢ s) ≤ ν a (countablePartitionSet n x) := meas_countablePartitionSet_le_of_fst_le hκ'ν n a x s gcongr · simp only [ne_eq, ENNReal.div_eq_top, h0, and_false, false_or, not_and, not_not] exact fun h_top ↦ eq_top_mono h_le h_top · apply hκκ' lemma densityProcess_antitone_kernel_right {ν' : Kernel α γ} (hνν' : ν ≤ ν') (hκν : fst κ ≤ ν) (n : ℕ) (a : α) (x : γ) (s : Set β) : densityProcess κ ν' n a x s ≤ densityProcess κ ν n a x s := by unfold densityProcess have h_le : κ a (countablePartitionSet n x ×ˢ s) ≤ ν a (countablePartitionSet n x) := meas_countablePartitionSet_le_of_fst_le hκν n a x s by_cases h0 : ν a (countablePartitionSet n x) = 0 · simp [le_antisymm (h_le.trans h0.le) zero_le', h0] gcongr · simp only [ne_eq, ENNReal.div_eq_top, h0, and_false, false_or, not_and, not_not] exact fun h_top ↦ eq_top_mono h_le h_top · apply hνν' @[simp] lemma densityProcess_empty (κ : Kernel α (γ × β)) (ν : Kernel α γ) (n : ℕ) (a : α) (x : γ) : densityProcess κ ν n a x ∅ = 0 := by simp [densityProcess] lemma tendsto_densityProcess_atTop_empty_of_antitone (κ : Kernel α (γ × β)) (ν : Kernel α γ) [IsFiniteKernel κ] (n : ℕ) (a : α) (x : γ) (seq : ℕ → Set β) (hseq : Antitone seq) (hseq_iInter : ⋂ i, seq i = ∅) (hseq_meas : ∀ m, MeasurableSet (seq m)) : Tendsto (fun m ↦ densityProcess κ ν n a x (seq m)) atTop (𝓝 (densityProcess κ ν n a x ∅)) := by simp_rw [densityProcess] by_cases h0 : ν a (countablePartitionSet n x) = 0 · simp_rw [h0, ENNReal.toReal_div] simp refine (ENNReal.tendsto_toReal ?_).comp ?_ · rw [ne_eq, ENNReal.div_eq_top] push_neg simp refine ENNReal.Tendsto.div_const ?_ (.inr h0) have : Tendsto (fun m ↦ κ a (countablePartitionSet n x ×ˢ seq m)) atTop (𝓝 ((κ a) (⋂ n_1, countablePartitionSet n x ×ˢ seq n_1))) := by apply tendsto_measure_iInter_atTop · measurability · exact fun _ _ h ↦ prod_mono_right <| hseq h · exact ⟨0, measure_ne_top _ _⟩ simpa only [← prod_iInter, hseq_iInter] using this lemma tendsto_densityProcess_atTop_of_antitone (κ : Kernel α (γ × β)) (ν : Kernel α γ) [IsFiniteKernel κ] (n : ℕ) (a : α) (x : γ) (seq : ℕ → Set β) (hseq : Antitone seq) (hseq_iInter : ⋂ i, seq i = ∅) (hseq_meas : ∀ m, MeasurableSet (seq m)) : Tendsto (fun m ↦ densityProcess κ ν n a x (seq m)) atTop (𝓝 0) := by rw [← densityProcess_empty κ ν n a x] exact tendsto_densityProcess_atTop_empty_of_antitone κ ν n a x seq hseq hseq_iInter hseq_meas lemma tendsto_densityProcess_limitProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : ∀ᵐ x ∂(ν a), Tendsto (fun n ↦ densityProcess κ ν n a x s) atTop (𝓝 ((countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a) x)) := by refine Submartingale.ae_tendsto_limitProcess (martingale_densityProcess hκν a hs).submartingale (R := (ν a univ).toNNReal) (fun n ↦ ?_) refine (eLpNorm_densityProcess_le hκν n a s).trans_eq ?_ rw [ENNReal.coe_toNNReal] exact measure_ne_top _ _ lemma memL1_limitProcess_densityProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : MemLp ((countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a)) 1 (ν a) := by refine Submartingale.memLp_limitProcess (martingale_densityProcess hκν a hs).submartingale (R := (ν a univ).toNNReal) (fun n ↦ ?_) refine (eLpNorm_densityProcess_le hκν n a s).trans_eq ?_ rw [ENNReal.coe_toNNReal] exact measure_ne_top _ _ lemma tendsto_eLpNorm_one_densityProcess_limitProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : Tendsto (fun n ↦ eLpNorm ((fun x ↦ densityProcess κ ν n a x s) - (countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a)) 1 (ν a)) atTop (𝓝 0) := by refine Submartingale.tendsto_eLpNorm_one_limitProcess ?_ ?_ · exact (martingale_densityProcess hκν a hs).submartingale · refine uniformIntegrable_of le_rfl ENNReal.one_ne_top ?_ ?_ · exact fun n ↦ (measurable_densityProcess_right κ ν n a hs).aestronglyMeasurable · refine fun ε _ ↦ ⟨2, fun n ↦ le_of_eq_of_le ?_ (?_ : 0 ≤ ENNReal.ofReal ε)⟩ · suffices {x | 2 ≤ ‖densityProcess κ ν n a x s‖₊} = ∅ by simp [this] ext x simp only [mem_setOf_eq, mem_empty_iff_false, iff_false, not_le] refine (?_ : _ ≤ (1 : ℝ≥0)).trans_lt one_lt_two rw [Real.nnnorm_of_nonneg (densityProcess_nonneg _ _ _ _ _ _)] exact mod_cast (densityProcess_le_one hκν _ _ _ _) · simp lemma tendsto_eLpNorm_one_restrict_densityProcess_limitProcess [IsFiniteKernel ν] (hκν : fst κ ≤ ν) (a : α) {s : Set β} (hs : MeasurableSet s) (A : Set γ) : Tendsto (fun n ↦ eLpNorm ((fun x ↦ densityProcess κ ν n a x s) - (countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a)) 1 ((ν a).restrict A)) atTop (𝓝 0) := tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds (tendsto_eLpNorm_one_densityProcess_limitProcess hκν a hs) (fun _ ↦ zero_le') (fun _ ↦ eLpNorm_restrict_le _ _ _ _) end DensityProcess section Density /-- Density of the kernel `κ` with respect to `ν`. This is a function `α → γ → Set β → ℝ` which is measurable on `α × γ` for all measurable sets `s : Set β` and satisfies that `∫ x in A, density κ ν a x s ∂(ν a) = (κ a).real (A ×ˢ s)` for all measurable `A : Set γ`. -/ noncomputable def density (κ : Kernel α (γ × β)) (ν : Kernel α γ) (a : α) (x : γ) (s : Set β) : ℝ := limsup (fun n ↦ densityProcess κ ν n a x s) atTop lemma density_ae_eq_limitProcess (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : (fun x ↦ density κ ν a x s) =ᵐ[ν a] (countableFiltration γ).limitProcess (fun n x ↦ densityProcess κ ν n a x s) (ν a) := by filter_upwards [tendsto_densityProcess_limitProcess hκν a hs] with t ht using ht.limsup_eq lemma tendsto_m_density (hκν : fst κ ≤ ν) (a : α) [IsFiniteKernel ν] {s : Set β} (hs : MeasurableSet s) : ∀ᵐ x ∂(ν a), Tendsto (fun n ↦ densityProcess κ ν n a x s) atTop (𝓝 (density κ ν a x s)) := by filter_upwards [tendsto_densityProcess_limitProcess hκν a hs, density_ae_eq_limitProcess hκν a hs] with t h1 h2 using h2 ▸ h1 lemma measurable_density (κ : Kernel α (γ × β)) (ν : Kernel α γ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun (p : α × γ) ↦ density κ ν p.1 p.2 s) := .limsup (fun n ↦ measurable_densityProcess κ ν n hs) lemma measurable_density_left (κ : Kernel α (γ × β)) (ν : Kernel α γ) (x : γ) {s : Set β} (hs : MeasurableSet s) : Measurable (fun a ↦ density κ ν a x s) := by change Measurable ((fun (p : α × γ) ↦ density κ ν p.1 p.2 s) ∘ (fun a ↦ (a, x))) exact (measurable_density κ ν hs).comp measurable_prodMk_right lemma measurable_density_right (κ : Kernel α (γ × β)) (ν : Kernel α γ) {s : Set β} (hs : MeasurableSet s) (a : α) : Measurable (fun x ↦ density κ ν a x s) := by change Measurable ((fun (p : α × γ) ↦ density κ ν p.1 p.2 s) ∘ (fun x ↦ (a, x))) exact (measurable_density κ ν hs).comp measurable_prodMk_left lemma density_mono_set (hκν : fst κ ≤ ν) (a : α) (x : γ) {s s' : Set β} (h : s ⊆ s') : density κ ν a x s ≤ density κ ν a x s' := by refine limsup_le_limsup ?_ ?_ ?_ · exact Eventually.of_forall (fun n ↦ densityProcess_mono_set hκν n a x h) · exact isCoboundedUnder_le_of_le atTop (fun i ↦ densityProcess_nonneg _ _ _ _ _ _) · exact isBoundedUnder_of ⟨1, fun n ↦ densityProcess_le_one hκν _ _ _ _⟩ lemma density_nonneg (hκν : fst κ ≤ ν) (a : α) (x : γ) (s : Set β) : 0 ≤ density κ ν a x s := by refine le_limsup_of_frequently_le ?_ ?_ · exact Frequently.of_forall (fun n ↦ densityProcess_nonneg _ _ _ _ _ _) · exact isBoundedUnder_of ⟨1, fun n ↦ densityProcess_le_one hκν _ _ _ _⟩ lemma density_le_one (hκν : fst κ ≤ ν) (a : α) (x : γ) (s : Set β) : density κ ν a x s ≤ 1 := by refine limsup_le_of_le ?_ ?_ · exact isCoboundedUnder_le_of_le atTop (fun i ↦ densityProcess_nonneg _ _ _ _ _ _) · exact Eventually.of_forall (fun n ↦ densityProcess_le_one hκν _ _ _ _) section Integral lemma eLpNorm_density_le (hκν : fst κ ≤ ν) (a : α) (s : Set β) : eLpNorm (fun x ↦ density κ ν a x s) 1 (ν a) ≤ ν a univ := by refine (eLpNorm_le_of_ae_bound (C := 1) (ae_of_all _ (fun t ↦ ?_))).trans ?_ · simp only [Real.norm_eq_abs, abs_of_nonneg (density_nonneg hκν a t s), density_le_one hκν a t s]
· simp lemma integrable_density (hκν : fst κ ≤ ν) [IsFiniteKernel ν] (a : α) {s : Set β} (hs : MeasurableSet s) : Integrable (fun x ↦ density κ ν a x s) (ν a) := by rw [← memLp_one_iff_integrable]
Mathlib/Probability/Kernel/Disintegration/Density.lean
490
495
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Julian Kuelshammer -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.Group.Commute.Basic import Mathlib.Algebra.Group.Pointwise.Set.Finite import Mathlib.Algebra.Group.Subgroup.Finite import Mathlib.Algebra.Module.NatInt import Mathlib.Algebra.Order.Group.Action import Mathlib.Algebra.Order.Ring.Abs import Mathlib.Data.Int.ModEq import Mathlib.Dynamics.PeriodicPts.Lemmas import Mathlib.GroupTheory.Index import Mathlib.NumberTheory.Divisors import Mathlib.Order.Interval.Set.Infinite /-! # Order of an element This file defines the order of an element of a finite group. For a finite group `G` the order of `x ∈ G` is the minimal `n ≥ 1` such that `x ^ n = 1`. ## Main definitions * `IsOfFinOrder` is a predicate on an element `x` of a monoid `G` saying that `x` is of finite order. * `IsOfFinAddOrder` is the additive analogue of `IsOfFinOrder`. * `orderOf x` defines the order of an element `x` of a monoid `G`, by convention its value is `0` if `x` has infinite order. * `addOrderOf` is the additive analogue of `orderOf`. ## Tags order of an element -/ assert_not_exists Field open Function Fintype Nat Pointwise Subgroup Submonoid open scoped Finset variable {G H A α β : Type*} section Monoid variable [Monoid G] {a b x y : G} {n m : ℕ} section IsOfFinOrder -- Porting note (https://github.com/leanprover-community/mathlib4/issues/12129): additional beta reduction needed @[to_additive] theorem isPeriodicPt_mul_iff_pow_eq_one (x : G) : IsPeriodicPt (x * ·) n 1 ↔ x ^ n = 1 := by rw [IsPeriodicPt, IsFixedPt, mul_left_iterate]; beta_reduce; rw [mul_one] /-- `IsOfFinOrder` is a predicate on an element `x` of a monoid to be of finite order, i.e. there exists `n ≥ 1` such that `x ^ n = 1`. -/ @[to_additive "`IsOfFinAddOrder` is a predicate on an element `a` of an additive monoid to be of finite order, i.e. there exists `n ≥ 1` such that `n • a = 0`."] def IsOfFinOrder (x : G) : Prop := (1 : G) ∈ periodicPts (x * ·) theorem isOfFinAddOrder_ofMul_iff : IsOfFinAddOrder (Additive.ofMul x) ↔ IsOfFinOrder x := Iff.rfl theorem isOfFinOrder_ofAdd_iff {α : Type*} [AddMonoid α] {x : α} : IsOfFinOrder (Multiplicative.ofAdd x) ↔ IsOfFinAddOrder x := Iff.rfl @[to_additive] theorem isOfFinOrder_iff_pow_eq_one : IsOfFinOrder x ↔ ∃ n, 0 < n ∧ x ^ n = 1 := by simp [IsOfFinOrder, mem_periodicPts, isPeriodicPt_mul_iff_pow_eq_one] @[to_additive] alias ⟨IsOfFinOrder.exists_pow_eq_one, _⟩ := isOfFinOrder_iff_pow_eq_one @[to_additive] lemma isOfFinOrder_iff_zpow_eq_one {G} [DivisionMonoid G] {x : G} : IsOfFinOrder x ↔ ∃ (n : ℤ), n ≠ 0 ∧ x ^ n = 1 := by rw [isOfFinOrder_iff_pow_eq_one] refine ⟨fun ⟨n, hn, hn'⟩ ↦ ⟨n, Int.natCast_ne_zero_iff_pos.mpr hn, zpow_natCast x n ▸ hn'⟩, fun ⟨n, hn, hn'⟩ ↦ ⟨n.natAbs, Int.natAbs_pos.mpr hn, ?_⟩⟩ rcases (Int.natAbs_eq_iff (a := n)).mp rfl with h | h · rwa [h, zpow_natCast] at hn' · rwa [h, zpow_neg, inv_eq_one, zpow_natCast] at hn' /-- See also `injective_pow_iff_not_isOfFinOrder`. -/ @[to_additive "See also `injective_nsmul_iff_not_isOfFinAddOrder`."] theorem not_isOfFinOrder_of_injective_pow {x : G} (h : Injective fun n : ℕ => x ^ n) : ¬IsOfFinOrder x := by simp_rw [isOfFinOrder_iff_pow_eq_one, not_exists, not_and] intro n hn_pos hnx rw [← pow_zero x] at hnx rw [h hnx] at hn_pos exact irrefl 0 hn_pos /-- 1 is of finite order in any monoid. -/ @[to_additive (attr := simp) "0 is of finite order in any additive monoid."] theorem IsOfFinOrder.one : IsOfFinOrder (1 : G) := isOfFinOrder_iff_pow_eq_one.mpr ⟨1, Nat.one_pos, one_pow 1⟩ @[to_additive] lemma IsOfFinOrder.pow {n : ℕ} : IsOfFinOrder a → IsOfFinOrder (a ^ n) := by simp_rw [isOfFinOrder_iff_pow_eq_one] rintro ⟨m, hm, ha⟩ exact ⟨m, hm, by simp [pow_right_comm _ n, ha]⟩ @[to_additive] lemma IsOfFinOrder.of_pow {n : ℕ} (h : IsOfFinOrder (a ^ n)) (hn : n ≠ 0) : IsOfFinOrder a := by rw [isOfFinOrder_iff_pow_eq_one] at * rcases h with ⟨m, hm, ha⟩ exact ⟨n * m, mul_pos hn.bot_lt hm, by rwa [pow_mul]⟩ @[to_additive (attr := simp)] lemma isOfFinOrder_pow {n : ℕ} : IsOfFinOrder (a ^ n) ↔ IsOfFinOrder a ∨ n = 0 := by rcases Decidable.eq_or_ne n 0 with rfl | hn · simp · exact ⟨fun h ↦ .inl <| h.of_pow hn, fun h ↦ (h.resolve_right hn).pow⟩
/-- Elements of finite order are of finite order in submonoids. -/ @[to_additive "Elements of finite order are of finite order in submonoids."] theorem Submonoid.isOfFinOrder_coe {H : Submonoid G} {x : H} : IsOfFinOrder (x : G) ↔ IsOfFinOrder x := by
Mathlib/GroupTheory/OrderOfElement.lean
116
120
/- 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.Data.Multiset.ZeroCons /-! # Basic results on multisets -/ -- No algebra should be required assert_not_exists Monoid universe v open List Subtype Nat Function variable {α : Type*} {β : Type v} {γ : Type*} namespace Multiset /-! ### `Multiset.toList` -/ section ToList /-- Produces a list of the elements in the multiset using choice. -/ noncomputable def toList (s : Multiset α) := s.out @[simp, norm_cast] theorem coe_toList (s : Multiset α) : (s.toList : Multiset α) = s := s.out_eq' @[simp] theorem toList_eq_nil {s : Multiset α} : s.toList = [] ↔ s = 0 := by rw [← coe_eq_zero, coe_toList] theorem empty_toList {s : Multiset α} : s.toList.isEmpty ↔ s = 0 := by simp @[simp] theorem toList_zero : (Multiset.toList 0 : List α) = [] := toList_eq_nil.mpr rfl @[simp] theorem mem_toList {a : α} {s : Multiset α} : a ∈ s.toList ↔ a ∈ s := by rw [← mem_coe, coe_toList] @[simp] theorem toList_eq_singleton_iff {a : α} {m : Multiset α} : m.toList = [a] ↔ m = {a} := by rw [← perm_singleton, ← coe_eq_coe, coe_toList, coe_singleton] @[simp] theorem toList_singleton (a : α) : ({a} : Multiset α).toList = [a] := Multiset.toList_eq_singleton_iff.2 rfl @[simp] theorem length_toList (s : Multiset α) : s.toList.length = card s := by rw [← coe_card, coe_toList] end ToList /-! ### Induction principles -/ /-- The strong induction principle for multisets. -/ @[elab_as_elim] def strongInductionOn {p : Multiset α → Sort*} (s : Multiset α) (ih : ∀ s, (∀ t < s, p t) → p s) : p s := (ih s) fun t _h => strongInductionOn t ih termination_by card s decreasing_by exact card_lt_card _h theorem strongInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) (H) : @strongInductionOn _ p s H = H s fun t _h => @strongInductionOn _ p t H := by rw [strongInductionOn] @[elab_as_elim] theorem case_strongInductionOn {p : Multiset α → Prop} (s : Multiset α) (h₀ : p 0) (h₁ : ∀ a s, (∀ t ≤ s, p t) → p (a ::ₘ s)) : p s := Multiset.strongInductionOn s fun s => Multiset.induction_on s (fun _ => h₀) fun _a _s _ ih => (h₁ _ _) fun _t h => ih _ <| lt_of_le_of_lt h <| lt_cons_self _ _ /-- Suppose that, given that `p t` can be defined on all supersets of `s` of cardinality less than `n`, one knows how to define `p s`. Then one can inductively define `p s` for all multisets `s` of cardinality less than `n`, starting from multisets of card `n` and iterating. This can be used either to define data, or to prove properties. -/ def strongDownwardInduction {p : Multiset α → Sort*} {n : ℕ} (H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) (s : Multiset α) : card s ≤ n → p s := H s fun {t} ht _h => strongDownwardInduction H t ht termination_by n - card s decreasing_by simp_wf; have := (card_lt_card _h); omega theorem strongDownwardInduction_eq {p : Multiset α → Sort*} {n : ℕ} (H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) (s : Multiset α) : strongDownwardInduction H s = H s fun ht _hst => strongDownwardInduction H _ ht := by rw [strongDownwardInduction] /-- Analogue of `strongDownwardInduction` with order of arguments swapped. -/ @[elab_as_elim] def strongDownwardInductionOn {p : Multiset α → Sort*} {n : ℕ} : ∀ s : Multiset α, (∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) → card s ≤ n → p s := fun s H => strongDownwardInduction H s theorem strongDownwardInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) {n : ℕ} (H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) : s.strongDownwardInductionOn H = H s fun {t} ht _h => t.strongDownwardInductionOn H ht := by dsimp only [strongDownwardInductionOn] rw [strongDownwardInduction] section Choose variable (p : α → Prop) [DecidablePred p] (l : Multiset α) /-- Given a proof `hp` that there exists a unique `a ∈ l` such that `p a`, `chooseX p l hp` returns that `a` together with proofs of `a ∈ l` and `p a`. -/ def chooseX : ∀ _hp : ∃! a, a ∈ l ∧ p a, { a // a ∈ l ∧ p a } := Quotient.recOn l (fun l' ex_unique => List.chooseX p l' (ExistsUnique.exists ex_unique)) (by intros a b _ funext hp suffices all_equal : ∀ x y : { t // t ∈ b ∧ p t }, x = y by apply all_equal rintro ⟨x, px⟩ ⟨y, py⟩ rcases hp with ⟨z, ⟨_z_mem_l, _pz⟩, z_unique⟩ congr calc x = z := z_unique x px _ = y := (z_unique y py).symm ) /-- Given a proof `hp` that there exists a unique `a ∈ l` such that `p a`, `choose p l hp` returns that `a`. -/ def choose (hp : ∃! a, a ∈ l ∧ p a) : α := chooseX p l hp theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) := (chooseX p l hp).property theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l := (choose_spec _ _ _).1 theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) := (choose_spec _ _ _).2 end Choose variable (α) in /-- The equivalence between lists and multisets of a subsingleton type. -/ def subsingletonEquiv [Subsingleton α] : List α ≃ Multiset α where toFun := ofList invFun := (Quot.lift id) fun (a b : List α) (h : a ~ b) => (List.ext_get h.length_eq) fun _ _ _ => Subsingleton.elim _ _ left_inv _ := rfl right_inv m := Quot.inductionOn m fun _ => rfl @[simp] theorem coe_subsingletonEquiv [Subsingleton α] : (subsingletonEquiv α : List α → Multiset α) = ofList := rfl section SizeOf set_option linter.deprecated false in @[deprecated "Deprecated without replacement." (since := "2025-02-07")] theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Multiset α} (hx : x ∈ s) : SizeOf.sizeOf x < SizeOf.sizeOf s := by induction s using Quot.inductionOn exact List.sizeOf_lt_sizeOf_of_mem hx end SizeOf end Multiset
Mathlib/Data/Multiset/Basic.lean
797
798
/- Copyright (c) 2022 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Filippo A. E. Nuccio, Sam van Gool -/ import Mathlib.Data.Fintype.Order import Mathlib.Order.Interval.Finset.Basic import Mathlib.Order.Irreducible import Mathlib.Order.UpperLower.Closure /-! # Birkhoff representation This file proves two facts which together are commonly referred to as "Birkhoff representation": 1. Any nonempty finite partial order is isomorphic to the partial order of sup-irreducible elements in its lattice of lower sets. 2. Any nonempty finite distributive lattice is isomorphic to the lattice of lower sets of its partial order of sup-irreducible elements. ## Main declarations For a finite nonempty partial order `α`: * `OrderEmbedding.supIrredLowerSet`: `α` is isomorphic to the order of its irreducible lower sets. If `α` is moreover a distributive lattice: * `OrderIso.lowerSetSupIrred`: `α` is isomorphic to the lattice of lower sets of its irreducible elements. * `OrderEmbedding.birkhoffSet`, `OrderEmbedding.birkhoffFinset`: Order embedding of `α` into the powerset lattice of its irreducible elements. * `LatticeHom.birkhoffSet`, `LatticeHom.birkhoffFinet`: Same as the previous two, but bundled as an injective lattice homomorphism. * `exists_birkhoff_representation`: `α` embeds into some powerset algebra. You should prefer using this over the explicit Birkhoff embedding because the Birkhoff embedding is littered with decidability footguns that this existential-packaged version can afford to avoid. ## See also These results form the object part of finite Stone duality: the functorial contravariant equivalence between the category of finite distributive lattices and the category of finite partial orders. TODO: extend to morphisms. ## References * [G. Birkhoff, *Rings of sets*][birkhoff1937] ## Tags birkhoff, representation, stone duality, lattice embedding -/ open Finset Function OrderDual UpperSet LowerSet variable {α : Type*} section PartialOrder variable [PartialOrder α] namespace UpperSet variable {s : UpperSet α} @[simp] lemma infIrred_Ici (a : α) : InfIrred (Ici a) := by refine ⟨fun h ↦ Ici_ne_top h.eq_top, fun s t hst ↦ ?_⟩ have := mem_Ici_iff.2 (le_refl a) rw [← hst] at this exact this.imp (fun ha ↦ le_antisymm (le_Ici.2 ha) <| hst.ge.trans inf_le_left) fun ha ↦ le_antisymm (le_Ici.2 ha) <| hst.ge.trans inf_le_right variable [Finite α] @[simp] lemma infIrred_iff_of_finite : InfIrred s ↔ ∃ a, Ici a = s := by refine ⟨fun hs ↦ ?_, ?_⟩ · obtain ⟨a, ha, has⟩ := (s : Set α).toFinite.exists_minimal_wrt id _ (coe_nonempty.2 hs.ne_top) exact ⟨a, (hs.2 <| erase_inf_Ici ha <| by simpa [eq_comm] using has).resolve_left (lt_erase.2 ha).ne'⟩ · rintro ⟨a, rfl⟩ exact infIrred_Ici _ end UpperSet namespace LowerSet variable {s : LowerSet α} @[simp] lemma supIrred_Iic (a : α) : SupIrred (Iic a) := by refine ⟨fun h ↦ Iic_ne_bot h.eq_bot, fun s t hst ↦ ?_⟩ have := mem_Iic_iff.2 (le_refl a) rw [← hst] at this exact this.imp (fun ha ↦ (le_sup_left.trans_eq hst).antisymm <| Iic_le.2 ha) fun ha ↦ (le_sup_right.trans_eq hst).antisymm <| Iic_le.2 ha variable [Finite α] @[simp] lemma supIrred_iff_of_finite : SupIrred s ↔ ∃ a, Iic a = s := by refine ⟨fun hs ↦ ?_, ?_⟩ · obtain ⟨a, ha, has⟩ := (s : Set α).toFinite.exists_maximal_wrt id _ (coe_nonempty.2 hs.ne_bot) exact ⟨a, (hs.2 <| erase_sup_Iic ha <| by simpa [eq_comm] using has).resolve_left (erase_lt.2 ha).ne⟩ · rintro ⟨a, rfl⟩ exact supIrred_Iic _ end LowerSet namespace OrderEmbedding /-- The **Birkhoff Embedding** of a finite partial order as sup-irreducible elements in its lattice of lower sets. -/ def supIrredLowerSet : α ↪o {s : LowerSet α // SupIrred s} where toFun a := ⟨Iic a, supIrred_Iic _⟩ inj' _ := by simp map_rel_iff' := by simp /-- The **Birkhoff Embedding** of a finite partial order as inf-irreducible elements in its lattice of lower sets. -/ def infIrredUpperSet : α ↪o {s : UpperSet α // InfIrred s} where toFun a := ⟨Ici a, infIrred_Ici _⟩ inj' _ := by simp map_rel_iff' := by simp @[simp] lemma supIrredLowerSet_apply (a : α) : supIrredLowerSet a = ⟨Iic a, supIrred_Iic _⟩ := rfl @[simp] lemma infIrredUpperSet_apply (a : α) : infIrredUpperSet a = ⟨Ici a, infIrred_Ici _⟩ := rfl variable [Finite α] lemma supIrredLowerSet_surjective : Surjective (supIrredLowerSet (α := α)) := by aesop (add simp Surjective) lemma infIrredUpperSet_surjective : Surjective (infIrredUpperSet (α := α)) := by aesop (add simp Surjective) end OrderEmbedding namespace OrderIso variable [Finite α] /-- **Birkhoff Representation for partial orders.** Any partial order is isomorphic to the partial order of sup-irreducible elements in its lattice of lower sets. -/ noncomputable def supIrredLowerSet : α ≃o {s : LowerSet α // SupIrred s} := RelIso.ofSurjective _ OrderEmbedding.supIrredLowerSet_surjective /-- **Birkhoff Representation for partial orders.** Any partial order is isomorphic to the partial order of inf-irreducible elements in its lattice of upper sets. -/ noncomputable def infIrredUpperSet : α ≃o {s : UpperSet α // InfIrred s} := RelIso.ofSurjective _ OrderEmbedding.infIrredUpperSet_surjective @[simp] lemma supIrredLowerSet_apply (a : α) : supIrredLowerSet a = ⟨Iic a, supIrred_Iic _⟩ := rfl @[simp] lemma infIrredUpperSet_apply (a : α) : infIrredUpperSet a = ⟨Ici a, infIrred_Ici _⟩ := rfl end OrderIso end PartialOrder namespace OrderIso section SemilatticeSup variable [SemilatticeSup α] [OrderBot α] [Finite α] @[simp] lemma supIrredLowerSet_symm_apply (s : {s : LowerSet α // SupIrred s}) [Fintype s] : supIrredLowerSet.symm s = (s.1 : Set α).toFinset.sup id := by classical obtain ⟨s, hs⟩ := s obtain ⟨a, rfl⟩ := supIrred_iff_of_finite.1 hs cases nonempty_fintype α have : LocallyFiniteOrder α := Fintype.toLocallyFiniteOrder simp [symm_apply_eq] end SemilatticeSup section SemilatticeInf variable [SemilatticeInf α] [OrderTop α] [Finite α] @[simp] lemma infIrredUpperSet_symm_apply (s : {s : UpperSet α // InfIrred s}) [Fintype s] : infIrredUpperSet.symm s = (s.1 : Set α).toFinset.inf id := by classical obtain ⟨s, hs⟩ := s obtain ⟨a, rfl⟩ := infIrred_iff_of_finite.1 hs cases nonempty_fintype α have : LocallyFiniteOrder α := Fintype.toLocallyFiniteOrder simp [symm_apply_eq] end SemilatticeInf end OrderIso section DistribLattice variable [DistribLattice α] [Fintype α] [@DecidablePred α SupIrred] open Classical in /-- **Birkhoff Representation for finite distributive lattices**. Any nonempty finite distributive lattice is isomorphic to the lattice of lower sets of its sup-irreducible elements. -/ noncomputable def OrderIso.lowerSetSupIrred [OrderBot α] : α ≃o LowerSet {a : α // SupIrred a} := Equiv.toOrderIso { toFun := fun a ↦ ⟨{b | ↑b ≤ a}, fun _ _ hcb hba ↦ hba.trans' hcb⟩ invFun := fun s ↦ (s : Set {a : α // SupIrred a}).toFinset.sup (↑) left_inv := fun a ↦ by refine le_antisymm (Finset.sup_le fun b ↦ Set.mem_toFinset.1) ?_ obtain ⟨s, rfl, hs⟩ := exists_supIrred_decomposition a exact Finset.sup_le fun i hi ↦ le_sup_of_le (b := ⟨i, hs hi⟩) (Set.mem_toFinset.2 <| le_sup (f := id) hi) le_rfl right_inv := fun s ↦ by ext a dsimp refine ⟨fun ha ↦ ?_, fun ha ↦ ?_⟩ · obtain ⟨i, hi, ha⟩ := a.2.supPrime.le_finset_sup.1 ha exact s.lower ha (Set.mem_toFinset.1 hi) · dsimp exact le_sup (Set.mem_toFinset.2 ha) } (fun _ _ hbc _ ↦ le_trans' hbc) fun _ _ hst ↦ Finset.sup_mono <| Set.toFinset_mono hst namespace OrderEmbedding /-- **Birkhoff's Representation Theorem**. Any finite distributive lattice can be embedded in a powerset lattice. -/ noncomputable def birkhoffSet : α ↪o Set {a : α // SupIrred a} := by by_cases h : IsEmpty α · exact OrderEmbedding.ofIsEmpty rw [not_isEmpty_iff] at h have := Fintype.toOrderBot α exact OrderIso.lowerSetSupIrred.toOrderEmbedding.trans ⟨⟨_, SetLike.coe_injective⟩, Iff.rfl⟩ /-- **Birkhoff's Representation Theorem**. Any finite distributive lattice can be embedded in a powerset lattice. -/ noncomputable def birkhoffFinset : α ↪o Finset {a : α // SupIrred a} := by exact birkhoffSet.trans Fintype.finsetOrderIsoSet.symm.toOrderEmbedding @[simp] lemma coe_birkhoffFinset (a : α) : birkhoffFinset a = birkhoffSet a := by classical -- TODO: This should be a single `simp` call but `simp` refuses to use -- `OrderIso.coe_toOrderEmbedding` and `Fintype.coe_finsetOrderIsoSet_symm` simp [birkhoffFinset] rw [OrderIso.coe_toOrderEmbedding, Fintype.coe_finsetOrderIsoSet_symm] simp @[simp] lemma birkhoffSet_sup (a b : α) : birkhoffSet (a ⊔ b) = birkhoffSet a ∪ birkhoffSet b := by unfold OrderEmbedding.birkhoffSet; split <;> simp [eq_iff_true_of_subsingleton] @[simp] lemma birkhoffSet_inf (a b : α) : birkhoffSet (a ⊓ b) = birkhoffSet a ∩ birkhoffSet b := by unfold OrderEmbedding.birkhoffSet; split <;> simp [eq_iff_true_of_subsingleton] @[simp] lemma birkhoffSet_apply [OrderBot α] (a : α) : birkhoffSet a = OrderIso.lowerSetSupIrred a := by simp [birkhoffSet]; have : Subsingleton (OrderBot α) := inferInstance; convert rfl
variable [DecidableEq α] @[simp] lemma birkhoffFinset_sup (a b : α) : birkhoffFinset (a ⊔ b) = birkhoffFinset a ∪ birkhoffFinset b := by
Mathlib/Order/Birkhoff.lean
238
242
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot -/ import Mathlib.Algebra.Group.Subgroup.Pointwise import Mathlib.Algebra.Order.Archimedean.Basic import Mathlib.Order.Filter.Bases.Finite import Mathlib.Topology.Algebra.Group.Defs import Mathlib.Topology.Algebra.Monoid import Mathlib.Topology.Homeomorph.Lemmas /-! # Topological groups This file defines the following typeclasses: * `IsTopologicalGroup`, `IsTopologicalAddGroup`: multiplicative and additive topological groups, i.e., groups with continuous `(*)` and `(⁻¹)` / `(+)` and `(-)`; * `ContinuousSub G` means that `G` has a continuous subtraction operation. There is an instance deducing `ContinuousSub` from `IsTopologicalGroup` but we use a separate typeclass because, e.g., `ℕ` and `ℝ≥0` have continuous subtraction but are not additive groups. We also define `Homeomorph` versions of several `Equiv`s: `Homeomorph.mulLeft`, `Homeomorph.mulRight`, `Homeomorph.inv`, and prove a few facts about neighbourhood filters in groups. ## Tags topological space, group, topological group -/ open Set Filter TopologicalSpace Function Topology MulOpposite Pointwise universe u v w x variable {G : Type w} {H : Type x} {α : Type u} {β : Type v} section ContinuousMulGroup /-! ### Groups with continuous multiplication In this section we prove a few statements about groups with continuous `(*)`. -/ variable [TopologicalSpace G] [Group G] [ContinuousMul G] /-- Multiplication from the left in a topological group as a homeomorphism. -/ @[to_additive "Addition from the left in a topological additive group as a homeomorphism."] protected def Homeomorph.mulLeft (a : G) : G ≃ₜ G := { Equiv.mulLeft a with continuous_toFun := continuous_const.mul continuous_id continuous_invFun := continuous_const.mul continuous_id } @[to_additive (attr := simp)] theorem Homeomorph.coe_mulLeft (a : G) : ⇑(Homeomorph.mulLeft a) = (a * ·) := rfl @[to_additive] theorem Homeomorph.mulLeft_symm (a : G) : (Homeomorph.mulLeft a).symm = Homeomorph.mulLeft a⁻¹ := by ext rfl @[to_additive] lemma isOpenMap_mul_left (a : G) : IsOpenMap (a * ·) := (Homeomorph.mulLeft a).isOpenMap @[to_additive IsOpen.left_addCoset] theorem IsOpen.leftCoset {U : Set G} (h : IsOpen U) (x : G) : IsOpen (x • U) := isOpenMap_mul_left x _ h @[to_additive] lemma isClosedMap_mul_left (a : G) : IsClosedMap (a * ·) := (Homeomorph.mulLeft a).isClosedMap @[to_additive IsClosed.left_addCoset] theorem IsClosed.leftCoset {U : Set G} (h : IsClosed U) (x : G) : IsClosed (x • U) := isClosedMap_mul_left x _ h /-- Multiplication from the right in a topological group as a homeomorphism. -/ @[to_additive "Addition from the right in a topological additive group as a homeomorphism."] protected def Homeomorph.mulRight (a : G) : G ≃ₜ G := { Equiv.mulRight a with continuous_toFun := continuous_id.mul continuous_const continuous_invFun := continuous_id.mul continuous_const } @[to_additive (attr := simp)] lemma Homeomorph.coe_mulRight (a : G) : ⇑(Homeomorph.mulRight a) = (· * a) := rfl @[to_additive] theorem Homeomorph.mulRight_symm (a : G) : (Homeomorph.mulRight a).symm = Homeomorph.mulRight a⁻¹ := by ext rfl @[to_additive] theorem isOpenMap_mul_right (a : G) : IsOpenMap (· * a) := (Homeomorph.mulRight a).isOpenMap @[to_additive IsOpen.right_addCoset] theorem IsOpen.rightCoset {U : Set G} (h : IsOpen U) (x : G) : IsOpen (op x • U) := isOpenMap_mul_right x _ h @[to_additive] theorem isClosedMap_mul_right (a : G) : IsClosedMap (· * a) := (Homeomorph.mulRight a).isClosedMap @[to_additive IsClosed.right_addCoset] theorem IsClosed.rightCoset {U : Set G} (h : IsClosed U) (x : G) : IsClosed (op x • U) := isClosedMap_mul_right x _ h @[to_additive] theorem discreteTopology_of_isOpen_singleton_one (h : IsOpen ({1} : Set G)) : DiscreteTopology G := by rw [← singletons_open_iff_discrete] intro g suffices {g} = (g⁻¹ * ·) ⁻¹' {1} by rw [this] exact (continuous_mul_left g⁻¹).isOpen_preimage _ h simp only [mul_one, Set.preimage_mul_left_singleton, eq_self_iff_true, inv_inv, Set.singleton_eq_singleton_iff] @[to_additive] theorem discreteTopology_iff_isOpen_singleton_one : DiscreteTopology G ↔ IsOpen ({1} : Set G) := ⟨fun h => forall_open_iff_discrete.mpr h {1}, discreteTopology_of_isOpen_singleton_one⟩ end ContinuousMulGroup /-! ### `ContinuousInv` and `ContinuousNeg` -/ section ContinuousInv variable [TopologicalSpace G] [Inv G] [ContinuousInv G] @[to_additive] theorem ContinuousInv.induced {α : Type*} {β : Type*} {F : Type*} [FunLike F α β] [Group α] [DivisionMonoid β] [MonoidHomClass F α β] [tβ : TopologicalSpace β] [ContinuousInv β] (f : F) : @ContinuousInv α (tβ.induced f) _ := by let _tα := tβ.induced f refine ⟨continuous_induced_rng.2 ?_⟩ simp only [Function.comp_def, map_inv] fun_prop @[to_additive] protected theorem Specializes.inv {x y : G} (h : x ⤳ y) : (x⁻¹) ⤳ (y⁻¹) := h.map continuous_inv @[to_additive] protected theorem Inseparable.inv {x y : G} (h : Inseparable x y) : Inseparable (x⁻¹) (y⁻¹) := h.map continuous_inv @[to_additive] protected theorem Specializes.zpow {G : Type*} [DivInvMonoid G] [TopologicalSpace G] [ContinuousMul G] [ContinuousInv G] {x y : G} (h : x ⤳ y) : ∀ m : ℤ, (x ^ m) ⤳ (y ^ m) | .ofNat n => by simpa using h.pow n | .negSucc n => by simpa using (h.pow (n + 1)).inv @[to_additive] protected theorem Inseparable.zpow {G : Type*} [DivInvMonoid G] [TopologicalSpace G] [ContinuousMul G] [ContinuousInv G] {x y : G} (h : Inseparable x y) (m : ℤ) : Inseparable (x ^ m) (y ^ m) := (h.specializes.zpow m).antisymm (h.specializes'.zpow m) @[to_additive] instance : ContinuousInv (ULift G) := ⟨continuous_uliftUp.comp (continuous_inv.comp continuous_uliftDown)⟩ @[to_additive] theorem continuousOn_inv {s : Set G} : ContinuousOn Inv.inv s := continuous_inv.continuousOn @[to_additive] theorem continuousWithinAt_inv {s : Set G} {x : G} : ContinuousWithinAt Inv.inv s x := continuous_inv.continuousWithinAt @[to_additive] theorem continuousAt_inv {x : G} : ContinuousAt Inv.inv x := continuous_inv.continuousAt @[to_additive] theorem tendsto_inv (a : G) : Tendsto Inv.inv (𝓝 a) (𝓝 a⁻¹) := continuousAt_inv variable [TopologicalSpace α] {f : α → G} {s : Set α} {x : α} @[to_additive] instance OrderDual.instContinuousInv : ContinuousInv Gᵒᵈ := ‹ContinuousInv G› @[to_additive] instance Prod.continuousInv [TopologicalSpace H] [Inv H] [ContinuousInv H] : ContinuousInv (G × H) := ⟨continuous_inv.fst'.prodMk continuous_inv.snd'⟩ variable {ι : Type*} @[to_additive] instance Pi.continuousInv {C : ι → Type*} [∀ i, TopologicalSpace (C i)] [∀ i, Inv (C i)] [∀ i, ContinuousInv (C i)] : ContinuousInv (∀ i, C i) where continuous_inv := continuous_pi fun i => (continuous_apply i).inv /-- A version of `Pi.continuousInv` for non-dependent functions. It is needed because sometimes Lean fails to use `Pi.continuousInv` for non-dependent functions. -/ @[to_additive "A version of `Pi.continuousNeg` for non-dependent functions. It is needed because sometimes Lean fails to use `Pi.continuousNeg` for non-dependent functions."] instance Pi.has_continuous_inv' : ContinuousInv (ι → G) := Pi.continuousInv @[to_additive] instance (priority := 100) continuousInv_of_discreteTopology [TopologicalSpace H] [Inv H] [DiscreteTopology H] : ContinuousInv H := ⟨continuous_of_discreteTopology⟩ section PointwiseLimits variable (G₁ G₂ : Type*) [TopologicalSpace G₂] [T2Space G₂] @[to_additive] theorem isClosed_setOf_map_inv [Inv G₁] [Inv G₂] [ContinuousInv G₂] : IsClosed { f : G₁ → G₂ | ∀ x, f x⁻¹ = (f x)⁻¹ } := by simp only [setOf_forall] exact isClosed_iInter fun i => isClosed_eq (continuous_apply _) (continuous_apply _).inv end PointwiseLimits instance [TopologicalSpace H] [Inv H] [ContinuousInv H] : ContinuousNeg (Additive H) where continuous_neg := @continuous_inv H _ _ _ instance [TopologicalSpace H] [Neg H] [ContinuousNeg H] : ContinuousInv (Multiplicative H) where continuous_inv := @continuous_neg H _ _ _ end ContinuousInv section ContinuousInvolutiveInv variable [TopologicalSpace G] [InvolutiveInv G] [ContinuousInv G] {s : Set G} @[to_additive] theorem IsCompact.inv (hs : IsCompact s) : IsCompact s⁻¹ := by rw [← image_inv_eq_inv] exact hs.image continuous_inv variable (G) /-- Inversion in a topological group as a homeomorphism. -/ @[to_additive "Negation in a topological group as a homeomorphism."] protected def Homeomorph.inv (G : Type*) [TopologicalSpace G] [InvolutiveInv G] [ContinuousInv G] : G ≃ₜ G := { Equiv.inv G with continuous_toFun := continuous_inv continuous_invFun := continuous_inv } @[to_additive (attr := simp)] lemma Homeomorph.coe_inv {G : Type*} [TopologicalSpace G] [InvolutiveInv G] [ContinuousInv G] : ⇑(Homeomorph.inv G) = Inv.inv := rfl @[to_additive] theorem nhds_inv (a : G) : 𝓝 a⁻¹ = (𝓝 a)⁻¹ := ((Homeomorph.inv G).map_nhds_eq a).symm @[to_additive] theorem isOpenMap_inv : IsOpenMap (Inv.inv : G → G) := (Homeomorph.inv _).isOpenMap @[to_additive] theorem isClosedMap_inv : IsClosedMap (Inv.inv : G → G) := (Homeomorph.inv _).isClosedMap variable {G} @[to_additive] theorem IsOpen.inv (hs : IsOpen s) : IsOpen s⁻¹ := hs.preimage continuous_inv @[to_additive] theorem IsClosed.inv (hs : IsClosed s) : IsClosed s⁻¹ := hs.preimage continuous_inv @[to_additive] theorem inv_closure : ∀ s : Set G, (closure s)⁻¹ = closure s⁻¹ := (Homeomorph.inv G).preimage_closure variable [TopologicalSpace α] {f : α → G} {s : Set α} {x : α} @[to_additive (attr := simp)] lemma continuous_inv_iff : Continuous f⁻¹ ↔ Continuous f := (Homeomorph.inv G).comp_continuous_iff @[to_additive (attr := simp)] lemma continuousAt_inv_iff : ContinuousAt f⁻¹ x ↔ ContinuousAt f x := (Homeomorph.inv G).comp_continuousAt_iff _ _ @[to_additive (attr := simp)] lemma continuousOn_inv_iff : ContinuousOn f⁻¹ s ↔ ContinuousOn f s := (Homeomorph.inv G).comp_continuousOn_iff _ _ @[to_additive] alias ⟨Continuous.of_inv, _⟩ := continuous_inv_iff @[to_additive] alias ⟨ContinuousAt.of_inv, _⟩ := continuousAt_inv_iff @[to_additive] alias ⟨ContinuousOn.of_inv, _⟩ := continuousOn_inv_iff end ContinuousInvolutiveInv section LatticeOps variable {ι' : Sort*} [Inv G] @[to_additive] theorem continuousInv_sInf {ts : Set (TopologicalSpace G)} (h : ∀ t ∈ ts, @ContinuousInv G t _) : @ContinuousInv G (sInf ts) _ := letI := sInf ts { continuous_inv := continuous_sInf_rng.2 fun t ht => continuous_sInf_dom ht (@ContinuousInv.continuous_inv G t _ (h t ht)) } @[to_additive] theorem continuousInv_iInf {ts' : ι' → TopologicalSpace G} (h' : ∀ i, @ContinuousInv G (ts' i) _) : @ContinuousInv G (⨅ i, ts' i) _ := by rw [← sInf_range] exact continuousInv_sInf (Set.forall_mem_range.mpr h') @[to_additive] theorem continuousInv_inf {t₁ t₂ : TopologicalSpace G} (h₁ : @ContinuousInv G t₁ _) (h₂ : @ContinuousInv G t₂ _) : @ContinuousInv G (t₁ ⊓ t₂) _ := by rw [inf_eq_iInf] refine continuousInv_iInf fun b => ?_ cases b <;> assumption end LatticeOps @[to_additive] theorem Topology.IsInducing.continuousInv {G H : Type*} [Inv G] [Inv H] [TopologicalSpace G] [TopologicalSpace H] [ContinuousInv H] {f : G → H} (hf : IsInducing f) (hf_inv : ∀ x, f x⁻¹ = (f x)⁻¹) : ContinuousInv G := ⟨hf.continuous_iff.2 <| by simpa only [Function.comp_def, hf_inv] using hf.continuous.inv⟩ @[deprecated (since := "2024-10-28")] alias Inducing.continuousInv := IsInducing.continuousInv section IsTopologicalGroup /-! ### Topological groups A topological group is a group in which the multiplication and inversion operations are continuous. Topological additive groups are defined in the same way. Equivalently, we can require that the division operation `x y ↦ x * y⁻¹` (resp., subtraction) is continuous. -/ section Conj instance ConjAct.units_continuousConstSMul {M} [Monoid M] [TopologicalSpace M] [ContinuousMul M] : ContinuousConstSMul (ConjAct Mˣ) M := ⟨fun _ => (continuous_const.mul continuous_id).mul continuous_const⟩ variable [TopologicalSpace G] [Inv G] [Mul G] [ContinuousMul G] /-- Conjugation is jointly continuous on `G × G` when both `mul` and `inv` are continuous. -/ @[to_additive continuous_addConj_prod "Conjugation is jointly continuous on `G × G` when both `add` and `neg` are continuous."] theorem IsTopologicalGroup.continuous_conj_prod [ContinuousInv G] : Continuous fun g : G × G => g.fst * g.snd * g.fst⁻¹ := continuous_mul.mul (continuous_inv.comp continuous_fst) @[deprecated (since := "2025-03-11")] alias IsTopologicalAddGroup.continuous_conj_sum := IsTopologicalAddGroup.continuous_addConj_prod /-- Conjugation by a fixed element is continuous when `mul` is continuous. -/ @[to_additive (attr := continuity) "Conjugation by a fixed element is continuous when `add` is continuous."] theorem IsTopologicalGroup.continuous_conj (g : G) : Continuous fun h : G => g * h * g⁻¹ := (continuous_mul_right g⁻¹).comp (continuous_mul_left g) /-- Conjugation acting on fixed element of the group is continuous when both `mul` and `inv` are continuous. -/ @[to_additive (attr := continuity) "Conjugation acting on fixed element of the additive group is continuous when both `add` and `neg` are continuous."] theorem IsTopologicalGroup.continuous_conj' [ContinuousInv G] (h : G) : Continuous fun g : G => g * h * g⁻¹ := (continuous_mul_right h).mul continuous_inv end Conj variable [TopologicalSpace G] [Group G] [IsTopologicalGroup G] [TopologicalSpace α] {f : α → G} {s : Set α} {x : α} instance : IsTopologicalGroup (ULift G) where section ZPow @[to_additive (attr := continuity, fun_prop)] theorem continuous_zpow : ∀ z : ℤ, Continuous fun a : G => a ^ z | Int.ofNat n => by simpa using continuous_pow n | Int.negSucc n => by simpa using (continuous_pow (n + 1)).inv instance AddGroup.continuousConstSMul_int {A} [AddGroup A] [TopologicalSpace A] [IsTopologicalAddGroup A] : ContinuousConstSMul ℤ A := ⟨continuous_zsmul⟩ instance AddGroup.continuousSMul_int {A} [AddGroup A] [TopologicalSpace A] [IsTopologicalAddGroup A] : ContinuousSMul ℤ A := ⟨continuous_prod_of_discrete_left.mpr continuous_zsmul⟩ @[to_additive (attr := continuity, fun_prop)] theorem Continuous.zpow {f : α → G} (h : Continuous f) (z : ℤ) : Continuous fun b => f b ^ z := (continuous_zpow z).comp h @[to_additive] theorem continuousOn_zpow {s : Set G} (z : ℤ) : ContinuousOn (fun x => x ^ z) s := (continuous_zpow z).continuousOn @[to_additive] theorem continuousAt_zpow (x : G) (z : ℤ) : ContinuousAt (fun x => x ^ z) x := (continuous_zpow z).continuousAt @[to_additive] theorem Filter.Tendsto.zpow {α} {l : Filter α} {f : α → G} {x : G} (hf : Tendsto f l (𝓝 x)) (z : ℤ) : Tendsto (fun x => f x ^ z) l (𝓝 (x ^ z)) := (continuousAt_zpow _ _).tendsto.comp hf @[to_additive] theorem ContinuousWithinAt.zpow {f : α → G} {x : α} {s : Set α} (hf : ContinuousWithinAt f s x) (z : ℤ) : ContinuousWithinAt (fun x => f x ^ z) s x := Filter.Tendsto.zpow hf z @[to_additive (attr := fun_prop)] theorem ContinuousAt.zpow {f : α → G} {x : α} (hf : ContinuousAt f x) (z : ℤ) : ContinuousAt (fun x => f x ^ z) x := Filter.Tendsto.zpow hf z @[to_additive (attr := fun_prop)] theorem ContinuousOn.zpow {f : α → G} {s : Set α} (hf : ContinuousOn f s) (z : ℤ) : ContinuousOn (fun x => f x ^ z) s := fun x hx => (hf x hx).zpow z end ZPow section OrderedCommGroup variable [TopologicalSpace H] [CommGroup H] [PartialOrder H] [IsOrderedMonoid H] [ContinuousInv H] @[to_additive] theorem tendsto_inv_nhdsGT {a : H} : Tendsto Inv.inv (𝓝[>] a) (𝓝[<] a⁻¹) := (continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal] @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Ioi := tendsto_neg_nhdsGT @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Ioi := tendsto_inv_nhdsGT @[to_additive] theorem tendsto_inv_nhdsLT {a : H} : Tendsto Inv.inv (𝓝[<] a) (𝓝[>] a⁻¹) := (continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal] @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Iio := tendsto_neg_nhdsLT @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Iio := tendsto_inv_nhdsLT @[to_additive] theorem tendsto_inv_nhdsGT_inv {a : H} : Tendsto Inv.inv (𝓝[>] a⁻¹) (𝓝[<] a) := by simpa only [inv_inv] using tendsto_inv_nhdsGT (a := a⁻¹) @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Ioi_neg := tendsto_neg_nhdsGT_neg @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Ioi_inv := tendsto_inv_nhdsGT_inv @[to_additive] theorem tendsto_inv_nhdsLT_inv {a : H} : Tendsto Inv.inv (𝓝[<] a⁻¹) (𝓝[>] a) := by simpa only [inv_inv] using tendsto_inv_nhdsLT (a := a⁻¹) @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Iio_neg := tendsto_neg_nhdsLT_neg @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Iio_inv := tendsto_inv_nhdsLT_inv @[to_additive] theorem tendsto_inv_nhdsGE {a : H} : Tendsto Inv.inv (𝓝[≥] a) (𝓝[≤] a⁻¹) := (continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal] @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Ici := tendsto_neg_nhdsGE @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Ici := tendsto_inv_nhdsGE @[to_additive] theorem tendsto_inv_nhdsLE {a : H} : Tendsto Inv.inv (𝓝[≤] a) (𝓝[≥] a⁻¹) := (continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal] @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Iic := tendsto_neg_nhdsLE @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Iic := tendsto_inv_nhdsLE @[to_additive] theorem tendsto_inv_nhdsGE_inv {a : H} : Tendsto Inv.inv (𝓝[≥] a⁻¹) (𝓝[≤] a) := by simpa only [inv_inv] using tendsto_inv_nhdsGE (a := a⁻¹) @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Ici_neg := tendsto_neg_nhdsGE_neg @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Ici_inv := tendsto_inv_nhdsGE_inv @[to_additive] theorem tendsto_inv_nhdsLE_inv {a : H} : Tendsto Inv.inv (𝓝[≤] a⁻¹) (𝓝[≥] a) := by simpa only [inv_inv] using tendsto_inv_nhdsLE (a := a⁻¹) @[deprecated (since := "2024-12-22")] alias tendsto_neg_nhdsWithin_Iic_neg := tendsto_neg_nhdsLE_neg @[to_additive existing, deprecated (since := "2024-12-22")] alias tendsto_inv_nhdsWithin_Iic_inv := tendsto_inv_nhdsLE_inv end OrderedCommGroup @[to_additive] instance Prod.instIsTopologicalGroup [TopologicalSpace H] [Group H] [IsTopologicalGroup H] : IsTopologicalGroup (G × H) where continuous_inv := continuous_inv.prodMap continuous_inv @[to_additive] instance OrderDual.instIsTopologicalGroup : IsTopologicalGroup Gᵒᵈ where @[to_additive] instance Pi.topologicalGroup {C : β → Type*} [∀ b, TopologicalSpace (C b)] [∀ b, Group (C b)] [∀ b, IsTopologicalGroup (C b)] : IsTopologicalGroup (∀ b, C b) where continuous_inv := continuous_pi fun i => (continuous_apply i).inv open MulOpposite @[to_additive] instance [Inv α] [ContinuousInv α] : ContinuousInv αᵐᵒᵖ := opHomeomorph.symm.isInducing.continuousInv unop_inv /-- If multiplication is continuous in `α`, then it also is in `αᵐᵒᵖ`. -/ @[to_additive "If addition is continuous in `α`, then it also is in `αᵃᵒᵖ`."] instance [Group α] [IsTopologicalGroup α] : IsTopologicalGroup αᵐᵒᵖ where variable (G) @[to_additive] theorem nhds_one_symm : comap Inv.inv (𝓝 (1 : G)) = 𝓝 (1 : G) := ((Homeomorph.inv G).comap_nhds_eq _).trans (congr_arg nhds inv_one) @[to_additive] theorem nhds_one_symm' : map Inv.inv (𝓝 (1 : G)) = 𝓝 (1 : G) := ((Homeomorph.inv G).map_nhds_eq _).trans (congr_arg nhds inv_one) @[to_additive] theorem inv_mem_nhds_one {S : Set G} (hS : S ∈ (𝓝 1 : Filter G)) : S⁻¹ ∈ 𝓝 (1 : G) := by rwa [← nhds_one_symm'] at hS /-- The map `(x, y) ↦ (x, x * y)` as a homeomorphism. This is a shear mapping. -/ @[to_additive "The map `(x, y) ↦ (x, x + y)` as a homeomorphism. This is a shear mapping."] protected def Homeomorph.shearMulRight : G × G ≃ₜ G × G := { Equiv.prodShear (Equiv.refl _) Equiv.mulLeft with continuous_toFun := by dsimp; fun_prop continuous_invFun := by dsimp; fun_prop } @[to_additive (attr := simp)] theorem Homeomorph.shearMulRight_coe : ⇑(Homeomorph.shearMulRight G) = fun z : G × G => (z.1, z.1 * z.2) := rfl @[to_additive (attr := simp)] theorem Homeomorph.shearMulRight_symm_coe : ⇑(Homeomorph.shearMulRight G).symm = fun z : G × G => (z.1, z.1⁻¹ * z.2) := rfl variable {G} @[to_additive] protected theorem Topology.IsInducing.topologicalGroup {F : Type*} [Group H] [TopologicalSpace H] [FunLike F H G] [MonoidHomClass F H G] (f : F) (hf : IsInducing f) : IsTopologicalGroup H := { toContinuousMul := hf.continuousMul _ toContinuousInv := hf.continuousInv (map_inv f) } @[deprecated (since := "2024-10-28")] alias Inducing.topologicalGroup := IsInducing.topologicalGroup @[to_additive] theorem topologicalGroup_induced {F : Type*} [Group H] [FunLike F H G] [MonoidHomClass F H G] (f : F) : @IsTopologicalGroup H (induced f ‹_›) _ := letI := induced f ‹_› IsInducing.topologicalGroup f ⟨rfl⟩ namespace Subgroup @[to_additive] instance (S : Subgroup G) : IsTopologicalGroup S := IsInducing.subtypeVal.topologicalGroup S.subtype end Subgroup /-- The (topological-space) closure of a subgroup of a topological group is itself a subgroup. -/ @[to_additive "The (topological-space) closure of an additive subgroup of an additive topological group is itself an additive subgroup."] def Subgroup.topologicalClosure (s : Subgroup G) : Subgroup G := { s.toSubmonoid.topologicalClosure with carrier := _root_.closure (s : Set G) inv_mem' := fun {g} hg => by simpa only [← Set.mem_inv, inv_closure, inv_coe_set] using hg } @[to_additive (attr := simp)] theorem Subgroup.topologicalClosure_coe {s : Subgroup G} : (s.topologicalClosure : Set G) = _root_.closure s := rfl @[to_additive] theorem Subgroup.le_topologicalClosure (s : Subgroup G) : s ≤ s.topologicalClosure := _root_.subset_closure @[to_additive] theorem Subgroup.isClosed_topologicalClosure (s : Subgroup G) : IsClosed (s.topologicalClosure : Set G) := isClosed_closure @[to_additive] theorem Subgroup.topologicalClosure_minimal (s : Subgroup G) {t : Subgroup G} (h : s ≤ t) (ht : IsClosed (t : Set G)) : s.topologicalClosure ≤ t := closure_minimal h ht @[to_additive] theorem DenseRange.topologicalClosure_map_subgroup [Group H] [TopologicalSpace H] [IsTopologicalGroup H] {f : G →* H} (hf : Continuous f) (hf' : DenseRange f) {s : Subgroup G} (hs : s.topologicalClosure = ⊤) : (s.map f).topologicalClosure = ⊤ := by rw [SetLike.ext'_iff] at hs ⊢ simp only [Subgroup.topologicalClosure_coe, Subgroup.coe_top, ← dense_iff_closure_eq] at hs ⊢ exact hf'.dense_image hf hs /-- The topological closure of a normal subgroup is normal. -/ @[to_additive "The topological closure of a normal additive subgroup is normal."] theorem Subgroup.is_normal_topologicalClosure {G : Type*} [TopologicalSpace G] [Group G] [IsTopologicalGroup G] (N : Subgroup G) [N.Normal] : (Subgroup.topologicalClosure N).Normal where conj_mem n hn g := by apply map_mem_closure (IsTopologicalGroup.continuous_conj g) hn exact fun m hm => Subgroup.Normal.conj_mem inferInstance m hm g @[to_additive] theorem mul_mem_connectedComponent_one {G : Type*} [TopologicalSpace G] [MulOneClass G] [ContinuousMul G] {g h : G} (hg : g ∈ connectedComponent (1 : G)) (hh : h ∈ connectedComponent (1 : G)) : g * h ∈ connectedComponent (1 : G) := by rw [connectedComponent_eq hg] have hmul : g ∈ connectedComponent (g * h) := by apply Continuous.image_connectedComponent_subset (continuous_mul_left g) rw [← connectedComponent_eq hh] exact ⟨(1 : G), mem_connectedComponent, by simp only [mul_one]⟩ simpa [← connectedComponent_eq hmul] using mem_connectedComponent @[to_additive] theorem inv_mem_connectedComponent_one {G : Type*} [TopologicalSpace G] [DivisionMonoid G] [ContinuousInv G] {g : G} (hg : g ∈ connectedComponent (1 : G)) : g⁻¹ ∈ connectedComponent (1 : G) := by rw [← inv_one] exact Continuous.image_connectedComponent_subset continuous_inv _ ((Set.mem_image _ _ _).mp ⟨g, hg, rfl⟩) /-- The connected component of 1 is a subgroup of `G`. -/ @[to_additive "The connected component of 0 is a subgroup of `G`."] def Subgroup.connectedComponentOfOne (G : Type*) [TopologicalSpace G] [Group G] [IsTopologicalGroup G] : Subgroup G where carrier := connectedComponent (1 : G) one_mem' := mem_connectedComponent mul_mem' hg hh := mul_mem_connectedComponent_one hg hh inv_mem' hg := inv_mem_connectedComponent_one hg /-- If a subgroup of a topological group is commutative, then so is its topological closure. See note [reducible non-instances]. -/ @[to_additive "If a subgroup of an additive topological group is commutative, then so is its topological closure. See note [reducible non-instances]."] abbrev Subgroup.commGroupTopologicalClosure [T2Space G] (s : Subgroup G) (hs : ∀ x y : s, x * y = y * x) : CommGroup s.topologicalClosure := { s.topologicalClosure.toGroup, s.toSubmonoid.commMonoidTopologicalClosure hs with } variable (G) in @[to_additive] lemma Subgroup.coe_topologicalClosure_bot : ((⊥ : Subgroup G).topologicalClosure : Set G) = _root_.closure ({1} : Set G) := by simp @[to_additive exists_nhds_half_neg] theorem exists_nhds_split_inv {s : Set G} (hs : s ∈ 𝓝 (1 : G)) : ∃ V ∈ 𝓝 (1 : G), ∀ v ∈ V, ∀ w ∈ V, v / w ∈ s := by have : (fun p : G × G => p.1 * p.2⁻¹) ⁻¹' s ∈ 𝓝 ((1, 1) : G × G) := continuousAt_fst.mul continuousAt_snd.inv (by simpa) simpa only [div_eq_mul_inv, nhds_prod_eq, mem_prod_self_iff, prod_subset_iff, mem_preimage] using this @[to_additive] theorem nhds_translation_mul_inv (x : G) : comap (· * x⁻¹) (𝓝 1) = 𝓝 x := ((Homeomorph.mulRight x⁻¹).comap_nhds_eq 1).trans <| show 𝓝 (1 * x⁻¹⁻¹) = 𝓝 x by simp @[to_additive (attr := simp)] theorem map_mul_left_nhds (x y : G) : map (x * ·) (𝓝 y) = 𝓝 (x * y) := (Homeomorph.mulLeft x).map_nhds_eq y @[to_additive] theorem map_mul_left_nhds_one (x : G) : map (x * ·) (𝓝 1) = 𝓝 x := by simp @[to_additive (attr := simp)] theorem map_mul_right_nhds (x y : G) : map (· * x) (𝓝 y) = 𝓝 (y * x) := (Homeomorph.mulRight x).map_nhds_eq y @[to_additive] theorem map_mul_right_nhds_one (x : G) : map (· * x) (𝓝 1) = 𝓝 x := by simp @[to_additive] theorem Filter.HasBasis.nhds_of_one {ι : Sort*} {p : ι → Prop} {s : ι → Set G} (hb : HasBasis (𝓝 1 : Filter G) p s) (x : G) : HasBasis (𝓝 x) p fun i => { y | y / x ∈ s i } := by rw [← nhds_translation_mul_inv] simp_rw [div_eq_mul_inv] exact hb.comap _ @[to_additive] theorem mem_closure_iff_nhds_one {x : G} {s : Set G} : x ∈ closure s ↔ ∀ U ∈ (𝓝 1 : Filter G), ∃ y ∈ s, y / x ∈ U := by rw [mem_closure_iff_nhds_basis ((𝓝 1 : Filter G).basis_sets.nhds_of_one x)] simp_rw [Set.mem_setOf, id] /-- A monoid homomorphism (a bundled morphism of a type that implements `MonoidHomClass`) from a topological group to a topological monoid is continuous provided that it is continuous at one. See also `uniformContinuous_of_continuousAt_one`. -/ @[to_additive "An additive monoid homomorphism (a bundled morphism of a type that implements `AddMonoidHomClass`) from an additive topological group to an additive topological monoid is continuous provided that it is continuous at zero. See also `uniformContinuous_of_continuousAt_zero`."] theorem continuous_of_continuousAt_one {M hom : Type*} [MulOneClass M] [TopologicalSpace M] [ContinuousMul M] [FunLike hom G M] [MonoidHomClass hom G M] (f : hom) (hf : ContinuousAt f 1) : Continuous f := continuous_iff_continuousAt.2 fun x => by simpa only [ContinuousAt, ← map_mul_left_nhds_one x, tendsto_map'_iff, Function.comp_def, map_mul, map_one, mul_one] using hf.tendsto.const_mul (f x) @[to_additive continuous_of_continuousAt_zero₂] theorem continuous_of_continuousAt_one₂ {H M : Type*} [CommMonoid M] [TopologicalSpace M] [ContinuousMul M] [Group H] [TopologicalSpace H] [IsTopologicalGroup H] (f : G →* H →* M) (hf : ContinuousAt (fun x : G × H ↦ f x.1 x.2) (1, 1)) (hl : ∀ x, ContinuousAt (f x) 1) (hr : ∀ y, ContinuousAt (f · y) 1) : Continuous (fun x : G × H ↦ f x.1 x.2) := continuous_iff_continuousAt.2 fun (x, y) => by simp only [ContinuousAt, nhds_prod_eq, ← map_mul_left_nhds_one x, ← map_mul_left_nhds_one y, prod_map_map_eq, tendsto_map'_iff, Function.comp_def, map_mul, MonoidHom.mul_apply] at * refine ((tendsto_const_nhds.mul ((hr y).comp tendsto_fst)).mul (((hl x).comp tendsto_snd).mul hf)).mono_right (le_of_eq ?_) simp only [map_one, mul_one, MonoidHom.one_apply] @[to_additive] lemma IsTopologicalGroup.isInducing_iff_nhds_one {H : Type*} [Group H] [TopologicalSpace H] [IsTopologicalGroup H] {F : Type*} [FunLike F G H] [MonoidHomClass F G H] {f : F} : Topology.IsInducing f ↔ 𝓝 (1 : G) = (𝓝 (1 : H)).comap f := by rw [Topology.isInducing_iff_nhds] refine ⟨(map_one f ▸ · 1), fun hf x ↦ ?_⟩ rw [← nhds_translation_mul_inv, ← nhds_translation_mul_inv (f x), Filter.comap_comap, hf, Filter.comap_comap] congr 1 ext; simp @[to_additive] lemma TopologicalGroup.isOpenMap_iff_nhds_one {H : Type*} [Monoid H] [TopologicalSpace H] [ContinuousConstSMul H H] {F : Type*} [FunLike F G H] [MonoidHomClass F G H] {f : F} : IsOpenMap f ↔ 𝓝 1 ≤ .map f (𝓝 1) := by refine ⟨fun H ↦ map_one f ▸ H.nhds_le 1, fun h ↦ IsOpenMap.of_nhds_le fun x ↦ ?_⟩ have : Filter.map (f x * ·) (𝓝 1) = 𝓝 (f x) := by simpa [-Homeomorph.map_nhds_eq, Units.smul_def] using (Homeomorph.smul ((toUnits x).map (MonoidHomClass.toMonoidHom f))).map_nhds_eq (1 : H) rw [← map_mul_left_nhds_one x, Filter.map_map, Function.comp_def, ← this] refine (Filter.map_mono h).trans ?_ simp [Function.comp_def] -- TODO: unify with `QuotientGroup.isOpenQuotientMap_mk` /-- Let `A` and `B` be topological groups, and let `φ : A → B` be a continuous surjective group homomorphism. Assume furthermore that `φ` is a quotient map (i.e., `V ⊆ B` is open iff `φ⁻¹ V` is open). Then `φ` is an open quotient map, and in particular an open map. -/ @[to_additive "Let `A` and `B` be topological additive groups, and let `φ : A → B` be a continuous surjective additive group homomorphism. Assume furthermore that `φ` is a quotient map (i.e., `V ⊆ B` is open iff `φ⁻¹ V` is open). Then `φ` is an open quotient map, and in particular an open map."] lemma MonoidHom.isOpenQuotientMap_of_isQuotientMap {A : Type*} [Group A] [TopologicalSpace A] [ContinuousMul A] {B : Type*} [Group B] [TopologicalSpace B] {F : Type*} [FunLike F A B] [MonoidHomClass F A B] {φ : F} (hφ : IsQuotientMap φ) : IsOpenQuotientMap φ where surjective := hφ.surjective continuous := hφ.continuous isOpenMap := by -- We need to check that if `U ⊆ A` is open then `φ⁻¹ (φ U)` is open. intro U hU rw [← hφ.isOpen_preimage] -- It suffices to show that `φ⁻¹ (φ U) = ⋃ (U * k⁻¹)` as `k` runs through the kernel of `φ`, -- as `U * k⁻¹` is open because `x ↦ x * k` is continuous. -- Remark: here is where we use that we have groups not monoids (you cannot avoid -- using both `k` and `k⁻¹` at this point). suffices ⇑φ ⁻¹' (⇑φ '' U) = ⋃ k ∈ ker (φ : A →* B), (fun x ↦ x * k) ⁻¹' U by exact this ▸ isOpen_biUnion (fun k _ ↦ Continuous.isOpen_preimage (by fun_prop) _ hU) ext x -- But this is an elementary calculation. constructor · rintro ⟨y, hyU, hyx⟩ apply Set.mem_iUnion_of_mem (x⁻¹ * y) simp_all · rintro ⟨_, ⟨k, rfl⟩, _, ⟨(hk : φ k = 1), rfl⟩, hx⟩ use x * k, hx rw [map_mul, hk, mul_one] @[to_additive] theorem IsTopologicalGroup.ext {G : Type*} [Group G] {t t' : TopologicalSpace G} (tg : @IsTopologicalGroup G t _) (tg' : @IsTopologicalGroup G t' _) (h : @nhds G t 1 = @nhds G t' 1) : t = t' := TopologicalSpace.ext_nhds fun x ↦ by rw [← @nhds_translation_mul_inv G t _ _ x, ← @nhds_translation_mul_inv G t' _ _ x, ← h] @[to_additive] theorem IsTopologicalGroup.ext_iff {G : Type*} [Group G] {t t' : TopologicalSpace G} (tg : @IsTopologicalGroup G t _) (tg' : @IsTopologicalGroup G t' _) : t = t' ↔ @nhds G t 1 = @nhds G t' 1 := ⟨fun h => h ▸ rfl, tg.ext tg'⟩ @[to_additive] theorem ContinuousInv.of_nhds_one {G : Type*} [Group G] [TopologicalSpace G] (hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1)) (hleft : ∀ x₀ : G, 𝓝 x₀ = map (fun x : G => x₀ * x) (𝓝 1)) (hconj : ∀ x₀ : G, Tendsto (fun x : G => x₀ * x * x₀⁻¹) (𝓝 1) (𝓝 1)) : ContinuousInv G := by refine ⟨continuous_iff_continuousAt.2 fun x₀ => ?_⟩ have : Tendsto (fun x => x₀⁻¹ * (x₀ * x⁻¹ * x₀⁻¹)) (𝓝 1) (map (x₀⁻¹ * ·) (𝓝 1)) := (tendsto_map.comp <| hconj x₀).comp hinv simpa only [ContinuousAt, hleft x₀, hleft x₀⁻¹, tendsto_map'_iff, Function.comp_def, mul_assoc, mul_inv_rev, inv_mul_cancel_left] using this @[to_additive] theorem IsTopologicalGroup.of_nhds_one' {G : Type u} [Group G] [TopologicalSpace G] (hmul : Tendsto (uncurry ((· * ·) : G → G → G)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1)) (hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1)) (hleft : ∀ x₀ : G, 𝓝 x₀ = map (fun x => x₀ * x) (𝓝 1)) (hright : ∀ x₀ : G, 𝓝 x₀ = map (fun x => x * x₀) (𝓝 1)) : IsTopologicalGroup G := { toContinuousMul := ContinuousMul.of_nhds_one hmul hleft hright toContinuousInv := ContinuousInv.of_nhds_one hinv hleft fun x₀ => le_of_eq (by rw [show (fun x => x₀ * x * x₀⁻¹) = (fun x => x * x₀⁻¹) ∘ fun x => x₀ * x from rfl, ← map_map, ← hleft, hright, map_map] simp [(· ∘ ·)]) } @[to_additive] theorem IsTopologicalGroup.of_nhds_one {G : Type u} [Group G] [TopologicalSpace G] (hmul : Tendsto (uncurry ((· * ·) : G → G → G)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1)) (hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1)) (hleft : ∀ x₀ : G, 𝓝 x₀ = map (x₀ * ·) (𝓝 1)) (hconj : ∀ x₀ : G, Tendsto (x₀ * · * x₀⁻¹) (𝓝 1) (𝓝 1)) : IsTopologicalGroup G := by refine IsTopologicalGroup.of_nhds_one' hmul hinv hleft fun x₀ => ?_ replace hconj : ∀ x₀ : G, map (x₀ * · * x₀⁻¹) (𝓝 1) = 𝓝 1 := fun x₀ => map_eq_of_inverse (x₀⁻¹ * · * x₀⁻¹⁻¹) (by ext; simp [mul_assoc]) (hconj _) (hconj _) rw [← hconj x₀] simpa [Function.comp_def] using hleft _ @[to_additive] theorem IsTopologicalGroup.of_comm_of_nhds_one {G : Type u} [CommGroup G] [TopologicalSpace G] (hmul : Tendsto (uncurry ((· * ·) : G → G → G)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1)) (hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1)) (hleft : ∀ x₀ : G, 𝓝 x₀ = map (x₀ * ·) (𝓝 1)) : IsTopologicalGroup G := IsTopologicalGroup.of_nhds_one hmul hinv hleft (by simpa using tendsto_id) variable (G) in /-- Any first countable topological group has an antitone neighborhood basis `u : ℕ → Set G` for which `(u (n + 1)) ^ 2 ⊆ u n`. The existence of such a neighborhood basis is a key tool for `QuotientGroup.completeSpace` -/ @[to_additive "Any first countable topological additive group has an antitone neighborhood basis `u : ℕ → set G` for which `u (n + 1) + u (n + 1) ⊆ u n`. The existence of such a neighborhood basis is a key tool for `QuotientAddGroup.completeSpace`"] theorem IsTopologicalGroup.exists_antitone_basis_nhds_one [FirstCountableTopology G] : ∃ u : ℕ → Set G, (𝓝 1).HasAntitoneBasis u ∧ ∀ n, u (n + 1) * u (n + 1) ⊆ u n := by rcases (𝓝 (1 : G)).exists_antitone_basis with ⟨u, hu, u_anti⟩ have := ((hu.prod_nhds hu).tendsto_iff hu).mp (by simpa only [mul_one] using continuous_mul.tendsto ((1, 1) : G × G)) simp only [and_self_iff, mem_prod, and_imp, Prod.forall, exists_true_left, Prod.exists, forall_true_left] at this have event_mul : ∀ n : ℕ, ∀ᶠ m in atTop, u m * u m ⊆ u n := by intro n rcases this n with ⟨j, k, -, h⟩ refine atTop_basis.eventually_iff.mpr ⟨max j k, True.intro, fun m hm => ?_⟩ rintro - ⟨a, ha, b, hb, rfl⟩
exact h a b (u_anti ((le_max_left _ _).trans hm) ha) (u_anti ((le_max_right _ _).trans hm) hb) obtain ⟨φ, -, hφ, φ_anti_basis⟩ := HasAntitoneBasis.subbasis_with_rel ⟨hu, u_anti⟩ event_mul exact ⟨u ∘ φ, φ_anti_basis, fun n => hφ n.lt_succ_self⟩ end IsTopologicalGroup
Mathlib/Topology/Algebra/Group/Basic.lean
892
897
/- Copyright (c) 2021 Heather Macbeth. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Heather Macbeth, Yury Kudryashov -/ import Mathlib.Topology.Order.Basic /-! # Bounded monotone sequences converge In this file we prove a few theorems of the form “if the range of a monotone function `f : ι → α` admits a least upper bound `a`, then `f x` tends to `a` as `x → ∞`”, as well as version of this statement for (conditionally) complete lattices that use `⨆ x, f x` instead of `IsLUB`. These theorems work for linear orders with order topologies as well as their products (both in terms of `Prod` and in terms of function types). In order to reduce code duplication, we introduce two typeclasses (one for the property formulated above and one for the dual property), prove theorems assuming one of these typeclasses, and provide instances for linear orders and their products. We also prove some "inverse" results: if `f n` is a monotone sequence and `a` is its limit, then `f n ≤ a` for all `n`. ## Tags monotone convergence -/ open Filter Set Function open scoped Topology variable {α β : Type*} /-- We say that `α` is a `SupConvergenceClass` if the following holds. Let `f : ι → α` be a monotone function, let `a : α` be a least upper bound of `Set.range f`. Then `f x` tends to `𝓝 a` as `x → ∞` (formally, at the filter `Filter.atTop`). We require this for `ι = (s : Set α)`, `f = (↑)` in the definition, then prove it for any `f` in `tendsto_atTop_isLUB`. This property holds for linear orders with order topology as well as their products. -/ class SupConvergenceClass (α : Type*) [Preorder α] [TopologicalSpace α] : Prop where /-- proof that a monotone function tends to `𝓝 a` as `x → ∞` -/ tendsto_coe_atTop_isLUB : ∀ (a : α) (s : Set α), IsLUB s a → Tendsto ((↑) : s → α) atTop (𝓝 a) /-- We say that `α` is an `InfConvergenceClass` if the following holds. Let `f : ι → α` be a monotone function, let `a : α` be a greatest lower bound of `Set.range f`. Then `f x` tends to `𝓝 a` as `x → -∞` (formally, at the filter `Filter.atBot`). We require this for `ι = (s : Set α)`, `f = (↑)` in the definition, then prove it for any `f` in `tendsto_atBot_isGLB`. This property holds for linear orders with order topology as well as their products. -/ class InfConvergenceClass (α : Type*) [Preorder α] [TopologicalSpace α] : Prop where /-- proof that a monotone function tends to `𝓝 a` as `x → -∞` -/ tendsto_coe_atBot_isGLB : ∀ (a : α) (s : Set α), IsGLB s a → Tendsto ((↑) : s → α) atBot (𝓝 a) instance OrderDual.supConvergenceClass [Preorder α] [TopologicalSpace α] [InfConvergenceClass α] : SupConvergenceClass αᵒᵈ := ⟨‹InfConvergenceClass α›.1⟩ instance OrderDual.infConvergenceClass [Preorder α] [TopologicalSpace α] [SupConvergenceClass α] : InfConvergenceClass αᵒᵈ := ⟨‹SupConvergenceClass α›.1⟩ -- see Note [lower instance priority] instance (priority := 100) LinearOrder.supConvergenceClass [TopologicalSpace α] [LinearOrder α] [OrderTopology α] : SupConvergenceClass α := by refine ⟨fun a s ha => tendsto_order.2 ⟨fun b hb => ?_, fun b hb => ?_⟩⟩ · rcases ha.exists_between hb with ⟨c, hcs, bc, bca⟩ lift c to s using hcs exact (eventually_ge_atTop c).mono fun x hx => bc.trans_le hx · exact Eventually.of_forall fun x => (ha.1 x.2).trans_lt hb -- see Note [lower instance priority] instance (priority := 100) LinearOrder.infConvergenceClass [TopologicalSpace α] [LinearOrder α] [OrderTopology α] : InfConvergenceClass α := show InfConvergenceClass αᵒᵈᵒᵈ from OrderDual.infConvergenceClass section variable {ι : Type*} [Preorder ι] [TopologicalSpace α] section IsLUB variable [Preorder α] [SupConvergenceClass α] {f : ι → α} {a : α} theorem tendsto_atTop_isLUB (h_mono : Monotone f) (ha : IsLUB (Set.range f) a) : Tendsto f atTop (𝓝 a) := by suffices Tendsto (rangeFactorization f) atTop atTop from (SupConvergenceClass.tendsto_coe_atTop_isLUB _ _ ha).comp this exact h_mono.rangeFactorization.tendsto_atTop_atTop fun b => b.2.imp fun a ha => ha.ge theorem tendsto_atBot_isLUB (h_anti : Antitone f) (ha : IsLUB (Set.range f) a) : Tendsto f atBot (𝓝 a) := by convert tendsto_atTop_isLUB h_anti.dual_left ha using 1 end IsLUB section IsGLB variable [Preorder α] [InfConvergenceClass α] {f : ι → α} {a : α} theorem tendsto_atBot_isGLB (h_mono : Monotone f) (ha : IsGLB (Set.range f) a) : Tendsto f atBot (𝓝 a) := by convert tendsto_atTop_isLUB h_mono.dual ha.dual using 1 theorem tendsto_atTop_isGLB (h_anti : Antitone f) (ha : IsGLB (Set.range f) a) : Tendsto f atTop (𝓝 a) := by convert tendsto_atBot_isLUB h_anti.dual ha.dual using 1 end IsGLB section CiSup variable [ConditionallyCompleteLattice α] [SupConvergenceClass α] {f : ι → α} theorem tendsto_atTop_ciSup (h_mono : Monotone f) (hbdd : BddAbove <| range f) : Tendsto f atTop (𝓝 (⨆ i, f i)) := by cases isEmpty_or_nonempty ι exacts [tendsto_of_isEmpty, tendsto_atTop_isLUB h_mono (isLUB_ciSup hbdd)] theorem tendsto_atBot_ciSup (h_anti : Antitone f) (hbdd : BddAbove <| range f) : Tendsto f atBot (𝓝 (⨆ i, f i)) := by convert tendsto_atTop_ciSup h_anti.dual hbdd.dual using 1 end CiSup section CiInf variable [ConditionallyCompleteLattice α] [InfConvergenceClass α] {f : ι → α} theorem tendsto_atBot_ciInf (h_mono : Monotone f) (hbdd : BddBelow <| range f) : Tendsto f atBot (𝓝 (⨅ i, f i)) := by convert tendsto_atTop_ciSup h_mono.dual hbdd.dual using 1 theorem tendsto_atTop_ciInf (h_anti : Antitone f) (hbdd : BddBelow <| range f) : Tendsto f atTop (𝓝 (⨅ i, f i)) := by convert tendsto_atBot_ciSup h_anti.dual hbdd.dual using 1 end CiInf section iSup variable [CompleteLattice α] [SupConvergenceClass α] {f : ι → α} theorem tendsto_atTop_iSup (h_mono : Monotone f) : Tendsto f atTop (𝓝 (⨆ i, f i)) := tendsto_atTop_ciSup h_mono (OrderTop.bddAbove _) theorem tendsto_atBot_iSup (h_anti : Antitone f) : Tendsto f atBot (𝓝 (⨆ i, f i)) := tendsto_atBot_ciSup h_anti (OrderTop.bddAbove _) end iSup section iInf variable [CompleteLattice α] [InfConvergenceClass α] {f : ι → α} theorem tendsto_atBot_iInf (h_mono : Monotone f) : Tendsto f atBot (𝓝 (⨅ i, f i)) := tendsto_atBot_ciInf h_mono (OrderBot.bddBelow _) theorem tendsto_atTop_iInf (h_anti : Antitone f) : Tendsto f atTop (𝓝 (⨅ i, f i)) := tendsto_atTop_ciInf h_anti (OrderBot.bddBelow _) end iInf end instance Prod.supConvergenceClass [Preorder α] [Preorder β] [TopologicalSpace α] [TopologicalSpace β] [SupConvergenceClass α] [SupConvergenceClass β] : SupConvergenceClass (α × β) := by constructor rintro ⟨a, b⟩ s h rw [isLUB_prod, ← range_restrict, ← range_restrict] at h have A : Tendsto (fun x : s => (x : α × β).1) atTop (𝓝 a) := tendsto_atTop_isLUB (monotone_fst.restrict s) h.1 have B : Tendsto (fun x : s => (x : α × β).2) atTop (𝓝 b) := tendsto_atTop_isLUB (monotone_snd.restrict s) h.2 exact A.prodMk_nhds B instance [Preorder α] [Preorder β] [TopologicalSpace α] [TopologicalSpace β] [InfConvergenceClass α] [InfConvergenceClass β] : InfConvergenceClass (α × β) := show InfConvergenceClass (αᵒᵈ × βᵒᵈ)ᵒᵈ from OrderDual.infConvergenceClass instance Pi.supConvergenceClass {ι : Type*} {α : ι → Type*} [∀ i, Preorder (α i)] [∀ i, TopologicalSpace (α i)] [∀ i, SupConvergenceClass (α i)] : SupConvergenceClass (∀ i, α i) := by refine ⟨fun f s h => ?_⟩ simp only [isLUB_pi, ← range_restrict] at h exact tendsto_pi_nhds.2 fun i => tendsto_atTop_isLUB ((monotone_eval _).restrict _) (h i) instance Pi.infConvergenceClass {ι : Type*} {α : ι → Type*} [∀ i, Preorder (α i)] [∀ i, TopologicalSpace (α i)] [∀ i, InfConvergenceClass (α i)] : InfConvergenceClass (∀ i, α i) := show InfConvergenceClass (∀ i, (α i)ᵒᵈ)ᵒᵈ from OrderDual.infConvergenceClass instance Pi.supConvergenceClass' {ι : Type*} [Preorder α] [TopologicalSpace α] [SupConvergenceClass α] : SupConvergenceClass (ι → α) := supConvergenceClass instance Pi.infConvergenceClass' {ι : Type*} [Preorder α] [TopologicalSpace α] [InfConvergenceClass α] : InfConvergenceClass (ι → α) := Pi.infConvergenceClass theorem tendsto_of_monotone {ι α : Type*} [Preorder ι] [TopologicalSpace α] [ConditionallyCompleteLinearOrder α] [OrderTopology α] {f : ι → α} (h_mono : Monotone f) : Tendsto f atTop atTop ∨ ∃ l, Tendsto f atTop (𝓝 l) := by classical exact if H : BddAbove (range f) then Or.inr ⟨_, tendsto_atTop_ciSup h_mono H⟩ else Or.inl <| tendsto_atTop_atTop_of_monotone' h_mono H theorem tendsto_of_antitone {ι α : Type*} [Preorder ι] [TopologicalSpace α] [ConditionallyCompleteLinearOrder α] [OrderTopology α] {f : ι → α} (h_mono : Antitone f) : Tendsto f atTop atBot ∨ ∃ l, Tendsto f atTop (𝓝 l) := @tendsto_of_monotone ι αᵒᵈ _ _ _ _ _ h_mono theorem tendsto_iff_tendsto_subseq_of_monotone {ι₁ ι₂ α : Type*} [SemilatticeSup ι₁] [Preorder ι₂] [Nonempty ι₁] [TopologicalSpace α] [ConditionallyCompleteLinearOrder α] [OrderTopology α] [NoMaxOrder α] {f : ι₂ → α} {φ : ι₁ → ι₂} {l : α} (hf : Monotone f) (hg : Tendsto φ atTop atTop) : Tendsto f atTop (𝓝 l) ↔ Tendsto (f ∘ φ) atTop (𝓝 l) := by constructor <;> intro h · exact h.comp hg · rcases tendsto_of_monotone hf with (h' | ⟨l', hl'⟩) · exact (not_tendsto_atTop_of_tendsto_nhds h (h'.comp hg)).elim · rwa [tendsto_nhds_unique h (hl'.comp hg)] theorem tendsto_iff_tendsto_subseq_of_antitone {ι₁ ι₂ α : Type*} [SemilatticeSup ι₁] [Preorder ι₂] [Nonempty ι₁] [TopologicalSpace α] [ConditionallyCompleteLinearOrder α] [OrderTopology α] [NoMinOrder α] {f : ι₂ → α} {φ : ι₁ → ι₂} {l : α} (hf : Antitone f) (hg : Tendsto φ atTop atTop) : Tendsto f atTop (𝓝 l) ↔ Tendsto (f ∘ φ) atTop (𝓝 l) := tendsto_iff_tendsto_subseq_of_monotone (α := αᵒᵈ) hf hg /-! The next family of results, such as `isLUB_of_tendsto_atTop` and `iSup_eq_of_tendsto`, are converses to the standard fact that bounded monotone functions converge. They state, that if a monotone function `f` tends to `a` along `Filter.atTop`, then that value `a` is a least upper bound for the range of `f`. Related theorems above (`IsLUB.isLUB_of_tendsto`, `IsGLB.isGLB_of_tendsto` etc) cover the case when `f x` tends to `a` as `x` tends to some point `b` in the domain. -/ theorem Monotone.ge_of_tendsto [TopologicalSpace α] [Preorder α] [OrderClosedTopology α] [SemilatticeSup β] {f : β → α} {a : α} (hf : Monotone f) (ha : Tendsto f atTop (𝓝 a)) (b : β) : f b ≤ a := haveI : Nonempty β := Nonempty.intro b _root_.ge_of_tendsto ha ((eventually_ge_atTop b).mono fun _ hxy => hf hxy)
theorem Monotone.le_of_tendsto [TopologicalSpace α] [Preorder α] [OrderClosedTopology α] [SemilatticeInf β] {f : β → α} {a : α} (hf : Monotone f) (ha : Tendsto f atBot (𝓝 a)) (b : β) : a ≤ f b := hf.dual.ge_of_tendsto ha b theorem Antitone.le_of_tendsto [TopologicalSpace α] [Preorder α] [OrderClosedTopology α] [SemilatticeSup β] {f : β → α} {a : α} (hf : Antitone f) (ha : Tendsto f atTop (𝓝 a)) (b : β) : a ≤ f b :=
Mathlib/Topology/Order/MonotoneConvergence.lean
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/- Copyright (c) 2021 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.Module.Basic import Mathlib.MeasureTheory.Function.SimpleFuncDense /-! # Strongly measurable and finitely strongly measurable functions A function `f` is said to be strongly measurable if `f` is the sequential limit of simple functions. It is said to be finitely strongly measurable with respect to a measure `μ` if the supports of those simple functions have finite measure. If the target space has a second countable topology, strongly measurable and measurable are equivalent. If the measure is sigma-finite, strongly measurable and finitely strongly measurable are equivalent. The main property of finitely strongly measurable functions is `FinStronglyMeasurable.exists_set_sigmaFinite`: there exists a measurable set `t` such that the function is supported on `t` and `μ.restrict t` is sigma-finite. As a consequence, we can prove some results for those functions as if the measure was sigma-finite. We provide a solid API for strongly measurable functions, as a basis for the Bochner integral. ## Main definitions * `StronglyMeasurable f`: `f : α → β` is the limit of a sequence `fs : ℕ → SimpleFunc α β`. * `FinStronglyMeasurable f μ`: `f : α → β` is the limit of a sequence `fs : ℕ → SimpleFunc α β` such that for all `n ∈ ℕ`, the measure of the support of `fs n` is finite. ## References * [Hytönen, Tuomas, Jan Van Neerven, Mark Veraar, and Lutz Weis. Analysis in Banach spaces. Springer, 2016.][Hytonen_VanNeerven_Veraar_Wies_2016] -/ -- Guard against import creep assert_not_exists InnerProductSpace open MeasureTheory Filter TopologicalSpace Function Set MeasureTheory.Measure open ENNReal Topology MeasureTheory NNReal variable {α β γ ι : Type*} [Countable ι] namespace MeasureTheory local infixr:25 " →ₛ " => SimpleFunc section Definitions variable [TopologicalSpace β] /-- A function is `StronglyMeasurable` if it is the limit of simple functions. -/ def StronglyMeasurable [MeasurableSpace α] (f : α → β) : Prop := ∃ fs : ℕ → α →ₛ β, ∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x)) /-- The notation for StronglyMeasurable giving the measurable space instance explicitly. -/ scoped notation "StronglyMeasurable[" m "]" => @MeasureTheory.StronglyMeasurable _ _ _ m /-- A function is `FinStronglyMeasurable` with respect to a measure if it is the limit of simple functions with support with finite measure. -/ def FinStronglyMeasurable [Zero β] {_ : MeasurableSpace α} (f : α → β) (μ : Measure α := by volume_tac) : Prop := ∃ fs : ℕ → α →ₛ β, (∀ n, μ (support (fs n)) < ∞) ∧ ∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x)) end Definitions open MeasureTheory /-! ## Strongly measurable functions -/ section StronglyMeasurable variable {_ : MeasurableSpace α} {μ : Measure α} {f : α → β} {g : ℕ → α} {m : ℕ} variable [TopologicalSpace β] theorem SimpleFunc.stronglyMeasurable (f : α →ₛ β) : StronglyMeasurable f := ⟨fun _ => f, fun _ => tendsto_const_nhds⟩ @[simp, nontriviality] lemma StronglyMeasurable.of_subsingleton_dom [Subsingleton α] : StronglyMeasurable f := ⟨fun _ => SimpleFunc.ofFinite f, fun _ => tendsto_const_nhds⟩ @[simp, nontriviality] lemma StronglyMeasurable.of_subsingleton_cod [Subsingleton β] : StronglyMeasurable f := by let f_sf : α →ₛ β := ⟨f, fun x => ?_, Set.Subsingleton.finite Set.subsingleton_of_subsingleton⟩ · exact ⟨fun _ => f_sf, fun x => tendsto_const_nhds⟩ · simp [Set.preimage, eq_iff_true_of_subsingleton] @[deprecated StronglyMeasurable.of_subsingleton_cod (since := "2025-04-09")] lemma Subsingleton.stronglyMeasurable [Subsingleton β] (f : α → β) : StronglyMeasurable f := .of_subsingleton_cod @[deprecated StronglyMeasurable.of_subsingleton_dom (since := "2025-04-09")] lemma Subsingleton.stronglyMeasurable' [Subsingleton α] (f : α → β) : StronglyMeasurable f := .of_subsingleton_dom theorem stronglyMeasurable_const {b : β} : StronglyMeasurable fun _ : α => b := ⟨fun _ => SimpleFunc.const α b, fun _ => tendsto_const_nhds⟩ @[to_additive] theorem stronglyMeasurable_one [One β] : StronglyMeasurable (1 : α → β) := stronglyMeasurable_const /-- A version of `stronglyMeasurable_const` that assumes `f x = f y` for all `x, y`. This version works for functions between empty types. -/ theorem stronglyMeasurable_const' (hf : ∀ x y, f x = f y) : StronglyMeasurable f := by nontriviality α inhabit α convert stronglyMeasurable_const (β := β) using 1 exact funext fun x => hf x default variable [MeasurableSingletonClass α] section aux omit [TopologicalSpace β] /-- Auxiliary definition for `StronglyMeasurable.of_discrete`. -/ private noncomputable def simpleFuncAux (f : α → β) (g : ℕ → α) : ℕ → SimpleFunc α β | 0 => .const _ (f (g 0)) | n + 1 => .piecewise {g n} (.singleton _) (.const _ <| f (g n)) (simpleFuncAux f g n) private lemma simpleFuncAux_eq_of_lt : ∀ n > m, simpleFuncAux f g n (g m) = f (g m) | _, .refl => by simp [simpleFuncAux] | _, Nat.le.step (m := n) hmn => by obtain hnm | hnm := eq_or_ne (g n) (g m) <;> simp [simpleFuncAux, Set.piecewise_eq_of_not_mem , hnm.symm, simpleFuncAux_eq_of_lt _ hmn] private lemma simpleFuncAux_eventuallyEq : ∀ᶠ n in atTop, simpleFuncAux f g n (g m) = f (g m) := eventually_atTop.2 ⟨_, simpleFuncAux_eq_of_lt⟩ end aux lemma StronglyMeasurable.of_discrete [Countable α] : StronglyMeasurable f := by nontriviality α nontriviality β obtain ⟨g, hg⟩ := exists_surjective_nat α exact ⟨simpleFuncAux f g, hg.forall.2 fun m ↦ tendsto_nhds_of_eventually_eq simpleFuncAux_eventuallyEq⟩ @[deprecated StronglyMeasurable.of_discrete (since := "2025-04-09")] theorem StronglyMeasurable.of_finite [Finite α] : StronglyMeasurable f := .of_discrete end StronglyMeasurable namespace StronglyMeasurable variable {f g : α → β} section BasicPropertiesInAnyTopologicalSpace variable [TopologicalSpace β] /-- A sequence of simple functions such that `∀ x, Tendsto (fun n => hf.approx n x) atTop (𝓝 (f x))`. That property is given by `stronglyMeasurable.tendsto_approx`. -/ protected noncomputable def approx {_ : MeasurableSpace α} (hf : StronglyMeasurable f) : ℕ → α →ₛ β := hf.choose protected theorem tendsto_approx {_ : MeasurableSpace α} (hf : StronglyMeasurable f) : ∀ x, Tendsto (fun n => hf.approx n x) atTop (𝓝 (f x)) := hf.choose_spec /-- Similar to `stronglyMeasurable.approx`, but enforces that the norm of every function in the sequence is less than `c` everywhere. If `‖f x‖ ≤ c` this sequence of simple functions verifies `Tendsto (fun n => hf.approxBounded n x) atTop (𝓝 (f x))`. -/ noncomputable def approxBounded {_ : MeasurableSpace α} [Norm β] [SMul ℝ β] (hf : StronglyMeasurable f) (c : ℝ) : ℕ → SimpleFunc α β := fun n => (hf.approx n).map fun x => min 1 (c / ‖x‖) • x theorem tendsto_approxBounded_of_norm_le {β} {f : α → β} [NormedAddCommGroup β] [NormedSpace ℝ β] {m : MeasurableSpace α} (hf : StronglyMeasurable[m] f) {c : ℝ} {x : α} (hfx : ‖f x‖ ≤ c) : Tendsto (fun n => hf.approxBounded c n x) atTop (𝓝 (f x)) := by have h_tendsto := hf.tendsto_approx x simp only [StronglyMeasurable.approxBounded, SimpleFunc.coe_map, Function.comp_apply] by_cases hfx0 : ‖f x‖ = 0 · rw [norm_eq_zero] at hfx0 rw [hfx0] at h_tendsto ⊢ have h_tendsto_norm : Tendsto (fun n => ‖hf.approx n x‖) atTop (𝓝 0) := by convert h_tendsto.norm rw [norm_zero] refine squeeze_zero_norm (fun n => ?_) h_tendsto_norm calc ‖min 1 (c / ‖hf.approx n x‖) • hf.approx n x‖ = ‖min 1 (c / ‖hf.approx n x‖)‖ * ‖hf.approx n x‖ := norm_smul _ _ _ ≤ ‖(1 : ℝ)‖ * ‖hf.approx n x‖ := by refine mul_le_mul_of_nonneg_right ?_ (norm_nonneg _) rw [norm_one, Real.norm_of_nonneg] · exact min_le_left _ _ · exact le_min zero_le_one (div_nonneg ((norm_nonneg _).trans hfx) (norm_nonneg _)) _ = ‖hf.approx n x‖ := by rw [norm_one, one_mul] rw [← one_smul ℝ (f x)] refine Tendsto.smul ?_ h_tendsto have : min 1 (c / ‖f x‖) = 1 := by rw [min_eq_left_iff, one_le_div (lt_of_le_of_ne (norm_nonneg _) (Ne.symm hfx0))] exact hfx nth_rw 2 [this.symm] refine Tendsto.min tendsto_const_nhds ?_ exact Tendsto.div tendsto_const_nhds h_tendsto.norm hfx0 theorem tendsto_approxBounded_ae {β} {f : α → β} [NormedAddCommGroup β] [NormedSpace ℝ β] {m m0 : MeasurableSpace α} {μ : Measure α} (hf : StronglyMeasurable[m] f) {c : ℝ} (hf_bound : ∀ᵐ x ∂μ, ‖f x‖ ≤ c) : ∀ᵐ x ∂μ, Tendsto (fun n => hf.approxBounded c n x) atTop (𝓝 (f x)) := by filter_upwards [hf_bound] with x hfx using tendsto_approxBounded_of_norm_le hf hfx theorem norm_approxBounded_le {β} {f : α → β} [SeminormedAddCommGroup β] [NormedSpace ℝ β] {m : MeasurableSpace α} {c : ℝ} (hf : StronglyMeasurable[m] f) (hc : 0 ≤ c) (n : ℕ) (x : α) : ‖hf.approxBounded c n x‖ ≤ c := by simp only [StronglyMeasurable.approxBounded, SimpleFunc.coe_map, Function.comp_apply] refine (norm_smul_le _ _).trans ?_ by_cases h0 : ‖hf.approx n x‖ = 0 · simp only [h0, _root_.div_zero, min_eq_right, zero_le_one, norm_zero, mul_zero] exact hc rcases le_total ‖hf.approx n x‖ c with h | h · rw [min_eq_left _] · simpa only [norm_one, one_mul] using h · rwa [one_le_div (lt_of_le_of_ne (norm_nonneg _) (Ne.symm h0))] · rw [min_eq_right _] · rw [norm_div, norm_norm, mul_comm, mul_div, div_eq_mul_inv, mul_comm, ← mul_assoc, inv_mul_cancel₀ h0, one_mul, Real.norm_of_nonneg hc] · rwa [div_le_one (lt_of_le_of_ne (norm_nonneg _) (Ne.symm h0))] theorem _root_.stronglyMeasurable_bot_iff [Nonempty β] [T2Space β] : StronglyMeasurable[⊥] f ↔ ∃ c, f = fun _ => c := by rcases isEmpty_or_nonempty α with hα | hα · simp [eq_iff_true_of_subsingleton] refine ⟨fun hf => ?_, fun hf_eq => ?_⟩ · refine ⟨f hα.some, ?_⟩ let fs := hf.approx have h_fs_tendsto : ∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x)) := hf.tendsto_approx have : ∀ n, ∃ c, ∀ x, fs n x = c := fun n => SimpleFunc.simpleFunc_bot (fs n) let cs n := (this n).choose have h_cs_eq : ∀ n, ⇑(fs n) = fun _ => cs n := fun n => funext (this n).choose_spec conv at h_fs_tendsto => enter [x, 1, n]; rw [h_cs_eq] have h_tendsto : Tendsto cs atTop (𝓝 (f hα.some)) := h_fs_tendsto hα.some ext1 x exact tendsto_nhds_unique (h_fs_tendsto x) h_tendsto · obtain ⟨c, rfl⟩ := hf_eq exact stronglyMeasurable_const end BasicPropertiesInAnyTopologicalSpace theorem finStronglyMeasurable_of_set_sigmaFinite [TopologicalSpace β] [Zero β] {m : MeasurableSpace α} {μ : Measure α} (hf_meas : StronglyMeasurable f) {t : Set α} (ht : MeasurableSet t) (hft_zero : ∀ x ∈ tᶜ, f x = 0) (htμ : SigmaFinite (μ.restrict t)) : FinStronglyMeasurable f μ := by haveI : SigmaFinite (μ.restrict t) := htμ let S := spanningSets (μ.restrict t) have hS_meas : ∀ n, MeasurableSet (S n) := measurableSet_spanningSets (μ.restrict t) let f_approx := hf_meas.approx let fs n := SimpleFunc.restrict (f_approx n) (S n ∩ t) have h_fs_t_compl : ∀ n, ∀ x, x ∉ t → fs n x = 0 := by intro n x hxt rw [SimpleFunc.restrict_apply _ ((hS_meas n).inter ht)] refine Set.indicator_of_not_mem ?_ _ simp [hxt] refine ⟨fs, ?_, fun x => ?_⟩ · simp_rw [SimpleFunc.support_eq, ← Finset.mem_coe] classical refine fun n => measure_biUnion_lt_top {y ∈ (fs n).range | y ≠ 0}.finite_toSet fun y hy => ?_ rw [SimpleFunc.restrict_preimage_singleton _ ((hS_meas n).inter ht)] swap · letI : (y : β) → Decidable (y = 0) := fun y => Classical.propDecidable _ rw [Finset.mem_coe, Finset.mem_filter] at hy exact hy.2 refine (measure_mono Set.inter_subset_left).trans_lt ?_ have h_lt_top := measure_spanningSets_lt_top (μ.restrict t) n rwa [Measure.restrict_apply' ht] at h_lt_top · by_cases hxt : x ∈ t swap · rw [funext fun n => h_fs_t_compl n x hxt, hft_zero x hxt] exact tendsto_const_nhds have h : Tendsto (fun n => (f_approx n) x) atTop (𝓝 (f x)) := hf_meas.tendsto_approx x obtain ⟨n₁, hn₁⟩ : ∃ n, ∀ m, n ≤ m → fs m x = f_approx m x := by obtain ⟨n, hn⟩ : ∃ n, ∀ m, n ≤ m → x ∈ S m ∩ t := by rsuffices ⟨n, hn⟩ : ∃ n, ∀ m, n ≤ m → x ∈ S m · exact ⟨n, fun m hnm => Set.mem_inter (hn m hnm) hxt⟩ rsuffices ⟨n, hn⟩ : ∃ n, x ∈ S n · exact ⟨n, fun m hnm => monotone_spanningSets (μ.restrict t) hnm hn⟩ rw [← Set.mem_iUnion, iUnion_spanningSets (μ.restrict t)] trivial refine ⟨n, fun m hnm => ?_⟩ simp_rw [fs, SimpleFunc.restrict_apply _ ((hS_meas m).inter ht), Set.indicator_of_mem (hn m hnm)] rw [tendsto_atTop'] at h ⊢ intro s hs obtain ⟨n₂, hn₂⟩ := h s hs refine ⟨max n₁ n₂, fun m hm => ?_⟩ rw [hn₁ m ((le_max_left _ _).trans hm.le)] exact hn₂ m ((le_max_right _ _).trans hm.le) /-- If the measure is sigma-finite, all strongly measurable functions are `FinStronglyMeasurable`. -/ @[aesop 5% apply (rule_sets := [Measurable])] protected theorem finStronglyMeasurable [TopologicalSpace β] [Zero β] {m0 : MeasurableSpace α} (hf : StronglyMeasurable f) (μ : Measure α) [SigmaFinite μ] : FinStronglyMeasurable f μ := hf.finStronglyMeasurable_of_set_sigmaFinite MeasurableSet.univ (by simp) (by rwa [Measure.restrict_univ]) /-- A strongly measurable function is measurable. -/ @[aesop 5% apply (rule_sets := [Measurable])] protected theorem measurable {_ : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β] (hf : StronglyMeasurable f) : Measurable f := measurable_of_tendsto_metrizable (fun n => (hf.approx n).measurable) (tendsto_pi_nhds.mpr hf.tendsto_approx) /-- A strongly measurable function is almost everywhere measurable. -/ @[aesop 5% apply (rule_sets := [Measurable])] protected theorem aemeasurable {_ : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β] {μ : Measure α} (hf : StronglyMeasurable f) : AEMeasurable f μ := hf.measurable.aemeasurable theorem _root_.Continuous.comp_stronglyMeasurable {_ : MeasurableSpace α} [TopologicalSpace β] [TopologicalSpace γ] {g : β → γ} {f : α → β} (hg : Continuous g) (hf : StronglyMeasurable f) : StronglyMeasurable fun x => g (f x) := ⟨fun n => SimpleFunc.map g (hf.approx n), fun x => (hg.tendsto _).comp (hf.tendsto_approx x)⟩ @[to_additive] nonrec theorem measurableSet_mulSupport {m : MeasurableSpace α} [One β] [TopologicalSpace β] [MetrizableSpace β] (hf : StronglyMeasurable f) : MeasurableSet (mulSupport f) := by borelize β exact measurableSet_mulSupport hf.measurable protected theorem mono {m m' : MeasurableSpace α} [TopologicalSpace β] (hf : StronglyMeasurable[m'] f) (h_mono : m' ≤ m) : StronglyMeasurable[m] f := by let f_approx : ℕ → @SimpleFunc α m β := fun n => @SimpleFunc.mk α m β (hf.approx n) (fun x => h_mono _ (SimpleFunc.measurableSet_fiber' _ x)) (SimpleFunc.finite_range (hf.approx n)) exact ⟨f_approx, hf.tendsto_approx⟩ protected theorem prodMk {m : MeasurableSpace α} [TopologicalSpace β] [TopologicalSpace γ] {f : α → β} {g : α → γ} (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable fun x => (f x, g x) := by refine ⟨fun n => SimpleFunc.pair (hf.approx n) (hg.approx n), fun x => ?_⟩ rw [nhds_prod_eq] exact Tendsto.prodMk (hf.tendsto_approx x) (hg.tendsto_approx x) @[deprecated (since := "2025-03-05")] protected alias prod_mk := StronglyMeasurable.prodMk theorem comp_measurable [TopologicalSpace β] {_ : MeasurableSpace α} {_ : MeasurableSpace γ} {f : α → β} {g : γ → α} (hf : StronglyMeasurable f) (hg : Measurable g) : StronglyMeasurable (f ∘ g) := ⟨fun n => SimpleFunc.comp (hf.approx n) g hg, fun x => hf.tendsto_approx (g x)⟩ theorem of_uncurry_left [TopologicalSpace β] {_ : MeasurableSpace α} {_ : MeasurableSpace γ} {f : α → γ → β} (hf : StronglyMeasurable (uncurry f)) {x : α} : StronglyMeasurable (f x) := hf.comp_measurable measurable_prodMk_left theorem of_uncurry_right [TopologicalSpace β] {_ : MeasurableSpace α} {_ : MeasurableSpace γ} {f : α → γ → β} (hf : StronglyMeasurable (uncurry f)) {y : γ} : StronglyMeasurable fun x => f x y := hf.comp_measurable measurable_prodMk_right protected theorem prod_swap {_ : MeasurableSpace α} {_ : MeasurableSpace β} [TopologicalSpace γ] {f : β × α → γ} (hf : StronglyMeasurable f) : StronglyMeasurable (fun z : α × β => f z.swap) := hf.comp_measurable measurable_swap protected theorem fst {_ : MeasurableSpace α} [mβ : MeasurableSpace β] [TopologicalSpace γ] {f : α → γ} (hf : StronglyMeasurable f) : StronglyMeasurable (fun z : α × β => f z.1) := hf.comp_measurable measurable_fst protected theorem snd [mα : MeasurableSpace α] {_ : MeasurableSpace β} [TopologicalSpace γ] {f : β → γ} (hf : StronglyMeasurable f) : StronglyMeasurable (fun z : α × β => f z.2) := hf.comp_measurable measurable_snd section Arithmetic variable {mα : MeasurableSpace α} [TopologicalSpace β] @[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable]))] protected theorem mul [Mul β] [ContinuousMul β] (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable (f * g) := ⟨fun n => hf.approx n * hg.approx n, fun x => (hf.tendsto_approx x).mul (hg.tendsto_approx x)⟩ @[to_additive (attr := measurability)] theorem mul_const [Mul β] [ContinuousMul β] (hf : StronglyMeasurable f) (c : β) : StronglyMeasurable fun x => f x * c := hf.mul stronglyMeasurable_const @[to_additive (attr := measurability)] theorem const_mul [Mul β] [ContinuousMul β] (hf : StronglyMeasurable f) (c : β) : StronglyMeasurable fun x => c * f x := stronglyMeasurable_const.mul hf @[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable])) const_nsmul] protected theorem pow [Monoid β] [ContinuousMul β] (hf : StronglyMeasurable f) (n : ℕ) : StronglyMeasurable (f ^ n) := ⟨fun k => hf.approx k ^ n, fun x => (hf.tendsto_approx x).pow n⟩ @[to_additive (attr := measurability)] protected theorem inv [Inv β] [ContinuousInv β] (hf : StronglyMeasurable f) : StronglyMeasurable f⁻¹ := ⟨fun n => (hf.approx n)⁻¹, fun x => (hf.tendsto_approx x).inv⟩ @[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable]))] protected theorem div [Div β] [ContinuousDiv β] (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable (f / g) := ⟨fun n => hf.approx n / hg.approx n, fun x => (hf.tendsto_approx x).div' (hg.tendsto_approx x)⟩ @[to_additive] theorem mul_iff_right [CommGroup β] [IsTopologicalGroup β] (hf : StronglyMeasurable f) : StronglyMeasurable (f * g) ↔ StronglyMeasurable g := ⟨fun h ↦ show g = f * g * f⁻¹ by simp only [mul_inv_cancel_comm] ▸ h.mul hf.inv, fun h ↦ hf.mul h⟩ @[to_additive] theorem mul_iff_left [CommGroup β] [IsTopologicalGroup β] (hf : StronglyMeasurable f) : StronglyMeasurable (g * f) ↔ StronglyMeasurable g := mul_comm g f ▸ mul_iff_right hf @[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable]))] protected theorem smul {𝕜} [TopologicalSpace 𝕜] [SMul 𝕜 β] [ContinuousSMul 𝕜 β] {f : α → 𝕜} {g : α → β} (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable fun x => f x • g x := continuous_smul.comp_stronglyMeasurable (hf.prodMk hg) @[to_additive (attr := measurability)] protected theorem const_smul {𝕜} [SMul 𝕜 β] [ContinuousConstSMul 𝕜 β] (hf : StronglyMeasurable f) (c : 𝕜) : StronglyMeasurable (c • f) := ⟨fun n => c • hf.approx n, fun x => (hf.tendsto_approx x).const_smul c⟩ @[to_additive (attr := measurability)] protected theorem const_smul' {𝕜} [SMul 𝕜 β] [ContinuousConstSMul 𝕜 β] (hf : StronglyMeasurable f) (c : 𝕜) : StronglyMeasurable fun x => c • f x := hf.const_smul c @[to_additive (attr := measurability)] protected theorem smul_const {𝕜} [TopologicalSpace 𝕜] [SMul 𝕜 β] [ContinuousSMul 𝕜 β] {f : α → 𝕜} (hf : StronglyMeasurable f) (c : β) : StronglyMeasurable fun x => f x • c := continuous_smul.comp_stronglyMeasurable (hf.prodMk stronglyMeasurable_const) /-- In a normed vector space, the addition of a measurable function and a strongly measurable function is measurable. Note that this is not true without further second-countability assumptions for the addition of two measurable functions. -/ theorem _root_.Measurable.add_stronglyMeasurable {α E : Type*} {_ : MeasurableSpace α} [AddCancelMonoid E] [TopologicalSpace E] [MeasurableSpace E] [BorelSpace E] [ContinuousAdd E] [PseudoMetrizableSpace E] {g f : α → E} (hg : Measurable g) (hf : StronglyMeasurable f) : Measurable (g + f) := by rcases hf with ⟨φ, hφ⟩ have : Tendsto (fun n x ↦ g x + φ n x) atTop (𝓝 (g + f)) := tendsto_pi_nhds.2 (fun x ↦ tendsto_const_nhds.add (hφ x)) apply measurable_of_tendsto_metrizable (fun n ↦ ?_) this exact hg.add_simpleFunc _ /-- In a normed vector space, the subtraction of a measurable function and a strongly measurable function is measurable. Note that this is not true without further second-countability assumptions for the subtraction of two measurable functions. -/ theorem _root_.Measurable.sub_stronglyMeasurable {α E : Type*} {_ : MeasurableSpace α} [AddGroup E] [TopologicalSpace E] [MeasurableSpace E] [BorelSpace E] [ContinuousAdd E] [ContinuousNeg E] [PseudoMetrizableSpace E] {g f : α → E} (hg : Measurable g) (hf : StronglyMeasurable f) : Measurable (g - f) := by rw [sub_eq_add_neg] exact hg.add_stronglyMeasurable hf.neg /-- In a normed vector space, the addition of a strongly measurable function and a measurable function is measurable. Note that this is not true without further second-countability assumptions for the addition of two measurable functions. -/ theorem _root_.Measurable.stronglyMeasurable_add {α E : Type*} {_ : MeasurableSpace α} [AddCancelMonoid E] [TopologicalSpace E] [MeasurableSpace E] [BorelSpace E] [ContinuousAdd E] [PseudoMetrizableSpace E] {g f : α → E} (hg : Measurable g) (hf : StronglyMeasurable f) : Measurable (f + g) := by rcases hf with ⟨φ, hφ⟩ have : Tendsto (fun n x ↦ φ n x + g x) atTop (𝓝 (f + g)) := tendsto_pi_nhds.2 (fun x ↦ (hφ x).add tendsto_const_nhds) apply measurable_of_tendsto_metrizable (fun n ↦ ?_) this exact hg.simpleFunc_add _ end Arithmetic section MulAction variable {M G G₀ : Type*} variable [TopologicalSpace β] variable [Monoid M] [MulAction M β] [ContinuousConstSMul M β] variable [Group G] [MulAction G β] [ContinuousConstSMul G β] variable [GroupWithZero G₀] [MulAction G₀ β] [ContinuousConstSMul G₀ β] theorem _root_.stronglyMeasurable_const_smul_iff {m : MeasurableSpace α} (c : G) : (StronglyMeasurable fun x => c • f x) ↔ StronglyMeasurable f := ⟨fun h => by simpa only [inv_smul_smul] using h.const_smul' c⁻¹, fun h => h.const_smul c⟩ nonrec theorem _root_.IsUnit.stronglyMeasurable_const_smul_iff {_ : MeasurableSpace α} {c : M} (hc : IsUnit c) : (StronglyMeasurable fun x => c • f x) ↔ StronglyMeasurable f := let ⟨u, hu⟩ := hc hu ▸ stronglyMeasurable_const_smul_iff u theorem _root_.stronglyMeasurable_const_smul_iff₀ {_ : MeasurableSpace α} {c : G₀} (hc : c ≠ 0) : (StronglyMeasurable fun x => c • f x) ↔ StronglyMeasurable f := (IsUnit.mk0 _ hc).stronglyMeasurable_const_smul_iff end MulAction section Order variable [MeasurableSpace α] [TopologicalSpace β] open Filter @[aesop safe 20 (rule_sets := [Measurable])] protected theorem sup [Max β] [ContinuousSup β] (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable (f ⊔ g) := ⟨fun n => hf.approx n ⊔ hg.approx n, fun x => (hf.tendsto_approx x).sup_nhds (hg.tendsto_approx x)⟩ @[aesop safe 20 (rule_sets := [Measurable])] protected theorem inf [Min β] [ContinuousInf β] (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable (f ⊓ g) := ⟨fun n => hf.approx n ⊓ hg.approx n, fun x => (hf.tendsto_approx x).inf_nhds (hg.tendsto_approx x)⟩ end Order /-! ### Big operators: `∏` and `∑` -/ section Monoid variable {M : Type*} [Monoid M] [TopologicalSpace M] [ContinuousMul M] {m : MeasurableSpace α} @[to_additive (attr := measurability)] theorem _root_.List.stronglyMeasurable_prod' (l : List (α → M)) (hl : ∀ f ∈ l, StronglyMeasurable f) : StronglyMeasurable l.prod := by induction' l with f l ihl; · exact stronglyMeasurable_one rw [List.forall_mem_cons] at hl rw [List.prod_cons] exact hl.1.mul (ihl hl.2) @[to_additive (attr := measurability)] theorem _root_.List.stronglyMeasurable_prod (l : List (α → M)) (hl : ∀ f ∈ l, StronglyMeasurable f) : StronglyMeasurable fun x => (l.map fun f : α → M => f x).prod := by simpa only [← Pi.list_prod_apply] using l.stronglyMeasurable_prod' hl end Monoid section CommMonoid variable {M : Type*} [CommMonoid M] [TopologicalSpace M] [ContinuousMul M] {m : MeasurableSpace α} @[to_additive (attr := measurability)] theorem _root_.Multiset.stronglyMeasurable_prod' (l : Multiset (α → M)) (hl : ∀ f ∈ l, StronglyMeasurable f) : StronglyMeasurable l.prod := by rcases l with ⟨l⟩ simpa using l.stronglyMeasurable_prod' (by simpa using hl) @[to_additive (attr := measurability)] theorem _root_.Multiset.stronglyMeasurable_prod (s : Multiset (α → M)) (hs : ∀ f ∈ s, StronglyMeasurable f) : StronglyMeasurable fun x => (s.map fun f : α → M => f x).prod := by simpa only [← Pi.multiset_prod_apply] using s.stronglyMeasurable_prod' hs @[to_additive (attr := measurability)] theorem _root_.Finset.stronglyMeasurable_prod' {ι : Type*} {f : ι → α → M} (s : Finset ι) (hf : ∀ i ∈ s, StronglyMeasurable (f i)) : StronglyMeasurable (∏ i ∈ s, f i) := Finset.prod_induction _ _ (fun _a _b ha hb => ha.mul hb) (@stronglyMeasurable_one α M _ _ _) hf @[to_additive (attr := measurability)] theorem _root_.Finset.stronglyMeasurable_prod {ι : Type*} {f : ι → α → M} (s : Finset ι) (hf : ∀ i ∈ s, StronglyMeasurable (f i)) : StronglyMeasurable fun a => ∏ i ∈ s, f i a := by simpa only [← Finset.prod_apply] using s.stronglyMeasurable_prod' hf end CommMonoid /-- The range of a strongly measurable function is separable. -/ protected theorem isSeparable_range {m : MeasurableSpace α} [TopologicalSpace β] (hf : StronglyMeasurable f) : TopologicalSpace.IsSeparable (range f) := by have : IsSeparable (closure (⋃ n, range (hf.approx n))) := .closure <| .iUnion fun n => (hf.approx n).finite_range.isSeparable apply this.mono rintro _ ⟨x, rfl⟩ apply mem_closure_of_tendsto (hf.tendsto_approx x) filter_upwards with n apply mem_iUnion_of_mem n exact mem_range_self _ theorem separableSpace_range_union_singleton {_ : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β] (hf : StronglyMeasurable f) {b : β} : SeparableSpace (range f ∪ {b} : Set β) := letI := pseudoMetrizableSpacePseudoMetric β (hf.isSeparable_range.union (finite_singleton _).isSeparable).separableSpace section SecondCountableStronglyMeasurable variable {mα : MeasurableSpace α} [MeasurableSpace β] /-- In a space with second countable topology, measurable implies strongly measurable. -/ @[aesop 90% apply (rule_sets := [Measurable])] theorem _root_.Measurable.stronglyMeasurable [TopologicalSpace β] [PseudoMetrizableSpace β] [SecondCountableTopology β] [OpensMeasurableSpace β] (hf : Measurable f) : StronglyMeasurable f := by letI := pseudoMetrizableSpacePseudoMetric β nontriviality β; inhabit β exact ⟨SimpleFunc.approxOn f hf Set.univ default (Set.mem_univ _), fun x ↦ SimpleFunc.tendsto_approxOn hf (Set.mem_univ _) (by rw [closure_univ]; simp)⟩ /-- In a space with second countable topology, strongly measurable and measurable are equivalent. -/ theorem _root_.stronglyMeasurable_iff_measurable [TopologicalSpace β] [MetrizableSpace β] [BorelSpace β] [SecondCountableTopology β] : StronglyMeasurable f ↔ Measurable f := ⟨fun h => h.measurable, fun h => Measurable.stronglyMeasurable h⟩ @[measurability] theorem _root_.stronglyMeasurable_id [TopologicalSpace α] [PseudoMetrizableSpace α] [OpensMeasurableSpace α] [SecondCountableTopology α] : StronglyMeasurable (id : α → α) := measurable_id.stronglyMeasurable end SecondCountableStronglyMeasurable /-- A function is strongly measurable if and only if it is measurable and has separable range. -/ theorem _root_.stronglyMeasurable_iff_measurable_separable {m : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β] : StronglyMeasurable f ↔ Measurable f ∧ IsSeparable (range f) := by refine ⟨fun H ↦ ⟨H.measurable, H.isSeparable_range⟩, fun ⟨Hm, Hsep⟩ ↦ ?_⟩ have := Hsep.secondCountableTopology have Hm' : StronglyMeasurable (rangeFactorization f) := Hm.subtype_mk.stronglyMeasurable exact continuous_subtype_val.comp_stronglyMeasurable Hm' /-- A continuous function is strongly measurable when either the source space or the target space is second-countable. -/ theorem _root_.Continuous.stronglyMeasurable [MeasurableSpace α] [TopologicalSpace α] [OpensMeasurableSpace α] [TopologicalSpace β] [PseudoMetrizableSpace β] [h : SecondCountableTopologyEither α β] {f : α → β} (hf : Continuous f) : StronglyMeasurable f := by borelize β cases h.out · rw [stronglyMeasurable_iff_measurable_separable] refine ⟨hf.measurable, ?_⟩ exact isSeparable_range hf · exact hf.measurable.stronglyMeasurable /-- A continuous function whose support is contained in a compact set is strongly measurable. -/ @[to_additive] theorem _root_.Continuous.stronglyMeasurable_of_mulSupport_subset_isCompact [MeasurableSpace α] [TopologicalSpace α] [OpensMeasurableSpace α] [MeasurableSpace β] [TopologicalSpace β] [PseudoMetrizableSpace β] [BorelSpace β] [One β] {f : α → β} (hf : Continuous f) {k : Set α} (hk : IsCompact k) (h'f : mulSupport f ⊆ k) : StronglyMeasurable f := by letI : PseudoMetricSpace β := pseudoMetrizableSpacePseudoMetric β rw [stronglyMeasurable_iff_measurable_separable] exact ⟨hf.measurable, (isCompact_range_of_mulSupport_subset_isCompact hf hk h'f).isSeparable⟩ /-- A continuous function with compact support is strongly measurable. -/ @[to_additive] theorem _root_.Continuous.stronglyMeasurable_of_hasCompactMulSupport [MeasurableSpace α] [TopologicalSpace α] [OpensMeasurableSpace α] [MeasurableSpace β] [TopologicalSpace β] [PseudoMetrizableSpace β] [BorelSpace β] [One β] {f : α → β} (hf : Continuous f) (h'f : HasCompactMulSupport f) : StronglyMeasurable f := hf.stronglyMeasurable_of_mulSupport_subset_isCompact h'f (subset_mulTSupport f) /-- A continuous function with compact support on a product space is strongly measurable for the product sigma-algebra. The subtlety is that we do not assume that the spaces are separable, so the product of the Borel sigma algebras might not contain all open sets, but still it contains enough of them to approximate compactly supported continuous functions. -/ lemma _root_.HasCompactSupport.stronglyMeasurable_of_prod {X Y : Type*} [Zero α] [TopologicalSpace X] [TopologicalSpace Y] [MeasurableSpace X] [MeasurableSpace Y] [OpensMeasurableSpace X] [OpensMeasurableSpace Y] [TopologicalSpace α] [PseudoMetrizableSpace α] {f : X × Y → α} (hf : Continuous f) (h'f : HasCompactSupport f) : StronglyMeasurable f := by borelize α apply stronglyMeasurable_iff_measurable_separable.2 ⟨h'f.measurable_of_prod hf, ?_⟩ letI : PseudoMetricSpace α := pseudoMetrizableSpacePseudoMetric α exact IsCompact.isSeparable (s := range f) (h'f.isCompact_range hf) /-- If `g` is a topological embedding, then `f` is strongly measurable iff `g ∘ f` is. -/ theorem _root_.Embedding.comp_stronglyMeasurable_iff {m : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β] [TopologicalSpace γ] [PseudoMetrizableSpace γ] {g : β → γ} {f : α → β} (hg : IsEmbedding g) : (StronglyMeasurable fun x => g (f x)) ↔ StronglyMeasurable f := by letI := pseudoMetrizableSpacePseudoMetric γ borelize β γ refine ⟨fun H => stronglyMeasurable_iff_measurable_separable.2 ⟨?_, ?_⟩, fun H => hg.continuous.comp_stronglyMeasurable H⟩ · let G : β → range g := rangeFactorization g have hG : IsClosedEmbedding G := { hg.codRestrict _ _ with isClosed_range := by rw [surjective_onto_range.range_eq] exact isClosed_univ } have : Measurable (G ∘ f) := Measurable.subtype_mk H.measurable exact hG.measurableEmbedding.measurable_comp_iff.1 this · have : IsSeparable (g ⁻¹' range (g ∘ f)) := hg.isSeparable_preimage H.isSeparable_range rwa [range_comp, hg.injective.preimage_image] at this /-- A sequential limit of strongly measurable functions is strongly measurable. -/ theorem _root_.stronglyMeasurable_of_tendsto {ι : Type*} {m : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β] (u : Filter ι) [NeBot u] [IsCountablyGenerated u] {f : ι → α → β} {g : α → β} (hf : ∀ i, StronglyMeasurable (f i)) (lim : Tendsto f u (𝓝 g)) : StronglyMeasurable g := by borelize β refine stronglyMeasurable_iff_measurable_separable.2 ⟨?_, ?_⟩ · exact measurable_of_tendsto_metrizable' u (fun i => (hf i).measurable) lim · rcases u.exists_seq_tendsto with ⟨v, hv⟩ have : IsSeparable (closure (⋃ i, range (f (v i)))) := .closure <| .iUnion fun i => (hf (v i)).isSeparable_range apply this.mono rintro _ ⟨x, rfl⟩ rw [tendsto_pi_nhds] at lim apply mem_closure_of_tendsto ((lim x).comp hv) filter_upwards with n apply mem_iUnion_of_mem n exact mem_range_self _ protected theorem piecewise {m : MeasurableSpace α} [TopologicalSpace β] {s : Set α} {_ : DecidablePred (· ∈ s)} (hs : MeasurableSet s) (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable (Set.piecewise s f g) := by refine ⟨fun n => SimpleFunc.piecewise s hs (hf.approx n) (hg.approx n), fun x => ?_⟩ by_cases hx : x ∈ s · simpa [@Set.piecewise_eq_of_mem _ _ _ _ _ (fun _ => Classical.propDecidable _) _ hx, hx] using hf.tendsto_approx x · simpa [@Set.piecewise_eq_of_not_mem _ _ _ _ _ (fun _ => Classical.propDecidable _) _ hx, hx] using hg.tendsto_approx x /-- this is slightly different from `StronglyMeasurable.piecewise`. It can be used to show `StronglyMeasurable (ite (x=0) 0 1)` by `exact StronglyMeasurable.ite (measurableSet_singleton 0) stronglyMeasurable_const stronglyMeasurable_const`, but replacing `StronglyMeasurable.ite` by `StronglyMeasurable.piecewise` in that example proof does not work. -/ protected theorem ite {_ : MeasurableSpace α} [TopologicalSpace β] {p : α → Prop} {_ : DecidablePred p} (hp : MeasurableSet { a : α | p a }) (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable fun x => ite (p x) (f x) (g x) := StronglyMeasurable.piecewise hp hf hg @[measurability] theorem _root_.MeasurableEmbedding.stronglyMeasurable_extend {f : α → β} {g : α → γ} {g' : γ → β} {mα : MeasurableSpace α} {mγ : MeasurableSpace γ} [TopologicalSpace β] (hg : MeasurableEmbedding g) (hf : StronglyMeasurable f) (hg' : StronglyMeasurable g') : StronglyMeasurable (Function.extend g f g') := by refine ⟨fun n => SimpleFunc.extend (hf.approx n) g hg (hg'.approx n), ?_⟩ intro x by_cases hx : ∃ y, g y = x · rcases hx with ⟨y, rfl⟩ simpa only [SimpleFunc.extend_apply, hg.injective, Injective.extend_apply] using hf.tendsto_approx y · simpa only [hx, SimpleFunc.extend_apply', not_false_iff, extend_apply'] using hg'.tendsto_approx x theorem _root_.MeasurableEmbedding.exists_stronglyMeasurable_extend {f : α → β} {g : α → γ} {_ : MeasurableSpace α} {_ : MeasurableSpace γ} [TopologicalSpace β] (hg : MeasurableEmbedding g) (hf : StronglyMeasurable f) (hne : γ → Nonempty β) : ∃ f' : γ → β, StronglyMeasurable f' ∧ f' ∘ g = f := ⟨Function.extend g f fun x => Classical.choice (hne x), hg.stronglyMeasurable_extend hf (stronglyMeasurable_const' fun _ _ => rfl), funext fun _ => hg.injective.extend_apply _ _ _⟩ theorem _root_.stronglyMeasurable_of_stronglyMeasurable_union_cover {m : MeasurableSpace α} [TopologicalSpace β] {f : α → β} (s t : Set α) (hs : MeasurableSet s) (ht : MeasurableSet t) (h : univ ⊆ s ∪ t) (hc : StronglyMeasurable fun a : s => f a) (hd : StronglyMeasurable fun a : t => f a) : StronglyMeasurable f := by nontriviality β; inhabit β suffices Function.extend Subtype.val (fun x : s ↦ f x) (Function.extend (↑) (fun x : t ↦ f x) fun _ ↦ default) = f from this ▸ (MeasurableEmbedding.subtype_coe hs).stronglyMeasurable_extend hc <| (MeasurableEmbedding.subtype_coe ht).stronglyMeasurable_extend hd stronglyMeasurable_const ext x by_cases hxs : x ∈ s · lift x to s using hxs simp [Subtype.coe_injective.extend_apply] · lift x to t using (h trivial).resolve_left hxs rw [extend_apply', Subtype.coe_injective.extend_apply] exact fun ⟨y, hy⟩ ↦ hxs <| hy ▸ y.2 theorem _root_.stronglyMeasurable_of_restrict_of_restrict_compl {_ : MeasurableSpace α} [TopologicalSpace β] {f : α → β} {s : Set α} (hs : MeasurableSet s) (h₁ : StronglyMeasurable (s.restrict f)) (h₂ : StronglyMeasurable (sᶜ.restrict f)) : StronglyMeasurable f := stronglyMeasurable_of_stronglyMeasurable_union_cover s sᶜ hs hs.compl (union_compl_self s).ge h₁ h₂ @[measurability] protected theorem indicator {_ : MeasurableSpace α} [TopologicalSpace β] [Zero β] (hf : StronglyMeasurable f) {s : Set α} (hs : MeasurableSet s) : StronglyMeasurable (s.indicator f) := hf.piecewise hs stronglyMeasurable_const /-- To prove that a property holds for any strongly measurable function, it is enough to show that it holds for constant indicator functions of measurable sets and that it is closed under addition and pointwise limit. To use in an induction proof, the syntax is `induction f, hf using StronglyMeasurable.induction with`. -/ theorem induction [MeasurableSpace α] [AddZeroClass β] [TopologicalSpace β] {P : (f : α → β) → StronglyMeasurable f → Prop} (ind : ∀ c ⦃s : Set α⦄ (hs : MeasurableSet s), P (s.indicator fun _ ↦ c) (stronglyMeasurable_const.indicator hs)) (add : ∀ ⦃f g : α → β⦄ (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) (hfg : StronglyMeasurable (f + g)), Disjoint f.support g.support → P f hf → P g hg → P (f + g) hfg) (lim : ∀ ⦃f : ℕ → α → β⦄ ⦃g : α → β⦄ (hf : ∀ n, StronglyMeasurable (f n)) (hg : StronglyMeasurable g), (∀ n, P (f n) (hf n)) → (∀ x, Tendsto (f · x) atTop (𝓝 (g x))) → P g hg) (f : α → β) (hf : StronglyMeasurable f) : P f hf := by let s := hf.approx refine lim (fun n ↦ (s n).stronglyMeasurable) hf (fun n ↦ ?_) hf.tendsto_approx change P (s n) (s n).stronglyMeasurable induction s n using SimpleFunc.induction with | const c hs => exact ind c hs | @add f g h_supp hf hg => exact add f.stronglyMeasurable g.stronglyMeasurable (f + g).stronglyMeasurable h_supp hf hg open scoped Classical in /-- To prove that a property holds for any strongly measurable function, it is enough to show that it holds for constant functions and that it is closed under piecewise combination of functions and pointwise limits. To use in an induction proof, the syntax is `induction f, hf using StronglyMeasurable.induction' with`. -/ theorem induction' [MeasurableSpace α] [Nonempty β] [TopologicalSpace β] {P : (f : α → β) → StronglyMeasurable f → Prop} (const : ∀ (c), P (fun _ ↦ c) stronglyMeasurable_const) (pcw : ∀ ⦃f g : α → β⦄ {s} (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) (hs : MeasurableSet s), P f hf → P g hg → P (s.piecewise f g) (hf.piecewise hs hg)) (lim : ∀ ⦃f : ℕ → α → β⦄ ⦃g : α → β⦄ (hf : ∀ n, StronglyMeasurable (f n)) (hg : StronglyMeasurable g), (∀ n, P (f n) (hf n)) → (∀ x, Tendsto (f · x) atTop (𝓝 (g x))) → P g hg) (f : α → β) (hf : StronglyMeasurable f) : P f hf := by let s := hf.approx refine lim (fun n ↦ (s n).stronglyMeasurable) hf (fun n ↦ ?_) hf.tendsto_approx change P (s n) (s n).stronglyMeasurable induction s n with | const c => exact const c | @pcw f g s hs Pf Pg => simp_rw [SimpleFunc.coe_piecewise] exact pcw f.stronglyMeasurable g.stronglyMeasurable hs Pf Pg @[aesop safe 20 apply (rule_sets := [Measurable])] protected theorem dist {_ : MeasurableSpace α} {β : Type*} [PseudoMetricSpace β] {f g : α → β} (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) : StronglyMeasurable fun x => dist (f x) (g x) := continuous_dist.comp_stronglyMeasurable (hf.prodMk hg) @[measurability] protected theorem norm {_ : MeasurableSpace α} {β : Type*} [SeminormedAddCommGroup β] {f : α → β} (hf : StronglyMeasurable f) : StronglyMeasurable fun x => ‖f x‖ := continuous_norm.comp_stronglyMeasurable hf @[measurability] protected theorem nnnorm {_ : MeasurableSpace α} {β : Type*} [SeminormedAddCommGroup β] {f : α → β} (hf : StronglyMeasurable f) : StronglyMeasurable fun x => ‖f x‖₊ := continuous_nnnorm.comp_stronglyMeasurable hf /-- The `enorm` of a strongly measurable function is measurable. Unlike `StrongMeasurable.norm` and `StronglyMeasurable.nnnorm`, this lemma proves measurability, **not** strong measurability. This is an intentional decision: for functions taking values in ℝ≥0∞, measurability is much more useful than strong measurability. -/ @[fun_prop, measurability] protected theorem enorm {_ : MeasurableSpace α} {β : Type*} [SeminormedAddCommGroup β] {f : α → β} (hf : StronglyMeasurable f) : Measurable (‖f ·‖ₑ) := (ENNReal.continuous_coe.comp_stronglyMeasurable hf.nnnorm).measurable @[deprecated (since := "2025-01-21")] alias ennnorm := StronglyMeasurable.enorm @[measurability] protected theorem real_toNNReal {_ : MeasurableSpace α} {f : α → ℝ} (hf : StronglyMeasurable f) : StronglyMeasurable fun x => (f x).toNNReal := continuous_real_toNNReal.comp_stronglyMeasurable hf section PseudoMetrizableSpace variable {E : Type*} {m m₀ : MeasurableSpace α} {μ : Measure[m₀] α} {f g : α → E} [TopologicalSpace E] [Preorder E] [OrderClosedTopology E] [PseudoMetrizableSpace E] lemma measurableSet_le (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) : MeasurableSet[m] {a | f a ≤ g a} := by borelize (E × E) exact (hf.prodMk hg).measurable isClosed_le_prod.measurableSet lemma measurableSet_lt (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) : MeasurableSet[m] {a | f a < g a} := by simpa only [lt_iff_le_not_le] using (hf.measurableSet_le hg).inter (hg.measurableSet_le hf).compl lemma ae_le_trim_of_stronglyMeasurable (hm : m ≤ m₀) (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) (hfg : f ≤ᵐ[μ] g) : f ≤ᵐ[μ.trim hm] g := by rwa [EventuallyLE, ae_iff, trim_measurableSet_eq hm] exact (hf.measurableSet_le hg).compl lemma ae_le_trim_iff (hm : m ≤ m₀) (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) : f ≤ᵐ[μ.trim hm] g ↔ f ≤ᵐ[μ] g := ⟨ae_le_of_ae_le_trim, ae_le_trim_of_stronglyMeasurable hm hf hg⟩ end PseudoMetrizableSpace section MetrizableSpace variable {E : Type*} {m m₀ : MeasurableSpace α} {μ : Measure[m₀] α} {f g : α → E} [TopologicalSpace E] [MetrizableSpace E] lemma measurableSet_eq_fun (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) : MeasurableSet[m] {a | f a = g a} := by borelize (E × E) exact (hf.prodMk hg).measurable isClosed_diagonal.measurableSet lemma ae_eq_trim_of_stronglyMeasurable (hm : m ≤ m₀) (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) (hfg : f =ᵐ[μ] g) : f =ᵐ[μ.trim hm] g := by rwa [EventuallyEq, ae_iff, trim_measurableSet_eq hm] exact (hf.measurableSet_eq_fun hg).compl lemma ae_eq_trim_iff (hm : m ≤ m₀) (hf : StronglyMeasurable[m] f) (hg : StronglyMeasurable[m] g) : f =ᵐ[μ.trim hm] g ↔ f =ᵐ[μ] g := ⟨ae_eq_of_ae_eq_trim, ae_eq_trim_of_stronglyMeasurable hm hf hg⟩ end MetrizableSpace theorem stronglyMeasurable_in_set {m : MeasurableSpace α} [TopologicalSpace β] [Zero β] {s : Set α} {f : α → β} (hs : MeasurableSet s) (hf : StronglyMeasurable f) (hf_zero : ∀ x, x ∉ s → f x = 0) : ∃ fs : ℕ → α →ₛ β, (∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x))) ∧ ∀ x ∉ s, ∀ n, fs n x = 0 := by let g_seq_s : ℕ → @SimpleFunc α m β := fun n => (hf.approx n).restrict s have hg_eq : ∀ x ∈ s, ∀ n, g_seq_s n x = hf.approx n x := by intro x hx n rw [SimpleFunc.coe_restrict _ hs, Set.indicator_of_mem hx] have hg_zero : ∀ x ∉ s, ∀ n, g_seq_s n x = 0 := by intro x hx n rw [SimpleFunc.coe_restrict _ hs, Set.indicator_of_not_mem hx] refine ⟨g_seq_s, fun x => ?_, hg_zero⟩ by_cases hx : x ∈ s · simp_rw [hg_eq x hx] exact hf.tendsto_approx x · simp_rw [hg_zero x hx, hf_zero x hx] exact tendsto_const_nhds /-- If the restriction to a set `s` of a σ-algebra `m` is included in the restriction to `s` of another σ-algebra `m₂` (hypothesis `hs`), the set `s` is `m` measurable and a function `f` supported on `s` is `m`-strongly-measurable, then `f` is also `m₂`-strongly-measurable. -/ theorem stronglyMeasurable_of_measurableSpace_le_on {α E} {m m₂ : MeasurableSpace α} [TopologicalSpace E] [Zero E] {s : Set α} {f : α → E} (hs_m : MeasurableSet[m] s) (hs : ∀ t, MeasurableSet[m] (s ∩ t) → MeasurableSet[m₂] (s ∩ t)) (hf : StronglyMeasurable[m] f) (hf_zero : ∀ x ∉ s, f x = 0) : StronglyMeasurable[m₂] f := by have hs_m₂ : MeasurableSet[m₂] s := by rw [← Set.inter_univ s] refine hs Set.univ ?_ rwa [Set.inter_univ] obtain ⟨g_seq_s, hg_seq_tendsto, hg_seq_zero⟩ := stronglyMeasurable_in_set hs_m hf hf_zero let g_seq_s₂ : ℕ → @SimpleFunc α m₂ E := fun n => { toFun := g_seq_s n measurableSet_fiber' := fun x => by rw [← Set.inter_univ (g_seq_s n ⁻¹' {x}), ← Set.union_compl_self s, Set.inter_union_distrib_left, Set.inter_comm (g_seq_s n ⁻¹' {x})] refine MeasurableSet.union (hs _ (hs_m.inter ?_)) ?_ · exact @SimpleFunc.measurableSet_fiber _ _ m _ _ by_cases hx : x = 0 · suffices g_seq_s n ⁻¹' {x} ∩ sᶜ = sᶜ by rw [this] exact hs_m₂.compl ext1 y rw [hx, Set.mem_inter_iff, Set.mem_preimage, Set.mem_singleton_iff] exact ⟨fun h => h.2, fun h => ⟨hg_seq_zero y h n, h⟩⟩ · suffices g_seq_s n ⁻¹' {x} ∩ sᶜ = ∅ by rw [this] exact MeasurableSet.empty ext1 y simp only [mem_inter_iff, mem_preimage, mem_singleton_iff, mem_compl_iff, mem_empty_iff_false, iff_false, not_and, not_not_mem] refine Function.mtr fun hys => ?_ rw [hg_seq_zero y hys n] exact Ne.symm hx finite_range' := @SimpleFunc.finite_range _ _ m (g_seq_s n) } exact ⟨g_seq_s₂, hg_seq_tendsto⟩ /-- If a function `f` is strongly measurable w.r.t. a sub-σ-algebra `m` and the measure is σ-finite on `m`, then there exists spanning measurable sets with finite measure on which `f` has bounded norm. In particular, `f` is integrable on each of those sets. -/ theorem exists_spanning_measurableSet_norm_le [SeminormedAddCommGroup β] {m m0 : MeasurableSpace α} (hm : m ≤ m0) (hf : StronglyMeasurable[m] f) (μ : Measure α) [SigmaFinite (μ.trim hm)] : ∃ s : ℕ → Set α, (∀ n, MeasurableSet[m] (s n) ∧ μ (s n) < ∞ ∧ ∀ x ∈ s n, ‖f x‖ ≤ n) ∧ ⋃ i, s i = Set.univ := by obtain ⟨s, hs, hs_univ⟩ := @exists_spanning_measurableSet_le _ m _ hf.nnnorm.measurable (μ.trim hm) _ refine ⟨s, fun n ↦ ⟨(hs n).1, (le_trim hm).trans_lt (hs n).2.1, fun x hx ↦ ?_⟩, hs_univ⟩ have hx_nnnorm : ‖f x‖₊ ≤ n := (hs n).2.2 x hx rw [← coe_nnnorm] norm_cast end StronglyMeasurable /-! ## Finitely strongly measurable functions -/ theorem finStronglyMeasurable_zero {α β} {m : MeasurableSpace α} {μ : Measure α} [Zero β] [TopologicalSpace β] : FinStronglyMeasurable (0 : α → β) μ := ⟨0, by simp only [Pi.zero_apply, SimpleFunc.coe_zero, support_zero', measure_empty, zero_lt_top, forall_const], fun _ => tendsto_const_nhds⟩ namespace FinStronglyMeasurable variable {m0 : MeasurableSpace α} {μ : Measure α} {f g : α → β} section sequence variable [Zero β] [TopologicalSpace β] (hf : FinStronglyMeasurable f μ) /-- A sequence of simple functions such that `∀ x, Tendsto (fun n ↦ hf.approx n x) atTop (𝓝 (f x))` and `∀ n, μ (support (hf.approx n)) < ∞`. These properties are given by `FinStronglyMeasurable.tendsto_approx` and `FinStronglyMeasurable.fin_support_approx`. -/ protected noncomputable def approx : ℕ → α →ₛ β := hf.choose protected theorem fin_support_approx : ∀ n, μ (support (hf.approx n)) < ∞ := hf.choose_spec.1 protected theorem tendsto_approx : ∀ x, Tendsto (fun n => hf.approx n x) atTop (𝓝 (f x)) := hf.choose_spec.2 end sequence /-- A finitely strongly measurable function is strongly measurable. -/ @[aesop 5% apply (rule_sets := [Measurable])] protected theorem stronglyMeasurable [Zero β] [TopologicalSpace β] (hf : FinStronglyMeasurable f μ) : StronglyMeasurable f := ⟨hf.approx, hf.tendsto_approx⟩ theorem exists_set_sigmaFinite [Zero β] [TopologicalSpace β] [T2Space β] (hf : FinStronglyMeasurable f μ) : ∃ t, MeasurableSet t ∧ (∀ x ∈ tᶜ, f x = 0) ∧ SigmaFinite (μ.restrict t) := by rcases hf with ⟨fs, hT_lt_top, h_approx⟩ let T n := support (fs n) have hT_meas : ∀ n, MeasurableSet (T n) := fun n => SimpleFunc.measurableSet_support (fs n) let t := ⋃ n, T n refine ⟨t, MeasurableSet.iUnion hT_meas, ?_, ?_⟩ · have h_fs_zero : ∀ n, ∀ x ∈ tᶜ, fs n x = 0 := by intro n x hxt rw [Set.mem_compl_iff, Set.mem_iUnion, not_exists] at hxt simpa [T] using hxt n refine fun x hxt => tendsto_nhds_unique (h_approx x) ?_ rw [funext fun n => h_fs_zero n x hxt] exact tendsto_const_nhds · refine ⟨⟨⟨fun n => tᶜ ∪ T n, fun _ => trivial, fun n => ?_, ?_⟩⟩⟩ · rw [Measure.restrict_apply' (MeasurableSet.iUnion hT_meas), Set.union_inter_distrib_right, Set.compl_inter_self t, Set.empty_union] exact (measure_mono Set.inter_subset_left).trans_lt (hT_lt_top n) · rw [← Set.union_iUnion tᶜ T] exact Set.compl_union_self _ /-- A finitely strongly measurable function is measurable. -/ protected theorem measurable [Zero β] [TopologicalSpace β] [PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β] (hf : FinStronglyMeasurable f μ) : Measurable f := hf.stronglyMeasurable.measurable section Arithmetic variable [TopologicalSpace β] @[aesop safe 20 (rule_sets := [Measurable])] protected theorem mul [MulZeroClass β] [ContinuousMul β] (hf : FinStronglyMeasurable f μ) (hg : FinStronglyMeasurable g μ) : FinStronglyMeasurable (f * g) μ := by refine ⟨fun n => hf.approx n * hg.approx n, ?_, fun x => (hf.tendsto_approx x).mul (hg.tendsto_approx x)⟩ intro n exact (measure_mono (support_mul_subset_left _ _)).trans_lt (hf.fin_support_approx n) @[aesop safe 20 (rule_sets := [Measurable])] protected theorem add [AddZeroClass β] [ContinuousAdd β] (hf : FinStronglyMeasurable f μ) (hg : FinStronglyMeasurable g μ) : FinStronglyMeasurable (f + g) μ := ⟨fun n => hf.approx n + hg.approx n, fun n => (measure_mono (Function.support_add _ _)).trans_lt ((measure_union_le _ _).trans_lt (ENNReal.add_lt_top.mpr ⟨hf.fin_support_approx n, hg.fin_support_approx n⟩)), fun x => (hf.tendsto_approx x).add (hg.tendsto_approx x)⟩ @[measurability] protected theorem neg [SubtractionMonoid β] [ContinuousNeg β] (hf : FinStronglyMeasurable f μ) : FinStronglyMeasurable (-f) μ := by refine ⟨fun n => -hf.approx n, fun n => ?_, fun x => (hf.tendsto_approx x).neg⟩ suffices μ (Function.support fun x => -(hf.approx n) x) < ∞ by convert this rw [Function.support_neg (hf.approx n)] exact hf.fin_support_approx n @[measurability] protected theorem sub [SubtractionMonoid β] [ContinuousSub β] (hf : FinStronglyMeasurable f μ) (hg : FinStronglyMeasurable g μ) : FinStronglyMeasurable (f - g) μ := ⟨fun n => hf.approx n - hg.approx n, fun n => (measure_mono (Function.support_sub _ _)).trans_lt ((measure_union_le _ _).trans_lt (ENNReal.add_lt_top.mpr ⟨hf.fin_support_approx n, hg.fin_support_approx n⟩)), fun x => (hf.tendsto_approx x).sub (hg.tendsto_approx x)⟩ @[measurability] protected theorem const_smul {𝕜} [TopologicalSpace 𝕜] [Zero β] [SMulZeroClass 𝕜 β] [ContinuousSMul 𝕜 β] (hf : FinStronglyMeasurable f μ) (c : 𝕜) : FinStronglyMeasurable (c • f) μ := by refine ⟨fun n => c • hf.approx n, fun n => ?_, fun x => (hf.tendsto_approx x).const_smul c⟩ rw [SimpleFunc.coe_smul] exact (measure_mono (support_const_smul_subset c _)).trans_lt (hf.fin_support_approx n) end Arithmetic section Order variable [TopologicalSpace β] [Zero β] @[aesop safe 20 (rule_sets := [Measurable])] protected theorem sup [SemilatticeSup β] [ContinuousSup β] (hf : FinStronglyMeasurable f μ) (hg : FinStronglyMeasurable g μ) : FinStronglyMeasurable (f ⊔ g) μ := by refine ⟨fun n => hf.approx n ⊔ hg.approx n, fun n => ?_, fun x => (hf.tendsto_approx x).sup_nhds (hg.tendsto_approx x)⟩ refine (measure_mono (support_sup _ _)).trans_lt ?_ exact measure_union_lt_top_iff.mpr ⟨hf.fin_support_approx n, hg.fin_support_approx n⟩ @[aesop safe 20 (rule_sets := [Measurable])] protected theorem inf [SemilatticeInf β] [ContinuousInf β] (hf : FinStronglyMeasurable f μ) (hg : FinStronglyMeasurable g μ) : FinStronglyMeasurable (f ⊓ g) μ := by refine ⟨fun n => hf.approx n ⊓ hg.approx n, fun n => ?_, fun x => (hf.tendsto_approx x).inf_nhds (hg.tendsto_approx x)⟩ refine (measure_mono (support_inf _ _)).trans_lt ?_ exact measure_union_lt_top_iff.mpr ⟨hf.fin_support_approx n, hg.fin_support_approx n⟩ end Order end FinStronglyMeasurable theorem finStronglyMeasurable_iff_stronglyMeasurable_and_exists_set_sigmaFinite {α β} {f : α → β} [TopologicalSpace β] [T2Space β] [Zero β] {_ : MeasurableSpace α} {μ : Measure α} : FinStronglyMeasurable f μ ↔ StronglyMeasurable f ∧ ∃ t, MeasurableSet t ∧ (∀ x ∈ tᶜ, f x = 0) ∧ SigmaFinite (μ.restrict t) := ⟨fun hf => ⟨hf.stronglyMeasurable, hf.exists_set_sigmaFinite⟩, fun hf => hf.1.finStronglyMeasurable_of_set_sigmaFinite hf.2.choose_spec.1 hf.2.choose_spec.2.1 hf.2.choose_spec.2.2⟩ section SecondCountableTopology variable {G : Type*} [SeminormedAddCommGroup G] [MeasurableSpace G] [BorelSpace G] [SecondCountableTopology G] {f : α → G} /-- In a space with second countable topology and a sigma-finite measure, `FinStronglyMeasurable` and `Measurable` are equivalent. -/ theorem finStronglyMeasurable_iff_measurable {_m0 : MeasurableSpace α} (μ : Measure α) [SigmaFinite μ] : FinStronglyMeasurable f μ ↔ Measurable f := ⟨fun h => h.measurable, fun h => (Measurable.stronglyMeasurable h).finStronglyMeasurable μ⟩ /-- In a space with second countable topology and a sigma-finite measure, a measurable function is `FinStronglyMeasurable`. -/ @[aesop 90% apply (rule_sets := [Measurable])] theorem finStronglyMeasurable_of_measurable {_m0 : MeasurableSpace α} (μ : Measure α) [SigmaFinite μ] (hf : Measurable f) : FinStronglyMeasurable f μ := (finStronglyMeasurable_iff_measurable μ).mpr hf end SecondCountableTopology theorem measurable_uncurry_of_continuous_of_measurable {α β ι : Type*} [TopologicalSpace ι] [MetrizableSpace ι] [MeasurableSpace ι] [SecondCountableTopology ι] [OpensMeasurableSpace ι] {mβ : MeasurableSpace β} [TopologicalSpace β] [PseudoMetrizableSpace β] [BorelSpace β] {m : MeasurableSpace α} {u : ι → α → β} (hu_cont : ∀ x, Continuous fun i => u i x) (h : ∀ i, Measurable (u i)) : Measurable (Function.uncurry u) := by obtain ⟨t_sf, ht_sf⟩ : ∃ t : ℕ → SimpleFunc ι ι, ∀ j x, Tendsto (fun n => u (t n j) x) atTop (𝓝 <| u j x) := by have h_str_meas : StronglyMeasurable (id : ι → ι) := stronglyMeasurable_id refine ⟨h_str_meas.approx, fun j x => ?_⟩ exact ((hu_cont x).tendsto j).comp (h_str_meas.tendsto_approx j) let U (n : ℕ) (p : ι × α) := u (t_sf n p.fst) p.snd have h_tendsto : Tendsto U atTop (𝓝 fun p => u p.fst p.snd) := by rw [tendsto_pi_nhds] exact fun p => ht_sf p.fst p.snd refine measurable_of_tendsto_metrizable (fun n => ?_) h_tendsto have h_meas : Measurable fun p : (t_sf n).range × α => u (↑p.fst) p.snd := by have : (fun p : ↥(t_sf n).range × α => u (↑p.fst) p.snd) = (fun p : α × (t_sf n).range => u (↑p.snd) p.fst) ∘ Prod.swap := rfl rw [this, @measurable_swap_iff α (↥(t_sf n).range) β m] exact measurable_from_prod_countable fun j => h j have : (fun p : ι × α => u (t_sf n p.fst) p.snd) = (fun p : ↥(t_sf n).range × α => u p.fst p.snd) ∘ fun p : ι × α => (⟨t_sf n p.fst, SimpleFunc.mem_range_self _ _⟩, p.snd) := rfl simp_rw [U, this] refine h_meas.comp (Measurable.prodMk ?_ measurable_snd) exact ((t_sf n).measurable.comp measurable_fst).subtype_mk theorem stronglyMeasurable_uncurry_of_continuous_of_stronglyMeasurable {α β ι : Type*} [TopologicalSpace ι] [MetrizableSpace ι] [MeasurableSpace ι] [SecondCountableTopology ι] [OpensMeasurableSpace ι] [TopologicalSpace β] [PseudoMetrizableSpace β] [MeasurableSpace α] {u : ι → α → β} (hu_cont : ∀ x, Continuous fun i => u i x) (h : ∀ i, StronglyMeasurable (u i)) : StronglyMeasurable (Function.uncurry u) := by borelize β obtain ⟨t_sf, ht_sf⟩ : ∃ t : ℕ → SimpleFunc ι ι, ∀ j x, Tendsto (fun n => u (t n j) x) atTop (𝓝 <| u j x) := by have h_str_meas : StronglyMeasurable (id : ι → ι) := stronglyMeasurable_id refine ⟨h_str_meas.approx, fun j x => ?_⟩ exact ((hu_cont x).tendsto j).comp (h_str_meas.tendsto_approx j) let U (n : ℕ) (p : ι × α) := u (t_sf n p.fst) p.snd have h_tendsto : Tendsto U atTop (𝓝 fun p => u p.fst p.snd) := by rw [tendsto_pi_nhds] exact fun p => ht_sf p.fst p.snd refine stronglyMeasurable_of_tendsto _ (fun n => ?_) h_tendsto have h_str_meas : StronglyMeasurable fun p : (t_sf n).range × α => u (↑p.fst) p.snd := by refine stronglyMeasurable_iff_measurable_separable.2 ⟨?_, ?_⟩ · have : (fun p : ↥(t_sf n).range × α => u (↑p.fst) p.snd) = (fun p : α × (t_sf n).range => u (↑p.snd) p.fst) ∘ Prod.swap := rfl rw [this, measurable_swap_iff] exact measurable_from_prod_countable fun j => (h j).measurable · have : IsSeparable (⋃ i : (t_sf n).range, range (u i)) := .iUnion fun i => (h i).isSeparable_range apply this.mono rintro _ ⟨⟨i, x⟩, rfl⟩ simp only [mem_iUnion, mem_range] exact ⟨i, x, rfl⟩ have : (fun p : ι × α => u (t_sf n p.fst) p.snd) = (fun p : ↥(t_sf n).range × α => u p.fst p.snd) ∘ fun p : ι × α => (⟨t_sf n p.fst, SimpleFunc.mem_range_self _ _⟩, p.snd) := rfl simp_rw [U, this] refine h_str_meas.comp_measurable (Measurable.prodMk ?_ measurable_snd) exact ((t_sf n).measurable.comp measurable_fst).subtype_mk end MeasureTheory
Mathlib/MeasureTheory/Function/StronglyMeasurable/Basic.lean
