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/- Copyright (c) 2019 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Data.Set.Piecewise import Mathlib.Logic.Equiv.Defs import Mathlib.Tactic.Core import Mathlib.Tactic.Attr.Core /-! # Partial equivalences This files defines equivalences between subsets of given types. An element `e` of `PartialEquiv α β` is made of two maps `e.toFun` and `e.invFun` respectively from α to β and from β to α (just like equivs), which are inverse to each other on the subsets `e.source` and `e.target` of respectively α and β. They are designed in particular to define charts on manifolds. The main functionality is `e.trans f`, which composes the two partial equivalences by restricting the source and target to the maximal set where the composition makes sense. As for equivs, we register a coercion to functions and use it in our simp normal form: we write `e x` and `e.symm y` instead of `e.toFun x` and `e.invFun y`. ## Main definitions * `Equiv.toPartialEquiv`: associating a partial equiv to an equiv, with source = target = univ * `PartialEquiv.symm`: the inverse of a partial equivalence * `PartialEquiv.trans`: the composition of two partial equivalences * `PartialEquiv.refl`: the identity partial equivalence * `PartialEquiv.ofSet`: the identity on a set `s` * `EqOnSource`: equivalence relation describing the "right" notion of equality for partial equivalences (see below in implementation notes) ## Implementation notes There are at least three possible implementations of partial equivalences: * equivs on subtypes * pairs of functions taking values in `Option α` and `Option β`, equal to none where the partial equivalence is not defined * pairs of functions defined everywhere, keeping the source and target as additional data Each of these implementations has pros and cons. * When dealing with subtypes, one still need to define additional API for composition and restriction of domains. Checking that one always belongs to the right subtype makes things very tedious, and leads quickly to DTT hell (as the subtype `u ∩ v` is not the "same" as `v ∩ u`, for instance). * With option-valued functions, the composition is very neat (it is just the usual composition, and the domain is restricted automatically). These are implemented in `PEquiv.lean`. For manifolds, where one wants to discuss thoroughly the smoothness of the maps, this creates however a lot of overhead as one would need to extend all classes of smoothness to option-valued maps. * The `PartialEquiv` version as explained above is easier to use for manifolds. The drawback is that there is extra useless data (the values of `toFun` and `invFun` outside of `source` and `target`). In particular, the equality notion between partial equivs is not "the right one", i.e., coinciding source and target and equality there. Moreover, there are no partial equivs in this sense between an empty type and a nonempty type. Since empty types are not that useful, and since one almost never needs to talk about equal partial equivs, this is not an issue in practice. Still, we introduce an equivalence relation `EqOnSource` that captures this right notion of equality, and show that many properties are invariant under this equivalence relation. ### Local coding conventions If a lemma deals with the intersection of a set with either source or target of a `PartialEquiv`, then it should use `e.source ∩ s` or `e.target ∩ t`, not `s ∩ e.source` or `t ∩ e.target`. -/ open Lean Meta Elab Tactic /-! Implementation of the `mfld_set_tac` tactic for working with the domains of partially-defined functions (`PartialEquiv`, `PartialHomeomorph`, etc). This is in a separate file from `Mathlib.Logic.Equiv.MfldSimpsAttr` because attributes need a new file to become functional. -/ /-- Common `@[simps]` configuration options used for manifold-related declarations. -/ def mfld_cfg : Simps.Config where attrs := [`mfld_simps] fullyApplied := false namespace Tactic.MfldSetTac /-- A very basic tactic to show that sets showing up in manifolds coincide or are included in one another. -/ elab (name := mfldSetTac) "mfld_set_tac" : tactic => withMainContext do let g ← getMainGoal let goalTy := (← instantiateMVars (← g.getDecl).type).getAppFnArgs match goalTy with | (``Eq, #[_ty, _e₁, _e₂]) => evalTactic (← `(tactic| ( apply Set.ext; intro my_y constructor <;> · intro h_my_y try simp only [*, mfld_simps] at h_my_y try simp only [*, mfld_simps]))) | (``Subset, #[_ty, _inst, _e₁, _e₂]) => evalTactic (← `(tactic| ( intro my_y h_my_y try simp only [*, mfld_simps] at h_my_y try simp only [*, mfld_simps]))) | _ => throwError "goal should be an equality or an inclusion" attribute [mfld_simps] and_true eq_self_iff_true Function.comp_apply end Tactic.MfldSetTac open Function Set variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*} /-- Local equivalence between subsets `source` and `target` of `α` and `β` respectively. The (global) maps `toFun : α → β` and `invFun : β → α` map `source` to `target` and conversely, and are inverse to each other there. The values of `toFun` outside of `source` and of `invFun` outside of `target` are irrelevant. -/ structure PartialEquiv (α : Type*) (β : Type*) where /-- The global function which has a partial inverse. Its value outside of the `source` subset is irrelevant. -/ toFun : α → β /-- The partial inverse to `toFun`. Its value outside of the `target` subset is irrelevant. -/ invFun : β → α /-- The domain of the partial equivalence. -/ source : Set α /-- The codomain of the partial equivalence. -/ target : Set β /-- The proposition that elements of `source` are mapped to elements of `target`. -/ map_source' : ∀ ⦃x⦄, x ∈ source → toFun x ∈ target /-- The proposition that elements of `target` are mapped to elements of `source`. -/ map_target' : ∀ ⦃x⦄, x ∈ target → invFun x ∈ source /-- The proposition that `invFun` is a left-inverse of `toFun` on `source`. -/ left_inv' : ∀ ⦃x⦄, x ∈ source → invFun (toFun x) = x /-- The proposition that `invFun` is a right-inverse of `toFun` on `target`. -/ right_inv' : ∀ ⦃x⦄, x ∈ target → toFun (invFun x) = x attribute [coe] PartialEquiv.toFun namespace PartialEquiv variable (e : PartialEquiv α β) (e' : PartialEquiv β γ) instance [Inhabited α] [Inhabited β] : Inhabited (PartialEquiv α β) := ⟨⟨const α default, const β default, ∅, ∅, mapsTo_empty _ _, mapsTo_empty _ _, eqOn_empty _ _, eqOn_empty _ _⟩⟩ /-- The inverse of a partial equivalence -/ @[symm] protected def symm : PartialEquiv β α where toFun := e.invFun invFun := e.toFun source := e.target target := e.source map_source' := e.map_target' map_target' := e.map_source' left_inv' := e.right_inv' right_inv' := e.left_inv' instance : CoeFun (PartialEquiv α β) fun _ => α → β := ⟨PartialEquiv.toFun⟩ /-- See Note [custom simps projection] -/ def Simps.symm_apply (e : PartialEquiv α β) : β → α := e.symm initialize_simps_projections PartialEquiv (toFun → apply, invFun → symm_apply) theorem coe_mk (f : α → β) (g s t ml mr il ir) : (PartialEquiv.mk f g s t ml mr il ir : α → β) = f := rfl @[simp, mfld_simps] theorem coe_symm_mk (f : α → β) (g s t ml mr il ir) : ((PartialEquiv.mk f g s t ml mr il ir).symm : β → α) = g := rfl @[simp, mfld_simps] theorem invFun_as_coe : e.invFun = e.symm := rfl @[simp, mfld_simps] theorem map_source {x : α} (h : x ∈ e.source) : e x ∈ e.target := e.map_source' h /-- Variant of `e.map_source` and `map_source'`, stated for images of subsets of `source`. -/ lemma map_source'' : e '' e.source ⊆ e.target := fun _ ⟨_, hx, hex⟩ ↦ mem_of_eq_of_mem (id hex.symm) (e.map_source' hx) @[simp, mfld_simps] theorem map_target {x : β} (h : x ∈ e.target) : e.symm x ∈ e.source := e.map_target' h @[simp, mfld_simps] theorem left_inv {x : α} (h : x ∈ e.source) : e.symm (e x) = x := e.left_inv' h @[simp, mfld_simps] theorem right_inv {x : β} (h : x ∈ e.target) : e (e.symm x) = x := e.right_inv' h theorem eq_symm_apply {x : α} {y : β} (hx : x ∈ e.source) (hy : y ∈ e.target) : x = e.symm y ↔ e x = y := ⟨fun h => by rw [← e.right_inv hy, h], fun h => by rw [← e.left_inv hx, h]⟩ protected theorem mapsTo : MapsTo e e.source e.target := fun _ => e.map_source theorem symm_mapsTo : MapsTo e.symm e.target e.source := e.symm.mapsTo protected theorem leftInvOn : LeftInvOn e.symm e e.source := fun _ => e.left_inv protected theorem rightInvOn : RightInvOn e.symm e e.target := fun _ => e.right_inv protected theorem invOn : InvOn e.symm e e.source e.target := ⟨e.leftInvOn, e.rightInvOn⟩ protected theorem injOn : InjOn e e.source := e.leftInvOn.injOn protected theorem bijOn : BijOn e e.source e.target := e.invOn.bijOn e.mapsTo e.symm_mapsTo protected theorem surjOn : SurjOn e e.source e.target := e.bijOn.surjOn /-- Interpret an `Equiv` as a `PartialEquiv` by restricting it to `s` in the domain and to `t` in the codomain. -/ @[simps -fullyApplied] def _root_.Equiv.toPartialEquivOfImageEq (e : α ≃ β) (s : Set α) (t : Set β) (h : e '' s = t) : PartialEquiv α β where toFun := e invFun := e.symm source := s target := t map_source' _ hx := h ▸ mem_image_of_mem _ hx map_target' x hx := by subst t rcases hx with ⟨x, hx, rfl⟩ rwa [e.symm_apply_apply] left_inv' x _ := e.symm_apply_apply x right_inv' x _ := e.apply_symm_apply x /-- Associate a `PartialEquiv` to an `Equiv`. -/ @[simps! (config := mfld_cfg)] def _root_.Equiv.toPartialEquiv (e : α ≃ β) : PartialEquiv α β := e.toPartialEquivOfImageEq univ univ <| by rw [image_univ, e.surjective.range_eq] instance inhabitedOfEmpty [IsEmpty α] [IsEmpty β] : Inhabited (PartialEquiv α β) := ⟨((Equiv.equivEmpty α).trans (Equiv.equivEmpty β).symm).toPartialEquiv⟩ /-- Create a copy of a `PartialEquiv` providing better definitional equalities. -/ @[simps -fullyApplied] def copy (e : PartialEquiv α β) (f : α → β) (hf : ⇑e = f) (g : β → α) (hg : ⇑e.symm = g) (s : Set α) (hs : e.source = s) (t : Set β) (ht : e.target = t) : PartialEquiv α β where toFun := f invFun := g source := s target := t map_source' _ := ht ▸ hs ▸ hf ▸ e.map_source map_target' _ := hs ▸ ht ▸ hg ▸ e.map_target left_inv' _ := hs ▸ hf ▸ hg ▸ e.left_inv right_inv' _ := ht ▸ hf ▸ hg ▸ e.right_inv theorem copy_eq (e : PartialEquiv α β) (f : α → β) (hf : ⇑e = f) (g : β → α) (hg : ⇑e.symm = g) (s : Set α) (hs : e.source = s) (t : Set β) (ht : e.target = t) : e.copy f hf g hg s hs t ht = e := by substs f g s t cases e rfl /-- Associate to a `PartialEquiv` an `Equiv` between the source and the target. -/ protected def toEquiv : e.source ≃ e.target where toFun x := ⟨e x, e.map_source x.mem⟩ invFun y := ⟨e.symm y, e.map_target y.mem⟩ left_inv := fun ⟨_, hx⟩ => Subtype.eq <| e.left_inv hx right_inv := fun ⟨_, hy⟩ => Subtype.eq <| e.right_inv hy @[simp, mfld_simps] theorem symm_source : e.symm.source = e.target := rfl @[simp, mfld_simps] theorem symm_target : e.symm.target = e.source := rfl @[simp, mfld_simps] theorem symm_symm : e.symm.symm = e := rfl theorem symm_bijective : Function.Bijective (PartialEquiv.symm : PartialEquiv α β → PartialEquiv β α) := Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩ theorem image_source_eq_target : e '' e.source = e.target := e.bijOn.image_eq theorem forall_mem_target {p : β → Prop} : (∀ y ∈ e.target, p y) ↔ ∀ x ∈ e.source, p (e x) := by rw [← image_source_eq_target, forall_mem_image] theorem exists_mem_target {p : β → Prop} : (∃ y ∈ e.target, p y) ↔ ∃ x ∈ e.source, p (e x) := by rw [← image_source_eq_target, exists_mem_image] /-- We say that `t : Set β` is an image of `s : Set α` under a partial equivalence if any of the following equivalent conditions hold: * `e '' (e.source ∩ s) = e.target ∩ t`; * `e.source ∩ e ⁻¹ t = e.source ∩ s`; * `∀ x ∈ e.source, e x ∈ t ↔ x ∈ s` (this one is used in the definition). -/ def IsImage (s : Set α) (t : Set β) : Prop := ∀ ⦃x⦄, x ∈ e.source → (e x ∈ t ↔ x ∈ s) namespace IsImage variable {e} {s : Set α} {t : Set β} {x : α} theorem apply_mem_iff (h : e.IsImage s t) (hx : x ∈ e.source) : e x ∈ t ↔ x ∈ s := h hx theorem symm_apply_mem_iff (h : e.IsImage s t) : ∀ ⦃y⦄, y ∈ e.target → (e.symm y ∈ s ↔ y ∈ t) := e.forall_mem_target.mpr fun x hx => by rw [e.left_inv hx, h hx] protected theorem symm (h : e.IsImage s t) : e.symm.IsImage t s := h.symm_apply_mem_iff @[simp] theorem symm_iff : e.symm.IsImage t s ↔ e.IsImage s t := ⟨fun h => h.symm, fun h => h.symm⟩ protected theorem mapsTo (h : e.IsImage s t) : MapsTo e (e.source ∩ s) (e.target ∩ t) := fun _ hx => ⟨e.mapsTo hx.1, (h hx.1).2 hx.2⟩ theorem symm_mapsTo (h : e.IsImage s t) : MapsTo e.symm (e.target ∩ t) (e.source ∩ s) := h.symm.mapsTo /-- Restrict a `PartialEquiv` to a pair of corresponding sets. -/ @[simps -fullyApplied] def restr (h : e.IsImage s t) : PartialEquiv α β where toFun := e invFun := e.symm source := e.source ∩ s target := e.target ∩ t map_source' := h.mapsTo map_target' := h.symm_mapsTo left_inv' := e.leftInvOn.mono inter_subset_left right_inv' := e.rightInvOn.mono inter_subset_left theorem image_eq (h : e.IsImage s t) : e '' (e.source ∩ s) = e.target ∩ t := h.restr.image_source_eq_target theorem symm_image_eq (h : e.IsImage s t) : e.symm '' (e.target ∩ t) = e.source ∩ s := h.symm.image_eq theorem iff_preimage_eq : e.IsImage s t ↔ e.source ∩ e ⁻¹' t = e.source ∩ s := by simp only [IsImage, Set.ext_iff, mem_inter_iff, mem_preimage, and_congr_right_iff] alias ⟨preimage_eq, of_preimage_eq⟩ := iff_preimage_eq theorem iff_symm_preimage_eq : e.IsImage s t ↔ e.target ∩ e.symm ⁻¹' s = e.target ∩ t := symm_iff.symm.trans iff_preimage_eq alias ⟨symm_preimage_eq, of_symm_preimage_eq⟩ := iff_symm_preimage_eq theorem of_image_eq (h : e '' (e.source ∩ s) = e.target ∩ t) : e.IsImage s t := of_symm_preimage_eq <| Eq.trans (of_symm_preimage_eq rfl).image_eq.symm h theorem of_symm_image_eq (h : e.symm '' (e.target ∩ t) = e.source ∩ s) : e.IsImage s t := of_preimage_eq <| Eq.trans (iff_preimage_eq.2 rfl).symm_image_eq.symm h protected theorem compl (h : e.IsImage s t) : e.IsImage sᶜ tᶜ := fun _ hx => not_congr (h hx) protected theorem inter {s' t'} (h : e.IsImage s t) (h' : e.IsImage s' t') : e.IsImage (s ∩ s') (t ∩ t') := fun _ hx => and_congr (h hx) (h' hx) protected theorem union {s' t'} (h : e.IsImage s t) (h' : e.IsImage s' t') : e.IsImage (s ∪ s') (t ∪ t') := fun _ hx => or_congr (h hx) (h' hx) protected theorem diff {s' t'} (h : e.IsImage s t) (h' : e.IsImage s' t') : e.IsImage (s \ s') (t \ t') := h.inter h'.compl theorem leftInvOn_piecewise {e' : PartialEquiv α β} [∀ i, Decidable (i ∈ s)] [∀ i, Decidable (i ∈ t)] (h : e.IsImage s t) (h' : e'.IsImage s t) : LeftInvOn (t.piecewise e.symm e'.symm) (s.piecewise e e') (s.ite e.source e'.source) := by rintro x (⟨he, hs⟩ | ⟨he, hs : x ∉ s⟩) · rw [piecewise_eq_of_mem _ _ _ hs, piecewise_eq_of_mem _ _ _ ((h he).2 hs), e.left_inv he] · rw [piecewise_eq_of_not_mem _ _ _ hs, piecewise_eq_of_not_mem _ _ _ ((h'.compl he).2 hs), e'.left_inv he] theorem inter_eq_of_inter_eq_of_eqOn {e' : PartialEquiv α β} (h : e.IsImage s t) (h' : e'.IsImage s t) (hs : e.source ∩ s = e'.source ∩ s) (heq : EqOn e e' (e.source ∩ s)) : e.target ∩ t = e'.target ∩ t := by rw [← h.image_eq, ← h'.image_eq, ← hs, heq.image_eq] theorem symm_eq_on_of_inter_eq_of_eqOn {e' : PartialEquiv α β} (h : e.IsImage s t) (hs : e.source ∩ s = e'.source ∩ s) (heq : EqOn e e' (e.source ∩ s)) : EqOn e.symm e'.symm (e.target ∩ t) := by rw [← h.image_eq] rintro y ⟨x, hx, rfl⟩ have hx' := hx; rw [hs] at hx' rw [e.left_inv hx.1, heq hx, e'.left_inv hx'.1] end IsImage theorem isImage_source_target : e.IsImage e.source e.target := fun x hx => by simp [hx] theorem isImage_source_target_of_disjoint (e' : PartialEquiv α β) (hs : Disjoint e.source e'.source) (ht : Disjoint e.target e'.target) : e.IsImage e'.source e'.target := IsImage.of_image_eq <| by rw [hs.inter_eq, ht.inter_eq, image_empty] theorem image_source_inter_eq' (s : Set α) : e '' (e.source ∩ s) = e.target ∩ e.symm ⁻¹' s := by rw [inter_comm, e.leftInvOn.image_inter', image_source_eq_target, inter_comm] theorem image_source_inter_eq (s : Set α) : e '' (e.source ∩ s) = e.target ∩ e.symm ⁻¹' (e.source ∩ s) := by rw [inter_comm, e.leftInvOn.image_inter, image_source_eq_target, inter_comm] theorem image_eq_target_inter_inv_preimage {s : Set α} (h : s ⊆ e.source) : e '' s = e.target ∩ e.symm ⁻¹' s := by rw [← e.image_source_inter_eq', inter_eq_self_of_subset_right h] theorem symm_image_eq_source_inter_preimage {s : Set β} (h : s ⊆ e.target) : e.symm '' s = e.source ∩ e ⁻¹' s := e.symm.image_eq_target_inter_inv_preimage h theorem symm_image_target_inter_eq (s : Set β) : e.symm '' (e.target ∩ s) = e.source ∩ e ⁻¹' (e.target ∩ s) := e.symm.image_source_inter_eq _ theorem symm_image_target_inter_eq' (s : Set β) : e.symm '' (e.target ∩ s) = e.source ∩ e ⁻¹' s := e.symm.image_source_inter_eq' _ theorem source_inter_preimage_inv_preimage (s : Set α) : e.source ∩ e ⁻¹' (e.symm ⁻¹' s) = e.source ∩ s := Set.ext fun x => and_congr_right_iff.2 fun hx => by simp only [mem_preimage, e.left_inv hx] theorem source_inter_preimage_target_inter (s : Set β) : e.source ∩ e ⁻¹' (e.target ∩ s) = e.source ∩ e ⁻¹' s := ext fun _ => ⟨fun hx => ⟨hx.1, hx.2.2⟩, fun hx => ⟨hx.1, e.map_source hx.1, hx.2⟩⟩ theorem target_inter_inv_preimage_preimage (s : Set β) : e.target ∩ e.symm ⁻¹' (e ⁻¹' s) = e.target ∩ s := e.symm.source_inter_preimage_inv_preimage _ theorem symm_image_image_of_subset_source {s : Set α} (h : s ⊆ e.source) : e.symm '' (e '' s) = s := (e.leftInvOn.mono h).image_image theorem image_symm_image_of_subset_target {s : Set β} (h : s ⊆ e.target) : e '' (e.symm '' s) = s := e.symm.symm_image_image_of_subset_source h theorem source_subset_preimage_target : e.source ⊆ e ⁻¹' e.target := e.mapsTo theorem symm_image_target_eq_source : e.symm '' e.target = e.source := e.symm.image_source_eq_target theorem target_subset_preimage_source : e.target ⊆ e.symm ⁻¹' e.source := e.symm_mapsTo /-- Two partial equivs that have the same `source`, same `toFun` and same `invFun`, coincide. -/ @[ext] protected theorem ext {e e' : PartialEquiv α β} (h : ∀ x, e x = e' x) (hsymm : ∀ x, e.symm x = e'.symm x) (hs : e.source = e'.source) : e = e' := by have A : (e : α → β) = e' := by ext x exact h x have B : (e.symm : β → α) = e'.symm := by ext x exact hsymm x have I : e '' e.source = e.target := e.image_source_eq_target have I' : e' '' e'.source = e'.target := e'.image_source_eq_target rw [A, hs, I'] at I cases e; cases e' simp_all /-- Restricting a partial equivalence to `e.source ∩ s` -/ protected def restr (s : Set α) : PartialEquiv α β := (@IsImage.of_symm_preimage_eq α β e s (e.symm ⁻¹' s) rfl).restr @[simp, mfld_simps] theorem restr_coe (s : Set α) : (e.restr s : α → β) = e := rfl @[simp, mfld_simps] theorem restr_coe_symm (s : Set α) : ((e.restr s).symm : β → α) = e.symm := rfl @[simp, mfld_simps] theorem restr_source (s : Set α) : (e.restr s).source = e.source ∩ s := rfl theorem source_restr_subset_source (s : Set α) : (e.restr s).source ⊆ e.source := inter_subset_left @[simp, mfld_simps] theorem restr_target (s : Set α) : (e.restr s).target = e.target ∩ e.symm ⁻¹' s := rfl theorem restr_eq_of_source_subset {e : PartialEquiv α β} {s : Set α} (h : e.source ⊆ s) : e.restr s = e := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [inter_eq_self_of_subset_left h]) @[simp, mfld_simps] theorem restr_univ {e : PartialEquiv α β} : e.restr univ = e := restr_eq_of_source_subset (subset_univ _) /-- The identity partial equiv -/ protected def refl (α : Type*) : PartialEquiv α α := (Equiv.refl α).toPartialEquiv @[simp, mfld_simps] theorem refl_source : (PartialEquiv.refl α).source = univ := rfl @[simp, mfld_simps] theorem refl_target : (PartialEquiv.refl α).target = univ := rfl @[simp, mfld_simps] theorem refl_coe : (PartialEquiv.refl α : α → α) = id := rfl @[simp, mfld_simps] theorem refl_symm : (PartialEquiv.refl α).symm = PartialEquiv.refl α := rfl @[mfld_simps] theorem refl_restr_source (s : Set α) : ((PartialEquiv.refl α).restr s).source = s := by simp @[mfld_simps] theorem refl_restr_target (s : Set α) : ((PartialEquiv.refl α).restr s).target = s := by simp /-- The identity partial equivalence on a set `s` -/ def ofSet (s : Set α) : PartialEquiv α α where toFun := id invFun := id source := s target := s map_source' _ hx := hx map_target' _ hx := hx left_inv' _ _ := rfl right_inv' _ _ := rfl @[simp, mfld_simps] theorem ofSet_source (s : Set α) : (PartialEquiv.ofSet s).source = s := rfl @[simp, mfld_simps] theorem ofSet_target (s : Set α) : (PartialEquiv.ofSet s).target = s := rfl @[simp, mfld_simps] theorem ofSet_coe (s : Set α) : (PartialEquiv.ofSet s : α → α) = id := rfl @[simp, mfld_simps] theorem ofSet_symm (s : Set α) : (PartialEquiv.ofSet s).symm = PartialEquiv.ofSet s := rfl /-- `Function.const` as a `PartialEquiv`. It consists of two constant maps in opposite directions. -/ @[simps] def single (a : α) (b : β) : PartialEquiv α β where toFun := Function.const α b invFun := Function.const β a source := {a} target := {b} map_source' _ _ := rfl map_target' _ _ := rfl left_inv' a' ha' := by rw [eq_of_mem_singleton ha', const_apply] right_inv' b' hb' := by rw [eq_of_mem_singleton hb', const_apply] /-- Composing two partial equivs if the target of the first coincides with the source of the second. -/ @[simps] protected def trans' (e' : PartialEquiv β γ) (h : e.target = e'.source) : PartialEquiv α γ where toFun := e' ∘ e invFun := e.symm ∘ e'.symm source := e.source target := e'.target map_source' x hx := by simp [← h, hx] map_target' y hy := by simp [h, hy] left_inv' x hx := by simp [hx, ← h] right_inv' y hy := by simp [hy, h] /-- Composing two partial equivs, by restricting to the maximal domain where their composition is well defined. Within the `Manifold` namespace, there is the notation `e ≫ f` for this. -/ @[trans] protected def trans : PartialEquiv α γ := PartialEquiv.trans' (e.symm.restr e'.source).symm (e'.restr e.target) (inter_comm _ _) @[simp, mfld_simps] theorem coe_trans : (e.trans e' : α → γ) = e' ∘ e := rfl @[simp, mfld_simps] theorem coe_trans_symm : ((e.trans e').symm : γ → α) = e.symm ∘ e'.symm := rfl theorem trans_apply {x : α} : (e.trans e') x = e' (e x) := rfl theorem trans_symm_eq_symm_trans_symm : (e.trans e').symm = e'.symm.trans e.symm := by cases e; cases e'; rfl @[simp, mfld_simps] theorem trans_source : (e.trans e').source = e.source ∩ e ⁻¹' e'.source := rfl theorem trans_source' : (e.trans e').source = e.source ∩ e ⁻¹' (e.target ∩ e'.source) := by mfld_set_tac theorem trans_source'' : (e.trans e').source = e.symm '' (e.target ∩ e'.source) := by rw [e.trans_source', e.symm_image_target_inter_eq] theorem image_trans_source : e '' (e.trans e').source = e.target ∩ e'.source := (e.symm.restr e'.source).symm.image_source_eq_target @[simp, mfld_simps] theorem trans_target : (e.trans e').target = e'.target ∩ e'.symm ⁻¹' e.target := rfl theorem trans_target' : (e.trans e').target = e'.target ∩ e'.symm ⁻¹' (e'.source ∩ e.target) := trans_source' e'.symm e.symm theorem trans_target'' : (e.trans e').target = e' '' (e'.source ∩ e.target) := trans_source'' e'.symm e.symm theorem inv_image_trans_target : e'.symm '' (e.trans e').target = e'.source ∩ e.target := image_trans_source e'.symm e.symm theorem trans_assoc (e'' : PartialEquiv γ δ) : (e.trans e').trans e'' = e.trans (e'.trans e'') := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source, @preimage_comp α β γ, inter_assoc]) @[simp, mfld_simps] theorem trans_refl : e.trans (PartialEquiv.refl β) = e := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source]) @[simp, mfld_simps] theorem refl_trans : (PartialEquiv.refl α).trans e = e := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source, preimage_id]) theorem trans_ofSet (s : Set β) : e.trans (ofSet s) = e.restr (e ⁻¹' s) := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) rfl theorem trans_refl_restr (s : Set β) : e.trans ((PartialEquiv.refl β).restr s) = e.restr (e ⁻¹' s) := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) (by simp [trans_source]) theorem trans_refl_restr' (s : Set β) : e.trans ((PartialEquiv.refl β).restr s) = e.restr (e.source ∩ e ⁻¹' s) := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) <| by simp only [trans_source, restr_source, refl_source, univ_inter] rw [← inter_assoc, inter_self] theorem restr_trans (s : Set α) : (e.restr s).trans e' = (e.trans e').restr s := PartialEquiv.ext (fun _ => rfl) (fun _ => rfl) <| by simp [trans_source, inter_comm, inter_assoc] /-- A lemma commonly useful when `e` and `e'` are charts of a manifold. -/ theorem mem_symm_trans_source {e' : PartialEquiv α γ} {x : α} (he : x ∈ e.source) (he' : x ∈ e'.source) : e x ∈ (e.symm.trans e').source := ⟨e.mapsTo he, by rwa [mem_preimage, PartialEquiv.symm_symm, e.left_inv he]⟩ /-- `EqOnSource e e'` means that `e` and `e'` have the same source, and coincide there. Then `e` and `e'` should really be considered the same partial equiv. -/ def EqOnSource (e e' : PartialEquiv α β) : Prop := e.source = e'.source ∧ e.source.EqOn e e' /-- `EqOnSource` is an equivalence relation. This instance provides the `≈` notation between two `PartialEquiv`s. -/ instance eqOnSourceSetoid : Setoid (PartialEquiv α β) where r := EqOnSource iseqv := by constructor <;> simp only [Equivalence, EqOnSource, EqOn] <;> aesop theorem eqOnSource_refl : e ≈ e := Setoid.refl _ /-- Two equivalent partial equivs have the same source. -/ theorem EqOnSource.source_eq {e e' : PartialEquiv α β} (h : e ≈ e') : e.source = e'.source := h.1 /-- Two equivalent partial equivs coincide on the source. -/ theorem EqOnSource.eqOn {e e' : PartialEquiv α β} (h : e ≈ e') : e.source.EqOn e e' := h.2 /-- Two equivalent partial equivs have the same target. -/ theorem EqOnSource.target_eq {e e' : PartialEquiv α β} (h : e ≈ e') : e.target = e'.target := by simp only [← image_source_eq_target, ← source_eq h, h.2.image_eq] /-- If two partial equivs are equivalent, so are their inverses. -/ theorem EqOnSource.symm' {e e' : PartialEquiv α β} (h : e ≈ e') : e.symm ≈ e'.symm := by refine ⟨target_eq h, eqOn_of_leftInvOn_of_rightInvOn e.leftInvOn ?_ ?_⟩ <;> simp only [symm_source, target_eq h, source_eq h, e'.symm_mapsTo] exact e'.rightInvOn.congr_right e'.symm_mapsTo (source_eq h ▸ h.eqOn.symm) /-- Two equivalent partial equivs have coinciding inverses on the target. -/ theorem EqOnSource.symm_eqOn {e e' : PartialEquiv α β} (h : e ≈ e') : EqOn e.symm e'.symm e.target := -- Porting note: `h.symm'` dot notation doesn't work anymore because `h` is not recognised as -- `PartialEquiv.EqOnSource` for some reason. eqOn (symm' h) /-- Composition of partial equivs respects equivalence. -/ theorem EqOnSource.trans' {e e' : PartialEquiv α β} {f f' : PartialEquiv β γ} (he : e ≈ e') (hf : f ≈ f') : e.trans f ≈ e'.trans f' := by constructor · rw [trans_source'', trans_source'', ← target_eq he, ← hf.1] exact (he.symm'.eqOn.mono inter_subset_left).image_eq · intro x hx rw [trans_source] at hx simp [Function.comp_apply, PartialEquiv.coe_trans, (he.2 hx.1).symm, hf.2 hx.2] /-- Restriction of partial equivs respects equivalence. -/ theorem EqOnSource.restr {e e' : PartialEquiv α β} (he : e ≈ e') (s : Set α) : e.restr s ≈ e'.restr s := by constructor · simp [he.1] · intro x hx simp only [mem_inter_iff, restr_source] at hx exact he.2 hx.1 /-- Preimages are respected by equivalence. -/ theorem EqOnSource.source_inter_preimage_eq {e e' : PartialEquiv α β} (he : e ≈ e') (s : Set β) : e.source ∩ e ⁻¹' s = e'.source ∩ e' ⁻¹' s := by rw [he.eqOn.inter_preimage_eq, source_eq he] /-- Composition of a partial equivalence and its inverse is equivalent to the restriction of the identity to the source. -/ theorem self_trans_symm : e.trans e.symm ≈ ofSet e.source := by have A : (e.trans e.symm).source = e.source := by mfld_set_tac refine ⟨by rw [A, ofSet_source], fun x hx => ?_⟩ rw [A] at hx simp only [hx, mfld_simps] /-- Composition of the inverse of a partial equivalence and this partial equivalence is equivalent to the restriction of the identity to the target. -/ theorem symm_trans_self : e.symm.trans e ≈ ofSet e.target := self_trans_symm e.symm /-- Two equivalent partial equivs are equal when the source and target are `univ`. -/ theorem eq_of_eqOnSource_univ (e e' : PartialEquiv α β) (h : e ≈ e') (s : e.source = univ) (t : e.target = univ) : e = e' := by refine PartialEquiv.ext (fun x => ?_) (fun x => ?_) h.1 · apply h.2 rw [s] exact mem_univ _ · apply h.symm'.2 rw [symm_source, t] exact mem_univ _ section Prod /-- The product of two partial equivalences, as a partial equivalence on the product. -/ def prod (e : PartialEquiv α β) (e' : PartialEquiv γ δ) : PartialEquiv (α × γ) (β × δ) where source := e.source ×ˢ e'.source target := e.target ×ˢ e'.target toFun p := (e p.1, e' p.2) invFun p := (e.symm p.1, e'.symm p.2) map_source' p hp := by simp_all map_target' p hp := by simp_all left_inv' p hp := by simp_all right_inv' p hp := by simp_all @[simp, mfld_simps] theorem prod_source (e : PartialEquiv α β) (e' : PartialEquiv γ δ) : (e.prod e').source = e.source ×ˢ e'.source := rfl @[simp, mfld_simps] theorem prod_target (e : PartialEquiv α β) (e' : PartialEquiv γ δ) : (e.prod e').target = e.target ×ˢ e'.target := rfl @[simp, mfld_simps] theorem prod_coe (e : PartialEquiv α β) (e' : PartialEquiv γ δ) : (e.prod e' : α × γ → β × δ) = fun p => (e p.1, e' p.2) := rfl theorem prod_coe_symm (e : PartialEquiv α β) (e' : PartialEquiv γ δ) : ((e.prod e').symm : β × δ → α × γ) = fun p => (e.symm p.1, e'.symm p.2) := rfl @[simp, mfld_simps] theorem prod_symm (e : PartialEquiv α β) (e' : PartialEquiv γ δ) :
(e.prod e').symm = e.symm.prod e'.symm := by ext x <;> simp [prod_coe_symm]
Mathlib/Logic/Equiv/PartialEquiv.lean
785
787
/- Copyright (c) 2020 Bhavik Mehta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Bhavik Mehta, Edward Ayers -/ import Mathlib.CategoryTheory.Limits.Shapes.Pullback.HasPullback import Mathlib.Data.Set.BooleanAlgebra /-! # Theory of sieves - For an object `X` of a category `C`, a `Sieve X` is a set of morphisms to `X` which is closed under left-composition. - The complete lattice structure on sieves is given, as well as the Galois insertion given by downward-closing. - A `Sieve X` (functorially) induces a presheaf on `C` together with a monomorphism to the yoneda embedding of `X`. ## Tags sieve, pullback -/ universe v₁ v₂ v₃ u₁ u₂ u₃ namespace CategoryTheory open Category Limits variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D] (F : C ⥤ D) variable {X Y Z : C} (f : Y ⟶ X) /-- A set of arrows all with codomain `X`. -/ def Presieve (X : C) := ∀ ⦃Y⦄, Set (Y ⟶ X)-- deriving CompleteLattice instance : CompleteLattice (Presieve X) := by dsimp [Presieve] infer_instance namespace Presieve noncomputable instance : Inhabited (Presieve X) := ⟨⊤⟩ /-- The full subcategory of the over category `C/X` consisting of arrows which belong to a presieve on `X`. -/ abbrev category {X : C} (P : Presieve X) := ObjectProperty.FullSubcategory fun f : Over X => P f.hom /-- Construct an object of `P.category`. -/ abbrev categoryMk {X : C} (P : Presieve X) {Y : C} (f : Y ⟶ X) (hf : P f) : P.category := ⟨Over.mk f, hf⟩ /-- Given a sieve `S` on `X : C`, its associated diagram `S.diagram` is defined to be the natural functor from the full subcategory of the over category `C/X` consisting of arrows in `S` to `C`. -/ abbrev diagram (S : Presieve X) : S.category ⥤ C := ObjectProperty.ι _ ⋙ Over.forget X /-- Given a sieve `S` on `X : C`, its associated cocone `S.cocone` is defined to be the natural cocone over the diagram defined above with cocone point `X`. -/ abbrev cocone (S : Presieve X) : Cocone S.diagram := (Over.forgetCocone X).whisker (ObjectProperty.ι _) /-- Given a set of arrows `S` all with codomain `X`, and a set of arrows with codomain `Y` for each `f : Y ⟶ X` in `S`, produce a set of arrows with codomain `X`: `{ g ≫ f | (f : Y ⟶ X) ∈ S, (g : Z ⟶ Y) ∈ R f }`. -/ def bind (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y) : Presieve X := fun Z h => ∃ (Y : C) (g : Z ⟶ Y) (f : Y ⟶ X) (H : S f), R H g ∧ g ≫ f = h /-- Structure which contains the data and properties for a morphism `h` satisfying `Presieve.bind S R h`. -/ structure BindStruct (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y) {Z : C} (h : Z ⟶ X) where /-- the intermediate object -/ Y : C /-- a morphism in the family of presieves `R` -/ g : Z ⟶ Y /-- a morphism in the presieve `S` -/ f : Y ⟶ X hf : S f hg : R hf g fac : g ≫ f = h attribute [reassoc (attr := simp)] BindStruct.fac /-- If a morphism `h` satisfies `Presieve.bind S R h`, this is a choice of a structure in `BindStruct S R h`. -/ noncomputable def bind.bindStruct {S : Presieve X} {R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y} {Z : C} {h : Z ⟶ X} (H : bind S R h) : BindStruct S R h := Nonempty.some (by obtain ⟨Y, g, f, hf, hg, fac⟩ := H exact ⟨{ hf := hf, hg := hg, fac := fac, .. }⟩) lemma BindStruct.bind {S : Presieve X} {R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y} {Z : C} {h : Z ⟶ X} (b : BindStruct S R h) : bind S R h := ⟨b.Y, b.g, b.f, b.hf, b.hg, b.fac⟩ @[simp] theorem bind_comp {S : Presieve X} {R : ∀ ⦃Y : C⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y} {g : Z ⟶ Y} (h₁ : S f) (h₂ : R h₁ g) : bind S R (g ≫ f) := ⟨_, _, _, h₁, h₂, rfl⟩ -- Porting note: it seems the definition of `Presieve` must be unfolded in order to define -- this inductive type, it was thus renamed `singleton'` -- Note we can't make this into `HasSingleton` because of the out-param. /-- The singleton presieve. -/ inductive singleton' : ⦃Y : C⦄ → (Y ⟶ X) → Prop | mk : singleton' f /-- The singleton presieve. -/ def singleton : Presieve X := singleton' f lemma singleton.mk {f : Y ⟶ X} : singleton f f := singleton'.mk @[simp] theorem singleton_eq_iff_domain (f g : Y ⟶ X) : singleton f g ↔ f = g := by constructor · rintro ⟨a, rfl⟩ rfl · rintro rfl apply singleton.mk theorem singleton_self : singleton f f := singleton.mk /-- Pullback a set of arrows with given codomain along a fixed map, by taking the pullback in the category. This is not the same as the arrow set of `Sieve.pullback`, but there is a relation between them in `pullbackArrows_comm`. -/ inductive pullbackArrows [HasPullbacks C] (R : Presieve X) : Presieve Y | mk (Z : C) (h : Z ⟶ X) : R h → pullbackArrows _ (pullback.snd h f) theorem pullback_singleton [HasPullbacks C] (g : Z ⟶ X) : pullbackArrows f (singleton g) = singleton (pullback.snd g f) := by funext W ext h constructor · rintro ⟨W, _, _, _⟩ exact singleton.mk · rintro ⟨_⟩ exact pullbackArrows.mk Z g singleton.mk /-- Construct the presieve given by the family of arrows indexed by `ι`. -/ inductive ofArrows {ι : Type*} (Y : ι → C) (f : ∀ i, Y i ⟶ X) : Presieve X | mk (i : ι) : ofArrows _ _ (f i) theorem ofArrows_pUnit : (ofArrows _ fun _ : PUnit => f) = singleton f := by funext Y ext g constructor · rintro ⟨_⟩ apply singleton.mk · rintro ⟨_⟩ exact ofArrows.mk PUnit.unit theorem ofArrows_pullback [HasPullbacks C] {ι : Type*} (Z : ι → C) (g : ∀ i : ι, Z i ⟶ X) : (ofArrows (fun i => pullback (g i) f) fun _ => pullback.snd _ _) = pullbackArrows f (ofArrows Z g) := by funext T ext h constructor · rintro ⟨hk⟩ exact pullbackArrows.mk _ _ (ofArrows.mk hk) · rintro ⟨W, k, ⟨_⟩⟩ apply ofArrows.mk theorem ofArrows_bind {ι : Type*} (Z : ι → C) (g : ∀ i : ι, Z i ⟶ X) (j : ∀ ⦃Y⦄ (f : Y ⟶ X), ofArrows Z g f → Type*) (W : ∀ ⦃Y⦄ (f : Y ⟶ X) (H), j f H → C) (k : ∀ ⦃Y⦄ (f : Y ⟶ X) (H i), W f H i ⟶ Y) : ((ofArrows Z g).bind fun _ f H => ofArrows (W f H) (k f H)) = ofArrows (fun i : Σi, j _ (ofArrows.mk i) => W (g i.1) _ i.2) fun ij => k (g ij.1) _ ij.2 ≫ g ij.1 := by funext Y ext f constructor · rintro ⟨_, _, _, ⟨i⟩, ⟨i'⟩, rfl⟩ exact ofArrows.mk (Sigma.mk _ _) · rintro ⟨i⟩ exact bind_comp _ (ofArrows.mk _) (ofArrows.mk _) theorem ofArrows_surj {ι : Type*} {Y : ι → C} (f : ∀ i, Y i ⟶ X) {Z : C} (g : Z ⟶ X) (hg : ofArrows Y f g) : ∃ (i : ι) (h : Y i = Z), g = eqToHom h.symm ≫ f i := by obtain ⟨i⟩ := hg exact ⟨i, rfl, by simp only [eqToHom_refl, id_comp]⟩ /-- Given a presieve on `F(X)`, we can define a presieve on `X` by taking the preimage via `F`. -/ def functorPullback (R : Presieve (F.obj X)) : Presieve X := fun _ f => R (F.map f) @[simp] theorem functorPullback_mem (R : Presieve (F.obj X)) {Y} (f : Y ⟶ X) : R.functorPullback F f ↔ R (F.map f) := Iff.rfl @[simp] theorem functorPullback_id (R : Presieve X) : R.functorPullback (𝟭 _) = R := rfl /-- Given a presieve `R` on `X`, the predicate `R.hasPullbacks` means that for all arrows `f` and `g` in `R`, the pullback of `f` and `g` exists. -/ class hasPullbacks (R : Presieve X) : Prop where /-- For all arrows `f` and `g` in `R`, the pullback of `f` and `g` exists. -/ has_pullbacks : ∀ {Y Z} {f : Y ⟶ X} (_ : R f) {g : Z ⟶ X} (_ : R g), HasPullback f g instance (R : Presieve X) [HasPullbacks C] : R.hasPullbacks := ⟨fun _ _ ↦ inferInstance⟩ instance {α : Type v₂} {X : α → C} {B : C} (π : (a : α) → X a ⟶ B) [(Presieve.ofArrows X π).hasPullbacks] (a b : α) : HasPullback (π a) (π b) := Presieve.hasPullbacks.has_pullbacks (Presieve.ofArrows.mk _) (Presieve.ofArrows.mk _) section FunctorPushforward variable {E : Type u₃} [Category.{v₃} E] (G : D ⥤ E) /-- Given a presieve on `X`, we can define a presieve on `F(X)` (which is actually a sieve) by taking the sieve generated by the image via `F`. -/ def functorPushforward (S : Presieve X) : Presieve (F.obj X) := fun Y f => ∃ (Z : C) (g : Z ⟶ X) (h : Y ⟶ F.obj Z), S g ∧ f = h ≫ F.map g /-- An auxiliary definition in order to fix the choice of the preimages between various definitions. -/ structure FunctorPushforwardStructure (S : Presieve X) {Y} (f : Y ⟶ F.obj X) where /-- an object in the source category -/ preobj : C /-- a map in the source category which has to be in the presieve -/ premap : preobj ⟶ X /-- the morphism which appear in the factorisation -/ lift : Y ⟶ F.obj preobj /-- the condition that `premap` is in the presieve -/ cover : S premap /-- the factorisation of the morphism -/ fac : f = lift ≫ F.map premap /-- The fixed choice of a preimage. -/ noncomputable def getFunctorPushforwardStructure {F : C ⥤ D} {S : Presieve X} {Y : D} {f : Y ⟶ F.obj X} (h : S.functorPushforward F f) : FunctorPushforwardStructure F S f := by choose Z f' g h₁ h using h exact ⟨Z, f', g, h₁, h⟩ theorem functorPushforward_comp (R : Presieve X) : R.functorPushforward (F ⋙ G) = (R.functorPushforward F).functorPushforward G := by funext x ext f constructor · rintro ⟨X, f₁, g₁, h₁, rfl⟩ exact ⟨F.obj X, F.map f₁, g₁, ⟨X, f₁, 𝟙 _, h₁, by simp⟩, rfl⟩ · rintro ⟨X, f₁, g₁, ⟨X', f₂, g₂, h₁, rfl⟩, rfl⟩ exact ⟨X', f₂, g₁ ≫ G.map g₂, h₁, by simp⟩ theorem image_mem_functorPushforward (R : Presieve X) {f : Y ⟶ X} (h : R f) : R.functorPushforward F (F.map f) := ⟨Y, f, 𝟙 _, h, by simp⟩ end FunctorPushforward end Presieve /-- For an object `X` of a category `C`, a `Sieve X` is a set of morphisms to `X` which is closed under left-composition. -/ structure Sieve {C : Type u₁} [Category.{v₁} C] (X : C) where /-- the underlying presieve -/ arrows : Presieve X /-- stability by precomposition -/ downward_closed : ∀ {Y Z f} (_ : arrows f) (g : Z ⟶ Y), arrows (g ≫ f) namespace Sieve instance : CoeFun (Sieve X) fun _ => Presieve X := ⟨Sieve.arrows⟩ initialize_simps_projections Sieve (arrows → apply) variable {S R : Sieve X} attribute [simp] downward_closed theorem arrows_ext : ∀ {R S : Sieve X}, R.arrows = S.arrows → R = S := by rintro ⟨_, _⟩ ⟨_, _⟩ rfl rfl @[ext] protected theorem ext {R S : Sieve X} (h : ∀ ⦃Y⦄ (f : Y ⟶ X), R f ↔ S f) : R = S := arrows_ext <| funext fun _ => funext fun f => propext <| h f open Lattice /-- The supremum of a collection of sieves: the union of them all. -/ protected def sup (𝒮 : Set (Sieve X)) : Sieve X where arrows _ := { f | ∃ S ∈ 𝒮, Sieve.arrows S f } downward_closed {_ _ f} hf _ := by obtain ⟨S, hS, hf⟩ := hf exact ⟨S, hS, S.downward_closed hf _⟩ /-- The infimum of a collection of sieves: the intersection of them all. -/ protected def inf (𝒮 : Set (Sieve X)) : Sieve X where arrows _ := { f | ∀ S ∈ 𝒮, Sieve.arrows S f } downward_closed {_ _ _} hf g S H := S.downward_closed (hf S H) g /-- The union of two sieves is a sieve. -/ protected def union (S R : Sieve X) : Sieve X where arrows _ f := S f ∨ R f downward_closed := by rintro _ _ _ (h | h) g <;> simp [h] /-- The intersection of two sieves is a sieve. -/ protected def inter (S R : Sieve X) : Sieve X where arrows _ f := S f ∧ R f downward_closed := by rintro _ _ _ ⟨h₁, h₂⟩ g simp [h₁, h₂] /-- Sieves on an object `X` form a complete lattice. We generate this directly rather than using the galois insertion for nicer definitional properties. -/ instance : CompleteLattice (Sieve X) where le S R := ∀ ⦃Y⦄ (f : Y ⟶ X), S f → R f le_refl _ _ _ := id le_trans _ _ _ S₁₂ S₂₃ _ _ h := S₂₃ _ (S₁₂ _ h) le_antisymm _ _ p q := Sieve.ext fun _ _ => ⟨p _, q _⟩ top := { arrows := fun _ => Set.univ downward_closed := fun _ _ => ⟨⟩ } bot := { arrows := fun _ => ∅ downward_closed := False.elim } sup := Sieve.union inf := Sieve.inter sSup := Sieve.sup sInf := Sieve.inf le_sSup _ S hS _ _ hf := ⟨S, hS, hf⟩ sSup_le := fun _ _ ha _ _ ⟨b, hb, hf⟩ => (ha b hb) _ hf sInf_le _ _ hS _ _ h := h _ hS le_sInf _ _ hS _ _ hf _ hR := hS _ hR _ hf le_sup_left _ _ _ _ := Or.inl le_sup_right _ _ _ _ := Or.inr sup_le _ _ _ h₁ h₂ _ f := by--ℰ S hS Y f := by rintro (hf | hf) · exact h₁ _ hf · exact h₂ _ hf inf_le_left _ _ _ _ := And.left inf_le_right _ _ _ _ := And.right le_inf _ _ _ p q _ _ z := ⟨p _ z, q _ z⟩ le_top _ _ _ _ := trivial bot_le _ _ _ := False.elim /-- The maximal sieve always exists. -/ instance sieveInhabited : Inhabited (Sieve X) := ⟨⊤⟩ @[simp] theorem sInf_apply {Ss : Set (Sieve X)} {Y} (f : Y ⟶ X) : sInf Ss f ↔ ∀ (S : Sieve X) (_ : S ∈ Ss), S f := Iff.rfl @[simp] theorem sSup_apply {Ss : Set (Sieve X)} {Y} (f : Y ⟶ X) : sSup Ss f ↔ ∃ (S : Sieve X) (_ : S ∈ Ss), S f := by simp [sSup, Sieve.sup, setOf] @[simp] theorem inter_apply {R S : Sieve X} {Y} (f : Y ⟶ X) : (R ⊓ S) f ↔ R f ∧ S f := Iff.rfl @[simp] theorem union_apply {R S : Sieve X} {Y} (f : Y ⟶ X) : (R ⊔ S) f ↔ R f ∨ S f := Iff.rfl @[simp] theorem top_apply (f : Y ⟶ X) : (⊤ : Sieve X) f := trivial /-- Generate the smallest sieve containing the given set of arrows. -/ @[simps] def generate (R : Presieve X) : Sieve X where arrows Z f := ∃ (Y : _) (h : Z ⟶ Y) (g : Y ⟶ X), R g ∧ h ≫ g = f downward_closed := by rintro Y Z _ ⟨W, g, f, hf, rfl⟩ h exact ⟨_, h ≫ g, _, hf, by simp⟩ /-- Given a presieve on `X`, and a sieve on each domain of an arrow in the presieve, we can bind to produce a sieve on `X`. -/ @[simps] def bind (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y) : Sieve X where arrows := S.bind fun _ _ h => R h downward_closed := by rintro Y Z f ⟨W, f, h, hh, hf, rfl⟩ g exact ⟨_, g ≫ f, _, hh, by simp [hf]⟩ /-- Structure which contains the data and properties for a morphism `h` satisfying `Sieve.bind S R h`. -/ abbrev BindStruct (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y) {Z : C} (h : Z ⟶ X) := Presieve.BindStruct S (fun _ _ hf ↦ R hf) h open Order Lattice theorem generate_le_iff (R : Presieve X) (S : Sieve X) : generate R ≤ S ↔ R ≤ S := ⟨fun H _ _ hg => H _ ⟨_, 𝟙 _, _, hg, id_comp _⟩, fun ss Y f => by rintro ⟨Z, f, g, hg, rfl⟩ exact S.downward_closed (ss Z hg) f⟩ /-- Show that there is a galois insertion (generate, set_over). -/ def giGenerate : GaloisInsertion (generate : Presieve X → Sieve X) arrows where gc := generate_le_iff choice 𝒢 _ := generate 𝒢 choice_eq _ _ := rfl le_l_u _ _ _ hf := ⟨_, 𝟙 _, _, hf, id_comp _⟩ theorem le_generate (R : Presieve X) : R ≤ generate R := giGenerate.gc.le_u_l R @[simp] theorem generate_sieve (S : Sieve X) : generate S = S := giGenerate.l_u_eq S /-- If the identity arrow is in a sieve, the sieve is maximal. -/ theorem id_mem_iff_eq_top : S (𝟙 X) ↔ S = ⊤ := ⟨fun h => top_unique fun Y f _ => by simpa using downward_closed _ h f, fun h => h.symm ▸ trivial⟩ /-- If an arrow set contains a split epi, it generates the maximal sieve. -/ theorem generate_of_contains_isSplitEpi {R : Presieve X} (f : Y ⟶ X) [IsSplitEpi f] (hf : R f) : generate R = ⊤ := by rw [← id_mem_iff_eq_top] exact ⟨_, section_ f, f, hf, by simp⟩ @[simp] theorem generate_of_singleton_isSplitEpi (f : Y ⟶ X) [IsSplitEpi f] : generate (Presieve.singleton f) = ⊤ := generate_of_contains_isSplitEpi f (Presieve.singleton_self _) @[simp] theorem generate_top : generate (⊤ : Presieve X) = ⊤ := generate_of_contains_isSplitEpi (𝟙 _) ⟨⟩ @[simp] lemma comp_mem_iff (i : X ⟶ Y) (f : Y ⟶ Z) [IsIso i] (S : Sieve Z) : S (i ≫ f) ↔ S f := by refine ⟨fun H ↦ ?_, fun H ↦ S.downward_closed H _⟩ convert S.downward_closed H (inv i) simp section variable {I : Type*} {X : C} (Y : I → C) (f : ∀ i, Y i ⟶ X) /-- The sieve of `X` generated by family of morphisms `Y i ⟶ X`. -/ abbrev ofArrows : Sieve X := generate (Presieve.ofArrows Y f) lemma ofArrows_mk (i : I) : ofArrows Y f (f i) := ⟨_, 𝟙 _, _, ⟨i⟩, by simp⟩ lemma mem_ofArrows_iff {W : C} (g : W ⟶ X) : ofArrows Y f g ↔ ∃ (i : I) (a : W ⟶ Y i), g = a ≫ f i := by constructor · rintro ⟨T, a, b, ⟨i⟩, rfl⟩ exact ⟨i, a, rfl⟩ · rintro ⟨i, a, rfl⟩ apply downward_closed _ (ofArrows_mk Y f i) variable {Y f} {W : C} {g : W ⟶ X} (hg : ofArrows Y f g) include hg in
lemma ofArrows.exists : ∃ (i : I) (h : W ⟶ Y i), g = h ≫ f i := by obtain ⟨_, h, _, ⟨i⟩, rfl⟩ := hg exact ⟨i, h, rfl⟩
Mathlib/CategoryTheory/Sites/Sieves.lean
471
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/- Copyright (c) 2021 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.LinearAlgebra.TensorAlgebra.Basic import Mathlib.LinearAlgebra.TensorPower.Basic /-! # Tensor algebras as direct sums of tensor powers In this file we show that `TensorAlgebra R M` is isomorphic to a direct sum of tensor powers, as `TensorAlgebra.equivDirectSum`. -/ suppress_compilation open scoped DirectSum TensorProduct variable {R M : Type*} [CommSemiring R] [AddCommMonoid M] [Module R M] namespace TensorPower /-- The canonical embedding from a tensor power to the tensor algebra -/ def toTensorAlgebra {n} : ⨂[R]^n M →ₗ[R] TensorAlgebra R M := PiTensorProduct.lift (TensorAlgebra.tprod R M n) @[simp] theorem toTensorAlgebra_tprod {n} (x : Fin n → M) : TensorPower.toTensorAlgebra (PiTensorProduct.tprod R x) = TensorAlgebra.tprod R M n x := PiTensorProduct.lift.tprod _ @[simp] theorem toTensorAlgebra_gOne : TensorPower.toTensorAlgebra (@GradedMonoid.GOne.one _ (fun n => ⨂[R]^n M) _ _) = 1 := by simp [GradedMonoid.GOne.one, TensorPower.toTensorAlgebra_tprod] @[simp] theorem toTensorAlgebra_gMul {i j} (a : (⨂[R]^i) M) (b : (⨂[R]^j) M) : TensorPower.toTensorAlgebra (@GradedMonoid.GMul.mul _ (fun n => ⨂[R]^n M) _ _ _ _ a b) = TensorPower.toTensorAlgebra a * TensorPower.toTensorAlgebra b := by -- change `a` and `b` to `tprod R a` and `tprod R b` rw [TensorPower.gMul_eq_coe_linearMap, ← LinearMap.compr₂_apply, ← @LinearMap.mul_apply' R, ← LinearMap.compl₂_apply, ← LinearMap.comp_apply] refine LinearMap.congr_fun (LinearMap.congr_fun ?_ a) b clear! a b ext (a b) -- Porting note: pulled the next two lines out of the long `simp only` below. simp only [LinearMap.compMultilinearMap_apply] rw [LinearMap.compr₂_apply, ← gMul_eq_coe_linearMap] simp only [LinearMap.compr₂_apply, LinearMap.mul_apply', LinearMap.compl₂_apply, LinearMap.comp_apply, LinearMap.compMultilinearMap_apply, PiTensorProduct.lift.tprod, TensorPower.tprod_mul_tprod, TensorPower.toTensorAlgebra_tprod, TensorAlgebra.tprod_apply, ← gMul_eq_coe_linearMap] refine Eq.trans ?_ List.prod_append congr -- Porting note: `erw` for `Function.comp` erw [← List.map_ofFn _ (TensorAlgebra.ι R), ← List.map_ofFn _ (TensorAlgebra.ι R), ← List.map_ofFn _ (TensorAlgebra.ι R), ← List.map_append, List.ofFn_fin_append] @[simp] theorem toTensorAlgebra_galgebra_toFun (r : R) : TensorPower.toTensorAlgebra (DirectSum.GAlgebra.toFun (R := R) (A := fun n => ⨂[R]^n M) r) = algebraMap _ _ r := by rw [TensorPower.galgebra_toFun_def, TensorPower.algebraMap₀_eq_smul_one, LinearMap.map_smul, TensorPower.toTensorAlgebra_gOne, Algebra.algebraMap_eq_smul_one] end TensorPower namespace TensorAlgebra /-- The canonical map from a direct sum of tensor powers to the tensor algebra. -/ def ofDirectSum : (⨁ n, ⨂[R]^n M) →ₐ[R] TensorAlgebra R M := DirectSum.toAlgebra _ _ (fun _ => TensorPower.toTensorAlgebra) TensorPower.toTensorAlgebra_gOne (fun {_ _} => TensorPower.toTensorAlgebra_gMul) @[simp] theorem ofDirectSum_of_tprod {n} (x : Fin n → M) : ofDirectSum (DirectSum.of _ n (PiTensorProduct.tprod R x)) = tprod R M n x := (DirectSum.toAddMonoid_of (fun _ ↦ LinearMap.toAddMonoidHom TensorPower.toTensorAlgebra) _ _).trans (TensorPower.toTensorAlgebra_tprod _) /-- The canonical map from the tensor algebra to a direct sum of tensor powers. -/ def toDirectSum : TensorAlgebra R M →ₐ[R] ⨁ n, ⨂[R]^n M := TensorAlgebra.lift R <| DirectSum.lof R ℕ (fun n => ⨂[R]^n M) _ ∘ₗ (LinearEquiv.symm <| PiTensorProduct.subsingletonEquiv (0 : Fin 1) : M ≃ₗ[R] _).toLinearMap @[simp] theorem toDirectSum_ι (x : M) : toDirectSum (ι R x) = DirectSum.of (fun n => ⨂[R]^n M) _ (PiTensorProduct.tprod R fun _ : Fin 1 => x) := TensorAlgebra.lift_ι_apply _ _ theorem ofDirectSum_comp_toDirectSum : ofDirectSum.comp toDirectSum = AlgHom.id R (TensorAlgebra R M) := by ext simp [DirectSum.lof_eq_of, tprod_apply] @[simp] theorem ofDirectSum_toDirectSum (x : TensorAlgebra R M) : ofDirectSum (TensorAlgebra.toDirectSum x) = x := AlgHom.congr_fun ofDirectSum_comp_toDirectSum x -- See https://github.com/leanprover-community/batteries/issues/365 for the simpNF issue. -- It seems the side condition `h` is not applied by `simpNF`. @[simp, nolint simpNF] theorem mk_reindex_cast {n m : ℕ} (h : n = m) (x : ⨂[R]^n M) : GradedMonoid.mk (A := fun i => (⨂[R]^i) M) m (PiTensorProduct.reindex R (fun _ ↦ M) (Equiv.cast <| congr_arg Fin h) x) = GradedMonoid.mk n x := Eq.symm (PiTensorProduct.gradedMonoid_eq_of_reindex_cast h rfl) @[simp] theorem mk_reindex_fin_cast {n m : ℕ} (h : n = m) (x : ⨂[R]^n M) : GradedMonoid.mk (A := fun i => (⨂[R]^i) M) m (PiTensorProduct.reindex R (fun _ ↦ M) (finCongr h) x) = GradedMonoid.mk n x := by rw [finCongr_eq_equivCast, mk_reindex_cast h] /-- The product of tensor products made of a single vector is the same as a single product of all the vectors. -/ theorem _root_.TensorPower.list_prod_gradedMonoid_mk_single (n : ℕ) (x : Fin n → M) : ((List.finRange n).map fun a => (GradedMonoid.mk _ (PiTensorProduct.tprod R fun _ : Fin 1 => x a) : GradedMonoid fun n => ⨂[R]^n M)).prod = GradedMonoid.mk n (PiTensorProduct.tprod R x) := by refine Fin.consInduction ?_ ?_ x <;> clear x · rw [List.finRange_zero, List.map_nil, List.prod_nil] rfl · intro n x₀ x ih rw [List.finRange_succ_eq_map, List.map_cons, List.prod_cons, List.map_map] simp_rw [Function.comp_def, Fin.cons_zero, Fin.cons_succ] rw [ih, GradedMonoid.mk_mul_mk, TensorPower.tprod_mul_tprod] refine TensorPower.gradedMonoid_eq_of_cast (add_comm _ _) ?_
dsimp only [GradedMonoid.mk] rw [TensorPower.cast_tprod] simp_rw [Fin.append_left_eq_cons, Function.comp_def] congr 1 with i theorem toDirectSum_tensorPower_tprod {n} (x : Fin n → M) : toDirectSum (tprod R M n x) = DirectSum.of _ n (PiTensorProduct.tprod R x) := by rw [tprod_apply, map_list_prod, List.map_ofFn] simp_rw [Function.comp_def, toDirectSum_ι] rw [DirectSum.list_prod_ofFn_of_eq_dProd] apply DirectSum.of_eq_of_gradedMonoid_eq rw [GradedMonoid.mk_list_dProd] rw [TensorPower.list_prod_gradedMonoid_mk_single] theorem toDirectSum_comp_ofDirectSum : toDirectSum.comp ofDirectSum = AlgHom.id R (⨁ n, ⨂[R]^n M) := by ext
Mathlib/LinearAlgebra/TensorAlgebra/ToTensorPower.lean
136
152
/- Copyright (c) 2018 Louis Carlin. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Louis Carlin, Mario Carneiro -/ import Mathlib.Algebra.EuclideanDomain.Defs import Mathlib.Algebra.Ring.Divisibility.Basic import Mathlib.Algebra.Ring.Regular import Mathlib.Algebra.GroupWithZero.Divisibility import Mathlib.Algebra.Ring.Basic /-! # Lemmas about Euclidean domains ## Main statements * `gcd_eq_gcd_ab`: states Bézout's lemma for Euclidean domains. -/ universe u namespace EuclideanDomain variable {R : Type u} variable [EuclideanDomain R] /-- The well founded relation in a Euclidean Domain satisfying `a % b ≺ b` for `b ≠ 0` -/ local infixl:50 " ≺ " => EuclideanDomain.r -- See note [lower instance priority] instance (priority := 100) toMulDivCancelClass : MulDivCancelClass R where mul_div_cancel a b hb := by refine (eq_of_sub_eq_zero ?_).symm by_contra h have := mul_right_not_lt b h rw [sub_mul, mul_comm (_ / _), sub_eq_iff_eq_add'.2 (div_add_mod (a * b) b).symm] at this exact this (mod_lt _ hb) theorem mod_eq_sub_mul_div {R : Type*} [EuclideanDomain R] (a b : R) : a % b = a - b * (a / b) := calc a % b = b * (a / b) + a % b - b * (a / b) := (add_sub_cancel_left _ _).symm _ = a - b * (a / b) := by rw [div_add_mod] theorem val_dvd_le : ∀ a b : R, b ∣ a → a ≠ 0 → ¬a ≺ b
| _, b, ⟨d, rfl⟩, ha => mul_left_not_lt b (mt (by rintro rfl; exact mul_zero _) ha) @[simp] theorem mod_eq_zero {a b : R} : a % b = 0 ↔ b ∣ a := ⟨fun h => by rw [← div_add_mod a b, h, add_zero] exact dvd_mul_right _ _, fun ⟨c, e⟩ => by rw [e, ← add_left_cancel_iff, div_add_mod, add_zero] haveI := Classical.dec
Mathlib/Algebra/EuclideanDomain/Basic.lean
47
55
/- Copyright (c) 2020 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov -/ import Mathlib.Algebra.Order.Group.Indicator import Mathlib.Algebra.Order.Pi import Mathlib.Analysis.Normed.Group.Basic /-! # Indicator function and (e)norm This file contains a few simple lemmas about `Set.indicator`, `norm` and `enorm`. ## Tags indicator, norm -/ open Set section ENormedAddMonoid variable {α ε : Type*} [TopologicalSpace ε] [ENormedAddMonoid ε] {s t : Set α} (f : α → ε) (a : α) lemma enorm_indicator_eq_indicator_enorm : ‖indicator s f a‖ₑ = indicator s (fun a => ‖f a‖ₑ) a := flip congr_fun a (indicator_comp_of_zero (enorm_zero (E := ε))).symm theorem enorm_indicator_le_of_subset (h : s ⊆ t) (f : α → ε) (a : α) : ‖indicator s f a‖ₑ ≤ ‖indicator t f a‖ₑ := by simp only [enorm_indicator_eq_indicator_enorm] apply indicator_le_indicator_of_subset ‹_› (zero_le _)
theorem indicator_enorm_le_enorm_self : indicator s (fun a => ‖f a‖ₑ) a ≤ ‖f a‖ₑ := indicator_le_self' (fun _ _ ↦ zero_le _) a theorem enorm_indicator_le_enorm_self : ‖indicator s f a‖ₑ ≤ ‖f a‖ₑ := by
Mathlib/Analysis/NormedSpace/IndicatorFunction.lean
34
37
/- Copyright (c) 2024 Violeta Hernández Palacios. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Violeta Hernández Palacios -/ import Mathlib.SetTheory.Cardinal.Arithmetic import Mathlib.SetTheory.Ordinal.Principal /-! # Ordinal arithmetic with cardinals This file collects results about the cardinality of different ordinal operations. -/ universe u v open Cardinal Ordinal Set /-! ### Cardinal operations with ordinal indices -/ namespace Cardinal /-- Bounds the cardinal of an ordinal-indexed union of sets. -/ lemma mk_iUnion_Ordinal_lift_le_of_le {β : Type v} {o : Ordinal.{u}} {c : Cardinal.{v}} (ho : lift.{v} o.card ≤ lift.{u} c) (hc : ℵ₀ ≤ c) (A : Ordinal → Set β) (hA : ∀ j < o, #(A j) ≤ c) : #(⋃ j < o, A j) ≤ c := by simp_rw [← mem_Iio, biUnion_eq_iUnion, iUnion, iSup, ← o.enumIsoToType.symm.surjective.range_comp] rw [← lift_le.{u}] apply ((mk_iUnion_le_lift _).trans _).trans_eq (mul_eq_self (aleph0_le_lift.2 hc)) rw [mk_toType] refine mul_le_mul' ho (ciSup_le' ?_) intro i simpa using hA _ (o.enumIsoToType.symm i).2 lemma mk_iUnion_Ordinal_le_of_le {β : Type*} {o : Ordinal} {c : Cardinal} (ho : o.card ≤ c) (hc : ℵ₀ ≤ c) (A : Ordinal → Set β) (hA : ∀ j < o, #(A j) ≤ c) : #(⋃ j < o, A j) ≤ c := by apply mk_iUnion_Ordinal_lift_le_of_le _ hc A hA rwa [Cardinal.lift_le] end Cardinal @[deprecated mk_iUnion_Ordinal_le_of_le (since := "2024-11-02")] alias Ordinal.Cardinal.mk_iUnion_Ordinal_le_of_le := mk_iUnion_Ordinal_le_of_le /-! ### Cardinality of ordinals -/ namespace Ordinal theorem lift_card_iSup_le_sum_card {ι : Type u} [Small.{v} ι] (f : ι → Ordinal.{v}) : Cardinal.lift.{u} (⨆ i, f i).card ≤ Cardinal.sum fun i ↦ (f i).card := by simp_rw [← mk_toType] rw [← mk_sigma, ← Cardinal.lift_id'.{v} #(Σ _, _), ← Cardinal.lift_umax.{v, u}] apply lift_mk_le_lift_mk_of_surjective (f := enumIsoToType _ ∘ (⟨(enumIsoToType _).symm ·.2, (mem_Iio.mp ((enumIsoToType _).symm _).2).trans_le (Ordinal.le_iSup _ _)⟩)) rw [EquivLike.comp_surjective] rintro ⟨x, hx⟩ obtain ⟨i, hi⟩ := Ordinal.lt_iSup_iff.mp hx exact ⟨⟨i, enumIsoToType _ ⟨x, hi⟩⟩, by simp⟩ theorem card_iSup_le_sum_card {ι : Type u} (f : ι → Ordinal.{max u v}) : (⨆ i, f i).card ≤ Cardinal.sum (fun i ↦ (f i).card) := by have := lift_card_iSup_le_sum_card f rwa [Cardinal.lift_id'] at this theorem card_iSup_Iio_le_sum_card {o : Ordinal.{u}} (f : Iio o → Ordinal.{max u v}) : (⨆ a : Iio o, f a).card ≤ Cardinal.sum fun i ↦ (f ((enumIsoToType o).symm i)).card := by apply le_of_eq_of_le (congr_arg _ _).symm (card_iSup_le_sum_card _) simpa using (enumIsoToType o).symm.iSup_comp (g := fun x ↦ f x) theorem card_iSup_Iio_le_card_mul_iSup {o : Ordinal.{u}} (f : Iio o → Ordinal.{max u v}) : (⨆ a : Iio o, f a).card ≤ Cardinal.lift.{v} o.card * ⨆ a : Iio o, (f a).card := by apply (card_iSup_Iio_le_sum_card f).trans convert ← sum_le_iSup_lift _ · exact mk_toType o · exact (enumIsoToType o).symm.iSup_comp (g := fun x ↦ (f x).card) theorem card_opow_le_of_omega0_le_left {a : Ordinal} (ha : ω ≤ a) (b : Ordinal) : (a ^ b).card ≤ max a.card b.card := by refine limitRecOn b ?_ ?_ ?_ · simpa using one_lt_omega0.le.trans ha · intro b IH rw [opow_succ, card_mul, card_succ, Cardinal.mul_eq_max_of_aleph0_le_right, max_comm] · apply (max_le_max_left _ IH).trans rw [← max_assoc, max_self] exact max_le_max_left _ le_self_add · rw [ne_eq, card_eq_zero, opow_eq_zero] rintro ⟨rfl, -⟩ cases omega0_pos.not_le ha · rwa [aleph0_le_card] · intro b hb IH rw [(isNormal_opow (one_lt_omega0.trans_le ha)).apply_of_isLimit hb] apply (card_iSup_Iio_le_card_mul_iSup _).trans rw [Cardinal.lift_id, Cardinal.mul_eq_max_of_aleph0_le_right, max_comm] · apply max_le _ (le_max_right _ _) apply ciSup_le' intro c exact (IH c.1 c.2).trans (max_le_max_left _ (card_le_card c.2.le)) · simpa using hb.pos.ne' · refine le_ciSup_of_le ?_ ⟨1, one_lt_omega0.trans_le <| omega0_le_of_isLimit hb⟩ ?_ · exact Cardinal.bddAbove_of_small _ · simpa theorem card_opow_le_of_omega0_le_right (a : Ordinal) {b : Ordinal} (hb : ω ≤ b) : (a ^ b).card ≤ max a.card b.card := by obtain ⟨n, rfl⟩ | ha := eq_nat_or_omega0_le a · apply (card_le_card <| opow_le_opow_left b (nat_lt_omega0 n).le).trans apply (card_opow_le_of_omega0_le_left le_rfl _).trans simp [hb] · exact card_opow_le_of_omega0_le_left ha b theorem card_opow_le (a b : Ordinal) : (a ^ b).card ≤ max ℵ₀ (max a.card b.card) := by obtain ⟨n, rfl⟩ | ha := eq_nat_or_omega0_le a · obtain ⟨m, rfl⟩ | hb := eq_nat_or_omega0_le b · rw [← natCast_opow, card_nat] exact le_max_of_le_left (nat_lt_aleph0 _).le · exact (card_opow_le_of_omega0_le_right _ hb).trans (le_max_right _ _) · exact (card_opow_le_of_omega0_le_left ha _).trans (le_max_right _ _) theorem card_opow_eq_of_omega0_le_left {a b : Ordinal} (ha : ω ≤ a) (hb : 0 < b) : (a ^ b).card = max a.card b.card := by apply (card_opow_le_of_omega0_le_left ha b).antisymm (max_le _ _) <;> apply card_le_card · exact left_le_opow a hb · exact right_le_opow b (one_lt_omega0.trans_le ha) theorem card_opow_eq_of_omega0_le_right {a b : Ordinal} (ha : 1 < a) (hb : ω ≤ b) : (a ^ b).card = max a.card b.card := by apply (card_opow_le_of_omega0_le_right a hb).antisymm (max_le _ _) <;> apply card_le_card · exact left_le_opow a (omega0_pos.trans_le hb) · exact right_le_opow b ha theorem card_omega0_opow {a : Ordinal} (h : a ≠ 0) : card (ω ^ a) = max ℵ₀ a.card := by rw [card_opow_eq_of_omega0_le_left le_rfl h.bot_lt, card_omega0] theorem card_opow_omega0 {a : Ordinal} (h : 1 < a) : card (a ^ ω) = max ℵ₀ a.card := by rw [card_opow_eq_of_omega0_le_right h le_rfl, card_omega0, max_comm] theorem principal_opow_omega (o : Ordinal) : Principal (· ^ ·) (ω_ o) := by obtain rfl | ho := Ordinal.eq_zero_or_pos o · rw [omega_zero] exact principal_opow_omega0 · intro a b ha hb rw [lt_omega_iff_card_lt] at ha hb ⊢ apply (card_opow_le a b).trans_lt (max_lt _ (max_lt ha hb)) rwa [← aleph_zero, aleph_lt_aleph] theorem IsInitial.principal_opow {o : Ordinal} (h : IsInitial o) (ho : ω ≤ o) : Principal (· ^ ·) o := by obtain ⟨a, rfl⟩ := mem_range_omega_iff.2 ⟨ho, h⟩ exact principal_opow_omega a theorem principal_opow_ord {c : Cardinal} (hc : ℵ₀ ≤ c) : Principal (· ^ ·) c.ord := by apply (isInitial_ord c).principal_opow rwa [omega0_le_ord] /-! ### Initial ordinals are principal -/ theorem principal_add_ord {c : Cardinal} (hc : ℵ₀ ≤ c) : Principal (· + ·) c.ord := by intro a b ha hb rw [lt_ord, card_add] at * exact add_lt_of_lt hc ha hb theorem IsInitial.principal_add {o : Ordinal} (h : IsInitial o) (ho : ω ≤ o) : Principal (· + ·) o := by rw [← h.ord_card] apply principal_add_ord rwa [aleph0_le_card] theorem principal_add_omega (o : Ordinal) : Principal (· + ·) (ω_ o) := (isInitial_omega o).principal_add (omega0_le_omega o) theorem principal_mul_ord {c : Cardinal} (hc : ℵ₀ ≤ c) : Principal (· * ·) c.ord := by intro a b ha hb rw [lt_ord, card_mul] at * exact mul_lt_of_lt hc ha hb theorem IsInitial.principal_mul {o : Ordinal} (h : IsInitial o) (ho : ω ≤ o) : Principal (· * ·) o := by rw [← h.ord_card] apply principal_mul_ord rwa [aleph0_le_card] theorem principal_mul_omega (o : Ordinal) : Principal (· * ·) (ω_ o) := (isInitial_omega o).principal_mul (omega0_le_omega o) @[deprecated principal_add_omega (since := "2024-11-08")] theorem _root_.Cardinal.principal_add_aleph (o : Ordinal) : Principal (· + ·) (ℵ_ o).ord := principal_add_ord <| aleph0_le_aleph o end Ordinal
Mathlib/SetTheory/Cardinal/Ordinal.lean
487
491
/- Copyright (c) 2021 Riccardo Brasca. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Riccardo Brasca -/ import Mathlib.Algebra.Group.Pointwise.Set.Finite import Mathlib.Algebra.Group.Subgroup.Pointwise import Mathlib.GroupTheory.QuotientGroup.Defs /-! # Finitely generated monoids and groups We define finitely generated monoids and groups. See also `Submodule.FG` and `Module.Finite` for finitely-generated modules. ## Main definition * `Submonoid.FG S`, `AddSubmonoid.FG S` : A submonoid `S` is finitely generated. * `Monoid.FG M`, `AddMonoid.FG M` : A typeclass indicating a type `M` is finitely generated as a monoid. * `Subgroup.FG S`, `AddSubgroup.FG S` : A subgroup `S` is finitely generated. * `Group.FG M`, `AddGroup.FG M` : A typeclass indicating a type `M` is finitely generated as a group. -/ assert_not_exists MonoidWithZero /-! ### Monoids and submonoids -/ open Pointwise variable {M N : Type*} [Monoid M] section Submonoid variable [Monoid N] {P : Submonoid M} {Q : Submonoid N} /-- A submonoid of `M` is finitely generated if it is the closure of a finite subset of `M`. -/ @[to_additive] def Submonoid.FG (P : Submonoid M) : Prop := ∃ S : Finset M, Submonoid.closure ↑S = P /-- An additive submonoid of `N` is finitely generated if it is the closure of a finite subset of `M`. -/ add_decl_doc AddSubmonoid.FG /-- An equivalent expression of `Submonoid.FG` in terms of `Set.Finite` instead of `Finset`. -/ @[to_additive "An equivalent expression of `AddSubmonoid.FG` in terms of `Set.Finite` instead of `Finset`."] theorem Submonoid.fg_iff (P : Submonoid M) : Submonoid.FG P ↔ ∃ S : Set M, Submonoid.closure S = P ∧ S.Finite := ⟨fun ⟨S, hS⟩ => ⟨S, hS, Finset.finite_toSet S⟩, fun ⟨S, hS, hf⟩ => ⟨Set.Finite.toFinset hf, by simp [hS]⟩⟩ theorem Submonoid.fg_iff_add_fg (P : Submonoid M) : P.FG ↔ P.toAddSubmonoid.FG := ⟨fun h => let ⟨S, hS, hf⟩ := (Submonoid.fg_iff _).1 h (AddSubmonoid.fg_iff _).mpr ⟨Additive.toMul ⁻¹' S, by simp [← Submonoid.toAddSubmonoid_closure, hS], hf⟩, fun h => let ⟨T, hT, hf⟩ := (AddSubmonoid.fg_iff _).1 h
(Submonoid.fg_iff _).mpr ⟨Additive.ofMul ⁻¹' T, by simp [← AddSubmonoid.toSubmonoid'_closure, hT], hf⟩⟩ theorem AddSubmonoid.fg_iff_mul_fg {M : Type*} [AddMonoid M] (P : AddSubmonoid M) : P.FG ↔ P.toSubmonoid.FG := by convert (Submonoid.fg_iff_add_fg (toSubmonoid P)).symm /-- The product of finitely generated submonoids is finitely generated. -/ @[to_additive "The product of finitely generated submonoids is finitely generated."]
Mathlib/GroupTheory/Finiteness.lean
63
71
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Johannes Hölzl, Kim Morrison, Jens Wagemaker, Johan Commelin -/ import Mathlib.Algebra.Polynomial.BigOperators import Mathlib.Algebra.Polynomial.RingDivision import Mathlib.Data.Set.Finite.Lemmas import Mathlib.RingTheory.Coprime.Lemmas import Mathlib.RingTheory.Localization.FractionRing import Mathlib.SetTheory.Cardinal.Order /-! # Theory of univariate polynomials We define the multiset of roots of a polynomial, and prove basic results about it. ## Main definitions * `Polynomial.roots p`: The multiset containing all the roots of `p`, including their multiplicities. * `Polynomial.rootSet p E`: The set of distinct roots of `p` in an algebra `E`. ## Main statements * `Polynomial.C_leadingCoeff_mul_prod_multiset_X_sub_C`: If a polynomial has as many roots as its degree, it can be written as the product of its leading coefficient with `∏ (X - a)` where `a` ranges through its roots. -/ assert_not_exists Ideal open Multiset Finset noncomputable section namespace Polynomial universe u v w z variable {R : Type u} {S : Type v} {T : Type w} {a b : R} {n : ℕ} section CommRing variable [CommRing R] [IsDomain R] {p q : R[X]} section Roots /-- `roots p` noncomputably gives a multiset containing all the roots of `p`, including their multiplicities. -/ noncomputable def roots (p : R[X]) : Multiset R := haveI := Classical.decEq R haveI := Classical.dec (p = 0) if h : p = 0 then ∅ else Classical.choose (exists_multiset_roots h) theorem roots_def [DecidableEq R] (p : R[X]) [Decidable (p = 0)] : p.roots = if h : p = 0 then ∅ else Classical.choose (exists_multiset_roots h) := by rename_i iR ip0 obtain rfl := Subsingleton.elim iR (Classical.decEq R) obtain rfl := Subsingleton.elim ip0 (Classical.dec (p = 0)) rfl @[simp] theorem roots_zero : (0 : R[X]).roots = 0 := dif_pos rfl theorem card_roots (hp0 : p ≠ 0) : (Multiset.card (roots p) : WithBot ℕ) ≤ degree p := by classical unfold roots rw [dif_neg hp0] exact (Classical.choose_spec (exists_multiset_roots hp0)).1 theorem card_roots' (p : R[X]) : Multiset.card p.roots ≤ natDegree p := by by_cases hp0 : p = 0 · simp [hp0] exact WithBot.coe_le_coe.1 (le_trans (card_roots hp0) (le_of_eq <| degree_eq_natDegree hp0)) theorem card_roots_sub_C {p : R[X]} {a : R} (hp0 : 0 < degree p) : (Multiset.card (p - C a).roots : WithBot ℕ) ≤ degree p := calc (Multiset.card (p - C a).roots : WithBot ℕ) ≤ degree (p - C a) := card_roots <| mt sub_eq_zero.1 fun h => not_le_of_gt hp0 <| h.symm ▸ degree_C_le _ = degree p := by rw [sub_eq_add_neg, ← C_neg]; exact degree_add_C hp0 theorem card_roots_sub_C' {p : R[X]} {a : R} (hp0 : 0 < degree p) : Multiset.card (p - C a).roots ≤ natDegree p := WithBot.coe_le_coe.1 (le_trans (card_roots_sub_C hp0) (le_of_eq <| degree_eq_natDegree fun h => by simp_all [lt_irrefl])) @[simp] theorem count_roots [DecidableEq R] (p : R[X]) : p.roots.count a = rootMultiplicity a p := by classical by_cases hp : p = 0 · simp [hp] rw [roots_def, dif_neg hp] exact (Classical.choose_spec (exists_multiset_roots hp)).2 a @[simp] theorem mem_roots' : a ∈ p.roots ↔ p ≠ 0 ∧ IsRoot p a := by classical rw [← count_pos, count_roots p, rootMultiplicity_pos'] theorem mem_roots (hp : p ≠ 0) : a ∈ p.roots ↔ IsRoot p a := mem_roots'.trans <| and_iff_right hp theorem ne_zero_of_mem_roots (h : a ∈ p.roots) : p ≠ 0 := (mem_roots'.1 h).1 theorem isRoot_of_mem_roots (h : a ∈ p.roots) : IsRoot p a := (mem_roots'.1 h).2 theorem mem_roots_map_of_injective [Semiring S] {p : S[X]} {f : S →+* R} (hf : Function.Injective f) {x : R} (hp : p ≠ 0) : x ∈ (p.map f).roots ↔ p.eval₂ f x = 0 := by rw [mem_roots ((Polynomial.map_ne_zero_iff hf).mpr hp), IsRoot, eval_map] lemma mem_roots_iff_aeval_eq_zero {x : R} (w : p ≠ 0) : x ∈ roots p ↔ aeval x p = 0 := by rw [aeval_def, ← mem_roots_map_of_injective (FaithfulSMul.algebraMap_injective _ _) w, Algebra.id.map_eq_id, map_id] theorem card_le_degree_of_subset_roots {p : R[X]} {Z : Finset R} (h : Z.val ⊆ p.roots) : #Z ≤ p.natDegree := (Multiset.card_le_card (Finset.val_le_iff_val_subset.2 h)).trans (Polynomial.card_roots' p) theorem finite_setOf_isRoot {p : R[X]} (hp : p ≠ 0) : Set.Finite { x | IsRoot p x } := by classical simpa only [← Finset.setOf_mem, Multiset.mem_toFinset, mem_roots hp] using p.roots.toFinset.finite_toSet theorem eq_zero_of_infinite_isRoot (p : R[X]) (h : Set.Infinite { x | IsRoot p x }) : p = 0 := not_imp_comm.mp finite_setOf_isRoot h theorem exists_max_root [LinearOrder R] (p : R[X]) (hp : p ≠ 0) : ∃ x₀, ∀ x, p.IsRoot x → x ≤ x₀ := Set.exists_upper_bound_image _ _ <| finite_setOf_isRoot hp theorem exists_min_root [LinearOrder R] (p : R[X]) (hp : p ≠ 0) : ∃ x₀, ∀ x, p.IsRoot x → x₀ ≤ x := Set.exists_lower_bound_image _ _ <| finite_setOf_isRoot hp theorem eq_of_infinite_eval_eq (p q : R[X]) (h : Set.Infinite { x | eval x p = eval x q }) : p = q := by rw [← sub_eq_zero] apply eq_zero_of_infinite_isRoot simpa only [IsRoot, eval_sub, sub_eq_zero] theorem roots_mul {p q : R[X]} (hpq : p * q ≠ 0) : (p * q).roots = p.roots + q.roots := by classical exact Multiset.ext.mpr fun r => by rw [count_add, count_roots, count_roots, count_roots, rootMultiplicity_mul hpq] theorem roots.le_of_dvd (h : q ≠ 0) : p ∣ q → roots p ≤ roots q := by rintro ⟨k, rfl⟩ exact Multiset.le_iff_exists_add.mpr ⟨k.roots, roots_mul h⟩ theorem mem_roots_sub_C' {p : R[X]} {a x : R} : x ∈ (p - C a).roots ↔ p ≠ C a ∧ p.eval x = a := by rw [mem_roots', IsRoot.def, sub_ne_zero, eval_sub, sub_eq_zero, eval_C] theorem mem_roots_sub_C {p : R[X]} {a x : R} (hp0 : 0 < degree p) : x ∈ (p - C a).roots ↔ p.eval x = a := mem_roots_sub_C'.trans <| and_iff_right fun hp => hp0.not_le <| hp.symm ▸ degree_C_le @[simp] theorem roots_X_sub_C (r : R) : roots (X - C r) = {r} := by classical ext s rw [count_roots, rootMultiplicity_X_sub_C, count_singleton] @[simp] theorem roots_X_add_C (r : R) : roots (X + C r) = {-r} := by simpa using roots_X_sub_C (-r) @[simp] theorem roots_X : roots (X : R[X]) = {0} := by rw [← roots_X_sub_C, C_0, sub_zero] @[simp] theorem roots_C (x : R) : (C x).roots = 0 := by classical exact if H : x = 0 then by rw [H, C_0, roots_zero] else Multiset.ext.mpr fun r => (by rw [count_roots, count_zero, rootMultiplicity_eq_zero (not_isRoot_C _ _ H)]) @[simp] theorem roots_one : (1 : R[X]).roots = ∅ := roots_C 1 @[simp] theorem roots_C_mul (p : R[X]) (ha : a ≠ 0) : (C a * p).roots = p.roots := by by_cases hp : p = 0 <;> simp only [roots_mul, *, Ne, mul_eq_zero, C_eq_zero, or_self_iff, not_false_iff, roots_C, zero_add, mul_zero] @[simp] theorem roots_smul_nonzero (p : R[X]) (ha : a ≠ 0) : (a • p).roots = p.roots := by rw [smul_eq_C_mul, roots_C_mul _ ha] @[simp] lemma roots_neg (p : R[X]) : (-p).roots = p.roots := by rw [← neg_one_smul R p, roots_smul_nonzero p (neg_ne_zero.mpr one_ne_zero)] @[simp] theorem roots_C_mul_X_sub_C_of_IsUnit (b : R) (a : Rˣ) : (C (a : R) * X - C b).roots = {a⁻¹ * b} := by rw [← roots_C_mul _ (Units.ne_zero a⁻¹), mul_sub, ← mul_assoc, ← C_mul, ← C_mul, Units.inv_mul, C_1, one_mul] exact roots_X_sub_C (a⁻¹ * b) @[simp] theorem roots_C_mul_X_add_C_of_IsUnit (b : R) (a : Rˣ) : (C (a : R) * X + C b).roots = {-(a⁻¹ * b)} := by rw [← sub_neg_eq_add, ← C_neg, roots_C_mul_X_sub_C_of_IsUnit, mul_neg] theorem roots_list_prod (L : List R[X]) : (0 : R[X]) ∉ L → L.prod.roots = (L : Multiset R[X]).bind roots := List.recOn L (fun _ => roots_one) fun hd tl ih H => by rw [List.mem_cons, not_or] at H rw [List.prod_cons, roots_mul (mul_ne_zero (Ne.symm H.1) <| List.prod_ne_zero H.2), ← Multiset.cons_coe, Multiset.cons_bind, ih H.2] theorem roots_multiset_prod (m : Multiset R[X]) : (0 : R[X]) ∉ m → m.prod.roots = m.bind roots := by rcases m with ⟨L⟩ simpa only [Multiset.prod_coe, quot_mk_to_coe''] using roots_list_prod L theorem roots_prod {ι : Type*} (f : ι → R[X]) (s : Finset ι) : s.prod f ≠ 0 → (s.prod f).roots = s.val.bind fun i => roots (f i) := by rcases s with ⟨m, hm⟩ simpa [Multiset.prod_eq_zero_iff, Multiset.bind_map] using roots_multiset_prod (m.map f) @[simp] theorem roots_pow (p : R[X]) (n : ℕ) : (p ^ n).roots = n • p.roots := by induction n with | zero => rw [pow_zero, roots_one, zero_smul, empty_eq_zero] | succ n ihn => rcases eq_or_ne p 0 with (rfl | hp) · rw [zero_pow n.succ_ne_zero, roots_zero, smul_zero] · rw [pow_succ, roots_mul (mul_ne_zero (pow_ne_zero _ hp) hp), ihn, add_smul, one_smul] theorem roots_X_pow (n : ℕ) : (X ^ n : R[X]).roots = n • ({0} : Multiset R) := by rw [roots_pow, roots_X] theorem roots_C_mul_X_pow (ha : a ≠ 0) (n : ℕ) : Polynomial.roots (C a * X ^ n) = n • ({0} : Multiset R) := by rw [roots_C_mul _ ha, roots_X_pow] @[simp] theorem roots_monomial (ha : a ≠ 0) (n : ℕ) : (monomial n a).roots = n • ({0} : Multiset R) := by rw [← C_mul_X_pow_eq_monomial, roots_C_mul_X_pow ha] theorem roots_prod_X_sub_C (s : Finset R) : (s.prod fun a => X - C a).roots = s.val := by apply (roots_prod (fun a => X - C a) s ?_).trans · simp_rw [roots_X_sub_C] rw [Multiset.bind_singleton, Multiset.map_id'] · refine prod_ne_zero_iff.mpr (fun a _ => X_sub_C_ne_zero a) @[simp] theorem roots_multiset_prod_X_sub_C (s : Multiset R) : (s.map fun a => X - C a).prod.roots = s := by rw [roots_multiset_prod, Multiset.bind_map] · simp_rw [roots_X_sub_C] rw [Multiset.bind_singleton, Multiset.map_id'] · rw [Multiset.mem_map] rintro ⟨a, -, h⟩ exact X_sub_C_ne_zero a h theorem card_roots_X_pow_sub_C {n : ℕ} (hn : 0 < n) (a : R) : Multiset.card (roots ((X : R[X]) ^ n - C a)) ≤ n := WithBot.coe_le_coe.1 <| calc (Multiset.card (roots ((X : R[X]) ^ n - C a)) : WithBot ℕ) ≤ degree ((X : R[X]) ^ n - C a) := card_roots (X_pow_sub_C_ne_zero hn a) _ = n := degree_X_pow_sub_C hn a section NthRoots /-- `nthRoots n a` noncomputably returns the solutions to `x ^ n = a`. -/ def nthRoots (n : ℕ) (a : R) : Multiset R := roots ((X : R[X]) ^ n - C a) @[simp] theorem mem_nthRoots {n : ℕ} (hn : 0 < n) {a x : R} : x ∈ nthRoots n a ↔ x ^ n = a := by rw [nthRoots, mem_roots (X_pow_sub_C_ne_zero hn a), IsRoot.def, eval_sub, eval_C, eval_pow, eval_X, sub_eq_zero] @[simp] theorem nthRoots_zero (r : R) : nthRoots 0 r = 0 := by simp only [empty_eq_zero, pow_zero, nthRoots, ← C_1, ← C_sub, roots_C] @[simp] theorem nthRoots_zero_right {R} [CommRing R] [IsDomain R] (n : ℕ) : nthRoots n (0 : R) = Multiset.replicate n 0 := by rw [nthRoots, C.map_zero, sub_zero, roots_pow, roots_X, Multiset.nsmul_singleton] theorem card_nthRoots (n : ℕ) (a : R) : Multiset.card (nthRoots n a) ≤ n := by classical exact (if hn : n = 0 then if h : (X : R[X]) ^ n - C a = 0 then by simp [Nat.zero_le, nthRoots, roots, h, dif_pos rfl, empty_eq_zero, Multiset.card_zero] else WithBot.coe_le_coe.1 (le_trans (card_roots h) (by rw [hn, pow_zero, ← C_1, ← RingHom.map_sub] exact degree_C_le)) else by rw [← Nat.cast_le (α := WithBot ℕ)] rw [← degree_X_pow_sub_C (Nat.pos_of_ne_zero hn) a] exact card_roots (X_pow_sub_C_ne_zero (Nat.pos_of_ne_zero hn) a)) @[simp] theorem nthRoots_two_eq_zero_iff {r : R} : nthRoots 2 r = 0 ↔ ¬IsSquare r := by simp_rw [isSquare_iff_exists_sq, eq_zero_iff_forall_not_mem, mem_nthRoots (by norm_num : 0 < 2), ← not_exists, eq_comm] /-- The multiset `nthRoots ↑n a` as a Finset. Previously `nthRootsFinset n` was defined to be `nthRoots n (1 : R)` as a Finset. That situation can be recovered by setting `a` to be `(1 : R)` -/ def nthRootsFinset (n : ℕ) {R : Type*} (a : R) [CommRing R] [IsDomain R] : Finset R := haveI := Classical.decEq R Multiset.toFinset (nthRoots n a) lemma nthRootsFinset_def (n : ℕ) {R : Type*} (a : R) [CommRing R] [IsDomain R] [DecidableEq R] : nthRootsFinset n a = Multiset.toFinset (nthRoots n a) := by unfold nthRootsFinset convert rfl @[simp] theorem mem_nthRootsFinset {n : ℕ} (h : 0 < n) (a : R) {x : R} : x ∈ nthRootsFinset n a ↔ x ^ (n : ℕ) = a := by classical rw [nthRootsFinset_def, mem_toFinset, mem_nthRoots h] @[simp] theorem nthRootsFinset_zero (a : R) : nthRootsFinset 0 a = ∅ := by classical simp [nthRootsFinset_def] theorem map_mem_nthRootsFinset {S F : Type*} [CommRing S] [IsDomain S] [FunLike F R S] [MonoidHomClass F R S] {a : R} {x : R} (hx : x ∈ nthRootsFinset n a) (f : F) : f x ∈ nthRootsFinset n (f a) := by by_cases hn : n = 0 · simp [hn] at hx · rw [mem_nthRootsFinset <| Nat.pos_of_ne_zero hn, ← map_pow, (mem_nthRootsFinset (Nat.pos_of_ne_zero hn) a).1 hx] theorem map_mem_nthRootsFinset_one {S F : Type*} [CommRing S] [IsDomain S] [FunLike F R S] [RingHomClass F R S] {x : R} (hx : x ∈ nthRootsFinset n 1) (f : F) : f x ∈ nthRootsFinset n 1 := by rw [← (map_one f)] exact map_mem_nthRootsFinset hx _ theorem mul_mem_nthRootsFinset {η₁ η₂ : R} {a₁ a₂ : R} (hη₁ : η₁ ∈ nthRootsFinset n a₁) (hη₂ : η₂ ∈ nthRootsFinset n a₂) : η₁ * η₂ ∈ nthRootsFinset n (a₁ * a₂) := by cases n with | zero => simp only [nthRootsFinset_zero, not_mem_empty] at hη₁ | succ n => rw [mem_nthRootsFinset n.succ_pos] at hη₁ hη₂ ⊢ rw [mul_pow, hη₁, hη₂] theorem ne_zero_of_mem_nthRootsFinset {η : R} {a : R} (ha : a ≠ 0) (hη : η ∈ nthRootsFinset n a) : η ≠ 0 := by nontriviality R rintro rfl cases n with | zero => simp only [nthRootsFinset_zero, not_mem_empty] at hη | succ n => rw [mem_nthRootsFinset n.succ_pos, zero_pow n.succ_ne_zero] at hη exact ha hη.symm theorem one_mem_nthRootsFinset (hn : 0 < n) : 1 ∈ nthRootsFinset n (1 : R) := by rw [mem_nthRootsFinset hn, one_pow] end NthRoots theorem zero_of_eval_zero [Infinite R] (p : R[X]) (h : ∀ x, p.eval x = 0) : p = 0 := by classical by_contra hp refine @Fintype.false R _ ?_ exact ⟨p.roots.toFinset, fun x => Multiset.mem_toFinset.mpr ((mem_roots hp).mpr (h _))⟩ theorem funext [Infinite R] {p q : R[X]} (ext : ∀ r : R, p.eval r = q.eval r) : p = q := by rw [← sub_eq_zero] apply zero_of_eval_zero intro x rw [eval_sub, sub_eq_zero, ext] variable [CommRing T] /-- Given a polynomial `p` with coefficients in a ring `T` and a `T`-algebra `S`, `aroots p S` is the multiset of roots of `p` regarded as a polynomial over `S`. -/ noncomputable abbrev aroots (p : T[X]) (S) [CommRing S] [IsDomain S] [Algebra T S] : Multiset S := (p.map (algebraMap T S)).roots theorem aroots_def (p : T[X]) (S) [CommRing S] [IsDomain S] [Algebra T S] : p.aroots S = (p.map (algebraMap T S)).roots := rfl theorem mem_aroots' [CommRing S] [IsDomain S] [Algebra T S] {p : T[X]} {a : S} : a ∈ p.aroots S ↔ p.map (algebraMap T S) ≠ 0 ∧ aeval a p = 0 := by rw [mem_roots', IsRoot.def, ← eval₂_eq_eval_map, aeval_def] theorem mem_aroots [CommRing S] [IsDomain S] [Algebra T S] [NoZeroSMulDivisors T S] {p : T[X]} {a : S} : a ∈ p.aroots S ↔ p ≠ 0 ∧ aeval a p = 0 := by rw [mem_aroots', Polynomial.map_ne_zero_iff] exact FaithfulSMul.algebraMap_injective T S theorem aroots_mul [CommRing S] [IsDomain S] [Algebra T S] [NoZeroSMulDivisors T S] {p q : T[X]} (hpq : p * q ≠ 0) : (p * q).aroots S = p.aroots S + q.aroots S := by suffices map (algebraMap T S) p * map (algebraMap T S) q ≠ 0 by rw [aroots_def, Polynomial.map_mul, roots_mul this] rwa [← Polynomial.map_mul, Polynomial.map_ne_zero_iff (FaithfulSMul.algebraMap_injective T S)] @[simp] theorem aroots_X_sub_C [CommRing S] [IsDomain S] [Algebra T S] (r : T) : aroots (X - C r) S = {algebraMap T S r} := by rw [aroots_def, Polynomial.map_sub, map_X, map_C, roots_X_sub_C] @[simp] theorem aroots_X [CommRing S] [IsDomain S] [Algebra T S] : aroots (X : T[X]) S = {0} := by rw [aroots_def, map_X, roots_X] @[simp] theorem aroots_C [CommRing S] [IsDomain S] [Algebra T S] (a : T) : (C a).aroots S = 0 := by rw [aroots_def, map_C, roots_C] @[simp] theorem aroots_zero (S) [CommRing S] [IsDomain S] [Algebra T S] : (0 : T[X]).aroots S = 0 := by rw [← C_0, aroots_C] @[simp] theorem aroots_one [CommRing S] [IsDomain S] [Algebra T S] : (1 : T[X]).aroots S = 0 := aroots_C 1 @[simp]
theorem aroots_neg [CommRing S] [IsDomain S] [Algebra T S] (p : T[X]) : (-p).aroots S = p.aroots S := by rw [aroots, Polynomial.map_neg, roots_neg]
Mathlib/Algebra/Polynomial/Roots.lean
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/- Copyright (c) 2023 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies -/ import Mathlib.Algebra.Order.Monovary import Mathlib.Algebra.Order.Ring.Basic import Mathlib.Analysis.Convex.Function import Mathlib.Tactic.FieldSimp /-! # Product of convex functions This file proves that the product of convex functions is convex, provided they monovary. As corollaries, we also prove that `x ↦ x ^ n` is convex * `Even.convexOn_pow`: for even `n : ℕ`. * `convexOn_pow`: over $[0, +∞)$ for `n : ℕ`. * `convexOn_zpow`: over $(0, +∞)$ For `n : ℤ`. -/ open Set variable {𝕜 E F : Type*} section LinearOrderedCommRing variable [CommRing 𝕜] [LinearOrder 𝕜] [IsStrictOrderedRing 𝕜] [CommRing E] [LinearOrder E] [IsStrictOrderedRing E] [AddCommGroup F] [LinearOrder F] [IsOrderedAddMonoid F] [Module 𝕜 E] [Module 𝕜 F] [Module E F] [IsScalarTower 𝕜 E F] [SMulCommClass 𝕜 E F] [OrderedSMul 𝕜 F] [OrderedSMul E F] {s : Set 𝕜} {f : 𝕜 → E} {g : 𝕜 → F} lemma ConvexOn.smul' (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) (hf₀ : ∀ ⦃x⦄, x ∈ s → 0 ≤ f x) (hg₀ : ∀ ⦃x⦄, x ∈ s → 0 ≤ g x) (hfg : MonovaryOn f g s) : ConvexOn 𝕜 s (f • g) := by refine ⟨hf.1, fun x hx y hy a b ha hb hab ↦ ?_⟩ dsimp refine (smul_le_smul (hf.2 hx hy ha hb hab) (hg.2 hx hy ha hb hab) (hf₀ <| hf.1 hx hy ha hb hab) <| add_nonneg (smul_nonneg ha <| hg₀ hx) <| smul_nonneg hb <| hg₀ hy).trans ?_ calc _ = (a * a) • (f x • g x) + (b * b) • (f y • g y) + (a * b) • (f x • g y + f y • g x) := ?_ _ ≤ (a * a) • (f x • g x) + (b * b) • (f y • g y) + (a * b) • (f x • g x + f y • g y) := by gcongr _ + (a * b) • ?_; exact hfg.smul_add_smul_le_smul_add_smul hx hy _ = (a * (a + b)) • (f x • g x) + (b * (a + b)) • (f y • g y) := by simp only [mul_add, add_smul, smul_add, mul_comm _ a]; abel _ = _ := by simp_rw [hab, mul_one] simp only [mul_add, add_smul, smul_add] rw [← smul_smul_smul_comm a, ← smul_smul_smul_comm b, ← smul_smul_smul_comm a b, ← smul_smul_smul_comm b b, smul_eq_mul, smul_eq_mul, smul_eq_mul, smul_eq_mul, mul_comm b, add_comm _ ((b * b) • f y • g y), add_add_add_comm, add_comm ((a * b) • f y • g x)] lemma ConcaveOn.smul' [OrderedSMul 𝕜 E] (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) (hf₀ : ∀ ⦃x⦄, x ∈ s → 0 ≤ f x) (hg₀ : ∀ ⦃x⦄, x ∈ s → 0 ≤ g x) (hfg : AntivaryOn f g s) : ConcaveOn 𝕜 s (f • g) := by refine ⟨hf.1, fun x hx y hy a b ha hb hab ↦ ?_⟩ dsimp refine (smul_le_smul (hf.2 hx hy ha hb hab) (hg.2 hx hy ha hb hab) (add_nonneg (smul_nonneg ha <| hf₀ hx) <| smul_nonneg hb <| hf₀ hy) (hg₀ <| hf.1 hx hy ha hb hab)).trans' ?_ calc a • f x • g x + b • f y • g y = (a * (a + b)) • (f x • g x) + (b * (a + b)) • (f y • g y) := by simp_rw [hab, mul_one] _ = (a * a) • (f x • g x) + (b * b) • (f y • g y) + (a * b) • (f x • g x + f y • g y) := by simp only [mul_add, add_smul, smul_add, mul_comm _ a]; abel _ ≤ (a * a) • (f x • g x) + (b * b) • (f y • g y) + (a * b) • (f x • g y + f y • g x) := by gcongr _ + (a * b) • ?_; exact hfg.smul_add_smul_le_smul_add_smul hx hy _ = _ := ?_ simp only [mul_add, add_smul, smul_add] rw [← smul_smul_smul_comm a, ← smul_smul_smul_comm b, ← smul_smul_smul_comm a b, ← smul_smul_smul_comm b b, smul_eq_mul, smul_eq_mul, smul_eq_mul, smul_eq_mul, mul_comm b a, add_comm ((a * b) • f x • g y), add_comm ((a * b) • f x • g y), add_add_add_comm] lemma ConvexOn.smul'' [OrderedSMul 𝕜 E] (hf : ConvexOn 𝕜 s f) (hg : ConvexOn 𝕜 s g) (hf₀ : ∀ ⦃x⦄, x ∈ s → f x ≤ 0) (hg₀ : ∀ ⦃x⦄, x ∈ s → g x ≤ 0) (hfg : AntivaryOn f g s) : ConcaveOn 𝕜 s (f • g) := by rw [← neg_smul_neg] exact hf.neg.smul' hg.neg (fun x hx ↦ neg_nonneg.2 <| hf₀ hx) (fun x hx ↦ neg_nonneg.2 <| hg₀ hx) hfg.neg lemma ConcaveOn.smul'' (hf : ConcaveOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) (hf₀ : ∀ ⦃x⦄, x ∈ s → f x ≤ 0) (hg₀ : ∀ ⦃x⦄, x ∈ s → g x ≤ 0) (hfg : MonovaryOn f g s) : ConvexOn 𝕜 s (f • g) := by rw [← neg_smul_neg] exact hf.neg.smul' hg.neg (fun x hx ↦ neg_nonneg.2 <| hf₀ hx) (fun x hx ↦ neg_nonneg.2 <| hg₀ hx) hfg.neg lemma ConvexOn.smul_concaveOn (hf : ConvexOn 𝕜 s f) (hg : ConcaveOn 𝕜 s g) (hf₀ : ∀ ⦃x⦄, x ∈ s → 0 ≤ f x) (hg₀ : ∀ ⦃x⦄, x ∈ s → g x ≤ 0) (hfg : AntivaryOn f g s) :
ConcaveOn 𝕜 s (f • g) := by rw [← neg_convexOn_iff, ← smul_neg] exact hf.smul' hg.neg hf₀ (fun x hx ↦ neg_nonneg.2 <| hg₀ hx) hfg.neg_right lemma ConcaveOn.smul_convexOn [OrderedSMul 𝕜 E] (hf : ConcaveOn 𝕜 s f) (hg : ConvexOn 𝕜 s g)
Mathlib/Analysis/Convex/Mul.lean
87
91
/- Copyright (c) 2023 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov, Joseph Myers -/ import Mathlib.Analysis.InnerProductSpace.Orthogonal import Mathlib.Analysis.Normed.Group.AddTorsor /-! # Perpendicular bisector of a segment We define `AffineSubspace.perpBisector p₁ p₂` to be the perpendicular bisector of the segment `[p₁, p₂]`, as a bundled affine subspace. We also prove that a point belongs to the perpendicular bisector if and only if it is equidistant from `p₁` and `p₂`, as well as a few linear equations that define this subspace. ## Keywords euclidean geometry, perpendicular, perpendicular bisector, line segment bisector, equidistant -/ open Set open scoped RealInnerProductSpace variable {V P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P] variable [NormedAddTorsor V P] noncomputable section namespace AffineSubspace variable {c p₁ p₂ : P} /-- Perpendicular bisector of a segment in a Euclidean affine space. -/ def perpBisector (p₁ p₂ : P) : AffineSubspace ℝ P := mk' (midpoint ℝ p₁ p₂) (LinearMap.ker (innerₛₗ ℝ (p₂ -ᵥ p₁))) /-- A point `c` belongs the perpendicular bisector of `[p₁, p₂] iff `p₂ -ᵥ p₁` is orthogonal to `c -ᵥ midpoint ℝ p₁ p₂`. -/ theorem mem_perpBisector_iff_inner_eq_zero' : c ∈ perpBisector p₁ p₂ ↔ ⟪p₂ -ᵥ p₁, c -ᵥ midpoint ℝ p₁ p₂⟫ = 0 := Iff.rfl /-- A point `c` belongs the perpendicular bisector of `[p₁, p₂] iff `c -ᵥ midpoint ℝ p₁ p₂` is orthogonal to `p₂ -ᵥ p₁`. -/ theorem mem_perpBisector_iff_inner_eq_zero : c ∈ perpBisector p₁ p₂ ↔ ⟪c -ᵥ midpoint ℝ p₁ p₂, p₂ -ᵥ p₁⟫ = 0 := inner_eq_zero_symm theorem mem_perpBisector_iff_inner_pointReflection_vsub_eq_zero : c ∈ perpBisector p₁ p₂ ↔ ⟪Equiv.pointReflection c p₁ -ᵥ p₂, p₂ -ᵥ p₁⟫ = 0 := by rw [mem_perpBisector_iff_inner_eq_zero, Equiv.pointReflection_apply, vsub_midpoint, invOf_eq_inv, ← smul_add, real_inner_smul_left, vadd_vsub_assoc] simp theorem mem_perpBisector_pointReflection_iff_inner_eq_zero : c ∈ perpBisector p₁ (Equiv.pointReflection p₂ p₁) ↔ ⟪c -ᵥ p₂, p₁ -ᵥ p₂⟫ = 0 := by rw [mem_perpBisector_iff_inner_eq_zero, midpoint_pointReflection_right, Equiv.pointReflection_apply, vadd_vsub_assoc, inner_add_right, add_self_eq_zero, ← neg_eq_zero, ← inner_neg_right, neg_vsub_eq_vsub_rev] theorem midpoint_mem_perpBisector (p₁ p₂ : P) : midpoint ℝ p₁ p₂ ∈ perpBisector p₁ p₂ := by simp [mem_perpBisector_iff_inner_eq_zero] theorem perpBisector_nonempty : (perpBisector p₁ p₂ : Set P).Nonempty := ⟨_, midpoint_mem_perpBisector _ _⟩ @[simp] theorem direction_perpBisector (p₁ p₂ : P) : (perpBisector p₁ p₂).direction = (ℝ ∙ (p₂ -ᵥ p₁))ᗮ := by rw [perpBisector, direction_mk'] ext x exact Submodule.mem_orthogonal_singleton_iff_inner_right.symm theorem mem_perpBisector_iff_inner_eq_inner : c ∈ perpBisector p₁ p₂ ↔ ⟪c -ᵥ p₁, p₂ -ᵥ p₁⟫ = ⟪c -ᵥ p₂, p₁ -ᵥ p₂⟫ := by rw [Iff.comm, mem_perpBisector_iff_inner_eq_zero, ← add_neg_eq_zero, ← inner_neg_right, neg_vsub_eq_vsub_rev, ← inner_add_left, vsub_midpoint, invOf_eq_inv, ← smul_add, real_inner_smul_left]; simp theorem mem_perpBisector_iff_inner_eq : c ∈ perpBisector p₁ p₂ ↔ ⟪c -ᵥ p₁, p₂ -ᵥ p₁⟫ = (dist p₁ p₂) ^ 2 / 2 := by rw [mem_perpBisector_iff_inner_eq_zero, ← vsub_sub_vsub_cancel_right _ _ p₁, inner_sub_left, sub_eq_zero, midpoint_vsub_left, invOf_eq_inv, real_inner_smul_left, real_inner_self_eq_norm_sq, dist_eq_norm_vsub' V, div_eq_inv_mul] theorem mem_perpBisector_iff_dist_eq : c ∈ perpBisector p₁ p₂ ↔ dist c p₁ = dist c p₂ := by rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← real_inner_add_sub_eq_zero_iff, vsub_sub_vsub_cancel_left, inner_add_left, add_eq_zero_iff_eq_neg, ← inner_neg_right, neg_vsub_eq_vsub_rev, mem_perpBisector_iff_inner_eq_inner] theorem mem_perpBisector_iff_dist_eq' : c ∈ perpBisector p₁ p₂ ↔ dist p₁ c = dist p₂ c := by simp only [mem_perpBisector_iff_dist_eq, dist_comm] theorem perpBisector_comm (p₁ p₂ : P) : perpBisector p₁ p₂ = perpBisector p₂ p₁ := by ext c; simp only [mem_perpBisector_iff_dist_eq, eq_comm] @[simp] theorem right_mem_perpBisector : p₂ ∈ perpBisector p₁ p₂ ↔ p₁ = p₂ := by simpa [mem_perpBisector_iff_inner_eq_inner] using eq_comm @[simp] theorem left_mem_perpBisector : p₁ ∈ perpBisector p₁ p₂ ↔ p₁ = p₂ := by rw [perpBisector_comm, right_mem_perpBisector, eq_comm] @[simp] theorem perpBisector_self (p : P) : perpBisector p p = ⊤ := top_unique fun _ ↦ by simp [mem_perpBisector_iff_inner_eq_inner] @[simp] theorem perpBisector_eq_top : perpBisector p₁ p₂ = ⊤ ↔ p₁ = p₂ := by refine ⟨fun h ↦ ?_, fun h ↦ h ▸ perpBisector_self _⟩ rw [← left_mem_perpBisector, h] trivial @[simp] theorem perpBisector_ne_bot : perpBisector p₁ p₂ ≠ ⊥ := by rw [← nonempty_iff_ne_bot]; exact perpBisector_nonempty end AffineSubspace open AffineSubspace namespace EuclideanGeometry /-- Suppose that `c₁` is equidistant from `p₁` and `p₂`, and the same applies to `c₂`. Then the vector between `c₁` and `c₂` is orthogonal to that between `p₁` and `p₂`. (In two dimensions, this says that the diagonals of a kite are orthogonal.) -/ theorem inner_vsub_vsub_of_dist_eq_of_dist_eq {c₁ c₂ p₁ p₂ : P} (hc₁ : dist p₁ c₁ = dist p₂ c₁) (hc₂ : dist p₁ c₂ = dist p₂ c₂) : ⟪c₂ -ᵥ c₁, p₂ -ᵥ p₁⟫ = 0 := by rw [← Submodule.mem_orthogonal_singleton_iff_inner_left, ← direction_perpBisector] apply vsub_mem_direction <;> rwa [mem_perpBisector_iff_dist_eq']
end EuclideanGeometry variable {V' P' : Type*} [NormedAddCommGroup V'] [InnerProductSpace ℝ V'] [MetricSpace P']
Mathlib/Geometry/Euclidean/PerpBisector.lean
129
132
/- Copyright (c) 2024 Joël Riou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joël Riou -/ import Mathlib.Algebra.Category.ModuleCat.Presheaf.Limits import Mathlib.Algebra.Category.ModuleCat.Sheaf import Mathlib.CategoryTheory.Sites.Limits /-! # Limits in categories of sheaves of modules In this file, it is shown that under suitable assumptions, limits exist in the category `SheafOfModules R`. ## TODO * do the same for colimits (which requires constructing the associated sheaf of modules functor) -/ universe v v₁ v₂ u₁ u₂ u open CategoryTheory Category Limits variable {C : Type u₁} [Category.{v₁} C] {J : GrothendieckTopology C} {D : Type u₂} [Category.{v₂} D] namespace PresheafOfModules variable {R : Cᵒᵖ ⥤ RingCat.{u}} {F : D ⥤ PresheafOfModules.{v} R} [∀ X, Small.{v} ((F ⋙ evaluation R X) ⋙ forget _).sections] {c : Cone F} [HasLimitsOfShape D AddCommGrp.{v}] lemma isSheaf_of_isLimit (hc : IsLimit c) (hF : ∀ j, Presheaf.IsSheaf J (F.obj j).presheaf) :
Presheaf.IsSheaf J (c.pt.presheaf) := by let G : D ⥤ Sheaf J AddCommGrp.{v} := { obj := fun j => ⟨(F.obj j).presheaf, hF j⟩ map := fun φ => ⟨(PresheafOfModules.toPresheaf R).map (F.map φ)⟩ } exact Sheaf.isSheaf_of_isLimit G _ (isLimitOfPreserves (toPresheaf R) hc)
Mathlib/Algebra/Category/ModuleCat/Sheaf/Limits.lean
37
41
/- 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 :=
Mathlib/Topology/Algebra/InfiniteSum/Basic.lean
569
572
/- Copyright (c) 2022 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash -/ import Mathlib.Analysis.Normed.Group.Quotient import Mathlib.Analysis.NormedSpace.Pointwise import Mathlib.Topology.Instances.AddCircle /-! # The additive circle as a normed group We define the normed group structure on `AddCircle p`, for `p : ℝ`. For example if `p = 1` then: `‖(x : AddCircle 1)‖ = |x - round x|` for any `x : ℝ` (see `UnitAddCircle.norm_eq`). ## Main definitions: * `AddCircle.norm_eq`: a characterisation of the norm on `AddCircle p` ## TODO * The fact `InnerProductGeometry.angle (Real.cos θ) (Real.sin θ) = ‖(θ : Real.Angle)‖` -/ noncomputable section open Metric QuotientAddGroup Set open Int hiding mem_zmultiples_iff open AddSubgroup namespace AddCircle variable (p : ℝ) instance : NormedAddCommGroup (AddCircle p) := QuotientAddGroup.instNormedAddCommGroup _ @[simp] theorem norm_coe_mul (x : ℝ) (t : ℝ) : ‖(↑(t * x) : AddCircle (t * p))‖ = |t| * ‖(x : AddCircle p)‖ := by obtain rfl | ht := eq_or_ne t 0 · simp simp only [norm_eq_infDist, Real.norm_eq_abs, ← Real.norm_eq_abs, ← infDist_smul₀ ht, smul_zero] congr with m simp only [zmultiples, eq_iff_sub_mem, zsmul_eq_mul, mem_mk, mem_setOf_eq, mem_smul_set_iff_inv_smul_mem₀ ht, smul_eq_mul] simp_rw [mul_left_comm, ← smul_eq_mul, Set.range_smul, mem_smul_set_iff_inv_smul_mem₀ ht] simp [mul_sub, ht, -mem_range] theorem norm_neg_period (x : ℝ) : ‖(x : AddCircle (-p))‖ = ‖(x : AddCircle p)‖ := by suffices ‖(↑(-1 * x) : AddCircle (-1 * p))‖ = ‖(x : AddCircle p)‖ by rw [← this, neg_one_mul] simp simp only [norm_coe_mul, abs_neg, abs_one, one_mul] @[simp] theorem norm_eq_of_zero {x : ℝ} : ‖(x : AddCircle (0 : ℝ))‖ = |x| := by suffices { y : ℝ | (y : AddCircle (0 : ℝ)) = (x : AddCircle (0 : ℝ)) } = {x} by simp [norm_eq_infDist, this] ext y simp [eq_iff_sub_mem, mem_zmultiples_iff, sub_eq_zero] theorem norm_eq {x : ℝ} : ‖(x : AddCircle p)‖ = |x - round (p⁻¹ * x) * p| := by suffices ∀ x : ℝ, ‖(x : AddCircle (1 : ℝ))‖ = |x - round x| by rcases eq_or_ne p 0 with (rfl | hp) · simp have hx := norm_coe_mul p x p⁻¹
rw [abs_inv, eq_inv_mul_iff_mul_eq₀ ((not_congr abs_eq_zero).mpr hp)] at hx rw [← hx, inv_mul_cancel₀ hp, this, ← abs_mul, mul_sub, mul_inv_cancel_left₀ hp, mul_comm p] clear! x p intros x simp only [le_antisymm_iff, le_norm_iff, Real.norm_eq_abs]
Mathlib/Analysis/Normed/Group/AddCircle.lean
71
75
/- Copyright (c) 2020 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov -/ import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap import Mathlib.MeasureTheory.Integral.Bochner.FundThmCalculus import Mathlib.MeasureTheory.Integral.Bochner.Set deprecated_module (since := "2025-04-15")
Mathlib/MeasureTheory/Integral/SetIntegral.lean
1,373
1,378
/- 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 :=
Mathlib/Order/WellFoundedSet.lean
784
790
/- Copyright (c) 2019 Gabriel Ebner. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Gabriel Ebner, Sébastien Gouëzel, Yury Kudryashov, Anatole Dedecker -/ import Mathlib.Analysis.Calculus.Deriv.Basic import Mathlib.Analysis.Calculus.FDeriv.Add /-! # One-dimensional derivatives of sums etc In this file we prove formulas about derivatives of `f + g`, `-f`, `f - g`, and `∑ i, f i x` for functions from the base field to a normed space over this field. For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of `Analysis/Calculus/Deriv/Basic`. ## Keywords derivative -/ universe u v w open scoped Topology Filter ENNReal open Asymptotics Set variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F] variable {f g : 𝕜 → F} variable {f' g' : F} variable {x : 𝕜} {s : Set 𝕜} {L : Filter 𝕜} section Add /-! ### Derivative of the sum of two functions -/ nonrec theorem HasDerivAtFilter.add (hf : HasDerivAtFilter f f' x L) (hg : HasDerivAtFilter g g' x L) : HasDerivAtFilter (fun y => f y + g y) (f' + g') x L := by simpa using (hf.add hg).hasDerivAtFilter nonrec theorem HasStrictDerivAt.add (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x) : HasStrictDerivAt (fun y => f y + g y) (f' + g') x := by simpa using (hf.add hg).hasStrictDerivAt nonrec theorem HasDerivWithinAt.add (hf : HasDerivWithinAt f f' s x) (hg : HasDerivWithinAt g g' s x) : HasDerivWithinAt (fun y => f y + g y) (f' + g') s x := hf.add hg nonrec theorem HasDerivAt.add (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) : HasDerivAt (fun x => f x + g x) (f' + g') x := hf.add hg theorem derivWithin_add (hf : DifferentiableWithinAt 𝕜 f s x) (hg : DifferentiableWithinAt 𝕜 g s x) : derivWithin (fun y => f y + g y) s x = derivWithin f s x + derivWithin g s x := by by_cases hsx : UniqueDiffWithinAt 𝕜 s x · exact (hf.hasDerivWithinAt.add hg.hasDerivWithinAt).derivWithin hsx · simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx] @[simp] theorem deriv_add (hf : DifferentiableAt 𝕜 f x) (hg : DifferentiableAt 𝕜 g x) : deriv (fun y => f y + g y) x = deriv f x + deriv g x := (hf.hasDerivAt.add hg.hasDerivAt).deriv @[simp] theorem hasDerivAtFilter_add_const_iff (c : F) : HasDerivAtFilter (f · + c) f' x L ↔ HasDerivAtFilter f f' x L := hasFDerivAtFilter_add_const_iff c alias ⟨_, HasDerivAtFilter.add_const⟩ := hasDerivAtFilter_add_const_iff @[simp] theorem hasStrictDerivAt_add_const_iff (c : F) : HasStrictDerivAt (f · + c) f' x ↔ HasStrictDerivAt f f' x := hasStrictFDerivAt_add_const_iff c alias ⟨_, HasStrictDerivAt.add_const⟩ := hasStrictDerivAt_add_const_iff @[simp] theorem hasDerivWithinAt_add_const_iff (c : F) : HasDerivWithinAt (f · + c) f' s x ↔ HasDerivWithinAt f f' s x := hasDerivAtFilter_add_const_iff c alias ⟨_, HasDerivWithinAt.add_const⟩ := hasDerivWithinAt_add_const_iff @[simp] theorem hasDerivAt_add_const_iff (c : F) : HasDerivAt (f · + c) f' x ↔ HasDerivAt f f' x := hasDerivAtFilter_add_const_iff c alias ⟨_, HasDerivAt.add_const⟩ := hasDerivAt_add_const_iff theorem derivWithin_add_const (c : F) : derivWithin (fun y => f y + c) s x = derivWithin f s x := by simp only [derivWithin, fderivWithin_add_const] theorem deriv_add_const (c : F) : deriv (fun y => f y + c) x = deriv f x := by simp only [deriv, fderiv_add_const] @[simp] theorem deriv_add_const' (c : F) : (deriv fun y => f y + c) = deriv f := funext fun _ => deriv_add_const c theorem hasDerivAtFilter_const_add_iff (c : F) : HasDerivAtFilter (c + f ·) f' x L ↔ HasDerivAtFilter f f' x L := hasFDerivAtFilter_const_add_iff c alias ⟨_, HasDerivAtFilter.const_add⟩ := hasDerivAtFilter_const_add_iff @[simp] theorem hasStrictDerivAt_const_add_iff (c : F) : HasStrictDerivAt (c + f ·) f' x ↔ HasStrictDerivAt f f' x := hasStrictFDerivAt_const_add_iff c alias ⟨_, HasStrictDerivAt.const_add⟩ := hasStrictDerivAt_const_add_iff @[simp] theorem hasDerivWithinAt_const_add_iff (c : F) : HasDerivWithinAt (c + f ·) f' s x ↔ HasDerivWithinAt f f' s x := hasDerivAtFilter_const_add_iff c alias ⟨_, HasDerivWithinAt.const_add⟩ := hasDerivWithinAt_const_add_iff @[simp] theorem hasDerivAt_const_add_iff (c : F) : HasDerivAt (c + f ·) f' x ↔ HasDerivAt f f' x := hasDerivAtFilter_const_add_iff c alias ⟨_, HasDerivAt.const_add⟩ := hasDerivAt_const_add_iff theorem derivWithin_const_add (c : F) : derivWithin (c + f ·) s x = derivWithin f s x := by simp only [derivWithin, fderivWithin_const_add] @[simp] theorem derivWithin_const_add_fun (c : F) : derivWithin (c + f ·) = derivWithin f := by ext apply derivWithin_const_add theorem deriv_const_add (c : F) : deriv (c + f ·) x = deriv f x := by simp only [deriv, fderiv_const_add] @[simp] theorem deriv_const_add' (c : F) : (deriv (c + f ·)) = deriv f := funext fun _ => deriv_const_add c lemma differentiableAt_comp_const_add {a b : 𝕜} : DifferentiableAt 𝕜 (fun x ↦ f (b + x)) a ↔ DifferentiableAt 𝕜 f (b + a) := by refine ⟨fun H ↦ ?_, fun H ↦ H.comp _ (differentiable_id.const_add _).differentiableAt⟩
convert DifferentiableAt.comp (b + a) (by simpa) (differentiable_id.const_add (-b)).differentiableAt ext
Mathlib/Analysis/Calculus/Deriv/Add.lean
151
153
/- Copyright (c) 2020 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen, Eric Wieser -/ import Mathlib.Data.Fin.Tuple.Basic /-! # Matrix and vector notation This file defines notation for vectors and matrices. Given `a b c d : α`, the notation allows us to write `![a, b, c, d] : Fin 4 → α`. Nesting vectors gives coefficients of a matrix, so `![![a, b], ![c, d]] : Fin 2 → Fin 2 → α`. In later files we introduce `!![a, b; c, d]` as notation for `Matrix.of ![![a, b], ![c, d]]`. ## Main definitions * `vecEmpty` is the empty vector (or `0` by `n` matrix) `![]` * `vecCons` prepends an entry to a vector, so `![a, b]` is `vecCons a (vecCons b vecEmpty)` ## Implementation notes The `simp` lemmas require that one of the arguments is of the form `vecCons _ _`. This ensures `simp` works with entries only when (some) entries are already given. In other words, this notation will only appear in the output of `simp` if it already appears in the input. ## Notations The main new notation is `![a, b]`, which gets expanded to `vecCons a (vecCons b vecEmpty)`. ## Examples Examples of usage can be found in the `MathlibTest/matrix.lean` file. -/ namespace Matrix universe u variable {α : Type u} section MatrixNotation /-- `![]` is the vector with no entries. -/ def vecEmpty : Fin 0 → α := Fin.elim0 /-- `vecCons h t` prepends an entry `h` to a vector `t`. The inverse functions are `vecHead` and `vecTail`. The notation `![a, b, ...]` expands to `vecCons a (vecCons b ...)`. -/ def vecCons {n : ℕ} (h : α) (t : Fin n → α) : Fin n.succ → α := Fin.cons h t /-- `![...]` notation is used to construct a vector `Fin n → α` using `Matrix.vecEmpty` and `Matrix.vecCons`. For instance, `![a, b, c] : Fin 3` is syntax for `vecCons a (vecCons b (vecCons c vecEmpty))`. Note that this should not be used as syntax for `Matrix` as it generates a term with the wrong type. The `!![a, b; c, d]` syntax (provided by `Matrix.matrixNotation`) should be used instead. -/ syntax (name := vecNotation) "![" term,* "]" : term macro_rules | `(![$term:term, $terms:term,*]) => `(vecCons $term ![$terms,*]) | `(![$term:term]) => `(vecCons $term ![]) | `(![]) => `(vecEmpty) /-- Unexpander for the `![x, y, ...]` notation. -/ @[app_unexpander vecCons] def vecConsUnexpander : Lean.PrettyPrinter.Unexpander | `($_ $term ![$term2, $terms,*]) => `(![$term, $term2, $terms,*]) | `($_ $term ![$term2]) => `(![$term, $term2]) | `($_ $term ![]) => `(![$term]) | _ => throw () /-- Unexpander for the `![]` notation. -/ @[app_unexpander vecEmpty] def vecEmptyUnexpander : Lean.PrettyPrinter.Unexpander | `($_:ident) => `(![]) | _ => throw () /-- `vecHead v` gives the first entry of the vector `v` -/ def vecHead {n : ℕ} (v : Fin n.succ → α) : α := v 0 /-- `vecTail v` gives a vector consisting of all entries of `v` except the first -/ def vecTail {n : ℕ} (v : Fin n.succ → α) : Fin n → α := v ∘ Fin.succ variable {m n : ℕ} /-- Use `![...]` notation for displaying a vector `Fin n → α`, for example: ``` #eval ![1, 2] + ![3, 4] -- ![4, 6] ``` -/ instance _root_.PiFin.hasRepr [Repr α] : Repr (Fin n → α) where reprPrec f _ := Std.Format.bracket "![" (Std.Format.joinSep ((List.finRange n).map fun n => repr (f n)) ("," ++ Std.Format.line)) "]" end MatrixNotation variable {m n o : ℕ} theorem empty_eq (v : Fin 0 → α) : v = ![] := Subsingleton.elim _ _ section Val @[simp] theorem head_fin_const (a : α) : (vecHead fun _ : Fin (n + 1) => a) = a := rfl @[simp] theorem cons_val_zero (x : α) (u : Fin m → α) : vecCons x u 0 = x := rfl theorem cons_val_zero' (h : 0 < m.succ) (x : α) (u : Fin m → α) : vecCons x u ⟨0, h⟩ = x := rfl @[simp] theorem cons_val_succ (x : α) (u : Fin m → α) (i : Fin m) : vecCons x u i.succ = u i := by simp [vecCons] @[simp] theorem cons_val_succ' {i : ℕ} (h : i.succ < m.succ) (x : α) (u : Fin m → α) : vecCons x u ⟨i.succ, h⟩ = u ⟨i, Nat.lt_of_succ_lt_succ h⟩ := by simp only [vecCons, Fin.cons, Fin.cases_succ'] section simprocs open Lean Qq /-- Parses a chain of `Matrix.vecCons` calls into elements, leaving everything else in the tail. `let ⟨xs, tailn, tail⟩ ← matchVecConsPrefix n e` decomposes `e : Fin n → _` in the form `vecCons x₀ <| ... <| vecCons xₙ <| tail` where `tail : Fin tailn → _`. -/ partial def matchVecConsPrefix (n : Q(Nat)) (e : Expr) : MetaM <| List Expr × Q(Nat) × Expr := do match_expr ← Meta.whnfR e with | Matrix.vecCons _ n x xs => do let (elems, n', tail) ← matchVecConsPrefix n xs return (x :: elems, n', tail) | _ => return ([], n, e) open Qq in /-- A simproc that handles terms of the form `Matrix.vecCons a f i` where `i` is a numeric literal. In practice, this is most effective at handling `![a, b, c] i`-style terms. -/ dsimproc cons_val (Matrix.vecCons _ _ _) := fun e => do let_expr Matrix.vecCons α en x xs' ei := ← Meta.whnfR e | return .continue let some i := ei.int? | return .continue let (xs, etailn, tail) ← matchVecConsPrefix en xs' let xs := x :: xs -- Determine if the tail is a numeral or only an offset. let (tailn, variadic, etailn) ← do let etailn_whnf : Q(ℕ) ← Meta.whnfD etailn if let Expr.lit (.natVal length) := etailn_whnf then pure (length, false, q(OfNat.ofNat $etailn_whnf)) else if let .some ((base : Q(ℕ)), offset) ← (Meta.isOffset? etailn_whnf).run then let offset_e : Q(ℕ) := mkNatLit offset pure (offset, true, q($base + $offset)) else pure (0, true, etailn) -- Wrap the index if possible, and abort if not let wrapped_i ← if variadic then -- can't wrap as we don't know the length unless 0 ≤ i ∧ i < xs.length + tailn do return .continue pure i.toNat else pure (i % (xs.length + tailn)).toNat if h : wrapped_i < xs.length then return .continue xs[wrapped_i] else -- Within the `tail` let _ ← synthInstanceQ q(NeZero $etailn) have i_lit : Q(ℕ) := mkRawNatLit (wrapped_i - xs.length) return .continue (.some <| .app tail q(OfNat.ofNat $i_lit : Fin $etailn)) end simprocs @[simp] theorem head_cons (x : α) (u : Fin m → α) : vecHead (vecCons x u) = x := rfl @[simp] theorem tail_cons (x : α) (u : Fin m → α) : vecTail (vecCons x u) = u := by ext simp [vecTail] theorem empty_val' {n' : Type*} (j : n') : (fun i => (![] : Fin 0 → n' → α) i j) = ![] := empty_eq _ @[simp] theorem cons_head_tail (u : Fin m.succ → α) : vecCons (vecHead u) (vecTail u) = u := Fin.cons_self_tail _ @[simp] theorem range_cons (x : α) (u : Fin n → α) : Set.range (vecCons x u) = {x} ∪ Set.range u := Set.ext fun y => by simp [Fin.exists_fin_succ, eq_comm] @[simp] theorem range_empty (u : Fin 0 → α) : Set.range u = ∅ := Set.range_eq_empty _ theorem range_cons_empty (x : α) (u : Fin 0 → α) : Set.range (Matrix.vecCons x u) = {x} := by rw [range_cons, range_empty, Set.union_empty] -- simp can prove this (up to commutativity) theorem range_cons_cons_empty (x y : α) (u : Fin 0 → α) : Set.range (vecCons x <| vecCons y u) = {x, y} := by rw [range_cons, range_cons_empty, Set.singleton_union] theorem vecCons_const (a : α) : (vecCons a fun _ : Fin n => a) = fun _ => a := funext <| Fin.forall_iff_succ.2 ⟨rfl, cons_val_succ _ _⟩ theorem vec_single_eq_const (a : α) : ![a] = fun _ => a := let _ : Unique (Fin 1) := inferInstance funext <| Unique.forall_iff.2 rfl /-- `![a, b, ...] 1` is equal to `b`. The simplifier needs a special lemma for length `≥ 2`, in addition to `cons_val_succ`, because `1 : Fin 1 = 0 : Fin 1`. -/ @[simp] theorem cons_val_one (x : α) (u : Fin m.succ → α) : vecCons x u 1 = u 0 := rfl theorem cons_val_two (x : α) (u : Fin m.succ.succ → α) : vecCons x u 2 = vecHead (vecTail u) := rfl lemma cons_val_three (x : α) (u : Fin m.succ.succ.succ → α) : vecCons x u 3 = vecHead (vecTail (vecTail u)) := rfl lemma cons_val_four (x : α) (u : Fin m.succ.succ.succ.succ → α) : vecCons x u 4 = vecHead (vecTail (vecTail (vecTail u))) := rfl @[simp] theorem cons_val_fin_one (x : α) (u : Fin 0 → α) : ∀ (i : Fin 1), vecCons x u i = x := by rw [Fin.forall_fin_one] rfl theorem cons_fin_one (x : α) (u : Fin 0 → α) : vecCons x u = fun _ => x := funext (cons_val_fin_one x u) open Lean Qq in /-- `mkVecLiteralQ ![x, y, z]` produces the term `q(![$x, $y, $z])`. -/ def _root_.PiFin.mkLiteralQ {u : Level} {α : Q(Type u)} {n : ℕ} (elems : Fin n → Q($α)) : Q(Fin $n → $α) := loop 0 (Nat.zero_le _) q(vecEmpty) where loop (i : ℕ) (hi : i ≤ n) (rest : Q(Fin $i → $α)) : let i' : Nat := i + 1; Q(Fin $(i') → $α) := if h : i < n then loop (i + 1) h q(vecCons $(elems (Fin.rev ⟨i, h⟩)) $rest) else rest attribute [nolint docBlame] _root_.PiFin.mkLiteralQ.loop open Lean Qq in protected instance _root_.PiFin.toExpr [ToLevel.{u}] [ToExpr α] (n : ℕ) : ToExpr (Fin n → α) := have lu := toLevel.{u} have eα : Q(Type $lu) := toTypeExpr α let toTypeExpr := q(Fin $n → $eα) { toTypeExpr, toExpr v := PiFin.mkLiteralQ fun i => show Q($eα) from toExpr (v i) } /-! ### `bit0` and `bit1` indices The following definitions and `simp` lemmas are used to allow numeral-indexed element of a vector given with matrix notation to be extracted by `simp` in Lean 3 (even when the numeral is larger than the number of elements in the vector, which is taken modulo that number of elements by virtue of the semantics of `bit0` and `bit1` and of addition on `Fin n`). -/ /-- `vecAppend ho u v` appends two vectors of lengths `m` and `n` to produce one of length `o = m + n`. This is a variant of `Fin.append` with an additional `ho` argument, which provides control of definitional equality for the vector length. This turns out to be helpful when providing simp lemmas to reduce `![a, b, c] n`, and also means that `vecAppend ho u v 0` is valid. `Fin.append u v 0` is not valid in this case because there is no `Zero (Fin (m + n))` instance. -/ def vecAppend {α : Type*} {o : ℕ} (ho : o = m + n) (u : Fin m → α) (v : Fin n → α) : Fin o → α := Fin.append u v ∘ Fin.cast ho theorem vecAppend_eq_ite {α : Type*} {o : ℕ} (ho : o = m + n) (u : Fin m → α) (v : Fin n → α) : vecAppend ho u v = fun i : Fin o => if h : (i : ℕ) < m then u ⟨i, h⟩ else v ⟨(i : ℕ) - m, by omega⟩ := by ext i rw [vecAppend, Fin.append, Function.comp_apply, Fin.addCases] congr with hi simp only [eq_rec_constant] rfl @[simp] theorem vecAppend_apply_zero {α : Type*} {o : ℕ} (ho : o + 1 = m + 1 + n) (u : Fin (m + 1) → α) (v : Fin n → α) : vecAppend ho u v 0 = u 0 := dif_pos _ @[simp] theorem empty_vecAppend (v : Fin n → α) : vecAppend n.zero_add.symm ![] v = v := by ext simp [vecAppend_eq_ite] @[simp] theorem cons_vecAppend (ho : o + 1 = m + 1 + n) (x : α) (u : Fin m → α) (v : Fin n → α) : vecAppend ho (vecCons x u) v = vecCons x (vecAppend (by omega) u v) := by ext i simp_rw [vecAppend_eq_ite] split_ifs with h · rcases i with ⟨⟨⟩ | i, hi⟩ · simp · simp only [Nat.add_lt_add_iff_right, Fin.val_mk] at h simp [h] · rcases i with ⟨⟨⟩ | i, hi⟩ · simp at h · rw [not_lt, Fin.val_mk, Nat.add_le_add_iff_right] at h simp [h, not_lt.2 h] /-- `vecAlt0 v` gives a vector with half the length of `v`, with only alternate elements (even-numbered). -/ def vecAlt0 (hm : m = n + n) (v : Fin m → α) (k : Fin n) : α := v ⟨(k : ℕ) + k, by omega⟩ /-- `vecAlt1 v` gives a vector with half the length of `v`, with only alternate elements (odd-numbered). -/ def vecAlt1 (hm : m = n + n) (v : Fin m → α) (k : Fin n) : α := v ⟨(k : ℕ) + k + 1, hm.symm ▸ Nat.add_succ_lt_add k.2 k.2⟩ section bits theorem vecAlt0_vecAppend (v : Fin n → α) : vecAlt0 rfl (vecAppend rfl v v) = v ∘ (fun n ↦ n + n) := by ext i simp_rw [Function.comp, vecAlt0, vecAppend_eq_ite] split_ifs with h <;> congr · rw [Fin.val_mk] at h exact (Nat.mod_eq_of_lt h).symm · rw [Fin.val_mk, not_lt] at h simp only [Fin.ext_iff, Fin.val_add, Fin.val_mk, Nat.mod_eq_sub_mod h] refine (Nat.mod_eq_of_lt ?_).symm omega theorem vecAlt1_vecAppend (v : Fin (n + 1) → α) : vecAlt1 rfl (vecAppend rfl v v) = v ∘ (fun n ↦ (n + n) + 1) := by ext i simp_rw [Function.comp, vecAlt1, vecAppend_eq_ite] cases n with | zero => obtain ⟨i, hi⟩ := i simp only [Nat.zero_add, Nat.lt_one_iff] at hi; subst i; rfl | succ n => split_ifs with h <;> congr · simp [Nat.mod_eq_of_lt, h] · rw [Fin.val_mk, not_lt] at h simp only [Fin.ext_iff, Fin.val_add, Fin.val_mk, Nat.mod_add_mod, Fin.val_one, Nat.mod_eq_sub_mod h, show 1 % (n + 2) = 1 from Nat.mod_eq_of_lt (by omega)] refine (Nat.mod_eq_of_lt ?_).symm omega @[simp] theorem vecHead_vecAlt0 (hm : m + 2 = n + 1 + (n + 1)) (v : Fin (m + 2) → α) : vecHead (vecAlt0 hm v) = v 0 := rfl @[simp] theorem vecHead_vecAlt1 (hm : m + 2 = n + 1 + (n + 1)) (v : Fin (m + 2) → α) : vecHead (vecAlt1 hm v) = v 1 := by simp [vecHead, vecAlt1] theorem cons_vec_bit0_eq_alt0 (x : α) (u : Fin n → α) (i : Fin (n + 1)) : vecCons x u (i + i) = vecAlt0 rfl (vecAppend rfl (vecCons x u) (vecCons x u)) i := by rw [vecAlt0_vecAppend]; rfl theorem cons_vec_bit1_eq_alt1 (x : α) (u : Fin n → α) (i : Fin (n + 1)) : vecCons x u ((i + i) + 1) = vecAlt1 rfl (vecAppend rfl (vecCons x u) (vecCons x u)) i := by rw [vecAlt1_vecAppend]; rfl end bits @[simp] theorem cons_vecAlt0 (h : m + 1 + 1 = n + 1 + (n + 1)) (x y : α) (u : Fin m → α) : vecAlt0 h (vecCons x (vecCons y u)) = vecCons x (vecAlt0 (by omega) u) := by ext i simp_rw [vecAlt0] rcases i with ⟨⟨⟩ | i, hi⟩ · rfl · simp only [← Nat.add_assoc, Nat.add_right_comm, cons_val_succ', cons_vecAppend, Nat.add_eq, vecAlt0] @[simp] theorem empty_vecAlt0 (α) {h} : vecAlt0 h (![] : Fin 0 → α) = ![] := by simp [eq_iff_true_of_subsingleton] @[simp] theorem cons_vecAlt1 (h : m + 1 + 1 = n + 1 + (n + 1)) (x y : α) (u : Fin m → α) : vecAlt1 h (vecCons x (vecCons y u)) = vecCons y (vecAlt1 (by omega) u) := by ext i simp_rw [vecAlt1] rcases i with ⟨⟨⟩ | i, hi⟩ · rfl · simp [vecAlt1, Nat.add_right_comm, ← Nat.add_assoc]
@[simp] theorem empty_vecAlt1 (α) {h} : vecAlt1 h (![] : Fin 0 → α) = ![] := by simp [eq_iff_true_of_subsingleton] end Val
Mathlib/Data/Fin/VecNotation.lean
410
416
/- Copyright (c) 2018 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Floris van Doorn, Gabriel Ebner, Yury Kudryashov -/ import Mathlib.Data.Set.Accumulate import Mathlib.Order.ConditionallyCompleteLattice.Finset import Mathlib.Order.Interval.Finset.Nat /-! # Conditionally complete linear order structure on `ℕ` In this file we * define a `ConditionallyCompleteLinearOrderBot` structure on `ℕ`; * prove a few lemmas about `iSup`/`iInf`/`Set.iUnion`/`Set.iInter` and natural numbers. -/ assert_not_exists MonoidWithZero open Set namespace Nat open scoped Classical in noncomputable instance : InfSet ℕ := ⟨fun s ↦ if h : ∃ n, n ∈ s then @Nat.find (fun n ↦ n ∈ s) _ h else 0⟩ open scoped Classical in noncomputable instance : SupSet ℕ := ⟨fun s ↦ if h : ∃ n, ∀ a ∈ s, a ≤ n then @Nat.find (fun n ↦ ∀ a ∈ s, a ≤ n) _ h else 0⟩ open scoped Classical in theorem sInf_def {s : Set ℕ} (h : s.Nonempty) : sInf s = @Nat.find (fun n ↦ n ∈ s) _ h := dif_pos _ open scoped Classical in theorem sSup_def {s : Set ℕ} (h : ∃ n, ∀ a ∈ s, a ≤ n) : sSup s = @Nat.find (fun n ↦ ∀ a ∈ s, a ≤ n) _ h := dif_pos _ theorem _root_.Set.Infinite.Nat.sSup_eq_zero {s : Set ℕ} (h : s.Infinite) : sSup s = 0 := dif_neg fun ⟨n, hn⟩ ↦ let ⟨k, hks, hk⟩ := h.exists_gt n (hn k hks).not_lt hk @[simp] theorem sInf_eq_zero {s : Set ℕ} : sInf s = 0 ↔ 0 ∈ s ∨ s = ∅ := by cases eq_empty_or_nonempty s with
| inl h => subst h simp only [or_true, eq_self_iff_true, iInf, InfSet.sInf, mem_empty_iff_false, exists_false, dif_neg, not_false_iff] | inr h => simp only [h.ne_empty, or_false, Nat.sInf_def, h, Nat.find_eq_zero] @[simp]
Mathlib/Data/Nat/Lattice.lean
50
55
/- Copyright (c) 2022 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers -/ import Mathlib.Analysis.Convex.Side import Mathlib.Geometry.Euclidean.Angle.Oriented.Rotation import Mathlib.Geometry.Euclidean.Angle.Unoriented.Affine /-! # Oriented angles. This file defines oriented angles in Euclidean affine spaces. ## Main definitions * `EuclideanGeometry.oangle`, with notation `∡`, is the oriented angle determined by three points. -/ noncomputable section open Module Complex open scoped Affine EuclideanGeometry Real RealInnerProductSpace ComplexConjugate namespace EuclideanGeometry variable {V : Type*} {P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P] [NormedAddTorsor V P] [hd2 : Fact (finrank ℝ V = 2)] [Module.Oriented ℝ V (Fin 2)] /-- A fixed choice of positive orientation of Euclidean space `ℝ²` -/ abbrev o := @Module.Oriented.positiveOrientation /-- The oriented angle at `p₂` between the line segments to `p₁` and `p₃`, modulo `2 * π`. If either of those points equals `p₂`, this is 0. See `EuclideanGeometry.angle` for the corresponding unoriented angle definition. -/ def oangle (p₁ p₂ p₃ : P) : Real.Angle := o.oangle (p₁ -ᵥ p₂) (p₃ -ᵥ p₂) @[inherit_doc] scoped notation "∡" => EuclideanGeometry.oangle /-- Oriented angles are continuous when neither end point equals the middle point. -/ theorem continuousAt_oangle {x : P × P × P} (hx12 : x.1 ≠ x.2.1) (hx32 : x.2.2 ≠ x.2.1) : ContinuousAt (fun y : P × P × P => ∡ y.1 y.2.1 y.2.2) x := by unfold oangle fun_prop (disch := simp [*]) /-- The angle ∡AAB at a point. -/ @[simp] theorem oangle_self_left (p₁ p₂ : P) : ∡ p₁ p₁ p₂ = 0 := by simp [oangle] /-- The angle ∡ABB at a point. -/ @[simp] theorem oangle_self_right (p₁ p₂ : P) : ∡ p₁ p₂ p₂ = 0 := by simp [oangle] /-- The angle ∡ABA at a point. -/ @[simp] theorem oangle_self_left_right (p₁ p₂ : P) : ∡ p₁ p₂ p₁ = 0 := o.oangle_self _ /-- If the angle between three points is nonzero, the first two points are not equal. -/ theorem left_ne_of_oangle_ne_zero {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ ≠ 0) : p₁ ≠ p₂ := by rw [← @vsub_ne_zero V]; exact o.left_ne_zero_of_oangle_ne_zero h /-- If the angle between three points is nonzero, the last two points are not equal. -/ theorem right_ne_of_oangle_ne_zero {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ ≠ 0) : p₃ ≠ p₂ := by rw [← @vsub_ne_zero V]; exact o.right_ne_zero_of_oangle_ne_zero h /-- If the angle between three points is nonzero, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_ne_zero {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ ≠ 0) : p₁ ≠ p₃ := by rw [← (vsub_left_injective p₂).ne_iff]; exact o.ne_of_oangle_ne_zero h /-- If the angle between three points is `π`, the first two points are not equal. -/ theorem left_ne_of_oangle_eq_pi {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = π) : p₁ ≠ p₂ := left_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `π`, the last two points are not equal. -/ theorem right_ne_of_oangle_eq_pi {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = π) : p₃ ≠ p₂ := right_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `π`, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_eq_pi {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = π) : p₁ ≠ p₃ := left_ne_right_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `π / 2`, the first two points are not equal. -/ theorem left_ne_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (π / 2 : ℝ)) : p₁ ≠ p₂ := left_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `π / 2`, the last two points are not equal. -/ theorem right_ne_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (π / 2 : ℝ)) : p₃ ≠ p₂ := right_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `π / 2`, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (π / 2 : ℝ)) : p₁ ≠ p₃ := left_ne_right_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `-π / 2`, the first two points are not equal. -/ theorem left_ne_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (-π / 2 : ℝ)) : p₁ ≠ p₂ := left_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `-π / 2`, the last two points are not equal. -/ theorem right_ne_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (-π / 2 : ℝ)) : p₃ ≠ p₂ := right_ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the angle between three points is `-π / 2`, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = (-π / 2 : ℝ)) : p₁ ≠ p₃ := left_ne_right_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : ∡ p₁ p₂ p₃ ≠ 0) /-- If the sign of the angle between three points is nonzero, the first two points are not equal. -/ theorem left_ne_of_oangle_sign_ne_zero {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign ≠ 0) : p₁ ≠ p₂ := left_ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1 /-- If the sign of the angle between three points is nonzero, the last two points are not equal. -/ theorem right_ne_of_oangle_sign_ne_zero {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign ≠ 0) : p₃ ≠ p₂ := right_ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1 /-- If the sign of the angle between three points is nonzero, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_sign_ne_zero {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign ≠ 0) : p₁ ≠ p₃ := left_ne_right_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1 /-- If the sign of the angle between three points is positive, the first two points are not equal. -/ theorem left_ne_of_oangle_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : p₁ ≠ p₂ := left_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0) /-- If the sign of the angle between three points is positive, the last two points are not equal. -/ theorem right_ne_of_oangle_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : p₃ ≠ p₂ := right_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0) /-- If the sign of the angle between three points is positive, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : p₁ ≠ p₃ := left_ne_right_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0) /-- If the sign of the angle between three points is negative, the first two points are not equal. -/ theorem left_ne_of_oangle_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) : p₁ ≠ p₂ := left_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0) /-- If the sign of the angle between three points is negative, the last two points are not equal. -/ theorem right_ne_of_oangle_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) : p₃ ≠ p₂ := right_ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0) /-- If the sign of the angle between three points is negative, the first and third points are not equal. -/ theorem left_ne_right_of_oangle_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) : p₁ ≠ p₃ := left_ne_right_of_oangle_sign_ne_zero (h.symm ▸ by decide : (∡ p₁ p₂ p₃).sign ≠ 0) /-- Reversing the order of the points passed to `oangle` negates the angle. -/ theorem oangle_rev (p₁ p₂ p₃ : P) : ∡ p₃ p₂ p₁ = -∡ p₁ p₂ p₃ := o.oangle_rev _ _ /-- Adding an angle to that with the order of the points reversed results in 0. -/ @[simp] theorem oangle_add_oangle_rev (p₁ p₂ p₃ : P) : ∡ p₁ p₂ p₃ + ∡ p₃ p₂ p₁ = 0 := o.oangle_add_oangle_rev _ _ /-- An oriented angle is zero if and only if the angle with the order of the points reversed is zero. -/ theorem oangle_eq_zero_iff_oangle_rev_eq_zero {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = 0 ↔ ∡ p₃ p₂ p₁ = 0 := o.oangle_eq_zero_iff_oangle_rev_eq_zero /-- An oriented angle is `π` if and only if the angle with the order of the points reversed is `π`. -/ theorem oangle_eq_pi_iff_oangle_rev_eq_pi {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = π ↔ ∡ p₃ p₂ p₁ = π := o.oangle_eq_pi_iff_oangle_rev_eq_pi /-- An oriented angle is not zero or `π` if and only if the three points are affinely independent. -/ theorem oangle_ne_zero_and_ne_pi_iff_affineIndependent {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ ≠ 0 ∧ ∡ p₁ p₂ p₃ ≠ π ↔ AffineIndependent ℝ ![p₁, p₂, p₃] := by rw [oangle, o.oangle_ne_zero_and_ne_pi_iff_linearIndependent, affineIndependent_iff_linearIndependent_vsub ℝ _ (1 : Fin 3), ← linearIndependent_equiv (finSuccAboveEquiv (1 : Fin 3))] convert Iff.rfl ext i fin_cases i <;> rfl /-- An oriented angle is zero or `π` if and only if the three points are collinear. -/ theorem oangle_eq_zero_or_eq_pi_iff_collinear {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = 0 ∨ ∡ p₁ p₂ p₃ = π ↔ Collinear ℝ ({p₁, p₂, p₃} : Set P) := by rw [← not_iff_not, not_or, oangle_ne_zero_and_ne_pi_iff_affineIndependent, affineIndependent_iff_not_collinear_set] /-- An oriented angle has a sign zero if and only if the three points are collinear. -/ theorem oangle_sign_eq_zero_iff_collinear {p₁ p₂ p₃ : P} : (∡ p₁ p₂ p₃).sign = 0 ↔ Collinear ℝ ({p₁, p₂, p₃} : Set P) := by rw [Real.Angle.sign_eq_zero_iff, oangle_eq_zero_or_eq_pi_iff_collinear] /-- If twice the oriented angles between two triples of points are equal, one triple is affinely independent if and only if the other is. -/ theorem affineIndependent_iff_of_two_zsmul_oangle_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (h : (2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆) : AffineIndependent ℝ ![p₁, p₂, p₃] ↔ AffineIndependent ℝ ![p₄, p₅, p₆] := by simp_rw [← oangle_ne_zero_and_ne_pi_iff_affineIndependent, ← Real.Angle.two_zsmul_ne_zero_iff, h] /-- If twice the oriented angles between two triples of points are equal, one triple is collinear if and only if the other is. -/ theorem collinear_iff_of_two_zsmul_oangle_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (h : (2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆) : Collinear ℝ ({p₁, p₂, p₃} : Set P) ↔ Collinear ℝ ({p₄, p₅, p₆} : Set P) := by simp_rw [← oangle_eq_zero_or_eq_pi_iff_collinear, ← Real.Angle.two_zsmul_eq_zero_iff, h] /-- If corresponding pairs of points in two angles have the same vector span, twice those angles are equal. -/ theorem two_zsmul_oangle_of_vectorSpan_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (h₁₂₄₅ : vectorSpan ℝ ({p₁, p₂} : Set P) = vectorSpan ℝ ({p₄, p₅} : Set P)) (h₃₂₆₅ : vectorSpan ℝ ({p₃, p₂} : Set P) = vectorSpan ℝ ({p₆, p₅} : Set P)) : (2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆ := by simp_rw [vectorSpan_pair] at h₁₂₄₅ h₃₂₆₅ exact o.two_zsmul_oangle_of_span_eq_of_span_eq h₁₂₄₅ h₃₂₆₅ /-- If the lines determined by corresponding pairs of points in two angles are parallel, twice those angles are equal. -/ theorem two_zsmul_oangle_of_parallel {p₁ p₂ p₃ p₄ p₅ p₆ : P} (h₁₂₄₅ : line[ℝ, p₁, p₂] ∥ line[ℝ, p₄, p₅]) (h₃₂₆₅ : line[ℝ, p₃, p₂] ∥ line[ℝ, p₆, p₅]) : (2 : ℤ) • ∡ p₁ p₂ p₃ = (2 : ℤ) • ∡ p₄ p₅ p₆ := by rw [AffineSubspace.affineSpan_pair_parallel_iff_vectorSpan_eq] at h₁₂₄₅ h₃₂₆₅ exact two_zsmul_oangle_of_vectorSpan_eq h₁₂₄₅ h₃₂₆₅ /-- Given three points not equal to `p`, the angle between the first and the second at `p` plus the angle between the second and the third equals the angle between the first and the third. -/ @[simp] theorem oangle_add {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) : ∡ p₁ p p₂ + ∡ p₂ p p₃ = ∡ p₁ p p₃ := o.oangle_add (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃) /-- Given three points not equal to `p`, the angle between the second and the third at `p` plus the angle between the first and the second equals the angle between the first and the third. -/ @[simp] theorem oangle_add_swap {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) : ∡ p₂ p p₃ + ∡ p₁ p p₂ = ∡ p₁ p p₃ := o.oangle_add_swap (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃) /-- Given three points not equal to `p`, the angle between the first and the third at `p` minus the angle between the first and the second equals the angle between the second and the third. -/ @[simp] theorem oangle_sub_left {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) : ∡ p₁ p p₃ - ∡ p₁ p p₂ = ∡ p₂ p p₃ := o.oangle_sub_left (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃) /-- Given three points not equal to `p`, the angle between the first and the third at `p` minus the angle between the second and the third equals the angle between the first and the second. -/ @[simp] theorem oangle_sub_right {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) : ∡ p₁ p p₃ - ∡ p₂ p p₃ = ∡ p₁ p p₂ := o.oangle_sub_right (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃) /-- Given three points not equal to `p`, adding the angles between them at `p` in cyclic order results in 0. -/ @[simp] theorem oangle_add_cyc3 {p p₁ p₂ p₃ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) (hp₃ : p₃ ≠ p) : ∡ p₁ p p₂ + ∡ p₂ p p₃ + ∡ p₃ p p₁ = 0 := o.oangle_add_cyc3 (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) (vsub_ne_zero.2 hp₃) /-- Pons asinorum, oriented angle-at-point form. -/ theorem oangle_eq_oangle_of_dist_eq {p₁ p₂ p₃ : P} (h : dist p₁ p₂ = dist p₁ p₃) : ∡ p₁ p₂ p₃ = ∡ p₂ p₃ p₁ := by simp_rw [dist_eq_norm_vsub V] at h rw [oangle, oangle, ← vsub_sub_vsub_cancel_left p₃ p₂ p₁, ← vsub_sub_vsub_cancel_left p₂ p₃ p₁, o.oangle_sub_eq_oangle_sub_rev_of_norm_eq h] /-- The angle at the apex of an isosceles triangle is `π` minus twice a base angle, oriented angle-at-point form. -/ theorem oangle_eq_pi_sub_two_zsmul_oangle_of_dist_eq {p₁ p₂ p₃ : P} (hn : p₂ ≠ p₃) (h : dist p₁ p₂ = dist p₁ p₃) : ∡ p₃ p₁ p₂ = π - (2 : ℤ) • ∡ p₁ p₂ p₃ := by simp_rw [dist_eq_norm_vsub V] at h rw [oangle, oangle] convert o.oangle_eq_pi_sub_two_zsmul_oangle_sub_of_norm_eq _ h using 1 · rw [← neg_vsub_eq_vsub_rev p₁ p₃, ← neg_vsub_eq_vsub_rev p₁ p₂, o.oangle_neg_neg] · rw [← o.oangle_sub_eq_oangle_sub_rev_of_norm_eq h]; simp · simpa using hn /-- A base angle of an isosceles triangle is acute, oriented angle-at-point form. -/ theorem abs_oangle_right_toReal_lt_pi_div_two_of_dist_eq {p₁ p₂ p₃ : P} (h : dist p₁ p₂ = dist p₁ p₃) : |(∡ p₁ p₂ p₃).toReal| < π / 2 := by simp_rw [dist_eq_norm_vsub V] at h rw [oangle, ← vsub_sub_vsub_cancel_left p₃ p₂ p₁] exact o.abs_oangle_sub_right_toReal_lt_pi_div_two h /-- A base angle of an isosceles triangle is acute, oriented angle-at-point form. -/ theorem abs_oangle_left_toReal_lt_pi_div_two_of_dist_eq {p₁ p₂ p₃ : P} (h : dist p₁ p₂ = dist p₁ p₃) : |(∡ p₂ p₃ p₁).toReal| < π / 2 := oangle_eq_oangle_of_dist_eq h ▸ abs_oangle_right_toReal_lt_pi_div_two_of_dist_eq h /-- The cosine of the oriented angle at `p` between two points not equal to `p` equals that of the unoriented angle. -/ theorem cos_oangle_eq_cos_angle {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) : Real.Angle.cos (∡ p₁ p p₂) = Real.cos (∠ p₁ p p₂) := o.cos_oangle_eq_cos_angle (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) /-- The oriented angle at `p` between two points not equal to `p` is plus or minus the unoriented angle. -/ theorem oangle_eq_angle_or_eq_neg_angle {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) : ∡ p₁ p p₂ = ∠ p₁ p p₂ ∨ ∡ p₁ p p₂ = -∠ p₁ p p₂ := o.oangle_eq_angle_or_eq_neg_angle (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) /-- The unoriented angle at `p` between two points not equal to `p` is the absolute value of the oriented angle. -/ theorem angle_eq_abs_oangle_toReal {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) : ∠ p₁ p p₂ = |(∡ p₁ p p₂).toReal| := o.angle_eq_abs_oangle_toReal (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) /-- If the sign of the oriented angle at `p` between two points is zero, either one of the points equals `p` or the unoriented angle is 0 or π. -/ theorem eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero {p p₁ p₂ : P} (h : (∡ p₁ p p₂).sign = 0) : p₁ = p ∨ p₂ = p ∨ ∠ p₁ p p₂ = 0 ∨ ∠ p₁ p p₂ = π := by convert o.eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero h <;> simp /-- If two unoriented angles are equal, and the signs of the corresponding oriented angles are equal, then the oriented angles are equal (even in degenerate cases). -/ theorem oangle_eq_of_angle_eq_of_sign_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (h : ∠ p₁ p₂ p₃ = ∠ p₄ p₅ p₆) (hs : (∡ p₁ p₂ p₃).sign = (∡ p₄ p₅ p₆).sign) : ∡ p₁ p₂ p₃ = ∡ p₄ p₅ p₆ := o.oangle_eq_of_angle_eq_of_sign_eq h hs /-- If the signs of two nondegenerate oriented angles between points are equal, the oriented angles are equal if and only if the unoriented angles are equal. -/ theorem angle_eq_iff_oangle_eq_of_sign_eq {p₁ p₂ p₃ p₄ p₅ p₆ : P} (hp₁ : p₁ ≠ p₂) (hp₃ : p₃ ≠ p₂) (hp₄ : p₄ ≠ p₅) (hp₆ : p₆ ≠ p₅) (hs : (∡ p₁ p₂ p₃).sign = (∡ p₄ p₅ p₆).sign) : ∠ p₁ p₂ p₃ = ∠ p₄ p₅ p₆ ↔ ∡ p₁ p₂ p₃ = ∡ p₄ p₅ p₆ := o.angle_eq_iff_oangle_eq_of_sign_eq (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₃) (vsub_ne_zero.2 hp₄) (vsub_ne_zero.2 hp₆) hs /-- The oriented angle between three points equals the unoriented angle if the sign is positive. -/ theorem oangle_eq_angle_of_sign_eq_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = 1) : ∡ p₁ p₂ p₃ = ∠ p₁ p₂ p₃ := o.oangle_eq_angle_of_sign_eq_one h /-- The oriented angle between three points equals minus the unoriented angle if the sign is negative. -/ theorem oangle_eq_neg_angle_of_sign_eq_neg_one {p₁ p₂ p₃ : P} (h : (∡ p₁ p₂ p₃).sign = -1) : ∡ p₁ p₂ p₃ = -∠ p₁ p₂ p₃ := o.oangle_eq_neg_angle_of_sign_eq_neg_one h /-- The unoriented angle at `p` between two points not equal to `p` is zero if and only if the unoriented angle is zero. -/ theorem oangle_eq_zero_iff_angle_eq_zero {p p₁ p₂ : P} (hp₁ : p₁ ≠ p) (hp₂ : p₂ ≠ p) : ∡ p₁ p p₂ = 0 ↔ ∠ p₁ p p₂ = 0 := o.oangle_eq_zero_iff_angle_eq_zero (vsub_ne_zero.2 hp₁) (vsub_ne_zero.2 hp₂) /-- The oriented angle between three points is `π` if and only if the unoriented angle is `π`. -/ theorem oangle_eq_pi_iff_angle_eq_pi {p₁ p₂ p₃ : P} : ∡ p₁ p₂ p₃ = π ↔ ∠ p₁ p₂ p₃ = π := o.oangle_eq_pi_iff_angle_eq_pi /-- If the oriented angle between three points is `π / 2`, so is the unoriented angle. -/ theorem angle_eq_pi_div_two_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) : ∠ p₁ p₂ p₃ = π / 2 := by rw [angle, ← InnerProductGeometry.inner_eq_zero_iff_angle_eq_pi_div_two] exact o.inner_eq_zero_of_oangle_eq_pi_div_two h /-- If the oriented angle between three points is `π / 2`, so is the unoriented angle (reversed). -/ theorem angle_rev_eq_pi_div_two_of_oangle_eq_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(π / 2)) : ∠ p₃ p₂ p₁ = π / 2 := by rw [angle_comm] exact angle_eq_pi_div_two_of_oangle_eq_pi_div_two h
/-- If the oriented angle between three points is `-π / 2`, the unoriented angle is `π / 2`. -/ theorem angle_eq_pi_div_two_of_oangle_eq_neg_pi_div_two {p₁ p₂ p₃ : P} (h : ∡ p₁ p₂ p₃ = ↑(-π / 2)) : ∠ p₁ p₂ p₃ = π / 2 := by
Mathlib/Geometry/Euclidean/Angle/Oriented/Affine.lean
372
374
/- Copyright (c) 2021 Jakob von Raumer. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jakob von Raumer -/ import Mathlib.Tactic.CategoryTheory.Monoidal.Basic import Mathlib.CategoryTheory.Closed.Monoidal import Mathlib.Tactic.ApplyFun /-! # Rigid (autonomous) monoidal categories This file defines rigid (autonomous) monoidal categories and the necessary theory about exact pairings and duals. ## Main definitions * `ExactPairing` of two objects of a monoidal category * Type classes `HasLeftDual` and `HasRightDual` that capture that a pairing exists * The `rightAdjointMate f` as a morphism `fᘁ : Yᘁ ⟶ Xᘁ` for a morphism `f : X ⟶ Y` * The classes of `RightRigidCategory`, `LeftRigidCategory` and `RigidCategory` ## Main statements * `comp_rightAdjointMate`: The adjoint mates of the composition is the composition of adjoint mates. ## Notations * `η_` and `ε_` denote the coevaluation and evaluation morphism of an exact pairing. * `Xᘁ` and `ᘁX` denote the right and left dual of an object, as well as the adjoint mate of a morphism. ## Future work * Show that `X ⊗ Y` and `Yᘁ ⊗ Xᘁ` form an exact pairing. * Show that the left adjoint mate of the right adjoint mate of a morphism is the morphism itself. * Simplify constructions in the case where a symmetry or braiding is present. * Show that `ᘁ` gives an equivalence of categories `C ≅ (Cᵒᵖ)ᴹᵒᵖ`. * Define pivotal categories (rigid categories equipped with a natural isomorphism `ᘁᘁ ≅ 𝟙 C`). ## Notes Although we construct the adjunction `tensorLeft Y ⊣ tensorLeft X` from `ExactPairing X Y`, this is not a bijective correspondence. I think the correct statement is that `tensorLeft Y` and `tensorLeft X` are module endofunctors of `C` as a right `C` module category, and `ExactPairing X Y` is in bijection with adjunctions compatible with this right `C` action. ## References * <https://ncatlab.org/nlab/show/rigid+monoidal+category> ## Tags rigid category, monoidal category -/ open CategoryTheory MonoidalCategory universe v v₁ v₂ v₃ u u₁ u₂ u₃ noncomputable section namespace CategoryTheory variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory C] /-- An exact pairing is a pair of objects `X Y : C` which admit a coevaluation and evaluation morphism which fulfill two triangle equalities. -/ class ExactPairing (X Y : C) where /-- Coevaluation of an exact pairing. Do not use directly. Use `ExactPairing.coevaluation` instead. -/ coevaluation' : 𝟙_ C ⟶ X ⊗ Y /-- Evaluation of an exact pairing. Do not use directly. Use `ExactPairing.evaluation` instead. -/ evaluation' : Y ⊗ X ⟶ 𝟙_ C coevaluation_evaluation' : Y ◁ coevaluation' ≫ (α_ _ _ _).inv ≫ evaluation' ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv := by aesop_cat evaluation_coevaluation' : coevaluation' ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ evaluation' = (λ_ X).hom ≫ (ρ_ X).inv := by aesop_cat namespace ExactPairing -- Porting note: as there is no mechanism equivalent to `[]` in Lean 3 to make -- arguments for class fields explicit, -- we now repeat all the fields without primes. -- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Making.20variable.20in.20class.20field.20explicit variable (X Y : C) variable [ExactPairing X Y] /-- Coevaluation of an exact pairing. -/ def coevaluation : 𝟙_ C ⟶ X ⊗ Y := @coevaluation' _ _ _ X Y _ /-- Evaluation of an exact pairing. -/ def evaluation : Y ⊗ X ⟶ 𝟙_ C := @evaluation' _ _ _ X Y _ @[inherit_doc] notation "η_" => ExactPairing.coevaluation @[inherit_doc] notation "ε_" => ExactPairing.evaluation lemma coevaluation_evaluation : Y ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ ε_ X _ ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv := coevaluation_evaluation' lemma evaluation_coevaluation : η_ _ _ ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ ε_ _ Y = (λ_ X).hom ≫ (ρ_ X).inv := evaluation_coevaluation' lemma coevaluation_evaluation'' : Y ◁ η_ X Y ⊗≫ ε_ X Y ▷ Y = ⊗𝟙.hom := by convert coevaluation_evaluation X Y <;> simp [monoidalComp] lemma evaluation_coevaluation'' : η_ X Y ▷ X ⊗≫ X ◁ ε_ X Y = ⊗𝟙.hom := by convert evaluation_coevaluation X Y <;> simp [monoidalComp] end ExactPairing attribute [reassoc (attr := simp)] ExactPairing.coevaluation_evaluation attribute [reassoc (attr := simp)] ExactPairing.evaluation_coevaluation instance exactPairingUnit : ExactPairing (𝟙_ C) (𝟙_ C) where coevaluation' := (ρ_ _).inv evaluation' := (ρ_ _).hom coevaluation_evaluation' := by monoidal_coherence evaluation_coevaluation' := by monoidal_coherence /-- A class of objects which have a right dual. -/ class HasRightDual (X : C) where /-- The right dual of the object `X`. -/ rightDual : C [exact : ExactPairing X rightDual] /-- A class of objects which have a left dual. -/ class HasLeftDual (Y : C) where /-- The left dual of the object `X`. -/ leftDual : C [exact : ExactPairing leftDual Y] attribute [instance] HasRightDual.exact attribute [instance] HasLeftDual.exact open ExactPairing HasRightDual HasLeftDual MonoidalCategory #adaptation_note /-- https://github.com/leanprover/lean4/pull/4596 The overlapping notation for `leftDual` and `leftAdjointMate` become more problematic in after https://github.com/leanprover/lean4/pull/4596, and we sometimes have to disambiguate with e.g. `(ᘁX : C)` where previously just `ᘁX` was enough. -/ @[inherit_doc] prefix:1024 "ᘁ" => leftDual @[inherit_doc] postfix:1024 "ᘁ" => rightDual instance hasRightDualUnit : HasRightDual (𝟙_ C) where rightDual := 𝟙_ C instance hasLeftDualUnit : HasLeftDual (𝟙_ C) where leftDual := 𝟙_ C instance hasRightDualLeftDual {X : C} [HasLeftDual X] : HasRightDual ᘁX where rightDual := X instance hasLeftDualRightDual {X : C} [HasRightDual X] : HasLeftDual Xᘁ where leftDual := X @[simp] theorem leftDual_rightDual {X : C} [HasRightDual X] : ᘁXᘁ = X := rfl @[simp] theorem rightDual_leftDual {X : C} [HasLeftDual X] : (ᘁX)ᘁ = X := rfl /-- The right adjoint mate `fᘁ : Xᘁ ⟶ Yᘁ` of a morphism `f : X ⟶ Y`. -/ def rightAdjointMate {X Y : C} [HasRightDual X] [HasRightDual Y] (f : X ⟶ Y) : Yᘁ ⟶ Xᘁ := (ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ _ ◁ f ▷ _ ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom /-- The left adjoint mate `ᘁf : ᘁY ⟶ ᘁX` of a morphism `f : X ⟶ Y`. -/ def leftAdjointMate {X Y : C} [HasLeftDual X] [HasLeftDual Y] (f : X ⟶ Y) : ᘁY ⟶ ᘁX := (λ_ _).inv ≫ η_ (ᘁX) X ▷ _ ≫ (_ ◁ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom @[inherit_doc] notation f "ᘁ" => rightAdjointMate f @[inherit_doc] notation "ᘁ" f => leftAdjointMate f @[simp] theorem rightAdjointMate_id {X : C} [HasRightDual X] : (𝟙 X)ᘁ = 𝟙 (Xᘁ) := by simp [rightAdjointMate] @[simp] theorem leftAdjointMate_id {X : C} [HasLeftDual X] : (ᘁ(𝟙 X)) = 𝟙 (ᘁX) := by simp [leftAdjointMate] theorem rightAdjointMate_comp {X Y Z : C} [HasRightDual X] [HasRightDual Y] {f : X ⟶ Y} {g : Xᘁ ⟶ Z} : fᘁ ≫ g = (ρ_ (Yᘁ)).inv ≫ _ ◁ η_ X (Xᘁ) ≫ _ ◁ (f ⊗ g) ≫ (α_ (Yᘁ) Y Z).inv ≫ ε_ Y (Yᘁ) ▷ _ ≫ (λ_ Z).hom := calc _ = 𝟙 _ ⊗≫ (Yᘁ : C) ◁ η_ X Xᘁ ≫ Yᘁ ◁ f ▷ Xᘁ ⊗≫ (ε_ Y Yᘁ ▷ Xᘁ ≫ 𝟙_ C ◁ g) ⊗≫ 𝟙 _ := by dsimp only [rightAdjointMate]; monoidal _ = _ := by rw [← whisker_exchange, tensorHom_def]; monoidal theorem leftAdjointMate_comp {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] {f : X ⟶ Y} {g : (ᘁX) ⟶ Z} : (ᘁf) ≫ g = (λ_ _).inv ≫ η_ (ᘁX : C) X ▷ _ ≫ (g ⊗ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom := calc _ = 𝟙 _ ⊗≫ η_ (ᘁX : C) X ▷ (ᘁY) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ⊗≫ ((ᘁX) ◁ ε_ (ᘁY) Y ≫ g ▷ 𝟙_ C) ⊗≫ 𝟙 _ := by dsimp only [leftAdjointMate]; monoidal _ = _ := by rw [whisker_exchange, tensorHom_def']; monoidal /-- The composition of right adjoint mates is the adjoint mate of the composition. -/ @[reassoc] theorem comp_rightAdjointMate {X Y Z : C} [HasRightDual X] [HasRightDual Y] [HasRightDual Z] {f : X ⟶ Y} {g : Y ⟶ Z} : (f ≫ g)ᘁ = gᘁ ≫ fᘁ := by rw [rightAdjointMate_comp] simp only [rightAdjointMate, comp_whiskerRight] simp only [← Category.assoc]; congr 3; simp only [Category.assoc] simp only [← MonoidalCategory.whiskerLeft_comp]; congr 2 symm calc _ = 𝟙 _ ⊗≫ (η_ Y Yᘁ ▷ 𝟙_ C ≫ (Y ⊗ Yᘁ) ◁ η_ X Xᘁ) ⊗≫ Y ◁ Yᘁ ◁ f ▷ Xᘁ ⊗≫ Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by rw [tensorHom_def']; monoidal _ = η_ X Xᘁ ⊗≫ (η_ Y Yᘁ ▷ (X ⊗ Xᘁ) ≫ (Y ⊗ Yᘁ) ◁ f ▷ Xᘁ) ⊗≫ Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by rw [← whisker_exchange]; monoidal _ = η_ X Xᘁ ⊗≫ f ▷ Xᘁ ⊗≫ (η_ Y Yᘁ ▷ Y ⊗≫ Y ◁ ε_ Y Yᘁ) ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by rw [← whisker_exchange]; monoidal _ = η_ X Xᘁ ≫ f ▷ Xᘁ ≫ g ▷ Xᘁ := by rw [evaluation_coevaluation'']; monoidal /-- The composition of left adjoint mates is the adjoint mate of the composition. -/ @[reassoc] theorem comp_leftAdjointMate {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] [HasLeftDual Z] {f : X ⟶ Y} {g : Y ⟶ Z} : (ᘁf ≫ g) = (ᘁg) ≫ ᘁf := by rw [leftAdjointMate_comp] simp only [leftAdjointMate, MonoidalCategory.whiskerLeft_comp] simp only [← Category.assoc]; congr 3; simp only [Category.assoc] simp only [← comp_whiskerRight]; congr 2 symm calc _ = 𝟙 _ ⊗≫ ((𝟙_ C) ◁ η_ (ᘁY) Y ≫ η_ (ᘁX) X ▷ ((ᘁY) ⊗ Y)) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ▷ Y ⊗≫ (ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by rw [tensorHom_def]; monoidal _ = η_ (ᘁX) X ⊗≫ (((ᘁX) ⊗ X) ◁ η_ (ᘁY) Y ≫ ((ᘁX) ◁ f) ▷ ((ᘁY) ⊗ Y)) ⊗≫ (ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by rw [whisker_exchange]; monoidal _ = η_ (ᘁX) X ⊗≫ ((ᘁX) ◁ f) ⊗≫ (ᘁX) ◁ (Y ◁ η_ (ᘁY) Y ⊗≫ ε_ (ᘁY) Y ▷ Y) ⊗≫ (ᘁX) ◁ g := by rw [whisker_exchange]; monoidal _ = η_ (ᘁX) X ≫ (ᘁX) ◁ f ≫ (ᘁX) ◁ g := by rw [coevaluation_evaluation'']; monoidal /-- Given an exact pairing on `Y Y'`, we get a bijection on hom-sets `(Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z)` by "pulling the string on the left" up or down. This gives the adjunction `tensorLeftAdjunction Y Y' : tensorLeft Y' ⊣ tensorLeft Y`. This adjunction is often referred to as "Frobenius reciprocity" in the fusion categories / planar algebras / subfactors literature. -/ def tensorLeftHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z) where toFun f := (λ_ _).inv ≫ η_ _ _ ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ f invFun f := Y' ◁ f ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom left_inv f := by calc _ = 𝟙 _ ⊗≫ Y' ◁ η_ Y Y' ▷ X ⊗≫ ((Y' ⊗ Y) ◁ f ≫ ε_ Y Y' ▷ Z) ⊗≫ 𝟙 _ := by monoidal _ = 𝟙 _ ⊗≫ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ▷ X ⊗≫ f := by rw [whisker_exchange]; monoidal _ = f := by rw [coevaluation_evaluation'']; monoidal right_inv f := by calc _ = 𝟙 _ ⊗≫ (η_ Y Y' ▷ X ≫ (Y ⊗ Y') ◁ f) ⊗≫ Y ◁ ε_ Y Y' ▷ Z ⊗≫ 𝟙 _ := by monoidal _ = f ⊗≫ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ▷ Z ⊗≫ 𝟙 _ := by rw [← whisker_exchange]; monoidal _ = f := by rw [evaluation_coevaluation'']; monoidal /-- Given an exact pairing on `Y Y'`, we get a bijection on hom-sets `(X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y')` by "pulling the string on the right" up or down. -/ def tensorRightHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y') where toFun f := (ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ f ▷ _ invFun f := f ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom left_inv f := by calc _ = 𝟙 _ ⊗≫ X ◁ η_ Y Y' ▷ Y ⊗≫ (f ▷ (Y' ⊗ Y) ≫ Z ◁ ε_ Y Y') ⊗≫ 𝟙 _ := by monoidal _ = 𝟙 _ ⊗≫ X ◁ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ⊗≫ f := by rw [← whisker_exchange]; monoidal _ = f := by rw [evaluation_coevaluation'']; monoidal right_inv f := by calc _ = 𝟙 _ ⊗≫ (X ◁ η_ Y Y' ≫ f ▷ (Y ⊗ Y')) ⊗≫ Z ◁ ε_ Y Y' ▷ Y' ⊗≫ 𝟙 _ := by monoidal _ = f ⊗≫ Z ◁ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ⊗≫ 𝟙 _ := by rw [whisker_exchange]; monoidal _ = f := by rw [coevaluation_evaluation'']; monoidal theorem tensorLeftHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : Y' ⊗ X ⟶ Z) (g : Z ⟶ Z') : (tensorLeftHomEquiv X Y Y' Z') (f ≫ g) = (tensorLeftHomEquiv X Y Y' Z) f ≫ Y ◁ g := by simp [tensorLeftHomEquiv] theorem tensorLeftHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X') (g : X' ⟶ Y ⊗ Z) : (tensorLeftHomEquiv X Y Y' Z).symm (f ≫ g) = _ ◁ f ≫ (tensorLeftHomEquiv X' Y Y' Z).symm g := by simp [tensorLeftHomEquiv] theorem tensorRightHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⊗ Y ⟶ Z) (g : Z ⟶ Z') : (tensorRightHomEquiv X Y Y' Z') (f ≫ g) = (tensorRightHomEquiv X Y Y' Z) f ≫ g ▷ Y' := by simp [tensorRightHomEquiv] theorem tensorRightHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X') (g : X' ⟶ Z ⊗ Y') : (tensorRightHomEquiv X Y Y' Z).symm (f ≫ g) = f ▷ Y ≫ (tensorRightHomEquiv X' Y Y' Z).symm g := by simp [tensorRightHomEquiv] /-- If `Y Y'` have an exact pairing, then the functor `tensorLeft Y'` is left adjoint to `tensorLeft Y`.
-/ def tensorLeftAdjunction (Y Y' : C) [ExactPairing Y Y'] : tensorLeft Y' ⊣ tensorLeft Y := Adjunction.mkOfHomEquiv { homEquiv := fun X Z => tensorLeftHomEquiv X Y Y' Z homEquiv_naturality_left_symm := fun f g => tensorLeftHomEquiv_symm_naturality f g
Mathlib/CategoryTheory/Monoidal/Rigid/Basic.lean
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/- 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) := angle_eq_iff_two_pi_dvd_sub.2 ⟨1, by rw [sub_zero, Int.cast_one, mul_one]⟩ @[simp] theorem neg_coe_pi : -(π : Angle) = π := by rw [← coe_neg, angle_eq_iff_two_pi_dvd_sub] use -1 simp [two_mul, sub_eq_add_neg] @[simp] theorem two_nsmul_coe_div_two (θ : ℝ) : (2 : ℕ) • (↑(θ / 2) : Angle) = θ := by rw [← coe_nsmul, two_nsmul, add_halves] @[simp] theorem two_zsmul_coe_div_two (θ : ℝ) : (2 : ℤ) • (↑(θ / 2) : Angle) = θ := by rw [← coe_zsmul, two_zsmul, add_halves] theorem two_nsmul_neg_pi_div_two : (2 : ℕ) • (↑(-π / 2) : Angle) = π := by rw [two_nsmul_coe_div_two, coe_neg, neg_coe_pi] theorem two_zsmul_neg_pi_div_two : (2 : ℤ) • (↑(-π / 2) : Angle) = π := by rw [two_zsmul, ← two_nsmul, two_nsmul_neg_pi_div_two] theorem sub_coe_pi_eq_add_coe_pi (θ : Angle) : θ - π = θ + π := by rw [sub_eq_add_neg, neg_coe_pi] @[simp] theorem two_nsmul_coe_pi : (2 : ℕ) • (π : Angle) = 0 := by simp [← natCast_mul_eq_nsmul] @[simp] theorem two_zsmul_coe_pi : (2 : ℤ) • (π : Angle) = 0 := by simp [← intCast_mul_eq_zsmul] @[simp] theorem coe_pi_add_coe_pi : (π : Real.Angle) + π = 0 := by rw [← two_nsmul, two_nsmul_coe_pi] theorem zsmul_eq_iff {ψ θ : Angle} {z : ℤ} (hz : z ≠ 0) : z • ψ = z • θ ↔ ∃ k : Fin z.natAbs, ψ = θ + (k : ℕ) • (2 * π / z : ℝ) := QuotientAddGroup.zmultiples_zsmul_eq_zsmul_iff hz theorem nsmul_eq_iff {ψ θ : Angle} {n : ℕ} (hz : n ≠ 0) : n • ψ = n • θ ↔ ∃ k : Fin n, ψ = θ + (k : ℕ) • (2 * π / n : ℝ) := QuotientAddGroup.zmultiples_nsmul_eq_nsmul_iff hz theorem two_zsmul_eq_iff {ψ θ : Angle} : (2 : ℤ) • ψ = (2 : ℤ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by have : Int.natAbs 2 = 2 := rfl rw [zsmul_eq_iff two_ne_zero, this, Fin.exists_fin_two, Fin.val_zero, Fin.val_one, zero_smul, add_zero, one_smul, Int.cast_two, mul_div_cancel_left₀ (_ : ℝ) two_ne_zero] theorem two_nsmul_eq_iff {ψ θ : Angle} : (2 : ℕ) • ψ = (2 : ℕ) • θ ↔ ψ = θ ∨ ψ = θ + ↑π := by simp_rw [← natCast_zsmul, Nat.cast_ofNat, two_zsmul_eq_iff] theorem two_nsmul_eq_zero_iff {θ : Angle} : (2 : ℕ) • θ = 0 ↔ θ = 0 ∨ θ = π := by convert two_nsmul_eq_iff <;> simp theorem two_nsmul_ne_zero_iff {θ : Angle} : (2 : ℕ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← two_nsmul_eq_zero_iff] theorem two_zsmul_eq_zero_iff {θ : Angle} : (2 : ℤ) • θ = 0 ↔ θ = 0 ∨ θ = π := by simp_rw [two_zsmul, ← two_nsmul, two_nsmul_eq_zero_iff] theorem two_zsmul_ne_zero_iff {θ : Angle} : (2 : ℤ) • θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← two_zsmul_eq_zero_iff] theorem eq_neg_self_iff {θ : Angle} : θ = -θ ↔ θ = 0 ∨ θ = π := by rw [← add_eq_zero_iff_eq_neg, ← two_nsmul, two_nsmul_eq_zero_iff] theorem ne_neg_self_iff {θ : Angle} : θ ≠ -θ ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← eq_neg_self_iff.not] theorem neg_eq_self_iff {θ : Angle} : -θ = θ ↔ θ = 0 ∨ θ = π := by rw [eq_comm, eq_neg_self_iff] theorem neg_ne_self_iff {θ : Angle} : -θ ≠ θ ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← neg_eq_self_iff.not] theorem two_nsmul_eq_pi_iff {θ : Angle} : (2 : ℕ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by have h : (π : Angle) = ((2 : ℕ) • (π / 2 : ℝ):) := by rw [two_nsmul, add_halves] nth_rw 1 [h] rw [coe_nsmul, two_nsmul_eq_iff] -- Porting note: `congr` didn't simplify the goal of iff of `Or`s convert Iff.rfl rw [add_comm, ← coe_add, ← sub_eq_zero, ← coe_sub, neg_div, ← neg_sub, sub_neg_eq_add, add_assoc, add_halves, ← two_mul, coe_neg, coe_two_pi, neg_zero] theorem two_zsmul_eq_pi_iff {θ : Angle} : (2 : ℤ) • θ = π ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by rw [two_zsmul, ← two_nsmul, two_nsmul_eq_pi_iff] theorem cos_eq_iff_coe_eq_or_eq_neg {θ ψ : ℝ} : cos θ = cos ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) = -ψ := by constructor · intro Hcos rw [← sub_eq_zero, cos_sub_cos, mul_eq_zero, mul_eq_zero, neg_eq_zero, eq_false (two_ne_zero' ℝ), false_or, sin_eq_zero_iff, sin_eq_zero_iff] at Hcos rcases Hcos with (⟨n, hn⟩ | ⟨n, hn⟩) · right rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), ← sub_eq_iff_eq_add] at hn rw [← hn, coe_sub, eq_neg_iff_add_eq_zero, sub_add_cancel, mul_assoc, intCast_mul_eq_zsmul, mul_comm, coe_two_pi, zsmul_zero] · left rw [eq_div_iff_mul_eq (two_ne_zero' ℝ), eq_sub_iff_add_eq] at hn rw [← hn, coe_add, mul_assoc, intCast_mul_eq_zsmul, mul_comm, coe_two_pi, zsmul_zero, zero_add] · rw [angle_eq_iff_two_pi_dvd_sub, ← coe_neg, angle_eq_iff_two_pi_dvd_sub] rintro (⟨k, H⟩ | ⟨k, H⟩) · rw [← sub_eq_zero, cos_sub_cos, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero] rw [← sub_eq_zero, cos_sub_cos, ← sub_neg_eq_add, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero, zero_mul] theorem sin_eq_iff_coe_eq_or_add_eq_pi {θ ψ : ℝ} : sin θ = sin ψ ↔ (θ : Angle) = ψ ∨ (θ : Angle) + ψ = π := by constructor · intro Hsin rw [← cos_pi_div_two_sub, ← cos_pi_div_two_sub] at Hsin rcases cos_eq_iff_coe_eq_or_eq_neg.mp Hsin with h | h · left rw [coe_sub, coe_sub] at h exact sub_right_inj.1 h right rw [coe_sub, coe_sub, eq_neg_iff_add_eq_zero, add_sub, sub_add_eq_add_sub, ← coe_add, add_halves, sub_sub, sub_eq_zero] at h exact h.symm · rw [angle_eq_iff_two_pi_dvd_sub, ← eq_sub_iff_add_eq, ← coe_sub, angle_eq_iff_two_pi_dvd_sub] rintro (⟨k, H⟩ | ⟨k, H⟩) · rw [← sub_eq_zero, sin_sub_sin, H, mul_assoc 2 π k, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), mul_comm π _, sin_int_mul_pi, mul_zero, zero_mul] have H' : θ + ψ = 2 * k * π + π := by rwa [← sub_add, sub_add_eq_add_sub, sub_eq_iff_eq_add, mul_assoc, mul_comm π _, ← mul_assoc] at H rw [← sub_eq_zero, sin_sub_sin, H', add_div, mul_assoc 2 _ π, mul_div_cancel_left₀ _ (two_ne_zero' ℝ), cos_add_pi_div_two, sin_int_mul_pi, neg_zero, mul_zero] theorem cos_sin_inj {θ ψ : ℝ} (Hcos : cos θ = cos ψ) (Hsin : sin θ = sin ψ) : (θ : Angle) = ψ := by rcases cos_eq_iff_coe_eq_or_eq_neg.mp Hcos with hc | hc; · exact hc rcases sin_eq_iff_coe_eq_or_add_eq_pi.mp Hsin with hs | hs; · exact hs rw [eq_neg_iff_add_eq_zero, hs] at hc obtain ⟨n, hn⟩ : ∃ n, n • _ = _ := QuotientAddGroup.leftRel_apply.mp (Quotient.exact' hc) rw [← neg_one_mul, add_zero, ← sub_eq_zero, zsmul_eq_mul, ← mul_assoc, ← sub_mul, mul_eq_zero, eq_false (ne_of_gt pi_pos), or_false, sub_neg_eq_add, ← Int.cast_zero, ← Int.cast_one, ← Int.cast_ofNat, ← Int.cast_mul, ← Int.cast_add, Int.cast_inj] at hn have : (n * 2 + 1) % (2 : ℤ) = 0 % (2 : ℤ) := congr_arg (· % (2 : ℤ)) hn rw [add_comm, Int.add_mul_emod_self_right] at this exact absurd this one_ne_zero /-- The sine of a `Real.Angle`. -/ def sin (θ : Angle) : ℝ := sin_periodic.lift θ @[simp] theorem sin_coe (x : ℝ) : sin (x : Angle) = Real.sin x := rfl @[continuity] theorem continuous_sin : Continuous sin := Real.continuous_sin.quotient_liftOn' _ /-- The cosine of a `Real.Angle`. -/ def cos (θ : Angle) : ℝ := cos_periodic.lift θ @[simp] theorem cos_coe (x : ℝ) : cos (x : Angle) = Real.cos x := rfl @[continuity] theorem continuous_cos : Continuous cos := Real.continuous_cos.quotient_liftOn' _ theorem cos_eq_real_cos_iff_eq_or_eq_neg {θ : Angle} {ψ : ℝ} : cos θ = Real.cos ψ ↔ θ = ψ ∨ θ = -ψ := by induction θ using Real.Angle.induction_on exact cos_eq_iff_coe_eq_or_eq_neg theorem cos_eq_iff_eq_or_eq_neg {θ ψ : Angle} : cos θ = cos ψ ↔ θ = ψ ∨ θ = -ψ := by induction ψ using Real.Angle.induction_on exact cos_eq_real_cos_iff_eq_or_eq_neg theorem sin_eq_real_sin_iff_eq_or_add_eq_pi {θ : Angle} {ψ : ℝ} : sin θ = Real.sin ψ ↔ θ = ψ ∨ θ + ψ = π := by induction θ using Real.Angle.induction_on exact sin_eq_iff_coe_eq_or_add_eq_pi theorem sin_eq_iff_eq_or_add_eq_pi {θ ψ : Angle} : sin θ = sin ψ ↔ θ = ψ ∨ θ + ψ = π := by induction ψ using Real.Angle.induction_on exact sin_eq_real_sin_iff_eq_or_add_eq_pi @[simp] theorem sin_zero : sin (0 : Angle) = 0 := by rw [← coe_zero, sin_coe, Real.sin_zero] theorem sin_coe_pi : sin (π : Angle) = 0 := by rw [sin_coe, Real.sin_pi] theorem sin_eq_zero_iff {θ : Angle} : sin θ = 0 ↔ θ = 0 ∨ θ = π := by nth_rw 1 [← sin_zero] rw [sin_eq_iff_eq_or_add_eq_pi] simp theorem sin_ne_zero_iff {θ : Angle} : sin θ ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← sin_eq_zero_iff] @[simp] theorem sin_neg (θ : Angle) : sin (-θ) = -sin θ := by induction θ using Real.Angle.induction_on exact Real.sin_neg _ theorem sin_antiperiodic : Function.Antiperiodic sin (π : Angle) := by intro θ induction θ using Real.Angle.induction_on exact Real.sin_antiperiodic _ @[simp] theorem sin_add_pi (θ : Angle) : sin (θ + π) = -sin θ := sin_antiperiodic θ @[simp] theorem sin_sub_pi (θ : Angle) : sin (θ - π) = -sin θ := sin_antiperiodic.sub_eq θ @[simp] theorem cos_zero : cos (0 : Angle) = 1 := by rw [← coe_zero, cos_coe, Real.cos_zero] theorem cos_coe_pi : cos (π : Angle) = -1 := by rw [cos_coe, Real.cos_pi] @[simp] theorem cos_neg (θ : Angle) : cos (-θ) = cos θ := by induction θ using Real.Angle.induction_on exact Real.cos_neg _ theorem cos_antiperiodic : Function.Antiperiodic cos (π : Angle) := by intro θ induction θ using Real.Angle.induction_on exact Real.cos_antiperiodic _ @[simp] theorem cos_add_pi (θ : Angle) : cos (θ + π) = -cos θ := cos_antiperiodic θ @[simp] theorem cos_sub_pi (θ : Angle) : cos (θ - π) = -cos θ := cos_antiperiodic.sub_eq θ theorem cos_eq_zero_iff {θ : Angle} : cos θ = 0 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by rw [← cos_pi_div_two, ← cos_coe, cos_eq_iff_eq_or_eq_neg, ← coe_neg, ← neg_div] theorem sin_add (θ₁ θ₂ : Real.Angle) : sin (θ₁ + θ₂) = sin θ₁ * cos θ₂ + cos θ₁ * sin θ₂ := by induction θ₁ using Real.Angle.induction_on induction θ₂ using Real.Angle.induction_on exact Real.sin_add _ _ theorem cos_add (θ₁ θ₂ : Real.Angle) : cos (θ₁ + θ₂) = cos θ₁ * cos θ₂ - sin θ₁ * sin θ₂ := by induction θ₂ using Real.Angle.induction_on induction θ₁ using Real.Angle.induction_on exact Real.cos_add _ _ @[simp] theorem cos_sq_add_sin_sq (θ : Real.Angle) : cos θ ^ 2 + sin θ ^ 2 = 1 := by induction θ using Real.Angle.induction_on exact Real.cos_sq_add_sin_sq _ theorem sin_add_pi_div_two (θ : Angle) : sin (θ + ↑(π / 2)) = cos θ := by induction θ using Real.Angle.induction_on exact Real.sin_add_pi_div_two _ theorem sin_sub_pi_div_two (θ : Angle) : sin (θ - ↑(π / 2)) = -cos θ := by induction θ using Real.Angle.induction_on exact Real.sin_sub_pi_div_two _ theorem sin_pi_div_two_sub (θ : Angle) : sin (↑(π / 2) - θ) = cos θ := by induction θ using Real.Angle.induction_on exact Real.sin_pi_div_two_sub _ theorem cos_add_pi_div_two (θ : Angle) : cos (θ + ↑(π / 2)) = -sin θ := by induction θ using Real.Angle.induction_on exact Real.cos_add_pi_div_two _ theorem cos_sub_pi_div_two (θ : Angle) : cos (θ - ↑(π / 2)) = sin θ := by induction θ using Real.Angle.induction_on exact Real.cos_sub_pi_div_two _ theorem cos_pi_div_two_sub (θ : Angle) : cos (↑(π / 2) - θ) = sin θ := by induction θ using Real.Angle.induction_on exact Real.cos_pi_div_two_sub _ theorem abs_sin_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) : |sin θ| = |sin ψ| := by rw [two_nsmul_eq_iff] at h rcases h with (rfl | rfl) · rfl · rw [sin_add_pi, abs_neg] theorem abs_sin_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) : |sin θ| = |sin ψ| := by simp_rw [two_zsmul, ← two_nsmul] at h exact abs_sin_eq_of_two_nsmul_eq h theorem abs_cos_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) : |cos θ| = |cos ψ| := by rw [two_nsmul_eq_iff] at h rcases h with (rfl | rfl) · rfl · rw [cos_add_pi, abs_neg] theorem abs_cos_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) : |cos θ| = |cos ψ| := by simp_rw [two_zsmul, ← two_nsmul] at h exact abs_cos_eq_of_two_nsmul_eq h @[simp] theorem coe_toIcoMod (θ ψ : ℝ) : ↑(toIcoMod two_pi_pos ψ θ) = (θ : Angle) := by rw [angle_eq_iff_two_pi_dvd_sub] refine ⟨-toIcoDiv two_pi_pos ψ θ, ?_⟩ rw [toIcoMod_sub_self, zsmul_eq_mul, mul_comm] @[simp] theorem coe_toIocMod (θ ψ : ℝ) : ↑(toIocMod two_pi_pos ψ θ) = (θ : Angle) := by rw [angle_eq_iff_two_pi_dvd_sub] refine ⟨-toIocDiv two_pi_pos ψ θ, ?_⟩ rw [toIocMod_sub_self, zsmul_eq_mul, mul_comm] /-- Convert a `Real.Angle` to a real number in the interval `Ioc (-π) π`. -/ def toReal (θ : Angle) : ℝ := (toIocMod_periodic two_pi_pos (-π)).lift θ theorem toReal_coe (θ : ℝ) : (θ : Angle).toReal = toIocMod two_pi_pos (-π) θ := rfl theorem toReal_coe_eq_self_iff {θ : ℝ} : (θ : Angle).toReal = θ ↔ -π < θ ∧ θ ≤ π := by rw [toReal_coe, toIocMod_eq_self two_pi_pos] ring_nf rfl theorem toReal_coe_eq_self_iff_mem_Ioc {θ : ℝ} : (θ : Angle).toReal = θ ↔ θ ∈ Set.Ioc (-π) π := by rw [toReal_coe_eq_self_iff, ← Set.mem_Ioc] theorem toReal_injective : Function.Injective toReal := by intro θ ψ h induction θ using Real.Angle.induction_on induction ψ using Real.Angle.induction_on simpa [toReal_coe, toIocMod_eq_toIocMod, zsmul_eq_mul, mul_comm _ (2 * π), ← angle_eq_iff_two_pi_dvd_sub, eq_comm] using h @[simp] theorem toReal_inj {θ ψ : Angle} : θ.toReal = ψ.toReal ↔ θ = ψ := toReal_injective.eq_iff @[simp] theorem coe_toReal (θ : Angle) : (θ.toReal : Angle) = θ := by induction θ using Real.Angle.induction_on exact coe_toIocMod _ _ theorem neg_pi_lt_toReal (θ : Angle) : -π < θ.toReal := by induction θ using Real.Angle.induction_on exact left_lt_toIocMod _ _ _ theorem toReal_le_pi (θ : Angle) : θ.toReal ≤ π := by induction θ using Real.Angle.induction_on convert toIocMod_le_right two_pi_pos _ _ ring theorem abs_toReal_le_pi (θ : Angle) : |θ.toReal| ≤ π := abs_le.2 ⟨(neg_pi_lt_toReal _).le, toReal_le_pi _⟩ theorem toReal_mem_Ioc (θ : Angle) : θ.toReal ∈ Set.Ioc (-π) π := ⟨neg_pi_lt_toReal _, toReal_le_pi _⟩ @[simp] theorem toIocMod_toReal (θ : Angle) : toIocMod two_pi_pos (-π) θ.toReal = θ.toReal := by induction θ using Real.Angle.induction_on rw [toReal_coe] exact toIocMod_toIocMod _ _ _ _ @[simp] theorem toReal_zero : (0 : Angle).toReal = 0 := by rw [← coe_zero, toReal_coe_eq_self_iff] exact ⟨Left.neg_neg_iff.2 Real.pi_pos, Real.pi_pos.le⟩ @[simp] theorem toReal_eq_zero_iff {θ : Angle} : θ.toReal = 0 ↔ θ = 0 := by nth_rw 1 [← toReal_zero] exact toReal_inj @[simp] theorem toReal_pi : (π : Angle).toReal = π := by rw [toReal_coe_eq_self_iff] exact ⟨Left.neg_lt_self Real.pi_pos, le_refl _⟩ @[simp] theorem toReal_eq_pi_iff {θ : Angle} : θ.toReal = π ↔ θ = π := by rw [← toReal_inj, toReal_pi] theorem pi_ne_zero : (π : Angle) ≠ 0 := by rw [← toReal_injective.ne_iff, toReal_pi, toReal_zero] exact Real.pi_ne_zero @[simp] theorem toReal_pi_div_two : ((π / 2 : ℝ) : Angle).toReal = π / 2 := toReal_coe_eq_self_iff.2 <| by constructor <;> linarith [pi_pos] @[simp] theorem toReal_eq_pi_div_two_iff {θ : Angle} : θ.toReal = π / 2 ↔ θ = (π / 2 : ℝ) := by rw [← toReal_inj, toReal_pi_div_two] @[simp] theorem toReal_neg_pi_div_two : ((-π / 2 : ℝ) : Angle).toReal = -π / 2 := toReal_coe_eq_self_iff.2 <| by constructor <;> linarith [pi_pos] @[simp] theorem toReal_eq_neg_pi_div_two_iff {θ : Angle} : θ.toReal = -π / 2 ↔ θ = (-π / 2 : ℝ) := by rw [← toReal_inj, toReal_neg_pi_div_two] theorem pi_div_two_ne_zero : ((π / 2 : ℝ) : Angle) ≠ 0 := by rw [← toReal_injective.ne_iff, toReal_pi_div_two, toReal_zero] exact div_ne_zero Real.pi_ne_zero two_ne_zero theorem neg_pi_div_two_ne_zero : ((-π / 2 : ℝ) : Angle) ≠ 0 := by rw [← toReal_injective.ne_iff, toReal_neg_pi_div_two, toReal_zero] exact div_ne_zero (neg_ne_zero.2 Real.pi_ne_zero) two_ne_zero theorem abs_toReal_coe_eq_self_iff {θ : ℝ} : |(θ : Angle).toReal| = θ ↔ 0 ≤ θ ∧ θ ≤ π := ⟨fun h => h ▸ ⟨abs_nonneg _, abs_toReal_le_pi _⟩, fun h => (toReal_coe_eq_self_iff.2 ⟨(Left.neg_neg_iff.2 Real.pi_pos).trans_le h.1, h.2⟩).symm ▸ abs_eq_self.2 h.1⟩ theorem abs_toReal_neg_coe_eq_self_iff {θ : ℝ} : |(-θ : Angle).toReal| = θ ↔ 0 ≤ θ ∧ θ ≤ π := by refine ⟨fun h => h ▸ ⟨abs_nonneg _, abs_toReal_le_pi _⟩, fun h => ?_⟩ by_cases hnegpi : θ = π; · simp [hnegpi, Real.pi_pos.le] rw [← coe_neg, toReal_coe_eq_self_iff.2 ⟨neg_lt_neg (lt_of_le_of_ne h.2 hnegpi), (neg_nonpos.2 h.1).trans Real.pi_pos.le⟩, abs_neg, abs_eq_self.2 h.1] theorem abs_toReal_eq_pi_div_two_iff {θ : Angle} : |θ.toReal| = π / 2 ↔ θ = (π / 2 : ℝ) ∨ θ = (-π / 2 : ℝ) := by rw [abs_eq (div_nonneg Real.pi_pos.le two_pos.le), ← neg_div, toReal_eq_pi_div_two_iff, toReal_eq_neg_pi_div_two_iff] theorem nsmul_toReal_eq_mul {n : ℕ} (h : n ≠ 0) {θ : Angle} : (n • θ).toReal = n * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / n) (π / n) := by nth_rw 1 [← coe_toReal θ] have h' : 0 < (n : ℝ) := mod_cast Nat.pos_of_ne_zero h rw [← coe_nsmul, nsmul_eq_mul, toReal_coe_eq_self_iff, Set.mem_Ioc, div_lt_iff₀' h', le_div_iff₀' h'] theorem two_nsmul_toReal_eq_two_mul {θ : Angle} : ((2 : ℕ) • θ).toReal = 2 * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / 2) (π / 2) := mod_cast nsmul_toReal_eq_mul two_ne_zero theorem two_zsmul_toReal_eq_two_mul {θ : Angle} : ((2 : ℤ) • θ).toReal = 2 * θ.toReal ↔ θ.toReal ∈ Set.Ioc (-π / 2) (π / 2) := by rw [two_zsmul, ← two_nsmul, two_nsmul_toReal_eq_two_mul] theorem toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff {θ : ℝ} {k : ℤ} : (θ : Angle).toReal = θ - 2 * k * π ↔ θ ∈ Set.Ioc ((2 * k - 1 : ℝ) * π) ((2 * k + 1) * π) := by rw [← sub_zero (θ : Angle), ← zsmul_zero k, ← coe_two_pi, ← coe_zsmul, ← coe_sub, zsmul_eq_mul, ← mul_assoc, mul_comm (k : ℝ), toReal_coe_eq_self_iff, Set.mem_Ioc] exact ⟨fun h => ⟨by linarith, by linarith⟩, fun h => ⟨by linarith, by linarith⟩⟩ theorem toReal_coe_eq_self_sub_two_pi_iff {θ : ℝ} : (θ : Angle).toReal = θ - 2 * π ↔ θ ∈ Set.Ioc π (3 * π) := by convert @toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff θ 1 <;> norm_num theorem toReal_coe_eq_self_add_two_pi_iff {θ : ℝ} : (θ : Angle).toReal = θ + 2 * π ↔ θ ∈ Set.Ioc (-3 * π) (-π) := by convert @toReal_coe_eq_self_sub_two_mul_int_mul_pi_iff θ (-1) using 2 <;> norm_num theorem two_nsmul_toReal_eq_two_mul_sub_two_pi {θ : Angle} : ((2 : ℕ) • θ).toReal = 2 * θ.toReal - 2 * π ↔ π / 2 < θ.toReal := by nth_rw 1 [← coe_toReal θ] rw [← coe_nsmul, two_nsmul, ← two_mul, toReal_coe_eq_self_sub_two_pi_iff, Set.mem_Ioc] exact ⟨fun h => by linarith, fun h => ⟨(div_lt_iff₀' (zero_lt_two' ℝ)).1 h, by linarith [pi_pos, toReal_le_pi θ]⟩⟩ theorem two_zsmul_toReal_eq_two_mul_sub_two_pi {θ : Angle} : ((2 : ℤ) • θ).toReal = 2 * θ.toReal - 2 * π ↔ π / 2 < θ.toReal := by rw [two_zsmul, ← two_nsmul, two_nsmul_toReal_eq_two_mul_sub_two_pi] theorem two_nsmul_toReal_eq_two_mul_add_two_pi {θ : Angle} : ((2 : ℕ) • θ).toReal = 2 * θ.toReal + 2 * π ↔ θ.toReal ≤ -π / 2 := by nth_rw 1 [← coe_toReal θ] rw [← coe_nsmul, two_nsmul, ← two_mul, toReal_coe_eq_self_add_two_pi_iff, Set.mem_Ioc] refine ⟨fun h => by linarith, fun h => ⟨by linarith [pi_pos, neg_pi_lt_toReal θ], (le_div_iff₀' (zero_lt_two' ℝ)).1 h⟩⟩ theorem two_zsmul_toReal_eq_two_mul_add_two_pi {θ : Angle} : ((2 : ℤ) • θ).toReal = 2 * θ.toReal + 2 * π ↔ θ.toReal ≤ -π / 2 := by rw [two_zsmul, ← two_nsmul, two_nsmul_toReal_eq_two_mul_add_two_pi] @[simp] theorem sin_toReal (θ : Angle) : Real.sin θ.toReal = sin θ := by conv_rhs => rw [← coe_toReal θ, sin_coe] @[simp] theorem cos_toReal (θ : Angle) : Real.cos θ.toReal = cos θ := by conv_rhs => rw [← coe_toReal θ, cos_coe] theorem cos_nonneg_iff_abs_toReal_le_pi_div_two {θ : Angle} : 0 ≤ cos θ ↔ |θ.toReal| ≤ π / 2 := by nth_rw 1 [← coe_toReal θ] rw [abs_le, cos_coe] refine ⟨fun h => ?_, cos_nonneg_of_mem_Icc⟩ by_contra hn rw [not_and_or, not_le, not_le] at hn refine (not_lt.2 h) ?_ rcases hn with (hn | hn) · rw [← Real.cos_neg] refine cos_neg_of_pi_div_two_lt_of_lt (by linarith) ?_ linarith [neg_pi_lt_toReal θ] · refine cos_neg_of_pi_div_two_lt_of_lt hn ?_ linarith [toReal_le_pi θ] theorem cos_pos_iff_abs_toReal_lt_pi_div_two {θ : Angle} : 0 < cos θ ↔ |θ.toReal| < π / 2 := by rw [lt_iff_le_and_ne, lt_iff_le_and_ne, cos_nonneg_iff_abs_toReal_le_pi_div_two, ← and_congr_right] rintro - rw [Ne, Ne, not_iff_not, @eq_comm ℝ 0, abs_toReal_eq_pi_div_two_iff, cos_eq_zero_iff] theorem cos_neg_iff_pi_div_two_lt_abs_toReal {θ : Angle} : cos θ < 0 ↔ π / 2 < |θ.toReal| := by rw [← not_le, ← not_le, not_iff_not, cos_nonneg_iff_abs_toReal_le_pi_div_two] theorem abs_cos_eq_abs_sin_of_two_nsmul_add_two_nsmul_eq_pi {θ ψ : Angle} (h : (2 : ℕ) • θ + (2 : ℕ) • ψ = π) : |cos θ| = |sin ψ| := by rw [← eq_sub_iff_add_eq, ← two_nsmul_coe_div_two, ← nsmul_sub, two_nsmul_eq_iff] at h rcases h with (rfl | rfl) <;> simp [cos_pi_div_two_sub] theorem abs_cos_eq_abs_sin_of_two_zsmul_add_two_zsmul_eq_pi {θ ψ : Angle} (h : (2 : ℤ) • θ + (2 : ℤ) • ψ = π) : |cos θ| = |sin ψ| := by simp_rw [two_zsmul, ← two_nsmul] at h exact abs_cos_eq_abs_sin_of_two_nsmul_add_two_nsmul_eq_pi h /-- The tangent of a `Real.Angle`. -/ def tan (θ : Angle) : ℝ := sin θ / cos θ theorem tan_eq_sin_div_cos (θ : Angle) : tan θ = sin θ / cos θ := rfl @[simp] theorem tan_coe (x : ℝ) : tan (x : Angle) = Real.tan x := by rw [tan, sin_coe, cos_coe, Real.tan_eq_sin_div_cos] @[simp] theorem tan_zero : tan (0 : Angle) = 0 := by rw [← coe_zero, tan_coe, Real.tan_zero] theorem tan_coe_pi : tan (π : Angle) = 0 := by rw [tan_coe, Real.tan_pi] theorem tan_periodic : Function.Periodic tan (π : Angle) := by intro θ induction θ using Real.Angle.induction_on rw [← coe_add, tan_coe, tan_coe] exact Real.tan_periodic _ @[simp] theorem tan_add_pi (θ : Angle) : tan (θ + π) = tan θ := tan_periodic θ @[simp] theorem tan_sub_pi (θ : Angle) : tan (θ - π) = tan θ := tan_periodic.sub_eq θ @[simp] theorem tan_toReal (θ : Angle) : Real.tan θ.toReal = tan θ := by conv_rhs => rw [← coe_toReal θ, tan_coe] theorem tan_eq_of_two_nsmul_eq {θ ψ : Angle} (h : (2 : ℕ) • θ = (2 : ℕ) • ψ) : tan θ = tan ψ := by rw [two_nsmul_eq_iff] at h rcases h with (rfl | rfl) · rfl · exact tan_add_pi _ theorem tan_eq_of_two_zsmul_eq {θ ψ : Angle} (h : (2 : ℤ) • θ = (2 : ℤ) • ψ) : tan θ = tan ψ := by simp_rw [two_zsmul, ← two_nsmul] at h exact tan_eq_of_two_nsmul_eq h theorem tan_eq_inv_of_two_nsmul_add_two_nsmul_eq_pi {θ ψ : Angle} (h : (2 : ℕ) • θ + (2 : ℕ) • ψ = π) : tan ψ = (tan θ)⁻¹ := by induction θ using Real.Angle.induction_on induction ψ using Real.Angle.induction_on rw [← smul_add, ← coe_add, ← coe_nsmul, two_nsmul, ← two_mul, angle_eq_iff_two_pi_dvd_sub] at h rcases h with ⟨k, h⟩ rw [sub_eq_iff_eq_add, ← mul_inv_cancel_left₀ two_ne_zero π, mul_assoc, ← mul_add, mul_right_inj' (two_ne_zero' ℝ), ← eq_sub_iff_add_eq', mul_inv_cancel_left₀ two_ne_zero π, inv_mul_eq_div, mul_comm] at h rw [tan_coe, tan_coe, ← tan_pi_div_two_sub, h, add_sub_assoc, add_comm] exact Real.tan_periodic.int_mul _ _ theorem tan_eq_inv_of_two_zsmul_add_two_zsmul_eq_pi {θ ψ : Angle} (h : (2 : ℤ) • θ + (2 : ℤ) • ψ = π) : tan ψ = (tan θ)⁻¹ := by simp_rw [two_zsmul, ← two_nsmul] at h exact tan_eq_inv_of_two_nsmul_add_two_nsmul_eq_pi h /-- The sign of a `Real.Angle` is `0` if the angle is `0` or `π`, `1` if the angle is strictly between `0` and `π` and `-1` is the angle is strictly between `-π` and `0`. It is defined as the sign of the sine of the angle. -/ def sign (θ : Angle) : SignType := SignType.sign (sin θ) @[simp] theorem sign_zero : (0 : Angle).sign = 0 := by rw [sign, sin_zero, _root_.sign_zero] @[simp] theorem sign_coe_pi : (π : Angle).sign = 0 := by rw [sign, sin_coe_pi, _root_.sign_zero] @[simp] theorem sign_neg (θ : Angle) : (-θ).sign = -θ.sign := by simp_rw [sign, sin_neg, Left.sign_neg] theorem sign_antiperiodic : Function.Antiperiodic sign (π : Angle) := fun θ => by rw [sign, sign, sin_add_pi, Left.sign_neg] @[simp] theorem sign_add_pi (θ : Angle) : (θ + π).sign = -θ.sign := sign_antiperiodic θ @[simp] theorem sign_pi_add (θ : Angle) : ((π : Angle) + θ).sign = -θ.sign := by rw [add_comm, sign_add_pi] @[simp] theorem sign_sub_pi (θ : Angle) : (θ - π).sign = -θ.sign := sign_antiperiodic.sub_eq θ @[simp] theorem sign_pi_sub (θ : Angle) : ((π : Angle) - θ).sign = θ.sign := by simp [sign_antiperiodic.sub_eq'] theorem sign_eq_zero_iff {θ : Angle} : θ.sign = 0 ↔ θ = 0 ∨ θ = π := by rw [sign, _root_.sign_eq_zero_iff, sin_eq_zero_iff] theorem sign_ne_zero_iff {θ : Angle} : θ.sign ≠ 0 ↔ θ ≠ 0 ∧ θ ≠ π := by rw [← not_or, ← sign_eq_zero_iff] theorem toReal_neg_iff_sign_neg {θ : Angle} : θ.toReal < 0 ↔ θ.sign = -1 := by rw [sign, ← sin_toReal, sign_eq_neg_one_iff] rcases lt_trichotomy θ.toReal 0 with (h | h | h) · exact ⟨fun _ => Real.sin_neg_of_neg_of_neg_pi_lt h (neg_pi_lt_toReal θ), fun _ => h⟩ · simp [h] · exact ⟨fun hn => False.elim (h.asymm hn), fun hn => False.elim (hn.not_le (sin_nonneg_of_nonneg_of_le_pi h.le (toReal_le_pi θ)))⟩ theorem toReal_nonneg_iff_sign_nonneg {θ : Angle} : 0 ≤ θ.toReal ↔ 0 ≤ θ.sign := by rcases lt_trichotomy θ.toReal 0 with (h | h | h) · refine ⟨fun hn => False.elim (h.not_le hn), fun hn => ?_⟩ rw [toReal_neg_iff_sign_neg.1 h] at hn exact False.elim (hn.not_lt (by decide)) · simp [h, sign, ← sin_toReal] · refine ⟨fun _ => ?_, fun _ => h.le⟩ rw [sign, ← sin_toReal, sign_nonneg_iff] exact sin_nonneg_of_nonneg_of_le_pi h.le (toReal_le_pi θ) @[simp] theorem sign_toReal {θ : Angle} (h : θ ≠ π) : SignType.sign θ.toReal = θ.sign := by rcases lt_trichotomy θ.toReal 0 with (ht | ht | ht) · simp [ht, toReal_neg_iff_sign_neg.1 ht] · simp [sign, ht, ← sin_toReal] · rw [sign, ← sin_toReal, sign_pos ht, sign_pos (sin_pos_of_pos_of_lt_pi ht ((toReal_le_pi θ).lt_of_ne (toReal_eq_pi_iff.not.2 h)))] theorem coe_abs_toReal_of_sign_nonneg {θ : Angle} (h : 0 ≤ θ.sign) : ↑|θ.toReal| = θ := by rw [abs_eq_self.2 (toReal_nonneg_iff_sign_nonneg.2 h), coe_toReal] theorem neg_coe_abs_toReal_of_sign_nonpos {θ : Angle} (h : θ.sign ≤ 0) : -↑|θ.toReal| = θ := by rw [SignType.nonpos_iff] at h rcases h with (h | h) · rw [abs_of_neg (toReal_neg_iff_sign_neg.2 h), coe_neg, neg_neg, coe_toReal] · rw [sign_eq_zero_iff] at h rcases h with (rfl | rfl) <;> simp [abs_of_pos Real.pi_pos] theorem eq_iff_sign_eq_and_abs_toReal_eq {θ ψ : Angle} : θ = ψ ↔ θ.sign = ψ.sign ∧ |θ.toReal| = |ψ.toReal| := by refine ⟨?_, fun h => ?_⟩ · rintro rfl exact ⟨rfl, rfl⟩ rcases h with ⟨hs, hr⟩
rw [abs_eq_abs] at hr rcases hr with (hr | hr)
Mathlib/Analysis/SpecialFunctions/Trigonometric/Angle.lean
784
785
/- Copyright (c) 2021 Yury Kudryashov. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yury Kudryashov -/ import Mathlib.Analysis.Convex.Between import Mathlib.MeasureTheory.Constructions.BorelSpace.Basic import Mathlib.MeasureTheory.Measure.Lebesgue.Basic import Mathlib.Topology.MetricSpace.Holder import Mathlib.Topology.MetricSpace.MetricSeparated /-! # Hausdorff measure and metric (outer) measures In this file we define the `d`-dimensional Hausdorff measure on an (extended) metric space `X` and the Hausdorff dimension of a set in an (extended) metric space. Let `μ d δ` be the maximal outer measure such that `μ d δ s ≤ (EMetric.diam s) ^ d` for every set of diameter less than `δ`. Then the Hausdorff measure `μH[d] s` of `s` is defined as `⨆ δ > 0, μ d δ s`. By Caratheodory theorem `MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`, this is a Borel measure on `X`. The value of `μH[d]`, `d > 0`, on a set `s` (measurable or not) is given by ``` μH[d] s = ⨆ (r : ℝ≥0∞) (hr : 0 < r), ⨅ (t : ℕ → Set X) (hts : s ⊆ ⋃ n, t n) (ht : ∀ n, EMetric.diam (t n) ≤ r), ∑' n, EMetric.diam (t n) ^ d ``` For every set `s` for any `d < d'` we have either `μH[d] s = ∞` or `μH[d'] s = 0`, see `MeasureTheory.Measure.hausdorffMeasure_zero_or_top`. In `Mathlib.Topology.MetricSpace.HausdorffDimension` we use this fact to define the Hausdorff dimension `dimH` of a set in an (extended) metric space. We also define two generalizations of the Hausdorff measure. In one generalization (see `MeasureTheory.Measure.mkMetric`) we take any function `m (diam s)` instead of `(diam s) ^ d`. In an even more general definition (see `MeasureTheory.Measure.mkMetric'`) we use any function of `m : Set X → ℝ≥0∞`. Some authors start with a partial function `m` defined only on some sets `s : Set X` (e.g., only on balls or only on measurable sets). This is equivalent to our definition applied to `MeasureTheory.extend m`. We also define a predicate `MeasureTheory.OuterMeasure.IsMetric` which says that an outer measure is additive on metric separated pairs of sets: `μ (s ∪ t) = μ s + μ t` provided that `⨅ (x ∈ s) (y ∈ t), edist x y ≠ 0`. This is the property required for the Caratheodory theorem `MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`, so we prove this theorem for any metric outer measure, then prove that outer measures constructed using `mkMetric'` are metric outer measures. ## Main definitions * `MeasureTheory.OuterMeasure.IsMetric`: an outer measure `μ` is called *metric* if `μ (s ∪ t) = μ s + μ t` for any two metric separated sets `s` and `t`. A metric outer measure in a Borel extended metric space is guaranteed to satisfy the Caratheodory condition, see `MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`. * `MeasureTheory.OuterMeasure.mkMetric'` and its particular case `MeasureTheory.OuterMeasure.mkMetric`: a construction of an outer measure that is guaranteed to be metric. Both constructions are generalizations of the Hausdorff measure. The same measures interpreted as Borel measures are called `MeasureTheory.Measure.mkMetric'` and `MeasureTheory.Measure.mkMetric`. * `MeasureTheory.Measure.hausdorffMeasure` a.k.a. `μH[d]`: the `d`-dimensional Hausdorff measure. There are many definitions of the Hausdorff measure that differ from each other by a multiplicative constant. We put `μH[d] s = ⨆ r > 0, ⨅ (t : ℕ → Set X) (hts : s ⊆ ⋃ n, t n) (ht : ∀ n, EMetric.diam (t n) ≤ r), ∑' n, ⨆ (ht : ¬Set.Subsingleton (t n)), (EMetric.diam (t n)) ^ d`, see `MeasureTheory.Measure.hausdorffMeasure_apply`. In the most interesting case `0 < d` one can omit the `⨆ (ht : ¬Set.Subsingleton (t n))` part. ## Main statements ### Basic properties * `MeasureTheory.OuterMeasure.IsMetric.borel_le_caratheodory`: if `μ` is a metric outer measure on an extended metric space `X` (that is, it is additive on pairs of metric separated sets), then every Borel set is Caratheodory measurable (hence, `μ` defines an actual `MeasureTheory.Measure`). See also `MeasureTheory.Measure.mkMetric`. * `MeasureTheory.Measure.hausdorffMeasure_mono`: `μH[d] s` is an antitone function of `d`. * `MeasureTheory.Measure.hausdorffMeasure_zero_or_top`: if `d₁ < d₂`, then for any `s`, either `μH[d₂] s = 0` or `μH[d₁] s = ∞`. Together with the previous lemma, this means that `μH[d] s` is equal to infinity on some ray `(-∞, D)` and is equal to zero on `(D, +∞)`, where `D` is a possibly infinite number called the *Hausdorff dimension* of `s`; `μH[D] s` can be zero, infinity, or anything in between. * `MeasureTheory.Measure.noAtoms_hausdorff`: Hausdorff measure has no atoms. ### Hausdorff measure in `ℝⁿ` * `MeasureTheory.hausdorffMeasure_pi_real`: for a nonempty `ι`, `μH[card ι]` on `ι → ℝ` equals Lebesgue measure. ## Notations We use the following notation localized in `MeasureTheory`. - `μH[d]` : `MeasureTheory.Measure.hausdorffMeasure d` ## Implementation notes There are a few similar constructions called the `d`-dimensional Hausdorff measure. E.g., some sources only allow coverings by balls and use `r ^ d` instead of `(diam s) ^ d`. While these construction lead to different Hausdorff measures, they lead to the same notion of the Hausdorff dimension. ## References * [Herbert Federer, Geometric Measure Theory, Chapter 2.10][Federer1996] ## Tags Hausdorff measure, measure, metric measure -/ open scoped NNReal ENNReal Topology open EMetric Set Function Filter Encodable Module TopologicalSpace noncomputable section variable {ι X Y : Type*} [EMetricSpace X] [EMetricSpace Y] namespace MeasureTheory namespace OuterMeasure /-! ### Metric outer measures In this section we define metric outer measures and prove Caratheodory theorem: a metric outer measure has the Caratheodory property. -/ /-- We say that an outer measure `μ` in an (e)metric space is *metric* if `μ (s ∪ t) = μ s + μ t` for any two metric separated sets `s`, `t`. -/ def IsMetric (μ : OuterMeasure X) : Prop := ∀ s t : Set X, Metric.AreSeparated s t → μ (s ∪ t) = μ s + μ t namespace IsMetric variable {μ : OuterMeasure X} /-- A metric outer measure is additive on a finite set of pairwise metric separated sets. -/ theorem finset_iUnion_of_pairwise_separated (hm : IsMetric μ) {I : Finset ι} {s : ι → Set X} (hI : ∀ i ∈ I, ∀ j ∈ I, i ≠ j → Metric.AreSeparated (s i) (s j)) : μ (⋃ i ∈ I, s i) = ∑ i ∈ I, μ (s i) := by classical induction I using Finset.induction_on with | empty => simp | insert i I hiI ihI => simp only [Finset.mem_insert] at hI rw [Finset.set_biUnion_insert, hm, ihI, Finset.sum_insert hiI] exacts [fun i hi j hj hij => hI i (Or.inr hi) j (Or.inr hj) hij, Metric.AreSeparated.finset_iUnion_right fun j hj => hI i (Or.inl rfl) j (Or.inr hj) (ne_of_mem_of_not_mem hj hiI).symm] /-- Caratheodory theorem. If `m` is a metric outer measure, then every Borel measurable set `t` is Caratheodory measurable: for any (not necessarily measurable) set `s` we have `μ (s ∩ t) + μ (s \ t) = μ s`. -/ theorem borel_le_caratheodory (hm : IsMetric μ) : borel X ≤ μ.caratheodory := by rw [borel_eq_generateFrom_isClosed] refine MeasurableSpace.generateFrom_le fun t ht => μ.isCaratheodory_iff_le.2 fun s => ?_ set S : ℕ → Set X := fun n => {x ∈ s | (↑n)⁻¹ ≤ infEdist x t} have Ssep (n) : Metric.AreSeparated (S n) t := ⟨n⁻¹, ENNReal.inv_ne_zero.2 (ENNReal.natCast_ne_top _), fun x hx y hy ↦ hx.2.trans <| infEdist_le_edist_of_mem hy⟩ have Ssep' : ∀ n, Metric.AreSeparated (S n) (s ∩ t) := fun n => (Ssep n).mono Subset.rfl inter_subset_right have S_sub : ∀ n, S n ⊆ s \ t := fun n => subset_inter inter_subset_left (Ssep n).subset_compl_right have hSs : ∀ n, μ (s ∩ t) + μ (S n) ≤ μ s := fun n => calc μ (s ∩ t) + μ (S n) = μ (s ∩ t ∪ S n) := Eq.symm <| hm _ _ <| (Ssep' n).symm _ ≤ μ (s ∩ t ∪ s \ t) := μ.mono <| union_subset_union_right _ <| S_sub n _ = μ s := by rw [inter_union_diff] have iUnion_S : ⋃ n, S n = s \ t := by refine Subset.antisymm (iUnion_subset S_sub) ?_ rintro x ⟨hxs, hxt⟩ rw [mem_iff_infEdist_zero_of_closed ht] at hxt rcases ENNReal.exists_inv_nat_lt hxt with ⟨n, hn⟩ exact mem_iUnion.2 ⟨n, hxs, hn.le⟩ /- Now we have `∀ n, μ (s ∩ t) + μ (S n) ≤ μ s` and we need to prove `μ (s ∩ t) + μ (⋃ n, S n) ≤ μ s`. We can't pass to the limit because `μ` is only an outer measure. -/ by_cases htop : μ (s \ t) = ∞ · rw [htop, add_top, ← htop] exact μ.mono diff_subset suffices μ (⋃ n, S n) ≤ ⨆ n, μ (S n) by calc μ (s ∩ t) + μ (s \ t) = μ (s ∩ t) + μ (⋃ n, S n) := by rw [iUnion_S] _ ≤ μ (s ∩ t) + ⨆ n, μ (S n) := by gcongr _ = ⨆ n, μ (s ∩ t) + μ (S n) := ENNReal.add_iSup .. _ ≤ μ s := iSup_le hSs /- It suffices to show that `∑' k, μ (S (k + 1) \ S k) ≠ ∞`. Indeed, if we have this, then for all `N` we have `μ (⋃ n, S n) ≤ μ (S N) + ∑' k, m (S (N + k + 1) \ S (N + k))` and the second term tends to zero, see `OuterMeasure.iUnion_nat_of_monotone_of_tsum_ne_top` for details. -/ have : ∀ n, S n ⊆ S (n + 1) := fun n x hx => ⟨hx.1, le_trans (ENNReal.inv_le_inv.2 <| Nat.cast_le.2 n.le_succ) hx.2⟩ refine (μ.iUnion_nat_of_monotone_of_tsum_ne_top this ?_).le; clear this /- While the sets `S (k + 1) \ S k` are not pairwise metric separated, the sets in each subsequence `S (2 * k + 1) \ S (2 * k)` and `S (2 * k + 2) \ S (2 * k)` are metric separated, so `m` is additive on each of those sequences. -/ rw [← tsum_even_add_odd ENNReal.summable ENNReal.summable, ENNReal.add_ne_top] suffices ∀ a, (∑' k : ℕ, μ (S (2 * k + 1 + a) \ S (2 * k + a))) ≠ ∞ from ⟨by simpa using this 0, by simpa using this 1⟩ refine fun r => ne_top_of_le_ne_top htop ?_ rw [← iUnion_S, ENNReal.tsum_eq_iSup_nat, iSup_le_iff] intro n rw [← hm.finset_iUnion_of_pairwise_separated] · exact μ.mono (iUnion_subset fun i => iUnion_subset fun _ x hx => mem_iUnion.2 ⟨_, hx.1⟩) suffices ∀ i j, i < j → Metric.AreSeparated (S (2 * i + 1 + r)) (s \ S (2 * j + r)) from fun i _ j _ hij => hij.lt_or_lt.elim (fun h => (this i j h).mono inter_subset_left fun x hx => by exact ⟨hx.1.1, hx.2⟩) fun h => (this j i h).symm.mono (fun x hx => by exact ⟨hx.1.1, hx.2⟩) inter_subset_left intro i j hj have A : ((↑(2 * j + r))⁻¹ : ℝ≥0∞) < (↑(2 * i + 1 + r))⁻¹ := by rw [ENNReal.inv_lt_inv, Nat.cast_lt]; omega refine ⟨(↑(2 * i + 1 + r))⁻¹ - (↑(2 * j + r))⁻¹, by simpa [tsub_eq_zero_iff_le] using A, fun x hx y hy => ?_⟩ have : infEdist y t < (↑(2 * j + r))⁻¹ := not_le.1 fun hle => hy.2 ⟨hy.1, hle⟩ rcases infEdist_lt_iff.mp this with ⟨z, hzt, hyz⟩ have hxz : (↑(2 * i + 1 + r))⁻¹ ≤ edist x z := le_infEdist.1 hx.2 _ hzt apply ENNReal.le_of_add_le_add_right hyz.ne_top refine le_trans ?_ (edist_triangle _ _ _) refine (add_le_add le_rfl hyz.le).trans (Eq.trans_le ?_ hxz) rw [tsub_add_cancel_of_le A.le] theorem le_caratheodory [MeasurableSpace X] [BorelSpace X] (hm : IsMetric μ) : ‹MeasurableSpace X› ≤ μ.caratheodory := by rw [BorelSpace.measurable_eq (α := X)] exact hm.borel_le_caratheodory end IsMetric /-! ### Constructors of metric outer measures In this section we provide constructors `MeasureTheory.OuterMeasure.mkMetric'` and `MeasureTheory.OuterMeasure.mkMetric` and prove that these outer measures are metric outer measures. We also prove basic lemmas about `map`/`comap` of these measures. -/ /-- Auxiliary definition for `OuterMeasure.mkMetric'`: given a function on sets `m : Set X → ℝ≥0∞`, returns the maximal outer measure `μ` such that `μ s ≤ m s` for any set `s` of diameter at most `r`. -/ def mkMetric'.pre (m : Set X → ℝ≥0∞) (r : ℝ≥0∞) : OuterMeasure X := boundedBy <| extend fun s (_ : diam s ≤ r) => m s /-- Given a function `m : Set X → ℝ≥0∞`, `mkMetric' m` is the supremum of `mkMetric'.pre m r` over `r > 0`. Equivalently, it is the limit of `mkMetric'.pre m r` as `r` tends to zero from the right. -/ def mkMetric' (m : Set X → ℝ≥0∞) : OuterMeasure X := ⨆ r > 0, mkMetric'.pre m r /-- Given a function `m : ℝ≥0∞ → ℝ≥0∞` and `r > 0`, let `μ r` be the maximal outer measure such that `μ s ≤ m (EMetric.diam s)` whenever `EMetric.diam s < r`. Then `mkMetric m = ⨆ r > 0, μ r`. -/ def mkMetric (m : ℝ≥0∞ → ℝ≥0∞) : OuterMeasure X := mkMetric' fun s => m (diam s) namespace mkMetric' variable {m : Set X → ℝ≥0∞} {r : ℝ≥0∞} {μ : OuterMeasure X} {s : Set X} theorem le_pre : μ ≤ pre m r ↔ ∀ s : Set X, diam s ≤ r → μ s ≤ m s := by simp only [pre, le_boundedBy, extend, le_iInf_iff] theorem pre_le (hs : diam s ≤ r) : pre m r s ≤ m s := (boundedBy_le _).trans <| iInf_le _ hs theorem mono_pre (m : Set X → ℝ≥0∞) {r r' : ℝ≥0∞} (h : r ≤ r') : pre m r' ≤ pre m r := le_pre.2 fun _ hs => pre_le (hs.trans h) theorem mono_pre_nat (m : Set X → ℝ≥0∞) : Monotone fun k : ℕ => pre m k⁻¹ := fun k l h => le_pre.2 fun _ hs => pre_le (hs.trans <| by simpa) theorem tendsto_pre (m : Set X → ℝ≥0∞) (s : Set X) : Tendsto (fun r => pre m r s) (𝓝[>] 0) (𝓝 <| mkMetric' m s) := by rw [← map_coe_Ioi_atBot, tendsto_map'_iff] simp only [mkMetric', OuterMeasure.iSup_apply, iSup_subtype'] exact tendsto_atBot_iSup fun r r' hr => mono_pre _ hr _ theorem tendsto_pre_nat (m : Set X → ℝ≥0∞) (s : Set X) : Tendsto (fun n : ℕ => pre m n⁻¹ s) atTop (𝓝 <| mkMetric' m s) := by refine (tendsto_pre m s).comp (tendsto_inf.2 ⟨ENNReal.tendsto_inv_nat_nhds_zero, ?_⟩) refine tendsto_principal.2 (Eventually.of_forall fun n => ?_) simp theorem eq_iSup_nat (m : Set X → ℝ≥0∞) : mkMetric' m = ⨆ n : ℕ, mkMetric'.pre m n⁻¹ := by ext1 s rw [iSup_apply] refine tendsto_nhds_unique (mkMetric'.tendsto_pre_nat m s) (tendsto_atTop_iSup fun k l hkl => mkMetric'.mono_pre_nat m hkl s) /-- `MeasureTheory.OuterMeasure.mkMetric'.pre m r` is a trimmed measure provided that `m (closure s) = m s` for any set `s`. -/ theorem trim_pre [MeasurableSpace X] [OpensMeasurableSpace X] (m : Set X → ℝ≥0∞) (hcl : ∀ s, m (closure s) = m s) (r : ℝ≥0∞) : (pre m r).trim = pre m r := by refine le_antisymm (le_pre.2 fun s hs => ?_) (le_trim _) rw [trim_eq_iInf] refine iInf_le_of_le (closure s) <| iInf_le_of_le subset_closure <| iInf_le_of_le measurableSet_closure ((pre_le ?_).trans_eq (hcl _)) rwa [diam_closure] end mkMetric' /-- An outer measure constructed using `OuterMeasure.mkMetric'` is a metric outer measure. -/ theorem mkMetric'_isMetric (m : Set X → ℝ≥0∞) : (mkMetric' m).IsMetric := by rintro s t ⟨r, r0, hr⟩ refine tendsto_nhds_unique_of_eventuallyEq (mkMetric'.tendsto_pre _ _) ((mkMetric'.tendsto_pre _ _).add (mkMetric'.tendsto_pre _ _)) ?_ rw [← pos_iff_ne_zero] at r0 filter_upwards [Ioo_mem_nhdsGT r0] rintro ε ⟨_, εr⟩ refine boundedBy_union_of_top_of_nonempty_inter ?_ rintro u ⟨x, hxs, hxu⟩ ⟨y, hyt, hyu⟩ have : ε < diam u := εr.trans_le ((hr x hxs y hyt).trans <| edist_le_diam_of_mem hxu hyu) exact iInf_eq_top.2 fun h => (this.not_le h).elim /-- If `c ∉ {0, ∞}` and `m₁ d ≤ c * m₂ d` for `d < ε` for some `ε > 0` (we use `≤ᶠ[𝓝[≥] 0]` to state this), then `mkMetric m₁ hm₁ ≤ c • mkMetric m₂ hm₂`. -/ theorem mkMetric_mono_smul {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} {c : ℝ≥0∞} (hc : c ≠ ∞) (h0 : c ≠ 0) (hle : m₁ ≤ᶠ[𝓝[≥] 0] c • m₂) : (mkMetric m₁ : OuterMeasure X) ≤ c • mkMetric m₂ := by classical rcases (mem_nhdsGE_iff_exists_Ico_subset' zero_lt_one).1 hle with ⟨r, hr0, hr⟩ refine fun s => le_of_tendsto_of_tendsto (mkMetric'.tendsto_pre _ s) (ENNReal.Tendsto.const_mul (mkMetric'.tendsto_pre _ s) (Or.inr hc)) (mem_of_superset (Ioo_mem_nhdsGT hr0) fun r' hr' => ?_) simp only [mem_setOf_eq, mkMetric'.pre, RingHom.id_apply] rw [← smul_eq_mul, ← smul_apply, smul_boundedBy hc] refine le_boundedBy.2 (fun t => (boundedBy_le _).trans ?_) _ simp only [smul_eq_mul, Pi.smul_apply, extend, iInf_eq_if] split_ifs with ht · apply hr exact ⟨zero_le _, ht.trans_lt hr'.2⟩ · simp [h0] @[simp] theorem mkMetric_top : (mkMetric (fun _ => ∞ : ℝ≥0∞ → ℝ≥0∞) : OuterMeasure X) = ⊤ := by simp_rw [mkMetric, mkMetric', mkMetric'.pre, extend_top, boundedBy_top, eq_top_iff] rw [le_iSup_iff] intro b hb simpa using hb ⊤ /-- If `m₁ d ≤ m₂ d` for `d < ε` for some `ε > 0` (we use `≤ᶠ[𝓝[≥] 0]` to state this), then `mkMetric m₁ hm₁ ≤ mkMetric m₂ hm₂`. -/ theorem mkMetric_mono {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} (hle : m₁ ≤ᶠ[𝓝[≥] 0] m₂) : (mkMetric m₁ : OuterMeasure X) ≤ mkMetric m₂ := by convert @mkMetric_mono_smul X _ _ m₂ _ ENNReal.one_ne_top one_ne_zero _ <;> simp [*] theorem isometry_comap_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) {f : X → Y} (hf : Isometry f) (H : Monotone m ∨ Surjective f) : comap f (mkMetric m) = mkMetric m := by simp only [mkMetric, mkMetric', mkMetric'.pre, inducedOuterMeasure, comap_iSup] refine surjective_id.iSup_congr id fun ε => surjective_id.iSup_congr id fun hε => ?_ rw [comap_boundedBy _ (H.imp _ id)] · congr with s : 1 apply extend_congr · simp [hf.ediam_image] · intros; simp [hf.injective.subsingleton_image_iff, hf.ediam_image] · intro h_mono s t hst simp only [extend, le_iInf_iff] intro ht apply le_trans _ (h_mono (diam_mono hst)) simp only [(diam_mono hst).trans ht, le_refl, ciInf_pos] theorem mkMetric_smul (m : ℝ≥0∞ → ℝ≥0∞) {c : ℝ≥0∞} (hc : c ≠ ∞) (hc' : c ≠ 0) : (mkMetric (c • m) : OuterMeasure X) = c • mkMetric m := by simp only [mkMetric, mkMetric', mkMetric'.pre, inducedOuterMeasure, ENNReal.smul_iSup] simp_rw [smul_iSup, smul_boundedBy hc, smul_extend _ hc', Pi.smul_apply] theorem mkMetric_nnreal_smul (m : ℝ≥0∞ → ℝ≥0∞) {c : ℝ≥0} (hc : c ≠ 0) : (mkMetric (c • m) : OuterMeasure X) = c • mkMetric m := by rw [ENNReal.smul_def, ENNReal.smul_def, mkMetric_smul m ENNReal.coe_ne_top (ENNReal.coe_ne_zero.mpr hc)] theorem isometry_map_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) {f : X → Y} (hf : Isometry f) (H : Monotone m ∨ Surjective f) : map f (mkMetric m) = restrict (range f) (mkMetric m) := by rw [← isometry_comap_mkMetric _ hf H, map_comap] theorem isometryEquiv_comap_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (f : X ≃ᵢ Y) : comap f (mkMetric m) = mkMetric m := isometry_comap_mkMetric _ f.isometry (Or.inr f.surjective) theorem isometryEquiv_map_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (f : X ≃ᵢ Y) : map f (mkMetric m) = mkMetric m := by rw [← isometryEquiv_comap_mkMetric _ f, map_comap_of_surjective f.surjective] theorem trim_mkMetric [MeasurableSpace X] [BorelSpace X] (m : ℝ≥0∞ → ℝ≥0∞) : (mkMetric m : OuterMeasure X).trim = mkMetric m := by simp only [mkMetric, mkMetric'.eq_iSup_nat, trim_iSup] congr 1 with n : 1 refine mkMetric'.trim_pre _ (fun s => ?_) _ simp theorem le_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (μ : OuterMeasure X) (r : ℝ≥0∞) (h0 : 0 < r) (hr : ∀ s, diam s ≤ r → μ s ≤ m (diam s)) : μ ≤ mkMetric m := le_iSup₂_of_le r h0 <| mkMetric'.le_pre.2 fun _ hs => hr _ hs end OuterMeasure /-! ### Metric measures In this section we use `MeasureTheory.OuterMeasure.toMeasure` and theorems about `MeasureTheory.OuterMeasure.mkMetric'`/`MeasureTheory.OuterMeasure.mkMetric` to define `MeasureTheory.Measure.mkMetric'`/`MeasureTheory.Measure.mkMetric`. We also restate some lemmas about metric outer measures for metric measures. -/ namespace Measure variable [MeasurableSpace X] [BorelSpace X] /-- Given a function `m : Set X → ℝ≥0∞`, `mkMetric' m` is the supremum of `μ r` over `r > 0`, where `μ r` is the maximal outer measure `μ` such that `μ s ≤ m s` for all `s`. While each `μ r` is an *outer* measure, the supremum is a measure. -/ def mkMetric' (m : Set X → ℝ≥0∞) : Measure X := (OuterMeasure.mkMetric' m).toMeasure (OuterMeasure.mkMetric'_isMetric _).le_caratheodory /-- Given a function `m : ℝ≥0∞ → ℝ≥0∞`, `mkMetric m` is the supremum of `μ r` over `r > 0`, where `μ r` is the maximal outer measure `μ` such that `μ s ≤ m s` for all sets `s` that contain at least two points. While each `mkMetric'.pre` is an *outer* measure, the supremum is a measure. -/ def mkMetric (m : ℝ≥0∞ → ℝ≥0∞) : Measure X := (OuterMeasure.mkMetric m).toMeasure (OuterMeasure.mkMetric'_isMetric _).le_caratheodory @[simp] theorem mkMetric'_toOuterMeasure (m : Set X → ℝ≥0∞) : (mkMetric' m).toOuterMeasure = (OuterMeasure.mkMetric' m).trim := rfl @[simp] theorem mkMetric_toOuterMeasure (m : ℝ≥0∞ → ℝ≥0∞) : (mkMetric m : Measure X).toOuterMeasure = OuterMeasure.mkMetric m := OuterMeasure.trim_mkMetric m end Measure theorem OuterMeasure.coe_mkMetric [MeasurableSpace X] [BorelSpace X] (m : ℝ≥0∞ → ℝ≥0∞) : ⇑(OuterMeasure.mkMetric m : OuterMeasure X) = Measure.mkMetric m := by rw [← Measure.mkMetric_toOuterMeasure, Measure.coe_toOuterMeasure] namespace Measure variable [MeasurableSpace X] [BorelSpace X] /-- If `c ∉ {0, ∞}` and `m₁ d ≤ c * m₂ d` for `d < ε` for some `ε > 0` (we use `≤ᶠ[𝓝[≥] 0]` to state this), then `mkMetric m₁ hm₁ ≤ c • mkMetric m₂ hm₂`. -/ theorem mkMetric_mono_smul {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} {c : ℝ≥0∞} (hc : c ≠ ∞) (h0 : c ≠ 0) (hle : m₁ ≤ᶠ[𝓝[≥] 0] c • m₂) : (mkMetric m₁ : Measure X) ≤ c • mkMetric m₂ := fun s ↦ by rw [← OuterMeasure.coe_mkMetric, coe_smul, ← OuterMeasure.coe_mkMetric] exact OuterMeasure.mkMetric_mono_smul hc h0 hle s @[simp] theorem mkMetric_top : (mkMetric (fun _ => ∞ : ℝ≥0∞ → ℝ≥0∞) : Measure X) = ⊤ := by apply toOuterMeasure_injective rw [mkMetric_toOuterMeasure, OuterMeasure.mkMetric_top, toOuterMeasure_top] /-- If `m₁ d ≤ m₂ d` for `d < ε` for some `ε > 0` (we use `≤ᶠ[𝓝[≥] 0]` to state this), then `mkMetric m₁ hm₁ ≤ mkMetric m₂ hm₂`. -/ theorem mkMetric_mono {m₁ m₂ : ℝ≥0∞ → ℝ≥0∞} (hle : m₁ ≤ᶠ[𝓝[≥] 0] m₂) : (mkMetric m₁ : Measure X) ≤ mkMetric m₂ := by convert @mkMetric_mono_smul X _ _ _ _ m₂ _ ENNReal.one_ne_top one_ne_zero _ <;> simp [*] /-- A formula for `MeasureTheory.Measure.mkMetric`. -/ theorem mkMetric_apply (m : ℝ≥0∞ → ℝ≥0∞) (s : Set X) : mkMetric m s = ⨆ (r : ℝ≥0∞) (_ : 0 < r), ⨅ (t : ℕ → Set X) (_ : s ⊆ iUnion t) (_ : ∀ n, diam (t n) ≤ r), ∑' n, ⨆ _ : (t n).Nonempty, m (diam (t n)) := by classical -- We mostly unfold the definitions but we need to switch the order of `∑'` and `⨅` simp only [← OuterMeasure.coe_mkMetric, OuterMeasure.mkMetric, OuterMeasure.mkMetric', OuterMeasure.iSup_apply, OuterMeasure.mkMetric'.pre, OuterMeasure.boundedBy_apply, extend] refine surjective_id.iSup_congr id fun r => iSup_congr_Prop Iff.rfl fun _ => surjective_id.iInf_congr _ fun t => iInf_congr_Prop Iff.rfl fun ht => ?_ dsimp by_cases htr : ∀ n, diam (t n) ≤ r · rw [iInf_eq_if, if_pos htr] congr 1 with n : 1 simp only [iInf_eq_if, htr n, id, if_true, iSup_and'] · rw [iInf_eq_if, if_neg htr] push_neg at htr; rcases htr with ⟨n, hn⟩ refine ENNReal.tsum_eq_top_of_eq_top ⟨n, ?_⟩ rw [iSup_eq_if, if_pos, iInf_eq_if, if_neg] · exact hn.not_le rcases diam_pos_iff.1 ((zero_le r).trans_lt hn) with ⟨x, hx, -⟩ exact ⟨x, hx⟩ theorem le_mkMetric (m : ℝ≥0∞ → ℝ≥0∞) (μ : Measure X) (ε : ℝ≥0∞) (h₀ : 0 < ε) (h : ∀ s : Set X, diam s ≤ ε → μ s ≤ m (diam s)) : μ ≤ mkMetric m := by rw [← toOuterMeasure_le, mkMetric_toOuterMeasure] exact OuterMeasure.le_mkMetric m μ.toOuterMeasure ε h₀ h /-- To bound the Hausdorff measure (or, more generally, for a measure defined using `MeasureTheory.Measure.mkMetric`) of a set, one may use coverings with maximum diameter tending to `0`, indexed by any sequence of countable types. -/ theorem mkMetric_le_liminf_tsum {β : Type*} {ι : β → Type*} [∀ n, Countable (ι n)] (s : Set X) {l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0)) (t : ∀ n : β, ι n → Set X) (ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n) (hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) (m : ℝ≥0∞ → ℝ≥0∞) : mkMetric m s ≤ liminf (fun n => ∑' i, m (diam (t n i))) l := by haveI : ∀ n, Encodable (ι n) := fun n => Encodable.ofCountable _ simp only [mkMetric_apply] refine iSup₂_le fun ε hε => ?_ refine le_of_forall_gt_imp_ge_of_dense fun c hc => ?_ rcases ((frequently_lt_of_liminf_lt (by isBoundedDefault) hc).and_eventually ((hr.eventually (gt_mem_nhds hε)).and (ht.and hst))).exists with ⟨n, hn, hrn, htn, hstn⟩ set u : ℕ → Set X := fun j => ⋃ b ∈ decode₂ (ι n) j, t n b refine iInf₂_le_of_le u (by rwa [iUnion_decode₂]) ?_ refine iInf_le_of_le (fun j => ?_) ?_ · rw [EMetric.diam_iUnion_mem_option] exact iSup₂_le fun _ _ => (htn _).trans hrn.le · calc (∑' j : ℕ, ⨆ _ : (u j).Nonempty, m (diam (u j))) = _ := tsum_iUnion_decode₂ (fun t : Set X => ⨆ _ : t.Nonempty, m (diam t)) (by simp) _ _ ≤ ∑' i : ι n, m (diam (t n i)) := ENNReal.tsum_le_tsum fun b => iSup_le fun _ => le_rfl _ ≤ c := hn.le /-- To bound the Hausdorff measure (or, more generally, for a measure defined using `MeasureTheory.Measure.mkMetric`) of a set, one may use coverings with maximum diameter tending to `0`, indexed by any sequence of finite types. -/ theorem mkMetric_le_liminf_sum {β : Type*} {ι : β → Type*} [hι : ∀ n, Fintype (ι n)] (s : Set X) {l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0)) (t : ∀ n : β, ι n → Set X) (ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n) (hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) (m : ℝ≥0∞ → ℝ≥0∞) : mkMetric m s ≤ liminf (fun n => ∑ i, m (diam (t n i))) l := by simpa only [tsum_fintype] using mkMetric_le_liminf_tsum s r hr t ht hst m /-! ### Hausdorff measure and Hausdorff dimension -/ /-- Hausdorff measure on an (e)metric space. -/ def hausdorffMeasure (d : ℝ) : Measure X := mkMetric fun r => r ^ d @[inherit_doc] scoped[MeasureTheory] notation "μH[" d "]" => MeasureTheory.Measure.hausdorffMeasure d theorem le_hausdorffMeasure (d : ℝ) (μ : Measure X) (ε : ℝ≥0∞) (h₀ : 0 < ε) (h : ∀ s : Set X, diam s ≤ ε → μ s ≤ diam s ^ d) : μ ≤ μH[d] := le_mkMetric _ μ ε h₀ h /-- A formula for `μH[d] s`. -/ theorem hausdorffMeasure_apply (d : ℝ) (s : Set X) : μH[d] s = ⨆ (r : ℝ≥0∞) (_ : 0 < r), ⨅ (t : ℕ → Set X) (_ : s ⊆ ⋃ n, t n) (_ : ∀ n, diam (t n) ≤ r), ∑' n, ⨆ _ : (t n).Nonempty, diam (t n) ^ d := mkMetric_apply _ _ /-- To bound the Hausdorff measure of a set, one may use coverings with maximum diameter tending to `0`, indexed by any sequence of countable types. -/ theorem hausdorffMeasure_le_liminf_tsum {β : Type*} {ι : β → Type*} [∀ n, Countable (ι n)] (d : ℝ) (s : Set X) {l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0)) (t : ∀ n : β, ι n → Set X) (ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n) (hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) : μH[d] s ≤ liminf (fun n => ∑' i, diam (t n i) ^ d) l := mkMetric_le_liminf_tsum s r hr t ht hst _ /-- To bound the Hausdorff measure of a set, one may use coverings with maximum diameter tending to `0`, indexed by any sequence of finite types. -/ theorem hausdorffMeasure_le_liminf_sum {β : Type*} {ι : β → Type*} [∀ n, Fintype (ι n)] (d : ℝ) (s : Set X) {l : Filter β} (r : β → ℝ≥0∞) (hr : Tendsto r l (𝓝 0)) (t : ∀ n : β, ι n → Set X) (ht : ∀ᶠ n in l, ∀ i, diam (t n i) ≤ r n) (hst : ∀ᶠ n in l, s ⊆ ⋃ i, t n i) : μH[d] s ≤ liminf (fun n => ∑ i, diam (t n i) ^ d) l := mkMetric_le_liminf_sum s r hr t ht hst _ /-- If `d₁ < d₂`, then for any set `s` we have either `μH[d₂] s = 0`, or `μH[d₁] s = ∞`. -/ theorem hausdorffMeasure_zero_or_top {d₁ d₂ : ℝ} (h : d₁ < d₂) (s : Set X) : μH[d₂] s = 0 ∨ μH[d₁] s = ∞ := by by_contra! H suffices ∀ c : ℝ≥0, c ≠ 0 → μH[d₂] s ≤ c * μH[d₁] s by rcases ENNReal.exists_nnreal_pos_mul_lt H.2 H.1 with ⟨c, hc0, hc⟩ exact hc.not_le (this c (pos_iff_ne_zero.1 hc0)) intro c hc refine le_iff'.1 (mkMetric_mono_smul ENNReal.coe_ne_top (mod_cast hc) ?_) s have : 0 < ((c : ℝ≥0∞) ^ (d₂ - d₁)⁻¹) := by rw [← ENNReal.coe_rpow_of_ne_zero hc, pos_iff_ne_zero, Ne, ENNReal.coe_eq_zero, NNReal.rpow_eq_zero_iff] exact mt And.left hc filter_upwards [Ico_mem_nhdsGE this] rintro r ⟨hr₀, hrc⟩ lift r to ℝ≥0 using ne_top_of_lt hrc rw [Pi.smul_apply, smul_eq_mul, ← ENNReal.div_le_iff_le_mul (Or.inr ENNReal.coe_ne_top) (Or.inr <| mt ENNReal.coe_eq_zero.1 hc)] rcases eq_or_ne r 0 with (rfl | hr₀) · rcases lt_or_le 0 d₂ with (h₂ | h₂) · simp only [h₂, ENNReal.zero_rpow_of_pos, zero_le, ENNReal.zero_div, ENNReal.coe_zero] · simp only [h.trans_le h₂, ENNReal.div_top, zero_le, ENNReal.zero_rpow_of_neg, ENNReal.coe_zero] · have : (r : ℝ≥0∞) ≠ 0 := by simpa only [ENNReal.coe_eq_zero, Ne] using hr₀ rw [← ENNReal.rpow_sub _ _ this ENNReal.coe_ne_top] refine (ENNReal.rpow_lt_rpow hrc (sub_pos.2 h)).le.trans ?_ rw [← ENNReal.rpow_mul, inv_mul_cancel₀ (sub_pos.2 h).ne', ENNReal.rpow_one] /-- Hausdorff measure `μH[d] s` is monotone in `d`. -/ theorem hausdorffMeasure_mono {d₁ d₂ : ℝ} (h : d₁ ≤ d₂) (s : Set X) : μH[d₂] s ≤ μH[d₁] s := by rcases h.eq_or_lt with (rfl | h); · exact le_rfl rcases hausdorffMeasure_zero_or_top h s with hs | hs · rw [hs]; exact zero_le _ · rw [hs]; exact le_top variable (X) in theorem noAtoms_hausdorff {d : ℝ} (hd : 0 < d) : NoAtoms (hausdorffMeasure d : Measure X) := by refine ⟨fun x => ?_⟩ rw [← nonpos_iff_eq_zero, hausdorffMeasure_apply] refine iSup₂_le fun ε _ => iInf₂_le_of_le (fun _ => {x}) ?_ <| iInf_le_of_le (fun _ => ?_) ?_ · exact subset_iUnion (fun _ => {x} : ℕ → Set X) 0 · simp only [EMetric.diam_singleton, zero_le] · simp [hd] @[simp] theorem hausdorffMeasure_zero_singleton (x : X) : μH[0] ({x} : Set X) = 1 := by apply le_antisymm · let r : ℕ → ℝ≥0∞ := fun _ => 0 let t : ℕ → Unit → Set X := fun _ _ => {x} have ht : ∀ᶠ n in atTop, ∀ i, diam (t n i) ≤ r n := by simp only [t, r, imp_true_iff, eq_self_iff_true, diam_singleton, eventually_atTop, nonpos_iff_eq_zero, exists_const] simpa [t, liminf_const] using hausdorffMeasure_le_liminf_sum 0 {x} r tendsto_const_nhds t ht · rw [hausdorffMeasure_apply] suffices (1 : ℝ≥0∞) ≤ ⨅ (t : ℕ → Set X) (_ : {x} ⊆ ⋃ n, t n) (_ : ∀ n, diam (t n) ≤ 1), ∑' n, ⨆ _ : (t n).Nonempty, diam (t n) ^ (0 : ℝ) by apply le_trans this _ convert le_iSup₂ (α := ℝ≥0∞) (1 : ℝ≥0∞) zero_lt_one rfl simp only [ENNReal.rpow_zero, le_iInf_iff] intro t hst _ rcases mem_iUnion.1 (hst (mem_singleton x)) with ⟨m, hm⟩ have A : (t m).Nonempty := ⟨x, hm⟩ calc (1 : ℝ≥0∞) = ⨆ h : (t m).Nonempty, 1 := by simp only [A, ciSup_pos] _ ≤ ∑' n, ⨆ h : (t n).Nonempty, 1 := ENNReal.le_tsum _ theorem one_le_hausdorffMeasure_zero_of_nonempty {s : Set X} (h : s.Nonempty) : 1 ≤ μH[0] s := by rcases h with ⟨x, hx⟩ calc (1 : ℝ≥0∞) = μH[0] ({x} : Set X) := (hausdorffMeasure_zero_singleton x).symm _ ≤ μH[0] s := measure_mono (singleton_subset_iff.2 hx) theorem hausdorffMeasure_le_one_of_subsingleton {s : Set X} (hs : s.Subsingleton) {d : ℝ} (hd : 0 ≤ d) : μH[d] s ≤ 1 := by rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩) · simp only [measure_empty, zero_le] · rw [(subsingleton_iff_singleton hx).1 hs] rcases eq_or_lt_of_le hd with (rfl | dpos) · simp only [le_refl, hausdorffMeasure_zero_singleton] · haveI := noAtoms_hausdorff X dpos simp only [zero_le, measure_singleton] end Measure end MeasureTheory /-! ### Hausdorff measure, Hausdorff dimension, and Hölder or Lipschitz continuous maps -/ open scoped MeasureTheory open MeasureTheory MeasureTheory.Measure variable [MeasurableSpace X] [BorelSpace X] [MeasurableSpace Y] [BorelSpace Y] namespace HolderOnWith variable {C r : ℝ≥0} {f : X → Y} {s : Set X} /-- If `f : X → Y` is Hölder continuous on `s` with a positive exponent `r`, then `μH[d] (f '' s) ≤ C ^ d * μH[r * d] s`. -/ theorem hausdorffMeasure_image_le (h : HolderOnWith C r f s) (hr : 0 < r) {d : ℝ} (hd : 0 ≤ d) : μH[d] (f '' s) ≤ (C : ℝ≥0∞) ^ d * μH[r * d] s := by -- We start with the trivial case `C = 0` rcases (zero_le C).eq_or_lt with (rfl | hC0) · rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩) · simp only [measure_empty, nonpos_iff_eq_zero, mul_zero, image_empty] have : f '' s = {f x} := have : (f '' s).Subsingleton := by simpa [diam_eq_zero_iff] using h.ediam_image_le (subsingleton_iff_singleton (mem_image_of_mem f hx)).1 this rw [this] rcases eq_or_lt_of_le hd with (rfl | h'd) · simp only [ENNReal.rpow_zero, one_mul, mul_zero] rw [hausdorffMeasure_zero_singleton] exact one_le_hausdorffMeasure_zero_of_nonempty ⟨x, hx⟩ · haveI := noAtoms_hausdorff Y h'd simp only [zero_le, measure_singleton] -- Now assume `C ≠ 0` · have hCd0 : (C : ℝ≥0∞) ^ d ≠ 0 := by simp [hC0.ne'] have hCd : (C : ℝ≥0∞) ^ d ≠ ∞ := by simp [hd] simp only [hausdorffMeasure_apply, ENNReal.mul_iSup, ENNReal.mul_iInf_of_ne hCd0 hCd, ← ENNReal.tsum_mul_left] refine iSup_le fun R => iSup_le fun hR => ?_ have : Tendsto (fun d : ℝ≥0∞ => (C : ℝ≥0∞) * d ^ (r : ℝ)) (𝓝 0) (𝓝 0) := ENNReal.tendsto_const_mul_rpow_nhds_zero_of_pos ENNReal.coe_ne_top hr rcases ENNReal.nhds_zero_basis_Iic.eventually_iff.1 (this.eventually (gt_mem_nhds hR)) with ⟨δ, δ0, H⟩ refine le_iSup₂_of_le δ δ0 <| iInf₂_mono' fun t hst ↦ ⟨fun n => f '' (t n ∩ s), ?_, iInf_mono' fun htδ ↦ ⟨fun n => (h.ediam_image_inter_le (t n)).trans (H (htδ n)).le, ?_⟩⟩ · rw [← image_iUnion, ← iUnion_inter] exact image_subset _ (subset_inter hst Subset.rfl) · refine ENNReal.tsum_le_tsum fun n => ?_ simp only [iSup_le_iff, image_nonempty] intro hft simp only [Nonempty.mono ((t n).inter_subset_left) hft, ciSup_pos] rw [ENNReal.rpow_mul, ← ENNReal.mul_rpow_of_nonneg _ _ hd] exact ENNReal.rpow_le_rpow (h.ediam_image_inter_le _) hd end HolderOnWith namespace LipschitzOnWith variable {K : ℝ≥0} {f : X → Y} {s : Set X} /-- If `f : X → Y` is `K`-Lipschitz on `s`, then `μH[d] (f '' s) ≤ K ^ d * μH[d] s`. -/ theorem hausdorffMeasure_image_le (h : LipschitzOnWith K f s) {d : ℝ} (hd : 0 ≤ d) : μH[d] (f '' s) ≤ (K : ℝ≥0∞) ^ d * μH[d] s := by simpa only [NNReal.coe_one, one_mul] using h.holderOnWith.hausdorffMeasure_image_le zero_lt_one hd end LipschitzOnWith namespace LipschitzWith variable {K : ℝ≥0} {f : X → Y} /-- If `f` is a `K`-Lipschitz map, then it increases the Hausdorff `d`-measures of sets at most by the factor of `K ^ d`. -/ theorem hausdorffMeasure_image_le (h : LipschitzWith K f) {d : ℝ} (hd : 0 ≤ d) (s : Set X) : μH[d] (f '' s) ≤ (K : ℝ≥0∞) ^ d * μH[d] s := h.lipschitzOnWith.hausdorffMeasure_image_le hd end LipschitzWith open scoped Pointwise theorem MeasureTheory.Measure.hausdorffMeasure_smul₀ {𝕜 E : Type*} [NormedAddCommGroup E] [NormedField 𝕜] [NormedSpace 𝕜 E] [MeasurableSpace E] [BorelSpace E] {d : ℝ} (hd : 0 ≤ d) {r : 𝕜} (hr : r ≠ 0) (s : Set E) : μH[d] (r • s) = ‖r‖₊ ^ d • μH[d] s := by have {r : 𝕜} (s : Set E) : μH[d] (r • s) ≤ ‖r‖₊ ^ d • μH[d] s := by simpa [ENNReal.coe_rpow_of_nonneg, hd] using (lipschitzWith_smul r).hausdorffMeasure_image_le hd s refine le_antisymm (this s) ?_ rw [← le_inv_smul_iff_of_pos] · dsimp rw [← NNReal.inv_rpow, ← nnnorm_inv] · refine Eq.trans_le ?_ (this (r • s)) rw [inv_smul_smul₀ hr] · simp [pos_iff_ne_zero, hr] /-! ### Antilipschitz maps do not decrease Hausdorff measures and dimension -/ namespace AntilipschitzWith variable {f : X → Y} {K : ℝ≥0} {d : ℝ} theorem hausdorffMeasure_preimage_le (hf : AntilipschitzWith K f) (hd : 0 ≤ d) (s : Set Y) : μH[d] (f ⁻¹' s) ≤ (K : ℝ≥0∞) ^ d * μH[d] s := by rcases eq_or_ne K 0 with (rfl | h0) · rcases eq_empty_or_nonempty (f ⁻¹' s) with (hs | ⟨x, hx⟩) · simp only [hs, measure_empty, zero_le] have : f ⁻¹' s = {x} := by haveI : Subsingleton X := hf.subsingleton have : (f ⁻¹' s).Subsingleton := subsingleton_univ.anti (subset_univ _) exact (subsingleton_iff_singleton hx).1 this rw [this] rcases eq_or_lt_of_le hd with (rfl | h'd) · simp only [ENNReal.rpow_zero, one_mul, mul_zero] rw [hausdorffMeasure_zero_singleton] exact one_le_hausdorffMeasure_zero_of_nonempty ⟨f x, hx⟩ · haveI := noAtoms_hausdorff X h'd simp only [zero_le, measure_singleton] have hKd0 : (K : ℝ≥0∞) ^ d ≠ 0 := by simp [h0] have hKd : (K : ℝ≥0∞) ^ d ≠ ∞ := by simp [hd] simp only [hausdorffMeasure_apply, ENNReal.mul_iSup, ENNReal.mul_iInf_of_ne hKd0 hKd, ← ENNReal.tsum_mul_left] refine iSup₂_le fun ε ε0 => ?_ refine le_iSup₂_of_le (ε / K) (by simp [ε0.ne']) ?_ refine le_iInf₂ fun t hst => le_iInf fun htε => ?_ replace hst : f ⁻¹' s ⊆ _ := preimage_mono hst; rw [preimage_iUnion] at hst refine iInf₂_le_of_le _ hst (iInf_le_of_le (fun n => ?_) ?_) · exact (hf.ediam_preimage_le _).trans (ENNReal.mul_le_of_le_div' <| htε n) · refine ENNReal.tsum_le_tsum fun n => iSup_le_iff.2 fun hft => ?_ simp only [nonempty_of_nonempty_preimage hft, ciSup_pos] rw [← ENNReal.mul_rpow_of_nonneg _ _ hd] exact ENNReal.rpow_le_rpow (hf.ediam_preimage_le _) hd theorem le_hausdorffMeasure_image (hf : AntilipschitzWith K f) (hd : 0 ≤ d) (s : Set X) : μH[d] s ≤ (K : ℝ≥0∞) ^ d * μH[d] (f '' s) := calc μH[d] s ≤ μH[d] (f ⁻¹' (f '' s)) := measure_mono (subset_preimage_image _ _) _ ≤ (K : ℝ≥0∞) ^ d * μH[d] (f '' s) := hf.hausdorffMeasure_preimage_le hd (f '' s) end AntilipschitzWith /-! ### Isometries preserve the Hausdorff measure and Hausdorff dimension -/ namespace Isometry variable {f : X → Y} {d : ℝ} theorem hausdorffMeasure_image (hf : Isometry f) (hd : 0 ≤ d ∨ Surjective f) (s : Set X) : μH[d] (f '' s) = μH[d] s := by simp only [hausdorffMeasure, ← OuterMeasure.coe_mkMetric, ← OuterMeasure.comap_apply] rw [OuterMeasure.isometry_comap_mkMetric _ hf (hd.imp_left _)] exact ENNReal.monotone_rpow_of_nonneg theorem hausdorffMeasure_preimage (hf : Isometry f) (hd : 0 ≤ d ∨ Surjective f) (s : Set Y) : μH[d] (f ⁻¹' s) = μH[d] (s ∩ range f) := by rw [← hf.hausdorffMeasure_image hd, image_preimage_eq_inter_range] theorem map_hausdorffMeasure (hf : Isometry f) (hd : 0 ≤ d ∨ Surjective f) : Measure.map f μH[d] = μH[d].restrict (range f) := by ext1 s hs rw [map_apply hf.continuous.measurable hs, Measure.restrict_apply hs, hf.hausdorffMeasure_preimage hd] end Isometry namespace IsometryEquiv @[simp] theorem hausdorffMeasure_image (e : X ≃ᵢ Y) (d : ℝ) (s : Set X) : μH[d] (e '' s) = μH[d] s := e.isometry.hausdorffMeasure_image (Or.inr e.surjective) s @[simp] theorem hausdorffMeasure_preimage (e : X ≃ᵢ Y) (d : ℝ) (s : Set Y) : μH[d] (e ⁻¹' s) = μH[d] s := by rw [← e.image_symm, e.symm.hausdorffMeasure_image] @[simp] theorem map_hausdorffMeasure (e : X ≃ᵢ Y) (d : ℝ) : Measure.map e μH[d] = μH[d] := by rw [e.isometry.map_hausdorffMeasure (Or.inr e.surjective), e.surjective.range_eq, restrict_univ] theorem measurePreserving_hausdorffMeasure (e : X ≃ᵢ Y) (d : ℝ) : MeasurePreserving e μH[d] μH[d] := ⟨e.continuous.measurable, map_hausdorffMeasure _ _⟩ end IsometryEquiv namespace MeasureTheory @[to_additive] theorem hausdorffMeasure_smul {α : Type*} [SMul α X] [IsIsometricSMul α X] {d : ℝ} (c : α) (h : 0 ≤ d ∨ Surjective (c • · : X → X)) (s : Set X) : μH[d] (c • s) = μH[d] s := (isometry_smul X c).hausdorffMeasure_image h _ @[to_additive] instance {d : ℝ} [Group X] [IsIsometricSMul X X] : IsMulLeftInvariant (μH[d] : Measure X) where map_mul_left_eq_self x := (IsometryEquiv.constSMul x).map_hausdorffMeasure _ @[to_additive] instance {d : ℝ} [Group X] [IsIsometricSMul Xᵐᵒᵖ X] : IsMulRightInvariant (μH[d] : Measure X) where map_mul_right_eq_self x := (IsometryEquiv.constSMul (MulOpposite.op x)).map_hausdorffMeasure _ /-! ### Hausdorff measure and Lebesgue measure -/ /-- In the space `ι → ℝ`, the Hausdorff measure coincides exactly with the Lebesgue measure. -/ @[simp] theorem hausdorffMeasure_pi_real {ι : Type*} [Fintype ι] : (μH[Fintype.card ι] : Measure (ι → ℝ)) = volume := by
classical -- it suffices to check that the two measures coincide on products of rational intervals refine (pi_eq_generateFrom (fun _ => Real.borel_eq_generateFrom_Ioo_rat.symm) (fun _ => Real.isPiSystem_Ioo_rat) (fun _ => Real.finiteSpanningSetsInIooRat _) ?_).symm simp only [mem_iUnion, mem_singleton_iff]
Mathlib/MeasureTheory/Measure/Hausdorff.lean
870
874
/- Copyright (c) 2019 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Frédéric Dupuis, Heather Macbeth -/ import Mathlib.Analysis.Convex.Basic import Mathlib.Analysis.InnerProductSpace.Orthogonal import Mathlib.Analysis.InnerProductSpace.Symmetric import Mathlib.Analysis.NormedSpace.RCLike import Mathlib.Analysis.RCLike.Lemmas import Mathlib.Algebra.DirectSum.Decomposition /-! # The orthogonal projection Given a nonempty complete subspace `K` of an inner product space `E`, this file constructs `K.orthogonalProjection : E →L[𝕜] K`, the orthogonal projection of `E` onto `K`. This map satisfies: for any point `u` in `E`, the point `v = K.orthogonalProjection u` in `K` minimizes the distance `‖u - v‖` to `u`. Also a linear isometry equivalence `K.reflection : E ≃ₗᵢ[𝕜] E` is constructed, by choosing, for each `u : E`, the point `K.reflection u` to satisfy `u + (K.reflection u) = 2 • K.orthogonalProjection u`. Basic API for `orthogonalProjection` and `reflection` is developed. Next, the orthogonal projection is used to prove a series of more subtle lemmas about the orthogonal complement of complete subspaces of `E` (the orthogonal complement itself was defined in `Analysis.InnerProductSpace.Orthogonal`); the lemma `Submodule.sup_orthogonal_of_completeSpace`, stating that for a complete subspace `K` of `E` we have `K ⊔ Kᗮ = ⊤`, is a typical example. ## References The orthogonal projection construction is adapted from * [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*] * [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*] The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html> -/ noncomputable section open InnerProductSpace open RCLike Real Filter open LinearMap (ker range) open Topology Finsupp variable {𝕜 E F : Type*} [RCLike 𝕜] variable [NormedAddCommGroup E] [NormedAddCommGroup F] variable [InnerProductSpace 𝕜 E] [InnerProductSpace ℝ F] local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y local notation "absR" => abs /-! ### Orthogonal projection in inner product spaces -/ -- FIXME this monolithic proof causes a deterministic timeout with `-T50000` -- It should be broken in a sequence of more manageable pieces, -- perhaps with individual statements for the three steps below. /-- **Existence of minimizers**, aka the **Hilbert projection theorem**. Let `u` be a point in a real inner product space, and let `K` be a nonempty complete convex subset. Then there exists a (unique) `v` in `K` that minimizes the distance `‖u - v‖` to `u`. -/ theorem exists_norm_eq_iInf_of_complete_convex {K : Set F} (ne : K.Nonempty) (h₁ : IsComplete K) (h₂ : Convex ℝ K) : ∀ u : F, ∃ v ∈ K, ‖u - v‖ = ⨅ w : K, ‖u - w‖ := fun u => by let δ := ⨅ w : K, ‖u - w‖ letI : Nonempty K := ne.to_subtype have zero_le_δ : 0 ≤ δ := le_ciInf fun _ => norm_nonneg _ have δ_le : ∀ w : K, δ ≤ ‖u - w‖ := ciInf_le ⟨0, Set.forall_mem_range.2 fun _ => norm_nonneg _⟩ have δ_le' : ∀ w ∈ K, δ ≤ ‖u - w‖ := fun w hw => δ_le ⟨w, hw⟩ -- Step 1: since `δ` is the infimum, can find a sequence `w : ℕ → K` in `K` -- such that `‖u - w n‖ < δ + 1 / (n + 1)` (which implies `‖u - w n‖ --> δ`); -- maybe this should be a separate lemma have exists_seq : ∃ w : ℕ → K, ∀ n, ‖u - w n‖ < δ + 1 / (n + 1) := by have hδ : ∀ n : ℕ, δ < δ + 1 / (n + 1) := fun n => lt_add_of_le_of_pos le_rfl Nat.one_div_pos_of_nat have h := fun n => exists_lt_of_ciInf_lt (hδ n) let w : ℕ → K := fun n => Classical.choose (h n) exact ⟨w, fun n => Classical.choose_spec (h n)⟩ rcases exists_seq with ⟨w, hw⟩ have norm_tendsto : Tendsto (fun n => ‖u - w n‖) atTop (𝓝 δ) := by have h : Tendsto (fun _ : ℕ => δ) atTop (𝓝 δ) := tendsto_const_nhds have h' : Tendsto (fun n : ℕ => δ + 1 / (n + 1)) atTop (𝓝 δ) := by convert h.add tendsto_one_div_add_atTop_nhds_zero_nat simp only [add_zero] exact tendsto_of_tendsto_of_tendsto_of_le_of_le h h' (fun x => δ_le _) fun x => le_of_lt (hw _) -- Step 2: Prove that the sequence `w : ℕ → K` is a Cauchy sequence have seq_is_cauchy : CauchySeq fun n => (w n : F) := by rw [cauchySeq_iff_le_tendsto_0] -- splits into three goals let b := fun n : ℕ => 8 * δ * (1 / (n + 1)) + 4 * (1 / (n + 1)) * (1 / (n + 1)) use fun n => √(b n) constructor -- first goal : `∀ (n : ℕ), 0 ≤ √(b n)` · intro n exact sqrt_nonneg _ constructor -- second goal : `∀ (n m N : ℕ), N ≤ n → N ≤ m → dist ↑(w n) ↑(w m) ≤ √(b N)` · intro p q N hp hq let wp := (w p : F) let wq := (w q : F) let a := u - wq let b := u - wp let half := 1 / (2 : ℝ) let div := 1 / ((N : ℝ) + 1) have : 4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ + ‖wp - wq‖ * ‖wp - wq‖ = 2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) := calc 4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ + ‖wp - wq‖ * ‖wp - wq‖ = 2 * ‖u - half • (wq + wp)‖ * (2 * ‖u - half • (wq + wp)‖) + ‖wp - wq‖ * ‖wp - wq‖ := by ring _ = absR (2 : ℝ) * ‖u - half • (wq + wp)‖ * (absR (2 : ℝ) * ‖u - half • (wq + wp)‖) + ‖wp - wq‖ * ‖wp - wq‖ := by rw [abs_of_nonneg] exact zero_le_two _ = ‖(2 : ℝ) • (u - half • (wq + wp))‖ * ‖(2 : ℝ) • (u - half • (wq + wp))‖ + ‖wp - wq‖ * ‖wp - wq‖ := by simp [norm_smul] _ = ‖a + b‖ * ‖a + b‖ + ‖a - b‖ * ‖a - b‖ := by rw [smul_sub, smul_smul, mul_one_div_cancel (_root_.two_ne_zero : (2 : ℝ) ≠ 0), ← one_add_one_eq_two, add_smul] simp only [one_smul] have eq₁ : wp - wq = a - b := (sub_sub_sub_cancel_left _ _ _).symm have eq₂ : u + u - (wq + wp) = a + b := by show u + u - (wq + wp) = u - wq + (u - wp) abel rw [eq₁, eq₂] _ = 2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) := parallelogram_law_with_norm ℝ _ _ have eq : δ ≤ ‖u - half • (wq + wp)‖ := by rw [smul_add] apply δ_le' apply h₂ repeat' exact Subtype.mem _ repeat' exact le_of_lt one_half_pos exact add_halves 1 have eq₁ : 4 * δ * δ ≤ 4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ := by simp_rw [mul_assoc] gcongr have eq₂ : ‖a‖ ≤ δ + div := le_trans (le_of_lt <| hw q) (add_le_add_left (Nat.one_div_le_one_div hq) _) have eq₂' : ‖b‖ ≤ δ + div := le_trans (le_of_lt <| hw p) (add_le_add_left (Nat.one_div_le_one_div hp) _) rw [dist_eq_norm] apply nonneg_le_nonneg_of_sq_le_sq · exact sqrt_nonneg _ rw [mul_self_sqrt] · calc ‖wp - wq‖ * ‖wp - wq‖ = 2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) - 4 * ‖u - half • (wq + wp)‖ * ‖u - half • (wq + wp)‖ := by simp [← this] _ ≤ 2 * (‖a‖ * ‖a‖ + ‖b‖ * ‖b‖) - 4 * δ * δ := by gcongr _ ≤ 2 * ((δ + div) * (δ + div) + (δ + div) * (δ + div)) - 4 * δ * δ := by gcongr _ = 8 * δ * div + 4 * div * div := by ring positivity -- third goal : `Tendsto (fun (n : ℕ) => √(b n)) atTop (𝓝 0)` suffices Tendsto (fun x ↦ √(8 * δ * x + 4 * x * x) : ℝ → ℝ) (𝓝 0) (𝓝 0) from this.comp tendsto_one_div_add_atTop_nhds_zero_nat exact Continuous.tendsto' (by fun_prop) _ _ (by simp) -- Step 3: By completeness of `K`, let `w : ℕ → K` converge to some `v : K`. -- Prove that it satisfies all requirements. rcases cauchySeq_tendsto_of_isComplete h₁ (fun n => Subtype.mem _) seq_is_cauchy with ⟨v, hv, w_tendsto⟩ use v use hv have h_cont : Continuous fun v => ‖u - v‖ := Continuous.comp continuous_norm (Continuous.sub continuous_const continuous_id) have : Tendsto (fun n => ‖u - w n‖) atTop (𝓝 ‖u - v‖) := by convert Tendsto.comp h_cont.continuousAt w_tendsto exact tendsto_nhds_unique this norm_tendsto /-- Characterization of minimizers for the projection on a convex set in a real inner product space. -/ theorem norm_eq_iInf_iff_real_inner_le_zero {K : Set F} (h : Convex ℝ K) {u : F} {v : F} (hv : v ∈ K) : (‖u - v‖ = ⨅ w : K, ‖u - w‖) ↔ ∀ w ∈ K, ⟪u - v, w - v⟫_ℝ ≤ 0 := by letI : Nonempty K := ⟨⟨v, hv⟩⟩ constructor · intro eq w hw let δ := ⨅ w : K, ‖u - w‖ let p := ⟪u - v, w - v⟫_ℝ let q := ‖w - v‖ ^ 2 have δ_le (w : K) : δ ≤ ‖u - w‖ := ciInf_le ⟨0, fun _ ⟨_, h⟩ => h ▸ norm_nonneg _⟩ _ have δ_le' (w) (hw : w ∈ K) : δ ≤ ‖u - w‖ := δ_le ⟨w, hw⟩ have (θ : ℝ) (hθ₁ : 0 < θ) (hθ₂ : θ ≤ 1) : 2 * p ≤ θ * q := by have : ‖u - v‖ ^ 2 ≤ ‖u - v‖ ^ 2 - 2 * θ * ⟪u - v, w - v⟫_ℝ + θ * θ * ‖w - v‖ ^ 2 := calc ‖u - v‖ ^ 2 _ ≤ ‖u - (θ • w + (1 - θ) • v)‖ ^ 2 := by simp only [sq]; apply mul_self_le_mul_self (norm_nonneg _) rw [eq]; apply δ_le' apply h hw hv exacts [le_of_lt hθ₁, sub_nonneg.2 hθ₂, add_sub_cancel _ _] _ = ‖u - v - θ • (w - v)‖ ^ 2 := by have : u - (θ • w + (1 - θ) • v) = u - v - θ • (w - v) := by rw [smul_sub, sub_smul, one_smul] simp only [sub_eq_add_neg, add_comm, add_left_comm, add_assoc, neg_add_rev] rw [this] _ = ‖u - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v) + θ * θ * ‖w - v‖ ^ 2 := by rw [@norm_sub_sq ℝ, inner_smul_right, norm_smul] simp only [sq] show ‖u - v‖ * ‖u - v‖ - 2 * (θ * inner (u - v) (w - v)) + absR θ * ‖w - v‖ * (absR θ * ‖w - v‖) = ‖u - v‖ * ‖u - v‖ - 2 * θ * inner (u - v) (w - v) + θ * θ * (‖w - v‖ * ‖w - v‖) rw [abs_of_pos hθ₁]; ring have eq₁ : ‖u - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v) + θ * θ * ‖w - v‖ ^ 2 = ‖u - v‖ ^ 2 + (θ * θ * ‖w - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v)) := by abel rw [eq₁, le_add_iff_nonneg_right] at this have eq₂ : θ * θ * ‖w - v‖ ^ 2 - 2 * θ * inner (u - v) (w - v) = θ * (θ * ‖w - v‖ ^ 2 - 2 * inner (u - v) (w - v)) := by ring rw [eq₂] at this exact le_of_sub_nonneg (nonneg_of_mul_nonneg_right this hθ₁) by_cases hq : q = 0 · rw [hq] at this have : p ≤ 0 := by have := this (1 : ℝ) (by norm_num) (by norm_num) linarith exact this · have q_pos : 0 < q := lt_of_le_of_ne (sq_nonneg _) fun h ↦ hq h.symm by_contra hp rw [not_le] at hp let θ := min (1 : ℝ) (p / q) have eq₁ : θ * q ≤ p := calc θ * q ≤ p / q * q := mul_le_mul_of_nonneg_right (min_le_right _ _) (sq_nonneg _) _ = p := div_mul_cancel₀ _ hq have : 2 * p ≤ p := calc 2 * p ≤ θ * q := by exact this θ (lt_min (by norm_num) (div_pos hp q_pos)) (by norm_num [θ]) _ ≤ p := eq₁ linarith · intro h apply le_antisymm · apply le_ciInf intro w apply nonneg_le_nonneg_of_sq_le_sq (norm_nonneg _) have := h w w.2 calc ‖u - v‖ * ‖u - v‖ ≤ ‖u - v‖ * ‖u - v‖ - 2 * inner (u - v) ((w : F) - v) := by linarith _ ≤ ‖u - v‖ ^ 2 - 2 * inner (u - v) ((w : F) - v) + ‖(w : F) - v‖ ^ 2 := by rw [sq] refine le_add_of_nonneg_right ?_ exact sq_nonneg _ _ = ‖u - v - (w - v)‖ ^ 2 := (@norm_sub_sq ℝ _ _ _ _ _ _).symm _ = ‖u - w‖ * ‖u - w‖ := by have : u - v - (w - v) = u - w := by abel rw [this, sq] · show ⨅ w : K, ‖u - w‖ ≤ (fun w : K => ‖u - w‖) ⟨v, hv⟩ apply ciInf_le use 0 rintro y ⟨z, rfl⟩ exact norm_nonneg _ variable (K : Submodule 𝕜 E) namespace Submodule /-- Existence of projections on complete subspaces. Let `u` be a point in an inner product space, and let `K` be a nonempty complete subspace. Then there exists a (unique) `v` in `K` that minimizes the distance `‖u - v‖` to `u`. This point `v` is usually called the orthogonal projection of `u` onto `K`. -/ theorem exists_norm_eq_iInf_of_complete_subspace (h : IsComplete (↑K : Set E)) : ∀ u : E, ∃ v ∈ K, ‖u - v‖ = ⨅ w : (K : Set E), ‖u - w‖ := by letI : InnerProductSpace ℝ E := InnerProductSpace.rclikeToReal 𝕜 E letI : Module ℝ E := RestrictScalars.module ℝ 𝕜 E let K' : Submodule ℝ E := Submodule.restrictScalars ℝ K exact exists_norm_eq_iInf_of_complete_convex ⟨0, K'.zero_mem⟩ h K'.convex /-- Characterization of minimizers in the projection on a subspace, in the real case. Let `u` be a point in a real inner product space, and let `K` be a nonempty subspace. Then point `v` minimizes the distance `‖u - v‖` over points in `K` if and only if for all `w ∈ K`, `⟪u - v, w⟫ = 0` (i.e., `u - v` is orthogonal to the subspace `K`). This is superseded by `norm_eq_iInf_iff_inner_eq_zero` that gives the same conclusion over any `RCLike` field. -/ theorem norm_eq_iInf_iff_real_inner_eq_zero (K : Submodule ℝ F) {u : F} {v : F} (hv : v ∈ K) : (‖u - v‖ = ⨅ w : (↑K : Set F), ‖u - w‖) ↔ ∀ w ∈ K, ⟪u - v, w⟫_ℝ = 0 := Iff.intro (by intro h have h : ∀ w ∈ K, ⟪u - v, w - v⟫_ℝ ≤ 0 := by rwa [norm_eq_iInf_iff_real_inner_le_zero] at h exacts [K.convex, hv] intro w hw have le : ⟪u - v, w⟫_ℝ ≤ 0 := by let w' := w + v have : w' ∈ K := Submodule.add_mem _ hw hv have h₁ := h w' this have h₂ : w' - v = w := by simp only [w', add_neg_cancel_right, sub_eq_add_neg] rw [h₂] at h₁ exact h₁ have ge : ⟪u - v, w⟫_ℝ ≥ 0 := by let w'' := -w + v have : w'' ∈ K := Submodule.add_mem _ (Submodule.neg_mem _ hw) hv have h₁ := h w'' this have h₂ : w'' - v = -w := by simp only [w'', neg_inj, add_neg_cancel_right, sub_eq_add_neg] rw [h₂, inner_neg_right] at h₁ linarith exact le_antisymm le ge) (by intro h have : ∀ w ∈ K, ⟪u - v, w - v⟫_ℝ ≤ 0 := by intro w hw let w' := w - v have : w' ∈ K := Submodule.sub_mem _ hw hv have h₁ := h w' this exact le_of_eq h₁ rwa [norm_eq_iInf_iff_real_inner_le_zero] exacts [Submodule.convex _, hv]) /-- Characterization of minimizers in the projection on a subspace. Let `u` be a point in an inner product space, and let `K` be a nonempty subspace. Then point `v` minimizes the distance `‖u - v‖` over points in `K` if and only if for all `w ∈ K`, `⟪u - v, w⟫ = 0` (i.e., `u - v` is orthogonal to the subspace `K`) -/ theorem norm_eq_iInf_iff_inner_eq_zero {u : E} {v : E} (hv : v ∈ K) : (‖u - v‖ = ⨅ w : K, ‖u - w‖) ↔ ∀ w ∈ K, ⟪u - v, w⟫ = 0 := by letI : InnerProductSpace ℝ E := InnerProductSpace.rclikeToReal 𝕜 E letI : Module ℝ E := RestrictScalars.module ℝ 𝕜 E let K' : Submodule ℝ E := K.restrictScalars ℝ constructor · intro H have A : ∀ w ∈ K, re ⟪u - v, w⟫ = 0 := (K'.norm_eq_iInf_iff_real_inner_eq_zero hv).1 H intro w hw apply RCLike.ext · simp [A w hw] · symm calc im (0 : 𝕜) = 0 := im.map_zero _ = re ⟪u - v, (-I : 𝕜) • w⟫ := (A _ (K.smul_mem (-I) hw)).symm _ = re (-I * ⟪u - v, w⟫) := by rw [inner_smul_right] _ = im ⟪u - v, w⟫ := by simp · intro H have : ∀ w ∈ K', ⟪u - v, w⟫_ℝ = 0 := by intro w hw rw [real_inner_eq_re_inner, H w hw] exact zero_re' exact (K'.norm_eq_iInf_iff_real_inner_eq_zero hv).2 this /-- A subspace `K : Submodule 𝕜 E` has an orthogonal projection if every vector `v : E` admits an orthogonal projection to `K`. -/ class HasOrthogonalProjection (K : Submodule 𝕜 E) : Prop where exists_orthogonal (v : E) : ∃ w ∈ K, v - w ∈ Kᗮ instance (priority := 100) HasOrthogonalProjection.ofCompleteSpace [CompleteSpace K] : K.HasOrthogonalProjection where exists_orthogonal v := by rcases K.exists_norm_eq_iInf_of_complete_subspace (completeSpace_coe_iff_isComplete.mp ‹_›) v with ⟨w, hwK, hw⟩ refine ⟨w, hwK, (K.mem_orthogonal' _).2 ?_⟩ rwa [← K.norm_eq_iInf_iff_inner_eq_zero hwK] instance [K.HasOrthogonalProjection] : Kᗮ.HasOrthogonalProjection where exists_orthogonal v := by rcases HasOrthogonalProjection.exists_orthogonal (K := K) v with ⟨w, hwK, hw⟩ refine ⟨_, hw, ?_⟩ rw [sub_sub_cancel] exact K.le_orthogonal_orthogonal hwK instance HasOrthogonalProjection.map_linearIsometryEquiv [K.HasOrthogonalProjection] {E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') : (K.map (f.toLinearEquiv : E →ₗ[𝕜] E')).HasOrthogonalProjection where exists_orthogonal v := by rcases HasOrthogonalProjection.exists_orthogonal (K := K) (f.symm v) with ⟨w, hwK, hw⟩ refine ⟨f w, Submodule.mem_map_of_mem hwK, Set.forall_mem_image.2 fun u hu ↦ ?_⟩ erw [← f.symm.inner_map_map, f.symm_apply_apply, map_sub, f.symm_apply_apply, hw u hu] instance HasOrthogonalProjection.map_linearIsometryEquiv' [K.HasOrthogonalProjection] {E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') : (K.map f.toLinearIsometry).HasOrthogonalProjection := HasOrthogonalProjection.map_linearIsometryEquiv K f instance : (⊤ : Submodule 𝕜 E).HasOrthogonalProjection := ⟨fun v ↦ ⟨v, trivial, by simp⟩⟩ section orthogonalProjection variable [K.HasOrthogonalProjection] /-- The orthogonal projection onto a complete subspace, as an unbundled function. This definition is only intended for use in setting up the bundled version `orthogonalProjection` and should not be used once that is defined. -/ def orthogonalProjectionFn (v : E) := (HasOrthogonalProjection.exists_orthogonal (K := K) v).choose variable {K} /-- The unbundled orthogonal projection is in the given subspace. This lemma is only intended for use in setting up the bundled version and should not be used once that is defined. -/ theorem orthogonalProjectionFn_mem (v : E) : K.orthogonalProjectionFn v ∈ K := (HasOrthogonalProjection.exists_orthogonal (K := K) v).choose_spec.left /-- The characterization of the unbundled orthogonal projection. This lemma is only intended for use in setting up the bundled version and should not be used once that is defined. -/ theorem orthogonalProjectionFn_inner_eq_zero (v : E) : ∀ w ∈ K, ⟪v - K.orthogonalProjectionFn v, w⟫ = 0 := (K.mem_orthogonal' _).1 (HasOrthogonalProjection.exists_orthogonal (K := K) v).choose_spec.right /-- The unbundled orthogonal projection is the unique point in `K` with the orthogonality property. This lemma is only intended for use in setting up the bundled version and should not be used once that is defined. -/ theorem eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero {u v : E} (hvm : v ∈ K) (hvo : ∀ w ∈ K, ⟪u - v, w⟫ = 0) : K.orthogonalProjectionFn u = v := by rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜] have hvs : K.orthogonalProjectionFn u - v ∈ K := Submodule.sub_mem K (orthogonalProjectionFn_mem u) hvm have huo : ⟪u - K.orthogonalProjectionFn u, K.orthogonalProjectionFn u - v⟫ = 0 := orthogonalProjectionFn_inner_eq_zero u _ hvs have huv : ⟪u - v, K.orthogonalProjectionFn u - v⟫ = 0 := hvo _ hvs have houv : ⟪u - v - (u - K.orthogonalProjectionFn u), K.orthogonalProjectionFn u - v⟫ = 0 := by rw [inner_sub_left, huo, huv, sub_zero] rwa [sub_sub_sub_cancel_left] at houv variable (K) theorem orthogonalProjectionFn_norm_sq (v : E) : ‖v‖ * ‖v‖ = ‖v - K.orthogonalProjectionFn v‖ * ‖v - K.orthogonalProjectionFn v‖ + ‖K.orthogonalProjectionFn v‖ * ‖K.orthogonalProjectionFn v‖ := by set p := K.orthogonalProjectionFn v have h' : ⟪v - p, p⟫ = 0 := orthogonalProjectionFn_inner_eq_zero _ _ (orthogonalProjectionFn_mem v) convert norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero (v - p) p h' using 2 <;> simp /-- The orthogonal projection onto a complete subspace. -/ def orthogonalProjection : E →L[𝕜] K := LinearMap.mkContinuous { toFun := fun v => ⟨K.orthogonalProjectionFn v, orthogonalProjectionFn_mem v⟩ map_add' := fun x y => by have hm : K.orthogonalProjectionFn x + K.orthogonalProjectionFn y ∈ K := Submodule.add_mem K (orthogonalProjectionFn_mem x) (orthogonalProjectionFn_mem y) have ho : ∀ w ∈ K, ⟪x + y - (K.orthogonalProjectionFn x + K.orthogonalProjectionFn y), w⟫ = 0 := by intro w hw rw [add_sub_add_comm, inner_add_left, orthogonalProjectionFn_inner_eq_zero _ w hw, orthogonalProjectionFn_inner_eq_zero _ w hw, add_zero] ext simp [eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hm ho] map_smul' := fun c x => by have hm : c • K.orthogonalProjectionFn x ∈ K := Submodule.smul_mem K _ (orthogonalProjectionFn_mem x) have ho : ∀ w ∈ K, ⟪c • x - c • K.orthogonalProjectionFn x, w⟫ = 0 := by intro w hw rw [← smul_sub, inner_smul_left, orthogonalProjectionFn_inner_eq_zero _ w hw, mul_zero] ext simp [eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hm ho] } 1 fun x => by simp only [one_mul, LinearMap.coe_mk] refine le_of_pow_le_pow_left₀ two_ne_zero (norm_nonneg _) ?_ change ‖K.orthogonalProjectionFn x‖ ^ 2 ≤ ‖x‖ ^ 2 nlinarith [K.orthogonalProjectionFn_norm_sq x] variable {K} @[simp] theorem orthogonalProjectionFn_eq (v : E) : K.orthogonalProjectionFn v = (K.orthogonalProjection v : E) := rfl /-- The characterization of the orthogonal projection. -/ @[simp] theorem orthogonalProjection_inner_eq_zero (v : E) : ∀ w ∈ K, ⟪v - K.orthogonalProjection v, w⟫ = 0 := orthogonalProjectionFn_inner_eq_zero v /-- The difference of `v` from its orthogonal projection onto `K` is in `Kᗮ`. -/ @[simp] theorem sub_orthogonalProjection_mem_orthogonal (v : E) : v - K.orthogonalProjection v ∈ Kᗮ := by intro w hw rw [inner_eq_zero_symm] exact orthogonalProjection_inner_eq_zero _ _ hw /-- The orthogonal projection is the unique point in `K` with the orthogonality property. -/ theorem eq_orthogonalProjection_of_mem_of_inner_eq_zero {u v : E} (hvm : v ∈ K) (hvo : ∀ w ∈ K, ⟪u - v, w⟫ = 0) : (K.orthogonalProjection u : E) = v := eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hvm hvo /-- A point in `K` with the orthogonality property (here characterized in terms of `Kᗮ`) must be the orthogonal projection. -/ theorem eq_orthogonalProjection_of_mem_orthogonal {u v : E} (hv : v ∈ K) (hvo : u - v ∈ Kᗮ) : (K.orthogonalProjection u : E) = v := eq_orthogonalProjectionFn_of_mem_of_inner_eq_zero hv <| (Submodule.mem_orthogonal' _ _).1 hvo /-- A point in `K` with the orthogonality property (here characterized in terms of `Kᗮ`) must be the orthogonal projection. -/ theorem eq_orthogonalProjection_of_mem_orthogonal' {u v z : E} (hv : v ∈ K) (hz : z ∈ Kᗮ) (hu : u = v + z) : (K.orthogonalProjection u : E) = v := eq_orthogonalProjection_of_mem_orthogonal hv (by simpa [hu] ) @[simp] theorem orthogonalProjection_orthogonal_val (u : E) : (Kᗮ.orthogonalProjection u : E) = u - K.orthogonalProjection u := eq_orthogonalProjection_of_mem_orthogonal' (sub_orthogonalProjection_mem_orthogonal _) (K.le_orthogonal_orthogonal (K.orthogonalProjection u).2) <| by simp theorem orthogonalProjection_orthogonal (u : E) : Kᗮ.orthogonalProjection u = ⟨u - K.orthogonalProjection u, sub_orthogonalProjection_mem_orthogonal _⟩ := Subtype.eq <| orthogonalProjection_orthogonal_val _ /-- The orthogonal projection of `y` on `U` minimizes the distance `‖y - x‖` for `x ∈ U`. -/ theorem orthogonalProjection_minimal {U : Submodule 𝕜 E} [U.HasOrthogonalProjection] (y : E) : ‖y - U.orthogonalProjection y‖ = ⨅ x : U, ‖y - x‖ := by rw [U.norm_eq_iInf_iff_inner_eq_zero (Submodule.coe_mem _)] exact orthogonalProjection_inner_eq_zero _ /-- The orthogonal projections onto equal subspaces are coerced back to the same point in `E`. -/ theorem eq_orthogonalProjection_of_eq_submodule {K' : Submodule 𝕜 E} [K'.HasOrthogonalProjection] (h : K = K') (u : E) : (K.orthogonalProjection u : E) = (K'.orthogonalProjection u : E) := by subst h; rfl /-- The orthogonal projection sends elements of `K` to themselves. -/ @[simp] theorem orthogonalProjection_mem_subspace_eq_self (v : K) : K.orthogonalProjection v = v := by ext apply eq_orthogonalProjection_of_mem_of_inner_eq_zero <;> simp /-- A point equals its orthogonal projection if and only if it lies in the subspace. -/ theorem orthogonalProjection_eq_self_iff {v : E} : (K.orthogonalProjection v : E) = v ↔ v ∈ K := by refine ⟨fun h => ?_, fun h => eq_orthogonalProjection_of_mem_of_inner_eq_zero h ?_⟩ · rw [← h] simp · simp @[simp] theorem orthogonalProjection_eq_zero_iff {v : E} : K.orthogonalProjection v = 0 ↔ v ∈ Kᗮ := by refine ⟨fun h ↦ ?_, fun h ↦ Subtype.eq <| eq_orthogonalProjection_of_mem_orthogonal (zero_mem _) ?_⟩ · simpa [h] using sub_orthogonalProjection_mem_orthogonal (K := K) v · simpa @[simp] theorem ker_orthogonalProjection : LinearMap.ker K.orthogonalProjection = Kᗮ := by ext; exact orthogonalProjection_eq_zero_iff theorem _root_.LinearIsometry.map_orthogonalProjection {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E →ₗᵢ[𝕜] E') (p : Submodule 𝕜 E) [p.HasOrthogonalProjection] [(p.map f.toLinearMap).HasOrthogonalProjection] (x : E) : f (p.orthogonalProjection x) = (p.map f.toLinearMap).orthogonalProjection (f x) := by refine (eq_orthogonalProjection_of_mem_of_inner_eq_zero ?_ fun y hy => ?_).symm · refine Submodule.apply_coe_mem_map _ _ rcases hy with ⟨x', hx', rfl : f x' = y⟩ rw [← f.map_sub, f.inner_map_map, orthogonalProjection_inner_eq_zero x x' hx'] theorem _root_.LinearIsometry.map_orthogonalProjection' {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E →ₗᵢ[𝕜] E') (p : Submodule 𝕜 E) [p.HasOrthogonalProjection] [(p.map f).HasOrthogonalProjection] (x : E) : f (p.orthogonalProjection x) = (p.map f).orthogonalProjection (f x) := have : (p.map f.toLinearMap).HasOrthogonalProjection := ‹_› f.map_orthogonalProjection p x /-- Orthogonal projection onto the `Submodule.map` of a subspace. -/ theorem orthogonalProjection_map_apply {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') (p : Submodule 𝕜 E) [p.HasOrthogonalProjection] (x : E') : ((p.map (f.toLinearEquiv : E →ₗ[𝕜] E')).orthogonalProjection x : E') = f (p.orthogonalProjection (f.symm x)) := by simpa only [f.coe_toLinearIsometry, f.apply_symm_apply] using (f.toLinearIsometry.map_orthogonalProjection' p (f.symm x)).symm /-- The orthogonal projection onto the trivial submodule is the zero map. -/ @[simp] theorem orthogonalProjection_bot : (⊥ : Submodule 𝕜 E).orthogonalProjection = 0 := by ext variable (K) /-- The orthogonal projection has norm `≤ 1`. -/ theorem orthogonalProjection_norm_le : ‖K.orthogonalProjection‖ ≤ 1 := LinearMap.mkContinuous_norm_le _ (by norm_num) _ variable (𝕜) theorem smul_orthogonalProjection_singleton {v : E} (w : E) : ((‖v‖ ^ 2 : ℝ) : 𝕜) • ((𝕜 ∙ v).orthogonalProjection w : E) = ⟪v, w⟫ • v := by suffices (((𝕜 ∙ v).orthogonalProjection (((‖v‖ : 𝕜) ^ 2) • w)) : E) = ⟪v, w⟫ • v by simpa using this apply eq_orthogonalProjection_of_mem_of_inner_eq_zero · rw [Submodule.mem_span_singleton] use ⟪v, w⟫ · rw [← Submodule.mem_orthogonal', Submodule.mem_orthogonal_singleton_iff_inner_left] simp [inner_sub_left, inner_smul_left, inner_self_eq_norm_sq_to_K, mul_comm] /-- Formula for orthogonal projection onto a single vector. -/ theorem orthogonalProjection_singleton {v : E} (w : E) : ((𝕜 ∙ v).orthogonalProjection w : E) = (⟪v, w⟫ / ((‖v‖ ^ 2 : ℝ) : 𝕜)) • v := by by_cases hv : v = 0 · rw [hv, eq_orthogonalProjection_of_eq_submodule (Submodule.span_zero_singleton 𝕜)] simp have hv' : ‖v‖ ≠ 0 := ne_of_gt (norm_pos_iff.mpr hv) have key : (((‖v‖ ^ 2 : ℝ) : 𝕜)⁻¹ * ((‖v‖ ^ 2 : ℝ) : 𝕜)) • (((𝕜 ∙ v).orthogonalProjection w) : E) = (((‖v‖ ^ 2 : ℝ) : 𝕜)⁻¹ * ⟪v, w⟫) • v := by simp [mul_smul, smul_orthogonalProjection_singleton 𝕜 w, -map_pow] convert key using 1 <;> field_simp [hv'] /-- Formula for orthogonal projection onto a single unit vector. -/ theorem orthogonalProjection_unit_singleton {v : E} (hv : ‖v‖ = 1) (w : E) : ((𝕜 ∙ v).orthogonalProjection w : E) = ⟪v, w⟫ • v := by rw [← smul_orthogonalProjection_singleton 𝕜 w] simp [hv] end orthogonalProjection section reflection variable [K.HasOrthogonalProjection] /-- Auxiliary definition for `reflection`: the reflection as a linear equivalence. -/ def reflectionLinearEquiv : E ≃ₗ[𝕜] E := LinearEquiv.ofInvolutive (2 • (K.subtype.comp K.orthogonalProjection.toLinearMap) - LinearMap.id) fun x => by simp [two_smul] /-- Reflection in a complete subspace of an inner product space. The word "reflection" is sometimes understood to mean specifically reflection in a codimension-one subspace, and sometimes more generally to cover operations such as reflection in a point. The definition here, of reflection in a subspace, is a more general sense of the word that includes both those common cases. -/ def reflection : E ≃ₗᵢ[𝕜] E := { K.reflectionLinearEquiv with norm_map' := by intro x let w : K := K.orthogonalProjection x let v := x - w have : ⟪v, w⟫ = 0 := orthogonalProjection_inner_eq_zero x w w.2 convert norm_sub_eq_norm_add this using 2 · rw [LinearEquiv.coe_mk, reflectionLinearEquiv, LinearEquiv.toFun_eq_coe, LinearEquiv.coe_ofInvolutive, LinearMap.sub_apply, LinearMap.id_apply, two_smul, LinearMap.add_apply, LinearMap.comp_apply, Submodule.subtype_apply, ContinuousLinearMap.coe_coe] dsimp [v] abel · simp only [v, add_sub_cancel, eq_self_iff_true] } variable {K} /-- The result of reflecting. -/ theorem reflection_apply (p : E) : K.reflection p = 2 • (K.orthogonalProjection p : E) - p := rfl /-- Reflection is its own inverse. -/ @[simp] theorem reflection_symm : K.reflection.symm = K.reflection := rfl /-- Reflection is its own inverse. -/ @[simp] theorem reflection_inv : K.reflection⁻¹ = K.reflection := rfl variable (K) /-- Reflecting twice in the same subspace. -/ @[simp] theorem reflection_reflection (p : E) : K.reflection (K.reflection p) = p := K.reflection.left_inv p /-- Reflection is involutive. -/ theorem reflection_involutive : Function.Involutive K.reflection := K.reflection_reflection /-- Reflection is involutive. -/ @[simp] theorem reflection_trans_reflection : K.reflection.trans K.reflection = LinearIsometryEquiv.refl 𝕜 E := LinearIsometryEquiv.ext <| reflection_involutive K /-- Reflection is involutive. -/ @[simp] theorem reflection_mul_reflection : K.reflection * K.reflection = 1 := reflection_trans_reflection _ theorem reflection_orthogonal_apply (v : E) : Kᗮ.reflection v = -K.reflection v := by simp [reflection_apply]; abel theorem reflection_orthogonal : Kᗮ.reflection = .trans K.reflection (.neg _) := by ext; apply reflection_orthogonal_apply variable {K} theorem reflection_singleton_apply (u v : E) : reflection (𝕜 ∙ u) v = 2 • (⟪u, v⟫ / ((‖u‖ : 𝕜) ^ 2)) • u - v := by rw [reflection_apply, orthogonalProjection_singleton, ofReal_pow] /-- A point is its own reflection if and only if it is in the subspace. -/ theorem reflection_eq_self_iff (x : E) : K.reflection x = x ↔ x ∈ K := by rw [← orthogonalProjection_eq_self_iff, reflection_apply, sub_eq_iff_eq_add', ← two_smul 𝕜, two_smul ℕ, ← two_smul 𝕜] refine (smul_right_injective E ?_).eq_iff exact two_ne_zero theorem reflection_mem_subspace_eq_self {x : E} (hx : x ∈ K) : K.reflection x = x := (reflection_eq_self_iff x).mpr hx /-- Reflection in the `Submodule.map` of a subspace. -/ theorem reflection_map_apply {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') (K : Submodule 𝕜 E) [K.HasOrthogonalProjection] (x : E') : reflection (K.map (f.toLinearEquiv : E →ₗ[𝕜] E')) x = f (K.reflection (f.symm x)) := by simp [two_smul, reflection_apply, orthogonalProjection_map_apply f K x] /-- Reflection in the `Submodule.map` of a subspace. -/ theorem reflection_map {E E' : Type*} [NormedAddCommGroup E] [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E] [InnerProductSpace 𝕜 E'] (f : E ≃ₗᵢ[𝕜] E') (K : Submodule 𝕜 E) [K.HasOrthogonalProjection] : reflection (K.map (f.toLinearEquiv : E →ₗ[𝕜] E')) = f.symm.trans (K.reflection.trans f) := LinearIsometryEquiv.ext <| reflection_map_apply f K /-- Reflection through the trivial subspace {0} is just negation. -/ @[simp] theorem reflection_bot : reflection (⊥ : Submodule 𝕜 E) = LinearIsometryEquiv.neg 𝕜 := by ext; simp [reflection_apply] end reflection end Submodule section Orthogonal namespace Submodule /-- If `K₁` is complete and contained in `K₂`, `K₁` and `K₁ᗮ ⊓ K₂` span `K₂`. -/ theorem sup_orthogonal_inf_of_completeSpace {K₁ K₂ : Submodule 𝕜 E} (h : K₁ ≤ K₂) [K₁.HasOrthogonalProjection] : K₁ ⊔ K₁ᗮ ⊓ K₂ = K₂ := by ext x rw [Submodule.mem_sup] let v : K₁ := orthogonalProjection K₁ x have hvm : x - v ∈ K₁ᗮ := sub_orthogonalProjection_mem_orthogonal x constructor · rintro ⟨y, hy, z, hz, rfl⟩ exact K₂.add_mem (h hy) hz.2 · exact fun hx => ⟨v, v.prop, x - v, ⟨hvm, K₂.sub_mem hx (h v.prop)⟩, add_sub_cancel _ _⟩ variable {K} in /-- If `K` is complete, `K` and `Kᗮ` span the whole space. -/ theorem sup_orthogonal_of_completeSpace [K.HasOrthogonalProjection] : K ⊔ Kᗮ = ⊤ := by convert Submodule.sup_orthogonal_inf_of_completeSpace (le_top : K ≤ ⊤) using 2 simp /-- If `K` is complete, any `v` in `E` can be expressed as a sum of elements of `K` and `Kᗮ`. -/ theorem exists_add_mem_mem_orthogonal [K.HasOrthogonalProjection] (v : E) : ∃ y ∈ K, ∃ z ∈ Kᗮ, v = y + z := ⟨K.orthogonalProjection v, Subtype.coe_prop _, v - K.orthogonalProjection v, sub_orthogonalProjection_mem_orthogonal _, by simp⟩ /-- If `K` admits an orthogonal projection, then the orthogonal complement of its orthogonal complement is itself. -/ @[simp] theorem orthogonal_orthogonal [K.HasOrthogonalProjection] : Kᗮᗮ = K := by ext v constructor · obtain ⟨y, hy, z, hz, rfl⟩ := K.exists_add_mem_mem_orthogonal v intro hv have hz' : z = 0 := by have hyz : ⟪z, y⟫ = 0 := by simp [hz y hy, inner_eq_zero_symm] simpa [inner_add_right, hyz] using hv z hz simp [hy, hz'] · intro hv w hw rw [inner_eq_zero_symm] exact hw v hv /-- In a Hilbert space, the orthogonal complement of the orthogonal complement of a subspace `K` is the topological closure of `K`. Note that the completeness assumption is necessary. Let `E` be the space `ℕ →₀ ℝ` with inner space structure inherited from `PiLp 2 (fun _ : ℕ ↦ ℝ)`. Let `K` be the subspace of sequences with the sum of all elements equal to zero. Then `Kᗮ = ⊥`, `Kᗮᗮ = ⊤`. -/ theorem orthogonal_orthogonal_eq_closure [CompleteSpace E] : Kᗮᗮ = K.topologicalClosure := by refine le_antisymm ?_ ?_ · convert Submodule.orthogonal_orthogonal_monotone K.le_topologicalClosure using 1 rw [K.topologicalClosure.orthogonal_orthogonal] · exact K.topologicalClosure_minimal K.le_orthogonal_orthogonal Kᗮ.isClosed_orthogonal variable {K} /-- If `K` admits an orthogonal projection, `K` and `Kᗮ` are complements of each other. -/ theorem isCompl_orthogonal_of_completeSpace [K.HasOrthogonalProjection] : IsCompl K Kᗮ := ⟨K.orthogonal_disjoint, codisjoint_iff.2 Submodule.sup_orthogonal_of_completeSpace⟩ @[simp] theorem orthogonalComplement_eq_orthogonalComplement {L : Submodule 𝕜 E} [K.HasOrthogonalProjection] [L.HasOrthogonalProjection] : Kᗮ = Lᗮ ↔ K = L := ⟨fun h ↦ by simpa using congr(Submodule.orthogonal $(h)), fun h ↦ congr(Submodule.orthogonal $(h))⟩ @[simp] theorem orthogonal_eq_bot_iff [K.HasOrthogonalProjection] : Kᗮ = ⊥ ↔ K = ⊤ := by refine ⟨?_, fun h => by rw [h, Submodule.top_orthogonal_eq_bot]⟩ intro h have : K ⊔ Kᗮ = ⊤ := Submodule.sup_orthogonal_of_completeSpace rwa [h, sup_comm, bot_sup_eq] at this /-- The orthogonal projection onto `K` of an element of `Kᗮ` is zero. -/ theorem orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero [K.HasOrthogonalProjection] {v : E} (hv : v ∈ Kᗮ) : K.orthogonalProjection v = 0 := by ext convert eq_orthogonalProjection_of_mem_orthogonal (K := K) _ _ <;> simp [hv] /-- The projection into `U` from an orthogonal submodule `V` is the zero map. -/ theorem IsOrtho.orthogonalProjection_comp_subtypeL {U V : Submodule 𝕜 E} [U.HasOrthogonalProjection] (h : U ⟂ V) : U.orthogonalProjection ∘L V.subtypeL = 0 := ContinuousLinearMap.ext fun v => orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero <| h.symm v.prop /-- The projection into `U` from `V` is the zero map if and only if `U` and `V` are orthogonal. -/ theorem orthogonalProjection_comp_subtypeL_eq_zero_iff {U V : Submodule 𝕜 E} [U.HasOrthogonalProjection] : U.orthogonalProjection ∘L V.subtypeL = 0 ↔ U ⟂ V := ⟨fun h u hu v hv => by convert orthogonalProjection_inner_eq_zero v u hu using 2 have : U.orthogonalProjection v = 0 := DFunLike.congr_fun h (⟨_, hv⟩ : V) rw [this, Submodule.coe_zero, sub_zero], Submodule.IsOrtho.orthogonalProjection_comp_subtypeL⟩ theorem orthogonalProjection_eq_linear_proj [K.HasOrthogonalProjection] (x : E) : K.orthogonalProjection x = K.linearProjOfIsCompl _ Submodule.isCompl_orthogonal_of_completeSpace x := by have : IsCompl K Kᗮ := Submodule.isCompl_orthogonal_of_completeSpace conv_lhs => rw [← Submodule.linear_proj_add_linearProjOfIsCompl_eq_self this x] rw [map_add, orthogonalProjection_mem_subspace_eq_self, orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero (Submodule.coe_mem _), add_zero] theorem orthogonalProjection_coe_linearMap_eq_linearProj [K.HasOrthogonalProjection] : (K.orthogonalProjection : E →ₗ[𝕜] K) = K.linearProjOfIsCompl _ Submodule.isCompl_orthogonal_of_completeSpace := LinearMap.ext <| orthogonalProjection_eq_linear_proj /-- The reflection in `K` of an element of `Kᗮ` is its negation. -/ theorem reflection_mem_subspace_orthogonalComplement_eq_neg [K.HasOrthogonalProjection] {v : E} (hv : v ∈ Kᗮ) : K.reflection v = -v := by simp [reflection_apply, orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero hv] /-- The orthogonal projection onto `Kᗮ` of an element of `K` is zero. -/ theorem orthogonalProjection_mem_subspace_orthogonal_precomplement_eq_zero [Kᗮ.HasOrthogonalProjection] {v : E} (hv : v ∈ K) : Kᗮ.orthogonalProjection v = 0 := orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero (K.le_orthogonal_orthogonal hv) /-- If `U ≤ V`, then projecting on `V` and then on `U` is the same as projecting on `U`. -/ theorem orthogonalProjection_orthogonalProjection_of_le {U V : Submodule 𝕜 E} [U.HasOrthogonalProjection] [V.HasOrthogonalProjection] (h : U ≤ V) (x : E) : U.orthogonalProjection (V.orthogonalProjection x) = U.orthogonalProjection x := Eq.symm <| by simpa only [sub_eq_zero, map_sub] using orthogonalProjection_mem_subspace_orthogonalComplement_eq_zero (Submodule.orthogonal_le h (sub_orthogonalProjection_mem_orthogonal x)) /-- Given a monotone family `U` of complete submodules of `E` and a fixed `x : E`, the orthogonal projection of `x` on `U i` tends to the orthogonal projection of `x` on `(⨆ i, U i).topologicalClosure` along `atTop`. -/ theorem orthogonalProjection_tendsto_closure_iSup {ι : Type*} [Preorder ι] (U : ι → Submodule 𝕜 E) [∀ i, (U i).HasOrthogonalProjection] [(⨆ i, U i).topologicalClosure.HasOrthogonalProjection] (hU : Monotone U) (x : E) : Filter.Tendsto (fun i => ((U i).orthogonalProjection x : E)) atTop (𝓝 ((⨆ i, U i).topologicalClosure.orthogonalProjection x : E)) := by refine .of_neBot_imp fun h ↦ ?_ cases atTop_neBot_iff.mp h let y := ((⨆ i, U i).topologicalClosure.orthogonalProjection x : E) have proj_x : ∀ i, (U i).orthogonalProjection x = (U i).orthogonalProjection y := fun i => (orthogonalProjection_orthogonalProjection_of_le ((le_iSup U i).trans (iSup U).le_topologicalClosure) _).symm suffices ∀ ε > 0, ∃ I, ∀ i ≥ I, ‖((U i).orthogonalProjection y : E) - y‖ < ε by simpa only [proj_x, NormedAddCommGroup.tendsto_atTop] using this intro ε hε obtain ⟨a, ha, hay⟩ : ∃ a ∈ ⨆ i, U i, dist y a < ε := by have y_mem : y ∈ (⨆ i, U i).topologicalClosure := Submodule.coe_mem _ rw [← SetLike.mem_coe, Submodule.topologicalClosure_coe, Metric.mem_closure_iff] at y_mem exact y_mem ε hε rw [dist_eq_norm] at hay obtain ⟨I, hI⟩ : ∃ I, a ∈ U I := by rwa [Submodule.mem_iSup_of_directed _ hU.directed_le] at ha refine ⟨I, fun i (hi : I ≤ i) => ?_⟩ rw [norm_sub_rev, orthogonalProjection_minimal] refine lt_of_le_of_lt ?_ hay change _ ≤ ‖y - (⟨a, hU hi hI⟩ : U i)‖ exact ciInf_le ⟨0, Set.forall_mem_range.mpr fun _ => norm_nonneg _⟩ _ /-- Given a monotone family `U` of complete submodules of `E` with dense span supremum, and a fixed `x : E`, the orthogonal projection of `x` on `U i` tends to `x` along `at_top`. -/ theorem orthogonalProjection_tendsto_self {ι : Type*} [Preorder ι] (U : ι → Submodule 𝕜 E) [∀ t, (U t).HasOrthogonalProjection] (hU : Monotone U) (x : E) (hU' : ⊤ ≤ (⨆ t, U t).topologicalClosure) : Filter.Tendsto (fun t => ((U t).orthogonalProjection x : E)) atTop (𝓝 x) := by have : (⨆ i, U i).topologicalClosure.HasOrthogonalProjection := by rw [top_unique hU'] infer_instance convert orthogonalProjection_tendsto_closure_iSup U hU x rw [eq_comm, orthogonalProjection_eq_self_iff, top_unique hU'] trivial /-- The orthogonal complement satisfies `Kᗮᗮᗮ = Kᗮ`. -/ theorem triorthogonal_eq_orthogonal [CompleteSpace E] : Kᗮᗮᗮ = Kᗮ := by rw [Kᗮ.orthogonal_orthogonal_eq_closure] exact K.isClosed_orthogonal.submodule_topologicalClosure_eq /-- The closure of `K` is the full space iff `Kᗮ` is trivial. -/ theorem topologicalClosure_eq_top_iff [CompleteSpace E] : K.topologicalClosure = ⊤ ↔ Kᗮ = ⊥ := by rw [← K.orthogonal_orthogonal_eq_closure] constructor <;> intro h · rw [← Submodule.triorthogonal_eq_orthogonal, h, Submodule.top_orthogonal_eq_bot] · rw [h, Submodule.bot_orthogonal_eq_top] end Submodule namespace Dense /- TODO: Move to another file? -/ open Submodule variable {K} {x y : E} theorem eq_zero_of_inner_left (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪x, v⟫ = 0) : x = 0 := by have : (⟪x, ·⟫) = 0 := (continuous_const.inner continuous_id).ext_on hK continuous_const (Subtype.forall.1 h) simpa using congr_fun this x theorem eq_zero_of_mem_orthogonal (hK : Dense (K : Set E)) (h : x ∈ Kᗮ) : x = 0 := eq_zero_of_inner_left hK fun v ↦ (mem_orthogonal' _ _).1 h _ v.2 /-- If `S` is dense and `x - y ∈ Kᗮ`, then `x = y`. -/ theorem eq_of_sub_mem_orthogonal (hK : Dense (K : Set E)) (h : x - y ∈ Kᗮ) : x = y := sub_eq_zero.1 <| eq_zero_of_mem_orthogonal hK h theorem eq_of_inner_left (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪x, v⟫ = ⟪y, v⟫) : x = y := hK.eq_of_sub_mem_orthogonal (Submodule.sub_mem_orthogonal_of_inner_left h) theorem eq_of_inner_right (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪(v : E), x⟫ = ⟪(v : E), y⟫) : x = y := hK.eq_of_sub_mem_orthogonal (Submodule.sub_mem_orthogonal_of_inner_right h) theorem eq_zero_of_inner_right (hK : Dense (K : Set E)) (h : ∀ v : K, ⟪(v : E), x⟫ = 0) : x = 0 := hK.eq_of_inner_right fun v => by rw [inner_zero_right, h v] end Dense namespace Submodule variable {K} /-- The reflection in `Kᗮ` of an element of `K` is its negation. -/ theorem reflection_mem_subspace_orthogonal_precomplement_eq_neg [K.HasOrthogonalProjection] {v : E} (hv : v ∈ K) : Kᗮ.reflection v = -v := reflection_mem_subspace_orthogonalComplement_eq_neg (K.le_orthogonal_orthogonal hv) /-- The orthogonal projection onto `(𝕜 ∙ v)ᗮ` of `v` is zero. -/ theorem orthogonalProjection_orthogonalComplement_singleton_eq_zero (v : E) : (𝕜 ∙ v)ᗮ.orthogonalProjection v = 0 := orthogonalProjection_mem_subspace_orthogonal_precomplement_eq_zero (Submodule.mem_span_singleton_self v) /-- The reflection in `(𝕜 ∙ v)ᗮ` of `v` is `-v`. -/ theorem reflection_orthogonalComplement_singleton_eq_neg (v : E) : reflection (𝕜 ∙ v)ᗮ v = -v := reflection_mem_subspace_orthogonal_precomplement_eq_neg (Submodule.mem_span_singleton_self v) theorem reflection_sub {v w : F} (h : ‖v‖ = ‖w‖) : reflection (ℝ ∙ (v - w))ᗮ v = w := by set R : F ≃ₗᵢ[ℝ] F := reflection (ℝ ∙ v - w)ᗮ suffices R v + R v = w + w by apply smul_right_injective F (by norm_num : (2 : ℝ) ≠ 0) simpa [two_smul] using this have h₁ : R (v - w) = -(v - w) := reflection_orthogonalComplement_singleton_eq_neg (v - w) have h₂ : R (v + w) = v + w := by apply reflection_mem_subspace_eq_self rw [Submodule.mem_orthogonal_singleton_iff_inner_left] rw [real_inner_add_sub_eq_zero_iff] exact h convert congr_arg₂ (· + ·) h₂ h₁ using 1 · simp · abel variable (K) section FiniteDimensional open Module variable [FiniteDimensional 𝕜 K] @[simp] theorem det_reflection : LinearMap.det K.reflection.toLinearMap = (-1) ^ finrank 𝕜 Kᗮ := by by_cases hK : FiniteDimensional 𝕜 Kᗮ swap · rw [finrank_of_infinite_dimensional hK, pow_zero, LinearMap.det_eq_one_of_finrank_eq_zero] exact finrank_of_infinite_dimensional fun h ↦ hK (h.finiteDimensional_submodule _) let e := K.prodEquivOfIsCompl _ K.isCompl_orthogonal_of_completeSpace let b := (finBasis 𝕜 K).prod (finBasis 𝕜 Kᗮ) have : LinearMap.toMatrix b b (e.symm ∘ₗ K.reflection.toLinearMap ∘ₗ e.symm.symm) = Matrix.fromBlocks 1 0 0 (-1) := by ext (_ | _) (_ | _) <;> simp [LinearMap.toMatrix_apply, b, Matrix.one_apply, Finsupp.single_apply, e, eq_comm, reflection_mem_subspace_eq_self, reflection_mem_subspace_orthogonalComplement_eq_neg] rw [← LinearMap.det_conj _ e.symm, ← LinearMap.det_toMatrix b, this, Matrix.det_fromBlocks_zero₂₁,
Matrix.det_one, one_mul, Matrix.det_neg, Fintype.card_fin, Matrix.det_one, mul_one]
Mathlib/Analysis/InnerProductSpace/Projection.lean
1,007
1,008
/- Copyright (c) 2019 Minchao Wu. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Minchao Wu, Chris Hughes, Mantas Bakšys -/ import Mathlib.Data.List.Basic import Mathlib.Order.BoundedOrder.Lattice import Mathlib.Data.List.Induction import Mathlib.Order.MinMax import Mathlib.Order.WithBot /-! # Minimum and maximum of lists ## Main definitions The main definitions are `argmax`, `argmin`, `minimum` and `maximum` for lists. `argmax f l` returns `some a`, where `a` of `l` that maximises `f a`. If there are `a b` such that `f a = f b`, it returns whichever of `a` or `b` comes first in the list. `argmax f [] = none` `minimum l` returns a `WithTop α`, the smallest element of `l` for nonempty lists, and `⊤` for `[]` -/ namespace List variable {α β : Type*} section ArgAux variable (r : α → α → Prop) [DecidableRel r] {l : List α} {o : Option α} {a : α} /-- Auxiliary definition for `argmax` and `argmin`. -/ def argAux (a : Option α) (b : α) : Option α := Option.casesOn a (some b) fun c => if r b c then some b else some c @[simp] theorem foldl_argAux_eq_none : l.foldl (argAux r) o = none ↔ l = [] ∧ o = none :=
List.reverseRecOn l (by simp) fun tl hd => by simp only [foldl_append, foldl_cons, argAux, foldl_nil, append_eq_nil_iff, and_false, false_and, iff_false] cases foldl (argAux r) o tl
Mathlib/Data/List/MinMax.lean
41
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/- Copyright (c) 2022 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.SpecialFunctions.Gaussian.GaussianIntegral import Mathlib.Analysis.Complex.CauchyIntegral import Mathlib.MeasureTheory.Integral.Pi import Mathlib.Analysis.Fourier.FourierTransform /-! # Fourier transform of the Gaussian We prove that the Fourier transform of the Gaussian function is another Gaussian: * `integral_cexp_quadratic`: general formula for `∫ (x : ℝ), exp (b * x ^ 2 + c * x + d)` * `fourierIntegral_gaussian`: for all complex `b` and `t` with `0 < re b`, we have `∫ x:ℝ, exp (I * t * x) * exp (-b * x^2) = (π / b) ^ (1 / 2) * exp (-t ^ 2 / (4 * b))`. * `fourierIntegral_gaussian_pi`: a variant with `b` and `t` scaled to give a more symmetric statement, and formulated in terms of the Fourier transform operator `𝓕`. We also give versions of these formulas in finite-dimensional inner product spaces, see `integral_cexp_neg_mul_sq_norm_add` and `fourierIntegral_gaussian_innerProductSpace`. -/ /-! ## Fourier integral of Gaussian functions -/ open Real Set MeasureTheory Filter Asymptotics intervalIntegral open scoped Real Topology FourierTransform RealInnerProductSpace open Complex hiding exp continuous_exp abs_of_nonneg sq_abs noncomputable section namespace GaussianFourier variable {b : ℂ} /-- The integral of the Gaussian function over the vertical edges of a rectangle with vertices at `(±T, 0)` and `(±T, c)`. -/ def verticalIntegral (b : ℂ) (c T : ℝ) : ℂ := ∫ y : ℝ in (0 : ℝ)..c, I * (cexp (-b * (T + y * I) ^ 2) - cexp (-b * (T - y * I) ^ 2)) /-- Explicit formula for the norm of the Gaussian function along the vertical edges. -/ theorem norm_cexp_neg_mul_sq_add_mul_I (b : ℂ) (c T : ℝ) : ‖cexp (-b * (T + c * I) ^ 2)‖ = exp (-(b.re * T ^ 2 - 2 * b.im * c * T - b.re * c ^ 2)) := by rw [Complex.norm_exp, neg_mul, neg_re, ← re_add_im b] simp only [sq, re_add_im, mul_re, mul_im, add_re, add_im, ofReal_re, ofReal_im, I_re, I_im] ring_nf theorem norm_cexp_neg_mul_sq_add_mul_I' (hb : b.re ≠ 0) (c T : ℝ) : ‖cexp (-b * (T + c * I) ^ 2)‖ = exp (-(b.re * (T - b.im * c / b.re) ^ 2 - c ^ 2 * (b.im ^ 2 / b.re + b.re))) := by have : b.re * T ^ 2 - 2 * b.im * c * T - b.re * c ^ 2 = b.re * (T - b.im * c / b.re) ^ 2 - c ^ 2 * (b.im ^ 2 / b.re + b.re) := by field_simp; ring rw [norm_cexp_neg_mul_sq_add_mul_I, this] theorem verticalIntegral_norm_le (hb : 0 < b.re) (c : ℝ) {T : ℝ} (hT : 0 ≤ T) : ‖verticalIntegral b c T‖ ≤ (2 : ℝ) * |c| * exp (-(b.re * T ^ 2 - (2 : ℝ) * |b.im| * |c| * T - b.re * c ^ 2)) := by -- first get uniform bound for integrand have vert_norm_bound :
∀ {T : ℝ}, 0 ≤ T → ∀ {c y : ℝ}, |y| ≤ |c| → ‖cexp (-b * (T + y * I) ^ 2)‖ ≤ exp (-(b.re * T ^ 2 - (2 : ℝ) * |b.im| * |c| * T - b.re * c ^ 2)) := by intro T hT c y hy rw [norm_cexp_neg_mul_sq_add_mul_I b] gcongr exp (- (_ - ?_ * _ - _ * ?_)) · (conv_lhs => rw [mul_assoc]); (conv_rhs => rw [mul_assoc]) gcongr _ * ?_ refine (le_abs_self _).trans ?_ rw [abs_mul] gcongr · rwa [sq_le_sq] -- now main proof apply (intervalIntegral.norm_integral_le_of_norm_le_const _).trans · rw [sub_zero] conv_lhs => simp only [mul_comm _ |c|] conv_rhs => conv => congr rw [mul_comm] rw [mul_assoc] · intro y hy have absy : |y| ≤ |c| := by rcases le_or_lt 0 c with (h | h) · rw [uIoc_of_le h] at hy rw [abs_of_nonneg h, abs_of_pos hy.1] exact hy.2 · rw [uIoc_of_ge h.le] at hy rw [abs_of_neg h, abs_of_nonpos hy.2, neg_le_neg_iff] exact hy.1.le rw [norm_mul, norm_I, one_mul, two_mul] refine (norm_sub_le _ _).trans (add_le_add (vert_norm_bound hT absy) ?_) rw [← abs_neg y] at absy simpa only [neg_mul, ofReal_neg] using vert_norm_bound hT absy theorem tendsto_verticalIntegral (hb : 0 < b.re) (c : ℝ) : Tendsto (verticalIntegral b c) atTop (𝓝 0) := by -- complete proof using squeeze theorem: rw [tendsto_zero_iff_norm_tendsto_zero]
Mathlib/Analysis/SpecialFunctions/Gaussian/FourierTransform.lean
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/- Copyright (c) 2020 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau, Eric Wieser -/ import Mathlib.Algebra.BigOperators.GroupWithZero.Action import Mathlib.Algebra.GroupWithZero.Invertible import Mathlib.LinearAlgebra.Prod /-! # Trivial Square-Zero Extension Given a ring `R` together with an `(R, R)`-bimodule `M`, the trivial square-zero extension of `M` over `R` is defined to be the `R`-algebra `R ⊕ M` with multiplication given by `(r₁ + m₁) * (r₂ + m₂) = r₁ r₂ + r₁ m₂ + m₁ r₂`. It is a square-zero extension because `M^2 = 0`. Note that expressing this requires bimodules; we write these in general for a not-necessarily-commutative `R` as: ```lean variable {R M : Type*} [Semiring R] [AddCommMonoid M] variable [Module R M] [Module Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] ``` If we instead work with a commutative `R'` acting symmetrically on `M`, we write ```lean variable {R' M : Type*} [CommSemiring R'] [AddCommMonoid M] variable [Module R' M] [Module R'ᵐᵒᵖ M] [IsCentralScalar R' M] ``` noting that in this context `IsCentralScalar R' M` implies `SMulCommClass R' R'ᵐᵒᵖ M`. Many of the later results in this file are only stated for the commutative `R'` for simplicity. ## Main definitions * `TrivSqZeroExt.inl`, `TrivSqZeroExt.inr`: the canonical inclusions into `TrivSqZeroExt R M`. * `TrivSqZeroExt.fst`, `TrivSqZeroExt.snd`: the canonical projections from `TrivSqZeroExt R M`. * `triv_sq_zero_ext.algebra`: the associated `R`-algebra structure. * `TrivSqZeroExt.lift`: the universal property of the trivial square-zero extension; algebra morphisms `TrivSqZeroExt R M →ₐ[S] A` are uniquely defined by an algebra morphism `f : R →ₐ[S] A` on `R` and a linear map `g : M →ₗ[S] A` on `M` such that: * `g x * g y = 0`: the elements of `M` continue to square to zero. * `g (r •> x) = f r * g x` and `g (x <• r) = g x * f r`: left and right actions are preserved by `g`. * `TrivSqZeroExt.lift`: the universal property of the trivial square-zero extension; algebra morphisms `TrivSqZeroExt R M →ₐ[R] A` are uniquely defined by linear maps `M →ₗ[R] A` for which the product of any two elements in the range is zero. -/ universe u v w /-- "Trivial Square-Zero Extension". Given a module `M` over a ring `R`, the trivial square-zero extension of `M` over `R` is defined to be the `R`-algebra `R × M` with multiplication given by `(r₁ + m₁) * (r₂ + m₂) = r₁ r₂ + r₁ m₂ + r₂ m₁`. It is a square-zero extension because `M^2 = 0`. -/ def TrivSqZeroExt (R : Type u) (M : Type v) := R × M local notation "tsze" => TrivSqZeroExt open scoped RightActions namespace TrivSqZeroExt open MulOpposite section Basic variable {R : Type u} {M : Type v} /-- The canonical inclusion `R → TrivSqZeroExt R M`. -/ def inl [Zero M] (r : R) : tsze R M := (r, 0) /-- The canonical inclusion `M → TrivSqZeroExt R M`. -/ def inr [Zero R] (m : M) : tsze R M := (0, m) /-- The canonical projection `TrivSqZeroExt R M → R`. -/ def fst (x : tsze R M) : R := x.1 /-- The canonical projection `TrivSqZeroExt R M → M`. -/ def snd (x : tsze R M) : M := x.2 @[simp] theorem fst_mk (r : R) (m : M) : fst (r, m) = r := rfl @[simp] theorem snd_mk (r : R) (m : M) : snd (r, m) = m := rfl @[ext] theorem ext {x y : tsze R M} (h1 : x.fst = y.fst) (h2 : x.snd = y.snd) : x = y := Prod.ext h1 h2 section variable (M) @[simp] theorem fst_inl [Zero M] (r : R) : (inl r : tsze R M).fst = r := rfl @[simp] theorem snd_inl [Zero M] (r : R) : (inl r : tsze R M).snd = 0 := rfl @[simp] theorem fst_comp_inl [Zero M] : fst ∘ (inl : R → tsze R M) = id := rfl @[simp] theorem snd_comp_inl [Zero M] : snd ∘ (inl : R → tsze R M) = 0 := rfl end section variable (R) @[simp] theorem fst_inr [Zero R] (m : M) : (inr m : tsze R M).fst = 0 := rfl @[simp] theorem snd_inr [Zero R] (m : M) : (inr m : tsze R M).snd = m := rfl @[simp] theorem fst_comp_inr [Zero R] : fst ∘ (inr : M → tsze R M) = 0 := rfl @[simp] theorem snd_comp_inr [Zero R] : snd ∘ (inr : M → tsze R M) = id := rfl end theorem fst_surjective [Nonempty M] : Function.Surjective (fst : tsze R M → R) := Prod.fst_surjective theorem snd_surjective [Nonempty R] : Function.Surjective (snd : tsze R M → M) := Prod.snd_surjective theorem inl_injective [Zero M] : Function.Injective (inl : R → tsze R M) := Function.LeftInverse.injective <| fst_inl _ theorem inr_injective [Zero R] : Function.Injective (inr : M → tsze R M) := Function.LeftInverse.injective <| snd_inr _ end Basic /-! ### Structures inherited from `Prod` Additive operators and scalar multiplication operate elementwise. -/ section Additive variable {T : Type*} {S : Type*} {R : Type u} {M : Type v} instance inhabited [Inhabited R] [Inhabited M] : Inhabited (tsze R M) := instInhabitedProd instance zero [Zero R] [Zero M] : Zero (tsze R M) := Prod.instZero instance add [Add R] [Add M] : Add (tsze R M) := Prod.instAdd instance sub [Sub R] [Sub M] : Sub (tsze R M) := Prod.instSub instance neg [Neg R] [Neg M] : Neg (tsze R M) := Prod.instNeg instance addSemigroup [AddSemigroup R] [AddSemigroup M] : AddSemigroup (tsze R M) := Prod.instAddSemigroup instance addZeroClass [AddZeroClass R] [AddZeroClass M] : AddZeroClass (tsze R M) := Prod.instAddZeroClass instance addMonoid [AddMonoid R] [AddMonoid M] : AddMonoid (tsze R M) := Prod.instAddMonoid instance addGroup [AddGroup R] [AddGroup M] : AddGroup (tsze R M) := Prod.instAddGroup instance addCommSemigroup [AddCommSemigroup R] [AddCommSemigroup M] : AddCommSemigroup (tsze R M) := Prod.instAddCommSemigroup instance addCommMonoid [AddCommMonoid R] [AddCommMonoid M] : AddCommMonoid (tsze R M) := Prod.instAddCommMonoid instance addCommGroup [AddCommGroup R] [AddCommGroup M] : AddCommGroup (tsze R M) := Prod.instAddCommGroup instance smul [SMul S R] [SMul S M] : SMul S (tsze R M) := Prod.instSMul instance isScalarTower [SMul T R] [SMul T M] [SMul S R] [SMul S M] [SMul T S] [IsScalarTower T S R] [IsScalarTower T S M] : IsScalarTower T S (tsze R M) := Prod.isScalarTower instance smulCommClass [SMul T R] [SMul T M] [SMul S R] [SMul S M] [SMulCommClass T S R] [SMulCommClass T S M] : SMulCommClass T S (tsze R M) := Prod.smulCommClass instance isCentralScalar [SMul S R] [SMul S M] [SMul Sᵐᵒᵖ R] [SMul Sᵐᵒᵖ M] [IsCentralScalar S R] [IsCentralScalar S M] : IsCentralScalar S (tsze R M) := Prod.isCentralScalar instance mulAction [Monoid S] [MulAction S R] [MulAction S M] : MulAction S (tsze R M) := Prod.mulAction instance distribMulAction [Monoid S] [AddMonoid R] [AddMonoid M] [DistribMulAction S R] [DistribMulAction S M] : DistribMulAction S (tsze R M) := Prod.distribMulAction instance module [Semiring S] [AddCommMonoid R] [AddCommMonoid M] [Module S R] [Module S M] : Module S (tsze R M) := Prod.instModule /-- The trivial square-zero extension is nontrivial if it is over a nontrivial ring. -/ instance instNontrivial_of_left {R M : Type*} [Nontrivial R] [Nonempty M] : Nontrivial (TrivSqZeroExt R M) := fst_surjective.nontrivial /-- The trivial square-zero extension is nontrivial if it is over a nontrivial module. -/ instance instNontrivial_of_right {R M : Type*} [Nonempty R] [Nontrivial M] : Nontrivial (TrivSqZeroExt R M) := snd_surjective.nontrivial @[simp] theorem fst_zero [Zero R] [Zero M] : (0 : tsze R M).fst = 0 := rfl @[simp] theorem snd_zero [Zero R] [Zero M] : (0 : tsze R M).snd = 0 := rfl @[simp] theorem fst_add [Add R] [Add M] (x₁ x₂ : tsze R M) : (x₁ + x₂).fst = x₁.fst + x₂.fst := rfl @[simp] theorem snd_add [Add R] [Add M] (x₁ x₂ : tsze R M) : (x₁ + x₂).snd = x₁.snd + x₂.snd := rfl @[simp] theorem fst_neg [Neg R] [Neg M] (x : tsze R M) : (-x).fst = -x.fst := rfl @[simp] theorem snd_neg [Neg R] [Neg M] (x : tsze R M) : (-x).snd = -x.snd := rfl @[simp] theorem fst_sub [Sub R] [Sub M] (x₁ x₂ : tsze R M) : (x₁ - x₂).fst = x₁.fst - x₂.fst := rfl @[simp] theorem snd_sub [Sub R] [Sub M] (x₁ x₂ : tsze R M) : (x₁ - x₂).snd = x₁.snd - x₂.snd := rfl @[simp] theorem fst_smul [SMul S R] [SMul S M] (s : S) (x : tsze R M) : (s • x).fst = s • x.fst := rfl @[simp] theorem snd_smul [SMul S R] [SMul S M] (s : S) (x : tsze R M) : (s • x).snd = s • x.snd := rfl theorem fst_sum {ι} [AddCommMonoid R] [AddCommMonoid M] (s : Finset ι) (f : ι → tsze R M) : (∑ i ∈ s, f i).fst = ∑ i ∈ s, (f i).fst := Prod.fst_sum theorem snd_sum {ι} [AddCommMonoid R] [AddCommMonoid M] (s : Finset ι) (f : ι → tsze R M) : (∑ i ∈ s, f i).snd = ∑ i ∈ s, (f i).snd := Prod.snd_sum section variable (M) @[simp] theorem inl_zero [Zero R] [Zero M] : (inl 0 : tsze R M) = 0 := rfl @[simp] theorem inl_add [Add R] [AddZeroClass M] (r₁ r₂ : R) : (inl (r₁ + r₂) : tsze R M) = inl r₁ + inl r₂ := ext rfl (add_zero 0).symm @[simp] theorem inl_neg [Neg R] [NegZeroClass M] (r : R) : (inl (-r) : tsze R M) = -inl r := ext rfl neg_zero.symm @[simp] theorem inl_sub [Sub R] [SubNegZeroMonoid M] (r₁ r₂ : R) : (inl (r₁ - r₂) : tsze R M) = inl r₁ - inl r₂ := ext rfl (sub_zero _).symm @[simp] theorem inl_smul [Monoid S] [AddMonoid M] [SMul S R] [DistribMulAction S M] (s : S) (r : R) : (inl (s • r) : tsze R M) = s • inl r := ext rfl (smul_zero s).symm theorem inl_sum {ι} [AddCommMonoid R] [AddCommMonoid M] (s : Finset ι) (f : ι → R) : (inl (∑ i ∈ s, f i) : tsze R M) = ∑ i ∈ s, inl (f i) := map_sum (LinearMap.inl ℕ _ _) _ _ end section variable (R) @[simp] theorem inr_zero [Zero R] [Zero M] : (inr 0 : tsze R M) = 0 := rfl @[simp] theorem inr_add [AddZeroClass R] [Add M] (m₁ m₂ : M) : (inr (m₁ + m₂) : tsze R M) = inr m₁ + inr m₂ := ext (add_zero 0).symm rfl @[simp] theorem inr_neg [NegZeroClass R] [Neg M] (m : M) : (inr (-m) : tsze R M) = -inr m := ext neg_zero.symm rfl @[simp] theorem inr_sub [SubNegZeroMonoid R] [Sub M] (m₁ m₂ : M) : (inr (m₁ - m₂) : tsze R M) = inr m₁ - inr m₂ := ext (sub_zero _).symm rfl @[simp] theorem inr_smul [Zero R] [SMulZeroClass S R] [SMul S M] (r : S) (m : M) : (inr (r • m) : tsze R M) = r • inr m := ext (smul_zero _).symm rfl theorem inr_sum {ι} [AddCommMonoid R] [AddCommMonoid M] (s : Finset ι) (f : ι → M) : (inr (∑ i ∈ s, f i) : tsze R M) = ∑ i ∈ s, inr (f i) := map_sum (LinearMap.inr ℕ _ _) _ _ end theorem inl_fst_add_inr_snd_eq [AddZeroClass R] [AddZeroClass M] (x : tsze R M) : inl x.fst + inr x.snd = x := ext (add_zero x.1) (zero_add x.2) /-- To show a property hold on all `TrivSqZeroExt R M` it suffices to show it holds on terms of the form `inl r + inr m`. -/ @[elab_as_elim, induction_eliminator, cases_eliminator] theorem ind {R M} [AddZeroClass R] [AddZeroClass M] {P : TrivSqZeroExt R M → Prop} (inl_add_inr : ∀ r m, P (inl r + inr m)) (x) : P x := inl_fst_add_inr_snd_eq x ▸ inl_add_inr x.1 x.2 /-- This cannot be marked `@[ext]` as it ends up being used instead of `LinearMap.prod_ext` when working with `R × M`. -/ theorem linearMap_ext {N} [Semiring S] [AddCommMonoid R] [AddCommMonoid M] [AddCommMonoid N] [Module S R] [Module S M] [Module S N] ⦃f g : tsze R M →ₗ[S] N⦄ (hl : ∀ r, f (inl r) = g (inl r)) (hr : ∀ m, f (inr m) = g (inr m)) : f = g := LinearMap.prod_ext (LinearMap.ext hl) (LinearMap.ext hr) variable (R M) /-- The canonical `R`-linear inclusion `M → TrivSqZeroExt R M`. -/ @[simps apply] def inrHom [Semiring R] [AddCommMonoid M] [Module R M] : M →ₗ[R] tsze R M := { LinearMap.inr R R M with toFun := inr } /-- The canonical `R`-linear projection `TrivSqZeroExt R M → M`. -/ @[simps apply] def sndHom [Semiring R] [AddCommMonoid M] [Module R M] : tsze R M →ₗ[R] M := { LinearMap.snd _ _ _ with toFun := snd } end Additive /-! ### Multiplicative structure -/ section Mul variable {R : Type u} {M : Type v} instance one [One R] [Zero M] : One (tsze R M) := ⟨(1, 0)⟩ instance mul [Mul R] [Add M] [SMul R M] [SMul Rᵐᵒᵖ M] : Mul (tsze R M) := ⟨fun x y => (x.1 * y.1, x.1 •> y.2 + x.2 <• y.1)⟩ @[simp] theorem fst_one [One R] [Zero M] : (1 : tsze R M).fst = 1 := rfl @[simp] theorem snd_one [One R] [Zero M] : (1 : tsze R M).snd = 0 := rfl @[simp] theorem fst_mul [Mul R] [Add M] [SMul R M] [SMul Rᵐᵒᵖ M] (x₁ x₂ : tsze R M) : (x₁ * x₂).fst = x₁.fst * x₂.fst := rfl @[simp] theorem snd_mul [Mul R] [Add M] [SMul R M] [SMul Rᵐᵒᵖ M] (x₁ x₂ : tsze R M) : (x₁ * x₂).snd = x₁.fst •> x₂.snd + x₁.snd <• x₂.fst := rfl section variable (M) @[simp] theorem inl_one [One R] [Zero M] : (inl 1 : tsze R M) = 1 := rfl @[simp] theorem inl_mul [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (r₁ r₂ : R) : (inl (r₁ * r₂) : tsze R M) = inl r₁ * inl r₂ := ext rfl <| show (0 : M) = r₁ •> (0 : M) + (0 : M) <• r₂ by rw [smul_zero, zero_add, smul_zero] theorem inl_mul_inl [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (r₁ r₂ : R) : (inl r₁ * inl r₂ : tsze R M) = inl (r₁ * r₂) := (inl_mul M r₁ r₂).symm end section variable (R) @[simp] theorem inr_mul_inr [Semiring R] [AddCommMonoid M] [Module R M] [Module Rᵐᵒᵖ M] (m₁ m₂ : M) : (inr m₁ * inr m₂ : tsze R M) = 0 := ext (mul_zero _) <| show (0 : R) •> m₂ + m₁ <• (0 : R) = 0 by rw [zero_smul, zero_add, op_zero, zero_smul] end theorem inl_mul_inr [MonoidWithZero R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (r : R) (m : M) : (inl r * inr m : tsze R M) = inr (r • m) := ext (mul_zero r) <| show r • m + (0 : Rᵐᵒᵖ) • (0 : M) = r • m by rw [smul_zero, add_zero] theorem inr_mul_inl [MonoidWithZero R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (r : R) (m : M) : (inr m * inl r : tsze R M) = inr (m <• r) := ext (zero_mul r) <| show (0 : R) •> (0 : M) + m <• r = m <• r by rw [smul_zero, zero_add] theorem inl_mul_eq_smul [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (r : R) (x : tsze R M) : inl r * x = r •> x := ext rfl (by dsimp; rw [smul_zero, add_zero]) theorem mul_inl_eq_op_smul [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (x : tsze R M) (r : R) : x * inl r = x <• r := ext rfl (by dsimp; rw [smul_zero, zero_add]) instance mulOneClass [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] : MulOneClass (tsze R M) := { TrivSqZeroExt.one, TrivSqZeroExt.mul with one_mul := fun x => ext (one_mul x.1) <| show (1 : R) •> x.2 + (0 : M) <• x.1 = x.2 by rw [one_smul, smul_zero, add_zero] mul_one := fun x => ext (mul_one x.1) <| show x.1 • (0 : M) + x.2 <• (1 : R) = x.2 by rw [smul_zero, zero_add, op_one, one_smul] } instance addMonoidWithOne [AddMonoidWithOne R] [AddMonoid M] : AddMonoidWithOne (tsze R M) := { TrivSqZeroExt.addMonoid, TrivSqZeroExt.one with natCast := fun n => inl n natCast_zero := by simp [Nat.cast] natCast_succ := fun _ => by ext <;> simp [Nat.cast] } @[simp] theorem fst_natCast [AddMonoidWithOne R] [AddMonoid M] (n : ℕ) : (n : tsze R M).fst = n := rfl @[simp] theorem snd_natCast [AddMonoidWithOne R] [AddMonoid M] (n : ℕ) : (n : tsze R M).snd = 0 := rfl @[simp] theorem inl_natCast [AddMonoidWithOne R] [AddMonoid M] (n : ℕ) : (inl n : tsze R M) = n := rfl instance addGroupWithOne [AddGroupWithOne R] [AddGroup M] : AddGroupWithOne (tsze R M) := { TrivSqZeroExt.addGroup, TrivSqZeroExt.addMonoidWithOne with intCast := fun z => inl z intCast_ofNat := fun _n => ext (Int.cast_natCast _) rfl intCast_negSucc := fun _n => ext (Int.cast_negSucc _) neg_zero.symm } @[simp] theorem fst_intCast [AddGroupWithOne R] [AddGroup M] (z : ℤ) : (z : tsze R M).fst = z := rfl @[simp] theorem snd_intCast [AddGroupWithOne R] [AddGroup M] (z : ℤ) : (z : tsze R M).snd = 0 := rfl @[simp] theorem inl_intCast [AddGroupWithOne R] [AddGroup M] (z : ℤ) : (inl z : tsze R M) = z := rfl instance nonAssocSemiring [Semiring R] [AddCommMonoid M] [Module R M] [Module Rᵐᵒᵖ M] : NonAssocSemiring (tsze R M) := { TrivSqZeroExt.addMonoidWithOne, TrivSqZeroExt.mulOneClass, TrivSqZeroExt.addCommMonoid with zero_mul := fun x => ext (zero_mul x.1) <| show (0 : R) •> x.2 + (0 : M) <• x.1 = 0 by rw [zero_smul, zero_add, smul_zero] mul_zero := fun x => ext (mul_zero x.1) <| show x.1 • (0 : M) + (0 : Rᵐᵒᵖ) • x.2 = 0 by rw [smul_zero, zero_add, zero_smul] left_distrib := fun x₁ x₂ x₃ => ext (mul_add x₁.1 x₂.1 x₃.1) <| show x₁.1 •> (x₂.2 + x₃.2) + x₁.2 <• (x₂.1 + x₃.1) = x₁.1 •> x₂.2 + x₁.2 <• x₂.1 + (x₁.1 •> x₃.2 + x₁.2 <• x₃.1) by simp_rw [smul_add, MulOpposite.op_add, add_smul, add_add_add_comm] right_distrib := fun x₁ x₂ x₃ => ext (add_mul x₁.1 x₂.1 x₃.1) <| show (x₁.1 + x₂.1) •> x₃.2 + (x₁.2 + x₂.2) <• x₃.1 = x₁.1 •> x₃.2 + x₁.2 <• x₃.1 + (x₂.1 •> x₃.2 + x₂.2 <• x₃.1) by simp_rw [add_smul, smul_add, add_add_add_comm] } instance nonAssocRing [Ring R] [AddCommGroup M] [Module R M] [Module Rᵐᵒᵖ M] : NonAssocRing (tsze R M) := { TrivSqZeroExt.addGroupWithOne, TrivSqZeroExt.nonAssocSemiring with } /-- In the general non-commutative case, the power operator is $$\begin{align} (r + m)^n &= r^n + r^{n-1}m + r^{n-2}mr + \cdots + rmr^{n-2} + mr^{n-1} \\ & =r^n + \sum_{i = 0}^{n - 1} r^{(n - 1) - i} m r^{i} \end{align}$$ In the commutative case this becomes the simpler $(r + m)^n = r^n + nr^{n-1}m$. -/ instance [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] : Pow (tsze R M) ℕ := ⟨fun x n => ⟨x.fst ^ n, ((List.range n).map fun i => x.fst ^ (n.pred - i) •> x.snd <• x.fst ^ i).sum⟩⟩ @[simp] theorem fst_pow [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (x : tsze R M) (n : ℕ) : fst (x ^ n) = x.fst ^ n := rfl theorem snd_pow_eq_sum [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (x : tsze R M) (n : ℕ) : snd (x ^ n) = ((List.range n).map fun i => x.fst ^ (n.pred - i) •> x.snd <• x.fst ^ i).sum := rfl theorem snd_pow_of_smul_comm [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] (x : tsze R M) (n : ℕ) (h : x.snd <• x.fst = x.fst •> x.snd) : snd (x ^ n) = n • x.fst ^ n.pred •> x.snd := by simp_rw [snd_pow_eq_sum, ← smul_comm (_ : R) (_ : Rᵐᵒᵖ), aux, smul_smul, ← pow_add] match n with | 0 => rw [Nat.pred_zero, pow_zero, List.range_zero, zero_smul, List.map_nil, List.sum_nil] | (Nat.succ n) => simp_rw [Nat.pred_succ] refine (List.sum_eq_card_nsmul _ (x.fst ^ n • x.snd) ?_).trans ?_ · rintro m hm simp_rw [List.mem_map, List.mem_range] at hm obtain ⟨i, hi, rfl⟩ := hm rw [Nat.sub_add_cancel (Nat.lt_succ_iff.mp hi)] · rw [List.length_map, List.length_range] where aux : ∀ n : ℕ, x.snd <• x.fst ^ n = x.fst ^ n •> x.snd := by intro n induction n with | zero => simp | succ n ih => rw [pow_succ, op_mul, mul_smul, mul_smul, ← h, smul_comm (_ : R) (op x.fst) x.snd, ih] theorem snd_pow_of_smul_comm' [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] (x : tsze R M) (n : ℕ) (h : x.snd <• x.fst = x.fst •> x.snd) : snd (x ^ n) = n • (x.snd <• x.fst ^ n.pred) := by rw [snd_pow_of_smul_comm _ _ h, snd_pow_of_smul_comm.aux _ h] @[simp] theorem snd_pow [CommMonoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [IsCentralScalar R M] (x : tsze R M) (n : ℕ) : snd (x ^ n) = n • x.fst ^ n.pred • x.snd := snd_pow_of_smul_comm _ _ (op_smul_eq_smul _ _) @[simp] theorem inl_pow [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] (r : R) (n : ℕ) : (inl r ^ n : tsze R M) = inl (r ^ n) := ext rfl <| by simp [snd_pow_eq_sum, List.map_const'] instance monoid [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] : Monoid (tsze R M) := { TrivSqZeroExt.mulOneClass with mul_assoc := fun x y z => ext (mul_assoc x.1 y.1 z.1) <| show (x.1 * y.1) •> z.2 + (x.1 •> y.2 + x.2 <• y.1) <• z.1 = x.1 •> (y.1 •> z.2 + y.2 <• z.1) + x.2 <• (y.1 * z.1) by simp_rw [smul_add, ← mul_smul, add_assoc, smul_comm, op_mul] npow := fun n x => x ^ n npow_zero := fun x => ext (pow_zero x.fst) (by simp [snd_pow_eq_sum]) npow_succ := fun n x => ext (pow_succ _ _) (by simp_rw [snd_mul, snd_pow_eq_sum, Nat.pred_succ] cases n · simp [List.range_succ] rw [List.sum_range_succ'] simp only [pow_zero, op_one, Nat.sub_zero, one_smul, Nat.succ_sub_succ_eq_sub, fst_pow, Nat.pred_succ, List.smul_sum, List.map_map, Function.comp_def] simp_rw [← smul_comm (_ : R) (_ : Rᵐᵒᵖ), smul_smul, pow_succ] rfl) } theorem fst_list_prod [Monoid R] [AddMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] (l : List (tsze R M)) : l.prod.fst = (l.map fst).prod := map_list_prod ({ toFun := fst, map_one' := fst_one, map_mul' := fst_mul } : tsze R M →* R) _ instance semiring [Semiring R] [AddCommMonoid M] [Module R M] [Module Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] : Semiring (tsze R M) := { TrivSqZeroExt.monoid, TrivSqZeroExt.nonAssocSemiring with } /-- The second element of a product $\prod_{i=0}^n (r_i + m_i)$ is a sum of terms of the form $r_0\cdots r_{i-1}m_ir_{i+1}\cdots r_n$. -/ theorem snd_list_prod [Monoid R] [AddCommMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] (l : List (tsze R M)) : l.prod.snd = (l.zipIdx.map fun x : tsze R M × ℕ => ((l.map fst).take x.2).prod •> x.fst.snd <• ((l.map fst).drop x.2.succ).prod).sum := by induction l with | nil => simp | cons x xs ih => rw [List.zipIdx_cons'] simp_rw [List.map_cons, List.map_map, Function.comp_def, Prod.map_snd, Prod.map_fst, id, List.take_zero, List.take_succ_cons, List.prod_nil, List.prod_cons, snd_mul, one_smul, List.drop, mul_smul, List.sum_cons, fst_list_prod, ih, List.smul_sum, List.map_map, ← smul_comm (_ : R) (_ : Rᵐᵒᵖ)] exact add_comm _ _ instance ring [Ring R] [AddCommGroup M] [Module R M] [Module Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] : Ring (tsze R M) := { TrivSqZeroExt.semiring, TrivSqZeroExt.nonAssocRing with } instance commMonoid [CommMonoid R] [AddCommMonoid M] [DistribMulAction R M] [DistribMulAction Rᵐᵒᵖ M] [IsCentralScalar R M] : CommMonoid (tsze R M) := { TrivSqZeroExt.monoid with mul_comm := fun x₁ x₂ => ext (mul_comm x₁.1 x₂.1) <| show x₁.1 •> x₂.2 + x₁.2 <• x₂.1 = x₂.1 •> x₁.2 + x₂.2 <• x₁.1 by rw [op_smul_eq_smul, op_smul_eq_smul, add_comm] } instance commSemiring [CommSemiring R] [AddCommMonoid M] [Module R M] [Module Rᵐᵒᵖ M] [IsCentralScalar R M] : CommSemiring (tsze R M) := { TrivSqZeroExt.commMonoid, TrivSqZeroExt.nonAssocSemiring with } instance commRing [CommRing R] [AddCommGroup M] [Module R M] [Module Rᵐᵒᵖ M] [IsCentralScalar R M] : CommRing (tsze R M) := { TrivSqZeroExt.nonAssocRing, TrivSqZeroExt.commSemiring with } variable (R M) /-- The canonical inclusion of rings `R → TrivSqZeroExt R M`. -/ @[simps apply] def inlHom [Semiring R] [AddCommMonoid M] [Module R M] [Module Rᵐᵒᵖ M] : R →+* tsze R M where toFun := inl map_one' := inl_one M map_mul' := inl_mul M map_zero' := inl_zero M map_add' := inl_add M end Mul section Inv variable {R : Type u} {M : Type v} variable [Neg M] [Inv R] [SMul Rᵐᵒᵖ M] [SMul R M] /-- Inversion of the trivial-square-zero extension, sending $r + m$ to $r^{-1} - r^{-1}mr^{-1}$. Strictly this is only a _two_-sided inverse when the left and right actions associate. -/ instance instInv : Inv (tsze R M) := ⟨fun b => (b.1⁻¹, -(b.1⁻¹ •> b.2 <• b.1⁻¹))⟩ @[simp] theorem fst_inv (x : tsze R M) : fst x⁻¹ = (fst x)⁻¹ := rfl @[simp] theorem snd_inv (x : tsze R M) : snd x⁻¹ = -((fst x)⁻¹ •> snd x <• (fst x)⁻¹) := rfl end Inv /-! This section is heavily inspired by analogous results about matrices. -/ section Invertible variable {R : Type u} {M : Type v} variable [AddCommGroup M] [Semiring R] [Module Rᵐᵒᵖ M] [Module R M] /-- `x.fst : R` is invertible when `x : tzre R M` is. -/ abbrev invertibleFstOfInvertible (x : tsze R M) [Invertible x] : Invertible x.fst where invOf := (⅟x).fst invOf_mul_self := by rw [← fst_mul, invOf_mul_self, fst_one] mul_invOf_self := by rw [← fst_mul, mul_invOf_self, fst_one] theorem fst_invOf (x : tsze R M) [Invertible x] [Invertible x.fst] : (⅟x).fst = ⅟(x.fst) := by letI := invertibleFstOfInvertible x convert (rfl : _ = ⅟ x.fst) theorem mul_left_eq_one (r : R) (x : tsze R M) (h : r * x.fst = 1) : (inl r + inr (-((r •> x.snd) <• r))) * x = 1 := by ext <;> dsimp · rw [add_zero, h] · rw [add_zero, zero_add, smul_neg, op_smul_op_smul, h, op_one, one_smul, add_neg_cancel] theorem mul_right_eq_one (x : tsze R M) (r : R) (h : x.fst * r = 1) : x * (inl r + inr (-(r •> (x.snd <• r)))) = 1 := by ext <;> dsimp · rw [add_zero, h] · rw [add_zero, zero_add, smul_neg, smul_smul, h, one_smul, neg_add_cancel] variable [SMulCommClass R Rᵐᵒᵖ M] /-- `x : tzre R M` is invertible when `x.fst : R` is. -/ abbrev invertibleOfInvertibleFst (x : tsze R M) [Invertible x.fst] : Invertible x where invOf := (⅟x.fst, -(⅟x.fst •> x.snd <• ⅟x.fst)) invOf_mul_self := by convert mul_left_eq_one _ _ (invOf_mul_self x.fst) ext <;> simp mul_invOf_self := by convert mul_right_eq_one _ _ (mul_invOf_self x.fst) ext <;> simp [smul_comm] theorem snd_invOf (x : tsze R M) [Invertible x] [Invertible x.fst] : (⅟x).snd = -(⅟x.fst •> x.snd <• ⅟x.fst) := by letI := invertibleOfInvertibleFst x convert congr_arg (TrivSqZeroExt.snd (R := R) (M := M)) (_ : _ = ⅟ x) convert rfl /-- Together `TrivSqZeroExt.detInvertibleOfInvertible` and `TrivSqZeroExt.invertibleOfDetInvertible` form an equivalence, although both sides of the equiv are subsingleton anyway. -/ @[simps] def invertibleEquivInvertibleFst (x : tsze R M) : Invertible x ≃ Invertible x.fst where toFun _ := invertibleFstOfInvertible x invFun _ := invertibleOfInvertibleFst x left_inv _ := Subsingleton.elim _ _ right_inv _ := Subsingleton.elim _ _ /-- When lowered to a prop, `Matrix.invertibleEquivInvertibleFst` forms an `iff`. -/ theorem isUnit_iff_isUnit_fst {x : tsze R M} : IsUnit x ↔ IsUnit x.fst := by simp only [← nonempty_invertible_iff_isUnit, (invertibleEquivInvertibleFst x).nonempty_congr] @[simp] theorem isUnit_inl_iff {r : R} : IsUnit (inl r : tsze R M) ↔ IsUnit r := by rw [isUnit_iff_isUnit_fst, fst_inl] @[simp] theorem isUnit_inr_iff {m : M} : IsUnit (inr m : tsze R M) ↔ Subsingleton R := by simp_rw [isUnit_iff_isUnit_fst, fst_inr, isUnit_zero_iff, subsingleton_iff_zero_eq_one] end Invertible section DivisionSemiring variable {R : Type u} {M : Type v} variable [DivisionSemiring R] [AddCommGroup M] [Module Rᵐᵒᵖ M] [Module R M] protected theorem inv_inl (r : R) : (inl r)⁻¹ = (inl (r⁻¹ : R) : tsze R M) := by ext · rw [fst_inv, fst_inl, fst_inl] · rw [snd_inv, fst_inl, snd_inl, snd_inl, smul_zero, smul_zero, neg_zero] @[simp] theorem inv_inr (m : M) : (inr m)⁻¹ = (0 : tsze R M) := by ext · rw [fst_inv, fst_inr, fst_zero, inv_zero] · rw [snd_inv, snd_inr, fst_inr, inv_zero, op_zero, zero_smul, snd_zero, neg_zero] @[simp] protected theorem inv_zero : (0 : tsze R M)⁻¹ = (0 : tsze R M) := by rw [← inl_zero, TrivSqZeroExt.inv_inl, inv_zero] @[simp] protected theorem inv_one : (1 : tsze R M)⁻¹ = (1 : tsze R M) := by rw [← inl_one, TrivSqZeroExt.inv_inl, inv_one] protected theorem inv_mul_cancel {x : tsze R M} (hx : fst x ≠ 0) : x⁻¹ * x = 1 := by convert mul_left_eq_one _ _ (_root_.inv_mul_cancel₀ hx) using 2 ext <;> simp variable [SMulCommClass R Rᵐᵒᵖ M] @[simp] theorem invOf_eq_inv (x : tsze R M) [Invertible x] : ⅟x = x⁻¹ := by letI := invertibleFstOfInvertible x ext <;> simp [fst_invOf, snd_invOf] protected theorem mul_inv_cancel {x : tsze R M} (hx : fst x ≠ 0) : x * x⁻¹ = 1 := by have : Invertible x.fst := Units.invertible (.mk0 _ hx) have := invertibleOfInvertibleFst x rw [← invOf_eq_inv, mul_invOf_self] protected theorem mul_inv_rev (a b : tsze R M) : (a * b)⁻¹ = b⁻¹ * a⁻¹ := by ext · rw [fst_inv, fst_mul, fst_mul, mul_inv_rev, fst_inv, fst_inv] · simp only [snd_inv, snd_mul, fst_mul, fst_inv] simp only [neg_smul, smul_neg, smul_add] simp_rw [mul_inv_rev, smul_comm (_ : R), op_smul_op_smul, smul_smul, add_comm, neg_add] obtain ha0 | ha := eq_or_ne (fst a) 0 · simp [ha0] obtain hb0 | hb := eq_or_ne (fst b) 0 · simp [hb0] rw [inv_mul_cancel_right₀ ha, mul_inv_cancel_left₀ hb] protected theorem inv_inv {x : tsze R M} (hx : fst x ≠ 0) : x⁻¹⁻¹ = x := -- adapted from `Matrix.nonsing_inv_nonsing_inv` calc x⁻¹⁻¹ = 1 * x⁻¹⁻¹ := by rw [one_mul] _ = x * x⁻¹ * x⁻¹⁻¹ := by rw [TrivSqZeroExt.mul_inv_cancel hx] _ = x := by rw [mul_assoc, TrivSqZeroExt.mul_inv_cancel, mul_one] rw [fst_inv] apply inv_ne_zero hx @[simp] theorem isUnit_inv_iff {x : tsze R M} : IsUnit x⁻¹ ↔ IsUnit x := by simp_rw [isUnit_iff_isUnit_fst, fst_inv, isUnit_iff_ne_zero, ne_eq, inv_eq_zero] end DivisionSemiring section DivisionRing variable {R : Type u} {M : Type v} variable [DivisionRing R] [AddCommGroup M] [Module Rᵐᵒᵖ M] [Module R M] protected theorem inv_neg {x : tsze R M} : (-x)⁻¹ = -(x⁻¹) := by ext <;> simp [inv_neg] end DivisionRing section Algebra variable (S : Type*) (R R' : Type u) (M : Type v) variable [CommSemiring S] [Semiring R] [CommSemiring R'] [AddCommMonoid M] variable [Algebra S R] [Module S M] [Module R M] [Module Rᵐᵒᵖ M] [SMulCommClass R Rᵐᵒᵖ M] variable [IsScalarTower S R M] [IsScalarTower S Rᵐᵒᵖ M] variable [Module R' M] [Module R'ᵐᵒᵖ M] [IsCentralScalar R' M] instance algebra' : Algebra S (tsze R M) where algebraMap := (TrivSqZeroExt.inlHom R M).comp (algebraMap S R) smul := (· • ·) commutes' := fun s x => ext (Algebra.commutes _ _) <| show algebraMap S R s •> x.snd + (0 : M) <• x.fst = x.fst •> (0 : M) + x.snd <• algebraMap S R s by rw [smul_zero, smul_zero, add_zero, zero_add] rw [Algebra.algebraMap_eq_smul_one, MulOpposite.op_smul, op_one, smul_assoc, one_smul, smul_assoc, one_smul] smul_def' := fun s x => ext (Algebra.smul_def _ _) <| show s • x.snd = algebraMap S R s •> x.snd + (0 : M) <• x.fst by rw [smul_zero, add_zero, algebraMap_smul] -- shortcut instance for the common case instance : Algebra R' (tsze R' M) := TrivSqZeroExt.algebra' _ _ _ theorem algebraMap_eq_inl : ⇑(algebraMap R' (tsze R' M)) = inl := rfl theorem algebraMap_eq_inlHom : algebraMap R' (tsze R' M) = inlHom R' M := rfl theorem algebraMap_eq_inl' (s : S) : algebraMap S (tsze R M) s = inl (algebraMap S R s) := rfl /-- The canonical `S`-algebra projection `TrivSqZeroExt R M → R`. -/ @[simps] def fstHom : tsze R M →ₐ[S] R where toFun := fst map_one' := fst_one map_mul' := fst_mul map_zero' := fst_zero (M := M) map_add' := fst_add commutes' _r := fst_inl M _ /-- The canonical `S`-algebra inclusion `R → TrivSqZeroExt R M`. -/ @[simps] def inlAlgHom : R →ₐ[S] tsze R M where toFun := inl map_one' := inl_one _ map_mul' := inl_mul _ map_zero' := inl_zero (M := M) map_add' := inl_add _ commutes' _r := (algebraMap_eq_inl' _ _ _ _).symm variable {R R' S M} theorem algHom_ext {A} [Semiring A] [Algebra R' A] ⦃f g : tsze R' M →ₐ[R'] A⦄ (h : ∀ m, f (inr m) = g (inr m)) : f = g := AlgHom.toLinearMap_injective <| linearMap_ext (fun _r => (f.commutes _).trans (g.commutes _).symm) h @[ext] theorem algHom_ext' {A} [Semiring A] [Algebra S A] ⦃f g : tsze R M →ₐ[S] A⦄ (hinl : f.comp (inlAlgHom S R M) = g.comp (inlAlgHom S R M)) (hinr : f.toLinearMap.comp (inrHom R M |>.restrictScalars S) = g.toLinearMap.comp (inrHom R M |>.restrictScalars S)) : f = g := AlgHom.toLinearMap_injective <| linearMap_ext (AlgHom.congr_fun hinl) (LinearMap.congr_fun hinr) variable {A : Type*} [Semiring A] [Algebra S A] [Algebra R' A] /-- Assemble an algebra morphism `TrivSqZeroExt R M →ₐ[S] A` from separate morphisms on `R` and `M`. Namely, we require that for an algebra morphism `f : R →ₐ[S] A` and a linear map `g : M →ₗ[S] A`, we have: * `g x * g y = 0`: the elements of `M` continue to square to zero. * `g (r •> x) = f r * g x` and `g (x <• r) = g x * f r`: scalar multiplication on the left and right is sent to left- and right- multiplication by the image under `f`. See `TrivSqZeroExt.liftEquiv` for this as an equiv; namely that any such algebra morphism can be factored in this way. When `R` is commutative, this can be invoked with `f = Algebra.ofId R A`, which satisfies `hfg` and `hgf`. This version is captured as an equiv by `TrivSqZeroExt.liftEquivOfComm`. -/ def lift (f : R →ₐ[S] A) (g : M →ₗ[S] A) (hg : ∀ x y, g x * g y = 0) (hfg : ∀ r x, g (r •> x) = f r * g x) (hgf : ∀ r x, g (x <• r) = g x * f r) : tsze R M →ₐ[S] A := AlgHom.ofLinearMap ((f.comp <| fstHom S R M).toLinearMap + g ∘ₗ (sndHom R M |>.restrictScalars S)) (show f 1 + g (0 : M) = 1 by rw [map_zero, map_one, add_zero]) (TrivSqZeroExt.ind fun r₁ m₁ => TrivSqZeroExt.ind fun r₂ m₂ => by dsimp simp only [add_zero, zero_add, add_mul, mul_add, smul_mul_smul_comm, hg, smul_zero, op_smul_eq_smul] rw [← map_mul, LinearMap.map_add, add_comm (g _), add_assoc, hfg, hgf]) theorem lift_def (f : R →ₐ[S] A) (g : M →ₗ[S] A) (hg : ∀ x y, g x * g y = 0) (hfg : ∀ r x, g (r • x) = f r * g x) (hgf : ∀ r x, g (op r • x) = g x * f r) (x : tsze R M) : lift f g hg hfg hgf x = f x.fst + g x.snd := rfl @[simp] theorem lift_apply_inl (f : R →ₐ[S] A) (g : M →ₗ[S] A) (hg : ∀ x y, g x * g y = 0) (hfg : ∀ r x, g (r •> x) = f r * g x) (hgf : ∀ r x, g (x <• r) = g x * f r) (r : R) : lift f g hg hfg hgf (inl r) = f r := show f r + g 0 = f r by rw [map_zero, add_zero] @[simp] theorem lift_apply_inr (f : R →ₐ[S] A) (g : M →ₗ[S] A) (hg : ∀ x y, g x * g y = 0) (hfg : ∀ r x, g (r •> x) = f r * g x) (hgf : ∀ r x, g (x <• r) = g x * f r) (m : M) : lift f g hg hfg hgf (inr m) = g m := show f 0 + g m = g m by rw [map_zero, zero_add] @[simp] theorem lift_comp_inlHom (f : R →ₐ[S] A) (g : M →ₗ[S] A) (hg : ∀ x y, g x * g y = 0) (hfg : ∀ r x, g (r •> x) = f r * g x) (hgf : ∀ r x, g (x <• r) = g x * f r) : (lift f g hg hfg hgf).comp (inlAlgHom S R M) = f := AlgHom.ext <| lift_apply_inl f g hg hfg hgf @[simp] theorem lift_comp_inrHom (f : R →ₐ[S] A) (g : M →ₗ[S] A) (hg : ∀ x y, g x * g y = 0) (hfg : ∀ r x, g (r •> x) = f r * g x) (hgf : ∀ r x, g (x <• r) = g x * f r) : (lift f g hg hfg hgf).toLinearMap.comp (inrHom R M |>.restrictScalars S) = g := LinearMap.ext <| lift_apply_inr f g hg hfg hgf /-- When applied to `inr` and `inl` themselves, `lift` is the identity. -/ @[simp] theorem lift_inlAlgHom_inrHom : lift (inlAlgHom _ _ _) (inrHom R M |>.restrictScalars S) (inr_mul_inr R) (fun _ _ => (inl_mul_inr _ _).symm) (fun _ _ => (inr_mul_inl _ _).symm) = AlgHom.id S (tsze R M) := algHom_ext' (lift_comp_inlHom _ _ _ _ _) (lift_comp_inrHom _ _ _ _ _) /-- A universal property of the trivial square-zero extension, providing a unique `TrivSqZeroExt R M →ₐ[R] A` for every pair of maps `f : R →ₐ[S] A` and `g : M →ₗ[S] A`, where the range of `g` has no non-zero products, and scaling the input to `g` on the left or right amounts to a corresponding multiplication by `f` in the output. This isomorphism is named to match the very similar `Complex.lift`. -/ @[simps! apply symm_apply_coe] def liftEquiv : {fg : (R →ₐ[S] A) × (M →ₗ[S] A) // (∀ x y, fg.2 x * fg.2 y = 0) ∧ (∀ r x, fg.2 (r •> x) = fg.1 r * fg.2 x) ∧ (∀ r x, fg.2 (x <• r) = fg.2 x * fg.1 r)} ≃ (tsze R M →ₐ[S] A) where toFun fg := lift fg.val.1 fg.val.2 fg.prop.1 fg.prop.2.1 fg.prop.2.2 invFun F := ⟨(F.comp (inlAlgHom _ _ _), F.toLinearMap ∘ₗ (inrHom _ _ |>.restrictScalars _)), (fun _x _y => (map_mul F _ _).symm.trans <| (F.congr_arg <| inr_mul_inr _ _ _).trans (map_zero F)), (fun _r _x => (F.congr_arg (inl_mul_inr _ _).symm).trans (map_mul F _ _)), (fun _r _x => (F.congr_arg (inr_mul_inl _ _).symm).trans (map_mul F _ _))⟩ left_inv _f := Subtype.ext <| Prod.ext (lift_comp_inlHom _ _ _ _ _) (lift_comp_inrHom _ _ _ _ _) right_inv _F := algHom_ext' (lift_comp_inlHom _ _ _ _ _) (lift_comp_inrHom _ _ _ _ _) /-- A simplified version of `TrivSqZeroExt.liftEquiv` for the commutative case. -/ @[simps! apply symm_apply_coe] def liftEquivOfComm : { f : M →ₗ[R'] A // ∀ x y, f x * f y = 0 } ≃ (tsze R' M →ₐ[R'] A) := by refine Equiv.trans ?_ liftEquiv exact { toFun := fun f => ⟨(Algebra.ofId _ _, f.val), f.prop, fun r x => by simp [Algebra.smul_def, Algebra.ofId_apply], fun r x => by simp [Algebra.smul_def, Algebra.ofId_apply, Algebra.commutes]⟩ invFun := fun fg => ⟨fg.val.2, fg.prop.1⟩ left_inv := fun f => rfl right_inv := fun fg => Subtype.ext <| Prod.ext (AlgHom.toLinearMap_injective <| LinearMap.ext_ring <| by simp) rfl } section map variable {N P : Type*} [AddCommMonoid N] [Module R' N] [Module R'ᵐᵒᵖ N] [IsCentralScalar R' N] [AddCommMonoid P] [Module R' P] [Module R'ᵐᵒᵖ P] [IsCentralScalar R' P] /-- Functoriality of `TrivSqZeroExt` when the ring is commutative: a linear map `f : M →ₗ[R'] N` induces a morphism of `R'`-algebras from `TrivSqZeroExt R' M` to `TrivSqZeroExt R' N`. Note that we cannot neatly state the non-commutative case, as we do not have morphisms of bimodules. -/ def map (f : M →ₗ[R'] N) : TrivSqZeroExt R' M →ₐ[R'] TrivSqZeroExt R' N := liftEquivOfComm ⟨inrHom R' N ∘ₗ f, fun _ _ => inr_mul_inr _ _ _⟩ @[simp] theorem map_inl (f : M →ₗ[R'] N) (r : R') : map f (inl r) = inl r := by rw [map, liftEquivOfComm_apply, lift_apply_inl, Algebra.ofId_apply, algebraMap_eq_inl] @[simp] theorem map_inr (f : M →ₗ[R'] N) (x : M) : map f (inr x) = inr (f x) := by rw [map, liftEquivOfComm_apply, lift_apply_inr, LinearMap.comp_apply, inrHom_apply] @[simp] theorem fst_map (f : M →ₗ[R'] N) (x : TrivSqZeroExt R' M) : fst (map f x) = fst x := by simp [map, lift_def, Algebra.ofId_apply, algebraMap_eq_inl] @[simp] theorem snd_map (f : M →ₗ[R'] N) (x : TrivSqZeroExt R' M) : snd (map f x) = f (snd x) := by simp [map, lift_def, Algebra.ofId_apply, algebraMap_eq_inl] @[simp] theorem map_comp_inlAlgHom (f : M →ₗ[R'] N) : (map f).comp (inlAlgHom R' R' M) = inlAlgHom R' R' N := AlgHom.ext <| map_inl _ @[simp] theorem map_comp_inrHom (f : M →ₗ[R'] N) : (map f).toLinearMap ∘ₗ inrHom R' M = inrHom R' N ∘ₗ f := LinearMap.ext <| map_inr _ @[simp] theorem fstHom_comp_map (f : M →ₗ[R'] N) : (fstHom R' R' N).comp (map f) = fstHom R' R' M := AlgHom.ext <| fst_map _ @[simp] theorem sndHom_comp_map (f : M →ₗ[R'] N) : sndHom R' N ∘ₗ (map f).toLinearMap = f ∘ₗ sndHom R' M := LinearMap.ext <| snd_map _ @[simp] theorem map_id : map (LinearMap.id : M →ₗ[R'] M) = AlgHom.id R' _ := by apply algHom_ext simp only [map_inr, LinearMap.id_coe, id_eq, AlgHom.coe_id, forall_const] theorem map_comp_map (f : M →ₗ[R'] N) (g : N →ₗ[R'] P) : map (g.comp f) = (map g).comp (map f) := by apply algHom_ext simp only [map_inr, LinearMap.coe_comp, Function.comp_apply, AlgHom.coe_comp, forall_const] end map end Algebra
end TrivSqZeroExt
Mathlib/Algebra/TrivSqZeroExt.lean
1,102
1,105
/- Copyright (c) 2021 Rémy Degenne. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov -/ import Mathlib.MeasureTheory.Function.L1Space.Integrable import Mathlib.MeasureTheory.Function.LpSpace.Indicator /-! # Functions integrable on a set and at a filter We define `IntegrableOn f s μ := Integrable f (μ.restrict s)` and prove theorems like `integrableOn_union : IntegrableOn f (s ∪ t) μ ↔ IntegrableOn f s μ ∧ IntegrableOn f t μ`. Next we define a predicate `IntegrableAtFilter (f : α → E) (l : Filter α) (μ : Measure α)` saying that `f` is integrable at some set `s ∈ l` and prove that a measurable function is integrable at `l` with respect to `μ` provided that `f` is bounded above at `l ⊓ ae μ` and `μ` is finite at `l`. -/ noncomputable section open Set Filter TopologicalSpace MeasureTheory Function open scoped Topology Interval Filter ENNReal MeasureTheory variable {α β ε E F : Type*} [MeasurableSpace α] [ENorm ε] [TopologicalSpace ε] section variable [TopologicalSpace β] {l l' : Filter α} {f g : α → β} {μ ν : Measure α} /-- A function `f` is strongly measurable at a filter `l` w.r.t. a measure `μ` if it is ae strongly measurable w.r.t. `μ.restrict s` for some `s ∈ l`. -/ def StronglyMeasurableAtFilter (f : α → β) (l : Filter α) (μ : Measure α := by volume_tac) := ∃ s ∈ l, AEStronglyMeasurable f (μ.restrict s) @[simp] theorem stronglyMeasurableAt_bot {f : α → β} : StronglyMeasurableAtFilter f ⊥ μ := ⟨∅, mem_bot, by simp⟩ protected theorem StronglyMeasurableAtFilter.eventually (h : StronglyMeasurableAtFilter f l μ) : ∀ᶠ s in l.smallSets, AEStronglyMeasurable f (μ.restrict s) := (eventually_smallSets' fun _ _ => AEStronglyMeasurable.mono_set).2 h protected theorem StronglyMeasurableAtFilter.filter_mono (h : StronglyMeasurableAtFilter f l μ) (h' : l' ≤ l) : StronglyMeasurableAtFilter f l' μ := let ⟨s, hsl, hs⟩ := h ⟨s, h' hsl, hs⟩ protected theorem MeasureTheory.AEStronglyMeasurable.stronglyMeasurableAtFilter (h : AEStronglyMeasurable f μ) : StronglyMeasurableAtFilter f l μ := ⟨univ, univ_mem, by rwa [Measure.restrict_univ]⟩ theorem AEStronglyMeasurable.stronglyMeasurableAtFilter_of_mem {s} (h : AEStronglyMeasurable f (μ.restrict s)) (hl : s ∈ l) : StronglyMeasurableAtFilter f l μ := ⟨s, hl, h⟩ @[deprecated (since := "2025-02-12")] alias AeStronglyMeasurable.stronglyMeasurableAtFilter_of_mem := AEStronglyMeasurable.stronglyMeasurableAtFilter_of_mem protected theorem MeasureTheory.StronglyMeasurable.stronglyMeasurableAtFilter (h : StronglyMeasurable f) : StronglyMeasurableAtFilter f l μ := h.aestronglyMeasurable.stronglyMeasurableAtFilter end namespace MeasureTheory section NormedAddCommGroup theorem hasFiniteIntegral_restrict_of_bounded [NormedAddCommGroup E] {f : α → E} {s : Set α} {μ : Measure α} {C} (hs : μ s < ∞) (hf : ∀ᵐ x ∂μ.restrict s, ‖f x‖ ≤ C) : HasFiniteIntegral f (μ.restrict s) := haveI : IsFiniteMeasure (μ.restrict s) := ⟨by rwa [Measure.restrict_apply_univ]⟩ hasFiniteIntegral_of_bounded hf variable [NormedAddCommGroup E] {f g : α → E} {s t : Set α} {μ ν : Measure α} /-- A function is `IntegrableOn` a set `s` if it is almost everywhere strongly measurable on `s` and if the integral of its pointwise norm over `s` is less than infinity. -/ def IntegrableOn (f : α → ε) (s : Set α) (μ : Measure α := by volume_tac) : Prop := Integrable f (μ.restrict s) theorem IntegrableOn.integrable (h : IntegrableOn f s μ) : Integrable f (μ.restrict s) := h @[simp] theorem integrableOn_empty : IntegrableOn f ∅ μ := by simp [IntegrableOn, integrable_zero_measure] @[simp] theorem integrableOn_univ : IntegrableOn f univ μ ↔ Integrable f μ := by rw [IntegrableOn, Measure.restrict_univ] theorem integrableOn_zero : IntegrableOn (fun _ => (0 : E)) s μ := integrable_zero _ _ _ @[simp] theorem integrableOn_const {C : E} : IntegrableOn (fun _ => C) s μ ↔ C = 0 ∨ μ s < ∞ := integrable_const_iff.trans <| by rw [isFiniteMeasure_restrict, lt_top_iff_ne_top] theorem IntegrableOn.mono (h : IntegrableOn f t ν) (hs : s ⊆ t) (hμ : μ ≤ ν) : IntegrableOn f s μ := h.mono_measure <| Measure.restrict_mono hs hμ theorem IntegrableOn.mono_set (h : IntegrableOn f t μ) (hst : s ⊆ t) : IntegrableOn f s μ := h.mono hst le_rfl theorem IntegrableOn.mono_measure (h : IntegrableOn f s ν) (hμ : μ ≤ ν) : IntegrableOn f s μ := h.mono (Subset.refl _) hμ theorem IntegrableOn.mono_set_ae (h : IntegrableOn f t μ) (hst : s ≤ᵐ[μ] t) : IntegrableOn f s μ := h.integrable.mono_measure <| Measure.restrict_mono_ae hst theorem IntegrableOn.congr_set_ae (h : IntegrableOn f t μ) (hst : s =ᵐ[μ] t) : IntegrableOn f s μ := h.mono_set_ae hst.le theorem IntegrableOn.congr_fun_ae (h : IntegrableOn f s μ) (hst : f =ᵐ[μ.restrict s] g) : IntegrableOn g s μ := Integrable.congr h hst theorem integrableOn_congr_fun_ae (hst : f =ᵐ[μ.restrict s] g) : IntegrableOn f s μ ↔ IntegrableOn g s μ := ⟨fun h => h.congr_fun_ae hst, fun h => h.congr_fun_ae hst.symm⟩ theorem IntegrableOn.congr_fun (h : IntegrableOn f s μ) (hst : EqOn f g s) (hs : MeasurableSet s) : IntegrableOn g s μ := h.congr_fun_ae ((ae_restrict_iff' hs).2 (Eventually.of_forall hst)) theorem integrableOn_congr_fun (hst : EqOn f g s) (hs : MeasurableSet s) : IntegrableOn f s μ ↔ IntegrableOn g s μ := ⟨fun h => h.congr_fun hst hs, fun h => h.congr_fun hst.symm hs⟩ theorem Integrable.integrableOn (h : Integrable f μ) : IntegrableOn f s μ := h.restrict theorem IntegrableOn.restrict (h : IntegrableOn f s μ) : IntegrableOn f s (μ.restrict t) := by dsimp only [IntegrableOn] at h ⊢ exact h.mono_measure <| Measure.restrict_mono_measure Measure.restrict_le_self _ theorem IntegrableOn.inter_of_restrict (h : IntegrableOn f s (μ.restrict t)) : IntegrableOn f (s ∩ t) μ := by have := h.mono_set (inter_subset_left (t := t)) rwa [IntegrableOn, μ.restrict_restrict_of_subset inter_subset_right] at this lemma Integrable.piecewise [DecidablePred (· ∈ s)] (hs : MeasurableSet s) (hf : IntegrableOn f s μ) (hg : IntegrableOn g sᶜ μ) : Integrable (s.piecewise f g) μ := by rw [IntegrableOn] at hf hg rw [← memLp_one_iff_integrable] at hf hg ⊢ exact MemLp.piecewise hs hf hg theorem IntegrableOn.left_of_union (h : IntegrableOn f (s ∪ t) μ) : IntegrableOn f s μ := h.mono_set subset_union_left theorem IntegrableOn.right_of_union (h : IntegrableOn f (s ∪ t) μ) : IntegrableOn f t μ := h.mono_set subset_union_right theorem IntegrableOn.union (hs : IntegrableOn f s μ) (ht : IntegrableOn f t μ) : IntegrableOn f (s ∪ t) μ := (hs.add_measure ht).mono_measure <| Measure.restrict_union_le _ _ @[simp] theorem integrableOn_union : IntegrableOn f (s ∪ t) μ ↔ IntegrableOn f s μ ∧ IntegrableOn f t μ := ⟨fun h => ⟨h.left_of_union, h.right_of_union⟩, fun h => h.1.union h.2⟩ @[simp] theorem integrableOn_singleton_iff {x : α} [MeasurableSingletonClass α] : IntegrableOn f {x} μ ↔ f x = 0 ∨ μ {x} < ∞ := by have : f =ᵐ[μ.restrict {x}] fun _ => f x := by filter_upwards [ae_restrict_mem (measurableSet_singleton x)] with _ ha simp only [mem_singleton_iff.1 ha] rw [IntegrableOn, integrable_congr this, integrable_const_iff, isFiniteMeasure_restrict, lt_top_iff_ne_top] @[simp] theorem integrableOn_finite_biUnion {s : Set β} (hs : s.Finite) {t : β → Set α} : IntegrableOn f (⋃ i ∈ s, t i) μ ↔ ∀ i ∈ s, IntegrableOn f (t i) μ := by induction s, hs using Set.Finite.induction_on with | empty => simp | insert _ _ hf => simp [hf, or_imp, forall_and] @[simp] theorem integrableOn_finset_iUnion {s : Finset β} {t : β → Set α} : IntegrableOn f (⋃ i ∈ s, t i) μ ↔ ∀ i ∈ s, IntegrableOn f (t i) μ := integrableOn_finite_biUnion s.finite_toSet @[simp] theorem integrableOn_finite_iUnion [Finite β] {t : β → Set α} : IntegrableOn f (⋃ i, t i) μ ↔ ∀ i, IntegrableOn f (t i) μ := by cases nonempty_fintype β simpa using @integrableOn_finset_iUnion _ _ _ _ _ f μ Finset.univ t lemma IntegrableOn.finset [MeasurableSingletonClass α] {μ : Measure α} [IsFiniteMeasure μ] {s : Finset α} {f : α → E} : IntegrableOn f s μ := by rw [← s.toSet.biUnion_of_singleton] simp [integrableOn_finset_iUnion, measure_lt_top] lemma IntegrableOn.of_finite [MeasurableSingletonClass α] {μ : Measure α} [IsFiniteMeasure μ] {s : Set α} (hs : s.Finite) {f : α → E} : IntegrableOn f s μ := by simpa using IntegrableOn.finset (s := hs.toFinset) theorem IntegrableOn.add_measure (hμ : IntegrableOn f s μ) (hν : IntegrableOn f s ν) : IntegrableOn f s (μ + ν) := by delta IntegrableOn; rw [Measure.restrict_add]; exact hμ.integrable.add_measure hν @[simp] theorem integrableOn_add_measure : IntegrableOn f s (μ + ν) ↔ IntegrableOn f s μ ∧ IntegrableOn f s ν := ⟨fun h => ⟨h.mono_measure (Measure.le_add_right le_rfl), h.mono_measure (Measure.le_add_left le_rfl)⟩, fun h => h.1.add_measure h.2⟩ theorem _root_.MeasurableEmbedding.integrableOn_map_iff [MeasurableSpace β] {e : α → β} (he : MeasurableEmbedding e) {f : β → E} {μ : Measure α} {s : Set β} : IntegrableOn f s (μ.map e) ↔ IntegrableOn (f ∘ e) (e ⁻¹' s) μ := by simp_rw [IntegrableOn, he.restrict_map, he.integrable_map_iff] theorem _root_.MeasurableEmbedding.integrableOn_iff_comap [MeasurableSpace β] {e : α → β} (he : MeasurableEmbedding e) {f : β → E} {μ : Measure β} {s : Set β} (hs : s ⊆ range e) : IntegrableOn f s μ ↔ IntegrableOn (f ∘ e) (e ⁻¹' s) (μ.comap e) := by simp_rw [← he.integrableOn_map_iff, he.map_comap, IntegrableOn, Measure.restrict_restrict_of_subset hs] theorem _root_.MeasurableEmbedding.integrableOn_range_iff_comap [MeasurableSpace β] {e : α → β} (he : MeasurableEmbedding e) {f : β → E} {μ : Measure β} : IntegrableOn f (range e) μ ↔ Integrable (f ∘ e) (μ.comap e) := by rw [he.integrableOn_iff_comap .rfl, preimage_range, integrableOn_univ] theorem integrableOn_iff_comap_subtypeVal (hs : MeasurableSet s) : IntegrableOn f s μ ↔ Integrable (f ∘ (↑) : s → E) (μ.comap (↑)) := by rw [← (MeasurableEmbedding.subtype_coe hs).integrableOn_range_iff_comap, Subtype.range_val] theorem integrableOn_map_equiv [MeasurableSpace β] (e : α ≃ᵐ β) {f : β → E} {μ : Measure α} {s : Set β} : IntegrableOn f s (μ.map e) ↔ IntegrableOn (f ∘ e) (e ⁻¹' s) μ := by simp only [IntegrableOn, e.restrict_map, integrable_map_equiv e] theorem MeasurePreserving.integrableOn_comp_preimage [MeasurableSpace β] {e : α → β} {ν} (h₁ : MeasurePreserving e μ ν) (h₂ : MeasurableEmbedding e) {f : β → E} {s : Set β} : IntegrableOn (f ∘ e) (e ⁻¹' s) μ ↔ IntegrableOn f s ν := (h₁.restrict_preimage_emb h₂ s).integrable_comp_emb h₂ theorem MeasurePreserving.integrableOn_image [MeasurableSpace β] {e : α → β} {ν} (h₁ : MeasurePreserving e μ ν) (h₂ : MeasurableEmbedding e) {f : β → E} {s : Set α} : IntegrableOn f (e '' s) ν ↔ IntegrableOn (f ∘ e) s μ := ((h₁.restrict_image_emb h₂ s).integrable_comp_emb h₂).symm theorem integrable_indicator_iff (hs : MeasurableSet s) : Integrable (indicator s f) μ ↔ IntegrableOn f s μ := by simp_rw [IntegrableOn, Integrable, hasFiniteIntegral_iff_enorm, enorm_indicator_eq_indicator_enorm, lintegral_indicator hs, aestronglyMeasurable_indicator_iff hs] theorem IntegrableOn.integrable_indicator (h : IntegrableOn f s μ) (hs : MeasurableSet s) : Integrable (indicator s f) μ := (integrable_indicator_iff hs).2 h @[fun_prop] theorem Integrable.indicator (h : Integrable f μ) (hs : MeasurableSet s) : Integrable (indicator s f) μ := h.integrableOn.integrable_indicator hs theorem IntegrableOn.indicator (h : IntegrableOn f s μ) (ht : MeasurableSet t) : IntegrableOn (indicator t f) s μ := Integrable.indicator h ht theorem integrable_indicatorConstLp {E} [NormedAddCommGroup E] {p : ℝ≥0∞} {s : Set α} (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : E) : Integrable (indicatorConstLp p hs hμs c) μ := by rw [integrable_congr indicatorConstLp_coeFn, integrable_indicator_iff hs, IntegrableOn, integrable_const_iff, isFiniteMeasure_restrict] exact .inr hμs /-- If a function is integrable on a set `s` and nonzero there, then the measurable hull of `s` is well behaved: the restriction of the measure to `toMeasurable μ s` coincides with its restriction to `s`. -/ theorem IntegrableOn.restrict_toMeasurable (hf : IntegrableOn f s μ) (h's : ∀ x ∈ s, f x ≠ 0) : μ.restrict (toMeasurable μ s) = μ.restrict s := by rcases exists_seq_strictAnti_tendsto (0 : ℝ) with ⟨u, _, u_pos, u_lim⟩ let v n := toMeasurable (μ.restrict s) { x | u n ≤ ‖f x‖ } have A : ∀ n, μ (s ∩ v n) ≠ ∞ := by intro n rw [inter_comm, ← Measure.restrict_apply (measurableSet_toMeasurable _ _), measure_toMeasurable] exact (hf.measure_norm_ge_lt_top (u_pos n)).ne apply Measure.restrict_toMeasurable_of_cover _ A intro x hx have : 0 < ‖f x‖ := by simp only [h's x hx, norm_pos_iff, Ne, not_false_iff] obtain ⟨n, hn⟩ : ∃ n, u n < ‖f x‖ := ((tendsto_order.1 u_lim).2 _ this).exists exact mem_iUnion.2 ⟨n, subset_toMeasurable _ _ hn.le⟩ /-- If a function is integrable on a set `s`, and vanishes on `t \ s`, then it is integrable on `t` if `t` is null-measurable. -/ theorem IntegrableOn.of_ae_diff_eq_zero (hf : IntegrableOn f s μ) (ht : NullMeasurableSet t μ) (h't : ∀ᵐ x ∂μ, x ∈ t \ s → f x = 0) : IntegrableOn f t μ := by let u := { x ∈ s | f x ≠ 0 } have hu : IntegrableOn f u μ := hf.mono_set fun x hx => hx.1 let v := toMeasurable μ u have A : IntegrableOn f v μ := by rw [IntegrableOn, hu.restrict_toMeasurable] · exact hu · intro x hx; exact hx.2 have B : IntegrableOn f (t \ v) μ := by apply integrableOn_zero.congr filter_upwards [ae_restrict_of_ae h't, ae_restrict_mem₀ (ht.diff (measurableSet_toMeasurable μ u).nullMeasurableSet)] with x hxt hx by_cases h'x : x ∈ s · by_contra H exact hx.2 (subset_toMeasurable μ u ⟨h'x, Ne.symm H⟩) · exact (hxt ⟨hx.1, h'x⟩).symm apply (A.union B).mono_set _ rw [union_diff_self] exact subset_union_right /-- If a function is integrable on a set `s`, and vanishes on `t \ s`, then it is integrable on `t` if `t` is measurable. -/ theorem IntegrableOn.of_forall_diff_eq_zero (hf : IntegrableOn f s μ) (ht : MeasurableSet t) (h't : ∀ x ∈ t \ s, f x = 0) : IntegrableOn f t μ := hf.of_ae_diff_eq_zero ht.nullMeasurableSet (Eventually.of_forall h't) /-- If a function is integrable on a set `s` and vanishes almost everywhere on its complement, then it is integrable. -/ theorem IntegrableOn.integrable_of_ae_not_mem_eq_zero (hf : IntegrableOn f s μ) (h't : ∀ᵐ x ∂μ, x ∉ s → f x = 0) : Integrable f μ := by rw [← integrableOn_univ] apply hf.of_ae_diff_eq_zero nullMeasurableSet_univ filter_upwards [h't] with x hx h'x using hx h'x.2 /-- If a function is integrable on a set `s` and vanishes everywhere on its complement, then it is integrable. -/ theorem IntegrableOn.integrable_of_forall_not_mem_eq_zero (hf : IntegrableOn f s μ) (h't : ∀ x, x ∉ s → f x = 0) : Integrable f μ := hf.integrable_of_ae_not_mem_eq_zero (Eventually.of_forall fun x hx => h't x hx) theorem integrableOn_iff_integrable_of_support_subset (h1s : support f ⊆ s) : IntegrableOn f s μ ↔ Integrable f μ := by refine ⟨fun h => ?_, fun h => h.integrableOn⟩ refine h.integrable_of_forall_not_mem_eq_zero fun x hx => ?_ contrapose! hx exact h1s (mem_support.2 hx) theorem integrableOn_Lp_of_measure_ne_top {E} [NormedAddCommGroup E] {p : ℝ≥0∞} {s : Set α} (f : Lp E p μ) (hp : 1 ≤ p) (hμs : μ s ≠ ∞) : IntegrableOn f s μ := by refine memLp_one_iff_integrable.mp ?_ have hμ_restrict_univ : (μ.restrict s) Set.univ < ∞ := by simpa only [Set.univ_inter, MeasurableSet.univ, Measure.restrict_apply, lt_top_iff_ne_top] haveI hμ_finite : IsFiniteMeasure (μ.restrict s) := ⟨hμ_restrict_univ⟩ exact ((Lp.memLp _).restrict s).mono_exponent hp theorem Integrable.lintegral_lt_top {f : α → ℝ} (hf : Integrable f μ) : (∫⁻ x, ENNReal.ofReal (f x) ∂μ) < ∞ := calc (∫⁻ x, ENNReal.ofReal (f x) ∂μ) ≤ ∫⁻ x, ↑‖f x‖₊ ∂μ := lintegral_ofReal_le_lintegral_enorm f _ < ∞ := hf.2 theorem IntegrableOn.setLIntegral_lt_top {f : α → ℝ} {s : Set α} (hf : IntegrableOn f s μ) : (∫⁻ x in s, ENNReal.ofReal (f x) ∂μ) < ∞ := Integrable.lintegral_lt_top hf /-- We say that a function `f` is *integrable at filter* `l` if it is integrable on some set `s ∈ l`. Equivalently, it is eventually integrable on `s` in `l.smallSets`. -/ def IntegrableAtFilter (f : α → ε) (l : Filter α) (μ : Measure α := by volume_tac) := ∃ s ∈ l, IntegrableOn f s μ
variable {l l' : Filter α} theorem _root_.MeasurableEmbedding.integrableAtFilter_map_iff [MeasurableSpace β] {e : α → β} (he : MeasurableEmbedding e) {f : β → E} : IntegrableAtFilter f (l.map e) (μ.map e) ↔ IntegrableAtFilter (f ∘ e) l μ := by simp_rw [IntegrableAtFilter, he.integrableOn_map_iff]