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/- Copyright (c) 2022 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers -/ import Mathlib.Algebra.ModEq import Mathlib.Algebra.Order.Archimedean.Basic import Mathlib.Algebra.Ring.Periodic import Mathlib.Data.Int.SuccPred import Mathlib.Order.Circular /-! # 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)`. -/ assert_not_exists TwoSidedIdeal noncomputable section section LinearOrderedAddCommGroup variable {α : Type*} [AddCommGroup α] [LinearOrder α] [IsOrderedAddMonoid α] [hα : Archimedean α] {p : α} (hp : 0 < p) {a b c : α} {n : ℤ} section include hp /-- 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 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 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 /-- 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 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 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 /-- Reduce `b` to the interval `Ico a (a + p)`. -/ def toIcoMod (a b : α) : α := b - toIcoDiv hp a b • p /-- Reduce `b` to the interval `Ioc a (a + p)`. -/ def toIocMod (a b : α) : α := b - toIocDiv hp a b • p theorem toIcoMod_mem_Ico (a b : α) : toIcoMod hp a b ∈ Set.Ico a (a + p) := sub_toIcoDiv_zsmul_mem_Ico hp a b 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 theorem toIocMod_mem_Ioc (a b : α) : toIocMod hp a b ∈ Set.Ioc a (a + p) := sub_toIocDiv_zsmul_mem_Ioc hp a b theorem left_le_toIcoMod (a b : α) : a ≤ toIcoMod hp a b := (Set.mem_Ico.1 (toIcoMod_mem_Ico hp a b)).1 theorem left_lt_toIocMod (a b : α) : a < toIocMod hp a b := (Set.mem_Ioc.1 (toIocMod_mem_Ioc hp a b)).1 theorem toIcoMod_lt_right (a b : α) : toIcoMod hp a b < a + p := (Set.mem_Ico.1 (toIcoMod_mem_Ico hp a b)).2 theorem toIocMod_le_right (a b : α) : toIocMod hp a b ≤ a + p := (Set.mem_Ioc.1 (toIocMod_mem_Ioc hp a b)).2 @[simp] theorem self_sub_toIcoDiv_zsmul (a b : α) : b - toIcoDiv hp a b • p = toIcoMod hp a b := rfl @[simp] theorem self_sub_toIocDiv_zsmul (a b : α) : b - toIocDiv hp a b • p = toIocMod hp a b := rfl @[simp] theorem toIcoDiv_zsmul_sub_self (a b : α) : toIcoDiv hp a b • p - b = -toIcoMod hp a b := by rw [toIcoMod, neg_sub] @[simp] theorem toIocDiv_zsmul_sub_self (a b : α) : toIocDiv hp a b • p - b = -toIocMod hp a b := by rw [toIocMod, neg_sub] @[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] @[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] @[simp] theorem self_sub_toIcoMod (a b : α) : b - toIcoMod hp a b = toIcoDiv hp a b • p := by rw [toIcoMod, sub_sub_cancel] @[simp] theorem self_sub_toIocMod (a b : α) : b - toIocMod hp a b = toIocDiv hp a b • p := by rw [toIocMod, sub_sub_cancel] @[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] @[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] @[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] @[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] 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] 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] @[simp] theorem toIcoDiv_apply_left (a : α) : toIcoDiv hp a a = 0 := toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by simp [hp] @[simp] theorem toIocDiv_apply_left (a : α) : toIocDiv hp a a = -1 := toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by simp [hp] @[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⟩ @[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⟩ theorem toIcoDiv_apply_right (a : α) : toIcoDiv hp a (a + p) = 1 := toIcoDiv_eq_of_sub_zsmul_mem_Ico hp <| by simp [hp] theorem toIocDiv_apply_right (a : α) : toIocDiv hp a (a + p) = 0 := toIocDiv_eq_of_sub_zsmul_mem_Ioc hp <| by simp [hp] 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⟩ 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⟩ @[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 @[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 @[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 @[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 @[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] /-! 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] /-! 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] @[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] @[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] @[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] @[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 @[simp] 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 @[simp] theorem toIocDiv_add_right (a b : α) : toIocDiv hp a (b + p) = toIocDiv hp a b + 1 := by simpa only [one_zsmul] using toIocDiv_add_zsmul hp a b 1 @[simp] theorem toIocDiv_add_right' (a b : α) : toIocDiv hp (a + p) b = toIocDiv hp a b - 1 := by simpa only [one_zsmul] using toIocDiv_add_zsmul' hp a b 1 @[simp] theorem toIcoDiv_add_left (a b : α) : toIcoDiv hp a (p + b) = toIcoDiv hp a b + 1 := by rw [add_comm, toIcoDiv_add_right] @[simp] theorem toIcoDiv_add_left' (a b : α) : toIcoDiv hp (p + a) b = toIcoDiv hp a b - 1 := by rw [add_comm, toIcoDiv_add_right'] @[simp] theorem toIocDiv_add_left (a b : α) : toIocDiv hp a (p + b) = toIocDiv hp a b + 1 := by rw [add_comm, toIocDiv_add_right] @[simp] theorem toIocDiv_add_left' (a b : α) : toIocDiv hp (p + a) b = toIocDiv hp a b - 1 := by rw [add_comm, toIocDiv_add_right'] @[simp] theorem toIcoDiv_sub (a b : α) : toIcoDiv hp a (b - p) = toIcoDiv hp a b - 1 := by simpa only [one_zsmul] using toIcoDiv_sub_zsmul hp a b 1 @[simp] theorem toIcoDiv_sub' (a b : α) : toIcoDiv hp (a - p) b = toIcoDiv hp a b + 1 := by simpa only [one_zsmul] using toIcoDiv_sub_zsmul' hp a b 1 @[simp] theorem toIocDiv_sub (a b : α) : toIocDiv hp a (b - p) = toIocDiv hp a b - 1 := by simpa only [one_zsmul] using toIocDiv_sub_zsmul hp a b 1 @[simp] theorem toIocDiv_sub' (a b : α) : toIocDiv hp (a - p) b = toIocDiv hp a b + 1 := by simpa only [one_zsmul] using toIocDiv_sub_zsmul' hp a b 1 theorem toIcoDiv_sub_eq_toIcoDiv_add (a b c : α) : toIcoDiv hp a (b - c) = toIcoDiv hp (a + c) b := by apply toIcoDiv_eq_of_sub_zsmul_mem_Ico rw [← sub_right_comm, Set.sub_mem_Ico_iff_left, add_right_comm] exact sub_toIcoDiv_zsmul_mem_Ico hp (a + c) b theorem toIocDiv_sub_eq_toIocDiv_add (a b c : α) : toIocDiv hp a (b - c) = toIocDiv hp (a + c) b := by apply toIocDiv_eq_of_sub_zsmul_mem_Ioc rw [← sub_right_comm, Set.sub_mem_Ioc_iff_left, add_right_comm] exact sub_toIocDiv_zsmul_mem_Ioc hp (a + c) b theorem toIcoDiv_sub_eq_toIcoDiv_add' (a b c : α) : toIcoDiv hp (a - c) b = toIcoDiv hp a (b + c) := by rw [← sub_neg_eq_add, toIcoDiv_sub_eq_toIcoDiv_add, sub_eq_add_neg] theorem toIocDiv_sub_eq_toIocDiv_add' (a b c : α) : toIocDiv hp (a - c) b = toIocDiv hp a (b + c) := by rw [← sub_neg_eq_add, toIocDiv_sub_eq_toIocDiv_add, sub_eq_add_neg] theorem toIcoDiv_neg (a b : α) : toIcoDiv hp a (-b) = -(toIocDiv hp (-a) b + 1) := by suffices toIcoDiv hp a (-b) = -toIocDiv hp (-(a + p)) b by rwa [neg_add, ← sub_eq_add_neg, toIocDiv_sub_eq_toIocDiv_add', toIocDiv_add_right] at this rw [← neg_eq_iff_eq_neg, eq_comm] apply toIocDiv_eq_of_sub_zsmul_mem_Ioc obtain ⟨hc, ho⟩ := sub_toIcoDiv_zsmul_mem_Ico hp a (-b) rw [← neg_lt_neg_iff, neg_sub' (-b), neg_neg, ← neg_smul] at ho rw [← neg_le_neg_iff, neg_sub' (-b), neg_neg, ← neg_smul] at hc refine ⟨ho, hc.trans_eq ?_⟩ rw [neg_add, neg_add_cancel_right] theorem toIcoDiv_neg' (a b : α) : toIcoDiv hp (-a) b = -(toIocDiv hp a (-b) + 1) := by simpa only [neg_neg] using toIcoDiv_neg hp (-a) (-b) theorem toIocDiv_neg (a b : α) : toIocDiv hp a (-b) = -(toIcoDiv hp (-a) b + 1) := by rw [← neg_neg b, toIcoDiv_neg, neg_neg, neg_neg, neg_add', neg_neg, add_sub_cancel_right] theorem toIocDiv_neg' (a b : α) : toIocDiv hp (-a) b = -(toIcoDiv hp a (-b) + 1) := by simpa only [neg_neg] using toIocDiv_neg hp (-a) (-b) @[simp] theorem toIcoMod_add_zsmul (a b : α) (m : ℤ) : toIcoMod hp a (b + m • p) = toIcoMod hp a b := by rw [toIcoMod, toIcoDiv_add_zsmul, toIcoMod, add_smul] abel @[simp] theorem toIcoMod_add_zsmul' (a b : α) (m : ℤ) : toIcoMod hp (a + m • p) b = toIcoMod hp a b + m • p := by simp only [toIcoMod, toIcoDiv_add_zsmul', sub_smul, sub_add] @[simp] theorem toIocMod_add_zsmul (a b : α) (m : ℤ) : toIocMod hp a (b + m • p) = toIocMod hp a b := by rw [toIocMod, toIocDiv_add_zsmul, toIocMod, add_smul] abel @[simp] theorem toIocMod_add_zsmul' (a b : α) (m : ℤ) : toIocMod hp (a + m • p) b = toIocMod hp a b + m • p := by simp only [toIocMod, toIocDiv_add_zsmul', sub_smul, sub_add] @[simp] theorem toIcoMod_zsmul_add (a b : α) (m : ℤ) : toIcoMod hp a (m • p + b) = toIcoMod hp a b := by rw [add_comm, toIcoMod_add_zsmul] @[simp] theorem toIcoMod_zsmul_add' (a b : α) (m : ℤ) : toIcoMod hp (m • p + a) b = m • p + toIcoMod hp a b := by rw [add_comm, toIcoMod_add_zsmul', add_comm] @[simp] theorem toIocMod_zsmul_add (a b : α) (m : ℤ) : toIocMod hp a (m • p + b) = toIocMod hp a b := by rw [add_comm, toIocMod_add_zsmul] @[simp] theorem toIocMod_zsmul_add' (a b : α) (m : ℤ) : toIocMod hp (m • p + a) b = m • p + toIocMod hp a b := by rw [add_comm, toIocMod_add_zsmul', add_comm] @[simp] theorem toIcoMod_sub_zsmul (a b : α) (m : ℤ) : toIcoMod hp a (b - m • p) = toIcoMod hp a b := by rw [sub_eq_add_neg, ← neg_smul, toIcoMod_add_zsmul] @[simp] theorem toIcoMod_sub_zsmul' (a b : α) (m : ℤ) : toIcoMod hp (a - m • p) b = toIcoMod hp a b - m • p := by simp_rw [sub_eq_add_neg, ← neg_smul, toIcoMod_add_zsmul'] @[simp] theorem toIocMod_sub_zsmul (a b : α) (m : ℤ) : toIocMod hp a (b - m • p) = toIocMod hp a b := by rw [sub_eq_add_neg, ← neg_smul, toIocMod_add_zsmul] @[simp] theorem toIocMod_sub_zsmul' (a b : α) (m : ℤ) : toIocMod hp (a - m • p) b = toIocMod hp a b - m • p := by simp_rw [sub_eq_add_neg, ← neg_smul, toIocMod_add_zsmul'] @[simp] theorem toIcoMod_add_right (a b : α) : toIcoMod hp a (b + p) = toIcoMod hp a b := by simpa only [one_zsmul] using toIcoMod_add_zsmul hp a b 1 @[simp] theorem toIcoMod_add_right' (a b : α) : toIcoMod hp (a + p) b = toIcoMod hp a b + p := by simpa only [one_zsmul] using toIcoMod_add_zsmul' hp a b 1 @[simp] theorem toIocMod_add_right (a b : α) : toIocMod hp a (b + p) = toIocMod hp a b := by simpa only [one_zsmul] using toIocMod_add_zsmul hp a b 1 @[simp] theorem toIocMod_add_right' (a b : α) : toIocMod hp (a + p) b = toIocMod hp a b + p := by simpa only [one_zsmul] using toIocMod_add_zsmul' hp a b 1 @[simp] theorem toIcoMod_add_left (a b : α) : toIcoMod hp a (p + b) = toIcoMod hp a b := by rw [add_comm, toIcoMod_add_right] @[simp] theorem toIcoMod_add_left' (a b : α) : toIcoMod hp (p + a) b = p + toIcoMod hp a b := by rw [add_comm, toIcoMod_add_right', add_comm] @[simp] theorem toIocMod_add_left (a b : α) : toIocMod hp a (p + b) = toIocMod hp a b := by rw [add_comm, toIocMod_add_right] @[simp] theorem toIocMod_add_left' (a b : α) : toIocMod hp (p + a) b = p + toIocMod hp a b := by rw [add_comm, toIocMod_add_right', add_comm] @[simp] theorem toIcoMod_sub (a b : α) : toIcoMod hp a (b - p) = toIcoMod hp a b := by simpa only [one_zsmul] using toIcoMod_sub_zsmul hp a b 1 @[simp] theorem toIcoMod_sub' (a b : α) : toIcoMod hp (a - p) b = toIcoMod hp a b - p := by simpa only [one_zsmul] using toIcoMod_sub_zsmul' hp a b 1 @[simp] theorem toIocMod_sub (a b : α) : toIocMod hp a (b - p) = toIocMod hp a b := by simpa only [one_zsmul] using toIocMod_sub_zsmul hp a b 1 @[simp] theorem toIocMod_sub' (a b : α) : toIocMod hp (a - p) b = toIocMod hp a b - p := by simpa only [one_zsmul] using toIocMod_sub_zsmul' hp a b 1 theorem toIcoMod_sub_eq_sub (a b c : α) : toIcoMod hp a (b - c) = toIcoMod hp (a + c) b - c := by simp_rw [toIcoMod, toIcoDiv_sub_eq_toIcoDiv_add, sub_right_comm] theorem toIocMod_sub_eq_sub (a b c : α) : toIocMod hp a (b - c) = toIocMod hp (a + c) b - c := by simp_rw [toIocMod, toIocDiv_sub_eq_toIocDiv_add, sub_right_comm] theorem toIcoMod_add_right_eq_add (a b c : α) : toIcoMod hp a (b + c) = toIcoMod hp (a - c) b + c := by simp_rw [toIcoMod, toIcoDiv_sub_eq_toIcoDiv_add', sub_add_eq_add_sub] theorem toIocMod_add_right_eq_add (a b c : α) : toIocMod hp a (b + c) = toIocMod hp (a - c) b + c := by simp_rw [toIocMod, toIocDiv_sub_eq_toIocDiv_add', sub_add_eq_add_sub] theorem toIcoMod_neg (a b : α) : toIcoMod hp a (-b) = p - toIocMod hp (-a) b := by simp_rw [toIcoMod, toIocMod, toIcoDiv_neg, neg_smul, add_smul] abel theorem toIcoMod_neg' (a b : α) : toIcoMod hp (-a) b = p - toIocMod hp a (-b) := by simpa only [neg_neg] using toIcoMod_neg hp (-a) (-b) theorem toIocMod_neg (a b : α) : toIocMod hp a (-b) = p - toIcoMod hp (-a) b := by simp_rw [toIocMod, toIcoMod, toIocDiv_neg, neg_smul, add_smul] abel theorem toIocMod_neg' (a b : α) : toIocMod hp (-a) b = p - toIcoMod hp a (-b) := by simpa only [neg_neg] using toIocMod_neg hp (-a) (-b) theorem toIcoMod_eq_toIcoMod : toIcoMod hp a b = toIcoMod hp a c ↔ ∃ n : ℤ, c - b = n • p := by refine ⟨fun h => ⟨toIcoDiv hp a c - toIcoDiv hp a b, ?_⟩, fun h => ?_⟩ · conv_lhs => rw [← toIcoMod_add_toIcoDiv_zsmul hp a b, ← toIcoMod_add_toIcoDiv_zsmul hp a c] rw [h, sub_smul] abel · rcases h with ⟨z, hz⟩ rw [sub_eq_iff_eq_add] at hz rw [hz, toIcoMod_zsmul_add] theorem toIocMod_eq_toIocMod : toIocMod hp a b = toIocMod hp a c ↔ ∃ n : ℤ, c - b = n • p := by refine ⟨fun h => ⟨toIocDiv hp a c - toIocDiv hp a b, ?_⟩, fun h => ?_⟩ · conv_lhs => rw [← toIocMod_add_toIocDiv_zsmul hp a b, ← toIocMod_add_toIocDiv_zsmul hp a c] rw [h, sub_smul] abel · rcases h with ⟨z, hz⟩ rw [sub_eq_iff_eq_add] at hz rw [hz, toIocMod_zsmul_add] /-! ### Links between the `Ico` and `Ioc` variants applied to the same element -/ section IcoIoc namespace AddCommGroup theorem modEq_iff_toIcoMod_eq_left : a ≡ b [PMOD p] ↔ toIcoMod hp a b = a := modEq_iff_eq_add_zsmul.trans ⟨by rintro ⟨n, rfl⟩ rw [toIcoMod_add_zsmul, toIcoMod_apply_left], fun h => ⟨toIcoDiv hp a b, eq_add_of_sub_eq h⟩⟩ theorem modEq_iff_toIocMod_eq_right : a ≡ b [PMOD p] ↔ toIocMod hp a b = a + p := by refine modEq_iff_eq_add_zsmul.trans ⟨?_, fun h => ⟨toIocDiv hp a b + 1, ?_⟩⟩ · rintro ⟨z, rfl⟩ rw [toIocMod_add_zsmul, toIocMod_apply_left] · rwa [add_one_zsmul, add_left_comm, ← sub_eq_iff_eq_add'] alias ⟨ModEq.toIcoMod_eq_left, _⟩ := modEq_iff_toIcoMod_eq_left alias ⟨ModEq.toIcoMod_eq_right, _⟩ := modEq_iff_toIocMod_eq_right variable (a b) open List in theorem tfae_modEq : TFAE [a ≡ b [PMOD p], ∀ z : ℤ, b - z • p ∉ Set.Ioo a (a + p), toIcoMod hp a b ≠ toIocMod hp a b, toIcoMod hp a b + p = toIocMod hp a b] := by rw [modEq_iff_toIcoMod_eq_left hp] tfae_have 3 → 2 := by rw [← not_exists, not_imp_not] exact fun ⟨i, hi⟩ => ((toIcoMod_eq_iff hp).2 ⟨Set.Ioo_subset_Ico_self hi, i, (sub_add_cancel b _).symm⟩).trans ((toIocMod_eq_iff hp).2 ⟨Set.Ioo_subset_Ioc_self hi, i, (sub_add_cancel b _).symm⟩).symm tfae_have 4 → 3 | h => by rw [← h, Ne, eq_comm, add_eq_left] exact hp.ne' tfae_have 1 → 4 | h => by rw [h, eq_comm, toIocMod_eq_iff, Set.right_mem_Ioc] refine ⟨lt_add_of_pos_right a hp, toIcoDiv hp a b - 1, ?_⟩ rw [sub_one_zsmul, add_add_add_comm, add_neg_cancel, add_zero] conv_lhs => rw [← toIcoMod_add_toIcoDiv_zsmul hp a b, h] tfae_have 2 → 1 := by rw [← not_exists, not_imp_comm] have h' := toIcoMod_mem_Ico hp a b exact fun h => ⟨_, h'.1.lt_of_ne' h, h'.2⟩ tfae_finish variable {a b} theorem modEq_iff_not_forall_mem_Ioo_mod : a ≡ b [PMOD p] ↔ ∀ z : ℤ, b - z • p ∉ Set.Ioo a (a + p) := (tfae_modEq hp a b).out 0 1 theorem modEq_iff_toIcoMod_ne_toIocMod : a ≡ b [PMOD p] ↔ toIcoMod hp a b ≠ toIocMod hp a b := (tfae_modEq hp a b).out 0 2 theorem modEq_iff_toIcoMod_add_period_eq_toIocMod : a ≡ b [PMOD p] ↔ toIcoMod hp a b + p = toIocMod hp a b := (tfae_modEq hp a b).out 0 3 theorem not_modEq_iff_toIcoMod_eq_toIocMod : ¬a ≡ b [PMOD p] ↔ toIcoMod hp a b = toIocMod hp a b := (modEq_iff_toIcoMod_ne_toIocMod _).not_left theorem not_modEq_iff_toIcoDiv_eq_toIocDiv : ¬a ≡ b [PMOD p] ↔ toIcoDiv hp a b = toIocDiv hp a b := by rw [not_modEq_iff_toIcoMod_eq_toIocMod hp, toIcoMod, toIocMod, sub_right_inj, zsmul_left_inj hp] theorem modEq_iff_toIcoDiv_eq_toIocDiv_add_one : a ≡ b [PMOD p] ↔ toIcoDiv hp a b = toIocDiv hp a b + 1 := by rw [modEq_iff_toIcoMod_add_period_eq_toIocMod hp, toIcoMod, toIocMod, ← eq_sub_iff_add_eq, sub_sub, sub_right_inj, ← add_one_zsmul, zsmul_left_inj hp] end AddCommGroup open AddCommGroup /-- If `a` and `b` fall within the same cycle WRT `c`, then they are congruent modulo `p`. -/ @[simp] theorem toIcoMod_inj {c : α} : toIcoMod hp c a = toIcoMod hp c b ↔ a ≡ b [PMOD p] := by simp_rw [toIcoMod_eq_toIcoMod, modEq_iff_eq_add_zsmul, sub_eq_iff_eq_add'] alias ⟨_, AddCommGroup.ModEq.toIcoMod_eq_toIcoMod⟩ := toIcoMod_inj theorem Ico_eq_locus_Ioc_eq_iUnion_Ioo : { b | toIcoMod hp a b = toIocMod hp a b } = ⋃ z : ℤ, Set.Ioo (a + z • p) (a + p + z • p) := by ext1 simp_rw [Set.mem_setOf, Set.mem_iUnion, ← Set.sub_mem_Ioo_iff_left, ← not_modEq_iff_toIcoMod_eq_toIocMod, modEq_iff_not_forall_mem_Ioo_mod hp, not_forall, Classical.not_not] theorem toIocDiv_wcovBy_toIcoDiv (a b : α) : toIocDiv hp a b ⩿ toIcoDiv hp a b := by suffices toIocDiv hp a b = toIcoDiv hp a b ∨ toIocDiv hp a b + 1 = toIcoDiv hp a b by rwa [wcovBy_iff_eq_or_covBy, ← Order.succ_eq_iff_covBy] rw [eq_comm, ← not_modEq_iff_toIcoDiv_eq_toIocDiv, eq_comm, ← modEq_iff_toIcoDiv_eq_toIocDiv_add_one] exact em' _ theorem toIcoMod_le_toIocMod (a b : α) : toIcoMod hp a b ≤ toIocMod hp a b := by rw [toIcoMod, toIocMod, sub_le_sub_iff_left] exact zsmul_left_mono hp.le (toIocDiv_wcovBy_toIcoDiv _ _ _).le theorem toIocMod_le_toIcoMod_add (a b : α) : toIocMod hp a b ≤ toIcoMod hp a b + p := by rw [toIcoMod, toIocMod, sub_add, sub_le_sub_iff_left, sub_le_iff_le_add, ← add_one_zsmul, (zsmul_left_strictMono hp).le_iff_le] apply (toIocDiv_wcovBy_toIcoDiv _ _ _).le_succ end IcoIoc open AddCommGroup theorem toIcoMod_eq_self : toIcoMod hp a b = b ↔ b ∈ Set.Ico a (a + p) := by rw [toIcoMod_eq_iff, and_iff_left] exact ⟨0, by simp⟩ theorem toIocMod_eq_self : toIocMod hp a b = b ↔ b ∈ Set.Ioc a (a + p) := by rw [toIocMod_eq_iff, and_iff_left] exact ⟨0, by simp⟩ @[simp] theorem toIcoMod_toIcoMod (a₁ a₂ b : α) : toIcoMod hp a₁ (toIcoMod hp a₂ b) = toIcoMod hp a₁ b := (toIcoMod_eq_toIcoMod _).2 ⟨toIcoDiv hp a₂ b, self_sub_toIcoMod hp a₂ b⟩ @[simp] theorem toIcoMod_toIocMod (a₁ a₂ b : α) : toIcoMod hp a₁ (toIocMod hp a₂ b) = toIcoMod hp a₁ b := (toIcoMod_eq_toIcoMod _).2 ⟨toIocDiv hp a₂ b, self_sub_toIocMod hp a₂ b⟩ @[simp] theorem toIocMod_toIocMod (a₁ a₂ b : α) : toIocMod hp a₁ (toIocMod hp a₂ b) = toIocMod hp a₁ b := (toIocMod_eq_toIocMod _).2 ⟨toIocDiv hp a₂ b, self_sub_toIocMod hp a₂ b⟩ @[simp] theorem toIocMod_toIcoMod (a₁ a₂ b : α) : toIocMod hp a₁ (toIcoMod hp a₂ b) = toIocMod hp a₁ b := (toIocMod_eq_toIocMod _).2 ⟨toIcoDiv hp a₂ b, self_sub_toIcoMod hp a₂ b⟩ theorem toIcoMod_periodic (a : α) : Function.Periodic (toIcoMod hp a) p := toIcoMod_add_right hp a theorem toIocMod_periodic (a : α) : Function.Periodic (toIocMod hp a) p := toIocMod_add_right hp a -- helper lemmas for when `a = 0` section Zero theorem toIcoMod_zero_sub_comm (a b : α) : toIcoMod hp 0 (a - b) = p - toIocMod hp 0 (b - a) := by rw [← neg_sub, toIcoMod_neg, neg_zero] theorem toIocMod_zero_sub_comm (a b : α) : toIocMod hp 0 (a - b) = p - toIcoMod hp 0 (b - a) := by rw [← neg_sub, toIocMod_neg, neg_zero] theorem toIcoDiv_eq_sub (a b : α) : toIcoDiv hp a b = toIcoDiv hp 0 (b - a) := by rw [toIcoDiv_sub_eq_toIcoDiv_add, zero_add] theorem toIocDiv_eq_sub (a b : α) : toIocDiv hp a b = toIocDiv hp 0 (b - a) := by rw [toIocDiv_sub_eq_toIocDiv_add, zero_add] theorem toIcoMod_eq_sub (a b : α) : toIcoMod hp a b = toIcoMod hp 0 (b - a) + a := by rw [toIcoMod_sub_eq_sub, zero_add, sub_add_cancel] theorem toIocMod_eq_sub (a b : α) : toIocMod hp a b = toIocMod hp 0 (b - a) + a := by rw [toIocMod_sub_eq_sub, zero_add, sub_add_cancel] theorem toIcoMod_add_toIocMod_zero (a b : α) : toIcoMod hp 0 (a - b) + toIocMod hp 0 (b - a) = p := by rw [toIcoMod_zero_sub_comm, sub_add_cancel] theorem toIocMod_add_toIcoMod_zero (a b : α) : toIocMod hp 0 (a - b) + toIcoMod hp 0 (b - a) = p := by rw [_root_.add_comm, toIcoMod_add_toIocMod_zero] end Zero /-- `toIcoMod` as an equiv from the quotient. -/ @[simps symm_apply] def QuotientAddGroup.equivIcoMod (a : α) : α ⧸ AddSubgroup.zmultiples p ≃ Set.Ico a (a + p) where toFun b := ⟨(toIcoMod_periodic hp a).lift b, QuotientAddGroup.induction_on b <| toIcoMod_mem_Ico hp a⟩ invFun := (↑) right_inv b := Subtype.ext <| (toIcoMod_eq_self hp).mpr b.prop left_inv b := by induction b using QuotientAddGroup.induction_on dsimp rw [QuotientAddGroup.eq_iff_sub_mem, toIcoMod_sub_self] apply AddSubgroup.zsmul_mem_zmultiples @[simp] theorem QuotientAddGroup.equivIcoMod_coe (a b : α) : QuotientAddGroup.equivIcoMod hp a ↑b = ⟨toIcoMod hp a b, toIcoMod_mem_Ico hp a _⟩ := rfl @[simp] theorem QuotientAddGroup.equivIcoMod_zero (a : α) : QuotientAddGroup.equivIcoMod hp a 0 = ⟨toIcoMod hp a 0, toIcoMod_mem_Ico hp a _⟩ := rfl /-- `toIocMod` as an equiv from the quotient. -/ @[simps symm_apply] def QuotientAddGroup.equivIocMod (a : α) : α ⧸ AddSubgroup.zmultiples p ≃ Set.Ioc a (a + p) where toFun b := ⟨(toIocMod_periodic hp a).lift b, QuotientAddGroup.induction_on b <| toIocMod_mem_Ioc hp a⟩ invFun := (↑) right_inv b := Subtype.ext <| (toIocMod_eq_self hp).mpr b.prop left_inv b := by induction b using QuotientAddGroup.induction_on dsimp rw [QuotientAddGroup.eq_iff_sub_mem, toIocMod_sub_self] apply AddSubgroup.zsmul_mem_zmultiples @[simp] theorem QuotientAddGroup.equivIocMod_coe (a b : α) : QuotientAddGroup.equivIocMod hp a ↑b = ⟨toIocMod hp a b, toIocMod_mem_Ioc hp a _⟩ := rfl @[simp] theorem QuotientAddGroup.equivIocMod_zero (a : α) : QuotientAddGroup.equivIocMod hp a 0 = ⟨toIocMod hp a 0, toIocMod_mem_Ioc hp a _⟩ := rfl end /-! ### The circular order structure on `α ⧸ AddSubgroup.zmultiples p` -/ section Circular open AddCommGroup private theorem toIxxMod_iff (x₁ x₂ x₃ : α) : toIcoMod hp x₁ x₂ ≤ toIocMod hp x₁ x₃ ↔ toIcoMod hp 0 (x₂ - x₁) + toIcoMod hp 0 (x₁ - x₃) ≤ p := by rw [toIcoMod_eq_sub, toIocMod_eq_sub _ x₁, add_le_add_iff_right, ← neg_sub x₁ x₃, toIocMod_neg, neg_zero, le_sub_iff_add_le] private theorem toIxxMod_cyclic_left {x₁ x₂ x₃ : α} (h : toIcoMod hp x₁ x₂ ≤ toIocMod hp x₁ x₃) : toIcoMod hp x₂ x₃ ≤ toIocMod hp x₂ x₁ := by let x₂' := toIcoMod hp x₁ x₂ let x₃' := toIcoMod hp x₂' x₃ have h : x₂' ≤ toIocMod hp x₁ x₃' := by simpa [x₃'] have h₂₁ : x₂' < x₁ + p := toIcoMod_lt_right _ _ _ have h₃₂ : x₃' - p < x₂' := sub_lt_iff_lt_add.2 (toIcoMod_lt_right _ _ _) suffices hequiv : x₃' ≤ toIocMod hp x₂' x₁ by obtain ⟨z, hd⟩ : ∃ z : ℤ, x₂ = x₂' + z • p := ((toIcoMod_eq_iff hp).1 rfl).2 simpa [hd, toIocMod_add_zsmul', toIcoMod_add_zsmul', add_le_add_iff_right] rcases le_or_lt x₃' (x₁ + p) with h₃₁ | h₁₃ · suffices hIoc₂₁ : toIocMod hp x₂' x₁ = x₁ + p from hIoc₂₁.symm.trans_ge h₃₁ apply (toIocMod_eq_iff hp).2 exact ⟨⟨h₂₁, by simp [x₂', left_le_toIcoMod]⟩, -1, by simp⟩ have hIoc₁₃ : toIocMod hp x₁ x₃' = x₃' - p := by apply (toIocMod_eq_iff hp).2 exact ⟨⟨lt_sub_iff_add_lt.2 h₁₃, le_of_lt (h₃₂.trans h₂₁)⟩, 1, by simp⟩ have not_h₃₂ := (h.trans hIoc₁₃.le).not_lt contradiction private theorem toIxxMod_antisymm (h₁₂₃ : toIcoMod hp a b ≤ toIocMod hp a c) (h₁₃₂ : toIcoMod hp a c ≤ toIocMod hp a b) : b ≡ a [PMOD p] ∨ c ≡ b [PMOD p] ∨ a ≡ c [PMOD p] := by by_contra! h rw [modEq_comm] at h rw [← (not_modEq_iff_toIcoMod_eq_toIocMod hp).mp h.2.2] at h₁₂₃ rw [← (not_modEq_iff_toIcoMod_eq_toIocMod hp).mp h.1] at h₁₃₂ exact h.2.1 ((toIcoMod_inj _).1 <| h₁₃₂.antisymm h₁₂₃) private theorem toIxxMod_total' (a b c : α) : toIcoMod hp b a ≤ toIocMod hp b c ∨ toIcoMod hp b c ≤ toIocMod hp b a := by /- an essential ingredient is the lemma saying {a-b} + {b-a} = period if a ≠ b (and = 0 if a = b). Thus if a ≠ b and b ≠ c then ({a-b} + {b-c}) + ({c-b} + {b-a}) = 2 * period, so one of `{a-b} + {b-c}` and `{c-b} + {b-a}` must be `≤ period` -/ have := congr_arg₂ (· + ·) (toIcoMod_add_toIocMod_zero hp a b) (toIcoMod_add_toIocMod_zero hp c b) simp only [add_add_add_comm] at this rw [_root_.add_comm (toIocMod _ _ _), add_add_add_comm, ← two_nsmul] at this replace := min_le_of_add_le_two_nsmul this.le
rw [min_le_iff] at this rw [toIxxMod_iff, toIxxMod_iff]
Mathlib/Algebra/Order/ToIntervalMod.lean
764
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/- Copyright (c) 2020 Johan Commelin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin, Robert Y. Lewis -/ import Mathlib.RingTheory.WittVector.Truncated import Mathlib.RingTheory.WittVector.Identities import Mathlib.NumberTheory.Padics.RingHoms /-! # Comparison isomorphism between `WittVector p (ZMod p)` and `ℤ_[p]` We construct a ring isomorphism between `WittVector p (ZMod p)` and `ℤ_[p]`. This isomorphism follows from the fact that both satisfy the universal property of the inverse limit of `ZMod (p^n)`. ## Main declarations * `WittVector.toZModPow`: a family of compatible ring homs `𝕎 (ZMod p) → ZMod (p^k)` * `WittVector.equiv`: the isomorphism ## References * [Hazewinkel, *Witt Vectors*][Haze09] * [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21] -/ noncomputable section variable {p : ℕ} [hp : Fact p.Prime] local notation "𝕎" => WittVector p namespace TruncatedWittVector variable (p) (n : ℕ) (R : Type*) [CommRing R] theorem eq_of_le_of_cast_pow_eq_zero [CharP R p] (i : ℕ) (hin : i ≤ n) (hpi : (p : TruncatedWittVector p n R) ^ i = 0) : i = n := by contrapose! hpi replace hin := lt_of_le_of_ne hin hpi; clear hpi have : (p : TruncatedWittVector p n R) ^ i = WittVector.truncate n ((p : 𝕎 R) ^ i) := by rw [RingHom.map_pow, map_natCast] rw [this, ne_eq, TruncatedWittVector.ext_iff, not_forall]; clear this use ⟨i, hin⟩ rw [WittVector.coeff_truncate, coeff_zero, Fin.val_mk, WittVector.coeff_p_pow] haveI : Nontrivial R := CharP.nontrivial_of_char_ne_one hp.1.ne_one exact one_ne_zero section Iso variable {R} theorem card_zmod : Fintype.card (TruncatedWittVector p n (ZMod p)) = p ^ n := by rw [card, ZMod.card] theorem charP_zmod : CharP (TruncatedWittVector p n (ZMod p)) (p ^ n) := charP_of_prime_pow_injective _ _ _ (card_zmod _ _) (eq_of_le_of_cast_pow_eq_zero p n (ZMod p)) attribute [local instance] charP_zmod /-- The unique isomorphism between `ZMod p^n` and `TruncatedWittVector p n (ZMod p)`. This isomorphism exists, because `TruncatedWittVector p n (ZMod p)` is a finite ring with characteristic and cardinality `p^n`. -/ def zmodEquivTrunc : ZMod (p ^ n) ≃+* TruncatedWittVector p n (ZMod p) := ZMod.ringEquiv (TruncatedWittVector p n (ZMod p)) (card_zmod _ _) theorem zmodEquivTrunc_apply {x : ZMod (p ^ n)} : zmodEquivTrunc p n x = ZMod.castHom (m := p ^ n) (by rfl) (TruncatedWittVector p n (ZMod p)) x := rfl /-- The following diagram commutes: ```text ZMod (p^n) ----------------------------> ZMod (p^m) | | | | v v TruncatedWittVector p n (ZMod p) ----> TruncatedWittVector p m (ZMod p) ``` Here the vertical arrows are `TruncatedWittVector.zmodEquivTrunc`, the horizontal arrow at the top is `ZMod.castHom`, and the horizontal arrow at the bottom is `TruncatedWittVector.truncate`. -/ theorem commutes {m : ℕ} (hm : n ≤ m) : (truncate hm).comp (zmodEquivTrunc p m).toRingHom = (zmodEquivTrunc p n).toRingHom.comp (ZMod.castHom (pow_dvd_pow p hm) _) := RingHom.ext_zmod _ _ theorem commutes' {m : ℕ} (hm : n ≤ m) (x : ZMod (p ^ m)) : truncate hm (zmodEquivTrunc p m x) = zmodEquivTrunc p n (ZMod.castHom (pow_dvd_pow p hm) _ x) := show (truncate hm).comp (zmodEquivTrunc p m).toRingHom x = _ by rw [commutes _ _ hm]; rfl theorem commutes_symm' {m : ℕ} (hm : n ≤ m) (x : TruncatedWittVector p m (ZMod p)) : (zmodEquivTrunc p n).symm (truncate hm x) = ZMod.castHom (pow_dvd_pow p hm) _ ((zmodEquivTrunc p m).symm x) := by apply (zmodEquivTrunc p n).injective rw [← commutes' _ _ hm] simp /-- The following diagram commutes: ```text TruncatedWittVector p n (ZMod p) ----> TruncatedWittVector p m (ZMod p) | | | | v v ZMod (p^n) ----------------------------> ZMod (p^m) ``` Here the vertical arrows are `(TruncatedWittVector.zmodEquivTrunc p _).symm`, the horizontal arrow at the top is `ZMod.castHom`, and the horizontal arrow at the bottom is `TruncatedWittVector.truncate`. -/ theorem commutes_symm {m : ℕ} (hm : n ≤ m) : (zmodEquivTrunc p n).symm.toRingHom.comp (truncate hm) = (ZMod.castHom (pow_dvd_pow p hm) _).comp (zmodEquivTrunc p m).symm.toRingHom := by ext; apply commutes_symm' end Iso end TruncatedWittVector
namespace WittVector open TruncatedWittVector
Mathlib/RingTheory/WittVector/Compare.lean
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/- Copyright (c) 2023 Frédéric Dupuis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Frédéric Dupuis -/ import Mathlib.Computability.AkraBazzi.GrowsPolynomially import Mathlib.Analysis.Calculus.Deriv.Inv import Mathlib.Analysis.SpecialFunctions.Pow.Deriv /-! # Divide-and-conquer recurrences and the Akra-Bazzi theorem A divide-and-conquer recurrence is a function `T : ℕ → ℝ` that satisfies a recurrence relation of the form `T(n) = ∑_{i=0}^{k-1} a_i T(r_i(n)) + g(n)` for large enough `n`, where `r_i(n)` is some function where `‖r_i(n) - b_i n‖ ∈ o(n / (log n)^2)` for every `i`, the `a_i`'s are some positive coefficients, and the `b_i`'s are reals `∈ (0,1)`. (Note that this can be improved to `O(n / (log n)^(1+ε))`, this is left as future work.) These recurrences arise mainly in the analysis of divide-and-conquer algorithms such as mergesort or Strassen's algorithm for matrix multiplication. This class of algorithms works by dividing an instance of the problem of size `n`, into `k` smaller instances, where the `i`'th instance is of size roughly `b_i n`, and calling itself recursively on those smaller instances. `T(n)` then represents the running time of the algorithm, and `g(n)` represents the running time required to actually divide up the instance and process the answers that come out of the recursive calls. Since virtually all such algorithms produce instances that are only approximately of size `b_i n` (they have to round up or down at the very least), we allow the instance sizes to be given by some function `r_i(n)` that approximates `b_i n`. The Akra-Bazzi theorem gives the asymptotic order of such a recurrence: it states that `T(n) ∈ Θ(n^p (1 + ∑_{u=0}^{n-1} g(n) / u^{p+1}))`, where `p` is the unique real number such that `∑ a_i b_i^p = 1`. ## Main definitions and results * `AkraBazziRecurrence T g a b r`: the predicate stating that `T : ℕ → ℝ` satisfies an Akra-Bazzi recurrence with parameters `g`, `a`, `b` and `r` as above. * `GrowsPolynomially`: The growth condition that `g` must satisfy for the theorem to apply. It roughly states that `c₁ g(n) ≤ g(u) ≤ c₂ g(n)`, for u between b*n and n for any constant `b ∈ (0,1)`. * `sumTransform`: The transformation which turns a function `g` into `n^p * ∑ u ∈ Finset.Ico n₀ n, g u / u^(p+1)`. * `asympBound`: The asymptotic bound satisfied by an Akra-Bazzi recurrence, namely `n^p (1 + ∑ g(u) / u^(p+1))` * `isTheta_asympBound`: The main result stating that `T(n) ∈ Θ(n^p (1 + ∑_{u=0}^{n-1} g(n) / u^{p+1}))` ## Implementation Note that the original version of the theorem has an integral rather than a sum in the above expression, and first considers the `T : ℝ → ℝ` case before moving on to `ℕ → ℝ`. We prove the above version with a sum, as it is simpler and more relevant for algorithms. ## TODO * Specialize this theorem to the very common case where the recurrence is of the form `T(n) = ℓT(r_i(n)) + g(n)` where `g(n) ∈ Θ(n^t)` for some `t`. (This is often called the "master theorem" in the literature.) * Add the original version of the theorem with an integral instead of a sum. ## References * Mohamad Akra and Louay Bazzi, On the solution of linear recurrence equations * Tom Leighton, Notes on better master theorems for divide-and-conquer recurrences * Manuel Eberl, Asymptotic reasoning in a proof assistant -/ open Finset Real Filter Asymptotics open scoped Topology /-! #### Definition of Akra-Bazzi recurrences This section defines the predicate `AkraBazziRecurrence T g a b r` which states that `T` satisfies the recurrence `T(n) = ∑_{i=0}^{k-1} a_i T(r_i(n)) + g(n)` with appropriate conditions on the various parameters. -/ /-- An Akra-Bazzi recurrence is a function that satisfies the recurrence `T n = (∑ i, a i * T (r i n)) + g n`. -/ structure AkraBazziRecurrence {α : Type*} [Fintype α] [Nonempty α] (T : ℕ → ℝ) (g : ℝ → ℝ) (a : α → ℝ) (b : α → ℝ) (r : α → ℕ → ℕ) where /-- Point below which the recurrence is in the base case -/ n₀ : ℕ /-- `n₀` is always `> 0` -/ n₀_gt_zero : 0 < n₀ /-- The `a`'s are nonzero -/ a_pos : ∀ i, 0 < a i /-- The `b`'s are nonzero -/ b_pos : ∀ i, 0 < b i /-- The b's are less than 1 -/ b_lt_one : ∀ i, b i < 1 /-- `g` is nonnegative -/ g_nonneg : ∀ x ≥ 0, 0 ≤ g x /-- `g` grows polynomially -/ g_grows_poly : AkraBazziRecurrence.GrowsPolynomially g /-- The actual recurrence -/ h_rec (n : ℕ) (hn₀ : n₀ ≤ n) : T n = (∑ i, a i * T (r i n)) + g n /-- Base case: `T(n) > 0` whenever `n < n₀` -/ T_gt_zero' (n : ℕ) (hn : n < n₀) : 0 < T n /-- The `r`'s always reduce `n` -/ r_lt_n : ∀ i n, n₀ ≤ n → r i n < n /-- The `r`'s approximate the `b`'s -/ dist_r_b : ∀ i, (fun n => (r i n : ℝ) - b i * n) =o[atTop] fun n => n / (log n) ^ 2 namespace AkraBazziRecurrence section min_max variable {α : Type*} [Finite α] [Nonempty α] /-- Smallest `b i` -/ noncomputable def min_bi (b : α → ℝ) : α := Classical.choose <| Finite.exists_min b /-- Largest `b i` -/ noncomputable def max_bi (b : α → ℝ) : α := Classical.choose <| Finite.exists_max b @[aesop safe apply] lemma min_bi_le {b : α → ℝ} (i : α) : b (min_bi b) ≤ b i := Classical.choose_spec (Finite.exists_min b) i @[aesop safe apply] lemma max_bi_le {b : α → ℝ} (i : α) : b i ≤ b (max_bi b) := Classical.choose_spec (Finite.exists_max b) i end min_max lemma isLittleO_self_div_log_id : (fun (n : ℕ) => n / log n ^ 2) =o[atTop] (fun (n : ℕ) => (n : ℝ)) := by calc (fun (n : ℕ) => (n : ℝ) / log n ^ 2) = fun (n : ℕ) => (n : ℝ) * ((log n) ^ 2)⁻¹ := by simp_rw [div_eq_mul_inv] _ =o[atTop] fun (n : ℕ) => (n : ℝ) * 1⁻¹ := by refine IsBigO.mul_isLittleO (isBigO_refl _ _) ?_ refine IsLittleO.inv_rev ?main ?zero case zero => simp case main => calc _ = (fun (_ : ℕ) => ((1 : ℝ) ^ 2)) := by simp _ =o[atTop] (fun (n : ℕ) => (log n)^2) := IsLittleO.pow (IsLittleO.natCast_atTop <| isLittleO_const_log_atTop) (by norm_num) _ = (fun (n : ℕ) => (n : ℝ)) := by ext; simp variable {α : Type*} [Fintype α] {T : ℕ → ℝ} {g : ℝ → ℝ} {a b : α → ℝ} {r : α → ℕ → ℕ} variable [Nonempty α] (R : AkraBazziRecurrence T g a b r) section include R lemma dist_r_b' : ∀ᶠ n in atTop, ∀ i, ‖(r i n : ℝ) - b i * n‖ ≤ n / log n ^ 2 := by rw [Filter.eventually_all] intro i simpa using IsLittleO.eventuallyLE (R.dist_r_b i) lemma eventually_b_le_r : ∀ᶠ (n : ℕ) in atTop, ∀ i, (b i : ℝ) * n - (n / log n ^ 2) ≤ r i n := by filter_upwards [R.dist_r_b'] with n hn intro i have h₁ : 0 ≤ b i := le_of_lt <| R.b_pos _ rw [sub_le_iff_le_add, add_comm, ← sub_le_iff_le_add] calc (b i : ℝ) * n - r i n = ‖b i * n‖ - ‖(r i n : ℝ)‖ := by simp only [norm_mul, RCLike.norm_natCast, sub_left_inj, Nat.cast_eq_zero, Real.norm_of_nonneg h₁] _ ≤ ‖(b i * n : ℝ) - r i n‖ := norm_sub_norm_le _ _ _ = ‖(r i n : ℝ) - b i * n‖ := norm_sub_rev _ _ _ ≤ n / log n ^ 2 := hn i lemma eventually_r_le_b : ∀ᶠ (n : ℕ) in atTop, ∀ i, r i n ≤ (b i : ℝ) * n + (n / log n ^ 2) := by filter_upwards [R.dist_r_b'] with n hn intro i calc r i n = b i * n + (r i n - b i * n) := by ring _ ≤ b i * n + ‖r i n - b i * n‖ := by gcongr; exact Real.le_norm_self _ _ ≤ b i * n + n / log n ^ 2 := by gcongr; exact hn i lemma eventually_r_lt_n : ∀ᶠ (n : ℕ) in atTop, ∀ i, r i n < n := by filter_upwards [eventually_ge_atTop R.n₀] with n hn exact fun i => R.r_lt_n i n hn lemma eventually_bi_mul_le_r : ∀ᶠ (n : ℕ) in atTop, ∀ i, (b (min_bi b) / 2) * n ≤ r i n := by have gt_zero : 0 < b (min_bi b) := R.b_pos (min_bi b) have hlo := isLittleO_self_div_log_id rw [Asymptotics.isLittleO_iff] at hlo have hlo' := hlo (by positivity : 0 < b (min_bi b) / 2) filter_upwards [hlo', R.eventually_b_le_r] with n hn hn' intro i simp only [Real.norm_of_nonneg (by positivity : 0 ≤ (n : ℝ))] at hn calc b (min_bi b) / 2 * n = b (min_bi b) * n - b (min_bi b) / 2 * n := by ring _ ≤ b (min_bi b) * n - ‖n / log n ^ 2‖ := by gcongr _ ≤ b i * n - ‖n / log n ^ 2‖ := by gcongr; aesop _ = b i * n - n / log n ^ 2 := by congr exact Real.norm_of_nonneg <| by positivity _ ≤ r i n := hn' i lemma bi_min_div_two_lt_one : b (min_bi b) / 2 < 1 := by have gt_zero : 0 < b (min_bi b) := R.b_pos (min_bi b) calc b (min_bi b) / 2 < b (min_bi b) := by aesop (add safe apply div_two_lt_of_pos) _ < 1 := R.b_lt_one _ lemma bi_min_div_two_pos : 0 < b (min_bi b) / 2 := div_pos (R.b_pos _) (by norm_num) lemma exists_eventually_const_mul_le_r : ∃ c ∈ Set.Ioo (0 : ℝ) 1, ∀ᶠ (n : ℕ) in atTop, ∀ i, c * n ≤ r i n := by have gt_zero : 0 < b (min_bi b) := R.b_pos (min_bi b) exact ⟨b (min_bi b) / 2, ⟨⟨by positivity, R.bi_min_div_two_lt_one⟩, R.eventually_bi_mul_le_r⟩⟩ lemma eventually_r_ge (C : ℝ) : ∀ᶠ (n : ℕ) in atTop, ∀ i, C ≤ r i n := by obtain ⟨c, hc_mem, hc⟩ := R.exists_eventually_const_mul_le_r filter_upwards [eventually_ge_atTop ⌈C / c⌉₊, hc] with n hn₁ hn₂ have h₁ := hc_mem.1 intro i calc C = c * (C / c) := by rw [← mul_div_assoc] exact (mul_div_cancel_left₀ _ (by positivity)).symm _ ≤ c * ⌈C / c⌉₊ := by gcongr; simp [Nat.le_ceil] _ ≤ c * n := by gcongr _ ≤ r i n := hn₂ i lemma tendsto_atTop_r (i : α) : Tendsto (r i) atTop atTop := by rw [tendsto_atTop] intro b have := R.eventually_r_ge b rw [Filter.eventually_all] at this exact_mod_cast this i lemma tendsto_atTop_r_real (i : α) : Tendsto (fun n => (r i n : ℝ)) atTop atTop := Tendsto.comp tendsto_natCast_atTop_atTop (R.tendsto_atTop_r i) lemma exists_eventually_r_le_const_mul : ∃ c ∈ Set.Ioo (0 : ℝ) 1, ∀ᶠ (n : ℕ) in atTop, ∀ i, r i n ≤ c * n := by let c := b (max_bi b) + (1 - b (max_bi b)) / 2 have h_max_bi_pos : 0 < b (max_bi b) := R.b_pos _ have h_max_bi_lt_one : 0 < 1 - b (max_bi b) := by have : b (max_bi b) < 1 := R.b_lt_one _ linarith have hc_pos : 0 < c := by positivity have h₁ : 0 < (1 - b (max_bi b)) / 2 := by positivity have hc_lt_one : c < 1 := calc b (max_bi b) + (1 - b (max_bi b)) / 2 = b (max_bi b) * (1 / 2) + 1 / 2 := by ring _ < 1 * (1 / 2) + 1 / 2 := by gcongr exact R.b_lt_one _ _ = 1 := by norm_num refine ⟨c, ⟨hc_pos, hc_lt_one⟩, ?_⟩ have hlo := isLittleO_self_div_log_id rw [Asymptotics.isLittleO_iff] at hlo have hlo' := hlo h₁ filter_upwards [hlo', R.eventually_r_le_b] with n hn hn' intro i rw [Real.norm_of_nonneg (by positivity)] at hn simp only [Real.norm_of_nonneg (by positivity : 0 ≤ (n : ℝ))] at hn calc r i n ≤ b i * n + n / log n ^ 2 := by exact hn' i _ ≤ b i * n + (1 - b (max_bi b)) / 2 * n := by gcongr _ = (b i + (1 - b (max_bi b)) / 2) * n := by ring _ ≤ (b (max_bi b) + (1 - b (max_bi b)) / 2) * n := by gcongr; exact max_bi_le _ lemma eventually_r_pos : ∀ᶠ (n : ℕ) in atTop, ∀ i, 0 < r i n := by rw [Filter.eventually_all] exact fun i => (R.tendsto_atTop_r i).eventually_gt_atTop 0 lemma eventually_log_b_mul_pos : ∀ᶠ (n : ℕ) in atTop, ∀ i, 0 < log (b i * n) := by rw [Filter.eventually_all] intro i have h : Tendsto (fun (n : ℕ) => log (b i * n)) atTop atTop := Tendsto.comp tendsto_log_atTop <| Tendsto.const_mul_atTop (b_pos R i) tendsto_natCast_atTop_atTop exact h.eventually_gt_atTop 0 @[aesop safe apply] lemma T_pos (n : ℕ) : 0 < T n := by induction n using Nat.strongRecOn with | ind n h_ind => cases lt_or_le n R.n₀ with | inl hn => exact R.T_gt_zero' n hn -- n < R.n₀ | inr hn => -- R.n₀ ≤ n rw [R.h_rec n hn] have := R.g_nonneg refine add_pos_of_pos_of_nonneg (Finset.sum_pos ?sum_elems univ_nonempty) (by aesop) exact fun i _ => mul_pos (R.a_pos i) <| h_ind _ (R.r_lt_n i _ hn) @[aesop safe apply] lemma T_nonneg (n : ℕ) : 0 ≤ T n := le_of_lt <| R.T_pos n end /-! #### Smoothing function We define `ε` as the "smoothing function" `fun n => 1 / log n`, which will be used in the form of a factor of `1 ± ε n` needed to make the induction step go through. This is its own definition to make it easier to switch to a different smoothing function. For example, choosing `1 / log n ^ δ` for a suitable choice of `δ` leads to a slightly tighter theorem at the price of a more complicated proof. This part of the file then proves several properties of this function that will be needed later in the proof. -/ /-- The "smoothing function" is defined as `1 / log n`. This is defined as an `ℝ → ℝ` function as opposed to `ℕ → ℝ` since this is more convenient for the proof, where we need to e.g. take derivatives. -/ noncomputable def smoothingFn (n : ℝ) : ℝ := 1 / log n local notation "ε" => smoothingFn lemma one_add_smoothingFn_le_two {x : ℝ} (hx : exp 1 ≤ x) : 1 + ε x ≤ 2 := by simp only [smoothingFn, ← one_add_one_eq_two] gcongr have : 1 < x := by calc 1 = exp 0 := by simp _ < exp 1 := by simp _ ≤ x := hx rw [div_le_one (log_pos this)] calc 1 = log (exp 1) := by simp _ ≤ log x := log_le_log (exp_pos _) hx lemma isLittleO_smoothingFn_one : ε =o[atTop] (fun _ => (1 : ℝ)) := by unfold smoothingFn refine isLittleO_of_tendsto (fun _ h => False.elim <| one_ne_zero h) ?_ simp only [one_div, div_one] exact Tendsto.inv_tendsto_atTop Real.tendsto_log_atTop lemma isEquivalent_one_add_smoothingFn_one : (fun x => 1 + ε x) ~[atTop] (fun _ => (1 : ℝ)) := IsEquivalent.add_isLittleO IsEquivalent.refl isLittleO_smoothingFn_one lemma isEquivalent_one_sub_smoothingFn_one : (fun x => 1 - ε x) ~[atTop] (fun _ => (1 : ℝ)) := IsEquivalent.sub_isLittleO IsEquivalent.refl isLittleO_smoothingFn_one lemma growsPolynomially_one_sub_smoothingFn : GrowsPolynomially fun x => 1 - ε x := GrowsPolynomially.of_isEquivalent_const isEquivalent_one_sub_smoothingFn_one lemma growsPolynomially_one_add_smoothingFn : GrowsPolynomially fun x => 1 + ε x := GrowsPolynomially.of_isEquivalent_const isEquivalent_one_add_smoothingFn_one lemma eventually_one_sub_smoothingFn_gt_const_real (c : ℝ) (hc : c < 1) : ∀ᶠ (x : ℝ) in atTop, c < 1 - ε x := by have h₁ : Tendsto (fun x => 1 - ε x) atTop (𝓝 1) := by rw [← isEquivalent_const_iff_tendsto one_ne_zero] exact isEquivalent_one_sub_smoothingFn_one rw [tendsto_order] at h₁ exact h₁.1 c hc lemma eventually_one_sub_smoothingFn_gt_const (c : ℝ) (hc : c < 1) : ∀ᶠ (n : ℕ) in atTop, c < 1 - ε n := Eventually.natCast_atTop (p := fun n => c < 1 - ε n) <| eventually_one_sub_smoothingFn_gt_const_real c hc lemma eventually_one_sub_smoothingFn_pos_real : ∀ᶠ (x : ℝ) in atTop, 0 < 1 - ε x := eventually_one_sub_smoothingFn_gt_const_real 0 zero_lt_one lemma eventually_one_sub_smoothingFn_pos : ∀ᶠ (n : ℕ) in atTop, 0 < 1 - ε n := (eventually_one_sub_smoothingFn_pos_real).natCast_atTop lemma eventually_one_sub_smoothingFn_nonneg : ∀ᶠ (n : ℕ) in atTop, 0 ≤ 1 - ε n := by filter_upwards [eventually_one_sub_smoothingFn_pos] with n hn; exact le_of_lt hn include R in lemma eventually_one_sub_smoothingFn_r_pos : ∀ᶠ (n : ℕ) in atTop, ∀ i, 0 < 1 - ε (r i n) := by rw [Filter.eventually_all] exact fun i => (R.tendsto_atTop_r_real i).eventually eventually_one_sub_smoothingFn_pos_real @[aesop safe apply] lemma differentiableAt_smoothingFn {x : ℝ} (hx : 1 < x) : DifferentiableAt ℝ ε x := by have : log x ≠ 0 := Real.log_ne_zero_of_pos_of_ne_one (by positivity) (ne_of_gt hx) show DifferentiableAt ℝ (fun z => 1 / log z) x simp_rw [one_div] exact DifferentiableAt.inv (differentiableAt_log (by positivity)) this @[aesop safe apply] lemma differentiableAt_one_sub_smoothingFn {x : ℝ} (hx : 1 < x) : DifferentiableAt ℝ (fun z => 1 - ε z) x := DifferentiableAt.sub (differentiableAt_const _) <| differentiableAt_smoothingFn hx lemma differentiableOn_one_sub_smoothingFn : DifferentiableOn ℝ (fun z => 1 - ε z) (Set.Ioi 1) := fun _ hx => (differentiableAt_one_sub_smoothingFn hx).differentiableWithinAt @[aesop safe apply] lemma differentiableAt_one_add_smoothingFn {x : ℝ} (hx : 1 < x) : DifferentiableAt ℝ (fun z => 1 + ε z) x := DifferentiableAt.add (differentiableAt_const _) <| differentiableAt_smoothingFn hx lemma differentiableOn_one_add_smoothingFn : DifferentiableOn ℝ (fun z => 1 + ε z) (Set.Ioi 1) := fun _ hx => (differentiableAt_one_add_smoothingFn hx).differentiableWithinAt lemma deriv_smoothingFn {x : ℝ} (hx : 1 < x) : deriv ε x = -x⁻¹ / (log x ^ 2) := by have : log x ≠ 0 := Real.log_ne_zero_of_pos_of_ne_one (by positivity) (ne_of_gt hx) show deriv (fun z => 1 / log z) x = -x⁻¹ / (log x ^ 2) rw [deriv_div] <;> aesop lemma isLittleO_deriv_smoothingFn : deriv ε =o[atTop] fun x => x⁻¹ := calc deriv ε =ᶠ[atTop] fun x => -x⁻¹ / (log x ^ 2) := by filter_upwards [eventually_gt_atTop 1] with x hx rw [deriv_smoothingFn hx] _ = fun x => (-x * log x ^ 2)⁻¹ := by simp_rw [neg_div, div_eq_mul_inv, ← mul_inv, neg_inv, neg_mul] _ =o[atTop] fun x => (x * 1)⁻¹ := by refine IsLittleO.inv_rev ?_ ?_ · refine IsBigO.mul_isLittleO (by rw [isBigO_neg_right]; aesop (add safe isBigO_refl)) ?_ rw [isLittleO_one_left_iff] exact Tendsto.comp tendsto_norm_atTop_atTop <| Tendsto.comp (tendsto_pow_atTop (by norm_num)) tendsto_log_atTop · exact Filter.Eventually.of_forall (fun x hx => by rw [mul_one] at hx; simp [hx]) _ = fun x => x⁻¹ := by simp lemma eventually_deriv_one_sub_smoothingFn : deriv (fun x => 1 - ε x) =ᶠ[atTop] fun x => x⁻¹ / (log x ^ 2) := calc deriv (fun x => 1 - ε x) =ᶠ[atTop] -(deriv ε) := by filter_upwards [eventually_gt_atTop 1] with x hx; rw [deriv_sub] <;> aesop _ =ᶠ[atTop] fun x => x⁻¹ / (log x ^ 2) := by filter_upwards [eventually_gt_atTop 1] with x hx simp [deriv_smoothingFn hx, neg_div] lemma eventually_deriv_one_add_smoothingFn : deriv (fun x => 1 + ε x) =ᶠ[atTop] fun x => -x⁻¹ / (log x ^ 2) := calc deriv (fun x => 1 + ε x) =ᶠ[atTop] deriv ε := by filter_upwards [eventually_gt_atTop 1] with x hx; rw [deriv_add] <;> aesop _ =ᶠ[atTop] fun x => -x⁻¹ / (log x ^ 2) := by filter_upwards [eventually_gt_atTop 1] with x hx simp [deriv_smoothingFn hx] lemma isLittleO_deriv_one_sub_smoothingFn : deriv (fun x => 1 - ε x) =o[atTop] fun (x : ℝ) => x⁻¹ := calc deriv (fun x => 1 - ε x) =ᶠ[atTop] fun z => -(deriv ε z) := by filter_upwards [eventually_gt_atTop 1] with x hx; rw [deriv_sub] <;> aesop _ =o[atTop] fun x => x⁻¹ := by rw [isLittleO_neg_left]; exact isLittleO_deriv_smoothingFn lemma isLittleO_deriv_one_add_smoothingFn : deriv (fun x => 1 + ε x) =o[atTop] fun (x : ℝ) => x⁻¹ := calc deriv (fun x => 1 + ε x) =ᶠ[atTop] fun z => deriv ε z := by filter_upwards [eventually_gt_atTop 1] with x hx; rw [deriv_add] <;> aesop _ =o[atTop] fun x => x⁻¹ := isLittleO_deriv_smoothingFn lemma eventually_one_add_smoothingFn_pos : ∀ᶠ (n : ℕ) in atTop, 0 < 1 + ε n := by have h₁ := isLittleO_smoothingFn_one rw [isLittleO_iff] at h₁ refine Eventually.natCast_atTop (p := fun n => 0 < 1 + ε n) ?_ filter_upwards [h₁ (by norm_num : (0 : ℝ) < 1/2), eventually_gt_atTop 1] with x _ hx' have : 0 < log x := Real.log_pos hx' show 0 < 1 + 1 / log x positivity include R in lemma eventually_one_add_smoothingFn_r_pos : ∀ᶠ (n : ℕ) in atTop, ∀ i, 0 < 1 + ε (r i n) := by rw [Filter.eventually_all] exact fun i => (R.tendsto_atTop_r i).eventually (f := r i) eventually_one_add_smoothingFn_pos lemma eventually_one_add_smoothingFn_nonneg : ∀ᶠ (n : ℕ) in atTop, 0 ≤ 1 + ε n := by filter_upwards [eventually_one_add_smoothingFn_pos] with n hn; exact le_of_lt hn lemma strictAntiOn_smoothingFn : StrictAntiOn ε (Set.Ioi 1) := by show StrictAntiOn (fun x => 1 / log x) (Set.Ioi 1) simp_rw [one_div] refine StrictAntiOn.comp_strictMonoOn inv_strictAntiOn ?log fun _ hx => log_pos hx refine StrictMonoOn.mono strictMonoOn_log (fun x hx => ?_) exact Set.Ioi_subset_Ioi zero_le_one hx lemma strictMonoOn_one_sub_smoothingFn : StrictMonoOn (fun (x : ℝ) => (1 : ℝ) - ε x) (Set.Ioi 1) := by simp_rw [sub_eq_add_neg] exact StrictMonoOn.const_add (StrictAntiOn.neg <| strictAntiOn_smoothingFn) 1 lemma strictAntiOn_one_add_smoothingFn : StrictAntiOn (fun (x : ℝ) => (1 : ℝ) + ε x) (Set.Ioi 1) := StrictAntiOn.const_add strictAntiOn_smoothingFn 1 section include R lemma isEquivalent_smoothingFn_sub_self (i : α) : (fun (n : ℕ) => ε (b i * n) - ε n) ~[atTop] fun n => -log (b i) / (log n)^2 := by calc (fun (n : ℕ) => 1 / log (b i * n) - 1 / log n) =ᶠ[atTop] fun (n : ℕ) => (log n - log (b i * n)) / (log (b i * n) * log n) := by filter_upwards [eventually_gt_atTop 1, R.eventually_log_b_mul_pos] with n hn hn' have h_log_pos : 0 < log n := Real.log_pos <| by aesop simp only [one_div] rw [inv_sub_inv (by have := hn' i; positivity) (by aesop)] _ =ᶠ[atTop] (fun (n : ℕ) ↦ (log n - log (b i) - log n) / ((log (b i) + log n) * log n)) := by filter_upwards [eventually_ne_atTop 0] with n hn have : 0 < b i := R.b_pos i rw [log_mul (by positivity) (by aesop), sub_add_eq_sub_sub] _ = (fun (n : ℕ) => -log (b i) / ((log (b i) + log n) * log n)) := by ext; congr; ring _ ~[atTop] (fun (n : ℕ) => -log (b i) / (log n * log n)) := by refine IsEquivalent.div (IsEquivalent.refl) <| IsEquivalent.mul ?_ (IsEquivalent.refl) have : (fun (n : ℕ) => log (b i) + log n) = fun (n : ℕ) => log n + log (b i) := by ext; simp [add_comm] rw [this] exact IsEquivalent.add_isLittleO IsEquivalent.refl <| IsLittleO.natCast_atTop (f := fun (_ : ℝ) => log (b i)) isLittleO_const_log_atTop _ = (fun (n : ℕ) => -log (b i) / (log n)^2) := by ext; congr 1; rw [← pow_two] lemma isTheta_smoothingFn_sub_self (i : α) : (fun (n : ℕ) => ε (b i * n) - ε n) =Θ[atTop] fun n => 1 / (log n)^2 := by calc (fun (n : ℕ) => ε (b i * n) - ε n) =Θ[atTop] fun n => (-log (b i)) / (log n)^2 := by exact (R.isEquivalent_smoothingFn_sub_self i).isTheta _ = fun (n : ℕ) => (-log (b i)) * 1 / (log n)^2 := by simp only [mul_one] _ = fun (n : ℕ) => -log (b i) * (1 / (log n)^2) := by simp_rw [← mul_div_assoc] _ =Θ[atTop] fun (n : ℕ) => 1 / (log n)^2 := by have : -log (b i) ≠ 0 := by rw [neg_ne_zero] exact Real.log_ne_zero_of_pos_of_ne_one (R.b_pos i) (ne_of_lt <| R.b_lt_one i) rw [← isTheta_const_mul_right this] /-! #### Akra-Bazzi exponent `p` Every Akra-Bazzi recurrence has an associated exponent, denoted by `p : ℝ`, such that `∑ a_i b_i^p = 1`. This section shows the existence and uniqueness of this exponent `p` for any `R : AkraBazziRecurrence`, and defines `R.asympBound` to be the asymptotic bound satisfied by `R`, namely `n^p (1 + ∑_{u < n} g(u) / u^(p+1))`. -/ @[continuity] lemma continuous_sumCoeffsExp : Continuous (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) := by refine continuous_finset_sum Finset.univ fun i _ => Continuous.mul (by fun_prop) ?_ exact Continuous.rpow continuous_const continuous_id (fun x => Or.inl (ne_of_gt (R.b_pos i))) lemma strictAnti_sumCoeffsExp : StrictAnti (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) := by rw [← Finset.sum_fn] refine Finset.sum_induction_nonempty _ _ (fun _ _ => StrictAnti.add) univ_nonempty ?terms refine fun i _ => StrictAnti.const_mul ?_ (R.a_pos i) exact Real.strictAnti_rpow_of_base_lt_one (R.b_pos i) (R.b_lt_one i) lemma tendsto_zero_sumCoeffsExp : Tendsto (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) atTop (𝓝 0) := by have h₁ : Finset.univ.sum (fun _ : α => (0 : ℝ)) = 0 := by simp rw [← h₁] refine tendsto_finset_sum (univ : Finset α) (fun i _ => ?_) rw [← mul_zero (a i)] refine Tendsto.mul (by simp) <| tendsto_rpow_atTop_of_base_lt_one _ ?_ (R.b_lt_one i) have := R.b_pos i linarith lemma tendsto_atTop_sumCoeffsExp : Tendsto (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) atBot atTop := by have h₁ : Tendsto (fun p : ℝ => (a (max_bi b) : ℝ) * b (max_bi b) ^ p) atBot atTop := Tendsto.const_mul_atTop (R.a_pos (max_bi b)) <| tendsto_rpow_atBot_of_base_lt_one _ (by have := R.b_pos (max_bi b); linarith) (R.b_lt_one _) refine tendsto_atTop_mono (fun p => ?_) h₁ refine Finset.single_le_sum (f := fun i => (a i : ℝ) * b i ^ p) (fun i _ => ?_) (mem_univ _) have h₁ : 0 < a i := R.a_pos i have h₂ : 0 < b i := R.b_pos i positivity lemma one_mem_range_sumCoeffsExp : 1 ∈ Set.range (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) := by refine mem_range_of_exists_le_of_exists_ge R.continuous_sumCoeffsExp ?le_one ?ge_one case le_one => exact R.tendsto_zero_sumCoeffsExp.eventually_le_const zero_lt_one |>.exists case ge_one => exact R.tendsto_atTop_sumCoeffsExp.eventually_ge_atTop _ |>.exists /-- The function x ↦ ∑ a_i b_i^x is injective. This implies the uniqueness of `p`. -/ lemma injective_sumCoeffsExp : Function.Injective (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) := R.strictAnti_sumCoeffsExp.injective end variable (a b) in /-- The exponent `p` associated with a particular Akra-Bazzi recurrence. -/ noncomputable irreducible_def p : ℝ := Function.invFun (fun (p : ℝ) => ∑ i, a i * (b i) ^ p) 1 include R in @[simp] lemma sumCoeffsExp_p_eq_one : ∑ i, a i * (b i) ^ p a b = 1 := by simp only [p] exact Function.invFun_eq (by rw [← Set.mem_range]; exact R.one_mem_range_sumCoeffsExp) /-! #### The sum transform This section defines the "sum transform" of a function `g` as `∑ u ∈ Finset.Ico n₀ n, g u / u^(p+1)`, and uses it to define `asympBound` as the bound satisfied by an Akra-Bazzi recurrence. Several properties of the sum transform are then proven. -/ /-- The transformation which turns a function `g` into `n^p * ∑ u ∈ Finset.Ico n₀ n, g u / u^(p+1)`. -/ noncomputable def sumTransform (p : ℝ) (g : ℝ → ℝ) (n₀ n : ℕ) := n^p * ∑ u ∈ Finset.Ico n₀ n, g u / u^(p + 1)
lemma sumTransform_def {p : ℝ} {g : ℝ → ℝ} {n₀ n : ℕ} : sumTransform p g n₀ n = n^p * ∑ u ∈ Finset.Ico n₀ n, g u / u^(p + 1) := rfl
Mathlib/Computability/AkraBazzi/AkraBazzi.lean
581
583
/- Copyright (c) 2021 Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Bhavik Mehta, Alena Gusakov, Yaël Dillies -/ import Mathlib.Data.Finset.Grade import Mathlib.Data.Finset.Sups import Mathlib.Logic.Function.Iterate /-! # Shadows This file defines shadows of a set family. The shadow of a set family is the set family of sets we get by removing any element from any set of the original family. If one pictures `Finset α` as a big hypercube (each dimension being membership of a given element), then taking the shadow corresponds to projecting each finset down once in all available directions. ## Main definitions * `Finset.shadow`: The shadow of a set family. Everything we can get by removing a new element from some set. * `Finset.upShadow`: The upper shadow of a set family. Everything we can get by adding an element to some set. ## Notation We define notation in locale `FinsetFamily`: * `∂ 𝒜`: Shadow of `𝒜`. * `∂⁺ 𝒜`: Upper shadow of `𝒜`. We also maintain the convention that `a, b : α` are elements of the ground type, `s, t : Finset α` are finsets, and `𝒜, ℬ : Finset (Finset α)` are finset families. ## References * https://github.com/b-mehta/maths-notes/blob/master/iii/mich/combinatorics.pdf * http://discretemath.imp.fu-berlin.de/DMII-2015-16/kruskal.pdf ## Tags shadow, set family -/ open Finset Nat variable {α : Type*} namespace Finset section Shadow variable [DecidableEq α] {𝒜 ℬ : Finset (Finset α)} {s t : Finset α} {a : α} {k r : ℕ} /-- The shadow of a set family `𝒜` is all sets we can get by removing one element from any set in `𝒜`, and the (`k` times) iterated shadow (`shadow^[k]`) is all sets we can get by removing `k` elements from any set in `𝒜`. -/ def shadow (𝒜 : Finset (Finset α)) : Finset (Finset α) := 𝒜.sup fun s => s.image (erase s) @[inherit_doc] scoped[FinsetFamily] notation:max "∂ " => Finset.shadow open FinsetFamily /-- The shadow of the empty set is empty. -/ @[simp] theorem shadow_empty : ∂ (∅ : Finset (Finset α)) = ∅ := rfl @[simp] lemma shadow_iterate_empty (k : ℕ) : ∂^[k] (∅ : Finset (Finset α)) = ∅ := by induction k <;> simp [*, shadow_empty] @[simp] theorem shadow_singleton_empty : ∂ ({∅} : Finset (Finset α)) = ∅ :=
rfl
Mathlib/Combinatorics/SetFamily/Shadow.lean
75
76
/- 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.Basic import Mathlib.Data.PNat.Prime import Mathlib.Data.Nat.Factors import Mathlib.Data.Multiset.OrderedMonoid import Mathlib.Data.Multiset.Sort /-! # 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`. -/ /-- 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, AddCommMonoid, DistribLattice, SemilatticeSup, Sub -- The `CanonicallyOrderedAdd, OrderBot, OrderedSub` instances should be constructed by a deriving -- handler. -- https://github.com/leanprover-community/mathlib4/issues/380 instance : IsOrderedCancelAddMonoid PrimeMultiset := inferInstanceAs (IsOrderedCancelAddMonoid (Multiset Nat.Primes)) instance : CanonicallyOrderedAdd PrimeMultiset := inferInstanceAs (CanonicallyOrderedAdd (Multiset Nat.Primes)) instance : OrderBot PrimeMultiset := inferInstanceAs (OrderBot (Multiset Nat.Primes)) instance : OrderedSub PrimeMultiset := inferInstanceAs (OrderedSub (Multiset Nat.Primes)) 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) theorem card_ofPrime (p : Nat.Primes) : Multiset.card (ofPrime p) = 1 := rfl /-- 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 (↑) instance coeNat : Coe PrimeMultiset (Multiset ℕ) := ⟨toNatMultiset⟩ /-- `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 (↑) @[simp] theorem coe_coeNatMonoidHom : (coeNatMonoidHom : PrimeMultiset → Multiset ℕ) = (↑) := rfl theorem coeNat_injective : Function.Injective ((↑) : PrimeMultiset → Multiset ℕ) := Multiset.map_injective Nat.Primes.coe_nat_injective theorem coeNat_ofPrime (p : Nat.Primes) : (ofPrime p : Multiset ℕ) = {(p : ℕ)} := rfl 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' /-- Converts a `PrimeMultiset` to a `Multiset ℕ+`. -/ def toPNatMultiset : PrimeMultiset → Multiset ℕ+ := fun v => v.map (↑) instance coePNat : Coe PrimeMultiset (Multiset ℕ+) := ⟨toPNatMultiset⟩ /-- `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 (↑) @[simp] theorem coe_coePNatMonoidHom : (coePNatMonoidHom : PrimeMultiset → Multiset ℕ+) = (↑) := rfl theorem coePNat_injective : Function.Injective ((↑) : PrimeMultiset → Multiset ℕ+) := Multiset.map_injective Nat.Primes.coe_pnat_injective theorem coePNat_ofPrime (p : Nat.Primes) : (ofPrime p : Multiset ℕ+) = {(p : ℕ+)} := rfl 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' instance coeMultisetPNatNat : Coe (Multiset ℕ+) (Multiset ℕ) := ⟨fun v => v.map (↑)⟩ theorem coePNat_nat (v : PrimeMultiset) : ((v : Multiset ℕ+) : Multiset ℕ) = (v : Multiset ℕ) := by change (v.map ((↑) : Nat.Primes → ℕ+)).map Subtype.val = v.map Subtype.val rw [Multiset.map_map] congr /-- The product of a `PrimeMultiset`, as a `ℕ+`. -/ def prod (v : PrimeMultiset) : ℕ+ := (v : Multiset PNat).prod theorem coe_prod (v : PrimeMultiset) : (v.prod : ℕ) = (v : Multiset ℕ).prod := by have h : (v.prod : ℕ) = ((v.map (↑) : Multiset ℕ+).map (↑)).prod := PNat.coeMonoidHom.map_multiset_prod v.toPNatMultiset simpa [Multiset.map_map] using h theorem prod_ofPrime (p : Nat.Primes) : (ofPrime p).prod = (p : ℕ+) := Multiset.prod_singleton _ /-- 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 theorem to_ofNatMultiset (v : Multiset ℕ) (h) : (ofNatMultiset v h : Multiset ℕ) = v := by dsimp [ofNatMultiset, toNatMultiset] rw [Multiset.map_pmap, Multiset.pmap_eq_map, Multiset.map_id'] theorem prod_ofNatMultiset (v : Multiset ℕ) (h) : ((ofNatMultiset v h).prod : ℕ) = (v.prod : ℕ) := by rw [coe_prod, to_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 theorem to_ofPNatMultiset (v : Multiset ℕ+) (h) : (ofPNatMultiset v h : Multiset ℕ+) = v := by dsimp [ofPNatMultiset, toPNatMultiset] have : (fun (p : ℕ+) (h : p.Prime) => ((↑) : 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] theorem prod_ofPNatMultiset (v : Multiset ℕ+) (h) : ((ofPNatMultiset v h).prod : ℕ+) = v.prod := by dsimp [prod] rw [to_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 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 /-- If a `List ℕ+` consists only of primes, it can be recast as a `PrimeMultiset` with the coercion from lists to multisets. -/ def ofPNatList (l : List ℕ+) (h : ∀ p : ℕ+, p ∈ l → p.Prime) : PrimeMultiset := ofPNatMultiset (l : Multiset ℕ+) h theorem prod_ofPNatList (l : List ℕ+) (h) : (ofPNatList l h).prod = l.prod := by have := prod_ofPNatMultiset (l : Multiset ℕ+) h rw [Multiset.prod_coe] at this exact this /-- The product map gives a homomorphism from the additive monoid of multisets to the multiplicative monoid ℕ+. -/ theorem prod_zero : (0 : PrimeMultiset).prod = 1 := by exact Multiset.prod_zero theorem prod_add (u v : PrimeMultiset) : (u + v).prod = u.prod * v.prod := by change (coePNatMonoidHom (u + v)).prod = _ rw [coePNatMonoidHom.map_add] exact Multiset.prod_add _ _ theorem prod_smul (d : ℕ) (u : PrimeMultiset) : (d • u).prod = u.prod ^ d := by induction d with | zero => simp only [zero_nsmul, pow_zero, prod_zero] | succ n ih => rw [succ_nsmul, prod_add, ih, pow_succ] end PrimeMultiset namespace PNat /-- The prime factors of n, regarded as a multiset -/ def factorMultiset (n : ℕ+) : PrimeMultiset := PrimeMultiset.ofNatList (Nat.primeFactorsList n) (@Nat.prime_of_mem_primeFactorsList n) /-- The product of the factors is the original number -/ theorem prod_factorMultiset (n : ℕ+) : (factorMultiset n).prod = n := eq <| by dsimp [factorMultiset] rw [PrimeMultiset.prod_ofNatList] exact Nat.prod_primeFactorsList n.ne_zero theorem coeNat_factorMultiset (n : ℕ+) : (factorMultiset n : Multiset ℕ) = (Nat.primeFactorsList n : Multiset ℕ) := PrimeMultiset.to_ofNatMultiset (Nat.primeFactorsList n) (@Nat.prime_of_mem_primeFactorsList n) end PNat namespace PrimeMultiset /-- If we start with a multiset of primes, take the product and then factor it, we get back the original multiset. -/ theorem factorMultiset_prod (v : PrimeMultiset) : v.prod.factorMultiset = v := by apply PrimeMultiset.coeNat_injective rw [v.prod.coeNat_factorMultiset, PrimeMultiset.coe_prod] rcases v with ⟨l⟩ dsimp [PrimeMultiset.toNatMultiset] let l' := l.map ((↑) : Nat.Primes → ℕ) have (p : ℕ) (hp : p ∈ l') : p.Prime := by simp only [List.map_subtype, List.map_id_fun', id_eq, List.mem_unattach, l'] at hp obtain ⟨hp', -⟩ := hp exact hp' exact Multiset.coe_eq_coe.mpr (@Nat.primeFactorsList_unique _ l' rfl this).symm end PrimeMultiset namespace PNat /-- Positive integers biject with multisets of primes. -/ def factorMultisetEquiv : ℕ+ ≃ PrimeMultiset where toFun := factorMultiset invFun := PrimeMultiset.prod left_inv := prod_factorMultiset right_inv := PrimeMultiset.factorMultiset_prod /-- Factoring gives a homomorphism from the multiplicative monoid ℕ+ to the additive monoid of multisets. -/ theorem factorMultiset_one : factorMultiset 1 = 0 := by simp [factorMultiset, PrimeMultiset.ofNatList, PrimeMultiset.ofNatMultiset] theorem factorMultiset_mul (n m : ℕ+) : factorMultiset (n * m) = factorMultiset n + factorMultiset m := by let u := factorMultiset n let v := factorMultiset m have : n = u.prod := (prod_factorMultiset n).symm; rw [this] have : m = v.prod := (prod_factorMultiset m).symm; rw [this] rw [← PrimeMultiset.prod_add] repeat' rw [PrimeMultiset.factorMultiset_prod] theorem factorMultiset_pow (n : ℕ+) (m : ℕ) : factorMultiset (n ^ m) = m • factorMultiset n := by let u := factorMultiset n have : n = u.prod := (prod_factorMultiset n).symm rw [this, ← PrimeMultiset.prod_smul] repeat' rw [PrimeMultiset.factorMultiset_prod] /-- Factoring a prime gives the corresponding one-element multiset. -/ theorem factorMultiset_ofPrime (p : Nat.Primes) : (p : ℕ+).factorMultiset = PrimeMultiset.ofPrime p := by apply factorMultisetEquiv.symm.injective change (p : ℕ+).factorMultiset.prod = (PrimeMultiset.ofPrime p).prod rw [(p : ℕ+).prod_factorMultiset, PrimeMultiset.prod_ofPrime] /-- We now have four different results that all encode the idea that inequality of multisets corresponds to divisibility of positive integers. -/ theorem factorMultiset_le_iff {m n : ℕ+} : factorMultiset m ≤ factorMultiset n ↔ m ∣ n := by constructor · intro h rw [← prod_factorMultiset m, ← prod_factorMultiset m] apply Dvd.intro (n.factorMultiset - m.factorMultiset).prod rw [← PrimeMultiset.prod_add, PrimeMultiset.factorMultiset_prod, add_tsub_cancel_of_le h, prod_factorMultiset] · intro h rw [← mul_div_exact h, factorMultiset_mul] exact le_self_add theorem factorMultiset_le_iff' {m : ℕ+} {v : PrimeMultiset} : factorMultiset m ≤ v ↔ m ∣ v.prod := by let h := @factorMultiset_le_iff m v.prod rw [v.factorMultiset_prod] at h exact h end PNat namespace PrimeMultiset theorem prod_dvd_iff {u v : PrimeMultiset} : u.prod ∣ v.prod ↔ u ≤ v := by let h := @PNat.factorMultiset_le_iff' u.prod v rw [u.factorMultiset_prod] at h exact h.symm theorem prod_dvd_iff' {u : PrimeMultiset} {n : ℕ+} : u.prod ∣ n ↔ u ≤ n.factorMultiset := by let h := @prod_dvd_iff u n.factorMultiset rw [n.prod_factorMultiset] at h exact h end PrimeMultiset namespace PNat /-- The gcd and lcm operations on positive integers correspond to the inf and sup operations on multisets. -/ theorem factorMultiset_gcd (m n : ℕ+) : factorMultiset (gcd m n) = factorMultiset m ⊓ factorMultiset n := by apply le_antisymm · apply le_inf_iff.mpr; constructor <;> apply factorMultiset_le_iff.mpr · exact gcd_dvd_left m n · exact gcd_dvd_right m n · rw [← PrimeMultiset.prod_dvd_iff, prod_factorMultiset] apply dvd_gcd <;> rw [PrimeMultiset.prod_dvd_iff'] · exact inf_le_left · exact inf_le_right theorem factorMultiset_lcm (m n : ℕ+) : factorMultiset (lcm m n) = factorMultiset m ⊔ factorMultiset n := by apply le_antisymm · rw [← PrimeMultiset.prod_dvd_iff, prod_factorMultiset] apply lcm_dvd <;> rw [← factorMultiset_le_iff'] · exact le_sup_left · exact le_sup_right · apply sup_le_iff.mpr; constructor <;> apply factorMultiset_le_iff.mpr · exact dvd_lcm_left m n · exact dvd_lcm_right m n /-- The number of occurrences of p in the factor multiset of m is the same as the p-adic valuation of m. -/ theorem count_factorMultiset (m : ℕ+) (p : Nat.Primes) (k : ℕ) : (p : ℕ+) ^ k ∣ m ↔ k ≤ m.factorMultiset.count p := by rw [Multiset.le_count_iff_replicate_le, ← factorMultiset_le_iff, factorMultiset_pow, factorMultiset_ofPrime] congr! 2 apply Multiset.eq_replicate.mpr constructor · rw [Multiset.card_nsmul, PrimeMultiset.card_ofPrime, mul_one] · intro q h rw [PrimeMultiset.ofPrime, Multiset.nsmul_singleton _ k] at h exact Multiset.eq_of_mem_replicate h end PNat namespace PrimeMultiset theorem prod_inf (u v : PrimeMultiset) : (u ⊓ v).prod = PNat.gcd u.prod v.prod := by let n := u.prod let m := v.prod change (u ⊓ v).prod = PNat.gcd n m have : u = n.factorMultiset := u.factorMultiset_prod.symm; rw [this] have : v = m.factorMultiset := v.factorMultiset_prod.symm; rw [this] rw [← PNat.factorMultiset_gcd n m, PNat.prod_factorMultiset] theorem prod_sup (u v : PrimeMultiset) : (u ⊔ v).prod = PNat.lcm u.prod v.prod := by let n := u.prod let m := v.prod change (u ⊔ v).prod = PNat.lcm n m have : u = n.factorMultiset := u.factorMultiset_prod.symm; rw [this] have : v = m.factorMultiset := v.factorMultiset_prod.symm; rw [this] rw [← PNat.factorMultiset_lcm n m, PNat.prod_factorMultiset] end PrimeMultiset
Mathlib/Data/PNat/Factors.lean
405
411
/- 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.CategoryTheory.Limits.Shapes.NormalMono.Basic import Mathlib.CategoryTheory.Limits.Shapes.FiniteProducts /-! # Normal mono categories with finite products and kernels have all equalizers. This, and the dual result, are used in the development of abelian categories. -/ noncomputable section open CategoryTheory open CategoryTheory.Limits variable {C : Type*} [Category C] [HasZeroMorphisms C] namespace CategoryTheory.NormalMonoCategory variable [HasFiniteProducts C] [HasKernels C] [IsNormalMonoCategory C] /-- The pullback of two monomorphisms exists. -/ @[irreducible, nolint defLemma] -- Porting note: changed to irreducible and a def def pullback_of_mono {X Y Z : C} (a : X ⟶ Z) (b : Y ⟶ Z) [Mono a] [Mono b] : HasLimit (cospan a b) := let ⟨P, f, haf, i⟩ := normalMonoOfMono a let ⟨Q, g, hbg, i'⟩ := normalMonoOfMono b let ⟨a', ha'⟩ := KernelFork.IsLimit.lift' i (kernel.ι (prod.lift f g)) <| calc kernel.ι (prod.lift f g) ≫ f _ = kernel.ι (prod.lift f g) ≫ prod.lift f g ≫ Limits.prod.fst := by rw [prod.lift_fst] _ = (0 : kernel (prod.lift f g) ⟶ P ⨯ Q) ≫ Limits.prod.fst := by rw [kernel.condition_assoc] _ = 0 := zero_comp let ⟨b', hb'⟩ := KernelFork.IsLimit.lift' i' (kernel.ι (prod.lift f g)) <| calc kernel.ι (prod.lift f g) ≫ g _ = kernel.ι (prod.lift f g) ≫ prod.lift f g ≫ Limits.prod.snd := by rw [prod.lift_snd] _ = (0 : kernel (prod.lift f g) ⟶ P ⨯ Q) ≫ Limits.prod.snd := by rw [kernel.condition_assoc] _ = 0 := zero_comp HasLimit.mk { cone := PullbackCone.mk a' b' <| by simp? at ha' hb' says simp only [parallelPair_obj_zero, Fork.ofι_pt, Fork.ι_ofι] at ha' hb' rw [ha', hb'] isLimit := PullbackCone.IsLimit.mk _ (fun s => kernel.lift (prod.lift f g) (PullbackCone.snd s ≫ b) <| Limits.prod.hom_ext (calc ((PullbackCone.snd s ≫ b) ≫ prod.lift f g) ≫ Limits.prod.fst = PullbackCone.snd s ≫ b ≫ f := by simp only [prod.lift_fst, Category.assoc] _ = PullbackCone.fst s ≫ a ≫ f := by rw [PullbackCone.condition_assoc] _ = PullbackCone.fst s ≫ 0 := by rw [haf] _ = 0 ≫ Limits.prod.fst := by rw [comp_zero, zero_comp] ) (calc ((PullbackCone.snd s ≫ b) ≫ prod.lift f g) ≫ Limits.prod.snd = PullbackCone.snd s ≫ b ≫ g := by simp only [prod.lift_snd, Category.assoc] _ = PullbackCone.snd s ≫ 0 := by rw [hbg] _ = 0 ≫ Limits.prod.snd := by rw [comp_zero, zero_comp] )) (fun s => (cancel_mono a).1 <| by rw [KernelFork.ι_ofι] at ha' simp [ha', PullbackCone.condition s]) (fun s => (cancel_mono b).1 <| by rw [KernelFork.ι_ofι] at hb' simp [hb']) fun s m h₁ _ => (cancel_mono (kernel.ι (prod.lift f g))).1 <| calc m ≫ kernel.ι (prod.lift f g) = m ≫ a' ≫ a := by congr exact ha'.symm _ = PullbackCone.fst s ≫ a := by rw [← Category.assoc, h₁] _ = PullbackCone.snd s ≫ b := PullbackCone.condition s _ = kernel.lift (prod.lift f g) (PullbackCone.snd s ≫ b) _ ≫ kernel.ι (prod.lift f g) := by rw [kernel.lift_ι] } section attribute [local instance] pullback_of_mono /-- The pullback of `(𝟙 X, f)` and `(𝟙 X, g)` -/ private abbrev P {X Y : C} (f g : X ⟶ Y) [Mono (prod.lift (𝟙 X) f)] [Mono (prod.lift (𝟙 X) g)] : C := pullback (prod.lift (𝟙 X) f) (prod.lift (𝟙 X) g) /-- The equalizer of `f` and `g` exists. -/ -- Porting note: changed to irreducible def since irreducible_def was breaking things @[irreducible, nolint defLemma] def hasLimit_parallelPair {X Y : C} (f g : X ⟶ Y) : HasLimit (parallelPair f g) := have huv : (pullback.fst _ _ : P f g ⟶ X) = pullback.snd _ _ := calc (pullback.fst _ _ : P f g ⟶ X) = pullback.fst _ _ ≫ 𝟙 _ := Eq.symm <| Category.comp_id _ _ = pullback.fst _ _ ≫ prod.lift (𝟙 X) f ≫ Limits.prod.fst := by rw [prod.lift_fst] _ = pullback.snd _ _ ≫ prod.lift (𝟙 X) g ≫ Limits.prod.fst := by rw [pullback.condition_assoc] _ = pullback.snd _ _ := by rw [prod.lift_fst, Category.comp_id] have hvu : (pullback.fst _ _ : P f g ⟶ X) ≫ f = pullback.snd _ _ ≫ g := calc (pullback.fst _ _ : P f g ⟶ X) ≫ f = pullback.fst _ _ ≫ prod.lift (𝟙 X) f ≫ Limits.prod.snd := by rw [prod.lift_snd] _ = pullback.snd _ _ ≫ prod.lift (𝟙 X) g ≫ Limits.prod.snd := by rw [pullback.condition_assoc] _ = pullback.snd _ _ ≫ g := by rw [prod.lift_snd] have huu : (pullback.fst _ _ : P f g ⟶ X) ≫ f = pullback.fst _ _ ≫ g := by rw [hvu, ← huv] HasLimit.mk { cone := Fork.ofι (pullback.fst _ _) huu isLimit := Fork.IsLimit.mk _ (fun s => pullback.lift (Fork.ι s) (Fork.ι s) <| Limits.prod.hom_ext (by simp only [prod.lift_fst, Category.assoc]) (by simp only [prod.comp_lift, Fork.condition s])) (fun s => by simp) fun s m h => pullback.hom_ext (by simpa only [pullback.lift_fst] using h) (by simpa only [huv.symm, pullback.lift_fst] using h) } end section attribute [local instance] hasLimit_parallelPair /-- A `NormalMonoCategory` category with finite products and kernels has all equalizers. -/ instance (priority := 100) hasEqualizers : HasEqualizers C := hasEqualizers_of_hasLimit_parallelPair _ end /-- If a zero morphism is a cokernel of `f`, then `f` is an epimorphism. -/ theorem epi_of_zero_cokernel {X Y : C} (f : X ⟶ Y) (Z : C) (l : IsColimit (CokernelCofork.ofπ (0 : Y ⟶ Z) (show f ≫ 0 = 0 by simp))) : Epi f := ⟨fun u v huv => by obtain ⟨W, w, hw, hl⟩ := normalMonoOfMono (equalizer.ι u v) obtain ⟨m, hm⟩ := equalizer.lift' f huv
have hwf : f ≫ w = 0 := by rw [← hm, Category.assoc, hw, comp_zero] obtain ⟨n, hn⟩ := CokernelCofork.IsColimit.desc' l _ hwf rw [Cofork.π_ofπ, zero_comp] at hn have : IsIso (equalizer.ι u v) := by apply isIso_limit_cone_parallelPair_of_eq hn.symm hl apply (cancel_epi (equalizer.ι u v)).1 exact equalizer.condition _ _⟩ section variable [HasZeroObject C]
Mathlib/CategoryTheory/Limits/Shapes/NormalMono/Equalizers.lean
152
162
/- 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.Nat import Mathlib.Algebra.Ring.Int.Defs import Mathlib.Data.Nat.Bitwise import Mathlib.Data.Nat.Cast.Order.Basic import Mathlib.Data.Nat.PSub import Mathlib.Data.Nat.Size import Mathlib.Data.Num.Bitwise /-! # Properties of the binary representation of integers -/ open Int 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 @[simp] theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 := rfl @[simp, norm_cast] theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = (n : α) + n := rfl @[simp, norm_cast] theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = ((n : α) + n) + 1 := rfl @[simp, norm_cast] theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n | 1 => Nat.cast_one | bit0 p => by dsimp; rw [Nat.cast_add, p.cast_to_nat] | bit1 p => by dsimp; rw [Nat.cast_add, Nat.cast_add, Nat.cast_one, p.cast_to_nat] @[norm_cast] theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n := cast_to_nat _ @[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] theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1 | 1 => rfl | bit0 _ => rfl | bit1 p => (congr_arg (fun n ↦ n + n) (succ_to_nat p)).trans <| show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm] theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl @[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 (fun n ↦ n + n) (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _ | bit0 a, bit1 b => (congr_arg (fun n ↦ (n + n) + 1) (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 (fun n ↦ (n + n) + 1) (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] 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 _, bit0 _ => rfl | bit0 a, bit1 b => congr_arg bit0 (add_succ a b) | bit1 _, bit0 _ => rfl | bit1 a, bit1 b => congr_arg bit1 (add_succ a b) theorem bit0_of_bit0 : ∀ n, n + n = bit0 n | 1 => rfl | bit0 p => congr_arg bit0 (bit0_of_bit0 p) | bit1 p => show bit0 (succ (p + p)) = _ by rw [bit0_of_bit0 p, succ] theorem bit1_of_bit1 (n : PosNum) : (n + n) + 1 = bit1 n := show (n + n) + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ] @[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] 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 _ 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 theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by induction' m with m IH m IH <;> intro n <;> obtain - | n | n := n <;> unfold cmp <;> try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl 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) @[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] @[norm_cast] theorem le_to_nat {m n : PosNum} : (m : ℕ) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr lt_to_nat end PosNum namespace Num variable {α : Type*} open PosNum theorem add_zero (n : Num) : n + 0 = n := by cases n <;> rfl theorem zero_add (n : Num) : 0 + n = n := by cases n <;> rfl theorem add_one : ∀ n : Num, n + 1 = succ n | 0 => rfl | pos p => by cases p <;> rfl 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 _, pos _ => congr_arg pos (PosNum.add_succ _ _) theorem bit0_of_bit0 : ∀ n : Num, n + n = n.bit0 | 0 => rfl | pos p => congr_arg pos p.bit0_of_bit0 theorem bit1_of_bit1 : ∀ n : Num, (n + n) + 1 = n.bit1 | 0 => rfl | pos p => congr_arg pos p.bit1_of_bit1 @[simp] theorem ofNat'_zero : Num.ofNat' 0 = 0 := by simp [Num.ofNat'] theorem ofNat'_bit (b n) : ofNat' (Nat.bit b n) = cond b Num.bit1 Num.bit0 (ofNat' n) := Nat.binaryRec_eq _ _ (.inl rfl) @[simp] theorem ofNat'_one : Num.ofNat' 1 = 1 := by erw [ofNat'_bit true 0, cond, ofNat'_zero]; rfl theorem bit1_succ : ∀ n : Num, n.bit1.succ = n.succ.bit0 | 0 => rfl | pos _n => rfl 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] · rw [show n.bit true + 1 = (n + 1).bit false by simp [Nat.bit, mul_add], ofNat'_bit, ofNat'_bit, ih] simp only [cond, add_one, bit1_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, *] @[simp, norm_cast] theorem cast_zero [Zero α] [One α] [Add α] : ((0 : Num) : α) = 0 := rfl @[simp] theorem cast_zero' [Zero α] [One α] [Add α] : (Num.zero : α) = 0 := rfl @[simp, norm_cast] theorem cast_one [Zero α] [One α] [Add α] : ((1 : Num) : α) = 1 := rfl @[simp] theorem cast_pos [Zero α] [One α] [Add α] (n : PosNum) : (Num.pos n : α) = n := rfl theorem succ'_to_nat : ∀ n, (succ' n : ℕ) = n + 1 | 0 => (Nat.zero_add _).symm | pos _p => PosNum.succ_to_nat _ theorem succ_to_nat (n) : (succ n : ℕ) = n + 1 := succ'_to_nat n @[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 @[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 _ _ @[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 _ _ 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 _ => to_nat_pos _ | pos _, 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] @[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] @[norm_cast] theorem le_to_nat {m n : Num} : (m : ℕ) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr lt_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 simpa only [Nat.bit_false, cond_false, two_mul, of_to_nat' p] using Num.ofNat'_bit false p | bit1 p => by simpa only [Nat.bit_true, cond_true, two_mul, of_to_nat' p] using Num.ofNat'_bit true p 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' lemma toNat_injective : Function.Injective (castNum : Num → ℕ) := Function.LeftInverse.injective of_to_nat' @[norm_cast] theorem to_nat_inj {m n : Num} : (m : ℕ) = n ↔ m = n := toNat_injective.eq_iff /-- 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 instance addMonoidWithOne : AddMonoidWithOne Num := { Num.addMonoid with natCast := Num.ofNat' one := 1 natCast_zero := ofNat'_zero natCast_succ := fun _ => ofNat'_succ } 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] instance partialOrder : PartialOrder Num where 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 instance isOrderedCancelAddMonoid : IsOrderedCancelAddMonoid Num where 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 := show a + b ≤ a + c → b ≤ c by transfer_rw; apply le_of_add_le_add_left instance linearOrder : LinearOrder Num := { le_total := by intro a b transfer_rw apply le_total toDecidableLT := Num.decidableLT toDecidableLE := Num.decidableLE -- This is relying on an automatically generated instance name, -- generated in a `deriving` handler. -- See https://github.com/leanprover/lean4/issues/2343 toDecidableEq := instDecidableEqNum } instance isStrictOrderedRing : IsStrictOrderedRing Num := { 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 exists_pair_ne := ⟨0, 1, by decide⟩ } @[norm_cast] theorem add_of_nat (m n) : ((m + n : ℕ) : Num) = m + n := add_ofNat' _ _ @[norm_cast] theorem to_nat_to_int (n : Num) : ((n : ℕ) : ℤ) = n := cast_to_nat _ @[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] 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] @[simp, norm_cast] theorem of_natCast {α} [AddMonoidWithOne α] (n : ℕ) : ((n : Num) : α) = n := by rw [← cast_to_nat, to_of_nat] @[norm_cast] theorem of_nat_inj {m n : ℕ} : (m : Num) = n ↔ m = n := ⟨fun h => Function.LeftInverse.injective to_of_nat h, congr_arg _⟩ -- 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' @[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]⟩⟩ end Num namespace PosNum variable {α : Type*} open Num -- 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' @[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 _⟩ 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 (n + 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 _ => rfl @[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] @[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 _)] instance dvd : Dvd PosNum := ⟨fun m n => pos m ∣ pos n⟩ @[norm_cast] theorem dvd_to_nat {m n : PosNum} : (m : ℕ) ∣ n ↔ m ∣ n := Num.dvd_to_nat (pos m) (pos n) 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, ← two_mul] erw [@Nat.size_bit false n] have := to_nat_pos n dsimp [Nat.bit]; omega | bit1 n => by rw [size, succ_to_nat, size_to_nat n, cast_bit1, ← two_mul] erw [@Nat.size_bit true n] dsimp [Nat.bit]; omega 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] theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat] theorem natSize_pos (n) : 0 < natSize n := by cases n <;> apply Nat.succ_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 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 instance distrib : Distrib PosNum where add := (· + ·) mul := (· * ·) left_distrib := by transfer; simp [mul_add] right_distrib := by transfer; simp [mul_add, mul_comm] 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 toDecidableLT := by infer_instance toDecidableLE := by infer_instance toDecidableEq := by infer_instance @[simp] theorem cast_to_num (n : PosNum) : ↑n = Num.pos n := by rw [← cast_to_nat, ← of_to_nat n] @[simp, norm_cast] theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> simp [bit, two_mul] @[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] @[simp 500, norm_cast] theorem cast_succ [AddMonoidWithOne α] (n : PosNum) : (succ n : α) = n + 1 := by rw [← add_one, cast_add, cast_one] @[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] @[simp] theorem one_le_cast [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] (n : PosNum) : (1 : α) ≤ n := by rw [← cast_to_nat, ← Nat.cast_one, Nat.cast_le (α := α)]; apply to_nat_pos @[simp] theorem cast_pos [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] (n : PosNum) : 0 < (n : α) := lt_of_lt_of_le zero_lt_one (one_le_cast n) @[simp, norm_cast] theorem cast_mul [NonAssocSemiring 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] @[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] @[simp, norm_cast] theorem cast_lt [Semiring α] [PartialOrder α] [IsStrictOrderedRing 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] @[simp, norm_cast] theorem cast_le [Semiring α] [LinearOrder α] [IsStrictOrderedRing α] {m n : PosNum} : (m : α) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr cast_lt 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 <;> simp [bit, two_mul] <;> rfl 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] theorem cast_succ [AddMonoidWithOne α] (n) : (succ n : α) = n + 1 := cast_succ' n @[simp, norm_cast] theorem cast_add [AddMonoidWithOne 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] @[simp, norm_cast] theorem cast_bit0 [NonAssocSemiring α] (n : Num) : (n.bit0 : α) = 2 * (n : α) := by rw [← bit0_of_bit0, two_mul, cast_add] @[simp, norm_cast] theorem cast_bit1 [NonAssocSemiring α] (n : Num) : (n.bit1 : α) = 2 * (n : α) + 1 := by rw [← bit1_of_bit1, bit0_of_bit0, cast_add, cast_bit0]; rfl @[simp, norm_cast] theorem cast_mul [NonAssocSemiring 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 _ _ theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n | 0 => Nat.size_zero.symm | pos p => p.size_to_nat theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n | 0 => rfl | pos p => p.size_eq_natSize theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat] @[simp 999] theorem ofNat'_eq : ∀ n, Num.ofNat' n = n := Nat.binaryRec (by simp) fun b n IH => by tauto theorem zneg_toZNum (n : Num) : -n.toZNum = n.toZNumNeg := by cases n <;> rfl theorem zneg_toZNumNeg (n : Num) : -n.toZNumNeg = n.toZNum := by cases n <;> rfl theorem toZNum_inj {m n : Num} : m.toZNum = n.toZNum ↔ m = n := ⟨fun h => by cases m <;> cases n <;> cases h <;> rfl, congr_arg _⟩ @[simp] theorem cast_toZNum [Zero α] [One α] [Add α] [Neg α] : ∀ n : Num, (n.toZNum : α) = n | 0 => rfl | Num.pos _p => rfl @[simp] theorem cast_toZNumNeg [SubtractionMonoid α] [One α] : ∀ n : Num, (n.toZNumNeg : α) = -n | 0 => neg_zero.symm | Num.pos _p => rfl @[simp] theorem add_toZNum (m n : Num) : Num.toZNum (m + n) = m.toZNum + n.toZNum := by cases m <;> cases n <;> rfl 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 theorem sub'_one (a : PosNum) : sub' a 1 = (pred' a).toZNum := by cases a <;> rfl theorem one_sub' (a : PosNum) : sub' 1 a = (pred' a).toZNumNeg := by cases a <;> rfl theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt := Iff.rfl 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 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 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 theorem cmp_swap (m n) : (cmp m n).swap = cmp n m := by cases m <;> cases n <;> try { rfl }; apply PosNum.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] @[simp, norm_cast] theorem cast_lt [Semiring α] [PartialOrder α] [IsStrictOrderedRing 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] @[simp, norm_cast] theorem cast_le [Semiring α] [LinearOrder α] [IsStrictOrderedRing α] {m n : Num} : (m : α) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr cast_lt @[simp, norm_cast] theorem cast_inj [Semiring α] [PartialOrder α] [IsStrictOrderedRing 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] theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt := Iff.rfl 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 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 obtain - | m := m <;> obtain - | n := 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 this b (n : PosNum) : (cond b (↑n) 0 : ℕ) = ↑(cond b (pos n) 0 : Num) := by cases b <;> rfl have this' b (n : PosNum) : ↑ (pos (PosNum.bit b n)) = Nat.bit b ↑n := by cases b <;> simp induction' m with m IH m IH generalizing n <;> obtain - | n | 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 [this'] 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] @[simp, norm_cast] theorem castNum_or : ∀ m n : Num, ↑(m ||| n) = (↑m ||| ↑n : ℕ) := by apply castNum_eq_bitwise fun x y => pos (PosNum.lor x y) <;> (try rintro (_ | _)) <;> (try rintro (_ | _)) <;> intros <;> rfl @[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 @[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 @[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 @[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, pow_succ, ← mul_assoc, mul_comm, -shiftl_eq_shiftLeft, -PosNum.shiftl_eq_shiftLeft, shiftl, mul_two] @[simp, norm_cast] theorem castNum_shiftRight (m : Num) (n : Nat) : ↑(m >>> n) = (m : ℕ) >>> (n : ℕ) := by obtain - | m := m <;> dsimp only [← shiftr_eq_shiftRight, shiftr] · symm apply Nat.zero_shiftRight induction' n with n IH generalizing m · cases m <;> rfl have hdiv2 : ∀ m, Nat.div2 (m + m) = m := by intro; rw [Nat.div2_val]; omega obtain - | m | 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 (m + m + 1) (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 [-add_assoc, Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val, hdiv2] · trans · apply IH change Nat.shiftRight m n = Nat.shiftRight (m + 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 [-add_assoc, Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val, hdiv2] @[simp] theorem castNum_testBit (m n) : testBit m n = Nat.testBit m n := by 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 <;> obtain - | m | m := m <;> simp only [PosNum.testBit] · rfl · rw [PosNum.cast_bit1, ← two_mul, ← congr_fun Nat.bit_true, Nat.testBit_bit_zero] · rw [PosNum.cast_bit0, ← two_mul, ← congr_fun Nat.bit_false, Nat.testBit_bit_zero] · simp [Nat.testBit_add_one] · rw [PosNum.cast_bit1, ← two_mul, ← congr_fun Nat.bit_true, Nat.testBit_bit_succ, IH] · rw [PosNum.cast_bit0, ← two_mul, ← congr_fun Nat.bit_false, Nat.testBit_bit_succ, IH] end Num namespace Int /-- Cast a `SNum` to the corresponding integer. -/ def ofSnum : SNum → ℤ := SNum.rec' (fun a => cond a (-1) 0) fun a _p IH => cond a (2 * IH + 1) (2 * IH) instance snumCoe : Coe SNum ℤ := ⟨ofSnum⟩ end Int instance SNum.lt : LT SNum := ⟨fun a b => (a : ℤ) < b⟩ instance SNum.le : LE SNum := ⟨fun a b => (a : ℤ) ≤ b⟩
Mathlib/Data/Num/Lemmas.lean
1,143
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/- Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn -/ import Mathlib.Data.Set.Prod import Mathlib.Logic.Equiv.Fin.Basic import Mathlib.ModelTheory.LanguageMap import Mathlib.Algebra.Order.Group.Nat /-! # Basics on First-Order Syntax This file defines first-order terms, formulas, sentences, and theories in a style inspired by the [Flypitch project](https://flypitch.github.io/). ## Main Definitions - A `FirstOrder.Language.Term` is defined so that `L.Term α` is the type of `L`-terms with free variables indexed by `α`. - A `FirstOrder.Language.Formula` is defined so that `L.Formula α` is the type of `L`-formulas with free variables indexed by `α`. - A `FirstOrder.Language.Sentence` is a formula with no free variables. - A `FirstOrder.Language.Theory` is a set of sentences. - The variables of terms and formulas can be relabelled with `FirstOrder.Language.Term.relabel`, `FirstOrder.Language.BoundedFormula.relabel`, and `FirstOrder.Language.Formula.relabel`. - Given an operation on terms and an operation on relations, `FirstOrder.Language.BoundedFormula.mapTermRel` gives an operation on formulas. - `FirstOrder.Language.BoundedFormula.castLE` adds more `Fin`-indexed variables. - `FirstOrder.Language.BoundedFormula.liftAt` raises the indexes of the `Fin`-indexed variables above a particular index. - `FirstOrder.Language.Term.subst` and `FirstOrder.Language.BoundedFormula.subst` substitute variables with given terms. - Language maps can act on syntactic objects with functions such as `FirstOrder.Language.LHom.onFormula`. - `FirstOrder.Language.Term.constantsVarsEquiv` and `FirstOrder.Language.BoundedFormula.constantsVarsEquiv` switch terms and formulas between having constants in the language and having extra variables indexed by the same type. ## Implementation Notes - Formulas use a modified version of de Bruijn variables. Specifically, a `L.BoundedFormula α n` is a formula with some variables indexed by a type `α`, which cannot be quantified over, and some indexed by `Fin n`, which can. For any `φ : L.BoundedFormula α (n + 1)`, we define the formula `∀' φ : L.BoundedFormula α n` by universally quantifying over the variable indexed by `n : Fin (n + 1)`. ## References For the Flypitch project: - [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*] [flypitch_cpp] - [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of the continuum hypothesis*][flypitch_itp] -/ universe u v w u' v' namespace FirstOrder namespace Language variable (L : Language.{u, v}) {L' : Language} variable {M : Type w} {α : Type u'} {β : Type v'} {γ : Type*} open FirstOrder open Structure Fin /-- A term on `α` is either a variable indexed by an element of `α` or a function symbol applied to simpler terms. -/ inductive Term (α : Type u') : Type max u u' | var : α → Term α | func : ∀ {l : ℕ} (_f : L.Functions l) (_ts : Fin l → Term α), Term α export Term (var func) variable {L} namespace Term instance instDecidableEq [DecidableEq α] [∀ n, DecidableEq (L.Functions n)] : DecidableEq (L.Term α) | .var a, .var b => decidable_of_iff (a = b) <| by simp | @Term.func _ _ m f xs, @Term.func _ _ n g ys => if h : m = n then letI : DecidableEq (L.Term α) := instDecidableEq decidable_of_iff (f = h ▸ g ∧ ∀ i : Fin m, xs i = ys (Fin.cast h i)) <| by subst h simp [funext_iff] else .isFalse <| by simp [h] | .var _, .func _ _ | .func _ _, .var _ => .isFalse <| by simp open Finset /-- The `Finset` of variables used in a given term. -/ @[simp] def varFinset [DecidableEq α] : L.Term α → Finset α | var i => {i} | func _f ts => univ.biUnion fun i => (ts i).varFinset /-- The `Finset` of variables from the left side of a sum used in a given term. -/ @[simp] def varFinsetLeft [DecidableEq α] : L.Term (α ⊕ β) → Finset α | var (Sum.inl i) => {i} | var (Sum.inr _i) => ∅ | func _f ts => univ.biUnion fun i => (ts i).varFinsetLeft /-- Relabels a term's variables along a particular function. -/ @[simp] def relabel (g : α → β) : L.Term α → L.Term β | var i => var (g i) | func f ts => func f fun {i} => (ts i).relabel g theorem relabel_id (t : L.Term α) : t.relabel id = t := by induction t with | var => rfl | func _ _ ih => simp [ih] @[simp] theorem relabel_id_eq_id : (Term.relabel id : L.Term α → L.Term α) = id := funext relabel_id @[simp] theorem relabel_relabel (f : α → β) (g : β → γ) (t : L.Term α) : (t.relabel f).relabel g = t.relabel (g ∘ f) := by induction t with | var => rfl | func _ _ ih => simp [ih] @[simp] theorem relabel_comp_relabel (f : α → β) (g : β → γ) : (Term.relabel g ∘ Term.relabel f : L.Term α → L.Term γ) = Term.relabel (g ∘ f) := funext (relabel_relabel f g) /-- Relabels a term's variables along a bijection. -/ @[simps] def relabelEquiv (g : α ≃ β) : L.Term α ≃ L.Term β := ⟨relabel g, relabel g.symm, fun t => by simp, fun t => by simp⟩ /-- Restricts a term to use only a set of the given variables. -/ def restrictVar [DecidableEq α] : ∀ (t : L.Term α) (_f : t.varFinset → β), L.Term β | var a, f => var (f ⟨a, mem_singleton_self a⟩) | func F ts, f => func F fun i => (ts i).restrictVar (f ∘ Set.inclusion (subset_biUnion_of_mem (fun i => varFinset (ts i)) (mem_univ i))) /-- Restricts a term to use only a set of the given variables on the left side of a sum. -/ def restrictVarLeft [DecidableEq α] {γ : Type*} : ∀ (t : L.Term (α ⊕ γ)) (_f : t.varFinsetLeft → β), L.Term (β ⊕ γ) | var (Sum.inl a), f => var (Sum.inl (f ⟨a, mem_singleton_self a⟩)) | var (Sum.inr a), _f => var (Sum.inr a) | func F ts, f => func F fun i => (ts i).restrictVarLeft (f ∘ Set.inclusion (subset_biUnion_of_mem (fun i => varFinsetLeft (ts i)) (mem_univ i))) end Term /-- The representation of a constant symbol as a term. -/ def Constants.term (c : L.Constants) : L.Term α := func c default /-- Applies a unary function to a term. -/ def Functions.apply₁ (f : L.Functions 1) (t : L.Term α) : L.Term α := func f ![t] /-- Applies a binary function to two terms. -/ def Functions.apply₂ (f : L.Functions 2) (t₁ t₂ : L.Term α) : L.Term α := func f ![t₁, t₂] namespace Term /-- Sends a term with constants to a term with extra variables. -/ @[simp] def constantsToVars : L[[γ]].Term α → L.Term (γ ⊕ α) | var a => var (Sum.inr a) | @func _ _ 0 f ts => Sum.casesOn f (fun f => func f fun i => (ts i).constantsToVars) fun c => var (Sum.inl c) | @func _ _ (_n + 1) f ts => Sum.casesOn f (fun f => func f fun i => (ts i).constantsToVars) fun c => isEmptyElim c /-- Sends a term with extra variables to a term with constants. -/ @[simp] def varsToConstants : L.Term (γ ⊕ α) → L[[γ]].Term α | var (Sum.inr a) => var a | var (Sum.inl c) => Constants.term (Sum.inr c) | func f ts => func (Sum.inl f) fun i => (ts i).varsToConstants /-- A bijection between terms with constants and terms with extra variables. -/ @[simps] def constantsVarsEquiv : L[[γ]].Term α ≃ L.Term (γ ⊕ α) := ⟨constantsToVars, varsToConstants, by intro t induction t with | var => rfl | @func n f _ ih => cases n · cases f · simp [constantsToVars, varsToConstants, ih] · simp [constantsToVars, varsToConstants, Constants.term, eq_iff_true_of_subsingleton] · obtain - | f := f · simp [constantsToVars, varsToConstants, ih] · exact isEmptyElim f, by intro t induction t with | var x => cases x <;> rfl | @func n f _ ih => cases n <;> · simp [varsToConstants, constantsToVars, ih]⟩ /-- A bijection between terms with constants and terms with extra variables. -/ def constantsVarsEquivLeft : L[[γ]].Term (α ⊕ β) ≃ L.Term ((γ ⊕ α) ⊕ β) := constantsVarsEquiv.trans (relabelEquiv (Equiv.sumAssoc _ _ _)).symm @[simp] theorem constantsVarsEquivLeft_apply (t : L[[γ]].Term (α ⊕ β)) : constantsVarsEquivLeft t = (constantsToVars t).relabel (Equiv.sumAssoc _ _ _).symm := rfl @[simp] theorem constantsVarsEquivLeft_symm_apply (t : L.Term ((γ ⊕ α) ⊕ β)) : constantsVarsEquivLeft.symm t = varsToConstants (t.relabel (Equiv.sumAssoc _ _ _)) := rfl instance inhabitedOfVar [Inhabited α] : Inhabited (L.Term α) := ⟨var default⟩ instance inhabitedOfConstant [Inhabited L.Constants] : Inhabited (L.Term α) := ⟨(default : L.Constants).term⟩ /-- Raises all of the `Fin`-indexed variables of a term greater than or equal to `m` by `n'`. -/ def liftAt {n : ℕ} (n' m : ℕ) : L.Term (α ⊕ (Fin n)) → L.Term (α ⊕ (Fin (n + n'))) := relabel (Sum.map id fun i => if ↑i < m then Fin.castAdd n' i else Fin.addNat i n') /-- Substitutes the variables in a given term with terms. -/ @[simp] def subst : L.Term α → (α → L.Term β) → L.Term β | var a, tf => tf a | func f ts, tf => func f fun i => (ts i).subst tf end Term /-- `&n` is notation for the `n`-th free variable of a bounded formula. -/ scoped[FirstOrder] prefix:arg "&" => FirstOrder.Language.Term.var ∘ Sum.inr namespace LHom open Term /-- Maps a term's symbols along a language map. -/ @[simp] def onTerm (φ : L →ᴸ L') : L.Term α → L'.Term α | var i => var i | func f ts => func (φ.onFunction f) fun i => onTerm φ (ts i) @[simp] theorem id_onTerm : ((LHom.id L).onTerm : L.Term α → L.Term α) = id := by ext t induction t with | var => rfl | func _ _ ih => simp_rw [onTerm, ih]; rfl @[simp] theorem comp_onTerm {L'' : Language} (φ : L' →ᴸ L'') (ψ : L →ᴸ L') : ((φ.comp ψ).onTerm : L.Term α → L''.Term α) = φ.onTerm ∘ ψ.onTerm := by ext t induction t with | var => rfl | func _ _ ih => simp_rw [onTerm, ih]; rfl end LHom /-- Maps a term's symbols along a language equivalence. -/ @[simps] def LEquiv.onTerm (φ : L ≃ᴸ L') : L.Term α ≃ L'.Term α where toFun := φ.toLHom.onTerm invFun := φ.invLHom.onTerm left_inv := by rw [Function.leftInverse_iff_comp, ← LHom.comp_onTerm, φ.left_inv, LHom.id_onTerm] right_inv := by rw [Function.rightInverse_iff_comp, ← LHom.comp_onTerm, φ.right_inv, LHom.id_onTerm] /-- Maps a term's symbols along a language equivalence. Deprecated in favor of `LEquiv.onTerm`. -/ @[deprecated LEquiv.onTerm (since := "2025-03-31")] alias Lequiv.onTerm := LEquiv.onTerm variable (L) (α) /-- `BoundedFormula α n` is the type of formulas with free variables indexed by `α` and up to `n` additional free variables. -/ inductive BoundedFormula : ℕ → Type max u v u' | falsum {n} : BoundedFormula n | equal {n} (t₁ t₂ : L.Term (α ⊕ (Fin n))) : BoundedFormula n | rel {n l : ℕ} (R : L.Relations l) (ts : Fin l → L.Term (α ⊕ (Fin n))) : BoundedFormula n /-- The implication between two bounded formulas -/ | imp {n} (f₁ f₂ : BoundedFormula n) : BoundedFormula n /-- The universal quantifier over bounded formulas -/ | all {n} (f : BoundedFormula (n + 1)) : BoundedFormula n /-- `Formula α` is the type of formulas with all free variables indexed by `α`. -/ abbrev Formula := L.BoundedFormula α 0 /-- A sentence is a formula with no free variables. -/ abbrev Sentence := L.Formula Empty /-- A theory is a set of sentences. -/ abbrev Theory := Set L.Sentence variable {L} {α} {n : ℕ} /-- Applies a relation to terms as a bounded formula. -/ def Relations.boundedFormula {l : ℕ} (R : L.Relations n) (ts : Fin n → L.Term (α ⊕ (Fin l))) : L.BoundedFormula α l := BoundedFormula.rel R ts /-- Applies a unary relation to a term as a bounded formula. -/ def Relations.boundedFormula₁ (r : L.Relations 1) (t : L.Term (α ⊕ (Fin n))) : L.BoundedFormula α n := r.boundedFormula ![t] /-- Applies a binary relation to two terms as a bounded formula. -/ def Relations.boundedFormula₂ (r : L.Relations 2) (t₁ t₂ : L.Term (α ⊕ (Fin n))) : L.BoundedFormula α n := r.boundedFormula ![t₁, t₂] /-- The equality of two terms as a bounded formula. -/ def Term.bdEqual (t₁ t₂ : L.Term (α ⊕ (Fin n))) : L.BoundedFormula α n := BoundedFormula.equal t₁ t₂ /-- Applies a relation to terms as a bounded formula. -/ def Relations.formula (R : L.Relations n) (ts : Fin n → L.Term α) : L.Formula α := R.boundedFormula fun i => (ts i).relabel Sum.inl /-- Applies a unary relation to a term as a formula. -/ def Relations.formula₁ (r : L.Relations 1) (t : L.Term α) : L.Formula α := r.formula ![t] /-- Applies a binary relation to two terms as a formula. -/ def Relations.formula₂ (r : L.Relations 2) (t₁ t₂ : L.Term α) : L.Formula α := r.formula ![t₁, t₂] /-- The equality of two terms as a first-order formula. -/ def Term.equal (t₁ t₂ : L.Term α) : L.Formula α := (t₁.relabel Sum.inl).bdEqual (t₂.relabel Sum.inl) namespace BoundedFormula instance : Inhabited (L.BoundedFormula α n) := ⟨falsum⟩ instance : Bot (L.BoundedFormula α n) := ⟨falsum⟩ /-- The negation of a bounded formula is also a bounded formula. -/ @[match_pattern] protected def not (φ : L.BoundedFormula α n) : L.BoundedFormula α n := φ.imp ⊥ /-- Puts an `∃` quantifier on a bounded formula. -/ @[match_pattern] protected def ex (φ : L.BoundedFormula α (n + 1)) : L.BoundedFormula α n := φ.not.all.not instance : Top (L.BoundedFormula α n) := ⟨BoundedFormula.not ⊥⟩ instance : Min (L.BoundedFormula α n) := ⟨fun f g => (f.imp g.not).not⟩ instance : Max (L.BoundedFormula α n) := ⟨fun f g => f.not.imp g⟩ /-- The biimplication between two bounded formulas. -/ protected def iff (φ ψ : L.BoundedFormula α n) := φ.imp ψ ⊓ ψ.imp φ open Finset /-- The `Finset` of variables used in a given formula. -/ @[simp] def freeVarFinset [DecidableEq α] : ∀ {n}, L.BoundedFormula α n → Finset α | _n, falsum => ∅ | _n, equal t₁ t₂ => t₁.varFinsetLeft ∪ t₂.varFinsetLeft | _n, rel _R ts => univ.biUnion fun i => (ts i).varFinsetLeft | _n, imp f₁ f₂ => f₁.freeVarFinset ∪ f₂.freeVarFinset | _n, all f => f.freeVarFinset /-- Casts `L.BoundedFormula α m` as `L.BoundedFormula α n`, where `m ≤ n`. -/ @[simp] def castLE : ∀ {m n : ℕ} (_h : m ≤ n), L.BoundedFormula α m → L.BoundedFormula α n | _m, _n, _h, falsum => falsum | _m, _n, h, equal t₁ t₂ => equal (t₁.relabel (Sum.map id (Fin.castLE h))) (t₂.relabel (Sum.map id (Fin.castLE h))) | _m, _n, h, rel R ts => rel R (Term.relabel (Sum.map id (Fin.castLE h)) ∘ ts) | _m, _n, h, imp f₁ f₂ => (f₁.castLE h).imp (f₂.castLE h) | _m, _n, h, all f => (f.castLE (add_le_add_right h 1)).all @[simp] theorem castLE_rfl {n} (h : n ≤ n) (φ : L.BoundedFormula α n) : φ.castLE h = φ := by induction φ with | falsum => rfl | equal => simp [Fin.castLE_of_eq] | rel => simp [Fin.castLE_of_eq] | imp _ _ ih1 ih2 => simp [Fin.castLE_of_eq, ih1, ih2] | all _ ih3 => simp [Fin.castLE_of_eq, ih3] @[simp] theorem castLE_castLE {k m n} (km : k ≤ m) (mn : m ≤ n) (φ : L.BoundedFormula α k) : (φ.castLE km).castLE mn = φ.castLE (km.trans mn) := by revert m n induction φ with | falsum => intros; rfl | equal => simp | rel => intros simp only [castLE, eq_self_iff_true, heq_iff_eq] rw [← Function.comp_assoc, Term.relabel_comp_relabel] simp | imp _ _ ih1 ih2 => simp [ih1, ih2] | all _ ih3 => intros; simp only [castLE, ih3] @[simp] theorem castLE_comp_castLE {k m n} (km : k ≤ m) (mn : m ≤ n) : (BoundedFormula.castLE mn ∘ BoundedFormula.castLE km : L.BoundedFormula α k → L.BoundedFormula α n) = BoundedFormula.castLE (km.trans mn) := funext (castLE_castLE km mn) /-- Restricts a bounded formula to only use a particular set of free variables. -/ def restrictFreeVar [DecidableEq α] : ∀ {n : ℕ} (φ : L.BoundedFormula α n) (_f : φ.freeVarFinset → β), L.BoundedFormula β n | _n, falsum, _f => falsum | _n, equal t₁ t₂, f => equal (t₁.restrictVarLeft (f ∘ Set.inclusion subset_union_left)) (t₂.restrictVarLeft (f ∘ Set.inclusion subset_union_right)) | _n, rel R ts, f => rel R fun i => (ts i).restrictVarLeft (f ∘ Set.inclusion (subset_biUnion_of_mem (fun i => Term.varFinsetLeft (ts i)) (mem_univ i))) | _n, imp φ₁ φ₂, f => (φ₁.restrictFreeVar (f ∘ Set.inclusion subset_union_left)).imp (φ₂.restrictFreeVar (f ∘ Set.inclusion subset_union_right)) | _n, all φ, f => (φ.restrictFreeVar f).all /-- Places universal quantifiers on all extra variables of a bounded formula. -/ def alls : ∀ {n}, L.BoundedFormula α n → L.Formula α | 0, φ => φ | _n + 1, φ => φ.all.alls /-- Places existential quantifiers on all extra variables of a bounded formula. -/ def exs : ∀ {n}, L.BoundedFormula α n → L.Formula α | 0, φ => φ | _n + 1, φ => φ.ex.exs /-- Maps bounded formulas along a map of terms and a map of relations. -/ def mapTermRel {g : ℕ → ℕ} (ft : ∀ n, L.Term (α ⊕ (Fin n)) → L'.Term (β ⊕ (Fin (g n)))) (fr : ∀ n, L.Relations n → L'.Relations n) (h : ∀ n, L'.BoundedFormula β (g (n + 1)) → L'.BoundedFormula β (g n + 1)) : ∀ {n}, L.BoundedFormula α n → L'.BoundedFormula β (g n) | _n, falsum => falsum | _n, equal t₁ t₂ => equal (ft _ t₁) (ft _ t₂) | _n, rel R ts => rel (fr _ R) fun i => ft _ (ts i) | _n, imp φ₁ φ₂ => (φ₁.mapTermRel ft fr h).imp (φ₂.mapTermRel ft fr h) | n, all φ => (h n (φ.mapTermRel ft fr h)).all /-- Raises all of the `Fin`-indexed variables of a formula greater than or equal to `m` by `n'`. -/ def liftAt : ∀ {n : ℕ} (n' _m : ℕ), L.BoundedFormula α n → L.BoundedFormula α (n + n') := fun {_} n' m φ => φ.mapTermRel (fun _ t => t.liftAt n' m) (fun _ => id) fun _ => castLE (by rw [add_assoc, add_comm 1, add_assoc]) @[simp] theorem mapTermRel_mapTermRel {L'' : Language} (ft : ∀ n, L.Term (α ⊕ (Fin n)) → L'.Term (β ⊕ (Fin n))) (fr : ∀ n, L.Relations n → L'.Relations n) (ft' : ∀ n, L'.Term (β ⊕ Fin n) → L''.Term (γ ⊕ (Fin n))) (fr' : ∀ n, L'.Relations n → L''.Relations n) {n} (φ : L.BoundedFormula α n) : ((φ.mapTermRel ft fr fun _ => id).mapTermRel ft' fr' fun _ => id) = φ.mapTermRel (fun _ => ft' _ ∘ ft _) (fun _ => fr' _ ∘ fr _) fun _ => id := by induction φ with | falsum => rfl | equal => simp [mapTermRel] | rel => simp [mapTermRel] | imp _ _ ih1 ih2 => simp [mapTermRel, ih1, ih2] | all _ ih3 => simp [mapTermRel, ih3] @[simp] theorem mapTermRel_id_id_id {n} (φ : L.BoundedFormula α n) : (φ.mapTermRel (fun _ => id) (fun _ => id) fun _ => id) = φ := by induction φ with | falsum => rfl | equal => simp [mapTermRel] | rel => simp [mapTermRel] | imp _ _ ih1 ih2 => simp [mapTermRel, ih1, ih2] | all _ ih3 => simp [mapTermRel, ih3] /-- An equivalence of bounded formulas given by an equivalence of terms and an equivalence of relations. -/ @[simps] def mapTermRelEquiv (ft : ∀ n, L.Term (α ⊕ (Fin n)) ≃ L'.Term (β ⊕ (Fin n))) (fr : ∀ n, L.Relations n ≃ L'.Relations n) {n} : L.BoundedFormula α n ≃ L'.BoundedFormula β n := ⟨mapTermRel (fun n => ft n) (fun n => fr n) fun _ => id, mapTermRel (fun n => (ft n).symm) (fun n => (fr n).symm) fun _ => id, fun φ => by simp, fun φ => by simp⟩ /-- A function to help relabel the variables in bounded formulas. -/ def relabelAux (g : α → β ⊕ (Fin n)) (k : ℕ) : α ⊕ (Fin k) → β ⊕ (Fin (n + k)) := Sum.map id finSumFinEquiv ∘ Equiv.sumAssoc _ _ _ ∘ Sum.map g id @[simp] theorem sumElim_comp_relabelAux {m : ℕ} {g : α → β ⊕ (Fin n)} {v : β → M} {xs : Fin (n + m) → M} : Sum.elim v xs ∘ relabelAux g m = Sum.elim (Sum.elim v (xs ∘ castAdd m) ∘ g) (xs ∘ natAdd n) := by ext x rcases x with x | x · simp only [BoundedFormula.relabelAux, Function.comp_apply, Sum.map_inl, Sum.elim_inl] rcases g x with l | r <;> simp · simp [BoundedFormula.relabelAux] @[deprecated (since := "2025-02-21")] alias sum_elim_comp_relabelAux := sumElim_comp_relabelAux @[simp] theorem relabelAux_sumInl (k : ℕ) : relabelAux (Sum.inl : α → α ⊕ (Fin n)) k = Sum.map id (natAdd n) := by ext x cases x <;> · simp [relabelAux] @[deprecated (since := "2025-02-21")] alias relabelAux_sum_inl := relabelAux_sumInl /-- Relabels a bounded formula's variables along a particular function. -/ def relabel (g : α → β ⊕ (Fin n)) {k} (φ : L.BoundedFormula α k) : L.BoundedFormula β (n + k) := φ.mapTermRel (fun _ t => t.relabel (relabelAux g _)) (fun _ => id) fun _ => castLE (ge_of_eq (add_assoc _ _ _)) /-- Relabels a bounded formula's free variables along a bijection. -/ def relabelEquiv (g : α ≃ β) {k} : L.BoundedFormula α k ≃ L.BoundedFormula β k := mapTermRelEquiv (fun _n => Term.relabelEquiv (g.sumCongr (_root_.Equiv.refl _))) fun _n => _root_.Equiv.refl _ @[simp] theorem relabel_falsum (g : α → β ⊕ (Fin n)) {k} : (falsum : L.BoundedFormula α k).relabel g = falsum := rfl @[simp] theorem relabel_bot (g : α → β ⊕ (Fin n)) {k} : (⊥ : L.BoundedFormula α k).relabel g = ⊥ := rfl @[simp] theorem relabel_imp (g : α → β ⊕ (Fin n)) {k} (φ ψ : L.BoundedFormula α k) : (φ.imp ψ).relabel g = (φ.relabel g).imp (ψ.relabel g) := rfl @[simp] theorem relabel_not (g : α → β ⊕ (Fin n)) {k} (φ : L.BoundedFormula α k) : φ.not.relabel g = (φ.relabel g).not := by simp [BoundedFormula.not] @[simp] theorem relabel_all (g : α → β ⊕ (Fin n)) {k} (φ : L.BoundedFormula α (k + 1)) : φ.all.relabel g = (φ.relabel g).all := by rw [relabel, mapTermRel, relabel] simp @[simp] theorem relabel_ex (g : α → β ⊕ (Fin n)) {k} (φ : L.BoundedFormula α (k + 1)) : φ.ex.relabel g = (φ.relabel g).ex := by simp [BoundedFormula.ex] @[simp] theorem relabel_sumInl (φ : L.BoundedFormula α n) : (φ.relabel Sum.inl : L.BoundedFormula α (0 + n)) = φ.castLE (ge_of_eq (zero_add n)) := by simp only [relabel, relabelAux_sumInl] induction φ with | falsum => rfl | equal => simp [Fin.natAdd_zero, castLE_of_eq, mapTermRel] | rel => simp [Fin.natAdd_zero, castLE_of_eq, mapTermRel]; rfl | imp _ _ ih1 ih2 => simp_all [mapTermRel] | all _ ih3 => simp_all [mapTermRel] @[deprecated (since := "2025-02-21")] alias relabel_sum_inl := relabel_sumInl /-- Substitutes the variables in a given formula with terms. -/ def subst {n : ℕ} (φ : L.BoundedFormula α n) (f : α → L.Term β) : L.BoundedFormula β n := φ.mapTermRel (fun _ t => t.subst (Sum.elim (Term.relabel Sum.inl ∘ f) (var ∘ Sum.inr))) (fun _ => id) fun _ => id /-- A bijection sending formulas with constants to formulas with extra variables. -/ def constantsVarsEquiv : L[[γ]].BoundedFormula α n ≃ L.BoundedFormula (γ ⊕ α) n := mapTermRelEquiv (fun _ => Term.constantsVarsEquivLeft) fun _ => Equiv.sumEmpty _ _ /-- Turns the extra variables of a bounded formula into free variables. -/ @[simp] def toFormula : ∀ {n : ℕ}, L.BoundedFormula α n → L.Formula (α ⊕ (Fin n)) | _n, falsum => falsum | _n, equal t₁ t₂ => t₁.equal t₂ | _n, rel R ts => R.formula ts | _n, imp φ₁ φ₂ => φ₁.toFormula.imp φ₂.toFormula | _n, all φ => (φ.toFormula.relabel (Sum.elim (Sum.inl ∘ Sum.inl) (Sum.map Sum.inr id ∘ finSumFinEquiv.symm))).all /-- Take the disjunction of a finite set of formulas -/ noncomputable def iSup [Finite β] (f : β → L.BoundedFormula α n) : L.BoundedFormula α n := let _ := Fintype.ofFinite β ((Finset.univ : Finset β).toList.map f).foldr (· ⊔ ·) ⊥ /-- Take the conjunction of a finite set of formulas -/ noncomputable def iInf [Finite β] (f : β → L.BoundedFormula α n) : L.BoundedFormula α n := let _ := Fintype.ofFinite β ((Finset.univ : Finset β).toList.map f).foldr (· ⊓ ·) ⊤ end BoundedFormula namespace LHom open BoundedFormula /-- Maps a bounded formula's symbols along a language map. -/ @[simp] def onBoundedFormula (g : L →ᴸ L') : ∀ {k : ℕ}, L.BoundedFormula α k → L'.BoundedFormula α k | _k, falsum => falsum | _k, equal t₁ t₂ => (g.onTerm t₁).bdEqual (g.onTerm t₂) | _k, rel R ts => (g.onRelation R).boundedFormula (g.onTerm ∘ ts) | _k, imp f₁ f₂ => (onBoundedFormula g f₁).imp (onBoundedFormula g f₂) | _k, all f => (onBoundedFormula g f).all @[simp] theorem id_onBoundedFormula : ((LHom.id L).onBoundedFormula : L.BoundedFormula α n → L.BoundedFormula α n) = id := by ext f induction f with | falsum => rfl | equal => rw [onBoundedFormula, LHom.id_onTerm, id, id, id, Term.bdEqual] | rel => rw [onBoundedFormula, LHom.id_onTerm]; rfl | imp _ _ ih1 ih2 => rw [onBoundedFormula, ih1, ih2, id, id, id] | all _ ih3 => rw [onBoundedFormula, ih3, id, id] @[simp] theorem comp_onBoundedFormula {L'' : Language} (φ : L' →ᴸ L'') (ψ : L →ᴸ L') : ((φ.comp ψ).onBoundedFormula : L.BoundedFormula α n → L''.BoundedFormula α n) = φ.onBoundedFormula ∘ ψ.onBoundedFormula := by ext f induction f with | falsum => rfl | equal => simp [Term.bdEqual] | rel => simp only [onBoundedFormula, comp_onRelation, comp_onTerm, Function.comp_apply]; rfl | imp _ _ ih1 ih2 => simp only [onBoundedFormula, Function.comp_apply, ih1, ih2, eq_self_iff_true, and_self_iff] | all _ ih3 => simp only [ih3, onBoundedFormula, Function.comp_apply] /-- Maps a formula's symbols along a language map. -/ def onFormula (g : L →ᴸ L') : L.Formula α → L'.Formula α := g.onBoundedFormula /-- Maps a sentence's symbols along a language map. -/ def onSentence (g : L →ᴸ L') : L.Sentence → L'.Sentence := g.onFormula /-- Maps a theory's symbols along a language map. -/ def onTheory (g : L →ᴸ L') (T : L.Theory) : L'.Theory := g.onSentence '' T @[simp] theorem mem_onTheory {g : L →ᴸ L'} {T : L.Theory} {φ : L'.Sentence} : φ ∈ g.onTheory T ↔ ∃ φ₀, φ₀ ∈ T ∧ g.onSentence φ₀ = φ := Set.mem_image _ _ _ end LHom namespace LEquiv /-- Maps a bounded formula's symbols along a language equivalence. -/ @[simps] def onBoundedFormula (φ : L ≃ᴸ L') : L.BoundedFormula α n ≃ L'.BoundedFormula α n where toFun := φ.toLHom.onBoundedFormula invFun := φ.invLHom.onBoundedFormula left_inv := by rw [Function.leftInverse_iff_comp, ← LHom.comp_onBoundedFormula, φ.left_inv, LHom.id_onBoundedFormula] right_inv := by rw [Function.rightInverse_iff_comp, ← LHom.comp_onBoundedFormula, φ.right_inv, LHom.id_onBoundedFormula] theorem onBoundedFormula_symm (φ : L ≃ᴸ L') : (φ.onBoundedFormula.symm : L'.BoundedFormula α n ≃ L.BoundedFormula α n) = φ.symm.onBoundedFormula := rfl /-- Maps a formula's symbols along a language equivalence. -/
def onFormula (φ : L ≃ᴸ L') : L.Formula α ≃ L'.Formula α :=
Mathlib/ModelTheory/Syntax.lean
689
689
/- Copyright (c) 2020 David Wärn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: David Wärn -/ import Mathlib.Data.Finset.Lattice.Fold import Mathlib.Logic.Encodable.Basic import Mathlib.Order.Atoms import Mathlib.Order.Cofinal import Mathlib.Order.UpperLower.Principal /-! # Order ideals, cofinal sets, and the Rasiowa–Sikorski lemma ## Main definitions Throughout this file, `P` is at least a preorder, but some sections require more structure, such as a bottom element, a top element, or a join-semilattice structure. - `Order.Ideal P`: the type of nonempty, upward directed, and downward closed subsets of `P`. Dual to the notion of a filter on a preorder. - `Order.IsIdeal I`: a predicate for when a `Set P` is an ideal. - `Order.Ideal.principal p`: the principal ideal generated by `p : P`. - `Order.Ideal.IsProper I`: a predicate for proper ideals. Dual to the notion of a proper filter. - `Order.Ideal.IsMaximal I`: a predicate for maximal ideals. Dual to the notion of an ultrafilter. - `Order.Cofinal P`: the type of subsets of `P` containing arbitrarily large elements. Dual to the notion of 'dense set' used in forcing. - `Order.idealOfCofinals p 𝒟`, where `p : P`, and `𝒟` is a countable family of cofinal subsets of `P`: an ideal in `P` which contains `p` and intersects every set in `𝒟`. (This a form of the Rasiowa–Sikorski lemma.) ## References - <https://en.wikipedia.org/wiki/Ideal_(order_theory)> - <https://en.wikipedia.org/wiki/Cofinal_(mathematics)> - <https://en.wikipedia.org/wiki/Rasiowa%E2%80%93Sikorski_lemma> Note that for the Rasiowa–Sikorski lemma, Wikipedia uses the opposite ordering on `P`, in line with most presentations of forcing. ## Tags ideal, cofinal, dense, countable, generic -/ open Function Set namespace Order variable {P : Type*} /-- An ideal on an order `P` is a subset of `P` that is - nonempty - upward directed (any pair of elements in the ideal has an upper bound in the ideal) - downward closed (any element less than an element of the ideal is in the ideal). -/ structure Ideal (P) [LE P] extends LowerSet P where /-- The ideal is nonempty. -/ nonempty' : carrier.Nonempty /-- The ideal is upward directed. -/ directed' : DirectedOn (· ≤ ·) carrier -- TODO: remove this configuration and use the default configuration. -- We keep this to be consistent with Lean 3. initialize_simps_projections Ideal (+toLowerSet, -carrier) /-- A subset of a preorder `P` is an ideal if it is - nonempty - upward directed (any pair of elements in the ideal has an upper bound in the ideal) - downward closed (any element less than an element of the ideal is in the ideal). -/ @[mk_iff] structure IsIdeal {P} [LE P] (I : Set P) : Prop where /-- The ideal is downward closed. -/ IsLowerSet : IsLowerSet I /-- The ideal is nonempty. -/ Nonempty : I.Nonempty /-- The ideal is upward directed. -/ Directed : DirectedOn (· ≤ ·) I /-- Create an element of type `Order.Ideal` from a set satisfying the predicate `Order.IsIdeal`. -/ def IsIdeal.toIdeal [LE P] {I : Set P} (h : IsIdeal I) : Ideal P := ⟨⟨I, h.IsLowerSet⟩, h.Nonempty, h.Directed⟩ namespace Ideal section LE variable [LE P] section variable {I s t : Ideal P} {x : P} theorem toLowerSet_injective : Injective (toLowerSet : Ideal P → LowerSet P) := fun s t _ ↦ by cases s cases t congr instance : SetLike (Ideal P) P where coe s := s.carrier coe_injective' _ _ h := toLowerSet_injective <| SetLike.coe_injective h @[ext] theorem ext {s t : Ideal P} : (s : Set P) = t → s = t := SetLike.ext' @[simp] theorem carrier_eq_coe (s : Ideal P) : s.carrier = s := rfl @[simp] theorem coe_toLowerSet (s : Ideal P) : (s.toLowerSet : Set P) = s := rfl protected theorem lower (s : Ideal P) : IsLowerSet (s : Set P) := s.lower' protected theorem nonempty (s : Ideal P) : (s : Set P).Nonempty := s.nonempty' protected theorem directed (s : Ideal P) : DirectedOn (· ≤ ·) (s : Set P) := s.directed' protected theorem isIdeal (s : Ideal P) : IsIdeal (s : Set P) := ⟨s.lower, s.nonempty, s.directed⟩ theorem mem_compl_of_ge {x y : P} : x ≤ y → x ∈ (I : Set P)ᶜ → y ∈ (I : Set P)ᶜ := fun h ↦ mt <| I.lower h /-- The partial ordering by subset inclusion, inherited from `Set P`. -/ instance instPartialOrderIdeal : PartialOrder (Ideal P) := PartialOrder.lift SetLike.coe SetLike.coe_injective theorem coe_subset_coe : (s : Set P) ⊆ t ↔ s ≤ t := Iff.rfl theorem coe_ssubset_coe : (s : Set P) ⊂ t ↔ s < t := Iff.rfl @[trans] theorem mem_of_mem_of_le {x : P} {I J : Ideal P} : x ∈ I → I ≤ J → x ∈ J := @Set.mem_of_mem_of_subset P x I J /-- A proper ideal is one that is not the whole set. Note that the whole set might not be an ideal. -/ @[mk_iff] class IsProper (I : Ideal P) : Prop where /-- This ideal is not the whole set. -/ ne_univ : (I : Set P) ≠ univ theorem isProper_of_not_mem {I : Ideal P} {p : P} (nmem : p ∉ I) : IsProper I := ⟨fun hp ↦ by have := mem_univ p rw [← hp] at this exact nmem this⟩ /-- An ideal is maximal if it is maximal in the collection of proper ideals. Note that `IsCoatom` is less general because ideals only have a top element when `P` is directed and nonempty. -/ @[mk_iff] class IsMaximal (I : Ideal P) : Prop extends IsProper I where /-- This ideal is maximal in the collection of proper ideals. -/ maximal_proper : ∀ ⦃J : Ideal P⦄, I < J → (J : Set P) = univ theorem inter_nonempty [IsDirected P (· ≥ ·)] (I J : Ideal P) : (I ∩ J : Set P).Nonempty := by obtain ⟨a, ha⟩ := I.nonempty obtain ⟨b, hb⟩ := J.nonempty obtain ⟨c, hac, hbc⟩ := exists_le_le a b exact ⟨c, I.lower hac ha, J.lower hbc hb⟩ end section Directed variable [IsDirected P (· ≤ ·)] [Nonempty P] {I : Ideal P} /-- In a directed and nonempty order, the top ideal of a is `univ`. -/ instance : OrderTop (Ideal P) where top := ⟨⊤, univ_nonempty, directedOn_univ⟩ le_top _ _ _ := LowerSet.mem_top @[simp] theorem top_toLowerSet : (⊤ : Ideal P).toLowerSet = ⊤ := rfl @[simp] theorem coe_top : ((⊤ : Ideal P) : Set P) = univ := rfl theorem isProper_of_ne_top (ne_top : I ≠ ⊤) : IsProper I := ⟨fun h ↦ ne_top <| ext h⟩ theorem IsProper.ne_top (_ : IsProper I) : I ≠ ⊤ := fun h ↦ IsProper.ne_univ <| congr_arg SetLike.coe h theorem _root_.IsCoatom.isProper (hI : IsCoatom I) : IsProper I := isProper_of_ne_top hI.1 theorem isProper_iff_ne_top : IsProper I ↔ I ≠ ⊤ := ⟨fun h ↦ h.ne_top, fun h ↦ isProper_of_ne_top h⟩ theorem IsMaximal.isCoatom (_ : IsMaximal I) : IsCoatom I := ⟨IsMaximal.toIsProper.ne_top, fun _ h ↦ ext <| IsMaximal.maximal_proper h⟩ theorem IsMaximal.isCoatom' [IsMaximal I] : IsCoatom I := IsMaximal.isCoatom ‹_› theorem _root_.IsCoatom.isMaximal (hI : IsCoatom I) : IsMaximal I := { IsCoatom.isProper hI with maximal_proper := fun _ hJ ↦ by simp [hI.2 _ hJ] } theorem isMaximal_iff_isCoatom : IsMaximal I ↔ IsCoatom I := ⟨fun h ↦ h.isCoatom, fun h ↦ IsCoatom.isMaximal h⟩ end Directed section OrderBot variable [OrderBot P] @[simp] theorem bot_mem (s : Ideal P) : ⊥ ∈ s := s.lower bot_le s.nonempty'.some_mem end OrderBot section OrderTop variable [OrderTop P] {I : Ideal P} theorem top_of_top_mem (h : ⊤ ∈ I) : I = ⊤ := by ext exact iff_of_true (I.lower le_top h) trivial theorem IsProper.top_not_mem (hI : IsProper I) : ⊤ ∉ I := fun h ↦ hI.ne_top <| top_of_top_mem h end OrderTop end LE section Preorder variable [Preorder P] section variable {I : Ideal P} {x y : P} /-- The smallest ideal containing a given element. -/ @[simps] def principal (p : P) : Ideal P where toLowerSet := LowerSet.Iic p nonempty' := nonempty_Iic directed' _ hx _ hy := ⟨p, le_rfl, hx, hy⟩ instance [Inhabited P] : Inhabited (Ideal P) := ⟨Ideal.principal default⟩ @[simp] theorem principal_le_iff : principal x ≤ I ↔ x ∈ I := ⟨fun h ↦ h le_rfl, fun hx _ hy ↦ I.lower hy hx⟩ @[simp] theorem mem_principal : x ∈ principal y ↔ x ≤ y := Iff.rfl lemma mem_principal_self : x ∈ principal x := mem_principal.2 (le_refl x) end section OrderBot variable [OrderBot P] /-- There is a bottom ideal when `P` has a bottom element. -/ instance : OrderBot (Ideal P) where bot := principal ⊥ bot_le := by simp @[simp] theorem principal_bot : principal (⊥ : P) = ⊥ := rfl end OrderBot section OrderTop variable [OrderTop P] @[simp] theorem principal_top : principal (⊤ : P) = ⊤ := toLowerSet_injective <| LowerSet.Iic_top end OrderTop end Preorder section SemilatticeSup variable [SemilatticeSup P] {x y : P} {I s : Ideal P} /-- A specific witness of `I.directed` when `P` has joins. -/ theorem sup_mem (hx : x ∈ s) (hy : y ∈ s) : x ⊔ y ∈ s := let ⟨_, hz, hx, hy⟩ := s.directed x hx y hy s.lower (sup_le hx hy) hz @[simp] theorem sup_mem_iff : x ⊔ y ∈ I ↔ x ∈ I ∧ y ∈ I := ⟨fun h ↦ ⟨I.lower le_sup_left h, I.lower le_sup_right h⟩, fun h ↦ sup_mem h.1 h.2⟩ @[simp] lemma finsetSup_mem_iff {P : Type*} [SemilatticeSup P] [OrderBot P] (t : Ideal P) {ι : Type*} {f : ι → P} {s : Finset ι} : s.sup f ∈ t ↔ ∀ i ∈ s, f i ∈ t := by classical induction s using Finset.induction_on <;> simp [*] end SemilatticeSup section SemilatticeSupDirected variable [SemilatticeSup P] [IsDirected P (· ≥ ·)] {x : P} {I J s t : Ideal P} /-- The infimum of two ideals of a co-directed order is their intersection. -/ instance : Min (Ideal P) := ⟨fun I J ↦ { toLowerSet := I.toLowerSet ⊓ J.toLowerSet nonempty' := inter_nonempty I J directed' := fun x hx y hy ↦ ⟨x ⊔ y, ⟨sup_mem hx.1 hy.1, sup_mem hx.2 hy.2⟩, by simp⟩ }⟩ /-- The supremum of two ideals of a co-directed order is the union of the down sets of the pointwise supremum of `I` and `J`. -/ instance : Max (Ideal P) := ⟨fun I J ↦ { carrier := { x | ∃ i ∈ I, ∃ j ∈ J, x ≤ i ⊔ j } nonempty' := by obtain ⟨w, h⟩ := inter_nonempty I J exact ⟨w, w, h.1, w, h.2, le_sup_left⟩ directed' := fun x ⟨xi, _, xj, _, _⟩ y ⟨yi, _, yj, _, _⟩ ↦ ⟨x ⊔ y, ⟨xi ⊔ yi, sup_mem ‹_› ‹_›, xj ⊔ yj, sup_mem ‹_› ‹_›, sup_le (calc x ≤ xi ⊔ xj := ‹_› _ ≤ xi ⊔ yi ⊔ (xj ⊔ yj) := sup_le_sup le_sup_left le_sup_left) (calc y ≤ yi ⊔ yj := ‹_› _ ≤ xi ⊔ yi ⊔ (xj ⊔ yj) := sup_le_sup le_sup_right le_sup_right)⟩, le_sup_left, le_sup_right⟩ lower' := fun _ _ h ⟨yi, hi, yj, hj, hxy⟩ ↦ ⟨yi, hi, yj, hj, h.trans hxy⟩ }⟩ instance : Lattice (Ideal P) := { Ideal.instPartialOrderIdeal with sup := (· ⊔ ·) le_sup_left := fun _ J i hi ↦ let ⟨w, hw⟩ := J.nonempty ⟨i, hi, w, hw, le_sup_left⟩ le_sup_right := fun I _ j hj ↦ let ⟨w, hw⟩ := I.nonempty ⟨w, hw, j, hj, le_sup_right⟩ sup_le := fun _ _ K hIK hJK _ ⟨_, hi, _, hj, ha⟩ ↦ K.lower ha <| sup_mem (mem_of_mem_of_le hi hIK) (mem_of_mem_of_le hj hJK) inf := (· ⊓ ·) inf_le_left := fun _ _ ↦ inter_subset_left inf_le_right := fun _ _ ↦ inter_subset_right le_inf := fun _ _ _ ↦ subset_inter } @[simp] theorem coe_sup : ↑(s ⊔ t) = { x | ∃ a ∈ s, ∃ b ∈ t, x ≤ a ⊔ b } := rfl @[simp] theorem coe_inf : (↑(s ⊓ t) : Set P) = ↑s ∩ ↑t := rfl @[simp] theorem mem_inf : x ∈ I ⊓ J ↔ x ∈ I ∧ x ∈ J := Iff.rfl @[simp] theorem mem_sup : x ∈ I ⊔ J ↔ ∃ i ∈ I, ∃ j ∈ J, x ≤ i ⊔ j := Iff.rfl theorem lt_sup_principal_of_not_mem (hx : x ∉ I) : I < I ⊔ principal x := le_sup_left.lt_of_ne fun h ↦ hx <| by simpa only [left_eq_sup, principal_le_iff] using h end SemilatticeSupDirected section SemilatticeSupOrderBot variable [SemilatticeSup P] [OrderBot P] {x : P} instance : InfSet (Ideal P) := ⟨fun S ↦ { toLowerSet := ⨅ s ∈ S, toLowerSet s nonempty' := ⟨⊥, by rw [LowerSet.carrier_eq_coe, LowerSet.coe_iInf₂, Set.mem_iInter₂] exact fun s _ ↦ s.bot_mem⟩ directed' := fun a ha b hb ↦ ⟨a ⊔ b, ⟨by rw [LowerSet.carrier_eq_coe, LowerSet.coe_iInf₂, Set.mem_iInter₂] at ha hb ⊢ exact fun s hs ↦ sup_mem (ha _ hs) (hb _ hs), le_sup_left, le_sup_right⟩⟩ }⟩ variable {S : Set (Ideal P)} @[simp] theorem coe_sInf : (↑(sInf S) : Set P) = ⋂ s ∈ S, ↑s := LowerSet.coe_iInf₂ _ @[simp] theorem mem_sInf : x ∈ sInf S ↔ ∀ s ∈ S, x ∈ s := by simp_rw [← SetLike.mem_coe, coe_sInf, mem_iInter₂] instance : CompleteLattice (Ideal P) := { (inferInstance : Lattice (Ideal P)), completeLatticeOfInf (Ideal P) fun S ↦ by refine ⟨fun s hs ↦ ?_, fun s hs ↦ by rwa [← coe_subset_coe, coe_sInf, subset_iInter₂_iff]⟩ rw [← coe_subset_coe, coe_sInf] exact biInter_subset_of_mem hs with } end SemilatticeSupOrderBot section DistribLattice variable [DistribLattice P] variable {I J : Ideal P} theorem eq_sup_of_le_sup {x i j : P} (hi : i ∈ I) (hj : j ∈ J) (hx : x ≤ i ⊔ j) : ∃ i' ∈ I, ∃ j' ∈ J, x = i' ⊔ j' := by refine ⟨x ⊓ i, I.lower inf_le_right hi, x ⊓ j, J.lower inf_le_right hj, ?_⟩ calc x = x ⊓ (i ⊔ j) := left_eq_inf.mpr hx _ = x ⊓ i ⊔ x ⊓ j := inf_sup_left _ _ _ theorem coe_sup_eq : ↑(I ⊔ J) = { x | ∃ i ∈ I, ∃ j ∈ J, x = i ⊔ j } := Set.ext fun _ ↦ ⟨fun ⟨_, _, _, _, _⟩ ↦ eq_sup_of_le_sup ‹_› ‹_› ‹_›, fun ⟨i, _, j, _, _⟩ ↦ ⟨i, ‹_›, j, ‹_›, le_of_eq ‹_›⟩⟩ end DistribLattice section BooleanAlgebra variable [BooleanAlgebra P] {x : P} {I : Ideal P} theorem IsProper.not_mem_of_compl_mem (hI : IsProper I) (hxc : xᶜ ∈ I) : x ∉ I := by intro hx apply hI.top_not_mem have ht : x ⊔ xᶜ ∈ I := sup_mem ‹_› ‹_› rwa [sup_compl_eq_top] at ht theorem IsProper.not_mem_or_compl_not_mem (hI : IsProper I) : x ∉ I ∨ xᶜ ∉ I := by have h : xᶜ ∈ I → x ∉ I := hI.not_mem_of_compl_mem tauto end BooleanAlgebra end Ideal /-- For a preorder `P`, `Cofinal P` is the type of subsets of `P` containing arbitrarily large elements. They are the dense sets in the topology whose open sets are terminal segments. -/ structure Cofinal (P) [Preorder P] where /-- The carrier of a `Cofinal` is the underlying set. -/ carrier : Set P /-- The `Cofinal` contains arbitrarily large elements. -/ isCofinal : IsCofinal carrier @[deprecated Cofinal.isCofinal (since := "2024-12-02")] alias Cofinal.mem_gt := Cofinal.isCofinal namespace Cofinal variable [Preorder P] instance : Inhabited (Cofinal P) := ⟨_, .univ⟩ instance : Membership P (Cofinal P) := ⟨fun D x ↦ x ∈ D.carrier⟩ variable (D : Cofinal P) (x : P) /-- A (noncomputable) element of a cofinal set lying above a given element. -/ noncomputable def above : P := Classical.choose <| D.isCofinal x theorem above_mem : D.above x ∈ D := (Classical.choose_spec <| D.isCofinal x).1 theorem le_above : x ≤ D.above x := (Classical.choose_spec <| D.isCofinal x).2 end Cofinal section IdealOfCofinals variable [Preorder P] (p : P) {ι : Type*} [Encodable ι] (𝒟 : ι → Cofinal P) /-- Given a starting point, and a countable family of cofinal sets, this is an increasing sequence that intersects each cofinal set. -/ noncomputable def sequenceOfCofinals : ℕ → P | 0 => p | n + 1 => match Encodable.decode n with | none => sequenceOfCofinals n | some i => (𝒟 i).above (sequenceOfCofinals n) theorem sequenceOfCofinals.monotone : Monotone (sequenceOfCofinals p 𝒟) := by apply monotone_nat_of_le_succ intro n dsimp only [sequenceOfCofinals, Nat.add] cases (Encodable.decode n : Option ι) · rfl · apply Cofinal.le_above theorem sequenceOfCofinals.encode_mem (i : ι) : sequenceOfCofinals p 𝒟 (Encodable.encode i + 1) ∈ 𝒟 i := by dsimp only [sequenceOfCofinals, Nat.add] rw [Encodable.encodek] apply Cofinal.above_mem /-- Given an element `p : P` and a family `𝒟` of cofinal subsets of a preorder `P`, indexed by a countable type, `idealOfCofinals p 𝒟` is an ideal in `P` which - contains `p`, according to `mem_idealOfCofinals p 𝒟`, and - intersects every set in `𝒟`, according to `cofinal_meets_idealOfCofinals p 𝒟`. This proves the Rasiowa–Sikorski lemma. -/ def idealOfCofinals : Ideal P where carrier := { x : P | ∃ n, x ≤ sequenceOfCofinals p 𝒟 n } lower' := fun _ _ hxy ⟨n, hn⟩ ↦ ⟨n, le_trans hxy hn⟩ nonempty' := ⟨p, 0, le_rfl⟩ directed' := fun _ ⟨n, hn⟩ _ ⟨m, hm⟩ ↦ ⟨_, ⟨max n m, le_rfl⟩, le_trans hn <| sequenceOfCofinals.monotone p 𝒟 (le_max_left _ _), le_trans hm <| sequenceOfCofinals.monotone p 𝒟 (le_max_right _ _)⟩ theorem mem_idealOfCofinals : p ∈ idealOfCofinals p 𝒟 := ⟨0, le_rfl⟩ /-- `idealOfCofinals p 𝒟` is `𝒟`-generic. -/ theorem cofinal_meets_idealOfCofinals (i : ι) : ∃ x : P, x ∈ 𝒟 i ∧ x ∈ idealOfCofinals p 𝒟 := ⟨_, sequenceOfCofinals.encode_mem p 𝒟 i, _, le_rfl⟩ end IdealOfCofinals section sUnion variable [Preorder P] /-- A non-empty directed union of ideals of sets in a preorder is an ideal. -/ lemma isIdeal_sUnion_of_directedOn {C : Set (Set P)} (hidl : ∀ I ∈ C, IsIdeal I) (hD : DirectedOn (· ⊆ ·) C) (hNe : C.Nonempty) : IsIdeal C.sUnion := by refine ⟨isLowerSet_sUnion (fun I hI ↦ (hidl I hI).1), Set.nonempty_sUnion.2 ?_, directedOn_sUnion hD (fun J hJ => (hidl J hJ).3)⟩ let ⟨I, hI⟩ := hNe exact ⟨I, ⟨hI, (hidl I hI).2⟩⟩ /-- A union of a nonempty chain of ideals of sets is an ideal. -/ lemma isIdeal_sUnion_of_isChain {C : Set (Set P)} (hidl : ∀ I ∈ C, IsIdeal I) (hC : IsChain (· ⊆ ·) C) (hNe : C.Nonempty) : IsIdeal C.sUnion := isIdeal_sUnion_of_directedOn hidl hC.directedOn hNe end sUnion end Order
Mathlib/Order/Ideal.lean
611
617
/- Copyright (c) 2015 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro -/ import Mathlib.Data.Finset.Attach import Mathlib.Data.Finset.Disjoint import Mathlib.Data.Finset.Erase import Mathlib.Data.Finset.Filter import Mathlib.Data.Finset.Range import Mathlib.Data.Finset.SDiff import Mathlib.Data.Multiset.Basic import Mathlib.Logic.Equiv.Set import Mathlib.Order.Directed import Mathlib.Order.Interval.Set.Defs import Mathlib.Data.Set.SymmDiff /-! # Basic lemmas on finite sets This file contains lemmas on the interaction of various definitions on the `Finset` type. For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`. ## Main declarations ### Main definitions * `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate. ### Equivalences between finsets * The `Mathlib/Logic/Equiv/Defs.lean` file describes a general type of equivalence, so look in there for any lemmas. There is some API for rewriting sums and products from `s` to `t` given that `s ≃ t`. TODO: examples ## Tags finite sets, finset -/ -- Assert that we define `Finset` without the material on `List.sublists`. -- Note that we cannot use `List.sublists` itself as that is defined very early. assert_not_exists List.sublistsLen Multiset.powerset CompleteLattice Monoid open Multiset Subtype Function universe u variable {α : Type*} {β : Type*} {γ : Type*} namespace Finset -- TODO: these should be global attributes, but this will require fixing other files attribute [local trans] Subset.trans Superset.trans set_option linter.deprecated false in @[deprecated "Deprecated without replacement." (since := "2025-02-07")] theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) : SizeOf.sizeOf x < SizeOf.sizeOf s := by cases s dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf] rw [Nat.add_comm] refine lt_trans ?_ (Nat.lt_succ_self _) exact Multiset.sizeOf_lt_sizeOf_of_mem hx /-! ### Lattice structure -/ section Lattice variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α} /-! #### union -/ @[simp] theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t := ext fun a => by simp @[simp] theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by simp only [disjoint_left, mem_union, or_imp, forall_and] @[simp] theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by simp only [disjoint_right, mem_union, or_imp, forall_and] /-! #### inter -/ theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty := not_disjoint_iff.trans <| by simp [Finset.Nonempty] alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by rw [← not_disjoint_iff_nonempty_inter] exact em _ omit [DecidableEq α] in theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) : Disjoint s t ↔ s = ∅ := disjoint_of_le_iff_left_eq_bot h lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} : s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _), not_disjoint_iff_nonempty_inter] end Lattice instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le /-! ### erase -/ section Erase variable [DecidableEq α] {s t u v : Finset α} {a b : α} @[simp] theorem erase_empty (a : α) : erase ∅ a = ∅ := rfl protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty := (hs.exists_ne a).imp <| by aesop @[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)] refine ⟨?_, fun hs ↦ hs.exists_ne a⟩ rintro ⟨b, hb, hba⟩ exact ⟨_, hb, _, ha, hba⟩ @[simp] theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by ext x simp @[simp] theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a := ext fun x => by simp +contextual only [mem_erase, mem_insert, and_congr_right_iff, false_or, iff_self, imp_true_iff] theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by rw [erase_insert_eq_erase, erase_eq_of_not_mem h] theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) : erase (insert a s) b = insert a (erase s b) := ext fun x => by have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h simp only [mem_erase, mem_insert, and_or_left, this] theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) : erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by simp only [cons_eq_insert, erase_insert_of_ne hb] @[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s := ext fun x => by simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and] apply or_iff_right_of_imp rintro rfl exact h lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by aesop lemma insert_erase_invOn : Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} := ⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩ theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s := calc s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _ _ = _ := insert_erase h theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩ obtain ⟨a, ht, hs⟩ := not_subset.1 h.2 exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩ theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s := ssubset_iff_exists_subset_erase.2 ⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩ theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h] theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp] exact forall_congr' fun x => forall_swap theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s := subset_insert_iff.1 <| Subset.rfl theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) := subset_insert_iff.2 <| Subset.rfl theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by rw [subset_insert_iff, erase_eq_of_not_mem h] theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by rw [← subset_insert_iff, insert_eq_of_mem h] theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a := fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h] end Erase lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) : ∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by classical obtain ⟨a, ha, b, hb, hab⟩ := hs have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩ refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;> simp [insert_erase this, insert_erase ha, *] /-! ### sdiff -/ section Sdiff variable [DecidableEq α] {s t u v : Finset α} {a b : α} lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by ext; aesop -- TODO: Do we want to delete this lemma and `Finset.disjUnion_singleton`, -- or instead add `Finset.union_singleton`/`Finset.singleton_union`? theorem sdiff_singleton_eq_erase (a : α) (s : Finset α) : s \ {a} = erase s a := by ext rw [mem_erase, mem_sdiff, mem_singleton, and_comm] -- This lemma matches `Finset.insert_eq` in functionality. theorem erase_eq (s : Finset α) (a : α) : s.erase a = s \ {a} := (sdiff_singleton_eq_erase _ _).symm theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by simp_rw [erase_eq, disjoint_sdiff_comm] lemma disjoint_insert_erase (ha : a ∉ t) : Disjoint (s.erase a) (insert a t) ↔ Disjoint s t := by rw [disjoint_erase_comm, erase_insert ha] lemma disjoint_erase_insert (ha : a ∉ s) : Disjoint (insert a s) (t.erase a) ↔ Disjoint s t := by rw [← disjoint_erase_comm, erase_insert ha] theorem disjoint_of_erase_left (ha : a ∉ t) (hst : Disjoint (s.erase a) t) : Disjoint s t := by rw [← erase_insert ha, ← disjoint_erase_comm, disjoint_insert_right] exact ⟨not_mem_erase _ _, hst⟩ theorem disjoint_of_erase_right (ha : a ∉ s) (hst : Disjoint s (t.erase a)) : Disjoint s t := by rw [← erase_insert ha, disjoint_erase_comm, disjoint_insert_left] exact ⟨not_mem_erase _ _, hst⟩ theorem inter_erase (a : α) (s t : Finset α) : s ∩ t.erase a = (s ∩ t).erase a := by simp only [erase_eq, inter_sdiff_assoc] @[simp] theorem erase_inter (a : α) (s t : Finset α) : s.erase a ∩ t = (s ∩ t).erase a := by simpa only [inter_comm t] using inter_erase a t s theorem erase_sdiff_comm (s t : Finset α) (a : α) : s.erase a \ t = (s \ t).erase a := by simp_rw [erase_eq, sdiff_right_comm] theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by rw [erase_inter, inter_erase] theorem erase_union_distrib (s t : Finset α) (a : α) : (s ∪ t).erase a = s.erase a ∪ t.erase a := by simp_rw [erase_eq, union_sdiff_distrib] theorem insert_inter_distrib (s t : Finset α) (a : α) : insert a (s ∩ t) = insert a s ∩ insert a t := by simp_rw [insert_eq, union_inter_distrib_left] theorem erase_sdiff_distrib (s t : Finset α) (a : α) : (s \ t).erase a = s.erase a \ t.erase a := by simp_rw [erase_eq, sdiff_sdiff, sup_sdiff_eq_sup le_rfl, sup_comm] theorem erase_union_of_mem (ha : a ∈ t) (s : Finset α) : s.erase a ∪ t = s ∪ t := by rw [← insert_erase (mem_union_right s ha), erase_union_distrib, ← union_insert, insert_erase ha] theorem union_erase_of_mem (ha : a ∈ s) (t : Finset α) : s ∪ t.erase a = s ∪ t := by rw [← insert_erase (mem_union_left t ha), erase_union_distrib, ← insert_union, insert_erase ha] theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)] theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib, inter_comm] theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) : insert x (s \ insert x t) = s \ t := by rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)] theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq, union_comm] theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq] theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff] --TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra` theorem sdiff_disjoint : Disjoint (t \ s) s := disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2 theorem disjoint_sdiff : Disjoint s (t \ s) := sdiff_disjoint.symm theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) := disjoint_of_subset_right inter_subset_right sdiff_disjoint end Sdiff /-! ### attach -/ @[simp] theorem attach_empty : attach (∅ : Finset α) = ∅ := rfl @[simp] theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by simp [Finset.Nonempty] @[aesop safe apply (rule_sets := [finsetNonempty])] protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff @[simp] theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by simp [eq_empty_iff_forall_not_mem] /-! ### filter -/ section Filter variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α} theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by classical ext x simp only [mem_singleton, forall_eq, mem_filter] split_ifs with h <;> by_cases h' : x = a <;> simp [h, h'] theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) : filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) := eq_of_veq <| Multiset.filter_cons_of_pos s.val hp theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) : filter p (cons a s ha) = filter p s := eq_of_veq <| Multiset.filter_cons_of_neg s.val hp theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] : Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by constructor <;> simp +contextual [disjoint_left] theorem disjoint_filter_filter' (s t : Finset α) {p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) : Disjoint (s.filter p) (t.filter q) := by simp_rw [disjoint_left, mem_filter] rintro a ⟨_, hp⟩ ⟨_, hq⟩ rw [Pi.disjoint_iff] at h simpa [hp, hq] using h a theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] : Disjoint (s.filter p) (t.filter fun a => ¬p a) := disjoint_filter_filter' s t disjoint_compl_right theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) : filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) := eq_of_veq <| Multiset.filter_add _ _ _ theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) : filter p (cons a s ha) = if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by split_ifs with h · rw [filter_cons_of_pos _ _ _ ha h] · rw [filter_cons_of_neg _ _ _ ha h] section variable [DecidableEq α] theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p := ext fun _ => by simp only [mem_filter, mem_union, or_and_right] theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x := ext fun x => by simp [mem_filter, mem_union, ← and_or_left] theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] : (s.filter fun i => i ∈ t) = s ∩ t := ext fun i => by simp [mem_filter, mem_inter] theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by ext simp [mem_filter, mem_inter, and_assoc] theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by ext simp only [mem_inter, mem_filter, and_right_comm] theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by rw [inter_comm, filter_inter, inter_comm] theorem filter_insert (a : α) (s : Finset α) : filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by ext x split_ifs with h <;> by_cases h' : x = a <;> simp [h, h'] theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by ext x simp only [and_assoc, mem_filter, iff_self, mem_erase] theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q := ext fun _ => by simp [mem_filter, mem_union, and_or_left] theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q := ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc] theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p := ext fun a => by simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or, Bool.not_eq_true, and_or_left, and_not_self, or_false] lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] : s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)] theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ := ext fun _ => by simp [mem_sdiff, mem_filter] theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) : ∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by classical refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩ · simp [filter_union_right, em] · intro x simp · intro x simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp] intro hx hx₂ exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩ -- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing -- on, e.g. `x ∈ s.filter (Eq b)`. /-- After filtering out everything that does not equal a given value, at most that value remains. This is equivalent to `filter_eq'` with the equality the other way. -/ theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) : s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by split_ifs with h · ext simp only [mem_filter, mem_singleton, decide_eq_true_eq] refine ⟨fun h => h.2.symm, ?_⟩ rintro rfl exact ⟨h, rfl⟩ · ext simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq] rintro m rfl exact h m /-- After filtering out everything that does not equal a given value, at most that value remains. This is equivalent to `filter_eq` with the equality the other way. -/ theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ := _root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b) theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => b ≠ a) = s.erase b := by ext simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not] tauto theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b := _root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b) theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) : s.filter p ∪ s.filter q = s := (filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) : (s.filter p ∪ s.filter fun a => ¬p a) = s := filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p end end Filter /-! ### range -/ section Range open Nat variable {n m l : ℕ} @[simp] theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by convert filter_eq (range n) m using 2 · ext rw [eq_comm] · simp end Range end Finset /-! ### dedup on list and multiset -/ namespace Multiset variable [DecidableEq α] {s t : Multiset α} @[simp] theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t := Finset.ext <| by simp @[simp] theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t := Finset.ext <| by simp @[simp] theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by ext; simp @[simp] theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 := Finset.val_inj.symm.trans Multiset.dedup_eq_zero @[simp] theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty] @[aesop safe apply (rule_sets := [finsetNonempty])] protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty @[simp] theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] : Multiset.toFinset (s.filter p) = s.toFinset.filter p := by ext; simp end Multiset namespace List variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β} {s : Finset α} {t : Set β} {t' : Finset β} @[simp] theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by ext simp @[simp] theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by ext simp @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff @[simp] theorem toFinset_filter (s : List α) (p : α → Bool) : (s.filter p).toFinset = s.toFinset.filter (p ·) := by ext; simp [List.mem_filter] end List namespace Finset section ToList @[simp] theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ := Multiset.toList_eq_nil.trans val_eq_zero theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp @[simp] theorem toList_empty : (∅ : Finset α).toList = [] := toList_eq_nil.mpr rfl theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] := mt toList_eq_nil.mp hs.ne_empty theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty := mt empty_toList.mp hs.ne_empty end ToList /-! ### choose -/ section Choose variable (p : α → Prop) [DecidablePred p] (l : Finset α) /-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of `l` satisfying `p` this unique element, as an element of the corresponding subtype. -/ def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } := Multiset.chooseX p l.val hp /-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of `l` satisfying `p` this unique element, as an element of the ambient type. -/ def choose (hp : ∃! a, a ∈ l ∧ p a) : α := chooseX p l hp theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) := (chooseX p l hp).property theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l := (choose_spec _ _ _).1 theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) := (choose_spec _ _ _).2 end Choose end Finset namespace Equiv variable [DecidableEq α] {s t : Finset α} open Finset /-- The disjoint union of finsets is a sum -/ def Finset.union (s t : Finset α) (h : Disjoint s t) : s ⊕ t ≃ (s ∪ t : Finset α) := Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm @[simp] theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) : Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ := rfl @[simp] theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) : Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ := rfl /-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/ def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) : ((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i := let e := Equiv.Finset.union s t h sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e) /-- A finset is equivalent to its coercion as a set. -/ def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where toFun a := ⟨a.1, mem_coe.2 a.2⟩ invFun a := ⟨a.1, mem_coe.1 a.2⟩ left_inv := fun _ ↦ rfl right_inv := fun _ ↦ rfl end Equiv namespace Multiset variable [DecidableEq α] @[simp] lemma toFinset_replicate (n : ℕ) (a : α) : (replicate n a).toFinset = if n = 0 then ∅ else {a} := by ext x simp only [mem_toFinset, Finset.mem_singleton, mem_replicate] split_ifs with hn <;> simp [hn] end Multiset
Mathlib/Data/Finset/Basic.lean
1,974
1,979
/- Copyright (c) 2020 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Algebra.Group.End import Mathlib.Data.Set.Function /-! # Fixed points of a self-map In this file we define * the predicate `IsFixedPt f x := f x = x`; * the set `fixedPoints f` of fixed points of a self-map `f`. We also prove some simple lemmas about `IsFixedPt` and `∘`, `iterate`, and `Semiconj`. ## Tags fixed point -/ open Equiv universe u v variable {α : Type u} {β : Type v} {f fa g : α → α} {x : α} {fb : β → β} {e : Perm α} namespace Function open Function (Commute) /-- Every point is a fixed point of `id`. -/ theorem isFixedPt_id (x : α) : IsFixedPt id x := (rfl :) /-- A function fixes every point iff it is the identity. -/ @[simp] theorem forall_isFixedPt_iff : (∀ x, IsFixedPt f x) ↔ f = id := ⟨funext, fun h ↦ h ▸ isFixedPt_id⟩ namespace IsFixedPt instance decidable [h : DecidableEq α] {f : α → α} {x : α} : Decidable (IsFixedPt f x) := h (f x) x /-- If `x` is a fixed point of `f`, then `f x = x`. This is useful, e.g., for `rw` or `simp`. -/ protected theorem eq (hf : IsFixedPt f x) : f x = x := hf /-- If `x` is a fixed point of `f` and `g`, then it is a fixed point of `f ∘ g`. -/ protected theorem comp (hf : IsFixedPt f x) (hg : IsFixedPt g x) : IsFixedPt (f ∘ g) x := calc f (g x) = f x := congr_arg f hg _ = x := hf /-- If `x` is a fixed point of `f`, then it is a fixed point of `f^[n]`. -/ protected theorem iterate (hf : IsFixedPt f x) (n : ℕ) : IsFixedPt f^[n] x := iterate_fixed hf n /-- If `x` is a fixed point of `f ∘ g` and `g`, then it is a fixed point of `f`. -/ theorem left_of_comp (hfg : IsFixedPt (f ∘ g) x) (hg : IsFixedPt g x) : IsFixedPt f x := calc f x = f (g x) := congr_arg f hg.symm _ = x := hfg /-- If `x` is a fixed point of `f` and `g` is a left inverse of `f`, then `x` is a fixed point of `g`. -/ theorem to_leftInverse (hf : IsFixedPt f x) (h : LeftInverse g f) : IsFixedPt g x := calc g x = g (f x) := congr_arg g hf.symm _ = x := h x /-- If `g` (semi)conjugates `fa` to `fb`, then it sends fixed points of `fa` to fixed points of `fb`. -/ protected theorem map {x : α} (hx : IsFixedPt fa x) {g : α → β} (h : Semiconj g fa fb) : IsFixedPt fb (g x) := calc fb (g x) = g (fa x) := (h.eq x).symm _ = g x := congr_arg g hx protected theorem apply {x : α} (hx : IsFixedPt f x) : IsFixedPt f (f x) := by convert hx theorem preimage_iterate {s : Set α} (h : IsFixedPt (Set.preimage f) s) (n : ℕ) : IsFixedPt (Set.preimage f^[n]) s := by rw [Set.preimage_iterate_eq] exact h.iterate n lemma image_iterate {s : Set α} (h : IsFixedPt (Set.image f) s) (n : ℕ) : IsFixedPt (Set.image f^[n]) s := Set.image_iterate_eq ▸ h.iterate n protected theorem equiv_symm (h : IsFixedPt e x) : IsFixedPt e.symm x := h.to_leftInverse e.leftInverse_symm protected theorem perm_inv (h : IsFixedPt e x) : IsFixedPt (⇑e⁻¹) x := h.equiv_symm protected theorem perm_pow (h : IsFixedPt e x) (n : ℕ) : IsFixedPt (⇑(e ^ n)) x := h.iterate _ protected theorem perm_zpow (h : IsFixedPt e x) : ∀ n : ℤ, IsFixedPt (⇑(e ^ n)) x | Int.ofNat _ => h.perm_pow _ | Int.negSucc n => (h.perm_pow <| n + 1).perm_inv end IsFixedPt @[simp] theorem Injective.isFixedPt_apply_iff (hf : Injective f) {x : α} : IsFixedPt f (f x) ↔ IsFixedPt f x := ⟨fun h => hf h.eq, IsFixedPt.apply⟩ /-- The set of fixed points of a map `f : α → α`. -/ def fixedPoints (f : α → α) : Set α := { x : α | IsFixedPt f x } instance fixedPoints.decidable [DecidableEq α] (f : α → α) (x : α) : Decidable (x ∈ fixedPoints f) := IsFixedPt.decidable @[simp] theorem mem_fixedPoints : x ∈ fixedPoints f ↔ IsFixedPt f x := Iff.rfl theorem mem_fixedPoints_iff {α : Type*} {f : α → α} {x : α} : x ∈ fixedPoints f ↔ f x = x := by rfl @[simp] theorem fixedPoints_id : fixedPoints (@id α) = Set.univ := Set.ext fun _ => by simpa using isFixedPt_id _ theorem fixedPoints_subset_range : fixedPoints f ⊆ Set.range f := fun x hx => ⟨x, hx⟩ /-- If `g` semiconjugates `fa` to `fb`, then it sends fixed points of `fa` to fixed points of `fb`. -/ theorem Semiconj.mapsTo_fixedPoints {g : α → β} (h : Semiconj g fa fb) : Set.MapsTo g (fixedPoints fa) (fixedPoints fb) := fun _ hx => hx.map h /-- Any two maps `f : α → β` and `g : β → α` are inverse of each other on the sets of fixed points of `f ∘ g` and `g ∘ f`, respectively. -/ theorem invOn_fixedPoints_comp (f : α → β) (g : β → α) : Set.InvOn f g (fixedPoints <| f ∘ g) (fixedPoints <| g ∘ f) := ⟨fun _ => id, fun _ => id⟩ /-- Any map `f` sends fixed points of `g ∘ f` to fixed points of `f ∘ g`. -/
theorem mapsTo_fixedPoints_comp (f : α → β) (g : β → α) : Set.MapsTo f (fixedPoints <| g ∘ f) (fixedPoints <| f ∘ g) := fun _ hx => hx.map fun _ => rfl
Mathlib/Dynamics/FixedPoints/Basic.lean
146
147
/- Copyright (c) 2018 Robert Y. Lewis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Robert Y. Lewis, Chris Hughes, Daniel Weber -/ import Batteries.Data.Nat.Gcd import Mathlib.Algebra.GroupWithZero.Associated import Mathlib.Algebra.Ring.Divisibility.Basic import Mathlib.Algebra.Ring.Int.Defs import Mathlib.Data.ENat.Basic import Mathlib.Algebra.BigOperators.Group.Finset.Basic /-! # Multiplicity of a divisor For a commutative monoid, this file introduces the notion of multiplicity of a divisor and proves several basic results on it. ## Main definitions * `emultiplicity a b`: for two elements `a` and `b` of a commutative monoid returns the largest number `n` such that `a ^ n ∣ b` or infinity, written `⊤`, if `a ^ n ∣ b` for all natural numbers `n`. * `multiplicity a b`: a `ℕ`-valued version of `multiplicity`, defaulting for `1` instead of `⊤`. The reason for using `1` as a default value instead of `0` is to have `multiplicity_eq_zero_iff`. * `FiniteMultiplicity a b`: a predicate denoting that the multiplicity of `a` in `b` is finite. -/ assert_not_exists Field variable {α β : Type*} open Nat /-- `multiplicity.Finite a b` indicates that the multiplicity of `a` in `b` is finite. -/ abbrev FiniteMultiplicity [Monoid α] (a b : α) : Prop := ∃ n : ℕ, ¬a ^ (n + 1) ∣ b @[deprecated (since := "2024-11-30")] alias multiplicity.Finite := FiniteMultiplicity open scoped Classical in /-- `emultiplicity a b` returns the largest natural number `n` such that `a ^ n ∣ b`, as an `ℕ∞`. If `∀ n, a ^ n ∣ b` then it returns `⊤`. -/ noncomputable def emultiplicity [Monoid α] (a b : α) : ℕ∞ := if h : FiniteMultiplicity a b then Nat.find h else ⊤ /-- A `ℕ`-valued version of `emultiplicity`, returning `1` instead of `⊤`. -/ noncomputable def multiplicity [Monoid α] (a b : α) : ℕ := (emultiplicity a b).untopD 1 section Monoid variable [Monoid α] [Monoid β] {a b : α} @[simp] theorem emultiplicity_eq_top : emultiplicity a b = ⊤ ↔ ¬FiniteMultiplicity a b := by simp [emultiplicity] theorem emultiplicity_lt_top {a b : α} : emultiplicity a b < ⊤ ↔ FiniteMultiplicity a b := by simp [lt_top_iff_ne_top, emultiplicity_eq_top] theorem finiteMultiplicity_iff_emultiplicity_ne_top : FiniteMultiplicity a b ↔ emultiplicity a b ≠ ⊤ := by simp @[deprecated (since := "2024-11-30")] alias finite_iff_emultiplicity_ne_top := finiteMultiplicity_iff_emultiplicity_ne_top alias ⟨FiniteMultiplicity.emultiplicity_ne_top, _⟩ := finite_iff_emultiplicity_ne_top @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.emultiplicity_ne_top := FiniteMultiplicity.emultiplicity_ne_top @[deprecated (since := "2024-11-08")] alias Finite.emultiplicity_ne_top := FiniteMultiplicity.emultiplicity_ne_top theorem finiteMultiplicity_of_emultiplicity_eq_natCast {n : ℕ} (h : emultiplicity a b = n) : FiniteMultiplicity a b := by by_contra! nh rw [← emultiplicity_eq_top, h] at nh trivial @[deprecated (since := "2024-11-30")] alias finite_of_emultiplicity_eq_natCast := finiteMultiplicity_of_emultiplicity_eq_natCast theorem multiplicity_eq_of_emultiplicity_eq_some {n : ℕ} (h : emultiplicity a b = n) : multiplicity a b = n := by simp [multiplicity, h] rfl theorem emultiplicity_ne_of_multiplicity_ne {n : ℕ} : multiplicity a b ≠ n → emultiplicity a b ≠ n := mt multiplicity_eq_of_emultiplicity_eq_some theorem FiniteMultiplicity.emultiplicity_eq_multiplicity (h : FiniteMultiplicity a b) : emultiplicity a b = multiplicity a b := by cases hm : emultiplicity a b · simp [h] at hm rw [multiplicity_eq_of_emultiplicity_eq_some hm] @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.emultiplicity_eq_multiplicity := FiniteMultiplicity.emultiplicity_eq_multiplicity theorem FiniteMultiplicity.emultiplicity_eq_iff_multiplicity_eq {n : ℕ} (h : FiniteMultiplicity a b) : emultiplicity a b = n ↔ multiplicity a b = n := by simp [h.emultiplicity_eq_multiplicity] @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.emultiplicity_eq_iff_multiplicity_eq := FiniteMultiplicity.emultiplicity_eq_iff_multiplicity_eq theorem emultiplicity_eq_iff_multiplicity_eq_of_ne_one {n : ℕ} (h : n ≠ 1) : emultiplicity a b = n ↔ multiplicity a b = n := by constructor · exact multiplicity_eq_of_emultiplicity_eq_some · intro h₂ simpa [multiplicity, WithTop.untopD_eq_iff, h] using h₂ theorem emultiplicity_eq_zero_iff_multiplicity_eq_zero : emultiplicity a b = 0 ↔ multiplicity a b = 0 := emultiplicity_eq_iff_multiplicity_eq_of_ne_one zero_ne_one @[simp] theorem multiplicity_eq_one_of_not_finiteMultiplicity (h : ¬FiniteMultiplicity a b) : multiplicity a b = 1 := by simp [multiplicity, emultiplicity_eq_top.2 h] @[deprecated (since := "2024-11-30")] alias multiplicity_eq_one_of_not_finite := multiplicity_eq_one_of_not_finiteMultiplicity @[simp] theorem multiplicity_le_emultiplicity : multiplicity a b ≤ emultiplicity a b := by by_cases hf : FiniteMultiplicity a b · simp [hf.emultiplicity_eq_multiplicity] · simp [hf, emultiplicity_eq_top.2] @[simp] theorem multiplicity_eq_of_emultiplicity_eq {c d : β} (h : emultiplicity a b = emultiplicity c d) : multiplicity a b = multiplicity c d := by unfold multiplicity rw [h] theorem multiplicity_le_of_emultiplicity_le {n : ℕ} (h : emultiplicity a b ≤ n) : multiplicity a b ≤ n := by exact_mod_cast multiplicity_le_emultiplicity.trans h theorem FiniteMultiplicity.emultiplicity_le_of_multiplicity_le (hfin : FiniteMultiplicity a b) {n : ℕ} (h : multiplicity a b ≤ n) : emultiplicity a b ≤ n := by rw [emultiplicity_eq_multiplicity hfin] assumption_mod_cast @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.emultiplicity_le_of_multiplicity_le := FiniteMultiplicity.emultiplicity_le_of_multiplicity_le theorem le_emultiplicity_of_le_multiplicity {n : ℕ} (h : n ≤ multiplicity a b) : n ≤ emultiplicity a b := by exact_mod_cast (WithTop.coe_mono h).trans multiplicity_le_emultiplicity theorem FiniteMultiplicity.le_multiplicity_of_le_emultiplicity (hfin : FiniteMultiplicity a b) {n : ℕ} (h : n ≤ emultiplicity a b) : n ≤ multiplicity a b := by rw [emultiplicity_eq_multiplicity hfin] at h assumption_mod_cast @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.le_multiplicity_of_le_emultiplicity := FiniteMultiplicity.le_multiplicity_of_le_emultiplicity theorem multiplicity_lt_of_emultiplicity_lt {n : ℕ} (h : emultiplicity a b < n) : multiplicity a b < n := by exact_mod_cast multiplicity_le_emultiplicity.trans_lt h theorem FiniteMultiplicity.emultiplicity_lt_of_multiplicity_lt (hfin : FiniteMultiplicity a b) {n : ℕ} (h : multiplicity a b < n) : emultiplicity a b < n := by rw [emultiplicity_eq_multiplicity hfin] assumption_mod_cast @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.emultiplicity_lt_of_multiplicity_lt := FiniteMultiplicity.emultiplicity_lt_of_multiplicity_lt theorem lt_emultiplicity_of_lt_multiplicity {n : ℕ} (h : n < multiplicity a b) : n < emultiplicity a b := by exact_mod_cast (WithTop.coe_strictMono h).trans_le multiplicity_le_emultiplicity theorem FiniteMultiplicity.lt_multiplicity_of_lt_emultiplicity (hfin : FiniteMultiplicity a b) {n : ℕ} (h : n < emultiplicity a b) : n < multiplicity a b := by rw [emultiplicity_eq_multiplicity hfin] at h assumption_mod_cast @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.lt_multiplicity_of_lt_emultiplicity := FiniteMultiplicity.lt_multiplicity_of_lt_emultiplicity theorem emultiplicity_pos_iff : 0 < emultiplicity a b ↔ 0 < multiplicity a b := by simp [pos_iff_ne_zero, pos_iff_ne_zero, emultiplicity_eq_zero_iff_multiplicity_eq_zero] theorem FiniteMultiplicity.def : FiniteMultiplicity a b ↔ ∃ n : ℕ, ¬a ^ (n + 1) ∣ b := Iff.rfl @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.def := FiniteMultiplicity.def theorem FiniteMultiplicity.not_dvd_of_one_right : FiniteMultiplicity a 1 → ¬a ∣ 1 := fun ⟨n, hn⟩ ⟨d, hd⟩ => hn ⟨d ^ (n + 1), (pow_mul_pow_eq_one (n + 1) hd.symm).symm⟩ @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.not_dvd_of_one_right := FiniteMultiplicity.not_dvd_of_one_right @[norm_cast] theorem Int.natCast_emultiplicity (a b : ℕ) : emultiplicity (a : ℤ) (b : ℤ) = emultiplicity a b := by unfold emultiplicity FiniteMultiplicity congr! <;> norm_cast @[norm_cast] theorem Int.natCast_multiplicity (a b : ℕ) : multiplicity (a : ℤ) (b : ℤ) = multiplicity a b := multiplicity_eq_of_emultiplicity_eq (natCast_emultiplicity a b) theorem FiniteMultiplicity.not_iff_forall : ¬FiniteMultiplicity a b ↔ ∀ n : ℕ, a ^ n ∣ b := ⟨fun h n => Nat.casesOn n (by rw [_root_.pow_zero] exact one_dvd _) (by simpa [FiniteMultiplicity] using h), by simp [FiniteMultiplicity, multiplicity]; tauto⟩ @[deprecated (since := "2024-11-30")]
alias multiplicity.Finite.not_iff_forall := FiniteMultiplicity.not_iff_forall theorem FiniteMultiplicity.not_unit (h : FiniteMultiplicity a b) : ¬IsUnit a := let ⟨n, hn⟩ := h hn ∘ IsUnit.dvd ∘ IsUnit.pow (n + 1) @[deprecated (since := "2024-11-30")] alias multiplicity.Finite.not_unit := FiniteMultiplicity.not_unit theorem FiniteMultiplicity.mul_left {c : α} :
Mathlib/RingTheory/Multiplicity.lean
233
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/- 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.ChartedSpace /-! # Local properties invariant under a groupoid We study properties of a triple `(g, s, x)` where `g` is a function between two spaces `H` and `H'`, `s` is a subset of `H` and `x` is a point of `H`. Our goal is to register how such a property should behave to make sense in charted spaces modelled on `H` and `H'`. The main examples we have in mind are the properties "`g` is differentiable at `x` within `s`", or "`g` is smooth at `x` within `s`". We want to develop general results that, when applied in these specific situations, say that the notion of smooth function in a manifold behaves well under restriction, intersection, is local, and so on. ## Main definitions * `LocalInvariantProp G G' P` says that a property `P` of a triple `(g, s, x)` is local, and invariant under composition by elements of the groupoids `G` and `G'` of `H` and `H'` respectively. * `ChartedSpace.LiftPropWithinAt` (resp. `LiftPropAt`, `LiftPropOn` and `LiftProp`): given a property `P` of `(g, s, x)` where `g : H → H'`, define the corresponding property for functions `M → M'` where `M` and `M'` are charted spaces modelled respectively on `H` and `H'`. We define these properties within a set at a point, or at a point, or on a set, or in the whole space. This lifting process (obtained by restricting to suitable chart domains) can always be done, but it only behaves well under locality and invariance assumptions. Given `hG : LocalInvariantProp G G' P`, we deduce many properties of the lifted property on the charted spaces. For instance, `hG.liftPropWithinAt_inter` says that `P g s x` is equivalent to `P g (s ∩ t) x` whenever `t` is a neighborhood of `x`. ## Implementation notes We do not use dot notation for properties of the lifted property. For instance, we have `hG.liftPropWithinAt_congr` saying that if `LiftPropWithinAt P g s x` holds, and `g` and `g'` coincide on `s`, then `LiftPropWithinAt P g' s x` holds. We can't call it `LiftPropWithinAt.congr` as it is in the namespace associated to `LocalInvariantProp`, not in the one for `LiftPropWithinAt`. -/ noncomputable section open Set Filter TopologicalSpace open scoped Manifold Topology variable {H M H' M' X : Type*} variable [TopologicalSpace H] [TopologicalSpace M] [ChartedSpace H M] variable [TopologicalSpace H'] [TopologicalSpace M'] [ChartedSpace H' M'] variable [TopologicalSpace X] namespace StructureGroupoid variable (G : StructureGroupoid H) (G' : StructureGroupoid H') /-- Structure recording good behavior of a property of a triple `(f, s, x)` where `f` is a function, `s` a set and `x` a point. Good behavior here means locality and invariance under given groupoids (both in the source and in the target). Given such a good behavior, the lift of this property to charted spaces admitting these groupoids will inherit the good behavior. -/ structure LocalInvariantProp (P : (H → H') → Set H → H → Prop) : Prop where is_local : ∀ {s x u} {f : H → H'}, IsOpen u → x ∈ u → (P f s x ↔ P f (s ∩ u) x) right_invariance' : ∀ {s x f} {e : PartialHomeomorph H H}, e ∈ G → x ∈ e.source → P f s x → P (f ∘ e.symm) (e.symm ⁻¹' s) (e x) congr_of_forall : ∀ {s x} {f g : H → H'}, (∀ y ∈ s, f y = g y) → f x = g x → P f s x → P g s x left_invariance' : ∀ {s x f} {e' : PartialHomeomorph H' H'}, e' ∈ G' → s ⊆ f ⁻¹' e'.source → f x ∈ e'.source → P f s x → P (e' ∘ f) s x variable {G G'} {P : (H → H') → Set H → H → Prop} variable (hG : G.LocalInvariantProp G' P) include hG namespace LocalInvariantProp theorem congr_set {s t : Set H} {x : H} {f : H → H'} (hu : s =ᶠ[𝓝 x] t) : P f s x ↔ P f t x := by obtain ⟨o, host, ho, hxo⟩ := mem_nhds_iff.mp hu.mem_iff simp_rw [subset_def, mem_setOf, ← and_congr_left_iff, ← mem_inter_iff, ← Set.ext_iff] at host rw [hG.is_local ho hxo, host, ← hG.is_local ho hxo] theorem is_local_nhds {s u : Set H} {x : H} {f : H → H'} (hu : u ∈ 𝓝[s] x) : P f s x ↔ P f (s ∩ u) x := hG.congr_set <| mem_nhdsWithin_iff_eventuallyEq.mp hu theorem congr_iff_nhdsWithin {s : Set H} {x : H} {f g : H → H'} (h1 : f =ᶠ[𝓝[s] x] g) (h2 : f x = g x) : P f s x ↔ P g s x := by simp_rw [hG.is_local_nhds h1] exact ⟨hG.congr_of_forall (fun y hy ↦ hy.2) h2, hG.congr_of_forall (fun y hy ↦ hy.2.symm) h2.symm⟩ theorem congr_nhdsWithin {s : Set H} {x : H} {f g : H → H'} (h1 : f =ᶠ[𝓝[s] x] g) (h2 : f x = g x) (hP : P f s x) : P g s x := (hG.congr_iff_nhdsWithin h1 h2).mp hP theorem congr_nhdsWithin' {s : Set H} {x : H} {f g : H → H'} (h1 : f =ᶠ[𝓝[s] x] g) (h2 : f x = g x) (hP : P g s x) : P f s x := (hG.congr_iff_nhdsWithin h1 h2).mpr hP theorem congr_iff {s : Set H} {x : H} {f g : H → H'} (h : f =ᶠ[𝓝 x] g) : P f s x ↔ P g s x := hG.congr_iff_nhdsWithin (mem_nhdsWithin_of_mem_nhds h) (mem_of_mem_nhds h :) theorem congr {s : Set H} {x : H} {f g : H → H'} (h : f =ᶠ[𝓝 x] g) (hP : P f s x) : P g s x := (hG.congr_iff h).mp hP theorem congr' {s : Set H} {x : H} {f g : H → H'} (h : f =ᶠ[𝓝 x] g) (hP : P g s x) : P f s x := hG.congr h.symm hP theorem left_invariance {s : Set H} {x : H} {f : H → H'} {e' : PartialHomeomorph H' H'} (he' : e' ∈ G') (hfs : ContinuousWithinAt f s x) (hxe' : f x ∈ e'.source) : P (e' ∘ f) s x ↔ P f s x := by have h2f := hfs.preimage_mem_nhdsWithin (e'.open_source.mem_nhds hxe') have h3f := ((e'.continuousAt hxe').comp_continuousWithinAt hfs).preimage_mem_nhdsWithin <| e'.symm.open_source.mem_nhds <| e'.mapsTo hxe' constructor · intro h rw [hG.is_local_nhds h3f] at h have h2 := hG.left_invariance' (G'.symm he') inter_subset_right (e'.mapsTo hxe') h rw [← hG.is_local_nhds h3f] at h2 refine hG.congr_nhdsWithin ?_ (e'.left_inv hxe') h2 exact eventually_of_mem h2f fun x' ↦ e'.left_inv · simp_rw [hG.is_local_nhds h2f] exact hG.left_invariance' he' inter_subset_right hxe' theorem right_invariance {s : Set H} {x : H} {f : H → H'} {e : PartialHomeomorph H H} (he : e ∈ G) (hxe : x ∈ e.source) : P (f ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P f s x := by refine ⟨fun h ↦ ?_, hG.right_invariance' he hxe⟩ have := hG.right_invariance' (G.symm he) (e.mapsTo hxe) h rw [e.symm_symm, e.left_inv hxe] at this refine hG.congr ?_ ((hG.congr_set ?_).mp this) · refine eventually_of_mem (e.open_source.mem_nhds hxe) fun x' hx' ↦ ?_ simp_rw [Function.comp_apply, e.left_inv hx'] · rw [eventuallyEq_set] refine eventually_of_mem (e.open_source.mem_nhds hxe) fun x' hx' ↦ ?_ simp_rw [mem_preimage, e.left_inv hx'] end LocalInvariantProp end StructureGroupoid namespace ChartedSpace /-- Given a property of germs of functions and sets in the model space, then one defines a corresponding property in a charted space, by requiring that it holds at the preferred chart at this point. (When the property is local and invariant, it will in fact hold using any chart, see `liftPropWithinAt_indep_chart`). We require continuity in the lifted property, as otherwise one single chart might fail to capture the behavior of the function. -/ @[mk_iff liftPropWithinAt_iff'] structure LiftPropWithinAt (P : (H → H') → Set H → H → Prop) (f : M → M') (s : Set M) (x : M) : Prop where continuousWithinAt : ContinuousWithinAt f s x prop : P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) ((chartAt H x).symm ⁻¹' s) (chartAt H x x) /-- Given a property of germs of functions and sets in the model space, then one defines a corresponding property of functions on sets in a charted space, by requiring that it holds around each point of the set, in the preferred charts. -/ def LiftPropOn (P : (H → H') → Set H → H → Prop) (f : M → M') (s : Set M) := ∀ x ∈ s, LiftPropWithinAt P f s x /-- Given a property of germs of functions and sets in the model space, then one defines a corresponding property of a function at a point in a charted space, by requiring that it holds in the preferred chart. -/ def LiftPropAt (P : (H → H') → Set H → H → Prop) (f : M → M') (x : M) := LiftPropWithinAt P f univ x theorem liftPropAt_iff {P : (H → H') → Set H → H → Prop} {f : M → M'} {x : M} : LiftPropAt P f x ↔ ContinuousAt f x ∧ P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) univ (chartAt H x x) := by rw [LiftPropAt, liftPropWithinAt_iff', continuousWithinAt_univ, preimage_univ] /-- Given a property of germs of functions and sets in the model space, then one defines a corresponding property of a function in a charted space, by requiring that it holds in the preferred chart around every point. -/ def LiftProp (P : (H → H') → Set H → H → Prop) (f : M → M') := ∀ x, LiftPropAt P f x theorem liftProp_iff {P : (H → H') → Set H → H → Prop} {f : M → M'} : LiftProp P f ↔ Continuous f ∧ ∀ x, P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) univ (chartAt H x x) := by simp_rw [LiftProp, liftPropAt_iff, forall_and, continuous_iff_continuousAt] end ChartedSpace open ChartedSpace namespace StructureGroupoid variable {G : StructureGroupoid H} {G' : StructureGroupoid H'} {e e' : PartialHomeomorph M H} {f f' : PartialHomeomorph M' H'} {P : (H → H') → Set H → H → Prop} {g g' : M → M'} {s t : Set M} {x : M} {Q : (H → H) → Set H → H → Prop} theorem liftPropWithinAt_univ : LiftPropWithinAt P g univ x ↔ LiftPropAt P g x := Iff.rfl theorem liftPropOn_univ : LiftPropOn P g univ ↔ LiftProp P g := by simp [LiftPropOn, LiftProp, LiftPropAt] theorem liftPropWithinAt_self {f : H → H'} {s : Set H} {x : H} : LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧ P f s x := liftPropWithinAt_iff' .. theorem liftPropWithinAt_self_source {f : H → M'} {s : Set H} {x : H} : LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧ P (chartAt H' (f x) ∘ f) s x := liftPropWithinAt_iff' .. theorem liftPropWithinAt_self_target {f : M → H'} : LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧ P (f ∘ (chartAt H x).symm) ((chartAt H x).symm ⁻¹' s) (chartAt H x x) := liftPropWithinAt_iff' .. namespace LocalInvariantProp section variable (hG : G.LocalInvariantProp G' P) include hG /-- `LiftPropWithinAt P f s x` is equivalent to a definition where we restrict the set we are considering to the domain of the charts at `x` and `f x`. -/ theorem liftPropWithinAt_iff {f : M → M'} : LiftPropWithinAt P f s x ↔ ContinuousWithinAt f s x ∧ P (chartAt H' (f x) ∘ f ∘ (chartAt H x).symm) ((chartAt H x).target ∩ (chartAt H x).symm ⁻¹' (s ∩ f ⁻¹' (chartAt H' (f x)).source)) (chartAt H x x) := by rw [liftPropWithinAt_iff'] refine and_congr_right fun hf ↦ hG.congr_set ?_ exact PartialHomeomorph.preimage_eventuallyEq_target_inter_preimage_inter hf (mem_chart_source H x) (chart_source_mem_nhds H' (f x)) theorem liftPropWithinAt_indep_chart_source_aux (g : M → H') (he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) (he' : e' ∈ G.maximalAtlas M) (xe' : x ∈ e'.source) : P (g ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P (g ∘ e'.symm) (e'.symm ⁻¹' s) (e' x) := by rw [← hG.right_invariance (compatible_of_mem_maximalAtlas he he')] swap; · simp only [xe, xe', mfld_simps] simp_rw [PartialHomeomorph.trans_apply, e.left_inv xe] rw [hG.congr_iff] · refine hG.congr_set ?_ refine (eventually_of_mem ?_ fun y (hy : y ∈ e'.symm ⁻¹' e.source) ↦ ?_).set_eq · refine (e'.symm.continuousAt <| e'.mapsTo xe').preimage_mem_nhds (e.open_source.mem_nhds ?_) simp_rw [e'.left_inv xe', xe] simp_rw [mem_preimage, PartialHomeomorph.coe_trans_symm, PartialHomeomorph.symm_symm, Function.comp_apply, e.left_inv hy] · refine ((e'.eventually_nhds' _ xe').mpr <| e.eventually_left_inverse xe).mono fun y hy ↦ ?_ simp only [mfld_simps] rw [hy] theorem liftPropWithinAt_indep_chart_target_aux2 (g : H → M') {x : H} {s : Set H} (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) (hf' : f' ∈ G'.maximalAtlas M') (xf' : g x ∈ f'.source) (hgs : ContinuousWithinAt g s x) : P (f ∘ g) s x ↔ P (f' ∘ g) s x := by have hcont : ContinuousWithinAt (f ∘ g) s x := (f.continuousAt xf).comp_continuousWithinAt hgs rw [← hG.left_invariance (compatible_of_mem_maximalAtlas hf hf') hcont (by simp only [xf, xf', mfld_simps])] refine hG.congr_iff_nhdsWithin ?_ (by simp only [xf, mfld_simps]) exact (hgs.eventually <| f.eventually_left_inverse xf).mono fun y ↦ congr_arg f' theorem liftPropWithinAt_indep_chart_target_aux {g : X → M'} {e : PartialHomeomorph X H} {x : X} {s : Set X} (xe : x ∈ e.source) (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) (hf' : f' ∈ G'.maximalAtlas M') (xf' : g x ∈ f'.source) (hgs : ContinuousWithinAt g s x) : P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P (f' ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by rw [← e.left_inv xe] at xf xf' hgs refine hG.liftPropWithinAt_indep_chart_target_aux2 (g ∘ e.symm) hf xf hf' xf' ?_ exact hgs.comp (e.symm.continuousAt <| e.mapsTo xe).continuousWithinAt Subset.rfl /-- If a property of a germ of function `g` on a pointed set `(s, x)` is invariant under the structure groupoid (by composition in the source space and in the target space), then expressing it in charted spaces does not depend on the element of the maximal atlas one uses both in the source and in the target manifolds, provided they are defined around `x` and `g x` respectively, and provided `g` is continuous within `s` at `x` (otherwise, the local behavior of `g` at `x` can not be captured with a chart in the target). -/ theorem liftPropWithinAt_indep_chart_aux (he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) (he' : e' ∈ G.maximalAtlas M) (xe' : x ∈ e'.source) (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) (hf' : f' ∈ G'.maximalAtlas M') (xf' : g x ∈ f'.source) (hgs : ContinuousWithinAt g s x) : P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) ↔ P (f' ∘ g ∘ e'.symm) (e'.symm ⁻¹' s) (e' x) := by rw [← Function.comp_assoc, hG.liftPropWithinAt_indep_chart_source_aux (f ∘ g) he xe he' xe', Function.comp_assoc, hG.liftPropWithinAt_indep_chart_target_aux xe' hf xf hf' xf' hgs] theorem liftPropWithinAt_indep_chart [HasGroupoid M G] [HasGroupoid M' G'] (he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) : LiftPropWithinAt P g s x ↔ ContinuousWithinAt g s x ∧ P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by simp only [liftPropWithinAt_iff'] exact and_congr_right <| hG.liftPropWithinAt_indep_chart_aux (chart_mem_maximalAtlas _ _) (mem_chart_source _ _) he xe (chart_mem_maximalAtlas _ _) (mem_chart_source _ _) hf xf /-- A version of `liftPropWithinAt_indep_chart`, only for the source. -/ theorem liftPropWithinAt_indep_chart_source [HasGroupoid M G] (he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) : LiftPropWithinAt P g s x ↔ LiftPropWithinAt P (g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by rw [liftPropWithinAt_self_source, liftPropWithinAt_iff', e.symm.continuousWithinAt_iff_continuousWithinAt_comp_right xe, e.symm_symm] refine and_congr Iff.rfl ?_ rw [Function.comp_apply, e.left_inv xe, ← Function.comp_assoc, hG.liftPropWithinAt_indep_chart_source_aux (chartAt _ (g x) ∘ g) (chart_mem_maximalAtlas G x) (mem_chart_source _ x) he xe, Function.comp_assoc] /-- A version of `liftPropWithinAt_indep_chart`, only for the target. -/ theorem liftPropWithinAt_indep_chart_target [HasGroupoid M' G'] (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) : LiftPropWithinAt P g s x ↔ ContinuousWithinAt g s x ∧ LiftPropWithinAt P (f ∘ g) s x := by rw [liftPropWithinAt_self_target, liftPropWithinAt_iff', and_congr_right_iff] intro hg simp_rw [(f.continuousAt xf).comp_continuousWithinAt hg, true_and] exact hG.liftPropWithinAt_indep_chart_target_aux (mem_chart_source _ _) (chart_mem_maximalAtlas _ _) (mem_chart_source _ _) hf xf hg /-- A version of `liftPropWithinAt_indep_chart`, that uses `LiftPropWithinAt` on both sides. -/ theorem liftPropWithinAt_indep_chart' [HasGroupoid M G] [HasGroupoid M' G'] (he : e ∈ G.maximalAtlas M) (xe : x ∈ e.source) (hf : f ∈ G'.maximalAtlas M') (xf : g x ∈ f.source) : LiftPropWithinAt P g s x ↔ ContinuousWithinAt g s x ∧ LiftPropWithinAt P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) (e x) := by rw [hG.liftPropWithinAt_indep_chart he xe hf xf, liftPropWithinAt_self, and_left_comm, Iff.comm, and_iff_right_iff_imp] intro h have h1 := (e.symm.continuousWithinAt_iff_continuousWithinAt_comp_right xe).mp h.1 have : ContinuousAt f ((g ∘ e.symm) (e x)) := by simp_rw [Function.comp, e.left_inv xe, f.continuousAt xf] exact this.comp_continuousWithinAt h1 theorem liftPropOn_indep_chart [HasGroupoid M G] [HasGroupoid M' G'] (he : e ∈ G.maximalAtlas M) (hf : f ∈ G'.maximalAtlas M') (h : LiftPropOn P g s) {y : H} (hy : y ∈ e.target ∩ e.symm ⁻¹' (s ∩ g ⁻¹' f.source)) : P (f ∘ g ∘ e.symm) (e.symm ⁻¹' s) y := by convert ((hG.liftPropWithinAt_indep_chart he (e.symm_mapsTo hy.1) hf hy.2.2).1 (h _ hy.2.1)).2 rw [e.right_inv hy.1] theorem liftPropWithinAt_inter' (ht : t ∈ 𝓝[s] x) : LiftPropWithinAt P g (s ∩ t) x ↔ LiftPropWithinAt P g s x := by rw [liftPropWithinAt_iff', liftPropWithinAt_iff', continuousWithinAt_inter' ht, hG.congr_set] simp_rw [eventuallyEq_set, mem_preimage, (chartAt _ x).eventually_nhds' (fun x ↦ x ∈ s ∩ t ↔ x ∈ s) (mem_chart_source _ x)] exact (mem_nhdsWithin_iff_eventuallyEq.mp ht).symm.mem_iff theorem liftPropWithinAt_inter (ht : t ∈ 𝓝 x) : LiftPropWithinAt P g (s ∩ t) x ↔ LiftPropWithinAt P g s x := hG.liftPropWithinAt_inter' (mem_nhdsWithin_of_mem_nhds ht) theorem liftPropWithinAt_congr_set (hu : s =ᶠ[𝓝 x] t) : LiftPropWithinAt P g s x ↔ LiftPropWithinAt P g t x := by rw [← hG.liftPropWithinAt_inter (s := s) hu, ← hG.liftPropWithinAt_inter (s := t) hu, ← eq_iff_iff] congr 1 aesop theorem liftPropAt_of_liftPropWithinAt (h : LiftPropWithinAt P g s x) (hs : s ∈ 𝓝 x) : LiftPropAt P g x := by rwa [← univ_inter s, hG.liftPropWithinAt_inter hs] at h theorem liftPropWithinAt_of_liftPropAt_of_mem_nhds (h : LiftPropAt P g x) (hs : s ∈ 𝓝 x) : LiftPropWithinAt P g s x := by rwa [← univ_inter s, hG.liftPropWithinAt_inter hs] theorem liftPropOn_of_locally_liftPropOn (h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ LiftPropOn P g (s ∩ u)) : LiftPropOn P g s := by intro x hx rcases h x hx with ⟨u, u_open, xu, hu⟩ have := hu x ⟨hx, xu⟩ rwa [hG.liftPropWithinAt_inter] at this exact u_open.mem_nhds xu theorem liftProp_of_locally_liftPropOn (h : ∀ x, ∃ u, IsOpen u ∧ x ∈ u ∧ LiftPropOn P g u) : LiftProp P g := by rw [← liftPropOn_univ] refine hG.liftPropOn_of_locally_liftPropOn fun x _ ↦ ?_ simp [h x] theorem liftPropWithinAt_congr_of_eventuallyEq (h : LiftPropWithinAt P g s x) (h₁ : g' =ᶠ[𝓝[s] x] g) (hx : g' x = g x) : LiftPropWithinAt P g' s x := by refine ⟨h.1.congr_of_eventuallyEq h₁ hx, ?_⟩ refine hG.congr_nhdsWithin' ?_ (by simp_rw [Function.comp_apply, (chartAt H x).left_inv (mem_chart_source H x), hx]) h.2 simp_rw [EventuallyEq, Function.comp_apply] rw [(chartAt H x).eventually_nhdsWithin' (fun y ↦ chartAt H' (g' x) (g' y) = chartAt H' (g x) (g y)) (mem_chart_source H x)] exact h₁.mono fun y hy ↦ by rw [hx, hy] theorem liftPropWithinAt_congr_of_eventuallyEq_of_mem (h : LiftPropWithinAt P g s x) (h₁ : g' =ᶠ[𝓝[s] x] g) (h₂ : x ∈ s) : LiftPropWithinAt P g' s x := liftPropWithinAt_congr_of_eventuallyEq hG h h₁ (mem_of_mem_nhdsWithin h₂ h₁ :) theorem liftPropWithinAt_congr_iff_of_eventuallyEq (h₁ : g' =ᶠ[𝓝[s] x] g) (hx : g' x = g x) : LiftPropWithinAt P g' s x ↔ LiftPropWithinAt P g s x := ⟨fun h ↦ hG.liftPropWithinAt_congr_of_eventuallyEq h h₁.symm hx.symm, fun h ↦ hG.liftPropWithinAt_congr_of_eventuallyEq h h₁ hx⟩ theorem liftPropWithinAt_congr_iff (h₁ : ∀ y ∈ s, g' y = g y) (hx : g' x = g x) : LiftPropWithinAt P g' s x ↔ LiftPropWithinAt P g s x := hG.liftPropWithinAt_congr_iff_of_eventuallyEq (eventually_nhdsWithin_of_forall h₁) hx theorem liftPropWithinAt_congr_iff_of_mem (h₁ : ∀ y ∈ s, g' y = g y) (hx : x ∈ s) : LiftPropWithinAt P g' s x ↔ LiftPropWithinAt P g s x := hG.liftPropWithinAt_congr_iff_of_eventuallyEq (eventually_nhdsWithin_of_forall h₁) (h₁ _ hx) theorem liftPropWithinAt_congr (h : LiftPropWithinAt P g s x) (h₁ : ∀ y ∈ s, g' y = g y) (hx : g' x = g x) : LiftPropWithinAt P g' s x := (hG.liftPropWithinAt_congr_iff h₁ hx).mpr h theorem liftPropWithinAt_congr_of_mem (h : LiftPropWithinAt P g s x) (h₁ : ∀ y ∈ s, g' y = g y) (hx : x ∈ s) : LiftPropWithinAt P g' s x := (hG.liftPropWithinAt_congr_iff h₁ (h₁ _ hx)).mpr h theorem liftPropAt_congr_iff_of_eventuallyEq (h₁ : g' =ᶠ[𝓝 x] g) : LiftPropAt P g' x ↔ LiftPropAt P g x := hG.liftPropWithinAt_congr_iff_of_eventuallyEq (by simp_rw [nhdsWithin_univ, h₁]) h₁.eq_of_nhds theorem liftPropAt_congr_of_eventuallyEq (h : LiftPropAt P g x) (h₁ : g' =ᶠ[𝓝 x] g) : LiftPropAt P g' x := (hG.liftPropAt_congr_iff_of_eventuallyEq h₁).mpr h theorem liftPropOn_congr (h : LiftPropOn P g s) (h₁ : ∀ y ∈ s, g' y = g y) : LiftPropOn P g' s := fun x hx ↦ hG.liftPropWithinAt_congr (h x hx) h₁ (h₁ x hx) theorem liftPropOn_congr_iff (h₁ : ∀ y ∈ s, g' y = g y) : LiftPropOn P g' s ↔ LiftPropOn P g s := ⟨fun h ↦ hG.liftPropOn_congr h fun y hy ↦ (h₁ y hy).symm, fun h ↦ hG.liftPropOn_congr h h₁⟩ end theorem liftPropWithinAt_mono_of_mem_nhdsWithin (mono_of_mem_nhdsWithin : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, s ∈ 𝓝[t] x → P f s x → P f t x) (h : LiftPropWithinAt P g s x) (hst : s ∈ 𝓝[t] x) : LiftPropWithinAt P g t x := by simp only [liftPropWithinAt_iff'] at h ⊢ refine ⟨h.1.mono_of_mem_nhdsWithin hst, mono_of_mem_nhdsWithin ?_ h.2⟩ simp_rw [← mem_map, (chartAt H x).symm.map_nhdsWithin_preimage_eq (mem_chart_target H x), (chartAt H x).left_inv (mem_chart_source H x), hst] @[deprecated (since := "2024-10-31")] alias liftPropWithinAt_mono_of_mem := liftPropWithinAt_mono_of_mem_nhdsWithin theorem liftPropWithinAt_mono (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x) (h : LiftPropWithinAt P g s x) (hts : t ⊆ s) : LiftPropWithinAt P g t x := by refine ⟨h.1.mono hts, mono (fun y hy ↦ ?_) h.2⟩ simp only [mfld_simps] at hy simp only [hy, hts _, mfld_simps] theorem liftPropWithinAt_of_liftPropAt (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x) (h : LiftPropAt P g x) : LiftPropWithinAt P g s x := by rw [← liftPropWithinAt_univ] at h exact liftPropWithinAt_mono mono h (subset_univ _) theorem liftPropOn_mono (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x) (h : LiftPropOn P g t) (hst : s ⊆ t) : LiftPropOn P g s := fun x hx ↦ liftPropWithinAt_mono mono (h x (hst hx)) hst theorem liftPropOn_of_liftProp (mono : ∀ ⦃s x t⦄ ⦃f : H → H'⦄, t ⊆ s → P f s x → P f t x) (h : LiftProp P g) : LiftPropOn P g s := by rw [← liftPropOn_univ] at h exact liftPropOn_mono mono h (subset_univ _) theorem liftPropAt_of_mem_maximalAtlas [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) (hx : x ∈ e.source) : LiftPropAt Q e x := by simp_rw [LiftPropAt, hG.liftPropWithinAt_indep_chart he hx G.id_mem_maximalAtlas (mem_univ _), (e.continuousAt hx).continuousWithinAt, true_and] exact hG.congr' (e.eventually_right_inverse' hx) (hQ _) theorem liftPropOn_of_mem_maximalAtlas [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) : LiftPropOn Q e e.source := by intro x hx apply hG.liftPropWithinAt_of_liftPropAt_of_mem_nhds (hG.liftPropAt_of_mem_maximalAtlas hQ he hx) exact e.open_source.mem_nhds hx theorem liftPropAt_symm_of_mem_maximalAtlas [HasGroupoid M G] {x : H} (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) (hx : x ∈ e.target) : LiftPropAt Q e.symm x := by suffices h : Q (e ∘ e.symm) univ x by have : e.symm x ∈ e.source := by simp only [hx, mfld_simps] rw [LiftPropAt, hG.liftPropWithinAt_indep_chart G.id_mem_maximalAtlas (mem_univ _) he this] refine ⟨(e.symm.continuousAt hx).continuousWithinAt, ?_⟩ simp only [h, mfld_simps] exact hG.congr' (e.eventually_right_inverse hx) (hQ x) theorem liftPropOn_symm_of_mem_maximalAtlas [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) (he : e ∈ maximalAtlas M G) : LiftPropOn Q e.symm e.target := by intro x hx apply hG.liftPropWithinAt_of_liftPropAt_of_mem_nhds (hG.liftPropAt_symm_of_mem_maximalAtlas hQ he hx) exact e.open_target.mem_nhds hx theorem liftPropAt_chart [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) : LiftPropAt Q (chartAt (H := H) x) x := hG.liftPropAt_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x) (mem_chart_source H x) theorem liftPropOn_chart [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) : LiftPropOn Q (chartAt (H := H) x) (chartAt (H := H) x).source := hG.liftPropOn_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x) theorem liftPropAt_chart_symm [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) : LiftPropAt Q (chartAt (H := H) x).symm ((chartAt H x) x) := hG.liftPropAt_symm_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x) (by simp) theorem liftPropOn_chart_symm [HasGroupoid M G] (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) : LiftPropOn Q (chartAt (H := H) x).symm (chartAt H x).target := hG.liftPropOn_symm_of_mem_maximalAtlas hQ (chart_mem_maximalAtlas G x) theorem liftPropAt_of_mem_groupoid (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) {f : PartialHomeomorph H H} (hf : f ∈ G) {x : H} (hx : x ∈ f.source) : LiftPropAt Q f x := liftPropAt_of_mem_maximalAtlas hG hQ (G.mem_maximalAtlas_of_mem_groupoid hf) hx theorem liftPropOn_of_mem_groupoid (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) {f : PartialHomeomorph H H} (hf : f ∈ G) : LiftPropOn Q f f.source := liftPropOn_of_mem_maximalAtlas hG hQ (G.mem_maximalAtlas_of_mem_groupoid hf) theorem liftProp_id (hG : G.LocalInvariantProp G Q) (hQ : ∀ y, Q id univ y) : LiftProp Q (id : M → M) := by simp_rw [liftProp_iff, continuous_id, true_and] exact fun x ↦ hG.congr' ((chartAt H x).eventually_right_inverse <| mem_chart_target H x) (hQ _) theorem liftPropAt_iff_comp_subtype_val (hG : LocalInvariantProp G G' P) {U : Opens M} (f : M → M') (x : U) : LiftPropAt P f x ↔ LiftPropAt P (f ∘ Subtype.val) x := by simp only [LiftPropAt, liftPropWithinAt_iff'] congrm ?_ ∧ ?_ · simp_rw [continuousWithinAt_univ, U.isOpenEmbedding'.continuousAt_iff] · apply hG.congr_iff exact (U.chartAt_subtype_val_symm_eventuallyEq).fun_comp (chartAt H' (f x) ∘ f) theorem liftPropAt_iff_comp_inclusion (hG : LocalInvariantProp G G' P) {U V : Opens M} (hUV : U ≤ V) (f : V → M') (x : U) : LiftPropAt P f (Set.inclusion hUV x) ↔ LiftPropAt P (f ∘ Set.inclusion hUV : U → M') x := by simp only [LiftPropAt, liftPropWithinAt_iff'] congrm ?_ ∧ ?_ · simp_rw [continuousWithinAt_univ, (TopologicalSpace.Opens.isOpenEmbedding_of_le hUV).continuousAt_iff] · apply hG.congr_iff exact (TopologicalSpace.Opens.chartAt_inclusion_symm_eventuallyEq hUV).fun_comp (chartAt H' (f (Set.inclusion hUV x)) ∘ f) theorem liftProp_subtype_val {Q : (H → H) → Set H → H → Prop} (hG : LocalInvariantProp G G Q) (hQ : ∀ y, Q id univ y) (U : Opens M) : LiftProp Q (Subtype.val : U → M) := by intro x show LiftPropAt Q (id ∘ Subtype.val) x rw [← hG.liftPropAt_iff_comp_subtype_val] apply hG.liftProp_id hQ theorem liftProp_inclusion {Q : (H → H) → Set H → H → Prop} (hG : LocalInvariantProp G G Q) (hQ : ∀ y, Q id univ y) {U V : Opens M} (hUV : U ≤ V) : LiftProp Q (Opens.inclusion hUV : U → V) := by intro x show LiftPropAt Q (id ∘ Opens.inclusion hUV) x rw [← hG.liftPropAt_iff_comp_inclusion hUV] apply hG.liftProp_id hQ end LocalInvariantProp section LocalStructomorph variable (G) open PartialHomeomorph /-- A function from a model space `H` to itself is a local structomorphism, with respect to a structure groupoid `G` for `H`, relative to a set `s` in `H`, if for all points `x` in the set, the function agrees with a `G`-structomorphism on `s` in a neighbourhood of `x`. -/ def IsLocalStructomorphWithinAt (f : H → H) (s : Set H) (x : H) : Prop := x ∈ s → ∃ e : PartialHomeomorph H H, e ∈ G ∧ EqOn f e.toFun (s ∩ e.source) ∧ x ∈ e.source /-- For a groupoid `G` which is `ClosedUnderRestriction`, being a local structomorphism is a local invariant property. -/ theorem isLocalStructomorphWithinAt_localInvariantProp [ClosedUnderRestriction G] : LocalInvariantProp G G (IsLocalStructomorphWithinAt G) := { is_local := by intro s x u f hu hux constructor · rintro h hx rcases h hx.1 with ⟨e, heG, hef, hex⟩ have : s ∩ u ∩ e.source ⊆ s ∩ e.source := by mfld_set_tac exact ⟨e, heG, hef.mono this, hex⟩ · rintro h hx rcases h ⟨hx, hux⟩ with ⟨e, heG, hef, hex⟩ refine ⟨e.restr (interior u), ?_, ?_, ?_⟩ · exact closedUnderRestriction' heG isOpen_interior · have : s ∩ u ∩ e.source = s ∩ (e.source ∩ u) := by mfld_set_tac simpa only [this, interior_interior, hu.interior_eq, mfld_simps] using hef · simp only [*, interior_interior, hu.interior_eq, mfld_simps] right_invariance' := by
intro s x f e' he'G he'x h hx have hxs : x ∈ s := by simpa only [e'.left_inv he'x, mfld_simps] using hx rcases h hxs with ⟨e, heG, hef, hex⟩ refine ⟨e'.symm.trans e, G.trans (G.symm he'G) heG, ?_, ?_⟩ · intro y hy simp only [mfld_simps] at hy simp only [hef ⟨hy.1, hy.2.2⟩, mfld_simps]
Mathlib/Geometry/Manifold/LocalInvariantProperties.lean
579
585
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mitchell Lee -/ import Mathlib.Algebra.BigOperators.Group.Finset.Indicator import Mathlib.Data.Fintype.BigOperators import Mathlib.Topology.Algebra.InfiniteSum.Defs import Mathlib.Topology.Algebra.Monoid.Defs /-! # Lemmas on infinite sums and products in topological monoids This file contains many simple lemmas on `tsum`, `HasSum` etc, which are placed here in order to keep the basic file of definitions as short as possible. Results requiring a group (rather than monoid) structure on the target should go in `Group.lean`. -/ noncomputable section open Filter Finset Function Topology variable {α β γ : Type*} section HasProd variable [CommMonoid α] [TopologicalSpace α] variable {f g : β → α} {a b : α} /-- Constant one function has product `1` -/ @[to_additive "Constant zero function has sum `0`"] theorem hasProd_one : HasProd (fun _ ↦ 1 : β → α) 1 := by simp [HasProd, tendsto_const_nhds] @[to_additive] theorem hasProd_empty [IsEmpty β] : HasProd f 1 := by convert @hasProd_one α β _ _ @[to_additive] theorem multipliable_one : Multipliable (fun _ ↦ 1 : β → α) := hasProd_one.multipliable @[to_additive] theorem multipliable_empty [IsEmpty β] : Multipliable f := hasProd_empty.multipliable /-- See `multipliable_congr_cofinite` for a version allowing the functions to disagree on a finite set. -/ @[to_additive "See `summable_congr_cofinite` for a version allowing the functions to disagree on a finite set."] theorem multipliable_congr (hfg : ∀ b, f b = g b) : Multipliable f ↔ Multipliable g := iff_of_eq (congr_arg Multipliable <| funext hfg) /-- See `Multipliable.congr_cofinite` for a version allowing the functions to disagree on a finite set. -/ @[to_additive "See `Summable.congr_cofinite` for a version allowing the functions to disagree on a finite set."] theorem Multipliable.congr (hf : Multipliable f) (hfg : ∀ b, f b = g b) : Multipliable g := (multipliable_congr hfg).mp hf @[to_additive] lemma HasProd.congr_fun (hf : HasProd f a) (h : ∀ x : β, g x = f x) : HasProd g a := (funext h : g = f) ▸ hf @[to_additive] theorem HasProd.hasProd_of_prod_eq {g : γ → α} (h_eq : ∀ u : Finset γ, ∃ v : Finset β, ∀ v', v ⊆ v' → ∃ u', u ⊆ u' ∧ ∏ x ∈ u', g x = ∏ b ∈ v', f b) (hf : HasProd g a) : HasProd f a := le_trans (map_atTop_finset_prod_le_of_prod_eq h_eq) hf @[to_additive] theorem hasProd_iff_hasProd {g : γ → α} (h₁ : ∀ u : Finset γ, ∃ v : Finset β, ∀ v', v ⊆ v' → ∃ u', u ⊆ u' ∧ ∏ x ∈ u', g x = ∏ b ∈ v', f b) (h₂ : ∀ v : Finset β, ∃ u : Finset γ, ∀ u', u ⊆ u' → ∃ v', v ⊆ v' ∧ ∏ b ∈ v', f b = ∏ x ∈ u', g x) : HasProd f a ↔ HasProd g a := ⟨HasProd.hasProd_of_prod_eq h₂, HasProd.hasProd_of_prod_eq h₁⟩ @[to_additive] theorem Function.Injective.multipliable_iff {g : γ → β} (hg : Injective g) (hf : ∀ x ∉ Set.range g, f x = 1) : Multipliable (f ∘ g) ↔ Multipliable f := exists_congr fun _ ↦ hg.hasProd_iff hf @[to_additive (attr := simp)] theorem hasProd_extend_one {g : β → γ} (hg : Injective g) : HasProd (extend g f 1) a ↔ HasProd f a := by rw [← hg.hasProd_iff, extend_comp hg] exact extend_apply' _ _ @[to_additive (attr := simp)] theorem multipliable_extend_one {g : β → γ} (hg : Injective g) : Multipliable (extend g f 1) ↔ Multipliable f := exists_congr fun _ ↦ hasProd_extend_one hg @[to_additive] theorem hasProd_subtype_iff_mulIndicator {s : Set β} : HasProd (f ∘ (↑) : s → α) a ↔ HasProd (s.mulIndicator f) a := by rw [← Set.mulIndicator_range_comp, Subtype.range_coe, hasProd_subtype_iff_of_mulSupport_subset Set.mulSupport_mulIndicator_subset] @[to_additive] theorem multipliable_subtype_iff_mulIndicator {s : Set β} : Multipliable (f ∘ (↑) : s → α) ↔ Multipliable (s.mulIndicator f) := exists_congr fun _ ↦ hasProd_subtype_iff_mulIndicator @[to_additive (attr := simp)] theorem hasProd_subtype_mulSupport : HasProd (f ∘ (↑) : mulSupport f → α) a ↔ HasProd f a := hasProd_subtype_iff_of_mulSupport_subset <| Set.Subset.refl _ @[to_additive] protected theorem Finset.multipliable (s : Finset β) (f : β → α) : Multipliable (f ∘ (↑) : (↑s : Set β) → α) := (s.hasProd f).multipliable @[to_additive] protected theorem Set.Finite.multipliable {s : Set β} (hs : s.Finite) (f : β → α) : Multipliable (f ∘ (↑) : s → α) := by have := hs.toFinset.multipliable f rwa [hs.coe_toFinset] at this @[to_additive] theorem multipliable_of_finite_mulSupport (h : (mulSupport f).Finite) : Multipliable f := by apply multipliable_of_ne_finset_one (s := h.toFinset); simp @[to_additive] lemma Multipliable.of_finite [Finite β] {f : β → α} : Multipliable f := multipliable_of_finite_mulSupport <| Set.finite_univ.subset (Set.subset_univ _) @[to_additive] theorem hasProd_single {f : β → α} (b : β) (hf : ∀ (b') (_ : b' ≠ b), f b' = 1) : HasProd f (f b) := suffices HasProd f (∏ b' ∈ {b}, f b') by simpa using this hasProd_prod_of_ne_finset_one <| by simpa [hf] @[to_additive (attr := simp)] lemma hasProd_unique [Unique β] (f : β → α) : HasProd f (f default) := hasProd_single default (fun _ hb ↦ False.elim <| hb <| Unique.uniq ..) @[to_additive (attr := simp)] lemma hasProd_singleton (m : β) (f : β → α) : HasProd (({m} : Set β).restrict f) (f m) := hasProd_unique (Set.restrict {m} f) @[to_additive] theorem hasProd_ite_eq (b : β) [DecidablePred (· = b)] (a : α) : HasProd (fun b' ↦ if b' = b then a else 1) a := by convert @hasProd_single _ _ _ _ (fun b' ↦ if b' = b then a else 1) b (fun b' hb' ↦ if_neg hb') exact (if_pos rfl).symm @[to_additive] theorem Equiv.hasProd_iff (e : γ ≃ β) : HasProd (f ∘ e) a ↔ HasProd f a := e.injective.hasProd_iff <| by simp @[to_additive] theorem Function.Injective.hasProd_range_iff {g : γ → β} (hg : Injective g) : HasProd (fun x : Set.range g ↦ f x) a ↔ HasProd (f ∘ g) a := (Equiv.ofInjective g hg).hasProd_iff.symm @[to_additive] theorem Equiv.multipliable_iff (e : γ ≃ β) : Multipliable (f ∘ e) ↔ Multipliable f := exists_congr fun _ ↦ e.hasProd_iff @[to_additive] theorem Equiv.hasProd_iff_of_mulSupport {g : γ → α} (e : mulSupport f ≃ mulSupport g) (he : ∀ x : mulSupport f, g (e x) = f x) : HasProd f a ↔ HasProd g a := by have : (g ∘ (↑)) ∘ e = f ∘ (↑) := funext he rw [← hasProd_subtype_mulSupport, ← this, e.hasProd_iff, hasProd_subtype_mulSupport] @[to_additive] theorem hasProd_iff_hasProd_of_ne_one_bij {g : γ → α} (i : mulSupport g → β) (hi : Injective i) (hf : mulSupport f ⊆ Set.range i) (hfg : ∀ x, f (i x) = g x) : HasProd f a ↔ HasProd g a := Iff.symm <| Equiv.hasProd_iff_of_mulSupport (Equiv.ofBijective (fun x ↦ ⟨i x, fun hx ↦ x.coe_prop <| hfg x ▸ hx⟩) ⟨fun _ _ h ↦ hi <| Subtype.ext_iff.1 h, fun y ↦ (hf y.coe_prop).imp fun _ hx ↦ Subtype.ext hx⟩) hfg @[to_additive] theorem Equiv.multipliable_iff_of_mulSupport {g : γ → α} (e : mulSupport f ≃ mulSupport g) (he : ∀ x : mulSupport f, g (e x) = f x) : Multipliable f ↔ Multipliable g := exists_congr fun _ ↦ e.hasProd_iff_of_mulSupport he @[to_additive] protected theorem HasProd.map [CommMonoid γ] [TopologicalSpace γ] (hf : HasProd f a) {G} [FunLike G α γ] [MonoidHomClass G α γ] (g : G) (hg : Continuous g) : HasProd (g ∘ f) (g a) := by have : (g ∘ fun s : Finset β ↦ ∏ b ∈ s, f b) = fun s : Finset β ↦ ∏ b ∈ s, (g ∘ f) b := funext <| map_prod g _ unfold HasProd rw [← this] exact (hg.tendsto a).comp hf @[to_additive] protected theorem Topology.IsInducing.hasProd_iff [CommMonoid γ] [TopologicalSpace γ] {G} [FunLike G α γ] [MonoidHomClass G α γ] {g : G} (hg : IsInducing g) (f : β → α) (a : α) : HasProd (g ∘ f) (g a) ↔ HasProd f a := by simp_rw [HasProd, comp_apply, ← map_prod] exact hg.tendsto_nhds_iff.symm @[deprecated (since := "2024-10-28")] alias Inducing.hasProd_iff := IsInducing.hasProd_iff @[to_additive] protected theorem Multipliable.map [CommMonoid γ] [TopologicalSpace γ] (hf : Multipliable f) {G} [FunLike G α γ] [MonoidHomClass G α γ] (g : G) (hg : Continuous g) : Multipliable (g ∘ f) := (hf.hasProd.map g hg).multipliable @[to_additive] protected theorem Multipliable.map_iff_of_leftInverse [CommMonoid γ] [TopologicalSpace γ] {G G'} [FunLike G α γ] [MonoidHomClass G α γ] [FunLike G' γ α] [MonoidHomClass G' γ α] (g : G) (g' : G') (hg : Continuous g) (hg' : Continuous g') (hinv : Function.LeftInverse g' g) : Multipliable (g ∘ f) ↔ Multipliable f := ⟨fun h ↦ by have := h.map _ hg' rwa [← Function.comp_assoc, hinv.id] at this, fun h ↦ h.map _ hg⟩ @[to_additive] theorem Multipliable.map_tprod [CommMonoid γ] [TopologicalSpace γ] [T2Space γ] (hf : Multipliable f) {G} [FunLike G α γ] [MonoidHomClass G α γ] (g : G) (hg : Continuous g) : g (∏' i, f i) = ∏' i, g (f i) := (HasProd.tprod_eq (HasProd.map hf.hasProd g hg)).symm @[to_additive] lemma Topology.IsInducing.multipliable_iff_tprod_comp_mem_range [CommMonoid γ] [TopologicalSpace γ] [T2Space γ] {G} [FunLike G α γ] [MonoidHomClass G α γ] {g : G} (hg : IsInducing g) (f : β → α) : Multipliable f ↔ Multipliable (g ∘ f) ∧ ∏' i, g (f i) ∈ Set.range g := by constructor · intro hf constructor · exact hf.map g hg.continuous · use ∏' i, f i exact hf.map_tprod g hg.continuous · rintro ⟨hgf, a, ha⟩ use a have := hgf.hasProd simp_rw [comp_apply, ← ha] at this exact (hg.hasProd_iff f a).mp this @[deprecated (since := "2024-10-28")] alias Inducing.multipliable_iff_tprod_comp_mem_range := IsInducing.multipliable_iff_tprod_comp_mem_range /-- "A special case of `Multipliable.map_iff_of_leftInverse` for convenience" -/ @[to_additive "A special case of `Summable.map_iff_of_leftInverse` for convenience"] protected theorem Multipliable.map_iff_of_equiv [CommMonoid γ] [TopologicalSpace γ] {G} [EquivLike G α γ] [MulEquivClass G α γ] (g : G) (hg : Continuous g) (hg' : Continuous (EquivLike.inv g : γ → α)) : Multipliable (g ∘ f) ↔ Multipliable f := Multipliable.map_iff_of_leftInverse g (g : α ≃* γ).symm hg hg' (EquivLike.left_inv g) @[to_additive] theorem Function.Surjective.multipliable_iff_of_hasProd_iff {α' : Type*} [CommMonoid α'] [TopologicalSpace α'] {e : α' → α} (hes : Function.Surjective e) {f : β → α} {g : γ → α'} (he : ∀ {a}, HasProd f (e a) ↔ HasProd g a) : Multipliable f ↔ Multipliable g := hes.exists.trans <| exists_congr <| @he variable [ContinuousMul α] @[to_additive] theorem HasProd.mul (hf : HasProd f a) (hg : HasProd g b) : HasProd (fun b ↦ f b * g b) (a * b) := by dsimp only [HasProd] at hf hg ⊢ simp_rw [prod_mul_distrib] exact hf.mul hg @[to_additive] theorem Multipliable.mul (hf : Multipliable f) (hg : Multipliable g) : Multipliable fun b ↦ f b * g b := (hf.hasProd.mul hg.hasProd).multipliable @[to_additive] theorem hasProd_prod {f : γ → β → α} {a : γ → α} {s : Finset γ} : (∀ i ∈ s, HasProd (f i) (a i)) → HasProd (fun b ↦ ∏ i ∈ s, f i b) (∏ i ∈ s, a i) := by classical exact Finset.induction_on s (by simp only [hasProd_one, prod_empty, forall_true_iff]) <| by simp +contextual only [mem_insert, forall_eq_or_imp, not_false_iff, prod_insert, and_imp] exact fun x s _ IH hx h ↦ hx.mul (IH h) @[to_additive] theorem multipliable_prod {f : γ → β → α} {s : Finset γ} (hf : ∀ i ∈ s, Multipliable (f i)) : Multipliable fun b ↦ ∏ i ∈ s, f i b := (hasProd_prod fun i hi ↦ (hf i hi).hasProd).multipliable @[to_additive] theorem HasProd.mul_disjoint {s t : Set β} (hs : Disjoint s t) (ha : HasProd (f ∘ (↑) : s → α) a) (hb : HasProd (f ∘ (↑) : t → α) b) : HasProd (f ∘ (↑) : (s ∪ t : Set β) → α) (a * b) := by rw [hasProd_subtype_iff_mulIndicator] at * rw [Set.mulIndicator_union_of_disjoint hs] exact ha.mul hb @[to_additive] theorem hasProd_prod_disjoint {ι} (s : Finset ι) {t : ι → Set β} {a : ι → α} (hs : (s : Set ι).Pairwise (Disjoint on t)) (hf : ∀ i ∈ s, HasProd (f ∘ (↑) : t i → α) (a i)) : HasProd (f ∘ (↑) : (⋃ i ∈ s, t i) → α) (∏ i ∈ s, a i) := by simp_rw [hasProd_subtype_iff_mulIndicator] at * rw [Finset.mulIndicator_biUnion _ _ hs] exact hasProd_prod hf @[to_additive] theorem HasProd.mul_isCompl {s t : Set β} (hs : IsCompl s t) (ha : HasProd (f ∘ (↑) : s → α) a) (hb : HasProd (f ∘ (↑) : t → α) b) : HasProd f (a * b) := by simpa [← hs.compl_eq] using (hasProd_subtype_iff_mulIndicator.1 ha).mul (hasProd_subtype_iff_mulIndicator.1 hb) @[to_additive] theorem HasProd.mul_compl {s : Set β} (ha : HasProd (f ∘ (↑) : s → α) a) (hb : HasProd (f ∘ (↑) : (sᶜ : Set β) → α) b) : HasProd f (a * b) := ha.mul_isCompl isCompl_compl hb @[to_additive] theorem Multipliable.mul_compl {s : Set β} (hs : Multipliable (f ∘ (↑) : s → α)) (hsc : Multipliable (f ∘ (↑) : (sᶜ : Set β) → α)) : Multipliable f := (hs.hasProd.mul_compl hsc.hasProd).multipliable @[to_additive] theorem HasProd.compl_mul {s : Set β} (ha : HasProd (f ∘ (↑) : (sᶜ : Set β) → α) a) (hb : HasProd (f ∘ (↑) : s → α) b) : HasProd f (a * b) := ha.mul_isCompl isCompl_compl.symm hb @[to_additive] theorem Multipliable.compl_add {s : Set β} (hs : Multipliable (f ∘ (↑) : (sᶜ : Set β) → α)) (hsc : Multipliable (f ∘ (↑) : s → α)) : Multipliable f := (hs.hasProd.compl_mul hsc.hasProd).multipliable /-- Version of `HasProd.update` for `CommMonoid` rather than `CommGroup`. Rather than showing that `f.update` has a specific product in terms of `HasProd`, it gives a relationship between the products of `f` and `f.update` given that both exist. -/ @[to_additive "Version of `HasSum.update` for `AddCommMonoid` rather than `AddCommGroup`. Rather than showing that `f.update` has a specific sum in terms of `HasSum`, it gives a relationship between the sums of `f` and `f.update` given that both exist."] theorem HasProd.update' {α β : Type*} [TopologicalSpace α] [CommMonoid α] [T2Space α] [ContinuousMul α] [DecidableEq β] {f : β → α} {a a' : α} (hf : HasProd f a) (b : β) (x : α) (hf' : HasProd (update f b x) a') : a * x = a' * f b := by have : ∀ b', f b' * ite (b' = b) x 1 = update f b x b' * ite (b' = b) (f b) 1 := by intro b' split_ifs with hb' · simpa only [Function.update_apply, hb', eq_self_iff_true] using mul_comm (f b) x · simp only [Function.update_apply, hb', if_false] have h := hf.mul (hasProd_ite_eq b x) simp_rw [this] at h exact HasProd.unique h (hf'.mul (hasProd_ite_eq b (f b))) /-- Version of `hasProd_ite_div_hasProd` for `CommMonoid` rather than `CommGroup`. Rather than showing that the `ite` expression has a specific product in terms of `HasProd`, it gives a relationship between the products of `f` and `ite (n = b) 0 (f n)` given that both exist. -/ @[to_additive "Version of `hasSum_ite_sub_hasSum` for `AddCommMonoid` rather than `AddCommGroup`. Rather than showing that the `ite` expression has a specific sum in terms of `HasSum`, it gives a relationship between the sums of `f` and `ite (n = b) 0 (f n)` given that both exist."] theorem eq_mul_of_hasProd_ite {α β : Type*} [TopologicalSpace α] [CommMonoid α] [T2Space α] [ContinuousMul α] [DecidableEq β] {f : β → α} {a : α} (hf : HasProd f a) (b : β) (a' : α) (hf' : HasProd (fun n ↦ ite (n = b) 1 (f n)) a') : a = a' * f b := by refine (mul_one a).symm.trans (hf.update' b 1 ?_) convert hf' apply update_apply end HasProd section tprod variable [CommMonoid α] [TopologicalSpace α] {f g : β → α} @[to_additive] theorem tprod_congr_set_coe (f : β → α) {s t : Set β} (h : s = t) : ∏' x : s, f x = ∏' x : t, f x := by rw [h] @[to_additive] theorem tprod_congr_subtype (f : β → α) {P Q : β → Prop} (h : ∀ x, P x ↔ Q x) : ∏' x : {x // P x}, f x = ∏' x : {x // Q x}, f x := tprod_congr_set_coe f <| Set.ext h @[to_additive] theorem tprod_eq_finprod (hf : (mulSupport f).Finite) : ∏' b, f b = ∏ᶠ b, f b := by simp [tprod_def, multipliable_of_finite_mulSupport hf, hf] @[to_additive] theorem tprod_eq_prod' {s : Finset β} (hf : mulSupport f ⊆ s) : ∏' b, f b = ∏ b ∈ s, f b := by rw [tprod_eq_finprod (s.finite_toSet.subset hf), finprod_eq_prod_of_mulSupport_subset _ hf] @[to_additive] theorem tprod_eq_prod {s : Finset β} (hf : ∀ b ∉ s, f b = 1) : ∏' b, f b = ∏ b ∈ s, f b := tprod_eq_prod' <| mulSupport_subset_iff'.2 hf @[to_additive (attr := simp)] theorem tprod_one : ∏' _ : β, (1 : α) = 1 := by rw [tprod_eq_finprod] <;> simp @[to_additive (attr := simp)] theorem tprod_empty [IsEmpty β] : ∏' b, f b = 1 := by rw [tprod_eq_prod (s := (∅ : Finset β))] <;> simp @[to_additive] theorem tprod_congr {f g : β → α} (hfg : ∀ b, f b = g b) : ∏' b, f b = ∏' b, g b := congr_arg tprod (funext hfg) @[to_additive] theorem tprod_fintype [Fintype β] (f : β → α) : ∏' b, f b = ∏ b, f b := by apply tprod_eq_prod; simp @[to_additive] theorem prod_eq_tprod_mulIndicator (f : β → α) (s : Finset β) : ∏ x ∈ s, f x = ∏' x, Set.mulIndicator (↑s) f x := by rw [tprod_eq_prod' (Set.mulSupport_mulIndicator_subset), Finset.prod_mulIndicator_subset _ Finset.Subset.rfl] @[to_additive] theorem tprod_bool (f : Bool → α) : ∏' i : Bool, f i = f false * f true := by rw [tprod_fintype, Fintype.prod_bool, mul_comm] @[to_additive] theorem tprod_eq_mulSingle {f : β → α} (b : β) (hf : ∀ b' ≠ b, f b' = 1) : ∏' b, f b = f b := by rw [tprod_eq_prod (s := {b}), prod_singleton] exact fun b' hb' ↦ hf b' (by simpa using hb') @[to_additive] theorem tprod_tprod_eq_mulSingle (f : β → γ → α) (b : β) (c : γ) (hfb : ∀ b' ≠ b, f b' c = 1) (hfc : ∀ b', ∀ c' ≠ c, f b' c' = 1) : ∏' (b') (c'), f b' c' = f b c := calc ∏' (b') (c'), f b' c' = ∏' b', f b' c := tprod_congr fun b' ↦ tprod_eq_mulSingle _ (hfc b') _ = f b c := tprod_eq_mulSingle _ hfb @[to_additive (attr := simp)] theorem tprod_ite_eq (b : β) [DecidablePred (· = b)] (a : α) : ∏' b', (if b' = b then a else 1) = a := by rw [tprod_eq_mulSingle b] · simp · intro b' hb'; simp [hb'] @[to_additive (attr := simp)] theorem Finset.tprod_subtype (s : Finset β) (f : β → α) : ∏' x : { x // x ∈ s }, f x = ∏ x ∈ s, f x := by rw [← prod_attach]; exact tprod_fintype _ @[to_additive] theorem Finset.tprod_subtype' (s : Finset β) (f : β → α) : ∏' x : (s : Set β), f x = ∏ x ∈ s, f x := by simp @[to_additive (attr := simp)] theorem tprod_singleton (b : β) (f : β → α) : ∏' x : ({b} : Set β), f x = f b := by rw [← coe_singleton, Finset.tprod_subtype', prod_singleton] open scoped Classical in @[to_additive] theorem Function.Injective.tprod_eq {g : γ → β} (hg : Injective g) {f : β → α} (hf : mulSupport f ⊆ Set.range g) : ∏' c, f (g c) = ∏' b, f b := by have : mulSupport f = g '' mulSupport (f ∘ g) := by rw [mulSupport_comp_eq_preimage, Set.image_preimage_eq_iff.2 hf] rw [← Function.comp_def] by_cases hf_fin : (mulSupport f).Finite · have hfg_fin : (mulSupport (f ∘ g)).Finite := hf_fin.preimage hg.injOn lift g to γ ↪ β using hg simp_rw [tprod_eq_prod' hf_fin.coe_toFinset.ge, tprod_eq_prod' hfg_fin.coe_toFinset.ge, comp_apply, ← Finset.prod_map] refine Finset.prod_congr (Finset.coe_injective ?_) fun _ _ ↦ rfl simp [this] · have hf_fin' : ¬ Set.Finite (mulSupport (f ∘ g)) := by rwa [this, Set.finite_image_iff hg.injOn] at hf_fin simp_rw [tprod_def, if_neg hf_fin, if_neg hf_fin', Multipliable, funext fun a => propext <| hg.hasProd_iff (mulSupport_subset_iff'.1 hf) (a := a)] @[to_additive] theorem Equiv.tprod_eq (e : γ ≃ β) (f : β → α) : ∏' c, f (e c) = ∏' b, f b := e.injective.tprod_eq <| by simp /-! ### `tprod` on subsets - part 1 -/ @[to_additive] theorem tprod_subtype_eq_of_mulSupport_subset {f : β → α} {s : Set β} (hs : mulSupport f ⊆ s) : ∏' x : s, f x = ∏' x, f x := Subtype.val_injective.tprod_eq <| by simpa @[to_additive] theorem tprod_subtype_mulSupport (f : β → α) : ∏' x : mulSupport f, f x = ∏' x, f x := tprod_subtype_eq_of_mulSupport_subset Set.Subset.rfl @[to_additive] theorem tprod_subtype (s : Set β) (f : β → α) : ∏' x : s, f x = ∏' x, s.mulIndicator f x := by rw [← tprod_subtype_eq_of_mulSupport_subset Set.mulSupport_mulIndicator_subset, tprod_congr] simp @[to_additive (attr := simp)] theorem tprod_univ (f : β → α) : ∏' x : (Set.univ : Set β), f x = ∏' x, f x := tprod_subtype_eq_of_mulSupport_subset <| Set.subset_univ _ @[to_additive] theorem tprod_image {g : γ → β} (f : β → α) {s : Set γ} (hg : Set.InjOn g s) : ∏' x : g '' s, f x = ∏' x : s, f (g x) := ((Equiv.Set.imageOfInjOn _ _ hg).tprod_eq fun x ↦ f x).symm @[to_additive] theorem tprod_range {g : γ → β} (f : β → α) (hg : Injective g) : ∏' x : Set.range g, f x = ∏' x, f (g x) := by rw [← Set.image_univ, tprod_image f hg.injOn] simp_rw [← comp_apply (g := g), tprod_univ (f ∘ g)] /-- If `f b = 1` for all `b ∈ t`, then the product of `f a` with `a ∈ s` is the same as the product of `f a` with `a ∈ s ∖ t`. -/ @[to_additive "If `f b = 0` for all `b ∈ t`, then the sum of `f a` with `a ∈ s` is the same as the sum of `f a` with `a ∈ s ∖ t`."] lemma tprod_setElem_eq_tprod_setElem_diff {f : β → α} (s t : Set β) (hf₀ : ∀ b ∈ t, f b = 1) : ∏' a : s, f a = ∏' a : (s \ t : Set β), f a := .symm <| (Set.inclusion_injective (t := s) Set.diff_subset).tprod_eq (f := f ∘ (↑)) <| mulSupport_subset_iff'.2 fun b hb ↦ hf₀ b <| by simpa using hb /-- If `f b = 1`, then the product of `f a` with `a ∈ s` is the same as the product of `f a` for `a ∈ s ∖ {b}`. -/ @[to_additive "If `f b = 0`, then the sum of `f a` with `a ∈ s` is the same as the sum of `f a` for `a ∈ s ∖ {b}`."] lemma tprod_eq_tprod_diff_singleton {f : β → α} (s : Set β) {b : β} (hf₀ : f b = 1) : ∏' a : s, f a = ∏' a : (s \ {b} : Set β), f a := tprod_setElem_eq_tprod_setElem_diff s {b} fun _ ha ↦ ha ▸ hf₀ @[to_additive] theorem tprod_eq_tprod_of_ne_one_bij {g : γ → α} (i : mulSupport g → β) (hi : Injective i) (hf : mulSupport f ⊆ Set.range i) (hfg : ∀ x, f (i x) = g x) : ∏' x, f x = ∏' y, g y := by rw [← tprod_subtype_mulSupport g, ← hi.tprod_eq hf] simp only [hfg] @[to_additive] theorem Equiv.tprod_eq_tprod_of_mulSupport {f : β → α} {g : γ → α} (e : mulSupport f ≃ mulSupport g) (he : ∀ x, g (e x) = f x) : ∏' x, f x = ∏' y, g y := .symm <| tprod_eq_tprod_of_ne_one_bij _ (Subtype.val_injective.comp e.injective) (by simp) he @[to_additive] theorem tprod_dite_right (P : Prop) [Decidable P] (x : β → ¬P → α) : ∏' b : β, (if h : P then (1 : α) else x b h) = if h : P then (1 : α) else ∏' b : β, x b h := by by_cases hP : P <;> simp [hP] @[to_additive] theorem tprod_dite_left (P : Prop) [Decidable P] (x : β → P → α) : ∏' b : β, (if h : P then x b h else 1) = if h : P then ∏' b : β, x b h else 1 := by by_cases hP : P <;> simp [hP] @[to_additive (attr := simp)] lemma tprod_extend_one {γ : Type*} {g : γ → β} (hg : Injective g) (f : γ → α) : ∏' y, extend g f 1 y = ∏' x, f x := by have : mulSupport (extend g f 1) ⊆ Set.range g := mulSupport_subset_iff'.2 <| extend_apply' _ _ simp_rw [← hg.tprod_eq this, hg.extend_apply] variable [T2Space α] @[to_additive] theorem Function.Surjective.tprod_eq_tprod_of_hasProd_iff_hasProd {α' : Type*} [CommMonoid α'] [TopologicalSpace α'] {e : α' → α} (hes : Function.Surjective e) (h1 : e 1 = 1) {f : β → α} {g : γ → α'} (h : ∀ {a}, HasProd f (e a) ↔ HasProd g a) : ∏' b, f b = e (∏' c, g c) := by_cases (fun x ↦ (h.mpr x.hasProd).tprod_eq) fun hg : ¬Multipliable g ↦ by have hf : ¬Multipliable f := mt (hes.multipliable_iff_of_hasProd_iff @h).1 hg simp [tprod_def, hf, hg, h1] @[to_additive] theorem tprod_eq_tprod_of_hasProd_iff_hasProd {f : β → α} {g : γ → α} (h : ∀ {a}, HasProd f a ↔ HasProd g a) : ∏' b, f b = ∏' c, g c := surjective_id.tprod_eq_tprod_of_hasProd_iff_hasProd rfl @h section ContinuousMul variable [ContinuousMul α] @[to_additive] protected theorem Multipliable.tprod_mul (hf : Multipliable f) (hg : Multipliable g) : ∏' b, (f b * g b) = (∏' b, f b) * ∏' b, g b := (hf.hasProd.mul hg.hasProd).tprod_eq @[deprecated (since := "2025-04-12")] alias tsum_add := Summable.tsum_add @[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_mul := Multipliable.tprod_mul @[to_additive] protected theorem Multipliable.tprod_finsetProd {f : γ → β → α} {s : Finset γ} (hf : ∀ i ∈ s, Multipliable (f i)) : ∏' b, ∏ i ∈ s, f i b = ∏ i ∈ s, ∏' b, f i b := (hasProd_prod fun i hi ↦ (hf i hi).hasProd).tprod_eq @[deprecated (since := "2025-02-13")] alias tprod_of_prod := Multipliable.tprod_finsetProd @[deprecated (since := "2025-04-12")] alias tsum_finsetSum := Summable.tsum_finsetSum @[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_finsetProd := Multipliable.tprod_finsetProd /-- Version of `tprod_eq_mul_tprod_ite` for `CommMonoid` rather than `CommGroup`. Requires a different convergence assumption involving `Function.update`. -/ @[to_additive "Version of `tsum_eq_add_tsum_ite` for `AddCommMonoid` rather than `AddCommGroup`. Requires a different convergence assumption involving `Function.update`."] protected theorem Multipliable.tprod_eq_mul_tprod_ite' [DecidableEq β] {f : β → α} (b : β) (hf : Multipliable (update f b 1)) : ∏' x, f x = f b * ∏' x, ite (x = b) 1 (f x) := calc ∏' x, f x = ∏' x, (ite (x = b) (f x) 1 * update f b 1 x) := tprod_congr fun n ↦ by split_ifs with h <;> simp [update_apply, h] _ = (∏' x, ite (x = b) (f x) 1) * ∏' x, update f b 1 x := Multipliable.tprod_mul ⟨ite (b = b) (f b) 1, hasProd_single b fun _ hb ↦ if_neg hb⟩ hf _ = ite (b = b) (f b) 1 * ∏' x, update f b 1 x := by congr exact tprod_eq_mulSingle b fun b' hb' ↦ if_neg hb' _ = f b * ∏' x, ite (x = b) 1 (f x) := by simp only [update, eq_self_iff_true, if_true, eq_rec_constant, dite_eq_ite] @[deprecated (since := "2025-04-12")] alias tsum_eq_add_tsum_ite' := Summable.tsum_eq_add_tsum_ite' @[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_eq_mul_tprod_ite' := Multipliable.tprod_eq_mul_tprod_ite' @[to_additive] protected theorem Multipliable.tprod_mul_tprod_compl {s : Set β} (hs : Multipliable (f ∘ (↑) : s → α)) (hsc : Multipliable (f ∘ (↑) : ↑sᶜ → α)) : (∏' x : s, f x) * ∏' x : ↑sᶜ, f x = ∏' x, f x := (hs.hasProd.mul_compl hsc.hasProd).tprod_eq.symm @[deprecated (since := "2025-04-12")] alias tsum_add_tsum_compl := Summable.tsum_add_tsum_compl @[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_mul_tprod_compl := Multipliable.tprod_mul_tprod_compl @[to_additive] protected theorem Multipliable.tprod_union_disjoint {s t : Set β} (hd : Disjoint s t) (hs : Multipliable (f ∘ (↑) : s → α)) (ht : Multipliable (f ∘ (↑) : t → α)) : ∏' x : ↑(s ∪ t), f x = (∏' x : s, f x) * ∏' x : t, f x := (hs.hasProd.mul_disjoint hd ht.hasProd).tprod_eq @[deprecated (since := "2025-04-12")] alias tsum_union_disjoint := Summable.tsum_union_disjoint @[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_union_disjoint := Multipliable.tprod_union_disjoint @[to_additive] protected theorem Multipliable.tprod_finset_bUnion_disjoint {ι} {s : Finset ι} {t : ι → Set β} (hd : (s : Set ι).Pairwise (Disjoint on t)) (hf : ∀ i ∈ s, Multipliable (f ∘ (↑) : t i → α)) : ∏' x : ⋃ i ∈ s, t i, f x = ∏ i ∈ s, ∏' x : t i, f x := (hasProd_prod_disjoint _ hd fun i hi ↦ (hf i hi).hasProd).tprod_eq @[deprecated (since := "2025-04-12")] alias tsum_finset_bUnion_disjoint := Summable.tsum_finset_bUnion_disjoint @[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_finset_bUnion_disjoint := Multipliable.tprod_finset_bUnion_disjoint end ContinuousMul
end tprod section CommMonoidWithZero variable [CommMonoidWithZero α] [TopologicalSpace α] {f : β → α} lemma hasProd_zero_of_exists_eq_zero (hf : ∃ b, f b = 0) : HasProd f 0 := by obtain ⟨b, hb⟩ := hf apply tendsto_const_nhds.congr' filter_upwards [eventually_ge_atTop {b}] with s hs exact (Finset.prod_eq_zero (Finset.singleton_subset_iff.mp hs) hb).symm lemma multipliable_of_exists_eq_zero (hf : ∃ b, f b = 0) : Multipliable f :=
Mathlib/Topology/Algebra/InfiniteSum/Basic.lean
637
649
/- Copyright (c) 2020 Jean Lo. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jean Lo -/ import Mathlib.Dynamics.Flow import Mathlib.Tactic.Monotonicity /-! # ω-limits For a function `ϕ : τ → α → β` where `β` is a topological space, we define the ω-limit under `ϕ` of a set `s` in `α` with respect to filter `f` on `τ`: an element `y : β` is in the ω-limit of `s` if the forward images of `s` intersect arbitrarily small neighbourhoods of `y` frequently "in the direction of `f`". In practice `ϕ` is often a continuous monoid-act, but the definition requires only that `ϕ` has a coercion to the appropriate function type. In the case where `τ` is `ℕ` or `ℝ` and `f` is `atTop`, we recover the usual definition of the ω-limit set as the set of all `y` such that there exist sequences `(tₙ)`, `(xₙ)` such that `ϕ tₙ xₙ ⟶ y` as `n ⟶ ∞`. ## Notations The `omegaLimit` locale provides the localised notation `ω` for `omegaLimit`, as well as `ω⁺` and `ω⁻` for `omegaLimit atTop` and `omegaLimit atBot` respectively for when the acting monoid is endowed with an order. -/ open Set Function Filter Topology /-! ### Definition and notation -/ section omegaLimit variable {τ : Type*} {α : Type*} {β : Type*} {ι : Type*} /-- The ω-limit of a set `s` under `ϕ` with respect to a filter `f` is `⋂ u ∈ f, cl (ϕ u s)`. -/ def omegaLimit [TopologicalSpace β] (f : Filter τ) (ϕ : τ → α → β) (s : Set α) : Set β := ⋂ u ∈ f, closure (image2 ϕ u s) @[inherit_doc] scoped[omegaLimit] notation "ω" => omegaLimit /-- The ω-limit w.r.t. `Filter.atTop`. -/ scoped[omegaLimit] notation "ω⁺" => omegaLimit Filter.atTop /-- The ω-limit w.r.t. `Filter.atBot`. -/ scoped[omegaLimit] notation "ω⁻" => omegaLimit Filter.atBot variable [TopologicalSpace β] variable (f : Filter τ) (ϕ : τ → α → β) (s s₁ s₂ : Set α) /-! ### Elementary properties -/ open omegaLimit theorem omegaLimit_def : ω f ϕ s = ⋂ u ∈ f, closure (image2 ϕ u s) := rfl theorem omegaLimit_subset_of_tendsto {m : τ → τ} {f₁ f₂ : Filter τ} (hf : Tendsto m f₁ f₂) : ω f₁ (fun t x ↦ ϕ (m t) x) s ⊆ ω f₂ ϕ s := by refine iInter₂_mono' fun u hu ↦ ⟨m ⁻¹' u, tendsto_def.mp hf _ hu, ?_⟩ rw [← image2_image_left] exact closure_mono (image2_subset (image_preimage_subset _ _) Subset.rfl) theorem omegaLimit_mono_left {f₁ f₂ : Filter τ} (hf : f₁ ≤ f₂) : ω f₁ ϕ s ⊆ ω f₂ ϕ s := omegaLimit_subset_of_tendsto ϕ s (tendsto_id'.2 hf) theorem omegaLimit_mono_right {s₁ s₂ : Set α} (hs : s₁ ⊆ s₂) : ω f ϕ s₁ ⊆ ω f ϕ s₂ := iInter₂_mono fun _u _hu ↦ closure_mono (image2_subset Subset.rfl hs) theorem isClosed_omegaLimit : IsClosed (ω f ϕ s) := isClosed_iInter fun _u ↦ isClosed_iInter fun _hu ↦ isClosed_closure theorem mapsTo_omegaLimit' {α' β' : Type*} [TopologicalSpace β'] {f : Filter τ} {ϕ : τ → α → β} {ϕ' : τ → α' → β'} {ga : α → α'} {s' : Set α'} (hs : MapsTo ga s s') {gb : β → β'} (hg : ∀ᶠ t in f, EqOn (gb ∘ ϕ t) (ϕ' t ∘ ga) s) (hgc : Continuous gb) : MapsTo gb (ω f ϕ s) (ω f ϕ' s') := by simp only [omegaLimit_def, mem_iInter, MapsTo] intro y hy u hu refine map_mem_closure hgc (hy _ (inter_mem hu hg)) (forall_mem_image2.2 fun t ht x hx ↦ ?_) calc ϕ' t (ga x) ∈ image2 ϕ' u s' := mem_image2_of_mem ht.1 (hs hx) _ = gb (ϕ t x) := ht.2 hx |>.symm theorem mapsTo_omegaLimit {α' β' : Type*} [TopologicalSpace β'] {f : Filter τ} {ϕ : τ → α → β} {ϕ' : τ → α' → β'} {ga : α → α'} {s' : Set α'} (hs : MapsTo ga s s') {gb : β → β'} (hg : ∀ t x, gb (ϕ t x) = ϕ' t (ga x)) (hgc : Continuous gb) : MapsTo gb (ω f ϕ s) (ω f ϕ' s') := mapsTo_omegaLimit' _ hs (Eventually.of_forall fun t x _hx ↦ hg t x) hgc theorem omegaLimit_image_eq {α' : Type*} (ϕ : τ → α' → β) (f : Filter τ) (g : α → α') : ω f ϕ (g '' s) = ω f (fun t x ↦ ϕ t (g x)) s := by simp only [omegaLimit, image2_image_right] theorem omegaLimit_preimage_subset {α' : Type*} (ϕ : τ → α' → β) (s : Set α') (f : Filter τ) (g : α → α') : ω f (fun t x ↦ ϕ t (g x)) (g ⁻¹' s) ⊆ ω f ϕ s := mapsTo_omegaLimit _ (mapsTo_preimage _ _) (fun _t _x ↦ rfl) continuous_id /-! ### Equivalent definitions of the omega limit The next few lemmas are various versions of the property characterising ω-limits: -/ /-- An element `y` is in the ω-limit set of `s` w.r.t. `f` if the preimages of an arbitrary neighbourhood of `y` frequently (w.r.t. `f`) intersects of `s`. -/ theorem mem_omegaLimit_iff_frequently (y : β) : y ∈ ω f ϕ s ↔ ∀ n ∈ 𝓝 y, ∃ᶠ t in f, (s ∩ ϕ t ⁻¹' n).Nonempty := by simp_rw [frequently_iff, omegaLimit_def, mem_iInter, mem_closure_iff_nhds] constructor · intro h _ hn _ hu rcases h _ hu _ hn with ⟨_, _, _, ht, _, hx, rfl⟩ exact ⟨_, ht, _, hx, by rwa [mem_preimage]⟩ · intro h _ hu _ hn rcases h _ hn hu with ⟨_, ht, _, hx, hϕtx⟩ exact ⟨_, hϕtx, _, ht, _, hx, rfl⟩ /-- An element `y` is in the ω-limit set of `s` w.r.t. `f` if the forward images of `s` frequently (w.r.t. `f`) intersect arbitrary neighbourhoods of `y`. -/ theorem mem_omegaLimit_iff_frequently₂ (y : β) : y ∈ ω f ϕ s ↔ ∀ n ∈ 𝓝 y, ∃ᶠ t in f, (ϕ t '' s ∩ n).Nonempty := by simp_rw [mem_omegaLimit_iff_frequently, image_inter_nonempty_iff] /-- An element `y` is in the ω-limit of `x` w.r.t. `f` if the forward images of `x` frequently (w.r.t. `f`) falls within an arbitrary neighbourhood of `y`. -/ theorem mem_omegaLimit_singleton_iff_map_cluster_point (x : α) (y : β) : y ∈ ω f ϕ {x} ↔ MapClusterPt y f fun t ↦ ϕ t x := by simp_rw [mem_omegaLimit_iff_frequently, mapClusterPt_iff_frequently, singleton_inter_nonempty, mem_preimage] /-! ### Set operations and omega limits -/ theorem omegaLimit_inter : ω f ϕ (s₁ ∩ s₂) ⊆ ω f ϕ s₁ ∩ ω f ϕ s₂ := subset_inter (omegaLimit_mono_right _ _ inter_subset_left) (omegaLimit_mono_right _ _ inter_subset_right) theorem omegaLimit_iInter (p : ι → Set α) : ω f ϕ (⋂ i, p i) ⊆ ⋂ i, ω f ϕ (p i) := subset_iInter fun _i ↦ omegaLimit_mono_right _ _ (iInter_subset _ _) theorem omegaLimit_union : ω f ϕ (s₁ ∪ s₂) = ω f ϕ s₁ ∪ ω f ϕ s₂ := by ext y; constructor · simp only [mem_union, mem_omegaLimit_iff_frequently, union_inter_distrib_right, union_nonempty, frequently_or_distrib] contrapose! simp only [not_frequently, not_nonempty_iff_eq_empty, ← subset_empty_iff] rintro ⟨⟨n₁, hn₁, h₁⟩, ⟨n₂, hn₂, h₂⟩⟩ refine ⟨n₁ ∩ n₂, inter_mem hn₁ hn₂, h₁.mono fun t ↦ ?_, h₂.mono fun t ↦ ?_⟩ exacts [Subset.trans <| inter_subset_inter_right _ <| preimage_mono inter_subset_left, Subset.trans <| inter_subset_inter_right _ <| preimage_mono inter_subset_right] · rintro (hy | hy) exacts [omegaLimit_mono_right _ _ subset_union_left hy, omegaLimit_mono_right _ _ subset_union_right hy] theorem omegaLimit_iUnion (p : ι → Set α) : ⋃ i, ω f ϕ (p i) ⊆ ω f ϕ (⋃ i, p i) := by rw [iUnion_subset_iff] exact fun i ↦ omegaLimit_mono_right _ _ (subset_iUnion _ _) /-! Different expressions for omega limits, useful for rewrites. In particular, one may restrict the intersection to sets in `f` which are subsets of some set `v` also in `f`. -/ theorem omegaLimit_eq_iInter : ω f ϕ s = ⋂ u : ↥f.sets, closure (image2 ϕ u s) := biInter_eq_iInter _ _ theorem omegaLimit_eq_biInter_inter {v : Set τ} (hv : v ∈ f) : ω f ϕ s = ⋂ u ∈ f, closure (image2 ϕ (u ∩ v) s) := Subset.antisymm (iInter₂_mono' fun u hu ↦ ⟨u ∩ v, inter_mem hu hv, Subset.rfl⟩) (iInter₂_mono fun _u _hu ↦ closure_mono <| image2_subset inter_subset_left Subset.rfl) theorem omegaLimit_eq_iInter_inter {v : Set τ} (hv : v ∈ f) : ω f ϕ s = ⋂ u : ↥f.sets, closure (image2 ϕ (u ∩ v) s) := by rw [omegaLimit_eq_biInter_inter _ _ _ hv] apply biInter_eq_iInter theorem omegaLimit_subset_closure_fw_image {u : Set τ} (hu : u ∈ f) : ω f ϕ s ⊆ closure (image2 ϕ u s) := by rw [omegaLimit_eq_iInter] intro _ hx rw [mem_iInter] at hx exact hx ⟨u, hu⟩ -- An instance with better keys instance : Inhabited f.sets := Filter.inhabitedMem /-! ### ω-limits and compactness -/ /-- A set is eventually carried into any open neighbourhood of its ω-limit:
if `c` is a compact set such that `closure {ϕ t x | t ∈ v, x ∈ s} ⊆ c` for some `v ∈ f` and `n` is an open neighbourhood of `ω f ϕ s`, then for some `u ∈ f` we have `closure {ϕ t x | t ∈ u, x ∈ s} ⊆ n`. -/ theorem eventually_closure_subset_of_isCompact_absorbing_of_isOpen_of_omegaLimit_subset' {c : Set β}
Mathlib/Dynamics/OmegaLimit.lean
204
207
/- Copyright (c) 2021 Heather Macbeth. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Heather Macbeth, Yury Kudryashov -/ import Mathlib.Topology.Order.Basic /-! # Bounded monotone sequences converge In this file we prove a few theorems of the form “if the range of a monotone function `f : ι → α` admits a least upper bound `a`, then `f x` tends to `a` as `x → ∞`”, as well as version of this statement for (conditionally) complete lattices that use `⨆ x, f x` instead of `IsLUB`. These theorems work for linear orders with order topologies as well as their products (both in terms of `Prod` and in terms of function types). In order to reduce code duplication, we introduce two typeclasses (one for the property formulated above and one for the dual property), prove theorems assuming one of these typeclasses, and provide instances for linear orders and their products. We also prove some "inverse" results: if `f n` is a monotone sequence and `a` is its limit, then `f n ≤ a` for all `n`. ## Tags monotone convergence -/ open Filter Set Function open scoped Topology variable {α β : Type*} /-- We say that `α` is a `SupConvergenceClass` if the following holds. Let `f : ι → α` be a monotone function, let `a : α` be a least upper bound of `Set.range f`. Then `f x` tends to `𝓝 a` as `x → ∞` (formally, at the filter `Filter.atTop`). We require this for `ι = (s : Set α)`, `f = (↑)` in the definition, then prove it for any `f` in `tendsto_atTop_isLUB`. This property holds for linear orders with order topology as well as their products. -/ class SupConvergenceClass (α : Type*) [Preorder α] [TopologicalSpace α] : Prop where /-- proof that a monotone function tends to `𝓝 a` as `x → ∞` -/ tendsto_coe_atTop_isLUB : ∀ (a : α) (s : Set α), IsLUB s a → Tendsto ((↑) : s → α) atTop (𝓝 a) /-- We say that `α` is an `InfConvergenceClass` if the following holds. Let `f : ι → α` be a monotone function, let `a : α` be a greatest lower bound of `Set.range f`. Then `f x` tends to `𝓝 a` as `x → -∞` (formally, at the filter `Filter.atBot`). We require this for `ι = (s : Set α)`, `f = (↑)` in the definition, then prove it for any `f` in `tendsto_atBot_isGLB`. This property holds for linear orders with order topology as well as their products. -/ class InfConvergenceClass (α : Type*) [Preorder α] [TopologicalSpace α] : Prop where /-- proof that a monotone function tends to `𝓝 a` as `x → -∞` -/ tendsto_coe_atBot_isGLB : ∀ (a : α) (s : Set α), IsGLB s a → Tendsto ((↑) : s → α) atBot (𝓝 a) instance OrderDual.supConvergenceClass [Preorder α] [TopologicalSpace α] [InfConvergenceClass α] : SupConvergenceClass αᵒᵈ := ⟨‹InfConvergenceClass α›.1⟩ instance OrderDual.infConvergenceClass [Preorder α] [TopologicalSpace α] [SupConvergenceClass α] : InfConvergenceClass αᵒᵈ := ⟨‹SupConvergenceClass α›.1⟩ -- see Note [lower instance priority] instance (priority := 100) LinearOrder.supConvergenceClass [TopologicalSpace α] [LinearOrder α] [OrderTopology α] : SupConvergenceClass α := by refine ⟨fun a s ha => tendsto_order.2 ⟨fun b hb => ?_, fun b hb => ?_⟩⟩ · rcases ha.exists_between hb with ⟨c, hcs, bc, bca⟩ lift c to s using hcs exact (eventually_ge_atTop c).mono fun x hx => bc.trans_le hx · exact Eventually.of_forall fun x => (ha.1 x.2).trans_lt hb -- see Note [lower instance priority] instance (priority := 100) LinearOrder.infConvergenceClass [TopologicalSpace α] [LinearOrder α] [OrderTopology α] : InfConvergenceClass α := show InfConvergenceClass αᵒᵈᵒᵈ from OrderDual.infConvergenceClass section variable {ι : Type*} [Preorder ι] [TopologicalSpace α] section IsLUB variable [Preorder α] [SupConvergenceClass α] {f : ι → α} {a : α} theorem tendsto_atTop_isLUB (h_mono : Monotone f) (ha : IsLUB (Set.range f) a) : Tendsto f atTop (𝓝 a) := by suffices Tendsto (rangeFactorization f) atTop atTop from (SupConvergenceClass.tendsto_coe_atTop_isLUB _ _ ha).comp this exact h_mono.rangeFactorization.tendsto_atTop_atTop fun b => b.2.imp fun a ha => ha.ge theorem tendsto_atBot_isLUB (h_anti : Antitone f) (ha : IsLUB (Set.range f) a) : Tendsto f atBot (𝓝 a) := by convert tendsto_atTop_isLUB h_anti.dual_left ha using 1 end IsLUB section IsGLB variable [Preorder α] [InfConvergenceClass α] {f : ι → α} {a : α} theorem tendsto_atBot_isGLB (h_mono : Monotone f) (ha : IsGLB (Set.range f) a) : Tendsto f atBot (𝓝 a) := by convert tendsto_atTop_isLUB h_mono.dual ha.dual using 1 theorem tendsto_atTop_isGLB (h_anti : Antitone f) (ha : IsGLB (Set.range f) a) : Tendsto f atTop (𝓝 a) := by convert tendsto_atBot_isLUB h_anti.dual ha.dual using 1 end IsGLB section CiSup variable [ConditionallyCompleteLattice α] [SupConvergenceClass α] {f : ι → α} theorem tendsto_atTop_ciSup (h_mono : Monotone f) (hbdd : BddAbove <| range f) : Tendsto f atTop (𝓝 (⨆ i, f i)) := by cases isEmpty_or_nonempty ι exacts [tendsto_of_isEmpty, tendsto_atTop_isLUB h_mono (isLUB_ciSup hbdd)] theorem tendsto_atBot_ciSup (h_anti : Antitone f) (hbdd : BddAbove <| range f) : Tendsto f atBot (𝓝 (⨆ i, f i)) := by convert tendsto_atTop_ciSup h_anti.dual hbdd.dual using 1 end CiSup section CiInf variable [ConditionallyCompleteLattice α] [InfConvergenceClass α] {f : ι → α} theorem tendsto_atBot_ciInf (h_mono : Monotone f) (hbdd : BddBelow <| range f) :
Tendsto f atBot (𝓝 (⨅ i, f i)) := by convert tendsto_atTop_ciSup h_mono.dual hbdd.dual using 1 theorem tendsto_atTop_ciInf (h_anti : Antitone f) (hbdd : BddBelow <| range f) : Tendsto f atTop (𝓝 (⨅ i, f i)) := by convert tendsto_atBot_ciSup h_anti.dual hbdd.dual using 1
Mathlib/Topology/Order/MonotoneConvergence.lean
127
130
/- 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.Analysis.NormedSpace.Multilinear.Basic import Mathlib.LinearAlgebra.Multilinear.Curry /-! # Currying and uncurrying continuous multilinear maps We associate to a continuous multilinear map in `n+1` variables (i.e., based on `Fin n.succ`) two curried functions, named `f.curryLeft` (which is a continuous linear map on `E 0` taking values in continuous multilinear maps in `n` variables) and `f.curryRight` (which is a continuous multilinear map in `n` variables taking values in continuous linear maps on `E (last n)`). The inverse operations are called `uncurryLeft` and `uncurryRight`. We also register continuous linear equiv versions of these correspondences, in `continuousMultilinearCurryLeftEquiv` and `continuousMultilinearCurryRightEquiv`. ## Main results * `ContinuousMultilinearMap.curryLeft`, `ContinuousLinearMap.uncurryLeft` and `continuousMultilinearCurryLeftEquiv` * `ContinuousMultilinearMap.curryRight`, `ContinuousMultilinearMap.uncurryRight` and `continuousMultilinearCurryRightEquiv`. -/ suppress_compilation noncomputable section open NNReal Finset Metric ContinuousMultilinearMap Fin Function /-! ### Type variables We use the following type variables in this file: * `𝕜` : a `NontriviallyNormedField`; * `ι`, `ι'` : finite index types with decidable equality; * `E`, `E₁` : families of normed vector spaces over `𝕜` indexed by `i : ι`; * `E'` : a family of normed vector spaces over `𝕜` indexed by `i' : ι'`; * `Ei` : a family of normed vector spaces over `𝕜` indexed by `i : Fin (Nat.succ n)`; * `G`, `G'` : normed vector spaces over `𝕜`. -/ universe u v v' wE wE₁ wE' wEi wG wG' variable {𝕜 : Type u} {ι : Type v} {ι' : Type v'} {n : ℕ} {E : ι → Type wE} {Ei : Fin n.succ → Type wEi} {G : Type wG} {G' : Type wG'} [Fintype ι] [Fintype ι'] [NontriviallyNormedField 𝕜] [∀ i, NormedAddCommGroup (E i)] [∀ i, NormedSpace 𝕜 (E i)] [∀ i, NormedAddCommGroup (Ei i)] [∀ i, NormedSpace 𝕜 (Ei i)] [NormedAddCommGroup G] [NormedSpace 𝕜 G] [NormedAddCommGroup G'] [NormedSpace 𝕜 G'] theorem ContinuousLinearMap.norm_map_tail_le (f : Ei 0 →L[𝕜] ContinuousMultilinearMap 𝕜 (fun i : Fin n => Ei i.succ) G) (m : ∀ i, Ei i) : ‖f (m 0) (tail m)‖ ≤ ‖f‖ * ∏ i, ‖m i‖ := calc ‖f (m 0) (tail m)‖ ≤ ‖f (m 0)‖ * ∏ i, ‖(tail m) i‖ := (f (m 0)).le_opNorm _ _ ≤ ‖f‖ * ‖m 0‖ * ∏ i, ‖tail m i‖ := mul_le_mul_of_nonneg_right (f.le_opNorm _) <| by positivity _ = ‖f‖ * (‖m 0‖ * ∏ i, ‖(tail m) i‖) := by ring _ = ‖f‖ * ∏ i, ‖m i‖ := by rw [prod_univ_succ] rfl theorem ContinuousMultilinearMap.norm_map_init_le (f : ContinuousMultilinearMap 𝕜 (fun i : Fin n => Ei <| castSucc i) (Ei (last n) →L[𝕜] G)) (m : ∀ i, Ei i) : ‖f (init m) (m (last n))‖ ≤ ‖f‖ * ∏ i, ‖m i‖ := calc ‖f (init m) (m (last n))‖ ≤ ‖f (init m)‖ * ‖m (last n)‖ := (f (init m)).le_opNorm _ _ ≤ (‖f‖ * ∏ i, ‖(init m) i‖) * ‖m (last n)‖ := (mul_le_mul_of_nonneg_right (f.le_opNorm _) (norm_nonneg _)) _ = ‖f‖ * ((∏ i, ‖(init m) i‖) * ‖m (last n)‖) := mul_assoc _ _ _ _ = ‖f‖ * ∏ i, ‖m i‖ := by rw [prod_univ_castSucc] rfl theorem ContinuousMultilinearMap.norm_map_cons_le (f : ContinuousMultilinearMap 𝕜 Ei G) (x : Ei 0) (m : ∀ i : Fin n, Ei i.succ) : ‖f (cons x m)‖ ≤ ‖f‖ * ‖x‖ * ∏ i, ‖m i‖ := calc ‖f (cons x m)‖ ≤ ‖f‖ * ∏ i, ‖cons x m i‖ := f.le_opNorm _ _ = ‖f‖ * ‖x‖ * ∏ i, ‖m i‖ := by
rw [prod_univ_succ] simp [mul_assoc] theorem ContinuousMultilinearMap.norm_map_snoc_le (f : ContinuousMultilinearMap 𝕜 Ei G) (m : ∀ i : Fin n, Ei <| castSucc i) (x : Ei (last n)) : ‖f (snoc m x)‖ ≤ (‖f‖ * ∏ i, ‖m i‖) * ‖x‖ := calc
Mathlib/Analysis/NormedSpace/Multilinear/Curry.lean
86
92
/- Copyright (c) 2021 Yaël Dillies, Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Bhavik Mehta -/ import Mathlib.Analysis.Convex.Hull /-! # Extreme sets This file defines extreme sets and extreme points for sets in a module. An extreme set of `A` is a subset of `A` that is as far as it can get in any outward direction: If point `x` is in it and point `y ∈ A`, then the line passing through `x` and `y` leaves `A` at `x`. This is an analytic notion of "being on the side of". It is weaker than being exposed (see `IsExposed.isExtreme`). ## Main declarations * `IsExtreme 𝕜 A B`: States that `B` is an extreme set of `A` (in the literature, `A` is often implicit). * `Set.extremePoints 𝕜 A`: Set of extreme points of `A` (corresponding to extreme singletons). * `Convex.mem_extremePoints_iff_convex_diff`: A useful equivalent condition to being an extreme point: `x` is an extreme point iff `A \ {x}` is convex. ## Implementation notes The exact definition of extremeness has been carefully chosen so as to make as many lemmas unconditional (in particular, the Krein-Milman theorem doesn't need the set to be convex!). In practice, `A` is often assumed to be a convex set. ## References See chapter 8 of [Barry Simon, *Convexity*][simon2011] ## TODO Prove lemmas relating extreme sets and points to the intrinsic frontier. -/ open Function Set Affine variable {𝕜 E F ι : Type*} {M : ι → Type*} section SMul variable (𝕜) [Semiring 𝕜] [PartialOrder 𝕜] [AddCommMonoid E] [SMul 𝕜 E] /-- A set `B` is an extreme subset of `A` if `B ⊆ A` and all points of `B` only belong to open segments whose ends are in `B`. -/ def IsExtreme (A B : Set E) : Prop := B ⊆ A ∧ ∀ ⦃x₁⦄, x₁ ∈ A → ∀ ⦃x₂⦄, x₂ ∈ A → ∀ ⦃x⦄, x ∈ B → x ∈ openSegment 𝕜 x₁ x₂ → x₁ ∈ B ∧ x₂ ∈ B /-- A point `x` is an extreme point of a set `A` if `x` belongs to no open segment with ends in `A`, except for the obvious `openSegment x x`. In order to prove that `x` is an extreme point of `A`, it is convenient to use `mem_extremePoints_iff_left` to avoid repeating arguments twice. -/ def Set.extremePoints (A : Set E) : Set E := { x ∈ A | ∀ ⦃x₁⦄, x₁ ∈ A → ∀ ⦃x₂⦄, x₂ ∈ A → x ∈ openSegment 𝕜 x₁ x₂ → x₁ = x ∧ x₂ = x } @[refl] protected theorem IsExtreme.refl (A : Set E) : IsExtreme 𝕜 A A := ⟨Subset.rfl, fun _ hx₁A _ hx₂A _ _ _ ↦ ⟨hx₁A, hx₂A⟩⟩ variable {𝕜} {A B C : Set E} {x : E} protected theorem IsExtreme.rfl : IsExtreme 𝕜 A A := IsExtreme.refl 𝕜 A @[trans] protected theorem IsExtreme.trans (hAB : IsExtreme 𝕜 A B) (hBC : IsExtreme 𝕜 B C) : IsExtreme 𝕜 A C := by refine ⟨Subset.trans hBC.1 hAB.1, fun x₁ hx₁A x₂ hx₂A x hxC hx ↦ ?_⟩ obtain ⟨hx₁B, hx₂B⟩ := hAB.2 hx₁A hx₂A (hBC.1 hxC) hx exact hBC.2 hx₁B hx₂B hxC hx protected theorem IsExtreme.antisymm : AntiSymmetric (IsExtreme 𝕜 : Set E → Set E → Prop) := fun _ _ hAB hBA ↦ Subset.antisymm hBA.1 hAB.1 instance : IsPartialOrder (Set E) (IsExtreme 𝕜) where refl := IsExtreme.refl 𝕜 trans _ _ _ := IsExtreme.trans antisymm := IsExtreme.antisymm theorem IsExtreme.inter (hAB : IsExtreme 𝕜 A B) (hAC : IsExtreme 𝕜 A C) : IsExtreme 𝕜 A (B ∩ C) := by use Subset.trans inter_subset_left hAB.1 rintro x₁ hx₁A x₂ hx₂A x ⟨hxB, hxC⟩ hx obtain ⟨hx₁B, hx₂B⟩ := hAB.2 hx₁A hx₂A hxB hx obtain ⟨hx₁C, hx₂C⟩ := hAC.2 hx₁A hx₂A hxC hx exact ⟨⟨hx₁B, hx₁C⟩, hx₂B, hx₂C⟩ protected theorem IsExtreme.mono (hAC : IsExtreme 𝕜 A C) (hBA : B ⊆ A) (hCB : C ⊆ B) : IsExtreme 𝕜 B C :=
⟨hCB, fun _ hx₁B _ hx₂B _ hxC hx ↦ hAC.2 (hBA hx₁B) (hBA hx₂B) hxC hx⟩ theorem isExtreme_iInter {ι : Sort*} [Nonempty ι] {F : ι → Set E} (hAF : ∀ i : ι, IsExtreme 𝕜 A (F i)) : IsExtreme 𝕜 A (⋂ i : ι, F i) := by obtain i := Classical.arbitrary ι refine ⟨iInter_subset_of_subset i (hAF i).1, fun x₁ hx₁A x₂ hx₂A x hxF hx ↦ ?_⟩ simp_rw [mem_iInter] at hxF ⊢
Mathlib/Analysis/Convex/Extreme.lean
97
103
/- Copyright (c) 2020 Johan Commelin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin -/ import Mathlib.RingTheory.WittVector.Frobenius import Mathlib.RingTheory.WittVector.Verschiebung import Mathlib.RingTheory.WittVector.MulP /-! ## Identities between operations on the ring of Witt vectors In this file we derive common identities between the Frobenius and Verschiebung operators. ## Main declarations * `frobenius_verschiebung`: the composition of Frobenius and Verschiebung is multiplication by `p` * `verschiebung_mul_frobenius`: the “projection formula”: `V(x * F y) = V x * y` * `iterate_verschiebung_mul_coeff`: an identity from [Haze09] 6.2 ## References * [Hazewinkel, *Witt Vectors*][Haze09] * [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21] -/ namespace WittVector variable {p : ℕ} {R : Type*} [hp : Fact p.Prime] [CommRing R] -- type as `\bbW` local notation "𝕎" => WittVector p noncomputable section -- Porting note: `ghost_calc` failure: `simp only []` and the manual instances had to be added. /-- The composition of Frobenius and Verschiebung is multiplication by `p`. -/ theorem frobenius_verschiebung (x : 𝕎 R) : frobenius (verschiebung x) = x * p := by have : IsPoly p fun {R} [CommRing R] x ↦ frobenius (verschiebung x) := IsPoly.comp (hg := frobenius_isPoly p) (hf := verschiebung_isPoly) have : IsPoly p fun {R} [CommRing R] x ↦ x * p := mulN_isPoly p p ghost_calc x ghost_simp [mul_comm] /-- Verschiebung is the same as multiplication by `p` on the ring of Witt vectors of `ZMod p`. -/ theorem verschiebung_zmod (x : 𝕎 (ZMod p)) : verschiebung x = x * p := by rw [← frobenius_verschiebung, frobenius_zmodp] variable (p R) theorem coeff_p_pow [CharP R p] (i : ℕ) : ((p : 𝕎 R) ^ i).coeff i = 1 := by induction' i with i h · simp only [one_coeff_zero, Ne, pow_zero] · rw [pow_succ, ← frobenius_verschiebung, coeff_frobenius_charP, verschiebung_coeff_succ, h, one_pow] theorem coeff_p_pow_eq_zero [CharP R p] {i j : ℕ} (hj : j ≠ i) : ((p : 𝕎 R) ^ i).coeff j = 0 := by induction' i with i hi generalizing j · rw [pow_zero, one_coeff_eq_of_pos] exact Nat.pos_of_ne_zero hj · rw [pow_succ, ← frobenius_verschiebung, coeff_frobenius_charP] cases j · rw [verschiebung_coeff_zero, zero_pow hp.out.ne_zero] · rw [verschiebung_coeff_succ, hi (ne_of_apply_ne _ hj), zero_pow hp.out.ne_zero] theorem coeff_p [CharP R p] (i : ℕ) : (p : 𝕎 R).coeff i = if i = 1 then 1 else 0 := by split_ifs with hi · simpa only [hi, pow_one] using coeff_p_pow p R 1 · simpa only [pow_one] using coeff_p_pow_eq_zero p R hi @[simp] theorem coeff_p_zero [CharP R p] : (p : 𝕎 R).coeff 0 = 0 := by rw [coeff_p, if_neg] exact zero_ne_one @[simp] theorem coeff_p_one [CharP R p] : (p : 𝕎 R).coeff 1 = 1 := by rw [coeff_p, if_pos rfl] theorem p_nonzero [Nontrivial R] [CharP R p] : (p : 𝕎 R) ≠ 0 := by intro h simpa only [h, zero_coeff, zero_ne_one] using coeff_p_one p R theorem FractionRing.p_nonzero [Nontrivial R] [CharP R p] : (p : FractionRing (𝕎 R)) ≠ 0 := by simpa using (IsFractionRing.injective (𝕎 R) (FractionRing (𝕎 R))).ne (WittVector.p_nonzero _ _) variable {p R} -- Porting note: `ghost_calc` failure: `simp only []` and the manual instances had to be added. /-- The “projection formula” for Frobenius and Verschiebung. -/ theorem verschiebung_mul_frobenius (x y : 𝕎 R) : verschiebung (x * frobenius y) = verschiebung x * y := by have : IsPoly₂ p fun {R} [Rcr : CommRing R] x y ↦ verschiebung (x * frobenius y) := IsPoly.comp₂ (hg := verschiebung_isPoly) (hf := IsPoly₂.comp (hh := mulIsPoly₂) (hf := idIsPolyI' p) (hg := frobenius_isPoly p)) have : IsPoly₂ p fun {R} [CommRing R] x y ↦ verschiebung x * y := IsPoly₂.comp (hh := mulIsPoly₂) (hf := verschiebung_isPoly) (hg := idIsPolyI' p) ghost_calc x y rintro ⟨⟩ <;> ghost_simp [mul_assoc] theorem mul_charP_coeff_zero [CharP R p] (x : 𝕎 R) : (x * p).coeff 0 = 0 := by rw [← frobenius_verschiebung, coeff_frobenius_charP, verschiebung_coeff_zero, zero_pow hp.out.ne_zero] theorem mul_charP_coeff_succ [CharP R p] (x : 𝕎 R) (i : ℕ) : (x * p).coeff (i + 1) = x.coeff i ^ p := by rw [← frobenius_verschiebung, coeff_frobenius_charP, verschiebung_coeff_succ] theorem mul_pow_charP_coeff_zero [CharP R p] (x : 𝕎 R) {m n : ℕ} (h : m < n) : (x * p ^ n).coeff m = 0 := by induction' n with n ih generalizing m · contradiction · rw [pow_succ, ← mul_assoc] cases m with | zero => exact mul_charP_coeff_zero _ | succ m' => rw [mul_charP_coeff_succ, ih, zero_pow hp.out.ne_zero]
simpa using h theorem mul_pow_charP_coeff_succ [CharP R p] (x : 𝕎 R) {m n : ℕ} :
Mathlib/RingTheory/WittVector/Identities.lean
119
121
/- 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 -/ import Mathlib.Analysis.Calculus.ContDiff.RCLike import Mathlib.Analysis.Calculus.IteratedDeriv.Lemmas import Mathlib.Analysis.Complex.RealDeriv import Mathlib.Analysis.SpecialFunctions.Exp import Mathlib.Analysis.SpecialFunctions.Exponential import Mathlib.GroupTheory.MonoidLocalization.Basic /-! # Complex and real exponential In this file we prove that `Complex.exp` and `Real.exp` are analytic functions. ## Tags exp, derivative -/ assert_not_exists IsConformalMap Conformal noncomputable section open Filter Asymptotics Set Function open scoped Topology /-! ## `Complex.exp` -/ section open Complex variable {E : Type} [NormedAddCommGroup E] [NormedSpace ℂ E] variable {f g : E → ℂ} {z : ℂ} {x : E} {s : Set E} /-- `exp` is entire -/ theorem analyticOnNhd_cexp : AnalyticOnNhd ℂ exp univ := by rw [Complex.exp_eq_exp_ℂ] exact fun x _ ↦ NormedSpace.exp_analytic x theorem analyticOn_cexp : AnalyticOn ℂ exp univ := analyticOnNhd_cexp.analyticOn /-- `exp` is analytic at any point -/ @[fun_prop] theorem analyticAt_cexp : AnalyticAt ℂ exp z := analyticOnNhd_cexp z (mem_univ _) /-- `exp ∘ f` is analytic -/ @[fun_prop] theorem AnalyticAt.cexp (fa : AnalyticAt ℂ f x) : AnalyticAt ℂ (exp ∘ f) x := analyticAt_cexp.comp fa /-- `exp ∘ f` is analytic -/ @[fun_prop] theorem AnalyticAt.cexp' (fa : AnalyticAt ℂ f x) : AnalyticAt ℂ (fun z ↦ exp (f z)) x := fa.cexp theorem AnalyticWithinAt.cexp (fa : AnalyticWithinAt ℂ f s x) : AnalyticWithinAt ℂ (fun z ↦ exp (f z)) s x := analyticAt_cexp.comp_analyticWithinAt fa /-- `exp ∘ f` is analytic -/ theorem AnalyticOnNhd.cexp (fs : AnalyticOnNhd ℂ f s) : AnalyticOnNhd ℂ (fun z ↦ exp (f z)) s := fun z n ↦ analyticAt_cexp.comp (fs z n) theorem AnalyticOn.cexp (fs : AnalyticOn ℂ f s) : AnalyticOn ℂ (fun z ↦ exp (f z)) s := analyticOnNhd_cexp.comp_analyticOn fs (mapsTo_univ _ _) end namespace Complex variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedAlgebra 𝕜 ℂ] /-- The complex exponential is everywhere differentiable, with the derivative `exp x`. -/ theorem hasDerivAt_exp (x : ℂ) : HasDerivAt exp (exp x) x := by rw [hasDerivAt_iff_isLittleO_nhds_zero] have : (1 : ℕ) < 2 := by norm_num refine (IsBigO.of_bound ‖exp x‖ ?_).trans_isLittleO (isLittleO_pow_id this) filter_upwards [Metric.ball_mem_nhds (0 : ℂ) zero_lt_one] simp only [Metric.mem_ball, dist_zero_right, norm_pow] exact fun z hz => exp_bound_sq x z hz.le @[simp] theorem differentiable_exp : Differentiable 𝕜 exp := fun x => (hasDerivAt_exp x).differentiableAt.restrictScalars 𝕜 @[simp] theorem differentiableAt_exp {x : ℂ} : DifferentiableAt 𝕜 exp x := differentiable_exp x @[simp] theorem deriv_exp : deriv exp = exp := funext fun x => (hasDerivAt_exp x).deriv @[simp] theorem iter_deriv_exp : ∀ n : ℕ, deriv^[n] exp = exp | 0 => rfl | n + 1 => by rw [iterate_succ_apply, deriv_exp, iter_deriv_exp n] theorem contDiff_exp {n : WithTop ℕ∞} : ContDiff 𝕜 n exp := analyticOnNhd_cexp.restrictScalars.contDiff theorem hasStrictDerivAt_exp (x : ℂ) : HasStrictDerivAt exp (exp x) x := contDiff_exp.contDiffAt.hasStrictDerivAt' (hasDerivAt_exp x) le_rfl theorem hasStrictFDerivAt_exp_real (x : ℂ) : HasStrictFDerivAt exp (exp x • (1 : ℂ →L[ℝ] ℂ)) x := (hasStrictDerivAt_exp x).complexToReal_fderiv end Complex section variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedAlgebra 𝕜 ℂ] {f : 𝕜 → ℂ} {f' : ℂ} {x : 𝕜} {s : Set 𝕜} theorem HasStrictDerivAt.cexp (hf : HasStrictDerivAt f f' x) : HasStrictDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) * f') x := (Complex.hasStrictDerivAt_exp (f x)).comp x hf theorem HasDerivAt.cexp (hf : HasDerivAt f f' x) : HasDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) * f') x := (Complex.hasDerivAt_exp (f x)).comp x hf theorem HasDerivWithinAt.cexp (hf : HasDerivWithinAt f f' s x) : HasDerivWithinAt (fun x => Complex.exp (f x)) (Complex.exp (f x) * f') s x := (Complex.hasDerivAt_exp (f x)).comp_hasDerivWithinAt x hf theorem derivWithin_cexp (hf : DifferentiableWithinAt 𝕜 f s x) (hxs : UniqueDiffWithinAt 𝕜 s x) : derivWithin (fun x => Complex.exp (f x)) s x = Complex.exp (f x) * derivWithin f s x := hf.hasDerivWithinAt.cexp.derivWithin hxs @[simp] theorem deriv_cexp (hc : DifferentiableAt 𝕜 f x) : deriv (fun x => Complex.exp (f x)) x = Complex.exp (f x) * deriv f x := hc.hasDerivAt.cexp.deriv end section variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [NormedAlgebra 𝕜 ℂ] {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {f : E → ℂ} {f' : E →L[𝕜] ℂ} {x : E} {s : Set E} theorem HasStrictFDerivAt.cexp (hf : HasStrictFDerivAt f f' x) : HasStrictFDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) • f') x := (Complex.hasStrictDerivAt_exp (f x)).comp_hasStrictFDerivAt x hf theorem HasFDerivWithinAt.cexp (hf : HasFDerivWithinAt f f' s x) : HasFDerivWithinAt (fun x => Complex.exp (f x)) (Complex.exp (f x) • f') s x := (Complex.hasDerivAt_exp (f x)).comp_hasFDerivWithinAt x hf theorem HasFDerivAt.cexp (hf : HasFDerivAt f f' x) : HasFDerivAt (fun x => Complex.exp (f x)) (Complex.exp (f x) • f') x := hasFDerivWithinAt_univ.1 <| hf.hasFDerivWithinAt.cexp theorem DifferentiableWithinAt.cexp (hf : DifferentiableWithinAt 𝕜 f s x) : DifferentiableWithinAt 𝕜 (fun x => Complex.exp (f x)) s x := hf.hasFDerivWithinAt.cexp.differentiableWithinAt @[simp, fun_prop] theorem DifferentiableAt.cexp (hc : DifferentiableAt 𝕜 f x) : DifferentiableAt 𝕜 (fun x => Complex.exp (f x)) x := hc.hasFDerivAt.cexp.differentiableAt theorem DifferentiableOn.cexp (hc : DifferentiableOn 𝕜 f s) : DifferentiableOn 𝕜 (fun x => Complex.exp (f x)) s := fun x h => (hc x h).cexp @[simp, fun_prop] theorem Differentiable.cexp (hc : Differentiable 𝕜 f) : Differentiable 𝕜 fun x => Complex.exp (f x) := fun x => (hc x).cexp theorem ContDiff.cexp {n} (h : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => Complex.exp (f x) := Complex.contDiff_exp.comp h theorem ContDiffAt.cexp {n} (hf : ContDiffAt 𝕜 n f x) : ContDiffAt 𝕜 n (fun x => Complex.exp (f x)) x := Complex.contDiff_exp.contDiffAt.comp x hf theorem ContDiffOn.cexp {n} (hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (fun x => Complex.exp (f x)) s := Complex.contDiff_exp.comp_contDiffOn hf theorem ContDiffWithinAt.cexp {n} (hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (fun x => Complex.exp (f x)) s x := Complex.contDiff_exp.contDiffAt.comp_contDiffWithinAt x hf end open Complex in @[simp] theorem iteratedDeriv_cexp_const_mul (n : ℕ) (c : ℂ) : (iteratedDeriv n fun s : ℂ => exp (c * s)) = fun s => c ^ n * exp (c * s) := by rw [iteratedDeriv_comp_const_mul contDiff_exp, iteratedDeriv_eq_iterate, iter_deriv_exp] /-! ## `Real.exp` -/ section open Real variable {x : ℝ} {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] {f : E → ℝ} {s : Set E} /-- `exp` is entire -/ theorem analyticOnNhd_rexp : AnalyticOnNhd ℝ exp univ := by rw [Real.exp_eq_exp_ℝ] exact fun x _ ↦ NormedSpace.exp_analytic x theorem analyticOn_rexp : AnalyticOn ℝ exp univ := analyticOnNhd_rexp.analyticOn /-- `exp` is analytic at any point -/ @[fun_prop] theorem analyticAt_rexp : AnalyticAt ℝ exp x := analyticOnNhd_rexp x (mem_univ _)
/-- `exp ∘ f` is analytic -/ @[fun_prop]
Mathlib/Analysis/SpecialFunctions/ExpDeriv.lean
218
220
/- Copyright (c) 2020 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Analysis.SpecificLimits.Basic import Mathlib.Order.Iterate import Mathlib.Order.SemiconjSup import Mathlib.Topology.Order.MonotoneContinuity import Mathlib.Algebra.CharP.Defs /-! # Translation number of a monotone real map that commutes with `x ↦ x + 1` Let `f : ℝ → ℝ` be a monotone map such that `f (x + 1) = f x + 1` for all `x`. Then the limit $$ \tau(f)=\lim_{n\to\infty}{f^n(x)-x}{n} $$ exists and does not depend on `x`. This number is called the *translation number* of `f`. Different authors use different notation for this number: `τ`, `ρ`, `rot`, etc In this file we define a structure `CircleDeg1Lift` for bundled maps with these properties, define translation number of `f : CircleDeg1Lift`, prove some estimates relating `f^n(x)-x` to `τ(f)`. In case of a continuous map `f` we also prove that `f` admits a point `x` such that `f^n(x)=x+m` if and only if `τ(f)=m/n`. Maps of this type naturally appear as lifts of orientation preserving circle homeomorphisms. More precisely, let `f` be an orientation preserving homeomorphism of the circle $S^1=ℝ/ℤ$, and consider a real number `a` such that `⟦a⟧ = f 0`, where `⟦⟧` means the natural projection `ℝ → ℝ/ℤ`. Then there exists a unique continuous function `F : ℝ → ℝ` such that `F 0 = a` and `⟦F x⟧ = f ⟦x⟧` for all `x` (this fact is not formalized yet). This function is strictly monotone, continuous, and satisfies `F (x + 1) = F x + 1`. The number `⟦τ F⟧ : ℝ / ℤ` is called the *rotation number* of `f`. It does not depend on the choice of `a`. ## Main definitions * `CircleDeg1Lift`: a monotone map `f : ℝ → ℝ` such that `f (x + 1) = f x + 1` for all `x`; the type `CircleDeg1Lift` is equipped with `Lattice` and `Monoid` structures; the multiplication is given by composition: `(f * g) x = f (g x)`. * `CircleDeg1Lift.translationNumber`: translation number of `f : CircleDeg1Lift`. ## Main statements We prove the following properties of `CircleDeg1Lift.translationNumber`. * `CircleDeg1Lift.translationNumber_eq_of_dist_bounded`: if the distance between `(f^n) 0` and `(g^n) 0` is bounded from above uniformly in `n : ℕ`, then `f` and `g` have equal translation numbers. * `CircleDeg1Lift.translationNumber_eq_of_semiconjBy`: if two `CircleDeg1Lift` maps `f`, `g` are semiconjugate by a `CircleDeg1Lift` map, then `τ f = τ g`. * `CircleDeg1Lift.translationNumber_units_inv`: if `f` is an invertible `CircleDeg1Lift` map (equivalently, `f` is a lift of an orientation-preserving circle homeomorphism), then the translation number of `f⁻¹` is the negative of the translation number of `f`. * `CircleDeg1Lift.translationNumber_mul_of_commute`: if `f` and `g` commute, then `τ (f * g) = τ f + τ g`. * `CircleDeg1Lift.translationNumber_eq_rat_iff`: the translation number of `f` is equal to a rational number `m / n` if and only if `(f^n) x = x + m` for some `x`. * `CircleDeg1Lift.semiconj_of_bijective_of_translationNumber_eq`: if `f` and `g` are two bijective `CircleDeg1Lift` maps and their translation numbers are equal, then these maps are semiconjugate to each other. * `CircleDeg1Lift.semiconj_of_group_action_of_forall_translationNumber_eq`: let `f₁` and `f₂` be two actions of a group `G` on the circle by degree 1 maps (formally, `f₁` and `f₂` are two homomorphisms from `G →* CircleDeg1Lift`). If the translation numbers of `f₁ g` and `f₂ g` are equal to each other for all `g : G`, then these two actions are semiconjugate by some `F : CircleDeg1Lift`. This is a version of Proposition 5.4 from [Étienne Ghys, Groupes d'homeomorphismes du cercle et cohomologie bornee][ghys87:groupes]. ## Notation We use a local notation `τ` for the translation number of `f : CircleDeg1Lift`. ## Implementation notes We define the translation number of `f : CircleDeg1Lift` to be the limit of the sequence `(f ^ (2 ^ n)) 0 / (2 ^ n)`, then prove that `((f ^ n) x - x) / n` tends to this number for any `x`. This way it is much easier to prove that the limit exists and basic properties of the limit. We define translation number for a wider class of maps `f : ℝ → ℝ` instead of lifts of orientation preserving circle homeomorphisms for two reasons: * non-strictly monotone circle self-maps with discontinuities naturally appear as Poincaré maps for some flows on the two-torus (e.g., one can take a constant flow and glue in a few Cherry cells); * definition and some basic properties still work for this class. ## References * [Étienne Ghys, Groupes d'homeomorphismes du cercle et cohomologie bornee][ghys87:groupes] ## TODO Here are some short-term goals. * Introduce a structure or a typeclass for lifts of circle homeomorphisms. We use `Units CircleDeg1Lift` for now, but it's better to have a dedicated type (or a typeclass?). * Prove that the `SemiconjBy` relation on circle homeomorphisms is an equivalence relation. * Introduce `ConditionallyCompleteLattice` structure, use it in the proof of `CircleDeg1Lift.semiconj_of_group_action_of_forall_translationNumber_eq`. * Prove that the orbits of the irrational rotation are dense in the circle. Deduce that a homeomorphism with an irrational rotation is semiconjugate to the corresponding irrational translation by a continuous `CircleDeg1Lift`. ## Tags circle homeomorphism, rotation number -/ open Filter Set Int Topology open Function hiding Commute /-! ### Definition and monoid structure -/ /-- A lift of a monotone degree one map `S¹ → S¹`. -/ structure CircleDeg1Lift : Type extends ℝ →o ℝ where map_add_one' : ∀ x, toFun (x + 1) = toFun x + 1 namespace CircleDeg1Lift instance : FunLike CircleDeg1Lift ℝ ℝ where coe f := f.toFun coe_injective' | ⟨⟨_, _⟩, _⟩, ⟨⟨_, _⟩, _⟩, rfl => rfl instance : OrderHomClass CircleDeg1Lift ℝ ℝ where map_rel f _ _ h := f.monotone' h @[simp] theorem coe_mk (f h) : ⇑(mk f h) = f := rfl variable (f g : CircleDeg1Lift) @[simp] theorem coe_toOrderHom : ⇑f.toOrderHom = f := rfl protected theorem monotone : Monotone f := f.monotone' @[mono] theorem mono {x y} (h : x ≤ y) : f x ≤ f y := f.monotone h theorem strictMono_iff_injective : StrictMono f ↔ Injective f := f.monotone.strictMono_iff_injective @[simp] theorem map_add_one : ∀ x, f (x + 1) = f x + 1 := f.map_add_one' @[simp] theorem map_one_add (x : ℝ) : f (1 + x) = 1 + f x := by rw [add_comm, map_add_one, add_comm 1] @[ext] theorem ext ⦃f g : CircleDeg1Lift⦄ (h : ∀ x, f x = g x) : f = g := DFunLike.ext f g h instance : Monoid CircleDeg1Lift where mul f g := { toOrderHom := f.1.comp g.1 map_add_one' := fun x => by simp [map_add_one] } one := ⟨.id, fun _ => rfl⟩ mul_one _ := rfl one_mul _ := rfl mul_assoc _ _ _ := DFunLike.coe_injective rfl instance : Inhabited CircleDeg1Lift := ⟨1⟩ @[simp] theorem coe_mul : ⇑(f * g) = f ∘ g := rfl theorem mul_apply (x) : (f * g) x = f (g x) := rfl @[simp] theorem coe_one : ⇑(1 : CircleDeg1Lift) = id := rfl instance unitsHasCoeToFun : CoeFun CircleDeg1Liftˣ fun _ => ℝ → ℝ := ⟨fun f => ⇑(f : CircleDeg1Lift)⟩ @[simp] theorem units_inv_apply_apply (f : CircleDeg1Liftˣ) (x : ℝ) : (f⁻¹ : CircleDeg1Liftˣ) (f x) = x := by simp only [← mul_apply, f.inv_mul, coe_one, id] @[simp] theorem units_apply_inv_apply (f : CircleDeg1Liftˣ) (x : ℝ) : f ((f⁻¹ : CircleDeg1Liftˣ) x) = x := by simp only [← mul_apply, f.mul_inv, coe_one, id] /-- If a lift of a circle map is bijective, then it is an order automorphism of the line. -/ def toOrderIso : CircleDeg1Liftˣ →* ℝ ≃o ℝ where toFun f := { toFun := f invFun := ⇑f⁻¹ left_inv := units_inv_apply_apply f right_inv := units_apply_inv_apply f map_rel_iff' := ⟨fun h => by simpa using mono (↑f⁻¹) h, mono f⟩ } map_one' := rfl map_mul' _ _ := rfl @[simp] theorem coe_toOrderIso (f : CircleDeg1Liftˣ) : ⇑(toOrderIso f) = f := rfl @[simp] theorem coe_toOrderIso_symm (f : CircleDeg1Liftˣ) : ⇑(toOrderIso f).symm = (f⁻¹ : CircleDeg1Liftˣ) := rfl @[simp] theorem coe_toOrderIso_inv (f : CircleDeg1Liftˣ) : ⇑(toOrderIso f)⁻¹ = (f⁻¹ : CircleDeg1Liftˣ) := rfl theorem isUnit_iff_bijective {f : CircleDeg1Lift} : IsUnit f ↔ Bijective f := ⟨fun ⟨u, h⟩ => h ▸ (toOrderIso u).bijective, fun h => Units.isUnit { val := f inv := { toFun := (Equiv.ofBijective f h).symm monotone' := fun x y hxy => (f.strictMono_iff_injective.2 h.1).le_iff_le.1 (by simp only [Equiv.ofBijective_apply_symm_apply f h, hxy]) map_add_one' := fun x => h.1 <| by simp only [Equiv.ofBijective_apply_symm_apply f, f.map_add_one] } val_inv := ext <| Equiv.ofBijective_apply_symm_apply f h inv_val := ext <| Equiv.ofBijective_symm_apply_apply f h }⟩ theorem coe_pow : ∀ n : ℕ, ⇑(f ^ n) = f^[n] | 0 => rfl | n + 1 => by ext x simp [coe_pow n, pow_succ] theorem semiconjBy_iff_semiconj {f g₁ g₂ : CircleDeg1Lift} : SemiconjBy f g₁ g₂ ↔ Semiconj f g₁ g₂ := CircleDeg1Lift.ext_iff theorem commute_iff_commute {f g : CircleDeg1Lift} : Commute f g ↔ Function.Commute f g := CircleDeg1Lift.ext_iff /-! ### Translate by a constant -/ /-- The map `y ↦ x + y` as a `CircleDeg1Lift`. More precisely, we define a homomorphism from `Multiplicative ℝ` to `CircleDeg1Liftˣ`, so the translation by `x` is `translation (Multiplicative.ofAdd x)`. -/ def translate : Multiplicative ℝ →* CircleDeg1Liftˣ := MonoidHom.toHomUnits <| { toFun := fun x => ⟨⟨fun y => x.toAdd + y, fun _ _ h => add_le_add_left h _⟩, fun _ => (add_assoc _ _ _).symm⟩ map_one' := ext <| zero_add map_mul' := fun _ _ => ext <| add_assoc _ _ } @[simp] theorem translate_apply (x y : ℝ) : translate (Multiplicative.ofAdd x) y = x + y := rfl @[simp] theorem translate_inv_apply (x y : ℝ) : (translate <| Multiplicative.ofAdd x)⁻¹ y = -x + y := rfl @[simp] theorem translate_zpow (x : ℝ) (n : ℤ) : translate (Multiplicative.ofAdd x) ^ n = translate (Multiplicative.ofAdd <| ↑n * x) := by simp only [← zsmul_eq_mul, ofAdd_zsmul, MonoidHom.map_zpow] @[simp] theorem translate_pow (x : ℝ) (n : ℕ) : translate (Multiplicative.ofAdd x) ^ n = translate (Multiplicative.ofAdd <| ↑n * x) := translate_zpow x n @[simp] theorem translate_iterate (x : ℝ) (n : ℕ) : (translate (Multiplicative.ofAdd x))^[n] = translate (Multiplicative.ofAdd <| ↑n * x) := by rw [← coe_pow, ← Units.val_pow_eq_pow_val, translate_pow] /-! ### Commutativity with integer translations In this section we prove that `f` commutes with translations by an integer number. First we formulate these statements (for a natural or an integer number, addition on the left or on the right, addition or subtraction) using `Function.Commute`, then reformulate as `simp` lemmas `map_int_add` etc. -/ theorem commute_nat_add (n : ℕ) : Function.Commute f (n + ·) := by simpa only [nsmul_one, add_left_iterate] using Function.Commute.iterate_right f.map_one_add n theorem commute_add_nat (n : ℕ) : Function.Commute f (· + n) := by simp only [add_comm _ (n : ℝ), f.commute_nat_add n] theorem commute_sub_nat (n : ℕ) : Function.Commute f (· - n) := by simpa only [sub_eq_add_neg] using (f.commute_add_nat n).inverses_right (Equiv.addRight _).right_inv (Equiv.addRight _).left_inv theorem commute_add_int : ∀ n : ℤ, Function.Commute f (· + n) | (n : ℕ) => f.commute_add_nat n | -[n+1] => by simpa [sub_eq_add_neg] using f.commute_sub_nat (n + 1) theorem commute_int_add (n : ℤ) : Function.Commute f (n + ·) := by simpa only [add_comm _ (n : ℝ)] using f.commute_add_int n theorem commute_sub_int (n : ℤ) : Function.Commute f (· - n) := by simpa only [sub_eq_add_neg] using (f.commute_add_int n).inverses_right (Equiv.addRight _).right_inv (Equiv.addRight _).left_inv @[simp] theorem map_int_add (m : ℤ) (x : ℝ) : f (m + x) = m + f x := f.commute_int_add m x @[simp] theorem map_add_int (x : ℝ) (m : ℤ) : f (x + m) = f x + m := f.commute_add_int m x @[simp] theorem map_sub_int (x : ℝ) (n : ℤ) : f (x - n) = f x - n := f.commute_sub_int n x @[simp] theorem map_add_nat (x : ℝ) (n : ℕ) : f (x + n) = f x + n := f.map_add_int x n @[simp] theorem map_nat_add (n : ℕ) (x : ℝ) : f (n + x) = n + f x := f.map_int_add n x @[simp] theorem map_sub_nat (x : ℝ) (n : ℕ) : f (x - n) = f x - n := f.map_sub_int x n theorem map_int_of_map_zero (n : ℤ) : f n = f 0 + n := by rw [← f.map_add_int, zero_add] @[simp]
theorem map_fract_sub_fract_eq (x : ℝ) : f (fract x) - fract x = f x - x := by rw [Int.fract, f.map_sub_int, sub_sub_sub_cancel_right]
Mathlib/Dynamics/Circle/RotationNumber/TranslationNumber.lean
341
343
/- 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 -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.Order.CauSeq.BigOperators import Mathlib.Algebra.Order.Star.Basic import Mathlib.Data.Complex.BigOperators import Mathlib.Data.Complex.Norm import Mathlib.Data.Nat.Choose.Sum /-! # Exponential Function This file contains the definitions of the real and complex exponential function. ## Main definitions * `Complex.exp`: The complex exponential function, defined via its Taylor series * `Real.exp`: The real exponential function, defined as the real part of the complex exponential -/ open CauSeq Finset IsAbsoluteValue open scoped ComplexConjugate namespace Complex theorem isCauSeq_norm_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, ‖z ^ m / m.factorial‖ := let ⟨n, hn⟩ := exists_nat_gt ‖z‖ have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (norm_nonneg _) hn IsCauSeq.series_ratio_test n (‖z‖ / n) (div_nonneg (norm_nonneg _) (le_of_lt hn0)) (by rwa [div_lt_iff₀ hn0, one_mul]) fun m hm => by rw [abs_norm, abs_norm, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div, mul_div_assoc, mul_div_right_comm, Complex.norm_mul, Complex.norm_div, norm_natCast] gcongr exact le_trans hm (Nat.le_succ _) @[deprecated (since := "2025-02-16")] alias isCauSeq_abs_exp := isCauSeq_norm_exp noncomputable section theorem isCauSeq_exp (z : ℂ) : IsCauSeq (‖·‖) fun n => ∑ m ∈ range n, z ^ m / m.factorial := (isCauSeq_norm_exp z).of_abv /-- The Cauchy sequence consisting of partial sums of the Taylor series of the complex exponential function -/ @[pp_nodot] def exp' (z : ℂ) : CauSeq ℂ (‖·‖) := ⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩ /-- The complex exponential function, defined via its Taylor series -/ @[pp_nodot] def exp (z : ℂ) : ℂ := CauSeq.lim (exp' z) /-- scoped notation for the complex exponential function -/ scoped notation "cexp" => Complex.exp end end Complex namespace Real open Complex noncomputable section /-- The real exponential function, defined as the real part of the complex exponential -/ @[pp_nodot] nonrec def exp (x : ℝ) : ℝ := (exp x).re /-- scoped notation for the real exponential function -/ scoped notation "rexp" => Real.exp end end Real namespace Complex variable (x y : ℂ) @[simp] theorem exp_zero : exp 0 = 1 := by rw [exp] refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩ convert (config := .unfoldSameFun) ε0 -- ε0 : ε > 0 but goal is _ < ε rcases j with - | j · exact absurd hj (not_le_of_gt zero_lt_one) · dsimp [exp'] induction' j with j ih · dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl] · rw [← ih (by simp [Nat.succ_le_succ])] simp only [sum_range_succ, pow_succ] simp theorem exp_add : exp (x + y) = exp x * exp y := by have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) = ∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial * (y ^ (i - k) / (i - k).factorial) := by intro j refine Finset.sum_congr rfl fun m _ => ?_ rw [add_pow, div_eq_mul_inv, sum_mul] refine Finset.sum_congr rfl fun I hi => ?_ have h₁ : (m.choose I : ℂ) ≠ 0 := Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi)))) have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi) rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv] simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹, mul_comm (m.choose I : ℂ)] rw [inv_mul_cancel₀ h₁] simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm] simp_rw [exp, exp', lim_mul_lim] apply (lim_eq_lim_of_equiv _).symm simp only [hj] exact cauchy_product (isCauSeq_norm_exp x) (isCauSeq_exp y) /-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ := { toFun := fun z => exp z.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℂ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℂ) expMonoidHom f s lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _ theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n | 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero] | Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul] @[simp] theorem exp_ne_zero : exp x ≠ 0 := fun h => zero_ne_one (α := ℂ) <| by rw [← exp_zero, ← add_neg_cancel x, exp_add, h]; simp theorem exp_neg : exp (-x) = (exp x)⁻¹ := by rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel₀ (exp_ne_zero x)] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by cases n · simp [exp_nat_mul] · simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul] @[simp] theorem exp_conj : exp (conj x) = conj (exp x) := by dsimp [exp] rw [← lim_conj] refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_) dsimp [exp', Function.comp_def, cauSeqConj] rw [map_sum (starRingEnd _)] refine sum_congr rfl fun n _ => ?_ rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal] @[simp] theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x := conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal] @[simp, norm_cast] theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x := ofReal_exp_ofReal_re _ @[simp] theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im] theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x := rfl end Complex namespace Real open Complex variable (x y : ℝ) @[simp] theorem exp_zero : exp 0 = 1 := by simp [Real.exp] nonrec theorem exp_add : exp (x + y) = exp x * exp y := by simp [exp_add, exp] /-- the exponential function as a monoid hom from `Multiplicative ℝ` to `ℝ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℝ) ℝ := { toFun := fun x => exp x.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℝ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℝ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℝ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℝ) ℝ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℝ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℝ) expMonoidHom f s lemma exp_nsmul (x : ℝ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℝ) ℝ _ _ expMonoidHom _ _ nonrec theorem exp_nat_mul (x : ℝ) (n : ℕ) : exp (n * x) = exp x ^ n := ofReal_injective (by simp [exp_nat_mul]) @[simp] nonrec theorem exp_ne_zero : exp x ≠ 0 := fun h => exp_ne_zero x <| by rw [exp, ← ofReal_inj] at h; simp_all nonrec theorem exp_neg : exp (-x) = (exp x)⁻¹ := ofReal_injective <| by simp [exp_neg] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] open IsAbsoluteValue Nat theorem sum_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) (n : ℕ) : ∑ i ∈ range n, x ^ i / i ! ≤ exp x := calc ∑ i ∈ range n, x ^ i / i ! ≤ lim (⟨_, isCauSeq_re (exp' x)⟩ : CauSeq ℝ abs) := by refine le_lim (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp only [exp', const_apply, re_sum] norm_cast refine sum_le_sum_of_subset_of_nonneg (range_mono hj) fun _ _ _ ↦ ?_ positivity _ = exp x := by rw [exp, Complex.exp, ← cauSeqRe, lim_re] lemma pow_div_factorial_le_exp (hx : 0 ≤ x) (n : ℕ) : x ^ n / n ! ≤ exp x := calc x ^ n / n ! ≤ ∑ k ∈ range (n + 1), x ^ k / k ! := single_le_sum (f := fun k ↦ x ^ k / k !) (fun k _ ↦ by positivity) (self_mem_range_succ n) _ ≤ exp x := sum_le_exp_of_nonneg hx _ theorem quadratic_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : 1 + x + x ^ 2 / 2 ≤ exp x := calc 1 + x + x ^ 2 / 2 = ∑ i ∈ range 3, x ^ i / i ! := by simp only [sum_range_succ, range_one, sum_singleton, _root_.pow_zero, factorial, cast_one, ne_eq, one_ne_zero, not_false_eq_true, div_self, pow_one, mul_one, div_one, Nat.mul_one, cast_succ, add_right_inj] ring_nf _ ≤ exp x := sum_le_exp_of_nonneg hx 3 private theorem add_one_lt_exp_of_pos {x : ℝ} (hx : 0 < x) : x + 1 < exp x := (by nlinarith : x + 1 < 1 + x + x ^ 2 / 2).trans_le (quadratic_le_exp_of_nonneg hx.le) private theorem add_one_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : x + 1 ≤ exp x := by rcases eq_or_lt_of_le hx with (rfl | h) · simp exact (add_one_lt_exp_of_pos h).le theorem one_le_exp {x : ℝ} (hx : 0 ≤ x) : 1 ≤ exp x := by linarith [add_one_le_exp_of_nonneg hx] @[bound] theorem exp_pos (x : ℝ) : 0 < exp x := (le_total 0 x).elim (lt_of_lt_of_le zero_lt_one ∘ one_le_exp) fun h => by rw [← neg_neg x, Real.exp_neg] exact inv_pos.2 (lt_of_lt_of_le zero_lt_one (one_le_exp (neg_nonneg.2 h))) @[bound] lemma exp_nonneg (x : ℝ) : 0 ≤ exp x := x.exp_pos.le @[simp] theorem abs_exp (x : ℝ) : |exp x| = exp x := abs_of_pos (exp_pos _) lemma exp_abs_le (x : ℝ) : exp |x| ≤ exp x + exp (-x) := by cases le_total x 0 <;> simp [abs_of_nonpos, abs_of_nonneg, exp_nonneg, *] @[mono] theorem exp_strictMono : StrictMono exp := fun x y h => by rw [← sub_add_cancel y x, Real.exp_add] exact (lt_mul_iff_one_lt_left (exp_pos _)).2 (lt_of_lt_of_le (by linarith) (add_one_le_exp_of_nonneg (by linarith))) @[gcongr] theorem exp_lt_exp_of_lt {x y : ℝ} (h : x < y) : exp x < exp y := exp_strictMono h @[mono] theorem exp_monotone : Monotone exp := exp_strictMono.monotone @[gcongr, bound] theorem exp_le_exp_of_le {x y : ℝ} (h : x ≤ y) : exp x ≤ exp y := exp_monotone h @[simp] theorem exp_lt_exp {x y : ℝ} : exp x < exp y ↔ x < y := exp_strictMono.lt_iff_lt @[simp] theorem exp_le_exp {x y : ℝ} : exp x ≤ exp y ↔ x ≤ y := exp_strictMono.le_iff_le theorem exp_injective : Function.Injective exp := exp_strictMono.injective @[simp] theorem exp_eq_exp {x y : ℝ} : exp x = exp y ↔ x = y := exp_injective.eq_iff @[simp] theorem exp_eq_one_iff : exp x = 1 ↔ x = 0 := exp_injective.eq_iff' exp_zero @[simp] theorem one_lt_exp_iff {x : ℝ} : 1 < exp x ↔ 0 < x := by rw [← exp_zero, exp_lt_exp] @[bound] private alias ⟨_, Bound.one_lt_exp_of_pos⟩ := one_lt_exp_iff @[simp] theorem exp_lt_one_iff {x : ℝ} : exp x < 1 ↔ x < 0 := by rw [← exp_zero, exp_lt_exp] @[simp] theorem exp_le_one_iff {x : ℝ} : exp x ≤ 1 ↔ x ≤ 0 := exp_zero ▸ exp_le_exp @[simp] theorem one_le_exp_iff {x : ℝ} : 1 ≤ exp x ↔ 0 ≤ x := exp_zero ▸ exp_le_exp end Real namespace Complex theorem sum_div_factorial_le {α : Type*} [Field α] [LinearOrder α] [IsStrictOrderedRing α] (n j : ℕ) (hn : 0 < n) : (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) ≤ n.succ / (n.factorial * n) := calc (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) = ∑ m ∈ range (j - n), (1 / ((m + n).factorial : α)) := by refine sum_nbij' (· - n) (· + n) ?_ ?_ ?_ ?_ ?_ <;> simp +contextual [lt_tsub_iff_right, tsub_add_cancel_of_le] _ ≤ ∑ m ∈ range (j - n), ((n.factorial : α) * (n.succ : α) ^ m)⁻¹ := by simp_rw [one_div] gcongr rw [← Nat.cast_pow, ← Nat.cast_mul, Nat.cast_le, add_comm] exact Nat.factorial_mul_pow_le_factorial _ = (n.factorial : α)⁻¹ * ∑ m ∈ range (j - n), (n.succ : α)⁻¹ ^ m := by simp [mul_inv, ← mul_sum, ← sum_mul, mul_comm, inv_pow] _ = ((n.succ : α) - n.succ * (n.succ : α)⁻¹ ^ (j - n)) / (n.factorial * n) := by have h₁ : (n.succ : α) ≠ 1 := @Nat.cast_one α _ ▸ mt Nat.cast_inj.1 (mt Nat.succ.inj (pos_iff_ne_zero.1 hn)) have h₂ : (n.succ : α) ≠ 0 := by positivity have h₃ : (n.factorial * n : α) ≠ 0 := by positivity have h₄ : (n.succ - 1 : α) = n := by simp rw [geom_sum_inv h₁ h₂, eq_div_iff_mul_eq h₃, mul_comm _ (n.factorial * n : α), ← mul_assoc (n.factorial⁻¹ : α), ← mul_inv_rev, h₄, ← mul_assoc (n.factorial * n : α), mul_comm (n : α) n.factorial, mul_inv_cancel₀ h₃, one_mul, mul_comm] _ ≤ n.succ / (n.factorial * n : α) := by gcongr; apply sub_le_self; positivity theorem exp_bound {x : ℂ} (hx : ‖x‖ ≤ 1) {n : ℕ} (hn : 0 < n) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (1 / m.factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr rw [Complex.norm_pow] exact pow_le_one₀ (norm_nonneg _) hx _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (1 / m.factorial : ℝ) := by simp [abs_mul, abv_pow abs, abs_div, ← mul_sum] _ ≤ ‖x‖ ^ n * (n.succ * (n.factorial * n : ℝ)⁻¹) := by gcongr exact sum_div_factorial_le _ _ hn theorem exp_bound' {x : ℂ} {n : ℕ} (hx : ‖x‖ / n.succ ≤ 1 / 2) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 let k := j - n have hj : j = n + k := (add_tsub_cancel_of_le hj).symm rw [hj, sum_range_add_sub_sum_range] calc ‖∑ i ∈ range k, x ^ (n + i) / ((n + i).factorial : ℂ)‖ ≤ ∑ i ∈ range k, ‖x ^ (n + i) / ((n + i).factorial : ℂ)‖ := IsAbsoluteValue.abv_sum _ _ _ _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / (n + i).factorial := by simp [norm_natCast, Complex.norm_pow] _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / ((n.factorial : ℝ) * (n.succ : ℝ) ^ i) := ?_ _ = ∑ i ∈ range k, ‖x‖ ^ n / n.factorial * (‖x‖ ^ i / (n.succ : ℝ) ^ i) := ?_ _ ≤ ‖x‖ ^ n / ↑n.factorial * 2 := ?_ · gcongr exact mod_cast Nat.factorial_mul_pow_le_factorial · refine Finset.sum_congr rfl fun _ _ => ?_ simp only [pow_add, div_eq_inv_mul, mul_inv, mul_left_comm, mul_assoc] · rw [← mul_sum] gcongr simp_rw [← div_pow] rw [geom_sum_eq, div_le_iff_of_neg] · trans (-1 : ℝ) · linarith · simp only [neg_le_sub_iff_le_add, div_pow, Nat.cast_succ, le_add_iff_nonneg_left] positivity · linarith · linarith theorem norm_exp_sub_one_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1‖ ≤ 2 * ‖x‖ := calc ‖exp x - 1‖ = ‖exp x - ∑ m ∈ range 1, x ^ m / m.factorial‖ := by simp [sum_range_succ] _ ≤ ‖x‖ ^ 1 * ((Nat.succ 1 : ℝ) * ((Nat.factorial 1) * (1 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ = 2 * ‖x‖ := by simp [two_mul, mul_two, mul_add, mul_comm, add_mul, Nat.factorial] theorem norm_exp_sub_one_sub_id_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1 - x‖ ≤ ‖x‖ ^ 2 := calc ‖exp x - 1 - x‖ = ‖exp x - ∑ m ∈ range 2, x ^ m / m.factorial‖ := by simp [sub_eq_add_neg, sum_range_succ_comm, add_assoc, Nat.factorial] _ ≤ ‖x‖ ^ 2 * ((Nat.succ 2 : ℝ) * (Nat.factorial 2 * (2 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ ≤ ‖x‖ ^ 2 * 1 := by gcongr; norm_num [Nat.factorial] _ = ‖x‖ ^ 2 := by rw [mul_one] lemma norm_exp_sub_sum_le_exp_norm_sub_sum (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] calc ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ _ ≤ (∑ m ∈ range j, ‖x‖ ^ m / m.factorial) - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [sum_range_sub_sum_range hj, sum_range_sub_sum_range hj] refine (IsAbsoluteValue.abv_sum norm ..).trans_eq ?_ congr with i simp [Complex.norm_pow] _ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by gcongr exact Real.sum_le_exp_of_nonneg (norm_nonneg _) _ lemma norm_exp_le_exp_norm (x : ℂ) : ‖exp x‖ ≤ Real.exp ‖x‖ := by convert norm_exp_sub_sum_le_exp_norm_sub_sum x 0 using 1 <;> simp lemma norm_exp_sub_sum_le_norm_mul_exp (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ _ rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (‖x‖ ^ (m - n) / (m - n).factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr with i hi · rw [Complex.norm_pow] · simp _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (‖x‖ ^ (m - n) / (m - n).factorial) := by rw [← mul_sum] _ = ‖x‖ ^ n * ∑ m ∈ range (j - n), (‖x‖ ^ m / m.factorial) := by congr 1 refine (sum_bij (fun m hm ↦ m + n) ?_ ?_ ?_ ?_).symm · intro a ha simp only [mem_filter, mem_range, le_add_iff_nonneg_left, zero_le, and_true] simp only [mem_range] at ha rwa [← lt_tsub_iff_right] · intro a ha b hb hab simpa using hab · intro b hb simp only [mem_range, exists_prop] simp only [mem_filter, mem_range] at hb refine ⟨b - n, ?_, ?_⟩ · rw [tsub_lt_tsub_iff_right hb.2] exact hb.1 · rw [tsub_add_cancel_of_le hb.2] · simp _ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by gcongr refine Real.sum_le_exp_of_nonneg ?_ _ exact norm_nonneg _ @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_le := norm_exp_sub_one_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_sub_id_le := norm_exp_sub_one_sub_id_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_exp_abs_sub_sum := norm_exp_sub_sum_le_exp_norm_sub_sum @[deprecated (since := "2025-02-16")] alias abs_exp_le_exp_abs := norm_exp_le_exp_norm @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_abs_mul_exp := norm_exp_sub_sum_le_norm_mul_exp end Complex namespace Real open Complex Finset nonrec theorem exp_bound {x : ℝ} (hx : |x| ≤ 1) {n : ℕ} (hn : 0 < n) : |exp x - ∑ m ∈ range n, x ^ m / m.factorial| ≤ |x| ^ n * (n.succ / (n.factorial * n)) := by have hxc : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx convert exp_bound hxc hn using 2 <;> norm_cast theorem exp_bound' {x : ℝ} (h1 : 0 ≤ x) (h2 : x ≤ 1) {n : ℕ} (hn : 0 < n) : Real.exp x ≤ (∑ m ∈ Finset.range n, x ^ m / m.factorial) + x ^ n * (n + 1) / (n.factorial * n) := by have h3 : |x| = x := by simpa have h4 : |x| ≤ 1 := by rwa [h3] have h' := Real.exp_bound h4 hn rw [h3] at h' have h'' := (abs_sub_le_iff.1 h').1 have t := sub_le_iff_le_add'.1 h'' simpa [mul_div_assoc] using t theorem abs_exp_sub_one_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1| ≤ 2 * |x| := by have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_le (x := x) this theorem abs_exp_sub_one_sub_id_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1 - x| ≤ x ^ 2 := by rw [← sq_abs] have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_sub_id_le this /-- A finite initial segment of the exponential series, followed by an arbitrary tail. For fixed `n` this is just a linear map wrt `r`, and each map is a simple linear function of the previous (see `expNear_succ`), with `expNear n x r ⟶ exp x` as `n ⟶ ∞`, for any `r`. -/ noncomputable def expNear (n : ℕ) (x r : ℝ) : ℝ := (∑ m ∈ range n, x ^ m / m.factorial) + x ^ n / n.factorial * r @[simp] theorem expNear_zero (x r) : expNear 0 x r = r := by simp [expNear] @[simp] theorem expNear_succ (n x r) : expNear (n + 1) x r = expNear n x (1 + x / (n + 1) * r) := by simp [expNear, range_succ, mul_add, add_left_comm, add_assoc, pow_succ, div_eq_mul_inv, mul_inv, Nat.factorial] ac_rfl theorem expNear_sub (n x r₁ r₂) : expNear n x r₁ - expNear n x r₂ = x ^ n / n.factorial * (r₁ - r₂) := by simp [expNear, mul_sub] theorem exp_approx_end (n m : ℕ) (x : ℝ) (e₁ : n + 1 = m) (h : |x| ≤ 1) : |exp x - expNear m x 0| ≤ |x| ^ m / m.factorial * ((m + 1) / m) := by simp only [expNear, mul_zero, add_zero] convert exp_bound (n := m) h ?_ using 1 · field_simp [mul_comm] · omega theorem exp_approx_succ {n} {x a₁ b₁ : ℝ} (m : ℕ) (e₁ : n + 1 = m) (a₂ b₂ : ℝ) (e : |1 + x / m * a₂ - a₁| ≤ b₁ - |x| / m * b₂) (h : |exp x - expNear m x a₂| ≤ |x| ^ m / m.factorial * b₂) : |exp x - expNear n x a₁| ≤ |x| ^ n / n.factorial * b₁ := by refine (abs_sub_le _ _ _).trans ((add_le_add_right h _).trans ?_) subst e₁; rw [expNear_succ, expNear_sub, abs_mul] convert mul_le_mul_of_nonneg_left (a := |x| ^ n / ↑(Nat.factorial n)) (le_sub_iff_add_le'.1 e) ?_ using 1 · simp [mul_add, pow_succ', div_eq_mul_inv, abs_mul, abs_inv, ← pow_abs, mul_inv, Nat.factorial] ac_rfl · simp [div_nonneg, abs_nonneg] theorem exp_approx_end' {n} {x a b : ℝ} (m : ℕ) (e₁ : n + 1 = m) (rm : ℝ) (er : ↑m = rm) (h : |x| ≤ 1) (e : |1 - a| ≤ b - |x| / rm * ((rm + 1) / rm)) : |exp x - expNear n x a| ≤ |x| ^ n / n.factorial * b := by subst er exact exp_approx_succ _ e₁ _ _ (by simpa using e) (exp_approx_end _ _ _ e₁ h) theorem exp_1_approx_succ_eq {n} {a₁ b₁ : ℝ} {m : ℕ} (en : n + 1 = m) {rm : ℝ} (er : ↑m = rm) (h : |exp 1 - expNear m 1 ((a₁ - 1) * rm)| ≤ |1| ^ m / m.factorial * (b₁ * rm)) : |exp 1 - expNear n 1 a₁| ≤ |1| ^ n / n.factorial * b₁ := by subst er refine exp_approx_succ _ en _ _ ?_ h field_simp [show (m : ℝ) ≠ 0 by norm_cast; omega] theorem exp_approx_start (x a b : ℝ) (h : |exp x - expNear 0 x a| ≤ |x| ^ 0 / Nat.factorial 0 * b) : |exp x - a| ≤ b := by simpa using h theorem exp_bound_div_one_sub_of_interval' {x : ℝ} (h1 : 0 < x) (h2 : x < 1) : Real.exp x < 1 / (1 - x) := by have H : 0 < 1 - (1 + x + x ^ 2) * (1 - x) := calc 0 < x ^ 3 := by positivity _ = 1 - (1 + x + x ^ 2) * (1 - x) := by ring calc exp x ≤ _ := exp_bound' h1.le h2.le zero_lt_three _ ≤ 1 + x + x ^ 2 := by -- Porting note: was `norm_num [Finset.sum] <;> nlinarith` -- This proof should be restored after the norm_num plugin for big operators is ported. -- (It may also need the positivity extensions in https://github.com/leanprover-community/mathlib4/pull/3907.) rw [show 3 = 1 + 1 + 1 from rfl] repeat rw [Finset.sum_range_succ] norm_num [Nat.factorial] nlinarith _ < 1 / (1 - x) := by rw [lt_div_iff₀] <;> nlinarith theorem exp_bound_div_one_sub_of_interval {x : ℝ} (h1 : 0 ≤ x) (h2 : x < 1) : Real.exp x ≤ 1 / (1 - x) := by rcases eq_or_lt_of_le h1 with (rfl | h1) · simp · exact (exp_bound_div_one_sub_of_interval' h1 h2).le theorem add_one_lt_exp {x : ℝ} (hx : x ≠ 0) : x + 1 < Real.exp x := by obtain hx | hx := hx.symm.lt_or_lt · exact add_one_lt_exp_of_pos hx obtain h' | h' := le_or_lt 1 (-x) · linarith [x.exp_pos] have hx' : 0 < x + 1 := by linarith simpa [add_comm, exp_neg, inv_lt_inv₀ (exp_pos _) hx'] using exp_bound_div_one_sub_of_interval' (neg_pos.2 hx) h' theorem add_one_le_exp (x : ℝ) : x + 1 ≤ Real.exp x := by obtain rfl | hx := eq_or_ne x 0 · simp · exact (add_one_lt_exp hx).le lemma one_sub_lt_exp_neg {x : ℝ} (hx : x ≠ 0) : 1 - x < exp (-x) := (sub_eq_neg_add _ _).trans_lt <| add_one_lt_exp <| neg_ne_zero.2 hx lemma one_sub_le_exp_neg (x : ℝ) : 1 - x ≤ exp (-x) := (sub_eq_neg_add _ _).trans_le <| add_one_le_exp _ theorem one_sub_div_pow_le_exp_neg {n : ℕ} {t : ℝ} (ht' : t ≤ n) : (1 - t / n) ^ n ≤ exp (-t) := by rcases eq_or_ne n 0 with (rfl | hn) · simp rwa [Nat.cast_zero] at ht' calc (1 - t / n) ^ n ≤ rexp (-(t / n)) ^ n := by gcongr · exact sub_nonneg.2 <| div_le_one_of_le₀ ht' n.cast_nonneg · exact one_sub_le_exp_neg _ _ = rexp (-t) := by rw [← Real.exp_nat_mul, mul_neg, mul_comm, div_mul_cancel₀]; positivity lemma le_inv_mul_exp (x : ℝ) {c : ℝ} (hc : 0 < c) : x ≤ c⁻¹ * exp (c * x) := by rw [le_inv_mul_iff₀ hc] calc c * x _ ≤ c * x + 1 := le_add_of_nonneg_right zero_le_one _ ≤ _ := Real.add_one_le_exp (c * x) end Real namespace Mathlib.Meta.Positivity open Lean.Meta Qq /-- Extension for the `positivity` tactic: `Real.exp` is always positive. -/ @[positivity Real.exp _] def evalExp : PositivityExt where eval {u α} _ _ e := do match u, α, e with | 0, ~q(ℝ), ~q(Real.exp $a) => assertInstancesCommute pure (.positive q(Real.exp_pos $a)) | _, _, _ => throwError "not Real.exp" end Mathlib.Meta.Positivity namespace Complex @[simp] theorem norm_exp_ofReal (x : ℝ) : ‖exp x‖ = Real.exp x := by rw [← ofReal_exp] exact Complex.norm_of_nonneg (le_of_lt (Real.exp_pos _)) @[deprecated (since := "2025-02-16")] alias abs_exp_ofReal := norm_exp_ofReal end Complex