Mathlib/MeasureTheory/Integral/IntegrableOn.lean
365
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/- Copyright (c) 2018 Michael Jendrusch. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Michael Jendrusch, Kim Morrison, Bhavik Mehta, Jakob von Raumer -/ import Mathlib.CategoryTheory.EqToHom import Mathlib.CategoryTheory.Functor.Trifunctor import Mathlib.CategoryTheory.Products.Basic /-! # Monoidal categories A monoidal category is a category equipped with a tensor product, unitors, and an associator. In the definition, we provide the tensor product as a pair of functions * `tensorObj : C → C → C` * `tensorHom : (X₁ ⟶ Y₁) → (X₂ ⟶ Y₂) → ((X₁ ⊗ X₂) ⟶ (Y₁ ⊗ Y₂))` and allow use of the overloaded notation `⊗` for both. The unitors and associator are provided componentwise. The tensor product can be expressed as a functor via `tensor : C × C ⥤ C`. The unitors and associator are gathered together as natural isomorphisms in `leftUnitor_nat_iso`, `rightUnitor_nat_iso` and `associator_nat_iso`. Some consequences of the definition are proved in other files after proving the coherence theorem, e.g. `(λ_ (𝟙_ C)).hom = (ρ_ (𝟙_ C)).hom` in `CategoryTheory.Monoidal.CoherenceLemmas`. ## Implementation notes In the definition of monoidal categories, we also provide the whiskering operators: * `whiskerLeft (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂) : X ⊗ Y₁ ⟶ X ⊗ Y₂`, denoted by `X ◁ f`, * `whiskerRight {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C) : X₁ ⊗ Y ⟶ X₂ ⊗ Y`, denoted by `f ▷ Y`. These are products of an object and a morphism (the terminology "whiskering" is borrowed from 2-category theory). The tensor product of morphisms `tensorHom` can be defined in terms of the whiskerings. There are two possible such definitions, which are related by the exchange property of the whiskerings. These two definitions are accessed by `tensorHom_def` and `tensorHom_def'`. By default, `tensorHom` is defined so that `tensorHom_def` holds definitionally. If you want to provide `tensorHom` and define `whiskerLeft` and `whiskerRight` in terms of it, you can use the alternative constructor `CategoryTheory.MonoidalCategory.ofTensorHom`. The whiskerings are useful when considering simp-normal forms of morphisms in monoidal categories. ### Simp-normal form for morphisms Rewriting involving associators and unitors could be very complicated. We try to ease this complexity by putting carefully chosen simp lemmas that rewrite any morphisms into the simp-normal form defined below. Rewriting into simp-normal form is especially useful in preprocessing performed by the `coherence` tactic. The simp-normal form of morphisms is defined to be an expression that has the minimal number of parentheses. More precisely, 1. it is a composition of morphisms like `f₁ ≫ f₂ ≫ f₃ ≫ f₄ ≫ f₅` such that each `fᵢ` is either a structural morphisms (morphisms made up only of identities, associators, unitors) or non-structural morphisms, and 2. each non-structural morphism in the composition is of the form `X₁ ◁ X₂ ◁ X₃ ◁ f ▷ X₄ ▷ X₅`, where each `Xᵢ` is a object that is not the identity or a tensor and `f` is a non-structural morphisms that is not the identity or a composite. Note that `X₁ ◁ X₂ ◁ X₃ ◁ f ▷ X₄ ▷ X₅` is actually `X₁ ◁ (X₂ ◁ (X₃ ◁ ((f ▷ X₄) ▷ X₅)))`. Currently, the simp lemmas don't rewrite `𝟙 X ⊗ f` and `f ⊗ 𝟙 Y` into `X ◁ f` and `f ▷ Y`, respectively, since it requires a huge refactoring. We hope to add these simp lemmas soon. ## References * Tensor categories, Etingof, Gelaki, Nikshych, Ostrik, http://www-math.mit.edu/~etingof/egnobookfinal.pdf * <https://stacks.math.columbia.edu/tag/0FFK>. -/ universe v u open CategoryTheory.Category open CategoryTheory.Iso namespace CategoryTheory /-- Auxiliary structure to carry only the data fields of (and provide notation for) `MonoidalCategory`. -/ class MonoidalCategoryStruct (C : Type u) [𝒞 : Category.{v} C] where /-- curried tensor product of objects -/ tensorObj : C → C → C /-- left whiskering for morphisms -/ whiskerLeft (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂) : tensorObj X Y₁ ⟶ tensorObj X Y₂ /-- right whiskering for morphisms -/ whiskerRight {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C) : tensorObj X₁ Y ⟶ tensorObj X₂ Y /-- Tensor product of identity maps is the identity: `(𝟙 X₁ ⊗ 𝟙 X₂) = 𝟙 (X₁ ⊗ X₂)` -/ -- By default, it is defined in terms of whiskerings. tensorHom {X₁ Y₁ X₂ Y₂ : C} (f : X₁ ⟶ Y₁) (g : X₂ ⟶ Y₂) : (tensorObj X₁ X₂ ⟶ tensorObj Y₁ Y₂) := whiskerRight f X₂ ≫ whiskerLeft Y₁ g /-- The tensor unity in the monoidal structure `𝟙_ C` -/ tensorUnit (C) : C /-- The associator isomorphism `(X ⊗ Y) ⊗ Z ≃ X ⊗ (Y ⊗ Z)` -/ associator : ∀ X Y Z : C, tensorObj (tensorObj X Y) Z ≅ tensorObj X (tensorObj Y Z) /-- The left unitor: `𝟙_ C ⊗ X ≃ X` -/ leftUnitor : ∀ X : C, tensorObj tensorUnit X ≅ X /-- The right unitor: `X ⊗ 𝟙_ C ≃ X` -/ rightUnitor : ∀ X : C, tensorObj X tensorUnit ≅ X namespace MonoidalCategory export MonoidalCategoryStruct (tensorObj whiskerLeft whiskerRight tensorHom tensorUnit associator leftUnitor rightUnitor) end MonoidalCategory namespace MonoidalCategory /-- Notation for `tensorObj`, the tensor product of objects in a monoidal category -/ scoped infixr:70 " ⊗ " => MonoidalCategoryStruct.tensorObj /-- Notation for the `whiskerLeft` operator of monoidal categories -/ scoped infixr:81 " ◁ " => MonoidalCategoryStruct.whiskerLeft /-- Notation for the `whiskerRight` operator of monoidal categories -/ scoped infixl:81 " ▷ " => MonoidalCategoryStruct.whiskerRight /-- Notation for `tensorHom`, the tensor product of morphisms in a monoidal category -/ scoped infixr:70 " ⊗ " => MonoidalCategoryStruct.tensorHom /-- Notation for `tensorUnit`, the two-sided identity of `⊗` -/ scoped notation "𝟙_ " C:arg => MonoidalCategoryStruct.tensorUnit C /-- Notation for the monoidal `associator`: `(X ⊗ Y) ⊗ Z ≃ X ⊗ (Y ⊗ Z)` -/ scoped notation "α_" => MonoidalCategoryStruct.associator /-- Notation for the `leftUnitor`: `𝟙_C ⊗ X ≃ X` -/ scoped notation "λ_" => MonoidalCategoryStruct.leftUnitor /-- Notation for the `rightUnitor`: `X ⊗ 𝟙_C ≃ X` -/ scoped notation "ρ_" => MonoidalCategoryStruct.rightUnitor /-- The property that the pentagon relation is satisfied by four objects in a category equipped with a `MonoidalCategoryStruct`. -/ def Pentagon {C : Type u} [Category.{v} C] [MonoidalCategoryStruct C] (Y₁ Y₂ Y₃ Y₄ : C) : Prop := (α_ Y₁ Y₂ Y₃).hom ▷ Y₄ ≫ (α_ Y₁ (Y₂ ⊗ Y₃) Y₄).hom ≫ Y₁ ◁ (α_ Y₂ Y₃ Y₄).hom = (α_ (Y₁ ⊗ Y₂) Y₃ Y₄).hom ≫ (α_ Y₁ Y₂ (Y₃ ⊗ Y₄)).hom end MonoidalCategory open MonoidalCategory /-- In a monoidal category, we can take the tensor product of objects, `X ⊗ Y` and of morphisms `f ⊗ g`. Tensor product does not need to be strictly associative on objects, but there is a specified associator, `α_ X Y Z : (X ⊗ Y) ⊗ Z ≅ X ⊗ (Y ⊗ Z)`. There is a tensor unit `𝟙_ C`, with specified left and right unitor isomorphisms `λ_ X : 𝟙_ C ⊗ X ≅ X` and `ρ_ X : X ⊗ 𝟙_ C ≅ X`. These associators and unitors satisfy the pentagon and triangle equations. -/ @[stacks 0FFK] -- Porting note: The Mathport did not translate the temporary notation class MonoidalCategory (C : Type u) [𝒞 : Category.{v} C] extends MonoidalCategoryStruct C where tensorHom_def {X₁ Y₁ X₂ Y₂ : C} (f : X₁ ⟶ Y₁) (g : X₂ ⟶ Y₂) : f ⊗ g = (f ▷ X₂) ≫ (Y₁ ◁ g) := by aesop_cat /-- Tensor product of identity maps is the identity: `(𝟙 X₁ ⊗ 𝟙 X₂) = 𝟙 (X₁ ⊗ X₂)` -/ tensor_id : ∀ X₁ X₂ : C, 𝟙 X₁ ⊗ 𝟙 X₂ = 𝟙 (X₁ ⊗ X₂) := by aesop_cat /-- Tensor product of compositions is composition of tensor products: `(f₁ ≫ g₁) ⊗ (f₂ ≫ g₂) = (f₁ ⊗ f₂) ≫ (g₁ ⊗ g₂)` -/ tensor_comp : ∀ {X₁ Y₁ Z₁ X₂ Y₂ Z₂ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (g₁ : Y₁ ⟶ Z₁) (g₂ : Y₂ ⟶ Z₂), (f₁ ≫ g₁) ⊗ (f₂ ≫ g₂) = (f₁ ⊗ f₂) ≫ (g₁ ⊗ g₂) := by aesop_cat whiskerLeft_id : ∀ (X Y : C), X ◁ 𝟙 Y = 𝟙 (X ⊗ Y) := by aesop_cat id_whiskerRight : ∀ (X Y : C), 𝟙 X ▷ Y = 𝟙 (X ⊗ Y) := by aesop_cat /-- Naturality of the associator isomorphism: `(f₁ ⊗ f₂) ⊗ f₃ ≃ f₁ ⊗ (f₂ ⊗ f₃)` -/ associator_naturality : ∀ {X₁ X₂ X₃ Y₁ Y₂ Y₃ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (f₃ : X₃ ⟶ Y₃), ((f₁ ⊗ f₂) ⊗ f₃) ≫ (α_ Y₁ Y₂ Y₃).hom = (α_ X₁ X₂ X₃).hom ≫ (f₁ ⊗ (f₂ ⊗ f₃)) := by aesop_cat /-- Naturality of the left unitor, commutativity of `𝟙_ C ⊗ X ⟶ 𝟙_ C ⊗ Y ⟶ Y` and `𝟙_ C ⊗ X ⟶ X ⟶ Y` -/ leftUnitor_naturality : ∀ {X Y : C} (f : X ⟶ Y), 𝟙_ _ ◁ f ≫ (λ_ Y).hom = (λ_ X).hom ≫ f := by aesop_cat /-- Naturality of the right unitor: commutativity of `X ⊗ 𝟙_ C ⟶ Y ⊗ 𝟙_ C ⟶ Y` and `X ⊗ 𝟙_ C ⟶ X ⟶ Y` -/ rightUnitor_naturality : ∀ {X Y : C} (f : X ⟶ Y), f ▷ 𝟙_ _ ≫ (ρ_ Y).hom = (ρ_ X).hom ≫ f := by aesop_cat /-- The pentagon identity relating the isomorphism between `X ⊗ (Y ⊗ (Z ⊗ W))` and `((X ⊗ Y) ⊗ Z) ⊗ W` -/ pentagon : ∀ W X Y Z : C, (α_ W X Y).hom ▷ Z ≫ (α_ W (X ⊗ Y) Z).hom ≫ W ◁ (α_ X Y Z).hom = (α_ (W ⊗ X) Y Z).hom ≫ (α_ W X (Y ⊗ Z)).hom := by aesop_cat /-- The identity relating the isomorphisms between `X ⊗ (𝟙_ C ⊗ Y)`, `(X ⊗ 𝟙_ C) ⊗ Y` and `X ⊗ Y` -/ triangle : ∀ X Y : C, (α_ X (𝟙_ _) Y).hom ≫ X ◁ (λ_ Y).hom = (ρ_ X).hom ▷ Y := by aesop_cat attribute [reassoc] MonoidalCategory.tensorHom_def attribute [reassoc, simp] MonoidalCategory.whiskerLeft_id attribute [reassoc, simp] MonoidalCategory.id_whiskerRight attribute [reassoc] MonoidalCategory.tensor_comp attribute [simp] MonoidalCategory.tensor_comp attribute [reassoc] MonoidalCategory.associator_naturality attribute [reassoc] MonoidalCategory.leftUnitor_naturality attribute [reassoc] MonoidalCategory.rightUnitor_naturality attribute [reassoc (attr := simp)] MonoidalCategory.pentagon attribute [reassoc (attr := simp)] MonoidalCategory.triangle namespace MonoidalCategory variable {C : Type u} [𝒞 : Category.{v} C] [MonoidalCategory C] @[simp] theorem id_tensorHom (X : C) {Y₁ Y₂ : C} (f : Y₁ ⟶ Y₂) : 𝟙 X ⊗ f = X ◁ f := by simp [tensorHom_def] @[simp] theorem tensorHom_id {X₁ X₂ : C} (f : X₁ ⟶ X₂) (Y : C) : f ⊗ 𝟙 Y = f ▷ Y := by simp [tensorHom_def] @[reassoc, simp] theorem whiskerLeft_comp (W : C) {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) : W ◁ (f ≫ g) = W ◁ f ≫ W ◁ g := by simp only [← id_tensorHom, ← tensor_comp, comp_id] @[reassoc, simp] theorem id_whiskerLeft {X Y : C} (f : X ⟶ Y) : 𝟙_ C ◁ f = (λ_ X).hom ≫ f ≫ (λ_ Y).inv := by rw [← assoc, ← leftUnitor_naturality]; simp [id_tensorHom] @[reassoc, simp] theorem tensor_whiskerLeft (X Y : C) {Z Z' : C} (f : Z ⟶ Z') : (X ⊗ Y) ◁ f = (α_ X Y Z).hom ≫ X ◁ Y ◁ f ≫ (α_ X Y Z').inv := by simp only [← id_tensorHom, ← tensorHom_id] rw [← assoc, ← associator_naturality] simp @[reassoc, simp] theorem comp_whiskerRight {W X Y : C} (f : W ⟶ X) (g : X ⟶ Y) (Z : C) : (f ≫ g) ▷ Z = f ▷ Z ≫ g ▷ Z := by simp only [← tensorHom_id, ← tensor_comp, id_comp] @[reassoc, simp] theorem whiskerRight_id {X Y : C} (f : X ⟶ Y) : f ▷ 𝟙_ C = (ρ_ X).hom ≫ f ≫ (ρ_ Y).inv := by rw [← assoc, ← rightUnitor_naturality]; simp [tensorHom_id] @[reassoc, simp] theorem whiskerRight_tensor {X X' : C} (f : X ⟶ X') (Y Z : C) : f ▷ (Y ⊗ Z) = (α_ X Y Z).inv ≫ f ▷ Y ▷ Z ≫ (α_ X' Y Z).hom := by simp only [← id_tensorHom, ← tensorHom_id] rw [associator_naturality] simp [tensor_id] @[reassoc, simp] theorem whisker_assoc (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) : (X ◁ f) ▷ Z = (α_ X Y Z).hom ≫ X ◁ f ▷ Z ≫ (α_ X Y' Z).inv := by simp only [← id_tensorHom, ← tensorHom_id] rw [← assoc, ← associator_naturality] simp @[reassoc] theorem whisker_exchange {W X Y Z : C} (f : W ⟶ X) (g : Y ⟶ Z) : W ◁ g ≫ f ▷ Z = f ▷ Y ≫ X ◁ g := by simp only [← id_tensorHom, ← tensorHom_id, ← tensor_comp, id_comp, comp_id] @[reassoc] theorem tensorHom_def' {X₁ Y₁ X₂ Y₂ : C} (f : X₁ ⟶ Y₁) (g : X₂ ⟶ Y₂) : f ⊗ g = X₁ ◁ g ≫ f ▷ Y₂ := whisker_exchange f g ▸ tensorHom_def f g @[reassoc (attr := simp)] theorem whiskerLeft_hom_inv (X : C) {Y Z : C} (f : Y ≅ Z) : X ◁ f.hom ≫ X ◁ f.inv = 𝟙 (X ⊗ Y) := by rw [← whiskerLeft_comp, hom_inv_id, whiskerLeft_id] @[reassoc (attr := simp)] theorem hom_inv_whiskerRight {X Y : C} (f : X ≅ Y) (Z : C) : f.hom ▷ Z ≫ f.inv ▷ Z = 𝟙 (X ⊗ Z) := by rw [← comp_whiskerRight, hom_inv_id, id_whiskerRight] @[reassoc (attr := simp)] theorem whiskerLeft_inv_hom (X : C) {Y Z : C} (f : Y ≅ Z) : X ◁ f.inv ≫ X ◁ f.hom = 𝟙 (X ⊗ Z) := by rw [← whiskerLeft_comp, inv_hom_id, whiskerLeft_id] @[reassoc (attr := simp)] theorem inv_hom_whiskerRight {X Y : C} (f : X ≅ Y) (Z : C) : f.inv ▷ Z ≫ f.hom ▷ Z = 𝟙 (Y ⊗ Z) := by rw [← comp_whiskerRight, inv_hom_id, id_whiskerRight] @[reassoc (attr := simp)] theorem whiskerLeft_hom_inv' (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] : X ◁ f ≫ X ◁ inv f = 𝟙 (X ⊗ Y) := by rw [← whiskerLeft_comp, IsIso.hom_inv_id, whiskerLeft_id] @[reassoc (attr := simp)] theorem hom_inv_whiskerRight' {X Y : C} (f : X ⟶ Y) [IsIso f] (Z : C) : f ▷ Z ≫ inv f ▷ Z = 𝟙 (X ⊗ Z) := by rw [← comp_whiskerRight, IsIso.hom_inv_id, id_whiskerRight] @[reassoc (attr := simp)] theorem whiskerLeft_inv_hom' (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] : X ◁ inv f ≫ X ◁ f = 𝟙 (X ⊗ Z) := by rw [← whiskerLeft_comp, IsIso.inv_hom_id, whiskerLeft_id] @[reassoc (attr := simp)] theorem inv_hom_whiskerRight' {X Y : C} (f : X ⟶ Y) [IsIso f] (Z : C) : inv f ▷ Z ≫ f ▷ Z = 𝟙 (Y ⊗ Z) := by rw [← comp_whiskerRight, IsIso.inv_hom_id, id_whiskerRight] /-- The left whiskering of an isomorphism is an isomorphism. -/ @[simps] def whiskerLeftIso (X : C) {Y Z : C} (f : Y ≅ Z) : X ⊗ Y ≅ X ⊗ Z where hom := X ◁ f.hom inv := X ◁ f.inv instance whiskerLeft_isIso (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] : IsIso (X ◁ f) := (whiskerLeftIso X (asIso f)).isIso_hom @[simp] theorem inv_whiskerLeft (X : C) {Y Z : C} (f : Y ⟶ Z) [IsIso f] : inv (X ◁ f) = X ◁ inv f := by aesop_cat @[simp] lemma whiskerLeftIso_refl (W X : C) : whiskerLeftIso W (Iso.refl X) = Iso.refl (W ⊗ X) := Iso.ext (whiskerLeft_id W X) @[simp] lemma whiskerLeftIso_trans (W : C) {X Y Z : C} (f : X ≅ Y) (g : Y ≅ Z) : whiskerLeftIso W (f ≪≫ g) = whiskerLeftIso W f ≪≫ whiskerLeftIso W g := Iso.ext (whiskerLeft_comp W f.hom g.hom) @[simp] lemma whiskerLeftIso_symm (W : C) {X Y : C} (f : X ≅ Y) : (whiskerLeftIso W f).symm = whiskerLeftIso W f.symm := rfl /-- The right whiskering of an isomorphism is an isomorphism. -/ @[simps!] def whiskerRightIso {X Y : C} (f : X ≅ Y) (Z : C) : X ⊗ Z ≅ Y ⊗ Z where hom := f.hom ▷ Z inv := f.inv ▷ Z instance whiskerRight_isIso {X Y : C} (f : X ⟶ Y) (Z : C) [IsIso f] : IsIso (f ▷ Z) := (whiskerRightIso (asIso f) Z).isIso_hom @[simp] theorem inv_whiskerRight {X Y : C} (f : X ⟶ Y) (Z : C) [IsIso f] : inv (f ▷ Z) = inv f ▷ Z := by aesop_cat @[simp] lemma whiskerRightIso_refl (X W : C) : whiskerRightIso (Iso.refl X) W = Iso.refl (X ⊗ W) := Iso.ext (id_whiskerRight X W) @[simp] lemma whiskerRightIso_trans {X Y Z : C} (f : X ≅ Y) (g : Y ≅ Z) (W : C) : whiskerRightIso (f ≪≫ g) W = whiskerRightIso f W ≪≫ whiskerRightIso g W := Iso.ext (comp_whiskerRight f.hom g.hom W) @[simp] lemma whiskerRightIso_symm {X Y : C} (f : X ≅ Y) (W : C) : (whiskerRightIso f W).symm = whiskerRightIso f.symm W := rfl /-- The tensor product of two isomorphisms is an isomorphism. -/ @[simps] def tensorIso {X Y X' Y' : C} (f : X ≅ Y) (g : X' ≅ Y') : X ⊗ X' ≅ Y ⊗ Y' where hom := f.hom ⊗ g.hom inv := f.inv ⊗ g.inv hom_inv_id := by rw [← tensor_comp, Iso.hom_inv_id, Iso.hom_inv_id, ← tensor_id] inv_hom_id := by rw [← tensor_comp, Iso.inv_hom_id, Iso.inv_hom_id, ← tensor_id] /-- Notation for `tensorIso`, the tensor product of isomorphisms -/ scoped infixr:70 " ⊗ " => tensorIso theorem tensorIso_def {X Y X' Y' : C} (f : X ≅ Y) (g : X' ≅ Y') : f ⊗ g = whiskerRightIso f X' ≪≫ whiskerLeftIso Y g := Iso.ext (tensorHom_def f.hom g.hom) theorem tensorIso_def' {X Y X' Y' : C} (f : X ≅ Y) (g : X' ≅ Y') : f ⊗ g = whiskerLeftIso X g ≪≫ whiskerRightIso f Y' := Iso.ext (tensorHom_def' f.hom g.hom) instance tensor_isIso {W X Y Z : C} (f : W ⟶ X) [IsIso f] (g : Y ⟶ Z) [IsIso g] : IsIso (f ⊗ g) := (asIso f ⊗ asIso g).isIso_hom @[simp] theorem inv_tensor {W X Y Z : C} (f : W ⟶ X) [IsIso f] (g : Y ⟶ Z) [IsIso g] : inv (f ⊗ g) = inv f ⊗ inv g := by simp [tensorHom_def ,whisker_exchange] variable {W X Y Z : C} theorem whiskerLeft_dite {P : Prop} [Decidable P] (X : C) {Y Z : C} (f : P → (Y ⟶ Z)) (f' : ¬P → (Y ⟶ Z)) : X ◁ (if h : P then f h else f' h) = if h : P then X ◁ f h else X ◁ f' h := by split_ifs <;> rfl theorem dite_whiskerRight {P : Prop} [Decidable P] {X Y : C} (f : P → (X ⟶ Y)) (f' : ¬P → (X ⟶ Y)) (Z : C) : (if h : P then f h else f' h) ▷ Z = if h : P then f h ▷ Z else f' h ▷ Z := by split_ifs <;> rfl theorem tensor_dite {P : Prop} [Decidable P] {W X Y Z : C} (f : W ⟶ X) (g : P → (Y ⟶ Z)) (g' : ¬P → (Y ⟶ Z)) : (f ⊗ if h : P then g h else g' h) = if h : P then f ⊗ g h else f ⊗ g' h := by split_ifs <;> rfl theorem dite_tensor {P : Prop} [Decidable P] {W X Y Z : C} (f : W ⟶ X) (g : P → (Y ⟶ Z)) (g' : ¬P → (Y ⟶ Z)) : (if h : P then g h else g' h) ⊗ f = if h : P then g h ⊗ f else g' h ⊗ f := by split_ifs <;> rfl @[simp] theorem whiskerLeft_eqToHom (X : C) {Y Z : C} (f : Y = Z) : X ◁ eqToHom f = eqToHom (congr_arg₂ tensorObj rfl f) := by cases f simp only [whiskerLeft_id, eqToHom_refl] @[simp] theorem eqToHom_whiskerRight {X Y : C} (f : X = Y) (Z : C) : eqToHom f ▷ Z = eqToHom (congr_arg₂ tensorObj f rfl) := by cases f simp only [id_whiskerRight, eqToHom_refl] @[reassoc] theorem associator_naturality_left {X X' : C} (f : X ⟶ X') (Y Z : C) : f ▷ Y ▷ Z ≫ (α_ X' Y Z).hom = (α_ X Y Z).hom ≫ f ▷ (Y ⊗ Z) := by simp @[reassoc] theorem associator_inv_naturality_left {X X' : C} (f : X ⟶ X') (Y Z : C) : f ▷ (Y ⊗ Z) ≫ (α_ X' Y Z).inv = (α_ X Y Z).inv ≫ f ▷ Y ▷ Z := by simp @[reassoc] theorem whiskerRight_tensor_symm {X X' : C} (f : X ⟶ X') (Y Z : C) : f ▷ Y ▷ Z = (α_ X Y Z).hom ≫ f ▷ (Y ⊗ Z) ≫ (α_ X' Y Z).inv := by simp @[reassoc] theorem associator_naturality_middle (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) : (X ◁ f) ▷ Z ≫ (α_ X Y' Z).hom = (α_ X Y Z).hom ≫ X ◁ f ▷ Z := by simp @[reassoc] theorem associator_inv_naturality_middle (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) : X ◁ f ▷ Z ≫ (α_ X Y' Z).inv = (α_ X Y Z).inv ≫ (X ◁ f) ▷ Z := by simp @[reassoc] theorem whisker_assoc_symm (X : C) {Y Y' : C} (f : Y ⟶ Y') (Z : C) : X ◁ f ▷ Z = (α_ X Y Z).inv ≫ (X ◁ f) ▷ Z ≫ (α_ X Y' Z).hom := by simp @[reassoc] theorem associator_naturality_right (X Y : C) {Z Z' : C} (f : Z ⟶ Z') : (X ⊗ Y) ◁ f ≫ (α_ X Y Z').hom = (α_ X Y Z).hom ≫ X ◁ Y ◁ f := by simp @[reassoc] theorem associator_inv_naturality_right (X Y : C) {Z Z' : C} (f : Z ⟶ Z') : X ◁ Y ◁ f ≫ (α_ X Y Z').inv = (α_ X Y Z).inv ≫ (X ⊗ Y) ◁ f := by simp @[reassoc] theorem tensor_whiskerLeft_symm (X Y : C) {Z Z' : C} (f : Z ⟶ Z') : X ◁ Y ◁ f = (α_ X Y Z).inv ≫ (X ⊗ Y) ◁ f ≫ (α_ X Y Z').hom := by simp @[reassoc] theorem leftUnitor_inv_naturality {X Y : C} (f : X ⟶ Y) : f ≫ (λ_ Y).inv = (λ_ X).inv ≫ _ ◁ f := by simp @[reassoc] theorem id_whiskerLeft_symm {X X' : C} (f : X ⟶ X') : f = (λ_ X).inv ≫ 𝟙_ C ◁ f ≫ (λ_ X').hom := by simp only [id_whiskerLeft, assoc, inv_hom_id, comp_id, inv_hom_id_assoc] @[reassoc] theorem rightUnitor_inv_naturality {X X' : C} (f : X ⟶ X') : f ≫ (ρ_ X').inv = (ρ_ X).inv ≫ f ▷ _ := by simp @[reassoc] theorem whiskerRight_id_symm {X Y : C} (f : X ⟶ Y) : f = (ρ_ X).inv ≫ f ▷ 𝟙_ C ≫ (ρ_ Y).hom := by simp theorem whiskerLeft_iff {X Y : C} (f g : X ⟶ Y) : 𝟙_ C ◁ f = 𝟙_ C ◁ g ↔ f = g := by simp theorem whiskerRight_iff {X Y : C} (f g : X ⟶ Y) : f ▷ 𝟙_ C = g ▷ 𝟙_ C ↔ f = g := by simp /-! The lemmas in the next section are true by coherence, but we prove them directly as they are used in proving the coherence theorem. -/ section @[reassoc (attr := simp)] theorem pentagon_inv : W ◁ (α_ X Y Z).inv ≫ (α_ W (X ⊗ Y) Z).inv ≫ (α_ W X Y).inv ▷ Z = (α_ W X (Y ⊗ Z)).inv ≫ (α_ (W ⊗ X) Y Z).inv := eq_of_inv_eq_inv (by simp) @[reassoc (attr := simp)] theorem pentagon_inv_inv_hom_hom_inv : (α_ W (X ⊗ Y) Z).inv ≫ (α_ W X Y).inv ▷ Z ≫ (α_ (W ⊗ X) Y Z).hom = W ◁ (α_ X Y Z).hom ≫ (α_ W X (Y ⊗ Z)).inv := by rw [← cancel_epi (W ◁ (α_ X Y Z).inv), ← cancel_mono (α_ (W ⊗ X) Y Z).inv] simp @[reassoc (attr := simp)] theorem pentagon_inv_hom_hom_hom_inv : (α_ (W ⊗ X) Y Z).inv ≫ (α_ W X Y).hom ▷ Z ≫ (α_ W (X ⊗ Y) Z).hom = (α_ W X (Y ⊗ Z)).hom ≫ W ◁ (α_ X Y Z).inv := eq_of_inv_eq_inv (by simp) @[reassoc (attr := simp)] theorem pentagon_hom_inv_inv_inv_inv : W ◁ (α_ X Y Z).hom ≫ (α_ W X (Y ⊗ Z)).inv ≫ (α_ (W ⊗ X) Y Z).inv = (α_ W (X ⊗ Y) Z).inv ≫ (α_ W X Y).inv ▷ Z := by simp [← cancel_epi (W ◁ (α_ X Y Z).inv)]
@[reassoc (attr := simp)] theorem pentagon_hom_hom_inv_hom_hom : (α_ (W ⊗ X) Y Z).hom ≫ (α_ W X (Y ⊗ Z)).hom ≫ W ◁ (α_ X Y Z).inv = (α_ W X Y).hom ▷ Z ≫ (α_ W (X ⊗ Y) Z).hom :=
Mathlib/CategoryTheory/Monoidal/Category.lean
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/- Copyright (c) 2021 Anne Baanen. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Anne Baanen -/ import Mathlib.Algebra.Polynomial.Degree.CardPowDegree import Mathlib.Analysis.SpecialFunctions.Pow.Real import Mathlib.NumberTheory.ClassNumber.AdmissibleAbsoluteValue import Mathlib.RingTheory.LocalRing.Basic /-! # Admissible absolute values on polynomials This file defines an admissible absolute value `Polynomial.cardPowDegreeIsAdmissible` which we use to show the class number of the ring of integers of a function field is finite. ## Main results * `Polynomial.cardPowDegreeIsAdmissible` shows `cardPowDegree`, mapping `p : Polynomial 𝔽_q` to `q ^ degree p`, is admissible -/ namespace Polynomial open AbsoluteValue Real variable {Fq : Type*} [Fintype Fq] /-- If `A` is a family of enough low-degree polynomials over a finite semiring, there is a pair of equal elements in `A`. -/ theorem exists_eq_polynomial [Semiring Fq] {d : ℕ} {m : ℕ} (hm : Fintype.card Fq ^ d ≤ m) (b : Fq[X]) (hb : natDegree b ≤ d) (A : Fin m.succ → Fq[X]) (hA : ∀ i, degree (A i) < degree b) : ∃ i₀ i₁, i₀ ≠ i₁ ∧ A i₁ = A i₀ := by -- Since there are > q^d elements of A, and only q^d choices for the highest `d` coefficients, -- there must be two elements of A with the same coefficients at -- `0`, ... `degree b - 1` ≤ `d - 1`. -- In other words, the following map is not injective: set f : Fin m.succ → Fin d → Fq := fun i j => (A i).coeff j have : Fintype.card (Fin d → Fq) < Fintype.card (Fin m.succ) := by simpa using lt_of_le_of_lt hm (Nat.lt_succ_self m) -- Therefore, the differences have all coefficients higher than `deg b - d` equal. obtain ⟨i₀, i₁, i_ne, i_eq⟩ := Fintype.exists_ne_map_eq_of_card_lt f this use i₀, i₁, i_ne ext j -- The coefficients higher than `deg b` are the same because they are equal to 0. by_cases hbj : degree b ≤ j · rw [coeff_eq_zero_of_degree_lt (lt_of_lt_of_le (hA _) hbj), coeff_eq_zero_of_degree_lt (lt_of_lt_of_le (hA _) hbj)] -- So we only need to look for the coefficients between `0` and `deg b`. rw [not_le] at hbj apply congr_fun i_eq.symm ⟨j, _⟩ exact lt_of_lt_of_le (coe_lt_degree.mp hbj) hb /-- If `A` is a family of enough low-degree polynomials over a finite ring, there is a pair of elements in `A` (with different indices but not necessarily distinct), such that their difference has small degree. -/ theorem exists_approx_polynomial_aux [Ring Fq] {d : ℕ} {m : ℕ} (hm : Fintype.card Fq ^ d ≤ m) (b : Fq[X]) (A : Fin m.succ → Fq[X]) (hA : ∀ i, degree (A i) < degree b) : ∃ i₀ i₁, i₀ ≠ i₁ ∧ degree (A i₁ - A i₀) < ↑(natDegree b - d) := by have hb : b ≠ 0 := by rintro rfl
specialize hA 0 rw [degree_zero] at hA exact not_lt_of_le bot_le hA -- Since there are > q^d elements of A, and only q^d choices for the highest `d` coefficients, -- there must be two elements of A with the same coefficients at -- `degree b - 1`, ... `degree b - d`. -- In other words, the following map is not injective: set f : Fin m.succ → Fin d → Fq := fun i j => (A i).coeff (natDegree b - j.succ) have : Fintype.card (Fin d → Fq) < Fintype.card (Fin m.succ) := by simpa using lt_of_le_of_lt hm (Nat.lt_succ_self m) -- Therefore, the differences have all coefficients higher than `deg b - d` equal. obtain ⟨i₀, i₁, i_ne, i_eq⟩ := Fintype.exists_ne_map_eq_of_card_lt f this use i₀, i₁, i_ne refine (degree_lt_iff_coeff_zero _ _).mpr fun j hj => ?_ -- The coefficients higher than `deg b` are the same because they are equal to 0. by_cases hbj : degree b ≤ j · refine coeff_eq_zero_of_degree_lt (lt_of_lt_of_le ?_ hbj) exact lt_of_le_of_lt (degree_sub_le _ _) (max_lt (hA _) (hA _)) -- So we only need to look for the coefficients between `deg b - d` and `deg b`. rw [coeff_sub, sub_eq_zero] rw [not_le, degree_eq_natDegree hb] at hbj have hbj : j < natDegree b := (@WithBot.coe_lt_coe _ _ _).mp hbj have hj : natDegree b - j.succ < d := by by_cases hd : natDegree b < d · exact lt_of_le_of_lt tsub_le_self hd · rw [not_lt] at hd have := lt_of_le_of_lt hj (Nat.lt_succ_self j) rwa [tsub_lt_iff_tsub_lt hd hbj] at this have : j = b.natDegree - (natDegree b - j.succ).succ := by rw [← Nat.succ_sub hbj, Nat.succ_sub_succ, tsub_tsub_cancel_of_le hbj.le] convert congr_fun i_eq.symm ⟨natDegree b - j.succ, hj⟩ variable [Field Fq] /-- If `A` is a family of enough low-degree polynomials over a finite field, there is a pair of elements in `A` (with different indices but not necessarily
Mathlib/NumberTheory/ClassNumber/AdmissibleCardPowDegree.lean
63
98
/- Copyright (c) 2022 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Tactic.NormNum.Basic import Mathlib.Data.Rat.Cast.CharZero import Mathlib.Algebra.Field.Basic /-! # `norm_num` plugins for `Rat.cast` and `⁻¹`. -/ variable {u : Lean.Level} namespace Mathlib.Meta.NormNum open Lean.Meta Qq /-- Helper function to synthesize a typed `CharZero α` expression given `Ring α`. -/ def inferCharZeroOfRing {α : Q(Type u)} (_i : Q(Ring $α) := by with_reducible assumption) : MetaM Q(CharZero $α) := return ← synthInstanceQ q(CharZero $α) <|> throwError "not a characteristic zero ring" /-- Helper function to synthesize a typed `CharZero α` expression given `Ring α`, if it exists. -/ def inferCharZeroOfRing? {α : Q(Type u)} (_i : Q(Ring $α) := by with_reducible assumption) : MetaM (Option Q(CharZero $α)) := return (← trySynthInstanceQ q(CharZero $α)).toOption /-- Helper function to synthesize a typed `CharZero α` expression given `AddMonoidWithOne α`. -/ def inferCharZeroOfAddMonoidWithOne {α : Q(Type u)} (_i : Q(AddMonoidWithOne $α) := by with_reducible assumption) : MetaM Q(CharZero $α) := return ← synthInstanceQ q(CharZero $α) <|> throwError "not a characteristic zero AddMonoidWithOne" /-- Helper function to synthesize a typed `CharZero α` expression given `AddMonoidWithOne α`, if it exists. -/ def inferCharZeroOfAddMonoidWithOne? {α : Q(Type u)} (_i : Q(AddMonoidWithOne $α) := by with_reducible assumption) : MetaM (Option Q(CharZero $α)) := return (← trySynthInstanceQ q(CharZero $α)).toOption /-- Helper function to synthesize a typed `CharZero α` expression given `DivisionRing α`. -/ def inferCharZeroOfDivisionRing {α : Q(Type u)} (_i : Q(DivisionRing $α) := by with_reducible assumption) : MetaM Q(CharZero $α) := return ← synthInstanceQ q(CharZero $α) <|> throwError "not a characteristic zero division ring" /-- Helper function to synthesize a typed `CharZero α` expression given `DivisionRing α`, if it exists. -/ def inferCharZeroOfDivisionRing? {α : Q(Type u)} (_i : Q(DivisionRing $α) := by with_reducible assumption) : MetaM (Option Q(CharZero $α)) := return (← trySynthInstanceQ q(CharZero $α)).toOption theorem isRat_mkRat : {a na n : ℤ} → {b nb d : ℕ} → IsInt a na → IsNat b nb → IsRat (na / nb : ℚ) n d → IsRat (mkRat a b) n d | _, _, _, _, _, _, ⟨rfl⟩, ⟨rfl⟩, ⟨_, h⟩ => by rw [Rat.mkRat_eq_div]; exact ⟨_, h⟩ attribute [local instance] monadLiftOptionMetaM in /-- The `norm_num` extension which identifies expressions of the form `mkRat a b`, such that `norm_num` successfully recognises both `a` and `b`, and returns `a / b`. -/ @[norm_num mkRat _ _] def evalMkRat : NormNumExt where eval {u α} (e : Q(ℚ)) : MetaM (Result e) := do let .app (.app (.const ``mkRat _) (a : Q(ℤ))) (b : Q(ℕ)) ← whnfR e | failure haveI' : $e =Q mkRat $a $b := ⟨⟩ let ra ← derive a let some ⟨_, na, pa⟩ := ra.toInt (q(Int.instRing) : Q(Ring Int)) | failure let ⟨nb, pb⟩ ← deriveNat q($b) q(AddCommMonoidWithOne.toAddMonoidWithOne) let rab ← derive q($na / $nb : Rat) let ⟨q, n, d, p⟩ ← rab.toRat' q(Rat.instDivisionRing) return .isRat' _ q n d q(isRat_mkRat $pa $pb $p) theorem isNat_ratCast {R : Type*} [DivisionRing R] : {q : ℚ} → {n : ℕ} → IsNat q n → IsNat (q : R) n | _, _, ⟨rfl⟩ => ⟨by simp⟩
theorem isInt_ratCast {R : Type*} [DivisionRing R] : {q : ℚ} → {n : ℤ} → IsInt q n → IsInt (q : R) n
Mathlib/Tactic/NormNum/Inv.lean
77
79
/- Copyright (c) 2014 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Algebra.Divisibility.Hom import Mathlib.Algebra.Group.Even import Mathlib.Algebra.Group.Nat.Hom import Mathlib.Algebra.Ring.Hom.Defs import Mathlib.Algebra.Ring.Nat /-! # Cast of natural numbers (additional theorems) This file proves additional properties about the *canonical* homomorphism from the natural numbers into an additive monoid with a one (`Nat.cast`). ## Main declarations * `castAddMonoidHom`: `cast` bundled as an `AddMonoidHom`. * `castRingHom`: `cast` bundled as a `RingHom`. -/ assert_not_exists OrderedCommGroup Commute.zero_right Commute.add_right abs_eq_max_neg NeZero.natCast_ne -- TODO: `MulOpposite.op_natCast` was not intended to be imported -- assert_not_exists MulOpposite.op_natCast open Additive Multiplicative variable {α β : Type*} namespace Nat /-- `Nat.cast : ℕ → α` as an `AddMonoidHom`. -/ def castAddMonoidHom (α : Type*) [AddMonoidWithOne α] : ℕ →+ α where toFun := Nat.cast map_add' := cast_add map_zero' := cast_zero @[simp] theorem coe_castAddMonoidHom [AddMonoidWithOne α] : (castAddMonoidHom α : ℕ → α) = Nat.cast := rfl lemma _root_.Even.natCast [AddMonoidWithOne α] {n : ℕ} (hn : Even n) : Even (n : α) := hn.map <| Nat.castAddMonoidHom α section NonAssocSemiring variable [NonAssocSemiring α] @[simp, norm_cast] lemma cast_mul (m n : ℕ) : ((m * n : ℕ) : α) = m * n := by induction n <;> simp [mul_succ, mul_add, *] variable (α) in /-- `Nat.cast : ℕ → α` as a `RingHom` -/ def castRingHom : ℕ →+* α := { castAddMonoidHom α with toFun := Nat.cast, map_one' := cast_one, map_mul' := cast_mul } @[simp, norm_cast] lemma coe_castRingHom : (castRingHom α : ℕ → α) = Nat.cast := rfl lemma _root_.nsmul_eq_mul' (a : α) (n : ℕ) : n • a = a * n := by induction n with | zero => rw [zero_nsmul, Nat.cast_zero, mul_zero] | succ n ih => rw [succ_nsmul, ih, Nat.cast_succ, mul_add, mul_one] @[simp] lemma _root_.nsmul_eq_mul (n : ℕ) (a : α) : n • a = n * a := by induction n with | zero => rw [zero_nsmul, Nat.cast_zero, zero_mul] | succ n ih => rw [succ_nsmul, ih, Nat.cast_succ, add_mul, one_mul] end NonAssocSemiring section Semiring variable [Semiring α] {m n : ℕ} @[simp, norm_cast] lemma cast_pow (m : ℕ) : ∀ n : ℕ, ↑(m ^ n) = (m ^ n : α) | 0 => by simp | n + 1 => by rw [_root_.pow_succ', _root_.pow_succ', cast_mul, cast_pow m n] lemma cast_dvd_cast (h : m ∣ n) : (m : α) ∣ (n : α) := map_dvd (Nat.castRingHom α) h alias _root_.Dvd.dvd.natCast := cast_dvd_cast end Semiring end Nat section AddMonoidHomClass variable {A B F : Type*} [AddMonoidWithOne B] [FunLike F ℕ A] [AddMonoidWithOne A] -- these versions are primed so that the `RingHomClass` versions aren't theorem eq_natCast' [AddMonoidHomClass F ℕ A] (f : F) (h1 : f 1 = 1) : ∀ n : ℕ, f n = n | 0 => by simp | n + 1 => by rw [map_add, h1, eq_natCast' f h1 n, Nat.cast_add_one] theorem map_natCast' {A} [AddMonoidWithOne A] [FunLike F A B] [AddMonoidHomClass F A B] (f : F) (h : f 1 = 1) : ∀ n : ℕ, f n = n := eq_natCast' ((f : A →+ B).comp <| Nat.castAddMonoidHom _) (by simpa) theorem map_ofNat' {A} [AddMonoidWithOne A] [FunLike F A B] [AddMonoidHomClass F A B] (f : F) (h : f 1 = 1) (n : ℕ) [n.AtLeastTwo] : f (OfNat.ofNat n) = OfNat.ofNat n := map_natCast' f h n end AddMonoidHomClass section MonoidWithZeroHomClass variable {A F : Type*} [MulZeroOneClass A] [FunLike F ℕ A] /-- If two `MonoidWithZeroHom`s agree on the positive naturals they are equal. -/ theorem ext_nat'' [ZeroHomClass F ℕ A] (f g : F) (h_pos : ∀ {n : ℕ}, 0 < n → f n = g n) : f = g := by apply DFunLike.ext rintro (_ | n) · simp · exact h_pos n.succ_pos @[ext] theorem MonoidWithZeroHom.ext_nat {f g : ℕ →*₀ A} : (∀ {n : ℕ}, 0 < n → f n = g n) → f = g := ext_nat'' f g end MonoidWithZeroHomClass section RingHomClass variable {R S F : Type*} [NonAssocSemiring R] [NonAssocSemiring S] @[simp] theorem eq_natCast [FunLike F ℕ R] [RingHomClass F ℕ R] (f : F) : ∀ n, f n = n := eq_natCast' f <| map_one f @[simp] theorem map_natCast [FunLike F R S] [RingHomClass F R S] (f : F) : ∀ n : ℕ, f (n : R) = n := map_natCast' f <| map_one f /-- This lemma is not marked `@[simp]` lemma because its `#discr_tree_key` (for the LHS) would just be `DFunLike.coe _ _`, due to the `ofNat` that https://github.com/leanprover/lean4/issues/2867 forces us to include, and therefore it would negatively impact performance. If that issue is resolved, this can be marked `@[simp]`. -/ theorem map_ofNat [FunLike F R S] [RingHomClass F R S] (f : F) (n : ℕ) [Nat.AtLeastTwo n] : (f ofNat(n) : S) = OfNat.ofNat n := map_natCast f n theorem ext_nat [FunLike F ℕ R] [RingHomClass F ℕ R] (f g : F) : f = g := ext_nat' f g <| by simp theorem NeZero.nat_of_neZero {R S} [NonAssocSemiring R] [NonAssocSemiring S] {F} [FunLike F R S] [RingHomClass F R S] (f : F) {n : ℕ} [hn : NeZero (n : S)] : NeZero (n : R) := .of_map (f := f) (neZero := by simp only [map_natCast, hn]) end RingHomClass namespace RingHom
/-- This is primed to match `eq_intCast'`. -/ theorem eq_natCast' {R} [NonAssocSemiring R] (f : ℕ →+* R) : f = Nat.castRingHom R := RingHom.ext <| eq_natCast f end RingHom
Mathlib/Data/Nat/Cast/Basic.lean
159
164
/- Copyright (c) 2022 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov, Heather Macbeth -/ import Mathlib.MeasureTheory.Function.L1Space.AEEqFun import Mathlib.MeasureTheory.Function.LpSpace.Complete import Mathlib.MeasureTheory.Function.LpSpace.Indicator /-! # Density of simple functions Show that each `Lᵖ` Borel measurable function can be approximated in `Lᵖ` norm by a sequence of simple functions. ## Main definitions * `MeasureTheory.Lp.simpleFunc`, the type of `Lp` simple functions * `coeToLp`, the embedding of `Lp.simpleFunc E p μ` into `Lp E p μ` ## Main results * `tendsto_approxOn_Lp_eLpNorm` (Lᵖ convergence): If `E` is a `NormedAddCommGroup` and `f` is measurable and `MemLp` (for `p < ∞`), then the simple functions `SimpleFunc.approxOn f hf s 0 h₀ n` may be considered as elements of `Lp E p μ`, and they tend in Lᵖ to `f`. * `Lp.simpleFunc.isDenseEmbedding`: the embedding `coeToLp` of the `Lp` simple functions into `Lp` is dense. * `Lp.simpleFunc.induction`, `Lp.induction`, `MemLp.induction`, `Integrable.induction`: to prove a predicate for all elements of one of these classes of functions, it suffices to check that it behaves correctly on simple functions. ## TODO For `E` finite-dimensional, simple functions `α →ₛ E` are dense in L^∞ -- prove this. ## Notations * `α →ₛ β` (local notation): the type of simple functions `α → β`. * `α →₁ₛ[μ] E`: the type of `L1` simple functions `α → β`. -/ noncomputable section open Set Function Filter TopologicalSpace ENNReal EMetric Finset open scoped Topology ENNReal MeasureTheory variable {α β ι E F 𝕜 : Type*} namespace MeasureTheory local infixr:25 " →ₛ " => SimpleFunc namespace SimpleFunc /-! ### Lp approximation by simple functions -/ section Lp variable [MeasurableSpace β] [MeasurableSpace E] [NormedAddCommGroup E] [NormedAddCommGroup F] {q : ℝ} {p : ℝ≥0∞} theorem nnnorm_approxOn_le [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (x : β) (n : ℕ) : ‖approxOn f hf s y₀ h₀ n x - f x‖₊ ≤ ‖f x - y₀‖₊ := by have := edist_approxOn_le hf h₀ x n rw [edist_comm y₀] at this simp only [edist_nndist, nndist_eq_nnnorm] at this exact mod_cast this theorem norm_approxOn_y₀_le [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (x : β) (n : ℕ) : ‖approxOn f hf s y₀ h₀ n x - y₀‖ ≤ ‖f x - y₀‖ + ‖f x - y₀‖ := by simpa [enorm, edist_eq_enorm_sub, ← ENNReal.coe_add, norm_sub_rev] using edist_approxOn_y0_le hf h₀ x n theorem norm_approxOn_zero_le [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} (h₀ : (0 : E) ∈ s) [SeparableSpace s] (x : β) (n : ℕ) : ‖approxOn f hf s 0 h₀ n x‖ ≤ ‖f x‖ + ‖f x‖ := by simpa [enorm, edist_eq_enorm_sub, ← ENNReal.coe_add, norm_sub_rev] using edist_approxOn_y0_le hf h₀ x n theorem tendsto_approxOn_Lp_eLpNorm [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (hp_ne_top : p ≠ ∞) {μ : Measure β} (hμ : ∀ᵐ x ∂μ, f x ∈ closure s) (hi : eLpNorm (fun x => f x - y₀) p μ < ∞) : Tendsto (fun n => eLpNorm (⇑(approxOn f hf s y₀ h₀ n) - f) p μ) atTop (𝓝 0) := by by_cases hp_zero : p = 0 · simpa only [hp_zero, eLpNorm_exponent_zero] using tendsto_const_nhds have hp : 0 < p.toReal := toReal_pos hp_zero hp_ne_top suffices Tendsto (fun n => ∫⁻ x, ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ^ p.toReal ∂μ) atTop (𝓝 0) by simp only [eLpNorm_eq_lintegral_rpow_enorm hp_zero hp_ne_top] convert continuous_rpow_const.continuousAt.tendsto.comp this simp [zero_rpow_of_pos (_root_.inv_pos.mpr hp)] -- We simply check the conditions of the Dominated Convergence Theorem: -- (1) The function "`p`-th power of distance between `f` and the approximation" is measurable have hF_meas n : Measurable fun x => ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ^ p.toReal := by simpa only [← edist_eq_enorm_sub] using (approxOn f hf s y₀ h₀ n).measurable_bind (fun y x => edist y (f x) ^ p.toReal) fun y => (measurable_edist_right.comp hf).pow_const p.toReal -- (2) The functions "`p`-th power of distance between `f` and the approximation" are uniformly -- bounded, at any given point, by `fun x => ‖f x - y₀‖ ^ p.toReal` have h_bound n : (fun x ↦ ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ^ p.toReal) ≤ᵐ[μ] (‖f · - y₀‖ₑ ^ p.toReal) := .of_forall fun x => rpow_le_rpow (coe_mono (nnnorm_approxOn_le hf h₀ x n)) toReal_nonneg -- (3) The bounding function `fun x => ‖f x - y₀‖ ^ p.toReal` has finite integral have h_fin : (∫⁻ a : β, ‖f a - y₀‖ₑ ^ p.toReal ∂μ) ≠ ⊤ := (lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top hp_zero hp_ne_top hi).ne -- (4) The functions "`p`-th power of distance between `f` and the approximation" tend pointwise -- to zero have h_lim : ∀ᵐ a : β ∂μ, Tendsto (‖approxOn f hf s y₀ h₀ · a - f a‖ₑ ^ p.toReal) atTop (𝓝 0) := by filter_upwards [hμ] with a ha have : Tendsto (fun n => (approxOn f hf s y₀ h₀ n) a - f a) atTop (𝓝 (f a - f a)) := (tendsto_approxOn hf h₀ ha).sub tendsto_const_nhds convert continuous_rpow_const.continuousAt.tendsto.comp (tendsto_coe.mpr this.nnnorm) simp [zero_rpow_of_pos hp] -- Then we apply the Dominated Convergence Theorem simpa using tendsto_lintegral_of_dominated_convergence _ hF_meas h_bound h_fin h_lim theorem memLp_approxOn [BorelSpace E] {f : β → E} {μ : Measure β} (fmeas : Measurable f) (hf : MemLp f p μ) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (hi₀ : MemLp (fun _ => y₀) p μ) (n : ℕ) : MemLp (approxOn f fmeas s y₀ h₀ n) p μ := by refine ⟨(approxOn f fmeas s y₀ h₀ n).aestronglyMeasurable, ?_⟩ suffices eLpNorm (fun x => approxOn f fmeas s y₀ h₀ n x - y₀) p μ < ⊤ by have : MemLp (fun x => approxOn f fmeas s y₀ h₀ n x - y₀) p μ := ⟨(approxOn f fmeas s y₀ h₀ n - const β y₀).aestronglyMeasurable, this⟩ convert eLpNorm_add_lt_top this hi₀ ext x simp have hf' : MemLp (fun x => ‖f x - y₀‖) p μ := by have h_meas : Measurable fun x => ‖f x - y₀‖ := by simp only [← dist_eq_norm] exact (continuous_id.dist continuous_const).measurable.comp fmeas refine ⟨h_meas.aemeasurable.aestronglyMeasurable, ?_⟩ rw [eLpNorm_norm] convert eLpNorm_add_lt_top hf hi₀.neg with x simp [sub_eq_add_neg] have : ∀ᵐ x ∂μ, ‖approxOn f fmeas s y₀ h₀ n x - y₀‖ ≤ ‖‖f x - y₀‖ + ‖f x - y₀‖‖ := by filter_upwards with x convert norm_approxOn_y₀_le fmeas h₀ x n using 1 rw [Real.norm_eq_abs, abs_of_nonneg] positivity calc eLpNorm (fun x => approxOn f fmeas s y₀ h₀ n x - y₀) p μ ≤ eLpNorm (fun x => ‖f x - y₀‖ + ‖f x - y₀‖) p μ := eLpNorm_mono_ae this _ < ⊤ := eLpNorm_add_lt_top hf' hf' theorem tendsto_approxOn_range_Lp_eLpNorm [BorelSpace E] {f : β → E} (hp_ne_top : p ≠ ∞) {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : eLpNorm f p μ < ∞) : Tendsto (fun n => eLpNorm (⇑(approxOn f fmeas (range f ∪ {0}) 0 (by simp) n) - f) p μ) atTop (𝓝 0) := by refine tendsto_approxOn_Lp_eLpNorm fmeas _ hp_ne_top ?_ ?_ · filter_upwards with x using subset_closure (by simp) · simpa using hf theorem memLp_approxOn_range [BorelSpace E] {f : β → E} {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : MemLp f p μ) (n : ℕ) : MemLp (approxOn f fmeas (range f ∪ {0}) 0 (by simp) n) p μ := memLp_approxOn fmeas hf (y₀ := 0) (by simp) MemLp.zero n theorem tendsto_approxOn_range_Lp [BorelSpace E] {f : β → E} [hp : Fact (1 ≤ p)] (hp_ne_top : p ≠ ∞) {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : MemLp f p μ) : Tendsto (fun n => (memLp_approxOn_range fmeas hf n).toLp (approxOn f fmeas (range f ∪ {0}) 0 (by simp) n)) atTop (𝓝 (hf.toLp f)) := by simpa only [Lp.tendsto_Lp_iff_tendsto_eLpNorm''] using tendsto_approxOn_range_Lp_eLpNorm hp_ne_top fmeas hf.2 /-- Any function in `ℒp` can be approximated by a simple function if `p < ∞`. -/ theorem _root_.MeasureTheory.MemLp.exists_simpleFunc_eLpNorm_sub_lt {E : Type*} [NormedAddCommGroup E] {f : β → E} {μ : Measure β} (hf : MemLp f p μ) (hp_ne_top : p ≠ ∞) {ε : ℝ≥0∞} (hε : ε ≠ 0) : ∃ g : β →ₛ E, eLpNorm (f - ⇑g) p μ < ε ∧ MemLp g p μ := by borelize E let f' := hf.1.mk f rsuffices ⟨g, hg, g_mem⟩ : ∃ g : β →ₛ E, eLpNorm (f' - ⇑g) p μ < ε ∧ MemLp g p μ · refine ⟨g, ?_, g_mem⟩ suffices eLpNorm (f - ⇑g) p μ = eLpNorm (f' - ⇑g) p μ by rwa [this] apply eLpNorm_congr_ae filter_upwards [hf.1.ae_eq_mk] with x hx simpa only [Pi.sub_apply, sub_left_inj] using hx have hf' : MemLp f' p μ := hf.ae_eq hf.1.ae_eq_mk have f'meas : Measurable f' := hf.1.measurable_mk have : SeparableSpace (range f' ∪ {0} : Set E) := StronglyMeasurable.separableSpace_range_union_singleton hf.1.stronglyMeasurable_mk rcases ((tendsto_approxOn_range_Lp_eLpNorm hp_ne_top f'meas hf'.2).eventually <| gt_mem_nhds hε.bot_lt).exists with ⟨n, hn⟩ rw [← eLpNorm_neg, neg_sub] at hn exact ⟨_, hn, memLp_approxOn_range f'meas hf' _⟩ end Lp /-! ### L1 approximation by simple functions -/ section Integrable variable [MeasurableSpace β] variable [MeasurableSpace E] [NormedAddCommGroup E] theorem tendsto_approxOn_L1_enorm [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] {μ : Measure β} (hμ : ∀ᵐ x ∂μ, f x ∈ closure s) (hi : HasFiniteIntegral (fun x => f x - y₀) μ) : Tendsto (fun n => ∫⁻ x, ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ∂μ) atTop (𝓝 0) := by simpa [eLpNorm_one_eq_lintegral_enorm] using tendsto_approxOn_Lp_eLpNorm hf h₀ one_ne_top hμ (by simpa [eLpNorm_one_eq_lintegral_enorm] using hi) @[deprecated (since := "2025-01-21")] alias tendsto_approxOn_L1_nnnorm := tendsto_approxOn_L1_enorm theorem integrable_approxOn [BorelSpace E] {f : β → E} {μ : Measure β} (fmeas : Measurable f) (hf : Integrable f μ) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (hi₀ : Integrable (fun _ => y₀) μ) (n : ℕ) : Integrable (approxOn f fmeas s y₀ h₀ n) μ := by rw [← memLp_one_iff_integrable] at hf hi₀ ⊢ exact memLp_approxOn fmeas hf h₀ hi₀ n theorem tendsto_approxOn_range_L1_enorm [OpensMeasurableSpace E] {f : β → E} {μ : Measure β} [SeparableSpace (range f ∪ {0} : Set E)] (fmeas : Measurable f) (hf : Integrable f μ) : Tendsto (fun n => ∫⁻ x, ‖approxOn f fmeas (range f ∪ {0}) 0 (by simp) n x - f x‖ₑ ∂μ) atTop (𝓝 0) := by apply tendsto_approxOn_L1_enorm fmeas · filter_upwards with x using subset_closure (by simp) · simpa using hf.2 @[deprecated (since := "2025-01-21")] alias tendsto_approxOn_range_L1_nnnorm := tendsto_approxOn_range_L1_enorm theorem integrable_approxOn_range [BorelSpace E] {f : β → E} {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : Integrable f μ) (n : ℕ) : Integrable (approxOn f fmeas (range f ∪ {0}) 0 (by simp) n) μ := integrable_approxOn fmeas hf _ (integrable_zero _ _ _) n end Integrable section SimpleFuncProperties variable [MeasurableSpace α] variable [NormedAddCommGroup E] [NormedAddCommGroup F] variable {μ : Measure α} {p : ℝ≥0∞} /-! ### Properties of simple functions in `Lp` spaces A simple function `f : α →ₛ E` into a normed group `E` verifies, for a measure `μ`: - `MemLp f 0 μ` and `MemLp f ∞ μ`, since `f` is a.e.-measurable and bounded, - for `0 < p < ∞`, `MemLp f p μ ↔ Integrable f μ ↔ f.FinMeasSupp μ ↔ ∀ y, y ≠ 0 → μ (f ⁻¹' {y}) < ∞`. -/ theorem exists_forall_norm_le (f : α →ₛ F) : ∃ C, ∀ x, ‖f x‖ ≤ C := exists_forall_le (f.map fun x => ‖x‖) theorem memLp_zero (f : α →ₛ E) (μ : Measure α) : MemLp f 0 μ := memLp_zero_iff_aestronglyMeasurable.mpr f.aestronglyMeasurable theorem memLp_top (f : α →ₛ E) (μ : Measure α) : MemLp f ∞ μ := let ⟨C, hfC⟩ := f.exists_forall_norm_le memLp_top_of_bound f.aestronglyMeasurable C <| Eventually.of_forall hfC protected theorem eLpNorm'_eq {p : ℝ} (f : α →ₛ F) (μ : Measure α) : eLpNorm' f p μ = (∑ y ∈ f.range, ‖y‖ₑ ^ p * μ (f ⁻¹' {y})) ^ (1 / p) := by have h_map : (‖f ·‖ₑ ^ p) = f.map (‖·‖ₑ ^ p) := by simp; rfl rw [eLpNorm'_eq_lintegral_enorm, h_map, lintegral_eq_lintegral, map_lintegral] theorem measure_preimage_lt_top_of_memLp (hp_pos : p ≠ 0) (hp_ne_top : p ≠ ∞) (f : α →ₛ E) (hf : MemLp f p μ) (y : E) (hy_ne : y ≠ 0) : μ (f ⁻¹' {y}) < ∞ := by have hp_pos_real : 0 < p.toReal := ENNReal.toReal_pos hp_pos hp_ne_top have hf_eLpNorm := MemLp.eLpNorm_lt_top hf rw [eLpNorm_eq_eLpNorm' hp_pos hp_ne_top, f.eLpNorm'_eq, one_div, ← @ENNReal.lt_rpow_inv_iff _ _ p.toReal⁻¹ (by simp [hp_pos_real]), @ENNReal.top_rpow_of_pos p.toReal⁻¹⁻¹ (by simp [hp_pos_real]), ENNReal.sum_lt_top] at hf_eLpNorm by_cases hyf : y ∈ f.range swap · suffices h_empty : f ⁻¹' {y} = ∅ by rw [h_empty, measure_empty]; exact ENNReal.coe_lt_top ext1 x rw [Set.mem_preimage, Set.mem_singleton_iff, mem_empty_iff_false, iff_false] refine fun hxy => hyf ?_ rw [mem_range, Set.mem_range] exact ⟨x, hxy⟩ specialize hf_eLpNorm y hyf rw [ENNReal.mul_lt_top_iff] at hf_eLpNorm cases hf_eLpNorm with | inl hf_eLpNorm => exact hf_eLpNorm.2 | inr hf_eLpNorm => cases hf_eLpNorm with | inl hf_eLpNorm => refine absurd ?_ hy_ne simpa [hp_pos_real] using hf_eLpNorm | inr hf_eLpNorm => simp [hf_eLpNorm] theorem memLp_of_finite_measure_preimage (p : ℝ≥0∞) {f : α →ₛ E} (hf : ∀ y, y ≠ 0 → μ (f ⁻¹' {y}) < ∞) : MemLp f p μ := by by_cases hp0 : p = 0 · rw [hp0, memLp_zero_iff_aestronglyMeasurable]; exact f.aestronglyMeasurable by_cases hp_top : p = ∞ · rw [hp_top]; exact memLp_top f μ refine ⟨f.aestronglyMeasurable, ?_⟩ rw [eLpNorm_eq_eLpNorm' hp0 hp_top, f.eLpNorm'_eq] refine ENNReal.rpow_lt_top_of_nonneg (by simp) (ENNReal.sum_lt_top.mpr fun y _ => ?_).ne by_cases hy0 : y = 0 · simp [hy0, ENNReal.toReal_pos hp0 hp_top] · refine ENNReal.mul_lt_top ?_ (hf y hy0) exact ENNReal.rpow_lt_top_of_nonneg ENNReal.toReal_nonneg ENNReal.coe_ne_top theorem memLp_iff {f : α →ₛ E} (hp_pos : p ≠ 0) (hp_ne_top : p ≠ ∞) : MemLp f p μ ↔ ∀ y, y ≠ 0 → μ (f ⁻¹' {y}) < ∞ := ⟨fun h => measure_preimage_lt_top_of_memLp hp_pos hp_ne_top f h, fun h => memLp_of_finite_measure_preimage p h⟩ theorem integrable_iff {f : α →ₛ E} : Integrable f μ ↔ ∀ y, y ≠ 0 → μ (f ⁻¹' {y}) < ∞ := memLp_one_iff_integrable.symm.trans <| memLp_iff one_ne_zero ENNReal.coe_ne_top theorem memLp_iff_integrable {f : α →ₛ E} (hp_pos : p ≠ 0) (hp_ne_top : p ≠ ∞) : MemLp f p μ ↔ Integrable f μ := (memLp_iff hp_pos hp_ne_top).trans integrable_iff.symm theorem memLp_iff_finMeasSupp {f : α →ₛ E} (hp_pos : p ≠ 0) (hp_ne_top : p ≠ ∞) : MemLp f p μ ↔ f.FinMeasSupp μ := (memLp_iff hp_pos hp_ne_top).trans finMeasSupp_iff.symm theorem integrable_iff_finMeasSupp {f : α →ₛ E} : Integrable f μ ↔ f.FinMeasSupp μ := integrable_iff.trans finMeasSupp_iff.symm theorem FinMeasSupp.integrable {f : α →ₛ E} (h : f.FinMeasSupp μ) : Integrable f μ := integrable_iff_finMeasSupp.2 h theorem integrable_pair {f : α →ₛ E} {g : α →ₛ F} : Integrable f μ → Integrable g μ → Integrable (pair f g) μ := by simpa only [integrable_iff_finMeasSupp] using FinMeasSupp.pair theorem memLp_of_isFiniteMeasure (f : α →ₛ E) (p : ℝ≥0∞) (μ : Measure α) [IsFiniteMeasure μ] : MemLp f p μ := let ⟨C, hfC⟩ := f.exists_forall_norm_le MemLp.of_bound f.aestronglyMeasurable C <| Eventually.of_forall hfC @[fun_prop] theorem integrable_of_isFiniteMeasure [IsFiniteMeasure μ] (f : α →ₛ E) : Integrable f μ := memLp_one_iff_integrable.mp (f.memLp_of_isFiniteMeasure 1 μ) theorem measure_preimage_lt_top_of_integrable (f : α →ₛ E) (hf : Integrable f μ) {x : E} (hx : x ≠ 0) : μ (f ⁻¹' {x}) < ∞ := integrable_iff.mp hf x hx theorem measure_support_lt_top_of_memLp (f : α →ₛ E) (hf : MemLp f p μ) (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞) : μ (support f) < ∞ := f.measure_support_lt_top ((memLp_iff hp_ne_zero hp_ne_top).mp hf) theorem measure_support_lt_top_of_integrable (f : α →ₛ E) (hf : Integrable f μ) : μ (support f) < ∞ := f.measure_support_lt_top (integrable_iff.mp hf) theorem measure_lt_top_of_memLp_indicator (hp_pos : p ≠ 0) (hp_ne_top : p ≠ ∞) {c : E} (hc : c ≠ 0) {s : Set α} (hs : MeasurableSet s) (hcs : MemLp ((const α c).piecewise s hs (const α 0)) p μ) : μ s < ⊤ := by have : Function.support (const α c) = Set.univ := Function.support_const hc simpa only [memLp_iff_finMeasSupp hp_pos hp_ne_top, finMeasSupp_iff_support, support_indicator, Set.inter_univ, this] using hcs end SimpleFuncProperties end SimpleFunc /-! Construction of the space of `Lp` simple functions, and its dense embedding into `Lp`. -/ namespace Lp open AEEqFun variable [MeasurableSpace α] [NormedAddCommGroup E] [NormedAddCommGroup F] (p : ℝ≥0∞) (μ : Measure α) variable (E) /-- `Lp.simpleFunc` is a subspace of Lp consisting of equivalence classes of an integrable simple function. -/ def simpleFunc : AddSubgroup (Lp E p μ) where carrier := { f : Lp E p μ | ∃ s : α →ₛ E, (AEEqFun.mk s s.aestronglyMeasurable : α →ₘ[μ] E) = f } zero_mem' := ⟨0, rfl⟩ add_mem' := by rintro f g ⟨s, hs⟩ ⟨t, ht⟩ use s + t simp only [← hs, ← ht, AEEqFun.mk_add_mk, AddSubgroup.coe_add, AEEqFun.mk_eq_mk, SimpleFunc.coe_add] neg_mem' := by rintro f ⟨s, hs⟩ use -s simp only [← hs, AEEqFun.neg_mk, SimpleFunc.coe_neg, AEEqFun.mk_eq_mk, AddSubgroup.coe_neg] variable {E p μ} namespace simpleFunc section Instances /-! Simple functions in Lp space form a `NormedSpace`. -/ protected theorem eq' {f g : Lp.simpleFunc E p μ} : (f : α →ₘ[μ] E) = (g : α →ₘ[μ] E) → f = g := Subtype.eq ∘ Subtype.eq /-! Implementation note: If `Lp.simpleFunc E p μ` were defined as a `𝕜`-submodule of `Lp E p μ`, then the next few lemmas, putting a normed `𝕜`-group structure on `Lp.simpleFunc E p μ`, would be unnecessary. But instead, `Lp.simpleFunc E p μ` is defined as an `AddSubgroup` of `Lp E p μ`, which does not permit this (but has the advantage of working when `E` itself is a normed group, i.e. has no scalar action). -/ variable [NormedRing 𝕜] [Module 𝕜 E] [IsBoundedSMul 𝕜 E] /-- If `E` is a normed space, `Lp.simpleFunc E p μ` is a `SMul`. Not declared as an instance as it is (as of writing) used only in the construction of the Bochner integral. -/ protected def smul : SMul 𝕜 (Lp.simpleFunc E p μ) := ⟨fun k f => ⟨k • (f : Lp E p μ), by rcases f with ⟨f, ⟨s, hs⟩⟩ use k • s apply Eq.trans (AEEqFun.smul_mk k s s.aestronglyMeasurable).symm _ rw [hs] rfl⟩⟩ attribute [local instance] simpleFunc.smul @[simp, norm_cast] theorem coe_smul (c : 𝕜) (f : Lp.simpleFunc E p μ) : ((c • f : Lp.simpleFunc E p μ) : Lp E p μ) = c • (f : Lp E p μ) := rfl /-- If `E` is a normed space, `Lp.simpleFunc E p μ` is a module. Not declared as an instance as it is (as of writing) used only in the construction of the Bochner integral. -/ protected def module : Module 𝕜 (Lp.simpleFunc E p μ) where one_smul f := by ext1; exact one_smul _ _ mul_smul x y f := by ext1; exact mul_smul _ _ _ smul_add x f g := by ext1; exact smul_add _ _ _ smul_zero x := by ext1; exact smul_zero _ add_smul x y f := by ext1; exact add_smul _ _ _ zero_smul f := by ext1; exact zero_smul _ _ attribute [local instance] simpleFunc.module /-- If `E` is a normed space, `Lp.simpleFunc E p μ` is a normed space. Not declared as an instance as it is (as of writing) used only in the construction of the Bochner integral. -/ protected theorem isBoundedSMul [Fact (1 ≤ p)] : IsBoundedSMul 𝕜 (Lp.simpleFunc E p μ) := IsBoundedSMul.of_norm_smul_le fun r f => (norm_smul_le r (f : Lp E p μ) :) @[deprecated (since := "2025-03-10")] protected alias boundedSMul := simpleFunc.isBoundedSMul attribute [local instance] simpleFunc.isBoundedSMul /-- If `E` is a normed space, `Lp.simpleFunc E p μ` is a normed space. Not declared as an instance as it is (as of writing) used only in the construction of the Bochner integral. -/ protected def normedSpace {𝕜} [NormedField 𝕜] [NormedSpace 𝕜 E] [Fact (1 ≤ p)] : NormedSpace 𝕜 (Lp.simpleFunc E p μ) := ⟨norm_smul_le (α := 𝕜) (β := Lp.simpleFunc E p μ)⟩ end Instances attribute [local instance] simpleFunc.module simpleFunc.normedSpace simpleFunc.isBoundedSMul section ToLp /-- Construct the equivalence class `[f]` of a simple function `f` satisfying `MemLp`. -/ abbrev toLp (f : α →ₛ E) (hf : MemLp f p μ) : Lp.simpleFunc E p μ := ⟨hf.toLp f, ⟨f, rfl⟩⟩ theorem toLp_eq_toLp (f : α →ₛ E) (hf : MemLp f p μ) : (toLp f hf : Lp E p μ) = hf.toLp f := rfl theorem toLp_eq_mk (f : α →ₛ E) (hf : MemLp f p μ) : (toLp f hf : α →ₘ[μ] E) = AEEqFun.mk f f.aestronglyMeasurable := rfl theorem toLp_zero : toLp (0 : α →ₛ E) MemLp.zero = (0 : Lp.simpleFunc E p μ) := rfl theorem toLp_add (f g : α →ₛ E) (hf : MemLp f p μ) (hg : MemLp g p μ) : toLp (f + g) (hf.add hg) = toLp f hf + toLp g hg := rfl theorem toLp_neg (f : α →ₛ E) (hf : MemLp f p μ) : toLp (-f) hf.neg = -toLp f hf := rfl theorem toLp_sub (f g : α →ₛ E) (hf : MemLp f p μ) (hg : MemLp g p μ) : toLp (f - g) (hf.sub hg) = toLp f hf - toLp g hg := by simp only [sub_eq_add_neg, ← toLp_neg, ← toLp_add] variable [NormedRing 𝕜] [Module 𝕜 E] [IsBoundedSMul 𝕜 E] theorem toLp_smul (f : α →ₛ E) (hf : MemLp f p μ) (c : 𝕜) : toLp (c • f) (hf.const_smul c) = c • toLp f hf := rfl nonrec theorem norm_toLp [Fact (1 ≤ p)] (f : α →ₛ E) (hf : MemLp f p μ) : ‖toLp f hf‖ = ENNReal.toReal (eLpNorm f p μ) := norm_toLp f hf end ToLp section ToSimpleFunc /-- Find a representative of a `Lp.simpleFunc`. -/ def toSimpleFunc (f : Lp.simpleFunc E p μ) : α →ₛ E := Classical.choose f.2 /-- `(toSimpleFunc f)` is measurable. -/ @[measurability] protected theorem measurable [MeasurableSpace E] (f : Lp.simpleFunc E p μ) : Measurable (toSimpleFunc f) := (toSimpleFunc f).measurable protected theorem stronglyMeasurable (f : Lp.simpleFunc E p μ) : StronglyMeasurable (toSimpleFunc f) := (toSimpleFunc f).stronglyMeasurable @[measurability] protected theorem aemeasurable [MeasurableSpace E] (f : Lp.simpleFunc E p μ) : AEMeasurable (toSimpleFunc f) μ := (simpleFunc.measurable f).aemeasurable protected theorem aestronglyMeasurable (f : Lp.simpleFunc E p μ) : AEStronglyMeasurable (toSimpleFunc f) μ := (simpleFunc.stronglyMeasurable f).aestronglyMeasurable theorem toSimpleFunc_eq_toFun (f : Lp.simpleFunc E p μ) : toSimpleFunc f =ᵐ[μ] f := show ⇑(toSimpleFunc f) =ᵐ[μ] ⇑(f : α →ₘ[μ] E) by convert (AEEqFun.coeFn_mk (toSimpleFunc f) (toSimpleFunc f).aestronglyMeasurable).symm using 2 exact (Classical.choose_spec f.2).symm /-- `toSimpleFunc f` satisfies the predicate `MemLp`. -/ protected theorem memLp (f : Lp.simpleFunc E p μ) : MemLp (toSimpleFunc f) p μ := MemLp.ae_eq (toSimpleFunc_eq_toFun f).symm <| mem_Lp_iff_memLp.mp (f : Lp E p μ).2 theorem toLp_toSimpleFunc (f : Lp.simpleFunc E p μ) : toLp (toSimpleFunc f) (simpleFunc.memLp f) = f := simpleFunc.eq' (Classical.choose_spec f.2) theorem toSimpleFunc_toLp (f : α →ₛ E) (hfi : MemLp f p μ) : toSimpleFunc (toLp f hfi) =ᵐ[μ] f := by rw [← AEEqFun.mk_eq_mk]; exact Classical.choose_spec (toLp f hfi).2 variable (E μ) theorem zero_toSimpleFunc : toSimpleFunc (0 : Lp.simpleFunc E p μ) =ᵐ[μ] 0 := by filter_upwards [toSimpleFunc_eq_toFun (0 : Lp.simpleFunc E p μ), Lp.coeFn_zero E 1 μ] with _ h₁ _ rwa [h₁] variable {E μ} theorem add_toSimpleFunc (f g : Lp.simpleFunc E p μ) : toSimpleFunc (f + g) =ᵐ[μ] toSimpleFunc f + toSimpleFunc g := by filter_upwards [toSimpleFunc_eq_toFun (f + g), toSimpleFunc_eq_toFun f, toSimpleFunc_eq_toFun g, Lp.coeFn_add (f : Lp E p μ) g] with _ simp only [AddSubgroup.coe_add, Pi.add_apply] iterate 4 intro h; rw [h] theorem neg_toSimpleFunc (f : Lp.simpleFunc E p μ) : toSimpleFunc (-f) =ᵐ[μ] -toSimpleFunc f := by filter_upwards [toSimpleFunc_eq_toFun (-f), toSimpleFunc_eq_toFun f, Lp.coeFn_neg (f : Lp E p μ)] with _ simp only [Pi.neg_apply, AddSubgroup.coe_neg] repeat intro h; rw [h] theorem sub_toSimpleFunc (f g : Lp.simpleFunc E p μ) : toSimpleFunc (f - g) =ᵐ[μ] toSimpleFunc f - toSimpleFunc g := by filter_upwards [toSimpleFunc_eq_toFun (f - g), toSimpleFunc_eq_toFun f, toSimpleFunc_eq_toFun g, Lp.coeFn_sub (f : Lp E p μ) g] with _ simp only [AddSubgroup.coe_sub, Pi.sub_apply] repeat' intro h; rw [h] variable [NormedRing 𝕜] [Module 𝕜 E] [IsBoundedSMul 𝕜 E] theorem smul_toSimpleFunc (k : 𝕜) (f : Lp.simpleFunc E p μ) : toSimpleFunc (k • f) =ᵐ[μ] k • ⇑(toSimpleFunc f) := by filter_upwards [toSimpleFunc_eq_toFun (k • f), toSimpleFunc_eq_toFun f, Lp.coeFn_smul k (f : Lp E p μ)] with _ simp only [Pi.smul_apply, coe_smul] repeat intro h; rw [h] theorem norm_toSimpleFunc [Fact (1 ≤ p)] (f : Lp.simpleFunc E p μ) : ‖f‖ = ENNReal.toReal (eLpNorm (toSimpleFunc f) p μ) := by simpa [toLp_toSimpleFunc] using norm_toLp (toSimpleFunc f) (simpleFunc.memLp f) end ToSimpleFunc section Induction variable (p) in /-- The characteristic function of a finite-measure measurable set `s`, as an `Lp` simple function. -/ def indicatorConst {s : Set α} (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : E) : Lp.simpleFunc E p μ :=
toLp ((SimpleFunc.const _ c).piecewise s hs (SimpleFunc.const _ 0)) (memLp_indicator_const p hs c (Or.inr hμs)) @[simp] theorem coe_indicatorConst {s : Set α} (hs : MeasurableSet s) (hμs : μ s ≠ ∞) (c : E) :
Mathlib/MeasureTheory/Function/SimpleFuncDenseLp.lean
602
606
/- Copyright (c) 2021 Chris Birkbeck. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Birkbeck -/ import Mathlib.Algebra.Group.Subgroup.Pointwise import Mathlib.GroupTheory.Coset.Basic /-! # Double cosets This file defines double cosets for two subgroups `H K` of a group `G` and the quotient of `G` by the double coset relation, i.e. `H \ G / K`. We also prove that `G` can be written as a disjoint union of the double cosets and that if one of `H` or `K` is the trivial group (i.e. `⊥` ) then this is the usual left or right quotient of a group by a subgroup. ## Main definitions * `rel`: The double coset relation defined by two subgroups `H K` of `G`. * `Doset.quotient`: The quotient of `G` by the double coset relation, i.e, `H \ G / K`. -/ assert_not_exists MonoidWithZero variable {G : Type*} [Group G] {α : Type*} [Mul α] open MulOpposite open scoped Pointwise namespace Doset /-- The double coset as an element of `Set α` corresponding to `s a t` -/ def doset (a : α) (s t : Set α) : Set α := s * {a} * t lemma doset_eq_image2 (a : α) (s t : Set α) : doset a s t = Set.image2 (· * a * ·) s t := by simp_rw [doset, Set.mul_singleton, ← Set.image2_mul, Set.image2_image_left] theorem mem_doset {s t : Set α} {a b : α} : b ∈ doset a s t ↔ ∃ x ∈ s, ∃ y ∈ t, b = x * a * y := by simp only [doset_eq_image2, Set.mem_image2, eq_comm] theorem mem_doset_self (H K : Subgroup G) (a : G) : a ∈ doset a H K := mem_doset.mpr ⟨1, H.one_mem, 1, K.one_mem, (one_mul a).symm.trans (mul_one (1 * a)).symm⟩ theorem doset_eq_of_mem {H K : Subgroup G} {a b : G} (hb : b ∈ doset a H K) : doset b H K = doset a H K := by obtain ⟨h, hh, k, hk, rfl⟩ := mem_doset.1 hb rw [doset, doset, ← Set.singleton_mul_singleton, ← Set.singleton_mul_singleton, mul_assoc, mul_assoc, Subgroup.singleton_mul_subgroup hk, ← mul_assoc, ← mul_assoc, Subgroup.subgroup_mul_singleton hh] theorem mem_doset_of_not_disjoint {H K : Subgroup G} {a b : G} (h : ¬Disjoint (doset a H K) (doset b H K)) : b ∈ doset a H K := by rw [Set.not_disjoint_iff] at h simp only [mem_doset] at * obtain ⟨x, ⟨l, hl, r, hr, hrx⟩, y, hy, ⟨r', hr', rfl⟩⟩ := h refine ⟨y⁻¹ * l, H.mul_mem (H.inv_mem hy) hl, r * r'⁻¹, K.mul_mem hr (K.inv_mem hr'), ?_⟩ rwa [mul_assoc, mul_assoc, eq_inv_mul_iff_mul_eq, ← mul_assoc, ← mul_assoc, eq_mul_inv_iff_mul_eq] theorem eq_of_not_disjoint {H K : Subgroup G} {a b : G} (h : ¬Disjoint (doset a H K) (doset b H K)) : doset a H K = doset b H K := by rw [disjoint_comm] at h have ha : a ∈ doset b H K := mem_doset_of_not_disjoint h apply doset_eq_of_mem ha /-- The setoid defined by the double_coset relation -/ def setoid (H K : Set G) : Setoid G := Setoid.ker fun x => doset x H K
/-- Quotient of `G` by the double coset relation, i.e. `H \ G / K` -/ def Quotient (H K : Set G) : Type _ := _root_.Quotient (setoid H K)
Mathlib/GroupTheory/DoubleCoset.lean
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/- Copyright (c) 2019 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn, Yury Kudryashov, Sébastien Gouëzel, Chris Hughes -/ import Mathlib.Data.Fin.Rev import Mathlib.Data.Nat.Find /-! # Operation on tuples We interpret maps `∀ i : Fin n, α i` as `n`-tuples of elements of possibly varying type `α i`, `(α 0, …, α (n-1))`. A particular case is `Fin n → α` of elements with all the same type. In this case when `α i` is a constant map, then tuples are isomorphic (but not definitionally equal) to `Vector`s. ## Main declarations There are three (main) ways to consider `Fin n` as a subtype of `Fin (n + 1)`, hence three (main) ways to move between tuples of length `n` and of length `n + 1` by adding/removing an entry. ### Adding at the start * `Fin.succ`: Send `i : Fin n` to `i + 1 : Fin (n + 1)`. This is defined in Core. * `Fin.cases`: Induction/recursion principle for `Fin`: To prove a property/define a function for all `Fin (n + 1)`, it is enough to prove/define it for `0` and for `i.succ` for all `i : Fin n`. This is defined in Core. * `Fin.cons`: Turn a tuple `f : Fin n → α` and an entry `a : α` into a tuple `Fin.cons a f : Fin (n + 1) → α` by adding `a` at the start. In general, tuples can be dependent functions, in which case `f : ∀ i : Fin n, α i.succ` and `a : α 0`. This is a special case of `Fin.cases`. * `Fin.tail`: Turn a tuple `f : Fin (n + 1) → α` into a tuple `Fin.tail f : Fin n → α` by forgetting the start. In general, tuples can be dependent functions, in which case `Fin.tail f : ∀ i : Fin n, α i.succ`. ### Adding at the end * `Fin.castSucc`: Send `i : Fin n` to `i : Fin (n + 1)`. This is defined in Core. * `Fin.lastCases`: Induction/recursion principle for `Fin`: To prove a property/define a function for all `Fin (n + 1)`, it is enough to prove/define it for `last n` and for `i.castSucc` for all `i : Fin n`. This is defined in Core. * `Fin.snoc`: Turn a tuple `f : Fin n → α` and an entry `a : α` into a tuple `Fin.snoc f a : Fin (n + 1) → α` by adding `a` at the end. In general, tuples can be dependent functions, in which case `f : ∀ i : Fin n, α i.castSucc` and `a : α (last n)`. This is a special case of `Fin.lastCases`. * `Fin.init`: Turn a tuple `f : Fin (n + 1) → α` into a tuple `Fin.init f : Fin n → α` by forgetting the start. In general, tuples can be dependent functions, in which case `Fin.init f : ∀ i : Fin n, α i.castSucc`. ### Adding in the middle For a **pivot** `p : Fin (n + 1)`, * `Fin.succAbove`: Send `i : Fin n` to * `i : Fin (n + 1)` if `i < p`, * `i + 1 : Fin (n + 1)` if `p ≤ i`. * `Fin.succAboveCases`: Induction/recursion principle for `Fin`: To prove a property/define a function for all `Fin (n + 1)`, it is enough to prove/define it for `p` and for `p.succAbove i` for all `i : Fin n`. * `Fin.insertNth`: Turn a tuple `f : Fin n → α` and an entry `a : α` into a tuple `Fin.insertNth f a : Fin (n + 1) → α` by adding `a` in position `p`. In general, tuples can be dependent functions, in which case `f : ∀ i : Fin n, α (p.succAbove i)` and `a : α p`. This is a special case of `Fin.succAboveCases`. * `Fin.removeNth`: Turn a tuple `f : Fin (n + 1) → α` into a tuple `Fin.removeNth p f : Fin n → α` by forgetting the `p`-th value. In general, tuples can be dependent functions, in which case `Fin.removeNth f : ∀ i : Fin n, α (succAbove p i)`. `p = 0` means we add at the start. `p = last n` means we add at the end. ### Miscellaneous * `Fin.find p` : returns the first index `n` where `p n` is satisfied, and `none` if it is never satisfied. * `Fin.append a b` : append two tuples. * `Fin.repeat n a` : repeat a tuple `n` times. -/ assert_not_exists Monoid universe u v namespace Fin variable {m n : ℕ} open Function section Tuple /-- There is exactly one tuple of size zero. -/ example (α : Fin 0 → Sort u) : Unique (∀ i : Fin 0, α i) := by infer_instance theorem tuple0_le {α : Fin 0 → Type*} [∀ i, Preorder (α i)] (f g : ∀ i, α i) : f ≤ g := finZeroElim variable {α : Fin (n + 1) → Sort u} (x : α 0) (q : ∀ i, α i) (p : ∀ i : Fin n, α i.succ) (i : Fin n) (y : α i.succ) (z : α 0) /-- The tail of an `n+1` tuple, i.e., its last `n` entries. -/ def tail (q : ∀ i, α i) : ∀ i : Fin n, α i.succ := fun i ↦ q i.succ theorem tail_def {n : ℕ} {α : Fin (n + 1) → Sort*} {q : ∀ i, α i} : (tail fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q k.succ := rfl /-- Adding an element at the beginning of an `n`-tuple, to get an `n+1`-tuple. -/ def cons (x : α 0) (p : ∀ i : Fin n, α i.succ) : ∀ i, α i := fun j ↦ Fin.cases x p j @[simp] theorem tail_cons : tail (cons x p) = p := by simp +unfoldPartialApp [tail, cons] @[simp] theorem cons_succ : cons x p i.succ = p i := by simp [cons] @[simp] theorem cons_zero : cons x p 0 = x := by simp [cons] @[simp] theorem cons_one {α : Fin (n + 2) → Sort*} (x : α 0) (p : ∀ i : Fin n.succ, α i.succ) : cons x p 1 = p 0 := by rw [← cons_succ x p]; rfl /-- Updating a tuple and adding an element at the beginning commute. -/ @[simp] theorem cons_update : cons x (update p i y) = update (cons x p) i.succ y := by ext j by_cases h : j = 0 · rw [h] simp [Ne.symm (succ_ne_zero i)] · let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this, cons_succ] by_cases h' : j' = i · rw [h'] simp · have : j'.succ ≠ i.succ := by rwa [Ne, succ_inj] rw [update_of_ne h', update_of_ne this, cons_succ] /-- As a binary function, `Fin.cons` is injective. -/ theorem cons_injective2 : Function.Injective2 (@cons n α) := fun x₀ y₀ x y h ↦ ⟨congr_fun h 0, funext fun i ↦ by simpa using congr_fun h (Fin.succ i)⟩ @[simp] theorem cons_inj {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} : cons x₀ x = cons y₀ y ↔ x₀ = y₀ ∧ x = y := cons_injective2.eq_iff theorem cons_left_injective (x : ∀ i : Fin n, α i.succ) : Function.Injective fun x₀ ↦ cons x₀ x := cons_injective2.left _ theorem cons_right_injective (x₀ : α 0) : Function.Injective (cons x₀) := cons_injective2.right _ /-- Adding an element at the beginning of a tuple and then updating it amounts to adding it directly. -/ theorem update_cons_zero : update (cons x p) 0 z = cons z p := by ext j by_cases h : j = 0 · rw [h] simp · simp only [h, update_of_ne, Ne, not_false_iff] let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this, cons_succ, cons_succ] /-- Concatenating the first element of a tuple with its tail gives back the original tuple -/ @[simp] theorem cons_self_tail : cons (q 0) (tail q) = q := by ext j by_cases h : j = 0 · rw [h] simp · let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this] unfold tail rw [cons_succ] /-- Equivalence between tuples of length `n + 1` and pairs of an element and a tuple of length `n` given by separating out the first element of the tuple. This is `Fin.cons` as an `Equiv`. -/ @[simps] def consEquiv (α : Fin (n + 1) → Type*) : α 0 × (∀ i, α (succ i)) ≃ ∀ i, α i where toFun f := cons f.1 f.2 invFun f := (f 0, tail f) left_inv f := by simp right_inv f := by simp /-- Recurse on an `n+1`-tuple by splitting it into a single element and an `n`-tuple. -/ @[elab_as_elim] def consCases {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x)) (x : ∀ i : Fin n.succ, α i) : P x := _root_.cast (by rw [cons_self_tail]) <| h (x 0) (tail x) @[simp] theorem consCases_cons {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x)) (x₀ : α 0) (x : ∀ i : Fin n, α i.succ) : @consCases _ _ _ h (cons x₀ x) = h x₀ x := by rw [consCases, cast_eq] congr /-- Recurse on a tuple by splitting into `Fin.elim0` and `Fin.cons`. -/ @[elab_as_elim] def consInduction {α : Sort*} {P : ∀ {n : ℕ}, (Fin n → α) → Sort v} (h0 : P Fin.elim0) (h : ∀ {n} (x₀) (x : Fin n → α), P x → P (Fin.cons x₀ x)) : ∀ {n : ℕ} (x : Fin n → α), P x | 0, x => by convert h0 | _ + 1, x => consCases (fun _ _ ↦ h _ _ <| consInduction h0 h _) x theorem cons_injective_of_injective {α} {x₀ : α} {x : Fin n → α} (hx₀ : x₀ ∉ Set.range x) (hx : Function.Injective x) : Function.Injective (cons x₀ x : Fin n.succ → α) := by refine Fin.cases ?_ ?_ · refine Fin.cases ?_ ?_ · intro rfl · intro j h rw [cons_zero, cons_succ] at h exact hx₀.elim ⟨_, h.symm⟩ · intro i refine Fin.cases ?_ ?_ · intro h rw [cons_zero, cons_succ] at h exact hx₀.elim ⟨_, h⟩ · intro j h rw [cons_succ, cons_succ] at h exact congr_arg _ (hx h) theorem cons_injective_iff {α} {x₀ : α} {x : Fin n → α} : Function.Injective (cons x₀ x : Fin n.succ → α) ↔ x₀ ∉ Set.range x ∧ Function.Injective x := by refine ⟨fun h ↦ ⟨?_, ?_⟩, fun h ↦ cons_injective_of_injective h.1 h.2⟩ · rintro ⟨i, hi⟩ replace h := @h i.succ 0 simp [hi] at h · simpa [Function.comp] using h.comp (Fin.succ_injective _) @[simp] theorem forall_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} : (∀ x, P x) ↔ P finZeroElim := ⟨fun h ↦ h _, fun h x ↦ Subsingleton.elim finZeroElim x ▸ h⟩ @[simp] theorem exists_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} : (∃ x, P x) ↔ P finZeroElim := ⟨fun ⟨x, h⟩ ↦ Subsingleton.elim x finZeroElim ▸ h, fun h ↦ ⟨_, h⟩⟩ theorem forall_fin_succ_pi {P : (∀ i, α i) → Prop} : (∀ x, P x) ↔ ∀ a v, P (Fin.cons a v) := ⟨fun h a v ↦ h (Fin.cons a v), consCases⟩ theorem exists_fin_succ_pi {P : (∀ i, α i) → Prop} : (∃ x, P x) ↔ ∃ a v, P (Fin.cons a v) := ⟨fun ⟨x, h⟩ ↦ ⟨x 0, tail x, (cons_self_tail x).symm ▸ h⟩, fun ⟨_, _, h⟩ ↦ ⟨_, h⟩⟩ /-- Updating the first element of a tuple does not change the tail. -/ @[simp] theorem tail_update_zero : tail (update q 0 z) = tail q := by ext j simp [tail] /-- Updating a nonzero element and taking the tail commute. -/ @[simp] theorem tail_update_succ : tail (update q i.succ y) = update (tail q) i y := by ext j by_cases h : j = i · rw [h] simp [tail] · simp [tail, (Fin.succ_injective n).ne h, h] theorem comp_cons {α : Sort*} {β : Sort*} (g : α → β) (y : α) (q : Fin n → α) : g ∘ cons y q = cons (g y) (g ∘ q) := by ext j by_cases h : j = 0 · rw [h] rfl · let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this, cons_succ, comp_apply, comp_apply, cons_succ] theorem comp_tail {α : Sort*} {β : Sort*} (g : α → β) (q : Fin n.succ → α) : g ∘ tail q = tail (g ∘ q) := by ext j simp [tail] section Preorder variable {α : Fin (n + 1) → Type*} theorem le_cons [∀ i, Preorder (α i)] {x : α 0} {q : ∀ i, α i} {p : ∀ i : Fin n, α i.succ} : q ≤ cons x p ↔ q 0 ≤ x ∧ tail q ≤ p := forall_fin_succ.trans <| and_congr Iff.rfl <| forall_congr' fun j ↦ by simp [tail] theorem cons_le [∀ i, Preorder (α i)] {x : α 0} {q : ∀ i, α i} {p : ∀ i : Fin n, α i.succ} : cons x p ≤ q ↔ x ≤ q 0 ∧ p ≤ tail q := @le_cons _ (fun i ↦ (α i)ᵒᵈ) _ x q p theorem cons_le_cons [∀ i, Preorder (α i)] {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} : cons x₀ x ≤ cons y₀ y ↔ x₀ ≤ y₀ ∧ x ≤ y := forall_fin_succ.trans <| and_congr_right' <| by simp only [cons_succ, Pi.le_def] end Preorder theorem range_fin_succ {α} (f : Fin (n + 1) → α) : Set.range f = insert (f 0) (Set.range (Fin.tail f)) := Set.ext fun _ ↦ exists_fin_succ.trans <| eq_comm.or Iff.rfl @[simp] theorem range_cons {α} {n : ℕ} (x : α) (b : Fin n → α) : Set.range (Fin.cons x b : Fin n.succ → α) = insert x (Set.range b) := by rw [range_fin_succ, cons_zero, tail_cons] section Append variable {α : Sort*} /-- Append a tuple of length `m` to a tuple of length `n` to get a tuple of length `m + n`. This is a non-dependent version of `Fin.add_cases`. -/ def append (a : Fin m → α) (b : Fin n → α) : Fin (m + n) → α := @Fin.addCases _ _ (fun _ => α) a b @[simp] theorem append_left (u : Fin m → α) (v : Fin n → α) (i : Fin m) : append u v (Fin.castAdd n i) = u i := addCases_left _ @[simp] theorem append_right (u : Fin m → α) (v : Fin n → α) (i : Fin n) : append u v (natAdd m i) = v i := addCases_right _ theorem append_right_nil (u : Fin m → α) (v : Fin n → α) (hv : n = 0) : append u v = u ∘ Fin.cast (by rw [hv, Nat.add_zero]) := by refine funext (Fin.addCases (fun l => ?_) fun r => ?_) · rw [append_left, Function.comp_apply] refine congr_arg u (Fin.ext ?_) simp · exact (Fin.cast hv r).elim0 @[simp] theorem append_elim0 (u : Fin m → α) : append u Fin.elim0 = u ∘ Fin.cast (Nat.add_zero _) := append_right_nil _ _ rfl theorem append_left_nil (u : Fin m → α) (v : Fin n → α) (hu : m = 0) : append u v = v ∘ Fin.cast (by rw [hu, Nat.zero_add]) := by refine funext (Fin.addCases (fun l => ?_) fun r => ?_) · exact (Fin.cast hu l).elim0 · rw [append_right, Function.comp_apply] refine congr_arg v (Fin.ext ?_) simp [hu] @[simp] theorem elim0_append (v : Fin n → α) : append Fin.elim0 v = v ∘ Fin.cast (Nat.zero_add _) := append_left_nil _ _ rfl theorem append_assoc {p : ℕ} (a : Fin m → α) (b : Fin n → α) (c : Fin p → α) : append (append a b) c = append a (append b c) ∘ Fin.cast (Nat.add_assoc ..) := by ext i rw [Function.comp_apply] refine Fin.addCases (fun l => ?_) (fun r => ?_) i · rw [append_left] refine Fin.addCases (fun ll => ?_) (fun lr => ?_) l · rw [append_left] simp [castAdd_castAdd] · rw [append_right] simp [castAdd_natAdd] · rw [append_right] simp [← natAdd_natAdd] /-- Appending a one-tuple to the left is the same as `Fin.cons`. -/ theorem append_left_eq_cons {n : ℕ} (x₀ : Fin 1 → α) (x : Fin n → α) : Fin.append x₀ x = Fin.cons (x₀ 0) x ∘ Fin.cast (Nat.add_comm ..) := by ext i refine Fin.addCases ?_ ?_ i <;> clear i · intro i rw [Subsingleton.elim i 0, Fin.append_left, Function.comp_apply, eq_comm] exact Fin.cons_zero _ _ · intro i rw [Fin.append_right, Function.comp_apply, Fin.cast_natAdd, eq_comm, Fin.addNat_one] exact Fin.cons_succ _ _ _ /-- `Fin.cons` is the same as appending a one-tuple to the left. -/ theorem cons_eq_append (x : α) (xs : Fin n → α) : cons x xs = append (cons x Fin.elim0) xs ∘ Fin.cast (Nat.add_comm ..) := by funext i; simp [append_left_eq_cons] @[simp] lemma append_cast_left {n m} (xs : Fin n → α) (ys : Fin m → α) (n' : ℕ) (h : n' = n) : Fin.append (xs ∘ Fin.cast h) ys = Fin.append xs ys ∘ (Fin.cast <| by rw [h]) := by subst h; simp @[simp] lemma append_cast_right {n m} (xs : Fin n → α) (ys : Fin m → α) (m' : ℕ) (h : m' = m) : Fin.append xs (ys ∘ Fin.cast h) = Fin.append xs ys ∘ (Fin.cast <| by rw [h]) := by subst h; simp lemma append_rev {m n} (xs : Fin m → α) (ys : Fin n → α) (i : Fin (m + n)) : append xs ys (rev i) = append (ys ∘ rev) (xs ∘ rev) (i.cast (Nat.add_comm ..)) := by rcases rev_surjective i with ⟨i, rfl⟩ rw [rev_rev] induction i using Fin.addCases · simp [rev_castAdd] · simp [cast_rev, rev_addNat] lemma append_comp_rev {m n} (xs : Fin m → α) (ys : Fin n → α) : append xs ys ∘ rev = append (ys ∘ rev) (xs ∘ rev) ∘ Fin.cast (Nat.add_comm ..) := funext <| append_rev xs ys theorem append_castAdd_natAdd {f : Fin (m + n) → α} : append (fun i ↦ f (castAdd n i)) (fun i ↦ f (natAdd m i)) = f := by unfold append addCases simp end Append section Repeat variable {α : Sort*} /-- Repeat `a` `m` times. For example `Fin.repeat 2 ![0, 3, 7] = ![0, 3, 7, 0, 3, 7]`. -/ def «repeat» (m : ℕ) (a : Fin n → α) : Fin (m * n) → α | i => a i.modNat @[simp] theorem repeat_apply (a : Fin n → α) (i : Fin (m * n)) : Fin.repeat m a i = a i.modNat := rfl @[simp] theorem repeat_zero (a : Fin n → α) : Fin.repeat 0 a = Fin.elim0 ∘ Fin.cast (Nat.zero_mul _) := funext fun x => (x.cast (Nat.zero_mul _)).elim0 @[simp] theorem repeat_one (a : Fin n → α) : Fin.repeat 1 a = a ∘ Fin.cast (Nat.one_mul _) := by generalize_proofs h apply funext rw [(Fin.rightInverse_cast h.symm).surjective.forall] intro i simp [modNat, Nat.mod_eq_of_lt i.is_lt] theorem repeat_succ (a : Fin n → α) (m : ℕ) : Fin.repeat m.succ a = append a (Fin.repeat m a) ∘ Fin.cast ((Nat.succ_mul _ _).trans (Nat.add_comm ..)) := by generalize_proofs h apply funext rw [(Fin.rightInverse_cast h.symm).surjective.forall] refine Fin.addCases (fun l => ?_) fun r => ?_ · simp [modNat, Nat.mod_eq_of_lt l.is_lt] · simp [modNat] @[simp] theorem repeat_add (a : Fin n → α) (m₁ m₂ : ℕ) : Fin.repeat (m₁ + m₂) a = append (Fin.repeat m₁ a) (Fin.repeat m₂ a) ∘ Fin.cast (Nat.add_mul ..) := by generalize_proofs h apply funext rw [(Fin.rightInverse_cast h.symm).surjective.forall] refine Fin.addCases (fun l => ?_) fun r => ?_ · simp [modNat, Nat.mod_eq_of_lt l.is_lt] · simp [modNat, Nat.add_mod] theorem repeat_rev (a : Fin n → α) (k : Fin (m * n)) : Fin.repeat m a k.rev = Fin.repeat m (a ∘ Fin.rev) k := congr_arg a k.modNat_rev theorem repeat_comp_rev (a : Fin n → α) : Fin.repeat m a ∘ Fin.rev = Fin.repeat m (a ∘ Fin.rev) := funext <| repeat_rev a end Repeat end Tuple section TupleRight /-! In the previous section, we have discussed inserting or removing elements on the left of a tuple. In this section, we do the same on the right. A difference is that `Fin (n+1)` is constructed inductively from `Fin n` starting from the left, not from the right. This implies that Lean needs more help to realize that elements belong to the right types, i.e., we need to insert casts at several places. -/ variable {α : Fin (n + 1) → Sort*} (x : α (last n)) (q : ∀ i, α i) (p : ∀ i : Fin n, α i.castSucc) (i : Fin n) (y : α i.castSucc) (z : α (last n)) /-- The beginning of an `n+1` tuple, i.e., its first `n` entries -/ def init (q : ∀ i, α i) (i : Fin n) : α i.castSucc := q i.castSucc theorem init_def {q : ∀ i, α i} : (init fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q k.castSucc := rfl /-- Adding an element at the end of an `n`-tuple, to get an `n+1`-tuple. The name `snoc` comes from `cons` (i.e., adding an element to the left of a tuple) read in reverse order. -/ def snoc (p : ∀ i : Fin n, α i.castSucc) (x : α (last n)) (i : Fin (n + 1)) : α i := if h : i.val < n then _root_.cast (by rw [Fin.castSucc_castLT i h]) (p (castLT i h)) else _root_.cast (by rw [eq_last_of_not_lt h]) x @[simp] theorem init_snoc : init (snoc p x) = p := by ext i simp only [init, snoc, coe_castSucc, is_lt, cast_eq, dite_true] convert cast_eq rfl (p i) @[simp] theorem snoc_castSucc : snoc p x i.castSucc = p i := by simp only [snoc, coe_castSucc, is_lt, cast_eq, dite_true] convert cast_eq rfl (p i) @[simp] theorem snoc_comp_castSucc {α : Sort*} {a : α} {f : Fin n → α} : (snoc f a : Fin (n + 1) → α) ∘ castSucc = f := funext fun i ↦ by rw [Function.comp_apply, snoc_castSucc] @[simp] theorem snoc_last : snoc p x (last n) = x := by simp [snoc] lemma snoc_zero {α : Sort*} (p : Fin 0 → α) (x : α) : Fin.snoc p x = fun _ ↦ x := by ext y have : Subsingleton (Fin (0 + 1)) := Fin.subsingleton_one simp only [Subsingleton.elim y (Fin.last 0), snoc_last] @[simp] theorem snoc_comp_nat_add {n m : ℕ} {α : Sort*} (f : Fin (m + n) → α) (a : α) : (snoc f a : Fin _ → α) ∘ (natAdd m : Fin (n + 1) → Fin (m + n + 1)) = snoc (f ∘ natAdd m) a := by ext i refine Fin.lastCases ?_ (fun i ↦ ?_) i · simp only [Function.comp_apply] rw [snoc_last, natAdd_last, snoc_last] · simp only [comp_apply, snoc_castSucc] rw [natAdd_castSucc, snoc_castSucc] @[simp] theorem snoc_cast_add {α : Fin (n + m + 1) → Sort*} (f : ∀ i : Fin (n + m), α i.castSucc) (a : α (last (n + m))) (i : Fin n) : (snoc f a) (castAdd (m + 1) i) = f (castAdd m i) := dif_pos _ @[simp] theorem snoc_comp_cast_add {n m : ℕ} {α : Sort*} (f : Fin (n + m) → α) (a : α) : (snoc f a : Fin _ → α) ∘ castAdd (m + 1) = f ∘ castAdd m := funext (snoc_cast_add _ _) /-- Updating a tuple and adding an element at the end commute. -/ @[simp] theorem snoc_update : snoc (update p i y) x = update (snoc p x) i.castSucc y := by ext j cases j using lastCases with | cast j => rcases eq_or_ne j i with rfl | hne <;> simp [*] | last => simp [Ne.symm] /-- Adding an element at the beginning of a tuple and then updating it amounts to adding it directly. -/ theorem update_snoc_last : update (snoc p x) (last n) z = snoc p z := by ext j cases j using lastCases <;> simp /-- As a binary function, `Fin.snoc` is injective. -/ theorem snoc_injective2 : Function.Injective2 (@snoc n α) := fun x y xₙ yₙ h ↦ ⟨funext fun i ↦ by simpa using congr_fun h (castSucc i), by simpa using congr_fun h (last n)⟩ @[simp] theorem snoc_inj {x y : ∀ i : Fin n, α i.castSucc} {xₙ yₙ : α (last n)} : snoc x xₙ = snoc y yₙ ↔ x = y ∧ xₙ = yₙ := snoc_injective2.eq_iff theorem snoc_right_injective (x : ∀ i : Fin n, α i.castSucc) : Function.Injective (snoc x) := snoc_injective2.right _ theorem snoc_left_injective (xₙ : α (last n)) : Function.Injective (snoc · xₙ) := snoc_injective2.left _ /-- Concatenating the first element of a tuple with its tail gives back the original tuple -/ @[simp] theorem snoc_init_self : snoc (init q) (q (last n)) = q := by ext j by_cases h : j.val < n · simp only [init, snoc, h, cast_eq, dite_true, castSucc_castLT] · rw [eq_last_of_not_lt h] simp /-- Updating the last element of a tuple does not change the beginning. -/ @[simp] theorem init_update_last : init (update q (last n) z) = init q := by ext j simp [init, Fin.ne_of_lt] /-- Updating an element and taking the beginning commute. -/ @[simp] theorem init_update_castSucc : init (update q i.castSucc y) = update (init q) i y := by ext j by_cases h : j = i · rw [h] simp [init] · simp [init, h, castSucc_inj] /-- `tail` and `init` commute. We state this lemma in a non-dependent setting, as otherwise it would involve a cast to convince Lean that the two types are equal, making it harder to use. -/ theorem tail_init_eq_init_tail {β : Sort*} (q : Fin (n + 2) → β) : tail (init q) = init (tail q) := by ext i simp [tail, init, castSucc_fin_succ] /-- `cons` and `snoc` commute. We state this lemma in a non-dependent setting, as otherwise it would involve a cast to convince Lean that the two types are equal, making it harder to use. -/ theorem cons_snoc_eq_snoc_cons {β : Sort*} (a : β) (q : Fin n → β) (b : β) : @cons n.succ (fun _ ↦ β) a (snoc q b) = snoc (cons a q) b := by ext i by_cases h : i = 0 · simp [h, snoc, castLT] set j := pred i h with ji have : i = j.succ := by rw [ji, succ_pred] rw [this, cons_succ] by_cases h' : j.val < n · set k := castLT j h' with jk have : j = castSucc k := by rw [jk, castSucc_castLT] rw [this, ← castSucc_fin_succ, snoc] simp [pred, snoc, cons] rw [eq_last_of_not_lt h', succ_last] simp theorem comp_snoc {α : Sort*} {β : Sort*} (g : α → β) (q : Fin n → α) (y : α) : g ∘ snoc q y = snoc (g ∘ q) (g y) := by ext j by_cases h : j.val < n · simp [h, snoc, castSucc_castLT] · rw [eq_last_of_not_lt h] simp /-- Appending a one-tuple to the right is the same as `Fin.snoc`. -/ theorem append_right_eq_snoc {α : Sort*} {n : ℕ} (x : Fin n → α) (x₀ : Fin 1 → α) : Fin.append x x₀ = Fin.snoc x (x₀ 0) := by ext i refine Fin.addCases ?_ ?_ i <;> clear i · intro i rw [Fin.append_left] exact (@snoc_castSucc _ (fun _ => α) _ _ i).symm · intro i rw [Subsingleton.elim i 0, Fin.append_right] exact (@snoc_last _ (fun _ => α) _ _).symm /-- `Fin.snoc` is the same as appending a one-tuple -/ theorem snoc_eq_append {α : Sort*} (xs : Fin n → α) (x : α) : snoc xs x = append xs (cons x Fin.elim0) := (append_right_eq_snoc xs (cons x Fin.elim0)).symm theorem append_left_snoc {n m} {α : Sort*} (xs : Fin n → α) (x : α) (ys : Fin m → α) : Fin.append (Fin.snoc xs x) ys = Fin.append xs (Fin.cons x ys) ∘ Fin.cast (Nat.succ_add_eq_add_succ ..) := by rw [snoc_eq_append, append_assoc, append_left_eq_cons, append_cast_right]; rfl theorem append_right_cons {n m} {α : Sort*} (xs : Fin n → α) (y : α) (ys : Fin m → α) : Fin.append xs (Fin.cons y ys) = Fin.append (Fin.snoc xs y) ys ∘ Fin.cast (Nat.succ_add_eq_add_succ ..).symm := by rw [append_left_snoc]; rfl theorem append_cons {α : Sort*} (a : α) (as : Fin n → α) (bs : Fin m → α) : Fin.append (cons a as) bs = cons a (Fin.append as bs) ∘ (Fin.cast <| Nat.add_right_comm n 1 m) := by funext i rcases i with ⟨i, -⟩ simp only [append, addCases, cons, castLT, cast, comp_apply] rcases i with - | i · simp · split_ifs with h · have : i < n := Nat.lt_of_succ_lt_succ h simp [addCases, this] · have : ¬i < n := Nat.not_le.mpr <| Nat.lt_succ.mp <| Nat.not_le.mp h simp [addCases, this] theorem append_snoc {α : Sort*} (as : Fin n → α) (bs : Fin m → α) (b : α) : Fin.append as (snoc bs b) = snoc (Fin.append as bs) b := by funext i rcases i with ⟨i, isLt⟩ simp only [append, addCases, castLT, cast_mk, subNat_mk, natAdd_mk, cast, snoc.eq_1, cast_eq, eq_rec_constant, Nat.add_eq, Nat.add_zero, castLT_mk] split_ifs with lt_n lt_add sub_lt nlt_add lt_add <;> (try rfl) · have := Nat.lt_add_right m lt_n contradiction · obtain rfl := Nat.eq_of_le_of_lt_succ (Nat.not_lt.mp nlt_add) isLt simp [Nat.add_comm n m] at sub_lt · have := Nat.sub_lt_left_of_lt_add (Nat.not_lt.mp lt_n) lt_add contradiction theorem comp_init {α : Sort*} {β : Sort*} (g : α → β) (q : Fin n.succ → α) : g ∘ init q = init (g ∘ q) := by ext j simp [init] /-- Equivalence between tuples of length `n + 1` and pairs of an element and a tuple of length `n` given by separating out the last element of the tuple. This is `Fin.snoc` as an `Equiv`. -/ @[simps] def snocEquiv (α : Fin (n + 1) → Type*) : α (last n) × (∀ i, α (castSucc i)) ≃ ∀ i, α i where toFun f _ := Fin.snoc f.2 f.1 _ invFun f := ⟨f _, Fin.init f⟩
left_inv f := by simp right_inv f := by simp /-- Recurse on an `n+1`-tuple by splitting it its initial `n`-tuple and its last element. -/ @[elab_as_elim, inline] def snocCases {P : (∀ i : Fin n.succ, α i) → Sort*} (h : ∀ xs x, P (Fin.snoc xs x)) (x : ∀ i : Fin n.succ, α i) : P x := _root_.cast (by rw [Fin.snoc_init_self]) <| h (Fin.init x) (x <| Fin.last _)
Mathlib/Data/Fin/Tuple/Basic.lean
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/- Copyright (c) 2014 Robert Y. Lewis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Robert Y. Lewis, Leonardo de Moura, Mario Carneiro, Floris van Doorn -/ import Mathlib.Algebra.Field.Basic import Mathlib.Algebra.GroupWithZero.Units.Lemmas import Mathlib.Algebra.Order.Ring.Abs import Mathlib.Order.Bounds.Basic import Mathlib.Order.Bounds.OrderIso import Mathlib.Tactic.Positivity.Core /-! # Lemmas about linear ordered (semi)fields -/ open Function OrderDual variable {ι α β : Type*} section LinearOrderedSemifield variable [Semifield α] [LinearOrder α] [IsStrictOrderedRing α] {a b c d e : α} {m n : ℤ} /-! ### Relating two divisions. -/ @[deprecated div_le_div_iff_of_pos_right (since := "2024-11-12")] theorem div_le_div_right (hc : 0 < c) : a / c ≤ b / c ↔ a ≤ b := div_le_div_iff_of_pos_right hc @[deprecated div_lt_div_iff_of_pos_right (since := "2024-11-12")] theorem div_lt_div_right (hc : 0 < c) : a / c < b / c ↔ a < b := div_lt_div_iff_of_pos_right hc @[deprecated div_lt_div_iff_of_pos_left (since := "2024-11-13")] theorem div_lt_div_left (ha : 0 < a) (hb : 0 < b) (hc : 0 < c) : a / b < a / c ↔ c < b := div_lt_div_iff_of_pos_left ha hb hc @[deprecated div_le_div_iff_of_pos_left (since := "2024-11-12")] theorem div_le_div_left (ha : 0 < a) (hb : 0 < b) (hc : 0 < c) : a / b ≤ a / c ↔ c ≤ b := div_le_div_iff_of_pos_left ha hb hc @[deprecated div_lt_div_iff₀ (since := "2024-11-12")] theorem div_lt_div_iff (b0 : 0 < b) (d0 : 0 < d) : a / b < c / d ↔ a * d < c * b := div_lt_div_iff₀ b0 d0 @[deprecated div_le_div_iff₀ (since := "2024-11-12")] theorem div_le_div_iff (b0 : 0 < b) (d0 : 0 < d) : a / b ≤ c / d ↔ a * d ≤ c * b := div_le_div_iff₀ b0 d0 @[deprecated div_le_div₀ (since := "2024-11-12")] theorem div_le_div (hc : 0 ≤ c) (hac : a ≤ c) (hd : 0 < d) (hbd : d ≤ b) : a / b ≤ c / d := div_le_div₀ hc hac hd hbd @[deprecated div_lt_div₀ (since := "2024-11-12")] theorem div_lt_div (hac : a < c) (hbd : d ≤ b) (c0 : 0 ≤ c) (d0 : 0 < d) : a / b < c / d := div_lt_div₀ hac hbd c0 d0 @[deprecated div_lt_div₀' (since := "2024-11-12")] theorem div_lt_div' (hac : a ≤ c) (hbd : d < b) (c0 : 0 < c) (d0 : 0 < d) : a / b < c / d := div_lt_div₀' hac hbd c0 d0 /-! ### Relating one division and involving `1` -/ @[bound] theorem div_le_self (ha : 0 ≤ a) (hb : 1 ≤ b) : a / b ≤ a := by simpa only [div_one] using div_le_div_of_nonneg_left ha zero_lt_one hb @[bound] theorem div_lt_self (ha : 0 < a) (hb : 1 < b) : a / b < a := by simpa only [div_one] using div_lt_div_of_pos_left ha zero_lt_one hb @[bound] theorem le_div_self (ha : 0 ≤ a) (hb₀ : 0 < b) (hb₁ : b ≤ 1) : a ≤ a / b := by simpa only [div_one] using div_le_div_of_nonneg_left ha hb₀ hb₁ theorem one_le_div (hb : 0 < b) : 1 ≤ a / b ↔ b ≤ a := by rw [le_div_iff₀ hb, one_mul] theorem div_le_one (hb : 0 < b) : a / b ≤ 1 ↔ a ≤ b := by rw [div_le_iff₀ hb, one_mul] theorem one_lt_div (hb : 0 < b) : 1 < a / b ↔ b < a := by rw [lt_div_iff₀ hb, one_mul] theorem div_lt_one (hb : 0 < b) : a / b < 1 ↔ a < b := by rw [div_lt_iff₀ hb, one_mul] theorem one_div_le (ha : 0 < a) (hb : 0 < b) : 1 / a ≤ b ↔ 1 / b ≤ a := by simpa using inv_le_comm₀ ha hb theorem one_div_lt (ha : 0 < a) (hb : 0 < b) : 1 / a < b ↔ 1 / b < a := by simpa using inv_lt_comm₀ ha hb theorem le_one_div (ha : 0 < a) (hb : 0 < b) : a ≤ 1 / b ↔ b ≤ 1 / a := by simpa using le_inv_comm₀ ha hb theorem lt_one_div (ha : 0 < a) (hb : 0 < b) : a < 1 / b ↔ b < 1 / a := by simpa using lt_inv_comm₀ ha hb @[bound] lemma Bound.one_lt_div_of_pos_of_lt (b0 : 0 < b) : b < a → 1 < a / b := (one_lt_div b0).mpr @[bound] lemma Bound.div_lt_one_of_pos_of_lt (b0 : 0 < b) : a < b → a / b < 1 := (div_lt_one b0).mpr /-! ### Relating two divisions, involving `1` -/ theorem one_div_le_one_div_of_le (ha : 0 < a) (h : a ≤ b) : 1 / b ≤ 1 / a := by simpa using inv_anti₀ ha h theorem one_div_lt_one_div_of_lt (ha : 0 < a) (h : a < b) : 1 / b < 1 / a := by rwa [lt_div_iff₀' ha, ← div_eq_mul_one_div, div_lt_one (ha.trans h)] theorem le_of_one_div_le_one_div (ha : 0 < a) (h : 1 / a ≤ 1 / b) : b ≤ a := le_imp_le_of_lt_imp_lt (one_div_lt_one_div_of_lt ha) h theorem lt_of_one_div_lt_one_div (ha : 0 < a) (h : 1 / a < 1 / b) : b < a := lt_imp_lt_of_le_imp_le (one_div_le_one_div_of_le ha) h /-- For the single implications with fewer assumptions, see `one_div_le_one_div_of_le` and `le_of_one_div_le_one_div` -/ theorem one_div_le_one_div (ha : 0 < a) (hb : 0 < b) : 1 / a ≤ 1 / b ↔ b ≤ a := div_le_div_iff_of_pos_left zero_lt_one ha hb /-- For the single implications with fewer assumptions, see `one_div_lt_one_div_of_lt` and `lt_of_one_div_lt_one_div` -/ theorem one_div_lt_one_div (ha : 0 < a) (hb : 0 < b) : 1 / a < 1 / b ↔ b < a := div_lt_div_iff_of_pos_left zero_lt_one ha hb theorem one_lt_one_div (h1 : 0 < a) (h2 : a < 1) : 1 < 1 / a := by rwa [lt_one_div (@zero_lt_one α _ _ _ _ _) h1, one_div_one] theorem one_le_one_div (h1 : 0 < a) (h2 : a ≤ 1) : 1 ≤ 1 / a := by rwa [le_one_div (@zero_lt_one α _ _ _ _ _) h1, one_div_one] /-! ### Results about halving. The equalities also hold in semifields of characteristic `0`. -/ theorem half_pos (h : 0 < a) : 0 < a / 2 := div_pos h zero_lt_two theorem one_half_pos : (0 : α) < 1 / 2 := half_pos zero_lt_one @[simp] theorem half_le_self_iff : a / 2 ≤ a ↔ 0 ≤ a := by rw [div_le_iff₀ (zero_lt_two' α), mul_two, le_add_iff_nonneg_left] @[simp] theorem half_lt_self_iff : a / 2 < a ↔ 0 < a := by rw [div_lt_iff₀ (zero_lt_two' α), mul_two, lt_add_iff_pos_left] alias ⟨_, half_le_self⟩ := half_le_self_iff alias ⟨_, half_lt_self⟩ := half_lt_self_iff alias div_two_lt_of_pos := half_lt_self theorem one_half_lt_one : (1 / 2 : α) < 1 := half_lt_self zero_lt_one theorem two_inv_lt_one : (2⁻¹ : α) < 1 := (one_div _).symm.trans_lt one_half_lt_one theorem left_lt_add_div_two : a < (a + b) / 2 ↔ a < b := by simp [lt_div_iff₀, mul_two] theorem add_div_two_lt_right : (a + b) / 2 < b ↔ a < b := by simp [div_lt_iff₀, mul_two] theorem add_thirds (a : α) : a / 3 + a / 3 + a / 3 = a := by rw [div_add_div_same, div_add_div_same, ← two_mul, ← add_one_mul 2 a, two_add_one_eq_three, mul_div_cancel_left₀ a three_ne_zero] /-! ### Miscellaneous lemmas -/ @[simp] lemma div_pos_iff_of_pos_left (ha : 0 < a) : 0 < a / b ↔ 0 < b := by simp only [div_eq_mul_inv, mul_pos_iff_of_pos_left ha, inv_pos] @[simp] lemma div_pos_iff_of_pos_right (hb : 0 < b) : 0 < a / b ↔ 0 < a := by simp only [div_eq_mul_inv, mul_pos_iff_of_pos_right (inv_pos.2 hb)] theorem mul_le_mul_of_mul_div_le (h : a * (b / c) ≤ d) (hc : 0 < c) : b * a ≤ d * c := by rw [← mul_div_assoc] at h rwa [mul_comm b, ← div_le_iff₀ hc] theorem div_mul_le_div_mul_of_div_le_div (h : a / b ≤ c / d) (he : 0 ≤ e) : a / (b * e) ≤ c / (d * e) := by rw [div_mul_eq_div_mul_one_div, div_mul_eq_div_mul_one_div] exact mul_le_mul_of_nonneg_right h (one_div_nonneg.2 he) theorem exists_pos_mul_lt {a : α} (h : 0 < a) (b : α) : ∃ c : α, 0 < c ∧ b * c < a := by have : 0 < a / max (b + 1) 1 := div_pos h (lt_max_iff.2 (Or.inr zero_lt_one)) refine ⟨a / max (b + 1) 1, this, ?_⟩ rw [← lt_div_iff₀ this, div_div_cancel₀ h.ne'] exact lt_max_iff.2 (Or.inl <| lt_add_one _) theorem exists_pos_lt_mul {a : α} (h : 0 < a) (b : α) : ∃ c : α, 0 < c ∧ b < c * a := let ⟨c, hc₀, hc⟩ := exists_pos_mul_lt h b; ⟨c⁻¹, inv_pos.2 hc₀, by rwa [← div_eq_inv_mul, lt_div_iff₀ hc₀]⟩ lemma monotone_div_right_of_nonneg (ha : 0 ≤ a) : Monotone (· / a) := fun _b _c hbc ↦ div_le_div_of_nonneg_right hbc ha lemma strictMono_div_right_of_pos (ha : 0 < a) : StrictMono (· / a) := fun _b _c hbc ↦ div_lt_div_of_pos_right hbc ha theorem Monotone.div_const {β : Type*} [Preorder β] {f : β → α} (hf : Monotone f) {c : α} (hc : 0 ≤ c) : Monotone fun x => f x / c := (monotone_div_right_of_nonneg hc).comp hf theorem StrictMono.div_const {β : Type*} [Preorder β] {f : β → α} (hf : StrictMono f) {c : α} (hc : 0 < c) : StrictMono fun x => f x / c := by simpa only [div_eq_mul_inv] using hf.mul_const (inv_pos.2 hc) -- see Note [lower instance priority] instance (priority := 100) LinearOrderedSemiField.toDenselyOrdered : DenselyOrdered α where dense a₁ a₂ h := ⟨(a₁ + a₂) / 2, calc a₁ = (a₁ + a₁) / 2 := (add_self_div_two a₁).symm _ < (a₁ + a₂) / 2 := div_lt_div_of_pos_right (add_lt_add_left h _) zero_lt_two , calc (a₁ + a₂) / 2 < (a₂ + a₂) / 2 := div_lt_div_of_pos_right (add_lt_add_right h _) zero_lt_two _ = a₂ := add_self_div_two a₂ ⟩ theorem min_div_div_right {c : α} (hc : 0 ≤ c) (a b : α) : min (a / c) (b / c) = min a b / c := (monotone_div_right_of_nonneg hc).map_min.symm theorem max_div_div_right {c : α} (hc : 0 ≤ c) (a b : α) : max (a / c) (b / c) = max a b / c := (monotone_div_right_of_nonneg hc).map_max.symm theorem one_div_strictAntiOn : StrictAntiOn (fun x : α => 1 / x) (Set.Ioi 0) := fun _ x1 _ y1 xy => (one_div_lt_one_div (Set.mem_Ioi.mp y1) (Set.mem_Ioi.mp x1)).mpr xy theorem one_div_pow_le_one_div_pow_of_le (a1 : 1 ≤ a) {m n : ℕ} (mn : m ≤ n) : 1 / a ^ n ≤ 1 / a ^ m := by refine (one_div_le_one_div ?_ ?_).mpr (pow_right_mono₀ a1 mn) <;> exact pow_pos (zero_lt_one.trans_le a1) _ theorem one_div_pow_lt_one_div_pow_of_lt (a1 : 1 < a) {m n : ℕ} (mn : m < n) : 1 / a ^ n < 1 / a ^ m := by refine (one_div_lt_one_div ?_ ?_).2 (pow_lt_pow_right₀ a1 mn) <;> exact pow_pos (zero_lt_one.trans a1) _ theorem one_div_pow_anti (a1 : 1 ≤ a) : Antitone fun n : ℕ => 1 / a ^ n := fun _ _ => one_div_pow_le_one_div_pow_of_le a1 theorem one_div_pow_strictAnti (a1 : 1 < a) : StrictAnti fun n : ℕ => 1 / a ^ n := fun _ _ => one_div_pow_lt_one_div_pow_of_lt a1 theorem inv_strictAntiOn : StrictAntiOn (fun x : α => x⁻¹) (Set.Ioi 0) := fun _ hx _ hy xy => (inv_lt_inv₀ hy hx).2 xy theorem inv_pow_le_inv_pow_of_le (a1 : 1 ≤ a) {m n : ℕ} (mn : m ≤ n) : (a ^ n)⁻¹ ≤ (a ^ m)⁻¹ := by convert one_div_pow_le_one_div_pow_of_le a1 mn using 1 <;> simp theorem inv_pow_lt_inv_pow_of_lt (a1 : 1 < a) {m n : ℕ} (mn : m < n) : (a ^ n)⁻¹ < (a ^ m)⁻¹ := by convert one_div_pow_lt_one_div_pow_of_lt a1 mn using 1 <;> simp theorem inv_pow_anti (a1 : 1 ≤ a) : Antitone fun n : ℕ => (a ^ n)⁻¹ := fun _ _ => inv_pow_le_inv_pow_of_le a1 theorem inv_pow_strictAnti (a1 : 1 < a) : StrictAnti fun n : ℕ => (a ^ n)⁻¹ := fun _ _ => inv_pow_lt_inv_pow_of_lt a1 theorem le_iff_forall_one_lt_le_mul₀ {α : Type*} [Semifield α] [LinearOrder α] [IsStrictOrderedRing α] {a b : α} (hb : 0 ≤ b) : a ≤ b ↔ ∀ ε, 1 < ε → a ≤ b * ε := by refine ⟨fun h _ hε ↦ h.trans <| le_mul_of_one_le_right hb hε.le, fun h ↦ ?_⟩ obtain rfl|hb := hb.eq_or_lt · simp_rw [zero_mul] at h exact h 2 one_lt_two refine le_of_forall_gt_imp_ge_of_dense fun x hbx => ?_ convert h (x / b) ((one_lt_div hb).mpr hbx) rw [mul_div_cancel₀ _ hb.ne'] /-! ### Results about `IsGLB` -/ theorem IsGLB.mul_left {s : Set α} (ha : 0 ≤ a) (hs : IsGLB s b) : IsGLB ((fun b => a * b) '' s) (a * b) := by rcases lt_or_eq_of_le ha with (ha | rfl) · exact (OrderIso.mulLeft₀ _ ha).isGLB_image'.2 hs · simp_rw [zero_mul] rw [hs.nonempty.image_const] exact isGLB_singleton theorem IsGLB.mul_right {s : Set α} (ha : 0 ≤ a) (hs : IsGLB s b) : IsGLB ((fun b => b * a) '' s) (b * a) := by simpa [mul_comm] using hs.mul_left ha end LinearOrderedSemifield section variable [Field α] [LinearOrder α] [IsStrictOrderedRing α] {a b c d : α} {n : ℤ} /-! ### Lemmas about pos, nonneg, nonpos, neg -/ theorem div_pos_iff : 0 < a / b ↔ 0 < a ∧ 0 < b ∨ a < 0 ∧ b < 0 := by simp only [division_def, mul_pos_iff, inv_pos, inv_lt_zero] theorem div_neg_iff : a / b < 0 ↔ 0 < a ∧ b < 0 ∨ a < 0 ∧ 0 < b := by simp [division_def, mul_neg_iff] theorem div_nonneg_iff : 0 ≤ a / b ↔ 0 ≤ a ∧ 0 ≤ b ∨ a ≤ 0 ∧ b ≤ 0 := by simp [division_def, mul_nonneg_iff] theorem div_nonpos_iff : a / b ≤ 0 ↔ 0 ≤ a ∧ b ≤ 0 ∨ a ≤ 0 ∧ 0 ≤ b := by simp [division_def, mul_nonpos_iff] theorem div_nonneg_of_nonpos (ha : a ≤ 0) (hb : b ≤ 0) : 0 ≤ a / b := div_nonneg_iff.2 <| Or.inr ⟨ha, hb⟩ theorem div_pos_of_neg_of_neg (ha : a < 0) (hb : b < 0) : 0 < a / b := div_pos_iff.2 <| Or.inr ⟨ha, hb⟩ theorem div_neg_of_neg_of_pos (ha : a < 0) (hb : 0 < b) : a / b < 0 := div_neg_iff.2 <| Or.inr ⟨ha, hb⟩ theorem div_neg_of_pos_of_neg (ha : 0 < a) (hb : b < 0) : a / b < 0 := div_neg_iff.2 <| Or.inl ⟨ha, hb⟩ /-! ### Relating one division with another term -/ theorem div_le_iff_of_neg (hc : c < 0) : b / c ≤ a ↔ a * c ≤ b := ⟨fun h => div_mul_cancel₀ b (ne_of_lt hc) ▸ mul_le_mul_of_nonpos_right h hc.le, fun h => calc a = a * c * (1 / c) := mul_mul_div a (ne_of_lt hc) _ ≥ b * (1 / c) := mul_le_mul_of_nonpos_right h (one_div_neg.2 hc).le _ = b / c := (div_eq_mul_one_div b c).symm ⟩ theorem div_le_iff_of_neg' (hc : c < 0) : b / c ≤ a ↔ c * a ≤ b := by rw [mul_comm, div_le_iff_of_neg hc] theorem le_div_iff_of_neg (hc : c < 0) : a ≤ b / c ↔ b ≤ a * c := by rw [← neg_neg c, mul_neg, div_neg, le_neg, div_le_iff₀ (neg_pos.2 hc), neg_mul] theorem le_div_iff_of_neg' (hc : c < 0) : a ≤ b / c ↔ b ≤ c * a := by rw [mul_comm, le_div_iff_of_neg hc] theorem div_lt_iff_of_neg (hc : c < 0) : b / c < a ↔ a * c < b := lt_iff_lt_of_le_iff_le <| le_div_iff_of_neg hc theorem div_lt_iff_of_neg' (hc : c < 0) : b / c < a ↔ c * a < b := by rw [mul_comm, div_lt_iff_of_neg hc] theorem lt_div_iff_of_neg (hc : c < 0) : a < b / c ↔ b < a * c := lt_iff_lt_of_le_iff_le <| div_le_iff_of_neg hc theorem lt_div_iff_of_neg' (hc : c < 0) : a < b / c ↔ b < c * a := by rw [mul_comm, lt_div_iff_of_neg hc] theorem div_le_one_of_ge (h : b ≤ a) (hb : b ≤ 0) : a / b ≤ 1 := by simpa only [neg_div_neg_eq] using div_le_one_of_le₀ (neg_le_neg h) (neg_nonneg_of_nonpos hb) /-! ### Bi-implications of inequalities using inversions -/ theorem inv_le_inv_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ ≤ b⁻¹ ↔ b ≤ a := by rw [← one_div, div_le_iff_of_neg ha, ← div_eq_inv_mul, div_le_iff_of_neg hb, one_mul] theorem inv_le_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ ≤ b ↔ b⁻¹ ≤ a := by rw [← inv_le_inv_of_neg hb (inv_lt_zero.2 ha), inv_inv] theorem le_inv_of_neg (ha : a < 0) (hb : b < 0) : a ≤ b⁻¹ ↔ b ≤ a⁻¹ := by rw [← inv_le_inv_of_neg (inv_lt_zero.2 hb) ha, inv_inv] theorem inv_lt_inv_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ < b⁻¹ ↔ b < a := lt_iff_lt_of_le_iff_le (inv_le_inv_of_neg hb ha) theorem inv_lt_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ < b ↔ b⁻¹ < a := lt_iff_lt_of_le_iff_le (le_inv_of_neg hb ha) theorem lt_inv_of_neg (ha : a < 0) (hb : b < 0) : a < b⁻¹ ↔ b < a⁻¹ := lt_iff_lt_of_le_iff_le (inv_le_of_neg hb ha) /-! ### Monotonicity results involving inversion -/ theorem sub_inv_antitoneOn_Ioi : AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Ioi c) := antitoneOn_iff_forall_lt.mpr fun _ ha _ hb hab ↦ inv_le_inv₀ (sub_pos.mpr hb) (sub_pos.mpr ha) |>.mpr <| sub_le_sub (le_of_lt hab) le_rfl theorem sub_inv_antitoneOn_Iio : AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Iio c) := antitoneOn_iff_forall_lt.mpr fun _ ha _ hb hab ↦ inv_le_inv_of_neg (sub_neg.mpr hb) (sub_neg.mpr ha) |>.mpr <| sub_le_sub (le_of_lt hab) le_rfl theorem sub_inv_antitoneOn_Icc_right (ha : c < a) : AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Icc a b) := by by_cases hab : a ≤ b · exact sub_inv_antitoneOn_Ioi.mono <| (Set.Icc_subset_Ioi_iff hab).mpr ha · simp [hab, Set.Subsingleton.antitoneOn] theorem sub_inv_antitoneOn_Icc_left (ha : b < c) : AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Icc a b) := by by_cases hab : a ≤ b · exact sub_inv_antitoneOn_Iio.mono <| (Set.Icc_subset_Iio_iff hab).mpr ha · simp [hab, Set.Subsingleton.antitoneOn] theorem inv_antitoneOn_Ioi : AntitoneOn (fun x : α ↦ x⁻¹) (Set.Ioi 0) := by convert sub_inv_antitoneOn_Ioi (α := α) exact (sub_zero _).symm theorem inv_antitoneOn_Iio : AntitoneOn (fun x : α ↦ x⁻¹) (Set.Iio 0) := by convert sub_inv_antitoneOn_Iio (α := α) exact (sub_zero _).symm theorem inv_antitoneOn_Icc_right (ha : 0 < a) : AntitoneOn (fun x : α ↦ x⁻¹) (Set.Icc a b) := by convert sub_inv_antitoneOn_Icc_right ha exact (sub_zero _).symm theorem inv_antitoneOn_Icc_left (hb : b < 0) : AntitoneOn (fun x : α ↦ x⁻¹) (Set.Icc a b) := by convert sub_inv_antitoneOn_Icc_left hb exact (sub_zero _).symm /-! ### Relating two divisions -/ theorem div_le_div_of_nonpos_of_le (hc : c ≤ 0) (h : b ≤ a) : a / c ≤ b / c := by rw [div_eq_mul_one_div a c, div_eq_mul_one_div b c] exact mul_le_mul_of_nonpos_right h (one_div_nonpos.2 hc) theorem div_lt_div_of_neg_of_lt (hc : c < 0) (h : b < a) : a / c < b / c := by rw [div_eq_mul_one_div a c, div_eq_mul_one_div b c] exact mul_lt_mul_of_neg_right h (one_div_neg.2 hc) theorem div_le_div_right_of_neg (hc : c < 0) : a / c ≤ b / c ↔ b ≤ a := ⟨le_imp_le_of_lt_imp_lt <| div_lt_div_of_neg_of_lt hc, div_le_div_of_nonpos_of_le <| hc.le⟩ theorem div_lt_div_right_of_neg (hc : c < 0) : a / c < b / c ↔ b < a := lt_iff_lt_of_le_iff_le <| div_le_div_right_of_neg hc /-! ### Relating one division and involving `1` -/ theorem one_le_div_of_neg (hb : b < 0) : 1 ≤ a / b ↔ a ≤ b := by rw [le_div_iff_of_neg hb, one_mul] theorem div_le_one_of_neg (hb : b < 0) : a / b ≤ 1 ↔ b ≤ a := by rw [div_le_iff_of_neg hb, one_mul] theorem one_lt_div_of_neg (hb : b < 0) : 1 < a / b ↔ a < b := by rw [lt_div_iff_of_neg hb, one_mul] theorem div_lt_one_of_neg (hb : b < 0) : a / b < 1 ↔ b < a := by rw [div_lt_iff_of_neg hb, one_mul] theorem one_div_le_of_neg (ha : a < 0) (hb : b < 0) : 1 / a ≤ b ↔ 1 / b ≤ a := by simpa using inv_le_of_neg ha hb theorem one_div_lt_of_neg (ha : a < 0) (hb : b < 0) : 1 / a < b ↔ 1 / b < a := by simpa using inv_lt_of_neg ha hb theorem le_one_div_of_neg (ha : a < 0) (hb : b < 0) : a ≤ 1 / b ↔ b ≤ 1 / a := by simpa using le_inv_of_neg ha hb theorem lt_one_div_of_neg (ha : a < 0) (hb : b < 0) : a < 1 / b ↔ b < 1 / a := by simpa using lt_inv_of_neg ha hb theorem one_lt_div_iff : 1 < a / b ↔ 0 < b ∧ b < a ∨ b < 0 ∧ a < b := by rcases lt_trichotomy b 0 with (hb | rfl | hb) · simp [hb, hb.not_lt, one_lt_div_of_neg] · simp [lt_irrefl, zero_le_one] · simp [hb, hb.not_lt, one_lt_div] theorem one_le_div_iff : 1 ≤ a / b ↔ 0 < b ∧ b ≤ a ∨ b < 0 ∧ a ≤ b := by rcases lt_trichotomy b 0 with (hb | rfl | hb) · simp [hb, hb.not_lt, one_le_div_of_neg] · simp [lt_irrefl, zero_lt_one.not_le, zero_lt_one] · simp [hb, hb.not_lt, one_le_div] theorem div_lt_one_iff : a / b < 1 ↔ 0 < b ∧ a < b ∨ b = 0 ∨ b < 0 ∧ b < a := by rcases lt_trichotomy b 0 with (hb | rfl | hb) · simp [hb, hb.not_lt, hb.ne, div_lt_one_of_neg] · simp [zero_lt_one] · simp [hb, hb.not_lt, div_lt_one, hb.ne.symm] theorem div_le_one_iff : a / b ≤ 1 ↔ 0 < b ∧ a ≤ b ∨ b = 0 ∨ b < 0 ∧ b ≤ a := by rcases lt_trichotomy b 0 with (hb | rfl | hb) · simp [hb, hb.not_lt, hb.ne, div_le_one_of_neg] · simp [zero_le_one] · simp [hb, hb.not_lt, div_le_one, hb.ne.symm] /-! ### Relating two divisions, involving `1` -/ theorem one_div_le_one_div_of_neg_of_le (hb : b < 0) (h : a ≤ b) : 1 / b ≤ 1 / a := by rwa [div_le_iff_of_neg' hb, ← div_eq_mul_one_div, div_le_one_of_neg (h.trans_lt hb)] theorem one_div_lt_one_div_of_neg_of_lt (hb : b < 0) (h : a < b) : 1 / b < 1 / a := by rwa [div_lt_iff_of_neg' hb, ← div_eq_mul_one_div, div_lt_one_of_neg (h.trans hb)] theorem le_of_neg_of_one_div_le_one_div (hb : b < 0) (h : 1 / a ≤ 1 / b) : b ≤ a := le_imp_le_of_lt_imp_lt (one_div_lt_one_div_of_neg_of_lt hb) h theorem lt_of_neg_of_one_div_lt_one_div (hb : b < 0) (h : 1 / a < 1 / b) : b < a := lt_imp_lt_of_le_imp_le (one_div_le_one_div_of_neg_of_le hb) h
/-- For the single implications with fewer assumptions, see `one_div_lt_one_div_of_neg_of_lt` and `lt_of_one_div_lt_one_div` -/ theorem one_div_le_one_div_of_neg (ha : a < 0) (hb : b < 0) : 1 / a ≤ 1 / b ↔ b ≤ a := by simpa [one_div] using inv_le_inv_of_neg ha hb
Mathlib/Algebra/Order/Field/Basic.lean
511
515
/- 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 -/ import Mathlib.Algebra.Polynomial.Identities import Mathlib.Analysis.SpecificLimits.Basic import Mathlib.NumberTheory.Padics.PadicIntegers import Mathlib.Topology.Algebra.Polynomial import Mathlib.Topology.MetricSpace.CauSeqFilter /-! # Hensel's lemma on ℤ_p This file proves Hensel's lemma on ℤ_p, roughly following Keith Conrad's writeup: <http://www.math.uconn.edu/~kconrad/blurbs/gradnumthy/hensel.pdf> Hensel's lemma gives a simple condition for the existence of a root of a polynomial. The proof and motivation are described in the paper [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019]. ## References * <http://www.math.uconn.edu/~kconrad/blurbs/gradnumthy/hensel.pdf> * [R. Y. Lewis, *A formal proof of Hensel's lemma over the p-adic integers*][lewis2019] * <https://en.wikipedia.org/wiki/Hensel%27s_lemma> ## Tags p-adic, p adic, padic, p-adic integer -/ noncomputable section open Topology -- We begin with some general lemmas that are used below in the computation. theorem padic_polynomial_dist {p : ℕ} [Fact p.Prime] (F : Polynomial ℤ_[p]) (x y : ℤ_[p]) : ‖F.eval x - F.eval y‖ ≤ ‖x - y‖ := let ⟨z, hz⟩ := F.evalSubFactor x y calc ‖F.eval x - F.eval y‖ = ‖z‖ * ‖x - y‖ := by simp [hz] _ ≤ 1 * ‖x - y‖ := by gcongr; apply PadicInt.norm_le_one _ = ‖x - y‖ := by simp open Filter Metric private theorem comp_tendsto_lim {p : ℕ} [Fact p.Prime] {F : Polynomial ℤ_[p]} (ncs : CauSeq ℤ_[p] norm) : Tendsto (fun i => F.eval (ncs i)) atTop (𝓝 (F.eval ncs.lim)) := Filter.Tendsto.comp (@Polynomial.continuousAt _ _ _ _ F _) ncs.tendsto_limit section variable {p : ℕ} [Fact p.Prime] {ncs : CauSeq ℤ_[p] norm} {F : Polynomial ℤ_[p]} {a : ℤ_[p]} (ncs_der_val : ∀ n, ‖F.derivative.eval (ncs n)‖ = ‖F.derivative.eval a‖) private theorem ncs_tendsto_lim : Tendsto (fun i => ‖F.derivative.eval (ncs i)‖) atTop (𝓝 ‖F.derivative.eval ncs.lim‖) := Tendsto.comp (continuous_iff_continuousAt.1 continuous_norm _) (comp_tendsto_lim _) include ncs_der_val private theorem ncs_tendsto_const : Tendsto (fun i => ‖F.derivative.eval (ncs i)‖) atTop (𝓝 ‖F.derivative.eval a‖) := by convert @tendsto_const_nhds ℝ _ ℕ _ _; rw [ncs_der_val] private theorem norm_deriv_eq : ‖F.derivative.eval ncs.lim‖ = ‖F.derivative.eval a‖ := tendsto_nhds_unique ncs_tendsto_lim (ncs_tendsto_const ncs_der_val) end section variable {p : ℕ} [Fact p.Prime] {ncs : CauSeq ℤ_[p] norm} {F : Polynomial ℤ_[p]} (hnorm : Tendsto (fun i => ‖F.eval (ncs i)‖) atTop (𝓝 0)) include hnorm private theorem tendsto_zero_of_norm_tendsto_zero : Tendsto (fun i => F.eval (ncs i)) atTop (𝓝 0) := tendsto_iff_norm_sub_tendsto_zero.2 (by simpa using hnorm) theorem limit_zero_of_norm_tendsto_zero : F.eval ncs.lim = 0 := tendsto_nhds_unique (comp_tendsto_lim _) (tendsto_zero_of_norm_tendsto_zero hnorm) end section Hensel open Nat variable (p : ℕ) [Fact p.Prime] (F : Polynomial ℤ_[p]) (a : ℤ_[p]) /-- `T` is an auxiliary value that is used to control the behavior of the polynomial `F`. -/ private def T_gen : ℝ := ‖F.eval a / ((F.derivative.eval a ^ 2 : ℤ_[p]) : ℚ_[p])‖ local notation "T" => @T_gen p _ F a variable {p F a} private theorem T_def : T = ‖F.eval a‖ / ‖F.derivative.eval a‖ ^ 2 := by simp [T_gen, ← PadicInt.norm_def] private theorem T_nonneg : 0 ≤ T := norm_nonneg _ private theorem T_pow_nonneg (n : ℕ) : 0 ≤ T ^ n := pow_nonneg T_nonneg _ variable (hnorm : ‖F.eval a‖ < ‖F.derivative.eval a‖ ^ 2) include hnorm private theorem deriv_sq_norm_pos : 0 < ‖F.derivative.eval a‖ ^ 2 := lt_of_le_of_lt (norm_nonneg _) hnorm private theorem deriv_sq_norm_ne_zero : ‖F.derivative.eval a‖ ^ 2 ≠ 0 := ne_of_gt (deriv_sq_norm_pos hnorm) private theorem deriv_norm_ne_zero : ‖F.derivative.eval a‖ ≠ 0 := fun h => deriv_sq_norm_ne_zero hnorm (by simp [*, sq]) private theorem deriv_norm_pos : 0 < ‖F.derivative.eval a‖ := lt_of_le_of_ne (norm_nonneg _) (Ne.symm (deriv_norm_ne_zero hnorm))
private theorem deriv_ne_zero : F.derivative.eval a ≠ 0 := mt norm_eq_zero.2 (deriv_norm_ne_zero hnorm)
Mathlib/NumberTheory/Padics/Hensel.lean
124
125
/- Copyright (c) 2019 Reid Barton. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Reid Barton, Johan Commelin, Bhavik Mehta -/ import Mathlib.CategoryTheory.Equivalence import Mathlib.CategoryTheory.Yoneda /-! # Adjunctions between functors `F ⊣ G` represents the data of an adjunction between two functors `F : C ⥤ D` and `G : D ⥤ C`. `F` is the left adjoint and `G` is the right adjoint. We provide various useful constructors: * `mkOfHomEquiv` * `mk'`: construct an adjunction from the data of a hom set equivalence, unit and counit natural transformations together with proofs of the equalities `homEquiv_unit` and `homEquiv_counit` relating them to each other. * `leftAdjointOfEquiv` / `rightAdjointOfEquiv` construct a left/right adjoint of a given functor given the action on objects and the relevant equivalence of morphism spaces. * `adjunctionOfEquivLeft` / `adjunctionOfEquivRight` witness that these constructions give adjunctions. There are also typeclasses `IsLeftAdjoint` / `IsRightAdjoint`, which asserts the existence of a adjoint functor. Given `[F.IsLeftAdjoint]`, a chosen right adjoint can be obtained as `F.rightAdjoint`. `Adjunction.comp` composes adjunctions. `toEquivalence` upgrades an adjunction to an equivalence, given witnesses that the unit and counit are pointwise isomorphisms. Conversely `Equivalence.toAdjunction` recovers the underlying adjunction from an equivalence. ## Overview of the directory `CategoryTheory.Adjunction` * Adjoint lifting theorems are in the directory `Lifting`. * The file `AdjointFunctorTheorems` proves the adjoint functor theorems. * The file `Comma` shows that for a functor `G : D ⥤ C` the data of an initial object in each `StructuredArrow` category on `G` is equivalent to a left adjoint to `G`, as well as the dual. * The file `Evaluation` shows that products and coproducts are adjoint to evaluation of functors. * The file `FullyFaithful` characterizes when adjoints are full or faithful in terms of the unit and counit. * The file `Limits` proves that left adjoints preserve colimits and right adjoints preserve limits. * The file `Mates` establishes the bijection between the 2-cells ``` L₁ R₁ C --→ D C ←-- D G ↓ ↗ ↓ H G ↓ ↘ ↓ H E --→ F E ←-- F L₂ R₂ ``` where `L₁ ⊣ R₁` and `L₂ ⊣ R₂`. Specializing to a pair of adjoints `L₁ L₂ : C ⥤ D`, `R₁ R₂ : D ⥤ C`, it provides equivalences `(L₂ ⟶ L₁) ≃ (R₁ ⟶ R₂)` and `(L₂ ≅ L₁) ≃ (R₁ ≅ R₂)`. * The file `Opposites` contains constructions to relate adjunctions of functors to adjunctions of their opposites. * The file `Reflective` defines reflective functors, i.e. fully faithful right adjoints. Note that many facts about reflective functors are proved in the earlier file `FullyFaithful`. * The file `Restrict` defines the restriction of an adjunction along fully faithful functors. * The file `Triple` proves that in an adjoint triple, the left adjoint is fully faithful if and only if the right adjoint is. * The file `Unique` proves uniqueness of adjoints. * The file `Whiskering` proves that functors `F : D ⥤ E` and `G : E ⥤ D` with an adjunction `F ⊣ G`, induce adjunctions between the functor categories `C ⥤ D` and `C ⥤ E`, and the functor categories `E ⥤ C` and `D ⥤ C`. ## Other files related to adjunctions * The file `CategoryTheory.Monad.Adjunction` develops the basic relationship between adjunctions and (co)monads. There it is also shown that given an adjunction `L ⊣ R` and an isomorphism `L ⋙ R ≅ 𝟭 C`, the unit is an isomorphism, and similarly for the counit. -/ namespace CategoryTheory open Category -- declare the `v`'s first; see `CategoryTheory.Category` for an explanation universe v₁ v₂ v₃ u₁ u₂ u₃ variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D] /-- `F ⊣ G` represents the data of an adjunction between two functors `F : C ⥤ D` and `G : D ⥤ C`. `F` is the left adjoint and `G` is the right adjoint. We use the unit-counit definition of an adjunction. There is a constructor `Adjunction.mk'` which constructs an adjunction from the data of a hom set equivalence, a unit, and a counit, together with proofs of the equalities `homEquiv_unit` and `homEquiv_counit` relating them to each other. There is also a constructor `Adjunction.mkOfHomEquiv` which constructs an adjunction from a natural hom set equivalence. To construct adjoints to a given functor, there are constructors `leftAdjointOfEquiv` and `adjunctionOfEquivLeft` (as well as their duals). -/ @[stacks 0037] structure Adjunction (F : C ⥤ D) (G : D ⥤ C) where /-- The unit of an adjunction -/ unit : 𝟭 C ⟶ F.comp G /-- The counit of an adjunction -/ counit : G.comp F ⟶ 𝟭 D /-- Equality of the composition of the unit and counit with the identity `F ⟶ FGF ⟶ F = 𝟙` -/ left_triangle_components (X : C) : F.map (unit.app X) ≫ counit.app (F.obj X) = 𝟙 (F.obj X) := by aesop_cat /-- Equality of the composition of the unit and counit with the identity `G ⟶ GFG ⟶ G = 𝟙` -/ right_triangle_components (Y : D) : unit.app (G.obj Y) ≫ G.map (counit.app Y) = 𝟙 (G.obj Y) := by aesop_cat /-- The notation `F ⊣ G` stands for `Adjunction F G` representing that `F` is left adjoint to `G` -/ infixl:15 " ⊣ " => Adjunction namespace Functor /-- A class asserting the existence of a right adjoint. -/ class IsLeftAdjoint (left : C ⥤ D) : Prop where exists_rightAdjoint : ∃ (right : D ⥤ C), Nonempty (left ⊣ right) /-- A class asserting the existence of a left adjoint. -/ class IsRightAdjoint (right : D ⥤ C) : Prop where exists_leftAdjoint : ∃ (left : C ⥤ D), Nonempty (left ⊣ right) /-- A chosen left adjoint to a functor that is a right adjoint. -/ noncomputable def leftAdjoint (R : D ⥤ C) [IsRightAdjoint R] : C ⥤ D := (IsRightAdjoint.exists_leftAdjoint (right := R)).choose /-- A chosen right adjoint to a functor that is a left adjoint. -/ noncomputable def rightAdjoint (L : C ⥤ D) [IsLeftAdjoint L] : D ⥤ C := (IsLeftAdjoint.exists_rightAdjoint (left := L)).choose end Functor /-- The adjunction associated to a functor known to be a left adjoint. -/ noncomputable def Adjunction.ofIsLeftAdjoint (left : C ⥤ D) [left.IsLeftAdjoint] : left ⊣ left.rightAdjoint := Functor.IsLeftAdjoint.exists_rightAdjoint.choose_spec.some /-- The adjunction associated to a functor known to be a right adjoint. -/ noncomputable def Adjunction.ofIsRightAdjoint (right : C ⥤ D) [right.IsRightAdjoint] : right.leftAdjoint ⊣ right := Functor.IsRightAdjoint.exists_leftAdjoint.choose_spec.some namespace Adjunction attribute [reassoc (attr := simp)] left_triangle_components right_triangle_components /-- The hom set equivalence associated to an adjunction. -/ @[simps -isSimp] def homEquiv {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) (X : C) (Y : D) : (F.obj X ⟶ Y) ≃ (X ⟶ G.obj Y) where toFun := fun f => adj.unit.app X ≫ G.map f invFun := fun g => F.map g ≫ adj.counit.app Y left_inv := fun f => by dsimp rw [F.map_comp, assoc, ← Functor.comp_map, adj.counit.naturality, ← assoc] simp right_inv := fun g => by simp only [Functor.comp_obj, Functor.map_comp] rw [← assoc, ← Functor.comp_map, ← adj.unit.naturality] simp alias homEquiv_unit := homEquiv_apply alias homEquiv_counit := homEquiv_symm_apply end Adjunction -- These lemmas are not global simp lemmas because certain adjunctions -- are constructed using `Adjunction.mkOfHomEquiv`, and we certainly -- do not want `dsimp` to apply `homEquiv_unit` or `homEquiv_counit` -- in that case. However, when proving general API results about adjunctions, -- it may be advisable to add a local simp attribute to these lemmas. attribute [local simp] Adjunction.homEquiv_unit Adjunction.homEquiv_counit namespace Adjunction @[ext] lemma ext {F : C ⥤ D} {G : D ⥤ C} {adj adj' : F ⊣ G} (h : adj.unit = adj'.unit) : adj = adj' := by suffices h' : adj.counit = adj'.counit by cases adj; cases adj'; aesop ext X apply (adj.homEquiv _ _).injective rw [Adjunction.homEquiv_unit, Adjunction.homEquiv_unit, Adjunction.right_triangle_components, h, Adjunction.right_triangle_components] section variable {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G) lemma isLeftAdjoint (adj : F ⊣ G) : F.IsLeftAdjoint := ⟨_, ⟨adj⟩⟩ lemma isRightAdjoint (adj : F ⊣ G) : G.IsRightAdjoint := ⟨_, ⟨adj⟩⟩ instance (R : D ⥤ C) [R.IsRightAdjoint] : R.leftAdjoint.IsLeftAdjoint := (ofIsRightAdjoint R).isLeftAdjoint instance (L : C ⥤ D) [L.IsLeftAdjoint] : L.rightAdjoint.IsRightAdjoint := (ofIsLeftAdjoint L).isRightAdjoint variable {X' X : C} {Y Y' : D} theorem homEquiv_id (X : C) : adj.homEquiv X _ (𝟙 _) = adj.unit.app X := by simp theorem homEquiv_symm_id (X : D) : (adj.homEquiv _ X).symm (𝟙 _) = adj.counit.app X := by simp theorem homEquiv_naturality_left_symm (f : X' ⟶ X) (g : X ⟶ G.obj Y) : (adj.homEquiv X' Y).symm (f ≫ g) = F.map f ≫ (adj.homEquiv X Y).symm g := by simp theorem homEquiv_naturality_left (f : X' ⟶ X) (g : F.obj X ⟶ Y) : (adj.homEquiv X' Y) (F.map f ≫ g) = f ≫ (adj.homEquiv X Y) g := by rw [← Equiv.eq_symm_apply] simp only [Equiv.symm_apply_apply, eq_self_iff_true, homEquiv_naturality_left_symm] theorem homEquiv_naturality_right (f : F.obj X ⟶ Y) (g : Y ⟶ Y') : (adj.homEquiv X Y') (f ≫ g) = (adj.homEquiv X Y) f ≫ G.map g := by simp theorem homEquiv_naturality_right_symm (f : X ⟶ G.obj Y) (g : Y ⟶ Y') : (adj.homEquiv X Y').symm (f ≫ G.map g) = (adj.homEquiv X Y).symm f ≫ g := by rw [Equiv.symm_apply_eq] simp only [homEquiv_naturality_right, eq_self_iff_true, Equiv.apply_symm_apply] @[reassoc] theorem homEquiv_naturality_left_square (f : X' ⟶ X) (g : F.obj X ⟶ Y') (h : F.obj X' ⟶ Y) (k : Y ⟶ Y') (w : F.map f ≫ g = h ≫ k) : f ≫ (adj.homEquiv X Y') g = (adj.homEquiv X' Y) h ≫ G.map k := by rw [← homEquiv_naturality_left, ← homEquiv_naturality_right, w] @[reassoc] theorem homEquiv_naturality_right_square (f : X' ⟶ X) (g : X ⟶ G.obj Y') (h : X' ⟶ G.obj Y) (k : Y ⟶ Y') (w : f ≫ g = h ≫ G.map k) : F.map f ≫ (adj.homEquiv X Y').symm g = (adj.homEquiv X' Y).symm h ≫ k := by rw [← homEquiv_naturality_left_symm, ← homEquiv_naturality_right_symm, w] theorem homEquiv_naturality_left_square_iff (f : X' ⟶ X) (g : F.obj X ⟶ Y') (h : F.obj X' ⟶ Y) (k : Y ⟶ Y') : (f ≫ (adj.homEquiv X Y') g = (adj.homEquiv X' Y) h ≫ G.map k) ↔ (F.map f ≫ g = h ≫ k) := ⟨fun w ↦ by simpa only [Equiv.symm_apply_apply] using homEquiv_naturality_right_square adj _ _ _ _ w, homEquiv_naturality_left_square adj f g h k⟩ theorem homEquiv_naturality_right_square_iff (f : X' ⟶ X) (g : X ⟶ G.obj Y') (h : X' ⟶ G.obj Y) (k : Y ⟶ Y') : (F.map f ≫ (adj.homEquiv X Y').symm g = (adj.homEquiv X' Y).symm h ≫ k) ↔ (f ≫ g = h ≫ G.map k) := ⟨fun w ↦ by simpa only [Equiv.apply_symm_apply] using homEquiv_naturality_left_square adj _ _ _ _ w, homEquiv_naturality_right_square adj f g h k⟩ @[simp] theorem left_triangle : whiskerRight adj.unit F ≫ whiskerLeft F adj.counit = 𝟙 _ := by ext; simp @[simp] theorem right_triangle : whiskerLeft G adj.unit ≫ whiskerRight adj.counit G = 𝟙 _ := by ext; simp @[reassoc (attr := simp)] theorem counit_naturality {X Y : D} (f : X ⟶ Y) : F.map (G.map f) ≫ adj.counit.app Y = adj.counit.app X ≫ f := adj.counit.naturality f
@[reassoc (attr := simp)] theorem unit_naturality {X Y : C} (f : X ⟶ Y) : adj.unit.app X ≫ G.map (F.map f) = f ≫ adj.unit.app Y := (adj.unit.naturality f).symm lemma unit_comp_map_eq_iff {A : C} {B : D} (f : F.obj A ⟶ B) (g : A ⟶ G.obj B) :
Mathlib/CategoryTheory/Adjunction/Basic.lean
264
270
/- Copyright (c) 2024 Joël Riou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joël Riou -/ import Mathlib.Algebra.Homology.HomotopyCategory.HomologicalFunctor import Mathlib.Algebra.Homology.HomotopyCategory.ShiftSequence import Mathlib.Algebra.Homology.HomotopyCategory.SingleFunctors import Mathlib.Algebra.Homology.HomotopyCategory.Triangulated import Mathlib.Algebra.Homology.Localization /-! # The derived category of an abelian category In this file, we construct the derived category `DerivedCategory C` of an abelian category `C`. It is equipped with a triangulated structure. The derived category is defined here as the localization of cochain complexes indexed by `ℤ` with respect to quasi-isomorphisms: it is a type synonym of `HomologicalComplexUpToQuasiIso C (ComplexShape.up ℤ)`. Then, we have a localization functor `DerivedCategory.Q : CochainComplex C ℤ ⥤ DerivedCategory C`. It was already shown in the file `Algebra.Homology.Localization` that the induced functor `DerivedCategory.Qh : HomotopyCategory C (ComplexShape.up ℤ) ⥤ DerivedCategory C` is a localization functor with respect to the class of morphisms `HomotopyCategory.quasiIso C (ComplexShape.up ℤ)`. In the lemma `HomotopyCategory.quasiIso_eq_subcategoryAcyclic_W` we obtain that this class of morphisms consists of morphisms whose cone belongs to the triangulated subcategory `HomotopyCategory.subcategoryAcyclic C` of acyclic complexes. Then, the triangulated structure on `DerivedCategory C` is deduced from the triangulated structure on the homotopy category (see file `Algebra.Homology.HomotopyCategory.Triangulated`) using the localization theorem for triangulated categories which was obtained in the file `CategoryTheory.Localization.Triangulated`. ## Implementation notes If `C : Type u` and `Category.{v} C`, the constructed localized category of cochain complexes with respect to quasi-isomorphisms has morphisms in `Type (max u v)`. However, in certain circumstances, it shall be possible to prove that they are `v`-small (when `C` is a Grothendieck abelian category (e.g. the category of modules over a ring), it should be so by a theorem of Hovey.). Then, when working with derived categories in mathlib, the user should add the variable `[HasDerivedCategory.{w} C]` which is the assumption that there is a chosen derived category with morphisms in `Type w`. When derived categories are used in order to prove statements which do not involve derived categories, the `HasDerivedCategory.{max u v}` instance should be obtained at the beginning of the proof, using the term `HasDerivedCategory.standard C`. ## TODO (@joelriou) - construct the distinguished triangle associated to a short exact sequence of cochain complexes (done), and compare the associated connecting homomorphism with the one defined in `Algebra.Homology.HomologySequence`. ## References * [Jean-Louis Verdier, *Des catégories dérivées des catégories abéliennes*][verdier1996] * [Mark Hovey, *Model category structures on chain complexes of sheaves*][hovey-2001] -/ assert_not_exists TwoSidedIdeal universe w v u open CategoryTheory Limits Pretriangulated variable (C : Type u) [Category.{v} C] [Abelian C] namespace HomotopyCategory /-- The triangulated subcategory of `HomotopyCategory C (ComplexShape.up ℤ)` consisting of acyclic complexes. -/ def subcategoryAcyclic : Triangulated.Subcategory (HomotopyCategory C (ComplexShape.up ℤ)) := (homologyFunctor C (ComplexShape.up ℤ) 0).homologicalKernel instance : (subcategoryAcyclic C).P.IsClosedUnderIsomorphisms := by dsimp [subcategoryAcyclic] infer_instance variable {C} lemma mem_subcategoryAcyclic_iff (X : HomotopyCategory C (ComplexShape.up ℤ)) : (subcategoryAcyclic C).P X ↔ ∀ (n : ℤ), IsZero ((homologyFunctor _ _ n).obj X) := Functor.mem_homologicalKernel_iff _ X
lemma quotient_obj_mem_subcategoryAcyclic_iff_exactAt (K : CochainComplex C ℤ) : (subcategoryAcyclic C).P ((quotient _ _).obj K) ↔ ∀ (n : ℤ), K.ExactAt n := by rw [mem_subcategoryAcyclic_iff] refine forall_congr' (fun n => ?_) simp only [HomologicalComplex.exactAt_iff_isZero_homology] exact ((homologyFunctorFactors C (ComplexShape.up ℤ) n).app K).isZero_iff
Mathlib/Algebra/Homology/DerivedCategory/Basic.lean
85
90
/- Copyright (c) 2021 Eric Wieser. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Eric Wieser -/ import Mathlib.Algebra.CharP.Lemmas import Mathlib.GroupTheory.OrderOfElement /-! # Lemmas about rings of characteristic two This file contains results about `CharP R 2`, in the `CharTwo` namespace. The lemmas in this file with a `_sq` suffix are just special cases of the `_pow_char` lemmas elsewhere, with a shorter name for ease of discovery, and no need for a `[Fact (Prime 2)]` argument. -/ assert_not_exists Algebra LinearMap variable {R ι : Type*} namespace CharTwo section AddMonoidWithOne variable [AddMonoidWithOne R] theorem two_eq_zero [CharP R 2] : (2 : R) = 0 := by rw [← Nat.cast_two, CharP.cast_eq_zero] /-- The only hypotheses required to build a `CharP R 2` instance are `1 ≠ 0` and `2 = 0`. -/ theorem of_one_ne_zero_of_two_eq_zero (h₁ : (1 : R) ≠ 0) (h₂ : (2 : R) = 0) : CharP R 2 where cast_eq_zero_iff n := by obtain hn | hn := Nat.even_or_odd n · simp_rw [hn.two_dvd, iff_true] exact natCast_eq_zero_of_even_of_two_eq_zero hn h₂ · simp_rw [hn.not_two_dvd_nat, iff_false] rwa [natCast_eq_one_of_odd_of_two_eq_zero hn h₂] end AddMonoidWithOne section Semiring variable [Semiring R] [CharP R 2] @[scoped simp] theorem add_self_eq_zero (x : R) : x + x = 0 := by rw [← two_smul R x, two_eq_zero, zero_smul] @[scoped simp] protected theorem two_nsmul (x : R) : 2 • x = 0 := by rw [two_smul, add_self_eq_zero] end Semiring section Ring variable [Ring R] [CharP R 2] @[scoped simp] theorem neg_eq (x : R) : -x = x := by rw [neg_eq_iff_add_eq_zero, add_self_eq_zero] theorem neg_eq' : Neg.neg = (id : R → R) := funext neg_eq @[scoped simp] theorem sub_eq_add (x y : R) : x - y = x + y := by rw [sub_eq_add_neg, neg_eq] @[deprecated sub_eq_add (since := "2024-10-24")] theorem sub_eq_add' : HSub.hSub = (· + · : R → R → R) := funext₂ sub_eq_add theorem add_eq_iff_eq_add {a b c : R} : a + b = c ↔ a = c + b := by rw [← sub_eq_iff_eq_add, sub_eq_add]
Mathlib/Algebra/CharP/Two.lean
74
74
/- Copyright (c) 2021 Hunter Monroe. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Hunter Monroe, Kyle Miller, Alena Gusakov -/ import Mathlib.Combinatorics.SimpleGraph.DeleteEdges import Mathlib.Data.Fintype.Powerset /-! # Subgraphs of a simple graph A subgraph of a simple graph consists of subsets of the graph's vertices and edges such that the endpoints of each edge are present in the vertex subset. The edge subset is formalized as a sub-relation of the adjacency relation of the simple graph. ## Main definitions * `Subgraph G` is the type of subgraphs of a `G : SimpleGraph V`. * `Subgraph.neighborSet`, `Subgraph.incidenceSet`, and `Subgraph.degree` are like their `SimpleGraph` counterparts, but they refer to vertices from `G` to avoid subtype coercions. * `Subgraph.coe` is the coercion from a `G' : Subgraph G` to a `SimpleGraph G'.verts`. (In Lean 3 this could not be a `Coe` instance since the destination type depends on `G'`.) * `Subgraph.IsSpanning` for whether a subgraph is a spanning subgraph and `Subgraph.IsInduced` for whether a subgraph is an induced subgraph. * Instances for `Lattice (Subgraph G)` and `BoundedOrder (Subgraph G)`. * `SimpleGraph.toSubgraph`: If a `SimpleGraph` is a subgraph of another, then you can turn it into a member of the larger graph's `SimpleGraph.Subgraph` type. * Graph homomorphisms from a subgraph to a graph (`Subgraph.map_top`) and between subgraphs (`Subgraph.map`). ## Implementation notes * Recall that subgraphs are not determined by their vertex sets, so `SetLike` does not apply to this kind of subobject. ## TODO * Images of graph homomorphisms as subgraphs. -/ universe u v namespace SimpleGraph /-- A subgraph of a `SimpleGraph` is a subset of vertices along with a restriction of the adjacency relation that is symmetric and is supported by the vertex subset. They also form a bounded lattice. Thinking of `V → V → Prop` as `Set (V × V)`, a set of darts (i.e., half-edges), then `Subgraph.adj_sub` is that the darts of a subgraph are a subset of the darts of `G`. -/ @[ext] structure Subgraph {V : Type u} (G : SimpleGraph V) where /-- Vertices of the subgraph -/ verts : Set V /-- Edges of the subgraph -/ Adj : V → V → Prop adj_sub : ∀ {v w : V}, Adj v w → G.Adj v w edge_vert : ∀ {v w : V}, Adj v w → v ∈ verts symm : Symmetric Adj := by aesop_graph -- Porting note: Originally `by obviously` initialize_simps_projections SimpleGraph.Subgraph (Adj → adj) variable {ι : Sort*} {V : Type u} {W : Type v} /-- The one-vertex subgraph. -/ @[simps] protected def singletonSubgraph (G : SimpleGraph V) (v : V) : G.Subgraph where verts := {v} Adj := ⊥ adj_sub := False.elim edge_vert := False.elim symm _ _ := False.elim /-- The one-edge subgraph. -/ @[simps] def subgraphOfAdj (G : SimpleGraph V) {v w : V} (hvw : G.Adj v w) : G.Subgraph where verts := {v, w} Adj a b := s(v, w) = s(a, b) adj_sub h := by rw [← G.mem_edgeSet, ← h] exact hvw edge_vert {a b} h := by apply_fun fun e ↦ a ∈ e at h simp only [Sym2.mem_iff, true_or, eq_iff_iff, iff_true] at h exact h namespace Subgraph variable {G : SimpleGraph V} {G₁ G₂ : G.Subgraph} {a b : V} protected theorem loopless (G' : Subgraph G) : Irreflexive G'.Adj := fun v h ↦ G.loopless v (G'.adj_sub h) theorem adj_comm (G' : Subgraph G) (v w : V) : G'.Adj v w ↔ G'.Adj w v := ⟨fun x ↦ G'.symm x, fun x ↦ G'.symm x⟩ @[symm] theorem adj_symm (G' : Subgraph G) {u v : V} (h : G'.Adj u v) : G'.Adj v u := G'.symm h protected theorem Adj.symm {G' : Subgraph G} {u v : V} (h : G'.Adj u v) : G'.Adj v u := G'.symm h protected theorem Adj.adj_sub {H : G.Subgraph} {u v : V} (h : H.Adj u v) : G.Adj u v := H.adj_sub h protected theorem Adj.fst_mem {H : G.Subgraph} {u v : V} (h : H.Adj u v) : u ∈ H.verts := H.edge_vert h protected theorem Adj.snd_mem {H : G.Subgraph} {u v : V} (h : H.Adj u v) : v ∈ H.verts := h.symm.fst_mem protected theorem Adj.ne {H : G.Subgraph} {u v : V} (h : H.Adj u v) : u ≠ v := h.adj_sub.ne theorem adj_congr_of_sym2 {H : G.Subgraph} {u v w x : V} (h2 : s(u, v) = s(w, x)) : H.Adj u v ↔ H.Adj w x := by simp only [Sym2.eq, Sym2.rel_iff', Prod.mk.injEq, Prod.swap_prod_mk] at h2 rcases h2 with hl | hr · rw [hl.1, hl.2] · rw [hr.1, hr.2, Subgraph.adj_comm] /-- Coercion from `G' : Subgraph G` to a `SimpleGraph G'.verts`. -/ @[simps] protected def coe (G' : Subgraph G) : SimpleGraph G'.verts where Adj v w := G'.Adj v w symm _ _ h := G'.symm h loopless v h := loopless G v (G'.adj_sub h) @[simp] theorem coe_adj_sub (G' : Subgraph G) (u v : G'.verts) (h : G'.coe.Adj u v) : G.Adj u v := G'.adj_sub h -- Given `h : H.Adj u v`, then `h.coe : H.coe.Adj ⟨u, _⟩ ⟨v, _⟩`. protected theorem Adj.coe {H : G.Subgraph} {u v : V} (h : H.Adj u v) : H.coe.Adj ⟨u, H.edge_vert h⟩ ⟨v, H.edge_vert h.symm⟩ := h instance (G : SimpleGraph V) (H : Subgraph G) [DecidableRel H.Adj] : DecidableRel H.coe.Adj := fun a b ↦ ‹DecidableRel H.Adj› _ _ /-- A subgraph is called a *spanning subgraph* if it contains all the vertices of `G`. -/ def IsSpanning (G' : Subgraph G) : Prop := ∀ v : V, v ∈ G'.verts theorem isSpanning_iff {G' : Subgraph G} : G'.IsSpanning ↔ G'.verts = Set.univ := Set.eq_univ_iff_forall.symm protected alias ⟨IsSpanning.verts_eq_univ, _⟩ := isSpanning_iff /-- Coercion from `Subgraph G` to `SimpleGraph V`. If `G'` is a spanning subgraph, then `G'.spanningCoe` yields an isomorphic graph. In general, this adds in all vertices from `V` as isolated vertices. -/ @[simps] protected def spanningCoe (G' : Subgraph G) : SimpleGraph V where Adj := G'.Adj symm := G'.symm loopless v hv := G.loopless v (G'.adj_sub hv) @[simp] theorem Adj.of_spanningCoe {G' : Subgraph G} {u v : G'.verts} (h : G'.spanningCoe.Adj u v) : G.Adj u v := G'.adj_sub h lemma spanningCoe_le (G' : G.Subgraph) : G'.spanningCoe ≤ G := fun _ _ ↦ G'.3 theorem spanningCoe_inj : G₁.spanningCoe = G₂.spanningCoe ↔ G₁.Adj = G₂.Adj := by simp [Subgraph.spanningCoe] lemma mem_of_adj_spanningCoe {v w : V} {s : Set V} (G : SimpleGraph s) (hadj : G.spanningCoe.Adj v w) : v ∈ s := by aesop @[simp] lemma spanningCoe_subgraphOfAdj {v w : V} (hadj : G.Adj v w) : (G.subgraphOfAdj hadj).spanningCoe = fromEdgeSet {s(v, w)} := by ext v w aesop /-- `spanningCoe` is equivalent to `coe` for a subgraph that `IsSpanning`. -/ @[simps] def spanningCoeEquivCoeOfSpanning (G' : Subgraph G) (h : G'.IsSpanning) : G'.spanningCoe ≃g G'.coe where toFun v := ⟨v, h v⟩ invFun v := v left_inv _ := rfl right_inv _ := rfl map_rel_iff' := Iff.rfl /-- A subgraph is called an *induced subgraph* if vertices of `G'` are adjacent if they are adjacent in `G`. -/ def IsInduced (G' : Subgraph G) : Prop := ∀ ⦃v⦄, v ∈ G'.verts → ∀ ⦃w⦄, w ∈ G'.verts → G.Adj v w → G'.Adj v w @[simp] protected lemma IsInduced.adj {G' : G.Subgraph} (hG' : G'.IsInduced) {a b : G'.verts} : G'.Adj a b ↔ G.Adj a b := ⟨coe_adj_sub _ _ _, hG' a.2 b.2⟩ /-- `H.support` is the set of vertices that form edges in the subgraph `H`. -/ def support (H : Subgraph G) : Set V := Rel.dom H.Adj theorem mem_support (H : Subgraph G) {v : V} : v ∈ H.support ↔ ∃ w, H.Adj v w := Iff.rfl theorem support_subset_verts (H : Subgraph G) : H.support ⊆ H.verts := fun _ ⟨_, h⟩ ↦ H.edge_vert h /-- `G'.neighborSet v` is the set of vertices adjacent to `v` in `G'`. -/ def neighborSet (G' : Subgraph G) (v : V) : Set V := {w | G'.Adj v w} theorem neighborSet_subset (G' : Subgraph G) (v : V) : G'.neighborSet v ⊆ G.neighborSet v := fun _ ↦ G'.adj_sub theorem neighborSet_subset_verts (G' : Subgraph G) (v : V) : G'.neighborSet v ⊆ G'.verts := fun _ h ↦ G'.edge_vert (adj_symm G' h) @[simp] theorem mem_neighborSet (G' : Subgraph G) (v w : V) : w ∈ G'.neighborSet v ↔ G'.Adj v w := Iff.rfl /-- A subgraph as a graph has equivalent neighbor sets. -/ def coeNeighborSetEquiv {G' : Subgraph G} (v : G'.verts) : G'.coe.neighborSet v ≃ G'.neighborSet v where toFun w := ⟨w, w.2⟩ invFun w := ⟨⟨w, G'.edge_vert (G'.adj_symm w.2)⟩, w.2⟩ left_inv _ := rfl right_inv _ := rfl /-- The edge set of `G'` consists of a subset of edges of `G`. -/ def edgeSet (G' : Subgraph G) : Set (Sym2 V) := Sym2.fromRel G'.symm theorem edgeSet_subset (G' : Subgraph G) : G'.edgeSet ⊆ G.edgeSet := Sym2.ind (fun _ _ ↦ G'.adj_sub) @[simp] protected lemma mem_edgeSet {G' : Subgraph G} {v w : V} : s(v, w) ∈ G'.edgeSet ↔ G'.Adj v w := .rfl @[simp] lemma edgeSet_coe {G' : G.Subgraph} : G'.coe.edgeSet = Sym2.map (↑) ⁻¹' G'.edgeSet := by ext e; induction e using Sym2.ind; simp lemma image_coe_edgeSet_coe (G' : G.Subgraph) : Sym2.map (↑) '' G'.coe.edgeSet = G'.edgeSet := by rw [edgeSet_coe, Set.image_preimage_eq_iff] rintro e he induction e using Sym2.ind with | h a b => rw [Subgraph.mem_edgeSet] at he exact ⟨s(⟨a, edge_vert _ he⟩, ⟨b, edge_vert _ he.symm⟩), Sym2.map_pair_eq ..⟩ theorem mem_verts_of_mem_edge {G' : Subgraph G} {e : Sym2 V} {v : V} (he : e ∈ G'.edgeSet) (hv : v ∈ e) : v ∈ G'.verts := by induction e rcases Sym2.mem_iff.mp hv with (rfl | rfl) · exact G'.edge_vert he · exact G'.edge_vert (G'.symm he) /-- The `incidenceSet` is the set of edges incident to a given vertex. -/ def incidenceSet (G' : Subgraph G) (v : V) : Set (Sym2 V) := {e ∈ G'.edgeSet | v ∈ e} theorem incidenceSet_subset_incidenceSet (G' : Subgraph G) (v : V) : G'.incidenceSet v ⊆ G.incidenceSet v := fun _ h ↦ ⟨G'.edgeSet_subset h.1, h.2⟩ theorem incidenceSet_subset (G' : Subgraph G) (v : V) : G'.incidenceSet v ⊆ G'.edgeSet := fun _ h ↦ h.1 /-- Give a vertex as an element of the subgraph's vertex type. -/ abbrev vert (G' : Subgraph G) (v : V) (h : v ∈ G'.verts) : G'.verts := ⟨v, h⟩ /-- Create an equal copy of a subgraph (see `copy_eq`) with possibly different definitional equalities. See Note [range copy pattern]. -/ def copy (G' : Subgraph G) (V'' : Set V) (hV : V'' = G'.verts) (adj' : V → V → Prop) (hadj : adj' = G'.Adj) : Subgraph G where verts := V'' Adj := adj' adj_sub := hadj.symm ▸ G'.adj_sub edge_vert := hV.symm ▸ hadj.symm ▸ G'.edge_vert symm := hadj.symm ▸ G'.symm theorem copy_eq (G' : Subgraph G) (V'' : Set V) (hV : V'' = G'.verts) (adj' : V → V → Prop) (hadj : adj' = G'.Adj) : G'.copy V'' hV adj' hadj = G' := Subgraph.ext hV hadj /-- The union of two subgraphs. -/ instance : Max G.Subgraph where max G₁ G₂ := { verts := G₁.verts ∪ G₂.verts Adj := G₁.Adj ⊔ G₂.Adj adj_sub := fun hab => Or.elim hab (fun h => G₁.adj_sub h) fun h => G₂.adj_sub h edge_vert := Or.imp (fun h => G₁.edge_vert h) fun h => G₂.edge_vert h symm := fun _ _ => Or.imp G₁.adj_symm G₂.adj_symm } /-- The intersection of two subgraphs. -/ instance : Min G.Subgraph where min G₁ G₂ := { verts := G₁.verts ∩ G₂.verts Adj := G₁.Adj ⊓ G₂.Adj adj_sub := fun hab => G₁.adj_sub hab.1 edge_vert := And.imp (fun h => G₁.edge_vert h) fun h => G₂.edge_vert h symm := fun _ _ => And.imp G₁.adj_symm G₂.adj_symm } /-- The `top` subgraph is `G` as a subgraph of itself. -/ instance : Top G.Subgraph where top := { verts := Set.univ Adj := G.Adj adj_sub := id edge_vert := @fun v _ _ => Set.mem_univ v symm := G.symm } /-- The `bot` subgraph is the subgraph with no vertices or edges. -/ instance : Bot G.Subgraph where bot := { verts := ∅ Adj := ⊥ adj_sub := False.elim edge_vert := False.elim symm := fun _ _ => id } instance : SupSet G.Subgraph where sSup s := { verts := ⋃ G' ∈ s, verts G' Adj := fun a b => ∃ G' ∈ s, Adj G' a b adj_sub := by rintro a b ⟨G', -, hab⟩ exact G'.adj_sub hab edge_vert := by rintro a b ⟨G', hG', hab⟩ exact Set.mem_iUnion₂_of_mem hG' (G'.edge_vert hab) symm := fun a b h => by simpa [adj_comm] using h } instance : InfSet G.Subgraph where sInf s := { verts := ⋂ G' ∈ s, verts G' Adj := fun a b => (∀ ⦃G'⦄, G' ∈ s → Adj G' a b) ∧ G.Adj a b adj_sub := And.right edge_vert := fun hab => Set.mem_iInter₂_of_mem fun G' hG' => G'.edge_vert <| hab.1 hG' symm := fun _ _ => And.imp (forall₂_imp fun _ _ => Adj.symm) G.adj_symm } @[simp] theorem sup_adj : (G₁ ⊔ G₂).Adj a b ↔ G₁.Adj a b ∨ G₂.Adj a b := Iff.rfl @[simp] theorem inf_adj : (G₁ ⊓ G₂).Adj a b ↔ G₁.Adj a b ∧ G₂.Adj a b := Iff.rfl @[simp] theorem top_adj : (⊤ : Subgraph G).Adj a b ↔ G.Adj a b := Iff.rfl @[simp] theorem not_bot_adj : ¬ (⊥ : Subgraph G).Adj a b := not_false @[simp] theorem verts_sup (G₁ G₂ : G.Subgraph) : (G₁ ⊔ G₂).verts = G₁.verts ∪ G₂.verts := rfl @[simp] theorem verts_inf (G₁ G₂ : G.Subgraph) : (G₁ ⊓ G₂).verts = G₁.verts ∩ G₂.verts := rfl @[simp] theorem verts_top : (⊤ : G.Subgraph).verts = Set.univ := rfl @[simp] theorem verts_bot : (⊥ : G.Subgraph).verts = ∅ := rfl @[simp] theorem sSup_adj {s : Set G.Subgraph} : (sSup s).Adj a b ↔ ∃ G ∈ s, Adj G a b := Iff.rfl @[simp] theorem sInf_adj {s : Set G.Subgraph} : (sInf s).Adj a b ↔ (∀ G' ∈ s, Adj G' a b) ∧ G.Adj a b := Iff.rfl @[simp] theorem iSup_adj {f : ι → G.Subgraph} : (⨆ i, f i).Adj a b ↔ ∃ i, (f i).Adj a b := by simp [iSup] @[simp] theorem iInf_adj {f : ι → G.Subgraph} : (⨅ i, f i).Adj a b ↔ (∀ i, (f i).Adj a b) ∧ G.Adj a b := by simp [iInf] theorem sInf_adj_of_nonempty {s : Set G.Subgraph} (hs : s.Nonempty) : (sInf s).Adj a b ↔ ∀ G' ∈ s, Adj G' a b := sInf_adj.trans <| and_iff_left_of_imp <| by obtain ⟨G', hG'⟩ := hs exact fun h => G'.adj_sub (h _ hG') theorem iInf_adj_of_nonempty [Nonempty ι] {f : ι → G.Subgraph} : (⨅ i, f i).Adj a b ↔ ∀ i, (f i).Adj a b := by rw [iInf, sInf_adj_of_nonempty (Set.range_nonempty _)] simp @[simp] theorem verts_sSup (s : Set G.Subgraph) : (sSup s).verts = ⋃ G' ∈ s, verts G' := rfl @[simp] theorem verts_sInf (s : Set G.Subgraph) : (sInf s).verts = ⋂ G' ∈ s, verts G' := rfl @[simp] theorem verts_iSup {f : ι → G.Subgraph} : (⨆ i, f i).verts = ⋃ i, (f i).verts := by simp [iSup] @[simp] theorem verts_iInf {f : ι → G.Subgraph} : (⨅ i, f i).verts = ⋂ i, (f i).verts := by simp [iInf] @[simp] lemma coe_bot : (⊥ : G.Subgraph).coe = ⊥ := rfl @[simp] lemma IsInduced.top : (⊤ : G.Subgraph).IsInduced := fun _ _ _ _ ↦ id /-- The graph isomorphism between the top element of `G.subgraph` and `G`. -/ def topIso : (⊤ : G.Subgraph).coe ≃g G where toFun := (↑) invFun a := ⟨a, Set.mem_univ _⟩ left_inv _ := Subtype.eta .. right_inv _ := rfl map_rel_iff' := .rfl theorem verts_spanningCoe_injective : (fun G' : Subgraph G => (G'.verts, G'.spanningCoe)).Injective := by intro G₁ G₂ h rw [Prod.ext_iff] at h exact Subgraph.ext h.1 (spanningCoe_inj.1 h.2) /-- For subgraphs `G₁`, `G₂`, `G₁ ≤ G₂` iff `G₁.verts ⊆ G₂.verts` and `∀ a b, G₁.adj a b → G₂.adj a b`. -/ instance distribLattice : DistribLattice G.Subgraph := { show DistribLattice G.Subgraph from verts_spanningCoe_injective.distribLattice _ (fun _ _ => rfl) fun _ _ => rfl with le := fun x y => x.verts ⊆ y.verts ∧ ∀ ⦃v w : V⦄, x.Adj v w → y.Adj v w } instance : BoundedOrder (Subgraph G) where top := ⊤ bot := ⊥ le_top x := ⟨Set.subset_univ _, fun _ _ => x.adj_sub⟩ bot_le _ := ⟨Set.empty_subset _, fun _ _ => False.elim⟩ /-- Note that subgraphs do not form a Boolean algebra, because of `verts`. -/ def completelyDistribLatticeMinimalAxioms : CompletelyDistribLattice.MinimalAxioms G.Subgraph := { Subgraph.distribLattice with le := (· ≤ ·) sup := (· ⊔ ·) inf := (· ⊓ ·) top := ⊤ bot := ⊥ le_top := fun G' => ⟨Set.subset_univ _, fun _ _ => G'.adj_sub⟩ bot_le := fun _ => ⟨Set.empty_subset _, fun _ _ => False.elim⟩ sSup := sSup -- Porting note: needed `apply` here to modify elaboration; previously the term itself was fine. le_sSup := fun s G' hG' => ⟨by apply Set.subset_iUnion₂ G' hG', fun _ _ hab => ⟨G', hG', hab⟩⟩ sSup_le := fun s G' hG' => ⟨Set.iUnion₂_subset fun _ hH => (hG' _ hH).1, by rintro a b ⟨H, hH, hab⟩ exact (hG' _ hH).2 hab⟩ sInf := sInf sInf_le := fun _ G' hG' => ⟨Set.iInter₂_subset G' hG', fun _ _ hab => hab.1 hG'⟩ le_sInf := fun _ G' hG' => ⟨Set.subset_iInter₂ fun _ hH => (hG' _ hH).1, fun _ _ hab => ⟨fun _ hH => (hG' _ hH).2 hab, G'.adj_sub hab⟩⟩ iInf_iSup_eq := fun f => Subgraph.ext (by simpa using iInf_iSup_eq) (by ext; simp [Classical.skolem]) } instance : CompletelyDistribLattice G.Subgraph := .ofMinimalAxioms completelyDistribLatticeMinimalAxioms @[gcongr] lemma verts_mono {H H' : G.Subgraph} (h : H ≤ H') : H.verts ⊆ H'.verts := h.1 lemma verts_monotone : Monotone (verts : G.Subgraph → Set V) := fun _ _ h ↦ h.1 @[simps] instance subgraphInhabited : Inhabited (Subgraph G) := ⟨⊥⟩ @[simp] theorem neighborSet_sup {H H' : G.Subgraph} (v : V) : (H ⊔ H').neighborSet v = H.neighborSet v ∪ H'.neighborSet v := rfl @[simp] theorem neighborSet_inf {H H' : G.Subgraph} (v : V) : (H ⊓ H').neighborSet v = H.neighborSet v ∩ H'.neighborSet v := rfl @[simp] theorem neighborSet_top (v : V) : (⊤ : G.Subgraph).neighborSet v = G.neighborSet v := rfl @[simp] theorem neighborSet_bot (v : V) : (⊥ : G.Subgraph).neighborSet v = ∅ := rfl @[simp] theorem neighborSet_sSup (s : Set G.Subgraph) (v : V) : (sSup s).neighborSet v = ⋃ G' ∈ s, neighborSet G' v := by ext simp @[simp] theorem neighborSet_sInf (s : Set G.Subgraph) (v : V) : (sInf s).neighborSet v = (⋂ G' ∈ s, neighborSet G' v) ∩ G.neighborSet v := by ext simp @[simp] theorem neighborSet_iSup (f : ι → G.Subgraph) (v : V) : (⨆ i, f i).neighborSet v = ⋃ i, (f i).neighborSet v := by simp [iSup] @[simp] theorem neighborSet_iInf (f : ι → G.Subgraph) (v : V) : (⨅ i, f i).neighborSet v = (⋂ i, (f i).neighborSet v) ∩ G.neighborSet v := by simp [iInf] @[simp] theorem edgeSet_top : (⊤ : Subgraph G).edgeSet = G.edgeSet := rfl @[simp] theorem edgeSet_bot : (⊥ : Subgraph G).edgeSet = ∅ := Set.ext <| Sym2.ind (by simp) @[simp] theorem edgeSet_inf {H₁ H₂ : Subgraph G} : (H₁ ⊓ H₂).edgeSet = H₁.edgeSet ∩ H₂.edgeSet := Set.ext <| Sym2.ind (by simp) @[simp] theorem edgeSet_sup {H₁ H₂ : Subgraph G} : (H₁ ⊔ H₂).edgeSet = H₁.edgeSet ∪ H₂.edgeSet := Set.ext <| Sym2.ind (by simp) @[simp] theorem edgeSet_sSup (s : Set G.Subgraph) : (sSup s).edgeSet = ⋃ G' ∈ s, edgeSet G' := by ext e induction e simp @[simp] theorem edgeSet_sInf (s : Set G.Subgraph) : (sInf s).edgeSet = (⋂ G' ∈ s, edgeSet G') ∩ G.edgeSet := by ext e induction e simp @[simp] theorem edgeSet_iSup (f : ι → G.Subgraph) : (⨆ i, f i).edgeSet = ⋃ i, (f i).edgeSet := by simp [iSup] @[simp] theorem edgeSet_iInf (f : ι → G.Subgraph) : (⨅ i, f i).edgeSet = (⋂ i, (f i).edgeSet) ∩ G.edgeSet := by simp [iInf] @[simp] theorem spanningCoe_top : (⊤ : Subgraph G).spanningCoe = G := rfl @[simp] theorem spanningCoe_bot : (⊥ : Subgraph G).spanningCoe = ⊥ := rfl /-- Turn a subgraph of a `SimpleGraph` into a member of its subgraph type. -/ @[simps] def _root_.SimpleGraph.toSubgraph (H : SimpleGraph V) (h : H ≤ G) : G.Subgraph where verts := Set.univ Adj := H.Adj adj_sub e := h e edge_vert _ := Set.mem_univ _ symm := H.symm theorem support_mono {H H' : Subgraph G} (h : H ≤ H') : H.support ⊆ H'.support := Rel.dom_mono h.2 theorem _root_.SimpleGraph.toSubgraph.isSpanning (H : SimpleGraph V) (h : H ≤ G) : (toSubgraph H h).IsSpanning := Set.mem_univ theorem spanningCoe_le_of_le {H H' : Subgraph G} (h : H ≤ H') : H.spanningCoe ≤ H'.spanningCoe := h.2 @[simp] lemma sup_spanningCoe (H H' : Subgraph G) : (H ⊔ H').spanningCoe = H.spanningCoe ⊔ H'.spanningCoe := rfl /-- The top of the `Subgraph G` lattice is equivalent to the graph itself. -/ def topEquiv : (⊤ : Subgraph G).coe ≃g G where toFun v := ↑v invFun v := ⟨v, trivial⟩ left_inv _ := rfl right_inv _ := rfl map_rel_iff' := Iff.rfl /-- The bottom of the `Subgraph G` lattice is equivalent to the empty graph on the empty vertex type. -/ def botEquiv : (⊥ : Subgraph G).coe ≃g (⊥ : SimpleGraph Empty) where toFun v := v.property.elim invFun v := v.elim left_inv := fun ⟨_, h⟩ ↦ h.elim right_inv v := v.elim map_rel_iff' := Iff.rfl theorem edgeSet_mono {H₁ H₂ : Subgraph G} (h : H₁ ≤ H₂) : H₁.edgeSet ≤ H₂.edgeSet := Sym2.ind h.2 theorem _root_.Disjoint.edgeSet {H₁ H₂ : Subgraph G} (h : Disjoint H₁ H₂) : Disjoint H₁.edgeSet H₂.edgeSet := disjoint_iff_inf_le.mpr <| by simpa using edgeSet_mono h.le_bot section map variable {G' : SimpleGraph W} {f : G →g G'} /-- Graph homomorphisms induce a covariant function on subgraphs. -/ @[simps] protected def map (f : G →g G') (H : G.Subgraph) : G'.Subgraph where verts := f '' H.verts Adj := Relation.Map H.Adj f f adj_sub := by rintro _ _ ⟨u, v, h, rfl, rfl⟩ exact f.map_rel (H.adj_sub h) edge_vert := by rintro _ _ ⟨u, v, h, rfl, rfl⟩ exact Set.mem_image_of_mem _ (H.edge_vert h) symm := by rintro _ _ ⟨u, v, h, rfl, rfl⟩ exact ⟨v, u, H.symm h, rfl, rfl⟩ @[simp] lemma map_id (H : G.Subgraph) : H.map Hom.id = H := by ext <;> simp lemma map_comp {U : Type*} {G'' : SimpleGraph U} (H : G.Subgraph) (f : G →g G') (g : G' →g G'') : H.map (g.comp f) = (H.map f).map g := by ext <;> simp [Subgraph.map] @[gcongr] lemma map_mono {H₁ H₂ : G.Subgraph} (hH : H₁ ≤ H₂) : H₁.map f ≤ H₂.map f := by constructor · intro simp only [map_verts, Set.mem_image, forall_exists_index, and_imp] rintro v hv rfl exact ⟨_, hH.1 hv, rfl⟩ · rintro _ _ ⟨u, v, ha, rfl, rfl⟩ exact ⟨_, _, hH.2 ha, rfl, rfl⟩ lemma map_monotone : Monotone (Subgraph.map f) := fun _ _ ↦ map_mono theorem map_sup (f : G →g G') (H₁ H₂ : G.Subgraph) : (H₁ ⊔ H₂).map f = H₁.map f ⊔ H₂.map f := by ext <;> simp [Set.image_union, map_adj, sup_adj, Relation.Map, or_and_right, exists_or] @[simp] lemma map_iso_top {H : SimpleGraph W} (e : G ≃g H) : Subgraph.map e.toHom ⊤ = ⊤ := by ext <;> simp [Relation.Map, e.apply_eq_iff_eq_symm_apply, ← e.map_rel_iff] @[simp] lemma edgeSet_map (f : G →g G') (H : G.Subgraph) : (H.map f).edgeSet = Sym2.map f '' H.edgeSet := Sym2.fromRel_relationMap .. end map /-- Graph homomorphisms induce a contravariant function on subgraphs. -/ @[simps] protected def comap {G' : SimpleGraph W} (f : G →g G') (H : G'.Subgraph) : G.Subgraph where verts := f ⁻¹' H.verts Adj u v := G.Adj u v ∧ H.Adj (f u) (f v) adj_sub h := h.1 edge_vert h := Set.mem_preimage.1 (H.edge_vert h.2) symm _ _ h := ⟨G.symm h.1, H.symm h.2⟩ theorem comap_monotone {G' : SimpleGraph W} (f : G →g G') : Monotone (Subgraph.comap f) := by intro H H' h constructor · intro simp only [comap_verts, Set.mem_preimage] apply h.1 · intro v w simp +contextual only [comap_adj, and_imp, true_and] intro apply h.2 @[simp] lemma comap_equiv_top {H : SimpleGraph W} (f : G →g H) : Subgraph.comap f ⊤ = ⊤ := by ext <;> simp +contextual [f.map_adj] theorem map_le_iff_le_comap {G' : SimpleGraph W} (f : G →g G') (H : G.Subgraph) (H' : G'.Subgraph) : H.map f ≤ H' ↔ H ≤ H'.comap f := by refine ⟨fun h ↦ ⟨fun v hv ↦ ?_, fun v w hvw ↦ ?_⟩, fun h ↦ ⟨fun v ↦ ?_, fun v w ↦ ?_⟩⟩ · simp only [comap_verts, Set.mem_preimage] exact h.1 ⟨v, hv, rfl⟩ · simp only [H.adj_sub hvw, comap_adj, true_and] exact h.2 ⟨v, w, hvw, rfl, rfl⟩ · simp only [map_verts, Set.mem_image, forall_exists_index, and_imp] rintro w hw rfl exact h.1 hw · simp only [Relation.Map, map_adj, forall_exists_index, and_imp] rintro u u' hu rfl rfl exact (h.2 hu).2 instance [DecidableEq V] [Fintype V] [DecidableRel G.Adj] : Fintype G.Subgraph := by refine .ofBijective (α := {H : Finset V × (V → V → Bool) // (∀ a b, H.2 a b → G.Adj a b) ∧ (∀ a b, H.2 a b → a ∈ H.1) ∧ ∀ a b, H.2 a b = H.2 b a}) (fun H ↦ ⟨H.1.1, fun a b ↦ H.1.2 a b, @H.2.1, @H.2.2.1, by simp [Symmetric, H.2.2.2]⟩) ⟨?_, fun H ↦ ?_⟩ · rintro ⟨⟨_, _⟩, -⟩ ⟨⟨_, _⟩, -⟩ simp [funext_iff] · classical exact ⟨⟨(H.verts.toFinset, fun a b ↦ H.Adj a b), fun a b ↦ by simpa using H.adj_sub, fun a b ↦ by simpa using H.edge_vert, by simp [H.adj_comm]⟩, by simp⟩ instance [Finite V] : Finite G.Subgraph := by classical cases nonempty_fintype V; infer_instance /-- Given two subgraphs, one a subgraph of the other, there is an induced injective homomorphism of the subgraphs as graphs. -/ @[simps] def inclusion {x y : Subgraph G} (h : x ≤ y) : x.coe →g y.coe where toFun v := ⟨↑v, And.left h v.property⟩ map_rel' hvw := h.2 hvw theorem inclusion.injective {x y : Subgraph G} (h : x ≤ y) : Function.Injective (inclusion h) := by intro v w h rw [inclusion, DFunLike.coe, Subtype.mk_eq_mk] at h exact Subtype.ext h /-- There is an induced injective homomorphism of a subgraph of `G` into `G`. -/ @[simps] protected def hom (x : Subgraph G) : x.coe →g G where toFun v := v map_rel' := x.adj_sub @[simp] lemma coe_hom (x : Subgraph G) : (x.hom : x.verts → V) = (fun (v : x.verts) => (v : V)) := rfl theorem hom_injective {x : Subgraph G} : Function.Injective x.hom := fun _ _ ↦ Subtype.ext @[deprecated (since := "2025-03-15")] alias hom.injective := hom_injective @[simp] lemma map_hom_top (G' : G.Subgraph) : Subgraph.map G'.hom ⊤ = G' := by aesop (add unfold safe Relation.Map, unsafe G'.edge_vert, unsafe Adj.symm) /-- There is an induced injective homomorphism of a subgraph of `G` as a spanning subgraph into `G`. -/ @[simps] def spanningHom (x : Subgraph G) : x.spanningCoe →g G where toFun := id map_rel' := x.adj_sub theorem spanningHom_injective {x : Subgraph G} : Function.Injective x.spanningHom := fun _ _ ↦ id @[deprecated (since := "2025-03-15")] alias spanningHom.injective := spanningHom_injective theorem neighborSet_subset_of_subgraph {x y : Subgraph G} (h : x ≤ y) (v : V) : x.neighborSet v ⊆ y.neighborSet v := fun _ h' ↦ h.2 h' instance neighborSet.decidablePred (G' : Subgraph G) [h : DecidableRel G'.Adj] (v : V) : DecidablePred (· ∈ G'.neighborSet v) := h v /-- If a graph is locally finite at a vertex, then so is a subgraph of that graph. -/ instance finiteAt {G' : Subgraph G} (v : G'.verts) [DecidableRel G'.Adj] [Fintype (G.neighborSet v)] : Fintype (G'.neighborSet v) := Set.fintypeSubset (G.neighborSet v) (G'.neighborSet_subset v) /-- If a subgraph is locally finite at a vertex, then so are subgraphs of that subgraph. This is not an instance because `G''` cannot be inferred. -/ def finiteAtOfSubgraph {G' G'' : Subgraph G} [DecidableRel G'.Adj] (h : G' ≤ G'') (v : G'.verts) [Fintype (G''.neighborSet v)] : Fintype (G'.neighborSet v) := Set.fintypeSubset (G''.neighborSet v) (neighborSet_subset_of_subgraph h v) instance (G' : Subgraph G) [Fintype G'.verts] (v : V) [DecidablePred (· ∈ G'.neighborSet v)] : Fintype (G'.neighborSet v) := Set.fintypeSubset G'.verts (neighborSet_subset_verts G' v) instance coeFiniteAt {G' : Subgraph G} (v : G'.verts) [Fintype (G'.neighborSet v)] : Fintype (G'.coe.neighborSet v) := Fintype.ofEquiv _ (coeNeighborSetEquiv v).symm theorem IsSpanning.card_verts [Fintype V] {G' : Subgraph G} [Fintype G'.verts] (h : G'.IsSpanning) : G'.verts.toFinset.card = Fintype.card V := by simp only [isSpanning_iff.1 h, Set.toFinset_univ] congr /-- The degree of a vertex in a subgraph. It's zero for vertices outside the subgraph. -/ def degree (G' : Subgraph G) (v : V) [Fintype (G'.neighborSet v)] : ℕ := Fintype.card (G'.neighborSet v) theorem finset_card_neighborSet_eq_degree {G' : Subgraph G} {v : V} [Fintype (G'.neighborSet v)] : (G'.neighborSet v).toFinset.card = G'.degree v := by rw [degree, Set.toFinset_card] theorem degree_le (G' : Subgraph G) (v : V) [Fintype (G'.neighborSet v)] [Fintype (G.neighborSet v)] : G'.degree v ≤ G.degree v := by rw [← card_neighborSet_eq_degree] exact Set.card_le_card (G'.neighborSet_subset v) theorem degree_le' (G' G'' : Subgraph G) (h : G' ≤ G'') (v : V) [Fintype (G'.neighborSet v)] [Fintype (G''.neighborSet v)] : G'.degree v ≤ G''.degree v := Set.card_le_card (neighborSet_subset_of_subgraph h v) @[simp] theorem coe_degree (G' : Subgraph G) (v : G'.verts) [Fintype (G'.coe.neighborSet v)] [Fintype (G'.neighborSet v)] : G'.coe.degree v = G'.degree v := by rw [← card_neighborSet_eq_degree] exact Fintype.card_congr (coeNeighborSetEquiv v) @[simp] theorem degree_spanningCoe {G' : G.Subgraph} (v : V) [Fintype (G'.neighborSet v)] [Fintype (G'.spanningCoe.neighborSet v)] : G'.spanningCoe.degree v = G'.degree v := by rw [← card_neighborSet_eq_degree, Subgraph.degree] congr! theorem degree_eq_one_iff_unique_adj {G' : Subgraph G} {v : V} [Fintype (G'.neighborSet v)] : G'.degree v = 1 ↔ ∃! w : V, G'.Adj v w := by rw [← finset_card_neighborSet_eq_degree, Finset.card_eq_one, Finset.singleton_iff_unique_mem] simp only [Set.mem_toFinset, mem_neighborSet] lemma neighborSet_eq_of_equiv {v : V} {H : Subgraph G} (h : G.neighborSet v ≃ H.neighborSet v) (hfin : (G.neighborSet v).Finite) : H.neighborSet v = G.neighborSet v := by lift H.neighborSet v to Finset V using h.set_finite_iff.mp hfin with s hs lift G.neighborSet v to Finset V using hfin with t ht refine congrArg _ <| Finset.eq_of_subset_of_card_le ?_ (Finset.card_eq_of_equiv h).le rw [← Finset.coe_subset, hs, ht] exact H.neighborSet_subset _ lemma adj_iff_of_neighborSet_equiv {v : V} {H : Subgraph G} (h : G.neighborSet v ≃ H.neighborSet v) (hfin : (G.neighborSet v).Finite) : ∀ {w}, H.Adj v w ↔ G.Adj v w := Set.ext_iff.mp (neighborSet_eq_of_equiv h hfin) _ end Subgraph section MkProperties /-! ### Properties of `singletonSubgraph` and `subgraphOfAdj` -/ variable {G : SimpleGraph V} {G' : SimpleGraph W} instance nonempty_singletonSubgraph_verts (v : V) : Nonempty (G.singletonSubgraph v).verts := ⟨⟨v, Set.mem_singleton v⟩⟩ @[simp] theorem singletonSubgraph_le_iff (v : V) (H : G.Subgraph) : G.singletonSubgraph v ≤ H ↔ v ∈ H.verts := by refine ⟨fun h ↦ h.1 (Set.mem_singleton v), ?_⟩ intro h constructor · rwa [singletonSubgraph_verts, Set.singleton_subset_iff] · exact fun _ _ ↦ False.elim @[simp] theorem map_singletonSubgraph (f : G →g G') {v : V} : Subgraph.map f (G.singletonSubgraph v) = G'.singletonSubgraph (f v) := by ext <;> simp only [Relation.Map, Subgraph.map_adj, singletonSubgraph_adj, Pi.bot_apply, exists_and_left, and_iff_left_iff_imp, IsEmpty.forall_iff, Subgraph.map_verts, singletonSubgraph_verts, Set.image_singleton] exact False.elim @[simp] theorem neighborSet_singletonSubgraph (v w : V) : (G.singletonSubgraph v).neighborSet w = ∅ := rfl @[simp] theorem edgeSet_singletonSubgraph (v : V) : (G.singletonSubgraph v).edgeSet = ∅ := Sym2.fromRel_bot theorem eq_singletonSubgraph_iff_verts_eq (H : G.Subgraph) {v : V} : H = G.singletonSubgraph v ↔ H.verts = {v} := by refine ⟨fun h ↦ by rw [h, singletonSubgraph_verts], fun h ↦ ?_⟩ ext · rw [h, singletonSubgraph_verts] · simp only [Prop.bot_eq_false, singletonSubgraph_adj, Pi.bot_apply, iff_false] intro ha have ha1 := ha.fst_mem have ha2 := ha.snd_mem rw [h, Set.mem_singleton_iff] at ha1 ha2 subst_vars exact ha.ne rfl instance nonempty_subgraphOfAdj_verts {v w : V} (hvw : G.Adj v w) : Nonempty (G.subgraphOfAdj hvw).verts := ⟨⟨v, by simp⟩⟩ @[simp] theorem edgeSet_subgraphOfAdj {v w : V} (hvw : G.Adj v w) : (G.subgraphOfAdj hvw).edgeSet = {s(v, w)} := by ext e refine e.ind ?_ simp only [eq_comm, Set.mem_singleton_iff, Subgraph.mem_edgeSet, subgraphOfAdj_adj, forall₂_true_iff] lemma subgraphOfAdj_le_of_adj {v w : V} (H : G.Subgraph) (h : H.Adj v w) : G.subgraphOfAdj (H.adj_sub h) ≤ H := by constructor · intro x rintro (rfl | rfl) <;> simp [H.edge_vert h, H.edge_vert h.symm] · simp only [subgraphOfAdj_adj, Sym2.eq, Sym2.rel_iff] rintro _ _ (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩) <;> simp [h, h.symm] theorem subgraphOfAdj_symm {v w : V} (hvw : G.Adj v w) : G.subgraphOfAdj hvw.symm = G.subgraphOfAdj hvw := by ext <;> simp [or_comm, and_comm] @[simp] theorem map_subgraphOfAdj (f : G →g G') {v w : V} (hvw : G.Adj v w) : Subgraph.map f (G.subgraphOfAdj hvw) = G'.subgraphOfAdj (f.map_adj hvw) := by ext · simp only [Subgraph.map_verts, subgraphOfAdj_verts, Set.mem_image, Set.mem_insert_iff, Set.mem_singleton_iff] constructor · rintro ⟨u, rfl | rfl, rfl⟩ <;> simp · rintro (rfl | rfl) · use v simp · use w simp · simp only [Relation.Map, Subgraph.map_adj, subgraphOfAdj_adj, Sym2.eq, Sym2.rel_iff] constructor · rintro ⟨a, b, ⟨rfl, rfl⟩ | ⟨rfl, rfl⟩, rfl, rfl⟩ <;> simp · rintro (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩) · use v, w simp · use w, v simp theorem neighborSet_subgraphOfAdj_subset {u v w : V} (hvw : G.Adj v w) : (G.subgraphOfAdj hvw).neighborSet u ⊆ {v, w} := (G.subgraphOfAdj hvw).neighborSet_subset_verts _ @[simp] theorem neighborSet_fst_subgraphOfAdj {v w : V} (hvw : G.Adj v w) : (G.subgraphOfAdj hvw).neighborSet v = {w} := by ext u suffices w = u ↔ u = w by simpa [hvw.ne.symm] using this rw [eq_comm] @[simp] theorem neighborSet_snd_subgraphOfAdj {v w : V} (hvw : G.Adj v w) : (G.subgraphOfAdj hvw).neighborSet w = {v} := by rw [subgraphOfAdj_symm hvw.symm] exact neighborSet_fst_subgraphOfAdj hvw.symm @[simp] theorem neighborSet_subgraphOfAdj_of_ne_of_ne {u v w : V} (hvw : G.Adj v w) (hv : u ≠ v) (hw : u ≠ w) : (G.subgraphOfAdj hvw).neighborSet u = ∅ := by ext simp [hv.symm, hw.symm] theorem neighborSet_subgraphOfAdj [DecidableEq V] {u v w : V} (hvw : G.Adj v w) : (G.subgraphOfAdj hvw).neighborSet u = (if u = v then {w} else ∅) ∪ if u = w then {v} else ∅ := by split_ifs <;> subst_vars <;> simp [*] theorem singletonSubgraph_fst_le_subgraphOfAdj {u v : V} {h : G.Adj u v} : G.singletonSubgraph u ≤ G.subgraphOfAdj h := by simp theorem singletonSubgraph_snd_le_subgraphOfAdj {u v : V} {h : G.Adj u v} : G.singletonSubgraph v ≤ G.subgraphOfAdj h := by simp @[simp] lemma support_subgraphOfAdj {u v : V} (h : G.Adj u v) : (G.subgraphOfAdj h).support = {u , v} := by ext rw [Subgraph.mem_support] simp only [subgraphOfAdj_adj, Sym2.eq, Sym2.rel_iff', Prod.mk.injEq, Prod.swap_prod_mk] refine ⟨?_, fun h ↦ h.elim (fun hl ↦ ⟨v, .inl ⟨hl.symm, rfl⟩⟩) fun hr ↦ ⟨u, .inr ⟨rfl, hr.symm⟩⟩⟩ rintro ⟨_, hw⟩ exact hw.elim (fun h1 ↦ .inl h1.1.symm) fun hr ↦ .inr hr.2.symm end MkProperties namespace Subgraph variable {G : SimpleGraph V} /-! ### Subgraphs of subgraphs -/ /-- Given a subgraph of a subgraph of `G`, construct a subgraph of `G`. -/ protected abbrev coeSubgraph {G' : G.Subgraph} : G'.coe.Subgraph → G.Subgraph := Subgraph.map G'.hom /-- Given a subgraph of `G`, restrict it to being a subgraph of another subgraph `G'` by taking the portion of `G` that intersects `G'`. -/ protected abbrev restrict {G' : G.Subgraph} : G.Subgraph → G'.coe.Subgraph := Subgraph.comap G'.hom @[simp] lemma verts_coeSubgraph {G' : Subgraph G} (G'' : Subgraph G'.coe) : (Subgraph.coeSubgraph G'').verts = (G''.verts : Set V) := rfl lemma coeSubgraph_adj {G' : G.Subgraph} (G'' : G'.coe.Subgraph) (v w : V) : (G'.coeSubgraph G'').Adj v w ↔ ∃ (hv : v ∈ G'.verts) (hw : w ∈ G'.verts), G''.Adj ⟨v, hv⟩ ⟨w, hw⟩ := by simp [Relation.Map] lemma restrict_adj {G' G'' : G.Subgraph} (v w : G'.verts) : (G'.restrict G'').Adj v w ↔ G'.Adj v w ∧ G''.Adj v w := Iff.rfl theorem restrict_coeSubgraph {G' : G.Subgraph} (G'' : G'.coe.Subgraph) : Subgraph.restrict (Subgraph.coeSubgraph G'') = G'' := by ext · simp · rw [restrict_adj, coeSubgraph_adj] simpa using G''.adj_sub theorem coeSubgraph_injective (G' : G.Subgraph) : Function.Injective (Subgraph.coeSubgraph : G'.coe.Subgraph → G.Subgraph) := Function.LeftInverse.injective restrict_coeSubgraph lemma coeSubgraph_le {H : G.Subgraph} (H' : H.coe.Subgraph) : Subgraph.coeSubgraph H' ≤ H := by constructor · simp · rintro v w ⟨_, _, h, rfl, rfl⟩ exact H'.adj_sub h lemma coeSubgraph_restrict_eq {H : G.Subgraph} (H' : G.Subgraph) : Subgraph.coeSubgraph (H.restrict H') = H ⊓ H' := by ext · simp [and_comm] · simp_rw [coeSubgraph_adj, restrict_adj] simp only [exists_and_left, exists_prop, inf_adj, and_congr_right_iff] intro h simp [H.edge_vert h, H.edge_vert h.symm] /-! ### Edge deletion -/ /-- Given a subgraph `G'` and a set of vertex pairs, remove all of the corresponding edges from its edge set, if present. See also: `SimpleGraph.deleteEdges`. -/ def deleteEdges (G' : G.Subgraph) (s : Set (Sym2 V)) : G.Subgraph where verts := G'.verts Adj := G'.Adj \ Sym2.ToRel s adj_sub h' := G'.adj_sub h'.1 edge_vert h' := G'.edge_vert h'.1 symm a b := by simp [G'.adj_comm, Sym2.eq_swap] section DeleteEdges variable {G' : G.Subgraph} (s : Set (Sym2 V)) @[simp] theorem deleteEdges_verts : (G'.deleteEdges s).verts = G'.verts := rfl @[simp] theorem deleteEdges_adj (v w : V) : (G'.deleteEdges s).Adj v w ↔ G'.Adj v w ∧ ¬s(v, w) ∈ s := Iff.rfl @[simp] theorem deleteEdges_deleteEdges (s s' : Set (Sym2 V)) : (G'.deleteEdges s).deleteEdges s' = G'.deleteEdges (s ∪ s') := by ext <;> simp [and_assoc, not_or] @[simp] theorem deleteEdges_empty_eq : G'.deleteEdges ∅ = G' := by ext <;> simp @[simp] theorem deleteEdges_spanningCoe_eq : G'.spanningCoe.deleteEdges s = (G'.deleteEdges s).spanningCoe := by ext simp theorem deleteEdges_coe_eq (s : Set (Sym2 G'.verts)) : G'.coe.deleteEdges s = (G'.deleteEdges (Sym2.map (↑) '' s)).coe := by ext ⟨v, hv⟩ ⟨w, hw⟩ simp only [SimpleGraph.deleteEdges_adj, coe_adj, deleteEdges_adj, Set.mem_image, not_exists, not_and, and_congr_right_iff] intro constructor · intro hs refine Sym2.ind ?_ rintro ⟨v', hv'⟩ ⟨w', hw'⟩ simp only [Sym2.map_pair_eq, Sym2.eq] contrapose! rintro (_ | _) <;> simpa only [Sym2.eq_swap] · intro h' hs exact h' _ hs rfl theorem coe_deleteEdges_eq (s : Set (Sym2 V)) : (G'.deleteEdges s).coe = G'.coe.deleteEdges (Sym2.map (↑) ⁻¹' s) := by ext ⟨v, hv⟩ ⟨w, hw⟩ simp theorem deleteEdges_le : G'.deleteEdges s ≤ G' := by constructor <;> simp +contextual [subset_rfl] theorem deleteEdges_le_of_le {s s' : Set (Sym2 V)} (h : s ⊆ s') : G'.deleteEdges s' ≤ G'.deleteEdges s := by constructor <;> simp +contextual only [deleteEdges_verts, deleteEdges_adj, true_and, and_imp, subset_rfl] exact fun _ _ _ hs' hs ↦ hs' (h hs) @[simp] theorem deleteEdges_inter_edgeSet_left_eq : G'.deleteEdges (G'.edgeSet ∩ s) = G'.deleteEdges s := by ext <;> simp +contextual [imp_false] @[simp] theorem deleteEdges_inter_edgeSet_right_eq : G'.deleteEdges (s ∩ G'.edgeSet) = G'.deleteEdges s := by ext <;> simp +contextual [imp_false] theorem coe_deleteEdges_le : (G'.deleteEdges s).coe ≤ (G'.coe : SimpleGraph G'.verts) := by intro v w simp +contextual theorem spanningCoe_deleteEdges_le (G' : G.Subgraph) (s : Set (Sym2 V)) : (G'.deleteEdges s).spanningCoe ≤ G'.spanningCoe := spanningCoe_le_of_le (deleteEdges_le s) end DeleteEdges /-! ### Induced subgraphs -/ /- Given a subgraph, we can change its vertex set while removing any invalid edges, which gives induced subgraphs. See also `SimpleGraph.induce` for the `SimpleGraph` version, which, unlike for subgraphs, results in a graph with a different vertex type. -/ /-- The induced subgraph of a subgraph. The expectation is that `s ⊆ G'.verts` for the usual notion of an induced subgraph, but, in general, `s` is taken to be the new vertex set and edges are induced from the subgraph `G'`. -/ @[simps] def induce (G' : G.Subgraph) (s : Set V) : G.Subgraph where verts := s Adj u v := u ∈ s ∧ v ∈ s ∧ G'.Adj u v adj_sub h := G'.adj_sub h.2.2 edge_vert h := h.1 symm _ _ h := ⟨h.2.1, h.1, G'.symm h.2.2⟩ theorem _root_.SimpleGraph.induce_eq_coe_induce_top (s : Set V) : G.induce s = ((⊤ : G.Subgraph).induce s).coe := by ext simp section Induce variable {G' G'' : G.Subgraph} {s s' : Set V} theorem induce_mono (hg : G' ≤ G'') (hs : s ⊆ s') : G'.induce s ≤ G''.induce s' := by constructor · simp [hs] · simp +contextual only [induce_adj, and_imp] intro v w hv hw ha exact ⟨hs hv, hs hw, hg.2 ha⟩ @[gcongr, mono] theorem induce_mono_left (hg : G' ≤ G'') : G'.induce s ≤ G''.induce s := induce_mono hg subset_rfl @[gcongr, mono] theorem induce_mono_right (hs : s ⊆ s') : G'.induce s ≤ G'.induce s' := induce_mono le_rfl hs @[simp] theorem induce_empty : G'.induce ∅ = ⊥ := by ext <;> simp @[simp] theorem induce_self_verts : G'.induce G'.verts = G' := by ext · simp · constructor <;> simp +contextual only [induce_adj, imp_true_iff, and_true] exact fun ha ↦ ⟨G'.edge_vert ha, G'.edge_vert ha.symm⟩ lemma le_induce_top_verts : G' ≤ (⊤ : G.Subgraph).induce G'.verts := calc G' = G'.induce G'.verts := Subgraph.induce_self_verts.symm _ ≤ (⊤ : G.Subgraph).induce G'.verts := Subgraph.induce_mono_left le_top lemma le_induce_union : G'.induce s ⊔ G'.induce s' ≤ G'.induce (s ∪ s') := by constructor · simp only [verts_sup, induce_verts, Set.Subset.rfl] · simp only [sup_adj, induce_adj, Set.mem_union] rintro v w (h | h) <;> simp [h] lemma le_induce_union_left : G'.induce s ≤ G'.induce (s ∪ s') := by exact (sup_le_iff.mp le_induce_union).1 lemma le_induce_union_right : G'.induce s' ≤ G'.induce (s ∪ s') := by exact (sup_le_iff.mp le_induce_union).2 theorem singletonSubgraph_eq_induce {v : V} : G.singletonSubgraph v = (⊤ : G.Subgraph).induce {v} := by ext <;> simp +contextual [-Set.bot_eq_empty, Prop.bot_eq_false] theorem subgraphOfAdj_eq_induce {v w : V} (hvw : G.Adj v w) : G.subgraphOfAdj hvw = (⊤ : G.Subgraph).induce {v, w} := by ext · simp · constructor · intro h simp only [subgraphOfAdj_adj, Sym2.eq, Sym2.rel_iff] at h obtain ⟨rfl, rfl⟩ | ⟨rfl, rfl⟩ := h <;> simp [hvw, hvw.symm] · intro h simp only [induce_adj, Set.mem_insert_iff, Set.mem_singleton_iff, top_adj] at h obtain ⟨rfl | rfl, rfl | rfl, ha⟩ := h <;> first |exact (ha.ne rfl).elim|simp instance instDecidableRel_induce_adj (s : Set V) [∀ a, Decidable (a ∈ s)] [DecidableRel G'.Adj] : DecidableRel (G'.induce s).Adj := fun _ _ ↦ instDecidableAnd end Induce /-- Given a subgraph and a set of vertices, delete all the vertices from the subgraph, if present. Any edges incident to the deleted vertices are deleted as well. -/ abbrev deleteVerts (G' : G.Subgraph) (s : Set V) : G.Subgraph := G'.induce (G'.verts \ s) section DeleteVerts variable {G' : G.Subgraph} {s : Set V} theorem deleteVerts_verts : (G'.deleteVerts s).verts = G'.verts \ s := rfl theorem deleteVerts_adj {u v : V} : (G'.deleteVerts s).Adj u v ↔ u ∈ G'.verts ∧ ¬u ∈ s ∧ v ∈ G'.verts ∧ ¬v ∈ s ∧ G'.Adj u v := by simp [and_assoc] @[simp]