Mathlib/Data/Complex/Exponential.lean
1,071
1,072
/- 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 -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.Order.CauSeq.BigOperators import Mathlib.Algebra.Order.Star.Basic import Mathlib.Data.Complex.BigOperators import Mathlib.Data.Complex.Norm import Mathlib.Data.Nat.Choose.Sum /-! # Exponential Function This file contains the definitions of the real and complex exponential function. ## Main definitions * `Complex.exp`: The complex exponential function, defined via its Taylor series * `Real.exp`: The real exponential function, defined as the real part of the complex exponential -/ open CauSeq Finset IsAbsoluteValue open scoped ComplexConjugate namespace Complex theorem isCauSeq_norm_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, ‖z ^ m / m.factorial‖ := let ⟨n, hn⟩ := exists_nat_gt ‖z‖ have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (norm_nonneg _) hn IsCauSeq.series_ratio_test n (‖z‖ / n) (div_nonneg (norm_nonneg _) (le_of_lt hn0)) (by rwa [div_lt_iff₀ hn0, one_mul]) fun m hm => by rw [abs_norm, abs_norm, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div, mul_div_assoc, mul_div_right_comm, Complex.norm_mul, Complex.norm_div, norm_natCast] gcongr exact le_trans hm (Nat.le_succ _) @[deprecated (since := "2025-02-16")] alias isCauSeq_abs_exp := isCauSeq_norm_exp noncomputable section theorem isCauSeq_exp (z : ℂ) : IsCauSeq (‖·‖) fun n => ∑ m ∈ range n, z ^ m / m.factorial := (isCauSeq_norm_exp z).of_abv /-- The Cauchy sequence consisting of partial sums of the Taylor series of the complex exponential function -/ @[pp_nodot] def exp' (z : ℂ) : CauSeq ℂ (‖·‖) := ⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩ /-- The complex exponential function, defined via its Taylor series -/ @[pp_nodot] def exp (z : ℂ) : ℂ := CauSeq.lim (exp' z) /-- scoped notation for the complex exponential function -/ scoped notation "cexp" => Complex.exp end end Complex namespace Real open Complex noncomputable section /-- The real exponential function, defined as the real part of the complex exponential -/ @[pp_nodot] nonrec def exp (x : ℝ) : ℝ := (exp x).re /-- scoped notation for the real exponential function -/ scoped notation "rexp" => Real.exp end end Real namespace Complex variable (x y : ℂ) @[simp] theorem exp_zero : exp 0 = 1 := by rw [exp] refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩ convert (config := .unfoldSameFun) ε0 -- ε0 : ε > 0 but goal is _ < ε rcases j with - | j · exact absurd hj (not_le_of_gt zero_lt_one) · dsimp [exp'] induction' j with j ih · dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl] · rw [← ih (by simp [Nat.succ_le_succ])] simp only [sum_range_succ, pow_succ] simp theorem exp_add : exp (x + y) = exp x * exp y := by have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) = ∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial * (y ^ (i - k) / (i - k).factorial) := by intro j refine Finset.sum_congr rfl fun m _ => ?_ rw [add_pow, div_eq_mul_inv, sum_mul] refine Finset.sum_congr rfl fun I hi => ?_ have h₁ : (m.choose I : ℂ) ≠ 0 := Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi)))) have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi) rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv] simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹, mul_comm (m.choose I : ℂ)] rw [inv_mul_cancel₀ h₁] simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm] simp_rw [exp, exp', lim_mul_lim] apply (lim_eq_lim_of_equiv _).symm simp only [hj] exact cauchy_product (isCauSeq_norm_exp x) (isCauSeq_exp y) /-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ := { toFun := fun z => exp z.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℂ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℂ) expMonoidHom f s lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _ theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n | 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero] | Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul] @[simp] theorem exp_ne_zero : exp x ≠ 0 := fun h => zero_ne_one (α := ℂ) <| by rw [← exp_zero, ← add_neg_cancel x, exp_add, h]; simp theorem exp_neg : exp (-x) = (exp x)⁻¹ := by rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel₀ (exp_ne_zero x)] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by cases n · simp [exp_nat_mul] · simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul] @[simp] theorem exp_conj : exp (conj x) = conj (exp x) := by dsimp [exp] rw [← lim_conj] refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_) dsimp [exp', Function.comp_def, cauSeqConj] rw [map_sum (starRingEnd _)] refine sum_congr rfl fun n _ => ?_ rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal] @[simp] theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x := conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal] @[simp, norm_cast] theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x := ofReal_exp_ofReal_re _ @[simp] theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im] theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x := rfl end Complex namespace Real open Complex variable (x y : ℝ) @[simp] theorem exp_zero : exp 0 = 1 := by simp [Real.exp] nonrec theorem exp_add : exp (x + y) = exp x * exp y := by simp [exp_add, exp] /-- the exponential function as a monoid hom from `Multiplicative ℝ` to `ℝ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℝ) ℝ := { toFun := fun x => exp x.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℝ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℝ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℝ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℝ) ℝ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℝ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℝ) expMonoidHom f s lemma exp_nsmul (x : ℝ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℝ) ℝ _ _ expMonoidHom _ _ nonrec theorem exp_nat_mul (x : ℝ) (n : ℕ) : exp (n * x) = exp x ^ n := ofReal_injective (by simp [exp_nat_mul]) @[simp] nonrec theorem exp_ne_zero : exp x ≠ 0 := fun h => exp_ne_zero x <| by rw [exp, ← ofReal_inj] at h; simp_all nonrec theorem exp_neg : exp (-x) = (exp x)⁻¹ := ofReal_injective <| by simp [exp_neg] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] open IsAbsoluteValue Nat theorem sum_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) (n : ℕ) : ∑ i ∈ range n, x ^ i / i ! ≤ exp x := calc ∑ i ∈ range n, x ^ i / i ! ≤ lim (⟨_, isCauSeq_re (exp' x)⟩ : CauSeq ℝ abs) := by refine le_lim (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp only [exp', const_apply, re_sum] norm_cast refine sum_le_sum_of_subset_of_nonneg (range_mono hj) fun _ _ _ ↦ ?_ positivity _ = exp x := by rw [exp, Complex.exp, ← cauSeqRe, lim_re] lemma pow_div_factorial_le_exp (hx : 0 ≤ x) (n : ℕ) : x ^ n / n ! ≤ exp x := calc x ^ n / n ! ≤ ∑ k ∈ range (n + 1), x ^ k / k ! := single_le_sum (f := fun k ↦ x ^ k / k !) (fun k _ ↦ by positivity) (self_mem_range_succ n) _ ≤ exp x := sum_le_exp_of_nonneg hx _ theorem quadratic_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : 1 + x + x ^ 2 / 2 ≤ exp x := calc 1 + x + x ^ 2 / 2 = ∑ i ∈ range 3, x ^ i / i ! := by simp only [sum_range_succ, range_one, sum_singleton, _root_.pow_zero, factorial, cast_one, ne_eq, one_ne_zero, not_false_eq_true, div_self, pow_one, mul_one, div_one, Nat.mul_one, cast_succ, add_right_inj] ring_nf _ ≤ exp x := sum_le_exp_of_nonneg hx 3 private theorem add_one_lt_exp_of_pos {x : ℝ} (hx : 0 < x) : x + 1 < exp x := (by nlinarith : x + 1 < 1 + x + x ^ 2 / 2).trans_le (quadratic_le_exp_of_nonneg hx.le) private theorem add_one_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : x + 1 ≤ exp x := by rcases eq_or_lt_of_le hx with (rfl | h) · simp exact (add_one_lt_exp_of_pos h).le theorem one_le_exp {x : ℝ} (hx : 0 ≤ x) : 1 ≤ exp x := by linarith [add_one_le_exp_of_nonneg hx] @[bound] theorem exp_pos (x : ℝ) : 0 < exp x := (le_total 0 x).elim (lt_of_lt_of_le zero_lt_one ∘ one_le_exp) fun h => by rw [← neg_neg x, Real.exp_neg] exact inv_pos.2 (lt_of_lt_of_le zero_lt_one (one_le_exp (neg_nonneg.2 h))) @[bound] lemma exp_nonneg (x : ℝ) : 0 ≤ exp x := x.exp_pos.le @[simp] theorem abs_exp (x : ℝ) : |exp x| = exp x := abs_of_pos (exp_pos _) lemma exp_abs_le (x : ℝ) : exp |x| ≤ exp x + exp (-x) := by cases le_total x 0 <;> simp [abs_of_nonpos, abs_of_nonneg, exp_nonneg, *] @[mono] theorem exp_strictMono : StrictMono exp := fun x y h => by rw [← sub_add_cancel y x, Real.exp_add] exact (lt_mul_iff_one_lt_left (exp_pos _)).2 (lt_of_lt_of_le (by linarith) (add_one_le_exp_of_nonneg (by linarith))) @[gcongr] theorem exp_lt_exp_of_lt {x y : ℝ} (h : x < y) : exp x < exp y := exp_strictMono h @[mono] theorem exp_monotone : Monotone exp := exp_strictMono.monotone @[gcongr, bound] theorem exp_le_exp_of_le {x y : ℝ} (h : x ≤ y) : exp x ≤ exp y := exp_monotone h @[simp] theorem exp_lt_exp {x y : ℝ} : exp x < exp y ↔ x < y := exp_strictMono.lt_iff_lt @[simp] theorem exp_le_exp {x y : ℝ} : exp x ≤ exp y ↔ x ≤ y := exp_strictMono.le_iff_le theorem exp_injective : Function.Injective exp := exp_strictMono.injective @[simp] theorem exp_eq_exp {x y : ℝ} : exp x = exp y ↔ x = y := exp_injective.eq_iff @[simp] theorem exp_eq_one_iff : exp x = 1 ↔ x = 0 := exp_injective.eq_iff' exp_zero @[simp] theorem one_lt_exp_iff {x : ℝ} : 1 < exp x ↔ 0 < x := by rw [← exp_zero, exp_lt_exp] @[bound] private alias ⟨_, Bound.one_lt_exp_of_pos⟩ := one_lt_exp_iff @[simp] theorem exp_lt_one_iff {x : ℝ} : exp x < 1 ↔ x < 0 := by rw [← exp_zero, exp_lt_exp] @[simp] theorem exp_le_one_iff {x : ℝ} : exp x ≤ 1 ↔ x ≤ 0 := exp_zero ▸ exp_le_exp @[simp] theorem one_le_exp_iff {x : ℝ} : 1 ≤ exp x ↔ 0 ≤ x := exp_zero ▸ exp_le_exp end Real namespace Complex theorem sum_div_factorial_le {α : Type*} [Field α] [LinearOrder α] [IsStrictOrderedRing α] (n j : ℕ) (hn : 0 < n) : (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) ≤ n.succ / (n.factorial * n) := calc (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) = ∑ m ∈ range (j - n), (1 / ((m + n).factorial : α)) := by refine sum_nbij' (· - n) (· + n) ?_ ?_ ?_ ?_ ?_ <;> simp +contextual [lt_tsub_iff_right, tsub_add_cancel_of_le] _ ≤ ∑ m ∈ range (j - n), ((n.factorial : α) * (n.succ : α) ^ m)⁻¹ := by simp_rw [one_div] gcongr rw [← Nat.cast_pow, ← Nat.cast_mul, Nat.cast_le, add_comm] exact Nat.factorial_mul_pow_le_factorial _ = (n.factorial : α)⁻¹ * ∑ m ∈ range (j - n), (n.succ : α)⁻¹ ^ m := by simp [mul_inv, ← mul_sum, ← sum_mul, mul_comm, inv_pow] _ = ((n.succ : α) - n.succ * (n.succ : α)⁻¹ ^ (j - n)) / (n.factorial * n) := by have h₁ : (n.succ : α) ≠ 1 := @Nat.cast_one α _ ▸ mt Nat.cast_inj.1 (mt Nat.succ.inj (pos_iff_ne_zero.1 hn)) have h₂ : (n.succ : α) ≠ 0 := by positivity have h₃ : (n.factorial * n : α) ≠ 0 := by positivity have h₄ : (n.succ - 1 : α) = n := by simp rw [geom_sum_inv h₁ h₂, eq_div_iff_mul_eq h₃, mul_comm _ (n.factorial * n : α), ← mul_assoc (n.factorial⁻¹ : α), ← mul_inv_rev, h₄, ← mul_assoc (n.factorial * n : α), mul_comm (n : α) n.factorial, mul_inv_cancel₀ h₃, one_mul, mul_comm] _ ≤ n.succ / (n.factorial * n : α) := by gcongr; apply sub_le_self; positivity theorem exp_bound {x : ℂ} (hx : ‖x‖ ≤ 1) {n : ℕ} (hn : 0 < n) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (1 / m.factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr rw [Complex.norm_pow] exact pow_le_one₀ (norm_nonneg _) hx _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (1 / m.factorial : ℝ) := by simp [abs_mul, abv_pow abs, abs_div, ← mul_sum] _ ≤ ‖x‖ ^ n * (n.succ * (n.factorial * n : ℝ)⁻¹) := by gcongr exact sum_div_factorial_le _ _ hn theorem exp_bound' {x : ℂ} {n : ℕ} (hx : ‖x‖ / n.succ ≤ 1 / 2) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 let k := j - n have hj : j = n + k := (add_tsub_cancel_of_le hj).symm rw [hj, sum_range_add_sub_sum_range] calc ‖∑ i ∈ range k, x ^ (n + i) / ((n + i).factorial : ℂ)‖ ≤ ∑ i ∈ range k, ‖x ^ (n + i) / ((n + i).factorial : ℂ)‖ := IsAbsoluteValue.abv_sum _ _ _ _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / (n + i).factorial := by simp [norm_natCast, Complex.norm_pow] _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / ((n.factorial : ℝ) * (n.succ : ℝ) ^ i) := ?_ _ = ∑ i ∈ range k, ‖x‖ ^ n / n.factorial * (‖x‖ ^ i / (n.succ : ℝ) ^ i) := ?_ _ ≤ ‖x‖ ^ n / ↑n.factorial * 2 := ?_ · gcongr exact mod_cast Nat.factorial_mul_pow_le_factorial · refine Finset.sum_congr rfl fun _ _ => ?_ simp only [pow_add, div_eq_inv_mul, mul_inv, mul_left_comm, mul_assoc] · rw [← mul_sum] gcongr simp_rw [← div_pow] rw [geom_sum_eq, div_le_iff_of_neg] · trans (-1 : ℝ) · linarith · simp only [neg_le_sub_iff_le_add, div_pow, Nat.cast_succ, le_add_iff_nonneg_left] positivity · linarith · linarith theorem norm_exp_sub_one_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1‖ ≤ 2 * ‖x‖ := calc ‖exp x - 1‖ = ‖exp x - ∑ m ∈ range 1, x ^ m / m.factorial‖ := by simp [sum_range_succ] _ ≤ ‖x‖ ^ 1 * ((Nat.succ 1 : ℝ) * ((Nat.factorial 1) * (1 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ = 2 * ‖x‖ := by simp [two_mul, mul_two, mul_add, mul_comm, add_mul, Nat.factorial] theorem norm_exp_sub_one_sub_id_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1 - x‖ ≤ ‖x‖ ^ 2 := calc ‖exp x - 1 - x‖ = ‖exp x - ∑ m ∈ range 2, x ^ m / m.factorial‖ := by simp [sub_eq_add_neg, sum_range_succ_comm, add_assoc, Nat.factorial] _ ≤ ‖x‖ ^ 2 * ((Nat.succ 2 : ℝ) * (Nat.factorial 2 * (2 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ ≤ ‖x‖ ^ 2 * 1 := by gcongr; norm_num [Nat.factorial] _ = ‖x‖ ^ 2 := by rw [mul_one] lemma norm_exp_sub_sum_le_exp_norm_sub_sum (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] calc ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ _ ≤ (∑ m ∈ range j, ‖x‖ ^ m / m.factorial) - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [sum_range_sub_sum_range hj, sum_range_sub_sum_range hj] refine (IsAbsoluteValue.abv_sum norm ..).trans_eq ?_ congr with i simp [Complex.norm_pow] _ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by gcongr exact Real.sum_le_exp_of_nonneg (norm_nonneg _) _ lemma norm_exp_le_exp_norm (x : ℂ) : ‖exp x‖ ≤ Real.exp ‖x‖ := by convert norm_exp_sub_sum_le_exp_norm_sub_sum x 0 using 1 <;> simp lemma norm_exp_sub_sum_le_norm_mul_exp (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ _ rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (‖x‖ ^ (m - n) / (m - n).factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr with i hi · rw [Complex.norm_pow] · simp _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (‖x‖ ^ (m - n) / (m - n).factorial) := by rw [← mul_sum] _ = ‖x‖ ^ n * ∑ m ∈ range (j - n), (‖x‖ ^ m / m.factorial) := by congr 1 refine (sum_bij (fun m hm ↦ m + n) ?_ ?_ ?_ ?_).symm · intro a ha simp only [mem_filter, mem_range, le_add_iff_nonneg_left, zero_le, and_true] simp only [mem_range] at ha rwa [← lt_tsub_iff_right] · intro a ha b hb hab simpa using hab · intro b hb simp only [mem_range, exists_prop] simp only [mem_filter, mem_range] at hb refine ⟨b - n, ?_, ?_⟩ · rw [tsub_lt_tsub_iff_right hb.2] exact hb.1 · rw [tsub_add_cancel_of_le hb.2] · simp _ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by gcongr refine Real.sum_le_exp_of_nonneg ?_ _ exact norm_nonneg _ @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_le := norm_exp_sub_one_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_sub_id_le := norm_exp_sub_one_sub_id_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_exp_abs_sub_sum := norm_exp_sub_sum_le_exp_norm_sub_sum @[deprecated (since := "2025-02-16")] alias abs_exp_le_exp_abs := norm_exp_le_exp_norm @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_abs_mul_exp := norm_exp_sub_sum_le_norm_mul_exp end Complex namespace Real open Complex Finset nonrec theorem exp_bound {x : ℝ} (hx : |x| ≤ 1) {n : ℕ} (hn : 0 < n) : |exp x - ∑ m ∈ range n, x ^ m / m.factorial| ≤ |x| ^ n * (n.succ / (n.factorial * n)) := by have hxc : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx convert exp_bound hxc hn using 2 <;> norm_cast theorem exp_bound' {x : ℝ} (h1 : 0 ≤ x) (h2 : x ≤ 1) {n : ℕ} (hn : 0 < n) : Real.exp x ≤ (∑ m ∈ Finset.range n, x ^ m / m.factorial) + x ^ n * (n + 1) / (n.factorial * n) := by have h3 : |x| = x := by simpa have h4 : |x| ≤ 1 := by rwa [h3] have h' := Real.exp_bound h4 hn rw [h3] at h' have h'' := (abs_sub_le_iff.1 h').1 have t := sub_le_iff_le_add'.1 h'' simpa [mul_div_assoc] using t theorem abs_exp_sub_one_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1| ≤ 2 * |x| := by have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_le (x := x) this theorem abs_exp_sub_one_sub_id_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1 - x| ≤ x ^ 2 := by rw [← sq_abs] have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_sub_id_le this /-- A finite initial segment of the exponential series, followed by an arbitrary tail. For fixed `n` this is just a linear map wrt `r`, and each map is a simple linear function of the previous (see `expNear_succ`), with `expNear n x r ⟶ exp x` as `n ⟶ ∞`, for any `r`. -/ noncomputable def expNear (n : ℕ) (x r : ℝ) : ℝ := (∑ m ∈ range n, x ^ m / m.factorial) + x ^ n / n.factorial * r @[simp] theorem expNear_zero (x r) : expNear 0 x r = r := by simp [expNear] @[simp] theorem expNear_succ (n x r) : expNear (n + 1) x r = expNear n x (1 + x / (n + 1) * r) := by simp [expNear, range_succ, mul_add, add_left_comm, add_assoc, pow_succ, div_eq_mul_inv, mul_inv, Nat.factorial] ac_rfl theorem expNear_sub (n x r₁ r₂) : expNear n x r₁ - expNear n x r₂ = x ^ n / n.factorial * (r₁ - r₂) := by simp [expNear, mul_sub] theorem exp_approx_end (n m : ℕ) (x : ℝ) (e₁ : n + 1 = m) (h : |x| ≤ 1) : |exp x - expNear m x 0| ≤ |x| ^ m / m.factorial * ((m + 1) / m) := by simp only [expNear, mul_zero, add_zero] convert exp_bound (n := m) h ?_ using 1 · field_simp [mul_comm] · omega theorem exp_approx_succ {n} {x a₁ b₁ : ℝ} (m : ℕ) (e₁ : n + 1 = m) (a₂ b₂ : ℝ) (e : |1 + x / m * a₂ - a₁| ≤ b₁ - |x| / m * b₂) (h : |exp x - expNear m x a₂| ≤ |x| ^ m / m.factorial * b₂) : |exp x - expNear n x a₁| ≤ |x| ^ n / n.factorial * b₁ := by refine (abs_sub_le _ _ _).trans ((add_le_add_right h _).trans ?_) subst e₁; rw [expNear_succ, expNear_sub, abs_mul] convert mul_le_mul_of_nonneg_left (a := |x| ^ n / ↑(Nat.factorial n)) (le_sub_iff_add_le'.1 e) ?_ using 1 · simp [mul_add, pow_succ', div_eq_mul_inv, abs_mul, abs_inv, ← pow_abs, mul_inv, Nat.factorial] ac_rfl · simp [div_nonneg, abs_nonneg] theorem exp_approx_end' {n} {x a b : ℝ} (m : ℕ) (e₁ : n + 1 = m) (rm : ℝ) (er : ↑m = rm) (h : |x| ≤ 1) (e : |1 - a| ≤ b - |x| / rm * ((rm + 1) / rm)) : |exp x - expNear n x a| ≤ |x| ^ n / n.factorial * b := by subst er exact exp_approx_succ _ e₁ _ _ (by simpa using e) (exp_approx_end _ _ _ e₁ h) theorem exp_1_approx_succ_eq {n} {a₁ b₁ : ℝ} {m : ℕ} (en : n + 1 = m) {rm : ℝ} (er : ↑m = rm) (h : |exp 1 - expNear m 1 ((a₁ - 1) * rm)| ≤ |1| ^ m / m.factorial * (b₁ * rm)) : |exp 1 - expNear n 1 a₁| ≤ |1| ^ n / n.factorial * b₁ := by subst er refine exp_approx_succ _ en _ _ ?_ h field_simp [show (m : ℝ) ≠ 0 by norm_cast; omega] theorem exp_approx_start (x a b : ℝ) (h : |exp x - expNear 0 x a| ≤ |x| ^ 0 / Nat.factorial 0 * b) : |exp x - a| ≤ b := by simpa using h theorem exp_bound_div_one_sub_of_interval' {x : ℝ} (h1 : 0 < x) (h2 : x < 1) : Real.exp x < 1 / (1 - x) := by have H : 0 < 1 - (1 + x + x ^ 2) * (1 - x) := calc 0 < x ^ 3 := by positivity _ = 1 - (1 + x + x ^ 2) * (1 - x) := by ring calc exp x ≤ _ := exp_bound' h1.le h2.le zero_lt_three _ ≤ 1 + x + x ^ 2 := by -- Porting note: was `norm_num [Finset.sum] <;> nlinarith` -- This proof should be restored after the norm_num plugin for big operators is ported. -- (It may also need the positivity extensions in https://github.com/leanprover-community/mathlib4/pull/3907.) rw [show 3 = 1 + 1 + 1 from rfl] repeat rw [Finset.sum_range_succ] norm_num [Nat.factorial] nlinarith _ < 1 / (1 - x) := by rw [lt_div_iff₀] <;> nlinarith theorem exp_bound_div_one_sub_of_interval {x : ℝ} (h1 : 0 ≤ x) (h2 : x < 1) : Real.exp x ≤ 1 / (1 - x) := by rcases eq_or_lt_of_le h1 with (rfl | h1) · simp · exact (exp_bound_div_one_sub_of_interval' h1 h2).le theorem add_one_lt_exp {x : ℝ} (hx : x ≠ 0) : x + 1 < Real.exp x := by obtain hx | hx := hx.symm.lt_or_lt · exact add_one_lt_exp_of_pos hx obtain h' | h' := le_or_lt 1 (-x) · linarith [x.exp_pos] have hx' : 0 < x + 1 := by linarith simpa [add_comm, exp_neg, inv_lt_inv₀ (exp_pos _) hx'] using exp_bound_div_one_sub_of_interval' (neg_pos.2 hx) h' theorem add_one_le_exp (x : ℝ) : x + 1 ≤ Real.exp x := by obtain rfl | hx := eq_or_ne x 0 · simp · exact (add_one_lt_exp hx).le lemma one_sub_lt_exp_neg {x : ℝ} (hx : x ≠ 0) : 1 - x < exp (-x) := (sub_eq_neg_add _ _).trans_lt <| add_one_lt_exp <| neg_ne_zero.2 hx lemma one_sub_le_exp_neg (x : ℝ) : 1 - x ≤ exp (-x) := (sub_eq_neg_add _ _).trans_le <| add_one_le_exp _ theorem one_sub_div_pow_le_exp_neg {n : ℕ} {t : ℝ} (ht' : t ≤ n) : (1 - t / n) ^ n ≤ exp (-t) := by rcases eq_or_ne n 0 with (rfl | hn) · simp rwa [Nat.cast_zero] at ht' calc (1 - t / n) ^ n ≤ rexp (-(t / n)) ^ n := by gcongr · exact sub_nonneg.2 <| div_le_one_of_le₀ ht' n.cast_nonneg · exact one_sub_le_exp_neg _ _ = rexp (-t) := by rw [← Real.exp_nat_mul, mul_neg, mul_comm, div_mul_cancel₀]; positivity lemma le_inv_mul_exp (x : ℝ) {c : ℝ} (hc : 0 < c) : x ≤ c⁻¹ * exp (c * x) := by rw [le_inv_mul_iff₀ hc] calc c * x _ ≤ c * x + 1 := le_add_of_nonneg_right zero_le_one _ ≤ _ := Real.add_one_le_exp (c * x) end Real namespace Mathlib.Meta.Positivity open Lean.Meta Qq /-- Extension for the `positivity` tactic: `Real.exp` is always positive. -/ @[positivity Real.exp _] def evalExp : PositivityExt where eval {u α} _ _ e := do match u, α, e with | 0, ~q(ℝ), ~q(Real.exp $a) => assertInstancesCommute pure (.positive q(Real.exp_pos $a)) | _, _, _ => throwError "not Real.exp" end Mathlib.Meta.Positivity namespace Complex @[simp] theorem norm_exp_ofReal (x : ℝ) : ‖exp x‖ = Real.exp x := by rw [← ofReal_exp] exact Complex.norm_of_nonneg (le_of_lt (Real.exp_pos _)) @[deprecated (since := "2025-02-16")] alias abs_exp_ofReal := norm_exp_ofReal end Complex
Mathlib/Data/Complex/Exponential.lean
825
825
/- Copyright (c) 2014 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Leonardo de Moura -/ import Batteries.Data.Nat.Gcd import Mathlib.Algebra.Group.Nat.Units import Mathlib.Algebra.GroupWithZero.Divisibility import Mathlib.Algebra.GroupWithZero.Nat /-! # Properties of `Nat.gcd`, `Nat.lcm`, and `Nat.Coprime` Definitions are provided in batteries. Generalizations of these are provided in a later file as `GCDMonoid.gcd` and `GCDMonoid.lcm`. Note that the global `IsCoprime` is not a straightforward generalization of `Nat.Coprime`, see `Nat.isCoprime_iff_coprime` for the connection between the two. Most of this file could be moved to batteries as well. -/ assert_not_exists OrderedCommMonoid namespace Nat variable {a a₁ a₂ b b₁ b₂ c : ℕ} /-! ### `gcd` -/ theorem gcd_greatest {a b d : ℕ} (hda : d ∣ a) (hdb : d ∣ b) (hd : ∀ e : ℕ, e ∣ a → e ∣ b → e ∣ d) : d = a.gcd b := (dvd_antisymm (hd _ (gcd_dvd_left a b) (gcd_dvd_right a b)) (dvd_gcd hda hdb)).symm /-! Lemmas where one argument consists of addition of a multiple of the other -/ @[simp] theorem pow_sub_one_mod_pow_sub_one (a b c : ℕ) : (a ^ c - 1) % (a ^ b - 1) = a ^ (c % b) - 1 := by rcases eq_zero_or_pos a with rfl | ha0 · simp [zero_pow_eq]; split_ifs <;> simp rcases Nat.eq_or_lt_of_le ha0 with rfl | ha1 · simp rcases eq_zero_or_pos b with rfl | hb0 · simp rcases lt_or_le c b with h | h · rw [mod_eq_of_lt, mod_eq_of_lt h] rwa [Nat.sub_lt_sub_iff_right (one_le_pow c a ha0), Nat.pow_lt_pow_iff_right ha1] · suffices a ^ (c - b + b) - 1 = a ^ (c - b) * (a ^ b - 1) + (a ^ (c - b) - 1) by rw [← Nat.sub_add_cancel h, add_mod_right, this, add_mod, mul_mod, mod_self, mul_zero, zero_mod, zero_add, mod_mod, pow_sub_one_mod_pow_sub_one] rw [← Nat.add_sub_assoc (one_le_pow (c - b) a ha0), ← mul_add_one, pow_add, Nat.sub_add_cancel (one_le_pow b a ha0)] @[simp] theorem pow_sub_one_gcd_pow_sub_one (a b c : ℕ) : gcd (a ^ b - 1) (a ^ c - 1) = a ^ gcd b c - 1 := by rcases eq_zero_or_pos b with rfl | hb · simp replace hb : c % b < b := mod_lt c hb rw [gcd_rec, pow_sub_one_mod_pow_sub_one, pow_sub_one_gcd_pow_sub_one, ← gcd_rec] /-! ### `lcm` -/ theorem lcm_dvd_mul (m n : ℕ) : lcm m n ∣ m * n := lcm_dvd (dvd_mul_right _ _) (dvd_mul_left _ _) theorem lcm_dvd_iff {m n k : ℕ} : lcm m n ∣ k ↔ m ∣ k ∧ n ∣ k := ⟨fun h => ⟨(dvd_lcm_left _ _).trans h, (dvd_lcm_right _ _).trans h⟩, and_imp.2 lcm_dvd⟩ theorem lcm_pos {m n : ℕ} : 0 < m → 0 < n → 0 < m.lcm n := by simp_rw [Nat.pos_iff_ne_zero] exact lcm_ne_zero theorem lcm_mul_left {m n k : ℕ} : (m * n).lcm (m * k) = m * n.lcm k := by apply dvd_antisymm · exact lcm_dvd (mul_dvd_mul_left m (dvd_lcm_left n k)) (mul_dvd_mul_left m (dvd_lcm_right n k)) · have h : m ∣ lcm (m * n) (m * k) := (dvd_mul_right m n).trans (dvd_lcm_left (m * n) (m * k)) rw [← dvd_div_iff_mul_dvd h, lcm_dvd_iff, dvd_div_iff_mul_dvd h, dvd_div_iff_mul_dvd h, ← lcm_dvd_iff] theorem lcm_mul_right {m n k : ℕ} : (m * n).lcm (k * n) = m.lcm k * n := by rw [mul_comm, mul_comm k n, lcm_mul_left, mul_comm] /-! ### `Coprime` See also `Nat.coprime_of_dvd` and `Nat.coprime_of_dvd'` to prove `Nat.Coprime m n`. -/ theorem Coprime.lcm_eq_mul {m n : ℕ} (h : Coprime m n) : lcm m n = m * n := by rw [← one_mul (lcm m n), ← h.gcd_eq_one, gcd_mul_lcm] theorem Coprime.symmetric : Symmetric Coprime := fun _ _ => Coprime.symm theorem Coprime.dvd_mul_right {m n k : ℕ} (H : Coprime k n) : k ∣ m * n ↔ k ∣ m := ⟨H.dvd_of_dvd_mul_right, fun h => dvd_mul_of_dvd_left h n⟩ theorem Coprime.dvd_mul_left {m n k : ℕ} (H : Coprime k m) : k ∣ m * n ↔ k ∣ n := ⟨H.dvd_of_dvd_mul_left, fun h => dvd_mul_of_dvd_right h m⟩ @[simp] theorem coprime_add_self_right {m n : ℕ} : Coprime m (n + m) ↔ Coprime m n := by rw [Coprime, Coprime, gcd_add_self_right] @[simp] theorem coprime_self_add_right {m n : ℕ} : Coprime m (m + n) ↔ Coprime m n := by rw [add_comm, coprime_add_self_right] @[simp] theorem coprime_add_self_left {m n : ℕ} : Coprime (m + n) n ↔ Coprime m n := by rw [Coprime, Coprime, gcd_add_self_left] @[simp] theorem coprime_self_add_left {m n : ℕ} : Coprime (m + n) m ↔ Coprime n m := by rw [Coprime, Coprime, gcd_self_add_left] @[simp] theorem coprime_add_mul_right_right (m n k : ℕ) : Coprime m (n + k * m) ↔ Coprime m n := by rw [Coprime, Coprime, gcd_add_mul_right_right] @[simp] theorem coprime_add_mul_left_right (m n k : ℕ) : Coprime m (n + m * k) ↔ Coprime m n := by rw [Coprime, Coprime, gcd_add_mul_left_right] @[simp] theorem coprime_mul_right_add_right (m n k : ℕ) : Coprime m (k * m + n) ↔ Coprime m n := by rw [Coprime, Coprime, gcd_mul_right_add_right] @[simp] theorem coprime_mul_left_add_right (m n k : ℕ) : Coprime m (m * k + n) ↔ Coprime m n := by rw [Coprime, Coprime, gcd_mul_left_add_right] @[simp] theorem coprime_add_mul_right_left (m n k : ℕ) : Coprime (m + k * n) n ↔ Coprime m n := by rw [Coprime, Coprime, gcd_add_mul_right_left] @[simp] theorem coprime_add_mul_left_left (m n k : ℕ) : Coprime (m + n * k) n ↔ Coprime m n := by rw [Coprime, Coprime, gcd_add_mul_left_left] @[simp] theorem coprime_mul_right_add_left (m n k : ℕ) : Coprime (k * n + m) n ↔ Coprime m n := by rw [Coprime, Coprime, gcd_mul_right_add_left] @[simp] theorem coprime_mul_left_add_left (m n k : ℕ) : Coprime (n * k + m) n ↔ Coprime m n := by rw [Coprime, Coprime, gcd_mul_left_add_left] lemma add_coprime_iff_left (h : c ∣ b) : Coprime (a + b) c ↔ Coprime a c := by obtain ⟨n, rfl⟩ := h; simp lemma add_coprime_iff_right (h : c ∣ a) : Coprime (a + b) c ↔ Coprime b c := by obtain ⟨n, rfl⟩ := h; simp lemma coprime_add_iff_left (h : a ∣ c) : Coprime a (b + c) ↔ Coprime a b := by obtain ⟨n, rfl⟩ := h; simp lemma coprime_add_iff_right (h : a ∣ b) : Coprime a (b + c) ↔ Coprime a c := by obtain ⟨n, rfl⟩ := h; simp -- TODO: Replace `Nat.Coprime.coprime_dvd_left` lemma Coprime.of_dvd_left (ha : a₁ ∣ a₂) (h : Coprime a₂ b) : Coprime a₁ b := h.coprime_dvd_left ha -- TODO: Replace `Nat.Coprime.coprime_dvd_right` lemma Coprime.of_dvd_right (hb : b₁ ∣ b₂) (h : Coprime a b₂) : Coprime a b₁ := h.coprime_dvd_right hb lemma Coprime.of_dvd (ha : a₁ ∣ a₂) (hb : b₁ ∣ b₂) (h : Coprime a₂ b₂) : Coprime a₁ b₁ := (h.of_dvd_left ha).of_dvd_right hb @[simp] theorem coprime_sub_self_left {m n : ℕ} (h : m ≤ n) : Coprime (n - m) m ↔ Coprime n m := by rw [Coprime, Coprime, gcd_sub_self_left h] @[simp] theorem coprime_sub_self_right {m n : ℕ} (h : m ≤ n) : Coprime m (n - m) ↔ Coprime m n := by rw [Coprime, Coprime, gcd_sub_self_right h] @[simp] theorem coprime_self_sub_left {m n : ℕ} (h : m ≤ n) : Coprime (n - m) n ↔ Coprime m n := by rw [Coprime, Coprime, gcd_self_sub_left h] @[simp] theorem coprime_self_sub_right {m n : ℕ} (h : m ≤ n) : Coprime n (n - m) ↔ Coprime n m := by rw [Coprime, Coprime, gcd_self_sub_right h] @[simp] theorem coprime_pow_left_iff {n : ℕ} (hn : 0 < n) (a b : ℕ) : Nat.Coprime (a ^ n) b ↔ Nat.Coprime a b := by obtain ⟨n, rfl⟩ := exists_eq_succ_of_ne_zero (Nat.ne_of_gt hn) rw [Nat.pow_succ, Nat.coprime_mul_iff_left] exact ⟨And.right, fun hab => ⟨hab.pow_left _, hab⟩⟩ @[simp] theorem coprime_pow_right_iff {n : ℕ} (hn : 0 < n) (a b : ℕ) : Nat.Coprime a (b ^ n) ↔ Nat.Coprime a b := by rw [Nat.coprime_comm, coprime_pow_left_iff hn, Nat.coprime_comm] theorem not_coprime_zero_zero : ¬Coprime 0 0 := by simp theorem coprime_one_left_iff (n : ℕ) : Coprime 1 n ↔ True := by simp [Coprime] theorem coprime_one_right_iff (n : ℕ) : Coprime n 1 ↔ True := by simp [Coprime] theorem gcd_mul_of_coprime_of_dvd {a b c : ℕ} (hac : Coprime a c) (b_dvd_c : b ∣ c) : gcd (a * b) c = b := by rcases exists_eq_mul_left_of_dvd b_dvd_c with ⟨d, rfl⟩ rw [gcd_mul_right] convert one_mul b exact Coprime.coprime_mul_right_right hac theorem Coprime.eq_of_mul_eq_zero {m n : ℕ} (h : m.Coprime n) (hmn : m * n = 0) : m = 0 ∧ n = 1 ∨ m = 1 ∧ n = 0 := (Nat.mul_eq_zero.mp hmn).imp (fun hm => ⟨hm, n.coprime_zero_left.mp <| hm ▸ h⟩) fun hn => let eq := hn ▸ h.symm ⟨m.coprime_zero_left.mp <| eq, hn⟩ @[deprecated (since := "2025-04-01")] alias prodDvdAndDvdOfDvdProd := dvdProdDvdOfDvdProd theorem coprime_iff_isRelPrime {m n : ℕ} : m.Coprime n ↔ IsRelPrime m n := by simp_rw [coprime_iff_gcd_eq_one, IsRelPrime, ← and_imp, ← dvd_gcd_iff, isUnit_iff_dvd_one] exact ⟨fun h _ ↦ (h ▸ ·), (dvd_one.mp <| · dvd_rfl)⟩ /-- If `k:ℕ` divides coprime `a` and `b` then `k = 1` -/ theorem eq_one_of_dvd_coprimes {a b k : ℕ} (h_ab_coprime : Coprime a b) (hka : k ∣ a) (hkb : k ∣ b) : k = 1 := dvd_one.mp (isUnit_iff_dvd_one.mp <| coprime_iff_isRelPrime.mp h_ab_coprime hka hkb) theorem Coprime.mul_add_mul_ne_mul {m n a b : ℕ} (cop : Coprime m n) (ha : a ≠ 0) (hb : b ≠ 0) : a * m + b * n ≠ m * n := by intro h obtain ⟨x, rfl⟩ : n ∣ a := cop.symm.dvd_of_dvd_mul_right ((Nat.dvd_add_iff_left (Nat.dvd_mul_left n b)).mpr ((congr_arg _ h).mpr (Nat.dvd_mul_left n m))) obtain ⟨y, rfl⟩ : m ∣ b := cop.dvd_of_dvd_mul_right ((Nat.dvd_add_iff_right (Nat.dvd_mul_left m (n * x))).mpr ((congr_arg _ h).mpr (Nat.dvd_mul_right m n))) rw [mul_comm, mul_ne_zero_iff, ← one_le_iff_ne_zero] at ha hb refine mul_ne_zero hb.2 ha.2 (eq_zero_of_mul_eq_self_left (ne_of_gt (add_le_add ha.1 hb.1)) ?_)
rw [← mul_assoc, ← h, Nat.add_mul, Nat.add_mul, mul_comm _ n, ← mul_assoc, mul_comm y] variable {x n m : ℕ} theorem gcd_mul_gcd_eq_iff_dvd_mul_of_coprime (hcop : Coprime n m) :
Mathlib/Data/Nat/GCD/Basic.lean
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/- Copyright (c) 2022 Andrew Yang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Andrew Yang -/ import Mathlib.CategoryTheory.Adjunction.FullyFaithful import Mathlib.CategoryTheory.Adjunction.Limits import Mathlib.CategoryTheory.Limits.Shapes.Pullback.CommSq import Mathlib.CategoryTheory.Limits.Shapes.StrictInitial import Mathlib.CategoryTheory.Limits.FunctorCategory.Basic import Mathlib.CategoryTheory.Limits.Constructions.FiniteProductsOfBinaryProducts /-! # Universal colimits and van Kampen colimits ## Main definitions - `CategoryTheory.IsUniversalColimit`: A (colimit) cocone over a diagram `F : J ⥤ C` is universal if it is stable under pullbacks. - `CategoryTheory.IsVanKampenColimit`: A (colimit) cocone over a diagram `F : J ⥤ C` is van Kampen if for every cocone `c'` over the pullback of the diagram `F' : J ⥤ C'`, `c'` is colimiting iff `c'` is the pullback of `c`. ## References - https://ncatlab.org/nlab/show/van+Kampen+colimit - [Stephen Lack and Paweł Sobociński, Adhesive Categories][adhesive2004] -/ open CategoryTheory.Limits namespace CategoryTheory universe v' u' v u variable {J : Type v'} [Category.{u'} J] {C : Type u} [Category.{v} C] variable {K : Type*} [Category K] {D : Type*} [Category D] section NatTrans /-- A natural transformation is equifibered if every commutative square of the following form is a pullback. ``` F(X) → F(Y) ↓ ↓ G(X) → G(Y) ``` -/ def NatTrans.Equifibered {F G : J ⥤ C} (α : F ⟶ G) : Prop := ∀ ⦃i j : J⦄ (f : i ⟶ j), IsPullback (F.map f) (α.app i) (α.app j) (G.map f) theorem NatTrans.equifibered_of_isIso {F G : J ⥤ C} (α : F ⟶ G) [IsIso α] : Equifibered α := fun _ _ f => IsPullback.of_vert_isIso ⟨NatTrans.naturality _ f⟩ theorem NatTrans.Equifibered.comp {F G H : J ⥤ C} {α : F ⟶ G} {β : G ⟶ H} (hα : Equifibered α) (hβ : Equifibered β) : Equifibered (α ≫ β) := fun _ _ f => (hα f).paste_vert (hβ f) theorem NatTrans.Equifibered.whiskerRight {F G : J ⥤ C} {α : F ⟶ G} (hα : Equifibered α) (H : C ⥤ D) [∀ (i j : J) (f : j ⟶ i), PreservesLimit (cospan (α.app i) (G.map f)) H] : Equifibered (whiskerRight α H) := fun _ _ f => (hα f).map H theorem NatTrans.Equifibered.whiskerLeft {K : Type*} [Category K] {F G : J ⥤ C} {α : F ⟶ G} (hα : Equifibered α) (H : K ⥤ J) : Equifibered (whiskerLeft H α) := fun _ _ f => hα (H.map f) theorem mapPair_equifibered {F F' : Discrete WalkingPair ⥤ C} (α : F ⟶ F') : NatTrans.Equifibered α := by rintro ⟨⟨⟩⟩ ⟨j⟩ ⟨⟨rfl : _ = j⟩⟩ all_goals dsimp; simp only [Discrete.functor_map_id] exact IsPullback.of_horiz_isIso ⟨by simp only [Category.comp_id, Category.id_comp]⟩ theorem NatTrans.equifibered_of_discrete {ι : Type*} {F G : Discrete ι ⥤ C} (α : F ⟶ G) : NatTrans.Equifibered α := by rintro ⟨i⟩ ⟨j⟩ ⟨⟨rfl : i = j⟩⟩ simp only [Discrete.functor_map_id] exact IsPullback.of_horiz_isIso ⟨by rw [Category.id_comp, Category.comp_id]⟩ end NatTrans /-- A (colimit) cocone over a diagram `F : J ⥤ C` is universal if it is stable under pullbacks. -/ def IsUniversalColimit {F : J ⥤ C} (c : Cocone F) : Prop := ∀ ⦃F' : J ⥤ C⦄ (c' : Cocone F') (α : F' ⟶ F) (f : c'.pt ⟶ c.pt) (_ : α ≫ c.ι = c'.ι ≫ (Functor.const J).map f) (_ : NatTrans.Equifibered α), (∀ j : J, IsPullback (c'.ι.app j) (α.app j) f (c.ι.app j)) → Nonempty (IsColimit c') /-- A (colimit) cocone over a diagram `F : J ⥤ C` is van Kampen if for every cocone `c'` over the pullback of the diagram `F' : J ⥤ C'`, `c'` is colimiting iff `c'` is the pullback of `c`. TODO: Show that this is iff the functor `C ⥤ Catᵒᵖ` sending `x` to `C/x` preserves it. TODO: Show that this is iff the inclusion functor `C ⥤ Span(C)` preserves it. -/ def IsVanKampenColimit {F : J ⥤ C} (c : Cocone F) : Prop := ∀ ⦃F' : J ⥤ C⦄ (c' : Cocone F') (α : F' ⟶ F) (f : c'.pt ⟶ c.pt) (_ : α ≫ c.ι = c'.ι ≫ (Functor.const J).map f) (_ : NatTrans.Equifibered α), Nonempty (IsColimit c') ↔ ∀ j : J, IsPullback (c'.ι.app j) (α.app j) f (c.ι.app j) theorem IsVanKampenColimit.isUniversal {F : J ⥤ C} {c : Cocone F} (H : IsVanKampenColimit c) : IsUniversalColimit c := fun _ c' α f h hα => (H c' α f h hα).mpr /-- A universal colimit is a colimit. -/ noncomputable def IsUniversalColimit.isColimit {F : J ⥤ C} {c : Cocone F} (h : IsUniversalColimit c) : IsColimit c := by refine ((h c (𝟙 F) (𝟙 c.pt :) (by rw [Functor.map_id, Category.comp_id, Category.id_comp]) (NatTrans.equifibered_of_isIso _)) fun j => ?_).some haveI : IsIso (𝟙 c.pt) := inferInstance exact IsPullback.of_vert_isIso ⟨by simp⟩ /-- A van Kampen colimit is a colimit. -/ noncomputable def IsVanKampenColimit.isColimit {F : J ⥤ C} {c : Cocone F} (h : IsVanKampenColimit c) : IsColimit c := h.isUniversal.isColimit theorem IsInitial.isVanKampenColimit [HasStrictInitialObjects C] {X : C} (h : IsInitial X) : IsVanKampenColimit (asEmptyCocone X) := by intro F' c' α f hf hα have : F' = Functor.empty C := by apply Functor.hext <;> rintro ⟨⟨⟩⟩ subst this haveI := h.isIso_to f refine ⟨by rintro _ ⟨⟨⟩⟩, fun _ => ⟨IsColimit.ofIsoColimit h (Cocones.ext (asIso f).symm <| by rintro ⟨⟨⟩⟩)⟩⟩ section Functor theorem IsUniversalColimit.of_iso {F : J ⥤ C} {c c' : Cocone F} (hc : IsUniversalColimit c) (e : c ≅ c') : IsUniversalColimit c' := by intro F' c'' α f h hα H have : c'.ι ≫ (Functor.const J).map e.inv.hom = c.ι := by ext j exact e.inv.2 j apply hc c'' α (f ≫ e.inv.1) (by rw [Functor.map_comp, ← reassoc_of% h, this]) hα intro j rw [← Category.comp_id (α.app j)] have : IsIso e.inv.hom := Functor.map_isIso (Cocones.forget _) e.inv exact (H j).paste_vert (IsPullback.of_vert_isIso ⟨by simp⟩) theorem IsVanKampenColimit.of_iso {F : J ⥤ C} {c c' : Cocone F} (H : IsVanKampenColimit c) (e : c ≅ c') : IsVanKampenColimit c' := by intro F' c'' α f h hα have : c'.ι ≫ (Functor.const J).map e.inv.hom = c.ι := by ext j exact e.inv.2 j rw [H c'' α (f ≫ e.inv.1) (by rw [Functor.map_comp, ← reassoc_of% h, this]) hα] apply forall_congr' intro j conv_lhs => rw [← Category.comp_id (α.app j)] haveI : IsIso e.inv.hom := Functor.map_isIso (Cocones.forget _) e.inv exact (IsPullback.of_vert_isIso ⟨by simp⟩).paste_vert_iff (NatTrans.congr_app h j).symm theorem IsVanKampenColimit.precompose_isIso {F G : J ⥤ C} (α : F ⟶ G) [IsIso α] {c : Cocone G} (hc : IsVanKampenColimit c) : IsVanKampenColimit ((Cocones.precompose α).obj c) := by intros F' c' α' f e hα refine (hc c' (α' ≫ α) f ((Category.assoc _ _ _).trans e) (hα.comp (NatTrans.equifibered_of_isIso _))).trans ?_ apply forall_congr' intro j simp only [Functor.const_obj_obj, NatTrans.comp_app, Cocones.precompose_obj_pt, Cocones.precompose_obj_ι] have : IsPullback (α.app j ≫ c.ι.app j) (α.app j) (𝟙 _) (c.ι.app j) := IsPullback.of_vert_isIso ⟨Category.comp_id _⟩ rw [← IsPullback.paste_vert_iff this _, Category.comp_id] exact (congr_app e j).symm theorem IsUniversalColimit.precompose_isIso {F G : J ⥤ C} (α : F ⟶ G) [IsIso α] {c : Cocone G} (hc : IsUniversalColimit c) : IsUniversalColimit ((Cocones.precompose α).obj c) := by intros F' c' α' f e hα H apply (hc c' (α' ≫ α) f ((Category.assoc _ _ _).trans e) (hα.comp (NatTrans.equifibered_of_isIso _))) intro j simp only [Functor.const_obj_obj, NatTrans.comp_app, Cocones.precompose_obj_pt, Cocones.precompose_obj_ι] rw [← Category.comp_id f] exact (H j).paste_vert (IsPullback.of_vert_isIso ⟨Category.comp_id _⟩) theorem IsVanKampenColimit.precompose_isIso_iff {F G : J ⥤ C} (α : F ⟶ G) [IsIso α] {c : Cocone G} : IsVanKampenColimit ((Cocones.precompose α).obj c) ↔ IsVanKampenColimit c := ⟨fun hc ↦ IsVanKampenColimit.of_iso (IsVanKampenColimit.precompose_isIso (inv α) hc) (Cocones.ext (Iso.refl _) (by simp)), IsVanKampenColimit.precompose_isIso α⟩ theorem IsUniversalColimit.of_mapCocone (G : C ⥤ D) {F : J ⥤ C} {c : Cocone F} [PreservesLimitsOfShape WalkingCospan G] [ReflectsColimitsOfShape J G] (hc : IsUniversalColimit (G.mapCocone c)) : IsUniversalColimit c := fun F' c' α f h hα H ↦ ⟨isColimitOfReflects _ (hc (G.mapCocone c') (whiskerRight α G) (G.map f) (by ext j; simpa using G.congr_map (NatTrans.congr_app h j)) (hα.whiskerRight G) (fun j ↦ (H j).map G)).some⟩ theorem IsVanKampenColimit.of_mapCocone (G : C ⥤ D) {F : J ⥤ C} {c : Cocone F} [∀ (i j : J) (X : C) (f : X ⟶ F.obj j) (g : i ⟶ j), PreservesLimit (cospan f (F.map g)) G] [∀ (i : J) (X : C) (f : X ⟶ c.pt), PreservesLimit (cospan f (c.ι.app i)) G] [ReflectsLimitsOfShape WalkingCospan G] [PreservesColimitsOfShape J G] [ReflectsColimitsOfShape J G] (H : IsVanKampenColimit (G.mapCocone c)) : IsVanKampenColimit c := by intro F' c' α f h hα refine (Iff.trans ?_ (H (G.mapCocone c') (whiskerRight α G) (G.map f) (by ext j; simpa using G.congr_map (NatTrans.congr_app h j)) (hα.whiskerRight G))).trans (forall_congr' fun j => ?_) · exact ⟨fun h => ⟨isColimitOfPreserves G h.some⟩, fun h => ⟨isColimitOfReflects G h.some⟩⟩ · exact IsPullback.map_iff G (NatTrans.congr_app h.symm j) theorem IsVanKampenColimit.mapCocone_iff (G : C ⥤ D) {F : J ⥤ C} {c : Cocone F} [G.IsEquivalence] : IsVanKampenColimit (G.mapCocone c) ↔ IsVanKampenColimit c := ⟨IsVanKampenColimit.of_mapCocone G, fun hc ↦ by let e : F ⋙ G ⋙ Functor.inv G ≅ F := NatIso.hcomp (Iso.refl F) G.asEquivalence.unitIso.symm apply IsVanKampenColimit.of_mapCocone G.inv apply (IsVanKampenColimit.precompose_isIso_iff e.inv).mp exact hc.of_iso (Cocones.ext (G.asEquivalence.unitIso.app c.pt) (fun j => (by simp [e])))⟩ theorem IsUniversalColimit.whiskerEquivalence {K : Type*} [Category K] (e : J ≌ K) {F : K ⥤ C} {c : Cocone F} (hc : IsUniversalColimit c) : IsUniversalColimit (c.whisker e.functor) := by intro F' c' α f e' hα H convert hc (c'.whisker e.inverse) (whiskerLeft e.inverse α ≫ (e.invFunIdAssoc F).hom) f ?_ ((hα.whiskerLeft _).comp (NatTrans.equifibered_of_isIso _)) ?_ using 1 · exact (IsColimit.whiskerEquivalenceEquiv e.symm).nonempty_congr · convert congr_arg (whiskerLeft e.inverse) e' ext simp · intro k rw [← Category.comp_id f] refine (H (e.inverse.obj k)).paste_vert ?_ have : IsIso (𝟙 (Cocone.whisker e.functor c).pt) := inferInstance exact IsPullback.of_vert_isIso ⟨by simp⟩ theorem IsUniversalColimit.whiskerEquivalence_iff {K : Type*} [Category K] (e : J ≌ K) {F : K ⥤ C} {c : Cocone F} : IsUniversalColimit (c.whisker e.functor) ↔ IsUniversalColimit c := ⟨fun hc ↦ ((hc.whiskerEquivalence e.symm).precompose_isIso (e.invFunIdAssoc F).inv).of_iso (Cocones.ext (Iso.refl _) (by simp)), IsUniversalColimit.whiskerEquivalence e⟩ theorem IsVanKampenColimit.whiskerEquivalence {K : Type*} [Category K] (e : J ≌ K) {F : K ⥤ C} {c : Cocone F} (hc : IsVanKampenColimit c) : IsVanKampenColimit (c.whisker e.functor) := by intro F' c' α f e' hα convert hc (c'.whisker e.inverse) (whiskerLeft e.inverse α ≫ (e.invFunIdAssoc F).hom) f ?_ ((hα.whiskerLeft _).comp (NatTrans.equifibered_of_isIso _)) using 1 · exact (IsColimit.whiskerEquivalenceEquiv e.symm).nonempty_congr · simp only [Functor.const_obj_obj, Functor.comp_obj, Cocone.whisker_pt, Cocone.whisker_ι, whiskerLeft_app, NatTrans.comp_app, Equivalence.invFunIdAssoc_hom_app, Functor.id_obj] constructor · intro H k rw [← Category.comp_id f] refine (H (e.inverse.obj k)).paste_vert ?_ have : IsIso (𝟙 (Cocone.whisker e.functor c).pt) := inferInstance exact IsPullback.of_vert_isIso ⟨by simp⟩ · intro H j have : α.app j = F'.map (e.unit.app _) ≫ α.app _ ≫ F.map (e.counit.app (e.functor.obj j)) := by simp [← Functor.map_comp] rw [← Category.id_comp f, this] refine IsPullback.paste_vert ?_ (H (e.functor.obj j)) exact IsPullback.of_vert_isIso ⟨by simp⟩ · ext k simpa using congr_app e' (e.inverse.obj k) theorem IsVanKampenColimit.whiskerEquivalence_iff {K : Type*} [Category K] (e : J ≌ K) {F : K ⥤ C} {c : Cocone F} : IsVanKampenColimit (c.whisker e.functor) ↔ IsVanKampenColimit c := ⟨fun hc ↦ ((hc.whiskerEquivalence e.symm).precompose_isIso (e.invFunIdAssoc F).inv).of_iso (Cocones.ext (Iso.refl _) (by simp)), IsVanKampenColimit.whiskerEquivalence e⟩ theorem isVanKampenColimit_of_evaluation [HasPullbacks D] [HasColimitsOfShape J D] (F : J ⥤ C ⥤ D) (c : Cocone F) (hc : ∀ x : C, IsVanKampenColimit (((evaluation C D).obj x).mapCocone c)) : IsVanKampenColimit c := by intro F' c' α f e hα have := fun x => hc x (((evaluation C D).obj x).mapCocone c') (whiskerRight α _) (((evaluation C D).obj x).map f) (by ext y dsimp exact NatTrans.congr_app (NatTrans.congr_app e y) x) (hα.whiskerRight _) constructor · rintro ⟨hc'⟩ j refine ⟨⟨(NatTrans.congr_app e j).symm⟩, ⟨evaluationJointlyReflectsLimits _ ?_⟩⟩ refine fun x => (isLimitMapConePullbackConeEquiv _ _).symm ?_ exact ((this x).mp ⟨isColimitOfPreserves _ hc'⟩ _).isLimit · exact fun H => ⟨evaluationJointlyReflectsColimits _ fun x => ((this x).mpr fun j => (H j).map ((evaluation C D).obj x)).some⟩ end Functor section reflective theorem IsUniversalColimit.map_reflective {Gl : C ⥤ D} {Gr : D ⥤ C} (adj : Gl ⊣ Gr) [Gr.Full] [Gr.Faithful] {F : J ⥤ D} {c : Cocone (F ⋙ Gr)} (H : IsUniversalColimit c) [∀ X (f : X ⟶ Gl.obj c.pt), HasPullback (Gr.map f) (adj.unit.app c.pt)] [∀ X (f : X ⟶ Gl.obj c.pt), PreservesLimit (cospan (Gr.map f) (adj.unit.app c.pt)) Gl] : IsUniversalColimit (Gl.mapCocone c) := by have := adj.rightAdjoint_preservesLimits have : PreservesColimitsOfSize.{u', v'} Gl := adj.leftAdjoint_preservesColimits intros F' c' α f h hα hc' have : HasPullback (Gl.map (Gr.map f)) (Gl.map (adj.unit.app c.pt)) := ⟨⟨_, isLimitPullbackConeMapOfIsLimit _ pullback.condition (IsPullback.of_hasPullback _ _).isLimit⟩⟩ let α' := α ≫ (Functor.associator _ _ _).hom ≫ whiskerLeft F adj.counit ≫ F.rightUnitor.hom have hα' : NatTrans.Equifibered α' := hα.comp (NatTrans.equifibered_of_isIso _)
have hadj : ∀ X, Gl.map (adj.unit.app X) = inv (adj.counit.app _) := by intro X apply IsIso.eq_inv_of_inv_hom_id exact adj.left_triangle_components _ haveI : ∀ X, IsIso (Gl.map (adj.unit.app X)) := by simp_rw [hadj] infer_instance have hα'' : ∀ j, Gl.map (Gr.map <| α'.app j) = adj.counit.app _ ≫ α.app j := by intro j rw [← cancel_mono (adj.counit.app <| F.obj j)] dsimp [α'] simp only [Category.comp_id, Adjunction.counit_naturality_assoc, Category.id_comp, Adjunction.counit_naturality, Category.assoc, Functor.map_comp] have hc'' : ∀ j, α.app j ≫ Gl.map (c.ι.app j) = c'.ι.app j ≫ f := NatTrans.congr_app h let β := isoWhiskerLeft F' (asIso adj.counit) ≪≫ F'.rightUnitor let c'' : Cocone (F' ⋙ Gr) := by refine { pt := pullback (Gr.map f) (adj.unit.app _) ι := { app := fun j ↦ pullback.lift (Gr.map <| c'.ι.app j) (Gr.map (α'.app j) ≫ c.ι.app j) ?_ naturality := ?_ } } · rw [← Gr.map_comp, ← hc''] erw [← adj.unit_naturality] rw [Gl.map_comp, hα''] dsimp simp only [Category.assoc, Functor.map_comp, adj.right_triangle_components_assoc] · intros i j g dsimp [α'] ext all_goals simp only [Category.comp_id, Category.id_comp, Category.assoc, ← Functor.map_comp, pullback.lift_fst, pullback.lift_snd, ← Functor.map_comp_assoc] · congr 1 exact c'.w _ · rw [α.naturality_assoc] dsimp rw [adj.counit_naturality, ← Category.assoc, Gr.map_comp_assoc] congr 1 exact c.w _ let cf : (Cocones.precompose β.hom).obj c' ⟶ Gl.mapCocone c'' := by refine { hom := pullback.lift ?_ f ?_ ≫ (PreservesPullback.iso _ _ _).inv, w := ?_ } · exact inv <| adj.counit.app c'.pt · simp [← cancel_mono (adj.counit.app <| Gl.obj c.pt)] · intro j rw [← Category.assoc, Iso.comp_inv_eq] ext all_goals simp only [c'', PreservesPullback.iso_hom_fst, PreservesPullback.iso_hom_snd, pullback.lift_fst, pullback.lift_snd, Category.assoc, Functor.mapCocone_ι_app, ← Gl.map_comp] · rw [IsIso.comp_inv_eq, adj.counit_naturality] dsimp [β] rw [Category.comp_id] · rw [Gl.map_comp, hα'', Category.assoc, hc''] dsimp [β] rw [Category.comp_id, Category.assoc] have : cf.hom ≫ (PreservesPullback.iso _ _ _).hom ≫ pullback.fst _ _ ≫ adj.counit.app _ = 𝟙 _ := by simp only [cf, IsIso.inv_hom_id, Iso.inv_hom_id_assoc, Category.assoc, pullback.lift_fst_assoc] have : IsIso cf := by apply @Cocones.cocone_iso_of_hom_iso (i := ?_) rw [← IsIso.eq_comp_inv] at this rw [this] infer_instance have ⟨Hc''⟩ := H c'' (whiskerRight α' Gr) (pullback.snd _ _) ?_ (hα'.whiskerRight Gr) ?_ · exact ⟨IsColimit.precomposeHomEquiv β c' <| (isColimitOfPreserves Gl Hc'').ofIsoColimit (asIso cf).symm⟩ · ext j dsimp [c''] simp only [Category.comp_id, Category.id_comp, Category.assoc, Functor.map_comp, pullback.lift_snd] · intro j apply IsPullback.of_right _ _ (IsPullback.of_hasPullback _ _) · dsimp [α', c''] simp only [Category.comp_id, Category.id_comp, Category.assoc, Functor.map_comp, pullback.lift_fst] rw [← Category.comp_id (Gr.map f)] refine ((hc' j).map Gr).paste_vert (IsPullback.of_vert_isIso ⟨?_⟩) rw [← adj.unit_naturality, Category.comp_id, ← Category.assoc, ← Category.id_comp (Gr.map ((Gl.mapCocone c).ι.app j))] congr 1 rw [← cancel_mono (Gr.map (adj.counit.app (F.obj j)))] dsimp simp only [Category.comp_id, Adjunction.right_triangle_components, Category.id_comp, Category.assoc] · dsimp [c''] simp only [Category.comp_id, Category.id_comp, Category.assoc, Functor.map_comp, pullback.lift_snd] theorem IsVanKampenColimit.map_reflective [HasColimitsOfShape J C] {Gl : C ⥤ D} {Gr : D ⥤ C} (adj : Gl ⊣ Gr) [Gr.Full] [Gr.Faithful] {F : J ⥤ D} {c : Cocone (F ⋙ Gr)} (H : IsVanKampenColimit c) [∀ X (f : X ⟶ Gl.obj c.pt), HasPullback (Gr.map f) (adj.unit.app c.pt)] [∀ X (f : X ⟶ Gl.obj c.pt), PreservesLimit (cospan (Gr.map f) (adj.unit.app c.pt)) Gl] [∀ X i (f : X ⟶ c.pt), PreservesLimit (cospan f (c.ι.app i)) Gl] : IsVanKampenColimit (Gl.mapCocone c) := by have := adj.rightAdjoint_preservesLimits have : PreservesColimitsOfSize.{u', v'} Gl := adj.leftAdjoint_preservesColimits intro F' c' α f h hα refine ⟨?_, H.isUniversal.map_reflective adj c' α f h hα⟩ intro ⟨hc'⟩ j let α' := α ≫ (Functor.associator _ _ _).hom ≫ whiskerLeft F adj.counit ≫ F.rightUnitor.hom have hα' : NatTrans.Equifibered α' := hα.comp (NatTrans.equifibered_of_isIso _) have hα'' : ∀ j, Gl.map (Gr.map <| α'.app j) = adj.counit.app _ ≫ α.app j := by
Mathlib/CategoryTheory/Limits/VanKampen.lean
308
409
/- Copyright (c) 2020 Simon Hudon. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Simon Hudon -/ import Mathlib.Data.Stream.Init import Mathlib.Tactic.ApplyFun import Mathlib.Control.Fix import Mathlib.Order.OmegaCompletePartialOrder /-! # Lawful fixed point operators This module defines the laws required of a `Fix` instance, using the theory of omega complete partial orders (ωCPO). Proofs of the lawfulness of all `Fix` instances in `Control.Fix` are provided. ## Main definition * class `LawfulFix` -/ universe u v variable {α : Type*} {β : α → Type*} open OmegaCompletePartialOrder /-- Intuitively, a fixed point operator `fix` is lawful if it satisfies `fix f = f (fix f)` for all `f`, but this is inconsistent / uninteresting in most cases due to the existence of "exotic" functions `f`, such as the function that is defined iff its argument is not, familiar from the halting problem. Instead, this requirement is limited to only functions that are `Continuous` in the sense of `ω`-complete partial orders, which excludes the example because it is not monotone (making the input argument less defined can make `f` more defined). -/ class LawfulFix (α : Type*) [OmegaCompletePartialOrder α] extends Fix α where fix_eq : ∀ {f : α → α}, ωScottContinuous f → Fix.fix f = f (Fix.fix f) namespace Part open Part Nat Nat.Upto namespace Fix variable (f : ((a : _) → Part <| β a) →o (a : _) → Part <| β a) theorem approx_mono' {i : ℕ} : Fix.approx f i ≤ Fix.approx f (succ i) := by induction i with | zero => dsimp [approx]; apply @bot_le _ _ _ (f ⊥) | succ _ i_ih => intro; apply f.monotone; apply i_ih theorem approx_mono ⦃i j : ℕ⦄ (hij : i ≤ j) : approx f i ≤ approx f j := by induction' j with j ih · cases hij exact le_rfl cases hij; · exact le_rfl exact le_trans (ih ‹_›) (approx_mono' f) theorem mem_iff (a : α) (b : β a) : b ∈ Part.fix f a ↔ ∃ i, b ∈ approx f i a := by classical by_cases h₀ : ∃ i : ℕ, (approx f i a).Dom · simp only [Part.fix_def f h₀] constructor <;> intro hh
· exact ⟨_, hh⟩ have h₁ := Nat.find_spec h₀ rw [dom_iff_mem] at h₁ obtain ⟨y, h₁⟩ := h₁ replace h₁ := approx_mono' f _ _ h₁ suffices y = b by
Mathlib/Control/LawfulFix.lean
63
68
/- Copyright (c) 2023 Rémi Bottinelli. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Rémi Bottinelli -/ import Mathlib.Data.Set.Function import Mathlib.Analysis.RCLike.Basic import Mathlib.Topology.EMetricSpace.BoundedVariation /-! # Constant speed This file defines the notion of constant (and unit) speed for a function `f : ℝ → E` with pseudo-emetric structure on `E` with respect to a set `s : Set ℝ` and "speed" `l : ℝ≥0`, and shows that if `f` has locally bounded variation on `s`, it can be obtained (up to distance zero, on `s`), as a composite `φ ∘ (variationOnFromTo f s a)`, where `φ` has unit speed and `a ∈ s`. ## Main definitions * `HasConstantSpeedOnWith f s l`, stating that the speed of `f` on `s` is `l`. * `HasUnitSpeedOn f s`, stating that the speed of `f` on `s` is `1`. * `naturalParameterization f s a : ℝ → E`, the unit speed reparameterization of `f` on `s` relative to `a`. ## Main statements * `unique_unit_speed_on_Icc_zero` proves that if `f` and `f ∘ φ` are both naturally parameterized on closed intervals starting at `0`, then `φ` must be the identity on those intervals. * `edist_naturalParameterization_eq_zero` proves that if `f` has locally bounded variation, then precomposing `naturalParameterization f s a` with `variationOnFromTo f s a` yields a function at distance zero from `f` on `s`. * `has_unit_speed_naturalParameterization` proves that if `f` has locally bounded variation, then `naturalParameterization f s a` has unit speed on `s`. ## Tags arc-length, parameterization -/ open scoped NNReal ENNReal open Set variable {α : Type*} [LinearOrder α] {E : Type*} [PseudoEMetricSpace E] variable (f : ℝ → E) (s : Set ℝ) (l : ℝ≥0) /-- `f` has constant speed `l` on `s` if the variation of `f` on `s ∩ Icc x y` is equal to `l * (y - x)` for any `x y` in `s`. -/ def HasConstantSpeedOnWith := ∀ ⦃x⦄ (_ : x ∈ s) ⦃y⦄ (_ : y ∈ s), eVariationOn f (s ∩ Icc x y) = ENNReal.ofReal (l * (y - x)) variable {f s l} theorem HasConstantSpeedOnWith.hasLocallyBoundedVariationOn (h : HasConstantSpeedOnWith f s l) : LocallyBoundedVariationOn f s := fun x y hx hy => by simp only [BoundedVariationOn, h hx hy, Ne, ENNReal.ofReal_ne_top, not_false_iff] theorem hasConstantSpeedOnWith_of_subsingleton (f : ℝ → E) {s : Set ℝ} (hs : s.Subsingleton) (l : ℝ≥0) : HasConstantSpeedOnWith f s l := by rintro x hx y hy; cases hs hx hy rw [eVariationOn.subsingleton f (fun y hy z hz => hs hy.1 hz.1 : (s ∩ Icc x x).Subsingleton)] simp only [sub_self, mul_zero, ENNReal.ofReal_zero] theorem hasConstantSpeedOnWith_iff_ordered : HasConstantSpeedOnWith f s l ↔ ∀ ⦃x⦄ (_ : x ∈ s) ⦃y⦄ (_ : y ∈ s), x ≤ y → eVariationOn f (s ∩ Icc x y) = ENNReal.ofReal (l * (y - x)) := by refine ⟨fun h x xs y ys _ => h xs ys, fun h x xs y ys => ?_⟩ rcases le_total x y with (xy | yx) · exact h xs ys xy · rw [eVariationOn.subsingleton, ENNReal.ofReal_of_nonpos] · exact mul_nonpos_of_nonneg_of_nonpos l.prop (sub_nonpos_of_le yx) · rintro z ⟨zs, xz, zy⟩ w ⟨ws, xw, wy⟩ cases le_antisymm (zy.trans yx) xz cases le_antisymm (wy.trans yx) xw rfl theorem hasConstantSpeedOnWith_iff_variationOnFromTo_eq : HasConstantSpeedOnWith f s l ↔ LocallyBoundedVariationOn f s ∧ ∀ ⦃x⦄ (_ : x ∈ s) ⦃y⦄ (_ : y ∈ s), variationOnFromTo f s x y = l * (y - x) := by constructor · rintro h; refine ⟨h.hasLocallyBoundedVariationOn, fun x xs y ys => ?_⟩ rw [hasConstantSpeedOnWith_iff_ordered] at h rcases le_total x y with (xy | yx) · rw [variationOnFromTo.eq_of_le f s xy, h xs ys xy] exact ENNReal.toReal_ofReal (mul_nonneg l.prop (sub_nonneg.mpr xy)) · rw [variationOnFromTo.eq_of_ge f s yx, h ys xs yx] have := ENNReal.toReal_ofReal (mul_nonneg l.prop (sub_nonneg.mpr yx)) simp_all only [NNReal.val_eq_coe]; ring · rw [hasConstantSpeedOnWith_iff_ordered] rintro h x xs y ys xy rw [← h.2 xs ys, variationOnFromTo.eq_of_le f s xy, ENNReal.ofReal_toReal (h.1 x y xs ys)] theorem HasConstantSpeedOnWith.union {t : Set ℝ} (hfs : HasConstantSpeedOnWith f s l) (hft : HasConstantSpeedOnWith f t l) {x : ℝ} (hs : IsGreatest s x) (ht : IsLeast t x) : HasConstantSpeedOnWith f (s ∪ t) l := by rw [hasConstantSpeedOnWith_iff_ordered] at hfs hft ⊢ rintro z (zs | zt) y (ys | yt) zy · have : (s ∪ t) ∩ Icc z y = s ∩ Icc z y := by
ext w; constructor · rintro ⟨ws | wt, zw, wy⟩ · exact ⟨ws, zw, wy⟩ · exact ⟨(le_antisymm (wy.trans (hs.2 ys)) (ht.2 wt)).symm ▸ hs.1, zw, wy⟩ · rintro ⟨ws, zwy⟩; exact ⟨Or.inl ws, zwy⟩ rw [this, hfs zs ys zy] · have : (s ∪ t) ∩ Icc z y = s ∩ Icc z x ∪ t ∩ Icc x y := by ext w; constructor · rintro ⟨ws | wt, zw, wy⟩ exacts [Or.inl ⟨ws, zw, hs.2 ws⟩, Or.inr ⟨wt, ht.2 wt, wy⟩] · rintro (⟨ws, zw, wx⟩ | ⟨wt, xw, wy⟩) exacts [⟨Or.inl ws, zw, wx.trans (ht.2 yt)⟩, ⟨Or.inr wt, (hs.2 zs).trans xw, wy⟩] rw [this, @eVariationOn.union _ _ _ _ f _ _ x, hfs zs hs.1 (hs.2 zs), hft ht.1 yt (ht.2 yt)] · have q := ENNReal.ofReal_add (mul_nonneg l.prop (sub_nonneg.mpr (hs.2 zs))) (mul_nonneg l.prop (sub_nonneg.mpr (ht.2 yt))) simp only [NNReal.val_eq_coe] at q rw [← q] ring_nf exacts [⟨⟨hs.1, hs.2 zs, le_rfl⟩, fun w ⟨_, _, wx⟩ => wx⟩, ⟨⟨ht.1, le_rfl, ht.2 yt⟩, fun w ⟨_, xw, _⟩ => xw⟩] · cases le_antisymm zy ((hs.2 ys).trans (ht.2 zt)) simp only [Icc_self, sub_self, mul_zero, ENNReal.ofReal_zero] exact eVariationOn.subsingleton _ fun _ ⟨_, uz⟩ _ ⟨_, vz⟩ => uz.trans vz.symm · have : (s ∪ t) ∩ Icc z y = t ∩ Icc z y := by ext w; constructor · rintro ⟨ws | wt, zw, wy⟩ · exact ⟨le_antisymm ((ht.2 zt).trans zw) (hs.2 ws) ▸ ht.1, zw, wy⟩ · exact ⟨wt, zw, wy⟩ · rintro ⟨wt, zwy⟩; exact ⟨Or.inr wt, zwy⟩ rw [this, hft zt yt zy] theorem HasConstantSpeedOnWith.Icc_Icc {x y z : ℝ} (hfs : HasConstantSpeedOnWith f (Icc x y) l) (hft : HasConstantSpeedOnWith f (Icc y z) l) : HasConstantSpeedOnWith f (Icc x z) l := by rcases le_total x y with (xy | yx) · rcases le_total y z with (yz | zy) · rw [← Set.Icc_union_Icc_eq_Icc xy yz]
Mathlib/Analysis/ConstantSpeed.lean
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/- 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 -/ import Mathlib.Algebra.CharP.Defs import Mathlib.Algebra.Order.CauSeq.BigOperators import Mathlib.Algebra.Order.Star.Basic import Mathlib.Data.Complex.BigOperators import Mathlib.Data.Complex.Norm import Mathlib.Data.Nat.Choose.Sum /-! # Exponential Function This file contains the definitions of the real and complex exponential function. ## Main definitions * `Complex.exp`: The complex exponential function, defined via its Taylor series * `Real.exp`: The real exponential function, defined as the real part of the complex exponential -/ open CauSeq Finset IsAbsoluteValue open scoped ComplexConjugate namespace Complex theorem isCauSeq_norm_exp (z : ℂ) : IsCauSeq abs fun n => ∑ m ∈ range n, ‖z ^ m / m.factorial‖ := let ⟨n, hn⟩ := exists_nat_gt ‖z‖ have hn0 : (0 : ℝ) < n := lt_of_le_of_lt (norm_nonneg _) hn IsCauSeq.series_ratio_test n (‖z‖ / n) (div_nonneg (norm_nonneg _) (le_of_lt hn0)) (by rwa [div_lt_iff₀ hn0, one_mul]) fun m hm => by rw [abs_norm, abs_norm, Nat.factorial_succ, pow_succ', mul_comm m.succ, Nat.cast_mul, ← div_div, mul_div_assoc, mul_div_right_comm, Complex.norm_mul, Complex.norm_div, norm_natCast] gcongr exact le_trans hm (Nat.le_succ _) @[deprecated (since := "2025-02-16")] alias isCauSeq_abs_exp := isCauSeq_norm_exp noncomputable section theorem isCauSeq_exp (z : ℂ) : IsCauSeq (‖·‖) fun n => ∑ m ∈ range n, z ^ m / m.factorial := (isCauSeq_norm_exp z).of_abv /-- The Cauchy sequence consisting of partial sums of the Taylor series of the complex exponential function -/ @[pp_nodot] def exp' (z : ℂ) : CauSeq ℂ (‖·‖) := ⟨fun n => ∑ m ∈ range n, z ^ m / m.factorial, isCauSeq_exp z⟩ /-- The complex exponential function, defined via its Taylor series -/ @[pp_nodot] def exp (z : ℂ) : ℂ := CauSeq.lim (exp' z) /-- scoped notation for the complex exponential function -/ scoped notation "cexp" => Complex.exp end end Complex namespace Real open Complex noncomputable section /-- The real exponential function, defined as the real part of the complex exponential -/ @[pp_nodot] nonrec def exp (x : ℝ) : ℝ := (exp x).re /-- scoped notation for the real exponential function -/ scoped notation "rexp" => Real.exp end end Real namespace Complex variable (x y : ℂ) @[simp] theorem exp_zero : exp 0 = 1 := by rw [exp] refine lim_eq_of_equiv_const fun ε ε0 => ⟨1, fun j hj => ?_⟩ convert (config := .unfoldSameFun) ε0 -- ε0 : ε > 0 but goal is _ < ε rcases j with - | j · exact absurd hj (not_le_of_gt zero_lt_one) · dsimp [exp'] induction' j with j ih · dsimp [exp']; simp [show Nat.succ 0 = 1 from rfl] · rw [← ih (by simp [Nat.succ_le_succ])] simp only [sum_range_succ, pow_succ] simp theorem exp_add : exp (x + y) = exp x * exp y := by have hj : ∀ j : ℕ, (∑ m ∈ range j, (x + y) ^ m / m.factorial) = ∑ i ∈ range j, ∑ k ∈ range (i + 1), x ^ k / k.factorial * (y ^ (i - k) / (i - k).factorial) := by intro j refine Finset.sum_congr rfl fun m _ => ?_ rw [add_pow, div_eq_mul_inv, sum_mul] refine Finset.sum_congr rfl fun I hi => ?_ have h₁ : (m.choose I : ℂ) ≠ 0 := Nat.cast_ne_zero.2 (pos_iff_ne_zero.1 (Nat.choose_pos (Nat.le_of_lt_succ (mem_range.1 hi)))) have h₂ := Nat.choose_mul_factorial_mul_factorial (Nat.le_of_lt_succ <| Finset.mem_range.1 hi) rw [← h₂, Nat.cast_mul, Nat.cast_mul, mul_inv, mul_inv] simp only [mul_left_comm (m.choose I : ℂ), mul_assoc, mul_left_comm (m.choose I : ℂ)⁻¹, mul_comm (m.choose I : ℂ)] rw [inv_mul_cancel₀ h₁] simp [div_eq_mul_inv, mul_comm, mul_assoc, mul_left_comm] simp_rw [exp, exp', lim_mul_lim] apply (lim_eq_lim_of_equiv _).symm simp only [hj] exact cauchy_product (isCauSeq_norm_exp x) (isCauSeq_exp y) /-- the exponential function as a monoid hom from `Multiplicative ℂ` to `ℂ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℂ) ℂ := { toFun := fun z => exp z.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℂ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℂ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℂ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℂ) ℂ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℂ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℂ) expMonoidHom f s lemma exp_nsmul (x : ℂ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℂ) ℂ _ _ expMonoidHom _ _ theorem exp_nat_mul (x : ℂ) : ∀ n : ℕ, exp (n * x) = exp x ^ n | 0 => by rw [Nat.cast_zero, zero_mul, exp_zero, pow_zero] | Nat.succ n => by rw [pow_succ, Nat.cast_add_one, add_mul, exp_add, ← exp_nat_mul _ n, one_mul] @[simp] theorem exp_ne_zero : exp x ≠ 0 := fun h => zero_ne_one (α := ℂ) <| by rw [← exp_zero, ← add_neg_cancel x, exp_add, h]; simp theorem exp_neg : exp (-x) = (exp x)⁻¹ := by rw [← mul_right_inj' (exp_ne_zero x), ← exp_add]; simp [mul_inv_cancel₀ (exp_ne_zero x)] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] theorem exp_int_mul (z : ℂ) (n : ℤ) : Complex.exp (n * z) = Complex.exp z ^ n := by cases n · simp [exp_nat_mul] · simp [exp_add, add_mul, pow_add, exp_neg, exp_nat_mul] @[simp] theorem exp_conj : exp (conj x) = conj (exp x) := by dsimp [exp] rw [← lim_conj] refine congr_arg CauSeq.lim (CauSeq.ext fun _ => ?_) dsimp [exp', Function.comp_def, cauSeqConj] rw [map_sum (starRingEnd _)] refine sum_congr rfl fun n _ => ?_ rw [map_div₀, map_pow, ← ofReal_natCast, conj_ofReal] @[simp] theorem ofReal_exp_ofReal_re (x : ℝ) : ((exp x).re : ℂ) = exp x := conj_eq_iff_re.1 <| by rw [← exp_conj, conj_ofReal] @[simp, norm_cast] theorem ofReal_exp (x : ℝ) : (Real.exp x : ℂ) = exp x := ofReal_exp_ofReal_re _ @[simp] theorem exp_ofReal_im (x : ℝ) : (exp x).im = 0 := by rw [← ofReal_exp_ofReal_re, ofReal_im] theorem exp_ofReal_re (x : ℝ) : (exp x).re = Real.exp x := rfl end Complex namespace Real open Complex variable (x y : ℝ) @[simp] theorem exp_zero : exp 0 = 1 := by simp [Real.exp] nonrec theorem exp_add : exp (x + y) = exp x * exp y := by simp [exp_add, exp] /-- the exponential function as a monoid hom from `Multiplicative ℝ` to `ℝ` -/ @[simps] noncomputable def expMonoidHom : MonoidHom (Multiplicative ℝ) ℝ := { toFun := fun x => exp x.toAdd, map_one' := by simp, map_mul' := by simp [exp_add] } theorem exp_list_sum (l : List ℝ) : exp l.sum = (l.map exp).prod := map_list_prod (M := Multiplicative ℝ) expMonoidHom l theorem exp_multiset_sum (s : Multiset ℝ) : exp s.sum = (s.map exp).prod := @MonoidHom.map_multiset_prod (Multiplicative ℝ) ℝ _ _ expMonoidHom s theorem exp_sum {α : Type*} (s : Finset α) (f : α → ℝ) : exp (∑ x ∈ s, f x) = ∏ x ∈ s, exp (f x) := map_prod (β := Multiplicative ℝ) expMonoidHom f s lemma exp_nsmul (x : ℝ) (n : ℕ) : exp (n • x) = exp x ^ n := @MonoidHom.map_pow (Multiplicative ℝ) ℝ _ _ expMonoidHom _ _ nonrec theorem exp_nat_mul (x : ℝ) (n : ℕ) : exp (n * x) = exp x ^ n := ofReal_injective (by simp [exp_nat_mul]) @[simp] nonrec theorem exp_ne_zero : exp x ≠ 0 := fun h => exp_ne_zero x <| by rw [exp, ← ofReal_inj] at h; simp_all nonrec theorem exp_neg : exp (-x) = (exp x)⁻¹ := ofReal_injective <| by simp [exp_neg] theorem exp_sub : exp (x - y) = exp x / exp y := by simp [sub_eq_add_neg, exp_add, exp_neg, div_eq_mul_inv] open IsAbsoluteValue Nat theorem sum_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) (n : ℕ) : ∑ i ∈ range n, x ^ i / i ! ≤ exp x := calc ∑ i ∈ range n, x ^ i / i ! ≤ lim (⟨_, isCauSeq_re (exp' x)⟩ : CauSeq ℝ abs) := by refine le_lim (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp only [exp', const_apply, re_sum] norm_cast refine sum_le_sum_of_subset_of_nonneg (range_mono hj) fun _ _ _ ↦ ?_ positivity _ = exp x := by rw [exp, Complex.exp, ← cauSeqRe, lim_re] lemma pow_div_factorial_le_exp (hx : 0 ≤ x) (n : ℕ) : x ^ n / n ! ≤ exp x := calc x ^ n / n ! ≤ ∑ k ∈ range (n + 1), x ^ k / k ! := single_le_sum (f := fun k ↦ x ^ k / k !) (fun k _ ↦ by positivity) (self_mem_range_succ n) _ ≤ exp x := sum_le_exp_of_nonneg hx _ theorem quadratic_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : 1 + x + x ^ 2 / 2 ≤ exp x := calc 1 + x + x ^ 2 / 2 = ∑ i ∈ range 3, x ^ i / i ! := by simp only [sum_range_succ, range_one, sum_singleton, _root_.pow_zero, factorial, cast_one, ne_eq, one_ne_zero, not_false_eq_true, div_self, pow_one, mul_one, div_one, Nat.mul_one, cast_succ, add_right_inj] ring_nf _ ≤ exp x := sum_le_exp_of_nonneg hx 3 private theorem add_one_lt_exp_of_pos {x : ℝ} (hx : 0 < x) : x + 1 < exp x := (by nlinarith : x + 1 < 1 + x + x ^ 2 / 2).trans_le (quadratic_le_exp_of_nonneg hx.le) private theorem add_one_le_exp_of_nonneg {x : ℝ} (hx : 0 ≤ x) : x + 1 ≤ exp x := by rcases eq_or_lt_of_le hx with (rfl | h) · simp exact (add_one_lt_exp_of_pos h).le theorem one_le_exp {x : ℝ} (hx : 0 ≤ x) : 1 ≤ exp x := by linarith [add_one_le_exp_of_nonneg hx] @[bound] theorem exp_pos (x : ℝ) : 0 < exp x := (le_total 0 x).elim (lt_of_lt_of_le zero_lt_one ∘ one_le_exp) fun h => by rw [← neg_neg x, Real.exp_neg] exact inv_pos.2 (lt_of_lt_of_le zero_lt_one (one_le_exp (neg_nonneg.2 h))) @[bound] lemma exp_nonneg (x : ℝ) : 0 ≤ exp x := x.exp_pos.le @[simp] theorem abs_exp (x : ℝ) : |exp x| = exp x := abs_of_pos (exp_pos _) lemma exp_abs_le (x : ℝ) : exp |x| ≤ exp x + exp (-x) := by cases le_total x 0 <;> simp [abs_of_nonpos, abs_of_nonneg, exp_nonneg, *] @[mono] theorem exp_strictMono : StrictMono exp := fun x y h => by rw [← sub_add_cancel y x, Real.exp_add] exact (lt_mul_iff_one_lt_left (exp_pos _)).2 (lt_of_lt_of_le (by linarith) (add_one_le_exp_of_nonneg (by linarith))) @[gcongr] theorem exp_lt_exp_of_lt {x y : ℝ} (h : x < y) : exp x < exp y := exp_strictMono h @[mono] theorem exp_monotone : Monotone exp := exp_strictMono.monotone @[gcongr, bound] theorem exp_le_exp_of_le {x y : ℝ} (h : x ≤ y) : exp x ≤ exp y := exp_monotone h @[simp] theorem exp_lt_exp {x y : ℝ} : exp x < exp y ↔ x < y := exp_strictMono.lt_iff_lt @[simp] theorem exp_le_exp {x y : ℝ} : exp x ≤ exp y ↔ x ≤ y := exp_strictMono.le_iff_le theorem exp_injective : Function.Injective exp := exp_strictMono.injective @[simp] theorem exp_eq_exp {x y : ℝ} : exp x = exp y ↔ x = y := exp_injective.eq_iff @[simp] theorem exp_eq_one_iff : exp x = 1 ↔ x = 0 := exp_injective.eq_iff' exp_zero @[simp] theorem one_lt_exp_iff {x : ℝ} : 1 < exp x ↔ 0 < x := by rw [← exp_zero, exp_lt_exp] @[bound] private alias ⟨_, Bound.one_lt_exp_of_pos⟩ := one_lt_exp_iff @[simp] theorem exp_lt_one_iff {x : ℝ} : exp x < 1 ↔ x < 0 := by rw [← exp_zero, exp_lt_exp] @[simp] theorem exp_le_one_iff {x : ℝ} : exp x ≤ 1 ↔ x ≤ 0 := exp_zero ▸ exp_le_exp @[simp] theorem one_le_exp_iff {x : ℝ} : 1 ≤ exp x ↔ 0 ≤ x := exp_zero ▸ exp_le_exp end Real namespace Complex theorem sum_div_factorial_le {α : Type*} [Field α] [LinearOrder α] [IsStrictOrderedRing α] (n j : ℕ) (hn : 0 < n) : (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) ≤ n.succ / (n.factorial * n) := calc (∑ m ∈ range j with n ≤ m, (1 / m.factorial : α)) = ∑ m ∈ range (j - n), (1 / ((m + n).factorial : α)) := by refine sum_nbij' (· - n) (· + n) ?_ ?_ ?_ ?_ ?_ <;> simp +contextual [lt_tsub_iff_right, tsub_add_cancel_of_le] _ ≤ ∑ m ∈ range (j - n), ((n.factorial : α) * (n.succ : α) ^ m)⁻¹ := by simp_rw [one_div] gcongr rw [← Nat.cast_pow, ← Nat.cast_mul, Nat.cast_le, add_comm] exact Nat.factorial_mul_pow_le_factorial _ = (n.factorial : α)⁻¹ * ∑ m ∈ range (j - n), (n.succ : α)⁻¹ ^ m := by simp [mul_inv, ← mul_sum, ← sum_mul, mul_comm, inv_pow] _ = ((n.succ : α) - n.succ * (n.succ : α)⁻¹ ^ (j - n)) / (n.factorial * n) := by have h₁ : (n.succ : α) ≠ 1 := @Nat.cast_one α _ ▸ mt Nat.cast_inj.1 (mt Nat.succ.inj (pos_iff_ne_zero.1 hn)) have h₂ : (n.succ : α) ≠ 0 := by positivity have h₃ : (n.factorial * n : α) ≠ 0 := by positivity have h₄ : (n.succ - 1 : α) = n := by simp rw [geom_sum_inv h₁ h₂, eq_div_iff_mul_eq h₃, mul_comm _ (n.factorial * n : α), ← mul_assoc (n.factorial⁻¹ : α), ← mul_inv_rev, h₄, ← mul_assoc (n.factorial * n : α), mul_comm (n : α) n.factorial, mul_inv_cancel₀ h₃, one_mul, mul_comm] _ ≤ n.succ / (n.factorial * n : α) := by gcongr; apply sub_le_self; positivity theorem exp_bound {x : ℂ} (hx : ‖x‖ ≤ 1) {n : ℕ} (hn : 0 < n) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * ((n.succ : ℝ) * (n.factorial * n : ℝ)⁻¹) rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (1 / m.factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr rw [Complex.norm_pow] exact pow_le_one₀ (norm_nonneg _) hx _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (1 / m.factorial : ℝ) := by simp [abs_mul, abv_pow abs, abs_div, ← mul_sum] _ ≤ ‖x‖ ^ n * (n.succ * (n.factorial * n : ℝ)⁻¹) := by gcongr exact sum_div_factorial_le _ _ hn theorem exp_bound' {x : ℂ} {n : ℕ} (hx : ‖x‖ / n.succ ≤ 1 / 2) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 := by rw [← lim_const (abv := norm) (∑ m ∈ range n, _), exp, sub_eq_add_neg, ← lim_neg, lim_add, ← lim_norm] refine lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n / n.factorial * 2 let k := j - n have hj : j = n + k := (add_tsub_cancel_of_le hj).symm rw [hj, sum_range_add_sub_sum_range] calc ‖∑ i ∈ range k, x ^ (n + i) / ((n + i).factorial : ℂ)‖ ≤ ∑ i ∈ range k, ‖x ^ (n + i) / ((n + i).factorial : ℂ)‖ := IsAbsoluteValue.abv_sum _ _ _ _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / (n + i).factorial := by simp [norm_natCast, Complex.norm_pow] _ ≤ ∑ i ∈ range k, ‖x‖ ^ (n + i) / ((n.factorial : ℝ) * (n.succ : ℝ) ^ i) := ?_ _ = ∑ i ∈ range k, ‖x‖ ^ n / n.factorial * (‖x‖ ^ i / (n.succ : ℝ) ^ i) := ?_ _ ≤ ‖x‖ ^ n / ↑n.factorial * 2 := ?_ · gcongr exact mod_cast Nat.factorial_mul_pow_le_factorial · refine Finset.sum_congr rfl fun _ _ => ?_ simp only [pow_add, div_eq_inv_mul, mul_inv, mul_left_comm, mul_assoc] · rw [← mul_sum] gcongr simp_rw [← div_pow] rw [geom_sum_eq, div_le_iff_of_neg] · trans (-1 : ℝ) · linarith · simp only [neg_le_sub_iff_le_add, div_pow, Nat.cast_succ, le_add_iff_nonneg_left] positivity · linarith · linarith theorem norm_exp_sub_one_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1‖ ≤ 2 * ‖x‖ := calc ‖exp x - 1‖ = ‖exp x - ∑ m ∈ range 1, x ^ m / m.factorial‖ := by simp [sum_range_succ] _ ≤ ‖x‖ ^ 1 * ((Nat.succ 1 : ℝ) * ((Nat.factorial 1) * (1 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ = 2 * ‖x‖ := by simp [two_mul, mul_two, mul_add, mul_comm, add_mul, Nat.factorial] theorem norm_exp_sub_one_sub_id_le {x : ℂ} (hx : ‖x‖ ≤ 1) : ‖exp x - 1 - x‖ ≤ ‖x‖ ^ 2 := calc ‖exp x - 1 - x‖ = ‖exp x - ∑ m ∈ range 2, x ^ m / m.factorial‖ := by simp [sub_eq_add_neg, sum_range_succ_comm, add_assoc, Nat.factorial] _ ≤ ‖x‖ ^ 2 * ((Nat.succ 2 : ℝ) * (Nat.factorial 2 * (2 : ℕ) : ℝ)⁻¹) := (exp_bound hx (by decide)) _ ≤ ‖x‖ ^ 2 * 1 := by gcongr; norm_num [Nat.factorial] _ = ‖x‖ ^ 2 := by rw [mul_one] lemma norm_exp_sub_sum_le_exp_norm_sub_sum (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] calc ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ _ ≤ (∑ m ∈ range j, ‖x‖ ^ m / m.factorial) - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by rw [sum_range_sub_sum_range hj, sum_range_sub_sum_range hj] refine (IsAbsoluteValue.abv_sum norm ..).trans_eq ?_ congr with i simp [Complex.norm_pow] _ ≤ Real.exp ‖x‖ - ∑ m ∈ range n, ‖x‖ ^ m / m.factorial := by gcongr exact Real.sum_le_exp_of_nonneg (norm_nonneg _) _ lemma norm_exp_le_exp_norm (x : ℂ) : ‖exp x‖ ≤ Real.exp ‖x‖ := by convert norm_exp_sub_sum_le_exp_norm_sub_sum x 0 using 1 <;> simp lemma norm_exp_sub_sum_le_norm_mul_exp (x : ℂ) (n : ℕ) : ‖exp x - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by rw [← CauSeq.lim_const (abv := norm) (∑ m ∈ range n, _), Complex.exp, sub_eq_add_neg, ← CauSeq.lim_neg, CauSeq.lim_add, ← lim_norm] refine CauSeq.lim_le (CauSeq.le_of_exists ⟨n, fun j hj => ?_⟩) simp_rw [← sub_eq_add_neg] show ‖(∑ m ∈ range j, x ^ m / m.factorial) - ∑ m ∈ range n, x ^ m / m.factorial‖ ≤ _ rw [sum_range_sub_sum_range hj] calc ‖∑ m ∈ range j with n ≤ m, (x ^ m / m.factorial : ℂ)‖ = ‖∑ m ∈ range j with n ≤ m, (x ^ n * (x ^ (m - n) / m.factorial) : ℂ)‖ := by refine congr_arg norm (sum_congr rfl fun m hm => ?_) rw [mem_filter, mem_range] at hm rw [← mul_div_assoc, ← pow_add, add_tsub_cancel_of_le hm.2] _ ≤ ∑ m ∈ range j with n ≤ m, ‖x ^ n * (x ^ (m - n) / m.factorial)‖ := IsAbsoluteValue.abv_sum norm .. _ ≤ ∑ m ∈ range j with n ≤ m, ‖x‖ ^ n * (‖x‖ ^ (m - n) / (m - n).factorial) := by simp_rw [Complex.norm_mul, Complex.norm_pow, Complex.norm_div, norm_natCast] gcongr with i hi · rw [Complex.norm_pow] · simp _ = ‖x‖ ^ n * ∑ m ∈ range j with n ≤ m, (‖x‖ ^ (m - n) / (m - n).factorial) := by rw [← mul_sum] _ = ‖x‖ ^ n * ∑ m ∈ range (j - n), (‖x‖ ^ m / m.factorial) := by congr 1 refine (sum_bij (fun m hm ↦ m + n) ?_ ?_ ?_ ?_).symm · intro a ha simp only [mem_filter, mem_range, le_add_iff_nonneg_left, zero_le, and_true] simp only [mem_range] at ha rwa [← lt_tsub_iff_right] · intro a ha b hb hab simpa using hab · intro b hb simp only [mem_range, exists_prop] simp only [mem_filter, mem_range] at hb refine ⟨b - n, ?_, ?_⟩ · rw [tsub_lt_tsub_iff_right hb.2] exact hb.1 · rw [tsub_add_cancel_of_le hb.2] · simp _ ≤ ‖x‖ ^ n * Real.exp ‖x‖ := by gcongr refine Real.sum_le_exp_of_nonneg ?_ _ exact norm_nonneg _ @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_le := norm_exp_sub_one_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_one_sub_id_le := norm_exp_sub_one_sub_id_le @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_exp_abs_sub_sum := norm_exp_sub_sum_le_exp_norm_sub_sum @[deprecated (since := "2025-02-16")] alias abs_exp_le_exp_abs := norm_exp_le_exp_norm @[deprecated (since := "2025-02-16")] alias abs_exp_sub_sum_le_abs_mul_exp := norm_exp_sub_sum_le_norm_mul_exp end Complex namespace Real open Complex Finset nonrec theorem exp_bound {x : ℝ} (hx : |x| ≤ 1) {n : ℕ} (hn : 0 < n) : |exp x - ∑ m ∈ range n, x ^ m / m.factorial| ≤ |x| ^ n * (n.succ / (n.factorial * n)) := by have hxc : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx convert exp_bound hxc hn using 2 <;> norm_cast theorem exp_bound' {x : ℝ} (h1 : 0 ≤ x) (h2 : x ≤ 1) {n : ℕ} (hn : 0 < n) : Real.exp x ≤ (∑ m ∈ Finset.range n, x ^ m / m.factorial) + x ^ n * (n + 1) / (n.factorial * n) := by have h3 : |x| = x := by simpa have h4 : |x| ≤ 1 := by rwa [h3] have h' := Real.exp_bound h4 hn rw [h3] at h' have h'' := (abs_sub_le_iff.1 h').1 have t := sub_le_iff_le_add'.1 h'' simpa [mul_div_assoc] using t theorem abs_exp_sub_one_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1| ≤ 2 * |x| := by have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx exact_mod_cast Complex.norm_exp_sub_one_le (x := x) this theorem abs_exp_sub_one_sub_id_le {x : ℝ} (hx : |x| ≤ 1) : |exp x - 1 - x| ≤ x ^ 2 := by
rw [← sq_abs] have : ‖(x : ℂ)‖ ≤ 1 := mod_cast hx
Mathlib/Data/Complex/Exponential.lean
550
551
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Johannes Hölzl -/ import Mathlib.Algebra.Order.Pi import Mathlib.MeasureTheory.Constructions.BorelSpace.Order /-! # Simple functions A function `f` from a measurable space to any type is called *simple*, if every preimage `f ⁻¹' {x}` is measurable, and the range is finite. In this file, we define simple functions and establish their basic properties; and we construct a sequence of simple functions approximating an arbitrary Borel measurable function `f : α → ℝ≥0∞`. The theorem `Measurable.ennreal_induction` shows that in order to prove something for an arbitrary measurable function into `ℝ≥0∞`, it is sufficient to show that the property holds for (multiples of) characteristic functions and is closed under addition and supremum of increasing sequences of functions. -/ noncomputable section open Set hiding restrict restrict_apply open Filter ENNReal open Function (support) open Topology NNReal ENNReal MeasureTheory namespace MeasureTheory variable {α β γ δ : Type*} /-- A function `f` from a measurable space to any type is called *simple*, if every preimage `f ⁻¹' {x}` is measurable, and the range is finite. This structure bundles a function with these properties. -/ structure SimpleFunc.{u, v} (α : Type u) [MeasurableSpace α] (β : Type v) where /-- The underlying function -/ toFun : α → β measurableSet_fiber' : ∀ x, MeasurableSet (toFun ⁻¹' {x}) finite_range' : (Set.range toFun).Finite local infixr:25 " →ₛ " => SimpleFunc namespace SimpleFunc section Measurable variable [MeasurableSpace α] instance instFunLike : FunLike (α →ₛ β) α β where coe := toFun coe_injective' | ⟨_, _, _⟩, ⟨_, _, _⟩, rfl => rfl theorem coe_injective ⦃f g : α →ₛ β⦄ (H : (f : α → β) = g) : f = g := DFunLike.ext' H @[ext] theorem ext {f g : α →ₛ β} (H : ∀ a, f a = g a) : f = g := DFunLike.ext _ _ H theorem finite_range (f : α →ₛ β) : (Set.range f).Finite := f.finite_range' theorem measurableSet_fiber (f : α →ₛ β) (x : β) : MeasurableSet (f ⁻¹' {x}) := f.measurableSet_fiber' x @[simp] theorem coe_mk (f : α → β) (h h') : ⇑(mk f h h') = f := rfl theorem apply_mk (f : α → β) (h h') (x : α) : SimpleFunc.mk f h h' x = f x := rfl /-- Simple function defined on a finite type. -/ def ofFinite [Finite α] [MeasurableSingletonClass α] (f : α → β) : α →ₛ β where toFun := f measurableSet_fiber' x := (toFinite (f ⁻¹' {x})).measurableSet finite_range' := Set.finite_range f /-- Simple function defined on the empty type. -/ def ofIsEmpty [IsEmpty α] : α →ₛ β := ofFinite isEmptyElim /-- Range of a simple function `α →ₛ β` as a `Finset β`. -/ protected def range (f : α →ₛ β) : Finset β := f.finite_range.toFinset @[simp] theorem mem_range {f : α →ₛ β} {b} : b ∈ f.range ↔ b ∈ range f := Finite.mem_toFinset _ theorem mem_range_self (f : α →ₛ β) (x : α) : f x ∈ f.range := mem_range.2 ⟨x, rfl⟩ @[simp] theorem coe_range (f : α →ₛ β) : (↑f.range : Set β) = Set.range f := f.finite_range.coe_toFinset theorem mem_range_of_measure_ne_zero {f : α →ₛ β} {x : β} {μ : Measure α} (H : μ (f ⁻¹' {x}) ≠ 0) : x ∈ f.range := let ⟨a, ha⟩ := nonempty_of_measure_ne_zero H mem_range.2 ⟨a, ha⟩ theorem forall_mem_range {f : α →ₛ β} {p : β → Prop} : (∀ y ∈ f.range, p y) ↔ ∀ x, p (f x) := by simp only [mem_range, Set.forall_mem_range] theorem exists_range_iff {f : α →ₛ β} {p : β → Prop} : (∃ y ∈ f.range, p y) ↔ ∃ x, p (f x) := by simpa only [mem_range, exists_prop] using Set.exists_range_iff theorem preimage_eq_empty_iff (f : α →ₛ β) (b : β) : f ⁻¹' {b} = ∅ ↔ b ∉ f.range := preimage_singleton_eq_empty.trans <| not_congr mem_range.symm theorem exists_forall_le [Nonempty β] [Preorder β] [IsDirected β (· ≤ ·)] (f : α →ₛ β) : ∃ C, ∀ x, f x ≤ C := f.range.exists_le.imp fun _ => forall_mem_range.1 /-- Constant function as a `SimpleFunc`. -/ def const (α) {β} [MeasurableSpace α] (b : β) : α →ₛ β := ⟨fun _ => b, fun _ => MeasurableSet.const _, finite_range_const⟩ instance instInhabited [Inhabited β] : Inhabited (α →ₛ β) := ⟨const _ default⟩ theorem const_apply (a : α) (b : β) : (const α b) a = b := rfl @[simp] theorem coe_const (b : β) : ⇑(const α b) = Function.const α b := rfl @[simp] theorem range_const (α) [MeasurableSpace α] [Nonempty α] (b : β) : (const α b).range = {b} := Finset.coe_injective <| by simp +unfoldPartialApp [Function.const] theorem range_const_subset (α) [MeasurableSpace α] (b : β) : (const α b).range ⊆ {b} := Finset.coe_subset.1 <| by simp theorem simpleFunc_bot {α} (f : @SimpleFunc α ⊥ β) [Nonempty β] : ∃ c, ∀ x, f x = c := by have hf_meas := @SimpleFunc.measurableSet_fiber α _ ⊥ f simp_rw [MeasurableSpace.measurableSet_bot_iff] at hf_meas exact (exists_eq_const_of_preimage_singleton hf_meas).imp fun c hc ↦ congr_fun hc theorem simpleFunc_bot' {α} [Nonempty β] (f : @SimpleFunc α ⊥ β) : ∃ c, f = @SimpleFunc.const α _ ⊥ c := letI : MeasurableSpace α := ⊥; (simpleFunc_bot f).imp fun _ ↦ ext theorem measurableSet_cut (r : α → β → Prop) (f : α →ₛ β) (h : ∀ b, MeasurableSet { a | r a b }) : MeasurableSet { a | r a (f a) } := by have : { a | r a (f a) } = ⋃ b ∈ range f, { a | r a b } ∩ f ⁻¹' {b} := by ext a suffices r a (f a) ↔ ∃ i, r a (f i) ∧ f a = f i by simpa exact ⟨fun h => ⟨a, ⟨h, rfl⟩⟩, fun ⟨a', ⟨h', e⟩⟩ => e.symm ▸ h'⟩ rw [this] exact MeasurableSet.biUnion f.finite_range.countable fun b _ => MeasurableSet.inter (h b) (f.measurableSet_fiber _) @[measurability] theorem measurableSet_preimage (f : α →ₛ β) (s) : MeasurableSet (f ⁻¹' s) := measurableSet_cut (fun _ b => b ∈ s) f fun b => MeasurableSet.const (b ∈ s) /-- A simple function is measurable -/ @[measurability, fun_prop] protected theorem measurable [MeasurableSpace β] (f : α →ₛ β) : Measurable f := fun s _ => measurableSet_preimage f s @[measurability] protected theorem aemeasurable [MeasurableSpace β] {μ : Measure α} (f : α →ₛ β) : AEMeasurable f μ := f.measurable.aemeasurable protected theorem sum_measure_preimage_singleton (f : α →ₛ β) {μ : Measure α} (s : Finset β) : (∑ y ∈ s, μ (f ⁻¹' {y})) = μ (f ⁻¹' ↑s) := sum_measure_preimage_singleton _ fun _ _ => f.measurableSet_fiber _ theorem sum_range_measure_preimage_singleton (f : α →ₛ β) (μ : Measure α) : (∑ y ∈ f.range, μ (f ⁻¹' {y})) = μ univ := by rw [f.sum_measure_preimage_singleton, coe_range, preimage_range] open scoped Classical in /-- If-then-else as a `SimpleFunc`. -/ def piecewise (s : Set α) (hs : MeasurableSet s) (f g : α →ₛ β) : α →ₛ β := ⟨s.piecewise f g, fun _ => letI : MeasurableSpace β := ⊤ f.measurable.piecewise hs g.measurable trivial, (f.finite_range.union g.finite_range).subset range_ite_subset⟩ open scoped Classical in @[simp] theorem coe_piecewise {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) : ⇑(piecewise s hs f g) = s.piecewise f g := rfl open scoped Classical in theorem piecewise_apply {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) (a) : piecewise s hs f g a = if a ∈ s then f a else g a := rfl open scoped Classical in @[simp] theorem piecewise_compl {s : Set α} (hs : MeasurableSet sᶜ) (f g : α →ₛ β) : piecewise sᶜ hs f g = piecewise s hs.of_compl g f := coe_injective <| by simp [hs] @[simp] theorem piecewise_univ (f g : α →ₛ β) : piecewise univ MeasurableSet.univ f g = f := coe_injective <| by simp @[simp] theorem piecewise_empty (f g : α →ₛ β) : piecewise ∅ MeasurableSet.empty f g = g := coe_injective <| by simp open scoped Classical in @[simp] theorem piecewise_same (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) : piecewise s hs f f = f := coe_injective <| Set.piecewise_same _ _ theorem support_indicator [Zero β] {s : Set α} (hs : MeasurableSet s) (f : α →ₛ β) : Function.support (f.piecewise s hs (SimpleFunc.const α 0)) = s ∩ Function.support f := Set.support_indicator open scoped Classical in theorem range_indicator {s : Set α} (hs : MeasurableSet s) (hs_nonempty : s.Nonempty) (hs_ne_univ : s ≠ univ) (x y : β) : (piecewise s hs (const α x) (const α y)).range = {x, y} := by simp only [← Finset.coe_inj, coe_range, coe_piecewise, range_piecewise, coe_const, Finset.coe_insert, Finset.coe_singleton, hs_nonempty.image_const, (nonempty_compl.2 hs_ne_univ).image_const, singleton_union, Function.const] theorem measurable_bind [MeasurableSpace γ] (f : α →ₛ β) (g : β → α → γ) (hg : ∀ b, Measurable (g b)) : Measurable fun a => g (f a) a := fun s hs => f.measurableSet_cut (fun a b => g b a ∈ s) fun b => hg b hs /-- If `f : α →ₛ β` is a simple function and `g : β → α →ₛ γ` is a family of simple functions, then `f.bind g` binds the first argument of `g` to `f`. In other words, `f.bind g a = g (f a) a`. -/ def bind (f : α →ₛ β) (g : β → α →ₛ γ) : α →ₛ γ := ⟨fun a => g (f a) a, fun c => f.measurableSet_cut (fun a b => g b a = c) fun b => (g b).measurableSet_preimage {c}, (f.finite_range.biUnion fun b _ => (g b).finite_range).subset <| by rintro _ ⟨a, rfl⟩; simp⟩ @[simp] theorem bind_apply (f : α →ₛ β) (g : β → α →ₛ γ) (a) : f.bind g a = g (f a) a := rfl /-- Given a function `g : β → γ` and a simple function `f : α →ₛ β`, `f.map g` return the simple function `g ∘ f : α →ₛ γ` -/ def map (g : β → γ) (f : α →ₛ β) : α →ₛ γ := bind f (const α ∘ g) theorem map_apply (g : β → γ) (f : α →ₛ β) (a) : f.map g a = g (f a) := rfl theorem map_map (g : β → γ) (h : γ → δ) (f : α →ₛ β) : (f.map g).map h = f.map (h ∘ g) := rfl @[simp] theorem coe_map (g : β → γ) (f : α →ₛ β) : (f.map g : α → γ) = g ∘ f := rfl @[simp] theorem range_map [DecidableEq γ] (g : β → γ) (f : α →ₛ β) : (f.map g).range = f.range.image g := Finset.coe_injective <| by simp only [coe_range, coe_map, Finset.coe_image, range_comp] @[simp] theorem map_const (g : β → γ) (b : β) : (const α b).map g = const α (g b) := rfl open scoped Classical in theorem map_preimage (f : α →ₛ β) (g : β → γ) (s : Set γ) : f.map g ⁻¹' s = f ⁻¹' ↑{b ∈ f.range | g b ∈ s} := by simp only [coe_range, sep_mem_eq, coe_map, Finset.coe_filter, ← mem_preimage, inter_comm, preimage_inter_range, ← Finset.mem_coe] exact preimage_comp open scoped Classical in theorem map_preimage_singleton (f : α →ₛ β) (g : β → γ) (c : γ) : f.map g ⁻¹' {c} = f ⁻¹' ↑{b ∈ f.range | g b = c} := map_preimage _ _ _ /-- Composition of a `SimpleFun` and a measurable function is a `SimpleFunc`. -/ def comp [MeasurableSpace β] (f : β →ₛ γ) (g : α → β) (hgm : Measurable g) : α →ₛ γ where toFun := f ∘ g finite_range' := f.finite_range.subset <| Set.range_comp_subset_range _ _ measurableSet_fiber' z := hgm (f.measurableSet_fiber z) @[simp] theorem coe_comp [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) : ⇑(f.comp g hgm) = f ∘ g := rfl theorem range_comp_subset_range [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) : (f.comp g hgm).range ⊆ f.range := Finset.coe_subset.1 <| by simp only [coe_range, coe_comp, Set.range_comp_subset_range] /-- Extend a `SimpleFunc` along a measurable embedding: `f₁.extend g hg f₂` is the function `F : β →ₛ γ` such that `F ∘ g = f₁` and `F y = f₂ y` whenever `y ∉ range g`. -/ def extend [MeasurableSpace β] (f₁ : α →ₛ γ) (g : α → β) (hg : MeasurableEmbedding g) (f₂ : β →ₛ γ) : β →ₛ γ where toFun := Function.extend g f₁ f₂ finite_range' := (f₁.finite_range.union <| f₂.finite_range.subset (image_subset_range _ _)).subset (range_extend_subset _ _ _) measurableSet_fiber' := by letI : MeasurableSpace γ := ⊤; haveI : MeasurableSingletonClass γ := ⟨fun _ => trivial⟩ exact fun x => hg.measurable_extend f₁.measurable f₂.measurable (measurableSet_singleton _) @[simp] theorem extend_apply [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g) (f₂ : β →ₛ γ) (x : α) : (f₁.extend g hg f₂) (g x) = f₁ x := hg.injective.extend_apply _ _ _ @[simp] theorem extend_apply' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g) (f₂ : β →ₛ γ) {y : β} (h : ¬∃ x, g x = y) : (f₁.extend g hg f₂) y = f₂ y := Function.extend_apply' _ _ _ h @[simp] theorem extend_comp_eq' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g) (f₂ : β →ₛ γ) : f₁.extend g hg f₂ ∘ g = f₁ := funext fun _ => extend_apply _ _ _ _ @[simp] theorem extend_comp_eq [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g) (f₂ : β →ₛ γ) : (f₁.extend g hg f₂).comp g hg.measurable = f₁ := coe_injective <| extend_comp_eq' _ hg _ /-- If `f` is a simple function taking values in `β → γ` and `g` is another simple function with the same domain and codomain `β`, then `f.seq g = f a (g a)`. -/ def seq (f : α →ₛ β → γ) (g : α →ₛ β) : α →ₛ γ := f.bind fun f => g.map f @[simp] theorem seq_apply (f : α →ₛ β → γ) (g : α →ₛ β) (a : α) : f.seq g a = f a (g a) := rfl /-- Combine two simple functions `f : α →ₛ β` and `g : α →ₛ β` into `fun a => (f a, g a)`. -/ def pair (f : α →ₛ β) (g : α →ₛ γ) : α →ₛ β × γ := (f.map Prod.mk).seq g @[simp] theorem pair_apply (f : α →ₛ β) (g : α →ₛ γ) (a) : pair f g a = (f a, g a) := rfl theorem pair_preimage (f : α →ₛ β) (g : α →ₛ γ) (s : Set β) (t : Set γ) : pair f g ⁻¹' s ×ˢ t = f ⁻¹' s ∩ g ⁻¹' t := rfl -- A special form of `pair_preimage` theorem pair_preimage_singleton (f : α →ₛ β) (g : α →ₛ γ) (b : β) (c : γ) : pair f g ⁻¹' {(b, c)} = f ⁻¹' {b} ∩ g ⁻¹' {c} := by rw [← singleton_prod_singleton] exact pair_preimage _ _ _ _ @[simp] theorem map_fst_pair (f : α →ₛ β) (g : α →ₛ γ) : (f.pair g).map Prod.fst = f := rfl @[simp] theorem map_snd_pair (f : α →ₛ β) (g : α →ₛ γ) : (f.pair g).map Prod.snd = g := rfl @[simp] theorem bind_const (f : α →ₛ β) : f.bind (const α) = f := by ext; simp @[to_additive] instance instOne [One β] : One (α →ₛ β) := ⟨const α 1⟩ @[to_additive] instance instMul [Mul β] : Mul (α →ₛ β) := ⟨fun f g => (f.map (· * ·)).seq g⟩ @[to_additive] instance instDiv [Div β] : Div (α →ₛ β) := ⟨fun f g => (f.map (· / ·)).seq g⟩ @[to_additive] instance instInv [Inv β] : Inv (α →ₛ β) := ⟨fun f => f.map Inv.inv⟩ instance instSup [Max β] : Max (α →ₛ β) := ⟨fun f g => (f.map (· ⊔ ·)).seq g⟩ instance instInf [Min β] : Min (α →ₛ β) := ⟨fun f g => (f.map (· ⊓ ·)).seq g⟩ instance instLE [LE β] : LE (α →ₛ β) := ⟨fun f g => ∀ a, f a ≤ g a⟩ @[to_additive (attr := simp)] theorem const_one [One β] : const α (1 : β) = 1 := rfl @[to_additive (attr := simp, norm_cast)] theorem coe_one [One β] : ⇑(1 : α →ₛ β) = 1 := rfl @[to_additive (attr := simp, norm_cast)] theorem coe_mul [Mul β] (f g : α →ₛ β) : ⇑(f * g) = ⇑f * ⇑g := rfl @[to_additive (attr := simp, norm_cast)] theorem coe_inv [Inv β] (f : α →ₛ β) : ⇑(f⁻¹) = (⇑f)⁻¹ := rfl @[to_additive (attr := simp, norm_cast)] theorem coe_div [Div β] (f g : α →ₛ β) : ⇑(f / g) = ⇑f / ⇑g := rfl @[simp, norm_cast] theorem coe_le [LE β] {f g : α →ₛ β} : (f : α → β) ≤ g ↔ f ≤ g := Iff.rfl @[simp, norm_cast] theorem coe_sup [Max β] (f g : α →ₛ β) : ⇑(f ⊔ g) = ⇑f ⊔ ⇑g := rfl @[simp, norm_cast] theorem coe_inf [Min β] (f g : α →ₛ β) : ⇑(f ⊓ g) = ⇑f ⊓ ⇑g := rfl @[to_additive] theorem mul_apply [Mul β] (f g : α →ₛ β) (a : α) : (f * g) a = f a * g a := rfl @[to_additive] theorem div_apply [Div β] (f g : α →ₛ β) (x : α) : (f / g) x = f x / g x := rfl @[to_additive] theorem inv_apply [Inv β] (f : α →ₛ β) (x : α) : f⁻¹ x = (f x)⁻¹ := rfl theorem sup_apply [Max β] (f g : α →ₛ β) (a : α) : (f ⊔ g) a = f a ⊔ g a := rfl theorem inf_apply [Min β] (f g : α →ₛ β) (a : α) : (f ⊓ g) a = f a ⊓ g a := rfl @[to_additive (attr := simp)] theorem range_one [Nonempty α] [One β] : (1 : α →ₛ β).range = {1} := Finset.ext fun x => by simp [eq_comm] @[simp] theorem range_eq_empty_of_isEmpty {β} [hα : IsEmpty α] (f : α →ₛ β) : f.range = ∅ := by rw [← Finset.not_nonempty_iff_eq_empty] by_contra h obtain ⟨y, hy_mem⟩ := h rw [SimpleFunc.mem_range, Set.mem_range] at hy_mem obtain ⟨x, hxy⟩ := hy_mem rw [isEmpty_iff] at hα exact hα x theorem eq_zero_of_mem_range_zero [Zero β] : ∀ {y : β}, y ∈ (0 : α →ₛ β).range → y = 0 := @(forall_mem_range.2 fun _ => rfl) @[to_additive] theorem mul_eq_map₂ [Mul β] (f g : α →ₛ β) : f * g = (pair f g).map fun p : β × β => p.1 * p.2 := rfl theorem sup_eq_map₂ [Max β] (f g : α →ₛ β) : f ⊔ g = (pair f g).map fun p : β × β => p.1 ⊔ p.2 := rfl @[to_additive] theorem const_mul_eq_map [Mul β] (f : α →ₛ β) (b : β) : const α b * f = f.map fun a => b * a := rfl @[to_additive] theorem map_mul [Mul β] [Mul γ] {g : β → γ} (hg : ∀ x y, g (x * y) = g x * g y) (f₁ f₂ : α →ₛ β) : (f₁ * f₂).map g = f₁.map g * f₂.map g := ext fun _ => hg _ _ variable {K : Type*} @[to_additive] instance instSMul [SMul K β] : SMul K (α →ₛ β) := ⟨fun k f => f.map (k • ·)⟩ @[to_additive (attr := simp)] theorem coe_smul [SMul K β] (c : K) (f : α →ₛ β) : ⇑(c • f) = c • ⇑f := rfl @[to_additive (attr := simp)] theorem smul_apply [SMul K β] (k : K) (f : α →ₛ β) (a : α) : (k • f) a = k • f a := rfl instance hasNatSMul [AddMonoid β] : SMul ℕ (α →ₛ β) := inferInstance @[to_additive existing hasNatSMul] instance hasNatPow [Monoid β] : Pow (α →ₛ β) ℕ := ⟨fun f n => f.map (· ^ n)⟩ @[simp] theorem coe_pow [Monoid β] (f : α →ₛ β) (n : ℕ) : ⇑(f ^ n) = (⇑f) ^ n := rfl theorem pow_apply [Monoid β] (n : ℕ) (f : α →ₛ β) (a : α) : (f ^ n) a = f a ^ n := rfl instance hasIntPow [DivInvMonoid β] : Pow (α →ₛ β) ℤ := ⟨fun f n => f.map (· ^ n)⟩ @[simp] theorem coe_zpow [DivInvMonoid β] (f : α →ₛ β) (z : ℤ) : ⇑(f ^ z) = (⇑f) ^ z := rfl theorem zpow_apply [DivInvMonoid β] (z : ℤ) (f : α →ₛ β) (a : α) : (f ^ z) a = f a ^ z := rfl -- TODO: work out how to generate these instances with `to_additive`, which gets confused by the -- argument order swap between `coe_smul` and `coe_pow`. section Additive instance instAddMonoid [AddMonoid β] : AddMonoid (α →ₛ β) := Function.Injective.addMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add fun _ _ => coe_smul _ _ instance instAddCommMonoid [AddCommMonoid β] : AddCommMonoid (α →ₛ β) := Function.Injective.addCommMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add fun _ _ => coe_smul _ _ instance instAddGroup [AddGroup β] : AddGroup (α →ₛ β) := Function.Injective.addGroup (fun f => show α → β from f) coe_injective coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _ instance instAddCommGroup [AddCommGroup β] : AddCommGroup (α →ₛ β) := Function.Injective.addCommGroup (fun f => show α → β from f) coe_injective coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _ end Additive @[to_additive existing] instance instMonoid [Monoid β] : Monoid (α →ₛ β) := Function.Injective.monoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow @[to_additive existing] instance instCommMonoid [CommMonoid β] : CommMonoid (α →ₛ β) := Function.Injective.commMonoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow @[to_additive existing] instance instGroup [Group β] : Group (α →ₛ β) := Function.Injective.group (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv coe_div coe_pow coe_zpow @[to_additive existing] instance instCommGroup [CommGroup β] : CommGroup (α →ₛ β) := Function.Injective.commGroup (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv coe_div coe_pow coe_zpow instance instModule [Semiring K] [AddCommMonoid β] [Module K β] : Module K (α →ₛ β) := Function.Injective.module K ⟨⟨fun f => show α → β from f, coe_zero⟩, coe_add⟩ coe_injective coe_smul theorem smul_eq_map [SMul K β] (k : K) (f : α →ₛ β) : k • f = f.map (k • ·) := rfl section Preorder variable [Preorder β] {s : Set α} {f f₁ f₂ g g₁ g₂ : α →ₛ β} {hs : MeasurableSet s} instance instPreorder : Preorder (α →ₛ β) := Preorder.lift (⇑) @[norm_cast] lemma coe_le_coe : ⇑f ≤ g ↔ f ≤ g := .rfl @[simp, norm_cast] lemma coe_lt_coe : ⇑f < g ↔ f < g := .rfl @[simp] lemma mk_le_mk {f g : α → β} {hf hg hf' hg'} : mk f hf hf' ≤ mk g hg hg' ↔ f ≤ g := Iff.rfl @[simp] lemma mk_lt_mk {f g : α → β} {hf hg hf' hg'} : mk f hf hf' < mk g hg hg' ↔ f < g := Iff.rfl @[gcongr] protected alias ⟨_, GCongr.mk_le_mk⟩ := mk_le_mk @[gcongr] protected alias ⟨_, GCongr.mk_lt_mk⟩ := mk_lt_mk @[gcongr] protected alias ⟨_, GCongr.coe_le_coe⟩ := coe_le_coe @[gcongr] protected alias ⟨_, GCongr.coe_lt_coe⟩ := coe_lt_coe open scoped Classical in @[gcongr] lemma piecewise_mono (hf : ∀ a ∈ s, f₁ a ≤ f₂ a) (hg : ∀ a ∉ s, g₁ a ≤ g₂ a) : piecewise s hs f₁ g₁ ≤ piecewise s hs f₂ g₂ := Set.piecewise_mono hf hg end Preorder instance instPartialOrder [PartialOrder β] : PartialOrder (α →ₛ β) := { SimpleFunc.instPreorder with le_antisymm := fun _f _g hfg hgf => ext fun a => le_antisymm (hfg a) (hgf a) } instance instOrderBot [LE β] [OrderBot β] : OrderBot (α →ₛ β) where bot := const α ⊥ bot_le _ _ := bot_le instance instOrderTop [LE β] [OrderTop β] : OrderTop (α →ₛ β) where top := const α ⊤ le_top _ _ := le_top @[to_additive] instance [CommMonoid β] [PartialOrder β] [IsOrderedMonoid β] : IsOrderedMonoid (α →ₛ β) where mul_le_mul_left _ _ h _ _ := mul_le_mul_left' (h _) _ instance instSemilatticeInf [SemilatticeInf β] : SemilatticeInf (α →ₛ β) := { SimpleFunc.instPartialOrder with inf := (· ⊓ ·) inf_le_left := fun _ _ _ => inf_le_left inf_le_right := fun _ _ _ => inf_le_right le_inf := fun _f _g _h hfh hgh a => le_inf (hfh a) (hgh a) } instance instSemilatticeSup [SemilatticeSup β] : SemilatticeSup (α →ₛ β) := { SimpleFunc.instPartialOrder with sup := (· ⊔ ·) le_sup_left := fun _ _ _ => le_sup_left le_sup_right := fun _ _ _ => le_sup_right sup_le := fun _f _g _h hfh hgh a => sup_le (hfh a) (hgh a) } instance instLattice [Lattice β] : Lattice (α →ₛ β) := { SimpleFunc.instSemilatticeSup, SimpleFunc.instSemilatticeInf with } instance instBoundedOrder [LE β] [BoundedOrder β] : BoundedOrder (α →ₛ β) := { SimpleFunc.instOrderBot, SimpleFunc.instOrderTop with } theorem finset_sup_apply [SemilatticeSup β] [OrderBot β] {f : γ → α →ₛ β} (s : Finset γ) (a : α) : s.sup f a = s.sup fun c => f c a := by classical refine Finset.induction_on s rfl ?_ intro a s _ ih rw [Finset.sup_insert, Finset.sup_insert, sup_apply, ih] section Restrict variable [Zero β] open scoped Classical in /-- Restrict a simple function `f : α →ₛ β` to a set `s`. If `s` is measurable, then `f.restrict s a = if a ∈ s then f a else 0`, otherwise `f.restrict s = const α 0`. -/ def restrict (f : α →ₛ β) (s : Set α) : α →ₛ β := if hs : MeasurableSet s then piecewise s hs f 0 else 0 theorem restrict_of_not_measurable {f : α →ₛ β} {s : Set α} (hs : ¬MeasurableSet s) : restrict f s = 0 := dif_neg hs @[simp] theorem coe_restrict (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) : ⇑(restrict f s) = indicator s f := by classical rw [restrict, dif_pos hs, coe_piecewise, coe_zero, piecewise_eq_indicator] @[simp] theorem restrict_univ (f : α →ₛ β) : restrict f univ = f := by simp [restrict] @[simp] theorem restrict_empty (f : α →ₛ β) : restrict f ∅ = 0 := by simp [restrict] open scoped Classical in theorem map_restrict_of_zero [Zero γ] {g : β → γ} (hg : g 0 = 0) (f : α →ₛ β) (s : Set α) : (f.restrict s).map g = (f.map g).restrict s := ext fun x => if hs : MeasurableSet s then by simp [hs, Set.indicator_comp_of_zero hg] else by simp [restrict_of_not_measurable hs, hg] theorem map_coe_ennreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) : (f.restrict s).map ((↑) : ℝ≥0 → ℝ≥0∞) = (f.map (↑)).restrict s := map_restrict_of_zero ENNReal.coe_zero _ _ theorem map_coe_nnreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) : (f.restrict s).map ((↑) : ℝ≥0 → ℝ) = (f.map (↑)).restrict s := map_restrict_of_zero NNReal.coe_zero _ _ theorem restrict_apply (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) (a) : restrict f s a = indicator s f a := by simp only [f.coe_restrict hs] theorem restrict_preimage (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {t : Set β} (ht : (0 : β) ∉ t) : restrict f s ⁻¹' t = s ∩ f ⁻¹' t := by simp [hs, indicator_preimage_of_not_mem _ _ ht, inter_comm] theorem restrict_preimage_singleton (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {r : β} (hr : r ≠ 0) : restrict f s ⁻¹' {r} = s ∩ f ⁻¹' {r} := f.restrict_preimage hs hr.symm theorem mem_restrict_range {r : β} {s : Set α} {f : α →ₛ β} (hs : MeasurableSet s) : r ∈ (restrict f s).range ↔ r = 0 ∧ s ≠ univ ∨ r ∈ f '' s := by rw [← Finset.mem_coe, coe_range, coe_restrict _ hs, mem_range_indicator] open scoped Classical in theorem mem_image_of_mem_range_restrict {r : β} {s : Set α} {f : α →ₛ β} (hr : r ∈ (restrict f s).range) (h0 : r ≠ 0) : r ∈ f '' s := if hs : MeasurableSet s then by simpa [mem_restrict_range hs, h0, -mem_range] using hr else by rw [restrict_of_not_measurable hs] at hr exact (h0 <| eq_zero_of_mem_range_zero hr).elim open scoped Classical in @[gcongr, mono] theorem restrict_mono [Preorder β] (s : Set α) {f g : α →ₛ β} (H : f ≤ g) : f.restrict s ≤ g.restrict s := if hs : MeasurableSet s then fun x => by simp only [coe_restrict _ hs, indicator_le_indicator (H x)] else by simp only [restrict_of_not_measurable hs, le_refl] end Restrict section Approx section variable [SemilatticeSup β] [OrderBot β] [Zero β] /-- Fix a sequence `i : ℕ → β`. Given a function `α → β`, its `n`-th approximation by simple functions is defined so that in case `β = ℝ≥0∞` it sends each `a` to the supremum of the set `{i k | k ≤ n ∧ i k ≤ f a}`, see `approx_apply` and `iSup_approx_apply` for details. -/ def approx (i : ℕ → β) (f : α → β) (n : ℕ) : α →ₛ β := (Finset.range n).sup fun k => restrict (const α (i k)) { a : α | i k ≤ f a } open scoped Classical in theorem approx_apply [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β] [OpensMeasurableSpace β] {i : ℕ → β} {f : α → β} {n : ℕ} (a : α) (hf : Measurable f) : (approx i f n : α →ₛ β) a = (Finset.range n).sup fun k => if i k ≤ f a then i k else 0 := by dsimp only [approx] rw [finset_sup_apply] congr funext k rw [restrict_apply] · simp only [coe_const, mem_setOf_eq, indicator_apply, Function.const_apply] · exact hf measurableSet_Ici theorem monotone_approx (i : ℕ → β) (f : α → β) : Monotone (approx i f) := fun _ _ h => Finset.sup_mono <| Finset.range_subset.2 h theorem approx_comp [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β] [OpensMeasurableSpace β] [MeasurableSpace γ] {i : ℕ → β} {f : γ → β} {g : α → γ} {n : ℕ} (a : α) (hf : Measurable f) (hg : Measurable g) : (approx i (f ∘ g) n : α →ₛ β) a = (approx i f n : γ →ₛ β) (g a) := by rw [approx_apply _ hf, approx_apply _ (hf.comp hg), Function.comp_apply] end theorem iSup_approx_apply [TopologicalSpace β] [CompleteLattice β] [OrderClosedTopology β] [Zero β] [MeasurableSpace β] [OpensMeasurableSpace β] (i : ℕ → β) (f : α → β) (a : α) (hf : Measurable f) (h_zero : (0 : β) = ⊥) : ⨆ n, (approx i f n : α →ₛ β) a = ⨆ (k) (_ : i k ≤ f a), i k := by refine le_antisymm (iSup_le fun n => ?_) (iSup_le fun k => iSup_le fun hk => ?_) · rw [approx_apply a hf, h_zero] refine Finset.sup_le fun k _ => ?_ split_ifs with h · exact le_iSup_of_le k (le_iSup (fun _ : i k ≤ f a => i k) h) · exact bot_le · refine le_iSup_of_le (k + 1) ?_ rw [approx_apply a hf] have : k ∈ Finset.range (k + 1) := Finset.mem_range.2 (Nat.lt_succ_self _) refine le_trans (le_of_eq ?_) (Finset.le_sup this) rw [if_pos hk] end Approx section EApprox variable {f : α → ℝ≥0∞} /-- A sequence of `ℝ≥0∞`s such that its range is the set of non-negative rational numbers. -/ def ennrealRatEmbed (n : ℕ) : ℝ≥0∞ := ENNReal.ofReal ((Encodable.decode (α := ℚ) n).getD (0 : ℚ)) theorem ennrealRatEmbed_encode (q : ℚ) : ennrealRatEmbed (Encodable.encode q) = Real.toNNReal q := by rw [ennrealRatEmbed, Encodable.encodek]; rfl /-- Approximate a function `α → ℝ≥0∞` by a sequence of simple functions. -/ def eapprox : (α → ℝ≥0∞) → ℕ → α →ₛ ℝ≥0∞ := approx ennrealRatEmbed theorem eapprox_lt_top (f : α → ℝ≥0∞) (n : ℕ) (a : α) : eapprox f n a < ∞ := by simp only [eapprox, approx, finset_sup_apply, Finset.mem_range, ENNReal.bot_eq_zero, restrict] rw [Finset.sup_lt_iff (α := ℝ≥0∞) WithTop.top_pos] intro b _ split_ifs · simp only [coe_zero, coe_piecewise, piecewise_eq_indicator, coe_const] calc { a : α | ennrealRatEmbed b ≤ f a }.indicator (fun _ => ennrealRatEmbed b) a ≤ ennrealRatEmbed b := indicator_le_self _ _ a _ < ⊤ := ENNReal.coe_lt_top · exact WithTop.top_pos @[mono] theorem monotone_eapprox (f : α → ℝ≥0∞) : Monotone (eapprox f) := monotone_approx _ f @[gcongr] lemma eapprox_mono {m n : ℕ} (hmn : m ≤ n) : eapprox f m ≤ eapprox f n := monotone_eapprox _ hmn lemma iSup_eapprox_apply (hf : Measurable f) (a : α) : ⨆ n, (eapprox f n : α →ₛ ℝ≥0∞) a = f a := by rw [eapprox, iSup_approx_apply ennrealRatEmbed f a hf rfl] refine le_antisymm (iSup_le fun i => iSup_le fun hi => hi) (le_of_not_gt ?_) intro h rcases ENNReal.lt_iff_exists_rat_btwn.1 h with ⟨q, _, lt_q, q_lt⟩ have : (Real.toNNReal q : ℝ≥0∞) ≤ ⨆ (k : ℕ) (_ : ennrealRatEmbed k ≤ f a), ennrealRatEmbed k := by refine le_iSup_of_le (Encodable.encode q) ?_ rw [ennrealRatEmbed_encode q] exact le_iSup_of_le (le_of_lt q_lt) le_rfl exact lt_irrefl _ (lt_of_le_of_lt this lt_q) lemma iSup_coe_eapprox (hf : Measurable f) : ⨆ n, ⇑(eapprox f n) = f := by simpa [funext_iff] using iSup_eapprox_apply hf theorem eapprox_comp [MeasurableSpace γ] {f : γ → ℝ≥0∞} {g : α → γ} {n : ℕ} (hf : Measurable f) (hg : Measurable g) : (eapprox (f ∘ g) n : α → ℝ≥0∞) = (eapprox f n : γ →ₛ ℝ≥0∞) ∘ g := funext fun a => approx_comp a hf hg lemma tendsto_eapprox {f : α → ℝ≥0∞} (hf_meas : Measurable f) (a : α) : Tendsto (fun n ↦ eapprox f n a) atTop (𝓝 (f a)) := by nth_rw 2 [← iSup_coe_eapprox hf_meas] rw [iSup_apply] exact tendsto_atTop_iSup fun _ _ hnm ↦ monotone_eapprox f hnm a /-- Approximate a function `α → ℝ≥0∞` by a series of simple functions taking their values
in `ℝ≥0`. -/ def eapproxDiff (f : α → ℝ≥0∞) : ℕ → α →ₛ ℝ≥0 | 0 => (eapprox f 0).map ENNReal.toNNReal | n + 1 => (eapprox f (n + 1) - eapprox f n).map ENNReal.toNNReal
Mathlib/MeasureTheory/Function/SimpleFunc.lean
810
814
/- 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, Kevin Klinge, Andrew Yang -/ import Mathlib.Algebra.Group.Submonoid.DistribMulAction import Mathlib.GroupTheory.OreLocalization.Basic import Mathlib.Algebra.GroupWithZero.Defs /-! # Localization over left Ore sets. This file proves results on the localization of rings (monoids with zeros) over a left Ore set. ## References * <https://ncatlab.org/nlab/show/Ore+localization> * [Zoran Škoda, *Noncommutative localization in noncommutative geometry*][skoda2006] ## Tags localization, Ore, non-commutative -/ assert_not_exists RelIso universe u open OreLocalization namespace OreLocalization section MonoidWithZero variable {R : Type*} [MonoidWithZero R] {S : Submonoid R} [OreSet S] @[simp] theorem zero_oreDiv' (s : S) : (0 : R) /ₒ s = 0 := by rw [OreLocalization.zero_def, oreDiv_eq_iff] exact ⟨s, 1, by simp [Submonoid.smul_def]⟩ instance : MonoidWithZero R[S⁻¹] where zero_mul x := by induction' x using OreLocalization.ind with r s rw [OreLocalization.zero_def, oreDiv_mul_char 0 r 1 s 0 1 (by simp), zero_mul, one_mul] mul_zero x := by induction' x using OreLocalization.ind with r s rw [OreLocalization.zero_def, mul_div_one, mul_zero, zero_oreDiv', zero_oreDiv'] end MonoidWithZero section CommMonoidWithZero variable {R : Type*} [CommMonoidWithZero R] {S : Submonoid R} [OreSet S] instance : CommMonoidWithZero R[S⁻¹] where __ := inferInstanceAs (MonoidWithZero R[S⁻¹]) __ := inferInstanceAs (CommMonoid R[S⁻¹]) end CommMonoidWithZero section DistribMulAction variable {R : Type*} [Monoid R] {S : Submonoid R} [OreSet S] {X : Type*} [AddMonoid X] variable [DistribMulAction R X] private def add'' (r₁ : X) (s₁ : S) (r₂ : X) (s₂ : S) : X[S⁻¹] := (oreDenom (s₁ : R) s₂ • r₁ + oreNum (s₁ : R) s₂ • r₂) /ₒ (oreDenom (s₁ : R) s₂ * s₁) private theorem add''_char (r₁ : X) (s₁ : S) (r₂ : X) (s₂ : S) (rb : R) (sb : R) (hb : sb * s₁ = rb * s₂) (h : sb * s₁ ∈ S) : add'' r₁ s₁ r₂ s₂ = (sb • r₁ + rb • r₂) /ₒ ⟨sb * s₁, h⟩ := by simp only [add''] have ha := ore_eq (s₁ : R) s₂ generalize oreNum (s₁ : R) s₂ = ra at * generalize oreDenom (s₁ : R) s₂ = sa at * rw [oreDiv_eq_iff] rcases oreCondition sb sa with ⟨rc, sc, hc⟩ have : sc * rb * s₂ = rc * ra * s₂ := by rw [mul_assoc rc, ← ha, ← mul_assoc, ← hc, mul_assoc, mul_assoc, hb] rcases ore_right_cancel _ _ s₂ this with ⟨sd, hd⟩ use sd * sc use sd * rc simp only [smul_add, smul_smul, Submonoid.smul_def, Submonoid.coe_mul] constructor · rw [mul_assoc _ _ rb, hd, mul_assoc, hc, mul_assoc, mul_assoc] · rw [mul_assoc, ← mul_assoc (sc : R), hc, mul_assoc, mul_assoc] attribute [local instance] OreLocalization.oreEqv private def add' (r₂ : X) (s₂ : S) : X[S⁻¹] → X[S⁻¹] := (--plus tilde Quotient.lift fun r₁s₁ : X × S => add'' r₁s₁.1 r₁s₁.2 r₂ s₂) <| by -- Porting note: `assoc_rw` & `noncomm_ring` were not ported yet rintro ⟨r₁', s₁'⟩ ⟨r₁, s₁⟩ ⟨sb, rb, hb, hb'⟩ -- s*, r* rcases oreCondition (s₁' : R) s₂ with ⟨rc, sc, hc⟩ --s~~, r~~ rcases oreCondition rb sc with ⟨rd, sd, hd⟩ -- s#, r# dsimp at * rw [add''_char _ _ _ _ rc sc hc (sc * s₁').2] have : sd * sb * s₁ = rd * rc * s₂ := by rw [mul_assoc, hb', ← mul_assoc, hd, mul_assoc, hc, ← mul_assoc] rw [add''_char _ _ _ _ (rd * rc : R) (sd * sb) this (sd * sb * s₁).2] rw [mul_smul, ← Submonoid.smul_def sb, hb, smul_smul, hd, oreDiv_eq_iff] use 1 use rd simp only [mul_smul, smul_add, one_smul, OneMemClass.coe_one, one_mul, true_and] rw [this, hc, mul_assoc] /-- The addition on the Ore localization. -/ @[irreducible] private def add : X[S⁻¹] → X[S⁻¹] → X[S⁻¹] := fun x => Quotient.lift (fun rs : X × S => add' rs.1 rs.2 x) (by rintro ⟨r₁, s₁⟩ ⟨r₂, s₂⟩ ⟨sb, rb, hb, hb'⟩ induction' x with r₃ s₃ show add'' _ _ _ _ = add'' _ _ _ _ dsimp only at * rcases oreCondition (s₃ : R) s₂ with ⟨rc, sc, hc⟩ rcases oreCondition rc sb with ⟨rd, sd, hd⟩ have : rd * rb * s₁ = sd * sc * s₃ := by rw [mul_assoc, ← hb', ← mul_assoc, ← hd, mul_assoc, ← hc, mul_assoc] rw [add''_char _ _ _ _ rc sc hc (sc * s₃).2] rw [add''_char _ _ _ _ _ _ this.symm (sd * sc * s₃).2] refine oreDiv_eq_iff.mpr ?_ simp only [Submonoid.mk_smul, smul_add] use sd, 1 simp only [one_smul, one_mul, mul_smul, ← hb, Submonoid.smul_def, ← mul_assoc, and_true] simp only [smul_smul, hd]) instance : Add X[S⁻¹] := ⟨add⟩ theorem oreDiv_add_oreDiv {r r' : X} {s s' : S} : r /ₒ s + r' /ₒ s' = (oreDenom (s : R) s' • r + oreNum (s : R) s' • r') /ₒ (oreDenom (s : R) s' * s) := by with_unfolding_all rfl theorem oreDiv_add_char' {r r' : X} (s s' : S) (rb : R) (sb : R) (h : sb * s = rb * s') (h' : sb * s ∈ S) : r /ₒ s + r' /ₒ s' = (sb • r + rb • r') /ₒ ⟨sb * s, h'⟩ := by with_unfolding_all exact add''_char r s r' s' rb sb h h' /-- A characterization of the addition on the Ore localizaion, allowing for arbitrary Ore numerator and Ore denominator. -/ theorem oreDiv_add_char {r r' : X} (s s' : S) (rb : R) (sb : S) (h : sb * s = rb * s') : r /ₒ s + r' /ₒ s' = (sb • r + rb • r') /ₒ (sb * s) := oreDiv_add_char' s s' rb sb h (sb * s).2 /-- Another characterization of the addition on the Ore localization, bundling up all witnesses and conditions into a sigma type. -/ def oreDivAddChar' (r r' : X) (s s' : S) : Σ'r'' : R, Σ's'' : S, s'' * s = r'' * s' ∧ r /ₒ s + r' /ₒ s' = (s'' • r + r'' • r') /ₒ (s'' * s) := ⟨oreNum (s : R) s', oreDenom (s : R) s', ore_eq (s : R) s', oreDiv_add_oreDiv⟩ @[simp] theorem add_oreDiv {r r' : X} {s : S} : r /ₒ s + r' /ₒ s = (r + r') /ₒ s := by simp [oreDiv_add_char s s 1 1 (by simp)] protected theorem add_assoc (x y z : X[S⁻¹]) : x + y + z = x + (y + z) := by induction' x with r₁ s₁ induction' y with r₂ s₂ induction' z with r₃ s₃ rcases oreDivAddChar' r₁ r₂ s₁ s₂ with ⟨ra, sa, ha, ha'⟩; rw [ha']; clear ha' rcases oreDivAddChar' (sa • r₁ + ra • r₂) r₃ (sa * s₁) s₃ with ⟨rc, sc, hc, q⟩; rw [q]; clear q simp only [smul_add, mul_assoc, add_assoc] simp_rw [← add_oreDiv, ← OreLocalization.expand'] congr 2 · rw [OreLocalization.expand r₂ s₂ ra (ha.symm ▸ (sa * s₁).2)]; congr; ext; exact ha · rw [OreLocalization.expand r₃ s₃ rc (hc.symm ▸ (sc * (sa * s₁)).2)]; congr; ext; exact hc @[simp] theorem zero_oreDiv (s : S) : (0 : X) /ₒ s = 0 := by rw [OreLocalization.zero_def, oreDiv_eq_iff] exact ⟨s, 1, by simp⟩ protected theorem zero_add (x : X[S⁻¹]) : 0 + x = x := by induction x rw [← zero_oreDiv, add_oreDiv]; simp protected theorem add_zero (x : X[S⁻¹]) : x + 0 = x := by induction x rw [← zero_oreDiv, add_oreDiv]; simp @[irreducible] private def nsmul : ℕ → X[S⁻¹] → X[S⁻¹] := nsmulRec instance : AddMonoid X[S⁻¹] where add_assoc := OreLocalization.add_assoc zero_add := OreLocalization.zero_add add_zero := OreLocalization.add_zero nsmul := nsmul nsmul_zero _ := by with_unfolding_all rfl nsmul_succ _ _ := by with_unfolding_all rfl protected theorem smul_zero (x : R[S⁻¹]) : x • (0 : X[S⁻¹]) = 0 := by induction' x with r s rw [OreLocalization.zero_def, smul_div_one, smul_zero, zero_oreDiv, zero_oreDiv] protected theorem smul_add (z : R[S⁻¹]) (x y : X[S⁻¹]) : z • (x + y) = z • x + z • y := by induction' x with r₁ s₁ induction' y with r₂ s₂ induction' z with r₃ s₃ rcases oreDivAddChar' r₁ r₂ s₁ s₂ with ⟨ra, sa, ha, ha'⟩; rw [ha']; clear ha'; norm_cast at ha rw [OreLocalization.expand' r₁ s₁ sa] rw [OreLocalization.expand r₂ s₂ ra (by rw [← ha]; apply SetLike.coe_mem)] rw [← Subtype.coe_eq_of_eq_mk ha] repeat rw [oreDiv_smul_oreDiv] simp only [smul_add, add_oreDiv] instance : DistribMulAction R[S⁻¹] X[S⁻¹] where smul_zero := OreLocalization.smul_zero smul_add := OreLocalization.smul_add instance {R₀} [Monoid R₀] [MulAction R₀ X] [MulAction R₀ R] [IsScalarTower R₀ R X] [IsScalarTower R₀ R R] : DistribMulAction R₀ X[S⁻¹] where smul_zero _ := by rw [← smul_one_oreDiv_one_smul, smul_zero] smul_add _ _ _ := by simp only [← smul_one_oreDiv_one_smul, smul_add] end DistribMulAction section AddCommMonoid variable {R : Type*} [Monoid R] {S : Submonoid R} [OreSet S] variable {X : Type*} [AddCommMonoid X] [DistribMulAction R X] protected theorem add_comm (x y : X[S⁻¹]) : x + y = y + x := by induction' x with r s induction' y with r' s' rcases oreDivAddChar' r r' s s' with ⟨ra, sa, ha, ha'⟩ rw [ha', oreDiv_add_char' s' s _ _ ha.symm (ha ▸ (sa * s).2), add_comm] congr; ext; exact ha instance instAddCommMonoidOreLocalization : AddCommMonoid X[S⁻¹] where add_comm := OreLocalization.add_comm end AddCommMonoid section AddGroup variable {R : Type*} [Monoid R] {S : Submonoid R} [OreSet S] variable {X : Type*} [AddGroup X] [DistribMulAction R X] /-- Negation on the Ore localization is defined via negation on the numerator. -/ @[irreducible] protected def neg : X[S⁻¹] → X[S⁻¹] := liftExpand (fun (r : X) (s : S) => -r /ₒ s) fun r t s ht => by -- Porting note (https://github.com/leanprover-community/mathlib4/issues/12129): additional beta reduction needed beta_reduce rw [← smul_neg, ← OreLocalization.expand] instance instNegOreLocalization : Neg X[S⁻¹] := ⟨OreLocalization.neg⟩ @[simp] protected theorem neg_def (r : X) (s : S) : -(r /ₒ s) = -r /ₒ s := by with_unfolding_all rfl protected theorem neg_add_cancel (x : X[S⁻¹]) : -x + x = 0 := by induction' x with r s; simp /-- `zsmul` of `OreLocalization` -/ @[irreducible] protected def zsmul : ℤ → X[S⁻¹] → X[S⁻¹] := zsmulRec unseal OreLocalization.zsmul in instance instAddGroupOreLocalization : AddGroup X[S⁻¹] where neg_add_cancel := OreLocalization.neg_add_cancel zsmul := OreLocalization.zsmul end AddGroup section AddCommGroup variable {R : Type*} [Monoid R] {S : Submonoid R} [OreSet S] variable {X : Type*} [AddCommGroup X] [DistribMulAction R X] instance : AddCommGroup X[S⁻¹] where __ := inferInstanceAs (AddGroup X[S⁻¹]) __ := inferInstanceAs (AddCommMonoid X[S⁻¹]) end AddCommGroup end OreLocalization
Mathlib/RingTheory/OreLocalization/Basic.lean
350
352
/- 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.Nat import Mathlib.Algebra.Ring.Int.Defs import Mathlib.Data.Nat.Bitwise import Mathlib.Data.Nat.Cast.Order.Basic import Mathlib.Data.Nat.PSub import Mathlib.Data.Nat.Size import Mathlib.Data.Num.Bitwise /-! # Properties of the binary representation of integers -/ open Int 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 @[simp] theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 := rfl @[simp, norm_cast] theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = (n : α) + n := rfl @[simp, norm_cast] theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = ((n : α) + n) + 1 := rfl @[simp, norm_cast] theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n | 1 => Nat.cast_one | bit0 p => by dsimp; rw [Nat.cast_add, p.cast_to_nat] | bit1 p => by dsimp; rw [Nat.cast_add, Nat.cast_add, Nat.cast_one, p.cast_to_nat] @[norm_cast] theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n := cast_to_nat _ @[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] theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1 | 1 => rfl | bit0 _ => rfl | bit1 p => (congr_arg (fun n ↦ n + n) (succ_to_nat p)).trans <| show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm] theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl @[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 (fun n ↦ n + n) (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _ | bit0 a, bit1 b => (congr_arg (fun n ↦ (n + n) + 1) (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 (fun n ↦ (n + n) + 1) (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] 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 _, bit0 _ => rfl | bit0 a, bit1 b => congr_arg bit0 (add_succ a b) | bit1 _, bit0 _ => rfl | bit1 a, bit1 b => congr_arg bit1 (add_succ a b) theorem bit0_of_bit0 : ∀ n, n + n = bit0 n | 1 => rfl | bit0 p => congr_arg bit0 (bit0_of_bit0 p) | bit1 p => show bit0 (succ (p + p)) = _ by rw [bit0_of_bit0 p, succ] theorem bit1_of_bit1 (n : PosNum) : (n + n) + 1 = bit1 n := show (n + n) + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ] @[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] 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 _ 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 theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by induction' m with m IH m IH <;> intro n <;> obtain - | n | n := n <;> unfold cmp <;> try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl 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) @[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] @[norm_cast] theorem le_to_nat {m n : PosNum} : (m : ℕ) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr lt_to_nat end PosNum namespace Num variable {α : Type*} open PosNum theorem add_zero (n : Num) : n + 0 = n := by cases n <;> rfl theorem zero_add (n : Num) : 0 + n = n := by cases n <;> rfl theorem add_one : ∀ n : Num, n + 1 = succ n | 0 => rfl | pos p => by cases p <;> rfl 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 _, pos _ => congr_arg pos (PosNum.add_succ _ _) theorem bit0_of_bit0 : ∀ n : Num, n + n = n.bit0 | 0 => rfl | pos p => congr_arg pos p.bit0_of_bit0 theorem bit1_of_bit1 : ∀ n : Num, (n + n) + 1 = n.bit1 | 0 => rfl | pos p => congr_arg pos p.bit1_of_bit1 @[simp] theorem ofNat'_zero : Num.ofNat' 0 = 0 := by simp [Num.ofNat'] theorem ofNat'_bit (b n) : ofNat' (Nat.bit b n) = cond b Num.bit1 Num.bit0 (ofNat' n) := Nat.binaryRec_eq _ _ (.inl rfl) @[simp] theorem ofNat'_one : Num.ofNat' 1 = 1 := by erw [ofNat'_bit true 0, cond, ofNat'_zero]; rfl theorem bit1_succ : ∀ n : Num, n.bit1.succ = n.succ.bit0 | 0 => rfl | pos _n => rfl 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] · rw [show n.bit true + 1 = (n + 1).bit false by simp [Nat.bit, mul_add], ofNat'_bit, ofNat'_bit, ih] simp only [cond, add_one, bit1_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, *] @[simp, norm_cast] theorem cast_zero [Zero α] [One α] [Add α] : ((0 : Num) : α) = 0 := rfl @[simp] theorem cast_zero' [Zero α] [One α] [Add α] : (Num.zero : α) = 0 := rfl @[simp, norm_cast] theorem cast_one [Zero α] [One α] [Add α] : ((1 : Num) : α) = 1 := rfl @[simp] theorem cast_pos [Zero α] [One α] [Add α] (n : PosNum) : (Num.pos n : α) = n := rfl theorem succ'_to_nat : ∀ n, (succ' n : ℕ) = n + 1 | 0 => (Nat.zero_add _).symm | pos _p => PosNum.succ_to_nat _ theorem succ_to_nat (n) : (succ n : ℕ) = n + 1 := succ'_to_nat n @[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 @[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 _ _ @[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 _ _ 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 _ => to_nat_pos _ | pos _, 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] @[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] @[norm_cast] theorem le_to_nat {m n : Num} : (m : ℕ) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr lt_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 simpa only [Nat.bit_false, cond_false, two_mul, of_to_nat' p] using Num.ofNat'_bit false p | bit1 p => by simpa only [Nat.bit_true, cond_true, two_mul, of_to_nat' p] using Num.ofNat'_bit true p 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' lemma toNat_injective : Function.Injective (castNum : Num → ℕ) := Function.LeftInverse.injective of_to_nat' @[norm_cast] theorem to_nat_inj {m n : Num} : (m : ℕ) = n ↔ m = n := toNat_injective.eq_iff /-- 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 instance addMonoidWithOne : AddMonoidWithOne Num := { Num.addMonoid with natCast := Num.ofNat' one := 1 natCast_zero := ofNat'_zero natCast_succ := fun _ => ofNat'_succ } 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] instance partialOrder : PartialOrder Num where 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 instance isOrderedCancelAddMonoid : IsOrderedCancelAddMonoid Num where 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 := show a + b ≤ a + c → b ≤ c by transfer_rw; apply le_of_add_le_add_left instance linearOrder : LinearOrder Num := { le_total := by intro a b transfer_rw apply le_total toDecidableLT := Num.decidableLT toDecidableLE := Num.decidableLE -- This is relying on an automatically generated instance name, -- generated in a `deriving` handler. -- See https://github.com/leanprover/lean4/issues/2343 toDecidableEq := instDecidableEqNum } instance isStrictOrderedRing : IsStrictOrderedRing Num := { 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 exists_pair_ne := ⟨0, 1, by decide⟩ } @[norm_cast] theorem add_of_nat (m n) : ((m + n : ℕ) : Num) = m + n := add_ofNat' _ _ @[norm_cast] theorem to_nat_to_int (n : Num) : ((n : ℕ) : ℤ) = n := cast_to_nat _ @[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] 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] @[simp, norm_cast] theorem of_natCast {α} [AddMonoidWithOne α] (n : ℕ) : ((n : Num) : α) = n := by rw [← cast_to_nat, to_of_nat] @[norm_cast] theorem of_nat_inj {m n : ℕ} : (m : Num) = n ↔ m = n := ⟨fun h => Function.LeftInverse.injective to_of_nat h, congr_arg _⟩ -- 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' @[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]⟩⟩ end Num namespace PosNum variable {α : Type*} open Num -- 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' @[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 _⟩ 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 (n + 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 _ => rfl @[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] @[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 _)] instance dvd : Dvd PosNum := ⟨fun m n => pos m ∣ pos n⟩ @[norm_cast] theorem dvd_to_nat {m n : PosNum} : (m : ℕ) ∣ n ↔ m ∣ n := Num.dvd_to_nat (pos m) (pos n) 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, ← two_mul] erw [@Nat.size_bit false n] have := to_nat_pos n dsimp [Nat.bit]; omega | bit1 n => by rw [size, succ_to_nat, size_to_nat n, cast_bit1, ← two_mul] erw [@Nat.size_bit true n] dsimp [Nat.bit]; omega 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] theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat] theorem natSize_pos (n) : 0 < natSize n := by cases n <;> apply Nat.succ_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 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 instance distrib : Distrib PosNum where add := (· + ·) mul := (· * ·) left_distrib := by transfer; simp [mul_add] right_distrib := by transfer; simp [mul_add, mul_comm] 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 toDecidableLT := by infer_instance toDecidableLE := by infer_instance toDecidableEq := by infer_instance @[simp] theorem cast_to_num (n : PosNum) : ↑n = Num.pos n := by rw [← cast_to_nat, ← of_to_nat n] @[simp, norm_cast] theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> simp [bit, two_mul] @[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] @[simp 500, norm_cast] theorem cast_succ [AddMonoidWithOne α] (n : PosNum) : (succ n : α) = n + 1 := by rw [← add_one, cast_add, cast_one] @[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] @[simp] theorem one_le_cast [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] (n : PosNum) : (1 : α) ≤ n := by rw [← cast_to_nat, ← Nat.cast_one, Nat.cast_le (α := α)]; apply to_nat_pos @[simp] theorem cast_pos [Semiring α] [PartialOrder α] [IsStrictOrderedRing α] (n : PosNum) : 0 < (n : α) := lt_of_lt_of_le zero_lt_one (one_le_cast n) @[simp, norm_cast] theorem cast_mul [NonAssocSemiring 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] @[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] @[simp, norm_cast] theorem cast_lt [Semiring α] [PartialOrder α] [IsStrictOrderedRing 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] @[simp, norm_cast] theorem cast_le [Semiring α] [LinearOrder α] [IsStrictOrderedRing α] {m n : PosNum} : (m : α) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr cast_lt 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 <;> simp [bit, two_mul] <;> rfl 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] theorem cast_succ [AddMonoidWithOne α] (n) : (succ n : α) = n + 1 := cast_succ' n @[simp, norm_cast] theorem cast_add [AddMonoidWithOne 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] @[simp, norm_cast] theorem cast_bit0 [NonAssocSemiring α] (n : Num) : (n.bit0 : α) = 2 * (n : α) := by rw [← bit0_of_bit0, two_mul, cast_add] @[simp, norm_cast] theorem cast_bit1 [NonAssocSemiring α] (n : Num) : (n.bit1 : α) = 2 * (n : α) + 1 := by rw [← bit1_of_bit1, bit0_of_bit0, cast_add, cast_bit0]; rfl @[simp, norm_cast] theorem cast_mul [NonAssocSemiring 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 _ _ theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n | 0 => Nat.size_zero.symm | pos p => p.size_to_nat theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n | 0 => rfl | pos p => p.size_eq_natSize theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat] @[simp 999] theorem ofNat'_eq : ∀ n, Num.ofNat' n = n := Nat.binaryRec (by simp) fun b n IH => by tauto theorem zneg_toZNum (n : Num) : -n.toZNum = n.toZNumNeg := by cases n <;> rfl theorem zneg_toZNumNeg (n : Num) : -n.toZNumNeg = n.toZNum := by cases n <;> rfl theorem toZNum_inj {m n : Num} : m.toZNum = n.toZNum ↔ m = n := ⟨fun h => by cases m <;> cases n <;> cases h <;> rfl, congr_arg _⟩ @[simp] theorem cast_toZNum [Zero α] [One α] [Add α] [Neg α] : ∀ n : Num, (n.toZNum : α) = n | 0 => rfl | Num.pos _p => rfl @[simp] theorem cast_toZNumNeg [SubtractionMonoid α] [One α] : ∀ n : Num, (n.toZNumNeg : α) = -n | 0 => neg_zero.symm | Num.pos _p => rfl @[simp] theorem add_toZNum (m n : Num) : Num.toZNum (m + n) = m.toZNum + n.toZNum := by cases m <;> cases n <;> rfl 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 theorem sub'_one (a : PosNum) : sub' a 1 = (pred' a).toZNum := by cases a <;> rfl theorem one_sub' (a : PosNum) : sub' 1 a = (pred' a).toZNumNeg := by cases a <;> rfl theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt := Iff.rfl 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 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 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 theorem cmp_swap (m n) : (cmp m n).swap = cmp n m := by cases m <;> cases n <;> try { rfl }; apply PosNum.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] @[simp, norm_cast] theorem cast_lt [Semiring α] [PartialOrder α] [IsStrictOrderedRing 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] @[simp, norm_cast] theorem cast_le [Semiring α] [LinearOrder α] [IsStrictOrderedRing α] {m n : Num} : (m : α) ≤ n ↔ m ≤ n := by rw [← not_lt]; exact not_congr cast_lt @[simp, norm_cast] theorem cast_inj [Semiring α] [PartialOrder α] [IsStrictOrderedRing 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] theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt := Iff.rfl 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 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 obtain - | m := m <;> obtain - | n := 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 this b (n : PosNum) : (cond b (↑n) 0 : ℕ) = ↑(cond b (pos n) 0 : Num) := by cases b <;> rfl have this' b (n : PosNum) : ↑ (pos (PosNum.bit b n)) = Nat.bit b ↑n := by cases b <;> simp induction' m with m IH m IH generalizing n <;> obtain - | n | 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 [this'] 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] @[simp, norm_cast] theorem castNum_or : ∀ m n : Num, ↑(m ||| n) = (↑m ||| ↑n : ℕ) := by apply castNum_eq_bitwise fun x y => pos (PosNum.lor x y) <;> (try rintro (_ | _)) <;> (try rintro (_ | _)) <;> intros <;> rfl @[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 @[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 @[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 @[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, pow_succ, ← mul_assoc, mul_comm, -shiftl_eq_shiftLeft, -PosNum.shiftl_eq_shiftLeft, shiftl, mul_two] @[simp, norm_cast] theorem castNum_shiftRight (m : Num) (n : Nat) : ↑(m >>> n) = (m : ℕ) >>> (n : ℕ) := by obtain - | m := m <;> dsimp only [← shiftr_eq_shiftRight, shiftr] · symm apply Nat.zero_shiftRight induction' n with n IH generalizing m · cases m <;> rfl have hdiv2 : ∀ m, Nat.div2 (m + m) = m := by intro; rw [Nat.div2_val]; omega obtain - | m | 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 (m + m + 1) (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 [-add_assoc, Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val, hdiv2] · trans · apply IH change Nat.shiftRight m n = Nat.shiftRight (m + 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 [-add_assoc, Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val, hdiv2] @[simp] theorem castNum_testBit (m n) : testBit m n = Nat.testBit m n := by 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 <;> obtain - | m | m := m <;> simp only [PosNum.testBit] · rfl · rw [PosNum.cast_bit1, ← two_mul, ← congr_fun Nat.bit_true, Nat.testBit_bit_zero] · rw [PosNum.cast_bit0, ← two_mul, ← congr_fun Nat.bit_false, Nat.testBit_bit_zero] · simp [Nat.testBit_add_one] · rw [PosNum.cast_bit1, ← two_mul, ← congr_fun Nat.bit_true, Nat.testBit_bit_succ, IH] · rw [PosNum.cast_bit0, ← two_mul, ← congr_fun Nat.bit_false, Nat.testBit_bit_succ, IH] end Num namespace Int /-- Cast a `SNum` to the corresponding integer. -/ def ofSnum : SNum → ℤ := SNum.rec' (fun a => cond a (-1) 0) fun a _p IH => cond a (2 * IH + 1) (2 * IH) instance snumCoe : Coe SNum ℤ := ⟨ofSnum⟩ end Int instance SNum.lt : LT SNum :=