theorem deleteVerts_deleteVerts (s s' : Set V) : (G'.deleteVerts s).deleteVerts s' = G'.deleteVerts (s ∪ s') := by ext <;> simp +contextual [not_or, and_assoc] @[simp] theorem deleteVerts_empty : G'.deleteVerts ∅ = G' := by simp [deleteVerts] theorem deleteVerts_le : G'.deleteVerts s ≤ G' := by constructor <;> simp [Set.diff_subset]
Mathlib/Combinatorics/SimpleGraph/Subgraph.lean
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/- Copyright (c) 2019 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel, Floris van Doorn -/ import Mathlib.Analysis.Calculus.ContDiff.Operations import Mathlib.Data.Finset.Sym import Mathlib.Data.Nat.Choose.Cast import Mathlib.Data.Nat.Choose.Multinomial /-! # Bounds on higher derivatives `norm_iteratedFDeriv_comp_le` gives the bound `n! * C * D ^ n` for the `n`-th derivative of `g ∘ f` assuming that the derivatives of `g` are bounded by `C` and the `i`-th derivative of `f` is bounded by `D ^ i`. -/ noncomputable section open scoped NNReal Nat universe u uD uE uF uG open Set Fin Filter Function variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {D : Type uD} [NormedAddCommGroup D] [NormedSpace 𝕜 D] {E : Type uE} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type uF} [NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG} [NormedAddCommGroup G] [NormedSpace 𝕜 G] {s s₁ t u : Set E} /-!## Quantitative bounds -/ /-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the iterated derivatives of `f` and `g` when `B` is bilinear. This lemma is an auxiliary version assuming all spaces live in the same universe, to enable an induction. Use instead `ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear` that removes this assumption. -/ theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_aux {Du Eu Fu Gu : Type u} [NormedAddCommGroup Du] [NormedSpace 𝕜 Du] [NormedAddCommGroup Eu] [NormedSpace 𝕜 Eu] [NormedAddCommGroup Fu] [NormedSpace 𝕜 Fu] [NormedAddCommGroup Gu] [NormedSpace 𝕜 Gu] (B : Eu →L[𝕜] Fu →L[𝕜] Gu) {f : Du → Eu} {g : Du → Fu} {n : ℕ} {s : Set Du} {x : Du} (hf : ContDiffOn 𝕜 n f s) (hg : ContDiffOn 𝕜 n g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) : ‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by /- We argue by induction on `n`. The bound is trivial for `n = 0`. For `n + 1`, we write the `(n+1)`-th derivative as the `n`-th derivative of the derivative `B f g' + B f' g`, and apply the inductive assumption to each of those two terms. For this induction to make sense, the spaces of linear maps that appear in the induction should be in the same universe as the original spaces, which explains why we assume in the lemma that all spaces live in the same universe. -/ induction' n with n IH generalizing Eu Fu Gu · simp only [norm_iteratedFDerivWithin_zero, zero_add, Finset.range_one, Finset.sum_singleton, Nat.choose_self, Nat.cast_one, one_mul, Nat.sub_zero, ← mul_assoc] apply B.le_opNorm₂ · have In : (n : WithTop ℕ∞) + 1 ≤ n.succ := by simp only [Nat.cast_succ, le_refl] -- Porting note: the next line is a hack allowing Lean to find the operator norm instance. let norm := @ContinuousLinearMap.hasOpNorm _ _ Eu ((Du →L[𝕜] Fu) →L[𝕜] Du →L[𝕜] Gu) _ _ _ _ _ _ (RingHom.id 𝕜) have I1 : ‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s x‖ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n + 1 - i) g s x‖ := by calc ‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s x‖ ≤ ‖B.precompR Du‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 g s) s x‖ := IH _ (hf.of_le (Nat.cast_le.2 (Nat.le_succ n))) (hg.fderivWithin hs In) _ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 g s) s x‖ := mul_le_mul_of_nonneg_right (B.norm_precompR_le Du) (by positivity) _ = _ := by congr 1 apply Finset.sum_congr rfl fun i hi => ?_ rw [Nat.succ_sub (Nat.lt_succ_iff.1 (Finset.mem_range.1 hi)), ← norm_iteratedFDerivWithin_fderivWithin hs hx] -- Porting note: the next line is a hack allowing Lean to find the operator norm instance. let norm := @ContinuousLinearMap.hasOpNorm _ _ (Du →L[𝕜] Eu) (Fu →L[𝕜] Du →L[𝕜] Gu) _ _ _ _ _ _ (RingHom.id 𝕜) have I2 : ‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x‖ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 (i + 1) f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := calc ‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x‖ ≤ ‖B.precompL Du‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 f s) s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := IH _ (hf.fderivWithin hs In) (hg.of_le (Nat.cast_le.2 (Nat.le_succ n))) _ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 f s) s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := mul_le_mul_of_nonneg_right (B.norm_precompL_le Du) (by positivity) _ = _ := by congr 1 apply Finset.sum_congr rfl fun i _ => ?_ rw [← norm_iteratedFDerivWithin_fderivWithin hs hx] have J : iteratedFDerivWithin 𝕜 n (fun y : Du => fderivWithin 𝕜 (fun y : Du => B (f y) (g y)) s y) s x = iteratedFDerivWithin 𝕜 n (fun y => B.precompR Du (f y) (fderivWithin 𝕜 g s y) + B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x := by apply iteratedFDerivWithin_congr (fun y hy => ?_) hx have L : (1 : WithTop ℕ∞) ≤ n.succ := by simpa only [ENat.coe_one, Nat.one_le_cast] using Nat.succ_pos n exact B.fderivWithin_of_bilinear (hf.differentiableOn L y hy) (hg.differentiableOn L y hy) (hs y hy) rw [← norm_iteratedFDerivWithin_fderivWithin hs hx, J] have A : ContDiffOn 𝕜 n (fun y => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s := (B.precompR Du).isBoundedBilinearMap.contDiff.comp₂_contDiffOn (hf.of_le (Nat.cast_le.2 (Nat.le_succ n))) (hg.fderivWithin hs In) have A' : ContDiffOn 𝕜 n (fun y => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s := (B.precompL Du).isBoundedBilinearMap.contDiff.comp₂_contDiffOn (hf.fderivWithin hs In) (hg.of_le (Nat.cast_le.2 (Nat.le_succ n))) rw [iteratedFDerivWithin_add_apply' (A.contDiffWithinAt hx) (A'.contDiffWithinAt hx) hs hx] apply (norm_add_le _ _).trans ((add_le_add I1 I2).trans (le_of_eq ?_)) simp_rw [← mul_add, mul_assoc] congr 1 exact (Finset.sum_choose_succ_mul (fun i j => ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 j g s x‖) n).symm /-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the iterated derivatives of `f` and `g` when `B` is bilinear: `‖D^n (x ↦ B (f x) (g x))‖ ≤ ‖B‖ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/ theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear (B : E →L[𝕜] F →L[𝕜] G) {f : D → E} {g : D → F} {N : WithTop ℕ∞} {s : Set D} {x : D} (hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by /- We reduce the bound to the case where all spaces live in the same universe (in which we already have proved the result), by using linear isometries between the spaces and their `ULift` to a common universe. These linear isometries preserve the norm of the iterated derivative. -/ let Du : Type max uD uE uF uG := ULift.{max uE uF uG, uD} D let Eu : Type max uD uE uF uG := ULift.{max uD uF uG, uE} E let Fu : Type max uD uE uF uG := ULift.{max uD uE uG, uF} F let Gu : Type max uD uE uF uG := ULift.{max uD uE uF, uG} G have isoD : Du ≃ₗᵢ[𝕜] D := LinearIsometryEquiv.ulift 𝕜 D have isoE : Eu ≃ₗᵢ[𝕜] E := LinearIsometryEquiv.ulift 𝕜 E have isoF : Fu ≃ₗᵢ[𝕜] F := LinearIsometryEquiv.ulift 𝕜 F have isoG : Gu ≃ₗᵢ[𝕜] G := LinearIsometryEquiv.ulift 𝕜 G -- lift `f` and `g` to versions `fu` and `gu` on the lifted spaces. let fu : Du → Eu := isoE.symm ∘ f ∘ isoD let gu : Du → Fu := isoF.symm ∘ g ∘ isoD -- lift the bilinear map `B` to a bilinear map `Bu` on the lifted spaces. let Bu₀ : Eu →L[𝕜] Fu →L[𝕜] G := ((B.comp (isoE : Eu →L[𝕜] E)).flip.comp (isoF : Fu →L[𝕜] F)).flip let Bu : Eu →L[𝕜] Fu →L[𝕜] Gu := ContinuousLinearMap.compL 𝕜 Eu (Fu →L[𝕜] G) (Fu →L[𝕜] Gu) (ContinuousLinearMap.compL 𝕜 Fu G Gu (isoG.symm : G →L[𝕜] Gu)) Bu₀ have hBu : Bu = ContinuousLinearMap.compL 𝕜 Eu (Fu →L[𝕜] G) (Fu →L[𝕜] Gu) (ContinuousLinearMap.compL 𝕜 Fu G Gu (isoG.symm : G →L[𝕜] Gu)) Bu₀ := rfl have Bu_eq : (fun y => Bu (fu y) (gu y)) = isoG.symm ∘ (fun y => B (f y) (g y)) ∘ isoD := by ext1 y simp [Du, Eu, Fu, Gu, hBu, Bu₀, fu, gu] -- All norms are preserved by the lifting process. have Bu_le : ‖Bu‖ ≤ ‖B‖ := by refine ContinuousLinearMap.opNorm_le_bound _ (norm_nonneg B) fun y => ?_ refine ContinuousLinearMap.opNorm_le_bound _ (by positivity) fun x => ?_ simp only [Du, Eu, Fu, Gu, hBu, Bu₀, compL_apply, coe_comp', Function.comp_apply, ContinuousLinearEquiv.coe_coe, LinearIsometryEquiv.coe_coe, flip_apply, LinearIsometryEquiv.norm_map] calc ‖B (isoE y) (isoF x)‖ ≤ ‖B (isoE y)‖ * ‖isoF x‖ := ContinuousLinearMap.le_opNorm _ _ _ ≤ ‖B‖ * ‖isoE y‖ * ‖isoF x‖ := by gcongr; apply ContinuousLinearMap.le_opNorm _ = ‖B‖ * ‖y‖ * ‖x‖ := by simp only [LinearIsometryEquiv.norm_map] let su := isoD ⁻¹' s have hsu : UniqueDiffOn 𝕜 su := isoD.toContinuousLinearEquiv.uniqueDiffOn_preimage_iff.2 hs let xu := isoD.symm x have hxu : xu ∈ su := by simpa only [xu, su, Set.mem_preimage, LinearIsometryEquiv.apply_symm_apply] using hx have xu_x : isoD xu = x := by simp only [xu, LinearIsometryEquiv.apply_symm_apply] have hfu : ContDiffOn 𝕜 n fu su := isoE.symm.contDiff.comp_contDiffOn ((hf.of_le hn).comp_continuousLinearMap (isoD : Du →L[𝕜] D)) have hgu : ContDiffOn 𝕜 n gu su := isoF.symm.contDiff.comp_contDiffOn ((hg.of_le hn).comp_continuousLinearMap (isoD : Du →L[𝕜] D)) have Nfu : ∀ i, ‖iteratedFDerivWithin 𝕜 i fu su xu‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by intro i rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hsu hxu] rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ hs, xu_x] rwa [← xu_x] at hx have Ngu : ∀ i, ‖iteratedFDerivWithin 𝕜 i gu su xu‖ = ‖iteratedFDerivWithin 𝕜 i g s x‖ := by intro i rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hsu hxu] rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ hs, xu_x] rwa [← xu_x] at hx have NBu : ‖iteratedFDerivWithin 𝕜 n (fun y => Bu (fu y) (gu y)) su xu‖ = ‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ := by rw [Bu_eq] rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hsu hxu] rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ hs, xu_x] rwa [← xu_x] at hx -- state the bound for the lifted objects, and deduce the original bound from it. have : ‖iteratedFDerivWithin 𝕜 n (fun y => Bu (fu y) (gu y)) su xu‖ ≤ ‖Bu‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i fu su xu‖ * ‖iteratedFDerivWithin 𝕜 (n - i) gu su xu‖ := Bu.norm_iteratedFDerivWithin_le_of_bilinear_aux hfu hgu hsu hxu simp only [Nfu, Ngu, NBu] at this exact this.trans (mul_le_mul_of_nonneg_right Bu_le (by positivity)) /-- Bounding the norm of the iterated derivative of `B (f x) (g x)` in terms of the iterated derivatives of `f` and `g` when `B` is bilinear: `‖D^n (x ↦ B (f x) (g x))‖ ≤ ‖B‖ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/ theorem ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear (B : E →L[𝕜] F →L[𝕜] G) {f : D → E} {g : D → F} {N : WithTop ℕ∞} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : D) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDeriv 𝕜 n (fun y => B (f y) (g y)) x‖ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by simp_rw [← iteratedFDerivWithin_univ] exact B.norm_iteratedFDerivWithin_le_of_bilinear hf.contDiffOn hg.contDiffOn uniqueDiffOn_univ (mem_univ x) hn /-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the iterated derivatives of `f` and `g` when `B` is bilinear of norm at most `1`: `‖D^n (x ↦ B (f x) (g x))‖ ≤ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/ theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_of_le_one (B : E →L[𝕜] F →L[𝕜] G) {f : D → E} {g : D → F} {N : WithTop ℕ∞} {s : Set D} {x : D} (hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {n : ℕ} (hn : n ≤ N) (hB : ‖B‖ ≤ 1) : ‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by apply (B.norm_iteratedFDerivWithin_le_of_bilinear hf hg hs hx hn).trans exact mul_le_of_le_one_left (by positivity) hB /-- Bounding the norm of the iterated derivative of `B (f x) (g x)` in terms of the iterated derivatives of `f` and `g` when `B` is bilinear of norm at most `1`: `‖D^n (x ↦ B (f x) (g x))‖ ≤ ∑_{k ≤ n} n.choose k ‖D^k f‖ ‖D^{n-k} g‖` -/ theorem ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear_of_le_one (B : E →L[𝕜] F →L[𝕜] G) {f : D → E} {g : D → F} {N : WithTop ℕ∞} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : D) {n : ℕ} (hn : n ≤ N) (hB : ‖B‖ ≤ 1) : ‖iteratedFDeriv 𝕜 n (fun y => B (f y) (g y)) x‖ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by simp_rw [← iteratedFDerivWithin_univ] exact B.norm_iteratedFDerivWithin_le_of_bilinear_of_le_one hf.contDiffOn hg.contDiffOn uniqueDiffOn_univ (mem_univ x) hn hB section variable {𝕜' : Type*} [NormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F] [IsScalarTower 𝕜 𝕜' F] theorem norm_iteratedFDerivWithin_smul_le {f : E → 𝕜'} {g : E → F} {N : WithTop ℕ∞} (hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) {x : E} (hx : x ∈ s) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y => f y • g y) s x‖ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := (ContinuousLinearMap.lsmul 𝕜 𝕜' : 𝕜' →L[𝕜] F →L[𝕜] F).norm_iteratedFDerivWithin_le_of_bilinear_of_le_one hf hg hs hx hn ContinuousLinearMap.opNorm_lsmul_le theorem norm_iteratedFDeriv_smul_le {f : E → 𝕜'} {g : E → F} {N : WithTop ℕ∞} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : E) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDeriv 𝕜 n (fun y => f y • g y) x‖ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := (ContinuousLinearMap.lsmul 𝕜 𝕜' : 𝕜' →L[𝕜] F →L[𝕜] F).norm_iteratedFDeriv_le_of_bilinear_of_le_one hf hg x hn ContinuousLinearMap.opNorm_lsmul_le end section variable {ι : Type*} {A : Type*} [NormedRing A] [NormedAlgebra 𝕜 A] {A' : Type*} [NormedCommRing A'] [NormedAlgebra 𝕜 A'] theorem norm_iteratedFDerivWithin_mul_le {f : E → A} {g : E → A} {N : WithTop ℕ∞} (hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) {x : E} (hx : x ∈ s) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y => f y * g y) s x‖ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := (ContinuousLinearMap.mul 𝕜 A : A →L[𝕜] A →L[𝕜] A).norm_iteratedFDerivWithin_le_of_bilinear_of_le_one hf hg hs hx hn (ContinuousLinearMap.opNorm_mul_le _ _) theorem norm_iteratedFDeriv_mul_le {f : E → A} {g : E → A} {N : WithTop ℕ∞} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : E) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDeriv 𝕜 n (fun y => f y * g y) x‖ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by simp_rw [← iteratedFDerivWithin_univ] exact norm_iteratedFDerivWithin_mul_le hf.contDiffOn hg.contDiffOn uniqueDiffOn_univ (mem_univ x) hn -- TODO: Add `norm_iteratedFDeriv[Within]_list_prod_le` for non-commutative `NormedRing A`. theorem norm_iteratedFDerivWithin_prod_le [DecidableEq ι] [NormOneClass A'] {u : Finset ι} {f : ι → E → A'} {N : WithTop ℕ∞} (hf : ∀ i ∈ u, ContDiffOn 𝕜 N (f i) s) (hs : UniqueDiffOn 𝕜 s) {x : E} (hx : x ∈ s) {n : ℕ} (hn : n ≤ N) : ‖iteratedFDerivWithin 𝕜 n (∏ j ∈ u, f j ·) s x‖ ≤ ∑ p ∈ u.sym n, (p : Multiset ι).multinomial * ∏ j ∈ u, ‖iteratedFDerivWithin 𝕜 (Multiset.count j p) (f j) s x‖ := by induction u using Finset.induction generalizing n with | empty => cases n with | zero => simp [Sym.eq_nil_of_card_zero] | succ n => simp [iteratedFDerivWithin_succ_const] | insert i u hi IH => conv => lhs; simp only [Finset.prod_insert hi] simp only [Finset.mem_insert, forall_eq_or_imp] at hf refine le_trans (norm_iteratedFDerivWithin_mul_le hf.1 (contDiffOn_prod hf.2) hs hx hn) ?_ rw [← Finset.sum_coe_sort (Finset.sym _ _)] rw [Finset.sum_equiv (Finset.symInsertEquiv hi) (t := Finset.univ) (g := (fun v ↦ v.multinomial * ∏ j ∈ insert i u, ‖iteratedFDerivWithin 𝕜 (v.count j) (f j) s x‖) ∘ Sym.toMultiset ∘ Subtype.val ∘ (Finset.symInsertEquiv hi).symm) (by simp) (by simp only [← comp_apply (g := Finset.symInsertEquiv hi), comp_assoc]; simp)] rw [← Finset.univ_sigma_univ, Finset.sum_sigma, Finset.sum_range] simp only [comp_apply, Finset.symInsertEquiv_symm_apply_coe] refine Finset.sum_le_sum ?_ intro m _ specialize IH hf.2 (n := n - m) (le_trans (by exact_mod_cast n.sub_le m) hn) refine le_trans (mul_le_mul_of_nonneg_left IH (by simp [mul_nonneg])) ?_ rw [Finset.mul_sum, ← Finset.sum_coe_sort] refine Finset.sum_le_sum ?_ simp only [Finset.mem_univ, forall_true_left, Subtype.forall, Finset.mem_sym_iff] intro p hp refine le_of_eq ?_ rw [Finset.prod_insert hi] have hip : i ∉ p := mt (hp i) hi rw [Sym.count_coe_fill_self_of_not_mem hip, Sym.multinomial_coe_fill_of_not_mem hip] suffices ∏ j ∈ u, ‖iteratedFDerivWithin 𝕜 (Multiset.count j p) (f j) s x‖ = ∏ j ∈ u, ‖iteratedFDerivWithin 𝕜 (Multiset.count j (Sym.fill i m p)) (f j) s x‖ by rw [this, Nat.cast_mul] ring refine Finset.prod_congr rfl ?_ intro j hj have hji : j ≠ i := mt (· ▸ hj) hi rw [Sym.count_coe_fill_of_ne hji] theorem norm_iteratedFDeriv_prod_le [DecidableEq ι] [NormOneClass A'] {u : Finset ι} {f : ι → E → A'} {N : WithTop ℕ∞} (hf : ∀ i ∈ u, ContDiff 𝕜 N (f i)) {x : E} {n : ℕ} (hn : n ≤ N) : ‖iteratedFDeriv 𝕜 n (∏ j ∈ u, f j ·) x‖ ≤ ∑ p ∈ u.sym n, (p : Multiset ι).multinomial * ∏ j ∈ u, ‖iteratedFDeriv 𝕜 ((p : Multiset ι).count j) (f j) x‖ := by simpa [iteratedFDerivWithin_univ] using norm_iteratedFDerivWithin_prod_le (fun i hi ↦ (hf i hi).contDiffOn) uniqueDiffOn_univ (mem_univ x) hn end /-- If the derivatives within a set of `g` at `f x` are bounded by `C`, and the `i`-th derivative within a set of `f` at `x` is bounded by `D^i` for all `1 ≤ i ≤ n`, then the `n`-th derivative of `g ∘ f` is bounded by `n! * C * D^n`. This lemma proves this estimate assuming additionally that two of the spaces live in the same universe, to make an induction possible. Use instead `norm_iteratedFDerivWithin_comp_le` that removes this assumption. -/ theorem norm_iteratedFDerivWithin_comp_le_aux {Fu Gu : Type u} [NormedAddCommGroup Fu] [NormedSpace 𝕜 Fu] [NormedAddCommGroup Gu] [NormedSpace 𝕜 Gu] {g : Fu → Gu} {f : E → Fu} {n : ℕ} {s : Set E} {t : Set Fu} {x : E} (hg : ContDiffOn 𝕜 n g t) (hf : ContDiffOn 𝕜 n f s) (ht : UniqueDiffOn 𝕜 t) (hs : UniqueDiffOn 𝕜 s) (hst : MapsTo f s t) (hx : x ∈ s) {C : ℝ} {D : ℝ} (hC : ∀ i, i ≤ n → ‖iteratedFDerivWithin 𝕜 i g t (f x)‖ ≤ C) (hD : ∀ i, 1 ≤ i → i ≤ n → ‖iteratedFDerivWithin 𝕜 i f s x‖ ≤ D ^ i) : ‖iteratedFDerivWithin 𝕜 n (g ∘ f) s x‖ ≤ n ! * C * D ^ n := by /- We argue by induction on `n`, using that `D^(n+1) (g ∘ f) = D^n (g ' ∘ f ⬝ f')`. The successive derivatives of `g' ∘ f` are controlled thanks to the inductive assumption, and those of `f'` are controlled by assumption. As composition of linear maps is a bilinear map, one may use `ContinuousLinearMap.norm_iteratedFDeriv_le_of_bilinear_of_le_one` to get from these a bound on `D^n (g ' ∘ f ⬝ f')`. -/ induction' n using Nat.case_strong_induction_on with n IH generalizing Gu · simpa [norm_iteratedFDerivWithin_zero, Nat.factorial_zero, algebraMap.coe_one, one_mul, pow_zero, mul_one, comp_apply] using hC 0 le_rfl have M : (n : WithTop ℕ∞) < n.succ := Nat.cast_lt.2 n.lt_succ_self have Cnonneg : 0 ≤ C := (norm_nonneg _).trans (hC 0 bot_le) have Dnonneg : 0 ≤ D := by have : 1 ≤ n + 1 := by simp only [le_add_iff_nonneg_left, zero_le'] simpa only [pow_one] using (norm_nonneg _).trans (hD 1 le_rfl this) -- use the inductive assumption to bound the derivatives of `g' ∘ f`. have I : ∀ i ∈ Finset.range (n + 1), ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 g t ∘ f) s x‖ ≤ i ! * C * D ^ i := by intro i hi simp only [Finset.mem_range_succ_iff] at hi apply IH i hi · apply hg.fderivWithin ht simp only [Nat.cast_succ] exact add_le_add_right (Nat.cast_le.2 hi) _ · apply hf.of_le (Nat.cast_le.2 (hi.trans n.le_succ)) · intro j hj have : ‖iteratedFDerivWithin 𝕜 j (fderivWithin 𝕜 g t) t (f x)‖ = ‖iteratedFDerivWithin 𝕜 (j + 1) g t (f x)‖ := by rw [iteratedFDerivWithin_succ_eq_comp_right ht (hst hx), comp_apply, LinearIsometryEquiv.norm_map] rw [this] exact hC (j + 1) (add_le_add (hj.trans hi) le_rfl) · intro j hj h'j exact hD j hj (h'j.trans (hi.trans n.le_succ)) -- reformulate `hD` as a bound for the derivatives of `f'`. have J : ∀ i, ‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 f s) s x‖ ≤ D ^ (n - i + 1) := by intro i have : ‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 f s) s x‖ = ‖iteratedFDerivWithin 𝕜 (n - i + 1) f s x‖ := by rw [iteratedFDerivWithin_succ_eq_comp_right hs hx, comp_apply, LinearIsometryEquiv.norm_map] rw [this] apply hD · simp only [le_add_iff_nonneg_left, zero_le'] · apply Nat.succ_le_succ tsub_le_self -- Now put these together: first, notice that we have to bound `D^n (g' ∘ f ⬝ f')`. calc ‖iteratedFDerivWithin 𝕜 (n + 1) (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 n (fun y : E => fderivWithin 𝕜 (g ∘ f) s y) s x‖ := by rw [iteratedFDerivWithin_succ_eq_comp_right hs hx, comp_apply, LinearIsometryEquiv.norm_map] _ = ‖iteratedFDerivWithin 𝕜 n (fun y : E => ContinuousLinearMap.compL 𝕜 E Fu Gu (fderivWithin 𝕜 g t (f y)) (fderivWithin 𝕜 f s y)) s x‖ := by have L : (1 : WithTop ℕ∞) ≤ n.succ := by simpa only [ENat.coe_one, Nat.one_le_cast] using n.succ_pos congr 1 refine iteratedFDerivWithin_congr (fun y hy => ?_) hx _ apply fderivWithin_comp _ _ _ hst (hs y hy) · exact hg.differentiableOn L _ (hst hy) · exact hf.differentiableOn L _ hy -- bound it using the fact that the composition of linear maps is a bilinear operation, -- for which we have bounds for the`n`-th derivative. _ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 g t ∘ f) s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 f s) s x‖ := by have A : ContDiffOn 𝕜 n (fderivWithin 𝕜 g t ∘ f) s := by apply ContDiffOn.comp _ (hf.of_le M.le) hst apply hg.fderivWithin ht simp only [Nat.cast_succ, le_refl] have B : ContDiffOn 𝕜 n (fderivWithin 𝕜 f s) s := by apply hf.fderivWithin hs simp only [Nat.cast_succ, le_refl] exact (ContinuousLinearMap.compL 𝕜 E Fu Gu).norm_iteratedFDerivWithin_le_of_bilinear_of_le_one A B hs hx le_rfl (ContinuousLinearMap.norm_compL_le 𝕜 E Fu Gu) -- bound each of the terms using the estimates on previous derivatives (that use the inductive -- assumption for `g' ∘ f`). _ ≤ ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * (i ! * C * D ^ i) * D ^ (n - i + 1) := by gcongr with i hi · exact I i hi · exact J i -- We are left with trivial algebraic manipulations to see that this is smaller than -- the claimed bound. _ = ∑ i ∈ Finset.range (n + 1), (n ! : ℝ) * ((i ! : ℝ)⁻¹ * i !) * C * (D ^ i * D ^ (n - i + 1)) * ((n - i)! : ℝ)⁻¹ := by congr! 1 with i hi simp only [Nat.cast_choose ℝ (Finset.mem_range_succ_iff.1 hi), div_eq_inv_mul, mul_inv] ring _ = ∑ i ∈ Finset.range (n + 1), (n ! : ℝ) * 1 * C * D ^ (n + 1) * ((n - i)! : ℝ)⁻¹ := by congr! with i hi · apply inv_mul_cancel₀ simpa only [Ne, Nat.cast_eq_zero] using i.factorial_ne_zero · rw [← pow_add] congr 1 rw [Nat.add_succ, Nat.succ_inj] exact Nat.add_sub_of_le (Finset.mem_range_succ_iff.1 hi) _ ≤ ∑ i ∈ Finset.range (n + 1), (n ! : ℝ) * 1 * C * D ^ (n + 1) * 1 := by gcongr with i apply inv_le_one_of_one_le₀ simpa only [Nat.one_le_cast] using (n - i).factorial_pos _ = (n + 1)! * C * D ^ (n + 1) := by simp only [mul_assoc, mul_one, Finset.sum_const, Finset.card_range, nsmul_eq_mul, Nat.factorial_succ, Nat.cast_mul] /-- If the derivatives within a set of `g` at `f x` are bounded by `C`, and the `i`-th derivative within a set of `f` at `x` is bounded by `D^i` for all `1 ≤ i ≤ n`, then the `n`-th derivative of `g ∘ f` is bounded by `n! * C * D^n`. -/ theorem norm_iteratedFDerivWithin_comp_le {g : F → G} {f : E → F} {n : ℕ} {s : Set E} {t : Set F} {x : E} {N : WithTop ℕ∞} (hg : ContDiffOn 𝕜 N g t) (hf : ContDiffOn 𝕜 N f s) (hn : n ≤ N) (ht : UniqueDiffOn 𝕜 t) (hs : UniqueDiffOn 𝕜 s) (hst : MapsTo f s t) (hx : x ∈ s) {C : ℝ} {D : ℝ} (hC : ∀ i, i ≤ n → ‖iteratedFDerivWithin 𝕜 i g t (f x)‖ ≤ C) (hD : ∀ i, 1 ≤ i → i ≤ n → ‖iteratedFDerivWithin 𝕜 i f s x‖ ≤ D ^ i) : ‖iteratedFDerivWithin 𝕜 n (g ∘ f) s x‖ ≤ n ! * C * D ^ n := by /- We reduce the bound to the case where all spaces live in the same universe (in which we already have proved the result), by using linear isometries between the spaces and their `ULift` to a common universe. These linear isometries preserve the norm of the iterated derivative. -/ let Fu : Type max uF uG := ULift.{uG, uF} F let Gu : Type max uF uG := ULift.{uF, uG} G have isoF : Fu ≃ₗᵢ[𝕜] F := LinearIsometryEquiv.ulift 𝕜 F have isoG : Gu ≃ₗᵢ[𝕜] G := LinearIsometryEquiv.ulift 𝕜 G -- lift `f` and `g` to versions `fu` and `gu` on the lifted spaces. let fu : E → Fu := isoF.symm ∘ f let gu : Fu → Gu := isoG.symm ∘ g ∘ isoF let tu := isoF ⁻¹' t have htu : UniqueDiffOn 𝕜 tu := isoF.toContinuousLinearEquiv.uniqueDiffOn_preimage_iff.2 ht have hstu : MapsTo fu s tu := fun y hy ↦ by simpa only [fu, tu, mem_preimage, comp_apply, LinearIsometryEquiv.apply_symm_apply] using hst hy have Ffu : isoF (fu x) = f x := by simp only [fu, comp_apply, LinearIsometryEquiv.apply_symm_apply] -- All norms are preserved by the lifting process. have hfu : ContDiffOn 𝕜 n fu s := isoF.symm.contDiff.comp_contDiffOn (hf.of_le hn) have hgu : ContDiffOn 𝕜 n gu tu := isoG.symm.contDiff.comp_contDiffOn ((hg.of_le hn).comp_continuousLinearMap (isoF : Fu →L[𝕜] F)) have Nfu : ∀ i, ‖iteratedFDerivWithin 𝕜 i fu s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := fun i ↦ by rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hs hx] simp_rw [← Nfu] at hD have Ngu : ∀ i, ‖iteratedFDerivWithin 𝕜 i gu tu (fu x)‖ = ‖iteratedFDerivWithin 𝕜 i g t (f x)‖ := fun i ↦ by rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ htu (hstu hx)] rw [LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right _ _ ht, Ffu] rw [Ffu] exact hst hx simp_rw [← Ngu] at hC have Nfgu : ‖iteratedFDerivWithin 𝕜 n (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 n (gu ∘ fu) s x‖ := by have : gu ∘ fu = isoG.symm ∘ g ∘ f := by ext x simp only [fu, gu, comp_apply, LinearIsometryEquiv.map_eq_iff, LinearIsometryEquiv.apply_symm_apply] rw [this, LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left _ _ hs hx] -- deduce the required bound from the one for `gu ∘ fu`. rw [Nfgu] exact norm_iteratedFDerivWithin_comp_le_aux hgu hfu htu hs hstu hx hC hD /-- If the derivatives of `g` at `f x` are bounded by `C`, and the `i`-th derivative of `f` at `x` is bounded by `D^i` for all `1 ≤ i ≤ n`, then the `n`-th derivative of `g ∘ f` is bounded by `n! * C * D^n`. -/ theorem norm_iteratedFDeriv_comp_le {g : F → G} {f : E → F} {n : ℕ} {N : WithTop ℕ∞} (hg : ContDiff 𝕜 N g) (hf : ContDiff 𝕜 N f) (hn : n ≤ N) (x : E) {C : ℝ} {D : ℝ} (hC : ∀ i, i ≤ n → ‖iteratedFDeriv 𝕜 i g (f x)‖ ≤ C) (hD : ∀ i, 1 ≤ i → i ≤ n → ‖iteratedFDeriv 𝕜 i f x‖ ≤ D ^ i) : ‖iteratedFDeriv 𝕜 n (g ∘ f) x‖ ≤ n ! * C * D ^ n := by simp_rw [← iteratedFDerivWithin_univ] at hC hD ⊢ exact norm_iteratedFDerivWithin_comp_le hg.contDiffOn hf.contDiffOn hn uniqueDiffOn_univ uniqueDiffOn_univ (mapsTo_univ _ _) (mem_univ x) hC hD section Apply theorem norm_iteratedFDerivWithin_clm_apply {f : E → F →L[𝕜] G} {g : E → F} {s : Set E} {x : E} {N : WithTop ℕ∞} {n : ℕ} (hf : ContDiffOn 𝕜 N f s) (hg : ContDiffOn 𝕜 N g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (hn : n ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y => (f y) (g y)) s x‖ ≤ ∑ i ∈ Finset.range (n + 1), ↑(n.choose i) * ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by let B : (F →L[𝕜] G) →L[𝕜] F →L[𝕜] G := ContinuousLinearMap.flip (ContinuousLinearMap.apply 𝕜 G) have hB : ‖B‖ ≤ 1 := by simp only [B, ContinuousLinearMap.opNorm_flip, ContinuousLinearMap.apply] refine ContinuousLinearMap.opNorm_le_bound _ zero_le_one fun f => ?_ simp only [ContinuousLinearMap.coe_id', id, one_mul] rfl exact B.norm_iteratedFDerivWithin_le_of_bilinear_of_le_one hf hg hs hx hn hB theorem norm_iteratedFDeriv_clm_apply {f : E → F →L[𝕜] G} {g : E → F} {N : WithTop ℕ∞} {n : ℕ} (hf : ContDiff 𝕜 N f) (hg : ContDiff 𝕜 N g) (x : E) (hn : n ≤ N) : ‖iteratedFDeriv 𝕜 n (fun y : E => (f y) (g y)) x‖ ≤ ∑ i ∈ Finset.range (n + 1), ↑(n.choose i) * ‖iteratedFDeriv 𝕜 i f x‖ * ‖iteratedFDeriv 𝕜 (n - i) g x‖ := by simp only [← iteratedFDerivWithin_univ] exact norm_iteratedFDerivWithin_clm_apply hf.contDiffOn hg.contDiffOn uniqueDiffOn_univ (Set.mem_univ x) hn theorem norm_iteratedFDerivWithin_clm_apply_const {f : E → F →L[𝕜] G} {c : F} {s : Set E} {x : E} {N : WithTop ℕ∞} {n : ℕ} (hf : ContDiffWithinAt 𝕜 N f s x) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (hn : n ≤ N) : ‖iteratedFDerivWithin 𝕜 n (fun y : E => (f y) c) s x‖ ≤ ‖c‖ * ‖iteratedFDerivWithin 𝕜 n f s x‖ := by let g : (F →L[𝕜] G) →L[𝕜] G := ContinuousLinearMap.apply 𝕜 G c
have h := g.norm_compContinuousMultilinearMap_le (iteratedFDerivWithin 𝕜 n f s x) rw [← g.iteratedFDerivWithin_comp_left hf hs hx hn] at h refine h.trans (mul_le_mul_of_nonneg_right ?_ (norm_nonneg _)) refine g.opNorm_le_bound (norm_nonneg _) fun f => ?_ rw [ContinuousLinearMap.apply_apply, mul_comm] exact f.le_opNorm c
Mathlib/Analysis/Calculus/ContDiff/Bounds.lean
551
557
/- Copyright (c) 2023 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash -/ import Mathlib.Algebra.Lie.Weights.Basic import Mathlib.LinearAlgebra.Trace import Mathlib.LinearAlgebra.FreeModule.PID /-! # Lie modules with linear weights Given a Lie module `M` over a nilpotent Lie algebra `L` with coefficients in `R`, one frequently studies `M` via its weights. These are functions `χ : L → R` whose corresponding weight space `LieModule.genWeightSpace M χ`, is non-trivial. If `L` is Abelian or if `R` has characteristic zero (and `M` is finite-dimensional) then such `χ` are necessarily `R`-linear. However in general non-linear weights do exist. For example if we take: * `R`: the field with two elements (or indeed any perfect field of characteristic two), * `L`: `sl₂` (this is nilpotent in characteristic two), * `M`: the natural two-dimensional representation of `L`, then there is a single weight and it is non-linear. (See remark following Proposition 9 of chapter VII, §1.3 in [N. Bourbaki, Chapters 7--9](bourbaki1975b).) We thus introduce a typeclass `LieModule.LinearWeights` to encode the fact that a Lie module does have linear weights and provide typeclass instances in the two important cases that `L` is Abelian or `R` has characteristic zero. ## Main definitions * `LieModule.LinearWeights`: a typeclass encoding the fact that a given Lie module has linear weights, and furthermore that the weights vanish on the derived ideal. * `LieModule.instLinearWeightsOfCharZero`: a typeclass instance encoding the fact that for an Abelian Lie algebra, the weights of any Lie module are linear. * `LieModule.instLinearWeightsOfIsLieAbelian`: a typeclass instance encoding the fact that in characteristic zero, the weights of any finite-dimensional Lie module are linear. * `LieModule.exists_forall_lie_eq_smul`: existence of simultaneous eigenvectors from existence of simultaneous generalized eigenvectors for Noetherian Lie modules with linear weights. -/ open Set variable (k R L M : Type*) [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M] [LieRingModule L M] [LieModule R L M] namespace LieModule /-- A typeclass encoding the fact that a given Lie module has linear weights, vanishing on the derived ideal. -/ class LinearWeights [LieRing.IsNilpotent L] : Prop where map_add : ∀ χ : L → R, genWeightSpace M χ ≠ ⊥ → ∀ x y, χ (x + y) = χ x + χ y map_smul : ∀ χ : L → R, genWeightSpace M χ ≠ ⊥ → ∀ (t : R) x, χ (t • x) = t • χ x map_lie : ∀ χ : L → R, genWeightSpace M χ ≠ ⊥ → ∀ x y : L, χ ⁅x, y⁆ = 0 namespace Weight variable [LieRing.IsNilpotent L] [LinearWeights R L M] (χ : Weight R L M) /-- A weight of a Lie module, bundled as a linear map. -/ @[simps] def toLinear : L →ₗ[R] R where toFun := χ map_add' := LinearWeights.map_add χ χ.genWeightSpace_ne_bot map_smul' := LinearWeights.map_smul χ χ.genWeightSpace_ne_bot instance instCoeLinearMap : CoeOut (Weight R L M) (L →ₗ[R] R) where coe := Weight.toLinear R L M instance instLinearMapClass : LinearMapClass (Weight R L M) R L R where map_add χ := LinearWeights.map_add χ χ.genWeightSpace_ne_bot map_smulₛₗ χ := LinearWeights.map_smul χ χ.genWeightSpace_ne_bot variable {R L M χ} @[simp] lemma apply_lie (x y : L) : χ ⁅x, y⁆ = 0 := LinearWeights.map_lie χ χ.genWeightSpace_ne_bot x y @[simp] lemma coe_coe : (↑(χ : L →ₗ[R] R) : L → R) = (χ : L → R) := rfl @[simp] lemma coe_toLinear_eq_zero_iff : (χ : L →ₗ[R] R) = 0 ↔ χ.IsZero := ⟨fun h ↦ funext fun x ↦ LinearMap.congr_fun h x, fun h ↦ by ext; simp [h.eq]⟩ lemma coe_toLinear_ne_zero_iff : (χ : L →ₗ[R] R) ≠ 0 ↔ χ.IsNonZero := by simp /-- The kernel of a weight of a Lie module with linear weights. -/ abbrev ker := LinearMap.ker (χ : L →ₗ[R] R) end Weight /-- For an Abelian Lie algebra, the weights of any Lie module are linear. -/ instance instLinearWeightsOfIsLieAbelian [IsLieAbelian L] [NoZeroSMulDivisors R M] : LinearWeights R L M := have aux : ∀ (χ : L → R), genWeightSpace M χ ≠ ⊥ → ∀ (x y : L), χ (x + y) = χ x + χ y := by have h : ∀ x y, Commute (toEnd R L M x) (toEnd R L M y) := fun x y ↦ by rw [commute_iff_lie_eq, ← LieHom.map_lie, trivial_lie_zero, LieHom.map_zero] intro χ hχ x y simp_rw [Ne, ← LieSubmodule.toSubmodule_inj, genWeightSpace, genWeightSpaceOf, LieSubmodule.iInf_toSubmodule, LieSubmodule.bot_toSubmodule] at hχ exact Module.End.map_add_of_iInf_genEigenspace_ne_bot_of_commute (toEnd R L M).toLinearMap χ _ hχ h x y { map_add := aux map_smul := fun χ hχ t x ↦ by simp_rw [Ne, ← LieSubmodule.toSubmodule_inj, genWeightSpace, genWeightSpaceOf, LieSubmodule.iInf_toSubmodule, LieSubmodule.bot_toSubmodule] at hχ exact Module.End.map_smul_of_iInf_genEigenspace_ne_bot (toEnd R L M).toLinearMap χ _ hχ t x map_lie := fun χ hχ t x ↦ by rw [trivial_lie_zero, ← add_left_inj (χ 0), ← aux χ hχ, zero_add, zero_add] } section FiniteDimensional open Module variable [IsDomain R] [IsPrincipalIdealRing R] [Module.Free R M] [Module.Finite R M] [LieRing.IsNilpotent L] lemma trace_comp_toEnd_genWeightSpace_eq (χ : L → R) :
LinearMap.trace R _ ∘ₗ (toEnd R L (genWeightSpace M χ)).toLinearMap = finrank R (genWeightSpace M χ) • χ := by ext x let n := toEnd R L (genWeightSpace M χ) x - χ x • LinearMap.id have h₁ : toEnd R L (genWeightSpace M χ) x = n + χ x • LinearMap.id := eq_add_of_sub_eq rfl have h₂ : LinearMap.trace R _ n = 0 := IsReduced.eq_zero _ <| LinearMap.isNilpotent_trace_of_isNilpotent <| isNilpotent_toEnd_sub_algebraMap M χ x rw [LinearMap.comp_apply, LieHom.coe_toLinearMap, h₁, map_add, h₂] simp [mul_comm (χ x)]
Mathlib/Algebra/Lie/Weights/Linear.lean
121
130
/- Copyright (c) 2019 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen -/ import Mathlib.Algebra.Order.Star.Basic import Mathlib.Data.Matrix.RowCol /-! # Dot product of two vectors This file contains some results on the map `dotProduct`, which maps two vectors `v w : n → R` to the sum of the entrywise products `v i * w i`. ## Main results * `dotProduct_stdBasis_one`: the dot product of `v` with the `i`th standard basis vector is `v i` * `dotProduct_eq_zero_iff`: if `v`'s dot product with all `w` is zero, then `v` is zero ## Tags matrix -/ variable {m n p R : Type*} section Semiring variable [Semiring R] [Fintype n] theorem dotProduct_eq (v w : n → R) (h : ∀ u, dotProduct v u = dotProduct w u) : v = w := by funext x classical rw [← dotProduct_single_one v x, ← dotProduct_single_one w x, h] @[deprecated (since := "2024-12-12")] protected alias Matrix.dotProduct_eq := dotProduct_eq
theorem dotProduct_eq_iff {v w : n → R} : (∀ u, dotProduct v u = dotProduct w u) ↔ v = w := ⟨fun h => dotProduct_eq v w h, fun h _ => h ▸ rfl⟩ @[deprecated (since := "2024-12-12")] protected alias Matrix.dotProduct_eq_iff := dotProduct_eq_iff
Mathlib/LinearAlgebra/Matrix/DotProduct.lean
41
45
/- Copyright (c) 2021 Jakob von Raumer. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jakob von Raumer -/ import Mathlib.Tactic.CategoryTheory.Monoidal.Basic import Mathlib.CategoryTheory.Closed.Monoidal import Mathlib.Tactic.ApplyFun /-! # Rigid (autonomous) monoidal categories This file defines rigid (autonomous) monoidal categories and the necessary theory about exact pairings and duals. ## Main definitions * `ExactPairing` of two objects of a monoidal category * Type classes `HasLeftDual` and `HasRightDual` that capture that a pairing exists * The `rightAdjointMate f` as a morphism `fᘁ : Yᘁ ⟶ Xᘁ` for a morphism `f : X ⟶ Y` * The classes of `RightRigidCategory`, `LeftRigidCategory` and `RigidCategory` ## Main statements * `comp_rightAdjointMate`: The adjoint mates of the composition is the composition of adjoint mates. ## Notations * `η_` and `ε_` denote the coevaluation and evaluation morphism of an exact pairing. * `Xᘁ` and `ᘁX` denote the right and left dual of an object, as well as the adjoint mate of a morphism. ## Future work * Show that `X ⊗ Y` and `Yᘁ ⊗ Xᘁ` form an exact pairing. * Show that the left adjoint mate of the right adjoint mate of a morphism is the morphism itself. * Simplify constructions in the case where a symmetry or braiding is present. * Show that `ᘁ` gives an equivalence of categories `C ≅ (Cᵒᵖ)ᴹᵒᵖ`. * Define pivotal categories (rigid categories equipped with a natural isomorphism `ᘁᘁ ≅ 𝟙 C`). ## Notes Although we construct the adjunction `tensorLeft Y ⊣ tensorLeft X` from `ExactPairing X Y`, this is not a bijective correspondence. I think the correct statement is that `tensorLeft Y` and `tensorLeft X` are module endofunctors of `C` as a right `C` module category, and `ExactPairing X Y` is in bijection with adjunctions compatible with this right `C` action. ## References * <https://ncatlab.org/nlab/show/rigid+monoidal+category> ## Tags rigid category, monoidal category -/ open CategoryTheory MonoidalCategory universe v v₁ v₂ v₃ u u₁ u₂ u₃ noncomputable section namespace CategoryTheory variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory C] /-- An exact pairing is a pair of objects `X Y : C` which admit a coevaluation and evaluation morphism which fulfill two triangle equalities. -/ class ExactPairing (X Y : C) where /-- Coevaluation of an exact pairing. Do not use directly. Use `ExactPairing.coevaluation` instead. -/ coevaluation' : 𝟙_ C ⟶ X ⊗ Y /-- Evaluation of an exact pairing. Do not use directly. Use `ExactPairing.evaluation` instead. -/ evaluation' : Y ⊗ X ⟶ 𝟙_ C coevaluation_evaluation' : Y ◁ coevaluation' ≫ (α_ _ _ _).inv ≫ evaluation' ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv := by aesop_cat evaluation_coevaluation' : coevaluation' ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ evaluation' = (λ_ X).hom ≫ (ρ_ X).inv := by aesop_cat namespace ExactPairing -- Porting note: as there is no mechanism equivalent to `[]` in Lean 3 to make -- arguments for class fields explicit, -- we now repeat all the fields without primes. -- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Making.20variable.20in.20class.20field.20explicit variable (X Y : C) variable [ExactPairing X Y] /-- Coevaluation of an exact pairing. -/ def coevaluation : 𝟙_ C ⟶ X ⊗ Y := @coevaluation' _ _ _ X Y _ /-- Evaluation of an exact pairing. -/ def evaluation : Y ⊗ X ⟶ 𝟙_ C := @evaluation' _ _ _ X Y _ @[inherit_doc] notation "η_" => ExactPairing.coevaluation @[inherit_doc] notation "ε_" => ExactPairing.evaluation lemma coevaluation_evaluation : Y ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ ε_ X _ ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv := coevaluation_evaluation' lemma evaluation_coevaluation : η_ _ _ ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ ε_ _ Y = (λ_ X).hom ≫ (ρ_ X).inv := evaluation_coevaluation' lemma coevaluation_evaluation'' : Y ◁ η_ X Y ⊗≫ ε_ X Y ▷ Y = ⊗𝟙.hom := by convert coevaluation_evaluation X Y <;> simp [monoidalComp] lemma evaluation_coevaluation'' : η_ X Y ▷ X ⊗≫ X ◁ ε_ X Y = ⊗𝟙.hom := by convert evaluation_coevaluation X Y <;> simp [monoidalComp] end ExactPairing attribute [reassoc (attr := simp)] ExactPairing.coevaluation_evaluation attribute [reassoc (attr := simp)] ExactPairing.evaluation_coevaluation instance exactPairingUnit : ExactPairing (𝟙_ C) (𝟙_ C) where coevaluation' := (ρ_ _).inv evaluation' := (ρ_ _).hom coevaluation_evaluation' := by monoidal_coherence evaluation_coevaluation' := by monoidal_coherence /-- A class of objects which have a right dual. -/ class HasRightDual (X : C) where /-- The right dual of the object `X`. -/ rightDual : C [exact : ExactPairing X rightDual] /-- A class of objects which have a left dual. -/ class HasLeftDual (Y : C) where /-- The left dual of the object `X`. -/ leftDual : C [exact : ExactPairing leftDual Y] attribute [instance] HasRightDual.exact attribute [instance] HasLeftDual.exact open ExactPairing HasRightDual HasLeftDual MonoidalCategory #adaptation_note /-- https://github.com/leanprover/lean4/pull/4596 The overlapping notation for `leftDual` and `leftAdjointMate` become more problematic in after https://github.com/leanprover/lean4/pull/4596, and we sometimes have to disambiguate with e.g. `(ᘁX : C)` where previously just `ᘁX` was enough. -/ @[inherit_doc] prefix:1024 "ᘁ" => leftDual @[inherit_doc] postfix:1024 "ᘁ" => rightDual instance hasRightDualUnit : HasRightDual (𝟙_ C) where rightDual := 𝟙_ C instance hasLeftDualUnit : HasLeftDual (𝟙_ C) where leftDual := 𝟙_ C instance hasRightDualLeftDual {X : C} [HasLeftDual X] : HasRightDual ᘁX where rightDual := X instance hasLeftDualRightDual {X : C} [HasRightDual X] : HasLeftDual Xᘁ where leftDual := X @[simp] theorem leftDual_rightDual {X : C} [HasRightDual X] : ᘁXᘁ = X := rfl @[simp] theorem rightDual_leftDual {X : C} [HasLeftDual X] : (ᘁX)ᘁ = X := rfl /-- The right adjoint mate `fᘁ : Xᘁ ⟶ Yᘁ` of a morphism `f : X ⟶ Y`. -/ def rightAdjointMate {X Y : C} [HasRightDual X] [HasRightDual Y] (f : X ⟶ Y) : Yᘁ ⟶ Xᘁ := (ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ _ ◁ f ▷ _ ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom /-- The left adjoint mate `ᘁf : ᘁY ⟶ ᘁX` of a morphism `f : X ⟶ Y`. -/ def leftAdjointMate {X Y : C} [HasLeftDual X] [HasLeftDual Y] (f : X ⟶ Y) : ᘁY ⟶ ᘁX := (λ_ _).inv ≫ η_ (ᘁX) X ▷ _ ≫ (_ ◁ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom @[inherit_doc] notation f "ᘁ" => rightAdjointMate f @[inherit_doc] notation "ᘁ" f => leftAdjointMate f @[simp] theorem rightAdjointMate_id {X : C} [HasRightDual X] : (𝟙 X)ᘁ = 𝟙 (Xᘁ) := by simp [rightAdjointMate] @[simp] theorem leftAdjointMate_id {X : C} [HasLeftDual X] : (ᘁ(𝟙 X)) = 𝟙 (ᘁX) := by simp [leftAdjointMate] theorem rightAdjointMate_comp {X Y Z : C} [HasRightDual X] [HasRightDual Y] {f : X ⟶ Y} {g : Xᘁ ⟶ Z} : fᘁ ≫ g = (ρ_ (Yᘁ)).inv ≫ _ ◁ η_ X (Xᘁ) ≫ _ ◁ (f ⊗ g) ≫ (α_ (Yᘁ) Y Z).inv ≫ ε_ Y (Yᘁ) ▷ _ ≫ (λ_ Z).hom := calc _ = 𝟙 _ ⊗≫ (Yᘁ : C) ◁ η_ X Xᘁ ≫ Yᘁ ◁ f ▷ Xᘁ ⊗≫ (ε_ Y Yᘁ ▷ Xᘁ ≫ 𝟙_ C ◁ g) ⊗≫ 𝟙 _ := by dsimp only [rightAdjointMate]; monoidal _ = _ := by rw [← whisker_exchange, tensorHom_def]; monoidal theorem leftAdjointMate_comp {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] {f : X ⟶ Y} {g : (ᘁX) ⟶ Z} : (ᘁf) ≫ g = (λ_ _).inv ≫ η_ (ᘁX : C) X ▷ _ ≫ (g ⊗ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom := calc _ = 𝟙 _ ⊗≫ η_ (ᘁX : C) X ▷ (ᘁY) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ⊗≫ ((ᘁX) ◁ ε_ (ᘁY) Y ≫ g ▷ 𝟙_ C) ⊗≫ 𝟙 _ := by dsimp only [leftAdjointMate]; monoidal _ = _ := by rw [whisker_exchange, tensorHom_def']; monoidal /-- The composition of right adjoint mates is the adjoint mate of the composition. -/ @[reassoc] theorem comp_rightAdjointMate {X Y Z : C} [HasRightDual X] [HasRightDual Y] [HasRightDual Z] {f : X ⟶ Y} {g : Y ⟶ Z} : (f ≫ g)ᘁ = gᘁ ≫ fᘁ := by rw [rightAdjointMate_comp] simp only [rightAdjointMate, comp_whiskerRight] simp only [← Category.assoc]; congr 3; simp only [Category.assoc] simp only [← MonoidalCategory.whiskerLeft_comp]; congr 2 symm calc _ = 𝟙 _ ⊗≫ (η_ Y Yᘁ ▷ 𝟙_ C ≫ (Y ⊗ Yᘁ) ◁ η_ X Xᘁ) ⊗≫ Y ◁ Yᘁ ◁ f ▷ Xᘁ ⊗≫ Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by rw [tensorHom_def']; monoidal _ = η_ X Xᘁ ⊗≫ (η_ Y Yᘁ ▷ (X ⊗ Xᘁ) ≫ (Y ⊗ Yᘁ) ◁ f ▷ Xᘁ) ⊗≫ Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by rw [← whisker_exchange]; monoidal _ = η_ X Xᘁ ⊗≫ f ▷ Xᘁ ⊗≫ (η_ Y Yᘁ ▷ Y ⊗≫ Y ◁ ε_ Y Yᘁ) ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by rw [← whisker_exchange]; monoidal _ = η_ X Xᘁ ≫ f ▷ Xᘁ ≫ g ▷ Xᘁ := by rw [evaluation_coevaluation'']; monoidal /-- The composition of left adjoint mates is the adjoint mate of the composition. -/ @[reassoc] theorem comp_leftAdjointMate {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] [HasLeftDual Z] {f : X ⟶ Y} {g : Y ⟶ Z} : (ᘁf ≫ g) = (ᘁg) ≫ ᘁf := by rw [leftAdjointMate_comp] simp only [leftAdjointMate, MonoidalCategory.whiskerLeft_comp] simp only [← Category.assoc]; congr 3; simp only [Category.assoc] simp only [← comp_whiskerRight]; congr 2 symm calc _ = 𝟙 _ ⊗≫ ((𝟙_ C) ◁ η_ (ᘁY) Y ≫ η_ (ᘁX) X ▷ ((ᘁY) ⊗ Y)) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ▷ Y ⊗≫ (ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by rw [tensorHom_def]; monoidal _ = η_ (ᘁX) X ⊗≫ (((ᘁX) ⊗ X) ◁ η_ (ᘁY) Y ≫ ((ᘁX) ◁ f) ▷ ((ᘁY) ⊗ Y)) ⊗≫ (ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by rw [whisker_exchange]; monoidal _ = η_ (ᘁX) X ⊗≫ ((ᘁX) ◁ f) ⊗≫ (ᘁX) ◁ (Y ◁ η_ (ᘁY) Y ⊗≫ ε_ (ᘁY) Y ▷ Y) ⊗≫ (ᘁX) ◁ g := by rw [whisker_exchange]; monoidal _ = η_ (ᘁX) X ≫ (ᘁX) ◁ f ≫ (ᘁX) ◁ g := by rw [coevaluation_evaluation'']; monoidal /-- Given an exact pairing on `Y Y'`, we get a bijection on hom-sets `(Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z)` by "pulling the string on the left" up or down. This gives the adjunction `tensorLeftAdjunction Y Y' : tensorLeft Y' ⊣ tensorLeft Y`. This adjunction is often referred to as "Frobenius reciprocity" in the fusion categories / planar algebras / subfactors literature. -/ def tensorLeftHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z) where toFun f := (λ_ _).inv ≫ η_ _ _ ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ f invFun f := Y' ◁ f ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom left_inv f := by calc _ = 𝟙 _ ⊗≫ Y' ◁ η_ Y Y' ▷ X ⊗≫ ((Y' ⊗ Y) ◁ f ≫ ε_ Y Y' ▷ Z) ⊗≫ 𝟙 _ := by monoidal _ = 𝟙 _ ⊗≫ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ▷ X ⊗≫ f := by rw [whisker_exchange]; monoidal _ = f := by rw [coevaluation_evaluation'']; monoidal right_inv f := by calc _ = 𝟙 _ ⊗≫ (η_ Y Y' ▷ X ≫ (Y ⊗ Y') ◁ f) ⊗≫ Y ◁ ε_ Y Y' ▷ Z ⊗≫ 𝟙 _ := by monoidal _ = f ⊗≫ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ▷ Z ⊗≫ 𝟙 _ := by rw [← whisker_exchange]; monoidal _ = f := by rw [evaluation_coevaluation'']; monoidal /-- Given an exact pairing on `Y Y'`, we get a bijection on hom-sets `(X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y')` by "pulling the string on the right" up or down. -/ def tensorRightHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y') where toFun f := (ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ f ▷ _ invFun f := f ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom left_inv f := by calc _ = 𝟙 _ ⊗≫ X ◁ η_ Y Y' ▷ Y ⊗≫ (f ▷ (Y' ⊗ Y) ≫ Z ◁ ε_ Y Y') ⊗≫ 𝟙 _ := by monoidal _ = 𝟙 _ ⊗≫ X ◁ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ⊗≫ f := by rw [← whisker_exchange]; monoidal _ = f := by rw [evaluation_coevaluation'']; monoidal right_inv f := by calc _ = 𝟙 _ ⊗≫ (X ◁ η_ Y Y' ≫ f ▷ (Y ⊗ Y')) ⊗≫ Z ◁ ε_ Y Y' ▷ Y' ⊗≫ 𝟙 _ := by monoidal _ = f ⊗≫ Z ◁ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ⊗≫ 𝟙 _ := by rw [whisker_exchange]; monoidal _ = f := by rw [coevaluation_evaluation'']; monoidal theorem tensorLeftHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : Y' ⊗ X ⟶ Z) (g : Z ⟶ Z') : (tensorLeftHomEquiv X Y Y' Z') (f ≫ g) = (tensorLeftHomEquiv X Y Y' Z) f ≫ Y ◁ g := by simp [tensorLeftHomEquiv] theorem tensorLeftHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X') (g : X' ⟶ Y ⊗ Z) : (tensorLeftHomEquiv X Y Y' Z).symm (f ≫ g) = _ ◁ f ≫ (tensorLeftHomEquiv X' Y Y' Z).symm g := by simp [tensorLeftHomEquiv] theorem tensorRightHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⊗ Y ⟶ Z) (g : Z ⟶ Z') : (tensorRightHomEquiv X Y Y' Z') (f ≫ g) = (tensorRightHomEquiv X Y Y' Z) f ≫ g ▷ Y' := by simp [tensorRightHomEquiv] theorem tensorRightHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X') (g : X' ⟶ Z ⊗ Y') : (tensorRightHomEquiv X Y Y' Z).symm (f ≫ g) = f ▷ Y ≫ (tensorRightHomEquiv X' Y Y' Z).symm g := by simp [tensorRightHomEquiv] /-- If `Y Y'` have an exact pairing, then the functor `tensorLeft Y'` is left adjoint to `tensorLeft Y`. -/ def tensorLeftAdjunction (Y Y' : C) [ExactPairing Y Y'] : tensorLeft Y' ⊣ tensorLeft Y := Adjunction.mkOfHomEquiv { homEquiv := fun X Z => tensorLeftHomEquiv X Y Y' Z homEquiv_naturality_left_symm := fun f g => tensorLeftHomEquiv_symm_naturality f g homEquiv_naturality_right := fun f g => tensorLeftHomEquiv_naturality f g } /-- If `Y Y'` have an exact pairing, then the functor `tensor_right Y` is left adjoint to `tensor_right Y'`. -/ def tensorRightAdjunction (Y Y' : C) [ExactPairing Y Y'] : tensorRight Y ⊣ tensorRight Y' := Adjunction.mkOfHomEquiv { homEquiv := fun X Z => tensorRightHomEquiv X Y Y' Z homEquiv_naturality_left_symm := fun f g => tensorRightHomEquiv_symm_naturality f g homEquiv_naturality_right := fun f g => tensorRightHomEquiv_naturality f g } /-- If `Y` has a left dual `ᘁY`, then it is a closed object, with the internal hom functor `Y ⟶[C] -` given by left tensoring by `ᘁY`. This has to be a definition rather than an instance to avoid diamonds, for example between `category_theory.monoidal_closed.functor_closed` and `CategoryTheory.Monoidal.functorHasLeftDual`. Moreover, in concrete applications there is often a more useful definition of the internal hom object than `ᘁY ⊗ X`, in which case the closed structure shouldn't come from `has_left_dual` (e.g. in the category `FinVect k`, it is more convenient to define the internal hom as `Y →ₗ[k] X` rather than `ᘁY ⊗ X` even though these are naturally isomorphic). -/ def closedOfHasLeftDual (Y : C) [HasLeftDual Y] : Closed Y where rightAdj := tensorLeft (ᘁY) adj := tensorLeftAdjunction (ᘁY) Y /-- `tensorLeftHomEquiv` commutes with tensoring on the right -/ theorem tensorLeftHomEquiv_tensor {X X' Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⟶ Y ⊗ Z) (g : X' ⟶ Z') : (tensorLeftHomEquiv (X ⊗ X') Y Y' (Z ⊗ Z')).symm ((f ⊗ g) ≫ (α_ _ _ _).hom) = (α_ _ _ _).inv ≫ ((tensorLeftHomEquiv X Y Y' Z).symm f ⊗ g) := by simp [tensorLeftHomEquiv, tensorHom_def'] /-- `tensorRightHomEquiv` commutes with tensoring on the left -/ theorem tensorRightHomEquiv_tensor {X X' Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⟶ Z ⊗ Y') (g : X' ⟶ Z') : (tensorRightHomEquiv (X' ⊗ X) Y Y' (Z' ⊗ Z)).symm ((g ⊗ f) ≫ (α_ _ _ _).inv) = (α_ _ _ _).hom ≫ (g ⊗ (tensorRightHomEquiv X Y Y' Z).symm f) := by simp [tensorRightHomEquiv, tensorHom_def] @[simp] theorem tensorLeftHomEquiv_symm_coevaluation_comp_whiskerLeft {Y Y' Z : C} [ExactPairing Y Y'] (f : Y' ⟶ Z) : (tensorLeftHomEquiv _ _ _ _).symm (η_ _ _ ≫ Y ◁ f) = (ρ_ _).hom ≫ f := by calc _ = Y' ◁ η_ Y Y' ⊗≫ ((Y' ⊗ Y) ◁ f ≫ ε_ Y Y' ▷ Z) ⊗≫ 𝟙 _ := by dsimp [tensorLeftHomEquiv]; monoidal _ = (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ⊗≫ f := by rw [whisker_exchange]; monoidal _ = _ := by rw [coevaluation_evaluation'']; monoidal @[simp] theorem tensorLeftHomEquiv_symm_coevaluation_comp_whiskerRight {X Y : C} [HasRightDual X] [HasRightDual Y] (f : X ⟶ Y) : (tensorLeftHomEquiv _ _ _ _).symm (η_ _ _ ≫ f ▷ (Xᘁ)) = (ρ_ _).hom ≫ fᘁ := by dsimp [tensorLeftHomEquiv, rightAdjointMate] simp @[simp] theorem tensorRightHomEquiv_symm_coevaluation_comp_whiskerLeft {X Y : C} [HasLeftDual X] [HasLeftDual Y] (f : X ⟶ Y) : (tensorRightHomEquiv _ (ᘁY) _ _).symm (η_ (ᘁX : C) X ≫ (ᘁX : C) ◁ f) = (λ_ _).hom ≫ ᘁf := by dsimp [tensorRightHomEquiv, leftAdjointMate] simp @[simp] theorem tensorRightHomEquiv_symm_coevaluation_comp_whiskerRight {Y Y' Z : C} [ExactPairing Y Y'] (f : Y ⟶ Z) : (tensorRightHomEquiv _ Y _ _).symm (η_ Y Y' ≫ f ▷ Y') = (λ_ _).hom ≫ f := calc _ = η_ Y Y' ▷ Y ⊗≫ (f ▷ (Y' ⊗ Y) ≫ Z ◁ ε_ Y Y') ⊗≫ 𝟙 _ := by dsimp [tensorRightHomEquiv]; monoidal _ = (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ⊗≫ f := by rw [← whisker_exchange]; monoidal _ = _ := by rw [evaluation_coevaluation'']; monoidal @[simp] theorem tensorLeftHomEquiv_whiskerLeft_comp_evaluation {Y Z : C} [HasLeftDual Z] (f : Y ⟶ ᘁZ) : (tensorLeftHomEquiv _ _ _ _) (Z ◁ f ≫ ε_ _ _) = f ≫ (ρ_ _).inv :=
calc _ = 𝟙 _ ⊗≫ (η_ (ᘁZ : C) Z ▷ Y ≫ ((ᘁZ) ⊗ Z) ◁ f) ⊗≫ (ᘁZ) ◁ ε_ (ᘁZ) Z := by dsimp [tensorLeftHomEquiv]; monoidal _ = f ⊗≫ (η_ (ᘁZ) Z ▷ (ᘁZ) ⊗≫ (ᘁZ) ◁ ε_ (ᘁZ) Z) := by rw [← whisker_exchange]; monoidal
Mathlib/CategoryTheory/Monoidal/Rigid/Basic.lean
422
426
/- Copyright (c) 2019 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn, Yury Kudryashov, Sébastien Gouëzel, Chris Hughes -/ import Mathlib.Data.Fin.Rev import Mathlib.Data.Nat.Find /-! # Operation on tuples We interpret maps `∀ i : Fin n, α i` as `n`-tuples of elements of possibly varying type `α i`, `(α 0, …, α (n-1))`. A particular case is `Fin n → α` of elements with all the same type. In this case when `α i` is a constant map, then tuples are isomorphic (but not definitionally equal) to `Vector`s. ## Main declarations There are three (main) ways to consider `Fin n` as a subtype of `Fin (n + 1)`, hence three (main) ways to move between tuples of length `n` and of length `n + 1` by adding/removing an entry. ### Adding at the start * `Fin.succ`: Send `i : Fin n` to `i + 1 : Fin (n + 1)`. This is defined in Core. * `Fin.cases`: Induction/recursion principle for `Fin`: To prove a property/define a function for all `Fin (n + 1)`, it is enough to prove/define it for `0` and for `i.succ` for all `i : Fin n`. This is defined in Core. * `Fin.cons`: Turn a tuple `f : Fin n → α` and an entry `a : α` into a tuple `Fin.cons a f : Fin (n + 1) → α` by adding `a` at the start. In general, tuples can be dependent functions, in which case `f : ∀ i : Fin n, α i.succ` and `a : α 0`. This is a special case of `Fin.cases`. * `Fin.tail`: Turn a tuple `f : Fin (n + 1) → α` into a tuple `Fin.tail f : Fin n → α` by forgetting the start. In general, tuples can be dependent functions, in which case `Fin.tail f : ∀ i : Fin n, α i.succ`. ### Adding at the end * `Fin.castSucc`: Send `i : Fin n` to `i : Fin (n + 1)`. This is defined in Core. * `Fin.lastCases`: Induction/recursion principle for `Fin`: To prove a property/define a function for all `Fin (n + 1)`, it is enough to prove/define it for `last n` and for `i.castSucc` for all `i : Fin n`. This is defined in Core. * `Fin.snoc`: Turn a tuple `f : Fin n → α` and an entry `a : α` into a tuple `Fin.snoc f a : Fin (n + 1) → α` by adding `a` at the end. In general, tuples can be dependent functions, in which case `f : ∀ i : Fin n, α i.castSucc` and `a : α (last n)`. This is a special case of `Fin.lastCases`. * `Fin.init`: Turn a tuple `f : Fin (n + 1) → α` into a tuple `Fin.init f : Fin n → α` by forgetting the start. In general, tuples can be dependent functions, in which case `Fin.init f : ∀ i : Fin n, α i.castSucc`. ### Adding in the middle For a **pivot** `p : Fin (n + 1)`, * `Fin.succAbove`: Send `i : Fin n` to * `i : Fin (n + 1)` if `i < p`, * `i + 1 : Fin (n + 1)` if `p ≤ i`. * `Fin.succAboveCases`: Induction/recursion principle for `Fin`: To prove a property/define a function for all `Fin (n + 1)`, it is enough to prove/define it for `p` and for `p.succAbove i` for all `i : Fin n`. * `Fin.insertNth`: Turn a tuple `f : Fin n → α` and an entry `a : α` into a tuple `Fin.insertNth f a : Fin (n + 1) → α` by adding `a` in position `p`. In general, tuples can be dependent functions, in which case `f : ∀ i : Fin n, α (p.succAbove i)` and `a : α p`. This is a special case of `Fin.succAboveCases`. * `Fin.removeNth`: Turn a tuple `f : Fin (n + 1) → α` into a tuple `Fin.removeNth p f : Fin n → α` by forgetting the `p`-th value. In general, tuples can be dependent functions, in which case `Fin.removeNth f : ∀ i : Fin n, α (succAbove p i)`. `p = 0` means we add at the start. `p = last n` means we add at the end. ### Miscellaneous * `Fin.find p` : returns the first index `n` where `p n` is satisfied, and `none` if it is never satisfied. * `Fin.append a b` : append two tuples. * `Fin.repeat n a` : repeat a tuple `n` times. -/ assert_not_exists Monoid universe u v namespace Fin variable {m n : ℕ} open Function section Tuple /-- There is exactly one tuple of size zero. -/ example (α : Fin 0 → Sort u) : Unique (∀ i : Fin 0, α i) := by infer_instance theorem tuple0_le {α : Fin 0 → Type*} [∀ i, Preorder (α i)] (f g : ∀ i, α i) : f ≤ g := finZeroElim variable {α : Fin (n + 1) → Sort u} (x : α 0) (q : ∀ i, α i) (p : ∀ i : Fin n, α i.succ) (i : Fin n) (y : α i.succ) (z : α 0) /-- The tail of an `n+1` tuple, i.e., its last `n` entries. -/ def tail (q : ∀ i, α i) : ∀ i : Fin n, α i.succ := fun i ↦ q i.succ theorem tail_def {n : ℕ} {α : Fin (n + 1) → Sort*} {q : ∀ i, α i} : (tail fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q k.succ := rfl /-- Adding an element at the beginning of an `n`-tuple, to get an `n+1`-tuple. -/ def cons (x : α 0) (p : ∀ i : Fin n, α i.succ) : ∀ i, α i := fun j ↦ Fin.cases x p j @[simp] theorem tail_cons : tail (cons x p) = p := by simp +unfoldPartialApp [tail, cons] @[simp] theorem cons_succ : cons x p i.succ = p i := by simp [cons] @[simp] theorem cons_zero : cons x p 0 = x := by simp [cons] @[simp] theorem cons_one {α : Fin (n + 2) → Sort*} (x : α 0) (p : ∀ i : Fin n.succ, α i.succ) : cons x p 1 = p 0 := by rw [← cons_succ x p]; rfl /-- Updating a tuple and adding an element at the beginning commute. -/ @[simp] theorem cons_update : cons x (update p i y) = update (cons x p) i.succ y := by ext j by_cases h : j = 0 · rw [h] simp [Ne.symm (succ_ne_zero i)] · let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this, cons_succ] by_cases h' : j' = i · rw [h'] simp · have : j'.succ ≠ i.succ := by rwa [Ne, succ_inj] rw [update_of_ne h', update_of_ne this, cons_succ] /-- As a binary function, `Fin.cons` is injective. -/ theorem cons_injective2 : Function.Injective2 (@cons n α) := fun x₀ y₀ x y h ↦ ⟨congr_fun h 0, funext fun i ↦ by simpa using congr_fun h (Fin.succ i)⟩ @[simp] theorem cons_inj {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} : cons x₀ x = cons y₀ y ↔ x₀ = y₀ ∧ x = y := cons_injective2.eq_iff theorem cons_left_injective (x : ∀ i : Fin n, α i.succ) : Function.Injective fun x₀ ↦ cons x₀ x := cons_injective2.left _ theorem cons_right_injective (x₀ : α 0) : Function.Injective (cons x₀) := cons_injective2.right _ /-- Adding an element at the beginning of a tuple and then updating it amounts to adding it directly. -/ theorem update_cons_zero : update (cons x p) 0 z = cons z p := by ext j by_cases h : j = 0 · rw [h] simp · simp only [h, update_of_ne, Ne, not_false_iff] let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this, cons_succ, cons_succ] /-- Concatenating the first element of a tuple with its tail gives back the original tuple -/ @[simp] theorem cons_self_tail : cons (q 0) (tail q) = q := by ext j by_cases h : j = 0 · rw [h] simp · let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this] unfold tail rw [cons_succ] /-- Equivalence between tuples of length `n + 1` and pairs of an element and a tuple of length `n` given by separating out the first element of the tuple. This is `Fin.cons` as an `Equiv`. -/ @[simps] def consEquiv (α : Fin (n + 1) → Type*) : α 0 × (∀ i, α (succ i)) ≃ ∀ i, α i where toFun f := cons f.1 f.2 invFun f := (f 0, tail f) left_inv f := by simp right_inv f := by simp /-- Recurse on an `n+1`-tuple by splitting it into a single element and an `n`-tuple. -/ @[elab_as_elim] def consCases {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x)) (x : ∀ i : Fin n.succ, α i) : P x := _root_.cast (by rw [cons_self_tail]) <| h (x 0) (tail x) @[simp] theorem consCases_cons {P : (∀ i : Fin n.succ, α i) → Sort v} (h : ∀ x₀ x, P (Fin.cons x₀ x)) (x₀ : α 0) (x : ∀ i : Fin n, α i.succ) : @consCases _ _ _ h (cons x₀ x) = h x₀ x := by rw [consCases, cast_eq] congr /-- Recurse on a tuple by splitting into `Fin.elim0` and `Fin.cons`. -/ @[elab_as_elim] def consInduction {α : Sort*} {P : ∀ {n : ℕ}, (Fin n → α) → Sort v} (h0 : P Fin.elim0) (h : ∀ {n} (x₀) (x : Fin n → α), P x → P (Fin.cons x₀ x)) : ∀ {n : ℕ} (x : Fin n → α), P x | 0, x => by convert h0 | _ + 1, x => consCases (fun _ _ ↦ h _ _ <| consInduction h0 h _) x theorem cons_injective_of_injective {α} {x₀ : α} {x : Fin n → α} (hx₀ : x₀ ∉ Set.range x) (hx : Function.Injective x) : Function.Injective (cons x₀ x : Fin n.succ → α) := by refine Fin.cases ?_ ?_ · refine Fin.cases ?_ ?_ · intro rfl · intro j h rw [cons_zero, cons_succ] at h exact hx₀.elim ⟨_, h.symm⟩ · intro i refine Fin.cases ?_ ?_ · intro h rw [cons_zero, cons_succ] at h exact hx₀.elim ⟨_, h⟩ · intro j h rw [cons_succ, cons_succ] at h exact congr_arg _ (hx h) theorem cons_injective_iff {α} {x₀ : α} {x : Fin n → α} : Function.Injective (cons x₀ x : Fin n.succ → α) ↔ x₀ ∉ Set.range x ∧ Function.Injective x := by refine ⟨fun h ↦ ⟨?_, ?_⟩, fun h ↦ cons_injective_of_injective h.1 h.2⟩ · rintro ⟨i, hi⟩ replace h := @h i.succ 0 simp [hi] at h · simpa [Function.comp] using h.comp (Fin.succ_injective _) @[simp] theorem forall_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} : (∀ x, P x) ↔ P finZeroElim := ⟨fun h ↦ h _, fun h x ↦ Subsingleton.elim finZeroElim x ▸ h⟩ @[simp] theorem exists_fin_zero_pi {α : Fin 0 → Sort*} {P : (∀ i, α i) → Prop} : (∃ x, P x) ↔ P finZeroElim := ⟨fun ⟨x, h⟩ ↦ Subsingleton.elim x finZeroElim ▸ h, fun h ↦ ⟨_, h⟩⟩ theorem forall_fin_succ_pi {P : (∀ i, α i) → Prop} : (∀ x, P x) ↔ ∀ a v, P (Fin.cons a v) := ⟨fun h a v ↦ h (Fin.cons a v), consCases⟩ theorem exists_fin_succ_pi {P : (∀ i, α i) → Prop} : (∃ x, P x) ↔ ∃ a v, P (Fin.cons a v) := ⟨fun ⟨x, h⟩ ↦ ⟨x 0, tail x, (cons_self_tail x).symm ▸ h⟩, fun ⟨_, _, h⟩ ↦ ⟨_, h⟩⟩ /-- Updating the first element of a tuple does not change the tail. -/ @[simp] theorem tail_update_zero : tail (update q 0 z) = tail q := by ext j simp [tail] /-- Updating a nonzero element and taking the tail commute. -/ @[simp] theorem tail_update_succ : tail (update q i.succ y) = update (tail q) i y := by ext j by_cases h : j = i · rw [h] simp [tail] · simp [tail, (Fin.succ_injective n).ne h, h] theorem comp_cons {α : Sort*} {β : Sort*} (g : α → β) (y : α) (q : Fin n → α) : g ∘ cons y q = cons (g y) (g ∘ q) := by ext j by_cases h : j = 0 · rw [h] rfl · let j' := pred j h have : j'.succ = j := succ_pred j h rw [← this, cons_succ, comp_apply, comp_apply, cons_succ] theorem comp_tail {α : Sort*} {β : Sort*} (g : α → β) (q : Fin n.succ → α) : g ∘ tail q = tail (g ∘ q) := by ext j simp [tail] section Preorder variable {α : Fin (n + 1) → Type*} theorem le_cons [∀ i, Preorder (α i)] {x : α 0} {q : ∀ i, α i} {p : ∀ i : Fin n, α i.succ} : q ≤ cons x p ↔ q 0 ≤ x ∧ tail q ≤ p := forall_fin_succ.trans <| and_congr Iff.rfl <| forall_congr' fun j ↦ by simp [tail] theorem cons_le [∀ i, Preorder (α i)] {x : α 0} {q : ∀ i, α i} {p : ∀ i : Fin n, α i.succ} : cons x p ≤ q ↔ x ≤ q 0 ∧ p ≤ tail q := @le_cons _ (fun i ↦ (α i)ᵒᵈ) _ x q p theorem cons_le_cons [∀ i, Preorder (α i)] {x₀ y₀ : α 0} {x y : ∀ i : Fin n, α i.succ} : cons x₀ x ≤ cons y₀ y ↔ x₀ ≤ y₀ ∧ x ≤ y := forall_fin_succ.trans <| and_congr_right' <| by simp only [cons_succ, Pi.le_def] end Preorder theorem range_fin_succ {α} (f : Fin (n + 1) → α) : Set.range f = insert (f 0) (Set.range (Fin.tail f)) := Set.ext fun _ ↦ exists_fin_succ.trans <| eq_comm.or Iff.rfl @[simp] theorem range_cons {α} {n : ℕ} (x : α) (b : Fin n → α) : Set.range (Fin.cons x b : Fin n.succ → α) = insert x (Set.range b) := by rw [range_fin_succ, cons_zero, tail_cons] section Append variable {α : Sort*} /-- Append a tuple of length `m` to a tuple of length `n` to get a tuple of length `m + n`. This is a non-dependent version of `Fin.add_cases`. -/ def append (a : Fin m → α) (b : Fin n → α) : Fin (m + n) → α := @Fin.addCases _ _ (fun _ => α) a b @[simp] theorem append_left (u : Fin m → α) (v : Fin n → α) (i : Fin m) : append u v (Fin.castAdd n i) = u i := addCases_left _ @[simp] theorem append_right (u : Fin m → α) (v : Fin n → α) (i : Fin n) : append u v (natAdd m i) = v i := addCases_right _ theorem append_right_nil (u : Fin m → α) (v : Fin n → α) (hv : n = 0) : append u v = u ∘ Fin.cast (by rw [hv, Nat.add_zero]) := by refine funext (Fin.addCases (fun l => ?_) fun r => ?_) · rw [append_left, Function.comp_apply] refine congr_arg u (Fin.ext ?_) simp · exact (Fin.cast hv r).elim0 @[simp] theorem append_elim0 (u : Fin m → α) : append u Fin.elim0 = u ∘ Fin.cast (Nat.add_zero _) := append_right_nil _ _ rfl theorem append_left_nil (u : Fin m → α) (v : Fin n → α) (hu : m = 0) : append u v = v ∘ Fin.cast (by rw [hu, Nat.zero_add]) := by refine funext (Fin.addCases (fun l => ?_) fun r => ?_) · exact (Fin.cast hu l).elim0 · rw [append_right, Function.comp_apply] refine congr_arg v (Fin.ext ?_) simp [hu] @[simp] theorem elim0_append (v : Fin n → α) : append Fin.elim0 v = v ∘ Fin.cast (Nat.zero_add _) := append_left_nil _ _ rfl theorem append_assoc {p : ℕ} (a : Fin m → α) (b : Fin n → α) (c : Fin p → α) : append (append a b) c = append a (append b c) ∘ Fin.cast (Nat.add_assoc ..) := by ext i rw [Function.comp_apply] refine Fin.addCases (fun l => ?_) (fun r => ?_) i · rw [append_left] refine Fin.addCases (fun ll => ?_) (fun lr => ?_) l · rw [append_left] simp [castAdd_castAdd] · rw [append_right] simp [castAdd_natAdd] · rw [append_right] simp [← natAdd_natAdd] /-- Appending a one-tuple to the left is the same as `Fin.cons`. -/ theorem append_left_eq_cons {n : ℕ} (x₀ : Fin 1 → α) (x : Fin n → α) : Fin.append x₀ x = Fin.cons (x₀ 0) x ∘ Fin.cast (Nat.add_comm ..) := by ext i refine Fin.addCases ?_ ?_ i <;> clear i · intro i rw [Subsingleton.elim i 0, Fin.append_left, Function.comp_apply, eq_comm] exact Fin.cons_zero _ _ · intro i rw [Fin.append_right, Function.comp_apply, Fin.cast_natAdd, eq_comm, Fin.addNat_one] exact Fin.cons_succ _ _ _ /-- `Fin.cons` is the same as appending a one-tuple to the left. -/ theorem cons_eq_append (x : α) (xs : Fin n → α) : cons x xs = append (cons x Fin.elim0) xs ∘ Fin.cast (Nat.add_comm ..) := by funext i; simp [append_left_eq_cons] @[simp] lemma append_cast_left {n m} (xs : Fin n → α) (ys : Fin m → α) (n' : ℕ) (h : n' = n) : Fin.append (xs ∘ Fin.cast h) ys = Fin.append xs ys ∘ (Fin.cast <| by rw [h]) := by subst h; simp @[simp] lemma append_cast_right {n m} (xs : Fin n → α) (ys : Fin m → α) (m' : ℕ) (h : m' = m) : Fin.append xs (ys ∘ Fin.cast h) = Fin.append xs ys ∘ (Fin.cast <| by rw [h]) := by subst h; simp lemma append_rev {m n} (xs : Fin m → α) (ys : Fin n → α) (i : Fin (m + n)) : append xs ys (rev i) = append (ys ∘ rev) (xs ∘ rev) (i.cast (Nat.add_comm ..)) := by rcases rev_surjective i with ⟨i, rfl⟩ rw [rev_rev] induction i using Fin.addCases · simp [rev_castAdd] · simp [cast_rev, rev_addNat] lemma append_comp_rev {m n} (xs : Fin m → α) (ys : Fin n → α) : append xs ys ∘ rev = append (ys ∘ rev) (xs ∘ rev) ∘ Fin.cast (Nat.add_comm ..) := funext <| append_rev xs ys theorem append_castAdd_natAdd {f : Fin (m + n) → α} : append (fun i ↦ f (castAdd n i)) (fun i ↦ f (natAdd m i)) = f := by unfold append addCases simp end Append section Repeat variable {α : Sort*} /-- Repeat `a` `m` times. For example `Fin.repeat 2 ![0, 3, 7] = ![0, 3, 7, 0, 3, 7]`. -/ def «repeat» (m : ℕ) (a : Fin n → α) : Fin (m * n) → α | i => a i.modNat @[simp] theorem repeat_apply (a : Fin n → α) (i : Fin (m * n)) : Fin.repeat m a i = a i.modNat := rfl @[simp] theorem repeat_zero (a : Fin n → α) : Fin.repeat 0 a = Fin.elim0 ∘ Fin.cast (Nat.zero_mul _) := funext fun x => (x.cast (Nat.zero_mul _)).elim0 @[simp] theorem repeat_one (a : Fin n → α) : Fin.repeat 1 a = a ∘ Fin.cast (Nat.one_mul _) := by generalize_proofs h apply funext rw [(Fin.rightInverse_cast h.symm).surjective.forall] intro i simp [modNat, Nat.mod_eq_of_lt i.is_lt] theorem repeat_succ (a : Fin n → α) (m : ℕ) : Fin.repeat m.succ a = append a (Fin.repeat m a) ∘ Fin.cast ((Nat.succ_mul _ _).trans (Nat.add_comm ..)) := by generalize_proofs h apply funext rw [(Fin.rightInverse_cast h.symm).surjective.forall] refine Fin.addCases (fun l => ?_) fun r => ?_ · simp [modNat, Nat.mod_eq_of_lt l.is_lt] · simp [modNat] @[simp] theorem repeat_add (a : Fin n → α) (m₁ m₂ : ℕ) : Fin.repeat (m₁ + m₂) a = append (Fin.repeat m₁ a) (Fin.repeat m₂ a) ∘ Fin.cast (Nat.add_mul ..) := by generalize_proofs h apply funext rw [(Fin.rightInverse_cast h.symm).surjective.forall] refine Fin.addCases (fun l => ?_) fun r => ?_ · simp [modNat, Nat.mod_eq_of_lt l.is_lt] · simp [modNat, Nat.add_mod] theorem repeat_rev (a : Fin n → α) (k : Fin (m * n)) : Fin.repeat m a k.rev = Fin.repeat m (a ∘ Fin.rev) k := congr_arg a k.modNat_rev theorem repeat_comp_rev (a : Fin n → α) : Fin.repeat m a ∘ Fin.rev = Fin.repeat m (a ∘ Fin.rev) := funext <| repeat_rev a end Repeat end Tuple section TupleRight /-! In the previous section, we have discussed inserting or removing elements on the left of a tuple. In this section, we do the same on the right. A difference is that `Fin (n+1)` is constructed inductively from `Fin n` starting from the left, not from the right. This implies that Lean needs more help to realize that elements belong to the right types, i.e., we need to insert casts at several places. -/ variable {α : Fin (n + 1) → Sort*} (x : α (last n)) (q : ∀ i, α i) (p : ∀ i : Fin n, α i.castSucc) (i : Fin n) (y : α i.castSucc) (z : α (last n)) /-- The beginning of an `n+1` tuple, i.e., its first `n` entries -/ def init (q : ∀ i, α i) (i : Fin n) : α i.castSucc := q i.castSucc theorem init_def {q : ∀ i, α i} : (init fun k : Fin (n + 1) ↦ q k) = fun k : Fin n ↦ q k.castSucc := rfl /-- Adding an element at the end of an `n`-tuple, to get an `n+1`-tuple. The name `snoc` comes from `cons` (i.e., adding an element to the left of a tuple) read in reverse order. -/ def snoc (p : ∀ i : Fin n, α i.castSucc) (x : α (last n)) (i : Fin (n + 1)) : α i := if h : i.val < n then _root_.cast (by rw [Fin.castSucc_castLT i h]) (p (castLT i h)) else _root_.cast (by rw [eq_last_of_not_lt h]) x @[simp] theorem init_snoc : init (snoc p x) = p := by ext i simp only [init, snoc, coe_castSucc, is_lt, cast_eq, dite_true] convert cast_eq rfl (p i) @[simp] theorem snoc_castSucc : snoc p x i.castSucc = p i := by simp only [snoc, coe_castSucc, is_lt, cast_eq, dite_true] convert cast_eq rfl (p i) @[simp] theorem snoc_comp_castSucc {α : Sort*} {a : α} {f : Fin n → α} : (snoc f a : Fin (n + 1) → α) ∘ castSucc = f := funext fun i ↦ by rw [Function.comp_apply, snoc_castSucc] @[simp] theorem snoc_last : snoc p x (last n) = x := by simp [snoc] lemma snoc_zero {α : Sort*} (p : Fin 0 → α) (x : α) : Fin.snoc p x = fun _ ↦ x := by ext y have : Subsingleton (Fin (0 + 1)) := Fin.subsingleton_one simp only [Subsingleton.elim y (Fin.last 0), snoc_last] @[simp] theorem snoc_comp_nat_add {n m : ℕ} {α : Sort*} (f : Fin (m + n) → α) (a : α) : (snoc f a : Fin _ → α) ∘ (natAdd m : Fin (n + 1) → Fin (m + n + 1)) = snoc (f ∘ natAdd m) a := by ext i refine Fin.lastCases ?_ (fun i ↦ ?_) i · simp only [Function.comp_apply] rw [snoc_last, natAdd_last, snoc_last] · simp only [comp_apply, snoc_castSucc] rw [natAdd_castSucc, snoc_castSucc] @[simp] theorem snoc_cast_add {α : Fin (n + m + 1) → Sort*} (f : ∀ i : Fin (n + m), α i.castSucc) (a : α (last (n + m))) (i : Fin n) : (snoc f a) (castAdd (m + 1) i) = f (castAdd m i) := dif_pos _ @[simp] theorem snoc_comp_cast_add {n m : ℕ} {α : Sort*} (f : Fin (n + m) → α) (a : α) : (snoc f a : Fin _ → α) ∘ castAdd (m + 1) = f ∘ castAdd m := funext (snoc_cast_add _ _) /-- Updating a tuple and adding an element at the end commute. -/ @[simp] theorem snoc_update : snoc (update p i y) x = update (snoc p x) i.castSucc y := by ext j cases j using lastCases with | cast j => rcases eq_or_ne j i with rfl | hne <;> simp [*] | last => simp [Ne.symm] /-- Adding an element at the beginning of a tuple and then updating it amounts to adding it directly. -/ theorem update_snoc_last : update (snoc p x) (last n) z = snoc p z := by ext j cases j using lastCases <;> simp /-- As a binary function, `Fin.snoc` is injective. -/ theorem snoc_injective2 : Function.Injective2 (@snoc n α) := fun x y xₙ yₙ h ↦ ⟨funext fun i ↦ by simpa using congr_fun h (castSucc i), by simpa using congr_fun h (last n)⟩ @[simp] theorem snoc_inj {x y : ∀ i : Fin n, α i.castSucc} {xₙ yₙ : α (last n)} : snoc x xₙ = snoc y yₙ ↔ x = y ∧ xₙ = yₙ := snoc_injective2.eq_iff theorem snoc_right_injective (x : ∀ i : Fin n, α i.castSucc) : Function.Injective (snoc x) := snoc_injective2.right _ theorem snoc_left_injective (xₙ : α (last n)) : Function.Injective (snoc · xₙ) := snoc_injective2.left _ /-- Concatenating the first element of a tuple with its tail gives back the original tuple -/ @[simp] theorem snoc_init_self : snoc (init q) (q (last n)) = q := by ext j by_cases h : j.val < n · simp only [init, snoc, h, cast_eq, dite_true, castSucc_castLT] · rw [eq_last_of_not_lt h] simp /-- Updating the last element of a tuple does not change the beginning. -/ @[simp] theorem init_update_last : init (update q (last n) z) = init q := by ext j simp [init, Fin.ne_of_lt] /-- Updating an element and taking the beginning commute. -/ @[simp] theorem init_update_castSucc : init (update q i.castSucc y) = update (init q) i y := by ext j by_cases h : j = i · rw [h] simp [init] · simp [init, h, castSucc_inj] /-- `tail` and `init` commute. We state this lemma in a non-dependent setting, as otherwise it would involve a cast to convince Lean that the two types are equal, making it harder to use. -/ theorem tail_init_eq_init_tail {β : Sort*} (q : Fin (n + 2) → β) : tail (init q) = init (tail q) := by ext i simp [tail, init, castSucc_fin_succ] /-- `cons` and `snoc` commute. We state this lemma in a non-dependent setting, as otherwise it would involve a cast to convince Lean that the two types are equal, making it harder to use. -/ theorem cons_snoc_eq_snoc_cons {β : Sort*} (a : β) (q : Fin n → β) (b : β) : @cons n.succ (fun _ ↦ β) a (snoc q b) = snoc (cons a q) b := by ext i by_cases h : i = 0 · simp [h, snoc, castLT] set j := pred i h with ji have : i = j.succ := by rw [ji, succ_pred] rw [this, cons_succ] by_cases h' : j.val < n · set k := castLT j h' with jk have : j = castSucc k := by rw [jk, castSucc_castLT] rw [this, ← castSucc_fin_succ, snoc] simp [pred, snoc, cons] rw [eq_last_of_not_lt h', succ_last] simp theorem comp_snoc {α : Sort*} {β : Sort*} (g : α → β) (q : Fin n → α) (y : α) : g ∘ snoc q y = snoc (g ∘ q) (g y) := by ext j by_cases h : j.val < n · simp [h, snoc, castSucc_castLT] · rw [eq_last_of_not_lt h] simp /-- Appending a one-tuple to the right is the same as `Fin.snoc`. -/ theorem append_right_eq_snoc {α : Sort*} {n : ℕ} (x : Fin n → α) (x₀ : Fin 1 → α) : Fin.append x x₀ = Fin.snoc x (x₀ 0) := by ext i refine Fin.addCases ?_ ?_ i <;> clear i · intro i rw [Fin.append_left] exact (@snoc_castSucc _ (fun _ => α) _ _ i).symm · intro i rw [Subsingleton.elim i 0, Fin.append_right] exact (@snoc_last _ (fun _ => α) _ _).symm /-- `Fin.snoc` is the same as appending a one-tuple -/ theorem snoc_eq_append {α : Sort*} (xs : Fin n → α) (x : α) : snoc xs x = append xs (cons x Fin.elim0) := (append_right_eq_snoc xs (cons x Fin.elim0)).symm theorem append_left_snoc {n m} {α : Sort*} (xs : Fin n → α) (x : α) (ys : Fin m → α) : Fin.append (Fin.snoc xs x) ys = Fin.append xs (Fin.cons x ys) ∘ Fin.cast (Nat.succ_add_eq_add_succ ..) := by rw [snoc_eq_append, append_assoc, append_left_eq_cons, append_cast_right]; rfl theorem append_right_cons {n m} {α : Sort*} (xs : Fin n → α) (y : α) (ys : Fin m → α) : Fin.append xs (Fin.cons y ys) = Fin.append (Fin.snoc xs y) ys ∘ Fin.cast (Nat.succ_add_eq_add_succ ..).symm := by rw [append_left_snoc]; rfl theorem append_cons {α : Sort*} (a : α) (as : Fin n → α) (bs : Fin m → α) : Fin.append (cons a as) bs = cons a (Fin.append as bs) ∘ (Fin.cast <| Nat.add_right_comm n 1 m) := by funext i rcases i with ⟨i, -⟩ simp only [append, addCases, cons, castLT, cast, comp_apply] rcases i with - | i · simp · split_ifs with h · have : i < n := Nat.lt_of_succ_lt_succ h simp [addCases, this] · have : ¬i < n := Nat.not_le.mpr <| Nat.lt_succ.mp <| Nat.not_le.mp h simp [addCases, this] theorem append_snoc {α : Sort*} (as : Fin n → α) (bs : Fin m → α) (b : α) : Fin.append as (snoc bs b) = snoc (Fin.append as bs) b := by funext i rcases i with ⟨i, isLt⟩ simp only [append, addCases, castLT, cast_mk, subNat_mk, natAdd_mk, cast, snoc.eq_1, cast_eq, eq_rec_constant, Nat.add_eq, Nat.add_zero, castLT_mk] split_ifs with lt_n lt_add sub_lt nlt_add lt_add <;> (try rfl) · have := Nat.lt_add_right m lt_n contradiction · obtain rfl := Nat.eq_of_le_of_lt_succ (Nat.not_lt.mp nlt_add) isLt simp [Nat.add_comm n m] at sub_lt · have := Nat.sub_lt_left_of_lt_add (Nat.not_lt.mp lt_n) lt_add contradiction theorem comp_init {α : Sort*} {β : Sort*} (g : α → β) (q : Fin n.succ → α) : g ∘ init q = init (g ∘ q) := by ext j simp [init] /-- Equivalence between tuples of length `n + 1` and pairs of an element and a tuple of length `n` given by separating out the last element of the tuple. This is `Fin.snoc` as an `Equiv`. -/ @[simps] def snocEquiv (α : Fin (n + 1) → Type*) : α (last n) × (∀ i, α (castSucc i)) ≃ ∀ i, α i where toFun f _ := Fin.snoc f.2 f.1 _ invFun f := ⟨f _, Fin.init f⟩ left_inv f := by simp right_inv f := by simp /-- Recurse on an `n+1`-tuple by splitting it its initial `n`-tuple and its last element. -/ @[elab_as_elim, inline] def snocCases {P : (∀ i : Fin n.succ, α i) → Sort*} (h : ∀ xs x, P (Fin.snoc xs x)) (x : ∀ i : Fin n.succ, α i) : P x := _root_.cast (by rw [Fin.snoc_init_self]) <| h (Fin.init x) (x <| Fin.last _) @[simp] lemma snocCases_snoc {P : (∀ i : Fin (n+1), α i) → Sort*} (h : ∀ x x₀, P (Fin.snoc x x₀)) (x : ∀ i : Fin n, (Fin.init α) i) (x₀ : α (Fin.last _)) : snocCases h (Fin.snoc x x₀) = h x x₀ := by rw [snocCases, cast_eq_iff_heq, Fin.init_snoc, Fin.snoc_last] /-- Recurse on a tuple by splitting into `Fin.elim0` and `Fin.snoc`. -/
@[elab_as_elim] def snocInduction {α : Sort*} {P : ∀ {n : ℕ}, (Fin n → α) → Sort*} (h0 : P Fin.elim0)
Mathlib/Data/Fin/Tuple/Basic.lean
716
719
/- 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.Additive import Mathlib.Algebra.Homology.ShortComplex.Exact import Mathlib.Algebra.Homology.ShortComplex.Preadditive import Mathlib.Tactic.Linarith /-! # The short complexes attached to homological complexes In this file, we define a functor `shortComplexFunctor C c i : HomologicalComplex C c ⥤ ShortComplex C`. By definition, the image of a homological complex `K` by this functor is the short complex `K.X (c.prev i) ⟶ K.X i ⟶ K.X (c.next i)`. The homology `K.homology i` of a homological complex `K` in degree `i` is defined as the homology of the short complex `(shortComplexFunctor C c i).obj K`, which can be abbreviated as `K.sc i`. -/ open CategoryTheory Category Limits namespace HomologicalComplex variable (C : Type*) [Category C] [HasZeroMorphisms C] {ι : Type*} (c : ComplexShape ι) /-- The functor `HomologicalComplex C c ⥤ ShortComplex C` which sends a homological complex `K` to the short complex `K.X i ⟶ K.X j ⟶ K.X k` for arbitrary indices `i`, `j` and `k`. -/ @[simps] def shortComplexFunctor' (i j k : ι) : HomologicalComplex C c ⥤ ShortComplex C where obj K := ShortComplex.mk (K.d i j) (K.d j k) (K.d_comp_d i j k) map f := { τ₁ := f.f i τ₂ := f.f j τ₃ := f.f k } /-- The functor `HomologicalComplex C c ⥤ ShortComplex C` which sends a homological complex `K` to the short complex `K.X (c.prev i) ⟶ K.X i ⟶ K.X (c.next i)`. -/ @[simps!] noncomputable def shortComplexFunctor (i : ι) := shortComplexFunctor' C c (c.prev i) i (c.next i) /-- The natural isomorphism `shortComplexFunctor C c j ≅ shortComplexFunctor' C c i j k` when `c.prev j = i` and `c.next j = k`. -/ @[simps!] noncomputable def natIsoSc' (i j k : ι) (hi : c.prev j = i) (hk : c.next j = k) : shortComplexFunctor C c j ≅ shortComplexFunctor' C c i j k := NatIso.ofComponents (fun K => ShortComplex.isoMk (K.XIsoOfEq hi) (Iso.refl _) (K.XIsoOfEq hk) (by simp) (by simp)) (by aesop_cat) variable {C c} variable (K L M : HomologicalComplex C c) (φ : K ⟶ L) (ψ : L ⟶ M) (i j k : ι) /-- The short complex `K.X i ⟶ K.X j ⟶ K.X k` for arbitrary indices `i`, `j` and `k`. -/ abbrev sc' := (shortComplexFunctor' C c i j k).obj K /-- The short complex `K.X (c.prev i) ⟶ K.X i ⟶ K.X (c.next i)`. -/ noncomputable abbrev sc := (shortComplexFunctor C c i).obj K /-- The canonical isomorphism `K.sc j ≅ K.sc' i j k` when `c.prev j = i` and `c.next j = k`. -/ noncomputable abbrev isoSc' (hi : c.prev j = i) (hk : c.next j = k) : K.sc j ≅ K.sc' i j k := (natIsoSc' C c i j k hi hk).app K /-- A homological complex `K` has homology in degree `i` if the associated short complex `K.sc i` has. -/ abbrev HasHomology := (K.sc i).HasHomology section variable [K.HasHomology i] /-- The homology in degree `i` of a homological complex. -/ noncomputable def homology := (K.sc i).homology /-- The cycles in degree `i` of a homological complex. -/ noncomputable def cycles := (K.sc i).cycles /-- The inclusion of the cycles of a homological complex. -/ noncomputable def iCycles : K.cycles i ⟶ K.X i := (K.sc i).iCycles /-- The homology class map from cycles to the homology of a homological complex. -/ noncomputable def homologyπ : K.cycles i ⟶ K.homology i := (K.sc i).homologyπ variable {i} /-- The morphism to `K.cycles i` that is induced by a "cycle", i.e. a morphism to `K.X i` whose postcomposition with the differential is zero. -/ noncomputable def liftCycles {A : C} (k : A ⟶ K.X i) (j : ι) (hj : c.next i = j) (hk : k ≫ K.d i j = 0) : A ⟶ K.cycles i := (K.sc i).liftCycles k (by subst hj; exact hk) /-- The morphism to `K.cycles i` that is induced by a "cycle", i.e. a morphism to `K.X i` whose postcomposition with the differential is zero. -/ noncomputable abbrev liftCycles' {A : C} (k : A ⟶ K.X i) (j : ι) (hj : c.Rel i j) (hk : k ≫ K.d i j = 0) : A ⟶ K.cycles i := K.liftCycles k j (c.next_eq' hj) hk @[reassoc (attr := simp)] lemma liftCycles_i {A : C} (k : A ⟶ K.X i) (j : ι) (hj : c.next i = j) (hk : k ≫ K.d i j = 0) : K.liftCycles k j hj hk ≫ K.iCycles i = k := by dsimp [liftCycles, iCycles] simp variable (i) /-- The map `K.X i ⟶ K.cycles j` induced by the differential `K.d i j`. -/ noncomputable def toCycles [K.HasHomology j] : K.X i ⟶ K.cycles j := K.liftCycles (K.d i j) (c.next j) rfl (K.d_comp_d _ _ _) @[reassoc (attr := simp)] lemma iCycles_d : K.iCycles i ≫ K.d i j = 0 := by by_cases hij : c.Rel i j · obtain rfl := c.next_eq' hij exact (K.sc i).iCycles_g · rw [K.shape _ _ hij, comp_zero] /-- `K.cycles i` is the kernel of `K.d i j` when `c.next i = j`. -/ noncomputable def cyclesIsKernel (hj : c.next i = j) : IsLimit (KernelFork.ofι (K.iCycles i) (K.iCycles_d i j)) := by obtain rfl := hj exact (K.sc i).cyclesIsKernel end @[reassoc (attr := simp)] lemma toCycles_i [K.HasHomology j] : K.toCycles i j ≫ K.iCycles j = K.d i j := liftCycles_i _ _ _ _ _ section variable [K.HasHomology i] instance : Mono (K.iCycles i) := by dsimp only [iCycles] infer_instance instance : Epi (K.homologyπ i) := by dsimp only [homologyπ] infer_instance end @[reassoc (attr := simp)] lemma d_toCycles [K.HasHomology k] : K.d i j ≫ K.toCycles j k = 0 := by simp only [← cancel_mono (K.iCycles k), assoc, toCycles_i, d_comp_d, zero_comp] variable {i j} in lemma toCycles_eq_zero [K.HasHomology j] (hij : ¬ c.Rel i j) : K.toCycles i j = 0 := by rw [← cancel_mono (K.iCycles j), toCycles_i, zero_comp, K.shape _ _ hij] variable {i} section variable [K.HasHomology i] @[reassoc] lemma comp_liftCycles {A' A : C} (k : A ⟶ K.X i) (j : ι) (hj : c.next i = j) (hk : k ≫ K.d i j = 0) (α : A' ⟶ A) : α ≫ K.liftCycles k j hj hk = K.liftCycles (α ≫ k) j hj (by rw [assoc, hk, comp_zero]) := by simp only [← cancel_mono (K.iCycles i), assoc, liftCycles_i] @[reassoc] lemma liftCycles_homologyπ_eq_zero_of_boundary {A : C} (k : A ⟶ K.X i) (j : ι) (hj : c.next i = j) {i' : ι} (x : A ⟶ K.X i') (hx : k = x ≫ K.d i' i) : K.liftCycles k j hj (by rw [hx, assoc, K.d_comp_d, comp_zero]) ≫ K.homologyπ i = 0 := by by_cases h : c.Rel i' i · obtain rfl := c.prev_eq' h exact (K.sc i).liftCycles_homologyπ_eq_zero_of_boundary _ x hx · have : liftCycles K k j hj (by rw [hx, assoc, K.d_comp_d, comp_zero]) = 0 := by rw [K.shape _ _ h, comp_zero] at hx rw [← cancel_mono (K.iCycles i), zero_comp, liftCycles_i, hx] rw [this, zero_comp] end variable (i) @[reassoc (attr := simp)] lemma toCycles_comp_homologyπ [K.HasHomology j] : K.toCycles i j ≫ K.homologyπ j = 0 := K.liftCycles_homologyπ_eq_zero_of_boundary (K.d i j) (c.next j) rfl (𝟙 _) (by simp) /-- `K.homology j` is the cokernel of `K.toCycles i j : K.X i ⟶ K.cycles j` when `c.prev j = i`. -/ noncomputable def homologyIsCokernel (hi : c.prev j = i) [K.HasHomology j] : IsColimit (CokernelCofork.ofπ (K.homologyπ j) (K.toCycles_comp_homologyπ i j)) := by subst hi exact (K.sc j).homologyIsCokernel section variable [K.HasHomology i] /-- The opcycles in degree `i` of a homological complex. -/ noncomputable def opcycles := (K.sc i).opcycles /-- The projection to the opcycles of a homological complex. -/ noncomputable def pOpcycles : K.X i ⟶ K.opcycles i := (K.sc i).pOpcycles /-- The inclusion map of the homology of a homological complex into its opcycles. -/ noncomputable def homologyι : K.homology i ⟶ K.opcycles i := (K.sc i).homologyι variable {i} /-- The morphism from `K.opcycles i` that is induced by an "opcycle", i.e. a morphism from `K.X i` whose precomposition with the differential is zero. -/ noncomputable def descOpcycles {A : C} (k : K.X i ⟶ A) (j : ι) (hj : c.prev i = j) (hk : K.d j i ≫ k = 0) : K.opcycles i ⟶ A := (K.sc i).descOpcycles k (by subst hj; exact hk) /-- The morphism from `K.opcycles i` that is induced by an "opcycle", i.e. a morphism from `K.X i` whose precomposition with the differential is zero. -/ noncomputable abbrev descOpcycles' {A : C} (k : K.X i ⟶ A) (j : ι) (hj : c.Rel j i) (hk : K.d j i ≫ k = 0) : K.opcycles i ⟶ A := K.descOpcycles k j (c.prev_eq' hj) hk @[reassoc (attr := simp)] lemma p_descOpcycles {A : C} (k : K.X i ⟶ A) (j : ι) (hj : c.prev i = j) (hk : K.d j i ≫ k = 0) : K.pOpcycles i ≫ K.descOpcycles k j hj hk = k := by dsimp [descOpcycles, pOpcycles] simp variable (i) /-- The map `K.opcycles i ⟶ K.X j` induced by the differential `K.d i j`. -/ noncomputable def fromOpcycles : K.opcycles i ⟶ K.X j := K.descOpcycles (K.d i j) (c.prev i) rfl (K.d_comp_d _ _ _) @[reassoc (attr := simp)] lemma d_pOpcycles [K.HasHomology j] : K.d i j ≫ K.pOpcycles j = 0 := by by_cases hij : c.Rel i j · obtain rfl := c.prev_eq' hij exact (K.sc j).f_pOpcycles · rw [K.shape _ _ hij, zero_comp] /-- `K.opcycles j` is the cokernel of `K.d i j` when `c.prev j = i`. -/ noncomputable def opcyclesIsCokernel (hi : c.prev j = i) [K.HasHomology j] : IsColimit (CokernelCofork.ofπ (K.pOpcycles j) (K.d_pOpcycles i j)) := by obtain rfl := hi exact (K.sc j).opcyclesIsCokernel @[reassoc (attr := simp)] lemma p_fromOpcycles : K.pOpcycles i ≫ K.fromOpcycles i j = K.d i j := p_descOpcycles _ _ _ _ _ instance : Epi (K.pOpcycles i) := by dsimp only [pOpcycles] infer_instance instance : Mono (K.homologyι i) := by dsimp only [homologyι] infer_instance @[reassoc (attr := simp)] lemma fromOpcycles_d : K.fromOpcycles i j ≫ K.d j k = 0 := by simp only [← cancel_epi (K.pOpcycles i), p_fromOpcycles_assoc, d_comp_d, comp_zero] variable {i j} in lemma fromOpcycles_eq_zero (hij : ¬ c.Rel i j) : K.fromOpcycles i j = 0 := by rw [← cancel_epi (K.pOpcycles i), p_fromOpcycles, comp_zero, K.shape _ _ hij] variable {i} @[reassoc] lemma descOpcycles_comp {A A' : C} (k : K.X i ⟶ A) (j : ι) (hj : c.prev i = j) (hk : K.d j i ≫ k = 0) (α : A ⟶ A') : K.descOpcycles k j hj hk ≫ α = K.descOpcycles (k ≫ α) j hj (by rw [reassoc_of% hk, zero_comp]) := by simp only [← cancel_epi (K.pOpcycles i), p_descOpcycles_assoc, p_descOpcycles] @[reassoc] lemma homologyι_descOpcycles_eq_zero_of_boundary {A : C} (k : K.X i ⟶ A) (j : ι) (hj : c.prev i = j) {i' : ι} (x : K.X i' ⟶ A) (hx : k = K.d i i' ≫ x) : K.homologyι i ≫ K.descOpcycles k j hj (by rw [hx, K.d_comp_d_assoc, zero_comp]) = 0 := by by_cases h : c.Rel i i' · obtain rfl := c.next_eq' h exact (K.sc i).homologyι_descOpcycles_eq_zero_of_boundary _ x hx · have : K.descOpcycles k j hj (by rw [hx, K.d_comp_d_assoc, zero_comp]) = 0 := by rw [K.shape _ _ h, zero_comp] at hx rw [← cancel_epi (K.pOpcycles i), comp_zero, p_descOpcycles, hx] rw [this, comp_zero] variable (i) @[reassoc (attr := simp)] lemma homologyι_comp_fromOpcycles : K.homologyι i ≫ K.fromOpcycles i j = 0 := K.homologyι_descOpcycles_eq_zero_of_boundary (K.d i j) _ rfl (𝟙 _) (by simp) /-- `K.homology i` is the kernel of `K.fromOpcycles i j : K.opcycles i ⟶ K.X j` when `c.next i = j`. -/ noncomputable def homologyIsKernel (hi : c.next i = j) : IsLimit (KernelFork.ofι (K.homologyι i) (K.homologyι_comp_fromOpcycles i j)) := by subst hi exact (K.sc i).homologyIsKernel variable {K L M} variable [L.HasHomology i] [M.HasHomology i] /-- The map `K.homology i ⟶ L.homology i` induced by a morphism in `HomologicalComplex`. -/ noncomputable def homologyMap : K.homology i ⟶ L.homology i := ShortComplex.homologyMap ((shortComplexFunctor C c i).map φ) /-- The map `K.cycles i ⟶ L.cycles i` induced by a morphism in `HomologicalComplex`. -/ noncomputable def cyclesMap : K.cycles i ⟶ L.cycles i := ShortComplex.cyclesMap ((shortComplexFunctor C c i).map φ) /-- The map `K.opcycles i ⟶ L.opcycles i` induced by a morphism in `HomologicalComplex`. -/ noncomputable def opcyclesMap : K.opcycles i ⟶ L.opcycles i := ShortComplex.opcyclesMap ((shortComplexFunctor C c i).map φ) @[reassoc (attr := simp)] lemma cyclesMap_i : cyclesMap φ i ≫ L.iCycles i = K.iCycles i ≫ φ.f i := ShortComplex.cyclesMap_i _ @[reassoc (attr := simp)] lemma p_opcyclesMap : K.pOpcycles i ≫ opcyclesMap φ i = φ.f i ≫ L.pOpcycles i := ShortComplex.p_opcyclesMap _ instance [Mono (φ.f i)] : Mono (cyclesMap φ i) := mono_of_mono_fac (cyclesMap_i φ i) instance [Epi (φ.f i)] : Epi (opcyclesMap φ i) := epi_of_epi_fac (p_opcyclesMap φ i) variable (K) @[simp] lemma homologyMap_id : homologyMap (𝟙 K) i = 𝟙 _ := ShortComplex.homologyMap_id _ @[simp] lemma cyclesMap_id : cyclesMap (𝟙 K) i = 𝟙 _ := ShortComplex.cyclesMap_id _ @[simp] lemma opcyclesMap_id : opcyclesMap (𝟙 K) i = 𝟙 _ := ShortComplex.opcyclesMap_id _ variable {K} @[reassoc] lemma homologyMap_comp : homologyMap (φ ≫ ψ) i = homologyMap φ i ≫ homologyMap ψ i := by dsimp [homologyMap] rw [Functor.map_comp, ShortComplex.homologyMap_comp] @[reassoc] lemma cyclesMap_comp : cyclesMap (φ ≫ ψ) i = cyclesMap φ i ≫ cyclesMap ψ i := by dsimp [cyclesMap] rw [Functor.map_comp, ShortComplex.cyclesMap_comp] @[reassoc] lemma opcyclesMap_comp : opcyclesMap (φ ≫ ψ) i = opcyclesMap φ i ≫ opcyclesMap ψ i := by dsimp [opcyclesMap] rw [Functor.map_comp, ShortComplex.opcyclesMap_comp] variable (K L) @[simp] lemma homologyMap_zero : homologyMap (0 : K ⟶ L) i = 0 := ShortComplex.homologyMap_zero _ _ @[simp] lemma cyclesMap_zero : cyclesMap (0 : K ⟶ L) i = 0 := ShortComplex.cyclesMap_zero _ _ @[simp] lemma opcyclesMap_zero : opcyclesMap (0 : K ⟶ L) i = 0 := ShortComplex.opcyclesMap_zero _ _ variable {K L} @[reassoc (attr := simp)] lemma homologyπ_naturality : K.homologyπ i ≫ homologyMap φ i = cyclesMap φ i ≫ L.homologyπ i := ShortComplex.homologyπ_naturality _ @[reassoc (attr := simp)] lemma homologyι_naturality : homologyMap φ i ≫ L.homologyι i = K.homologyι i ≫ opcyclesMap φ i := ShortComplex.homologyι_naturality _ @[reassoc (attr := simp)] lemma homology_π_ι : K.homologyπ i ≫ K.homologyι i = K.iCycles i ≫ K.pOpcycles i := (K.sc i).homology_π_ι variable {i} @[reassoc (attr := simp)] lemma opcyclesMap_comp_descOpcycles {A : C} (k : L.X i ⟶ A) (j : ι) (hj : c.prev i = j) (hk : L.d j i ≫ k = 0) (φ : K ⟶ L) : opcyclesMap φ i ≫ L.descOpcycles k j hj hk = K.descOpcycles (φ.f i ≫ k) j hj (by rw [← φ.comm_assoc, hk, comp_zero]) := by simp only [← cancel_epi (K.pOpcycles i), p_opcyclesMap_assoc, p_descOpcycles] @[reassoc (attr := simp)] lemma liftCycles_comp_cyclesMap {A : C} (k : A ⟶ K.X i) (j : ι) (hj : c.next i = j) (hk : k ≫ K.d i j = 0) (φ : K ⟶ L) : K.liftCycles k j hj hk ≫ cyclesMap φ i = L.liftCycles (k ≫ φ.f i) j hj (by rw [assoc, φ.comm, reassoc_of% hk, zero_comp]) := by simp only [← cancel_mono (L.iCycles i), assoc, cyclesMap_i, liftCycles_i_assoc, liftCycles_i] section variable (C c i) attribute [local simp] homologyMap_comp cyclesMap_comp opcyclesMap_comp /-- The `i`th homology functor `HomologicalComplex C c ⥤ C`. -/ @[simps] noncomputable def homologyFunctor [CategoryWithHomology C] : HomologicalComplex C c ⥤ C where obj K := K.homology i map f := homologyMap f i /-- The homology functor to graded objects. -/ @[simps] noncomputable def gradedHomologyFunctor [CategoryWithHomology C] : HomologicalComplex C c ⥤ GradedObject ι C where obj K i := K.homology i map f i := homologyMap f i /-- The `i`th cycles functor `HomologicalComplex C c ⥤ C`. -/ @[simps] noncomputable def cyclesFunctor [CategoryWithHomology C] : HomologicalComplex C c ⥤ C where obj K := K.cycles i map f := cyclesMap f i /-- The `i`th opcycles functor `HomologicalComplex C c ⥤ C`. -/ @[simps] noncomputable def opcyclesFunctor [CategoryWithHomology C] : HomologicalComplex C c ⥤ C where obj K := K.opcycles i map f := opcyclesMap f i /-- The natural transformation `K.homologyπ i : K.cycles i ⟶ K.homology i` for all `K : HomologicalComplex C c`. -/ @[simps] noncomputable def natTransHomologyπ [CategoryWithHomology C] : cyclesFunctor C c i ⟶ homologyFunctor C c i where app K := K.homologyπ i /-- The natural transformation `K.homologyι i : K.homology i ⟶ K.opcycles i` for all `K : HomologicalComplex C c`. -/ @[simps] noncomputable def natTransHomologyι [CategoryWithHomology C] : homologyFunctor C c i ⟶ opcyclesFunctor C c i where app K := K.homologyι i /-- The natural isomorphism `K.homology i ≅ (K.sc i).homology` for all homological complexes `K`. -/ @[simps!] noncomputable def homologyFunctorIso [CategoryWithHomology C] : homologyFunctor C c i ≅ shortComplexFunctor C c i ⋙ ShortComplex.homologyFunctor C := Iso.refl _ /-- The natural isomorphism `K.homology j ≅ (K.sc' i j k).homology` for all homological complexes `K` when `c.prev j = i` and `c.next j = k`. -/ noncomputable def homologyFunctorIso' [CategoryWithHomology C] (hi : c.prev j = i) (hk : c.next j = k) : homologyFunctor C c j ≅ shortComplexFunctor' C c i j k ⋙ ShortComplex.homologyFunctor C := homologyFunctorIso C c j ≪≫ isoWhiskerRight (natIsoSc' C c i j k hi hk) _ instance [CategoryWithHomology C] : (homologyFunctor C c i).PreservesZeroMorphisms where instance [CategoryWithHomology C] : (opcyclesFunctor C c i).PreservesZeroMorphisms where instance [CategoryWithHomology C] : (cyclesFunctor C c i).PreservesZeroMorphisms where end end section variable (hj : c.next i = j) (h : K.d i j = 0) [K.HasHomology i] include hj h lemma isIso_iCycles : IsIso (K.iCycles i) := by subst hj exact ShortComplex.isIso_iCycles _ h /-- The canonical isomorphism `K.cycles i ≅ K.X i` when the differential from `i` is zero. -/ @[simps! hom] noncomputable def iCyclesIso : K.cycles i ≅ K.X i := have := K.isIso_iCycles i j hj h asIso (K.iCycles i) @[reassoc (attr := simp)] lemma iCyclesIso_hom_inv_id : K.iCycles i ≫ (K.iCyclesIso i j hj h).inv = 𝟙 _ := (K.iCyclesIso i j hj h).hom_inv_id @[reassoc (attr := simp)] lemma iCyclesIso_inv_hom_id : (K.iCyclesIso i j hj h).inv ≫ K.iCycles i = 𝟙 _ := (K.iCyclesIso i j hj h).inv_hom_id lemma isIso_homologyι : IsIso (K.homologyι i) := ShortComplex.isIso_homologyι _ (by aesop_cat) /-- The canonical isomorphism `K.homology i ≅ K.opcycles i` when the differential from `i` is zero. -/ @[simps! hom] noncomputable def isoHomologyι : K.homology i ≅ K.opcycles i := have := K.isIso_homologyι i j hj h asIso (K.homologyι i)
@[reassoc (attr := simp)] lemma isoHomologyι_hom_inv_id : K.homologyι i ≫ (K.isoHomologyι i j hj h).inv = 𝟙 _ :=
Mathlib/Algebra/Homology/ShortComplex/HomologicalComplex.lean
517
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/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Data.Finset.Fold import Mathlib.Data.Multiset.Bind import Mathlib.Order.SetNotation /-! # Unions of finite sets This file defines the union of a family `t : α → Finset β` of finsets bounded by a finset `s : Finset α`. ## Main declarations * `Finset.disjUnion`: Given a hypothesis `h` which states that finsets `s` and `t` are disjoint, `s.disjUnion t h` is the set such that `a ∈ disjUnion s t h` iff `a ∈ s` or `a ∈ t`; this does not require decidable equality on the type `α`. * `Finset.biUnion`: Finite unions of finsets; given an indexing function `f : α → Finset β` and an `s : Finset α`, `s.biUnion f` is the union of all finsets of the form `f a` for `a ∈ s`. ## TODO Remove `Finset.biUnion` in favour of `Finset.sup`. -/ assert_not_exists MonoidWithZero MulAction variable {α β γ : Type*} {s s₁ s₂ : Finset α} {t t₁ t₂ : α → Finset β} namespace Finset section DisjiUnion /-- `disjiUnion s f h` is the set such that `a ∈ disjiUnion s f` iff `a ∈ f i` for some `i ∈ s`. It is the same as `s.biUnion f`, but it does not require decidable equality on the type. The hypothesis ensures that the sets are disjoint. -/ def disjiUnion (s : Finset α) (t : α → Finset β) (hf : (s : Set α).PairwiseDisjoint t) : Finset β := ⟨s.val.bind (Finset.val ∘ t), Multiset.nodup_bind.2 ⟨fun a _ ↦ (t a).nodup, s.nodup.pairwise fun _ ha _ hb hab ↦ disjoint_val.2 <| hf ha hb hab⟩⟩ @[simp] lemma disjiUnion_val (s : Finset α) (t : α → Finset β) (h) : (s.disjiUnion t h).1 = s.1.bind fun a ↦ (t a).1 := rfl @[simp] lemma disjiUnion_empty (t : α → Finset β) : disjiUnion ∅ t (by simp) = ∅ := rfl @[simp] lemma mem_disjiUnion {b : β} {h} : b ∈ s.disjiUnion t h ↔ ∃ a ∈ s, b ∈ t a := by simp only [mem_def, disjiUnion_val, Multiset.mem_bind, exists_prop] @[simp, norm_cast] lemma coe_disjiUnion {h} : (s.disjiUnion t h : Set β) = ⋃ x ∈ (s : Set α), t x := by simp [Set.ext_iff, mem_disjiUnion, Set.mem_iUnion, mem_coe, imp_true_iff] @[simp] lemma disjiUnion_cons (a : α) (s : Finset α) (ha : a ∉ s) (f : α → Finset β) (H) : disjiUnion (cons a s ha) f H = (f a).disjUnion ((s.disjiUnion f) fun _ hb _ hc ↦ H (mem_cons_of_mem hb) (mem_cons_of_mem hc)) (disjoint_left.2 fun _ hb h ↦ let ⟨_, hc, h⟩ := mem_disjiUnion.mp h disjoint_left.mp (H (mem_cons_self a s) (mem_cons_of_mem hc) (ne_of_mem_of_not_mem hc ha).symm) hb h) := eq_of_veq <| Multiset.cons_bind _ _ _ @[simp] lemma singleton_disjiUnion (a : α) {h} : Finset.disjiUnion {a} t h = t a := eq_of_veq <| Multiset.singleton_bind _ _ lemma disjiUnion_disjiUnion (s : Finset α) (f : α → Finset β) (g : β → Finset γ) (h1 h2) : (s.disjiUnion f h1).disjiUnion g h2 = s.attach.disjiUnion (fun a ↦ ((f a).disjiUnion g) fun _ hb _ hc ↦ h2 (mem_disjiUnion.mpr ⟨_, a.prop, hb⟩) (mem_disjiUnion.mpr ⟨_, a.prop, hc⟩)) fun a _ b _ hab ↦ disjoint_left.mpr fun x hxa hxb ↦ by obtain ⟨xa, hfa, hga⟩ := mem_disjiUnion.mp hxa obtain ⟨xb, hfb, hgb⟩ := mem_disjiUnion.mp hxb refine disjoint_left.mp (h2 (mem_disjiUnion.mpr ⟨_, a.prop, hfa⟩) (mem_disjiUnion.mpr ⟨_, b.prop, hfb⟩) ?_) hga hgb rintro rfl exact disjoint_left.mp (h1 a.prop b.prop <| Subtype.coe_injective.ne hab) hfa hfb := eq_of_veq <| Multiset.bind_assoc.trans (Multiset.attach_bind_coe _ _).symm lemma sUnion_disjiUnion {f : α → Finset (Set β)} (I : Finset α) (hf : (I : Set α).PairwiseDisjoint f) : ⋃₀ (I.disjiUnion f hf : Set (Set β)) = ⋃ a ∈ I, ⋃₀ ↑(f a) := by ext simp only [coe_disjiUnion, Set.mem_sUnion, Set.mem_iUnion, mem_coe, exists_prop] tauto section DecidableEq variable [DecidableEq β] {s : Finset α} {t : Finset β} {f : α → β} private lemma pairwiseDisjoint_fibers : Set.PairwiseDisjoint ↑t fun a ↦ s.filter (f · = a) := fun x' hx y' hy hne ↦ by simp_rw [disjoint_left, mem_filter]; rintro i ⟨_, rfl⟩ ⟨_, rfl⟩; exact hne rfl @[simp] lemma disjiUnion_filter_eq (s : Finset α) (t : Finset β) (f : α → β) : t.disjiUnion (fun a ↦ s.filter (f · = a)) pairwiseDisjoint_fibers = s.filter fun c ↦ f c ∈ t := ext fun b => by simpa using and_comm lemma disjiUnion_filter_eq_of_maps_to (h : ∀ x ∈ s, f x ∈ t) : t.disjiUnion (fun a ↦ s.filter (f · = a)) pairwiseDisjoint_fibers = s := by simpa [filter_eq_self] end DecidableEq theorem map_disjiUnion {f : α ↪ β} {s : Finset α} {t : β → Finset γ} {h} : (s.map f).disjiUnion t h = s.disjiUnion (fun a => t (f a)) fun _ ha _ hb hab => h (mem_map_of_mem _ ha) (mem_map_of_mem _ hb) (f.injective.ne hab) := eq_of_veq <| Multiset.bind_map _ _ _ theorem disjiUnion_map {s : Finset α} {t : α → Finset β} {f : β ↪ γ} {h} : (s.disjiUnion t h).map f = s.disjiUnion (fun a => (t a).map f) (h.mono' fun _ _ ↦ (disjoint_map _).2) := eq_of_veq <| Multiset.map_bind _ _ _ variable {f : α → β} {op : β → β → β} [hc : Std.Commutative op] [ha : Std.Associative op] theorem fold_disjiUnion {ι : Type*} {s : Finset ι} {t : ι → Finset α} {b : ι → β} {b₀ : β} (h) : (s.disjiUnion t h).fold op (s.fold op b₀ b) f = s.fold op b₀ fun i => (t i).fold op (b i) f := (congr_arg _ <| Multiset.map_bind _ _ _).trans (Multiset.fold_bind _ _ _ _ _) end DisjiUnion section BUnion variable [DecidableEq β] /-- `Finset.biUnion s t` is the union of `t a` over `a ∈ s`. (This was formerly `bind` due to the monad structure on types with `DecidableEq`.) -/ protected def biUnion (s : Finset α) (t : α → Finset β) : Finset β := (s.1.bind fun a ↦ (t a).1).toFinset @[simp] lemma biUnion_val (s : Finset α) (t : α → Finset β) : (s.biUnion t).1 = (s.1.bind fun a ↦ (t a).1).dedup := rfl @[simp] lemma biUnion_empty : Finset.biUnion ∅ t = ∅ := rfl @[simp] lemma mem_biUnion {b : β} : b ∈ s.biUnion t ↔ ∃ a ∈ s, b ∈ t a := by simp only [mem_def, biUnion_val, Multiset.mem_dedup, Multiset.mem_bind, exists_prop] @[simp, norm_cast] lemma coe_biUnion : (s.biUnion t : Set β) = ⋃ x ∈ (s : Set α), t x := by simp [Set.ext_iff, mem_biUnion, Set.mem_iUnion, mem_coe, imp_true_iff] @[simp] lemma biUnion_insert [DecidableEq α] {a : α} : (insert a s).biUnion t = t a ∪ s.biUnion t := by aesop lemma biUnion_congr (hs : s₁ = s₂) (ht : ∀ a ∈ s₁, t₁ a = t₂ a) : s₁.biUnion t₁ = s₂.biUnion t₂ := by aesop @[simp] lemma disjiUnion_eq_biUnion (s : Finset α) (f : α → Finset β) (hf) : s.disjiUnion f hf = s.biUnion f := eq_of_veq (s.disjiUnion f hf).nodup.dedup.symm lemma biUnion_subset {s' : Finset β} : s.biUnion t ⊆ s' ↔ ∀ x ∈ s, t x ⊆ s' := by simp only [subset_iff, mem_biUnion] exact ⟨fun H a ha b hb ↦ H ⟨a, ha, hb⟩, fun H b ⟨a, ha, hb⟩ ↦ H a ha hb⟩ @[simp] lemma singleton_biUnion {a : α} : Finset.biUnion {a} t = t a := by classical rw [← insert_empty_eq, biUnion_insert, biUnion_empty, union_empty] lemma biUnion_inter (s : Finset α) (f : α → Finset β) (t : Finset β) : s.biUnion f ∩ t = s.biUnion fun x ↦ f x ∩ t := by ext x simp only [mem_biUnion, mem_inter] tauto lemma inter_biUnion (t : Finset β) (s : Finset α) (f : α → Finset β) : t ∩ s.biUnion f = s.biUnion fun x ↦ t ∩ f x := by rw [inter_comm, biUnion_inter] simp [inter_comm] lemma biUnion_biUnion [DecidableEq γ] (s : Finset α) (f : α → Finset β) (g : β → Finset γ) : (s.biUnion f).biUnion g = s.biUnion fun a ↦ (f a).biUnion g := by ext simp only [Finset.mem_biUnion, exists_prop] simp_rw [← exists_and_right, ← exists_and_left, and_assoc] rw [exists_comm] lemma bind_toFinset [DecidableEq α] (s : Multiset α) (t : α → Multiset β) : (s.bind t).toFinset = s.toFinset.biUnion fun a ↦ (t a).toFinset := ext fun x ↦ by simp only [Multiset.mem_toFinset, mem_biUnion, Multiset.mem_bind, exists_prop] lemma biUnion_mono (h : ∀ a ∈ s, t₁ a ⊆ t₂ a) : s.biUnion t₁ ⊆ s.biUnion t₂ := by have : ∀ b a, a ∈ s → b ∈ t₁ a → ∃ a : α, a ∈ s ∧ b ∈ t₂ a := fun b a ha hb ↦ ⟨a, ha, Finset.mem_of_subset (h a ha) hb⟩ simpa only [subset_iff, mem_biUnion, exists_imp, and_imp, exists_prop] lemma biUnion_subset_biUnion_of_subset_left (t : α → Finset β) (h : s₁ ⊆ s₂) : s₁.biUnion t ⊆ s₂.biUnion t := fun x ↦ by simp only [and_imp, mem_biUnion, exists_prop]; exact Exists.imp fun a ha ↦ ⟨h ha.1, ha.2⟩ lemma subset_biUnion_of_mem (u : α → Finset β) {x : α} (xs : x ∈ s) : u x ⊆ s.biUnion u := singleton_biUnion.superset.trans <| biUnion_subset_biUnion_of_subset_left u <| singleton_subset_iff.2 xs @[simp] lemma biUnion_subset_iff_forall_subset {α β : Type*} [DecidableEq β] {s : Finset α} {t : Finset β} {f : α → Finset β} : s.biUnion f ⊆ t ↔ ∀ x ∈ s, f x ⊆ t := ⟨fun h _ hx ↦ (subset_biUnion_of_mem f hx).trans h, fun h _ hx ↦ let ⟨_, ha₁, ha₂⟩ := mem_biUnion.mp hx h _ ha₁ ha₂⟩ @[simp] lemma biUnion_singleton_eq_self [DecidableEq α] : s.biUnion (singleton : α → Finset α) = s := ext fun x ↦ by simp only [mem_biUnion, mem_singleton, exists_prop, exists_eq_right'] lemma filter_biUnion (s : Finset α) (f : α → Finset β) (p : β → Prop) [DecidablePred p] : (s.biUnion f).filter p = s.biUnion fun a ↦ (f a).filter p := by ext b simp only [mem_biUnion, exists_prop, mem_filter] constructor · rintro ⟨⟨a, ha, hba⟩, hb⟩ exact ⟨a, ha, hba, hb⟩ · rintro ⟨a, ha, hba, hb⟩ exact ⟨⟨a, ha, hba⟩, hb⟩ lemma biUnion_filter_eq_of_maps_to [DecidableEq α] {s : Finset α} {t : Finset β} {f : α → β} (h : ∀ x ∈ s, f x ∈ t) : (t.biUnion fun a ↦ s.filter fun c ↦ f c = a) = s := by simpa only [disjiUnion_eq_biUnion] using disjiUnion_filter_eq_of_maps_to h lemma erase_biUnion (f : α → Finset β) (s : Finset α) (b : β) : (s.biUnion f).erase b = s.biUnion fun x ↦ (f x).erase b := by ext a simp only [mem_biUnion, not_exists, not_and, mem_erase, ne_eq] tauto @[simp] lemma biUnion_nonempty : (s.biUnion t).Nonempty ↔ ∃ x ∈ s, (t x).Nonempty := by simp only [Finset.Nonempty, mem_biUnion] rw [exists_swap] simp [exists_and_left] lemma Nonempty.biUnion (hs : s.Nonempty) (ht : ∀ x ∈ s, (t x).Nonempty) : (s.biUnion t).Nonempty := biUnion_nonempty.2 <| hs.imp fun x hx ↦ ⟨hx, ht x hx⟩ lemma disjoint_biUnion_left (s : Finset α) (f : α → Finset β) (t : Finset β) : Disjoint (s.biUnion f) t ↔ ∀ i ∈ s, Disjoint (f i) t := by classical refine s.induction ?_ ?_ · simp only [forall_mem_empty_iff, biUnion_empty, disjoint_empty_left] · intro i s his ih simp only [disjoint_union_left, biUnion_insert, his, forall_mem_insert, ih] lemma disjoint_biUnion_right (s : Finset β) (t : Finset α) (f : α → Finset β) : Disjoint s (t.biUnion f) ↔ ∀ i ∈ t, Disjoint s (f i) := by simpa only [_root_.disjoint_comm] using disjoint_biUnion_left t f s theorem image_biUnion [DecidableEq γ] {f : α → β} {s : Finset α} {t : β → Finset γ} : (s.image f).biUnion t = s.biUnion fun a => t (f a) := haveI := Classical.decEq α Finset.induction_on s rfl fun a s _ ih => by simp only [image_insert, biUnion_insert, ih] theorem biUnion_image [DecidableEq γ] {s : Finset α} {t : α → Finset β} {f : β → γ} : (s.biUnion t).image f = s.biUnion fun a => (t a).image f := haveI := Classical.decEq α Finset.induction_on s rfl fun a s _ ih => by simp only [biUnion_insert, image_union, ih]
theorem image_biUnion_filter_eq [DecidableEq α] (s : Finset β) (g : β → α) : ((s.image g).biUnion fun a => s.filter fun c => g c = a) = s :=
Mathlib/Data/Finset/Union.lean
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/- Copyright (c) 2020 Joseph Myers. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joseph Myers, Manuel Candales -/ import Mathlib.Analysis.Convex.Between import Mathlib.Analysis.Normed.Group.AddTorsor import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic import Mathlib.Analysis.Normed.Affine.Isometry /-! # Angles between points This file defines unoriented angles in Euclidean affine spaces. ## Main definitions * `EuclideanGeometry.angle`, with notation `∠`, is the undirected angle determined by three points. ## TODO Prove the triangle inequality for the angle. -/ noncomputable section open Real RealInnerProductSpace namespace EuclideanGeometry open InnerProductGeometry variable {V P : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P] [NormedAddTorsor V P] {p p₀ : P} /-- The undirected angle at `p₂` between the line segments to `p₁` and `p₃`. If either of those points equals `p₂`, this is π/2. Use `open scoped EuclideanGeometry` to access the `∠ p₁ p₂ p₃` notation. -/ nonrec def angle (p₁ p₂ p₃ : P) : ℝ := angle (p₁ -ᵥ p₂ : V) (p₃ -ᵥ p₂) @[inherit_doc] scoped notation "∠" => EuclideanGeometry.angle theorem continuousAt_angle {x : P × P × P} (hx12 : x.1 ≠ x.2.1) (hx32 : x.2.2 ≠ x.2.1) : ContinuousAt (fun y : P × P × P => ∠ y.1 y.2.1 y.2.2) x := by let f : P × P × P → V × V := fun y => (y.1 -ᵥ y.2.1, y.2.2 -ᵥ y.2.1) have hf1 : (f x).1 ≠ 0 := by simp [f, hx12] have hf2 : (f x).2 ≠ 0 := by simp [f, hx32] exact (InnerProductGeometry.continuousAt_angle hf1 hf2).comp (by fun_prop) @[simp] theorem _root_.AffineIsometry.angle_map {V₂ P₂ : Type*} [NormedAddCommGroup V₂] [InnerProductSpace ℝ V₂] [MetricSpace P₂] [NormedAddTorsor V₂ P₂] (f : P →ᵃⁱ[ℝ] P₂) (p₁ p₂ p₃ : P) : ∠ (f p₁) (f p₂) (f p₃) = ∠ p₁ p₂ p₃ := by simp_rw [angle, ← AffineIsometry.map_vsub, LinearIsometry.angle_map] @[simp, norm_cast] theorem _root_.AffineSubspace.angle_coe {s : AffineSubspace ℝ P} (p₁ p₂ p₃ : s) : haveI : Nonempty s := ⟨p₁⟩ ∠ (p₁ : P) (p₂ : P) (p₃ : P) = ∠ p₁ p₂ p₃ := haveI : Nonempty s := ⟨p₁⟩ s.subtypeₐᵢ.angle_map p₁ p₂ p₃ /-- Angles are translation invariant -/ @[simp] theorem angle_const_vadd (v : V) (p₁ p₂ p₃ : P) : ∠ (v +ᵥ p₁) (v +ᵥ p₂) (v +ᵥ p₃) = ∠ p₁ p₂ p₃ := (AffineIsometryEquiv.constVAdd ℝ P v).toAffineIsometry.angle_map _ _ _ /-- Angles are translation invariant -/ @[simp] theorem angle_vadd_const (v₁ v₂ v₃ : V) (p : P) : ∠ (v₁ +ᵥ p) (v₂ +ᵥ p) (v₃ +ᵥ p) = ∠ v₁ v₂ v₃ := (AffineIsometryEquiv.vaddConst ℝ p).toAffineIsometry.angle_map _ _ _ /-- Angles are translation invariant -/ @[simp] theorem angle_const_vsub (p p₁ p₂ p₃ : P) : ∠ (p -ᵥ p₁) (p -ᵥ p₂) (p -ᵥ p₃) = ∠ p₁ p₂ p₃ := (AffineIsometryEquiv.constVSub ℝ p).toAffineIsometry.angle_map _ _ _ /-- Angles are translation invariant -/ @[simp] theorem angle_vsub_const (p₁ p₂ p₃ p : P) : ∠ (p₁ -ᵥ p) (p₂ -ᵥ p) (p₃ -ᵥ p) = ∠ p₁ p₂ p₃ := (AffineIsometryEquiv.vaddConst ℝ p).symm.toAffineIsometry.angle_map _ _ _ /-- Angles in a vector space are translation invariant -/ @[simp] theorem angle_add_const (v₁ v₂ v₃ : V) (v : V) : ∠ (v₁ + v) (v₂ + v) (v₃ + v) = ∠ v₁ v₂ v₃ := angle_vadd_const _ _ _ _ /-- Angles in a vector space are translation invariant -/ @[simp] theorem angle_const_add (v : V) (v₁ v₂ v₃ : V) : ∠ (v + v₁) (v + v₂) (v + v₃) = ∠ v₁ v₂ v₃ := angle_const_vadd _ _ _ _ /-- Angles in a vector space are translation invariant -/ @[simp] theorem angle_sub_const (v₁ v₂ v₃ : V) (v : V) : ∠ (v₁ - v) (v₂ - v) (v₃ - v) = ∠ v₁ v₂ v₃ := by simpa only [vsub_eq_sub] using angle_vsub_const v₁ v₂ v₃ v /-- Angles in a vector space are invariant to inversion -/ @[simp] theorem angle_const_sub (v : V) (v₁ v₂ v₃ : V) : ∠ (v - v₁) (v - v₂) (v - v₃) = ∠ v₁ v₂ v₃ := by simpa only [vsub_eq_sub] using angle_const_vsub v v₁ v₂ v₃ /-- Angles in a vector space are invariant to inversion -/ @[simp] theorem angle_neg (v₁ v₂ v₃ : V) : ∠ (-v₁) (-v₂) (-v₃) = ∠ v₁ v₂ v₃ := by simpa only [zero_sub] using angle_const_sub 0 v₁ v₂ v₃ /-- The angle at a point does not depend on the order of the other two points. -/ nonrec theorem angle_comm (p₁ p₂ p₃ : P) : ∠ p₁ p₂ p₃ = ∠ p₃ p₂ p₁ := angle_comm _ _ /-- The angle at a point is nonnegative. -/ nonrec theorem angle_nonneg (p₁ p₂ p₃ : P) : 0 ≤ ∠ p₁ p₂ p₃ := angle_nonneg _ _ /-- The angle at a point is at most π. -/ nonrec theorem angle_le_pi (p₁ p₂ p₃ : P) : ∠ p₁ p₂ p₃ ≤ π := angle_le_pi _ _ /-- The angle ∠AAB at a point is always `π / 2`. -/ @[simp] lemma angle_self_left (p₀ p : P) : ∠ p₀ p₀ p = π / 2 := by unfold angle rw [vsub_self] exact angle_zero_left _ /-- The angle ∠ABB at a point is always `π / 2`. -/ @[simp] lemma angle_self_right (p₀ p : P) : ∠ p p₀ p₀ = π / 2 := by rw [angle_comm, angle_self_left] /-- The angle ∠ABA at a point is `0`, unless `A = B`. -/ theorem angle_self_of_ne (h : p ≠ p₀) : ∠ p p₀ p = 0 := angle_self <| vsub_ne_zero.2 h /-- If the angle ∠ABC at a point is π, the angle ∠BAC is 0. -/ theorem angle_eq_zero_of_angle_eq_pi_left {p₁ p₂ p₃ : P} (h : ∠ p₁ p₂ p₃ = π) : ∠ p₂ p₁ p₃ = 0 := by unfold angle at h rw [angle_eq_pi_iff] at h rcases h with ⟨hp₁p₂, ⟨r, ⟨hr, hpr⟩⟩⟩ unfold angle rw [angle_eq_zero_iff] rw [← neg_vsub_eq_vsub_rev, neg_ne_zero] at hp₁p₂ use hp₁p₂, -r + 1, add_pos (neg_pos_of_neg hr) zero_lt_one rw [add_smul, ← neg_vsub_eq_vsub_rev p₁ p₂, smul_neg] simp [← hpr] /-- If the angle ∠ABC at a point is π, the angle ∠BCA is 0. -/ theorem angle_eq_zero_of_angle_eq_pi_right {p₁ p₂ p₃ : P} (h : ∠ p₁ p₂ p₃ = π) : ∠ p₂ p₃ p₁ = 0 := by rw [angle_comm] at h exact angle_eq_zero_of_angle_eq_pi_left h /-- If ∠BCD = π, then ∠ABC = ∠ABD. -/ theorem angle_eq_angle_of_angle_eq_pi (p₁ : P) {p₂ p₃ p₄ : P} (h : ∠ p₂ p₃ p₄ = π) : ∠ p₁ p₂ p₃ = ∠ p₁ p₂ p₄ := by unfold angle at * rcases angle_eq_pi_iff.1 h with ⟨_, ⟨r, ⟨hr, hpr⟩⟩⟩ rw [eq_comm] convert angle_smul_right_of_pos (p₁ -ᵥ p₂) (p₃ -ᵥ p₂) (add_pos (neg_pos_of_neg hr) zero_lt_one) rw [add_smul, ← neg_vsub_eq_vsub_rev p₂ p₃, smul_neg, neg_smul, ← hpr] simp /-- If ∠BCD = π, then ∠ACB + ∠ACD = π. -/ nonrec theorem angle_add_angle_eq_pi_of_angle_eq_pi (p₁ : P) {p₂ p₃ p₄ : P} (h : ∠ p₂ p₃ p₄ = π) : ∠ p₁ p₃ p₂ + ∠ p₁ p₃ p₄ = π := by unfold angle at h rw [angle_comm p₁ p₃ p₂, angle_comm p₁ p₃ p₄] unfold angle exact angle_add_angle_eq_pi_of_angle_eq_pi _ h /-- **Vertical Angles Theorem**: angles opposite each other, formed by two intersecting straight lines, are equal. -/ theorem angle_eq_angle_of_angle_eq_pi_of_angle_eq_pi {p₁ p₂ p₃ p₄ p₅ : P} (hapc : ∠ p₁ p₅ p₃ = π) (hbpd : ∠ p₂ p₅ p₄ = π) : ∠ p₁ p₅ p₂ = ∠ p₃ p₅ p₄ := by linarith [angle_add_angle_eq_pi_of_angle_eq_pi p₁ hbpd, angle_comm p₄ p₅ p₁, angle_add_angle_eq_pi_of_angle_eq_pi p₄ hapc, angle_comm p₄ p₅ p₃] /-- If ∠ABC = π then dist A B ≠ 0. -/ theorem left_dist_ne_zero_of_angle_eq_pi {p₁ p₂ p₃ : P} (h : ∠ p₁ p₂ p₃ = π) : dist p₁ p₂ ≠ 0 := by by_contra heq rw [dist_eq_zero] at heq rw [heq, angle_self_left] at h exact Real.pi_ne_zero (by linarith) /-- If ∠ABC = π then dist C B ≠ 0. -/ theorem right_dist_ne_zero_of_angle_eq_pi {p₁ p₂ p₃ : P} (h : ∠ p₁ p₂ p₃ = π) : dist p₃ p₂ ≠ 0 := left_dist_ne_zero_of_angle_eq_pi <| (angle_comm _ _ _).trans h /-- If ∠ABC = π, then (dist A C) = (dist A B) + (dist B C). -/ theorem dist_eq_add_dist_of_angle_eq_pi {p₁ p₂ p₃ : P} (h : ∠ p₁ p₂ p₃ = π) : dist p₁ p₃ = dist p₁ p₂ + dist p₃ p₂ := by rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right] exact norm_sub_eq_add_norm_of_angle_eq_pi h /-- If A ≠ B and C ≠ B then ∠ABC = π if and only if (dist A C) = (dist A B) + (dist B C). -/ theorem dist_eq_add_dist_iff_angle_eq_pi {p₁ p₂ p₃ : P} (hp₁p₂ : p₁ ≠ p₂) (hp₃p₂ : p₃ ≠ p₂) : dist p₁ p₃ = dist p₁ p₂ + dist p₃ p₂ ↔ ∠ p₁ p₂ p₃ = π := by rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right] exact norm_sub_eq_add_norm_iff_angle_eq_pi (fun he => hp₁p₂ (vsub_eq_zero_iff_eq.1 he)) fun he => hp₃p₂ (vsub_eq_zero_iff_eq.1 he) /-- If ∠ABC = 0, then (dist A C) = abs ((dist A B) - (dist B C)). -/ theorem dist_eq_abs_sub_dist_of_angle_eq_zero {p₁ p₂ p₃ : P} (h : ∠ p₁ p₂ p₃ = 0) : dist p₁ p₃ = |dist p₁ p₂ - dist p₃ p₂| := by rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right] exact norm_sub_eq_abs_sub_norm_of_angle_eq_zero h /-- If A ≠ B and C ≠ B then ∠ABC = 0 if and only if (dist A C) = abs ((dist A B) - (dist B C)). -/ theorem dist_eq_abs_sub_dist_iff_angle_eq_zero {p₁ p₂ p₃ : P} (hp₁p₂ : p₁ ≠ p₂) (hp₃p₂ : p₃ ≠ p₂) : dist p₁ p₃ = |dist p₁ p₂ - dist p₃ p₂| ↔ ∠ p₁ p₂ p₃ = 0 := by rw [dist_eq_norm_vsub V, dist_eq_norm_vsub V, dist_eq_norm_vsub V, ← vsub_sub_vsub_cancel_right] exact norm_sub_eq_abs_sub_norm_iff_angle_eq_zero (fun he => hp₁p₂ (vsub_eq_zero_iff_eq.1 he)) fun he => hp₃p₂ (vsub_eq_zero_iff_eq.1 he) /-- If M is the midpoint of the segment AB, then ∠AMB = π. -/ theorem angle_midpoint_eq_pi (p₁ p₂ : P) (hp₁p₂ : p₁ ≠ p₂) : ∠ p₁ (midpoint ℝ p₁ p₂) p₂ = π := by simp only [angle, left_vsub_midpoint, invOf_eq_inv, right_vsub_midpoint, inv_pos, zero_lt_two, angle_smul_right_of_pos, angle_smul_left_of_pos] rw [← neg_vsub_eq_vsub_rev p₁ p₂] apply angle_self_neg_of_nonzero simpa only [ne_eq, vsub_eq_zero_iff_eq] /-- If M is the midpoint of the segment AB and C is the same distance from A as it is from B then ∠CMA = π / 2. -/ theorem angle_left_midpoint_eq_pi_div_two_of_dist_eq {p₁ p₂ p₃ : P} (h : dist p₃ p₁ = dist p₃ p₂) : ∠ p₃ (midpoint ℝ p₁ p₂) p₁ = π / 2 := by let m : P := midpoint ℝ p₁ p₂ have h1 : p₃ -ᵥ p₁ = p₃ -ᵥ m - (p₁ -ᵥ m) := (vsub_sub_vsub_cancel_right p₃ p₁ m).symm have h2 : p₃ -ᵥ p₂ = p₃ -ᵥ m + (p₁ -ᵥ m) := by rw [left_vsub_midpoint, ← midpoint_vsub_right, vsub_add_vsub_cancel] rw [dist_eq_norm_vsub V p₃ p₁, dist_eq_norm_vsub V p₃ p₂, h1, h2] at h exact (norm_add_eq_norm_sub_iff_angle_eq_pi_div_two (p₃ -ᵥ m) (p₁ -ᵥ m)).mp h.symm /-- If M is the midpoint of the segment AB and C is the same distance from A as it is from B then ∠CMB = π / 2. -/ theorem angle_right_midpoint_eq_pi_div_two_of_dist_eq {p₁ p₂ p₃ : P} (h : dist p₃ p₁ = dist p₃ p₂) : ∠ p₃ (midpoint ℝ p₁ p₂) p₂ = π / 2 := by rw [midpoint_comm p₁ p₂, angle_left_midpoint_eq_pi_div_two_of_dist_eq h.symm] /-- If the second of three points is strictly between the other two, the angle at that point is π. -/ theorem _root_.Sbtw.angle₁₂₃_eq_pi {p₁ p₂ p₃ : P} (h : Sbtw ℝ p₁ p₂ p₃) : ∠ p₁ p₂ p₃ = π := by rw [angle, angle_eq_pi_iff] rcases h with ⟨⟨r, ⟨hr0, hr1⟩, hp₂⟩, hp₂p₁, hp₂p₃⟩ refine ⟨vsub_ne_zero.2 hp₂p₁.symm, -(1 - r) / r, ?_⟩ have hr0' : r ≠ 0 := by rintro rfl rw [← hp₂] at hp₂p₁ simp at hp₂p₁ have hr1' : r ≠ 1 := by rintro rfl rw [← hp₂] at hp₂p₃
simp at hp₂p₃ replace hr0 := hr0.lt_of_ne hr0'.symm replace hr1 := hr1.lt_of_ne hr1' refine ⟨div_neg_of_neg_of_pos (Left.neg_neg_iff.2 (sub_pos.2 hr1)) hr0, ?_⟩ rw [← hp₂, AffineMap.lineMap_apply, vsub_vadd_eq_vsub_sub, vsub_vadd_eq_vsub_sub, vsub_self, zero_sub, smul_neg, smul_smul, div_mul_cancel₀ _ hr0', neg_smul, neg_neg, sub_eq_iff_eq_add, ←
Mathlib/Geometry/Euclidean/Angle/Unoriented/Affine.lean
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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, Yury Kudryashov -/ import Mathlib.Analysis.Calculus.FormalMultilinearSeries import Mathlib.Analysis.SpecificLimits.Normed import Mathlib.Logic.Equiv.Fin.Basic import Mathlib.Tactic.Bound.Attribute import Mathlib.Topology.Algebra.InfiniteSum.Module /-! # Analytic functions A function is analytic in one dimension around `0` if it can be written as a converging power series `Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not always possible in nonzero characteristic (in characteristic 2, the previous example has no symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition, and we only require the existence of a converging series. The general framework is important to say that the exponential map on bounded operators on a Banach space is analytic, as well as the inverse on invertible operators. ## Main definitions Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n` for `n : ℕ`. * `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially. * `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n` is bounded above, then `r ≤ p.radius`; * `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`, `p.isLittleO_one_of_lt_radius`, `p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then `‖p n‖ * r ^ n` tends to zero exponentially; * `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then `r < p.radius`; * `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`. * `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`. Additionally, let `f` be a function from `E` to `F`. * `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`, `f (x + y) = ∑'_n pₙ yⁿ`. * `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds `HasFPowerSeriesOnBall f p x r`. * `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`. * `AnalyticOnNhd 𝕜 f s`: the function `f` is analytic at every point of `s`. We also define versions of `HasFPowerSeriesOnBall`, `AnalyticAt`, and `AnalyticOnNhd` restricted to a set, similar to `ContinuousWithinAt`. See `Mathlib.Analysis.Analytic.Within` for basic properties. * `AnalyticWithinAt 𝕜 f s x` means a power series at `x` converges to `f` on `𝓝[s ∪ {x}] x`. * `AnalyticOn 𝕜 f s t` means `∀ x ∈ t, AnalyticWithinAt 𝕜 f s x`. We develop the basic properties of these notions, notably: * If a function admits a power series, it is continuous (see `HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and `AnalyticAt.continuousAt`). * In a complete space, the sum of a formal power series with positive radius is well defined on the disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`. ## Implementation details We only introduce the radius of convergence of a power series, as `p.radius`. For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent) notion, describing the polydisk of convergence. This notion is more specific, and not necessary to build the general theory. We do not define it here. -/ noncomputable section variable {𝕜 E F G : Type*} open Topology NNReal Filter ENNReal Set Asymptotics namespace FormalMultilinearSeries variable [Semiring 𝕜] [AddCommMonoid E] [AddCommMonoid F] [Module 𝕜 E] [Module 𝕜 F] variable [TopologicalSpace E] [TopologicalSpace F] variable [ContinuousAdd E] [ContinuousAdd F] variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F] /-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A priori, it only behaves well when `‖x‖ < p.radius`. -/ protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F := ∑' n : ℕ, p n fun _ => x /-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum `Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/ def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F := ∑ k ∈ Finset.range n, p k fun _ : Fin k => x /-- The partial sums of a formal multilinear series are continuous. -/ theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) : Continuous (p.partialSum n) := by unfold partialSum fun_prop end FormalMultilinearSeries /-! ### The radius of a formal multilinear series -/ variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G] namespace FormalMultilinearSeries variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} /-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ` converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these definitions are *not* equivalent in general. -/ def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ := ⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞) /-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/ theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) : (r : ℝ≥0∞) ≤ p.radius := le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h /-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/ theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) : (r : ℝ≥0∞) ≤ p.radius := p.le_radius_of_bound C fun n => mod_cast h n /-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/ theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : ↑r ≤ p.radius := Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC => p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n) theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) : ↑r ≤ p.radius := p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius := p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => h.le_tsum' _ theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius := p.le_radius_of_summable_nnnorm <| by simp only [← coe_nnnorm] at h exact mod_cast h theorem radius_eq_top_of_forall_nnreal_isBigO (h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ := ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r) theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ := p.radius_eq_top_of_forall_nnreal_isBigO fun r => (isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) : p.radius = ∞ := p.radius_eq_top_of_eventually_eq_zero <| mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩ @[simp] theorem constFormalMultilinearSeries_radius {v : F} : (constFormalMultilinearSeries 𝕜 E v).radius = ⊤ := (constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1 (by simp [constFormalMultilinearSeries]) /-- `0` has infinite radius of convergence -/ @[simp] lemma zero_radius : (0 : FormalMultilinearSeries 𝕜 E F).radius = ∞ := by rw [← constFormalMultilinearSeries_zero] exact constFormalMultilinearSeries_radius /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially: for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/ theorem isLittleO_of_lt_radius (h : ↑r < p.radius) : ∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4 rw [this] -- Porting note: was -- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4] simp only [radius, lt_iSup_iff] at h rcases h with ⟨t, C, hC, rt⟩ rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt rw [← div_lt_one this] at rt refine ⟨_, rt, C, Or.inr zero_lt_one, fun n => ?_⟩ calc |‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by field_simp [mul_right_comm, abs_mul] _ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/ theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) : (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) := let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially: for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/ theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) : ∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp (p.isLittleO_of_lt_radius h) rcases this with ⟨a, ha, C, hC, H⟩ exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩ /-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/ theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1) (hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5) rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩ rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀ lift a to ℝ≥0 using ha.1.le have : (r : ℝ) < r / a := by simpa only [div_one] using (div_lt_div_iff_of_pos_left h₀ zero_lt_one ha.1).2 ha.2 norm_cast at this rw [← ENNReal.coe_lt_coe] at this refine this.trans_le (p.le_radius_of_bound C fun n => ?_) rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff₀ (pow_pos ha.1 n)] exact (le_abs_self _).trans (hp n) /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/ theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C := let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h ⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one₀ ha.1.le ha.2.le)⟩ /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/ theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n := let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h ⟨C, hC, fun n => Iff.mpr (le_div_iff₀ (pow_pos h0 _)) (hp n)⟩ /-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/ theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C := let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h ⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩ theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ} (h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius := p.le_radius_of_isBigO (h.isBigO_one _) theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F) (hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius := p.le_radius_of_tendsto hs.tendsto_atTop_zero theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E} (h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n := fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs) theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) : Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _)) hp ((summable_geometric_of_lt_one ha.1.le ha.2).mul_left _) theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E} (hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by rw [mem_emetric_ball_zero_iff] at hx refine .of_nonneg_of_le (fun _ ↦ norm_nonneg _) (fun n ↦ ((p n).le_opNorm _).trans_eq ?_) (p.summable_norm_mul_pow hx) simp theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) : Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by rw [← NNReal.summable_coe] push_cast exact p.summable_norm_mul_pow h protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E} (hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x := (p.summable_norm_apply hx).of_norm theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F) (hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ := ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r) theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) : p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by constructor · intro h r obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius (show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top) refine .of_norm_bounded (fun n ↦ (C : ℝ) * a ^ n) ((summable_geometric_of_lt_one ha.1.le ha.2).mul_left _) fun n ↦ ?_ specialize hp n rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))] · exact p.radius_eq_top_of_summable_norm /-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/ theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) : ∃ (C r : _) (_ : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩ have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0] rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩ refine ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => ?_⟩ rw [inv_pow, ← div_eq_mul_inv] exact hCp n lemma radius_le_of_le {𝕜' E' F' : Type*} [NontriviallyNormedField 𝕜'] [NormedAddCommGroup E'] [NormedSpace 𝕜' E'] [NormedAddCommGroup F'] [NormedSpace 𝕜' F'] {p : FormalMultilinearSeries 𝕜 E F} {q : FormalMultilinearSeries 𝕜' E' F'} (h : ∀ n, ‖p n‖ ≤ ‖q n‖) : q.radius ≤ p.radius := by apply le_of_forall_nnreal_lt (fun r hr ↦ ?_) rcases norm_mul_pow_le_of_lt_radius _ hr with ⟨C, -, hC⟩ apply le_radius_of_bound _ C (fun n ↦ ?_) apply le_trans _ (hC n) gcongr exact h n /-- The radius of the sum of two formal series is at least the minimum of their two radii. -/ theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) : min p.radius q.radius ≤ (p + q).radius := by refine ENNReal.le_of_forall_nnreal_lt fun r hr => ?_ rw [lt_min_iff] at hr have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO refine (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => ?_).trans this) rw [← add_mul, norm_mul, norm_mul, norm_norm] exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _) @[simp] theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by simp only [radius, neg_apply, norm_neg] theorem radius_le_smul {p : FormalMultilinearSeries 𝕜 E F} {c : 𝕜} : p.radius ≤ (c • p).radius := by simp only [radius, smul_apply] refine iSup_mono fun r ↦ iSup_mono' fun C ↦ ⟨‖c‖ * C, iSup_mono' fun h ↦ ?_⟩ simp only [le_refl, exists_prop, and_true] intro n rw [norm_smul c (p n), mul_assoc] gcongr exact h n theorem radius_smul_eq (p : FormalMultilinearSeries 𝕜 E F) {c : 𝕜} (hc : c ≠ 0) : (c • p).radius = p.radius := by apply eq_of_le_of_le _ radius_le_smul exact radius_le_smul.trans_eq (congr_arg _ <| inv_smul_smul₀ hc p) @[simp] theorem radius_shift (p : FormalMultilinearSeries 𝕜 E F) : p.shift.radius = p.radius := by simp only [radius, shift, Nat.succ_eq_add_one, ContinuousMultilinearMap.curryRight_norm] congr ext r apply eq_of_le_of_le · apply iSup_mono' intro C use ‖p 0‖ ⊔ (C * r) apply iSup_mono' intro h simp only [le_refl, le_sup_iff, exists_prop, and_true] intro n rcases n with - | m · simp right rw [pow_succ, ← mul_assoc] apply mul_le_mul_of_nonneg_right (h m) zero_le_coe · apply iSup_mono' intro C use ‖p 1‖ ⊔ C / r apply iSup_mono' intro h simp only [le_refl, le_sup_iff, exists_prop, and_true] intro n cases eq_zero_or_pos r with | inl hr => rw [hr] cases n <;> simp | inr hr => right rw [← NNReal.coe_pos] at hr specialize h (n + 1) rw [le_div_iff₀ hr] rwa [pow_succ, ← mul_assoc] at h @[simp] theorem radius_unshift (p : FormalMultilinearSeries 𝕜 E (E →L[𝕜] F)) (z : F) : (p.unshift z).radius = p.radius := by rw [← radius_shift, unshift_shift] protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E} (hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) := (p.summable hx).hasSum theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F) (f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by refine ENNReal.le_of_forall_nnreal_lt fun r hr => ?_ apply le_radius_of_isBigO apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO refine IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ ?_) (isBigO_refl _ _) refine IsBigOWith.of_bound (Eventually.of_forall fun n => ?_) simpa only [norm_norm] using f.norm_compContinuousMultilinearMap_le (p n) end FormalMultilinearSeries /-! ### Expanding a function as a power series -/ section variable {f g : E → F} {p pf : FormalMultilinearSeries 𝕜 E F} {s t : Set E} {x : E} {r r' : ℝ≥0∞} /-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as a power series on the ball of radius `r > 0` around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `‖y‖ < r`. -/ structure HasFPowerSeriesOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) (r : ℝ≥0∞) : Prop where r_le : r ≤ p.radius r_pos : 0 < r hasSum : ∀ {y}, y ∈ EMetric.ball (0 : E) r → HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y)) /-- Analogue of `HasFPowerSeriesOnBall` where convergence is required only on a set `s`. We also require convergence at `x` as the behavior of this notion is very bad otherwise. -/ structure HasFPowerSeriesWithinOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (s : Set E) (x : E) (r : ℝ≥0∞) : Prop where /-- `p` converges on `ball 0 r` -/ r_le : r ≤ p.radius /-- The radius of convergence is positive -/ r_pos : 0 < r /-- `p converges to f` within `s` -/ hasSum : ∀ {y}, x + y ∈ insert x s → y ∈ EMetric.ball (0 : E) r → HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y)) /-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as a power series around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `y` in a neighborhood of `0`. -/ def HasFPowerSeriesAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) := ∃ r, HasFPowerSeriesOnBall f p x r /-- Analogue of `HasFPowerSeriesAt` where convergence is required only on a set `s`. -/ def HasFPowerSeriesWithinAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (s : Set E) (x : E) := ∃ r, HasFPowerSeriesWithinOnBall f p s x r -- Teach the `bound` tactic that power series have positive radius attribute [bound_forward] HasFPowerSeriesOnBall.r_pos HasFPowerSeriesWithinOnBall.r_pos variable (𝕜) /-- Given a function `f : E → F`, we say that `f` is analytic at `x` if it admits a convergent power series expansion around `x`. -/ @[fun_prop] def AnalyticAt (f : E → F) (x : E) := ∃ p : FormalMultilinearSeries 𝕜 E F, HasFPowerSeriesAt f p x /-- `f` is analytic within `s` at `x` if it has a power series at `x` that converges on `𝓝[s] x` -/ def AnalyticWithinAt (f : E → F) (s : Set E) (x : E) : Prop := ∃ p : FormalMultilinearSeries 𝕜 E F, HasFPowerSeriesWithinAt f p s x /-- Given a function `f : E → F`, we say that `f` is analytic on a set `s` if it is analytic around every point of `s`. -/ def AnalyticOnNhd (f : E → F) (s : Set E) := ∀ x, x ∈ s → AnalyticAt 𝕜 f x /-- `f` is analytic within `s` if it is analytic within `s` at each point of `s`. Note that this is weaker than `AnalyticOnNhd 𝕜 f s`, as `f` is allowed to be arbitrary outside `s`. -/ def AnalyticOn (f : E → F) (s : Set E) : Prop := ∀ x ∈ s, AnalyticWithinAt 𝕜 f s x /-! ### `HasFPowerSeriesOnBall` and `HasFPowerSeriesWithinOnBall` -/ variable {𝕜} theorem HasFPowerSeriesOnBall.hasFPowerSeriesAt (hf : HasFPowerSeriesOnBall f p x r) : HasFPowerSeriesAt f p x := ⟨r, hf⟩ theorem HasFPowerSeriesAt.analyticAt (hf : HasFPowerSeriesAt f p x) : AnalyticAt 𝕜 f x := ⟨p, hf⟩ theorem HasFPowerSeriesOnBall.analyticAt (hf : HasFPowerSeriesOnBall f p x r) : AnalyticAt 𝕜 f x := hf.hasFPowerSeriesAt.analyticAt theorem HasFPowerSeriesWithinOnBall.hasFPowerSeriesWithinAt (hf : HasFPowerSeriesWithinOnBall f p s x r) : HasFPowerSeriesWithinAt f p s x := ⟨r, hf⟩ theorem HasFPowerSeriesWithinAt.analyticWithinAt (hf : HasFPowerSeriesWithinAt f p s x) : AnalyticWithinAt 𝕜 f s x := ⟨p, hf⟩ theorem HasFPowerSeriesWithinOnBall.analyticWithinAt (hf : HasFPowerSeriesWithinOnBall f p s x r) : AnalyticWithinAt 𝕜 f s x := hf.hasFPowerSeriesWithinAt.analyticWithinAt /-- If a function `f` has a power series `p` around `x`, then the function `z ↦ f (z - y)` has the same power series around `x + y`. -/ theorem HasFPowerSeriesOnBall.comp_sub (hf : HasFPowerSeriesOnBall f p x r) (y : E) : HasFPowerSeriesOnBall (fun z => f (z - y)) p (x + y) r := { r_le := hf.r_le r_pos := hf.r_pos hasSum := fun {z} hz => by convert hf.hasSum hz using 2 abel } theorem HasFPowerSeriesWithinOnBall.hasSum_sub (hf : HasFPowerSeriesWithinOnBall f p s x r) {y : E} (hy : y ∈ (insert x s) ∩ EMetric.ball x r) : HasSum (fun n : ℕ => p n fun _ => y - x) (f y) := by have : y - x ∈ EMetric.ball (0 : E) r := by simpa [edist_eq_enorm_sub] using hy.2 have := hf.hasSum (by simpa only [add_sub_cancel] using hy.1) this simpa only [add_sub_cancel] theorem HasFPowerSeriesOnBall.hasSum_sub (hf : HasFPowerSeriesOnBall f p x r) {y : E} (hy : y ∈ EMetric.ball x r) : HasSum (fun n : ℕ => p n fun _ => y - x) (f y) := by have : y - x ∈ EMetric.ball (0 : E) r := by simpa [edist_eq_enorm_sub] using hy simpa only [add_sub_cancel] using hf.hasSum this theorem HasFPowerSeriesOnBall.radius_pos (hf : HasFPowerSeriesOnBall f p x r) : 0 < p.radius := lt_of_lt_of_le hf.r_pos hf.r_le theorem HasFPowerSeriesWithinOnBall.radius_pos (hf : HasFPowerSeriesWithinOnBall f p s x r) : 0 < p.radius := lt_of_lt_of_le hf.r_pos hf.r_le theorem HasFPowerSeriesAt.radius_pos (hf : HasFPowerSeriesAt f p x) : 0 < p.radius := let ⟨_, hr⟩ := hf hr.radius_pos theorem HasFPowerSeriesWithinOnBall.of_le (hf : HasFPowerSeriesWithinOnBall f p s x r) (r'_pos : 0 < r') (hr : r' ≤ r) : HasFPowerSeriesWithinOnBall f p s x r' := ⟨le_trans hr hf.1, r'_pos, fun hy h'y => hf.hasSum hy (EMetric.ball_subset_ball hr h'y)⟩ theorem HasFPowerSeriesOnBall.mono (hf : HasFPowerSeriesOnBall f p x r) (r'_pos : 0 < r') (hr : r' ≤ r) : HasFPowerSeriesOnBall f p x r' := ⟨le_trans hr hf.1, r'_pos, fun hy => hf.hasSum (EMetric.ball_subset_ball hr hy)⟩ lemma HasFPowerSeriesWithinOnBall.congr {f g : E → F} {p : FormalMultilinearSeries 𝕜 E F} {s : Set E} {x : E} {r : ℝ≥0∞} (h : HasFPowerSeriesWithinOnBall f p s x r) (h' : EqOn g f (s ∩ EMetric.ball x r)) (h'' : g x = f x) : HasFPowerSeriesWithinOnBall g p s x r := by refine ⟨h.r_le, h.r_pos, ?_⟩ intro y hy h'y convert h.hasSum hy h'y using 1 simp only [mem_insert_iff, add_eq_left] at hy rcases hy with rfl | hy · simpa using h'' · apply h' refine ⟨hy, ?_⟩ simpa [edist_eq_enorm_sub] using h'y /-- Variant of `HasFPowerSeriesWithinOnBall.congr` in which one requests equality on `insert x s` instead of separating `x` and `s`. -/ lemma HasFPowerSeriesWithinOnBall.congr' {f g : E → F} {p : FormalMultilinearSeries 𝕜 E F} {s : Set E} {x : E} {r : ℝ≥0∞} (h : HasFPowerSeriesWithinOnBall f p s x r) (h' : EqOn g f (insert x s ∩ EMetric.ball x r)) : HasFPowerSeriesWithinOnBall g p s x r := by refine ⟨h.r_le, h.r_pos, fun {y} hy h'y ↦ ?_⟩ convert h.hasSum hy h'y using 1 exact h' ⟨hy, by simpa [edist_eq_enorm_sub] using h'y⟩ lemma HasFPowerSeriesWithinAt.congr {f g : E → F} {p : FormalMultilinearSeries 𝕜 E F} {s : Set E} {x : E} (h : HasFPowerSeriesWithinAt f p s x) (h' : g =ᶠ[𝓝[s] x] f) (h'' : g x = f x) : HasFPowerSeriesWithinAt g p s x := by rcases h with ⟨r, hr⟩ obtain ⟨ε, εpos, hε⟩ : ∃ ε > 0, EMetric.ball x ε ∩ s ⊆ {y | g y = f y} := EMetric.mem_nhdsWithin_iff.1 h' let r' := min r ε refine ⟨r', ?_⟩ have := hr.of_le (r' := r') (by simp [r', εpos, hr.r_pos]) (min_le_left _ _) apply this.congr _ h'' intro z hz exact hε ⟨EMetric.ball_subset_ball (min_le_right _ _) hz.2, hz.1⟩ theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r) (hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r := { r_le := hf.r_le r_pos := hf.r_pos hasSum := fun {y} hy => by convert hf.hasSum hy using 1 apply hg.symm simpa [edist_eq_enorm_sub] using hy } theorem HasFPowerSeriesAt.congr (hf : HasFPowerSeriesAt f p x) (hg : f =ᶠ[𝓝 x] g) : HasFPowerSeriesAt g p x := by rcases hf with ⟨r₁, h₁⟩ rcases EMetric.mem_nhds_iff.mp hg with ⟨r₂, h₂pos, h₂⟩ exact ⟨min r₁ r₂, (h₁.mono (lt_min h₁.r_pos h₂pos) inf_le_left).congr fun y hy => h₂ (EMetric.ball_subset_ball inf_le_right hy)⟩
theorem HasFPowerSeriesWithinOnBall.unique (hf : HasFPowerSeriesWithinOnBall f p s x r) (hg : HasFPowerSeriesWithinOnBall g p s x r) :
Mathlib/Analysis/Analytic/Basic.lean
581
583
/- Copyright (c) 2021 Alex J. Best. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Alex J. Best -/ import Mathlib.Algebra.GroupWithZero.Units.Basic import Mathlib.Algebra.Group.Action.Basic import Mathlib.Algebra.Group.Pointwise.Set.Scalar /-! # Pointwise actions on sets in Pi types This file contains lemmas about pointwise actions on sets in Pi types. ## Tags set multiplication, set addition, pointwise addition, pointwise multiplication, pi -/ open Pointwise open Set variable {K ι : Type*} {R : ι → Type*} @[to_additive] theorem smul_pi_subset [∀ i, SMul K (R i)] (r : K) (s : Set ι) (t : ∀ i, Set (R i)) : r • pi s t ⊆ pi s (r • t) := piMap_image_pi_subset _ @[to_additive] theorem smul_univ_pi [∀ i, SMul K (R i)] (r : K) (t : ∀ i, Set (R i)) : r • pi (univ : Set ι) t = pi (univ : Set ι) (r • t) := piMap_image_univ_pi _ _ @[to_additive]
theorem smul_pi [Group K] [∀ i, MulAction K (R i)] (r : K) (S : Set ι) (t : ∀ i, Set (R i)) : r • S.pi t = S.pi (r • t) := piMap_image_pi (fun _ _ => MulAction.surjective _) _ theorem smul_pi₀ [GroupWithZero K] [∀ i, MulAction K (R i)] {r : K} (S : Set ι) (t : ∀ i, Set (R i)) (hr : r ≠ 0) : r • S.pi t = S.pi (r • t) :=
Mathlib/Algebra/Module/PointwisePi.lean
38
43
/- 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
Mathlib/MeasureTheory/Function/StronglyMeasurable/Basic.lean
593
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/- Copyright (c) 2020 Patrick Massot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Patrick Massot -/ import Mathlib.Topology.Path /-! # Path connectedness Continuing from `Mathlib.Topology.Path`, this file defines path components and path-connected spaces. ## Main definitions In the file the unit interval `[0, 1]` in `ℝ` is denoted by `I`, and `X` is a topological space. * `Joined (x y : X)` means there is a path between `x` and `y`. * `Joined.somePath (h : Joined x y)` selects some path between two points `x` and `y`. * `pathComponent (x : X)` is the set of points joined to `x`. * `PathConnectedSpace X` is a predicate class asserting that `X` is non-empty and every two points of `X` are joined. Then there are corresponding relative notions for `F : Set X`. * `JoinedIn F (x y : X)` means there is a path `γ` joining `x` to `y` with values in `F`. * `JoinedIn.somePath (h : JoinedIn F x y)` selects a path from `x` to `y` inside `F`. * `pathComponentIn F (x : X)` is the set of points joined to `x` in `F`. * `IsPathConnected F` asserts that `F` is non-empty and every two points of `F` are joined in `F`. ## Main theorems * `Joined` is an equivalence relation, while `JoinedIn F` is at least symmetric and transitive. One can link the absolute and relative version in two directions, using `(univ : Set X)` or the subtype `↥F`. * `pathConnectedSpace_iff_univ : PathConnectedSpace X ↔ IsPathConnected (univ : Set X)` * `isPathConnected_iff_pathConnectedSpace : IsPathConnected F ↔ PathConnectedSpace ↥F` Furthermore, it is shown that continuous images and quotients of path-connected sets/spaces are path-connected, and that every path-connected set/space is also connected. -/ noncomputable section open Topology Filter unitInterval Set Function variable {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {x y z : X} {ι : Type*} /-! ### Being joined by a path -/ /-- The relation "being joined by a path". This is an equivalence relation. -/ def Joined (x y : X) : Prop := Nonempty (Path x y) @[refl] theorem Joined.refl (x : X) : Joined x x := ⟨Path.refl x⟩ /-- When two points are joined, choose some path from `x` to `y`. -/ def Joined.somePath (h : Joined x y) : Path x y := Nonempty.some h @[symm] theorem Joined.symm {x y : X} (h : Joined x y) : Joined y x := ⟨h.somePath.symm⟩ @[trans] theorem Joined.trans {x y z : X} (hxy : Joined x y) (hyz : Joined y z) : Joined x z := ⟨hxy.somePath.trans hyz.somePath⟩ variable (X) /-- The setoid corresponding the equivalence relation of being joined by a continuous path. -/ def pathSetoid : Setoid X where r := Joined iseqv := Equivalence.mk Joined.refl Joined.symm Joined.trans /-- The quotient type of points of a topological space modulo being joined by a continuous path. -/ def ZerothHomotopy := Quotient (pathSetoid X) instance ZerothHomotopy.inhabited : Inhabited (ZerothHomotopy ℝ) := ⟨@Quotient.mk' ℝ (pathSetoid ℝ) 0⟩ variable {X} /-! ### Being joined by a path inside a set -/ /-- The relation "being joined by a path in `F`". Not quite an equivalence relation since it's not reflexive for points that do not belong to `F`. -/ def JoinedIn (F : Set X) (x y : X) : Prop := ∃ γ : Path x y, ∀ t, γ t ∈ F variable {F : Set X} theorem JoinedIn.mem (h : JoinedIn F x y) : x ∈ F ∧ y ∈ F := by rcases h with ⟨γ, γ_in⟩ have : γ 0 ∈ F ∧ γ 1 ∈ F := by constructor <;> apply γ_in simpa using this theorem JoinedIn.source_mem (h : JoinedIn F x y) : x ∈ F := h.mem.1 theorem JoinedIn.target_mem (h : JoinedIn F x y) : y ∈ F := h.mem.2 /-- When `x` and `y` are joined in `F`, choose a path from `x` to `y` inside `F` -/ def JoinedIn.somePath (h : JoinedIn F x y) : Path x y := Classical.choose h theorem JoinedIn.somePath_mem (h : JoinedIn F x y) (t : I) : h.somePath t ∈ F := Classical.choose_spec h t /-- If `x` and `y` are joined in the set `F`, then they are joined in the subtype `F`. -/ theorem JoinedIn.joined_subtype (h : JoinedIn F x y) : Joined (⟨x, h.source_mem⟩ : F) (⟨y, h.target_mem⟩ : F) := ⟨{ toFun := fun t => ⟨h.somePath t, h.somePath_mem t⟩ continuous_toFun := by fun_prop source' := by simp target' := by simp }⟩ theorem JoinedIn.ofLine {f : ℝ → X} (hf : ContinuousOn f I) (h₀ : f 0 = x) (h₁ : f 1 = y) (hF : f '' I ⊆ F) : JoinedIn F x y := ⟨Path.ofLine hf h₀ h₁, fun t => hF <| Path.ofLine_mem hf h₀ h₁ t⟩ theorem JoinedIn.joined (h : JoinedIn F x y) : Joined x y := ⟨h.somePath⟩ theorem joinedIn_iff_joined (x_in : x ∈ F) (y_in : y ∈ F) : JoinedIn F x y ↔ Joined (⟨x, x_in⟩ : F) (⟨y, y_in⟩ : F) := ⟨fun h => h.joined_subtype, fun h => ⟨h.somePath.map continuous_subtype_val, by simp⟩⟩ @[simp] theorem joinedIn_univ : JoinedIn univ x y ↔ Joined x y := by simp [JoinedIn, Joined, exists_true_iff_nonempty] theorem JoinedIn.mono {U V : Set X} (h : JoinedIn U x y) (hUV : U ⊆ V) : JoinedIn V x y := ⟨h.somePath, fun t => hUV (h.somePath_mem t)⟩ theorem JoinedIn.refl (h : x ∈ F) : JoinedIn F x x := ⟨Path.refl x, fun _t => h⟩ @[symm] theorem JoinedIn.symm (h : JoinedIn F x y) : JoinedIn F y x := by obtain ⟨hx, hy⟩ := h.mem simp_all only [joinedIn_iff_joined] exact h.symm theorem JoinedIn.trans (hxy : JoinedIn F x y) (hyz : JoinedIn F y z) : JoinedIn F x z := by obtain ⟨hx, hy⟩ := hxy.mem obtain ⟨hx, hy⟩ := hyz.mem simp_all only [joinedIn_iff_joined] exact hxy.trans hyz theorem Specializes.joinedIn (h : x ⤳ y) (hx : x ∈ F) (hy : y ∈ F) : JoinedIn F x y := by refine ⟨⟨⟨Set.piecewise {1} (const I y) (const I x), ?_⟩, by simp, by simp⟩, fun t ↦ ?_⟩ · exact isClosed_singleton.continuous_piecewise_of_specializes continuous_const continuous_const fun _ ↦ h · simp only [Path.coe_mk_mk, piecewise] split_ifs <;> assumption theorem Inseparable.joinedIn (h : Inseparable x y) (hx : x ∈ F) (hy : y ∈ F) : JoinedIn F x y := h.specializes.joinedIn hx hy theorem JoinedIn.map_continuousOn (h : JoinedIn F x y) {f : X → Y} (hf : ContinuousOn f F) : JoinedIn (f '' F) (f x) (f y) := let ⟨γ, hγ⟩ := h ⟨γ.map' <| hf.mono (range_subset_iff.mpr hγ), fun t ↦ mem_image_of_mem _ (hγ t)⟩ theorem JoinedIn.map (h : JoinedIn F x y) {f : X → Y} (hf : Continuous f) : JoinedIn (f '' F) (f x) (f y) := h.map_continuousOn hf.continuousOn theorem Topology.IsInducing.joinedIn_image {f : X → Y} (hf : IsInducing f) (hx : x ∈ F) (hy : y ∈ F) : JoinedIn (f '' F) (f x) (f y) ↔ JoinedIn F x y := by refine ⟨?_, (.map · hf.continuous)⟩ rintro ⟨γ, hγ⟩ choose γ' hγ'F hγ' using hγ have h₀ : x ⤳ γ' 0 := by rw [← hf.specializes_iff, hγ', γ.source] have h₁ : γ' 1 ⤳ y := by rw [← hf.specializes_iff, hγ', γ.target] have h : JoinedIn F (γ' 0) (γ' 1) := by refine ⟨⟨⟨γ', ?_⟩, rfl, rfl⟩, hγ'F⟩ simpa only [hf.continuous_iff, comp_def, hγ'] using map_continuous γ exact (h₀.joinedIn hx (hγ'F _)).trans <| h.trans <| h₁.joinedIn (hγ'F _) hy @[deprecated (since := "2024-10-28")] alias Inducing.joinedIn_image := IsInducing.joinedIn_image /-! ### Path component -/ /-- The path component of `x` is the set of points that can be joined to `x`. -/ def pathComponent (x : X) := { y | Joined x y } theorem mem_pathComponent_iff : x ∈ pathComponent y ↔ Joined y x := .rfl @[simp] theorem mem_pathComponent_self (x : X) : x ∈ pathComponent x := Joined.refl x @[simp] theorem pathComponent.nonempty (x : X) : (pathComponent x).Nonempty := ⟨x, mem_pathComponent_self x⟩ theorem mem_pathComponent_of_mem (h : x ∈ pathComponent y) : y ∈ pathComponent x := Joined.symm h theorem pathComponent_symm : x ∈ pathComponent y ↔ y ∈ pathComponent x := ⟨fun h => mem_pathComponent_of_mem h, fun h => mem_pathComponent_of_mem h⟩ theorem pathComponent_congr (h : x ∈ pathComponent y) : pathComponent x = pathComponent y := by ext z constructor · intro h' rw [pathComponent_symm] exact (h.trans h').symm · intro h' rw [pathComponent_symm] at h' ⊢ exact h'.trans h theorem pathComponent_subset_component (x : X) : pathComponent x ⊆ connectedComponent x := fun y h => (isConnected_range h.somePath.continuous).subset_connectedComponent ⟨0, by simp⟩ ⟨1, by simp⟩ /-- The path component of `x` in `F` is the set of points that can be joined to `x` in `F`. -/ def pathComponentIn (x : X) (F : Set X) := { y | JoinedIn F x y } @[simp] theorem pathComponentIn_univ (x : X) : pathComponentIn x univ = pathComponent x := by simp [pathComponentIn, pathComponent, JoinedIn, Joined, exists_true_iff_nonempty] theorem Joined.mem_pathComponent (hyz : Joined y z) (hxy : y ∈ pathComponent x) : z ∈ pathComponent x := hxy.trans hyz theorem mem_pathComponentIn_self (h : x ∈ F) : x ∈ pathComponentIn x F := JoinedIn.refl h theorem pathComponentIn_subset : pathComponentIn x F ⊆ F := fun _ hy ↦ hy.target_mem theorem pathComponentIn_nonempty_iff : (pathComponentIn x F).Nonempty ↔ x ∈ F := ⟨fun ⟨_, ⟨γ, hγ⟩⟩ ↦ γ.source ▸ hγ 0, fun hx ↦ ⟨x, mem_pathComponentIn_self hx⟩⟩ theorem pathComponentIn_congr (h : x ∈ pathComponentIn y F) : pathComponentIn x F = pathComponentIn y F := by ext; exact ⟨h.trans, h.symm.trans⟩ @[gcongr] theorem pathComponentIn_mono {G : Set X} (h : F ⊆ G) : pathComponentIn x F ⊆ pathComponentIn x G := fun _ ⟨γ, hγ⟩ ↦ ⟨γ, fun t ↦ h (hγ t)⟩ /-! ### Path connected sets -/ /-- A set `F` is path connected if it contains a point that can be joined to all other in `F`. -/ def IsPathConnected (F : Set X) : Prop := ∃ x ∈ F, ∀ {y}, y ∈ F → JoinedIn F x y theorem isPathConnected_iff_eq : IsPathConnected F ↔ ∃ x ∈ F, pathComponentIn x F = F := by constructor <;> rintro ⟨x, x_in, h⟩ <;> use x, x_in · ext y exact ⟨fun hy => hy.mem.2, h⟩ · intro y y_in rwa [← h] at y_in theorem IsPathConnected.joinedIn (h : IsPathConnected F) : ∀ᵉ (x ∈ F) (y ∈ F), JoinedIn F x y := fun _x x_in _y y_in => let ⟨_b, _b_in, hb⟩ := h (hb x_in).symm.trans (hb y_in) theorem isPathConnected_iff : IsPathConnected F ↔ F.Nonempty ∧ ∀ᵉ (x ∈ F) (y ∈ F), JoinedIn F x y := ⟨fun h => ⟨let ⟨b, b_in, _hb⟩ := h; ⟨b, b_in⟩, h.joinedIn⟩, fun ⟨⟨b, b_in⟩, h⟩ => ⟨b, b_in, fun x_in => h _ b_in _ x_in⟩⟩ /-- If `f` is continuous on `F` and `F` is path-connected, so is `f(F)`. -/ theorem IsPathConnected.image' (hF : IsPathConnected F) {f : X → Y} (hf : ContinuousOn f F) : IsPathConnected (f '' F) := by rcases hF with ⟨x, x_in, hx⟩ use f x, mem_image_of_mem f x_in rintro _ ⟨y, y_in, rfl⟩ refine ⟨(hx y_in).somePath.map' ?_, fun t ↦ ⟨_, (hx y_in).somePath_mem t, rfl⟩⟩ exact hf.mono (range_subset_iff.2 (hx y_in).somePath_mem) /-- If `f` is continuous and `F` is path-connected, so is `f(F)`. -/ theorem IsPathConnected.image (hF : IsPathConnected F) {f : X → Y} (hf : Continuous f) : IsPathConnected (f '' F) := hF.image' hf.continuousOn /-- If `f : X → Y` is an inducing map, `f(F)` is path-connected iff `F` is. -/ nonrec theorem Topology.IsInducing.isPathConnected_iff {f : X → Y} (hf : IsInducing f) : IsPathConnected F ↔ IsPathConnected (f '' F) := by simp only [IsPathConnected, forall_mem_image, exists_mem_image] refine exists_congr fun x ↦ and_congr_right fun hx ↦ forall₂_congr fun y hy ↦ ?_ rw [hf.joinedIn_image hx hy] @[deprecated (since := "2024-10-28")] alias Inducing.isPathConnected_iff := IsInducing.isPathConnected_iff /-- If `h : X → Y` is a homeomorphism, `h(s)` is path-connected iff `s` is. -/ @[simp] theorem Homeomorph.isPathConnected_image {s : Set X} (h : X ≃ₜ Y) : IsPathConnected (h '' s) ↔ IsPathConnected s := h.isInducing.isPathConnected_iff.symm /-- If `h : X → Y` is a homeomorphism, `h⁻¹(s)` is path-connected iff `s` is. -/ @[simp] theorem Homeomorph.isPathConnected_preimage {s : Set Y} (h : X ≃ₜ Y) : IsPathConnected (h ⁻¹' s) ↔ IsPathConnected s := by rw [← Homeomorph.image_symm]; exact h.symm.isPathConnected_image theorem IsPathConnected.mem_pathComponent (h : IsPathConnected F) (x_in : x ∈ F) (y_in : y ∈ F) : y ∈ pathComponent x := (h.joinedIn x x_in y y_in).joined theorem IsPathConnected.subset_pathComponent (h : IsPathConnected F) (x_in : x ∈ F) : F ⊆ pathComponent x := fun _y y_in => h.mem_pathComponent x_in y_in theorem IsPathConnected.subset_pathComponentIn {s : Set X} (hs : IsPathConnected s) (hxs : x ∈ s) (hsF : s ⊆ F) : s ⊆ pathComponentIn x F := fun y hys ↦ (hs.joinedIn x hxs y hys).mono hsF theorem isPathConnected_singleton (x : X) : IsPathConnected ({x} : Set X) := by refine ⟨x, rfl, ?_⟩ rintro y rfl exact JoinedIn.refl rfl theorem isPathConnected_pathComponentIn (h : x ∈ F) : IsPathConnected (pathComponentIn x F) := ⟨x, mem_pathComponentIn_self h, fun ⟨γ, hγ⟩ ↦ by refine ⟨γ, fun t ↦ ⟨(γ.truncateOfLE t.2.1).cast (γ.extend_zero.symm) (γ.extend_extends' t).symm, fun t' ↦ ?_⟩⟩ dsimp [Path.truncateOfLE, Path.truncate] exact γ.extend_extends' ⟨min (max t'.1 0) t.1, by simp [t.2.1, t.2.2]⟩ ▸ hγ _⟩ theorem isPathConnected_pathComponent : IsPathConnected (pathComponent x) := by rw [← pathComponentIn_univ] exact isPathConnected_pathComponentIn (mem_univ x) theorem IsPathConnected.union {U V : Set X} (hU : IsPathConnected U) (hV : IsPathConnected V) (hUV : (U ∩ V).Nonempty) : IsPathConnected (U ∪ V) := by rcases hUV with ⟨x, xU, xV⟩ use x, Or.inl xU rintro y (yU | yV) · exact (hU.joinedIn x xU y yU).mono subset_union_left · exact (hV.joinedIn x xV y yV).mono subset_union_right /-- If a set `W` is path-connected, then it is also path-connected when seen as a set in a smaller ambient type `U` (when `U` contains `W`). -/ theorem IsPathConnected.preimage_coe {U W : Set X} (hW : IsPathConnected W) (hWU : W ⊆ U) : IsPathConnected (((↑) : U → X) ⁻¹' W) := by rwa [IsInducing.subtypeVal.isPathConnected_iff, Subtype.image_preimage_val, inter_eq_right.2 hWU] theorem IsPathConnected.exists_path_through_family {n : ℕ} {s : Set X} (h : IsPathConnected s) (p : Fin (n + 1) → X) (hp : ∀ i, p i ∈ s) : ∃ γ : Path (p 0) (p n), range γ ⊆ s ∧ ∀ i, p i ∈ range γ := by let p' : ℕ → X := fun k => if h : k < n + 1 then p ⟨k, h⟩ else p ⟨0, n.zero_lt_succ⟩ obtain ⟨γ, hγ⟩ : ∃ γ : Path (p' 0) (p' n), (∀ i ≤ n, p' i ∈ range γ) ∧ range γ ⊆ s := by have hp' : ∀ i ≤ n, p' i ∈ s := by intro i hi simp [p', Nat.lt_succ_of_le hi, hp] clear_value p' clear hp p induction n with | zero => use Path.refl (p' 0) constructor · rintro i hi rw [Nat.le_zero.mp hi] exact ⟨0, rfl⟩ · rw [range_subset_iff] rintro _x exact hp' 0 le_rfl | succ n hn => rcases hn fun i hi => hp' i <| Nat.le_succ_of_le hi with ⟨γ₀, hγ₀⟩ rcases h.joinedIn (p' n) (hp' n n.le_succ) (p' <| n + 1) (hp' (n + 1) <| le_rfl) with ⟨γ₁, hγ₁⟩ let γ : Path (p' 0) (p' <| n + 1) := γ₀.trans γ₁ use γ have range_eq : range γ = range γ₀ ∪ range γ₁ := γ₀.trans_range γ₁ constructor · rintro i hi by_cases hi' : i ≤ n · rw [range_eq] left exact hγ₀.1 i hi' · rw [not_le, ← Nat.succ_le_iff] at hi' have : i = n.succ := le_antisymm hi hi' rw [this] use 1 exact γ.target · rw [range_eq] apply union_subset hγ₀.2 rw [range_subset_iff] exact hγ₁ have hpp' : ∀ k < n + 1, p k = p' k := by intro k hk simp only [p', hk, dif_pos] congr ext rw [Fin.val_cast_of_lt hk] use γ.cast (hpp' 0 n.zero_lt_succ) (hpp' n n.lt_succ_self) simp only [γ.cast_coe] refine And.intro hγ.2 ?_ rintro ⟨i, hi⟩ suffices p ⟨i, hi⟩ = p' i by convert hγ.1 i (Nat.le_of_lt_succ hi) rw [← hpp' i hi] suffices i = i % n.succ by congr rw [Nat.mod_eq_of_lt hi] theorem IsPathConnected.exists_path_through_family' {n : ℕ} {s : Set X} (h : IsPathConnected s) (p : Fin (n + 1) → X) (hp : ∀ i, p i ∈ s) : ∃ (γ : Path (p 0) (p n)) (t : Fin (n + 1) → I), (∀ t, γ t ∈ s) ∧ ∀ i, γ (t i) = p i := by rcases h.exists_path_through_family p hp with ⟨γ, hγ⟩ rcases hγ with ⟨h₁, h₂⟩ simp only [range, mem_setOf_eq] at h₂ rw [range_subset_iff] at h₁ choose! t ht using h₂ exact ⟨γ, t, h₁, ht⟩ /-! ### Path connected spaces -/ /-- A topological space is path-connected if it is non-empty and every two points can be joined by a continuous path. -/ @[mk_iff] class PathConnectedSpace (X : Type*) [TopologicalSpace X] : Prop where /-- A path-connected space must be nonempty. -/ nonempty : Nonempty X /-- Any two points in a path-connected space must be joined by a continuous path. -/ joined : ∀ x y : X, Joined x y theorem pathConnectedSpace_iff_zerothHomotopy : PathConnectedSpace X ↔ Nonempty (ZerothHomotopy X) ∧ Subsingleton (ZerothHomotopy X) := by letI := pathSetoid X constructor · intro h refine ⟨(nonempty_quotient_iff _).mpr h.1, ⟨?_⟩⟩ rintro ⟨x⟩ ⟨y⟩ exact Quotient.sound (PathConnectedSpace.joined x y) · unfold ZerothHomotopy rintro ⟨h, h'⟩ exact ⟨(nonempty_quotient_iff _).mp h, fun x y => Quotient.exact <| Subsingleton.elim ⟦x⟧ ⟦y⟧⟩ namespace PathConnectedSpace variable [PathConnectedSpace X] /-- Use path-connectedness to build a path between two points. -/ def somePath (x y : X) : Path x y := Nonempty.some (joined x y) end PathConnectedSpace theorem pathConnectedSpace_iff_univ : PathConnectedSpace X ↔ IsPathConnected (univ : Set X) := by simp [pathConnectedSpace_iff, isPathConnected_iff, nonempty_iff_univ_nonempty] theorem isPathConnected_iff_pathConnectedSpace : IsPathConnected F ↔ PathConnectedSpace F := by rw [pathConnectedSpace_iff_univ, IsInducing.subtypeVal.isPathConnected_iff, image_univ, Subtype.range_val_subtype, setOf_mem_eq] theorem isPathConnected_univ [PathConnectedSpace X] : IsPathConnected (univ : Set X) := pathConnectedSpace_iff_univ.mp inferInstance theorem isPathConnected_range [PathConnectedSpace X] {f : X → Y} (hf : Continuous f) : IsPathConnected (range f) := by rw [← image_univ] exact isPathConnected_univ.image hf theorem Function.Surjective.pathConnectedSpace [PathConnectedSpace X] {f : X → Y} (hf : Surjective f) (hf' : Continuous f) : PathConnectedSpace Y := by rw [pathConnectedSpace_iff_univ, ← hf.range_eq] exact isPathConnected_range hf' instance Quotient.instPathConnectedSpace {s : Setoid X} [PathConnectedSpace X] : PathConnectedSpace (Quotient s) := Quotient.mk'_surjective.pathConnectedSpace continuous_coinduced_rng /-- This is a special case of `NormedSpace.instPathConnectedSpace` (and `IsTopologicalAddGroup.pathConnectedSpace`). It exists only to simplify dependencies. -/ instance Real.instPathConnectedSpace : PathConnectedSpace ℝ where joined x y := ⟨⟨⟨fun (t : I) ↦ (1 - t) * x + t * y, by fun_prop⟩, by simp, by simp⟩⟩ nonempty := inferInstance theorem pathConnectedSpace_iff_eq : PathConnectedSpace X ↔ ∃ x : X, pathComponent x = univ := by simp [pathConnectedSpace_iff_univ, isPathConnected_iff_eq] -- see Note [lower instance priority] instance (priority := 100) PathConnectedSpace.connectedSpace [PathConnectedSpace X] : ConnectedSpace X := by rw [connectedSpace_iff_connectedComponent] rcases isPathConnected_iff_eq.mp (pathConnectedSpace_iff_univ.mp ‹_›) with ⟨x, _x_in, hx⟩ use x rw [← univ_subset_iff] exact (by simpa using hx : pathComponent x = univ) ▸ pathComponent_subset_component x theorem IsPathConnected.isConnected (hF : IsPathConnected F) : IsConnected F := by rw [isConnected_iff_connectedSpace] rw [isPathConnected_iff_pathConnectedSpace] at hF exact @PathConnectedSpace.connectedSpace _ _ hF namespace PathConnectedSpace variable [PathConnectedSpace X] theorem exists_path_through_family {n : ℕ} (p : Fin (n + 1) → X) : ∃ γ : Path (p 0) (p n), ∀ i, p i ∈ range γ := by have : IsPathConnected (univ : Set X) := pathConnectedSpace_iff_univ.mp (by infer_instance) rcases this.exists_path_through_family p fun _i => True.intro with ⟨γ, -, h⟩ exact ⟨γ, h⟩ theorem exists_path_through_family' {n : ℕ} (p : Fin (n + 1) → X) : ∃ (γ : Path (p 0) (p n)) (t : Fin (n + 1) → I), ∀ i, γ (t i) = p i := by have : IsPathConnected (univ : Set X) := pathConnectedSpace_iff_univ.mp (by infer_instance) rcases this.exists_path_through_family' p fun _i => True.intro with ⟨γ, t, -, h⟩ exact ⟨γ, t, h⟩ end PathConnectedSpace
Mathlib/Topology/Connected/PathConnected.lean
1,260
1,270
/- Copyright (c) 2023 Peter Nelson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Peter Nelson -/ import Mathlib.Data.Finite.Prod import Mathlib.Data.Matroid.Init import Mathlib.Data.Set.Card import Mathlib.Data.Set.Finite.Powerset import Mathlib.Order.UpperLower.Closure /-! # Matroids A `Matroid` is a structure that combinatorially abstracts the notion of linear independence and dependence; matroids have connections with graph theory, discrete optimization, additive combinatorics and algebraic geometry. Mathematically, a matroid `M` is a structure on a set `E` comprising a collection of subsets of `E` called the bases of `M`, where the bases are required to obey certain axioms. This file gives a definition of a matroid `M` in terms of its bases, and some API relating independent sets (subsets of bases) and the notion of a basis of a set `X` (a maximal independent subset of `X`). ## Main definitions * a `Matroid α` on a type `α` is a structure comprising a 'ground set' and a suitably behaved 'base' predicate. Given `M : Matroid α` ... * `M.E` denotes the ground set of `M`, which has type `Set α` * For `B : Set α`, `M.IsBase B` means that `B` is a base of `M`. * For `I : Set α`, `M.Indep I` means that `I` is independent in `M` (that is, `I` is contained in a base of `M`). * For `D : Set α`, `M.Dep D` means that `D` is contained in the ground set of `M` but isn't independent. * For `I : Set α` and `X : Set α`, `M.IsBasis I X` means that `I` is a maximal independent subset of `X`. * `M.Finite` means that `M` has finite ground set. * `M.Nonempty` means that the ground set of `M` is nonempty. * `RankFinite M` means that the bases of `M` are finite. * `RankInfinite M` means that the bases of `M` are infinite. * `RankPos M` means that the bases of `M` are nonempty. * `Finitary M` means that a set is independent if and only if all its finite subsets are independent. * `aesop_mat` : a tactic designed to prove `X ⊆ M.E` for some set `X` and matroid `M`. ## Implementation details There are a few design decisions worth discussing. ### Finiteness The first is that our matroids are allowed to be infinite. Unlike with many mathematical structures, this isn't such an obvious choice. Finite matroids have been studied since the 1930's, and there was never controversy as to what is and isn't an example of a finite matroid - in fact, surprisingly many apparently different definitions of a matroid give rise to the same class of objects. However, generalizing different definitions of a finite matroid to the infinite in the obvious way (i.e. by simply allowing the ground set to be infinite) gives a number of different notions of 'infinite matroid' that disagree with each other, and that all lack nice properties. Many different competing notions of infinite matroid were studied through the years; in fact, the problem of which definition is the best was only really solved in 2013, when Bruhn et al. [2] showed that there is a unique 'reasonable' notion of an infinite matroid (these objects had previously defined by Higgs under the name 'B-matroid'). These are defined by adding one carefully chosen axiom to the standard set, and adapting existing axioms to not mention set cardinalities; they enjoy nearly all the nice properties of standard finite matroids. Even though at least 90% of the literature is on finite matroids, B-matroids are the definition we use, because they allow for additional generality, nearly all theorems are still true and just as easy to state, and (hopefully) the more general definition will prevent the need for a costly future refactor. The disadvantage is that developing API for the finite case is harder work (for instance, it is harder to prove that something is a matroid in the first place, and one must deal with `ℕ∞` rather than `ℕ`). For serious work on finite matroids, we provide the typeclasses `[M.Finite]` and `[RankFinite M]` and associated API. ### Cardinality Just as with bases of a vector space, all bases of a finite matroid `M` are finite and have the same cardinality; this cardinality is an important invariant known as the 'rank' of `M`. For infinite matroids, bases are not in general equicardinal; in fact the equicardinality of bases of infinite matroids is independent of ZFC [3]. What is still true is that either all bases are finite and equicardinal, or all bases are infinite. This means that the natural notion of 'size' for a set in matroid theory is given by the function `Set.encard`, which is the cardinality as a term in `ℕ∞`. We use this function extensively in building the API; it is preferable to both `Set.ncard` and `Finset.card` because it allows infinite sets to be handled without splitting into cases. ### The ground `Set` A last place where we make a consequential choice is making the ground set of a matroid a structure field of type `Set α` (where `α` is the type of 'possible matroid elements') rather than just having a type `α` of all the matroid elements. This is because of how common it is to simultaneously consider a number of matroids on different but related ground sets. For example, a matroid `M` on ground set `E` can have its structure 'restricted' to some subset `R ⊆ E` to give a smaller matroid `M ↾ R` with ground set `R`. A statement like `(M ↾ R₁) ↾ R₂ = M ↾ R₂` is mathematically obvious. But if the ground set of a matroid is a type, this doesn't typecheck, and is only true up to canonical isomorphism. Restriction is just the tip of the iceberg here; one can also 'contract' and 'delete' elements and sets of elements in a matroid to give a smaller matroid, and in practice it is common to make statements like `M₁.E = M₂.E ∩ M₃.E` and `((M ⟋ e) ↾ R) ⟋ C = M ⟋ (C ∪ {e}) ↾ R`. Such things are a nightmare to work with unless `=` is actually propositional equality (especially because the relevant coercions are usually between sets and not just elements). So the solution is that the ground set `M.E` has type `Set α`, and there are elements of type `α` that aren't in the matroid. The tradeoff is that for many statements, one now has to add hypotheses of the form `X ⊆ M.E` to make sure than `X` is actually 'in the matroid', rather than letting a 'type of matroid elements' take care of this invisibly. It still seems that this is worth it. The tactic `aesop_mat` exists specifically to discharge such goals with minimal fuss (using default values). The tactic works fairly well, but has room for improvement. A related decision is to not have matroids themselves be a typeclass. This would make things be notationally simpler (having `Base` in the presence of `[Matroid α]` rather than `M.Base` for a term `M : Matroid α`) but is again just too awkward when one has multiple matroids on the same type. In fact, in regular written mathematics, it is normal to explicitly indicate which matroid something is happening in, so our notation mirrors common practice. ### Notation We use a few nonstandard conventions in theorem names that are related to the above. First, we mirror common informal practice by referring explicitly to the `ground` set rather than the notation `E`. (Writing `ground` everywhere in a proof term would be unwieldy, and writing `E` in theorem names would be unnatural to read.) Second, because we are typically interested in subsets of the ground set `M.E`, using `Set.compl` is inconvenient, since `Xᶜ ⊆ M.E` is typically false for `X ⊆ M.E`. On the other hand (especially when duals arise), it is common to complement a set `X ⊆ M.E` *within* the ground set, giving `M.E \ X`. For this reason, we use the term `compl` in theorem names to refer to taking a set difference with respect to the ground set, rather than a complement within a type. The lemma `compl_isBase_dual` is one of the many examples of this. Finally, in theorem names, matroid predicates that apply to sets (such as `Base`, `Indep`, `IsBasis`) are typically used as suffixes rather than prefixes. For instance, we have `ground_indep_iff_isBase` rather than `indep_ground_iff_isBase`. ## References * [J. Oxley, Matroid Theory][oxley2011] * [H. Bruhn, R. Diestel, M. Kriesell, R. Pendavingh, P. Wollan, Axioms for infinite matroids, Adv. Math 239 (2013), 18-46][bruhnDiestelKriesselPendavinghWollan2013] * [N. Bowler, S. Geschke, Self-dual uniform matroids on infinite sets, Proc. Amer. Math. Soc. 144 (2016), 459-471][bowlerGeschke2015] -/ assert_not_exists Field open Set /-- A predicate `P` on sets satisfies the **exchange property** if, for all `X` and `Y` satisfying `P` and all `a ∈ X \ Y`, there exists `b ∈ Y \ X` so that swapping `a` for `b` in `X` maintains `P`. -/ def Matroid.ExchangeProperty {α : Type*} (P : Set α → Prop) : Prop := ∀ X Y, P X → P Y → ∀ a ∈ X \ Y, ∃ b ∈ Y \ X, P (insert b (X \ {a})) /-- A set `X` has the maximal subset property for a predicate `P` if every subset of `X` satisfying `P` is contained in a maximal subset of `X` satisfying `P`. -/ def Matroid.ExistsMaximalSubsetProperty {α : Type*} (P : Set α → Prop) (X : Set α) : Prop := ∀ I, P I → I ⊆ X → ∃ J, I ⊆ J ∧ Maximal (fun K ↦ P K ∧ K ⊆ X) J /-- A `Matroid α` is a ground set `E` of type `Set α`, and a nonempty collection of its subsets satisfying the exchange property and the maximal subset property. Each such set is called a `Base` of `M`. An `Indep`endent set is just a set contained in a base, but we include this predicate as a structure field for better definitional properties. In most cases, using this definition directly is not the best way to construct a matroid, since it requires specifying both the bases and independent sets. If the bases are known, use `Matroid.ofBase` or a variant. If just the independent sets are known, define an `IndepMatroid`, and then use `IndepMatroid.matroid`. -/ structure Matroid (α : Type*) where /-- `M` has a ground set `E`. -/ (E : Set α) /-- `M` has a predicate `Base` defining its bases. -/ (IsBase : Set α → Prop) /-- `M` has a predicate `Indep` defining its independent sets. -/ (Indep : Set α → Prop) /-- The `Indep`endent sets are those contained in `Base`s. -/ (indep_iff' : ∀ ⦃I⦄, Indep I ↔ ∃ B, IsBase B ∧ I ⊆ B) /-- There is at least one `Base`. -/ (exists_isBase : ∃ B, IsBase B) /-- For any bases `B`, `B'` and `e ∈ B \ B'`, there is some `f ∈ B' \ B` for which `B-e+f` is a base. -/ (isBase_exchange : Matroid.ExchangeProperty IsBase) /-- Every independent subset `I` of a set `X` for is contained in a maximal independent subset of `X`. -/ (maximality : ∀ X, X ⊆ E → Matroid.ExistsMaximalSubsetProperty Indep X) /-- Every base is contained in the ground set. -/ (subset_ground : ∀ B, IsBase B → B ⊆ E) attribute [local ext] Matroid namespace Matroid variable {α : Type*} {M : Matroid α} @[deprecated (since := "2025-02-14")] alias Base := IsBase instance (M : Matroid α) : Nonempty {B // M.IsBase B} := nonempty_subtype.2 M.exists_isBase /-- Typeclass for a matroid having finite ground set. Just a wrapper for `M.E.Finite`. -/ @[mk_iff] protected class Finite (M : Matroid α) : Prop where /-- The ground set is finite -/ (ground_finite : M.E.Finite) /-- Typeclass for a matroid having nonempty ground set. Just a wrapper for `M.E.Nonempty`. -/ protected class Nonempty (M : Matroid α) : Prop where /-- The ground set is nonempty -/ (ground_nonempty : M.E.Nonempty) theorem ground_nonempty (M : Matroid α) [M.Nonempty] : M.E.Nonempty := Nonempty.ground_nonempty theorem ground_nonempty_iff (M : Matroid α) : M.E.Nonempty ↔ M.Nonempty := ⟨fun h ↦ ⟨h⟩, fun ⟨h⟩ ↦ h⟩ lemma nonempty_type (M : Matroid α) [h : M.Nonempty] : Nonempty α := ⟨M.ground_nonempty.some⟩ theorem ground_finite (M : Matroid α) [M.Finite] : M.E.Finite := Finite.ground_finite theorem set_finite (M : Matroid α) [M.Finite] (X : Set α) (hX : X ⊆ M.E := by aesop) : X.Finite := M.ground_finite.subset hX instance finite_of_finite [Finite α] {M : Matroid α} : M.Finite := ⟨Set.toFinite _⟩ /-- A `RankFinite` matroid is one whose bases are finite -/ @[mk_iff] class RankFinite (M : Matroid α) : Prop where /-- There is a finite base -/ exists_finite_isBase : ∃ B, M.IsBase B ∧ B.Finite @[deprecated (since := "2025-02-09")] alias FiniteRk := RankFinite instance rankFinite_of_finite (M : Matroid α) [M.Finite] : RankFinite M := ⟨M.exists_isBase.imp (fun B hB ↦ ⟨hB, M.set_finite B (M.subset_ground _ hB)⟩)⟩ /-- An `RankInfinite` matroid is one whose bases are infinite. -/ @[mk_iff] class RankInfinite (M : Matroid α) : Prop where /-- There is an infinite base -/ exists_infinite_isBase : ∃ B, M.IsBase B ∧ B.Infinite @[deprecated (since := "2025-02-09")] alias InfiniteRk := RankInfinite /-- A `RankPos` matroid is one whose bases are nonempty. -/ @[mk_iff] class RankPos (M : Matroid α) : Prop where /-- The empty set isn't a base -/ empty_not_isBase : ¬M.IsBase ∅ @[deprecated (since := "2025-02-09")] alias RkPos := RankPos instance rankPos_nonempty {M : Matroid α} [M.RankPos] : M.Nonempty := by obtain ⟨B, hB⟩ := M.exists_isBase obtain rfl | ⟨e, heB⟩ := B.eq_empty_or_nonempty · exact False.elim <| RankPos.empty_not_isBase hB exact ⟨e, M.subset_ground B hB heB ⟩ @[deprecated (since := "2025-01-20")] alias rkPos_iff_empty_not_base := rankPos_iff section exchange namespace ExchangeProperty variable {IsBase : Set α → Prop} {B B' : Set α} /-- A family of sets with the exchange property is an antichain. -/ theorem antichain (exch : ExchangeProperty IsBase) (hB : IsBase B) (hB' : IsBase B') (h : B ⊆ B') : B = B' := h.antisymm (fun x hx ↦ by_contra (fun hxB ↦ let ⟨_, hy, _⟩ := exch B' B hB' hB x ⟨hx, hxB⟩; hy.2 <| h hy.1)) theorem encard_diff_le_aux {B₁ B₂ : Set α} (exch : ExchangeProperty IsBase) (hB₁ : IsBase B₁) (hB₂ : IsBase B₂) : (B₁ \ B₂).encard ≤ (B₂ \ B₁).encard := by obtain (he | hinf | ⟨e, he, hcard⟩) := (B₂ \ B₁).eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt · rw [exch.antichain hB₂ hB₁ (diff_eq_empty.mp he)] · exact le_top.trans_eq hinf.symm obtain ⟨f, hf, hB'⟩ := exch B₂ B₁ hB₂ hB₁ e he have : encard (insert f (B₂ \ {e}) \ B₁) < encard (B₂ \ B₁) := by rw [insert_diff_of_mem _ hf.1, diff_diff_comm]; exact hcard have hencard := encard_diff_le_aux exch hB₁ hB' rw [insert_diff_of_mem _ hf.1, diff_diff_comm, ← union_singleton, ← diff_diff, diff_diff_right, inter_singleton_eq_empty.mpr he.2, union_empty] at hencard rw [← encard_diff_singleton_add_one he, ← encard_diff_singleton_add_one hf] exact add_le_add_right hencard 1 termination_by (B₂ \ B₁).encard variable {B₁ B₂ : Set α} /-- For any two sets `B₁`, `B₂` in a family with the exchange property, the differences `B₁ \ B₂` and `B₂ \ B₁` have the same `ℕ∞`-cardinality. -/ theorem encard_diff_eq (exch : ExchangeProperty IsBase) (hB₁ : IsBase B₁) (hB₂ : IsBase B₂) : (B₁ \ B₂).encard = (B₂ \ B₁).encard := (encard_diff_le_aux exch hB₁ hB₂).antisymm (encard_diff_le_aux exch hB₂ hB₁) /-- Any two sets `B₁`, `B₂` in a family with the exchange property have the same `ℕ∞`-cardinality. -/ theorem encard_isBase_eq (exch : ExchangeProperty IsBase) (hB₁ : IsBase B₁) (hB₂ : IsBase B₂) : B₁.encard = B₂.encard := by rw [← encard_diff_add_encard_inter B₁ B₂, exch.encard_diff_eq hB₁ hB₂, inter_comm, encard_diff_add_encard_inter] end ExchangeProperty end exchange section aesop /-- The `aesop_mat` tactic attempts to prove a set is contained in the ground set of a matroid. It uses a `[Matroid]` ruleset, and is allowed to fail. -/ macro (name := aesop_mat) "aesop_mat" c:Aesop.tactic_clause* : tactic => `(tactic| aesop $c* (config := { terminal := true }) (rule_sets := [$(Lean.mkIdent `Matroid):ident])) /- We add a number of trivial lemmas (deliberately specialized to statements in terms of the ground set of a matroid) to the ruleset `Matroid` for `aesop`. -/ variable {X Y : Set α} {e : α} @[aesop unsafe 5% (rule_sets := [Matroid])] private theorem inter_right_subset_ground (hX : X ⊆ M.E) : X ∩ Y ⊆ M.E := inter_subset_left.trans hX @[aesop unsafe 5% (rule_sets := [Matroid])] private theorem inter_left_subset_ground (hX : X ⊆ M.E) : Y ∩ X ⊆ M.E := inter_subset_right.trans hX @[aesop unsafe 5% (rule_sets := [Matroid])] private theorem diff_subset_ground (hX : X ⊆ M.E) : X \ Y ⊆ M.E := diff_subset.trans hX @[aesop unsafe 10% (rule_sets := [Matroid])] private theorem ground_diff_subset_ground : M.E \ X ⊆ M.E := diff_subset_ground rfl.subset @[aesop unsafe 10% (rule_sets := [Matroid])] private theorem singleton_subset_ground (he : e ∈ M.E) : {e} ⊆ M.E := singleton_subset_iff.mpr he @[aesop unsafe 5% (rule_sets := [Matroid])] private theorem subset_ground_of_subset (hXY : X ⊆ Y) (hY : Y ⊆ M.E) : X ⊆ M.E := hXY.trans hY @[aesop unsafe 5% (rule_sets := [Matroid])] private theorem mem_ground_of_mem_of_subset (hX : X ⊆ M.E) (heX : e ∈ X) : e ∈ M.E := hX heX @[aesop safe (rule_sets := [Matroid])] private theorem insert_subset_ground {e : α} {X : Set α} {M : Matroid α} (he : e ∈ M.E) (hX : X ⊆ M.E) : insert e X ⊆ M.E := insert_subset he hX @[aesop safe (rule_sets := [Matroid])] private theorem ground_subset_ground {M : Matroid α} : M.E ⊆ M.E := rfl.subset attribute [aesop safe (rule_sets := [Matroid])] empty_subset union_subset iUnion_subset end aesop section IsBase variable {B B₁ B₂ : Set α} @[aesop unsafe 10% (rule_sets := [Matroid])] theorem IsBase.subset_ground (hB : M.IsBase B) : B ⊆ M.E := M.subset_ground B hB theorem IsBase.exchange {e : α} (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) (hx : e ∈ B₁ \ B₂) : ∃ y ∈ B₂ \ B₁, M.IsBase (insert y (B₁ \ {e})) := M.isBase_exchange B₁ B₂ hB₁ hB₂ _ hx theorem IsBase.exchange_mem {e : α} (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) (hxB₁ : e ∈ B₁) (hxB₂ : e ∉ B₂) : ∃ y, (y ∈ B₂ ∧ y ∉ B₁) ∧ M.IsBase (insert y (B₁ \ {e})) := by simpa using hB₁.exchange hB₂ ⟨hxB₁, hxB₂⟩ theorem IsBase.eq_of_subset_isBase (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) (hB₁B₂ : B₁ ⊆ B₂) : B₁ = B₂ := M.isBase_exchange.antichain hB₁ hB₂ hB₁B₂ theorem IsBase.not_isBase_of_ssubset {X : Set α} (hB : M.IsBase B) (hX : X ⊂ B) : ¬ M.IsBase X := fun h ↦ hX.ne (h.eq_of_subset_isBase hB hX.subset) theorem IsBase.insert_not_isBase {e : α} (hB : M.IsBase B) (heB : e ∉ B) : ¬ M.IsBase (insert e B) := fun h ↦ h.not_isBase_of_ssubset (ssubset_insert heB) hB theorem IsBase.encard_diff_comm (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) : (B₁ \ B₂).encard = (B₂ \ B₁).encard := M.isBase_exchange.encard_diff_eq hB₁ hB₂ theorem IsBase.ncard_diff_comm (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) : (B₁ \ B₂).ncard = (B₂ \ B₁).ncard := by rw [ncard_def, hB₁.encard_diff_comm hB₂, ← ncard_def] theorem IsBase.encard_eq_encard_of_isBase (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) : B₁.encard = B₂.encard := by rw [M.isBase_exchange.encard_isBase_eq hB₁ hB₂] theorem IsBase.ncard_eq_ncard_of_isBase (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) : B₁.ncard = B₂.ncard := by rw [ncard_def B₁, hB₁.encard_eq_encard_of_isBase hB₂, ← ncard_def] theorem IsBase.finite_of_finite {B' : Set α} (hB : M.IsBase B) (h : B.Finite) (hB' : M.IsBase B') : B'.Finite := (finite_iff_finite_of_encard_eq_encard (hB.encard_eq_encard_of_isBase hB')).mp h theorem IsBase.infinite_of_infinite (hB : M.IsBase B) (h : B.Infinite) (hB₁ : M.IsBase B₁) : B₁.Infinite := by_contra (fun hB_inf ↦ (hB₁.finite_of_finite (not_infinite.mp hB_inf) hB).not_infinite h) theorem IsBase.finite [RankFinite M] (hB : M.IsBase B) : B.Finite := let ⟨_,hB₀⟩ := ‹RankFinite M›.exists_finite_isBase hB₀.1.finite_of_finite hB₀.2 hB theorem IsBase.infinite [RankInfinite M] (hB : M.IsBase B) : B.Infinite := let ⟨_,hB₀⟩ := ‹RankInfinite M›.exists_infinite_isBase hB₀.1.infinite_of_infinite hB₀.2 hB theorem empty_not_isBase [h : RankPos M] : ¬M.IsBase ∅ := h.empty_not_isBase theorem IsBase.nonempty [RankPos M] (hB : M.IsBase B) : B.Nonempty := by rw [nonempty_iff_ne_empty]; rintro rfl; exact M.empty_not_isBase hB theorem IsBase.rankPos_of_nonempty (hB : M.IsBase B) (h : B.Nonempty) : M.RankPos := by rw [rankPos_iff] intro he obtain rfl := he.eq_of_subset_isBase hB (empty_subset B) simp at h theorem IsBase.rankFinite_of_finite (hB : M.IsBase B) (hfin : B.Finite) : RankFinite M := ⟨⟨B, hB, hfin⟩⟩ theorem IsBase.rankInfinite_of_infinite (hB : M.IsBase B) (h : B.Infinite) : RankInfinite M := ⟨⟨B, hB, h⟩⟩ theorem not_rankFinite (M : Matroid α) [RankInfinite M] : ¬ RankFinite M := by intro h; obtain ⟨B,hB⟩ := M.exists_isBase; exact hB.infinite hB.finite theorem not_rankInfinite (M : Matroid α) [RankFinite M] : ¬ RankInfinite M := by intro h; obtain ⟨B,hB⟩ := M.exists_isBase; exact hB.infinite hB.finite theorem rankFinite_or_rankInfinite (M : Matroid α) : RankFinite M ∨ RankInfinite M := let ⟨B, hB⟩ := M.exists_isBase B.finite_or_infinite.imp hB.rankFinite_of_finite hB.rankInfinite_of_infinite @[deprecated (since := "2025-03-27")] alias finite_or_rankInfinite := rankFinite_or_rankInfinite @[simp] theorem not_rankFinite_iff (M : Matroid α) : ¬ RankFinite M ↔ RankInfinite M := M.rankFinite_or_rankInfinite.elim (fun h ↦ iff_of_false (by simpa) M.not_rankInfinite) fun h ↦ iff_of_true M.not_rankFinite h @[simp] theorem not_rankInfinite_iff (M : Matroid α) : ¬ RankInfinite M ↔ RankFinite M := by rw [← not_rankFinite_iff, not_not] theorem IsBase.diff_finite_comm (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) : (B₁ \ B₂).Finite ↔ (B₂ \ B₁).Finite := finite_iff_finite_of_encard_eq_encard (hB₁.encard_diff_comm hB₂) theorem IsBase.diff_infinite_comm (hB₁ : M.IsBase B₁) (hB₂ : M.IsBase B₂) : (B₁ \ B₂).Infinite ↔ (B₂ \ B₁).Infinite := infinite_iff_infinite_of_encard_eq_encard (hB₁.encard_diff_comm hB₂) theorem ext_isBase {M₁ M₂ : Matroid α} (hE : M₁.E = M₂.E) (h : ∀ ⦃B⦄, B ⊆ M₁.E → (M₁.IsBase B ↔ M₂.IsBase B)) : M₁ = M₂ := by have h' : ∀ B, M₁.IsBase B ↔ M₂.IsBase B := fun B ↦ ⟨fun hB ↦ (h hB.subset_ground).1 hB, fun hB ↦ (h <| hB.subset_ground.trans_eq hE.symm).2 hB⟩ ext <;> simp [hE, M₁.indep_iff', M₂.indep_iff', h'] @[deprecated (since := "2024-12-25")] alias eq_of_isBase_iff_isBase_forall := ext_isBase theorem ext_iff_isBase {M₁ M₂ : Matroid α} : M₁ = M₂ ↔ M₁.E = M₂.E ∧ ∀ ⦃B⦄, B ⊆ M₁.E → (M₁.IsBase B ↔ M₂.IsBase B) := ⟨fun h ↦ by simp [h], fun ⟨hE, h⟩ ↦ ext_isBase hE h⟩ theorem isBase_compl_iff_maximal_disjoint_isBase (hB : B ⊆ M.E := by aesop_mat) : M.IsBase (M.E \ B) ↔ Maximal (fun I ↦ I ⊆ M.E ∧ ∃ B, M.IsBase B ∧ Disjoint I B) B := by simp_rw [maximal_iff, and_iff_right hB, and_imp, forall_exists_index] refine ⟨fun h ↦ ⟨⟨_, h, disjoint_sdiff_right⟩, fun I hI B' ⟨hB', hIB'⟩ hBI ↦ hBI.antisymm ?_⟩, fun ⟨⟨B', hB', hBB'⟩,h⟩ ↦ ?_⟩ · rw [hB'.eq_of_subset_isBase h, ← subset_compl_iff_disjoint_right, diff_eq, compl_inter, compl_compl] at hIB' · exact fun e he ↦ (hIB' he).elim (fun h' ↦ (h' (hI he)).elim) id rw [subset_diff, and_iff_right hB'.subset_ground, disjoint_comm] exact disjoint_of_subset_left hBI hIB' rw [h diff_subset B' ⟨hB', disjoint_sdiff_left⟩] · simpa [hB'.subset_ground] simp [subset_diff, hB, hBB'] end IsBase section dep_indep /-- A subset of `M.E` is `Dep`endent if it is not `Indep`endent . -/ def Dep (M : Matroid α) (D : Set α) : Prop := ¬M.Indep D ∧ D ⊆ M.E variable {B B' I J D X : Set α} {e f : α} theorem indep_iff : M.Indep I ↔ ∃ B, M.IsBase B ∧ I ⊆ B := M.indep_iff' (I := I) theorem setOf_indep_eq (M : Matroid α) : {I | M.Indep I} = lowerClosure ({B | M.IsBase B}) := by simp_rw [indep_iff, lowerClosure, LowerSet.coe_mk, mem_setOf, le_eq_subset] theorem Indep.exists_isBase_superset (hI : M.Indep I) : ∃ B, M.IsBase B ∧ I ⊆ B := indep_iff.1 hI theorem dep_iff : M.Dep D ↔ ¬M.Indep D ∧ D ⊆ M.E := Iff.rfl theorem setOf_dep_eq (M : Matroid α) : {D | M.Dep D} = {I | M.Indep I}ᶜ ∩ Iic M.E := rfl @[aesop unsafe 30% (rule_sets := [Matroid])] theorem Indep.subset_ground (hI : M.Indep I) : I ⊆ M.E := by obtain ⟨B, hB, hIB⟩ := hI.exists_isBase_superset exact hIB.trans hB.subset_ground @[aesop unsafe 20% (rule_sets := [Matroid])] theorem Dep.subset_ground (hD : M.Dep D) : D ⊆ M.E := hD.2 theorem indep_or_dep (hX : X ⊆ M.E := by aesop_mat) : M.Indep X ∨ M.Dep X := by rw [Dep, and_iff_left hX] apply em theorem Indep.not_dep (hI : M.Indep I) : ¬ M.Dep I := fun h ↦ h.1 hI theorem Dep.not_indep (hD : M.Dep D) : ¬ M.Indep D := hD.1 theorem dep_of_not_indep (hD : ¬ M.Indep D) (hDE : D ⊆ M.E := by aesop_mat) : M.Dep D := ⟨hD, hDE⟩ theorem indep_of_not_dep (hI : ¬ M.Dep I) (hIE : I ⊆ M.E := by aesop_mat) : M.Indep I := by_contra (fun h ↦ hI ⟨h, hIE⟩) @[simp] theorem not_dep_iff (hX : X ⊆ M.E := by aesop_mat) : ¬ M.Dep X ↔ M.Indep X := by rw [Dep, and_iff_left hX, not_not] @[simp] theorem not_indep_iff (hX : X ⊆ M.E := by aesop_mat) : ¬ M.Indep X ↔ M.Dep X := by rw [Dep, and_iff_left hX] theorem indep_iff_not_dep : M.Indep I ↔ ¬M.Dep I ∧ I ⊆ M.E := by rw [dep_iff, not_and, not_imp_not] exact ⟨fun h ↦ ⟨fun _ ↦ h, h.subset_ground⟩, fun h ↦ h.1 h.2⟩ theorem Indep.subset (hJ : M.Indep J) (hIJ : I ⊆ J) : M.Indep I := by obtain ⟨B, hB, hJB⟩ := hJ.exists_isBase_superset exact indep_iff.2 ⟨B, hB, hIJ.trans hJB⟩ theorem Dep.superset (hD : M.Dep D) (hDX : D ⊆ X) (hXE : X ⊆ M.E := by aesop_mat) : M.Dep X := dep_of_not_indep (fun hI ↦ (hI.subset hDX).not_dep hD) theorem IsBase.indep (hB : M.IsBase B) : M.Indep B := indep_iff.2 ⟨B, hB, subset_rfl⟩ @[simp] theorem empty_indep (M : Matroid α) : M.Indep ∅ := Exists.elim M.exists_isBase (fun _ hB ↦ hB.indep.subset (empty_subset _)) theorem Dep.nonempty (hD : M.Dep D) : D.Nonempty := by rw [nonempty_iff_ne_empty]; rintro rfl; exact hD.not_indep M.empty_indep theorem Indep.finite [RankFinite M] (hI : M.Indep I) : I.Finite := let ⟨_, hB, hIB⟩ := hI.exists_isBase_superset hB.finite.subset hIB theorem Indep.rankPos_of_nonempty (hI : M.Indep I) (hne : I.Nonempty) : M.RankPos := by obtain ⟨B, hB, hIB⟩ := hI.exists_isBase_superset exact hB.rankPos_of_nonempty (hne.mono hIB) theorem Indep.inter_right (hI : M.Indep I) (X : Set α) : M.Indep (I ∩ X) := hI.subset inter_subset_left theorem Indep.inter_left (hI : M.Indep I) (X : Set α) : M.Indep (X ∩ I) := hI.subset inter_subset_right theorem Indep.diff (hI : M.Indep I) (X : Set α) : M.Indep (I \ X) := hI.subset diff_subset theorem IsBase.eq_of_subset_indep (hB : M.IsBase B) (hI : M.Indep I) (hBI : B ⊆ I) : B = I := let ⟨B', hB', hB'I⟩ := hI.exists_isBase_superset hBI.antisymm (by rwa [hB.eq_of_subset_isBase hB' (hBI.trans hB'I)]) theorem isBase_iff_maximal_indep : M.IsBase B ↔ Maximal M.Indep B := by rw [maximal_subset_iff] refine ⟨fun h ↦ ⟨h.indep, fun _ ↦ h.eq_of_subset_indep⟩, fun ⟨h, h'⟩ ↦ ?_⟩ obtain ⟨B', hB', hBB'⟩ := h.exists_isBase_superset rwa [h' hB'.indep hBB'] theorem Indep.isBase_of_maximal (hI : M.Indep I) (h : ∀ ⦃J⦄, M.Indep J → I ⊆ J → I = J) : M.IsBase I := by rwa [isBase_iff_maximal_indep, maximal_subset_iff, and_iff_right hI] theorem IsBase.dep_of_ssubset (hB : M.IsBase B) (h : B ⊂ X) (hX : X ⊆ M.E := by aesop_mat) : M.Dep X := ⟨fun hX ↦ h.ne (hB.eq_of_subset_indep hX h.subset), hX⟩ theorem IsBase.dep_of_insert (hB : M.IsBase B) (heB : e ∉ B) (he : e ∈ M.E := by aesop_mat) : M.Dep (insert e B) := hB.dep_of_ssubset (ssubset_insert heB) (insert_subset he hB.subset_ground) theorem IsBase.mem_of_insert_indep (hB : M.IsBase B) (heB : M.Indep (insert e B)) : e ∈ B := by_contra fun he ↦ (hB.dep_of_insert he (heB.subset_ground (mem_insert _ _))).not_indep heB /-- If the difference of two IsBases is a singleton, then they differ by an insertion/removal -/ theorem IsBase.eq_exchange_of_diff_eq_singleton (hB : M.IsBase B) (hB' : M.IsBase B') (h : B \ B' = {e}) : ∃ f ∈ B' \ B, B' = (insert f B) \ {e} := by obtain ⟨f, hf, hb⟩ := hB.exchange hB' (h.symm.subset (mem_singleton e)) have hne : f ≠ e := by rintro rfl; exact hf.2 (h.symm.subset (mem_singleton f)).1 rw [insert_diff_singleton_comm hne] at hb refine ⟨f, hf, (hb.eq_of_subset_isBase hB' ?_).symm⟩ rw [diff_subset_iff, insert_subset_iff, union_comm, ← diff_subset_iff, h, and_iff_left rfl.subset] exact Or.inl hf.1 theorem IsBase.exchange_isBase_of_indep (hB : M.IsBase B) (hf : f ∉ B) (hI : M.Indep (insert f (B \ {e}))) : M.IsBase (insert f (B \ {e})) := by obtain ⟨B', hB', hIB'⟩ := hI.exists_isBase_superset have hcard := hB'.encard_diff_comm hB rw [insert_subset_iff, ← diff_eq_empty, diff_diff_comm, diff_eq_empty, subset_singleton_iff_eq] at hIB' obtain ⟨hfB, (h | h)⟩ := hIB' · rw [h, encard_empty, encard_eq_zero, eq_empty_iff_forall_not_mem] at hcard exact (hcard f ⟨hfB, hf⟩).elim rw [h, encard_singleton, encard_eq_one] at hcard obtain ⟨x, hx⟩ := hcard obtain (rfl : f = x) := hx.subset ⟨hfB, hf⟩ simp_rw [← h, ← singleton_union, ← hx, sdiff_sdiff_right_self, inf_eq_inter, inter_comm B, diff_union_inter] exact hB' theorem IsBase.exchange_isBase_of_indep' (hB : M.IsBase B) (he : e ∈ B) (hf : f ∉ B) (hI : M.Indep (insert f B \ {e})) : M.IsBase (insert f B \ {e}) := by have hfe : f ≠ e := ne_of_mem_of_not_mem he hf |>.symm rw [← insert_diff_singleton_comm hfe] at * exact hB.exchange_isBase_of_indep hf hI lemma insert_isBase_of_insert_indep {M : Matroid α} {I : Set α} {e f : α} (he : e ∉ I) (hf : f ∉ I) (heI : M.IsBase (insert e I)) (hfI : M.Indep (insert f I)) : M.IsBase (insert f I) := by obtain rfl | hef := eq_or_ne e f · assumption simpa [diff_singleton_eq_self he, hfI] using heI.exchange_isBase_of_indep (e := e) (f := f) (by simp [hef.symm, hf]) theorem IsBase.insert_dep (hB : M.IsBase B) (h : e ∈ M.E \ B) : M.Dep (insert e B) := by rw [← not_indep_iff (insert_subset h.1 hB.subset_ground)] exact h.2 ∘ (fun hi ↦ insert_eq_self.mp (hB.eq_of_subset_indep hi (subset_insert e B)).symm) theorem Indep.exists_insert_of_not_isBase (hI : M.Indep I) (hI' : ¬M.IsBase I) (hB : M.IsBase B) : ∃ e ∈ B \ I, M.Indep (insert e I) := by obtain ⟨B', hB', hIB'⟩ := hI.exists_isBase_superset obtain ⟨x, hxB', hx⟩ := exists_of_ssubset (hIB'.ssubset_of_ne (by (rintro rfl; exact hI' hB'))) by_cases hxB : x ∈ B · exact ⟨x, ⟨hxB, hx⟩, hB'.indep.subset (insert_subset hxB' hIB')⟩ obtain ⟨e,he, hBase⟩ := hB'.exchange hB ⟨hxB',hxB⟩ exact ⟨e, ⟨he.1, not_mem_subset hIB' he.2⟩, indep_iff.2 ⟨_, hBase, insert_subset_insert (subset_diff_singleton hIB' hx)⟩⟩ /-- This is the same as `Indep.exists_insert_of_not_isBase`, but phrased so that it is defeq to the augmentation axiom for independent sets. -/ theorem Indep.exists_insert_of_not_maximal (M : Matroid α) ⦃I B : Set α⦄ (hI : M.Indep I) (hInotmax : ¬ Maximal M.Indep I) (hB : Maximal M.Indep B) : ∃ x ∈ B \ I, M.Indep (insert x I) := by simp only [maximal_subset_iff, hI, not_and, not_forall, exists_prop, true_imp_iff] at hB hInotmax refine hI.exists_insert_of_not_isBase (fun hIb ↦ ?_) ?_ · obtain ⟨I', hII', hI', hne⟩ := hInotmax exact hne <| hIb.eq_of_subset_indep hII' hI' exact hB.1.isBase_of_maximal fun J hJ hBJ ↦ hB.2 hJ hBJ theorem Indep.isBase_of_forall_insert (hB : M.Indep B) (hBmax : ∀ e ∈ M.E \ B, ¬ M.Indep (insert e B)) : M.IsBase B := by refine by_contra fun hnb ↦ ?_ obtain ⟨B', hB'⟩ := M.exists_isBase obtain ⟨e, he, h⟩ := hB.exists_insert_of_not_isBase hnb hB' exact hBmax e ⟨hB'.subset_ground he.1, he.2⟩ h theorem ground_indep_iff_isBase : M.Indep M.E ↔ M.IsBase M.E := ⟨fun h ↦ h.isBase_of_maximal (fun _ hJ hEJ ↦ hEJ.antisymm hJ.subset_ground), IsBase.indep⟩ theorem IsBase.exists_insert_of_ssubset (hB : M.IsBase B) (hIB : I ⊂ B) (hB' : M.IsBase B') : ∃ e ∈ B' \ I, M.Indep (insert e I) := (hB.indep.subset hIB.subset).exists_insert_of_not_isBase (fun hI ↦ hIB.ne (hI.eq_of_subset_isBase hB hIB.subset)) hB' @[ext] theorem ext_indep {M₁ M₂ : Matroid α} (hE : M₁.E = M₂.E) (h : ∀ ⦃I⦄, I ⊆ M₁.E → (M₁.Indep I ↔ M₂.Indep I)) : M₁ = M₂ := have h' : M₁.Indep = M₂.Indep := by ext I by_cases hI : I ⊆ M₁.E · rwa [h] exact iff_of_false (fun hi ↦ hI hi.subset_ground) (fun hi ↦ hI (hi.subset_ground.trans_eq hE.symm)) ext_isBase hE (fun B _ ↦ by simp_rw [isBase_iff_maximal_indep, h']) @[deprecated (since := "2024-12-25")] alias eq_of_indep_iff_indep_forall := ext_indep
theorem ext_iff_indep {M₁ M₂ : Matroid α} : M₁ = M₂ ↔ (M₁.E = M₂.E) ∧ ∀ ⦃I⦄, I ⊆ M₁.E → (M₁.Indep I ↔ M₂.Indep I) := ⟨fun h ↦ by (subst h; simp), fun h ↦ ext_indep h.1 h.2⟩
Mathlib/Data/Matroid/Basic.lean
724
726
/- Copyright (c) 2022 Kevin H. Wilson. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kevin H. Wilson -/ import Mathlib.Analysis.Calculus.MeanValue import Mathlib.Analysis.NormedSpace.RCLike import Mathlib.Order.Filter.Curry /-! # Swapping limits and derivatives via uniform convergence The purpose of this file is to prove that the derivative of the pointwise limit of a sequence of functions is the pointwise limit of the functions' derivatives when the derivatives converge _uniformly_. The formal statement appears as `hasFDerivAt_of_tendstoLocallyUniformlyOn`. ## Main statements * `uniformCauchySeqOnFilter_of_fderiv`: If 1. `f : ℕ → E → G` is a sequence of functions which have derivatives `f' : ℕ → E → (E →L[𝕜] G)` on a neighborhood of `x`, 2. the functions `f` converge at `x`, and 3. the derivatives `f'` form a Cauchy sequence uniformly on a neighborhood of `x`, then the `f` form a Cauchy sequence _uniformly_ on a neighborhood of `x` * `hasFDerivAt_of_tendstoUniformlyOnFilter` : Suppose (1), (2), and (3) above are true. Let `g` (resp. `g'`) be the limiting function of the `f` (resp. `g'`). Then `f'` is the derivative of `g` on a neighborhood of `x` * `hasFDerivAt_of_tendstoUniformlyOn`: An often-easier-to-use version of the above theorem when *all* the derivatives exist and functions converge on a common open set and the derivatives converge uniformly there. Each of the above statements also has variations that support `deriv` instead of `fderiv`. ## Implementation notes Our technique for proving the main result is the famous "`ε / 3` proof." In words, you can find it explained, for instance, at [this StackExchange post](https://math.stackexchange.com/questions/214218/uniform-convergence-of-derivatives-tao-14-2-7). The subtlety is that we want to prove that the difference quotients of the `g` converge to the `g'`. That is, we want to prove something like: ``` ∀ ε > 0, ∃ δ > 0, ∀ y ∈ B_δ(x), |y - x|⁻¹ * |(g y - g x) - g' x (y - x)| < ε. ``` To do so, we will need to introduce a pair of quantifiers ```lean ∀ ε > 0, ∃ N, ∀ n ≥ N, ∃ δ > 0, ∀ y ∈ B_δ(x), |y - x|⁻¹ * |(g y - g x) - g' x (y - x)| < ε. ``` So how do we write this in terms of filters? Well, the initial definition of the derivative is ```lean tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (𝓝 x) (𝓝 0) ``` There are two ways we might introduce `n`. We could do: ```lean ∀ᶠ (n : ℕ) in atTop, Tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (𝓝 x) (𝓝 0) ``` but this is equivalent to the quantifier order `∃ N, ∀ n ≥ N, ∀ ε > 0, ∃ δ > 0, ∀ y ∈ B_δ(x)`, which _implies_ our desired `∀ ∃ ∀ ∃ ∀` but is _not_ equivalent to it. On the other hand, we might try ```lean Tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (atTop ×ˢ 𝓝 x) (𝓝 0) ``` but this is equivalent to the quantifier order `∀ ε > 0, ∃ N, ∃ δ > 0, ∀ n ≥ N, ∀ y ∈ B_δ(x)`, which again _implies_ our desired `∀ ∃ ∀ ∃ ∀` but is not equivalent to it. So to get the quantifier order we want, we need to introduce a new filter construction, which we call a "curried filter" ```lean Tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (atTop.curry (𝓝 x)) (𝓝 0) ``` Then the above implications are `Filter.Tendsto.curry` and `Filter.Tendsto.mono_left Filter.curry_le_prod`. We will use both of these deductions as part of our proof. We note that if you loosen the assumptions of the main theorem then the proof becomes quite a bit easier. In particular, if you assume there is a common neighborhood `s` where all of the three assumptions of `hasFDerivAt_of_tendstoUniformlyOnFilter` hold and that the `f'` are continuous, then you can avoid the mean value theorem and much of the work around curried filters. ## Tags uniform convergence, limits of derivatives -/ open Filter open scoped uniformity Filter Topology section LimitsOfDerivatives variable {ι : Type*} {l : Filter ι} {E : Type*} [NormedAddCommGroup E] {𝕜 : Type*} [NontriviallyNormedField 𝕜] [IsRCLikeNormedField 𝕜] [NormedSpace 𝕜 E] {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G] {f : ι → E → G} {g : E → G} {f' : ι → E → E →L[𝕜] G} {g' : E → E →L[𝕜] G} {x : E} /-- If a sequence of functions real or complex functions are eventually differentiable on a neighborhood of `x`, they are Cauchy _at_ `x`, and their derivatives are a uniform Cauchy sequence in a neighborhood of `x`, then the functions form a uniform Cauchy sequence in a neighborhood of `x`. -/ theorem uniformCauchySeqOnFilter_of_fderiv (hf' : UniformCauchySeqOnFilter f' l (𝓝 x)) (hf : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2) (hfg : Cauchy (map (fun n => f n x) l)) : UniformCauchySeqOnFilter f l (𝓝 x) := by letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜 letI : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 _ rw [SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero] at hf' ⊢ suffices TendstoUniformlyOnFilter (fun (n : ι × ι) (z : E) => f n.1 z - f n.2 z - (f n.1 x - f n.2 x)) 0 (l ×ˢ l) (𝓝 x) ∧ TendstoUniformlyOnFilter (fun (n : ι × ι) (_ : E) => f n.1 x - f n.2 x) 0 (l ×ˢ l) (𝓝 x) by have := this.1.add this.2 rw [add_zero] at this exact this.congr (by simp) constructor · -- This inequality follows from the mean value theorem. To apply it, we will need to shrink our -- neighborhood to small enough ball rw [Metric.tendstoUniformlyOnFilter_iff] at hf' ⊢ intro ε hε have := (tendsto_swap4_prod.eventually (hf.prod_mk hf)).diag_of_prod_right obtain ⟨a, b, c, d, e⟩ := eventually_prod_iff.1 ((hf' ε hε).and this) obtain ⟨R, hR, hR'⟩ := Metric.nhds_basis_ball.eventually_iff.mp d let r := min 1 R have hr : 0 < r := by simp [r, hR] have hr' : ∀ ⦃y : E⦄, y ∈ Metric.ball x r → c y := fun y hy => hR' (lt_of_lt_of_le (Metric.mem_ball.mp hy) (min_le_right _ _)) have hxy : ∀ y : E, y ∈ Metric.ball x r → ‖y - x‖ < 1 := by intro y hy rw [Metric.mem_ball, dist_eq_norm] at hy exact lt_of_lt_of_le hy (min_le_left _ _) have hxyε : ∀ y : E, y ∈ Metric.ball x r → ε * ‖y - x‖ < ε := by intro y hy exact (mul_lt_iff_lt_one_right hε.lt).mpr (hxy y hy) -- With a small ball in hand, apply the mean value theorem refine eventually_prod_iff.mpr ⟨_, b, fun e : E => Metric.ball x r e, eventually_mem_set.mpr (Metric.nhds_basis_ball.mem_of_mem hr), fun {n} hn {y} hy => ?_⟩ simp only [Pi.zero_apply, dist_zero_left] at e ⊢ refine lt_of_le_of_lt ?_ (hxyε y hy) exact Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le (fun y hy => ((e hn (hr' hy)).2.1.sub (e hn (hr' hy)).2.2).hasFDerivWithinAt) (fun y hy => (e hn (hr' hy)).1.le) (convex_ball x r) (Metric.mem_ball_self hr) hy · -- This is just `hfg` run through `eventually_prod_iff` refine Metric.tendstoUniformlyOnFilter_iff.mpr fun ε hε => ?_ obtain ⟨t, ht, ht'⟩ := (Metric.cauchy_iff.mp hfg).2 ε hε exact eventually_prod_iff.mpr ⟨fun n : ι × ι => f n.1 x ∈ t ∧ f n.2 x ∈ t, eventually_prod_iff.mpr ⟨_, ht, _, ht, fun {n} hn {n'} hn' => ⟨hn, hn'⟩⟩, fun _ => True, by simp, fun {n} hn {y} _ => by simpa [norm_sub_rev, dist_eq_norm] using ht' _ hn.1 _ hn.2⟩ /-- A variant of the second fundamental theorem of calculus (FTC-2): If a sequence of functions between real or complex normed spaces are differentiable on a ball centered at `x`, they form a Cauchy sequence _at_ `x`, and their derivatives are Cauchy uniformly on the ball, then the functions form a uniform Cauchy sequence on the ball. NOTE: The fact that we work on a ball is typically all that is necessary to work with power series and Dirichlet series (our primary use case). However, this can be generalized by replacing the ball with any connected, bounded, open set and replacing uniform convergence with local uniform convergence. See `cauchy_map_of_uniformCauchySeqOn_fderiv`. -/ theorem uniformCauchySeqOn_ball_of_fderiv {r : ℝ} (hf' : UniformCauchySeqOn f' l (Metric.ball x r)) (hf : ∀ n : ι, ∀ y : E, y ∈ Metric.ball x r → HasFDerivAt (f n) (f' n y) y) (hfg : Cauchy (map (fun n => f n x) l)) : UniformCauchySeqOn f l (Metric.ball x r) := by letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜 letI : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 _ have : NeBot l := (cauchy_map_iff.1 hfg).1 rcases le_or_lt r 0 with (hr | hr) · simp only [Metric.ball_eq_empty.2 hr, UniformCauchySeqOn, Set.mem_empty_iff_false, IsEmpty.forall_iff, eventually_const, imp_true_iff] rw [SeminormedAddGroup.uniformCauchySeqOn_iff_tendstoUniformlyOn_zero] at hf' ⊢ suffices TendstoUniformlyOn (fun (n : ι × ι) (z : E) => f n.1 z - f n.2 z - (f n.1 x - f n.2 x)) 0 (l ×ˢ l) (Metric.ball x r) ∧ TendstoUniformlyOn (fun (n : ι × ι) (_ : E) => f n.1 x - f n.2 x) 0 (l ×ˢ l) (Metric.ball x r) by have := this.1.add this.2 rw [add_zero] at this refine this.congr ?_ filter_upwards with n z _ using (by simp) constructor · -- This inequality follows from the mean value theorem rw [Metric.tendstoUniformlyOn_iff] at hf' ⊢ intro ε hε obtain ⟨q, hqpos, hq⟩ : ∃ q : ℝ, 0 < q ∧ q * r < ε := by simp_rw [mul_comm] exact exists_pos_mul_lt hε.lt r apply (hf' q hqpos.gt).mono intro n hn y hy simp_rw [dist_eq_norm, Pi.zero_apply, zero_sub, norm_neg] at hn ⊢ have mvt := Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le (fun z hz => ((hf n.1 z hz).sub (hf n.2 z hz)).hasFDerivWithinAt) (fun z hz => (hn z hz).le) (convex_ball x r) (Metric.mem_ball_self hr) hy refine lt_of_le_of_lt mvt ?_ have : q * ‖y - x‖ < q * r := mul_lt_mul' rfl.le (by simpa only [dist_eq_norm] using Metric.mem_ball.mp hy) (norm_nonneg _) hqpos exact this.trans hq · -- This is just `hfg` run through `eventually_prod_iff` refine Metric.tendstoUniformlyOn_iff.mpr fun ε hε => ?_ obtain ⟨t, ht, ht'⟩ := (Metric.cauchy_iff.mp hfg).2 ε hε rw [eventually_prod_iff] refine ⟨fun n => f n x ∈ t, ht, fun n => f n x ∈ t, ht, ?_⟩ intro n hn n' hn' z _ rw [dist_eq_norm, Pi.zero_apply, zero_sub, norm_neg, ← dist_eq_norm] exact ht' _ hn _ hn' /-- If a sequence of functions between real or complex normed spaces are differentiable on a preconnected open set, they form a Cauchy sequence _at_ `x`, and their derivatives are Cauchy uniformly on the set, then the functions form a Cauchy sequence at any point in the set. -/ theorem cauchy_map_of_uniformCauchySeqOn_fderiv {s : Set E} (hs : IsOpen s) (h's : IsPreconnected s) (hf' : UniformCauchySeqOn f' l s) (hf : ∀ n : ι, ∀ y : E, y ∈ s → HasFDerivAt (f n) (f' n y) y) {x₀ x : E} (hx₀ : x₀ ∈ s) (hx : x ∈ s) (hfg : Cauchy (map (fun n => f n x₀) l)) : Cauchy (map (fun n => f n x) l) := by have : NeBot l := (cauchy_map_iff.1 hfg).1 let t := { y | y ∈ s ∧ Cauchy (map (fun n => f n y) l) } suffices H : s ⊆ t from (H hx).2 have A : ∀ x ε, x ∈ t → Metric.ball x ε ⊆ s → Metric.ball x ε ⊆ t := fun x ε xt hx y hy => ⟨hx hy, (uniformCauchySeqOn_ball_of_fderiv (hf'.mono hx) (fun n y hy => hf n y (hx hy)) xt.2).cauchy_map hy⟩ have open_t : IsOpen t := by rw [Metric.isOpen_iff] intro x hx rcases Metric.isOpen_iff.1 hs x hx.1 with ⟨ε, εpos, hε⟩ exact ⟨ε, εpos, A x ε hx hε⟩ have st_nonempty : (s ∩ t).Nonempty := ⟨x₀, hx₀, ⟨hx₀, hfg⟩⟩ suffices H : closure t ∩ s ⊆ t from h's.subset_of_closure_inter_subset open_t st_nonempty H rintro x ⟨xt, xs⟩ obtain ⟨ε, εpos, hε⟩ : ∃ (ε : ℝ), ε > 0 ∧ Metric.ball x ε ⊆ s := Metric.isOpen_iff.1 hs x xs obtain ⟨y, yt, hxy⟩ : ∃ (y : E), y ∈ t ∧ dist x y < ε / 2 := Metric.mem_closure_iff.1 xt _ (half_pos εpos) have B : Metric.ball y (ε / 2) ⊆ Metric.ball x ε := by apply Metric.ball_subset_ball'; rw [dist_comm]; linarith exact A y (ε / 2) yt (B.trans hε) (Metric.mem_ball.2 hxy) /-- If `f_n → g` pointwise and the derivatives `(f_n)' → h` _uniformly_ converge, then in fact for a fixed `y`, the difference quotients `‖z - y‖⁻¹ • (f_n z - f_n y)` converge _uniformly_ to `‖z - y‖⁻¹ • (g z - g y)` -/ theorem difference_quotients_converge_uniformly {E : Type*} [NormedAddCommGroup E] {𝕜 : Type*} [RCLike 𝕜] [NormedSpace 𝕜 E] {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G] {f : ι → E → G} {g : E → G} {f' : ι → E → E →L[𝕜] G} {g' : E → E →L[𝕜] G} {x : E} (hf' : TendstoUniformlyOnFilter f' g' l (𝓝 x)) (hf : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2) (hfg : ∀ᶠ y : E in 𝓝 x, Tendsto (fun n => f n y) l (𝓝 (g y))) : TendstoUniformlyOnFilter (fun n : ι => fun y : E => (‖y - x‖⁻¹ : 𝕜) • (f n y - f n x)) (fun y : E => (‖y - x‖⁻¹ : 𝕜) • (g y - g x)) l (𝓝 x) := by let A : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 _ refine UniformCauchySeqOnFilter.tendstoUniformlyOnFilter_of_tendsto ?_ ((hfg.and (eventually_const.mpr hfg.self_of_nhds)).mono fun y hy => (hy.1.sub hy.2).const_smul _) rw [SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero] rw [Metric.tendstoUniformlyOnFilter_iff] have hfg' := hf'.uniformCauchySeqOnFilter rw [SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero] at hfg' rw [Metric.tendstoUniformlyOnFilter_iff] at hfg' intro ε hε obtain ⟨q, hqpos, hqε⟩ := exists_pos_rat_lt hε specialize hfg' (q : ℝ) (by simp [hqpos]) have := (tendsto_swap4_prod.eventually (hf.prod_mk hf)).diag_of_prod_right obtain ⟨a, b, c, d, e⟩ := eventually_prod_iff.1 (hfg'.and this) obtain ⟨r, hr, hr'⟩ := Metric.nhds_basis_ball.eventually_iff.mp d rw [eventually_prod_iff] refine ⟨_, b, fun e : E => Metric.ball x r e, eventually_mem_set.mpr (Metric.nhds_basis_ball.mem_of_mem hr), fun {n} hn {y} hy => ?_⟩ simp only [Pi.zero_apply, dist_zero_left] rw [← smul_sub, norm_smul, norm_inv, RCLike.norm_coe_norm] refine lt_of_le_of_lt ?_ hqε by_cases hyz' : x = y; · simp [hyz', hqpos.le] have hyz : 0 < ‖y - x‖ := by rw [norm_pos_iff]; intro hy'; exact hyz' (eq_of_sub_eq_zero hy').symm rw [inv_mul_le_iff₀ hyz, mul_comm, sub_sub_sub_comm] simp only [Pi.zero_apply, dist_zero_left] at e refine Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le (fun y hy => ((e hn (hr' hy)).2.1.sub (e hn (hr' hy)).2.2).hasFDerivWithinAt) (fun y hy => (e hn (hr' hy)).1.le) (convex_ball x r) (Metric.mem_ball_self hr) hy /-- `(d/dx) lim_{n → ∞} f n x = lim_{n → ∞} f' n x` when the `f' n` converge _uniformly_ to their limit at `x`. In words the assumptions mean the following: * `hf'`: The `f'` converge "uniformly at" `x` to `g'`. This does not mean that the `f' n` even converge away from `x`! * `hf`: For all `(y, n)` with `y` sufficiently close to `x` and `n` sufficiently large, `f' n` is the derivative of `f n` * `hfg`: The `f n` converge pointwise to `g` on a neighborhood of `x` -/ theorem hasFDerivAt_of_tendstoUniformlyOnFilter [NeBot l] (hf' : TendstoUniformlyOnFilter f' g' l (𝓝 x))
(hf : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2) (hfg : ∀ᶠ y in 𝓝 x, Tendsto (fun n => f n y) l (𝓝 (g y))) : HasFDerivAt g (g' x) x := by letI : RCLike 𝕜 := IsRCLikeNormedField.rclike 𝕜 -- The proof strategy follows several steps: -- 1. The quantifiers in the definition of the derivative are -- `∀ ε > 0, ∃δ > 0, ∀y ∈ B_δ(x)`. We will introduce a quantifier in the middle: -- `∀ ε > 0, ∃N, ∀n ≥ N, ∃δ > 0, ∀y ∈ B_δ(x)` which will allow us to introduce the `f(') n` -- 2. The order of the quantifiers `hfg` are opposite to what we need. We will be able to swap -- the quantifiers using the uniform convergence assumption rw [hasFDerivAt_iff_tendsto] -- Introduce extra quantifier via curried filters suffices Tendsto (fun y : ι × E => ‖y.2 - x‖⁻¹ * ‖g y.2 - g x - (g' x) (y.2 - x)‖) (l.curry (𝓝 x)) (𝓝 0) by rw [Metric.tendsto_nhds] at this ⊢ intro ε hε specialize this ε hε rw [eventually_curry_iff] at this simp only at this exact (eventually_const.mp this).mono (by simp only [imp_self, forall_const]) -- With the new quantifier in hand, we can perform the famous `ε/3` proof. Specifically, -- we will break up the limit (the difference functions minus the derivative go to 0) into 3: -- * The difference functions of the `f n` converge *uniformly* to the difference functions -- of the `g n` -- * The `f' n` are the derivatives of the `f n` -- * The `f' n` converge to `g'` at `x` conv => congr ext rw [← abs_norm, ← abs_inv, ← @RCLike.norm_ofReal 𝕜 _ _, RCLike.ofReal_inv, ← norm_smul] rw [← tendsto_zero_iff_norm_tendsto_zero] have : (fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (g a.2 - g x - (g' x) (a.2 - x))) = ((fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (g a.2 - g x - (f a.1 a.2 - f a.1 x))) + fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (f a.1 a.2 - f a.1 x - ((f' a.1 x) a.2 - (f' a.1 x) x))) + fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (f' a.1 x - g' x) (a.2 - x) := by ext; simp only [Pi.add_apply]; rw [← smul_add, ← smul_add]; congr simp only [map_sub, sub_add_sub_cancel, ContinuousLinearMap.coe_sub', Pi.sub_apply] abel simp_rw [this] have : 𝓝 (0 : G) = 𝓝 (0 + 0 + 0) := by simp only [add_zero] rw [this] refine Tendsto.add (Tendsto.add ?_ ?_) ?_ · have := difference_quotients_converge_uniformly hf' hf hfg rw [Metric.tendstoUniformlyOnFilter_iff] at this rw [Metric.tendsto_nhds] intro ε hε apply ((this ε hε).filter_mono curry_le_prod).mono intro n hn rw [dist_eq_norm] at hn ⊢ convert hn using 2 module · -- (Almost) the definition of the derivatives rw [Metric.tendsto_nhds] intro ε hε rw [eventually_curry_iff] refine hf.curry.mono fun n hn => ?_ have := hn.self_of_nhds rw [hasFDerivAt_iff_tendsto, Metric.tendsto_nhds] at this refine (this ε hε).mono fun y hy => ?_ rw [dist_eq_norm] at hy ⊢ simp only [sub_zero, map_sub, norm_mul, norm_inv, norm_norm] at hy ⊢ rw [norm_smul, norm_inv, RCLike.norm_coe_norm] exact hy · -- hfg' after specializing to `x` and applying the definition of the operator norm refine Tendsto.mono_left ?_ curry_le_prod have h1 : Tendsto (fun n : ι × E => g' n.2 - f' n.1 n.2) (l ×ˢ 𝓝 x) (𝓝 0) := by rw [Metric.tendstoUniformlyOnFilter_iff] at hf' exact Metric.tendsto_nhds.mpr fun ε hε => by simpa using hf' ε hε have h2 : Tendsto (fun n : ι => g' x - f' n x) l (𝓝 0) := by rw [Metric.tendsto_nhds] at h1 ⊢ exact fun ε hε => (h1 ε hε).curry.mono fun n hn => hn.self_of_nhds refine squeeze_zero_norm ?_ (tendsto_zero_iff_norm_tendsto_zero.mp (tendsto_fst.comp (h2.prodMap tendsto_id))) intro n simp_rw [norm_smul, norm_inv, RCLike.norm_coe_norm] by_cases hx : x = n.2; · simp [hx] have hnx : 0 < ‖n.2 - x‖ := by rw [norm_pos_iff]; intro hx'; exact hx (eq_of_sub_eq_zero hx').symm rw [inv_mul_le_iff₀ hnx, mul_comm] simp only [Function.comp_apply, Prod.map_apply'] rw [norm_sub_rev] exact (f' n.1 x - g' x).le_opNorm (n.2 - x) theorem hasFDerivAt_of_tendstoLocallyUniformlyOn [NeBot l] {s : Set E} (hs : IsOpen s)
Mathlib/Analysis/Calculus/UniformLimitsDeriv.lean
307
392
/- Copyright (c) 2022 Johannes Hölzl. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Patrick Massot, Yury Kudryashov, Kevin H. Wilson, Heather Macbeth -/ import Mathlib.Order.Filter.Tendsto /-! # Product and coproduct filters In this file we define `Filter.prod f g` (notation: `f ×ˢ g`) and `Filter.coprod f g`. The product of two filters is the largest filter `l` such that `Filter.Tendsto Prod.fst l f` and `Filter.Tendsto Prod.snd l g`. ## Implementation details The product filter cannot be defined using the monad structure on filters. For example: ```lean F := do {x ← seq, y ← top, return (x, y)} G := do {y ← top, x ← seq, return (x, y)} ``` hence: ```lean s ∈ F ↔ ∃ n, [n..∞] × univ ⊆ s s ∈ G ↔ ∀ i:ℕ, ∃ n, [n..∞] × {i} ⊆ s ``` Now `⋃ i, [i..∞] × {i}` is in `G` but not in `F`. As product filter we want to have `F` as result. ## Notations * `f ×ˢ g` : `Filter.prod f g`, localized in `Filter`. -/ open Set open Filter namespace Filter variable {α β γ δ : Type*} {ι : Sort*} section Prod variable {s : Set α} {t : Set β} {f : Filter α} {g : Filter β} theorem prod_mem_prod (hs : s ∈ f) (ht : t ∈ g) : s ×ˢ t ∈ f ×ˢ g := inter_mem_inf (preimage_mem_comap hs) (preimage_mem_comap ht) theorem mem_prod_iff {s : Set (α × β)} {f : Filter α} {g : Filter β} : s ∈ f ×ˢ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ×ˢ t₂ ⊆ s := by constructor · rintro ⟨t₁, ⟨s₁, hs₁, hts₁⟩, t₂, ⟨s₂, hs₂, hts₂⟩, rfl⟩ exact ⟨s₁, hs₁, s₂, hs₂, fun p ⟨h, h'⟩ => ⟨hts₁ h, hts₂ h'⟩⟩ · rintro ⟨t₁, ht₁, t₂, ht₂, h⟩ exact mem_inf_of_inter (preimage_mem_comap ht₁) (preimage_mem_comap ht₂) h @[simp] theorem compl_diagonal_mem_prod {l₁ l₂ : Filter α} : (diagonal α)ᶜ ∈ l₁ ×ˢ l₂ ↔ Disjoint l₁ l₂ := by simp only [mem_prod_iff, Filter.disjoint_iff, prod_subset_compl_diagonal_iff_disjoint] @[simp] theorem prod_mem_prod_iff [f.NeBot] [g.NeBot] : s ×ˢ t ∈ f ×ˢ g ↔ s ∈ f ∧ t ∈ g := ⟨fun h => let ⟨_s', hs', _t', ht', H⟩ := mem_prod_iff.1 h (prod_subset_prod_iff.1 H).elim (fun ⟨hs's, ht't⟩ => ⟨mem_of_superset hs' hs's, mem_of_superset ht' ht't⟩) fun h => h.elim (fun hs'e => absurd hs'e (nonempty_of_mem hs').ne_empty) fun ht'e => absurd ht'e (nonempty_of_mem ht').ne_empty, fun h => prod_mem_prod h.1 h.2⟩ theorem mem_prod_principal {s : Set (α × β)} : s ∈ f ×ˢ 𝓟 t ↔ { a | ∀ b ∈ t, (a, b) ∈ s } ∈ f := by rw [← @exists_mem_subset_iff _ f, mem_prod_iff] refine exists_congr fun u => Iff.rfl.and ⟨?_, fun h => ⟨t, mem_principal_self t, ?_⟩⟩ · rintro ⟨v, v_in, hv⟩ a a_in b b_in exact hv (mk_mem_prod a_in <| v_in b_in) · rintro ⟨x, y⟩ ⟨hx, hy⟩ exact h hx y hy theorem mem_prod_top {s : Set (α × β)} : s ∈ f ×ˢ (⊤ : Filter β) ↔ { a | ∀ b, (a, b) ∈ s } ∈ f := by rw [← principal_univ, mem_prod_principal] simp only [mem_univ, forall_true_left] theorem eventually_prod_principal_iff {p : α × β → Prop} {s : Set β} : (∀ᶠ x : α × β in f ×ˢ 𝓟 s, p x) ↔ ∀ᶠ x : α in f, ∀ y : β, y ∈ s → p (x, y) := by rw [eventually_iff, eventually_iff, mem_prod_principal] simp only [mem_setOf_eq] theorem comap_prod (f : α → β × γ) (b : Filter β) (c : Filter γ) : comap f (b ×ˢ c) = comap (Prod.fst ∘ f) b ⊓ comap (Prod.snd ∘ f) c := by rw [prod_eq_inf, comap_inf, Filter.comap_comap, Filter.comap_comap] theorem comap_prodMap_prod (f : α → β) (g : γ → δ) (lb : Filter β) (ld : Filter δ) : comap (Prod.map f g) (lb ×ˢ ld) = comap f lb ×ˢ comap g ld := by simp [prod_eq_inf, comap_comap, Function.comp_def] theorem prod_top : f ×ˢ (⊤ : Filter β) = f.comap Prod.fst := by rw [prod_eq_inf, comap_top, inf_top_eq] theorem top_prod : (⊤ : Filter α) ×ˢ g = g.comap Prod.snd := by rw [prod_eq_inf, comap_top, top_inf_eq] theorem sup_prod (f₁ f₂ : Filter α) (g : Filter β) : (f₁ ⊔ f₂) ×ˢ g = (f₁ ×ˢ g) ⊔ (f₂ ×ˢ g) := by simp only [prod_eq_inf, comap_sup, inf_sup_right] theorem prod_sup (f : Filter α) (g₁ g₂ : Filter β) : f ×ˢ (g₁ ⊔ g₂) = (f ×ˢ g₁) ⊔ (f ×ˢ g₂) := by simp only [prod_eq_inf, comap_sup, inf_sup_left] theorem eventually_prod_iff {p : α × β → Prop} : (∀ᶠ x in f ×ˢ g, p x) ↔ ∃ pa : α → Prop, (∀ᶠ x in f, pa x) ∧ ∃ pb : β → Prop, (∀ᶠ y in g, pb y) ∧ ∀ {x}, pa x → ∀ {y}, pb y → p (x, y) := by simpa only [Set.prod_subset_iff] using @mem_prod_iff α β p f g theorem tendsto_fst : Tendsto Prod.fst (f ×ˢ g) f := tendsto_inf_left tendsto_comap theorem tendsto_snd : Tendsto Prod.snd (f ×ˢ g) g := tendsto_inf_right tendsto_comap /-- If a function tends to a product `g ×ˢ h` of filters, then its first component tends to `g`. See also `Filter.Tendsto.fst_nhds` for the special case of converging to a point in a product of two topological spaces. -/ theorem Tendsto.fst {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) : Tendsto (fun a ↦ (m a).1) f g := tendsto_fst.comp H /-- If a function tends to a product `g ×ˢ h` of filters, then its second component tends to `h`. See also `Filter.Tendsto.snd_nhds` for the special case of converging to a point in a product of two topological spaces. -/ theorem Tendsto.snd {h : Filter γ} {m : α → β × γ} (H : Tendsto m f (g ×ˢ h)) : Tendsto (fun a ↦ (m a).2) f h := tendsto_snd.comp H theorem Tendsto.prodMk {h : Filter γ} {m₁ : α → β} {m₂ : α → γ} (h₁ : Tendsto m₁ f g) (h₂ : Tendsto m₂ f h) : Tendsto (fun x => (m₁ x, m₂ x)) f (g ×ˢ h) := tendsto_inf.2 ⟨tendsto_comap_iff.2 h₁, tendsto_comap_iff.2 h₂⟩ @[deprecated (since := "2025-03-10")] alias Tendsto.prod_mk := Tendsto.prodMk theorem tendsto_prod_swap : Tendsto (Prod.swap : α × β → β × α) (f ×ˢ g) (g ×ˢ f) := tendsto_snd.prodMk tendsto_fst theorem Eventually.prod_inl {la : Filter α} {p : α → Prop} (h : ∀ᶠ x in la, p x) (lb : Filter β) : ∀ᶠ x in la ×ˢ lb, p (x : α × β).1 := tendsto_fst.eventually h theorem Eventually.prod_inr {lb : Filter β} {p : β → Prop} (h : ∀ᶠ x in lb, p x) (la : Filter α) : ∀ᶠ x in la ×ˢ lb, p (x : α × β).2 := tendsto_snd.eventually h theorem Eventually.prod_mk {la : Filter α} {pa : α → Prop} (ha : ∀ᶠ x in la, pa x) {lb : Filter β} {pb : β → Prop} (hb : ∀ᶠ y in lb, pb y) : ∀ᶠ p in la ×ˢ lb, pa (p : α × β).1 ∧ pb p.2 := (ha.prod_inl lb).and (hb.prod_inr la) theorem EventuallyEq.prodMap {δ} {la : Filter α} {fa ga : α → γ} (ha : fa =ᶠ[la] ga) {lb : Filter β} {fb gb : β → δ} (hb : fb =ᶠ[lb] gb) : Prod.map fa fb =ᶠ[la ×ˢ lb] Prod.map ga gb := (Eventually.prod_mk ha hb).mono fun _ h => Prod.ext h.1 h.2 @[deprecated (since := "2025-03-10")] alias EventuallyEq.prod_map := EventuallyEq.prodMap theorem EventuallyLE.prodMap {δ} [LE γ] [LE δ] {la : Filter α} {fa ga : α → γ} (ha : fa ≤ᶠ[la] ga) {lb : Filter β} {fb gb : β → δ} (hb : fb ≤ᶠ[lb] gb) : Prod.map fa fb ≤ᶠ[la ×ˢ lb] Prod.map ga gb := Eventually.prod_mk ha hb @[deprecated (since := "2025-03-10")] alias EventuallyLE.prod_map := EventuallyLE.prodMap theorem Eventually.curry {la : Filter α} {lb : Filter β} {p : α × β → Prop} (h : ∀ᶠ x in la ×ˢ lb, p x) : ∀ᶠ x in la, ∀ᶠ y in lb, p (x, y) := by rcases eventually_prod_iff.1 h with ⟨pa, ha, pb, hb, h⟩ exact ha.mono fun a ha => hb.mono fun b hb => h ha hb protected lemma Frequently.uncurry {la : Filter α} {lb : Filter β} {p : α → β → Prop} (h : ∃ᶠ x in la, ∃ᶠ y in lb, p x y) : ∃ᶠ xy in la ×ˢ lb, p xy.1 xy.2 := mt (fun h ↦ by simpa only [not_frequently] using h.curry) h lemma Frequently.of_curry {la : Filter α} {lb : Filter β} {p : α × β → Prop} (h : ∃ᶠ x in la, ∃ᶠ y in lb, p (x, y)) : ∃ᶠ xy in la ×ˢ lb, p xy := h.uncurry /-- A fact that is eventually true about all pairs `l ×ˢ l` is eventually true about all diagonal pairs `(i, i)` -/ theorem Eventually.diag_of_prod {p : α × α → Prop} (h : ∀ᶠ i in f ×ˢ f, p i) : ∀ᶠ i in f, p (i, i) := by obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h apply (ht.and hs).mono fun x hx => hst hx.1 hx.2 theorem Eventually.diag_of_prod_left {f : Filter α} {g : Filter γ} {p : (α × α) × γ → Prop} : (∀ᶠ x in (f ×ˢ f) ×ˢ g, p x) → ∀ᶠ x : α × γ in f ×ˢ g, p ((x.1, x.1), x.2) := by intro h obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h exact (ht.diag_of_prod.prod_mk hs).mono fun x hx => by simp only [hst hx.1 hx.2] theorem Eventually.diag_of_prod_right {f : Filter α} {g : Filter γ} {p : α × γ × γ → Prop} : (∀ᶠ x in f ×ˢ (g ×ˢ g), p x) → ∀ᶠ x : α × γ in f ×ˢ g, p (x.1, x.2, x.2) := by intro h obtain ⟨t, ht, s, hs, hst⟩ := eventually_prod_iff.1 h exact (ht.prod_mk hs.diag_of_prod).mono fun x hx => by simp only [hst hx.1 hx.2] theorem tendsto_diag : Tendsto (fun i => (i, i)) f (f ×ˢ f) := tendsto_iff_eventually.mpr fun _ hpr => hpr.diag_of_prod theorem prod_iInf_left [Nonempty ι] {f : ι → Filter α} {g : Filter β} : (⨅ i, f i) ×ˢ g = ⨅ i, f i ×ˢ g := by simp only [prod_eq_inf, comap_iInf, iInf_inf] theorem prod_iInf_right [Nonempty ι] {f : Filter α} {g : ι → Filter β} : (f ×ˢ ⨅ i, g i) = ⨅ i, f ×ˢ g i := by simp only [prod_eq_inf, comap_iInf, inf_iInf] @[mono, gcongr] theorem prod_mono {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) : f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ := inf_le_inf (comap_mono hf) (comap_mono hg) @[gcongr] theorem prod_mono_left (g : Filter β) {f₁ f₂ : Filter α} (hf : f₁ ≤ f₂) : f₁ ×ˢ g ≤ f₂ ×ˢ g := Filter.prod_mono hf rfl.le @[gcongr] theorem prod_mono_right (f : Filter α) {g₁ g₂ : Filter β} (hf : g₁ ≤ g₂) : f ×ˢ g₁ ≤ f ×ˢ g₂ := Filter.prod_mono rfl.le hf theorem prod_comap_comap_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x} {f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : β₁ → α₁} {m₂ : β₂ → α₂} : comap m₁ f₁ ×ˢ comap m₂ f₂ = comap (fun p : β₁ × β₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) := by simp only [prod_eq_inf, comap_comap, comap_inf, Function.comp_def] theorem prod_comm' : f ×ˢ g = comap Prod.swap (g ×ˢ f) := by simp only [prod_eq_inf, comap_comap, Function.comp_def, inf_comm, Prod.swap, comap_inf] theorem prod_comm : f ×ˢ g = map (fun p : β × α => (p.2, p.1)) (g ×ˢ f) := by rw [prod_comm', ← map_swap_eq_comap_swap] rfl theorem mem_prod_iff_left {s : Set (α × β)} : s ∈ f ×ˢ g ↔ ∃ t ∈ f, ∀ᶠ y in g, ∀ x ∈ t, (x, y) ∈ s := by simp only [mem_prod_iff, prod_subset_iff] refine exists_congr fun _ => Iff.rfl.and <| Iff.trans ?_ exists_mem_subset_iff exact exists_congr fun _ => Iff.rfl.and forall₂_swap theorem mem_prod_iff_right {s : Set (α × β)} : s ∈ f ×ˢ g ↔ ∃ t ∈ g, ∀ᶠ x in f, ∀ y ∈ t, (x, y) ∈ s := by rw [prod_comm, mem_map, mem_prod_iff_left]; rfl @[simp] theorem map_fst_prod (f : Filter α) (g : Filter β) [NeBot g] : map Prod.fst (f ×ˢ g) = f := by ext s simp only [mem_map, mem_prod_iff_left, mem_preimage, eventually_const, ← subset_def, exists_mem_subset_iff] @[simp] theorem map_snd_prod (f : Filter α) (g : Filter β) [NeBot f] : map Prod.snd (f ×ˢ g) = g := by rw [prod_comm, map_map]; apply map_fst_prod @[simp] theorem prod_le_prod {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} [NeBot f₁] [NeBot g₁] : f₁ ×ˢ g₁ ≤ f₂ ×ˢ g₂ ↔ f₁ ≤ f₂ ∧ g₁ ≤ g₂ := ⟨fun h => ⟨map_fst_prod f₁ g₁ ▸ tendsto_fst.mono_left h, map_snd_prod f₁ g₁ ▸ tendsto_snd.mono_left h⟩, fun h => prod_mono h.1 h.2⟩ @[simp] theorem prod_inj {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} [NeBot f₁] [NeBot g₁] : f₁ ×ˢ g₁ = f₂ ×ˢ g₂ ↔ f₁ = f₂ ∧ g₁ = g₂ := by refine ⟨fun h => ?_, fun h => h.1 ▸ h.2 ▸ rfl⟩ have hle : f₁ ≤ f₂ ∧ g₁ ≤ g₂ := prod_le_prod.1 h.le haveI := neBot_of_le hle.1; haveI := neBot_of_le hle.2 exact ⟨hle.1.antisymm <| (prod_le_prod.1 h.ge).1, hle.2.antisymm <| (prod_le_prod.1 h.ge).2⟩ theorem eventually_swap_iff {p : α × β → Prop} : (∀ᶠ x : α × β in f ×ˢ g, p x) ↔ ∀ᶠ y : β × α in g ×ˢ f, p y.swap := by rw [prod_comm]; rfl theorem prod_assoc (f : Filter α) (g : Filter β) (h : Filter γ) : map (Equiv.prodAssoc α β γ) ((f ×ˢ g) ×ˢ h) = f ×ˢ (g ×ˢ h) := by simp_rw [← comap_equiv_symm, prod_eq_inf, comap_inf, comap_comap, inf_assoc, Function.comp_def, Equiv.prodAssoc_symm_apply] theorem prod_assoc_symm (f : Filter α) (g : Filter β) (h : Filter γ) : map (Equiv.prodAssoc α β γ).symm (f ×ˢ (g ×ˢ h)) = (f ×ˢ g) ×ˢ h := by simp_rw [map_equiv_symm, prod_eq_inf, comap_inf, comap_comap, inf_assoc, Function.comp_def, Equiv.prodAssoc_apply] theorem tendsto_prodAssoc {h : Filter γ} : Tendsto (Equiv.prodAssoc α β γ) ((f ×ˢ g) ×ˢ h) (f ×ˢ (g ×ˢ h)) := (prod_assoc f g h).le theorem tendsto_prodAssoc_symm {h : Filter γ} : Tendsto (Equiv.prodAssoc α β γ).symm (f ×ˢ (g ×ˢ h)) ((f ×ˢ g) ×ˢ h) := (prod_assoc_symm f g h).le /-- A useful lemma when dealing with uniformities. -/ theorem map_swap4_prod {h : Filter γ} {k : Filter δ} : map (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) ((f ×ˢ g) ×ˢ (h ×ˢ k)) = (f ×ˢ h) ×ˢ (g ×ˢ k) := by simp_rw [map_swap4_eq_comap, prod_eq_inf, comap_inf, comap_comap]; ac_rfl theorem tendsto_swap4_prod {h : Filter γ} {k : Filter δ} : Tendsto (fun p : (α × β) × γ × δ => ((p.1.1, p.2.1), (p.1.2, p.2.2))) ((f ×ˢ g) ×ˢ (h ×ˢ k)) ((f ×ˢ h) ×ˢ (g ×ˢ k)) := map_swap4_prod.le theorem prod_map_map_eq.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x} {f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : α₁ → β₁} {m₂ : α₂ → β₂} : map m₁ f₁ ×ˢ map m₂ f₂ = map (fun p : α₁ × α₂ => (m₁ p.1, m₂ p.2)) (f₁ ×ˢ f₂) := le_antisymm (fun s hs => let ⟨s₁, hs₁, s₂, hs₂, h⟩ := mem_prod_iff.mp hs mem_of_superset (prod_mem_prod (image_mem_map hs₁) (image_mem_map hs₂)) <| by rwa [prod_image_image_eq, image_subset_iff]) ((tendsto_map.comp tendsto_fst).prodMk (tendsto_map.comp tendsto_snd)) theorem prod_map_map_eq' {α₁ : Type*} {α₂ : Type*} {β₁ : Type*} {β₂ : Type*} (f : α₁ → α₂) (g : β₁ → β₂) (F : Filter α₁) (G : Filter β₁) : map f F ×ˢ map g G = map (Prod.map f g) (F ×ˢ G) := prod_map_map_eq theorem prod_map_left (f : α → β) (F : Filter α) (G : Filter γ) : map f F ×ˢ G = map (Prod.map f id) (F ×ˢ G) := by rw [← prod_map_map_eq', map_id] theorem prod_map_right (f : β → γ) (F : Filter α) (G : Filter β) : F ×ˢ map f G = map (Prod.map id f) (F ×ˢ G) := by rw [← prod_map_map_eq', map_id] theorem le_prod_map_fst_snd {f : Filter (α × β)} : f ≤ map Prod.fst f ×ˢ map Prod.snd f := le_inf le_comap_map le_comap_map theorem Tendsto.prodMap {δ : Type*} {f : α → γ} {g : β → δ} {a : Filter α} {b : Filter β} {c : Filter γ} {d : Filter δ} (hf : Tendsto f a c) (hg : Tendsto g b d) : Tendsto (Prod.map f g) (a ×ˢ b) (c ×ˢ d) := by rw [Tendsto, Prod.map_def, ← prod_map_map_eq] exact Filter.prod_mono hf hg @[deprecated (since := "2025-03-10")] alias Tendsto.prod_map := Tendsto.prodMap protected theorem map_prod (m : α × β → γ) (f : Filter α) (g : Filter β) : map m (f ×ˢ g) = (f.map fun a b => m (a, b)).seq g := by simp only [Filter.ext_iff, mem_map, mem_prod_iff, mem_map_seq_iff, exists_and_left] intro s constructor · exact fun ⟨t, ht, s, hs, h⟩ => ⟨s, hs, t, ht, fun x hx y hy => @h ⟨x, y⟩ ⟨hx, hy⟩⟩ · exact fun ⟨s, hs, t, ht, h⟩ => ⟨t, ht, s, hs, fun ⟨x, y⟩ ⟨hx, hy⟩ => h x hx y hy⟩ theorem prod_eq : f ×ˢ g = (f.map Prod.mk).seq g := f.map_prod id g theorem prod_inf_prod {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} : (f₁ ×ˢ g₁) ⊓ (f₂ ×ˢ g₂) = (f₁ ⊓ f₂) ×ˢ (g₁ ⊓ g₂) := by simp only [prod_eq_inf, comap_inf, inf_comm, inf_assoc, inf_left_comm] theorem inf_prod {f₁ f₂ : Filter α} : (f₁ ⊓ f₂) ×ˢ g = (f₁ ×ˢ g) ⊓ (f₂ ×ˢ g) := by rw [prod_inf_prod, inf_idem] theorem prod_inf {g₁ g₂ : Filter β} : f ×ˢ (g₁ ⊓ g₂) = (f ×ˢ g₁) ⊓ (f ×ˢ g₂) := by rw [prod_inf_prod, inf_idem] @[simp] theorem prod_principal_principal {s : Set α} {t : Set β} : 𝓟 s ×ˢ 𝓟 t = 𝓟 (s ×ˢ t) := by simp only [prod_eq_inf, comap_principal, principal_eq_iff_eq, comap_principal, inf_principal]; rfl @[simp] theorem pure_prod {a : α} {f : Filter β} : pure a ×ˢ f = map (Prod.mk a) f := by rw [prod_eq, map_pure, pure_seq_eq_map] theorem map_pure_prod (f : α → β → γ) (a : α) (B : Filter β) : map (Function.uncurry f) (pure a ×ˢ B) = map (f a) B := by rw [Filter.pure_prod]; rfl @[simp] theorem prod_pure {b : β} : f ×ˢ pure b = map (fun a => (a, b)) f := by rw [prod_eq, seq_pure, map_map]; rfl theorem prod_pure_pure {a : α} {b : β} : (pure a : Filter α) ×ˢ (pure b : Filter β) = pure (a, b) := by simp @[simp] theorem prod_eq_bot : f ×ˢ g = ⊥ ↔ f = ⊥ ∨ g = ⊥ := by simp_rw [← empty_mem_iff_bot, mem_prod_iff, subset_empty_iff, prod_eq_empty_iff, ← exists_prop, Subtype.exists', exists_or, exists_const, Subtype.exists, exists_prop, exists_eq_right] @[simp] theorem prod_bot : f ×ˢ (⊥ : Filter β) = ⊥ := prod_eq_bot.2 <| Or.inr rfl @[simp] theorem bot_prod : (⊥ : Filter α) ×ˢ g = ⊥ := prod_eq_bot.2 <| Or.inl rfl theorem prod_neBot : NeBot (f ×ˢ g) ↔ NeBot f ∧ NeBot g := by simp only [neBot_iff, Ne, prod_eq_bot, not_or] protected theorem NeBot.prod (hf : NeBot f) (hg : NeBot g) : NeBot (f ×ˢ g) := prod_neBot.2 ⟨hf, hg⟩ instance prod.instNeBot [hf : NeBot f] [hg : NeBot g] : NeBot (f ×ˢ g) := hf.prod hg @[simp] lemma disjoint_prod {f' : Filter α} {g' : Filter β} : Disjoint (f ×ˢ g) (f' ×ˢ g') ↔ Disjoint f f' ∨ Disjoint g g' := by simp only [disjoint_iff, prod_inf_prod, prod_eq_bot] /-- `p ∧ q` occurs frequently along the product of two filters iff both `p` and `q` occur frequently along the corresponding filters. -/ theorem frequently_prod_and {p : α → Prop} {q : β → Prop} : (∃ᶠ x in f ×ˢ g, p x.1 ∧ q x.2) ↔ (∃ᶠ a in f, p a) ∧ ∃ᶠ b in g, q b := by simp only [frequently_iff_neBot, ← prod_neBot, ← prod_inf_prod, prod_principal_principal] rfl theorem tendsto_prod_iff {f : α × β → γ} {x : Filter α} {y : Filter β} {z : Filter γ} : Tendsto f (x ×ˢ y) z ↔ ∀ W ∈ z, ∃ U ∈ x, ∃ V ∈ y, ∀ x y, x ∈ U → y ∈ V → f (x, y) ∈ W := by simp only [tendsto_def, mem_prod_iff, prod_sub_preimage_iff, exists_prop] theorem tendsto_prod_iff' {g' : Filter γ} {s : α → β × γ} : Tendsto s f (g ×ˢ g') ↔ Tendsto (fun n => (s n).1) f g ∧ Tendsto (fun n => (s n).2) f g' := by simp only [prod_eq_inf, tendsto_inf, tendsto_comap_iff, Function.comp_def] theorem le_prod {f : Filter (α × β)} {g : Filter α} {g' : Filter β} : (f ≤ g ×ˢ g') ↔ Tendsto Prod.fst f g ∧ Tendsto Prod.snd f g' := tendsto_prod_iff' end Prod /-! ### Coproducts of filters -/ section Coprod variable {f : Filter α} {g : Filter β} theorem coprod_eq_prod_top_sup_top_prod (f : Filter α) (g : Filter β) : Filter.coprod f g = f ×ˢ ⊤ ⊔ ⊤ ×ˢ g := by rw [prod_top, top_prod] rfl theorem mem_coprod_iff {s : Set (α × β)} {f : Filter α} {g : Filter β} : s ∈ f.coprod g ↔ (∃ t₁ ∈ f, Prod.fst ⁻¹' t₁ ⊆ s) ∧ ∃ t₂ ∈ g, Prod.snd ⁻¹' t₂ ⊆ s := by simp [Filter.coprod] @[simp] theorem bot_coprod (l : Filter β) : (⊥ : Filter α).coprod l = comap Prod.snd l := by simp [Filter.coprod] @[simp] theorem coprod_bot (l : Filter α) : l.coprod (⊥ : Filter β) = comap Prod.fst l := by simp [Filter.coprod] theorem bot_coprod_bot : (⊥ : Filter α).coprod (⊥ : Filter β) = ⊥ := by simp theorem compl_mem_coprod {s : Set (α × β)} {la : Filter α} {lb : Filter β} : sᶜ ∈ la.coprod lb ↔ (Prod.fst '' s)ᶜ ∈ la ∧ (Prod.snd '' s)ᶜ ∈ lb := by simp only [Filter.coprod, mem_sup, compl_mem_comap] @[mono] theorem coprod_mono {f₁ f₂ : Filter α} {g₁ g₂ : Filter β} (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) : f₁.coprod g₁ ≤ f₂.coprod g₂ := sup_le_sup (comap_mono hf) (comap_mono hg) theorem coprod_neBot_iff : (f.coprod g).NeBot ↔ f.NeBot ∧ Nonempty β ∨ Nonempty α ∧ g.NeBot := by simp [Filter.coprod] @[instance] theorem coprod_neBot_left [NeBot f] [Nonempty β] : (f.coprod g).NeBot := coprod_neBot_iff.2 (Or.inl ⟨‹_›, ‹_›⟩) @[instance] theorem coprod_neBot_right [NeBot g] [Nonempty α] : (f.coprod g).NeBot := coprod_neBot_iff.2 (Or.inr ⟨‹_›, ‹_›⟩) theorem coprod_inf_prod_le (f₁ f₂ : Filter α) (g₁ g₂ : Filter β) : f₁.coprod g₁ ⊓ f₂ ×ˢ g₂ ≤ f₁ ×ˢ g₂ ⊔ f₂ ×ˢ g₁ := calc f₁.coprod g₁ ⊓ f₂ ×ˢ g₂ _ = (f₁ ×ˢ ⊤ ⊔ ⊤ ×ˢ g₁) ⊓ f₂ ×ˢ g₂ := by rw [coprod_eq_prod_top_sup_top_prod] _ = f₁ ×ˢ ⊤ ⊓ f₂ ×ˢ g₂ ⊔ ⊤ ×ˢ g₁ ⊓ f₂ ×ˢ g₂ := inf_sup_right _ _ _ _ = (f₁ ⊓ f₂) ×ˢ g₂ ⊔ f₂ ×ˢ (g₁ ⊓ g₂) := by simp [prod_inf_prod] _ ≤ f₁ ×ˢ g₂ ⊔ f₂ ×ˢ g₁ := sup_le_sup (prod_mono inf_le_left le_rfl) (prod_mono le_rfl inf_le_left) theorem principal_coprod_principal (s : Set α) (t : Set β) : (𝓟 s).coprod (𝓟 t) = 𝓟 (sᶜ ×ˢ tᶜ)ᶜ := by rw [Filter.coprod, comap_principal, comap_principal, sup_principal, Set.prod_eq, compl_inter, preimage_compl, preimage_compl, compl_compl, compl_compl] -- this inequality can be strict; see `map_const_principal_coprod_map_id_principal` and -- `map_prodMap_const_id_principal_coprod_principal` below. theorem map_prodMap_coprod_le.{u, v, w, x} {α₁ : Type u} {α₂ : Type v} {β₁ : Type w} {β₂ : Type x} {f₁ : Filter α₁} {f₂ : Filter α₂} {m₁ : α₁ → β₁} {m₂ : α₂ → β₂} : map (Prod.map m₁ m₂) (f₁.coprod f₂) ≤ (map m₁ f₁).coprod (map m₂ f₂) := by intro s simp only [mem_map, mem_coprod_iff] rintro ⟨⟨u₁, hu₁, h₁⟩, u₂, hu₂, h₂⟩ refine ⟨⟨m₁ ⁻¹' u₁, hu₁, fun _ hx => h₁ ?_⟩, ⟨m₂ ⁻¹' u₂, hu₂, fun _ hx => h₂ ?_⟩⟩ <;> convert hx @[deprecated (since := "2025-03-10")] alias map_prod_map_coprod_le := map_prodMap_coprod_le /-- Characterization of the coproduct of the `Filter.map`s of two principal filters `𝓟 {a}` and `𝓟 {i}`, the first under the constant function `fun a => b` and the second under the identity function. Together with the next lemma, `map_prodMap_const_id_principal_coprod_principal`, this provides an example showing that the inequality in the lemma `map_prodMap_coprod_le` can be strict. -/ theorem map_const_principal_coprod_map_id_principal {α β ι : Type*} (a : α) (b : β) (i : ι) : (map (fun _ => b) (𝓟 {a})).coprod (map id (𝓟 {i})) =
𝓟 ((({b} : Set β) ×ˢ univ) ∪ (univ ×ˢ ({i} : Set ι))) := by simp only [map_principal, Filter.coprod, comap_principal, sup_principal, image_singleton, image_id, prod_univ, univ_prod, id]
Mathlib/Order/Filter/Prod.lean
508
510
/- 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, Sébastien Gouëzel -/ import Mathlib.Analysis.Normed.Field.Basic import Mathlib.Topology.MetricSpace.Cauchy /-! # Completeness in terms of `Cauchy` filters vs `isCauSeq` sequences In this file we apply `Metric.complete_of_cauchySeq_tendsto` to prove that a `NormedRing` is complete in terms of `Cauchy` filter if and only if it is complete in terms of `CauSeq` Cauchy sequences. -/ universe u v open Set Filter Topology variable {β : Type v} theorem CauSeq.tendsto_limit [NormedRing β] [hn : IsAbsoluteValue (norm : β → ℝ)] (f : CauSeq β norm) [CauSeq.IsComplete β norm] : Tendsto f atTop (𝓝 f.lim) := tendsto_nhds.mpr (by intro s os lfs suffices ∃ a : ℕ, ∀ b : ℕ, b ≥ a → f b ∈ s by simpa using this rcases Metric.isOpen_iff.1 os _ lfs with ⟨ε, ⟨hε, hεs⟩⟩ obtain ⟨N, hN⟩ := Setoid.symm (CauSeq.equiv_lim f) _ hε exists N intro b hb apply hεs dsimp [Metric.ball] rw [dist_comm, dist_eq_norm] solve_by_elim) variable [NormedField β] /- This section shows that if we have a uniform space generated by an absolute value, topological completeness and Cauchy sequence completeness coincide. The problem is that there isn't a good notion of "uniform space generated by an absolute value", so right now this is specific to norm. Furthermore, norm only instantiates IsAbsoluteValue on NormedDivisionRing. This needs to be fixed, since it prevents showing that ℤ_[hp] is complete. -/ open Metric theorem CauchySeq.isCauSeq {f : ℕ → β} (hf : CauchySeq f) : IsCauSeq norm f := by obtain ⟨hf1, hf2⟩ := cauchy_iff.1 hf intro ε hε rcases hf2 { x | dist x.1 x.2 < ε } (dist_mem_uniformity hε) with ⟨t, ⟨ht, htsub⟩⟩ simp only [mem_map, mem_atTop_sets, mem_preimage] at ht; obtain ⟨N, hN⟩ := ht exists N
intro j hj rw [← dist_eq_norm] apply @htsub (f j, f N) apply Set.mk_mem_prod <;> solve_by_elim [le_refl] theorem CauSeq.cauchySeq (f : CauSeq β norm) : CauchySeq f := by refine cauchy_iff.2 ⟨by infer_instance, fun s hs => ?_⟩ rcases mem_uniformity_dist.1 hs with ⟨ε, ⟨hε, hεs⟩⟩ obtain ⟨N, hN⟩ := CauSeq.cauchy₂ f hε exists { n | n ≥ N }.image f
Mathlib/Topology/MetricSpace/CauSeqFilter.lean
55
64
/- Copyright (c) 2019 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne -/ import Mathlib.MeasureTheory.Integral.Bochner.Basic import Mathlib.MeasureTheory.Integral.Bochner.L1 import Mathlib.MeasureTheory.Integral.Bochner.VitaliCaratheodory deprecated_module (since := "2025-04-13")
Mathlib/MeasureTheory/Integral/Bochner.lean
1,487
1,494
/- Copyright (c) 2022 Antoine Chambert-Loir. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Chambert-Loir -/ import Mathlib.Algebra.Group.Subgroup.Lattice import Mathlib.GroupTheory.GroupAction.FixedPoints /-! # Fixing submonoid, fixing subgroup of an action In the presence of an action of a monoid or a group, this file defines the fixing submonoid or the fixing subgroup, and relates it to the set of fixed points via a Galois connection. ## Main definitions * `fixingSubmonoid M s` : in the presence of `MulAction M α` (with `Monoid M`) it is the `Submonoid M` consisting of elements which fix `s : Set α` pointwise. * `fixingSubmonoid_fixedPoints_gc M α` is the `GaloisConnection` that relates `fixingSubmonoid` with `fixedPoints`. * `fixingSubgroup M s` : in the presence of `MulAction M α` (with `Group M`) it is the `Subgroup M` consisting of elements which fix `s : Set α` pointwise. * `fixingSubgroup_fixedPoints_gc M α` is the `GaloisConnection` that relates `fixingSubgroup` with `fixedPoints`. TODO : * Maybe other lemmas are useful * Treat semigroups ? * add `to_additive` for the various lemmas -/ section Monoid open MulAction variable (M : Type*) {α : Type*} [Monoid M] [MulAction M α] /-- The submonoid fixing a set under a `MulAction`. -/ @[to_additive "The additive submonoid fixing a set under an `AddAction`."] def fixingSubmonoid (s : Set α) : Submonoid M where carrier := { ϕ : M | ∀ x : s, ϕ • (x : α) = x } one_mem' _ := one_smul _ _ mul_mem' {x y} hx hy z := by rw [mul_smul, hy z, hx z] @[to_additive] theorem mem_fixingSubmonoid_iff {s : Set α} {m : M} : m ∈ fixingSubmonoid M s ↔ ∀ y ∈ s, m • y = y := ⟨fun hg y hy => hg ⟨y, hy⟩, fun h ⟨y, hy⟩ => h y hy⟩ variable (α) /-- The Galois connection between fixing submonoids and fixed points of a monoid action -/ @[to_additive] theorem fixingSubmonoid_fixedPoints_gc : GaloisConnection (OrderDual.toDual ∘ fixingSubmonoid M) ((fun P : Submonoid M => fixedPoints P α) ∘ OrderDual.ofDual) := fun _s _P => ⟨fun h s hs p => h p.2 ⟨s, hs⟩, fun h p hp s => h s.2 ⟨p, hp⟩⟩ @[to_additive] theorem fixingSubmonoid_antitone : Antitone fun s : Set α => fixingSubmonoid M s := (fixingSubmonoid_fixedPoints_gc M α).monotone_l @[to_additive fixedPoints_antitone_addSubmonoid] theorem fixedPoints_antitone : Antitone fun P : Submonoid M => fixedPoints P α := (fixingSubmonoid_fixedPoints_gc M α).monotone_u.dual_left /-- Fixing submonoid of union is intersection -/ @[to_additive] theorem fixingSubmonoid_union {s t : Set α} : fixingSubmonoid M (s ∪ t) = fixingSubmonoid M s ⊓ fixingSubmonoid M t := (fixingSubmonoid_fixedPoints_gc M α).l_sup /-- Fixing submonoid of iUnion is intersection -/ @[to_additive] theorem fixingSubmonoid_iUnion {ι : Sort*} {s : ι → Set α} : fixingSubmonoid M (⋃ i, s i) = ⨅ i, fixingSubmonoid M (s i) := (fixingSubmonoid_fixedPoints_gc M α).l_iSup /-- Fixed points of sup of submonoids is intersection -/ @[to_additive] theorem fixedPoints_submonoid_sup {P Q : Submonoid M} : fixedPoints (↥(P ⊔ Q)) α = fixedPoints P α ∩ fixedPoints Q α := (fixingSubmonoid_fixedPoints_gc M α).u_inf /-- Fixed points of iSup of submonoids is intersection -/ @[to_additive] theorem fixedPoints_submonoid_iSup {ι : Sort*} {P : ι → Submonoid M} : fixedPoints (↥(iSup P)) α = ⋂ i, fixedPoints (P i) α := (fixingSubmonoid_fixedPoints_gc M α).u_iInf end Monoid section Group open MulAction variable (M : Type*) {α : Type*} [Group M] [MulAction M α] /-- The subgroup fixing a set under a `MulAction`. -/ @[to_additive "The additive subgroup fixing a set under an `AddAction`."] def fixingSubgroup (s : Set α) : Subgroup M := { fixingSubmonoid M s with inv_mem' := fun hx z => by rw [inv_smul_eq_iff, hx z] } @[to_additive] theorem mem_fixingSubgroup_iff {s : Set α} {m : M} : m ∈ fixingSubgroup M s ↔ ∀ y ∈ s, m • y = y := ⟨fun hg y hy => hg ⟨y, hy⟩, fun h ⟨y, hy⟩ => h y hy⟩ @[to_additive] theorem mem_fixingSubgroup_iff_subset_fixedBy {s : Set α} {m : M} : m ∈ fixingSubgroup M s ↔ s ⊆ fixedBy α m := by simp_rw [mem_fixingSubgroup_iff, Set.subset_def, mem_fixedBy] @[to_additive] theorem mem_fixingSubgroup_compl_iff_movedBy_subset {s : Set α} {m : M} : m ∈ fixingSubgroup M sᶜ ↔ (fixedBy α m)ᶜ ⊆ s := by rw [mem_fixingSubgroup_iff_subset_fixedBy, Set.compl_subset_comm] variable (α) /-- The Galois connection between fixing subgroups and fixed points of a group action -/ @[to_additive] theorem fixingSubgroup_fixedPoints_gc : GaloisConnection (OrderDual.toDual ∘ fixingSubgroup M) ((fun P : Subgroup M => fixedPoints P α) ∘ OrderDual.ofDual) := fun _s _P => ⟨fun h s hs p => h p.2 ⟨s, hs⟩, fun h p hp s => h s.2 ⟨p, hp⟩⟩ @[to_additive] theorem fixingSubgroup_antitone : Antitone (fixingSubgroup M : Set α → Subgroup M) := (fixingSubgroup_fixedPoints_gc M α).monotone_l @[to_additive] theorem fixedPoints_subgroup_antitone : Antitone fun P : Subgroup M => fixedPoints P α := (fixingSubgroup_fixedPoints_gc M α).monotone_u.dual_left /-- Fixing subgroup of union is intersection -/ @[to_additive] theorem fixingSubgroup_union {s t : Set α} : fixingSubgroup M (s ∪ t) = fixingSubgroup M s ⊓ fixingSubgroup M t := (fixingSubgroup_fixedPoints_gc M α).l_sup /-- Fixing subgroup of iUnion is intersection -/ @[to_additive] theorem fixingSubgroup_iUnion {ι : Sort*} {s : ι → Set α} : fixingSubgroup M (⋃ i, s i) = ⨅ i, fixingSubgroup M (s i) := (fixingSubgroup_fixedPoints_gc M α).l_iSup /-- Fixed points of sup of subgroups is intersection -/ @[to_additive] theorem fixedPoints_subgroup_sup {P Q : Subgroup M} : fixedPoints (↥(P ⊔ Q)) α = fixedPoints P α ∩ fixedPoints Q α := (fixingSubgroup_fixedPoints_gc M α).u_inf /-- Fixed points of iSup of subgroups is intersection -/ @[to_additive] theorem fixedPoints_subgroup_iSup {ι : Sort*} {P : ι → Subgroup M} : fixedPoints (↥(iSup P)) α = ⋂ i, fixedPoints (P i) α := (fixingSubgroup_fixedPoints_gc M α).u_iInf /-- The orbit of the fixing subgroup of `sᶜ` (ie. the moving subgroup of `s`) is a subset of `s` -/ @[to_additive] theorem orbit_fixingSubgroup_compl_subset {s : Set α} {a : α} (a_in_s : a ∈ s) : MulAction.orbit (fixingSubgroup M sᶜ) a ⊆ s := by intro b b_in_orbit let ⟨⟨g, g_fixing⟩, g_eq⟩ := MulAction.mem_orbit_iff.mp b_in_orbit
rw [Submonoid.mk_smul] at g_eq rw [mem_fixingSubgroup_compl_iff_movedBy_subset] at g_fixing rwa [← g_eq, smul_mem_of_set_mem_fixedBy (set_mem_fixedBy_of_movedBy_subset g_fixing)] end Group
Mathlib/GroupTheory/GroupAction/FixingSubgroup.lean
175
181
/- Copyright (c) 2022 Moritz Doll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Moritz Doll -/ import Mathlib.Analysis.SpecialFunctions.Integrals import Mathlib.MeasureTheory.Measure.Lebesgue.EqHaar import Mathlib.MeasureTheory.Integral.Layercake /-! # Japanese Bracket In this file, we show that Japanese bracket $(1 + \|x\|^2)^{1/2}$ can be estimated from above and below by $1 + \|x\|$. The functions $(1 + \|x\|^2)^{-r/2}$ and $(1 + |x|)^{-r}$ are integrable provided that `r` is larger than the dimension. ## Main statements * `integrable_one_add_norm`: the function $(1 + |x|)^{-r}$ is integrable * `integrable_jap` the Japanese bracket is integrable -/ noncomputable section open scoped NNReal Filter Topology ENNReal open Asymptotics Filter Set Real MeasureTheory Module variable {E : Type*} [NormedAddCommGroup E] theorem sqrt_one_add_norm_sq_le (x : E) : √((1 : ℝ) + ‖x‖ ^ 2) ≤ 1 + ‖x‖ := by rw [sqrt_le_left (by positivity)] simp [add_sq] theorem one_add_norm_le_sqrt_two_mul_sqrt (x : E) : (1 : ℝ) + ‖x‖ ≤ √2 * √(1 + ‖x‖ ^ 2) := by rw [← sqrt_mul zero_le_two]
have := sq_nonneg (‖x‖ - 1) apply le_sqrt_of_sq_le linarith theorem rpow_neg_one_add_norm_sq_le {r : ℝ} (x : E) (hr : 0 < r) : ((1 : ℝ) + ‖x‖ ^ 2) ^ (-r / 2) ≤ (2 : ℝ) ^ (r / 2) * (1 + ‖x‖) ^ (-r) :=
Mathlib/Analysis/SpecialFunctions/JapaneseBracket.lean
41
46
/- Copyright (c) 2020 Floris van Doorn. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Floris van Doorn -/ import Mathlib.Data.Set.Prod /-! # N-ary images of sets This file defines `Set.image2`, the binary image of sets. This is mostly useful to define pointwise operations and `Set.seq`. ## Notes This file is very similar to `Data.Finset.NAry`, to `Order.Filter.NAry`, and to `Data.Option.NAry`. Please keep them in sync. -/ open Function namespace Set variable {α α' β β' γ γ' δ δ' ε ε' ζ ζ' ν : Type*} {f f' : α → β → γ} variable {s s' : Set α} {t t' : Set β} {u : Set γ} {v : Set δ} {a : α} {b : β} theorem mem_image2_iff (hf : Injective2 f) : f a b ∈ image2 f s t ↔ a ∈ s ∧ b ∈ t := ⟨by rintro ⟨a', ha', b', hb', h⟩ rcases hf h with ⟨rfl, rfl⟩ exact ⟨ha', hb'⟩, fun ⟨ha, hb⟩ => mem_image2_of_mem ha hb⟩ /-- image2 is monotone with respect to `⊆`. -/ @[gcongr] theorem image2_subset (hs : s ⊆ s') (ht : t ⊆ t') : image2 f s t ⊆ image2 f s' t' := by rintro _ ⟨a, ha, b, hb, rfl⟩ exact mem_image2_of_mem (hs ha) (ht hb) @[gcongr] theorem image2_subset_left (ht : t ⊆ t') : image2 f s t ⊆ image2 f s t' := image2_subset Subset.rfl ht @[gcongr] theorem image2_subset_right (hs : s ⊆ s') : image2 f s t ⊆ image2 f s' t := image2_subset hs Subset.rfl theorem image_subset_image2_left (hb : b ∈ t) : (fun a => f a b) '' s ⊆ image2 f s t := forall_mem_image.2 fun _ ha => mem_image2_of_mem ha hb theorem image_subset_image2_right (ha : a ∈ s) : f a '' t ⊆ image2 f s t := forall_mem_image.2 fun _ => mem_image2_of_mem ha lemma forall_mem_image2 {p : γ → Prop} : (∀ z ∈ image2 f s t, p z) ↔ ∀ x ∈ s, ∀ y ∈ t, p (f x y) := by aesop lemma exists_mem_image2 {p : γ → Prop} : (∃ z ∈ image2 f s t, p z) ↔ ∃ x ∈ s, ∃ y ∈ t, p (f x y) := by aesop @[deprecated (since := "2024-11-23")] alias forall_image2_iff := forall_mem_image2 @[simp] theorem image2_subset_iff {u : Set γ} : image2 f s t ⊆ u ↔ ∀ x ∈ s, ∀ y ∈ t, f x y ∈ u := forall_mem_image2 theorem image2_subset_iff_left : image2 f s t ⊆ u ↔ ∀ a ∈ s, (fun b => f a b) '' t ⊆ u := by simp_rw [image2_subset_iff, image_subset_iff, subset_def, mem_preimage] theorem image2_subset_iff_right : image2 f s t ⊆ u ↔ ∀ b ∈ t, (fun a => f a b) '' s ⊆ u := by simp_rw [image2_subset_iff, image_subset_iff, subset_def, mem_preimage, @forall₂_swap α] variable (f) @[simp] lemma image_prod : (fun x : α × β ↦ f x.1 x.2) '' s ×ˢ t = image2 f s t := ext fun _ ↦ by simp [and_assoc] @[simp] lemma image_uncurry_prod (s : Set α) (t : Set β) : uncurry f '' s ×ˢ t = image2 f s t := image_prod _ @[simp] lemma image2_mk_eq_prod : image2 Prod.mk s t = s ×ˢ t := ext <| by simp @[simp] lemma image2_curry (f : α × β → γ) (s : Set α) (t : Set β) : image2 (fun a b ↦ f (a, b)) s t = f '' s ×ˢ t := by simp [← image_uncurry_prod, uncurry] theorem image2_swap (s : Set α) (t : Set β) : image2 f s t = image2 (fun a b => f b a) t s := by ext constructor <;> rintro ⟨a, ha, b, hb, rfl⟩ <;> exact ⟨b, hb, a, ha, rfl⟩ variable {f} theorem image2_union_left : image2 f (s ∪ s') t = image2 f s t ∪ image2 f s' t := by simp_rw [← image_prod, union_prod, image_union] theorem image2_union_right : image2 f s (t ∪ t') = image2 f s t ∪ image2 f s t' := by rw [← image2_swap, image2_union_left, image2_swap f, image2_swap f] lemma image2_inter_left (hf : Injective2 f) : image2 f (s ∩ s') t = image2 f s t ∩ image2 f s' t := by simp_rw [← image_uncurry_prod, inter_prod, image_inter hf.uncurry] lemma image2_inter_right (hf : Injective2 f) : image2 f s (t ∩ t') = image2 f s t ∩ image2 f s t' := by simp_rw [← image_uncurry_prod, prod_inter, image_inter hf.uncurry] @[simp] theorem image2_empty_left : image2 f ∅ t = ∅ := ext <| by simp @[simp] theorem image2_empty_right : image2 f s ∅ = ∅ := ext <| by simp theorem Nonempty.image2 : s.Nonempty → t.Nonempty → (image2 f s t).Nonempty := fun ⟨_, ha⟩ ⟨_, hb⟩ => ⟨_, mem_image2_of_mem ha hb⟩ @[simp] theorem image2_nonempty_iff : (image2 f s t).Nonempty ↔ s.Nonempty ∧ t.Nonempty := ⟨fun ⟨_, a, ha, b, hb, _⟩ => ⟨⟨a, ha⟩, b, hb⟩, fun h => h.1.image2 h.2⟩ theorem Nonempty.of_image2_left (h : (Set.image2 f s t).Nonempty) : s.Nonempty := (image2_nonempty_iff.1 h).1 theorem Nonempty.of_image2_right (h : (Set.image2 f s t).Nonempty) : t.Nonempty := (image2_nonempty_iff.1 h).2 @[simp] theorem image2_eq_empty_iff : image2 f s t = ∅ ↔ s = ∅ ∨ t = ∅ := by rw [← not_nonempty_iff_eq_empty, image2_nonempty_iff, not_and_or] simp [not_nonempty_iff_eq_empty] theorem Subsingleton.image2 (hs : s.Subsingleton) (ht : t.Subsingleton) (f : α → β → γ) : (image2 f s t).Subsingleton := by rw [← image_prod] apply (hs.prod ht).image theorem image2_inter_subset_left : image2 f (s ∩ s') t ⊆ image2 f s t ∩ image2 f s' t := Monotone.map_inf_le (fun _ _ ↦ image2_subset_right) s s' theorem image2_inter_subset_right : image2 f s (t ∩ t') ⊆ image2 f s t ∩ image2 f s t' := Monotone.map_inf_le (fun _ _ ↦ image2_subset_left) t t' @[simp] theorem image2_singleton_left : image2 f {a} t = f a '' t := ext fun x => by simp @[simp] theorem image2_singleton_right : image2 f s {b} = (fun a => f a b) '' s := ext fun x => by simp theorem image2_singleton : image2 f {a} {b} = {f a b} := by simp @[simp] theorem image2_insert_left : image2 f (insert a s) t = (fun b => f a b) '' t ∪ image2 f s t := by rw [insert_eq, image2_union_left, image2_singleton_left] @[simp] theorem image2_insert_right : image2 f s (insert b t) = (fun a => f a b) '' s ∪ image2 f s t := by rw [insert_eq, image2_union_right, image2_singleton_right] @[congr] theorem image2_congr (h : ∀ a ∈ s, ∀ b ∈ t, f a b = f' a b) : image2 f s t = image2 f' s t := by ext constructor <;> rintro ⟨a, ha, b, hb, rfl⟩ <;> exact ⟨a, ha, b, hb, by rw [h a ha b hb]⟩ /-- A common special case of `image2_congr` -/ theorem image2_congr' (h : ∀ a b, f a b = f' a b) : image2 f s t = image2 f' s t := image2_congr fun a _ b _ => h a b theorem image_image2 (f : α → β → γ) (g : γ → δ) : g '' image2 f s t = image2 (fun a b => g (f a b)) s t := by simp only [← image_prod, image_image] theorem image2_image_left (f : γ → β → δ) (g : α → γ) : image2 f (g '' s) t = image2 (fun a b => f (g a) b) s t := by ext; simp theorem image2_image_right (f : α → γ → δ) (g : β → γ) : image2 f s (g '' t) = image2 (fun a b => f a (g b)) s t := by ext; simp @[simp] theorem image2_left (h : t.Nonempty) : image2 (fun x _ => x) s t = s := by simp [nonempty_def.mp h, Set.ext_iff] @[simp] theorem image2_right (h : s.Nonempty) : image2 (fun _ y => y) s t = t := by simp [nonempty_def.mp h, Set.ext_iff] lemma image2_range (f : α' → β' → γ) (g : α → α') (h : β → β') : image2 f (range g) (range h) = range fun x : α × β ↦ f (g x.1) (h x.2) := by simp_rw [← image_univ, image2_image_left, image2_image_right, ← image_prod, univ_prod_univ] theorem image2_assoc {f : δ → γ → ε} {g : α → β → δ} {f' : α → ε' → ε} {g' : β → γ → ε'} (h_assoc : ∀ a b c, f (g a b) c = f' a (g' b c)) : image2 f (image2 g s t) u = image2 f' s (image2 g' t u) := eq_of_forall_subset_iff fun _ ↦ by simp only [image2_subset_iff, forall_mem_image2, h_assoc] theorem image2_comm {g : β → α → γ} (h_comm : ∀ a b, f a b = g b a) : image2 f s t = image2 g t s := (image2_swap _ _ _).trans <| by simp_rw [h_comm] theorem image2_left_comm {f : α → δ → ε} {g : β → γ → δ} {f' : α → γ → δ'} {g' : β → δ' → ε} (h_left_comm : ∀ a b c, f a (g b c) = g' b (f' a c)) : image2 f s (image2 g t u) = image2 g' t (image2 f' s u) := by rw [image2_swap f', image2_swap f] exact image2_assoc fun _ _ _ => h_left_comm _ _ _ theorem image2_right_comm {f : δ → γ → ε} {g : α → β → δ} {f' : α → γ → δ'} {g' : δ' → β → ε} (h_right_comm : ∀ a b c, f (g a b) c = g' (f' a c) b) : image2 f (image2 g s t) u = image2 g' (image2 f' s u) t := by rw [image2_swap g, image2_swap g'] exact image2_assoc fun _ _ _ => h_right_comm _ _ _ theorem image2_image2_image2_comm {f : ε → ζ → ν} {g : α → β → ε} {h : γ → δ → ζ} {f' : ε' → ζ' → ν} {g' : α → γ → ε'} {h' : β → δ → ζ'} (h_comm : ∀ a b c d, f (g a b) (h c d) = f' (g' a c) (h' b d)) : image2 f (image2 g s t) (image2 h u v) = image2 f' (image2 g' s u) (image2 h' t v) := by ext; constructor · rintro ⟨_, ⟨a, ha, b, hb, rfl⟩, _, ⟨c, hc, d, hd, rfl⟩, rfl⟩ exact ⟨_, ⟨a, ha, c, hc, rfl⟩, _, ⟨b, hb, d, hd, rfl⟩, (h_comm _ _ _ _).symm⟩ · rintro ⟨_, ⟨a, ha, c, hc, rfl⟩, _, ⟨b, hb, d, hd, rfl⟩, rfl⟩ exact ⟨_, ⟨a, ha, b, hb, rfl⟩, _, ⟨c, hc, d, hd, rfl⟩, h_comm _ _ _ _⟩ theorem image_image2_distrib {g : γ → δ} {f' : α' → β' → δ} {g₁ : α → α'} {g₂ : β → β'} (h_distrib : ∀ a b, g (f a b) = f' (g₁ a) (g₂ b)) : (image2 f s t).image g = image2 f' (s.image g₁) (t.image g₂) := by simp_rw [image_image2, image2_image_left, image2_image_right, h_distrib] /-- Symmetric statement to `Set.image2_image_left_comm`. -/ theorem image_image2_distrib_left {g : γ → δ} {f' : α' → β → δ} {g' : α → α'} (h_distrib : ∀ a b, g (f a b) = f' (g' a) b) : (image2 f s t).image g = image2 f' (s.image g') t := (image_image2_distrib h_distrib).trans <| by rw [image_id'] /-- Symmetric statement to `Set.image_image2_right_comm`. -/ theorem image_image2_distrib_right {g : γ → δ} {f' : α → β' → δ} {g' : β → β'} (h_distrib : ∀ a b, g (f a b) = f' a (g' b)) : (image2 f s t).image g = image2 f' s (t.image g') := (image_image2_distrib h_distrib).trans <| by rw [image_id'] /-- Symmetric statement to `Set.image_image2_distrib_left`. -/ theorem image2_image_left_comm {f : α' → β → γ} {g : α → α'} {f' : α → β → δ} {g' : δ → γ} (h_left_comm : ∀ a b, f (g a) b = g' (f' a b)) : image2 f (s.image g) t = (image2 f' s t).image g' := (image_image2_distrib_left fun a b => (h_left_comm a b).symm).symm /-- Symmetric statement to `Set.image_image2_distrib_right`. -/ theorem image_image2_right_comm {f : α → β' → γ} {g : β → β'} {f' : α → β → δ} {g' : δ → γ} (h_right_comm : ∀ a b, f a (g b) = g' (f' a b)) : image2 f s (t.image g) = (image2 f' s t).image g' := (image_image2_distrib_right fun a b => (h_right_comm a b).symm).symm /-- The other direction does not hold because of the `s`-`s` cross terms on the RHS. -/ theorem image2_distrib_subset_left {f : α → δ → ε} {g : β → γ → δ} {f₁ : α → β → β'} {f₂ : α → γ → γ'} {g' : β' → γ' → ε} (h_distrib : ∀ a b c, f a (g b c) = g' (f₁ a b) (f₂ a c)) : image2 f s (image2 g t u) ⊆ image2 g' (image2 f₁ s t) (image2 f₂ s u) := by rintro _ ⟨a, ha, _, ⟨b, hb, c, hc, rfl⟩, rfl⟩ rw [h_distrib] exact mem_image2_of_mem (mem_image2_of_mem ha hb) (mem_image2_of_mem ha hc) /-- The other direction does not hold because of the `u`-`u` cross terms on the RHS. -/ theorem image2_distrib_subset_right {f : δ → γ → ε} {g : α → β → δ} {f₁ : α → γ → α'} {f₂ : β → γ → β'} {g' : α' → β' → ε} (h_distrib : ∀ a b c, f (g a b) c = g' (f₁ a c) (f₂ b c)) : image2 f (image2 g s t) u ⊆ image2 g' (image2 f₁ s u) (image2 f₂ t u) := by rintro _ ⟨_, ⟨a, ha, b, hb, rfl⟩, c, hc, rfl⟩ rw [h_distrib] exact mem_image2_of_mem (mem_image2_of_mem ha hc) (mem_image2_of_mem hb hc) theorem image_image2_antidistrib {g : γ → δ} {f' : β' → α' → δ} {g₁ : β → β'} {g₂ : α → α'} (h_antidistrib : ∀ a b, g (f a b) = f' (g₁ b) (g₂ a)) : (image2 f s t).image g = image2 f' (t.image g₁) (s.image g₂) := by rw [image2_swap f] exact image_image2_distrib fun _ _ => h_antidistrib _ _ /-- Symmetric statement to `Set.image2_image_left_anticomm`. -/ theorem image_image2_antidistrib_left {g : γ → δ} {f' : β' → α → δ} {g' : β → β'} (h_antidistrib : ∀ a b, g (f a b) = f' (g' b) a) : (image2 f s t).image g = image2 f' (t.image g') s := (image_image2_antidistrib h_antidistrib).trans <| by rw [image_id'] /-- Symmetric statement to `Set.image_image2_right_anticomm`. -/ theorem image_image2_antidistrib_right {g : γ → δ} {f' : β → α' → δ} {g' : α → α'} (h_antidistrib : ∀ a b, g (f a b) = f' b (g' a)) : (image2 f s t).image g = image2 f' t (s.image g') := (image_image2_antidistrib h_antidistrib).trans <| by rw [image_id'] /-- Symmetric statement to `Set.image_image2_antidistrib_left`. -/ theorem image2_image_left_anticomm {f : α' → β → γ} {g : α → α'} {f' : β → α → δ} {g' : δ → γ} (h_left_anticomm : ∀ a b, f (g a) b = g' (f' b a)) : image2 f (s.image g) t = (image2 f' t s).image g' := (image_image2_antidistrib_left fun a b => (h_left_anticomm b a).symm).symm /-- Symmetric statement to `Set.image_image2_antidistrib_right`. -/ theorem image_image2_right_anticomm {f : α → β' → γ} {g : β → β'} {f' : β → α → δ} {g' : δ → γ} (h_right_anticomm : ∀ a b, f a (g b) = g' (f' b a)) : image2 f s (t.image g) = (image2 f' t s).image g' := (image_image2_antidistrib_right fun a b => (h_right_anticomm b a).symm).symm /-- If `a` is a left identity for `f : α → β → β`, then `{a}` is a left identity for `Set.image2 f`. -/ lemma image2_left_identity {f : α → β → β} {a : α} (h : ∀ b, f a b = b) (t : Set β) : image2 f {a} t = t := by rw [image2_singleton_left, show f a = id from funext h, image_id] /-- If `b` is a right identity for `f : α → β → α`, then `{b}` is a right identity for `Set.image2 f`. -/ lemma image2_right_identity {f : α → β → α} {b : β} (h : ∀ a, f a b = a) (s : Set α) : image2 f s {b} = s := by rw [image2_singleton_right, funext h, image_id'] theorem image2_inter_union_subset_union : image2 f (s ∩ s') (t ∪ t') ⊆ image2 f s t ∪ image2 f s' t' := by rw [image2_union_right] exact union_subset_union (image2_subset_right inter_subset_left) (image2_subset_right inter_subset_right)
theorem image2_union_inter_subset_union : image2 f (s ∪ s') (t ∩ t') ⊆ image2 f s t ∪ image2 f s' t' := by rw [image2_union_left] exact union_subset_union (image2_subset_left inter_subset_left)
Mathlib/Data/Set/NAry.lean
317
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/- Copyright (c) 2023 Joël Riou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Joël Riou, Kim Morrison, Adam Topaz -/ import Mathlib.CategoryTheory.Limits.Preserves.Shapes.BinaryProducts import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Products import Mathlib.CategoryTheory.Limits.ConcreteCategory.Basic import Mathlib.CategoryTheory.Limits.Types.Shapes import Mathlib.CategoryTheory.Limits.Shapes.Multiequalizer import Mathlib.CategoryTheory.Limits.Shapes.Kernels import Mathlib.CategoryTheory.ConcreteCategory.EpiMono import Mathlib.CategoryTheory.Limits.Constructions.EpiMono /-! # Limits in concrete categories In this file, we combine the description of limits in `Types` and the API about the preservation of products and pullbacks in order to describe these limits in a concrete category `C`. If `F : J → C` is a family of objects in `C`, we define a bijection `Limits.Concrete.productEquiv F : ToType (∏ᶜ F) ≃ ∀ j, ToType (F j)`. Similarly, if `f₁ : X₁ ⟶ S` and `f₂ : X₂ ⟶ S` are two morphisms, the elements in `pullback f₁ f₂` are identified by `Limits.Concrete.pullbackEquiv` to compatible tuples of elements in `X₁ × X₂`. Some results are also obtained for the terminal object, binary products, wide-pullbacks, wide-pushouts, multiequalizers and cokernels. -/ universe w w' v u t r namespace CategoryTheory.Limits.Concrete variable {C : Type u} [Category.{v} C] section Products section ProductEquiv variable {FC : C → C → Type*} {CC : C → Type max w v} [∀ X Y, FunLike (FC X Y) (CC X) (CC Y)] variable [ConcreteCategory.{max w v} C FC] {J : Type w} (F : J → C) [HasProduct F] [PreservesLimit (Discrete.functor F) (forget C)] /-- The equivalence `ToType (∏ᶜ F) ≃ ∀ j, ToType (F j)` if `F : J → C` is a family of objects in a concrete category `C`. -/ noncomputable def productEquiv : ToType (∏ᶜ F) ≃ ∀ j, ToType (F j) := ((PreservesProduct.iso (forget C) F) ≪≫ (Types.productIso.{w, v} fun j => ToType (F j))).toEquiv @[simp] lemma productEquiv_apply_apply (x : ToType (∏ᶜ F)) (j : J) : productEquiv F x j = Pi.π F j x := congr_fun (piComparison_comp_π (forget C) F j) x @[simp] lemma productEquiv_symm_apply_π (x : ∀ j, ToType (F j)) (j : J) : Pi.π F j ((productEquiv F).symm x) = x j := by rw [← productEquiv_apply_apply, Equiv.apply_symm_apply] end ProductEquiv section ProductExt variable {J : Type w} (f : J → C) [HasProduct f] {D : Type t} [Category.{r} D] variable {FD : D → D → Type*} {DD : D → Type max w r} [∀ X Y, FunLike (FD X Y) (DD X) (DD Y)] variable [ConcreteCategory.{max w r} D FD] (F : C ⥤ D) [PreservesLimit (Discrete.functor f) F] [HasProduct fun j => F.obj (f j)] [PreservesLimitsOfShape WalkingCospan (forget D)] [PreservesLimit (Discrete.functor fun b ↦ F.toPrefunctor.obj (f b)) (forget D)] lemma Pi.map_ext (x y : ToType (F.obj (∏ᶜ f : C))) (h : ∀ i, F.map (Pi.π f i) x = F.map (Pi.π f i) y) : x = y := by apply ConcreteCategory.injective_of_mono_of_preservesPullback (PreservesProduct.iso F f).hom apply Concrete.limit_ext _ (piComparison F _ x) (piComparison F _ y) intro ⟨j⟩ rw [← ConcreteCategory.comp_apply, ← ConcreteCategory.comp_apply, piComparison_comp_π] exact h j end ProductExt end Products section Terminal variable {FC : C → C → Type*} {CC : C → Type w} [∀ X Y, FunLike (FC X Y) (CC X) (CC Y)] variable [ConcreteCategory.{w} C FC] /-- If `forget C` preserves terminals and `X` is terminal, then `ToType X` is a singleton. -/ noncomputable def uniqueOfTerminalOfPreserves [PreservesLimit (Functor.empty.{0} C) (forget C)] (X : C) (h : IsTerminal X) : Unique (ToType X) := Types.isTerminalEquivUnique (ToType X) <| IsTerminal.isTerminalObj (forget C) X h /-- If `forget C` reflects terminals and `ToType X` is a singleton, then `X` is terminal. -/ noncomputable def terminalOfUniqueOfReflects [ReflectsLimit (Functor.empty.{0} C) (forget C)] (X : C) (h : Unique (ToType X)) : IsTerminal X := IsTerminal.isTerminalOfObj (forget C) X <| (Types.isTerminalEquivUnique (ToType X)).symm h /-- The equivalence `IsTerminal X ≃ Unique (ToType X)` if the forgetful functor preserves and reflects terminals. -/ noncomputable def terminalIffUnique [PreservesLimit (Functor.empty.{0} C) (forget C)] [ReflectsLimit (Functor.empty.{0} C) (forget C)] (X : C) : IsTerminal X ≃ Unique (ToType X) := (IsTerminal.isTerminalIffObj (forget C) X).trans <| Types.isTerminalEquivUnique _ variable (C) variable [HasTerminal C] [PreservesLimit (Functor.empty.{0} C) (forget C)] /-- The equivalence `ToType (⊤_ C) ≃ PUnit` when `C` is a concrete category. -/ noncomputable def terminalEquiv : ToType (⊤_ C) ≃ PUnit := (PreservesTerminal.iso (forget C) ≪≫ Types.terminalIso).toEquiv noncomputable instance : Unique (ToType (⊤_ C)) where default := (terminalEquiv C).symm PUnit.unit uniq _ := (terminalEquiv C).injective (Subsingleton.elim _ _) end Terminal section Initial variable {FC : C → C → Type*} {CC : C → Type w} [∀ X Y, FunLike (FC X Y) (CC X) (CC Y)] variable [ConcreteCategory.{w} C FC] /-- If `forget C` preserves initials and `X` is initial, then `ToType X` is empty. -/ lemma empty_of_initial_of_preserves [PreservesColimit (Functor.empty.{0} C) (forget C)] (X : C) (h : Nonempty (IsInitial X)) : IsEmpty (ToType X) := by rw [← Types.initial_iff_empty] exact Nonempty.map (IsInitial.isInitialObj (forget C) _) h /-- If `forget C` reflects initials and `ToType X` is empty, then `X` is initial. -/ lemma initial_of_empty_of_reflects [ReflectsColimit (Functor.empty.{0} C) (forget C)] (X : C) (h : IsEmpty (ToType X)) : Nonempty (IsInitial X) := Nonempty.map (IsInitial.isInitialOfObj (forget C) _) <| (Types.initial_iff_empty (ToType X)).mpr h /-- If `forget C` preserves and reflects initials, then `X` is initial if and only if `ToType X` is empty. -/ lemma initial_iff_empty_of_preserves_of_reflects [PreservesColimit (Functor.empty.{0} C) (forget C)] [ReflectsColimit (Functor.empty.{0} C) (forget C)] (X : C) : Nonempty (IsInitial X) ↔ IsEmpty (ToType X) := by rw [← Types.initial_iff_empty, (IsInitial.isInitialIffObj (forget C) X).nonempty_congr] rfl end Initial section BinaryProducts variable {FC : C → C → Type*} {CC : C → Type w} [∀ X Y, FunLike (FC X Y) (CC X) (CC Y)] variable [ConcreteCategory.{w} C FC] (X₁ X₂ : C) [HasBinaryProduct X₁ X₂] [PreservesLimit (pair X₁ X₂) (forget C)] /-- The equivalence `ToType (X₁ ⨯ X₂) ≃ (ToType X₁) × (ToType X₂)` if `X₁` and `X₂` are objects in a concrete category `C`. -/ noncomputable def prodEquiv : ToType (X₁ ⨯ X₂) ≃ ToType X₁ × ToType X₂ := (PreservesLimitPair.iso (forget C) X₁ X₂ ≪≫ Types.binaryProductIso _ _).toEquiv @[simp] lemma prodEquiv_apply_fst (x : ToType (X₁ ⨯ X₂)) : (prodEquiv X₁ X₂ x).fst = (Limits.prod.fst : X₁ ⨯ X₂ ⟶ X₁) x := congr_fun (prodComparison_fst (forget C) X₁ X₂) x @[simp] lemma prodEquiv_apply_snd (x : ToType (X₁ ⨯ X₂)) : (prodEquiv X₁ X₂ x).snd = (Limits.prod.snd : X₁ ⨯ X₂ ⟶ X₂) x := congr_fun (prodComparison_snd (forget C) X₁ X₂) x
@[simp] lemma prodEquiv_symm_apply_fst (x : ToType X₁ × ToType X₂) : (Limits.prod.fst : X₁ ⨯ X₂ ⟶ X₁) ((prodEquiv X₁ X₂).symm x) = x.1 := by obtain ⟨y, rfl⟩ := (prodEquiv X₁ X₂).surjective x
Mathlib/CategoryTheory/Limits/Shapes/ConcreteCategory.lean
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/- Copyright (c) 2018 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Reid Barton, Mario Carneiro, Kim Morrison, Floris van Doorn -/ import Mathlib.CategoryTheory.Limits.IsLimit import Mathlib.CategoryTheory.Category.ULift import Mathlib.CategoryTheory.EssentiallySmall import Mathlib.CategoryTheory.Functor.EpiMono import Mathlib.Logic.Equiv.Basic /-! # Existence of limits and colimits In `CategoryTheory.Limits.IsLimit` we defined `IsLimit c`, the data showing that a cone `c` is a limit cone. The two main structures defined in this file are: * `LimitCone F`, which consists of a choice of cone for `F` and the fact it is a limit cone, and * `HasLimit F`, asserting the mere existence of some limit cone for `F`. `HasLimit` is a propositional typeclass (it's important that it is a proposition merely asserting the existence of a limit, as otherwise we would have non-defeq problems from incompatible instances). While `HasLimit` only asserts the existence of a limit cone, we happily use the axiom of choice in mathlib, so there are convenience functions all depending on `HasLimit F`: * `limit F : C`, producing some limit object (of course all such are isomorphic) * `limit.π F j : limit F ⟶ F.obj j`, the morphisms out of the limit, * `limit.lift F c : c.pt ⟶ limit F`, the universal morphism from any other `c : Cone F`, etc. Key to using the `HasLimit` interface is that there is an `@[ext]` lemma stating that to check `f = g`, for `f g : Z ⟶ limit F`, it suffices to check `f ≫ limit.π F j = g ≫ limit.π F j` for every `j`. This, combined with `@[simp]` lemmas, makes it possible to prove many easy facts about limits using automation (e.g. `tidy`). There are abbreviations `HasLimitsOfShape J C` and `HasLimits C` asserting the existence of classes of limits. Later more are introduced, for finite limits, special shapes of limits, etc. Ideally, many results about limits should be stated first in terms of `IsLimit`, and then a result in terms of `HasLimit` derived from this. At this point, however, this is far from uniformly achieved in mathlib --- often statements are only written in terms of `HasLimit`. ## Implementation At present we simply say everything twice, in order to handle both limits and colimits. It would be highly desirable to have some automation support, e.g. a `@[dualize]` attribute that behaves similarly to `@[to_additive]`. ## References * [Stacks: Limits and colimits](https://stacks.math.columbia.edu/tag/002D) -/ noncomputable section open CategoryTheory CategoryTheory.Category CategoryTheory.Functor Opposite namespace CategoryTheory.Limits -- morphism levels before object levels. See note [CategoryTheory universes]. universe v₁ u₁ v₂ u₂ v₃ u₃ v v' v'' u u' u'' variable {J : Type u₁} [Category.{v₁} J] {K : Type u₂} [Category.{v₂} K] variable {C : Type u} [Category.{v} C] variable {F : J ⥤ C} section Limit /-- `LimitCone F` contains a cone over `F` together with the information that it is a limit. -/ structure LimitCone (F : J ⥤ C) where /-- The cone itself -/ cone : Cone F /-- The proof that is the limit cone -/ isLimit : IsLimit cone /-- `HasLimit F` represents the mere existence of a limit for `F`. -/ class HasLimit (F : J ⥤ C) : Prop where mk' :: /-- There is some limit cone for `F` -/ exists_limit : Nonempty (LimitCone F) theorem HasLimit.mk {F : J ⥤ C} (d : LimitCone F) : HasLimit F := ⟨Nonempty.intro d⟩ /-- Use the axiom of choice to extract explicit `LimitCone F` from `HasLimit F`. -/ def getLimitCone (F : J ⥤ C) [HasLimit F] : LimitCone F := Classical.choice <| HasLimit.exists_limit variable (J C) /-- `C` has limits of shape `J` if there exists a limit for every functor `F : J ⥤ C`. -/ class HasLimitsOfShape : Prop where /-- All functors `F : J ⥤ C` from `J` have limits -/ has_limit : ∀ F : J ⥤ C, HasLimit F := by infer_instance /-- `C` has all limits of size `v₁ u₁` (`HasLimitsOfSize.{v₁ u₁} C`) if it has limits of every shape `J : Type u₁` with `[Category.{v₁} J]`. -/ @[pp_with_univ] class HasLimitsOfSize (C : Type u) [Category.{v} C] : Prop where /-- All functors `F : J ⥤ C` from all small `J` have limits -/ has_limits_of_shape : ∀ (J : Type u₁) [Category.{v₁} J], HasLimitsOfShape J C := by infer_instance /-- `C` has all (small) limits if it has limits of every shape that is as big as its hom-sets. -/ abbrev HasLimits (C : Type u) [Category.{v} C] : Prop := HasLimitsOfSize.{v, v} C theorem HasLimits.has_limits_of_shape {C : Type u} [Category.{v} C] [HasLimits C] (J : Type v) [Category.{v} J] : HasLimitsOfShape J C := HasLimitsOfSize.has_limits_of_shape J variable {J C} -- see Note [lower instance priority] instance (priority := 100) hasLimitOfHasLimitsOfShape {J : Type u₁} [Category.{v₁} J] [HasLimitsOfShape J C] (F : J ⥤ C) : HasLimit F := HasLimitsOfShape.has_limit F -- see Note [lower instance priority] instance (priority := 100) hasLimitsOfShapeOfHasLimits {J : Type u₁} [Category.{v₁} J] [HasLimitsOfSize.{v₁, u₁} C] : HasLimitsOfShape J C := HasLimitsOfSize.has_limits_of_shape J -- Interface to the `HasLimit` class. /-- An arbitrary choice of limit cone for a functor. -/ def limit.cone (F : J ⥤ C) [HasLimit F] : Cone F := (getLimitCone F).cone /-- An arbitrary choice of limit object of a functor. -/ def limit (F : J ⥤ C) [HasLimit F] := (limit.cone F).pt /-- The projection from the limit object to a value of the functor. -/ def limit.π (F : J ⥤ C) [HasLimit F] (j : J) : limit F ⟶ F.obj j := (limit.cone F).π.app j @[reassoc] theorem limit.π_comp_eqToHom (F : J ⥤ C) [HasLimit F] {j j' : J} (hj : j = j') : limit.π F j ≫ eqToHom (by subst hj; rfl) = limit.π F j' := by subst hj simp @[simp] theorem limit.cone_x {F : J ⥤ C} [HasLimit F] : (limit.cone F).pt = limit F := rfl @[simp] theorem limit.cone_π {F : J ⥤ C} [HasLimit F] : (limit.cone F).π.app = limit.π _ := rfl @[reassoc (attr := simp)] theorem limit.w (F : J ⥤ C) [HasLimit F] {j j' : J} (f : j ⟶ j') : limit.π F j ≫ F.map f = limit.π F j' := (limit.cone F).w f /-- Evidence that the arbitrary choice of cone provided by `limit.cone F` is a limit cone. -/ def limit.isLimit (F : J ⥤ C) [HasLimit F] : IsLimit (limit.cone F) := (getLimitCone F).isLimit /-- The morphism from the cone point of any other cone to the limit object. -/ def limit.lift (F : J ⥤ C) [HasLimit F] (c : Cone F) : c.pt ⟶ limit F := (limit.isLimit F).lift c @[simp] theorem limit.isLimit_lift {F : J ⥤ C} [HasLimit F] (c : Cone F) : (limit.isLimit F).lift c = limit.lift F c := rfl @[reassoc (attr := simp)] theorem limit.lift_π {F : J ⥤ C} [HasLimit F] (c : Cone F) (j : J) : limit.lift F c ≫ limit.π F j = c.π.app j := IsLimit.fac _ c j /-- Functoriality of limits. Usually this morphism should be accessed through `lim.map`, but may be needed separately when you have specified limits for the source and target functors, but not necessarily for all functors of shape `J`. -/ def limMap {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) : limit F ⟶ limit G := IsLimit.map _ (limit.isLimit G) α @[reassoc (attr := simp)] theorem limMap_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) (j : J) : limMap α ≫ limit.π G j = limit.π F j ≫ α.app j := limit.lift_π _ j /-- The cone morphism from any cone to the arbitrary choice of limit cone. -/ def limit.coneMorphism {F : J ⥤ C} [HasLimit F] (c : Cone F) : c ⟶ limit.cone F := (limit.isLimit F).liftConeMorphism c @[simp] theorem limit.coneMorphism_hom {F : J ⥤ C} [HasLimit F] (c : Cone F) : (limit.coneMorphism c).hom = limit.lift F c := rfl theorem limit.coneMorphism_π {F : J ⥤ C} [HasLimit F] (c : Cone F) (j : J) : (limit.coneMorphism c).hom ≫ limit.π F j = c.π.app j := by simp @[reassoc (attr := simp)] theorem limit.conePointUniqueUpToIso_hom_comp {F : J ⥤ C} [HasLimit F] {c : Cone F} (hc : IsLimit c) (j : J) : (IsLimit.conePointUniqueUpToIso hc (limit.isLimit _)).hom ≫ limit.π F j = c.π.app j := IsLimit.conePointUniqueUpToIso_hom_comp _ _ _ @[reassoc (attr := simp)] theorem limit.conePointUniqueUpToIso_inv_comp {F : J ⥤ C} [HasLimit F] {c : Cone F} (hc : IsLimit c) (j : J) : (IsLimit.conePointUniqueUpToIso (limit.isLimit _) hc).inv ≫ limit.π F j = c.π.app j := IsLimit.conePointUniqueUpToIso_inv_comp _ _ _ theorem limit.existsUnique {F : J ⥤ C} [HasLimit F] (t : Cone F) : ∃! l : t.pt ⟶ limit F, ∀ j, l ≫ limit.π F j = t.π.app j := (limit.isLimit F).existsUnique _ /-- Given any other limit cone for `F`, the chosen `limit F` is isomorphic to the cone point. -/ def limit.isoLimitCone {F : J ⥤ C} [HasLimit F] (t : LimitCone F) : limit F ≅ t.cone.pt := IsLimit.conePointUniqueUpToIso (limit.isLimit F) t.isLimit @[reassoc (attr := simp)] theorem limit.isoLimitCone_hom_π {F : J ⥤ C} [HasLimit F] (t : LimitCone F) (j : J) : (limit.isoLimitCone t).hom ≫ t.cone.π.app j = limit.π F j := by dsimp [limit.isoLimitCone, IsLimit.conePointUniqueUpToIso] simp @[reassoc (attr := simp)] theorem limit.isoLimitCone_inv_π {F : J ⥤ C} [HasLimit F] (t : LimitCone F) (j : J) : (limit.isoLimitCone t).inv ≫ limit.π F j = t.cone.π.app j := by dsimp [limit.isoLimitCone, IsLimit.conePointUniqueUpToIso] simp @[ext] theorem limit.hom_ext {F : J ⥤ C} [HasLimit F] {X : C} {f f' : X ⟶ limit F} (w : ∀ j, f ≫ limit.π F j = f' ≫ limit.π F j) : f = f' := (limit.isLimit F).hom_ext w @[reassoc (attr := simp)] theorem limit.lift_map {F G : J ⥤ C} [HasLimit F] [HasLimit G] (c : Cone F) (α : F ⟶ G) : limit.lift F c ≫ limMap α = limit.lift G ((Cones.postcompose α).obj c) := by ext rw [assoc, limMap_π, limit.lift_π_assoc, limit.lift_π] rfl @[simp] theorem limit.lift_cone {F : J ⥤ C} [HasLimit F] : limit.lift F (limit.cone F) = 𝟙 (limit F) := (limit.isLimit _).lift_self /-- The isomorphism (in `Type`) between morphisms from a specified object `W` to the limit object, and cones with cone point `W`. -/ def limit.homIso (F : J ⥤ C) [HasLimit F] (W : C) : ULift.{u₁} (W ⟶ limit F : Type v) ≅ F.cones.obj (op W) := (limit.isLimit F).homIso W @[simp] theorem limit.homIso_hom (F : J ⥤ C) [HasLimit F] {W : C} (f : ULift (W ⟶ limit F)) : (limit.homIso F W).hom f = (const J).map f.down ≫ (limit.cone F).π := (limit.isLimit F).homIso_hom f /-- The isomorphism (in `Type`) between morphisms from a specified object `W` to the limit object, and an explicit componentwise description of cones with cone point `W`. -/ def limit.homIso' (F : J ⥤ C) [HasLimit F] (W : C) : ULift.{u₁} (W ⟶ limit F : Type v) ≅ { p : ∀ j, W ⟶ F.obj j // ∀ {j j' : J} (f : j ⟶ j'), p j ≫ F.map f = p j' } := (limit.isLimit F).homIso' W theorem limit.lift_extend {F : J ⥤ C} [HasLimit F] (c : Cone F) {X : C} (f : X ⟶ c.pt) : limit.lift F (c.extend f) = f ≫ limit.lift F c := by aesop_cat /-- If a functor `F` has a limit, so does any naturally isomorphic functor. -/ theorem hasLimit_of_iso {F G : J ⥤ C} [HasLimit F] (α : F ≅ G) : HasLimit G := HasLimit.mk { cone := (Cones.postcompose α.hom).obj (limit.cone F) isLimit := (IsLimit.postcomposeHomEquiv _ _).symm (limit.isLimit F) } @[deprecated (since := "2025-03-03")] alias hasLimitOfIso := hasLimit_of_iso theorem hasLimit_iff_of_iso {F G : J ⥤ C} (α : F ≅ G) : HasLimit F ↔ HasLimit G := ⟨fun _ ↦ hasLimit_of_iso α, fun _ ↦ hasLimit_of_iso α.symm⟩ -- See the construction of limits from products and equalizers -- for an example usage. /-- If a functor `G` has the same collection of cones as a functor `F` which has a limit, then `G` also has a limit. -/ theorem HasLimit.ofConesIso {J K : Type u₁} [Category.{v₁} J] [Category.{v₂} K] (F : J ⥤ C) (G : K ⥤ C) (h : F.cones ≅ G.cones) [HasLimit F] : HasLimit G := HasLimit.mk ⟨_, IsLimit.ofNatIso (IsLimit.natIso (limit.isLimit F) ≪≫ h)⟩ /-- The limits of `F : J ⥤ C` and `G : J ⥤ C` are isomorphic, if the functors are naturally isomorphic. -/ def HasLimit.isoOfNatIso {F G : J ⥤ C} [HasLimit F] [HasLimit G] (w : F ≅ G) : limit F ≅ limit G := IsLimit.conePointsIsoOfNatIso (limit.isLimit F) (limit.isLimit G) w @[reassoc (attr := simp)] theorem HasLimit.isoOfNatIso_hom_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (w : F ≅ G) (j : J) : (HasLimit.isoOfNatIso w).hom ≫ limit.π G j = limit.π F j ≫ w.hom.app j := IsLimit.conePointsIsoOfNatIso_hom_comp _ _ _ _ @[reassoc (attr := simp)] theorem HasLimit.isoOfNatIso_inv_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (w : F ≅ G) (j : J) : (HasLimit.isoOfNatIso w).inv ≫ limit.π F j = limit.π G j ≫ w.inv.app j := IsLimit.conePointsIsoOfNatIso_inv_comp _ _ _ _ @[reassoc (attr := simp)] theorem HasLimit.lift_isoOfNatIso_hom {F G : J ⥤ C} [HasLimit F] [HasLimit G] (t : Cone F) (w : F ≅ G) : limit.lift F t ≫ (HasLimit.isoOfNatIso w).hom = limit.lift G ((Cones.postcompose w.hom).obj _) := IsLimit.lift_comp_conePointsIsoOfNatIso_hom _ _ _ @[reassoc (attr := simp)] theorem HasLimit.lift_isoOfNatIso_inv {F G : J ⥤ C} [HasLimit F] [HasLimit G] (t : Cone G) (w : F ≅ G) : limit.lift G t ≫ (HasLimit.isoOfNatIso w).inv = limit.lift F ((Cones.postcompose w.inv).obj _) := IsLimit.lift_comp_conePointsIsoOfNatIso_inv _ _ _ /-- The limits of `F : J ⥤ C` and `G : K ⥤ C` are isomorphic, if there is an equivalence `e : J ≌ K` making the triangle commute up to natural isomorphism. -/ def HasLimit.isoOfEquivalence {F : J ⥤ C} [HasLimit F] {G : K ⥤ C} [HasLimit G] (e : J ≌ K) (w : e.functor ⋙ G ≅ F) : limit F ≅ limit G := IsLimit.conePointsIsoOfEquivalence (limit.isLimit F) (limit.isLimit G) e w @[simp] theorem HasLimit.isoOfEquivalence_hom_π {F : J ⥤ C} [HasLimit F] {G : K ⥤ C} [HasLimit G] (e : J ≌ K) (w : e.functor ⋙ G ≅ F) (k : K) : (HasLimit.isoOfEquivalence e w).hom ≫ limit.π G k = limit.π F (e.inverse.obj k) ≫ w.inv.app (e.inverse.obj k) ≫ G.map (e.counit.app k) := by simp only [HasLimit.isoOfEquivalence, IsLimit.conePointsIsoOfEquivalence_hom] dsimp simp @[simp] theorem HasLimit.isoOfEquivalence_inv_π {F : J ⥤ C} [HasLimit F] {G : K ⥤ C} [HasLimit G] (e : J ≌ K) (w : e.functor ⋙ G ≅ F) (j : J) : (HasLimit.isoOfEquivalence e w).inv ≫ limit.π F j = limit.π G (e.functor.obj j) ≫ w.hom.app j := by simp only [HasLimit.isoOfEquivalence, IsLimit.conePointsIsoOfEquivalence_hom] dsimp simp section Pre variable (F) variable [HasLimit F] (E : K ⥤ J) [HasLimit (E ⋙ F)] /-- The canonical morphism from the limit of `F` to the limit of `E ⋙ F`. -/ def limit.pre : limit F ⟶ limit (E ⋙ F) := limit.lift (E ⋙ F) ((limit.cone F).whisker E) @[reassoc (attr := simp)] theorem limit.pre_π (k : K) : limit.pre F E ≫ limit.π (E ⋙ F) k = limit.π F (E.obj k) := by erw [IsLimit.fac] rfl @[simp] theorem limit.lift_pre (c : Cone F) : limit.lift F c ≫ limit.pre F E = limit.lift (E ⋙ F) (c.whisker E) := by ext; simp variable {L : Type u₃} [Category.{v₃} L] variable (D : L ⥤ K) @[simp] theorem limit.pre_pre [h : HasLimit (D ⋙ E ⋙ F)] : haveI : HasLimit ((D ⋙ E) ⋙ F) := h limit.pre F E ≫ limit.pre (E ⋙ F) D = limit.pre F (D ⋙ E) := by haveI : HasLimit ((D ⋙ E) ⋙ F) := h ext j; erw [assoc, limit.pre_π, limit.pre_π, limit.pre_π]; rfl variable {E F} /-- - If we have particular limit cones available for `E ⋙ F` and for `F`, we obtain a formula for `limit.pre F E`. -/ theorem limit.pre_eq (s : LimitCone (E ⋙ F)) (t : LimitCone F) : limit.pre F E = (limit.isoLimitCone t).hom ≫ s.isLimit.lift (t.cone.whisker E) ≫ (limit.isoLimitCone s).inv := by aesop_cat end Pre section Post variable {D : Type u'} [Category.{v'} D] variable (F : J ⥤ C) [HasLimit F] (G : C ⥤ D) [HasLimit (F ⋙ G)] /-- The canonical morphism from `G` applied to the limit of `F` to the limit of `F ⋙ G`. -/ def limit.post : G.obj (limit F) ⟶ limit (F ⋙ G) := limit.lift (F ⋙ G) (G.mapCone (limit.cone F)) @[reassoc (attr := simp)] theorem limit.post_π (j : J) : limit.post F G ≫ limit.π (F ⋙ G) j = G.map (limit.π F j) := by erw [IsLimit.fac] rfl @[simp] theorem limit.lift_post (c : Cone F) : G.map (limit.lift F c) ≫ limit.post F G = limit.lift (F ⋙ G) (G.mapCone c) := by ext rw [assoc, limit.post_π, ← G.map_comp, limit.lift_π, limit.lift_π] rfl @[simp] theorem limit.post_post {E : Type u''} [Category.{v''} E] (H : D ⥤ E) [h : HasLimit ((F ⋙ G) ⋙ H)] : -- H G (limit F) ⟶ H (limit (F ⋙ G)) ⟶ limit ((F ⋙ G) ⋙ H) equals -- H G (limit F) ⟶ limit (F ⋙ (G ⋙ H)) haveI : HasLimit (F ⋙ G ⋙ H) := h H.map (limit.post F G) ≫ limit.post (F ⋙ G) H = limit.post F (G ⋙ H) := by haveI : HasLimit (F ⋙ G ⋙ H) := h ext; erw [assoc, limit.post_π, ← H.map_comp, limit.post_π, limit.post_π]; rfl end Post theorem limit.pre_post {D : Type u'} [Category.{v'} D] (E : K ⥤ J) (F : J ⥤ C) (G : C ⥤ D) [HasLimit F] [HasLimit (E ⋙ F)] [HasLimit (F ⋙ G)] [h : HasLimit ((E ⋙ F) ⋙ G)] :-- G (limit F) ⟶ G (limit (E ⋙ F)) ⟶ limit ((E ⋙ F) ⋙ G) vs -- G (limit F) ⟶ limit F ⋙ G ⟶ limit (E ⋙ (F ⋙ G)) or haveI : HasLimit (E ⋙ F ⋙ G) := h G.map (limit.pre F E) ≫ limit.post (E ⋙ F) G = limit.post F G ≫ limit.pre (F ⋙ G) E := by haveI : HasLimit (E ⋙ F ⋙ G) := h ext; erw [assoc, limit.post_π, ← G.map_comp, limit.pre_π, assoc, limit.pre_π, limit.post_π] open CategoryTheory.Equivalence instance hasLimitEquivalenceComp (e : K ≌ J) [HasLimit F] : HasLimit (e.functor ⋙ F) := HasLimit.mk { cone := Cone.whisker e.functor (limit.cone F) isLimit := IsLimit.whiskerEquivalence (limit.isLimit F) e } -- not entirely sure why this is needed /-- If a `E ⋙ F` has a limit, and `E` is an equivalence, we can construct a limit of `F`. -/ theorem hasLimitOfEquivalenceComp (e : K ≌ J) [HasLimit (e.functor ⋙ F)] : HasLimit F := by haveI : HasLimit (e.inverse ⋙ e.functor ⋙ F) := Limits.hasLimitEquivalenceComp e.symm apply hasLimit_of_iso (e.invFunIdAssoc F) -- `hasLimitCompEquivalence` and `hasLimitOfCompEquivalence` -- are proved in `CategoryTheory/Adjunction/Limits.lean`. section LimFunctor variable [HasLimitsOfShape J C] section /-- `limit F` is functorial in `F`, when `C` has all limits of shape `J`. -/ @[simps] def lim : (J ⥤ C) ⥤ C where obj F := limit F map α := limMap α map_id F := by apply Limits.limit.hom_ext; intro j simp map_comp α β := by apply Limits.limit.hom_ext; intro j simp [assoc] end variable {G : J ⥤ C} (α : F ⟶ G) theorem limMap_eq : limMap α = lim.map α := rfl theorem limit.map_pre [HasLimitsOfShape K C] (E : K ⥤ J) : lim.map α ≫ limit.pre G E = limit.pre F E ≫ lim.map (whiskerLeft E α) := by ext simp theorem limit.map_pre' [HasLimitsOfShape K C] (F : J ⥤ C) {E₁ E₂ : K ⥤ J} (α : E₁ ⟶ E₂) : limit.pre F E₂ = limit.pre F E₁ ≫ lim.map (whiskerRight α F) := by ext1; simp [← category.assoc] theorem limit.id_pre (F : J ⥤ C) : limit.pre F (𝟭 _) = lim.map (Functor.leftUnitor F).inv := by aesop_cat theorem limit.map_post {D : Type u'} [Category.{v'} D] [HasLimitsOfShape J D] (H : C ⥤ D) : /- H (limit F) ⟶ H (limit G) ⟶ limit (G ⋙ H) vs H (limit F) ⟶ limit (F ⋙ H) ⟶ limit (G ⋙ H) -/ H.map (limMap α) ≫ limit.post G H = limit.post F H ≫ limMap (whiskerRight α H) := by ext simp only [whiskerRight_app, limMap_π, assoc, limit.post_π_assoc, limit.post_π, ← H.map_comp] /-- The isomorphism between morphisms from `W` to the cone point of the limit cone for `F` and cones over `F` with cone point `W` is natural in `F`. -/ def limYoneda : lim ⋙ yoneda ⋙ (whiskeringRight _ _ _).obj uliftFunctor.{u₁} ≅ CategoryTheory.cones J C := NatIso.ofComponents fun F => NatIso.ofComponents fun W => limit.homIso F (unop W) /-- The constant functor and limit functor are adjoint to each other -/ def constLimAdj : (const J : C ⥤ J ⥤ C) ⊣ lim := Adjunction.mk' { homEquiv := fun c g ↦ { toFun := fun f => limit.lift _ ⟨c, f⟩ invFun := fun f => { app := fun _ => f ≫ limit.π _ _ } left_inv := by aesop_cat right_inv := by aesop_cat } unit := { app := fun _ => limit.lift _ ⟨_, 𝟙 _⟩ } counit := { app := fun g => { app := limit.π _ } } } instance : IsRightAdjoint (lim : (J ⥤ C) ⥤ C) := ⟨_, ⟨constLimAdj⟩⟩ end LimFunctor instance limMap_mono' {F G : J ⥤ C} [HasLimitsOfShape J C] (α : F ⟶ G) [Mono α] : Mono (limMap α) := (lim : (J ⥤ C) ⥤ C).map_mono α instance limMap_mono {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) [∀ j, Mono (α.app j)] : Mono (limMap α) := ⟨fun {Z} u v h => limit.hom_ext fun j => (cancel_mono (α.app j)).1 <| by simpa using h =≫ limit.π _ j⟩ section Adjunction variable {L : (J ⥤ C) ⥤ C} (adj : Functor.const _ ⊣ L) /- The fact that the existence of limits of shape `J` is equivalent to the existence of a right adjoint to the constant functor `C ⥤ (J ⥤ C)` is obtained in the file `Mathlib.CategoryTheory.Limits.ConeCategory`: see the lemma `hasLimitsOfShape_iff_isLeftAdjoint_const`. In the definitions below, given an adjunction `adj : Functor.const _ ⊣ (L : (J ⥤ C) ⥤ C)`, we directly construct a limit cone for any `F : J ⥤ C`. -/ /-- The limit cone obtained from a right adjoint of the constant functor. -/ @[simps] noncomputable def coneOfAdj (F : J ⥤ C) : Cone F where pt := L.obj F π := adj.counit.app F /-- The cones defined by `coneOfAdj` are limit cones. -/ @[simps] def isLimitConeOfAdj (F : J ⥤ C) : IsLimit (coneOfAdj adj F) where lift s := adj.homEquiv _ _ s.π fac s j := by have eq := NatTrans.congr_app (adj.counit.naturality s.π) j have eq' := NatTrans.congr_app (adj.left_triangle_components s.pt) j dsimp at eq eq' ⊢ rw [adj.homEquiv_unit, assoc, eq, reassoc_of% eq'] uniq s m hm := (adj.homEquiv _ _).symm.injective (by ext j; simpa using hm j) end Adjunction /-- We can transport limits of shape `J` along an equivalence `J ≌ J'`. -/ theorem hasLimitsOfShape_of_equivalence {J' : Type u₂} [Category.{v₂} J'] (e : J ≌ J') [HasLimitsOfShape J C] : HasLimitsOfShape J' C := by constructor intro F apply hasLimitOfEquivalenceComp e variable (C) /-- A category that has larger limits also has smaller limits. -/ theorem hasLimitsOfSizeOfUnivLE [UnivLE.{v₂, v₁}] [UnivLE.{u₂, u₁}] [HasLimitsOfSize.{v₁, u₁} C] : HasLimitsOfSize.{v₂, u₂} C where has_limits_of_shape J {_} := hasLimitsOfShape_of_equivalence ((ShrinkHoms.equivalence J).trans <| Shrink.equivalence _).symm /-- `hasLimitsOfSizeShrink.{v u} C` tries to obtain `HasLimitsOfSize.{v u} C` from some other `HasLimitsOfSize C`. -/ theorem hasLimitsOfSizeShrink [HasLimitsOfSize.{max v₁ v₂, max u₁ u₂} C] : HasLimitsOfSize.{v₁, u₁} C := hasLimitsOfSizeOfUnivLE.{max v₁ v₂, max u₁ u₂} C instance (priority := 100) hasSmallestLimitsOfHasLimits [HasLimits C] : HasLimitsOfSize.{0, 0} C := hasLimitsOfSizeShrink.{0, 0} C end Limit section Colimit /-- `ColimitCocone F` contains a cocone over `F` together with the information that it is a colimit. -/ structure ColimitCocone (F : J ⥤ C) where /-- The cocone itself -/ cocone : Cocone F /-- The proof that it is the colimit cocone -/ isColimit : IsColimit cocone /-- `HasColimit F` represents the mere existence of a colimit for `F`. -/ class HasColimit (F : J ⥤ C) : Prop where mk' :: /-- There exists a colimit for `F` -/ exists_colimit : Nonempty (ColimitCocone F) theorem HasColimit.mk {F : J ⥤ C} (d : ColimitCocone F) : HasColimit F := ⟨Nonempty.intro d⟩ /-- Use the axiom of choice to extract explicit `ColimitCocone F` from `HasColimit F`. -/ def getColimitCocone (F : J ⥤ C) [HasColimit F] : ColimitCocone F := Classical.choice <| HasColimit.exists_colimit variable (J C) /-- `C` has colimits of shape `J` if there exists a colimit for every functor `F : J ⥤ C`. -/ class HasColimitsOfShape : Prop where /-- All `F : J ⥤ C` have colimits for a fixed `J` -/ has_colimit : ∀ F : J ⥤ C, HasColimit F := by infer_instance /-- `C` has all colimits of size `v₁ u₁` (`HasColimitsOfSize.{v₁ u₁} C`) if it has colimits of every shape `J : Type u₁` with `[Category.{v₁} J]`. -/ @[pp_with_univ] class HasColimitsOfSize (C : Type u) [Category.{v} C] : Prop where /-- All `F : J ⥤ C` have colimits for all small `J` -/ has_colimits_of_shape : ∀ (J : Type u₁) [Category.{v₁} J], HasColimitsOfShape J C := by infer_instance /-- `C` has all (small) colimits if it has colimits of every shape that is as big as its hom-sets. -/ abbrev HasColimits (C : Type u) [Category.{v} C] : Prop := HasColimitsOfSize.{v, v} C theorem HasColimits.hasColimitsOfShape {C : Type u} [Category.{v} C] [HasColimits C] (J : Type v) [Category.{v} J] : HasColimitsOfShape J C := HasColimitsOfSize.has_colimits_of_shape J variable {J C} -- see Note [lower instance priority] instance (priority := 100) hasColimitOfHasColimitsOfShape {J : Type u₁} [Category.{v₁} J] [HasColimitsOfShape J C] (F : J ⥤ C) : HasColimit F := HasColimitsOfShape.has_colimit F -- see Note [lower instance priority] instance (priority := 100) hasColimitsOfShapeOfHasColimitsOfSize {J : Type u₁} [Category.{v₁} J] [HasColimitsOfSize.{v₁, u₁} C] : HasColimitsOfShape J C := HasColimitsOfSize.has_colimits_of_shape J -- Interface to the `HasColimit` class. /-- An arbitrary choice of colimit cocone of a functor. -/ def colimit.cocone (F : J ⥤ C) [HasColimit F] : Cocone F := (getColimitCocone F).cocone /-- An arbitrary choice of colimit object of a functor. -/ def colimit (F : J ⥤ C) [HasColimit F] := (colimit.cocone F).pt /-- The coprojection from a value of the functor to the colimit object. -/ def colimit.ι (F : J ⥤ C) [HasColimit F] (j : J) : F.obj j ⟶ colimit F := (colimit.cocone F).ι.app j @[reassoc] theorem colimit.eqToHom_comp_ι (F : J ⥤ C) [HasColimit F] {j j' : J} (hj : j = j') : eqToHom (by subst hj; rfl) ≫ colimit.ι F j = colimit.ι F j' := by subst hj simp @[simp] theorem colimit.cocone_ι {F : J ⥤ C} [HasColimit F] (j : J) : (colimit.cocone F).ι.app j = colimit.ι _ j := rfl @[simp] theorem colimit.cocone_x {F : J ⥤ C} [HasColimit F] : (colimit.cocone F).pt = colimit F := rfl @[reassoc (attr := simp)] theorem colimit.w (F : J ⥤ C) [HasColimit F] {j j' : J} (f : j ⟶ j') : F.map f ≫ colimit.ι F j' = colimit.ι F j := (colimit.cocone F).w f /-- Evidence that the arbitrary choice of cocone is a colimit cocone. -/ def colimit.isColimit (F : J ⥤ C) [HasColimit F] : IsColimit (colimit.cocone F) := (getColimitCocone F).isColimit /-- The morphism from the colimit object to the cone point of any other cocone. -/ def colimit.desc (F : J ⥤ C) [HasColimit F] (c : Cocone F) : colimit F ⟶ c.pt := (colimit.isColimit F).desc c @[simp] theorem colimit.isColimit_desc {F : J ⥤ C} [HasColimit F] (c : Cocone F) : (colimit.isColimit F).desc c = colimit.desc F c := rfl /-- We have lots of lemmas describing how to simplify `colimit.ι F j ≫ _`, and combined with `colimit.ext` we rely on these lemmas for many calculations. However, since `Category.assoc` is a `@[simp]` lemma, often expressions are right associated, and it's hard to apply these lemmas about `colimit.ι`. We thus use `reassoc` to define additional `@[simp]` lemmas, with an arbitrary extra morphism. (see `Tactic/reassoc_axiom.lean`) -/ @[reassoc (attr := simp)] theorem colimit.ι_desc {F : J ⥤ C} [HasColimit F] (c : Cocone F) (j : J) : colimit.ι F j ≫ colimit.desc F c = c.ι.app j := IsColimit.fac _ c j /-- Functoriality of colimits. Usually this morphism should be accessed through `colim.map`, but may be needed separately when you have specified colimits for the source and target functors, but not necessarily for all functors of shape `J`. -/ def colimMap {F G : J ⥤ C} [HasColimit F] [HasColimit G] (α : F ⟶ G) : colimit F ⟶ colimit G := IsColimit.map (colimit.isColimit F) _ α @[reassoc (attr := simp)] theorem ι_colimMap {F G : J ⥤ C} [HasColimit F] [HasColimit G] (α : F ⟶ G) (j : J) : colimit.ι F j ≫ colimMap α = α.app j ≫ colimit.ι G j := colimit.ι_desc _ j /-- The cocone morphism from the arbitrary choice of colimit cocone to any cocone. -/ def colimit.coconeMorphism {F : J ⥤ C} [HasColimit F] (c : Cocone F) : colimit.cocone F ⟶ c := (colimit.isColimit F).descCoconeMorphism c @[simp] theorem colimit.coconeMorphism_hom {F : J ⥤ C} [HasColimit F] (c : Cocone F) : (colimit.coconeMorphism c).hom = colimit.desc F c := rfl theorem colimit.ι_coconeMorphism {F : J ⥤ C} [HasColimit F] (c : Cocone F) (j : J) : colimit.ι F j ≫ (colimit.coconeMorphism c).hom = c.ι.app j := by simp @[reassoc (attr := simp)] theorem colimit.comp_coconePointUniqueUpToIso_hom {F : J ⥤ C} [HasColimit F] {c : Cocone F} (hc : IsColimit c) (j : J) : colimit.ι F j ≫ (IsColimit.coconePointUniqueUpToIso (colimit.isColimit _) hc).hom = c.ι.app j := IsColimit.comp_coconePointUniqueUpToIso_hom _ _ _ @[reassoc (attr := simp)] theorem colimit.comp_coconePointUniqueUpToIso_inv {F : J ⥤ C} [HasColimit F] {c : Cocone F} (hc : IsColimit c) (j : J) : colimit.ι F j ≫ (IsColimit.coconePointUniqueUpToIso hc (colimit.isColimit _)).inv = c.ι.app j := IsColimit.comp_coconePointUniqueUpToIso_inv _ _ _ theorem colimit.existsUnique {F : J ⥤ C} [HasColimit F] (t : Cocone F) : ∃! d : colimit F ⟶ t.pt, ∀ j, colimit.ι F j ≫ d = t.ι.app j := (colimit.isColimit F).existsUnique _ /-- Given any other colimit cocone for `F`, the chosen `colimit F` is isomorphic to the cocone point. -/ def colimit.isoColimitCocone {F : J ⥤ C} [HasColimit F] (t : ColimitCocone F) : colimit F ≅ t.cocone.pt := IsColimit.coconePointUniqueUpToIso (colimit.isColimit F) t.isColimit @[reassoc (attr := simp)] theorem colimit.isoColimitCocone_ι_hom {F : J ⥤ C} [HasColimit F] (t : ColimitCocone F) (j : J) : colimit.ι F j ≫ (colimit.isoColimitCocone t).hom = t.cocone.ι.app j := by dsimp [colimit.isoColimitCocone, IsColimit.coconePointUniqueUpToIso] simp @[reassoc (attr := simp)] theorem colimit.isoColimitCocone_ι_inv {F : J ⥤ C} [HasColimit F] (t : ColimitCocone F) (j : J) : t.cocone.ι.app j ≫ (colimit.isoColimitCocone t).inv = colimit.ι F j := by dsimp [colimit.isoColimitCocone, IsColimit.coconePointUniqueUpToIso] simp @[ext] theorem colimit.hom_ext {F : J ⥤ C} [HasColimit F] {X : C} {f f' : colimit F ⟶ X} (w : ∀ j, colimit.ι F j ≫ f = colimit.ι F j ≫ f') : f = f' := (colimit.isColimit F).hom_ext w @[simp] theorem colimit.desc_cocone {F : J ⥤ C} [HasColimit F] : colimit.desc F (colimit.cocone F) = 𝟙 (colimit F) := (colimit.isColimit _).desc_self /-- The isomorphism (in `Type`) between morphisms from the colimit object to a specified object `W`, and cocones with cone point `W`. -/ def colimit.homIso (F : J ⥤ C) [HasColimit F] (W : C) : ULift.{u₁} (colimit F ⟶ W : Type v) ≅ F.cocones.obj W := (colimit.isColimit F).homIso W @[simp] theorem colimit.homIso_hom (F : J ⥤ C) [HasColimit F] {W : C} (f : ULift (colimit F ⟶ W)) : (colimit.homIso F W).hom f = (colimit.cocone F).ι ≫ (const J).map f.down := (colimit.isColimit F).homIso_hom f /-- The isomorphism (in `Type`) between morphisms from the colimit object to a specified object `W`, and an explicit componentwise description of cocones with cone point `W`. -/ def colimit.homIso' (F : J ⥤ C) [HasColimit F] (W : C) : ULift.{u₁} (colimit F ⟶ W : Type v) ≅ { p : ∀ j, F.obj j ⟶ W // ∀ {j j'} (f : j ⟶ j'), F.map f ≫ p j' = p j } := (colimit.isColimit F).homIso' W theorem colimit.desc_extend (F : J ⥤ C) [HasColimit F] (c : Cocone F) {X : C} (f : c.pt ⟶ X) : colimit.desc F (c.extend f) = colimit.desc F c ≫ f := by ext1; rw [← Category.assoc]; simp -- This has the isomorphism pointing in the opposite direction than in `has_limit_of_iso`. -- This is intentional; it seems to help with elaboration. /-- If `F` has a colimit, so does any naturally isomorphic functor. -/ theorem hasColimit_of_iso {F G : J ⥤ C} [HasColimit F] (α : G ≅ F) : HasColimit G := HasColimit.mk { cocone := (Cocones.precompose α.hom).obj (colimit.cocone F) isColimit := (IsColimit.precomposeHomEquiv _ _).symm (colimit.isColimit F) } @[deprecated (since := "2025-03-03")] alias hasColimitOfIso := hasColimit_of_iso theorem hasColimit_iff_of_iso {F G : J ⥤ C} (α : F ≅ G) : HasColimit F ↔ HasColimit G := ⟨fun _ ↦ hasColimit_of_iso α.symm, fun _ ↦ hasColimit_of_iso α⟩ /-- If a functor `G` has the same collection of cocones as a functor `F` which has a colimit, then `G` also has a colimit. -/ theorem HasColimit.ofCoconesIso {K : Type u₁} [Category.{v₂} K] (F : J ⥤ C) (G : K ⥤ C) (h : F.cocones ≅ G.cocones) [HasColimit F] : HasColimit G := HasColimit.mk ⟨_, IsColimit.ofNatIso (IsColimit.natIso (colimit.isColimit F) ≪≫ h)⟩ /-- The colimits of `F : J ⥤ C` and `G : J ⥤ C` are isomorphic, if the functors are naturally isomorphic. -/ def HasColimit.isoOfNatIso {F G : J ⥤ C} [HasColimit F] [HasColimit G] (w : F ≅ G) : colimit F ≅ colimit G := IsColimit.coconePointsIsoOfNatIso (colimit.isColimit F) (colimit.isColimit G) w @[reassoc (attr := simp)] theorem HasColimit.isoOfNatIso_ι_hom {F G : J ⥤ C} [HasColimit F] [HasColimit G] (w : F ≅ G) (j : J) : colimit.ι F j ≫ (HasColimit.isoOfNatIso w).hom = w.hom.app j ≫ colimit.ι G j := IsColimit.comp_coconePointsIsoOfNatIso_hom _ _ _ _ @[reassoc (attr := simp)] theorem HasColimit.isoOfNatIso_ι_inv {F G : J ⥤ C} [HasColimit F] [HasColimit G] (w : F ≅ G) (j : J) : colimit.ι G j ≫ (HasColimit.isoOfNatIso w).inv = w.inv.app j ≫ colimit.ι F j := IsColimit.comp_coconePointsIsoOfNatIso_inv _ _ _ _ @[reassoc (attr := simp)] theorem HasColimit.isoOfNatIso_hom_desc {F G : J ⥤ C} [HasColimit F] [HasColimit G] (t : Cocone G) (w : F ≅ G) : (HasColimit.isoOfNatIso w).hom ≫ colimit.desc G t = colimit.desc F ((Cocones.precompose w.hom).obj _) := IsColimit.coconePointsIsoOfNatIso_hom_desc _ _ _ @[reassoc (attr := simp)] theorem HasColimit.isoOfNatIso_inv_desc {F G : J ⥤ C} [HasColimit F] [HasColimit G] (t : Cocone F) (w : F ≅ G) : (HasColimit.isoOfNatIso w).inv ≫ colimit.desc F t = colimit.desc G ((Cocones.precompose w.inv).obj _) := IsColimit.coconePointsIsoOfNatIso_inv_desc _ _ _ /-- The colimits of `F : J ⥤ C` and `G : K ⥤ C` are isomorphic, if there is an equivalence `e : J ≌ K` making the triangle commute up to natural isomorphism. -/ def HasColimit.isoOfEquivalence {F : J ⥤ C} [HasColimit F] {G : K ⥤ C} [HasColimit G] (e : J ≌ K) (w : e.functor ⋙ G ≅ F) : colimit F ≅ colimit G := IsColimit.coconePointsIsoOfEquivalence (colimit.isColimit F) (colimit.isColimit G) e w @[simp] theorem HasColimit.isoOfEquivalence_hom_π {F : J ⥤ C} [HasColimit F] {G : K ⥤ C} [HasColimit G] (e : J ≌ K) (w : e.functor ⋙ G ≅ F) (j : J) : colimit.ι F j ≫ (HasColimit.isoOfEquivalence e w).hom = F.map (e.unit.app j) ≫ w.inv.app _ ≫ colimit.ι G _ := by simp [HasColimit.isoOfEquivalence, IsColimit.coconePointsIsoOfEquivalence_inv] @[simp] theorem HasColimit.isoOfEquivalence_inv_π {F : J ⥤ C} [HasColimit F] {G : K ⥤ C} [HasColimit G] (e : J ≌ K) (w : e.functor ⋙ G ≅ F) (k : K) : colimit.ι G k ≫ (HasColimit.isoOfEquivalence e w).inv = G.map (e.counitInv.app k) ≫ w.hom.app (e.inverse.obj k) ≫ colimit.ι F (e.inverse.obj k) := by simp [HasColimit.isoOfEquivalence, IsColimit.coconePointsIsoOfEquivalence_inv] section Pre variable (F) variable [HasColimit F] (E : K ⥤ J) [HasColimit (E ⋙ F)] /-- The canonical morphism from the colimit of `E ⋙ F` to the colimit of `F`. -/ def colimit.pre : colimit (E ⋙ F) ⟶ colimit F := colimit.desc (E ⋙ F) ((colimit.cocone F).whisker E) @[reassoc (attr := simp)] theorem colimit.ι_pre (k : K) : colimit.ι (E ⋙ F) k ≫ colimit.pre F E = colimit.ι F (E.obj k) := by erw [IsColimit.fac] rfl @[reassoc (attr := simp)] theorem colimit.ι_inv_pre [IsIso (pre F E)] (k : K) : colimit.ι F (E.obj k) ≫ inv (colimit.pre F E) = colimit.ι (E ⋙ F) k := by simp [IsIso.comp_inv_eq] @[reassoc (attr := simp)] theorem colimit.pre_desc (c : Cocone F) : colimit.pre F E ≫ colimit.desc F c = colimit.desc (E ⋙ F) (c.whisker E) := by ext; rw [← assoc, colimit.ι_pre]; simp variable {L : Type u₃} [Category.{v₃} L] variable (D : L ⥤ K) @[simp] theorem colimit.pre_pre [h : HasColimit (D ⋙ E ⋙ F)] : haveI : HasColimit ((D ⋙ E) ⋙ F) := h colimit.pre (E ⋙ F) D ≫ colimit.pre F E = colimit.pre F (D ⋙ E) := by ext j rw [← assoc, colimit.ι_pre, colimit.ι_pre] haveI : HasColimit ((D ⋙ E) ⋙ F) := h exact (colimit.ι_pre F (D ⋙ E) j).symm variable {E F} /-- - If we have particular colimit cocones available for `E ⋙ F` and for `F`, we obtain a formula for `colimit.pre F E`. -/ theorem colimit.pre_eq (s : ColimitCocone (E ⋙ F)) (t : ColimitCocone F) : colimit.pre F E = (colimit.isoColimitCocone s).hom ≫ s.isColimit.desc (t.cocone.whisker E) ≫ (colimit.isoColimitCocone t).inv := by aesop_cat end Pre section Post variable {D : Type u'} [Category.{v'} D] variable (F) variable [HasColimit F] (G : C ⥤ D) [HasColimit (F ⋙ G)] /-- The canonical morphism from `G` applied to the colimit of `F ⋙ G` to `G` applied to the colimit of `F`. -/ def colimit.post : colimit (F ⋙ G) ⟶ G.obj (colimit F) := colimit.desc (F ⋙ G) (G.mapCocone (colimit.cocone F)) @[reassoc (attr := simp)] theorem colimit.ι_post (j : J) : colimit.ι (F ⋙ G) j ≫ colimit.post F G = G.map (colimit.ι F j) := by erw [IsColimit.fac] rfl @[simp] theorem colimit.post_desc (c : Cocone F) : colimit.post F G ≫ G.map (colimit.desc F c) = colimit.desc (F ⋙ G) (G.mapCocone c) := by ext rw [← assoc, colimit.ι_post, ← G.map_comp, colimit.ι_desc, colimit.ι_desc] rfl @[simp] theorem colimit.post_post {E : Type u''} [Category.{v''} E] (H : D ⥤ E) -- H G (colimit F) ⟶ H (colimit (F ⋙ G)) ⟶ colimit ((F ⋙ G) ⋙ H) equals -- H G (colimit F) ⟶ colimit (F ⋙ (G ⋙ H)) [h : HasColimit ((F ⋙ G) ⋙ H)] : haveI : HasColimit (F ⋙ G ⋙ H) := h colimit.post (F ⋙ G) H ≫ H.map (colimit.post F G) = colimit.post F (G ⋙ H) := by ext j rw [← assoc, colimit.ι_post, ← H.map_comp, colimit.ι_post] haveI : HasColimit (F ⋙ G ⋙ H) := h exact (colimit.ι_post F (G ⋙ H) j).symm end Post theorem colimit.pre_post {D : Type u'} [Category.{v'} D] (E : K ⥤ J) (F : J ⥤ C) (G : C ⥤ D) [HasColimit F] [HasColimit (E ⋙ F)] [HasColimit (F ⋙ G)] [h : HasColimit ((E ⋙ F) ⋙ G)] : -- G (colimit F) ⟶ G (colimit (E ⋙ F)) ⟶ colimit ((E ⋙ F) ⋙ G) vs -- G (colimit F) ⟶ colimit F ⋙ G ⟶ colimit (E ⋙ (F ⋙ G)) or haveI : HasColimit (E ⋙ F ⋙ G) := h colimit.post (E ⋙ F) G ≫ G.map (colimit.pre F E) = colimit.pre (F ⋙ G) E ≫ colimit.post F G := by ext j rw [← assoc, colimit.ι_post, ← G.map_comp, colimit.ι_pre, ← assoc] haveI : HasColimit (E ⋙ F ⋙ G) := h erw [colimit.ι_pre (F ⋙ G) E j, colimit.ι_post] open CategoryTheory.Equivalence instance hasColimit_equivalence_comp (e : K ≌ J) [HasColimit F] : HasColimit (e.functor ⋙ F) := HasColimit.mk { cocone := Cocone.whisker e.functor (colimit.cocone F) isColimit := IsColimit.whiskerEquivalence (colimit.isColimit F) e } /-- If a `E ⋙ F` has a colimit, and `E` is an equivalence, we can construct a colimit of `F`. -/ theorem hasColimit_of_equivalence_comp (e : K ≌ J) [HasColimit (e.functor ⋙ F)] : HasColimit F := by haveI : HasColimit (e.inverse ⋙ e.functor ⋙ F) := Limits.hasColimit_equivalence_comp e.symm apply hasColimit_of_iso (e.invFunIdAssoc F).symm section ColimFunctor variable [HasColimitsOfShape J C] section /-- `colimit F` is functorial in `F`, when `C` has all colimits of shape `J`. -/ @[simps] def colim : (J ⥤ C) ⥤ C where obj F := colimit F map α := colimMap α end variable {G : J ⥤ C} (α : F ⟶ G) theorem colimMap_eq : colimMap α = colim.map α := rfl @[reassoc] theorem colimit.ι_map (j : J) : colimit.ι F j ≫ colim.map α = α.app j ≫ colimit.ι G j := by simp @[reassoc (attr := simp)] theorem colimit.map_desc (c : Cocone G) : colimMap α ≫ colimit.desc G c = colimit.desc F ((Cocones.precompose α).obj c) := by ext j simp [← assoc, colimit.ι_map, assoc, colimit.ι_desc, colimit.ι_desc] theorem colimit.pre_map [HasColimitsOfShape K C] (E : K ⥤ J) : colimit.pre F E ≫ colim.map α = colim.map (whiskerLeft E α) ≫ colimit.pre G E := by ext rw [← assoc, colimit.ι_pre, colimit.ι_map, ← assoc, colimit.ι_map, assoc, colimit.ι_pre] rfl theorem colimit.pre_map' [HasColimitsOfShape K C] (F : J ⥤ C) {E₁ E₂ : K ⥤ J} (α : E₁ ⟶ E₂) : colimit.pre F E₁ = colim.map (whiskerRight α F) ≫ colimit.pre F E₂ := by ext1 simp [← assoc, assoc] theorem colimit.pre_id (F : J ⥤ C) : colimit.pre F (𝟭 _) = colim.map (Functor.leftUnitor F).hom := by aesop_cat theorem colimit.map_post {D : Type u'} [Category.{v'} D] [HasColimitsOfShape J D] (H : C ⥤ D) :/- H (colimit F) ⟶ H (colimit G) ⟶ colimit (G ⋙ H) vs H (colimit F) ⟶ colimit (F ⋙ H) ⟶ colimit (G ⋙ H) -/ colimit.post F H ≫ H.map (colim.map α) = colim.map (whiskerRight α H) ≫ colimit.post G H := by ext rw [← assoc, colimit.ι_post, ← H.map_comp, colimit.ι_map, H.map_comp] rw [← assoc, colimit.ι_map, assoc, colimit.ι_post] rfl /-- The isomorphism between morphisms from the cone point of the colimit cocone for `F` to `W` and cocones over `F` with cone point `W` is natural in `F`. -/ def colimCoyoneda : colim.op ⋙ coyoneda ⋙ (whiskeringRight _ _ _).obj uliftFunctor.{u₁} ≅ CategoryTheory.cocones J C := NatIso.ofComponents fun F => NatIso.ofComponents fun W => colimit.homIso (unop F) W /-- The colimit functor and constant functor are adjoint to each other -/ def colimConstAdj : (colim : (J ⥤ C) ⥤ C) ⊣ const J := Adjunction.mk' { homEquiv := fun f c ↦ { toFun := fun g => { app := fun _ => colimit.ι _ _ ≫ g } invFun := fun g => colimit.desc _ ⟨_, g⟩ left_inv := by aesop_cat right_inv := by aesop_cat } unit := { app := fun g => { app := colimit.ι _ } } counit := { app := fun _ => colimit.desc _ ⟨_, 𝟙 _⟩ } } instance : IsLeftAdjoint (colim : (J ⥤ C) ⥤ C) := ⟨_, ⟨colimConstAdj⟩⟩ end ColimFunctor instance colimMap_epi' {F G : J ⥤ C} [HasColimitsOfShape J C] (α : F ⟶ G) [Epi α] : Epi (colimMap α) := (colim : (J ⥤ C) ⥤ C).map_epi α instance colimMap_epi {F G : J ⥤ C} [HasColimit F] [HasColimit G] (α : F ⟶ G) [∀ j, Epi (α.app j)] : Epi (colimMap α) := ⟨fun {Z} u v h => colimit.hom_ext fun j => (cancel_epi (α.app j)).1 <| by simpa using colimit.ι _ j ≫= h⟩ /-- We can transport colimits of shape `J` along an equivalence `J ≌ J'`. -/ theorem hasColimitsOfShape_of_equivalence {J' : Type u₂} [Category.{v₂} J'] (e : J ≌ J') [HasColimitsOfShape J C] : HasColimitsOfShape J' C := by constructor intro F apply hasColimit_of_equivalence_comp e variable (C) /-- A category that has larger colimits also has smaller colimits. -/ theorem hasColimitsOfSizeOfUnivLE [UnivLE.{v₂, v₁}] [UnivLE.{u₂, u₁}] [HasColimitsOfSize.{v₁, u₁} C] : HasColimitsOfSize.{v₂, u₂} C where has_colimits_of_shape J {_} := hasColimitsOfShape_of_equivalence ((ShrinkHoms.equivalence J).trans <| Shrink.equivalence _).symm /-- `hasColimitsOfSizeShrink.{v u} C` tries to obtain `HasColimitsOfSize.{v u} C` from some other `HasColimitsOfSize C`. -/ theorem hasColimitsOfSizeShrink [HasColimitsOfSize.{max v₁ v₂, max u₁ u₂} C] : HasColimitsOfSize.{v₁, u₁} C := hasColimitsOfSizeOfUnivLE.{max v₁ v₂, max u₁ u₂} C instance (priority := 100) hasSmallestColimitsOfHasColimits [HasColimits C] : HasColimitsOfSize.{0, 0} C := hasColimitsOfSizeShrink.{0, 0} C end Colimit section Opposite /-- If `t : Cone F` is a limit cone, then `t.op : Cocone F.op` is a colimit cocone. -/ def IsLimit.op {t : Cone F} (P : IsLimit t) : IsColimit t.op where desc s := (P.lift s.unop).op fac s j := congrArg Quiver.Hom.op (P.fac s.unop (unop j)) uniq s m w := by dsimp rw [← P.uniq s.unop m.unop] · rfl · dsimp intro j rw [← w] rfl /-- If `t : Cocone F` is a colimit cocone, then `t.op : Cone F.op` is a limit cone. -/ def IsColimit.op {t : Cocone F} (P : IsColimit t) : IsLimit t.op where lift s := (P.desc s.unop).op fac s j := congrArg Quiver.Hom.op (P.fac s.unop (unop j)) uniq s m w := by dsimp rw [← P.uniq s.unop m.unop] · rfl · dsimp intro j rw [← w] rfl /-- If `t : Cone F.op` is a limit cone, then `t.unop : Cocone F` is a colimit cocone. -/ def IsLimit.unop {t : Cone F.op} (P : IsLimit t) : IsColimit t.unop where desc s := (P.lift s.op).unop fac s j := congrArg Quiver.Hom.unop (P.fac s.op (.op j)) uniq s m w := by dsimp rw [← P.uniq s.op m.op] · rfl · dsimp intro j rw [← w] rfl /-- If `t : Cocone F.op` is a colimit cocone, then `t.unop : Cone F` is a limit cone. -/ def IsColimit.unop {t : Cocone F.op} (P : IsColimit t) : IsLimit t.unop where lift s := (P.desc s.op).unop
fac s j := congrArg Quiver.Hom.unop (P.fac s.op (.op j)) uniq s m w := by
Mathlib/CategoryTheory/Limits/HasLimits.lean
1,149
1,150
/- Copyright (c) 2021 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash -/ import Mathlib.Algebra.Lie.Ideal /-! # Ideal operations for Lie algebras Given a Lie module `M` over a Lie algebra `L`, there is a natural action of the Lie ideals of `L` on the Lie submodules of `M`. In the special case that `M = L` with the adjoint action, this provides a pairing of Lie ideals which is especially important. For example, it can be used to define solvability / nilpotency of a Lie algebra via the derived / lower-central series. ## Main definitions * `LieSubmodule.hasBracket` * `LieSubmodule.lieIdeal_oper_eq_linear_span` * `LieIdeal.map_bracket_le` * `LieIdeal.comap_bracket_le` ## Notation Given a Lie module `M` over a Lie algebra `L`, together with a Lie submodule `N ⊆ M` and a Lie ideal `I ⊆ L`, we introduce the notation `⁅I, N⁆` for the Lie submodule of `M` corresponding to the action defined in this file. ## Tags lie algebra, ideal operation -/ universe u v w w₁ w₂ namespace LieSubmodule variable {R : Type u} {L : Type v} {M : Type w} {M₂ : Type w₁} variable [CommRing R] [LieRing L] variable [AddCommGroup M] [Module R M] [LieRingModule L M] variable [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] variable (N N' : LieSubmodule R L M) (N₂ : LieSubmodule R L M₂) variable (f : M →ₗ⁅R,L⁆ M₂) section LieIdealOperations theorem map_comap_le : map f (comap f N₂) ≤ N₂ := (N₂ : Set M₂).image_preimage_subset f theorem map_comap_eq (hf : N₂ ≤ f.range) : map f (comap f N₂) = N₂ := by rw [SetLike.ext'_iff] exact Set.image_preimage_eq_of_subset hf theorem le_comap_map : N ≤ comap f (map f N) := (N : Set M).subset_preimage_image f theorem comap_map_eq (hf : f.ker = ⊥) : comap f (map f N) = N := by rw [SetLike.ext'_iff] exact (N : Set M).preimage_image_eq (f.ker_eq_bot.mp hf) @[simp] theorem map_comap_incl : map N.incl (comap N.incl N') = N ⊓ N' := by rw [← toSubmodule_inj] exact (N : Submodule R M).map_comap_subtype N' variable [LieAlgebra R L] [LieModule R L M₂] (I J : LieIdeal R L) /-- Given a Lie module `M` over a Lie algebra `L`, the set of Lie ideals of `L` acts on the set of submodules of `M`. -/ instance hasBracket : Bracket (LieIdeal R L) (LieSubmodule R L M) := ⟨fun I N => lieSpan R L { ⁅(x : L), (n : M)⁆ | (x : I) (n : N) }⟩ theorem lieIdeal_oper_eq_span : ⁅I, N⁆ = lieSpan R L { ⁅(x : L), (n : M)⁆ | (x : I) (n : N) } := rfl /-- See also `LieSubmodule.lieIdeal_oper_eq_linear_span'` and `LieSubmodule.lieIdeal_oper_eq_tensor_map_range`. -/ theorem lieIdeal_oper_eq_linear_span [LieModule R L M] : (↑⁅I, N⁆ : Submodule R M) = Submodule.span R { ⁅(x : L), (n : M)⁆ | (x : I) (n : N) } := by apply le_antisymm · let s := { ⁅(x : L), (n : M)⁆ | (x : I) (n : N) } have aux : ∀ (y : L), ∀ m' ∈ Submodule.span R s, ⁅y, m'⁆ ∈ Submodule.span R s := by intro y m' hm' refine Submodule.span_induction (R := R) (M := M) (s := s) (p := fun m' _ ↦ ⁅y, m'⁆ ∈ Submodule.span R s) ?_ ?_ ?_ ?_ hm' · rintro m'' ⟨x, n, hm''⟩; rw [← hm'', leibniz_lie] refine Submodule.add_mem _ ?_ ?_ <;> apply Submodule.subset_span · use ⟨⁅y, ↑x⁆, I.lie_mem x.property⟩, n · use x, ⟨⁅y, ↑n⁆, N.lie_mem n.property⟩ · simp only [lie_zero, Submodule.zero_mem] · intro m₁ m₂ _ _ hm₁ hm₂; rw [lie_add]; exact Submodule.add_mem _ hm₁ hm₂ · intro t m'' _ hm''; rw [lie_smul]; exact Submodule.smul_mem _ t hm'' change _ ≤ ({ Submodule.span R s with lie_mem := fun hm' => aux _ _ hm' } : LieSubmodule R L M) rw [lieIdeal_oper_eq_span, lieSpan_le] exact Submodule.subset_span · rw [lieIdeal_oper_eq_span]; apply submodule_span_le_lieSpan theorem lieIdeal_oper_eq_linear_span' [LieModule R L M] : (↑⁅I, N⁆ : Submodule R M) = Submodule.span R { ⁅x, n⁆ | (x ∈ I) (n ∈ N) } := by rw [lieIdeal_oper_eq_linear_span] congr ext m constructor · rintro ⟨⟨x, hx⟩, ⟨n, hn⟩, rfl⟩ exact ⟨x, hx, n, hn, rfl⟩ · rintro ⟨x, hx, n, hn, rfl⟩ exact ⟨⟨x, hx⟩, ⟨n, hn⟩, rfl⟩ theorem lie_le_iff : ⁅I, N⁆ ≤ N' ↔ ∀ x ∈ I, ∀ m ∈ N, ⁅x, m⁆ ∈ N' := by rw [lieIdeal_oper_eq_span, LieSubmodule.lieSpan_le] refine ⟨fun h x hx m hm => h ⟨⟨x, hx⟩, ⟨m, hm⟩, rfl⟩, ?_⟩ rintro h _ ⟨⟨x, hx⟩, ⟨m, hm⟩, rfl⟩ exact h x hx m hm variable {N I} in theorem lie_coe_mem_lie (x : I) (m : N) : ⁅(x : L), (m : M)⁆ ∈ ⁅I, N⁆ := by rw [lieIdeal_oper_eq_span]; apply subset_lieSpan; use x, m variable {N I} in theorem lie_mem_lie {x : L} {m : M} (hx : x ∈ I) (hm : m ∈ N) : ⁅x, m⁆ ∈ ⁅I, N⁆ := lie_coe_mem_lie ⟨x, hx⟩ ⟨m, hm⟩ theorem lie_comm : ⁅I, J⁆ = ⁅J, I⁆ := by suffices ∀ I J : LieIdeal R L, ⁅I, J⁆ ≤ ⁅J, I⁆ by exact le_antisymm (this I J) (this J I) clear! I J; intro I J rw [lieIdeal_oper_eq_span, lieSpan_le]; rintro x ⟨y, z, h⟩; rw [← h] rw [← lie_skew, ← lie_neg, ← LieSubmodule.coe_neg] apply lie_coe_mem_lie theorem lie_le_right : ⁅I, N⁆ ≤ N := by rw [lieIdeal_oper_eq_span, lieSpan_le]; rintro m ⟨x, n, hn⟩; rw [← hn] exact N.lie_mem n.property theorem lie_le_left : ⁅I, J⁆ ≤ I := by rw [lie_comm]; exact lie_le_right I J theorem lie_le_inf : ⁅I, J⁆ ≤ I ⊓ J := by rw [le_inf_iff]; exact ⟨lie_le_left I J, lie_le_right J I⟩ @[simp] theorem lie_bot : ⁅I, (⊥ : LieSubmodule R L M)⁆ = ⊥ := by rw [eq_bot_iff]; apply lie_le_right @[simp] theorem bot_lie : ⁅(⊥ : LieIdeal R L), N⁆ = ⊥ := by suffices ⁅(⊥ : LieIdeal R L), N⁆ ≤ ⊥ by exact le_bot_iff.mp this rw [lieIdeal_oper_eq_span, lieSpan_le]; rintro m ⟨⟨x, hx⟩, n, hn⟩; rw [← hn] change x ∈ (⊥ : LieIdeal R L) at hx; rw [mem_bot] at hx; simp [hx] theorem lie_eq_bot_iff : ⁅I, N⁆ = ⊥ ↔ ∀ x ∈ I, ∀ m ∈ N, ⁅(x : L), m⁆ = 0 := by rw [lieIdeal_oper_eq_span, LieSubmodule.lieSpan_eq_bot_iff] refine ⟨fun h x hx m hm => h ⁅x, m⁆ ⟨⟨x, hx⟩, ⟨m, hm⟩, rfl⟩, ?_⟩ rintro h - ⟨⟨x, hx⟩, ⟨⟨n, hn⟩, rfl⟩⟩ exact h x hx n hn variable {I J N N'} in theorem mono_lie (h₁ : I ≤ J) (h₂ : N ≤ N') : ⁅I, N⁆ ≤ ⁅J, N'⁆ := by intro m h rw [lieIdeal_oper_eq_span, mem_lieSpan] at h; rw [lieIdeal_oper_eq_span, mem_lieSpan] intro N hN; apply h; rintro m' ⟨⟨x, hx⟩, ⟨n, hn⟩, hm⟩; rw [← hm]; apply hN use ⟨x, h₁ hx⟩, ⟨n, h₂ hn⟩ variable {I J} in theorem mono_lie_left (h : I ≤ J) : ⁅I, N⁆ ≤ ⁅J, N⁆ := mono_lie h (le_refl N) variable {N N'} in theorem mono_lie_right (h : N ≤ N') : ⁅I, N⁆ ≤ ⁅I, N'⁆ := mono_lie (le_refl I) h @[simp] theorem lie_sup : ⁅I, N ⊔ N'⁆ = ⁅I, N⁆ ⊔ ⁅I, N'⁆ := by have h : ⁅I, N⁆ ⊔ ⁅I, N'⁆ ≤ ⁅I, N ⊔ N'⁆ := by rw [sup_le_iff]; constructor <;> apply mono_lie_right <;> [exact le_sup_left; exact le_sup_right] suffices ⁅I, N ⊔ N'⁆ ≤ ⁅I, N⁆ ⊔ ⁅I, N'⁆ by exact le_antisymm this h rw [lieIdeal_oper_eq_span, lieSpan_le] rintro m ⟨x, ⟨n, hn⟩, h⟩ simp only [SetLike.mem_coe] rw [LieSubmodule.mem_sup] at hn ⊢ rcases hn with ⟨n₁, hn₁, n₂, hn₂, hn'⟩ use ⁅(x : L), (⟨n₁, hn₁⟩ : N)⁆; constructor; · apply lie_coe_mem_lie use ⁅(x : L), (⟨n₂, hn₂⟩ : N')⁆; constructor; · apply lie_coe_mem_lie simp [← h, ← hn'] @[simp] theorem sup_lie : ⁅I ⊔ J, N⁆ = ⁅I, N⁆ ⊔ ⁅J, N⁆ := by have h : ⁅I, N⁆ ⊔ ⁅J, N⁆ ≤ ⁅I ⊔ J, N⁆ := by rw [sup_le_iff]; constructor <;> apply mono_lie_left <;> [exact le_sup_left; exact le_sup_right] suffices ⁅I ⊔ J, N⁆ ≤ ⁅I, N⁆ ⊔ ⁅J, N⁆ by exact le_antisymm this h rw [lieIdeal_oper_eq_span, lieSpan_le] rintro m ⟨⟨x, hx⟩, n, h⟩ simp only [SetLike.mem_coe] rw [LieSubmodule.mem_sup] at hx ⊢ rcases hx with ⟨x₁, hx₁, x₂, hx₂, hx'⟩
use ⁅((⟨x₁, hx₁⟩ : I) : L), (n : N)⁆; constructor; · apply lie_coe_mem_lie use ⁅((⟨x₂, hx₂⟩ : J) : L), (n : N)⁆; constructor; · apply lie_coe_mem_lie simp [← h, ← hx']
Mathlib/Algebra/Lie/IdealOperations.lean