⟨fun a b => (a : ℤ) < b⟩ instance SNum.le : LE SNum := ⟨fun a b => (a : ℤ) ≤ b⟩
Mathlib/Data/Num/Lemmas.lean
881
916
/- Copyright (c) 2023 Ashvni Narayanan. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Ashvni Narayanan, Moritz Firsching, Michael Stoll -/ import Mathlib.Algebra.Group.EvenFunction import Mathlib.Data.ZMod.Units import Mathlib.NumberTheory.MulChar.Basic /-! # Dirichlet Characters Let `R` be a commutative monoid with zero. A Dirichlet character `χ` of level `n` over `R` is a multiplicative character from `ZMod n` to `R` sending non-units to 0. We then obtain some properties of `toUnitHom χ`, the restriction of `χ` to a group homomorphism `(ZMod n)ˣ →* Rˣ`. Main definitions: - `DirichletCharacter`: The type representing a Dirichlet character. - `changeLevel`: Extend the Dirichlet character χ of level `n` to level `m`, where `n` divides `m`. - `conductor`: The conductor of a Dirichlet character. - `IsPrimitive`: If the level is equal to the conductor. ## Tags dirichlet character, multiplicative character -/ /-! ### Definitions -/ /-- The type of Dirichlet characters of level `n`. -/ abbrev DirichletCharacter (R : Type*) [CommMonoidWithZero R] (n : ℕ) := MulChar (ZMod n) R open MulChar variable {R : Type*} [CommMonoidWithZero R] {n : ℕ} (χ : DirichletCharacter R n) namespace DirichletCharacter lemma toUnitHom_eq_char' {a : ZMod n} (ha : IsUnit a) : χ a = χ.toUnitHom ha.unit := by simp lemma toUnitHom_inj (ψ : DirichletCharacter R n) : toUnitHom χ = toUnitHom ψ ↔ χ = ψ := by simp @[deprecated (since := "2024-12-29")] alias toUnitHom_eq_iff := toUnitHom_inj lemma eval_modulus_sub (x : ZMod n) : χ (n - x) = χ (-x) := by simp /-! ### Changing levels -/ /-- A function that modifies the level of a Dirichlet character to some multiple of its original level. -/ noncomputable def changeLevel {n m : ℕ} (hm : n ∣ m) : DirichletCharacter R n →* DirichletCharacter R m where toFun ψ := MulChar.ofUnitHom (ψ.toUnitHom.comp (ZMod.unitsMap hm)) map_one' := by ext; simp map_mul' ψ₁ ψ₂ := by ext; simp lemma changeLevel_def {m : ℕ} (hm : n ∣ m) : changeLevel hm χ = MulChar.ofUnitHom (χ.toUnitHom.comp (ZMod.unitsMap hm)) := rfl lemma changeLevel_toUnitHom {m : ℕ} (hm : n ∣ m) : (changeLevel hm χ).toUnitHom = χ.toUnitHom.comp (ZMod.unitsMap hm) := by simp [changeLevel] /-- The `changeLevel` map is injective (except in the degenerate case `m = 0`). -/ lemma changeLevel_injective {m : ℕ} [NeZero m] (hm : n ∣ m) : Function.Injective (changeLevel (R := R) hm) := by intro _ _ h ext1 y obtain ⟨z, rfl⟩ := ZMod.unitsMap_surjective hm y rw [MulChar.ext_iff] at h simpa [changeLevel_def] using h z @[simp] lemma changeLevel_eq_one_iff {m : ℕ} {χ : DirichletCharacter R n} (hm : n ∣ m) [NeZero m] : changeLevel hm χ = 1 ↔ χ = 1 := map_eq_one_iff _ (changeLevel_injective hm) @[simp]
lemma changeLevel_self : changeLevel (dvd_refl n) χ = χ := by simp [changeLevel, ZMod.unitsMap]
Mathlib/NumberTheory/DirichletCharacter/Basic.lean
84
85
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Sébastien Gouëzel, Yury Kudryashov -/ import Mathlib.Dynamics.Ergodic.MeasurePreserving import Mathlib.LinearAlgebra.Determinant import Mathlib.LinearAlgebra.Matrix.Diagonal import Mathlib.LinearAlgebra.Matrix.Transvection import Mathlib.MeasureTheory.Group.LIntegral import Mathlib.MeasureTheory.Integral.Marginal import Mathlib.MeasureTheory.Measure.Stieltjes import Mathlib.MeasureTheory.Measure.Haar.OfBasis /-! # Lebesgue measure on the real line and on `ℝⁿ` We show that the Lebesgue measure on the real line (constructed as a particular case of additive Haar measure on inner product spaces) coincides with the Stieltjes measure associated to the function `x ↦ x`. We deduce properties of this measure on `ℝ`, and then of the product Lebesgue measure on `ℝⁿ`. In particular, we prove that they are translation invariant. We show that, on `ℝⁿ`, a linear map acts on Lebesgue measure by rescaling it through the absolute value of its determinant, in `Real.map_linearMap_volume_pi_eq_smul_volume_pi`. More properties of the Lebesgue measure are deduced from this in `Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean`, where they are proved more generally for any additive Haar measure on a finite-dimensional real vector space. -/ assert_not_exists MeasureTheory.integral noncomputable section open Set Filter MeasureTheory MeasureTheory.Measure TopologicalSpace open ENNReal (ofReal) open scoped ENNReal NNReal Topology /-! ### Definition of the Lebesgue measure and lengths of intervals -/ namespace Real variable {ι : Type*} [Fintype ι] /-- The volume on the real line (as a particular case of the volume on a finite-dimensional inner product space) coincides with the Stieltjes measure coming from the identity function. -/ theorem volume_eq_stieltjes_id : (volume : Measure ℝ) = StieltjesFunction.id.measure := by haveI : IsAddLeftInvariant StieltjesFunction.id.measure := ⟨fun a => Eq.symm <| Real.measure_ext_Ioo_rat fun p q => by simp only [Measure.map_apply (measurable_const_add a) measurableSet_Ioo, sub_sub_sub_cancel_right, StieltjesFunction.measure_Ioo, StieltjesFunction.id_leftLim, StieltjesFunction.id_apply, id, preimage_const_add_Ioo]⟩ have A : StieltjesFunction.id.measure (stdOrthonormalBasis ℝ ℝ).toBasis.parallelepiped = 1 := by change StieltjesFunction.id.measure (parallelepiped (stdOrthonormalBasis ℝ ℝ)) = 1 rcases parallelepiped_orthonormalBasis_one_dim (stdOrthonormalBasis ℝ ℝ) with (H | H) <;> simp only [H, StieltjesFunction.measure_Icc, StieltjesFunction.id_apply, id, tsub_zero, StieltjesFunction.id_leftLim, sub_neg_eq_add, zero_add, ENNReal.ofReal_one] conv_rhs => rw [addHaarMeasure_unique StieltjesFunction.id.measure (stdOrthonormalBasis ℝ ℝ).toBasis.parallelepiped, A] simp only [volume, Basis.addHaar, one_smul] theorem volume_val (s) : volume s = StieltjesFunction.id.measure s := by simp [volume_eq_stieltjes_id] @[simp] theorem volume_Ico {a b : ℝ} : volume (Ico a b) = ofReal (b - a) := by simp [volume_val] @[simp] theorem volume_real_Ico {a b : ℝ} : volume.real (Ico a b) = max (b - a) 0 := by simp [measureReal_def, ENNReal.toReal_ofReal'] theorem volume_real_Ico_of_le {a b : ℝ} (hab : a ≤ b) : volume.real (Ico a b) = b - a := by simp [hab] @[simp] theorem volume_Icc {a b : ℝ} : volume (Icc a b) = ofReal (b - a) := by simp [volume_val] @[simp] theorem volume_real_Icc {a b : ℝ} : volume.real (Icc a b) = max (b - a) 0 := by simp [measureReal_def, ENNReal.toReal_ofReal'] theorem volume_real_Icc_of_le {a b : ℝ} (hab : a ≤ b) : volume.real (Icc a b) = b - a := by simp [hab] @[simp] theorem volume_Ioo {a b : ℝ} : volume (Ioo a b) = ofReal (b - a) := by simp [volume_val] @[simp] theorem volume_real_Ioo {a b : ℝ} : volume.real (Ioo a b) = max (b - a) 0 := by simp [measureReal_def, ENNReal.toReal_ofReal'] theorem volume_real_Ioo_of_le {a b : ℝ} (hab : a ≤ b) : volume.real (Ioo a b) = b - a := by simp [hab] @[simp] theorem volume_Ioc {a b : ℝ} : volume (Ioc a b) = ofReal (b - a) := by simp [volume_val] @[simp] theorem volume_real_Ioc {a b : ℝ} : volume.real (Ioc a b) = max (b - a) 0 := by simp [measureReal_def, ENNReal.toReal_ofReal'] theorem volume_real_Ioc_of_le {a b : ℝ} (hab : a ≤ b) : volume.real (Ioc a b) = b - a := by simp [hab] theorem volume_singleton {a : ℝ} : volume ({a} : Set ℝ) = 0 := by simp [volume_val] theorem volume_univ : volume (univ : Set ℝ) = ∞ := ENNReal.eq_top_of_forall_nnreal_le fun r => calc (r : ℝ≥0∞) = volume (Icc (0 : ℝ) r) := by simp _ ≤ volume univ := measure_mono (subset_univ _) @[simp] theorem volume_ball (a r : ℝ) : volume (Metric.ball a r) = ofReal (2 * r) := by rw [ball_eq_Ioo, volume_Ioo, ← sub_add, add_sub_cancel_left, two_mul] @[simp] theorem volume_real_ball {a r : ℝ} (hr : 0 ≤ r) : volume.real (Metric.ball a r) = 2 * r := by simp [measureReal_def, hr] @[simp] theorem volume_closedBall (a r : ℝ) : volume (Metric.closedBall a r) = ofReal (2 * r) := by rw [closedBall_eq_Icc, volume_Icc, ← sub_add, add_sub_cancel_left, two_mul] @[simp] theorem volume_real_closedBall {a r : ℝ} (hr : 0 ≤ r) : volume.real (Metric.closedBall a r) = 2 * r := by simp [measureReal_def, hr] @[simp] theorem volume_emetric_ball (a : ℝ) (r : ℝ≥0∞) : volume (EMetric.ball a r) = 2 * r := by rcases eq_or_ne r ∞ with (rfl | hr) · rw [Metric.emetric_ball_top, volume_univ, two_mul, _root_.top_add] · lift r to ℝ≥0 using hr rw [Metric.emetric_ball_nnreal, volume_ball, two_mul, ← NNReal.coe_add, ENNReal.ofReal_coe_nnreal, ENNReal.coe_add, two_mul] @[simp] theorem volume_emetric_closedBall (a : ℝ) (r : ℝ≥0∞) : volume (EMetric.closedBall a r) = 2 * r := by rcases eq_or_ne r ∞ with (rfl | hr) · rw [EMetric.closedBall_top, volume_univ, two_mul, _root_.top_add] · lift r to ℝ≥0 using hr rw [Metric.emetric_closedBall_nnreal, volume_closedBall, two_mul, ← NNReal.coe_add, ENNReal.ofReal_coe_nnreal, ENNReal.coe_add, two_mul] instance noAtoms_volume : NoAtoms (volume : Measure ℝ) := ⟨fun _ => volume_singleton⟩ @[simp] theorem volume_interval {a b : ℝ} : volume (uIcc a b) = ofReal |b - a| := by rw [← Icc_min_max, volume_Icc, max_sub_min_eq_abs] @[simp] theorem volume_real_interval {a b : ℝ} : volume.real (uIcc a b) = |b - a| := by simp [measureReal_def] @[simp] theorem volume_Ioi {a : ℝ} : volume (Ioi a) = ∞ := top_unique <| le_of_tendsto' ENNReal.tendsto_nat_nhds_top fun n => calc (n : ℝ≥0∞) = volume (Ioo a (a + n)) := by simp _ ≤ volume (Ioi a) := measure_mono Ioo_subset_Ioi_self @[simp] theorem volume_Ici {a : ℝ} : volume (Ici a) = ∞ := by rw [← measure_congr Ioi_ae_eq_Ici]; simp @[simp] theorem volume_Iio {a : ℝ} : volume (Iio a) = ∞ := top_unique <| le_of_tendsto' ENNReal.tendsto_nat_nhds_top fun n => calc (n : ℝ≥0∞) = volume (Ioo (a - n) a) := by simp _ ≤ volume (Iio a) := measure_mono Ioo_subset_Iio_self @[simp] theorem volume_Iic {a : ℝ} : volume (Iic a) = ∞ := by rw [← measure_congr Iio_ae_eq_Iic]; simp instance locallyFinite_volume : IsLocallyFiniteMeasure (volume : Measure ℝ) := ⟨fun x => ⟨Ioo (x - 1) (x + 1), IsOpen.mem_nhds isOpen_Ioo ⟨sub_lt_self _ zero_lt_one, lt_add_of_pos_right _ zero_lt_one⟩, by simp only [Real.volume_Ioo, ENNReal.ofReal_lt_top]⟩⟩ instance isFiniteMeasure_restrict_Icc (x y : ℝ) : IsFiniteMeasure (volume.restrict (Icc x y)) := ⟨by simp⟩ instance isFiniteMeasure_restrict_Ico (x y : ℝ) : IsFiniteMeasure (volume.restrict (Ico x y)) := ⟨by simp⟩ instance isFiniteMeasure_restrict_Ioc (x y : ℝ) : IsFiniteMeasure (volume.restrict (Ioc x y)) := ⟨by simp⟩ instance isFiniteMeasure_restrict_Ioo (x y : ℝ) : IsFiniteMeasure (volume.restrict (Ioo x y)) := ⟨by simp⟩ theorem volume_le_diam (s : Set ℝ) : volume s ≤ EMetric.diam s := by by_cases hs : Bornology.IsBounded s · rw [Real.ediam_eq hs, ← volume_Icc] exact volume.mono hs.subset_Icc_sInf_sSup · rw [Metric.ediam_of_unbounded hs]; exact le_top theorem _root_.Filter.Eventually.volume_pos_of_nhds_real {p : ℝ → Prop} {a : ℝ} (h : ∀ᶠ x in 𝓝 a, p x) : (0 : ℝ≥0∞) < volume { x | p x } := by rcases h.exists_Ioo_subset with ⟨l, u, hx, hs⟩ refine lt_of_lt_of_le ?_ (measure_mono hs) simpa [-mem_Ioo] using hx.1.trans hx.2 /-! ### Volume of a box in `ℝⁿ` -/ theorem volume_Icc_pi {a b : ι → ℝ} : volume (Icc a b) = ∏ i, ENNReal.ofReal (b i - a i) := by rw [← pi_univ_Icc, volume_pi_pi] simp only [Real.volume_Icc] @[simp] theorem volume_Icc_pi_toReal {a b : ι → ℝ} (h : a ≤ b) : (volume (Icc a b)).toReal = ∏ i, (b i - a i) := by simp only [volume_Icc_pi, ENNReal.toReal_prod, ENNReal.toReal_ofReal (sub_nonneg.2 (h _))] theorem volume_pi_Ioo {a b : ι → ℝ} : volume (pi univ fun i => Ioo (a i) (b i)) = ∏ i, ENNReal.ofReal (b i - a i) := (measure_congr Measure.univ_pi_Ioo_ae_eq_Icc).trans volume_Icc_pi @[simp] theorem volume_pi_Ioo_toReal {a b : ι → ℝ} (h : a ≤ b) : (volume (pi univ fun i => Ioo (a i) (b i))).toReal = ∏ i, (b i - a i) := by simp only [volume_pi_Ioo, ENNReal.toReal_prod, ENNReal.toReal_ofReal (sub_nonneg.2 (h _))] theorem volume_pi_Ioc {a b : ι → ℝ} : volume (pi univ fun i => Ioc (a i) (b i)) = ∏ i, ENNReal.ofReal (b i - a i) := (measure_congr Measure.univ_pi_Ioc_ae_eq_Icc).trans volume_Icc_pi @[simp] theorem volume_pi_Ioc_toReal {a b : ι → ℝ} (h : a ≤ b) : (volume (pi univ fun i => Ioc (a i) (b i))).toReal = ∏ i, (b i - a i) := by simp only [volume_pi_Ioc, ENNReal.toReal_prod, ENNReal.toReal_ofReal (sub_nonneg.2 (h _))] theorem volume_pi_Ico {a b : ι → ℝ} : volume (pi univ fun i => Ico (a i) (b i)) = ∏ i, ENNReal.ofReal (b i - a i) := (measure_congr Measure.univ_pi_Ico_ae_eq_Icc).trans volume_Icc_pi @[simp] theorem volume_pi_Ico_toReal {a b : ι → ℝ} (h : a ≤ b) : (volume (pi univ fun i => Ico (a i) (b i))).toReal = ∏ i, (b i - a i) := by simp only [volume_pi_Ico, ENNReal.toReal_prod, ENNReal.toReal_ofReal (sub_nonneg.2 (h _))] @[simp] nonrec theorem volume_pi_ball (a : ι → ℝ) {r : ℝ} (hr : 0 < r) : volume (Metric.ball a r) = ENNReal.ofReal ((2 * r) ^ Fintype.card ι) := by simp only [MeasureTheory.volume_pi_ball a hr, volume_ball, Finset.prod_const] exact (ENNReal.ofReal_pow (mul_nonneg zero_le_two hr.le) _).symm @[simp] nonrec theorem volume_pi_closedBall (a : ι → ℝ) {r : ℝ} (hr : 0 ≤ r) : volume (Metric.closedBall a r) = ENNReal.ofReal ((2 * r) ^ Fintype.card ι) := by simp only [MeasureTheory.volume_pi_closedBall a hr, volume_closedBall, Finset.prod_const] exact (ENNReal.ofReal_pow (mul_nonneg zero_le_two hr) _).symm theorem volume_pi_le_prod_diam (s : Set (ι → ℝ)) : volume s ≤ ∏ i : ι, EMetric.diam (Function.eval i '' s) := calc volume s ≤ volume (pi univ fun i => closure (Function.eval i '' s)) := volume.mono <| Subset.trans (subset_pi_eval_image univ s) <| pi_mono fun _ _ => subset_closure _ = ∏ i, volume (closure <| Function.eval i '' s) := volume_pi_pi _ _ ≤ ∏ i : ι, EMetric.diam (Function.eval i '' s) := Finset.prod_le_prod' fun _ _ => (volume_le_diam _).trans_eq (EMetric.diam_closure _) theorem volume_pi_le_diam_pow (s : Set (ι → ℝ)) : volume s ≤ EMetric.diam s ^ Fintype.card ι := calc volume s ≤ ∏ i : ι, EMetric.diam (Function.eval i '' s) := volume_pi_le_prod_diam s _ ≤ ∏ _i : ι, (1 : ℝ≥0) * EMetric.diam s := (Finset.prod_le_prod' fun i _ => (LipschitzWith.eval i).ediam_image_le s) _ = EMetric.diam s ^ Fintype.card ι := by simp only [ENNReal.coe_one, one_mul, Finset.prod_const, Fintype.card] /-! ### Images of the Lebesgue measure under multiplication in ℝ -/ theorem smul_map_volume_mul_left {a : ℝ} (h : a ≠ 0) : ENNReal.ofReal |a| • Measure.map (a * ·) volume = volume := by refine (Real.measure_ext_Ioo_rat fun p q => ?_).symm rcases lt_or_gt_of_ne h with h | h · simp only [Real.volume_Ioo, Measure.smul_apply, ← ENNReal.ofReal_mul (le_of_lt <| neg_pos.2 h), Measure.map_apply (measurable_const_mul a) measurableSet_Ioo, neg_sub_neg, neg_mul, preimage_const_mul_Ioo_of_neg _ _ h, abs_of_neg h, mul_sub, smul_eq_mul, mul_div_cancel₀ _ (ne_of_lt h)] · simp only [Real.volume_Ioo, Measure.smul_apply, ← ENNReal.ofReal_mul (le_of_lt h), Measure.map_apply (measurable_const_mul a) measurableSet_Ioo, preimage_const_mul_Ioo _ _ h, abs_of_pos h, mul_sub, mul_div_cancel₀ _ (ne_of_gt h), smul_eq_mul] theorem map_volume_mul_left {a : ℝ} (h : a ≠ 0) : Measure.map (a * ·) volume = ENNReal.ofReal |a⁻¹| • volume := by conv_rhs => rw [← Real.smul_map_volume_mul_left h, smul_smul, ← ENNReal.ofReal_mul (abs_nonneg _), ← abs_mul, inv_mul_cancel₀ h, abs_one, ENNReal.ofReal_one, one_smul] @[simp] theorem volume_preimage_mul_left {a : ℝ} (h : a ≠ 0) (s : Set ℝ) : volume ((a * ·) ⁻¹' s) = ENNReal.ofReal (abs a⁻¹) * volume s := calc volume ((a * ·) ⁻¹' s) = Measure.map (a * ·) volume s := ((Homeomorph.mulLeft₀ a h).toMeasurableEquiv.map_apply s).symm _ = ENNReal.ofReal (abs a⁻¹) * volume s := by rw [map_volume_mul_left h]; rfl theorem smul_map_volume_mul_right {a : ℝ} (h : a ≠ 0) : ENNReal.ofReal |a| • Measure.map (· * a) volume = volume := by simpa only [mul_comm] using Real.smul_map_volume_mul_left h theorem map_volume_mul_right {a : ℝ} (h : a ≠ 0) : Measure.map (· * a) volume = ENNReal.ofReal |a⁻¹| • volume := by simpa only [mul_comm] using Real.map_volume_mul_left h @[simp] theorem volume_preimage_mul_right {a : ℝ} (h : a ≠ 0) (s : Set ℝ) : volume ((· * a) ⁻¹' s) = ENNReal.ofReal (abs a⁻¹) * volume s := calc volume ((· * a) ⁻¹' s) = Measure.map (· * a) volume s := ((Homeomorph.mulRight₀ a h).toMeasurableEquiv.map_apply s).symm _ = ENNReal.ofReal (abs a⁻¹) * volume s := by rw [map_volume_mul_right h]; rfl /-! ### Images of the Lebesgue measure under translation/linear maps in ℝⁿ -/ open Matrix /-- A diagonal matrix rescales Lebesgue according to its determinant. This is a special case of `Real.map_matrix_volume_pi_eq_smul_volume_pi`, that one should use instead (and whose proof uses this particular case). -/ theorem smul_map_diagonal_volume_pi [DecidableEq ι] {D : ι → ℝ} (h : det (diagonal D) ≠ 0) : ENNReal.ofReal (abs (det (diagonal D))) • Measure.map (toLin' (diagonal D)) volume = volume := by refine (Measure.pi_eq fun s hs => ?_).symm simp only [det_diagonal, Measure.coe_smul, Algebra.id.smul_eq_mul, Pi.smul_apply] rw [Measure.map_apply _ (MeasurableSet.univ_pi hs)] swap; · exact Continuous.measurable (LinearMap.continuous_on_pi _) have : (Matrix.toLin' (diagonal D) ⁻¹' Set.pi Set.univ fun i : ι => s i) = Set.pi Set.univ fun i : ι => (D i * ·) ⁻¹' s i := by ext f simp only [LinearMap.coe_proj, Algebra.id.smul_eq_mul, LinearMap.smul_apply, mem_univ_pi, mem_preimage, LinearMap.pi_apply, diagonal_toLin'] have B : ∀ i, ofReal (abs (D i)) * volume ((D i * ·) ⁻¹' s i) = volume (s i) := by intro i have A : D i ≠ 0 := by simp only [det_diagonal, Ne] at h exact Finset.prod_ne_zero_iff.1 h i (Finset.mem_univ i) rw [volume_preimage_mul_left A, ← mul_assoc, ← ENNReal.ofReal_mul (abs_nonneg _), ← abs_mul, mul_inv_cancel₀ A, abs_one, ENNReal.ofReal_one, one_mul] rw [this, volume_pi_pi, Finset.abs_prod, ENNReal.ofReal_prod_of_nonneg fun i _ => abs_nonneg (D i), ← Finset.prod_mul_distrib] simp only [B] /-- A transvection preserves Lebesgue measure. -/ theorem volume_preserving_transvectionStruct [DecidableEq ι] (t : TransvectionStruct ι ℝ) : MeasurePreserving (toLin' t.toMatrix) := by /- We use `lmarginal` to conveniently use Fubini's theorem. Along the coordinate where there is a shearing, it acts like a translation, and therefore preserves Lebesgue. -/ have ht : Measurable (toLin' t.toMatrix) := (toLin' t.toMatrix).continuous_of_finiteDimensional.measurable refine ⟨ht, ?_⟩ refine (pi_eq fun s hs ↦ ?_).symm have h2s : MeasurableSet (univ.pi s) := .pi countable_univ fun i _ ↦ hs i simp_rw [← pi_pi, ← lintegral_indicator_one h2s] rw [lintegral_map (measurable_one.indicator h2s) ht, volume_pi] refine lintegral_eq_of_lmarginal_eq {t.i} ((measurable_one.indicator h2s).comp ht) (measurable_one.indicator h2s) ?_ simp_rw [lmarginal_singleton] ext x cases t with | mk t_i t_j t_hij t_c => simp [transvection, mulVec_stdBasisMatrix, t_hij.symm, ← Function.update_add, lintegral_add_right_eq_self fun xᵢ ↦ indicator (univ.pi s) 1 (Function.update x t_i xᵢ)] /-- Any invertible matrix rescales Lebesgue measure through the absolute value of its determinant. -/ theorem map_matrix_volume_pi_eq_smul_volume_pi [DecidableEq ι] {M : Matrix ι ι ℝ} (hM : det M ≠ 0) : Measure.map (toLin' M) volume = ENNReal.ofReal (abs (det M)⁻¹) • volume := by -- This follows from the cases we have already proved, of diagonal matrices and transvections, -- as these matrices generate all invertible matrices. apply diagonal_transvection_induction_of_det_ne_zero _ M hM · intro D hD conv_rhs => rw [← smul_map_diagonal_volume_pi hD] rw [smul_smul, ← ENNReal.ofReal_mul (abs_nonneg _), ← abs_mul, inv_mul_cancel₀ hD, abs_one, ENNReal.ofReal_one, one_smul] · intro t simp_rw [Matrix.TransvectionStruct.det, _root_.inv_one, abs_one, ENNReal.ofReal_one, one_smul, (volume_preserving_transvectionStruct _).map_eq] · intro A B _ _ IHA IHB rw [toLin'_mul, det_mul, LinearMap.coe_comp, ← Measure.map_map, IHB, Measure.map_smul, IHA, smul_smul, ← ENNReal.ofReal_mul (abs_nonneg _), ← abs_mul, mul_comm, mul_inv] · apply Continuous.measurable apply LinearMap.continuous_on_pi · apply Continuous.measurable apply LinearMap.continuous_on_pi /-- Any invertible linear map rescales Lebesgue measure through the absolute value of its determinant. -/ theorem map_linearMap_volume_pi_eq_smul_volume_pi {f : (ι → ℝ) →ₗ[ℝ] ι → ℝ} (hf : LinearMap.det f ≠ 0) : Measure.map f volume = ENNReal.ofReal (abs (LinearMap.det f)⁻¹) • volume := by classical -- this is deduced from the matrix case let M := LinearMap.toMatrix' f have A : LinearMap.det f = det M := by simp only [M, LinearMap.det_toMatrix'] have B : f = toLin' M := by simp only [M, toLin'_toMatrix'] rw [A, B] apply map_matrix_volume_pi_eq_smul_volume_pi rwa [A] at hf end Real section regionBetween variable {α : Type*} /-- The region between two real-valued functions on an arbitrary set. -/ def regionBetween (f g : α → ℝ) (s : Set α) : Set (α × ℝ) := { p : α × ℝ | p.1 ∈ s ∧ p.2 ∈ Ioo (f p.1) (g p.1) } theorem regionBetween_subset (f g : α → ℝ) (s : Set α) : regionBetween f g s ⊆ s ×ˢ univ := by simpa only [prod_univ, regionBetween, Set.preimage, setOf_subset_setOf] using fun a => And.left variable [MeasurableSpace α] {μ : Measure α} {f g : α → ℝ} {s : Set α} /-- The region between two measurable functions on a measurable set is measurable. -/ theorem measurableSet_regionBetween (hf : Measurable f) (hg : Measurable g) (hs : MeasurableSet s) : MeasurableSet (regionBetween f g s) := by dsimp only [regionBetween, Ioo, mem_setOf_eq, setOf_and] refine MeasurableSet.inter ?_ ((measurableSet_lt (hf.comp measurable_fst) measurable_snd).inter (measurableSet_lt measurable_snd (hg.comp measurable_fst))) exact measurable_fst hs /-- The region between two measurable functions on a measurable set is measurable; a version for the region together with the graph of the upper function. -/ theorem measurableSet_region_between_oc (hf : Measurable f) (hg : Measurable g) (hs : MeasurableSet s) : MeasurableSet { p : α × ℝ | p.fst ∈ s ∧ p.snd ∈ Ioc (f p.fst) (g p.fst) } := by dsimp only [regionBetween, Ioc, mem_setOf_eq, setOf_and] refine MeasurableSet.inter ?_ ((measurableSet_lt (hf.comp measurable_fst) measurable_snd).inter (measurableSet_le measurable_snd (hg.comp measurable_fst))) exact measurable_fst hs /-- The region between two measurable functions on a measurable set is measurable; a version for the region together with the graph of the lower function. -/ theorem measurableSet_region_between_co (hf : Measurable f) (hg : Measurable g) (hs : MeasurableSet s) : MeasurableSet { p : α × ℝ | p.fst ∈ s ∧ p.snd ∈ Ico (f p.fst) (g p.fst) } := by dsimp only [regionBetween, Ico, mem_setOf_eq, setOf_and] refine MeasurableSet.inter ?_ ((measurableSet_le (hf.comp measurable_fst) measurable_snd).inter (measurableSet_lt measurable_snd (hg.comp measurable_fst))) exact measurable_fst hs /-- The region between two measurable functions on a measurable set is measurable; a version for the region together with the graphs of both functions. -/ theorem measurableSet_region_between_cc (hf : Measurable f) (hg : Measurable g) (hs : MeasurableSet s) : MeasurableSet { p : α × ℝ | p.fst ∈ s ∧ p.snd ∈ Icc (f p.fst) (g p.fst) } := by dsimp only [regionBetween, Icc, mem_setOf_eq, setOf_and] refine MeasurableSet.inter ?_ ((measurableSet_le (hf.comp measurable_fst) measurable_snd).inter (measurableSet_le measurable_snd (hg.comp measurable_fst))) exact measurable_fst hs /-- The graph of a measurable function is a measurable set. -/ theorem measurableSet_graph (hf : Measurable f) : MeasurableSet { p : α × ℝ | p.snd = f p.fst } := by simpa using measurableSet_region_between_cc hf hf MeasurableSet.univ theorem volume_regionBetween_eq_lintegral' (hf : Measurable f) (hg : Measurable g)
(hs : MeasurableSet s) : μ.prod volume (regionBetween f g s) = ∫⁻ y in s, ENNReal.ofReal ((g - f) y) ∂μ := by classical rw [Measure.prod_apply] · have h : (fun x => volume { a | x ∈ s ∧ a ∈ Ioo (f x) (g x) }) = s.indicator fun x => ENNReal.ofReal (g x - f x) := by funext x rw [indicator_apply]
Mathlib/MeasureTheory/Measure/Lebesgue/Basic.lean
494
502
/- Copyright (c) 2020 Johan Commelin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin, Robert Y. Lewis -/ import Mathlib.RingTheory.WittVector.StructurePolynomial /-! # Witt vectors In this file we define the type of `p`-typical Witt vectors and ring operations on it. The ring axioms are verified in `Mathlib/RingTheory/WittVector/Basic.lean`. For a fixed commutative ring `R` and prime `p`, a Witt vector `x : 𝕎 R` is an infinite sequence `ℕ → R` of elements of `R`. However, the ring operations `+` and `*` are not defined in the obvious component-wise way. Instead, these operations are defined via certain polynomials using the machinery in `Mathlib/RingTheory/WittVector/StructurePolynomial.lean`. The `n`th value of the sum of two Witt vectors can depend on the `0`-th through `n`th values of the summands. This effectively simulates a “carrying” operation. ## Main definitions * `WittVector p R`: the type of `p`-typical Witt vectors with coefficients in `R`. * `WittVector.coeff x n`: projects the `n`th value of the Witt vector `x`. ## Notation We use notation `𝕎 R`, entered `\bbW`, for the Witt vectors over `R`. ## References * [Hazewinkel, *Witt Vectors*][Haze09] * [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21] -/ noncomputable section /-- `WittVector p R` is the ring of `p`-typical Witt vectors over the commutative ring `R`, where `p` is a prime number. If `p` is invertible in `R`, this ring is isomorphic to `ℕ → R` (the product of `ℕ` copies of `R`). If `R` is a ring of characteristic `p`, then `WittVector p R` is a ring of characteristic `0`. The canonical example is `WittVector p (ZMod p)`, which is isomorphic to the `p`-adic integers `ℤ_[p]`. -/ structure WittVector (p : ℕ) (R : Type*) where mk' :: /-- `x.coeff n` is the `n`th coefficient of the Witt vector `x`. This concept does not have a standard name in the literature. -/ coeff : ℕ → R -- Porting note: added to make the `p` argument explicit /-- Construct a Witt vector `mk p x : 𝕎 R` from a sequence `x` of elements of `R`. -/ def WittVector.mk (p : ℕ) {R : Type*} (coeff : ℕ → R) : WittVector p R := mk' coeff variable {p : ℕ} /- We cannot make this `localized` notation, because the `p` on the RHS doesn't occur on the left Hiding the `p` in the notation is very convenient, so we opt for repeating the `local notation` in other files that use Witt vectors. -/ local notation "𝕎" => WittVector p -- type as `\bbW` namespace WittVector variable {R : Type*} @[ext] theorem ext {x y : 𝕎 R} (h : ∀ n, x.coeff n = y.coeff n) : x = y := by cases x cases y simp only at h simp [funext_iff, h] variable (p) theorem coeff_mk (x : ℕ → R) : (mk p x).coeff = x := rfl /- These instances are not needed for the rest of the development, but it is interesting to establish early on that `WittVector p` is a lawful functor. -/ instance : Functor (WittVector p) where map f v := mk p (f ∘ v.coeff) mapConst a _ := mk p fun _ => a instance : LawfulFunctor (WittVector p) where map_const := rfl -- Porting note: no longer needs to deconstruct `v` to conclude `{coeff := v.coeff} = v` id_map _ := rfl comp_map _ _ _ := rfl variable [hp : Fact p.Prime] [CommRing R] open MvPolynomial section RingOperations /-- The polynomials used for defining the element `0` of the ring of Witt vectors. -/ def wittZero : ℕ → MvPolynomial (Fin 0 × ℕ) ℤ := wittStructureInt p 0 /-- The polynomials used for defining the element `1` of the ring of Witt vectors. -/ def wittOne : ℕ → MvPolynomial (Fin 0 × ℕ) ℤ := wittStructureInt p 1 /-- The polynomials used for defining the addition of the ring of Witt vectors. -/ def wittAdd : ℕ → MvPolynomial (Fin 2 × ℕ) ℤ := wittStructureInt p (X 0 + X 1) /-- The polynomials used for defining repeated addition of the ring of Witt vectors. -/ def wittNSMul (n : ℕ) : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ := wittStructureInt p (n • X (0 : (Fin 1))) /-- The polynomials used for defining repeated addition of the ring of Witt vectors. -/ def wittZSMul (n : ℤ) : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ := wittStructureInt p (n • X (0 : (Fin 1))) /-- The polynomials used for describing the subtraction of the ring of Witt vectors. -/ def wittSub : ℕ → MvPolynomial (Fin 2 × ℕ) ℤ := wittStructureInt p (X 0 - X 1) /-- The polynomials used for defining the multiplication of the ring of Witt vectors. -/ def wittMul : ℕ → MvPolynomial (Fin 2 × ℕ) ℤ := wittStructureInt p (X 0 * X 1) /-- The polynomials used for defining the negation of the ring of Witt vectors. -/ def wittNeg : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ := wittStructureInt p (-X 0) /-- The polynomials used for defining repeated addition of the ring of Witt vectors. -/ def wittPow (n : ℕ) : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ := wittStructureInt p (X 0 ^ n) variable {p} /-- An auxiliary definition used in `WittVector.eval`. Evaluates a polynomial whose variables come from the disjoint union of `k` copies of `ℕ`, with a curried evaluation `x`. This can be defined more generally but we use only a specific instance here. -/ def peval {k : ℕ} (φ : MvPolynomial (Fin k × ℕ) ℤ) (x : Fin k → ℕ → R) : R := aeval (Function.uncurry x) φ /-- Let `φ` be a family of polynomials, indexed by natural numbers, whose variables come from the disjoint union of `k` copies of `ℕ`, and let `xᵢ` be a Witt vector for `0 ≤ i < k`. `eval φ x` evaluates `φ` mapping the variable `X_(i, n)` to the `n`th coefficient of `xᵢ`. Instantiating `φ` with certain polynomials defined in `Mathlib/RingTheory/WittVector/StructurePolynomial.lean` establishes the ring operations on `𝕎 R`. For example, `WittVector.wittAdd` is such a `φ` with `k = 2`; evaluating this at `(x₀, x₁)` gives us the sum of two Witt vectors `x₀ + x₁`. -/ def eval {k : ℕ} (φ : ℕ → MvPolynomial (Fin k × ℕ) ℤ) (x : Fin k → 𝕎 R) : 𝕎 R := mk p fun n => peval (φ n) fun i => (x i).coeff instance : Zero (𝕎 R) := ⟨eval (wittZero p) ![]⟩ instance : Inhabited (𝕎 R) := ⟨0⟩ instance : One (𝕎 R) := ⟨eval (wittOne p) ![]⟩ instance : Add (𝕎 R) := ⟨fun x y => eval (wittAdd p) ![x, y]⟩ instance : Sub (𝕎 R) := ⟨fun x y => eval (wittSub p) ![x, y]⟩ instance hasNatScalar : SMul ℕ (𝕎 R) := ⟨fun n x => eval (wittNSMul p n) ![x]⟩ instance hasIntScalar : SMul ℤ (𝕎 R) := ⟨fun n x => eval (wittZSMul p n) ![x]⟩ instance : Mul (𝕎 R) := ⟨fun x y => eval (wittMul p) ![x, y]⟩ instance : Neg (𝕎 R) := ⟨fun x => eval (wittNeg p) ![x]⟩ instance hasNatPow : Pow (𝕎 R) ℕ := ⟨fun x n => eval (wittPow p n) ![x]⟩ instance : NatCast (𝕎 R) := ⟨Nat.unaryCast⟩ instance : IntCast (𝕎 R) := ⟨Int.castDef⟩ end RingOperations section WittStructureSimplifications @[simp] theorem wittZero_eq_zero (n : ℕ) : wittZero p n = 0 := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittZero, wittStructureRat, bind₁, aeval_zero', constantCoeff_xInTermsOfW, map_zero, map_wittStructureInt] @[simp] theorem wittOne_zero_eq_one : wittOne p 0 = 1 := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittOne, wittStructureRat, xInTermsOfW_zero, map_one, bind₁_X_right, map_wittStructureInt] @[simp] theorem wittOne_pos_eq_zero (n : ℕ) (hn : 0 < n) : wittOne p n = 0 := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittOne, wittStructureRat, RingHom.map_zero, map_one, RingHom.map_one, map_wittStructureInt] induction n using Nat.strong_induction_on with | h n IH => ?_ rw [xInTermsOfW_eq] simp only [map_mul, map_sub, map_sum, map_pow, bind₁_X_right, bind₁_C_right] rw [sub_mul, one_mul] rw [Finset.sum_eq_single 0] · simp only [invOf_eq_inv, one_mul, inv_pow, tsub_zero, RingHom.map_one, pow_zero] simp only [one_pow, one_mul, xInTermsOfW_zero, sub_self, bind₁_X_right] · intro i hin hi0 rw [Finset.mem_range] at hin rw [IH _ hin (Nat.pos_of_ne_zero hi0), zero_pow (pow_ne_zero _ hp.1.ne_zero), mul_zero] · rw [Finset.mem_range]; intro; contradiction @[simp] theorem wittAdd_zero : wittAdd p 0 = X (0, 0) + X (1, 0) := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittAdd, wittStructureRat, map_add, rename_X, xInTermsOfW_zero, map_X, wittPolynomial_zero, bind₁_X_right, map_wittStructureInt] @[simp] theorem wittSub_zero : wittSub p 0 = X (0, 0) - X (1, 0) := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittSub, wittStructureRat, map_sub, rename_X, xInTermsOfW_zero, map_X, wittPolynomial_zero, bind₁_X_right, map_wittStructureInt] @[simp] theorem wittMul_zero : wittMul p 0 = X (0, 0) * X (1, 0) := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittMul, wittStructureRat, rename_X, xInTermsOfW_zero, map_X, wittPolynomial_zero, map_mul, bind₁_X_right, map_wittStructureInt] @[simp] theorem wittNeg_zero : wittNeg p 0 = -X (0, 0) := by apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective simp only [wittNeg, wittStructureRat, rename_X, xInTermsOfW_zero, map_X, wittPolynomial_zero, map_neg, bind₁_X_right, map_wittStructureInt] @[simp] theorem constantCoeff_wittAdd (n : ℕ) : constantCoeff (wittAdd p n) = 0 := by apply constantCoeff_wittStructureInt p _ _ n simp only [add_zero, RingHom.map_add, constantCoeff_X] @[simp] theorem constantCoeff_wittSub (n : ℕ) : constantCoeff (wittSub p n) = 0 := by apply constantCoeff_wittStructureInt p _ _ n simp only [sub_zero, RingHom.map_sub, constantCoeff_X] @[simp] theorem constantCoeff_wittMul (n : ℕ) : constantCoeff (wittMul p n) = 0 := by apply constantCoeff_wittStructureInt p _ _ n simp only [mul_zero, RingHom.map_mul, constantCoeff_X] @[simp] theorem constantCoeff_wittNeg (n : ℕ) : constantCoeff (wittNeg p n) = 0 := by apply constantCoeff_wittStructureInt p _ _ n simp only [neg_zero, RingHom.map_neg, constantCoeff_X] @[simp] theorem constantCoeff_wittNSMul (m : ℕ) (n : ℕ) : constantCoeff (wittNSMul p m n) = 0 := by apply constantCoeff_wittStructureInt p _ _ n simp only [smul_zero, map_nsmul, constantCoeff_X] @[simp] theorem constantCoeff_wittZSMul (z : ℤ) (n : ℕ) : constantCoeff (wittZSMul p z n) = 0 := by apply constantCoeff_wittStructureInt p _ _ n simp only [smul_zero, map_zsmul, constantCoeff_X] end WittStructureSimplifications section Coeff variable (R) @[simp] theorem zero_coeff (n : ℕ) : (0 : 𝕎 R).coeff n = 0 := show (aeval _ (wittZero p n) : R) = 0 by simp only [wittZero_eq_zero, map_zero] @[simp] theorem one_coeff_zero : (1 : 𝕎 R).coeff 0 = 1 := show (aeval _ (wittOne p 0) : R) = 1 by simp only [wittOne_zero_eq_one, map_one] @[simp] theorem one_coeff_eq_of_pos (n : ℕ) (hn : 0 < n) : coeff (1 : 𝕎 R) n = 0 := show (aeval _ (wittOne p n) : R) = 0 by simp only [hn, wittOne_pos_eq_zero, map_zero] variable {p R} @[simp] theorem v2_coeff {p' R'} (x y : WittVector p' R') (i : Fin 2) : (![x, y] i).coeff = ![x.coeff, y.coeff] i := by fin_cases i <;> simp -- Porting note: the lemmas below needed `coeff_mk` added to the `simp` calls theorem add_coeff (x y : 𝕎 R) (n : ℕ) :
(x + y).coeff n = peval (wittAdd p n) ![x.coeff, y.coeff] := by simp [(· + ·), Add.add, eval, coeff_mk]
Mathlib/RingTheory/WittVector/Defs.lean
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/- Copyright (c) 2018 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau, Mario Carneiro -/ import Mathlib.Algebra.Module.Submodule.Equiv import Mathlib.Algebra.NoZeroSMulDivisors.Basic /-! # Basics on bilinear maps This file provides basics on bilinear maps. The most general form considered are maps that are semilinear in both arguments. They are of type `M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P`, where `M` and `N` are modules over `R` and `S` respectively, `P` is a module over both `R₂` and `S₂` with commuting actions, and `ρ₁₂ : R →+* R₂` and `σ₁₂ : S →+* S₂`. ## Main declarations * `LinearMap.mk₂`: a constructor for bilinear maps, taking an unbundled function together with proof witnesses of bilinearity * `LinearMap.flip`: turns a bilinear map `M × N → P` into `N × M → P` * `LinearMap.lflip`: given a linear map from `M` to `N →ₗ[R] P`, i.e., a bilinear map `M → N → P`, change the order of variables and get a linear map from `N` to `M →ₗ[R] P`. * `LinearMap.lcomp`: composition of a given linear map `M → N` with a linear map `N → P` as a linear map from `Nₗ →ₗ[R] Pₗ` to `M →ₗ[R] Pₗ` * `LinearMap.llcomp`: composition of linear maps as a bilinear map from `(M →ₗ[R] N) × (N →ₗ[R] P)` to `M →ₗ[R] P` * `LinearMap.compl₂`: composition of a linear map `Q → N` and a bilinear map `M → N → P` to form a bilinear map `M → Q → P`. * `LinearMap.compr₂`: composition of a linear map `P → Q` and a bilinear map `M → N → P` to form a bilinear map `M → N → Q`. * `LinearMap.lsmul`: scalar multiplication as a bilinear map `R × M → M` ## Tags bilinear -/ open Function namespace LinearMap section Semiring -- the `ₗ` subscript variables are for special cases about linear (as opposed to semilinear) maps variable {R : Type*} [Semiring R] {S : Type*} [Semiring S] variable {R₂ : Type*} [Semiring R₂] {S₂ : Type*} [Semiring S₂] variable {M : Type*} {N : Type*} {P : Type*} variable {M₂ : Type*} {N₂ : Type*} {P₂ : Type*} variable {Pₗ : Type*} variable {M' : Type*} {P' : Type*} variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P] variable [AddCommMonoid M₂] [AddCommMonoid N₂] [AddCommMonoid P₂] [AddCommMonoid Pₗ] variable [AddCommGroup M'] [AddCommGroup P'] variable [Module R M] [Module S N] [Module R₂ P] [Module S₂ P] variable [Module R M₂] [Module S N₂] [Module R P₂] [Module S₂ P₂] variable [Module R Pₗ] [Module S Pₗ] variable [Module R M'] [Module R₂ P'] [Module S₂ P'] variable [SMulCommClass S₂ R₂ P] [SMulCommClass S R Pₗ] [SMulCommClass S₂ R₂ P'] variable [SMulCommClass S₂ R P₂] variable {ρ₁₂ : R →+* R₂} {σ₁₂ : S →+* S₂} variable (ρ₁₂ σ₁₂) /-- Create a bilinear map from a function that is semilinear in each component. See `mk₂'` and `mk₂` for the linear case. -/ def mk₂'ₛₗ (f : M → N → P) (H1 : ∀ m₁ m₂ n, f (m₁ + m₂) n = f m₁ n + f m₂ n) (H2 : ∀ (c : R) (m n), f (c • m) n = ρ₁₂ c • f m n) (H3 : ∀ m n₁ n₂, f m (n₁ + n₂) = f m n₁ + f m n₂) (H4 : ∀ (c : S) (m n), f m (c • n) = σ₁₂ c • f m n) : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P where toFun m := { toFun := f m map_add' := H3 m map_smul' := fun c => H4 c m } map_add' m₁ m₂ := LinearMap.ext <| H1 m₁ m₂ map_smul' c m := LinearMap.ext <| H2 c m variable {ρ₁₂ σ₁₂} @[simp] theorem mk₂'ₛₗ_apply (f : M → N → P) {H1 H2 H3 H4} (m : M) (n : N) : (mk₂'ₛₗ ρ₁₂ σ₁₂ f H1 H2 H3 H4 : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) m n = f m n := rfl variable (R S) /-- Create a bilinear map from a function that is linear in each component. See `mk₂` for the special case where both arguments come from modules over the same ring. -/ def mk₂' (f : M → N → Pₗ) (H1 : ∀ m₁ m₂ n, f (m₁ + m₂) n = f m₁ n + f m₂ n) (H2 : ∀ (c : R) (m n), f (c • m) n = c • f m n) (H3 : ∀ m n₁ n₂, f m (n₁ + n₂) = f m n₁ + f m n₂) (H4 : ∀ (c : S) (m n), f m (c • n) = c • f m n) : M →ₗ[R] N →ₗ[S] Pₗ := mk₂'ₛₗ (RingHom.id R) (RingHom.id S) f H1 H2 H3 H4 variable {R S} @[simp] theorem mk₂'_apply (f : M → N → Pₗ) {H1 H2 H3 H4} (m : M) (n : N) : (mk₂' R S f H1 H2 H3 H4 : M →ₗ[R] N →ₗ[S] Pₗ) m n = f m n := rfl theorem ext₂ {f g : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P} (H : ∀ m n, f m n = g m n) : f = g := LinearMap.ext fun m => LinearMap.ext fun n => H m n theorem congr_fun₂ {f g : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P} (h : f = g) (x y) : f x y = g x y := LinearMap.congr_fun (LinearMap.congr_fun h x) y theorem ext_iff₂ {f g : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P} : f = g ↔ ∀ m n, f m n = g m n := ⟨congr_fun₂, ext₂⟩ section attribute [local instance] SMulCommClass.symm /-- Given a linear map from `M` to linear maps from `N` to `P`, i.e., a bilinear map from `M × N` to `P`, change the order of variables and get a linear map from `N` to linear maps from `M` to `P`. -/ def flip (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) : N →ₛₗ[σ₁₂] M →ₛₗ[ρ₁₂] P := mk₂'ₛₗ σ₁₂ ρ₁₂ (fun n m => f m n) (fun _ _ m => (f m).map_add _ _) (fun _ _ m => (f m).map_smulₛₗ _ _) (fun n m₁ m₂ => by simp only [map_add, add_apply]) -- Note: https://github.com/leanprover-community/mathlib4/pull/8386 changed `map_smulₛₗ` into `map_smulₛₗ _`. -- It looks like we now run out of assignable metavariables. (fun c n m => by simp only [map_smulₛₗ _, smul_apply]) end @[simp] theorem flip_apply (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (m : M) (n : N) : flip f n m = f m n := rfl attribute [local instance] SMulCommClass.symm @[simp] theorem flip_flip (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) : f.flip.flip = f := LinearMap.ext₂ fun _x _y => (f.flip.flip_apply _ _).trans (f.flip_apply _ _) theorem flip_inj {f g : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P} (H : flip f = flip g) : f = g := ext₂ fun m n => show flip f n m = flip g n m by rw [H] theorem map_zero₂ (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (y) : f 0 y = 0 := (flip f y).map_zero theorem map_neg₂ (f : M' →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P') (x y) : f (-x) y = -f x y := (flip f y).map_neg _ theorem map_sub₂ (f : M' →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P') (x y z) : f (x - y) z = f x z - f y z := (flip f z).map_sub _ _ theorem map_add₂ (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (x₁ x₂ y) : f (x₁ + x₂) y = f x₁ y + f x₂ y := (flip f y).map_add _ _ theorem map_smul₂ (f : M₂ →ₗ[R] N₂ →ₛₗ[σ₁₂] P₂) (r : R) (x y) : f (r • x) y = r • f x y := (flip f y).map_smul _ _ theorem map_smulₛₗ₂ (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (r : R) (x y) : f (r • x) y = ρ₁₂ r • f x y := (flip f y).map_smulₛₗ _ _ theorem map_sum₂ {ι : Type*} (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (t : Finset ι) (x : ι → M) (y) : f (∑ i ∈ t, x i) y = ∑ i ∈ t, f (x i) y := _root_.map_sum (flip f y) _ _ /-- Restricting a bilinear map in the second entry -/ def domRestrict₂ (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (q : Submodule S N) : M →ₛₗ[ρ₁₂] q →ₛₗ[σ₁₂] P where toFun m := (f m).domRestrict q map_add' m₁ m₂ := LinearMap.ext fun _ => by simp only [map_add, domRestrict_apply, add_apply] map_smul' c m := LinearMap.ext fun _ => by simp only [f.map_smulₛₗ, domRestrict_apply, smul_apply] theorem domRestrict₂_apply (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (q : Submodule S N) (x : M) (y : q) : f.domRestrict₂ q x y = f x y := rfl /-- Restricting a bilinear map in both components -/ def domRestrict₁₂ (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (p : Submodule R M) (q : Submodule S N) : p →ₛₗ[ρ₁₂] q →ₛₗ[σ₁₂] P := (f.domRestrict p).domRestrict₂ q theorem domRestrict₁₂_apply (f : M →ₛₗ[ρ₁₂] N →ₛₗ[σ₁₂] P) (p : Submodule R M) (q : Submodule S N) (x : p) (y : q) : f.domRestrict₁₂ p q x y = f x y := rfl section restrictScalars variable (R' S' : Type*) variable [Semiring R'] [Semiring S'] [Module R' M] [Module S' N] [Module R' Pₗ] [Module S' Pₗ] variable [SMulCommClass S' R' Pₗ] variable [SMul S' S] [IsScalarTower S' S N] [IsScalarTower S' S Pₗ] variable [SMul R' R] [IsScalarTower R' R M] [IsScalarTower R' R Pₗ] /-- If `B : M → N → Pₗ` is `R`-`S` bilinear and `R'` and `S'` are compatible scalar multiplications, then the restriction of scalars is a `R'`-`S'` bilinear map. -/ @[simps!] def restrictScalars₁₂ (B : M →ₗ[R] N →ₗ[S] Pₗ) : M →ₗ[R'] N →ₗ[S'] Pₗ := LinearMap.mk₂' R' S' (B · ·) B.map_add₂ (fun r' m _ ↦ by dsimp only rw [← smul_one_smul R r' m, map_smul₂, smul_one_smul]) (fun _ ↦ map_add _) (fun _ x ↦ (B x).map_smul_of_tower _) theorem restrictScalars₁₂_injective : Function.Injective (LinearMap.restrictScalars₁₂ R' S' : (M →ₗ[R] N →ₗ[S] Pₗ) → (M →ₗ[R'] N →ₗ[S'] Pₗ)) := fun _ _ h ↦ ext₂ (congr_fun₂ h :) @[simp] theorem restrictScalars₁₂_inj {B B' : M →ₗ[R] N →ₗ[S] Pₗ} : B.restrictScalars₁₂ R' S' = B'.restrictScalars₁₂ R' S' ↔ B = B' := (restrictScalars₁₂_injective R' S').eq_iff end restrictScalars end Semiring section CommSemiring variable {R : Type*} [CommSemiring R] {R₂ : Type*} [CommSemiring R₂] variable {R₃ : Type*} [CommSemiring R₃] {R₄ : Type*} [CommSemiring R₄] variable {M : Type*} {N : Type*} {P : Type*} {Q : Type*} variable {Mₗ : Type*} {Nₗ : Type*} {Pₗ : Type*} {Qₗ Qₗ' : Type*} variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P] [AddCommMonoid Q] variable [AddCommMonoid Mₗ] [AddCommMonoid Nₗ] [AddCommMonoid Pₗ] variable [AddCommMonoid Qₗ] [AddCommMonoid Qₗ'] variable [Module R M] [Module R₂ N] [Module R₃ P] [Module R₄ Q] variable [Module R Mₗ] [Module R Nₗ] [Module R Pₗ] [Module R Qₗ] [Module R Qₗ'] variable {σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R →+* R₃} variable {σ₄₂ : R₄ →+* R₂} {σ₄₃ : R₄ →+* R₃} variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [RingHomCompTriple σ₄₂ σ₂₃ σ₄₃] variable (R) /-- Create a bilinear map from a function that is linear in each component. This is a shorthand for `mk₂'` for the common case when `R = S`. -/ def mk₂ (f : M → Nₗ → Pₗ) (H1 : ∀ m₁ m₂ n, f (m₁ + m₂) n = f m₁ n + f m₂ n) (H2 : ∀ (c : R) (m n), f (c • m) n = c • f m n) (H3 : ∀ m n₁ n₂, f m (n₁ + n₂) = f m n₁ + f m n₂) (H4 : ∀ (c : R) (m n), f m (c • n) = c • f m n) : M →ₗ[R] Nₗ →ₗ[R] Pₗ := mk₂' R R f H1 H2 H3 H4 @[simp] theorem mk₂_apply (f : M → Nₗ → Pₗ) {H1 H2 H3 H4} (m : M) (n : Nₗ) : (mk₂ R f H1 H2 H3 H4 : M →ₗ[R] Nₗ →ₗ[R] Pₗ) m n = f m n := rfl variable {R} /-- Given a linear map from `M` to linear maps from `N` to `P`, i.e., a bilinear map `M → N → P`, change the order of variables and get a linear map from `N` to linear maps from `M` to `P`. -/ def lflip : (M →ₛₗ[σ₁₃] N →ₛₗ[σ₂₃] P) →ₗ[R₃] N →ₛₗ[σ₂₃] M →ₛₗ[σ₁₃] P where toFun := flip map_add' _ _ := rfl map_smul' _ _ := rfl variable (f : M →ₛₗ[σ₁₃] N →ₛₗ[σ₂₃] P) @[simp] theorem lflip_apply (m : M) (n : N) : lflip f n m = f m n := rfl variable (R Pₗ) /-- Composing a given linear map `M → N` with a linear map `N → P` as a linear map from `Nₗ →ₗ[R] Pₗ` to `M →ₗ[R] Pₗ`. -/ def lcomp (f : M →ₗ[R] Nₗ) : (Nₗ →ₗ[R] Pₗ) →ₗ[R] M →ₗ[R] Pₗ := flip <| LinearMap.comp (flip id) f variable {R Pₗ} @[simp] theorem lcomp_apply (f : M →ₗ[R] Nₗ) (g : Nₗ →ₗ[R] Pₗ) (x : M) : lcomp _ _ f g x = g (f x) := rfl theorem lcomp_apply' (f : M →ₗ[R] Nₗ) (g : Nₗ →ₗ[R] Pₗ) : lcomp R Pₗ f g = g ∘ₗ f := rfl variable (P σ₂₃) /-- Composing a semilinear map `M → N` and a semilinear map `N → P` to form a semilinear map `M → P` is itself a linear map. -/ def lcompₛₗ (f : M →ₛₗ[σ₁₂] N) : (N →ₛₗ[σ₂₃] P) →ₗ[R₃] M →ₛₗ[σ₁₃] P := flip <| LinearMap.comp (flip id) f variable {P σ₂₃} @[simp] theorem lcompₛₗ_apply (f : M →ₛₗ[σ₁₂] N) (g : N →ₛₗ[σ₂₃] P) (x : M) : lcompₛₗ P σ₂₃ f g x = g (f x) := rfl variable (R M Nₗ Pₗ) /-- Composing linear maps as a bilinear map from `(M →ₗ[R] N) × (N →ₗ[R] P)` to `M →ₗ[R] P` -/ def llcomp : (Nₗ →ₗ[R] Pₗ) →ₗ[R] (M →ₗ[R] Nₗ) →ₗ[R] M →ₗ[R] Pₗ := flip { toFun := lcomp R Pₗ map_add' := fun _f _f' => ext₂ fun g _x => g.map_add _ _ map_smul' := fun (_c : R) _f => ext₂ fun g _x => g.map_smul _ _ } variable {R M Nₗ Pₗ} section @[simp] theorem llcomp_apply (f : Nₗ →ₗ[R] Pₗ) (g : M →ₗ[R] Nₗ) (x : M) : llcomp R M Nₗ Pₗ f g x = f (g x) := rfl theorem llcomp_apply' (f : Nₗ →ₗ[R] Pₗ) (g : M →ₗ[R] Nₗ) : llcomp R M Nₗ Pₗ f g = f ∘ₗ g := rfl end /-- Composing a linear map `Q → N` and a bilinear map `M → N → P` to form a bilinear map `M → Q → P`. -/ def compl₂ {R₅ : Type*} [CommSemiring R₅] [Module R₅ P] [SMulCommClass R₃ R₅ P] {σ₁₅ : R →+* R₅} (h : M →ₛₗ[σ₁₅] N →ₛₗ[σ₂₃] P) (g : Q →ₛₗ[σ₄₂] N) : M →ₛₗ[σ₁₅] Q →ₛₗ[σ₄₃] P where toFun a := (lcompₛₗ P σ₂₃ g) (h a) map_add' _ _ := by simp [map_add] map_smul' _ _ := by simp only [LinearMap.map_smulₛₗ, lcompₛₗ] rfl @[simp] theorem compl₂_apply (g : Q →ₛₗ[σ₄₂] N) (m : M) (q : Q) : f.compl₂ g m q = f m (g q) := rfl @[simp] theorem compl₂_id : f.compl₂ LinearMap.id = f := by ext rw [compl₂_apply, id_coe, _root_.id] /-- Composing linear maps `Q → M` and `Q' → N` with a bilinear map `M → N → P` to form a bilinear map `Q → Q' → P`. -/ def compl₁₂ {R₁ : Type*} [CommSemiring R₁] [Module R₂ N] [Module R₂ Pₗ] [Module R₁ Pₗ] [Module R₁ Mₗ] [SMulCommClass R₂ R₁ Pₗ] [Module R₁ Qₗ] [Module R₂ Qₗ'] (f : Mₗ →ₗ[R₁] N →ₗ[R₂] Pₗ) (g : Qₗ →ₗ[R₁] Mₗ) (g' : Qₗ' →ₗ[R₂] N) : Qₗ →ₗ[R₁] Qₗ' →ₗ[R₂] Pₗ := (f.comp g).compl₂ g' @[simp] theorem compl₁₂_apply (f : Mₗ →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Qₗ →ₗ[R] Mₗ) (g' : Qₗ' →ₗ[R] Nₗ) (x : Qₗ) (y : Qₗ') : f.compl₁₂ g g' x y = f (g x) (g' y) := rfl @[simp] theorem compl₁₂_id_id (f : Mₗ →ₗ[R] Nₗ →ₗ[R] Pₗ) : f.compl₁₂ LinearMap.id LinearMap.id = f := by ext simp_rw [compl₁₂_apply, id_coe, _root_.id] theorem compl₁₂_inj {f₁ f₂ : Mₗ →ₗ[R] Nₗ →ₗ[R] Pₗ} {g : Qₗ →ₗ[R] Mₗ} {g' : Qₗ' →ₗ[R] Nₗ} (hₗ : Function.Surjective g) (hᵣ : Function.Surjective g') : f₁.compl₁₂ g g' = f₂.compl₁₂ g g' ↔ f₁ = f₂ := by constructor <;> intro h · -- B₁.comp l r = B₂.comp l r → B₁ = B₂ ext x y obtain ⟨x', hx⟩ := hₗ x subst hx obtain ⟨y', hy⟩ := hᵣ y subst hy convert LinearMap.congr_fun₂ h x' y' using 0 · -- B₁ = B₂ → B₁.comp l r = B₂.comp l r subst h; rfl /-- Composing a linear map `P → Q` and a bilinear map `M → N → P` to form a bilinear map `M → N → Q`. -/ def compr₂ (f : M →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Pₗ →ₗ[R] Qₗ) : M →ₗ[R] Nₗ →ₗ[R] Qₗ := llcomp R Nₗ Pₗ Qₗ g ∘ₗ f @[simp] theorem compr₂_apply (f : M →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Pₗ →ₗ[R] Qₗ) (m : M) (n : Nₗ) : f.compr₂ g m n = g (f m n) := rfl /-- A version of `Function.Injective.comp` for composition of a bilinear map with a linear map. -/ theorem injective_compr₂_of_injective (f : M →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Pₗ →ₗ[R] Qₗ) (hf : Injective f) (hg : Injective g) : Injective (f.compr₂ g) := hg.injective_linearMapComp_left.comp hf /-- A version of `Function.Surjective.comp` for composition of a bilinear map with a linear map. -/ theorem surjective_compr₂_of_exists_rightInverse (f : M →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Pₗ →ₗ[R] Qₗ) (hf : Surjective f) (hg : ∃ g' : Qₗ →ₗ[R] Pₗ, g.comp g' = LinearMap.id) :
Surjective (f.compr₂ g) := (surjective_comp_left_of_exists_rightInverse hg).comp hf /-- A version of `Function.Surjective.comp` for composition of a bilinear map with a linear map. -/ theorem surjective_compr₂_of_equiv (f : M →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Pₗ ≃ₗ[R] Qₗ) (hf : Surjective f) : Surjective (f.compr₂ g.toLinearMap) := surjective_compr₂_of_exists_rightInverse f g.toLinearMap hf ⟨g.symm, by simp⟩ /-- A version of `Function.Bijective.comp` for composition of a bilinear map with a linear map. -/ theorem bijective_compr₂_of_equiv (f : M →ₗ[R] Nₗ →ₗ[R] Pₗ) (g : Pₗ ≃ₗ[R] Qₗ) (hf : Bijective f) : Bijective (f.compr₂ g.toLinearMap) := ⟨injective_compr₂_of_injective f g.toLinearMap hf.1 g.bijective.1, surjective_compr₂_of_equiv f g hf.2⟩
Mathlib/LinearAlgebra/BilinearMap.lean
368
380
/- 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.Fin.VecNotation import Mathlib.Logic.Small.Basic import Mathlib.SetTheory.ZFC.PSet /-! # A model of ZFC In this file, we model Zermelo-Fraenkel set theory (+ choice) using Lean's underlying type theory, building on the pre-sets defined in `Mathlib.SetTheory.ZFC.PSet`. The theory of classes is developed in `Mathlib.SetTheory.ZFC.Class`. ## Main definitions * `ZFSet`: ZFC set. Defined as `PSet` quotiented by `PSet.Equiv`, the extensional equivalence. * `ZFSet.choice`: Axiom of choice. Proved from Lean's axiom of choice. * `ZFSet.omega`: The von Neumann ordinal `ω` as a `Set`. * `Classical.allZFSetDefinable`: All functions are classically definable. * `ZFSet.IsFunc` : Predicate that a ZFC set is a subset of `x × y` that can be considered as a ZFC function `x → y`. That is, each member of `x` is related by the ZFC set to exactly one member of `y`. * `ZFSet.funs`: ZFC set of ZFC functions `x → y`. * `ZFSet.Hereditarily p x`: Predicate that every set in the transitive closure of `x` has property `p`. ## Notes To avoid confusion between the Lean `Set` and the ZFC `Set`, docstrings in this file refer to them respectively as "`Set`" and "ZFC set". -/ universe u /-- The ZFC universe of sets consists of the type of pre-sets, quotiented by extensional equivalence. -/ @[pp_with_univ] def ZFSet : Type (u + 1) := Quotient PSet.setoid.{u} namespace ZFSet /-- Turns a pre-set into a ZFC set. -/ def mk : PSet → ZFSet := Quotient.mk'' @[simp] theorem mk_eq (x : PSet) : @Eq ZFSet ⟦x⟧ (mk x) := rfl @[simp] theorem mk_out : ∀ x : ZFSet, mk x.out = x := Quotient.out_eq /-- A set function is "definable" if it is the image of some n-ary `PSet` function. This isn't exactly definability, but is useful as a sufficient condition for functions that have a computable image. -/ class Definable (n) (f : (Fin n → ZFSet.{u}) → ZFSet.{u}) where /-- Turns a definable function into an n-ary `PSet` function. -/ out : (Fin n → PSet.{u}) → PSet.{u} /-- A set function `f` is the image of `Definable.out f`. -/ mk_out xs : mk (out xs) = f (mk <| xs ·) := by simp attribute [simp] Definable.mk_out /-- An abbrev of `ZFSet.Definable` for unary functions. -/ abbrev Definable₁ (f : ZFSet.{u} → ZFSet.{u}) := Definable 1 (fun s ↦ f (s 0)) /-- A simpler constructor for `ZFSet.Definable₁`. -/ abbrev Definable₁.mk {f : ZFSet.{u} → ZFSet.{u}} (out : PSet.{u} → PSet.{u}) (mk_out : ∀ x, ⟦out x⟧ = f ⟦x⟧) : Definable₁ f where out xs := out (xs 0) mk_out xs := mk_out (xs 0) /-- Turns a unary definable function into a unary `PSet` function. -/ abbrev Definable₁.out (f : ZFSet.{u} → ZFSet.{u}) [Definable₁ f] : PSet.{u} → PSet.{u} := fun x ↦ Definable.out (fun s ↦ f (s 0)) ![x] lemma Definable₁.mk_out {f : ZFSet.{u} → ZFSet.{u}} [Definable₁ f] {x : PSet} : .mk (out f x) = f (.mk x) := Definable.mk_out ![x] /-- An abbrev of `ZFSet.Definable` for binary functions. -/ abbrev Definable₂ (f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}) := Definable 2 (fun s ↦ f (s 0) (s 1)) /-- A simpler constructor for `ZFSet.Definable₂`. -/ abbrev Definable₂.mk {f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}} (out : PSet.{u} → PSet.{u} → PSet.{u}) (mk_out : ∀ x y, ⟦out x y⟧ = f ⟦x⟧ ⟦y⟧) : Definable₂ f where out xs := out (xs 0) (xs 1) mk_out xs := mk_out (xs 0) (xs 1) /-- Turns a binary definable function into a binary `PSet` function. -/ abbrev Definable₂.out (f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}) [Definable₂ f] : PSet.{u} → PSet.{u} → PSet.{u} := fun x y ↦ Definable.out (fun s ↦ f (s 0) (s 1)) ![x, y] lemma Definable₂.mk_out {f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}} [Definable₂ f] {x y : PSet} : .mk (out f x y) = f (.mk x) (.mk y) := Definable.mk_out ![x, y] instance (f) [Definable₁ f] (n g) [Definable n g] : Definable n (fun s ↦ f (g s)) where out xs := Definable₁.out f (Definable.out g xs) instance (f) [Definable₂ f] (n g₁ g₂) [Definable n g₁] [Definable n g₂] : Definable n (fun s ↦ f (g₁ s) (g₂ s)) where out xs := Definable₂.out f (Definable.out g₁ xs) (Definable.out g₂ xs) instance (n) (i) : Definable n (fun s ↦ s i) where out s := s i lemma Definable.out_equiv {n} (f : (Fin n → ZFSet.{u}) → ZFSet.{u}) [Definable n f] {xs ys : Fin n → PSet} (h : ∀ i, xs i ≈ ys i) : out f xs ≈ out f ys := by rw [← Quotient.eq_iff_equiv, mk_eq, mk_eq, mk_out, mk_out] exact congrArg _ (funext fun i ↦ Quotient.sound (h i)) lemma Definable₁.out_equiv (f : ZFSet.{u} → ZFSet.{u}) [Definable₁ f] {x y : PSet} (h : x ≈ y) : out f x ≈ out f y := Definable.out_equiv _ (by simp [h]) lemma Definable₂.out_equiv (f : ZFSet.{u} → ZFSet.{u} → ZFSet.{u}) [Definable₂ f] {x₁ y₁ x₂ y₂ : PSet} (h₁ : x₁ ≈ y₁) (h₂ : x₂ ≈ y₂) : out f x₁ x₂ ≈ out f y₁ y₂ := Definable.out_equiv _ (by simp [Fin.forall_fin_succ, h₁, h₂]) end ZFSet namespace Classical open PSet ZFSet /-- All functions are classically definable. -/ noncomputable def allZFSetDefinable {n} (F : (Fin n → ZFSet.{u}) → ZFSet.{u}) : Definable n F where out xs := (F (mk <| xs ·)).out end Classical namespace ZFSet open PSet theorem eq {x y : PSet} : mk x = mk y ↔ Equiv x y := Quotient.eq theorem sound {x y : PSet} (h : PSet.Equiv x y) : mk x = mk y := Quotient.sound h theorem exact {x y : PSet} : mk x = mk y → PSet.Equiv x y := Quotient.exact /-- The membership relation for ZFC sets is inherited from the membership relation for pre-sets. -/ protected def Mem : ZFSet → ZFSet → Prop := Quotient.lift₂ (· ∈ ·) fun _ _ _ _ hx hy => propext ((Mem.congr_left hx).trans (Mem.congr_right hy)) instance : Membership ZFSet ZFSet where mem t s := ZFSet.Mem s t @[simp] theorem mk_mem_iff {x y : PSet} : mk x ∈ mk y ↔ x ∈ y := Iff.rfl /-- Convert a ZFC set into a `Set` of ZFC sets -/ def toSet (u : ZFSet.{u}) : Set ZFSet.{u} := { x | x ∈ u } @[simp] theorem mem_toSet (a u : ZFSet.{u}) : a ∈ u.toSet ↔ a ∈ u := Iff.rfl instance small_toSet (x : ZFSet.{u}) : Small.{u} x.toSet := Quotient.inductionOn x fun a => by let f : a.Type → (mk a).toSet := fun i => ⟨mk <| a.Func i, func_mem a i⟩ suffices Function.Surjective f by exact small_of_surjective this rintro ⟨y, hb⟩ induction y using Quotient.inductionOn obtain ⟨i, h⟩ := hb exact ⟨i, Subtype.coe_injective (Quotient.sound h.symm)⟩ /-- A nonempty set is one that contains some element. -/ protected def Nonempty (u : ZFSet) : Prop := u.toSet.Nonempty theorem nonempty_def (u : ZFSet) : u.Nonempty ↔ ∃ x, x ∈ u := Iff.rfl theorem nonempty_of_mem {x u : ZFSet} (h : x ∈ u) : u.Nonempty := ⟨x, h⟩ @[simp] theorem nonempty_toSet_iff {u : ZFSet} : u.toSet.Nonempty ↔ u.Nonempty := Iff.rfl /-- `x ⊆ y` as ZFC sets means that all members of `x` are members of `y`. -/ protected def Subset (x y : ZFSet.{u}) := ∀ ⦃z⦄, z ∈ x → z ∈ y instance hasSubset : HasSubset ZFSet := ⟨ZFSet.Subset⟩ theorem subset_def {x y : ZFSet.{u}} : x ⊆ y ↔ ∀ ⦃z⦄, z ∈ x → z ∈ y := Iff.rfl instance : IsRefl ZFSet (· ⊆ ·) := ⟨fun _ _ => id⟩ instance : IsTrans ZFSet (· ⊆ ·) := ⟨fun _ _ _ hxy hyz _ ha => hyz (hxy ha)⟩ @[simp] theorem subset_iff : ∀ {x y : PSet}, mk x ⊆ mk y ↔ x ⊆ y | ⟨_, A⟩, ⟨_, _⟩ => ⟨fun h a => @h ⟦A a⟧ (Mem.mk A a), fun h z => Quotient.inductionOn z fun _ ⟨a, za⟩ => let ⟨b, ab⟩ := h a ⟨b, za.trans ab⟩⟩ @[simp] theorem toSet_subset_iff {x y : ZFSet} : x.toSet ⊆ y.toSet ↔ x ⊆ y := by
simp [subset_def, Set.subset_def] @[ext]
Mathlib/SetTheory/ZFC/Basic.lean
232
234
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Kim Morrison -/ import Mathlib.Algebra.BigOperators.Finsupp.Basic import Mathlib.Algebra.BigOperators.Group.Finset.Preimage import Mathlib.Algebra.Module.Defs import Mathlib.Data.Rat.BigOperators /-! # Miscellaneous definitions, lemmas, and constructions using finsupp ## Main declarations * `Finsupp.graph`: the finset of input and output pairs with non-zero outputs. * `Finsupp.mapRange.equiv`: `Finsupp.mapRange` as an equiv. * `Finsupp.mapDomain`: maps the domain of a `Finsupp` by a function and by summing. * `Finsupp.comapDomain`: postcomposition of a `Finsupp` with a function injective on the preimage of its support. * `Finsupp.some`: restrict a finitely supported function on `Option α` to a finitely supported function on `α`. * `Finsupp.filter`: `filter p f` is the finitely supported function that is `f a` if `p a` is true and 0 otherwise. * `Finsupp.frange`: the image of a finitely supported function on its support. * `Finsupp.subtype_domain`: the restriction of a finitely supported function `f` to a subtype. ## Implementation notes This file is a `noncomputable theory` and uses classical logic throughout. ## TODO * This file is currently ~1600 lines long and is quite a miscellany of definitions and lemmas, so it should be divided into smaller pieces. * Expand the list of definitions and important lemmas to the module docstring. -/ noncomputable section open Finset Function variable {α β γ ι M M' N P G H R S : Type*} namespace Finsupp /-! ### Declarations about `graph` -/ section Graph variable [Zero M] /-- The graph of a finitely supported function over its support, i.e. the finset of input and output pairs with non-zero outputs. -/ def graph (f : α →₀ M) : Finset (α × M) := f.support.map ⟨fun a => Prod.mk a (f a), fun _ _ h => (Prod.mk.inj h).1⟩ theorem mk_mem_graph_iff {a : α} {m : M} {f : α →₀ M} : (a, m) ∈ f.graph ↔ f a = m ∧ m ≠ 0 := by simp_rw [graph, mem_map, mem_support_iff] constructor · rintro ⟨b, ha, rfl, -⟩ exact ⟨rfl, ha⟩ · rintro ⟨rfl, ha⟩ exact ⟨a, ha, rfl⟩ @[simp] theorem mem_graph_iff {c : α × M} {f : α →₀ M} : c ∈ f.graph ↔ f c.1 = c.2 ∧ c.2 ≠ 0 := by cases c exact mk_mem_graph_iff theorem mk_mem_graph (f : α →₀ M) {a : α} (ha : a ∈ f.support) : (a, f a) ∈ f.graph := mk_mem_graph_iff.2 ⟨rfl, mem_support_iff.1 ha⟩ theorem apply_eq_of_mem_graph {a : α} {m : M} {f : α →₀ M} (h : (a, m) ∈ f.graph) : f a = m := (mem_graph_iff.1 h).1 @[simp 1100] -- Higher priority shortcut instance for `mem_graph_iff`. theorem not_mem_graph_snd_zero (a : α) (f : α →₀ M) : (a, (0 : M)) ∉ f.graph := fun h => (mem_graph_iff.1 h).2.irrefl @[simp] theorem image_fst_graph [DecidableEq α] (f : α →₀ M) : f.graph.image Prod.fst = f.support := by classical simp only [graph, map_eq_image, image_image, Embedding.coeFn_mk, Function.comp_def, image_id'] theorem graph_injective (α M) [Zero M] : Injective (@graph α M _) := by intro f g h classical have hsup : f.support = g.support := by rw [← image_fst_graph, h, image_fst_graph] refine ext_iff'.2 ⟨hsup, fun x hx => apply_eq_of_mem_graph <| h.symm ▸ ?_⟩ exact mk_mem_graph _ (hsup ▸ hx) @[simp] theorem graph_inj {f g : α →₀ M} : f.graph = g.graph ↔ f = g := (graph_injective α M).eq_iff @[simp] theorem graph_zero : graph (0 : α →₀ M) = ∅ := by simp [graph] @[simp] theorem graph_eq_empty {f : α →₀ M} : f.graph = ∅ ↔ f = 0 := (graph_injective α M).eq_iff' graph_zero end Graph end Finsupp /-! ### Declarations about `mapRange` -/ section MapRange namespace Finsupp section Equiv variable [Zero M] [Zero N] [Zero P] /-- `Finsupp.mapRange` as an equiv. -/ @[simps apply] def mapRange.equiv (f : M ≃ N) (hf : f 0 = 0) (hf' : f.symm 0 = 0) : (α →₀ M) ≃ (α →₀ N) where toFun := (mapRange f hf : (α →₀ M) → α →₀ N) invFun := (mapRange f.symm hf' : (α →₀ N) → α →₀ M) left_inv x := by rw [← mapRange_comp _ _ _ _] <;> simp_rw [Equiv.symm_comp_self] · exact mapRange_id _ · rfl right_inv x := by rw [← mapRange_comp _ _ _ _] <;> simp_rw [Equiv.self_comp_symm] · exact mapRange_id _ · rfl @[simp] theorem mapRange.equiv_refl : mapRange.equiv (Equiv.refl M) rfl rfl = Equiv.refl (α →₀ M) := Equiv.ext mapRange_id theorem mapRange.equiv_trans (f : M ≃ N) (hf : f 0 = 0) (hf') (f₂ : N ≃ P) (hf₂ : f₂ 0 = 0) (hf₂') : (mapRange.equiv (f.trans f₂) (by rw [Equiv.trans_apply, hf, hf₂]) (by rw [Equiv.symm_trans_apply, hf₂', hf']) : (α →₀ _) ≃ _) = (mapRange.equiv f hf hf').trans (mapRange.equiv f₂ hf₂ hf₂') := Equiv.ext <| mapRange_comp f₂ hf₂ f hf ((congrArg f₂ hf).trans hf₂) @[simp] theorem mapRange.equiv_symm (f : M ≃ N) (hf hf') : ((mapRange.equiv f hf hf').symm : (α →₀ _) ≃ _) = mapRange.equiv f.symm hf' hf := Equiv.ext fun _ => rfl end Equiv section ZeroHom variable [Zero M] [Zero N] [Zero P] /-- Composition with a fixed zero-preserving homomorphism is itself a zero-preserving homomorphism on functions. -/ @[simps] def mapRange.zeroHom (f : ZeroHom M N) : ZeroHom (α →₀ M) (α →₀ N) where toFun := (mapRange f f.map_zero : (α →₀ M) → α →₀ N) map_zero' := mapRange_zero @[simp] theorem mapRange.zeroHom_id : mapRange.zeroHom (ZeroHom.id M) = ZeroHom.id (α →₀ M) := ZeroHom.ext mapRange_id theorem mapRange.zeroHom_comp (f : ZeroHom N P) (f₂ : ZeroHom M N) : (mapRange.zeroHom (f.comp f₂) : ZeroHom (α →₀ _) _) = (mapRange.zeroHom f).comp (mapRange.zeroHom f₂) := ZeroHom.ext <| mapRange_comp f (map_zero f) f₂ (map_zero f₂) (by simp only [comp_apply, map_zero]) end ZeroHom section AddMonoidHom variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P] variable {F : Type*} [FunLike F M N] [AddMonoidHomClass F M N] /-- Composition with a fixed additive homomorphism is itself an additive homomorphism on functions. -/ @[simps] def mapRange.addMonoidHom (f : M →+ N) : (α →₀ M) →+ α →₀ N where toFun := (mapRange f f.map_zero : (α →₀ M) → α →₀ N) map_zero' := mapRange_zero -- Porting note: need either `dsimp only` or to specify `hf`: -- see also: https://github.com/leanprover-community/mathlib4/issues/12129 map_add' := mapRange_add (hf := f.map_zero) f.map_add
@[simp] theorem mapRange.addMonoidHom_id : mapRange.addMonoidHom (AddMonoidHom.id M) = AddMonoidHom.id (α →₀ M) :=
Mathlib/Data/Finsupp/Basic.lean
191
194
/- Copyright (c) 2020 Patrick Massot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Patrick Massot, Kim Morrison -/ import Mathlib.Algebra.Order.Interval.Set.Instances import Mathlib.Order.Interval.Set.ProjIcc import Mathlib.Topology.Algebra.Ring.Real /-! # The unit interval, as a topological space Use `open unitInterval` to turn on the notation `I := Set.Icc (0 : ℝ) (1 : ℝ)`. We provide basic instances, as well as a custom tactic for discharging `0 ≤ ↑x`, `0 ≤ 1 - ↑x`, `↑x ≤ 1`, and `1 - ↑x ≤ 1` when `x : I`. -/ noncomputable section open Topology Filter Set Int Set.Icc /-! ### The unit interval -/ /-- The unit interval `[0,1]` in ℝ. -/ abbrev unitInterval : Set ℝ := Set.Icc 0 1 @[inherit_doc] scoped[unitInterval] notation "I" => unitInterval namespace unitInterval theorem zero_mem : (0 : ℝ) ∈ I := ⟨le_rfl, zero_le_one⟩ theorem one_mem : (1 : ℝ) ∈ I := ⟨zero_le_one, le_rfl⟩ theorem mul_mem {x y : ℝ} (hx : x ∈ I) (hy : y ∈ I) : x * y ∈ I := ⟨mul_nonneg hx.1 hy.1, mul_le_one₀ hx.2 hy.1 hy.2⟩ theorem div_mem {x y : ℝ} (hx : 0 ≤ x) (hy : 0 ≤ y) (hxy : x ≤ y) : x / y ∈ I := ⟨div_nonneg hx hy, div_le_one_of_le₀ hxy hy⟩ theorem fract_mem (x : ℝ) : fract x ∈ I := ⟨fract_nonneg _, (fract_lt_one _).le⟩ theorem mem_iff_one_sub_mem {t : ℝ} : t ∈ I ↔ 1 - t ∈ I := by rw [mem_Icc, mem_Icc] constructor <;> intro <;> constructor <;> linarith instance hasZero : Zero I := ⟨⟨0, zero_mem⟩⟩ instance hasOne : One I := ⟨⟨1, by constructor <;> norm_num⟩⟩ instance : ZeroLEOneClass I := ⟨zero_le_one (α := ℝ)⟩ instance : CompleteLattice I := have : Fact ((0 : ℝ) ≤ 1) := ⟨zero_le_one⟩; inferInstance lemma univ_eq_Icc : (univ : Set I) = Icc (0 : I) (1 : I) := Icc_bot_top.symm @[norm_cast] theorem coe_ne_zero {x : I} : (x : ℝ) ≠ 0 ↔ x ≠ 0 := coe_eq_zero.not @[norm_cast] theorem coe_ne_one {x : I} : (x : ℝ) ≠ 1 ↔ x ≠ 1 := coe_eq_one.not @[simp, norm_cast] theorem coe_pos {x : I} : (0 : ℝ) < x ↔ 0 < x := Iff.rfl @[simp, norm_cast] theorem coe_lt_one {x : I} : (x : ℝ) < 1 ↔ x < 1 := Iff.rfl instance : Nonempty I := ⟨0⟩ instance : Mul I := ⟨fun x y => ⟨x * y, mul_mem x.2 y.2⟩⟩ theorem mul_le_left {x y : I} : x * y ≤ x := Subtype.coe_le_coe.mp <| mul_le_of_le_one_right x.2.1 y.2.2 theorem mul_le_right {x y : I} : x * y ≤ y := Subtype.coe_le_coe.mp <| mul_le_of_le_one_left y.2.1 x.2.2 /-- Unit interval central symmetry. -/ def symm : I → I := fun t => ⟨1 - t, mem_iff_one_sub_mem.mp t.prop⟩ @[inherit_doc] scoped notation "σ" => unitInterval.symm @[simp] theorem symm_zero : σ 0 = 1 := Subtype.ext <| by simp [symm] @[simp] theorem symm_one : σ 1 = 0 := Subtype.ext <| by simp [symm] @[simp] theorem symm_symm (x : I) : σ (σ x) = x := Subtype.ext <| by simp [symm] theorem symm_involutive : Function.Involutive (symm : I → I) := symm_symm theorem symm_bijective : Function.Bijective (symm : I → I) := symm_involutive.bijective @[simp] theorem coe_symm_eq (x : I) : (σ x : ℝ) = 1 - x := rfl @[simp] theorem symm_projIcc (x : ℝ) : symm (projIcc 0 1 zero_le_one x) = projIcc 0 1 zero_le_one (1 - x) := by ext rcases le_total x 0 with h₀ | h₀ · simp [projIcc_of_le_left, projIcc_of_right_le, h₀] · rcases le_total x 1 with h₁ | h₁ · lift x to I using ⟨h₀, h₁⟩ simp_rw [← coe_symm_eq, projIcc_val] · simp [projIcc_of_le_left, projIcc_of_right_le, h₁] @[continuity, fun_prop] theorem continuous_symm : Continuous σ := Continuous.subtype_mk (by fun_prop) _ /-- `unitInterval.symm` as a `Homeomorph`. -/ @[simps] def symmHomeomorph : I ≃ₜ I where toFun := symm invFun := symm left_inv := symm_symm right_inv := symm_symm theorem strictAnti_symm : StrictAnti σ := fun _ _ h ↦ sub_lt_sub_left (α := ℝ) h _ @[simp] theorem symm_inj {i j : I} : σ i = σ j ↔ i = j := symm_bijective.injective.eq_iff theorem half_le_symm_iff (t : I) : 1 / 2 ≤ (σ t : ℝ) ↔ (t : ℝ) ≤ 1 / 2 := by rw [coe_symm_eq, le_sub_iff_add_le, add_comm, ← le_sub_iff_add_le, sub_half] @[simp] lemma symm_eq_one {i : I} : σ i = 1 ↔ i = 0 := by rw [← symm_zero, symm_inj] @[simp] lemma symm_eq_zero {i : I} : σ i = 0 ↔ i = 1 := by rw [← symm_one, symm_inj] @[simp] theorem symm_le_symm {i j : I} : σ i ≤ σ j ↔ j ≤ i := by simp only [symm, Subtype.mk_le_mk, sub_le_sub_iff, add_le_add_iff_left, Subtype.coe_le_coe] theorem le_symm_comm {i j : I} : i ≤ σ j ↔ j ≤ σ i := by rw [← symm_le_symm, symm_symm] theorem symm_le_comm {i j : I} : σ i ≤ j ↔ σ j ≤ i := by rw [← symm_le_symm, symm_symm] @[simp] theorem symm_lt_symm {i j : I} : σ i < σ j ↔ j < i := by simp only [symm, Subtype.mk_lt_mk, sub_lt_sub_iff_left, Subtype.coe_lt_coe] theorem lt_symm_comm {i j : I} : i < σ j ↔ j < σ i := by rw [← symm_lt_symm, symm_symm] theorem symm_lt_comm {i j : I} : σ i < j ↔ σ j < i := by rw [← symm_lt_symm, symm_symm] instance : ConnectedSpace I := Subtype.connectedSpace ⟨nonempty_Icc.mpr zero_le_one, isPreconnected_Icc⟩ /-- Verify there is an instance for `CompactSpace I`. -/ example : CompactSpace I := by infer_instance theorem nonneg (x : I) : 0 ≤ (x : ℝ) := x.2.1 theorem one_minus_nonneg (x : I) : 0 ≤ 1 - (x : ℝ) := by simpa using x.2.2 theorem le_one (x : I) : (x : ℝ) ≤ 1 := x.2.2 theorem one_minus_le_one (x : I) : 1 - (x : ℝ) ≤ 1 := by simpa using x.2.1 theorem add_pos {t : I} {x : ℝ} (hx : 0 < x) : 0 < (x + t : ℝ) := add_pos_of_pos_of_nonneg hx <| nonneg _ /-- like `unitInterval.nonneg`, but with the inequality in `I`. -/ theorem nonneg' {t : I} : 0 ≤ t := t.2.1 /-- like `unitInterval.le_one`, but with the inequality in `I`. -/ theorem le_one' {t : I} : t ≤ 1 := t.2.2 protected lemma pos_iff_ne_zero {x : I} : 0 < x ↔ x ≠ 0 := bot_lt_iff_ne_bot protected lemma lt_one_iff_ne_one {x : I} : x < 1 ↔ x ≠ 1 := lt_top_iff_ne_top lemma eq_one_or_eq_zero_of_le_mul {i j : I} (h : i ≤ j * i) : i = 0 ∨ j = 1 := by contrapose! h rw [← unitInterval.lt_one_iff_ne_one, ← coe_lt_one, ← unitInterval.pos_iff_ne_zero, ← coe_pos] at h rw [← Subtype.coe_lt_coe, coe_mul] simpa using mul_lt_mul_of_pos_right h.right h.left instance : Nontrivial I := ⟨⟨1, 0, (one_ne_zero <| congrArg Subtype.val ·)⟩⟩ theorem mul_pos_mem_iff {a t : ℝ} (ha : 0 < a) : a * t ∈ I ↔ t ∈ Set.Icc (0 : ℝ) (1 / a) := by constructor <;> rintro ⟨h₁, h₂⟩ <;> constructor · exact nonneg_of_mul_nonneg_right h₁ ha · rwa [le_div_iff₀ ha, mul_comm]
· exact mul_nonneg ha.le h₁ · rwa [le_div_iff₀ ha, mul_comm] at h₂ theorem two_mul_sub_one_mem_iff {t : ℝ} : 2 * t - 1 ∈ I ↔ t ∈ Set.Icc (1 / 2 : ℝ) 1 := by constructor <;> rintro ⟨h₁, h₂⟩ <;> constructor <;> linarith /-- The unit interval as a submonoid of ℝ. -/ def submonoid : Submonoid ℝ where carrier := unitInterval one_mem' := unitInterval.one_mem
Mathlib/Topology/UnitInterval.lean
214
223
/- Copyright (c) 2020 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Logic.Function.Iterate import Mathlib.Order.Monotone.Basic /-! # Inequalities on iterates In this file we prove some inequalities comparing `f^[n] x` and `g^[n] x` where `f` and `g` are two self-maps that commute with each other. Current selection of inequalities is motivated by formalization of the rotation number of a circle homeomorphism. -/ open Function open Function (Commute) namespace Monotone variable {α : Type*} [Preorder α] {f : α → α} {x y : ℕ → α} /-! ### Comparison of two sequences If $f$ is a monotone function, then $∀ k, x_{k+1} ≤ f(x_k)$ implies that $x_k$ grows slower than $f^k(x_0)$, and similarly for the reversed inequalities. If $x_k$ and $y_k$ are two sequences such that $x_{k+1} ≤ f(x_k)$ and $y_{k+1} ≥ f(y_k)$ for all $k < n$, then $x_0 ≤ y_0$ implies $x_n ≤ y_n$, see `Monotone.seq_le_seq`. If some of the inequalities in this lemma are strict, then we have $x_n < y_n$. The rest of the lemmas in this section formalize this fact for different inequalities made strict. -/ theorem seq_le_seq (hf : Monotone f) (n : ℕ) (h₀ : x 0 ≤ y 0) (hx : ∀ k < n, x (k + 1) ≤ f (x k)) (hy : ∀ k < n, f (y k) ≤ y (k + 1)) : x n ≤ y n := by induction n with | zero => exact h₀ | succ n ihn => refine (hx _ n.lt_succ_self).trans ((hf <| ihn ?_ ?_).trans (hy _ n.lt_succ_self)) · exact fun k hk => hx _ (hk.trans n.lt_succ_self) · exact fun k hk => hy _ (hk.trans n.lt_succ_self) theorem seq_pos_lt_seq_of_lt_of_le (hf : Monotone f) {n : ℕ} (hn : 0 < n) (h₀ : x 0 ≤ y 0) (hx : ∀ k < n, x (k + 1) < f (x k)) (hy : ∀ k < n, f (y k) ≤ y (k + 1)) : x n < y n := by induction n with | zero => exact hn.false.elim | succ n ihn => suffices x n ≤ y n from (hx n n.lt_succ_self).trans_le ((hf this).trans <| hy n n.lt_succ_self) cases n with | zero => exact h₀ | succ n => refine (ihn n.zero_lt_succ (fun k hk => hx _ ?_) fun k hk => hy _ ?_).le <;> exact hk.trans n.succ.lt_succ_self theorem seq_pos_lt_seq_of_le_of_lt (hf : Monotone f) {n : ℕ} (hn : 0 < n) (h₀ : x 0 ≤ y 0) (hx : ∀ k < n, x (k + 1) ≤ f (x k)) (hy : ∀ k < n, f (y k) < y (k + 1)) : x n < y n := hf.dual.seq_pos_lt_seq_of_lt_of_le hn h₀ hy hx theorem seq_lt_seq_of_lt_of_le (hf : Monotone f) (n : ℕ) (h₀ : x 0 < y 0) (hx : ∀ k < n, x (k + 1) < f (x k)) (hy : ∀ k < n, f (y k) ≤ y (k + 1)) : x n < y n := by cases n exacts [h₀, hf.seq_pos_lt_seq_of_lt_of_le (Nat.zero_lt_succ _) h₀.le hx hy] theorem seq_lt_seq_of_le_of_lt (hf : Monotone f) (n : ℕ) (h₀ : x 0 < y 0) (hx : ∀ k < n, x (k + 1) ≤ f (x k)) (hy : ∀ k < n, f (y k) < y (k + 1)) : x n < y n := hf.dual.seq_lt_seq_of_lt_of_le n h₀ hy hx /-! ### Iterates of two functions In this section we compare the iterates of a monotone function `f : α → α` to iterates of any function `g : β → β`. If `h : β → α` satisfies `h ∘ g ≤ f ∘ h`, then `h (g^[n] x)` grows slower than `f^[n] (h x)`, and similarly for the reversed inequality. Then we specialize these two lemmas to the case `β = α`, `h = id`. -/ variable {β : Type*} {g : β → β} {h : β → α} open Function theorem le_iterate_comp_of_le (hf : Monotone f) (H : h ∘ g ≤ f ∘ h) (n : ℕ) : h ∘ g^[n] ≤ f^[n] ∘ h := fun x => by apply hf.seq_le_seq n <;> intros <;> simp [iterate_succ', -iterate_succ, comp_apply, id_eq, le_refl] case hx => exact H _ theorem iterate_comp_le_of_le (hf : Monotone f) (H : f ∘ h ≤ h ∘ g) (n : ℕ) : f^[n] ∘ h ≤ h ∘ g^[n] := hf.dual.le_iterate_comp_of_le H n /-- If `f ≤ g` and `f` is monotone, then `f^[n] ≤ g^[n]`. -/ theorem iterate_le_of_le {g : α → α} (hf : Monotone f) (h : f ≤ g) (n : ℕ) : f^[n] ≤ g^[n] := hf.iterate_comp_le_of_le h n /-- If `f ≤ g` and `g` is monotone, then `f^[n] ≤ g^[n]`. -/ theorem le_iterate_of_le {g : α → α} (hg : Monotone g) (h : f ≤ g) (n : ℕ) : f^[n] ≤ g^[n] := hg.dual.iterate_le_of_le h n end Monotone /-! ### Comparison of iterations and the identity function If $f(x) ≤ x$ for all $x$ (we express this as `f ≤ id` in the code), then the same is true for any iterate of $f$, and similarly for the reversed inequality. -/ namespace Function section Preorder variable {α : Type*} [Preorder α] {f : α → α} /-- If $x ≤ f x$ for all $x$ (we write this as `id ≤ f`), then the same is true for any iterate `f^[n]` of `f`. -/ theorem id_le_iterate_of_id_le (h : id ≤ f) (n : ℕ) : id ≤ f^[n] := by simpa only [iterate_id] using monotone_id.iterate_le_of_le h n theorem iterate_le_id_of_le_id (h : f ≤ id) (n : ℕ) : f^[n] ≤ id := @id_le_iterate_of_id_le αᵒᵈ _ f h n theorem monotone_iterate_of_id_le (h : id ≤ f) : Monotone fun m => f^[m] := monotone_nat_of_le_succ fun n x => by rw [iterate_succ_apply'] exact h _ theorem antitone_iterate_of_le_id (h : f ≤ id) : Antitone fun m => f^[m] := fun m n hmn => @monotone_iterate_of_id_le αᵒᵈ _ f h m n hmn end Preorder /-! ### Iterates of commuting functions If `f` and `g` are monotone and commute, then `f x ≤ g x` implies `f^[n] x ≤ g^[n] x`, see `Function.Commute.iterate_le_of_map_le`. We also prove two strict inequality versions of this lemma, as well as `iff` versions. -/ namespace Commute section Preorder variable {α : Type*} [Preorder α] {f g : α → α} theorem iterate_le_of_map_le (h : Commute f g) (hf : Monotone f) (hg : Monotone g) {x} (hx : f x ≤ g x) (n : ℕ) : f^[n] x ≤ g^[n] x := by apply hf.seq_le_seq n · rfl · intros; rw [iterate_succ_apply'] · intros; simp [h.iterate_right _ _, hg.iterate _ hx] theorem iterate_pos_lt_of_map_lt (h : Commute f g) (hf : Monotone f) (hg : StrictMono g) {x} (hx : f x < g x) {n} (hn : 0 < n) : f^[n] x < g^[n] x := by apply hf.seq_pos_lt_seq_of_le_of_lt hn · rfl · intros; rw [iterate_succ_apply'] · intros; simp [h.iterate_right _ _, hg.iterate _ hx] theorem iterate_pos_lt_of_map_lt' (h : Commute f g) (hf : StrictMono f) (hg : Monotone g) {x} (hx : f x < g x) {n} (hn : 0 < n) : f^[n] x < g^[n] x := @iterate_pos_lt_of_map_lt αᵒᵈ _ g f h.symm hg.dual hf.dual x hx n hn end Preorder variable {α : Type*} [LinearOrder α] {f g : α → α} theorem iterate_pos_lt_iff_map_lt (h : Commute f g) (hf : Monotone f) (hg : StrictMono g) {x n} (hn : 0 < n) : f^[n] x < g^[n] x ↔ f x < g x := by rcases lt_trichotomy (f x) (g x) with (H | H | H) · simp only [*, iterate_pos_lt_of_map_lt] · simp only [*, h.iterate_eq_of_map_eq, lt_irrefl] · simp only [lt_asymm H, lt_asymm (h.symm.iterate_pos_lt_of_map_lt' hg hf H hn)] theorem iterate_pos_lt_iff_map_lt' (h : Commute f g) (hf : StrictMono f) (hg : Monotone g) {x n} (hn : 0 < n) : f^[n] x < g^[n] x ↔ f x < g x := @iterate_pos_lt_iff_map_lt αᵒᵈ _ _ _ h.symm hg.dual hf.dual x n hn theorem iterate_pos_le_iff_map_le (h : Commute f g) (hf : Monotone f) (hg : StrictMono g) {x n} (hn : 0 < n) : f^[n] x ≤ g^[n] x ↔ f x ≤ g x := by simpa only [not_lt] using not_congr (h.symm.iterate_pos_lt_iff_map_lt' hg hf hn) theorem iterate_pos_le_iff_map_le' (h : Commute f g) (hf : StrictMono f) (hg : Monotone g) {x n} (hn : 0 < n) : f^[n] x ≤ g^[n] x ↔ f x ≤ g x := by simpa only [not_lt] using not_congr (h.symm.iterate_pos_lt_iff_map_lt hg hf hn) theorem iterate_pos_eq_iff_map_eq (h : Commute f g) (hf : Monotone f) (hg : StrictMono g) {x n} (hn : 0 < n) : f^[n] x = g^[n] x ↔ f x = g x := by simp only [le_antisymm_iff, h.iterate_pos_le_iff_map_le hf hg hn, h.symm.iterate_pos_le_iff_map_le' hg hf hn] end Commute end Function namespace Monotone variable {α : Type*} [Preorder α] {f : α → α} {x : α} /-- If `f` is a monotone map and `x ≤ f x` at some point `x`, then the iterates `f^[n] x` form a monotone sequence. -/ theorem monotone_iterate_of_le_map (hf : Monotone f) (hx : x ≤ f x) : Monotone fun n => f^[n] x := monotone_nat_of_le_succ fun n => by rw [iterate_succ_apply] exact hf.iterate n hx /-- If `f` is a monotone map and `f x ≤ x` at some point `x`, then the iterates `f^[n] x` form an antitone sequence. -/ theorem antitone_iterate_of_map_le (hf : Monotone f) (hx : f x ≤ x) : Antitone fun n => f^[n] x := hf.dual.monotone_iterate_of_le_map hx end Monotone namespace StrictMono variable {α : Type*} [Preorder α] {f : α → α} {x : α} /-- If `f` is a strictly monotone map and `x < f x` at some point `x`, then the iterates `f^[n] x` form a strictly monotone sequence. -/ theorem strictMono_iterate_of_lt_map (hf : StrictMono f) (hx : x < f x) : StrictMono fun n => f^[n] x := strictMono_nat_of_lt_succ fun n => by rw [iterate_succ_apply] exact hf.iterate n hx /-- If `f` is a strictly antitone map and `f x < x` at some point `x`, then the iterates `f^[n] x` form a strictly antitone sequence. -/ theorem strictAnti_iterate_of_map_lt (hf : StrictMono f) (hx : f x < x) : StrictAnti fun n => f^[n] x := hf.dual.strictMono_iterate_of_lt_map hx end StrictMono
Mathlib/Order/Iterate.lean
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/- Copyright (c) 2019 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Jakob von Raumer -/ import Mathlib.CategoryTheory.Limits.Shapes.FiniteProducts import Mathlib.CategoryTheory.Limits.Shapes.Kernels /-! # Biproducts and binary biproducts We introduce the notion of (finite) biproducts. Binary biproducts are defined in `CategoryTheory.Limits.Shapes.BinaryBiproducts`. These are slightly unusual relative to the other shapes in the library, as they are simultaneously limits and colimits. (Zero objects are similar; they are "biterminal".) For results about biproducts in preadditive categories see `CategoryTheory.Preadditive.Biproducts`. For biproducts indexed by a `Fintype J`, a `bicone` consists of a cone point `X` and morphisms `π j : X ⟶ F j` and `ι j : F j ⟶ X` for each `j`, such that `ι j ≫ π j'` is the identity when `j = j'` and zero otherwise. ## Notation As `⊕` is already taken for the sum of types, we introduce the notation `X ⊞ Y` for a binary biproduct. We introduce `⨁ f` for the indexed biproduct. ## Implementation notes Prior to https://github.com/leanprover-community/mathlib3/pull/14046, `HasFiniteBiproducts` required a `DecidableEq` instance on the indexing type. As this had no pay-off (everything about limits is non-constructive in mathlib), and occasional cost (constructing decidability instances appropriate for constructions involving the indexing type), we made everything classical. -/ noncomputable section universe w w' v u open CategoryTheory Functor namespace CategoryTheory.Limits variable {J : Type w} universe uC' uC uD' uD variable {C : Type uC} [Category.{uC'} C] [HasZeroMorphisms C] variable {D : Type uD} [Category.{uD'} D] [HasZeroMorphisms D] open scoped Classical in /-- A `c : Bicone F` is: * an object `c.pt` and * morphisms `π j : pt ⟶ F j` and `ι j : F j ⟶ pt` for each `j`, * such that `ι j ≫ π j'` is the identity when `j = j'` and zero otherwise. -/ structure Bicone (F : J → C) where pt : C π : ∀ j, pt ⟶ F j ι : ∀ j, F j ⟶ pt ι_π : ∀ j j', ι j ≫ π j' = if h : j = j' then eqToHom (congrArg F h) else 0 := by aesop attribute [inherit_doc Bicone] Bicone.pt Bicone.π Bicone.ι Bicone.ι_π @[reassoc (attr := simp)] theorem bicone_ι_π_self {F : J → C} (B : Bicone F) (j : J) : B.ι j ≫ B.π j = 𝟙 (F j) := by simpa using B.ι_π j j @[reassoc (attr := simp)] theorem bicone_ι_π_ne {F : J → C} (B : Bicone F) {j j' : J} (h : j ≠ j') : B.ι j ≫ B.π j' = 0 := by simpa [h] using B.ι_π j j' variable {F : J → C} /-- A bicone morphism between two bicones for the same diagram is a morphism of the bicone points which commutes with the cone and cocone legs. -/ structure BiconeMorphism {F : J → C} (A B : Bicone F) where /-- A morphism between the two vertex objects of the bicones -/ hom : A.pt ⟶ B.pt /-- The triangle consisting of the two natural transformations and `hom` commutes -/ wπ : ∀ j : J, hom ≫ B.π j = A.π j := by aesop_cat /-- The triangle consisting of the two natural transformations and `hom` commutes -/ wι : ∀ j : J, A.ι j ≫ hom = B.ι j := by aesop_cat attribute [reassoc (attr := simp)] BiconeMorphism.wι BiconeMorphism.wπ /-- The category of bicones on a given diagram. -/ @[simps] instance Bicone.category : Category (Bicone F) where Hom A B := BiconeMorphism A B comp f g := { hom := f.hom ≫ g.hom } id B := { hom := 𝟙 B.pt } -- Porting note: if we do not have `simps` automatically generate the lemma for simplifying -- the `hom` field of a category, we need to write the `ext` lemma in terms of the categorical -- morphism, rather than the underlying structure. @[ext] theorem BiconeMorphism.ext {c c' : Bicone F} (f g : c ⟶ c') (w : f.hom = g.hom) : f = g := by cases f cases g congr namespace Bicones /-- To give an isomorphism between cocones, it suffices to give an isomorphism between their vertices which commutes with the cocone maps. -/ @[aesop apply safe (rule_sets := [CategoryTheory]), simps] def ext {c c' : Bicone F} (φ : c.pt ≅ c'.pt) (wι : ∀ j, c.ι j ≫ φ.hom = c'.ι j := by aesop_cat) (wπ : ∀ j, φ.hom ≫ c'.π j = c.π j := by aesop_cat) : c ≅ c' where hom := { hom := φ.hom } inv := { hom := φ.inv wι := fun j => φ.comp_inv_eq.mpr (wι j).symm wπ := fun j => φ.inv_comp_eq.mpr (wπ j).symm } variable (F) in /-- A functor `G : C ⥤ D` sends bicones over `F` to bicones over `G.obj ∘ F` functorially. -/ @[simps] def functoriality (G : C ⥤ D) [Functor.PreservesZeroMorphisms G] : Bicone F ⥤ Bicone (G.obj ∘ F) where obj A := { pt := G.obj A.pt π := fun j => G.map (A.π j) ι := fun j => G.map (A.ι j) ι_π := fun i j => (Functor.map_comp _ _ _).symm.trans <| by rw [A.ι_π] aesop_cat } map f := { hom := G.map f.hom wπ := fun j => by simp [-BiconeMorphism.wπ, ← f.wπ j] wι := fun j => by simp [-BiconeMorphism.wι, ← f.wι j] } variable (G : C ⥤ D) instance functoriality_full [G.PreservesZeroMorphisms] [G.Full] [G.Faithful] : (functoriality F G).Full where map_surjective t := ⟨{ hom := G.preimage t.hom wι := fun j => G.map_injective (by simpa using t.wι j) wπ := fun j => G.map_injective (by simpa using t.wπ j) }, by aesop_cat⟩ instance functoriality_faithful [G.PreservesZeroMorphisms] [G.Faithful] : (functoriality F G).Faithful where map_injective {_X} {_Y} f g h := BiconeMorphism.ext f g <| G.map_injective <| congr_arg BiconeMorphism.hom h end Bicones namespace Bicone attribute [local aesop safe tactic (rule_sets := [CategoryTheory])] CategoryTheory.Discrete.discreteCases -- Porting note: would it be okay to use this more generally? attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Eq /-- Extract the cone from a bicone. -/ def toConeFunctor : Bicone F ⥤ Cone (Discrete.functor F) where obj B := { pt := B.pt, π := { app := fun j => B.π j.as } } map {_ _} F := { hom := F.hom, w := fun _ => F.wπ _ } /-- A shorthand for `toConeFunctor.obj` -/ abbrev toCone (B : Bicone F) : Cone (Discrete.functor F) := toConeFunctor.obj B -- TODO Consider changing this API to `toFan (B : Bicone F) : Fan F`. @[simp] theorem toCone_pt (B : Bicone F) : B.toCone.pt = B.pt := rfl @[simp] theorem toCone_π_app (B : Bicone F) (j : Discrete J) : B.toCone.π.app j = B.π j.as := rfl theorem toCone_π_app_mk (B : Bicone F) (j : J) : B.toCone.π.app ⟨j⟩ = B.π j := rfl @[simp] theorem toCone_proj (B : Bicone F) (j : J) : Fan.proj B.toCone j = B.π j := rfl /-- Extract the cocone from a bicone. -/ def toCoconeFunctor : Bicone F ⥤ Cocone (Discrete.functor F) where obj B := { pt := B.pt, ι := { app := fun j => B.ι j.as } } map {_ _} F := { hom := F.hom, w := fun _ => F.wι _ } /-- A shorthand for `toCoconeFunctor.obj` -/ abbrev toCocone (B : Bicone F) : Cocone (Discrete.functor F) := toCoconeFunctor.obj B @[simp] theorem toCocone_pt (B : Bicone F) : B.toCocone.pt = B.pt := rfl @[simp] theorem toCocone_ι_app (B : Bicone F) (j : Discrete J) : B.toCocone.ι.app j = B.ι j.as := rfl @[simp] theorem toCocone_inj (B : Bicone F) (j : J) : Cofan.inj B.toCocone j = B.ι j := rfl theorem toCocone_ι_app_mk (B : Bicone F) (j : J) : B.toCocone.ι.app ⟨j⟩ = B.ι j := rfl open scoped Classical in /-- We can turn any limit cone over a discrete collection of objects into a bicone. -/ @[simps] def ofLimitCone {f : J → C} {t : Cone (Discrete.functor f)} (ht : IsLimit t) : Bicone f where pt := t.pt π j := t.π.app ⟨j⟩ ι j := ht.lift (Fan.mk _ fun j' => if h : j = j' then eqToHom (congr_arg f h) else 0) ι_π j j' := by simp open scoped Classical in theorem ι_of_isLimit {f : J → C} {t : Bicone f} (ht : IsLimit t.toCone) (j : J) : t.ι j = ht.lift (Fan.mk _ fun j' => if h : j = j' then eqToHom (congr_arg f h) else 0) := ht.hom_ext fun j' => by rw [ht.fac] simp [t.ι_π] open scoped Classical in /-- We can turn any colimit cocone over a discrete collection of objects into a bicone. -/ @[simps] def ofColimitCocone {f : J → C} {t : Cocone (Discrete.functor f)} (ht : IsColimit t) : Bicone f where pt := t.pt π j := ht.desc (Cofan.mk _ fun j' => if h : j' = j then eqToHom (congr_arg f h) else 0) ι j := t.ι.app ⟨j⟩ ι_π j j' := by simp open scoped Classical in theorem π_of_isColimit {f : J → C} {t : Bicone f} (ht : IsColimit t.toCocone) (j : J) : t.π j = ht.desc (Cofan.mk _ fun j' => if h : j' = j then eqToHom (congr_arg f h) else 0) := ht.hom_ext fun j' => by rw [ht.fac] simp [t.ι_π] /-- Structure witnessing that a bicone is both a limit cone and a colimit cocone. -/ structure IsBilimit {F : J → C} (B : Bicone F) where isLimit : IsLimit B.toCone isColimit : IsColimit B.toCocone attribute [inherit_doc IsBilimit] IsBilimit.isLimit IsBilimit.isColimit attribute [simp] IsBilimit.mk.injEq attribute [local ext] Bicone.IsBilimit instance subsingleton_isBilimit {f : J → C} {c : Bicone f} : Subsingleton c.IsBilimit := ⟨fun _ _ => Bicone.IsBilimit.ext (Subsingleton.elim _ _) (Subsingleton.elim _ _)⟩ section Whisker variable {K : Type w'} /-- Whisker a bicone with an equivalence between the indexing types. -/ @[simps] def whisker {f : J → C} (c : Bicone f) (g : K ≃ J) : Bicone (f ∘ g) where pt := c.pt π k := c.π (g k) ι k := c.ι (g k) ι_π k k' := by simp only [c.ι_π] split_ifs with h h' h' <;> simp [Equiv.apply_eq_iff_eq g] at h h' <;> tauto /-- Taking the cone of a whiskered bicone results in a cone isomorphic to one gained by whiskering the cone and postcomposing with a suitable isomorphism. -/ def whiskerToCone {f : J → C} (c : Bicone f) (g : K ≃ J) : (c.whisker g).toCone ≅ (Cones.postcompose (Discrete.functorComp f g).inv).obj (c.toCone.whisker (Discrete.functor (Discrete.mk ∘ g))) := Cones.ext (Iso.refl _) (by simp) /-- Taking the cocone of a whiskered bicone results in a cone isomorphic to one gained by whiskering the cocone and precomposing with a suitable isomorphism. -/ def whiskerToCocone {f : J → C} (c : Bicone f) (g : K ≃ J) : (c.whisker g).toCocone ≅ (Cocones.precompose (Discrete.functorComp f g).hom).obj (c.toCocone.whisker (Discrete.functor (Discrete.mk ∘ g))) := Cocones.ext (Iso.refl _) (by simp) /-- Whiskering a bicone with an equivalence between types preserves being a bilimit bicone. -/ noncomputable def whiskerIsBilimitIff {f : J → C} (c : Bicone f) (g : K ≃ J) : (c.whisker g).IsBilimit ≃ c.IsBilimit := by refine equivOfSubsingletonOfSubsingleton (fun hc => ⟨?_, ?_⟩) fun hc => ⟨?_, ?_⟩ · let this := IsLimit.ofIsoLimit hc.isLimit (Bicone.whiskerToCone c g) let this := (IsLimit.postcomposeHomEquiv (Discrete.functorComp f g).symm _) this exact IsLimit.ofWhiskerEquivalence (Discrete.equivalence g) this · let this := IsColimit.ofIsoColimit hc.isColimit (Bicone.whiskerToCocone c g) let this := (IsColimit.precomposeHomEquiv (Discrete.functorComp f g) _) this exact IsColimit.ofWhiskerEquivalence (Discrete.equivalence g) this · apply IsLimit.ofIsoLimit _ (Bicone.whiskerToCone c g).symm apply (IsLimit.postcomposeHomEquiv (Discrete.functorComp f g).symm _).symm _ exact IsLimit.whiskerEquivalence hc.isLimit (Discrete.equivalence g) · apply IsColimit.ofIsoColimit _ (Bicone.whiskerToCocone c g).symm apply (IsColimit.precomposeHomEquiv (Discrete.functorComp f g) _).symm _ exact IsColimit.whiskerEquivalence hc.isColimit (Discrete.equivalence g) end Whisker end Bicone /-- A bicone over `F : J → C`, which is both a limit cone and a colimit cocone. -/ structure LimitBicone (F : J → C) where bicone : Bicone F isBilimit : bicone.IsBilimit attribute [inherit_doc LimitBicone] LimitBicone.bicone LimitBicone.isBilimit /-- `HasBiproduct F` expresses the mere existence of a bicone which is simultaneously a limit and a colimit of the diagram `F`. -/ class HasBiproduct (F : J → C) : Prop where mk' :: exists_biproduct : Nonempty (LimitBicone F) attribute [inherit_doc HasBiproduct] HasBiproduct.exists_biproduct theorem HasBiproduct.mk {F : J → C} (d : LimitBicone F) : HasBiproduct F := ⟨Nonempty.intro d⟩ /-- Use the axiom of choice to extract explicit `BiproductData F` from `HasBiproduct F`. -/ def getBiproductData (F : J → C) [HasBiproduct F] : LimitBicone F := Classical.choice HasBiproduct.exists_biproduct /-- A bicone for `F` which is both a limit cone and a colimit cocone. -/ def biproduct.bicone (F : J → C) [HasBiproduct F] : Bicone F := (getBiproductData F).bicone /-- `biproduct.bicone F` is a bilimit bicone. -/ def biproduct.isBilimit (F : J → C) [HasBiproduct F] : (biproduct.bicone F).IsBilimit := (getBiproductData F).isBilimit /-- `biproduct.bicone F` is a limit cone. -/ def biproduct.isLimit (F : J → C) [HasBiproduct F] : IsLimit (biproduct.bicone F).toCone := (getBiproductData F).isBilimit.isLimit /-- `biproduct.bicone F` is a colimit cocone. -/ def biproduct.isColimit (F : J → C) [HasBiproduct F] : IsColimit (biproduct.bicone F).toCocone := (getBiproductData F).isBilimit.isColimit instance (priority := 100) hasProduct_of_hasBiproduct [HasBiproduct F] : HasProduct F := HasLimit.mk { cone := (biproduct.bicone F).toCone isLimit := biproduct.isLimit F } instance (priority := 100) hasCoproduct_of_hasBiproduct [HasBiproduct F] : HasCoproduct F := HasColimit.mk { cocone := (biproduct.bicone F).toCocone isColimit := biproduct.isColimit F } variable (J C) /-- `C` has biproducts of shape `J` if we have a limit and a colimit, with the same cone points, of every function `F : J → C`. -/ class HasBiproductsOfShape : Prop where has_biproduct : ∀ F : J → C, HasBiproduct F attribute [instance 100] HasBiproductsOfShape.has_biproduct /-- `HasFiniteBiproducts C` represents a choice of biproduct for every family of objects in `C` indexed by a finite type. -/ class HasFiniteBiproducts : Prop where out : ∀ n, HasBiproductsOfShape (Fin n) C attribute [inherit_doc HasFiniteBiproducts] HasFiniteBiproducts.out variable {J} theorem hasBiproductsOfShape_of_equiv {K : Type w'} [HasBiproductsOfShape K C] (e : J ≃ K) : HasBiproductsOfShape J C := ⟨fun F => let ⟨⟨h⟩⟩ := HasBiproductsOfShape.has_biproduct (F ∘ e.symm) let ⟨c, hc⟩ := h HasBiproduct.mk <| by simpa only [Function.comp_def, e.symm_apply_apply] using LimitBicone.mk (c.whisker e) ((c.whiskerIsBilimitIff _).2 hc)⟩ instance (priority := 100) hasBiproductsOfShape_finite [HasFiniteBiproducts C] [Finite J] : HasBiproductsOfShape J C := by rcases Finite.exists_equiv_fin J with ⟨n, ⟨e⟩⟩ haveI : HasBiproductsOfShape (Fin n) C := HasFiniteBiproducts.out n exact hasBiproductsOfShape_of_equiv C e instance (priority := 100) hasFiniteProducts_of_hasFiniteBiproducts [HasFiniteBiproducts C] : HasFiniteProducts C where out _ := ⟨fun _ => hasLimit_of_iso Discrete.natIsoFunctor.symm⟩ instance (priority := 100) hasFiniteCoproducts_of_hasFiniteBiproducts [HasFiniteBiproducts C] : HasFiniteCoproducts C where out _ := ⟨fun _ => hasColimit_of_iso Discrete.natIsoFunctor⟩ instance (priority := 100) hasProductsOfShape_of_hasBiproductsOfShape [HasBiproductsOfShape J C] : HasProductsOfShape J C where has_limit _ := hasLimit_of_iso Discrete.natIsoFunctor.symm instance (priority := 100) hasCoproductsOfShape_of_hasBiproductsOfShape [HasBiproductsOfShape J C] : HasCoproductsOfShape J C where has_colimit _ := hasColimit_of_iso Discrete.natIsoFunctor variable {C} /-- The isomorphism between the specified limit and the specified colimit for a functor with a bilimit. -/ def biproductIso (F : J → C) [HasBiproduct F] : Limits.piObj F ≅ Limits.sigmaObj F := (IsLimit.conePointUniqueUpToIso (limit.isLimit _) (biproduct.isLimit F)).trans <| IsColimit.coconePointUniqueUpToIso (biproduct.isColimit F) (colimit.isColimit _) variable {J : Type w} {K : Type*} variable {C : Type u} [Category.{v} C] [HasZeroMorphisms C] /-- `biproduct f` computes the biproduct of a family of elements `f`. (It is defined as an abbreviation for `limit (Discrete.functor f)`, so for most facts about `biproduct f`, you will just use general facts about limits and colimits.) -/ abbrev biproduct (f : J → C) [HasBiproduct f] : C := (biproduct.bicone f).pt @[inherit_doc biproduct] notation "⨁ " f:20 => biproduct f /-- The projection onto a summand of a biproduct. -/ abbrev biproduct.π (f : J → C) [HasBiproduct f] (b : J) : ⨁ f ⟶ f b := (biproduct.bicone f).π b @[simp] theorem biproduct.bicone_π (f : J → C) [HasBiproduct f] (b : J) : (biproduct.bicone f).π b = biproduct.π f b := rfl /-- The inclusion into a summand of a biproduct. -/ abbrev biproduct.ι (f : J → C) [HasBiproduct f] (b : J) : f b ⟶ ⨁ f := (biproduct.bicone f).ι b @[simp] theorem biproduct.bicone_ι (f : J → C) [HasBiproduct f] (b : J) : (biproduct.bicone f).ι b = biproduct.ι f b := rfl /-- Note that as this lemma has an `if` in the statement, we include a `DecidableEq` argument. This means you may not be able to `simp` using this lemma unless you `open scoped Classical`. -/ @[reassoc] theorem biproduct.ι_π [DecidableEq J] (f : J → C) [HasBiproduct f] (j j' : J) : biproduct.ι f j ≫ biproduct.π f j' = if h : j = j' then eqToHom (congr_arg f h) else 0 := by convert (biproduct.bicone f).ι_π j j' @[reassoc] -- Porting note: both versions proven by simp theorem biproduct.ι_π_self (f : J → C) [HasBiproduct f] (j : J) : biproduct.ι f j ≫ biproduct.π f j = 𝟙 _ := by simp [biproduct.ι_π] @[reassoc (attr := simp)] theorem biproduct.ι_π_ne (f : J → C) [HasBiproduct f] {j j' : J} (h : j ≠ j') : biproduct.ι f j ≫ biproduct.π f j' = 0 := by simp [biproduct.ι_π, h] -- The `simpNF` linter incorrectly identifies these as simp lemmas that could never apply. -- It seems the side condition `w` is not applied by `simpNF`. -- https://github.com/leanprover-community/mathlib4/issues/5049 -- They are used by `simp` in `biproduct.whiskerEquiv` below. @[reassoc (attr := simp, nolint simpNF)] theorem biproduct.eqToHom_comp_ι (f : J → C) [HasBiproduct f] {j j' : J} (w : j = j') : eqToHom (by simp [w]) ≫ biproduct.ι f j' = biproduct.ι f j := by cases w simp -- The `simpNF` linter incorrectly identifies these as simp lemmas that could never apply. -- It seems the side condition `w` is not applied by `simpNF`. -- https://github.com/leanprover-community/mathlib4/issues/5049 -- They are used by `simp` in `biproduct.whiskerEquiv` below. @[reassoc (attr := simp, nolint simpNF)] theorem biproduct.π_comp_eqToHom (f : J → C) [HasBiproduct f] {j j' : J} (w : j = j') : biproduct.π f j ≫ eqToHom (by simp [w]) = biproduct.π f j' := by cases w simp /-- Given a collection of maps into the summands, we obtain a map into the biproduct. -/ abbrev biproduct.lift {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, P ⟶ f b) : P ⟶ ⨁ f := (biproduct.isLimit f).lift (Fan.mk P p) /-- Given a collection of maps out of the summands, we obtain a map out of the biproduct. -/ abbrev biproduct.desc {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, f b ⟶ P) : ⨁ f ⟶ P := (biproduct.isColimit f).desc (Cofan.mk P p) @[reassoc (attr := simp)] theorem biproduct.lift_π {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, P ⟶ f b) (j : J) : biproduct.lift p ≫ biproduct.π f j = p j := (biproduct.isLimit f).fac _ ⟨j⟩ @[reassoc (attr := simp)] theorem biproduct.ι_desc {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, f b ⟶ P) (j : J) : biproduct.ι f j ≫ biproduct.desc p = p j := (biproduct.isColimit f).fac _ ⟨j⟩ /-- Given a collection of maps between corresponding summands of a pair of biproducts indexed by the same type, we obtain a map between the biproducts. -/ abbrev biproduct.map {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ⟶ g b) : ⨁ f ⟶ ⨁ g := IsLimit.map (biproduct.bicone f).toCone (biproduct.isLimit g) (Discrete.natTrans (fun j => p j.as)) /-- An alternative to `biproduct.map` constructed via colimits. This construction only exists in order to show it is equal to `biproduct.map`. -/ abbrev biproduct.map' {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ⟶ g b) : ⨁ f ⟶ ⨁ g := IsColimit.map (biproduct.isColimit f) (biproduct.bicone g).toCocone (Discrete.natTrans fun j => p j.as) -- We put this at slightly higher priority than `biproduct.hom_ext'`, -- to get the matrix indices in the "right" order. @[ext 1001] theorem biproduct.hom_ext {f : J → C} [HasBiproduct f] {Z : C} (g h : Z ⟶ ⨁ f) (w : ∀ j, g ≫ biproduct.π f j = h ≫ biproduct.π f j) : g = h := (biproduct.isLimit f).hom_ext fun j => w j.as @[ext] theorem biproduct.hom_ext' {f : J → C} [HasBiproduct f] {Z : C} (g h : ⨁ f ⟶ Z) (w : ∀ j, biproduct.ι f j ≫ g = biproduct.ι f j ≫ h) : g = h := (biproduct.isColimit f).hom_ext fun j => w j.as /-- The canonical isomorphism between the chosen biproduct and the chosen product. -/ def biproduct.isoProduct (f : J → C) [HasBiproduct f] : ⨁ f ≅ ∏ᶜ f := IsLimit.conePointUniqueUpToIso (biproduct.isLimit f) (limit.isLimit _) @[simp] theorem biproduct.isoProduct_hom {f : J → C} [HasBiproduct f] : (biproduct.isoProduct f).hom = Pi.lift (biproduct.π f) := limit.hom_ext fun j => by simp [biproduct.isoProduct] @[simp] theorem biproduct.isoProduct_inv {f : J → C} [HasBiproduct f] : (biproduct.isoProduct f).inv = biproduct.lift (Pi.π f) := biproduct.hom_ext _ _ fun j => by simp [Iso.inv_comp_eq] /-- The canonical isomorphism between the chosen biproduct and the chosen coproduct. -/ def biproduct.isoCoproduct (f : J → C) [HasBiproduct f] : ⨁ f ≅ ∐ f := IsColimit.coconePointUniqueUpToIso (biproduct.isColimit f) (colimit.isColimit _) @[simp] theorem biproduct.isoCoproduct_inv {f : J → C} [HasBiproduct f] : (biproduct.isoCoproduct f).inv = Sigma.desc (biproduct.ι f) := colimit.hom_ext fun j => by simp [biproduct.isoCoproduct] @[simp] theorem biproduct.isoCoproduct_hom {f : J → C} [HasBiproduct f] : (biproduct.isoCoproduct f).hom = biproduct.desc (Sigma.ι f) := biproduct.hom_ext' _ _ fun j => by simp [← Iso.eq_comp_inv] /-- If a category has biproducts of a shape `J`, its `colim` and `lim` functor on diagrams over `J` are isomorphic. -/ @[simps!] def HasBiproductsOfShape.colimIsoLim [HasBiproductsOfShape J C] : colim (J := Discrete J) (C := C) ≅ lim := NatIso.ofComponents (fun F => (Sigma.isoColimit F).symm ≪≫ (biproduct.isoCoproduct _).symm ≪≫ biproduct.isoProduct _ ≪≫ Pi.isoLimit F) fun η => colimit.hom_ext fun ⟨i⟩ => limit.hom_ext fun ⟨j⟩ => by classical by_cases h : i = j <;> simp_all [h, Sigma.isoColimit, Pi.isoLimit, biproduct.ι_π, biproduct.ι_π_assoc] theorem biproduct.map_eq_map' {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ⟶ g b) : biproduct.map p = biproduct.map' p := by classical ext dsimp simp only [Discrete.natTrans_app, Limits.IsColimit.ι_map_assoc, Limits.IsLimit.map_π, Category.assoc, ← Bicone.toCone_π_app_mk, ← biproduct.bicone_π, ← Bicone.toCocone_ι_app_mk, ← biproduct.bicone_ι] dsimp rw [biproduct.ι_π_assoc, biproduct.ι_π] split_ifs with h · subst h; simp · simp @[reassoc (attr := simp)] theorem biproduct.map_π {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) (j : J) : biproduct.map p ≫ biproduct.π g j = biproduct.π f j ≫ p j := Limits.IsLimit.map_π _ _ _ (Discrete.mk j) @[reassoc (attr := simp)] theorem biproduct.ι_map {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) (j : J) : biproduct.ι f j ≫ biproduct.map p = p j ≫ biproduct.ι g j := by rw [biproduct.map_eq_map'] apply Limits.IsColimit.ι_map (biproduct.isColimit f) (biproduct.bicone g).toCocone (Discrete.natTrans fun j => p j.as) (Discrete.mk j) @[reassoc (attr := simp)] theorem biproduct.map_desc {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) {P : C} (k : ∀ j, g j ⟶ P) : biproduct.map p ≫ biproduct.desc k = biproduct.desc fun j => p j ≫ k j := by ext; simp @[reassoc (attr := simp)] theorem biproduct.lift_map {f g : J → C} [HasBiproduct f] [HasBiproduct g] {P : C} (k : ∀ j, P ⟶ f j) (p : ∀ j, f j ⟶ g j) : biproduct.lift k ≫ biproduct.map p = biproduct.lift fun j => k j ≫ p j := by ext; simp /-- Given a collection of isomorphisms between corresponding summands of a pair of biproducts indexed by the same type, we obtain an isomorphism between the biproducts. -/ @[simps] def biproduct.mapIso {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ≅ g b) : ⨁ f ≅ ⨁ g where hom := biproduct.map fun b => (p b).hom inv := biproduct.map fun b => (p b).inv instance biproduct.map_epi {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) [∀ j, Epi (p j)] : Epi (biproduct.map p) := by classical have : biproduct.map p = (biproduct.isoCoproduct _).hom ≫ Sigma.map p ≫ (biproduct.isoCoproduct _).inv := by ext simp only [map_π, isoCoproduct_hom, isoCoproduct_inv, Category.assoc, ι_desc_assoc, ι_colimMap_assoc, Discrete.functor_obj_eq_as, Discrete.natTrans_app, colimit.ι_desc_assoc, Cofan.mk_pt, Cofan.mk_ι_app, ι_π, ι_π_assoc] split all_goals simp_all rw [this] infer_instance instance Pi.map_epi {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) [∀ j, Epi (p j)] : Epi (Pi.map p) := by rw [show Pi.map p = (biproduct.isoProduct _).inv ≫ biproduct.map p ≫ (biproduct.isoProduct _).hom by aesop] infer_instance instance biproduct.map_mono {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) [∀ j, Mono (p j)] : Mono (biproduct.map p) := by rw [show biproduct.map p = (biproduct.isoProduct _).hom ≫ Pi.map p ≫ (biproduct.isoProduct _).inv by aesop] infer_instance instance Sigma.map_mono {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j) [∀ j, Mono (p j)] : Mono (Sigma.map p) := by rw [show Sigma.map p = (biproduct.isoCoproduct _).inv ≫ biproduct.map p ≫ (biproduct.isoCoproduct _).hom by aesop] infer_instance /-- Two biproducts which differ by an equivalence in the indexing type, and up to isomorphism in the factors, are isomorphic. Unfortunately there are two natural ways to define each direction of this isomorphism (because it is true for both products and coproducts separately). We give the alternative definitions as lemmas below. -/ @[simps] def biproduct.whiskerEquiv {f : J → C} {g : K → C} (e : J ≃ K) (w : ∀ j, g (e j) ≅ f j) [HasBiproduct f] [HasBiproduct g] : ⨁ f ≅ ⨁ g where hom := biproduct.desc fun j => (w j).inv ≫ biproduct.ι g (e j) inv := biproduct.desc fun k => eqToHom (by simp) ≫ (w (e.symm k)).hom ≫ biproduct.ι f _ lemma biproduct.whiskerEquiv_hom_eq_lift {f : J → C} {g : K → C} (e : J ≃ K) (w : ∀ j, g (e j) ≅ f j) [HasBiproduct f] [HasBiproduct g] : (biproduct.whiskerEquiv e w).hom = biproduct.lift fun k => biproduct.π f (e.symm k) ≫ (w _).inv ≫ eqToHom (by simp) := by simp only [whiskerEquiv_hom] ext k j by_cases h : k = e j · subst h simp · simp only [ι_desc_assoc, Category.assoc, ne_eq, lift_π] rw [biproduct.ι_π_ne, biproduct.ι_π_ne_assoc] · simp · rintro rfl simp at h · exact Ne.symm h lemma biproduct.whiskerEquiv_inv_eq_lift {f : J → C} {g : K → C} (e : J ≃ K) (w : ∀ j, g (e j) ≅ f j) [HasBiproduct f] [HasBiproduct g] : (biproduct.whiskerEquiv e w).inv = biproduct.lift fun j => biproduct.π g (e j) ≫ (w j).hom := by simp only [whiskerEquiv_inv] ext j k by_cases h : k = e j · subst h simp only [ι_desc_assoc, ← eqToHom_iso_hom_naturality_assoc w (e.symm_apply_apply j).symm, Equiv.symm_apply_apply, eqToHom_comp_ι, Category.assoc, bicone_ι_π_self, Category.comp_id, lift_π, bicone_ι_π_self_assoc] · simp only [ι_desc_assoc, Category.assoc, ne_eq, lift_π] rw [biproduct.ι_π_ne, biproduct.ι_π_ne_assoc] · simp · exact h · rintro rfl simp at h attribute [local simp] Sigma.forall in instance {ι} (f : ι → Type*) (g : (i : ι) → (f i) → C) [∀ i, HasBiproduct (g i)] [HasBiproduct fun i => ⨁ g i] : HasBiproduct fun p : Σ i, f i => g p.1 p.2 where exists_biproduct := Nonempty.intro { bicone := { pt := ⨁ fun i => ⨁ g i ι := fun X => biproduct.ι (g X.1) X.2 ≫ biproduct.ι (fun i => ⨁ g i) X.1 π := fun X => biproduct.π (fun i => ⨁ g i) X.1 ≫ biproduct.π (g X.1) X.2 ι_π := fun ⟨j, x⟩ ⟨j', y⟩ => by split_ifs with h · obtain ⟨rfl, rfl⟩ := h simp · simp only [Sigma.mk.inj_iff, not_and] at h by_cases w : j = j' · cases w simp only [heq_eq_eq, forall_true_left] at h simp [biproduct.ι_π_ne _ h] · simp [biproduct.ι_π_ne_assoc _ w] } isBilimit := { isLimit := mkFanLimit _ (fun s => biproduct.lift fun b => biproduct.lift fun c => s.proj ⟨b, c⟩) isColimit := mkCofanColimit _ (fun s => biproduct.desc fun b => biproduct.desc fun c => s.inj ⟨b, c⟩) } } /-- An iterated biproduct is a biproduct over a sigma type. -/ @[simps] def biproductBiproductIso {ι} (f : ι → Type*) (g : (i : ι) → (f i) → C) [∀ i, HasBiproduct (g i)] [HasBiproduct fun i => ⨁ g i] : (⨁ fun i => ⨁ g i) ≅ (⨁ fun p : Σ i, f i => g p.1 p.2) where hom := biproduct.lift fun ⟨i, x⟩ => biproduct.π _ i ≫ biproduct.π _ x inv := biproduct.lift fun i => biproduct.lift fun x => biproduct.π _ (⟨i, x⟩ : Σ i, f i) section πKernel section variable (f : J → C) [HasBiproduct f] variable (p : J → Prop) [HasBiproduct (Subtype.restrict p f)] /-- The canonical morphism from the biproduct over a restricted index type to the biproduct of the full index type. -/ def biproduct.fromSubtype : ⨁ Subtype.restrict p f ⟶ ⨁ f := biproduct.desc fun j => biproduct.ι _ j.val /-- The canonical morphism from a biproduct to the biproduct over a restriction of its index type. -/ def biproduct.toSubtype : ⨁ f ⟶ ⨁ Subtype.restrict p f := biproduct.lift fun _ => biproduct.π _ _ @[reassoc (attr := simp)] theorem biproduct.fromSubtype_π [DecidablePred p] (j : J) : biproduct.fromSubtype f p ≫ biproduct.π f j = if h : p j then biproduct.π (Subtype.restrict p f) ⟨j, h⟩ else 0 := by classical ext i; dsimp rw [biproduct.fromSubtype, biproduct.ι_desc_assoc, biproduct.ι_π] by_cases h : p j · rw [dif_pos h, biproduct.ι_π] split_ifs with h₁ h₂ h₂ exacts [rfl, False.elim (h₂ (Subtype.ext h₁)), False.elim (h₁ (congr_arg Subtype.val h₂)), rfl] · rw [dif_neg h, dif_neg (show (i : J) ≠ j from fun h₂ => h (h₂ ▸ i.2)), comp_zero] theorem biproduct.fromSubtype_eq_lift [DecidablePred p] : biproduct.fromSubtype f p = biproduct.lift fun j => if h : p j then biproduct.π (Subtype.restrict p f) ⟨j, h⟩ else 0 := biproduct.hom_ext _ _ (by simp) @[reassoc] -- Porting note: both version solved using simp theorem biproduct.fromSubtype_π_subtype (j : Subtype p) : biproduct.fromSubtype f p ≫ biproduct.π f j = biproduct.π (Subtype.restrict p f) j := by classical ext rw [biproduct.fromSubtype, biproduct.ι_desc_assoc, biproduct.ι_π, biproduct.ι_π] split_ifs with h₁ h₂ h₂ exacts [rfl, False.elim (h₂ (Subtype.ext h₁)), False.elim (h₁ (congr_arg Subtype.val h₂)), rfl] @[reassoc (attr := simp)] theorem biproduct.toSubtype_π (j : Subtype p) : biproduct.toSubtype f p ≫ biproduct.π (Subtype.restrict p f) j = biproduct.π f j := biproduct.lift_π _ _ @[reassoc (attr := simp)] theorem biproduct.ι_toSubtype [DecidablePred p] (j : J) : biproduct.ι f j ≫ biproduct.toSubtype f p = if h : p j then biproduct.ι (Subtype.restrict p f) ⟨j, h⟩ else 0 := by classical ext i rw [biproduct.toSubtype, Category.assoc, biproduct.lift_π, biproduct.ι_π] by_cases h : p j · rw [dif_pos h, biproduct.ι_π] split_ifs with h₁ h₂ h₂ exacts [rfl, False.elim (h₂ (Subtype.ext h₁)), False.elim (h₁ (congr_arg Subtype.val h₂)), rfl] · rw [dif_neg h, dif_neg (show j ≠ i from fun h₂ => h (h₂.symm ▸ i.2)), zero_comp] theorem biproduct.toSubtype_eq_desc [DecidablePred p] : biproduct.toSubtype f p = biproduct.desc fun j => if h : p j then biproduct.ι (Subtype.restrict p f) ⟨j, h⟩ else 0 := biproduct.hom_ext' _ _ (by simp) @[reassoc] theorem biproduct.ι_toSubtype_subtype (j : Subtype p) : biproduct.ι f j ≫ biproduct.toSubtype f p = biproduct.ι (Subtype.restrict p f) j := by classical ext rw [biproduct.toSubtype, Category.assoc, biproduct.lift_π, biproduct.ι_π, biproduct.ι_π] split_ifs with h₁ h₂ h₂ exacts [rfl, False.elim (h₂ (Subtype.ext h₁)), False.elim (h₁ (congr_arg Subtype.val h₂)), rfl] @[reassoc (attr := simp)] theorem biproduct.ι_fromSubtype (j : Subtype p) : biproduct.ι (Subtype.restrict p f) j ≫ biproduct.fromSubtype f p = biproduct.ι f j := biproduct.ι_desc _ _
@[reassoc (attr := simp)] theorem biproduct.fromSubtype_toSubtype : biproduct.fromSubtype f p ≫ biproduct.toSubtype f p = 𝟙 (⨁ Subtype.restrict p f) := by
Mathlib/CategoryTheory/Limits/Shapes/Biproducts.lean
782
785
/- Copyright (c) 2023 Ashvni Narayanan. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Ashvni Narayanan, Moritz Firsching, Michael Stoll -/ import Mathlib.Algebra.Group.EvenFunction import Mathlib.Data.ZMod.Units import Mathlib.NumberTheory.MulChar.Basic /-! # Dirichlet Characters Let `R` be a commutative monoid with zero. A Dirichlet character `χ` of level `n` over `R` is a multiplicative character from `ZMod n` to `R` sending non-units to 0. We then obtain some properties of `toUnitHom χ`, the restriction of `χ` to a group homomorphism `(ZMod n)ˣ →* Rˣ`. Main definitions: - `DirichletCharacter`: The type representing a Dirichlet character. - `changeLevel`: Extend the Dirichlet character χ of level `n` to level `m`, where `n` divides `m`. - `conductor`: The conductor of a Dirichlet character. - `IsPrimitive`: If the level is equal to the conductor. ## Tags dirichlet character, multiplicative character -/ /-! ### Definitions -/ /-- The type of Dirichlet characters of level `n`. -/ abbrev DirichletCharacter (R : Type*) [CommMonoidWithZero R] (n : ℕ) := MulChar (ZMod n) R open MulChar variable {R : Type*} [CommMonoidWithZero R] {n : ℕ} (χ : DirichletCharacter R n) namespace DirichletCharacter lemma toUnitHom_eq_char' {a : ZMod n} (ha : IsUnit a) : χ a = χ.toUnitHom ha.unit := by simp lemma toUnitHom_inj (ψ : DirichletCharacter R n) : toUnitHom χ = toUnitHom ψ ↔ χ = ψ := by simp @[deprecated (since := "2024-12-29")] alias toUnitHom_eq_iff := toUnitHom_inj lemma eval_modulus_sub (x : ZMod n) : χ (n - x) = χ (-x) := by simp /-! ### Changing levels -/ /-- A function that modifies the level of a Dirichlet character to some multiple of its original level. -/ noncomputable def changeLevel {n m : ℕ} (hm : n ∣ m) : DirichletCharacter R n →* DirichletCharacter R m where toFun ψ := MulChar.ofUnitHom (ψ.toUnitHom.comp (ZMod.unitsMap hm)) map_one' := by ext; simp map_mul' ψ₁ ψ₂ := by ext; simp lemma changeLevel_def {m : ℕ} (hm : n ∣ m) : changeLevel hm χ = MulChar.ofUnitHom (χ.toUnitHom.comp (ZMod.unitsMap hm)) := rfl lemma changeLevel_toUnitHom {m : ℕ} (hm : n ∣ m) :
(changeLevel hm χ).toUnitHom = χ.toUnitHom.comp (ZMod.unitsMap hm) := by simp [changeLevel] /-- The `changeLevel` map is injective (except in the degenerate case `m = 0`). -/ lemma changeLevel_injective {m : ℕ} [NeZero m] (hm : n ∣ m) : Function.Injective (changeLevel (R := R) hm) := by intro _ _ h ext1 y
Mathlib/NumberTheory/DirichletCharacter/Basic.lean
66
73
/- Copyright (c) 2018 Simon Hudon. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Simon Hudon -/ import Mathlib.Control.Applicative import Mathlib.Control.Traversable.Basic import Mathlib.Data.List.Forall2 import Mathlib.Data.Set.Functor /-! # LawfulTraversable instances This file provides instances of `LawfulTraversable` for types from the core library: `Option`, `List` and `Sum`. -/ universe u v section Option open Functor variable {F G : Type u → Type u} variable [Applicative F] [Applicative G] variable [LawfulApplicative G] theorem Option.id_traverse {α} (x : Option α) : Option.traverse (pure : α → Id α) x = x := by cases x <;> rfl theorem Option.comp_traverse {α β γ} (f : β → F γ) (g : α → G β) (x : Option α) : Option.traverse (Comp.mk ∘ (f <$> ·) ∘ g) x = Comp.mk (Option.traverse f <$> Option.traverse g x) := by cases x <;> (simp! [functor_norm] <;> rfl) theorem Option.traverse_eq_map_id {α β} (f : α → β) (x : Option α) : Option.traverse ((pure : _ → Id _) ∘ f) x = (pure : _ → Id _) (f <$> x) := by cases x <;> rfl variable (η : ApplicativeTransformation F G) theorem Option.naturality [LawfulApplicative F] {α β} (f : α → F β) (x : Option α) : η (Option.traverse f x) = Option.traverse (@η _ ∘ f) x := by -- Porting note: added `ApplicativeTransformation` theorems rcases x with - | x <;> simp! [*, functor_norm, ApplicativeTransformation.preserves_map, ApplicativeTransformation.preserves_seq, ApplicativeTransformation.preserves_pure] end Option instance : LawfulTraversable Option := { show LawfulMonad Option from inferInstance with id_traverse := Option.id_traverse comp_traverse := Option.comp_traverse traverse_eq_map_id := Option.traverse_eq_map_id naturality := fun η _ _ f x => Option.naturality η f x } namespace List variable {F G : Type u → Type u} variable [Applicative F] [Applicative G] section variable [LawfulApplicative G] open Applicative Functor List protected theorem id_traverse {α} (xs : List α) : List.traverse (pure : α → Id α) xs = xs := by induction xs <;> simp! [*, List.traverse, functor_norm]; rfl protected theorem comp_traverse {α β γ} (f : β → F γ) (g : α → G β) (x : List α) : List.traverse (Comp.mk ∘ (f <$> ·) ∘ g) x = Comp.mk (List.traverse f <$> List.traverse g x) := by induction x <;> simp! [*, functor_norm] <;> rfl protected theorem traverse_eq_map_id {α β} (f : α → β) (x : List α) : List.traverse ((pure : _ → Id _) ∘ f) x = (pure : _ → Id _) (f <$> x) := by induction x <;> simp! [*, functor_norm]; rfl variable [LawfulApplicative F] (η : ApplicativeTransformation F G) protected theorem naturality {α β} (f : α → F β) (x : List α) : η (List.traverse f x) = List.traverse (@η _ ∘ f) x := by -- Porting note: added `ApplicativeTransformation` theorems induction x <;> simp! [*, functor_norm, ApplicativeTransformation.preserves_map, ApplicativeTransformation.preserves_seq, ApplicativeTransformation.preserves_pure] instance : LawfulTraversable.{u} List := { show LawfulMonad List from inferInstance with id_traverse := List.id_traverse comp_traverse := List.comp_traverse traverse_eq_map_id := List.traverse_eq_map_id naturality := List.naturality } end section Traverse variable {α' β' : Type u} (f : α' → F β') @[simp] theorem traverse_nil : traverse f ([] : List α') = (pure [] : F (List β')) := rfl @[simp] theorem traverse_cons (a : α') (l : List α') : traverse f (a :: l) = (· :: ·) <$> f a <*> traverse f l := rfl variable [LawfulApplicative F] @[simp] theorem traverse_append : ∀ as bs : List α', traverse f (as ++ bs) = (· ++ ·) <$> traverse f as <*> traverse f bs | [], bs => by simp [functor_norm] | a :: as, bs => by simp [traverse_append as bs, functor_norm]; congr theorem mem_traverse {f : α' → Set β'} : ∀ (l : List α') (n : List β'), n ∈ traverse f l ↔ Forall₂ (fun b a => b ∈ f a) n l | [], [] => by simp | a :: as, [] => by simp | [], b :: bs => by simp | a :: as, b :: bs => by simp [mem_traverse as bs] end Traverse end List namespace Sum section Traverse variable {σ : Type u} variable {F G : Type u → Type u} variable [Applicative F] [Applicative G] open Applicative Functor protected theorem traverse_map {α β γ : Type u} (g : α → β) (f : β → G γ) (x : σ ⊕ α) : Sum.traverse f (g <$> x) = Sum.traverse (f ∘ g) x := by cases x <;> simp [Sum.traverse, id_map, functor_norm] <;> rfl protected theorem id_traverse {σ α} (x : σ ⊕ α) : Sum.traverse (pure : α → Id α) x = x := by cases x <;> rfl variable [LawfulApplicative G] protected theorem comp_traverse {α β γ : Type u} (f : β → F γ) (g : α → G β) (x : σ ⊕ α) : Sum.traverse (Comp.mk ∘ (f <$> ·) ∘ g) x = Comp.mk.{u} (Sum.traverse f <$> Sum.traverse g x) := by cases x <;> (simp! [Sum.traverse, map_id, functor_norm] <;> rfl) protected theorem traverse_eq_map_id {α β} (f : α → β) (x : σ ⊕ α) : Sum.traverse ((pure : _ → Id _) ∘ f) x = (pure : _ → Id _) (f <$> x) := by induction x <;> simp! [*, functor_norm] <;> rfl protected theorem map_traverse {α β γ} (g : α → G β) (f : β → γ) (x : σ ⊕ α) : (f <$> ·) <$> Sum.traverse g x = Sum.traverse (f <$> g ·) x := by cases x <;> simp [Sum.traverse, id_map, functor_norm] <;> congr
variable [LawfulApplicative F] (η : ApplicativeTransformation F G)
Mathlib/Control/Traversable/Instances.lean
160
161
/- Copyright (c) 2020 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou -/ import Mathlib.Data.Set.Order import Mathlib.Order.Bounds.Basic import Mathlib.Order.Interval.Set.Image import Mathlib.Order.Interval.Set.LinearOrder import Mathlib.Tactic.Common /-! # Intervals without endpoints ordering In any lattice `α`, we define `uIcc a b` to be `Icc (a ⊓ b) (a ⊔ b)`, which in a linear order is the set of elements lying between `a` and `b`. `Icc a b` requires the assumption `a ≤ b` to be meaningful, which is sometimes inconvenient. The interval as defined in this file is always the set of things lying between `a` and `b`, regardless of the relative order of `a` and `b`. For real numbers, `uIcc a b` is the same as `segment ℝ a b`. In a product or pi type, `uIcc a b` is the smallest box containing `a` and `b`. For example, `uIcc (1, -1) (-1, 1) = Icc (-1, -1) (1, 1)` is the square of vertices `(1, -1)`, `(-1, -1)`, `(-1, 1)`, `(1, 1)`. In `Finset α` (seen as a hypercube of dimension `Fintype.card α`), `uIcc a b` is the smallest subcube containing both `a` and `b`. ## Notation We use the localized notation `[[a, b]]` for `uIcc a b`. One can open the locale `Interval` to make the notation available. -/ open Function open OrderDual (toDual ofDual) variable {α β : Type*} namespace Set section Lattice variable [Lattice α] [Lattice β] {a a₁ a₂ b b₁ b₂ x : α} /-- `uIcc a b` is the set of elements lying between `a` and `b`, with `a` and `b` included. Note that we define it more generally in a lattice as `Set.Icc (a ⊓ b) (a ⊔ b)`. In a product type, `uIcc` corresponds to the bounding box of the two elements. -/ def uIcc (a b : α) : Set α := Icc (a ⊓ b) (a ⊔ b) /-- `[[a, b]]` denotes the set of elements lying between `a` and `b`, inclusive. -/ scoped[Interval] notation "[[" a ", " b "]]" => Set.uIcc a b open Interval @[simp] lemma uIcc_toDual (a b : α) : [[toDual a, toDual b]] = ofDual ⁻¹' [[a, b]] := -- Note: needed to hint `(α := α)` after https://github.com/leanprover-community/mathlib4/pull/8386 (elaboration order?) Icc_toDual (α := α) @[deprecated (since := "2025-03-20")] alias dual_uIcc := uIcc_toDual @[simp] theorem uIcc_ofDual (a b : αᵒᵈ) : [[ofDual a, ofDual b]] = toDual ⁻¹' [[a, b]] := Icc_ofDual @[simp] lemma uIcc_of_le (h : a ≤ b) : [[a, b]] = Icc a b := by rw [uIcc, inf_eq_left.2 h, sup_eq_right.2 h] @[simp] lemma uIcc_of_ge (h : b ≤ a) : [[a, b]] = Icc b a := by rw [uIcc, inf_eq_right.2 h, sup_eq_left.2 h] lemma uIcc_comm (a b : α) : [[a, b]] = [[b, a]] := by simp_rw [uIcc, inf_comm, sup_comm] lemma uIcc_of_lt (h : a < b) : [[a, b]] = Icc a b := uIcc_of_le h.le lemma uIcc_of_gt (h : b < a) : [[a, b]] = Icc b a := uIcc_of_ge h.le lemma uIcc_self : [[a, a]] = {a} := by simp [uIcc] @[simp] lemma nonempty_uIcc : [[a, b]].Nonempty := nonempty_Icc.2 inf_le_sup lemma Icc_subset_uIcc : Icc a b ⊆ [[a, b]] := Icc_subset_Icc inf_le_left le_sup_right lemma Icc_subset_uIcc' : Icc b a ⊆ [[a, b]] := Icc_subset_Icc inf_le_right le_sup_left @[simp] lemma left_mem_uIcc : a ∈ [[a, b]] := ⟨inf_le_left, le_sup_left⟩ @[simp] lemma right_mem_uIcc : b ∈ [[a, b]] := ⟨inf_le_right, le_sup_right⟩ lemma mem_uIcc_of_le (ha : a ≤ x) (hb : x ≤ b) : x ∈ [[a, b]] := Icc_subset_uIcc ⟨ha, hb⟩ lemma mem_uIcc_of_ge (hb : b ≤ x) (ha : x ≤ a) : x ∈ [[a, b]] := Icc_subset_uIcc' ⟨hb, ha⟩ lemma uIcc_subset_uIcc (h₁ : a₁ ∈ [[a₂, b₂]]) (h₂ : b₁ ∈ [[a₂, b₂]]) : [[a₁, b₁]] ⊆ [[a₂, b₂]] := Icc_subset_Icc (le_inf h₁.1 h₂.1) (sup_le h₁.2 h₂.2) lemma uIcc_subset_Icc (ha : a₁ ∈ Icc a₂ b₂) (hb : b₁ ∈ Icc a₂ b₂) : [[a₁, b₁]] ⊆ Icc a₂ b₂ := Icc_subset_Icc (le_inf ha.1 hb.1) (sup_le ha.2 hb.2) lemma uIcc_subset_uIcc_iff_mem : [[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ a₁ ∈ [[a₂, b₂]] ∧ b₁ ∈ [[a₂, b₂]] := Iff.intro (fun h => ⟨h left_mem_uIcc, h right_mem_uIcc⟩) fun h => uIcc_subset_uIcc h.1 h.2 lemma uIcc_subset_uIcc_iff_le' : [[a₁, b₁]] ⊆ [[a₂, b₂]] ↔ a₂ ⊓ b₂ ≤ a₁ ⊓ b₁ ∧ a₁ ⊔ b₁ ≤ a₂ ⊔ b₂ := Icc_subset_Icc_iff inf_le_sup lemma uIcc_subset_uIcc_right (h : x ∈ [[a, b]]) : [[x, b]] ⊆ [[a, b]] := uIcc_subset_uIcc h right_mem_uIcc lemma uIcc_subset_uIcc_left (h : x ∈ [[a, b]]) : [[a, x]] ⊆ [[a, b]] := uIcc_subset_uIcc left_mem_uIcc h lemma bdd_below_bdd_above_iff_subset_uIcc (s : Set α) : BddBelow s ∧ BddAbove s ↔ ∃ a b, s ⊆ [[a, b]] := bddBelow_bddAbove_iff_subset_Icc.trans ⟨fun ⟨a, b, h⟩ => ⟨a, b, fun _ hx => Icc_subset_uIcc (h hx)⟩, fun ⟨_, _, h⟩ => ⟨_, _, h⟩⟩ section Prod @[simp] theorem uIcc_prod_uIcc (a₁ a₂ : α) (b₁ b₂ : β) : [[a₁, a₂]] ×ˢ [[b₁, b₂]] = [[(a₁, b₁), (a₂, b₂)]] := Icc_prod_Icc _ _ _ _ theorem uIcc_prod_eq (a b : α × β) : [[a, b]] = [[a.1, b.1]] ×ˢ [[a.2, b.2]] := by simp end Prod end Lattice open Interval section DistribLattice variable [DistribLattice α] {a b c : α} lemma eq_of_mem_uIcc_of_mem_uIcc (ha : a ∈ [[b, c]]) (hb : b ∈ [[a, c]]) : a = b := eq_of_inf_eq_sup_eq (inf_congr_right ha.1 hb.1) <| sup_congr_right ha.2 hb.2 lemma eq_of_mem_uIcc_of_mem_uIcc' : b ∈ [[a, c]] → c ∈ [[a, b]] → b = c := by simpa only [uIcc_comm a] using eq_of_mem_uIcc_of_mem_uIcc lemma uIcc_injective_right (a : α) : Injective fun b => uIcc b a := fun b c h => by rw [Set.ext_iff] at h exact eq_of_mem_uIcc_of_mem_uIcc ((h _).1 left_mem_uIcc) ((h _).2 left_mem_uIcc) lemma uIcc_injective_left (a : α) : Injective (uIcc a) := by simpa only [uIcc_comm] using uIcc_injective_right a end DistribLattice section LinearOrder variable [LinearOrder α] section Lattice variable [Lattice β] {f : α → β} {a b : α} lemma _root_.MonotoneOn.mapsTo_uIcc (hf : MonotoneOn f (uIcc a b)) : MapsTo f (uIcc a b) (uIcc (f a) (f b)) := by rw [uIcc, uIcc, ← hf.map_sup, ← hf.map_inf] <;> apply_rules [left_mem_uIcc, right_mem_uIcc, hf.mapsTo_Icc] lemma _root_.AntitoneOn.mapsTo_uIcc (hf : AntitoneOn f (uIcc a b)) : MapsTo f (uIcc a b) (uIcc (f a) (f b)) := by rw [uIcc, uIcc, ← hf.map_sup, ← hf.map_inf] <;> apply_rules [left_mem_uIcc, right_mem_uIcc, hf.mapsTo_Icc] lemma _root_.Monotone.mapsTo_uIcc (hf : Monotone f) : MapsTo f (uIcc a b) (uIcc (f a) (f b)) := (hf.monotoneOn _).mapsTo_uIcc lemma _root_.Antitone.mapsTo_uIcc (hf : Antitone f) : MapsTo f (uIcc a b) (uIcc (f a) (f b)) := (hf.antitoneOn _).mapsTo_uIcc lemma _root_.MonotoneOn.image_uIcc_subset (hf : MonotoneOn f (uIcc a b)) : f '' uIcc a b ⊆ uIcc (f a) (f b) := hf.mapsTo_uIcc.image_subset lemma _root_.AntitoneOn.image_uIcc_subset (hf : AntitoneOn f (uIcc a b)) : f '' uIcc a b ⊆ uIcc (f a) (f b) := hf.mapsTo_uIcc.image_subset lemma _root_.Monotone.image_uIcc_subset (hf : Monotone f) : f '' uIcc a b ⊆ uIcc (f a) (f b) := (hf.monotoneOn _).image_uIcc_subset
lemma _root_.Antitone.image_uIcc_subset (hf : Antitone f) : f '' uIcc a b ⊆ uIcc (f a) (f b) := (hf.antitoneOn _).image_uIcc_subset end Lattice
Mathlib/Order/Interval/Set/UnorderedInterval.lean
190
193
/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.Multiset.Dedup /-! # The fold operation for a commutative associative operation over a multiset. -/ namespace Multiset variable {α β : Type*} /-! ### fold -/ section Fold variable (op : α → α → α) [hc : Std.Commutative op] [ha : Std.Associative op] local notation a " * " b => op a b /-- `fold op b s` folds a commutative associative operation `op` over the multiset `s`. -/ def fold : α → Multiset α → α := foldr op theorem fold_eq_foldr (b : α) (s : Multiset α) : fold op b s = foldr op b s := rfl @[simp] theorem coe_fold_r (b : α) (l : List α) : fold op b l = l.foldr op b := rfl theorem coe_fold_l (b : α) (l : List α) : fold op b l = l.foldl op b := (coe_foldr_swap op b l).trans <| by simp [hc.comm] theorem fold_eq_foldl (b : α) (s : Multiset α) : fold op b s = foldl op b s := Quot.inductionOn s fun _ => coe_fold_l _ _ _ @[simp] theorem fold_zero (b : α) : (0 : Multiset α).fold op b = b := rfl @[simp] theorem fold_cons_left : ∀ (b a : α) (s : Multiset α), (a ::ₘ s).fold op b = a * s.fold op b := foldr_cons _ theorem fold_cons_right (b a : α) (s : Multiset α) : (a ::ₘ s).fold op b = s.fold op b * a := by simp [hc.comm] theorem fold_cons'_right (b a : α) (s : Multiset α) : (a ::ₘ s).fold op b = s.fold op (b * a) := by rw [fold_eq_foldl, foldl_cons, ← fold_eq_foldl] theorem fold_cons'_left (b a : α) (s : Multiset α) : (a ::ₘ s).fold op b = s.fold op (a * b) := by rw [fold_cons'_right, hc.comm] theorem fold_add (b₁ b₂ : α) (s₁ s₂ : Multiset α) : (s₁ + s₂).fold op (b₁ * b₂) = s₁.fold op b₁ * s₂.fold op b₂ := Multiset.induction_on s₂ (by rw [Multiset.add_zero, fold_zero, ← fold_cons'_right, ← fold_cons_right op]) (fun a b h => by rw [fold_cons_left, add_cons, fold_cons_left, h, ← ha.assoc, hc.comm a, ha.assoc]) theorem fold_singleton (b a : α) : ({a} : Multiset α).fold op b = a * b := foldr_singleton _ _ _ theorem fold_distrib {f g : β → α} (u₁ u₂ : α) (s : Multiset β) : (s.map fun x => f x * g x).fold op (u₁ * u₂) = (s.map f).fold op u₁ * (s.map g).fold op u₂ := Multiset.induction_on s (by simp) (fun a b h => by rw [map_cons, fold_cons_left, h, map_cons, fold_cons_left, map_cons, fold_cons_right, ha.assoc, ← ha.assoc (g a), hc.comm (g a), ha.assoc, hc.comm (g a), ha.assoc]) theorem fold_hom {op' : β → β → β} [Std.Commutative op'] [Std.Associative op'] {m : α → β} (hm : ∀ x y, m (op x y) = op' (m x) (m y)) (b : α) (s : Multiset α) : (s.map m).fold op' (m b) = m (s.fold op b) := Multiset.induction_on s (by simp) (by simp +contextual [hm]) theorem fold_union_inter [DecidableEq α] (s₁ s₂ : Multiset α) (b₁ b₂ : α) : ((s₁ ∪ s₂).fold op b₁ * (s₁ ∩ s₂).fold op b₂) = s₁.fold op b₁ * s₂.fold op b₂ := by rw [← fold_add op, union_add_inter, fold_add op] @[simp] theorem fold_dedup_idem [DecidableEq α] [hi : Std.IdempotentOp op] (s : Multiset α) (b : α) : (dedup s).fold op b = s.fold op b := Multiset.induction_on s (by simp) fun a s IH => by by_cases h : a ∈ s <;> simp [IH, h] show fold op b s = op a (fold op b s) rw [← cons_erase h, fold_cons_left, ← ha.assoc, hi.idempotent] end Fold end Multiset
Mathlib/Data/Multiset/Fold.lean
126
135
/- Copyright (c) 2023 Kyle Miller, Rémi Bottinelli. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kyle Miller, Rémi Bottinelli -/ import Mathlib.Combinatorics.SimpleGraph.Path import Mathlib.Data.Set.Card /-! # Connectivity of subgraphs and induced graphs ## Main definitions * `SimpleGraph.Subgraph.Preconnected` and `SimpleGraph.Subgraph.Connected` give subgraphs connectivity predicates via `SimpleGraph.subgraph.coe`. -/ namespace SimpleGraph universe u v variable {V : Type u} {V' : Type v} {G : SimpleGraph V} {G' : SimpleGraph V'} namespace Subgraph /-- A subgraph is preconnected if it is preconnected when coerced to be a simple graph. Note: This is a structure to make it so one can be precise about how dot notation resolves. -/ protected structure Preconnected (H : G.Subgraph) : Prop where protected coe : H.coe.Preconnected instance {H : G.Subgraph} : Coe H.Preconnected H.coe.Preconnected := ⟨Preconnected.coe⟩ instance {H : G.Subgraph} : CoeFun H.Preconnected (fun _ => ∀ u v : H.verts, H.coe.Reachable u v) := ⟨fun h => h.coe⟩ protected lemma preconnected_iff {H : G.Subgraph} : H.Preconnected ↔ H.coe.Preconnected := ⟨fun ⟨h⟩ => h, .mk⟩ /-- A subgraph is connected if it is connected when coerced to be a simple graph. Note: This is a structure to make it so one can be precise about how dot notation resolves. -/ protected structure Connected (H : G.Subgraph) : Prop where protected coe : H.coe.Connected instance {H : G.Subgraph} : Coe H.Connected H.coe.Connected := ⟨Connected.coe⟩ instance {H : G.Subgraph} : CoeFun H.Connected (fun _ => ∀ u v : H.verts, H.coe.Reachable u v) := ⟨fun h => h.coe⟩ protected lemma connected_iff' {H : G.Subgraph} : H.Connected ↔ H.coe.Connected := ⟨fun ⟨h⟩ => h, .mk⟩ protected lemma connected_iff {H : G.Subgraph} : H.Connected ↔ H.Preconnected ∧ H.verts.Nonempty := by rw [H.connected_iff', connected_iff, H.preconnected_iff, Set.nonempty_coe_sort] protected lemma Connected.preconnected {H : G.Subgraph} (h : H.Connected) : H.Preconnected := by rw [H.connected_iff] at h; exact h.1 protected lemma Connected.nonempty {H : G.Subgraph} (h : H.Connected) : H.verts.Nonempty := by rw [H.connected_iff] at h; exact h.2 theorem singletonSubgraph_connected {v : V} : (G.singletonSubgraph v).Connected := by refine ⟨⟨?_⟩⟩ rintro ⟨a, ha⟩ ⟨b, hb⟩ simp only [singletonSubgraph_verts, Set.mem_singleton_iff] at ha hb subst_vars rfl @[simp] theorem subgraphOfAdj_connected {v w : V} (hvw : G.Adj v w) : (G.subgraphOfAdj hvw).Connected := by refine ⟨⟨?_⟩⟩ rintro ⟨a, ha⟩ ⟨b, hb⟩ simp only [subgraphOfAdj_verts, Set.mem_insert_iff, Set.mem_singleton_iff] at ha hb obtain rfl | rfl := ha <;> obtain rfl | rfl := hb <;> first | rfl | (apply Adj.reachable; simp) lemma top_induce_pair_connected_of_adj {u v : V} (huv : G.Adj u v) : ((⊤ : G.Subgraph).induce {u, v}).Connected := by rw [← subgraphOfAdj_eq_induce huv] exact subgraphOfAdj_connected huv @[mono] protected lemma Connected.mono {H H' : G.Subgraph} (hle : H ≤ H') (hv : H.verts = H'.verts) (h : H.Connected) : H'.Connected := by rw [← Subgraph.copy_eq H' H.verts hv H'.Adj rfl] refine ⟨h.coe.mono ?_⟩ rintro ⟨v, hv⟩ ⟨w, hw⟩ hvw exact hle.2 hvw protected lemma Connected.mono' {H H' : G.Subgraph} (hle : ∀ v w, H.Adj v w → H'.Adj v w) (hv : H.verts = H'.verts) (h : H.Connected) : H'.Connected := by exact h.mono ⟨hv.le, hle⟩ hv protected lemma Connected.sup {H K : G.Subgraph} (hH : H.Connected) (hK : K.Connected) (hn : (H ⊓ K).verts.Nonempty) : (H ⊔ K).Connected := by rw [Subgraph.connected_iff', connected_iff_exists_forall_reachable] obtain ⟨u, hu, hu'⟩ := hn exists ⟨u, Or.inl hu⟩ rintro ⟨v, (hv|hv)⟩ · exact Reachable.map (Subgraph.inclusion (le_sup_left : H ≤ H ⊔ K)) (hH ⟨u, hu⟩ ⟨v, hv⟩) · exact Reachable.map (Subgraph.inclusion (le_sup_right : K ≤ H ⊔ K)) (hK ⟨u, hu'⟩ ⟨v, hv⟩) /-- This lemma establishes a condition under which a subgraph is the same as a connected component.
Note the asymmetry in the hypothesis `h`: `v` is in `H.verts`, but `w` is not required to be. -/ lemma Connected.exists_verts_eq_connectedComponentSupp {H : Subgraph G} (hc : H.Connected) (h : ∀ v ∈ H.verts, ∀ w, G.Adj v w → H.Adj v w) : ∃ c : G.ConnectedComponent, H.verts = c.supp := by rw [SimpleGraph.ConnectedComponent.exists] obtain ⟨v, hv⟩ := hc.nonempty use v
Mathlib/Combinatorics/SimpleGraph/Connectivity/Subgraph.lean
109
116
/- Copyright (c) 2022 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn -/ import Mathlib.MeasureTheory.Integral.IntegrableOn /-! # Locally integrable functions A function is called *locally integrable* (`MeasureTheory.LocallyIntegrable`) if it is integrable on a neighborhood of every point. More generally, it is *locally integrable on `s`* if it is locally integrable on a neighbourhood within `s` of any point of `s`. This file contains properties of locally integrable functions, and integrability results on compact sets. ## Main statements * `Continuous.locallyIntegrable`: A continuous function is locally integrable. * `ContinuousOn.locallyIntegrableOn`: A function which is continuous on `s` is locally integrable on `s`. -/ open MeasureTheory MeasureTheory.Measure Set Function TopologicalSpace Bornology open scoped Topology Interval ENNReal variable {X Y E F R : Type*} [MeasurableSpace X] [TopologicalSpace X] variable [MeasurableSpace Y] [TopologicalSpace Y] variable [NormedAddCommGroup E] [NormedAddCommGroup F] {f g : X → E} {μ : Measure X} {s : Set X} namespace MeasureTheory section LocallyIntegrableOn /-- A function `f : X → E` is *locally integrable on s*, for `s ⊆ X`, if for every `x ∈ s` there is a neighbourhood of `x` within `s` on which `f` is integrable. (Note this is, in general, strictly weaker than local integrability with respect to `μ.restrict s`.) -/ def LocallyIntegrableOn (f : X → E) (s : Set X) (μ : Measure X := by volume_tac) : Prop := ∀ x : X, x ∈ s → IntegrableAtFilter f (𝓝[s] x) μ theorem LocallyIntegrableOn.mono_set (hf : LocallyIntegrableOn f s μ) {t : Set X} (hst : t ⊆ s) : LocallyIntegrableOn f t μ := fun x hx => (hf x <| hst hx).filter_mono (nhdsWithin_mono x hst) theorem LocallyIntegrableOn.norm (hf : LocallyIntegrableOn f s μ) : LocallyIntegrableOn (fun x => ‖f x‖) s μ := fun t ht => let ⟨U, hU_nhd, hU_int⟩ := hf t ht ⟨U, hU_nhd, hU_int.norm⟩ theorem LocallyIntegrableOn.mono (hf : LocallyIntegrableOn f s μ) {g : X → F} (hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) : LocallyIntegrableOn g s μ := by intro x hx rcases hf x hx with ⟨t, t_mem, ht⟩ exact ⟨t, t_mem, Integrable.mono ht hg.restrict (ae_restrict_of_ae h)⟩ theorem IntegrableOn.locallyIntegrableOn (hf : IntegrableOn f s μ) : LocallyIntegrableOn f s μ := fun _ _ => ⟨s, self_mem_nhdsWithin, hf⟩ /-- If a function is locally integrable on a compact set, then it is integrable on that set. -/ theorem LocallyIntegrableOn.integrableOn_isCompact (hf : LocallyIntegrableOn f s μ) (hs : IsCompact s) : IntegrableOn f s μ := IsCompact.induction_on hs integrableOn_empty (fun _u _v huv hv => hv.mono_set huv) (fun _u _v hu hv => integrableOn_union.mpr ⟨hu, hv⟩) hf theorem LocallyIntegrableOn.integrableOn_compact_subset (hf : LocallyIntegrableOn f s μ) {t : Set X} (hst : t ⊆ s) (ht : IsCompact t) : IntegrableOn f t μ := (hf.mono_set hst).integrableOn_isCompact ht /-- If a function `f` is locally integrable on a set `s` in a second countable topological space, then there exist countably many open sets `u` covering `s` such that `f` is integrable on each set `u ∩ s`. -/ theorem LocallyIntegrableOn.exists_countable_integrableOn [SecondCountableTopology X] (hf : LocallyIntegrableOn f s μ) : ∃ T : Set (Set X), T.Countable ∧ (∀ u ∈ T, IsOpen u) ∧ (s ⊆ ⋃ u ∈ T, u) ∧ (∀ u ∈ T, IntegrableOn f (u ∩ s) μ) := by have : ∀ x : s, ∃ u, IsOpen u ∧ x.1 ∈ u ∧ IntegrableOn f (u ∩ s) μ := by rintro ⟨x, hx⟩ rcases hf x hx with ⟨t, ht, h't⟩ rcases mem_nhdsWithin.1 ht with ⟨u, u_open, x_mem, u_sub⟩ exact ⟨u, u_open, x_mem, h't.mono_set u_sub⟩ choose u u_open xu hu using this obtain ⟨T, T_count, hT⟩ : ∃ T : Set s, T.Countable ∧ s ⊆ ⋃ i ∈ T, u i := by have : s ⊆ ⋃ x : s, u x := fun y hy => mem_iUnion_of_mem ⟨y, hy⟩ (xu ⟨y, hy⟩) obtain ⟨T, hT_count, hT_un⟩ := isOpen_iUnion_countable u u_open exact ⟨T, hT_count, by rwa [hT_un]⟩ refine ⟨u '' T, T_count.image _, ?_, by rwa [biUnion_image], ?_⟩ · rintro v ⟨w, -, rfl⟩ exact u_open _ · rintro v ⟨w, -, rfl⟩ exact hu _ /-- If a function `f` is locally integrable on a set `s` in a second countable topological space, then there exists a sequence of open sets `u n` covering `s` such that `f` is integrable on each set `u n ∩ s`. -/ theorem LocallyIntegrableOn.exists_nat_integrableOn [SecondCountableTopology X] (hf : LocallyIntegrableOn f s μ) : ∃ u : ℕ → Set X, (∀ n, IsOpen (u n)) ∧ (s ⊆ ⋃ n, u n) ∧ (∀ n, IntegrableOn f (u n ∩ s) μ) := by rcases hf.exists_countable_integrableOn with ⟨T, T_count, T_open, sT, hT⟩ let T' : Set (Set X) := insert ∅ T have T'_count : T'.Countable := Countable.insert ∅ T_count have T'_ne : T'.Nonempty := by simp only [T', insert_nonempty] rcases T'_count.exists_eq_range T'_ne with ⟨u, hu⟩ refine ⟨u, ?_, ?_, ?_⟩ · intro n have : u n ∈ T' := by rw [hu]; exact mem_range_self n rcases mem_insert_iff.1 this with h|h · rw [h] exact isOpen_empty · exact T_open _ h · intro x hx obtain ⟨v, hv, h'v⟩ : ∃ v, v ∈ T ∧ x ∈ v := by simpa only [mem_iUnion, exists_prop] using sT hx have : v ∈ range u := by rw [← hu]; exact subset_insert ∅ T hv obtain ⟨n, rfl⟩ : ∃ n, u n = v := by simpa only [mem_range] using this exact mem_iUnion_of_mem _ h'v · intro n have : u n ∈ T' := by rw [hu]; exact mem_range_self n rcases mem_insert_iff.1 this with h|h · simp only [h, empty_inter, integrableOn_empty] · exact hT _ h theorem LocallyIntegrableOn.aestronglyMeasurable [SecondCountableTopology X] (hf : LocallyIntegrableOn f s μ) : AEStronglyMeasurable f (μ.restrict s) := by rcases hf.exists_nat_integrableOn with ⟨u, -, su, hu⟩ have : s = ⋃ n, u n ∩ s := by rw [← iUnion_inter]; exact (inter_eq_right.mpr su).symm rw [this, aestronglyMeasurable_iUnion_iff] exact fun i : ℕ => (hu i).aestronglyMeasurable /-- If `s` is locally closed (e.g. open or closed), then `f` is locally integrable on `s` iff it is integrable on every compact subset contained in `s`. -/ theorem locallyIntegrableOn_iff [LocallyCompactSpace X] (hs : IsLocallyClosed s) : LocallyIntegrableOn f s μ ↔ ∀ (k : Set X), k ⊆ s → IsCompact k → IntegrableOn f k μ := by refine ⟨fun hf k hk ↦ hf.integrableOn_compact_subset hk, fun hf x hx ↦ ?_⟩ rcases hs with ⟨U, Z, hU, hZ, rfl⟩ rcases exists_compact_subset hU hx.1 with ⟨K, hK, hxK, hKU⟩ rw [nhdsWithin_inter_of_mem (nhdsWithin_le_nhds <| hU.mem_nhds hx.1)] refine ⟨Z ∩ K, inter_mem_nhdsWithin _ (mem_interior_iff_mem_nhds.1 hxK), ?_⟩ exact hf (Z ∩ K) (fun y hy ↦ ⟨hKU hy.2, hy.1⟩) (.inter_left hK hZ) protected theorem LocallyIntegrableOn.add (hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) : LocallyIntegrableOn (f + g) s μ := fun x hx ↦ (hf x hx).add (hg x hx) protected theorem LocallyIntegrableOn.sub (hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) : LocallyIntegrableOn (f - g) s μ := fun x hx ↦ (hf x hx).sub (hg x hx) protected theorem LocallyIntegrableOn.neg (hf : LocallyIntegrableOn f s μ) : LocallyIntegrableOn (-f) s μ := fun x hx ↦ (hf x hx).neg end LocallyIntegrableOn /-- A function `f : X → E` is *locally integrable* if it is integrable on a neighborhood of every point. In particular, it is integrable on all compact sets, see `LocallyIntegrable.integrableOn_isCompact`. -/ def LocallyIntegrable (f : X → E) (μ : Measure X := by volume_tac) : Prop := ∀ x : X, IntegrableAtFilter f (𝓝 x) μ theorem locallyIntegrable_comap (hs : MeasurableSet s) : LocallyIntegrable (fun x : s ↦ f x) (μ.comap Subtype.val) ↔ LocallyIntegrableOn f s μ := by simp_rw [LocallyIntegrableOn, Subtype.forall', ← map_nhds_subtype_val] exact forall_congr' fun _ ↦ (MeasurableEmbedding.subtype_coe hs).integrableAtFilter_iff_comap.symm theorem locallyIntegrableOn_univ : LocallyIntegrableOn f univ μ ↔ LocallyIntegrable f μ := by simp only [LocallyIntegrableOn, nhdsWithin_univ, mem_univ, true_imp_iff]; rfl theorem LocallyIntegrable.locallyIntegrableOn (hf : LocallyIntegrable f μ) (s : Set X) : LocallyIntegrableOn f s μ := fun x _ => (hf x).filter_mono nhdsWithin_le_nhds theorem Integrable.locallyIntegrable (hf : Integrable f μ) : LocallyIntegrable f μ := fun _ => hf.integrableAtFilter _ theorem LocallyIntegrable.mono (hf : LocallyIntegrable f μ) {g : X → F} (hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) : LocallyIntegrable g μ := by rw [← locallyIntegrableOn_univ] at hf ⊢ exact hf.mono hg h
/-- If `f` is locally integrable with respect to `μ.restrict s`, it is locally integrable on `s`. (See `locallyIntegrableOn_iff_locallyIntegrable_restrict` for an iff statement when `s` is closed.) -/
Mathlib/MeasureTheory/Function/LocallyIntegrable.lean
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/- 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.Data.List.Defs import Mathlib.Data.Nat.Basic import Mathlib.Tactic.Common /-! # Streams a.k.a. infinite lists a.k.a. infinite sequences -/ open Nat Function Option namespace Stream' universe u v w variable {α : Type u} {β : Type v} {δ : Type w} variable (m n : ℕ) (x y : List α) (a b : Stream' α) instance [Inhabited α] : Inhabited (Stream' α) := ⟨Stream'.const default⟩ @[simp] protected theorem eta (s : Stream' α) : head s :: tail s = s := funext fun i => by cases i <;> rfl /-- Alias for `Stream'.eta` to match `List` API. -/ alias cons_head_tail := Stream'.eta @[ext] protected theorem ext {s₁ s₂ : Stream' α} : (∀ n, get s₁ n = get s₂ n) → s₁ = s₂ := fun h => funext h @[simp] theorem get_zero_cons (a : α) (s : Stream' α) : get (a::s) 0 = a := rfl @[simp] theorem head_cons (a : α) (s : Stream' α) : head (a::s) = a := rfl @[simp] theorem tail_cons (a : α) (s : Stream' α) : tail (a::s) = s := rfl @[simp] theorem get_drop (n m : ℕ) (s : Stream' α) : get (drop m s) n = get s (m + n) := by rw [Nat.add_comm] rfl theorem tail_eq_drop (s : Stream' α) : tail s = drop 1 s := rfl @[simp] theorem drop_drop (n m : ℕ) (s : Stream' α) : drop n (drop m s) = drop (m + n) s := by ext; simp [Nat.add_assoc] @[simp] theorem get_tail {n : ℕ} {s : Stream' α} : s.tail.get n = s.get (n + 1) := rfl @[simp] theorem tail_drop' {i : ℕ} {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' {i : ℕ} {s : Stream' α} : drop i (tail s) = s.drop (i + 1) := rfl theorem tail_drop (n : ℕ) (s : Stream' α) : tail (drop n s) = drop n (tail s) := by simp theorem get_succ (n : ℕ) (s : Stream' α) : get s (succ n) = get (tail s) n := rfl @[simp] theorem get_succ_cons (n : ℕ) (s : Stream' α) (x : α) : get (x :: s) n.succ = get s n := rfl @[simp] lemma get_cons_append_zero {a : α} {x : List α} {s : Stream' α} : (a :: x ++ₛ s).get 0 = a := rfl @[simp] lemma append_eq_cons {a : α} {as : Stream' α} : [a] ++ₛ as = a :: as := by rfl @[simp] theorem drop_zero {s : Stream' α} : s.drop 0 = s := rfl theorem drop_succ (n : ℕ) (s : Stream' α) : drop (succ n) s = drop n (tail s) := rfl theorem head_drop (a : Stream' α) (n : ℕ) : (a.drop n).head = a.get n := by simp 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]⟩ theorem cons_injective_left (s : Stream' α) : Function.Injective fun x => cons x s := cons_injective2.left _ theorem cons_injective_right (x : α) : Function.Injective (cons x) := cons_injective2.right _ theorem all_def (p : α → Prop) (s : Stream' α) : All p s = ∀ n, p (get s n) := rfl theorem any_def (p : α → Prop) (s : Stream' α) : Any p s = ∃ n, p (get s n) := rfl @[simp] theorem mem_cons (a : α) (s : Stream' α) : a ∈ a::s := Exists.intro 0 rfl 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]) theorem eq_or_mem_of_mem_cons {a b : α} {s : Stream' α} : (a ∈ b::s) → a = b ∨ a ∈ s := fun ⟨n, h⟩ => by rcases n with - | n' · left exact h · right rw [get_succ, tail_cons] at h exact ⟨n', h⟩ theorem mem_of_get_eq {n : ℕ} {s : Stream' α} {a : α} : a = get s n → a ∈ s := fun h => Exists.intro n h section Map variable (f : α → β) theorem drop_map (n : ℕ) (s : Stream' α) : drop n (map f s) = map f (drop n s) := Stream'.ext fun _ => rfl @[simp] theorem get_map (n : ℕ) (s : Stream' α) : get (map f s) n = f (get s n) := rfl theorem tail_map (s : Stream' α) : tail (map f s) = map f (tail s) := rfl @[simp] theorem head_map (s : Stream' α) : head (map f s) = f (head s) := rfl 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] 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 @[simp] theorem map_id (s : Stream' α) : map id s = s := rfl @[simp] theorem map_map (g : β → δ) (f : α → β) (s : Stream' α) : map g (map f s) = map (g ∘ f) s := rfl @[simp] theorem map_tail (s : Stream' α) : map f (tail s) = tail (map f s) := rfl 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]) 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⟩ end Map section Zip variable (f : α → β → δ) theorem drop_zip (n : ℕ) (s₁ : Stream' α) (s₂ : Stream' β) : drop n (zip f s₁ s₂) = zip f (drop n s₁) (drop n s₂) := Stream'.ext fun _ => rfl @[simp] theorem get_zip (n : ℕ) (s₁ : Stream' α) (s₂ : Stream' β) : get (zip f s₁ s₂) n = f (get s₁ n) (get s₂ n) := rfl theorem head_zip (s₁ : Stream' α) (s₂ : Stream' β) : head (zip f s₁ s₂) = f (head s₁) (head s₂) := rfl theorem tail_zip (s₁ : Stream' α) (s₂ : Stream' β) : tail (zip f s₁ s₂) = zip f (tail s₁) (tail s₂) := rfl 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 @[simp] theorem get_enum (s : Stream' α) (n : ℕ) : get (enum s) n = (n, s.get n) := rfl theorem enum_eq_zip (s : Stream' α) : enum s = zip Prod.mk nats s := rfl end Zip @[simp] theorem mem_const (a : α) : a ∈ const a := Exists.intro 0 rfl theorem const_eq (a : α) : const a = a::const a := by apply Stream'.ext; intro n cases n <;> rfl @[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 @[simp] theorem map_const (f : α → β) (a : α) : map f (const a) = const (f a) := rfl @[simp] theorem get_const (n : ℕ) (a : α) : get (const a) n = a := rfl @[simp] theorem drop_const (n : ℕ) (a : α) : drop n (const a) = const a := Stream'.ext fun _ => rfl @[simp] theorem head_iterate (f : α → α) (a : α) : head (iterate f a) = a := rfl theorem get_succ_iterate' (n : ℕ) (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'] 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 @[simp] theorem get_zero_iterate (f : α → α) (a : α) : get (iterate f a) 0 = a := rfl theorem get_succ_iterate (n : ℕ) (f : α → α) (a : α) : get (iterate f a) (succ n) = get (iterate f (f a)) n := by rw [get_succ, tail_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 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 -- 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) 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)) 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) @[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 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 section Corec theorem corec_def (f : α → β) (g : α → α) (a : α) : corec f g a = map f (iterate g a) := rfl theorem corec_eq (f : α → β) (g : α → α) (a : α) : corec f g a = f a :: corec f g (g a) := by rw [corec_def, map_eq, head_iterate, tail_iterate]; rfl theorem corec_id_id_eq_const (a : α) : corec id id a = const a := by rw [corec_def, map_id, iterate_id] theorem corec_id_f_eq_iterate (f : α → α) (a : α) : corec id f a = iterate f a := rfl end Corec section Corec' theorem corec'_eq (f : α → β × α) (a : α) : corec' f a = (f a).1 :: corec' f (f a).2 := corec_eq _ _ _ end Corec' theorem unfolds_eq (g : α → β) (f : α → α) (a : α) : unfolds g f a = g a :: unfolds g f (f a) := by unfold unfolds; rw [corec_eq] theorem get_unfolds_head_tail : ∀ (n : ℕ) (s : Stream' α), get (unfolds head tail s) n = get s n := by intro n; induction' n with n' ih · intro s rfl · intro s rw [get_succ, get_succ, unfolds_eq, tail_cons, ih] theorem unfolds_head_eq : ∀ s : Stream' α, unfolds head tail s = s := fun s => Stream'.ext fun n => get_unfolds_head_tail n s theorem interleave_eq (s₁ s₂ : Stream' α) : s₁ ⋈ s₂ = head s₁::head s₂::(tail s₁ ⋈ tail s₂) := by let t := tail s₁ ⋈ tail s₂ show s₁ ⋈ s₂ = head s₁::head s₂::t unfold interleave; unfold corecOn; rw [corec_eq]; dsimp; rw [corec_eq]; rfl theorem tail_interleave (s₁ s₂ : Stream' α) : tail (s₁ ⋈ s₂) = s₂ ⋈ tail s₁ := by unfold interleave corecOn; rw [corec_eq]; rfl theorem interleave_tail_tail (s₁ s₂ : Stream' α) : tail s₁ ⋈ tail s₂ = tail (tail (s₁ ⋈ s₂)) := by rw [interleave_eq s₁ s₂]; rfl theorem get_interleave_left : ∀ (n : ℕ) (s₁ s₂ : Stream' α), get (s₁ ⋈ s₂) (2 * n) = get s₁ n | 0, _, _ => rfl | n + 1, s₁, s₂ => by change get (s₁ ⋈ s₂) (succ (succ (2 * n))) = get s₁ (succ n) rw [get_succ, get_succ, interleave_eq, tail_cons, tail_cons] rw [get_interleave_left n (tail s₁) (tail s₂)] rfl theorem get_interleave_right : ∀ (n : ℕ) (s₁ s₂ : Stream' α), get (s₁ ⋈ s₂) (2 * n + 1) = get s₂ n | 0, _, _ => rfl | n + 1, s₁, s₂ => by change get (s₁ ⋈ s₂) (succ (succ (2 * n + 1))) = get s₂ (succ n) rw [get_succ, get_succ, interleave_eq, tail_cons, tail_cons, get_interleave_right n (tail s₁) (tail s₂)] rfl theorem mem_interleave_left {a : α} {s₁ : Stream' α} (s₂ : Stream' α) : a ∈ s₁ → a ∈ s₁ ⋈ s₂ := fun ⟨n, h⟩ => Exists.intro (2 * n) (by rw [h, get_interleave_left]) theorem mem_interleave_right {a : α} {s₁ : Stream' α} (s₂ : Stream' α) : a ∈ s₂ → a ∈ s₁ ⋈ s₂ := fun ⟨n, h⟩ => Exists.intro (2 * n + 1) (by rw [h, get_interleave_right]) theorem odd_eq (s : Stream' α) : odd s = even (tail s) := rfl @[simp] theorem head_even (s : Stream' α) : head (even s) = head s := rfl theorem tail_even (s : Stream' α) : tail (even s) = even (tail (tail s)) := by unfold even rw [corec_eq] rfl theorem even_cons_cons (a₁ a₂ : α) (s : Stream' α) : even (a₁::a₂::s) = a₁::even s := by unfold even rw [corec_eq]; rfl theorem even_tail (s : Stream' α) : even (tail s) = odd s := rfl theorem even_interleave (s₁ s₂ : Stream' α) : even (s₁ ⋈ s₂) = s₁ := eq_of_bisim (fun s₁' s₁ => ∃ s₂, s₁' = even (s₁ ⋈ s₂)) (fun s₁' s₁ ⟨s₂, h₁⟩ => by rw [h₁] constructor · rfl · exact ⟨tail s₂, by rw [interleave_eq, even_cons_cons, tail_cons]⟩) (Exists.intro s₂ rfl) theorem interleave_even_odd (s₁ : Stream' α) : even s₁ ⋈ odd s₁ = s₁ := eq_of_bisim (fun s' s => s' = even s ⋈ odd s) (fun s' s (h : s' = even s ⋈ odd s) => by rw [h]; constructor · rfl · simp [odd_eq, odd_eq, tail_interleave, tail_even]) rfl theorem get_even : ∀ (n : ℕ) (s : Stream' α), get (even s) n = get s (2 * n) | 0, _ => rfl | succ n, s => by change get (even s) (succ n) = get s (succ (succ (2 * n))) rw [get_succ, get_succ, tail_even, get_even n]; rfl theorem get_odd : ∀ (n : ℕ) (s : Stream' α), get (odd s) n = get s (2 * n + 1) := fun n s => by rw [odd_eq, get_even]; rfl theorem mem_of_mem_even (a : α) (s : Stream' α) : a ∈ even s → a ∈ s := fun ⟨n, h⟩ => Exists.intro (2 * n) (by rw [h, get_even]) theorem mem_of_mem_odd (a : α) (s : Stream' α) : a ∈ odd s → a ∈ s := fun ⟨n, h⟩ => Exists.intro (2 * n + 1) (by rw [h, get_odd]) @[simp] theorem nil_append_stream (s : Stream' α) : appendStream' [] s = s := rfl theorem cons_append_stream (a : α) (l : List α) (s : Stream' α) : appendStream' (a::l) s = a::appendStream' l s := rfl @[simp] theorem append_append_stream : ∀ (l₁ l₂ : List α) (s : Stream' α), l₁ ++ l₂ ++ₛ s = l₁ ++ₛ (l₂ ++ₛ s) | [], _, _ => rfl | List.cons a l₁, l₂, s => by rw [List.cons_append, cons_append_stream, cons_append_stream, append_append_stream l₁] lemma get_append_left (h : n < x.length) : (x ++ₛ a).get n = x[n] := by induction' x with b x ih generalizing n · simp at h · rcases n with (_ | n) · simp · simp [ih n (by simpa using h), cons_append_stream] @[simp] lemma get_append_right : (x ++ₛ a).get (x.length + n) = a.get n := by induction' x <;> simp [Nat.succ_add, *, cons_append_stream] @[simp] lemma get_append_length : (x ++ₛ a).get x.length = a.get 0 := get_append_right 0 x a lemma append_right_injective (h : x ++ₛ a = x ++ₛ b) : a = b := by ext n; replace h := congr_arg (fun a ↦ a.get (x.length + n)) h; simpa using h @[simp] lemma append_right_inj : x ++ₛ a = x ++ₛ b ↔ a = b := ⟨append_right_injective x a b, by simp +contextual⟩ lemma append_left_injective (h : x ++ₛ a = y ++ₛ b) (hl : x.length = y.length) : x = y := by apply List.ext_getElem hl intros rw [← get_append_left, ← get_append_left, h] theorem map_append_stream (f : α → β) : ∀ (l : List α) (s : Stream' α), map f (l ++ₛ s) = List.map f l ++ₛ map f s | [], _ => rfl | List.cons a l, s => by rw [cons_append_stream, List.map_cons, map_cons, cons_append_stream, map_append_stream f l] theorem drop_append_stream : ∀ (l : List α) (s : Stream' α), drop l.length (l ++ₛ s) = s | [], s => by rfl | List.cons a l, s => by rw [List.length_cons, drop_succ, cons_append_stream, tail_cons, drop_append_stream l s] theorem append_stream_head_tail (s : Stream' α) : [head s] ++ₛ tail s = s := by simp theorem mem_append_stream_right : ∀ {a : α} (l : List α) {s : Stream' α}, a ∈ s → a ∈ l ++ₛ s | _, [], _, h => h | a, List.cons _ l, s, h => have ih : a ∈ l ++ₛ s := mem_append_stream_right l h mem_cons_of_mem _ ih theorem mem_append_stream_left : ∀ {a : α} {l : List α} (s : Stream' α), a ∈ l → a ∈ l ++ₛ s | _, [], _, h => absurd h List.not_mem_nil | a, List.cons b l, s, h => Or.elim (List.eq_or_mem_of_mem_cons h) (fun aeqb : a = b => Exists.intro 0 aeqb) fun ainl : a ∈ l => mem_cons_of_mem b (mem_append_stream_left s ainl) @[simp] theorem take_zero (s : Stream' α) : take 0 s = [] := rfl -- This lemma used to be simp, but we removed it from the simp set because: -- 1) It duplicates the (often large) `s` term, resulting in large tactic states. -- 2) It conflicts with the very useful `dropLast_take` lemma below (causing nonconfluence). theorem take_succ (n : ℕ) (s : Stream' α) : take (succ n) s = head s::take n (tail s) := rfl @[simp] theorem take_succ_cons {a : α} (n : ℕ) (s : Stream' α) : take (n+1) (a::s) = a :: take n s := rfl
theorem take_succ' {s : Stream' α} : ∀ n, s.take (n+1) = s.take n ++ [s.get n] | 0 => rfl
Mathlib/Data/Stream/Init.lean
516
517
/- Copyright (c) 2022 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Peter Nelson -/ import Mathlib.Order.Antichain /-! # Minimality and Maximality This file proves basic facts about minimality and maximality of an element with respect to a predicate `P` on an ordered type `α`. ## Implementation Details This file underwent a refactor from a version where minimality and maximality were defined using sets rather than predicates, and with an unbundled order relation rather than a `LE` instance. A side effect is that it has become less straightforward to state that something is minimal with respect to a relation that is *not* defeq to the default `LE`. One possible way would be with a type synonym, and another would be with an ad hoc `LE` instance and `@` notation. This was not an issue in practice anywhere in mathlib at the time of the refactor, but it may be worth re-examining this to make it easier in the future; see the TODO below. ## TODO * In the linearly ordered case, versions of lemmas like `minimal_mem_image` will hold with `MonotoneOn`/`AntitoneOn` assumptions rather than the stronger `x ≤ y ↔ f x ≤ f y` assumptions. * `Set.maximal_iff_forall_insert` and `Set.minimal_iff_forall_diff_singleton` will generalize to lemmas about covering in the case of an `IsStronglyAtomic`/`IsStronglyCoatomic` order. * `Finset` versions of the lemmas about sets. * API to allow for easily expressing min/maximality with respect to an arbitrary non-`LE` relation. * API for `MinimalFor`/`MaximalFor` -/ assert_not_exists CompleteLattice open Set OrderDual variable {α : Type*} {P Q : α → Prop} {a x y : α} section LE variable [LE α] @[simp] theorem minimal_toDual : Minimal (fun x ↦ P (ofDual x)) (toDual x) ↔ Maximal P x := Iff.rfl alias ⟨Minimal.of_dual, Minimal.dual⟩ := minimal_toDual @[simp] theorem maximal_toDual : Maximal (fun x ↦ P (ofDual x)) (toDual x) ↔ Minimal P x := Iff.rfl alias ⟨Maximal.of_dual, Maximal.dual⟩ := maximal_toDual @[simp] theorem minimal_false : ¬ Minimal (fun _ ↦ False) x := by simp [Minimal] @[simp] theorem maximal_false : ¬ Maximal (fun _ ↦ False) x := by simp [Maximal] @[simp] theorem minimal_true : Minimal (fun _ ↦ True) x ↔ IsMin x := by simp [IsMin, Minimal] @[simp] theorem maximal_true : Maximal (fun _ ↦ True) x ↔ IsMax x := minimal_true (α := αᵒᵈ) @[simp] theorem minimal_subtype {x : Subtype Q} : Minimal (fun x ↦ P x.1) x ↔ Minimal (P ⊓ Q) x := by obtain ⟨x, hx⟩ := x simp only [Minimal, Subtype.forall, Subtype.mk_le_mk, Pi.inf_apply, inf_Prop_eq] tauto @[simp] theorem maximal_subtype {x : Subtype Q} : Maximal (fun x ↦ P x.1) x ↔ Maximal (P ⊓ Q) x := minimal_subtype (α := αᵒᵈ) theorem maximal_true_subtype {x : Subtype P} : Maximal (fun _ ↦ True) x ↔ Maximal P x := by obtain ⟨x, hx⟩ := x simp [Maximal, hx] theorem minimal_true_subtype {x : Subtype P} : Minimal (fun _ ↦ True) x ↔ Minimal P x := by obtain ⟨x, hx⟩ := x simp [Minimal, hx] @[simp] theorem minimal_minimal : Minimal (Minimal P) x ↔ Minimal P x := ⟨fun h ↦ h.prop, fun h ↦ ⟨h, fun _ hy hyx ↦ h.le_of_le hy.prop hyx⟩⟩ @[simp] theorem maximal_maximal : Maximal (Maximal P) x ↔ Maximal P x := minimal_minimal (α := αᵒᵈ) /-- If `P` is down-closed, then minimal elements satisfying `P` are exactly the globally minimal elements satisfying `P`. -/ theorem minimal_iff_isMin (hP : ∀ ⦃x y⦄, P y → x ≤ y → P x) : Minimal P x ↔ P x ∧ IsMin x := ⟨fun h ↦ ⟨h.prop, fun _ h' ↦ h.le_of_le (hP h.prop h') h'⟩, fun h ↦ ⟨h.1, fun _ _ h' ↦ h.2 h'⟩⟩ /-- If `P` is up-closed, then maximal elements satisfying `P` are exactly the globally maximal elements satisfying `P`. -/ theorem maximal_iff_isMax (hP : ∀ ⦃x y⦄, P y → y ≤ x → P x) : Maximal P x ↔ P x ∧ IsMax x := ⟨fun h ↦ ⟨h.prop, fun _ h' ↦ h.le_of_ge (hP h.prop h') h'⟩, fun h ↦ ⟨h.1, fun _ _ h' ↦ h.2 h'⟩⟩ theorem Minimal.mono (h : Minimal P x) (hle : Q ≤ P) (hQ : Q x) : Minimal Q x := ⟨hQ, fun y hQy ↦ h.le_of_le (hle y hQy)⟩ theorem Maximal.mono (h : Maximal P x) (hle : Q ≤ P) (hQ : Q x) : Maximal Q x := ⟨hQ, fun y hQy ↦ h.le_of_ge (hle y hQy)⟩ theorem Minimal.and_right (h : Minimal P x) (hQ : Q x) : Minimal (fun x ↦ P x ∧ Q x) x := h.mono (fun _ ↦ And.left) ⟨h.prop, hQ⟩ theorem Minimal.and_left (h : Minimal P x) (hQ : Q x) : Minimal (fun x ↦ (Q x ∧ P x)) x := h.mono (fun _ ↦ And.right) ⟨hQ, h.prop⟩ theorem Maximal.and_right (h : Maximal P x) (hQ : Q x) : Maximal (fun x ↦ (P x ∧ Q x)) x := h.mono (fun _ ↦ And.left) ⟨h.prop, hQ⟩ theorem Maximal.and_left (h : Maximal P x) (hQ : Q x) : Maximal (fun x ↦ (Q x ∧ P x)) x := h.mono (fun _ ↦ And.right) ⟨hQ, h.prop⟩ @[simp] theorem minimal_eq_iff : Minimal (· = y) x ↔ x = y := by simp +contextual [Minimal] @[simp] theorem maximal_eq_iff : Maximal (· = y) x ↔ x = y := by simp +contextual [Maximal] theorem not_minimal_iff (hx : P x) : ¬ Minimal P x ↔ ∃ y, P y ∧ y ≤ x ∧ ¬ (x ≤ y) := by simp [Minimal, hx] theorem not_maximal_iff (hx : P x) : ¬ Maximal P x ↔ ∃ y, P y ∧ x ≤ y ∧ ¬ (y ≤ x) := not_minimal_iff (α := αᵒᵈ) hx theorem Minimal.or (h : Minimal (fun x ↦ P x ∨ Q x) x) : Minimal P x ∨ Minimal Q x := by obtain ⟨h | h, hmin⟩ := h · exact .inl ⟨h, fun y hy hyx ↦ hmin (Or.inl hy) hyx⟩ exact .inr ⟨h, fun y hy hyx ↦ hmin (Or.inr hy) hyx⟩ theorem Maximal.or (h : Maximal (fun x ↦ P x ∨ Q x) x) : Maximal P x ∨ Maximal Q x := Minimal.or (α := αᵒᵈ) h theorem minimal_and_iff_right_of_imp (hPQ : ∀ ⦃x⦄, P x → Q x) : Minimal (fun x ↦ P x ∧ Q x) x ↔ (Minimal P x) ∧ Q x := by simp_rw [and_iff_left_of_imp (fun x ↦ hPQ x), iff_self_and] exact fun h ↦ hPQ h.prop theorem minimal_and_iff_left_of_imp (hPQ : ∀ ⦃x⦄, P x → Q x) : Minimal (fun x ↦ Q x ∧ P x) x ↔ Q x ∧ (Minimal P x) := by simp_rw [iff_comm, and_comm, minimal_and_iff_right_of_imp hPQ, and_comm] theorem maximal_and_iff_right_of_imp (hPQ : ∀ ⦃x⦄, P x → Q x) : Maximal (fun x ↦ P x ∧ Q x) x ↔ (Maximal P x) ∧ Q x := minimal_and_iff_right_of_imp (α := αᵒᵈ) hPQ theorem maximal_and_iff_left_of_imp (hPQ : ∀ ⦃x⦄, P x → Q x) : Maximal (fun x ↦ Q x ∧ P x) x ↔ Q x ∧ (Maximal P x) := minimal_and_iff_left_of_imp (α := αᵒᵈ) hPQ end LE section Preorder variable [Preorder α] theorem minimal_iff_forall_lt : Minimal P x ↔ P x ∧ ∀ ⦃y⦄, y < x → ¬ P y := by simp [Minimal, lt_iff_le_not_le, not_imp_not, imp.swap] theorem maximal_iff_forall_gt : Maximal P x ↔ P x ∧ ∀ ⦃y⦄, x < y → ¬ P y := minimal_iff_forall_lt (α := αᵒᵈ) theorem Minimal.not_prop_of_lt (h : Minimal P x) (hlt : y < x) : ¬ P y := (minimal_iff_forall_lt.1 h).2 hlt theorem Maximal.not_prop_of_gt (h : Maximal P x) (hlt : x < y) : ¬ P y := (maximal_iff_forall_gt.1 h).2 hlt theorem Minimal.not_lt (h : Minimal P x) (hy : P y) : ¬ (y < x) := fun hlt ↦ h.not_prop_of_lt hlt hy theorem Maximal.not_gt (h : Maximal P x) (hy : P y) : ¬ (x < y) := fun hlt ↦ h.not_prop_of_gt hlt hy @[simp] theorem minimal_le_iff : Minimal (· ≤ y) x ↔ x ≤ y ∧ IsMin x := minimal_iff_isMin (fun _ _ h h' ↦ h'.trans h) @[simp] theorem maximal_ge_iff : Maximal (y ≤ ·) x ↔ y ≤ x ∧ IsMax x := minimal_le_iff (α := αᵒᵈ) @[simp] theorem minimal_lt_iff : Minimal (· < y) x ↔ x < y ∧ IsMin x := minimal_iff_isMin (fun _ _ h h' ↦ h'.trans_lt h) @[simp] theorem maximal_gt_iff : Maximal (y < ·) x ↔ y < x ∧ IsMax x := minimal_lt_iff (α := αᵒᵈ) theorem not_minimal_iff_exists_lt (hx : P x) : ¬ Minimal P x ↔ ∃ y, y < x ∧ P y := by simp_rw [not_minimal_iff hx, lt_iff_le_not_le, and_comm] alias ⟨exists_lt_of_not_minimal, _⟩ := not_minimal_iff_exists_lt theorem not_maximal_iff_exists_gt (hx : P x) : ¬ Maximal P x ↔ ∃ y, x < y ∧ P y := not_minimal_iff_exists_lt (α := αᵒᵈ) hx alias ⟨exists_gt_of_not_maximal, _⟩ := not_maximal_iff_exists_gt end Preorder section PartialOrder variable [PartialOrder α] theorem Minimal.eq_of_ge (hx : Minimal P x) (hy : P y) (hge : y ≤ x) : x = y := (hx.2 hy hge).antisymm hge theorem Minimal.eq_of_le (hx : Minimal P x) (hy : P y) (hle : y ≤ x) : y = x := (hx.eq_of_ge hy hle).symm theorem Maximal.eq_of_le (hx : Maximal P x) (hy : P y) (hle : x ≤ y) : x = y := hle.antisymm <| hx.2 hy hle theorem Maximal.eq_of_ge (hx : Maximal P x) (hy : P y) (hge : x ≤ y) : y = x := (hx.eq_of_le hy hge).symm theorem minimal_iff : Minimal P x ↔ P x ∧ ∀ ⦃y⦄, P y → y ≤ x → x = y := ⟨fun h ↦ ⟨h.1, fun _ ↦ h.eq_of_ge⟩, fun h ↦ ⟨h.1, fun _ hy hle ↦ (h.2 hy hle).le⟩⟩ theorem maximal_iff : Maximal P x ↔ P x ∧ ∀ ⦃y⦄, P y → x ≤ y → x = y := minimal_iff (α := αᵒᵈ) theorem minimal_mem_iff {s : Set α} : Minimal (· ∈ s) x ↔ x ∈ s ∧ ∀ ⦃y⦄, y ∈ s → y ≤ x → x = y := minimal_iff theorem maximal_mem_iff {s : Set α} : Maximal (· ∈ s) x ↔ x ∈ s ∧ ∀ ⦃y⦄, y ∈ s → x ≤ y → x = y := maximal_iff /-- If `P y` holds, and everything satisfying `P` is above `y`, then `y` is the unique minimal element satisfying `P`. -/ theorem minimal_iff_eq (hy : P y) (hP : ∀ ⦃x⦄, P x → y ≤ x) : Minimal P x ↔ x = y := ⟨fun h ↦ h.eq_of_ge hy (hP h.prop), by rintro rfl; exact ⟨hy, fun z hz _ ↦ hP hz⟩⟩ /-- If `P y` holds, and everything satisfying `P` is below `y`, then `y` is the unique maximal element satisfying `P`. -/ theorem maximal_iff_eq (hy : P y) (hP : ∀ ⦃x⦄, P x → x ≤ y) : Maximal P x ↔ x = y := minimal_iff_eq (α := αᵒᵈ) hy hP @[simp] theorem minimal_ge_iff : Minimal (y ≤ ·) x ↔ x = y := minimal_iff_eq rfl.le fun _ ↦ id @[simp] theorem maximal_le_iff : Maximal (· ≤ y) x ↔ x = y := maximal_iff_eq rfl.le fun _ ↦ id theorem minimal_iff_minimal_of_imp_of_forall (hPQ : ∀ ⦃x⦄, Q x → P x) (h : ∀ ⦃x⦄, P x → ∃ y, y ≤ x ∧ Q y) : Minimal P x ↔ Minimal Q x := by refine ⟨fun h' ↦ ⟨?_, fun y hy hyx ↦ h'.le_of_le (hPQ hy) hyx⟩, fun h' ↦ ⟨hPQ h'.prop, fun y hy hyx ↦ ?_⟩⟩ · obtain ⟨y, hyx, hy⟩ := h h'.prop rwa [((h'.le_of_le (hPQ hy)) hyx).antisymm hyx] obtain ⟨z, hzy, hz⟩ := h hy exact (h'.le_of_le hz (hzy.trans hyx)).trans hzy theorem maximal_iff_maximal_of_imp_of_forall (hPQ : ∀ ⦃x⦄, Q x → P x) (h : ∀ ⦃x⦄, P x → ∃ y, x ≤ y ∧ Q y) : Maximal P x ↔ Maximal Q x := minimal_iff_minimal_of_imp_of_forall (α := αᵒᵈ) hPQ h end PartialOrder section Subset variable {P : Set α → Prop} {s t : Set α} theorem Minimal.eq_of_superset (h : Minimal P s) (ht : P t) (hts : t ⊆ s) : s = t := h.eq_of_ge ht hts theorem Maximal.eq_of_subset (h : Maximal P s) (ht : P t) (hst : s ⊆ t) : s = t := h.eq_of_le ht hst theorem Minimal.eq_of_subset (h : Minimal P s) (ht : P t) (hts : t ⊆ s) : t = s := h.eq_of_le ht hts theorem Maximal.eq_of_superset (h : Maximal P s) (ht : P t) (hst : s ⊆ t) : t = s := h.eq_of_ge ht hst theorem minimal_subset_iff : Minimal P s ↔ P s ∧ ∀ ⦃t⦄, P t → t ⊆ s → s = t := _root_.minimal_iff theorem maximal_subset_iff : Maximal P s ↔ P s ∧ ∀ ⦃t⦄, P t → s ⊆ t → s = t := _root_.maximal_iff theorem minimal_subset_iff' : Minimal P s ↔ P s ∧ ∀ ⦃t⦄, P t → t ⊆ s → s ⊆ t := Iff.rfl theorem maximal_subset_iff' : Maximal P s ↔ P s ∧ ∀ ⦃t⦄, P t → s ⊆ t → t ⊆ s := Iff.rfl theorem not_minimal_subset_iff (hs : P s) : ¬ Minimal P s ↔ ∃ t, t ⊂ s ∧ P t := not_minimal_iff_exists_lt hs theorem not_maximal_subset_iff (hs : P s) : ¬ Maximal P s ↔ ∃ t, s ⊂ t ∧ P t := not_maximal_iff_exists_gt hs theorem Set.minimal_iff_forall_ssubset : Minimal P s ↔ P s ∧ ∀ ⦃t⦄, t ⊂ s → ¬ P t := minimal_iff_forall_lt theorem Minimal.not_prop_of_ssubset (h : Minimal P s) (ht : t ⊂ s) : ¬ P t := (minimal_iff_forall_lt.1 h).2 ht theorem Minimal.not_ssubset (h : Minimal P s) (ht : P t) : ¬ t ⊂ s := h.not_lt ht theorem Maximal.mem_of_prop_insert (h : Maximal P s) (hx : P (insert x s)) : x ∈ s := h.eq_of_subset hx (subset_insert _ _) ▸ mem_insert .. theorem Minimal.not_mem_of_prop_diff_singleton (h : Minimal P s) (hx : P (s \ {x})) : x ∉ s := fun hxs ↦ ((h.eq_of_superset hx diff_subset).subset hxs).2 rfl theorem Set.minimal_iff_forall_diff_singleton (hP : ∀ ⦃s t⦄, P t → t ⊆ s → P s) : Minimal P s ↔ P s ∧ ∀ x ∈ s, ¬ P (s \ {x}) := ⟨fun h ↦ ⟨h.1, fun _ hx hP ↦ h.not_mem_of_prop_diff_singleton hP hx⟩, fun h ↦ ⟨h.1, fun _ ht hts x hxs ↦ by_contra fun hxt ↦ h.2 x hxs (hP ht <| subset_diff_singleton hts hxt)⟩⟩ theorem Set.exists_diff_singleton_of_not_minimal (hP : ∀ ⦃s t⦄, P t → t ⊆ s → P s) (hs : P s) (h : ¬ Minimal P s) : ∃ x ∈ s, P (s \ {x}) := by simpa [Set.minimal_iff_forall_diff_singleton hP, hs] using h theorem Set.maximal_iff_forall_ssuperset : Maximal P s ↔ P s ∧ ∀ ⦃t⦄, s ⊂ t → ¬ P t := maximal_iff_forall_gt theorem Maximal.not_prop_of_ssuperset (h : Maximal P s) (ht : s ⊂ t) : ¬ P t := (maximal_iff_forall_gt.1 h).2 ht theorem Maximal.not_ssuperset (h : Maximal P s) (ht : P t) : ¬ s ⊂ t := h.not_gt ht theorem Set.maximal_iff_forall_insert (hP : ∀ ⦃s t⦄, P t → s ⊆ t → P s) : Maximal P s ↔ P s ∧ ∀ x ∉ s, ¬ P (insert x s) := by simp only [not_imp_not] exact ⟨fun h ↦ ⟨h.1, fun x ↦ h.mem_of_prop_insert⟩, fun h ↦ ⟨h.1, fun t ht hst x hxt ↦ h.2 x (hP ht <| insert_subset hxt hst)⟩⟩ theorem Set.exists_insert_of_not_maximal (hP : ∀ ⦃s t⦄, P t → s ⊆ t → P s) (hs : P s) (h : ¬ Maximal P s) : ∃ x ∉ s, P (insert x s) := by simpa [Set.maximal_iff_forall_insert hP, hs] using h /- TODO : generalize `minimal_iff_forall_diff_singleton` and `maximal_iff_forall_insert` to `IsStronglyCoatomic`/`IsStronglyAtomic` orders. -/ end Subset section Set variable {s t : Set α} section Preorder variable [Preorder α] theorem setOf_minimal_subset (s : Set α) : {x | Minimal (· ∈ s) x} ⊆ s :=
sep_subset .. theorem setOf_maximal_subset (s : Set α) : {x | Maximal (· ∈ s) x} ⊆ s :=
Mathlib/Order/Minimal.lean
359
361
/- Copyright (c) 2020 Kevin Kappelmann. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kevin Kappelmann -/ import Mathlib.Algebra.ContinuedFractions.ContinuantsRecurrence import Mathlib.Algebra.ContinuedFractions.TerminatedStable import Mathlib.Tactic.FieldSimp import Mathlib.Tactic.Ring /-! # Equivalence of Recursive and Direct Computations of Convergents of Generalized Continued Fractions ## Summary We show the equivalence of two computations of convergents (recurrence relation (`convs`) vs. direct evaluation (`convs'`)) for generalized continued fractions (`GenContFract`s) on linear ordered fields. We follow the proof from [hardy2008introduction], Chapter 10. Here's a sketch: Let `c` be a continued fraction `[h; (a₀, b₀), (a₁, b₁), (a₂, b₂),...]`, visually: $$ c = h + \dfrac{a_0} {b_0 + \dfrac{a_1} {b_1 + \dfrac{a_2} {b_2 + \dfrac{a_3} {b_3 + \dots}}}} $$ One can compute the convergents of `c` in two ways: 1. Directly evaluating the fraction described by `c` up to a given `n` (`convs'`) 2. Using the recurrence (`convs`): - `A₋₁ = 1, A₀ = h, Aₙ = bₙ₋₁ * Aₙ₋₁ + aₙ₋₁ * Aₙ₋₂`, and - `B₋₁ = 0, B₀ = 1, Bₙ = bₙ₋₁ * Bₙ₋₁ + aₙ₋₁ * Bₙ₋₂`. To show the equivalence of the computations in the main theorem of this file `convs_eq_convs'`, we proceed by induction. The case `n = 0` is trivial. For `n + 1`, we first "squash" the `n + 1`th position of `c` into the `n`th position to obtain another continued fraction `c' := [h; (a₀, b₀),..., (aₙ-₁, bₙ-₁), (aₙ, bₙ + aₙ₊₁ / bₙ₊₁), (aₙ₊₁, bₙ₊₁),...]`. This squashing process is formalised in section `Squash`. Note that directly evaluating `c` up to position `n + 1` is equal to evaluating `c'` up to `n`. This is shown in lemma `succ_nth_conv'_eq_squashGCF_nth_conv'`. By the inductive hypothesis, the two computations for the `n`th convergent of `c` coincide. So all that is left to show is that the recurrence relation for `c` at `n + 1` and `c'` at `n` coincide. This can be shown by another induction. The corresponding lemma in this file is `succ_nth_conv_eq_squashGCF_nth_conv`. ## Main Theorems - `GenContFract.convs_eq_convs'` shows the equivalence under a strict positivity restriction on the sequence. - `ContFract.convs_eq_convs'` shows the equivalence for regular continued fractions. ## References - https://en.wikipedia.org/wiki/Generalized_continued_fraction - [*Hardy, GH and Wright, EM and Heath-Brown, Roger and Silverman, Joseph*][hardy2008introduction] ## Tags fractions, recurrence, equivalence -/ variable {K : Type*} {n : ℕ} namespace GenContFract variable {g : GenContFract K} {s : Stream'.Seq <| Pair K} section Squash /-! We will show the equivalence of the computations by induction. To make the induction work, we need to be able to *squash* the nth and (n + 1)th value of a sequence. This squashing itself and the lemmas about it are not very interesting. As a reader, you hence might want to skip this section. -/ section WithDivisionRing variable [DivisionRing K] /-- Given a sequence of `GenContFract.Pair`s `s = [(a₀, bₒ), (a₁, b₁), ...]`, `squashSeq s n` combines `⟨aₙ, bₙ⟩` and `⟨aₙ₊₁, bₙ₊₁⟩` at position `n` to `⟨aₙ, bₙ + aₙ₊₁ / bₙ₊₁⟩`. For example, `squashSeq s 0 = [(a₀, bₒ + a₁ / b₁), (a₁, b₁),...]`. If `s.TerminatedAt (n + 1)`, then `squashSeq s n = s`. -/ def squashSeq (s : Stream'.Seq <| Pair K) (n : ℕ) : Stream'.Seq (Pair K) := match Prod.mk (s.get? n) (s.get? (n + 1)) with | ⟨some gp_n, some gp_succ_n⟩ => Stream'.Seq.nats.zipWith -- return the squashed value at position `n`; otherwise, do nothing. (fun n' gp => if n' = n then ⟨gp_n.a, gp_n.b + gp_succ_n.a / gp_succ_n.b⟩ else gp) s | _ => s /-! We now prove some simple lemmas about the squashed sequence -/ /-- If the sequence already terminated at position `n + 1`, nothing gets squashed. -/ theorem squashSeq_eq_self_of_terminated (terminatedAt_succ_n : s.TerminatedAt (n + 1)) : squashSeq s n = s := by change s.get? (n + 1) = none at terminatedAt_succ_n
cases s_nth_eq : s.get? n <;> simp only [*, squashSeq] /-- If the sequence has not terminated before position `n + 1`, the value at `n + 1` gets squashed into position `n`. -/
Mathlib/Algebra/ContinuedFractions/ConvergentsEquiv.lean
106
109
/- Copyright (c) 2023 Joël Riou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joël Riou -/ import Mathlib.Algebra.Homology.ShortComplex.Homology /-! # Quasi-isomorphisms of short complexes This file introduces the typeclass `QuasiIso φ` for a morphism `φ : S₁ ⟶ S₂` of short complexes (which have homology): the condition is that the induced morphism `homologyMap φ` in homology is an isomorphism. -/ namespace CategoryTheory open Category Limits namespace ShortComplex variable {C : Type _} [Category C] [HasZeroMorphisms C] {S₁ S₂ S₃ S₄ : ShortComplex C} [S₁.HasHomology] [S₂.HasHomology] [S₃.HasHomology] [S₄.HasHomology] /-- A morphism `φ : S₁ ⟶ S₂` of short complexes that have homology is a quasi-isomorphism if the induced map `homologyMap φ : S₁.homology ⟶ S₂.homology` is an isomorphism. -/ class QuasiIso (φ : S₁ ⟶ S₂) : Prop where /-- the homology map is an isomorphism -/ isIso' : IsIso (homologyMap φ) instance QuasiIso.isIso (φ : S₁ ⟶ S₂) [QuasiIso φ] : IsIso (homologyMap φ) := QuasiIso.isIso' lemma quasiIso_iff (φ : S₁ ⟶ S₂) : QuasiIso φ ↔ IsIso (homologyMap φ) := by constructor · intro h infer_instance · intro h exact ⟨h⟩ instance quasiIso_of_isIso (φ : S₁ ⟶ S₂) [IsIso φ] : QuasiIso φ := ⟨(homologyMapIso (asIso φ)).isIso_hom⟩ instance quasiIso_comp (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃) [hφ : QuasiIso φ] [hφ' : QuasiIso φ'] : QuasiIso (φ ≫ φ') := by rw [quasiIso_iff] at hφ hφ' ⊢ rw [homologyMap_comp] infer_instance lemma quasiIso_of_comp_left (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃) [hφ : QuasiIso φ] [hφφ' : QuasiIso (φ ≫ φ')] : QuasiIso φ' := by rw [quasiIso_iff] at hφ hφφ' ⊢ rw [homologyMap_comp] at hφφ' exact IsIso.of_isIso_comp_left (homologyMap φ) (homologyMap φ')
lemma quasiIso_iff_comp_left (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃) [hφ : QuasiIso φ] : QuasiIso (φ ≫ φ') ↔ QuasiIso φ' := by constructor · intro exact quasiIso_of_comp_left φ φ' · intro exact quasiIso_comp φ φ'
Mathlib/Algebra/Homology/ShortComplex/QuasiIso.lean
60
66
/- 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.Algebra.GroupWithZero.Divisibility import Mathlib.Data.Nat.SuccPred import Mathlib.Order.SuccPred.InitialSeg import Mathlib.SetTheory.Ordinal.Basic /-! # 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`. Various other basic arithmetic results are given in `Principal.lean` instead. -/ assert_not_exists Field Module noncomputable section open Function Cardinal Set Equiv Order open scoped Ordinal universe u v w namespace Ordinal variable {α β 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⟩ @[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 instance instAddLeftReflectLE : AddLeftReflectLE Ordinal.{u} where elim c a b := by refine inductionOn₃ a b c fun α r _ β s _ γ t _ ⟨f⟩ ↦ ?_ have H₁ a : f (Sum.inl a) = Sum.inl a := by simpa using ((InitialSeg.leAdd t r).trans f).eq (InitialSeg.leAdd t s) a have H₂ a : ∃ b, f (Sum.inr a) = Sum.inr b := by generalize hx : f (Sum.inr a) = x obtain x | x := x · rw [← H₁, f.inj] at hx contradiction · exact ⟨x, rfl⟩ choose g hg using H₂ refine (RelEmbedding.ofMonotone g fun _ _ h ↦ ?_).ordinal_type_le rwa [← @Sum.lex_inr_inr _ t _ s, ← hg, ← hg, f.map_rel_iff, Sum.lex_inr_inr] instance : IsLeftCancelAdd Ordinal where add_left_cancel a b c h := by simpa only [le_antisymm_iff, add_le_add_iff_left] using h @[deprecated add_left_cancel_iff (since := "2024-12-11")] protected theorem add_left_cancel (a) {b c : Ordinal} : a + b = a + c ↔ b = c := add_left_cancel_iff 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 instAddLeftStrictMono : AddLeftStrictMono Ordinal.{u} := ⟨fun a _b _c ↦ (add_lt_add_iff_left' a).2⟩ instance instAddLeftReflectLT : AddLeftReflectLT Ordinal.{u} := ⟨fun a _b _c ↦ (add_lt_add_iff_left' a).1⟩ instance instAddRightReflectLT : AddRightReflectLT Ordinal.{u} := ⟨fun _a _b _c ↦ lt_imp_lt_of_le_imp_le fun h => add_le_add_right h _⟩ 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] 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] theorem add_eq_zero_iff {a b : Ordinal} : a + b = 0 ↔ a = 0 ∧ b = 0 := inductionOn₂ a b fun α r _ β s _ => by simp_rw [← type_sum_lex, type_eq_zero_iff_isEmpty] exact isEmpty_sum theorem left_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : a = 0 := (add_eq_zero_iff.1 h).1 theorem right_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : b = 0 := (add_eq_zero_iff.1 h).2 /-! ### The predecessor of an ordinal -/ open Classical in /-- 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 @[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 theorem pred_le_self (o) : pred o ≤ o := by classical exact 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] 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⟩ theorem pred_eq_iff_not_succ' {o} : pred o = o ↔ ∀ a, o ≠ succ a := by simpa using 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, not_le]) (iff_not_comm.1 pred_eq_iff_not_succ).symm @[simp] theorem pred_zero : pred 0 = 0 := pred_eq_iff_not_succ'.2 fun a => (succ_ne_zero a).symm 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]⟩ 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⟩⟩ theorem lt_pred {a b} : a < pred b ↔ succ a < b := by classical exact 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] theorem pred_le {a b} : pred a ≤ b ↔ a ≤ succ b := le_iff_le_iff_lt_iff_lt.2 lt_pred @[simp] theorem lift_is_succ {o : Ordinal.{v}} : (∃ a, lift.{u} o = succ a) ↔ ∃ a, o = succ a := ⟨fun ⟨a, h⟩ => let ⟨b, e⟩ := mem_range_lift_of_le <| show a ≤ lift.{u} o from le_of_lt <| h.symm ▸ lt_succ a ⟨b, (lift_inj.{u,v}).1 <| by rw [h, ← e, lift_succ]⟩, fun ⟨a, h⟩ => ⟨lift.{u} a, by simp only [h, lift_succ]⟩⟩ @[simp] theorem lift_pred (o : Ordinal.{v}) : lift.{u} (pred o) = pred (lift.{u} o) := by classical exact if h : ∃ a, o = succ a then by obtain ⟨a, e⟩ := h; 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)] /-! ### Limit ordinals -/ /-- A limit ordinal is an ordinal which is not zero and not a successor. TODO: deprecate this in favor of `Order.IsSuccLimit`. -/ def IsLimit (o : Ordinal) : Prop := IsSuccLimit o theorem isLimit_iff {o} : IsLimit o ↔ o ≠ 0 ∧ IsSuccPrelimit o := by simp [IsLimit, IsSuccLimit] theorem IsLimit.isSuccPrelimit {o} (h : IsLimit o) : IsSuccPrelimit o := IsSuccLimit.isSuccPrelimit h theorem IsLimit.succ_lt {o a : Ordinal} (h : IsLimit o) : a < o → succ a < o := IsSuccLimit.succ_lt h theorem isSuccPrelimit_zero : IsSuccPrelimit (0 : Ordinal) := isSuccPrelimit_bot theorem not_zero_isLimit : ¬IsLimit 0 := not_isSuccLimit_bot theorem not_succ_isLimit (o) : ¬IsLimit (succ o) := not_isSuccLimit_succ o theorem not_succ_of_isLimit {o} (h : IsLimit o) : ¬∃ a, o = succ a | ⟨a, e⟩ => not_succ_isLimit a (e ▸ h) theorem succ_lt_of_isLimit {o a : Ordinal} (h : IsLimit o) : succ a < o ↔ a < o := IsSuccLimit.succ_lt_iff h 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 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)⟩ 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) @[simp] theorem lift_isLimit (o : Ordinal.{v}) : IsLimit (lift.{u,v} o) ↔ IsLimit o := liftInitialSeg.isSuccLimit_apply_iff theorem IsLimit.pos {o : Ordinal} (h : IsLimit o) : 0 < o := IsSuccLimit.bot_lt h theorem IsLimit.ne_zero {o : Ordinal} (h : IsLimit o) : o ≠ 0 := h.pos.ne' theorem IsLimit.one_lt {o : Ordinal} (h : IsLimit o) : 1 < o := by simpa only [succ_zero] using h.succ_lt h.pos theorem IsLimit.nat_lt {o : Ordinal} (h : IsLimit o) : ∀ n : ℕ, (n : Ordinal) < o | 0 => h.pos | n + 1 => h.succ_lt (IsLimit.nat_lt h n) theorem zero_or_succ_or_limit (o : Ordinal) : o = 0 ∨ (∃ a, o = succ a) ∨ IsLimit o := by simpa [eq_comm] using isMin_or_mem_range_succ_or_isSuccLimit o theorem isLimit_of_not_succ_of_ne_zero {o : Ordinal} (h : ¬∃ a, o = succ a) (h' : o ≠ 0) : IsLimit o := ((zero_or_succ_or_limit o).resolve_left h').resolve_left h -- TODO: this is an iff with `IsSuccPrelimit` theorem IsLimit.sSup_Iio {o : Ordinal} (h : IsLimit o) : sSup (Iio o) = o := by apply (csSup_le' (fun a ha ↦ le_of_lt ha)).antisymm apply le_of_forall_lt intro a ha exact (lt_succ a).trans_le (le_csSup bddAbove_Iio (h.succ_lt ha)) theorem IsLimit.iSup_Iio {o : Ordinal} (h : IsLimit o) : ⨆ a : Iio o, a.1 = o := by rw [← sSup_eq_iSup', h.sSup_Iio] /-- 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 {motive : Ordinal → Sort*} (o : Ordinal) (zero : motive 0) (succ : ∀ o, motive o → motive (succ o)) (isLimit : ∀ o, IsLimit o → (∀ o' < o, motive o') → motive o) : motive o := by refine SuccOrder.limitRecOn o (fun a ha ↦ ?_) (fun a _ ↦ succ a) isLimit convert zero simpa using ha @[simp] theorem limitRecOn_zero {motive} (H₁ H₂ H₃) : @limitRecOn motive 0 H₁ H₂ H₃ = H₁ := SuccOrder.limitRecOn_isMin _ _ _ isMin_bot @[simp] theorem limitRecOn_succ {motive} (o H₁ H₂ H₃) : @limitRecOn motive (succ o) H₁ H₂ H₃ = H₂ o (@limitRecOn motive o H₁ H₂ H₃) := SuccOrder.limitRecOn_succ .. @[simp] theorem limitRecOn_limit {motive} (o H₁ H₂ H₃ h) : @limitRecOn motive o H₁ H₂ H₃ = H₃ o h fun x _h => @limitRecOn motive x H₁ H₂ H₃ := SuccOrder.limitRecOn_of_isSuccLimit .. /-- Bounded recursion on ordinals. Similar to `limitRecOn`, with the assumption `o < l` added to all cases. The final term's domain is the ordinals below `l`. -/ @[elab_as_elim] def boundedLimitRecOn {l : Ordinal} (lLim : l.IsLimit) {motive : Iio l → Sort*} (o : Iio l) (zero : motive ⟨0, lLim.pos⟩) (succ : (o : Iio l) → motive o → motive ⟨succ o, lLim.succ_lt o.2⟩) (isLimit : (o : Iio l) → IsLimit o → (Π o' < o, motive o') → motive o) : motive o := limitRecOn (motive := fun p ↦ (h : p < l) → motive ⟨p, h⟩) o.1 (fun _ ↦ zero) (fun o ih h ↦ succ ⟨o, _⟩ <| ih <| (lt_succ o).trans h) (fun _o ho ih _ ↦ isLimit _ ho fun _o' h ↦ ih _ h _) o.2 @[simp] theorem boundedLimitRec_zero {l} (lLim : l.IsLimit) {motive} (H₁ H₂ H₃) : @boundedLimitRecOn l lLim motive ⟨0, lLim.pos⟩ H₁ H₂ H₃ = H₁ := by rw [boundedLimitRecOn, limitRecOn_zero] @[simp] theorem boundedLimitRec_succ {l} (lLim : l.IsLimit) {motive} (o H₁ H₂ H₃) : @boundedLimitRecOn l lLim motive ⟨succ o.1, lLim.succ_lt o.2⟩ H₁ H₂ H₃ = H₂ o (@boundedLimitRecOn l lLim motive o H₁ H₂ H₃) := by rw [boundedLimitRecOn, limitRecOn_succ] rfl theorem boundedLimitRec_limit {l} (lLim : l.IsLimit) {motive} (o H₁ H₂ H₃ oLim) : @boundedLimitRecOn l lLim motive o H₁ H₂ H₃ = H₃ o oLim (fun x _ ↦ @boundedLimitRecOn l lLim motive x H₁ H₂ H₃) := by rw [boundedLimitRecOn, limitRecOn_limit] rfl instance orderTopToTypeSucc (o : Ordinal) : OrderTop (succ o).toType := @OrderTop.mk _ _ (Top.mk _) le_enum_succ theorem enum_succ_eq_top {o : Ordinal} : enum (α := (succ o).toType) (· < ·) ⟨o, type_toType _ ▸ lt_succ o⟩ = ⊤ := rfl 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.mpr _ · rw [enum_typein] · rw [Subtype.mk_lt_mk, lt_succ_iff] theorem toType_noMax_of_succ_lt {o : Ordinal} (ho : ∀ a < o, succ a < o) : NoMaxOrder o.toType := ⟨has_succ_of_type_succ_lt (type_toType _ ▸ ho)⟩ 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.succ_lt (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, Subtype.mk_lt_mk] apply lt_succ @[simp] theorem typein_ordinal (o : Ordinal.{u}) : @typein Ordinal (· < ·) _ o = Ordinal.lift.{u + 1} o := by refine Quotient.inductionOn o ?_ rintro ⟨α, r, wo⟩; apply Quotient.sound constructor; refine ((RelIso.preimage Equiv.ulift r).trans (enum r).symm).symm theorem mk_Iio_ordinal (o : Ordinal.{u}) : #(Iio o) = Cardinal.lift.{u + 1} o.card := by rw [lift_card, ← typein_ordinal] rfl /-! ### 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 theorem IsNormal.limit_le {f} (H : IsNormal f) : ∀ {o}, IsLimit o → ∀ {a}, f o ≤ a ↔ ∀ b < o, f b ≤ a := @H.2 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 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.succ_lt h)) theorem IsNormal.monotone {f} (H : IsNormal f) : Monotone f := H.strictMono.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⟩⟩⟩ theorem IsNormal.lt_iff {f} (H : IsNormal f) {a b} : f a < f b ↔ a < b := StrictMono.lt_iff_lt <| H.strictMono 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 theorem IsNormal.inj {f} (H : IsNormal f) {a b} : f a = f b ↔ a = b := by simp only [le_antisymm_iff, H.le_iff] theorem IsNormal.id_le {f} (H : IsNormal f) : id ≤ f := H.strictMono.id_le theorem IsNormal.le_apply {f} (H : IsNormal f) {a} : a ≤ f a := H.strictMono.le_apply theorem IsNormal.le_iff_eq {f} (H : IsNormal f) {a} : f a ≤ a ↔ f a = a := H.le_apply.le_iff_eq 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 _ pa => (H.le_iff.2 ((H₂ _).1 le_rfl _ pa)).trans h, fun h => by induction b using limitRecOn with | zero => obtain ⟨x, px⟩ := p0 have := Ordinal.le_zero.1 ((H₂ _).1 (Ordinal.zero_le _) _ px) rw [this] at px exact h _ px | succ 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) | isLimit 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)⟩ 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 theorem IsNormal.refl : IsNormal id := ⟨lt_succ, fun _o l _a => Ordinal.limit_le l⟩ 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 _⟩ theorem IsNormal.isLimit {f} (H : IsNormal f) {o} (ho : IsLimit o) : IsLimit (f o) := by rw [isLimit_iff, isSuccPrelimit_iff_succ_lt] use (H.lt_iff.2 ho.pos).ne_bot intro a ha obtain ⟨b, hb, hab⟩ := (H.limit_lt ho).1 ha rw [← succ_le_iff] at hab apply hab.trans_lt rwa [H.lt_iff] theorem add_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a + b ≤ c ↔ ∀ b' < b, a + b' ≤ c := ⟨fun h _ 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; rcases 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.succ_lt (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⟩ theorem isNormal_add_right (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⟩ theorem isLimit_add (a) {b} : IsLimit b → IsLimit (a + b) := (isNormal_add_right a).isLimit alias IsLimit.add := isLimit_add /-! ### Subtraction on ordinals -/ /-- The set in the definition of subtraction is nonempty. -/ private theorem sub_nonempty {a b : Ordinal} : { o | a ≤ b + o }.Nonempty := ⟨a, le_add_left _ _⟩ /-- `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 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⟩ theorem lt_sub {a b c : Ordinal} : a < b - c ↔ c + a < b := lt_iff_lt_of_le_iff_le sub_le 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 _ _) theorem sub_eq_of_add_eq {a b c : Ordinal} (h : a + b = c) : c - a = b := h ▸ add_sub_cancel _ _ theorem sub_le_self (a b : Ordinal) : a - b ≤ a := sub_le.2 <| le_add_left _ _ 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) 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] 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) 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 @[simp] theorem zero_sub (a : Ordinal) : 0 - a = 0 := by rw [← Ordinal.le_zero]; apply sub_le_self @[simp] theorem sub_self (a : Ordinal) : a - a = 0 := by simpa only [add_zero] using add_sub_cancel a 0 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]⟩ protected theorem sub_ne_zero_iff_lt {a b : Ordinal} : a - b ≠ 0 ↔ b < a := by simpa using Ordinal.sub_eq_zero_iff_le.not 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] @[simp] theorem add_sub_add_cancel (a b c : Ordinal) : a + b - (a + c) = b - c := by rw [← sub_sub, add_sub_cancel] theorem le_sub_of_add_le {a b c : Ordinal} (h : b + c ≤ a) : c ≤ a - b := by rw [← add_le_add_iff_left b] exact h.trans (le_add_sub a b) theorem sub_lt_of_lt_add {a b c : Ordinal} (h : a < b + c) (hc : 0 < c) : a - b < c := by obtain hab | hba := lt_or_le a b · rwa [Ordinal.sub_eq_zero_iff_le.2 hab.le] · rwa [sub_lt_of_le hba] theorem lt_add_iff {a b c : Ordinal} (hc : c ≠ 0) : a < b + c ↔ ∃ d < c, a ≤ b + d := by use fun h ↦ ⟨_, sub_lt_of_lt_add h hc.bot_lt, le_add_sub a b⟩ rintro ⟨d, hd, ha⟩ exact ha.trans_lt (add_lt_add_left hd b) theorem add_le_iff {a b c : Ordinal} (hb : b ≠ 0) : a + b ≤ c ↔ ∀ d < b, a + d < c := by simpa using (lt_add_iff hb).not @[deprecated add_le_iff (since := "2024-12-08")] theorem add_le_of_forall_add_lt {a b c : Ordinal} (hb : 0 < b) (h : ∀ d < b, a + d < c) : a + b ≤ c := (add_le_iff hb.ne').2 h theorem isLimit_sub {a b} (ha : IsLimit a) (h : b < a) : IsLimit (a - b) := by rw [isLimit_iff, Ordinal.sub_ne_zero_iff_lt, isSuccPrelimit_iff_succ_lt] refine ⟨h, fun c hc ↦ ?_⟩ rw [lt_sub] at hc ⊢ rw [add_succ] exact ha.succ_lt hc /-! ### 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, _⟩ ⟨β, s, _⟩ => ⟦⟨β × α, Prod.Lex s r, inferInstance⟩⟧ : WellOrder → WellOrder → Ordinal) fun ⟨_, _, _⟩ _ _ _ ⟨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] simp only [eq_self_iff_true, true_and] 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, or_false] 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 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⟩ @[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 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, reduceCtorEq] <;> -- Porting note: `Sum.inr.inj_iff` is required. simp only [Sum.inl.inj_iff, Sum.inr.inj_iff, true_or, false_and, false_or]⟩⟩⟩ theorem mul_succ (a b : Ordinal) : a * succ b = a * b + a := mul_add_one a b instance mulLeftMono : MulLeftMono 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 obtain ⟨-, -, h'⟩ | ⟨-, h'⟩ := h · exact Prod.Lex.left _ _ (f.toRelEmbedding.map_rel_iff.2 h') · exact Prod.Lex.right _ h'⟩ instance mulRightMono : MulRightMono 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 : γ × α => (a.1, f a.2)) fun a b h => ?_).ordinal_type_le obtain ⟨-, -, h'⟩ | ⟨-, h'⟩ := h · exact Prod.Lex.left _ _ h' · exact Prod.Lex.right _ (f.toRelEmbedding.map_rel_iff.2 h')⟩ 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] 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] 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 obtain ⟨b, a⟩ := enum _ ⟨_, l⟩ exact irrefl _ (this _ _) intro a b rw [← typein_lt_typein (Prod.Lex s r), typein_enum] have := H _ (h.succ_lt (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 obtain ⟨-, -, h⟩ | ⟨-, h⟩ := h · exact (irrefl _ h).elim · exact h · refine Sum.inl (⟨b', ?_⟩, a') obtain ⟨-, -, h⟩ | ⟨e, 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, false_or, 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, dif_neg, not_false_iff, Sum.lex_inr_inl, false_and] at h ⊢ obtain ⟨-, -, h₂_h⟩ | e₂ := h₂ <;> [exact asymm h h₂_h; exact e₂ rfl] · 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 _ 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⟩ theorem isNormal_mul_right {a : Ordinal} (h : 0 < a) : IsNormal (a * ·) := -- Porting note (https://github.com/leanprover-community/mathlib4/issues/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 _ l _ => mul_le_of_limit l⟩ 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) theorem mul_lt_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b < a * c ↔ b < c := (isNormal_mul_right a0).lt_iff theorem mul_le_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c := (isNormal_mul_right a0).le_iff 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 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 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 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 theorem mul_right_inj {a b c : Ordinal} (a0 : 0 < a) : a * b = a * c ↔ b = c := (isNormal_mul_right a0).inj theorem isLimit_mul {a b : Ordinal} (a0 : 0 < a) : IsLimit b → IsLimit (a * b) := (isNormal_mul_right a0).isLimit theorem isLimit_mul_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 isLimit_add _ l · exact isLimit_mul l.pos lb 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] private theorem add_mul_limit_aux {a b c : Ordinal} (ba : b + a = a) (l : IsLimit c) (IH : ∀ c' < c, (a + b) * succ c' = a * succ c' + b) : (a + b) * c = a * c := le_antisymm ((mul_le_of_limit l).2 fun c' h => by apply (mul_le_mul_left' (le_succ c') _).trans rw [IH _ h] apply (add_le_add_left _ _).trans · rw [← mul_succ] exact mul_le_mul_left' (succ_le_of_lt <| l.succ_lt h) _ · rw [← ba] exact le_add_right _ _) (mul_le_mul_right' (le_add_right _ _) _) theorem add_mul_succ {a b : Ordinal} (c) (ba : b + a = a) : (a + b) * succ c = a * succ c + b := by induction c using limitRecOn with | zero => simp only [succ_zero, mul_one] | succ c IH => rw [mul_succ, IH, ← add_assoc, add_assoc _ b, ba, ← mul_succ] | isLimit c l IH => rw [mul_succ, add_mul_limit_aux ba l IH, mul_succ, add_assoc] theorem add_mul_limit {a b c : Ordinal} (ba : b + a = a) (l : IsLimit c) : (a + b) * c = a * c := add_mul_limit_aux ba l fun c' _ => add_mul_succ c' ba /-! ### Division on ordinals -/ /-- The set in the definition of division is nonempty. -/ private 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)⟩ /-- `a / b` is the unique ordinal `o` satisfying `a = b * o + o'` with `o' < b`. -/ instance div : Div Ordinal := ⟨fun a b => if b = 0 then 0 else sInf { o | a < b * succ o }⟩ @[simp] theorem div_zero (a : Ordinal) : a / 0 = 0 := dif_pos rfl private theorem div_def (a) {b : Ordinal} (h : b ≠ 0) : a / b = sInf { o | a < b * succ o } := dif_neg h 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) 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 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⟩ 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] theorem div_pos {b c : Ordinal} (h : c ≠ 0) : 0 < b / c ↔ c ≤ b := by simp [lt_div h] theorem le_div {a b c : Ordinal} (c0 : c ≠ 0) : a ≤ b / c ↔ c * a ≤ b := by induction a using limitRecOn with | zero => simp only [mul_zero, Ordinal.zero_le] | succ _ _ => rw [succ_le_iff, lt_div c0] | isLimit _ h₁ h₂ => revert h₁ h₂ simp +contextual only [mul_le_of_limit, limit_le, forall_true_iff] 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 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) 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 @[simp] theorem zero_div (a : Ordinal) : 0 / a = 0 := Ordinal.le_zero.1 <| div_le_of_le_mul <| Ordinal.zero_le _ 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 theorem div_le_left {a b : Ordinal} (h : a ≤ b) (c : Ordinal) : a / c ≤ b / c := by obtain rfl | hc := eq_or_ne c 0 · rw [div_zero, div_zero] · rw [le_div hc] exact (mul_div_le a c).trans h 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 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 @[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 theorem mul_add_div_mul {a c : Ordinal} (hc : c < a) (b d : Ordinal) : (a * b + c) / (a * d) = b / d := by have ha : a ≠ 0 := ((Ordinal.zero_le c).trans_lt hc).ne' obtain rfl | hd := eq_or_ne d 0 · rw [mul_zero, div_zero, div_zero] · have H := mul_ne_zero ha hd apply le_antisymm · rw [← lt_succ_iff, div_lt H, mul_assoc] · apply (add_lt_add_left hc _).trans_le rw [← mul_succ] apply mul_le_mul_left' rw [succ_le_iff] exact lt_mul_succ_div b hd · rw [le_div H, mul_assoc] exact (mul_le_mul_left' (mul_div_le b d) a).trans (le_add_right _ c) theorem mul_div_mul_cancel {a : Ordinal} (ha : a ≠ 0) (b c) : a * b / (a * c) = b / c := by convert mul_add_div_mul (Ordinal.pos_iff_ne_zero.2 ha) b c using 1 rw [add_zero] @[simp] theorem div_one (a : Ordinal) : a / 1 = a := by simpa only [one_mul] using mul_div_cancel a Ordinal.one_ne_zero @[simp] theorem div_self {a : Ordinal} (h : a ≠ 0) : a / a = 1 := by simpa only [mul_one] using mul_div_cancel 1 h 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] 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 isLimit_sub 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 isLimit_add a h · simpa only [add_zero] 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⟩ 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] 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 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) 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 theorem mod_le (a b : Ordinal) : a % b ≤ a := sub_le_self a _ @[simp] theorem mod_zero (a : Ordinal) : a % 0 = a := by simp only [mod_def, div_zero, zero_mul, sub_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] @[simp] theorem zero_mod (b : Ordinal) : 0 % b = 0 := by simp only [mod_def, zero_div, mul_zero, sub_self] theorem div_add_mod (a b : Ordinal) : b * (a / b) + a % b = a := Ordinal.add_sub_cancel_of_le <| mul_div_le _ _ 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 @[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] @[simp] theorem mod_one (a : Ordinal) : a % 1 = 0 := by simp only [mod_def, div_one, one_mul, sub_self] 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⟩ 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] theorem dvd_iff_mod_eq_zero {a b : Ordinal} : b ∣ a ↔ a % b = 0 := ⟨mod_eq_zero_of_dvd, dvd_of_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] @[simp] theorem mul_mod (x y : Ordinal) : x * y % x = 0 := by simpa using mul_add_mod_self x y 0 theorem mul_add_mod_mul {w x : Ordinal} (hw : w < x) (y z : Ordinal) : (x * y + w) % (x * z) = x * (y % z) + w := by rw [mod_def, mul_add_div_mul hw] apply sub_eq_of_add_eq rw [← add_assoc, mul_assoc, ← mul_add, div_add_mod] theorem mul_mod_mul (x y z : Ordinal) : (x * y) % (x * z) = x * (y % z) := by obtain rfl | hx := Ordinal.eq_zero_or_pos x · simp · convert mul_add_mod_mul hx y z using 1 <;> rw [add_zero] 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] @[simp] theorem mod_mod (a b : Ordinal) : a % b % b = a % b := mod_mod_of_dvd a dvd_rfl /-! ### Casting naturals into ordinals, compatibility with operations -/ instance instCharZero : CharZero Ordinal := by refine ⟨fun a b h ↦ ?_⟩ rwa [← Cardinal.ord_nat, ← Cardinal.ord_nat, Cardinal.ord_inj, Nat.cast_inj] at h @[simp] theorem one_add_natCast (m : ℕ) : 1 + (m : Ordinal) = succ m := by rw [← Nat.cast_one, ← Nat.cast_add, add_comm] rfl @[simp] theorem one_add_ofNat (m : ℕ) [m.AtLeastTwo] : 1 + (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] @[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 (Nat.cast_le.2 h), Nat.cast_zero] · rw [← add_left_cancel_iff (a := ↑n), ← Nat.cast_add, add_tsub_cancel_of_le h, Ordinal.add_sub_cancel_of_le (Nat.cast_le.2 h)] @[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' : (n : Ordinal) ≠ 0 := Nat.cast_ne_zero.2 hn apply le_antisymm · rw [le_div hn', ← natCast_mul, Nat.cast_le, mul_comm] apply Nat.div_mul_le_self · rw [div_le hn', ← add_one_eq_succ, ← Nat.cast_succ, ← natCast_mul, Nat.cast_lt, mul_comm, ← Nat.div_lt_iff_lt_mul (Nat.pos_of_ne_zero hn)] apply Nat.lt_succ_self @[simp, norm_cast] theorem natCast_mod (m n : ℕ) : ((m % n : ℕ) : Ordinal) = m % n := by rw [← add_left_cancel_iff, div_add_mod, ← natCast_div, ← natCast_mul, ← Nat.cast_add, Nat.div_add_mod] @[simp] theorem lift_natCast : ∀ n : ℕ, lift.{u, v} n = n | 0 => by simp | n + 1 => by simp [lift_natCast n] @[simp] theorem lift_ofNat (n : ℕ) [n.AtLeastTwo] : lift.{u, v} ofNat(n) = OfNat.ofNat n := lift_natCast n theorem lt_omega0 {o : Ordinal} : o < ω ↔ ∃ n : ℕ, o = n := by simp_rw [← Cardinal.ord_aleph0, Cardinal.lt_ord, lt_aleph0, card_eq_nat] theorem nat_lt_omega0 (n : ℕ) : ↑n < ω := lt_omega0.2 ⟨_, rfl⟩ theorem eq_nat_or_omega0_le (o : Ordinal) : (∃ n : ℕ, o = n) ∨ ω ≤ o := by obtain ho | ho := lt_or_le o ω · exact Or.inl <| lt_omega0.1 ho · exact Or.inr ho theorem omega0_pos : 0 < ω := nat_lt_omega0 0 theorem omega0_ne_zero : ω ≠ 0 := omega0_pos.ne' theorem one_lt_omega0 : 1 < ω := by simpa only [Nat.cast_one] using nat_lt_omega0 1 theorem isLimit_omega0 : IsLimit ω := by rw [isLimit_iff, isSuccPrelimit_iff_succ_lt] refine ⟨omega0_ne_zero, fun o h => ?_⟩ obtain ⟨n, rfl⟩ := lt_omega0.1 h exact nat_lt_omega0 (n + 1) theorem omega0_le {o : Ordinal} : ω ≤ o ↔ ∀ n : ℕ, ↑n ≤ o := ⟨fun h n => (nat_lt_omega0 _).le.trans h, fun H => le_of_forall_lt fun a h => by let ⟨n, e⟩ := lt_omega0.1 h rw [e, ← succ_le_iff]; exact H (n + 1)⟩ theorem nat_lt_limit {o} (h : IsLimit o) : ∀ n : ℕ, ↑n < o | 0 => h.pos | n + 1 => h.succ_lt (nat_lt_limit h n) theorem omega0_le_of_isLimit {o} (h : IsLimit o) : ω ≤ o := omega0_le.2 fun n => le_of_lt <| nat_lt_limit h n theorem natCast_add_omega0 (n : ℕ) : n + ω = ω := by refine le_antisymm (le_of_forall_lt fun a ha ↦ ?_) (le_add_left _ _) obtain ⟨b, hb', hb⟩ := (lt_add_iff omega0_ne_zero).1 ha obtain ⟨m, rfl⟩ := lt_omega0.1 hb' apply hb.trans_lt exact_mod_cast nat_lt_omega0 (n + m) theorem one_add_omega0 : 1 + ω = ω := mod_cast natCast_add_omega0 1 theorem add_omega0 {a : Ordinal} (h : a < ω) : a + ω = ω := by obtain ⟨n, rfl⟩ := lt_omega0.1 h exact natCast_add_omega0 n @[simp] theorem natCast_add_of_omega0_le {o} (h : ω ≤ o) (n : ℕ) : n + o = o := by rw [← Ordinal.add_sub_cancel_of_le h, ← add_assoc, natCast_add_omega0] @[simp] theorem one_add_of_omega0_le {o} (h : ω ≤ o) : 1 + o = o := mod_cast natCast_add_of_omega0_le h 1 open Ordinal theorem isLimit_iff_omega0_dvd {a : Ordinal} : IsLimit a ↔ a ≠ 0 ∧ ω ∣ a := by refine ⟨fun l => ⟨l.ne_zero, ⟨a / ω, le_antisymm ?_ (mul_div_le _ _)⟩⟩, fun h => ?_⟩ · refine (limit_le l).2 fun x hx => le_of_lt ?_ rw [← div_lt omega0_ne_zero, ← succ_le_iff, le_div omega0_ne_zero, mul_succ, add_le_of_limit isLimit_omega0] intro b hb rcases lt_omega0.1 hb with ⟨n, rfl⟩ exact (add_le_add_right (mul_div_le _ _) _).trans (lt_sub.1 <| nat_lt_limit (isLimit_sub l hx) _).le · rcases h with ⟨a0, b, rfl⟩ refine isLimit_mul_left isLimit_omega0 (Ordinal.pos_iff_ne_zero.2 <| mt ?_ a0) intro e simp only [e, mul_zero] @[simp] theorem natCast_mod_omega0 (n : ℕ) : n % ω = n := mod_eq_of_lt (nat_lt_omega0 n) end Ordinal namespace Cardinal open Ordinal @[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_omega0_le] rwa [← ord_aleph0, ord_le_ord] theorem isLimit_ord {c} (co : ℵ₀ ≤ c) : (ord c).IsLimit := by rw [isLimit_iff, isSuccPrelimit_iff_succ_lt] refine ⟨fun h => aleph0_ne_zero ?_, fun a => lt_imp_lt_of_le_imp_le fun h => ?_⟩ · rw [← Ordinal.le_zero, ord_le] at h simpa only [card_zero, nonpos_iff_eq_zero] using co.trans h · rw [ord_le] at h ⊢ rwa [← @add_one_of_aleph0_le (card a), ← card_succ] rw [← ord_le, ← le_succ_of_isLimit, ord_le] · exact co.trans h · rw [ord_aleph0] exact Ordinal.isLimit_omega0 theorem noMaxOrder {c} (h : ℵ₀ ≤ c) : NoMaxOrder c.ord.toType := toType_noMax_of_succ_lt fun _ ↦ (isLimit_ord h).succ_lt end Cardinal
Mathlib/SetTheory/Ordinal/Arithmetic.lean
1,687
1,689
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro, Kim Morrison -/ import Mathlib.Tactic.NormNum.Basic import Mathlib.Tactic.TryThis import Mathlib.Util.AtomM /-! # The `abel` tactic Evaluate expressions in the language of additive, commutative monoids and groups. -/ -- TODO: assert_not_exists NonUnitalNonAssociativeSemiring assert_not_exists OrderedAddCommMonoid TopologicalSpace PseudoMetricSpace namespace Mathlib.Tactic.Abel open Lean Elab Meta Tactic Qq initialize registerTraceClass `abel initialize registerTraceClass `abel.detail /-- Tactic for evaluating equations in the language of *additive*, commutative monoids and groups. `abel` and its variants work as both tactics and conv tactics. * `abel1` fails if the target is not an equality that is provable by the axioms of commutative monoids/groups. * `abel_nf` rewrites all group expressions into a normal form. * In tactic mode, `abel_nf at h` can be used to rewrite in a hypothesis. * `abel_nf (config := cfg)` allows for additional configuration: * `red`: the reducibility setting (overridden by `!`) * `zetaDelta`: if true, local let variables can be unfolded (overridden by `!`) * `recursive`: if true, `abel_nf` will also recurse into atoms * `abel!`, `abel1!`, `abel_nf!` will use a more aggressive reducibility setting to identify atoms. For example: ``` example [AddCommMonoid α] (a b : α) : a + (b + a) = a + a + b := by abel example [AddCommGroup α] (a : α) : (3 : ℤ) • a = a + (2 : ℤ) • a := by abel ``` ## Future work * In mathlib 3, `abel` accepted additional optional arguments: ``` syntax "abel" (&" raw" <|> &" term")? (location)? : tactic ``` It is undecided whether these features should be restored eventually. -/ syntax (name := abel) "abel" "!"? : tactic /-- The `Context` for a call to `abel`. Stores a few options for this call, and caches some common subexpressions such as typeclass instances and `0 : α`. -/ structure Context where /-- The type of the ambient additive commutative group or monoid. -/ α : Expr /-- The universe level for `α`. -/ univ : Level /-- The expression representing `0 : α`. -/ α0 : Expr /-- Specify whether we are in an additive commutative group or an additive commutative monoid. -/ isGroup : Bool /-- The `AddCommGroup α` or `AddCommMonoid α` expression. -/ inst : Expr /-- Populate a `context` object for evaluating `e`. -/ def mkContext (e : Expr) : MetaM Context := do let α ← inferType e let c ← synthInstance (← mkAppM ``AddCommMonoid #[α]) let cg ← synthInstance? (← mkAppM ``AddCommGroup #[α]) let u ← mkFreshLevelMVar _ ← isDefEq (.sort (.succ u)) (← inferType α) let α0 ← Expr.ofNat α 0 match cg with | some cg => return ⟨α, u, α0, true, cg⟩ | _ => return ⟨α, u, α0, false, c⟩ /-- The monad for `Abel` contains, in addition to the `AtomM` state, some information about the current type we are working over, so that we can consistently use group lemmas or monoid lemmas as appropriate. -/ abbrev M := ReaderT Context AtomM /-- Apply the function `n : ∀ {α} [inst : AddWhatever α], _` to the implicit parameters in the context, and the given list of arguments. -/ def Context.app (c : Context) (n : Name) (inst : Expr) : Array Expr → Expr := mkAppN (((@Expr.const n [c.univ]).app c.α).app inst) /-- Apply the function `n : ∀ {α} [inst α], _` to the implicit parameters in the context, and the given list of arguments. Compared to `context.app`, this takes the name of the typeclass, rather than an inferred typeclass instance. -/ def Context.mkApp (c : Context) (n inst : Name) (l : Array Expr) : MetaM Expr := do return c.app n (← synthInstance ((Expr.const inst [c.univ]).app c.α)) l /-- Add the letter "g" to the end of the name, e.g. turning `term` into `termg`. This is used to choose between declarations taking `AddCommMonoid` and those taking `AddCommGroup` instances. -/ def addG : Name → Name | .str p s => .str p (s ++ "g") | n => n /-- Apply the function `n : ∀ {α} [AddComm{Monoid,Group} α]` to the given list of arguments. Will use the `AddComm{Monoid,Group}` instance that has been cached in the context. -/ def iapp (n : Name) (xs : Array Expr) : M Expr := do let c ← read return c.app (if c.isGroup then addG n else n) c.inst xs /-- A type synonym used by `abel` to represent `n • x + a` in an additive commutative monoid. -/ def term {α} [AddCommMonoid α] (n : ℕ) (x a : α) : α := n • x + a /-- A type synonym used by `abel` to represent `n • x + a` in an additive commutative group. -/ def termg {α} [AddCommGroup α] (n : ℤ) (x a : α) : α := n • x + a /-- Evaluate a term with coefficient `n`, atom `x` and successor terms `a`. -/ def mkTerm (n x a : Expr) : M Expr := iapp ``term #[n, x, a] /-- Interpret an integer as a coefficient to a term. -/ def intToExpr (n : ℤ) : M Expr := do Expr.ofInt (mkConst (if (← read).isGroup then ``Int else ``Nat) []) n /-- A normal form for `abel`. Expressions are represented as a list of terms of the form `e = n • x`, where `n : ℤ` and `x` is an arbitrary element of the additive commutative monoid or group. We explicitly track the `Expr` forms of `e` and `n`, even though they could be reconstructed, for efficiency. -/ inductive NormalExpr : Type | zero (e : Expr) : NormalExpr | nterm (e : Expr) (n : Expr × ℤ) (x : ℕ × Expr) (a : NormalExpr) : NormalExpr deriving Inhabited /-- Extract the expression from a normal form. -/ def NormalExpr.e : NormalExpr → Expr | .zero e => e | .nterm e .. => e instance : Coe NormalExpr Expr where coe := NormalExpr.e /-- Construct the normal form representing a single term. -/ def NormalExpr.term' (n : Expr × ℤ) (x : ℕ × Expr) (a : NormalExpr) : M NormalExpr := return .nterm (← mkTerm n.1 x.2 a) n x a /-- Construct the normal form representing zero. -/ def NormalExpr.zero' : M NormalExpr := return NormalExpr.zero (← read).α0 open NormalExpr theorem const_add_term {α} [AddCommMonoid α] (k n x a a') (h : k + a = a') : k + @term α _ n x a = term n x a' := by simp [h.symm, term, add_comm, add_assoc] theorem const_add_termg {α} [AddCommGroup α] (k n x a a') (h : k + a = a') : k + @termg α _ n x a = termg n x a' := by simp [h.symm, termg, add_comm, add_assoc] theorem term_add_const {α} [AddCommMonoid α] (n x a k a') (h : a + k = a') : @term α _ n x a + k = term n x a' := by simp [h.symm, term, add_assoc] theorem term_add_constg {α} [AddCommGroup α] (n x a k a') (h : a + k = a') : @termg α _ n x a + k = termg n x a' := by simp [h.symm, termg, add_assoc] theorem term_add_term {α} [AddCommMonoid α] (n₁ x a₁ n₂ a₂ n' a') (h₁ : n₁ + n₂ = n') (h₂ : a₁ + a₂ = a') : @term α _ n₁ x a₁ + @term α _ n₂ x a₂ = term n' x a' := by simp [h₁.symm, h₂.symm, term, add_nsmul, add_assoc, add_left_comm] theorem term_add_termg {α} [AddCommGroup α] (n₁ x a₁ n₂ a₂ n' a') (h₁ : n₁ + n₂ = n') (h₂ : a₁ + a₂ = a') : @termg α _ n₁ x a₁ + @termg α _ n₂ x a₂ = termg n' x a' := by simp only [termg, h₁.symm, add_zsmul, h₂.symm] exact add_add_add_comm (n₁ • x) a₁ (n₂ • x) a₂ theorem zero_term {α} [AddCommMonoid α] (x a) : @term α _ 0 x a = a := by simp [term, zero_nsmul, one_nsmul] theorem zero_termg {α} [AddCommGroup α] (x a) : @termg α _ 0 x a = a := by simp [termg, zero_zsmul] /-- Interpret the sum of two expressions in `abel`'s normal form. -/ partial def evalAdd : NormalExpr → NormalExpr → M (NormalExpr × Expr) | zero _, e₂ => do let p ← mkAppM ``zero_add #[e₂] return (e₂, p) | e₁, zero _ => do let p ← mkAppM ``add_zero #[e₁] return (e₁, p) | he₁@(nterm e₁ n₁ x₁ a₁), he₂@(nterm e₂ n₂ x₂ a₂) => do if x₁.1 = x₂.1 then let n' ← Mathlib.Meta.NormNum.eval (← mkAppM ``HAdd.hAdd #[n₁.1, n₂.1]) let (a', h₂) ← evalAdd a₁ a₂ let k := n₁.2 + n₂.2 let p₁ ← iapp ``term_add_term #[n₁.1, x₁.2, a₁, n₂.1, a₂, n'.expr, a', ← n'.getProof, h₂] if k = 0 then do let p ← mkEqTrans p₁ (← iapp ``zero_term #[x₁.2, a']) return (a', p) else return (← term' (n'.expr, k) x₁ a', p₁)
else if x₁.1 < x₂.1 then do let (a', h) ← evalAdd a₁ he₂
Mathlib/Tactic/Abel.lean
215
216
/- Copyright (c) 2021 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.MeasureTheory.Covering.VitaliFamily import Mathlib.MeasureTheory.Function.AEMeasurableOrder import Mathlib.MeasureTheory.Integral.Average import Mathlib.MeasureTheory.Measure.Decomposition.Lebesgue import Mathlib.MeasureTheory.Measure.Regular /-! # Differentiation of measures On a second countable metric space with a measure `μ`, consider a Vitali family (i.e., for each `x` one has a family of sets shrinking to `x`, with a good behavior with respect to covering theorems). Consider also another measure `ρ`. Then, for almost every `x`, the ratio `ρ a / μ a` converges when `a` shrinks to `x` along the Vitali family, towards the Radon-Nikodym derivative of `ρ` with respect to `μ`. This is the main theorem on differentiation of measures. This theorem is proved in this file, under the name `VitaliFamily.ae_tendsto_rnDeriv`. Note that, almost surely, `μ a` is eventually positive and finite (see `VitaliFamily.ae_eventually_measure_pos` and `VitaliFamily.eventually_measure_lt_top`), so the ratio really makes sense. For concrete applications, one needs concrete instances of Vitali families, as provided for instance by `Besicovitch.vitaliFamily` (for balls) or by `Vitali.vitaliFamily` (for doubling measures). Specific applications to Lebesgue density points and the Lebesgue differentiation theorem are also derived: * `VitaliFamily.ae_tendsto_measure_inter_div` states that, for almost every point `x ∈ s`, then `μ (s ∩ a) / μ a` tends to `1` as `a` shrinks to `x` along a Vitali family. * `VitaliFamily.ae_tendsto_average_norm_sub` states that, for almost every point `x`, then the average of `y ↦ ‖f y - f x‖` on `a` tends to `0` as `a` shrinks to `x` along a Vitali family. ## Sketch of proof Let `v` be a Vitali family for `μ`. Assume for simplicity that `ρ` is absolutely continuous with respect to `μ`, as the case of a singular measure is easier. It is easy to see that a set `s` on which `liminf ρ a / μ a < q` satisfies `ρ s ≤ q * μ s`, by using a disjoint subcovering provided by the definition of Vitali families. Similarly for the limsup. It follows that a set on which `ρ a / μ a` oscillates has measure `0`, and therefore that `ρ a / μ a` converges almost surely (`VitaliFamily.ae_tendsto_div`). Moreover, on a set where the limit is close to a constant `c`, one gets `ρ s ∼ c μ s`, using again a covering lemma as above. It follows that `ρ` is equal to `μ.withDensity (v.limRatio ρ x)`, where `v.limRatio ρ x` is the limit of `ρ a / μ a` at `x` (which is well defined almost everywhere). By uniqueness of the Radon-Nikodym derivative, one gets `v.limRatio ρ x = ρ.rnDeriv μ x` almost everywhere, completing the proof. There is a difficulty in this sketch: this argument works well when `v.limRatio ρ` is measurable, but there is no guarantee that this is the case, especially if one doesn't make further assumptions on the Vitali family. We use an indirect argument to show that `v.limRatio ρ` is always almost everywhere measurable, again based on the disjoint subcovering argument (see `VitaliFamily.exists_measurable_supersets_limRatio`), and then proceed as sketched above but replacing `v.limRatio ρ` by a measurable version called `v.limRatioMeas ρ`. ## Counterexample The standing assumption in this file is that spaces are second countable. Without this assumption, measures may be zero locally but nonzero globally, which is not compatible with differentiation theory (which deduces global information from local one). Here is an example displaying this behavior. Define a measure `μ` by `μ s = 0` if `s` is covered by countably many balls of radius `1`, and `μ s = ∞` otherwise. This is indeed a countably additive measure, which is moreover locally finite and doubling at small scales. It vanishes on every ball of radius `1`, so all the quantities in differentiation theory (defined as ratios of measures as the radius tends to zero) make no sense. However, the measure is not globally zero if the space is big enough. ## References * [Herbert Federer, Geometric Measure Theory, Chapter 2.9][Federer1996] -/ open MeasureTheory Metric Set Filter TopologicalSpace MeasureTheory.Measure open scoped Filter ENNReal MeasureTheory NNReal Topology variable {α : Type*} [PseudoMetricSpace α] {m0 : MeasurableSpace α} {μ : Measure α} (v : VitaliFamily μ) {E : Type*} [NormedAddCommGroup E] namespace VitaliFamily /-- The limit along a Vitali family of `ρ a / μ a` where it makes sense, and garbage otherwise. Do *not* use this definition: it is only a temporary device to show that this ratio tends almost everywhere to the Radon-Nikodym derivative. -/ noncomputable def limRatio (ρ : Measure α) (x : α) : ℝ≥0∞ := limUnder (v.filterAt x) fun a => ρ a / μ a /-- For almost every point `x`, sufficiently small sets in a Vitali family around `x` have positive measure. (This is a nontrivial result, following from the covering property of Vitali families). -/ theorem ae_eventually_measure_pos [SecondCountableTopology α] : ∀ᵐ x ∂μ, ∀ᶠ a in v.filterAt x, 0 < μ a := by set s := {x | ¬∀ᶠ a in v.filterAt x, 0 < μ a} with hs simp -zeta only [not_lt, not_eventually, nonpos_iff_eq_zero] at hs change μ s = 0 let f : α → Set (Set α) := fun _ => {a | μ a = 0} have h : v.FineSubfamilyOn f s := by intro x hx ε εpos rw [hs] at hx simp only [frequently_filterAt_iff, exists_prop, gt_iff_lt, mem_setOf_eq] at hx rcases hx ε εpos with ⟨a, a_sets, ax, μa⟩ exact ⟨a, ⟨a_sets, μa⟩, ax⟩ refine le_antisymm ?_ bot_le calc μ s ≤ ∑' x : h.index, μ (h.covering x) := h.measure_le_tsum _ = ∑' x : h.index, 0 := by congr; ext1 x; exact h.covering_mem x.2 _ = 0 := by simp only [tsum_zero, add_zero] /-- For every point `x`, sufficiently small sets in a Vitali family around `x` have finite measure. (This is a trivial result, following from the fact that the measure is locally finite). -/ theorem eventually_measure_lt_top [IsLocallyFiniteMeasure μ] (x : α) : ∀ᶠ a in v.filterAt x, μ a < ∞ := (μ.finiteAt_nhds x).eventually.filter_mono inf_le_left /-- If two measures `ρ` and `ν` have, at every point of a set `s`, arbitrarily small sets in a Vitali family satisfying `ρ a ≤ ν a`, then `ρ s ≤ ν s` if `ρ ≪ μ`. -/ theorem measure_le_of_frequently_le [SecondCountableTopology α] [BorelSpace α] {ρ : Measure α} (ν : Measure α) [IsLocallyFiniteMeasure ν] (hρ : ρ ≪ μ) (s : Set α) (hs : ∀ x ∈ s, ∃ᶠ a in v.filterAt x, ρ a ≤ ν a) : ρ s ≤ ν s := by -- this follows from a covering argument using the sets satisfying `ρ a ≤ ν a`. apply ENNReal.le_of_forall_pos_le_add fun ε εpos _ => ?_ obtain ⟨U, sU, U_open, νU⟩ : ∃ (U : Set α), s ⊆ U ∧ IsOpen U ∧ ν U ≤ ν s + ε := exists_isOpen_le_add s ν (ENNReal.coe_pos.2 εpos).ne' let f : α → Set (Set α) := fun _ => {a | ρ a ≤ ν a ∧ a ⊆ U} have h : v.FineSubfamilyOn f s := by apply v.fineSubfamilyOn_of_frequently f s fun x hx => ?_ have := (hs x hx).and_eventually ((v.eventually_filterAt_mem_setsAt x).and (v.eventually_filterAt_subset_of_nhds (U_open.mem_nhds (sU hx)))) apply Frequently.mono this rintro a ⟨ρa, _, aU⟩ exact ⟨ρa, aU⟩ haveI : Encodable h.index := h.index_countable.toEncodable calc ρ s ≤ ∑' x : h.index, ρ (h.covering x) := h.measure_le_tsum_of_absolutelyContinuous hρ _ ≤ ∑' x : h.index, ν (h.covering x) := ENNReal.tsum_le_tsum fun x => (h.covering_mem x.2).1 _ = ν (⋃ x : h.index, h.covering x) := by rw [measure_iUnion h.covering_disjoint_subtype fun i => h.measurableSet_u i.2] _ ≤ ν U := (measure_mono (iUnion_subset fun i => (h.covering_mem i.2).2)) _ ≤ ν s + ε := νU theorem eventually_filterAt_integrableOn (x : α) {f : α → E} (hf : LocallyIntegrable f μ) : ∀ᶠ a in v.filterAt x, IntegrableOn f a μ := by rcases hf x with ⟨w, w_nhds, hw⟩ filter_upwards [v.eventually_filterAt_subset_of_nhds w_nhds] with a ha exact hw.mono_set ha section variable [SecondCountableTopology α] [BorelSpace α] [IsLocallyFiniteMeasure μ] {ρ : Measure α} [IsLocallyFiniteMeasure ρ] /-- If a measure `ρ` is singular with respect to `μ`, then for `μ` almost every `x`, the ratio `ρ a / μ a` tends to zero when `a` shrinks to `x` along the Vitali family. This makes sense as `μ a` is eventually positive by `ae_eventually_measure_pos`. -/ theorem ae_eventually_measure_zero_of_singular (hρ : ρ ⟂ₘ μ) : ∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 0) := by have A : ∀ ε > (0 : ℝ≥0), ∀ᵐ x ∂μ, ∀ᶠ a in v.filterAt x, ρ a < ε * μ a := by intro ε εpos set s := {x | ¬∀ᶠ a in v.filterAt x, ρ a < ε * μ a} with hs change μ s = 0 obtain ⟨o, _, ρo, μo⟩ : ∃ o : Set α, MeasurableSet o ∧ ρ o = 0 ∧ μ oᶜ = 0 := hρ apply le_antisymm _ bot_le calc μ s ≤ μ (s ∩ o ∪ oᶜ) := by conv_lhs => rw [← inter_union_compl s o] gcongr apply inter_subset_right _ ≤ μ (s ∩ o) + μ oᶜ := measure_union_le _ _ _ = μ (s ∩ o) := by rw [μo, add_zero] _ = (ε : ℝ≥0∞)⁻¹ * (ε • μ) (s ∩ o) := by simp only [coe_nnreal_smul_apply, ← mul_assoc, mul_comm _ (ε : ℝ≥0∞)] rw [ENNReal.mul_inv_cancel (ENNReal.coe_pos.2 εpos).ne' ENNReal.coe_ne_top, one_mul] _ ≤ (ε : ℝ≥0∞)⁻¹ * ρ (s ∩ o) := by gcongr refine v.measure_le_of_frequently_le ρ smul_absolutelyContinuous _ ?_ intro x hx rw [hs] at hx simp only [mem_inter_iff, not_lt, not_eventually, mem_setOf_eq] at hx exact hx.1 _ ≤ (ε : ℝ≥0∞)⁻¹ * ρ o := by gcongr; apply inter_subset_right _ = 0 := by rw [ρo, mul_zero] obtain ⟨u, _, u_pos, u_lim⟩ : ∃ u : ℕ → ℝ≥0, StrictAnti u ∧ (∀ n : ℕ, 0 < u n) ∧ Tendsto u atTop (𝓝 0) := exists_seq_strictAnti_tendsto (0 : ℝ≥0) have B : ∀ᵐ x ∂μ, ∀ n, ∀ᶠ a in v.filterAt x, ρ a < u n * μ a := ae_all_iff.2 fun n => A (u n) (u_pos n) filter_upwards [B, v.ae_eventually_measure_pos] intro x hx h'x refine tendsto_order.2 ⟨fun z hz => (ENNReal.not_lt_zero hz).elim, fun z hz => ?_⟩ obtain ⟨w, w_pos, w_lt⟩ : ∃ w : ℝ≥0, (0 : ℝ≥0∞) < w ∧ (w : ℝ≥0∞) < z := ENNReal.lt_iff_exists_nnreal_btwn.1 hz obtain ⟨n, hn⟩ : ∃ n, u n < w := ((tendsto_order.1 u_lim).2 w (ENNReal.coe_pos.1 w_pos)).exists filter_upwards [hx n, h'x, v.eventually_measure_lt_top x] intro a ha μa_pos μa_lt_top rw [ENNReal.div_lt_iff (Or.inl μa_pos.ne') (Or.inl μa_lt_top.ne)] exact ha.trans_le (mul_le_mul_right' ((ENNReal.coe_le_coe.2 hn.le).trans w_lt.le) _) section AbsolutelyContinuous variable (hρ : ρ ≪ μ) include hρ /-- A set of points `s` satisfying both `ρ a ≤ c * μ a` and `ρ a ≥ d * μ a` at arbitrarily small sets in a Vitali family has measure `0` if `c < d`. Indeed, the first inequality should imply that `ρ s ≤ c * μ s`, and the second one that `ρ s ≥ d * μ s`, a contradiction if `0 < μ s`. -/ theorem null_of_frequently_le_of_frequently_ge {c d : ℝ≥0} (hcd : c < d) (s : Set α) (hc : ∀ x ∈ s, ∃ᶠ a in v.filterAt x, ρ a ≤ c * μ a) (hd : ∀ x ∈ s, ∃ᶠ a in v.filterAt x, (d : ℝ≥0∞) * μ a ≤ ρ a) : μ s = 0 := by apply measure_null_of_locally_null s fun x _ => ?_ obtain ⟨o, xo, o_open, μo⟩ : ∃ o : Set α, x ∈ o ∧ IsOpen o ∧ μ o < ∞ := Measure.exists_isOpen_measure_lt_top μ x refine ⟨s ∩ o, inter_mem_nhdsWithin _ (o_open.mem_nhds xo), ?_⟩ let s' := s ∩ o by_contra h apply lt_irrefl (ρ s') calc ρ s' ≤ c * μ s' := v.measure_le_of_frequently_le (c • μ) hρ s' fun x hx => hc x hx.1 _ < d * μ s' := by apply (ENNReal.mul_lt_mul_right h _).2 (ENNReal.coe_lt_coe.2 hcd) exact (lt_of_le_of_lt (measure_mono inter_subset_right) μo).ne _ ≤ ρ s' := v.measure_le_of_frequently_le ρ smul_absolutelyContinuous s' fun x hx ↦ hd x hx.1 /-- If `ρ` is absolutely continuous with respect to `μ`, then for almost every `x`, the ratio `ρ a / μ a` converges as `a` shrinks to `x` along a Vitali family for `μ`. -/ theorem ae_tendsto_div : ∀ᵐ x ∂μ, ∃ c, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 c) := by obtain ⟨w, w_count, w_dense, _, w_top⟩ : ∃ w : Set ℝ≥0∞, w.Countable ∧ Dense w ∧ 0 ∉ w ∧ ∞ ∉ w := ENNReal.exists_countable_dense_no_zero_top have I : ∀ x ∈ w, x ≠ ∞ := fun x xs hx => w_top (hx ▸ xs) have A : ∀ c ∈ w, ∀ d ∈ w, c < d → ∀ᵐ x ∂μ, ¬((∃ᶠ a in v.filterAt x, ρ a / μ a < c) ∧ ∃ᶠ a in v.filterAt x, d < ρ a / μ a) := by intro c hc d hd hcd lift c to ℝ≥0 using I c hc lift d to ℝ≥0 using I d hd apply v.null_of_frequently_le_of_frequently_ge hρ (ENNReal.coe_lt_coe.1 hcd) · simp only [and_imp, exists_prop, not_frequently, not_and, not_lt, not_le, not_eventually, mem_setOf_eq, mem_compl_iff, not_forall] intro x h1x _ apply h1x.mono fun a ha => ?_ refine (ENNReal.div_le_iff_le_mul ?_ (Or.inr (bot_le.trans_lt ha).ne')).1 ha.le simp only [ENNReal.coe_ne_top, Ne, or_true, not_false_iff] · simp only [and_imp, exists_prop, not_frequently, not_and, not_lt, not_le, not_eventually, mem_setOf_eq, mem_compl_iff, not_forall] intro x _ h2x apply h2x.mono fun a ha => ?_ exact ENNReal.mul_le_of_le_div ha.le have B : ∀ᵐ x ∂μ, ∀ c ∈ w, ∀ d ∈ w, c < d → ¬((∃ᶠ a in v.filterAt x, ρ a / μ a < c) ∧ ∃ᶠ a in v.filterAt x, d < ρ a / μ a) := by #adaptation_note /-- 2024-04-23 The next two lines were previously just `simpa only [ae_ball_iff w_count, ae_all_iff]` -/ rw [ae_ball_iff w_count]; intro x hx; rw [ae_ball_iff w_count]; revert x simpa only [ae_all_iff] filter_upwards [B] intro x hx exact tendsto_of_no_upcrossings w_dense hx theorem ae_tendsto_limRatio : ∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) := by filter_upwards [v.ae_tendsto_div hρ] intro x hx exact tendsto_nhds_limUnder hx /-- Given two thresholds `p < q`, the sets `{x | v.limRatio ρ x < p}` and `{x | q < v.limRatio ρ x}` are obviously disjoint. The key to proving that `v.limRatio ρ` is almost everywhere measurable is to show that these sets have measurable supersets which are also disjoint, up to zero measure. This is the content of this lemma. -/ theorem exists_measurable_supersets_limRatio {p q : ℝ≥0} (hpq : p < q) : ∃ a b, MeasurableSet a ∧ MeasurableSet b ∧ {x | v.limRatio ρ x < p} ⊆ a ∧ {x | (q : ℝ≥0∞) < v.limRatio ρ x} ⊆ b ∧ μ (a ∩ b) = 0 := by /- Here is a rough sketch, assuming that the measure is finite and the limit is well defined everywhere. Let `u := {x | v.limRatio ρ x < p}` and `w := {x | q < v.limRatio ρ x}`. They have measurable supersets `u'` and `w'` of the same measure. We will show that these satisfy the conclusion of the theorem, i.e., `μ (u' ∩ w') = 0`. For this, note that `ρ (u' ∩ w') = ρ (u ∩ w')` (as `w'` is measurable, see `measure_toMeasurable_add_inter_left`). The latter set is included in the set where the limit of the ratios is `< p`, and therefore its measure is `≤ p * μ (u ∩ w')`. Using the same trick in the other direction gives that this is `p * μ (u' ∩ w')`. We have shown that `ρ (u' ∩ w') ≤ p * μ (u' ∩ w')`. Arguing in the same way but using the `w` part gives `q * μ (u' ∩ w') ≤ ρ (u' ∩ w')`. If `μ (u' ∩ w')` were nonzero, this would be a contradiction as `p < q`. For the rigorous proof, we need to work on a part of the space where the measure is finite (provided by `spanningSets (ρ + μ)`) and to restrict to the set where the limit is well defined (called `s` below, of full measure). Otherwise, the argument goes through. -/ let s := {x | ∃ c, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 c)} let o : ℕ → Set α := spanningSets (ρ + μ) let u n := s ∩ {x | v.limRatio ρ x < p} ∩ o n let w n := s ∩ {x | (q : ℝ≥0∞) < v.limRatio ρ x} ∩ o n -- the supersets are obtained by restricting to the set `s` where the limit is well defined, to -- a finite measure part `o n`, taking a measurable superset here, and then taking the union over -- `n`. refine ⟨toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (u n), toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (w n), ?_, ?_, ?_, ?_, ?_⟩ -- check that these sets are measurable supersets as required · exact (measurableSet_toMeasurable _ _).union (MeasurableSet.iUnion fun n => measurableSet_toMeasurable _ _) · exact (measurableSet_toMeasurable _ _).union (MeasurableSet.iUnion fun n => measurableSet_toMeasurable _ _) · intro x hx by_cases h : x ∈ s · refine Or.inr (mem_iUnion.2 ⟨spanningSetsIndex (ρ + μ) x, ?_⟩) exact subset_toMeasurable _ _ ⟨⟨h, hx⟩, mem_spanningSetsIndex _ _⟩ · exact Or.inl (subset_toMeasurable μ sᶜ h) · intro x hx by_cases h : x ∈ s · refine Or.inr (mem_iUnion.2 ⟨spanningSetsIndex (ρ + μ) x, ?_⟩) exact subset_toMeasurable _ _ ⟨⟨h, hx⟩, mem_spanningSetsIndex _ _⟩ · exact Or.inl (subset_toMeasurable μ sᶜ h) -- it remains to check the nontrivial part that these sets have zero measure intersection. -- it suffices to do it for fixed `m` and `n`, as one is taking countable unions. suffices H : ∀ m n : ℕ, μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) = 0 by have A : (toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (u n)) ∩ (toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (w n)) ⊆ toMeasurable μ sᶜ ∪ ⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n) := by simp only [inter_union_distrib_left, union_inter_distrib_right, true_and, subset_union_left, union_subset_iff, inter_self] refine ⟨?_, ?_, ?_⟩ · exact inter_subset_right.trans subset_union_left · exact inter_subset_left.trans subset_union_left · simp_rw [iUnion_inter, inter_iUnion]; exact subset_union_right refine le_antisymm ((measure_mono A).trans ?_) bot_le calc μ (toMeasurable μ sᶜ ∪ ⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤ μ (toMeasurable μ sᶜ) + μ (⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := measure_union_le _ _ _ = μ (⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by have : μ sᶜ = 0 := v.ae_tendsto_div hρ; rw [measure_toMeasurable, this, zero_add] _ ≤ ∑' (m) (n), μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := ((measure_iUnion_le _).trans (ENNReal.tsum_le_tsum fun m => measure_iUnion_le _)) _ = 0 := by simp only [H, tsum_zero] -- now starts the nontrivial part of the argument. We fix `m` and `n`, and show that the -- measurable supersets of `u m` and `w n` have zero measure intersection by using the lemmas -- `measure_toMeasurable_add_inter_left` (to reduce to `u m` or `w n` instead of the measurable -- superset) and `measure_le_of_frequently_le` to compare their measures for `ρ` and `μ`. intro m n have I : (ρ + μ) (u m) ≠ ∞ := by apply (lt_of_le_of_lt (measure_mono _) (measure_spanningSets_lt_top (ρ + μ) m)).ne exact inter_subset_right have J : (ρ + μ) (w n) ≠ ∞ := by apply (lt_of_le_of_lt (measure_mono _) (measure_spanningSets_lt_top (ρ + μ) n)).ne exact inter_subset_right have A : ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤ p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := calc ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) = ρ (u m ∩ toMeasurable (ρ + μ) (w n)) := measure_toMeasurable_add_inter_left (measurableSet_toMeasurable _ _) I _ ≤ (p • μ) (u m ∩ toMeasurable (ρ + μ) (w n)) := by refine v.measure_le_of_frequently_le (p • μ) hρ _ fun x hx => ?_ have L : Tendsto (fun a : Set α => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) := tendsto_nhds_limUnder hx.1.1.1 have I : ∀ᶠ b : Set α in v.filterAt x, ρ b / μ b < p := (tendsto_order.1 L).2 _ hx.1.1.2 apply I.frequently.mono fun a ha => ?_ rw [coe_nnreal_smul_apply] refine (ENNReal.div_le_iff_le_mul ?_ (Or.inr (bot_le.trans_lt ha).ne')).1 ha.le simp only [ENNReal.coe_ne_top, Ne, or_true, not_false_iff] _ = p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by simp only [coe_nnreal_smul_apply, measure_toMeasurable_add_inter_right (measurableSet_toMeasurable _ _) I] have B : (q : ℝ≥0∞) * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤ ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := calc (q : ℝ≥0∞) * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) = (q : ℝ≥0∞) * μ (toMeasurable (ρ + μ) (u m) ∩ w n) := by conv_rhs => rw [inter_comm] rw [inter_comm, measure_toMeasurable_add_inter_right (measurableSet_toMeasurable _ _) J] _ ≤ ρ (toMeasurable (ρ + μ) (u m) ∩ w n) := by rw [← coe_nnreal_smul_apply] refine v.measure_le_of_frequently_le _ (.smul_left .rfl _) _ ?_ intro x hx have L : Tendsto (fun a : Set α => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) := tendsto_nhds_limUnder hx.2.1.1 have I : ∀ᶠ b : Set α in v.filterAt x, (q : ℝ≥0∞) < ρ b / μ b := (tendsto_order.1 L).1 _ hx.2.1.2 apply I.frequently.mono fun a ha => ?_ rw [coe_nnreal_smul_apply] exact ENNReal.mul_le_of_le_div ha.le _ = ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by conv_rhs => rw [inter_comm] rw [inter_comm] exact (measure_toMeasurable_add_inter_left (measurableSet_toMeasurable _ _) J).symm by_contra h apply lt_irrefl (ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n))) calc ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤ p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := A _ < q * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by gcongr suffices H : (ρ + μ) (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≠ ∞ by simp only [not_or, ENNReal.add_eq_top, Pi.add_apply, Ne, coe_add] at H exact H.2 apply (lt_of_le_of_lt (measure_mono inter_subset_left) _).ne rw [measure_toMeasurable] apply lt_of_le_of_lt (measure_mono _) (measure_spanningSets_lt_top (ρ + μ) m) exact inter_subset_right _ ≤ ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := B theorem aemeasurable_limRatio : AEMeasurable (v.limRatio ρ) μ := by apply ENNReal.aemeasurable_of_exist_almost_disjoint_supersets _ _ fun p q hpq => ?_ exact v.exists_measurable_supersets_limRatio hρ hpq /-- A measurable version of `v.limRatio ρ`. Do *not* use this definition: it is only a temporary device to show that `v.limRatio` is almost everywhere equal to the Radon-Nikodym derivative. -/ noncomputable def limRatioMeas : α → ℝ≥0∞ := (v.aemeasurable_limRatio hρ).mk _ theorem limRatioMeas_measurable : Measurable (v.limRatioMeas hρ) := AEMeasurable.measurable_mk _ theorem ae_tendsto_limRatioMeas : ∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatioMeas hρ x)) := by filter_upwards [v.ae_tendsto_limRatio hρ, AEMeasurable.ae_eq_mk (v.aemeasurable_limRatio hρ)] intro x hx h'x rwa [h'x] at hx /-- If, for all `x` in a set `s`, one has frequently `ρ a / μ a < p`, then `ρ s ≤ p * μ s`, as proved in `measure_le_of_frequently_le`. Since `ρ a / μ a` tends almost everywhere to `v.limRatioMeas hρ x`, the same property holds for sets `s` on which `v.limRatioMeas hρ < p`. -/ theorem measure_le_mul_of_subset_limRatioMeas_lt {p : ℝ≥0} {s : Set α} (h : s ⊆ {x | v.limRatioMeas hρ x < p}) : ρ s ≤ p * μ s := by let t := {x : α | Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatioMeas hρ x))} have A : μ tᶜ = 0 := v.ae_tendsto_limRatioMeas hρ suffices H : ρ (s ∩ t) ≤ (p • μ) (s ∩ t) by calc ρ s = ρ (s ∩ t ∪ s ∩ tᶜ) := by rw [inter_union_compl] _ ≤ ρ (s ∩ t) + ρ (s ∩ tᶜ) := measure_union_le _ _ _ ≤ (p • μ) (s ∩ t) + ρ tᶜ := by gcongr; apply inter_subset_right _ ≤ p * μ (s ∩ t) := by simp [(hρ A)] _ ≤ p * μ s := by gcongr; apply inter_subset_left refine v.measure_le_of_frequently_le (p • μ) hρ _ fun x hx => ?_ have I : ∀ᶠ b : Set α in v.filterAt x, ρ b / μ b < p := (tendsto_order.1 hx.2).2 _ (h hx.1) apply I.frequently.mono fun a ha => ?_ rw [coe_nnreal_smul_apply] refine (ENNReal.div_le_iff_le_mul ?_ (Or.inr (bot_le.trans_lt ha).ne')).1 ha.le simp only [ENNReal.coe_ne_top, Ne, or_true, not_false_iff] /-- If, for all `x` in a set `s`, one has frequently `q < ρ a / μ a`, then `q * μ s ≤ ρ s`, as proved in `measure_le_of_frequently_le`. Since `ρ a / μ a` tends almost everywhere to `v.limRatioMeas hρ x`, the same property holds for sets `s` on which `q < v.limRatioMeas hρ`. -/ theorem mul_measure_le_of_subset_lt_limRatioMeas {q : ℝ≥0} {s : Set α} (h : s ⊆ {x | (q : ℝ≥0∞) < v.limRatioMeas hρ x}) : (q : ℝ≥0∞) * μ s ≤ ρ s := by let t := {x : α | Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatioMeas hρ x))} have A : μ tᶜ = 0 := v.ae_tendsto_limRatioMeas hρ suffices H : (q • μ) (s ∩ t) ≤ ρ (s ∩ t) by calc (q • μ) s = (q • μ) (s ∩ t ∪ s ∩ tᶜ) := by rw [inter_union_compl] _ ≤ (q • μ) (s ∩ t) + (q • μ) (s ∩ tᶜ) := measure_union_le _ _ _ ≤ ρ (s ∩ t) + (q • μ) tᶜ := by gcongr; apply inter_subset_right _ = ρ (s ∩ t) := by simp [A] _ ≤ ρ s := by gcongr; apply inter_subset_left refine v.measure_le_of_frequently_le _ (.smul_left .rfl _) _ ?_ intro x hx have I : ∀ᶠ a in v.filterAt x, (q : ℝ≥0∞) < ρ a / μ a := (tendsto_order.1 hx.2).1 _ (h hx.1) apply I.frequently.mono fun a ha => ?_ rw [coe_nnreal_smul_apply] exact ENNReal.mul_le_of_le_div ha.le /-- The points with `v.limRatioMeas hρ x = ∞` have measure `0` for `μ`. -/ theorem measure_limRatioMeas_top : μ {x | v.limRatioMeas hρ x = ∞} = 0 := by refine measure_null_of_locally_null _ fun x _ => ?_ obtain ⟨o, xo, o_open, μo⟩ : ∃ o : Set α, x ∈ o ∧ IsOpen o ∧ ρ o < ∞ := Measure.exists_isOpen_measure_lt_top ρ x let s := {x : α | v.limRatioMeas hρ x = ∞} ∩ o refine ⟨s, inter_mem_nhdsWithin _ (o_open.mem_nhds xo), le_antisymm ?_ bot_le⟩ have ρs : ρ s ≠ ∞ := ((measure_mono inter_subset_right).trans_lt μo).ne have A : ∀ q : ℝ≥0, 1 ≤ q → μ s ≤ (q : ℝ≥0∞)⁻¹ * ρ s := by intro q hq rw [mul_comm, ← div_eq_mul_inv, ENNReal.le_div_iff_mul_le _ (Or.inr ρs), mul_comm] · apply v.mul_measure_le_of_subset_lt_limRatioMeas hρ intro y hy have : v.limRatioMeas hρ y = ∞ := hy.1 simp only [this, ENNReal.coe_lt_top, mem_setOf_eq] · simp only [(zero_lt_one.trans_le hq).ne', true_or, ENNReal.coe_eq_zero, Ne, not_false_iff] have B : Tendsto (fun q : ℝ≥0 => (q : ℝ≥0∞)⁻¹ * ρ s) atTop (𝓝 (∞⁻¹ * ρ s)) := by apply ENNReal.Tendsto.mul_const _ (Or.inr ρs) exact ENNReal.tendsto_inv_iff.2 (ENNReal.tendsto_coe_nhds_top.2 tendsto_id) simp only [zero_mul, ENNReal.inv_top] at B apply ge_of_tendsto B exact eventually_atTop.2 ⟨1, A⟩ /-- The points with `v.limRatioMeas hρ x = 0` have measure `0` for `ρ`. -/ theorem measure_limRatioMeas_zero : ρ {x | v.limRatioMeas hρ x = 0} = 0 := by refine measure_null_of_locally_null _ fun x _ => ?_ obtain ⟨o, xo, o_open, μo⟩ : ∃ o : Set α, x ∈ o ∧ IsOpen o ∧ μ o < ∞ := Measure.exists_isOpen_measure_lt_top μ x let s := {x : α | v.limRatioMeas hρ x = 0} ∩ o refine ⟨s, inter_mem_nhdsWithin _ (o_open.mem_nhds xo), le_antisymm ?_ bot_le⟩ have μs : μ s ≠ ∞ := ((measure_mono inter_subset_right).trans_lt μo).ne have A : ∀ q : ℝ≥0, 0 < q → ρ s ≤ q * μ s := by intro q hq apply v.measure_le_mul_of_subset_limRatioMeas_lt hρ intro y hy have : v.limRatioMeas hρ y = 0 := hy.1 simp only [this, mem_setOf_eq, hq, ENNReal.coe_pos] have B : Tendsto (fun q : ℝ≥0 => (q : ℝ≥0∞) * μ s) (𝓝[>] (0 : ℝ≥0)) (𝓝 ((0 : ℝ≥0) * μ s)) := by apply ENNReal.Tendsto.mul_const _ (Or.inr μs) rw [ENNReal.tendsto_coe] exact nhdsWithin_le_nhds simp only [zero_mul, ENNReal.coe_zero] at B apply ge_of_tendsto B filter_upwards [self_mem_nhdsWithin] using A /-- As an intermediate step to show that `μ.withDensity (v.limRatioMeas hρ) = ρ`, we show here that `μ.withDensity (v.limRatioMeas hρ) ≤ t^2 ρ` for any `t > 1`. -/ theorem withDensity_le_mul {s : Set α} (hs : MeasurableSet s) {t : ℝ≥0} (ht : 1 < t) : μ.withDensity (v.limRatioMeas hρ) s ≤ (t : ℝ≥0∞) ^ 2 * ρ s := by /- We cut `s` into the sets where `v.limRatioMeas hρ = 0`, where `v.limRatioMeas hρ = ∞`, and where `v.limRatioMeas hρ ∈ [t^n, t^(n+1))` for `n : ℤ`. The first and second have measure `0`. For the latter, since `v.limRatioMeas hρ` fluctuates by at most `t` on this slice, we can use `measure_le_mul_of_subset_limRatioMeas_lt` and `mul_measure_le_of_subset_lt_limRatioMeas` to show that the two measures are comparable up to `t` (in fact `t^2` for technical reasons of strict inequalities). -/ have t_ne_zero' : t ≠ 0 := (zero_lt_one.trans ht).ne' have t_ne_zero : (t : ℝ≥0∞) ≠ 0 := by simpa only [ENNReal.coe_eq_zero, Ne] using t_ne_zero' let ν := μ.withDensity (v.limRatioMeas hρ) let f := v.limRatioMeas hρ have f_meas : Measurable f := v.limRatioMeas_measurable hρ -- Note(kmill): smul elaborator when used for CoeFun fails to get CoeFun instance to trigger -- unless you use the `(... :)` notation. Another fix is using `(2 : Nat)`, so this appears -- to be an unpleasant interaction with default instances. have A : ν (s ∩ f ⁻¹' {0}) ≤ ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {0}) := by apply le_trans _ (zero_le _) have M : MeasurableSet (s ∩ f ⁻¹' {0}) := hs.inter (f_meas (measurableSet_singleton _)) simp only [f, ν, nonpos_iff_eq_zero, M, withDensity_apply, lintegral_eq_zero_iff f_meas] apply (ae_restrict_iff' M).2 exact Eventually.of_forall fun x hx => hx.2 have B : ν (s ∩ f ⁻¹' {∞}) ≤ ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {∞}) := by apply le_trans (le_of_eq _) (zero_le _) apply withDensity_absolutelyContinuous μ _ rw [← nonpos_iff_eq_zero] exact (measure_mono inter_subset_right).trans (v.measure_limRatioMeas_top hρ).le have C : ∀ n : ℤ, ν (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) ≤ ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := by intro n let I := Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1)) have M : MeasurableSet (s ∩ f ⁻¹' I) := hs.inter (f_meas measurableSet_Ico) simp only [ν, I, M, withDensity_apply, coe_nnreal_smul_apply] calc (∫⁻ x in s ∩ f ⁻¹' I, f x ∂μ) ≤ ∫⁻ _ in s ∩ f ⁻¹' I, (t : ℝ≥0∞) ^ (n + 1) ∂μ := lintegral_mono_ae ((ae_restrict_iff' M).2 (Eventually.of_forall fun x hx => hx.2.2.le)) _ = (t : ℝ≥0∞) ^ (n + 1) * μ (s ∩ f ⁻¹' I) := by simp only [lintegral_const, MeasurableSet.univ, Measure.restrict_apply, univ_inter] _ = (t : ℝ≥0∞) ^ (2 : ℤ) * ((t : ℝ≥0∞) ^ (n - 1) * μ (s ∩ f ⁻¹' I)) := by rw [← mul_assoc, ← ENNReal.zpow_add t_ne_zero ENNReal.coe_ne_top] congr 2 abel _ ≤ (t : ℝ≥0∞) ^ (2 : ℤ) * ρ (s ∩ f ⁻¹' I) := by gcongr rw [← ENNReal.coe_zpow (zero_lt_one.trans ht).ne'] apply v.mul_measure_le_of_subset_lt_limRatioMeas hρ intro x hx apply lt_of_lt_of_le _ hx.2.1 rw [← ENNReal.coe_zpow (zero_lt_one.trans ht).ne', ENNReal.coe_lt_coe, sub_eq_add_neg, zpow_add₀ t_ne_zero'] conv_rhs => rw [← mul_one (t ^ n)] gcongr rw [zpow_neg_one] exact inv_lt_one_of_one_lt₀ ht calc ν s = ν (s ∩ f ⁻¹' {0}) + ν (s ∩ f ⁻¹' {∞}) + ∑' n : ℤ, ν (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := measure_eq_measure_preimage_add_measure_tsum_Ico_zpow ν f_meas hs ht _ ≤ ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {0}) + ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {∞}) + ∑' n : ℤ, ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' Ico (t ^ n) (t ^ (n + 1))) := (add_le_add (add_le_add A B) (ENNReal.tsum_le_tsum C)) _ = ((t : ℝ≥0∞) ^ 2 • ρ :) s := (measure_eq_measure_preimage_add_measure_tsum_Ico_zpow ((t : ℝ≥0∞) ^ 2 • ρ) f_meas hs ht).symm /-- As an intermediate step to show that `μ.withDensity (v.limRatioMeas hρ) = ρ`, we show here that `ρ ≤ t μ.withDensity (v.limRatioMeas hρ)` for any `t > 1`. -/ theorem le_mul_withDensity {s : Set α} (hs : MeasurableSet s) {t : ℝ≥0} (ht : 1 < t) : ρ s ≤ t * μ.withDensity (v.limRatioMeas hρ) s := by /- We cut `s` into the sets where `v.limRatioMeas hρ = 0`, where `v.limRatioMeas hρ = ∞`, and where `v.limRatioMeas hρ ∈ [t^n, t^(n+1))` for `n : ℤ`. The first and second have measure `0`. For the latter, since `v.limRatioMeas hρ` fluctuates by at most `t` on this slice, we can use `measure_le_mul_of_subset_limRatioMeas_lt` and `mul_measure_le_of_subset_lt_limRatioMeas` to show that the two measures are comparable up to `t`. -/ have t_ne_zero' : t ≠ 0 := (zero_lt_one.trans ht).ne' have t_ne_zero : (t : ℝ≥0∞) ≠ 0 := by simpa only [ENNReal.coe_eq_zero, Ne] using t_ne_zero' let ν := μ.withDensity (v.limRatioMeas hρ) let f := v.limRatioMeas hρ have f_meas : Measurable f := v.limRatioMeas_measurable hρ have A : ρ (s ∩ f ⁻¹' {0}) ≤ (t • ν) (s ∩ f ⁻¹' {0}) := by refine le_trans (measure_mono inter_subset_right) (le_trans (le_of_eq ?_) (zero_le _)) exact v.measure_limRatioMeas_zero hρ have B : ρ (s ∩ f ⁻¹' {∞}) ≤ (t • ν) (s ∩ f ⁻¹' {∞}) := by apply le_trans (le_of_eq _) (zero_le _) apply hρ rw [← nonpos_iff_eq_zero] exact (measure_mono inter_subset_right).trans (v.measure_limRatioMeas_top hρ).le have C : ∀ n : ℤ, ρ (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) ≤ (t • ν) (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := by intro n let I := Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1)) have M : MeasurableSet (s ∩ f ⁻¹' I) := hs.inter (f_meas measurableSet_Ico) simp only [ν, I, M, withDensity_apply, coe_nnreal_smul_apply] calc ρ (s ∩ f ⁻¹' I) ≤ (t : ℝ≥0∞) ^ (n + 1) * μ (s ∩ f ⁻¹' I) := by rw [← ENNReal.coe_zpow t_ne_zero'] apply v.measure_le_mul_of_subset_limRatioMeas_lt hρ intro x hx apply hx.2.2.trans_le (le_of_eq _) rw [ENNReal.coe_zpow t_ne_zero'] _ = ∫⁻ _ in s ∩ f ⁻¹' I, (t : ℝ≥0∞) ^ (n + 1) ∂μ := by simp only [lintegral_const, MeasurableSet.univ, Measure.restrict_apply, univ_inter] _ ≤ ∫⁻ x in s ∩ f ⁻¹' I, t * f x ∂μ := by apply lintegral_mono_ae ((ae_restrict_iff' M).2 (Eventually.of_forall fun x hx => ?_)) rw [add_comm, ENNReal.zpow_add t_ne_zero ENNReal.coe_ne_top, zpow_one] exact mul_le_mul_left' hx.2.1 _ _ = t * ∫⁻ x in s ∩ f ⁻¹' I, f x ∂μ := lintegral_const_mul _ f_meas calc ρ s = ρ (s ∩ f ⁻¹' {0}) + ρ (s ∩ f ⁻¹' {∞}) + ∑' n : ℤ, ρ (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := measure_eq_measure_preimage_add_measure_tsum_Ico_zpow ρ f_meas hs ht _ ≤ (t • ν) (s ∩ f ⁻¹' {0}) + (t • ν) (s ∩ f ⁻¹' {∞}) + ∑' n : ℤ, (t • ν) (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := (add_le_add (add_le_add A B) (ENNReal.tsum_le_tsum C)) _ = (t • ν) s := (measure_eq_measure_preimage_add_measure_tsum_Ico_zpow (t • ν) f_meas hs ht).symm theorem withDensity_limRatioMeas_eq : μ.withDensity (v.limRatioMeas hρ) = ρ := by ext1 s hs refine le_antisymm ?_ ?_ · have : Tendsto (fun t : ℝ≥0 => ((t : ℝ≥0∞) ^ 2 * ρ s : ℝ≥0∞)) (𝓝[>] 1) (𝓝 ((1 : ℝ≥0∞) ^ 2 * ρ s)) := by refine ENNReal.Tendsto.mul ?_ ?_ tendsto_const_nhds ?_ · exact ENNReal.Tendsto.pow (ENNReal.tendsto_coe.2 nhdsWithin_le_nhds) · simp only [one_pow, ENNReal.coe_one, true_or, Ne, not_false_iff, one_ne_zero] · simp only [one_pow, ENNReal.coe_one, Ne, or_true, ENNReal.one_ne_top, not_false_iff] simp only [one_pow, one_mul, ENNReal.coe_one] at this refine ge_of_tendsto this ?_ filter_upwards [self_mem_nhdsWithin] with _ ht exact v.withDensity_le_mul hρ hs ht · have : Tendsto (fun t : ℝ≥0 => (t : ℝ≥0∞) * μ.withDensity (v.limRatioMeas hρ) s) (𝓝[>] 1) (𝓝 ((1 : ℝ≥0∞) * μ.withDensity (v.limRatioMeas hρ) s)) := by refine ENNReal.Tendsto.mul_const (ENNReal.tendsto_coe.2 nhdsWithin_le_nhds) ?_ simp only [ENNReal.coe_one, true_or, Ne, not_false_iff, one_ne_zero] simp only [one_mul, ENNReal.coe_one] at this refine ge_of_tendsto this ?_ filter_upwards [self_mem_nhdsWithin] with _ ht exact v.le_mul_withDensity hρ hs ht /-- Weak version of the main theorem on differentiation of measures: given a Vitali family `v` for a locally finite measure `μ`, and another locally finite measure `ρ`, then for `μ`-almost every `x` the ratio `ρ a / μ a` converges, when `a` shrinks to `x` along the Vitali family, towards the Radon-Nikodym derivative of `ρ` with respect to `μ`. This version assumes that `ρ` is absolutely continuous with respect to `μ`. The general version without this superfluous assumption is `VitaliFamily.ae_tendsto_rnDeriv`. -/ theorem ae_tendsto_rnDeriv_of_absolutelyContinuous : ∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (ρ.rnDeriv μ x)) := by have A : (μ.withDensity (v.limRatioMeas hρ)).rnDeriv μ =ᵐ[μ] v.limRatioMeas hρ := rnDeriv_withDensity μ (v.limRatioMeas_measurable hρ) rw [v.withDensity_limRatioMeas_eq hρ] at A filter_upwards [v.ae_tendsto_limRatioMeas hρ, A] with _ _ h'x rwa [h'x] end AbsolutelyContinuous variable (ρ) /-- Main theorem on differentiation of measures: given a Vitali family `v` for a locally finite measure `μ`, and another locally finite measure `ρ`, then for `μ`-almost every `x` the ratio `ρ a / μ a` converges, when `a` shrinks to `x` along the Vitali family, towards the Radon-Nikodym derivative of `ρ` with respect to `μ`. -/ theorem ae_tendsto_rnDeriv : ∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (ρ.rnDeriv μ x)) := by let t := μ.withDensity (ρ.rnDeriv μ) have eq_add : ρ = ρ.singularPart μ + t := haveLebesgueDecomposition_add _ _ have A : ∀ᵐ x ∂μ, Tendsto (fun a => ρ.singularPart μ a / μ a) (v.filterAt x) (𝓝 0) := v.ae_eventually_measure_zero_of_singular (mutuallySingular_singularPart ρ μ) have B : ∀ᵐ x ∂μ, t.rnDeriv μ x = ρ.rnDeriv μ x := rnDeriv_withDensity μ (measurable_rnDeriv ρ μ) have C : ∀ᵐ x ∂μ, Tendsto (fun a => t a / μ a) (v.filterAt x) (𝓝 (t.rnDeriv μ x)) := v.ae_tendsto_rnDeriv_of_absolutelyContinuous (withDensity_absolutelyContinuous _ _) filter_upwards [A, B, C] with _ Ax Bx Cx convert Ax.add Cx using 1 · ext1 a conv_lhs => rw [eq_add] simp only [Pi.add_apply, coe_add, ENNReal.add_div] · simp only [Bx, zero_add] /-! ### Lebesgue density points -/ /-- Given a measurable set `s`, then `μ (s ∩ a) / μ a` converges when `a` shrinks to a typical point `x` along a Vitali family. The limit is `1` for `x ∈ s` and `0` for `x ∉ s`. This shows that almost every point of `s` is a Lebesgue density point for `s`. A version for non-measurable sets holds, but it only gives the first conclusion, see `ae_tendsto_measure_inter_div`. -/ theorem ae_tendsto_measure_inter_div_of_measurableSet {s : Set α} (hs : MeasurableSet s) : ∀ᵐ x ∂μ, Tendsto (fun a => μ (s ∩ a) / μ a) (v.filterAt x) (𝓝 (s.indicator 1 x)) := by haveI : IsLocallyFiniteMeasure (μ.restrict s) := isLocallyFiniteMeasure_of_le restrict_le_self filter_upwards [ae_tendsto_rnDeriv v (μ.restrict s), rnDeriv_restrict_self μ hs] intro x hx h'x simpa only [h'x, restrict_apply' hs, inter_comm] using hx /-- Given an arbitrary set `s`, then `μ (s ∩ a) / μ a` converges to `1` when `a` shrinks to a typical point of `s` along a Vitali family. This shows that almost every point of `s` is a Lebesgue density point for `s`. A stronger version for measurable sets is given in `ae_tendsto_measure_inter_div_of_measurableSet`. -/ theorem ae_tendsto_measure_inter_div (s : Set α) : ∀ᵐ x ∂μ.restrict s, Tendsto (fun a => μ (s ∩ a) / μ a) (v.filterAt x) (𝓝 1) := by let t := toMeasurable μ s have A : ∀ᵐ x ∂μ.restrict s, Tendsto (fun a => μ (t ∩ a) / μ a) (v.filterAt x) (𝓝 (t.indicator 1 x)) := by apply ae_mono restrict_le_self
apply ae_tendsto_measure_inter_div_of_measurableSet exact measurableSet_toMeasurable _ _ have B : ∀ᵐ x ∂μ.restrict s, t.indicator 1 x = (1 : ℝ≥0∞) := by refine ae_restrict_of_ae_restrict_of_subset (subset_toMeasurable μ s) ?_ filter_upwards [ae_restrict_mem (measurableSet_toMeasurable μ s)] with _ hx simp only [t, hx, Pi.one_apply, indicator_of_mem] filter_upwards [A, B] with x hx h'x
Mathlib/MeasureTheory/Covering/Differentiation.lean
733
739
/- Copyright (c) 2021 Lu-Ming Zhang. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Lu-Ming Zhang -/ import Mathlib.Algebra.Group.Fin.Basic import Mathlib.LinearAlgebra.Matrix.Symmetric import Mathlib.Tactic.Abel /-! # Circulant matrices This file contains the definition and basic results about circulant matrices. Given a vector `v : n → α` indexed by a type that is endowed with subtraction, `Matrix.circulant v` is the matrix whose `(i, j)`th entry is `v (i - j)`. ## Main results - `Matrix.circulant`: the circulant matrix generated by a given vector `v : n → α`. - `Matrix.circulant_mul`: the product of two circulant matrices `circulant v` and `circulant w` is the circulant matrix generated by `circulant v *ᵥ w`. - `Matrix.circulant_mul_comm`: multiplication of circulant matrices commutes when the elements do. ## Implementation notes `Matrix.Fin.foo` is the `Fin n` version of `Matrix.foo`. Namely, the index type of the circulant matrices in discussion is `Fin n`. ## Tags circulant, matrix -/ variable {α β n R : Type*} namespace Matrix open Function open Matrix /-- Given the condition `[Sub n]` and a vector `v : n → α`, we define `circulant v` to be the circulant matrix generated by `v` of type `Matrix n n α`. The `(i,j)`th entry is defined to be `v (i - j)`. -/ def circulant [Sub n] (v : n → α) : Matrix n n α := of fun i j => v (i - j) -- TODO: set as an equation lemma for `circulant`, see https://github.com/leanprover-community/mathlib4/pull/3024 @[simp] theorem circulant_apply [Sub n] (v : n → α) (i j) : circulant v i j = v (i - j) := rfl theorem circulant_col_zero_eq [SubtractionMonoid n] (v : n → α) (i : n) : circulant v i 0 = v i := congr_arg v (sub_zero _) theorem circulant_injective [SubtractionMonoid n] : Injective (circulant : (n → α) → Matrix n n α) := by intro v w h ext k rw [← circulant_col_zero_eq v, ← circulant_col_zero_eq w, h] theorem Fin.circulant_injective : ∀ n, Injective fun v : Fin n → α => circulant v | 0 => by simp [Injective] | _ + 1 => Matrix.circulant_injective @[simp]
theorem circulant_inj [SubtractionMonoid n] {v w : n → α} : circulant v = circulant w ↔ v = w := circulant_injective.eq_iff
Mathlib/LinearAlgebra/Matrix/Circulant.lean
67
69
/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.Finite.Defs import Mathlib.Data.Finset.BooleanAlgebra import Mathlib.Data.Finset.Image import Mathlib.Data.Fintype.Defs import Mathlib.Data.Fintype.OfMap import Mathlib.Data.Fintype.Sets import Mathlib.Data.List.FinRange /-! # Instances for finite types This file is a collection of basic `Fintype` instances for types such as `Fin`, `Prod` and pi types. -/ assert_not_exists Monoid open Function open Nat universe u v variable {α β γ : Type*} open Finset instance Fin.fintype (n : ℕ) : Fintype (Fin n) := ⟨⟨List.finRange n, List.nodup_finRange n⟩, List.mem_finRange⟩ theorem Fin.univ_def (n : ℕ) : (univ : Finset (Fin n)) = ⟨List.finRange n, List.nodup_finRange n⟩ := rfl theorem Finset.val_univ_fin (n : ℕ) : (Finset.univ : Finset (Fin n)).val = List.finRange n := rfl /-- See also `nonempty_encodable`, `nonempty_denumerable`. -/ theorem nonempty_fintype (α : Type*) [Finite α] : Nonempty (Fintype α) := by rcases Finite.exists_equiv_fin α with ⟨n, ⟨e⟩⟩ exact ⟨.ofEquiv _ e.symm⟩ @[simp] theorem List.toFinset_finRange (n : ℕ) : (List.finRange n).toFinset = Finset.univ := by ext; simp @[simp] theorem Fin.univ_val_map {n : ℕ} (f : Fin n → α) : Finset.univ.val.map f = List.ofFn f := by simp [List.ofFn_eq_map, univ_def] theorem Fin.univ_image_def {n : ℕ} [DecidableEq α] (f : Fin n → α) : Finset.univ.image f = (List.ofFn f).toFinset := by simp [Finset.image] theorem Fin.univ_map_def {n : ℕ} (f : Fin n ↪ α) : Finset.univ.map f = ⟨List.ofFn f, List.nodup_ofFn.mpr f.injective⟩ := by simp [Finset.map] @[simp] theorem Fin.image_succAbove_univ {n : ℕ} (i : Fin (n + 1)) : univ.image i.succAbove = {i}ᶜ := by ext m simp @[simp] theorem Fin.image_succ_univ (n : ℕ) : (univ : Finset (Fin n)).image Fin.succ = {0}ᶜ := by rw [← Fin.succAbove_zero, Fin.image_succAbove_univ] @[simp] theorem Fin.image_castSucc (n : ℕ) : (univ : Finset (Fin n)).image Fin.castSucc = {Fin.last n}ᶜ := by rw [← Fin.succAbove_last, Fin.image_succAbove_univ] /- The following three lemmas use `Finset.cons` instead of `insert` and `Finset.map` instead of `Finset.image` to reduce proof obligations downstream. -/ /-- Embed `Fin n` into `Fin (n + 1)` by prepending zero to the `univ` -/ theorem Fin.univ_succ (n : ℕ) : (univ : Finset (Fin (n + 1))) = Finset.cons 0 (univ.map ⟨Fin.succ, Fin.succ_injective _⟩) (by simp [map_eq_image]) := by simp [map_eq_image] /-- Embed `Fin n` into `Fin (n + 1)` by appending a new `Fin.last n` to the `univ` -/ theorem Fin.univ_castSuccEmb (n : ℕ) : (univ : Finset (Fin (n + 1))) = Finset.cons (Fin.last n) (univ.map Fin.castSuccEmb) (by simp [map_eq_image]) := by simp [map_eq_image] /-- Embed `Fin n` into `Fin (n + 1)` by inserting around a specified pivot `p : Fin (n + 1)` into the `univ` -/ theorem Fin.univ_succAbove (n : ℕ) (p : Fin (n + 1)) : (univ : Finset (Fin (n + 1))) = Finset.cons p (univ.map <| Fin.succAboveEmb p) (by simp) := by simp [map_eq_image] @[simp] theorem Fin.univ_image_get [DecidableEq α] (l : List α) : Finset.univ.image l.get = l.toFinset := by simp [univ_image_def] @[simp] theorem Fin.univ_image_getElem' [DecidableEq β] (l : List α) (f : α → β) : Finset.univ.image (fun i : Fin l.length => f <| l[(i : Nat)]) = (l.map f).toFinset := by simp only [univ_image_def, List.ofFn_getElem_eq_map] theorem Fin.univ_image_get' [DecidableEq β] (l : List α) (f : α → β) : Finset.univ.image (f <| l.get ·) = (l.map f).toFinset := by simp @[instance] def Unique.fintype {α : Type*} [Unique α] : Fintype α := Fintype.ofSubsingleton default /-- Short-circuit instance to decrease search for `Unique.fintype`, since that relies on a subsingleton elimination for `Unique`. -/ instance Fintype.subtypeEq (y : α) : Fintype { x // x = y } := Fintype.subtype {y} (by simp) /-- Short-circuit instance to decrease search for `Unique.fintype`, since that relies on a subsingleton elimination for `Unique`. -/ instance Fintype.subtypeEq' (y : α) : Fintype { x // y = x } := Fintype.subtype {y} (by simp [eq_comm]) theorem Fintype.univ_empty : @univ Empty _ = ∅ := rfl theorem Fintype.univ_pempty : @univ PEmpty _ = ∅ := rfl instance Unit.fintype : Fintype Unit := Fintype.ofSubsingleton () theorem Fintype.univ_unit : @univ Unit _ = {()} := rfl instance PUnit.fintype : Fintype PUnit := Fintype.ofSubsingleton PUnit.unit theorem Fintype.univ_punit : @univ PUnit _ = {PUnit.unit} := rfl @[simp] theorem Fintype.univ_bool : @univ Bool _ = {true, false} := rfl /-- Given that `α × β` is a fintype, `α` is also a fintype. -/ def Fintype.prodLeft {α β} [DecidableEq α] [Fintype (α × β)] [Nonempty β] : Fintype α := ⟨(@univ (α × β) _).image Prod.fst, fun a => by simp⟩ /-- Given that `α × β` is a fintype, `β` is also a fintype. -/ def Fintype.prodRight {α β} [DecidableEq β] [Fintype (α × β)] [Nonempty α] : Fintype β := ⟨(@univ (α × β) _).image Prod.snd, fun b => by simp⟩ instance ULift.fintype (α : Type*) [Fintype α] : Fintype (ULift α) := Fintype.ofEquiv _ Equiv.ulift.symm instance PLift.fintype (α : Type*) [Fintype α] : Fintype (PLift α) := Fintype.ofEquiv _ Equiv.plift.symm instance PLift.fintypeProp (p : Prop) [Decidable p] : Fintype (PLift p) := ⟨if h : p then {⟨h⟩} else ∅, fun ⟨h⟩ => by simp [h]⟩ instance Quotient.fintype [Fintype α] (s : Setoid α) [DecidableRel ((· ≈ ·) : α → α → Prop)] : Fintype (Quotient s) := Fintype.ofSurjective Quotient.mk'' Quotient.mk''_surjective instance PSigma.fintypePropLeft {α : Prop} {β : α → Type*} [Decidable α] [∀ a, Fintype (β a)] : Fintype (Σ'a, β a) := if h : α then Fintype.ofEquiv (β h) ⟨fun x => ⟨h, x⟩, PSigma.snd, fun _ => rfl, fun ⟨_, _⟩ => rfl⟩ else ⟨∅, fun x => (h x.1).elim⟩ instance PSigma.fintypePropRight {α : Type*} {β : α → Prop} [∀ a, Decidable (β a)] [Fintype α] : Fintype (Σ'a, β a) := Fintype.ofEquiv { a // β a } ⟨fun ⟨x, y⟩ => ⟨x, y⟩, fun ⟨x, y⟩ => ⟨x, y⟩, fun ⟨_, _⟩ => rfl, fun ⟨_, _⟩ => rfl⟩ instance PSigma.fintypePropProp {α : Prop} {β : α → Prop} [Decidable α] [∀ a, Decidable (β a)] : Fintype (Σ'a, β a) := if h : ∃ a, β a then ⟨{⟨h.fst, h.snd⟩}, fun ⟨_, _⟩ => by simp⟩ else ⟨∅, fun ⟨x, y⟩ => (h ⟨x, y⟩).elim⟩ instance pfunFintype (p : Prop) [Decidable p] (α : p → Type*) [∀ hp, Fintype (α hp)] : Fintype (∀ hp : p, α hp) := if hp : p then Fintype.ofEquiv (α hp) ⟨fun a _ => a, fun f => f hp, fun _ => rfl, fun _ => rfl⟩ else ⟨singleton fun h => (hp h).elim, fun h => mem_singleton.2 (funext fun x => by contradiction)⟩ section Trunc /-- For `s : Multiset α`, we can lift the existential statement that `∃ x, x ∈ s` to a `Trunc α`. -/ def truncOfMultisetExistsMem {α} (s : Multiset α) : (∃ x, x ∈ s) → Trunc α := Quotient.recOnSubsingleton s fun l h => match l, h with | [], _ => False.elim (by tauto) | a :: _, _ => Trunc.mk a /-- A `Nonempty` `Fintype` constructively contains an element. -/ def truncOfNonemptyFintype (α) [Nonempty α] [Fintype α] : Trunc α := truncOfMultisetExistsMem Finset.univ.val (by simp) /-- By iterating over the elements of a fintype, we can lift an existential statement `∃ a, P a` to `Trunc (Σ' a, P a)`, containing data. -/ def truncSigmaOfExists {α} [Fintype α] {P : α → Prop} [DecidablePred P] (h : ∃ a, P a) : Trunc (Σ'a, P a) := @truncOfNonemptyFintype (Σ'a, P a) ((Exists.elim h) fun a ha => ⟨⟨a, ha⟩⟩) _ end Trunc namespace Multiset variable [Fintype α] [Fintype β] @[simp] theorem count_univ [DecidableEq α] (a : α) : count a Finset.univ.val = 1 := count_eq_one_of_mem Finset.univ.nodup (Finset.mem_univ _) @[simp] theorem map_univ_val_equiv (e : α ≃ β) : map e univ.val = univ.val := by rw [← congr_arg Finset.val (Finset.map_univ_equiv e), Finset.map_val, Equiv.coe_toEmbedding] /-- For functions on finite sets, they are bijections iff they map universes into universes. -/ @[simp] theorem bijective_iff_map_univ_eq_univ (f : α → β) : f.Bijective ↔ map f (Finset.univ : Finset α).val = univ.val := ⟨fun bij ↦ congr_arg (·.val) (map_univ_equiv <| Equiv.ofBijective f bij), fun eq ↦ ⟨ fun a₁ a₂ ↦ inj_on_of_nodup_map (eq.symm ▸ univ.nodup) _ (mem_univ a₁) _ (mem_univ a₂), fun b ↦ have ⟨a, _, h⟩ := mem_map.mp (eq.symm ▸ mem_univ_val b); ⟨a, h⟩⟩⟩ end Multiset /-- Auxiliary definition to show `exists_seq_of_forall_finset_exists`. -/ noncomputable def seqOfForallFinsetExistsAux {α : Type*} [DecidableEq α] (P : α → Prop) (r : α → α → Prop) (h : ∀ s : Finset α, ∃ y, (∀ x ∈ s, P x) → P y ∧ ∀ x ∈ s, r x y) : ℕ → α | n => Classical.choose (h (Finset.image (fun i : Fin n => seqOfForallFinsetExistsAux P r h i) (Finset.univ : Finset (Fin n)))) /-- Induction principle to build a sequence, by adding one point at a time satisfying a given relation with respect to all the previously chosen points. More precisely, Assume that, for any finite set `s`, one can find another point satisfying some relation `r` with respect to all the points in `s`. Then one may construct a function `f : ℕ → α` such that `r (f m) (f n)` holds whenever `m < n`. We also ensure that all constructed points satisfy a given predicate `P`. -/ theorem exists_seq_of_forall_finset_exists {α : Type*} (P : α → Prop) (r : α → α → Prop) (h : ∀ s : Finset α, (∀ x ∈ s, P x) → ∃ y, P y ∧ ∀ x ∈ s, r x y) : ∃ f : ℕ → α, (∀ n, P (f n)) ∧ ∀ m n, m < n → r (f m) (f n) := by classical have : Nonempty α := by rcases h ∅ (by simp) with ⟨y, _⟩ exact ⟨y⟩ choose! F hF using h have h' : ∀ s : Finset α, ∃ y, (∀ x ∈ s, P x) → P y ∧ ∀ x ∈ s, r x y := fun s => ⟨F s, hF s⟩ set f := seqOfForallFinsetExistsAux P r h' with hf have A : ∀ n : ℕ, P (f n) := by intro n induction' n using Nat.strong_induction_on with n IH have IH' : ∀ x : Fin n, P (f x) := fun n => IH n.1 n.2 rw [hf, seqOfForallFinsetExistsAux] exact (Classical.choose_spec (h' (Finset.image (fun i : Fin n => f i) (Finset.univ : Finset (Fin n)))) (by simp [IH'])).1 refine ⟨f, A, fun m n hmn => ?_⟩ conv_rhs => rw [hf] rw [seqOfForallFinsetExistsAux] apply (Classical.choose_spec (h' (Finset.image (fun i : Fin n => f i) (Finset.univ : Finset (Fin n)))) (by simp [A])).2 exact Finset.mem_image.2 ⟨⟨m, hmn⟩, Finset.mem_univ _, rfl⟩ /-- Induction principle to build a sequence, by adding one point at a time satisfying a given symmetric relation with respect to all the previously chosen points. More precisely, Assume that, for any finite set `s`, one can find another point satisfying some relation `r` with respect to all the points in `s`. Then one may construct a function `f : ℕ → α` such that `r (f m) (f n)` holds whenever `m ≠ n`. We also ensure that all constructed points satisfy a given predicate `P`. -/ theorem exists_seq_of_forall_finset_exists' {α : Type*} (P : α → Prop) (r : α → α → Prop) [IsSymm α r] (h : ∀ s : Finset α, (∀ x ∈ s, P x) → ∃ y, P y ∧ ∀ x ∈ s, r x y) : ∃ f : ℕ → α, (∀ n, P (f n)) ∧ Pairwise (r on f) := by rcases exists_seq_of_forall_finset_exists P r h with ⟨f, hf, hf'⟩ refine ⟨f, hf, fun m n hmn => ?_⟩ rcases lt_trichotomy m n with (h | rfl | h) · exact hf' m n h · exact (hmn rfl).elim · unfold Function.onFun apply symm exact hf' n m h
Mathlib/Data/Fintype/Basic.lean
848
850
/- 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.Data.Set.Constructions import Mathlib.Order.Filter.AtTopBot.CountablyGenerated import Mathlib.Topology.Constructions import Mathlib.Topology.ContinuousOn /-! # 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 /-- 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⟩ theorem isTopologicalBasis_of_subbasis_of_finiteInter {s : Set (Set α)} (hsg : t = generateFrom s) (hsi : FiniteInter s) : IsTopologicalBasis s := by convert isTopologicalBasis_of_subbasis hsg refine le_antisymm (fun t ht ↦ ⟨{t}, by simpa using ht⟩) ?_ rintro _ ⟨g, ⟨hg, hgs⟩, rfl⟩ lift g to Finset (Set α) using hg exact hsi.finiteInter_mem g hgs theorem isTopologicalBasis_of_subbasis_of_inter {r : Set (Set α)} (hsg : t = generateFrom r) (hsi : ∀ ⦃s⦄, s ∈ r → ∀ ⦃t⦄, t ∈ r → s ∩ t ∈ r) : IsTopologicalBasis (insert univ r) := isTopologicalBasis_of_subbasis_of_finiteInter (by simpa using hsg) (FiniteInter.mk₂ hsi) 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 _ ⟨hts, hat⟩ ↦ (h_open _ hts).mem_nhds hat /-- 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⟩ 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] theorem IsTopologicalBasis.of_isOpen_of_subset {s s' : Set (Set α)} (h_open : ∀ u ∈ s', IsOpen u) (hs : IsTopologicalBasis s) (hss' : s ⊆ s') : IsTopologicalBasis s' := isTopologicalBasis_of_isOpen_of_nhds h_open fun a _ ha u_open ↦ have ⟨t, hts, ht⟩ := hs.isOpen_iff.mp u_open a ha; ⟨t, hss' hts, ht⟩ 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]⟩ 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 theorem IsTopologicalBasis.insert_empty {s : Set (Set α)} (h : IsTopologicalBasis s) : IsTopologicalBasis (insert ∅ s) := h.of_isOpen_of_subset (by rintro _ (rfl | hu); exacts [isOpen_empty, h.isOpen hu]) (subset_insert ..) theorem IsTopologicalBasis.diff_empty {s : Set (Set α)} (h : IsTopologicalBasis s) : IsTopologicalBasis (s \ {∅}) := isTopologicalBasis_of_isOpen_of_nhds (fun _ hu ↦ h.isOpen hu.1) fun a _ ha hu ↦ have ⟨t, hts, ht⟩ := h.isOpen_iff.mp hu a ha ⟨t, ⟨hts, ne_of_mem_of_not_mem' ht.1 <| not_mem_empty _⟩, ht⟩ 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 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 /-- 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⟩ 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⟩ 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)⟩ 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⟩ 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] /-- 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⟩⟩ 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 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⟩ theorem isTopologicalBasis_opens : IsTopologicalBasis { U : Set α | IsOpen U } := isTopologicalBasis_of_isOpen_of_nhds (by tauto) (by tauto) protected lemma IsTopologicalBasis.isInducing {β} [TopologicalSpace β] {f : α → β} {T : Set (Set β)} (hf : IsInducing 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 @[deprecated (since := "2024-10-28")] alias IsTopologicalBasis.inducing := IsTopologicalBasis.isInducing protected theorem IsTopologicalBasis.induced {α} [s : TopologicalSpace β] (f : α → β) {T : Set (Set β)} (h : IsTopologicalBasis T) : IsTopologicalBasis (t := induced f s) ((preimage f) '' T) := h.isInducing (t := induced f s) (.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 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
Mathlib/Topology/Bases.lean
268
272
/- Copyright (c) 2023 Joël Riou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joël Riou -/ import Mathlib.Algebra.Homology.ShortComplex.QuasiIso import Mathlib.CategoryTheory.Limits.Preserves.Finite import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels /-! # Functors which preserves homology If `F : C ⥤ D` is a functor between categories with zero morphisms, we shall say that `F` preserves homology when `F` preserves both kernels and cokernels. This typeclass is named `[F.PreservesHomology]`, and is automatically satisfied when `F` preserves both finite limits and finite colimits. If `S : ShortComplex C` and `[F.PreservesHomology]`, then there is an isomorphism `S.mapHomologyIso F : (S.map F).homology ≅ F.obj S.homology`, which is part of the natural isomorphism `homologyFunctorIso F` between the functors `F.mapShortComplex ⋙ homologyFunctor D` and `homologyFunctor C ⋙ F`. -/ namespace CategoryTheory open Category Limits variable {C D : Type*} [Category C] [Category D] [HasZeroMorphisms C] [HasZeroMorphisms D] namespace Functor variable (F : C ⥤ D) /-- A functor preserves homology when it preserves both kernels and cokernels. -/ class PreservesHomology (F : C ⥤ D) [PreservesZeroMorphisms F] : Prop where /-- the functor preserves kernels -/ preservesKernels ⦃X Y : C⦄ (f : X ⟶ Y) : PreservesLimit (parallelPair f 0) F := by infer_instance /-- the functor preserves cokernels -/ preservesCokernels ⦃X Y : C⦄ (f : X ⟶ Y) : PreservesColimit (parallelPair f 0) F := by infer_instance variable [PreservesZeroMorphisms F] /-- A functor which preserves homology preserves kernels. -/ lemma PreservesHomology.preservesKernel [F.PreservesHomology] {X Y : C} (f : X ⟶ Y) : PreservesLimit (parallelPair f 0) F := PreservesHomology.preservesKernels _ /-- A functor which preserves homology preserves cokernels. -/ lemma PreservesHomology.preservesCokernel [F.PreservesHomology] {X Y : C} (f : X ⟶ Y) : PreservesColimit (parallelPair f 0) F := PreservesHomology.preservesCokernels _ noncomputable instance preservesHomologyOfExact [PreservesFiniteLimits F] [PreservesFiniteColimits F] : F.PreservesHomology where end Functor namespace ShortComplex variable {S S₁ S₂ : ShortComplex C} namespace LeftHomologyData variable (h : S.LeftHomologyData) (F : C ⥤ D) /-- A left homology data `h` of a short complex `S` is preserved by a functor `F` is `F` preserves the kernel of `S.g : S.X₂ ⟶ S.X₃` and the cokernel of `h.f' : S.X₁ ⟶ h.K`. -/ class IsPreservedBy [F.PreservesZeroMorphisms] : Prop where /-- the functor preserves the kernel of `S.g : S.X₂ ⟶ S.X₃`. -/ g : PreservesLimit (parallelPair S.g 0) F /-- the functor preserves the cokernel of `h.f' : S.X₁ ⟶ h.K`. -/ f' : PreservesColimit (parallelPair h.f' 0) F variable [F.PreservesZeroMorphisms] noncomputable instance isPreservedBy_of_preservesHomology [F.PreservesHomology] : h.IsPreservedBy F where g := Functor.PreservesHomology.preservesKernel _ _ f' := Functor.PreservesHomology.preservesCokernel _ _ variable [h.IsPreservedBy F] include h in /-- When a left homology data is preserved by a functor `F`, this functor preserves the kernel of `S.g : S.X₂ ⟶ S.X₃`. -/ lemma IsPreservedBy.hg : PreservesLimit (parallelPair S.g 0) F := @IsPreservedBy.g _ _ _ _ _ _ _ h F _ _ /-- When a left homology data `h` is preserved by a functor `F`, this functor preserves the cokernel of `h.f' : S.X₁ ⟶ h.K`. -/ lemma IsPreservedBy.hf' : PreservesColimit (parallelPair h.f' 0) F := IsPreservedBy.f' /-- When a left homology data `h` of a short complex `S` is preserved by a functor `F`, this is the induced left homology data `h.map F` for the short complex `S.map F`. -/ @[simps] noncomputable def map : (S.map F).LeftHomologyData := by have := IsPreservedBy.hg h F have := IsPreservedBy.hf' h F have wi : F.map h.i ≫ F.map S.g = 0 := by rw [← F.map_comp, h.wi, F.map_zero] have hi := KernelFork.mapIsLimit _ h.hi F let f' : F.obj S.X₁ ⟶ F.obj h.K := hi.lift (KernelFork.ofι (S.map F).f (S.map F).zero) have hf' : f' = F.map h.f' := Fork.IsLimit.hom_ext hi (by rw [Fork.IsLimit.lift_ι hi] simp only [KernelFork.map_ι, Fork.ι_ofι, map_f, ← F.map_comp, f'_i]) have wπ : f' ≫ F.map h.π = 0 := by rw [hf', ← F.map_comp, f'_π, F.map_zero] have hπ : IsColimit (CokernelCofork.ofπ (F.map h.π) wπ) := by let e : parallelPair f' 0 ≅ parallelPair (F.map h.f') 0 := parallelPair.ext (Iso.refl _) (Iso.refl _) (by simpa using hf') (by simp) refine IsColimit.precomposeInvEquiv e _ (IsColimit.ofIsoColimit (CokernelCofork.mapIsColimit _ h.hπ' F) ?_) exact Cofork.ext (Iso.refl _) (by simp [e]) exact { K := F.obj h.K H := F.obj h.H i := F.map h.i π := F.map h.π wi := wi hi := hi wπ := wπ hπ := hπ } @[simp] lemma map_f' : (h.map F).f' = F.map h.f' := by rw [← cancel_mono (h.map F).i, f'_i, map_f, map_i, ← F.map_comp, f'_i] end LeftHomologyData /-- Given a left homology map data `ψ : LeftHomologyMapData φ h₁ h₂` such that both left homology data `h₁` and `h₂` are preserved by a functor `F`, this is the induced left homology map data for the morphism `F.mapShortComplex.map φ`. -/ @[simps] def LeftHomologyMapData.map {φ : S₁ ⟶ S₂} {h₁ : S₁.LeftHomologyData} {h₂ : S₂.LeftHomologyData} (ψ : LeftHomologyMapData φ h₁ h₂) (F : C ⥤ D) [F.PreservesZeroMorphisms] [h₁.IsPreservedBy F] [h₂.IsPreservedBy F] : LeftHomologyMapData (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) where φK := F.map ψ.φK φH := F.map ψ.φH commi := by simpa only [F.map_comp] using F.congr_map ψ.commi commf' := by simpa only [LeftHomologyData.map_f', F.map_comp] using F.congr_map ψ.commf' commπ := by simpa only [F.map_comp] using F.congr_map ψ.commπ namespace RightHomologyData variable (h : S.RightHomologyData) (F : C ⥤ D) /-- A right homology data `h` of a short complex `S` is preserved by a functor `F` is `F` preserves the cokernel of `S.f : S.X₁ ⟶ S.X₂` and the kernel of `h.g' : h.Q ⟶ S.X₃`. -/ class IsPreservedBy [F.PreservesZeroMorphisms] : Prop where /-- the functor preserves the cokernel of `S.f : S.X₁ ⟶ S.X₂`. -/ f : PreservesColimit (parallelPair S.f 0) F /-- the functor preserves the kernel of `h.g' : h.Q ⟶ S.X₃`. -/ g' : PreservesLimit (parallelPair h.g' 0) F variable [F.PreservesZeroMorphisms] noncomputable instance isPreservedBy_of_preservesHomology [F.PreservesHomology] : h.IsPreservedBy F where f := Functor.PreservesHomology.preservesCokernel F _ g' := Functor.PreservesHomology.preservesKernel F _ variable [h.IsPreservedBy F] include h in /-- When a right homology data is preserved by a functor `F`, this functor preserves the cokernel of `S.f : S.X₁ ⟶ S.X₂`. -/ lemma IsPreservedBy.hf : PreservesColimit (parallelPair S.f 0) F := @IsPreservedBy.f _ _ _ _ _ _ _ h F _ _ /-- When a right homology data `h` is preserved by a functor `F`, this functor preserves the kernel of `h.g' : h.Q ⟶ S.X₃`. -/ lemma IsPreservedBy.hg' : PreservesLimit (parallelPair h.g' 0) F := @IsPreservedBy.g' _ _ _ _ _ _ _ h F _ _ /-- When a right homology data `h` of a short complex `S` is preserved by a functor `F`, this is the induced right homology data `h.map F` for the short complex `S.map F`. -/ @[simps] noncomputable def map : (S.map F).RightHomologyData := by have := IsPreservedBy.hf h F have := IsPreservedBy.hg' h F have wp : F.map S.f ≫ F.map h.p = 0 := by rw [← F.map_comp, h.wp, F.map_zero] have hp := CokernelCofork.mapIsColimit _ h.hp F let g' : F.obj h.Q ⟶ F.obj S.X₃ := hp.desc (CokernelCofork.ofπ (S.map F).g (S.map F).zero) have hg' : g' = F.map h.g' := by apply Cofork.IsColimit.hom_ext hp rw [Cofork.IsColimit.π_desc hp] simp only [Cofork.π_ofπ, CokernelCofork.map_π, map_g, ← F.map_comp, p_g'] have wι : F.map h.ι ≫ g' = 0 := by rw [hg', ← F.map_comp, ι_g', F.map_zero] have hι : IsLimit (KernelFork.ofι (F.map h.ι) wι) := by let e : parallelPair g' 0 ≅ parallelPair (F.map h.g') 0 := parallelPair.ext (Iso.refl _) (Iso.refl _) (by simpa using hg') (by simp) refine IsLimit.postcomposeHomEquiv e _ (IsLimit.ofIsoLimit (KernelFork.mapIsLimit _ h.hι' F) ?_) exact Fork.ext (Iso.refl _) (by simp [e]) exact { Q := F.obj h.Q H := F.obj h.H p := F.map h.p ι := F.map h.ι wp := wp hp := hp wι := wι hι := hι } @[simp] lemma map_g' : (h.map F).g' = F.map h.g' := by rw [← cancel_epi (h.map F).p, p_g', map_g, map_p, ← F.map_comp, p_g'] end RightHomologyData /-- Given a right homology map data `ψ : RightHomologyMapData φ h₁ h₂` such that both right homology data `h₁` and `h₂` are preserved by a functor `F`, this is the induced right homology map data for the morphism `F.mapShortComplex.map φ`. -/ @[simps] def RightHomologyMapData.map {φ : S₁ ⟶ S₂} {h₁ : S₁.RightHomologyData} {h₂ : S₂.RightHomologyData} (ψ : RightHomologyMapData φ h₁ h₂) (F : C ⥤ D) [F.PreservesZeroMorphisms] [h₁.IsPreservedBy F] [h₂.IsPreservedBy F] : RightHomologyMapData (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) where φQ := F.map ψ.φQ φH := F.map ψ.φH commp := by simpa only [F.map_comp] using F.congr_map ψ.commp commg' := by simpa only [RightHomologyData.map_g', F.map_comp] using F.congr_map ψ.commg' commι := by simpa only [F.map_comp] using F.congr_map ψ.commι /-- When a homology data `h` of a short complex `S` is such that both `h.left` and `h.right` are preserved by a functor `F`, this is the induced homology data `h.map F` for the short complex `S.map F`. -/ @[simps] noncomputable def HomologyData.map (h : S.HomologyData) (F : C ⥤ D) [F.PreservesZeroMorphisms] [h.left.IsPreservedBy F] [h.right.IsPreservedBy F] : (S.map F).HomologyData where left := h.left.map F right := h.right.map F iso := F.mapIso h.iso comm := by simpa only [F.map_comp] using F.congr_map h.comm /-- Given a homology map data `ψ : HomologyMapData φ h₁ h₂` such that `h₁.left`, `h₁.right`, `h₂.left` and `h₂.right` are all preserved by a functor `F`, this is the induced homology map data for the morphism `F.mapShortComplex.map φ`. -/ @[simps] def HomologyMapData.map {φ : S₁ ⟶ S₂} {h₁ : S₁.HomologyData} {h₂ : S₂.HomologyData} (ψ : HomologyMapData φ h₁ h₂) (F : C ⥤ D) [F.PreservesZeroMorphisms] [h₁.left.IsPreservedBy F] [h₁.right.IsPreservedBy F] [h₂.left.IsPreservedBy F] [h₂.right.IsPreservedBy F] : HomologyMapData (F.mapShortComplex.map φ) (h₁.map F) (h₂.map F) where left := ψ.left.map F right := ψ.right.map F end ShortComplex namespace Functor variable (F : C ⥤ D) [PreservesZeroMorphisms F] (S : ShortComplex C) {S₁ S₂ : ShortComplex C} /-- A functor preserves the left homology of a short complex `S` if it preserves all the left homology data of `S`. -/ class PreservesLeftHomologyOf : Prop where /-- the functor preserves all the left homology data of the short complex -/ isPreservedBy : ∀ (h : S.LeftHomologyData), h.IsPreservedBy F /-- A functor preserves the right homology of a short complex `S` if it preserves all the right homology data of `S`. -/ class PreservesRightHomologyOf : Prop where /-- the functor preserves all the right homology data of the short complex -/ isPreservedBy : ∀ (h : S.RightHomologyData), h.IsPreservedBy F instance PreservesHomology.preservesLeftHomologyOf [F.PreservesHomology] : F.PreservesLeftHomologyOf S := ⟨inferInstance⟩ instance PreservesHomology.preservesRightHomologyOf [F.PreservesHomology] : F.PreservesRightHomologyOf S := ⟨inferInstance⟩ variable {S} /-- If a functor preserves a certain left homology data of a short complex `S`, then it preserves the left homology of `S`. -/ lemma PreservesLeftHomologyOf.mk' (h : S.LeftHomologyData) [h.IsPreservedBy F] : F.PreservesLeftHomologyOf S where isPreservedBy h' := { g := ShortComplex.LeftHomologyData.IsPreservedBy.hg h F f' := by have := ShortComplex.LeftHomologyData.IsPreservedBy.hf' h F let e : parallelPair h.f' 0 ≅ parallelPair h'.f' 0 := parallelPair.ext (Iso.refl _) (ShortComplex.cyclesMapIso' (Iso.refl S) h h') (by simp) (by simp) exact preservesColimit_of_iso_diagram F e } /-- If a functor preserves a certain right homology data of a short complex `S`, then it preserves the right homology of `S`. -/ lemma PreservesRightHomologyOf.mk' (h : S.RightHomologyData) [h.IsPreservedBy F] : F.PreservesRightHomologyOf S where isPreservedBy h' := { f := ShortComplex.RightHomologyData.IsPreservedBy.hf h F g' := by have := ShortComplex.RightHomologyData.IsPreservedBy.hg' h F let e : parallelPair h.g' 0 ≅ parallelPair h'.g' 0 := parallelPair.ext (ShortComplex.opcyclesMapIso' (Iso.refl S) h h') (Iso.refl _) (by simp) (by simp) exact preservesLimit_of_iso_diagram F e } end Functor namespace ShortComplex variable {S : ShortComplex C} (h₁ : S.LeftHomologyData) (h₂ : S.RightHomologyData) (F : C ⥤ D) [F.PreservesZeroMorphisms] instance LeftHomologyData.isPreservedBy_of_preserves [F.PreservesLeftHomologyOf S] : h₁.IsPreservedBy F := Functor.PreservesLeftHomologyOf.isPreservedBy _ instance RightHomologyData.isPreservedBy_of_preserves [F.PreservesRightHomologyOf S] : h₂.IsPreservedBy F := Functor.PreservesRightHomologyOf.isPreservedBy _ variable (S) instance hasLeftHomology_of_preserves [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] : (S.map F).HasLeftHomology := HasLeftHomology.mk' (S.leftHomologyData.map F) instance hasLeftHomology_of_preserves' [S.HasLeftHomology] [F.PreservesLeftHomologyOf S] : (F.mapShortComplex.obj S).HasLeftHomology := by dsimp; infer_instance instance hasRightHomology_of_preserves [S.HasRightHomology] [F.PreservesRightHomologyOf S] : (S.map F).HasRightHomology := HasRightHomology.mk' (S.rightHomologyData.map F) instance hasRightHomology_of_preserves' [S.HasRightHomology] [F.PreservesRightHomologyOf S] : (F.mapShortComplex.obj S).HasRightHomology := by dsimp; infer_instance instance hasHomology_of_preserves [S.HasHomology] [F.PreservesLeftHomologyOf S] [F.PreservesRightHomologyOf S] : (S.map F).HasHomology := HasHomology.mk' (S.homologyData.map F) instance hasHomology_of_preserves' [S.HasHomology] [F.PreservesLeftHomologyOf S] [F.PreservesRightHomologyOf S] : (F.mapShortComplex.obj S).HasHomology := by dsimp; infer_instance section variable (hl : S.LeftHomologyData) (hr : S.RightHomologyData) {S₁ S₂ : ShortComplex C} (φ : S₁ ⟶ S₂) (hl₁ : S₁.LeftHomologyData) (hr₁ : S₁.RightHomologyData) (hl₂ : S₂.LeftHomologyData) (hr₂ : S₂.RightHomologyData) (h₁ : S₁.HomologyData) (h₂ : S₂.HomologyData) (F : C ⥤ D) [F.PreservesZeroMorphisms] namespace LeftHomologyData variable [hl₁.IsPreservedBy F] [hl₂.IsPreservedBy F] lemma map_cyclesMap' : F.map (ShortComplex.cyclesMap' φ hl₁ hl₂) = ShortComplex.cyclesMap' (F.mapShortComplex.map φ) (hl₁.map F) (hl₂.map F) := by have γ : ShortComplex.LeftHomologyMapData φ hl₁ hl₂ := default rw [γ.cyclesMap'_eq, (γ.map F).cyclesMap'_eq, ShortComplex.LeftHomologyMapData.map_φK] lemma map_leftHomologyMap' : F.map (ShortComplex.leftHomologyMap' φ hl₁ hl₂) = ShortComplex.leftHomologyMap' (F.mapShortComplex.map φ) (hl₁.map F) (hl₂.map F) := by have γ : ShortComplex.LeftHomologyMapData φ hl₁ hl₂ := default rw [γ.leftHomologyMap'_eq, (γ.map F).leftHomologyMap'_eq, ShortComplex.LeftHomologyMapData.map_φH] end LeftHomologyData namespace RightHomologyData
variable [hr₁.IsPreservedBy F] [hr₂.IsPreservedBy F] lemma map_opcyclesMap' : F.map (ShortComplex.opcyclesMap' φ hr₁ hr₂) = ShortComplex.opcyclesMap' (F.mapShortComplex.map φ) (hr₁.map F) (hr₂.map F) := by
Mathlib/Algebra/Homology/ShortComplex/PreservesHomology.lean
377
380
/- 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.SymmDiff import Mathlib.Order.SuccPred.Relation import Mathlib.Topology.Irreducible /-! # 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 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 /-- 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 theorem IsConnected.nonempty {s : Set α} (h : IsConnected s) : s.Nonempty := h.1 theorem IsConnected.isPreconnected {s : Set α} (h : IsConnected s) : IsPreconnected s := h.2 theorem IsPreirreducible.isPreconnected {s : Set α} (H : IsPreirreducible s) : IsPreconnected s := fun _ _ hu hv _ => H _ _ hu hv theorem IsIrreducible.isConnected {s : Set α} (H : IsIrreducible s) : IsConnected s := ⟨H.nonempty, H.isPreirreducible.isPreconnected⟩ theorem isPreconnected_empty : IsPreconnected (∅ : Set α) := isPreirreducible_empty.isPreconnected theorem isConnected_singleton {x} : IsConnected ({x} : Set α) := isIrreducible_singleton.isConnected theorem isPreconnected_singleton {x} : IsPreconnected ({x} : Set α) := isConnected_singleton.isPreconnected theorem Set.Subsingleton.isPreconnected {s : Set α} (hs : s.Subsingleton) : IsPreconnected s := hs.induction_on isPreconnected_empty fun _ => isPreconnected_singleton /-- 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 (https://github.com/leanprover-community/mathlib4/issues/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⟩ /-- 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] /-- 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⟩ 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)
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)
Mathlib/Topology/Connected/Basic.lean
116
120