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/- 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 Mathlib.Data.Set.Operations import Mathlib.Order.Basic import Mathlib.Order.BooleanAlgebra import Mathlib.Tactic.Tauto import Mathlib.Tactic.ByContra import Mathlib.Util.Delaborators import Mathlib.Tactic.Lift /-! # Basic properties of sets Sets in Lean are homogeneous; all their elements have the same type. Sets whose elements have type `X` are thus defined as `Set X := X → Prop`. Note that this function need not be decidable. The definition is in the module `Mathlib.Data.Set.Defs`. This file provides some basic definitions related to sets and functions not present in the definitions file, as well as extra lemmas for functions defined in the definitions file and `Mathlib.Data.Set.Operations` (empty set, univ, union, intersection, insert, singleton, set-theoretic difference, complement, and powerset). Note that a set is a term, not a type. There is a coercion from `Set α` to `Type*` sending `s` to the corresponding subtype `↥s`. See also the file `SetTheory/ZFC.lean`, which contains an encoding of ZFC set theory in Lean. ## Main definitions Notation used here: - `f : α → β` is a function, - `s : Set α` and `s₁ s₂ : Set α` are subsets of `α` - `t : Set β` is a subset of `β`. Definitions in the file: * `Nonempty s : Prop` : the predicate `s ≠ ∅`. Note that this is the preferred way to express the fact that `s` has an element (see the Implementation Notes). * `inclusion s₁ s₂ : ↥s₁ → ↥s₂` : the map `↥s₁ → ↥s₂` induced by an inclusion `s₁ ⊆ s₂`. ## Notation * `sᶜ` for the complement of `s` ## Implementation notes * `s.Nonempty` is to be preferred to `s ≠ ∅` or `∃ x, x ∈ s`. It has the advantage that the `s.Nonempty` dot notation can be used. * For `s : Set α`, do not use `Subtype s`. Instead use `↥s` or `(s : Type*)` or `s`. ## Tags set, sets, subset, subsets, union, intersection, insert, singleton, complement, powerset -/ assert_not_exists RelIso /-! ### Set coercion to a type -/ open Function universe u v namespace Set variable {α : Type u} {s t : Set α} instance instBooleanAlgebra : BooleanAlgebra (Set α) := { (inferInstance : BooleanAlgebra (α → Prop)) with sup := (· ∪ ·), le := (· ≤ ·), lt := fun s t => s ⊆ t ∧ ¬t ⊆ s, inf := (· ∩ ·), bot := ∅, compl := (·ᶜ), top := univ, sdiff := (· \ ·) } instance : HasSSubset (Set α) := ⟨(· < ·)⟩ @[simp] theorem top_eq_univ : (⊤ : Set α) = univ := rfl @[simp] theorem bot_eq_empty : (⊥ : Set α) = ∅ := rfl @[simp] theorem sup_eq_union : ((· ⊔ ·) : Set α → Set α → Set α) = (· ∪ ·) := rfl @[simp] theorem inf_eq_inter : ((· ⊓ ·) : Set α → Set α → Set α) = (· ∩ ·) := rfl @[simp] theorem le_eq_subset : ((· ≤ ·) : Set α → Set α → Prop) = (· ⊆ ·) := rfl @[simp] theorem lt_eq_ssubset : ((· < ·) : Set α → Set α → Prop) = (· ⊂ ·) := rfl theorem le_iff_subset : s ≤ t ↔ s ⊆ t := Iff.rfl theorem lt_iff_ssubset : s < t ↔ s ⊂ t := Iff.rfl alias ⟨_root_.LE.le.subset, _root_.HasSubset.Subset.le⟩ := le_iff_subset alias ⟨_root_.LT.lt.ssubset, _root_.HasSSubset.SSubset.lt⟩ := lt_iff_ssubset instance PiSetCoe.canLift (ι : Type u) (α : ι → Type v) [∀ i, Nonempty (α i)] (s : Set ι) : CanLift (∀ i : s, α i) (∀ i, α i) (fun f i => f i) fun _ => True := PiSubtype.canLift ι α s instance PiSetCoe.canLift' (ι : Type u) (α : Type v) [Nonempty α] (s : Set ι) : CanLift (s → α) (ι → α) (fun f i => f i) fun _ => True := PiSetCoe.canLift ι (fun _ => α) s end Set section SetCoe variable {α : Type u} instance (s : Set α) : CoeTC s α := ⟨fun x => x.1⟩ theorem Set.coe_eq_subtype (s : Set α) : ↥s = { x // x ∈ s } := rfl @[simp] theorem Set.coe_setOf (p : α → Prop) : ↥{ x | p x } = { x // p x } := rfl theorem SetCoe.forall {s : Set α} {p : s → Prop} : (∀ x : s, p x) ↔ ∀ (x) (h : x ∈ s), p ⟨x, h⟩ := Subtype.forall theorem SetCoe.exists {s : Set α} {p : s → Prop} : (∃ x : s, p x) ↔ ∃ (x : _) (h : x ∈ s), p ⟨x, h⟩ := Subtype.exists theorem SetCoe.exists' {s : Set α} {p : ∀ x, x ∈ s → Prop} : (∃ (x : _) (h : x ∈ s), p x h) ↔ ∃ x : s, p x.1 x.2 := (@SetCoe.exists _ _ fun x => p x.1 x.2).symm theorem SetCoe.forall' {s : Set α} {p : ∀ x, x ∈ s → Prop} : (∀ (x) (h : x ∈ s), p x h) ↔ ∀ x : s, p x.1 x.2 := (@SetCoe.forall _ _ fun x => p x.1 x.2).symm @[simp] theorem set_coe_cast : ∀ {s t : Set α} (H' : s = t) (H : ↥s = ↥t) (x : s), cast H x = ⟨x.1, H' ▸ x.2⟩ | _, _, rfl, _, _ => rfl theorem SetCoe.ext {s : Set α} {a b : s} : (a : α) = b → a = b := Subtype.eq theorem SetCoe.ext_iff {s : Set α} {a b : s} : (↑a : α) = ↑b ↔ a = b := Iff.intro SetCoe.ext fun h => h ▸ rfl end SetCoe /-- See also `Subtype.prop` -/ theorem Subtype.mem {α : Type*} {s : Set α} (p : s) : (p : α) ∈ s := p.prop /-- Duplicate of `Eq.subset'`, which currently has elaboration problems. -/ theorem Eq.subset {α} {s t : Set α} : s = t → s ⊆ t := fun h₁ _ h₂ => by rw [← h₁]; exact h₂ namespace Set variable {α : Type u} {β : Type v} {a b : α} {s s₁ s₂ t t₁ t₂ u : Set α} instance : Inhabited (Set α) := ⟨∅⟩ @[trans] theorem mem_of_mem_of_subset {x : α} {s t : Set α} (hx : x ∈ s) (h : s ⊆ t) : x ∈ t := h hx theorem forall_in_swap {p : α → β → Prop} : (∀ a ∈ s, ∀ (b), p a b) ↔ ∀ (b), ∀ a ∈ s, p a b := by tauto theorem setOf_injective : Function.Injective (@setOf α) := injective_id theorem setOf_inj {p q : α → Prop} : { x | p x } = { x | q x } ↔ p = q := Iff.rfl /-! ### Lemmas about `mem` and `setOf` -/ theorem mem_setOf {a : α} {p : α → Prop} : a ∈ { x | p x } ↔ p a := Iff.rfl /-- This lemma is intended for use with `rw` where a membership predicate is needed, hence the explicit argument and the equality in the reverse direction from normal. See also `Set.mem_setOf_eq` for the reverse direction applied to an argument. -/ theorem eq_mem_setOf (p : α → Prop) : p = (· ∈ {a | p a}) := rfl /-- If `h : a ∈ {x | p x}` then `h.out : p x`. These are definitionally equal, but this can nevertheless be useful for various reasons, e.g. to apply further projection notation or in an argument to `simp`. -/ theorem _root_.Membership.mem.out {p : α → Prop} {a : α} (h : a ∈ { x | p x }) : p a := h theorem nmem_setOf_iff {a : α} {p : α → Prop} : a ∉ { x | p x } ↔ ¬p a := Iff.rfl @[simp] theorem setOf_mem_eq {s : Set α} : { x | x ∈ s } = s := rfl theorem setOf_set {s : Set α} : setOf s = s := rfl theorem setOf_app_iff {p : α → Prop} {x : α} : { x | p x } x ↔ p x := Iff.rfl theorem mem_def {a : α} {s : Set α} : a ∈ s ↔ s a := Iff.rfl theorem setOf_bijective : Bijective (setOf : (α → Prop) → Set α) := bijective_id theorem subset_setOf {p : α → Prop} {s : Set α} : s ⊆ setOf p ↔ ∀ x, x ∈ s → p x := Iff.rfl theorem setOf_subset {p : α → Prop} {s : Set α} : setOf p ⊆ s ↔ ∀ x, p x → x ∈ s := Iff.rfl @[simp] theorem setOf_subset_setOf {p q : α → Prop} : { a | p a } ⊆ { a | q a } ↔ ∀ a, p a → q a := Iff.rfl theorem setOf_and {p q : α → Prop} : { a | p a ∧ q a } = { a | p a } ∩ { a | q a } := rfl theorem setOf_or {p q : α → Prop} : { a | p a ∨ q a } = { a | p a } ∪ { a | q a } := rfl /-! ### Subset and strict subset relations -/ instance : IsRefl (Set α) (· ⊆ ·) := show IsRefl (Set α) (· ≤ ·) by infer_instance instance : IsTrans (Set α) (· ⊆ ·) := show IsTrans (Set α) (· ≤ ·) by infer_instance instance : Trans ((· ⊆ ·) : Set α → Set α → Prop) (· ⊆ ·) (· ⊆ ·) := show Trans (· ≤ ·) (· ≤ ·) (· ≤ ·) by infer_instance instance : IsAntisymm (Set α) (· ⊆ ·) := show IsAntisymm (Set α) (· ≤ ·) by infer_instance instance : IsIrrefl (Set α) (· ⊂ ·) := show IsIrrefl (Set α) (· < ·) by infer_instance instance : IsTrans (Set α) (· ⊂ ·) := show IsTrans (Set α) (· < ·) by infer_instance instance : Trans ((· ⊂ ·) : Set α → Set α → Prop) (· ⊂ ·) (· ⊂ ·) := show Trans (· < ·) (· < ·) (· < ·) by infer_instance instance : Trans ((· ⊂ ·) : Set α → Set α → Prop) (· ⊆ ·) (· ⊂ ·) := show Trans (· < ·) (· ≤ ·) (· < ·) by infer_instance instance : Trans ((· ⊆ ·) : Set α → Set α → Prop) (· ⊂ ·) (· ⊂ ·) := show Trans (· ≤ ·) (· < ·) (· < ·) by infer_instance instance : IsAsymm (Set α) (· ⊂ ·) := show IsAsymm (Set α) (· < ·) by infer_instance instance : IsNonstrictStrictOrder (Set α) (· ⊆ ·) (· ⊂ ·) := ⟨fun _ _ => Iff.rfl⟩ -- TODO(Jeremy): write a tactic to unfold specific instances of generic notation? theorem subset_def : (s ⊆ t) = ∀ x, x ∈ s → x ∈ t := rfl theorem ssubset_def : (s ⊂ t) = (s ⊆ t ∧ ¬t ⊆ s) := rfl @[refl] theorem Subset.refl (a : Set α) : a ⊆ a := fun _ => id theorem Subset.rfl {s : Set α} : s ⊆ s := Subset.refl s @[trans] theorem Subset.trans {a b c : Set α} (ab : a ⊆ b) (bc : b ⊆ c) : a ⊆ c := fun _ h => bc <| ab h @[trans] theorem mem_of_eq_of_mem {x y : α} {s : Set α} (hx : x = y) (h : y ∈ s) : x ∈ s := hx.symm ▸ h theorem Subset.antisymm {a b : Set α} (h₁ : a ⊆ b) (h₂ : b ⊆ a) : a = b := Set.ext fun _ => ⟨@h₁ _, @h₂ _⟩ theorem Subset.antisymm_iff {a b : Set α} : a = b ↔ a ⊆ b ∧ b ⊆ a := ⟨fun e => ⟨e.subset, e.symm.subset⟩, fun ⟨h₁, h₂⟩ => Subset.antisymm h₁ h₂⟩ -- an alternative name theorem eq_of_subset_of_subset {a b : Set α} : a ⊆ b → b ⊆ a → a = b := Subset.antisymm theorem mem_of_subset_of_mem {s₁ s₂ : Set α} {a : α} (h : s₁ ⊆ s₂) : a ∈ s₁ → a ∈ s₂ := @h _ theorem not_mem_subset (h : s ⊆ t) : a ∉ t → a ∉ s := mt <| mem_of_subset_of_mem h theorem not_subset : ¬s ⊆ t ↔ ∃ a ∈ s, a ∉ t := by simp only [subset_def, not_forall, exists_prop] theorem not_top_subset : ¬⊤ ⊆ s ↔ ∃ a, a ∉ s := by simp [not_subset] lemma eq_of_forall_subset_iff (h : ∀ u, s ⊆ u ↔ t ⊆ u) : s = t := eq_of_forall_ge_iff h /-! ### Definition of strict subsets `s ⊂ t` and basic properties. -/ protected theorem eq_or_ssubset_of_subset (h : s ⊆ t) : s = t ∨ s ⊂ t := eq_or_lt_of_le h theorem exists_of_ssubset {s t : Set α} (h : s ⊂ t) : ∃ x ∈ t, x ∉ s := not_subset.1 h.2 protected theorem ssubset_iff_subset_ne {s t : Set α} : s ⊂ t ↔ s ⊆ t ∧ s ≠ t := @lt_iff_le_and_ne (Set α) _ s t theorem ssubset_iff_of_subset {s t : Set α} (h : s ⊆ t) : s ⊂ t ↔ ∃ x ∈ t, x ∉ s := ⟨exists_of_ssubset, fun ⟨_, hxt, hxs⟩ => ⟨h, fun h => hxs <| h hxt⟩⟩ theorem ssubset_iff_exists {s t : Set α} : s ⊂ t ↔ s ⊆ t ∧ ∃ x ∈ t, x ∉ s := ⟨fun h ↦ ⟨h.le, Set.exists_of_ssubset h⟩, fun ⟨h1, h2⟩ ↦ (Set.ssubset_iff_of_subset h1).mpr h2⟩ protected theorem ssubset_of_ssubset_of_subset {s₁ s₂ s₃ : Set α} (hs₁s₂ : s₁ ⊂ s₂) (hs₂s₃ : s₂ ⊆ s₃) : s₁ ⊂ s₃ := ⟨Subset.trans hs₁s₂.1 hs₂s₃, fun hs₃s₁ => hs₁s₂.2 (Subset.trans hs₂s₃ hs₃s₁)⟩ protected theorem ssubset_of_subset_of_ssubset {s₁ s₂ s₃ : Set α} (hs₁s₂ : s₁ ⊆ s₂) (hs₂s₃ : s₂ ⊂ s₃) : s₁ ⊂ s₃ := ⟨Subset.trans hs₁s₂ hs₂s₃.1, fun hs₃s₁ => hs₂s₃.2 (Subset.trans hs₃s₁ hs₁s₂)⟩ theorem not_mem_empty (x : α) : ¬x ∈ (∅ : Set α) := id theorem not_not_mem : ¬a ∉ s ↔ a ∈ s := not_not /-! ### Non-empty sets -/ theorem nonempty_coe_sort {s : Set α} : Nonempty ↥s ↔ s.Nonempty := nonempty_subtype alias ⟨_, Nonempty.coe_sort⟩ := nonempty_coe_sort theorem nonempty_def : s.Nonempty ↔ ∃ x, x ∈ s := Iff.rfl theorem nonempty_of_mem {x} (h : x ∈ s) : s.Nonempty := ⟨x, h⟩ theorem Nonempty.not_subset_empty : s.Nonempty → ¬s ⊆ ∅ | ⟨_, hx⟩, hs => hs hx /-- Extract a witness from `s.Nonempty`. This function might be used instead of case analysis on the argument. Note that it makes a proof depend on the `Classical.choice` axiom. -/ protected noncomputable def Nonempty.some (h : s.Nonempty) : α := Classical.choose h protected theorem Nonempty.some_mem (h : s.Nonempty) : h.some ∈ s := Classical.choose_spec h theorem Nonempty.mono (ht : s ⊆ t) (hs : s.Nonempty) : t.Nonempty := hs.imp ht theorem nonempty_of_not_subset (h : ¬s ⊆ t) : (s \ t).Nonempty := let ⟨x, xs, xt⟩ := not_subset.1 h ⟨x, xs, xt⟩ theorem nonempty_of_ssubset (ht : s ⊂ t) : (t \ s).Nonempty := nonempty_of_not_subset ht.2 theorem Nonempty.of_diff (h : (s \ t).Nonempty) : s.Nonempty := h.imp fun _ => And.left theorem nonempty_of_ssubset' (ht : s ⊂ t) : t.Nonempty := (nonempty_of_ssubset ht).of_diff theorem Nonempty.inl (hs : s.Nonempty) : (s ∪ t).Nonempty := hs.imp fun _ => Or.inl theorem Nonempty.inr (ht : t.Nonempty) : (s ∪ t).Nonempty := ht.imp fun _ => Or.inr @[simp] theorem union_nonempty : (s ∪ t).Nonempty ↔ s.Nonempty ∨ t.Nonempty := exists_or theorem Nonempty.left (h : (s ∩ t).Nonempty) : s.Nonempty := h.imp fun _ => And.left theorem Nonempty.right (h : (s ∩ t).Nonempty) : t.Nonempty := h.imp fun _ => And.right theorem inter_nonempty : (s ∩ t).Nonempty ↔ ∃ x, x ∈ s ∧ x ∈ t := Iff.rfl theorem inter_nonempty_iff_exists_left : (s ∩ t).Nonempty ↔ ∃ x ∈ s, x ∈ t := by simp_rw [inter_nonempty] theorem inter_nonempty_iff_exists_right : (s ∩ t).Nonempty ↔ ∃ x ∈ t, x ∈ s := by simp_rw [inter_nonempty, and_comm] theorem nonempty_iff_univ_nonempty : Nonempty α ↔ (univ : Set α).Nonempty := ⟨fun ⟨x⟩ => ⟨x, trivial⟩, fun ⟨x, _⟩ => ⟨x⟩⟩ @[simp] theorem univ_nonempty : ∀ [Nonempty α], (univ : Set α).Nonempty | ⟨x⟩ => ⟨x, trivial⟩ theorem Nonempty.to_subtype : s.Nonempty → Nonempty (↥s) := nonempty_subtype.2 theorem Nonempty.to_type : s.Nonempty → Nonempty α := fun ⟨x, _⟩ => ⟨x⟩ instance univ.nonempty [Nonempty α] : Nonempty (↥(Set.univ : Set α)) := Set.univ_nonempty.to_subtype -- Redeclare for refined keys -- `Nonempty (@Subtype _ (@Membership.mem _ (Set _) _ (@Top.top (Set _) _)))` instance instNonemptyTop [Nonempty α] : Nonempty (⊤ : Set α) := inferInstanceAs (Nonempty (univ : Set α)) theorem Nonempty.of_subtype [Nonempty (↥s)] : s.Nonempty := nonempty_subtype.mp ‹_› @[deprecated (since := "2024-11-23")] alias nonempty_of_nonempty_subtype := Nonempty.of_subtype /-! ### Lemmas about the empty set -/ theorem empty_def : (∅ : Set α) = { _x : α | False } := rfl @[simp] theorem mem_empty_iff_false (x : α) : x ∈ (∅ : Set α) ↔ False := Iff.rfl @[simp] theorem setOf_false : { _a : α | False } = ∅ := rfl @[simp] theorem setOf_bot : { _x : α | ⊥ } = ∅ := rfl @[simp] theorem empty_subset (s : Set α) : ∅ ⊆ s := nofun @[simp] theorem subset_empty_iff {s : Set α} : s ⊆ ∅ ↔ s = ∅ := (Subset.antisymm_iff.trans <| and_iff_left (empty_subset _)).symm theorem eq_empty_iff_forall_not_mem {s : Set α} : s = ∅ ↔ ∀ x, x ∉ s := subset_empty_iff.symm theorem eq_empty_of_forall_not_mem (h : ∀ x, x ∉ s) : s = ∅ := subset_empty_iff.1 h theorem eq_empty_of_subset_empty {s : Set α} : s ⊆ ∅ → s = ∅ := subset_empty_iff.1 theorem eq_empty_of_isEmpty [IsEmpty α] (s : Set α) : s = ∅ := eq_empty_of_subset_empty fun x _ => isEmptyElim x /-- There is exactly one set of a type that is empty. -/ instance uniqueEmpty [IsEmpty α] : Unique (Set α) where default := ∅ uniq := eq_empty_of_isEmpty /-- See also `Set.nonempty_iff_ne_empty`. -/ theorem not_nonempty_iff_eq_empty {s : Set α} : ¬s.Nonempty ↔ s = ∅ := by simp only [Set.Nonempty, not_exists, eq_empty_iff_forall_not_mem] /-- See also `Set.not_nonempty_iff_eq_empty`. -/ theorem nonempty_iff_ne_empty : s.Nonempty ↔ s ≠ ∅ := not_nonempty_iff_eq_empty.not_right /-- See also `nonempty_iff_ne_empty'`. -/ theorem not_nonempty_iff_eq_empty' : ¬Nonempty s ↔ s = ∅ := by rw [nonempty_subtype, not_exists, eq_empty_iff_forall_not_mem] /-- See also `not_nonempty_iff_eq_empty'`. -/ theorem nonempty_iff_ne_empty' : Nonempty s ↔ s ≠ ∅ := not_nonempty_iff_eq_empty'.not_right alias ⟨Nonempty.ne_empty, _⟩ := nonempty_iff_ne_empty @[simp] theorem not_nonempty_empty : ¬(∅ : Set α).Nonempty := fun ⟨_, hx⟩ => hx @[simp] theorem isEmpty_coe_sort {s : Set α} : IsEmpty (↥s) ↔ s = ∅ := not_iff_not.1 <| by simpa using nonempty_iff_ne_empty theorem eq_empty_or_nonempty (s : Set α) : s = ∅ ∨ s.Nonempty := or_iff_not_imp_left.2 nonempty_iff_ne_empty.2 theorem subset_eq_empty {s t : Set α} (h : t ⊆ s) (e : s = ∅) : t = ∅ := subset_empty_iff.1 <| e ▸ h theorem forall_mem_empty {p : α → Prop} : (∀ x ∈ (∅ : Set α), p x) ↔ True := iff_true_intro fun _ => False.elim instance (α : Type u) : IsEmpty.{u + 1} (↥(∅ : Set α)) := ⟨fun x => x.2⟩ @[simp] theorem empty_ssubset : ∅ ⊂ s ↔ s.Nonempty := (@bot_lt_iff_ne_bot (Set α) _ _ _).trans nonempty_iff_ne_empty.symm alias ⟨_, Nonempty.empty_ssubset⟩ := empty_ssubset /-! ### Universal set. In Lean `@univ α` (or `univ : Set α`) is the set that contains all elements of type `α`. Mathematically it is the same as `α` but it has a different type. -/ @[simp] theorem setOf_true : { _x : α | True } = univ := rfl @[simp] theorem setOf_top : { _x : α | ⊤ } = univ := rfl @[simp] theorem univ_eq_empty_iff : (univ : Set α) = ∅ ↔ IsEmpty α := eq_empty_iff_forall_not_mem.trans ⟨fun H => ⟨fun x => H x trivial⟩, fun H x _ => @IsEmpty.false α H x⟩ theorem empty_ne_univ [Nonempty α] : (∅ : Set α) ≠ univ := fun e => not_isEmpty_of_nonempty α <| univ_eq_empty_iff.1 e.symm @[simp] theorem subset_univ (s : Set α) : s ⊆ univ := fun _ _ => trivial @[simp] theorem univ_subset_iff {s : Set α} : univ ⊆ s ↔ s = univ := @top_le_iff _ _ _ s alias ⟨eq_univ_of_univ_subset, _⟩ := univ_subset_iff theorem eq_univ_iff_forall {s : Set α} : s = univ ↔ ∀ x, x ∈ s := univ_subset_iff.symm.trans <| forall_congr' fun _ => imp_iff_right trivial theorem eq_univ_of_forall {s : Set α} : (∀ x, x ∈ s) → s = univ := eq_univ_iff_forall.2 theorem Nonempty.eq_univ [Subsingleton α] : s.Nonempty → s = univ := by rintro ⟨x, hx⟩ exact eq_univ_of_forall fun y => by rwa [Subsingleton.elim y x] theorem eq_univ_of_subset {s t : Set α} (h : s ⊆ t) (hs : s = univ) : t = univ := eq_univ_of_univ_subset <| (hs ▸ h : univ ⊆ t) theorem exists_mem_of_nonempty (α) : ∀ [Nonempty α], ∃ x : α, x ∈ (univ : Set α) | ⟨x⟩ => ⟨x, trivial⟩ theorem ne_univ_iff_exists_not_mem {α : Type*} (s : Set α) : s ≠ univ ↔ ∃ a, a ∉ s := by rw [← not_forall, ← eq_univ_iff_forall] theorem not_subset_iff_exists_mem_not_mem {α : Type*} {s t : Set α} : ¬s ⊆ t ↔ ∃ x, x ∈ s ∧ x ∉ t := by simp [subset_def] theorem univ_unique [Unique α] : @Set.univ α = {default} := Set.ext fun x => iff_of_true trivial <| Subsingleton.elim x default theorem ssubset_univ_iff : s ⊂ univ ↔ s ≠ univ := lt_top_iff_ne_top instance nontrivial_of_nonempty [Nonempty α] : Nontrivial (Set α) := ⟨⟨∅, univ, empty_ne_univ⟩⟩ /-! ### Lemmas about union -/ theorem union_def {s₁ s₂ : Set α} : s₁ ∪ s₂ = { a | a ∈ s₁ ∨ a ∈ s₂ } := rfl theorem mem_union_left {x : α} {a : Set α} (b : Set α) : x ∈ a → x ∈ a ∪ b := Or.inl theorem mem_union_right {x : α} {b : Set α} (a : Set α) : x ∈ b → x ∈ a ∪ b := Or.inr theorem mem_or_mem_of_mem_union {x : α} {a b : Set α} (H : x ∈ a ∪ b) : x ∈ a ∨ x ∈ b := H theorem MemUnion.elim {x : α} {a b : Set α} {P : Prop} (H₁ : x ∈ a ∪ b) (H₂ : x ∈ a → P) (H₃ : x ∈ b → P) : P := Or.elim H₁ H₂ H₃ @[simp] theorem mem_union (x : α) (a b : Set α) : x ∈ a ∪ b ↔ x ∈ a ∨ x ∈ b := Iff.rfl @[simp] theorem union_self (a : Set α) : a ∪ a = a := ext fun _ => or_self_iff @[simp] theorem union_empty (a : Set α) : a ∪ ∅ = a := ext fun _ => iff_of_eq (or_false _) @[simp] theorem empty_union (a : Set α) : ∅ ∪ a = a := ext fun _ => iff_of_eq (false_or _) theorem union_comm (a b : Set α) : a ∪ b = b ∪ a := ext fun _ => or_comm theorem union_assoc (a b c : Set α) : a ∪ b ∪ c = a ∪ (b ∪ c) := ext fun _ => or_assoc instance union_isAssoc : Std.Associative (α := Set α) (· ∪ ·) := ⟨union_assoc⟩ instance union_isComm : Std.Commutative (α := Set α) (· ∪ ·) := ⟨union_comm⟩ theorem union_left_comm (s₁ s₂ s₃ : Set α) : s₁ ∪ (s₂ ∪ s₃) = s₂ ∪ (s₁ ∪ s₃) := ext fun _ => or_left_comm theorem union_right_comm (s₁ s₂ s₃ : Set α) : s₁ ∪ s₂ ∪ s₃ = s₁ ∪ s₃ ∪ s₂ := ext fun _ => or_right_comm @[simp] theorem union_eq_left {s t : Set α} : s ∪ t = s ↔ t ⊆ s := sup_eq_left @[simp] theorem union_eq_right {s t : Set α} : s ∪ t = t ↔ s ⊆ t := sup_eq_right theorem union_eq_self_of_subset_left {s t : Set α} (h : s ⊆ t) : s ∪ t = t := union_eq_right.mpr h theorem union_eq_self_of_subset_right {s t : Set α} (h : t ⊆ s) : s ∪ t = s := union_eq_left.mpr h @[simp] theorem subset_union_left {s t : Set α} : s ⊆ s ∪ t := fun _ => Or.inl @[simp] theorem subset_union_right {s t : Set α} : t ⊆ s ∪ t := fun _ => Or.inr theorem union_subset {s t r : Set α} (sr : s ⊆ r) (tr : t ⊆ r) : s ∪ t ⊆ r := fun _ => Or.rec (@sr _) (@tr _) @[simp] theorem union_subset_iff {s t u : Set α} : s ∪ t ⊆ u ↔ s ⊆ u ∧ t ⊆ u := (forall_congr' fun _ => or_imp).trans forall_and @[gcongr] theorem union_subset_union {s₁ s₂ t₁ t₂ : Set α} (h₁ : s₁ ⊆ s₂) (h₂ : t₁ ⊆ t₂) : s₁ ∪ t₁ ⊆ s₂ ∪ t₂ := fun _ => Or.imp (@h₁ _) (@h₂ _) @[gcongr] theorem union_subset_union_left {s₁ s₂ : Set α} (t) (h : s₁ ⊆ s₂) : s₁ ∪ t ⊆ s₂ ∪ t := union_subset_union h Subset.rfl @[gcongr] theorem union_subset_union_right (s) {t₁ t₂ : Set α} (h : t₁ ⊆ t₂) : s ∪ t₁ ⊆ s ∪ t₂ := union_subset_union Subset.rfl h theorem subset_union_of_subset_left {s t : Set α} (h : s ⊆ t) (u : Set α) : s ⊆ t ∪ u := h.trans subset_union_left theorem subset_union_of_subset_right {s u : Set α} (h : s ⊆ u) (t : Set α) : s ⊆ t ∪ u := h.trans subset_union_right theorem union_congr_left (ht : t ⊆ s ∪ u) (hu : u ⊆ s ∪ t) : s ∪ t = s ∪ u := sup_congr_left ht hu theorem union_congr_right (hs : s ⊆ t ∪ u) (ht : t ⊆ s ∪ u) : s ∪ u = t ∪ u := sup_congr_right hs ht theorem union_eq_union_iff_left : s ∪ t = s ∪ u ↔ t ⊆ s ∪ u ∧ u ⊆ s ∪ t := sup_eq_sup_iff_left theorem union_eq_union_iff_right : s ∪ u = t ∪ u ↔ s ⊆ t ∪ u ∧ t ⊆ s ∪ u := sup_eq_sup_iff_right @[simp] theorem union_empty_iff {s t : Set α} : s ∪ t = ∅ ↔ s = ∅ ∧ t = ∅ := by simp only [← subset_empty_iff] exact union_subset_iff @[simp] theorem union_univ (s : Set α) : s ∪ univ = univ := sup_top_eq _ @[simp] theorem univ_union (s : Set α) : univ ∪ s = univ := top_sup_eq _ @[simp] theorem ssubset_union_left_iff : s ⊂ s ∪ t ↔ ¬ t ⊆ s := left_lt_sup @[simp] theorem ssubset_union_right_iff : t ⊂ s ∪ t ↔ ¬ s ⊆ t := right_lt_sup /-! ### Lemmas about intersection -/ theorem inter_def {s₁ s₂ : Set α} : s₁ ∩ s₂ = { a | a ∈ s₁ ∧ a ∈ s₂ } := rfl @[simp, mfld_simps] theorem mem_inter_iff (x : α) (a b : Set α) : x ∈ a ∩ b ↔ x ∈ a ∧ x ∈ b := Iff.rfl theorem mem_inter {x : α} {a b : Set α} (ha : x ∈ a) (hb : x ∈ b) : x ∈ a ∩ b := ⟨ha, hb⟩ theorem mem_of_mem_inter_left {x : α} {a b : Set α} (h : x ∈ a ∩ b) : x ∈ a := h.left theorem mem_of_mem_inter_right {x : α} {a b : Set α} (h : x ∈ a ∩ b) : x ∈ b := h.right @[simp] theorem inter_self (a : Set α) : a ∩ a = a := ext fun _ => and_self_iff @[simp] theorem inter_empty (a : Set α) : a ∩ ∅ = ∅ := ext fun _ => iff_of_eq (and_false _) @[simp] theorem empty_inter (a : Set α) : ∅ ∩ a = ∅ := ext fun _ => iff_of_eq (false_and _) theorem inter_comm (a b : Set α) : a ∩ b = b ∩ a := ext fun _ => and_comm theorem inter_assoc (a b c : Set α) : a ∩ b ∩ c = a ∩ (b ∩ c) := ext fun _ => and_assoc instance inter_isAssoc : Std.Associative (α := Set α) (· ∩ ·) := ⟨inter_assoc⟩ instance inter_isComm : Std.Commutative (α := Set α) (· ∩ ·) := ⟨inter_comm⟩ theorem inter_left_comm (s₁ s₂ s₃ : Set α) : s₁ ∩ (s₂ ∩ s₃) = s₂ ∩ (s₁ ∩ s₃) := ext fun _ => and_left_comm theorem inter_right_comm (s₁ s₂ s₃ : Set α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ s₃ ∩ s₂ := ext fun _ => and_right_comm @[simp, mfld_simps] theorem inter_subset_left {s t : Set α} : s ∩ t ⊆ s := fun _ => And.left @[simp] theorem inter_subset_right {s t : Set α} : s ∩ t ⊆ t := fun _ => And.right theorem subset_inter {s t r : Set α} (rs : r ⊆ s) (rt : r ⊆ t) : r ⊆ s ∩ t := fun _ h => ⟨rs h, rt h⟩ @[simp] theorem subset_inter_iff {s t r : Set α} : r ⊆ s ∩ t ↔ r ⊆ s ∧ r ⊆ t := (forall_congr' fun _ => imp_and).trans forall_and @[simp] lemma inter_eq_left : s ∩ t = s ↔ s ⊆ t := inf_eq_left @[simp] lemma inter_eq_right : s ∩ t = t ↔ t ⊆ s := inf_eq_right @[simp] lemma left_eq_inter : s = s ∩ t ↔ s ⊆ t := left_eq_inf @[simp] lemma right_eq_inter : t = s ∩ t ↔ t ⊆ s := right_eq_inf theorem inter_eq_self_of_subset_left {s t : Set α} : s ⊆ t → s ∩ t = s := inter_eq_left.mpr theorem inter_eq_self_of_subset_right {s t : Set α} : t ⊆ s → s ∩ t = t := inter_eq_right.mpr theorem inter_congr_left (ht : s ∩ u ⊆ t) (hu : s ∩ t ⊆ u) : s ∩ t = s ∩ u := inf_congr_left ht hu theorem inter_congr_right (hs : t ∩ u ⊆ s) (ht : s ∩ u ⊆ t) : s ∩ u = t ∩ u := inf_congr_right hs ht theorem inter_eq_inter_iff_left : s ∩ t = s ∩ u ↔ s ∩ u ⊆ t ∧ s ∩ t ⊆ u := inf_eq_inf_iff_left theorem inter_eq_inter_iff_right : s ∩ u = t ∩ u ↔ t ∩ u ⊆ s ∧ s ∩ u ⊆ t := inf_eq_inf_iff_right @[simp, mfld_simps] theorem inter_univ (a : Set α) : a ∩ univ = a := inf_top_eq _ @[simp, mfld_simps] theorem univ_inter (a : Set α) : univ ∩ a = a := top_inf_eq _ @[gcongr] theorem inter_subset_inter {s₁ s₂ t₁ t₂ : Set α} (h₁ : s₁ ⊆ t₁) (h₂ : s₂ ⊆ t₂) : s₁ ∩ s₂ ⊆ t₁ ∩ t₂ := fun _ => And.imp (@h₁ _) (@h₂ _) @[gcongr] theorem inter_subset_inter_left {s t : Set α} (u : Set α) (H : s ⊆ t) : s ∩ u ⊆ t ∩ u := inter_subset_inter H Subset.rfl @[gcongr] theorem inter_subset_inter_right {s t : Set α} (u : Set α) (H : s ⊆ t) : u ∩ s ⊆ u ∩ t := inter_subset_inter Subset.rfl H theorem union_inter_cancel_left {s t : Set α} : (s ∪ t) ∩ s = s := inter_eq_self_of_subset_right subset_union_left theorem union_inter_cancel_right {s t : Set α} : (s ∪ t) ∩ t = t := inter_eq_self_of_subset_right subset_union_right theorem inter_setOf_eq_sep (s : Set α) (p : α → Prop) : s ∩ {a | p a} = {a ∈ s | p a} := rfl theorem setOf_inter_eq_sep (p : α → Prop) (s : Set α) : {a | p a} ∩ s = {a ∈ s | p a} := inter_comm _ _ @[simp] theorem inter_ssubset_right_iff : s ∩ t ⊂ t ↔ ¬ t ⊆ s := inf_lt_right @[simp] theorem inter_ssubset_left_iff : s ∩ t ⊂ s ↔ ¬ s ⊆ t := inf_lt_left /-! ### Distributivity laws -/ theorem inter_union_distrib_left (s t u : Set α) : s ∩ (t ∪ u) = s ∩ t ∪ s ∩ u := inf_sup_left _ _ _ theorem union_inter_distrib_right (s t u : Set α) : (s ∪ t) ∩ u = s ∩ u ∪ t ∩ u := inf_sup_right _ _ _ theorem union_inter_distrib_left (s t u : Set α) : s ∪ t ∩ u = (s ∪ t) ∩ (s ∪ u) := sup_inf_left _ _ _ theorem inter_union_distrib_right (s t u : Set α) : s ∩ t ∪ u = (s ∪ u) ∩ (t ∪ u) := sup_inf_right _ _ _ theorem union_union_distrib_left (s t u : Set α) : s ∪ (t ∪ u) = s ∪ t ∪ (s ∪ u) := sup_sup_distrib_left _ _ _ theorem union_union_distrib_right (s t u : Set α) : s ∪ t ∪ u = s ∪ u ∪ (t ∪ u) := sup_sup_distrib_right _ _ _ theorem inter_inter_distrib_left (s t u : Set α) : s ∩ (t ∩ u) = s ∩ t ∩ (s ∩ u) := inf_inf_distrib_left _ _ _ theorem inter_inter_distrib_right (s t u : Set α) : s ∩ t ∩ u = s ∩ u ∩ (t ∩ u) := inf_inf_distrib_right _ _ _ theorem union_union_union_comm (s t u v : Set α) : s ∪ t ∪ (u ∪ v) = s ∪ u ∪ (t ∪ v) := sup_sup_sup_comm _ _ _ _ theorem inter_inter_inter_comm (s t u v : Set α) : s ∩ t ∩ (u ∩ v) = s ∩ u ∩ (t ∩ v) := inf_inf_inf_comm _ _ _ _ /-! ### Lemmas about sets defined as `{x ∈ s | p x}`. -/ section Sep variable {p q : α → Prop} {x : α} theorem mem_sep (xs : x ∈ s) (px : p x) : x ∈ { x ∈ s | p x } := ⟨xs, px⟩ @[simp] theorem sep_mem_eq : { x ∈ s | x ∈ t } = s ∩ t := rfl @[simp] theorem mem_sep_iff : x ∈ { x ∈ s | p x } ↔ x ∈ s ∧ p x := Iff.rfl theorem sep_ext_iff : { x ∈ s | p x } = { x ∈ s | q x } ↔ ∀ x ∈ s, p x ↔ q x := by simp_rw [Set.ext_iff, mem_sep_iff, and_congr_right_iff] theorem sep_eq_of_subset (h : s ⊆ t) : { x ∈ t | x ∈ s } = s := inter_eq_self_of_subset_right h @[simp] theorem sep_subset (s : Set α) (p : α → Prop) : { x ∈ s | p x } ⊆ s := fun _ => And.left @[simp] theorem sep_eq_self_iff_mem_true : { x ∈ s | p x } = s ↔ ∀ x ∈ s, p x := by simp_rw [Set.ext_iff, mem_sep_iff, and_iff_left_iff_imp] @[simp] theorem sep_eq_empty_iff_mem_false : { x ∈ s | p x } = ∅ ↔ ∀ x ∈ s, ¬p x := by simp_rw [Set.ext_iff, mem_sep_iff, mem_empty_iff_false, iff_false, not_and] theorem sep_true : { x ∈ s | True } = s := inter_univ s theorem sep_false : { x ∈ s | False } = ∅ := inter_empty s theorem sep_empty (p : α → Prop) : { x ∈ (∅ : Set α) | p x } = ∅ := empty_inter {x | p x} theorem sep_univ : { x ∈ (univ : Set α) | p x } = { x | p x } := univ_inter {x | p x} @[simp] theorem sep_union : { x | (x ∈ s ∨ x ∈ t) ∧ p x } = { x ∈ s | p x } ∪ { x ∈ t | p x } := union_inter_distrib_right { x | x ∈ s } { x | x ∈ t } p @[simp] theorem sep_inter : { x | (x ∈ s ∧ x ∈ t) ∧ p x } = { x ∈ s | p x } ∩ { x ∈ t | p x } := inter_inter_distrib_right s t {x | p x} @[simp] theorem sep_and : { x ∈ s | p x ∧ q x } = { x ∈ s | p x } ∩ { x ∈ s | q x } := inter_inter_distrib_left s {x | p x} {x | q x} @[simp] theorem sep_or : { x ∈ s | p x ∨ q x } = { x ∈ s | p x } ∪ { x ∈ s | q x } := inter_union_distrib_left s p q @[simp] theorem sep_setOf : { x ∈ { y | p y } | q x } = { x | p x ∧ q x } := rfl end Sep /-- See also `Set.sdiff_inter_right_comm`. -/ lemma inter_diff_assoc (a b c : Set α) : (a ∩ b) \ c = a ∩ (b \ c) := inf_sdiff_assoc .. /-- See also `Set.inter_diff_assoc`. -/ lemma sdiff_inter_right_comm (s t u : Set α) : s \ t ∩ u = (s ∩ u) \ t := sdiff_inf_right_comm .. lemma inter_sdiff_left_comm (s t u : Set α) : s ∩ (t \ u) = t ∩ (s \ u) := inf_sdiff_left_comm .. theorem diff_union_diff_cancel (hts : t ⊆ s) (hut : u ⊆ t) : s \ t ∪ t \ u = s \ u := sdiff_sup_sdiff_cancel hts hut /-- A version of `diff_union_diff_cancel` with more general hypotheses. -/ theorem diff_union_diff_cancel' (hi : s ∩ u ⊆ t) (hu : t ⊆ s ∪ u) : (s \ t) ∪ (t \ u) = s \ u := sdiff_sup_sdiff_cancel' hi hu theorem diff_diff_eq_sdiff_union (h : u ⊆ s) : s \ (t \ u) = s \ t ∪ u := sdiff_sdiff_eq_sdiff_sup h theorem inter_diff_distrib_left (s t u : Set α) : s ∩ (t \ u) = (s ∩ t) \ (s ∩ u) := inf_sdiff_distrib_left _ _ _ theorem inter_diff_distrib_right (s t u : Set α) : (s \ t) ∩ u = (s ∩ u) \ (t ∩ u) := inf_sdiff_distrib_right _ _ _ theorem diff_inter_distrib_right (s t r : Set α) : (t ∩ r) \ s = (t \ s) ∩ (r \ s) := inf_sdiff /-! ### Lemmas about complement -/ theorem compl_def (s : Set α) : sᶜ = { x | x ∉ s } := rfl theorem mem_compl {s : Set α} {x : α} (h : x ∉ s) : x ∈ sᶜ := h theorem compl_setOf {α} (p : α → Prop) : { a | p a }ᶜ = { a | ¬p a } := rfl theorem not_mem_of_mem_compl {s : Set α} {x : α} (h : x ∈ sᶜ) : x ∉ s := h theorem not_mem_compl_iff {x : α} : x ∉ sᶜ ↔ x ∈ s := not_not @[simp] theorem inter_compl_self (s : Set α) : s ∩ sᶜ = ∅ := inf_compl_eq_bot @[simp] theorem compl_inter_self (s : Set α) : sᶜ ∩ s = ∅ := compl_inf_eq_bot @[simp] theorem compl_empty : (∅ : Set α)ᶜ = univ := compl_bot @[simp] theorem compl_union (s t : Set α) : (s ∪ t)ᶜ = sᶜ ∩ tᶜ := compl_sup theorem compl_inter (s t : Set α) : (s ∩ t)ᶜ = sᶜ ∪ tᶜ := compl_inf @[simp] theorem compl_univ : (univ : Set α)ᶜ = ∅ := compl_top @[simp] theorem compl_empty_iff {s : Set α} : sᶜ = ∅ ↔ s = univ := compl_eq_bot @[simp] theorem compl_univ_iff {s : Set α} : sᶜ = univ ↔ s = ∅ := compl_eq_top theorem compl_ne_univ : sᶜ ≠ univ ↔ s.Nonempty := compl_univ_iff.not.trans nonempty_iff_ne_empty.symm lemma inl_compl_union_inr_compl {α β : Type*} {s : Set α} {t : Set β} : Sum.inl '' sᶜ ∪ Sum.inr '' tᶜ = (Sum.inl '' s ∪ Sum.inr '' t)ᶜ := by rw [compl_union] aesop theorem nonempty_compl : sᶜ.Nonempty ↔ s ≠ univ := (ne_univ_iff_exists_not_mem s).symm theorem union_eq_compl_compl_inter_compl (s t : Set α) : s ∪ t = (sᶜ ∩ tᶜ)ᶜ := ext fun _ => or_iff_not_and_not theorem inter_eq_compl_compl_union_compl (s t : Set α) : s ∩ t = (sᶜ ∪ tᶜ)ᶜ := ext fun _ => and_iff_not_or_not @[simp] theorem union_compl_self (s : Set α) : s ∪ sᶜ = univ := eq_univ_iff_forall.2 fun _ => em _ @[simp] theorem compl_union_self (s : Set α) : sᶜ ∪ s = univ := by rw [union_comm, union_compl_self] theorem compl_subset_comm : sᶜ ⊆ t ↔ tᶜ ⊆ s := @compl_le_iff_compl_le _ s _ _ theorem subset_compl_comm : s ⊆ tᶜ ↔ t ⊆ sᶜ := @le_compl_iff_le_compl _ _ _ t @[simp] theorem compl_subset_compl : sᶜ ⊆ tᶜ ↔ t ⊆ s := @compl_le_compl_iff_le (Set α) _ _ _ @[gcongr] theorem compl_subset_compl_of_subset (h : t ⊆ s) : sᶜ ⊆ tᶜ := compl_subset_compl.2 h theorem subset_union_compl_iff_inter_subset {s t u : Set α} : s ⊆ t ∪ uᶜ ↔ s ∩ u ⊆ t := (@isCompl_compl _ u _).le_sup_right_iff_inf_left_le theorem compl_subset_iff_union {s t : Set α} : sᶜ ⊆ t ↔ s ∪ t = univ := Iff.symm <| eq_univ_iff_forall.trans <| forall_congr' fun _ => or_iff_not_imp_left theorem inter_subset (a b c : Set α) : a ∩ b ⊆ c ↔ a ⊆ bᶜ ∪ c := forall_congr' fun _ => and_imp.trans <| imp_congr_right fun _ => imp_iff_not_or theorem inter_compl_nonempty_iff {s t : Set α} : (s ∩ tᶜ).Nonempty ↔ ¬s ⊆ t := (not_subset.trans <| exists_congr fun x => by simp [mem_compl]).symm /-! ### Lemmas about set difference -/ theorem not_mem_diff_of_mem {s t : Set α} {x : α} (hx : x ∈ t) : x ∉ s \ t := fun h => h.2 hx theorem mem_of_mem_diff {s t : Set α} {x : α} (h : x ∈ s \ t) : x ∈ s := h.left theorem not_mem_of_mem_diff {s t : Set α} {x : α} (h : x ∈ s \ t) : x ∉ t := h.right theorem diff_eq_compl_inter {s t : Set α} : s \ t = tᶜ ∩ s := by rw [diff_eq, inter_comm] theorem diff_nonempty {s t : Set α} : (s \ t).Nonempty ↔ ¬s ⊆ t := inter_compl_nonempty_iff theorem diff_subset {s t : Set α} : s \ t ⊆ s := show s \ t ≤ s from sdiff_le theorem diff_subset_compl (s t : Set α) : s \ t ⊆ tᶜ := diff_eq_compl_inter ▸ inter_subset_left theorem union_diff_cancel' {s t u : Set α} (h₁ : s ⊆ t) (h₂ : t ⊆ u) : t ∪ u \ s = u := sup_sdiff_cancel' h₁ h₂ theorem union_diff_cancel {s t : Set α} (h : s ⊆ t) : s ∪ t \ s = t := sup_sdiff_cancel_right h theorem union_diff_cancel_left {s t : Set α} (h : s ∩ t ⊆ ∅) : (s ∪ t) \ s = t := Disjoint.sup_sdiff_cancel_left <| disjoint_iff_inf_le.2 h theorem union_diff_cancel_right {s t : Set α} (h : s ∩ t ⊆ ∅) : (s ∪ t) \ t = s := Disjoint.sup_sdiff_cancel_right <| disjoint_iff_inf_le.2 h @[simp] theorem union_diff_left {s t : Set α} : (s ∪ t) \ s = t \ s := sup_sdiff_left_self @[simp] theorem union_diff_right {s t : Set α} : (s ∪ t) \ t = s \ t := sup_sdiff_right_self theorem union_diff_distrib {s t u : Set α} : (s ∪ t) \ u = s \ u ∪ t \ u := sup_sdiff @[simp] theorem inter_diff_self (a b : Set α) : a ∩ (b \ a) = ∅ := inf_sdiff_self_right @[simp] theorem inter_union_diff (s t : Set α) : s ∩ t ∪ s \ t = s := sup_inf_sdiff s t @[simp] theorem diff_union_inter (s t : Set α) : s \ t ∪ s ∩ t = s := by rw [union_comm] exact sup_inf_sdiff _ _ @[simp] theorem inter_union_compl (s t : Set α) : s ∩ t ∪ s ∩ tᶜ = s := inter_union_diff _ _ @[gcongr] theorem diff_subset_diff {s₁ s₂ t₁ t₂ : Set α} : s₁ ⊆ s₂ → t₂ ⊆ t₁ → s₁ \ t₁ ⊆ s₂ \ t₂ := show s₁ ≤ s₂ → t₂ ≤ t₁ → s₁ \ t₁ ≤ s₂ \ t₂ from sdiff_le_sdiff @[gcongr] theorem diff_subset_diff_left {s₁ s₂ t : Set α} (h : s₁ ⊆ s₂) : s₁ \ t ⊆ s₂ \ t := sdiff_le_sdiff_right ‹s₁ ≤ s₂› @[gcongr] theorem diff_subset_diff_right {s t u : Set α} (h : t ⊆ u) : s \ u ⊆ s \ t := sdiff_le_sdiff_left ‹t ≤ u› theorem diff_subset_diff_iff_subset {r : Set α} (hs : s ⊆ r) (ht : t ⊆ r) : r \ s ⊆ r \ t ↔ t ⊆ s := sdiff_le_sdiff_iff_le hs ht theorem compl_eq_univ_diff (s : Set α) : sᶜ = univ \ s := top_sdiff.symm @[simp] theorem empty_diff (s : Set α) : (∅ \ s : Set α) = ∅ := bot_sdiff theorem diff_eq_empty {s t : Set α} : s \ t = ∅ ↔ s ⊆ t := sdiff_eq_bot_iff @[simp] theorem diff_empty {s : Set α} : s \ ∅ = s := sdiff_bot @[simp] theorem diff_univ (s : Set α) : s \ univ = ∅ := diff_eq_empty.2 (subset_univ s) theorem diff_diff {u : Set α} : (s \ t) \ u = s \ (t ∪ u) := sdiff_sdiff_left -- the following statement contains parentheses to help the reader theorem diff_diff_comm {s t u : Set α} : (s \ t) \ u = (s \ u) \ t := sdiff_sdiff_comm theorem diff_subset_iff {s t u : Set α} : s \ t ⊆ u ↔ s ⊆ t ∪ u := show s \ t ≤ u ↔ s ≤ t ∪ u from sdiff_le_iff theorem subset_diff_union (s t : Set α) : s ⊆ s \ t ∪ t := show s ≤ s \ t ∪ t from le_sdiff_sup theorem diff_union_of_subset {s t : Set α} (h : t ⊆ s) : s \ t ∪ t = s := Subset.antisymm (union_subset diff_subset h) (subset_diff_union _ _) theorem diff_subset_comm {s t u : Set α} : s \ t ⊆ u ↔ s \ u ⊆ t := show s \ t ≤ u ↔ s \ u ≤ t from sdiff_le_comm theorem diff_inter {s t u : Set α} : s \ (t ∩ u) = s \ t ∪ s \ u := sdiff_inf theorem diff_inter_diff : s \ t ∩ (s \ u) = s \ (t ∪ u) := sdiff_sup.symm theorem diff_compl : s \ tᶜ = s ∩ t := sdiff_compl theorem compl_diff : (t \ s)ᶜ = s ∪ tᶜ := Eq.trans compl_sdiff himp_eq theorem diff_diff_right {s t u : Set α} : s \ (t \ u) = s \ t ∪ s ∩ u := sdiff_sdiff_right' theorem inter_diff_right_comm : (s ∩ t) \ u = s \ u ∩ t := by rw [diff_eq, diff_eq, inter_right_comm] theorem diff_inter_right_comm : (s \ u) ∩ t = (s ∩ t) \ u := by rw [diff_eq, diff_eq, inter_right_comm] @[simp] theorem union_diff_self {s t : Set α} : s ∪ t \ s = s ∪ t := sup_sdiff_self _ _ @[simp] theorem diff_union_self {s t : Set α} : s \ t ∪ t = s ∪ t := sdiff_sup_self _ _ @[simp] theorem diff_inter_self {a b : Set α} : b \ a ∩ a = ∅ := inf_sdiff_self_left @[simp] theorem diff_inter_self_eq_diff {s t : Set α} : s \ (t ∩ s) = s \ t := sdiff_inf_self_right _ _ @[simp] theorem diff_self_inter {s t : Set α} : s \ (s ∩ t) = s \ t := sdiff_inf_self_left _ _ theorem diff_self {s : Set α} : s \ s = ∅ := sdiff_self theorem diff_diff_right_self (s t : Set α) : s \ (s \ t) = s ∩ t := sdiff_sdiff_right_self theorem diff_diff_cancel_left {s t : Set α} (h : s ⊆ t) : t \ (t \ s) = s := sdiff_sdiff_eq_self h theorem union_eq_diff_union_diff_union_inter (s t : Set α) : s ∪ t = s \ t ∪ t \ s ∪ s ∩ t := sup_eq_sdiff_sup_sdiff_sup_inf /-! ### Powerset -/ theorem mem_powerset {x s : Set α} (h : x ⊆ s) : x ∈ 𝒫 s := @h theorem subset_of_mem_powerset {x s : Set α} (h : x ∈ 𝒫 s) : x ⊆ s := @h @[simp] theorem mem_powerset_iff (x s : Set α) : x ∈ 𝒫 s ↔ x ⊆ s := Iff.rfl theorem powerset_inter (s t : Set α) : 𝒫(s ∩ t) = 𝒫 s ∩ 𝒫 t := ext fun _ => subset_inter_iff @[simp] theorem powerset_mono : 𝒫 s ⊆ 𝒫 t ↔ s ⊆ t := ⟨fun h => @h _ (fun _ h => h), fun h _ hu _ ha => h (hu ha)⟩ theorem monotone_powerset : Monotone (powerset : Set α → Set (Set α)) := fun _ _ => powerset_mono.2 @[simp] theorem powerset_nonempty : (𝒫 s).Nonempty := ⟨∅, fun _ h => empty_subset s h⟩ @[simp] theorem powerset_empty : 𝒫(∅ : Set α) = {∅} := ext fun _ => subset_empty_iff @[simp] theorem powerset_univ : 𝒫(univ : Set α) = univ := eq_univ_of_forall subset_univ /-! ### Sets defined as an if-then-else -/ @[deprecated _root_.mem_dite (since := "2025-01-30")] protected theorem mem_dite (p : Prop) [Decidable p] (s : p → Set α) (t : ¬ p → Set α) (x : α) : (x ∈ if h : p then s h else t h) ↔ (∀ h : p, x ∈ s h) ∧ ∀ h : ¬p, x ∈ t h := _root_.mem_dite theorem mem_dite_univ_right (p : Prop) [Decidable p] (t : p → Set α) (x : α) : (x ∈ if h : p then t h else univ) ↔ ∀ h : p, x ∈ t h := by simp [mem_dite] @[simp] theorem mem_ite_univ_right (p : Prop) [Decidable p] (t : Set α) (x : α) : x ∈ ite p t Set.univ ↔ p → x ∈ t := mem_dite_univ_right p (fun _ => t) x theorem mem_dite_univ_left (p : Prop) [Decidable p] (t : ¬p → Set α) (x : α) : (x ∈ if h : p then univ else t h) ↔ ∀ h : ¬p, x ∈ t h := by split_ifs <;> simp_all @[simp] theorem mem_ite_univ_left (p : Prop) [Decidable p] (t : Set α) (x : α) : x ∈ ite p Set.univ t ↔ ¬p → x ∈ t := mem_dite_univ_left p (fun _ => t) x theorem mem_dite_empty_right (p : Prop) [Decidable p] (t : p → Set α) (x : α) : (x ∈ if h : p then t h else ∅) ↔ ∃ h : p, x ∈ t h := by simp only [mem_dite, mem_empty_iff_false, imp_false, not_not] exact ⟨fun h => ⟨h.2, h.1 h.2⟩, fun ⟨h₁, h₂⟩ => ⟨fun _ => h₂, h₁⟩⟩ @[simp] theorem mem_ite_empty_right (p : Prop) [Decidable p] (t : Set α) (x : α) : x ∈ ite p t ∅ ↔ p ∧ x ∈ t := (mem_dite_empty_right p (fun _ => t) x).trans (by simp) theorem mem_dite_empty_left (p : Prop) [Decidable p] (t : ¬p → Set α) (x : α) : (x ∈ if h : p then ∅ else t h) ↔ ∃ h : ¬p, x ∈ t h := by simp only [mem_dite, mem_empty_iff_false, imp_false] exact ⟨fun h => ⟨h.1, h.2 h.1⟩, fun ⟨h₁, h₂⟩ => ⟨fun h => h₁ h, fun _ => h₂⟩⟩ @[simp] theorem mem_ite_empty_left (p : Prop) [Decidable p] (t : Set α) (x : α) : x ∈ ite p ∅ t ↔ ¬p ∧ x ∈ t := (mem_dite_empty_left p (fun _ => t) x).trans (by simp) /-! ### If-then-else for sets -/ /-- `ite` for sets: `Set.ite t s s' ∩ t = s ∩ t`, `Set.ite t s s' ∩ tᶜ = s' ∩ tᶜ`. Defined as `s ∩ t ∪ s' \ t`. -/ protected def ite (t s s' : Set α) : Set α := s ∩ t ∪ s' \ t @[simp] theorem ite_inter_self (t s s' : Set α) : t.ite s s' ∩ t = s ∩ t := by rw [Set.ite, union_inter_distrib_right, diff_inter_self, inter_assoc, inter_self, union_empty] @[simp] theorem ite_compl (t s s' : Set α) : tᶜ.ite s s' = t.ite s' s := by rw [Set.ite, Set.ite, diff_compl, union_comm, diff_eq] @[simp] theorem ite_inter_compl_self (t s s' : Set α) : t.ite s s' ∩ tᶜ = s' ∩ tᶜ := by rw [← ite_compl, ite_inter_self] @[simp] theorem ite_diff_self (t s s' : Set α) : t.ite s s' \ t = s' \ t := ite_inter_compl_self t s s' @[simp] theorem ite_same (t s : Set α) : t.ite s s = s := inter_union_diff _ _ @[simp] theorem ite_left (s t : Set α) : s.ite s t = s ∪ t := by simp [Set.ite] @[simp] theorem ite_right (s t : Set α) : s.ite t s = t ∩ s := by simp [Set.ite] @[simp] theorem ite_empty (s s' : Set α) : Set.ite ∅ s s' = s' := by simp [Set.ite] @[simp] theorem ite_univ (s s' : Set α) : Set.ite univ s s' = s := by simp [Set.ite] @[simp] theorem ite_empty_left (t s : Set α) : t.ite ∅ s = s \ t := by simp [Set.ite] @[simp] theorem ite_empty_right (t s : Set α) : t.ite s ∅ = s ∩ t := by simp [Set.ite] theorem ite_mono (t : Set α) {s₁ s₁' s₂ s₂' : Set α} (h : s₁ ⊆ s₂) (h' : s₁' ⊆ s₂') : t.ite s₁ s₁' ⊆ t.ite s₂ s₂' := union_subset_union (inter_subset_inter_left _ h) (inter_subset_inter_left _ h') theorem ite_subset_union (t s s' : Set α) : t.ite s s' ⊆ s ∪ s' := union_subset_union inter_subset_left diff_subset theorem inter_subset_ite (t s s' : Set α) : s ∩ s' ⊆ t.ite s s' := ite_same t (s ∩ s') ▸ ite_mono _ inter_subset_left inter_subset_right theorem ite_inter_inter (t s₁ s₂ s₁' s₂' : Set α) : t.ite (s₁ ∩ s₂) (s₁' ∩ s₂') = t.ite s₁ s₁' ∩ t.ite s₂ s₂' := by ext x simp only [Set.ite, Set.mem_inter_iff, Set.mem_diff, Set.mem_union] tauto theorem ite_inter (t s₁ s₂ s : Set α) : t.ite (s₁ ∩ s) (s₂ ∩ s) = t.ite s₁ s₂ ∩ s := by rw [ite_inter_inter, ite_same] theorem ite_inter_of_inter_eq (t : Set α) {s₁ s₂ s : Set α} (h : s₁ ∩ s = s₂ ∩ s) : t.ite s₁ s₂ ∩ s = s₁ ∩ s := by rw [← ite_inter, ← h, ite_same] theorem subset_ite {t s s' u : Set α} : u ⊆ t.ite s s' ↔ u ∩ t ⊆ s ∧ u \ t ⊆ s' := by simp only [subset_def, ← forall_and] refine forall_congr' fun x => ?_ by_cases hx : x ∈ t <;> simp [*, Set.ite] theorem ite_eq_of_subset_left (t : Set α) {s₁ s₂ : Set α} (h : s₁ ⊆ s₂) : t.ite s₁ s₂ = s₁ ∪ (s₂ \ t) := by ext x by_cases hx : x ∈ t <;> simp [*, Set.ite, or_iff_right_of_imp (@h x)] theorem ite_eq_of_subset_right (t : Set α) {s₁ s₂ : Set α} (h : s₂ ⊆ s₁) : t.ite s₁ s₂ = (s₁ ∩ t) ∪ s₂ := by ext x by_cases hx : x ∈ t <;> simp [*, Set.ite, or_iff_left_of_imp (@h x)] end Set open Set namespace Function variable {α : Type*} {β : Type*} theorem Injective.nonempty_apply_iff {f : Set α → Set β} (hf : Injective f) (h2 : f ∅ = ∅) {s : Set α} : (f s).Nonempty ↔ s.Nonempty := by rw [nonempty_iff_ne_empty, ← h2, nonempty_iff_ne_empty, hf.ne_iff] end Function namespace Subsingleton variable {α : Type*} [Subsingleton α] theorem eq_univ_of_nonempty {s : Set α} : s.Nonempty → s = univ := fun ⟨x, hx⟩ => eq_univ_of_forall fun y => Subsingleton.elim x y ▸ hx @[elab_as_elim] theorem set_cases {p : Set α → Prop} (h0 : p ∅) (h1 : p univ) (s) : p s := (s.eq_empty_or_nonempty.elim fun h => h.symm ▸ h0) fun h => (eq_univ_of_nonempty h).symm ▸ h1 theorem mem_iff_nonempty {α : Type*} [Subsingleton α] {s : Set α} {x : α} : x ∈ s ↔ s.Nonempty := ⟨fun hx => ⟨x, hx⟩, fun ⟨y, hy⟩ => Subsingleton.elim y x ▸ hy⟩ end Subsingleton /-! ### Decidability instances for sets -/ namespace Set variable {α : Type u} (s t : Set α) (a b : α) instance decidableSdiff [Decidable (a ∈ s)] [Decidable (a ∈ t)] : Decidable (a ∈ s \ t) := inferInstanceAs (Decidable (a ∈ s ∧ a ∉ t)) instance decidableInter [Decidable (a ∈ s)] [Decidable (a ∈ t)] : Decidable (a ∈ s ∩ t) := inferInstanceAs (Decidable (a ∈ s ∧ a ∈ t)) instance decidableUnion [Decidable (a ∈ s)] [Decidable (a ∈ t)] : Decidable (a ∈ s ∪ t) := inferInstanceAs (Decidable (a ∈ s ∨ a ∈ t)) instance decidableCompl [Decidable (a ∈ s)] : Decidable (a ∈ sᶜ) := inferInstanceAs (Decidable (a ∉ s)) instance decidableEmptyset : Decidable (a ∈ (∅ : Set α)) := Decidable.isFalse (by simp) instance decidableUniv : Decidable (a ∈ univ) := Decidable.isTrue (by simp) instance decidableInsert [Decidable (a = b)] [Decidable (a ∈ s)] : Decidable (a ∈ insert b s) := inferInstanceAs (Decidable (_ ∨ _)) instance decidableSetOf (p : α → Prop) [Decidable (p a)] : Decidable (a ∈ { a | p a }) := by assumption end Set variable {α : Type*} {s t u : Set α} namespace Equiv /-- Given a predicate `p : α → Prop`, produces an equivalence between `Set {a : α // p a}` and `{s : Set α // ∀ a ∈ s, p a}`. -/ protected def setSubtypeComm (p : α → Prop) : Set {a : α // p a} ≃ {s : Set α // ∀ a ∈ s, p a} where toFun s := ⟨{a | ∃ h : p a, s ⟨a, h⟩}, fun _ h ↦ h.1⟩ invFun s := {a | a.val ∈ s.val} left_inv s := by ext a; exact ⟨fun h ↦ h.2, fun h ↦ ⟨a.property, h⟩⟩ right_inv s := by ext; exact ⟨fun h ↦ h.2, fun h ↦ ⟨s.property _ h, h⟩⟩ @[simp] protected lemma setSubtypeComm_apply (p : α → Prop) (s : Set {a // p a}) : (Equiv.setSubtypeComm p) s = ⟨{a | ∃ h : p a, ⟨a, h⟩ ∈ s}, fun _ h ↦ h.1⟩ := rfl @[simp] protected lemma setSubtypeComm_symm_apply (p : α → Prop) (s : {s // ∀ a ∈ s, p a}) : (Equiv.setSubtypeComm p).symm s = {a | a.val ∈ s.val} := rfl end Equiv
Mathlib/Data/Set/Basic.lean
1,577
1,578
/- Copyright (c) 2015, 2017 Jeremy Avigad. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jeremy Avigad, Robert Y. Lewis, Johannes Hölzl, Mario Carneiro, Sébastien Gouëzel -/ import Mathlib.Data.ENNReal.Real import Mathlib.Tactic.Bound.Attribute import Mathlib.Topology.Bornology.Basic import Mathlib.Topology.EMetricSpace.Defs import Mathlib.Topology.UniformSpace.Basic /-! ## Pseudo-metric spaces This file defines pseudo-metric spaces: these differ from metric spaces by not imposing the condition `dist x y = 0 → x = y`. Many definitions and theorems expected on (pseudo-)metric spaces are already introduced on uniform spaces and topological spaces. For example: open and closed sets, compactness, completeness, continuity and uniform continuity. ## Main definitions * `Dist α`: Endows a space `α` with a function `dist a b`. * `PseudoMetricSpace α`: A space endowed with a distance function, which can be zero even if the two elements are non-equal. * `Metric.ball x ε`: The set of all points `y` with `dist y x < ε`. * `Metric.Bounded s`: Whether a subset of a `PseudoMetricSpace` is bounded. * `MetricSpace α`: A `PseudoMetricSpace` with the guarantee `dist x y = 0 → x = y`. Additional useful definitions: * `nndist a b`: `dist` as a function to the non-negative reals. * `Metric.closedBall x ε`: The set of all points `y` with `dist y x ≤ ε`. * `Metric.sphere x ε`: The set of all points `y` with `dist y x = ε`. TODO (anyone): Add "Main results" section. ## Tags pseudo_metric, dist -/ assert_not_exists compactSpace_uniformity open Set Filter TopologicalSpace Bornology open scoped ENNReal NNReal Uniformity Topology universe u v w variable {α : Type u} {β : Type v} {X ι : Type*} theorem UniformSpace.ofDist_aux (ε : ℝ) (hε : 0 < ε) : ∃ δ > (0 : ℝ), ∀ x < δ, ∀ y < δ, x + y < ε := ⟨ε / 2, half_pos hε, fun _x hx _y hy => add_halves ε ▸ add_lt_add hx hy⟩ /-- Construct a uniform structure from a distance function and metric space axioms -/ def UniformSpace.ofDist (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : UniformSpace α := .ofFun dist dist_self dist_comm dist_triangle ofDist_aux /-- Construct a bornology from a distance function and metric space axioms. -/ abbrev Bornology.ofDist {α : Type*} (dist : α → α → ℝ) (dist_comm : ∀ x y, dist x y = dist y x) (dist_triangle : ∀ x y z, dist x z ≤ dist x y + dist y z) : Bornology α := Bornology.ofBounded { s : Set α | ∃ C, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C } ⟨0, fun _ hx _ => hx.elim⟩ (fun _ ⟨c, hc⟩ _ h => ⟨c, fun _ hx _ hy => hc (h hx) (h hy)⟩) (fun s hs t ht => by rcases s.eq_empty_or_nonempty with rfl | ⟨x, hx⟩ · rwa [empty_union] rcases t.eq_empty_or_nonempty with rfl | ⟨y, hy⟩ · rwa [union_empty] rsuffices ⟨C, hC⟩ : ∃ C, ∀ z ∈ s ∪ t, dist x z ≤ C · refine ⟨C + C, fun a ha b hb => (dist_triangle a x b).trans ?_⟩ simpa only [dist_comm] using add_le_add (hC _ ha) (hC _ hb) rcases hs with ⟨Cs, hs⟩; rcases ht with ⟨Ct, ht⟩ refine ⟨max Cs (dist x y + Ct), fun z hz => hz.elim (fun hz => (hs hx hz).trans (le_max_left _ _)) (fun hz => (dist_triangle x y z).trans <| (add_le_add le_rfl (ht hy hz)).trans (le_max_right _ _))⟩) fun z => ⟨dist z z, forall_eq.2 <| forall_eq.2 le_rfl⟩ /-- The distance function (given an ambient metric space on `α`), which returns a nonnegative real number `dist x y` given `x y : α`. -/ @[ext] class Dist (α : Type*) where /-- Distance between two points -/ dist : α → α → ℝ export Dist (dist) -- the uniform structure and the emetric space structure are embedded in the metric space structure -- to avoid instance diamond issues. See Note [forgetful inheritance]. /-- This is an internal lemma used inside the default of `PseudoMetricSpace.edist`. -/ private theorem dist_nonneg' {α} {x y : α} (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) : 0 ≤ dist x y := have : 0 ≤ 2 * dist x y := calc 0 = dist x x := (dist_self _).symm _ ≤ dist x y + dist y x := dist_triangle _ _ _ _ = 2 * dist x y := by rw [two_mul, dist_comm] nonneg_of_mul_nonneg_right this two_pos /-- A pseudometric space is a type endowed with a `ℝ`-valued distance `dist` satisfying reflexivity `dist x x = 0`, commutativity `dist x y = dist y x`, and the triangle inequality `dist x z ≤ dist x y + dist y z`. Note that we do not require `dist x y = 0 → x = y`. See metric spaces (`MetricSpace`) for the similar class with that stronger assumption. Any pseudometric space is a topological space and a uniform space (see `TopologicalSpace`, `UniformSpace`), where the topology and uniformity come from the metric. Note that a T1 pseudometric space is just a metric space. We make the uniformity/topology part of the data instead of deriving it from the metric. This eg ensures that we do not get a diamond when doing `[PseudoMetricSpace α] [PseudoMetricSpace β] : TopologicalSpace (α × β)`: The product metric and product topology agree, but not definitionally so. See Note [forgetful inheritance]. -/ class PseudoMetricSpace (α : Type u) : Type u extends Dist α where dist_self : ∀ x : α, dist x x = 0 dist_comm : ∀ x y : α, dist x y = dist y x dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z /-- Extended distance between two points -/ edist : α → α → ℝ≥0∞ := fun x y => ENNReal.ofNNReal ⟨dist x y, dist_nonneg' _ ‹_› ‹_› ‹_›⟩ edist_dist : ∀ x y : α, edist x y = ENNReal.ofReal (dist x y) := by intros x y; exact ENNReal.coe_nnreal_eq _ toUniformSpace : UniformSpace α := .ofDist dist dist_self dist_comm dist_triangle uniformity_dist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | dist p.1 p.2 < ε } := by intros; rfl toBornology : Bornology α := Bornology.ofDist dist dist_comm dist_triangle cobounded_sets : (Bornology.cobounded α).sets = { s | ∃ C : ℝ, ∀ x ∈ sᶜ, ∀ y ∈ sᶜ, dist x y ≤ C } := by intros; rfl /-- Two pseudo metric space structures with the same distance function coincide. -/ @[ext] theorem PseudoMetricSpace.ext {α : Type*} {m m' : PseudoMetricSpace α} (h : m.toDist = m'.toDist) : m = m' := by let d := m.toDist obtain ⟨_, _, _, _, hed, _, hU, _, hB⟩ := m let d' := m'.toDist obtain ⟨_, _, _, _, hed', _, hU', _, hB'⟩ := m' obtain rfl : d = d' := h congr · ext x y : 2 rw [hed, hed'] · exact UniformSpace.ext (hU.trans hU'.symm) · ext : 2 rw [← Filter.mem_sets, ← Filter.mem_sets, hB, hB'] variable [PseudoMetricSpace α] attribute [instance] PseudoMetricSpace.toUniformSpace PseudoMetricSpace.toBornology -- see Note [lower instance priority] instance (priority := 200) PseudoMetricSpace.toEDist : EDist α := ⟨PseudoMetricSpace.edist⟩ /-- Construct a pseudo-metric space structure whose underlying topological space structure (definitionally) agrees which a pre-existing topology which is compatible with a given distance function. -/ def PseudoMetricSpace.ofDistTopology {α : Type u} [TopologicalSpace α] (dist : α → α → ℝ) (dist_self : ∀ x : α, dist x x = 0) (dist_comm : ∀ x y : α, dist x y = dist y x) (dist_triangle : ∀ x y z : α, dist x z ≤ dist x y + dist y z) (H : ∀ s : Set α, IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ∀ y, dist x y < ε → y ∈ s) : PseudoMetricSpace α := { dist := dist dist_self := dist_self dist_comm := dist_comm dist_triangle := dist_triangle toUniformSpace := (UniformSpace.ofDist dist dist_self dist_comm dist_triangle).replaceTopology <| TopologicalSpace.ext_iff.2 fun s ↦ (H s).trans <| forall₂_congr fun x _ ↦ ((UniformSpace.hasBasis_ofFun (exists_gt (0 : ℝ)) dist dist_self dist_comm dist_triangle UniformSpace.ofDist_aux).comap (Prod.mk x)).mem_iff.symm uniformity_dist := rfl toBornology := Bornology.ofDist dist dist_comm dist_triangle cobounded_sets := rfl } @[simp] theorem dist_self (x : α) : dist x x = 0 := PseudoMetricSpace.dist_self x theorem dist_comm (x y : α) : dist x y = dist y x := PseudoMetricSpace.dist_comm x y theorem edist_dist (x y : α) : edist x y = ENNReal.ofReal (dist x y) := PseudoMetricSpace.edist_dist x y @[bound] theorem dist_triangle (x y z : α) : dist x z ≤ dist x y + dist y z := PseudoMetricSpace.dist_triangle x y z theorem dist_triangle_left (x y z : α) : dist x y ≤ dist z x + dist z y := by rw [dist_comm z]; apply dist_triangle theorem dist_triangle_right (x y z : α) : dist x y ≤ dist x z + dist y z := by rw [dist_comm y]; apply dist_triangle theorem dist_triangle4 (x y z w : α) : dist x w ≤ dist x y + dist y z + dist z w := calc dist x w ≤ dist x z + dist z w := dist_triangle x z w _ ≤ dist x y + dist y z + dist z w := add_le_add_right (dist_triangle x y z) _ theorem dist_triangle4_left (x₁ y₁ x₂ y₂ : α) : dist x₂ y₂ ≤ dist x₁ y₁ + (dist x₁ x₂ + dist y₁ y₂) := by rw [add_left_comm, dist_comm x₁, ← add_assoc] apply dist_triangle4 theorem dist_triangle4_right (x₁ y₁ x₂ y₂ : α) : dist x₁ y₁ ≤ dist x₁ x₂ + dist y₁ y₂ + dist x₂ y₂ := by rw [add_right_comm, dist_comm y₁] apply dist_triangle4 theorem dist_triangle8 (a b c d e f g h : α) : dist a h ≤ dist a b + dist b c + dist c d + dist d e + dist e f + dist f g + dist g h := by apply le_trans (dist_triangle4 a f g h) apply add_le_add_right (add_le_add_right _ (dist f g)) (dist g h) apply le_trans (dist_triangle4 a d e f) apply add_le_add_right (add_le_add_right _ (dist d e)) (dist e f) exact dist_triangle4 a b c d theorem swap_dist : Function.swap (@dist α _) = dist := by funext x y; exact dist_comm _ _ theorem abs_dist_sub_le (x y z : α) : |dist x z - dist y z| ≤ dist x y := abs_sub_le_iff.2 ⟨sub_le_iff_le_add.2 (dist_triangle _ _ _), sub_le_iff_le_add.2 (dist_triangle_left _ _ _)⟩ @[bound] theorem dist_nonneg {x y : α} : 0 ≤ dist x y := dist_nonneg' dist dist_self dist_comm dist_triangle namespace Mathlib.Meta.Positivity open Lean Meta Qq Function /-- Extension for the `positivity` tactic: distances are nonnegative. -/ @[positivity Dist.dist _ _] def evalDist : PositivityExt where eval {u α} _zα _pα e := do match u, α, e with | 0, ~q(ℝ), ~q(@Dist.dist $β $inst $a $b) => let _inst ← synthInstanceQ q(PseudoMetricSpace $β) assertInstancesCommute pure (.nonnegative q(dist_nonneg)) | _, _, _ => throwError "not dist" end Mathlib.Meta.Positivity example {x y : α} : 0 ≤ dist x y := by positivity @[simp] theorem abs_dist {a b : α} : |dist a b| = dist a b := abs_of_nonneg dist_nonneg /-- A version of `Dist` that takes value in `ℝ≥0`. -/ class NNDist (α : Type*) where /-- Nonnegative distance between two points -/ nndist : α → α → ℝ≥0 export NNDist (nndist) -- see Note [lower instance priority] /-- Distance as a nonnegative real number. -/ instance (priority := 100) PseudoMetricSpace.toNNDist : NNDist α := ⟨fun a b => ⟨dist a b, dist_nonneg⟩⟩ /-- Express `dist` in terms of `nndist` -/ theorem dist_nndist (x y : α) : dist x y = nndist x y := rfl @[simp, norm_cast] theorem coe_nndist (x y : α) : ↑(nndist x y) = dist x y := rfl /-- Express `edist` in terms of `nndist` -/ theorem edist_nndist (x y : α) : edist x y = nndist x y := by rw [edist_dist, dist_nndist, ENNReal.ofReal_coe_nnreal] /-- Express `nndist` in terms of `edist` -/ theorem nndist_edist (x y : α) : nndist x y = (edist x y).toNNReal := by simp [edist_nndist] @[simp, norm_cast] theorem coe_nnreal_ennreal_nndist (x y : α) : ↑(nndist x y) = edist x y := (edist_nndist x y).symm @[simp, norm_cast] theorem edist_lt_coe {x y : α} {c : ℝ≥0} : edist x y < c ↔ nndist x y < c := by rw [edist_nndist, ENNReal.coe_lt_coe] @[simp, norm_cast] theorem edist_le_coe {x y : α} {c : ℝ≥0} : edist x y ≤ c ↔ nndist x y ≤ c := by rw [edist_nndist, ENNReal.coe_le_coe] /-- In a pseudometric space, the extended distance is always finite -/ theorem edist_lt_top {α : Type*} [PseudoMetricSpace α] (x y : α) : edist x y < ⊤ := (edist_dist x y).symm ▸ ENNReal.ofReal_lt_top /-- In a pseudometric space, the extended distance is always finite -/ theorem edist_ne_top (x y : α) : edist x y ≠ ⊤ := (edist_lt_top x y).ne /-- `nndist x x` vanishes -/ @[simp] theorem nndist_self (a : α) : nndist a a = 0 := NNReal.coe_eq_zero.1 (dist_self a) @[simp, norm_cast] theorem dist_lt_coe {x y : α} {c : ℝ≥0} : dist x y < c ↔ nndist x y < c := Iff.rfl @[simp, norm_cast] theorem dist_le_coe {x y : α} {c : ℝ≥0} : dist x y ≤ c ↔ nndist x y ≤ c := Iff.rfl @[simp] theorem edist_lt_ofReal {x y : α} {r : ℝ} : edist x y < ENNReal.ofReal r ↔ dist x y < r := by rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg] @[simp] theorem edist_le_ofReal {x y : α} {r : ℝ} (hr : 0 ≤ r) : edist x y ≤ ENNReal.ofReal r ↔ dist x y ≤ r := by rw [edist_dist, ENNReal.ofReal_le_ofReal_iff hr] /-- Express `nndist` in terms of `dist` -/ theorem nndist_dist (x y : α) : nndist x y = Real.toNNReal (dist x y) := by rw [dist_nndist, Real.toNNReal_coe] theorem nndist_comm (x y : α) : nndist x y = nndist y x := NNReal.eq <| dist_comm x y /-- Triangle inequality for the nonnegative distance -/ theorem nndist_triangle (x y z : α) : nndist x z ≤ nndist x y + nndist y z := dist_triangle _ _ _ theorem nndist_triangle_left (x y z : α) : nndist x y ≤ nndist z x + nndist z y := dist_triangle_left _ _ _ theorem nndist_triangle_right (x y z : α) : nndist x y ≤ nndist x z + nndist y z := dist_triangle_right _ _ _ /-- Express `dist` in terms of `edist` -/ theorem dist_edist (x y : α) : dist x y = (edist x y).toReal := by rw [edist_dist, ENNReal.toReal_ofReal dist_nonneg] namespace Metric -- instantiate pseudometric space as a topology variable {x y z : α} {δ ε ε₁ ε₂ : ℝ} {s : Set α} /-- `ball x ε` is the set of all points `y` with `dist y x < ε` -/ def ball (x : α) (ε : ℝ) : Set α := { y | dist y x < ε } @[simp] theorem mem_ball : y ∈ ball x ε ↔ dist y x < ε := Iff.rfl theorem mem_ball' : y ∈ ball x ε ↔ dist x y < ε := by rw [dist_comm, mem_ball] theorem pos_of_mem_ball (hy : y ∈ ball x ε) : 0 < ε := dist_nonneg.trans_lt hy theorem mem_ball_self (h : 0 < ε) : x ∈ ball x ε := by rwa [mem_ball, dist_self] @[simp] theorem nonempty_ball : (ball x ε).Nonempty ↔ 0 < ε := ⟨fun ⟨_x, hx⟩ => pos_of_mem_ball hx, fun h => ⟨x, mem_ball_self h⟩⟩ @[simp] theorem ball_eq_empty : ball x ε = ∅ ↔ ε ≤ 0 := by rw [← not_nonempty_iff_eq_empty, nonempty_ball, not_lt] @[simp] theorem ball_zero : ball x 0 = ∅ := by rw [ball_eq_empty] /-- If a point belongs to an open ball, then there is a strictly smaller radius whose ball also contains it. See also `exists_lt_subset_ball`. -/ theorem exists_lt_mem_ball_of_mem_ball (h : x ∈ ball y ε) : ∃ ε' < ε, x ∈ ball y ε' := by simp only [mem_ball] at h ⊢ exact ⟨(dist x y + ε) / 2, by linarith, by linarith⟩ theorem ball_eq_ball (ε : ℝ) (x : α) : UniformSpace.ball x { p | dist p.2 p.1 < ε } = Metric.ball x ε := rfl theorem ball_eq_ball' (ε : ℝ) (x : α) : UniformSpace.ball x { p | dist p.1 p.2 < ε } = Metric.ball x ε := by ext simp [dist_comm, UniformSpace.ball] @[simp] theorem iUnion_ball_nat (x : α) : ⋃ n : ℕ, ball x n = univ := iUnion_eq_univ_iff.2 fun y => exists_nat_gt (dist y x) @[simp] theorem iUnion_ball_nat_succ (x : α) : ⋃ n : ℕ, ball x (n + 1) = univ := iUnion_eq_univ_iff.2 fun y => (exists_nat_gt (dist y x)).imp fun _ h => h.trans (lt_add_one _) /-- `closedBall x ε` is the set of all points `y` with `dist y x ≤ ε` -/ def closedBall (x : α) (ε : ℝ) := { y | dist y x ≤ ε } @[simp] theorem mem_closedBall : y ∈ closedBall x ε ↔ dist y x ≤ ε := Iff.rfl theorem mem_closedBall' : y ∈ closedBall x ε ↔ dist x y ≤ ε := by rw [dist_comm, mem_closedBall] /-- `sphere x ε` is the set of all points `y` with `dist y x = ε` -/ def sphere (x : α) (ε : ℝ) := { y | dist y x = ε } @[simp] theorem mem_sphere : y ∈ sphere x ε ↔ dist y x = ε := Iff.rfl theorem mem_sphere' : y ∈ sphere x ε ↔ dist x y = ε := by rw [dist_comm, mem_sphere] theorem ne_of_mem_sphere (h : y ∈ sphere x ε) (hε : ε ≠ 0) : y ≠ x := ne_of_mem_of_not_mem h <| by simpa using hε.symm theorem nonneg_of_mem_sphere (hy : y ∈ sphere x ε) : 0 ≤ ε := dist_nonneg.trans_eq hy @[simp] theorem sphere_eq_empty_of_neg (hε : ε < 0) : sphere x ε = ∅ := Set.eq_empty_iff_forall_not_mem.mpr fun _y hy => (nonneg_of_mem_sphere hy).not_lt hε theorem sphere_eq_empty_of_subsingleton [Subsingleton α] (hε : ε ≠ 0) : sphere x ε = ∅ := Set.eq_empty_iff_forall_not_mem.mpr fun _ h => ne_of_mem_sphere h hε (Subsingleton.elim _ _) instance sphere_isEmpty_of_subsingleton [Subsingleton α] [NeZero ε] : IsEmpty (sphere x ε) := by rw [sphere_eq_empty_of_subsingleton (NeZero.ne ε)]; infer_instance theorem closedBall_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 ≤ ε) : closedBall x ε = {x} := by ext x' simpa [Subsingleton.allEq x x'] theorem ball_eq_singleton_of_subsingleton [Subsingleton α] (h : 0 < ε) : ball x ε = {x} := by ext x' simpa [Subsingleton.allEq x x'] theorem mem_closedBall_self (h : 0 ≤ ε) : x ∈ closedBall x ε := by rwa [mem_closedBall, dist_self] @[simp] theorem nonempty_closedBall : (closedBall x ε).Nonempty ↔ 0 ≤ ε := ⟨fun ⟨_x, hx⟩ => dist_nonneg.trans hx, fun h => ⟨x, mem_closedBall_self h⟩⟩ @[simp] theorem closedBall_eq_empty : closedBall x ε = ∅ ↔ ε < 0 := by rw [← not_nonempty_iff_eq_empty, nonempty_closedBall, not_le] /-- Closed balls and spheres coincide when the radius is non-positive -/ theorem closedBall_eq_sphere_of_nonpos (hε : ε ≤ 0) : closedBall x ε = sphere x ε := Set.ext fun _ => (hε.trans dist_nonneg).le_iff_eq theorem ball_subset_closedBall : ball x ε ⊆ closedBall x ε := fun _y hy => mem_closedBall.2 (le_of_lt hy) theorem sphere_subset_closedBall : sphere x ε ⊆ closedBall x ε := fun _ => le_of_eq lemma sphere_subset_ball {r R : ℝ} (h : r < R) : sphere x r ⊆ ball x R := fun _x hx ↦ (mem_sphere.1 hx).trans_lt h theorem closedBall_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (closedBall x δ) (ball y ε) := Set.disjoint_left.mpr fun _a ha1 ha2 => (h.trans <| dist_triangle_left _ _ _).not_lt <| add_lt_add_of_le_of_lt ha1 ha2 theorem ball_disjoint_closedBall (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (closedBall y ε) := (closedBall_disjoint_ball <| by rwa [add_comm, dist_comm]).symm theorem ball_disjoint_ball (h : δ + ε ≤ dist x y) : Disjoint (ball x δ) (ball y ε) := (closedBall_disjoint_ball h).mono_left ball_subset_closedBall theorem closedBall_disjoint_closedBall (h : δ + ε < dist x y) : Disjoint (closedBall x δ) (closedBall y ε) := Set.disjoint_left.mpr fun _a ha1 ha2 => h.not_le <| (dist_triangle_left _ _ _).trans <| add_le_add ha1 ha2 theorem sphere_disjoint_ball : Disjoint (sphere x ε) (ball x ε) := Set.disjoint_left.mpr fun _y hy₁ hy₂ => absurd hy₁ <| ne_of_lt hy₂ @[simp] theorem ball_union_sphere : ball x ε ∪ sphere x ε = closedBall x ε := Set.ext fun _y => (@le_iff_lt_or_eq ℝ _ _ _).symm @[simp] theorem sphere_union_ball : sphere x ε ∪ ball x ε = closedBall x ε := by rw [union_comm, ball_union_sphere] @[simp] theorem closedBall_diff_sphere : closedBall x ε \ sphere x ε = ball x ε := by rw [← ball_union_sphere, Set.union_diff_cancel_right sphere_disjoint_ball.symm.le_bot] @[simp] theorem closedBall_diff_ball : closedBall x ε \ ball x ε = sphere x ε := by rw [← ball_union_sphere, Set.union_diff_cancel_left sphere_disjoint_ball.symm.le_bot] theorem mem_ball_comm : x ∈ ball y ε ↔ y ∈ ball x ε := by rw [mem_ball', mem_ball] theorem mem_closedBall_comm : x ∈ closedBall y ε ↔ y ∈ closedBall x ε := by rw [mem_closedBall', mem_closedBall] theorem mem_sphere_comm : x ∈ sphere y ε ↔ y ∈ sphere x ε := by rw [mem_sphere', mem_sphere] @[gcongr] theorem ball_subset_ball (h : ε₁ ≤ ε₂) : ball x ε₁ ⊆ ball x ε₂ := fun _y yx => lt_of_lt_of_le (mem_ball.1 yx) h theorem closedBall_eq_bInter_ball : closedBall x ε = ⋂ δ > ε, ball x δ := by ext y; rw [mem_closedBall, ← forall_lt_iff_le', mem_iInter₂]; rfl theorem ball_subset_ball' (h : ε₁ + dist x y ≤ ε₂) : ball x ε₁ ⊆ ball y ε₂ := fun z hz => calc dist z y ≤ dist z x + dist x y := dist_triangle _ _ _ _ < ε₁ + dist x y := add_lt_add_right (mem_ball.1 hz) _ _ ≤ ε₂ := h @[gcongr] theorem closedBall_subset_closedBall (h : ε₁ ≤ ε₂) : closedBall x ε₁ ⊆ closedBall x ε₂ := fun _y (yx : _ ≤ ε₁) => le_trans yx h theorem closedBall_subset_closedBall' (h : ε₁ + dist x y ≤ ε₂) : closedBall x ε₁ ⊆ closedBall y ε₂ := fun z hz => calc dist z y ≤ dist z x + dist x y := dist_triangle _ _ _ _ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _ _ ≤ ε₂ := h theorem closedBall_subset_ball (h : ε₁ < ε₂) : closedBall x ε₁ ⊆ ball x ε₂ := fun y (yh : dist y x ≤ ε₁) => lt_of_le_of_lt yh h theorem closedBall_subset_ball' (h : ε₁ + dist x y < ε₂) : closedBall x ε₁ ⊆ ball y ε₂ := fun z hz => calc dist z y ≤ dist z x + dist x y := dist_triangle _ _ _ _ ≤ ε₁ + dist x y := add_le_add_right (mem_closedBall.1 hz) _ _ < ε₂ := h theorem dist_le_add_of_nonempty_closedBall_inter_closedBall (h : (closedBall x ε₁ ∩ closedBall y ε₂).Nonempty) : dist x y ≤ ε₁ + ε₂ := let ⟨z, hz⟩ := h calc dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _ _ ≤ ε₁ + ε₂ := add_le_add hz.1 hz.2 theorem dist_lt_add_of_nonempty_closedBall_inter_ball (h : (closedBall x ε₁ ∩ ball y ε₂).Nonempty) : dist x y < ε₁ + ε₂ := let ⟨z, hz⟩ := h calc dist x y ≤ dist z x + dist z y := dist_triangle_left _ _ _ _ < ε₁ + ε₂ := add_lt_add_of_le_of_lt hz.1 hz.2 theorem dist_lt_add_of_nonempty_ball_inter_closedBall (h : (ball x ε₁ ∩ closedBall y ε₂).Nonempty) : dist x y < ε₁ + ε₂ := by rw [inter_comm] at h rw [add_comm, dist_comm] exact dist_lt_add_of_nonempty_closedBall_inter_ball h theorem dist_lt_add_of_nonempty_ball_inter_ball (h : (ball x ε₁ ∩ ball y ε₂).Nonempty) : dist x y < ε₁ + ε₂ := dist_lt_add_of_nonempty_closedBall_inter_ball <| h.mono (inter_subset_inter ball_subset_closedBall Subset.rfl) @[simp] theorem iUnion_closedBall_nat (x : α) : ⋃ n : ℕ, closedBall x n = univ := iUnion_eq_univ_iff.2 fun y => exists_nat_ge (dist y x) theorem iUnion_inter_closedBall_nat (s : Set α) (x : α) : ⋃ n : ℕ, s ∩ closedBall x n = s := by rw [← inter_iUnion, iUnion_closedBall_nat, inter_univ] theorem ball_subset (h : dist x y ≤ ε₂ - ε₁) : ball x ε₁ ⊆ ball y ε₂ := fun z zx => by rw [← add_sub_cancel ε₁ ε₂] exact lt_of_le_of_lt (dist_triangle z x y) (add_lt_add_of_lt_of_le zx h) theorem ball_half_subset (y) (h : y ∈ ball x (ε / 2)) : ball y (ε / 2) ⊆ ball x ε := ball_subset <| by rw [sub_self_div_two]; exact le_of_lt h theorem exists_ball_subset_ball (h : y ∈ ball x ε) : ∃ ε' > 0, ball y ε' ⊆ ball x ε := ⟨_, sub_pos.2 h, ball_subset <| by rw [sub_sub_self]⟩ /-- If a property holds for all points in closed balls of arbitrarily large radii, then it holds for all points. -/ theorem forall_of_forall_mem_closedBall (p : α → Prop) (x : α) (H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ closedBall x R, p y) (y : α) : p y := by obtain ⟨R, hR, h⟩ : ∃ R ≥ dist y x, ∀ z : α, z ∈ closedBall x R → p z := frequently_iff.1 H (Ici_mem_atTop (dist y x)) exact h _ hR /-- If a property holds for all points in balls of arbitrarily large radii, then it holds for all points. -/ theorem forall_of_forall_mem_ball (p : α → Prop) (x : α) (H : ∃ᶠ R : ℝ in atTop, ∀ y ∈ ball x R, p y) (y : α) : p y := by obtain ⟨R, hR, h⟩ : ∃ R > dist y x, ∀ z : α, z ∈ ball x R → p z := frequently_iff.1 H (Ioi_mem_atTop (dist y x)) exact h _ hR theorem isBounded_iff {s : Set α} : IsBounded s ↔ ∃ C : ℝ, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := by rw [isBounded_def, ← Filter.mem_sets, @PseudoMetricSpace.cobounded_sets α, mem_setOf_eq, compl_compl] theorem isBounded_iff_eventually {s : Set α} : IsBounded s ↔ ∀ᶠ C in atTop, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := isBounded_iff.trans ⟨fun ⟨C, h⟩ => eventually_atTop.2 ⟨C, fun _C' hC' _x hx _y hy => (h hx hy).trans hC'⟩, Eventually.exists⟩ theorem isBounded_iff_exists_ge {s : Set α} (c : ℝ) : IsBounded s ↔ ∃ C, c ≤ C ∧ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → dist x y ≤ C := ⟨fun h => ((eventually_ge_atTop c).and (isBounded_iff_eventually.1 h)).exists, fun h => isBounded_iff.2 <| h.imp fun _ => And.right⟩ theorem isBounded_iff_nndist {s : Set α} : IsBounded s ↔ ∃ C : ℝ≥0, ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → nndist x y ≤ C := by simp only [isBounded_iff_exists_ge 0, NNReal.exists, ← NNReal.coe_le_coe, ← dist_nndist, NNReal.coe_mk, exists_prop] theorem toUniformSpace_eq : ‹PseudoMetricSpace α›.toUniformSpace = .ofDist dist dist_self dist_comm dist_triangle := UniformSpace.ext PseudoMetricSpace.uniformity_dist theorem uniformity_basis_dist : (𝓤 α).HasBasis (fun ε : ℝ => 0 < ε) fun ε => { p : α × α | dist p.1 p.2 < ε } := by rw [toUniformSpace_eq] exact UniformSpace.hasBasis_ofFun (exists_gt _) _ _ _ _ _ /-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers accumulating to zero, then `f i`-neighborhoods of the diagonal form a basis of `𝓤 α`. For specific bases see `uniformity_basis_dist`, `uniformity_basis_dist_inv_nat_succ`, and `uniformity_basis_dist_inv_nat_pos`. -/ protected theorem mk_uniformity_basis {β : Type*} {p : β → Prop} {f : β → ℝ} (hf₀ : ∀ i, p i → 0 < f i) (hf : ∀ ⦃ε⦄, 0 < ε → ∃ i, p i ∧ f i ≤ ε) : (𝓤 α).HasBasis p fun i => { p : α × α | dist p.1 p.2 < f i } := by refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩ constructor · rintro ⟨ε, ε₀, hε⟩ rcases hf ε₀ with ⟨i, hi, H⟩ exact ⟨i, hi, fun x (hx : _ < _) => hε <| lt_of_lt_of_le hx H⟩ · exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, H⟩ theorem uniformity_basis_dist_rat : (𝓤 α).HasBasis (fun r : ℚ => 0 < r) fun r => { p : α × α | dist p.1 p.2 < r } := Metric.mk_uniformity_basis (fun _ => Rat.cast_pos.2) fun _ε hε => let ⟨r, hr0, hrε⟩ := exists_rat_btwn hε ⟨r, Rat.cast_pos.1 hr0, hrε.le⟩ theorem uniformity_basis_dist_inv_nat_succ : (𝓤 α).HasBasis (fun _ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / (↑n + 1) } := Metric.mk_uniformity_basis (fun n _ => div_pos zero_lt_one <| Nat.cast_add_one_pos n) fun _ε ε0 => (exists_nat_one_div_lt ε0).imp fun _n hn => ⟨trivial, le_of_lt hn⟩ theorem uniformity_basis_dist_inv_nat_pos : (𝓤 α).HasBasis (fun n : ℕ => 0 < n) fun n : ℕ => { p : α × α | dist p.1 p.2 < 1 / ↑n } := Metric.mk_uniformity_basis (fun _ hn => div_pos zero_lt_one <| Nat.cast_pos.2 hn) fun _ ε0 => let ⟨n, hn⟩ := exists_nat_one_div_lt ε0 ⟨n + 1, Nat.succ_pos n, mod_cast hn.le⟩ theorem uniformity_basis_dist_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 < r ^ n } := Metric.mk_uniformity_basis (fun _ _ => pow_pos h0 _) fun _ε ε0 => let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1 ⟨n, trivial, hn.le⟩ theorem uniformity_basis_dist_lt {R : ℝ} (hR : 0 < R) : (𝓤 α).HasBasis (fun r : ℝ => 0 < r ∧ r < R) fun r => { p : α × α | dist p.1 p.2 < r } := Metric.mk_uniformity_basis (fun _ => And.left) fun r hr => ⟨min r (R / 2), ⟨lt_min hr (half_pos hR), min_lt_iff.2 <| Or.inr (half_lt_self hR)⟩, min_le_left _ _⟩ /-- Given `f : β → ℝ`, if `f` sends `{i | p i}` to a set of positive numbers accumulating to zero, then closed neighborhoods of the diagonal of sizes `{f i | p i}` form a basis of `𝓤 α`. Currently we have only one specific basis `uniformity_basis_dist_le` based on this constructor. More can be easily added if needed in the future. -/ protected theorem mk_uniformity_basis_le {β : Type*} {p : β → Prop} {f : β → ℝ} (hf₀ : ∀ x, p x → 0 < f x) (hf : ∀ ε, 0 < ε → ∃ x, p x ∧ f x ≤ ε) : (𝓤 α).HasBasis p fun x => { p : α × α | dist p.1 p.2 ≤ f x } := by refine ⟨fun s => uniformity_basis_dist.mem_iff.trans ?_⟩ constructor · rintro ⟨ε, ε₀, hε⟩ rcases exists_between ε₀ with ⟨ε', hε'⟩ rcases hf ε' hε'.1 with ⟨i, hi, H⟩ exact ⟨i, hi, fun x (hx : _ ≤ _) => hε <| lt_of_le_of_lt (le_trans hx H) hε'.2⟩ · exact fun ⟨i, hi, H⟩ => ⟨f i, hf₀ i hi, fun x (hx : _ < _) => H (mem_setOf.2 hx.le)⟩ /-- Constant size closed neighborhoods of the diagonal form a basis of the uniformity filter. -/ theorem uniformity_basis_dist_le : (𝓤 α).HasBasis ((0 : ℝ) < ·) fun ε => { p : α × α | dist p.1 p.2 ≤ ε } := Metric.mk_uniformity_basis_le (fun _ => id) fun ε ε₀ => ⟨ε, ε₀, le_refl ε⟩ theorem uniformity_basis_dist_le_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓤 α).HasBasis (fun _ : ℕ => True) fun n : ℕ => { p : α × α | dist p.1 p.2 ≤ r ^ n } := Metric.mk_uniformity_basis_le (fun _ _ => pow_pos h0 _) fun _ε ε0 => let ⟨n, hn⟩ := exists_pow_lt_of_lt_one ε0 h1 ⟨n, trivial, hn.le⟩ theorem mem_uniformity_dist {s : Set (α × α)} : s ∈ 𝓤 α ↔ ∃ ε > 0, ∀ ⦃a b : α⦄, dist a b < ε → (a, b) ∈ s := uniformity_basis_dist.mem_uniformity_iff /-- A constant size neighborhood of the diagonal is an entourage. -/ theorem dist_mem_uniformity {ε : ℝ} (ε0 : 0 < ε) : { p : α × α | dist p.1 p.2 < ε } ∈ 𝓤 α := mem_uniformity_dist.2 ⟨ε, ε0, fun _ _ ↦ id⟩ theorem uniformContinuous_iff [PseudoMetricSpace β] {f : α → β} : UniformContinuous f ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃a b : α⦄, dist a b < δ → dist (f a) (f b) < ε := uniformity_basis_dist.uniformContinuous_iff uniformity_basis_dist theorem uniformContinuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} : UniformContinuousOn f s ↔ ∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y < δ → dist (f x) (f y) < ε := Metric.uniformity_basis_dist.uniformContinuousOn_iff Metric.uniformity_basis_dist theorem uniformContinuousOn_iff_le [PseudoMetricSpace β] {f : α → β} {s : Set α} : UniformContinuousOn f s ↔ ∀ ε > 0, ∃ δ > 0, ∀ x ∈ s, ∀ y ∈ s, dist x y ≤ δ → dist (f x) (f y) ≤ ε := Metric.uniformity_basis_dist_le.uniformContinuousOn_iff Metric.uniformity_basis_dist_le theorem nhds_basis_ball : (𝓝 x).HasBasis (0 < ·) (ball x) := nhds_basis_uniformity uniformity_basis_dist theorem mem_nhds_iff : s ∈ 𝓝 x ↔ ∃ ε > 0, ball x ε ⊆ s := nhds_basis_ball.mem_iff theorem eventually_nhds_iff {p : α → Prop} : (∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ ⦃y⦄, dist y x < ε → p y := mem_nhds_iff theorem eventually_nhds_iff_ball {p : α → Prop} : (∀ᶠ y in 𝓝 x, p y) ↔ ∃ ε > 0, ∀ y ∈ ball x ε, p y := mem_nhds_iff /-- A version of `Filter.eventually_prod_iff` where the first filter consists of neighborhoods in a pseudo-metric space. -/ theorem eventually_nhds_prod_iff {f : Filter ι} {x₀ : α} {p : α × ι → Prop} : (∀ᶠ x in 𝓝 x₀ ×ˢ f, p x) ↔ ∃ ε > (0 : ℝ), ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧ ∀ ⦃x⦄, dist x x₀ < ε → ∀ ⦃i⦄, pa i → p (x, i) := by refine (nhds_basis_ball.prod f.basis_sets).eventually_iff.trans ?_ simp only [Prod.exists, forall_prod_set, id, mem_ball, and_assoc, exists_and_left, and_imp] rfl /-- A version of `Filter.eventually_prod_iff` where the second filter consists of neighborhoods in a pseudo-metric space. -/ theorem eventually_prod_nhds_iff {f : Filter ι} {x₀ : α} {p : ι × α → Prop} : (∀ᶠ x in f ×ˢ 𝓝 x₀, p x) ↔ ∃ pa : ι → Prop, (∀ᶠ i in f, pa i) ∧ ∃ ε > 0, ∀ ⦃i⦄, pa i → ∀ ⦃x⦄, dist x x₀ < ε → p (i, x) := by rw [eventually_swap_iff, Metric.eventually_nhds_prod_iff] constructor <;> · rintro ⟨a1, a2, a3, a4, a5⟩ exact ⟨a3, a4, a1, a2, fun _ b1 b2 b3 => a5 b3 b1⟩ theorem nhds_basis_closedBall : (𝓝 x).HasBasis (fun ε : ℝ => 0 < ε) (closedBall x) := nhds_basis_uniformity uniformity_basis_dist_le theorem nhds_basis_ball_inv_nat_succ : (𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (1 / (↑n + 1)) := nhds_basis_uniformity uniformity_basis_dist_inv_nat_succ theorem nhds_basis_ball_inv_nat_pos : (𝓝 x).HasBasis (fun n => 0 < n) fun n : ℕ => ball x (1 / ↑n) := nhds_basis_uniformity uniformity_basis_dist_inv_nat_pos theorem nhds_basis_ball_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓝 x).HasBasis (fun _ => True) fun n : ℕ => ball x (r ^ n) := nhds_basis_uniformity (uniformity_basis_dist_pow h0 h1) theorem nhds_basis_closedBall_pow {r : ℝ} (h0 : 0 < r) (h1 : r < 1) : (𝓝 x).HasBasis (fun _ => True) fun n : ℕ => closedBall x (r ^ n) := nhds_basis_uniformity (uniformity_basis_dist_le_pow h0 h1) theorem isOpen_iff : IsOpen s ↔ ∀ x ∈ s, ∃ ε > 0, ball x ε ⊆ s := by simp only [isOpen_iff_mem_nhds, mem_nhds_iff] @[simp] theorem isOpen_ball : IsOpen (ball x ε) := isOpen_iff.2 fun _ => exists_ball_subset_ball theorem ball_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : ball x ε ∈ 𝓝 x := isOpen_ball.mem_nhds (mem_ball_self ε0) theorem closedBall_mem_nhds (x : α) {ε : ℝ} (ε0 : 0 < ε) : closedBall x ε ∈ 𝓝 x := mem_of_superset (ball_mem_nhds x ε0) ball_subset_closedBall theorem closedBall_mem_nhds_of_mem {x c : α} {ε : ℝ} (h : x ∈ ball c ε) : closedBall c ε ∈ 𝓝 x := mem_of_superset (isOpen_ball.mem_nhds h) ball_subset_closedBall theorem nhdsWithin_basis_ball {s : Set α} : (𝓝[s] x).HasBasis (fun ε : ℝ => 0 < ε) fun ε => ball x ε ∩ s := nhdsWithin_hasBasis nhds_basis_ball s theorem mem_nhdsWithin_iff {t : Set α} : s ∈ 𝓝[t] x ↔ ∃ ε > 0, ball x ε ∩ t ⊆ s := nhdsWithin_basis_ball.mem_iff theorem tendsto_nhdsWithin_nhdsWithin [PseudoMetricSpace β] {t : Set β} {f : α → β} {a b} : Tendsto f (𝓝[s] a) (𝓝[t] b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → f x ∈ t ∧ dist (f x) b < ε := (nhdsWithin_basis_ball.tendsto_iff nhdsWithin_basis_ball).trans <| by simp only [inter_comm _ s, inter_comm _ t, mem_inter_iff, and_imp, gt_iff_lt, mem_ball] theorem tendsto_nhdsWithin_nhds [PseudoMetricSpace β] {f : α → β} {a b} : Tendsto f (𝓝[s] a) (𝓝 b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → dist (f x) b < ε := by rw [← nhdsWithin_univ b, tendsto_nhdsWithin_nhdsWithin] simp only [mem_univ, true_and] theorem tendsto_nhds_nhds [PseudoMetricSpace β] {f : α → β} {a b} : Tendsto f (𝓝 a) (𝓝 b) ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, dist x a < δ → dist (f x) b < ε := nhds_basis_ball.tendsto_iff nhds_basis_ball theorem continuousAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} : ContinuousAt f a ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, dist x a < δ → dist (f x) (f a) < ε := by rw [ContinuousAt, tendsto_nhds_nhds] theorem continuousWithinAt_iff [PseudoMetricSpace β] {f : α → β} {a : α} {s : Set α} : ContinuousWithinAt f s a ↔ ∀ ε > 0, ∃ δ > 0, ∀ ⦃x : α⦄, x ∈ s → dist x a < δ → dist (f x) (f a) < ε := by rw [ContinuousWithinAt, tendsto_nhdsWithin_nhds] theorem continuousOn_iff [PseudoMetricSpace β] {f : α → β} {s : Set α} : ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∃ δ > 0, ∀ a ∈ s, dist a b < δ → dist (f a) (f b) < ε := by simp [ContinuousOn, continuousWithinAt_iff] theorem continuous_iff [PseudoMetricSpace β] {f : α → β} : Continuous f ↔ ∀ b, ∀ ε > 0, ∃ δ > 0, ∀ a, dist a b < δ → dist (f a) (f b) < ε := continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds_nhds theorem tendsto_nhds {f : Filter β} {u : β → α} {a : α} : Tendsto u f (𝓝 a) ↔ ∀ ε > 0, ∀ᶠ x in f, dist (u x) a < ε := nhds_basis_ball.tendsto_right_iff theorem continuousAt_iff' [TopologicalSpace β] {f : β → α} {b : β} : ContinuousAt f b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝 b, dist (f x) (f b) < ε := by rw [ContinuousAt, tendsto_nhds] theorem continuousWithinAt_iff' [TopologicalSpace β] {f : β → α} {b : β} {s : Set β} : ContinuousWithinAt f s b ↔ ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by rw [ContinuousWithinAt, tendsto_nhds] theorem continuousOn_iff' [TopologicalSpace β] {f : β → α} {s : Set β} : ContinuousOn f s ↔ ∀ b ∈ s, ∀ ε > 0, ∀ᶠ x in 𝓝[s] b, dist (f x) (f b) < ε := by simp [ContinuousOn, continuousWithinAt_iff'] theorem continuous_iff' [TopologicalSpace β] {f : β → α} : Continuous f ↔ ∀ (a), ∀ ε > 0, ∀ᶠ x in 𝓝 a, dist (f x) (f a) < ε := continuous_iff_continuousAt.trans <| forall_congr' fun _ => tendsto_nhds theorem tendsto_atTop [Nonempty β] [SemilatticeSup β] {u : β → α} {a : α} : Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n ≥ N, dist (u n) a < ε := (atTop_basis.tendsto_iff nhds_basis_ball).trans <| by simp only [true_and, mem_ball, mem_Ici] /-- A variant of `tendsto_atTop` that uses `∃ N, ∀ n > N, ...` rather than `∃ N, ∀ n ≥ N, ...` -/ theorem tendsto_atTop' [Nonempty β] [SemilatticeSup β] [NoMaxOrder β] {u : β → α} {a : α} : Tendsto u atTop (𝓝 a) ↔ ∀ ε > 0, ∃ N, ∀ n > N, dist (u n) a < ε := (atTop_basis_Ioi.tendsto_iff nhds_basis_ball).trans <| by simp only [true_and, gt_iff_lt, mem_Ioi, mem_ball] theorem isOpen_singleton_iff {α : Type*} [PseudoMetricSpace α] {x : α} : IsOpen ({x} : Set α) ↔ ∃ ε > 0, ∀ y, dist y x < ε → y = x := by simp [isOpen_iff, subset_singleton_iff, mem_ball] theorem _root_.Dense.exists_dist_lt {s : Set α} (hs : Dense s) (x : α) {ε : ℝ} (hε : 0 < ε) : ∃ y ∈ s, dist x y < ε := by have : (ball x ε).Nonempty := by simp [hε] simpa only [mem_ball'] using hs.exists_mem_open isOpen_ball this nonrec theorem _root_.DenseRange.exists_dist_lt {β : Type*} {f : β → α} (hf : DenseRange f) (x : α) {ε : ℝ} (hε : 0 < ε) : ∃ y, dist x (f y) < ε := exists_range_iff.1 (hf.exists_dist_lt x hε) /-- (Pseudo) metric space has discrete `UniformSpace` structure iff the distances between distinct points are uniformly bounded away from zero. -/ protected lemma uniformSpace_eq_bot : ‹PseudoMetricSpace α›.toUniformSpace = ⊥ ↔ ∃ r : ℝ, 0 < r ∧ Pairwise (r ≤ dist · · : α → α → Prop) := by simp only [uniformity_basis_dist.uniformSpace_eq_bot, mem_setOf_eq, not_lt] end Metric open Metric /-- If the distances between distinct points in a (pseudo) metric space are uniformly bounded away from zero, then the space has discrete topology. -/ lemma DiscreteTopology.of_forall_le_dist {α} [PseudoMetricSpace α] {r : ℝ} (hpos : 0 < r) (hr : Pairwise (r ≤ dist · · : α → α → Prop)) : DiscreteTopology α := ⟨by rw [Metric.uniformSpace_eq_bot.2 ⟨r, hpos, hr⟩, UniformSpace.toTopologicalSpace_bot]⟩ /- Instantiate a pseudometric space as a pseudoemetric space. Before we can state the instance, we need to show that the uniform structure coming from the edistance and the distance coincide. -/ theorem Metric.uniformity_edist_aux {α} (d : α → α → ℝ≥0) : ⨅ ε > (0 : ℝ), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } = ⨅ ε > (0 : ℝ≥0∞), 𝓟 { p : α × α | ↑(d p.1 p.2) < ε } := by simp only [le_antisymm_iff, le_iInf_iff, le_principal_iff] refine ⟨fun ε hε => ?_, fun ε hε => ?_⟩ · rcases ENNReal.lt_iff_exists_nnreal_btwn.1 hε with ⟨ε', ε'0, ε'ε⟩ refine mem_iInf_of_mem (ε' : ℝ) (mem_iInf_of_mem (ENNReal.coe_pos.1 ε'0) ?_) exact fun x hx => lt_trans (ENNReal.coe_lt_coe.2 hx) ε'ε · lift ε to ℝ≥0 using le_of_lt hε refine mem_iInf_of_mem (ε : ℝ≥0∞) (mem_iInf_of_mem (ENNReal.coe_pos.2 hε) ?_) exact fun _ => ENNReal.coe_lt_coe.1 theorem Metric.uniformity_edist : 𝓤 α = ⨅ ε > 0, 𝓟 { p : α × α | edist p.1 p.2 < ε } := by simp only [PseudoMetricSpace.uniformity_dist, dist_nndist, edist_nndist, Metric.uniformity_edist_aux] -- see Note [lower instance priority] /-- A pseudometric space induces a pseudoemetric space -/ instance (priority := 100) PseudoMetricSpace.toPseudoEMetricSpace : PseudoEMetricSpace α := { ‹PseudoMetricSpace α› with edist_self := by simp [edist_dist] edist_comm := fun _ _ => by simp only [edist_dist, dist_comm] edist_triangle := fun x y z => by simp only [edist_dist, ← ENNReal.ofReal_add, dist_nonneg] rw [ENNReal.ofReal_le_ofReal_iff _] · exact dist_triangle _ _ _ · simpa using add_le_add (dist_nonneg : 0 ≤ dist x y) dist_nonneg uniformity_edist := Metric.uniformity_edist } /-- In a pseudometric space, an open ball of infinite radius is the whole space -/ theorem Metric.eball_top_eq_univ (x : α) : EMetric.ball x ∞ = Set.univ := Set.eq_univ_iff_forall.mpr fun y => edist_lt_top y x /-- Balls defined using the distance or the edistance coincide -/ @[simp] theorem Metric.emetric_ball {x : α} {ε : ℝ} : EMetric.ball x (ENNReal.ofReal ε) = ball x ε := by ext y simp only [EMetric.mem_ball, mem_ball, edist_dist] exact ENNReal.ofReal_lt_ofReal_iff_of_nonneg dist_nonneg /-- Balls defined using the distance or the edistance coincide -/ @[simp] theorem Metric.emetric_ball_nnreal {x : α} {ε : ℝ≥0} : EMetric.ball x ε = ball x ε := by rw [← Metric.emetric_ball] simp /-- Closed balls defined using the distance or the edistance coincide -/ theorem Metric.emetric_closedBall {x : α} {ε : ℝ} (h : 0 ≤ ε) : EMetric.closedBall x (ENNReal.ofReal ε) = closedBall x ε := by ext y; simp [edist_le_ofReal h] /-- Closed balls defined using the distance or the edistance coincide -/ @[simp] theorem Metric.emetric_closedBall_nnreal {x : α} {ε : ℝ≥0} : EMetric.closedBall x ε = closedBall x ε := by rw [← Metric.emetric_closedBall ε.coe_nonneg, ENNReal.ofReal_coe_nnreal] @[simp] theorem Metric.emetric_ball_top (x : α) : EMetric.ball x ⊤ = univ := eq_univ_of_forall fun _ => edist_lt_top _ _ /-- Build a new pseudometric space from an old one where the bundled uniform structure is provably (but typically non-definitionaly) equal to some given uniform structure. See Note [forgetful inheritance]. See Note [reducible non-instances]. -/ abbrev PseudoMetricSpace.replaceUniformity {α} [U : UniformSpace α] (m : PseudoMetricSpace α) (H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : PseudoMetricSpace α := { m with toUniformSpace := U uniformity_dist := H.trans PseudoMetricSpace.uniformity_dist } theorem PseudoMetricSpace.replaceUniformity_eq {α} [U : UniformSpace α] (m : PseudoMetricSpace α) (H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : m.replaceUniformity H = m := by ext rfl -- ensure that the bornology is unchanged when replacing the uniformity. example {α} [U : UniformSpace α] (m : PseudoMetricSpace α) (H : 𝓤[U] = 𝓤[PseudoEMetricSpace.toUniformSpace]) : (PseudoMetricSpace.replaceUniformity m H).toBornology = m.toBornology := by with_reducible_and_instances rfl /-- Build a new pseudo metric space from an old one where the bundled topological structure is provably (but typically non-definitionaly) equal to some given topological structure. See Note [forgetful inheritance]. See Note [reducible non-instances]. -/ abbrev PseudoMetricSpace.replaceTopology {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ) (H : U = m.toUniformSpace.toTopologicalSpace) : PseudoMetricSpace γ := @PseudoMetricSpace.replaceUniformity γ (m.toUniformSpace.replaceTopology H) m rfl theorem PseudoMetricSpace.replaceTopology_eq {γ} [U : TopologicalSpace γ] (m : PseudoMetricSpace γ) (H : U = m.toUniformSpace.toTopologicalSpace) : m.replaceTopology H = m := by ext rfl /-- One gets a pseudometric space from an emetric space if the edistance is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the uniformity are defeq in the pseudometric space and the pseudoemetric space. In this definition, the distance is given separately, to be able to prescribe some expression which is not defeq to the push-forward of the edistance to reals. See note [reducible non-instances]. -/ abbrev PseudoEMetricSpace.toPseudoMetricSpaceOfDist {α : Type u} [e : PseudoEMetricSpace α] (dist : α → α → ℝ) (edist_ne_top : ∀ x y : α, edist x y ≠ ⊤) (h : ∀ x y, dist x y = ENNReal.toReal (edist x y)) : PseudoMetricSpace α where dist := dist dist_self x := by simp [h] dist_comm x y := by simp [h, edist_comm] dist_triangle x y z := by simp only [h] exact ENNReal.toReal_le_add (edist_triangle _ _ _) (edist_ne_top _ _) (edist_ne_top _ _) edist := edist edist_dist _ _ := by simp only [h, ENNReal.ofReal_toReal (edist_ne_top _ _)] toUniformSpace := e.toUniformSpace uniformity_dist := e.uniformity_edist.trans <| by simpa only [ENNReal.coe_toNNReal (edist_ne_top _ _), h] using (Metric.uniformity_edist_aux fun x y : α => (edist x y).toNNReal).symm /-- One gets a pseudometric space from an emetric space if the edistance is everywhere finite, by pushing the edistance to reals. We set it up so that the edist and the uniformity are defeq in the pseudometric space and the emetric space. -/ abbrev PseudoEMetricSpace.toPseudoMetricSpace {α : Type u} [PseudoEMetricSpace α] (h : ∀ x y : α, edist x y ≠ ⊤) : PseudoMetricSpace α := PseudoEMetricSpace.toPseudoMetricSpaceOfDist (fun x y => ENNReal.toReal (edist x y)) h fun _ _ => rfl /-- Build a new pseudometric space from an old one where the bundled bornology structure is provably (but typically non-definitionaly) equal to some given bornology structure. See Note [forgetful inheritance]. See Note [reducible non-instances]. -/ abbrev PseudoMetricSpace.replaceBornology {α} [B : Bornology α] (m : PseudoMetricSpace α) (H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) : PseudoMetricSpace α := { m with toBornology := B cobounded_sets := Set.ext <| compl_surjective.forall.2 fun s => (H s).trans <| by rw [isBounded_iff, mem_setOf_eq, compl_compl] } theorem PseudoMetricSpace.replaceBornology_eq {α} [m : PseudoMetricSpace α] [B : Bornology α] (H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) : PseudoMetricSpace.replaceBornology _ H = m := by ext rfl -- ensure that the uniformity is unchanged when replacing the bornology. example {α} [B : Bornology α] (m : PseudoMetricSpace α) (H : ∀ s, @IsBounded _ B s ↔ @IsBounded _ PseudoMetricSpace.toBornology s) : (PseudoMetricSpace.replaceBornology m H).toUniformSpace = m.toUniformSpace := by with_reducible_and_instances rfl section Real /-- Instantiate the reals as a pseudometric space. -/ instance Real.pseudoMetricSpace : PseudoMetricSpace ℝ where dist x y := |x - y| dist_self := by simp [abs_zero] dist_comm _ _ := abs_sub_comm _ _ dist_triangle _ _ _ := abs_sub_le _ _ _ theorem Real.dist_eq (x y : ℝ) : dist x y = |x - y| := rfl theorem Real.nndist_eq (x y : ℝ) : nndist x y = Real.nnabs (x - y) := rfl theorem Real.nndist_eq' (x y : ℝ) : nndist x y = Real.nnabs (y - x) := nndist_comm _ _ theorem Real.dist_0_eq_abs (x : ℝ) : dist x 0 = |x| := by simp [Real.dist_eq] theorem Real.sub_le_dist (x y : ℝ) : x - y ≤ dist x y := by rw [Real.dist_eq, le_abs] exact Or.inl (le_refl _) theorem Real.ball_eq_Ioo (x r : ℝ) : ball x r = Ioo (x - r) (x + r) := Set.ext fun y => by rw [mem_ball, dist_comm, Real.dist_eq, abs_sub_lt_iff, mem_Ioo, ← sub_lt_iff_lt_add', sub_lt_comm] theorem Real.closedBall_eq_Icc {x r : ℝ} : closedBall x r = Icc (x - r) (x + r) := by ext y rw [mem_closedBall, dist_comm, Real.dist_eq, abs_sub_le_iff, mem_Icc, ← sub_le_iff_le_add', sub_le_comm] theorem Real.Ioo_eq_ball (x y : ℝ) : Ioo x y = ball ((x + y) / 2) ((y - x) / 2) := by rw [Real.ball_eq_Ioo, ← sub_div, add_comm, ← sub_add, add_sub_cancel_left, add_self_div_two, ← add_div, add_assoc, add_sub_cancel, add_self_div_two] theorem Real.Icc_eq_closedBall (x y : ℝ) : Icc x y = closedBall ((x + y) / 2) ((y - x) / 2) := by rw [Real.closedBall_eq_Icc, ← sub_div, add_comm, ← sub_add, add_sub_cancel_left, add_self_div_two, ← add_div, add_assoc, add_sub_cancel, add_self_div_two] theorem Metric.uniformity_eq_comap_nhds_zero : 𝓤 α = comap (fun p : α × α => dist p.1 p.2) (𝓝 (0 : ℝ)) := by ext s simp only [mem_uniformity_dist, (nhds_basis_ball.comap _).mem_iff] simp [subset_def, Real.dist_0_eq_abs] theorem tendsto_uniformity_iff_dist_tendsto_zero {f : ι → α × α} {p : Filter ι} : Tendsto f p (𝓤 α) ↔ Tendsto (fun x => dist (f x).1 (f x).2) p (𝓝 0) := by rw [Metric.uniformity_eq_comap_nhds_zero, tendsto_comap_iff, Function.comp_def] theorem Filter.Tendsto.congr_dist {f₁ f₂ : ι → α} {p : Filter ι} {a : α} (h₁ : Tendsto f₁ p (𝓝 a)) (h : Tendsto (fun x => dist (f₁ x) (f₂ x)) p (𝓝 0)) : Tendsto f₂ p (𝓝 a) := h₁.congr_uniformity <| tendsto_uniformity_iff_dist_tendsto_zero.2 h alias tendsto_of_tendsto_of_dist := Filter.Tendsto.congr_dist theorem tendsto_iff_of_dist {f₁ f₂ : ι → α} {p : Filter ι} {a : α} (h : Tendsto (fun x => dist (f₁ x) (f₂ x)) p (𝓝 0)) : Tendsto f₁ p (𝓝 a) ↔ Tendsto f₂ p (𝓝 a) := Uniform.tendsto_congr <| tendsto_uniformity_iff_dist_tendsto_zero.2 h end Real theorem PseudoMetricSpace.dist_eq_of_dist_zero (x : α) {y z : α} (h : dist y z = 0) : dist x y = dist x z := dist_comm y x ▸ dist_comm z x ▸ sub_eq_zero.1 (abs_nonpos_iff.1 (h ▸ abs_dist_sub_le y z x)) theorem dist_dist_dist_le_left (x y z : α) : dist (dist x z) (dist y z) ≤ dist x y := abs_dist_sub_le .. theorem dist_dist_dist_le_right (x y z : α) : dist (dist x y) (dist x z) ≤ dist y z := by simpa only [dist_comm x] using dist_dist_dist_le_left y z x theorem dist_dist_dist_le (x y x' y' : α) : dist (dist x y) (dist x' y') ≤ dist x x' + dist y y' := (dist_triangle _ _ _).trans <| add_le_add (dist_dist_dist_le_left _ _ _) (dist_dist_dist_le_right _ _ _) theorem nhds_comap_dist (a : α) : ((𝓝 (0 : ℝ)).comap (dist · a)) = 𝓝 a := by simp only [@nhds_eq_comap_uniformity α, Metric.uniformity_eq_comap_nhds_zero, comap_comap, Function.comp_def, dist_comm] theorem tendsto_iff_dist_tendsto_zero {f : β → α} {x : Filter β} {a : α} : Tendsto f x (𝓝 a) ↔ Tendsto (fun b => dist (f b) a) x (𝓝 0) := by rw [← nhds_comap_dist a, tendsto_comap_iff, Function.comp_def] namespace Metric variable {x y z : α} {ε ε₁ ε₂ : ℝ} {s : Set α} theorem ball_subset_interior_closedBall : ball x ε ⊆ interior (closedBall x ε) := interior_maximal ball_subset_closedBall isOpen_ball /-- ε-characterization of the closure in pseudometric spaces -/ theorem mem_closure_iff {s : Set α} {a : α} : a ∈ closure s ↔ ∀ ε > 0, ∃ b ∈ s, dist a b < ε := (mem_closure_iff_nhds_basis nhds_basis_ball).trans <| by simp only [mem_ball, dist_comm] theorem mem_closure_range_iff {e : β → α} {a : α} : a ∈ closure (range e) ↔ ∀ ε > 0, ∃ k : β, dist a (e k) < ε := by simp only [mem_closure_iff, exists_range_iff] theorem mem_closure_range_iff_nat {e : β → α} {a : α} : a ∈ closure (range e) ↔ ∀ n : ℕ, ∃ k : β, dist a (e k) < 1 / ((n : ℝ) + 1) := (mem_closure_iff_nhds_basis nhds_basis_ball_inv_nat_succ).trans <| by simp only [mem_ball, dist_comm, exists_range_iff, forall_const] theorem mem_of_closed' {s : Set α} (hs : IsClosed s) {a : α} : a ∈ s ↔ ∀ ε > 0, ∃ b ∈ s, dist a b < ε := by simpa only [hs.closure_eq] using @mem_closure_iff _ _ s a theorem dense_iff {s : Set α} : Dense s ↔ ∀ x, ∀ r > 0, (ball x r ∩ s).Nonempty := forall_congr' fun x => by simp only [mem_closure_iff, Set.Nonempty, exists_prop, mem_inter_iff, mem_ball', and_comm] theorem dense_iff_iUnion_ball (s : Set α) : Dense s ↔ ∀ r > 0, ⋃ c ∈ s, ball c r = univ := by simp_rw [eq_univ_iff_forall, mem_iUnion, exists_prop, mem_ball, Dense, mem_closure_iff, forall_comm (α := α)] theorem denseRange_iff {f : β → α} : DenseRange f ↔ ∀ x, ∀ r > 0, ∃ y, dist x (f y) < r := forall_congr' fun x => by simp only [mem_closure_iff, exists_range_iff] end Metric open Additive Multiplicative instance : PseudoMetricSpace (Additive α) := ‹_› instance : PseudoMetricSpace (Multiplicative α) := ‹_› section variable [PseudoMetricSpace X] @[simp] theorem nndist_ofMul (a b : X) : nndist (ofMul a) (ofMul b) = nndist a b := rfl @[simp] theorem nndist_ofAdd (a b : X) : nndist (ofAdd a) (ofAdd b) = nndist a b := rfl @[simp] theorem nndist_toMul (a b : Additive X) : nndist a.toMul b.toMul = nndist a b := rfl @[simp] theorem nndist_toAdd (a b : Multiplicative X) : nndist a.toAdd b.toAdd = nndist a b := rfl end open OrderDual instance : PseudoMetricSpace αᵒᵈ := ‹_› section variable [PseudoMetricSpace X] @[simp] theorem nndist_toDual (a b : X) : nndist (toDual a) (toDual b) = nndist a b := rfl @[simp] theorem nndist_ofDual (a b : Xᵒᵈ) : nndist (ofDual a) (ofDual b) = nndist a b := rfl end
Mathlib/Topology/MetricSpace/Pseudo/Defs.lean
1,386
1,390
/- Copyright (c) 2017 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Algebra.Ring.Associated import Mathlib.Algebra.Star.Unitary import Mathlib.RingTheory.PrincipalIdealDomain import Mathlib.Tactic.Ring import Mathlib.Algebra.EuclideanDomain.Int /-! # ℤ[√d] The ring of integers adjoined with a square root of `d : ℤ`. After defining the norm, we show that it is a linearly ordered commutative ring, as well as an integral domain. We provide the universal property, that ring homomorphisms `ℤ√d →+* R` correspond to choices of square roots of `d` in `R`. -/ /-- The ring of integers adjoined with a square root of `d`. These have the form `a + b √d` where `a b : ℤ`. The components are called `re` and `im` by analogy to the negative `d` case. -/ @[ext] structure Zsqrtd (d : ℤ) where /-- Component of the integer not multiplied by `√d` -/ re : ℤ /-- Component of the integer multiplied by `√d` -/ im : ℤ deriving DecidableEq @[inherit_doc] prefix:100 "ℤ√" => Zsqrtd namespace Zsqrtd section variable {d : ℤ} /-- Convert an integer to a `ℤ√d` -/ def ofInt (n : ℤ) : ℤ√d := ⟨n, 0⟩ theorem ofInt_re (n : ℤ) : (ofInt n : ℤ√d).re = n := rfl theorem ofInt_im (n : ℤ) : (ofInt n : ℤ√d).im = 0 := rfl /-- The zero of the ring -/ instance : Zero (ℤ√d) := ⟨ofInt 0⟩ @[simp] theorem zero_re : (0 : ℤ√d).re = 0 := rfl @[simp] theorem zero_im : (0 : ℤ√d).im = 0 := rfl instance : Inhabited (ℤ√d) := ⟨0⟩ /-- The one of the ring -/ instance : One (ℤ√d) := ⟨ofInt 1⟩ @[simp] theorem one_re : (1 : ℤ√d).re = 1 := rfl @[simp] theorem one_im : (1 : ℤ√d).im = 0 := rfl /-- The representative of `√d` in the ring -/ def sqrtd : ℤ√d := ⟨0, 1⟩ @[simp] theorem sqrtd_re : (sqrtd : ℤ√d).re = 0 := rfl @[simp] theorem sqrtd_im : (sqrtd : ℤ√d).im = 1 := rfl /-- Addition of elements of `ℤ√d` -/ instance : Add (ℤ√d) := ⟨fun z w => ⟨z.1 + w.1, z.2 + w.2⟩⟩ @[simp] theorem add_def (x y x' y' : ℤ) : (⟨x, y⟩ + ⟨x', y'⟩ : ℤ√d) = ⟨x + x', y + y'⟩ := rfl @[simp] theorem add_re (z w : ℤ√d) : (z + w).re = z.re + w.re := rfl @[simp] theorem add_im (z w : ℤ√d) : (z + w).im = z.im + w.im := rfl /-- Negation in `ℤ√d` -/ instance : Neg (ℤ√d) := ⟨fun z => ⟨-z.1, -z.2⟩⟩ @[simp] theorem neg_re (z : ℤ√d) : (-z).re = -z.re := rfl @[simp] theorem neg_im (z : ℤ√d) : (-z).im = -z.im := rfl /-- Multiplication in `ℤ√d` -/ instance : Mul (ℤ√d) := ⟨fun z w => ⟨z.1 * w.1 + d * z.2 * w.2, z.1 * w.2 + z.2 * w.1⟩⟩ @[simp] theorem mul_re (z w : ℤ√d) : (z * w).re = z.re * w.re + d * z.im * w.im := rfl @[simp] theorem mul_im (z w : ℤ√d) : (z * w).im = z.re * w.im + z.im * w.re := rfl instance addCommGroup : AddCommGroup (ℤ√d) := by refine { add := (· + ·) zero := (0 : ℤ√d) sub := fun a b => a + -b neg := Neg.neg nsmul := @nsmulRec (ℤ√d) ⟨0⟩ ⟨(· + ·)⟩ zsmul := @zsmulRec (ℤ√d) ⟨0⟩ ⟨(· + ·)⟩ ⟨Neg.neg⟩ (@nsmulRec (ℤ√d) ⟨0⟩ ⟨(· + ·)⟩) add_assoc := ?_ zero_add := ?_ add_zero := ?_ neg_add_cancel := ?_ add_comm := ?_ } <;> intros <;> ext <;> simp [add_comm, add_left_comm] @[simp] theorem sub_re (z w : ℤ√d) : (z - w).re = z.re - w.re := rfl @[simp] theorem sub_im (z w : ℤ√d) : (z - w).im = z.im - w.im := rfl instance addGroupWithOne : AddGroupWithOne (ℤ√d) := { Zsqrtd.addCommGroup with natCast := fun n => ofInt n intCast := ofInt one := 1 } instance commRing : CommRing (ℤ√d) := by refine { Zsqrtd.addGroupWithOne with mul := (· * ·) npow := @npowRec (ℤ√d) ⟨1⟩ ⟨(· * ·)⟩, add_comm := ?_ left_distrib := ?_ right_distrib := ?_ zero_mul := ?_ mul_zero := ?_ mul_assoc := ?_ one_mul := ?_ mul_one := ?_ mul_comm := ?_ } <;> intros <;> ext <;> simp <;> ring instance : AddMonoid (ℤ√d) := by infer_instance instance : Monoid (ℤ√d) := by infer_instance instance : CommMonoid (ℤ√d) := by infer_instance instance : CommSemigroup (ℤ√d) := by infer_instance instance : Semigroup (ℤ√d) := by infer_instance instance : AddCommSemigroup (ℤ√d) := by infer_instance instance : AddSemigroup (ℤ√d) := by infer_instance instance : CommSemiring (ℤ√d) := by infer_instance instance : Semiring (ℤ√d) := by infer_instance instance : Ring (ℤ√d) := by infer_instance instance : Distrib (ℤ√d) := by infer_instance /-- Conjugation in `ℤ√d`. The conjugate of `a + b √d` is `a - b √d`. -/ instance : Star (ℤ√d) where star z := ⟨z.1, -z.2⟩ @[simp] theorem star_mk (x y : ℤ) : star (⟨x, y⟩ : ℤ√d) = ⟨x, -y⟩ := rfl @[simp] theorem star_re (z : ℤ√d) : (star z).re = z.re := rfl @[simp] theorem star_im (z : ℤ√d) : (star z).im = -z.im := rfl instance : StarRing (ℤ√d) where star_involutive _ := Zsqrtd.ext rfl (neg_neg _) star_mul a b := by ext <;> simp <;> ring star_add _ _ := Zsqrtd.ext rfl (neg_add _ _) -- Porting note: proof was `by decide` instance nontrivial : Nontrivial (ℤ√d) := ⟨⟨0, 1, Zsqrtd.ext_iff.not.mpr (by simp)⟩⟩ @[simp] theorem natCast_re (n : ℕ) : (n : ℤ√d).re = n := rfl @[simp] theorem ofNat_re (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℤ√d).re = n := rfl @[simp] theorem natCast_im (n : ℕ) : (n : ℤ√d).im = 0 := rfl @[simp] theorem ofNat_im (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℤ√d).im = 0 := rfl theorem natCast_val (n : ℕ) : (n : ℤ√d) = ⟨n, 0⟩ := rfl @[simp] theorem intCast_re (n : ℤ) : (n : ℤ√d).re = n := by cases n <;> rfl @[simp] theorem intCast_im (n : ℤ) : (n : ℤ√d).im = 0 := by cases n <;> rfl theorem intCast_val (n : ℤ) : (n : ℤ√d) = ⟨n, 0⟩ := by ext <;> simp instance : CharZero (ℤ√d) where cast_injective m n := by simp [Zsqrtd.ext_iff] @[simp] theorem ofInt_eq_intCast (n : ℤ) : (ofInt n : ℤ√d) = n := by ext <;> simp [ofInt_re, ofInt_im] @[simp] theorem nsmul_val (n : ℕ) (x y : ℤ) : (n : ℤ√d) * ⟨x, y⟩ = ⟨n * x, n * y⟩ := by ext <;> simp @[simp] theorem smul_val (n x y : ℤ) : (n : ℤ√d) * ⟨x, y⟩ = ⟨n * x, n * y⟩ := by ext <;> simp theorem smul_re (a : ℤ) (b : ℤ√d) : (↑a * b).re = a * b.re := by simp theorem smul_im (a : ℤ) (b : ℤ√d) : (↑a * b).im = a * b.im := by simp @[simp] theorem muld_val (x y : ℤ) : sqrtd (d := d) * ⟨x, y⟩ = ⟨d * y, x⟩ := by ext <;> simp @[simp] theorem dmuld : sqrtd (d := d) * sqrtd (d := d) = d := by ext <;> simp @[simp] theorem smuld_val (n x y : ℤ) : sqrtd * (n : ℤ√d) * ⟨x, y⟩ = ⟨d * n * y, n * x⟩ := by ext <;> simp theorem decompose {x y : ℤ} : (⟨x, y⟩ : ℤ√d) = x + sqrtd (d := d) * y := by ext <;> simp theorem mul_star {x y : ℤ} : (⟨x, y⟩ * star ⟨x, y⟩ : ℤ√d) = x * x - d * y * y := by ext <;> simp [sub_eq_add_neg, mul_comm] theorem intCast_dvd (z : ℤ) (a : ℤ√d) : ↑z ∣ a ↔ z ∣ a.re ∧ z ∣ a.im := by constructor · rintro ⟨x, rfl⟩ simp only [add_zero, intCast_re, zero_mul, mul_im, dvd_mul_right, and_self_iff, mul_re, mul_zero, intCast_im] · rintro ⟨⟨r, hr⟩, ⟨i, hi⟩⟩ use ⟨r, i⟩ rw [smul_val, Zsqrtd.ext_iff] exact ⟨hr, hi⟩ @[simp, norm_cast] theorem intCast_dvd_intCast (a b : ℤ) : (a : ℤ√d) ∣ b ↔ a ∣ b := by rw [intCast_dvd] constructor · rintro ⟨hre, -⟩ rwa [intCast_re] at hre · rw [intCast_re, intCast_im] exact fun hc => ⟨hc, dvd_zero a⟩ protected theorem eq_of_smul_eq_smul_left {a : ℤ} {b c : ℤ√d} (ha : a ≠ 0) (h : ↑a * b = a * c) : b = c := by rw [Zsqrtd.ext_iff] at h ⊢ apply And.imp _ _ h <;> simpa only [smul_re, smul_im] using mul_left_cancel₀ ha section Gcd theorem gcd_eq_zero_iff (a : ℤ√d) : Int.gcd a.re a.im = 0 ↔ a = 0 := by simp only [Int.gcd_eq_zero_iff, Zsqrtd.ext_iff, eq_self_iff_true, zero_im, zero_re]
theorem gcd_pos_iff (a : ℤ√d) : 0 < Int.gcd a.re a.im ↔ a ≠ 0 :=
Mathlib/NumberTheory/Zsqrtd/Basic.lean
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/- Copyright (c) 2016 Leonardo de Moura. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Leonardo de Moura -/ import Mathlib.Control.Basic import Mathlib.Data.Set.Defs import Mathlib.Data.Set.Lattice.Image import Mathlib.Data.Set.Notation /-! # Functoriality of `Set` This file defines the functor structure of `Set`. -/ universe u open Function Set.Notation namespace Set variable {α β : Type u} {s : Set α} {f : α → Set β} /-- The `Set` functor is a monad. This is not a global instance because it does not have computational content, so it does not make much sense using `do` notation in general. Plus, this would cause monad-related coercions and monad lifting logic to become activated. Either use `attribute [local instance] Set.monad` to make it be a local instance or use `SetM.run do ...` when `do` notation is wanted. -/ protected def monad : Monad.{u} Set where pure a := {a} bind s f := ⋃ i ∈ s, f i seq s t := Set.seq s (t ()) map := Set.image section with_instance attribute [local instance] Set.monad @[simp] theorem bind_def : s >>= f = ⋃ i ∈ s, f i := rfl @[simp] theorem fmap_eq_image (f : α → β) : f <$> s = f '' s := rfl @[simp] theorem seq_eq_set_seq (s : Set (α → β)) (t : Set α) : s <*> t = s.seq t := rfl @[simp] theorem pure_def (a : α) : (pure a : Set α) = {a} := rfl /-- `Set.image2` in terms of monadic operations. Note that this can't be taken as the definition because of the lack of universe polymorphism. -/ theorem image2_def {α β γ : Type u} (f : α → β → γ) (s : Set α) (t : Set β) : image2 f s t = f <$> s <*> t := by ext simp instance : LawfulMonad Set := LawfulMonad.mk' (id_map := image_id) (pure_bind := biUnion_singleton) (bind_assoc := fun _ _ _ => by simp only [bind_def, biUnion_iUnion]) (bind_pure_comp := fun _ _ => (image_eq_iUnion _ _).symm) (bind_map := fun _ _ => seq_def.symm) instance : CommApplicative (Set : Type u → Type u) := ⟨fun s t => prod_image_seq_comm s t⟩ instance : Alternative Set := { Set.monad with orElse := fun s t => s ∪ (t ()) failure := ∅ } /-! ### Monadic coercion lemmas -/ variable {β : Set α} {γ : Set β} theorem mem_coe_of_mem {a : α} (ha : a ∈ β) (ha' : ⟨a, ha⟩ ∈ γ) : a ∈ (γ : Set α) := ⟨_, ⟨⟨_, rfl⟩, _, ⟨ha', rfl⟩, rfl⟩⟩ theorem coe_subset : (γ : Set α) ⊆ β := by intro _ ⟨_, ⟨⟨⟨_, ha⟩, rfl⟩, _, ⟨_, rfl⟩, _⟩⟩; convert ha theorem mem_of_mem_coe {a : α} (ha : a ∈ (γ : Set α)) : ⟨a, coe_subset ha⟩ ∈ γ := by rcases ha with ⟨_, ⟨_, rfl⟩, _, ⟨ha, rfl⟩, _⟩; convert ha theorem eq_univ_of_coe_eq (hγ : (γ : Set α) = β) : γ = univ := eq_univ_of_forall fun ⟨_, ha⟩ => mem_of_mem_coe <| hγ.symm ▸ ha theorem image_coe_eq_restrict_image {δ : Type*} {f : α → δ} : f '' γ = β.restrict f '' γ := ext fun _ => ⟨fun ⟨_, h, ha⟩ => ⟨_, mem_of_mem_coe h, ha⟩, fun ⟨_, h, ha⟩ => ⟨_, mem_coe_of_mem _ h, ha⟩⟩ end with_instance /-! ### Coercion applying functoriality for `Subtype.val` The `Monad` instance gives a coercion using the internal function `Lean.Internal.coeM`. In practice this is only used for applying the `Set` functor to `Subtype.val`, as was defined in `Data.Set.Notation`. -/ /-- The coercion from `Set.monad` as an instance is equal to the coercion in `Data.Set.Notation`. -/ theorem coe_eq_image_val (t : Set s) : @Lean.Internal.coeM Set s α _ Set.monad t = (t : Set α) := by change ⋃ (x ∈ t), {x.1} = _ ext simp variable {β : Set α} {γ : Set β} {a : α}
theorem mem_image_val_of_mem (ha : a ∈ β) (ha' : ⟨a, ha⟩ ∈ γ) : a ∈ (γ : Set α) := ⟨_, ha', rfl⟩ theorem image_val_subset : (γ : Set α) ⊆ β := by
Mathlib/Data/Set/Functor.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, Jean Lo, Calle Sönne, Sébastien Gouëzel, Rémy Degenne -/ import Mathlib.Analysis.SpecialFunctions.Pow.Continuity import Mathlib.Analysis.SpecialFunctions.Complex.LogDeriv import Mathlib.Analysis.Calculus.FDeriv.Extend import Mathlib.Analysis.Calculus.Deriv.Prod import Mathlib.Analysis.SpecialFunctions.Log.Deriv import Mathlib.Analysis.SpecialFunctions.Trigonometric.Deriv /-! # Derivatives of power function on `ℂ`, `ℝ`, `ℝ≥0`, and `ℝ≥0∞` We also prove differentiability and provide derivatives for the power functions `x ^ y`. -/ noncomputable section open scoped Real Topology NNReal ENNReal open Filter namespace Complex theorem hasStrictFDerivAt_cpow {p : ℂ × ℂ} (hp : p.1 ∈ slitPlane) : HasStrictFDerivAt (fun x : ℂ × ℂ => x.1 ^ x.2) ((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℂ ℂ ℂ + (p.1 ^ p.2 * log p.1) • ContinuousLinearMap.snd ℂ ℂ ℂ) p := by have A : p.1 ≠ 0 := slitPlane_ne_zero hp have : (fun x : ℂ × ℂ => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) := ((isOpen_ne.preimage continuous_fst).eventually_mem A).mono fun p hp => cpow_def_of_ne_zero hp _ rw [cpow_sub _ _ A, cpow_one, mul_div_left_comm, mul_smul, mul_smul] refine HasStrictFDerivAt.congr_of_eventuallyEq ?_ this.symm simpa only [cpow_def_of_ne_zero A, div_eq_mul_inv, mul_smul, add_comm, smul_add] using ((hasStrictFDerivAt_fst.clog hp).mul hasStrictFDerivAt_snd).cexp theorem hasStrictFDerivAt_cpow' {x y : ℂ} (hp : x ∈ slitPlane) : HasStrictFDerivAt (fun x : ℂ × ℂ => x.1 ^ x.2) ((y * x ^ (y - 1)) • ContinuousLinearMap.fst ℂ ℂ ℂ + (x ^ y * log x) • ContinuousLinearMap.snd ℂ ℂ ℂ) (x, y) := @hasStrictFDerivAt_cpow (x, y) hp theorem hasStrictDerivAt_const_cpow {x y : ℂ} (h : x ≠ 0 ∨ y ≠ 0) : HasStrictDerivAt (fun y => x ^ y) (x ^ y * log x) y := by rcases em (x = 0) with (rfl | hx) · replace h := h.neg_resolve_left rfl rw [log_zero, mul_zero] refine (hasStrictDerivAt_const y 0).congr_of_eventuallyEq ?_ exact (isOpen_ne.eventually_mem h).mono fun y hy => (zero_cpow hy).symm · simpa only [cpow_def_of_ne_zero hx, mul_one] using ((hasStrictDerivAt_id y).const_mul (log x)).cexp theorem hasFDerivAt_cpow {p : ℂ × ℂ} (hp : p.1 ∈ slitPlane) : HasFDerivAt (fun x : ℂ × ℂ => x.1 ^ x.2) ((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℂ ℂ ℂ + (p.1 ^ p.2 * log p.1) • ContinuousLinearMap.snd ℂ ℂ ℂ) p := (hasStrictFDerivAt_cpow hp).hasFDerivAt end Complex section fderiv open Complex variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℂ E] {f g : E → ℂ} {f' g' : E →L[ℂ] ℂ} {x : E} {s : Set E} {c : ℂ} theorem HasStrictFDerivAt.cpow (hf : HasStrictFDerivAt f f' x) (hg : HasStrictFDerivAt g g' x) (h0 : f x ∈ slitPlane) : HasStrictFDerivAt (fun x => f x ^ g x) ((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Complex.log (f x)) • g') x := (hasStrictFDerivAt_cpow (p := (f x, g x)) h0).comp x (hf.prodMk hg) theorem HasStrictFDerivAt.const_cpow (hf : HasStrictFDerivAt f f' x) (h0 : c ≠ 0 ∨ f x ≠ 0) : HasStrictFDerivAt (fun x => c ^ f x) ((c ^ f x * Complex.log c) • f') x := (hasStrictDerivAt_const_cpow h0).comp_hasStrictFDerivAt x hf theorem HasFDerivAt.cpow (hf : HasFDerivAt f f' x) (hg : HasFDerivAt g g' x) (h0 : f x ∈ slitPlane) : HasFDerivAt (fun x => f x ^ g x) ((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Complex.log (f x)) • g') x := by convert (@Complex.hasFDerivAt_cpow ((fun x => (f x, g x)) x) h0).comp x (hf.prodMk hg) theorem HasFDerivAt.const_cpow (hf : HasFDerivAt f f' x) (h0 : c ≠ 0 ∨ f x ≠ 0) : HasFDerivAt (fun x => c ^ f x) ((c ^ f x * Complex.log c) • f') x := (hasStrictDerivAt_const_cpow h0).hasDerivAt.comp_hasFDerivAt x hf theorem HasFDerivWithinAt.cpow (hf : HasFDerivWithinAt f f' s x) (hg : HasFDerivWithinAt g g' s x) (h0 : f x ∈ slitPlane) : HasFDerivWithinAt (fun x => f x ^ g x) ((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Complex.log (f x)) • g') s x := by convert (@Complex.hasFDerivAt_cpow ((fun x => (f x, g x)) x) h0).comp_hasFDerivWithinAt x (hf.prodMk hg) theorem HasFDerivWithinAt.const_cpow (hf : HasFDerivWithinAt f f' s x) (h0 : c ≠ 0 ∨ f x ≠ 0) : HasFDerivWithinAt (fun x => c ^ f x) ((c ^ f x * Complex.log c) • f') s x := (hasStrictDerivAt_const_cpow h0).hasDerivAt.comp_hasFDerivWithinAt x hf theorem DifferentiableAt.cpow (hf : DifferentiableAt ℂ f x) (hg : DifferentiableAt ℂ g x) (h0 : f x ∈ slitPlane) : DifferentiableAt ℂ (fun x => f x ^ g x) x := (hf.hasFDerivAt.cpow hg.hasFDerivAt h0).differentiableAt theorem DifferentiableAt.const_cpow (hf : DifferentiableAt ℂ f x) (h0 : c ≠ 0 ∨ f x ≠ 0) : DifferentiableAt ℂ (fun x => c ^ f x) x := (hf.hasFDerivAt.const_cpow h0).differentiableAt theorem DifferentiableAt.cpow_const (hf : DifferentiableAt ℂ f x) (h0 : f x ∈ slitPlane) : DifferentiableAt ℂ (fun x => f x ^ c) x := hf.cpow (differentiableAt_const c) h0 theorem DifferentiableWithinAt.cpow (hf : DifferentiableWithinAt ℂ f s x) (hg : DifferentiableWithinAt ℂ g s x) (h0 : f x ∈ slitPlane) : DifferentiableWithinAt ℂ (fun x => f x ^ g x) s x := (hf.hasFDerivWithinAt.cpow hg.hasFDerivWithinAt h0).differentiableWithinAt theorem DifferentiableWithinAt.const_cpow (hf : DifferentiableWithinAt ℂ f s x) (h0 : c ≠ 0 ∨ f x ≠ 0) : DifferentiableWithinAt ℂ (fun x => c ^ f x) s x := (hf.hasFDerivWithinAt.const_cpow h0).differentiableWithinAt theorem DifferentiableWithinAt.cpow_const (hf : DifferentiableWithinAt ℂ f s x) (h0 : f x ∈ slitPlane) : DifferentiableWithinAt ℂ (fun x => f x ^ c) s x := hf.cpow (differentiableWithinAt_const c) h0 theorem DifferentiableOn.cpow (hf : DifferentiableOn ℂ f s) (hg : DifferentiableOn ℂ g s) (h0 : Set.MapsTo f s slitPlane) : DifferentiableOn ℂ (fun x ↦ f x ^ g x) s := fun x hx ↦ (hf x hx).cpow (hg x hx) (h0 hx) theorem DifferentiableOn.const_cpow (hf : DifferentiableOn ℂ f s) (h0 : c ≠ 0 ∨ ∀ x ∈ s, f x ≠ 0) : DifferentiableOn ℂ (fun x ↦ c ^ f x) s := fun x hx ↦ (hf x hx).const_cpow (h0.imp_right fun h ↦ h x hx) theorem DifferentiableOn.cpow_const (hf : DifferentiableOn ℂ f s) (h0 : ∀ x ∈ s, f x ∈ slitPlane) : DifferentiableOn ℂ (fun x => f x ^ c) s := hf.cpow (differentiableOn_const c) h0 theorem Differentiable.cpow (hf : Differentiable ℂ f) (hg : Differentiable ℂ g) (h0 : ∀ x, f x ∈ slitPlane) : Differentiable ℂ (fun x ↦ f x ^ g x) := fun x ↦ (hf x).cpow (hg x) (h0 x) theorem Differentiable.const_cpow (hf : Differentiable ℂ f) (h0 : c ≠ 0 ∨ ∀ x, f x ≠ 0) : Differentiable ℂ (fun x ↦ c ^ f x) := fun x ↦ (hf x).const_cpow (h0.imp_right fun h ↦ h x) @[fun_prop] lemma differentiable_const_cpow_of_neZero (z : ℂ) [NeZero z] : Differentiable ℂ fun s : ℂ ↦ z ^ s := differentiable_id.const_cpow (.inl <| NeZero.ne z) @[fun_prop] lemma differentiableAt_const_cpow_of_neZero (z : ℂ) [NeZero z] (t : ℂ) : DifferentiableAt ℂ (fun s : ℂ ↦ z ^ s) t := differentiableAt_id.const_cpow (.inl <| NeZero.ne z) end fderiv section deriv open Complex variable {f g : ℂ → ℂ} {s : Set ℂ} {f' g' x c : ℂ} /-- A private lemma that rewrites the output of lemmas like `HasFDerivAt.cpow` to the form expected by lemmas like `HasDerivAt.cpow`. -/ private theorem aux : ((g x * f x ^ (g x - 1)) • (1 : ℂ →L[ℂ] ℂ).smulRight f' + (f x ^ g x * log (f x)) • (1 : ℂ →L[ℂ] ℂ).smulRight g') 1 = g x * f x ^ (g x - 1) * f' + f x ^ g x * log (f x) * g' := by simp only [Algebra.id.smul_eq_mul, one_mul, ContinuousLinearMap.one_apply, ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.add_apply, Pi.smul_apply, ContinuousLinearMap.coe_smul'] nonrec theorem HasStrictDerivAt.cpow (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x) (h0 : f x ∈ slitPlane) : HasStrictDerivAt (fun x => f x ^ g x) (g x * f x ^ (g x - 1) * f' + f x ^ g x * Complex.log (f x) * g') x := by simpa using (hf.cpow hg h0).hasStrictDerivAt theorem HasStrictDerivAt.const_cpow (hf : HasStrictDerivAt f f' x) (h : c ≠ 0 ∨ f x ≠ 0) : HasStrictDerivAt (fun x => c ^ f x) (c ^ f x * Complex.log c * f') x := (hasStrictDerivAt_const_cpow h).comp x hf theorem Complex.hasStrictDerivAt_cpow_const (h : x ∈ slitPlane) : HasStrictDerivAt (fun z : ℂ => z ^ c) (c * x ^ (c - 1)) x := by simpa only [mul_zero, add_zero, mul_one] using (hasStrictDerivAt_id x).cpow (hasStrictDerivAt_const x c) h theorem HasStrictDerivAt.cpow_const (hf : HasStrictDerivAt f f' x) (h0 : f x ∈ slitPlane) : HasStrictDerivAt (fun x => f x ^ c) (c * f x ^ (c - 1) * f') x := (Complex.hasStrictDerivAt_cpow_const h0).comp x hf theorem HasDerivAt.cpow (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) (h0 : f x ∈ slitPlane) : HasDerivAt (fun x => f x ^ g x) (g x * f x ^ (g x - 1) * f' + f x ^ g x * Complex.log (f x) * g') x := by simpa only [aux] using (hf.hasFDerivAt.cpow hg h0).hasDerivAt theorem HasDerivAt.const_cpow (hf : HasDerivAt f f' x) (h0 : c ≠ 0 ∨ f x ≠ 0) : HasDerivAt (fun x => c ^ f x) (c ^ f x * Complex.log c * f') x := (hasStrictDerivAt_const_cpow h0).hasDerivAt.comp x hf theorem HasDerivAt.cpow_const (hf : HasDerivAt f f' x) (h0 : f x ∈ slitPlane) : HasDerivAt (fun x => f x ^ c) (c * f x ^ (c - 1) * f') x := (Complex.hasStrictDerivAt_cpow_const h0).hasDerivAt.comp x hf theorem HasDerivWithinAt.cpow (hf : HasDerivWithinAt f f' s x) (hg : HasDerivWithinAt g g' s x) (h0 : f x ∈ slitPlane) : HasDerivWithinAt (fun x => f x ^ g x) (g x * f x ^ (g x - 1) * f' + f x ^ g x * Complex.log (f x) * g') s x := by simpa only [aux] using (hf.hasFDerivWithinAt.cpow hg h0).hasDerivWithinAt theorem HasDerivWithinAt.const_cpow (hf : HasDerivWithinAt f f' s x) (h0 : c ≠ 0 ∨ f x ≠ 0) : HasDerivWithinAt (fun x => c ^ f x) (c ^ f x * Complex.log c * f') s x := (hasStrictDerivAt_const_cpow h0).hasDerivAt.comp_hasDerivWithinAt x hf theorem HasDerivWithinAt.cpow_const (hf : HasDerivWithinAt f f' s x) (h0 : f x ∈ slitPlane) : HasDerivWithinAt (fun x => f x ^ c) (c * f x ^ (c - 1) * f') s x := (Complex.hasStrictDerivAt_cpow_const h0).hasDerivAt.comp_hasDerivWithinAt x hf /-- Although `fun x => x ^ r` for fixed `r` is *not* complex-differentiable along the negative real line, it is still real-differentiable, and the derivative is what one would formally expect. See `hasDerivAt_ofReal_cpow_const` for an alternate formulation. -/ theorem hasDerivAt_ofReal_cpow_const' {x : ℝ} (hx : x ≠ 0) {r : ℂ} (hr : r ≠ -1) : HasDerivAt (fun y : ℝ => (y : ℂ) ^ (r + 1) / (r + 1)) (x ^ r) x := by rw [Ne, ← add_eq_zero_iff_eq_neg, ← Ne] at hr rcases lt_or_gt_of_ne hx.symm with (hx | hx) · -- easy case : `0 < x` apply HasDerivAt.comp_ofReal (e := fun y => (y : ℂ) ^ (r + 1) / (r + 1)) convert HasDerivAt.div_const (𝕜 := ℂ) ?_ (r + 1) using 1 · exact (mul_div_cancel_right₀ _ hr).symm · convert HasDerivAt.cpow_const ?_ ?_ using 1 · rw [add_sub_cancel_right, mul_comm]; exact (mul_one _).symm · exact hasDerivAt_id (x : ℂ) · simp [hx] · -- harder case : `x < 0` have : ∀ᶠ y : ℝ in 𝓝 x, (y : ℂ) ^ (r + 1) / (r + 1) = (-y : ℂ) ^ (r + 1) * exp (π * I * (r + 1)) / (r + 1) := by refine Filter.eventually_of_mem (Iio_mem_nhds hx) fun y hy => ?_ rw [ofReal_cpow_of_nonpos (le_of_lt hy)] refine HasDerivAt.congr_of_eventuallyEq ?_ this rw [ofReal_cpow_of_nonpos (le_of_lt hx)] suffices HasDerivAt (fun y : ℝ => (-↑y) ^ (r + 1) * exp (↑π * I * (r + 1))) ((r + 1) * (-↑x) ^ r * exp (↑π * I * r)) x by convert this.div_const (r + 1) using 1 conv_rhs => rw [mul_assoc, mul_comm, mul_div_cancel_right₀ _ hr] rw [mul_add ((π : ℂ) * _), mul_one, exp_add, exp_pi_mul_I, mul_comm (_ : ℂ) (-1 : ℂ), neg_one_mul] simp_rw [mul_neg, ← neg_mul, ← ofReal_neg] suffices HasDerivAt (fun y : ℝ => (↑(-y) : ℂ) ^ (r + 1)) (-(r + 1) * ↑(-x) ^ r) x by convert this.neg.mul_const _ using 1; ring suffices HasDerivAt (fun y : ℝ => (y : ℂ) ^ (r + 1)) ((r + 1) * ↑(-x) ^ r) (-x) by convert @HasDerivAt.scomp ℝ _ ℂ _ _ x ℝ _ _ _ _ _ _ _ _ this (hasDerivAt_neg x) using 1 rw [real_smul, ofReal_neg 1, ofReal_one]; ring suffices HasDerivAt (fun y : ℂ => y ^ (r + 1)) ((r + 1) * ↑(-x) ^ r) ↑(-x) by exact this.comp_ofReal conv in ↑_ ^ _ => rw [(by ring : r = r + 1 - 1)] convert HasDerivAt.cpow_const ?_ ?_ using 1 · rw [add_sub_cancel_right, add_sub_cancel_right]; exact (mul_one _).symm · exact hasDerivAt_id ((-x : ℝ) : ℂ) · simp [hx] @[deprecated (since := "2024-12-15")] alias hasDerivAt_ofReal_cpow := hasDerivAt_ofReal_cpow_const' /-- An alternate formulation of `hasDerivAt_ofReal_cpow_const'`. -/ theorem hasDerivAt_ofReal_cpow_const {x : ℝ} (hx : x ≠ 0) {r : ℂ} (hr : r ≠ 0) : HasDerivAt (fun y : ℝ => (y : ℂ) ^ r) (r * x ^ (r - 1)) x := by have := HasDerivAt.const_mul r <| hasDerivAt_ofReal_cpow_const' hx (by rwa [ne_eq, sub_eq_neg_self]) simpa [sub_add_cancel, mul_div_cancel₀ _ hr] using this /-- A version of `DifferentiableAt.cpow_const` for a real function. -/ theorem DifferentiableAt.ofReal_cpow_const {f : ℝ → ℝ} {x : ℝ} (hf : DifferentiableAt ℝ f x) (h0 : f x ≠ 0) (h1 : c ≠ 0) : DifferentiableAt ℝ (fun (y : ℝ) => (f y : ℂ) ^ c) x := (hasDerivAt_ofReal_cpow_const h0 h1).differentiableAt.comp x hf theorem Complex.deriv_cpow_const (hx : x ∈ Complex.slitPlane) : deriv (fun (x : ℂ) ↦ x ^ c) x = c * x ^ (c - 1) := (hasStrictDerivAt_cpow_const hx).hasDerivAt.deriv /-- A version of `Complex.deriv_cpow_const` for a real variable. -/ theorem Complex.deriv_ofReal_cpow_const {x : ℝ} (hx : x ≠ 0) (hc : c ≠ 0) : deriv (fun x : ℝ ↦ (x : ℂ) ^ c) x = c * x ^ (c - 1) := (hasDerivAt_ofReal_cpow_const hx hc).deriv theorem deriv_cpow_const (hf : DifferentiableAt ℂ f x) (hx : f x ∈ Complex.slitPlane) : deriv (fun (x : ℂ) ↦ f x ^ c) x = c * f x ^ (c - 1) * deriv f x := (hf.hasDerivAt.cpow_const hx).deriv theorem isTheta_deriv_ofReal_cpow_const_atTop {c : ℂ} (hc : c ≠ 0) : deriv (fun (x : ℝ) => (x : ℂ) ^ c) =Θ[atTop] fun x => x ^ (c.re - 1) := by calc _ =ᶠ[atTop] fun x : ℝ ↦ c * x ^ (c - 1) := by filter_upwards [eventually_ne_atTop 0] with x hx using by rw [deriv_ofReal_cpow_const hx hc] _ =Θ[atTop] fun x : ℝ ↦ ‖(x : ℂ) ^ (c - 1)‖ := (Asymptotics.IsTheta.of_norm_eventuallyEq EventuallyEq.rfl).const_mul_left hc _ =ᶠ[atTop] fun x ↦ x ^ (c.re - 1) := by filter_upwards [eventually_gt_atTop 0] with x hx rw [norm_cpow_eq_rpow_re_of_pos hx, sub_re, one_re] theorem isBigO_deriv_ofReal_cpow_const_atTop (c : ℂ) : deriv (fun (x : ℝ) => (x : ℂ) ^ c) =O[atTop] fun x => x ^ (c.re - 1) := by obtain rfl | hc := eq_or_ne c 0 · simp_rw [cpow_zero, deriv_const', Asymptotics.isBigO_zero] · exact (isTheta_deriv_ofReal_cpow_const_atTop hc).1 end deriv namespace Real variable {x y z : ℝ} /-- `(x, y) ↦ x ^ y` is strictly differentiable at `p : ℝ × ℝ` such that `0 < p.fst`. -/ theorem hasStrictFDerivAt_rpow_of_pos (p : ℝ × ℝ) (hp : 0 < p.1) : HasStrictFDerivAt (fun x : ℝ × ℝ => x.1 ^ x.2) ((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℝ ℝ ℝ + (p.1 ^ p.2 * log p.1) • ContinuousLinearMap.snd ℝ ℝ ℝ) p := by have : (fun x : ℝ × ℝ => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) := (continuousAt_fst.eventually (lt_mem_nhds hp)).mono fun p hp => rpow_def_of_pos hp _ refine HasStrictFDerivAt.congr_of_eventuallyEq ?_ this.symm convert ((hasStrictFDerivAt_fst.log hp.ne').mul hasStrictFDerivAt_snd).exp using 1 rw [rpow_sub_one hp.ne', ← rpow_def_of_pos hp, smul_add, smul_smul, mul_div_left_comm, div_eq_mul_inv, smul_smul, smul_smul, mul_assoc, add_comm] /-- `(x, y) ↦ x ^ y` is strictly differentiable at `p : ℝ × ℝ` such that `p.fst < 0`. -/ theorem hasStrictFDerivAt_rpow_of_neg (p : ℝ × ℝ) (hp : p.1 < 0) : HasStrictFDerivAt (fun x : ℝ × ℝ => x.1 ^ x.2) ((p.2 * p.1 ^ (p.2 - 1)) • ContinuousLinearMap.fst ℝ ℝ ℝ + (p.1 ^ p.2 * log p.1 - exp (log p.1 * p.2) * sin (p.2 * π) * π) • ContinuousLinearMap.snd ℝ ℝ ℝ) p := by have : (fun x : ℝ × ℝ => x.1 ^ x.2) =ᶠ[𝓝 p] fun x => exp (log x.1 * x.2) * cos (x.2 * π) := (continuousAt_fst.eventually (gt_mem_nhds hp)).mono fun p hp => rpow_def_of_neg hp _ refine HasStrictFDerivAt.congr_of_eventuallyEq ?_ this.symm convert ((hasStrictFDerivAt_fst.log hp.ne).mul hasStrictFDerivAt_snd).exp.mul (hasStrictFDerivAt_snd.mul_const π).cos using 1 simp_rw [rpow_sub_one hp.ne, smul_add, ← add_assoc, smul_smul, ← add_smul, ← mul_assoc, mul_comm (cos _), ← rpow_def_of_neg hp] rw [div_eq_mul_inv, add_comm]; congr 2 <;> ring /-- The function `fun (x, y) => x ^ y` is infinitely smooth at `(x, y)` unless `x = 0`. -/ theorem contDiffAt_rpow_of_ne (p : ℝ × ℝ) (hp : p.1 ≠ 0) {n : WithTop ℕ∞} : ContDiffAt ℝ n (fun p : ℝ × ℝ => p.1 ^ p.2) p := by rcases hp.lt_or_lt with hneg | hpos exacts [(((contDiffAt_fst.log hneg.ne).mul contDiffAt_snd).exp.mul (contDiffAt_snd.mul contDiffAt_const).cos).congr_of_eventuallyEq ((continuousAt_fst.eventually (gt_mem_nhds hneg)).mono fun p hp => rpow_def_of_neg hp _), ((contDiffAt_fst.log hpos.ne').mul contDiffAt_snd).exp.congr_of_eventuallyEq ((continuousAt_fst.eventually (lt_mem_nhds hpos)).mono fun p hp => rpow_def_of_pos hp _)] theorem differentiableAt_rpow_of_ne (p : ℝ × ℝ) (hp : p.1 ≠ 0) : DifferentiableAt ℝ (fun p : ℝ × ℝ => p.1 ^ p.2) p := (contDiffAt_rpow_of_ne p hp).differentiableAt le_rfl theorem _root_.HasStrictDerivAt.rpow {f g : ℝ → ℝ} {f' g' : ℝ} (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x) (h : 0 < f x) : HasStrictDerivAt (fun x => f x ^ g x) (f' * g x * f x ^ (g x - 1) + g' * f x ^ g x * Real.log (f x)) x := by convert (hasStrictFDerivAt_rpow_of_pos ((fun x => (f x, g x)) x) h).comp_hasStrictDerivAt x (hf.prodMk hg) using 1 simp [mul_assoc, mul_comm, mul_left_comm] theorem hasStrictDerivAt_rpow_const_of_ne {x : ℝ} (hx : x ≠ 0) (p : ℝ) : HasStrictDerivAt (fun x => x ^ p) (p * x ^ (p - 1)) x := by rcases hx.lt_or_lt with hx | hx · have := (hasStrictFDerivAt_rpow_of_neg (x, p) hx).comp_hasStrictDerivAt x ((hasStrictDerivAt_id x).prodMk (hasStrictDerivAt_const x p)) convert this using 1; simp · simpa using (hasStrictDerivAt_id x).rpow (hasStrictDerivAt_const x p) hx theorem hasStrictDerivAt_const_rpow {a : ℝ} (ha : 0 < a) (x : ℝ) : HasStrictDerivAt (fun x => a ^ x) (a ^ x * log a) x := by simpa using (hasStrictDerivAt_const _ _).rpow (hasStrictDerivAt_id x) ha lemma differentiableAt_rpow_const_of_ne (p : ℝ) {x : ℝ} (hx : x ≠ 0) : DifferentiableAt ℝ (fun x => x ^ p) x := (hasStrictDerivAt_rpow_const_of_ne hx p).differentiableAt lemma differentiableOn_rpow_const (p : ℝ) : DifferentiableOn ℝ (fun x => (x : ℝ) ^ p) {0}ᶜ := fun _ hx => (Real.differentiableAt_rpow_const_of_ne p hx).differentiableWithinAt /-- This lemma says that `fun x => a ^ x` is strictly differentiable for `a < 0`. Note that these values of `a` are outside of the "official" domain of `a ^ x`, and we may redefine `a ^ x` for negative `a` if some other definition will be more convenient. -/ theorem hasStrictDerivAt_const_rpow_of_neg {a x : ℝ} (ha : a < 0) : HasStrictDerivAt (fun x => a ^ x) (a ^ x * log a - exp (log a * x) * sin (x * π) * π) x := by simpa using (hasStrictFDerivAt_rpow_of_neg (a, x) ha).comp_hasStrictDerivAt x ((hasStrictDerivAt_const _ _).prodMk (hasStrictDerivAt_id _)) end Real namespace Real variable {z x y : ℝ} theorem hasDerivAt_rpow_const {x p : ℝ} (h : x ≠ 0 ∨ 1 ≤ p) : HasDerivAt (fun x => x ^ p) (p * x ^ (p - 1)) x := by rcases ne_or_eq x 0 with (hx | rfl) · exact (hasStrictDerivAt_rpow_const_of_ne hx _).hasDerivAt replace h : 1 ≤ p := h.neg_resolve_left rfl apply hasDerivAt_of_hasDerivAt_of_ne fun x hx => (hasStrictDerivAt_rpow_const_of_ne hx p).hasDerivAt exacts [continuousAt_id.rpow_const (Or.inr (zero_le_one.trans h)), continuousAt_const.mul (continuousAt_id.rpow_const (Or.inr (sub_nonneg.2 h)))] theorem differentiable_rpow_const {p : ℝ} (hp : 1 ≤ p) : Differentiable ℝ fun x : ℝ => x ^ p := fun _ => (hasDerivAt_rpow_const (Or.inr hp)).differentiableAt theorem deriv_rpow_const {x p : ℝ} (h : x ≠ 0 ∨ 1 ≤ p) : deriv (fun x : ℝ => x ^ p) x = p * x ^ (p - 1) := (hasDerivAt_rpow_const h).deriv theorem deriv_rpow_const' {p : ℝ} (h : 1 ≤ p) : (deriv fun x : ℝ => x ^ p) = fun x => p * x ^ (p - 1) := funext fun _ => deriv_rpow_const (Or.inr h) theorem contDiffAt_rpow_const_of_ne {x p : ℝ} {n : WithTop ℕ∞} (h : x ≠ 0) : ContDiffAt ℝ n (fun x => x ^ p) x := (contDiffAt_rpow_of_ne (x, p) h).comp x (contDiffAt_id.prodMk contDiffAt_const) theorem contDiff_rpow_const_of_le {p : ℝ} {n : ℕ} (h : ↑n ≤ p) : ContDiff ℝ n fun x : ℝ => x ^ p := by induction' n with n ihn generalizing p · exact contDiff_zero.2 (continuous_id.rpow_const fun x => Or.inr <| by simpa using h) · have h1 : 1 ≤ p := le_trans (by simp) h rw [Nat.cast_succ, ← le_sub_iff_add_le] at h rw [show ((n + 1 : ℕ) : WithTop ℕ∞) = n + 1 from rfl, contDiff_succ_iff_deriv, deriv_rpow_const' h1] simp only [WithTop.natCast_ne_top, analyticOn_univ, IsEmpty.forall_iff, true_and] exact ⟨differentiable_rpow_const h1, contDiff_const.mul (ihn h)⟩ theorem contDiffAt_rpow_const_of_le {x p : ℝ} {n : ℕ} (h : ↑n ≤ p) : ContDiffAt ℝ n (fun x : ℝ => x ^ p) x := (contDiff_rpow_const_of_le h).contDiffAt theorem contDiffAt_rpow_const {x p : ℝ} {n : ℕ} (h : x ≠ 0 ∨ ↑n ≤ p) : ContDiffAt ℝ n (fun x : ℝ => x ^ p) x := h.elim contDiffAt_rpow_const_of_ne contDiffAt_rpow_const_of_le theorem hasStrictDerivAt_rpow_const {x p : ℝ} (hx : x ≠ 0 ∨ 1 ≤ p) : HasStrictDerivAt (fun x => x ^ p) (p * x ^ (p - 1)) x := ContDiffAt.hasStrictDerivAt' (contDiffAt_rpow_const (by rwa [← Nat.cast_one] at hx)) (hasDerivAt_rpow_const hx) le_rfl end Real section Differentiability open Real section fderiv variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] {f g : E → ℝ} {f' g' : E →L[ℝ] ℝ} {x : E} {s : Set E} {c p : ℝ} {n : WithTop ℕ∞} #adaptation_note /-- https://github.com/leanprover/lean4/pull/6024 added `by exact` to deal with unification issues. -/ theorem HasFDerivWithinAt.rpow (hf : HasFDerivWithinAt f f' s x) (hg : HasFDerivWithinAt g g' s x) (h : 0 < f x) : HasFDerivWithinAt (fun x => f x ^ g x) ((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Real.log (f x)) • g') s x := by exact (hasStrictFDerivAt_rpow_of_pos (f x, g x) h).hasFDerivAt.comp_hasFDerivWithinAt x (hf.prodMk hg) theorem HasFDerivAt.rpow (hf : HasFDerivAt f f' x) (hg : HasFDerivAt g g' x) (h : 0 < f x) : HasFDerivAt (fun x => f x ^ g x) ((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Real.log (f x)) • g') x := by exact (hasStrictFDerivAt_rpow_of_pos (f x, g x) h).hasFDerivAt.comp x (hf.prodMk hg) theorem HasStrictFDerivAt.rpow (hf : HasStrictFDerivAt f f' x) (hg : HasStrictFDerivAt g g' x) (h : 0 < f x) : HasStrictFDerivAt (fun x => f x ^ g x) ((g x * f x ^ (g x - 1)) • f' + (f x ^ g x * Real.log (f x)) • g') x := (hasStrictFDerivAt_rpow_of_pos (f x, g x) h).comp x (hf.prodMk hg) #adaptation_note /-- https://github.com/leanprover/lean4/pull/6024 added `by exact` to deal with unification issues. -/ theorem DifferentiableWithinAt.rpow (hf : DifferentiableWithinAt ℝ f s x) (hg : DifferentiableWithinAt ℝ g s x) (h : f x ≠ 0) : DifferentiableWithinAt ℝ (fun x => f x ^ g x) s x := by exact (differentiableAt_rpow_of_ne (f x, g x) h).comp_differentiableWithinAt x (hf.prodMk hg) #adaptation_note /-- https://github.com/leanprover/lean4/pull/6024 added `by exact` to deal with unification issues. -/ theorem DifferentiableAt.rpow (hf : DifferentiableAt ℝ f x) (hg : DifferentiableAt ℝ g x) (h : f x ≠ 0) : DifferentiableAt ℝ (fun x => f x ^ g x) x := by exact (differentiableAt_rpow_of_ne (f x, g x) h).comp x (hf.prodMk hg) theorem DifferentiableOn.rpow (hf : DifferentiableOn ℝ f s) (hg : DifferentiableOn ℝ g s) (h : ∀ x ∈ s, f x ≠ 0) : DifferentiableOn ℝ (fun x => f x ^ g x) s := fun x hx => (hf x hx).rpow (hg x hx) (h x hx) theorem Differentiable.rpow (hf : Differentiable ℝ f) (hg : Differentiable ℝ g) (h : ∀ x, f x ≠ 0) : Differentiable ℝ fun x => f x ^ g x := fun x => (hf x).rpow (hg x) (h x) theorem HasFDerivWithinAt.rpow_const (hf : HasFDerivWithinAt f f' s x) (h : f x ≠ 0 ∨ 1 ≤ p) : HasFDerivWithinAt (fun x => f x ^ p) ((p * f x ^ (p - 1)) • f') s x := (hasDerivAt_rpow_const h).comp_hasFDerivWithinAt x hf theorem HasFDerivAt.rpow_const (hf : HasFDerivAt f f' x) (h : f x ≠ 0 ∨ 1 ≤ p) : HasFDerivAt (fun x => f x ^ p) ((p * f x ^ (p - 1)) • f') x := (hasDerivAt_rpow_const h).comp_hasFDerivAt x hf theorem HasStrictFDerivAt.rpow_const (hf : HasStrictFDerivAt f f' x) (h : f x ≠ 0 ∨ 1 ≤ p) : HasStrictFDerivAt (fun x => f x ^ p) ((p * f x ^ (p - 1)) • f') x := (hasStrictDerivAt_rpow_const h).comp_hasStrictFDerivAt x hf theorem DifferentiableWithinAt.rpow_const (hf : DifferentiableWithinAt ℝ f s x) (h : f x ≠ 0 ∨ 1 ≤ p) : DifferentiableWithinAt ℝ (fun x => f x ^ p) s x := (hf.hasFDerivWithinAt.rpow_const h).differentiableWithinAt @[simp] theorem DifferentiableAt.rpow_const (hf : DifferentiableAt ℝ f x) (h : f x ≠ 0 ∨ 1 ≤ p) : DifferentiableAt ℝ (fun x => f x ^ p) x := (hf.hasFDerivAt.rpow_const h).differentiableAt theorem DifferentiableOn.rpow_const (hf : DifferentiableOn ℝ f s) (h : ∀ x ∈ s, f x ≠ 0 ∨ 1 ≤ p) : DifferentiableOn ℝ (fun x => f x ^ p) s := fun x hx => (hf x hx).rpow_const (h x hx) theorem Differentiable.rpow_const (hf : Differentiable ℝ f) (h : ∀ x, f x ≠ 0 ∨ 1 ≤ p) : Differentiable ℝ fun x => f x ^ p := fun x => (hf x).rpow_const (h x) theorem HasFDerivWithinAt.const_rpow (hf : HasFDerivWithinAt f f' s x) (hc : 0 < c) : HasFDerivWithinAt (fun x => c ^ f x) ((c ^ f x * Real.log c) • f') s x := (hasStrictDerivAt_const_rpow hc (f x)).hasDerivAt.comp_hasFDerivWithinAt x hf theorem HasFDerivAt.const_rpow (hf : HasFDerivAt f f' x) (hc : 0 < c) : HasFDerivAt (fun x => c ^ f x) ((c ^ f x * Real.log c) • f') x := (hasStrictDerivAt_const_rpow hc (f x)).hasDerivAt.comp_hasFDerivAt x hf theorem HasStrictFDerivAt.const_rpow (hf : HasStrictFDerivAt f f' x) (hc : 0 < c) : HasStrictFDerivAt (fun x => c ^ f x) ((c ^ f x * Real.log c) • f') x := (hasStrictDerivAt_const_rpow hc (f x)).comp_hasStrictFDerivAt x hf #adaptation_note /-- https://github.com/leanprover/lean4/pull/6024 added `by exact` to deal with unification issues. -/ theorem ContDiffWithinAt.rpow (hf : ContDiffWithinAt ℝ n f s x) (hg : ContDiffWithinAt ℝ n g s x) (h : f x ≠ 0) : ContDiffWithinAt ℝ n (fun x => f x ^ g x) s x := by exact (contDiffAt_rpow_of_ne (f x, g x) h).comp_contDiffWithinAt x (hf.prodMk hg) #adaptation_note /-- https://github.com/leanprover/lean4/pull/6024 added `by exact` to deal with unification issues. -/ theorem ContDiffAt.rpow (hf : ContDiffAt ℝ n f x) (hg : ContDiffAt ℝ n g x) (h : f x ≠ 0) : ContDiffAt ℝ n (fun x => f x ^ g x) x := by exact (contDiffAt_rpow_of_ne (f x, g x) h).comp x (hf.prodMk hg) theorem ContDiffOn.rpow (hf : ContDiffOn ℝ n f s) (hg : ContDiffOn ℝ n g s) (h : ∀ x ∈ s, f x ≠ 0) : ContDiffOn ℝ n (fun x => f x ^ g x) s := fun x hx => (hf x hx).rpow (hg x hx) (h x hx) theorem ContDiff.rpow (hf : ContDiff ℝ n f) (hg : ContDiff ℝ n g) (h : ∀ x, f x ≠ 0) : ContDiff ℝ n fun x => f x ^ g x := contDiff_iff_contDiffAt.mpr fun x => hf.contDiffAt.rpow hg.contDiffAt (h x) theorem ContDiffWithinAt.rpow_const_of_ne (hf : ContDiffWithinAt ℝ n f s x) (h : f x ≠ 0) : ContDiffWithinAt ℝ n (fun x => f x ^ p) s x := hf.rpow contDiffWithinAt_const h theorem ContDiffAt.rpow_const_of_ne (hf : ContDiffAt ℝ n f x) (h : f x ≠ 0) : ContDiffAt ℝ n (fun x => f x ^ p) x := hf.rpow contDiffAt_const h theorem ContDiffOn.rpow_const_of_ne (hf : ContDiffOn ℝ n f s) (h : ∀ x ∈ s, f x ≠ 0) : ContDiffOn ℝ n (fun x => f x ^ p) s := fun x hx => (hf x hx).rpow_const_of_ne (h x hx) theorem ContDiff.rpow_const_of_ne (hf : ContDiff ℝ n f) (h : ∀ x, f x ≠ 0) : ContDiff ℝ n fun x => f x ^ p := hf.rpow contDiff_const h variable {m : ℕ} theorem ContDiffWithinAt.rpow_const_of_le (hf : ContDiffWithinAt ℝ m f s x) (h : ↑m ≤ p) : ContDiffWithinAt ℝ m (fun x => f x ^ p) s x := (contDiffAt_rpow_const_of_le h).comp_contDiffWithinAt x hf theorem ContDiffAt.rpow_const_of_le (hf : ContDiffAt ℝ m f x) (h : ↑m ≤ p) : ContDiffAt ℝ m (fun x => f x ^ p) x := by rw [← contDiffWithinAt_univ] at *; exact hf.rpow_const_of_le h theorem ContDiffOn.rpow_const_of_le (hf : ContDiffOn ℝ m f s) (h : ↑m ≤ p) : ContDiffOn ℝ m (fun x => f x ^ p) s := fun x hx => (hf x hx).rpow_const_of_le h theorem ContDiff.rpow_const_of_le (hf : ContDiff ℝ m f) (h : ↑m ≤ p) : ContDiff ℝ m fun x => f x ^ p := contDiff_iff_contDiffAt.mpr fun _ => hf.contDiffAt.rpow_const_of_le h end fderiv section deriv variable {f g : ℝ → ℝ} {f' g' x y p : ℝ} {s : Set ℝ} theorem HasDerivWithinAt.rpow (hf : HasDerivWithinAt f f' s x) (hg : HasDerivWithinAt g g' s x) (h : 0 < f x) : HasDerivWithinAt (fun x => f x ^ g x) (f' * g x * f x ^ (g x - 1) + g' * f x ^ g x * Real.log (f x)) s x := by convert (hf.hasFDerivWithinAt.rpow hg.hasFDerivWithinAt h).hasDerivWithinAt using 1 dsimp; ring theorem HasDerivAt.rpow (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) (h : 0 < f x) : HasDerivAt (fun x => f x ^ g x) (f' * g x * f x ^ (g x - 1) + g' * f x ^ g x * Real.log (f x)) x := by
rw [← hasDerivWithinAt_univ] at * exact hf.rpow hg h theorem HasDerivWithinAt.rpow_const (hf : HasDerivWithinAt f f' s x) (hx : f x ≠ 0 ∨ 1 ≤ p) :
Mathlib/Analysis/SpecialFunctions/Pow/Deriv.lean
599
602
/- 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.Data.List.Iterate import Mathlib.GroupTheory.Perm.Cycle.Basic import Mathlib.GroupTheory.NoncommPiCoprod import Mathlib.Tactic.Group /-! # Cycle factors of a permutation Let `β` be a `Fintype` and `f : Equiv.Perm β`. * `Equiv.Perm.cycleOf`: `f.cycleOf x` is the cycle of `f` that `x` belongs to. * `Equiv.Perm.cycleFactors`: `f.cycleFactors` is a list of disjoint cyclic permutations that multiply to `f`. -/ open Equiv Function Finset variable {ι α β : Type*} namespace Equiv.Perm /-! ### `cycleOf` -/ section CycleOf variable {f g : Perm α} {x y : α} /-- `f.cycleOf x` is the cycle of the permutation `f` to which `x` belongs. -/ def cycleOf (f : Perm α) [DecidableRel f.SameCycle] (x : α) : Perm α := ofSubtype (subtypePerm f fun _ => sameCycle_apply_right.symm : Perm { y // SameCycle f x y }) theorem cycleOf_apply (f : Perm α) [DecidableRel f.SameCycle] (x y : α) : cycleOf f x y = if SameCycle f x y then f y else y := by dsimp only [cycleOf] split_ifs with h · apply ofSubtype_apply_of_mem exact h · apply ofSubtype_apply_of_not_mem exact h theorem cycleOf_inv (f : Perm α) [DecidableRel f.SameCycle] (x : α) : (cycleOf f x)⁻¹ = cycleOf f⁻¹ x := Equiv.ext fun y => by rw [inv_eq_iff_eq, cycleOf_apply, cycleOf_apply] split_ifs <;> simp_all [sameCycle_inv, sameCycle_inv_apply_right] @[simp] theorem cycleOf_pow_apply_self (f : Perm α) [DecidableRel f.SameCycle] (x : α) : ∀ n : ℕ, (cycleOf f x ^ n) x = (f ^ n) x := by intro n induction n with | zero => rfl | succ n hn => rw [pow_succ', mul_apply, cycleOf_apply, hn, if_pos, pow_succ', mul_apply] exact ⟨n, rfl⟩ @[simp] theorem cycleOf_zpow_apply_self (f : Perm α) [DecidableRel f.SameCycle] (x : α) : ∀ n : ℤ, (cycleOf f x ^ n) x = (f ^ n) x := by intro z cases z with | ofNat z => exact cycleOf_pow_apply_self f x z | negSucc z => rw [zpow_negSucc, ← inv_pow, cycleOf_inv, zpow_negSucc, ← inv_pow, cycleOf_pow_apply_self] theorem SameCycle.cycleOf_apply [DecidableRel f.SameCycle] : SameCycle f x y → cycleOf f x y = f y := ofSubtype_apply_of_mem _ theorem cycleOf_apply_of_not_sameCycle [DecidableRel f.SameCycle] : ¬SameCycle f x y → cycleOf f x y = y := ofSubtype_apply_of_not_mem _ theorem SameCycle.cycleOf_eq [DecidableRel f.SameCycle] (h : SameCycle f x y) : cycleOf f x = cycleOf f y := by ext z rw [Equiv.Perm.cycleOf_apply] split_ifs with hz · exact (h.symm.trans hz).cycleOf_apply.symm · exact (cycleOf_apply_of_not_sameCycle (mt h.trans hz)).symm @[simp] theorem cycleOf_apply_apply_zpow_self (f : Perm α) [DecidableRel f.SameCycle] (x : α) (k : ℤ) : cycleOf f x ((f ^ k) x) = (f ^ (k + 1) : Perm α) x := by rw [SameCycle.cycleOf_apply] · rw [add_comm, zpow_add, zpow_one, mul_apply] · exact ⟨k, rfl⟩ @[simp] theorem cycleOf_apply_apply_pow_self (f : Perm α) [DecidableRel f.SameCycle] (x : α) (k : ℕ) : cycleOf f x ((f ^ k) x) = (f ^ (k + 1) : Perm α) x := by convert cycleOf_apply_apply_zpow_self f x k using 1 @[simp] theorem cycleOf_apply_apply_self (f : Perm α) [DecidableRel f.SameCycle] (x : α) : cycleOf f x (f x) = f (f x) := by convert cycleOf_apply_apply_pow_self f x 1 using 1 @[simp] theorem cycleOf_apply_self (f : Perm α) [DecidableRel f.SameCycle] (x : α) : cycleOf f x x = f x := SameCycle.rfl.cycleOf_apply theorem IsCycle.cycleOf_eq [DecidableRel f.SameCycle] (hf : IsCycle f) (hx : f x ≠ x) : cycleOf f x = f := Equiv.ext fun y => if h : SameCycle f x y then by rw [h.cycleOf_apply] else by rw [cycleOf_apply_of_not_sameCycle h, Classical.not_not.1 (mt ((isCycle_iff_sameCycle hx).1 hf).2 h)] @[simp] theorem cycleOf_eq_one_iff (f : Perm α) [DecidableRel f.SameCycle] : cycleOf f x = 1 ↔ f x = x := by simp_rw [Perm.ext_iff, cycleOf_apply, one_apply] refine ⟨fun h => (if_pos (SameCycle.refl f x)).symm.trans (h x), fun h y => ?_⟩ by_cases hy : f y = y · rw [hy, ite_self] · exact if_neg (mt SameCycle.apply_eq_self_iff (by tauto)) @[simp] theorem cycleOf_self_apply (f : Perm α) [DecidableRel f.SameCycle] (x : α) : cycleOf f (f x) = cycleOf f x := (sameCycle_apply_right.2 SameCycle.rfl).symm.cycleOf_eq @[simp] theorem cycleOf_self_apply_pow (f : Perm α) [DecidableRel f.SameCycle] (n : ℕ) (x : α) : cycleOf f ((f ^ n) x) = cycleOf f x := SameCycle.rfl.pow_left.cycleOf_eq @[simp] theorem cycleOf_self_apply_zpow (f : Perm α) [DecidableRel f.SameCycle] (n : ℤ) (x : α) : cycleOf f ((f ^ n) x) = cycleOf f x := SameCycle.rfl.zpow_left.cycleOf_eq protected theorem IsCycle.cycleOf [DecidableRel f.SameCycle] [DecidableEq α] (hf : IsCycle f) : cycleOf f x = if f x = x then 1 else f := by by_cases hx : f x = x · rwa [if_pos hx, cycleOf_eq_one_iff] · rwa [if_neg hx, hf.cycleOf_eq] theorem cycleOf_one [DecidableRel (1 : Perm α).SameCycle] (x : α) : cycleOf 1 x = 1 := (cycleOf_eq_one_iff 1).mpr rfl theorem isCycle_cycleOf (f : Perm α) [DecidableRel f.SameCycle] (hx : f x ≠ x) : IsCycle (cycleOf f x) := have : cycleOf f x x ≠ x := by rwa [SameCycle.rfl.cycleOf_apply] (isCycle_iff_sameCycle this).2 @fun y => ⟨fun h => mt h.apply_eq_self_iff.2 this, fun h => if hxy : SameCycle f x y then let ⟨i, hi⟩ := hxy ⟨i, by rw [cycleOf_zpow_apply_self, hi]⟩ else by rw [cycleOf_apply_of_not_sameCycle hxy] at h exact (h rfl).elim⟩ theorem pow_mod_orderOf_cycleOf_apply (f : Perm α) [DecidableRel f.SameCycle] (n : ℕ) (x : α) : (f ^ (n % orderOf (cycleOf f x))) x = (f ^ n) x := by rw [← cycleOf_pow_apply_self f, ← cycleOf_pow_apply_self f, pow_mod_orderOf] theorem cycleOf_mul_of_apply_right_eq_self [DecidableRel f.SameCycle] [DecidableRel (f * g).SameCycle] (h : Commute f g) (x : α) (hx : g x = x) : (f * g).cycleOf x = f.cycleOf x := by ext y by_cases hxy : (f * g).SameCycle x y · obtain ⟨z, rfl⟩ := hxy rw [cycleOf_apply_apply_zpow_self] simp [h.mul_zpow, zpow_apply_eq_self_of_apply_eq_self hx] · rw [cycleOf_apply_of_not_sameCycle hxy, cycleOf_apply_of_not_sameCycle] contrapose! hxy obtain ⟨z, rfl⟩ := hxy refine ⟨z, ?_⟩ simp [h.mul_zpow, zpow_apply_eq_self_of_apply_eq_self hx] theorem Disjoint.cycleOf_mul_distrib [DecidableRel f.SameCycle] [DecidableRel g.SameCycle] [DecidableRel (f * g).SameCycle] [DecidableRel (g * f).SameCycle] (h : f.Disjoint g) (x : α) : (f * g).cycleOf x = f.cycleOf x * g.cycleOf x := by rcases (disjoint_iff_eq_or_eq.mp h) x with hfx | hgx
· simp [h.commute.eq, cycleOf_mul_of_apply_right_eq_self h.symm.commute, hfx] · simp [cycleOf_mul_of_apply_right_eq_self h.commute, hgx] private theorem mem_support_cycleOf_iff_aux [DecidableRel f.SameCycle] [DecidableEq α] [Fintype α] : y ∈ support (f.cycleOf x) ↔ SameCycle f x y ∧ x ∈ support f := by by_cases hx : f x = x
Mathlib/GroupTheory/Perm/Cycle/Factors.lean
185
190
/- 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.Group.Nat.Defs import Mathlib.CategoryTheory.Category.Preorder import Mathlib.CategoryTheory.EqToHom import Mathlib.CategoryTheory.Functor.Const import Mathlib.Order.Fin.Basic import Mathlib.Tactic.FinCases import Mathlib.Tactic.SuppressCompilation /-! # Composable arrows If `C` is a category, the type of `n`-simplices in the nerve of `C` identifies to the type of functors `Fin (n + 1) ⥤ C`, which can be thought as families of `n` composable arrows in `C`. In this file, we introduce and study this category `ComposableArrows C n` of `n` composable arrows in `C`. If `F : ComposableArrows C n`, we define `F.left` as the leftmost object, `F.right` as the rightmost object, and `F.hom : F.left ⟶ F.right` is the canonical map. The most significant definition in this file is the constructor `F.precomp f : ComposableArrows C (n + 1)` for `F : ComposableArrows C n` and `f : X ⟶ F.left`: "it shifts `F` towards the right and inserts `f` on the left". This `precomp` has good definitional properties. In the namespace `CategoryTheory.ComposableArrows`, we provide constructors like `mk₁ f`, `mk₂ f g`, `mk₃ f g h` for `ComposableArrows C n` for small `n`. TODO (@joelriou): * redefine `Arrow C` as `ComposableArrow C 1`? * construct some elements in `ComposableArrows m (Fin (n + 1))` for small `n` the precomposition with which shall induce functors `ComposableArrows C n ⥤ ComposableArrows C m` which correspond to simplicial operations (specifically faces) with good definitional properties (this might be necessary for up to `n = 7` in order to formalize spectral sequences following Verdier) -/ /-! New `simprocs` that run even in `dsimp` have caused breakages in this file. (e.g. `dsimp` can now simplify `2 + 3` to `5`) For now, we just turn off simprocs in this file. We'll soon provide finer grained options here, e.g. to turn off simprocs only in `dsimp`, etc. *However*, hopefully it is possible to refactor the material here so that no backwards compatibility `set_option`s are required at all -/ set_option simprocs false namespace CategoryTheory open Category variable (C : Type*) [Category C] /-- `ComposableArrows C n` is the type of functors `Fin (n + 1) ⥤ C`. -/ abbrev ComposableArrows (n : ℕ) := Fin (n + 1) ⥤ C namespace ComposableArrows variable {C} {n m : ℕ} variable (F G : ComposableArrows C n) /-- A wrapper for `omega` which prefaces it with some quick and useful attempts -/ macro "valid" : tactic => `(tactic| first | assumption | apply zero_le | apply le_rfl | transitivity <;> assumption | omega) /-- The `i`th object (with `i : ℕ` such that `i ≤ n`) of `F : ComposableArrows C n`. -/ @[simp] abbrev obj' (i : ℕ) (hi : i ≤ n := by valid) : C := F.obj ⟨i, by omega⟩ /-- The map `F.obj' i ⟶ F.obj' j` when `F : ComposableArrows C n`, and `i` and `j` are natural numbers such that `i ≤ j ≤ n`. -/ @[simp] abbrev map' (i j : ℕ) (hij : i ≤ j := by valid) (hjn : j ≤ n := by valid) : F.obj ⟨i, by omega⟩ ⟶ F.obj ⟨j, by omega⟩ := F.map (homOfLE (by simp only [Fin.mk_le_mk] valid)) lemma map'_self (i : ℕ) (hi : i ≤ n := by valid) : F.map' i i = 𝟙 _ := F.map_id _ lemma map'_comp (i j k : ℕ) (hij : i ≤ j := by valid) (hjk : j ≤ k := by valid) (hk : k ≤ n := by valid) : F.map' i k = F.map' i j ≫ F.map' j k := F.map_comp _ _ /-- The leftmost object of `F : ComposableArrows C n`. -/ abbrev left := obj' F 0 /-- The rightmost object of `F : ComposableArrows C n`. -/ abbrev right := obj' F n /-- The canonical map `F.left ⟶ F.right` for `F : ComposableArrows C n`. -/ abbrev hom : F.left ⟶ F.right := map' F 0 n variable {F G} /-- The map `F.obj' i ⟶ G.obj' i` induced on `i`th objects by a morphism `F ⟶ G` in `ComposableArrows C n` when `i` is a natural number such that `i ≤ n`. -/ @[simp] abbrev app' (φ : F ⟶ G) (i : ℕ) (hi : i ≤ n := by valid) : F.obj' i ⟶ G.obj' i := φ.app _ @[reassoc] lemma naturality' (φ : F ⟶ G) (i j : ℕ) (hij : i ≤ j := by valid) (hj : j ≤ n := by valid) : F.map' i j ≫ app' φ j = app' φ i ≫ G.map' i j := φ.naturality _ /-- Constructor for `ComposableArrows C 0`. -/ @[simps!] def mk₀ (X : C) : ComposableArrows C 0 := (Functor.const (Fin 1)).obj X namespace Mk₁ variable (X₀ X₁ : C) /-- The map which sends `0 : Fin 2` to `X₀` and `1` to `X₁`. -/ @[simp] def obj : Fin 2 → C | ⟨0, _⟩ => X₀ | ⟨1, _⟩ => X₁ variable {X₀ X₁} variable (f : X₀ ⟶ X₁) /-- The obvious map `obj X₀ X₁ i ⟶ obj X₀ X₁ j` whenever `i j : Fin 2` satisfy `i ≤ j`. -/ @[simp] def map : ∀ (i j : Fin 2) (_ : i ≤ j), obj X₀ X₁ i ⟶ obj X₀ X₁ j | ⟨0, _⟩, ⟨0, _⟩, _ => 𝟙 _ | ⟨0, _⟩, ⟨1, _⟩, _ => f | ⟨1, _⟩, ⟨1, _⟩, _ => 𝟙 _ lemma map_id (i : Fin 2) : map f i i (by simp) = 𝟙 _ := match i with | 0 => rfl | 1 => rfl lemma map_comp {i j k : Fin 2} (hij : i ≤ j) (hjk : j ≤ k) : map f i k (hij.trans hjk) = map f i j hij ≫ map f j k hjk := by obtain rfl | rfl : i = j ∨ j = k := by omega · rw [map_id, id_comp] · rw [map_id, comp_id] end Mk₁ /-- Constructor for `ComposableArrows C 1`. -/ @[simps] def mk₁ {X₀ X₁ : C} (f : X₀ ⟶ X₁) : ComposableArrows C 1 where obj := Mk₁.obj X₀ X₁ map g := Mk₁.map f _ _ (leOfHom g) map_id := Mk₁.map_id f map_comp g g' := Mk₁.map_comp f (leOfHom g) (leOfHom g') /-- Constructor for morphisms `F ⟶ G` in `ComposableArrows C n` which takes as inputs a family of morphisms `F.obj i ⟶ G.obj i` and the naturality condition only for the maps in `Fin (n + 1)` given by inequalities of the form `i ≤ i + 1`. -/ @[simps] def homMk {F G : ComposableArrows C n} (app : ∀ i, F.obj i ⟶ G.obj i) (w : ∀ (i : ℕ) (hi : i < n), F.map' i (i + 1) ≫ app _ = app _ ≫ G.map' i (i + 1)) : F ⟶ G where app := app naturality := by suffices ∀ (k i j : ℕ) (hj : i + k = j) (hj' : j ≤ n), F.map' i j ≫ app _ = app _ ≫ G.map' i j by rintro ⟨i, hi⟩ ⟨j, hj⟩ hij have hij' := leOfHom hij simp only [Fin.mk_le_mk] at hij' obtain ⟨k, hk⟩ := Nat.le.dest hij' exact this k i j hk (by valid) intro k induction' k with k hk · intro i j hj hj' simp only [add_zero] at hj obtain rfl := hj rw [F.map'_self i, G.map'_self i, id_comp, comp_id] · intro i j hj hj' rw [← add_assoc] at hj subst hj rw [F.map'_comp i (i + k) (i + k + 1), G.map'_comp i (i + k) (i + k + 1), assoc, w (i + k) (by valid), reassoc_of% (hk i (i + k) rfl (by valid))] /-- Constructor for isomorphisms `F ≅ G` in `ComposableArrows C n` which takes as inputs a family of isomorphisms `F.obj i ≅ G.obj i` and the naturality condition only for the maps in `Fin (n + 1)` given by inequalities of the form `i ≤ i + 1`. -/ @[simps] def isoMk {F G : ComposableArrows C n} (app : ∀ i, F.obj i ≅ G.obj i) (w : ∀ (i : ℕ) (hi : i < n), F.map' i (i + 1) ≫ (app _).hom = (app _).hom ≫ G.map' i (i + 1)) : F ≅ G where hom := homMk (fun i => (app i).hom) w inv := homMk (fun i => (app i).inv) (fun i hi => by dsimp only rw [← cancel_epi ((app _).hom), ← reassoc_of% (w i hi), Iso.hom_inv_id, comp_id, Iso.hom_inv_id_assoc]) lemma ext {F G : ComposableArrows C n} (h : ∀ i, F.obj i = G.obj i) (w : ∀ (i : ℕ) (hi : i < n), F.map' i (i + 1) = eqToHom (h _) ≫ G.map' i (i + 1) ≫ eqToHom (h _).symm) : F = G := Functor.ext_of_iso (isoMk (fun i => eqToIso (h i)) (fun i hi => by simp [w i hi])) h (fun _ => rfl) /-- Constructor for morphisms in `ComposableArrows C 0`. -/ @[simps!] def homMk₀ {F G : ComposableArrows C 0} (f : F.obj' 0 ⟶ G.obj' 0) : F ⟶ G := homMk (fun i => match i with | ⟨0, _⟩ => f) (fun i hi => by simp at hi) @[ext] lemma hom_ext₀ {F G : ComposableArrows C 0} {φ φ' : F ⟶ G} (h : app' φ 0 = app' φ' 0) : φ = φ' := by ext i fin_cases i exact h /-- Constructor for isomorphisms in `ComposableArrows C 0`. -/ @[simps!] def isoMk₀ {F G : ComposableArrows C 0} (e : F.obj' 0 ≅ G.obj' 0) : F ≅ G where hom := homMk₀ e.hom inv := homMk₀ e.inv lemma ext₀ {F G : ComposableArrows C 0} (h : F.obj' 0 = G.obj 0) : F = G := ext (fun i => match i with | ⟨0, _⟩ => h) (fun i hi => by simp at hi) lemma mk₀_surjective (F : ComposableArrows C 0) : ∃ (X : C), F = mk₀ X := ⟨F.obj' 0, ext₀ rfl⟩ /-- Constructor for morphisms in `ComposableArrows C 1`. -/ @[simps!] def homMk₁ {F G : ComposableArrows C 1} (left : F.obj' 0 ⟶ G.obj' 0) (right : F.obj' 1 ⟶ G.obj' 1) (w : F.map' 0 1 ≫ right = left ≫ G.map' 0 1 := by aesop_cat) : F ⟶ G := homMk (fun i => match i with | ⟨0, _⟩ => left | ⟨1, _⟩ => right) (by intro i hi obtain rfl : i = 0 := by simpa using hi exact w) @[ext] lemma hom_ext₁ {F G : ComposableArrows C 1} {φ φ' : F ⟶ G} (h₀ : app' φ 0 = app' φ' 0) (h₁ : app' φ 1 = app' φ' 1) : φ = φ' := by ext i match i with | 0 => exact h₀ | 1 => exact h₁ /-- Constructor for isomorphisms in `ComposableArrows C 1`. -/ @[simps!] def isoMk₁ {F G : ComposableArrows C 1} (left : F.obj' 0 ≅ G.obj' 0) (right : F.obj' 1 ≅ G.obj' 1) (w : F.map' 0 1 ≫ right.hom = left.hom ≫ G.map' 0 1 := by aesop_cat) : F ≅ G where hom := homMk₁ left.hom right.hom w inv := homMk₁ left.inv right.inv (by rw [← cancel_mono right.hom, assoc, assoc, w, right.inv_hom_id, left.inv_hom_id_assoc] apply comp_id) lemma map'_eq_hom₁ (F : ComposableArrows C 1) : F.map' 0 1 = F.hom := rfl lemma ext₁ {F G : ComposableArrows C 1} (left : F.left = G.left) (right : F.right = G.right) (w : F.hom = eqToHom left ≫ G.hom ≫ eqToHom right.symm) : F = G := Functor.ext_of_iso (isoMk₁ (eqToIso left) (eqToIso right) (by simp [map'_eq_hom₁, w])) (fun i => by fin_cases i <;> assumption) (fun i => by fin_cases i <;> rfl) lemma mk₁_surjective (X : ComposableArrows C 1) : ∃ (X₀ X₁ : C) (f : X₀ ⟶ X₁), X = mk₁ f := ⟨_, _, X.map' 0 1, ext₁ rfl rfl (by simp)⟩ variable (F) namespace Precomp variable (X : C) /-- The map `Fin (n + 1 + 1) → C` which "shifts" `F.obj'` to the right and inserts `X` in the zeroth position. -/ def obj : Fin (n + 1 + 1) → C | ⟨0, _⟩ => X | ⟨i + 1, hi⟩ => F.obj' i @[simp] lemma obj_zero : obj F X 0 = X := rfl @[simp] lemma obj_one : obj F X 1 = F.obj' 0 := rfl @[simp] lemma obj_succ (i : ℕ) (hi : i + 1 < n + 1 + 1) : obj F X ⟨i + 1, hi⟩ = F.obj' i := rfl variable {X} (f : X ⟶ F.left) /-- Auxiliary definition for the action on maps of the functor `F.precomp f`. It sends `0 ≤ 1` to `f` and `i + 1 ≤ j + 1` to `F.map' i j`. -/ def map : ∀ (i j : Fin (n + 1 + 1)) (_ : i ≤ j), obj F X i ⟶ obj F X j | ⟨0, _⟩, ⟨0, _⟩, _ => 𝟙 X | ⟨0, _⟩, ⟨1, _⟩, _ => f | ⟨0, _⟩, ⟨j + 2, hj⟩, _ => f ≫ F.map' 0 (j + 1) | ⟨i + 1, hi⟩, ⟨j + 1, hj⟩, hij => F.map' i j (by simpa using hij) @[simp] lemma map_zero_zero : map F f 0 0 (by simp) = 𝟙 X := rfl @[simp] lemma map_one_one : map F f 1 1 (by simp) = F.map (𝟙 _) := rfl @[simp] lemma map_zero_one : map F f 0 1 (by simp) = f := rfl @[simp] lemma map_zero_one' : map F f 0 ⟨0 + 1, by simp⟩ (by simp) = f := rfl @[simp] lemma map_zero_succ_succ (j : ℕ) (hj : j + 2 < n + 1 + 1) : map F f 0 ⟨j + 2, hj⟩ (by simp) = f ≫ F.map' 0 (j+1) := rfl @[simp] lemma map_succ_succ (i j : ℕ) (hi : i + 1 < n + 1 + 1) (hj : j + 1 < n + 1 + 1) (hij : i + 1 ≤ j + 1) : map F f ⟨i + 1, hi⟩ ⟨j + 1, hj⟩ hij = F.map' i j := rfl @[simp] lemma map_one_succ (j : ℕ) (hj : j + 1 < n + 1 + 1) : map F f 1 ⟨j + 1, hj⟩ (by simp [Fin.le_def]) = F.map' 0 j := rfl lemma map_id (i : Fin (n + 1 + 1)) : map F f i i (by simp) = 𝟙 _ := by obtain ⟨_|_, hi⟩ := i <;> simp lemma map_comp {i j k : Fin (n + 1 + 1)} (hij : i ≤ j) (hjk : j ≤ k) : map F f i k (hij.trans hjk) = map F f i j hij ≫ map F f j k hjk := by obtain ⟨i, hi⟩ := i obtain ⟨j, hj⟩ := j obtain ⟨k, hk⟩ := k cases i · obtain _ | _ | j := j · dsimp rw [id_comp] · obtain _ | _ | k := k · simp [Nat.succ.injEq] at hjk · simp · rfl · obtain _ | _ | k := k · simp [Fin.ext_iff] at hjk · simp [Fin.le_def] at hjk omega · dsimp rw [assoc, ← F.map_comp, homOfLE_comp] · obtain _ | j := j · simp [Fin.ext_iff] at hij · obtain _ | k := k · simp [Fin.ext_iff] at hjk · dsimp rw [← F.map_comp, homOfLE_comp] end Precomp /-- "Precomposition" of `F : ComposableArrows C n` by a morphism `f : X ⟶ F.left`. -/ @[simps] def precomp {X : C} (f : X ⟶ F.left) : ComposableArrows C (n + 1) where obj := Precomp.obj F X map g := Precomp.map F f _ _ (leOfHom g) map_id := Precomp.map_id F f map_comp g g' := Precomp.map_comp F f (leOfHom g) (leOfHom g') /-- Constructor for `ComposableArrows C 2`. -/ @[simp] def mk₂ {X₀ X₁ X₂ : C} (f : X₀ ⟶ X₁) (g : X₁ ⟶ X₂) : ComposableArrows C 2 := (mk₁ g).precomp f /-- Constructor for `ComposableArrows C 3`. -/ @[simp] def mk₃ {X₀ X₁ X₂ X₃ : C} (f : X₀ ⟶ X₁) (g : X₁ ⟶ X₂) (h : X₂ ⟶ X₃) : ComposableArrows C 3 := (mk₂ g h).precomp f /-- Constructor for `ComposableArrows C 4`. -/ @[simp] def mk₄ {X₀ X₁ X₂ X₃ X₄ : C} (f : X₀ ⟶ X₁) (g : X₁ ⟶ X₂) (h : X₂ ⟶ X₃) (i : X₃ ⟶ X₄) : ComposableArrows C 4 := (mk₃ g h i).precomp f /-- Constructor for `ComposableArrows C 5`. -/ @[simp] def mk₅ {X₀ X₁ X₂ X₃ X₄ X₅ : C} (f : X₀ ⟶ X₁) (g : X₁ ⟶ X₂) (h : X₂ ⟶ X₃) (i : X₃ ⟶ X₄) (j : X₄ ⟶ X₅) : ComposableArrows C 5 := (mk₄ g h i j).precomp f section variable {X₀ X₁ X₂ X₃ X₄ : C} (f : X₀ ⟶ X₁) (g : X₁ ⟶ X₂) (h : X₂ ⟶ X₃) (i : X₃ ⟶ X₄) /-! These examples are meant to test the good definitional properties of `precomp`, and that `dsimp` can see through. -/ example : map' (mk₂ f g) 0 1 = f := by dsimp example : map' (mk₂ f g) 1 2 = g := by dsimp example : map' (mk₂ f g) 0 2 = f ≫ g := by dsimp example : (mk₂ f g).hom = f ≫ g := by dsimp example : map' (mk₂ f g) 0 0 = 𝟙 _ := by dsimp example : map' (mk₂ f g) 1 1 = 𝟙 _ := by dsimp example : map' (mk₂ f g) 2 2 = 𝟙 _ := by dsimp example : map' (mk₃ f g h) 0 1 = f := by dsimp example : map' (mk₃ f g h) 1 2 = g := by dsimp example : map' (mk₃ f g h) 2 3 = h := by dsimp example : map' (mk₃ f g h) 0 3 = f ≫ g ≫ h := by dsimp example : (mk₃ f g h).hom = f ≫ g ≫ h := by dsimp example : map' (mk₃ f g h) 0 2 = f ≫ g := by dsimp example : map' (mk₃ f g h) 1 3 = g ≫ h := by dsimp end /-- The map `ComposableArrows C m → ComposableArrows C n` obtained by precomposition with a functor `Fin (n + 1) ⥤ Fin (m + 1)`. -/ @[simps!] def whiskerLeft (F : ComposableArrows C m) (Φ : Fin (n + 1) ⥤ Fin (m + 1)) : ComposableArrows C n := Φ ⋙ F /-- The functor `ComposableArrows C m ⥤ ComposableArrows C n` obtained by precomposition with a functor `Fin (n + 1) ⥤ Fin (m + 1)`. -/ @[simps!] def whiskerLeftFunctor (Φ : Fin (n + 1) ⥤ Fin (m + 1)) : ComposableArrows C m ⥤ ComposableArrows C n where obj F := F.whiskerLeft Φ map f := CategoryTheory.whiskerLeft Φ f /-- The functor `Fin n ⥤ Fin (n + 1)` which sends `i` to `i.succ`. -/ @[simps] def _root_.Fin.succFunctor (n : ℕ) : Fin n ⥤ Fin (n + 1) where obj i := i.succ map {_ _} hij := homOfLE (Fin.succ_le_succ_iff.2 (leOfHom hij)) /-- The functor `ComposableArrows C (n + 1) ⥤ ComposableArrows C n` which forgets the first arrow. -/ @[simps!] def δ₀Functor : ComposableArrows C (n + 1) ⥤ ComposableArrows C n := whiskerLeftFunctor (Fin.succFunctor (n + 1)) /-- The `ComposableArrows C n` obtained by forgetting the first arrow. -/ abbrev δ₀ (F : ComposableArrows C (n + 1)) := δ₀Functor.obj F @[simp] lemma precomp_δ₀ {X : C} (f : X ⟶ F.left) : (F.precomp f).δ₀ = F := rfl /-- The functor `Fin n ⥤ Fin (n + 1)` which sends `i` to `i.castSucc`. -/ @[simps] def _root_.Fin.castSuccFunctor (n : ℕ) : Fin n ⥤ Fin (n + 1) where obj i := i.castSucc map hij := hij /-- The functor `ComposableArrows C (n + 1) ⥤ ComposableArrows C n` which forgets the last arrow. -/ @[simps!] def δlastFunctor : ComposableArrows C (n + 1) ⥤ ComposableArrows C n := whiskerLeftFunctor (Fin.castSuccFunctor (n + 1)) /-- The `ComposableArrows C n` obtained by forgetting the first arrow. -/ abbrev δlast (F : ComposableArrows C (n + 1)) := δlastFunctor.obj F section variable {F G : ComposableArrows C (n + 1)} /-- Inductive construction of morphisms in `ComposableArrows C (n + 1)`: in order to construct a morphism `F ⟶ G`, it suffices to provide `α : F.obj' 0 ⟶ G.obj' 0` and `β : F.δ₀ ⟶ G.δ₀` such that `F.map' 0 1 ≫ app' β 0 = α ≫ G.map' 0 1`. -/ def homMkSucc (α : F.obj' 0 ⟶ G.obj' 0) (β : F.δ₀ ⟶ G.δ₀) (w : F.map' 0 1 ≫ app' β 0 = α ≫ G.map' 0 1) : F ⟶ G := homMk (fun i => match i with | ⟨0, _⟩ => α | ⟨i + 1, hi⟩ => app' β i) (fun i hi => by obtain _ | i := i · exact w · exact naturality' β i (i + 1)) variable (α : F.obj' 0 ⟶ G.obj' 0) (β : F.δ₀ ⟶ G.δ₀) (w : F.map' 0 1 ≫ app' β 0 = α ≫ G.map' 0 1) @[simp] lemma homMkSucc_app_zero : (homMkSucc α β w).app 0 = α := rfl @[simp] lemma homMkSucc_app_succ (i : ℕ) (hi : i + 1 < n + 1 + 1) : (homMkSucc α β w).app ⟨i + 1, hi⟩ = app' β i := rfl end lemma hom_ext_succ {F G : ComposableArrows C (n + 1)} {f g : F ⟶ G} (h₀ : app' f 0 = app' g 0) (h₁ : δ₀Functor.map f = δ₀Functor.map g) : f = g := by ext ⟨i, hi⟩ obtain _ | i := i · exact h₀ · exact congr_app h₁ ⟨i, by valid⟩ /-- Inductive construction of isomorphisms in `ComposableArrows C (n + 1)`: in order to construct an isomorphism `F ≅ G`, it suffices to provide `α : F.obj' 0 ≅ G.obj' 0` and `β : F.δ₀ ≅ G.δ₀` such that `F.map' 0 1 ≫ app' β.hom 0 = α.hom ≫ G.map' 0 1`. -/ @[simps] def isoMkSucc {F G : ComposableArrows C (n + 1)} (α : F.obj' 0 ≅ G.obj' 0) (β : F.δ₀ ≅ G.δ₀) (w : F.map' 0 1 ≫ app' β.hom 0 = α.hom ≫ G.map' 0 1) : F ≅ G where hom := homMkSucc α.hom β.hom w inv := homMkSucc α.inv β.inv (by rw [← cancel_epi α.hom, ← reassoc_of% w, α.hom_inv_id_assoc, β.hom_inv_id_app] dsimp rw [comp_id]) hom_inv_id := by apply hom_ext_succ · simp · ext ⟨i, hi⟩ simp inv_hom_id := by apply hom_ext_succ · simp · ext ⟨i, hi⟩ simp lemma ext_succ {F G : ComposableArrows C (n + 1)} (h₀ : F.obj' 0 = G.obj' 0) (h : F.δ₀ = G.δ₀) (w : F.map' 0 1 = eqToHom h₀ ≫ G.map' 0 1 ≫ eqToHom (Functor.congr_obj h.symm 0)) : F = G := by have : ∀ i, F.obj i = G.obj i := by intro ⟨i, hi⟩ rcases i with - | i · exact h₀ · exact Functor.congr_obj h ⟨i, by valid⟩ exact Functor.ext_of_iso (isoMkSucc (eqToIso h₀) (eqToIso h) (by rw [w] dsimp [app'] rw [eqToHom_app, assoc, assoc, eqToHom_trans, eqToHom_refl, comp_id])) this (by rintro ⟨_|_, hi⟩ <;> simp) lemma precomp_surjective (F : ComposableArrows C (n + 1)) : ∃ (F₀ : ComposableArrows C n) (X₀ : C) (f₀ : X₀ ⟶ F₀.left), F = F₀.precomp f₀ := ⟨F.δ₀, _, F.map' 0 1, ext_succ rfl (by simp) (by simp)⟩ section variable {f g : ComposableArrows C 2} (app₀ : f.obj' 0 ⟶ g.obj' 0) (app₁ : f.obj' 1 ⟶ g.obj' 1) (app₂ : f.obj' 2 ⟶ g.obj' 2) (w₀ : f.map' 0 1 ≫ app₁ = app₀ ≫ g.map' 0 1) (w₁ : f.map' 1 2 ≫ app₂ = app₁ ≫ g.map' 1 2) /-- Constructor for morphisms in `ComposableArrows C 2`. -/ def homMk₂ : f ⟶ g := homMkSucc app₀ (homMk₁ app₁ app₂ w₁) w₀ @[simp] lemma homMk₂_app_zero : (homMk₂ app₀ app₁ app₂ w₀ w₁).app 0 = app₀ := rfl @[simp] lemma homMk₂_app_one : (homMk₂ app₀ app₁ app₂ w₀ w₁).app 1 = app₁ := rfl @[simp] lemma homMk₂_app_two : (homMk₂ app₀ app₁ app₂ w₀ w₁).app ⟨2, by valid⟩ = app₂ := rfl end @[ext] lemma hom_ext₂ {f g : ComposableArrows C 2} {φ φ' : f ⟶ g} (h₀ : app' φ 0 = app' φ' 0) (h₁ : app' φ 1 = app' φ' 1) (h₂ : app' φ 2 = app' φ' 2) : φ = φ' := hom_ext_succ h₀ (hom_ext₁ h₁ h₂) /-- Constructor for isomorphisms in `ComposableArrows C 2`. -/ @[simps] def isoMk₂ {f g : ComposableArrows C 2} (app₀ : f.obj' 0 ≅ g.obj' 0) (app₁ : f.obj' 1 ≅ g.obj' 1) (app₂ : f.obj' 2 ≅ g.obj' 2) (w₀ : f.map' 0 1 ≫ app₁.hom = app₀.hom ≫ g.map' 0 1) (w₁ : f.map' 1 2 ≫ app₂.hom = app₁.hom ≫ g.map' 1 2) : f ≅ g where hom := homMk₂ app₀.hom app₁.hom app₂.hom w₀ w₁ inv := homMk₂ app₀.inv app₁.inv app₂.inv (by rw [← cancel_epi app₀.hom, ← reassoc_of% w₀, app₁.hom_inv_id, comp_id, app₀.hom_inv_id_assoc]) (by rw [← cancel_epi app₁.hom, ← reassoc_of% w₁, app₂.hom_inv_id, comp_id, app₁.hom_inv_id_assoc]) lemma ext₂ {f g : ComposableArrows C 2} (h₀ : f.obj' 0 = g.obj' 0) (h₁ : f.obj' 1 = g.obj' 1) (h₂ : f.obj' 2 = g.obj' 2) (w₀ : f.map' 0 1 = eqToHom h₀ ≫ g.map' 0 1 ≫ eqToHom h₁.symm) (w₁ : f.map' 1 2 = eqToHom h₁ ≫ g.map' 1 2 ≫ eqToHom h₂.symm) : f = g := ext_succ h₀ (ext₁ h₁ h₂ w₁) w₀ lemma mk₂_surjective (X : ComposableArrows C 2) : ∃ (X₀ X₁ X₂ : C) (f₀ : X₀ ⟶ X₁) (f₁ : X₁ ⟶ X₂), X = mk₂ f₀ f₁ := ⟨_, _, _, X.map' 0 1, X.map' 1 2, ext₂ rfl rfl rfl (by simp) (by simp)⟩ section variable {f g : ComposableArrows C 3} (app₀ : f.obj' 0 ⟶ g.obj' 0) (app₁ : f.obj' 1 ⟶ g.obj' 1) (app₂ : f.obj' 2 ⟶ g.obj' 2) (app₃ : f.obj' 3 ⟶ g.obj' 3) (w₀ : f.map' 0 1 ≫ app₁ = app₀ ≫ g.map' 0 1) (w₁ : f.map' 1 2 ≫ app₂ = app₁ ≫ g.map' 1 2) (w₂ : f.map' 2 3 ≫ app₃ = app₂ ≫ g.map' 2 3) /-- Constructor for morphisms in `ComposableArrows C 3`. -/ def homMk₃ : f ⟶ g := homMkSucc app₀ (homMk₂ app₁ app₂ app₃ w₁ w₂) w₀ @[simp] lemma homMk₃_app_zero : (homMk₃ app₀ app₁ app₂ app₃ w₀ w₁ w₂).app 0 = app₀ := rfl @[simp] lemma homMk₃_app_one : (homMk₃ app₀ app₁ app₂ app₃ w₀ w₁ w₂).app 1 = app₁ := rfl @[simp] lemma homMk₃_app_two : (homMk₃ app₀ app₁ app₂ app₃ w₀ w₁ w₂).app ⟨2, by valid⟩ = app₂ := rfl @[simp] lemma homMk₃_app_three : (homMk₃ app₀ app₁ app₂ app₃ w₀ w₁ w₂).app ⟨3, by valid⟩ = app₃ := rfl end @[ext] lemma hom_ext₃ {f g : ComposableArrows C 3} {φ φ' : f ⟶ g} (h₀ : app' φ 0 = app' φ' 0) (h₁ : app' φ 1 = app' φ' 1) (h₂ : app' φ 2 = app' φ' 2) (h₃ : app' φ 3 = app' φ' 3) : φ = φ' := hom_ext_succ h₀ (hom_ext₂ h₁ h₂ h₃) /-- Constructor for isomorphisms in `ComposableArrows C 3`. -/ @[simps] def isoMk₃ {f g : ComposableArrows C 3} (app₀ : f.obj' 0 ≅ g.obj' 0) (app₁ : f.obj' 1 ≅ g.obj' 1) (app₂ : f.obj' 2 ≅ g.obj' 2) (app₃ : f.obj' 3 ≅ g.obj' 3) (w₀ : f.map' 0 1 ≫ app₁.hom = app₀.hom ≫ g.map' 0 1) (w₁ : f.map' 1 2 ≫ app₂.hom = app₁.hom ≫ g.map' 1 2) (w₂ : f.map' 2 3 ≫ app₃.hom = app₂.hom ≫ g.map' 2 3) : f ≅ g where hom := homMk₃ app₀.hom app₁.hom app₂.hom app₃.hom w₀ w₁ w₂ inv := homMk₃ app₀.inv app₁.inv app₂.inv app₃.inv (by rw [← cancel_epi app₀.hom, ← reassoc_of% w₀, app₁.hom_inv_id, comp_id, app₀.hom_inv_id_assoc]) (by rw [← cancel_epi app₁.hom, ← reassoc_of% w₁, app₂.hom_inv_id, comp_id, app₁.hom_inv_id_assoc]) (by rw [← cancel_epi app₂.hom, ← reassoc_of% w₂, app₃.hom_inv_id, comp_id, app₂.hom_inv_id_assoc]) lemma ext₃ {f g : ComposableArrows C 3} (h₀ : f.obj' 0 = g.obj' 0) (h₁ : f.obj' 1 = g.obj' 1) (h₂ : f.obj' 2 = g.obj' 2) (h₃ : f.obj' 3 = g.obj' 3) (w₀ : f.map' 0 1 = eqToHom h₀ ≫ g.map' 0 1 ≫ eqToHom h₁.symm) (w₁ : f.map' 1 2 = eqToHom h₁ ≫ g.map' 1 2 ≫ eqToHom h₂.symm) (w₂ : f.map' 2 3 = eqToHom h₂ ≫ g.map' 2 3 ≫ eqToHom h₃.symm) : f = g := ext_succ h₀ (ext₂ h₁ h₂ h₃ w₁ w₂) w₀ lemma mk₃_surjective (X : ComposableArrows C 3) : ∃ (X₀ X₁ X₂ X₃ : C) (f₀ : X₀ ⟶ X₁) (f₁ : X₁ ⟶ X₂) (f₂ : X₂ ⟶ X₃), X = mk₃ f₀ f₁ f₂ := ⟨_, _, _, _, X.map' 0 1, X.map' 1 2, X.map' 2 3, ext₃ rfl rfl rfl rfl (by simp) (by simp) (by simp)⟩ section variable {f g : ComposableArrows C 4} (app₀ : f.obj' 0 ⟶ g.obj' 0) (app₁ : f.obj' 1 ⟶ g.obj' 1) (app₂ : f.obj' 2 ⟶ g.obj' 2) (app₃ : f.obj' 3 ⟶ g.obj' 3) (app₄ : f.obj' 4 ⟶ g.obj' 4) (w₀ : f.map' 0 1 ≫ app₁ = app₀ ≫ g.map' 0 1)
(w₁ : f.map' 1 2 ≫ app₂ = app₁ ≫ g.map' 1 2) (w₂ : f.map' 2 3 ≫ app₃ = app₂ ≫ g.map' 2 3) (w₃ : f.map' 3 4 ≫ app₄ = app₃ ≫ g.map' 3 4)
Mathlib/CategoryTheory/ComposableArrows.lean
674
677
/- Copyright (c) 2022 Zhouhang Zhou. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Zhouhang Zhou, Yury Kudryashov, Heather Macbeth -/ import Mathlib.MeasureTheory.Function.L1Space.AEEqFun import Mathlib.MeasureTheory.Function.LpSpace.Complete import Mathlib.MeasureTheory.Function.LpSpace.Indicator /-! # Density of simple functions Show that each `Lᵖ` Borel measurable function can be approximated in `Lᵖ` norm by a sequence of simple functions. ## Main definitions * `MeasureTheory.Lp.simpleFunc`, the type of `Lp` simple functions * `coeToLp`, the embedding of `Lp.simpleFunc E p μ` into `Lp E p μ` ## Main results * `tendsto_approxOn_Lp_eLpNorm` (Lᵖ convergence): If `E` is a `NormedAddCommGroup` and `f` is measurable and `MemLp` (for `p < ∞`), then the simple functions `SimpleFunc.approxOn f hf s 0 h₀ n` may be considered as elements of `Lp E p μ`, and they tend in Lᵖ to `f`. * `Lp.simpleFunc.isDenseEmbedding`: the embedding `coeToLp` of the `Lp` simple functions into `Lp` is dense. * `Lp.simpleFunc.induction`, `Lp.induction`, `MemLp.induction`, `Integrable.induction`: to prove a predicate for all elements of one of these classes of functions, it suffices to check that it behaves correctly on simple functions. ## TODO For `E` finite-dimensional, simple functions `α →ₛ E` are dense in L^∞ -- prove this. ## Notations * `α →ₛ β` (local notation): the type of simple functions `α → β`. * `α →₁ₛ[μ] E`: the type of `L1` simple functions `α → β`. -/ noncomputable section open Set Function Filter TopologicalSpace ENNReal EMetric Finset open scoped Topology ENNReal MeasureTheory variable {α β ι E F 𝕜 : Type*} namespace MeasureTheory local infixr:25 " →ₛ " => SimpleFunc namespace SimpleFunc /-! ### Lp approximation by simple functions -/ section Lp variable [MeasurableSpace β] [MeasurableSpace E] [NormedAddCommGroup E] [NormedAddCommGroup F] {q : ℝ} {p : ℝ≥0∞} theorem nnnorm_approxOn_le [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (x : β) (n : ℕ) : ‖approxOn f hf s y₀ h₀ n x - f x‖₊ ≤ ‖f x - y₀‖₊ := by have := edist_approxOn_le hf h₀ x n rw [edist_comm y₀] at this simp only [edist_nndist, nndist_eq_nnnorm] at this exact mod_cast this theorem norm_approxOn_y₀_le [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (x : β) (n : ℕ) : ‖approxOn f hf s y₀ h₀ n x - y₀‖ ≤ ‖f x - y₀‖ + ‖f x - y₀‖ := by simpa [enorm, edist_eq_enorm_sub, ← ENNReal.coe_add, norm_sub_rev] using edist_approxOn_y0_le hf h₀ x n theorem norm_approxOn_zero_le [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} (h₀ : (0 : E) ∈ s) [SeparableSpace s] (x : β) (n : ℕ) : ‖approxOn f hf s 0 h₀ n x‖ ≤ ‖f x‖ + ‖f x‖ := by simpa [enorm, edist_eq_enorm_sub, ← ENNReal.coe_add, norm_sub_rev] using edist_approxOn_y0_le hf h₀ x n theorem tendsto_approxOn_Lp_eLpNorm [OpensMeasurableSpace E] {f : β → E} (hf : Measurable f) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (hp_ne_top : p ≠ ∞) {μ : Measure β} (hμ : ∀ᵐ x ∂μ, f x ∈ closure s) (hi : eLpNorm (fun x => f x - y₀) p μ < ∞) : Tendsto (fun n => eLpNorm (⇑(approxOn f hf s y₀ h₀ n) - f) p μ) atTop (𝓝 0) := by by_cases hp_zero : p = 0 · simpa only [hp_zero, eLpNorm_exponent_zero] using tendsto_const_nhds have hp : 0 < p.toReal := toReal_pos hp_zero hp_ne_top suffices Tendsto (fun n => ∫⁻ x, ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ^ p.toReal ∂μ) atTop (𝓝 0) by simp only [eLpNorm_eq_lintegral_rpow_enorm hp_zero hp_ne_top] convert continuous_rpow_const.continuousAt.tendsto.comp this simp [zero_rpow_of_pos (_root_.inv_pos.mpr hp)] -- We simply check the conditions of the Dominated Convergence Theorem: -- (1) The function "`p`-th power of distance between `f` and the approximation" is measurable have hF_meas n : Measurable fun x => ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ^ p.toReal := by simpa only [← edist_eq_enorm_sub] using (approxOn f hf s y₀ h₀ n).measurable_bind (fun y x => edist y (f x) ^ p.toReal) fun y => (measurable_edist_right.comp hf).pow_const p.toReal -- (2) The functions "`p`-th power of distance between `f` and the approximation" are uniformly -- bounded, at any given point, by `fun x => ‖f x - y₀‖ ^ p.toReal` have h_bound n : (fun x ↦ ‖approxOn f hf s y₀ h₀ n x - f x‖ₑ ^ p.toReal) ≤ᵐ[μ] (‖f · - y₀‖ₑ ^ p.toReal) := .of_forall fun x => rpow_le_rpow (coe_mono (nnnorm_approxOn_le hf h₀ x n)) toReal_nonneg -- (3) The bounding function `fun x => ‖f x - y₀‖ ^ p.toReal` has finite integral have h_fin : (∫⁻ a : β, ‖f a - y₀‖ₑ ^ p.toReal ∂μ) ≠ ⊤ := (lintegral_rpow_enorm_lt_top_of_eLpNorm_lt_top hp_zero hp_ne_top hi).ne -- (4) The functions "`p`-th power of distance between `f` and the approximation" tend pointwise -- to zero have h_lim : ∀ᵐ a : β ∂μ, Tendsto (‖approxOn f hf s y₀ h₀ · a - f a‖ₑ ^ p.toReal) atTop (𝓝 0) := by filter_upwards [hμ] with a ha have : Tendsto (fun n => (approxOn f hf s y₀ h₀ n) a - f a) atTop (𝓝 (f a - f a)) := (tendsto_approxOn hf h₀ ha).sub tendsto_const_nhds convert continuous_rpow_const.continuousAt.tendsto.comp (tendsto_coe.mpr this.nnnorm) simp [zero_rpow_of_pos hp] -- Then we apply the Dominated Convergence Theorem simpa using tendsto_lintegral_of_dominated_convergence _ hF_meas h_bound h_fin h_lim theorem memLp_approxOn [BorelSpace E] {f : β → E} {μ : Measure β} (fmeas : Measurable f) (hf : MemLp f p μ) {s : Set E} {y₀ : E} (h₀ : y₀ ∈ s) [SeparableSpace s] (hi₀ : MemLp (fun _ => y₀) p μ) (n : ℕ) : MemLp (approxOn f fmeas s y₀ h₀ n) p μ := by refine ⟨(approxOn f fmeas s y₀ h₀ n).aestronglyMeasurable, ?_⟩ suffices eLpNorm (fun x => approxOn f fmeas s y₀ h₀ n x - y₀) p μ < ⊤ by have : MemLp (fun x => approxOn f fmeas s y₀ h₀ n x - y₀) p μ := ⟨(approxOn f fmeas s y₀ h₀ n - const β y₀).aestronglyMeasurable, this⟩ convert eLpNorm_add_lt_top this hi₀ ext x simp have hf' : MemLp (fun x => ‖f x - y₀‖) p μ := by have h_meas : Measurable fun x => ‖f x - y₀‖ := by simp only [← dist_eq_norm] exact (continuous_id.dist continuous_const).measurable.comp fmeas refine ⟨h_meas.aemeasurable.aestronglyMeasurable, ?_⟩ rw [eLpNorm_norm] convert eLpNorm_add_lt_top hf hi₀.neg with x simp [sub_eq_add_neg] have : ∀ᵐ x ∂μ, ‖approxOn f fmeas s y₀ h₀ n x - y₀‖ ≤ ‖‖f x - y₀‖ + ‖f x - y₀‖‖ := by filter_upwards with x convert norm_approxOn_y₀_le fmeas h₀ x n using 1 rw [Real.norm_eq_abs, abs_of_nonneg] positivity calc eLpNorm (fun x => approxOn f fmeas s y₀ h₀ n x - y₀) p μ ≤ eLpNorm (fun x => ‖f x - y₀‖ + ‖f x - y₀‖) p μ := eLpNorm_mono_ae this _ < ⊤ := eLpNorm_add_lt_top hf' hf' theorem tendsto_approxOn_range_Lp_eLpNorm [BorelSpace E] {f : β → E} (hp_ne_top : p ≠ ∞) {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : eLpNorm f p μ < ∞) : Tendsto (fun n => eLpNorm (⇑(approxOn f fmeas (range f ∪ {0}) 0 (by simp) n) - f) p μ) atTop (𝓝 0) := by refine tendsto_approxOn_Lp_eLpNorm fmeas _ hp_ne_top ?_ ?_ · filter_upwards with x using subset_closure (by simp) · simpa using hf theorem memLp_approxOn_range [BorelSpace E] {f : β → E} {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : MemLp f p μ) (n : ℕ) : MemLp (approxOn f fmeas (range f ∪ {0}) 0 (by simp) n) p μ := memLp_approxOn fmeas hf (y₀ := 0) (by simp) MemLp.zero n theorem tendsto_approxOn_range_Lp [BorelSpace E] {f : β → E} [hp : Fact (1 ≤ p)] (hp_ne_top : p ≠ ∞) {μ : Measure β} (fmeas : Measurable f) [SeparableSpace (range f ∪ {0} : Set E)] (hf : MemLp f p μ) : Tendsto (fun n => (memLp_approxOn_range fmeas hf n).toLp (approxOn f fmeas (range f ∪ {0}) 0 (by simp) n)) atTop (𝓝 (hf.toLp f)) := by simpa only [Lp.tendsto_Lp_iff_tendsto_eLpNorm''] using tendsto_approxOn_range_Lp_eLpNorm hp_ne_top fmeas hf.2 /-- Any function in `ℒp` can be approximated by a simple function if `p < ∞`. -/ theorem _root_.MeasureTheory.MemLp.exists_simpleFunc_eLpNorm_sub_lt {E : Type*} [NormedAddCommGroup E] {f : β → E} {μ : Measure β} (hf : MemLp f p μ) (hp_ne_top : p ≠ ∞) {ε : ℝ≥0∞} (hε : ε ≠ 0) : ∃ g : β →ₛ E, eLpNorm (f - ⇑g) p μ < ε ∧ MemLp g p μ := by borelize E let f' := hf.1.mk f rsuffices ⟨g, hg, g_mem⟩ : ∃ g : β →ₛ E, eLpNorm (f' - ⇑g) p μ < ε ∧ MemLp g p μ · refine ⟨g, ?_, g_mem⟩
suffices eLpNorm (f - ⇑g) p μ = eLpNorm (f' - ⇑g) p μ by rwa [this] apply eLpNorm_congr_ae filter_upwards [hf.1.ae_eq_mk] with x hx simpa only [Pi.sub_apply, sub_left_inj] using hx have hf' : MemLp f' p μ := hf.ae_eq hf.1.ae_eq_mk have f'meas : Measurable f' := hf.1.measurable_mk have : SeparableSpace (range f' ∪ {0} : Set E) := StronglyMeasurable.separableSpace_range_union_singleton hf.1.stronglyMeasurable_mk rcases ((tendsto_approxOn_range_Lp_eLpNorm hp_ne_top f'meas hf'.2).eventually <|
Mathlib/MeasureTheory/Function/SimpleFuncDenseLp.lean
184
192
/- 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]
Mathlib/Algebra/Order/ToIntervalMod.lean
534
535
/- Copyright (c) 2020 Damiano Testa. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Damiano Testa -/ import Mathlib.Algebra.Polynomial.Degree.TrailingDegree import Mathlib.Algebra.Polynomial.EraseLead /-! # Reverse of a univariate polynomial The main definition is `reverse`. Applying `reverse` to a polynomial `f : R[X]` produces the polynomial with a reversed list of coefficients, equivalent to `X^f.natDegree * f(1/X)`. The main result is that `reverse (f * g) = reverse f * reverse g`, provided the leading coefficients of `f` and `g` do not multiply to zero. -/ namespace Polynomial open Finsupp Finset open scoped Polynomial section Semiring variable {R : Type*} [Semiring R] {f : R[X]} /-- If `i ≤ N`, then `revAtFun N i` returns `N - i`, otherwise it returns `i`. This is the map used by the embedding `revAt`. -/ def revAtFun (N i : ℕ) : ℕ := ite (i ≤ N) (N - i) i theorem revAtFun_invol {N i : ℕ} : revAtFun N (revAtFun N i) = i := by unfold revAtFun split_ifs with h j · exact tsub_tsub_cancel_of_le h · exfalso apply j exact Nat.sub_le N i · rfl theorem revAtFun_inj {N : ℕ} : Function.Injective (revAtFun N) := by intro a b hab rw [← @revAtFun_invol N a, hab, revAtFun_invol] /-- If `i ≤ N`, then `revAt N i` returns `N - i`, otherwise it returns `i`. Essentially, this embedding is only used for `i ≤ N`. The advantage of `revAt N i` over `N - i` is that `revAt` is an involution. -/ def revAt (N : ℕ) : Function.Embedding ℕ ℕ where toFun i := ite (i ≤ N) (N - i) i inj' := revAtFun_inj /-- We prefer to use the bundled `revAt` over unbundled `revAtFun`. -/ @[simp] theorem revAtFun_eq (N i : ℕ) : revAtFun N i = revAt N i := rfl @[simp] theorem revAt_invol {N i : ℕ} : (revAt N) (revAt N i) = i := revAtFun_invol @[simp] theorem revAt_le {N i : ℕ} (H : i ≤ N) : revAt N i = N - i := if_pos H lemma revAt_eq_self_of_lt {N i : ℕ} (h : N < i) : revAt N i = i := by simp [revAt, Nat.not_le.mpr h] theorem revAt_add {N O n o : ℕ} (hn : n ≤ N) (ho : o ≤ O) : revAt (N + O) (n + o) = revAt N n + revAt O o := by rcases Nat.le.dest hn with ⟨n', rfl⟩ rcases Nat.le.dest ho with ⟨o', rfl⟩ repeat' rw [revAt_le (le_add_right rfl.le)] rw [add_assoc, add_left_comm n' o, ← add_assoc, revAt_le (le_add_right rfl.le)] repeat' rw [add_tsub_cancel_left] theorem revAt_zero (N : ℕ) : revAt N 0 = N := by simp /-- `reflect N f` is the polynomial such that `(reflect N f).coeff i = f.coeff (revAt N i)`. In other words, the terms with exponent `[0, ..., N]` now have exponent `[N, ..., 0]`. In practice, `reflect` is only used when `N` is at least as large as the degree of `f`. Eventually, it will be used with `N` exactly equal to the degree of `f`. -/ noncomputable def reflect (N : ℕ) : R[X] → R[X] | ⟨f⟩ => ⟨Finsupp.embDomain (revAt N) f⟩ theorem reflect_support (N : ℕ) (f : R[X]) : (reflect N f).support = Finset.image (revAt N) f.support := by rcases f with ⟨⟩ ext1 simp only [reflect, support_ofFinsupp, support_embDomain, Finset.mem_map, Finset.mem_image] @[simp] theorem coeff_reflect (N : ℕ) (f : R[X]) (i : ℕ) : coeff (reflect N f) i = f.coeff (revAt N i) := by rcases f with ⟨f⟩ simp only [reflect, coeff] calc Finsupp.embDomain (revAt N) f i = Finsupp.embDomain (revAt N) f (revAt N (revAt N i)) := by rw [revAt_invol] _ = f (revAt N i) := Finsupp.embDomain_apply _ _ _ @[simp] theorem reflect_zero {N : ℕ} : reflect N (0 : R[X]) = 0 := rfl @[simp] theorem reflect_eq_zero_iff {N : ℕ} {f : R[X]} : reflect N (f : R[X]) = 0 ↔ f = 0 := by rw [ofFinsupp_eq_zero, reflect, embDomain_eq_zero, ofFinsupp_eq_zero] @[simp] theorem reflect_add (f g : R[X]) (N : ℕ) : reflect N (f + g) = reflect N f + reflect N g := by ext simp only [coeff_add, coeff_reflect] @[simp] theorem reflect_C_mul (f : R[X]) (r : R) (N : ℕ) : reflect N (C r * f) = C r * reflect N f := by ext simp only [coeff_reflect, coeff_C_mul] theorem reflect_C_mul_X_pow (N n : ℕ) {c : R} : reflect N (C c * X ^ n) = C c * X ^ revAt N n := by ext rw [reflect_C_mul, coeff_C_mul, coeff_C_mul, coeff_X_pow, coeff_reflect] split_ifs with h · rw [h, revAt_invol, coeff_X_pow_self] · rw [not_mem_support_iff.mp] intro a rw [← one_mul (X ^ n), ← C_1] at a apply h rw [← mem_support_C_mul_X_pow a, revAt_invol] @[simp] theorem reflect_C (r : R) (N : ℕ) : reflect N (C r) = C r * X ^ N := by conv_lhs => rw [← mul_one (C r), ← pow_zero X, reflect_C_mul_X_pow, revAt_zero] @[simp] theorem reflect_monomial (N n : ℕ) : reflect N ((X : R[X]) ^ n) = X ^ revAt N n := by rw [← one_mul (X ^ n), ← one_mul (X ^ revAt N n), ← C_1, reflect_C_mul_X_pow] @[simp] lemma reflect_one_X : reflect 1 (X : R[X]) = 1 := by simpa using reflect_monomial 1 1 (R := R) lemma reflect_map {S : Type*} [Semiring S] (f : R →+* S) (p : R[X]) (n : ℕ) : (p.map f).reflect n = (p.reflect n).map f := by ext; simp @[simp] lemma reflect_one (n : ℕ) : (1 : R[X]).reflect n = Polynomial.X ^ n := by rw [← C.map_one, reflect_C, map_one, one_mul] theorem reflect_mul_induction (cf cg : ℕ) : ∀ N O : ℕ, ∀ f g : R[X], #f.support ≤ cf.succ → #g.support ≤ cg.succ → f.natDegree ≤ N → g.natDegree ≤ O → reflect (N + O) (f * g) = reflect N f * reflect O g := by induction' cf with cf hcf --first induction (left): base case · induction' cg with cg hcg -- second induction (right): base case · intro N O f g Cf Cg Nf Og rw [← C_mul_X_pow_eq_self Cf, ← C_mul_X_pow_eq_self Cg] simp_rw [mul_assoc, X_pow_mul, mul_assoc, ← pow_add (X : R[X]), reflect_C_mul, reflect_monomial, add_comm, revAt_add Nf Og, mul_assoc, X_pow_mul, mul_assoc, ← pow_add (X : R[X]), add_comm] -- second induction (right): induction step · intro N O f g Cf Cg Nf Og by_cases g0 : g = 0 · rw [g0, reflect_zero, mul_zero, mul_zero, reflect_zero] rw [← eraseLead_add_C_mul_X_pow g, mul_add, reflect_add, reflect_add, mul_add, hcg, hcg] <;> try assumption · exact le_add_left card_support_C_mul_X_pow_le_one · exact le_trans (natDegree_C_mul_X_pow_le g.leadingCoeff g.natDegree) Og · exact Nat.lt_succ_iff.mp (gt_of_ge_of_gt Cg (eraseLead_support_card_lt g0)) · exact le_trans eraseLead_natDegree_le_aux Og --first induction (left): induction step · intro N O f g Cf Cg Nf Og by_cases f0 : f = 0 · rw [f0, reflect_zero, zero_mul, zero_mul, reflect_zero] rw [← eraseLead_add_C_mul_X_pow f, add_mul, reflect_add, reflect_add, add_mul, hcf, hcf] <;> try assumption · exact le_add_left card_support_C_mul_X_pow_le_one · exact le_trans (natDegree_C_mul_X_pow_le f.leadingCoeff f.natDegree) Nf · exact Nat.lt_succ_iff.mp (gt_of_ge_of_gt Cf (eraseLead_support_card_lt f0)) · exact le_trans eraseLead_natDegree_le_aux Nf @[simp] theorem reflect_mul (f g : R[X]) {F G : ℕ} (Ff : f.natDegree ≤ F) (Gg : g.natDegree ≤ G) : reflect (F + G) (f * g) = reflect F f * reflect G g := reflect_mul_induction _ _ F G f g f.support.card.le_succ g.support.card.le_succ Ff Gg section Eval₂ variable {S : Type*} [CommSemiring S] theorem eval₂_reflect_mul_pow (i : R →+* S) (x : S) [Invertible x] (N : ℕ) (f : R[X]) (hf : f.natDegree ≤ N) : eval₂ i (⅟ x) (reflect N f) * x ^ N = eval₂ i x f := by refine induction_with_natDegree_le (fun f => eval₂ i (⅟ x) (reflect N f) * x ^ N = eval₂ i x f) _ ?_ ?_ ?_ f hf · simp · intro n r _ hnN simp only [revAt_le hnN, reflect_C_mul_X_pow, eval₂_X_pow, eval₂_C, eval₂_mul] conv in x ^ N => rw [← Nat.sub_add_cancel hnN] rw [pow_add, ← mul_assoc, mul_assoc (i r), ← mul_pow, invOf_mul_self, one_pow, mul_one] · intros simp [*, add_mul] theorem eval₂_reflect_eq_zero_iff (i : R →+* S) (x : S) [Invertible x] (N : ℕ) (f : R[X]) (hf : f.natDegree ≤ N) : eval₂ i (⅟ x) (reflect N f) = 0 ↔ eval₂ i x f = 0 := by conv_rhs => rw [← eval₂_reflect_mul_pow i x N f hf] constructor · intro h rw [h, zero_mul] · intro h rw [← mul_one (eval₂ i (⅟ x) _), ← one_pow N, ← mul_invOf_self x, mul_pow, ← mul_assoc, h, zero_mul] end Eval₂ /-- The reverse of a polynomial f is the polynomial obtained by "reading f backwards". Even though this is not the actual definition, `reverse f = f (1/X) * X ^ f.natDegree`. -/ noncomputable def reverse (f : R[X]) : R[X] := reflect f.natDegree f theorem coeff_reverse (f : R[X]) (n : ℕ) : f.reverse.coeff n = f.coeff (revAt f.natDegree n) := by rw [reverse, coeff_reflect] @[simp] theorem coeff_zero_reverse (f : R[X]) : coeff (reverse f) 0 = leadingCoeff f := by rw [coeff_reverse, revAt_le (zero_le f.natDegree), tsub_zero, leadingCoeff] @[simp] theorem reverse_zero : reverse (0 : R[X]) = 0 := rfl @[simp] theorem reverse_eq_zero : f.reverse = 0 ↔ f = 0 := by simp [reverse] theorem reverse_natDegree_le (f : R[X]) : f.reverse.natDegree ≤ f.natDegree := by rw [natDegree_le_iff_degree_le, degree_le_iff_coeff_zero] intro n hn rw [Nat.cast_lt] at hn rw [coeff_reverse, revAt, Function.Embedding.coeFn_mk, if_neg (not_le_of_gt hn), coeff_eq_zero_of_natDegree_lt hn] theorem natDegree_eq_reverse_natDegree_add_natTrailingDegree (f : R[X]) : f.natDegree = f.reverse.natDegree + f.natTrailingDegree := by by_cases hf : f = 0 · rw [hf, reverse_zero, natDegree_zero, natTrailingDegree_zero] apply le_antisymm · refine tsub_le_iff_right.mp ?_ apply le_natDegree_of_ne_zero rw [reverse, coeff_reflect, ← revAt_le f.natTrailingDegree_le_natDegree, revAt_invol] exact trailingCoeff_nonzero_iff_nonzero.mpr hf · rw [← le_tsub_iff_left f.reverse_natDegree_le] apply natTrailingDegree_le_of_ne_zero have key := mt leadingCoeff_eq_zero.mp (mt reverse_eq_zero.mp hf) rwa [leadingCoeff, coeff_reverse, revAt_le f.reverse_natDegree_le] at key theorem reverse_natDegree (f : R[X]) : f.reverse.natDegree = f.natDegree - f.natTrailingDegree := by rw [f.natDegree_eq_reverse_natDegree_add_natTrailingDegree, add_tsub_cancel_right] theorem reverse_leadingCoeff (f : R[X]) : f.reverse.leadingCoeff = f.trailingCoeff := by rw [leadingCoeff, reverse_natDegree, ← revAt_le f.natTrailingDegree_le_natDegree, coeff_reverse, revAt_invol, trailingCoeff] theorem natTrailingDegree_reverse (f : R[X]) : f.reverse.natTrailingDegree = 0 := by rw [natTrailingDegree_eq_zero, reverse_eq_zero, coeff_zero_reverse, leadingCoeff_ne_zero] exact eq_or_ne _ _ theorem reverse_trailingCoeff (f : R[X]) : f.reverse.trailingCoeff = f.leadingCoeff := by rw [trailingCoeff, natTrailingDegree_reverse, coeff_zero_reverse] theorem reverse_mul {f g : R[X]} (fg : f.leadingCoeff * g.leadingCoeff ≠ 0) : reverse (f * g) = reverse f * reverse g := by unfold reverse rw [natDegree_mul' fg, reflect_mul f g rfl.le rfl.le] @[simp] theorem reverse_mul_of_domain {R : Type*} [Semiring R] [NoZeroDivisors R] (f g : R[X]) : reverse (f * g) = reverse f * reverse g := by by_cases f0 : f = 0 · simp only [f0, zero_mul, reverse_zero] by_cases g0 : g = 0 · rw [g0, mul_zero, reverse_zero, mul_zero] simp [reverse_mul, *] theorem trailingCoeff_mul {R : Type*} [Semiring R] [NoZeroDivisors R] (p q : R[X]) : (p * q).trailingCoeff = p.trailingCoeff * q.trailingCoeff := by rw [← reverse_leadingCoeff, reverse_mul_of_domain, leadingCoeff_mul, reverse_leadingCoeff, reverse_leadingCoeff] @[simp] theorem coeff_one_reverse (f : R[X]) : coeff (reverse f) 1 = nextCoeff f := by rw [coeff_reverse, nextCoeff] split_ifs with hf · have : coeff f 1 = 0 := coeff_eq_zero_of_natDegree_lt (by simp only [hf, zero_lt_one]) simp [*, revAt] · rw [revAt_le] exact Nat.succ_le_iff.2 (pos_iff_ne_zero.2 hf) @[simp] lemma reverse_C (t : R) : reverse (C t) = C t := by simp [reverse] @[simp] lemma reverse_mul_X (p : R[X]) : reverse (p * X) = reverse p := by nontriviality R
rcases eq_or_ne p 0 with rfl | hp · simp · simp [reverse, hp]
Mathlib/Algebra/Polynomial/Reverse.lean
313
316
/- 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.Topology.UniformSpace.Cauchy /-! # Uniform convergence A sequence of functions `Fₙ` (with values in a metric space) converges uniformly on a set `s` to a function `f` if, for all `ε > 0`, for all large enough `n`, one has for all `y ∈ s` the inequality `dist (f y, Fₙ y) < ε`. Under uniform convergence, many properties of the `Fₙ` pass to the limit, most notably continuity. We prove this in the file, defining the notion of uniform convergence in the more general setting of uniform spaces, and with respect to an arbitrary indexing set endowed with a filter (instead of just `ℕ` with `atTop`). ## Main results Let `α` be a topological space, `β` a uniform space, `Fₙ` and `f` be functions from `α` to `β` (where the index `n` belongs to an indexing type `ι` endowed with a filter `p`). * `TendstoUniformlyOn F f p s`: the fact that `Fₙ` converges uniformly to `f` on `s`. This means that, for any entourage `u` of the diagonal, for large enough `n` (with respect to `p`), one has `(f y, Fₙ y) ∈ u` for all `y ∈ s`. * `TendstoUniformly F f p`: same notion with `s = univ`. * `TendstoUniformlyOn.continuousOn`: a uniform limit on a set of functions which are continuous on this set is itself continuous on this set. * `TendstoUniformly.continuous`: a uniform limit of continuous functions is continuous. * `TendstoUniformlyOn.tendsto_comp`: If `Fₙ` tends uniformly to `f` on a set `s`, and `gₙ` tends to `x` within `s`, then `Fₙ gₙ` tends to `f x` if `f` is continuous at `x` within `s`. * `TendstoUniformly.tendsto_comp`: If `Fₙ` tends uniformly to `f`, and `gₙ` tends to `x`, then `Fₙ gₙ` tends to `f x`. Finally, we introduce the notion of a uniform Cauchy sequence, which is to uniform convergence what a Cauchy sequence is to the usual notion of convergence. ## Implementation notes We derive most of our initial results from an auxiliary definition `TendstoUniformlyOnFilter`. This definition in and of itself can sometimes be useful, e.g., when studying the local behavior of the `Fₙ` near a point, which would typically look like `TendstoUniformlyOnFilter F f p (𝓝 x)`. Still, while this may be the "correct" definition (see `tendstoUniformlyOn_iff_tendstoUniformlyOnFilter`), it is somewhat unwieldy to work with in practice. Thus, we provide the more traditional definition in `TendstoUniformlyOn`. ## Tags Uniform limit, uniform convergence, tends uniformly to -/ noncomputable section open Topology Uniformity Filter Set Uniform variable {α β γ ι : Type*} [UniformSpace β] variable {F : ι → α → β} {f : α → β} {s s' : Set α} {x : α} {p : Filter ι} {p' : Filter α} /-! ### Different notions of uniform convergence We define uniform convergence, on a set or in the whole space. -/ /-- A sequence of functions `Fₙ` converges uniformly on a filter `p'` to a limiting function `f` with respect to the filter `p` if, for any entourage of the diagonal `u`, one has `p ×ˢ p'`-eventually `(f x, Fₙ x) ∈ u`. -/ def TendstoUniformlyOnFilter (F : ι → α → β) (f : α → β) (p : Filter ι) (p' : Filter α) := ∀ u ∈ 𝓤 β, ∀ᶠ n : ι × α in p ×ˢ p', (f n.snd, F n.fst n.snd) ∈ u /-- A sequence of functions `Fₙ` converges uniformly on a filter `p'` to a limiting function `f` w.r.t. filter `p` iff the function `(n, x) ↦ (f x, Fₙ x)` converges along `p ×ˢ p'` to the uniformity. In other words: one knows nothing about the behavior of `x` in this limit besides it being in `p'`. -/ theorem tendstoUniformlyOnFilter_iff_tendsto : TendstoUniformlyOnFilter F f p p' ↔ Tendsto (fun q : ι × α => (f q.2, F q.1 q.2)) (p ×ˢ p') (𝓤 β) := Iff.rfl /-- A sequence of functions `Fₙ` converges uniformly on a set `s` to a limiting function `f` with respect to the filter `p` if, for any entourage of the diagonal `u`, one has `p`-eventually `(f x, Fₙ x) ∈ u` for all `x ∈ s`. -/ def TendstoUniformlyOn (F : ι → α → β) (f : α → β) (p : Filter ι) (s : Set α) := ∀ u ∈ 𝓤 β, ∀ᶠ n in p, ∀ x : α, x ∈ s → (f x, F n x) ∈ u theorem tendstoUniformlyOn_iff_tendstoUniformlyOnFilter : TendstoUniformlyOn F f p s ↔ TendstoUniformlyOnFilter F f p (𝓟 s) := by simp only [TendstoUniformlyOn, TendstoUniformlyOnFilter] apply forall₂_congr simp_rw [eventually_prod_principal_iff] simp alias ⟨TendstoUniformlyOn.tendstoUniformlyOnFilter, TendstoUniformlyOnFilter.tendstoUniformlyOn⟩ := tendstoUniformlyOn_iff_tendstoUniformlyOnFilter /-- A sequence of functions `Fₙ` converges uniformly on a set `s` to a limiting function `f` w.r.t. filter `p` iff the function `(n, x) ↦ (f x, Fₙ x)` converges along `p ×ˢ 𝓟 s` to the uniformity. In other words: one knows nothing about the behavior of `x` in this limit besides it being in `s`. -/ theorem tendstoUniformlyOn_iff_tendsto : TendstoUniformlyOn F f p s ↔ Tendsto (fun q : ι × α => (f q.2, F q.1 q.2)) (p ×ˢ 𝓟 s) (𝓤 β) := by simp [tendstoUniformlyOn_iff_tendstoUniformlyOnFilter, tendstoUniformlyOnFilter_iff_tendsto] /-- A sequence of functions `Fₙ` converges uniformly to a limiting function `f` with respect to a filter `p` if, for any entourage of the diagonal `u`, one has `p`-eventually `(f x, Fₙ x) ∈ u` for all `x`. -/ def TendstoUniformly (F : ι → α → β) (f : α → β) (p : Filter ι) := ∀ u ∈ 𝓤 β, ∀ᶠ n in p, ∀ x : α, (f x, F n x) ∈ u theorem tendstoUniformlyOn_univ : TendstoUniformlyOn F f p univ ↔ TendstoUniformly F f p := by simp [TendstoUniformlyOn, TendstoUniformly] theorem tendstoUniformly_iff_tendstoUniformlyOnFilter : TendstoUniformly F f p ↔ TendstoUniformlyOnFilter F f p ⊤ := by rw [← tendstoUniformlyOn_univ, tendstoUniformlyOn_iff_tendstoUniformlyOnFilter, principal_univ] theorem TendstoUniformly.tendstoUniformlyOnFilter (h : TendstoUniformly F f p) : TendstoUniformlyOnFilter F f p ⊤ := by rwa [← tendstoUniformly_iff_tendstoUniformlyOnFilter] theorem tendstoUniformlyOn_iff_tendstoUniformly_comp_coe : TendstoUniformlyOn F f p s ↔ TendstoUniformly (fun i (x : s) => F i x) (f ∘ (↑)) p := forall₂_congr fun u _ => by simp /-- A sequence of functions `Fₙ` converges uniformly to a limiting function `f` w.r.t. filter `p` iff the function `(n, x) ↦ (f x, Fₙ x)` converges along `p ×ˢ ⊤` to the uniformity. In other words: one knows nothing about the behavior of `x` in this limit. -/ theorem tendstoUniformly_iff_tendsto : TendstoUniformly F f p ↔ Tendsto (fun q : ι × α => (f q.2, F q.1 q.2)) (p ×ˢ ⊤) (𝓤 β) := by simp [tendstoUniformly_iff_tendstoUniformlyOnFilter, tendstoUniformlyOnFilter_iff_tendsto] /-- Uniform convergence implies pointwise convergence. -/ theorem TendstoUniformlyOnFilter.tendsto_at (h : TendstoUniformlyOnFilter F f p p') (hx : 𝓟 {x} ≤ p') : Tendsto (fun n => F n x) p <| 𝓝 (f x) := by refine Uniform.tendsto_nhds_right.mpr fun u hu => mem_map.mpr ?_ filter_upwards [(h u hu).curry] intro i h simpa using h.filter_mono hx /-- Uniform convergence implies pointwise convergence. -/ theorem TendstoUniformlyOn.tendsto_at (h : TendstoUniformlyOn F f p s) (hx : x ∈ s) : Tendsto (fun n => F n x) p <| 𝓝 (f x) := h.tendstoUniformlyOnFilter.tendsto_at (le_principal_iff.mpr <| mem_principal.mpr <| singleton_subset_iff.mpr <| hx) /-- Uniform convergence implies pointwise convergence. -/ theorem TendstoUniformly.tendsto_at (h : TendstoUniformly F f p) (x : α) : Tendsto (fun n => F n x) p <| 𝓝 (f x) := h.tendstoUniformlyOnFilter.tendsto_at le_top theorem TendstoUniformlyOnFilter.mono_left {p'' : Filter ι} (h : TendstoUniformlyOnFilter F f p p') (hp : p'' ≤ p) : TendstoUniformlyOnFilter F f p'' p' := fun u hu => (h u hu).filter_mono (p'.prod_mono_left hp) theorem TendstoUniformlyOnFilter.mono_right {p'' : Filter α} (h : TendstoUniformlyOnFilter F f p p') (hp : p'' ≤ p') : TendstoUniformlyOnFilter F f p p'' := fun u hu => (h u hu).filter_mono (p.prod_mono_right hp)
theorem TendstoUniformlyOn.mono (h : TendstoUniformlyOn F f p s) (h' : s' ⊆ s) : TendstoUniformlyOn F f p s' :=
Mathlib/Topology/UniformSpace/UniformConvergence.lean
160
162
/- Copyright (c) 2022 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies -/ import Mathlib.Order.Filter.Prod /-! # N-ary maps of filter This file defines the binary and ternary maps of filters. This is mostly useful to define pointwise operations on filters. ## Main declarations * `Filter.map₂`: Binary map of filters. ## Notes This file is very similar to `Data.Set.NAry`, `Data.Finset.NAry` and `Data.Option.NAry`. Please keep them in sync. -/ open Function Set open Filter namespace Filter variable {α α' β β' γ γ' δ δ' ε ε' : Type*} {m : α → β → γ} {f f₁ f₂ : Filter α} {g g₁ g₂ : Filter β} {h : Filter γ} {s : Set α} {t : Set β} {u : Set γ} {a : α} {b : β} /-- The image of a binary function `m : α → β → γ` as a function `Filter α → Filter β → Filter γ`. Mathematically this should be thought of as the image of the corresponding function `α × β → γ`. -/ def map₂ (m : α → β → γ) (f : Filter α) (g : Filter β) : Filter γ := ((f ×ˢ g).map (uncurry m)).copy { s | ∃ u ∈ f, ∃ v ∈ g, image2 m u v ⊆ s } fun _ ↦ by simp only [mem_map, mem_prod_iff, image2_subset_iff, prod_subset_iff]; rfl @[simp 900] theorem mem_map₂_iff : u ∈ map₂ m f g ↔ ∃ s ∈ f, ∃ t ∈ g, image2 m s t ⊆ u := Iff.rfl theorem image2_mem_map₂ (hs : s ∈ f) (ht : t ∈ g) : image2 m s t ∈ map₂ m f g := ⟨_, hs, _, ht, Subset.rfl⟩ theorem map_prod_eq_map₂ (m : α → β → γ) (f : Filter α) (g : Filter β) : Filter.map (fun p : α × β => m p.1 p.2) (f ×ˢ g) = map₂ m f g := by rw [map₂, copy_eq, uncurry_def] theorem map_prod_eq_map₂' (m : α × β → γ) (f : Filter α) (g : Filter β) : Filter.map m (f ×ˢ g) = map₂ (fun a b => m (a, b)) f g := map_prod_eq_map₂ m.curry f g @[simp] theorem map₂_mk_eq_prod (f : Filter α) (g : Filter β) : map₂ Prod.mk f g = f ×ˢ g := by simp only [← map_prod_eq_map₂, map_id'] -- lemma image2_mem_map₂_iff (hm : injective2 m) : image2 m s t ∈ map₂ m f g ↔ s ∈ f ∧ t ∈ g := -- ⟨by { rintro ⟨u, v, hu, hv, h⟩, rw image2_subset_image2_iff hm at h, -- exact ⟨mem_of_superset hu h.1, mem_of_superset hv h.2⟩ }, fun h ↦ image2_mem_map₂ h.1 h.2⟩ @[gcongr] theorem map₂_mono (hf : f₁ ≤ f₂) (hg : g₁ ≤ g₂) : map₂ m f₁ g₁ ≤ map₂ m f₂ g₂ := fun _ ⟨s, hs, t, ht, hst⟩ => ⟨s, hf hs, t, hg ht, hst⟩ @[gcongr] theorem map₂_mono_left (h : g₁ ≤ g₂) : map₂ m f g₁ ≤ map₂ m f g₂ := map₂_mono Subset.rfl h @[gcongr] theorem map₂_mono_right (h : f₁ ≤ f₂) : map₂ m f₁ g ≤ map₂ m f₂ g := map₂_mono h Subset.rfl @[simp] theorem le_map₂_iff {h : Filter γ} : h ≤ map₂ m f g ↔ ∀ ⦃s⦄, s ∈ f → ∀ ⦃t⦄, t ∈ g → image2 m s t ∈ h := ⟨fun H _ hs _ ht => H <| image2_mem_map₂ hs ht, fun H _ ⟨_, hs, _, ht, hu⟩ => mem_of_superset (H hs ht) hu⟩ @[simp] theorem map₂_eq_bot_iff : map₂ m f g = ⊥ ↔ f = ⊥ ∨ g = ⊥ := by simp [← map_prod_eq_map₂] @[simp] theorem map₂_bot_left : map₂ m ⊥ g = ⊥ := map₂_eq_bot_iff.2 <| .inl rfl @[simp] theorem map₂_bot_right : map₂ m f ⊥ = ⊥ := map₂_eq_bot_iff.2 <| .inr rfl @[simp] theorem map₂_neBot_iff : (map₂ m f g).NeBot ↔ f.NeBot ∧ g.NeBot := by simp [neBot_iff, not_or] protected theorem NeBot.map₂ (hf : f.NeBot) (hg : g.NeBot) : (map₂ m f g).NeBot := map₂_neBot_iff.2 ⟨hf, hg⟩ instance map₂.neBot [NeBot f] [NeBot g] : NeBot (map₂ m f g) := .map₂ ‹_› ‹_› theorem NeBot.of_map₂_left (h : (map₂ m f g).NeBot) : f.NeBot := (map₂_neBot_iff.1 h).1 theorem NeBot.of_map₂_right (h : (map₂ m f g).NeBot) : g.NeBot := (map₂_neBot_iff.1 h).2 theorem map₂_sup_left : map₂ m (f₁ ⊔ f₂) g = map₂ m f₁ g ⊔ map₂ m f₂ g := by simp_rw [← map_prod_eq_map₂, sup_prod, map_sup] theorem map₂_sup_right : map₂ m f (g₁ ⊔ g₂) = map₂ m f g₁ ⊔ map₂ m f g₂ := by simp_rw [← map_prod_eq_map₂, prod_sup, map_sup] theorem map₂_inf_subset_left : map₂ m (f₁ ⊓ f₂) g ≤ map₂ m f₁ g ⊓ map₂ m f₂ g := Monotone.map_inf_le (fun _ _ ↦ map₂_mono_right) f₁ f₂ theorem map₂_inf_subset_right : map₂ m f (g₁ ⊓ g₂) ≤ map₂ m f g₁ ⊓ map₂ m f g₂ := Monotone.map_inf_le (fun _ _ ↦ map₂_mono_left) g₁ g₂ @[simp] theorem map₂_pure_left : map₂ m (pure a) g = g.map (m a) := by rw [← map_prod_eq_map₂, pure_prod, map_map]; rfl @[simp] theorem map₂_pure_right : map₂ m f (pure b) = f.map (m · b) := by rw [← map_prod_eq_map₂, prod_pure, map_map]; rfl theorem map₂_pure : map₂ m (pure a) (pure b) = pure (m a b) := by rw [map₂_pure_right, map_pure] theorem map₂_swap (m : α → β → γ) (f : Filter α) (g : Filter β) : map₂ m f g = map₂ (fun a b => m b a) g f := by rw [← map_prod_eq_map₂, prod_comm, map_map, ← map_prod_eq_map₂, Function.comp_def] @[simp] theorem map₂_left [NeBot g] : map₂ (fun x _ => x) f g = f := by rw [← map_prod_eq_map₂, map_fst_prod] @[simp] theorem map₂_right [NeBot f] : map₂ (fun _ y => y) f g = g := by rw [map₂_swap, map₂_left] theorem map_map₂ (m : α → β → γ) (n : γ → δ) : (map₂ m f g).map n = map₂ (fun a b => n (m a b)) f g := by rw [← map_prod_eq_map₂, ← map_prod_eq_map₂, map_map]; rfl theorem map₂_map_left (m : γ → β → δ) (n : α → γ) : map₂ m (f.map n) g = map₂ (fun a b => m (n a) b) f g := by rw [← map_prod_eq_map₂, ← map_prod_eq_map₂, ← @map_id _ g, prod_map_map_eq, map_map, map_id]; rfl theorem map₂_map_right (m : α → γ → δ) (n : β → γ) : map₂ m f (g.map n) = map₂ (fun a b => m a (n b)) f g := by rw [map₂_swap, map₂_map_left, map₂_swap] @[simp] theorem map₂_curry (m : α × β → γ) (f : Filter α) (g : Filter β) : map₂ m.curry f g = (f ×ˢ g).map m := (map_prod_eq_map₂' _ _ _).symm @[simp]
theorem map_uncurry_prod (m : α → β → γ) (f : Filter α) (g : Filter β) : (f ×ˢ g).map (uncurry m) = map₂ m f g :=
Mathlib/Order/Filter/NAry.lean
155
156
/- Copyright (c) 2018 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes, Johannes Hölzl, Kim Morrison, Jens Wagemaker -/ import Mathlib.Algebra.MonoidAlgebra.Degree import Mathlib.Algebra.Order.Ring.WithTop import Mathlib.Algebra.Polynomial.Basic import Mathlib.Data.Nat.Cast.WithTop import Mathlib.Data.Nat.SuccPred import Mathlib.Order.SuccPred.WithBot /-! # Degree of univariate polynomials ## Main definitions * `Polynomial.degree`: the degree of a polynomial, where `0` has degree `⊥` * `Polynomial.natDegree`: the degree of a polynomial, where `0` has degree `0` * `Polynomial.leadingCoeff`: the leading coefficient of a polynomial * `Polynomial.Monic`: a polynomial is monic if its leading coefficient is 0 * `Polynomial.nextCoeff`: the next coefficient after the leading coefficient ## Main results * `Polynomial.degree_eq_natDegree`: the degree and natDegree coincide for nonzero polynomials -/ noncomputable section open Finsupp Finset open Polynomial namespace Polynomial universe u v variable {R : Type u} {S : Type v} {a b c d : R} {n m : ℕ} section Semiring variable [Semiring R] {p q r : R[X]} /-- `degree p` is the degree of the polynomial `p`, i.e. the largest `X`-exponent in `p`. `degree p = some n` when `p ≠ 0` and `n` is the highest power of `X` that appears in `p`, otherwise `degree 0 = ⊥`. -/ def degree (p : R[X]) : WithBot ℕ := p.support.max /-- `natDegree p` forces `degree p` to ℕ, by defining `natDegree 0 = 0`. -/ def natDegree (p : R[X]) : ℕ := (degree p).unbotD 0 /-- `leadingCoeff p` gives the coefficient of the highest power of `X` in `p`. -/ def leadingCoeff (p : R[X]) : R := coeff p (natDegree p) /-- a polynomial is `Monic` if its leading coefficient is 1 -/ def Monic (p : R[X]) := leadingCoeff p = (1 : R) theorem Monic.def : Monic p ↔ leadingCoeff p = 1 := Iff.rfl instance Monic.decidable [DecidableEq R] : Decidable (Monic p) := by unfold Monic; infer_instance @[simp] theorem Monic.leadingCoeff {p : R[X]} (hp : p.Monic) : leadingCoeff p = 1 := hp theorem Monic.coeff_natDegree {p : R[X]} (hp : p.Monic) : p.coeff p.natDegree = 1 := hp @[simp] theorem degree_zero : degree (0 : R[X]) = ⊥ := rfl @[simp] theorem natDegree_zero : natDegree (0 : R[X]) = 0 := rfl @[simp] theorem coeff_natDegree : coeff p (natDegree p) = leadingCoeff p := rfl @[simp] theorem degree_eq_bot : degree p = ⊥ ↔ p = 0 := ⟨fun h => support_eq_empty.1 (Finset.max_eq_bot.1 h), fun h => h.symm ▸ rfl⟩ theorem degree_ne_bot : degree p ≠ ⊥ ↔ p ≠ 0 := degree_eq_bot.not theorem degree_eq_natDegree (hp : p ≠ 0) : degree p = (natDegree p : WithBot ℕ) := by let ⟨n, hn⟩ := not_forall.1 (mt Option.eq_none_iff_forall_not_mem.2 (mt degree_eq_bot.1 hp)) have hn : degree p = some n := Classical.not_not.1 hn rw [natDegree, hn]; rfl theorem degree_eq_iff_natDegree_eq {p : R[X]} {n : ℕ} (hp : p ≠ 0) : p.degree = n ↔ p.natDegree = n := by rw [degree_eq_natDegree hp]; exact WithBot.coe_eq_coe theorem degree_eq_iff_natDegree_eq_of_pos {p : R[X]} {n : ℕ} (hn : 0 < n) : p.degree = n ↔ p.natDegree = n := by obtain rfl|h := eq_or_ne p 0 · simp [hn.ne] · exact degree_eq_iff_natDegree_eq h theorem natDegree_eq_of_degree_eq_some {p : R[X]} {n : ℕ} (h : degree p = n) : natDegree p = n := by rw [natDegree, h, Nat.cast_withBot, WithBot.unbotD_coe] theorem degree_ne_of_natDegree_ne {n : ℕ} : p.natDegree ≠ n → degree p ≠ n := mt natDegree_eq_of_degree_eq_some @[simp] theorem degree_le_natDegree : degree p ≤ natDegree p := WithBot.giUnbotDBot.gc.le_u_l _ theorem natDegree_eq_of_degree_eq [Semiring S] {q : S[X]} (h : degree p = degree q) : natDegree p = natDegree q := by unfold natDegree; rw [h] theorem le_degree_of_ne_zero (h : coeff p n ≠ 0) : (n : WithBot ℕ) ≤ degree p := by rw [Nat.cast_withBot] exact Finset.le_sup (mem_support_iff.2 h) theorem degree_mono [Semiring S] {f : R[X]} {g : S[X]} (h : f.support ⊆ g.support) : f.degree ≤ g.degree := Finset.sup_mono h theorem degree_le_degree (h : coeff q (natDegree p) ≠ 0) : degree p ≤ degree q := by by_cases hp : p = 0 · rw [hp, degree_zero] exact bot_le · rw [degree_eq_natDegree hp] exact le_degree_of_ne_zero h theorem natDegree_le_iff_degree_le {n : ℕ} : natDegree p ≤ n ↔ degree p ≤ n := WithBot.unbotD_le_iff (fun _ ↦ bot_le) theorem natDegree_lt_iff_degree_lt (hp : p ≠ 0) : p.natDegree < n ↔ p.degree < ↑n := WithBot.unbotD_lt_iff (absurd · (degree_eq_bot.not.mpr hp)) alias ⟨degree_le_of_natDegree_le, natDegree_le_of_degree_le⟩ := natDegree_le_iff_degree_le theorem natDegree_le_natDegree [Semiring S] {q : S[X]} (hpq : p.degree ≤ q.degree) : p.natDegree ≤ q.natDegree := WithBot.giUnbotDBot.gc.monotone_l hpq @[simp] theorem degree_C (ha : a ≠ 0) : degree (C a) = (0 : WithBot ℕ) := by rw [degree, ← monomial_zero_left, support_monomial 0 ha, max_eq_sup_coe, sup_singleton, WithBot.coe_zero] theorem degree_C_le : degree (C a) ≤ 0 := by by_cases h : a = 0 · rw [h, C_0] exact bot_le · rw [degree_C h] theorem degree_C_lt : degree (C a) < 1 := degree_C_le.trans_lt <| WithBot.coe_lt_coe.mpr zero_lt_one theorem degree_one_le : degree (1 : R[X]) ≤ (0 : WithBot ℕ) := by rw [← C_1]; exact degree_C_le @[simp] theorem natDegree_C (a : R) : natDegree (C a) = 0 := by by_cases ha : a = 0 · have : C a = 0 := by rw [ha, C_0] rw [natDegree, degree_eq_bot.2 this, WithBot.unbotD_bot] · rw [natDegree, degree_C ha, WithBot.unbotD_zero] @[simp] theorem natDegree_one : natDegree (1 : R[X]) = 0 := natDegree_C 1 @[simp] theorem natDegree_natCast (n : ℕ) : natDegree (n : R[X]) = 0 := by simp only [← C_eq_natCast, natDegree_C] @[simp] theorem natDegree_ofNat (n : ℕ) [Nat.AtLeastTwo n] : natDegree (ofNat(n) : R[X]) = 0 := natDegree_natCast _ theorem degree_natCast_le (n : ℕ) : degree (n : R[X]) ≤ 0 := degree_le_of_natDegree_le (by simp) @[simp] theorem degree_monomial (n : ℕ) (ha : a ≠ 0) : degree (monomial n a) = n := by rw [degree, support_monomial n ha, max_singleton, Nat.cast_withBot] @[simp] theorem degree_C_mul_X_pow (n : ℕ) (ha : a ≠ 0) : degree (C a * X ^ n) = n := by rw [C_mul_X_pow_eq_monomial, degree_monomial n ha] theorem degree_C_mul_X (ha : a ≠ 0) : degree (C a * X) = 1 := by simpa only [pow_one] using degree_C_mul_X_pow 1 ha theorem degree_monomial_le (n : ℕ) (a : R) : degree (monomial n a) ≤ n := letI := Classical.decEq R if h : a = 0 then by rw [h, (monomial n).map_zero, degree_zero]; exact bot_le else le_of_eq (degree_monomial n h) theorem degree_C_mul_X_pow_le (n : ℕ) (a : R) : degree (C a * X ^ n) ≤ n := by rw [C_mul_X_pow_eq_monomial] apply degree_monomial_le theorem degree_C_mul_X_le (a : R) : degree (C a * X) ≤ 1 := by simpa only [pow_one] using degree_C_mul_X_pow_le 1 a @[simp] theorem natDegree_C_mul_X_pow (n : ℕ) (a : R) (ha : a ≠ 0) : natDegree (C a * X ^ n) = n := natDegree_eq_of_degree_eq_some (degree_C_mul_X_pow n ha) @[simp] theorem natDegree_C_mul_X (a : R) (ha : a ≠ 0) : natDegree (C a * X) = 1 := by simpa only [pow_one] using natDegree_C_mul_X_pow 1 a ha @[simp] theorem natDegree_monomial [DecidableEq R] (i : ℕ) (r : R) : natDegree (monomial i r) = if r = 0 then 0 else i := by split_ifs with hr · simp [hr] · rw [← C_mul_X_pow_eq_monomial, natDegree_C_mul_X_pow i r hr] theorem natDegree_monomial_le (a : R) {m : ℕ} : (monomial m a).natDegree ≤ m := by classical rw [Polynomial.natDegree_monomial] split_ifs exacts [Nat.zero_le _, le_rfl] theorem natDegree_monomial_eq (i : ℕ) {r : R} (r0 : r ≠ 0) : (monomial i r).natDegree = i := letI := Classical.decEq R Eq.trans (natDegree_monomial _ _) (if_neg r0) theorem coeff_ne_zero_of_eq_degree (hn : degree p = n) : coeff p n ≠ 0 := fun h => mem_support_iff.mp (mem_of_max hn) h theorem degree_X_pow_le (n : ℕ) : degree (X ^ n : R[X]) ≤ n := by simpa only [C_1, one_mul] using degree_C_mul_X_pow_le n (1 : R) theorem degree_X_le : degree (X : R[X]) ≤ 1 := degree_monomial_le _ _ theorem natDegree_X_le : (X : R[X]).natDegree ≤ 1 := natDegree_le_of_degree_le degree_X_le theorem withBotSucc_degree_eq_natDegree_add_one (h : p ≠ 0) : p.degree.succ = p.natDegree + 1 := by rw [degree_eq_natDegree h] exact WithBot.succ_coe p.natDegree end Semiring section NonzeroSemiring variable [Semiring R] [Nontrivial R] {p q : R[X]} @[simp] theorem degree_one : degree (1 : R[X]) = (0 : WithBot ℕ) := degree_C one_ne_zero @[simp] theorem degree_X : degree (X : R[X]) = 1 := degree_monomial _ one_ne_zero @[simp] theorem natDegree_X : (X : R[X]).natDegree = 1 := natDegree_eq_of_degree_eq_some degree_X end NonzeroSemiring section Ring variable [Ring R] @[simp] theorem degree_neg (p : R[X]) : degree (-p) = degree p := by unfold degree; rw [support_neg] theorem degree_neg_le_of_le {a : WithBot ℕ} {p : R[X]} (hp : degree p ≤ a) : degree (-p) ≤ a := p.degree_neg.le.trans hp @[simp] theorem natDegree_neg (p : R[X]) : natDegree (-p) = natDegree p := by simp [natDegree] theorem natDegree_neg_le_of_le {p : R[X]} (hp : natDegree p ≤ m) : natDegree (-p) ≤ m := (natDegree_neg p).le.trans hp @[simp] theorem natDegree_intCast (n : ℤ) : natDegree (n : R[X]) = 0 := by rw [← C_eq_intCast, natDegree_C] theorem degree_intCast_le (n : ℤ) : degree (n : R[X]) ≤ 0 := degree_le_of_natDegree_le (by simp) @[simp] theorem leadingCoeff_neg (p : R[X]) : (-p).leadingCoeff = -p.leadingCoeff := by rw [leadingCoeff, leadingCoeff, natDegree_neg, coeff_neg] end Ring section Semiring variable [Semiring R] {p : R[X]} /-- The second-highest coefficient, or 0 for constants -/ def nextCoeff (p : R[X]) : R := if p.natDegree = 0 then 0 else p.coeff (p.natDegree - 1) lemma nextCoeff_eq_zero : p.nextCoeff = 0 ↔ p.natDegree = 0 ∨ 0 < p.natDegree ∧ p.coeff (p.natDegree - 1) = 0 := by simp [nextCoeff, or_iff_not_imp_left, pos_iff_ne_zero]; aesop lemma nextCoeff_ne_zero : p.nextCoeff ≠ 0 ↔ p.natDegree ≠ 0 ∧ p.coeff (p.natDegree - 1) ≠ 0 := by simp [nextCoeff] @[simp] theorem nextCoeff_C_eq_zero (c : R) : nextCoeff (C c) = 0 := by rw [nextCoeff] simp theorem nextCoeff_of_natDegree_pos (hp : 0 < p.natDegree) : nextCoeff p = p.coeff (p.natDegree - 1) := by rw [nextCoeff, if_neg] contrapose! hp simpa variable {p q : R[X]} {ι : Type*} theorem degree_add_le (p q : R[X]) : degree (p + q) ≤ max (degree p) (degree q) := by simpa only [degree, ← support_toFinsupp, toFinsupp_add] using AddMonoidAlgebra.sup_support_add_le _ _ _ theorem degree_add_le_of_degree_le {p q : R[X]} {n : ℕ} (hp : degree p ≤ n) (hq : degree q ≤ n) : degree (p + q) ≤ n := (degree_add_le p q).trans <| max_le hp hq theorem degree_add_le_of_le {a b : WithBot ℕ} (hp : degree p ≤ a) (hq : degree q ≤ b) : degree (p + q) ≤ max a b := (p.degree_add_le q).trans <| max_le_max ‹_› ‹_› theorem natDegree_add_le (p q : R[X]) : natDegree (p + q) ≤ max (natDegree p) (natDegree q) := by rcases le_max_iff.1 (degree_add_le p q) with h | h <;> simp [natDegree_le_natDegree h] theorem natDegree_add_le_of_degree_le {p q : R[X]} {n : ℕ} (hp : natDegree p ≤ n) (hq : natDegree q ≤ n) : natDegree (p + q) ≤ n := (natDegree_add_le p q).trans <| max_le hp hq theorem natDegree_add_le_of_le (hp : natDegree p ≤ m) (hq : natDegree q ≤ n) : natDegree (p + q) ≤ max m n := (p.natDegree_add_le q).trans <| max_le_max ‹_› ‹_› @[simp] theorem leadingCoeff_zero : leadingCoeff (0 : R[X]) = 0 := rfl @[simp] theorem leadingCoeff_eq_zero : leadingCoeff p = 0 ↔ p = 0 := ⟨fun h => Classical.by_contradiction fun hp => mt mem_support_iff.1 (Classical.not_not.2 h) (mem_of_max (degree_eq_natDegree hp)), fun h => h.symm ▸ leadingCoeff_zero⟩ theorem leadingCoeff_ne_zero : leadingCoeff p ≠ 0 ↔ p ≠ 0 := by rw [Ne, leadingCoeff_eq_zero] theorem leadingCoeff_eq_zero_iff_deg_eq_bot : leadingCoeff p = 0 ↔ degree p = ⊥ := by rw [leadingCoeff_eq_zero, degree_eq_bot] theorem natDegree_C_mul_X_pow_le (a : R) (n : ℕ) : natDegree (C a * X ^ n) ≤ n := natDegree_le_iff_degree_le.2 <| degree_C_mul_X_pow_le _ _ theorem degree_erase_le (p : R[X]) (n : ℕ) : degree (p.erase n) ≤ degree p := by rcases p with ⟨p⟩ simp only [erase_def, degree, coeff, support] apply sup_mono rw [Finsupp.support_erase] apply Finset.erase_subset theorem degree_erase_lt (hp : p ≠ 0) : degree (p.erase (natDegree p)) < degree p := by apply lt_of_le_of_ne (degree_erase_le _ _) rw [degree_eq_natDegree hp, degree, support_erase] exact fun h => not_mem_erase _ _ (mem_of_max h) theorem degree_update_le (p : R[X]) (n : ℕ) (a : R) : degree (p.update n a) ≤ max (degree p) n := by classical rw [degree, support_update] split_ifs · exact (Finset.max_mono (erase_subset _ _)).trans (le_max_left _ _) · rw [max_insert, max_comm] exact le_rfl theorem degree_sum_le (s : Finset ι) (f : ι → R[X]) : degree (∑ i ∈ s, f i) ≤ s.sup fun b => degree (f b) := Finset.cons_induction_on s (by simp only [sum_empty, sup_empty, degree_zero, le_refl]) fun a s has ih => calc degree (∑ i ∈ cons a s has, f i) ≤ max (degree (f a)) (degree (∑ i ∈ s, f i)) := by rw [Finset.sum_cons]; exact degree_add_le _ _ _ ≤ _ := by rw [sup_cons]; exact max_le_max le_rfl ih theorem degree_mul_le (p q : R[X]) : degree (p * q) ≤ degree p + degree q := by simpa only [degree, ← support_toFinsupp, toFinsupp_mul] using AddMonoidAlgebra.sup_support_mul_le (WithBot.coe_add _ _).le _ _ theorem degree_mul_le_of_le {a b : WithBot ℕ} (hp : degree p ≤ a) (hq : degree q ≤ b) : degree (p * q) ≤ a + b := (p.degree_mul_le _).trans <| add_le_add ‹_› ‹_› theorem degree_pow_le (p : R[X]) : ∀ n : ℕ, degree (p ^ n) ≤ n • degree p | 0 => by rw [pow_zero, zero_nsmul]; exact degree_one_le | n + 1 => calc degree (p ^ (n + 1)) ≤ degree (p ^ n) + degree p := by rw [pow_succ]; exact degree_mul_le _ _ _ ≤ _ := by rw [succ_nsmul]; exact add_le_add_right (degree_pow_le _ _) _ theorem degree_pow_le_of_le {a : WithBot ℕ} (b : ℕ) (hp : degree p ≤ a) : degree (p ^ b) ≤ b * a := by induction b with | zero => simp [degree_one_le] | succ n hn => rw [Nat.cast_succ, add_mul, one_mul, pow_succ] exact degree_mul_le_of_le hn hp @[simp] theorem leadingCoeff_monomial (a : R) (n : ℕ) : leadingCoeff (monomial n a) = a := by classical by_cases ha : a = 0 · simp only [ha, (monomial n).map_zero, leadingCoeff_zero] · rw [leadingCoeff, natDegree_monomial, if_neg ha, coeff_monomial] simp theorem leadingCoeff_C_mul_X_pow (a : R) (n : ℕ) : leadingCoeff (C a * X ^ n) = a := by rw [C_mul_X_pow_eq_monomial, leadingCoeff_monomial] theorem leadingCoeff_C_mul_X (a : R) : leadingCoeff (C a * X) = a := by simpa only [pow_one] using leadingCoeff_C_mul_X_pow a 1 @[simp] theorem leadingCoeff_C (a : R) : leadingCoeff (C a) = a := leadingCoeff_monomial a 0 theorem leadingCoeff_X_pow (n : ℕ) : leadingCoeff ((X : R[X]) ^ n) = 1 := by simpa only [C_1, one_mul] using leadingCoeff_C_mul_X_pow (1 : R) n theorem leadingCoeff_X : leadingCoeff (X : R[X]) = 1 := by simpa only [pow_one] using @leadingCoeff_X_pow R _ 1 @[simp] theorem monic_X_pow (n : ℕ) : Monic (X ^ n : R[X]) := leadingCoeff_X_pow n @[simp] theorem monic_X : Monic (X : R[X]) := leadingCoeff_X theorem leadingCoeff_one : leadingCoeff (1 : R[X]) = 1 := leadingCoeff_C 1 @[simp] theorem monic_one : Monic (1 : R[X]) := leadingCoeff_C _ theorem Monic.ne_zero {R : Type*} [Semiring R] [Nontrivial R] {p : R[X]} (hp : p.Monic) : p ≠ 0 := by rintro rfl simp [Monic] at hp theorem Monic.ne_zero_of_ne (h : (0 : R) ≠ 1) {p : R[X]} (hp : p.Monic) : p ≠ 0 := by nontriviality R exact hp.ne_zero theorem Monic.ne_zero_of_polynomial_ne {r} (hp : Monic p) (hne : q ≠ r) : p ≠ 0 := haveI := Nontrivial.of_polynomial_ne hne hp.ne_zero theorem natDegree_mul_le {p q : R[X]} : natDegree (p * q) ≤ natDegree p + natDegree q := by apply natDegree_le_of_degree_le apply le_trans (degree_mul_le p q) rw [Nat.cast_add] apply add_le_add <;> apply degree_le_natDegree theorem natDegree_mul_le_of_le (hp : natDegree p ≤ m) (hg : natDegree q ≤ n) : natDegree (p * q) ≤ m + n := natDegree_mul_le.trans <| add_le_add ‹_› ‹_› theorem natDegree_pow_le {p : R[X]} {n : ℕ} : (p ^ n).natDegree ≤ n * p.natDegree := by induction n with | zero => simp | succ i hi => rw [pow_succ, Nat.succ_mul] apply le_trans natDegree_mul_le (add_le_add_right hi _) theorem natDegree_pow_le_of_le (n : ℕ) (hp : natDegree p ≤ m) : natDegree (p ^ n) ≤ n * m := natDegree_pow_le.trans (Nat.mul_le_mul le_rfl ‹_›) theorem natDegree_eq_zero_iff_degree_le_zero : p.natDegree = 0 ↔ p.degree ≤ 0 := by rw [← nonpos_iff_eq_zero, natDegree_le_iff_degree_le, Nat.cast_zero] theorem degree_zero_le : degree (0 : R[X]) ≤ 0 := natDegree_eq_zero_iff_degree_le_zero.mp rfl theorem degree_le_iff_coeff_zero (f : R[X]) (n : WithBot ℕ) : degree f ≤ n ↔ ∀ m : ℕ, n < m → coeff f m = 0 := by simp only [degree, Finset.max, Finset.sup_le_iff, mem_support_iff, Ne, ← not_le, not_imp_comm, Nat.cast_withBot] theorem degree_lt_iff_coeff_zero (f : R[X]) (n : ℕ) : degree f < n ↔ ∀ m : ℕ, n ≤ m → coeff f m = 0 := by simp only [degree, Finset.sup_lt_iff (WithBot.bot_lt_coe n), mem_support_iff, WithBot.coe_lt_coe, ← @not_le ℕ, max_eq_sup_coe, Nat.cast_withBot, Ne, not_imp_not] theorem natDegree_pos_iff_degree_pos : 0 < natDegree p ↔ 0 < degree p := lt_iff_lt_of_le_iff_le natDegree_le_iff_degree_le end Semiring section NontrivialSemiring variable [Semiring R] [Nontrivial R] {p q : R[X]} (n : ℕ) @[simp] theorem degree_X_pow : degree ((X : R[X]) ^ n) = n := by rw [X_pow_eq_monomial, degree_monomial _ (one_ne_zero' R)] @[simp] theorem natDegree_X_pow : natDegree ((X : R[X]) ^ n) = n := natDegree_eq_of_degree_eq_some (degree_X_pow n) end NontrivialSemiring section Ring variable [Ring R] {p q : R[X]} theorem degree_sub_le (p q : R[X]) : degree (p - q) ≤ max (degree p) (degree q) := by simpa only [degree_neg q] using degree_add_le p (-q) theorem degree_sub_le_of_le {a b : WithBot ℕ} (hp : degree p ≤ a) (hq : degree q ≤ b) : degree (p - q) ≤ max a b := (p.degree_sub_le q).trans <| max_le_max ‹_› ‹_› theorem natDegree_sub_le (p q : R[X]) : natDegree (p - q) ≤ max (natDegree p) (natDegree q) := by simpa only [← natDegree_neg q] using natDegree_add_le p (-q) theorem natDegree_sub_le_of_le (hp : natDegree p ≤ m) (hq : natDegree q ≤ n) : natDegree (p - q) ≤ max m n := (p.natDegree_sub_le q).trans <| max_le_max ‹_› ‹_› theorem degree_sub_lt (hd : degree p = degree q) (hp0 : p ≠ 0) (hlc : leadingCoeff p = leadingCoeff q) : degree (p - q) < degree p := have hp : monomial (natDegree p) (leadingCoeff p) + p.erase (natDegree p) = p := monomial_add_erase _ _ have hq : monomial (natDegree q) (leadingCoeff q) + q.erase (natDegree q) = q := monomial_add_erase _ _ have hd' : natDegree p = natDegree q := by unfold natDegree; rw [hd] have hq0 : q ≠ 0 := mt degree_eq_bot.2 (hd ▸ mt degree_eq_bot.1 hp0) calc degree (p - q) = degree (erase (natDegree q) p + -erase (natDegree q) q) := by conv => lhs rw [← hp, ← hq, hlc, hd', add_sub_add_left_eq_sub, sub_eq_add_neg] _ ≤ max (degree (erase (natDegree q) p)) (degree (erase (natDegree q) q)) := (degree_neg (erase (natDegree q) q) ▸ degree_add_le _ _) _ < degree p := max_lt_iff.2 ⟨hd' ▸ degree_erase_lt hp0, hd.symm ▸ degree_erase_lt hq0⟩ theorem degree_X_sub_C_le (r : R) : (X - C r).degree ≤ 1 := (degree_sub_le _ _).trans (max_le degree_X_le (degree_C_le.trans zero_le_one)) theorem natDegree_X_sub_C_le (r : R) : (X - C r).natDegree ≤ 1 := natDegree_le_iff_degree_le.2 <| degree_X_sub_C_le r end Ring end Polynomial
Mathlib/Algebra/Polynomial/Degree/Definitions.lean
1,640
1,641
/- Copyright (c) 2021 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Data.Matrix.Basis import Mathlib.Data.Matrix.DMatrix import Mathlib.LinearAlgebra.Matrix.Determinant.Basic import Mathlib.LinearAlgebra.Matrix.Reindex import Mathlib.Tactic.FieldSimp /-! # Transvections Transvections are matrices of the form `1 + stdBasisMatrix i j c`, where `stdBasisMatrix i j c` is the basic matrix with a `c` at position `(i, j)`. Multiplying by such a transvection on the left (resp. on the right) amounts to adding `c` times the `j`-th row to the `i`-th row (resp `c` times the `i`-th column to the `j`-th column). Therefore, they are useful to present algorithms operating on rows and columns. Transvections are a special case of *elementary matrices* (according to most references, these also contain the matrices exchanging rows, and the matrices multiplying a row by a constant). We show that, over a field, any matrix can be written as `L * D * L'`, where `L` and `L'` are products of transvections and `D` is diagonal. In other words, one can reduce a matrix to diagonal form by operations on its rows and columns, a variant of Gauss' pivot algorithm. ## Main definitions and results * `transvection i j c` is the matrix equal to `1 + stdBasisMatrix i j c`. * `TransvectionStruct n R` is a structure containing the data of `i, j, c` and a proof that `i ≠ j`. These are often easier to manipulate than straight matrices, especially in inductive arguments. * `exists_list_transvec_mul_diagonal_mul_list_transvec` states that any matrix `M` over a field can be written in the form `t_1 * ... * t_k * D * t'_1 * ... * t'_l`, where `D` is diagonal and the `t_i`, `t'_j` are transvections. * `diagonal_transvection_induction` shows that a property which is true for diagonal matrices and transvections, and invariant under product, is true for all matrices. * `diagonal_transvection_induction_of_det_ne_zero` is the same statement over invertible matrices. ## Implementation details The proof of the reduction results is done inductively on the size of the matrices, reducing an `(r + 1) × (r + 1)` matrix to a matrix whose last row and column are zeroes, except possibly for the last diagonal entry. This step is done as follows. If all the coefficients on the last row and column are zero, there is nothing to do. Otherwise, one can put a nonzero coefficient in the last diagonal entry by a row or column operation, and then subtract this last diagonal entry from the other entries in the last row and column to make them vanish. This step is done in the type `Fin r ⊕ Unit`, where `Fin r` is useful to choose arbitrarily some order in which we cancel the coefficients, and the sum structure is useful to use the formalism of block matrices. To proceed with the induction, we reindex our matrices to reduce to the above situation. -/ universe u₁ u₂ namespace Matrix variable (n p : Type*) (R : Type u₂) {𝕜 : Type*} [Field 𝕜] variable [DecidableEq n] [DecidableEq p] variable [CommRing R] section Transvection variable {R n} (i j : n) /-- The transvection matrix `transvection i j c` is equal to the identity plus `c` at position `(i, j)`. Multiplying by it on the left (as in `transvection i j c * M`) corresponds to adding `c` times the `j`-th row of `M` to its `i`-th row. Multiplying by it on the right corresponds to adding `c` times the `i`-th column to the `j`-th column. -/ def transvection (c : R) : Matrix n n R := 1 + Matrix.stdBasisMatrix i j c @[simp] theorem transvection_zero : transvection i j (0 : R) = 1 := by simp [transvection] section /-- A transvection matrix is obtained from the identity by adding `c` times the `j`-th row to the `i`-th row. -/ theorem updateRow_eq_transvection [Finite n] (c : R) : updateRow (1 : Matrix n n R) i ((1 : Matrix n n R) i + c • (1 : Matrix n n R) j) = transvection i j c := by cases nonempty_fintype n ext a b by_cases ha : i = a · by_cases hb : j = b · simp only [ha, updateRow_self, Pi.add_apply, one_apply, Pi.smul_apply, hb, ↓reduceIte, smul_eq_mul, mul_one, transvection, add_apply, StdBasisMatrix.apply_same] · simp only [ha, updateRow_self, Pi.add_apply, one_apply, Pi.smul_apply, hb, ↓reduceIte, smul_eq_mul, mul_zero, add_zero, transvection, add_apply, and_false, not_false_eq_true, StdBasisMatrix.apply_of_ne] · simp only [updateRow_ne, transvection, ha, Ne.symm ha, StdBasisMatrix.apply_of_ne, add_zero, Algebra.id.smul_eq_mul, Ne, not_false_iff, DMatrix.add_apply, Pi.smul_apply, mul_zero, false_and, add_apply] variable [Fintype n] theorem transvection_mul_transvection_same (h : i ≠ j) (c d : R) : transvection i j c * transvection i j d = transvection i j (c + d) := by simp [transvection, Matrix.add_mul, Matrix.mul_add, h, h.symm, add_smul, add_assoc, stdBasisMatrix_add] @[simp] theorem transvection_mul_apply_same (b : n) (c : R) (M : Matrix n n R) : (transvection i j c * M) i b = M i b + c * M j b := by simp [transvection, Matrix.add_mul] @[simp] theorem mul_transvection_apply_same (a : n) (c : R) (M : Matrix n n R) : (M * transvection i j c) a j = M a j + c * M a i := by simp [transvection, Matrix.mul_add, mul_comm] @[simp] theorem transvection_mul_apply_of_ne (a b : n) (ha : a ≠ i) (c : R) (M : Matrix n n R) : (transvection i j c * M) a b = M a b := by simp [transvection, Matrix.add_mul, ha] @[simp] theorem mul_transvection_apply_of_ne (a b : n) (hb : b ≠ j) (c : R) (M : Matrix n n R) : (M * transvection i j c) a b = M a b := by simp [transvection, Matrix.mul_add, hb] @[simp] theorem det_transvection_of_ne (h : i ≠ j) (c : R) : det (transvection i j c) = 1 := by rw [← updateRow_eq_transvection i j, det_updateRow_add_smul_self _ h, det_one] end variable (R n) /-- A structure containing all the information from which one can build a nontrivial transvection. This structure is easier to manipulate than transvections as one has a direct access to all the relevant fields. -/ structure TransvectionStruct where (i j : n) hij : i ≠ j c : R instance [Nontrivial n] : Nonempty (TransvectionStruct n R) := by choose x y hxy using exists_pair_ne n exact ⟨⟨x, y, hxy, 0⟩⟩ namespace TransvectionStruct variable {R n} /-- Associating to a `transvection_struct` the corresponding transvection matrix. -/ def toMatrix (t : TransvectionStruct n R) : Matrix n n R := transvection t.i t.j t.c @[simp] theorem toMatrix_mk (i j : n) (hij : i ≠ j) (c : R) : TransvectionStruct.toMatrix ⟨i, j, hij, c⟩ = transvection i j c := rfl @[simp] protected theorem det [Fintype n] (t : TransvectionStruct n R) : det t.toMatrix = 1 := det_transvection_of_ne _ _ t.hij _ @[simp] theorem det_toMatrix_prod [Fintype n] (L : List (TransvectionStruct n 𝕜)) : det (L.map toMatrix).prod = 1 := by induction L with | nil => simp | cons _ _ IH => simp [IH] /-- The inverse of a `TransvectionStruct`, designed so that `t.inv.toMatrix` is the inverse of `t.toMatrix`. -/ @[simps] protected def inv (t : TransvectionStruct n R) : TransvectionStruct n R where i := t.i j := t.j hij := t.hij c := -t.c section variable [Fintype n] theorem inv_mul (t : TransvectionStruct n R) : t.inv.toMatrix * t.toMatrix = 1 := by rcases t with ⟨_, _, t_hij⟩ simp [toMatrix, transvection_mul_transvection_same, t_hij] theorem mul_inv (t : TransvectionStruct n R) : t.toMatrix * t.inv.toMatrix = 1 := by rcases t with ⟨_, _, t_hij⟩ simp [toMatrix, transvection_mul_transvection_same, t_hij] theorem reverse_inv_prod_mul_prod (L : List (TransvectionStruct n R)) : (L.reverse.map (toMatrix ∘ TransvectionStruct.inv)).prod * (L.map toMatrix).prod = 1 := by induction L with | nil => simp | cons t L IH => suffices (L.reverse.map (toMatrix ∘ TransvectionStruct.inv)).prod * (t.inv.toMatrix * t.toMatrix) * (L.map toMatrix).prod = 1 by simpa [Matrix.mul_assoc] simpa [inv_mul] using IH theorem prod_mul_reverse_inv_prod (L : List (TransvectionStruct n R)) : (L.map toMatrix).prod * (L.reverse.map (toMatrix ∘ TransvectionStruct.inv)).prod = 1 := by induction L with | nil => simp | cons t L IH => suffices t.toMatrix * ((L.map toMatrix).prod * (L.reverse.map (toMatrix ∘ TransvectionStruct.inv)).prod) * t.inv.toMatrix = 1 by simpa [Matrix.mul_assoc] simp_rw [IH, Matrix.mul_one, t.mul_inv] /-- `M` is a scalar matrix if it commutes with every nontrivial transvection (elementary matrix). -/ theorem _root_.Matrix.mem_range_scalar_of_commute_transvectionStruct {M : Matrix n n R} (hM : ∀ t : TransvectionStruct n R, Commute t.toMatrix M) : M ∈ Set.range (Matrix.scalar n) := by refine mem_range_scalar_of_commute_stdBasisMatrix ?_ intro i j hij simpa [transvection, mul_add, add_mul] using (hM ⟨i, j, hij, 1⟩).eq theorem _root_.Matrix.mem_range_scalar_iff_commute_transvectionStruct {M : Matrix n n R} : M ∈ Set.range (Matrix.scalar n) ↔ ∀ t : TransvectionStruct n R, Commute t.toMatrix M := by refine ⟨fun h t => ?_, mem_range_scalar_of_commute_transvectionStruct⟩ rw [mem_range_scalar_iff_commute_stdBasisMatrix] at h refine (Commute.one_left M).add_left ?_ convert (h _ _ t.hij).smul_left t.c using 1 rw [smul_stdBasisMatrix, smul_eq_mul, mul_one] end open Sum /-- Given a `TransvectionStruct` on `n`, define the corresponding `TransvectionStruct` on `n ⊕ p` using the identity on `p`. -/ def sumInl (t : TransvectionStruct n R) : TransvectionStruct (n ⊕ p) R where i := inl t.i j := inl t.j hij := by simp [t.hij] c := t.c theorem toMatrix_sumInl (t : TransvectionStruct n R) : (t.sumInl p).toMatrix = fromBlocks t.toMatrix 0 0 1 := by cases t ext a b rcases a with a | a <;> rcases b with b | b · by_cases h : a = b <;> simp [TransvectionStruct.sumInl, transvection, h, stdBasisMatrix] · simp [TransvectionStruct.sumInl, transvection] · simp [TransvectionStruct.sumInl, transvection] · by_cases h : a = b <;> simp [TransvectionStruct.sumInl, transvection, h] @[simp] theorem sumInl_toMatrix_prod_mul [Fintype n] [Fintype p] (M : Matrix n n R) (L : List (TransvectionStruct n R)) (N : Matrix p p R) : (L.map (toMatrix ∘ sumInl p)).prod * fromBlocks M 0 0 N = fromBlocks ((L.map toMatrix).prod * M) 0 0 N := by induction L with | nil => simp | cons t L IH => simp [Matrix.mul_assoc, IH, toMatrix_sumInl, fromBlocks_multiply] @[simp] theorem mul_sumInl_toMatrix_prod [Fintype n] [Fintype p] (M : Matrix n n R) (L : List (TransvectionStruct n R)) (N : Matrix p p R) : fromBlocks M 0 0 N * (L.map (toMatrix ∘ sumInl p)).prod = fromBlocks (M * (L.map toMatrix).prod) 0 0 N := by induction L generalizing M N with | nil => simp | cons t L IH => simp [IH, toMatrix_sumInl, fromBlocks_multiply] variable {p} /-- Given a `TransvectionStruct` on `n` and an equivalence between `n` and `p`, define the corresponding `TransvectionStruct` on `p`. -/ def reindexEquiv (e : n ≃ p) (t : TransvectionStruct n R) : TransvectionStruct p R where i := e t.i j := e t.j hij := by simp [t.hij] c := t.c variable [Fintype n] [Fintype p] theorem toMatrix_reindexEquiv (e : n ≃ p) (t : TransvectionStruct n R) : (t.reindexEquiv e).toMatrix = reindexAlgEquiv R _ e t.toMatrix := by rcases t with ⟨t_i, t_j, _⟩ ext a b simp only [reindexEquiv, transvection, mul_boole, Algebra.id.smul_eq_mul, toMatrix_mk, submatrix_apply, reindex_apply, DMatrix.add_apply, Pi.smul_apply, reindexAlgEquiv_apply] by_cases ha : e t_i = a <;> by_cases hb : e t_j = b <;> by_cases hab : a = b <;> simp [ha, hb, hab, ← e.apply_eq_iff_eq_symm_apply, stdBasisMatrix] theorem toMatrix_reindexEquiv_prod (e : n ≃ p) (L : List (TransvectionStruct n R)) : (L.map (toMatrix ∘ reindexEquiv e)).prod = reindexAlgEquiv R _ e (L.map toMatrix).prod := by induction L with | nil => simp | cons t L IH => simp only [toMatrix_reindexEquiv, IH, Function.comp_apply, List.prod_cons, reindexAlgEquiv_apply, List.map] exact (reindexAlgEquiv_mul R _ _ _ _).symm end TransvectionStruct end Transvection /-! # Reducing matrices by left and right multiplication by transvections In this section, we show that any matrix can be reduced to diagonal form by left and right multiplication by transvections (or, equivalently, by elementary operations on lines and columns). The main step is to kill the last row and column of a matrix in `Fin r ⊕ Unit` with nonzero last coefficient, by subtracting this coefficient from the other ones. The list of these operations is recorded in `list_transvec_col M` and `list_transvec_row M`. We have to analyze inductively how these operations affect the coefficients in the last row and the last column to conclude that they have the desired effect. Once this is done, one concludes the reduction by induction on the size of the matrices, through a suitable reindexing to identify any fintype with `Fin r ⊕ Unit`. -/ namespace Pivot variable {R} {r : ℕ} (M : Matrix (Fin r ⊕ Unit) (Fin r ⊕ Unit) 𝕜) open Unit Sum Fin TransvectionStruct /-- A list of transvections such that multiplying on the left with these transvections will replace the last column with zeroes. -/ def listTransvecCol : List (Matrix (Fin r ⊕ Unit) (Fin r ⊕ Unit) 𝕜) := List.ofFn fun i : Fin r => transvection (inl i) (inr unit) <| -M (inl i) (inr unit) / M (inr unit) (inr unit) /-- A list of transvections such that multiplying on the right with these transvections will replace the last row with zeroes. -/ def listTransvecRow : List (Matrix (Fin r ⊕ Unit) (Fin r ⊕ Unit) 𝕜) := List.ofFn fun i : Fin r => transvection (inr unit) (inl i) <| -M (inr unit) (inl i) / M (inr unit) (inr unit) @[simp] theorem length_listTransvecCol : (listTransvecCol M).length = r := by simp [listTransvecCol] theorem listTransvecCol_getElem {i : ℕ} (h : i < (listTransvecCol M).length) : (listTransvecCol M)[i] = letI i' : Fin r := ⟨i, length_listTransvecCol M ▸ h⟩ transvection (inl i') (inr unit) <| -M (inl i') (inr unit) / M (inr unit) (inr unit) := by simp [listTransvecCol] @[simp] theorem length_listTransvecRow : (listTransvecRow M).length = r := by simp [listTransvecRow] theorem listTransvecRow_getElem {i : ℕ} (h : i < (listTransvecRow M).length) : (listTransvecRow M)[i] = letI i' : Fin r := ⟨i, length_listTransvecRow M ▸ h⟩ transvection (inr unit) (inl i') <| -M (inr unit) (inl i') / M (inr unit) (inr unit) := by simp [listTransvecRow, Fin.cast] /-- Multiplying by some of the matrices in `listTransvecCol M` does not change the last row. -/ theorem listTransvecCol_mul_last_row_drop (i : Fin r ⊕ Unit) {k : ℕ} (hk : k ≤ r) : (((listTransvecCol M).drop k).prod * M) (inr unit) i = M (inr unit) i := by induction hk using Nat.decreasingInduction with | of_succ n hn IH => have hn' : n < (listTransvecCol M).length := by simpa [listTransvecCol] using hn rw [List.drop_eq_getElem_cons hn'] simpa [listTransvecCol, Matrix.mul_assoc] | self => simp only [length_listTransvecCol, le_refl, List.drop_eq_nil_of_le, List.prod_nil, Matrix.one_mul] /-- Multiplying by all the matrices in `listTransvecCol M` does not change the last row. -/ theorem listTransvecCol_mul_last_row (i : Fin r ⊕ Unit) : ((listTransvecCol M).prod * M) (inr unit) i = M (inr unit) i := by simpa using listTransvecCol_mul_last_row_drop M i (zero_le _) /-- Multiplying by all the matrices in `listTransvecCol M` kills all the coefficients in the last column but the last one. -/ theorem listTransvecCol_mul_last_col (hM : M (inr unit) (inr unit) ≠ 0) (i : Fin r) : ((listTransvecCol M).prod * M) (inl i) (inr unit) = 0 := by suffices H : ∀ k : ℕ, k ≤ r → (((listTransvecCol M).drop k).prod * M) (inl i) (inr unit) = if k ≤ i then 0 else M (inl i) (inr unit) by simpa only [List.drop, _root_.zero_le, ite_true] using H 0 (zero_le _) intro k hk induction hk using Nat.decreasingInduction with | of_succ n hn IH => have hn' : n < (listTransvecCol M).length := by simpa [listTransvecCol] using hn let n' : Fin r := ⟨n, hn⟩ rw [List.drop_eq_getElem_cons hn'] have A : (listTransvecCol M)[n] = transvection (inl n') (inr unit) (-M (inl n') (inr unit) / M (inr unit) (inr unit)) := by simp [n', listTransvecCol] simp only [Matrix.mul_assoc, A, List.prod_cons] by_cases h : n' = i · have hni : n = i := by cases i simp only [n', Fin.mk_eq_mk] at h simp [h] simp only [h, transvection_mul_apply_same, IH, ← hni, add_le_iff_nonpos_right, listTransvecCol_mul_last_row_drop _ _ hn] field_simp [hM] · have hni : n ≠ i := by rintro rfl cases i simp [n'] at h simp only [ne_eq, inl.injEq, Ne.symm h, not_false_eq_true, transvection_mul_apply_of_ne] rw [IH] rcases le_or_lt (n + 1) i with (hi | hi) · simp only [hi, n.le_succ.trans hi, if_true] · rw [if_neg, if_neg] · simpa only [hni.symm, not_le, or_false] using Nat.lt_succ_iff_lt_or_eq.1 hi · simpa only [not_le] using hi | self => simp only [length_listTransvecCol, le_refl, List.drop_eq_nil_of_le, List.prod_nil, Matrix.one_mul] rw [if_neg] simpa only [not_le] using i.2 /-- Multiplying by some of the matrices in `listTransvecRow M` does not change the last column. -/ theorem mul_listTransvecRow_last_col_take (i : Fin r ⊕ Unit) {k : ℕ} (hk : k ≤ r) : (M * ((listTransvecRow M).take k).prod) i (inr unit) = M i (inr unit) := by induction k with | zero => simp only [Matrix.mul_one, List.take_zero, List.prod_nil, List.take, Matrix.mul_one] | succ k IH => have hkr : k < r := hk let k' : Fin r := ⟨k, hkr⟩ have : (listTransvecRow M)[k]? = ↑(transvection (inr Unit.unit) (inl k') (-M (inr Unit.unit) (inl k') / M (inr Unit.unit) (inr Unit.unit))) := by simp only [k', listTransvecRow, List.ofFnNthVal, hkr, dif_pos, List.getElem?_ofFn] simp only [List.take_succ, ← Matrix.mul_assoc, this, List.prod_append, Matrix.mul_one, List.prod_cons, List.prod_nil, Option.toList_some] rw [mul_transvection_apply_of_ne, IH hkr.le] simp only [Ne, not_false_iff, reduceCtorEq] /-- Multiplying by all the matrices in `listTransvecRow M` does not change the last column. -/ theorem mul_listTransvecRow_last_col (i : Fin r ⊕ Unit) : (M * (listTransvecRow M).prod) i (inr unit) = M i (inr unit) := by have A : (listTransvecRow M).length = r := by simp [listTransvecRow] rw [← List.take_length (l := listTransvecRow M), A] simpa using mul_listTransvecRow_last_col_take M i le_rfl /-- Multiplying by all the matrices in `listTransvecRow M` kills all the coefficients in the last row but the last one. -/ theorem mul_listTransvecRow_last_row (hM : M (inr unit) (inr unit) ≠ 0) (i : Fin r) : (M * (listTransvecRow M).prod) (inr unit) (inl i) = 0 := by suffices H : ∀ k : ℕ, k ≤ r → (M * ((listTransvecRow M).take k).prod) (inr unit) (inl i) = if k ≤ i then M (inr unit) (inl i) else 0 by have A : (listTransvecRow M).length = r := by simp [listTransvecRow] rw [← List.take_length (l := listTransvecRow M), A] have : ¬r ≤ i := by simp simpa only [this, ite_eq_right_iff] using H r le_rfl intro k hk induction k with | zero => simp only [if_true, Matrix.mul_one, List.take_zero, zero_le', List.prod_nil] | succ n IH => have hnr : n < r := hk let n' : Fin r := ⟨n, hnr⟩ have A : (listTransvecRow M)[n]? = ↑(transvection (inr unit) (inl n') (-M (inr unit) (inl n') / M (inr unit) (inr unit))) := by simp only [n', listTransvecRow, List.ofFnNthVal, hnr, dif_pos, List.getElem?_ofFn] simp only [List.take_succ, A, ← Matrix.mul_assoc, List.prod_append, Matrix.mul_one, List.prod_cons, List.prod_nil, Option.toList_some] by_cases h : n' = i · have hni : n = i := by cases i simp only [n', Fin.mk_eq_mk] at h simp only [h] have : ¬n.succ ≤ i := by simp only [← hni, n.lt_succ_self, not_le] simp only [h, mul_transvection_apply_same, List.take, if_false, mul_listTransvecRow_last_col_take _ _ hnr.le, hni.le, this, if_true, IH hnr.le] field_simp [hM] · have hni : n ≠ i := by rintro rfl cases i tauto simp only [IH hnr.le, Ne, mul_transvection_apply_of_ne, Ne.symm h, inl.injEq, not_false_eq_true] rcases le_or_lt (n + 1) i with (hi | hi) · simp [hi, n.le_succ.trans hi, if_true] · rw [if_neg, if_neg] · simpa only [not_le] using hi · simpa only [hni.symm, not_le, or_false] using Nat.lt_succ_iff_lt_or_eq.1 hi /-- Multiplying by all the matrices either in `listTransvecCol M` and `listTransvecRow M` kills all the coefficients in the last row but the last one. -/ theorem listTransvecCol_mul_mul_listTransvecRow_last_col (hM : M (inr unit) (inr unit) ≠ 0) (i : Fin r) : ((listTransvecCol M).prod * M * (listTransvecRow M).prod) (inr unit) (inl i) = 0 := by have : listTransvecRow M = listTransvecRow ((listTransvecCol M).prod * M) := by simp [listTransvecRow, listTransvecCol_mul_last_row] rw [this] apply mul_listTransvecRow_last_row simpa [listTransvecCol_mul_last_row] using hM /-- Multiplying by all the matrices either in `listTransvecCol M` and `listTransvecRow M` kills all the coefficients in the last column but the last one. -/ theorem listTransvecCol_mul_mul_listTransvecRow_last_row (hM : M (inr unit) (inr unit) ≠ 0) (i : Fin r) : ((listTransvecCol M).prod * M * (listTransvecRow M).prod) (inl i) (inr unit) = 0 := by have : listTransvecCol M = listTransvecCol (M * (listTransvecRow M).prod) := by simp [listTransvecCol, mul_listTransvecRow_last_col] rw [this, Matrix.mul_assoc] apply listTransvecCol_mul_last_col simpa [mul_listTransvecRow_last_col] using hM /-- Multiplying by all the matrices either in `listTransvecCol M` and `listTransvecRow M` turns the matrix in block-diagonal form. -/ theorem isTwoBlockDiagonal_listTransvecCol_mul_mul_listTransvecRow (hM : M (inr unit) (inr unit) ≠ 0) : IsTwoBlockDiagonal ((listTransvecCol M).prod * M * (listTransvecRow M).prod) := by constructor · ext i j have : j = unit := by simp only [eq_iff_true_of_subsingleton] simp [toBlocks₁₂, this, listTransvecCol_mul_mul_listTransvecRow_last_row M hM] · ext i j have : i = unit := by simp only [eq_iff_true_of_subsingleton] simp [toBlocks₂₁, this, listTransvecCol_mul_mul_listTransvecRow_last_col M hM] /-- There exist two lists of `TransvectionStruct` such that multiplying by them on the left and on the right makes a matrix block-diagonal, when the last coefficient is nonzero. -/ theorem exists_isTwoBlockDiagonal_of_ne_zero (hM : M (inr unit) (inr unit) ≠ 0) : ∃ L L' : List (TransvectionStruct (Fin r ⊕ Unit) 𝕜), IsTwoBlockDiagonal ((L.map toMatrix).prod * M * (L'.map toMatrix).prod) := by let L : List (TransvectionStruct (Fin r ⊕ Unit) 𝕜) := List.ofFn fun i : Fin r => ⟨inl i, inr unit, by simp, -M (inl i) (inr unit) / M (inr unit) (inr unit)⟩ let L' : List (TransvectionStruct (Fin r ⊕ Unit) 𝕜) := List.ofFn fun i : Fin r => ⟨inr unit, inl i, by simp, -M (inr unit) (inl i) / M (inr unit) (inr unit)⟩ refine ⟨L, L', ?_⟩ have A : L.map toMatrix = listTransvecCol M := by simp [L, listTransvecCol, Function.comp_def] have B : L'.map toMatrix = listTransvecRow M := by simp [L', listTransvecRow, Function.comp_def] rw [A, B] exact isTwoBlockDiagonal_listTransvecCol_mul_mul_listTransvecRow M hM /-- There exist two lists of `TransvectionStruct` such that multiplying by them on the left and on the right makes a matrix block-diagonal. -/ theorem exists_isTwoBlockDiagonal_list_transvec_mul_mul_list_transvec (M : Matrix (Fin r ⊕ Unit) (Fin r ⊕ Unit) 𝕜) : ∃ L L' : List (TransvectionStruct (Fin r ⊕ Unit) 𝕜), IsTwoBlockDiagonal ((L.map toMatrix).prod * M * (L'.map toMatrix).prod) := by by_cases H : IsTwoBlockDiagonal M · refine ⟨List.nil, List.nil, by simpa using H⟩ -- we have already proved this when the last coefficient is nonzero by_cases hM : M (inr unit) (inr unit) ≠ 0 · exact exists_isTwoBlockDiagonal_of_ne_zero M hM -- when the last coefficient is zero but there is a nonzero coefficient on the last row or the -- last column, we will first put this nonzero coefficient in last position, and then argue as -- above. push_neg at hM simp only [not_and_or, IsTwoBlockDiagonal, toBlocks₁₂, toBlocks₂₁, ← Matrix.ext_iff] at H have : ∃ i : Fin r, M (inl i) (inr unit) ≠ 0 ∨ M (inr unit) (inl i) ≠ 0 := by rcases H with H | H · contrapose! H rintro i ⟨⟩ exact (H i).1 · contrapose! H rintro ⟨⟩ j exact (H j).2 rcases this with ⟨i, h | h⟩ · let M' := transvection (inr Unit.unit) (inl i) 1 * M have hM' : M' (inr unit) (inr unit) ≠ 0 := by simpa [M', hM] rcases exists_isTwoBlockDiagonal_of_ne_zero M' hM' with ⟨L, L', hLL'⟩ rw [Matrix.mul_assoc] at hLL' refine ⟨L ++ [⟨inr unit, inl i, by simp, 1⟩], L', ?_⟩ simp only [List.map_append, List.prod_append, Matrix.mul_one, toMatrix_mk, List.prod_cons, List.prod_nil, List.map, Matrix.mul_assoc (L.map toMatrix).prod] exact hLL' · let M' := M * transvection (inl i) (inr unit) 1 have hM' : M' (inr unit) (inr unit) ≠ 0 := by simpa [M', hM] rcases exists_isTwoBlockDiagonal_of_ne_zero M' hM' with ⟨L, L', hLL'⟩ refine ⟨L, ⟨inl i, inr unit, by simp, 1⟩::L', ?_⟩ simp only [← Matrix.mul_assoc, toMatrix_mk, List.prod_cons, List.map] rw [Matrix.mul_assoc (L.map toMatrix).prod] exact hLL' /-- Inductive step for the reduction: if one knows that any size `r` matrix can be reduced to diagonal form by elementary operations, then one deduces it for matrices over `Fin r ⊕ Unit`. -/ theorem exists_list_transvec_mul_mul_list_transvec_eq_diagonal_induction (IH : ∀ M : Matrix (Fin r) (Fin r) 𝕜, ∃ (L₀ L₀' : List (TransvectionStruct (Fin r) 𝕜)) (D₀ : Fin r → 𝕜), (L₀.map toMatrix).prod * M * (L₀'.map toMatrix).prod = diagonal D₀) (M : Matrix (Fin r ⊕ Unit) (Fin r ⊕ Unit) 𝕜) : ∃ (L L' : List (TransvectionStruct (Fin r ⊕ Unit) 𝕜)) (D : Fin r ⊕ Unit → 𝕜), (L.map toMatrix).prod * M * (L'.map toMatrix).prod = diagonal D := by rcases exists_isTwoBlockDiagonal_list_transvec_mul_mul_list_transvec M with ⟨L₁, L₁', hM⟩ let M' := (L₁.map toMatrix).prod * M * (L₁'.map toMatrix).prod let M'' := toBlocks₁₁ M' rcases IH M'' with ⟨L₀, L₀', D₀, h₀⟩ set c := M' (inr unit) (inr unit) refine ⟨L₀.map (sumInl Unit) ++ L₁, L₁' ++ L₀'.map (sumInl Unit), Sum.elim D₀ fun _ => M' (inr unit) (inr unit), ?_⟩ suffices (L₀.map (toMatrix ∘ sumInl Unit)).prod * M' * (L₀'.map (toMatrix ∘ sumInl Unit)).prod = diagonal (Sum.elim D₀ fun _ => c) by simpa [M', c, Matrix.mul_assoc] have : M' = fromBlocks M'' 0 0 (diagonal fun _ => c) := by rw [← fromBlocks_toBlocks M', hM.1, hM.2] rfl rw [this] simp [h₀] variable {n p} [Fintype n] [Fintype p] /-- Reduction to diagonal form by elementary operations is invariant under reindexing. -/ theorem reindex_exists_list_transvec_mul_mul_list_transvec_eq_diagonal (M : Matrix p p 𝕜) (e : p ≃ n) (H : ∃ (L L' : List (TransvectionStruct n 𝕜)) (D : n → 𝕜), (L.map toMatrix).prod * Matrix.reindexAlgEquiv 𝕜 _ e M * (L'.map toMatrix).prod = diagonal D) : ∃ (L L' : List (TransvectionStruct p 𝕜)) (D : p → 𝕜), (L.map toMatrix).prod * M * (L'.map toMatrix).prod = diagonal D := by rcases H with ⟨L₀, L₀', D₀, h₀⟩ refine ⟨L₀.map (reindexEquiv e.symm), L₀'.map (reindexEquiv e.symm), D₀ ∘ e, ?_⟩ have : M = reindexAlgEquiv 𝕜 _ e.symm (reindexAlgEquiv 𝕜 _ e M) := by simp only [Equiv.symm_symm, submatrix_submatrix, reindex_apply, submatrix_id_id, Equiv.symm_comp_self, reindexAlgEquiv_apply] rw [this] simp only [toMatrix_reindexEquiv_prod, List.map_map, reindexAlgEquiv_apply] simp only [← reindexAlgEquiv_apply 𝕜, ← reindexAlgEquiv_mul, h₀] simp only [Equiv.symm_symm, reindex_apply, submatrix_diagonal_equiv, reindexAlgEquiv_apply] /-- Any matrix can be reduced to diagonal form by elementary operations. Formulated here on `Type 0` because we will make an induction using `Fin r`. See `exists_list_transvec_mul_mul_list_transvec_eq_diagonal` for the general version (which follows from this one and reindexing). -/ theorem exists_list_transvec_mul_mul_list_transvec_eq_diagonal_aux (n : Type) [Fintype n] [DecidableEq n] (M : Matrix n n 𝕜) : ∃ (L L' : List (TransvectionStruct n 𝕜)) (D : n → 𝕜), (L.map toMatrix).prod * M * (L'.map toMatrix).prod = diagonal D := by suffices ∀ cn, Fintype.card n = cn → ∃ (L L' : List (TransvectionStruct n 𝕜)) (D : n → 𝕜), (L.map toMatrix).prod * M * (L'.map toMatrix).prod = diagonal D by exact this _ rfl intro cn hn induction cn generalizing n M with | zero => refine ⟨List.nil, List.nil, fun _ => 1, ?_⟩ ext i j rw [Fintype.card_eq_zero_iff] at hn exact hn.elim' i | succ r IH => have e : n ≃ Fin r ⊕ Unit := by refine Fintype.equivOfCardEq ?_ rw [hn] rw [@Fintype.card_sum (Fin r) Unit _ _] simp apply reindex_exists_list_transvec_mul_mul_list_transvec_eq_diagonal M e apply exists_list_transvec_mul_mul_list_transvec_eq_diagonal_induction fun N => IH (Fin r) N (by simp) /-- Any matrix can be reduced to diagonal form by elementary operations. -/ theorem exists_list_transvec_mul_mul_list_transvec_eq_diagonal (M : Matrix n n 𝕜) : ∃ (L L' : List (TransvectionStruct n 𝕜)) (D : n → 𝕜), (L.map toMatrix).prod * M * (L'.map toMatrix).prod = diagonal D := by have e : n ≃ Fin (Fintype.card n) := Fintype.equivOfCardEq (by simp) apply reindex_exists_list_transvec_mul_mul_list_transvec_eq_diagonal M e apply exists_list_transvec_mul_mul_list_transvec_eq_diagonal_aux /-- Any matrix can be written as the product of transvections, a diagonal matrix, and transvections. -/ theorem exists_list_transvec_mul_diagonal_mul_list_transvec (M : Matrix n n 𝕜) : ∃ (L L' : List (TransvectionStruct n 𝕜)) (D : n → 𝕜), M = (L.map toMatrix).prod * diagonal D * (L'.map toMatrix).prod := by rcases exists_list_transvec_mul_mul_list_transvec_eq_diagonal M with ⟨L, L', D, h⟩ refine ⟨L.reverse.map TransvectionStruct.inv, L'.reverse.map TransvectionStruct.inv, D, ?_⟩ suffices M = (L.reverse.map (toMatrix ∘ TransvectionStruct.inv)).prod * (L.map toMatrix).prod * M * ((L'.map toMatrix).prod * (L'.reverse.map (toMatrix ∘ TransvectionStruct.inv)).prod) by simpa [← h, Matrix.mul_assoc] rw [reverse_inv_prod_mul_prod, prod_mul_reverse_inv_prod, Matrix.one_mul, Matrix.mul_one] end Pivot open Pivot TransvectionStruct variable {n} [Fintype n] /-- Induction principle for matrices based on transvections: if a property is true for all diagonal matrices, all transvections, and is stable under product, then it is true for all matrices. This is
the useful way to say that matrices are generated by diagonal matrices and transvections. We state a slightly more general version: to prove a property for a matrix `M`, it suffices to assume that the diagonal matrices we consider have the same determinant as `M`. This is useful to obtain similar principles for `SLₙ` or `GLₙ`. -/ theorem diagonal_transvection_induction (P : Matrix n n 𝕜 → Prop) (M : Matrix n n 𝕜) (hdiag : ∀ D : n → 𝕜, det (diagonal D) = det M → P (diagonal D)) (htransvec : ∀ t : TransvectionStruct n 𝕜, P t.toMatrix) (hmul : ∀ A B, P A → P B → P (A * B)) : P M := by rcases exists_list_transvec_mul_diagonal_mul_list_transvec M with ⟨L, L', D, h⟩ have PD : P (diagonal D) := hdiag D (by simp [h])
Mathlib/LinearAlgebra/Matrix/Transvection.lean
693
703
/- Copyright (c) 2024 Christian Merten. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Christian Merten -/ import Mathlib.CategoryTheory.Limits.Constructions.LimitsOfProductsAndEqualizers import Mathlib.CategoryTheory.Limits.FintypeCat import Mathlib.CategoryTheory.Limits.MonoCoprod import Mathlib.CategoryTheory.Limits.Shapes.ConcreteCategory import Mathlib.CategoryTheory.Limits.Shapes.Diagonal import Mathlib.CategoryTheory.SingleObj import Mathlib.Data.Finite.Card import Mathlib.Algebra.Equiv.TransferInstance /-! # Definition and basic properties of Galois categories We define the notion of a Galois category and a fiber functor as in SGA1, following the definitions in Lenstras notes (see below for a reference). ## Main definitions * `PreGaloisCategory` : defining properties of Galois categories not involving a fiber functor * `FiberFunctor` : a fiber functor from a `PreGaloisCategory` to `FintypeCat` * `GaloisCategory` : a `PreGaloisCategory` that admits a `FiberFunctor` * `IsConnected` : an object of a category is connected if it is not initial and does not have non-trivial subobjects ## Implementation details We mostly follow Def 3.1 in Lenstras notes. In axiom (G3) we omit the factorisation of morphisms in epimorphisms and monomorphisms as this is not needed for the proof of the fundamental theorem on Galois categories (and then follows from it). ## References * [lenstraGSchemes]: H. W. Lenstra. Galois theory for schemes. -/ universe u₁ u₂ v₁ v₂ w t namespace CategoryTheory open Limits Functor /-! A category `C` is a PreGalois category if it satisfies all properties of a Galois category in the sense of SGA1 that do not involve a fiber functor. A Galois category should furthermore admit a fiber functor. The only difference between `[PreGaloisCategory C] (F : C ⥤ FintypeCat) [FiberFunctor F]` and `[GaloisCategory C]` is that the former fixes one fiber functor `F`. -/ /-- Definition of a (Pre)Galois category. Lenstra, Def 3.1, (G1)-(G3) -/ class PreGaloisCategory (C : Type u₁) [Category.{u₂, u₁} C] : Prop where /-- `C` has a terminal object (G1). -/ hasTerminal : HasTerminal C := by infer_instance /-- `C` has pullbacks (G1). -/ hasPullbacks : HasPullbacks C := by infer_instance /-- `C` has finite coproducts (G2). -/ hasFiniteCoproducts : HasFiniteCoproducts C := by infer_instance /-- `C` has quotients by finite groups (G2). -/ hasQuotientsByFiniteGroups (G : Type u₂) [Group G] [Finite G] : HasColimitsOfShape (SingleObj G) C := by infer_instance /-- Every monomorphism in `C` induces an isomorphism on a direct summand (G3). -/ monoInducesIsoOnDirectSummand {X Y : C} (i : X ⟶ Y) [Mono i] : ∃ (Z : C) (u : Z ⟶ Y), Nonempty (IsColimit (BinaryCofan.mk i u)) namespace PreGaloisCategory /-- Definition of a fiber functor from a Galois category. Lenstra, Def 3.1, (G4)-(G6) -/ class FiberFunctor {C : Type u₁} [Category.{u₂, u₁} C] [PreGaloisCategory C] (F : C ⥤ FintypeCat.{w}) where /-- `F` preserves terminal objects (G4). -/ preservesTerminalObjects : PreservesLimitsOfShape (CategoryTheory.Discrete PEmpty.{1}) F := by infer_instance /-- `F` preserves pullbacks (G4). -/ preservesPullbacks : PreservesLimitsOfShape WalkingCospan F := by infer_instance /-- `F` preserves finite coproducts (G5). -/ preservesFiniteCoproducts : PreservesFiniteCoproducts F := by infer_instance /-- `F` preserves epimorphisms (G5). -/ preservesEpis : Functor.PreservesEpimorphisms F := by infer_instance /-- `F` preserves quotients by finite groups (G5). -/ preservesQuotientsByFiniteGroups (G : Type u₂) [Group G] [Finite G] : PreservesColimitsOfShape (SingleObj G) F := by infer_instance /-- `F` reflects isomorphisms (G6). -/ reflectsIsos : F.ReflectsIsomorphisms := by infer_instance /-- An object of a category `C` is connected if it is not initial and has no non-trivial subobjects. Lenstra, 3.12. -/ class IsConnected {C : Type u₁} [Category.{u₂, u₁} C] (X : C) : Prop where /-- `X` is not an initial object. -/ notInitial : IsInitial X → False /-- `X` has no non-trivial subobjects. -/ noTrivialComponent (Y : C) (i : Y ⟶ X) [Mono i] : (IsInitial Y → False) → IsIso i /-- A functor is said to preserve connectedness if whenever `X : C` is connected, also `F.obj X` is connected. -/ class PreservesIsConnected {C : Type u₁} [Category.{u₂, u₁} C] {D : Type v₁} [Category.{v₂, v₁} D] (F : C ⥤ D) : Prop where /-- `F.obj X` is connected if `X` is connected. -/ preserves : ∀ {X : C} [IsConnected X], IsConnected (F.obj X) section variable {C : Type u₁} [Category.{u₂, u₁} C] [PreGaloisCategory C] attribute [instance] hasTerminal hasPullbacks hasFiniteCoproducts hasQuotientsByFiniteGroups instance : HasFiniteLimits C := hasFiniteLimits_of_hasTerminal_and_pullbacks instance : HasBinaryProducts C := hasBinaryProducts_of_hasTerminal_and_pullbacks C instance : HasEqualizers C := hasEqualizers_of_hasPullbacks_and_binary_products -- A `PreGaloisCategory` has quotients by finite groups in arbitrary universes. -/ instance {G : Type*} [Group G] [Finite G] : HasColimitsOfShape (SingleObj G) C := by obtain ⟨G', hg, hf, ⟨e⟩⟩ := Finite.exists_type_univ_nonempty_mulEquiv G exact Limits.hasColimitsOfShape_of_equivalence e.toSingleObjEquiv.symm end namespace FiberFunctor variable {C : Type u₁} [Category.{u₂, u₁} C] {F : C ⥤ FintypeCat.{w}} [PreGaloisCategory C] [FiberFunctor F] attribute [instance] preservesTerminalObjects preservesPullbacks preservesEpis preservesFiniteCoproducts reflectsIsos preservesQuotientsByFiniteGroups noncomputable instance : ReflectsLimitsOfShape (Discrete PEmpty.{1}) F := reflectsLimitsOfShape_of_reflectsIsomorphisms noncomputable instance : ReflectsColimitsOfShape (Discrete PEmpty.{1}) F := reflectsColimitsOfShape_of_reflectsIsomorphisms noncomputable instance : PreservesFiniteLimits F := preservesFiniteLimits_of_preservesTerminal_and_pullbacks F /-- Fiber functors preserve quotients by finite groups in arbitrary universes. -/ instance {G : Type*} [Group G] [Finite G] : PreservesColimitsOfShape (SingleObj G) F := by choose G' hg hf he using Finite.exists_type_univ_nonempty_mulEquiv G exact Limits.preservesColimitsOfShape_of_equiv he.some.toSingleObjEquiv.symm F /-- Fiber functors reflect monomorphisms. -/ instance : ReflectsMonomorphisms F := ReflectsMonomorphisms.mk <| by intro X Y f _ haveI : IsIso (pullback.fst (F.map f) (F.map f)) := isIso_fst_of_mono (F.map f) haveI : IsIso (F.map (pullback.fst f f)) := by rw [← PreservesPullback.iso_hom_fst] exact IsIso.comp_isIso haveI : IsIso (pullback.fst f f) := isIso_of_reflects_iso (pullback.fst _ _) F exact (pullback.diagonal_isKernelPair f).mono_of_isIso_fst /-- Fiber functors are faithful. -/ instance : F.Faithful where map_injective {X Y} f g h := by haveI : IsIso (equalizer.ι (F.map f) (F.map g)) := equalizer.ι_of_eq h haveI : IsIso (F.map (equalizer.ι f g)) := by rw [← equalizerComparison_comp_π f g F] exact IsIso.comp_isIso haveI : IsIso (equalizer.ι f g) := isIso_of_reflects_iso _ F exact eq_of_epi_equalizer section /-- If `F` is a fiber functor and `E` is an equivalence between categories of finite types, then `F ⋙ E` is again a fiber functor. -/ lemma comp_right (E : FintypeCat.{w} ⥤ FintypeCat.{t}) [E.IsEquivalence] : FiberFunctor (F ⋙ E) where preservesQuotientsByFiniteGroups _ := comp_preservesColimitsOfShape F E end end FiberFunctor variable {C : Type u₁} [Category.{u₂, u₁} C] (F : C ⥤ FintypeCat.{w}) /-- The canonical action of `Aut F` on the fiber of each object. -/ instance (X : C) : MulAction (Aut F) (F.obj X) where smul σ x := σ.hom.app X x one_smul _ := rfl mul_smul _ _ _ := rfl lemma mulAction_def {X : C} (σ : Aut F) (x : F.obj X) : σ • x = σ.hom.app X x := rfl lemma mulAction_naturality {X Y : C} (σ : Aut F) (f : X ⟶ Y) (x : F.obj X) : σ • F.map f x = F.map f (σ • x) := FunctorToFintypeCat.naturality F F σ.hom f x /-- An object that is neither initial or connected has a non-trivial subobject. -/ lemma has_non_trivial_subobject_of_not_isConnected_of_not_initial (X : C) (hc : ¬ IsConnected X) (hi : IsInitial X → False) : ∃ (Y : C) (v : Y ⟶ X), (IsInitial Y → False) ∧ Mono v ∧ (¬ IsIso v) := by contrapose! hc exact ⟨hi, fun Y i hm hni ↦ hc Y i hni hm⟩ /-- The cardinality of the fiber is preserved under isomorphisms. -/ lemma card_fiber_eq_of_iso {X Y : C} (i : X ≅ Y) : Nat.card (F.obj X) = Nat.card (F.obj Y) := by have e : F.obj X ≃ F.obj Y := Iso.toEquiv (mapIso (F ⋙ FintypeCat.incl) i) exact Nat.card_eq_of_bijective e (Equiv.bijective e) variable [PreGaloisCategory C] [FiberFunctor F] /-- An object is initial if and only if its fiber is empty. -/ lemma initial_iff_fiber_empty (X : C) : Nonempty (IsInitial X) ↔ IsEmpty (F.obj X) := by rw [(IsInitial.isInitialIffObj F X).nonempty_congr] haveI : PreservesFiniteColimits (forget FintypeCat) := by show PreservesFiniteColimits FintypeCat.incl infer_instance haveI : ReflectsColimit (Functor.empty.{0} _) (forget FintypeCat) := by show ReflectsColimit (Functor.empty.{0} _) FintypeCat.incl infer_instance exact Concrete.initial_iff_empty_of_preserves_of_reflects (F.obj X) /-- An object is not initial if and only if its fiber is nonempty. -/ lemma not_initial_iff_fiber_nonempty (X : C) : (IsInitial X → False) ↔ Nonempty (F.obj X) := by rw [← not_isEmpty_iff] refine ⟨fun h he ↦ ?_, fun h hin ↦ h <| (initial_iff_fiber_empty F X).mp ⟨hin⟩⟩ exact Nonempty.elim ((initial_iff_fiber_empty F X).mpr he) h /-- An object whose fiber is inhabited is not initial. -/ lemma not_initial_of_inhabited {X : C} (x : F.obj X) (h : IsInitial X) : False := ((initial_iff_fiber_empty F X).mp ⟨h⟩).false x /-- The fiber of a connected object is nonempty. -/ instance nonempty_fiber_of_isConnected (X : C) [IsConnected X] : Nonempty (F.obj X) := by by_contra h have ⟨hin⟩ : Nonempty (IsInitial X) := (initial_iff_fiber_empty F X).mpr (not_nonempty_iff.mp h) exact IsConnected.notInitial hin /-- The fiber of the equalizer of `f g : X ⟶ Y` is equivalent to the set of agreement of `f` and `g`. -/ noncomputable def fiberEqualizerEquiv {X Y : C} (f g : X ⟶ Y) : F.obj (equalizer f g) ≃ { x : F.obj X // F.map f x = F.map g x } := (PreservesEqualizer.iso (F ⋙ FintypeCat.incl) f g ≪≫ Types.equalizerIso (F.map f) (F.map g)).toEquiv @[simp] lemma fiberEqualizerEquiv_symm_ι_apply {X Y : C} {f g : X ⟶ Y} (x : F.obj X) (h : F.map f x = F.map g x) : F.map (equalizer.ι f g) ((fiberEqualizerEquiv F f g).symm ⟨x, h⟩) = x := by simp [fiberEqualizerEquiv] change ((Types.equalizerIso _ _).inv ≫ _ ≫ (F ⋙ FintypeCat.incl).map (equalizer.ι f g)) _ = _ erw [PreservesEqualizer.iso_inv_ι, Types.equalizerIso_inv_comp_ι] /-- The fiber of the pullback is the fiber product of the fibers. -/ noncomputable def fiberPullbackEquiv {X A B : C} (f : A ⟶ X) (g : B ⟶ X) : F.obj (pullback f g) ≃ { p : F.obj A × F.obj B // F.map f p.1 = F.map g p.2 } := (PreservesPullback.iso (F ⋙ FintypeCat.incl) f g ≪≫ Types.pullbackIsoPullback (F.map f) (F.map g)).toEquiv @[simp] lemma fiberPullbackEquiv_symm_fst_apply {X A B : C} {f : A ⟶ X} {g : B ⟶ X} (a : F.obj A) (b : F.obj B) (h : F.map f a = F.map g b) : F.map (pullback.fst f g) ((fiberPullbackEquiv F f g).symm ⟨(a, b), h⟩) = a := by simp [fiberPullbackEquiv] change ((Types.pullbackIsoPullback _ _).inv ≫ _ ≫ (F ⋙ FintypeCat.incl).map (pullback.fst f g)) _ = _ erw [PreservesPullback.iso_inv_fst, Types.pullbackIsoPullback_inv_fst] @[simp] lemma fiberPullbackEquiv_symm_snd_apply {X A B : C} {f : A ⟶ X} {g : B ⟶ X} (a : F.obj A) (b : F.obj B) (h : F.map f a = F.map g b) : F.map (pullback.snd f g) ((fiberPullbackEquiv F f g).symm ⟨(a, b), h⟩) = b := by simp [fiberPullbackEquiv] change ((Types.pullbackIsoPullback _ _).inv ≫ _ ≫ (F ⋙ FintypeCat.incl).map (pullback.snd f g)) _ = _ erw [PreservesPullback.iso_inv_snd, Types.pullbackIsoPullback_inv_snd] /-- The fiber of the binary product is the binary product of the fibers. -/ noncomputable def fiberBinaryProductEquiv (X Y : C) : F.obj (X ⨯ Y) ≃ F.obj X × F.obj Y := (PreservesLimitPair.iso (F ⋙ FintypeCat.incl) X Y ≪≫ Types.binaryProductIso (F.obj X) (F.obj Y)).toEquiv @[simp] lemma fiberBinaryProductEquiv_symm_fst_apply {X Y : C} (x : F.obj X) (y : F.obj Y) : F.map prod.fst ((fiberBinaryProductEquiv F X Y).symm (x, y)) = x := by simp only [fiberBinaryProductEquiv, comp_obj, FintypeCat.incl_obj, Iso.toEquiv_comp, Equiv.symm_trans_apply, Iso.toEquiv_symm_fun] change ((Types.binaryProductIso _ _).inv ≫ _ ≫ (F ⋙ FintypeCat.incl).map prod.fst) _ = _ erw [PreservesLimitPair.iso_inv_fst, Types.binaryProductIso_inv_comp_fst] @[simp] lemma fiberBinaryProductEquiv_symm_snd_apply {X Y : C} (x : F.obj X) (y : F.obj Y) : F.map prod.snd ((fiberBinaryProductEquiv F X Y).symm (x, y)) = y := by simp only [fiberBinaryProductEquiv, comp_obj, FintypeCat.incl_obj, Iso.toEquiv_comp, Equiv.symm_trans_apply, Iso.toEquiv_symm_fun] change ((Types.binaryProductIso _ _).inv ≫ _ ≫ (F ⋙ FintypeCat.incl).map prod.snd) _ = _ erw [PreservesLimitPair.iso_inv_snd, Types.binaryProductIso_inv_comp_snd] /-- The evaluation map is injective for connected objects. -/ lemma evaluation_injective_of_isConnected (A X : C) [IsConnected A] (a : F.obj A) : Function.Injective (fun (f : A ⟶ X) ↦ F.map f a) := by intro f g (h : F.map f a = F.map g a) haveI : IsIso (equalizer.ι f g) := by apply IsConnected.noTrivialComponent _ (equalizer.ι f g) exact not_initial_of_inhabited F ((fiberEqualizerEquiv F f g).symm ⟨a, h⟩) exact eq_of_epi_equalizer /-- The evaluation map on automorphisms is injective for connected objects. -/ lemma evaluation_aut_injective_of_isConnected (A : C) [IsConnected A] (a : F.obj A) : Function.Injective (fun f : Aut A ↦ F.map (f.hom) a) := by show Function.Injective ((fun f : A ⟶ A ↦ F.map f a) ∘ (fun f : Aut A ↦ f.hom))
apply Function.Injective.comp · exact evaluation_injective_of_isConnected F A A a · exact @Aut.ext _ _ A /-- A morphism from an object `X` with non-empty fiber to a connected object `A` is an epimorphism. -/ lemma epi_of_nonempty_of_isConnected {X A : C} [IsConnected A] [h : Nonempty (F.obj X)] (f : X ⟶ A) : Epi f := Epi.mk <| fun {Z} u v huv ↦ by apply evaluation_injective_of_isConnected F A Z (F.map f (Classical.arbitrary _))
Mathlib/CategoryTheory/Galois/Basic.lean
313
321
/- Copyright (c) 2019 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Justus Springer -/ import Mathlib.Topology.Category.TopCat.OpenNhds import Mathlib.Topology.Sheaves.SheafCondition.UniqueGluing /-! # Stalks For a presheaf `F` on a topological space `X`, valued in some category `C`, the *stalk* of `F` at the point `x : X` is defined as the colimit of the composition of the inclusion of categories `(OpenNhds x)ᵒᵖ ⥤ (Opens X)ᵒᵖ` and the functor `F : (Opens X)ᵒᵖ ⥤ C`. For an open neighborhood `U` of `x`, we define the map `F.germ x : F.obj (op U) ⟶ F.stalk x` as the canonical morphism into this colimit. Taking stalks is functorial: For every point `x : X` we define a functor `stalkFunctor C x`, sending presheaves on `X` to objects of `C`. Furthermore, for a map `f : X ⟶ Y` between topological spaces, we define `stalkPushforward` as the induced map on the stalks `(f _* ℱ).stalk (f x) ⟶ ℱ.stalk x`. Some lemmas about stalks and germs only hold for certain classes of concrete categories. A basic property of forgetful functors of categories of algebraic structures (like `MonCat`, `CommRingCat`,...) is that they preserve filtered colimits. Since stalks are filtered colimits, this ensures that the stalks of presheaves valued in these categories behave exactly as for `Type`-valued presheaves. For example, in `germ_exist` we prove that in such a category, every element of the stalk is the germ of a section. Furthermore, if we require the forgetful functor to reflect isomorphisms and preserve limits (as is the case for most algebraic structures), we have access to the unique gluing API and can prove further properties. Most notably, in `is_iso_iff_stalk_functor_map_iso`, we prove that in such a category, a morphism of sheaves is an isomorphism if and only if all of its stalk maps are isomorphisms. See also the definition of "algebraic structures" in the stacks project: https://stacks.math.columbia.edu/tag/007L -/ assert_not_exists OrderedCommMonoid noncomputable section universe v u v' u' open CategoryTheory open TopCat open CategoryTheory.Limits open TopologicalSpace Topology open Opposite open scoped AlgebraicGeometry variable {C : Type u} [Category.{v} C] variable [HasColimits.{v} C] variable {X Y Z : TopCat.{v}} namespace TopCat.Presheaf variable (C) in /-- Stalks are functorial with respect to morphisms of presheaves over a fixed `X`. -/ def stalkFunctor (x : X) : X.Presheaf C ⥤ C := (whiskeringLeft _ _ C).obj (OpenNhds.inclusion x).op ⋙ colim /-- The stalk of a presheaf `F` at a point `x` is calculated as the colimit of the functor nbhds x ⥤ opens F.X ⥤ C -/ def stalk (ℱ : X.Presheaf C) (x : X) : C := (stalkFunctor C x).obj ℱ -- -- colimit ((open_nhds.inclusion x).op ⋙ ℱ) @[simp] theorem stalkFunctor_obj (ℱ : X.Presheaf C) (x : X) : (stalkFunctor C x).obj ℱ = ℱ.stalk x := rfl /-- The germ of a section of a presheaf over an open at a point of that open. -/ def germ (F : X.Presheaf C) (U : Opens X) (x : X) (hx : x ∈ U) : F.obj (op U) ⟶ stalk F x := colimit.ι ((OpenNhds.inclusion x).op ⋙ F) (op ⟨U, hx⟩) /-- The germ of a global section of a presheaf at a point. -/ def Γgerm (F : X.Presheaf C) (x : X) : F.obj (op ⊤) ⟶ stalk F x := F.germ ⊤ x True.intro @[reassoc] theorem germ_res (F : X.Presheaf C) {U V : Opens X} (i : U ⟶ V) (x : X) (hx : x ∈ U) : F.map i.op ≫ F.germ U x hx = F.germ V x (i.le hx) := let i' : (⟨U, hx⟩ : OpenNhds x) ⟶ ⟨V, i.le hx⟩ := i colimit.w ((OpenNhds.inclusion x).op ⋙ F) i'.op /-- A variant of `germ_res` with `op V ⟶ op U` so that the LHS is more general and simp fires more easier. -/ @[reassoc (attr := simp)] theorem germ_res' (F : X.Presheaf C) {U V : Opens X} (i : op V ⟶ op U) (x : X) (hx : x ∈ U) : F.map i ≫ F.germ U x hx = F.germ V x (i.unop.le hx) := let i' : (⟨U, hx⟩ : OpenNhds x) ⟶ ⟨V, i.unop.le hx⟩ := i.unop colimit.w ((OpenNhds.inclusion x).op ⋙ F) i'.op @[reassoc] lemma map_germ_eq_Γgerm (F : X.Presheaf C) {U : Opens X} {i : U ⟶ ⊤} (x : X) (hx : x ∈ U) : F.map i.op ≫ F.germ U x hx = F.Γgerm x := germ_res F i x hx variable {FC : C → C → Type*} {CC : C → Type*} [∀ X Y, FunLike (FC X Y) (CC X) (CC Y)] theorem germ_res_apply (F : X.Presheaf C) {U V : Opens X} (i : U ⟶ V) (x : X) (hx : x ∈ U) [ConcreteCategory C FC] (s) : F.germ U x hx (F.map i.op s) = F.germ V x (i.le hx) s := by rw [← ConcreteCategory.comp_apply, germ_res] theorem germ_res_apply' (F : X.Presheaf C) {U V : Opens X} (i : op V ⟶ op U) (x : X) (hx : x ∈ U) [ConcreteCategory C FC] (s) : F.germ U x hx (F.map i s) = F.germ V x (i.unop.le hx) s := by rw [← ConcreteCategory.comp_apply, germ_res'] lemma Γgerm_res_apply (F : X.Presheaf C) {U : Opens X} {i : U ⟶ ⊤} (x : X) (hx : x ∈ U) [ConcreteCategory C FC] (s) : F.germ U x hx (F.map i.op s) = F.Γgerm x s := F.germ_res_apply i x hx s /-- A morphism from the stalk of `F` at `x` to some object `Y` is completely determined by its composition with the `germ` morphisms. -/ @[ext] theorem stalk_hom_ext (F : X.Presheaf C) {x} {Y : C} {f₁ f₂ : F.stalk x ⟶ Y} (ih : ∀ (U : Opens X) (hxU : x ∈ U), F.germ U x hxU ≫ f₁ = F.germ U x hxU ≫ f₂) : f₁ = f₂ := colimit.hom_ext fun U => by induction U with | op U => obtain ⟨U, hxU⟩ := U; exact ih U hxU @[reassoc (attr := simp)] theorem stalkFunctor_map_germ {F G : X.Presheaf C} (U : Opens X) (x : X) (hx : x ∈ U) (f : F ⟶ G) : F.germ U x hx ≫ (stalkFunctor C x).map f = f.app (op U) ≫ G.germ U x hx := colimit.ι_map (whiskerLeft (OpenNhds.inclusion x).op f) (op ⟨U, hx⟩) theorem stalkFunctor_map_germ_apply [ConcreteCategory C FC] {F G : X.Presheaf C} (U : Opens X) (x : X) (hx : x ∈ U) (f : F ⟶ G) (s) : (stalkFunctor C x).map f (F.germ U x hx s) = G.germ U x hx (f.app (op U) s) := by rw [← ConcreteCategory.comp_apply, ← stalkFunctor_map_germ, ConcreteCategory.comp_apply] rfl -- a variant of `stalkFunctor_map_germ_apply` that makes simpNF happy. @[simp] theorem stalkFunctor_map_germ_apply' [ConcreteCategory C FC] {F G : X.Presheaf C} (U : Opens X) (x : X) (hx : x ∈ U) (f : F ⟶ G) (s) : DFunLike.coe (F := ToHom (F.stalk x) (G.stalk x)) (ConcreteCategory.hom ((stalkFunctor C x).map f)) (F.germ U x hx s) = G.germ U x hx (f.app (op U) s) := stalkFunctor_map_germ_apply U x hx f s variable (C) /-- For a presheaf `F` on a space `X`, a continuous map `f : X ⟶ Y` induces a morphisms between the stalk of `f _ * F` at `f x` and the stalk of `F` at `x`. -/ def stalkPushforward (f : X ⟶ Y) (F : X.Presheaf C) (x : X) : (f _* F).stalk (f x) ⟶ F.stalk x := by -- This is a hack; Lean doesn't like to elaborate the term written directly. refine ?_ ≫ colimit.pre _ (OpenNhds.map f x).op exact colim.map (whiskerRight (NatTrans.op (OpenNhds.inclusionMapIso f x).inv) F) @[reassoc (attr := simp), elementwise (attr := simp)] theorem stalkPushforward_germ (f : X ⟶ Y) (F : X.Presheaf C) (U : Opens Y) (x : X) (hx : f x ∈ U) : (f _* F).germ U (f x) hx ≫ F.stalkPushforward C f x = F.germ ((Opens.map f).obj U) x hx := by simp [germ, stalkPushforward] -- Here are two other potential solutions, suggested by @fpvandoorn at -- <https://github.com/leanprover-community/mathlib/pull/1018#discussion_r283978240> -- However, I can't get the subsequent two proofs to work with either one. -- def stalkPushforward'' (f : X ⟶ Y) (ℱ : X.Presheaf C) (x : X) : -- (f _* ℱ).stalk (f x) ⟶ ℱ.stalk x := -- colim.map ((Functor.associator _ _ _).inv ≫ -- whiskerRight (NatTrans.op (OpenNhds.inclusionMapIso f x).inv) ℱ) ≫ -- colimit.pre ((OpenNhds.inclusion x).op ⋙ ℱ) (OpenNhds.map f x).op -- def stalkPushforward''' (f : X ⟶ Y) (ℱ : X.Presheaf C) (x : X) : -- (f _* ℱ).stalk (f x) ⟶ ℱ.stalk x := -- (colim.map (whiskerRight (NatTrans.op (OpenNhds.inclusionMapIso f x).inv) ℱ) : -- colim.obj ((OpenNhds.inclusion (f x) ⋙ Opens.map f).op ⋙ ℱ) ⟶ _) ≫ -- colimit.pre ((OpenNhds.inclusion x).op ⋙ ℱ) (OpenNhds.map f x).op namespace stalkPushforward @[simp] theorem id (ℱ : X.Presheaf C) (x : X) : ℱ.stalkPushforward C (𝟙 X) x = (stalkFunctor C x).map (Pushforward.id ℱ).hom := by ext simp only [stalkPushforward, germ, colim_map, ι_colimMap_assoc, whiskerRight_app] erw [CategoryTheory.Functor.map_id] simp [stalkFunctor] @[simp] theorem comp (ℱ : X.Presheaf C) (f : X ⟶ Y) (g : Y ⟶ Z) (x : X) : ℱ.stalkPushforward C (f ≫ g) x = (f _* ℱ).stalkPushforward C g (f x) ≫ ℱ.stalkPushforward C f x := by ext simp [germ, stalkPushforward] theorem stalkPushforward_iso_of_isInducing {f : X ⟶ Y} (hf : IsInducing f) (F : X.Presheaf C) (x : X) : IsIso (F.stalkPushforward _ f x) := by haveI := Functor.initial_of_adjunction (hf.adjunctionNhds x) convert (Functor.Final.colimitIso (OpenNhds.map f x).op ((OpenNhds.inclusion x).op ⋙ F)).isIso_hom refine stalk_hom_ext _ fun U hU ↦ (stalkPushforward_germ _ f F _ x hU).trans ?_ symm exact colimit.ι_pre ((OpenNhds.inclusion x).op ⋙ F) (OpenNhds.map f x).op _ @[deprecated (since := "2024-10-27")] alias stalkPushforward_iso_of_isOpenEmbedding := stalkPushforward_iso_of_isInducing end stalkPushforward section stalkPullback /-- The morphism `ℱ_{f x} ⟶ (f⁻¹ℱ)ₓ` that factors through `(f_*f⁻¹ℱ)_{f x}`. -/ def stalkPullbackHom (f : X ⟶ Y) (F : Y.Presheaf C) (x : X) : F.stalk (f x) ⟶ ((pullback C f).obj F).stalk x := (stalkFunctor _ (f x)).map ((pushforwardPullbackAdjunction C f).unit.app F) ≫ stalkPushforward _ _ _ x @[reassoc (attr := simp)] lemma germ_stalkPullbackHom (f : X ⟶ Y) (F : Y.Presheaf C) (x : X) (U : Opens Y) (hU : f x ∈ U) : F.germ U (f x) hU ≫ stalkPullbackHom C f F x = ((pushforwardPullbackAdjunction C f).unit.app F).app _ ≫ ((pullback C f).obj F).germ ((Opens.map f).obj U) x hU := by simp [stalkPullbackHom, germ, stalkFunctor, stalkPushforward] /-- The morphism `(f⁻¹ℱ)(U) ⟶ ℱ_{f(x)}` for some `U ∋ x`. -/ def germToPullbackStalk (f : X ⟶ Y) (F : Y.Presheaf C) (U : Opens X) (x : X) (hx : x ∈ U) : ((pullback C f).obj F).obj (op U) ⟶ F.stalk (f x) := ((Opens.map f).op.isPointwiseLeftKanExtensionLeftKanExtensionUnit F (op U)).desc { pt := F.stalk ((f : X → Y) (x : X)) ι := { app := fun V => F.germ _ (f x) (V.hom.unop.le hx) naturality := fun _ _ i => by simp } } variable {C} in @[ext] lemma pullback_obj_obj_ext {Z : C} {f : X ⟶ Y} {F : Y.Presheaf C} (U : (Opens X)ᵒᵖ) {φ ψ : ((pullback C f).obj F).obj U ⟶ Z} (h : ∀ (V : Opens Y) (hV : U.unop ≤ (Opens.map f).obj V), ((pushforwardPullbackAdjunction C f).unit.app F).app (op V) ≫ ((pullback C f).obj F).map (homOfLE hV).op ≫ φ = ((pushforwardPullbackAdjunction C f).unit.app F).app (op V) ≫ ((pullback C f).obj F).map (homOfLE hV).op ≫ ψ) : φ = ψ := by obtain ⟨U⟩ := U apply ((Opens.map f).op.isPointwiseLeftKanExtensionLeftKanExtensionUnit F _).hom_ext rintro ⟨⟨V⟩, ⟨⟩, ⟨b⟩⟩ simpa [pushforwardPullbackAdjunction, Functor.lanAdjunction_unit] using h V (leOfHom b) @[reassoc (attr := simp)] lemma pushforwardPullbackAdjunction_unit_pullback_map_germToPullbackStalk (f : X ⟶ Y) (F : Y.Presheaf C) (U : Opens X) (x : X) (hx : x ∈ U) (V : Opens Y) (hV : U ≤ (Opens.map f).obj V) : ((pushforwardPullbackAdjunction C f).unit.app F).app (op V) ≫ ((pullback C f).obj F).map (homOfLE hV).op ≫ germToPullbackStalk C f F U x hx = F.germ _ (f x) (hV hx) := by simpa [pushforwardPullbackAdjunction] using ((Opens.map f).op.isPointwiseLeftKanExtensionLeftKanExtensionUnit F (op U)).fac _ (CostructuredArrow.mk (homOfLE hV).op) @[reassoc (attr := simp)] lemma germToPullbackStalk_stalkPullbackHom (f : X ⟶ Y) (F : Y.Presheaf C) (U : Opens X) (x : X) (hx : x ∈ U) : germToPullbackStalk C f F U x hx ≫ stalkPullbackHom C f F x = ((pullback C f).obj F).germ _ x hx := by ext V hV dsimp simp only [pushforwardPullbackAdjunction_unit_pullback_map_germToPullbackStalk_assoc, germ_stalkPullbackHom, germ_res] @[reassoc (attr := simp)] lemma pushforwardPullbackAdjunction_unit_app_app_germToPullbackStalk (f : X ⟶ Y) (F : Y.Presheaf C) (V : (Opens Y)ᵒᵖ) (x : X) (hx : f x ∈ V.unop) : ((pushforwardPullbackAdjunction C f).unit.app F).app V ≫ germToPullbackStalk C f F _ x hx = F.germ _ (f x) hx := by simpa using pushforwardPullbackAdjunction_unit_pullback_map_germToPullbackStalk C f F ((Opens.map f).obj V.unop) x hx V.unop (by rfl) /-- The morphism `(f⁻¹ℱ)ₓ ⟶ ℱ_{f(x)}`. -/ def stalkPullbackInv (f : X ⟶ Y) (F : Y.Presheaf C) (x : X) : ((pullback C f).obj F).stalk x ⟶ F.stalk (f x) := colimit.desc ((OpenNhds.inclusion x).op ⋙ (Presheaf.pullback C f).obj F) { pt := F.stalk (f x) ι := { app := fun U => F.germToPullbackStalk _ f (unop U).1 x (unop U).2 naturality := fun U V i => by dsimp ext W hW dsimp [OpenNhds.inclusion] rw [Category.comp_id, ← Functor.map_comp_assoc, pushforwardPullbackAdjunction_unit_pullback_map_germToPullbackStalk] erw [pushforwardPullbackAdjunction_unit_pullback_map_germToPullbackStalk] } } @[reassoc (attr := simp)] lemma germ_stalkPullbackInv (f : X ⟶ Y) (F : Y.Presheaf C) (x : X) (V : Opens X) (hV : x ∈ V) : ((pullback C f).obj F).germ _ x hV ≫ stalkPullbackInv C f F x = F.germToPullbackStalk _ f V x hV := by apply colimit.ι_desc /-- The isomorphism `ℱ_{f(x)} ≅ (f⁻¹ℱ)ₓ`. -/ def stalkPullbackIso (f : X ⟶ Y) (F : Y.Presheaf C) (x : X) : F.stalk (f x) ≅ ((pullback C f).obj F).stalk x where hom := stalkPullbackHom _ _ _ _ inv := stalkPullbackInv _ _ _ _ hom_inv_id := by ext U hU dsimp rw [germ_stalkPullbackHom_assoc, germ_stalkPullbackInv, Category.comp_id, pushforwardPullbackAdjunction_unit_app_app_germToPullbackStalk] inv_hom_id := by ext V hV dsimp rw [germ_stalkPullbackInv_assoc, Category.comp_id, germToPullbackStalk_stalkPullbackHom] end stalkPullback section stalkSpecializes variable {C} /-- If `x` specializes to `y`, then there is a natural map `F.stalk y ⟶ F.stalk x`. -/ noncomputable def stalkSpecializes (F : X.Presheaf C) {x y : X} (h : x ⤳ y) : F.stalk y ⟶ F.stalk x := by refine colimit.desc _ ⟨_, fun U => ?_, ?_⟩ · exact colimit.ι ((OpenNhds.inclusion x).op ⋙ F) (op ⟨(unop U).1, (specializes_iff_forall_open.mp h _ (unop U).1.2 (unop U).2 :)⟩) · intro U V i dsimp rw [Category.comp_id] let U' : OpenNhds x := ⟨_, (specializes_iff_forall_open.mp h _ (unop U).1.2 (unop U).2 :)⟩ let V' : OpenNhds x := ⟨_, (specializes_iff_forall_open.mp h _ (unop V).1.2 (unop V).2 :)⟩ exact colimit.w ((OpenNhds.inclusion x).op ⋙ F) (show V' ⟶ U' from i.unop).op @[reassoc (attr := simp), elementwise nosimp] theorem germ_stalkSpecializes (F : X.Presheaf C) {U : Opens X} {y : X} (hy : y ∈ U) {x : X} (h : x ⤳ y) : F.germ U y hy ≫ F.stalkSpecializes h = F.germ U x (h.mem_open U.isOpen hy) := colimit.ι_desc _ _ @[simp] theorem stalkSpecializes_refl {C : Type*} [Category C] [Limits.HasColimits C] {X : TopCat} (F : X.Presheaf C) (x : X) : F.stalkSpecializes (specializes_refl x) = 𝟙 _ := by ext simp @[reassoc (attr := simp), elementwise (attr := simp)] theorem stalkSpecializes_comp {C : Type*} [Category C] [Limits.HasColimits C] {X : TopCat} (F : X.Presheaf C) {x y z : X} (h : x ⤳ y) (h' : y ⤳ z) : F.stalkSpecializes h' ≫ F.stalkSpecializes h = F.stalkSpecializes (h.trans h') := by ext simp @[reassoc (attr := simp), elementwise (attr := simp)] theorem stalkSpecializes_stalkFunctor_map {F G : X.Presheaf C} (f : F ⟶ G) {x y : X} (h : x ⤳ y) : F.stalkSpecializes h ≫ (stalkFunctor C x).map f = (stalkFunctor C y).map f ≫ G.stalkSpecializes h := by change (_ : colimit _ ⟶ _) = (_ : colimit _ ⟶ _) ext; delta stalkFunctor; simpa [stalkSpecializes] using by rfl -- See https://github.com/leanprover-community/batteries/issues/365 for the simpNF issue. -- It seems the side condition `h` is not applied by `simpNF`. @[reassoc, elementwise, simp, nolint simpNF] theorem stalkSpecializes_stalkPushforward (f : X ⟶ Y) (F : X.Presheaf C) {x y : X} (h : x ⤳ y) : (f _* F).stalkSpecializes (f.hom.map_specializes h) ≫ F.stalkPushforward _ f x = F.stalkPushforward _ f y ≫ F.stalkSpecializes h := by change (_ : colimit _ ⟶ _) = (_ : colimit _ ⟶ _) ext; delta stalkPushforward simp only [stalkSpecializes, colimit.ι_desc_assoc, colimit.ι_map_assoc, colimit.ι_pre, Category.assoc, colimit.pre_desc, colimit.ι_desc] rfl /-- The stalks are isomorphic on inseparable points -/ @[simps] def stalkCongr {X : TopCat} {C : Type*} [Category C] [HasColimits C] (F : X.Presheaf C) {x y : X} (e : Inseparable x y) : F.stalk x ≅ F.stalk y := ⟨F.stalkSpecializes e.ge, F.stalkSpecializes e.le, by simp, by simp⟩ end stalkSpecializes section Concrete variable {C} {CC : C → Type v} [∀ X Y, FunLike (FC X Y) (CC X) (CC Y)] variable [instCC : ConcreteCategory.{v} C FC] -- Porting note (https://github.com/leanprover-community/mathlib4/issues/11215): TODO: @[ext] attribute only applies to structures or lemmas proving x = y -- @[ext] theorem germ_ext (F : X.Presheaf C) {U V : Opens X} {x : X} {hxU : x ∈ U} {hxV : x ∈ V} (W : Opens X) (hxW : x ∈ W) (iWU : W ⟶ U) (iWV : W ⟶ V) {sU : ToType (F.obj (op U))} {sV : ToType (F.obj (op V))} (ih : F.map iWU.op sU = F.map iWV.op sV) : F.germ _ x hxU sU = F.germ _ x hxV sV := by rw [← F.germ_res iWU x hxW, ← F.germ_res iWV x hxW, ConcreteCategory.comp_apply, ConcreteCategory.comp_apply, ih] variable [PreservesFilteredColimits (forget C)] /-- For presheaves valued in a concrete category whose forgetful functor preserves filtered colimits, every element of the stalk is the germ of a section. -/ theorem germ_exist (F : X.Presheaf C) (x : X) (t : ToType (stalk.{v, u} F x)) : ∃ (U : Opens X) (m : x ∈ U) (s : ToType (F.obj (op U))), F.germ _ x m s = t := by obtain ⟨U, s, e⟩ := Types.jointly_surjective.{v, v} _ (isColimitOfPreserves (forget C) (colimit.isColimit _)) t revert s e induction U with | op U => ?_ obtain ⟨V, m⟩ := U intro s e exact ⟨V, m, s, e⟩ theorem germ_eq (F : X.Presheaf C) {U V : Opens X} (x : X) (mU : x ∈ U) (mV : x ∈ V) (s : ToType (F.obj (op U))) (t : ToType (F.obj (op V))) (h : F.germ U x mU s = F.germ V x mV t) : ∃ (W : Opens X) (_m : x ∈ W) (iU : W ⟶ U) (iV : W ⟶ V), F.map iU.op s = F.map iV.op t := by obtain ⟨W, iU, iV, e⟩ := (Types.FilteredColimit.isColimit_eq_iff.{v, v} _ (isColimitOfPreserves (forget C) (colimit.isColimit ((OpenNhds.inclusion x).op ⋙ F)))).mp h exact ⟨(unop W).1, (unop W).2, iU.unop, iV.unop, e⟩ theorem stalkFunctor_map_injective_of_app_injective {F G : Presheaf C X} (f : F ⟶ G) (h : ∀ U : Opens X, Function.Injective (f.app (op U))) (x : X) : Function.Injective ((stalkFunctor C x).map f) := fun s t hst => by
rcases germ_exist F x s with ⟨U₁, hxU₁, s, rfl⟩ rcases germ_exist F x t with ⟨U₂, hxU₂, t, rfl⟩ rw [stalkFunctor_map_germ_apply, stalkFunctor_map_germ_apply] at hst obtain ⟨W, hxW, iWU₁, iWU₂, heq⟩ := G.germ_eq x hxU₁ hxU₂ _ _ hst rw [← ConcreteCategory.comp_apply, ← ConcreteCategory.comp_apply, ← f.naturality, ← f.naturality, ConcreteCategory.comp_apply, ConcreteCategory.comp_apply] at heq replace heq := h W heq convert congr_arg (F.germ _ x hxW) heq using 1 exacts [(F.germ_res_apply iWU₁ x hxW s).symm, (F.germ_res_apply iWU₂ x hxW t).symm] variable [HasLimits C] [PreservesLimits (forget C)] [(forget C).ReflectsIsomorphisms]
Mathlib/Topology/Sheaves/Stalks.lean
429
440
/- 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.Topology import Mathlib.Analysis.NormedSpace.Pointwise import Mathlib.Analysis.Seminorm import Mathlib.Analysis.LocallyConvex.Bounded import Mathlib.Analysis.RCLike.Basic /-! # The Minkowski functional This file defines the Minkowski functional, aka gauge. The Minkowski functional of a set `s` is the function which associates each point to how much you need to scale `s` for `x` to be inside it. When `s` is symmetric, convex and absorbent, its gauge is a seminorm. Reciprocally, any seminorm arises as the gauge of some set, namely its unit ball. This induces the equivalence of seminorms and locally convex topological vector spaces. ## Main declarations For a real vector space, * `gauge`: Aka Minkowski functional. `gauge s x` is the least (actually, an infimum) `r` such that `x ∈ r • s`. * `gaugeSeminorm`: The Minkowski functional as a seminorm, when `s` is symmetric, convex and absorbent. ## References * [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966] ## Tags Minkowski functional, gauge -/ open NormedField Set open scoped Pointwise Topology NNReal noncomputable section variable {𝕜 E : Type*} section AddCommGroup variable [AddCommGroup E] [Module ℝ E] /-- The Minkowski functional. Given a set `s` in a real vector space, `gauge s` is the functional which sends `x : E` to the smallest `r : ℝ` such that `x` is in `s` scaled by `r`. -/ def gauge (s : Set E) (x : E) : ℝ := sInf { r : ℝ | 0 < r ∧ x ∈ r • s } variable {s t : Set E} {x : E} {a : ℝ} theorem gauge_def : gauge s x = sInf ({ r ∈ Set.Ioi (0 : ℝ) | x ∈ r • s }) := rfl /-- An alternative definition of the gauge using scalar multiplication on the element rather than on the set. -/ theorem gauge_def' : gauge s x = sInf {r ∈ Set.Ioi (0 : ℝ) | r⁻¹ • x ∈ s} := by congrm sInf {r | ?_} exact and_congr_right fun hr => mem_smul_set_iff_inv_smul_mem₀ hr.ne' _ _ private theorem gauge_set_bddBelow : BddBelow { r : ℝ | 0 < r ∧ x ∈ r • s } := ⟨0, fun _ hr => hr.1.le⟩ /-- If the given subset is `Absorbent` then the set we take an infimum over in `gauge` is nonempty, which is useful for proving many properties about the gauge. -/ theorem Absorbent.gauge_set_nonempty (absorbs : Absorbent ℝ s) : { r : ℝ | 0 < r ∧ x ∈ r • s }.Nonempty := let ⟨r, hr₁, hr₂⟩ := (absorbs x).exists_pos ⟨r, hr₁, hr₂ r (Real.norm_of_nonneg hr₁.le).ge rfl⟩ theorem gauge_mono (hs : Absorbent ℝ s) (h : s ⊆ t) : gauge t ≤ gauge s := fun _ => csInf_le_csInf gauge_set_bddBelow hs.gauge_set_nonempty fun _ hr => ⟨hr.1, smul_set_mono h hr.2⟩ theorem exists_lt_of_gauge_lt (absorbs : Absorbent ℝ s) (h : gauge s x < a) : ∃ b, 0 < b ∧ b < a ∧ x ∈ b • s := by obtain ⟨b, ⟨hb, hx⟩, hba⟩ := exists_lt_of_csInf_lt absorbs.gauge_set_nonempty h exact ⟨b, hb, hba, hx⟩ /-- The gauge evaluated at `0` is always zero (mathematically this requires `0` to be in the set `s` but, the real infimum of the empty set in Lean being defined as `0`, it holds unconditionally). -/ @[simp] theorem gauge_zero : gauge s 0 = 0 := by rw [gauge_def'] by_cases h : (0 : E) ∈ s · simp only [smul_zero, sep_true, h, csInf_Ioi] · simp only [smul_zero, sep_false, h, Real.sInf_empty] @[simp] theorem gauge_zero' : gauge (0 : Set E) = 0 := by ext x rw [gauge_def'] obtain rfl | hx := eq_or_ne x 0 · simp only [csInf_Ioi, mem_zero, Pi.zero_apply, eq_self_iff_true, sep_true, smul_zero] · simp only [mem_zero, Pi.zero_apply, inv_eq_zero, smul_eq_zero] convert Real.sInf_empty exact eq_empty_iff_forall_not_mem.2 fun r hr => hr.2.elim (ne_of_gt hr.1) hx @[simp] theorem gauge_empty : gauge (∅ : Set E) = 0 := by ext simp only [gauge_def', Real.sInf_empty, mem_empty_iff_false, Pi.zero_apply, sep_false] theorem gauge_of_subset_zero (h : s ⊆ 0) : gauge s = 0 := by obtain rfl | rfl := subset_singleton_iff_eq.1 h exacts [gauge_empty, gauge_zero'] /-- The gauge is always nonnegative. -/ theorem gauge_nonneg (x : E) : 0 ≤ gauge s x := Real.sInf_nonneg fun _ hx => hx.1.le theorem gauge_neg (symmetric : ∀ x ∈ s, -x ∈ s) (x : E) : gauge s (-x) = gauge s x := by have : ∀ x, -x ∈ s ↔ x ∈ s := fun x => ⟨fun h => by simpa using symmetric _ h, symmetric x⟩ simp_rw [gauge_def', smul_neg, this]
theorem gauge_neg_set_neg (x : E) : gauge (-s) (-x) = gauge s x := by simp_rw [gauge_def', smul_neg, neg_mem_neg]
Mathlib/Analysis/Convex/Gauge.lean
119
121
/- Copyright (c) 2022 Yaël Dillies, Sara Rousta. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies, Sara Rousta -/ import Mathlib.Logic.Equiv.Set import Mathlib.Order.Interval.Set.OrderEmbedding import Mathlib.Order.SetNotation /-! # Properties of unbundled upper/lower sets This file proves results on `IsUpperSet` and `IsLowerSet`, including their interactions with set operations, images, preimages and order duals, and properties that reflect stronger assumptions on the underlying order (such as `PartialOrder` and `LinearOrder`). ## TODO * Lattice structure on antichains. * Order equivalence between upper/lower sets and antichains. -/ open OrderDual Set variable {α β : Type*} {ι : Sort*} {κ : ι → Sort*} attribute [aesop norm unfold] IsUpperSet IsLowerSet section LE variable [LE α] {s t : Set α} {a : α} theorem isUpperSet_empty : IsUpperSet (∅ : Set α) := fun _ _ _ => id theorem isLowerSet_empty : IsLowerSet (∅ : Set α) := fun _ _ _ => id theorem isUpperSet_univ : IsUpperSet (univ : Set α) := fun _ _ _ => id theorem isLowerSet_univ : IsLowerSet (univ : Set α) := fun _ _ _ => id theorem IsUpperSet.compl (hs : IsUpperSet s) : IsLowerSet sᶜ := fun _a _b h hb ha => hb <| hs h ha theorem IsLowerSet.compl (hs : IsLowerSet s) : IsUpperSet sᶜ := fun _a _b h hb ha => hb <| hs h ha @[simp] theorem isUpperSet_compl : IsUpperSet sᶜ ↔ IsLowerSet s := ⟨fun h => by convert h.compl rw [compl_compl], IsLowerSet.compl⟩ @[simp] theorem isLowerSet_compl : IsLowerSet sᶜ ↔ IsUpperSet s := ⟨fun h => by convert h.compl rw [compl_compl], IsUpperSet.compl⟩ theorem IsUpperSet.union (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∪ t) := fun _ _ h => Or.imp (hs h) (ht h) theorem IsLowerSet.union (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∪ t) := fun _ _ h => Or.imp (hs h) (ht h) theorem IsUpperSet.inter (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∩ t) := fun _ _ h => And.imp (hs h) (ht h) theorem IsLowerSet.inter (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∩ t) := fun _ _ h => And.imp (hs h) (ht h) theorem isUpperSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋃₀ S) := fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩ theorem isLowerSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋃₀ S) := fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩ theorem isUpperSet_iUnion {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋃ i, f i) := isUpperSet_sUnion <| forall_mem_range.2 hf theorem isLowerSet_iUnion {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋃ i, f i) := isLowerSet_sUnion <| forall_mem_range.2 hf theorem isUpperSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) : IsUpperSet (⋃ (i) (j), f i j) := isUpperSet_iUnion fun i => isUpperSet_iUnion <| hf i theorem isLowerSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) : IsLowerSet (⋃ (i) (j), f i j) := isLowerSet_iUnion fun i => isLowerSet_iUnion <| hf i theorem isUpperSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋂₀ S) := fun _ _ h => forall₂_imp fun s hs => hf s hs h theorem isLowerSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋂₀ S) := fun _ _ h => forall₂_imp fun s hs => hf s hs h theorem isUpperSet_iInter {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋂ i, f i) := isUpperSet_sInter <| forall_mem_range.2 hf theorem isLowerSet_iInter {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋂ i, f i) := isLowerSet_sInter <| forall_mem_range.2 hf theorem isUpperSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) : IsUpperSet (⋂ (i) (j), f i j) := isUpperSet_iInter fun i => isUpperSet_iInter <| hf i theorem isLowerSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) : IsLowerSet (⋂ (i) (j), f i j) := isLowerSet_iInter fun i => isLowerSet_iInter <| hf i @[simp] theorem isLowerSet_preimage_ofDual_iff : IsLowerSet (ofDual ⁻¹' s) ↔ IsUpperSet s := Iff.rfl @[simp] theorem isUpperSet_preimage_ofDual_iff : IsUpperSet (ofDual ⁻¹' s) ↔ IsLowerSet s := Iff.rfl @[simp] theorem isLowerSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsLowerSet (toDual ⁻¹' s) ↔ IsUpperSet s := Iff.rfl @[simp] theorem isUpperSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsUpperSet (toDual ⁻¹' s) ↔ IsLowerSet s := Iff.rfl alias ⟨_, IsUpperSet.toDual⟩ := isLowerSet_preimage_ofDual_iff alias ⟨_, IsLowerSet.toDual⟩ := isUpperSet_preimage_ofDual_iff alias ⟨_, IsUpperSet.ofDual⟩ := isLowerSet_preimage_toDual_iff alias ⟨_, IsLowerSet.ofDual⟩ := isUpperSet_preimage_toDual_iff lemma IsUpperSet.isLowerSet_preimage_coe (hs : IsUpperSet s) : IsLowerSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t := by aesop lemma IsLowerSet.isUpperSet_preimage_coe (hs : IsLowerSet s) : IsUpperSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t := by aesop lemma IsUpperSet.sdiff (hs : IsUpperSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t) : IsUpperSet (s \ t) := fun _b _c hbc hb ↦ ⟨hs hbc hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hbc⟩ lemma IsLowerSet.sdiff (hs : IsLowerSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t) : IsLowerSet (s \ t) := fun _b _c hcb hb ↦ ⟨hs hcb hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hcb⟩ lemma IsUpperSet.sdiff_of_isLowerSet (hs : IsUpperSet s) (ht : IsLowerSet t) : IsUpperSet (s \ t) := hs.sdiff <| by aesop lemma IsLowerSet.sdiff_of_isUpperSet (hs : IsLowerSet s) (ht : IsUpperSet t) : IsLowerSet (s \ t) := hs.sdiff <| by aesop lemma IsUpperSet.erase (hs : IsUpperSet s) (has : ∀ b ∈ s, b ≤ a → b = a) : IsUpperSet (s \ {a}) := hs.sdiff <| by simpa using has lemma IsLowerSet.erase (hs : IsLowerSet s) (has : ∀ b ∈ s, a ≤ b → b = a) : IsLowerSet (s \ {a}) := hs.sdiff <| by simpa using has end LE section Preorder variable [Preorder α] [Preorder β] {s : Set α} {p : α → Prop} (a : α) theorem isUpperSet_Ici : IsUpperSet (Ici a) := fun _ _ => ge_trans theorem isLowerSet_Iic : IsLowerSet (Iic a) := fun _ _ => le_trans theorem isUpperSet_Ioi : IsUpperSet (Ioi a) := fun _ _ => flip lt_of_lt_of_le theorem isLowerSet_Iio : IsLowerSet (Iio a) := fun _ _ => lt_of_le_of_lt theorem isUpperSet_iff_Ici_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ici a ⊆ s := by simp [IsUpperSet, subset_def, @forall_swap (_ ∈ s)] theorem isLowerSet_iff_Iic_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iic a ⊆ s := by simp [IsLowerSet, subset_def, @forall_swap (_ ∈ s)] alias ⟨IsUpperSet.Ici_subset, _⟩ := isUpperSet_iff_Ici_subset alias ⟨IsLowerSet.Iic_subset, _⟩ := isLowerSet_iff_Iic_subset theorem IsUpperSet.Ioi_subset (h : IsUpperSet s) ⦃a⦄ (ha : a ∈ s) : Ioi a ⊆ s := Ioi_subset_Ici_self.trans <| h.Ici_subset ha theorem IsLowerSet.Iio_subset (h : IsLowerSet s) ⦃a⦄ (ha : a ∈ s) : Iio a ⊆ s := h.toDual.Ioi_subset ha theorem IsUpperSet.ordConnected (h : IsUpperSet s) : s.OrdConnected := ⟨fun _ ha _ _ => Icc_subset_Ici_self.trans <| h.Ici_subset ha⟩ theorem IsLowerSet.ordConnected (h : IsLowerSet s) : s.OrdConnected := ⟨fun _ _ _ hb => Icc_subset_Iic_self.trans <| h.Iic_subset hb⟩ theorem IsUpperSet.preimage (hs : IsUpperSet s) {f : β → α} (hf : Monotone f) : IsUpperSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h theorem IsLowerSet.preimage (hs : IsLowerSet s) {f : β → α} (hf : Monotone f) : IsLowerSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h theorem IsUpperSet.image (hs : IsUpperSet s) (f : α ≃o β) : IsUpperSet (f '' s : Set β) := by change IsUpperSet ((f : α ≃ β) '' s) rw [Set.image_equiv_eq_preimage_symm] exact hs.preimage f.symm.monotone theorem IsLowerSet.image (hs : IsLowerSet s) (f : α ≃o β) : IsLowerSet (f '' s : Set β) := by change IsLowerSet ((f : α ≃ β) '' s) rw [Set.image_equiv_eq_preimage_symm] exact hs.preimage f.symm.monotone theorem OrderEmbedding.image_Ici (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) : e '' Ici a = Ici (e a) := by rw [← e.preimage_Ici, image_preimage_eq_inter_range, inter_eq_left.2 <| he.Ici_subset (mem_range_self _)] theorem OrderEmbedding.image_Iic (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) : e '' Iic a = Iic (e a) := e.dual.image_Ici he a theorem OrderEmbedding.image_Ioi (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) : e '' Ioi a = Ioi (e a) := by rw [← e.preimage_Ioi, image_preimage_eq_inter_range, inter_eq_left.2 <| he.Ioi_subset (mem_range_self _)] theorem OrderEmbedding.image_Iio (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) : e '' Iio a = Iio (e a) := e.dual.image_Ioi he a @[simp] theorem Set.monotone_mem : Monotone (· ∈ s) ↔ IsUpperSet s := Iff.rfl @[simp] theorem Set.antitone_mem : Antitone (· ∈ s) ↔ IsLowerSet s := forall_swap @[simp] theorem isUpperSet_setOf : IsUpperSet { a | p a } ↔ Monotone p := Iff.rfl @[simp] theorem isLowerSet_setOf : IsLowerSet { a | p a } ↔ Antitone p := forall_swap lemma IsUpperSet.upperBounds_subset (hs : IsUpperSet s) : s.Nonempty → upperBounds s ⊆ s := fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha lemma IsLowerSet.lowerBounds_subset (hs : IsLowerSet s) : s.Nonempty → lowerBounds s ⊆ s := fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha section OrderTop variable [OrderTop α] theorem IsLowerSet.top_mem (hs : IsLowerSet s) : ⊤ ∈ s ↔ s = univ := ⟨fun h => eq_univ_of_forall fun _ => hs le_top h, fun h => h.symm ▸ mem_univ _⟩ theorem IsUpperSet.top_mem (hs : IsUpperSet s) : ⊤ ∈ s ↔ s.Nonempty := ⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs le_top ha⟩ theorem IsUpperSet.not_top_mem (hs : IsUpperSet s) : ⊤ ∉ s ↔ s = ∅ := hs.top_mem.not.trans not_nonempty_iff_eq_empty end OrderTop section OrderBot variable [OrderBot α] theorem IsUpperSet.bot_mem (hs : IsUpperSet s) : ⊥ ∈ s ↔ s = univ := ⟨fun h => eq_univ_of_forall fun _ => hs bot_le h, fun h => h.symm ▸ mem_univ _⟩ theorem IsLowerSet.bot_mem (hs : IsLowerSet s) : ⊥ ∈ s ↔ s.Nonempty := ⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs bot_le ha⟩ theorem IsLowerSet.not_bot_mem (hs : IsLowerSet s) : ⊥ ∉ s ↔ s = ∅ := hs.bot_mem.not.trans not_nonempty_iff_eq_empty end OrderBot section NoMaxOrder variable [NoMaxOrder α] theorem IsUpperSet.not_bddAbove (hs : IsUpperSet s) : s.Nonempty → ¬BddAbove s := by rintro ⟨a, ha⟩ ⟨b, hb⟩ obtain ⟨c, hc⟩ := exists_gt b exact hc.not_le (hb <| hs ((hb ha).trans hc.le) ha) theorem not_bddAbove_Ici : ¬BddAbove (Ici a) := (isUpperSet_Ici _).not_bddAbove nonempty_Ici theorem not_bddAbove_Ioi : ¬BddAbove (Ioi a) := (isUpperSet_Ioi _).not_bddAbove nonempty_Ioi end NoMaxOrder section NoMinOrder variable [NoMinOrder α] theorem IsLowerSet.not_bddBelow (hs : IsLowerSet s) : s.Nonempty → ¬BddBelow s := by rintro ⟨a, ha⟩ ⟨b, hb⟩ obtain ⟨c, hc⟩ := exists_lt b exact hc.not_le (hb <| hs (hc.le.trans <| hb ha) ha) theorem not_bddBelow_Iic : ¬BddBelow (Iic a) := (isLowerSet_Iic _).not_bddBelow nonempty_Iic theorem not_bddBelow_Iio : ¬BddBelow (Iio a) := (isLowerSet_Iio _).not_bddBelow nonempty_Iio end NoMinOrder end Preorder section PartialOrder variable [PartialOrder α] {s : Set α} theorem isUpperSet_iff_forall_lt : IsUpperSet s ↔ ∀ ⦃a b : α⦄, a < b → a ∈ s → b ∈ s := forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and] theorem isLowerSet_iff_forall_lt : IsLowerSet s ↔ ∀ ⦃a b : α⦄, b < a → a ∈ s → b ∈ s := forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and] theorem isUpperSet_iff_Ioi_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ioi a ⊆ s := by simp [isUpperSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)] theorem isLowerSet_iff_Iio_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iio a ⊆ s := by simp [isLowerSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)] end PartialOrder section LinearOrder variable [LinearOrder α] {s t : Set α} theorem IsUpperSet.total (hs : IsUpperSet s) (ht : IsUpperSet t) : s ⊆ t ∨ t ⊆ s := by by_contra! h simp_rw [Set.not_subset] at h obtain ⟨⟨a, has, hat⟩, b, hbt, hbs⟩ := h obtain hab | hba := le_total a b · exact hbs (hs hab has) · exact hat (ht hba hbt) theorem IsLowerSet.total (hs : IsLowerSet s) (ht : IsLowerSet t) : s ⊆ t ∨ t ⊆ s := hs.toDual.total ht.toDual end LinearOrder
Mathlib/Order/UpperLower/Basic.lean
842
843
/- Copyright (c) 2020 Pim Spelier, Daan van Gent. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Pim Spelier, Daan van Gent -/ import Mathlib.Data.Fintype.Basic import Mathlib.Data.Num.Lemmas import Mathlib.Data.Option.Basic import Mathlib.SetTheory.Cardinal.Basic import Mathlib.Tactic.DeriveFintype /-! # Encodings This file contains the definition of a (finite) encoding, a map from a type to strings in an alphabet, used in defining computability by Turing machines. It also contains several examples: ## Examples - `finEncodingNatBool` : a binary encoding of ℕ in a simple alphabet. - `finEncodingNatΓ'` : a binary encoding of ℕ in the alphabet used for TM's. - `unaryFinEncodingNat` : a unary encoding of ℕ - `finEncodingBoolBool` : an encoding of bool. -/ universe u v open Cardinal namespace Computability /-- An encoding of a type in a certain alphabet, together with a decoding. -/ structure Encoding (α : Type u) where /-- The alphabet of the encoding -/ Γ : Type v /-- The encoding function -/ encode : α → List Γ /-- The decoding function -/ decode : List Γ → Option α /-- Decoding and encoding are inverses of each other. -/ decode_encode : ∀ x, decode (encode x) = some x theorem Encoding.encode_injective {α : Type u} (e : Encoding α) : Function.Injective e.encode := by refine fun _ _ h => Option.some_injective _ ?_ rw [← e.decode_encode, ← e.decode_encode, h] /-- An encoding plus a guarantee of finiteness of the alphabet. -/ structure FinEncoding (α : Type u) extends Encoding.{u, 0} α where /-- The alphabet of the encoding is finite -/ ΓFin : Fintype Γ instance Γ.fintype {α : Type u} (e : FinEncoding α) : Fintype e.toEncoding.Γ := e.ΓFin /-- A standard Turing machine alphabet, consisting of blank,bit0,bit1,bra,ket,comma. -/ inductive Γ' | blank | bit (b : Bool) | bra | ket | comma deriving DecidableEq, Fintype instance inhabitedΓ' : Inhabited Γ' := ⟨Γ'.blank⟩ /-- The natural inclusion of bool in Γ'. -/ def inclusionBoolΓ' : Bool → Γ' := Γ'.bit /-- An arbitrary section of the natural inclusion of bool in Γ'. -/ def sectionΓ'Bool : Γ' → Bool | Γ'.bit b => b | _ => Inhabited.default @[simp] theorem sectionΓ'Bool_inclusionBoolΓ' {b} : sectionΓ'Bool (inclusionBoolΓ' b) = b := by cases b <;> rfl @[deprecated sectionΓ'Bool_inclusionBoolΓ' (since := "2025-01-21")] theorem leftInverse_section_inclusion : Function.LeftInverse sectionΓ'Bool inclusionBoolΓ' := fun x => Bool.casesOn x rfl rfl theorem inclusionBoolΓ'_injective : Function.Injective inclusionBoolΓ' := Function.HasLeftInverse.injective ⟨_, (fun _ => sectionΓ'Bool_inclusionBoolΓ')⟩ /-- An encoding function of the positive binary numbers in bool. -/ def encodePosNum : PosNum → List Bool | PosNum.one => [true] | PosNum.bit0 n => false :: encodePosNum n | PosNum.bit1 n => true :: encodePosNum n /-- An encoding function of the binary numbers in bool. -/ def encodeNum : Num → List Bool | Num.zero => [] | Num.pos n => encodePosNum n /-- An encoding function of ℕ in bool. -/ def encodeNat (n : ℕ) : List Bool := encodeNum n /-- A decoding function from `List Bool` to the positive binary numbers. -/ def decodePosNum : List Bool → PosNum | false :: l => PosNum.bit0 (decodePosNum l) | true :: l => ite (l = []) PosNum.one (PosNum.bit1 (decodePosNum l)) | _ => PosNum.one /-- A decoding function from `List Bool` to the binary numbers. -/ def decodeNum : List Bool → Num := fun l => ite (l = []) Num.zero <| decodePosNum l /-- A decoding function from `List Bool` to ℕ. -/ def decodeNat : List Bool → Nat := fun l => decodeNum l theorem encodePosNum_nonempty (n : PosNum) : encodePosNum n ≠ [] := PosNum.casesOn n (List.cons_ne_nil _ _) (fun _m => List.cons_ne_nil _ _) fun _m => List.cons_ne_nil _ _ @[simp] theorem decode_encodePosNum : ∀ n, decodePosNum (encodePosNum n) = n := by intro n induction' n with m hm m hm <;> unfold encodePosNum decodePosNum · rfl · rw [hm] exact if_neg (encodePosNum_nonempty m) · exact congr_arg PosNum.bit0 hm @[simp] theorem decode_encodeNum : ∀ n, decodeNum (encodeNum n) = n := by intro n obtain - | n := n <;> unfold encodeNum decodeNum · rfl rw [decode_encodePosNum n] rw [PosNum.cast_to_num] exact if_neg (encodePosNum_nonempty n) @[simp] theorem decode_encodeNat : ∀ n, decodeNat (encodeNat n) = n := by intro n conv_rhs => rw [← Num.to_of_nat n] exact congr_arg ((↑) : Num → ℕ) (decode_encodeNum n) /-- A binary encoding of ℕ in bool. -/ def encodingNatBool : Encoding ℕ where Γ := Bool encode := encodeNat decode n := some (decodeNat n) decode_encode n := congr_arg _ (decode_encodeNat n) /-- A binary fin_encoding of ℕ in bool. -/ def finEncodingNatBool : FinEncoding ℕ := ⟨encodingNatBool, Bool.fintype⟩
/-- A binary encoding of ℕ in Γ'. -/ def encodingNatΓ' : Encoding ℕ where Γ := Γ' encode x := List.map inclusionBoolΓ' (encodeNat x)
Mathlib/Computability/Encoding.lean
152
155
/- Copyright (c) 2020 Kim Morrison. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kim Morrison, Johan Commelin, Andrew Yang, Joël Riou -/ import Mathlib.Algebra.Group.Basic import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Zero import Mathlib.CategoryTheory.Monoidal.End import Mathlib.CategoryTheory.Monoidal.Discrete /-! # Shift A `Shift` on a category `C` indexed by a monoid `A` is nothing more than a monoidal functor from `A` to `C ⥤ C`. A typical example to keep in mind might be the category of complexes `⋯ → C_{n-1} → C_n → C_{n+1} → ⋯`. It has a shift indexed by `ℤ`, where we assign to each `n : ℤ` the functor `C ⥤ C` that re-indexes the terms, so the degree `i` term of `Shift n C` would be the degree `i+n`-th term of `C`. ## Main definitions * `HasShift`: A typeclass asserting the existence of a shift functor. * `shiftEquiv`: When the indexing monoid is a group, then the functor indexed by `n` and `-n` forms a self-equivalence of `C`. * `shiftComm`: When the indexing monoid is commutative, then shifts commute as well. ## Implementation Notes `[HasShift C A]` is implemented using monoidal functors from `Discrete A` to `C ⥤ C`. However, the API of monoidal functors is used only internally: one should use the API of shifts functors which includes `shiftFunctor C a : C ⥤ C` for `a : A`, `shiftFunctorZero C A : shiftFunctor C (0 : A) ≅ 𝟭 C` and `shiftFunctorAdd C i j : shiftFunctor C (i + j) ≅ shiftFunctor C i ⋙ shiftFunctor C j` (and its variant `shiftFunctorAdd'`). These isomorphisms satisfy some coherence properties which are stated in lemmas like `shiftFunctorAdd'_assoc`, `shiftFunctorAdd'_zero_add` and `shiftFunctorAdd'_add_zero`. -/ namespace CategoryTheory noncomputable section universe v u variable (C : Type u) (A : Type*) [Category.{v} C] attribute [local instance] endofunctorMonoidalCategory variable {A C} section Defs variable (A C) [AddMonoid A] /-- A category has a shift indexed by an additive monoid `A` if there is a monoidal functor from `A` to `C ⥤ C`. -/ class HasShift (C : Type u) (A : Type*) [Category.{v} C] [AddMonoid A] where /-- a shift is a monoidal functor from `A` to `C ⥤ C` -/ shift : Discrete A ⥤ C ⥤ C /-- `shift` is monoidal -/ shiftMonoidal : shift.Monoidal := by infer_instance /-- A helper structure to construct the shift functor `(Discrete A) ⥤ (C ⥤ C)`. -/ structure ShiftMkCore where /-- the family of shift functors -/ F : A → C ⥤ C /-- the shift by 0 identifies to the identity functor -/ zero : F 0 ≅ 𝟭 C /-- the composition of shift functors identifies to the shift by the sum -/ add : ∀ n m : A, F (n + m) ≅ F n ⋙ F m /-- compatibility with the associativity -/ assoc_hom_app : ∀ (m₁ m₂ m₃ : A) (X : C), (add (m₁ + m₂) m₃).hom.app X ≫ (F m₃).map ((add m₁ m₂).hom.app X) = eqToHom (by rw [add_assoc]) ≫ (add m₁ (m₂ + m₃)).hom.app X ≫ (add m₂ m₃).hom.app ((F m₁).obj X) := by aesop_cat /-- compatibility with the left addition with 0 -/ zero_add_hom_app : ∀ (n : A) (X : C), (add 0 n).hom.app X = eqToHom (by dsimp; rw [zero_add]) ≫ (F n).map (zero.inv.app X) := by aesop_cat /-- compatibility with the right addition with 0 -/ add_zero_hom_app : ∀ (n : A) (X : C), (add n 0).hom.app X = eqToHom (by dsimp; rw [add_zero]) ≫ zero.inv.app ((F n).obj X) := by aesop_cat namespace ShiftMkCore variable {C A} attribute [reassoc] assoc_hom_app @[reassoc] lemma assoc_inv_app (h : ShiftMkCore C A) (m₁ m₂ m₃ : A) (X : C) : (h.F m₃).map ((h.add m₁ m₂).inv.app X) ≫ (h.add (m₁ + m₂) m₃).inv.app X = (h.add m₂ m₃).inv.app ((h.F m₁).obj X) ≫ (h.add m₁ (m₂ + m₃)).inv.app X ≫ eqToHom (by rw [add_assoc]) := by rw [← cancel_mono ((h.add (m₁ + m₂) m₃).hom.app X ≫ (h.F m₃).map ((h.add m₁ m₂).hom.app X)), Category.assoc, Category.assoc, Category.assoc, Iso.inv_hom_id_app_assoc, ← Functor.map_comp, Iso.inv_hom_id_app, Functor.map_id, h.assoc_hom_app, eqToHom_trans_assoc, eqToHom_refl, Category.id_comp, Iso.inv_hom_id_app_assoc, Iso.inv_hom_id_app] rfl lemma zero_add_inv_app (h : ShiftMkCore C A) (n : A) (X : C) : (h.add 0 n).inv.app X = (h.F n).map (h.zero.hom.app X) ≫ eqToHom (by dsimp; rw [zero_add]) := by rw [← cancel_epi ((h.add 0 n).hom.app X), Iso.hom_inv_id_app, h.zero_add_hom_app, Category.assoc, ← Functor.map_comp_assoc, Iso.inv_hom_id_app, Functor.map_id, Category.id_comp, eqToHom_trans, eqToHom_refl] lemma add_zero_inv_app (h : ShiftMkCore C A) (n : A) (X : C) : (h.add n 0).inv.app X = h.zero.hom.app ((h.F n).obj X) ≫ eqToHom (by dsimp; rw [add_zero]) := by rw [← cancel_epi ((h.add n 0).hom.app X), Iso.hom_inv_id_app, h.add_zero_hom_app, Category.assoc, Iso.inv_hom_id_app_assoc, eqToHom_trans, eqToHom_refl] end ShiftMkCore section attribute [local simp] eqToHom_map instance (h : ShiftMkCore C A) : (Discrete.functor h.F).Monoidal := Functor.CoreMonoidal.toMonoidal { εIso := h.zero.symm μIso := fun m n ↦ (h.add m.as n.as).symm μIso_hom_natural_left := by rintro ⟨X⟩ ⟨Y⟩ ⟨⟨⟨rfl⟩⟩⟩ ⟨X'⟩ ext dsimp simp μIso_hom_natural_right := by rintro ⟨X⟩ ⟨Y⟩ ⟨X'⟩ ⟨⟨⟨rfl⟩⟩⟩ ext dsimp simp associativity := by rintro ⟨m₁⟩ ⟨m₂⟩ ⟨m₃⟩ ext X simp [endofunctorMonoidalCategory, h.assoc_inv_app_assoc] left_unitality := by rintro ⟨n⟩ ext X simp [endofunctorMonoidalCategory, h.zero_add_inv_app, ← Functor.map_comp] right_unitality := by rintro ⟨n⟩ ext X simp [endofunctorMonoidalCategory, h.add_zero_inv_app] } /-- Constructs a `HasShift C A` instance from `ShiftMkCore`. -/ def hasShiftMk (h : ShiftMkCore C A) : HasShift C A where shift := Discrete.functor h.F end section variable [HasShift C A] /-- The monoidal functor from `A` to `C ⥤ C` given a `HasShift` instance. -/ def shiftMonoidalFunctor : Discrete A ⥤ C ⥤ C := HasShift.shift instance : (shiftMonoidalFunctor C A).Monoidal := HasShift.shiftMonoidal variable {A} open Functor.Monoidal /-- The shift autoequivalence, moving objects and morphisms 'up'. -/ def shiftFunctor (i : A) : C ⥤ C := (shiftMonoidalFunctor C A).obj ⟨i⟩ /-- Shifting by `i + j` is the same as shifting by `i` and then shifting by `j`. -/ def shiftFunctorAdd (i j : A) : shiftFunctor C (i + j) ≅ shiftFunctor C i ⋙ shiftFunctor C j := (μIso (shiftMonoidalFunctor C A) ⟨i⟩ ⟨j⟩).symm /-- When `k = i + j`, shifting by `k` is the same as shifting by `i` and then shifting by `j`. -/ def shiftFunctorAdd' (i j k : A) (h : i + j = k) : shiftFunctor C k ≅ shiftFunctor C i ⋙ shiftFunctor C j := eqToIso (by rw [h]) ≪≫ shiftFunctorAdd C i j lemma shiftFunctorAdd'_eq_shiftFunctorAdd (i j : A) : shiftFunctorAdd' C i j (i+j) rfl = shiftFunctorAdd C i j := by ext1 apply Category.id_comp variable (A) in /-- Shifting by zero is the identity functor. -/ def shiftFunctorZero : shiftFunctor C (0 : A) ≅ 𝟭 C := (εIso (shiftMonoidalFunctor C A)).symm /-- Shifting by `a` such that `a = 0` identifies to the identity functor. -/ def shiftFunctorZero' (a : A) (ha : a = 0) : shiftFunctor C a ≅ 𝟭 C := eqToIso (by rw [ha]) ≪≫ shiftFunctorZero C A end variable {C A} lemma ShiftMkCore.shiftFunctor_eq (h : ShiftMkCore C A) (a : A) : letI := hasShiftMk C A h shiftFunctor C a = h.F a := rfl lemma ShiftMkCore.shiftFunctorZero_eq (h : ShiftMkCore C A) : letI := hasShiftMk C A h shiftFunctorZero C A = h.zero := rfl lemma ShiftMkCore.shiftFunctorAdd_eq (h : ShiftMkCore C A) (a b : A) : letI := hasShiftMk C A h shiftFunctorAdd C a b = h.add a b := rfl set_option quotPrecheck false in /-- shifting an object `X` by `n` is obtained by the notation `X⟦n⟧` -/ notation -- Any better notational suggestions? X "⟦" n "⟧" => (shiftFunctor _ n).obj X set_option quotPrecheck false in /-- shifting a morphism `f` by `n` is obtained by the notation `f⟦n⟧'` -/ notation f "⟦" n "⟧'" => (shiftFunctor _ n).map f variable (C) variable [HasShift C A] lemma shiftFunctorAdd'_zero_add (a : A) : shiftFunctorAdd' C 0 a a (zero_add a) = (Functor.leftUnitor _).symm ≪≫ isoWhiskerRight (shiftFunctorZero C A).symm (shiftFunctor C a) := by ext X dsimp [shiftFunctorAdd', shiftFunctorZero, shiftFunctor] simp only [eqToHom_app, obj_ε_app, Discrete.addMonoidal_leftUnitor, eqToIso.inv, eqToHom_map, Category.id_comp] rfl lemma shiftFunctorAdd'_add_zero (a : A) : shiftFunctorAdd' C a 0 a (add_zero a) = (Functor.rightUnitor _).symm ≪≫ isoWhiskerLeft (shiftFunctor C a) (shiftFunctorZero C A).symm := by ext dsimp [shiftFunctorAdd', shiftFunctorZero, shiftFunctor] simp only [eqToHom_app, ε_app_obj, Discrete.addMonoidal_rightUnitor, eqToIso.inv, eqToHom_map, Category.id_comp] rfl lemma shiftFunctorAdd'_assoc (a₁ a₂ a₃ a₁₂ a₂₃ a₁₂₃ : A) (h₁₂ : a₁ + a₂ = a₁₂) (h₂₃ : a₂ + a₃ = a₂₃) (h₁₂₃ : a₁ + a₂ + a₃ = a₁₂₃) : shiftFunctorAdd' C a₁₂ a₃ a₁₂₃ (by rw [← h₁₂, h₁₂₃]) ≪≫ isoWhiskerRight (shiftFunctorAdd' C a₁ a₂ a₁₂ h₁₂) _ ≪≫ Functor.associator _ _ _ = shiftFunctorAdd' C a₁ a₂₃ a₁₂₃ (by rw [← h₂₃, ← add_assoc, h₁₂₃]) ≪≫ isoWhiskerLeft _ (shiftFunctorAdd' C a₂ a₃ a₂₃ h₂₃) := by subst h₁₂ h₂₃ h₁₂₃ ext X dsimp simp only [shiftFunctorAdd'_eq_shiftFunctorAdd, Category.comp_id] dsimp [shiftFunctorAdd'] simp only [eqToHom_app] dsimp [shiftFunctorAdd, shiftFunctor] simp only [obj_μ_inv_app, Discrete.addMonoidal_associator, eqToIso.hom, eqToHom_map, eqToHom_app] erw [δ_μ_app_assoc, Category.assoc] rfl lemma shiftFunctorAdd_assoc (a₁ a₂ a₃ : A) : shiftFunctorAdd C (a₁ + a₂) a₃ ≪≫ isoWhiskerRight (shiftFunctorAdd C a₁ a₂) _ ≪≫ Functor.associator _ _ _ = shiftFunctorAdd' C a₁ (a₂ + a₃) _ (add_assoc a₁ a₂ a₃).symm ≪≫ isoWhiskerLeft _ (shiftFunctorAdd C a₂ a₃) := by ext X simpa [shiftFunctorAdd'_eq_shiftFunctorAdd] using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_assoc C a₁ a₂ a₃ _ _ _ rfl rfl rfl)) X variable {C} lemma shiftFunctorAdd'_zero_add_hom_app (a : A) (X : C) : (shiftFunctorAdd' C 0 a a (zero_add a)).hom.app X = ((shiftFunctorZero C A).inv.app X)⟦a⟧' := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_zero_add C a)) X lemma shiftFunctorAdd_zero_add_hom_app (a : A) (X : C) : (shiftFunctorAdd C 0 a).hom.app X = eqToHom (by dsimp; rw [zero_add]) ≫ ((shiftFunctorZero C A).inv.app X)⟦a⟧' := by simp [← shiftFunctorAdd'_zero_add_hom_app, shiftFunctorAdd'] lemma shiftFunctorAdd'_zero_add_inv_app (a : A) (X : C) : (shiftFunctorAdd' C 0 a a (zero_add a)).inv.app X = ((shiftFunctorZero C A).hom.app X)⟦a⟧' := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd'_zero_add C a)) X lemma shiftFunctorAdd_zero_add_inv_app (a : A) (X : C) : (shiftFunctorAdd C 0 a).inv.app X = ((shiftFunctorZero C A).hom.app X)⟦a⟧' ≫ eqToHom (by dsimp; rw [zero_add]) := by simp [← shiftFunctorAdd'_zero_add_inv_app, shiftFunctorAdd'] lemma shiftFunctorAdd'_add_zero_hom_app (a : A) (X : C) : (shiftFunctorAdd' C a 0 a (add_zero a)).hom.app X = (shiftFunctorZero C A).inv.app (X⟦a⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_add_zero C a)) X lemma shiftFunctorAdd_add_zero_hom_app (a : A) (X : C) : (shiftFunctorAdd C a 0).hom.app X = eqToHom (by dsimp; rw [add_zero]) ≫ (shiftFunctorZero C A).inv.app (X⟦a⟧) := by simp [← shiftFunctorAdd'_add_zero_hom_app, shiftFunctorAdd'] lemma shiftFunctorAdd'_add_zero_inv_app (a : A) (X : C) : (shiftFunctorAdd' C a 0 a (add_zero a)).inv.app X = (shiftFunctorZero C A).hom.app (X⟦a⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd'_add_zero C a)) X lemma shiftFunctorAdd_add_zero_inv_app (a : A) (X : C) : (shiftFunctorAdd C a 0).inv.app X = (shiftFunctorZero C A).hom.app (X⟦a⟧) ≫ eqToHom (by dsimp; rw [add_zero]) := by simp [← shiftFunctorAdd'_add_zero_inv_app, shiftFunctorAdd'] @[reassoc] lemma shiftFunctorAdd'_assoc_hom_app (a₁ a₂ a₃ a₁₂ a₂₃ a₁₂₃ : A) (h₁₂ : a₁ + a₂ = a₁₂) (h₂₃ : a₂ + a₃ = a₂₃) (h₁₂₃ : a₁ + a₂ + a₃ = a₁₂₃) (X : C) : (shiftFunctorAdd' C a₁₂ a₃ a₁₂₃ (by rw [← h₁₂, h₁₂₃])).hom.app X ≫ ((shiftFunctorAdd' C a₁ a₂ a₁₂ h₁₂).hom.app X)⟦a₃⟧' = (shiftFunctorAdd' C a₁ a₂₃ a₁₂₃ (by rw [← h₂₃, ← add_assoc, h₁₂₃])).hom.app X ≫ (shiftFunctorAdd' C a₂ a₃ a₂₃ h₂₃).hom.app (X⟦a₁⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd'_assoc C _ _ _ _ _ _ h₁₂ h₂₃ h₁₂₃)) X @[reassoc] lemma shiftFunctorAdd'_assoc_inv_app (a₁ a₂ a₃ a₁₂ a₂₃ a₁₂₃ : A) (h₁₂ : a₁ + a₂ = a₁₂) (h₂₃ : a₂ + a₃ = a₂₃) (h₁₂₃ : a₁ + a₂ + a₃ = a₁₂₃) (X : C) : ((shiftFunctorAdd' C a₁ a₂ a₁₂ h₁₂).inv.app X)⟦a₃⟧' ≫ (shiftFunctorAdd' C a₁₂ a₃ a₁₂₃ (by rw [← h₁₂, h₁₂₃])).inv.app X = (shiftFunctorAdd' C a₂ a₃ a₂₃ h₂₃).inv.app (X⟦a₁⟧) ≫ (shiftFunctorAdd' C a₁ a₂₃ a₁₂₃ (by rw [← h₂₃, ← add_assoc, h₁₂₃])).inv.app X := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd'_assoc C _ _ _ _ _ _ h₁₂ h₂₃ h₁₂₃)) X @[reassoc] lemma shiftFunctorAdd_assoc_hom_app (a₁ a₂ a₃ : A) (X : C) : (shiftFunctorAdd C (a₁ + a₂) a₃).hom.app X ≫ ((shiftFunctorAdd C a₁ a₂).hom.app X)⟦a₃⟧' = (shiftFunctorAdd' C a₁ (a₂ + a₃) (a₁ + a₂ + a₃) (add_assoc _ _ _).symm).hom.app X ≫ (shiftFunctorAdd C a₂ a₃).hom.app (X⟦a₁⟧) := by simpa using NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorAdd_assoc C a₁ a₂ a₃)) X @[reassoc] lemma shiftFunctorAdd_assoc_inv_app (a₁ a₂ a₃ : A) (X : C) : ((shiftFunctorAdd C a₁ a₂).inv.app X)⟦a₃⟧' ≫ (shiftFunctorAdd C (a₁ + a₂) a₃).inv.app X = (shiftFunctorAdd C a₂ a₃).inv.app (X⟦a₁⟧) ≫ (shiftFunctorAdd' C a₁ (a₂ + a₃) (a₁ + a₂ + a₃) (add_assoc _ _ _).symm).inv.app X := by simpa using NatTrans.congr_app (congr_arg Iso.inv (shiftFunctorAdd_assoc C a₁ a₂ a₃)) X end Defs section AddMonoid variable [AddMonoid A] [HasShift C A] (X Y : C) (f : X ⟶ Y) --@[simp] --theorem HasShift.shift_obj_obj (n : A) (X : C) : (HasShift.shift.obj ⟨n⟩).obj X = X⟦n⟧ := -- rfl /-- Shifting by `i + j` is the same as shifting by `i` and then shifting by `j`. -/ abbrev shiftAdd (i j : A) : X⟦i + j⟧ ≅ X⟦i⟧⟦j⟧ := (shiftFunctorAdd C i j).app _ theorem shift_shift' (i j : A) : f⟦i⟧'⟦j⟧' = (shiftAdd X i j).inv ≫ f⟦i + j⟧' ≫ (shiftAdd Y i j).hom := by symm rw [← Functor.comp_map, Iso.app_inv] apply NatIso.naturality_1 variable (A) /-- Shifting by zero is the identity functor. -/ abbrev shiftZero : X⟦(0 : A)⟧ ≅ X := (shiftFunctorZero C A).app _ theorem shiftZero' : f⟦(0 : A)⟧' = (shiftZero A X).hom ≫ f ≫ (shiftZero A Y).inv := by symm rw [Iso.app_inv, Iso.app_hom] apply NatIso.naturality_2 variable (C) {A} /-- When `i + j = 0`, shifting by `i` and by `j` gives the identity functor -/ def shiftFunctorCompIsoId (i j : A) (h : i + j = 0) : shiftFunctor C i ⋙ shiftFunctor C j ≅ 𝟭 C := (shiftFunctorAdd' C i j 0 h).symm ≪≫ shiftFunctorZero C A end AddMonoid section AddGroup variable (C) variable [AddGroup A] [HasShift C A] /-- Shifting by `i` and shifting by `j` forms an equivalence when `i + j = 0`. -/ @[simps] def shiftEquiv' (i j : A) (h : i + j = 0) : C ≌ C where functor := shiftFunctor C i inverse := shiftFunctor C j unitIso := (shiftFunctorCompIsoId C i j h).symm counitIso := shiftFunctorCompIsoId C j i (by rw [← add_left_inj j, add_assoc, h, zero_add, add_zero]) functor_unitIso_comp X := by convert (equivOfTensorIsoUnit (shiftMonoidalFunctor C A) ⟨i⟩ ⟨j⟩ (Discrete.eqToIso h) (Discrete.eqToIso (by dsimp; rw [← add_left_inj j, add_assoc, h, zero_add, add_zero])) (Subsingleton.elim _ _)).functor_unitIso_comp X all_goals ext X dsimp [shiftFunctorCompIsoId, unitOfTensorIsoUnit, shiftFunctorAdd'] simp only [Category.assoc, eqToHom_map] rfl /-- Shifting by `n` and shifting by `-n` forms an equivalence. -/ abbrev shiftEquiv (n : A) : C ≌ C := shiftEquiv' C n (-n) (add_neg_cancel n) variable (X Y : C) (f : X ⟶ Y) /-- Shifting by `i` is an equivalence. -/ instance (i : A) : (shiftFunctor C i).IsEquivalence := by change (shiftEquiv C i).functor.IsEquivalence infer_instance variable {C} /-- Shifting by `i` and then shifting by `-i` is the identity. -/ abbrev shiftShiftNeg (i : A) : X⟦i⟧⟦-i⟧ ≅ X := (shiftEquiv C i).unitIso.symm.app X /-- Shifting by `-i` and then shifting by `i` is the identity. -/ abbrev shiftNegShift (i : A) : X⟦-i⟧⟦i⟧ ≅ X := (shiftEquiv C i).counitIso.app X variable {X Y} theorem shift_shift_neg' (i : A) : f⟦i⟧'⟦-i⟧' = (shiftFunctorCompIsoId C i (-i) (add_neg_cancel i)).hom.app X ≫ f ≫ (shiftFunctorCompIsoId C i (-i) (add_neg_cancel i)).inv.app Y := (NatIso.naturality_2 (shiftFunctorCompIsoId C i (-i) (add_neg_cancel i)) f).symm theorem shift_neg_shift' (i : A) : f⟦-i⟧'⟦i⟧' = (shiftFunctorCompIsoId C (-i) i (neg_add_cancel i)).hom.app X ≫ f ≫ (shiftFunctorCompIsoId C (-i) i (neg_add_cancel i)).inv.app Y := (NatIso.naturality_2 (shiftFunctorCompIsoId C (-i) i (neg_add_cancel i)) f).symm theorem shift_equiv_triangle (n : A) (X : C) : (shiftShiftNeg X n).inv⟦n⟧' ≫ (shiftNegShift (X⟦n⟧) n).hom = 𝟙 (X⟦n⟧) := (shiftEquiv C n).functor_unitIso_comp X section theorem shift_shiftFunctorCompIsoId_hom_app (n m : A) (h : n + m = 0) (X : C) : ((shiftFunctorCompIsoId C n m h).hom.app X)⟦n⟧' = (shiftFunctorCompIsoId C m n (by rw [← neg_eq_of_add_eq_zero_left h, add_neg_cancel])).hom.app (X⟦n⟧) := by dsimp [shiftFunctorCompIsoId] simpa only [Functor.map_comp, ← shiftFunctorAdd'_zero_add_inv_app n X, ← shiftFunctorAdd'_add_zero_inv_app n X] using shiftFunctorAdd'_assoc_inv_app n m n 0 0 n h (by rw [← neg_eq_of_add_eq_zero_left h, add_neg_cancel]) (by rw [h, zero_add]) X theorem shift_shiftFunctorCompIsoId_inv_app (n m : A) (h : n + m = 0) (X : C) : ((shiftFunctorCompIsoId C n m h).inv.app X)⟦n⟧' = ((shiftFunctorCompIsoId C m n (by rw [← neg_eq_of_add_eq_zero_left h, add_neg_cancel])).inv.app (X⟦n⟧)) := by rw [← cancel_mono (((shiftFunctorCompIsoId C n m h).hom.app X)⟦n⟧'), ← Functor.map_comp, Iso.inv_hom_id_app, Functor.map_id, shift_shiftFunctorCompIsoId_hom_app, Iso.inv_hom_id_app] rfl theorem shift_shiftFunctorCompIsoId_add_neg_cancel_hom_app (n : A) (X : C) : ((shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).hom.app X)⟦n⟧' = (shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).hom.app (X⟦n⟧) := by apply shift_shiftFunctorCompIsoId_hom_app theorem shift_shiftFunctorCompIsoId_add_neg_cancel_inv_app (n : A) (X : C) : ((shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).inv.app X)⟦n⟧' = (shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).inv.app (X⟦n⟧) := by apply shift_shiftFunctorCompIsoId_inv_app theorem shift_shiftFunctorCompIsoId_neg_add_cancel_hom_app (n : A) (X : C) : ((shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).hom.app X)⟦-n⟧' = (shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).hom.app (X⟦-n⟧) := by apply shift_shiftFunctorCompIsoId_hom_app theorem shift_shiftFunctorCompIsoId_neg_add_cancel_inv_app (n : A) (X : C) : ((shiftFunctorCompIsoId C (-n) n (neg_add_cancel n)).inv.app X)⟦-n⟧' = (shiftFunctorCompIsoId C n (-n) (add_neg_cancel n)).inv.app (X⟦-n⟧) := by apply shift_shiftFunctorCompIsoId_inv_app end section variable (A) lemma shiftFunctorCompIsoId_zero_zero_hom_app (X : C) : (shiftFunctorCompIsoId C 0 0 (add_zero 0)).hom.app X = ((shiftFunctorZero C A).hom.app X)⟦0⟧' ≫ (shiftFunctorZero C A).hom.app X := by simp [shiftFunctorCompIsoId, shiftFunctorAdd'_zero_add_inv_app] lemma shiftFunctorCompIsoId_zero_zero_inv_app (X : C) : (shiftFunctorCompIsoId C 0 0 (add_zero 0)).inv.app X = (shiftFunctorZero C A).inv.app X ≫ ((shiftFunctorZero C A).inv.app X)⟦0⟧' := by simp [shiftFunctorCompIsoId, shiftFunctorAdd'_zero_add_hom_app] end section variable (m n p m' n' p' : A) (hm : m' + m = 0) (hn : n' + n = 0) (hp : p' + p = 0) (h : m + n = p) lemma shiftFunctorCompIsoId_add'_inv_app : (shiftFunctorCompIsoId C p' p hp).inv.app X = (shiftFunctorCompIsoId C n' n hn).inv.app X ≫ (shiftFunctorCompIsoId C m' m hm).inv.app (X⟦n'⟧)⟦n⟧' ≫ (shiftFunctorAdd' C m n p h).inv.app (X⟦n'⟧⟦m'⟧) ≫ ((shiftFunctorAdd' C n' m' p' (by rw [← add_left_inj p, hp, ← h, add_assoc, ← add_assoc m', hm, zero_add, hn])).inv.app X)⟦p⟧' := by dsimp [shiftFunctorCompIsoId] simp only [Functor.map_comp, Category.assoc] congr 1 rw [← NatTrans.naturality] dsimp rw [← cancel_mono ((shiftFunctorAdd' C p' p 0 hp).inv.app X), Iso.hom_inv_id_app, Category.assoc, Category.assoc, Category.assoc, Category.assoc, ← shiftFunctorAdd'_assoc_inv_app p' m n n' p 0 (by rw [← add_left_inj n, hn, add_assoc, h, hp]) h (by rw [add_assoc, h, hp]), ← Functor.map_comp_assoc, ← Functor.map_comp_assoc, ← Functor.map_comp_assoc, Category.assoc, Category.assoc, shiftFunctorAdd'_assoc_inv_app n' m' m p' 0 n' _ _ (by rw [add_assoc, hm, add_zero]), Iso.hom_inv_id_app_assoc, ← shiftFunctorAdd'_add_zero_hom_app, Iso.hom_inv_id_app, Functor.map_id, Category.id_comp, Iso.hom_inv_id_app] lemma shiftFunctorCompIsoId_add'_hom_app : (shiftFunctorCompIsoId C p' p hp).hom.app X = ((shiftFunctorAdd' C n' m' p' (by rw [← add_left_inj p, hp, ← h, add_assoc, ← add_assoc m', hm, zero_add, hn])).hom.app X)⟦p⟧' ≫ (shiftFunctorAdd' C m n p h).hom.app (X⟦n'⟧⟦m'⟧) ≫ (shiftFunctorCompIsoId C m' m hm).hom.app (X⟦n'⟧)⟦n⟧' ≫ (shiftFunctorCompIsoId C n' n hn).hom.app X := by rw [← cancel_mono ((shiftFunctorCompIsoId C p' p hp).inv.app X), Iso.hom_inv_id_app, shiftFunctorCompIsoId_add'_inv_app m n p m' n' p' hm hn hp h, Category.assoc, Category.assoc, Category.assoc, Iso.hom_inv_id_app_assoc, ← Functor.map_comp_assoc, Iso.hom_inv_id_app] dsimp rw [Functor.map_id, Category.id_comp, Iso.hom_inv_id_app_assoc, ← Functor.map_comp, Iso.hom_inv_id_app, Functor.map_id] end open CategoryTheory.Limits variable [HasZeroMorphisms C] theorem shift_zero_eq_zero (X Y : C) (n : A) : (0 : X ⟶ Y)⟦n⟧' = (0 : X⟦n⟧ ⟶ Y⟦n⟧) := CategoryTheory.Functor.map_zero _ _ _ end AddGroup section AddCommMonoid variable [AddCommMonoid A] [HasShift C A] variable (C) /-- When shifts are indexed by an additive commutative monoid, then shifts commute. -/ def shiftFunctorComm (i j : A) : shiftFunctor C i ⋙ shiftFunctor C j ≅ shiftFunctor C j ⋙ shiftFunctor C i := (shiftFunctorAdd C i j).symm ≪≫ shiftFunctorAdd' C j i (i + j) (add_comm j i) lemma shiftFunctorComm_eq (i j k : A) (h : i + j = k) : shiftFunctorComm C i j = (shiftFunctorAdd' C i j k h).symm ≪≫ shiftFunctorAdd' C j i k (by rw [add_comm j i, h]) := by subst h rw [shiftFunctorAdd'_eq_shiftFunctorAdd] rfl @[simp] lemma shiftFunctorComm_eq_refl (i : A) : shiftFunctorComm C i i = Iso.refl _ := by rw [shiftFunctorComm_eq C i i (i + i) rfl, Iso.symm_self_id] lemma shiftFunctorComm_symm (i j : A) : (shiftFunctorComm C i j).symm = shiftFunctorComm C j i := by ext1 dsimp rw [shiftFunctorComm_eq C i j (i+j) rfl, shiftFunctorComm_eq C j i (i+j) (add_comm j i)] rfl variable {C} variable (X Y : C) (f : X ⟶ Y) /-- When shifts are indexed by an additive commutative monoid, then shifts commute. -/ abbrev shiftComm (i j : A) : X⟦i⟧⟦j⟧ ≅ X⟦j⟧⟦i⟧ := (shiftFunctorComm C i j).app X @[simp] theorem shiftComm_symm (i j : A) : (shiftComm X i j).symm = shiftComm X j i := by ext exact NatTrans.congr_app (congr_arg Iso.hom (shiftFunctorComm_symm C i j)) X variable {X Y} /-- When shifts are indexed by an additive commutative monoid, then shifts commute. -/ theorem shiftComm' (i j : A) : f⟦i⟧'⟦j⟧' = (shiftComm _ _ _).hom ≫ f⟦j⟧'⟦i⟧' ≫ (shiftComm _ _ _).hom := by erw [← shiftComm_symm Y i j, ← ((shiftFunctorComm C i j).hom.naturality_assoc f)] dsimp simp only [Iso.hom_inv_id_app, Functor.comp_obj, Category.comp_id] @[reassoc] theorem shiftComm_hom_comp (i j : A) : (shiftComm X i j).hom ≫ f⟦j⟧'⟦i⟧' = f⟦i⟧'⟦j⟧' ≫ (shiftComm Y i j).hom := by rw [shiftComm', ← shiftComm_symm, Iso.symm_hom, Iso.inv_hom_id_assoc] lemma shiftFunctorZero_hom_app_shift (n : A) : (shiftFunctorZero C A).hom.app (X⟦n⟧) = (shiftFunctorComm C n 0).hom.app X ≫ ((shiftFunctorZero C A).hom.app X)⟦n⟧' := by rw [← shiftFunctorAdd'_zero_add_inv_app n X, shiftFunctorComm_eq C n 0 n (add_zero n)] dsimp rw [Category.assoc, Iso.hom_inv_id_app, Category.comp_id, shiftFunctorAdd'_add_zero_inv_app] lemma shiftFunctorZero_inv_app_shift (n : A) : (shiftFunctorZero C A).inv.app (X⟦n⟧) = ((shiftFunctorZero C A).inv.app X)⟦n⟧' ≫ (shiftFunctorComm C n 0).inv.app X := by rw [← cancel_mono ((shiftFunctorZero C A).hom.app (X⟦n⟧)), Category.assoc, Iso.inv_hom_id_app, shiftFunctorZero_hom_app_shift, Iso.inv_hom_id_app_assoc, ← Functor.map_comp, Iso.inv_hom_id_app] dsimp rw [Functor.map_id] lemma shiftFunctorComm_zero_hom_app (a : A) : (shiftFunctorComm C a 0).hom.app X = (shiftFunctorZero C A).hom.app (X⟦a⟧) ≫ ((shiftFunctorZero C A).inv.app X)⟦a⟧' := by simp only [shiftFunctorZero_hom_app_shift, Category.assoc, ← Functor.map_comp, Iso.hom_inv_id_app, Functor.map_id, Functor.comp_obj, Category.comp_id] @[reassoc] lemma shiftFunctorComm_hom_app_comp_shift_shiftFunctorAdd_hom_app (m₁ m₂ m₃ : A) (X : C) : (shiftFunctorComm C m₁ (m₂ + m₃)).hom.app X ≫ ((shiftFunctorAdd C m₂ m₃).hom.app X)⟦m₁⟧' = (shiftFunctorAdd C m₂ m₃).hom.app (X⟦m₁⟧) ≫ ((shiftFunctorComm C m₁ m₂).hom.app X)⟦m₃⟧' ≫ (shiftFunctorComm C m₁ m₃).hom.app (X⟦m₂⟧) := by rw [← cancel_mono ((shiftFunctorComm C m₁ m₃).inv.app (X⟦m₂⟧)), ← cancel_mono (((shiftFunctorComm C m₁ m₂).inv.app X)⟦m₃⟧')] simp only [Category.assoc, Iso.hom_inv_id_app] dsimp simp only [Category.id_comp, ← Functor.map_comp, Iso.hom_inv_id_app] dsimp simp only [Functor.map_id, Category.comp_id, shiftFunctorComm_eq C _ _ _ rfl, ← shiftFunctorAdd'_eq_shiftFunctorAdd] dsimp simp only [Category.assoc, Iso.hom_inv_id_app_assoc, Iso.inv_hom_id_app_assoc, ← Functor.map_comp, shiftFunctorAdd'_assoc_hom_app_assoc m₂ m₃ m₁ (m₂ + m₃) (m₁ + m₃) (m₁ + (m₂ + m₃)) rfl (add_comm m₃ m₁) (add_comm _ m₁) X, ← shiftFunctorAdd'_assoc_hom_app_assoc m₂ m₁ m₃ (m₁ + m₂) (m₁ + m₃) (m₁ + (m₂ + m₃)) (add_comm _ _) rfl (by rw [add_comm m₂ m₁, add_assoc]) X, shiftFunctorAdd'_assoc_hom_app m₁ m₂ m₃ (m₁ + m₂) (m₂ + m₃) (m₁ + (m₂ + m₃)) rfl rfl (add_assoc _ _ _) X] end AddCommMonoid namespace Functor.FullyFaithful variable {D : Type*} [Category D] [AddMonoid A] [HasShift D A] variable {F : C ⥤ D} (hF : F.FullyFaithful) variable (s : A → C ⥤ C) (i : ∀ i, s i ⋙ F ≅ F ⋙ shiftFunctor D i) namespace hasShift /-- auxiliary definition for `FullyFaithful.hasShift` -/ def zero : s 0 ≅ 𝟭 C := (hF.whiskeringRight C).preimageIso ((i 0) ≪≫ isoWhiskerLeft F (shiftFunctorZero D A) ≪≫ Functor.rightUnitor _ ≪≫ (Functor.leftUnitor _).symm) @[simp] lemma map_zero_hom_app (X : C) : F.map ((zero hF s i).hom.app X) = (i 0).hom.app X ≫ (shiftFunctorZero D A).hom.app (F.obj X) := by simp [zero] @[simp] lemma map_zero_inv_app (X : C) : F.map ((zero hF s i).inv.app X) = (shiftFunctorZero D A).inv.app (F.obj X) ≫ (i 0).inv.app X := by simp [zero] /-- auxiliary definition for `FullyFaithful.hasShift` -/ def add (a b : A) : s (a + b) ≅ s a ⋙ s b := (hF.whiskeringRight C).preimageIso (i (a + b) ≪≫ isoWhiskerLeft _ (shiftFunctorAdd D a b) ≪≫ (Functor.associator _ _ _).symm ≪≫ (isoWhiskerRight (i a).symm _) ≪≫ Functor.associator _ _ _ ≪≫ (isoWhiskerLeft _ (i b).symm) ≪≫ (Functor.associator _ _ _).symm) @[simp] lemma map_add_hom_app (a b : A) (X : C) : F.map ((add hF s i a b).hom.app X) = (i (a + b)).hom.app X ≫ (shiftFunctorAdd D a b).hom.app (F.obj X) ≫ ((i a).inv.app X)⟦b⟧' ≫ (i b).inv.app ((s a).obj X) := by dsimp [add] simp
@[simp] lemma map_add_inv_app (a b : A) (X : C) : F.map ((add hF s i a b).inv.app X) = (i b).hom.app ((s a).obj X) ≫ ((i a).hom.app X)⟦b⟧' ≫ (shiftFunctorAdd D a b).inv.app (F.obj X) ≫ (i (a + b)).inv.app X := by dsimp [add]
Mathlib/CategoryTheory/Shift/Basic.lean
701
707
/- Copyright (c) 2022 Moritz Doll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Moritz Doll, Anatole Dedecker -/ import Mathlib.Analysis.LocallyConvex.Bounded import Mathlib.Analysis.Seminorm import Mathlib.Data.Real.Sqrt import Mathlib.Topology.Algebra.Equicontinuity import Mathlib.Topology.MetricSpace.Equicontinuity import Mathlib.Topology.Algebra.FilterBasis import Mathlib.Topology.Algebra.Module.LocallyConvex /-! # Topology induced by a family of seminorms ## Main definitions * `SeminormFamily.basisSets`: The set of open seminorm balls for a family of seminorms. * `SeminormFamily.moduleFilterBasis`: A module filter basis formed by the open balls. * `Seminorm.IsBounded`: A linear map `f : E →ₗ[𝕜] F` is bounded iff every seminorm in `F` can be bounded by a finite number of seminorms in `E`. ## Main statements * `WithSeminorms.toLocallyConvexSpace`: A space equipped with a family of seminorms is locally convex. * `WithSeminorms.firstCountable`: A space is first countable if it's topology is induced by a countable family of seminorms. ## Continuity of semilinear maps If `E` and `F` are topological vector space with the topology induced by a family of seminorms, then we have a direct method to prove that a linear map is continuous: * `Seminorm.continuous_from_bounded`: A bounded linear map `f : E →ₗ[𝕜] F` is continuous. If the topology of a space `E` is induced by a family of seminorms, then we can characterize von Neumann boundedness in terms of that seminorm family. Together with `LinearMap.continuous_of_locally_bounded` this gives general criterion for continuity. * `WithSeminorms.isVonNBounded_iff_finset_seminorm_bounded` * `WithSeminorms.isVonNBounded_iff_seminorm_bounded` * `WithSeminorms.image_isVonNBounded_iff_finset_seminorm_bounded` * `WithSeminorms.image_isVonNBounded_iff_seminorm_bounded` ## Tags seminorm, locally convex -/ open NormedField Set Seminorm TopologicalSpace Filter List open NNReal Pointwise Topology Uniformity variable {𝕜 𝕜₂ 𝕝 𝕝₂ E F G ι ι' : Type*} section FilterBasis variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] variable (𝕜 E ι) /-- An abbreviation for indexed families of seminorms. This is mainly to allow for dot-notation. -/ abbrev SeminormFamily := ι → Seminorm 𝕜 E variable {𝕜 E ι} namespace SeminormFamily /-- The sets of a filter basis for the neighborhood filter of 0. -/ def basisSets (p : SeminormFamily 𝕜 E ι) : Set (Set E) := ⋃ (s : Finset ι) (r) (_ : 0 < r), singleton (ball (s.sup p) (0 : E) r) variable (p : SeminormFamily 𝕜 E ι) theorem basisSets_iff {U : Set E} : U ∈ p.basisSets ↔ ∃ (i : Finset ι) (r : ℝ), 0 < r ∧ U = ball (i.sup p) 0 r := by simp only [basisSets, mem_iUnion, exists_prop, mem_singleton_iff] theorem basisSets_mem (i : Finset ι) {r : ℝ} (hr : 0 < r) : (i.sup p).ball 0 r ∈ p.basisSets := (basisSets_iff _).mpr ⟨i, _, hr, rfl⟩ theorem basisSets_singleton_mem (i : ι) {r : ℝ} (hr : 0 < r) : (p i).ball 0 r ∈ p.basisSets := (basisSets_iff _).mpr ⟨{i}, _, hr, by rw [Finset.sup_singleton]⟩ theorem basisSets_nonempty [Nonempty ι] : p.basisSets.Nonempty := by let i := Classical.arbitrary ι refine nonempty_def.mpr ⟨(p i).ball 0 1, ?_⟩ exact p.basisSets_singleton_mem i zero_lt_one theorem basisSets_intersect (U V : Set E) (hU : U ∈ p.basisSets) (hV : V ∈ p.basisSets) : ∃ z ∈ p.basisSets, z ⊆ U ∩ V := by classical rcases p.basisSets_iff.mp hU with ⟨s, r₁, hr₁, hU⟩ rcases p.basisSets_iff.mp hV with ⟨t, r₂, hr₂, hV⟩ use ((s ∪ t).sup p).ball 0 (min r₁ r₂) refine ⟨p.basisSets_mem (s ∪ t) (lt_min_iff.mpr ⟨hr₁, hr₂⟩), ?_⟩ rw [hU, hV, ball_finset_sup_eq_iInter _ _ _ (lt_min_iff.mpr ⟨hr₁, hr₂⟩), ball_finset_sup_eq_iInter _ _ _ hr₁, ball_finset_sup_eq_iInter _ _ _ hr₂] exact Set.subset_inter (Set.iInter₂_mono' fun i hi => ⟨i, Finset.subset_union_left hi, ball_mono <| min_le_left _ _⟩) (Set.iInter₂_mono' fun i hi => ⟨i, Finset.subset_union_right hi, ball_mono <| min_le_right _ _⟩) theorem basisSets_zero (U) (hU : U ∈ p.basisSets) : (0 : E) ∈ U := by rcases p.basisSets_iff.mp hU with ⟨ι', r, hr, hU⟩ rw [hU, mem_ball_zero, map_zero] exact hr theorem basisSets_add (U) (hU : U ∈ p.basisSets) : ∃ V ∈ p.basisSets, V + V ⊆ U := by rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩ use (s.sup p).ball 0 (r / 2) refine ⟨p.basisSets_mem s (div_pos hr zero_lt_two), ?_⟩ refine Set.Subset.trans (ball_add_ball_subset (s.sup p) (r / 2) (r / 2) 0 0) ?_ rw [hU, add_zero, add_halves] theorem basisSets_neg (U) (hU' : U ∈ p.basisSets) : ∃ V ∈ p.basisSets, V ⊆ (fun x : E => -x) ⁻¹' U := by rcases p.basisSets_iff.mp hU' with ⟨s, r, _, hU⟩ rw [hU, neg_preimage, neg_ball (s.sup p), neg_zero] exact ⟨U, hU', Eq.subset hU⟩ /-- The `addGroupFilterBasis` induced by the filter basis `Seminorm.basisSets`. -/ protected def addGroupFilterBasis [Nonempty ι] : AddGroupFilterBasis E := addGroupFilterBasisOfComm p.basisSets p.basisSets_nonempty p.basisSets_intersect p.basisSets_zero p.basisSets_add p.basisSets_neg theorem basisSets_smul_right (v : E) (U : Set E) (hU : U ∈ p.basisSets) : ∀ᶠ x : 𝕜 in 𝓝 0, x • v ∈ U := by rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩ rw [hU, Filter.eventually_iff] simp_rw [(s.sup p).mem_ball_zero, map_smul_eq_mul] by_cases h : 0 < (s.sup p) v · simp_rw [(lt_div_iff₀ h).symm] rw [← _root_.ball_zero_eq] exact Metric.ball_mem_nhds 0 (div_pos hr h) simp_rw [le_antisymm (not_lt.mp h) (apply_nonneg _ v), mul_zero, hr] exact IsOpen.mem_nhds isOpen_univ (mem_univ 0) variable [Nonempty ι] theorem basisSets_smul (U) (hU : U ∈ p.basisSets) : ∃ V ∈ 𝓝 (0 : 𝕜), ∃ W ∈ p.addGroupFilterBasis.sets, V • W ⊆ U := by rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩ refine ⟨Metric.ball 0 √r, Metric.ball_mem_nhds 0 (Real.sqrt_pos.mpr hr), ?_⟩ refine ⟨(s.sup p).ball 0 √r, p.basisSets_mem s (Real.sqrt_pos.mpr hr), ?_⟩ refine Set.Subset.trans (ball_smul_ball (s.sup p) √r √r) ?_ rw [hU, Real.mul_self_sqrt (le_of_lt hr)] theorem basisSets_smul_left (x : 𝕜) (U : Set E) (hU : U ∈ p.basisSets) : ∃ V ∈ p.addGroupFilterBasis.sets, V ⊆ (fun y : E => x • y) ⁻¹' U := by rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩ rw [hU] by_cases h : x ≠ 0 · rw [(s.sup p).smul_ball_preimage 0 r x h, smul_zero] use (s.sup p).ball 0 (r / ‖x‖) exact ⟨p.basisSets_mem s (div_pos hr (norm_pos_iff.mpr h)), Subset.rfl⟩ refine ⟨(s.sup p).ball 0 r, p.basisSets_mem s hr, ?_⟩ simp only [not_ne_iff.mp h, Set.subset_def, mem_ball_zero, hr, mem_univ, map_zero, imp_true_iff, preimage_const_of_mem, zero_smul] /-- The `moduleFilterBasis` induced by the filter basis `Seminorm.basisSets`. -/ protected def moduleFilterBasis : ModuleFilterBasis 𝕜 E where toAddGroupFilterBasis := p.addGroupFilterBasis smul' := p.basisSets_smul _ smul_left' := p.basisSets_smul_left smul_right' := p.basisSets_smul_right theorem filter_eq_iInf (p : SeminormFamily 𝕜 E ι) : p.moduleFilterBasis.toFilterBasis.filter = ⨅ i, (𝓝 0).comap (p i) := by refine le_antisymm (le_iInf fun i => ?_) ?_ · rw [p.moduleFilterBasis.toFilterBasis.hasBasis.le_basis_iff (Metric.nhds_basis_ball.comap _)] intro ε hε refine ⟨(p i).ball 0 ε, ?_, ?_⟩ · rw [← (Finset.sup_singleton : _ = p i)] exact p.basisSets_mem {i} hε · rw [id, (p i).ball_zero_eq_preimage_ball] · rw [p.moduleFilterBasis.toFilterBasis.hasBasis.ge_iff] rintro U (hU : U ∈ p.basisSets) rcases p.basisSets_iff.mp hU with ⟨s, r, hr, rfl⟩ rw [id, Seminorm.ball_finset_sup_eq_iInter _ _ _ hr, s.iInter_mem_sets] exact fun i _ => Filter.mem_iInf_of_mem i ⟨Metric.ball 0 r, Metric.ball_mem_nhds 0 hr, Eq.subset (p i).ball_zero_eq_preimage_ball.symm⟩ /-- If a family of seminorms is continuous, then their basis sets are neighborhoods of zero. -/ lemma basisSets_mem_nhds {𝕜 E ι : Type*} [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E] (p : SeminormFamily 𝕜 E ι) (hp : ∀ i, Continuous (p i)) (U : Set E) (hU : U ∈ p.basisSets) : U ∈ 𝓝 (0 : E) := by obtain ⟨s, r, hr, rfl⟩ := p.basisSets_iff.mp hU clear hU refine Seminorm.ball_mem_nhds ?_ hr classical induction s using Finset.induction_on case empty => simpa using continuous_zero case insert a s _ hs => simp only [Finset.sup_insert, coe_sup] exact Continuous.max (hp a) hs end SeminormFamily end FilterBasis section Bounded namespace Seminorm variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] variable [NormedField 𝕜₂] [AddCommGroup F] [Module 𝕜₂ F] variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂] -- Todo: This should be phrased entirely in terms of the von Neumann bornology. /-- The proposition that a linear map is bounded between spaces with families of seminorms. -/ def IsBounded (p : ι → Seminorm 𝕜 E) (q : ι' → Seminorm 𝕜₂ F) (f : E →ₛₗ[σ₁₂] F) : Prop := ∀ i, ∃ s : Finset ι, ∃ C : ℝ≥0, (q i).comp f ≤ C • s.sup p theorem isBounded_const (ι' : Type*) [Nonempty ι'] {p : ι → Seminorm 𝕜 E} {q : Seminorm 𝕜₂ F} (f : E →ₛₗ[σ₁₂] F) : IsBounded p (fun _ : ι' => q) f ↔ ∃ (s : Finset ι) (C : ℝ≥0), q.comp f ≤ C • s.sup p := by simp only [IsBounded, forall_const] theorem const_isBounded (ι : Type*) [Nonempty ι] {p : Seminorm 𝕜 E} {q : ι' → Seminorm 𝕜₂ F} (f : E →ₛₗ[σ₁₂] F) : IsBounded (fun _ : ι => p) q f ↔ ∀ i, ∃ C : ℝ≥0, (q i).comp f ≤ C • p := by constructor <;> intro h i · rcases h i with ⟨s, C, h⟩ exact ⟨C, le_trans h (smul_le_smul (Finset.sup_le fun _ _ => le_rfl) le_rfl)⟩ use {Classical.arbitrary ι} simp only [h, Finset.sup_singleton] theorem isBounded_sup {p : ι → Seminorm 𝕜 E} {q : ι' → Seminorm 𝕜₂ F} {f : E →ₛₗ[σ₁₂] F} (hf : IsBounded p q f) (s' : Finset ι') : ∃ (C : ℝ≥0) (s : Finset ι), (s'.sup q).comp f ≤ C • s.sup p := by classical obtain rfl | _ := s'.eq_empty_or_nonempty · exact ⟨1, ∅, by simp [Seminorm.bot_eq_zero]⟩ choose fₛ fC hf using hf use s'.card • s'.sup fC, Finset.biUnion s' fₛ have hs : ∀ i : ι', i ∈ s' → (q i).comp f ≤ s'.sup fC • (Finset.biUnion s' fₛ).sup p := by intro i hi refine (hf i).trans (smul_le_smul ?_ (Finset.le_sup hi)) exact Finset.sup_mono (Finset.subset_biUnion_of_mem fₛ hi) refine (comp_mono f (finset_sup_le_sum q s')).trans ?_ simp_rw [← pullback_apply, map_sum, pullback_apply] refine (Finset.sum_le_sum hs).trans ?_ rw [Finset.sum_const, smul_assoc] end Seminorm end Bounded section Topology variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [Nonempty ι] /-- The proposition that the topology of `E` is induced by a family of seminorms `p`. -/ structure WithSeminorms (p : SeminormFamily 𝕜 E ι) [topology : TopologicalSpace E] : Prop where topology_eq_withSeminorms : topology = p.moduleFilterBasis.topology theorem WithSeminorms.withSeminorms_eq {p : SeminormFamily 𝕜 E ι} [t : TopologicalSpace E] (hp : WithSeminorms p) : t = p.moduleFilterBasis.topology := hp.1 variable [TopologicalSpace E] variable {p : SeminormFamily 𝕜 E ι} theorem WithSeminorms.topologicalAddGroup (hp : WithSeminorms p) : IsTopologicalAddGroup E := by rw [hp.withSeminorms_eq] exact AddGroupFilterBasis.isTopologicalAddGroup _ theorem WithSeminorms.continuousSMul (hp : WithSeminorms p) : ContinuousSMul 𝕜 E := by rw [hp.withSeminorms_eq] exact ModuleFilterBasis.continuousSMul _ theorem WithSeminorms.hasBasis (hp : WithSeminorms p) : (𝓝 (0 : E)).HasBasis (fun s : Set E => s ∈ p.basisSets) id := by rw [congr_fun (congr_arg (@nhds E) hp.1) 0] exact AddGroupFilterBasis.nhds_zero_hasBasis _ theorem WithSeminorms.hasBasis_zero_ball (hp : WithSeminorms p) : (𝓝 (0 : E)).HasBasis (fun sr : Finset ι × ℝ => 0 < sr.2) fun sr => (sr.1.sup p).ball 0 sr.2 := by refine ⟨fun V => ?_⟩ simp only [hp.hasBasis.mem_iff, SeminormFamily.basisSets_iff, Prod.exists] constructor · rintro ⟨-, ⟨s, r, hr, rfl⟩, hV⟩ exact ⟨s, r, hr, hV⟩ · rintro ⟨s, r, hr, hV⟩ exact ⟨_, ⟨s, r, hr, rfl⟩, hV⟩ theorem WithSeminorms.hasBasis_ball (hp : WithSeminorms p) {x : E} : (𝓝 (x : E)).HasBasis (fun sr : Finset ι × ℝ => 0 < sr.2) fun sr => (sr.1.sup p).ball x sr.2 := by have : IsTopologicalAddGroup E := hp.topologicalAddGroup rw [← map_add_left_nhds_zero] convert hp.hasBasis_zero_ball.map (x + ·) using 1 ext sr : 1 -- Porting note: extra type ascriptions needed on `0` have : (sr.fst.sup p).ball (x +ᵥ (0 : E)) sr.snd = x +ᵥ (sr.fst.sup p).ball 0 sr.snd := Eq.symm (Seminorm.vadd_ball (sr.fst.sup p)) rwa [vadd_eq_add, add_zero] at this /-- The `x`-neighbourhoods of a space whose topology is induced by a family of seminorms are exactly the sets which contain seminorm balls around `x`. -/ theorem WithSeminorms.mem_nhds_iff (hp : WithSeminorms p) (x : E) (U : Set E) : U ∈ 𝓝 x ↔ ∃ s : Finset ι, ∃ r > 0, (s.sup p).ball x r ⊆ U := by rw [hp.hasBasis_ball.mem_iff, Prod.exists] /-- The open sets of a space whose topology is induced by a family of seminorms are exactly the sets which contain seminorm balls around all of their points. -/ theorem WithSeminorms.isOpen_iff_mem_balls (hp : WithSeminorms p) (U : Set E) : IsOpen U ↔ ∀ x ∈ U, ∃ s : Finset ι, ∃ r > 0, (s.sup p).ball x r ⊆ U := by simp_rw [← WithSeminorms.mem_nhds_iff hp _ U, isOpen_iff_mem_nhds] /- Note that through the following lemmas, one also immediately has that separating families of seminorms induce T₂ and T₃ topologies by `IsTopologicalAddGroup.t2Space` and `IsTopologicalAddGroup.t3Space` -/ /-- A separating family of seminorms induces a T₁ topology. -/ theorem WithSeminorms.T1_of_separating (hp : WithSeminorms p) (h : ∀ x, x ≠ 0 → ∃ i, p i x ≠ 0) : T1Space E := by have := hp.topologicalAddGroup refine IsTopologicalAddGroup.t1Space _ ?_ rw [← isOpen_compl_iff, hp.isOpen_iff_mem_balls] rintro x (hx : x ≠ 0) obtain ⟨i, pi_nonzero⟩ := h x hx refine ⟨{i}, p i x, by positivity, subset_compl_singleton_iff.mpr ?_⟩ rw [Finset.sup_singleton, mem_ball, zero_sub, map_neg_eq_map, not_lt] /-- A family of seminorms inducing a T₁ topology is separating. -/ theorem WithSeminorms.separating_of_T1 [T1Space E] (hp : WithSeminorms p) (x : E) (hx : x ≠ 0) : ∃ i, p i x ≠ 0 := by have := ((t1Space_TFAE E).out 0 9).mp (inferInstanceAs <| T1Space E) by_contra! h refine hx (this ?_) rw [hp.hasBasis_zero_ball.specializes_iff] rintro ⟨s, r⟩ (hr : 0 < r) simp only [ball_finset_sup_eq_iInter _ _ _ hr, mem_iInter₂, mem_ball_zero, h, hr, forall_true_iff] /-- A family of seminorms is separating iff it induces a T₁ topology. -/ theorem WithSeminorms.separating_iff_T1 (hp : WithSeminorms p) : (∀ x, x ≠ 0 → ∃ i, p i x ≠ 0) ↔ T1Space E := by refine ⟨WithSeminorms.T1_of_separating hp, ?_⟩ intro exact WithSeminorms.separating_of_T1 hp end Topology section Tendsto variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [Nonempty ι] [TopologicalSpace E] variable {p : SeminormFamily 𝕜 E ι} /-- Convergence along filters for `WithSeminorms`. Variant with `Finset.sup`. -/ theorem WithSeminorms.tendsto_nhds' (hp : WithSeminorms p) (u : F → E) {f : Filter F} (y₀ : E) : Filter.Tendsto u f (𝓝 y₀) ↔ ∀ (s : Finset ι) (ε), 0 < ε → ∀ᶠ x in f, s.sup p (u x - y₀) < ε := by simp [hp.hasBasis_ball.tendsto_right_iff] /-- Convergence along filters for `WithSeminorms`. -/ theorem WithSeminorms.tendsto_nhds (hp : WithSeminorms p) (u : F → E) {f : Filter F} (y₀ : E) : Filter.Tendsto u f (𝓝 y₀) ↔ ∀ i ε, 0 < ε → ∀ᶠ x in f, p i (u x - y₀) < ε := by rw [hp.tendsto_nhds' u y₀] exact ⟨fun h i => by simpa only [Finset.sup_singleton] using h {i}, fun h s ε hε => (s.eventually_all.2 fun i _ => h i ε hε).mono fun _ => finset_sup_apply_lt hε⟩ variable [SemilatticeSup F] [Nonempty F] /-- Limit `→ ∞` for `WithSeminorms`. -/ theorem WithSeminorms.tendsto_nhds_atTop (hp : WithSeminorms p) (u : F → E) (y₀ : E) : Filter.Tendsto u Filter.atTop (𝓝 y₀) ↔ ∀ i ε, 0 < ε → ∃ x₀, ∀ x, x₀ ≤ x → p i (u x - y₀) < ε := by rw [hp.tendsto_nhds u y₀] exact forall₃_congr fun _ _ _ => Filter.eventually_atTop end Tendsto section IsTopologicalAddGroup variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] variable [Nonempty ι] section TopologicalSpace variable [t : TopologicalSpace E] theorem SeminormFamily.withSeminorms_of_nhds [IsTopologicalAddGroup E] (p : SeminormFamily 𝕜 E ι) (h : 𝓝 (0 : E) = p.moduleFilterBasis.toFilterBasis.filter) : WithSeminorms p := by refine ⟨IsTopologicalAddGroup.ext inferInstance p.addGroupFilterBasis.isTopologicalAddGroup ?_⟩ rw [AddGroupFilterBasis.nhds_zero_eq] exact h theorem SeminormFamily.withSeminorms_of_hasBasis [IsTopologicalAddGroup E] (p : SeminormFamily 𝕜 E ι) (h : (𝓝 (0 : E)).HasBasis (fun s : Set E => s ∈ p.basisSets) id) : WithSeminorms p := p.withSeminorms_of_nhds <| Filter.HasBasis.eq_of_same_basis h p.addGroupFilterBasis.toFilterBasis.hasBasis theorem SeminormFamily.withSeminorms_iff_nhds_eq_iInf [IsTopologicalAddGroup E] (p : SeminormFamily 𝕜 E ι) : WithSeminorms p ↔ (𝓝 (0 : E)) = ⨅ i, (𝓝 0).comap (p i) := by rw [← p.filter_eq_iInf] refine ⟨fun h => ?_, p.withSeminorms_of_nhds⟩ rw [h.topology_eq_withSeminorms] exact AddGroupFilterBasis.nhds_zero_eq _ /-- The topology induced by a family of seminorms is exactly the infimum of the ones induced by each seminorm individually. We express this as a characterization of `WithSeminorms p`. -/ theorem SeminormFamily.withSeminorms_iff_topologicalSpace_eq_iInf [IsTopologicalAddGroup E] (p : SeminormFamily 𝕜 E ι) : WithSeminorms p ↔ t = ⨅ i, (p i).toSeminormedAddCommGroup.toUniformSpace.toTopologicalSpace := by rw [p.withSeminorms_iff_nhds_eq_iInf, IsTopologicalAddGroup.ext_iff inferInstance (topologicalAddGroup_iInf fun i => inferInstance), nhds_iInf] congrm _ = ⨅ i, ?_ exact @comap_norm_nhds_zero _ (p i).toSeminormedAddGroup theorem WithSeminorms.continuous_seminorm {p : SeminormFamily 𝕜 E ι} (hp : WithSeminorms p) (i : ι) : Continuous (p i) := by have := hp.topologicalAddGroup rw [p.withSeminorms_iff_topologicalSpace_eq_iInf.mp hp] exact continuous_iInf_dom (@continuous_norm _ (p i).toSeminormedAddGroup) end TopologicalSpace /-- The uniform structure induced by a family of seminorms is exactly the infimum of the ones induced by each seminorm individually. We express this as a characterization of `WithSeminorms p`. -/ theorem SeminormFamily.withSeminorms_iff_uniformSpace_eq_iInf [u : UniformSpace E] [IsUniformAddGroup E] (p : SeminormFamily 𝕜 E ι) : WithSeminorms p ↔ u = ⨅ i, (p i).toSeminormedAddCommGroup.toUniformSpace := by rw [p.withSeminorms_iff_nhds_eq_iInf, IsUniformAddGroup.ext_iff inferInstance (isUniformAddGroup_iInf fun i => inferInstance), UniformSpace.toTopologicalSpace_iInf, nhds_iInf] congrm _ = ⨅ i, ?_ exact @comap_norm_nhds_zero _ (p i).toAddGroupSeminorm.toSeminormedAddGroup end IsTopologicalAddGroup section NormedSpace /-- The topology of a `NormedSpace 𝕜 E` is induced by the seminorm `normSeminorm 𝕜 E`. -/ theorem norm_withSeminorms (𝕜 E) [NormedField 𝕜] [SeminormedAddCommGroup E] [NormedSpace 𝕜 E] : WithSeminorms fun _ : Fin 1 => normSeminorm 𝕜 E := by let p : SeminormFamily 𝕜 E (Fin 1) := fun _ => normSeminorm 𝕜 E refine ⟨SeminormedAddCommGroup.toIsTopologicalAddGroup.ext p.addGroupFilterBasis.isTopologicalAddGroup ?_⟩ refine Filter.HasBasis.eq_of_same_basis Metric.nhds_basis_ball ?_ rw [← ball_normSeminorm 𝕜 E] refine Filter.HasBasis.to_hasBasis p.addGroupFilterBasis.nhds_zero_hasBasis ?_ fun r hr => ⟨(normSeminorm 𝕜 E).ball 0 r, p.basisSets_singleton_mem 0 hr, rfl.subset⟩ rintro U (hU : U ∈ p.basisSets) rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩ use r, hr rw [hU, id] by_cases h : s.Nonempty · rw [Finset.sup_const h] rw [Finset.not_nonempty_iff_eq_empty.mp h, Finset.sup_empty, ball_bot _ hr] exact Set.subset_univ _ end NormedSpace section NontriviallyNormedField variable [NontriviallyNormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [Nonempty ι] variable {p : SeminormFamily 𝕜 E ι} variable [TopologicalSpace E] theorem WithSeminorms.isVonNBounded_iff_finset_seminorm_bounded {s : Set E} (hp : WithSeminorms p) : Bornology.IsVonNBounded 𝕜 s ↔ ∀ I : Finset ι, ∃ r > 0, ∀ x ∈ s, I.sup p x < r := by rw [hp.hasBasis.isVonNBounded_iff] constructor · intro h I simp only [id] at h specialize h ((I.sup p).ball 0 1) (p.basisSets_mem I zero_lt_one) rcases h.exists_pos with ⟨r, hr, h⟩ obtain ⟨a, ha⟩ := NormedField.exists_lt_norm 𝕜 r specialize h a (le_of_lt ha) rw [Seminorm.smul_ball_zero (norm_pos_iff.1 <| hr.trans ha), mul_one] at h refine ⟨‖a‖, lt_trans hr ha, ?_⟩ intro x hx specialize h hx exact (Finset.sup I p).mem_ball_zero.mp h intro h s' hs' rcases p.basisSets_iff.mp hs' with ⟨I, r, hr, hs'⟩ rw [id, hs'] rcases h I with ⟨r', _, h'⟩ simp_rw [← (I.sup p).mem_ball_zero] at h' refine Absorbs.mono_right ?_ h' exact (Finset.sup I p).ball_zero_absorbs_ball_zero hr theorem WithSeminorms.image_isVonNBounded_iff_finset_seminorm_bounded (f : G → E) {s : Set G} (hp : WithSeminorms p) : Bornology.IsVonNBounded 𝕜 (f '' s) ↔ ∀ I : Finset ι, ∃ r > 0, ∀ x ∈ s, I.sup p (f x) < r := by simp_rw [hp.isVonNBounded_iff_finset_seminorm_bounded, Set.forall_mem_image] theorem WithSeminorms.isVonNBounded_iff_seminorm_bounded {s : Set E} (hp : WithSeminorms p) : Bornology.IsVonNBounded 𝕜 s ↔ ∀ i : ι, ∃ r > 0, ∀ x ∈ s, p i x < r := by rw [hp.isVonNBounded_iff_finset_seminorm_bounded] constructor · intro hI i convert hI {i} rw [Finset.sup_singleton] intro hi I by_cases hI : I.Nonempty · choose r hr h using hi have h' : 0 < I.sup' hI r := by rcases hI with ⟨i, hi⟩ exact lt_of_lt_of_le (hr i) (Finset.le_sup' r hi) refine ⟨I.sup' hI r, h', fun x hx => finset_sup_apply_lt h' fun i hi => ?_⟩ refine lt_of_lt_of_le (h i x hx) ?_ simp only [Finset.le_sup'_iff, exists_prop] exact ⟨i, hi, (Eq.refl _).le⟩ simp only [Finset.not_nonempty_iff_eq_empty.mp hI, Finset.sup_empty, coe_bot, Pi.zero_apply, exists_prop] exact ⟨1, zero_lt_one, fun _ _ => zero_lt_one⟩ theorem WithSeminorms.image_isVonNBounded_iff_seminorm_bounded (f : G → E) {s : Set G} (hp : WithSeminorms p) : Bornology.IsVonNBounded 𝕜 (f '' s) ↔ ∀ i : ι, ∃ r > 0, ∀ x ∈ s, p i (f x) < r := by simp_rw [hp.isVonNBounded_iff_seminorm_bounded, Set.forall_mem_image] end NontriviallyNormedField -- TODO: the names in this section are not very predictable section continuous_of_bounded namespace Seminorm variable [NontriviallyNormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] variable [NormedField 𝕝] [Module 𝕝 E] variable [NontriviallyNormedField 𝕜₂] [AddCommGroup F] [Module 𝕜₂ F] variable [NormedField 𝕝₂] [Module 𝕝₂ F] variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂] variable {τ₁₂ : 𝕝 →+* 𝕝₂} [RingHomIsometric τ₁₂] variable [Nonempty ι] [Nonempty ι'] theorem continuous_of_continuous_comp {q : SeminormFamily 𝕝₂ F ι'} [TopologicalSpace E] [IsTopologicalAddGroup E] [TopologicalSpace F] (hq : WithSeminorms q) (f : E →ₛₗ[τ₁₂] F) (hf : ∀ i, Continuous ((q i).comp f)) : Continuous f := by have : IsTopologicalAddGroup F := hq.topologicalAddGroup refine continuous_of_continuousAt_zero f ?_ simp_rw [ContinuousAt, f.map_zero, q.withSeminorms_iff_nhds_eq_iInf.mp hq, Filter.tendsto_iInf, Filter.tendsto_comap_iff] intro i convert (hf i).continuousAt.tendsto exact (map_zero _).symm theorem continuous_iff_continuous_comp {q : SeminormFamily 𝕜₂ F ι'} [TopologicalSpace E] [IsTopologicalAddGroup E] [TopologicalSpace F] (hq : WithSeminorms q) (f : E →ₛₗ[σ₁₂] F) : Continuous f ↔ ∀ i, Continuous ((q i).comp f) := ⟨fun h i => (hq.continuous_seminorm i).comp h, continuous_of_continuous_comp hq f⟩ theorem continuous_from_bounded {p : SeminormFamily 𝕝 E ι} {q : SeminormFamily 𝕝₂ F ι'} {_ : TopologicalSpace E} (hp : WithSeminorms p) {_ : TopologicalSpace F} (hq : WithSeminorms q) (f : E →ₛₗ[τ₁₂] F) (hf : Seminorm.IsBounded p q f) : Continuous f := by have : IsTopologicalAddGroup E := hp.topologicalAddGroup refine continuous_of_continuous_comp hq _ fun i => ?_ rcases hf i with ⟨s, C, hC⟩ rw [← Seminorm.finset_sup_smul] at hC -- Note: we deduce continuouty of `s.sup (C • p)` from that of `∑ i ∈ s, C • p i`. -- The reason is that there is no `continuous_finset_sup`, and even if it were we couldn't -- really use it since `ℝ` is not an `OrderBot`. refine Seminorm.continuous_of_le ?_ (hC.trans <| Seminorm.finset_sup_le_sum _ _) change Continuous (fun x ↦ Seminorm.coeFnAddMonoidHom _ _ (∑ i ∈ s, C • p i) x) simp_rw [map_sum, Finset.sum_apply] exact (continuous_finset_sum _ fun i _ ↦ (hp.continuous_seminorm i).const_smul (C : ℝ)) theorem cont_withSeminorms_normedSpace (F) [SeminormedAddCommGroup F] [NormedSpace 𝕝₂ F] [TopologicalSpace E] {p : ι → Seminorm 𝕝 E} (hp : WithSeminorms p) (f : E →ₛₗ[τ₁₂] F) (hf : ∃ (s : Finset ι) (C : ℝ≥0), (normSeminorm 𝕝₂ F).comp f ≤ C • s.sup p) : Continuous f := by rw [← Seminorm.isBounded_const (Fin 1)] at hf exact continuous_from_bounded hp (norm_withSeminorms 𝕝₂ F) f hf theorem cont_normedSpace_to_withSeminorms (E) [SeminormedAddCommGroup E] [NormedSpace 𝕝 E] [TopologicalSpace F] {q : ι → Seminorm 𝕝₂ F} (hq : WithSeminorms q)
(f : E →ₛₗ[τ₁₂] F) (hf : ∀ i : ι, ∃ C : ℝ≥0, (q i).comp f ≤ C • normSeminorm 𝕝 E) : Continuous f := by rw [← Seminorm.const_isBounded (Fin 1)] at hf exact continuous_from_bounded (norm_withSeminorms 𝕝 E) hq f hf /-- Let `E` and `F` be two topological vector spaces over a `NontriviallyNormedField`, and assume that the topology of `F` is generated by some family of seminorms `q`. For a family `f` of linear maps from `E` to `F`, the following are equivalent: * `f` is equicontinuous at `0`. * `f` is equicontinuous.