/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison -/ import Mathlib.Algebra.Polynomial.AlgebraMap import Mathlib.RingTheory.IsTensorProduct /-! # Base change of polynomial algebras Given `[CommSemiring R] [Semiring A] [Algebra R A]` we show `A[X] ≃ₐ[R] (A ⊗[R] R[X])`. -/ -- This file should not become entangled with `RingTheory/MatrixAlgebra`. assert_not_exists Matrix universe u v w open Polynomial TensorProduct open Algebra.TensorProduct (algHomOfLinearMapTensorProduct includeLeft) noncomputable section variable (R A : Type*) variable [CommSemiring R] variable [Semiring A] [Algebra R A] namespace PolyEquivTensor /-- (Implementation detail). The function underlying `A ⊗[R] R[X] →ₐ[R] A[X]`, as a bilinear function of two arguments. -/ def toFunBilinear : A →ₗ[A] R[X] →ₗ[R] A[X] := LinearMap.toSpanSingleton A _ (aeval (Polynomial.X : A[X])).toLinearMap theorem toFunBilinear_apply_apply (a : A) (p : R[X]) : toFunBilinear R A a p = a • (aeval X) p := rfl @[simp] theorem toFunBilinear_apply_eq_smul (a : A) (p : R[X]) : toFunBilinear R A a p = a • p.map (algebraMap R A) := rfl theorem toFunBilinear_apply_eq_sum (a : A) (p : R[X]) : toFunBilinear R A a p = p.sum fun n r ↦ monomial n (a * algebraMap R A r) := by conv_lhs => rw [toFunBilinear_apply_eq_smul, ← p.sum_monomial_eq, sum, Polynomial.map_sum] simp [Finset.smul_sum, sum, ← smul_eq_mul] /-- (Implementation detail). The function underlying `A ⊗[R] R[X] →ₐ[R] A[X]`, as a linear map. -/ def toFunLinear : A ⊗[R] R[X] →ₗ[R] A[X] := TensorProduct.lift (toFunBilinear R A) @[simp] theorem toFunLinear_tmul_apply (a : A) (p : R[X]) : toFunLinear R A (a ⊗ₜ[R] p) = toFunBilinear R A a p := rfl -- We apparently need to provide the decidable instance here -- in order to successfully rewrite by this lemma. theorem toFunLinear_mul_tmul_mul_aux_1 (p : R[X]) (k : ℕ) (h : Decidable ¬p.coeff k = 0) (a : A) : ite (¬coeff p k = 0) (a * (algebraMap R A) (coeff p k)) 0 = a * (algebraMap R A) (coeff p k) := by classical split_ifs <;> simp [*] theorem toFunLinear_mul_tmul_mul_aux_2 (k : ℕ) (a₁ a₂ : A) (p₁ p₂ : R[X]) : a₁ * a₂ * (algebraMap R A) ((p₁ * p₂).coeff k) = (Finset.antidiagonal k).sum fun x => a₁ * (algebraMap R A) (coeff p₁ x.1) * (a₂ * (algebraMap R A) (coeff p₂ x.2)) := by simp_rw [mul_assoc, Algebra.commutes, ← Finset.mul_sum, mul_assoc, ← Finset.mul_sum] congr simp_rw [Algebra.commutes (coeff p₂ _), coeff_mul, map_sum, RingHom.map_mul] theorem toFunLinear_mul_tmul_mul (a₁ a₂ : A) (p₁ p₂ : R[X]) : (toFunLinear R A) ((a₁ * a₂) ⊗ₜ[R] (p₁ * p₂)) = (toFunLinear R A) (a₁ ⊗ₜ[R] p₁) * (toFunLinear R A) (a₂ ⊗ₜ[R] p₂) := by classical simp only [toFunLinear_tmul_apply, toFunBilinear_apply_eq_sum] ext k simp_rw [coeff_sum, coeff_monomial, sum_def, Finset.sum_ite_eq', mem_support_iff, Ne] conv_rhs => rw [coeff_mul] simp_rw [finset_sum_coeff, coeff_monomial, Finset.sum_ite_eq', mem_support_iff, Ne, mul_ite, mul_zero, ite_mul, zero_mul] simp_rw [← ite_zero_mul (¬coeff p₁ _ = 0) (a₁ * (algebraMap R A) (coeff p₁ _))] simp_rw [← mul_ite_zero (¬coeff p₂ _ = 0) _ (_ * _)] simp_rw [toFunLinear_mul_tmul_mul_aux_1, toFunLinear_mul_tmul_mul_aux_2] theorem toFunLinear_one_tmul_one : toFunLinear R A (1 ⊗ₜ[R] 1) = 1 := by rw [toFunLinear_tmul_apply, toFunBilinear_apply_apply, Polynomial.aeval_one, one_smul] /-- (Implementation detail). The algebra homomorphism `A ⊗[R] R[X] →ₐ[R] A[X]`. -/ def toFunAlgHom : A ⊗[R] R[X] →ₐ[R] A[X] := algHomOfLinearMapTensorProduct (toFunLinear R A) (toFunLinear_mul_tmul_mul R A) (toFunLinear_one_tmul_one R A) @[simp] theorem toFunAlgHom_apply_tmul_eq_smul (a : A) (p : R[X]) : toFunAlgHom R A (a ⊗ₜ[R] p) = a • p.map (algebraMap R A) := rfl theorem toFunAlgHom_apply_tmul (a : A) (p : R[X]) : toFunAlgHom R A (a ⊗ₜ[R] p) = p.sum fun n r => monomial n (a * (algebraMap R A) r) := toFunBilinear_apply_eq_sum R A _ _ /-- (Implementation detail.) The bare function `A[X] → A ⊗[R] R[X]`. (We don't need to show that it's an algebra map, thankfully --- just that it's an inverse.) -/ def invFun (p : A[X]) : A ⊗[R] R[X] := p.eval₂ (includeLeft : A →ₐ[R] A ⊗[R] R[X]) ((1 : A) ⊗ₜ[R] (X : R[X])) @[simp] theorem invFun_add {p q} : invFun R A (p + q) = invFun R A p + invFun R A q := by simp only [invFun, eval₂_add] theorem invFun_monomial (n : ℕ) (a : A) : invFun R A (monomial n a) = (a ⊗ₜ[R] 1) * 1 ⊗ₜ[R] X ^ n := eval₂_monomial _ _ theorem left_inv (x : A ⊗ R[X]) : invFun R A ((toFunAlgHom R A) x) = x := by refine TensorProduct.induction_on x ?_ ?_ ?_ · simp [invFun] · intro a p dsimp only [invFun] rw [toFunAlgHom_apply_tmul, eval₂_sum] simp_rw [eval₂_monomial, AlgHom.coe_toRingHom, Algebra.TensorProduct.tmul_pow, one_pow, Algebra.TensorProduct.includeLeft_apply, Algebra.TensorProduct.tmul_mul_tmul, mul_one, one_mul, ← Algebra.commutes, ← Algebra.smul_def, smul_tmul, sum_def, ← tmul_sum] conv_rhs => rw [← sum_C_mul_X_pow_eq p] simp only [Algebra.smul_def] rfl · intro p q hp hq simp only [map_add, invFun_add, hp, hq] theorem right_inv (x : A[X]) : (toFunAlgHom R A) (invFun R A x) = x := by refine Polynomial.induction_on' x ?_ ?_ · intro p q hp hq simp only [invFun_add, map_add, hp, hq] · intro n a rw [invFun_monomial, Algebra.TensorProduct.tmul_pow, one_pow, Algebra.TensorProduct.tmul_mul_tmul, mul_one, one_mul, toFunAlgHom_apply_tmul, X_pow_eq_monomial, sum_monomial_index] <;> simp /-- (Implementation detail) The equivalence, ignoring the algebra structure, `(A ⊗[R] R[X]) ≃ A[X]`. -/ def equiv : A ⊗[R] R[X] ≃ A[X] where toFun := toFunAlgHom R A invFun := invFun R A left_inv := left_inv R A right_inv := right_inv R A end PolyEquivTensor open PolyEquivTensor /-- The `R`-algebra isomorphism `A[X] ≃ₐ[R] (A ⊗[R] R[X])`. -/ def polyEquivTensor : A[X] ≃ₐ[R] A ⊗[R] R[X] := AlgEquiv.symm { PolyEquivTensor.toFunAlgHom R A, PolyEquivTensor.equiv R A with } @[simp] theorem polyEquivTensor_apply (p : A[X]) : polyEquivTensor R A p = p.eval₂ (includeLeft : A →ₐ[R] A ⊗[R] R[X]) ((1 : A) ⊗ₜ[R] (X : R[X])) := rfl @[simp] theorem polyEquivTensor_symm_apply_tmul_eq_smul (a : A) (p : R[X]) : (polyEquivTensor R A).symm (a ⊗ₜ p) = a • p.map (algebraMap R A) := rfl theorem polyEquivTensor_symm_apply_tmul (a : A) (p : R[X]) : (polyEquivTensor R A).symm (a ⊗ₜ p) = p.sum fun n r => monomial n (a * algebraMap R A r) := toFunAlgHom_apply_tmul _ _ _ _ section variable (A : Type*) [CommSemiring A] [Algebra R A] /-- The `A`-algebra isomorphism `A[X] ≃ₐ[A] A ⊗[R] R[X]` (when `A` is commutative). -/ def polyEquivTensor' : A[X] ≃ₐ[A] A ⊗[R] R[X] where __ := polyEquivTensor R A commutes' a := by simp /-- `polyEquivTensor' R A` is the same as `polyEquivTensor R A` as a function. -/ @[simp] theorem coe_polyEquivTensor' : ⇑(polyEquivTensor' R A) = polyEquivTensor R A := rfl @[simp] theorem coe_polyEquivTensor'_symm : ⇑(polyEquivTensor' R A).symm = (polyEquivTensor R A).symm := rfl end /-- If `A` is an `R`-algebra, then `A[X]` is an `R[X]` algebra. This gives a diamond for `Algebra R[X] R[X][X]`, so this is not a global instance. -/ @[reducible] def Polynomial.algebra : Algebra R[X] A[X] := (mapRingHom (algebraMap R A)).toAlgebra' fun _ _ ↦ by ext; rw [coeff_mul, ← Finset.Nat.sum_antidiagonal_swap, coeff_mul]; simp [Algebra.commutes] attribute [local instance] Polynomial.algebra @[simp] theorem Polynomial.algebraMap_def : algebraMap R[X] A[X] = mapRingHom (algebraMap R A) := rfl instance : IsScalarTower R R[X] A[X] := .of_algebraMap_eq' (mapRingHom_comp_C _).symm instance [FaithfulSMul R A] : FaithfulSMul R[X] A[X] := (faithfulSMul_iff_algebraMap_injective ..).mpr (map_injective _ <| FaithfulSMul.algebraMap_injective ..) variable {S : Type*} [CommSemiring S] [Algebra R S] instance : Algebra.IsPushout R S R[X] S[X] where out := .of_equiv (polyEquivTensor' R S).symm fun _ ↦ (polyEquivTensor_symm_apply_tmul_eq_smul ..).trans <| one_smul .. instance : Algebra.IsPushout R R[X] S S[X] := .symm inferInstance
Mathlib/RingTheory/PolynomialAlgebra.lean
287
291
/- 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, Wen Yang -/ import Mathlib.LinearAlgebra.Matrix.Transvection import Mathlib.LinearAlgebra.Matrix.NonsingularInverse import Mathlib.Tactic.FinCases /-! # Block matrices and their determinant This file defines a predicate `Matrix.BlockTriangular` saying a matrix is block triangular, and proves the value of the determinant for various matrices built out of blocks. ## Main definitions * `Matrix.BlockTriangular` expresses that an `o` by `o` matrix is block triangular, if the rows and columns are ordered according to some order `b : o → α` ## Main results * `Matrix.det_of_blockTriangular`: the determinant of a block triangular matrix is equal to the product of the determinants of all the blocks * `Matrix.det_of_upperTriangular` and `Matrix.det_of_lowerTriangular`: the determinant of a triangular matrix is the product of the entries along the diagonal ## Tags matrix, diagonal, det, block triangular -/ open Finset Function OrderDual open Matrix universe v variable {α β m n o : Type*} {m' n' : α → Type*} variable {R : Type v} {M N : Matrix m m R} {b : m → α} namespace Matrix section LT variable [LT α] section Zero variable [Zero R] /-- Let `b` map rows and columns of a square matrix `M` to blocks indexed by `α`s. Then `BlockTriangular M n b` says the matrix is block triangular. -/ def BlockTriangular (M : Matrix m m R) (b : m → α) : Prop := ∀ ⦃i j⦄, b j < b i → M i j = 0 @[simp] protected theorem BlockTriangular.submatrix {f : n → m} (h : M.BlockTriangular b) : (M.submatrix f f).BlockTriangular (b ∘ f) := fun _ _ hij => h hij theorem blockTriangular_reindex_iff {b : n → α} {e : m ≃ n} : (reindex e e M).BlockTriangular b ↔ M.BlockTriangular (b ∘ e) := by refine ⟨fun h => ?_, fun h => ?_⟩ · convert h.submatrix simp only [reindex_apply, submatrix_submatrix, submatrix_id_id, Equiv.symm_comp_self] · convert h.submatrix simp only [comp_assoc b e e.symm, Equiv.self_comp_symm, comp_id] protected theorem BlockTriangular.transpose : M.BlockTriangular b → Mᵀ.BlockTriangular (toDual ∘ b) := swap @[simp] protected theorem blockTriangular_transpose_iff {b : m → αᵒᵈ} : Mᵀ.BlockTriangular b ↔ M.BlockTriangular (ofDual ∘ b) := forall_swap @[simp] theorem blockTriangular_zero : BlockTriangular (0 : Matrix m m R) b := fun _ _ _ => rfl end Zero protected theorem BlockTriangular.neg [NegZeroClass R] {M : Matrix m m R} (hM : BlockTriangular M b) : BlockTriangular (-M) b := fun _ _ h => by rw [neg_apply, hM h, neg_zero] theorem BlockTriangular.add [AddZeroClass R] (hM : BlockTriangular M b) (hN : BlockTriangular N b) : BlockTriangular (M + N) b := fun i j h => by simp_rw [Matrix.add_apply, hM h, hN h, zero_add] theorem BlockTriangular.sub [SubNegZeroMonoid R] (hM : BlockTriangular M b) (hN : BlockTriangular N b) : BlockTriangular (M - N) b := fun i j h => by simp_rw [Matrix.sub_apply, hM h, hN h, sub_zero] lemma BlockTriangular.add_iff_right [AddGroup R] (hM : BlockTriangular M b) : BlockTriangular (M + N) b ↔ BlockTriangular N b := ⟨(by simpa using hM.neg.add ·), hM.add⟩ lemma BlockTriangular.add_iff_left [AddGroup R] (hN : BlockTriangular N b) : BlockTriangular (M + N) b ↔ BlockTriangular M b := ⟨(by simpa using ·.sub hN), (·.add hN)⟩ lemma BlockTriangular.sub_iff_right [AddGroup R] (hM : BlockTriangular M b) : BlockTriangular (M - N) b ↔ BlockTriangular N b := ⟨(by simpa using ·.neg.add hM), hM.sub⟩ lemma BlockTriangular.sub_iff_left [AddGroup R] (hN : BlockTriangular N b) : BlockTriangular (M - N) b ↔ BlockTriangular M b := ⟨(by simpa using ·.add hN), (·.sub hN)⟩ lemma BlockTriangular.map {S F} [FunLike F R S] [Zero R] [Zero S] [ZeroHomClass F R S] (f : F) (h : BlockTriangular M b) : BlockTriangular (M.map f) b := fun i j lt ↦ by simp [h lt] lemma BlockTriangular.comp [Zero R] {M : Matrix m m (Matrix n n R)} (h : BlockTriangular M b) : BlockTriangular (M.comp m m n n R) fun i ↦ b i.1 := fun i j lt ↦ by simp [h lt] end LT section Preorder variable [Preorder α] section Zero variable [Zero R] theorem blockTriangular_diagonal [DecidableEq m] (d : m → R) : BlockTriangular (diagonal d) b := fun _ _ h => diagonal_apply_ne' d fun h' => ne_of_lt h (congr_arg _ h') theorem blockTriangular_blockDiagonal' [DecidableEq α] (d : ∀ i : α, Matrix (m' i) (m' i) R) : BlockTriangular (blockDiagonal' d) Sigma.fst := by rintro ⟨i, i'⟩ ⟨j, j'⟩ h apply blockDiagonal'_apply_ne d i' j' fun h' => ne_of_lt h h'.symm theorem blockTriangular_blockDiagonal [DecidableEq α] (d : α → Matrix m m R) : BlockTriangular (blockDiagonal d) Prod.snd := by rintro ⟨i, i'⟩ ⟨j, j'⟩ h rw [blockDiagonal'_eq_blockDiagonal, blockTriangular_blockDiagonal'] exact h variable [DecidableEq m] theorem blockTriangular_one [One R] : BlockTriangular (1 : Matrix m m R) b := blockTriangular_diagonal _ theorem blockTriangular_stdBasisMatrix {i j : m} (hij : b i ≤ b j) (c : R) : BlockTriangular (stdBasisMatrix i j c) b := by intro r s hrs apply StdBasisMatrix.apply_of_ne rintro ⟨rfl, rfl⟩ exact (hij.trans_lt hrs).false theorem blockTriangular_stdBasisMatrix' {i j : m} (hij : b j ≤ b i) (c : R) : BlockTriangular (stdBasisMatrix i j c) (toDual ∘ b) := blockTriangular_stdBasisMatrix (by exact toDual_le_toDual.mpr hij) _ end Zero variable [CommRing R] [DecidableEq m] theorem blockTriangular_transvection {i j : m} (hij : b i ≤ b j) (c : R) : BlockTriangular (transvection i j c) b := blockTriangular_one.add (blockTriangular_stdBasisMatrix hij c) theorem blockTriangular_transvection' {i j : m} (hij : b j ≤ b i) (c : R) : BlockTriangular (transvection i j c) (OrderDual.toDual ∘ b) := blockTriangular_one.add (blockTriangular_stdBasisMatrix' hij c) end Preorder section LinearOrder variable [LinearOrder α] theorem BlockTriangular.mul [Fintype m] [NonUnitalNonAssocSemiring R] {M N : Matrix m m R} (hM : BlockTriangular M b) (hN : BlockTriangular N b) : BlockTriangular (M * N) b := by intro i j hij apply Finset.sum_eq_zero intro k _ by_cases hki : b k < b i · simp_rw [hM hki, zero_mul] · simp_rw [hN (lt_of_lt_of_le hij (le_of_not_lt hki)), mul_zero] end LinearOrder theorem upper_two_blockTriangular [Zero R] [Preorder α] (A : Matrix m m R) (B : Matrix m n R) (D : Matrix n n R) {a b : α} (hab : a < b) : BlockTriangular (fromBlocks A B 0 D) (Sum.elim (fun _ => a) fun _ => b) := by rintro (c | c) (d | d) hcd <;> first | simp [hab.not_lt] at hcd ⊢ /-! ### Determinant -/ variable [CommRing R] [DecidableEq m] [Fintype m] [DecidableEq n] [Fintype n] theorem equiv_block_det (M : Matrix m m R) {p q : m → Prop} [DecidablePred p] [DecidablePred q] (e : ∀ x, q x ↔ p x) : (toSquareBlockProp M p).det = (toSquareBlockProp M q).det := by convert Matrix.det_reindex_self (Equiv.subtypeEquivRight e) (toSquareBlockProp M q) -- Removed `@[simp]` attribute, -- as the LHS simplifies already to `M.toSquareBlock id i ⟨i, ⋯⟩ ⟨i, ⋯⟩` theorem det_toSquareBlock_id (M : Matrix m m R) (i : m) : (M.toSquareBlock id i).det = M i i := letI : Unique { a // id a = i } := ⟨⟨⟨i, rfl⟩⟩, fun j => Subtype.ext j.property⟩ (det_unique _).trans rfl theorem det_toBlock (M : Matrix m m R) (p : m → Prop) [DecidablePred p] : M.det = (fromBlocks (toBlock M p p) (toBlock M p fun j => ¬p j) (toBlock M (fun j => ¬p j) p) <| toBlock M (fun j => ¬p j) fun j => ¬p j).det := by rw [← Matrix.det_reindex_self (Equiv.sumCompl p).symm M] rw [det_apply', det_apply'] congr; ext σ; congr; ext x generalize hy : σ x = y cases x <;> cases y <;> simp only [Matrix.reindex_apply, toBlock_apply, Equiv.symm_symm, Equiv.sumCompl_apply_inr, Equiv.sumCompl_apply_inl, fromBlocks_apply₁₁, fromBlocks_apply₁₂, fromBlocks_apply₂₁, fromBlocks_apply₂₂, Matrix.submatrix_apply] theorem twoBlockTriangular_det (M : Matrix m m R) (p : m → Prop) [DecidablePred p] (h : ∀ i, ¬p i → ∀ j, p j → M i j = 0) : M.det = (toSquareBlockProp M p).det * (toSquareBlockProp M fun i => ¬p i).det := by rw [det_toBlock M p] convert det_fromBlocks_zero₂₁ (toBlock M p p) (toBlock M p fun j => ¬p j) (toBlock M (fun j => ¬p j) fun j => ¬p j) ext i j exact h (↑i) i.2 (↑j) j.2 theorem twoBlockTriangular_det' (M : Matrix m m R) (p : m → Prop) [DecidablePred p] (h : ∀ i, p i → ∀ j, ¬p j → M i j = 0) : M.det = (toSquareBlockProp M p).det * (toSquareBlockProp M fun i => ¬p i).det := by rw [M.twoBlockTriangular_det fun i => ¬p i, mul_comm] · congr 1 exact equiv_block_det _ fun _ => not_not.symm · simpa only [Classical.not_not] using h protected theorem BlockTriangular.det [DecidableEq α] [LinearOrder α] (hM : BlockTriangular M b) : M.det = ∏ a ∈ univ.image b, (M.toSquareBlock b a).det := by suffices ∀ hs : Finset α, univ.image b = hs → M.det = ∏ a ∈ hs, (M.toSquareBlock b a).det by exact this _ rfl intro s hs induction s using Finset.strongInduction generalizing m with | H s ih => subst hs cases isEmpty_or_nonempty m · simp let k := (univ.image b).max' (univ_nonempty.image _) rw [twoBlockTriangular_det' M fun i => b i = k] · have : univ.image b = insert k ((univ.image b).erase k) := by rw [insert_erase] apply max'_mem rw [this, prod_insert (not_mem_erase _ _)] refine congr_arg _ ?_ let b' := fun i : { a // b a ≠ k } => b ↑i have h' : BlockTriangular (M.toSquareBlockProp fun i => b i ≠ k) b' := hM.submatrix have hb' : image b' univ = (image b univ).erase k := by convert image_subtype_ne_univ_eq_image_erase k b rw [ih _ (erase_ssubset <| max'_mem _ _) h' hb'] refine Finset.prod_congr rfl fun l hl => ?_ let he : { a // b' a = l } ≃ { a // b a = l } := haveI hc : ∀ i, b i = l → b i ≠ k := fun i hi => ne_of_eq_of_ne hi (ne_of_mem_erase hl)
Equiv.subtypeSubtypeEquivSubtype @(hc) simp only [toSquareBlock_def] erw [← Matrix.det_reindex_self he.symm fun i j : { a // b a = l } => M ↑i ↑j] rfl
Mathlib/LinearAlgebra/Matrix/Block.lean
260
263
/- Copyright (c) 2022 Violeta Hernández Palacios. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Violeta Hernández Palacios -/ import Mathlib.SetTheory.Ordinal.FixedPoint /-! # Principal ordinals We define principal or indecomposable ordinals, and we prove the standard properties about them. ## Main definitions and results * `Principal`: A principal or indecomposable ordinal under some binary operation. We include 0 and any other typically excluded edge cases for simplicity. * `not_bddAbove_principal`: Principal ordinals (under any operation) are unbounded. * `principal_add_iff_zero_or_omega0_opow`: The main characterization theorem for additive principal ordinals. * `principal_mul_iff_le_two_or_omega0_opow_opow`: The main characterization theorem for multiplicative principal ordinals. ## TODO * Prove that exponential principal ordinals are 0, 1, 2, ω, or epsilon numbers, i.e. fixed points of `fun x ↦ ω ^ x`. -/ universe u open Order namespace Ordinal variable {a b c o : Ordinal.{u}} section Arbitrary variable {op : Ordinal → Ordinal → Ordinal} /-! ### Principal ordinals -/ /-- An ordinal `o` is said to be principal or indecomposable under an operation when the set of ordinals less than it is closed under that operation. In standard mathematical usage, this term is almost exclusively used for additive and multiplicative principal ordinals. For simplicity, we break usual convention and regard `0` as principal. -/ def Principal (op : Ordinal → Ordinal → Ordinal) (o : Ordinal) : Prop := ∀ ⦃a b⦄, a < o → b < o → op a b < o theorem principal_swap_iff : Principal (Function.swap op) o ↔ Principal op o := by constructor <;> exact fun h a b ha hb => h hb ha theorem not_principal_iff : ¬ Principal op o ↔ ∃ a < o, ∃ b < o, o ≤ op a b := by simp [Principal] theorem principal_iff_of_monotone (h₁ : ∀ a, Monotone (op a)) (h₂ : ∀ a, Monotone (Function.swap op a)) : Principal op o ↔ ∀ a < o, op a a < o := by use fun h a ha => h ha ha intro H a b ha hb obtain hab | hba := le_or_lt a b · exact (h₂ b hab).trans_lt <| H b hb · exact (h₁ a hba.le).trans_lt <| H a ha theorem not_principal_iff_of_monotone (h₁ : ∀ a, Monotone (op a)) (h₂ : ∀ a, Monotone (Function.swap op a)) : ¬ Principal op o ↔ ∃ a < o, o ≤ op a a := by simp [principal_iff_of_monotone h₁ h₂] theorem principal_zero : Principal op 0 := fun a _ h => (Ordinal.not_lt_zero a h).elim @[simp] theorem principal_one_iff : Principal op 1 ↔ op 0 0 = 0 := by refine ⟨fun h => ?_, fun h a b ha hb => ?_⟩ · rw [← lt_one_iff_zero] exact h zero_lt_one zero_lt_one · rwa [lt_one_iff_zero, ha, hb] at * theorem Principal.iterate_lt (hao : a < o) (ho : Principal op o) (n : ℕ) : (op a)^[n] a < o := by induction' n with n hn · rwa [Function.iterate_zero] · rw [Function.iterate_succ'] exact ho hao hn theorem op_eq_self_of_principal (hao : a < o) (H : IsNormal (op a)) (ho : Principal op o) (ho' : IsLimit o) : op a o = o := by apply H.le_apply.antisymm' rw [← IsNormal.bsup_eq.{u, u} H ho', bsup_le_iff] exact fun b hbo => (ho hao hbo).le theorem nfp_le_of_principal (hao : a < o) (ho : Principal op o) : nfp (op a) a ≤ o := nfp_le fun n => (ho.iterate_lt hao n).le end Arbitrary /-! ### Principal ordinals are unbounded -/ /-- We give an explicit construction for a principal ordinal larger or equal than `o`. -/ private theorem principal_nfp_iSup (op : Ordinal → Ordinal → Ordinal) (o : Ordinal) : Principal op (nfp (fun x ↦ ⨆ y : Set.Iio x ×ˢ Set.Iio x, succ (op y.1.1 y.1.2)) o) := by intro a b ha hb rw [lt_nfp_iff] at * obtain ⟨m, ha⟩ := ha obtain ⟨n, hb⟩ := hb obtain h | h := le_total ((fun x ↦ ⨆ y : Set.Iio x ×ˢ Set.Iio x, succ (op y.1.1 y.1.2))^[m] o) ((fun x ↦ ⨆ y : Set.Iio x ×ˢ Set.Iio x, succ (op y.1.1 y.1.2))^[n] o) · use n + 1 rw [Function.iterate_succ'] apply (lt_succ _).trans_le exact Ordinal.le_iSup (fun y : Set.Iio _ ×ˢ Set.Iio _ ↦ succ (op y.1.1 y.1.2)) ⟨_, Set.mk_mem_prod (ha.trans_le h) hb⟩ · use m + 1 rw [Function.iterate_succ'] apply (lt_succ _).trans_le exact Ordinal.le_iSup (fun y : Set.Iio _ ×ˢ Set.Iio _ ↦ succ (op y.1.1 y.1.2)) ⟨_, Set.mk_mem_prod ha (hb.trans_le h)⟩ /-- Principal ordinals under any operation are unbounded. -/ theorem not_bddAbove_principal (op : Ordinal → Ordinal → Ordinal) : ¬ BddAbove { o | Principal op o } := by rintro ⟨a, ha⟩ exact ((le_nfp _ _).trans (ha (principal_nfp_iSup op (succ a)))).not_lt (lt_succ a) /-! #### Additive principal ordinals -/ theorem principal_add_one : Principal (· + ·) 1 := principal_one_iff.2 <| zero_add 0 theorem principal_add_of_le_one (ho : o ≤ 1) : Principal (· + ·) o := by rcases le_one_iff.1 ho with (rfl | rfl) · exact principal_zero · exact principal_add_one theorem isLimit_of_principal_add (ho₁ : 1 < o) (ho : Principal (· + ·) o) : o.IsLimit := by rw [isLimit_iff, isSuccPrelimit_iff_succ_lt] exact ⟨ho₁.ne_bot, fun _ ha ↦ ho ha ho₁⟩ theorem principal_add_iff_add_left_eq_self : Principal (· + ·) o ↔ ∀ a < o, a + o = o := by refine ⟨fun ho a hao => ?_, fun h a b hao hbo => ?_⟩ · rcases lt_or_le 1 o with ho₁ | ho₁ · exact op_eq_self_of_principal hao (isNormal_add_right a) ho (isLimit_of_principal_add ho₁ ho) · rcases le_one_iff.1 ho₁ with (rfl | rfl) · exact (Ordinal.not_lt_zero a hao).elim · rw [lt_one_iff_zero] at hao rw [hao, zero_add] · rw [← h a hao] exact (isNormal_add_right a).strictMono hbo theorem exists_lt_add_of_not_principal_add (ha : ¬ Principal (· + ·) a) : ∃ b < a, ∃ c < a, b + c = a := by rw [not_principal_iff] at ha rcases ha with ⟨b, hb, c, hc, H⟩ refine ⟨b, hb, _, lt_of_le_of_ne (sub_le_self a b) fun hab => ?_, Ordinal.add_sub_cancel_of_le hb.le⟩ rw [← sub_le, hab] at H exact H.not_lt hc theorem principal_add_iff_add_lt_ne_self : Principal (· + ·) a ↔ ∀ b < a, ∀ c < a, b + c ≠ a := ⟨fun ha _ hb _ hc => (ha hb hc).ne, fun H => by by_contra! ha rcases exists_lt_add_of_not_principal_add ha with ⟨b, hb, c, hc, rfl⟩ exact (H b hb c hc).irrefl⟩ theorem principal_add_omega0 : Principal (· + ·) ω := principal_add_iff_add_left_eq_self.2 fun _ => add_omega0 theorem add_omega0_opow (h : a < ω ^ b) : a + ω ^ b = ω ^ b := by refine le_antisymm ?_ (le_add_left _ a) induction' b using limitRecOn with b _ b l IH · rw [opow_zero, ← succ_zero, lt_succ_iff, Ordinal.le_zero] at h rw [h, zero_add]
· rw [opow_succ] at h rcases (lt_mul_of_limit isLimit_omega0).1 h with ⟨x, xo, ax⟩ apply (add_le_add_right ax.le _).trans rw [opow_succ, ← mul_add, add_omega0 xo] · rcases (lt_opow_of_limit omega0_ne_zero l).1 h with ⟨x, xb, ax⟩
Mathlib/SetTheory/Ordinal/Principal.lean
175
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/- Copyright (c) 2023 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Calculus.LineDeriv.Basic import Mathlib.Analysis.Calculus.FDeriv.Measurable /-! # Measurability of the line derivative We prove in `measurable_lineDeriv` that the line derivative of a function (with respect to a locally compact scalar field) is measurable, provided the function is continuous. In `measurable_lineDeriv_uncurry`, assuming additionally that the source space is second countable, we show that `(x, v) ↦ lineDeriv 𝕜 f x v` is also measurable. An assumption such as continuity is necessary, as otherwise one could alternate in a non-measurable way between differentiable and non-differentiable functions along the various lines directed by `v`. -/ open MeasureTheory variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [LocallyCompactSpace 𝕜] {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E] [MeasurableSpace E] [OpensMeasurableSpace E] {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F] [CompleteSpace F] {f : E → F} {v : E} /-! Measurability of the line derivative `lineDeriv 𝕜 f x v` with respect to a fixed direction `v`. -/ theorem measurableSet_lineDifferentiableAt (hf : Continuous f) : MeasurableSet {x : E | LineDifferentiableAt 𝕜 f x v} := by borelize 𝕜 let g : E → 𝕜 → F := fun x t ↦ f (x + t • v) have hg : Continuous g.uncurry := by fun_prop exact measurable_prodMk_right (measurableSet_of_differentiableAt_with_param 𝕜 hg) theorem measurable_lineDeriv [MeasurableSpace F] [BorelSpace F] (hf : Continuous f) : Measurable (fun x ↦ lineDeriv 𝕜 f x v) := by borelize 𝕜 let g : E → 𝕜 → F := fun x t ↦ f (x + t • v) have hg : Continuous g.uncurry := by fun_prop exact (measurable_deriv_with_param hg).comp measurable_prodMk_right theorem stronglyMeasurable_lineDeriv [SecondCountableTopologyEither E F] (hf : Continuous f) : StronglyMeasurable (fun x ↦ lineDeriv 𝕜 f x v) := by borelize 𝕜 let g : E → 𝕜 → F := fun x t ↦ f (x + t • v) have hg : Continuous g.uncurry := by fun_prop exact (stronglyMeasurable_deriv_with_param hg).comp_measurable measurable_prodMk_right theorem aemeasurable_lineDeriv [MeasurableSpace F] [BorelSpace F] (hf : Continuous f) (μ : Measure E) : AEMeasurable (fun x ↦ lineDeriv 𝕜 f x v) μ := (measurable_lineDeriv hf).aemeasurable theorem aestronglyMeasurable_lineDeriv [SecondCountableTopologyEither E F] (hf : Continuous f) (μ : Measure E) : AEStronglyMeasurable (fun x ↦ lineDeriv 𝕜 f x v) μ := (stronglyMeasurable_lineDeriv hf).aestronglyMeasurable /-! Measurability of the line derivative `lineDeriv 𝕜 f x v` when varying both `x` and `v`. For this, we need an additional second countability assumption on `E` to make sure that open sets are measurable in `E × E`. -/ variable [SecondCountableTopology E] theorem measurableSet_lineDifferentiableAt_uncurry (hf : Continuous f) : MeasurableSet {p : E × E | LineDifferentiableAt 𝕜 f p.1 p.2} := by borelize 𝕜 let g : (E × E) → 𝕜 → F := fun p t ↦ f (p.1 + t • p.2) have : Continuous g.uncurry := hf.comp <| (continuous_fst.comp continuous_fst).add <| continuous_snd.smul (continuous_snd.comp continuous_fst) have M_meas : MeasurableSet {q : (E × E) × 𝕜 | DifferentiableAt 𝕜 (g q.1) q.2} := measurableSet_of_differentiableAt_with_param 𝕜 this exact measurable_prodMk_right M_meas theorem measurable_lineDeriv_uncurry [MeasurableSpace F] [BorelSpace F] (hf : Continuous f) : Measurable (fun (p : E × E) ↦ lineDeriv 𝕜 f p.1 p.2) := by borelize 𝕜 let g : (E × E) → 𝕜 → F := fun p t ↦ f (p.1 + t • p.2) have : Continuous g.uncurry := hf.comp <| (continuous_fst.comp continuous_fst).add <| continuous_snd.smul (continuous_snd.comp continuous_fst) exact (measurable_deriv_with_param this).comp measurable_prodMk_right
theorem stronglyMeasurable_lineDeriv_uncurry (hf : Continuous f) : StronglyMeasurable (fun (p : E × E) ↦ lineDeriv 𝕜 f p.1 p.2) := by borelize 𝕜 let g : (E × E) → 𝕜 → F := fun p t ↦ f (p.1 + t • p.2) have : Continuous g.uncurry := hf.comp <| (continuous_fst.comp continuous_fst).add <| continuous_snd.smul (continuous_snd.comp continuous_fst) exact (stronglyMeasurable_deriv_with_param this).comp_measurable measurable_prodMk_right
Mathlib/Analysis/Calculus/LineDeriv/Measurable.lean
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/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johan Commelin, Kim Morrison -/ import Mathlib.Algebra.Category.Ring.Colimits import Mathlib.Algebra.Category.Ring.Instances import Mathlib.Algebra.Category.Ring.Limits import Mathlib.Algebra.Ring.Subring.Basic import Mathlib.RingTheory.Localization.AtPrime import Mathlib.RingTheory.Spectrum.Prime.Topology import Mathlib.Topology.Sheaves.LocalPredicate /-! # The structure sheaf on `PrimeSpectrum R`. We define the structure sheaf on `TopCat.of (PrimeSpectrum R)`, for a commutative ring `R` and prove basic properties about it. We define this as a subsheaf of the sheaf of dependent functions into the localizations, cut out by the condition that the function must be locally equal to a ratio of elements of `R`. Because the condition "is equal to a fraction" passes to smaller open subsets, the subset of functions satisfying this condition is automatically a subpresheaf. Because the condition "is locally equal to a fraction" is local, it is also a subsheaf. (It may be helpful to refer back to `Mathlib/Topology/Sheaves/SheafOfFunctions.lean`, where we show that dependent functions into any type family form a sheaf, and also `Mathlib/Topology/Sheaves/LocalPredicate.lean`, where we characterise the predicates which pick out sub-presheaves and sub-sheaves of these sheaves.) We also set up the ring structure, obtaining `structureSheaf : Sheaf CommRingCat (PrimeSpectrum.Top R)`. We then construct two basic isomorphisms, relating the structure sheaf to the underlying ring `R`. First, `StructureSheaf.stalkIso` gives an isomorphism between the stalk of the structure sheaf at a point `p` and the localization of `R` at the prime ideal `p`. Second, `StructureSheaf.basicOpenIso` gives an isomorphism between the structure sheaf on `basicOpen f` and the localization of `R` at the submonoid of powers of `f`. ## References * [Robin Hartshorne, *Algebraic Geometry*][Har77] -/ universe u noncomputable section variable (R : Type u) [CommRing R] open TopCat open TopologicalSpace open CategoryTheory open Opposite namespace AlgebraicGeometry /-- The prime spectrum, just as a topological space. -/ def PrimeSpectrum.Top : TopCat := TopCat.of (PrimeSpectrum R) namespace StructureSheaf /-- The type family over `PrimeSpectrum R` consisting of the localization over each point. -/ def Localizations (P : PrimeSpectrum.Top R) : Type u := Localization.AtPrime P.asIdeal instance commRingLocalizations (P : PrimeSpectrum.Top R) : CommRing <| Localizations R P := inferInstanceAs <| CommRing <| Localization.AtPrime P.asIdeal instance localRingLocalizations (P : PrimeSpectrum.Top R) : IsLocalRing <| Localizations R P := inferInstanceAs <| IsLocalRing <| Localization.AtPrime P.asIdeal instance (P : PrimeSpectrum.Top R) : Inhabited (Localizations R P) := ⟨1⟩ instance (U : Opens (PrimeSpectrum.Top R)) (x : U) : Algebra R (Localizations R x) := inferInstanceAs <| Algebra R (Localization.AtPrime x.1.asIdeal) instance (U : Opens (PrimeSpectrum.Top R)) (x : U) : IsLocalization.AtPrime (Localizations R x) (x : PrimeSpectrum.Top R).asIdeal := Localization.isLocalization variable {R} /-- The predicate saying that a dependent function on an open `U` is realised as a fixed fraction `r / s` in each of the stalks (which are localizations at various prime ideals). -/ def IsFraction {U : Opens (PrimeSpectrum.Top R)} (f : ∀ x : U, Localizations R x) : Prop := ∃ r s : R, ∀ x : U, ¬s ∈ x.1.asIdeal ∧ f x * algebraMap _ _ s = algebraMap _ _ r theorem IsFraction.eq_mk' {U : Opens (PrimeSpectrum.Top R)} {f : ∀ x : U, Localizations R x} (hf : IsFraction f) : ∃ r s : R, ∀ x : U, ∃ hs : s ∉ x.1.asIdeal, f x = IsLocalization.mk' (Localization.AtPrime _) r (⟨s, hs⟩ : (x : PrimeSpectrum.Top R).asIdeal.primeCompl) := by rcases hf with ⟨r, s, h⟩ refine ⟨r, s, fun x => ⟨(h x).1, (IsLocalization.mk'_eq_iff_eq_mul.mpr ?_).symm⟩⟩ exact (h x).2.symm variable (R) /-- The predicate `IsFraction` is "prelocal", in the sense that if it holds on `U` it holds on any open subset `V` of `U`. -/ def isFractionPrelocal : PrelocalPredicate (Localizations R) where pred {_} f := IsFraction f res := by rintro V U i f ⟨r, s, w⟩; exact ⟨r, s, fun x => w (i x)⟩ /-- We will define the structure sheaf as the subsheaf of all dependent functions in `Π x : U, Localizations R x` consisting of those functions which can locally be expressed as a ratio of (the images in the localization of) elements of `R`. Quoting Hartshorne: For an open set $U ⊆ Spec A$, we define $𝒪(U)$ to be the set of functions $s : U → ⨆_{𝔭 ∈ U} A_𝔭$, such that $s(𝔭) ∈ A_𝔭$ for each $𝔭$, and such that $s$ is locally a quotient of elements of $A$: to be precise, we require that for each $𝔭 ∈ U$, there is a neighborhood $V$ of $𝔭$, contained in $U$, and elements $a, f ∈ A$, such that for each $𝔮 ∈ V, f ∉ 𝔮$, and $s(𝔮) = a/f$ in $A_𝔮$. Now Hartshorne had the disadvantage of not knowing about dependent functions, so we replace his circumlocution about functions into a disjoint union with `Π x : U, Localizations x`. -/ def isLocallyFraction : LocalPredicate (Localizations R) := (isFractionPrelocal R).sheafify @[simp] theorem isLocallyFraction_pred {U : Opens (PrimeSpectrum.Top R)} (f : ∀ x : U, Localizations R x) : (isLocallyFraction R).pred f = ∀ x : U, ∃ (V : _) (_ : x.1 ∈ V) (i : V ⟶ U), ∃ r s : R, ∀ y : V, ¬s ∈ y.1.asIdeal ∧ f (i y : U) * algebraMap _ _ s = algebraMap _ _ r := rfl /-- The functions satisfying `isLocallyFraction` form a subring. -/ def sectionsSubring (U : (Opens (PrimeSpectrum.Top R))ᵒᵖ) : Subring (∀ x : U.unop, Localizations R x) where carrier := { f | (isLocallyFraction R).pred f } zero_mem' := by refine fun x => ⟨unop U, x.2, 𝟙 _, 0, 1, fun y => ⟨?_, ?_⟩⟩ · rw [← Ideal.ne_top_iff_one]; exact y.1.isPrime.1 · simp one_mem' := by refine fun x => ⟨unop U, x.2, 𝟙 _, 1, 1, fun y => ⟨?_, ?_⟩⟩ · rw [← Ideal.ne_top_iff_one]; exact y.1.isPrime.1 · simp add_mem' := by intro a b ha hb x rcases ha x with ⟨Va, ma, ia, ra, sa, wa⟩ rcases hb x with ⟨Vb, mb, ib, rb, sb, wb⟩ refine ⟨Va ⊓ Vb, ⟨ma, mb⟩, Opens.infLELeft _ _ ≫ ia, ra * sb + rb * sa, sa * sb, ?_⟩ intro ⟨y, hy⟩ rcases wa (Opens.infLELeft _ _ ⟨y, hy⟩) with ⟨nma, wa⟩ rcases wb (Opens.infLERight _ _ ⟨y, hy⟩) with ⟨nmb, wb⟩ fconstructor · intro H; cases y.isPrime.mem_or_mem H <;> contradiction · simp only [Opens.apply_mk, Pi.add_apply, RingHom.map_mul, add_mul, RingHom.map_add] at wa wb ⊢ rw [← wa, ← wb] simp only [mul_assoc] congr 2 rw [mul_comm] neg_mem' := by intro a ha x rcases ha x with ⟨V, m, i, r, s, w⟩ refine ⟨V, m, i, -r, s, ?_⟩ intro y rcases w y with ⟨nm, w⟩ fconstructor · exact nm · simp only [RingHom.map_neg, Pi.neg_apply] rw [← w] simp only [neg_mul] mul_mem' := by intro a b ha hb x rcases ha x with ⟨Va, ma, ia, ra, sa, wa⟩ rcases hb x with ⟨Vb, mb, ib, rb, sb, wb⟩ refine ⟨Va ⊓ Vb, ⟨ma, mb⟩, Opens.infLELeft _ _ ≫ ia, ra * rb, sa * sb, ?_⟩ intro ⟨y, hy⟩ rcases wa (Opens.infLELeft _ _ ⟨y, hy⟩) with ⟨nma, wa⟩ rcases wb (Opens.infLERight _ _ ⟨y, hy⟩) with ⟨nmb, wb⟩ fconstructor · intro H; cases y.isPrime.mem_or_mem H <;> contradiction · simp only [Opens.apply_mk, Pi.mul_apply, RingHom.map_mul] at wa wb ⊢ rw [← wa, ← wb] simp only [mul_left_comm, mul_assoc, mul_comm] end StructureSheaf open StructureSheaf /-- The structure sheaf (valued in `Type`, not yet `CommRingCat`) is the subsheaf consisting of functions satisfying `isLocallyFraction`. -/ def structureSheafInType : Sheaf (Type u) (PrimeSpectrum.Top R) := subsheafToTypes (isLocallyFraction R) instance commRingStructureSheafInTypeObj (U : (Opens (PrimeSpectrum.Top R))ᵒᵖ) : CommRing ((structureSheafInType R).1.obj U) := (sectionsSubring R U).toCommRing open PrimeSpectrum /-- The structure presheaf, valued in `CommRingCat`, constructed by dressing up the `Type` valued structure presheaf. -/ @[simps obj_carrier] def structurePresheafInCommRing : Presheaf CommRingCat (PrimeSpectrum.Top R) where obj U := CommRingCat.of ((structureSheafInType R).1.obj U) map {_ _} i := CommRingCat.ofHom { toFun := (structureSheafInType R).1.map i map_zero' := rfl map_add' := fun _ _ => rfl map_one' := rfl map_mul' := fun _ _ => rfl } /-- Some glue, verifying that the structure presheaf valued in `CommRingCat` agrees with the `Type` valued structure presheaf. -/ def structurePresheafCompForget : structurePresheafInCommRing R ⋙ forget CommRingCat ≅ (structureSheafInType R).1 := NatIso.ofComponents fun _ => Iso.refl _ open TopCat.Presheaf /-- The structure sheaf on $Spec R$, valued in `CommRingCat`. This is provided as a bundled `SheafedSpace` as `Spec.SheafedSpace R` later. -/ def Spec.structureSheaf : Sheaf CommRingCat (PrimeSpectrum.Top R) := ⟨structurePresheafInCommRing R, (-- We check the sheaf condition under `forget CommRingCat`. isSheaf_iff_isSheaf_comp _ _).mpr (isSheaf_of_iso (structurePresheafCompForget R).symm (structureSheafInType R).cond)⟩ open Spec (structureSheaf) namespace StructureSheaf @[simp] theorem res_apply (U V : Opens (PrimeSpectrum.Top R)) (i : V ⟶ U) (s : (structureSheaf R).1.obj (op U)) (x : V) : ((structureSheaf R).1.map i.op s).1 x = (s.1 (i x) :) := rfl /- Notation in this comment X = Spec R OX = structure sheaf In the following we construct an isomorphism between OX_p and R_p given any point p corresponding to a prime ideal in R. We do this via 8 steps: 1. def const (f g : R) (V) (hv : V ≤ D_g) : OX(V) [for api] 2. def toOpen (U) : R ⟶ OX(U) 3. [2] def toStalk (p : Spec R) : R ⟶ OX_p 4. [2] def toBasicOpen (f : R) : R_f ⟶ OX(D_f) 5. [3] def localizationToStalk (p : Spec R) : R_p ⟶ OX_p 6. def openToLocalization (U) (p) (hp : p ∈ U) : OX(U) ⟶ R_p 7. [6] def stalkToFiberRingHom (p : Spec R) : OX_p ⟶ R_p 8. [5,7] def stalkIso (p : Spec R) : OX_p ≅ R_p In the square brackets we list the dependencies of a construction on the previous steps. -/ /-- The section of `structureSheaf R` on an open `U` sending each `x ∈ U` to the element `f/g` in the localization of `R` at `x`. -/ def const (f g : R) (U : Opens (PrimeSpectrum.Top R)) (hu : ∀ x ∈ U, g ∈ (x : PrimeSpectrum.Top R).asIdeal.primeCompl) : (structureSheaf R).1.obj (op U) := ⟨fun x => IsLocalization.mk' _ f ⟨g, hu x x.2⟩, fun x => ⟨U, x.2, 𝟙 _, f, g, fun y => ⟨hu y y.2, IsLocalization.mk'_spec _ _ _⟩⟩⟩ @[simp] theorem const_apply (f g : R) (U : Opens (PrimeSpectrum.Top R)) (hu : ∀ x ∈ U, g ∈ (x : PrimeSpectrum.Top R).asIdeal.primeCompl) (x : U) : (const R f g U hu).1 x = IsLocalization.mk' (Localization.AtPrime x.1.asIdeal) f ⟨g, hu x x.2⟩ := rfl theorem const_apply' (f g : R) (U : Opens (PrimeSpectrum.Top R)) (hu : ∀ x ∈ U, g ∈ (x : PrimeSpectrum.Top R).asIdeal.primeCompl) (x : U) (hx : g ∈ (x : PrimeSpectrum.Top R).asIdeal.primeCompl) : (const R f g U hu).1 x = IsLocalization.mk' _ f ⟨g, hx⟩ := rfl theorem exists_const (U) (s : (structureSheaf R).1.obj (op U)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) : ∃ (V : Opens (PrimeSpectrum.Top R)) (_ : x ∈ V) (i : V ⟶ U) (f g : R) (hg : _), const R f g V hg = (structureSheaf R).1.map i.op s := let ⟨V, hxV, iVU, f, g, hfg⟩ := s.2 ⟨x, hx⟩ ⟨V, hxV, iVU, f, g, fun y hyV => (hfg ⟨y, hyV⟩).1, Subtype.eq <| funext fun y => IsLocalization.mk'_eq_iff_eq_mul.2 <| Eq.symm <| (hfg y).2⟩ @[simp] theorem res_const (f g : R) (U hu V hv i) : (structureSheaf R).1.map i (const R f g U hu) = const R f g V hv := rfl theorem res_const' (f g : R) (V hv) : (structureSheaf R).1.map (homOfLE hv).op (const R f g (PrimeSpectrum.basicOpen g) fun _ => id) = const R f g V hv := rfl theorem const_zero (f : R) (U hu) : const R 0 f U hu = 0 := Subtype.eq <| funext fun x => IsLocalization.mk'_eq_iff_eq_mul.2 <| by rw [RingHom.map_zero] exact (mul_eq_zero_of_left rfl ((algebraMap R (Localizations R x)) _)).symm theorem const_self (f : R) (U hu) : const R f f U hu = 1 := Subtype.eq <| funext fun _ => IsLocalization.mk'_self _ _ theorem const_one (U) : (const R 1 1 U fun _ _ => Submonoid.one_mem _) = 1 := const_self R 1 U _ theorem const_add (f₁ f₂ g₁ g₂ : R) (U hu₁ hu₂) : const R f₁ g₁ U hu₁ + const R f₂ g₂ U hu₂ = const R (f₁ * g₂ + f₂ * g₁) (g₁ * g₂) U fun x hx => Submonoid.mul_mem _ (hu₁ x hx) (hu₂ x hx) := Subtype.eq <| funext fun x => Eq.symm <| IsLocalization.mk'_add _ _ ⟨g₁, hu₁ x x.2⟩ ⟨g₂, hu₂ x x.2⟩ theorem const_mul (f₁ f₂ g₁ g₂ : R) (U hu₁ hu₂) : const R f₁ g₁ U hu₁ * const R f₂ g₂ U hu₂ = const R (f₁ * f₂) (g₁ * g₂) U fun x hx => Submonoid.mul_mem _ (hu₁ x hx) (hu₂ x hx) := Subtype.eq <| funext fun x => Eq.symm <| IsLocalization.mk'_mul _ f₁ f₂ ⟨g₁, hu₁ x x.2⟩ ⟨g₂, hu₂ x x.2⟩ theorem const_ext {f₁ f₂ g₁ g₂ : R} {U hu₁ hu₂} (h : f₁ * g₂ = f₂ * g₁) : const R f₁ g₁ U hu₁ = const R f₂ g₂ U hu₂ := Subtype.eq <| funext fun x => IsLocalization.mk'_eq_of_eq (by rw [mul_comm, Subtype.coe_mk, ← h, mul_comm, Subtype.coe_mk]) theorem const_congr {f₁ f₂ g₁ g₂ : R} {U hu} (hf : f₁ = f₂) (hg : g₁ = g₂) : const R f₁ g₁ U hu = const R f₂ g₂ U (hg ▸ hu) := by substs hf hg; rfl theorem const_mul_rev (f g : R) (U hu₁ hu₂) : const R f g U hu₁ * const R g f U hu₂ = 1 := by rw [const_mul, const_congr R rfl (mul_comm g f), const_self] theorem const_mul_cancel (f g₁ g₂ : R) (U hu₁ hu₂) : const R f g₁ U hu₁ * const R g₁ g₂ U hu₂ = const R f g₂ U hu₂ := by rw [const_mul, const_ext]; rw [mul_assoc] theorem const_mul_cancel' (f g₁ g₂ : R) (U hu₁ hu₂) : const R g₁ g₂ U hu₂ * const R f g₁ U hu₁ = const R f g₂ U hu₂ := by rw [mul_comm, const_mul_cancel] /-- The canonical ring homomorphism interpreting an element of `R` as a section of the structure sheaf. -/ def toOpen (U : Opens (PrimeSpectrum.Top R)) : CommRingCat.of R ⟶ (structureSheaf R).1.obj (op U) := CommRingCat.ofHom { toFun f := ⟨fun _ => algebraMap R _ f, fun x => ⟨U, x.2, 𝟙 _, f, 1, fun y => ⟨(Ideal.ne_top_iff_one _).1 y.1.2.1, by simp [RingHom.map_one, mul_one]⟩⟩⟩ map_one' := Subtype.eq <| funext fun _ => RingHom.map_one _ map_mul' _ _ := Subtype.eq <| funext fun _ => RingHom.map_mul _ _ _ map_zero' := Subtype.eq <| funext fun _ => RingHom.map_zero _ map_add' _ _ := Subtype.eq <| funext fun _ => RingHom.map_add _ _ _ } @[simp] theorem toOpen_res (U V : Opens (PrimeSpectrum.Top R)) (i : V ⟶ U) : toOpen R U ≫ (structureSheaf R).1.map i.op = toOpen R V := rfl @[simp] theorem toOpen_apply (U : Opens (PrimeSpectrum.Top R)) (f : R) (x : U) : (toOpen R U f).1 x = algebraMap _ _ f := rfl theorem toOpen_eq_const (U : Opens (PrimeSpectrum.Top R)) (f : R) : toOpen R U f = const R f 1 U fun x _ => (Ideal.ne_top_iff_one _).1 x.2.1 := Subtype.eq <| funext fun _ => Eq.symm <| IsLocalization.mk'_one _ f /-- The canonical ring homomorphism interpreting an element of `R` as an element of the stalk of `structureSheaf R` at `x`. -/ def toStalk (x : PrimeSpectrum.Top R) : CommRingCat.of R ⟶ (structureSheaf R).presheaf.stalk x := (toOpen R ⊤ ≫ (structureSheaf R).presheaf.germ _ x (by trivial)) @[simp] theorem toOpen_germ (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) : toOpen R U ≫ (structureSheaf R).presheaf.germ U x hx = toStalk R x := by rw [← toOpen_res R ⊤ U (homOfLE le_top : U ⟶ ⊤), Category.assoc, Presheaf.germ_res]; rfl @[simp] theorem germ_toOpen (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) (f : R) : (structureSheaf R).presheaf.germ U x hx (toOpen R U f) = toStalk R x f := by rw [← toOpen_germ]; rfl theorem toOpen_Γgerm_apply (x : PrimeSpectrum.Top R) (f : R) : (structureSheaf R).presheaf.Γgerm x (toOpen R ⊤ f) = toStalk R x f := rfl theorem isUnit_to_basicOpen_self (f : R) : IsUnit (toOpen R (PrimeSpectrum.basicOpen f) f) := isUnit_of_mul_eq_one _ (const R 1 f (PrimeSpectrum.basicOpen f) fun _ => id) <| by rw [toOpen_eq_const, const_mul_rev] theorem isUnit_toStalk (x : PrimeSpectrum.Top R) (f : x.asIdeal.primeCompl) : IsUnit (toStalk R x (f : R)) := by rw [← germ_toOpen R (PrimeSpectrum.basicOpen (f : R)) x f.2 (f : R)] exact RingHom.isUnit_map _ (isUnit_to_basicOpen_self R f) /-- The canonical ring homomorphism from the localization of `R` at `p` to the stalk of the structure sheaf at the point `p`. -/ def localizationToStalk (x : PrimeSpectrum.Top R) : CommRingCat.of (Localization.AtPrime x.asIdeal) ⟶ (structureSheaf R).presheaf.stalk x := CommRingCat.ofHom <| show Localization.AtPrime x.asIdeal →+* _ from IsLocalization.lift (isUnit_toStalk R x) @[simp] theorem localizationToStalk_of (x : PrimeSpectrum.Top R) (f : R) : localizationToStalk R x (algebraMap _ (Localization _) f) = toStalk R x f := IsLocalization.lift_eq (S := Localization x.asIdeal.primeCompl) _ f @[simp] theorem localizationToStalk_mk' (x : PrimeSpectrum.Top R) (f : R) (s : x.asIdeal.primeCompl) : localizationToStalk R x (IsLocalization.mk' (Localization.AtPrime x.asIdeal) f s) = (structureSheaf R).presheaf.germ (PrimeSpectrum.basicOpen (s : R)) x s.2 (const R f s (PrimeSpectrum.basicOpen s) fun _ => id) := (IsLocalization.lift_mk'_spec (S := Localization.AtPrime x.asIdeal) _ _ _ _).2 <| by rw [← germ_toOpen R (PrimeSpectrum.basicOpen s) x s.2, ← germ_toOpen R (PrimeSpectrum.basicOpen s) x s.2, ← RingHom.map_mul, toOpen_eq_const, toOpen_eq_const, const_mul_cancel'] /-- The ring homomorphism that takes a section of the structure sheaf of `R` on the open set `U`, implemented as a subtype of dependent functions to localizations at prime ideals, and evaluates the section on the point corresponding to a given prime ideal. -/ def openToLocalization (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) : (structureSheaf R).1.obj (op U) ⟶ CommRingCat.of (Localization.AtPrime x.asIdeal) := CommRingCat.ofHom { toFun s := (s.1 ⟨x, hx⟩ :) map_one' := rfl map_mul' _ _ := rfl map_zero' := rfl map_add' _ _ := rfl } @[simp] theorem coe_openToLocalization (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) : (openToLocalization R U x hx : (structureSheaf R).1.obj (op U) → Localization.AtPrime x.asIdeal) = fun s => s.1 ⟨x, hx⟩ := rfl theorem openToLocalization_apply (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) (s : (structureSheaf R).1.obj (op U)) : openToLocalization R U x hx s = s.1 ⟨x, hx⟩ := rfl /-- The ring homomorphism from the stalk of the structure sheaf of `R` at a point corresponding to a prime ideal `p` to the localization of `R` at `p`, formed by gluing the `openToLocalization` maps. -/ def stalkToFiberRingHom (x : PrimeSpectrum.Top R) : (structureSheaf R).presheaf.stalk x ⟶ CommRingCat.of (Localization.AtPrime x.asIdeal) := Limits.colimit.desc ((OpenNhds.inclusion x).op ⋙ (structureSheaf R).1) { pt := _ ι := { app := fun U => openToLocalization R ((OpenNhds.inclusion _).obj (unop U)) x (unop U).2 } } @[simp] theorem germ_comp_stalkToFiberRingHom (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) : (structureSheaf R).presheaf.germ U x hx ≫ stalkToFiberRingHom R x = openToLocalization R U x hx := Limits.colimit.ι_desc _ _ @[simp] theorem stalkToFiberRingHom_germ (U : Opens (PrimeSpectrum.Top R)) (x : PrimeSpectrum.Top R) (hx : x ∈ U) (s : (structureSheaf R).1.obj (op U)) : stalkToFiberRingHom R x ((structureSheaf R).presheaf.germ U x hx s) = s.1 ⟨x, hx⟩ := RingHom.ext_iff.mp (CommRingCat.hom_ext_iff.mp (germ_comp_stalkToFiberRingHom R U x hx)) s @[simp] theorem toStalk_comp_stalkToFiberRingHom (x : PrimeSpectrum.Top R) : toStalk R x ≫ stalkToFiberRingHom R x = CommRingCat.ofHom (algebraMap _ _) := by rw [toStalk, Category.assoc, germ_comp_stalkToFiberRingHom]; rfl @[simp] theorem stalkToFiberRingHom_toStalk (x : PrimeSpectrum.Top R) (f : R) : stalkToFiberRingHom R x (toStalk R x f) = algebraMap _ _ f := RingHom.ext_iff.1 (CommRingCat.hom_ext_iff.mp (toStalk_comp_stalkToFiberRingHom R x)) _ /-- The ring isomorphism between the stalk of the structure sheaf of `R` at a point `p` corresponding to a prime ideal in `R` and the localization of `R` at `p`. -/ @[simps] def stalkIso (x : PrimeSpectrum.Top R) : (structureSheaf R).presheaf.stalk x ≅ CommRingCat.of (Localization.AtPrime x.asIdeal) where hom := stalkToFiberRingHom R x inv := localizationToStalk R x hom_inv_id := by apply stalk_hom_ext intro U hxU ext s dsimp only [CommRingCat.hom_comp, RingHom.coe_comp, Function.comp_apply, CommRingCat.hom_id, RingHom.coe_id, id_eq] rw [stalkToFiberRingHom_germ] obtain ⟨V, hxV, iVU, f, g, (hg : V ≤ PrimeSpectrum.basicOpen _), hs⟩ := exists_const _ _ s x hxU have := res_apply R U V iVU s ⟨x, hxV⟩ dsimp only [isLocallyFraction_pred, Opens.apply_mk] at this rw [← this, ← hs, const_apply, localizationToStalk_mk'] refine (structureSheaf R).presheaf.germ_ext V hxV (homOfLE hg) iVU ?_ rw [← hs, res_const'] inv_hom_id := CommRingCat.hom_ext <| @IsLocalization.ringHom_ext R _ x.asIdeal.primeCompl (Localization.AtPrime x.asIdeal) _ _ (Localization.AtPrime x.asIdeal) _ _ (RingHom.comp (stalkToFiberRingHom R x).hom (localizationToStalk R x).hom) (RingHom.id (Localization.AtPrime _)) <| by ext f rw [RingHom.comp_apply, RingHom.comp_apply, localizationToStalk_of, stalkToFiberRingHom_toStalk, RingHom.comp_apply, RingHom.id_apply] instance (x : PrimeSpectrum R) : IsIso (stalkToFiberRingHom R x) := (stalkIso R x).isIso_hom instance (x : PrimeSpectrum R) : IsLocalHom (stalkToFiberRingHom R x).hom := isLocalHom_of_isIso _ instance (x : PrimeSpectrum R) : IsIso (localizationToStalk R x) := (stalkIso R x).isIso_inv instance (x : PrimeSpectrum R) : IsLocalHom (localizationToStalk R x).hom := isLocalHom_of_isIso _ @[simp, reassoc] theorem stalkToFiberRingHom_localizationToStalk (x : PrimeSpectrum.Top R) : stalkToFiberRingHom R x ≫ localizationToStalk R x = 𝟙 _ := (stalkIso R x).hom_inv_id @[simp, reassoc] theorem localizationToStalk_stalkToFiberRingHom (x : PrimeSpectrum.Top R) : localizationToStalk R x ≫ stalkToFiberRingHom R x = 𝟙 _ := (stalkIso R x).inv_hom_id /-- The canonical ring homomorphism interpreting `s ∈ R_f` as a section of the structure sheaf on the basic open defined by `f ∈ R`. -/ def toBasicOpen (f : R) : Localization.Away f →+* (structureSheaf R).1.obj (op <| PrimeSpectrum.basicOpen f) := IsLocalization.Away.lift f (isUnit_to_basicOpen_self R f) @[simp] theorem toBasicOpen_mk' (s f : R) (g : Submonoid.powers s) : toBasicOpen R s (IsLocalization.mk' (Localization.Away s) f g) = const R f g (PrimeSpectrum.basicOpen s) fun _ hx => Submonoid.powers_le.2 hx g.2 := (IsLocalization.lift_mk'_spec _ _ _ _).2 <| by rw [toOpen_eq_const, toOpen_eq_const, const_mul_cancel'] @[simp] theorem localization_toBasicOpen (f : R) : RingHom.comp (toBasicOpen R f) (algebraMap R (Localization.Away f)) = (toOpen R (PrimeSpectrum.basicOpen f)).hom := RingHom.ext fun g => by rw [toBasicOpen, IsLocalization.Away.lift, RingHom.comp_apply, IsLocalization.lift_eq] @[simp] theorem toBasicOpen_to_map (s f : R) : toBasicOpen R s (algebraMap R (Localization.Away s) f) = const R f 1 (PrimeSpectrum.basicOpen s) fun _ _ => Submonoid.one_mem _ := (IsLocalization.lift_eq _ _).trans <| toOpen_eq_const _ _ _ -- The proof here follows the argument in Hartshorne's Algebraic Geometry, Proposition II.2.2. theorem toBasicOpen_injective (f : R) : Function.Injective (toBasicOpen R f) := by intro s t h_eq obtain ⟨a, ⟨b, hb⟩, rfl⟩ := IsLocalization.mk'_surjective (Submonoid.powers f) s obtain ⟨c, ⟨d, hd⟩, rfl⟩ := IsLocalization.mk'_surjective (Submonoid.powers f) t simp only [toBasicOpen_mk'] at h_eq rw [IsLocalization.eq] -- We know that the fractions `a/b` and `c/d` are equal as sections of the structure sheaf on -- `basicOpen f`. We need to show that they agree as elements in the localization of `R` at `f`. -- This amounts showing that `r * (d * a) = r * (b * c)`, for some power `r = f ^ n` of `f`. -- We define `I` as the ideal of *all* elements `r` satisfying the above equation. let I : Ideal R := { carrier := { r : R | r * (d * a) = r * (b * c) } zero_mem' := by simp only [Set.mem_setOf_eq, zero_mul] add_mem' := fun {r₁ r₂} hr₁ hr₂ => by dsimp at hr₁ hr₂ ⊢; simp only [add_mul, hr₁, hr₂] smul_mem' := fun {r₁ r₂} hr₂ => by dsimp at hr₂ ⊢; simp only [mul_assoc, hr₂] } -- Our claim now reduces to showing that `f` is contained in the radical of `I` suffices f ∈ I.radical by obtain ⟨n, hn⟩ := this exact ⟨⟨f ^ n, n, rfl⟩, hn⟩ rw [← PrimeSpectrum.vanishingIdeal_zeroLocus_eq_radical, PrimeSpectrum.mem_vanishingIdeal] intro p hfp contrapose hfp rw [PrimeSpectrum.mem_zeroLocus, Set.not_subset] have := congr_fun (congr_arg Subtype.val h_eq) ⟨p, hfp⟩ dsimp at this rw [IsLocalization.eq (S := Localization.AtPrime p.asIdeal)] at this obtain ⟨r, hr⟩ := this exact ⟨r.1, hr, r.2⟩ /- Auxiliary lemma for surjectivity of `toBasicOpen`. Every section can locally be represented on basic opens `basicOpen g` as a fraction `f/g` -/ theorem locally_const_basicOpen (U : Opens (PrimeSpectrum.Top R)) (s : (structureSheaf R).1.obj (op U)) (x : U) : ∃ (f g : R) (i : PrimeSpectrum.basicOpen g ⟶ U), x.1 ∈ PrimeSpectrum.basicOpen g ∧ (const R f g (PrimeSpectrum.basicOpen g) fun _ hy => hy) = (structureSheaf R).1.map i.op s := by -- First, any section `s` can be represented as a fraction `f/g` on some open neighborhood of `x` -- and we may pass to a `basicOpen h`, since these form a basis obtain ⟨V, hxV : x.1 ∈ V.1, iVU, f, g, hVDg : V ≤ PrimeSpectrum.basicOpen g, s_eq⟩ := exists_const R U s x.1 x.2 obtain ⟨_, ⟨h, rfl⟩, hxDh, hDhV : PrimeSpectrum.basicOpen h ≤ V⟩ := PrimeSpectrum.isTopologicalBasis_basic_opens.exists_subset_of_mem_open hxV V.2 -- The problem is of course, that `g` and `h` don't need to coincide. -- But, since `basicOpen h ≤ basicOpen g`, some power of `h` must be a multiple of `g` obtain ⟨n, hn⟩ := (PrimeSpectrum.basicOpen_le_basicOpen_iff h g).mp (Set.Subset.trans hDhV hVDg) -- Actually, we will need a *nonzero* power of `h`. -- This is because we will need the equality `basicOpen (h ^ n) = basicOpen h`, which only -- holds for a nonzero power `n`. We therefore artificially increase `n` by one. replace hn := Ideal.mul_mem_right h (Ideal.span {g}) hn rw [← pow_succ, Ideal.mem_span_singleton'] at hn obtain ⟨c, hc⟩ := hn have basic_opens_eq := PrimeSpectrum.basicOpen_pow h (n + 1) (by omega) have i_basic_open := eqToHom basic_opens_eq ≫ homOfLE hDhV -- We claim that `(f * c) / h ^ (n+1)` is our desired representation use f * c, h ^ (n + 1), i_basic_open ≫ iVU, (basic_opens_eq.symm.le :) hxDh rw [op_comp, Functor.map_comp, ConcreteCategory.comp_apply, ← s_eq, res_const] -- Note that the last rewrite here generated an additional goal, which was a parameter -- of `res_const`. We prove this goal first swap · intro y hy rw [basic_opens_eq] at hy exact (Set.Subset.trans hDhV hVDg :) hy -- All that is left is a simple calculation apply const_ext rw [mul_assoc f c g, hc] /- Auxiliary lemma for surjectivity of `toBasicOpen`. A local representation of a section `s` as fractions `a i / h i` on finitely many basic opens `basicOpen (h i)` can be "normalized" in such a way that `a i * h j = h i * a j` for all `i, j` -/ theorem normalize_finite_fraction_representation (U : Opens (PrimeSpectrum.Top R)) (s : (structureSheaf R).1.obj (op U)) {ι : Type*} (t : Finset ι) (a h : ι → R) (iDh : ∀ i : ι, PrimeSpectrum.basicOpen (h i) ⟶ U) (h_cover : U ≤ ⨆ i ∈ t, PrimeSpectrum.basicOpen (h i)) (hs : ∀ i : ι, (const R (a i) (h i) (PrimeSpectrum.basicOpen (h i)) fun _ hy => hy) = (structureSheaf R).1.map (iDh i).op s) : ∃ (a' h' : ι → R) (iDh' : ∀ i : ι, PrimeSpectrum.basicOpen (h' i) ⟶ U), (U ≤ ⨆ i ∈ t, PrimeSpectrum.basicOpen (h' i)) ∧ (∀ (i) (_ : i ∈ t) (j) (_ : j ∈ t), a' i * h' j = h' i * a' j) ∧ ∀ i ∈ t, (structureSheaf R).1.map (iDh' i).op s = const R (a' i) (h' i) (PrimeSpectrum.basicOpen (h' i)) fun _ hy => hy := by -- First we show that the fractions `(a i * h j) / (h i * h j)` and `(h i * a j) / (h i * h j)` -- coincide in the localization of `R` at `h i * h j` have fractions_eq : ∀ i j : ι, IsLocalization.mk' (Localization.Away (h i * h j)) (a i * h j) ⟨h i * h j, Submonoid.mem_powers _⟩ = IsLocalization.mk' _ (h i * a j) ⟨h i * h j, Submonoid.mem_powers _⟩ := by intro i j let D := PrimeSpectrum.basicOpen (h i * h j) let iDi : D ⟶ PrimeSpectrum.basicOpen (h i) := homOfLE (PrimeSpectrum.basicOpen_mul_le_left _ _) let iDj : D ⟶ PrimeSpectrum.basicOpen (h j) := homOfLE (PrimeSpectrum.basicOpen_mul_le_right _ _) -- Crucially, we need injectivity of `toBasicOpen` apply toBasicOpen_injective R (h i * h j) rw [toBasicOpen_mk', toBasicOpen_mk'] simp only [] -- Here, both sides of the equation are equal to a restriction of `s` trans on_goal 1 => convert congr_arg ((structureSheaf R).1.map iDj.op) (hs j).symm using 1 convert congr_arg ((structureSheaf R).1.map iDi.op) (hs i) using 1 all_goals rw [res_const]; apply const_ext; ring -- The remaining two goals were generated during the rewrite of `res_const` -- These can be solved immediately exacts [PrimeSpectrum.basicOpen_mul_le_left _ _, PrimeSpectrum.basicOpen_mul_le_right _ _] -- From the equality in the localization, we obtain for each `(i,j)` some power `(h i * h j) ^ n` -- which equalizes `a i * h j` and `h i * a j` have exists_power : ∀ i j : ι, ∃ n : ℕ, a i * h j * (h i * h j) ^ n = h i * a j * (h i * h j) ^ n := by intro i j obtain ⟨⟨c, n, rfl⟩, hc⟩ := IsLocalization.eq.mp (fractions_eq i j) use n + 1 rw [pow_succ] dsimp at hc convert hc using 1 <;> ring let n := fun p : ι × ι => (exists_power p.1 p.2).choose have n_spec := fun p : ι × ι => (exists_power p.fst p.snd).choose_spec -- We need one power `(h i * h j) ^ N` that works for *all* pairs `(i,j)` -- Since there are only finitely many indices involved, we can pick the supremum. let N := (t ×ˢ t).sup n have basic_opens_eq : ∀ i : ι, PrimeSpectrum.basicOpen (h i ^ (N + 1)) = PrimeSpectrum.basicOpen (h i) := fun i => PrimeSpectrum.basicOpen_pow _ _ (by omega) -- Expanding the fraction `a i / h i` by the power `(h i) ^ n` gives the desired normalization refine ⟨fun i => a i * h i ^ N, fun i => h i ^ (N + 1), fun i => eqToHom (basic_opens_eq i) ≫ iDh i, ?_, ?_, ?_⟩ · simpa only [basic_opens_eq] using h_cover · intro i hi j hj -- Here we need to show that our new fractions `a i / h i` satisfy the normalization condition -- Of course, the power `N` we used to expand the fractions might be bigger than the power -- `n (i, j)` which was originally chosen. We denote their difference by `k` have n_le_N : n (i, j) ≤ N := Finset.le_sup (Finset.mem_product.mpr ⟨hi, hj⟩) obtain ⟨k, hk⟩ := Nat.le.dest n_le_N simp only [← hk, pow_add, pow_one] -- To accommodate for the difference `k`, we multiply both sides of the equation `n_spec (i, j)` -- by `(h i * h j) ^ k` convert congr_arg (fun z => z * (h i * h j) ^ k) (n_spec (i, j)) using 1 <;> · simp only [n, mul_pow]; ring -- Lastly, we need to show that the new fractions still represent our original `s` intro i _ rw [op_comp, Functor.map_comp, ConcreteCategory.comp_apply, ← hs, res_const] -- additional goal spit out by `res_const` swap · exact (basic_opens_eq i).le apply const_ext dsimp rw [pow_succ] ring -- Porting note: in the following proof there are two places where `⋃ i, ⋃ (hx : i ∈ _), ... ` -- though `hx` is not used in `...` part, it is still required to maintain the structure of -- the original proof in mathlib3. set_option linter.unusedVariables false in -- The proof here follows the argument in Hartshorne's Algebraic Geometry, Proposition II.2.2. theorem toBasicOpen_surjective (f : R) : Function.Surjective (toBasicOpen R f) := by intro s -- In this proof, `basicOpen f` will play two distinct roles: Firstly, it is an open set in the -- prime spectrum. Secondly, it is used as an indexing type for various families of objects -- (open sets, ring elements, ...). In order to make the distinction clear, we introduce a type -- alias `ι` that is used whenever we want think of it as an indexing type. let ι : Type u := PrimeSpectrum.basicOpen f -- First, we pick some cover of basic opens, on which we can represent `s` as a fraction choose a' h' iDh' hxDh' s_eq' using locally_const_basicOpen R (PrimeSpectrum.basicOpen f) s -- Since basic opens are compact, we can pass to a finite subcover obtain ⟨t, ht_cover'⟩ := (PrimeSpectrum.isCompact_basicOpen f).elim_finite_subcover (fun i : ι => PrimeSpectrum.basicOpen (h' i)) (fun i => PrimeSpectrum.isOpen_basicOpen) -- Here, we need to show that our basic opens actually form a cover of `basicOpen f` fun x hx => by rw [Set.mem_iUnion]; exact ⟨⟨x, hx⟩, hxDh' ⟨x, hx⟩⟩ simp only [← Opens.coe_iSup, SetLike.coe_subset_coe] at ht_cover' -- We use the normalization lemma from above to obtain the relation `a i * h j = h i * a j` obtain ⟨a, h, iDh, ht_cover, ah_ha, s_eq⟩ := normalize_finite_fraction_representation R (PrimeSpectrum.basicOpen f) s t a' h' iDh' ht_cover' s_eq' clear s_eq' iDh' hxDh' ht_cover' a' h' simp only [← SetLike.coe_subset_coe, Opens.coe_iSup] at ht_cover replace ht_cover : (PrimeSpectrum.basicOpen f : Set <| PrimeSpectrum R) ⊆ ⋃ (i : ι) (x : i ∈ t), (PrimeSpectrum.basicOpen (h i) : Set _) := ht_cover -- Next we show that some power of `f` is a linear combination of the `h i` obtain ⟨n, hn⟩ : f ∈ (Ideal.span (h '' ↑t)).radical := by rw [← PrimeSpectrum.vanishingIdeal_zeroLocus_eq_radical, PrimeSpectrum.zeroLocus_span] simp [PrimeSpectrum.basicOpen_eq_zeroLocus_compl] at ht_cover replace ht_cover : (PrimeSpectrum.zeroLocus {f})ᶜ ⊆ ⋃ (i : ι) (x : i ∈ t), (PrimeSpectrum.zeroLocus {h i})ᶜ := ht_cover rw [Set.compl_subset_comm] at ht_cover -- Why doesn't `simp_rw` do this? simp_rw [Set.compl_iUnion, compl_compl, ← PrimeSpectrum.zeroLocus_iUnion, ← Finset.set_biUnion_coe, ← Set.image_eq_iUnion] at ht_cover apply PrimeSpectrum.vanishingIdeal_anti_mono ht_cover exact PrimeSpectrum.subset_vanishingIdeal_zeroLocus {f} (Set.mem_singleton f) replace hn := Ideal.mul_mem_right f _ hn rw [← pow_succ, Ideal.span, Finsupp.mem_span_image_iff_linearCombination] at hn rcases hn with ⟨b, b_supp, hb⟩ rw [Finsupp.linearCombination_apply_of_mem_supported R b_supp] at hb dsimp at hb -- Finally, we have all the ingredients. -- We claim that our preimage is given by `(∑ (i : ι) ∈ t, b i * a i) / f ^ (n+1)` use IsLocalization.mk' (Localization.Away f) (∑ i ∈ t, b i * a i) (⟨f ^ (n + 1), n + 1, rfl⟩ : Submonoid.powers _) rw [toBasicOpen_mk'] -- Since the structure sheaf is a sheaf, we can show the desired equality locally. -- Annoyingly, `Sheaf.eq_of_locally_eq'` requires an open cover indexed by a *type*, so we need to -- coerce our finset `t` to a type first. let tt := ((t : Set (PrimeSpectrum.basicOpen f)) : Type u) apply (structureSheaf R).eq_of_locally_eq' (fun i : tt => PrimeSpectrum.basicOpen (h i)) (PrimeSpectrum.basicOpen f) fun i : tt => iDh i · -- This feels a little redundant, since already have `ht_cover` as a hypothesis -- Unfortunately, `ht_cover` uses a bounded union over the set `t`, while here we have the -- Union indexed by the type `tt`, so we need some boilerplate to translate one to the other intro x hx rw [SetLike.mem_coe, TopologicalSpace.Opens.mem_iSup] have := ht_cover hx rw [← Finset.set_biUnion_coe, Set.mem_iUnion₂] at this rcases this with ⟨i, i_mem, x_mem⟩ exact ⟨⟨i, i_mem⟩, x_mem⟩ rintro ⟨i, hi⟩ dsimp change (structureSheaf R).1.map (iDh i).op _ = (structureSheaf R).1.map (iDh i).op _ rw [s_eq i hi, res_const] -- Again, `res_const` spits out an additional goal swap · intro y hy change y ∈ PrimeSpectrum.basicOpen (f ^ (n + 1)) rw [PrimeSpectrum.basicOpen_pow f (n + 1) (by omega)] exact (leOfHom (iDh i) :) hy -- The rest of the proof is just computation apply const_ext rw [← hb, Finset.sum_mul, Finset.mul_sum] apply Finset.sum_congr rfl intro j hj rw [mul_assoc, ah_ha j hj i hi] ring instance isIso_toBasicOpen (f : R) : IsIso (CommRingCat.ofHom (toBasicOpen R f)) := haveI : IsIso ((forget CommRingCat).map (CommRingCat.ofHom (toBasicOpen R f))) := (isIso_iff_bijective _).mpr ⟨toBasicOpen_injective R f, toBasicOpen_surjective R f⟩ isIso_of_reflects_iso _ (forget CommRingCat) /-- The ring isomorphism between the structure sheaf on `basicOpen f` and the localization of `R` at the submonoid of powers of `f`. -/ def basicOpenIso (f : R) : (structureSheaf R).1.obj (op (PrimeSpectrum.basicOpen f)) ≅ CommRingCat.of (Localization.Away f) := (asIso (CommRingCat.ofHom (toBasicOpen R f))).symm instance stalkAlgebra (p : PrimeSpectrum R) : Algebra R ((structureSheaf R).presheaf.stalk p) := (toStalk R p).hom.toAlgebra @[simp] theorem stalkAlgebra_map (p : PrimeSpectrum R) (r : R) : algebraMap R ((structureSheaf R).presheaf.stalk p) r = toStalk R p r := rfl /-- Stalk of the structure sheaf at a prime p as localization of R -/ instance IsLocalization.to_stalk (p : PrimeSpectrum R) : IsLocalization.AtPrime ((structureSheaf R).presheaf.stalk p) p.asIdeal := by convert (IsLocalization.isLocalization_iff_of_ringEquiv (S := Localization.AtPrime p.asIdeal) _ (stalkIso R p).symm.commRingCatIsoToRingEquiv).mp Localization.isLocalization apply Algebra.algebra_ext intro rw [stalkAlgebra_map] congr 2 change toStalk R p = _ ≫ (stalkIso R p).inv rw [Iso.eq_comp_inv] exact toStalk_comp_stalkToFiberRingHom R p instance openAlgebra (U : (Opens (PrimeSpectrum R))ᵒᵖ) : Algebra R ((structureSheaf R).val.obj U) := (toOpen R (unop U)).hom.toAlgebra @[simp] theorem openAlgebra_map (U : (Opens (PrimeSpectrum R))ᵒᵖ) (r : R) : algebraMap R ((structureSheaf R).val.obj U) r = toOpen R (unop U) r := rfl /-- Sections of the structure sheaf of Spec R on a basic open as localization of R -/ instance IsLocalization.to_basicOpen (r : R) : IsLocalization.Away r ((structureSheaf R).val.obj (op <| PrimeSpectrum.basicOpen r)) := by convert (IsLocalization.isLocalization_iff_of_ringEquiv (S := Localization.Away r) _ (basicOpenIso R r).symm.commRingCatIsoToRingEquiv).mp Localization.isLocalization apply Algebra.algebra_ext intro x congr 1 exact (localization_toBasicOpen R r).symm instance to_basicOpen_epi (r : R) : Epi (toOpen R (PrimeSpectrum.basicOpen r)) := ⟨fun _ _ h => CommRingCat.hom_ext (IsLocalization.ringHom_ext (Submonoid.powers r) (CommRingCat.hom_ext_iff.mp h))⟩ @[elementwise] theorem to_global_factors : toOpen R ⊤ = CommRingCat.ofHom (algebraMap R (Localization.Away (1 : R))) ≫ CommRingCat.ofHom (toBasicOpen R (1 : R)) ≫ (structureSheaf R).1.map (eqToHom PrimeSpectrum.basicOpen_one.symm).op := by rw [← Category.assoc] change toOpen R ⊤ = (CommRingCat.ofHom <| (toBasicOpen R 1).comp (algebraMap R (Localization.Away 1))) ≫ (structureSheaf R).1.map (eqToHom _).op rw [localization_toBasicOpen R, CommRingCat.ofHom_hom, toOpen_res] instance isIso_to_global : IsIso (toOpen R ⊤) := by let hom := CommRingCat.ofHom (algebraMap R (Localization.Away (1 : R))) haveI : IsIso hom := (IsLocalization.atOne R (Localization.Away (1 : R))).toRingEquiv.toCommRingCatIso.isIso_hom rw [to_global_factors R] infer_instance /-- The ring isomorphism between the ring `R` and the global sections `Γ(X, 𝒪ₓ)`. -/ @[simps! inv] def globalSectionsIso : CommRingCat.of R ≅ (structureSheaf R).1.obj (op ⊤) := asIso (toOpen R ⊤) @[simp] theorem globalSectionsIso_hom (R : CommRingCat) : (globalSectionsIso R).hom = toOpen R ⊤ := rfl @[simp, reassoc, elementwise nosimp] theorem toStalk_stalkSpecializes {R : Type*} [CommRing R] {x y : PrimeSpectrum R} (h : x ⤳ y) : toStalk R y ≫ (structureSheaf R).presheaf.stalkSpecializes h = toStalk R x := by dsimp [toStalk]; simp [-toOpen_germ] @[simp, reassoc, elementwise nosimp] theorem localizationToStalk_stalkSpecializes {R : Type*} [CommRing R] {x y : PrimeSpectrum R} (h : x ⤳ y) : StructureSheaf.localizationToStalk R y ≫ (structureSheaf R).presheaf.stalkSpecializes h = CommRingCat.ofHom (PrimeSpectrum.localizationMapOfSpecializes h) ≫ StructureSheaf.localizationToStalk R x := by ext : 1 apply IsLocalization.ringHom_ext (S := Localization.AtPrime y.asIdeal) y.asIdeal.primeCompl rw [CommRingCat.hom_comp, RingHom.comp_assoc, CommRingCat.hom_comp, RingHom.comp_assoc] dsimp [localizationToStalk, PrimeSpectrum.localizationMapOfSpecializes] rw [IsLocalization.lift_comp, IsLocalization.lift_comp, IsLocalization.lift_comp] exact CommRingCat.hom_ext_iff.mp (toStalk_stalkSpecializes h) @[simp, reassoc, elementwise nosimp] theorem stalkSpecializes_stalk_to_fiber {R : Type*} [CommRing R] {x y : PrimeSpectrum R} (h : x ⤳ y) : (structureSheaf R).presheaf.stalkSpecializes h ≫ StructureSheaf.stalkToFiberRingHom R x = StructureSheaf.stalkToFiberRingHom R y ≫ (CommRingCat.ofHom (PrimeSpectrum.localizationMapOfSpecializes h)) := by change _ ≫ (StructureSheaf.stalkIso R x).hom = (StructureSheaf.stalkIso R y).hom ≫ _ rw [← Iso.eq_comp_inv, Category.assoc, ← Iso.inv_comp_eq] exact localizationToStalk_stalkSpecializes h section Comap variable {R} {S : Type u} [CommRing S] {P : Type u} [CommRing P] /-- Given a ring homomorphism `f : R →+* S`, an open set `U` of the prime spectrum of `R` and an open set `V` of the prime spectrum of `S`, such that `V ⊆ (comap f) ⁻¹' U`, we can push a section `s` on `U` to a section on `V`, by composing with `Localization.localRingHom _ _ f` from the left and `comap f` from the right. Explicitly, if `s` evaluates on `comap f p` to `a / b`, its image on `V` evaluates on `p` to `f(a) / f(b)`. At the moment, we work with arbitrary dependent functions `s : Π x : U, Localizations R x`. Below, we prove the predicate `isLocallyFraction` is preserved by this map, hence it can be extended to a morphism between the structure sheaves of `R` and `S`. -/ def comapFun (f : R →+* S) (U : Opens (PrimeSpectrum.Top R)) (V : Opens (PrimeSpectrum.Top S)) (hUV : V.1 ⊆ PrimeSpectrum.comap f ⁻¹' U.1) (s : ∀ x : U, Localizations R x) (y : V) : Localizations S y := Localization.localRingHom (PrimeSpectrum.comap f y.1).asIdeal _ f rfl (s ⟨PrimeSpectrum.comap f y.1, hUV y.2⟩ :) theorem comapFunIsLocallyFraction (f : R →+* S) (U : Opens (PrimeSpectrum.Top R)) (V : Opens (PrimeSpectrum.Top S)) (hUV : V.1 ⊆ PrimeSpectrum.comap f ⁻¹' U.1) (s : ∀ x : U, Localizations R x) (hs : (isLocallyFraction R).toPrelocalPredicate.pred s) : (isLocallyFraction S).toPrelocalPredicate.pred (comapFun f U V hUV s) := by rintro ⟨p, hpV⟩ -- Since `s` is locally fraction, we can find a neighborhood `W` of `PrimeSpectrum.comap f p` -- in `U`, such that `s = a / b` on `W`, for some ring elements `a, b : R`. rcases hs ⟨PrimeSpectrum.comap f p, hUV hpV⟩ with ⟨W, m, iWU, a, b, h_frac⟩ -- We claim that we can write our new section as the fraction `f a / f b` on the neighborhood -- `(comap f) ⁻¹ W ⊓ V` of `p`. refine ⟨Opens.comap (PrimeSpectrum.comap f) W ⊓ V, ⟨m, hpV⟩, Opens.infLERight _ _, f a, f b, ?_⟩ rintro ⟨q, ⟨hqW, hqV⟩⟩ specialize h_frac ⟨PrimeSpectrum.comap f q, hqW⟩ refine ⟨h_frac.1, ?_⟩ dsimp only [comapFun] erw [← Localization.localRingHom_to_map (PrimeSpectrum.comap f q).asIdeal, ← RingHom.map_mul, h_frac.2, Localization.localRingHom_to_map] rfl /-- For a ring homomorphism `f : R →+* S` and open sets `U` and `V` of the prime spectra of `R` and `S` such that `V ⊆ (comap f) ⁻¹ U`, the induced ring homomorphism from the structure sheaf of `R` at `U` to the structure sheaf of `S` at `V`. Explicitly, this map is given as follows: For a point `p : V`, if the section `s` evaluates on `p` to the fraction `a / b`, its image on `V` evaluates on `p` to the fraction `f(a) / f(b)`. -/ def comap (f : R →+* S) (U : Opens (PrimeSpectrum.Top R)) (V : Opens (PrimeSpectrum.Top S)) (hUV : V.1 ⊆ PrimeSpectrum.comap f ⁻¹' U.1) : (structureSheaf R).1.obj (op U) →+* (structureSheaf S).1.obj (op V) where toFun s := ⟨comapFun f U V hUV s.1, comapFunIsLocallyFraction f U V hUV s.1 s.2⟩ map_one' := Subtype.ext <| funext fun p => by dsimp rw [comapFun, (sectionsSubring R (op U)).coe_one, Pi.one_apply, RingHom.map_one] rfl map_zero' := Subtype.ext <| funext fun p => by dsimp rw [comapFun, (sectionsSubring R (op U)).coe_zero, Pi.zero_apply, RingHom.map_zero] rfl map_add' s t := Subtype.ext <| funext fun p => by dsimp rw [comapFun, (sectionsSubring R (op U)).coe_add, Pi.add_apply, RingHom.map_add] rfl map_mul' s t := Subtype.ext <| funext fun p => by dsimp rw [comapFun, (sectionsSubring R (op U)).coe_mul, Pi.mul_apply, RingHom.map_mul] rfl @[simp] theorem comap_apply (f : R →+* S) (U : Opens (PrimeSpectrum.Top R)) (V : Opens (PrimeSpectrum.Top S)) (hUV : V.1 ⊆ PrimeSpectrum.comap f ⁻¹' U.1) (s : (structureSheaf R).1.obj (op U)) (p : V) : (comap f U V hUV s).1 p = Localization.localRingHom (PrimeSpectrum.comap f p.1).asIdeal _ f rfl (s.1 ⟨PrimeSpectrum.comap f p.1, hUV p.2⟩ :) := rfl theorem comap_const (f : R →+* S) (U : Opens (PrimeSpectrum.Top R)) (V : Opens (PrimeSpectrum.Top S)) (hUV : V.1 ⊆ PrimeSpectrum.comap f ⁻¹' U.1) (a b : R) (hb : ∀ x : PrimeSpectrum R, x ∈ U → b ∈ x.asIdeal.primeCompl) : comap f U V hUV (const R a b U hb) = const S (f a) (f b) V fun p hpV => hb (PrimeSpectrum.comap f p) (hUV hpV) := Subtype.eq <| funext fun p => by rw [comap_apply, const_apply, const_apply, Localization.localRingHom_mk'] /-- For an inclusion `i : V ⟶ U` between open sets of the prime spectrum of `R`, the comap of the identity from OO_X(U) to OO_X(V) equals as the restriction map of the structure sheaf. This is a generalization of the fact that, for fixed `U`, the comap of the identity from OO_X(U) to OO_X(U) is the identity. -/
theorem comap_id_eq_map (U V : Opens (PrimeSpectrum.Top R)) (iVU : V ⟶ U) : (comap (RingHom.id R) U V fun _ hpV => leOfHom iVU <| hpV) = ((structureSheaf R).1.map iVU.op).hom := RingHom.ext fun s => Subtype.eq <| funext fun p => by rw [comap_apply] -- Unfortunately, we cannot use `Localization.localRingHom_id` here, because -- `PrimeSpectrum.comap (RingHom.id R) p` is not *definitionally* equal to `p`. Instead, we use -- that we can write `s` as a fraction `a/b` in a small neighborhood around `p`. Since -- `PrimeSpectrum.comap (RingHom.id R) p` equals `p`, it is also contained in the same -- neighborhood, hence `s` equals `a/b` there too. obtain ⟨W, hpW, iWU, h⟩ := s.2 (iVU p) obtain ⟨a, b, h'⟩ := h.eq_mk' obtain ⟨hb₁, s_eq₁⟩ := h' ⟨p, hpW⟩
Mathlib/AlgebraicGeometry/StructureSheaf.lean
1,043
1,055
/- Copyright (c) 2019 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Jakob von Raumer -/ import Mathlib.CategoryTheory.Limits.Shapes.FiniteProducts import Mathlib.CategoryTheory.Limits.Shapes.Kernels /-! # Biproducts and binary biproducts We introduce the notion of (finite) biproducts. Binary biproducts are defined in `CategoryTheory.Limits.Shapes.BinaryBiproducts`. These are slightly unusual relative to the other shapes in the library, as they are simultaneously limits and colimits. (Zero objects are similar; they are "biterminal".) For results about biproducts in preadditive categories see `CategoryTheory.Preadditive.Biproducts`. For biproducts indexed by a `Fintype J`, a `bicone` consists of a cone point `X` and morphisms `π j : X ⟶ F j` and `ι j : F j ⟶ X` for each `j`, such that `ι j ≫ π j'` is the identity when `j = j'` and zero otherwise. ## Notation As `⊕` is already taken for the sum of types, we introduce the notation `X ⊞ Y` for a binary biproduct. We introduce `⨁ f` for the indexed biproduct. ## Implementation notes Prior to https://github.com/leanprover-community/mathlib3/pull/14046, `HasFiniteBiproducts` required a `DecidableEq` instance on the indexing type. As this had no pay-off (everything about limits is non-constructive in mathlib), and occasional cost (constructing decidability instances appropriate for constructions involving the indexing type), we made everything classical. -/ noncomputable section universe w w' v u open CategoryTheory Functor namespace CategoryTheory.Limits variable {J : Type w} universe uC' uC uD' uD variable {C : Type uC} [Category.{uC'} C] [HasZeroMorphisms C] variable {D : Type uD} [Category.{uD'} D] [HasZeroMorphisms D] open scoped Classical in /-- A `c : Bicone F` is: * an object `c.pt` and * morphisms `π j : pt ⟶ F j` and `ι j : F j ⟶ pt` for each `j`, * such that `ι j ≫ π j'` is the identity when `j = j'` and zero otherwise. -/ structure Bicone (F : J → C) where pt : C π : ∀ j, pt ⟶ F j ι : ∀ j, F j ⟶ pt ι_π : ∀ j j', ι j ≫ π j' = if h : j = j' then eqToHom (congrArg F h) else 0 := by aesop attribute [inherit_doc Bicone] Bicone.pt Bicone.π Bicone.ι Bicone.ι_π @[reassoc (attr := simp)] theorem bicone_ι_π_self {F : J → C} (B : Bicone F) (j : J) : B.ι j ≫ B.π j = 𝟙 (F j) := by simpa using B.ι_π j j @[reassoc (attr := simp)] theorem bicone_ι_π_ne {F : J → C} (B : Bicone F) {j j' : J} (h : j ≠ j') : B.ι j ≫ B.π j' = 0 := by simpa [h] using B.ι_π j j' variable {F : J → C} /-- A bicone morphism between two bicones for the same diagram is a morphism of the bicone points which commutes with the cone and cocone legs. -/ structure BiconeMorphism {F : J → C} (A B : Bicone F) where /-- A morphism between the two vertex objects of the bicones -/ hom : A.pt ⟶ B.pt /-- The triangle consisting of the two natural transformations and `hom` commutes -/ wπ : ∀ j : J, hom ≫ B.π j = A.π j := by aesop_cat /-- The triangle consisting of the two natural transformations and `hom` commutes -/ wι : ∀ j : J, A.ι j ≫ hom = B.ι j := by aesop_cat attribute [reassoc (attr := simp)] BiconeMorphism.wι BiconeMorphism.wπ /-- The category of bicones on a given diagram. -/ @[simps] instance Bicone.category : Category (Bicone F) where Hom A B := BiconeMorphism A B comp f g := { hom := f.hom ≫ g.hom } id B := { hom := 𝟙 B.pt } -- Porting note: if we do not have `simps` automatically generate the lemma for simplifying -- the `hom` field of a category, we need to write the `ext` lemma in terms of the categorical -- morphism, rather than the underlying structure. @[ext] theorem BiconeMorphism.ext {c c' : Bicone F} (f g : c ⟶ c') (w : f.hom = g.hom) : f = g := by cases f cases g congr namespace Bicones /-- To give an isomorphism between cocones, it suffices to give an isomorphism between their vertices which commutes with the cocone maps. -/ @[aesop apply safe (rule_sets := [CategoryTheory]), simps] def ext {c c' : Bicone F} (φ : c.pt ≅ c'.pt) (wι : ∀ j, c.ι j ≫ φ.hom = c'.ι j := by aesop_cat) (wπ : ∀ j, φ.hom ≫ c'.π j = c.π j := by aesop_cat) : c ≅ c' where hom := { hom := φ.hom } inv := { hom := φ.inv wι := fun j => φ.comp_inv_eq.mpr (wι j).symm wπ := fun j => φ.inv_comp_eq.mpr (wπ j).symm } variable (F) in /-- A functor `G : C ⥤ D` sends bicones over `F` to bicones over `G.obj ∘ F` functorially. -/ @[simps] def functoriality (G : C ⥤ D) [Functor.PreservesZeroMorphisms G] : Bicone F ⥤ Bicone (G.obj ∘ F) where obj A := { pt := G.obj A.pt π := fun j => G.map (A.π j) ι := fun j => G.map (A.ι j) ι_π := fun i j => (Functor.map_comp _ _ _).symm.trans <| by rw [A.ι_π] aesop_cat } map f := { hom := G.map f.hom wπ := fun j => by simp [-BiconeMorphism.wπ, ← f.wπ j] wι := fun j => by simp [-BiconeMorphism.wι, ← f.wι j] } variable (G : C ⥤ D) instance functoriality_full [G.PreservesZeroMorphisms] [G.Full] [G.Faithful] : (functoriality F G).Full where map_surjective t := ⟨{ hom := G.preimage t.hom wι := fun j => G.map_injective (by simpa using t.wι j) wπ := fun j => G.map_injective (by simpa using t.wπ j) }, by aesop_cat⟩ instance functoriality_faithful [G.PreservesZeroMorphisms] [G.Faithful] : (functoriality F G).Faithful where map_injective {_X} {_Y} f g h := BiconeMorphism.ext f g <| G.map_injective <| congr_arg BiconeMorphism.hom h end Bicones namespace Bicone attribute [local aesop safe tactic (rule_sets := [CategoryTheory])] CategoryTheory.Discrete.discreteCases -- Porting note: would it be okay to use this more generally? attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Eq /-- Extract the cone from a bicone. -/ def toConeFunctor : Bicone F ⥤ Cone (Discrete.functor F) where obj B := { pt := B.pt, π := { app := fun j => B.π j.as } } map {_ _} F := { hom := F.hom, w := fun _ => F.wπ _ } /-- A shorthand for `toConeFunctor.obj` -/ abbrev toCone (B : Bicone F) : Cone (Discrete.functor F) := toConeFunctor.obj B -- TODO Consider changing this API to `toFan (B : Bicone F) : Fan F`. @[simp] theorem toCone_pt (B : Bicone F) : B.toCone.pt = B.pt := rfl @[simp] theorem toCone_π_app (B : Bicone F) (j : Discrete J) : B.toCone.π.app j = B.π j.as := rfl theorem toCone_π_app_mk (B : Bicone F) (j : J) : B.toCone.π.app ⟨j⟩ = B.π j := rfl @[simp] theorem toCone_proj (B : Bicone F) (j : J) : Fan.proj B.toCone j = B.π j := rfl /-- Extract the cocone from a bicone. -/ def toCoconeFunctor : Bicone F ⥤ Cocone (Discrete.functor F) where obj B := { pt := B.pt, ι := { app := fun j => B.ι j.as } } map {_ _} F := { hom := F.hom, w := fun _ => F.wι _ } /-- A shorthand for `toCoconeFunctor.obj` -/ abbrev toCocone (B : Bicone F) : Cocone (Discrete.functor F) := toCoconeFunctor.obj B @[simp] theorem toCocone_pt (B : Bicone F) : B.toCocone.pt = B.pt := rfl @[simp] theorem toCocone_ι_app (B : Bicone F) (j : Discrete J) : B.toCocone.ι.app j = B.ι j.as := rfl @[simp] theorem toCocone_inj (B : Bicone F) (j : J) : Cofan.inj B.toCocone j = B.ι j := rfl theorem toCocone_ι_app_mk (B : Bicone F) (j : J) : B.toCocone.ι.app ⟨j⟩ = B.ι j := rfl open scoped Classical in /-- We can turn any limit cone over a discrete collection of objects into a bicone. -/ @[simps] def ofLimitCone {f : J → C} {t : Cone (Discrete.functor f)} (ht : IsLimit t) : Bicone f where pt := t.pt π j := t.π.app ⟨j⟩ ι j := ht.lift (Fan.mk _ fun j' => if h : j = j' then eqToHom (congr_arg f h) else 0) ι_π j j' := by simp open scoped Classical in theorem ι_of_isLimit {f : J → C} {t : Bicone f} (ht : IsLimit t.toCone) (j : J) : t.ι j = ht.lift (Fan.mk _ fun j' => if h : j = j' then eqToHom (congr_arg f h) else 0) := ht.hom_ext fun j' => by rw [ht.fac] simp [t.ι_π] open scoped Classical in /-- We can turn any colimit cocone over a discrete collection of objects into a bicone. -/ @[simps] def ofColimitCocone {f : J → C} {t : Cocone (Discrete.functor f)} (ht : IsColimit t) : Bicone f where pt := t.pt π j := ht.desc (Cofan.mk _ fun j' => if h : j' = j then eqToHom (congr_arg f h) else 0) ι j := t.ι.app ⟨j⟩ ι_π j j' := by simp open scoped Classical in theorem π_of_isColimit {f : J → C} {t : Bicone f} (ht : IsColimit t.toCocone) (j : J) : t.π j = ht.desc (Cofan.mk _ fun j' => if h : j' = j then eqToHom (congr_arg f h) else 0) := ht.hom_ext fun j' => by rw [ht.fac] simp [t.ι_π] /-- Structure witnessing that a bicone is both a limit cone and a colimit cocone. -/ structure IsBilimit {F : J → C} (B : Bicone F) where isLimit : IsLimit B.toCone isColimit : IsColimit B.toCocone attribute [inherit_doc IsBilimit] IsBilimit.isLimit IsBilimit.isColimit attribute [simp] IsBilimit.mk.injEq attribute [local ext] Bicone.IsBilimit instance subsingleton_isBilimit {f : J → C} {c : Bicone f} : Subsingleton c.IsBilimit := ⟨fun _ _ => Bicone.IsBilimit.ext (Subsingleton.elim _ _) (Subsingleton.elim _ _)⟩
section Whisker variable {K : Type w'}
Mathlib/CategoryTheory/Limits/Shapes/Biproducts.lean
242
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/- Copyright (c) 2020 Anatole Dedecker. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anatole Dedecker, Alexey Soloyev, Junyan Xu, Kamila Szewczyk -/ import Mathlib.Algebra.EuclideanDomain.Basic import Mathlib.Algebra.LinearRecurrence import Mathlib.Data.Fin.VecNotation import Mathlib.Data.Nat.Fib.Basic import Mathlib.Data.Real.Irrational import Mathlib.Tactic.NormNum.NatFib import Mathlib.Tactic.NormNum.Prime /-! # The golden ratio and its conjugate This file defines the golden ratio `φ := (1 + √5)/2` and its conjugate `ψ := (1 - √5)/2`, which are the two real roots of `X² - X - 1`. Along with various computational facts about them, we prove their irrationality, and we link them to the Fibonacci sequence by proving Binet's formula. -/ noncomputable section open Polynomial /-- The golden ratio `φ := (1 + √5)/2`. -/ abbrev goldenRatio : ℝ := (1 + √5) / 2 /-- The conjugate of the golden ratio `ψ := (1 - √5)/2`. -/ abbrev goldenConj : ℝ := (1 - √5) / 2 @[inherit_doc goldenRatio] scoped[goldenRatio] notation "φ" => goldenRatio @[inherit_doc goldenConj] scoped[goldenRatio] notation "ψ" => goldenConj open Real goldenRatio /-- The inverse of the golden ratio is the opposite of its conjugate. -/ theorem inv_gold : φ⁻¹ = -ψ := by have : 1 + √5 ≠ 0 := ne_of_gt (add_pos (by norm_num) <| Real.sqrt_pos.mpr (by norm_num)) field_simp [sub_mul, mul_add] norm_num /-- The opposite of the golden ratio is the inverse of its conjugate. -/ theorem inv_goldConj : ψ⁻¹ = -φ := by rw [inv_eq_iff_eq_inv, ← neg_inv, ← neg_eq_iff_eq_neg] exact inv_gold.symm @[simp] theorem gold_mul_goldConj : φ * ψ = -1 := by field_simp rw [← sq_sub_sq] norm_num @[simp] theorem goldConj_mul_gold : ψ * φ = -1 := by rw [mul_comm] exact gold_mul_goldConj @[simp] theorem gold_add_goldConj : φ + ψ = 1 := by rw [goldenRatio, goldenConj] ring theorem one_sub_goldConj : 1 - φ = ψ := by linarith [gold_add_goldConj] theorem one_sub_gold : 1 - ψ = φ := by linarith [gold_add_goldConj] @[simp] theorem gold_sub_goldConj : φ - ψ = √5 := by ring theorem gold_pow_sub_gold_pow (n : ℕ) : φ ^ (n + 2) - φ ^ (n + 1) = φ ^ n := by rw [goldenRatio]; ring_nf; norm_num; ring @[simp 1200] theorem gold_sq : φ ^ 2 = φ + 1 := by rw [goldenRatio, ← sub_eq_zero] ring_nf rw [Real.sq_sqrt] <;> norm_num @[simp 1200] theorem goldConj_sq : ψ ^ 2 = ψ + 1 := by rw [goldenConj, ← sub_eq_zero] ring_nf rw [Real.sq_sqrt] <;> norm_num theorem gold_pos : 0 < φ := mul_pos (by apply add_pos <;> norm_num) <| inv_pos.2 zero_lt_two theorem gold_ne_zero : φ ≠ 0 := ne_of_gt gold_pos theorem one_lt_gold : 1 < φ := by refine lt_of_mul_lt_mul_left ?_ (le_of_lt gold_pos) simp [← sq, gold_pos, zero_lt_one] theorem gold_lt_two : φ < 2 := by calc (1 + sqrt 5) / 2 < (1 + 3) / 2 := by gcongr; rw [sqrt_lt'] <;> norm_num _ = 2 := by norm_num theorem goldConj_neg : ψ < 0 := by linarith [one_sub_goldConj, one_lt_gold] theorem goldConj_ne_zero : ψ ≠ 0 := ne_of_lt goldConj_neg theorem neg_one_lt_goldConj : -1 < ψ := by rw [neg_lt, ← inv_gold] exact inv_lt_one_of_one_lt₀ one_lt_gold /-! ## Irrationality -/ /-- The golden ratio is irrational. -/ theorem gold_irrational : Irrational φ := by have := Nat.Prime.irrational_sqrt (show Nat.Prime 5 by norm_num) have := this.ratCast_add 1 convert this.ratCast_mul (show (0.5 : ℚ) ≠ 0 by norm_num) norm_num field_simp /-- The conjugate of the golden ratio is irrational. -/
theorem goldConj_irrational : Irrational ψ := by have := Nat.Prime.irrational_sqrt (show Nat.Prime 5 by norm_num) have := this.ratCast_sub 1
Mathlib/Data/Real/GoldenRatio.lean
129
131
/- Copyright (c) 2015 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro -/ import Mathlib.Data.Finset.Attach import Mathlib.Data.Finset.Disjoint import Mathlib.Data.Finset.Erase import Mathlib.Data.Finset.Filter import Mathlib.Data.Finset.Range import Mathlib.Data.Finset.SDiff import Mathlib.Data.Multiset.Basic import Mathlib.Logic.Equiv.Set import Mathlib.Order.Directed import Mathlib.Order.Interval.Set.Defs import Mathlib.Data.Set.SymmDiff /-! # Basic lemmas on finite sets This file contains lemmas on the interaction of various definitions on the `Finset` type. For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`. ## Main declarations ### Main definitions * `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate. ### Equivalences between finsets * The `Mathlib/Logic/Equiv/Defs.lean` file describes a general type of equivalence, so look in there for any lemmas. There is some API for rewriting sums and products from `s` to `t` given that `s ≃ t`. TODO: examples ## Tags finite sets, finset -/ -- Assert that we define `Finset` without the material on `List.sublists`. -- Note that we cannot use `List.sublists` itself as that is defined very early. assert_not_exists List.sublistsLen Multiset.powerset CompleteLattice Monoid open Multiset Subtype Function universe u variable {α : Type*} {β : Type*} {γ : Type*} namespace Finset -- TODO: these should be global attributes, but this will require fixing other files attribute [local trans] Subset.trans Superset.trans set_option linter.deprecated false in @[deprecated "Deprecated without replacement." (since := "2025-02-07")] theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) : SizeOf.sizeOf x < SizeOf.sizeOf s := by cases s dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf] rw [Nat.add_comm] refine lt_trans ?_ (Nat.lt_succ_self _) exact Multiset.sizeOf_lt_sizeOf_of_mem hx /-! ### Lattice structure -/ section Lattice variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α} /-! #### union -/ @[simp] theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t := ext fun a => by simp @[simp] theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by simp only [disjoint_left, mem_union, or_imp, forall_and] @[simp] theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by simp only [disjoint_right, mem_union, or_imp, forall_and] /-! #### inter -/ theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty := not_disjoint_iff.trans <| by simp [Finset.Nonempty] alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by rw [← not_disjoint_iff_nonempty_inter] exact em _ omit [DecidableEq α] in theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) : Disjoint s t ↔ s = ∅ := disjoint_of_le_iff_left_eq_bot h lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} : s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _), not_disjoint_iff_nonempty_inter] end Lattice instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le /-! ### erase -/ section Erase variable [DecidableEq α] {s t u v : Finset α} {a b : α} @[simp] theorem erase_empty (a : α) : erase ∅ a = ∅ := rfl protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty := (hs.exists_ne a).imp <| by aesop @[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)] refine ⟨?_, fun hs ↦ hs.exists_ne a⟩ rintro ⟨b, hb, hba⟩ exact ⟨_, hb, _, ha, hba⟩ @[simp] theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by ext x simp @[simp] theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a := ext fun x => by simp +contextual only [mem_erase, mem_insert, and_congr_right_iff, false_or, iff_self, imp_true_iff] theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by rw [erase_insert_eq_erase, erase_eq_of_not_mem h] theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) : erase (insert a s) b = insert a (erase s b) := ext fun x => by have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h simp only [mem_erase, mem_insert, and_or_left, this] theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) : erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by simp only [cons_eq_insert, erase_insert_of_ne hb] @[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s := ext fun x => by simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and] apply or_iff_right_of_imp rintro rfl exact h lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by aesop lemma insert_erase_invOn : Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} := ⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩ theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s := calc s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _ _ = _ := insert_erase h theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩ obtain ⟨a, ht, hs⟩ := not_subset.1 h.2 exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩ theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s := ssubset_iff_exists_subset_erase.2 ⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩ theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h] theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp] exact forall_congr' fun x => forall_swap theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s := subset_insert_iff.1 <| Subset.rfl theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) := subset_insert_iff.2 <| Subset.rfl theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by rw [subset_insert_iff, erase_eq_of_not_mem h] theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by rw [← subset_insert_iff, insert_eq_of_mem h] theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a := fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h] end Erase lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) : ∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by classical obtain ⟨a, ha, b, hb, hab⟩ := hs have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩ refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;> simp [insert_erase this, insert_erase ha, *] /-! ### sdiff -/ section Sdiff variable [DecidableEq α] {s t u v : Finset α} {a b : α} lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by ext; aesop -- TODO: Do we want to delete this lemma and `Finset.disjUnion_singleton`, -- or instead add `Finset.union_singleton`/`Finset.singleton_union`? theorem sdiff_singleton_eq_erase (a : α) (s : Finset α) : s \ {a} = erase s a := by ext rw [mem_erase, mem_sdiff, mem_singleton, and_comm] -- This lemma matches `Finset.insert_eq` in functionality. theorem erase_eq (s : Finset α) (a : α) : s.erase a = s \ {a} := (sdiff_singleton_eq_erase _ _).symm theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by simp_rw [erase_eq, disjoint_sdiff_comm] lemma disjoint_insert_erase (ha : a ∉ t) : Disjoint (s.erase a) (insert a t) ↔ Disjoint s t := by rw [disjoint_erase_comm, erase_insert ha] lemma disjoint_erase_insert (ha : a ∉ s) : Disjoint (insert a s) (t.erase a) ↔ Disjoint s t := by rw [← disjoint_erase_comm, erase_insert ha] theorem disjoint_of_erase_left (ha : a ∉ t) (hst : Disjoint (s.erase a) t) : Disjoint s t := by rw [← erase_insert ha, ← disjoint_erase_comm, disjoint_insert_right] exact ⟨not_mem_erase _ _, hst⟩ theorem disjoint_of_erase_right (ha : a ∉ s) (hst : Disjoint s (t.erase a)) : Disjoint s t := by rw [← erase_insert ha, disjoint_erase_comm, disjoint_insert_left] exact ⟨not_mem_erase _ _, hst⟩ theorem inter_erase (a : α) (s t : Finset α) : s ∩ t.erase a = (s ∩ t).erase a := by simp only [erase_eq, inter_sdiff_assoc] @[simp] theorem erase_inter (a : α) (s t : Finset α) : s.erase a ∩ t = (s ∩ t).erase a := by simpa only [inter_comm t] using inter_erase a t s theorem erase_sdiff_comm (s t : Finset α) (a : α) : s.erase a \ t = (s \ t).erase a := by simp_rw [erase_eq, sdiff_right_comm] theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by rw [erase_inter, inter_erase] theorem erase_union_distrib (s t : Finset α) (a : α) : (s ∪ t).erase a = s.erase a ∪ t.erase a := by simp_rw [erase_eq, union_sdiff_distrib] theorem insert_inter_distrib (s t : Finset α) (a : α) : insert a (s ∩ t) = insert a s ∩ insert a t := by simp_rw [insert_eq, union_inter_distrib_left] theorem erase_sdiff_distrib (s t : Finset α) (a : α) : (s \ t).erase a = s.erase a \ t.erase a := by simp_rw [erase_eq, sdiff_sdiff, sup_sdiff_eq_sup le_rfl, sup_comm] theorem erase_union_of_mem (ha : a ∈ t) (s : Finset α) : s.erase a ∪ t = s ∪ t := by rw [← insert_erase (mem_union_right s ha), erase_union_distrib, ← union_insert, insert_erase ha] theorem union_erase_of_mem (ha : a ∈ s) (t : Finset α) : s ∪ t.erase a = s ∪ t := by rw [← insert_erase (mem_union_left t ha), erase_union_distrib, ← insert_union, insert_erase ha] theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)] theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib, inter_comm] theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) : insert x (s \ insert x t) = s \ t := by rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)] theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq, union_comm] theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq] theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff] --TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra` theorem sdiff_disjoint : Disjoint (t \ s) s := disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2 theorem disjoint_sdiff : Disjoint s (t \ s) := sdiff_disjoint.symm theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) := disjoint_of_subset_right inter_subset_right sdiff_disjoint end Sdiff /-! ### attach -/ @[simp] theorem attach_empty : attach (∅ : Finset α) = ∅ := rfl @[simp] theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by simp [Finset.Nonempty] @[aesop safe apply (rule_sets := [finsetNonempty])] protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff @[simp] theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by simp [eq_empty_iff_forall_not_mem] /-! ### filter -/ section Filter variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α} theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by classical ext x simp only [mem_singleton, forall_eq, mem_filter] split_ifs with h <;> by_cases h' : x = a <;> simp [h, h'] theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) : filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) := eq_of_veq <| Multiset.filter_cons_of_pos s.val hp theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) : filter p (cons a s ha) = filter p s := eq_of_veq <| Multiset.filter_cons_of_neg s.val hp theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] : Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by constructor <;> simp +contextual [disjoint_left] theorem disjoint_filter_filter' (s t : Finset α) {p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) : Disjoint (s.filter p) (t.filter q) := by simp_rw [disjoint_left, mem_filter] rintro a ⟨_, hp⟩ ⟨_, hq⟩ rw [Pi.disjoint_iff] at h simpa [hp, hq] using h a theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] : Disjoint (s.filter p) (t.filter fun a => ¬p a) := disjoint_filter_filter' s t disjoint_compl_right theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) : filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) := eq_of_veq <| Multiset.filter_add _ _ _ theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) : filter p (cons a s ha) = if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by split_ifs with h · rw [filter_cons_of_pos _ _ _ ha h] · rw [filter_cons_of_neg _ _ _ ha h] section variable [DecidableEq α] theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p := ext fun _ => by simp only [mem_filter, mem_union, or_and_right] theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x := ext fun x => by simp [mem_filter, mem_union, ← and_or_left] theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] : (s.filter fun i => i ∈ t) = s ∩ t := ext fun i => by simp [mem_filter, mem_inter] theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by ext simp [mem_filter, mem_inter, and_assoc] theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by ext simp only [mem_inter, mem_filter, and_right_comm] theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by rw [inter_comm, filter_inter, inter_comm] theorem filter_insert (a : α) (s : Finset α) : filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by ext x split_ifs with h <;> by_cases h' : x = a <;> simp [h, h'] theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by ext x simp only [and_assoc, mem_filter, iff_self, mem_erase] theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q := ext fun _ => by simp [mem_filter, mem_union, and_or_left] theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q := ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc] theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p := ext fun a => by simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or, Bool.not_eq_true, and_or_left, and_not_self, or_false] lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] : s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)] theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ := ext fun _ => by simp [mem_sdiff, mem_filter] theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) : ∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by classical refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩ · simp [filter_union_right, em] · intro x simp · intro x simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp] intro hx hx₂ exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩ -- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing -- on, e.g. `x ∈ s.filter (Eq b)`. /-- After filtering out everything that does not equal a given value, at most that value remains. This is equivalent to `filter_eq'` with the equality the other way. -/ theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) : s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by split_ifs with h · ext simp only [mem_filter, mem_singleton, decide_eq_true_eq] refine ⟨fun h => h.2.symm, ?_⟩ rintro rfl exact ⟨h, rfl⟩ · ext simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq] rintro m rfl exact h m /-- After filtering out everything that does not equal a given value, at most that value remains. This is equivalent to `filter_eq` with the equality the other way. -/ theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ := _root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b) theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => b ≠ a) = s.erase b := by ext simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not] tauto theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b := _root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b) theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) : s.filter p ∪ s.filter q = s := (filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) : (s.filter p ∪ s.filter fun a => ¬p a) = s := filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p end end Filter /-! ### range -/ section Range open Nat variable {n m l : ℕ} @[simp] theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by convert filter_eq (range n) m using 2 · ext rw [eq_comm] · simp end Range end Finset /-! ### dedup on list and multiset -/ namespace Multiset variable [DecidableEq α] {s t : Multiset α} @[simp] theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t := Finset.ext <| by simp @[simp] theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t := Finset.ext <| by simp @[simp] theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by ext; simp @[simp] theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 := Finset.val_inj.symm.trans Multiset.dedup_eq_zero @[simp] theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty] @[aesop safe apply (rule_sets := [finsetNonempty])] protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty @[simp] theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] : Multiset.toFinset (s.filter p) = s.toFinset.filter p := by ext; simp end Multiset namespace List variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β} {s : Finset α} {t : Set β} {t' : Finset β} @[simp] theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by ext simp @[simp] theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by ext simp @[aesop safe apply (rule_sets := [finsetNonempty])] alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff @[simp] theorem toFinset_filter (s : List α) (p : α → Bool) : (s.filter p).toFinset = s.toFinset.filter (p ·) := by ext; simp [List.mem_filter] end List namespace Finset section ToList @[simp] theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ := Multiset.toList_eq_nil.trans val_eq_zero theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp @[simp] theorem toList_empty : (∅ : Finset α).toList = [] := toList_eq_nil.mpr rfl theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] := mt toList_eq_nil.mp hs.ne_empty theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty := mt empty_toList.mp hs.ne_empty end ToList /-! ### choose -/ section Choose variable (p : α → Prop) [DecidablePred p] (l : Finset α) /-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of `l` satisfying `p` this unique element, as an element of the corresponding subtype. -/ def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } := Multiset.chooseX p l.val hp /-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of `l` satisfying `p` this unique element, as an element of the ambient type. -/ def choose (hp : ∃! a, a ∈ l ∧ p a) : α := chooseX p l hp theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) := (chooseX p l hp).property theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l := (choose_spec _ _ _).1 theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) := (choose_spec _ _ _).2 end Choose end Finset namespace Equiv variable [DecidableEq α] {s t : Finset α} open Finset /-- The disjoint union of finsets is a sum -/ def Finset.union (s t : Finset α) (h : Disjoint s t) : s ⊕ t ≃ (s ∪ t : Finset α) := Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm @[simp] theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) : Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ := rfl @[simp] theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) : Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ := rfl /-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/ def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) : ((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i := let e := Equiv.Finset.union s t h sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e) /-- A finset is equivalent to its coercion as a set. -/ def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where toFun a := ⟨a.1, mem_coe.2 a.2⟩ invFun a := ⟨a.1, mem_coe.1 a.2⟩ left_inv := fun _ ↦ rfl right_inv := fun _ ↦ rfl end Equiv namespace Multiset variable [DecidableEq α] @[simp] lemma toFinset_replicate (n : ℕ) (a : α) : (replicate n a).toFinset = if n = 0 then ∅ else {a} := by ext x simp only [mem_toFinset, Finset.mem_singleton, mem_replicate] split_ifs with hn <;> simp [hn] end Multiset
Mathlib/Data/Finset/Basic.lean
3,010
3,014
/- 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.Data.Prod.Lex import Mathlib.Data.Sigma.Lex import Mathlib.Order.RelIso.Set import Mathlib.Order.WellQuasiOrder import Mathlib.Tactic.TFAE /-! # Well-founded sets This file introduces versions of `WellFounded` and `WellQuasiOrdered` for sets. ## Main Definitions * `Set.WellFoundedOn s r` indicates that the relation `r` is well-founded when restricted to the set `s`. * `Set.IsWF s` indicates that `<` is well-founded when restricted to `s`. * `Set.PartiallyWellOrderedOn s r` indicates that the relation `r` is partially well-ordered (also known as well quasi-ordered) when restricted to the set `s`. * `Set.IsPWO s` indicates that any infinite sequence of elements in `s` contains an infinite monotone subsequence. Note that this is equivalent to containing only two comparable elements. ## Main Results * Higman's Lemma, `Set.PartiallyWellOrderedOn.partiallyWellOrderedOn_sublistForall₂`, shows that if `r` is partially well-ordered on `s`, then `List.SublistForall₂` is partially well-ordered on the set of lists of elements of `s`. The result was originally published by Higman, but this proof more closely follows Nash-Williams. * `Set.wellFoundedOn_iff` relates `well_founded_on` to the well-foundedness of a relation on the original type, to avoid dealing with subtypes. * `Set.IsWF.mono` shows that a subset of a well-founded subset is well-founded. * `Set.IsWF.union` shows that the union of two well-founded subsets is well-founded. * `Finset.isWF` shows that all `Finset`s are well-founded. ## TODO * Prove that `s` is partial well ordered iff it has no infinite descending chain or antichain. * Rename `Set.PartiallyWellOrderedOn` to `Set.WellQuasiOrderedOn` and `Set.IsPWO` to `Set.IsWQO`. ## References * [Higman, *Ordering by Divisibility in Abstract Algebras*][Higman52] * [Nash-Williams, *On Well-Quasi-Ordering Finite Trees*][Nash-Williams63] -/ assert_not_exists OrderedSemiring open scoped Function -- required for scoped `on` notation variable {ι α β γ : Type*} {π : ι → Type*} namespace Set /-! ### Relations well-founded on sets -/ /-- `s.WellFoundedOn r` indicates that the relation `r` is `WellFounded` when restricted to `s`. -/ def WellFoundedOn (s : Set α) (r : α → α → Prop) : Prop := WellFounded (Subrel r (· ∈ s)) @[simp] theorem wellFoundedOn_empty (r : α → α → Prop) : WellFoundedOn ∅ r := wellFounded_of_isEmpty _ section WellFoundedOn variable {r r' : α → α → Prop} section AnyRel variable {f : β → α} {s t : Set α} {x y : α} theorem wellFoundedOn_iff : s.WellFoundedOn r ↔ WellFounded fun a b : α => r a b ∧ a ∈ s ∧ b ∈ s := by have f : RelEmbedding (Subrel r (· ∈ s)) fun a b : α => r a b ∧ a ∈ s ∧ b ∈ s := ⟨⟨(↑), Subtype.coe_injective⟩, by simp⟩ refine ⟨fun h => ?_, f.wellFounded⟩ rw [WellFounded.wellFounded_iff_has_min] intro t ht by_cases hst : (s ∩ t).Nonempty · rw [← Subtype.preimage_coe_nonempty] at hst rcases h.has_min (Subtype.val ⁻¹' t) hst with ⟨⟨m, ms⟩, mt, hm⟩ exact ⟨m, mt, fun x xt ⟨xm, xs, _⟩ => hm ⟨x, xs⟩ xt xm⟩ · rcases ht with ⟨m, mt⟩ exact ⟨m, mt, fun x _ ⟨_, _, ms⟩ => hst ⟨m, ⟨ms, mt⟩⟩⟩ @[simp] theorem wellFoundedOn_univ : (univ : Set α).WellFoundedOn r ↔ WellFounded r := by simp [wellFoundedOn_iff] theorem _root_.WellFounded.wellFoundedOn : WellFounded r → s.WellFoundedOn r := InvImage.wf _ @[simp] theorem wellFoundedOn_range : (range f).WellFoundedOn r ↔ WellFounded (r on f) := by let f' : β → range f := fun c => ⟨f c, c, rfl⟩ refine ⟨fun h => (InvImage.wf f' h).mono fun c c' => id, fun h => ⟨?_⟩⟩ rintro ⟨_, c, rfl⟩ refine Acc.of_downward_closed f' ?_ _ ?_ · rintro _ ⟨_, c', rfl⟩ - exact ⟨c', rfl⟩ · exact h.apply _ @[simp] theorem wellFoundedOn_image {s : Set β} : (f '' s).WellFoundedOn r ↔ s.WellFoundedOn (r on f) := by rw [image_eq_range]; exact wellFoundedOn_range namespace WellFoundedOn protected theorem induction (hs : s.WellFoundedOn r) (hx : x ∈ s) {P : α → Prop} (hP : ∀ y ∈ s, (∀ z ∈ s, r z y → P z) → P y) : P x := by let Q : s → Prop := fun y => P y change Q ⟨x, hx⟩ refine WellFounded.induction hs ⟨x, hx⟩ ?_ simpa only [Subtype.forall] protected theorem mono (h : t.WellFoundedOn r') (hle : r ≤ r') (hst : s ⊆ t) : s.WellFoundedOn r := by rw [wellFoundedOn_iff] at * exact Subrelation.wf (fun xy => ⟨hle _ _ xy.1, hst xy.2.1, hst xy.2.2⟩) h theorem mono' (h : ∀ (a) (_ : a ∈ s) (b) (_ : b ∈ s), r' a b → r a b) : s.WellFoundedOn r → s.WellFoundedOn r' := Subrelation.wf @fun a b => h _ a.2 _ b.2 theorem subset (h : t.WellFoundedOn r) (hst : s ⊆ t) : s.WellFoundedOn r := h.mono le_rfl hst open Relation open List in /-- `a` is accessible under the relation `r` iff `r` is well-founded on the downward transitive closure of `a` under `r` (including `a` or not). -/ theorem acc_iff_wellFoundedOn {α} {r : α → α → Prop} {a : α} : TFAE [Acc r a, WellFoundedOn { b | ReflTransGen r b a } r, WellFoundedOn { b | TransGen r b a } r] := by tfae_have 1 → 2 := by refine fun h => ⟨fun b => InvImage.accessible Subtype.val ?_⟩ rw [← acc_transGen_iff] at h ⊢ obtain h' | h' := reflTransGen_iff_eq_or_transGen.1 b.2 · rwa [h'] at h · exact h.inv h' tfae_have 2 → 3 := fun h => h.subset fun _ => TransGen.to_reflTransGen tfae_have 3 → 1 := by refine fun h => Acc.intro _ (fun b hb => (h.apply ⟨b, .single hb⟩).of_fibration Subtype.val ?_) exact fun ⟨c, hc⟩ d h => ⟨⟨d, .head h hc⟩, h, rfl⟩ tfae_finish end WellFoundedOn end AnyRel section IsStrictOrder variable [IsStrictOrder α r] {s t : Set α} instance IsStrictOrder.subset : IsStrictOrder α fun a b : α => r a b ∧ a ∈ s ∧ b ∈ s where toIsIrrefl := ⟨fun a con => irrefl_of r a con.1⟩ toIsTrans := ⟨fun _ _ _ ab bc => ⟨trans_of r ab.1 bc.1, ab.2.1, bc.2.2⟩⟩ theorem wellFoundedOn_iff_no_descending_seq : s.WellFoundedOn r ↔ ∀ f : ((· > ·) : ℕ → ℕ → Prop) ↪r r, ¬∀ n, f n ∈ s := by simp only [wellFoundedOn_iff, RelEmbedding.wellFounded_iff_no_descending_seq, ← not_exists, ← not_nonempty_iff, not_iff_not] constructor · rintro ⟨⟨f, hf⟩⟩ have H : ∀ n, f n ∈ s := fun n => (hf.2 n.lt_succ_self).2.2 refine ⟨⟨f, ?_⟩, H⟩ simpa only [H, and_true] using @hf · rintro ⟨⟨f, hf⟩, hfs : ∀ n, f n ∈ s⟩ refine ⟨⟨f, ?_⟩⟩ simpa only [hfs, and_true] using @hf theorem WellFoundedOn.union (hs : s.WellFoundedOn r) (ht : t.WellFoundedOn r) : (s ∪ t).WellFoundedOn r := by rw [wellFoundedOn_iff_no_descending_seq] at * rintro f hf rcases Nat.exists_subseq_of_forall_mem_union f hf with ⟨g, hg | hg⟩ exacts [hs (g.dual.ltEmbedding.trans f) hg, ht (g.dual.ltEmbedding.trans f) hg] @[simp] theorem wellFoundedOn_union : (s ∪ t).WellFoundedOn r ↔ s.WellFoundedOn r ∧ t.WellFoundedOn r := ⟨fun h => ⟨h.subset subset_union_left, h.subset subset_union_right⟩, fun h => h.1.union h.2⟩ end IsStrictOrder end WellFoundedOn /-! ### Sets well-founded w.r.t. the strict inequality -/ section LT variable [LT α] {s t : Set α} /-- `s.IsWF` indicates that `<` is well-founded when restricted to `s`. -/ def IsWF (s : Set α) : Prop := WellFoundedOn s (· < ·) @[simp] theorem isWF_empty : IsWF (∅ : Set α) := wellFounded_of_isEmpty _ theorem IsWF.mono (h : IsWF t) (st : s ⊆ t) : IsWF s := h.subset st theorem isWF_univ_iff : IsWF (univ : Set α) ↔ WellFoundedLT α := by simp [IsWF, wellFoundedOn_iff, isWellFounded_iff] theorem IsWF.of_wellFoundedLT [h : WellFoundedLT α] (s : Set α) : s.IsWF := (Set.isWF_univ_iff.2 h).mono s.subset_univ @[deprecated IsWF.of_wellFoundedLT (since := "2025-01-16")] theorem _root_.WellFounded.isWF (h : WellFounded ((· < ·) : α → α → Prop)) (s : Set α) : s.IsWF := have : WellFoundedLT α := ⟨h⟩ .of_wellFoundedLT s end LT section Preorder variable [Preorder α] {s t : Set α} {a : α} protected nonrec theorem IsWF.union (hs : IsWF s) (ht : IsWF t) : IsWF (s ∪ t) := hs.union ht @[simp] theorem isWF_union : IsWF (s ∪ t) ↔ IsWF s ∧ IsWF t := wellFoundedOn_union end Preorder section Preorder variable [Preorder α] {s t : Set α} {a : α} theorem isWF_iff_no_descending_seq : IsWF s ↔ ∀ f : ℕ → α, StrictAnti f → ¬∀ n, f (OrderDual.toDual n) ∈ s := wellFoundedOn_iff_no_descending_seq.trans ⟨fun H f hf => H ⟨⟨f, hf.injective⟩, hf.lt_iff_lt⟩, fun H f => H f fun _ _ => f.map_rel_iff.2⟩ end Preorder /-! ### Partially well-ordered sets -/ /-- `s.PartiallyWellOrderedOn r` indicates that the relation `r` is `WellQuasiOrdered` when restricted to `s`. A set is partially well-ordered by a relation `r` when any infinite sequence contains two elements where the first is related to the second by `r`. Equivalently, any antichain (see `IsAntichain`) is finite, see `Set.partiallyWellOrderedOn_iff_finite_antichains`. TODO: rename this to `WellQuasiOrderedOn` to match `WellQuasiOrdered`. -/ def PartiallyWellOrderedOn (s : Set α) (r : α → α → Prop) : Prop := WellQuasiOrdered (Subrel r (· ∈ s)) section PartiallyWellOrderedOn variable {r : α → α → Prop} {r' : β → β → Prop} {f : α → β} {s : Set α} {t : Set α} {a : α} theorem PartiallyWellOrderedOn.exists_lt (hs : s.PartiallyWellOrderedOn r) {f : ℕ → α} (hf : ∀ n, f n ∈ s) : ∃ m n, m < n ∧ r (f m) (f n) := hs fun n ↦ ⟨_, hf n⟩ theorem partiallyWellOrderedOn_iff_exists_lt : s.PartiallyWellOrderedOn r ↔ ∀ f : ℕ → α, (∀ n, f n ∈ s) → ∃ m n, m < n ∧ r (f m) (f n) := ⟨PartiallyWellOrderedOn.exists_lt, fun hf f ↦ hf _ fun n ↦ (f n).2⟩ theorem PartiallyWellOrderedOn.mono (ht : t.PartiallyWellOrderedOn r) (h : s ⊆ t) : s.PartiallyWellOrderedOn r := fun f ↦ ht (Set.inclusion h ∘ f) @[simp] theorem partiallyWellOrderedOn_empty (r : α → α → Prop) : PartiallyWellOrderedOn ∅ r := wellQuasiOrdered_of_isEmpty _ theorem PartiallyWellOrderedOn.union (hs : s.PartiallyWellOrderedOn r) (ht : t.PartiallyWellOrderedOn r) : (s ∪ t).PartiallyWellOrderedOn r := by intro f obtain ⟨g, hgs | hgt⟩ := Nat.exists_subseq_of_forall_mem_union _ fun x ↦ (f x).2 · rcases hs.exists_lt hgs with ⟨m, n, hlt, hr⟩ exact ⟨g m, g n, g.strictMono hlt, hr⟩ · rcases ht.exists_lt hgt with ⟨m, n, hlt, hr⟩ exact ⟨g m, g n, g.strictMono hlt, hr⟩ @[simp] theorem partiallyWellOrderedOn_union : (s ∪ t).PartiallyWellOrderedOn r ↔ s.PartiallyWellOrderedOn r ∧ t.PartiallyWellOrderedOn r := ⟨fun h ↦ ⟨h.mono subset_union_left, h.mono subset_union_right⟩, fun h ↦ h.1.union h.2⟩ theorem PartiallyWellOrderedOn.image_of_monotone_on (hs : s.PartiallyWellOrderedOn r) (hf : ∀ a₁ ∈ s, ∀ a₂ ∈ s, r a₁ a₂ → r' (f a₁) (f a₂)) : (f '' s).PartiallyWellOrderedOn r' := by rw [partiallyWellOrderedOn_iff_exists_lt] at * intro g' hg' choose g hgs heq using hg' obtain rfl : f ∘ g = g' := funext heq obtain ⟨m, n, hlt, hmn⟩ := hs g hgs exact ⟨m, n, hlt, hf _ (hgs m) _ (hgs n) hmn⟩ -- TODO: prove this in terms of `IsAntichain.finite_of_wellQuasiOrdered` theorem _root_.IsAntichain.finite_of_partiallyWellOrderedOn (ha : IsAntichain r s) (hp : s.PartiallyWellOrderedOn r) : s.Finite := by refine not_infinite.1 fun hi => ?_ obtain ⟨m, n, hmn, h⟩ := hp (hi.natEmbedding _) exact hmn.ne ((hi.natEmbedding _).injective <| Subtype.val_injective <| ha.eq (hi.natEmbedding _ m).2 (hi.natEmbedding _ n).2 h) section IsRefl variable [IsRefl α r] protected theorem Finite.partiallyWellOrderedOn (hs : s.Finite) : s.PartiallyWellOrderedOn r := hs.to_subtype.wellQuasiOrdered _ theorem _root_.IsAntichain.partiallyWellOrderedOn_iff (hs : IsAntichain r s) : s.PartiallyWellOrderedOn r ↔ s.Finite := ⟨hs.finite_of_partiallyWellOrderedOn, Finite.partiallyWellOrderedOn⟩ @[simp] theorem partiallyWellOrderedOn_singleton (a : α) : PartiallyWellOrderedOn {a} r := (finite_singleton a).partiallyWellOrderedOn @[nontriviality] theorem Subsingleton.partiallyWellOrderedOn (hs : s.Subsingleton) : PartiallyWellOrderedOn s r := hs.finite.partiallyWellOrderedOn @[simp] theorem partiallyWellOrderedOn_insert : PartiallyWellOrderedOn (insert a s) r ↔ PartiallyWellOrderedOn s r := by simp only [← singleton_union, partiallyWellOrderedOn_union, partiallyWellOrderedOn_singleton, true_and] protected theorem PartiallyWellOrderedOn.insert (h : PartiallyWellOrderedOn s r) (a : α) : PartiallyWellOrderedOn (insert a s) r := partiallyWellOrderedOn_insert.2 h theorem partiallyWellOrderedOn_iff_finite_antichains [IsSymm α r] : s.PartiallyWellOrderedOn r ↔ ∀ t, t ⊆ s → IsAntichain r t → t.Finite := by refine ⟨fun h t ht hrt => hrt.finite_of_partiallyWellOrderedOn (h.mono ht), ?_⟩ rw [partiallyWellOrderedOn_iff_exists_lt] intro hs f hf by_contra! H refine infinite_range_of_injective (fun m n hmn => ?_) (hs _ (range_subset_iff.2 hf) ?_) · obtain h | h | h := lt_trichotomy m n · refine (H _ _ h ?_).elim rw [hmn] exact refl _ · exact h · refine (H _ _ h ?_).elim rw [hmn] exact refl _ rintro _ ⟨m, hm, rfl⟩ _ ⟨n, hn, rfl⟩ hmn obtain h | h := (ne_of_apply_ne _ hmn).lt_or_lt · exact H _ _ h · exact mt symm (H _ _ h) end IsRefl section IsPreorder variable [IsPreorder α r] theorem PartiallyWellOrderedOn.exists_monotone_subseq (h : s.PartiallyWellOrderedOn r) {f : ℕ → α} (hf : ∀ n, f n ∈ s) : ∃ g : ℕ ↪o ℕ, ∀ m n : ℕ, m ≤ n → r (f (g m)) (f (g n)) := WellQuasiOrdered.exists_monotone_subseq h fun n ↦ ⟨_, hf n⟩ theorem partiallyWellOrderedOn_iff_exists_monotone_subseq : s.PartiallyWellOrderedOn r ↔ ∀ f : ℕ → α, (∀ n, f n ∈ s) → ∃ g : ℕ ↪o ℕ, ∀ m n : ℕ, m ≤ n → r (f (g m)) (f (g n)) := by use PartiallyWellOrderedOn.exists_monotone_subseq rw [PartiallyWellOrderedOn, wellQuasiOrdered_iff_exists_monotone_subseq] exact fun H f ↦ H _ fun n ↦ (f n).2 protected theorem PartiallyWellOrderedOn.prod {t : Set β} (hs : PartiallyWellOrderedOn s r) (ht : PartiallyWellOrderedOn t r') : PartiallyWellOrderedOn (s ×ˢ t) fun x y : α × β => r x.1 y.1 ∧ r' x.2 y.2 := by rw [partiallyWellOrderedOn_iff_exists_lt] intro f hf obtain ⟨g₁, h₁⟩ := hs.exists_monotone_subseq fun n => (hf n).1 obtain ⟨m, n, hlt, hle⟩ := ht.exists_lt fun n => (hf _).2 exact ⟨g₁ m, g₁ n, g₁.strictMono hlt, h₁ _ _ hlt.le, hle⟩ theorem PartiallyWellOrderedOn.wellFoundedOn (h : s.PartiallyWellOrderedOn r) : s.WellFoundedOn fun a b => r a b ∧ ¬ r b a := h.wellFounded end IsPreorder end PartiallyWellOrderedOn section IsPWO variable [Preorder α] [Preorder β] {s t : Set α} /-- A subset of a preorder is partially well-ordered when any infinite sequence contains a monotone subsequence of length 2 (or equivalently, an infinite monotone subsequence). -/ def IsPWO (s : Set α) : Prop := PartiallyWellOrderedOn s (· ≤ ·) nonrec theorem IsPWO.mono (ht : t.IsPWO) : s ⊆ t → s.IsPWO := ht.mono nonrec theorem IsPWO.exists_monotone_subseq (h : s.IsPWO) {f : ℕ → α} (hf : ∀ n, f n ∈ s) : ∃ g : ℕ ↪o ℕ, Monotone (f ∘ g) := h.exists_monotone_subseq hf theorem isPWO_iff_exists_monotone_subseq : s.IsPWO ↔ ∀ f : ℕ → α, (∀ n, f n ∈ s) → ∃ g : ℕ ↪o ℕ, Monotone (f ∘ g) := partiallyWellOrderedOn_iff_exists_monotone_subseq protected theorem IsPWO.isWF (h : s.IsPWO) : s.IsWF := by simpa only [← lt_iff_le_not_le] using h.wellFoundedOn nonrec theorem IsPWO.prod {t : Set β} (hs : s.IsPWO) (ht : t.IsPWO) : IsPWO (s ×ˢ t) := hs.prod ht theorem IsPWO.image_of_monotoneOn (hs : s.IsPWO) {f : α → β} (hf : MonotoneOn f s) : IsPWO (f '' s) := hs.image_of_monotone_on hf theorem IsPWO.image_of_monotone (hs : s.IsPWO) {f : α → β} (hf : Monotone f) : IsPWO (f '' s) := hs.image_of_monotone_on (hf.monotoneOn _) protected nonrec theorem IsPWO.union (hs : IsPWO s) (ht : IsPWO t) : IsPWO (s ∪ t) := hs.union ht @[simp] theorem isPWO_union : IsPWO (s ∪ t) ↔ IsPWO s ∧ IsPWO t := partiallyWellOrderedOn_union protected theorem Finite.isPWO (hs : s.Finite) : IsPWO s := hs.partiallyWellOrderedOn @[simp] theorem isPWO_of_finite [Finite α] : s.IsPWO := s.toFinite.isPWO @[simp] theorem isPWO_singleton (a : α) : IsPWO ({a} : Set α) := (finite_singleton a).isPWO @[simp] theorem isPWO_empty : IsPWO (∅ : Set α) := finite_empty.isPWO protected theorem Subsingleton.isPWO (hs : s.Subsingleton) : IsPWO s := hs.finite.isPWO @[simp] theorem isPWO_insert {a} : IsPWO (insert a s) ↔ IsPWO s := by simp only [← singleton_union, isPWO_union, isPWO_singleton, true_and] protected theorem IsPWO.insert (h : IsPWO s) (a : α) : IsPWO (insert a s) := isPWO_insert.2 h protected theorem Finite.isWF (hs : s.Finite) : IsWF s := hs.isPWO.isWF @[simp] theorem isWF_singleton {a : α} : IsWF ({a} : Set α) := (finite_singleton a).isWF protected theorem Subsingleton.isWF (hs : s.Subsingleton) : IsWF s := hs.isPWO.isWF @[simp] theorem isWF_insert {a} : IsWF (insert a s) ↔ IsWF s := by simp only [← singleton_union, isWF_union, isWF_singleton, true_and] protected theorem IsWF.insert (h : IsWF s) (a : α) : IsWF (insert a s) := isWF_insert.2 h end IsPWO section WellFoundedOn variable {r : α → α → Prop} [IsStrictOrder α r] {s : Set α} {a : α} protected theorem Finite.wellFoundedOn (hs : s.Finite) : s.WellFoundedOn r := letI := partialOrderOfSO r hs.isWF @[simp] theorem wellFoundedOn_singleton : WellFoundedOn ({a} : Set α) r := (finite_singleton a).wellFoundedOn protected theorem Subsingleton.wellFoundedOn (hs : s.Subsingleton) : s.WellFoundedOn r := hs.finite.wellFoundedOn @[simp] theorem wellFoundedOn_insert : WellFoundedOn (insert a s) r ↔ WellFoundedOn s r := by simp only [← singleton_union, wellFoundedOn_union, wellFoundedOn_singleton, true_and] @[simp] theorem wellFoundedOn_sdiff_singleton : WellFoundedOn (s \ {a}) r ↔ WellFoundedOn s r := by simp only [← wellFoundedOn_insert (a := a), insert_diff_singleton, mem_insert_iff, true_or, insert_eq_of_mem] protected theorem WellFoundedOn.insert (h : WellFoundedOn s r) (a : α) : WellFoundedOn (insert a s) r := wellFoundedOn_insert.2 h protected theorem WellFoundedOn.sdiff_singleton (h : WellFoundedOn s r) (a : α) : WellFoundedOn (s \ {a}) r := wellFoundedOn_sdiff_singleton.2 h lemma WellFoundedOn.mapsTo {α β : Type*} {r : α → α → Prop} (f : β → α) {s : Set α} {t : Set β} (h : MapsTo f t s) (hw : s.WellFoundedOn r) : t.WellFoundedOn (r on f) := by exact InvImage.wf (fun x : t ↦ ⟨f x, h x.prop⟩) hw end WellFoundedOn section LinearOrder variable [LinearOrder α] {s : Set α} /-- In a linear order, the predicates `Set.IsPWO` and `Set.IsWF` are equivalent. -/ theorem isPWO_iff_isWF : s.IsPWO ↔ s.IsWF := by change WellQuasiOrdered (· ≤ ·) ↔ WellFounded (· < ·) rw [← wellQuasiOrderedLE_def, ← isWellFounded_iff, wellQuasiOrderedLE_iff_wellFoundedLT] alias ⟨_, IsWF.isPWO⟩ := isPWO_iff_isWF @[deprecated isPWO_iff_isWF (since := "2025-01-21")] theorem isWF_iff_isPWO : s.IsWF ↔ s.IsPWO := isPWO_iff_isWF.symm /-- If `α` is a linear order with well-founded `<`, then any set in it is a partially well-ordered set. Note this does not hold without the linearity assumption. -/ lemma IsPWO.of_linearOrder [WellFoundedLT α] (s : Set α) : s.IsPWO := (IsWF.of_wellFoundedLT s).isPWO end LinearOrder end Set namespace Finset variable {r : α → α → Prop} @[simp] protected theorem partiallyWellOrderedOn [IsRefl α r] (s : Finset α) : (s : Set α).PartiallyWellOrderedOn r := s.finite_toSet.partiallyWellOrderedOn @[simp] protected theorem isPWO [Preorder α] (s : Finset α) : Set.IsPWO (↑s : Set α) := s.partiallyWellOrderedOn @[simp] protected theorem isWF [Preorder α] (s : Finset α) : Set.IsWF (↑s : Set α) := s.finite_toSet.isWF @[simp] protected theorem wellFoundedOn [IsStrictOrder α r] (s : Finset α) : Set.WellFoundedOn (↑s : Set α) r := letI := partialOrderOfSO r s.isWF theorem wellFoundedOn_sup [IsStrictOrder α r] (s : Finset ι) {f : ι → Set α} : (s.sup f).WellFoundedOn r ↔ ∀ i ∈ s, (f i).WellFoundedOn r := Finset.cons_induction_on s (by simp) fun a s ha hs => by simp [-sup_set_eq_biUnion, hs] theorem partiallyWellOrderedOn_sup (s : Finset ι) {f : ι → Set α} : (s.sup f).PartiallyWellOrderedOn r ↔ ∀ i ∈ s, (f i).PartiallyWellOrderedOn r := Finset.cons_induction_on s (by simp) fun a s ha hs => by simp [-sup_set_eq_biUnion, hs] theorem isWF_sup [Preorder α] (s : Finset ι) {f : ι → Set α} : (s.sup f).IsWF ↔ ∀ i ∈ s, (f i).IsWF := s.wellFoundedOn_sup theorem isPWO_sup [Preorder α] (s : Finset ι) {f : ι → Set α} : (s.sup f).IsPWO ↔ ∀ i ∈ s, (f i).IsPWO := s.partiallyWellOrderedOn_sup @[simp] theorem wellFoundedOn_bUnion [IsStrictOrder α r] (s : Finset ι) {f : ι → Set α} : (⋃ i ∈ s, f i).WellFoundedOn r ↔ ∀ i ∈ s, (f i).WellFoundedOn r := by simpa only [Finset.sup_eq_iSup] using s.wellFoundedOn_sup @[simp] theorem partiallyWellOrderedOn_bUnion (s : Finset ι) {f : ι → Set α} : (⋃ i ∈ s, f i).PartiallyWellOrderedOn r ↔ ∀ i ∈ s, (f i).PartiallyWellOrderedOn r := by simpa only [Finset.sup_eq_iSup] using s.partiallyWellOrderedOn_sup @[simp] theorem isWF_bUnion [Preorder α] (s : Finset ι) {f : ι → Set α} : (⋃ i ∈ s, f i).IsWF ↔ ∀ i ∈ s, (f i).IsWF := s.wellFoundedOn_bUnion @[simp] theorem isPWO_bUnion [Preorder α] (s : Finset ι) {f : ι → Set α} : (⋃ i ∈ s, f i).IsPWO ↔ ∀ i ∈ s, (f i).IsPWO := s.partiallyWellOrderedOn_bUnion end Finset namespace Set section Preorder variable [Preorder α] {s t : Set α} {a : α} /-- `Set.IsWF.min` returns a minimal element of a nonempty well-founded set. -/ noncomputable nonrec def IsWF.min (hs : IsWF s) (hn : s.Nonempty) : α := hs.min univ (nonempty_iff_univ_nonempty.1 hn.to_subtype) theorem IsWF.min_mem (hs : IsWF s) (hn : s.Nonempty) : hs.min hn ∈ s := (WellFounded.min hs univ (nonempty_iff_univ_nonempty.1 hn.to_subtype)).2 nonrec theorem IsWF.not_lt_min (hs : IsWF s) (hn : s.Nonempty) (ha : a ∈ s) : ¬a < hs.min hn := hs.not_lt_min univ (nonempty_iff_univ_nonempty.1 hn.to_subtype) (mem_univ (⟨a, ha⟩ : s)) theorem IsWF.min_of_subset_not_lt_min {hs : s.IsWF} {hsn : s.Nonempty} {ht : t.IsWF} {htn : t.Nonempty} (hst : s ⊆ t) : ¬hs.min hsn < ht.min htn := ht.not_lt_min htn (hst (min_mem hs hsn)) @[simp] theorem isWF_min_singleton (a) {hs : IsWF ({a} : Set α)} {hn : ({a} : Set α).Nonempty} : hs.min hn = a := eq_of_mem_singleton (IsWF.min_mem hs hn) theorem IsWF.min_eq_of_lt (hs : s.IsWF) (ha : a ∈ s) (hlt : ∀ b ∈ s, b ≠ a → a < b) : hs.min (nonempty_of_mem ha) = a := by by_contra h exact (hs.not_lt_min (nonempty_of_mem ha) ha) (hlt (hs.min (nonempty_of_mem ha)) (hs.min_mem (nonempty_of_mem ha)) h) end Preorder section PartialOrder variable [PartialOrder α] {s : Set α} {a : α} theorem IsWF.min_eq_of_le (hs : s.IsWF) (ha : a ∈ s) (hle : ∀ b ∈ s, a ≤ b) : hs.min (nonempty_of_mem ha) = a := (eq_of_le_of_not_lt (hle (hs.min (nonempty_of_mem ha)) (hs.min_mem (nonempty_of_mem ha))) (hs.not_lt_min (nonempty_of_mem ha) ha)).symm end PartialOrder section LinearOrder variable [LinearOrder α] {s t : Set α} {a : α} theorem IsWF.min_le (hs : s.IsWF) (hn : s.Nonempty) (ha : a ∈ s) : hs.min hn ≤ a := le_of_not_lt (hs.not_lt_min hn ha) theorem IsWF.le_min_iff (hs : s.IsWF) (hn : s.Nonempty) : a ≤ hs.min hn ↔ ∀ b, b ∈ s → a ≤ b := ⟨fun ha _b hb => le_trans ha (hs.min_le hn hb), fun h => h _ (hs.min_mem _)⟩ theorem IsWF.min_le_min_of_subset {hs : s.IsWF} {hsn : s.Nonempty} {ht : t.IsWF} {htn : t.Nonempty} (hst : s ⊆ t) : ht.min htn ≤ hs.min hsn := (IsWF.le_min_iff _ _).2 fun _b hb => ht.min_le htn (hst hb) theorem IsWF.min_union (hs : s.IsWF) (hsn : s.Nonempty) (ht : t.IsWF) (htn : t.Nonempty) : (hs.union ht).min (union_nonempty.2 (Or.intro_left _ hsn)) = Min.min (hs.min hsn) (ht.min htn) := by refine le_antisymm (le_min (IsWF.min_le_min_of_subset subset_union_left) (IsWF.min_le_min_of_subset subset_union_right)) ?_ rw [min_le_iff] exact ((mem_union _ _ _).1 ((hs.union ht).min_mem (union_nonempty.2 (.inl hsn)))).imp (hs.min_le _) (ht.min_le _) end LinearOrder end Set open Set section LocallyFiniteOrder variable {s : Set α} [Preorder α] [LocallyFiniteOrder α] theorem BddBelow.wellFoundedOn_lt : BddBelow s → s.WellFoundedOn (· < ·) := by rw [wellFoundedOn_iff_no_descending_seq] rintro ⟨a, ha⟩ f hf refine infinite_range_of_injective f.injective ?_ exact (finite_Icc a <| f 0).subset <| range_subset_iff.2 <| fun n => ⟨ha <| hf _, antitone_iff_forall_lt.2 (fun a b hab => (f.map_rel_iff.2 hab).le) <| Nat.zero_le _⟩ theorem BddAbove.wellFoundedOn_gt : BddAbove s → s.WellFoundedOn (· > ·) := fun h => h.dual.wellFoundedOn_lt theorem BddBelow.isWF : BddBelow s → IsWF s := BddBelow.wellFoundedOn_lt end LocallyFiniteOrder namespace Set.PartiallyWellOrderedOn variable {r : α → α → Prop} -- TODO: move this material to the main file on WQOs. /-- In the context of partial well-orderings, a bad sequence is a nonincreasing sequence whose range is contained in a particular set `s`. One exists if and only if `s` is not partially well-ordered. -/ def IsBadSeq (r : α → α → Prop) (s : Set α) (f : ℕ → α) : Prop := (∀ n, f n ∈ s) ∧ ∀ m n : ℕ, m < n → ¬r (f m) (f n) theorem iff_forall_not_isBadSeq (r : α → α → Prop) (s : Set α) : s.PartiallyWellOrderedOn r ↔ ∀ f, ¬IsBadSeq r s f := by rw [partiallyWellOrderedOn_iff_exists_lt] exact forall_congr' fun f => by simp [IsBadSeq] /-- This indicates that every bad sequence `g` that agrees with `f` on the first `n` terms has `rk (f n) ≤ rk (g n)`. -/ def IsMinBadSeq (r : α → α → Prop) (rk : α → ℕ) (s : Set α) (n : ℕ) (f : ℕ → α) : Prop := ∀ g : ℕ → α, (∀ m : ℕ, m < n → f m = g m) → rk (g n) < rk (f n) → ¬IsBadSeq r s g /-- Given a bad sequence `f`, this constructs a bad sequence that agrees with `f` on the first `n` terms and is minimal at `n`. -/ noncomputable def minBadSeqOfBadSeq (r : α → α → Prop) (rk : α → ℕ) (s : Set α) (n : ℕ) (f : ℕ → α) (hf : IsBadSeq r s f) : { g : ℕ → α // (∀ m : ℕ, m < n → f m = g m) ∧ IsBadSeq r s g ∧ IsMinBadSeq r rk s n g } := by classical have h : ∃ (k : ℕ) (g : ℕ → α), (∀ m, m < n → f m = g m) ∧ IsBadSeq r s g ∧ rk (g n) = k := ⟨_, f, fun _ _ => rfl, hf, rfl⟩ obtain ⟨h1, h2, h3⟩ := Classical.choose_spec (Nat.find_spec h) refine ⟨Classical.choose (Nat.find_spec h), h1, by convert h2, fun g hg1 hg2 con => ?_⟩ refine Nat.find_min h ?_ ⟨g, fun m mn => (h1 m mn).trans (hg1 m mn), con, rfl⟩ rwa [← h3] theorem exists_min_bad_of_exists_bad (r : α → α → Prop) (rk : α → ℕ) (s : Set α) : (∃ f, IsBadSeq r s f) → ∃ f, IsBadSeq r s f ∧ ∀ n, IsMinBadSeq r rk s n f := by rintro ⟨f0, hf0 : IsBadSeq r s f0⟩ let fs : ∀ n : ℕ, { f : ℕ → α // IsBadSeq r s f ∧ IsMinBadSeq r rk s n f } := by refine Nat.rec ?_ fun n fn => ?_ · exact ⟨(minBadSeqOfBadSeq r rk s 0 f0 hf0).1, (minBadSeqOfBadSeq r rk s 0 f0 hf0).2.2⟩ · exact ⟨(minBadSeqOfBadSeq r rk s (n + 1) fn.1 fn.2.1).1, (minBadSeqOfBadSeq r rk s (n + 1) fn.1 fn.2.1).2.2⟩ have h : ∀ m n, m ≤ n → (fs m).1 m = (fs n).1 m := fun m n mn => by obtain ⟨k, rfl⟩ := Nat.exists_eq_add_of_le mn; clear mn induction' k with k ih · rfl · rw [ih, (minBadSeqOfBadSeq r rk s (m + k + 1) (fs (m + k)).1 (fs (m + k)).2.1).2.1 m (Nat.lt_succ_iff.2 (Nat.add_le_add_left k.zero_le m))] rfl refine ⟨fun n => (fs n).1 n, ⟨fun n => (fs n).2.1.1 n, fun m n mn => ?_⟩, fun n g hg1 hg2 => ?_⟩ · dsimp rw [h m n mn.le] exact (fs n).2.1.2 m n mn · refine (fs n).2.2 g (fun m mn => ?_) hg2 rw [← h m n mn.le, ← hg1 m mn] theorem iff_not_exists_isMinBadSeq (rk : α → ℕ) {s : Set α} : s.PartiallyWellOrderedOn r ↔ ¬∃ f, IsBadSeq r s f ∧ ∀ n, IsMinBadSeq r rk s n f := by rw [iff_forall_not_isBadSeq, ← not_exists, not_congr] constructor · apply exists_min_bad_of_exists_bad · rintro ⟨f, hf1, -⟩ exact ⟨f, hf1⟩ /-- Higman's Lemma, which states that for any reflexive, transitive relation `r` which is partially well-ordered on a set `s`, the relation `List.SublistForall₂ r` is partially well-ordered on the set of lists of elements of `s`. That relation is defined so that `List.SublistForall₂ r l₁ l₂` whenever `l₁` related pointwise by `r` to a sublist of `l₂`. -/ theorem partiallyWellOrderedOn_sublistForall₂ (r : α → α → Prop) [IsPreorder α r] {s : Set α} (h : s.PartiallyWellOrderedOn r) : { l : List α | ∀ x, x ∈ l → x ∈ s }.PartiallyWellOrderedOn (List.SublistForall₂ r) := by rcases isEmpty_or_nonempty α · exact subsingleton_of_subsingleton.partiallyWellOrderedOn inhabit α rw [iff_not_exists_isMinBadSeq List.length] rintro ⟨f, hf1, hf2⟩ have hnil : ∀ n, f n ≠ List.nil := fun n con => hf1.2 n n.succ n.lt_succ_self (con.symm ▸ List.SublistForall₂.nil) obtain ⟨g, hg⟩ := h.exists_monotone_subseq fun n => hf1.1 n _ (List.head!_mem_self (hnil n)) have hf' := hf2 (g 0) (fun n => if n < g 0 then f n else List.tail (f (g (n - g 0)))) (fun m hm => (if_pos hm).symm) ?_ swap · simp only [if_neg (lt_irrefl (g 0)), Nat.sub_self] rw [List.length_tail, ← Nat.pred_eq_sub_one] exact Nat.pred_lt fun con => hnil _ (List.length_eq_zero_iff.1 con) rw [IsBadSeq] at hf' push_neg at hf' obtain ⟨m, n, mn, hmn⟩ := hf' fun n x hx => by split_ifs at hx with hn exacts [hf1.1 _ _ hx, hf1.1 _ _ (List.tail_subset _ hx)] by_cases hn : n < g 0 · apply hf1.2 m n mn rwa [if_pos hn, if_pos (mn.trans hn)] at hmn · obtain ⟨n', rfl⟩ := Nat.exists_eq_add_of_le (not_lt.1 hn) rw [if_neg hn, add_comm (g 0) n', Nat.add_sub_cancel_right] at hmn split_ifs at hmn with hm · apply hf1.2 m (g n') (lt_of_lt_of_le hm (g.monotone n'.zero_le)) exact _root_.trans hmn (List.tail_sublistForall₂_self _) · rw [← Nat.sub_lt_iff_lt_add' (le_of_not_lt hm)] at mn apply hf1.2 _ _ (g.lt_iff_lt.2 mn) rw [← List.cons_head!_tail (hnil (g (m - g 0))), ← List.cons_head!_tail (hnil (g n'))] exact List.SublistForall₂.cons (hg _ _ (le_of_lt mn)) hmn theorem subsetProdLex [PartialOrder α] [Preorder β] {s : Set (α ×ₗ β)} (hα : ((fun (x : α ×ₗ β) => (ofLex x).1) '' s).IsPWO) (hβ : ∀ a, {y | toLex (a, y) ∈ s}.IsPWO) : s.IsPWO := by rw [IsPWO, partiallyWellOrderedOn_iff_exists_lt] intro f hf rw [isPWO_iff_exists_monotone_subseq] at hα obtain ⟨g, hg⟩ : ∃ (g : (ℕ ↪o ℕ)), Monotone fun n => (ofLex f (g n)).1 := hα (fun n => (ofLex f n).1) (fun k => mem_image_of_mem (fun x => (ofLex x).1) (hf k)) have hhg : ∀ n, (ofLex f (g 0)).1 ≤ (ofLex f (g n)).1 := fun n => hg n.zero_le by_cases hc : ∃ n, (ofLex f (g 0)).1 < (ofLex f (g n)).1 · obtain ⟨n, hn⟩ := hc use (g 0), (g n) constructor · by_contra hx simp_all · exact Prod.Lex.toLex_le_toLex.mpr <| .inl hn · have hhc : ∀ n, (ofLex f (g 0)).1 = (ofLex f (g n)).1 := by intro n rw [not_exists] at hc exact (hhg n).eq_of_not_lt (hc n) obtain ⟨g', hg'⟩ : ∃ g' : ℕ ↪o ℕ, Monotone ((fun n ↦ (ofLex f (g (g' n))).2)) := by simp_rw [isPWO_iff_exists_monotone_subseq] at hβ apply hβ (ofLex f (g 0)).1 fun n ↦ (ofLex f (g n)).2 intro n rw [hhc n] simpa using hf _ use (g (g' 0)), (g (g' 1)) suffices (f (g (g' 0))) ≤ (f (g (g' 1))) by simpa · refine Prod.Lex.toLex_le_toLex.mpr <| .inr ⟨?_, ?_⟩ · exact (hhc (g' 0)).symm.trans (hhc (g' 1)) · exact hg' (Nat.zero_le 1) theorem imageProdLex [Preorder α] [Preorder β] {s : Set (α ×ₗ β)} (hαβ : s.IsPWO) : ((fun (x : α ×ₗ β) => (ofLex x).1)'' s).IsPWO := IsPWO.image_of_monotone hαβ Prod.Lex.monotone_fst theorem fiberProdLex [Preorder α] [Preorder β] {s : Set (α ×ₗ β)} (hαβ : s.IsPWO) (a : α) : {y | toLex (a, y) ∈ s}.IsPWO := by let f : α ×ₗ β → β := fun x => (ofLex x).2 have h : {y | toLex (a, y) ∈ s} = f '' (s ∩ (fun x ↦ (ofLex x).1) ⁻¹' {a}) := by ext x simp [f] rw [h] apply IsPWO.image_of_monotoneOn (hαβ.mono inter_subset_left) rintro b ⟨-, hb⟩ c ⟨-, hc⟩ hbc simp only [mem_preimage, mem_singleton_iff] at hb hc have : (ofLex b).1 < (ofLex c).1 ∨ (ofLex b).1 = (ofLex c).1 ∧ f b ≤ f c := Prod.Lex.toLex_le_toLex.mp hbc simp_all only [lt_self_iff_false, true_and, false_or] theorem ProdLex_iff [PartialOrder α] [Preorder β] {s : Set (α ×ₗ β)} : s.IsPWO ↔
((fun (x : α ×ₗ β) ↦ (ofLex x).1) '' s).IsPWO ∧ ∀ a, {y | toLex (a, y) ∈ s}.IsPWO := ⟨fun h ↦ ⟨imageProdLex h, fiberProdLex h⟩, fun h ↦ subsetProdLex h.1 h.2⟩ end Set.PartiallyWellOrderedOn /-- A version of **Dickson's lemma** any subset of functions `Π s : σ, α s` is partially well ordered, when `σ` is a `Fintype` and each `α s` is a linear well order. This includes the classical case of Dickson's lemma that `ℕ ^ n` is a well partial order. Some generalizations would be possible based on this proof, to include cases where the target is partially well ordered, and also to consider the case of `Set.PartiallyWellOrderedOn` instead of `Set.IsPWO`. -/ theorem Pi.isPWO {α : ι → Type*} [∀ i, LinearOrder (α i)] [∀ i, IsWellOrder (α i) (· < ·)] [Finite ι] (s : Set (∀ i, α i)) : s.IsPWO := by cases nonempty_fintype ι suffices ∀ (s : Finset ι) (f : ℕ → ∀ s, α s), ∃ g : ℕ ↪o ℕ, ∀ ⦃a b : ℕ⦄, a ≤ b → ∀ x, x ∈ s → (f ∘ g) a x ≤ (f ∘ g) b x by refine isPWO_iff_exists_monotone_subseq.2 fun f _ => ?_ simpa only [Finset.mem_univ, true_imp_iff] using this Finset.univ f refine Finset.cons_induction ?_ ?_ · intro f exists RelEmbedding.refl (· ≤ ·) simp only [IsEmpty.forall_iff, imp_true_iff, forall_const, Finset.not_mem_empty] · intro x s hx ih f obtain ⟨g, hg⟩ := (IsPWO.of_linearOrder univ).exists_monotone_subseq (f := (f · x)) mem_univ obtain ⟨g', hg'⟩ := ih (f ∘ g) refine ⟨g'.trans g, fun a b hab => (Finset.forall_mem_cons _ _).2 ?_⟩ exact ⟨hg (OrderHomClass.mono g' hab), hg' hab⟩ section ProdLex variable {rα : α → α → Prop} {rβ : β → β → Prop} {f : γ → α} {g : γ → β} {s : Set γ} /-- Stronger version of `WellFounded.prod_lex`. Instead of requiring `rβ on g` to be well-founded,
Mathlib/Order/WellFoundedSet.lean
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/- Copyright (c) 2019 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Bhavik Mehta -/ import Mathlib.CategoryTheory.Comma.Over.Basic import Mathlib.CategoryTheory.Discrete.Basic import Mathlib.CategoryTheory.EpiMono import Mathlib.CategoryTheory.Limits.Shapes.Terminal /-! # Binary (co)products We define a category `WalkingPair`, which is the index category for a binary (co)product diagram. A convenience method `pair X Y` constructs the functor from the walking pair, hitting the given objects. We define `prod X Y` and `coprod X Y` as limits and colimits of such functors. Typeclasses `HasBinaryProducts` and `HasBinaryCoproducts` assert the existence of (co)limits shaped as walking pairs. We include lemmas for simplifying equations involving projections and coprojections, and define braiding and associating isomorphisms, and the product comparison morphism. ## References * [Stacks: Products of pairs](https://stacks.math.columbia.edu/tag/001R) * [Stacks: coproducts of pairs](https://stacks.math.columbia.edu/tag/04AN) -/ universe v v₁ u u₁ u₂ open CategoryTheory namespace CategoryTheory.Limits /-- The type of objects for the diagram indexing a binary (co)product. -/ inductive WalkingPair : Type | left | right deriving DecidableEq, Inhabited open WalkingPair /-- The equivalence swapping left and right. -/ def WalkingPair.swap : WalkingPair ≃ WalkingPair where toFun | left => right | right => left invFun | left => right | right => left left_inv j := by cases j <;> rfl right_inv j := by cases j <;> rfl @[simp] theorem WalkingPair.swap_apply_left : WalkingPair.swap left = right := rfl @[simp] theorem WalkingPair.swap_apply_right : WalkingPair.swap right = left := rfl @[simp] theorem WalkingPair.swap_symm_apply_tt : WalkingPair.swap.symm left = right := rfl @[simp] theorem WalkingPair.swap_symm_apply_ff : WalkingPair.swap.symm right = left := rfl /-- An equivalence from `WalkingPair` to `Bool`, sometimes useful when reindexing limits. -/ def WalkingPair.equivBool : WalkingPair ≃ Bool where toFun | left => true | right => false -- to match equiv.sum_equiv_sigma_bool invFun b := Bool.recOn b right left left_inv j := by cases j <;> rfl right_inv b := by cases b <;> rfl @[simp] theorem WalkingPair.equivBool_apply_left : WalkingPair.equivBool left = true := rfl @[simp] theorem WalkingPair.equivBool_apply_right : WalkingPair.equivBool right = false := rfl @[simp] theorem WalkingPair.equivBool_symm_apply_true : WalkingPair.equivBool.symm true = left := rfl @[simp] theorem WalkingPair.equivBool_symm_apply_false : WalkingPair.equivBool.symm false = right := rfl variable {C : Type u} /-- The function on the walking pair, sending the two points to `X` and `Y`. -/ def pairFunction (X Y : C) : WalkingPair → C := fun j => WalkingPair.casesOn j X Y @[simp] theorem pairFunction_left (X Y : C) : pairFunction X Y left = X := rfl @[simp] theorem pairFunction_right (X Y : C) : pairFunction X Y right = Y := rfl variable [Category.{v} C] /-- The diagram on the walking pair, sending the two points to `X` and `Y`. -/ def pair (X Y : C) : Discrete WalkingPair ⥤ C := Discrete.functor fun j => WalkingPair.casesOn j X Y @[simp] theorem pair_obj_left (X Y : C) : (pair X Y).obj ⟨left⟩ = X := rfl @[simp] theorem pair_obj_right (X Y : C) : (pair X Y).obj ⟨right⟩ = Y := rfl section variable {F G : Discrete WalkingPair ⥤ C} (f : F.obj ⟨left⟩ ⟶ G.obj ⟨left⟩) (g : F.obj ⟨right⟩ ⟶ G.obj ⟨right⟩) attribute [local aesop safe tactic (rule_sets := [CategoryTheory])] CategoryTheory.Discrete.discreteCases /-- The natural transformation between two functors out of the walking pair, specified by its components. -/ def mapPair : F ⟶ G where app | ⟨left⟩ => f | ⟨right⟩ => g naturality := fun ⟨X⟩ ⟨Y⟩ ⟨⟨u⟩⟩ => by aesop_cat @[simp] theorem mapPair_left : (mapPair f g).app ⟨left⟩ = f := rfl @[simp] theorem mapPair_right : (mapPair f g).app ⟨right⟩ = g := rfl /-- The natural isomorphism between two functors out of the walking pair, specified by its components. -/ @[simps!] def mapPairIso (f : F.obj ⟨left⟩ ≅ G.obj ⟨left⟩) (g : F.obj ⟨right⟩ ≅ G.obj ⟨right⟩) : F ≅ G := NatIso.ofComponents (fun j ↦ match j with | ⟨left⟩ => f | ⟨right⟩ => g) (fun ⟨⟨u⟩⟩ => by aesop_cat) end /-- Every functor out of the walking pair is naturally isomorphic (actually, equal) to a `pair` -/ @[simps!] def diagramIsoPair (F : Discrete WalkingPair ⥤ C) : F ≅ pair (F.obj ⟨WalkingPair.left⟩) (F.obj ⟨WalkingPair.right⟩) := mapPairIso (Iso.refl _) (Iso.refl _) section variable {D : Type u₁} [Category.{v₁} D] /-- The natural isomorphism between `pair X Y ⋙ F` and `pair (F.obj X) (F.obj Y)`. -/ def pairComp (X Y : C) (F : C ⥤ D) : pair X Y ⋙ F ≅ pair (F.obj X) (F.obj Y) := diagramIsoPair _ end /-- A binary fan is just a cone on a diagram indexing a product. -/ abbrev BinaryFan (X Y : C) := Cone (pair X Y) /-- The first projection of a binary fan. -/ abbrev BinaryFan.fst {X Y : C} (s : BinaryFan X Y) := s.π.app ⟨WalkingPair.left⟩ /-- The second projection of a binary fan. -/ abbrev BinaryFan.snd {X Y : C} (s : BinaryFan X Y) := s.π.app ⟨WalkingPair.right⟩ @[simp] theorem BinaryFan.π_app_left {X Y : C} (s : BinaryFan X Y) : s.π.app ⟨WalkingPair.left⟩ = s.fst := rfl @[simp] theorem BinaryFan.π_app_right {X Y : C} (s : BinaryFan X Y) : s.π.app ⟨WalkingPair.right⟩ = s.snd := rfl /-- Constructs an isomorphism of `BinaryFan`s out of an isomorphism of the tips that commutes with the projections. -/ def BinaryFan.ext {A B : C} {c c' : BinaryFan A B} (e : c.pt ≅ c'.pt) (h₁ : c.fst = e.hom ≫ c'.fst) (h₂ : c.snd = e.hom ≫ c'.snd) : c ≅ c' := Cones.ext e (fun j => by rcases j with ⟨⟨⟩⟩ <;> assumption) @[simp] lemma BinaryFan.ext_hom_hom {A B : C} {c c' : BinaryFan A B} (e : c.pt ≅ c'.pt) (h₁ : c.fst = e.hom ≫ c'.fst) (h₂ : c.snd = e.hom ≫ c'.snd) : (ext e h₁ h₂).hom.hom = e.hom := rfl /-- A convenient way to show that a binary fan is a limit. -/ def BinaryFan.IsLimit.mk {X Y : C} (s : BinaryFan X Y) (lift : ∀ {T : C} (_ : T ⟶ X) (_ : T ⟶ Y), T ⟶ s.pt) (hl₁ : ∀ {T : C} (f : T ⟶ X) (g : T ⟶ Y), lift f g ≫ s.fst = f) (hl₂ : ∀ {T : C} (f : T ⟶ X) (g : T ⟶ Y), lift f g ≫ s.snd = g) (uniq : ∀ {T : C} (f : T ⟶ X) (g : T ⟶ Y) (m : T ⟶ s.pt) (_ : m ≫ s.fst = f) (_ : m ≫ s.snd = g), m = lift f g) : IsLimit s := Limits.IsLimit.mk (fun t => lift (BinaryFan.fst t) (BinaryFan.snd t)) (by rintro t (rfl | rfl) · exact hl₁ _ _ · exact hl₂ _ _) fun _ _ h => uniq _ _ _ (h ⟨WalkingPair.left⟩) (h ⟨WalkingPair.right⟩) theorem BinaryFan.IsLimit.hom_ext {W X Y : C} {s : BinaryFan X Y} (h : IsLimit s) {f g : W ⟶ s.pt} (h₁ : f ≫ s.fst = g ≫ s.fst) (h₂ : f ≫ s.snd = g ≫ s.snd) : f = g := h.hom_ext fun j => Discrete.recOn j fun j => WalkingPair.casesOn j h₁ h₂ /-- A binary cofan is just a cocone on a diagram indexing a coproduct. -/ abbrev BinaryCofan (X Y : C) := Cocone (pair X Y) /-- The first inclusion of a binary cofan. -/ abbrev BinaryCofan.inl {X Y : C} (s : BinaryCofan X Y) := s.ι.app ⟨WalkingPair.left⟩ /-- The second inclusion of a binary cofan. -/ abbrev BinaryCofan.inr {X Y : C} (s : BinaryCofan X Y) := s.ι.app ⟨WalkingPair.right⟩ /-- Constructs an isomorphism of `BinaryCofan`s out of an isomorphism of the tips that commutes with the injections. -/ def BinaryCofan.ext {A B : C} {c c' : BinaryCofan A B} (e : c.pt ≅ c'.pt) (h₁ : c.inl ≫ e.hom = c'.inl) (h₂ : c.inr ≫ e.hom = c'.inr) : c ≅ c' := Cocones.ext e (fun j => by rcases j with ⟨⟨⟩⟩ <;> assumption) @[simp] lemma BinaryCofan.ext_hom_hom {A B : C} {c c' : BinaryCofan A B} (e : c.pt ≅ c'.pt) (h₁ : c.inl ≫ e.hom = c'.inl) (h₂ : c.inr ≫ e.hom = c'.inr) : (ext e h₁ h₂).hom.hom = e.hom := rfl @[simp] theorem BinaryCofan.ι_app_left {X Y : C} (s : BinaryCofan X Y) : s.ι.app ⟨WalkingPair.left⟩ = s.inl := rfl @[simp] theorem BinaryCofan.ι_app_right {X Y : C} (s : BinaryCofan X Y) : s.ι.app ⟨WalkingPair.right⟩ = s.inr := rfl /-- A convenient way to show that a binary cofan is a colimit. -/ def BinaryCofan.IsColimit.mk {X Y : C} (s : BinaryCofan X Y) (desc : ∀ {T : C} (_ : X ⟶ T) (_ : Y ⟶ T), s.pt ⟶ T) (hd₁ : ∀ {T : C} (f : X ⟶ T) (g : Y ⟶ T), s.inl ≫ desc f g = f) (hd₂ : ∀ {T : C} (f : X ⟶ T) (g : Y ⟶ T), s.inr ≫ desc f g = g) (uniq : ∀ {T : C} (f : X ⟶ T) (g : Y ⟶ T) (m : s.pt ⟶ T) (_ : s.inl ≫ m = f) (_ : s.inr ≫ m = g), m = desc f g) : IsColimit s := Limits.IsColimit.mk (fun t => desc (BinaryCofan.inl t) (BinaryCofan.inr t)) (by rintro t (rfl | rfl) · exact hd₁ _ _ · exact hd₂ _ _) fun _ _ h => uniq _ _ _ (h ⟨WalkingPair.left⟩) (h ⟨WalkingPair.right⟩) theorem BinaryCofan.IsColimit.hom_ext {W X Y : C} {s : BinaryCofan X Y} (h : IsColimit s) {f g : s.pt ⟶ W} (h₁ : s.inl ≫ f = s.inl ≫ g) (h₂ : s.inr ≫ f = s.inr ≫ g) : f = g := h.hom_ext fun j => Discrete.recOn j fun j => WalkingPair.casesOn j h₁ h₂ variable {X Y : C} section attribute [local aesop safe tactic (rule_sets := [CategoryTheory])] CategoryTheory.Discrete.discreteCases -- Porting note: would it be okay to use this more generally? attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Eq /-- A binary fan with vertex `P` consists of the two projections `π₁ : P ⟶ X` and `π₂ : P ⟶ Y`. -/ @[simps pt] def BinaryFan.mk {P : C} (π₁ : P ⟶ X) (π₂ : P ⟶ Y) : BinaryFan X Y where pt := P π := { app := fun | { as := j } => match j with | left => π₁ | right => π₂ } /-- A binary cofan with vertex `P` consists of the two inclusions `ι₁ : X ⟶ P` and `ι₂ : Y ⟶ P`. -/ @[simps pt] def BinaryCofan.mk {P : C} (ι₁ : X ⟶ P) (ι₂ : Y ⟶ P) : BinaryCofan X Y where pt := P ι := { app := fun | { as := j } => match j with | left => ι₁ | right => ι₂ } end @[simp] theorem BinaryFan.mk_fst {P : C} (π₁ : P ⟶ X) (π₂ : P ⟶ Y) : (BinaryFan.mk π₁ π₂).fst = π₁ := rfl @[simp] theorem BinaryFan.mk_snd {P : C} (π₁ : P ⟶ X) (π₂ : P ⟶ Y) : (BinaryFan.mk π₁ π₂).snd = π₂ := rfl @[simp] theorem BinaryCofan.mk_inl {P : C} (ι₁ : X ⟶ P) (ι₂ : Y ⟶ P) : (BinaryCofan.mk ι₁ ι₂).inl = ι₁ := rfl @[simp] theorem BinaryCofan.mk_inr {P : C} (ι₁ : X ⟶ P) (ι₂ : Y ⟶ P) : (BinaryCofan.mk ι₁ ι₂).inr = ι₂ := rfl /-- Every `BinaryFan` is isomorphic to an application of `BinaryFan.mk`. -/ def isoBinaryFanMk {X Y : C} (c : BinaryFan X Y) : c ≅ BinaryFan.mk c.fst c.snd := Cones.ext (Iso.refl _) fun ⟨l⟩ => by cases l; repeat simp /-- Every `BinaryFan` is isomorphic to an application of `BinaryFan.mk`. -/ def isoBinaryCofanMk {X Y : C} (c : BinaryCofan X Y) : c ≅ BinaryCofan.mk c.inl c.inr := Cocones.ext (Iso.refl _) fun ⟨l⟩ => by cases l; repeat simp /-- This is a more convenient formulation to show that a `BinaryFan` constructed using `BinaryFan.mk` is a limit cone. -/ def BinaryFan.isLimitMk {W : C} {fst : W ⟶ X} {snd : W ⟶ Y} (lift : ∀ s : BinaryFan X Y, s.pt ⟶ W) (fac_left : ∀ s : BinaryFan X Y, lift s ≫ fst = s.fst) (fac_right : ∀ s : BinaryFan X Y, lift s ≫ snd = s.snd) (uniq : ∀ (s : BinaryFan X Y) (m : s.pt ⟶ W) (_ : m ≫ fst = s.fst) (_ : m ≫ snd = s.snd), m = lift s) : IsLimit (BinaryFan.mk fst snd) := { lift := lift fac := fun s j => by rcases j with ⟨⟨⟩⟩ exacts [fac_left s, fac_right s] uniq := fun s m w => uniq s m (w ⟨WalkingPair.left⟩) (w ⟨WalkingPair.right⟩) } /-- This is a more convenient formulation to show that a `BinaryCofan` constructed using `BinaryCofan.mk` is a colimit cocone. -/ def BinaryCofan.isColimitMk {W : C} {inl : X ⟶ W} {inr : Y ⟶ W} (desc : ∀ s : BinaryCofan X Y, W ⟶ s.pt) (fac_left : ∀ s : BinaryCofan X Y, inl ≫ desc s = s.inl) (fac_right : ∀ s : BinaryCofan X Y, inr ≫ desc s = s.inr) (uniq : ∀ (s : BinaryCofan X Y) (m : W ⟶ s.pt) (_ : inl ≫ m = s.inl) (_ : inr ≫ m = s.inr), m = desc s) : IsColimit (BinaryCofan.mk inl inr) := { desc := desc fac := fun s j => by rcases j with ⟨⟨⟩⟩ exacts [fac_left s, fac_right s] uniq := fun s m w => uniq s m (w ⟨WalkingPair.left⟩) (w ⟨WalkingPair.right⟩) } /-- If `s` is a limit binary fan over `X` and `Y`, then every pair of morphisms `f : W ⟶ X` and `g : W ⟶ Y` induces a morphism `l : W ⟶ s.pt` satisfying `l ≫ s.fst = f` and `l ≫ s.snd = g`. -/ @[simps] def BinaryFan.IsLimit.lift' {W X Y : C} {s : BinaryFan X Y} (h : IsLimit s) (f : W ⟶ X) (g : W ⟶ Y) : { l : W ⟶ s.pt // l ≫ s.fst = f ∧ l ≫ s.snd = g } := ⟨h.lift <| BinaryFan.mk f g, h.fac _ _, h.fac _ _⟩ /-- If `s` is a colimit binary cofan over `X` and `Y`,, then every pair of morphisms `f : X ⟶ W` and `g : Y ⟶ W` induces a morphism `l : s.pt ⟶ W` satisfying `s.inl ≫ l = f` and `s.inr ≫ l = g`. -/ @[simps] def BinaryCofan.IsColimit.desc' {W X Y : C} {s : BinaryCofan X Y} (h : IsColimit s) (f : X ⟶ W) (g : Y ⟶ W) : { l : s.pt ⟶ W // s.inl ≫ l = f ∧ s.inr ≫ l = g } := ⟨h.desc <| BinaryCofan.mk f g, h.fac _ _, h.fac _ _⟩ /-- Binary products are symmetric. -/ def BinaryFan.isLimitFlip {X Y : C} {c : BinaryFan X Y} (hc : IsLimit c) : IsLimit (BinaryFan.mk c.snd c.fst) := BinaryFan.isLimitMk (fun s => hc.lift (BinaryFan.mk s.snd s.fst)) (fun _ => hc.fac _ _) (fun _ => hc.fac _ _) fun s _ e₁ e₂ => BinaryFan.IsLimit.hom_ext hc (e₂.trans (hc.fac (BinaryFan.mk s.snd s.fst) ⟨WalkingPair.left⟩).symm) (e₁.trans (hc.fac (BinaryFan.mk s.snd s.fst) ⟨WalkingPair.right⟩).symm) theorem BinaryFan.isLimit_iff_isIso_fst {X Y : C} (h : IsTerminal Y) (c : BinaryFan X Y) : Nonempty (IsLimit c) ↔ IsIso c.fst := by constructor · rintro ⟨H⟩ obtain ⟨l, hl, -⟩ := BinaryFan.IsLimit.lift' H (𝟙 X) (h.from X) exact ⟨⟨l, BinaryFan.IsLimit.hom_ext H (by simpa [hl, -Category.comp_id] using Category.comp_id _) (h.hom_ext _ _), hl⟩⟩ · intro exact ⟨BinaryFan.IsLimit.mk _ (fun f _ => f ≫ inv c.fst) (fun _ _ => by simp) (fun _ _ => h.hom_ext _ _) fun _ _ _ e _ => by simp [← e]⟩ theorem BinaryFan.isLimit_iff_isIso_snd {X Y : C} (h : IsTerminal X) (c : BinaryFan X Y) : Nonempty (IsLimit c) ↔ IsIso c.snd := by refine Iff.trans ?_ (BinaryFan.isLimit_iff_isIso_fst h (BinaryFan.mk c.snd c.fst)) exact ⟨fun h => ⟨BinaryFan.isLimitFlip h.some⟩, fun h => ⟨(BinaryFan.isLimitFlip h.some).ofIsoLimit (isoBinaryFanMk c).symm⟩⟩ /-- If `X' ≅ X`, then `X × Y` also is the product of `X'` and `Y`. -/ noncomputable def BinaryFan.isLimitCompLeftIso {X Y X' : C} (c : BinaryFan X Y) (f : X ⟶ X') [IsIso f] (h : IsLimit c) : IsLimit (BinaryFan.mk (c.fst ≫ f) c.snd) := by fapply BinaryFan.isLimitMk · exact fun s => h.lift (BinaryFan.mk (s.fst ≫ inv f) s.snd) · intro s -- Porting note: simp timed out here simp only [Category.comp_id,BinaryFan.π_app_left,IsIso.inv_hom_id, BinaryFan.mk_fst,IsLimit.fac_assoc,eq_self_iff_true,Category.assoc] · intro s -- Porting note: simp timed out here simp only [BinaryFan.π_app_right,BinaryFan.mk_snd,eq_self_iff_true,IsLimit.fac] · intro s m e₁ e₂ -- Porting note: simpa timed out here also apply BinaryFan.IsLimit.hom_ext h · simpa only [BinaryFan.π_app_left,BinaryFan.mk_fst,Category.assoc,IsLimit.fac,IsIso.eq_comp_inv] · simpa only [BinaryFan.π_app_right,BinaryFan.mk_snd,IsLimit.fac] /-- If `Y' ≅ Y`, then `X x Y` also is the product of `X` and `Y'`. -/ noncomputable def BinaryFan.isLimitCompRightIso {X Y Y' : C} (c : BinaryFan X Y) (f : Y ⟶ Y') [IsIso f] (h : IsLimit c) : IsLimit (BinaryFan.mk c.fst (c.snd ≫ f)) := BinaryFan.isLimitFlip <| BinaryFan.isLimitCompLeftIso _ f (BinaryFan.isLimitFlip h) /-- Binary coproducts are symmetric. -/ def BinaryCofan.isColimitFlip {X Y : C} {c : BinaryCofan X Y} (hc : IsColimit c) : IsColimit (BinaryCofan.mk c.inr c.inl) := BinaryCofan.isColimitMk (fun s => hc.desc (BinaryCofan.mk s.inr s.inl)) (fun _ => hc.fac _ _) (fun _ => hc.fac _ _) fun s _ e₁ e₂ => BinaryCofan.IsColimit.hom_ext hc (e₂.trans (hc.fac (BinaryCofan.mk s.inr s.inl) ⟨WalkingPair.left⟩).symm) (e₁.trans (hc.fac (BinaryCofan.mk s.inr s.inl) ⟨WalkingPair.right⟩).symm) theorem BinaryCofan.isColimit_iff_isIso_inl {X Y : C} (h : IsInitial Y) (c : BinaryCofan X Y) : Nonempty (IsColimit c) ↔ IsIso c.inl := by constructor · rintro ⟨H⟩ obtain ⟨l, hl, -⟩ := BinaryCofan.IsColimit.desc' H (𝟙 X) (h.to X) refine ⟨⟨l, hl, BinaryCofan.IsColimit.hom_ext H (?_) (h.hom_ext _ _)⟩⟩ rw [Category.comp_id] have e : (inl c ≫ l) ≫ inl c = 𝟙 X ≫ inl c := congrArg (·≫inl c) hl rwa [Category.assoc,Category.id_comp] at e · intro exact ⟨BinaryCofan.IsColimit.mk _ (fun f _ => inv c.inl ≫ f) (fun _ _ => IsIso.hom_inv_id_assoc _ _) (fun _ _ => h.hom_ext _ _) fun _ _ _ e _ => (IsIso.eq_inv_comp _).mpr e⟩ theorem BinaryCofan.isColimit_iff_isIso_inr {X Y : C} (h : IsInitial X) (c : BinaryCofan X Y) : Nonempty (IsColimit c) ↔ IsIso c.inr := by refine Iff.trans ?_ (BinaryCofan.isColimit_iff_isIso_inl h (BinaryCofan.mk c.inr c.inl)) exact ⟨fun h => ⟨BinaryCofan.isColimitFlip h.some⟩, fun h => ⟨(BinaryCofan.isColimitFlip h.some).ofIsoColimit (isoBinaryCofanMk c).symm⟩⟩ /-- If `X' ≅ X`, then `X ⨿ Y` also is the coproduct of `X'` and `Y`. -/ noncomputable def BinaryCofan.isColimitCompLeftIso {X Y X' : C} (c : BinaryCofan X Y) (f : X' ⟶ X) [IsIso f] (h : IsColimit c) : IsColimit (BinaryCofan.mk (f ≫ c.inl) c.inr) := by fapply BinaryCofan.isColimitMk · exact fun s => h.desc (BinaryCofan.mk (inv f ≫ s.inl) s.inr) · intro s -- Porting note: simp timed out here too simp only [IsColimit.fac,BinaryCofan.ι_app_left,eq_self_iff_true, Category.assoc,BinaryCofan.mk_inl,IsIso.hom_inv_id_assoc] · intro s -- Porting note: simp timed out here too simp only [IsColimit.fac,BinaryCofan.ι_app_right,eq_self_iff_true,BinaryCofan.mk_inr] · intro s m e₁ e₂ apply BinaryCofan.IsColimit.hom_ext h · rw [← cancel_epi f] -- Porting note: simp timed out here too simpa only [IsColimit.fac,BinaryCofan.ι_app_left,eq_self_iff_true, Category.assoc,BinaryCofan.mk_inl,IsIso.hom_inv_id_assoc] using e₁ -- Porting note: simp timed out here too · simpa only [IsColimit.fac,BinaryCofan.ι_app_right,eq_self_iff_true,BinaryCofan.mk_inr] /-- If `Y' ≅ Y`, then `X ⨿ Y` also is the coproduct of `X` and `Y'`. -/ noncomputable def BinaryCofan.isColimitCompRightIso {X Y Y' : C} (c : BinaryCofan X Y) (f : Y' ⟶ Y) [IsIso f] (h : IsColimit c) : IsColimit (BinaryCofan.mk c.inl (f ≫ c.inr)) := BinaryCofan.isColimitFlip <| BinaryCofan.isColimitCompLeftIso _ f (BinaryCofan.isColimitFlip h) /-- An abbreviation for `HasLimit (pair X Y)`. -/ abbrev HasBinaryProduct (X Y : C) := HasLimit (pair X Y) /-- An abbreviation for `HasColimit (pair X Y)`. -/ abbrev HasBinaryCoproduct (X Y : C) := HasColimit (pair X Y) /-- If we have a product of `X` and `Y`, we can access it using `prod X Y` or `X ⨯ Y`. -/ noncomputable abbrev prod (X Y : C) [HasBinaryProduct X Y] := limit (pair X Y) /-- If we have a coproduct of `X` and `Y`, we can access it using `coprod X Y` or `X ⨿ Y`. -/ noncomputable abbrev coprod (X Y : C) [HasBinaryCoproduct X Y] := colimit (pair X Y) /-- Notation for the product -/ notation:20 X " ⨯ " Y:20 => prod X Y /-- Notation for the coproduct -/ notation:20 X " ⨿ " Y:20 => coprod X Y /-- The projection map to the first component of the product. -/ noncomputable abbrev prod.fst {X Y : C} [HasBinaryProduct X Y] : X ⨯ Y ⟶ X := limit.π (pair X Y) ⟨WalkingPair.left⟩ /-- The projection map to the second component of the product. -/ noncomputable abbrev prod.snd {X Y : C} [HasBinaryProduct X Y] : X ⨯ Y ⟶ Y := limit.π (pair X Y) ⟨WalkingPair.right⟩ /-- The inclusion map from the first component of the coproduct. -/ noncomputable abbrev coprod.inl {X Y : C} [HasBinaryCoproduct X Y] : X ⟶ X ⨿ Y := colimit.ι (pair X Y) ⟨WalkingPair.left⟩ /-- The inclusion map from the second component of the coproduct. -/ noncomputable abbrev coprod.inr {X Y : C} [HasBinaryCoproduct X Y] : Y ⟶ X ⨿ Y := colimit.ι (pair X Y) ⟨WalkingPair.right⟩ /-- The binary fan constructed from the projection maps is a limit. -/ noncomputable def prodIsProd (X Y : C) [HasBinaryProduct X Y] : IsLimit (BinaryFan.mk (prod.fst : X ⨯ Y ⟶ X) prod.snd) := (limit.isLimit _).ofIsoLimit (Cones.ext (Iso.refl _) (fun ⟨u⟩ => by cases u · dsimp; simp only [Category.id_comp]; rfl · dsimp; simp only [Category.id_comp]; rfl )) /-- The binary cofan constructed from the coprojection maps is a colimit. -/ noncomputable def coprodIsCoprod (X Y : C) [HasBinaryCoproduct X Y] : IsColimit (BinaryCofan.mk (coprod.inl : X ⟶ X ⨿ Y) coprod.inr) := (colimit.isColimit _).ofIsoColimit (Cocones.ext (Iso.refl _) (fun ⟨u⟩ => by cases u · dsimp; simp only [Category.comp_id] · dsimp; simp only [Category.comp_id] )) @[ext 1100] theorem prod.hom_ext {W X Y : C} [HasBinaryProduct X Y] {f g : W ⟶ X ⨯ Y} (h₁ : f ≫ prod.fst = g ≫ prod.fst) (h₂ : f ≫ prod.snd = g ≫ prod.snd) : f = g := BinaryFan.IsLimit.hom_ext (limit.isLimit _) h₁ h₂ @[ext 1100] theorem coprod.hom_ext {W X Y : C} [HasBinaryCoproduct X Y] {f g : X ⨿ Y ⟶ W} (h₁ : coprod.inl ≫ f = coprod.inl ≫ g) (h₂ : coprod.inr ≫ f = coprod.inr ≫ g) : f = g := BinaryCofan.IsColimit.hom_ext (colimit.isColimit _) h₁ h₂ /-- If the product of `X` and `Y` exists, then every pair of morphisms `f : W ⟶ X` and `g : W ⟶ Y` induces a morphism `prod.lift f g : W ⟶ X ⨯ Y`. -/ noncomputable abbrev prod.lift {W X Y : C} [HasBinaryProduct X Y] (f : W ⟶ X) (g : W ⟶ Y) : W ⟶ X ⨯ Y := limit.lift _ (BinaryFan.mk f g) /-- diagonal arrow of the binary product in the category `fam I` -/ noncomputable abbrev diag (X : C) [HasBinaryProduct X X] : X ⟶ X ⨯ X := prod.lift (𝟙 _) (𝟙 _) /-- If the coproduct of `X` and `Y` exists, then every pair of morphisms `f : X ⟶ W` and `g : Y ⟶ W` induces a morphism `coprod.desc f g : X ⨿ Y ⟶ W`. -/ noncomputable abbrev coprod.desc {W X Y : C} [HasBinaryCoproduct X Y] (f : X ⟶ W) (g : Y ⟶ W) : X ⨿ Y ⟶ W := colimit.desc _ (BinaryCofan.mk f g) /-- codiagonal arrow of the binary coproduct -/ noncomputable abbrev codiag (X : C) [HasBinaryCoproduct X X] : X ⨿ X ⟶ X := coprod.desc (𝟙 _) (𝟙 _) @[reassoc] theorem prod.lift_fst {W X Y : C} [HasBinaryProduct X Y] (f : W ⟶ X) (g : W ⟶ Y) : prod.lift f g ≫ prod.fst = f := limit.lift_π _ _ @[reassoc] theorem prod.lift_snd {W X Y : C} [HasBinaryProduct X Y] (f : W ⟶ X) (g : W ⟶ Y) : prod.lift f g ≫ prod.snd = g := limit.lift_π _ _ @[reassoc] theorem coprod.inl_desc {W X Y : C} [HasBinaryCoproduct X Y] (f : X ⟶ W) (g : Y ⟶ W) : coprod.inl ≫ coprod.desc f g = f := colimit.ι_desc _ _ @[reassoc] theorem coprod.inr_desc {W X Y : C} [HasBinaryCoproduct X Y] (f : X ⟶ W) (g : Y ⟶ W) : coprod.inr ≫ coprod.desc f g = g := colimit.ι_desc _ _ instance prod.mono_lift_of_mono_left {W X Y : C} [HasBinaryProduct X Y] (f : W ⟶ X) (g : W ⟶ Y) [Mono f] : Mono (prod.lift f g) := mono_of_mono_fac <| prod.lift_fst _ _ instance prod.mono_lift_of_mono_right {W X Y : C} [HasBinaryProduct X Y] (f : W ⟶ X) (g : W ⟶ Y) [Mono g] : Mono (prod.lift f g) := mono_of_mono_fac <| prod.lift_snd _ _ instance coprod.epi_desc_of_epi_left {W X Y : C} [HasBinaryCoproduct X Y] (f : X ⟶ W) (g : Y ⟶ W) [Epi f] : Epi (coprod.desc f g) := epi_of_epi_fac <| coprod.inl_desc _ _ instance coprod.epi_desc_of_epi_right {W X Y : C} [HasBinaryCoproduct X Y] (f : X ⟶ W) (g : Y ⟶ W) [Epi g] : Epi (coprod.desc f g) := epi_of_epi_fac <| coprod.inr_desc _ _ /-- If the product of `X` and `Y` exists, then every pair of morphisms `f : W ⟶ X` and `g : W ⟶ Y` induces a morphism `l : W ⟶ X ⨯ Y` satisfying `l ≫ Prod.fst = f` and `l ≫ Prod.snd = g`. -/ noncomputable def prod.lift' {W X Y : C} [HasBinaryProduct X Y] (f : W ⟶ X) (g : W ⟶ Y) : { l : W ⟶ X ⨯ Y // l ≫ prod.fst = f ∧ l ≫ prod.snd = g } := ⟨prod.lift f g, prod.lift_fst _ _, prod.lift_snd _ _⟩ /-- If the coproduct of `X` and `Y` exists, then every pair of morphisms `f : X ⟶ W` and `g : Y ⟶ W` induces a morphism `l : X ⨿ Y ⟶ W` satisfying `coprod.inl ≫ l = f` and `coprod.inr ≫ l = g`. -/ noncomputable def coprod.desc' {W X Y : C} [HasBinaryCoproduct X Y] (f : X ⟶ W) (g : Y ⟶ W) : { l : X ⨿ Y ⟶ W // coprod.inl ≫ l = f ∧ coprod.inr ≫ l = g } := ⟨coprod.desc f g, coprod.inl_desc _ _, coprod.inr_desc _ _⟩ /-- If the products `W ⨯ X` and `Y ⨯ Z` exist, then every pair of morphisms `f : W ⟶ Y` and `g : X ⟶ Z` induces a morphism `prod.map f g : W ⨯ X ⟶ Y ⨯ Z`. -/ noncomputable def prod.map {W X Y Z : C} [HasBinaryProduct W X] [HasBinaryProduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) : W ⨯ X ⟶ Y ⨯ Z := limMap (mapPair f g) /-- If the coproducts `W ⨿ X` and `Y ⨿ Z` exist, then every pair of morphisms `f : W ⟶ Y` and `g : W ⟶ Z` induces a morphism `coprod.map f g : W ⨿ X ⟶ Y ⨿ Z`. -/ noncomputable def coprod.map {W X Y Z : C} [HasBinaryCoproduct W X] [HasBinaryCoproduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) : W ⨿ X ⟶ Y ⨿ Z := colimMap (mapPair f g) noncomputable section ProdLemmas -- Making the reassoc version of this a simp lemma seems to be more harmful than helpful. @[reassoc, simp] theorem prod.comp_lift {V W X Y : C} [HasBinaryProduct X Y] (f : V ⟶ W) (g : W ⟶ X) (h : W ⟶ Y) : f ≫ prod.lift g h = prod.lift (f ≫ g) (f ≫ h) := by ext <;> simp theorem prod.comp_diag {X Y : C} [HasBinaryProduct Y Y] (f : X ⟶ Y) : f ≫ diag Y = prod.lift f f := by simp @[reassoc (attr := simp)] theorem prod.map_fst {W X Y Z : C} [HasBinaryProduct W X] [HasBinaryProduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) : prod.map f g ≫ prod.fst = prod.fst ≫ f := limMap_π _ _ @[reassoc (attr := simp)] theorem prod.map_snd {W X Y Z : C} [HasBinaryProduct W X] [HasBinaryProduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) : prod.map f g ≫ prod.snd = prod.snd ≫ g := limMap_π _ _ @[simp] theorem prod.map_id_id {X Y : C} [HasBinaryProduct X Y] : prod.map (𝟙 X) (𝟙 Y) = 𝟙 _ := by ext <;> simp @[simp] theorem prod.lift_fst_snd {X Y : C} [HasBinaryProduct X Y] : prod.lift prod.fst prod.snd = 𝟙 (X ⨯ Y) := by ext <;> simp @[reassoc (attr := simp)] theorem prod.lift_map {V W X Y Z : C} [HasBinaryProduct W X] [HasBinaryProduct Y Z] (f : V ⟶ W) (g : V ⟶ X) (h : W ⟶ Y) (k : X ⟶ Z) : prod.lift f g ≫ prod.map h k = prod.lift (f ≫ h) (g ≫ k) := by ext <;> simp @[simp] theorem prod.lift_fst_comp_snd_comp {W X Y Z : C} [HasBinaryProduct W Y] [HasBinaryProduct X Z] (g : W ⟶ X) (g' : Y ⟶ Z) : prod.lift (prod.fst ≫ g) (prod.snd ≫ g') = prod.map g g' := by rw [← prod.lift_map] simp -- We take the right hand side here to be simp normal form, as this way composition lemmas for -- `f ≫ h` and `g ≫ k` can fire (eg `id_comp`) , while `map_fst` and `map_snd` can still work just -- as well. @[reassoc (attr := simp)] theorem prod.map_map {A₁ A₂ A₃ B₁ B₂ B₃ : C} [HasBinaryProduct A₁ B₁] [HasBinaryProduct A₂ B₂] [HasBinaryProduct A₃ B₃] (f : A₁ ⟶ A₂) (g : B₁ ⟶ B₂) (h : A₂ ⟶ A₃) (k : B₂ ⟶ B₃) : prod.map f g ≫ prod.map h k = prod.map (f ≫ h) (g ≫ k) := by ext <;> simp -- TODO: is it necessary to weaken the assumption here? @[reassoc] theorem prod.map_swap {A B X Y : C} (f : A ⟶ B) (g : X ⟶ Y) [HasLimitsOfShape (Discrete WalkingPair) C] : prod.map (𝟙 X) f ≫ prod.map g (𝟙 B) = prod.map g (𝟙 A) ≫ prod.map (𝟙 Y) f := by simp @[reassoc] theorem prod.map_comp_id {X Y Z W : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasBinaryProduct X W] [HasBinaryProduct Z W] [HasBinaryProduct Y W] : prod.map (f ≫ g) (𝟙 W) = prod.map f (𝟙 W) ≫ prod.map g (𝟙 W) := by simp @[reassoc] theorem prod.map_id_comp {X Y Z W : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasBinaryProduct W X] [HasBinaryProduct W Y] [HasBinaryProduct W Z] : prod.map (𝟙 W) (f ≫ g) = prod.map (𝟙 W) f ≫ prod.map (𝟙 W) g := by simp /-- If the products `W ⨯ X` and `Y ⨯ Z` exist, then every pair of isomorphisms `f : W ≅ Y` and `g : X ≅ Z` induces an isomorphism `prod.mapIso f g : W ⨯ X ≅ Y ⨯ Z`. -/ @[simps] def prod.mapIso {W X Y Z : C} [HasBinaryProduct W X] [HasBinaryProduct Y Z] (f : W ≅ Y) (g : X ≅ Z) : W ⨯ X ≅ Y ⨯ Z where hom := prod.map f.hom g.hom inv := prod.map f.inv g.inv instance isIso_prod {W X Y Z : C} [HasBinaryProduct W X] [HasBinaryProduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) [IsIso f] [IsIso g] : IsIso (prod.map f g) := (prod.mapIso (asIso f) (asIso g)).isIso_hom instance prod.map_mono {C : Type*} [Category C] {W X Y Z : C} (f : W ⟶ Y) (g : X ⟶ Z) [Mono f] [Mono g] [HasBinaryProduct W X] [HasBinaryProduct Y Z] : Mono (prod.map f g) := ⟨fun i₁ i₂ h => by ext · rw [← cancel_mono f] simpa using congr_arg (fun f => f ≫ prod.fst) h · rw [← cancel_mono g] simpa using congr_arg (fun f => f ≫ prod.snd) h⟩ @[reassoc] theorem prod.diag_map {X Y : C} (f : X ⟶ Y) [HasBinaryProduct X X] [HasBinaryProduct Y Y] : diag X ≫ prod.map f f = f ≫ diag Y := by simp @[reassoc] theorem prod.diag_map_fst_snd {X Y : C} [HasBinaryProduct X Y] [HasBinaryProduct (X ⨯ Y) (X ⨯ Y)] : diag (X ⨯ Y) ≫ prod.map prod.fst prod.snd = 𝟙 (X ⨯ Y) := by simp @[reassoc] theorem prod.diag_map_fst_snd_comp [HasLimitsOfShape (Discrete WalkingPair) C] {X X' Y Y' : C} (g : X ⟶ Y) (g' : X' ⟶ Y') : diag (X ⨯ X') ≫ prod.map (prod.fst ≫ g) (prod.snd ≫ g') = prod.map g g' := by simp instance {X : C} [HasBinaryProduct X X] : IsSplitMono (diag X) := IsSplitMono.mk' { retraction := prod.fst } end ProdLemmas noncomputable section CoprodLemmas @[reassoc, simp] theorem coprod.desc_comp {V W X Y : C} [HasBinaryCoproduct X Y] (f : V ⟶ W) (g : X ⟶ V) (h : Y ⟶ V) : coprod.desc g h ≫ f = coprod.desc (g ≫ f) (h ≫ f) := by ext <;> simp theorem coprod.diag_comp {X Y : C} [HasBinaryCoproduct X X] (f : X ⟶ Y) : codiag X ≫ f = coprod.desc f f := by simp @[reassoc (attr := simp)] theorem coprod.inl_map {W X Y Z : C} [HasBinaryCoproduct W X] [HasBinaryCoproduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) : coprod.inl ≫ coprod.map f g = f ≫ coprod.inl := ι_colimMap _ _ @[reassoc (attr := simp)] theorem coprod.inr_map {W X Y Z : C} [HasBinaryCoproduct W X] [HasBinaryCoproduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) : coprod.inr ≫ coprod.map f g = g ≫ coprod.inr := ι_colimMap _ _ @[simp] theorem coprod.map_id_id {X Y : C} [HasBinaryCoproduct X Y] : coprod.map (𝟙 X) (𝟙 Y) = 𝟙 _ := by ext <;> simp @[simp] theorem coprod.desc_inl_inr {X Y : C} [HasBinaryCoproduct X Y] : coprod.desc coprod.inl coprod.inr = 𝟙 (X ⨿ Y) := by ext <;> simp -- The simp linter says simp can prove the reassoc version of this lemma. @[reassoc, simp] theorem coprod.map_desc {S T U V W : C} [HasBinaryCoproduct U W] [HasBinaryCoproduct T V] (f : U ⟶ S) (g : W ⟶ S) (h : T ⟶ U) (k : V ⟶ W) : coprod.map h k ≫ coprod.desc f g = coprod.desc (h ≫ f) (k ≫ g) := by ext <;> simp @[simp] theorem coprod.desc_comp_inl_comp_inr {W X Y Z : C} [HasBinaryCoproduct W Y] [HasBinaryCoproduct X Z] (g : W ⟶ X) (g' : Y ⟶ Z) : coprod.desc (g ≫ coprod.inl) (g' ≫ coprod.inr) = coprod.map g g' := by rw [← coprod.map_desc]; simp -- We take the right hand side here to be simp normal form, as this way composition lemmas for -- `f ≫ h` and `g ≫ k` can fire (eg `id_comp`) , while `inl_map` and `inr_map` can still work just -- as well. @[reassoc (attr := simp)] theorem coprod.map_map {A₁ A₂ A₃ B₁ B₂ B₃ : C} [HasBinaryCoproduct A₁ B₁] [HasBinaryCoproduct A₂ B₂] [HasBinaryCoproduct A₃ B₃] (f : A₁ ⟶ A₂) (g : B₁ ⟶ B₂) (h : A₂ ⟶ A₃) (k : B₂ ⟶ B₃) : coprod.map f g ≫ coprod.map h k = coprod.map (f ≫ h) (g ≫ k) := by ext <;> simp -- I don't think it's a good idea to make any of the following three simp lemmas. @[reassoc] theorem coprod.map_swap {A B X Y : C} (f : A ⟶ B) (g : X ⟶ Y) [HasColimitsOfShape (Discrete WalkingPair) C] : coprod.map (𝟙 X) f ≫ coprod.map g (𝟙 B) = coprod.map g (𝟙 A) ≫ coprod.map (𝟙 Y) f := by simp @[reassoc] theorem coprod.map_comp_id {X Y Z W : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasBinaryCoproduct Z W] [HasBinaryCoproduct Y W] [HasBinaryCoproduct X W] : coprod.map (f ≫ g) (𝟙 W) = coprod.map f (𝟙 W) ≫ coprod.map g (𝟙 W) := by simp @[reassoc] theorem coprod.map_id_comp {X Y Z W : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasBinaryCoproduct W X] [HasBinaryCoproduct W Y] [HasBinaryCoproduct W Z] : coprod.map (𝟙 W) (f ≫ g) = coprod.map (𝟙 W) f ≫ coprod.map (𝟙 W) g := by simp /-- If the coproducts `W ⨿ X` and `Y ⨿ Z` exist, then every pair of isomorphisms `f : W ≅ Y` and `g : W ≅ Z` induces an isomorphism `coprod.mapIso f g : W ⨿ X ≅ Y ⨿ Z`. -/ @[simps] def coprod.mapIso {W X Y Z : C} [HasBinaryCoproduct W X] [HasBinaryCoproduct Y Z] (f : W ≅ Y) (g : X ≅ Z) : W ⨿ X ≅ Y ⨿ Z where hom := coprod.map f.hom g.hom inv := coprod.map f.inv g.inv instance isIso_coprod {W X Y Z : C} [HasBinaryCoproduct W X] [HasBinaryCoproduct Y Z] (f : W ⟶ Y) (g : X ⟶ Z) [IsIso f] [IsIso g] : IsIso (coprod.map f g) := (coprod.mapIso (asIso f) (asIso g)).isIso_hom instance coprod.map_epi {C : Type*} [Category C] {W X Y Z : C} (f : W ⟶ Y) (g : X ⟶ Z) [Epi f] [Epi g] [HasBinaryCoproduct W X] [HasBinaryCoproduct Y Z] : Epi (coprod.map f g) := ⟨fun i₁ i₂ h => by ext · rw [← cancel_epi f] simpa using congr_arg (fun f => coprod.inl ≫ f) h · rw [← cancel_epi g] simpa using congr_arg (fun f => coprod.inr ≫ f) h⟩ @[reassoc] theorem coprod.map_codiag {X Y : C} (f : X ⟶ Y) [HasBinaryCoproduct X X] [HasBinaryCoproduct Y Y] : coprod.map f f ≫ codiag Y = codiag X ≫ f := by simp @[reassoc] theorem coprod.map_inl_inr_codiag {X Y : C} [HasBinaryCoproduct X Y] [HasBinaryCoproduct (X ⨿ Y) (X ⨿ Y)] : coprod.map coprod.inl coprod.inr ≫ codiag (X ⨿ Y) = 𝟙 (X ⨿ Y) := by simp @[reassoc] theorem coprod.map_comp_inl_inr_codiag [HasColimitsOfShape (Discrete WalkingPair) C] {X X' Y Y' : C} (g : X ⟶ Y) (g' : X' ⟶ Y') : coprod.map (g ≫ coprod.inl) (g' ≫ coprod.inr) ≫ codiag (Y ⨿ Y') = coprod.map g g' := by simp end CoprodLemmas variable (C) /-- `HasBinaryProducts` represents a choice of product for every pair of objects. -/ @[stacks 001T] abbrev HasBinaryProducts := HasLimitsOfShape (Discrete WalkingPair) C /-- `HasBinaryCoproducts` represents a choice of coproduct for every pair of objects. -/ @[stacks 04AP] abbrev HasBinaryCoproducts :=
HasColimitsOfShape (Discrete WalkingPair) C
Mathlib/CategoryTheory/Limits/Shapes/BinaryProducts.lean
848
849
/- Copyright (c) 2019 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Yaël Dillies -/ import Mathlib.Algebra.Module.BigOperators import Mathlib.GroupTheory.Perm.Basic import Mathlib.GroupTheory.Perm.Finite import Mathlib.GroupTheory.Perm.List import Mathlib.GroupTheory.Perm.Sign /-! # Cycles of a permutation This file starts the theory of cycles in permutations. ## Main definitions In the following, `f : Equiv.Perm β`. * `Equiv.Perm.SameCycle`: `f.SameCycle x y` when `x` and `y` are in the same cycle of `f`. * `Equiv.Perm.IsCycle`: `f` is a cycle if any two nonfixed points of `f` are related by repeated applications of `f`, and `f` is not the identity. * `Equiv.Perm.IsCycleOn`: `f` is a cycle on a set `s` when any two points of `s` are related by repeated applications of `f`. ## Notes `Equiv.Perm.IsCycle` and `Equiv.Perm.IsCycleOn` are different in three ways: * `IsCycle` is about the entire type while `IsCycleOn` is restricted to a set. * `IsCycle` forbids the identity while `IsCycleOn` allows it (if `s` is a subsingleton). * `IsCycleOn` forbids fixed points on `s` (if `s` is nontrivial), while `IsCycle` allows them. -/ open Equiv Function Finset variable {ι α β : Type*} namespace Equiv.Perm /-! ### `SameCycle` -/ section SameCycle variable {f g : Perm α} {p : α → Prop} {x y z : α} /-- The equivalence relation indicating that two points are in the same cycle of a permutation. -/ def SameCycle (f : Perm α) (x y : α) : Prop := ∃ i : ℤ, (f ^ i) x = y @[refl] theorem SameCycle.refl (f : Perm α) (x : α) : SameCycle f x x := ⟨0, rfl⟩ theorem SameCycle.rfl : SameCycle f x x := SameCycle.refl _ _ protected theorem _root_.Eq.sameCycle (h : x = y) (f : Perm α) : f.SameCycle x y := by rw [h] @[symm] theorem SameCycle.symm : SameCycle f x y → SameCycle f y x := fun ⟨i, hi⟩ => ⟨-i, by rw [zpow_neg, ← hi, inv_apply_self]⟩ theorem sameCycle_comm : SameCycle f x y ↔ SameCycle f y x := ⟨SameCycle.symm, SameCycle.symm⟩ @[trans] theorem SameCycle.trans : SameCycle f x y → SameCycle f y z → SameCycle f x z := fun ⟨i, hi⟩ ⟨j, hj⟩ => ⟨j + i, by rw [zpow_add, mul_apply, hi, hj]⟩ variable (f) in theorem SameCycle.equivalence : Equivalence (SameCycle f) := ⟨SameCycle.refl f, SameCycle.symm, SameCycle.trans⟩ /-- The setoid defined by the `SameCycle` relation. -/ def SameCycle.setoid (f : Perm α) : Setoid α where r := f.SameCycle iseqv := SameCycle.equivalence f @[simp] theorem sameCycle_one : SameCycle 1 x y ↔ x = y := by simp [SameCycle] @[simp] theorem sameCycle_inv : SameCycle f⁻¹ x y ↔ SameCycle f x y := (Equiv.neg _).exists_congr_left.trans <| by simp [SameCycle] alias ⟨SameCycle.of_inv, SameCycle.inv⟩ := sameCycle_inv @[simp] theorem sameCycle_conj : SameCycle (g * f * g⁻¹) x y ↔ SameCycle f (g⁻¹ x) (g⁻¹ y) := exists_congr fun i => by simp [conj_zpow, eq_inv_iff_eq]
theorem SameCycle.conj : SameCycle f x y → SameCycle (g * f * g⁻¹) (g x) (g y) := by
Mathlib/GroupTheory/Perm/Cycle/Basic.lean
94
95
/- Copyright (c) 2019 Jan-David Salchow. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jan-David Salchow, Sébastien Gouëzel, Jean Lo -/ import Mathlib.Analysis.NormedSpace.OperatorNorm.Basic /-! # Operator norm as an `NNNorm` Operator norm as an `NNNorm`, i.e. taking values in non-negative reals. -/ suppress_compilation open Bornology open Filter hiding map_smul open scoped NNReal Topology Uniformity -- the `ₗ` subscript variables are for special cases about linear (as opposed to semilinear) maps variable {𝕜 𝕜₂ 𝕜₃ E Eₗ F Fₗ G Gₗ 𝓕 : Type*} section SemiNormed open Metric ContinuousLinearMap variable [SeminormedAddCommGroup E] [SeminormedAddCommGroup Eₗ] [SeminormedAddCommGroup F] [SeminormedAddCommGroup Fₗ] [SeminormedAddCommGroup G] [SeminormedAddCommGroup Gₗ] variable [NontriviallyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] [NontriviallyNormedField 𝕜₃] [NormedSpace 𝕜 E] [NormedSpace 𝕜 Eₗ] [NormedSpace 𝕜₂ F] [NormedSpace 𝕜 Fₗ] [NormedSpace 𝕜₃ G] [NormedSpace 𝕜 Gₗ] {σ₁₂ : 𝕜 →+* 𝕜₂} {σ₂₃ : 𝕜₂ →+* 𝕜₃} {σ₁₃ : 𝕜 →+* 𝕜₃} [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] variable [FunLike 𝓕 E F] namespace ContinuousLinearMap section OpNorm open Set Real section variable [RingHomIsometric σ₁₂] [RingHomIsometric σ₂₃] (f g : E →SL[σ₁₂] F) (h : F →SL[σ₂₃] G) (x : E) theorem nnnorm_def (f : E →SL[σ₁₂] F) : ‖f‖₊ = sInf { c | ∀ x, ‖f x‖₊ ≤ c * ‖x‖₊ } := by ext rw [NNReal.coe_sInf, coe_nnnorm, norm_def, NNReal.coe_image] simp_rw [← NNReal.coe_le_coe, NNReal.coe_mul, coe_nnnorm, mem_setOf_eq, NNReal.coe_mk, exists_prop] /-- If one controls the norm of every `A x`, then one controls the norm of `A`. -/ theorem opNNNorm_le_bound (f : E →SL[σ₁₂] F) (M : ℝ≥0) (hM : ∀ x, ‖f x‖₊ ≤ M * ‖x‖₊) : ‖f‖₊ ≤ M := opNorm_le_bound f (zero_le M) hM /-- If one controls the norm of every `A x`, `‖x‖₊ ≠ 0`, then one controls the norm of `A`. -/ theorem opNNNorm_le_bound' (f : E →SL[σ₁₂] F) (M : ℝ≥0) (hM : ∀ x, ‖x‖₊ ≠ 0 → ‖f x‖₊ ≤ M * ‖x‖₊) : ‖f‖₊ ≤ M := opNorm_le_bound' f (zero_le M) fun x hx => hM x <| by rwa [← NNReal.coe_ne_zero] /-- For a continuous real linear map `f`, if one controls the norm of every `f x`, `‖x‖₊ = 1`, then one controls the norm of `f`. -/ theorem opNNNorm_le_of_unit_nnnorm [NormedSpace ℝ E] [NormedSpace ℝ F] {f : E →L[ℝ] F} {C : ℝ≥0} (hf : ∀ x, ‖x‖₊ = 1 → ‖f x‖₊ ≤ C) : ‖f‖₊ ≤ C := opNorm_le_of_unit_norm C.coe_nonneg fun x hx => hf x <| by rwa [← NNReal.coe_eq_one] theorem opNNNorm_le_of_lipschitz {f : E →SL[σ₁₂] F} {K : ℝ≥0} (hf : LipschitzWith K f) : ‖f‖₊ ≤ K := opNorm_le_of_lipschitz hf theorem opNNNorm_eq_of_bounds {φ : E →SL[σ₁₂] F} (M : ℝ≥0) (h_above : ∀ x, ‖φ x‖₊ ≤ M * ‖x‖₊) (h_below : ∀ N, (∀ x, ‖φ x‖₊ ≤ N * ‖x‖₊) → M ≤ N) : ‖φ‖₊ = M := Subtype.ext <| opNorm_eq_of_bounds (zero_le M) h_above <| Subtype.forall'.mpr h_below theorem opNNNorm_le_iff {f : E →SL[σ₁₂] F} {C : ℝ≥0} : ‖f‖₊ ≤ C ↔ ∀ x, ‖f x‖₊ ≤ C * ‖x‖₊ := opNorm_le_iff C.2 theorem isLeast_opNNNorm : IsLeast {C : ℝ≥0 | ∀ x, ‖f x‖₊ ≤ C * ‖x‖₊} ‖f‖₊ := by simpa only [← opNNNorm_le_iff] using isLeast_Ici theorem opNNNorm_comp_le [RingHomIsometric σ₁₃] (f : E →SL[σ₁₂] F) : ‖h.comp f‖₊ ≤ ‖h‖₊ * ‖f‖₊ := opNorm_comp_le h f lemma opENorm_comp_le [RingHomIsometric σ₁₃] (f : E →SL[σ₁₂] F) : ‖h.comp f‖ₑ ≤ ‖h‖ₑ * ‖f‖ₑ := by simpa [enorm, ← ENNReal.coe_mul] using opNNNorm_comp_le h f theorem le_opNNNorm : ‖f x‖₊ ≤ ‖f‖₊ * ‖x‖₊ := f.le_opNorm x lemma le_opENorm : ‖f x‖ₑ ≤ ‖f‖ₑ * ‖x‖ₑ := by dsimp [enorm]; exact mod_cast le_opNNNorm .. theorem nndist_le_opNNNorm (x y : E) : nndist (f x) (f y) ≤ ‖f‖₊ * nndist x y := dist_le_opNorm f x y /-- continuous linear maps are Lipschitz continuous. -/ theorem lipschitz : LipschitzWith ‖f‖₊ f := AddMonoidHomClass.lipschitz_of_bound_nnnorm f _ f.le_opNNNorm /-- Evaluation of a continuous linear map `f` at a point is Lipschitz continuous in `f`. -/ theorem lipschitz_apply (x : E) : LipschitzWith ‖x‖₊ fun f : E →SL[σ₁₂] F => f x := lipschitzWith_iff_norm_sub_le.2 fun f g => ((f - g).le_opNorm x).trans_eq (mul_comm _ _) end section Sup variable [RingHomIsometric σ₁₂] theorem exists_mul_lt_apply_of_lt_opNNNorm (f : E →SL[σ₁₂] F) {r : ℝ≥0} (hr : r < ‖f‖₊) : ∃ x, r * ‖x‖₊ < ‖f x‖₊ := by simpa only [not_forall, not_le, Set.mem_setOf] using not_mem_of_lt_csInf (nnnorm_def f ▸ hr : r < sInf { c : ℝ≥0 | ∀ x, ‖f x‖₊ ≤ c * ‖x‖₊ }) (OrderBot.bddBelow _) theorem exists_mul_lt_of_lt_opNorm (f : E →SL[σ₁₂] F) {r : ℝ} (hr₀ : 0 ≤ r) (hr : r < ‖f‖) : ∃ x, r * ‖x‖ < ‖f x‖ := by lift r to ℝ≥0 using hr₀ exact f.exists_mul_lt_apply_of_lt_opNNNorm hr theorem exists_lt_apply_of_lt_opNNNorm {𝕜 𝕜₂ E F : Type*} [NormedAddCommGroup E] [SeminormedAddCommGroup F] [DenselyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] {σ₁₂ : 𝕜 →+* 𝕜₂} [NormedSpace 𝕜 E] [NormedSpace 𝕜₂ F] [RingHomIsometric σ₁₂] (f : E →SL[σ₁₂] F) {r : ℝ≥0} (hr : r < ‖f‖₊) : ∃ x : E, ‖x‖₊ < 1 ∧ r < ‖f x‖₊ := by obtain ⟨y, hy⟩ := f.exists_mul_lt_apply_of_lt_opNNNorm hr have hy' : ‖y‖₊ ≠ 0 := nnnorm_ne_zero_iff.2 fun heq => by simp [heq, nnnorm_zero, map_zero, not_lt_zero'] at hy have hfy : ‖f y‖₊ ≠ 0 := (zero_le'.trans_lt hy).ne' rw [← inv_inv ‖f y‖₊, NNReal.lt_inv_iff_mul_lt (inv_ne_zero hfy), mul_assoc, mul_comm ‖y‖₊, ← mul_assoc, ← NNReal.lt_inv_iff_mul_lt hy'] at hy obtain ⟨k, hk₁, hk₂⟩ := NormedField.exists_lt_nnnorm_lt 𝕜 hy refine ⟨k • y, (nnnorm_smul k y).symm ▸ (NNReal.lt_inv_iff_mul_lt hy').1 hk₂, ?_⟩ have : ‖σ₁₂ k‖₊ = ‖k‖₊ := Subtype.ext RingHomIsometric.is_iso rwa [map_smulₛₗ f, nnnorm_smul, ← div_lt_iff₀ hfy.bot_lt, div_eq_mul_inv, this] theorem exists_lt_apply_of_lt_opNorm {𝕜 𝕜₂ E F : Type*} [NormedAddCommGroup E] [SeminormedAddCommGroup F] [DenselyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] {σ₁₂ : 𝕜 →+* 𝕜₂} [NormedSpace 𝕜 E] [NormedSpace 𝕜₂ F] [RingHomIsometric σ₁₂] (f : E →SL[σ₁₂] F) {r : ℝ} (hr : r < ‖f‖) : ∃ x : E, ‖x‖ < 1 ∧ r < ‖f x‖ := by by_cases hr₀ : r < 0 · exact ⟨0, by simpa using hr₀⟩ · lift r to ℝ≥0 using not_lt.1 hr₀ exact f.exists_lt_apply_of_lt_opNNNorm hr theorem sSup_unit_ball_eq_nnnorm {𝕜 𝕜₂ E F : Type*} [NormedAddCommGroup E] [SeminormedAddCommGroup F] [DenselyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] {σ₁₂ : 𝕜 →+* 𝕜₂} [NormedSpace 𝕜 E] [NormedSpace 𝕜₂ F] [RingHomIsometric σ₁₂] (f : E →SL[σ₁₂] F) : sSup ((fun x => ‖f x‖₊) '' ball 0 1) = ‖f‖₊ := by refine csSup_eq_of_forall_le_of_forall_lt_exists_gt ((nonempty_ball.mpr zero_lt_one).image _) ?_ fun ub hub => ?_ · rintro - ⟨x, hx, rfl⟩ simpa only [mul_one] using f.le_opNorm_of_le (mem_ball_zero_iff.1 hx).le · obtain ⟨x, hx, hxf⟩ := f.exists_lt_apply_of_lt_opNNNorm hub exact ⟨_, ⟨x, mem_ball_zero_iff.2 hx, rfl⟩, hxf⟩ theorem sSup_unit_ball_eq_norm {𝕜 𝕜₂ E F : Type*} [NormedAddCommGroup E] [SeminormedAddCommGroup F] [DenselyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] {σ₁₂ : 𝕜 →+* 𝕜₂} [NormedSpace 𝕜 E] [NormedSpace 𝕜₂ F] [RingHomIsometric σ₁₂] (f : E →SL[σ₁₂] F) : sSup ((fun x => ‖f x‖) '' ball 0 1) = ‖f‖ := by simpa only [NNReal.coe_sSup, Set.image_image] using NNReal.coe_inj.2 f.sSup_unit_ball_eq_nnnorm theorem sSup_unitClosedBall_eq_nnnorm {𝕜 𝕜₂ E F : Type*} [NormedAddCommGroup E] [SeminormedAddCommGroup F] [DenselyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] {σ₁₂ : 𝕜 →+* 𝕜₂} [NormedSpace 𝕜 E] [NormedSpace 𝕜₂ F] [RingHomIsometric σ₁₂] (f : E →SL[σ₁₂] F) : sSup ((fun x => ‖f x‖₊) '' closedBall 0 1) = ‖f‖₊ := by have hbdd : ∀ y ∈ (fun x => ‖f x‖₊) '' closedBall 0 1, y ≤ ‖f‖₊ := by rintro - ⟨x, hx, rfl⟩ exact f.unit_le_opNorm x (mem_closedBall_zero_iff.1 hx) refine le_antisymm (csSup_le ((nonempty_closedBall.mpr zero_le_one).image _) hbdd) ?_ rw [← sSup_unit_ball_eq_nnnorm] exact csSup_le_csSup ⟨‖f‖₊, hbdd⟩ ((nonempty_ball.2 zero_lt_one).image _) (Set.image_subset _ ball_subset_closedBall) @[deprecated (since := "2024-12-01")] alias sSup_closed_unit_ball_eq_nnnorm := sSup_unitClosedBall_eq_nnnorm theorem sSup_unitClosedBall_eq_norm {𝕜 𝕜₂ E F : Type*} [NormedAddCommGroup E] [SeminormedAddCommGroup F] [DenselyNormedField 𝕜] [NontriviallyNormedField 𝕜₂] {σ₁₂ : 𝕜 →+* 𝕜₂} [NormedSpace 𝕜 E] [NormedSpace 𝕜₂ F] [RingHomIsometric σ₁₂] (f : E →SL[σ₁₂] F) : sSup ((fun x => ‖f x‖) '' closedBall 0 1) = ‖f‖ := by simpa only [NNReal.coe_sSup, Set.image_image] using
NNReal.coe_inj.2 f.sSup_unitClosedBall_eq_nnnorm @[deprecated (since := "2024-12-01")] alias sSup_closed_unit_ball_eq_norm := sSup_unitClosedBall_eq_norm end Sup end OpNorm end ContinuousLinearMap
Mathlib/Analysis/NormedSpace/OperatorNorm/NNNorm.lean
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/- Copyright (c) 2023 Sophie Morel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sophie Morel -/ import Mathlib.Analysis.Analytic.Constructions import Mathlib.Analysis.Analytic.CPolynomialDef /-! # Properties of continuously polynomial functions We expand the API around continuously polynomial functions. Notably, we show that this class is stable under the usual operations (addition, subtraction, negation). We also prove that continuous multilinear maps are continuously polynomial, and so are continuous linear maps into continuous multilinear maps. In particular, such maps are analytic. -/ variable {𝕜 E F G : Type*} [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G] open scoped Topology open Set Filter Asymptotics NNReal ENNReal variable {f g : E → F} {p pf pg : FormalMultilinearSeries 𝕜 E F} {x : E} {r r' : ℝ≥0∞} {n m : ℕ} theorem hasFiniteFPowerSeriesOnBall_const {c : F} {e : E} : HasFiniteFPowerSeriesOnBall (fun _ => c) (constFormalMultilinearSeries 𝕜 E c) e 1 ⊤ := ⟨hasFPowerSeriesOnBall_const, fun n hn ↦ constFormalMultilinearSeries_apply (id hn : 0 < n).ne'⟩ theorem hasFiniteFPowerSeriesAt_const {c : F} {e : E} : HasFiniteFPowerSeriesAt (fun _ => c) (constFormalMultilinearSeries 𝕜 E c) e 1 := ⟨⊤, hasFiniteFPowerSeriesOnBall_const⟩ theorem CPolynomialAt_const {v : F} : CPolynomialAt 𝕜 (fun _ => v) x := ⟨constFormalMultilinearSeries 𝕜 E v, 1, hasFiniteFPowerSeriesAt_const⟩ theorem CPolynomialOn_const {v : F} {s : Set E} : CPolynomialOn 𝕜 (fun _ => v) s := fun _ _ => CPolynomialAt_const theorem HasFiniteFPowerSeriesOnBall.add (hf : HasFiniteFPowerSeriesOnBall f pf x n r) (hg : HasFiniteFPowerSeriesOnBall g pg x m r) : HasFiniteFPowerSeriesOnBall (f + g) (pf + pg) x (max n m) r := ⟨hf.1.add hg.1, fun N hN ↦ by rw [Pi.add_apply, hf.finite _ ((le_max_left n m).trans hN), hg.finite _ ((le_max_right n m).trans hN), zero_add]⟩ theorem HasFiniteFPowerSeriesAt.add (hf : HasFiniteFPowerSeriesAt f pf x n) (hg : HasFiniteFPowerSeriesAt g pg x m) : HasFiniteFPowerSeriesAt (f + g) (pf + pg) x (max n m) := by rcases (hf.eventually.and hg.eventually).exists with ⟨r, hr⟩ exact ⟨r, hr.1.add hr.2⟩ theorem CPolynomialAt.add (hf : CPolynomialAt 𝕜 f x) (hg : CPolynomialAt 𝕜 g x) : CPolynomialAt 𝕜 (f + g) x := let ⟨_, _, hpf⟩ := hf let ⟨_, _, hqf⟩ := hg (hpf.add hqf).cpolynomialAt theorem HasFiniteFPowerSeriesOnBall.neg (hf : HasFiniteFPowerSeriesOnBall f pf x n r) : HasFiniteFPowerSeriesOnBall (-f) (-pf) x n r := ⟨hf.1.neg, fun m hm ↦ by rw [Pi.neg_apply, hf.finite m hm, neg_zero]⟩ theorem HasFiniteFPowerSeriesAt.neg (hf : HasFiniteFPowerSeriesAt f pf x n) : HasFiniteFPowerSeriesAt (-f) (-pf) x n := let ⟨_, hrf⟩ := hf hrf.neg.hasFiniteFPowerSeriesAt theorem CPolynomialAt.neg (hf : CPolynomialAt 𝕜 f x) : CPolynomialAt 𝕜 (-f) x := let ⟨_, _, hpf⟩ := hf hpf.neg.cpolynomialAt theorem HasFiniteFPowerSeriesOnBall.sub (hf : HasFiniteFPowerSeriesOnBall f pf x n r) (hg : HasFiniteFPowerSeriesOnBall g pg x m r) : HasFiniteFPowerSeriesOnBall (f - g) (pf - pg) x (max n m) r := by simpa only [sub_eq_add_neg] using hf.add hg.neg theorem HasFiniteFPowerSeriesAt.sub (hf : HasFiniteFPowerSeriesAt f pf x n) (hg : HasFiniteFPowerSeriesAt g pg x m) : HasFiniteFPowerSeriesAt (f - g) (pf - pg) x (max n m) := by simpa only [sub_eq_add_neg] using hf.add hg.neg theorem CPolynomialAt.sub (hf : CPolynomialAt 𝕜 f x) (hg : CPolynomialAt 𝕜 g x) : CPolynomialAt 𝕜 (f - g) x := by simpa only [sub_eq_add_neg] using hf.add hg.neg theorem CPolynomialOn.add {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : CPolynomialOn 𝕜 g s) : CPolynomialOn 𝕜 (f + g) s := fun z hz => (hf z hz).add (hg z hz) theorem CPolynomialOn.sub {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : CPolynomialOn 𝕜 g s) : CPolynomialOn 𝕜 (f - g) s := fun z hz => (hf z hz).sub (hg z hz) /-! ### Continuous multilinear maps We show that continuous multilinear maps are continuously polynomial, and therefore analytic. -/ namespace ContinuousMultilinearMap variable {ι : Type*} {Em : ι → Type*} [∀ i, NormedAddCommGroup (Em i)] [∀ i, NormedSpace 𝕜 (Em i)] [Fintype ι] (f : ContinuousMultilinearMap 𝕜 Em F) {x : Π i, Em i} {s : Set (Π i, Em i)} open FormalMultilinearSeries protected theorem hasFiniteFPowerSeriesOnBall : HasFiniteFPowerSeriesOnBall f f.toFormalMultilinearSeries 0 (Fintype.card ι + 1) ⊤ := .mk' (fun _ hm ↦ dif_neg (Nat.succ_le_iff.mp hm).ne) ENNReal.zero_lt_top fun y _ ↦ by rw [Finset.sum_eq_single_of_mem _ (Finset.self_mem_range_succ _), zero_add] · rw [toFormalMultilinearSeries, dif_pos rfl]; rfl · intro m _ ne; rw [toFormalMultilinearSeries, dif_neg ne.symm]; rfl lemma cpolynomialAt : CPolynomialAt 𝕜 f x := f.hasFiniteFPowerSeriesOnBall.cpolynomialAt_of_mem (by simp only [Metric.emetric_ball_top, Set.mem_univ]) lemma cpolynomialOn : CPolynomialOn 𝕜 f s := fun _ _ ↦ f.cpolynomialAt @[deprecated (since := "2025-02-15")] alias cpolyomialOn := cpolynomialOn lemma analyticOnNhd : AnalyticOnNhd 𝕜 f s := f.cpolynomialOn.analyticOnNhd lemma analyticOn : AnalyticOn 𝕜 f s := f.analyticOnNhd.analyticOn lemma analyticAt : AnalyticAt 𝕜 f x := f.cpolynomialAt.analyticAt lemma analyticWithinAt : AnalyticWithinAt 𝕜 f s x := f.analyticAt.analyticWithinAt end ContinuousMultilinearMap /-! ### Continuous linear maps into continuous multilinear maps We show that a continuous linear map into continuous multilinear maps is continuously polynomial (as a function of two variables, i.e., uncurried). Therefore, it is also analytic. -/ namespace ContinuousLinearMap variable {ι : Type*} {Em : ι → Type*} [∀ i, NormedAddCommGroup (Em i)] [∀ i, NormedSpace 𝕜 (Em i)] [Fintype ι] (f : G →L[𝕜] ContinuousMultilinearMap 𝕜 Em F) {s : Set (G × (Π i, Em i))} {x : G × (Π i, Em i)} /-- Formal multilinear series associated to a linear map into multilinear maps. -/ noncomputable def toFormalMultilinearSeriesOfMultilinear : FormalMultilinearSeries 𝕜 (G × (Π i, Em i)) F := fun n ↦ if h : Fintype.card (Option ι) = n then (f.continuousMultilinearMapOption).domDomCongr (Fintype.equivFinOfCardEq h) else 0 protected theorem hasFiniteFPowerSeriesOnBall_uncurry_of_multilinear : HasFiniteFPowerSeriesOnBall (fun (p : G × (Π i, Em i)) ↦ f p.1 p.2) f.toFormalMultilinearSeriesOfMultilinear 0 (Fintype.card (Option ι) + 1) ⊤ := by apply HasFiniteFPowerSeriesOnBall.mk' ?_ ENNReal.zero_lt_top ?_ · intro m hm apply dif_neg exact Nat.ne_of_lt hm · intro y _ rw [Finset.sum_eq_single_of_mem _ (Finset.self_mem_range_succ _), zero_add] · rw [toFormalMultilinearSeriesOfMultilinear, dif_pos rfl]; rfl · intro m _ ne; rw [toFormalMultilinearSeriesOfMultilinear, dif_neg ne.symm]; rfl lemma cpolynomialAt_uncurry_of_multilinear : CPolynomialAt 𝕜 (fun (p : G × (Π i, Em i)) ↦ f p.1 p.2) x := f.hasFiniteFPowerSeriesOnBall_uncurry_of_multilinear.cpolynomialAt_of_mem (by simp only [Metric.emetric_ball_top, Set.mem_univ]) lemma cpolyomialOn_uncurry_of_multilinear : CPolynomialOn 𝕜 (fun (p : G × (Π i, Em i)) ↦ f p.1 p.2) s := fun _ _ ↦ f.cpolynomialAt_uncurry_of_multilinear lemma analyticOnNhd_uncurry_of_multilinear : AnalyticOnNhd 𝕜 (fun (p : G × (Π i, Em i)) ↦ f p.1 p.2) s := f.cpolyomialOn_uncurry_of_multilinear.analyticOnNhd lemma analyticOn_uncurry_of_multilinear :
AnalyticOn 𝕜 (fun (p : G × (Π i, Em i)) ↦ f p.1 p.2) s := f.analyticOnNhd_uncurry_of_multilinear.analyticOn
Mathlib/Analysis/Analytic/CPolynomial.lean
181
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/- Copyright (c) 2019 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.Algebra.Regular.Basic import Mathlib.GroupTheory.MonoidLocalization.Basic import Mathlib.LinearAlgebra.Matrix.MvPolynomial import Mathlib.LinearAlgebra.Matrix.Polynomial import Mathlib.RingTheory.Polynomial.Basic /-! # Cramer's rule and adjugate matrices The adjugate matrix is the transpose of the cofactor matrix. It is calculated with Cramer's rule, which we introduce first. The vectors returned by Cramer's rule are given by the linear map `cramer`, which sends a matrix `A` and vector `b` to the vector consisting of the determinant of replacing the `i`th column of `A` with `b` at index `i` (written as `(A.update_column i b).det`). Using Cramer's rule, we can compute for each matrix `A` the matrix `adjugate A`. The entries of the adjugate are the minors of `A`. Instead of defining a minor by deleting row `i` and column `j` of `A`, we replace the `i`th row of `A` with the `j`th basis vector; the resulting matrix has the same determinant but more importantly equals Cramer's rule applied to `A` and the `j`th basis vector, simplifying the subsequent proofs. We prove the adjugate behaves like `det A • A⁻¹`. ## Main definitions * `Matrix.cramer A b`: the vector output by Cramer's rule on `A` and `b`. * `Matrix.adjugate A`: the adjugate (or classical adjoint) of the matrix `A`. ## References * https://en.wikipedia.org/wiki/Cramer's_rule#Finding_inverse_matrix ## Tags cramer, cramer's rule, adjugate -/ namespace Matrix universe u v w variable {m : Type u} {n : Type v} {α : Type w} variable [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m] [CommRing α] open Matrix Polynomial Equiv Equiv.Perm Finset section Cramer /-! ### `cramer` section Introduce the linear map `cramer` with values defined by `cramerMap`. After defining `cramerMap` and showing it is linear, we will restrict our proofs to using `cramer`. -/ variable (A : Matrix n n α) (b : n → α) /-- `cramerMap A b i` is the determinant of the matrix `A` with column `i` replaced with `b`, and thus `cramerMap A b` is the vector output by Cramer's rule on `A` and `b`. If `A * x = b` has a unique solution in `x`, `cramerMap A` sends the vector `b` to `A.det • x`. Otherwise, the outcome of `cramerMap` is well-defined but not necessarily useful. -/ def cramerMap (i : n) : α := (A.updateCol i b).det theorem cramerMap_is_linear (i : n) : IsLinearMap α fun b => cramerMap A b i := { map_add := det_updateCol_add _ _ map_smul := det_updateCol_smul _ _ } theorem cramer_is_linear : IsLinearMap α (cramerMap A) := by constructor <;> intros <;> ext i · apply (cramerMap_is_linear A i).1 · apply (cramerMap_is_linear A i).2 /-- `cramer A b i` is the determinant of the matrix `A` with column `i` replaced with `b`, and thus `cramer A b` is the vector output by Cramer's rule on `A` and `b`. If `A * x = b` has a unique solution in `x`, `cramer A` sends the vector `b` to `A.det • x`. Otherwise, the outcome of `cramer` is well-defined but not necessarily useful. -/ def cramer (A : Matrix n n α) : (n → α) →ₗ[α] (n → α) := IsLinearMap.mk' (cramerMap A) (cramer_is_linear A) theorem cramer_apply (i : n) : cramer A b i = (A.updateCol i b).det := rfl theorem cramer_transpose_apply (i : n) : cramer Aᵀ b i = (A.updateRow i b).det := by rw [cramer_apply, updateCol_transpose, det_transpose] theorem cramer_transpose_row_self (i : n) : Aᵀ.cramer (A i) = Pi.single i A.det := by ext j rw [cramer_apply, Pi.single_apply] split_ifs with h · -- i = j: this entry should be `A.det` subst h simp only [updateCol_transpose, det_transpose, updateRow_eq_self] · -- i ≠ j: this entry should be 0 rw [updateCol_transpose, det_transpose] apply det_zero_of_row_eq h rw [updateRow_self, updateRow_ne (Ne.symm h)] theorem cramer_row_self (i : n) (h : ∀ j, b j = A j i) : A.cramer b = Pi.single i A.det := by rw [← transpose_transpose A, det_transpose] convert cramer_transpose_row_self Aᵀ i exact funext h @[simp] theorem cramer_one : cramer (1 : Matrix n n α) = 1 := by ext i j convert congr_fun (cramer_row_self (1 : Matrix n n α) (Pi.single i 1) i _) j · simp · intro j rw [Matrix.one_eq_pi_single, Pi.single_comm] theorem cramer_smul (r : α) (A : Matrix n n α) : cramer (r • A) = r ^ (Fintype.card n - 1) • cramer A := LinearMap.ext fun _ => funext fun _ => det_updateCol_smul_left _ _ _ _ @[simp] theorem cramer_subsingleton_apply [Subsingleton n] (A : Matrix n n α) (b : n → α) (i : n) : cramer A b i = b i := by rw [cramer_apply, det_eq_elem_of_subsingleton _ i, updateCol_self] theorem cramer_zero [Nontrivial n] : cramer (0 : Matrix n n α) = 0 := by ext i j obtain ⟨j', hj'⟩ : ∃ j', j' ≠ j := exists_ne j apply det_eq_zero_of_column_eq_zero j' intro j'' simp [updateCol_ne hj'] /-- Use linearity of `cramer` to take it out of a summation. -/ theorem sum_cramer {β} (s : Finset β) (f : β → n → α) : (∑ x ∈ s, cramer A (f x)) = cramer A (∑ x ∈ s, f x) := (map_sum (cramer A) ..).symm /-- Use linearity of `cramer` and vector evaluation to take `cramer A _ i` out of a summation. -/ theorem sum_cramer_apply {β} (s : Finset β) (f : n → β → α) (i : n) : (∑ x ∈ s, cramer A (fun j => f j x) i) = cramer A (fun j : n => ∑ x ∈ s, f j x) i := calc (∑ x ∈ s, cramer A (fun j => f j x) i) = (∑ x ∈ s, cramer A fun j => f j x) i := (Finset.sum_apply i s _).symm _ = cramer A (fun j : n => ∑ x ∈ s, f j x) i := by rw [sum_cramer, cramer_apply, cramer_apply] simp only [updateCol] congr with j congr apply Finset.sum_apply theorem cramer_submatrix_equiv (A : Matrix m m α) (e : n ≃ m) (b : n → α) : cramer (A.submatrix e e) b = cramer A (b ∘ e.symm) ∘ e := by ext i simp_rw [Function.comp_apply, cramer_apply, updateCol_submatrix_equiv, det_submatrix_equiv_self e, Function.comp_def] theorem cramer_reindex (e : m ≃ n) (A : Matrix m m α) (b : n → α) : cramer (reindex e e A) b = cramer A (b ∘ e) ∘ e.symm := cramer_submatrix_equiv _ _ _ end Cramer section Adjugate /-! ### `adjugate` section Define the `adjugate` matrix and a few equations. These will hold for any matrix over a commutative ring. -/ /-- The adjugate matrix is the transpose of the cofactor matrix. Typically, the cofactor matrix is defined by taking minors, i.e. the determinant of the matrix with a row and column removed. However, the proof of `mul_adjugate` becomes a lot easier if we use the matrix replacing a column with a basis vector, since it allows us to use facts about the `cramer` map. -/ def adjugate (A : Matrix n n α) : Matrix n n α := of fun i => cramer Aᵀ (Pi.single i 1) theorem adjugate_def (A : Matrix n n α) : adjugate A = of fun i => cramer Aᵀ (Pi.single i 1) := rfl theorem adjugate_apply (A : Matrix n n α) (i j : n) : adjugate A i j = (A.updateRow j (Pi.single i 1)).det := by rw [adjugate_def, of_apply, cramer_apply, updateCol_transpose, det_transpose] theorem adjugate_transpose (A : Matrix n n α) : (adjugate A)ᵀ = adjugate Aᵀ := by ext i j rw [transpose_apply, adjugate_apply, adjugate_apply, updateRow_transpose, det_transpose] rw [det_apply', det_apply'] apply Finset.sum_congr rfl intro σ _ congr 1 by_cases h : i = σ j · -- Everything except `(i , j)` (= `(σ j , j)`) is given by A, and the rest is a single `1`. congr ext j' subst h have : σ j' = σ j ↔ j' = j := σ.injective.eq_iff rw [updateRow_apply, updateCol_apply] simp_rw [this] rw [← dite_eq_ite, ← dite_eq_ite] congr 1 with rfl rw [Pi.single_eq_same, Pi.single_eq_same] · -- Otherwise, we need to show that there is a `0` somewhere in the product. have : (∏ j' : n, updateCol A j (Pi.single i 1) (σ j') j') = 0 := by apply prod_eq_zero (mem_univ j) rw [updateCol_self, Pi.single_eq_of_ne' h] rw [this] apply prod_eq_zero (mem_univ (σ⁻¹ i)) erw [apply_symm_apply σ i, updateRow_self] apply Pi.single_eq_of_ne intro h' exact h ((symm_apply_eq σ).mp h') @[simp] theorem adjugate_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m α) : adjugate (A.submatrix e e) = (adjugate A).submatrix e e := by ext i j have : (fun j ↦ Pi.single i 1 <| e.symm j) = Pi.single (e i) 1 := Function.update_comp_equiv (0 : n → α) e.symm i 1 rw [adjugate_apply, submatrix_apply, adjugate_apply, ← det_submatrix_equiv_self e, updateRow_submatrix_equiv, this] theorem adjugate_reindex (e : m ≃ n) (A : Matrix m m α) : adjugate (reindex e e A) = reindex e e (adjugate A) := adjugate_submatrix_equiv_self _ _ /-- Since the map `b ↦ cramer A b` is linear in `b`, it must be multiplication by some matrix. This matrix is `A.adjugate`. -/ theorem cramer_eq_adjugate_mulVec (A : Matrix n n α) (b : n → α) : cramer A b = A.adjugate *ᵥ b := by nth_rw 2 [← A.transpose_transpose] rw [← adjugate_transpose, adjugate_def] have : b = ∑ i, b i • (Pi.single i 1 : n → α) := by refine (pi_eq_sum_univ b).trans ?_ congr with j simp [Pi.single_apply, eq_comm] conv_lhs => rw [this] ext k simp [mulVec, dotProduct, mul_comm] theorem mul_adjugate_apply (A : Matrix n n α) (i j k) : A i k * adjugate A k j = cramer Aᵀ (Pi.single k (A i k)) j := by rw [← smul_eq_mul, adjugate, of_apply, ← Pi.smul_apply, ← LinearMap.map_smul, ← Pi.single_smul', smul_eq_mul, mul_one] theorem mul_adjugate (A : Matrix n n α) : A * adjugate A = A.det • (1 : Matrix n n α) := by ext i j rw [mul_apply, Pi.smul_apply, Pi.smul_apply, one_apply, smul_eq_mul, mul_boole] simp [mul_adjugate_apply, sum_cramer_apply, cramer_transpose_row_self, Pi.single_apply, eq_comm] theorem adjugate_mul (A : Matrix n n α) : adjugate A * A = A.det • (1 : Matrix n n α) := calc adjugate A * A = (Aᵀ * adjugate Aᵀ)ᵀ := by rw [← adjugate_transpose, ← transpose_mul, transpose_transpose] _ = _ := by rw [mul_adjugate Aᵀ, det_transpose, transpose_smul, transpose_one] theorem adjugate_smul (r : α) (A : Matrix n n α) : adjugate (r • A) = r ^ (Fintype.card n - 1) • adjugate A := by rw [adjugate, adjugate, transpose_smul, cramer_smul] rfl /-- A stronger form of **Cramer's rule** that allows us to solve some instances of `A * x = b` even if the determinant is not a unit. A sufficient (but still not necessary) condition is that `A.det` divides `b`. -/ @[simp] theorem mulVec_cramer (A : Matrix n n α) (b : n → α) : A *ᵥ cramer A b = A.det • b := by rw [cramer_eq_adjugate_mulVec, mulVec_mulVec, mul_adjugate, smul_mulVec_assoc, one_mulVec] theorem adjugate_subsingleton [Subsingleton n] (A : Matrix n n α) : adjugate A = 1 := by ext i j simp [Subsingleton.elim i j, adjugate_apply, det_eq_elem_of_subsingleton _ i, one_apply] theorem adjugate_eq_one_of_card_eq_one {A : Matrix n n α} (h : Fintype.card n = 1) : adjugate A = 1 := haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le adjugate_subsingleton _ @[simp] theorem adjugate_zero [Nontrivial n] : adjugate (0 : Matrix n n α) = 0 := by ext i j obtain ⟨j', hj'⟩ : ∃ j', j' ≠ j := exists_ne j apply det_eq_zero_of_column_eq_zero j' intro j'' simp [updateCol_ne hj'] @[simp] theorem adjugate_one : adjugate (1 : Matrix n n α) = 1 := by ext simp [adjugate_def, Matrix.one_apply, Pi.single_apply, eq_comm] @[simp] theorem adjugate_diagonal (v : n → α) : adjugate (diagonal v) = diagonal fun i => ∏ j ∈ Finset.univ.erase i, v j := by ext i j simp only [adjugate_def, cramer_apply, diagonal_transpose, of_apply] obtain rfl | hij := eq_or_ne i j · rw [diagonal_apply_eq, diagonal_updateCol_single, det_diagonal, prod_update_of_mem (Finset.mem_univ _), sdiff_singleton_eq_erase, one_mul] · rw [diagonal_apply_ne _ hij] refine det_eq_zero_of_row_eq_zero j fun k => ?_ obtain rfl | hjk := eq_or_ne k j
· rw [updateCol_self, Pi.single_eq_of_ne' hij] · rw [updateCol_ne hjk, diagonal_apply_ne' _ hjk]
Mathlib/LinearAlgebra/Matrix/Adjugate.lean
315
317
/- Copyright (c) 2020 Fox Thomson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Fox Thomson -/ import Mathlib.Computability.Language import Mathlib.Tactic.AdaptationNote /-! # Regular Expressions This file contains the formal definition for regular expressions and basic lemmas. Note these are regular expressions in terms of formal language theory. Note this is different to regex's used in computer science such as the POSIX standard. ## TODO * Show that this regular expressions and DFA/NFA's are equivalent. -/ open List Set open Computability universe u variable {α β γ : Type*} -- Disable generation of unneeded lemmas which the simpNF linter would complain about. set_option genSizeOfSpec false in set_option genInjectivity false in /-- This is the definition of regular expressions. The names used here is to mirror the definition of a Kleene algebra (https://en.wikipedia.org/wiki/Kleene_algebra). * `0` (`zero`) matches nothing * `1` (`epsilon`) matches only the empty string * `char a` matches only the string 'a' * `star P` matches any finite concatenation of strings which match `P` * `P + Q` (`plus P Q`) matches anything which match `P` or `Q` * `P * Q` (`comp P Q`) matches `x ++ y` if `x` matches `P` and `y` matches `Q` -/ inductive RegularExpression (α : Type u) : Type u | zero : RegularExpression α | epsilon : RegularExpression α | char : α → RegularExpression α | plus : RegularExpression α → RegularExpression α → RegularExpression α | comp : RegularExpression α → RegularExpression α → RegularExpression α | star : RegularExpression α → RegularExpression α namespace RegularExpression variable {a b : α} instance : Inhabited (RegularExpression α) := ⟨zero⟩ instance : Add (RegularExpression α) := ⟨plus⟩ instance : Mul (RegularExpression α) := ⟨comp⟩ instance : One (RegularExpression α) := ⟨epsilon⟩ instance : Zero (RegularExpression α) := ⟨zero⟩ instance : Pow (RegularExpression α) ℕ := ⟨fun n r => npowRec r n⟩ @[simp] theorem zero_def : (zero : RegularExpression α) = 0 := rfl @[simp] theorem one_def : (epsilon : RegularExpression α) = 1 := rfl @[simp] theorem plus_def (P Q : RegularExpression α) : plus P Q = P + Q := rfl @[simp] theorem comp_def (P Q : RegularExpression α) : comp P Q = P * Q := rfl -- This was renamed to `matches'` during the port of Lean 4 as `matches` is a reserved word. /-- `matches' P` provides a language which contains all strings that `P` matches -/ -- Porting note: was '@[simp] but removed based on -- https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/simpNF.20issues.20in.20Computability.2ERegularExpressions.20!4.232306/near/328355362 def matches' : RegularExpression α → Language α | 0 => 0 | 1 => 1 | char a => {[a]} | P + Q => P.matches' + Q.matches' | P * Q => P.matches' * Q.matches' | star P => P.matches'∗ @[simp] theorem matches'_zero : (0 : RegularExpression α).matches' = 0 := rfl @[simp] theorem matches'_epsilon : (1 : RegularExpression α).matches' = 1 := rfl @[simp] theorem matches'_char (a : α) : (char a).matches' = {[a]} := rfl @[simp] theorem matches'_add (P Q : RegularExpression α) : (P + Q).matches' = P.matches' + Q.matches' := rfl @[simp] theorem matches'_mul (P Q : RegularExpression α) : (P * Q).matches' = P.matches' * Q.matches' := rfl @[simp] theorem matches'_pow (P : RegularExpression α) : ∀ n : ℕ, (P ^ n).matches' = P.matches' ^ n | 0 => matches'_epsilon | n + 1 => (matches'_mul _ _).trans <| Eq.trans (congrFun (congrArg HMul.hMul (matches'_pow P n)) (matches' P)) (pow_succ _ n).symm @[simp] theorem matches'_star (P : RegularExpression α) : P.star.matches' = P.matches'∗ := rfl /-- `matchEpsilon P` is true if and only if `P` matches the empty string -/ def matchEpsilon : RegularExpression α → Bool | 0 => false | 1 => true | char _ => false | P + Q => P.matchEpsilon || Q.matchEpsilon | P * Q => P.matchEpsilon && Q.matchEpsilon | star _P => true section DecidableEq variable [DecidableEq α] /-- `P.deriv a` matches `x` if `P` matches `a :: x`, the Brzozowski derivative of `P` with respect to `a` -/ def deriv : RegularExpression α → α → RegularExpression α | 0, _ => 0 | 1, _ => 0 | char a₁, a₂ => if a₁ = a₂ then 1 else 0 | P + Q, a => deriv P a + deriv Q a | P * Q, a => if P.matchEpsilon then deriv P a * Q + deriv Q a else deriv P a * Q | star P, a => deriv P a * star P @[simp] theorem deriv_zero (a : α) : deriv 0 a = 0 := rfl @[simp] theorem deriv_one (a : α) : deriv 1 a = 0 := rfl @[simp] theorem deriv_char_self (a : α) : deriv (char a) a = 1 := if_pos rfl @[simp] theorem deriv_char_of_ne (h : a ≠ b) : deriv (char a) b = 0 := if_neg h @[simp] theorem deriv_add (P Q : RegularExpression α) (a : α) : deriv (P + Q) a = deriv P a + deriv Q a := rfl @[simp] theorem deriv_star (P : RegularExpression α) (a : α) : deriv P.star a = deriv P a * star P := rfl /-- `P.rmatch x` is true if and only if `P` matches `x`. This is a computable definition equivalent to `matches'`. -/ def rmatch : RegularExpression α → List α → Bool | P, [] => matchEpsilon P | P, a :: as => rmatch (P.deriv a) as @[simp] theorem zero_rmatch (x : List α) : rmatch 0 x = false := by induction x <;> simp [rmatch, matchEpsilon, *] theorem one_rmatch_iff (x : List α) : rmatch 1 x ↔ x = [] := by induction x <;> simp [rmatch, matchEpsilon, *] theorem char_rmatch_iff (a : α) (x : List α) : rmatch (char a) x ↔ x = [a] := by rcases x with - | ⟨_, x⟩ · exact of_decide_eq_true rfl · rcases x with - | ⟨head, tail⟩ · rw [rmatch, deriv, List.singleton_inj] split <;> tauto · rw [rmatch, rmatch, deriv, cons.injEq] split · simp_rw [deriv_one, zero_rmatch, reduceCtorEq, and_false] · simp_rw [deriv_zero, zero_rmatch, reduceCtorEq, and_false] theorem add_rmatch_iff (P Q : RegularExpression α) (x : List α) : (P + Q).rmatch x ↔ P.rmatch x ∨ Q.rmatch x := by induction' x with _ _ ih generalizing P Q · simp only [rmatch, matchEpsilon, Bool.or_eq_true_iff] · rw [rmatch, deriv_add] exact ih _ _ theorem mul_rmatch_iff (P Q : RegularExpression α) (x : List α) : (P * Q).rmatch x ↔ ∃ t u : List α, x = t ++ u ∧ P.rmatch t ∧ Q.rmatch u := by induction' x with a x ih generalizing P Q · rw [rmatch]; simp only [matchEpsilon] constructor · intro h refine ⟨[], [], rfl, ?_⟩ rw [rmatch, rmatch] rwa [Bool.and_eq_true_iff] at h · rintro ⟨t, u, h₁, h₂⟩ obtain ⟨ht, hu⟩ := List.append_eq_nil_iff.1 h₁.symm subst ht hu repeat rw [rmatch] at h₂ simp [h₂] · rw [rmatch]; simp only [deriv] split_ifs with hepsilon · rw [add_rmatch_iff, ih] constructor · rintro (⟨t, u, _⟩ | h) · exact ⟨a :: t, u, by tauto⟩ · exact ⟨[], a :: x, rfl, hepsilon, h⟩
· rintro ⟨t, u, h, hP, hQ⟩ rcases t with - | ⟨b, t⟩
Mathlib/Computability/RegularExpressions.lean
227
228
/- Copyright (c) 2023 Joachim Breitner. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joachim Breitner -/ import Mathlib.Probability.ProbabilityMassFunction.Basic import Mathlib.Probability.ProbabilityMassFunction.Constructions import Mathlib.MeasureTheory.Integral.Bochner.Basic /-! # Integrals with a measure derived from probability mass functions. This files connects `PMF` with `integral`. The main result is that the integral (i.e. the expected value) with regard to a measure derived from a `PMF` is a sum weighted by the `PMF`. It also provides the expected value for specific probability mass functions. -/ namespace PMF open MeasureTheory ENNReal TopologicalSpace section General variable {α : Type*} [MeasurableSpace α] [MeasurableSingletonClass α] variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E] theorem integral_eq_tsum (p : PMF α) (f : α → E) (hf : Integrable f p.toMeasure) : ∫ a, f a ∂(p.toMeasure) = ∑' a, (p a).toReal • f a := calc _ = ∫ a in p.support, f a ∂(p.toMeasure) := by rw [restrict_toMeasure_support p] _ = ∑' (a : support p), (p.toMeasure {a.val}).toReal • f a := by apply integral_countable f p.support_countable rwa [IntegrableOn, restrict_toMeasure_support p] _ = ∑' (a : support p), (p a).toReal • f a := by congr with x; congr 2 apply PMF.toMeasure_apply_singleton p x (MeasurableSet.singleton _) _ = ∑' a, (p a).toReal • f a := tsum_subtype_eq_of_support_subset <| calc (fun a ↦ (p a).toReal • f a).support ⊆ (fun a ↦ (p a).toReal).support := Function.support_smul_subset_left _ _ _ ⊆ support p := fun x h1 h2 => h1 (by simp [h2]) theorem integral_eq_sum [Fintype α] (p : PMF α) (f : α → E) : ∫ a, f a ∂(p.toMeasure) = ∑ a, (p a).toReal • f a := by rw [integral_fintype _ .of_finite] congr with x rw [measureReal_def] congr 2 exact PMF.toMeasure_apply_singleton p x (MeasurableSet.singleton _)
end General
Mathlib/Probability/ProbabilityMassFunction/Integrals.lean
51
52
/- Copyright (c) 2019 Gabriel Ebner. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Gabriel Ebner, Anatole Dedecker, Yury Kudryashov -/ import Mathlib.Analysis.Calculus.Deriv.Basic import Mathlib.Analysis.Calculus.FDeriv.Mul import Mathlib.Analysis.Calculus.FDeriv.Add /-! # Derivative of `f x * g x` In this file we prove formulas for `(f x * g x)'` and `(f x • g x)'`. For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of `Analysis/Calculus/Deriv/Basic`. ## Keywords derivative, multiplication -/ universe u v w noncomputable section open scoped Topology Filter ENNReal open Filter Asymptotics Set open ContinuousLinearMap (smulRight smulRight_one_eq_iff) variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F] variable {E : Type w} [NormedAddCommGroup E] [NormedSpace 𝕜 E] variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G] variable {f : 𝕜 → F} variable {f' : F} variable {x : 𝕜} variable {s : Set 𝕜} variable {L : Filter 𝕜} /-! ### Derivative of bilinear maps -/ namespace ContinuousLinearMap variable {B : E →L[𝕜] F →L[𝕜] G} {u : 𝕜 → E} {v : 𝕜 → F} {u' : E} {v' : F} theorem hasDerivWithinAt_of_bilinear (hu : HasDerivWithinAt u u' s x) (hv : HasDerivWithinAt v v' s x) : HasDerivWithinAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) s x := by simpa using (B.hasFDerivWithinAt_of_bilinear hu.hasFDerivWithinAt hv.hasFDerivWithinAt).hasDerivWithinAt theorem hasDerivAt_of_bilinear (hu : HasDerivAt u u' x) (hv : HasDerivAt v v' x) : HasDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by simpa using (B.hasFDerivAt_of_bilinear hu.hasFDerivAt hv.hasFDerivAt).hasDerivAt theorem hasStrictDerivAt_of_bilinear (hu : HasStrictDerivAt u u' x) (hv : HasStrictDerivAt v v' x) : HasStrictDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by simpa using (B.hasStrictFDerivAt_of_bilinear hu.hasStrictFDerivAt hv.hasStrictFDerivAt).hasStrictDerivAt theorem derivWithin_of_bilinear (hu : DifferentiableWithinAt 𝕜 u s x) (hv : DifferentiableWithinAt 𝕜 v s x) : derivWithin (fun y => B (u y) (v y)) s x = B (u x) (derivWithin v s x) + B (derivWithin u s x) (v x) := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x · exact (B.hasDerivWithinAt_of_bilinear hu.hasDerivWithinAt hv.hasDerivWithinAt).derivWithin hsx · simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx] theorem deriv_of_bilinear (hu : DifferentiableAt 𝕜 u x) (hv : DifferentiableAt 𝕜 v x) : deriv (fun y => B (u y) (v y)) x = B (u x) (deriv v x) + B (deriv u x) (v x) := (B.hasDerivAt_of_bilinear hu.hasDerivAt hv.hasDerivAt).deriv end ContinuousLinearMap section SMul /-! ### Derivative of the multiplication of a scalar function and a vector function -/ variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F] [IsScalarTower 𝕜 𝕜' F] {c : 𝕜 → 𝕜'} {c' : 𝕜'} theorem HasDerivWithinAt.smul (hc : HasDerivWithinAt c c' s x) (hf : HasDerivWithinAt f f' s x) : HasDerivWithinAt (fun y => c y • f y) (c x • f' + c' • f x) s x := by simpa using (HasFDerivWithinAt.smul hc hf).hasDerivWithinAt theorem HasDerivAt.smul (hc : HasDerivAt c c' x) (hf : HasDerivAt f f' x) : HasDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by rw [← hasDerivWithinAt_univ] at * exact hc.smul hf nonrec theorem HasStrictDerivAt.smul (hc : HasStrictDerivAt c c' x) (hf : HasStrictDerivAt f f' x) : HasStrictDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by simpa using (hc.smul hf).hasStrictDerivAt theorem derivWithin_smul (hc : DifferentiableWithinAt 𝕜 c s x) (hf : DifferentiableWithinAt 𝕜 f s x) : derivWithin (fun y => c y • f y) s x = c x • derivWithin f s x + derivWithin c s x • f x := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x · exact (hc.hasDerivWithinAt.smul hf.hasDerivWithinAt).derivWithin hsx · simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx] theorem deriv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) : deriv (fun y => c y • f y) x = c x • deriv f x + deriv c x • f x := (hc.hasDerivAt.smul hf.hasDerivAt).deriv theorem HasStrictDerivAt.smul_const (hc : HasStrictDerivAt c c' x) (f : F) : HasStrictDerivAt (fun y => c y • f) (c' • f) x := by have := hc.smul (hasStrictDerivAt_const x f) rwa [smul_zero, zero_add] at this theorem HasDerivWithinAt.smul_const (hc : HasDerivWithinAt c c' s x) (f : F) : HasDerivWithinAt (fun y => c y • f) (c' • f) s x := by have := hc.smul (hasDerivWithinAt_const x s f) rwa [smul_zero, zero_add] at this theorem HasDerivAt.smul_const (hc : HasDerivAt c c' x) (f : F) : HasDerivAt (fun y => c y • f) (c' • f) x := by rw [← hasDerivWithinAt_univ] at * exact hc.smul_const f theorem derivWithin_smul_const (hc : DifferentiableWithinAt 𝕜 c s x) (f : F) : derivWithin (fun y => c y • f) s x = derivWithin c s x • f := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x · exact (hc.hasDerivWithinAt.smul_const f).derivWithin hsx · simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx] theorem deriv_smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) : deriv (fun y => c y • f) x = deriv c x • f := (hc.hasDerivAt.smul_const f).deriv end SMul section ConstSMul variable {R : Type*} [Semiring R] [Module R F] [SMulCommClass 𝕜 R F] [ContinuousConstSMul R F] nonrec theorem HasStrictDerivAt.const_smul (c : R) (hf : HasStrictDerivAt f f' x) : HasStrictDerivAt (fun y => c • f y) (c • f') x := by simpa using (hf.const_smul c).hasStrictDerivAt nonrec theorem HasDerivAtFilter.const_smul (c : R) (hf : HasDerivAtFilter f f' x L) : HasDerivAtFilter (fun y => c • f y) (c • f') x L := by simpa using (hf.const_smul c).hasDerivAtFilter nonrec theorem HasDerivWithinAt.const_smul (c : R) (hf : HasDerivWithinAt f f' s x) : HasDerivWithinAt (fun y => c • f y) (c • f') s x := hf.const_smul c nonrec theorem HasDerivAt.const_smul (c : R) (hf : HasDerivAt f f' x) : HasDerivAt (fun y => c • f y) (c • f') x := hf.const_smul c theorem derivWithin_const_smul (c : R) (hf : DifferentiableWithinAt 𝕜 f s x) : derivWithin (fun y => c • f y) s x = c • derivWithin f s x := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x · exact (hf.hasDerivWithinAt.const_smul c).derivWithin hsx · simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx] theorem deriv_const_smul (c : R) (hf : DifferentiableAt 𝕜 f x) : deriv (fun y => c • f y) x = c • deriv f x := (hf.hasDerivAt.const_smul c).deriv /-- A variant of `deriv_const_smul` without differentiability assumption when the scalar multiplication is by field elements. -/ lemma deriv_const_smul' {f : 𝕜 → F} {x : 𝕜} {R : Type*} [Field R] [Module R F] [SMulCommClass 𝕜 R F] [ContinuousConstSMul R F] (c : R) : deriv (fun y ↦ c • f y) x = c • deriv f x := by by_cases hf : DifferentiableAt 𝕜 f x · exact deriv_const_smul c hf · rcases eq_or_ne c 0 with rfl | hc · simp only [zero_smul, deriv_const'] · have H : ¬DifferentiableAt 𝕜 (fun y ↦ c • f y) x := by contrapose! hf conv => enter [2, y]; rw [← inv_smul_smul₀ hc (f y)] exact DifferentiableAt.const_smul hf c⁻¹ rw [deriv_zero_of_not_differentiableAt hf, deriv_zero_of_not_differentiableAt H, smul_zero] end ConstSMul section Mul /-! ### Derivative of the multiplication of two functions -/ variable {𝕜' 𝔸 : Type*} [NormedField 𝕜'] [NormedRing 𝔸] [NormedAlgebra 𝕜 𝕜'] [NormedAlgebra 𝕜 𝔸] {c d : 𝕜 → 𝔸} {c' d' : 𝔸} {u v : 𝕜 → 𝕜'} theorem HasDerivWithinAt.mul (hc : HasDerivWithinAt c c' s x) (hd : HasDerivWithinAt d d' s x) : HasDerivWithinAt (fun y => c y * d y) (c' * d x + c x * d') s x := by have := (HasFDerivWithinAt.mul' hc hd).hasDerivWithinAt rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul, add_comm] at this theorem HasDerivAt.mul (hc : HasDerivAt c c' x) (hd : HasDerivAt d d' x) : HasDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by rw [← hasDerivWithinAt_univ] at * exact hc.mul hd theorem HasStrictDerivAt.mul (hc : HasStrictDerivAt c c' x) (hd : HasStrictDerivAt d d' x) : HasStrictDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by have := (HasStrictFDerivAt.mul' hc hd).hasStrictDerivAt rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul, add_comm] at this theorem derivWithin_mul (hc : DifferentiableWithinAt 𝕜 c s x) (hd : DifferentiableWithinAt 𝕜 d s x) : derivWithin (fun y => c y * d y) s x = derivWithin c s x * d x + c x * derivWithin d s x := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x · exact (hc.hasDerivWithinAt.mul hd.hasDerivWithinAt).derivWithin hsx · simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx] @[simp] theorem deriv_mul (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) : deriv (fun y => c y * d y) x = deriv c x * d x + c x * deriv d x := (hc.hasDerivAt.mul hd.hasDerivAt).deriv theorem HasDerivWithinAt.mul_const (hc : HasDerivWithinAt c c' s x) (d : 𝔸) : HasDerivWithinAt (fun y => c y * d) (c' * d) s x := by convert hc.mul (hasDerivWithinAt_const x s d) using 1 rw [mul_zero, add_zero] theorem HasDerivAt.mul_const (hc : HasDerivAt c c' x) (d : 𝔸) : HasDerivAt (fun y => c y * d) (c' * d) x := by rw [← hasDerivWithinAt_univ] at * exact hc.mul_const d theorem hasDerivAt_mul_const (c : 𝕜) : HasDerivAt (fun x => x * c) c x := by simpa only [one_mul] using (hasDerivAt_id' x).mul_const c theorem HasStrictDerivAt.mul_const (hc : HasStrictDerivAt c c' x) (d : 𝔸) : HasStrictDerivAt (fun y => c y * d) (c' * d) x := by convert hc.mul (hasStrictDerivAt_const x d) using 1 rw [mul_zero, add_zero]
theorem derivWithin_mul_const (hc : DifferentiableWithinAt 𝕜 c s x) (d : 𝔸) : derivWithin (fun y => c y * d) s x = derivWithin c s x * d := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x
Mathlib/Analysis/Calculus/Deriv/Mul.lean
242
245
/- Copyright (c) 2023 Shogo Saito. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Shogo Saito. Adapted for mathlib by Hunter Monroe -/ import Mathlib.Algebra.BigOperators.Ring.List import Mathlib.Data.Nat.ModEq import Mathlib.Data.Nat.GCD.BigOperators /-! # Chinese Remainder Theorem This file provides definitions and theorems for the Chinese Remainder Theorem. These are used in Gödel's Beta function, which is used in proving Gödel's incompleteness theorems. ## Main result - `chineseRemainderOfList`: Definition of the Chinese remainder of a list ## Tags Chinese Remainder Theorem, Gödel, beta function -/ open scoped Function -- required for scoped `on` notation namespace Nat variable {ι : Type*} lemma modEq_list_prod_iff {a b} {l : List ℕ} (co : l.Pairwise Coprime) : a ≡ b [MOD l.prod] ↔ ∀ i, a ≡ b [MOD l.get i] := by induction' l with m l ih · simp [modEq_one] · have : Coprime m l.prod := coprime_list_prod_right_iff.mpr (List.pairwise_cons.mp co).1 simp only [List.prod_cons, ← modEq_and_modEq_iff_modEq_mul this, ih (List.Pairwise.of_cons co), List.length_cons] constructor · rintro ⟨h0, hs⟩ i cases i using Fin.cases <;> simp_all · intro h; exact ⟨h 0, fun i => h i.succ⟩ lemma modEq_list_prod_iff' {a b} {s : ι → ℕ} {l : List ι} (co : l.Pairwise (Coprime on s)) : a ≡ b [MOD (l.map s).prod] ↔ ∀ i ∈ l, a ≡ b [MOD s i] := by induction' l with i l ih · simp [modEq_one] · have : Coprime (s i) (l.map s).prod := by simp only [coprime_list_prod_right_iff, List.mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂] intro j hj exact (List.pairwise_cons.mp co).1 j hj simp [← modEq_and_modEq_iff_modEq_mul this, ih (List.Pairwise.of_cons co)] variable (a s : ι → ℕ) /-- The natural number less than `(l.map s).prod` congruent to `a i` mod `s i` for all `i ∈ l`. -/ def chineseRemainderOfList : (l : List ι) → l.Pairwise (Coprime on s) → { k // ∀ i ∈ l, k ≡ a i [MOD s i] } | [], _ => ⟨0, by simp⟩ | i :: l, co => by have : Coprime (s i) (l.map s).prod := by simp only [coprime_list_prod_right_iff, List.mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂] intro j hj exact (List.pairwise_cons.mp co).1 j hj have ih := chineseRemainderOfList l co.of_cons have k := chineseRemainder this (a i) ih use k simp only [List.mem_cons, forall_eq_or_imp, k.prop.1, true_and] intro j hj exact ((modEq_list_prod_iff' co.of_cons).mp k.prop.2 j hj).trans (ih.prop j hj) @[simp] theorem chineseRemainderOfList_nil : (chineseRemainderOfList a s [] List.Pairwise.nil : ℕ) = 0 := rfl theorem chineseRemainderOfList_lt_prod (l : List ι) (co : l.Pairwise (Coprime on s)) (hs : ∀ i ∈ l, s i ≠ 0) : chineseRemainderOfList a s l co < (l.map s).prod := by cases l with | nil => simp | cons i l => simp only [chineseRemainderOfList, List.map_cons, List.prod_cons] have : Coprime (s i) (l.map s).prod := by simp only [coprime_list_prod_right_iff, List.mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂] intro j hj exact (List.pairwise_cons.mp co).1 j hj refine chineseRemainder_lt_mul this (a i) (chineseRemainderOfList a s l co.of_cons) (hs i List.mem_cons_self) ?_ simp only [ne_eq, List.prod_eq_zero_iff, List.mem_map, not_exists, not_and] intro j hj exact hs j (List.mem_cons_of_mem _ hj) theorem chineseRemainderOfList_modEq_unique (l : List ι) (co : l.Pairwise (Coprime on s)) {z} (hz : ∀ i ∈ l, z ≡ a i [MOD s i]) : z ≡ chineseRemainderOfList a s l co [MOD (l.map s).prod] := by induction' l with i l ih · simp [modEq_one] · simp only [List.map_cons, List.prod_cons, chineseRemainderOfList] have : Coprime (s i) (l.map s).prod := by simp only [coprime_list_prod_right_iff, List.mem_map, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂] intro j hj exact (List.pairwise_cons.mp co).1 j hj exact chineseRemainder_modEq_unique this (hz i List.mem_cons_self) (ih co.of_cons (fun j hj => hz j (List.mem_cons_of_mem _ hj))) theorem chineseRemainderOfList_perm {l l' : List ι} (hl : l.Perm l') (hs : ∀ i ∈ l, s i ≠ 0) (co : l.Pairwise (Coprime on s)) : (chineseRemainderOfList a s l co : ℕ) = chineseRemainderOfList a s l' (co.perm hl coprime_comm.mpr) := by let z := chineseRemainderOfList a s l' (co.perm hl coprime_comm.mpr) have hlp : (l.map s).prod = (l'.map s).prod := List.Perm.prod_eq (List.Perm.map s hl) exact (chineseRemainderOfList_modEq_unique a s l co (z := z) (fun i hi => z.prop i (hl.symm.mem_iff.mpr hi))).symm.eq_of_lt_of_lt (chineseRemainderOfList_lt_prod _ _ _ _ hs) (by rw [hlp] exact chineseRemainderOfList_lt_prod _ _ _ _ (by simpa [List.Perm.mem_iff hl.symm] using hs)) /-- The natural number less than `(m.map s).prod` congruent to `a i` mod `s i` for all `i ∈ m`. -/ def chineseRemainderOfMultiset {m : Multiset ι} : m.Nodup → (∀ i ∈ m, s i ≠ 0) → Set.Pairwise {x | x ∈ m} (Coprime on s) → { k // ∀ i ∈ m, k ≡ a i [MOD s i] } := Quotient.recOn m (fun l nod _ co => chineseRemainderOfList a s l (List.Nodup.pairwise_of_forall_ne nod co)) (fun l l' (pp : l.Perm l') ↦ funext fun nod' : l'.Nodup => have nod : l.Nodup := pp.symm.nodup_iff.mp nod' funext fun hs' : ∀ i ∈ l', s i ≠ 0 => have hs : ∀ i ∈ l, s i ≠ 0 := by simpa [List.Perm.mem_iff pp] using hs' funext fun co' : Set.Pairwise {x | x ∈ l'} (Coprime on s) => have co : Set.Pairwise {x | x ∈ l} (Coprime on s) := by simpa [List.Perm.mem_iff pp] using co' have lco : l.Pairwise (Coprime on s) := List.Nodup.pairwise_of_forall_ne nod co have : ∀ {m' e nod'' hs'' co''}, @Eq.ndrec (Multiset ι) l (fun m ↦ m.Nodup → (∀ i ∈ m, s i ≠ 0) → Set.Pairwise {x | x ∈ m} (Coprime on s) → { k // ∀ i ∈ m, k ≡ a i [MOD s i] }) (fun nod _ co ↦ chineseRemainderOfList a s l (List.Nodup.pairwise_of_forall_ne nod co)) m' e nod'' hs'' co'' = (chineseRemainderOfList a s l lco : ℕ) := by rintro _ rfl _ _ _; rfl by ext; exact this.trans <| chineseRemainderOfList_perm a s pp hs lco)
theorem chineseRemainderOfMultiset_lt_prod {m : Multiset ι} (nod : m.Nodup) (hs : ∀ i ∈ m, s i ≠ 0) (pp : Set.Pairwise {x | x ∈ m} (Coprime on s)) : chineseRemainderOfMultiset a s nod hs pp < (m.map s).prod := by induction' m using Quot.ind with l unfold chineseRemainderOfMultiset simpa using chineseRemainderOfList_lt_prod a s l
Mathlib/Data/Nat/ChineseRemainder.lean
145
151
/- Copyright (c) 2018 Robert Y. Lewis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Robert Y. Lewis, Mario Carneiro, Johan Commelin -/ import Mathlib.NumberTheory.Padics.PadicNumbers import Mathlib.RingTheory.DiscreteValuationRing.Basic /-! # p-adic integers This file defines the `p`-adic integers `ℤ_[p]` as the subtype of `ℚ_[p]` with norm `≤ 1`. We show that `ℤ_[p]` * is complete, * is nonarchimedean, * is a normed ring, * is a local ring, and * is a discrete valuation ring. The relation between `ℤ_[p]` and `ZMod p` is established in another file. ## Important definitions * `PadicInt` : the type of `p`-adic integers ## Notation We introduce the notation `ℤ_[p]` for the `p`-adic integers. ## Implementation notes Much, but not all, of this file assumes that `p` is prime. This assumption is inferred automatically by taking `[Fact p.Prime]` as a type class argument. Coercions into `ℤ_[p]` are set up to work with the `norm_cast` tactic. ## References * [F. Q. Gouvêa, *p-adic numbers*][gouvea1997] * [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019] * <https://en.wikipedia.org/wiki/P-adic_number> ## Tags p-adic, p adic, padic, p-adic integer -/ open Padic Metric IsLocalRing noncomputable section variable (p : ℕ) [hp : Fact p.Prime] /-- The `p`-adic integers `ℤ_[p]` are the `p`-adic numbers with norm `≤ 1`. -/ def PadicInt : Type := {x : ℚ_[p] // ‖x‖ ≤ 1} /-- The ring of `p`-adic integers. -/ notation "ℤ_[" p "]" => PadicInt p namespace PadicInt variable {p} {x y : ℤ_[p]} /-! ### Ring structure and coercion to `ℚ_[p]` -/ instance : Coe ℤ_[p] ℚ_[p] := ⟨Subtype.val⟩ theorem ext {x y : ℤ_[p]} : (x : ℚ_[p]) = y → x = y := Subtype.ext variable (p) /-- The `p`-adic integers as a subring of `ℚ_[p]`. -/ def subring : Subring ℚ_[p] where carrier := { x : ℚ_[p] | ‖x‖ ≤ 1 } zero_mem' := by norm_num one_mem' := by norm_num add_mem' hx hy := (padicNormE.nonarchimedean _ _).trans <| max_le_iff.2 ⟨hx, hy⟩ mul_mem' hx hy := (padicNormE.mul _ _).trans_le <| mul_le_one₀ hx (norm_nonneg _) hy neg_mem' hx := (norm_neg _).trans_le hx @[simp] theorem mem_subring_iff {x : ℚ_[p]} : x ∈ subring p ↔ ‖x‖ ≤ 1 := Iff.rfl variable {p} instance instCommRing : CommRing ℤ_[p] := inferInstanceAs <| CommRing (subring p) instance : Inhabited ℤ_[p] := ⟨0⟩ @[simp] theorem mk_zero {h} : (⟨0, h⟩ : ℤ_[p]) = (0 : ℤ_[p]) := rfl @[simp, norm_cast] theorem coe_add (z1 z2 : ℤ_[p]) : ((z1 + z2 : ℤ_[p]) : ℚ_[p]) = z1 + z2 := rfl @[simp, norm_cast] theorem coe_mul (z1 z2 : ℤ_[p]) : ((z1 * z2 : ℤ_[p]) : ℚ_[p]) = z1 * z2 := rfl @[simp, norm_cast] theorem coe_neg (z1 : ℤ_[p]) : ((-z1 : ℤ_[p]) : ℚ_[p]) = -z1 := rfl @[simp, norm_cast] theorem coe_sub (z1 z2 : ℤ_[p]) : ((z1 - z2 : ℤ_[p]) : ℚ_[p]) = z1 - z2 := rfl @[simp, norm_cast] theorem coe_one : ((1 : ℤ_[p]) : ℚ_[p]) = 1 := rfl @[simp, norm_cast] theorem coe_zero : ((0 : ℤ_[p]) : ℚ_[p]) = 0 := rfl @[simp] lemma coe_eq_zero : (x : ℚ_[p]) = 0 ↔ x = 0 := by rw [← coe_zero, Subtype.coe_inj] lemma coe_ne_zero : (x : ℚ_[p]) ≠ 0 ↔ x ≠ 0 := coe_eq_zero.not @[simp, norm_cast] theorem coe_natCast (n : ℕ) : ((n : ℤ_[p]) : ℚ_[p]) = n := rfl @[simp, norm_cast] theorem coe_intCast (z : ℤ) : ((z : ℤ_[p]) : ℚ_[p]) = z := rfl /-- The coercion from `ℤ_[p]` to `ℚ_[p]` as a ring homomorphism. -/ def Coe.ringHom : ℤ_[p] →+* ℚ_[p] := (subring p).subtype @[simp, norm_cast] theorem coe_pow (x : ℤ_[p]) (n : ℕ) : (↑(x ^ n) : ℚ_[p]) = (↑x : ℚ_[p]) ^ n := rfl theorem mk_coe (k : ℤ_[p]) : (⟨k, k.2⟩ : ℤ_[p]) = k := by simp /-- The inverse of a `p`-adic integer with norm equal to `1` is also a `p`-adic integer. Otherwise, the inverse is defined to be `0`. -/ def inv : ℤ_[p] → ℤ_[p] | ⟨k, _⟩ => if h : ‖k‖ = 1 then ⟨k⁻¹, by simp [h]⟩ else 0 instance : CharZero ℤ_[p] where cast_injective m n h := Nat.cast_injective (R := ℚ_[p]) (by rw [Subtype.ext_iff] at h; norm_cast at h) @[norm_cast] theorem intCast_eq (z1 z2 : ℤ) : (z1 : ℤ_[p]) = z2 ↔ z1 = z2 := by simp /-- A sequence of integers that is Cauchy with respect to the `p`-adic norm converges to a `p`-adic integer. -/ def ofIntSeq (seq : ℕ → ℤ) (h : IsCauSeq (padicNorm p) fun n => seq n) : ℤ_[p] := ⟨⟦⟨_, h⟩⟧, show ↑(PadicSeq.norm _) ≤ (1 : ℝ) by rw [PadicSeq.norm] split_ifs with hne <;> norm_cast apply padicNorm.of_int⟩ /-! ### Instances We now show that `ℤ_[p]` is a * complete metric space * normed ring * integral domain -/ variable (p) instance : MetricSpace ℤ_[p] := Subtype.metricSpace instance : IsUltrametricDist ℤ_[p] := IsUltrametricDist.subtype _ instance completeSpace : CompleteSpace ℤ_[p] := have : IsClosed { x : ℚ_[p] | ‖x‖ ≤ 1 } := isClosed_le continuous_norm continuous_const this.completeSpace_coe instance : Norm ℤ_[p] := ⟨fun z => ‖(z : ℚ_[p])‖⟩ variable {p} in theorem norm_def {z : ℤ_[p]} : ‖z‖ = ‖(z : ℚ_[p])‖ := rfl instance : NormedCommRing ℤ_[p] where __ := instCommRing dist_eq := fun ⟨_, _⟩ ⟨_, _⟩ ↦ rfl norm_mul_le := by simp [norm_def] instance : NormOneClass ℤ_[p] := ⟨norm_def.trans norm_one⟩ instance : NormMulClass ℤ_[p] := ⟨fun x y ↦ by simp [norm_def]⟩ instance : IsDomain ℤ_[p] := NoZeroDivisors.to_isDomain _ variable {p} /-! ### Norm -/ theorem norm_le_one (z : ℤ_[p]) : ‖z‖ ≤ 1 := z.2 theorem nonarchimedean (q r : ℤ_[p]) : ‖q + r‖ ≤ max ‖q‖ ‖r‖ := padicNormE.nonarchimedean _ _ theorem norm_add_eq_max_of_ne {q r : ℤ_[p]} : ‖q‖ ≠ ‖r‖ → ‖q + r‖ = max ‖q‖ ‖r‖ := padicNormE.add_eq_max_of_ne theorem norm_eq_of_norm_add_lt_right {z1 z2 : ℤ_[p]} (h : ‖z1 + z2‖ < ‖z2‖) : ‖z1‖ = ‖z2‖ := by_contra fun hne => not_lt_of_ge (by rw [norm_add_eq_max_of_ne hne]; apply le_max_right) h theorem norm_eq_of_norm_add_lt_left {z1 z2 : ℤ_[p]} (h : ‖z1 + z2‖ < ‖z1‖) : ‖z1‖ = ‖z2‖ := by_contra fun hne => not_lt_of_ge (by rw [norm_add_eq_max_of_ne hne]; apply le_max_left) h @[simp] theorem padic_norm_e_of_padicInt (z : ℤ_[p]) : ‖(z : ℚ_[p])‖ = ‖z‖ := by simp [norm_def] theorem norm_intCast_eq_padic_norm (z : ℤ) : ‖(z : ℤ_[p])‖ = ‖(z : ℚ_[p])‖ := by simp [norm_def] @[simp] theorem norm_eq_padic_norm {q : ℚ_[p]} (hq : ‖q‖ ≤ 1) : @norm ℤ_[p] _ ⟨q, hq⟩ = ‖q‖ := rfl @[simp] theorem norm_p : ‖(p : ℤ_[p])‖ = (p : ℝ)⁻¹ := padicNormE.norm_p theorem norm_p_pow (n : ℕ) : ‖(p : ℤ_[p]) ^ n‖ = (p : ℝ) ^ (-n : ℤ) := by simp private def cauSeq_to_rat_cauSeq (f : CauSeq ℤ_[p] norm) : CauSeq ℚ_[p] fun a => ‖a‖ := ⟨fun n => f n, fun _ hε => by simpa [norm, norm_def] using f.cauchy hε⟩ variable (p) instance complete : CauSeq.IsComplete ℤ_[p] norm := ⟨fun f => have hqn : ‖CauSeq.lim (cauSeq_to_rat_cauSeq f)‖ ≤ 1 := padicNormE_lim_le zero_lt_one fun _ => norm_le_one _ ⟨⟨_, hqn⟩, fun ε => by simpa [norm, norm_def] using CauSeq.equiv_lim (cauSeq_to_rat_cauSeq f) ε⟩⟩ theorem exists_pow_neg_lt {ε : ℝ} (hε : 0 < ε) : ∃ k : ℕ, (p : ℝ) ^ (-(k : ℤ)) < ε := by obtain ⟨k, hk⟩ := exists_nat_gt ε⁻¹ use k rw [← inv_lt_inv₀ hε (zpow_pos _ _)] · rw [zpow_neg, inv_inv, zpow_natCast] apply lt_of_lt_of_le hk norm_cast apply le_of_lt convert Nat.lt_pow_self _ using 1 exact hp.1.one_lt · exact mod_cast hp.1.pos theorem exists_pow_neg_lt_rat {ε : ℚ} (hε : 0 < ε) : ∃ k : ℕ, (p : ℚ) ^ (-(k : ℤ)) < ε := by obtain ⟨k, hk⟩ := @exists_pow_neg_lt p _ ε (mod_cast hε) use k rw [show (p : ℝ) = (p : ℚ) by simp] at hk exact mod_cast hk variable {p} theorem norm_int_lt_one_iff_dvd (k : ℤ) : ‖(k : ℤ_[p])‖ < 1 ↔ (p : ℤ) ∣ k := suffices ‖(k : ℚ_[p])‖ < 1 ↔ ↑p ∣ k by rwa [norm_intCast_eq_padic_norm] padicNormE.norm_int_lt_one_iff_dvd k theorem norm_int_le_pow_iff_dvd {k : ℤ} {n : ℕ} : ‖(k : ℤ_[p])‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ (p ^ n : ℤ) ∣ k := suffices ‖(k : ℚ_[p])‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ (p ^ n : ℤ) ∣ k by simpa [norm_intCast_eq_padic_norm] padicNormE.norm_int_le_pow_iff_dvd _ _ /-! ### Valuation on `ℤ_[p]` -/ lemma valuation_coe_nonneg : 0 ≤ (x : ℚ_[p]).valuation := by obtain rfl | hx := eq_or_ne x 0 · simp have := x.2 rwa [Padic.norm_eq_zpow_neg_valuation <| coe_ne_zero.2 hx, zpow_le_one_iff_right₀, neg_nonpos] at this exact mod_cast hp.out.one_lt /-- `PadicInt.valuation` lifts the `p`-adic valuation on `ℚ` to `ℤ_[p]`. -/ def valuation (x : ℤ_[p]) : ℕ := (x : ℚ_[p]).valuation.toNat @[simp, norm_cast] lemma valuation_coe (x : ℤ_[p]) : (x : ℚ_[p]).valuation = x.valuation := by simp [valuation, valuation_coe_nonneg] @[simp] lemma valuation_zero : valuation (0 : ℤ_[p]) = 0 := by simp [valuation] @[simp] lemma valuation_one : valuation (1 : ℤ_[p]) = 0 := by simp [valuation] @[simp] lemma valuation_p : valuation (p : ℤ_[p]) = 1 := by simp [valuation] lemma le_valuation_add (hxy : x + y ≠ 0) : min x.valuation y.valuation ≤ (x + y).valuation := by zify; simpa [← valuation_coe] using Padic.le_valuation_add <| coe_ne_zero.2 hxy @[simp] lemma valuation_mul (hx : x ≠ 0) (hy : y ≠ 0) : (x * y).valuation = x.valuation + y.valuation := by zify; simp [← valuation_coe, Padic.valuation_mul (coe_ne_zero.2 hx) (coe_ne_zero.2 hy)] @[simp] lemma valuation_pow (x : ℤ_[p]) (n : ℕ) : (x ^ n).valuation = n * x.valuation := by zify; simp [← valuation_coe] lemma norm_eq_zpow_neg_valuation {x : ℤ_[p]} (hx : x ≠ 0) : ‖x‖ = p ^ (-x.valuation : ℤ) := by simp [norm_def, Padic.norm_eq_zpow_neg_valuation <| coe_ne_zero.2 hx] @[deprecated (since := "2024-12-10")] alias norm_eq_pow_val := norm_eq_zpow_neg_valuation -- TODO: Do we really need this lemma? @[simp] theorem valuation_p_pow_mul (n : ℕ) (c : ℤ_[p]) (hc : c ≠ 0) : ((p : ℤ_[p]) ^ n * c).valuation = n + c.valuation := by rw [valuation_mul (NeZero.ne _) hc, valuation_pow, valuation_p, mul_one] section Units /-! ### Units of `ℤ_[p]` -/ theorem mul_inv : ∀ {z : ℤ_[p]}, ‖z‖ = 1 → z * z.inv = 1 | ⟨k, _⟩, h => by have hk : k ≠ 0 := fun h' => zero_ne_one' ℚ_[p] (by simp [h'] at h) unfold PadicInt.inv rw [norm_eq_padic_norm] at h dsimp only rw [dif_pos h] apply Subtype.ext_iff_val.2 simp [mul_inv_cancel₀ hk] theorem inv_mul {z : ℤ_[p]} (hz : ‖z‖ = 1) : z.inv * z = 1 := by rw [mul_comm, mul_inv hz] theorem isUnit_iff {z : ℤ_[p]} : IsUnit z ↔ ‖z‖ = 1 := ⟨fun h => by rcases isUnit_iff_dvd_one.1 h with ⟨w, eq⟩ refine le_antisymm (norm_le_one _) ?_ have := mul_le_mul_of_nonneg_left (norm_le_one w) (norm_nonneg z) rwa [mul_one, ← norm_mul, ← eq, norm_one] at this, fun h => ⟨⟨z, z.inv, mul_inv h, inv_mul h⟩, rfl⟩⟩ theorem norm_lt_one_add {z1 z2 : ℤ_[p]} (hz1 : ‖z1‖ < 1) (hz2 : ‖z2‖ < 1) : ‖z1 + z2‖ < 1 := lt_of_le_of_lt (nonarchimedean _ _) (max_lt hz1 hz2) theorem norm_lt_one_mul {z1 z2 : ℤ_[p]} (hz2 : ‖z2‖ < 1) : ‖z1 * z2‖ < 1 := calc ‖z1 * z2‖ = ‖z1‖ * ‖z2‖ := by simp _ < 1 := mul_lt_one_of_nonneg_of_lt_one_right (norm_le_one _) (norm_nonneg _) hz2 theorem mem_nonunits {z : ℤ_[p]} : z ∈ nonunits ℤ_[p] ↔ ‖z‖ < 1 := by rw [lt_iff_le_and_ne]; simp [norm_le_one z, nonunits, isUnit_iff] theorem not_isUnit_iff {z : ℤ_[p]} : ¬IsUnit z ↔ ‖z‖ < 1 := by simpa using mem_nonunits /-- A `p`-adic number `u` with `‖u‖ = 1` is a unit of `ℤ_[p]`. -/ def mkUnits {u : ℚ_[p]} (h : ‖u‖ = 1) : ℤ_[p]ˣ := let z : ℤ_[p] := ⟨u, le_of_eq h⟩ ⟨z, z.inv, mul_inv h, inv_mul h⟩ @[simp] theorem mkUnits_eq {u : ℚ_[p]} (h : ‖u‖ = 1) : ((mkUnits h : ℤ_[p]) : ℚ_[p]) = u := rfl @[simp] theorem norm_units (u : ℤ_[p]ˣ) : ‖(u : ℤ_[p])‖ = 1 := isUnit_iff.mp <| by simp /-- `unitCoeff hx` is the unit `u` in the unique representation `x = u * p ^ n`. See `unitCoeff_spec`. -/ def unitCoeff {x : ℤ_[p]} (hx : x ≠ 0) : ℤ_[p]ˣ := let u : ℚ_[p] := x * (p : ℚ_[p]) ^ (-x.valuation : ℤ) have hu : ‖u‖ = 1 := by simp [u, hx, pow_ne_zero _ (NeZero.ne _), norm_eq_zpow_neg_valuation] mkUnits hu @[simp] theorem unitCoeff_coe {x : ℤ_[p]} (hx : x ≠ 0) : (unitCoeff hx : ℚ_[p]) = x * (p : ℚ_[p]) ^ (-x.valuation : ℤ) := rfl theorem unitCoeff_spec {x : ℤ_[p]} (hx : x ≠ 0) : x = (unitCoeff hx : ℤ_[p]) * (p : ℤ_[p]) ^ x.valuation := by apply Subtype.coe_injective push_cast rw [unitCoeff_coe, mul_assoc, ← zpow_natCast, ← zpow_add₀] · simp · exact NeZero.ne _ end Units section NormLeIff /-! ### Various characterizations of open unit balls -/ theorem norm_le_pow_iff_le_valuation (x : ℤ_[p]) (hx : x ≠ 0) (n : ℕ) : ‖x‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ n ≤ x.valuation := by rw [norm_eq_zpow_neg_valuation hx, zpow_le_zpow_iff_right₀, neg_le_neg_iff, Nat.cast_le] exact mod_cast hp.out.one_lt theorem mem_span_pow_iff_le_valuation (x : ℤ_[p]) (hx : x ≠ 0) (n : ℕ) : x ∈ (Ideal.span {(p : ℤ_[p]) ^ n} : Ideal ℤ_[p]) ↔ n ≤ x.valuation := by rw [Ideal.mem_span_singleton] constructor · rintro ⟨c, rfl⟩ suffices c ≠ 0 by rw [valuation_p_pow_mul _ _ this] exact le_self_add contrapose! hx rw [hx, mul_zero] · nth_rewrite 2 [unitCoeff_spec hx] simpa [Units.isUnit, IsUnit.dvd_mul_left] using pow_dvd_pow _ theorem norm_le_pow_iff_mem_span_pow (x : ℤ_[p]) (n : ℕ) : ‖x‖ ≤ (p : ℝ) ^ (-n : ℤ) ↔ x ∈ (Ideal.span {(p : ℤ_[p]) ^ n} : Ideal ℤ_[p]) := by by_cases hx : x = 0 · subst hx simp only [norm_zero, zpow_neg, zpow_natCast, inv_nonneg, iff_true, Submodule.zero_mem] exact mod_cast Nat.zero_le _ rw [norm_le_pow_iff_le_valuation x hx, mem_span_pow_iff_le_valuation x hx] theorem norm_le_pow_iff_norm_lt_pow_add_one (x : ℤ_[p]) (n : ℤ) : ‖x‖ ≤ (p : ℝ) ^ n ↔ ‖x‖ < (p : ℝ) ^ (n + 1) := by rw [norm_def]; exact Padic.norm_le_pow_iff_norm_lt_pow_add_one _ _ theorem norm_lt_pow_iff_norm_le_pow_sub_one (x : ℤ_[p]) (n : ℤ) : ‖x‖ < (p : ℝ) ^ n ↔ ‖x‖ ≤ (p : ℝ) ^ (n - 1) := by rw [norm_le_pow_iff_norm_lt_pow_add_one, sub_add_cancel] theorem norm_lt_one_iff_dvd (x : ℤ_[p]) : ‖x‖ < 1 ↔ ↑p ∣ x := by have := norm_le_pow_iff_mem_span_pow x 1 rw [Ideal.mem_span_singleton, pow_one] at this rw [← this, norm_le_pow_iff_norm_lt_pow_add_one] simp only [zpow_zero, Int.ofNat_zero, Int.natCast_succ, neg_add_cancel, zero_add] @[simp] theorem pow_p_dvd_int_iff (n : ℕ) (a : ℤ) : (p : ℤ_[p]) ^ n ∣ a ↔ (p ^ n : ℤ) ∣ a := by rw [← Nat.cast_pow, ← norm_int_le_pow_iff_dvd, norm_le_pow_iff_mem_span_pow, Ideal.mem_span_singleton, Nat.cast_pow] end NormLeIff section Dvr /-! ### Discrete valuation ring -/ instance : IsLocalRing ℤ_[p] := IsLocalRing.of_nonunits_add <| by simp only [mem_nonunits]; exact fun x y => norm_lt_one_add theorem p_nonnunit : (p : ℤ_[p]) ∈ nonunits ℤ_[p] := by have : (p : ℝ)⁻¹ < 1 := inv_lt_one_of_one_lt₀ <| mod_cast hp.out.one_lt rwa [← norm_p, ← mem_nonunits] at this theorem maximalIdeal_eq_span_p : maximalIdeal ℤ_[p] = Ideal.span {(p : ℤ_[p])} := by apply le_antisymm · intro x hx simp only [IsLocalRing.mem_maximalIdeal, mem_nonunits] at hx rwa [Ideal.mem_span_singleton, ← norm_lt_one_iff_dvd] · rw [Ideal.span_le, Set.singleton_subset_iff] exact p_nonnunit theorem prime_p : Prime (p : ℤ_[p]) := by rw [← Ideal.span_singleton_prime, ← maximalIdeal_eq_span_p] · infer_instance · exact NeZero.ne _
Mathlib/NumberTheory/Padics/PadicIntegers.lean
448
448
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Floris van Doorn -/ import Mathlib.Data.Countable.Small import Mathlib.Data.Fintype.BigOperators import Mathlib.Data.Fintype.Powerset import Mathlib.Data.Nat.Cast.Order.Basic import Mathlib.Data.Set.Countable import Mathlib.Logic.Equiv.Fin.Basic import Mathlib.Logic.Small.Set import Mathlib.Logic.UnivLE import Mathlib.SetTheory.Cardinal.Order /-! # Basic results on cardinal numbers We provide a collection of basic results on cardinal numbers, in particular focussing on finite/countable/small types and sets. ## Main definitions * `Cardinal.powerlt a b` or `a ^< b` is defined as the supremum of `a ^ c` for `c < b`. ## References * <https://en.wikipedia.org/wiki/Cardinal_number> ## Tags cardinal number, cardinal arithmetic, cardinal exponentiation, aleph, Cantor's theorem, König's theorem, Konig's theorem -/ assert_not_exists Field open List (Vector) open Function Order Set noncomputable section universe u v w v' w' variable {α β : Type u} namespace Cardinal /-! ### Lifting cardinals to a higher universe -/ @[simp] lemma mk_preimage_down {s : Set α} : #(ULift.down.{v} ⁻¹' s) = lift.{v} (#s) := by rw [← mk_uLift, Cardinal.eq] constructor let f : ULift.down ⁻¹' s → ULift s := fun x ↦ ULift.up (restrictPreimage s ULift.down x) have : Function.Bijective f := ULift.up_bijective.comp (restrictPreimage_bijective _ (ULift.down_bijective)) exact Equiv.ofBijective f this -- `simp` can't figure out universe levels: normal form is `lift_mk_shrink'`. theorem lift_mk_shrink (α : Type u) [Small.{v} α] : Cardinal.lift.{max u w} #(Shrink.{v} α) = Cardinal.lift.{max v w} #α := lift_mk_eq.2 ⟨(equivShrink α).symm⟩ @[simp] theorem lift_mk_shrink' (α : Type u) [Small.{v} α] : Cardinal.lift.{u} #(Shrink.{v} α) = Cardinal.lift.{v} #α := lift_mk_shrink.{u, v, 0} α @[simp] theorem lift_mk_shrink'' (α : Type max u v) [Small.{v} α] : Cardinal.lift.{u} #(Shrink.{v} α) = #α := by rw [← lift_umax, lift_mk_shrink.{max u v, v, 0} α, ← lift_umax, lift_id] theorem prod_eq_of_fintype {α : Type u} [h : Fintype α] (f : α → Cardinal.{v}) : prod f = Cardinal.lift.{u} (∏ i, f i) := by revert f refine Fintype.induction_empty_option ?_ ?_ ?_ α (h_fintype := h) · intro α β hβ e h f letI := Fintype.ofEquiv β e.symm rw [← e.prod_comp f, ← h] exact mk_congr (e.piCongrLeft _).symm · intro f rw [Fintype.univ_pempty, Finset.prod_empty, lift_one, Cardinal.prod, mk_eq_one] · intro α hα h f rw [Cardinal.prod, mk_congr Equiv.piOptionEquivProd, mk_prod, lift_umax.{v, u}, mk_out, ← Cardinal.prod, lift_prod, Fintype.prod_option, lift_mul, ← h fun a => f (some a)] simp only [lift_id] /-! ### Basic cardinals -/ theorem le_one_iff_subsingleton {α : Type u} : #α ≤ 1 ↔ Subsingleton α := ⟨fun ⟨f⟩ => ⟨fun _ _ => f.injective (Subsingleton.elim _ _)⟩, fun ⟨h⟩ => ⟨fun _ => ULift.up 0, fun _ _ _ => h _ _⟩⟩ @[simp] theorem mk_le_one_iff_set_subsingleton {s : Set α} : #s ≤ 1 ↔ s.Subsingleton := le_one_iff_subsingleton.trans s.subsingleton_coe alias ⟨_, _root_.Set.Subsingleton.cardinalMk_le_one⟩ := mk_le_one_iff_set_subsingleton @[deprecated (since := "2024-11-10")] alias _root_.Set.Subsingleton.cardinal_mk_le_one := Set.Subsingleton.cardinalMk_le_one private theorem cast_succ (n : ℕ) : ((n + 1 : ℕ) : Cardinal.{u}) = n + 1 := by change #(ULift.{u} _) = #(ULift.{u} _) + 1 rw [← mk_option] simp /-! ### Order properties -/ theorem one_lt_iff_nontrivial {α : Type u} : 1 < #α ↔ Nontrivial α := by rw [← not_le, le_one_iff_subsingleton, ← not_nontrivial_iff_subsingleton, Classical.not_not] lemma sInf_eq_zero_iff {s : Set Cardinal} : sInf s = 0 ↔ s = ∅ ∨ ∃ a ∈ s, a = 0 := by refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩ · rcases s.eq_empty_or_nonempty with rfl | hne · exact Or.inl rfl · exact Or.inr ⟨sInf s, csInf_mem hne, h⟩ · rcases h with rfl | ⟨a, ha, rfl⟩ · exact Cardinal.sInf_empty · exact eq_bot_iff.2 (csInf_le' ha) lemma iInf_eq_zero_iff {ι : Sort*} {f : ι → Cardinal} : (⨅ i, f i) = 0 ↔ IsEmpty ι ∨ ∃ i, f i = 0 := by simp [iInf, sInf_eq_zero_iff] /-- A variant of `ciSup_of_empty` but with `0` on the RHS for convenience -/ protected theorem iSup_of_empty {ι} (f : ι → Cardinal) [IsEmpty ι] : iSup f = 0 := ciSup_of_empty f @[simp] theorem lift_sInf (s : Set Cardinal) : lift.{u, v} (sInf s) = sInf (lift.{u, v} '' s) := by rcases eq_empty_or_nonempty s with (rfl | hs) · simp · exact lift_monotone.map_csInf hs @[simp] theorem lift_iInf {ι} (f : ι → Cardinal) : lift.{u, v} (iInf f) = ⨅ i, lift.{u, v} (f i) := by unfold iInf convert lift_sInf (range f) simp_rw [← comp_apply (f := lift), range_comp] end Cardinal /-! ### Small sets of cardinals -/ namespace Cardinal instance small_Iic (a : Cardinal.{u}) : Small.{u} (Iic a) := by rw [← mk_out a] apply @small_of_surjective (Set a.out) (Iic #a.out) _ fun x => ⟨#x, mk_set_le x⟩ rintro ⟨x, hx⟩ simpa using le_mk_iff_exists_set.1 hx instance small_Iio (a : Cardinal.{u}) : Small.{u} (Iio a) := small_subset Iio_subset_Iic_self instance small_Icc (a b : Cardinal.{u}) : Small.{u} (Icc a b) := small_subset Icc_subset_Iic_self instance small_Ico (a b : Cardinal.{u}) : Small.{u} (Ico a b) := small_subset Ico_subset_Iio_self instance small_Ioc (a b : Cardinal.{u}) : Small.{u} (Ioc a b) := small_subset Ioc_subset_Iic_self instance small_Ioo (a b : Cardinal.{u}) : Small.{u} (Ioo a b) := small_subset Ioo_subset_Iio_self /-- A set of cardinals is bounded above iff it's small, i.e. it corresponds to a usual ZFC set. -/ theorem bddAbove_iff_small {s : Set Cardinal.{u}} : BddAbove s ↔ Small.{u} s := ⟨fun ⟨a, ha⟩ => @small_subset _ (Iic a) s (fun _ h => ha h) _, by rintro ⟨ι, ⟨e⟩⟩ use sum.{u, u} fun x ↦ e.symm x intro a ha simpa using le_sum (fun x ↦ e.symm x) (e ⟨a, ha⟩)⟩ theorem bddAbove_of_small (s : Set Cardinal.{u}) [h : Small.{u} s] : BddAbove s := bddAbove_iff_small.2 h theorem bddAbove_range {ι : Type*} [Small.{u} ι] (f : ι → Cardinal.{u}) : BddAbove (Set.range f) := bddAbove_of_small _ theorem bddAbove_image (f : Cardinal.{u} → Cardinal.{max u v}) {s : Set Cardinal.{u}} (hs : BddAbove s) : BddAbove (f '' s) := by rw [bddAbove_iff_small] at hs ⊢ exact small_lift _ theorem bddAbove_range_comp {ι : Type u} {f : ι → Cardinal.{v}} (hf : BddAbove (range f)) (g : Cardinal.{v} → Cardinal.{max v w}) : BddAbove (range (g ∘ f)) := by rw [range_comp] exact bddAbove_image g hf /-- The type of cardinals in universe `u` is not `Small.{u}`. This is a version of the Burali-Forti paradox. -/ theorem _root_.not_small_cardinal : ¬ Small.{u} Cardinal.{max u v} := by intro h have := small_lift.{_, v} Cardinal.{max u v} rw [← small_univ_iff, ← bddAbove_iff_small] at this exact not_bddAbove_univ this instance uncountable : Uncountable Cardinal.{u} := Uncountable.of_not_small not_small_cardinal.{u} /-! ### Bounds on suprema -/ theorem sum_le_iSup_lift {ι : Type u} (f : ι → Cardinal.{max u v}) : sum f ≤ Cardinal.lift #ι * iSup f := by rw [← (iSup f).lift_id, ← lift_umax, lift_umax.{max u v, u}, ← sum_const] exact sum_le_sum _ _ (le_ciSup <| bddAbove_of_small _) theorem sum_le_iSup {ι : Type u} (f : ι → Cardinal.{u}) : sum f ≤ #ι * iSup f := by rw [← lift_id #ι] exact sum_le_iSup_lift f /-- The lift of a supremum is the supremum of the lifts. -/ theorem lift_sSup {s : Set Cardinal} (hs : BddAbove s) : lift.{u} (sSup s) = sSup (lift.{u} '' s) := by apply ((le_csSup_iff' (bddAbove_image.{_,u} _ hs)).2 fun c hc => _).antisymm (csSup_le' _) · intro c hc by_contra h obtain ⟨d, rfl⟩ := Cardinal.mem_range_lift_of_le (not_le.1 h).le simp_rw [lift_le] at h hc rw [csSup_le_iff' hs] at h exact h fun a ha => lift_le.1 <| hc (mem_image_of_mem _ ha) · rintro i ⟨j, hj, rfl⟩ exact lift_le.2 (le_csSup hs hj) /-- The lift of a supremum is the supremum of the lifts. -/ theorem lift_iSup {ι : Type v} {f : ι → Cardinal.{w}} (hf : BddAbove (range f)) : lift.{u} (iSup f) = ⨆ i, lift.{u} (f i) := by rw [iSup, iSup, lift_sSup hf, ← range_comp] simp [Function.comp_def] /-- To prove that the lift of a supremum is bounded by some cardinal `t`, it suffices to show that the lift of each cardinal is bounded by `t`. -/ theorem lift_iSup_le {ι : Type v} {f : ι → Cardinal.{w}} {t : Cardinal} (hf : BddAbove (range f)) (w : ∀ i, lift.{u} (f i) ≤ t) : lift.{u} (iSup f) ≤ t := by rw [lift_iSup hf] exact ciSup_le' w @[simp] theorem lift_iSup_le_iff {ι : Type v} {f : ι → Cardinal.{w}} (hf : BddAbove (range f)) {t : Cardinal} : lift.{u} (iSup f) ≤ t ↔ ∀ i, lift.{u} (f i) ≤ t := by rw [lift_iSup hf] exact ciSup_le_iff' (bddAbove_range_comp.{_,_,u} hf _) /-- To prove an inequality between the lifts to a common universe of two different supremums, it suffices to show that the lift of each cardinal from the smaller supremum if bounded by the lift of some cardinal from the larger supremum. -/ theorem lift_iSup_le_lift_iSup {ι : Type v} {ι' : Type v'} {f : ι → Cardinal.{w}} {f' : ι' → Cardinal.{w'}} (hf : BddAbove (range f)) (hf' : BddAbove (range f')) {g : ι → ι'} (h : ∀ i, lift.{w'} (f i) ≤ lift.{w} (f' (g i))) : lift.{w'} (iSup f) ≤ lift.{w} (iSup f') := by rw [lift_iSup hf, lift_iSup hf'] exact ciSup_mono' (bddAbove_range_comp.{_,_,w} hf' _) fun i => ⟨_, h i⟩ /-- A variant of `lift_iSup_le_lift_iSup` with universes specialized via `w = v` and `w' = v'`. This is sometimes necessary to avoid universe unification issues. -/ theorem lift_iSup_le_lift_iSup' {ι : Type v} {ι' : Type v'} {f : ι → Cardinal.{v}} {f' : ι' → Cardinal.{v'}} (hf : BddAbove (range f)) (hf' : BddAbove (range f')) (g : ι → ι') (h : ∀ i, lift.{v'} (f i) ≤ lift.{v} (f' (g i))) : lift.{v'} (iSup f) ≤ lift.{v} (iSup f') := lift_iSup_le_lift_iSup hf hf' h /-! ### Properties about the cast from `ℕ` -/ theorem mk_finset_of_fintype [Fintype α] : #(Finset α) = 2 ^ Fintype.card α := by simp [Pow.pow] @[norm_cast] theorem nat_succ (n : ℕ) : (n.succ : Cardinal) = succ ↑n := by rw [Nat.cast_succ] refine (add_one_le_succ _).antisymm (succ_le_of_lt ?_) rw [← Nat.cast_succ] exact Nat.cast_lt.2 (Nat.lt_succ_self _) lemma succ_natCast (n : ℕ) : Order.succ (n : Cardinal) = n + 1 := by rw [← Cardinal.nat_succ] norm_cast lemma natCast_add_one_le_iff {n : ℕ} {c : Cardinal} : n + 1 ≤ c ↔ n < c := by rw [← Order.succ_le_iff, Cardinal.succ_natCast] lemma two_le_iff_one_lt {c : Cardinal} : 2 ≤ c ↔ 1 < c := by convert natCast_add_one_le_iff norm_cast @[simp] theorem succ_zero : succ (0 : Cardinal) = 1 := by norm_cast -- This works generally to prove inequalities between numeric cardinals. theorem one_lt_two : (1 : Cardinal) < 2 := by norm_cast theorem exists_finset_le_card (α : Type*) (n : ℕ) (h : n ≤ #α) : ∃ s : Finset α, n ≤ s.card := by obtain hα|hα := finite_or_infinite α · let hα := Fintype.ofFinite α use Finset.univ simpa only [mk_fintype, Nat.cast_le] using h · obtain ⟨s, hs⟩ := Infinite.exists_subset_card_eq α n exact ⟨s, hs.ge⟩ theorem card_le_of {α : Type u} {n : ℕ} (H : ∀ s : Finset α, s.card ≤ n) : #α ≤ n := by contrapose! H apply exists_finset_le_card α (n+1) simpa only [nat_succ, succ_le_iff] using H theorem cantor' (a) {b : Cardinal} (hb : 1 < b) : a < b ^ a := by rw [← succ_le_iff, (by norm_cast : succ (1 : Cardinal) = 2)] at hb exact (cantor a).trans_le (power_le_power_right hb) theorem one_le_iff_pos {c : Cardinal} : 1 ≤ c ↔ 0 < c := by rw [← succ_zero, succ_le_iff] theorem one_le_iff_ne_zero {c : Cardinal} : 1 ≤ c ↔ c ≠ 0 := by rw [one_le_iff_pos, pos_iff_ne_zero] @[simp] theorem lt_one_iff_zero {c : Cardinal} : c < 1 ↔ c = 0 := by simpa using lt_succ_bot_iff (a := c) /-! ### Properties about `aleph0` -/ theorem nat_lt_aleph0 (n : ℕ) : (n : Cardinal.{u}) < ℵ₀ := succ_le_iff.1 (by rw [← nat_succ, ← lift_mk_fin, aleph0, lift_mk_le.{u}] exact ⟨⟨(↑), fun a b => Fin.ext⟩⟩) @[simp] theorem one_lt_aleph0 : 1 < ℵ₀ := by simpa using nat_lt_aleph0 1 @[simp] theorem one_le_aleph0 : 1 ≤ ℵ₀ := one_lt_aleph0.le theorem lt_aleph0 {c : Cardinal} : c < ℵ₀ ↔ ∃ n : ℕ, c = n := ⟨fun h => by rcases lt_lift_iff.1 h with ⟨c, h', rfl⟩ rcases le_mk_iff_exists_set.1 h'.1 with ⟨S, rfl⟩ suffices S.Finite by lift S to Finset ℕ using this simp contrapose! h' haveI := Infinite.to_subtype h' exact ⟨Infinite.natEmbedding S⟩, fun ⟨_, e⟩ => e.symm ▸ nat_lt_aleph0 _⟩ lemma succ_eq_of_lt_aleph0 {c : Cardinal} (h : c < ℵ₀) : Order.succ c = c + 1 := by obtain ⟨n, hn⟩ := Cardinal.lt_aleph0.mp h rw [hn, succ_natCast] theorem aleph0_le {c : Cardinal} : ℵ₀ ≤ c ↔ ∀ n : ℕ, ↑n ≤ c := ⟨fun h _ => (nat_lt_aleph0 _).le.trans h, fun h => le_of_not_lt fun hn => by rcases lt_aleph0.1 hn with ⟨n, rfl⟩ exact (Nat.lt_succ_self _).not_le (Nat.cast_le.1 (h (n + 1)))⟩ theorem isSuccPrelimit_aleph0 : IsSuccPrelimit ℵ₀ := isSuccPrelimit_of_succ_lt fun a ha => by rcases lt_aleph0.1 ha with ⟨n, rfl⟩ rw [← nat_succ] apply nat_lt_aleph0 theorem isSuccLimit_aleph0 : IsSuccLimit ℵ₀ := by rw [Cardinal.isSuccLimit_iff] exact ⟨aleph0_ne_zero, isSuccPrelimit_aleph0⟩ lemma not_isSuccLimit_natCast : (n : ℕ) → ¬ IsSuccLimit (n : Cardinal.{u}) | 0, e => e.1 isMin_bot | Nat.succ n, e => Order.not_isSuccPrelimit_succ _ (nat_succ n ▸ e.2) theorem not_isSuccLimit_of_lt_aleph0 {c : Cardinal} (h : c < ℵ₀) : ¬ IsSuccLimit c := by obtain ⟨n, rfl⟩ := lt_aleph0.1 h exact not_isSuccLimit_natCast n theorem aleph0_le_of_isSuccLimit {c : Cardinal} (h : IsSuccLimit c) : ℵ₀ ≤ c := by contrapose! h exact not_isSuccLimit_of_lt_aleph0 h theorem isStrongLimit_aleph0 : IsStrongLimit ℵ₀ := by refine ⟨aleph0_ne_zero, fun x hx ↦ ?_⟩ obtain ⟨n, rfl⟩ := lt_aleph0.1 hx exact_mod_cast nat_lt_aleph0 _ theorem IsStrongLimit.aleph0_le {c} (H : IsStrongLimit c) : ℵ₀ ≤ c := aleph0_le_of_isSuccLimit H.isSuccLimit lemma exists_eq_natCast_of_iSup_eq {ι : Type u} [Nonempty ι] (f : ι → Cardinal.{v}) (hf : BddAbove (range f)) (n : ℕ) (h : ⨆ i, f i = n) : ∃ i, f i = n := exists_eq_of_iSup_eq_of_not_isSuccLimit.{u, v} f hf (not_isSuccLimit_natCast n) h @[simp] theorem range_natCast : range ((↑) : ℕ → Cardinal) = Iio ℵ₀ := ext fun x => by simp only [mem_Iio, mem_range, eq_comm, lt_aleph0] theorem mk_eq_nat_iff {α : Type u} {n : ℕ} : #α = n ↔ Nonempty (α ≃ Fin n) := by rw [← lift_mk_fin, ← lift_uzero #α, lift_mk_eq'] theorem lt_aleph0_iff_finite {α : Type u} : #α < ℵ₀ ↔ Finite α := by simp only [lt_aleph0, mk_eq_nat_iff, finite_iff_exists_equiv_fin] theorem lt_aleph0_iff_fintype {α : Type u} : #α < ℵ₀ ↔ Nonempty (Fintype α) := lt_aleph0_iff_finite.trans (finite_iff_nonempty_fintype _) theorem lt_aleph0_of_finite (α : Type u) [Finite α] : #α < ℵ₀ := lt_aleph0_iff_finite.2 ‹_› theorem lt_aleph0_iff_set_finite {S : Set α} : #S < ℵ₀ ↔ S.Finite := lt_aleph0_iff_finite.trans finite_coe_iff alias ⟨_, _root_.Set.Finite.lt_aleph0⟩ := lt_aleph0_iff_set_finite @[simp] theorem lt_aleph0_iff_subtype_finite {p : α → Prop} : #{ x // p x } < ℵ₀ ↔ { x | p x }.Finite := lt_aleph0_iff_set_finite theorem mk_le_aleph0_iff : #α ≤ ℵ₀ ↔ Countable α := by rw [countable_iff_nonempty_embedding, aleph0, ← lift_uzero #α, lift_mk_le'] @[simp] theorem mk_le_aleph0 [Countable α] : #α ≤ ℵ₀ := mk_le_aleph0_iff.mpr ‹_› theorem le_aleph0_iff_set_countable {s : Set α} : #s ≤ ℵ₀ ↔ s.Countable := mk_le_aleph0_iff alias ⟨_, _root_.Set.Countable.le_aleph0⟩ := le_aleph0_iff_set_countable @[simp] theorem le_aleph0_iff_subtype_countable {p : α → Prop} : #{ x // p x } ≤ ℵ₀ ↔ { x | p x }.Countable := le_aleph0_iff_set_countable theorem aleph0_lt_mk_iff : ℵ₀ < #α ↔ Uncountable α := by rw [← not_le, ← not_countable_iff, not_iff_not, mk_le_aleph0_iff] @[simp] theorem aleph0_lt_mk [Uncountable α] : ℵ₀ < #α := aleph0_lt_mk_iff.mpr ‹_› instance canLiftCardinalNat : CanLift Cardinal ℕ (↑) fun x => x < ℵ₀ := ⟨fun _ hx => let ⟨n, hn⟩ := lt_aleph0.mp hx ⟨n, hn.symm⟩⟩ theorem add_lt_aleph0 {a b : Cardinal} (ha : a < ℵ₀) (hb : b < ℵ₀) : a + b < ℵ₀ := match a, b, lt_aleph0.1 ha, lt_aleph0.1 hb with | _, _, ⟨m, rfl⟩, ⟨n, rfl⟩ => by rw [← Nat.cast_add]; apply nat_lt_aleph0 theorem add_lt_aleph0_iff {a b : Cardinal} : a + b < ℵ₀ ↔ a < ℵ₀ ∧ b < ℵ₀ := ⟨fun h => ⟨(self_le_add_right _ _).trans_lt h, (self_le_add_left _ _).trans_lt h⟩, fun ⟨h1, h2⟩ => add_lt_aleph0 h1 h2⟩ theorem aleph0_le_add_iff {a b : Cardinal} : ℵ₀ ≤ a + b ↔ ℵ₀ ≤ a ∨ ℵ₀ ≤ b := by simp only [← not_lt, add_lt_aleph0_iff, not_and_or] /-- See also `Cardinal.nsmul_lt_aleph0_iff_of_ne_zero` if you already have `n ≠ 0`. -/ theorem nsmul_lt_aleph0_iff {n : ℕ} {a : Cardinal} : n • a < ℵ₀ ↔ n = 0 ∨ a < ℵ₀ := by cases n with | zero => simpa using nat_lt_aleph0 0 | succ n => simp only [Nat.succ_ne_zero, false_or] induction' n with n ih · simp rw [succ_nsmul, add_lt_aleph0_iff, ih, and_self_iff] /-- See also `Cardinal.nsmul_lt_aleph0_iff` for a hypothesis-free version. -/ theorem nsmul_lt_aleph0_iff_of_ne_zero {n : ℕ} {a : Cardinal} (h : n ≠ 0) : n • a < ℵ₀ ↔ a < ℵ₀ := nsmul_lt_aleph0_iff.trans <| or_iff_right h theorem mul_lt_aleph0 {a b : Cardinal} (ha : a < ℵ₀) (hb : b < ℵ₀) : a * b < ℵ₀ := match a, b, lt_aleph0.1 ha, lt_aleph0.1 hb with | _, _, ⟨m, rfl⟩, ⟨n, rfl⟩ => by rw [← Nat.cast_mul]; apply nat_lt_aleph0 theorem mul_lt_aleph0_iff {a b : Cardinal} : a * b < ℵ₀ ↔ a = 0 ∨ b = 0 ∨ a < ℵ₀ ∧ b < ℵ₀ := by refine ⟨fun h => ?_, ?_⟩ · by_cases ha : a = 0 · exact Or.inl ha right by_cases hb : b = 0 · exact Or.inl hb right rw [← Ne, ← one_le_iff_ne_zero] at ha hb constructor · rw [← mul_one a] exact (mul_le_mul' le_rfl hb).trans_lt h · rw [← one_mul b] exact (mul_le_mul' ha le_rfl).trans_lt h rintro (rfl | rfl | ⟨ha, hb⟩) <;> simp only [*, mul_lt_aleph0, aleph0_pos, zero_mul, mul_zero] /-- See also `Cardinal.aleph0_le_mul_iff`. -/ theorem aleph0_le_mul_iff {a b : Cardinal} : ℵ₀ ≤ a * b ↔ a ≠ 0 ∧ b ≠ 0 ∧ (ℵ₀ ≤ a ∨ ℵ₀ ≤ b) := by let h := (@mul_lt_aleph0_iff a b).not rwa [not_lt, not_or, not_or, not_and_or, not_lt, not_lt] at h /-- See also `Cardinal.aleph0_le_mul_iff'`. -/ theorem aleph0_le_mul_iff' {a b : Cardinal.{u}} : ℵ₀ ≤ a * b ↔ a ≠ 0 ∧ ℵ₀ ≤ b ∨ ℵ₀ ≤ a ∧ b ≠ 0 := by have : ∀ {a : Cardinal.{u}}, ℵ₀ ≤ a → a ≠ 0 := fun a => ne_bot_of_le_ne_bot aleph0_ne_zero a simp only [aleph0_le_mul_iff, and_or_left, and_iff_right_of_imp this, @and_left_comm (a ≠ 0)] simp only [and_comm, or_comm] theorem mul_lt_aleph0_iff_of_ne_zero {a b : Cardinal} (ha : a ≠ 0) (hb : b ≠ 0) : a * b < ℵ₀ ↔ a < ℵ₀ ∧ b < ℵ₀ := by simp [mul_lt_aleph0_iff, ha, hb] theorem power_lt_aleph0 {a b : Cardinal} (ha : a < ℵ₀) (hb : b < ℵ₀) : a ^ b < ℵ₀ := match a, b, lt_aleph0.1 ha, lt_aleph0.1 hb with | _, _, ⟨m, rfl⟩, ⟨n, rfl⟩ => by rw [power_natCast, ← Nat.cast_pow]; apply nat_lt_aleph0 theorem eq_one_iff_unique {α : Type*} : #α = 1 ↔ Subsingleton α ∧ Nonempty α := calc #α = 1 ↔ #α ≤ 1 ∧ 1 ≤ #α := le_antisymm_iff _ ↔ Subsingleton α ∧ Nonempty α := le_one_iff_subsingleton.and (one_le_iff_ne_zero.trans mk_ne_zero_iff) theorem infinite_iff {α : Type u} : Infinite α ↔ ℵ₀ ≤ #α := by rw [← not_lt, lt_aleph0_iff_finite, not_finite_iff_infinite] lemma aleph0_le_mk_iff : ℵ₀ ≤ #α ↔ Infinite α := infinite_iff.symm lemma mk_lt_aleph0_iff : #α < ℵ₀ ↔ Finite α := by simp [← not_le, aleph0_le_mk_iff] @[simp] lemma mk_lt_aleph0 [Finite α] : #α < ℵ₀ := mk_lt_aleph0_iff.2 ‹_› @[simp] theorem aleph0_le_mk (α : Type u) [Infinite α] : ℵ₀ ≤ #α := infinite_iff.1 ‹_› @[simp] theorem mk_eq_aleph0 (α : Type*) [Countable α] [Infinite α] : #α = ℵ₀ := mk_le_aleph0.antisymm <| aleph0_le_mk _ theorem denumerable_iff {α : Type u} : Nonempty (Denumerable α) ↔ #α = ℵ₀ := ⟨fun ⟨h⟩ => mk_congr ((@Denumerable.eqv α h).trans Equiv.ulift.symm), fun h => by obtain ⟨f⟩ := Quotient.exact h exact ⟨Denumerable.mk' <| f.trans Equiv.ulift⟩⟩ theorem mk_denumerable (α : Type u) [Denumerable α] : #α = ℵ₀ := denumerable_iff.1 ⟨‹_›⟩ theorem _root_.Set.countable_infinite_iff_nonempty_denumerable {α : Type*} {s : Set α} : s.Countable ∧ s.Infinite ↔ Nonempty (Denumerable s) := by rw [nonempty_denumerable_iff, ← Set.infinite_coe_iff, countable_coe_iff] @[simp] theorem aleph0_add_aleph0 : ℵ₀ + ℵ₀ = ℵ₀ := mk_denumerable _ theorem aleph0_mul_aleph0 : ℵ₀ * ℵ₀ = ℵ₀ := mk_denumerable _ @[simp] theorem nat_mul_aleph0 {n : ℕ} (hn : n ≠ 0) : ↑n * ℵ₀ = ℵ₀ := le_antisymm (lift_mk_fin n ▸ mk_le_aleph0) <| le_mul_of_one_le_left (zero_le _) <| by rwa [← Nat.cast_one, Nat.cast_le, Nat.one_le_iff_ne_zero] @[simp] theorem aleph0_mul_nat {n : ℕ} (hn : n ≠ 0) : ℵ₀ * n = ℵ₀ := by rw [mul_comm, nat_mul_aleph0 hn] @[simp] theorem ofNat_mul_aleph0 {n : ℕ} [Nat.AtLeastTwo n] : ofNat(n) * ℵ₀ = ℵ₀ := nat_mul_aleph0 (NeZero.ne n) @[simp] theorem aleph0_mul_ofNat {n : ℕ} [Nat.AtLeastTwo n] : ℵ₀ * ofNat(n) = ℵ₀ := aleph0_mul_nat (NeZero.ne n) @[simp] theorem add_le_aleph0 {c₁ c₂ : Cardinal} : c₁ + c₂ ≤ ℵ₀ ↔ c₁ ≤ ℵ₀ ∧ c₂ ≤ ℵ₀ := ⟨fun h => ⟨le_self_add.trans h, le_add_self.trans h⟩, fun h => aleph0_add_aleph0 ▸ add_le_add h.1 h.2⟩ @[simp] theorem aleph0_add_nat (n : ℕ) : ℵ₀ + n = ℵ₀ := (add_le_aleph0.2 ⟨le_rfl, (nat_lt_aleph0 n).le⟩).antisymm le_self_add @[simp] theorem nat_add_aleph0 (n : ℕ) : ↑n + ℵ₀ = ℵ₀ := by rw [add_comm, aleph0_add_nat] @[simp] theorem ofNat_add_aleph0 {n : ℕ} [Nat.AtLeastTwo n] : ofNat(n) + ℵ₀ = ℵ₀ := nat_add_aleph0 n @[simp] theorem aleph0_add_ofNat {n : ℕ} [Nat.AtLeastTwo n] : ℵ₀ + ofNat(n) = ℵ₀ := aleph0_add_nat n theorem exists_nat_eq_of_le_nat {c : Cardinal} {n : ℕ} (h : c ≤ n) : ∃ m, m ≤ n ∧ c = m := by lift c to ℕ using h.trans_lt (nat_lt_aleph0 _) exact ⟨c, mod_cast h, rfl⟩ theorem mk_int : #ℤ = ℵ₀ := mk_denumerable ℤ theorem mk_pnat : #ℕ+ = ℵ₀ := mk_denumerable ℕ+ @[deprecated (since := "2025-04-27")] alias mk_pNat := mk_pnat /-! ### Cardinalities of basic sets and types -/ @[simp] theorem mk_additive : #(Additive α) = #α := rfl @[simp] theorem mk_multiplicative : #(Multiplicative α) = #α := rfl @[to_additive (attr := simp)] theorem mk_mulOpposite : #(MulOpposite α) = #α := mk_congr MulOpposite.opEquiv.symm theorem mk_singleton {α : Type u} (x : α) : #({x} : Set α) = 1 := mk_eq_one _ @[simp] theorem mk_vector (α : Type u) (n : ℕ) : #(List.Vector α n) = #α ^ n := (mk_congr (Equiv.vectorEquivFin α n)).trans <| by simp theorem mk_list_eq_sum_pow (α : Type u) : #(List α) = sum fun n : ℕ => #α ^ n := calc #(List α) = #(Σn, List.Vector α n) := mk_congr (Equiv.sigmaFiberEquiv List.length).symm _ = sum fun n : ℕ => #α ^ n := by simp theorem mk_quot_le {α : Type u} {r : α → α → Prop} : #(Quot r) ≤ #α := mk_le_of_surjective Quot.exists_rep theorem mk_quotient_le {α : Type u} {s : Setoid α} : #(Quotient s) ≤ #α := mk_quot_le theorem mk_subtype_le_of_subset {α : Type u} {p q : α → Prop} (h : ∀ ⦃x⦄, p x → q x) : #(Subtype p) ≤ #(Subtype q) := ⟨Embedding.subtypeMap (Embedding.refl α) h⟩ theorem mk_emptyCollection (α : Type u) : #(∅ : Set α) = 0 := mk_eq_zero _ theorem mk_emptyCollection_iff {α : Type u} {s : Set α} : #s = 0 ↔ s = ∅ := by constructor · intro h rw [mk_eq_zero_iff] at h exact eq_empty_iff_forall_not_mem.2 fun x hx => h.elim' ⟨x, hx⟩ · rintro rfl exact mk_emptyCollection _ @[simp] theorem mk_univ {α : Type u} : #(@univ α) = #α := mk_congr (Equiv.Set.univ α) @[simp] lemma mk_setProd {α β : Type u} (s : Set α) (t : Set β) : #(s ×ˢ t) = #s * #t := by rw [mul_def, mk_congr (Equiv.Set.prod ..)] theorem mk_image_le {α β : Type u} {f : α → β} {s : Set α} : #(f '' s) ≤ #s := mk_le_of_surjective surjective_onto_image lemma mk_image2_le {α β γ : Type u} {f : α → β → γ} {s : Set α} {t : Set β} : #(image2 f s t) ≤ #s * #t := by rw [← image_uncurry_prod, ← mk_setProd] exact mk_image_le theorem mk_image_le_lift {α : Type u} {β : Type v} {f : α → β} {s : Set α} : lift.{u} #(f '' s) ≤ lift.{v} #s := lift_mk_le.{0}.mpr ⟨Embedding.ofSurjective _ surjective_onto_image⟩ theorem mk_range_le {α β : Type u} {f : α → β} : #(range f) ≤ #α := mk_le_of_surjective surjective_onto_range theorem mk_range_le_lift {α : Type u} {β : Type v} {f : α → β} : lift.{u} #(range f) ≤ lift.{v} #α := lift_mk_le.{0}.mpr ⟨Embedding.ofSurjective _ surjective_onto_range⟩ theorem mk_range_eq (f : α → β) (h : Injective f) : #(range f) = #α := mk_congr (Equiv.ofInjective f h).symm theorem mk_range_eq_lift {α : Type u} {β : Type v} {f : α → β} (hf : Injective f) : lift.{max u w} #(range f) = lift.{max v w} #α := lift_mk_eq.{v,u,w}.mpr ⟨(Equiv.ofInjective f hf).symm⟩ theorem mk_range_eq_of_injective {α : Type u} {β : Type v} {f : α → β} (hf : Injective f) : lift.{u} #(range f) = lift.{v} #α := lift_mk_eq'.mpr ⟨(Equiv.ofInjective f hf).symm⟩ lemma lift_mk_le_lift_mk_of_injective {α : Type u} {β : Type v} {f : α → β} (hf : Injective f) : Cardinal.lift.{v} (#α) ≤ Cardinal.lift.{u} (#β) := by rw [← Cardinal.mk_range_eq_of_injective hf] exact Cardinal.lift_le.2 (Cardinal.mk_set_le _) lemma lift_mk_le_lift_mk_of_surjective {α : Type u} {β : Type v} {f : α → β} (hf : Surjective f) : Cardinal.lift.{u} (#β) ≤ Cardinal.lift.{v} (#α) := lift_mk_le_lift_mk_of_injective (injective_surjInv hf) theorem mk_image_eq_of_injOn {α β : Type u} (f : α → β) (s : Set α) (h : InjOn f s) : #(f '' s) = #s := mk_congr (Equiv.Set.imageOfInjOn f s h).symm theorem mk_image_eq_of_injOn_lift {α : Type u} {β : Type v} (f : α → β) (s : Set α) (h : InjOn f s) : lift.{u} #(f '' s) = lift.{v} #s := lift_mk_eq.{v, u, 0}.mpr ⟨(Equiv.Set.imageOfInjOn f s h).symm⟩ theorem mk_image_eq {α β : Type u} {f : α → β} {s : Set α} (hf : Injective f) : #(f '' s) = #s := mk_image_eq_of_injOn _ _ hf.injOn theorem mk_image_eq_lift {α : Type u} {β : Type v} (f : α → β) (s : Set α) (h : Injective f) : lift.{u} #(f '' s) = lift.{v} #s := mk_image_eq_of_injOn_lift _ _ h.injOn @[simp] theorem mk_image_embedding_lift {β : Type v} (f : α ↪ β) (s : Set α) : lift.{u} #(f '' s) = lift.{v} #s := mk_image_eq_lift _ _ f.injective @[simp] theorem mk_image_embedding (f : α ↪ β) (s : Set α) : #(f '' s) = #s := by simpa using mk_image_embedding_lift f s theorem mk_iUnion_le_sum_mk {α ι : Type u} {f : ι → Set α} : #(⋃ i, f i) ≤ sum fun i => #(f i) := calc #(⋃ i, f i) ≤ #(Σi, f i) := mk_le_of_surjective (Set.sigmaToiUnion_surjective f) _ = sum fun i => #(f i) := mk_sigma _ theorem mk_iUnion_le_sum_mk_lift {α : Type u} {ι : Type v} {f : ι → Set α} : lift.{v} #(⋃ i, f i) ≤ sum fun i => #(f i) := calc lift.{v} #(⋃ i, f i) ≤ #(Σi, f i) := mk_le_of_surjective <| ULift.up_surjective.comp (Set.sigmaToiUnion_surjective f) _ = sum fun i => #(f i) := mk_sigma _ theorem mk_iUnion_eq_sum_mk {α ι : Type u} {f : ι → Set α} (h : Pairwise (Disjoint on f)) : #(⋃ i, f i) = sum fun i => #(f i) := calc #(⋃ i, f i) = #(Σi, f i) := mk_congr (Set.unionEqSigmaOfDisjoint h) _ = sum fun i => #(f i) := mk_sigma _ theorem mk_iUnion_eq_sum_mk_lift {α : Type u} {ι : Type v} {f : ι → Set α} (h : Pairwise (Disjoint on f)) : lift.{v} #(⋃ i, f i) = sum fun i => #(f i) := calc lift.{v} #(⋃ i, f i) = #(Σi, f i) := mk_congr <| .trans Equiv.ulift (Set.unionEqSigmaOfDisjoint h) _ = sum fun i => #(f i) := mk_sigma _ theorem mk_iUnion_le {α ι : Type u} (f : ι → Set α) : #(⋃ i, f i) ≤ #ι * ⨆ i, #(f i) := mk_iUnion_le_sum_mk.trans (sum_le_iSup _) theorem mk_iUnion_le_lift {α : Type u} {ι : Type v} (f : ι → Set α) : lift.{v} #(⋃ i, f i) ≤ lift.{u} #ι * ⨆ i, lift.{v} #(f i) := by refine mk_iUnion_le_sum_mk_lift.trans <| Eq.trans_le ?_ (sum_le_iSup_lift _) rw [← lift_sum, lift_id'.{_,u}] theorem mk_sUnion_le {α : Type u} (A : Set (Set α)) : #(⋃₀ A) ≤ #A * ⨆ s : A, #s := by rw [sUnion_eq_iUnion] apply mk_iUnion_le theorem mk_biUnion_le {ι α : Type u} (A : ι → Set α) (s : Set ι) : #(⋃ x ∈ s, A x) ≤ #s * ⨆ x : s, #(A x.1) := by rw [biUnion_eq_iUnion] apply mk_iUnion_le theorem mk_biUnion_le_lift {α : Type u} {ι : Type v} (A : ι → Set α) (s : Set ι) : lift.{v} #(⋃ x ∈ s, A x) ≤ lift.{u} #s * ⨆ x : s, lift.{v} #(A x.1) := by rw [biUnion_eq_iUnion] apply mk_iUnion_le_lift theorem finset_card_lt_aleph0 (s : Finset α) : #(↑s : Set α) < ℵ₀ := lt_aleph0_of_finite _ theorem mk_set_eq_nat_iff_finset {α} {s : Set α} {n : ℕ} : #s = n ↔ ∃ t : Finset α, (t : Set α) = s ∧ t.card = n := by constructor · intro h lift s to Finset α using lt_aleph0_iff_set_finite.1 (h.symm ▸ nat_lt_aleph0 n) simpa using h · rintro ⟨t, rfl, rfl⟩ exact mk_coe_finset theorem mk_eq_nat_iff_finset {n : ℕ} : #α = n ↔ ∃ t : Finset α, (t : Set α) = univ ∧ t.card = n := by rw [← mk_univ, mk_set_eq_nat_iff_finset] theorem mk_eq_nat_iff_fintype {n : ℕ} : #α = n ↔ ∃ h : Fintype α, @Fintype.card α h = n := by rw [mk_eq_nat_iff_finset] constructor · rintro ⟨t, ht, hn⟩ exact ⟨⟨t, eq_univ_iff_forall.1 ht⟩, hn⟩ · rintro ⟨⟨t, ht⟩, hn⟩ exact ⟨t, eq_univ_iff_forall.2 ht, hn⟩ theorem mk_union_add_mk_inter {α : Type u} {S T : Set α} : #(S ∪ T : Set α) + #(S ∩ T : Set α) = #S + #T := by classical exact Quot.sound ⟨Equiv.Set.unionSumInter S T⟩ /-- The cardinality of a union is at most the sum of the cardinalities of the two sets. -/ theorem mk_union_le {α : Type u} (S T : Set α) : #(S ∪ T : Set α) ≤ #S + #T := @mk_union_add_mk_inter α S T ▸ self_le_add_right #(S ∪ T : Set α) #(S ∩ T : Set α) theorem mk_union_of_disjoint {α : Type u} {S T : Set α} (H : Disjoint S T) : #(S ∪ T : Set α) = #S + #T := by classical exact Quot.sound ⟨Equiv.Set.union H⟩ theorem mk_insert {α : Type u} {s : Set α} {a : α} (h : a ∉ s) : #(insert a s : Set α) = #s + 1 := by rw [← union_singleton, mk_union_of_disjoint, mk_singleton] simpa theorem mk_insert_le {α : Type u} {s : Set α} {a : α} : #(insert a s : Set α) ≤ #s + 1 := by by_cases h : a ∈ s · simp only [insert_eq_of_mem h, self_le_add_right] · rw [mk_insert h] theorem mk_sum_compl {α} (s : Set α) : #s + #(sᶜ : Set α) = #α := by classical exact mk_congr (Equiv.Set.sumCompl s) theorem mk_le_mk_of_subset {α} {s t : Set α} (h : s ⊆ t) : #s ≤ #t := ⟨Set.embeddingOfSubset s t h⟩ theorem mk_le_iff_forall_finset_subset_card_le {α : Type u} {n : ℕ} {t : Set α} : #t ≤ n ↔ ∀ s : Finset α, (s : Set α) ⊆ t → s.card ≤ n := by refine ⟨fun H s hs ↦ by simpa using (mk_le_mk_of_subset hs).trans H, fun H ↦ ?_⟩ apply card_le_of (fun s ↦ ?_) classical let u : Finset α := s.image Subtype.val have : u.card = s.card := Finset.card_image_of_injOn Subtype.coe_injective.injOn rw [← this] apply H simp only [u, Finset.coe_image, image_subset_iff, Subtype.coe_preimage_self, subset_univ] theorem mk_subtype_mono {p q : α → Prop} (h : ∀ x, p x → q x) : #{ x // p x } ≤ #{ x // q x } := ⟨embeddingOfSubset _ _ h⟩ theorem le_mk_diff_add_mk (S T : Set α) : #S ≤ #(S \ T : Set α) + #T := (mk_le_mk_of_subset <| subset_diff_union _ _).trans <| mk_union_le _ _ theorem mk_diff_add_mk {S T : Set α} (h : T ⊆ S) : #(S \ T : Set α) + #T = #S := by refine (mk_union_of_disjoint <| ?_).symm.trans <| by rw [diff_union_of_subset h] exact disjoint_sdiff_self_left theorem mk_union_le_aleph0 {α} {P Q : Set α} : #(P ∪ Q : Set α) ≤ ℵ₀ ↔ #P ≤ ℵ₀ ∧ #Q ≤ ℵ₀ := by simp only [le_aleph0_iff_subtype_countable, mem_union, setOf_mem_eq, Set.union_def, ← countable_union] theorem mk_sep (s : Set α) (t : α → Prop) : #({ x ∈ s | t x } : Set α) = #{ x : s | t x.1 } := mk_congr (Equiv.Set.sep s t) theorem mk_preimage_of_injective_lift {α : Type u} {β : Type v} (f : α → β) (s : Set β) (h : Injective f) : lift.{v} #(f ⁻¹' s) ≤ lift.{u} #s := by rw [lift_mk_le.{0}] -- Porting note: Needed to insert `mem_preimage.mp` below use Subtype.coind (fun x => f x.1) fun x => mem_preimage.mp x.2 apply Subtype.coind_injective; exact h.comp Subtype.val_injective theorem mk_preimage_of_subset_range_lift {α : Type u} {β : Type v} (f : α → β) (s : Set β) (h : s ⊆ range f) : lift.{u} #s ≤ lift.{v} #(f ⁻¹' s) := by rw [← image_preimage_eq_iff] at h nth_rewrite 1 [← h] apply mk_image_le_lift theorem mk_preimage_of_injective_of_subset_range_lift {β : Type v} (f : α → β) (s : Set β) (h : Injective f) (h2 : s ⊆ range f) : lift.{v} #(f ⁻¹' s) = lift.{u} #s := le_antisymm (mk_preimage_of_injective_lift f s h) (mk_preimage_of_subset_range_lift f s h2) theorem mk_preimage_of_injective_of_subset_range (f : α → β) (s : Set β) (h : Injective f) (h2 : s ⊆ range f) : #(f ⁻¹' s) = #s := by convert mk_preimage_of_injective_of_subset_range_lift.{u, u} f s h h2 using 1 <;> rw [lift_id] @[simp] theorem mk_preimage_equiv_lift {β : Type v} (f : α ≃ β) (s : Set β) : lift.{v} #(f ⁻¹' s) = lift.{u} #s := by apply mk_preimage_of_injective_of_subset_range_lift _ _ f.injective rw [f.range_eq_univ] exact fun _ _ ↦ ⟨⟩ @[simp] theorem mk_preimage_equiv (f : α ≃ β) (s : Set β) : #(f ⁻¹' s) = #s := by simpa using mk_preimage_equiv_lift f s theorem mk_preimage_of_injective (f : α → β) (s : Set β) (h : Injective f) : #(f ⁻¹' s) ≤ #s := by rw [← lift_id #(↑(f ⁻¹' s)), ← lift_id #(↑s)] exact mk_preimage_of_injective_lift f s h theorem mk_preimage_of_subset_range (f : α → β) (s : Set β) (h : s ⊆ range f) : #s ≤ #(f ⁻¹' s) := by rw [← lift_id #(↑(f ⁻¹' s)), ← lift_id #(↑s)] exact mk_preimage_of_subset_range_lift f s h theorem mk_subset_ge_of_subset_image_lift {α : Type u} {β : Type v} (f : α → β) {s : Set α} {t : Set β} (h : t ⊆ f '' s) : lift.{u} #t ≤ lift.{v} #({ x ∈ s | f x ∈ t } : Set α) := by rw [image_eq_range] at h convert mk_preimage_of_subset_range_lift _ _ h using 1 rw [mk_sep] rfl theorem mk_subset_ge_of_subset_image (f : α → β) {s : Set α} {t : Set β} (h : t ⊆ f '' s) : #t ≤ #({ x ∈ s | f x ∈ t } : Set α) := by rw [image_eq_range] at h convert mk_preimage_of_subset_range _ _ h using 1 rw [mk_sep] rfl theorem le_mk_iff_exists_subset {c : Cardinal} {α : Type u} {s : Set α} : c ≤ #s ↔ ∃ p : Set α, p ⊆ s ∧ #p = c := by rw [le_mk_iff_exists_set, ← Subtype.exists_set_subtype] apply exists_congr; intro t; rw [mk_image_eq]; apply Subtype.val_injective @[simp] theorem mk_range_inl {α : Type u} {β : Type v} : #(range (@Sum.inl α β)) = lift.{v} #α := by rw [← lift_id'.{u, v} #_, (Equiv.Set.rangeInl α β).lift_cardinal_eq, lift_umax.{u, v}] @[simp] theorem mk_range_inr {α : Type u} {β : Type v} : #(range (@Sum.inr α β)) = lift.{u} #β := by rw [← lift_id'.{v, u} #_, (Equiv.Set.rangeInr α β).lift_cardinal_eq, lift_umax.{v, u}] theorem two_le_iff : (2 : Cardinal) ≤ #α ↔ ∃ x y : α, x ≠ y := by rw [← Nat.cast_two, nat_succ, succ_le_iff, Nat.cast_one, one_lt_iff_nontrivial, nontrivial_iff] theorem two_le_iff' (x : α) : (2 : Cardinal) ≤ #α ↔ ∃ y : α, y ≠ x := by rw [two_le_iff, ← nontrivial_iff, nontrivial_iff_exists_ne x] theorem mk_eq_two_iff : #α = 2 ↔ ∃ x y : α, x ≠ y ∧ ({x, y} : Set α) = univ := by classical simp only [← @Nat.cast_two Cardinal, mk_eq_nat_iff_finset, Finset.card_eq_two] constructor · rintro ⟨t, ht, x, y, hne, rfl⟩ exact ⟨x, y, hne, by simpa using ht⟩ · rintro ⟨x, y, hne, h⟩ exact ⟨{x, y}, by simpa using h, x, y, hne, rfl⟩ theorem mk_eq_two_iff' (x : α) : #α = 2 ↔ ∃! y, y ≠ x := by rw [mk_eq_two_iff]; constructor · rintro ⟨a, b, hne, h⟩ simp only [eq_univ_iff_forall, mem_insert_iff, mem_singleton_iff] at h rcases h x with (rfl | rfl) exacts [⟨b, hne.symm, fun z => (h z).resolve_left⟩, ⟨a, hne, fun z => (h z).resolve_right⟩] · rintro ⟨y, hne, hy⟩ exact ⟨x, y, hne.symm, eq_univ_of_forall fun z => or_iff_not_imp_left.2 (hy z)⟩ theorem exists_not_mem_of_length_lt {α : Type*} (l : List α) (h : ↑l.length < #α) : ∃ z : α, z ∉ l := by classical contrapose! h calc #α = #(Set.univ : Set α) := mk_univ.symm _ ≤ #l.toFinset := mk_le_mk_of_subset fun x _ => List.mem_toFinset.mpr (h x) _ = l.toFinset.card := Cardinal.mk_coe_finset _ ≤ l.length := Nat.cast_le.mpr (List.toFinset_card_le l) theorem three_le {α : Type*} (h : 3 ≤ #α) (x : α) (y : α) : ∃ z : α, z ≠ x ∧ z ≠ y := by have : ↑(3 : ℕ) ≤ #α := by simpa using h have : ↑(2 : ℕ) < #α := by rwa [← succ_le_iff, ← Cardinal.nat_succ] have := exists_not_mem_of_length_lt [x, y] this simpa [not_or] using this /-! ### `powerlt` operation -/ /-- The function `a ^< b`, defined as the supremum of `a ^ c` for `c < b`. -/ def powerlt (a b : Cardinal.{u}) : Cardinal.{u} := ⨆ c : Iio b, a ^ (c : Cardinal) @[inherit_doc] infixl:80 " ^< " => powerlt theorem le_powerlt {b c : Cardinal.{u}} (a) (h : c < b) : (a^c) ≤ a ^< b := by refine le_ciSup (f := fun y : Iio b => a ^ (y : Cardinal)) ?_ ⟨c, h⟩ rw [← image_eq_range] exact bddAbove_image.{u, u} _ bddAbove_Iio theorem powerlt_le {a b c : Cardinal.{u}} : a ^< b ≤ c ↔ ∀ x < b, a ^ x ≤ c := by rw [powerlt, ciSup_le_iff'] · simp · rw [← image_eq_range] exact bddAbove_image.{u, u} _ bddAbove_Iio theorem powerlt_le_powerlt_left {a b c : Cardinal} (h : b ≤ c) : a ^< b ≤ a ^< c := powerlt_le.2 fun _ hx => le_powerlt a <| hx.trans_le h theorem powerlt_mono_left (a) : Monotone fun c => a ^< c := fun _ _ => powerlt_le_powerlt_left theorem powerlt_succ {a b : Cardinal} (h : a ≠ 0) : a ^< succ b = a ^ b := (powerlt_le.2 fun _ h' => power_le_power_left h <| le_of_lt_succ h').antisymm <| le_powerlt a (lt_succ b) theorem powerlt_min {a b c : Cardinal} : a ^< min b c = min (a ^< b) (a ^< c) := (powerlt_mono_left a).map_min theorem powerlt_max {a b c : Cardinal} : a ^< max b c = max (a ^< b) (a ^< c) := (powerlt_mono_left a).map_max theorem zero_powerlt {a : Cardinal} (h : a ≠ 0) : 0 ^< a = 1 := by apply (powerlt_le.2 fun c _ => zero_power_le _).antisymm rw [← power_zero] exact le_powerlt 0 (pos_iff_ne_zero.2 h) @[simp] theorem powerlt_zero {a : Cardinal} : a ^< 0 = 0 := by convert Cardinal.iSup_of_empty _
exact Subtype.isEmpty_of_false fun x => mem_Iio.not.mpr (Cardinal.zero_le x).not_lt end Cardinal
Mathlib/SetTheory/Cardinal/Basic.lean
989
992
/- Copyright (c) 2023 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Algebra.Group.PUnit import Mathlib.Algebra.Group.Subgroup.Ker import Mathlib.Algebra.Group.Submonoid.Membership import Mathlib.GroupTheory.Congruence.Basic /-! # Coproduct (free product) of two monoids or groups In this file we define `Monoid.Coprod M N` (notation: `M ∗ N`) to be the coproduct (a.k.a. free product) of two monoids. The same type is used for the coproduct of two monoids and for the coproduct of two groups. The coproduct `M ∗ N` has the following universal property: for any monoid `P` and homomorphisms `f : M →* P`, `g : N →* P`, there exists a unique homomorphism `fg : M ∗ N →* P` such that `fg ∘ Monoid.Coprod.inl = f` and `fg ∘ Monoid.Coprod.inr = g`, where `Monoid.Coprod.inl : M →* M ∗ N` and `Monoid.Coprod.inr : N →* M ∗ N` are canonical embeddings. This homomorphism `fg` is given by `Monoid.Coprod.lift f g`. We also define some homomorphisms and isomorphisms about `M ∗ N`, and provide additive versions of all definitions and theorems. ## Main definitions ### Types * `Monoid.Coprod M N` (a.k.a. `M ∗ N`): the free product (a.k.a. coproduct) of two monoids `M` and `N`. * `AddMonoid.Coprod M N` (no notation): the additive version of `Monoid.Coprod`. In other sections, we only list multiplicative definitions. ### Instances * `MulOneClass`, `Monoid`, and `Group` structures on the coproduct `M ∗ N`. ### Monoid homomorphisms * `Monoid.Coprod.mk`: the projection `FreeMonoid (M ⊕ N) →* M ∗ N`. * `Monoid.Coprod.inl`, `Monoid.Coprod.inr`: canonical embeddings `M →* M ∗ N` and `N →* M ∗ N`. * `Monoid.Coprod.lift`: construct a monoid homomorphism `M ∗ N →* P` from homomorphisms `M →* P` and `N →* P`; see also `Monoid.Coprod.liftEquiv`. * `Monoid.Coprod.clift`: a constructor for homomorphisms `M ∗ N →* P` that allows the user to control the computational behavior. * `Monoid.Coprod.map`: combine two homomorphisms `f : M →* N` and `g : M' →* N'` into `M ∗ M' →* N ∗ N'`. * `Monoid.Coprod.swap`: the natural homomorphism `M ∗ N →* N ∗ M`. * `Monoid.Coprod.fst`, `Monoid.Coprod.snd`, and `Monoid.Coprod.toProd`: natural projections `M ∗ N →* M`, `M ∗ N →* N`, and `M ∗ N →* M × N`. ### Monoid isomorphisms * `MulEquiv.coprodCongr`: a `MulEquiv` version of `Monoid.Coprod.map`. * `MulEquiv.coprodComm`: a `MulEquiv` version of `Monoid.Coprod.swap`. * `MulEquiv.coprodAssoc`: associativity of the coproduct. * `MulEquiv.coprodPUnit`, `MulEquiv.punitCoprod`: free product by `PUnit` on the left or on the right is isomorphic to the original monoid. ## Main results The universal property of the coproduct is given by the definition `Monoid.Coprod.lift` and the lemma `Monoid.Coprod.lift_unique`. We also prove a slightly more general extensionality lemma `Monoid.Coprod.hom_ext` for homomorphisms `M ∗ N →* P` and prove lots of basic lemmas like `Monoid.Coprod.fst_comp_inl`. ## Implementation details The definition of the coproduct of an indexed family of monoids is formalized in `Monoid.CoprodI`. While mathematically `M ∗ N` is a particular case of the coproduct of an indexed family of monoids, it is easier to build API from scratch instead of using something like ``` def Monoid.Coprod M N := Monoid.CoprodI ![M, N] ``` or ``` def Monoid.Coprod M N := Monoid.CoprodI (fun b : Bool => cond b M N) ``` There are several reasons to build an API from scratch. - API about `Con` makes it easy to define the required type and prove the universal property, so there is little overhead compared to transferring API from `Monoid.CoprodI`. - If `M` and `N` live in different universes, then the definition has to add `ULift`s; this makes it harder to transfer API and definitions. - As of now, we have no way to automatically build an instance of `(k : Fin 2) → Monoid (![M, N] k)` from `[Monoid M]` and `[Monoid N]`, not even speaking about more advanced typeclass assumptions that involve both `M` and `N`. - Using a list of `M ⊕ N` instead of, e.g., a list of `Σ k : Fin 2, ![M, N] k` as the underlying type makes it possible to write computationally effective code (though this point is not tested yet). ## TODO - Prove `Monoid.CoprodI (f : Fin 2 → Type*) ≃* f 0 ∗ f 1` and `Monoid.CoprodI (f : Bool → Type*) ≃* f false ∗ f true`. ## Tags group, monoid, coproduct, free product -/ assert_not_exists MonoidWithZero open FreeMonoid Function List Set namespace Monoid /-- The minimal congruence relation `c` on `FreeMonoid (M ⊕ N)` such that `FreeMonoid.of ∘ Sum.inl` and `FreeMonoid.of ∘ Sum.inr` are monoid homomorphisms to the quotient by `c`. -/ @[to_additive "The minimal additive congruence relation `c` on `FreeAddMonoid (M ⊕ N)` such that `FreeAddMonoid.of ∘ Sum.inl` and `FreeAddMonoid.of ∘ Sum.inr` are additive monoid homomorphisms to the quotient by `c`."] def coprodCon (M N : Type*) [MulOneClass M] [MulOneClass N] : Con (FreeMonoid (M ⊕ N)) := sInf {c | (∀ x y : M, c (of (Sum.inl (x * y))) (of (Sum.inl x) * of (Sum.inl y))) ∧ (∀ x y : N, c (of (Sum.inr (x * y))) (of (Sum.inr x) * of (Sum.inr y))) ∧ c (of <| Sum.inl 1) 1 ∧ c (of <| Sum.inr 1) 1} /-- Coproduct of two monoids or groups. -/ @[to_additive "Coproduct of two additive monoids or groups."] def Coprod (M N : Type*) [MulOneClass M] [MulOneClass N] := (coprodCon M N).Quotient namespace Coprod @[inherit_doc] scoped infix:30 " ∗ " => Coprod section MulOneClass variable {M N M' N' P : Type*} [MulOneClass M] [MulOneClass N] [MulOneClass M'] [MulOneClass N'] [MulOneClass P] @[to_additive] protected instance : MulOneClass (M ∗ N) := Con.mulOneClass _ /-- The natural projection `FreeMonoid (M ⊕ N) →* M ∗ N`. -/ @[to_additive "The natural projection `FreeAddMonoid (M ⊕ N) →+ AddMonoid.Coprod M N`."] def mk : FreeMonoid (M ⊕ N) →* M ∗ N := Con.mk' _ @[to_additive (attr := simp)] theorem con_ker_mk : Con.ker mk = coprodCon M N := Con.mk'_ker _ @[to_additive] theorem mk_surjective : Surjective (@mk M N _ _) := Quot.mk_surjective @[to_additive (attr := simp)] theorem mrange_mk : MonoidHom.mrange (@mk M N _ _) = ⊤ := Con.mrange_mk' @[to_additive] theorem mk_eq_mk {w₁ w₂ : FreeMonoid (M ⊕ N)} : mk w₁ = mk w₂ ↔ coprodCon M N w₁ w₂ := Con.eq _ /-- The natural embedding `M →* M ∗ N`. -/ @[to_additive "The natural embedding `M →+ AddMonoid.Coprod M N`."] def inl : M →* M ∗ N where toFun := fun x => mk (of (.inl x)) map_one' := mk_eq_mk.2 fun _c hc => hc.2.2.1 map_mul' := fun x y => mk_eq_mk.2 fun _c hc => hc.1 x y /-- The natural embedding `N →* M ∗ N`. -/ @[to_additive "The natural embedding `N →+ AddMonoid.Coprod M N`."] def inr : N →* M ∗ N where toFun := fun x => mk (of (.inr x)) map_one' := mk_eq_mk.2 fun _c hc => hc.2.2.2 map_mul' := fun x y => mk_eq_mk.2 fun _c hc => hc.2.1 x y @[to_additive (attr := simp)] theorem mk_of_inl (x : M) : (mk (of (.inl x)) : M ∗ N) = inl x := rfl @[to_additive (attr := simp)] theorem mk_of_inr (x : N) : (mk (of (.inr x)) : M ∗ N) = inr x := rfl @[to_additive (attr := elab_as_elim)] theorem induction_on' {C : M ∗ N → Prop} (m : M ∗ N) (one : C 1) (inl_mul : ∀ m x, C x → C (inl m * x)) (inr_mul : ∀ n x, C x → C (inr n * x)) : C m := by rcases mk_surjective m with ⟨x, rfl⟩ induction x using FreeMonoid.inductionOn' with | one => exact one | mul_of x xs ih => cases x with | inl m => simpa using inl_mul m _ ih | inr n => simpa using inr_mul n _ ih
@[to_additive (attr := elab_as_elim)] theorem induction_on {C : M ∗ N → Prop} (m : M ∗ N)
Mathlib/GroupTheory/Coprod/Basic.lean
202
204
/- Copyright (c) 2017 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Yaël Dillies, David Loeffler -/ import Mathlib.Order.PartialSups import Mathlib.Order.Interval.Finset.Fin /-! # Making a sequence disjoint This file defines the way to make a sequence of sets - or, more generally, a map from a partially ordered type `ι` into a (generalized) Boolean algebra `α` - into a *pairwise disjoint* sequence with the same partial sups. For a sequence `f : ℕ → α`, this new sequence will be `f 0`, `f 1 \ f 0`, `f 2 \ (f 0 ⊔ f 1) ⋯`. It is actually unique, as `disjointed_unique` shows. ## Main declarations * `disjointed f`: The map sending `i` to `f i \ (⨆ j < i, f j)`. We require the index type to be a `LocallyFiniteOrderBot` to ensure that the supremum is well defined. * `partialSups_disjointed`: `disjointed f` has the same partial sups as `f`. * `disjoint_disjointed`: The elements of `disjointed f` are pairwise disjoint. * `disjointed_unique`: `disjointed f` is the only pairwise disjoint sequence having the same partial sups as `f`. * `Fintype.sup_disjointed` (for finite `ι`) or `iSup_disjointed` (for complete `α`): `disjointed f` has the same supremum as `f`. Limiting case of `partialSups_disjointed`. * `Fintype.exists_disjointed_le`: for any finite family `f : ι → α`, there exists a pairwise disjoint family `g : ι → α` which is bounded above by `f` and has the same supremum. This is an analogue of `disjointed` for arbitrary finite index types (but without any uniqueness). We also provide set notation variants of some lemmas. -/ assert_not_exists SuccAddOrder open Finset Order variable {α ι : Type*} open scoped Function -- required for scoped `on` notation section GeneralizedBooleanAlgebra variable [GeneralizedBooleanAlgebra α] section Preorder -- the *index type* is a preorder variable [Preorder ι] [LocallyFiniteOrderBot ι] /-- The function mapping `i` to `f i \ (⨆ j < i, f j)`. When `ι` is a partial order, this is the unique function `g` having the same `partialSups` as `f` and such that `g i` and `g j` are disjoint whenever `i < j`. -/ def disjointed (f : ι → α) (i : ι) : α := f i \ (Iio i).sup f lemma disjointed_apply (f : ι → α) (i : ι) : disjointed f i = f i \ (Iio i).sup f := rfl lemma disjointed_of_isMin (f : ι → α) {i : ι} (hn : IsMin i) : disjointed f i = f i := by have : Iio i = ∅ := by rwa [← Finset.coe_eq_empty, coe_Iio, Set.Iio_eq_empty_iff] simp only [disjointed_apply, this, sup_empty, sdiff_bot] @[simp] lemma disjointed_bot [OrderBot ι] (f : ι → α) : disjointed f ⊥ = f ⊥ := disjointed_of_isMin _ isMin_bot theorem disjointed_le_id : disjointed ≤ (id : (ι → α) → ι → α) := fun _ _ ↦ sdiff_le theorem disjointed_le (f : ι → α) : disjointed f ≤ f := disjointed_le_id f theorem disjoint_disjointed_of_lt (f : ι → α) {i j : ι} (h : i < j) :
Disjoint (disjointed f i) (disjointed f j) := (disjoint_sdiff_self_right.mono_left <| le_sup (mem_Iio.mpr h)).mono_left (disjointed_le f i) lemma disjointed_eq_self {f : ι → α} {i : ι} (hf : ∀ j < i, Disjoint (f j) (f i)) : disjointed f i = f i := by rw [disjointed_apply, sdiff_eq_left, disjoint_iff, sup_inf_distrib_left, sup_congr rfl <| fun j hj ↦ disjoint_iff.mp <| (hf _ (mem_Iio.mp hj)).symm]
Mathlib/Order/Disjointed.lean
74
80
/- Copyright (c) 2022 Damiano Testa. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Damiano Testa -/ import Mathlib.Algebra.Group.Subsemigroup.Operations import Mathlib.Algebra.MonoidAlgebra.Support import Mathlib.Order.Filter.Extr /-! # Lemmas about the `sup` and `inf` of the support of `AddMonoidAlgebra` ## TODO The current plan is to state and prove lemmas about `Finset.sup (Finsupp.support f) D` with a "generic" degree/weight function `D` from the grading Type `A` to a somewhat ordered Type `B`. Next, the general lemmas get specialized for some yet-to-be-defined `degree`s. -/ variable {R R' A T B ι : Type*} namespace AddMonoidAlgebra /-! # sup-degree and inf-degree of an `AddMonoidAlgebra` Let `R` be a semiring and let `A` be a `SemilatticeSup`. For an element `f : R[A]`, this file defines * `AddMonoidAlgebra.supDegree`: the sup-degree taking values in `WithBot A`, * `AddMonoidAlgebra.infDegree`: the inf-degree taking values in `WithTop A`. If the grading type `A` is a linearly ordered additive monoid, then these two notions of degree coincide with the standard one: * the sup-degree is the maximum of the exponents of the monomials that appear with non-zero coefficient in `f`, or `⊥`, if `f = 0`; * the inf-degree is the minimum of the exponents of the monomials that appear with non-zero coefficient in `f`, or `⊤`, if `f = 0`. The main results are * `AddMonoidAlgebra.supDegree_mul_le`: the sup-degree of a product is at most the sum of the sup-degrees, * `AddMonoidAlgebra.le_infDegree_mul`: the inf-degree of a product is at least the sum of the inf-degrees, * `AddMonoidAlgebra.supDegree_add_le`: the sup-degree of a sum is at most the sup of the sup-degrees, * `AddMonoidAlgebra.le_infDegree_add`: the inf-degree of a sum is at least the inf of the inf-degrees. ## Implementation notes The current plan is to state and prove lemmas about `Finset.sup (Finsupp.support f) D` with a "generic" degree/weight function `D` from the grading Type `A` to a somewhat ordered Type `B`. Next, the general lemmas get specialized twice: * once for `supDegree` (essentially a simple application) and * once for `infDegree` (a simple application, via `OrderDual`). These final lemmas are the ones that likely get used the most. The generic lemmas about `Finset.support.sup` may not be used directly much outside of this file. To see this in action, you can look at the triple `(sup_support_mul_le, maxDegree_mul_le, le_minDegree_mul)`. -/ section GeneralResultsAssumingSemilatticeSup variable [SemilatticeSup B] [OrderBot B] [SemilatticeInf T] [OrderTop T] section Semiring variable [Semiring R] section ExplicitDegrees /-! In this section, we use `degb` and `degt` to denote "degree functions" on `A` with values in a type with *b*ot or *t*op respectively. -/ variable (degb : A → B) (degt : A → T) (f g : R[A]) theorem sup_support_add_le : (f + g).support.sup degb ≤ f.support.sup degb ⊔ g.support.sup degb := by classical exact (Finset.sup_mono Finsupp.support_add).trans_eq Finset.sup_union theorem le_inf_support_add : f.support.inf degt ⊓ g.support.inf degt ≤ (f + g).support.inf degt := sup_support_add_le (fun a : A => OrderDual.toDual (degt a)) f g end ExplicitDegrees section AddOnly variable [Add A] [Add B] [Add T] [AddLeftMono B] [AddRightMono B] [AddLeftMono T] [AddRightMono T] theorem sup_support_mul_le {degb : A → B} (degbm : ∀ {a b}, degb (a + b) ≤ degb a + degb b) (f g : R[A]) : (f * g).support.sup degb ≤ f.support.sup degb + g.support.sup degb := by classical exact (Finset.sup_mono <| support_mul _ _).trans <| Finset.sup_add_le.2 fun _fd fds _gd gds ↦ degbm.trans <| add_le_add (Finset.le_sup fds) (Finset.le_sup gds) theorem le_inf_support_mul {degt : A → T} (degtm : ∀ {a b}, degt a + degt b ≤ degt (a + b)) (f g : R[A]) : f.support.inf degt + g.support.inf degt ≤ (f * g).support.inf degt := sup_support_mul_le (B := Tᵒᵈ) degtm f g end AddOnly section AddMonoids variable [AddMonoid A] [AddMonoid B] [AddLeftMono B] [AddRightMono B] [AddMonoid T] [AddLeftMono T] [AddRightMono T] {degb : A → B} {degt : A → T} theorem sup_support_list_prod_le (degb0 : degb 0 ≤ 0) (degbm : ∀ a b, degb (a + b) ≤ degb a + degb b) : ∀ l : List R[A], l.prod.support.sup degb ≤ (l.map fun f : R[A] => f.support.sup degb).sum | [] => by rw [List.map_nil, Finset.sup_le_iff, List.prod_nil, List.sum_nil] exact fun a ha => by rwa [Finset.mem_singleton.mp (Finsupp.support_single_subset ha)] | f::fs => by rw [List.prod_cons, List.map_cons, List.sum_cons] exact (sup_support_mul_le (@fun a b => degbm a b) _ _).trans (add_le_add_left (sup_support_list_prod_le degb0 degbm fs) _) theorem le_inf_support_list_prod (degt0 : 0 ≤ degt 0) (degtm : ∀ a b, degt a + degt b ≤ degt (a + b)) (l : List R[A]) : (l.map fun f : R[A] => f.support.inf degt).sum ≤ l.prod.support.inf degt := by refine OrderDual.ofDual_le_ofDual.mpr ?_ refine sup_support_list_prod_le ?_ ?_ l · refine (OrderDual.ofDual_le_ofDual.mp ?_) exact degt0 · refine (fun a b => OrderDual.ofDual_le_ofDual.mp ?_) exact degtm a b theorem sup_support_pow_le (degb0 : degb 0 ≤ 0) (degbm : ∀ a b, degb (a + b) ≤ degb a + degb b) (n : ℕ) (f : R[A]) : (f ^ n).support.sup degb ≤ n • f.support.sup degb := by rw [← List.prod_replicate, ← List.sum_replicate] refine (sup_support_list_prod_le degb0 degbm _).trans_eq ?_ rw [List.map_replicate] theorem le_inf_support_pow (degt0 : 0 ≤ degt 0) (degtm : ∀ a b, degt a + degt b ≤ degt (a + b)) (n : ℕ) (f : R[A]) : n • f.support.inf degt ≤ (f ^ n).support.inf degt := by refine OrderDual.ofDual_le_ofDual.mpr <| sup_support_pow_le (OrderDual.ofDual_le_ofDual.mp ?_) (fun a b => OrderDual.ofDual_le_ofDual.mp ?_) n f · exact degt0 · exact degtm _ _ end AddMonoids
end Semiring section CommutativeLemmas variable [CommSemiring R] [AddCommMonoid A] [AddCommMonoid B] [AddLeftMono B] [AddRightMono B]
Mathlib/Algebra/MonoidAlgebra/Degree.lean
156
161
/- 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 import Mathlib.Algebra.Polynomial.Degree.Monomial /-! # 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 section EraseLead theorem eraseLead_support (f : R[X]) : f.eraseLead.support = f.support.erase f.natDegree := by simp only [eraseLead, support_erase] 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] @[simp] theorem eraseLead_coeff_natDegree : f.eraseLead.coeff f.natDegree = 0 := by simp [eraseLead_coeff] theorem eraseLead_coeff_of_ne (i : ℕ) (hi : i ≠ f.natDegree) : f.eraseLead.coeff i = f.coeff i := by simp [eraseLead_coeff, hi] @[simp] theorem eraseLead_zero : eraseLead (0 : R[X]) = 0 := by simp only [eraseLead, erase_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 _) @[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] @[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 @[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] theorem eraseLead_ne_zero (f0 : 2 ≤ #f.support) : 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 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 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 theorem natDegree_not_mem_eraseLead_support : f.natDegree ∉ (eraseLead f).support := fun h => ne_natDegree_of_mem_eraseLead_support h rfl theorem eraseLead_support_card_lt (h : f ≠ 0) : #(eraseLead f).support < #f.support := by rw [eraseLead_support] exact card_lt_card (erase_ssubset <| natDegree_mem_support_of_nonzero h) theorem card_support_eraseLead_add_one (h : f ≠ 0) : #f.eraseLead.support + 1 = #f.support := by set c := #f.support 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 = #f.support - 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 = c + 1) : #f.eraseLead.support = c := by rw [card_support_eraseLead, fc, add_tsub_cancel_right] theorem card_support_eq_one_of_eraseLead_eq_zero (h₀ : f ≠ 0) (h₁ : f.eraseLead = 0) : #f.support = 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 ≤ 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] @[simp] theorem eraseLead_C (r : R) : eraseLead (C r) = 0 := eraseLead_monomial _ _ @[simp] theorem eraseLead_X : eraseLead (X : R[X]) = 0 := eraseLead_monomial _ _ @[simp] theorem eraseLead_X_pow (n : ℕ) : eraseLead (X ^ n : R[X]) = 0 := by rw [X_pow_eq_monomial, eraseLead_monomial] @[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] @[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_degree_lt_left {p q : R[X]} (pq : q.degree < p.degree) : (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_degree_lt pq).symm] simpa using (coeff_eq_zero_of_degree_lt (lt_of_lt_of_le pq degree_le_natDegree)).symm · rw [eraseLead_coeff, coeff_add, coeff_add, eraseLead_coeff, if_neg, if_neg nd] rintro rfl exact nd (natDegree_add_eq_left_of_degree_lt pq) theorem eraseLead_add_of_natDegree_lt_left {p q : R[X]} (pq : q.natDegree < p.natDegree) : (p + q).eraseLead = p.eraseLead + q := eraseLead_add_of_degree_lt_left (degree_lt_degree pq) theorem eraseLead_add_of_degree_lt_right {p q : R[X]} (pq : p.degree < q.degree) : (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_degree_lt pq).symm] simpa using (coeff_eq_zero_of_degree_lt (lt_of_lt_of_le pq degree_le_natDegree)).symm · rw [eraseLead_coeff, coeff_add, coeff_add, eraseLead_coeff, if_neg, if_neg nd] rintro rfl exact nd (natDegree_add_eq_right_of_degree_lt pq) theorem eraseLead_add_of_natDegree_lt_right {p q : R[X]} (pq : p.natDegree < q.natDegree) : (p + q).eraseLead = p + q.eraseLead := eraseLead_add_of_degree_lt_right (degree_lt_degree pq) theorem eraseLead_degree_le : (eraseLead f).degree ≤ f.degree := f.degree_erase_le _ theorem degree_eraseLead_lt (hf : f ≠ 0) : (eraseLead f).degree < f.degree := f.degree_erase_lt hf theorem eraseLead_natDegree_le_aux : (eraseLead f).natDegree ≤ f.natDegree := natDegree_le_natDegree eraseLead_degree_le theorem eraseLead_natDegree_lt (f0 : 2 ≤ #f.support) : (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 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 theorem eraseLead_natDegree_lt_or_eraseLead_eq_zero (f : R[X]) : (eraseLead f).natDegree < f.natDegree ∨ f.eraseLead = 0 := by by_cases h : #f.support ≤ 1 · right rw [← C_mul_X_pow_eq_self h] simp · left apply eraseLead_natDegree_lt (lt_of_not_ge h) theorem eraseLead_natDegree_le (f : R[X]) : (eraseLead f).natDegree ≤ f.natDegree - 1 := by rcases f.eraseLead_natDegree_lt_or_eraseLead_eq_zero with (h | h) · exact Nat.le_sub_one_of_lt h · simp only [h, natDegree_zero, zero_le] lemma natDegree_eraseLead (h : f.nextCoeff ≠ 0) : f.eraseLead.natDegree = f.natDegree - 1 := by have := natDegree_pos_of_nextCoeff_ne_zero h refine f.eraseLead_natDegree_le.antisymm <| le_natDegree_of_ne_zero ?_ rwa [eraseLead_coeff_of_ne _ (tsub_lt_self _ _).ne, ← nextCoeff_of_natDegree_pos] all_goals positivity lemma natDegree_eraseLead_add_one (h : f.nextCoeff ≠ 0) : f.eraseLead.natDegree + 1 = f.natDegree := by rw [natDegree_eraseLead h, tsub_add_cancel_of_le] exact natDegree_pos_of_nextCoeff_ne_zero h theorem natDegree_eraseLead_le_of_nextCoeff_eq_zero (h : f.nextCoeff = 0) : f.eraseLead.natDegree ≤ f.natDegree - 2 := by refine natDegree_le_pred (n := f.natDegree - 1) (eraseLead_natDegree_le f) ?_ rw [nextCoeff_eq_zero, natDegree_eq_zero] at h obtain ⟨a, rfl⟩ | ⟨hf, h⟩ := h · simp rw [eraseLead_coeff_of_ne _ (tsub_lt_self hf zero_lt_one).ne, ← nextCoeff_of_natDegree_pos hf] simp [nextCoeff_eq_zero, h, eq_zero_or_pos] lemma two_le_natDegree_of_nextCoeff_eraseLead (hlead : f.eraseLead ≠ 0) (hnext : f.nextCoeff = 0) : 2 ≤ f.natDegree := by contrapose! hlead rw [Nat.lt_succ_iff, Nat.le_one_iff_eq_zero_or_eq_one, natDegree_eq_zero, natDegree_eq_one] at hlead obtain ⟨a, rfl⟩ | ⟨a, ha, b, rfl⟩ := hlead · simp · rw [nextCoeff_C_mul_X_add_C ha] at hnext subst b simp theorem leadingCoeff_eraseLead_eq_nextCoeff (h : f.nextCoeff ≠ 0) : f.eraseLead.leadingCoeff = f.nextCoeff := by have := natDegree_pos_of_nextCoeff_ne_zero h rw [leadingCoeff, nextCoeff, natDegree_eraseLead h, if_neg, eraseLead_coeff_of_ne _ (tsub_lt_self _ _).ne] all_goals positivity theorem nextCoeff_eq_zero_of_eraseLead_eq_zero (h : f.eraseLead = 0) : f.nextCoeff = 0 := by by_contra h₂ exact leadingCoeff_ne_zero.mp (leadingCoeff_eraseLead_eq_nextCoeff h₂ ▸ h₂) h end EraseLead /-- An induction lemma for polynomials. It takes a natural number `N` as a parameter, that is required to be at least as big as the `nat_degree` of the polynomial. This is useful to prove results where you want to change each term in a polynomial to something else depending on the `nat_degree` of the polynomial itself and not on the specific `nat_degree` of each term. -/ theorem induction_with_natDegree_le (P : R[X] → Prop) (N : ℕ) (P_0 : P 0) (P_C_mul_pow : ∀ n : ℕ, ∀ r : R, r ≠ 0 → n ≤ N → P (C r * X ^ n)) (P_C_add : ∀ f g : R[X], f.natDegree < g.natDegree → g.natDegree ≤ N → P f → P g → P (f + g)) : ∀ f : R[X], f.natDegree ≤ N → P f := by intro f df generalize hd : #f.support = c revert f induction' c with c hc · intro f _ f0 convert P_0 simpa [support_eq_empty, card_eq_zero] using f0 · intro f df f0 rw [← eraseLead_add_C_mul_X_pow f] cases c · convert P_C_mul_pow f.natDegree f.leadingCoeff ?_ df using 1 · convert zero_add (C (leadingCoeff f) * X ^ f.natDegree) rw [← card_support_eq_zero, card_support_eraseLead' f0] · rw [leadingCoeff_ne_zero, Ne, ← card_support_eq_zero, f0] exact zero_ne_one.symm refine P_C_add f.eraseLead _ ?_ ?_ ?_ ?_ · refine (eraseLead_natDegree_lt ?_).trans_le (le_of_eq ?_) · exact (Nat.succ_le_succ (Nat.succ_le_succ (Nat.zero_le _))).trans f0.ge · rw [natDegree_C_mul_X_pow _ _ (leadingCoeff_ne_zero.mpr _)] rintro rfl simp at f0 · exact (natDegree_C_mul_X_pow_le f.leadingCoeff f.natDegree).trans df · exact hc _ (eraseLead_natDegree_le_aux.trans df) (card_support_eraseLead' f0) · refine P_C_mul_pow _ _ ?_ df rw [Ne, leadingCoeff_eq_zero, ← card_support_eq_zero, f0] exact Nat.succ_ne_zero _ /-- Let `φ : R[x] → S[x]` be an additive map, `k : ℕ` a bound, and `fu : ℕ → ℕ` a "sufficiently monotone" map. Assume also that * `φ` maps to `0` all monomials of degree less than `k`, * `φ` maps each monomial `m` in `R[x]` to a polynomial `φ m` of degree `fu (deg m)`. Then, `φ` maps each polynomial `p` in `R[x]` to a polynomial of degree `fu (deg p)`. -/ theorem mono_map_natDegree_eq {S F : Type*} [Semiring S] [FunLike F R[X] S[X]] [AddMonoidHomClass F R[X] S[X]] {φ : F} {p : R[X]} (k : ℕ) (fu : ℕ → ℕ) (fu0 : ∀ {n}, n ≤ k → fu n = 0) (fc : ∀ {n m}, k ≤ n → n < m → fu n < fu m) (φ_k : ∀ {f : R[X]}, f.natDegree < k → φ f = 0) (φ_mon_nat : ∀ n c, c ≠ 0 → (φ (monomial n c)).natDegree = fu n) : (φ p).natDegree = fu p.natDegree := by refine induction_with_natDegree_le (fun p => (φ p).natDegree = fu p.natDegree) p.natDegree (by simp [fu0]) ?_ ?_ _ rfl.le · intro n r r0 _ rw [natDegree_C_mul_X_pow _ _ r0, C_mul_X_pow_eq_monomial, φ_mon_nat _ _ r0] · intro f g fg _ fk gk rw [natDegree_add_eq_right_of_natDegree_lt fg, map_add] by_cases FG : k ≤ f.natDegree · rw [natDegree_add_eq_right_of_natDegree_lt, gk] rw [fk, gk] exact fc FG fg · cases k · exact (FG (Nat.zero_le _)).elim · rwa [φ_k (not_le.mp FG), zero_add] theorem map_natDegree_eq_sub {S F : Type*} [Semiring S] [FunLike F R[X] S[X]] [AddMonoidHomClass F R[X] S[X]] {φ : F} {p : R[X]} {k : ℕ} (φ_k : ∀ f : R[X], f.natDegree < k → φ f = 0) (φ_mon : ∀ n c, c ≠ 0 → (φ (monomial n c)).natDegree = n - k) : (φ p).natDegree = p.natDegree - k := mono_map_natDegree_eq k (fun j => j - k) (by simp_all) (@fun _ _ h => (tsub_lt_tsub_iff_right h).mpr) (φ_k _) φ_mon theorem map_natDegree_eq_natDegree {S F : Type*} [Semiring S] [FunLike F R[X] S[X]] [AddMonoidHomClass F R[X] S[X]] {φ : F} (p) (φ_mon_nat : ∀ n c, c ≠ 0 → (φ (monomial n c)).natDegree = n) : (φ p).natDegree = p.natDegree := (map_natDegree_eq_sub (fun _ h => (Nat.not_lt_zero _ h).elim) (by simpa)).trans p.natDegree.sub_zero theorem card_support_eq' {n : ℕ} (k : Fin n → ℕ) (x : Fin n → R) (hk : Function.Injective k) (hx : ∀ i, x i ≠ 0) : #(∑ i, C (x i) * X ^ k i).support = n := by suffices (∑ i, C (x i) * X ^ k i).support = image k univ by rw [this, univ.card_image_of_injective hk, card_fin] simp_rw [Finset.ext_iff, mem_support_iff, finset_sum_coeff, coeff_C_mul_X_pow, mem_image, mem_univ, true_and] refine fun i => ⟨fun h => ?_, ?_⟩ · obtain ⟨j, _, h⟩ := exists_ne_zero_of_sum_ne_zero h exact ⟨j, (ite_ne_right_iff.mp h).1.symm⟩ · rintro ⟨j, _, rfl⟩ rw [sum_eq_single_of_mem j (mem_univ j), if_pos rfl] · exact hx j · exact fun m _ hmj => if_neg fun h => hmj.symm (hk h) theorem card_support_eq {n : ℕ} : #f.support = n ↔ ∃ (k : Fin n → ℕ) (x : Fin n → R) (_ : StrictMono k) (_ : ∀ i, x i ≠ 0), f = ∑ i, C (x i) * X ^ k i := by refine ⟨?_, fun ⟨k, x, hk, hx, hf⟩ => hf.symm ▸ card_support_eq' k x hk.injective hx⟩ induction n generalizing f with | zero => exact fun hf => ⟨0, 0, fun x => x.elim0, fun x => x.elim0, card_support_eq_zero.mp hf⟩ | succ n hn => intro h obtain ⟨k, x, hk, hx, hf⟩ := hn (card_support_eraseLead' h) have H : ¬∃ k : Fin n, Fin.castSucc k = Fin.last n := by rintro ⟨i, hi⟩ exact i.castSucc_lt_last.ne hi refine ⟨Function.extend Fin.castSucc k fun _ => f.natDegree,
Function.extend Fin.castSucc x fun _ => f.leadingCoeff, ?_, ?_, ?_⟩ · intro i j hij have hi : i ∈ Set.range (Fin.castSucc : Fin n → Fin (n + 1)) := by rw [Fin.range_castSucc, Set.mem_def] exact lt_of_lt_of_le hij (Nat.lt_succ_iff.mp j.2) obtain ⟨i, rfl⟩ := hi rw [Fin.strictMono_castSucc.injective.extend_apply] by_cases hj : ∃ j₀, Fin.castSucc j₀ = j · obtain ⟨j, rfl⟩ := hj rwa [Fin.strictMono_castSucc.injective.extend_apply, hk.lt_iff_lt, ← Fin.castSucc_lt_castSucc_iff] · rw [Function.extend_apply' _ _ _ hj] apply lt_natDegree_of_mem_eraseLead_support
Mathlib/Algebra/Polynomial/EraseLead.lean
363
375