Mathlib/Analysis/LocallyConvex/WithSeminorms.lean
589
598
/- Copyright (c) 2022 Jireh Loreaux. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Jireh Loreaux -/ import Mathlib.Algebra.Star.Basic import Mathlib.Data.Set.Finite.Basic import Mathlib.Data.Set.Lattice.Image import Mathlib.Algebra.Group.Pointwise.Set.Basic /-! # Pointwise star operation on sets This file defines the star operation pointwise on sets and provides the basic API. Besides basic facts about how the star operation acts on sets (e.g., `(s ∩ t)⋆ = s⋆ ∩ t⋆`), if `s t : Set α`, then under suitable assumption on `α`, it is shown * `(s + t)⋆ = s⋆ + t⋆` * `(s * t)⋆ = t⋆ + s⋆` * `(s⁻¹)⋆ = (s⋆)⁻¹` -/ namespace Set open Pointwise local postfix:max "⋆" => star variable {α : Type*} {s t : Set α} {a : α} /-- The set `(star s : Set α)` is defined as `{x | star x ∈ s}` in the locale `Pointwise`. In the usual case where `star` is involutive, it is equal to `{star s | x ∈ s}`, see `Set.image_star`. -/ protected def star [Star α] : Star (Set α) := ⟨preimage Star.star⟩ scoped[Pointwise] attribute [instance] Set.star @[simp] theorem star_empty [Star α] : (∅ : Set α)⋆ = ∅ := rfl @[simp] theorem star_univ [Star α] : (univ : Set α)⋆ = univ := rfl @[simp] theorem nonempty_star [InvolutiveStar α] {s : Set α} : s⋆.Nonempty ↔ s.Nonempty := star_involutive.surjective.nonempty_preimage theorem Nonempty.star [InvolutiveStar α] {s : Set α} (h : s.Nonempty) : s⋆.Nonempty := nonempty_star.2 h @[simp] theorem mem_star [Star α] : a ∈ s⋆ ↔ a⋆ ∈ s := Iff.rfl theorem star_mem_star [InvolutiveStar α] : a⋆ ∈ s⋆ ↔ a ∈ s := by simp only [mem_star, star_star] @[simp] theorem star_preimage [Star α] : Star.star ⁻¹' s = s⋆ := rfl @[simp] theorem image_star [InvolutiveStar α] : Star.star '' s = s⋆ := by simp only [← star_preimage] rw [image_eq_preimage_of_inverse] <;> intro <;> simp only [star_star] @[simp] theorem inter_star [Star α] : (s ∩ t)⋆ = s⋆ ∩ t⋆ := preimage_inter @[simp] theorem union_star [Star α] : (s ∪ t)⋆ = s⋆ ∪ t⋆ := preimage_union @[simp] theorem iInter_star {ι : Sort*} [Star α] (s : ι → Set α) : (⋂ i, s i)⋆ = ⋂ i, (s i)⋆ := preimage_iInter @[simp] theorem iUnion_star {ι : Sort*} [Star α] (s : ι → Set α) : (⋃ i, s i)⋆ = ⋃ i, (s i)⋆ := preimage_iUnion @[simp] theorem compl_star [Star α] : sᶜ⋆ = s⋆ᶜ := preimage_compl @[simp] instance [InvolutiveStar α] : InvolutiveStar (Set α) where star := Star.star star_involutive s := by simp only [← star_preimage, preimage_preimage, star_star, preimage_id'] @[simp] theorem star_subset_star [InvolutiveStar α] {s t : Set α} : s⋆ ⊆ t⋆ ↔ s ⊆ t := Equiv.star.surjective.preimage_subset_preimage_iff theorem star_subset [InvolutiveStar α] {s t : Set α} : s⋆ ⊆ t ↔ s ⊆ t⋆ := by rw [← star_subset_star, star_star] theorem Finite.star [InvolutiveStar α] {s : Set α} (hs : s.Finite) : s⋆.Finite := hs.preimage star_injective.injOn theorem star_singleton {β : Type*} [InvolutiveStar β] (x : β) : ({x} : Set β)⋆ = {x⋆} := by ext1 y rw [mem_star, mem_singleton_iff, mem_singleton_iff, star_eq_iff_star_eq, eq_comm] protected theorem star_mul [Mul α] [StarMul α] (s t : Set α) : (s * t)⋆ = t⋆ * s⋆ := by simp_rw [← image_star, ← image2_mul, image_image2, image2_image_left, image2_image_right, star_mul, image2_swap _ s t] protected theorem star_add [AddMonoid α] [StarAddMonoid α] (s t : Set α) : (s + t)⋆ = s⋆ + t⋆ := by simp_rw [← image_star, ← image2_add, image_image2, image2_image_left, image2_image_right, star_add] @[simp] instance [Star α] [TrivialStar α] : TrivialStar (Set α) where star_trivial s := by rw [← star_preimage] ext1 simp [star_trivial]
protected theorem star_inv [Group α] [StarMul α] (s : Set α) : s⁻¹⋆ = s⋆⁻¹ := by ext
Mathlib/Algebra/Star/Pointwise.lean
115
117
/- Copyright (c) 2022 Moritz Doll. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Moritz Doll -/ import Mathlib.Analysis.InnerProductSpace.Adjoint import Mathlib.Topology.Algebra.Module.Equiv /-! # Partially defined linear operators on Hilbert spaces We will develop the basics of the theory of unbounded operators on Hilbert spaces. ## Main definitions * `LinearPMap.IsFormalAdjoint`: An operator `T` is a formal adjoint of `S` if for all `x` in the domain of `T` and `y` in the domain of `S`, we have that `⟪T x, y⟫ = ⟪x, S y⟫`. * `LinearPMap.adjoint`: The adjoint of a map `E →ₗ.[𝕜] F` as a map `F →ₗ.[𝕜] E`. ## Main statements * `LinearPMap.adjoint_isFormalAdjoint`: The adjoint is a formal adjoint * `LinearPMap.IsFormalAdjoint.le_adjoint`: Every formal adjoint is contained in the adjoint * `ContinuousLinearMap.toPMap_adjoint_eq_adjoint_toPMap_of_dense`: The adjoint on `ContinuousLinearMap` and `LinearPMap` coincide. ## Notation * For `T : E →ₗ.[𝕜] F` the adjoint can be written as `T†`. This notation is localized in `LinearPMap`. ## Implementation notes We use the junk value pattern to define the adjoint for all `LinearPMap`s. In the case that `T : E →ₗ.[𝕜] F` is not densely defined the adjoint `T†` is the zero map from `T.adjoint.domain` to `E`. ## References * [J. Weidmann, *Linear Operators in Hilbert Spaces*][weidmann_linear] ## Tags Unbounded operators, closed operators -/ noncomputable section open RCLike open scoped ComplexConjugate variable {𝕜 E F : Type*} [RCLike 𝕜] variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E] variable [NormedAddCommGroup F] [InnerProductSpace 𝕜 F] local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y namespace LinearPMap /-- An operator `T` is a formal adjoint of `S` if for all `x` in the domain of `T` and `y` in the domain of `S`, we have that `⟪T x, y⟫ = ⟪x, S y⟫`. -/ def IsFormalAdjoint (T : E →ₗ.[𝕜] F) (S : F →ₗ.[𝕜] E) : Prop := ∀ (x : T.domain) (y : S.domain), ⟪T x, y⟫ = ⟪(x : E), S y⟫ variable {T : E →ₗ.[𝕜] F} {S : F →ₗ.[𝕜] E} @[symm] protected theorem IsFormalAdjoint.symm (h : T.IsFormalAdjoint S) : S.IsFormalAdjoint T := fun y _ => by rw [← inner_conj_symm, ← inner_conj_symm (y : F), h]
variable (T)
Mathlib/Analysis/InnerProductSpace/LinearPMap.lean
74
76
/- Copyright (c) 2019 Chris Hughes. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Chris Hughes -/ import Mathlib.Data.Option.Basic import Batteries.Tactic.Congr import Mathlib.Data.Set.Basic import Mathlib.Tactic.Contrapose /-! # Partial Equivalences In this file, we define partial equivalences `PEquiv`, which are a bijection between a subset of `α` and a subset of `β`. Notationally, a `PEquiv` is denoted by "`≃.`" (note that the full stop is part of the notation). The way we store these internally is with two functions `f : α → Option β` and the reverse function `g : β → Option α`, with the condition that if `f a` is `some b`, then `g b` is `some a`. ## Main results - `PEquiv.ofSet`: creates a `PEquiv` from a set `s`, which sends an element to itself if it is in `s`. - `PEquiv.single`: given two elements `a : α` and `b : β`, create a `PEquiv` that sends them to each other, and ignores all other elements. - `PEquiv.injective_of_forall_ne_isSome`/`injective_of_forall_isSome`: If the domain of a `PEquiv` is all of `α` (except possibly one point), its `toFun` is injective. ## Canonical order `PEquiv` is canonically ordered by inclusion; that is, if a function `f` defined on a subset `s` is equal to `g` on that subset, but `g` is also defined on a larger set, then `f ≤ g`. We also have a definition of `⊥`, which is the empty `PEquiv` (sends all to `none`), which in the end gives us a `SemilatticeInf` with an `OrderBot` instance. ## Tags pequiv, partial equivalence -/ assert_not_exists RelIso universe u v w x /-- A `PEquiv` is a partial equivalence, a representation of a bijection between a subset of `α` and a subset of `β`. See also `PartialEquiv` for a version that requires `toFun` and `invFun` to be globally defined functions and has `source` and `target` sets as extra fields. -/ structure PEquiv (α : Type u) (β : Type v) where /-- The underlying partial function of a `PEquiv` -/ toFun : α → Option β /-- The partial inverse of `toFun` -/ invFun : β → Option α /-- `invFun` is the partial inverse of `toFun` -/ inv : ∀ (a : α) (b : β), a ∈ invFun b ↔ b ∈ toFun a /-- A `PEquiv` is a partial equivalence, a representation of a bijection between a subset of `α` and a subset of `β`. See also `PartialEquiv` for a version that requires `toFun` and `invFun` to be globally defined functions and has `source` and `target` sets as extra fields. -/ infixr:25 " ≃. " => PEquiv namespace PEquiv variable {α : Type u} {β : Type v} {γ : Type w} {δ : Type x} open Function Option instance : FunLike (α ≃. β) α (Option β) := { coe := toFun coe_injective' := by rintro ⟨f₁, f₂, hf⟩ ⟨g₁, g₂, hg⟩ (rfl : f₁ = g₁) congr with y x simp only [hf, hg] } @[simp] theorem coe_mk (f₁ : α → Option β) (f₂ h) : (mk f₁ f₂ h : α → Option β) = f₁ := rfl theorem coe_mk_apply (f₁ : α → Option β) (f₂ : β → Option α) (h) (x : α) : (PEquiv.mk f₁ f₂ h : α → Option β) x = f₁ x := rfl @[ext] theorem ext {f g : α ≃. β} (h : ∀ x, f x = g x) : f = g := DFunLike.ext f g h /-- The identity map as a partial equivalence. -/ @[refl] protected def refl (α : Type*) : α ≃. α where toFun := some invFun := some inv _ _ := eq_comm /-- The inverse partial equivalence. -/ @[symm] protected def symm (f : α ≃. β) : β ≃. α where toFun := f.2 invFun := f.1 inv _ _ := (f.inv _ _).symm theorem mem_iff_mem (f : α ≃. β) : ∀ {a : α} {b : β}, a ∈ f.symm b ↔ b ∈ f a := f.3 _ _ theorem eq_some_iff (f : α ≃. β) : ∀ {a : α} {b : β}, f.symm b = some a ↔ f a = some b := f.3 _ _ /-- Composition of partial equivalences `f : α ≃. β` and `g : β ≃. γ`. -/ @[trans] protected def trans (f : α ≃. β) (g : β ≃. γ) : α ≃. γ where toFun a := (f a).bind g invFun a := (g.symm a).bind f.symm inv a b := by simp_all [and_comm, eq_some_iff f, eq_some_iff g, bind_eq_some_iff] @[simp] theorem refl_apply (a : α) : PEquiv.refl α a = some a := rfl @[simp] theorem symm_refl : (PEquiv.refl α).symm = PEquiv.refl α := rfl @[simp] theorem symm_symm (f : α ≃. β) : f.symm.symm = f := rfl theorem symm_bijective : Function.Bijective (PEquiv.symm : (α ≃. β) → β ≃. α) := Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩ theorem symm_injective : Function.Injective (@PEquiv.symm α β) := symm_bijective.injective theorem trans_assoc (f : α ≃. β) (g : β ≃. γ) (h : γ ≃. δ) : (f.trans g).trans h = f.trans (g.trans h) := ext fun _ => Option.bind_assoc _ _ _ theorem mem_trans (f : α ≃. β) (g : β ≃. γ) (a : α) (c : γ) : c ∈ f.trans g a ↔ ∃ b, b ∈ f a ∧ c ∈ g b := Option.bind_eq_some' theorem trans_eq_some (f : α ≃. β) (g : β ≃. γ) (a : α) (c : γ) : f.trans g a = some c ↔ ∃ b, f a = some b ∧ g b = some c := Option.bind_eq_some' theorem trans_eq_none (f : α ≃. β) (g : β ≃. γ) (a : α) : f.trans g a = none ↔ ∀ b c, b ∉ f a ∨ c ∉ g b := by simp only [eq_none_iff_forall_not_mem, mem_trans, imp_iff_not_or.symm] push_neg exact forall_swap @[simp] theorem refl_trans (f : α ≃. β) : (PEquiv.refl α).trans f = f := by ext; dsimp [PEquiv.trans]; rfl @[simp] theorem trans_refl (f : α ≃. β) : f.trans (PEquiv.refl β) = f := by ext; dsimp [PEquiv.trans]; simp protected theorem inj (f : α ≃. β) {a₁ a₂ : α} {b : β} (h₁ : b ∈ f a₁) (h₂ : b ∈ f a₂) : a₁ = a₂ := by rw [← mem_iff_mem] at *; cases h : f.symm b <;> simp_all /-- If the domain of a `PEquiv` is `α` except a point, its forward direction is injective. -/ theorem injective_of_forall_ne_isSome (f : α ≃. β) (a₂ : α) (h : ∀ a₁ : α, a₁ ≠ a₂ → isSome (f a₁)) : Injective f := HasLeftInverse.injective ⟨fun b => Option.recOn b a₂ fun b' => Option.recOn (f.symm b') a₂ id, fun x => by classical cases hfx : f x · have : x = a₂ := not_imp_comm.1 (h x) (hfx.symm ▸ by simp) simp [this] · dsimp only rw [(eq_some_iff f).2 hfx] rfl⟩ /-- If the domain of a `PEquiv` is all of `α`, its forward direction is injective. -/ theorem injective_of_forall_isSome {f : α ≃. β} (h : ∀ a : α, isSome (f a)) : Injective f := (Classical.em (Nonempty α)).elim (fun hn => injective_of_forall_ne_isSome f (Classical.choice hn) fun a _ => h a) fun hn x => (hn ⟨x⟩).elim section OfSet variable (s : Set α) [DecidablePred (· ∈ s)] /-- Creates a `PEquiv` that is the identity on `s`, and `none` outside of it. -/ def ofSet (s : Set α) [DecidablePred (· ∈ s)] : α ≃. α where toFun a := if a ∈ s then some a else none invFun a := if a ∈ s then some a else none inv a b := by split_ifs with hb ha ha · simp [eq_comm] · simp [ne_of_mem_of_not_mem hb ha] · simp [ne_of_mem_of_not_mem ha hb] · simp theorem mem_ofSet_self_iff {s : Set α} [DecidablePred (· ∈ s)] {a : α} : a ∈ ofSet s a ↔ a ∈ s := by dsimp [ofSet]; split_ifs <;> simp [*] theorem mem_ofSet_iff {s : Set α} [DecidablePred (· ∈ s)] {a b : α} : a ∈ ofSet s b ↔ a = b ∧ a ∈ s := by dsimp [ofSet] split_ifs with h · simp only [mem_def, eq_comm, some.injEq, iff_self_and] rintro rfl exact h · simp only [mem_def, false_iff, not_and, reduceCtorEq] rintro rfl exact h @[simp] theorem ofSet_eq_some_iff {s : Set α} {_ : DecidablePred (· ∈ s)} {a b : α} : ofSet s b = some a ↔ a = b ∧ a ∈ s := mem_ofSet_iff theorem ofSet_eq_some_self_iff {s : Set α} {_ : DecidablePred (· ∈ s)} {a : α} : ofSet s a = some a ↔ a ∈ s := mem_ofSet_self_iff @[simp] theorem ofSet_symm : (ofSet s).symm = ofSet s := rfl @[simp] theorem ofSet_univ : ofSet Set.univ = PEquiv.refl α := rfl @[simp] theorem ofSet_eq_refl {s : Set α} [DecidablePred (· ∈ s)] : ofSet s = PEquiv.refl α ↔ s = Set.univ := ⟨fun h => by rw [Set.eq_univ_iff_forall] intro rw [← mem_ofSet_self_iff, h] exact rfl, fun h => by simp only [← ofSet_univ, h]⟩ end OfSet theorem symm_trans_rev (f : α ≃. β) (g : β ≃. γ) : (f.trans g).symm = g.symm.trans f.symm := rfl theorem self_trans_symm (f : α ≃. β) : f.trans f.symm = ofSet { a | (f a).isSome } := by ext dsimp [PEquiv.trans] simp only [eq_some_iff f, Option.isSome_iff_exists, Option.mem_def, bind_eq_some', ofSet_eq_some_iff] constructor · rintro ⟨b, hb₁, hb₂⟩ exact ⟨PEquiv.inj _ hb₂ hb₁, b, hb₂⟩ · simp +contextual theorem symm_trans_self (f : α ≃. β) : f.symm.trans f = ofSet { b | (f.symm b).isSome } := symm_injective <| by simp [symm_trans_rev, self_trans_symm, -symm_symm] theorem trans_symm_eq_iff_forall_isSome {f : α ≃. β} : f.trans f.symm = PEquiv.refl α ↔ ∀ a, isSome (f a) := by rw [self_trans_symm, ofSet_eq_refl, Set.eq_univ_iff_forall]; rfl instance instBotPEquiv : Bot (α ≃. β) := ⟨{ toFun := fun _ => none invFun := fun _ => none inv := by simp }⟩ instance : Inhabited (α ≃. β) := ⟨⊥⟩ @[simp] theorem bot_apply (a : α) : (⊥ : α ≃. β) a = none := rfl @[simp] theorem symm_bot : (⊥ : α ≃. β).symm = ⊥ := rfl @[simp] theorem trans_bot (f : α ≃. β) : f.trans (⊥ : β ≃. γ) = ⊥ := by ext; dsimp [PEquiv.trans]; simp @[simp] theorem bot_trans (f : β ≃. γ) : (⊥ : α ≃. β).trans f = ⊥ := by ext; dsimp [PEquiv.trans]; simp theorem isSome_symm_get (f : α ≃. β) {a : α} (h : isSome (f a)) : isSome (f.symm (Option.get _ h)) := isSome_iff_exists.2 ⟨a, by rw [f.eq_some_iff, some_get]⟩ section Single variable [DecidableEq α] [DecidableEq β] [DecidableEq γ] /-- Create a `PEquiv` which sends `a` to `b` and `b` to `a`, but is otherwise `none`. -/ def single (a : α) (b : β) : α ≃. β where toFun x := if x = a then some b else none invFun x := if x = b then some a else none inv x y := by split_ifs with h1 h2 · simp [*] · simp only [mem_def, some.injEq, iff_false, reduceCtorEq] at * exact Ne.symm h2 · simp only [mem_def, some.injEq, false_iff, reduceCtorEq] at * exact Ne.symm h1 · simp theorem mem_single (a : α) (b : β) : b ∈ single a b a := if_pos rfl theorem mem_single_iff (a₁ a₂ : α) (b₁ b₂ : β) : b₁ ∈ single a₂ b₂ a₁ ↔ a₁ = a₂ ∧ b₁ = b₂ := by dsimp [single]; split_ifs <;> simp [*, eq_comm] @[simp] theorem symm_single (a : α) (b : β) : (single a b).symm = single b a := rfl @[simp] theorem single_apply (a : α) (b : β) : single a b a = some b := if_pos rfl theorem single_apply_of_ne {a₁ a₂ : α} (h : a₁ ≠ a₂) (b : β) : single a₁ b a₂ = none := if_neg h.symm theorem single_trans_of_mem (a : α) {b : β} {c : γ} {f : β ≃. γ} (h : c ∈ f b) : (single a b).trans f = single a c := by ext dsimp [single, PEquiv.trans] split_ifs <;> simp_all theorem trans_single_of_mem {a : α} {b : β} (c : γ) {f : α ≃. β} (h : b ∈ f a) : f.trans (single b c) = single a c := symm_injective <| single_trans_of_mem _ ((mem_iff_mem f).2 h) @[simp] theorem single_trans_single (a : α) (b : β) (c : γ) : (single a b).trans (single b c) = single a c := single_trans_of_mem _ (mem_single _ _) @[simp] theorem single_subsingleton_eq_refl [Subsingleton α] (a b : α) : single a b = PEquiv.refl α := by ext i j dsimp [single] rw [if_pos (Subsingleton.elim i a), Subsingleton.elim i j, Subsingleton.elim b j] theorem trans_single_of_eq_none {b : β} (c : γ) {f : δ ≃. β} (h : f.symm b = none) : f.trans (single b c) = ⊥ := by ext simp only [eq_none_iff_forall_not_mem, Option.mem_def, f.eq_some_iff] at h dsimp [PEquiv.trans, single] simp only [mem_def, bind_eq_some_iff, iff_false, not_exists, not_and, reduceCtorEq] intros split_ifs <;> simp_all theorem single_trans_of_eq_none (a : α) {b : β} {f : β ≃. δ} (h : f b = none) : (single a b).trans f = ⊥ := symm_injective <| trans_single_of_eq_none _ h theorem single_trans_single_of_ne {b₁ b₂ : β} (h : b₁ ≠ b₂) (a : α) (c : γ) : (single a b₁).trans (single b₂ c) = ⊥ := single_trans_of_eq_none _ (single_apply_of_ne h.symm _) end Single section Order instance instPartialOrderPEquiv : PartialOrder (α ≃. β) where le f g := ∀ (a : α) (b : β), b ∈ f a → b ∈ g a le_refl _ _ _ := id le_trans _ _ _ fg gh a b := gh a b ∘ fg a b le_antisymm f g fg gf := ext (by intro a rcases h : g a with _ | b · exact eq_none_iff_forall_not_mem.2 fun b hb => Option.not_mem_none b <| h ▸ fg a b hb · exact gf _ _ h) theorem le_def {f g : α ≃. β} : f ≤ g ↔ ∀ (a : α) (b : β), b ∈ f a → b ∈ g a := Iff.rfl instance : OrderBot (α ≃. β) := { instBotPEquiv with bot_le := fun _ _ _ h => (not_mem_none _ h).elim } instance [DecidableEq α] [DecidableEq β] : SemilatticeInf (α ≃. β) := { instPartialOrderPEquiv with inf := fun f g => { toFun := fun a => if f a = g a then f a else none invFun := fun b => if f.symm b = g.symm b then f.symm b else none inv := fun a b => by have hf := @mem_iff_mem _ _ f a b have hg := @mem_iff_mem _ _ g a b
simp only [Option.mem_def] at * split_ifs with h1 h2 h2 <;> try simp [hf] · contrapose! h2 rw [h2]
Mathlib/Data/PEquiv.lean
388
391
/- Copyright (c) 2018 Patrick Massot. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Patrick Massot, Johannes Hölzl, Yaël Dillies -/ import Mathlib.Analysis.Normed.Group.Seminorm import Mathlib.Data.NNReal.Basic import Mathlib.Topology.Algebra.Support import Mathlib.Topology.MetricSpace.Basic import Mathlib.Topology.Order.Real /-! # Normed (semi)groups In this file we define 10 classes: * `Norm`, `NNNorm`: auxiliary classes endowing a type `α` with a function `norm : α → ℝ` (notation: `‖x‖`) and `nnnorm : α → ℝ≥0` (notation: `‖x‖₊`), respectively; * `Seminormed...Group`: A seminormed (additive) (commutative) group is an (additive) (commutative) group with a norm and a compatible pseudometric space structure: `∀ x y, dist x y = ‖x / y‖` or `∀ x y, dist x y = ‖x - y‖`, depending on the group operation. * `Normed...Group`: A normed (additive) (commutative) group is an (additive) (commutative) group with a norm and a compatible metric space structure. We also prove basic properties of (semi)normed groups and provide some instances. ## Notes The current convention `dist x y = ‖x - y‖` means that the distance is invariant under right addition, but actions in mathlib are usually from the left. This means we might want to change it to `dist x y = ‖-x + y‖`. The normed group hierarchy would lend itself well to a mixin design (that is, having `SeminormedGroup` and `SeminormedAddGroup` not extend `Group` and `AddGroup`), but we choose not to for performance concerns. ## Tags normed group -/ variable {𝓕 α ι κ E F G : Type*} open Filter Function Metric Bornology open ENNReal Filter NNReal Uniformity Pointwise Topology /-- Auxiliary class, endowing a type `E` with a function `norm : E → ℝ` with notation `‖x‖`. This class is designed to be extended in more interesting classes specifying the properties of the norm. -/ @[notation_class] class Norm (E : Type*) where /-- the `ℝ`-valued norm function. -/ norm : E → ℝ /-- Auxiliary class, endowing a type `α` with a function `nnnorm : α → ℝ≥0` with notation `‖x‖₊`. -/ @[notation_class] class NNNorm (E : Type*) where /-- the `ℝ≥0`-valued norm function. -/ nnnorm : E → ℝ≥0 /-- Auxiliary class, endowing a type `α` with a function `enorm : α → ℝ≥0∞` with notation `‖x‖ₑ`. -/ @[notation_class] class ENorm (E : Type*) where /-- the `ℝ≥0∞`-valued norm function. -/ enorm : E → ℝ≥0∞ export Norm (norm) export NNNorm (nnnorm) export ENorm (enorm) @[inherit_doc] notation "‖" e "‖" => norm e @[inherit_doc] notation "‖" e "‖₊" => nnnorm e @[inherit_doc] notation "‖" e "‖ₑ" => enorm e section ENorm variable {E : Type*} [NNNorm E] {x : E} {r : ℝ≥0} instance NNNorm.toENorm : ENorm E where enorm := (‖·‖₊ : E → ℝ≥0∞) lemma enorm_eq_nnnorm (x : E) : ‖x‖ₑ = ‖x‖₊ := rfl @[simp] lemma toNNReal_enorm (x : E) : ‖x‖ₑ.toNNReal = ‖x‖₊ := rfl @[simp, norm_cast] lemma coe_le_enorm : r ≤ ‖x‖ₑ ↔ r ≤ ‖x‖₊ := by simp [enorm] @[simp, norm_cast] lemma enorm_le_coe : ‖x‖ₑ ≤ r ↔ ‖x‖₊ ≤ r := by simp [enorm] @[simp, norm_cast] lemma coe_lt_enorm : r < ‖x‖ₑ ↔ r < ‖x‖₊ := by simp [enorm] @[simp, norm_cast] lemma enorm_lt_coe : ‖x‖ₑ < r ↔ ‖x‖₊ < r := by simp [enorm] @[simp] lemma enorm_ne_top : ‖x‖ₑ ≠ ∞ := by simp [enorm] @[simp] lemma enorm_lt_top : ‖x‖ₑ < ∞ := by simp [enorm] end ENorm /-- A type `E` equipped with a continuous map `‖·‖ₑ : E → ℝ≥0∞` NB. We do not demand that the topology is somehow defined by the enorm: for ℝ≥0∞ (the motivating example behind this definition), this is not true. -/ class ContinuousENorm (E : Type*) [TopologicalSpace E] extends ENorm E where continuous_enorm : Continuous enorm /-- An enormed monoid is an additive monoid endowed with a continuous enorm. -/ class ENormedAddMonoid (E : Type*) [TopologicalSpace E] extends ContinuousENorm E, AddMonoid E where enorm_eq_zero : ∀ x : E, ‖x‖ₑ = 0 ↔ x = 0 protected enorm_add_le : ∀ x y : E, ‖x + y‖ₑ ≤ ‖x‖ₑ + ‖y‖ₑ /-- An enormed monoid is a monoid endowed with a continuous enorm. -/ @[to_additive] class ENormedMonoid (E : Type*) [TopologicalSpace E] extends ContinuousENorm E, Monoid E where enorm_eq_zero : ∀ x : E, ‖x‖ₑ = 0 ↔ x = 1 enorm_mul_le : ∀ x y : E, ‖x * y‖ₑ ≤ ‖x‖ₑ + ‖y‖ₑ /-- An enormed commutative monoid is an additive commutative monoid endowed with a continuous enorm. We don't have `ENormedAddCommMonoid` extend `EMetricSpace`, since the canonical instance `ℝ≥0∞` is not an `EMetricSpace`. This is because `ℝ≥0∞` carries the order topology, which is distinct from the topology coming from `edist`. -/ class ENormedAddCommMonoid (E : Type*) [TopologicalSpace E] extends ENormedAddMonoid E, AddCommMonoid E where /-- An enormed commutative monoid is a commutative monoid endowed with a continuous enorm. -/ @[to_additive] class ENormedCommMonoid (E : Type*) [TopologicalSpace E] extends ENormedMonoid E, CommMonoid E where /-- A seminormed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a pseudometric space structure. -/ class SeminormedAddGroup (E : Type*) extends Norm E, AddGroup E, PseudoMetricSpace E where dist := fun x y => ‖x - y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop /-- A seminormed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a pseudometric space structure. -/ @[to_additive] class SeminormedGroup (E : Type*) extends Norm E, Group E, PseudoMetricSpace E where dist := fun x y => ‖x / y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop /-- A normed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a metric space structure. -/ class NormedAddGroup (E : Type*) extends Norm E, AddGroup E, MetricSpace E where dist := fun x y => ‖x - y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop /-- A normed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a metric space structure. -/ @[to_additive] class NormedGroup (E : Type*) extends Norm E, Group E, MetricSpace E where dist := fun x y => ‖x / y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop /-- A seminormed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a pseudometric space structure. -/ class SeminormedAddCommGroup (E : Type*) extends Norm E, AddCommGroup E, PseudoMetricSpace E where dist := fun x y => ‖x - y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop /-- A seminormed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a pseudometric space structure. -/ @[to_additive] class SeminormedCommGroup (E : Type*) extends Norm E, CommGroup E, PseudoMetricSpace E where dist := fun x y => ‖x / y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop /-- A normed group is an additive group endowed with a norm for which `dist x y = ‖x - y‖` defines a metric space structure. -/ class NormedAddCommGroup (E : Type*) extends Norm E, AddCommGroup E, MetricSpace E where dist := fun x y => ‖x - y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x - y‖ := by aesop /-- A normed group is a group endowed with a norm for which `dist x y = ‖x / y‖` defines a metric space structure. -/ @[to_additive] class NormedCommGroup (E : Type*) extends Norm E, CommGroup E, MetricSpace E where dist := fun x y => ‖x / y‖ /-- The distance function is induced by the norm. -/ dist_eq : ∀ x y, dist x y = ‖x / y‖ := by aesop -- See note [lower instance priority] @[to_additive] instance (priority := 100) NormedGroup.toSeminormedGroup [NormedGroup E] : SeminormedGroup E := { ‹NormedGroup E› with } -- See note [lower instance priority] @[to_additive] instance (priority := 100) NormedCommGroup.toSeminormedCommGroup [NormedCommGroup E] : SeminormedCommGroup E := { ‹NormedCommGroup E› with } -- See note [lower instance priority] @[to_additive] instance (priority := 100) SeminormedCommGroup.toSeminormedGroup [SeminormedCommGroup E] : SeminormedGroup E := { ‹SeminormedCommGroup E› with } -- See note [lower instance priority] @[to_additive] instance (priority := 100) NormedCommGroup.toNormedGroup [NormedCommGroup E] : NormedGroup E := { ‹NormedCommGroup E› with } -- See note [reducible non-instances] /-- Construct a `NormedGroup` from a `SeminormedGroup` satisfying `∀ x, ‖x‖ = 0 → x = 1`. This avoids having to go back to the `(Pseudo)MetricSpace` level when declaring a `NormedGroup` instance as a special case of a more general `SeminormedGroup` instance. -/ @[to_additive "Construct a `NormedAddGroup` from a `SeminormedAddGroup` satisfying `∀ x, ‖x‖ = 0 → x = 0`. This avoids having to go back to the `(Pseudo)MetricSpace` level when declaring a `NormedAddGroup` instance as a special case of a more general `SeminormedAddGroup` instance."] abbrev NormedGroup.ofSeparation [SeminormedGroup E] (h : ∀ x : E, ‖x‖ = 0 → x = 1) : NormedGroup E where dist_eq := ‹SeminormedGroup E›.dist_eq toMetricSpace := { eq_of_dist_eq_zero := fun hxy => div_eq_one.1 <| h _ <| (‹SeminormedGroup E›.dist_eq _ _).symm.trans hxy } -- See note [reducible non-instances] /-- Construct a `NormedCommGroup` from a `SeminormedCommGroup` satisfying `∀ x, ‖x‖ = 0 → x = 1`. This avoids having to go back to the `(Pseudo)MetricSpace` level when declaring a `NormedCommGroup` instance as a special case of a more general `SeminormedCommGroup` instance. -/ @[to_additive "Construct a `NormedAddCommGroup` from a `SeminormedAddCommGroup` satisfying `∀ x, ‖x‖ = 0 → x = 0`. This avoids having to go back to the `(Pseudo)MetricSpace` level when declaring a `NormedAddCommGroup` instance as a special case of a more general `SeminormedAddCommGroup` instance."] abbrev NormedCommGroup.ofSeparation [SeminormedCommGroup E] (h : ∀ x : E, ‖x‖ = 0 → x = 1) : NormedCommGroup E := { ‹SeminormedCommGroup E›, NormedGroup.ofSeparation h with } -- See note [reducible non-instances] /-- Construct a seminormed group from a multiplication-invariant distance. -/ @[to_additive "Construct a seminormed group from a translation-invariant distance."] abbrev SeminormedGroup.ofMulDist [Norm E] [Group E] [PseudoMetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) : SeminormedGroup E where dist_eq x y := by rw [h₁]; apply le_antisymm · simpa only [div_eq_mul_inv, ← mul_inv_cancel y] using h₂ _ _ _ · simpa only [div_mul_cancel, one_mul] using h₂ (x / y) 1 y -- See note [reducible non-instances] /-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/ @[to_additive "Construct a seminormed group from a translation-invariant pseudodistance."] abbrev SeminormedGroup.ofMulDist' [Norm E] [Group E] [PseudoMetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) : SeminormedGroup E where dist_eq x y := by rw [h₁]; apply le_antisymm · simpa only [div_mul_cancel, one_mul] using h₂ (x / y) 1 y · simpa only [div_eq_mul_inv, ← mul_inv_cancel y] using h₂ _ _ _ -- See note [reducible non-instances] /-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/ @[to_additive "Construct a seminormed group from a translation-invariant pseudodistance."] abbrev SeminormedCommGroup.ofMulDist [Norm E] [CommGroup E] [PseudoMetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) : SeminormedCommGroup E := { SeminormedGroup.ofMulDist h₁ h₂ with mul_comm := mul_comm } -- See note [reducible non-instances] /-- Construct a seminormed group from a multiplication-invariant pseudodistance. -/ @[to_additive "Construct a seminormed group from a translation-invariant pseudodistance."] abbrev SeminormedCommGroup.ofMulDist' [Norm E] [CommGroup E] [PseudoMetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) : SeminormedCommGroup E := { SeminormedGroup.ofMulDist' h₁ h₂ with mul_comm := mul_comm } -- See note [reducible non-instances] /-- Construct a normed group from a multiplication-invariant distance. -/ @[to_additive "Construct a normed group from a translation-invariant distance."] abbrev NormedGroup.ofMulDist [Norm E] [Group E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) : NormedGroup E := { SeminormedGroup.ofMulDist h₁ h₂ with eq_of_dist_eq_zero := eq_of_dist_eq_zero } -- See note [reducible non-instances] /-- Construct a normed group from a multiplication-invariant pseudodistance. -/ @[to_additive "Construct a normed group from a translation-invariant pseudodistance."] abbrev NormedGroup.ofMulDist' [Norm E] [Group E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) : NormedGroup E := { SeminormedGroup.ofMulDist' h₁ h₂ with eq_of_dist_eq_zero := eq_of_dist_eq_zero } -- See note [reducible non-instances] /-- Construct a normed group from a multiplication-invariant pseudodistance. -/ @[to_additive "Construct a normed group from a translation-invariant pseudodistance."] abbrev NormedCommGroup.ofMulDist [Norm E] [CommGroup E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist x y ≤ dist (x * z) (y * z)) : NormedCommGroup E := { NormedGroup.ofMulDist h₁ h₂ with mul_comm := mul_comm } -- See note [reducible non-instances] /-- Construct a normed group from a multiplication-invariant pseudodistance. -/ @[to_additive "Construct a normed group from a translation-invariant pseudodistance."] abbrev NormedCommGroup.ofMulDist' [Norm E] [CommGroup E] [MetricSpace E] (h₁ : ∀ x : E, ‖x‖ = dist x 1) (h₂ : ∀ x y z : E, dist (x * z) (y * z) ≤ dist x y) : NormedCommGroup E := { NormedGroup.ofMulDist' h₁ h₂ with mul_comm := mul_comm } -- See note [reducible non-instances] /-- Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the pseudometric space structure from the seminorm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`). -/ @[to_additive "Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the pseudometric space structure from the seminorm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`)."] abbrev GroupSeminorm.toSeminormedGroup [Group E] (f : GroupSeminorm E) : SeminormedGroup E where dist x y := f (x / y) norm := f dist_eq _ _ := rfl dist_self x := by simp only [div_self', map_one_eq_zero] dist_triangle := le_map_div_add_map_div f dist_comm := map_div_rev f -- See note [reducible non-instances] /-- Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the pseudometric space structure from the seminorm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`). -/ @[to_additive "Construct a seminormed group from a seminorm, i.e., registering the pseudodistance and the pseudometric space structure from the seminorm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`)."] abbrev GroupSeminorm.toSeminormedCommGroup [CommGroup E] (f : GroupSeminorm E) : SeminormedCommGroup E := { f.toSeminormedGroup with mul_comm := mul_comm } -- See note [reducible non-instances] /-- Construct a normed group from a norm, i.e., registering the distance and the metric space structure from the norm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`). -/ @[to_additive "Construct a normed group from a norm, i.e., registering the distance and the metric space structure from the norm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`)."] abbrev GroupNorm.toNormedGroup [Group E] (f : GroupNorm E) : NormedGroup E := { f.toGroupSeminorm.toSeminormedGroup with eq_of_dist_eq_zero := fun h => div_eq_one.1 <| eq_one_of_map_eq_zero f h } -- See note [reducible non-instances] /-- Construct a normed group from a norm, i.e., registering the distance and the metric space structure from the norm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`). -/ @[to_additive "Construct a normed group from a norm, i.e., registering the distance and the metric space structure from the norm properties. Note that in most cases this instance creates bad definitional equalities (e.g., it does not take into account a possibly existing `UniformSpace` instance on `E`)."] abbrev GroupNorm.toNormedCommGroup [CommGroup E] (f : GroupNorm E) : NormedCommGroup E := { f.toNormedGroup with mul_comm := mul_comm } section SeminormedGroup variable [SeminormedGroup E] [SeminormedGroup F] [SeminormedGroup G] {s : Set E} {a a₁ a₂ b c : E} {r r₁ r₂ : ℝ} @[to_additive] theorem dist_eq_norm_div (a b : E) : dist a b = ‖a / b‖ := SeminormedGroup.dist_eq _ _ @[to_additive] theorem dist_eq_norm_div' (a b : E) : dist a b = ‖b / a‖ := by rw [dist_comm, dist_eq_norm_div] alias dist_eq_norm := dist_eq_norm_sub alias dist_eq_norm' := dist_eq_norm_sub' @[to_additive of_forall_le_norm] lemma DiscreteTopology.of_forall_le_norm' (hpos : 0 < r) (hr : ∀ x : E, x ≠ 1 → r ≤ ‖x‖) : DiscreteTopology E := .of_forall_le_dist hpos fun x y hne ↦ by simp only [dist_eq_norm_div] exact hr _ (div_ne_one.2 hne) @[to_additive (attr := simp)] theorem dist_one_right (a : E) : dist a 1 = ‖a‖ := by rw [dist_eq_norm_div, div_one] @[to_additive] theorem inseparable_one_iff_norm {a : E} : Inseparable a 1 ↔ ‖a‖ = 0 := by rw [Metric.inseparable_iff, dist_one_right] @[to_additive] lemma dist_one_left (a : E) : dist 1 a = ‖a‖ := by rw [dist_comm, dist_one_right] @[to_additive (attr := simp)] lemma dist_one : dist (1 : E) = norm := funext dist_one_left
Mathlib/Analysis/Normed/Group/Basic.lean
415
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/- Copyright (c) 2017 Robert Y. Lewis. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Robert Y. Lewis, Keeley Hoek -/ import Mathlib.Algebra.NeZero import Mathlib.Data.Int.DivMod import Mathlib.Logic.Embedding.Basic import Mathlib.Logic.Equiv.Set import Mathlib.Tactic.Common import Mathlib.Tactic.Attr.Register /-! # The finite type with `n` elements `Fin n` is the type whose elements are natural numbers smaller than `n`. This file expands on the development in the core library. ## Main definitions ### Induction principles * `finZeroElim` : Elimination principle for the empty set `Fin 0`, generalizes `Fin.elim0`. Further definitions and eliminators can be found in `Init.Data.Fin.Lemmas` ### Embeddings and isomorphisms * `Fin.valEmbedding` : coercion to natural numbers as an `Embedding`; * `Fin.succEmb` : `Fin.succ` as an `Embedding`; * `Fin.castLEEmb h` : `Fin.castLE` as an `Embedding`, embed `Fin n` into `Fin m`, `h : n ≤ m`; * `finCongr` : `Fin.cast` as an `Equiv`, equivalence between `Fin n` and `Fin m` when `n = m`; * `Fin.castAddEmb m` : `Fin.castAdd` as an `Embedding`, embed `Fin n` into `Fin (n+m)`; * `Fin.castSuccEmb` : `Fin.castSucc` as an `Embedding`, embed `Fin n` into `Fin (n+1)`; * `Fin.addNatEmb m i` : `Fin.addNat` as an `Embedding`, add `m` on `i` on the right, generalizes `Fin.succ`; * `Fin.natAddEmb n i` : `Fin.natAdd` as an `Embedding`, adds `n` on `i` on the left; ### Other casts * `Fin.divNat i` : divides `i : Fin (m * n)` by `n`; * `Fin.modNat i` : takes the mod of `i : Fin (m * n)` by `n`; -/ assert_not_exists Monoid Finset open Fin Nat Function attribute [simp] Fin.succ_ne_zero Fin.castSucc_lt_last /-- Elimination principle for the empty set `Fin 0`, dependent version. -/ def finZeroElim {α : Fin 0 → Sort*} (x : Fin 0) : α x := x.elim0 namespace Fin @[simp] theorem mk_eq_one {n a : Nat} {ha : a < n + 2} : (⟨a, ha⟩ : Fin (n + 2)) = 1 ↔ a = 1 := mk.inj_iff @[simp] theorem one_eq_mk {n a : Nat} {ha : a < n + 2} : 1 = (⟨a, ha⟩ : Fin (n + 2)) ↔ a = 1 := by simp [eq_comm] instance {n : ℕ} : CanLift ℕ (Fin n) Fin.val (· < n) where prf k hk := ⟨⟨k, hk⟩, rfl⟩ /-- A dependent variant of `Fin.elim0`. -/ def rec0 {α : Fin 0 → Sort*} (i : Fin 0) : α i := absurd i.2 (Nat.not_lt_zero _) variable {n m : ℕ} --variable {a b : Fin n} -- this *really* breaks stuff theorem val_injective : Function.Injective (@Fin.val n) := @Fin.eq_of_val_eq n /-- If you actually have an element of `Fin n`, then the `n` is always positive -/ lemma size_positive : Fin n → 0 < n := Fin.pos lemma size_positive' [Nonempty (Fin n)] : 0 < n := ‹Nonempty (Fin n)›.elim Fin.pos protected theorem prop (a : Fin n) : a.val < n := a.2 lemma lt_last_iff_ne_last {a : Fin (n + 1)} : a < last n ↔ a ≠ last n := by simp [Fin.lt_iff_le_and_ne, le_last] lemma ne_zero_of_lt {a b : Fin (n + 1)} (hab : a < b) : b ≠ 0 := Fin.ne_of_gt <| Fin.lt_of_le_of_lt a.zero_le hab lemma ne_last_of_lt {a b : Fin (n + 1)} (hab : a < b) : a ≠ last n := Fin.ne_of_lt <| Fin.lt_of_lt_of_le hab b.le_last /-- Equivalence between `Fin n` and `{ i // i < n }`. -/ @[simps apply symm_apply] def equivSubtype : Fin n ≃ { i // i < n } where toFun a := ⟨a.1, a.2⟩ invFun a := ⟨a.1, a.2⟩ left_inv := fun ⟨_, _⟩ => rfl right_inv := fun ⟨_, _⟩ => rfl section coe /-! ### coercions and constructions -/ theorem val_eq_val (a b : Fin n) : (a : ℕ) = b ↔ a = b := Fin.ext_iff.symm theorem ne_iff_vne (a b : Fin n) : a ≠ b ↔ a.1 ≠ b.1 := Fin.ext_iff.not theorem mk_eq_mk {a h a' h'} : @mk n a h = @mk n a' h' ↔ a = a' := Fin.ext_iff -- syntactic tautologies now /-- Assume `k = l`. If two functions defined on `Fin k` and `Fin l` are equal on each element, then they coincide (in the heq sense). -/ protected theorem heq_fun_iff {α : Sort*} {k l : ℕ} (h : k = l) {f : Fin k → α} {g : Fin l → α} : HEq f g ↔ ∀ i : Fin k, f i = g ⟨(i : ℕ), h ▸ i.2⟩ := by subst h simp [funext_iff] /-- Assume `k = l` and `k' = l'`. If two functions `Fin k → Fin k' → α` and `Fin l → Fin l' → α` are equal on each pair, then they coincide (in the heq sense). -/ protected theorem heq_fun₂_iff {α : Sort*} {k l k' l' : ℕ} (h : k = l) (h' : k' = l') {f : Fin k → Fin k' → α} {g : Fin l → Fin l' → α} : HEq f g ↔ ∀ (i : Fin k) (j : Fin k'), f i j = g ⟨(i : ℕ), h ▸ i.2⟩ ⟨(j : ℕ), h' ▸ j.2⟩ := by subst h subst h' simp [funext_iff] /-- Two elements of `Fin k` and `Fin l` are heq iff their values in `ℕ` coincide. This requires `k = l`. For the left implication without this assumption, see `val_eq_val_of_heq`. -/ protected theorem heq_ext_iff {k l : ℕ} (h : k = l) {i : Fin k} {j : Fin l} : HEq i j ↔ (i : ℕ) = (j : ℕ) := by subst h simp [val_eq_val] end coe section Order /-! ### order -/ theorem le_iff_val_le_val {a b : Fin n} : a ≤ b ↔ (a : ℕ) ≤ b := Iff.rfl /-- `a < b` as natural numbers if and only if `a < b` in `Fin n`. -/ @[norm_cast, simp] theorem val_fin_lt {n : ℕ} {a b : Fin n} : (a : ℕ) < (b : ℕ) ↔ a < b := Iff.rfl /-- `a ≤ b` as natural numbers if and only if `a ≤ b` in `Fin n`. -/ @[norm_cast, simp] theorem val_fin_le {n : ℕ} {a b : Fin n} : (a : ℕ) ≤ (b : ℕ) ↔ a ≤ b := Iff.rfl theorem min_val {a : Fin n} : min (a : ℕ) n = a := by simp theorem max_val {a : Fin n} : max (a : ℕ) n = n := by simp /-- The inclusion map `Fin n → ℕ` is an embedding. -/ @[simps -fullyApplied apply] def valEmbedding : Fin n ↪ ℕ := ⟨val, val_injective⟩ @[simp] theorem equivSubtype_symm_trans_valEmbedding : equivSubtype.symm.toEmbedding.trans valEmbedding = Embedding.subtype (· < n) := rfl /-- Use the ordering on `Fin n` for checking recursive definitions. For example, the following definition is not accepted by the termination checker, unless we declare the `WellFoundedRelation` instance: ```lean def factorial {n : ℕ} : Fin n → ℕ | ⟨0, _⟩ := 1 | ⟨i + 1, hi⟩ := (i + 1) * factorial ⟨i, i.lt_succ_self.trans hi⟩ ``` -/ instance {n : ℕ} : WellFoundedRelation (Fin n) := measure (val : Fin n → ℕ) @[deprecated (since := "2025-02-24")] alias val_zero' := val_zero /-- `Fin.mk_zero` in `Lean` only applies in `Fin (n + 1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ @[simp] theorem mk_zero' (n : ℕ) [NeZero n] : (⟨0, pos_of_neZero n⟩ : Fin n) = 0 := rfl /-- The `Fin.zero_le` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ @[simp] protected theorem zero_le' [NeZero n] (a : Fin n) : 0 ≤ a := Nat.zero_le a.val @[simp, norm_cast] theorem val_eq_zero_iff [NeZero n] {a : Fin n} : a.val = 0 ↔ a = 0 := by rw [Fin.ext_iff, val_zero] theorem val_ne_zero_iff [NeZero n] {a : Fin n} : a.val ≠ 0 ↔ a ≠ 0 := val_eq_zero_iff.not @[simp, norm_cast] theorem val_pos_iff [NeZero n] {a : Fin n} : 0 < a.val ↔ 0 < a := by rw [← val_fin_lt, val_zero] /-- The `Fin.pos_iff_ne_zero` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ theorem pos_iff_ne_zero' [NeZero n] (a : Fin n) : 0 < a ↔ a ≠ 0 := by rw [← val_pos_iff, Nat.pos_iff_ne_zero, val_ne_zero_iff] @[simp] lemma cast_eq_self (a : Fin n) : a.cast rfl = a := rfl @[simp] theorem cast_eq_zero {k l : ℕ} [NeZero k] [NeZero l] (h : k = l) (x : Fin k) : Fin.cast h x = 0 ↔ x = 0 := by simp [← val_eq_zero_iff] lemma cast_injective {k l : ℕ} (h : k = l) : Injective (Fin.cast h) := fun a b hab ↦ by simpa [← val_eq_val] using hab theorem last_pos' [NeZero n] : 0 < last n := n.pos_of_neZero theorem one_lt_last [NeZero n] : 1 < last (n + 1) := by rw [lt_iff_val_lt_val, val_one, val_last, Nat.lt_add_left_iff_pos, Nat.pos_iff_ne_zero] exact NeZero.ne n end Order /-! ### Coercions to `ℤ` and the `fin_omega` tactic. -/ open Int theorem coe_int_sub_eq_ite {n : Nat} (u v : Fin n) : ((u - v : Fin n) : Int) = if v ≤ u then (u - v : Int) else (u - v : Int) + n := by rw [Fin.sub_def] split · rw [natCast_emod, Int.emod_eq_sub_self_emod, Int.emod_eq_of_lt] <;> omega · rw [natCast_emod, Int.emod_eq_of_lt] <;> omega theorem coe_int_sub_eq_mod {n : Nat} (u v : Fin n) : ((u - v : Fin n) : Int) = ((u : Int) - (v : Int)) % n := by rw [coe_int_sub_eq_ite] split · rw [Int.emod_eq_of_lt] <;> omega · rw [Int.emod_eq_add_self_emod, Int.emod_eq_of_lt] <;> omega theorem coe_int_add_eq_ite {n : Nat} (u v : Fin n) : ((u + v : Fin n) : Int) = if (u + v : ℕ) < n then (u + v : Int) else (u + v : Int) - n := by rw [Fin.add_def] split · rw [natCast_emod, Int.emod_eq_of_lt] <;> omega · rw [natCast_emod, Int.emod_eq_sub_self_emod, Int.emod_eq_of_lt] <;> omega theorem coe_int_add_eq_mod {n : Nat} (u v : Fin n) : ((u + v : Fin n) : Int) = ((u : Int) + (v : Int)) % n := by rw [coe_int_add_eq_ite] split · rw [Int.emod_eq_of_lt] <;> omega · rw [Int.emod_eq_sub_self_emod, Int.emod_eq_of_lt] <;> omega -- Write `a + b` as `if (a + b : ℕ) < n then (a + b : ℤ) else (a + b : ℤ) - n` and -- similarly `a - b` as `if (b : ℕ) ≤ a then (a - b : ℤ) else (a - b : ℤ) + n`. attribute [fin_omega] coe_int_sub_eq_ite coe_int_add_eq_ite -- Rewrite inequalities in `Fin` to inequalities in `ℕ` attribute [fin_omega] Fin.lt_iff_val_lt_val Fin.le_iff_val_le_val -- Rewrite `1 : Fin (n + 2)` to `1 : ℤ` attribute [fin_omega] val_one /-- Preprocessor for `omega` to handle inequalities in `Fin`. Note that this involves a lot of case splitting, so may be slow. -/ -- Further adjustment to the simp set can probably make this more powerful. -- Please experiment and PR updates! macro "fin_omega" : tactic => `(tactic| { try simp only [fin_omega, ← Int.ofNat_lt, ← Int.ofNat_le] at * omega }) section Add /-! ### addition, numerals, and coercion from Nat -/ @[simp] theorem val_one' (n : ℕ) [NeZero n] : ((1 : Fin n) : ℕ) = 1 % n := rfl @[deprecated val_one' (since := "2025-03-10")] theorem val_one'' {n : ℕ} : ((1 : Fin (n + 1)) : ℕ) = 1 % (n + 1) := rfl instance nontrivial {n : ℕ} : Nontrivial (Fin (n + 2)) where exists_pair_ne := ⟨0, 1, (ne_iff_vne 0 1).mpr (by simp [val_one, val_zero])⟩ theorem nontrivial_iff_two_le : Nontrivial (Fin n) ↔ 2 ≤ n := by rcases n with (_ | _ | n) <;> simp [Fin.nontrivial, not_nontrivial, Nat.succ_le_iff] section Monoid instance inhabitedFinOneAdd (n : ℕ) : Inhabited (Fin (1 + n)) := haveI : NeZero (1 + n) := by rw [Nat.add_comm]; infer_instance inferInstance @[simp] theorem default_eq_zero (n : ℕ) [NeZero n] : (default : Fin n) = 0 := rfl instance instNatCast [NeZero n] : NatCast (Fin n) where natCast i := Fin.ofNat' n i lemma natCast_def [NeZero n] (a : ℕ) : (a : Fin n) = ⟨a % n, mod_lt _ n.pos_of_neZero⟩ := rfl end Monoid theorem val_add_eq_ite {n : ℕ} (a b : Fin n) : (↑(a + b) : ℕ) = if n ≤ a + b then a + b - n else a + b := by rw [Fin.val_add, Nat.add_mod_eq_ite, Nat.mod_eq_of_lt (show ↑a < n from a.2), Nat.mod_eq_of_lt (show ↑b < n from b.2)] theorem val_add_eq_of_add_lt {n : ℕ} {a b : Fin n} (huv : a.val + b.val < n) : (a + b).val = a.val + b.val := by rw [val_add] simp [Nat.mod_eq_of_lt huv] lemma intCast_val_sub_eq_sub_add_ite {n : ℕ} (a b : Fin n) : ((a - b).val : ℤ) = a.val - b.val + if b ≤ a then 0 else n := by split <;> fin_omega lemma one_le_of_ne_zero {n : ℕ} [NeZero n] {k : Fin n} (hk : k ≠ 0) : 1 ≤ k := by obtain ⟨n, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (NeZero.ne n) cases n with | zero => simp only [Nat.reduceAdd, Fin.isValue, Fin.zero_le] | succ n => rwa [Fin.le_iff_val_le_val, Fin.val_one, Nat.one_le_iff_ne_zero, val_ne_zero_iff] lemma val_sub_one_of_ne_zero [NeZero n] {i : Fin n} (hi : i ≠ 0) : (i - 1).val = i - 1 := by obtain ⟨n, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (NeZero.ne n) rw [Fin.sub_val_of_le (one_le_of_ne_zero hi), Fin.val_one', Nat.mod_eq_of_lt (Nat.succ_le_iff.mpr (nontrivial_iff_two_le.mp <| nontrivial_of_ne i 0 hi))] section OfNatCoe @[simp] theorem ofNat'_eq_cast (n : ℕ) [NeZero n] (a : ℕ) : Fin.ofNat' n a = a := rfl @[simp] lemma val_natCast (a n : ℕ) [NeZero n] : (a : Fin n).val = a % n := rfl /-- Converting an in-range number to `Fin (n + 1)` produces a result whose value is the original number. -/ theorem val_cast_of_lt {n : ℕ} [NeZero n] {a : ℕ} (h : a < n) : (a : Fin n).val = a := Nat.mod_eq_of_lt h /-- If `n` is non-zero, converting the value of a `Fin n` to `Fin n` results in the same value. -/ @[simp, norm_cast] theorem cast_val_eq_self {n : ℕ} [NeZero n] (a : Fin n) : (a.val : Fin n) = a := Fin.ext <| val_cast_of_lt a.isLt -- This is a special case of `CharP.cast_eq_zero` that doesn't require typeclass search @[simp high] lemma natCast_self (n : ℕ) [NeZero n] : (n : Fin n) = 0 := by ext; simp @[simp] lemma natCast_eq_zero {a n : ℕ} [NeZero n] : (a : Fin n) = 0 ↔ n ∣ a := by simp [Fin.ext_iff, Nat.dvd_iff_mod_eq_zero] @[simp] theorem natCast_eq_last (n) : (n : Fin (n + 1)) = Fin.last n := by ext; simp theorem le_val_last (i : Fin (n + 1)) : i ≤ n := by rw [Fin.natCast_eq_last] exact Fin.le_last i variable {a b : ℕ} lemma natCast_le_natCast (han : a ≤ n) (hbn : b ≤ n) : (a : Fin (n + 1)) ≤ b ↔ a ≤ b := by rw [← Nat.lt_succ_iff] at han hbn simp [le_iff_val_le_val, -val_fin_le, Nat.mod_eq_of_lt, han, hbn] lemma natCast_lt_natCast (han : a ≤ n) (hbn : b ≤ n) : (a : Fin (n + 1)) < b ↔ a < b := by rw [← Nat.lt_succ_iff] at han hbn; simp [lt_iff_val_lt_val, Nat.mod_eq_of_lt, han, hbn] lemma natCast_mono (hbn : b ≤ n) (hab : a ≤ b) : (a : Fin (n + 1)) ≤ b := (natCast_le_natCast (hab.trans hbn) hbn).2 hab lemma natCast_strictMono (hbn : b ≤ n) (hab : a < b) : (a : Fin (n + 1)) < b := (natCast_lt_natCast (hab.le.trans hbn) hbn).2 hab end OfNatCoe end Add section Succ /-! ### succ and casts into larger Fin types -/ lemma succ_injective (n : ℕ) : Injective (@Fin.succ n) := fun a b ↦ by simp [Fin.ext_iff] /-- `Fin.succ` as an `Embedding` -/ def succEmb (n : ℕ) : Fin n ↪ Fin (n + 1) where toFun := succ inj' := succ_injective _ @[simp] theorem coe_succEmb : ⇑(succEmb n) = Fin.succ := rfl @[deprecated (since := "2025-04-12")] alias val_succEmb := coe_succEmb @[simp] theorem exists_succ_eq {x : Fin (n + 1)} : (∃ y, Fin.succ y = x) ↔ x ≠ 0 := ⟨fun ⟨_, hy⟩ => hy ▸ succ_ne_zero _, x.cases (fun h => h.irrefl.elim) (fun _ _ => ⟨_, rfl⟩)⟩ theorem exists_succ_eq_of_ne_zero {x : Fin (n + 1)} (h : x ≠ 0) : ∃ y, Fin.succ y = x := exists_succ_eq.mpr h @[simp] theorem succ_zero_eq_one' [NeZero n] : Fin.succ (0 : Fin n) = 1 := by cases n · exact (NeZero.ne 0 rfl).elim · rfl theorem one_pos' [NeZero n] : (0 : Fin (n + 1)) < 1 := succ_zero_eq_one' (n := n) ▸ succ_pos _ theorem zero_ne_one' [NeZero n] : (0 : Fin (n + 1)) ≠ 1 := Fin.ne_of_lt one_pos' /-- The `Fin.succ_one_eq_two` in `Lean` only applies in `Fin (n+2)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ @[simp] theorem succ_one_eq_two' [NeZero n] : Fin.succ (1 : Fin (n + 1)) = 2 := by cases n · exact (NeZero.ne 0 rfl).elim · rfl -- Version of `succ_one_eq_two` to be used by `dsimp`. -- Note the `'` swapped around due to a move to std4. /-- The `Fin.le_zero_iff` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ @[simp] theorem le_zero_iff' {n : ℕ} [NeZero n] {k : Fin n} : k ≤ 0 ↔ k = 0 := ⟨fun h => Fin.ext <| by rw [Nat.eq_zero_of_le_zero h]; rfl, by rintro rfl; exact Nat.le_refl _⟩ -- TODO: Move to Batteries @[simp] lemma castLE_inj {hmn : m ≤ n} {a b : Fin m} : castLE hmn a = castLE hmn b ↔ a = b := by simp [Fin.ext_iff] @[simp] lemma castAdd_inj {a b : Fin m} : castAdd n a = castAdd n b ↔ a = b := by simp [Fin.ext_iff] attribute [simp] castSucc_inj lemma castLE_injective (hmn : m ≤ n) : Injective (castLE hmn) := fun _ _ hab ↦ Fin.ext (congr_arg val hab :) lemma castAdd_injective (m n : ℕ) : Injective (@Fin.castAdd m n) := castLE_injective _ lemma castSucc_injective (n : ℕ) : Injective (@Fin.castSucc n) := castAdd_injective _ _ /-- `Fin.castLE` as an `Embedding`, `castLEEmb h i` embeds `i` into a larger `Fin` type. -/ @[simps apply] def castLEEmb (h : n ≤ m) : Fin n ↪ Fin m where toFun := castLE h inj' := castLE_injective _ @[simp, norm_cast] lemma coe_castLEEmb {m n} (hmn : m ≤ n) : castLEEmb hmn = castLE hmn := rfl /- The next proof can be golfed a lot using `Fintype.card`. It is written this way to define `ENat.card` and `Nat.card` without a `Fintype` dependency (not done yet). -/ lemma nonempty_embedding_iff : Nonempty (Fin n ↪ Fin m) ↔ n ≤ m := by refine ⟨fun h ↦ ?_, fun h ↦ ⟨castLEEmb h⟩⟩ induction n generalizing m with | zero => exact m.zero_le | succ n ihn => obtain ⟨e⟩ := h rcases exists_eq_succ_of_ne_zero (pos_iff_nonempty.2 (Nonempty.map e inferInstance)).ne' with ⟨m, rfl⟩ refine Nat.succ_le_succ <| ihn ⟨?_⟩ refine ⟨fun i ↦ (e.setValue 0 0 i.succ).pred (mt e.setValue_eq_iff.1 i.succ_ne_zero), fun i j h ↦ ?_⟩ simpa only [pred_inj, EmbeddingLike.apply_eq_iff_eq, succ_inj] using h lemma equiv_iff_eq : Nonempty (Fin m ≃ Fin n) ↔ m = n := ⟨fun ⟨e⟩ ↦ le_antisymm (nonempty_embedding_iff.1 ⟨e⟩) (nonempty_embedding_iff.1 ⟨e.symm⟩), fun h ↦ h ▸ ⟨.refl _⟩⟩ @[simp] lemma castLE_castSucc {n m} (i : Fin n) (h : n + 1 ≤ m) : i.castSucc.castLE h = i.castLE (Nat.le_of_succ_le h) := rfl @[simp] lemma castLE_comp_castSucc {n m} (h : n + 1 ≤ m) : Fin.castLE h ∘ Fin.castSucc = Fin.castLE (Nat.le_of_succ_le h) := rfl @[simp] lemma castLE_rfl (n : ℕ) : Fin.castLE (le_refl n) = id := rfl @[simp] theorem range_castLE {n k : ℕ} (h : n ≤ k) : Set.range (castLE h) = { i : Fin k | (i : ℕ) < n } := Set.ext fun x => ⟨fun ⟨y, hy⟩ => hy ▸ y.2, fun hx => ⟨⟨x, hx⟩, rfl⟩⟩ @[simp] theorem coe_of_injective_castLE_symm {n k : ℕ} (h : n ≤ k) (i : Fin k) (hi) : ((Equiv.ofInjective _ (castLE_injective h)).symm ⟨i, hi⟩ : ℕ) = i := by rw [← coe_castLE h] exact congr_arg Fin.val (Equiv.apply_ofInjective_symm _ _) theorem leftInverse_cast (eq : n = m) : LeftInverse (Fin.cast eq.symm) (Fin.cast eq) := fun _ => rfl theorem rightInverse_cast (eq : n = m) : RightInverse (Fin.cast eq.symm) (Fin.cast eq) := fun _ => rfl @[simp] theorem cast_inj (eq : n = m) {a b : Fin n} : a.cast eq = b.cast eq ↔ a = b := by simp [← val_inj] @[simp] theorem cast_lt_cast (eq : n = m) {a b : Fin n} : a.cast eq < b.cast eq ↔ a < b := Iff.rfl @[simp] theorem cast_le_cast (eq : n = m) {a b : Fin n} : a.cast eq ≤ b.cast eq ↔ a ≤ b := Iff.rfl /-- The 'identity' equivalence between `Fin m` and `Fin n` when `m = n`. -/ @[simps] def _root_.finCongr (eq : n = m) : Fin n ≃ Fin m where toFun := Fin.cast eq invFun := Fin.cast eq.symm left_inv := leftInverse_cast eq right_inv := rightInverse_cast eq @[simp] lemma _root_.finCongr_apply_mk (h : m = n) (k : ℕ) (hk : k < m) : finCongr h ⟨k, hk⟩ = ⟨k, h ▸ hk⟩ := rfl @[simp] lemma _root_.finCongr_refl (h : n = n := rfl) : finCongr h = Equiv.refl (Fin n) := by ext; simp @[simp] lemma _root_.finCongr_symm (h : m = n) : (finCongr h).symm = finCongr h.symm := rfl @[simp] lemma _root_.finCongr_apply_coe (h : m = n) (k : Fin m) : (finCongr h k : ℕ) = k := rfl lemma _root_.finCongr_symm_apply_coe (h : m = n) (k : Fin n) : ((finCongr h).symm k : ℕ) = k := rfl /-- While in many cases `finCongr` is better than `Equiv.cast`/`cast`, sometimes we want to apply a generic theorem about `cast`. -/ lemma _root_.finCongr_eq_equivCast (h : n = m) : finCongr h = .cast (h ▸ rfl) := by subst h; simp /-- While in many cases `Fin.cast` is better than `Equiv.cast`/`cast`, sometimes we want to apply a generic theorem about `cast`. -/ theorem cast_eq_cast (h : n = m) : (Fin.cast h : Fin n → Fin m) = _root_.cast (h ▸ rfl) := by subst h ext rfl /-- `Fin.castAdd` as an `Embedding`, `castAddEmb m i` embeds `i : Fin n` in `Fin (n+m)`. See also `Fin.natAddEmb` and `Fin.addNatEmb`. -/ def castAddEmb (m) : Fin n ↪ Fin (n + m) := castLEEmb (le_add_right n m) @[simp] lemma coe_castAddEmb (m) : (castAddEmb m : Fin n → Fin (n + m)) = castAdd m := rfl lemma castAddEmb_apply (m) (i : Fin n) : castAddEmb m i = castAdd m i := rfl /-- `Fin.castSucc` as an `Embedding`, `castSuccEmb i` embeds `i : Fin n` in `Fin (n+1)`. -/ def castSuccEmb : Fin n ↪ Fin (n + 1) := castAddEmb _ @[simp, norm_cast] lemma coe_castSuccEmb : (castSuccEmb : Fin n → Fin (n + 1)) = Fin.castSucc := rfl lemma castSuccEmb_apply (i : Fin n) : castSuccEmb i = i.castSucc := rfl theorem castSucc_le_succ {n} (i : Fin n) : i.castSucc ≤ i.succ := Nat.le_succ i @[simp] theorem castSucc_le_castSucc_iff {a b : Fin n} : castSucc a ≤ castSucc b ↔ a ≤ b := .rfl @[simp] theorem succ_le_castSucc_iff {a b : Fin n} : succ a ≤ castSucc b ↔ a < b := by rw [le_castSucc_iff, succ_lt_succ_iff] @[simp] theorem castSucc_lt_succ_iff {a b : Fin n} : castSucc a < succ b ↔ a ≤ b := by rw [castSucc_lt_iff_succ_le, succ_le_succ_iff] theorem le_of_castSucc_lt_of_succ_lt {a b : Fin (n + 1)} {i : Fin n} (hl : castSucc i < a) (hu : b < succ i) : b < a := by simp [Fin.lt_def, -val_fin_lt] at *; omega theorem castSucc_lt_or_lt_succ (p : Fin (n + 1)) (i : Fin n) : castSucc i < p ∨ p < i.succ := by simp [Fin.lt_def, -val_fin_lt]; omega theorem succ_le_or_le_castSucc (p : Fin (n + 1)) (i : Fin n) : succ i ≤ p ∨ p ≤ i.castSucc := by rw [le_castSucc_iff, ← castSucc_lt_iff_succ_le] exact p.castSucc_lt_or_lt_succ i theorem eq_castSucc_of_ne_last {x : Fin (n + 1)} (h : x ≠ (last _)) : ∃ y, Fin.castSucc y = x := exists_castSucc_eq.mpr h @[deprecated (since := "2025-02-06")] alias exists_castSucc_eq_of_ne_last := eq_castSucc_of_ne_last theorem forall_fin_succ' {P : Fin (n + 1) → Prop} : (∀ i, P i) ↔ (∀ i : Fin n, P i.castSucc) ∧ P (.last _) := ⟨fun H => ⟨fun _ => H _, H _⟩, fun ⟨H0, H1⟩ i => Fin.lastCases H1 H0 i⟩ -- to match `Fin.eq_zero_or_eq_succ` theorem eq_castSucc_or_eq_last {n : Nat} (i : Fin (n + 1)) : (∃ j : Fin n, i = j.castSucc) ∨ i = last n := i.lastCases (Or.inr rfl) (Or.inl ⟨·, rfl⟩) @[simp] theorem castSucc_ne_last {n : ℕ} (i : Fin n) : i.castSucc ≠ .last n := Fin.ne_of_lt i.castSucc_lt_last theorem exists_fin_succ' {P : Fin (n + 1) → Prop} : (∃ i, P i) ↔ (∃ i : Fin n, P i.castSucc) ∨ P (.last _) := ⟨fun ⟨i, h⟩ => Fin.lastCases Or.inr (fun i hi => Or.inl ⟨i, hi⟩) i h, fun h => h.elim (fun ⟨i, hi⟩ => ⟨i.castSucc, hi⟩) (fun h => ⟨.last _, h⟩)⟩ /-- The `Fin.castSucc_zero` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ @[simp] theorem castSucc_zero' [NeZero n] : castSucc (0 : Fin n) = 0 := rfl @[simp] theorem castSucc_pos_iff [NeZero n] {i : Fin n} : 0 < castSucc i ↔ 0 < i := by simp [← val_pos_iff] /-- `castSucc i` is positive when `i` is positive. The `Fin.castSucc_pos` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ alias ⟨_, castSucc_pos'⟩ := castSucc_pos_iff /-- The `Fin.castSucc_eq_zero_iff` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ @[simp] theorem castSucc_eq_zero_iff' [NeZero n] (a : Fin n) : castSucc a = 0 ↔ a = 0 := Fin.ext_iff.trans <| (Fin.ext_iff.trans <| by simp).symm /-- The `Fin.castSucc_ne_zero_iff` in `Lean` only applies in `Fin (n+1)`. This one instead uses a `NeZero n` typeclass hypothesis. -/ theorem castSucc_ne_zero_iff' [NeZero n] (a : Fin n) : castSucc a ≠ 0 ↔ a ≠ 0 := not_iff_not.mpr <| castSucc_eq_zero_iff' a theorem castSucc_ne_zero_of_lt {p i : Fin n} (h : p < i) : castSucc i ≠ 0 := by cases n · exact i.elim0 · rw [castSucc_ne_zero_iff', Ne, Fin.ext_iff] exact ((zero_le _).trans_lt h).ne' theorem succ_ne_last_iff (a : Fin (n + 1)) : succ a ≠ last (n + 1) ↔ a ≠ last n := not_iff_not.mpr <| succ_eq_last_succ theorem succ_ne_last_of_lt {p i : Fin n} (h : i < p) : succ i ≠ last n := by cases n · exact i.elim0 · rw [succ_ne_last_iff, Ne, Fin.ext_iff] exact ((le_last _).trans_lt' h).ne @[norm_cast, simp] theorem coe_eq_castSucc {a : Fin n} : (a : Fin (n + 1)) = castSucc a := by ext exact val_cast_of_lt (Nat.lt.step a.is_lt) theorem coe_succ_lt_iff_lt {n : ℕ} {j k : Fin n} : (j : Fin <| n + 1) < k ↔ j < k := by simp only [coe_eq_castSucc, castSucc_lt_castSucc_iff] @[simp] theorem range_castSucc {n : ℕ} : Set.range (castSucc : Fin n → Fin n.succ) = ({ i | (i : ℕ) < n } : Set (Fin n.succ)) := range_castLE (by omega) @[simp] theorem coe_of_injective_castSucc_symm {n : ℕ} (i : Fin n.succ) (hi) : ((Equiv.ofInjective castSucc (castSucc_injective _)).symm ⟨i, hi⟩ : ℕ) = i := by rw [← coe_castSucc] exact congr_arg val (Equiv.apply_ofInjective_symm _ _) /-- `Fin.addNat` as an `Embedding`, `addNatEmb m i` adds `m` to `i`, generalizes `Fin.succ`. -/ @[simps! apply] def addNatEmb (m) : Fin n ↪ Fin (n + m) where toFun := (addNat · m) inj' a b := by simp [Fin.ext_iff] /-- `Fin.natAdd` as an `Embedding`, `natAddEmb n i` adds `n` to `i` "on the left". -/ @[simps! apply] def natAddEmb (n) {m} : Fin m ↪ Fin (n + m) where toFun := natAdd n inj' a b := by simp [Fin.ext_iff] theorem castSucc_castAdd (i : Fin n) : castSucc (castAdd m i) = castAdd (m + 1) i := rfl theorem castSucc_natAdd (i : Fin m) : castSucc (natAdd n i) = natAdd n (castSucc i) := rfl theorem succ_castAdd (i : Fin n) : succ (castAdd m i) = if h : i.succ = last _ then natAdd n (0 : Fin (m + 1)) else castAdd (m + 1) ⟨i.1 + 1, lt_of_le_of_ne i.2 (Fin.val_ne_iff.mpr h)⟩ := by split_ifs with h exacts [Fin.ext (congr_arg Fin.val h :), rfl] theorem succ_natAdd (i : Fin m) : succ (natAdd n i) = natAdd n (succ i) := rfl end Succ section Pred /-! ### pred -/ theorem pred_one' [NeZero n] (h := (zero_ne_one' (n := n)).symm) : Fin.pred (1 : Fin (n + 1)) h = 0 := by simp_rw [Fin.ext_iff, coe_pred, val_one', val_zero, Nat.sub_eq_zero_iff_le, Nat.mod_le] theorem pred_last (h := Fin.ext_iff.not.2 last_pos'.ne') : pred (last (n + 1)) h = last n := by simp_rw [← succ_last, pred_succ] theorem pred_lt_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : pred i hi < j ↔ i < succ j := by rw [← succ_lt_succ_iff, succ_pred] theorem lt_pred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : j < pred i hi ↔ succ j < i := by rw [← succ_lt_succ_iff, succ_pred] theorem pred_le_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : pred i hi ≤ j ↔ i ≤ succ j := by rw [← succ_le_succ_iff, succ_pred] theorem le_pred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : j ≤ pred i hi ↔ succ j ≤ i := by rw [← succ_le_succ_iff, succ_pred] theorem castSucc_pred_eq_pred_castSucc {a : Fin (n + 1)} (ha : a ≠ 0) (ha' := castSucc_ne_zero_iff.mpr ha) : (a.pred ha).castSucc = (castSucc a).pred ha' := rfl theorem castSucc_pred_add_one_eq {a : Fin (n + 1)} (ha : a ≠ 0) : (a.pred ha).castSucc + 1 = a := by cases a using cases · exact (ha rfl).elim · rw [pred_succ, coeSucc_eq_succ] theorem le_pred_castSucc_iff {a b : Fin (n + 1)} (ha : castSucc a ≠ 0) : b ≤ (castSucc a).pred ha ↔ b < a := by rw [le_pred_iff, succ_le_castSucc_iff] theorem pred_castSucc_lt_iff {a b : Fin (n + 1)} (ha : castSucc a ≠ 0) : (castSucc a).pred ha < b ↔ a ≤ b := by rw [pred_lt_iff, castSucc_lt_succ_iff] theorem pred_castSucc_lt {a : Fin (n + 1)} (ha : castSucc a ≠ 0) : (castSucc a).pred ha < a := by rw [pred_castSucc_lt_iff, le_def] theorem le_castSucc_pred_iff {a b : Fin (n + 1)} (ha : a ≠ 0) : b ≤ castSucc (a.pred ha) ↔ b < a := by rw [castSucc_pred_eq_pred_castSucc, le_pred_castSucc_iff] theorem castSucc_pred_lt_iff {a b : Fin (n + 1)} (ha : a ≠ 0) : castSucc (a.pred ha) < b ↔ a ≤ b := by rw [castSucc_pred_eq_pred_castSucc, pred_castSucc_lt_iff] theorem castSucc_pred_lt {a : Fin (n + 1)} (ha : a ≠ 0) : castSucc (a.pred ha) < a := by rw [castSucc_pred_lt_iff, le_def] end Pred section CastPred /-- `castPred i` sends `i : Fin (n + 1)` to `Fin n` as long as i ≠ last n. -/ @[inline] def castPred (i : Fin (n + 1)) (h : i ≠ last n) : Fin n := castLT i (val_lt_last h) @[simp] lemma castLT_eq_castPred (i : Fin (n + 1)) (h : i < last _) (h' := Fin.ext_iff.not.2 h.ne) : castLT i h = castPred i h' := rfl @[simp] lemma coe_castPred (i : Fin (n + 1)) (h : i ≠ last _) : (castPred i h : ℕ) = i := rfl @[simp] theorem castPred_castSucc {i : Fin n} (h' := Fin.ext_iff.not.2 (castSucc_lt_last i).ne) : castPred (castSucc i) h' = i := rfl @[simp] theorem castSucc_castPred (i : Fin (n + 1)) (h : i ≠ last n) : castSucc (i.castPred h) = i := by rcases exists_castSucc_eq.mpr h with ⟨y, rfl⟩ rw [castPred_castSucc] theorem castPred_eq_iff_eq_castSucc (i : Fin (n + 1)) (hi : i ≠ last _) (j : Fin n) : castPred i hi = j ↔ i = castSucc j := ⟨fun h => by rw [← h, castSucc_castPred], fun h => by simp_rw [h, castPred_castSucc]⟩ @[simp] theorem castPred_mk (i : ℕ) (h₁ : i < n) (h₂ := h₁.trans (Nat.lt_succ_self _)) (h₃ : ⟨i, h₂⟩ ≠ last _ := (ne_iff_vne _ _).mpr (val_last _ ▸ h₁.ne)) : castPred ⟨i, h₂⟩ h₃ = ⟨i, h₁⟩ := rfl @[simp] theorem castPred_le_castPred_iff {i j : Fin (n + 1)} {hi : i ≠ last n} {hj : j ≠ last n} : castPred i hi ≤ castPred j hj ↔ i ≤ j := Iff.rfl /-- A version of the right-to-left implication of `castPred_le_castPred_iff` that deduces `i ≠ last n` from `i ≤ j` and `j ≠ last n`. -/ @[gcongr] theorem castPred_le_castPred {i j : Fin (n + 1)} (h : i ≤ j) (hj : j ≠ last n) : castPred i (by rw [← lt_last_iff_ne_last] at hj ⊢; exact Fin.lt_of_le_of_lt h hj) ≤ castPred j hj := h @[simp] theorem castPred_lt_castPred_iff {i j : Fin (n + 1)} {hi : i ≠ last n} {hj : j ≠ last n} : castPred i hi < castPred j hj ↔ i < j := Iff.rfl /-- A version of the right-to-left implication of `castPred_lt_castPred_iff` that deduces `i ≠ last n` from `i < j`. -/ @[gcongr] theorem castPred_lt_castPred {i j : Fin (n + 1)} (h : i < j) (hj : j ≠ last n) : castPred i (ne_last_of_lt h) < castPred j hj := h theorem castPred_lt_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) : castPred i hi < j ↔ i < castSucc j := by rw [← castSucc_lt_castSucc_iff, castSucc_castPred] theorem lt_castPred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) : j < castPred i hi ↔ castSucc j < i := by rw [← castSucc_lt_castSucc_iff, castSucc_castPred] theorem castPred_le_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) : castPred i hi ≤ j ↔ i ≤ castSucc j := by rw [← castSucc_le_castSucc_iff, castSucc_castPred] theorem le_castPred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ last n) : j ≤ castPred i hi ↔ castSucc j ≤ i := by rw [← castSucc_le_castSucc_iff, castSucc_castPred] @[simp] theorem castPred_inj {i j : Fin (n + 1)} {hi : i ≠ last n} {hj : j ≠ last n} : castPred i hi = castPred j hj ↔ i = j := by simp_rw [Fin.ext_iff, le_antisymm_iff, ← le_def, castPred_le_castPred_iff] theorem castPred_zero' [NeZero n] (h := Fin.ext_iff.not.2 last_pos'.ne) : castPred (0 : Fin (n + 1)) h = 0 := rfl theorem castPred_zero (h := Fin.ext_iff.not.2 last_pos.ne) : castPred (0 : Fin (n + 2)) h = 0 := rfl @[simp] theorem castPred_eq_zero [NeZero n] {i : Fin (n + 1)} (h : i ≠ last n) : Fin.castPred i h = 0 ↔ i = 0 := by rw [← castPred_zero', castPred_inj] @[simp] theorem castPred_one [NeZero n] (h := Fin.ext_iff.not.2 one_lt_last.ne) : castPred (1 : Fin (n + 2)) h = 1 := by cases n · exact subsingleton_one.elim _ 1 · rfl theorem succ_castPred_eq_castPred_succ {a : Fin (n + 1)} (ha : a ≠ last n) (ha' := a.succ_ne_last_iff.mpr ha) : (a.castPred ha).succ = (succ a).castPred ha' := rfl theorem succ_castPred_eq_add_one {a : Fin (n + 1)} (ha : a ≠ last n) : (a.castPred ha).succ = a + 1 := by cases a using lastCases · exact (ha rfl).elim · rw [castPred_castSucc, coeSucc_eq_succ] theorem castpred_succ_le_iff {a b : Fin (n + 1)} (ha : succ a ≠ last (n + 1)) : (succ a).castPred ha ≤ b ↔ a < b := by rw [castPred_le_iff, succ_le_castSucc_iff] theorem lt_castPred_succ_iff {a b : Fin (n + 1)} (ha : succ a ≠ last (n + 1)) : b < (succ a).castPred ha ↔ b ≤ a := by rw [lt_castPred_iff, castSucc_lt_succ_iff] theorem lt_castPred_succ {a : Fin (n + 1)} (ha : succ a ≠ last (n + 1)) : a < (succ a).castPred ha := by rw [lt_castPred_succ_iff, le_def] theorem succ_castPred_le_iff {a b : Fin (n + 1)} (ha : a ≠ last n) : succ (a.castPred ha) ≤ b ↔ a < b := by rw [succ_castPred_eq_castPred_succ ha, castpred_succ_le_iff] theorem lt_succ_castPred_iff {a b : Fin (n + 1)} (ha : a ≠ last n) : b < succ (a.castPred ha) ↔ b ≤ a := by rw [succ_castPred_eq_castPred_succ ha, lt_castPred_succ_iff] theorem lt_succ_castPred {a : Fin (n + 1)} (ha : a ≠ last n) : a < succ (a.castPred ha) := by rw [lt_succ_castPred_iff, le_def] theorem castPred_le_pred_iff {a b : Fin (n + 1)} (ha : a ≠ last n) (hb : b ≠ 0) : castPred a ha ≤ pred b hb ↔ a < b := by rw [le_pred_iff, succ_castPred_le_iff] theorem pred_lt_castPred_iff {a b : Fin (n + 1)} (ha : a ≠ 0) (hb : b ≠ last n) : pred a ha < castPred b hb ↔ a ≤ b := by rw [lt_castPred_iff, castSucc_pred_lt_iff ha] theorem pred_lt_castPred {a : Fin (n + 1)} (h₁ : a ≠ 0) (h₂ : a ≠ last n) : pred a h₁ < castPred a h₂ := by rw [pred_lt_castPred_iff, le_def] end CastPred section SuccAbove variable {p : Fin (n + 1)} {i j : Fin n} /-- `succAbove p i` embeds `Fin n` into `Fin (n + 1)` with a hole around `p`. -/ def succAbove (p : Fin (n + 1)) (i : Fin n) : Fin (n + 1) := if castSucc i < p then i.castSucc else i.succ /-- Embedding `i : Fin n` into `Fin (n + 1)` with a hole around `p : Fin (n + 1)` embeds `i` by `castSucc` when the resulting `i.castSucc < p`. -/ lemma succAbove_of_castSucc_lt (p : Fin (n + 1)) (i : Fin n) (h : castSucc i < p) : p.succAbove i = castSucc i := if_pos h lemma succAbove_of_succ_le (p : Fin (n + 1)) (i : Fin n) (h : succ i ≤ p) : p.succAbove i = castSucc i := succAbove_of_castSucc_lt _ _ (castSucc_lt_iff_succ_le.mpr h) /-- Embedding `i : Fin n` into `Fin (n + 1)` with a hole around `p : Fin (n + 1)` embeds `i` by `succ` when the resulting `p < i.succ`. -/ lemma succAbove_of_le_castSucc (p : Fin (n + 1)) (i : Fin n) (h : p ≤ castSucc i) : p.succAbove i = i.succ := if_neg (Fin.not_lt.2 h) lemma succAbove_of_lt_succ (p : Fin (n + 1)) (i : Fin n) (h : p < succ i) : p.succAbove i = succ i := succAbove_of_le_castSucc _ _ (le_castSucc_iff.mpr h) lemma succAbove_succ_of_lt (p i : Fin n) (h : p < i) : succAbove p.succ i = i.succ := succAbove_of_lt_succ _ _ (succ_lt_succ_iff.mpr h) lemma succAbove_succ_of_le (p i : Fin n) (h : i ≤ p) : succAbove p.succ i = i.castSucc := succAbove_of_succ_le _ _ (succ_le_succ_iff.mpr h) @[simp] lemma succAbove_succ_self (j : Fin n) : j.succ.succAbove j = j.castSucc := succAbove_succ_of_le _ _ Fin.le_rfl lemma succAbove_castSucc_of_lt (p i : Fin n) (h : i < p) : succAbove p.castSucc i = i.castSucc := succAbove_of_castSucc_lt _ _ (castSucc_lt_castSucc_iff.2 h) lemma succAbove_castSucc_of_le (p i : Fin n) (h : p ≤ i) : succAbove p.castSucc i = i.succ := succAbove_of_le_castSucc _ _ (castSucc_le_castSucc_iff.2 h) @[simp] lemma succAbove_castSucc_self (j : Fin n) : succAbove j.castSucc j = j.succ := succAbove_castSucc_of_le _ _ Fin.le_rfl lemma succAbove_pred_of_lt (p i : Fin (n + 1)) (h : p < i) (hi := Fin.ne_of_gt <| Fin.lt_of_le_of_lt p.zero_le h) : succAbove p (i.pred hi) = i := by rw [succAbove_of_lt_succ _ _ (succ_pred _ _ ▸ h), succ_pred] lemma succAbove_pred_of_le (p i : Fin (n + 1)) (h : i ≤ p) (hi : i ≠ 0) : succAbove p (i.pred hi) = (i.pred hi).castSucc := succAbove_of_succ_le _ _ (succ_pred _ _ ▸ h) @[simp] lemma succAbove_pred_self (p : Fin (n + 1)) (h : p ≠ 0) : succAbove p (p.pred h) = (p.pred h).castSucc := succAbove_pred_of_le _ _ Fin.le_rfl h lemma succAbove_castPred_of_lt (p i : Fin (n + 1)) (h : i < p) (hi := Fin.ne_of_lt <| Nat.lt_of_lt_of_le h p.le_last) : succAbove p (i.castPred hi) = i := by rw [succAbove_of_castSucc_lt _ _ (castSucc_castPred _ _ ▸ h), castSucc_castPred] lemma succAbove_castPred_of_le (p i : Fin (n + 1)) (h : p ≤ i) (hi : i ≠ last n) : succAbove p (i.castPred hi) = (i.castPred hi).succ := succAbove_of_le_castSucc _ _ (castSucc_castPred _ _ ▸ h) lemma succAbove_castPred_self (p : Fin (n + 1)) (h : p ≠ last n) : succAbove p (p.castPred h) = (p.castPred h).succ := succAbove_castPred_of_le _ _ Fin.le_rfl h /-- Embedding `i : Fin n` into `Fin (n + 1)` with a hole around `p : Fin (n + 1)` never results in `p` itself -/ @[simp] lemma succAbove_ne (p : Fin (n + 1)) (i : Fin n) : p.succAbove i ≠ p := by rcases p.castSucc_lt_or_lt_succ i with (h | h) · rw [succAbove_of_castSucc_lt _ _ h] exact Fin.ne_of_lt h · rw [succAbove_of_lt_succ _ _ h] exact Fin.ne_of_gt h @[simp] lemma ne_succAbove (p : Fin (n + 1)) (i : Fin n) : p ≠ p.succAbove i := (succAbove_ne _ _).symm /-- Given a fixed pivot `p : Fin (n + 1)`, `p.succAbove` is injective. -/ lemma succAbove_right_injective : Injective p.succAbove := by rintro i j hij unfold succAbove at hij split_ifs at hij with hi hj hj · exact castSucc_injective _ hij · rw [hij] at hi cases hj <| Nat.lt_trans j.castSucc_lt_succ hi · rw [← hij] at hj cases hi <| Nat.lt_trans i.castSucc_lt_succ hj · exact succ_injective _ hij /-- Given a fixed pivot `p : Fin (n + 1)`, `p.succAbove` is injective. -/ lemma succAbove_right_inj : p.succAbove i = p.succAbove j ↔ i = j := succAbove_right_injective.eq_iff /-- `Fin.succAbove p` as an `Embedding`. -/ @[simps!] def succAboveEmb (p : Fin (n + 1)) : Fin n ↪ Fin (n + 1) := ⟨p.succAbove, succAbove_right_injective⟩ @[simp, norm_cast] lemma coe_succAboveEmb (p : Fin (n + 1)) : p.succAboveEmb = p.succAbove := rfl @[simp] lemma succAbove_ne_zero_zero [NeZero n] {a : Fin (n + 1)} (ha : a ≠ 0) : a.succAbove 0 = 0 := by rw [Fin.succAbove_of_castSucc_lt] · exact castSucc_zero' · exact Fin.pos_iff_ne_zero.2 ha lemma succAbove_eq_zero_iff [NeZero n] {a : Fin (n + 1)} {b : Fin n} (ha : a ≠ 0) : a.succAbove b = 0 ↔ b = 0 := by rw [← succAbove_ne_zero_zero ha, succAbove_right_inj] lemma succAbove_ne_zero [NeZero n] {a : Fin (n + 1)} {b : Fin n} (ha : a ≠ 0) (hb : b ≠ 0) : a.succAbove b ≠ 0 := mt (succAbove_eq_zero_iff ha).mp hb /-- Embedding `Fin n` into `Fin (n + 1)` with a hole around zero embeds by `succ`. -/ @[simp] lemma succAbove_zero : succAbove (0 : Fin (n + 1)) = Fin.succ := rfl lemma succAbove_zero_apply (i : Fin n) : succAbove 0 i = succ i := by rw [succAbove_zero] @[simp] lemma succAbove_ne_last_last {a : Fin (n + 2)} (h : a ≠ last (n + 1)) : a.succAbove (last n) = last (n + 1) := by rw [succAbove_of_lt_succ _ _ (succ_last _ ▸ lt_last_iff_ne_last.2 h), succ_last] lemma succAbove_eq_last_iff {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ last _) : a.succAbove b = last _ ↔ b = last _ := by rw [← succAbove_ne_last_last ha, succAbove_right_inj] lemma succAbove_ne_last {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ last _) (hb : b ≠ last _) : a.succAbove b ≠ last _ := mt (succAbove_eq_last_iff ha).mp hb /-- Embedding `Fin n` into `Fin (n + 1)` with a hole around `last n` embeds by `castSucc`. -/ @[simp] lemma succAbove_last : succAbove (last n) = castSucc := by ext; simp only [succAbove_of_castSucc_lt, castSucc_lt_last] lemma succAbove_last_apply (i : Fin n) : succAbove (last n) i = castSucc i := by rw [succAbove_last] /-- Embedding `i : Fin n` into `Fin (n + 1)` using a pivot `p` that is greater results in a value that is less than `p`. -/ lemma succAbove_lt_iff_castSucc_lt (p : Fin (n + 1)) (i : Fin n) : p.succAbove i < p ↔ castSucc i < p := by rcases castSucc_lt_or_lt_succ p i with H | H · rwa [iff_true_right H, succAbove_of_castSucc_lt _ _ H] · rw [castSucc_lt_iff_succ_le, iff_false_right (Fin.not_le.2 H), succAbove_of_lt_succ _ _ H] exact Fin.not_lt.2 <| Fin.le_of_lt H lemma succAbove_lt_iff_succ_le (p : Fin (n + 1)) (i : Fin n) : p.succAbove i < p ↔ succ i ≤ p := by rw [succAbove_lt_iff_castSucc_lt, castSucc_lt_iff_succ_le] /-- Embedding `i : Fin n` into `Fin (n + 1)` using a pivot `p` that is lesser results in a value that is greater than `p`. -/ lemma lt_succAbove_iff_le_castSucc (p : Fin (n + 1)) (i : Fin n) : p < p.succAbove i ↔ p ≤ castSucc i := by rcases castSucc_lt_or_lt_succ p i with H | H · rw [iff_false_right (Fin.not_le.2 H), succAbove_of_castSucc_lt _ _ H] exact Fin.not_lt.2 <| Fin.le_of_lt H · rwa [succAbove_of_lt_succ _ _ H, iff_true_left H, le_castSucc_iff] lemma lt_succAbove_iff_lt_castSucc (p : Fin (n + 1)) (i : Fin n) : p < p.succAbove i ↔ p < succ i := by rw [lt_succAbove_iff_le_castSucc, le_castSucc_iff] /-- Embedding a positive `Fin n` results in a positive `Fin (n + 1)` -/ lemma succAbove_pos [NeZero n] (p : Fin (n + 1)) (i : Fin n) (h : 0 < i) : 0 < p.succAbove i := by by_cases H : castSucc i < p · simpa [succAbove_of_castSucc_lt _ _ H] using castSucc_pos' h · simp [succAbove_of_le_castSucc _ _ (Fin.not_lt.1 H)] lemma castPred_succAbove (x : Fin n) (y : Fin (n + 1)) (h : castSucc x < y) (h' := Fin.ne_last_of_lt <| (succAbove_lt_iff_castSucc_lt ..).2 h) : (y.succAbove x).castPred h' = x := by rw [castPred_eq_iff_eq_castSucc, succAbove_of_castSucc_lt _ _ h] lemma pred_succAbove (x : Fin n) (y : Fin (n + 1)) (h : y ≤ castSucc x) (h' := Fin.ne_zero_of_lt <| (lt_succAbove_iff_le_castSucc ..).2 h) : (y.succAbove x).pred h' = x := by simp only [succAbove_of_le_castSucc _ _ h, pred_succ] lemma exists_succAbove_eq {x y : Fin (n + 1)} (h : x ≠ y) : ∃ z, y.succAbove z = x := by obtain hxy | hyx := Fin.lt_or_lt_of_ne h exacts [⟨_, succAbove_castPred_of_lt _ _ hxy⟩, ⟨_, succAbove_pred_of_lt _ _ hyx⟩] @[simp] lemma exists_succAbove_eq_iff {x y : Fin (n + 1)} : (∃ z, x.succAbove z = y) ↔ y ≠ x := ⟨by rintro ⟨y, rfl⟩; exact succAbove_ne _ _, exists_succAbove_eq⟩ /-- The range of `p.succAbove` is everything except `p`. -/ @[simp] lemma range_succAbove (p : Fin (n + 1)) : Set.range p.succAbove = {p}ᶜ := Set.ext fun _ => exists_succAbove_eq_iff @[simp] lemma range_succ (n : ℕ) : Set.range (Fin.succ : Fin n → Fin (n + 1)) = {0}ᶜ := by rw [← succAbove_zero]; exact range_succAbove (0 : Fin (n + 1)) /-- `succAbove` is injective at the pivot -/ lemma succAbove_left_injective : Injective (@succAbove n) := fun _ _ h => by simpa [range_succAbove] using congr_arg (fun f : Fin n → Fin (n + 1) => (Set.range f)ᶜ) h /-- `succAbove` is injective at the pivot -/ @[simp] lemma succAbove_left_inj {x y : Fin (n + 1)} : x.succAbove = y.succAbove ↔ x = y := succAbove_left_injective.eq_iff @[simp] lemma zero_succAbove {n : ℕ} (i : Fin n) : (0 : Fin (n + 1)).succAbove i = i.succ := rfl lemma succ_succAbove_zero {n : ℕ} [NeZero n] (i : Fin n) : succAbove i.succ 0 = 0 := by simp /-- `succ` commutes with `succAbove`. -/ @[simp] lemma succ_succAbove_succ {n : ℕ} (i : Fin (n + 1)) (j : Fin n) : i.succ.succAbove j.succ = (i.succAbove j).succ := by obtain h | h := i.lt_or_le (succ j) · rw [succAbove_of_lt_succ _ _ h, succAbove_succ_of_lt _ _ h] · rwa [succAbove_of_castSucc_lt _ _ h, succAbove_succ_of_le, succ_castSucc] /-- `castSucc` commutes with `succAbove`. -/ @[simp] lemma castSucc_succAbove_castSucc {n : ℕ} {i : Fin (n + 1)} {j : Fin n} : i.castSucc.succAbove j.castSucc = (i.succAbove j).castSucc := by rcases i.le_or_lt (castSucc j) with (h | h) · rw [succAbove_of_le_castSucc _ _ h, succAbove_castSucc_of_le _ _ h, succ_castSucc] · rw [succAbove_of_castSucc_lt _ _ h, succAbove_castSucc_of_lt _ _ h] /-- `pred` commutes with `succAbove`. -/ lemma pred_succAbove_pred {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ 0) (hb : b ≠ 0) (hk := succAbove_ne_zero ha hb) : (a.pred ha).succAbove (b.pred hb) = (a.succAbove b).pred hk := by simp_rw [← succ_inj (b := pred (succAbove a b) hk), ← succ_succAbove_succ, succ_pred] /-- `castPred` commutes with `succAbove`. -/ lemma castPred_succAbove_castPred {a : Fin (n + 2)} {b : Fin (n + 1)} (ha : a ≠ last (n + 1)) (hb : b ≠ last n) (hk := succAbove_ne_last ha hb) : (a.castPred ha).succAbove (b.castPred hb) = (a.succAbove b).castPred hk := by simp_rw [← castSucc_inj (b := (a.succAbove b).castPred hk), ← castSucc_succAbove_castSucc, castSucc_castPred] lemma one_succAbove_zero {n : ℕ} : (1 : Fin (n + 2)).succAbove 0 = 0 := by rfl /-- By moving `succ` to the outside of this expression, we create opportunities for further simplification using `succAbove_zero` or `succ_succAbove_zero`. -/ @[simp] lemma succ_succAbove_one {n : ℕ} [NeZero n] (i : Fin (n + 1)) : i.succ.succAbove 1 = (i.succAbove 0).succ := by rw [← succ_zero_eq_one']; convert succ_succAbove_succ i 0 @[simp] lemma one_succAbove_succ {n : ℕ} (j : Fin n) : (1 : Fin (n + 2)).succAbove j.succ = j.succ.succ := by have := succ_succAbove_succ 0 j; rwa [succ_zero_eq_one, zero_succAbove] at this @[simp] lemma one_succAbove_one {n : ℕ} : (1 : Fin (n + 3)).succAbove 1 = 2 := by simpa only [succ_zero_eq_one, val_zero, zero_succAbove, succ_one_eq_two] using succ_succAbove_succ (0 : Fin (n + 2)) (0 : Fin (n + 2)) end SuccAbove section PredAbove /-- `predAbove p i` surjects `i : Fin (n+1)` into `Fin n` by subtracting one if `p < i`. -/ def predAbove (p : Fin n) (i : Fin (n + 1)) : Fin n := if h : castSucc p < i then pred i (Fin.ne_zero_of_lt h) else castPred i (Fin.ne_of_lt <| Fin.lt_of_le_of_lt (Fin.not_lt.1 h) (castSucc_lt_last _)) lemma predAbove_of_le_castSucc (p : Fin n) (i : Fin (n + 1)) (h : i ≤ castSucc p) (hi := Fin.ne_of_lt <| Fin.lt_of_le_of_lt h <| castSucc_lt_last _) : p.predAbove i = i.castPred hi := dif_neg <| Fin.not_lt.2 h lemma predAbove_of_lt_succ (p : Fin n) (i : Fin (n + 1)) (h : i < succ p) (hi := Fin.ne_last_of_lt h) : p.predAbove i = i.castPred hi := predAbove_of_le_castSucc _ _ (le_castSucc_iff.mpr h) lemma predAbove_of_castSucc_lt (p : Fin n) (i : Fin (n + 1)) (h : castSucc p < i) (hi := Fin.ne_zero_of_lt h) : p.predAbove i = i.pred hi := dif_pos h lemma predAbove_of_succ_le (p : Fin n) (i : Fin (n + 1)) (h : succ p ≤ i) (hi := Fin.ne_of_gt <| Fin.lt_of_lt_of_le (succ_pos _) h) : p.predAbove i = i.pred hi := predAbove_of_castSucc_lt _ _ (castSucc_lt_iff_succ_le.mpr h) lemma predAbove_succ_of_lt (p i : Fin n) (h : i < p) (hi := succ_ne_last_of_lt h) : p.predAbove (succ i) = (i.succ).castPred hi := by rw [predAbove_of_lt_succ _ _ (succ_lt_succ_iff.mpr h)] lemma predAbove_succ_of_le (p i : Fin n) (h : p ≤ i) : p.predAbove (succ i) = i := by rw [predAbove_of_succ_le _ _ (succ_le_succ_iff.mpr h), pred_succ] @[simp] lemma predAbove_succ_self (p : Fin n) : p.predAbove (succ p) = p := predAbove_succ_of_le _ _ Fin.le_rfl lemma predAbove_castSucc_of_lt (p i : Fin n) (h : p < i) (hi := castSucc_ne_zero_of_lt h) : p.predAbove (castSucc i) = i.castSucc.pred hi := by rw [predAbove_of_castSucc_lt _ _ (castSucc_lt_castSucc_iff.2 h)] lemma predAbove_castSucc_of_le (p i : Fin n) (h : i ≤ p) : p.predAbove (castSucc i) = i := by rw [predAbove_of_le_castSucc _ _ (castSucc_le_castSucc_iff.mpr h), castPred_castSucc] @[simp] lemma predAbove_castSucc_self (p : Fin n) : p.predAbove (castSucc p) = p := predAbove_castSucc_of_le _ _ Fin.le_rfl lemma predAbove_pred_of_lt (p i : Fin (n + 1)) (h : i < p) (hp := Fin.ne_zero_of_lt h) (hi := Fin.ne_last_of_lt h) : (pred p hp).predAbove i = castPred i hi := by rw [predAbove_of_lt_succ _ _ (succ_pred _ _ ▸ h)] lemma predAbove_pred_of_le (p i : Fin (n + 1)) (h : p ≤ i) (hp : p ≠ 0) (hi := Fin.ne_of_gt <| Fin.lt_of_lt_of_le (Fin.pos_iff_ne_zero.2 hp) h) : (pred p hp).predAbove i = pred i hi := by rw [predAbove_of_succ_le _ _ (succ_pred _ _ ▸ h)] lemma predAbove_pred_self (p : Fin (n + 1)) (hp : p ≠ 0) : (pred p hp).predAbove p = pred p hp := predAbove_pred_of_le _ _ Fin.le_rfl hp lemma predAbove_castPred_of_lt (p i : Fin (n + 1)) (h : p < i) (hp := Fin.ne_last_of_lt h) (hi := Fin.ne_zero_of_lt h) : (castPred p hp).predAbove i = pred i hi := by rw [predAbove_of_castSucc_lt _ _ (castSucc_castPred _ _ ▸ h)] lemma predAbove_castPred_of_le (p i : Fin (n + 1)) (h : i ≤ p) (hp : p ≠ last n) (hi := Fin.ne_of_lt <| Fin.lt_of_le_of_lt h <| Fin.lt_last_iff_ne_last.2 hp) : (castPred p hp).predAbove i = castPred i hi := by rw [predAbove_of_le_castSucc _ _ (castSucc_castPred _ _ ▸ h)] lemma predAbove_castPred_self (p : Fin (n + 1)) (hp : p ≠ last n) : (castPred p hp).predAbove p = castPred p hp := predAbove_castPred_of_le _ _ Fin.le_rfl hp @[simp] lemma predAbove_right_zero [NeZero n] {i : Fin n} : predAbove (i : Fin n) 0 = 0 := by cases n
· exact i.elim0 · rw [predAbove_of_le_castSucc _ _ (zero_le _), castPred_zero]
Mathlib/Data/Fin/Basic.lean
1,239
1,241
/- Copyright (c) 2024 Antoine Chambert-Loir. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Antoine Chambert-Loir -/ import Mathlib.LinearAlgebra.DirectSum.Finsupp import Mathlib.Algebra.MvPolynomial.Eval import Mathlib.RingTheory.TensorProduct.Basic import Mathlib.Algebra.MvPolynomial.Equiv import Mathlib.RingTheory.IsTensorProduct /-! # Tensor Product of (multivariate) polynomial rings Let `Semiring R`, `Algebra R S` and `Module R N`. * `MvPolynomial.rTensor` gives the linear equivalence `MvPolynomial σ S ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ (S ⊗[R] N)` characterized, for `p : MvPolynomial σ S`, `n : N` and `d : σ →₀ ℕ`, by `rTensor (p ⊗ₜ[R] n) d = (coeff d p) ⊗ₜ[R] n` * `MvPolynomial.scalarRTensor` gives the linear equivalence `MvPolynomial σ R ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ N` such that `MvPolynomial.scalarRTensor (p ⊗ₜ[R] n) d = coeff d p • n` for `p : MvPolynomial σ R`, `n : N` and `d : σ →₀ ℕ`, by * `MvPolynomial.rTensorAlgHom`, the algebra morphism from the tensor product of a polynomial algebra by an algebra to a polynomial algebra * `MvPolynomial.rTensorAlgEquiv`, `MvPolynomial.scalarRTensorAlgEquiv`, the tensor product of a polynomial algebra by an algebra is algebraically equivalent to a polynomial algebra ## TODO : * `MvPolynomial.rTensor` could be phrased in terms of `AddMonoidAlgebra`, and `MvPolynomial.rTensor` then has `smul` by the polynomial algebra. * `MvPolynomial.rTensorAlgHom` and `MvPolynomial.scalarRTensorAlgEquiv` are morphisms for the algebra structure by `MvPolynomial σ R`. -/ universe u v noncomputable section namespace MvPolynomial open DirectSum TensorProduct open Set LinearMap Submodule variable {R : Type u} {N : Type v} [CommSemiring R] variable {σ : Type*} variable {S : Type*} [CommSemiring S] [Algebra R S] section Module variable [DecidableEq σ] variable [AddCommMonoid N] [Module R N] /-- The tensor product of a polynomial ring by a module is linearly equivalent to a Finsupp of a tensor product -/ noncomputable def rTensor : MvPolynomial σ S ⊗[R] N ≃ₗ[S] (σ →₀ ℕ) →₀ (S ⊗[R] N) := TensorProduct.finsuppLeft' _ _ _ _ _ lemma rTensor_apply_tmul (p : MvPolynomial σ S) (n : N) : rTensor (p ⊗ₜ[R] n) = p.sum (fun i m ↦ Finsupp.single i (m ⊗ₜ[R] n)) := TensorProduct.finsuppLeft_apply_tmul p n lemma rTensor_apply_tmul_apply (p : MvPolynomial σ S) (n : N) (d : σ →₀ ℕ) : rTensor (p ⊗ₜ[R] n) d = (coeff d p) ⊗ₜ[R] n := TensorProduct.finsuppLeft_apply_tmul_apply p n d lemma rTensor_apply_monomial_tmul (e : σ →₀ ℕ) (s : S) (n : N) (d : σ →₀ ℕ) : rTensor (monomial e s ⊗ₜ[R] n) d = if e = d then s ⊗ₜ[R] n else 0 := by simp only [rTensor_apply_tmul_apply, coeff_monomial, ite_tmul] lemma rTensor_apply_X_tmul (s : σ) (n : N) (d : σ →₀ ℕ) : rTensor (X s ⊗ₜ[R] n) d = if Finsupp.single s 1 = d then (1 : S) ⊗ₜ[R] n else 0 := by rw [rTensor_apply_tmul_apply, coeff_X', ite_tmul] lemma rTensor_apply (t : MvPolynomial σ S ⊗[R] N) (d : σ →₀ ℕ) : rTensor t d = ((lcoeff S d).restrictScalars R).rTensor N t := TensorProduct.finsuppLeft_apply t d @[simp] lemma rTensor_symm_apply_single (d : σ →₀ ℕ) (s : S) (n : N) : rTensor.symm (Finsupp.single d (s ⊗ₜ n)) = (monomial d s) ⊗ₜ[R] n := TensorProduct.finsuppLeft_symm_apply_single (R := R) d s n /-- The tensor product of the polynomial algebra by a module is linearly equivalent to a Finsupp of that module -/ noncomputable def scalarRTensor : MvPolynomial σ R ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ N := TensorProduct.finsuppScalarLeft _ _ _ lemma scalarRTensor_apply_tmul (p : MvPolynomial σ R) (n : N) : scalarRTensor (p ⊗ₜ[R] n) = p.sum (fun i m ↦ Finsupp.single i (m • n)) := TensorProduct.finsuppScalarLeft_apply_tmul p n lemma scalarRTensor_apply_tmul_apply (p : MvPolynomial σ R) (n : N) (d : σ →₀ ℕ) : scalarRTensor (p ⊗ₜ[R] n) d = coeff d p • n :=
TensorProduct.finsuppScalarLeft_apply_tmul_apply p n d lemma scalarRTensor_apply_monomial_tmul (e : σ →₀ ℕ) (r : R) (n : N) (d : σ →₀ ℕ) :
Mathlib/RingTheory/TensorProduct/MvPolynomial.lean
107
109
/- Copyright (c) 2019 Sébastien Gouëzel. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Sébastien Gouëzel -/ import Mathlib.Analysis.Analytic.Within import Mathlib.Analysis.Calculus.FDeriv.Analytic import Mathlib.Analysis.Calculus.ContDiff.FTaylorSeries /-! # Higher differentiability A function is `C^1` on a domain if it is differentiable there, and its derivative is continuous. By induction, it is `C^n` if it is `C^{n-1}` and its (n-1)-th derivative is `C^1` there or, equivalently, if it is `C^1` and its derivative is `C^{n-1}`. It is `C^∞` if it is `C^n` for all n. Finally, it is `C^ω` if it is analytic (as well as all its derivative, which is automatic if the space is complete). We formalize these notions with predicates `ContDiffWithinAt`, `ContDiffAt`, `ContDiffOn` and `ContDiff` saying that the function is `C^n` within a set at a point, at a point, on a set and on the whole space respectively. To avoid the issue of choice when choosing a derivative in sets where the derivative is not necessarily unique, `ContDiffOn` is not defined directly in terms of the regularity of the specific choice `iteratedFDerivWithin 𝕜 n f s` inside `s`, but in terms of the existence of a nice sequence of derivatives, expressed with a predicate `HasFTaylorSeriesUpToOn` defined in the file `FTaylorSeries`. We prove basic properties of these notions. ## Main definitions and results Let `f : E → F` be a map between normed vector spaces over a nontrivially normed field `𝕜`. * `ContDiff 𝕜 n f`: expresses that `f` is `C^n`, i.e., it admits a Taylor series up to rank `n`. * `ContDiffOn 𝕜 n f s`: expresses that `f` is `C^n` in `s`. * `ContDiffAt 𝕜 n f x`: expresses that `f` is `C^n` around `x`. * `ContDiffWithinAt 𝕜 n f s x`: expresses that `f` is `C^n` around `x` within the set `s`. In sets of unique differentiability, `ContDiffOn 𝕜 n f s` can be expressed in terms of the properties of `iteratedFDerivWithin 𝕜 m f s` for `m ≤ n`. In the whole space, `ContDiff 𝕜 n f` can be expressed in terms of the properties of `iteratedFDeriv 𝕜 m f` for `m ≤ n`. ## Implementation notes The definitions in this file are designed to work on any field `𝕜`. They are sometimes slightly more complicated than the naive definitions one would guess from the intuition over the real or complex numbers, but they are designed to circumvent the lack of gluing properties and partitions of unity in general. In the usual situations, they coincide with the usual definitions. ### Definition of `C^n` functions in domains One could define `C^n` functions in a domain `s` by fixing an arbitrary choice of derivatives (this is what we do with `iteratedFDerivWithin`) and requiring that all these derivatives up to `n` are continuous. If the derivative is not unique, this could lead to strange behavior like two `C^n` functions `f` and `g` on `s` whose sum is not `C^n`. A better definition is thus to say that a function is `C^n` inside `s` if it admits a sequence of derivatives up to `n` inside `s`. This definition still has the problem that a function which is locally `C^n` would not need to be `C^n`, as different choices of sequences of derivatives around different points might possibly not be glued together to give a globally defined sequence of derivatives. (Note that this issue can not happen over reals, thanks to partition of unity, but the behavior over a general field is not so clear, and we want a definition for general fields). Also, there are locality problems for the order parameter: one could image a function which, for each `n`, has a nice sequence of derivatives up to order `n`, but they do not coincide for varying `n` and can therefore not be glued to give rise to an infinite sequence of derivatives. This would give a function which is `C^n` for all `n`, but not `C^∞`. We solve this issue by putting locality conditions in space and order in our definition of `ContDiffWithinAt` and `ContDiffOn`. The resulting definition is slightly more complicated to work with (in fact not so much), but it gives rise to completely satisfactory theorems. For instance, with this definition, a real function which is `C^m` (but not better) on `(-1/m, 1/m)` for each natural `m` is by definition `C^∞` at `0`. There is another issue with the definition of `ContDiffWithinAt 𝕜 n f s x`. We can require the existence and good behavior of derivatives up to order `n` on a neighborhood of `x` within `s`. However, this does not imply continuity or differentiability within `s` of the function at `x` when `x` does not belong to `s`. Therefore, we require such existence and good behavior on a neighborhood of `x` within `s ∪ {x}` (which appears as `insert x s` in this file). ## Notations We use the notation `E [×n]→L[𝕜] F` for the space of continuous multilinear maps on `E^n` with values in `F`. This is the space in which the `n`-th derivative of a function from `E` to `F` lives. In this file, we denote `(⊤ : ℕ∞) : WithTop ℕ∞` with `∞`, and `⊤ : WithTop ℕ∞` with `ω`. To avoid ambiguities with the two tops, the theorems name use either `infty` or `omega`. These notations are scoped in `ContDiff`. ## Tags derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series -/ noncomputable section open Set Fin Filter Function open scoped NNReal Topology ContDiff universe u uE uF uG uX variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type uE} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type uF} [NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG} [NormedAddCommGroup G] [NormedSpace 𝕜 G] {X : Type uX} [NormedAddCommGroup X] [NormedSpace 𝕜 X] {s s₁ t u : Set E} {f f₁ : E → F} {g : F → G} {x x₀ : E} {c : F} {m n : WithTop ℕ∞} {p : E → FormalMultilinearSeries 𝕜 E F} /-! ### Smooth functions within a set around a point -/ variable (𝕜) in /-- A function is continuously differentiable up to order `n` within a set `s` at a point `x` if it admits continuous derivatives up to order `n` in a neighborhood of `x` in `s ∪ {x}`. For `n = ∞`, we only require that this holds up to any finite order (where the neighborhood may depend on the finite order we consider). For `n = ω`, we require the function to be analytic within `s` at `x`. The precise definition we give (all the derivatives should be analytic) is more involved to work around issues when the space is not complete, but it is equivalent when the space is complete. For instance, a real function which is `C^m` on `(-1/m, 1/m)` for each natural `m`, but not better, is `C^∞` at `0` within `univ`. -/ def ContDiffWithinAt (n : WithTop ℕ∞) (f : E → F) (s : Set E) (x : E) : Prop := match n with | ω => ∃ u ∈ 𝓝[insert x s] x, ∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn ω f p u ∧ ∀ i, AnalyticOn 𝕜 (fun x ↦ p x i) u | (n : ℕ∞) => ∀ m : ℕ, m ≤ n → ∃ u ∈ 𝓝[insert x s] x, ∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn m f p u lemma HasFTaylorSeriesUpToOn.analyticOn (hf : HasFTaylorSeriesUpToOn ω f p s) (h : AnalyticOn 𝕜 (fun x ↦ p x 0) s) : AnalyticOn 𝕜 f s := by have : AnalyticOn 𝕜 (fun x ↦ (continuousMultilinearCurryFin0 𝕜 E F) (p x 0)) s := (LinearIsometryEquiv.analyticOnNhd _ _ ).comp_analyticOn h (Set.mapsTo_univ _ _) exact this.congr (fun y hy ↦ (hf.zero_eq _ hy).symm) lemma ContDiffWithinAt.analyticOn (h : ContDiffWithinAt 𝕜 ω f s x) : ∃ u ∈ 𝓝[insert x s] x, AnalyticOn 𝕜 f u := by obtain ⟨u, hu, p, hp, h'p⟩ := h exact ⟨u, hu, hp.analyticOn (h'p 0)⟩ lemma ContDiffWithinAt.analyticWithinAt (h : ContDiffWithinAt 𝕜 ω f s x) : AnalyticWithinAt 𝕜 f s x := by obtain ⟨u, hu, hf⟩ := h.analyticOn have xu : x ∈ u := mem_of_mem_nhdsWithin (by simp) hu exact (hf x xu).mono_of_mem_nhdsWithin (nhdsWithin_mono _ (subset_insert _ _) hu) theorem contDiffWithinAt_omega_iff_analyticWithinAt [CompleteSpace F] : ContDiffWithinAt 𝕜 ω f s x ↔ AnalyticWithinAt 𝕜 f s x := by refine ⟨fun h ↦ h.analyticWithinAt, fun h ↦ ?_⟩ obtain ⟨u, hu, p, hp, h'p⟩ := h.exists_hasFTaylorSeriesUpToOn ω exact ⟨u, hu, p, hp.of_le le_top, fun i ↦ h'p i⟩ theorem contDiffWithinAt_nat {n : ℕ} : ContDiffWithinAt 𝕜 n f s x ↔ ∃ u ∈ 𝓝[insert x s] x, ∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn n f p u := ⟨fun H => H n le_rfl, fun ⟨u, hu, p, hp⟩ _m hm => ⟨u, hu, p, hp.of_le (mod_cast hm)⟩⟩ /-- When `n` is either a natural number or `ω`, one can characterize the property of being `C^n` as the existence of a neighborhood on which there is a Taylor series up to order `n`, requiring in addition that its terms are analytic in the `ω` case. -/ lemma contDiffWithinAt_iff_of_ne_infty (hn : n ≠ ∞) : ContDiffWithinAt 𝕜 n f s x ↔ ∃ u ∈ 𝓝[insert x s] x, ∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn n f p u ∧ (n = ω → ∀ i, AnalyticOn 𝕜 (fun x ↦ p x i) u) := by match n with | ω => simp [ContDiffWithinAt] | ∞ => simp at hn | (n : ℕ) => simp [contDiffWithinAt_nat] theorem ContDiffWithinAt.of_le (h : ContDiffWithinAt 𝕜 n f s x) (hmn : m ≤ n) : ContDiffWithinAt 𝕜 m f s x := by match n with | ω => match m with | ω => exact h | (m : ℕ∞) => intro k _ obtain ⟨u, hu, p, hp, -⟩ := h exact ⟨u, hu, p, hp.of_le le_top⟩ | (n : ℕ∞) => match m with | ω => simp at hmn | (m : ℕ∞) => exact fun k hk ↦ h k (le_trans hk (mod_cast hmn)) /-- In a complete space, a function which is analytic within a set at a point is also `C^ω` there. Note that the same statement for `AnalyticOn` does not require completeness, see `AnalyticOn.contDiffOn`. -/ theorem AnalyticWithinAt.contDiffWithinAt [CompleteSpace F] (h : AnalyticWithinAt 𝕜 f s x) : ContDiffWithinAt 𝕜 n f s x := (contDiffWithinAt_omega_iff_analyticWithinAt.2 h).of_le le_top theorem contDiffWithinAt_iff_forall_nat_le {n : ℕ∞} : ContDiffWithinAt 𝕜 n f s x ↔ ∀ m : ℕ, ↑m ≤ n → ContDiffWithinAt 𝕜 m f s x := ⟨fun H _ hm => H.of_le (mod_cast hm), fun H m hm => H m hm _ le_rfl⟩ theorem contDiffWithinAt_infty : ContDiffWithinAt 𝕜 ∞ f s x ↔ ∀ n : ℕ, ContDiffWithinAt 𝕜 n f s x := contDiffWithinAt_iff_forall_nat_le.trans <| by simp only [forall_prop_of_true, le_top] @[deprecated (since := "2024-11-25")] alias contDiffWithinAt_top := contDiffWithinAt_infty theorem ContDiffWithinAt.continuousWithinAt (h : ContDiffWithinAt 𝕜 n f s x) : ContinuousWithinAt f s x := by have := h.of_le (zero_le _) simp only [ContDiffWithinAt, nonpos_iff_eq_zero, Nat.cast_eq_zero, mem_pure, forall_eq, CharP.cast_eq_zero] at this rcases this with ⟨u, hu, p, H⟩ rw [mem_nhdsWithin_insert] at hu exact (H.continuousOn.continuousWithinAt hu.1).mono_of_mem_nhdsWithin hu.2 theorem ContDiffWithinAt.congr_of_eventuallyEq (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x := by match n with | ω => obtain ⟨u, hu, p, H, H'⟩ := h exact ⟨{x ∈ u | f₁ x = f x}, Filter.inter_mem hu (mem_nhdsWithin_insert.2 ⟨hx, h₁⟩), p, (H.mono (sep_subset _ _)).congr fun _ ↦ And.right, fun i ↦ (H' i).mono (sep_subset _ _)⟩ | (n : ℕ∞) => intro m hm let ⟨u, hu, p, H⟩ := h m hm exact ⟨{ x ∈ u | f₁ x = f x }, Filter.inter_mem hu (mem_nhdsWithin_insert.2 ⟨hx, h₁⟩), p, (H.mono (sep_subset _ _)).congr fun _ ↦ And.right⟩ theorem Filter.EventuallyEq.congr_contDiffWithinAt (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x := ⟨fun H ↦ H.congr_of_eventuallyEq h₁.symm hx.symm, fun H ↦ H.congr_of_eventuallyEq h₁ hx⟩ theorem ContDiffWithinAt.congr_of_eventuallyEq_insert (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : f₁ =ᶠ[𝓝[insert x s] x] f) : ContDiffWithinAt 𝕜 n f₁ s x := h.congr_of_eventuallyEq (nhdsWithin_mono x (subset_insert x s) h₁) (mem_of_mem_nhdsWithin (mem_insert x s) h₁ :) theorem Filter.EventuallyEq.congr_contDiffWithinAt_of_insert (h₁ : f₁ =ᶠ[𝓝[insert x s] x] f) : ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x := ⟨fun H ↦ H.congr_of_eventuallyEq_insert h₁.symm, fun H ↦ H.congr_of_eventuallyEq_insert h₁⟩ theorem ContDiffWithinAt.congr_of_eventuallyEq_of_mem (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x := h.congr_of_eventuallyEq h₁ <| h₁.self_of_nhdsWithin hx theorem Filter.EventuallyEq.congr_contDiffWithinAt_of_mem (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : x ∈ s): ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x := ⟨fun H ↦ H.congr_of_eventuallyEq_of_mem h₁.symm hx, fun H ↦ H.congr_of_eventuallyEq_of_mem h₁ hx⟩ theorem ContDiffWithinAt.congr (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ s, f₁ y = f y) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x := h.congr_of_eventuallyEq (Filter.eventuallyEq_of_mem self_mem_nhdsWithin h₁) hx theorem contDiffWithinAt_congr (h₁ : ∀ y ∈ s, f₁ y = f y) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x := ⟨fun h' ↦ h'.congr (fun x hx ↦ (h₁ x hx).symm) hx.symm, fun h' ↦ h'.congr h₁ hx⟩ theorem ContDiffWithinAt.congr_of_mem (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ s, f₁ y = f y) (hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x := h.congr h₁ (h₁ _ hx) theorem contDiffWithinAt_congr_of_mem (h₁ : ∀ y ∈ s, f₁ y = f y) (hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x := contDiffWithinAt_congr h₁ (h₁ x hx) theorem ContDiffWithinAt.congr_of_insert (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ insert x s, f₁ y = f y) : ContDiffWithinAt 𝕜 n f₁ s x := h.congr (fun y hy ↦ h₁ y (mem_insert_of_mem _ hy)) (h₁ x (mem_insert _ _)) theorem contDiffWithinAt_congr_of_insert (h₁ : ∀ y ∈ insert x s, f₁ y = f y) : ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x := contDiffWithinAt_congr (fun y hy ↦ h₁ y (mem_insert_of_mem _ hy)) (h₁ x (mem_insert _ _)) theorem ContDiffWithinAt.mono_of_mem_nhdsWithin (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E} (hst : s ∈ 𝓝[t] x) : ContDiffWithinAt 𝕜 n f t x := by match n with | ω => obtain ⟨u, hu, p, H, H'⟩ := h exact ⟨u, nhdsWithin_le_of_mem (insert_mem_nhdsWithin_insert hst) hu, p, H, H'⟩ | (n : ℕ∞) => intro m hm rcases h m hm with ⟨u, hu, p, H⟩ exact ⟨u, nhdsWithin_le_of_mem (insert_mem_nhdsWithin_insert hst) hu, p, H⟩ @[deprecated (since := "2024-10-30")] alias ContDiffWithinAt.mono_of_mem := ContDiffWithinAt.mono_of_mem_nhdsWithin theorem ContDiffWithinAt.mono (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E} (hst : t ⊆ s) : ContDiffWithinAt 𝕜 n f t x := h.mono_of_mem_nhdsWithin <| Filter.mem_of_superset self_mem_nhdsWithin hst theorem ContDiffWithinAt.congr_mono (h : ContDiffWithinAt 𝕜 n f s x) (h' : EqOn f₁ f s₁) (h₁ : s₁ ⊆ s) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s₁ x := (h.mono h₁).congr h' hx theorem ContDiffWithinAt.congr_set (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E} (hst : s =ᶠ[𝓝 x] t) : ContDiffWithinAt 𝕜 n f t x := by rw [← nhdsWithin_eq_iff_eventuallyEq] at hst apply h.mono_of_mem_nhdsWithin <| hst ▸ self_mem_nhdsWithin @[deprecated (since := "2024-10-23")] alias ContDiffWithinAt.congr_nhds := ContDiffWithinAt.congr_set theorem contDiffWithinAt_congr_set {t : Set E} (hst : s =ᶠ[𝓝 x] t) : ContDiffWithinAt 𝕜 n f s x ↔ ContDiffWithinAt 𝕜 n f t x := ⟨fun h => h.congr_set hst, fun h => h.congr_set hst.symm⟩ @[deprecated (since := "2024-10-23")] alias contDiffWithinAt_congr_nhds := contDiffWithinAt_congr_set theorem contDiffWithinAt_inter' (h : t ∈ 𝓝[s] x) : ContDiffWithinAt 𝕜 n f (s ∩ t) x ↔ ContDiffWithinAt 𝕜 n f s x := contDiffWithinAt_congr_set (mem_nhdsWithin_iff_eventuallyEq.1 h).symm theorem contDiffWithinAt_inter (h : t ∈ 𝓝 x) : ContDiffWithinAt 𝕜 n f (s ∩ t) x ↔ ContDiffWithinAt 𝕜 n f s x := contDiffWithinAt_inter' (mem_nhdsWithin_of_mem_nhds h) theorem contDiffWithinAt_insert_self : ContDiffWithinAt 𝕜 n f (insert x s) x ↔ ContDiffWithinAt 𝕜 n f s x := by match n with | ω => simp [ContDiffWithinAt] | (n : ℕ∞) => simp_rw [ContDiffWithinAt, insert_idem] theorem contDiffWithinAt_insert {y : E} : ContDiffWithinAt 𝕜 n f (insert y s) x ↔ ContDiffWithinAt 𝕜 n f s x := by rcases eq_or_ne x y with (rfl | hx) · exact contDiffWithinAt_insert_self refine ⟨fun h ↦ h.mono (subset_insert _ _), fun h ↦ ?_⟩ apply h.mono_of_mem_nhdsWithin simp [nhdsWithin_insert_of_ne hx, self_mem_nhdsWithin] alias ⟨ContDiffWithinAt.of_insert, ContDiffWithinAt.insert'⟩ := contDiffWithinAt_insert protected theorem ContDiffWithinAt.insert (h : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n f (insert x s) x := h.insert' theorem contDiffWithinAt_diff_singleton {y : E} : ContDiffWithinAt 𝕜 n f (s \ {y}) x ↔ ContDiffWithinAt 𝕜 n f s x := by rw [← contDiffWithinAt_insert, insert_diff_singleton, contDiffWithinAt_insert] /-- If a function is `C^n` within a set at a point, with `n ≥ 1`, then it is differentiable within this set at this point. -/ theorem ContDiffWithinAt.differentiableWithinAt' (h : ContDiffWithinAt 𝕜 n f s x) (hn : 1 ≤ n) : DifferentiableWithinAt 𝕜 f (insert x s) x := by rcases contDiffWithinAt_nat.1 (h.of_le hn) with ⟨u, hu, p, H⟩ rcases mem_nhdsWithin.1 hu with ⟨t, t_open, xt, tu⟩ rw [inter_comm] at tu exact (differentiableWithinAt_inter (IsOpen.mem_nhds t_open xt)).1 <| ((H.mono tu).differentiableOn le_rfl) x ⟨mem_insert x s, xt⟩ theorem ContDiffWithinAt.differentiableWithinAt (h : ContDiffWithinAt 𝕜 n f s x) (hn : 1 ≤ n) : DifferentiableWithinAt 𝕜 f s x := (h.differentiableWithinAt' hn).mono (subset_insert x s) /-- A function is `C^(n + 1)` on a domain iff locally, it has a derivative which is `C^n` (and moreover the function is analytic when `n = ω`). -/ theorem contDiffWithinAt_succ_iff_hasFDerivWithinAt (hn : n ≠ ∞) : ContDiffWithinAt 𝕜 (n + 1) f s x ↔ ∃ u ∈ 𝓝[insert x s] x, (n = ω → AnalyticOn 𝕜 f u) ∧ ∃ f' : E → E →L[𝕜] F, (∀ x ∈ u, HasFDerivWithinAt f (f' x) u x) ∧ ContDiffWithinAt 𝕜 n f' u x := by have h'n : n + 1 ≠ ∞ := by simpa using hn constructor · intro h rcases (contDiffWithinAt_iff_of_ne_infty h'n).1 h with ⟨u, hu, p, Hp, H'p⟩ refine ⟨u, hu, ?_, fun y => (continuousMultilinearCurryFin1 𝕜 E F) (p y 1), fun y hy => Hp.hasFDerivWithinAt le_add_self hy, ?_⟩ · rintro rfl exact Hp.analyticOn (H'p rfl 0) apply (contDiffWithinAt_iff_of_ne_infty hn).2 refine ⟨u, ?_, fun y : E => (p y).shift, ?_⟩ · convert @self_mem_nhdsWithin _ _ x u have : x ∈ insert x s := by simp exact insert_eq_of_mem (mem_of_mem_nhdsWithin this hu) · rw [hasFTaylorSeriesUpToOn_succ_iff_right] at Hp refine ⟨Hp.2.2, ?_⟩ rintro rfl i change AnalyticOn 𝕜 (fun x ↦ (continuousMultilinearCurryRightEquiv' 𝕜 i E F) (p x (i + 1))) u apply (LinearIsometryEquiv.analyticOnNhd _ _).comp_analyticOn ?_ (Set.mapsTo_univ _ _) exact H'p rfl _ · rintro ⟨u, hu, hf, f', f'_eq_deriv, Hf'⟩ rw [contDiffWithinAt_iff_of_ne_infty h'n] rcases (contDiffWithinAt_iff_of_ne_infty hn).1 Hf' with ⟨v, hv, p', Hp', p'_an⟩ refine ⟨v ∩ u, ?_, fun x => (p' x).unshift (f x), ?_, ?_⟩ · apply Filter.inter_mem _ hu apply nhdsWithin_le_of_mem hu exact nhdsWithin_mono _ (subset_insert x u) hv · rw [hasFTaylorSeriesUpToOn_succ_iff_right] refine ⟨fun y _ => rfl, fun y hy => ?_, ?_⟩ · change HasFDerivWithinAt (fun z => (continuousMultilinearCurryFin0 𝕜 E F).symm (f z)) (FormalMultilinearSeries.unshift (p' y) (f y) 1).curryLeft (v ∩ u) y rw [← Function.comp_def _ f, LinearIsometryEquiv.comp_hasFDerivWithinAt_iff'] convert (f'_eq_deriv y hy.2).mono inter_subset_right rw [← Hp'.zero_eq y hy.1] ext z change ((p' y 0) (init (@cons 0 (fun _ => E) z 0))) (@cons 0 (fun _ => E) z 0 (last 0)) = ((p' y 0) 0) z congr norm_num [eq_iff_true_of_subsingleton] · convert (Hp'.mono inter_subset_left).congr fun x hx => Hp'.zero_eq x hx.1 using 1 · ext x y change p' x 0 (init (@snoc 0 (fun _ : Fin 1 => E) 0 y)) y = p' x 0 0 y rw [init_snoc] · ext x k v y change p' x k (init (@snoc k (fun _ : Fin k.succ => E) v y)) (@snoc k (fun _ : Fin k.succ => E) v y (last k)) = p' x k v y rw [snoc_last, init_snoc] · intro h i simp only [WithTop.add_eq_top, WithTop.one_ne_top, or_false] at h match i with | 0 => simp only [FormalMultilinearSeries.unshift] apply AnalyticOnNhd.comp_analyticOn _ ((hf h).mono inter_subset_right) (Set.mapsTo_univ _ _) exact LinearIsometryEquiv.analyticOnNhd _ _ | i + 1 => simp only [FormalMultilinearSeries.unshift, Nat.succ_eq_add_one] apply AnalyticOnNhd.comp_analyticOn _ ((p'_an h i).mono inter_subset_left) (Set.mapsTo_univ _ _) exact LinearIsometryEquiv.analyticOnNhd _ _ /-- A version of `contDiffWithinAt_succ_iff_hasFDerivWithinAt` where all derivatives are taken within the same set. -/ theorem contDiffWithinAt_succ_iff_hasFDerivWithinAt' (hn : n ≠ ∞) : ContDiffWithinAt 𝕜 (n + 1) f s x ↔ ∃ u ∈ 𝓝[insert x s] x, u ⊆ insert x s ∧ (n = ω → AnalyticOn 𝕜 f u) ∧ ∃ f' : E → E →L[𝕜] F, (∀ x ∈ u, HasFDerivWithinAt f (f' x) s x) ∧ ContDiffWithinAt 𝕜 n f' s x := by refine ⟨fun hf => ?_, ?_⟩ · obtain ⟨u, hu, f_an, f', huf', hf'⟩ := (contDiffWithinAt_succ_iff_hasFDerivWithinAt hn).mp hf obtain ⟨w, hw, hxw, hwu⟩ := mem_nhdsWithin.mp hu rw [inter_comm] at hwu refine ⟨insert x s ∩ w, inter_mem_nhdsWithin _ (hw.mem_nhds hxw), inter_subset_left, ?_, f', fun y hy => ?_, ?_⟩ · intro h apply (f_an h).mono hwu · refine ((huf' y <| hwu hy).mono hwu).mono_of_mem_nhdsWithin ?_ refine mem_of_superset ?_ (inter_subset_inter_left _ (subset_insert _ _)) exact inter_mem_nhdsWithin _ (hw.mem_nhds hy.2) · exact hf'.mono_of_mem_nhdsWithin (nhdsWithin_mono _ (subset_insert _ _) hu) · rw [← contDiffWithinAt_insert, contDiffWithinAt_succ_iff_hasFDerivWithinAt hn, insert_eq_of_mem (mem_insert _ _)] rintro ⟨u, hu, hus, f_an, f', huf', hf'⟩ exact ⟨u, hu, f_an, f', fun y hy => (huf' y hy).insert'.mono hus, hf'.insert.mono hus⟩ /-! ### Smooth functions within a set -/ variable (𝕜) in /-- A function is continuously differentiable up to `n` on `s` if, for any point `x` in `s`, it admits continuous derivatives up to order `n` on a neighborhood of `x` in `s`. For `n = ∞`, we only require that this holds up to any finite order (where the neighborhood may depend on the finite order we consider). -/ def ContDiffOn (n : WithTop ℕ∞) (f : E → F) (s : Set E) : Prop := ∀ x ∈ s, ContDiffWithinAt 𝕜 n f s x theorem HasFTaylorSeriesUpToOn.contDiffOn {n : ℕ∞} {f' : E → FormalMultilinearSeries 𝕜 E F} (hf : HasFTaylorSeriesUpToOn n f f' s) : ContDiffOn 𝕜 n f s := by intro x hx m hm use s simp only [Set.insert_eq_of_mem hx, self_mem_nhdsWithin, true_and] exact ⟨f', hf.of_le (mod_cast hm)⟩ theorem ContDiffOn.contDiffWithinAt (h : ContDiffOn 𝕜 n f s) (hx : x ∈ s) : ContDiffWithinAt 𝕜 n f s x := h x hx theorem ContDiffOn.of_le (h : ContDiffOn 𝕜 n f s) (hmn : m ≤ n) : ContDiffOn 𝕜 m f s := fun x hx => (h x hx).of_le hmn theorem ContDiffWithinAt.contDiffOn' (hm : m ≤ n) (h' : m = ∞ → n = ω) (h : ContDiffWithinAt 𝕜 n f s x) : ∃ u, IsOpen u ∧ x ∈ u ∧ ContDiffOn 𝕜 m f (insert x s ∩ u) := by rcases eq_or_ne n ω with rfl | hn · obtain ⟨t, ht, p, hp, h'p⟩ := h rcases mem_nhdsWithin.1 ht with ⟨u, huo, hxu, hut⟩ rw [inter_comm] at hut refine ⟨u, huo, hxu, ?_⟩ suffices ContDiffOn 𝕜 ω f (insert x s ∩ u) from this.of_le le_top intro y hy refine ⟨insert x s ∩ u, ?_, p, hp.mono hut, fun i ↦ (h'p i).mono hut⟩ simp only [insert_eq_of_mem, hy, self_mem_nhdsWithin] · match m with | ω => simp [hn] at hm | ∞ => exact (hn (h' rfl)).elim | (m : ℕ) => rcases contDiffWithinAt_nat.1 (h.of_le hm) with ⟨t, ht, p, hp⟩ rcases mem_nhdsWithin.1 ht with ⟨u, huo, hxu, hut⟩ rw [inter_comm] at hut exact ⟨u, huo, hxu, (hp.mono hut).contDiffOn⟩ theorem ContDiffWithinAt.contDiffOn (hm : m ≤ n) (h' : m = ∞ → n = ω) (h : ContDiffWithinAt 𝕜 n f s x) : ∃ u ∈ 𝓝[insert x s] x, u ⊆ insert x s ∧ ContDiffOn 𝕜 m f u := by obtain ⟨_u, uo, xu, h⟩ := h.contDiffOn' hm h' exact ⟨_, inter_mem_nhdsWithin _ (uo.mem_nhds xu), inter_subset_left, h⟩ theorem ContDiffOn.analyticOn (h : ContDiffOn 𝕜 ω f s) : AnalyticOn 𝕜 f s := fun x hx ↦ (h x hx).analyticWithinAt /-- A function is `C^n` within a set at a point, for `n : ℕ`, if and only if it is `C^n` on a neighborhood of this point. -/ theorem contDiffWithinAt_iff_contDiffOn_nhds (hn : n ≠ ∞) : ContDiffWithinAt 𝕜 n f s x ↔ ∃ u ∈ 𝓝[insert x s] x, ContDiffOn 𝕜 n f u := by refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩ · rcases h.contDiffOn le_rfl (by simp [hn]) with ⟨u, hu, h'u⟩ exact ⟨u, hu, h'u.2⟩ · rcases h with ⟨u, u_mem, hu⟩ have : x ∈ u := mem_of_mem_nhdsWithin (mem_insert x s) u_mem exact (hu x this).mono_of_mem_nhdsWithin (nhdsWithin_mono _ (subset_insert x s) u_mem) protected theorem ContDiffWithinAt.eventually (h : ContDiffWithinAt 𝕜 n f s x) (hn : n ≠ ∞) : ∀ᶠ y in 𝓝[insert x s] x, ContDiffWithinAt 𝕜 n f s y := by rcases h.contDiffOn le_rfl (by simp [hn]) with ⟨u, hu, _, hd⟩ have : ∀ᶠ y : E in 𝓝[insert x s] x, u ∈ 𝓝[insert x s] y ∧ y ∈ u := (eventually_eventually_nhdsWithin.2 hu).and hu refine this.mono fun y hy => (hd y hy.2).mono_of_mem_nhdsWithin ?_ exact nhdsWithin_mono y (subset_insert _ _) hy.1 theorem ContDiffOn.of_succ (h : ContDiffOn 𝕜 (n + 1) f s) : ContDiffOn 𝕜 n f s := h.of_le le_self_add theorem ContDiffOn.one_of_succ (h : ContDiffOn 𝕜 (n + 1) f s) : ContDiffOn 𝕜 1 f s := h.of_le le_add_self theorem contDiffOn_iff_forall_nat_le {n : ℕ∞} : ContDiffOn 𝕜 n f s ↔ ∀ m : ℕ, ↑m ≤ n → ContDiffOn 𝕜 m f s := ⟨fun H _ hm => H.of_le (mod_cast hm), fun H x hx m hm => H m hm x hx m le_rfl⟩ theorem contDiffOn_infty : ContDiffOn 𝕜 ∞ f s ↔ ∀ n : ℕ, ContDiffOn 𝕜 n f s := contDiffOn_iff_forall_nat_le.trans <| by simp only [le_top, forall_prop_of_true] @[deprecated (since := "2024-11-27")] alias contDiffOn_top := contDiffOn_infty @[deprecated (since := "2024-11-27")] alias contDiffOn_infty_iff_contDiffOn_omega := contDiffOn_infty theorem contDiffOn_all_iff_nat : (∀ (n : ℕ∞), ContDiffOn 𝕜 n f s) ↔ ∀ n : ℕ, ContDiffOn 𝕜 n f s := by refine ⟨fun H n => H n, ?_⟩ rintro H (_ | n) exacts [contDiffOn_infty.2 H, H n] theorem ContDiffOn.continuousOn (h : ContDiffOn 𝕜 n f s) : ContinuousOn f s := fun x hx => (h x hx).continuousWithinAt theorem ContDiffOn.congr (h : ContDiffOn 𝕜 n f s) (h₁ : ∀ x ∈ s, f₁ x = f x) : ContDiffOn 𝕜 n f₁ s := fun x hx => (h x hx).congr h₁ (h₁ x hx) theorem contDiffOn_congr (h₁ : ∀ x ∈ s, f₁ x = f x) : ContDiffOn 𝕜 n f₁ s ↔ ContDiffOn 𝕜 n f s := ⟨fun H => H.congr fun x hx => (h₁ x hx).symm, fun H => H.congr h₁⟩ theorem ContDiffOn.mono (h : ContDiffOn 𝕜 n f s) {t : Set E} (hst : t ⊆ s) : ContDiffOn 𝕜 n f t := fun x hx => (h x (hst hx)).mono hst theorem ContDiffOn.congr_mono (hf : ContDiffOn 𝕜 n f s) (h₁ : ∀ x ∈ s₁, f₁ x = f x) (hs : s₁ ⊆ s) : ContDiffOn 𝕜 n f₁ s₁ := (hf.mono hs).congr h₁ /-- If a function is `C^n` on a set with `n ≥ 1`, then it is differentiable there. -/ theorem ContDiffOn.differentiableOn (h : ContDiffOn 𝕜 n f s) (hn : 1 ≤ n) : DifferentiableOn 𝕜 f s := fun x hx => (h x hx).differentiableWithinAt hn /-- If a function is `C^n` around each point in a set, then it is `C^n` on the set. -/ theorem contDiffOn_of_locally_contDiffOn (h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ ContDiffOn 𝕜 n f (s ∩ u)) : ContDiffOn 𝕜 n f s := by intro x xs rcases h x xs with ⟨u, u_open, xu, hu⟩ apply (contDiffWithinAt_inter _).1 (hu x ⟨xs, xu⟩) exact IsOpen.mem_nhds u_open xu /-- A function is `C^(n + 1)` on a domain iff locally, it has a derivative which is `C^n`. -/ theorem contDiffOn_succ_iff_hasFDerivWithinAt (hn : n ≠ ∞) : ContDiffOn 𝕜 (n + 1) f s ↔ ∀ x ∈ s, ∃ u ∈ 𝓝[insert x s] x, (n = ω → AnalyticOn 𝕜 f u) ∧ ∃ f' : E → E →L[𝕜] F, (∀ x ∈ u, HasFDerivWithinAt f (f' x) u x) ∧ ContDiffOn 𝕜 n f' u := by constructor · intro h x hx rcases (contDiffWithinAt_succ_iff_hasFDerivWithinAt hn).1 (h x hx) with ⟨u, hu, f_an, f', hf', Hf'⟩ rcases Hf'.contDiffOn le_rfl (by simp [hn]) with ⟨v, vu, v'u, hv⟩ rw [insert_eq_of_mem hx] at hu ⊢ have xu : x ∈ u := mem_of_mem_nhdsWithin hx hu rw [insert_eq_of_mem xu] at vu v'u exact ⟨v, nhdsWithin_le_of_mem hu vu, fun h ↦ (f_an h).mono v'u, f', fun y hy ↦ (hf' y (v'u hy)).mono v'u, hv⟩ · intro h x hx rw [contDiffWithinAt_succ_iff_hasFDerivWithinAt hn] rcases h x hx with ⟨u, u_nhbd, f_an, f', hu, hf'⟩ have : x ∈ u := mem_of_mem_nhdsWithin (mem_insert _ _) u_nhbd exact ⟨u, u_nhbd, f_an, f', hu, hf' x this⟩ /-! ### Iterated derivative within a set -/ @[simp] theorem contDiffOn_zero : ContDiffOn 𝕜 0 f s ↔ ContinuousOn f s := by refine ⟨fun H => H.continuousOn, fun H => fun x hx m hm ↦ ?_⟩ have : (m : WithTop ℕ∞) = 0 := le_antisymm (mod_cast hm) bot_le rw [this] refine ⟨insert x s, self_mem_nhdsWithin, ftaylorSeriesWithin 𝕜 f s, ?_⟩ rw [hasFTaylorSeriesUpToOn_zero_iff] exact ⟨by rwa [insert_eq_of_mem hx], fun x _ => by simp [ftaylorSeriesWithin]⟩ theorem contDiffWithinAt_zero (hx : x ∈ s) : ContDiffWithinAt 𝕜 0 f s x ↔ ∃ u ∈ 𝓝[s] x, ContinuousOn f (s ∩ u) := by constructor · intro h obtain ⟨u, H, p, hp⟩ := h 0 le_rfl refine ⟨u, ?_, ?_⟩ · simpa [hx] using H · simp only [Nat.cast_zero, hasFTaylorSeriesUpToOn_zero_iff] at hp exact hp.1.mono inter_subset_right · rintro ⟨u, H, hu⟩ rw [← contDiffWithinAt_inter' H] have h' : x ∈ s ∩ u := ⟨hx, mem_of_mem_nhdsWithin hx H⟩ exact (contDiffOn_zero.mpr hu).contDiffWithinAt h' /-- When a function is `C^n` in a set `s` of unique differentiability, it admits `ftaylorSeriesWithin 𝕜 f s` as a Taylor series up to order `n` in `s`. -/ protected theorem ContDiffOn.ftaylorSeriesWithin (h : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) : HasFTaylorSeriesUpToOn n f (ftaylorSeriesWithin 𝕜 f s) s := by constructor · intro x _ simp only [ftaylorSeriesWithin, ContinuousMultilinearMap.curry0_apply, iteratedFDerivWithin_zero_apply] · intro m hm x hx have : (m + 1 : ℕ) ≤ n := ENat.add_one_natCast_le_withTop_of_lt hm rcases (h x hx).of_le this _ le_rfl with ⟨u, hu, p, Hp⟩ rw [insert_eq_of_mem hx] at hu rcases mem_nhdsWithin.1 hu with ⟨o, o_open, xo, ho⟩ rw [inter_comm] at ho have : p x m.succ = ftaylorSeriesWithin 𝕜 f s x m.succ := by change p x m.succ = iteratedFDerivWithin 𝕜 m.succ f s x rw [← iteratedFDerivWithin_inter_open o_open xo] exact (Hp.mono ho).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl (hs.inter o_open) ⟨hx, xo⟩ rw [← this, ← hasFDerivWithinAt_inter (IsOpen.mem_nhds o_open xo)] have A : ∀ y ∈ s ∩ o, p y m = ftaylorSeriesWithin 𝕜 f s y m := by rintro y ⟨hy, yo⟩ change p y m = iteratedFDerivWithin 𝕜 m f s y rw [← iteratedFDerivWithin_inter_open o_open yo] exact (Hp.mono ho).eq_iteratedFDerivWithin_of_uniqueDiffOn (mod_cast Nat.le_succ m) (hs.inter o_open) ⟨hy, yo⟩ exact ((Hp.mono ho).fderivWithin m (mod_cast lt_add_one m) x ⟨hx, xo⟩).congr (fun y hy => (A y hy).symm) (A x ⟨hx, xo⟩).symm · intro m hm apply continuousOn_of_locally_continuousOn intro x hx rcases (h x hx).of_le hm _ le_rfl with ⟨u, hu, p, Hp⟩ rcases mem_nhdsWithin.1 hu with ⟨o, o_open, xo, ho⟩ rw [insert_eq_of_mem hx] at ho rw [inter_comm] at ho refine ⟨o, o_open, xo, ?_⟩ have A : ∀ y ∈ s ∩ o, p y m = ftaylorSeriesWithin 𝕜 f s y m := by rintro y ⟨hy, yo⟩ change p y m = iteratedFDerivWithin 𝕜 m f s y rw [← iteratedFDerivWithin_inter_open o_open yo] exact (Hp.mono ho).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl (hs.inter o_open) ⟨hy, yo⟩ exact ((Hp.mono ho).cont m le_rfl).congr fun y hy => (A y hy).symm theorem iteratedFDerivWithin_subset {n : ℕ} (st : s ⊆ t) (hs : UniqueDiffOn 𝕜 s) (ht : UniqueDiffOn 𝕜 t) (h : ContDiffOn 𝕜 n f t) (hx : x ∈ s) : iteratedFDerivWithin 𝕜 n f s x = iteratedFDerivWithin 𝕜 n f t x := (((h.ftaylorSeriesWithin ht).mono st).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl hs hx).symm theorem ContDiffWithinAt.eventually_hasFTaylorSeriesUpToOn {f : E → F} {s : Set E} {a : E} (h : ContDiffWithinAt 𝕜 n f s a) (hs : UniqueDiffOn 𝕜 s) (ha : a ∈ s) {m : ℕ} (hm : m ≤ n) : ∀ᶠ t in (𝓝[s] a).smallSets, HasFTaylorSeriesUpToOn m f (ftaylorSeriesWithin 𝕜 f s) t := by rcases h.contDiffOn' hm (by simp) with ⟨U, hUo, haU, hfU⟩ have : ∀ᶠ t in (𝓝[s] a).smallSets, t ⊆ s ∩ U := by rw [eventually_smallSets_subset] exact inter_mem_nhdsWithin _ <| hUo.mem_nhds haU refine this.mono fun t ht ↦ .mono ?_ ht rw [insert_eq_of_mem ha] at hfU refine (hfU.ftaylorSeriesWithin (hs.inter hUo)).congr_series fun k hk x hx ↦ ?_ exact iteratedFDerivWithin_inter_open hUo hx.2 /-- On a set with unique differentiability, an analytic function is automatically `C^ω`, as its successive derivatives are also analytic. This does not require completeness of the space. See also `AnalyticOn.contDiffOn_of_completeSpace`. -/ theorem AnalyticOn.contDiffOn (h : AnalyticOn 𝕜 f s) (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 n f s := by suffices ContDiffOn 𝕜 ω f s from this.of_le le_top rcases h.exists_hasFTaylorSeriesUpToOn hs with ⟨p, hp⟩ intro x hx refine ⟨s, ?_, p, hp⟩ rw [insert_eq_of_mem hx] exact self_mem_nhdsWithin /-- On a set with unique differentiability, an analytic function is automatically `C^ω`, as its successive derivatives are also analytic. This does not require completeness of the space. See also `AnalyticOnNhd.contDiffOn_of_completeSpace`. -/ theorem AnalyticOnNhd.contDiffOn (h : AnalyticOnNhd 𝕜 f s) (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 n f s := h.analyticOn.contDiffOn hs /-- An analytic function is automatically `C^ω` in a complete space -/ theorem AnalyticOn.contDiffOn_of_completeSpace [CompleteSpace F] (h : AnalyticOn 𝕜 f s) : ContDiffOn 𝕜 n f s := fun x hx ↦ (h x hx).contDiffWithinAt /-- An analytic function is automatically `C^ω` in a complete space -/ theorem AnalyticOnNhd.contDiffOn_of_completeSpace [CompleteSpace F] (h : AnalyticOnNhd 𝕜 f s) : ContDiffOn 𝕜 n f s := h.analyticOn.contDiffOn_of_completeSpace theorem contDiffOn_of_continuousOn_differentiableOn {n : ℕ∞} (Hcont : ∀ m : ℕ, m ≤ n → ContinuousOn (fun x => iteratedFDerivWithin 𝕜 m f s x) s) (Hdiff : ∀ m : ℕ, m < n → DifferentiableOn 𝕜 (fun x => iteratedFDerivWithin 𝕜 m f s x) s) : ContDiffOn 𝕜 n f s := by intro x hx m hm rw [insert_eq_of_mem hx] refine ⟨s, self_mem_nhdsWithin, ftaylorSeriesWithin 𝕜 f s, ?_⟩ constructor · intro y _ simp only [ftaylorSeriesWithin, ContinuousMultilinearMap.curry0_apply, iteratedFDerivWithin_zero_apply] · intro k hk y hy convert (Hdiff k (lt_of_lt_of_le (mod_cast hk) (mod_cast hm)) y hy).hasFDerivWithinAt · intro k hk exact Hcont k (le_trans (mod_cast hk) (mod_cast hm)) theorem contDiffOn_of_differentiableOn {n : ℕ∞} (h : ∀ m : ℕ, m ≤ n → DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 m f s) s) : ContDiffOn 𝕜 n f s := contDiffOn_of_continuousOn_differentiableOn (fun m hm => (h m hm).continuousOn) fun m hm => h m (le_of_lt hm) theorem contDiffOn_of_analyticOn_iteratedFDerivWithin (h : ∀ m, AnalyticOn 𝕜 (iteratedFDerivWithin 𝕜 m f s) s) : ContDiffOn 𝕜 n f s := by suffices ContDiffOn 𝕜 ω f s from this.of_le le_top intro x hx refine ⟨insert x s, self_mem_nhdsWithin, ftaylorSeriesWithin 𝕜 f s, ?_, ?_⟩ · rw [insert_eq_of_mem hx] constructor · intro y _ simp only [ftaylorSeriesWithin, ContinuousMultilinearMap.curry0_apply, iteratedFDerivWithin_zero_apply] · intro k _ y hy exact ((h k).differentiableOn y hy).hasFDerivWithinAt · intro k _ exact (h k).continuousOn · intro i rw [insert_eq_of_mem hx] exact h i theorem contDiffOn_omega_iff_analyticOn (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 ω f s ↔ AnalyticOn 𝕜 f s := ⟨fun h m ↦ h.analyticOn m, fun h ↦ h.contDiffOn hs⟩ theorem ContDiffOn.continuousOn_iteratedFDerivWithin {m : ℕ} (h : ContDiffOn 𝕜 n f s) (hmn : m ≤ n) (hs : UniqueDiffOn 𝕜 s) : ContinuousOn (iteratedFDerivWithin 𝕜 m f s) s := ((h.of_le hmn).ftaylorSeriesWithin hs).cont m le_rfl theorem ContDiffOn.differentiableOn_iteratedFDerivWithin {m : ℕ} (h : ContDiffOn 𝕜 n f s) (hmn : m < n) (hs : UniqueDiffOn 𝕜 s) : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 m f s) s := by intro x hx have : (m + 1 : ℕ) ≤ n := ENat.add_one_natCast_le_withTop_of_lt hmn apply (((h.of_le this).ftaylorSeriesWithin hs).fderivWithin m ?_ x hx).differentiableWithinAt exact_mod_cast lt_add_one m theorem ContDiffWithinAt.differentiableWithinAt_iteratedFDerivWithin {m : ℕ} (h : ContDiffWithinAt 𝕜 n f s x) (hmn : m < n) (hs : UniqueDiffOn 𝕜 (insert x s)) : DifferentiableWithinAt 𝕜 (iteratedFDerivWithin 𝕜 m f s) s x := by have : (m + 1 : WithTop ℕ∞) ≠ ∞ := Ne.symm (ne_of_beq_false rfl) rcases h.contDiffOn' (ENat.add_one_natCast_le_withTop_of_lt hmn) (by simp [this]) with ⟨u, uo, xu, hu⟩ set t := insert x s ∩ u have A : t =ᶠ[𝓝[≠] x] s := by simp only [set_eventuallyEq_iff_inf_principal, ← nhdsWithin_inter'] rw [← inter_assoc, nhdsWithin_inter_of_mem', ← diff_eq_compl_inter, insert_diff_of_mem, diff_eq_compl_inter] exacts [rfl, mem_nhdsWithin_of_mem_nhds (uo.mem_nhds xu)] have B : iteratedFDerivWithin 𝕜 m f s =ᶠ[𝓝 x] iteratedFDerivWithin 𝕜 m f t := iteratedFDerivWithin_eventually_congr_set' _ A.symm _ have C : DifferentiableWithinAt 𝕜 (iteratedFDerivWithin 𝕜 m f t) t x := hu.differentiableOn_iteratedFDerivWithin (Nat.cast_lt.2 m.lt_succ_self) (hs.inter uo) x ⟨mem_insert _ _, xu⟩ rw [differentiableWithinAt_congr_set' _ A] at C exact C.congr_of_eventuallyEq (B.filter_mono inf_le_left) B.self_of_nhds theorem contDiffOn_iff_continuousOn_differentiableOn {n : ℕ∞} (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 n f s ↔ (∀ m : ℕ, m ≤ n → ContinuousOn (fun x => iteratedFDerivWithin 𝕜 m f s x) s) ∧ ∀ m : ℕ, m < n → DifferentiableOn 𝕜 (fun x => iteratedFDerivWithin 𝕜 m f s x) s := ⟨fun h => ⟨fun _m hm => h.continuousOn_iteratedFDerivWithin (mod_cast hm) hs, fun _m hm => h.differentiableOn_iteratedFDerivWithin (mod_cast hm) hs⟩, fun h => contDiffOn_of_continuousOn_differentiableOn h.1 h.2⟩ theorem contDiffOn_nat_iff_continuousOn_differentiableOn {n : ℕ} (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 n f s ↔ (∀ m : ℕ, m ≤ n → ContinuousOn (fun x => iteratedFDerivWithin 𝕜 m f s x) s) ∧ ∀ m : ℕ, m < n → DifferentiableOn 𝕜 (fun x => iteratedFDerivWithin 𝕜 m f s x) s := by rw [← WithTop.coe_natCast, contDiffOn_iff_continuousOn_differentiableOn hs] simp theorem contDiffOn_succ_of_fderivWithin (hf : DifferentiableOn 𝕜 f s) (h' : n = ω → AnalyticOn 𝕜 f s) (h : ContDiffOn 𝕜 n (fun y => fderivWithin 𝕜 f s y) s) : ContDiffOn 𝕜 (n + 1) f s := by rcases eq_or_ne n ∞ with rfl | hn · rw [ENat.coe_top_add_one, contDiffOn_infty] intro m x hx apply ContDiffWithinAt.of_le _ (show (m : WithTop ℕ∞) ≤ m + 1 from le_self_add) rw [contDiffWithinAt_succ_iff_hasFDerivWithinAt (by simp), insert_eq_of_mem hx] exact ⟨s, self_mem_nhdsWithin, (by simp), fderivWithin 𝕜 f s, fun y hy => (hf y hy).hasFDerivWithinAt, (h x hx).of_le (mod_cast le_top)⟩ · intro x hx rw [contDiffWithinAt_succ_iff_hasFDerivWithinAt hn, insert_eq_of_mem hx] exact ⟨s, self_mem_nhdsWithin, h', fderivWithin 𝕜 f s, fun y hy => (hf y hy).hasFDerivWithinAt, h x hx⟩ theorem contDiffOn_of_analyticOn_of_fderivWithin (hf : AnalyticOn 𝕜 f s) (h : ContDiffOn 𝕜 ω (fun y ↦ fderivWithin 𝕜 f s y) s) : ContDiffOn 𝕜 n f s := by suffices ContDiffOn 𝕜 (ω + 1) f s from this.of_le le_top exact contDiffOn_succ_of_fderivWithin hf.differentiableOn (fun _ ↦ hf) h /-- A function is `C^(n + 1)` on a domain with unique derivatives if and only if it is differentiable there, and its derivative (expressed with `fderivWithin`) is `C^n`. -/ theorem contDiffOn_succ_iff_fderivWithin (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 (n + 1) f s ↔ DifferentiableOn 𝕜 f s ∧ (n = ω → AnalyticOn 𝕜 f s) ∧ ContDiffOn 𝕜 n (fderivWithin 𝕜 f s) s := by refine ⟨fun H => ?_, fun h => contDiffOn_succ_of_fderivWithin h.1 h.2.1 h.2.2⟩ refine ⟨H.differentiableOn le_add_self, ?_, fun x hx => ?_⟩ · rintro rfl exact H.analyticOn have A (m : ℕ) (hm : m ≤ n) : ContDiffWithinAt 𝕜 m (fun y => fderivWithin 𝕜 f s y) s x := by rcases (contDiffWithinAt_succ_iff_hasFDerivWithinAt (n := m) (ne_of_beq_false rfl)).1 (H.of_le (add_le_add_right hm 1) x hx) with ⟨u, hu, -, f', hff', hf'⟩ rcases mem_nhdsWithin.1 hu with ⟨o, o_open, xo, ho⟩ rw [inter_comm, insert_eq_of_mem hx] at ho have := hf'.mono ho rw [contDiffWithinAt_inter' (mem_nhdsWithin_of_mem_nhds (IsOpen.mem_nhds o_open xo))] at this apply this.congr_of_eventuallyEq_of_mem _ hx have : o ∩ s ∈ 𝓝[s] x := mem_nhdsWithin.2 ⟨o, o_open, xo, Subset.refl _⟩ rw [inter_comm] at this refine Filter.eventuallyEq_of_mem this fun y hy => ?_ have A : fderivWithin 𝕜 f (s ∩ o) y = f' y := ((hff' y (ho hy)).mono ho).fderivWithin (hs.inter o_open y hy) rwa [fderivWithin_inter (o_open.mem_nhds hy.2)] at A match n with | ω => exact (H.analyticOn.fderivWithin hs).contDiffOn hs (n := ω) x hx | ∞ => exact contDiffWithinAt_infty.2 (fun m ↦ A m (mod_cast le_top)) | (n : ℕ) => exact A n le_rfl theorem contDiffOn_succ_iff_hasFDerivWithinAt_of_uniqueDiffOn (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 (n + 1) f s ↔ (n = ω → AnalyticOn 𝕜 f s) ∧ ∃ f' : E → E →L[𝕜] F, ContDiffOn 𝕜 n f' s ∧ ∀ x, x ∈ s → HasFDerivWithinAt f (f' x) s x := by rw [contDiffOn_succ_iff_fderivWithin hs] refine ⟨fun h => ⟨h.2.1, fderivWithin 𝕜 f s, h.2.2, fun x hx => (h.1 x hx).hasFDerivWithinAt⟩, fun ⟨f_an, h⟩ => ?_⟩ rcases h with ⟨f', h1, h2⟩ refine ⟨fun x hx => (h2 x hx).differentiableWithinAt, f_an, fun x hx => ?_⟩ exact (h1 x hx).congr_of_mem (fun y hy => (h2 y hy).fderivWithin (hs y hy)) hx @[deprecated (since := "2024-11-27")] alias contDiffOn_succ_iff_hasFDerivWithin := contDiffOn_succ_iff_hasFDerivWithinAt_of_uniqueDiffOn theorem contDiffOn_infty_iff_fderivWithin (hs : UniqueDiffOn 𝕜 s) : ContDiffOn 𝕜 ∞ f s ↔ DifferentiableOn 𝕜 f s ∧ ContDiffOn 𝕜 ∞ (fderivWithin 𝕜 f s) s := by rw [← ENat.coe_top_add_one, contDiffOn_succ_iff_fderivWithin hs] simp @[deprecated (since := "2024-11-27")] alias contDiffOn_top_iff_fderivWithin := contDiffOn_infty_iff_fderivWithin /-- A function is `C^(n + 1)` on an open domain if and only if it is differentiable there, and its derivative (expressed with `fderiv`) is `C^n`. -/ theorem contDiffOn_succ_iff_fderiv_of_isOpen (hs : IsOpen s) : ContDiffOn 𝕜 (n + 1) f s ↔ DifferentiableOn 𝕜 f s ∧ (n = ω → AnalyticOn 𝕜 f s) ∧ ContDiffOn 𝕜 n (fderiv 𝕜 f) s := by rw [contDiffOn_succ_iff_fderivWithin hs.uniqueDiffOn, contDiffOn_congr fun x hx ↦ fderivWithin_of_isOpen hs hx] theorem contDiffOn_infty_iff_fderiv_of_isOpen (hs : IsOpen s) : ContDiffOn 𝕜 ∞ f s ↔ DifferentiableOn 𝕜 f s ∧ ContDiffOn 𝕜 ∞ (fderiv 𝕜 f) s := by rw [← ENat.coe_top_add_one, contDiffOn_succ_iff_fderiv_of_isOpen hs] simp @[deprecated (since := "2024-11-27")] alias contDiffOn_top_iff_fderiv_of_isOpen := contDiffOn_infty_iff_fderiv_of_isOpen protected theorem ContDiffOn.fderivWithin (hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) : ContDiffOn 𝕜 m (fderivWithin 𝕜 f s) s := ((contDiffOn_succ_iff_fderivWithin hs).1 (hf.of_le hmn)).2.2 theorem ContDiffOn.fderiv_of_isOpen (hf : ContDiffOn 𝕜 n f s) (hs : IsOpen s) (hmn : m + 1 ≤ n) : ContDiffOn 𝕜 m (fderiv 𝕜 f) s := (hf.fderivWithin hs.uniqueDiffOn hmn).congr fun _ hx => (fderivWithin_of_isOpen hs hx).symm theorem ContDiffOn.continuousOn_fderivWithin (h : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (hn : 1 ≤ n) : ContinuousOn (fderivWithin 𝕜 f s) s := ((contDiffOn_succ_iff_fderivWithin hs).1 (h.of_le (show 0 + (1 : WithTop ℕ∞) ≤ n from hn))).2.2.continuousOn theorem ContDiffOn.continuousOn_fderiv_of_isOpen (h : ContDiffOn 𝕜 n f s) (hs : IsOpen s)
(hn : 1 ≤ n) : ContinuousOn (fderiv 𝕜 f) s := ((contDiffOn_succ_iff_fderiv_of_isOpen hs).1 (h.of_le (show 0 + (1 : WithTop ℕ∞) ≤ n from hn))).2.2.continuousOn /-! ### Smooth functions at a point -/ variable (𝕜) in
Mathlib/Analysis/Calculus/ContDiff/Defs.lean
908
914
/- Copyright (c) 2017 Microsoft Corporation. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Johannes Hölzl, Mario Carneiro, Oliver Nash -/ import Mathlib.Data.Finset.Card import Mathlib.Data.Finset.Union /-! # Finsets in product types This file defines finset constructions on the product type `α × β`. Beware not to confuse with the `Finset.prod` operation which computes the multiplicative product. ## Main declarations * `Finset.product`: Turns `s : Finset α`, `t : Finset β` into their product in `Finset (α × β)`. * `Finset.diag`: For `s : Finset α`, `s.diag` is the `Finset (α × α)` of pairs `(a, a)` with `a ∈ s`. * `Finset.offDiag`: For `s : Finset α`, `s.offDiag` is the `Finset (α × α)` of pairs `(a, b)` with `a, b ∈ s` and `a ≠ b`. -/ assert_not_exists MonoidWithZero open Multiset variable {α β γ : Type*} namespace Finset /-! ### prod -/ section Prod variable {s s' : Finset α} {t t' : Finset β} {a : α} {b : β} /-- `product s t` is the set of pairs `(a, b)` such that `a ∈ s` and `b ∈ t`. -/ protected def product (s : Finset α) (t : Finset β) : Finset (α × β) := ⟨_, s.nodup.product t.nodup⟩ instance instSProd : SProd (Finset α) (Finset β) (Finset (α × β)) where sprod := Finset.product @[simp] theorem product_eq_sprod : Finset.product s t = s ×ˢ t := rfl @[simp] theorem product_val : (s ×ˢ t).1 = s.1 ×ˢ t.1 := rfl @[simp] theorem mem_product {p : α × β} : p ∈ s ×ˢ t ↔ p.1 ∈ s ∧ p.2 ∈ t := Multiset.mem_product theorem mk_mem_product (ha : a ∈ s) (hb : b ∈ t) : (a, b) ∈ s ×ˢ t := mem_product.2 ⟨ha, hb⟩ @[simp, norm_cast] theorem coe_product (s : Finset α) (t : Finset β) : (↑(s ×ˢ t) : Set (α × β)) = (s : Set α) ×ˢ t := Set.ext fun _ => Finset.mem_product theorem subset_product_image_fst [DecidableEq α] : (s ×ˢ t).image Prod.fst ⊆ s := fun i => by simp +contextual [mem_image] theorem subset_product_image_snd [DecidableEq β] : (s ×ˢ t).image Prod.snd ⊆ t := fun i => by simp +contextual [mem_image] theorem product_image_fst [DecidableEq α] (ht : t.Nonempty) : (s ×ˢ t).image Prod.fst = s := by ext i simp [mem_image, ht.exists_mem] theorem product_image_snd [DecidableEq β] (ht : s.Nonempty) : (s ×ˢ t).image Prod.snd = t := by ext i simp [mem_image, ht.exists_mem] theorem subset_product [DecidableEq α] [DecidableEq β] {s : Finset (α × β)} : s ⊆ s.image Prod.fst ×ˢ s.image Prod.snd := fun _ hp => mem_product.2 ⟨mem_image_of_mem _ hp, mem_image_of_mem _ hp⟩ @[gcongr] theorem product_subset_product (hs : s ⊆ s') (ht : t ⊆ t') : s ×ˢ t ⊆ s' ×ˢ t' := fun ⟨_, _⟩ h => mem_product.2 ⟨hs (mem_product.1 h).1, ht (mem_product.1 h).2⟩ @[gcongr] theorem product_subset_product_left (hs : s ⊆ s') : s ×ˢ t ⊆ s' ×ˢ t := product_subset_product hs (Subset.refl _) @[gcongr] theorem product_subset_product_right (ht : t ⊆ t') : s ×ˢ t ⊆ s ×ˢ t' := product_subset_product (Subset.refl _) ht theorem prodMap_image_product {δ : Type*} [DecidableEq β] [DecidableEq δ] (f : α → β) (g : γ → δ) (s : Finset α) (t : Finset γ) : (s ×ˢ t).image (Prod.map f g) = s.image f ×ˢ t.image g := mod_cast Set.prodMap_image_prod f g s t theorem prodMap_map_product {δ : Type*} (f : α ↪ β) (g : γ ↪ δ) (s : Finset α) (t : Finset γ) : (s ×ˢ t).map (f.prodMap g) = s.map f ×ˢ t.map g := by simpa [← coe_inj] using Set.prodMap_image_prod f g s t theorem map_swap_product (s : Finset α) (t : Finset β) : (t ×ˢ s).map ⟨Prod.swap, Prod.swap_injective⟩ = s ×ˢ t := coe_injective <| by push_cast exact Set.image_swap_prod _ _ @[simp] theorem image_swap_product [DecidableEq (α × β)] (s : Finset α) (t : Finset β) : (t ×ˢ s).image Prod.swap = s ×ˢ t := coe_injective <| by push_cast exact Set.image_swap_prod _ _ theorem product_eq_biUnion [DecidableEq (α × β)] (s : Finset α) (t : Finset β) : s ×ˢ t = s.biUnion fun a => t.image fun b => (a, b) := ext fun ⟨x, y⟩ => by simp only [mem_product, mem_biUnion, mem_image, exists_prop, Prod.mk_inj, and_left_comm, exists_and_left, exists_eq_right, exists_eq_left] theorem product_eq_biUnion_right [DecidableEq (α × β)] (s : Finset α) (t : Finset β) : s ×ˢ t = t.biUnion fun b => s.image fun a => (a, b) := ext fun ⟨x, y⟩ => by simp only [mem_product, mem_biUnion, mem_image, exists_prop, Prod.mk_inj, and_left_comm, exists_and_left, exists_eq_right, exists_eq_left] /-- See also `Finset.sup_product_left`. -/ @[simp] theorem product_biUnion [DecidableEq γ] (s : Finset α) (t : Finset β) (f : α × β → Finset γ) : (s ×ˢ t).biUnion f = s.biUnion fun a => t.biUnion fun b => f (a, b) := by classical simp_rw [product_eq_biUnion, biUnion_biUnion, image_biUnion] @[simp] theorem card_product (s : Finset α) (t : Finset β) : card (s ×ˢ t) = card s * card t := Multiset.card_product _ _ /-- The product of two Finsets is nontrivial iff both are nonempty at least one of them is nontrivial. -/ lemma nontrivial_prod_iff : (s ×ˢ t).Nontrivial ↔ s.Nonempty ∧ t.Nonempty ∧ (s.Nontrivial ∨ t.Nontrivial) := by simp_rw [← card_pos, ← one_lt_card_iff_nontrivial, card_product]; apply Nat.one_lt_mul_iff theorem filter_product (p : α → Prop) (q : β → Prop) [DecidablePred p] [DecidablePred q] : ((s ×ˢ t).filter fun x : α × β => p x.1 ∧ q x.2) = s.filter p ×ˢ t.filter q := by ext ⟨a, b⟩ simp [mem_filter, mem_product, decide_eq_true_eq, and_comm, and_left_comm, and_assoc] theorem filter_product_left (p : α → Prop) [DecidablePred p] : ((s ×ˢ t).filter fun x : α × β => p x.1) = s.filter p ×ˢ t := by
simpa using filter_product p fun _ => true theorem filter_product_right (q : β → Prop) [DecidablePred q] : ((s ×ˢ t).filter fun x : α × β => q x.2) = s ×ˢ t.filter q := by
Mathlib/Data/Finset/Prod.lean
153
156
/- Copyright (c) 2018 Mario Carneiro. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Mario Carneiro -/ import Mathlib.Algebra.Order.Ring.Nat import Mathlib.Logic.Encodable.Pi import Mathlib.Logic.Function.Iterate /-! # The primitive recursive functions The primitive recursive functions are the least collection of functions `ℕ → ℕ` which are closed under projections (using the `pair` pairing function), composition, zero, successor, and primitive recursion (i.e. `Nat.rec` where the motive is `C n := ℕ`). We can extend this definition to a large class of basic types by using canonical encodings of types as natural numbers (Gödel numbering), which we implement through the type class `Encodable`. (More precisely, we need that the composition of encode with decode yields a primitive recursive function, so we have the `Primcodable` type class for this.) In the above, the pairing function is primitive recursive by definition. This deviates from the textbook definition of primitive recursive functions, which instead work with *`n`-ary* functions. We formalize the textbook definition in `Nat.Primrec'`. `Nat.Primrec'.prim_iff` then proves it is equivalent to our chosen formulation. For more discussionn of this and other design choices in this formalization, see [carneiro2019]. ## Main definitions - `Nat.Primrec f`: `f` is primitive recursive, for functions `f : ℕ → ℕ` - `Primrec f`: `f` is primitive recursive, for functions between `Primcodable` types - `Primcodable α`: well-behaved encoding of `α` into `ℕ`, i.e. one such that roundtripping through the encoding functions adds no computational power ## References * [Mario Carneiro, *Formalizing computability theory via partial recursive functions*][carneiro2019] -/ open List (Vector) open Denumerable Encodable Function namespace Nat /-- Calls the given function on a pair of entries `n`, encoded via the pairing function. -/ @[simp, reducible] def unpaired {α} (f : ℕ → ℕ → α) (n : ℕ) : α := f n.unpair.1 n.unpair.2 /-- The primitive recursive functions `ℕ → ℕ`. -/ protected inductive Primrec : (ℕ → ℕ) → Prop | zero : Nat.Primrec fun _ => 0 | protected succ : Nat.Primrec succ | left : Nat.Primrec fun n => n.unpair.1 | right : Nat.Primrec fun n => n.unpair.2 | pair {f g} : Nat.Primrec f → Nat.Primrec g → Nat.Primrec fun n => pair (f n) (g n) | comp {f g} : Nat.Primrec f → Nat.Primrec g → Nat.Primrec fun n => f (g n) | prec {f g} : Nat.Primrec f → Nat.Primrec g → Nat.Primrec (unpaired fun z n => n.rec (f z) fun y IH => g <| pair z <| pair y IH) namespace Primrec theorem of_eq {f g : ℕ → ℕ} (hf : Nat.Primrec f) (H : ∀ n, f n = g n) : Nat.Primrec g := (funext H : f = g) ▸ hf theorem const : ∀ n : ℕ, Nat.Primrec fun _ => n | 0 => zero | n + 1 => Primrec.succ.comp (const n) protected theorem id : Nat.Primrec id := (left.pair right).of_eq fun n => by simp theorem prec1 {f} (m : ℕ) (hf : Nat.Primrec f) : Nat.Primrec fun n => n.rec m fun y IH => f <| Nat.pair y IH := ((prec (const m) (hf.comp right)).comp (zero.pair Primrec.id)).of_eq fun n => by simp theorem casesOn1 {f} (m : ℕ) (hf : Nat.Primrec f) : Nat.Primrec (Nat.casesOn · m f) := (prec1 m (hf.comp left)).of_eq <| by simp -- Porting note: `Nat.Primrec.casesOn` is already declared as a recursor. theorem casesOn' {f g} (hf : Nat.Primrec f) (hg : Nat.Primrec g) : Nat.Primrec (unpaired fun z n => n.casesOn (f z) fun y => g <| Nat.pair z y) := (prec hf (hg.comp (pair left (left.comp right)))).of_eq fun n => by simp protected theorem swap : Nat.Primrec (unpaired (swap Nat.pair)) := (pair right left).of_eq fun n => by simp theorem swap' {f} (hf : Nat.Primrec (unpaired f)) : Nat.Primrec (unpaired (swap f)) := (hf.comp .swap).of_eq fun n => by simp theorem pred : Nat.Primrec pred := (casesOn1 0 Primrec.id).of_eq fun n => by cases n <;> simp [*] theorem add : Nat.Primrec (unpaired (· + ·)) := (prec .id ((Primrec.succ.comp right).comp right)).of_eq fun p => by simp; induction p.unpair.2 <;> simp [*, Nat.add_assoc] theorem sub : Nat.Primrec (unpaired (· - ·)) := (prec .id ((pred.comp right).comp right)).of_eq fun p => by simp; induction p.unpair.2 <;> simp [*, Nat.sub_add_eq] theorem mul : Nat.Primrec (unpaired (· * ·)) := (prec zero (add.comp (pair left (right.comp right)))).of_eq fun p => by simp; induction p.unpair.2 <;> simp [*, mul_succ, add_comm _ (unpair p).fst] theorem pow : Nat.Primrec (unpaired (· ^ ·)) := (prec (const 1) (mul.comp (pair (right.comp right) left))).of_eq fun p => by simp; induction p.unpair.2 <;> simp [*, Nat.pow_succ] end Primrec end Nat /-- A `Primcodable` type is, essentially, an `Encodable` type for which the encode/decode functions are primitive recursive. However, such a definition is circular. Instead, we ask that the composition of `decode : ℕ → Option α` with `encode : Option α → ℕ` is primitive recursive. Said composition is the identity function, restricted to the image of `encode`. Thus, in a way, the added requirement ensures that no predicates can be smuggled in through a cunning choice of the subset of `ℕ` into which the type is encoded. -/ class Primcodable (α : Type*) extends Encodable α where -- Porting note: was `prim [] `. -- This means that `prim` does not take the type explicitly in Lean 4 prim : Nat.Primrec fun n => Encodable.encode (decode n) namespace Primcodable open Nat.Primrec instance (priority := 10) ofDenumerable (α) [Denumerable α] : Primcodable α := ⟨Nat.Primrec.succ.of_eq <| by simp⟩ /-- Builds a `Primcodable` instance from an equivalence to a `Primcodable` type. -/ def ofEquiv (α) {β} [Primcodable α] (e : β ≃ α) : Primcodable β := { __ := Encodable.ofEquiv α e prim := (@Primcodable.prim α _).of_eq fun n => by rw [decode_ofEquiv] cases (@decode α _ n) <;> simp [encode_ofEquiv] } instance empty : Primcodable Empty := ⟨zero⟩ instance unit : Primcodable PUnit := ⟨(casesOn1 1 zero).of_eq fun n => by cases n <;> simp⟩ instance option {α : Type*} [h : Primcodable α] : Primcodable (Option α) := ⟨(casesOn1 1 ((casesOn1 0 (.comp .succ .succ)).comp (@Primcodable.prim α _))).of_eq fun n => by cases n with | zero => rfl | succ n => rw [decode_option_succ] cases H : @decode α _ n <;> simp [H]⟩ instance bool : Primcodable Bool := ⟨(casesOn1 1 (casesOn1 2 zero)).of_eq fun n => match n with | 0 => rfl | 1 => rfl | (n + 2) => by rw [decode_ge_two] <;> simp⟩ end Primcodable /-- `Primrec f` means `f` is primitive recursive (after encoding its input and output as natural numbers). -/ def Primrec {α β} [Primcodable α] [Primcodable β] (f : α → β) : Prop := Nat.Primrec fun n => encode ((@decode α _ n).map f) namespace Primrec variable {α : Type*} {β : Type*} {σ : Type*} variable [Primcodable α] [Primcodable β] [Primcodable σ] open Nat.Primrec protected theorem encode : Primrec (@encode α _) := (@Primcodable.prim α _).of_eq fun n => by cases @decode α _ n <;> rfl protected theorem decode : Primrec (@decode α _) := Nat.Primrec.succ.comp (@Primcodable.prim α _) theorem dom_denumerable {α β} [Denumerable α] [Primcodable β] {f : α → β} : Primrec f ↔ Nat.Primrec fun n => encode (f (ofNat α n)) := ⟨fun h => (pred.comp h).of_eq fun n => by simp, fun h => (Nat.Primrec.succ.comp h).of_eq fun n => by simp⟩ theorem nat_iff {f : ℕ → ℕ} : Primrec f ↔ Nat.Primrec f := dom_denumerable theorem encdec : Primrec fun n => encode (@decode α _ n) := nat_iff.2 Primcodable.prim theorem option_some : Primrec (@some α) := ((casesOn1 0 (Nat.Primrec.succ.comp .succ)).comp (@Primcodable.prim α _)).of_eq fun n => by cases @decode α _ n <;> simp theorem of_eq {f g : α → σ} (hf : Primrec f) (H : ∀ n, f n = g n) : Primrec g := (funext H : f = g) ▸ hf theorem const (x : σ) : Primrec fun _ : α => x := ((casesOn1 0 (.const (encode x).succ)).comp (@Primcodable.prim α _)).of_eq fun n => by cases @decode α _ n <;> rfl protected theorem id : Primrec (@id α) := (@Primcodable.prim α).of_eq <| by simp theorem comp {f : β → σ} {g : α → β} (hf : Primrec f) (hg : Primrec g) : Primrec fun a => f (g a) := ((casesOn1 0 (.comp hf (pred.comp hg))).comp (@Primcodable.prim α _)).of_eq fun n => by cases @decode α _ n <;> simp [encodek] theorem succ : Primrec Nat.succ := nat_iff.2 Nat.Primrec.succ theorem pred : Primrec Nat.pred := nat_iff.2 Nat.Primrec.pred theorem encode_iff {f : α → σ} : (Primrec fun a => encode (f a)) ↔ Primrec f := ⟨fun h => Nat.Primrec.of_eq h fun n => by cases @decode α _ n <;> rfl, Primrec.encode.comp⟩ theorem ofNat_iff {α β} [Denumerable α] [Primcodable β] {f : α → β} : Primrec f ↔ Primrec fun n => f (ofNat α n) := dom_denumerable.trans <| nat_iff.symm.trans encode_iff protected theorem ofNat (α) [Denumerable α] : Primrec (ofNat α) := ofNat_iff.1 Primrec.id theorem option_some_iff {f : α → σ} : (Primrec fun a => some (f a)) ↔ Primrec f := ⟨fun h => encode_iff.1 <| pred.comp <| encode_iff.2 h, option_some.comp⟩ theorem of_equiv {β} {e : β ≃ α} : haveI := Primcodable.ofEquiv α e Primrec e := letI : Primcodable β := Primcodable.ofEquiv α e encode_iff.1 Primrec.encode theorem of_equiv_symm {β} {e : β ≃ α} : haveI := Primcodable.ofEquiv α e Primrec e.symm := letI := Primcodable.ofEquiv α e encode_iff.1 (show Primrec fun a => encode (e (e.symm a)) by simp [Primrec.encode]) theorem of_equiv_iff {β} (e : β ≃ α) {f : σ → β} : haveI := Primcodable.ofEquiv α e (Primrec fun a => e (f a)) ↔ Primrec f := letI := Primcodable.ofEquiv α e ⟨fun h => (of_equiv_symm.comp h).of_eq fun a => by simp, of_equiv.comp⟩ theorem of_equiv_symm_iff {β} (e : β ≃ α) {f : σ → α} : haveI := Primcodable.ofEquiv α e (Primrec fun a => e.symm (f a)) ↔ Primrec f := letI := Primcodable.ofEquiv α e ⟨fun h => (of_equiv.comp h).of_eq fun a => by simp, of_equiv_symm.comp⟩ end Primrec namespace Primcodable open Nat.Primrec instance prod {α β} [Primcodable α] [Primcodable β] : Primcodable (α × β) := ⟨((casesOn' zero ((casesOn' zero .succ).comp (pair right ((@Primcodable.prim β).comp left)))).comp (pair right ((@Primcodable.prim α).comp left))).of_eq fun n => by simp only [Nat.unpaired, Nat.unpair_pair, decode_prod_val] cases @decode α _ n.unpair.1; · simp cases @decode β _ n.unpair.2 <;> simp⟩ end Primcodable namespace Primrec variable {α : Type*} [Primcodable α] open Nat.Primrec theorem fst {α β} [Primcodable α] [Primcodable β] : Primrec (@Prod.fst α β) := ((casesOn' zero ((casesOn' zero (Nat.Primrec.succ.comp left)).comp (pair right ((@Primcodable.prim β).comp left)))).comp (pair right ((@Primcodable.prim α).comp left))).of_eq fun n => by simp only [Nat.unpaired, Nat.unpair_pair, decode_prod_val] cases @decode α _ n.unpair.1 <;> simp cases @decode β _ n.unpair.2 <;> simp theorem snd {α β} [Primcodable α] [Primcodable β] : Primrec (@Prod.snd α β) := ((casesOn' zero ((casesOn' zero (Nat.Primrec.succ.comp right)).comp (pair right ((@Primcodable.prim β).comp left)))).comp (pair right ((@Primcodable.prim α).comp left))).of_eq fun n => by simp only [Nat.unpaired, Nat.unpair_pair, decode_prod_val] cases @decode α _ n.unpair.1 <;> simp cases @decode β _ n.unpair.2 <;> simp theorem pair {α β γ} [Primcodable α] [Primcodable β] [Primcodable γ] {f : α → β} {g : α → γ} (hf : Primrec f) (hg : Primrec g) : Primrec fun a => (f a, g a) := ((casesOn1 0 (Nat.Primrec.succ.comp <| .pair (Nat.Primrec.pred.comp hf) (Nat.Primrec.pred.comp hg))).comp (@Primcodable.prim α _)).of_eq fun n => by cases @decode α _ n <;> simp [encodek] theorem unpair : Primrec Nat.unpair := (pair (nat_iff.2 .left) (nat_iff.2 .right)).of_eq fun n => by simp theorem list_getElem?₁ : ∀ l : List α, Primrec (l[·]? : ℕ → Option α) | [] => dom_denumerable.2 zero | a :: l => dom_denumerable.2 <| (casesOn1 (encode a).succ <| dom_denumerable.1 <| list_getElem?₁ l).of_eq fun n => by cases n <;> simp @[deprecated (since := "2025-02-14")] alias list_get?₁ := list_getElem?₁ end Primrec /-- `Primrec₂ f` means `f` is a binary primitive recursive function. This is technically unnecessary since we can always curry all the arguments together, but there are enough natural two-arg functions that it is convenient to express this directly. -/ def Primrec₂ {α β σ} [Primcodable α] [Primcodable β] [Primcodable σ] (f : α → β → σ) := Primrec fun p : α × β => f p.1 p.2 /-- `PrimrecPred p` means `p : α → Prop` is a (decidable) primitive recursive predicate, which is to say that `decide ∘ p : α → Bool` is primitive recursive. -/ def PrimrecPred {α} [Primcodable α] (p : α → Prop) [DecidablePred p] := Primrec fun a => decide (p a) /-- `PrimrecRel p` means `p : α → β → Prop` is a (decidable) primitive recursive relation, which is to say that `decide ∘ p : α → β → Bool` is primitive recursive. -/ def PrimrecRel {α β} [Primcodable α] [Primcodable β] (s : α → β → Prop) [∀ a b, Decidable (s a b)] := Primrec₂ fun a b => decide (s a b) namespace Primrec₂ variable {α : Type*} {β : Type*} {σ : Type*} variable [Primcodable α] [Primcodable β] [Primcodable σ] theorem mk {f : α → β → σ} (hf : Primrec fun p : α × β => f p.1 p.2) : Primrec₂ f := hf theorem of_eq {f g : α → β → σ} (hg : Primrec₂ f) (H : ∀ a b, f a b = g a b) : Primrec₂ g := (by funext a b; apply H : f = g) ▸ hg theorem const (x : σ) : Primrec₂ fun (_ : α) (_ : β) => x := Primrec.const _ protected theorem pair : Primrec₂ (@Prod.mk α β) := Primrec.pair .fst .snd theorem left : Primrec₂ fun (a : α) (_ : β) => a := .fst theorem right : Primrec₂ fun (_ : α) (b : β) => b := .snd theorem natPair : Primrec₂ Nat.pair := by simp [Primrec₂, Primrec]; constructor theorem unpaired {f : ℕ → ℕ → α} : Primrec (Nat.unpaired f) ↔ Primrec₂ f := ⟨fun h => by simpa using h.comp natPair, fun h => h.comp Primrec.unpair⟩ theorem unpaired' {f : ℕ → ℕ → ℕ} : Nat.Primrec (Nat.unpaired f) ↔ Primrec₂ f := Primrec.nat_iff.symm.trans unpaired
theorem encode_iff {f : α → β → σ} : (Primrec₂ fun a b => encode (f a b)) ↔ Primrec₂ f := Primrec.encode_iff theorem option_some_iff {f : α → β → σ} : (Primrec₂ fun a b => some (f a b)) ↔ Primrec₂ f := Primrec.option_some_iff
Mathlib/Computability/Primrec.lean
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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, 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
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/- Copyright (c) 2021 Oliver Nash. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Oliver Nash -/ import Mathlib.Algebra.Ring.Divisibility.Lemmas import Mathlib.Algebra.Lie.Nilpotent import Mathlib.Algebra.Lie.Engel import Mathlib.LinearAlgebra.Eigenspace.Pi import Mathlib.RingTheory.Artinian.Module import Mathlib.LinearAlgebra.Trace import Mathlib.LinearAlgebra.FreeModule.PID /-! # Weight spaces of Lie modules of nilpotent Lie algebras Just as a key tool when studying the behaviour of a linear operator is to decompose the space on which it acts into a sum of (generalised) eigenspaces, a key tool when studying a representation `M` of Lie algebra `L` is to decompose `M` into a sum of simultaneous eigenspaces of `x` as `x` ranges over `L`. These simultaneous generalised eigenspaces are known as the weight spaces of `M`. When `L` is nilpotent, it follows from the binomial theorem that weight spaces are Lie submodules. Basic definitions and properties of the above ideas are provided in this file. ## Main definitions * `LieModule.genWeightSpaceOf` * `LieModule.genWeightSpace` * `LieModule.Weight` * `LieModule.posFittingCompOf` * `LieModule.posFittingComp` * `LieModule.iSup_ucs_eq_genWeightSpace_zero` * `LieModule.iInf_lowerCentralSeries_eq_posFittingComp` * `LieModule.isCompl_genWeightSpace_zero_posFittingComp` * `LieModule.iSupIndep_genWeightSpace` * `LieModule.iSup_genWeightSpace_eq_top` ## References * [N. Bourbaki, *Lie Groups and Lie Algebras, Chapters 7--9*](bourbaki1975b) ## Tags lie character, eigenvalue, eigenspace, weight, weight vector, root, root vector -/ variable {K R L M : Type*} [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M] [LieRingModule L M] [LieModule R L M] namespace LieModule open Set Function TensorProduct LieModule variable (M) in /-- If `M` is a representation of a Lie algebra `L` and `χ : L → R` is a family of scalars, then `weightSpace M χ` is the intersection of the `χ x`-eigenspaces of the action of `x` on `M` as `x` ranges over `L`. -/ def weightSpace (χ : L → R) : LieSubmodule R L M where __ := ⨅ x : L, (toEnd R L M x).eigenspace (χ x) lie_mem {x m} hm := by simp_all [smul_comm (χ x)] lemma mem_weightSpace (χ : L → R) (m : M) : m ∈ weightSpace M χ ↔ ∀ x, ⁅x, m⁆ = χ x • m := by simp [weightSpace] section notation_genWeightSpaceOf /-- Until we define `LieModule.genWeightSpaceOf`, it is useful to have some notation as follows: -/ local notation3 "𝕎("M", " χ", " x")" => (toEnd R L M x).maxGenEigenspace χ /-- See also `bourbaki1975b` Chapter VII §1.1, Proposition 2 (ii). -/ protected theorem weight_vector_multiplication (M₁ M₂ M₃ : Type*) [AddCommGroup M₁] [Module R M₁] [LieRingModule L M₁] [LieModule R L M₁] [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂] [AddCommGroup M₃] [Module R M₃] [LieRingModule L M₃] [LieModule R L M₃] (g : M₁ ⊗[R] M₂ →ₗ⁅R,L⁆ M₃) (χ₁ χ₂ : R) (x : L) : LinearMap.range ((g : M₁ ⊗[R] M₂ →ₗ[R] M₃).comp (mapIncl 𝕎(M₁, χ₁, x) 𝕎(M₂, χ₂, x))) ≤ 𝕎(M₃, χ₁ + χ₂, x) := by -- Unpack the statement of the goal. intro m₃ simp only [TensorProduct.mapIncl, LinearMap.mem_range, LinearMap.coe_comp, LieModuleHom.coe_toLinearMap, Function.comp_apply, Pi.add_apply, exists_imp, Module.End.mem_maxGenEigenspace] rintro t rfl -- Set up some notation. let F : Module.End R M₃ := toEnd R L M₃ x - (χ₁ + χ₂) • ↑1 -- The goal is linear in `t` so use induction to reduce to the case that `t` is a pure tensor. refine t.induction_on ?_ ?_ ?_ · use 0; simp only [LinearMap.map_zero, LieModuleHom.map_zero] swap · rintro t₁ t₂ ⟨k₁, hk₁⟩ ⟨k₂, hk₂⟩; use max k₁ k₂ simp only [LieModuleHom.map_add, LinearMap.map_add, Module.End.pow_map_zero_of_le (le_max_left k₁ k₂) hk₁, Module.End.pow_map_zero_of_le (le_max_right k₁ k₂) hk₂, add_zero] -- Now the main argument: pure tensors. rintro ⟨m₁, hm₁⟩ ⟨m₂, hm₂⟩ change ∃ k, (F ^ k) ((g : M₁ ⊗[R] M₂ →ₗ[R] M₃) (m₁ ⊗ₜ m₂)) = (0 : M₃) -- Eliminate `g` from the picture. let f₁ : Module.End R (M₁ ⊗[R] M₂) := (toEnd R L M₁ x - χ₁ • ↑1).rTensor M₂ let f₂ : Module.End R (M₁ ⊗[R] M₂) := (toEnd R L M₂ x - χ₂ • ↑1).lTensor M₁ have h_comm_square : F ∘ₗ ↑g = (g : M₁ ⊗[R] M₂ →ₗ[R] M₃).comp (f₁ + f₂) := by ext m₁ m₂ simp only [f₁, f₂, F, ← g.map_lie x (m₁ ⊗ₜ m₂), add_smul, sub_tmul, tmul_sub, smul_tmul, lie_tmul_right, tmul_smul, toEnd_apply_apply, LieModuleHom.map_smul, Module.End.one_apply, LieModuleHom.coe_toLinearMap, LinearMap.smul_apply, Function.comp_apply, LinearMap.coe_comp, LinearMap.rTensor_tmul, LieModuleHom.map_add, LinearMap.add_apply, LieModuleHom.map_sub, LinearMap.sub_apply, LinearMap.lTensor_tmul, AlgebraTensorModule.curry_apply, TensorProduct.curry_apply, LinearMap.toFun_eq_coe, LinearMap.coe_restrictScalars] abel rsuffices ⟨k, hk⟩ : ∃ k : ℕ, ((f₁ + f₂) ^ k) (m₁ ⊗ₜ m₂) = 0 · use k change (F ^ k) (g.toLinearMap (m₁ ⊗ₜ[R] m₂)) = 0 rw [← LinearMap.comp_apply, Module.End.commute_pow_left_of_commute h_comm_square, LinearMap.comp_apply, hk, LinearMap.map_zero] -- Unpack the information we have about `m₁`, `m₂`. simp only [Module.End.mem_maxGenEigenspace] at hm₁ hm₂ obtain ⟨k₁, hk₁⟩ := hm₁ obtain ⟨k₂, hk₂⟩ := hm₂ have hf₁ : (f₁ ^ k₁) (m₁ ⊗ₜ m₂) = 0 := by simp only [f₁, hk₁, zero_tmul, LinearMap.rTensor_tmul, LinearMap.rTensor_pow] have hf₂ : (f₂ ^ k₂) (m₁ ⊗ₜ m₂) = 0 := by simp only [f₂, hk₂, tmul_zero, LinearMap.lTensor_tmul, LinearMap.lTensor_pow] -- It's now just an application of the binomial theorem. use k₁ + k₂ - 1 have hf_comm : Commute f₁ f₂ := by ext m₁ m₂ simp only [f₁, f₂, Module.End.mul_apply, LinearMap.rTensor_tmul, LinearMap.lTensor_tmul, AlgebraTensorModule.curry_apply, LinearMap.toFun_eq_coe, LinearMap.lTensor_tmul, TensorProduct.curry_apply, LinearMap.coe_restrictScalars] rw [hf_comm.add_pow'] simp only [TensorProduct.mapIncl, Submodule.subtype_apply, Finset.sum_apply, Submodule.coe_mk, LinearMap.coeFn_sum, TensorProduct.map_tmul, LinearMap.smul_apply] -- The required sum is zero because each individual term is zero. apply Finset.sum_eq_zero rintro ⟨i, j⟩ hij -- Eliminate the binomial coefficients from the picture. suffices (f₁ ^ i * f₂ ^ j) (m₁ ⊗ₜ m₂) = 0 by rw [this]; apply smul_zero -- Finish off with appropriate case analysis. rcases Nat.le_or_le_of_add_eq_add_pred (Finset.mem_antidiagonal.mp hij) with hi | hj · rw [(hf_comm.pow_pow i j).eq, Module.End.mul_apply, Module.End.pow_map_zero_of_le hi hf₁, LinearMap.map_zero] · rw [Module.End.mul_apply, Module.End.pow_map_zero_of_le hj hf₂, LinearMap.map_zero] lemma lie_mem_maxGenEigenspace_toEnd {χ₁ χ₂ : R} {x y : L} {m : M} (hy : y ∈ 𝕎(L, χ₁, x)) (hm : m ∈ 𝕎(M, χ₂, x)) : ⁅y, m⁆ ∈ 𝕎(M, χ₁ + χ₂, x) := by apply LieModule.weight_vector_multiplication L M M (toModuleHom R L M) χ₁ χ₂ simp only [LieModuleHom.coe_toLinearMap, Function.comp_apply, LinearMap.coe_comp, TensorProduct.mapIncl, LinearMap.mem_range] use ⟨y, hy⟩ ⊗ₜ ⟨m, hm⟩ simp only [Submodule.subtype_apply, toModuleHom_apply, TensorProduct.map_tmul] variable (M) /-- If `M` is a representation of a nilpotent Lie algebra `L`, `χ` is a scalar, and `x : L`, then `genWeightSpaceOf M χ x` is the maximal generalized `χ`-eigenspace of the action of `x` on `M`. It is a Lie submodule because `L` is nilpotent. -/ def genWeightSpaceOf [LieRing.IsNilpotent L] (χ : R) (x : L) : LieSubmodule R L M := { 𝕎(M, χ, x) with lie_mem := by intro y m hm simp only [AddSubsemigroup.mem_carrier, AddSubmonoid.mem_toSubsemigroup, Submodule.mem_toAddSubmonoid] at hm ⊢ rw [← zero_add χ] exact lie_mem_maxGenEigenspace_toEnd (by simp) hm } end notation_genWeightSpaceOf variable (M) variable [LieRing.IsNilpotent L] theorem mem_genWeightSpaceOf (χ : R) (x : L) (m : M) : m ∈ genWeightSpaceOf M χ x ↔ ∃ k : ℕ, ((toEnd R L M x - χ • ↑1) ^ k) m = 0 := by simp [genWeightSpaceOf] theorem coe_genWeightSpaceOf_zero (x : L) : ↑(genWeightSpaceOf M (0 : R) x) = ⨆ k, LinearMap.ker (toEnd R L M x ^ k) := by simp [genWeightSpaceOf, ← Module.End.iSup_genEigenspace_eq] /-- If `M` is a representation of a nilpotent Lie algebra `L` and `χ : L → R` is a family of scalars, then `genWeightSpace M χ` is the intersection of the maximal generalized `χ x`-eigenspaces of the action of `x` on `M` as `x` ranges over `L`. It is a Lie submodule because `L` is nilpotent. -/ def genWeightSpace (χ : L → R) : LieSubmodule R L M := ⨅ x, genWeightSpaceOf M (χ x) x theorem mem_genWeightSpace (χ : L → R) (m : M) : m ∈ genWeightSpace M χ ↔ ∀ x, ∃ k : ℕ, ((toEnd R L M x - χ x • ↑1) ^ k) m = 0 := by simp [genWeightSpace, mem_genWeightSpaceOf] lemma genWeightSpace_le_genWeightSpaceOf (x : L) (χ : L → R) : genWeightSpace M χ ≤ genWeightSpaceOf M (χ x) x := iInf_le _ x lemma weightSpace_le_genWeightSpace (χ : L → R) : weightSpace M χ ≤ genWeightSpace M χ := by apply le_iInf intro x rw [← (LieSubmodule.toSubmodule_orderEmbedding R L M).le_iff_le] apply (iInf_le _ x).trans exact ((toEnd R L M x).genEigenspace (χ x)).monotone le_top variable (R L) in /-- A weight of a Lie module is a map `L → R` such that the corresponding weight space is non-trivial. -/ structure Weight where /-- The family of eigenvalues corresponding to a weight. -/ toFun : L → R genWeightSpace_ne_bot' : genWeightSpace M toFun ≠ ⊥ namespace Weight instance instFunLike : FunLike (Weight R L M) L R where coe χ := χ.1 coe_injective' χ₁ χ₂ h := by cases χ₁; cases χ₂; simp_all @[simp] lemma coe_weight_mk (χ : L → R) (h) : (↑(⟨χ, h⟩ : Weight R L M) : L → R) = χ := rfl lemma genWeightSpace_ne_bot (χ : Weight R L M) : genWeightSpace M χ ≠ ⊥ := χ.genWeightSpace_ne_bot' variable {M} @[ext] lemma ext {χ₁ χ₂ : Weight R L M} (h : ∀ x, χ₁ x = χ₂ x) : χ₁ = χ₂ := by obtain ⟨f₁, _⟩ := χ₁; obtain ⟨f₂, _⟩ := χ₂; aesop lemma ext_iff' {χ₁ χ₂ : Weight R L M} : (χ₁ : L → R) = χ₂ ↔ χ₁ = χ₂ := by simp lemma exists_ne_zero (χ : Weight R L M) : ∃ x ∈ genWeightSpace M χ, x ≠ 0 := by simpa [LieSubmodule.eq_bot_iff] using χ.genWeightSpace_ne_bot instance [Subsingleton M] : IsEmpty (Weight R L M) := ⟨fun h ↦ h.2 (Subsingleton.elim _ _)⟩ instance [Nontrivial (genWeightSpace M (0 : L → R))] : Zero (Weight R L M) := ⟨0, fun e ↦ not_nontrivial (⊥ : LieSubmodule R L M) (e ▸ ‹_›)⟩ @[simp] lemma coe_zero [Nontrivial (genWeightSpace M (0 : L → R))] : ((0 : Weight R L M) : L → R) = 0 := rfl lemma zero_apply [Nontrivial (genWeightSpace M (0 : L → R))] (x) : (0 : Weight R L M) x = 0 := rfl /-- The proposition that a weight of a Lie module is zero. We make this definition because we cannot define a `Zero (Weight R L M)` instance since the weight space of the zero function can be trivial. -/ def IsZero (χ : Weight R L M) := (χ : L → R) = 0 @[simp] lemma IsZero.eq {χ : Weight R L M} (hχ : χ.IsZero) : (χ : L → R) = 0 := hχ @[simp] lemma coe_eq_zero_iff (χ : Weight R L M) : (χ : L → R) = 0 ↔ χ.IsZero := Iff.rfl lemma isZero_iff_eq_zero [Nontrivial (genWeightSpace M (0 : L → R))] {χ : Weight R L M} : χ.IsZero ↔ χ = 0 := Weight.ext_iff' (χ₂ := 0) lemma isZero_zero [Nontrivial (genWeightSpace M (0 : L → R))] : IsZero (0 : Weight R L M) := rfl /-- The proposition that a weight of a Lie module is non-zero. -/ abbrev IsNonZero (χ : Weight R L M) := ¬ IsZero (χ : Weight R L M) lemma isNonZero_iff_ne_zero [Nontrivial (genWeightSpace M (0 : L → R))] {χ : Weight R L M} : χ.IsNonZero ↔ χ ≠ 0 := isZero_iff_eq_zero.not noncomputable instance : DecidablePred (IsNonZero (R := R) (L := L) (M := M)) := Classical.decPred _ variable (R L M) in /-- The set of weights is equivalent to a subtype. -/ def equivSetOf : Weight R L M ≃ {χ : L → R | genWeightSpace M χ ≠ ⊥} where toFun w := ⟨w.1, w.2⟩ invFun w := ⟨w.1, w.2⟩ left_inv w := by simp right_inv w := by simp lemma genWeightSpaceOf_ne_bot (χ : Weight R L M) (x : L) : genWeightSpaceOf M (χ x) x ≠ ⊥ := by have : ⨅ x, genWeightSpaceOf M (χ x) x ≠ ⊥ := χ.genWeightSpace_ne_bot contrapose! this rw [eq_bot_iff] exact le_of_le_of_eq (iInf_le _ _) this lemma hasEigenvalueAt (χ : Weight R L M) (x : L) : (toEnd R L M x).HasEigenvalue (χ x) := by obtain ⟨k : ℕ, hk : (toEnd R L M x).genEigenspace (χ x) k ≠ ⊥⟩ := by simpa [genWeightSpaceOf, ← Module.End.iSup_genEigenspace_eq] using χ.genWeightSpaceOf_ne_bot x exact Module.End.hasEigenvalue_of_hasGenEigenvalue hk lemma apply_eq_zero_of_isNilpotent [NoZeroSMulDivisors R M] [IsReduced R] (x : L) (h : _root_.IsNilpotent (toEnd R L M x)) (χ : Weight R L M) : χ x = 0 := ((χ.hasEigenvalueAt x).isNilpotent_of_isNilpotent h).eq_zero end Weight /-- See also the more useful form `LieModule.zero_genWeightSpace_eq_top_of_nilpotent`. -/ @[simp] theorem zero_genWeightSpace_eq_top_of_nilpotent' [IsNilpotent L M] : genWeightSpace M (0 : L → R) = ⊤ := by ext simp [genWeightSpace, genWeightSpaceOf] theorem coe_genWeightSpace_of_top (χ : L → R) : (genWeightSpace M (χ ∘ (⊤ : LieSubalgebra R L).incl) : Submodule R M) = genWeightSpace M χ := by ext m simp only [mem_genWeightSpace, LieSubmodule.mem_toSubmodule, Subtype.forall] apply forall_congr' simp @[simp] theorem zero_genWeightSpace_eq_top_of_nilpotent [IsNilpotent L M] : genWeightSpace M (0 : (⊤ : LieSubalgebra R L) → R) = ⊤ := by ext m simp only [mem_genWeightSpace, Pi.zero_apply, zero_smul, sub_zero, Subtype.forall, forall_true_left, LieSubalgebra.toEnd_mk, LieSubalgebra.mem_top, LieSubmodule.mem_top, iff_true] intro x obtain ⟨k, hk⟩ := exists_forall_pow_toEnd_eq_zero R L M exact ⟨k, by simp [hk x]⟩ theorem exists_genWeightSpace_le_ker_of_isNoetherian [IsNoetherian R M] (χ : L → R) (x : L) : ∃ k : ℕ, genWeightSpace M χ ≤ LinearMap.ker ((toEnd R L M x - algebraMap R _ (χ x)) ^ k) := by use (toEnd R L M x).maxGenEigenspaceIndex (χ x) intro m hm replace hm : m ∈ (toEnd R L M x).maxGenEigenspace (χ x) := genWeightSpace_le_genWeightSpaceOf M x χ hm rwa [Module.End.maxGenEigenspace_eq, Module.End.genEigenspace_nat] at hm variable (R) in theorem exists_genWeightSpace_zero_le_ker_of_isNoetherian [IsNoetherian R M] (x : L) : ∃ k : ℕ, genWeightSpace M (0 : L → R) ≤ LinearMap.ker (toEnd R L M x ^ k) := by simpa using exists_genWeightSpace_le_ker_of_isNoetherian M (0 : L → R) x lemma isNilpotent_toEnd_sub_algebraMap [IsNoetherian R M] (χ : L → R) (x : L) : _root_.IsNilpotent <| toEnd R L (genWeightSpace M χ) x - algebraMap R _ (χ x) := by have : toEnd R L (genWeightSpace M χ) x - algebraMap R _ (χ x) = (toEnd R L M x - algebraMap R _ (χ x)).restrict (fun m hm ↦ sub_mem (LieSubmodule.lie_mem _ hm) (Submodule.smul_mem _ _ hm)) := by rfl obtain ⟨k, hk⟩ := exists_genWeightSpace_le_ker_of_isNoetherian M χ x use k ext ⟨m, hm⟩ simp only [this, Module.End.pow_restrict _, LinearMap.zero_apply, ZeroMemClass.coe_zero, ZeroMemClass.coe_eq_zero] exact ZeroMemClass.coe_eq_zero.mp (hk hm) /-- A (nilpotent) Lie algebra acts nilpotently on the zero weight space of a Noetherian Lie module. -/ theorem isNilpotent_toEnd_genWeightSpace_zero [IsNoetherian R M] (x : L) : _root_.IsNilpotent <| toEnd R L (genWeightSpace M (0 : L → R)) x := by simpa using isNilpotent_toEnd_sub_algebraMap M (0 : L → R) x /-- By Engel's theorem, the zero weight space of a Noetherian Lie module is nilpotent. -/ instance [IsNoetherian R M] : IsNilpotent L (genWeightSpace M (0 : L → R)) := isNilpotent_iff_forall'.mpr <| isNilpotent_toEnd_genWeightSpace_zero M variable (R L) @[simp] lemma genWeightSpace_zero_normalizer_eq_self : (genWeightSpace M (0 : L → R)).normalizer = genWeightSpace M 0 := by refine le_antisymm ?_ (LieSubmodule.le_normalizer _) intro m hm rw [LieSubmodule.mem_normalizer] at hm simp only [mem_genWeightSpace, Pi.zero_apply, zero_smul, sub_zero] at hm ⊢ intro y obtain ⟨k, hk⟩ := hm y y use k + 1 simpa [pow_succ, Module.End.mul_eq_comp] lemma iSup_ucs_le_genWeightSpace_zero : ⨆ k, (⊥ : LieSubmodule R L M).ucs k ≤ genWeightSpace M (0 : L → R) := by simpa using LieSubmodule.ucs_le_of_normalizer_eq_self (genWeightSpace_zero_normalizer_eq_self R L M) /-- See also `LieModule.iInf_lowerCentralSeries_eq_posFittingComp`. -/ lemma iSup_ucs_eq_genWeightSpace_zero [IsNoetherian R M] : ⨆ k, (⊥ : LieSubmodule R L M).ucs k = genWeightSpace M (0 : L → R) := by obtain ⟨k, hk⟩ := (LieSubmodule.isNilpotent_iff_exists_self_le_ucs <| genWeightSpace M (0 : L → R)).mp inferInstance refine le_antisymm (iSup_ucs_le_genWeightSpace_zero R L M) (le_trans hk ?_) exact le_iSup (fun k ↦ (⊥ : LieSubmodule R L M).ucs k) k variable {L} /-- If `M` is a representation of a nilpotent Lie algebra `L`, and `x : L`, then `posFittingCompOf R M x` is the infimum of the decreasing system `range φₓ ⊇ range φₓ² ⊇ range φₓ³ ⊇ ⋯` where `φₓ : End R M := toEnd R L M x`. We call this the "positive Fitting component" because with appropriate assumptions (e.g., `R` is a field and `M` is finite-dimensional) `φₓ` induces the so-called Fitting decomposition: `M = M₀ ⊕ M₁` where `M₀ = genWeightSpaceOf M 0 x` and `M₁ = posFittingCompOf R M x`. It is a Lie submodule because `L` is nilpotent. -/ def posFittingCompOf (x : L) : LieSubmodule R L M := { toSubmodule := ⨅ k, LinearMap.range (toEnd R L M x ^ k) lie_mem := by set φ := toEnd R L M x intros y m hm simp only [AddSubsemigroup.mem_carrier, AddSubmonoid.mem_toSubsemigroup, Submodule.mem_toAddSubmonoid, Submodule.mem_iInf, LinearMap.mem_range] at hm ⊢ intro k obtain ⟨N, hN⟩ := LieAlgebra.nilpotent_ad_of_nilpotent_algebra R L obtain ⟨m, rfl⟩ := hm (N + k) let f₁ : Module.End R (L ⊗[R] M) := (LieAlgebra.ad R L x).rTensor M let f₂ : Module.End R (L ⊗[R] M) := φ.lTensor L replace hN : f₁ ^ N = 0 := by ext; simp [f₁, hN] have h₁ : Commute f₁ f₂ := by ext; simp [f₁, f₂] have h₂ : φ ∘ₗ toModuleHom R L M = toModuleHom R L M ∘ₗ (f₁ + f₂) := by ext; simp [φ, f₁, f₂] obtain ⟨q, hq⟩ := h₁.add_pow_dvd_pow_of_pow_eq_zero_right (N + k).le_succ hN use toModuleHom R L M (q (y ⊗ₜ m)) change (φ ^ k).comp ((toModuleHom R L M : L ⊗[R] M →ₗ[R] M)) _ = _ simp [φ, f₁, f₂, Module.End.commute_pow_left_of_commute h₂, LinearMap.comp_apply (g := (f₁ + f₂) ^ k), ← LinearMap.comp_apply (g := q), ← Module.End.mul_eq_comp, ← hq] } variable {M} in lemma mem_posFittingCompOf (x : L) (m : M) : m ∈ posFittingCompOf R M x ↔ ∀ (k : ℕ), ∃ n, (toEnd R L M x ^ k) n = m := by simp [posFittingCompOf] @[simp] lemma posFittingCompOf_le_lowerCentralSeries (x : L) (k : ℕ) : posFittingCompOf R M x ≤ lowerCentralSeries R L M k := by suffices ∀ m l, (toEnd R L M x ^ l) m ∈ lowerCentralSeries R L M l by intro m hm obtain ⟨n, rfl⟩ := (mem_posFittingCompOf R x m).mp hm k exact this n k intro m l induction l with | zero => simp | succ l ih => simp only [lowerCentralSeries_succ, pow_succ', Module.End.mul_apply] exact LieSubmodule.lie_mem_lie (LieSubmodule.mem_top x) ih @[simp] lemma posFittingCompOf_eq_bot_of_isNilpotent [IsNilpotent L M] (x : L) : posFittingCompOf R M x = ⊥ := by simp_rw [eq_bot_iff, ← iInf_lowerCentralSeries_eq_bot_of_isNilpotent, le_iInf_iff, posFittingCompOf_le_lowerCentralSeries, forall_const] variable (L) /-- If `M` is a representation of a nilpotent Lie algebra `L` with coefficients in `R`, then `posFittingComp R L M` is the span of the positive Fitting components of the action of `x` on `M`, as `x` ranges over `L`. It is a Lie submodule because `L` is nilpotent. -/ def posFittingComp : LieSubmodule R L M := ⨆ x, posFittingCompOf R M x lemma mem_posFittingComp (m : M) : m ∈ posFittingComp R L M ↔ m ∈ ⨆ (x : L), posFittingCompOf R M x := by rfl lemma posFittingCompOf_le_posFittingComp (x : L) : posFittingCompOf R M x ≤ posFittingComp R L M := by rw [posFittingComp]; exact le_iSup (posFittingCompOf R M) x lemma posFittingComp_le_iInf_lowerCentralSeries : posFittingComp R L M ≤ ⨅ k, lowerCentralSeries R L M k := by simp [posFittingComp] /-- See also `LieModule.iSup_ucs_eq_genWeightSpace_zero`. -/ @[simp] lemma iInf_lowerCentralSeries_eq_posFittingComp [IsNoetherian R M] [IsArtinian R M] : ⨅ k, lowerCentralSeries R L M k = posFittingComp R L M := by refine le_antisymm ?_ (posFittingComp_le_iInf_lowerCentralSeries R L M) apply iInf_lcs_le_of_isNilpotent_quot rw [LieModule.isNilpotent_iff_forall' (R := R)] intro x obtain ⟨k, hk⟩ := Filter.eventually_atTop.mp (toEnd R L M x).eventually_iInf_range_pow_eq use k ext ⟨m⟩ set F := posFittingComp R L M replace hk : (toEnd R L M x ^ k) m ∈ F := by apply posFittingCompOf_le_posFittingComp R L M x simp_rw [← LieSubmodule.mem_toSubmodule, posFittingCompOf, hk k (le_refl k)] apply LinearMap.mem_range_self suffices (toEnd R L (M ⧸ F) x ^ k) (LieSubmodule.Quotient.mk (N := F) m) = LieSubmodule.Quotient.mk (N := F) ((toEnd R L M x ^ k) m) by simpa [Submodule.Quotient.quot_mk_eq_mk, this] have := LinearMap.congr_fun (Module.End.commute_pow_left_of_commute (LieSubmodule.Quotient.toEnd_comp_mk' F x) k) m simpa using this @[simp] lemma posFittingComp_eq_bot_of_isNilpotent [IsNilpotent L M] : posFittingComp R L M = ⊥ := by simp [posFittingComp] section map_comap variable {R L M} variable {M₂ : Type*} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂] {χ : L → R} (f : M →ₗ⁅R,L⁆ M₂) lemma map_posFittingComp_le : (posFittingComp R L M).map f ≤ posFittingComp R L M₂ := by rw [posFittingComp, posFittingComp, LieSubmodule.map_iSup] refine iSup_mono fun y ↦ LieSubmodule.map_le_iff_le_comap.mpr fun m hm ↦ ?_ simp only [mem_posFittingCompOf] at hm simp only [LieSubmodule.mem_comap, mem_posFittingCompOf] intro k obtain ⟨n, hn⟩ := hm k use f n rw [LieModule.toEnd_pow_apply_map, hn] lemma map_genWeightSpace_le : (genWeightSpace M χ).map f ≤ genWeightSpace M₂ χ := by rw [LieSubmodule.map_le_iff_le_comap] intro m hm simp only [LieSubmodule.mem_comap, mem_genWeightSpace] intro x have : (toEnd R L M₂ x - χ x • ↑1) ∘ₗ f = f ∘ₗ (toEnd R L M x - χ x • ↑1) := by ext; simp obtain ⟨k, h⟩ := (mem_genWeightSpace _ _ _).mp hm x refine ⟨k, ?_⟩ simpa [h] using LinearMap.congr_fun (Module.End.commute_pow_left_of_commute this k) m variable {f} lemma comap_genWeightSpace_eq_of_injective (hf : Injective f) : (genWeightSpace M₂ χ).comap f = genWeightSpace M χ := by refine le_antisymm (fun m hm ↦ ?_) ?_ · simp only [LieSubmodule.mem_comap, mem_genWeightSpace] at hm simp only [mem_genWeightSpace] intro x have h : (toEnd R L M₂ x - χ x • ↑1) ∘ₗ f = f ∘ₗ (toEnd R L M x - χ x • ↑1) := by ext; simp obtain ⟨k, hk⟩ := hm x use k suffices f (((toEnd R L M x - χ x • ↑1) ^ k) m) = 0 by rw [← f.map_zero] at this; exact hf this simpa [hk] using (LinearMap.congr_fun (Module.End.commute_pow_left_of_commute h k) m).symm · rw [← LieSubmodule.map_le_iff_le_comap] exact map_genWeightSpace_le f lemma map_genWeightSpace_eq_of_injective (hf : Injective f) : (genWeightSpace M χ).map f = genWeightSpace M₂ χ ⊓ f.range := by refine le_antisymm (le_inf_iff.mpr ⟨map_genWeightSpace_le f, LieSubmodule.map_le_range f⟩) ?_ rintro - ⟨hm, ⟨m, rfl⟩⟩ simp only [← comap_genWeightSpace_eq_of_injective hf, LieSubmodule.mem_map, LieSubmodule.mem_comap] exact ⟨m, hm, rfl⟩ lemma map_genWeightSpace_eq (e : M ≃ₗ⁅R,L⁆ M₂) : (genWeightSpace M χ).map e = genWeightSpace M₂ χ := by simp [map_genWeightSpace_eq_of_injective e.injective] lemma map_posFittingComp_eq (e : M ≃ₗ⁅R,L⁆ M₂) : (posFittingComp R L M).map e = posFittingComp R L M₂ := by refine le_antisymm (map_posFittingComp_le _) ?_ suffices posFittingComp R L M₂ = ((posFittingComp R L M₂).map (e.symm : M₂ →ₗ⁅R,L⁆ M)).map e by rw [this] exact LieSubmodule.map_mono (map_posFittingComp_le _) rw [← LieSubmodule.map_comp] convert LieSubmodule.map_id ext simp lemma posFittingComp_map_incl_sup_of_codisjoint [IsNoetherian R M] [IsArtinian R M] {N₁ N₂ : LieSubmodule R L M} (h : Codisjoint N₁ N₂) : (posFittingComp R L N₁).map N₁.incl ⊔ (posFittingComp R L N₂).map N₂.incl = posFittingComp R L M := by obtain ⟨l, hl⟩ := Filter.eventually_atTop.mp <| (eventually_iInf_lowerCentralSeries_eq R L N₁).and <| (eventually_iInf_lowerCentralSeries_eq R L N₂).and (eventually_iInf_lowerCentralSeries_eq R L M) obtain ⟨hl₁, hl₂, hl₃⟩ := hl l (le_refl _) simp_rw [← iInf_lowerCentralSeries_eq_posFittingComp, hl₁, hl₂, hl₃, LieSubmodule.lowerCentralSeries_map_eq_lcs, ← LieSubmodule.lcs_sup, lowerCentralSeries, h.eq_top] lemma genWeightSpace_genWeightSpaceOf_map_incl (x : L) (χ : L → R) : (genWeightSpace (genWeightSpaceOf M (χ x) x) χ).map (genWeightSpaceOf M (χ x) x).incl = genWeightSpace M χ := by simpa [map_genWeightSpace_eq_of_injective (genWeightSpaceOf M (χ x) x).injective_incl] using genWeightSpace_le_genWeightSpaceOf M x χ end map_comap section fitting_decomposition variable [IsNoetherian R M] [IsArtinian R M] lemma isCompl_genWeightSpaceOf_zero_posFittingCompOf (x : L) : IsCompl (genWeightSpaceOf M 0 x) (posFittingCompOf R M x) := by simpa only [isCompl_iff, codisjoint_iff, disjoint_iff, ← LieSubmodule.toSubmodule_inj, LieSubmodule.sup_toSubmodule, LieSubmodule.inf_toSubmodule, LieSubmodule.top_toSubmodule, LieSubmodule.bot_toSubmodule, coe_genWeightSpaceOf_zero] using (toEnd R L M x).isCompl_iSup_ker_pow_iInf_range_pow /-- This lemma exists only to simplify the proof of `LieModule.isCompl_genWeightSpace_zero_posFittingComp`. -/ private lemma isCompl_genWeightSpace_zero_posFittingComp_aux (h : ∀ N < (⊤ : LieSubmodule R L M), IsCompl (genWeightSpace N 0) (posFittingComp R L N)) : IsCompl (genWeightSpace M 0) (posFittingComp R L M) := by set M₀ := genWeightSpace M (0 : L → R) set M₁ := posFittingComp R L M rcases forall_or_exists_not (fun (x : L) ↦ genWeightSpaceOf M (0 : R) x = ⊤) with h | ⟨x, hx : genWeightSpaceOf M (0 : R) x ≠ ⊤⟩ · suffices IsNilpotent L M by simp [M₀, M₁, isCompl_top_bot] replace h : M₀ = ⊤ := by simpa [M₀, genWeightSpace] rw [← LieModule.isNilpotent_of_top_iff' (R := R), ← h] infer_instance · set M₀ₓ := genWeightSpaceOf M (0 : R) x set M₁ₓ := posFittingCompOf R M x set M₀ₓ₀ := genWeightSpace M₀ₓ (0 : L → R) set M₀ₓ₁ := posFittingComp R L M₀ₓ have h₁ : IsCompl M₀ₓ M₁ₓ := isCompl_genWeightSpaceOf_zero_posFittingCompOf R L M x have h₂ : IsCompl M₀ₓ₀ M₀ₓ₁ := h M₀ₓ hx.lt_top have h₃ : M₀ₓ₀.map M₀ₓ.incl = M₀ := by rw [map_genWeightSpace_eq_of_injective M₀ₓ.injective_incl, inf_eq_left, LieSubmodule.range_incl] exact iInf_le _ x have h₄ : M₀ₓ₁.map M₀ₓ.incl ⊔ M₁ₓ = M₁ := by apply le_antisymm <| sup_le_iff.mpr ⟨map_posFittingComp_le _, posFittingCompOf_le_posFittingComp R L M x⟩ rw [← posFittingComp_map_incl_sup_of_codisjoint h₁.codisjoint] exact sup_le_sup_left LieSubmodule.map_incl_le _ rw [← h₃, ← h₄] apply Disjoint.isCompl_sup_right_of_isCompl_sup_left · rw [disjoint_iff, ← LieSubmodule.map_inf M₀ₓ.injective_incl, h₂.inf_eq_bot, LieSubmodule.map_bot] · rwa [← LieSubmodule.map_sup, h₂.sup_eq_top, LieModuleHom.map_top, LieSubmodule.range_incl] /-- This is the Fitting decomposition of the Lie module `M`. -/ lemma isCompl_genWeightSpace_zero_posFittingComp : IsCompl (genWeightSpace M 0) (posFittingComp R L M) := by let P : LieSubmodule R L M → Prop := fun N ↦ IsCompl (genWeightSpace N 0) (posFittingComp R L N) suffices P ⊤ by let e := LieModuleEquiv.ofTop R L M rw [← map_genWeightSpace_eq e, ← map_posFittingComp_eq e] exact (LieSubmodule.orderIsoMapComap e).isCompl_iff.mp this refine (LieSubmodule.wellFoundedLT_of_isArtinian R L M).induction (C := P) _ fun N hN ↦ ?_ refine isCompl_genWeightSpace_zero_posFittingComp_aux R L N fun N' hN' ↦ ?_ suffices IsCompl (genWeightSpace (N'.map N.incl) 0) (posFittingComp R L (N'.map N.incl)) by
let e := LieSubmodule.equivMapOfInjective N' N.injective_incl rw [← map_genWeightSpace_eq e, ← map_posFittingComp_eq e] at this exact (LieSubmodule.orderIsoMapComap e).isCompl_iff.mpr this exact hN _ (LieSubmodule.map_incl_lt_iff_lt_top.mpr hN') end fitting_decomposition lemma disjoint_genWeightSpaceOf [NoZeroSMulDivisors R M] {x : L} {φ₁ φ₂ : R} (h : φ₁ ≠ φ₂) : Disjoint (genWeightSpaceOf M φ₁ x) (genWeightSpaceOf M φ₂ x) := by rw [← LieSubmodule.disjoint_toSubmodule] dsimp [genWeightSpaceOf] exact Module.End.disjoint_genEigenspace _ h _ _ lemma disjoint_genWeightSpace [NoZeroSMulDivisors R M] {χ₁ χ₂ : L → R} (h : χ₁ ≠ χ₂) : Disjoint (genWeightSpace M χ₁) (genWeightSpace M χ₂) := by obtain ⟨x, hx⟩ : ∃ x, χ₁ x ≠ χ₂ x := Function.ne_iff.mp h exact (disjoint_genWeightSpaceOf R L M hx).mono (genWeightSpace_le_genWeightSpaceOf M x χ₁) (genWeightSpace_le_genWeightSpaceOf M x χ₂) lemma injOn_genWeightSpace [NoZeroSMulDivisors R M] : InjOn (fun (χ : L → R) ↦ genWeightSpace M χ) {χ | genWeightSpace M χ ≠ ⊥} := by rintro χ₁ _ χ₂ hχ₂ (hχ₁₂ : genWeightSpace M χ₁ = genWeightSpace M χ₂) contrapose! hχ₂ simpa [hχ₁₂] using disjoint_genWeightSpace R L M hχ₂ /-- Lie module weight spaces are independent. See also `LieModule.iSupIndep_genWeightSpace'`. -/ lemma iSupIndep_genWeightSpace [NoZeroSMulDivisors R M] : iSupIndep fun χ : L → R ↦ genWeightSpace M χ := by simp only [← LieSubmodule.iSupIndep_toSubmodule, genWeightSpace, LieSubmodule.iInf_toSubmodule] exact Module.End.independent_iInf_maxGenEigenspace_of_forall_mapsTo (toEnd R L M) (fun x y φ z ↦ (genWeightSpaceOf M φ y).lie_mem) @[deprecated (since := "2024-11-24")] alias independent_genWeightSpace := iSupIndep_genWeightSpace lemma iSupIndep_genWeightSpace' [NoZeroSMulDivisors R M] : iSupIndep fun χ : Weight R L M ↦ genWeightSpace M χ := (iSupIndep_genWeightSpace R L M).comp <| Subtype.val_injective.comp (Weight.equivSetOf R L M).injective @[deprecated (since := "2024-11-24")] alias independent_genWeightSpace' := iSupIndep_genWeightSpace'
Mathlib/Algebra/Lie/Weights/Basic.lean
643
686
/- Copyright (c) 2021 Bhavik Mehta, Yaël Dillies. 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.Fintype.Powerset import Mathlib.Order.Antichain import Mathlib.Order.Interval.Finset.Nat import Mathlib.Algebra.BigOperators.Group.Finset.Basic /-! # `r`-sets and slice This file defines the `r`-th slice of a set family and provides a way to say that a set family is made of `r`-sets. An `r`-set is a finset of cardinality `r` (aka of *size* `r`). The `r`-th slice of a set family is the set family made of its `r`-sets. ## Main declarations * `Set.Sized`: `A.Sized r` means that `A` only contains `r`-sets. * `Finset.slice`: `A.slice r` is the set of `r`-sets in `A`. ## Notation `A # r` is notation for `A.slice r` in locale `finset_family`. -/ open Finset Nat variable {α : Type*} {ι : Sort*} {κ : ι → Sort*} namespace Set variable {A B : Set (Finset α)} {s : Finset α} {r : ℕ} /-! ### Families of `r`-sets -/ /-- `Sized r A` means that every Finset in `A` has size `r`. -/ def Sized (r : ℕ) (A : Set (Finset α)) : Prop := ∀ ⦃x⦄, x ∈ A → #x = r theorem Sized.mono (h : A ⊆ B) (hB : B.Sized r) : A.Sized r := fun _x hx => hB <| h hx @[simp] lemma sized_empty : (∅ : Set (Finset α)).Sized r := by simp [Sized] @[simp] lemma sized_singleton : ({s} : Set (Finset α)).Sized r ↔ #s = r := by simp [Sized] theorem sized_union : (A ∪ B).Sized r ↔ A.Sized r ∧ B.Sized r := ⟨fun hA => ⟨hA.mono subset_union_left, hA.mono subset_union_right⟩, fun hA _x hx => hx.elim (fun h => hA.1 h) fun h => hA.2 h⟩ alias ⟨_, sized.union⟩ := sized_union --TODO: A `forall_iUnion` lemma would be handy here. @[simp] theorem sized_iUnion {f : ι → Set (Finset α)} : (⋃ i, f i).Sized r ↔ ∀ i, (f i).Sized r := by simp_rw [Set.Sized, Set.mem_iUnion, forall_exists_index] exact forall_swap -- `simp` normal form is `sized_iUnion`. theorem sized_iUnion₂ {f : ∀ i, κ i → Set (Finset α)} : (⋃ (i) (j), f i j).Sized r ↔ ∀ i j, (f i j).Sized r := by simp only [Set.sized_iUnion] protected theorem Sized.isAntichain (hA : A.Sized r) : IsAntichain (· ⊆ ·) A := fun _s hs _t ht h hst => h <| Finset.eq_of_subset_of_card_le hst ((hA ht).trans (hA hs).symm).le protected theorem Sized.subsingleton (hA : A.Sized 0) : A.Subsingleton := subsingleton_of_forall_eq ∅ fun _s hs => card_eq_zero.1 <| hA hs theorem Sized.subsingleton' [Fintype α] (hA : A.Sized (Fintype.card α)) : A.Subsingleton := subsingleton_of_forall_eq Finset.univ fun s hs => s.card_eq_iff_eq_univ.1 <| hA hs theorem Sized.empty_mem_iff (hA : A.Sized r) : ∅ ∈ A ↔ A = {∅} := hA.isAntichain.bot_mem_iff theorem Sized.univ_mem_iff [Fintype α] (hA : A.Sized r) : Finset.univ ∈ A ↔ A = {Finset.univ} := hA.isAntichain.top_mem_iff theorem sized_powersetCard (s : Finset α) (r : ℕ) : (powersetCard r s : Set (Finset α)).Sized r := fun _t ht => (mem_powersetCard.1 ht).2 end Set namespace Finset section Sized variable [Fintype α] {𝒜 : Finset (Finset α)} {s : Finset α} {r : ℕ} theorem subset_powersetCard_univ_iff : 𝒜 ⊆ powersetCard r univ ↔ (𝒜 : Set (Finset α)).Sized r := forall_congr' fun A => by rw [mem_powersetCard_univ, mem_coe] alias ⟨_, _root_.Set.Sized.subset_powersetCard_univ⟩ := subset_powersetCard_univ_iff theorem _root_.Set.Sized.card_le (h𝒜 : (𝒜 : Set (Finset α)).Sized r) : #𝒜 ≤ (Fintype.card α).choose r := by rw [Fintype.card, ← card_powersetCard] exact card_le_card (subset_powersetCard_univ_iff.mpr h𝒜) end Sized /-! ### Slices -/
section Slice
Mathlib/Data/Finset/Slice.lean
107
108
/- Copyright (c) 2021 Yaël Dillies. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Yaël Dillies -/ import Mathlib.Order.ConditionallyCompleteLattice.Basic import Mathlib.Order.Cover import Mathlib.Order.Iterate /-! # Successor and predecessor This file defines successor and predecessor orders. `succ a`, the successor of an element `a : α` is the least element greater than `a`. `pred a` is the greatest element less than `a`. Typical examples include `ℕ`, `ℤ`, `ℕ+`, `Fin n`, but also `ENat`, the lexicographic order of a successor/predecessor order... ## Typeclasses * `SuccOrder`: Order equipped with a sensible successor function. * `PredOrder`: Order equipped with a sensible predecessor function. ## Implementation notes Maximal elements don't have a sensible successor. Thus the naïve typeclass ```lean class NaiveSuccOrder (α : Type*) [Preorder α] where (succ : α → α) (succ_le_iff : ∀ {a b}, succ a ≤ b ↔ a < b) (lt_succ_iff : ∀ {a b}, a < succ b ↔ a ≤ b) ``` can't apply to an `OrderTop` because plugging in `a = b = ⊤` into either of `succ_le_iff` and `lt_succ_iff` yields `⊤ < ⊤` (or more generally `m < m` for a maximal element `m`). The solution taken here is to remove the implications `≤ → <` and instead require that `a < succ a` for all non maximal elements (enforced by the combination of `le_succ` and the contrapositive of `max_of_succ_le`). The stricter condition of every element having a sensible successor can be obtained through the combination of `SuccOrder α` and `NoMaxOrder α`. -/ open Function OrderDual Set variable {α β : Type*} /-- Order equipped with a sensible successor function. -/ @[ext] class SuccOrder (α : Type*) [Preorder α] where /-- Successor function -/ succ : α → α /-- Proof of basic ordering with respect to `succ` -/ le_succ : ∀ a, a ≤ succ a /-- Proof of interaction between `succ` and maximal element -/ max_of_succ_le {a} : succ a ≤ a → IsMax a /-- Proof that `succ a` is the least element greater than `a` -/ succ_le_of_lt {a b} : a < b → succ a ≤ b /-- Order equipped with a sensible predecessor function. -/ @[ext] class PredOrder (α : Type*) [Preorder α] where /-- Predecessor function -/ pred : α → α /-- Proof of basic ordering with respect to `pred` -/ pred_le : ∀ a, pred a ≤ a /-- Proof of interaction between `pred` and minimal element -/ min_of_le_pred {a} : a ≤ pred a → IsMin a /-- Proof that `pred b` is the greatest element less than `b` -/ le_pred_of_lt {a b} : a < b → a ≤ pred b instance [Preorder α] [SuccOrder α] : PredOrder αᵒᵈ where pred := toDual ∘ SuccOrder.succ ∘ ofDual pred_le := by simp only [comp, OrderDual.forall, ofDual_toDual, toDual_le_toDual, SuccOrder.le_succ, implies_true] min_of_le_pred h := by apply SuccOrder.max_of_succ_le h le_pred_of_lt := by intro a b h; exact SuccOrder.succ_le_of_lt h instance [Preorder α] [PredOrder α] : SuccOrder αᵒᵈ where succ := toDual ∘ PredOrder.pred ∘ ofDual le_succ := by simp only [comp, OrderDual.forall, ofDual_toDual, toDual_le_toDual, PredOrder.pred_le, implies_true] max_of_succ_le h := by apply PredOrder.min_of_le_pred h succ_le_of_lt := by intro a b h; exact PredOrder.le_pred_of_lt h section Preorder variable [Preorder α] /-- A constructor for `SuccOrder α` usable when `α` has no maximal element. -/ def SuccOrder.ofSuccLeIff (succ : α → α) (hsucc_le_iff : ∀ {a b}, succ a ≤ b ↔ a < b) : SuccOrder α := { succ le_succ := fun _ => (hsucc_le_iff.1 le_rfl).le max_of_succ_le := fun ha => (lt_irrefl _ <| hsucc_le_iff.1 ha).elim succ_le_of_lt := fun h => hsucc_le_iff.2 h } /-- A constructor for `PredOrder α` usable when `α` has no minimal element. -/ def PredOrder.ofLePredIff (pred : α → α) (hle_pred_iff : ∀ {a b}, a ≤ pred b ↔ a < b) : PredOrder α := { pred pred_le := fun _ => (hle_pred_iff.1 le_rfl).le min_of_le_pred := fun ha => (lt_irrefl _ <| hle_pred_iff.1 ha).elim le_pred_of_lt := fun h => hle_pred_iff.2 h } end Preorder section LinearOrder variable [LinearOrder α] /-- A constructor for `SuccOrder α` for `α` a linear order. -/ @[simps] def SuccOrder.ofCore (succ : α → α) (hn : ∀ {a}, ¬IsMax a → ∀ b, a < b ↔ succ a ≤ b) (hm : ∀ a, IsMax a → succ a = a) : SuccOrder α := { succ succ_le_of_lt := fun {a b} => by_cases (fun h hab => (hm a h).symm ▸ hab.le) fun h => (hn h b).mp le_succ := fun a => by_cases (fun h => (hm a h).symm.le) fun h => le_of_lt <| by simpa using (hn h a).not max_of_succ_le := fun {a} => not_imp_not.mp fun h => by simpa using (hn h a).not } /-- A constructor for `PredOrder α` for `α` a linear order. -/ @[simps] def PredOrder.ofCore (pred : α → α) (hn : ∀ {a}, ¬IsMin a → ∀ b, b ≤ pred a ↔ b < a) (hm : ∀ a, IsMin a → pred a = a) : PredOrder α := { pred le_pred_of_lt := fun {a b} => by_cases (fun h hab => (hm b h).symm ▸ hab.le) fun h => (hn h a).mpr pred_le := fun a => by_cases (fun h => (hm a h).le) fun h => le_of_lt <| by simpa using (hn h a).not min_of_le_pred := fun {a} => not_imp_not.mp fun h => by simpa using (hn h a).not } variable (α) open Classical in /-- A well-order is a `SuccOrder`. -/ noncomputable def SuccOrder.ofLinearWellFoundedLT [WellFoundedLT α] : SuccOrder α := ofCore (fun a ↦ if h : (Ioi a).Nonempty then wellFounded_lt.min _ h else a) (fun ha _ ↦ by rw [not_isMax_iff] at ha simp_rw [Set.Nonempty, mem_Ioi, dif_pos ha] exact ⟨(wellFounded_lt.min_le · ha), lt_of_lt_of_le (wellFounded_lt.min_mem _ ha)⟩) fun _ ha ↦ dif_neg (not_not_intro ha <| not_isMax_iff.mpr ·) /-- A linear order with well-founded greater-than relation is a `PredOrder`. -/ noncomputable def PredOrder.ofLinearWellFoundedGT (α) [LinearOrder α] [WellFoundedGT α] : PredOrder α := letI := SuccOrder.ofLinearWellFoundedLT αᵒᵈ; inferInstanceAs (PredOrder αᵒᵈᵒᵈ) end LinearOrder /-! ### Successor order -/ namespace Order section Preorder variable [Preorder α] [SuccOrder α] {a b : α} /-- The successor of an element. If `a` is not maximal, then `succ a` is the least element greater than `a`. If `a` is maximal, then `succ a = a`. -/ def succ : α → α := SuccOrder.succ theorem le_succ : ∀ a : α, a ≤ succ a := SuccOrder.le_succ theorem max_of_succ_le {a : α} : succ a ≤ a → IsMax a := SuccOrder.max_of_succ_le theorem succ_le_of_lt {a b : α} : a < b → succ a ≤ b := SuccOrder.succ_le_of_lt alias _root_.LT.lt.succ_le := succ_le_of_lt @[simp] theorem succ_le_iff_isMax : succ a ≤ a ↔ IsMax a := ⟨max_of_succ_le, fun h => h <| le_succ _⟩ alias ⟨_root_.IsMax.of_succ_le, _root_.IsMax.succ_le⟩ := succ_le_iff_isMax @[simp] theorem lt_succ_iff_not_isMax : a < succ a ↔ ¬IsMax a := ⟨not_isMax_of_lt, fun ha => (le_succ a).lt_of_not_le fun h => ha <| max_of_succ_le h⟩ alias ⟨_, lt_succ_of_not_isMax⟩ := lt_succ_iff_not_isMax theorem wcovBy_succ (a : α) : a ⩿ succ a := ⟨le_succ a, fun _ hb => (succ_le_of_lt hb).not_lt⟩ theorem covBy_succ_of_not_isMax (h : ¬IsMax a) : a ⋖ succ a := (wcovBy_succ a).covBy_of_lt <| lt_succ_of_not_isMax h theorem lt_succ_of_le_of_not_isMax (hab : b ≤ a) (ha : ¬IsMax a) : b < succ a := hab.trans_lt <| lt_succ_of_not_isMax ha theorem succ_le_iff_of_not_isMax (ha : ¬IsMax a) : succ a ≤ b ↔ a < b := ⟨(lt_succ_of_not_isMax ha).trans_le, succ_le_of_lt⟩ lemma succ_lt_succ_of_not_isMax (h : a < b) (hb : ¬ IsMax b) : succ a < succ b := lt_succ_of_le_of_not_isMax (succ_le_of_lt h) hb @[simp, mono, gcongr] theorem succ_le_succ (h : a ≤ b) : succ a ≤ succ b := by by_cases hb : IsMax b · by_cases hba : b ≤ a · exact (hb <| hba.trans <| le_succ _).trans (le_succ _) · exact succ_le_of_lt ((h.lt_of_not_le hba).trans_le <| le_succ b) · rw [succ_le_iff_of_not_isMax fun ha => hb <| ha.mono h] apply lt_succ_of_le_of_not_isMax h hb theorem succ_mono : Monotone (succ : α → α) := fun _ _ => succ_le_succ /-- See also `Order.succ_eq_of_covBy`. -/ lemma le_succ_of_wcovBy (h : a ⩿ b) : b ≤ succ a := by obtain hab | ⟨-, hba⟩ := h.covBy_or_le_and_le · by_contra hba exact h.2 (lt_succ_of_not_isMax hab.lt.not_isMax) <| hab.lt.succ_le.lt_of_not_le hba · exact hba.trans (le_succ _) alias _root_.WCovBy.le_succ := le_succ_of_wcovBy theorem le_succ_iterate (k : ℕ) (x : α) : x ≤ succ^[k] x := id_le_iterate_of_id_le le_succ _ _ theorem isMax_iterate_succ_of_eq_of_lt {n m : ℕ} (h_eq : succ^[n] a = succ^[m] a) (h_lt : n < m) : IsMax (succ^[n] a) := by refine max_of_succ_le (le_trans ?_ h_eq.symm.le) rw [← iterate_succ_apply' succ] have h_le : n + 1 ≤ m := Nat.succ_le_of_lt h_lt exact Monotone.monotone_iterate_of_le_map succ_mono (le_succ a) h_le theorem isMax_iterate_succ_of_eq_of_ne {n m : ℕ} (h_eq : succ^[n] a = succ^[m] a) (h_ne : n ≠ m) : IsMax (succ^[n] a) := by rcases le_total n m with h | h · exact isMax_iterate_succ_of_eq_of_lt h_eq (lt_of_le_of_ne h h_ne) · rw [h_eq] exact isMax_iterate_succ_of_eq_of_lt h_eq.symm (lt_of_le_of_ne h h_ne.symm) theorem Iic_subset_Iio_succ_of_not_isMax (ha : ¬IsMax a) : Iic a ⊆ Iio (succ a) := fun _ => (lt_succ_of_le_of_not_isMax · ha) theorem Ici_succ_of_not_isMax (ha : ¬IsMax a) : Ici (succ a) = Ioi a := Set.ext fun _ => succ_le_iff_of_not_isMax ha theorem Icc_subset_Ico_succ_right_of_not_isMax (hb : ¬IsMax b) : Icc a b ⊆ Ico a (succ b) := by rw [← Ici_inter_Iio, ← Ici_inter_Iic] gcongr intro _ h apply lt_succ_of_le_of_not_isMax h hb theorem Ioc_subset_Ioo_succ_right_of_not_isMax (hb : ¬IsMax b) : Ioc a b ⊆ Ioo a (succ b) := by rw [← Ioi_inter_Iio, ← Ioi_inter_Iic] gcongr intro _ h apply Iic_subset_Iio_succ_of_not_isMax hb h theorem Icc_succ_left_of_not_isMax (ha : ¬IsMax a) : Icc (succ a) b = Ioc a b := by rw [← Ici_inter_Iic, Ici_succ_of_not_isMax ha, Ioi_inter_Iic] theorem Ico_succ_left_of_not_isMax (ha : ¬IsMax a) : Ico (succ a) b = Ioo a b := by rw [← Ici_inter_Iio, Ici_succ_of_not_isMax ha, Ioi_inter_Iio] section NoMaxOrder variable [NoMaxOrder α] theorem lt_succ (a : α) : a < succ a := lt_succ_of_not_isMax <| not_isMax a @[simp] theorem lt_succ_of_le : a ≤ b → a < succ b := (lt_succ_of_le_of_not_isMax · <| not_isMax b) @[simp] theorem succ_le_iff : succ a ≤ b ↔ a < b := succ_le_iff_of_not_isMax <| not_isMax a @[gcongr] theorem succ_lt_succ (hab : a < b) : succ a < succ b := by simp [hab] theorem succ_strictMono : StrictMono (succ : α → α) := fun _ _ => succ_lt_succ theorem covBy_succ (a : α) : a ⋖ succ a := covBy_succ_of_not_isMax <| not_isMax a theorem Iic_subset_Iio_succ (a : α) : Iic a ⊆ Iio (succ a) := by simp @[simp] theorem Ici_succ (a : α) : Ici (succ a) = Ioi a := Ici_succ_of_not_isMax <| not_isMax _ @[simp] theorem Icc_subset_Ico_succ_right (a b : α) : Icc a b ⊆ Ico a (succ b) := Icc_subset_Ico_succ_right_of_not_isMax <| not_isMax _ @[simp] theorem Ioc_subset_Ioo_succ_right (a b : α) : Ioc a b ⊆ Ioo a (succ b) := Ioc_subset_Ioo_succ_right_of_not_isMax <| not_isMax _ @[simp] theorem Icc_succ_left (a b : α) : Icc (succ a) b = Ioc a b := Icc_succ_left_of_not_isMax <| not_isMax _ @[simp] theorem Ico_succ_left (a b : α) : Ico (succ a) b = Ioo a b := Ico_succ_left_of_not_isMax <| not_isMax _ end NoMaxOrder end Preorder section PartialOrder variable [PartialOrder α] [SuccOrder α] {a b : α} @[simp] theorem succ_eq_iff_isMax : succ a = a ↔ IsMax a := ⟨fun h => max_of_succ_le h.le, fun h => h.eq_of_ge <| le_succ _⟩ alias ⟨_, _root_.IsMax.succ_eq⟩ := succ_eq_iff_isMax lemma le_iff_eq_or_succ_le : a ≤ b ↔ a = b ∨ succ a ≤ b := by by_cases ha : IsMax a · simpa [ha.succ_eq] using le_of_eq · rw [succ_le_iff_of_not_isMax ha, le_iff_eq_or_lt] theorem le_le_succ_iff : a ≤ b ∧ b ≤ succ a ↔ b = a ∨ b = succ a := by refine ⟨fun h => or_iff_not_imp_left.2 fun hba : b ≠ a => h.2.antisymm (succ_le_of_lt <| h.1.lt_of_ne <| hba.symm), ?_⟩ rintro (rfl | rfl) · exact ⟨le_rfl, le_succ b⟩ · exact ⟨le_succ a, le_rfl⟩ /-- See also `Order.le_succ_of_wcovBy`. -/ lemma succ_eq_of_covBy (h : a ⋖ b) : succ a = b := (succ_le_of_lt h.lt).antisymm h.wcovBy.le_succ alias _root_.CovBy.succ_eq := succ_eq_of_covBy theorem _root_.OrderIso.map_succ [PartialOrder β] [SuccOrder β] (f : α ≃o β) (a : α) : f (succ a) = succ (f a) := by by_cases h : IsMax a · rw [h.succ_eq, (f.isMax_apply.2 h).succ_eq] · exact (f.map_covBy.2 <| covBy_succ_of_not_isMax h).succ_eq.symm section NoMaxOrder variable [NoMaxOrder α] theorem succ_eq_iff_covBy : succ a = b ↔ a ⋖ b := ⟨by rintro rfl; exact covBy_succ _, CovBy.succ_eq⟩ end NoMaxOrder section OrderTop variable [OrderTop α] @[simp] theorem succ_top : succ (⊤ : α) = ⊤ := by rw [succ_eq_iff_isMax, isMax_iff_eq_top] theorem succ_le_iff_eq_top : succ a ≤ a ↔ a = ⊤ := succ_le_iff_isMax.trans isMax_iff_eq_top theorem lt_succ_iff_ne_top : a < succ a ↔ a ≠ ⊤ := lt_succ_iff_not_isMax.trans not_isMax_iff_ne_top end OrderTop section OrderBot variable [OrderBot α] [Nontrivial α] theorem bot_lt_succ (a : α) : ⊥ < succ a := (lt_succ_of_not_isMax not_isMax_bot).trans_le <| succ_mono bot_le theorem succ_ne_bot (a : α) : succ a ≠ ⊥ := (bot_lt_succ a).ne' end OrderBot end PartialOrder section LinearOrder variable [LinearOrder α] [SuccOrder α] {a b : α} theorem le_of_lt_succ {a b : α} : a < succ b → a ≤ b := fun h ↦ by by_contra! nh exact (h.trans_le (succ_le_of_lt nh)).false theorem lt_succ_iff_of_not_isMax (ha : ¬IsMax a) : b < succ a ↔ b ≤ a := ⟨le_of_lt_succ, fun h => h.trans_lt <| lt_succ_of_not_isMax ha⟩ theorem succ_lt_succ_iff_of_not_isMax (ha : ¬IsMax a) (hb : ¬IsMax b) : succ a < succ b ↔ a < b := by rw [lt_succ_iff_of_not_isMax hb, succ_le_iff_of_not_isMax ha] theorem succ_le_succ_iff_of_not_isMax (ha : ¬IsMax a) (hb : ¬IsMax b) : succ a ≤ succ b ↔ a ≤ b := by rw [succ_le_iff_of_not_isMax ha, lt_succ_iff_of_not_isMax hb] theorem Iio_succ_of_not_isMax (ha : ¬IsMax a) : Iio (succ a) = Iic a := Set.ext fun _ => lt_succ_iff_of_not_isMax ha theorem Ico_succ_right_of_not_isMax (hb : ¬IsMax b) : Ico a (succ b) = Icc a b := by rw [← Ici_inter_Iio, Iio_succ_of_not_isMax hb, Ici_inter_Iic] theorem Ioo_succ_right_of_not_isMax (hb : ¬IsMax b) : Ioo a (succ b) = Ioc a b := by rw [← Ioi_inter_Iio, Iio_succ_of_not_isMax hb, Ioi_inter_Iic] theorem succ_eq_succ_iff_of_not_isMax (ha : ¬IsMax a) (hb : ¬IsMax b) : succ a = succ b ↔ a = b := by rw [eq_iff_le_not_lt, eq_iff_le_not_lt, succ_le_succ_iff_of_not_isMax ha hb, succ_lt_succ_iff_of_not_isMax ha hb] theorem le_succ_iff_eq_or_le : a ≤ succ b ↔ a = succ b ∨ a ≤ b := by by_cases hb : IsMax b · rw [hb.succ_eq, or_iff_right_of_imp le_of_eq] · rw [← lt_succ_iff_of_not_isMax hb, le_iff_eq_or_lt] theorem lt_succ_iff_eq_or_lt_of_not_isMax (hb : ¬IsMax b) : a < succ b ↔ a = b ∨ a < b := (lt_succ_iff_of_not_isMax hb).trans le_iff_eq_or_lt theorem not_isMin_succ [Nontrivial α] (a : α) : ¬ IsMin (succ a) := by obtain ha | ha := (le_succ a).eq_or_lt · exact (ha ▸ succ_eq_iff_isMax.1 ha.symm).not_isMin · exact not_isMin_of_lt ha theorem Iic_succ (a : α) : Iic (succ a) = insert (succ a) (Iic a) := ext fun _ => le_succ_iff_eq_or_le theorem Icc_succ_right (h : a ≤ succ b) : Icc a (succ b) = insert (succ b) (Icc a b) := by simp_rw [← Ici_inter_Iic, Iic_succ, inter_insert_of_mem (mem_Ici.2 h)] theorem Ioc_succ_right (h : a < succ b) : Ioc a (succ b) = insert (succ b) (Ioc a b) := by simp_rw [← Ioi_inter_Iic, Iic_succ, inter_insert_of_mem (mem_Ioi.2 h)] theorem Iio_succ_eq_insert_of_not_isMax (h : ¬IsMax a) : Iio (succ a) = insert a (Iio a) := ext fun _ => lt_succ_iff_eq_or_lt_of_not_isMax h theorem Ico_succ_right_eq_insert_of_not_isMax (h₁ : a ≤ b) (h₂ : ¬IsMax b) : Ico a (succ b) = insert b (Ico a b) := by simp_rw [← Iio_inter_Ici, Iio_succ_eq_insert_of_not_isMax h₂, insert_inter_of_mem (mem_Ici.2 h₁)] theorem Ioo_succ_right_eq_insert_of_not_isMax (h₁ : a < b) (h₂ : ¬IsMax b) : Ioo a (succ b) = insert b (Ioo a b) := by simp_rw [← Iio_inter_Ioi, Iio_succ_eq_insert_of_not_isMax h₂, insert_inter_of_mem (mem_Ioi.2 h₁)] section NoMaxOrder variable [NoMaxOrder α] @[simp] theorem lt_succ_iff : a < succ b ↔ a ≤ b := lt_succ_iff_of_not_isMax <| not_isMax b theorem succ_le_succ_iff : succ a ≤ succ b ↔ a ≤ b := by simp theorem succ_lt_succ_iff : succ a < succ b ↔ a < b := by simp alias ⟨le_of_succ_le_succ, _⟩ := succ_le_succ_iff alias ⟨lt_of_succ_lt_succ, _⟩ := succ_lt_succ_iff -- TODO: prove for a succ-archimedean non-linear order with bottom @[simp] theorem Iio_succ (a : α) : Iio (succ a) = Iic a := Iio_succ_of_not_isMax <| not_isMax _ @[simp] theorem Ico_succ_right (a b : α) : Ico a (succ b) = Icc a b := Ico_succ_right_of_not_isMax <| not_isMax _ -- TODO: prove for a succ-archimedean non-linear order @[simp] theorem Ioo_succ_right (a b : α) : Ioo a (succ b) = Ioc a b := Ioo_succ_right_of_not_isMax <| not_isMax _ @[simp] theorem succ_eq_succ_iff : succ a = succ b ↔ a = b := succ_eq_succ_iff_of_not_isMax (not_isMax a) (not_isMax b) theorem succ_injective : Injective (succ : α → α) := fun _ _ => succ_eq_succ_iff.1 theorem succ_ne_succ_iff : succ a ≠ succ b ↔ a ≠ b := succ_injective.ne_iff alias ⟨_, succ_ne_succ⟩ := succ_ne_succ_iff theorem lt_succ_iff_eq_or_lt : a < succ b ↔ a = b ∨ a < b := lt_succ_iff.trans le_iff_eq_or_lt theorem Iio_succ_eq_insert (a : α) : Iio (succ a) = insert a (Iio a) := Iio_succ_eq_insert_of_not_isMax <| not_isMax a theorem Ico_succ_right_eq_insert (h : a ≤ b) : Ico a (succ b) = insert b (Ico a b) := Ico_succ_right_eq_insert_of_not_isMax h <| not_isMax b theorem Ioo_succ_right_eq_insert (h : a < b) : Ioo a (succ b) = insert b (Ioo a b) := Ioo_succ_right_eq_insert_of_not_isMax h <| not_isMax b @[simp] theorem Ioo_eq_empty_iff_le_succ : Ioo a b = ∅ ↔ b ≤ succ a := by refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩ · contrapose! h exact ⟨succ a, lt_succ_iff_not_isMax.mpr (not_isMax a), h⟩ · ext x suffices a < x → b ≤ x by simpa exact fun hx ↦ le_of_lt_succ <| lt_of_le_of_lt h <| succ_strictMono hx end NoMaxOrder section OrderBot variable [OrderBot α] theorem lt_succ_bot_iff [NoMaxOrder α] : a < succ ⊥ ↔ a = ⊥ := by rw [lt_succ_iff, le_bot_iff] theorem le_succ_bot_iff : a ≤ succ ⊥ ↔ a = ⊥ ∨ a = succ ⊥ := by rw [le_succ_iff_eq_or_le, le_bot_iff, or_comm] end OrderBot end LinearOrder /-- There is at most one way to define the successors in a `PartialOrder`. -/ instance [PartialOrder α] : Subsingleton (SuccOrder α) := ⟨by intro h₀ h₁ ext a by_cases ha : IsMax a · exact (@IsMax.succ_eq _ _ h₀ _ ha).trans ha.succ_eq.symm · exact @CovBy.succ_eq _ _ h₀ _ _ (covBy_succ_of_not_isMax ha)⟩ theorem succ_eq_sInf [CompleteLattice α] [SuccOrder α] (a : α) : succ a = sInf (Set.Ioi a) := by apply (le_sInf fun b => succ_le_of_lt).antisymm obtain rfl | ha := eq_or_ne a ⊤ · rw [succ_top] exact le_top · exact sInf_le (lt_succ_iff_ne_top.2 ha) theorem succ_eq_iInf [CompleteLattice α] [SuccOrder α] (a : α) : succ a = ⨅ b > a, b := by rw [succ_eq_sInf, iInf_subtype', iInf, Subtype.range_coe_subtype, Ioi] theorem succ_eq_csInf [ConditionallyCompleteLattice α] [SuccOrder α] [NoMaxOrder α] (a : α) : succ a = sInf (Set.Ioi a) := by apply (le_csInf nonempty_Ioi fun b => succ_le_of_lt).antisymm exact csInf_le ⟨a, fun b => le_of_lt⟩ <| lt_succ a /-! ### Predecessor order -/ section Preorder variable [Preorder α] [PredOrder α] {a b : α} /-- The predecessor of an element. If `a` is not minimal, then `pred a` is the greatest element less than `a`. If `a` is minimal, then `pred a = a`. -/ def pred : α → α := PredOrder.pred theorem pred_le : ∀ a : α, pred a ≤ a := PredOrder.pred_le theorem min_of_le_pred {a : α} : a ≤ pred a → IsMin a := PredOrder.min_of_le_pred theorem le_pred_of_lt {a b : α} : a < b → a ≤ pred b := PredOrder.le_pred_of_lt alias _root_.LT.lt.le_pred := le_pred_of_lt @[simp] theorem le_pred_iff_isMin : a ≤ pred a ↔ IsMin a := ⟨min_of_le_pred, fun h => h <| pred_le _⟩ alias ⟨_root_.IsMin.of_le_pred, _root_.IsMin.le_pred⟩ := le_pred_iff_isMin @[simp] theorem pred_lt_iff_not_isMin : pred a < a ↔ ¬IsMin a := ⟨not_isMin_of_lt, fun ha => (pred_le a).lt_of_not_le fun h => ha <| min_of_le_pred h⟩ alias ⟨_, pred_lt_of_not_isMin⟩ := pred_lt_iff_not_isMin theorem pred_wcovBy (a : α) : pred a ⩿ a := ⟨pred_le a, fun _ hb nh => (le_pred_of_lt nh).not_lt hb⟩ theorem pred_covBy_of_not_isMin (h : ¬IsMin a) : pred a ⋖ a := (pred_wcovBy a).covBy_of_lt <| pred_lt_of_not_isMin h theorem pred_lt_of_not_isMin_of_le (ha : ¬IsMin a) : a ≤ b → pred a < b := (pred_lt_of_not_isMin ha).trans_le theorem le_pred_iff_of_not_isMin (ha : ¬IsMin a) : b ≤ pred a ↔ b < a := ⟨fun h => h.trans_lt <| pred_lt_of_not_isMin ha, le_pred_of_lt⟩ lemma pred_lt_pred_of_not_isMin (h : a < b) (ha : ¬ IsMin a) : pred a < pred b := pred_lt_of_not_isMin_of_le ha <| le_pred_of_lt h theorem pred_le_pred_of_not_isMin_of_le (ha : ¬IsMin a) (hb : ¬IsMin b) : a ≤ b → pred a ≤ pred b := by rw [le_pred_iff_of_not_isMin hb] apply pred_lt_of_not_isMin_of_le ha @[simp, mono, gcongr] theorem pred_le_pred {a b : α} (h : a ≤ b) : pred a ≤ pred b := succ_le_succ h.dual theorem pred_mono : Monotone (pred : α → α) := fun _ _ => pred_le_pred /-- See also `Order.pred_eq_of_covBy`. -/ lemma pred_le_of_wcovBy (h : a ⩿ b) : pred b ≤ a := by obtain hab | ⟨-, hba⟩ := h.covBy_or_le_and_le · by_contra hba exact h.2 (hab.lt.le_pred.lt_of_not_le hba) (pred_lt_of_not_isMin hab.lt.not_isMin) · exact (pred_le _).trans hba alias _root_.WCovBy.pred_le := pred_le_of_wcovBy theorem pred_iterate_le (k : ℕ) (x : α) : pred^[k] x ≤ x := by conv_rhs => rw [(by simp only [Function.iterate_id, id] : x = id^[k] x)] exact Monotone.iterate_le_of_le pred_mono pred_le k x theorem isMin_iterate_pred_of_eq_of_lt {n m : ℕ} (h_eq : pred^[n] a = pred^[m] a) (h_lt : n < m) : IsMin (pred^[n] a) := @isMax_iterate_succ_of_eq_of_lt αᵒᵈ _ _ _ _ _ h_eq h_lt theorem isMin_iterate_pred_of_eq_of_ne {n m : ℕ} (h_eq : pred^[n] a = pred^[m] a) (h_ne : n ≠ m) : IsMin (pred^[n] a) := @isMax_iterate_succ_of_eq_of_ne αᵒᵈ _ _ _ _ _ h_eq h_ne theorem Ici_subset_Ioi_pred_of_not_isMin (ha : ¬IsMin a) : Ici a ⊆ Ioi (pred a) := fun _ ↦ pred_lt_of_not_isMin_of_le ha theorem Iic_pred_of_not_isMin (ha : ¬IsMin a) : Iic (pred a) = Iio a := Set.ext fun _ => le_pred_iff_of_not_isMin ha theorem Icc_subset_Ioc_pred_left_of_not_isMin (ha : ¬IsMin a) : Icc a b ⊆ Ioc (pred a) b := by rw [← Ioi_inter_Iic, ← Ici_inter_Iic] gcongr apply Ici_subset_Ioi_pred_of_not_isMin ha theorem Ico_subset_Ioo_pred_left_of_not_isMin (ha : ¬IsMin a) : Ico a b ⊆ Ioo (pred a) b := by rw [← Ioi_inter_Iio, ← Ici_inter_Iio] gcongr apply Ici_subset_Ioi_pred_of_not_isMin ha theorem Icc_pred_right_of_not_isMin (ha : ¬IsMin b) : Icc a (pred b) = Ico a b := by rw [← Ici_inter_Iic, Iic_pred_of_not_isMin ha, Ici_inter_Iio] theorem Ioc_pred_right_of_not_isMin (ha : ¬IsMin b) : Ioc a (pred b) = Ioo a b := by rw [← Ioi_inter_Iic, Iic_pred_of_not_isMin ha, Ioi_inter_Iio] section NoMinOrder variable [NoMinOrder α] theorem pred_lt (a : α) : pred a < a := pred_lt_of_not_isMin <| not_isMin a @[simp] theorem pred_lt_of_le : a ≤ b → pred a < b := pred_lt_of_not_isMin_of_le <| not_isMin a @[simp] theorem le_pred_iff : a ≤ pred b ↔ a < b := le_pred_iff_of_not_isMin <| not_isMin b theorem pred_le_pred_of_le : a ≤ b → pred a ≤ pred b := by intro; simp_all theorem pred_lt_pred : a < b → pred a < pred b := by intro; simp_all theorem pred_strictMono : StrictMono (pred : α → α) := fun _ _ => pred_lt_pred theorem pred_covBy (a : α) : pred a ⋖ a := pred_covBy_of_not_isMin <| not_isMin a theorem Ici_subset_Ioi_pred (a : α) : Ici a ⊆ Ioi (pred a) := by simp @[simp] theorem Iic_pred (a : α) : Iic (pred a) = Iio a := Iic_pred_of_not_isMin <| not_isMin a @[simp] theorem Icc_subset_Ioc_pred_left (a b : α) : Icc a b ⊆ Ioc (pred a) b := Icc_subset_Ioc_pred_left_of_not_isMin <| not_isMin _ @[simp] theorem Ico_subset_Ioo_pred_left (a b : α) : Ico a b ⊆ Ioo (pred a) b := Ico_subset_Ioo_pred_left_of_not_isMin <| not_isMin _ @[simp] theorem Icc_pred_right (a b : α) : Icc a (pred b) = Ico a b := Icc_pred_right_of_not_isMin <| not_isMin _ @[simp] theorem Ioc_pred_right (a b : α) : Ioc a (pred b) = Ioo a b := Ioc_pred_right_of_not_isMin <| not_isMin _ end NoMinOrder end Preorder section PartialOrder variable [PartialOrder α] [PredOrder α] {a b : α} @[simp] theorem pred_eq_iff_isMin : pred a = a ↔ IsMin a := ⟨fun h => min_of_le_pred h.ge, fun h => h.eq_of_le <| pred_le _⟩ alias ⟨_, _root_.IsMin.pred_eq⟩ := pred_eq_iff_isMin lemma le_iff_eq_or_le_pred : a ≤ b ↔ a = b ∨ a ≤ pred b := by by_cases hb : IsMin b · simpa [hb.pred_eq] using le_of_eq · rw [le_pred_iff_of_not_isMin hb, le_iff_eq_or_lt] theorem pred_le_le_iff {a b : α} : pred a ≤ b ∧ b ≤ a ↔ b = a ∨ b = pred a := by refine ⟨fun h => or_iff_not_imp_left.2 fun hba : b ≠ a => (le_pred_of_lt <| h.2.lt_of_ne hba).antisymm h.1, ?_⟩ rintro (rfl | rfl) · exact ⟨pred_le b, le_rfl⟩ · exact ⟨le_rfl, pred_le a⟩ /-- See also `Order.pred_le_of_wcovBy`. -/ lemma pred_eq_of_covBy (h : a ⋖ b) : pred b = a := h.wcovBy.pred_le.antisymm (le_pred_of_lt h.lt) alias _root_.CovBy.pred_eq := pred_eq_of_covBy theorem _root_.OrderIso.map_pred {β : Type*} [PartialOrder β] [PredOrder β] (f : α ≃o β) (a : α) : f (pred a) = pred (f a) := f.dual.map_succ a section NoMinOrder variable [NoMinOrder α] theorem pred_eq_iff_covBy : pred b = a ↔ a ⋖ b := ⟨by rintro rfl exact pred_covBy _, CovBy.pred_eq⟩ end NoMinOrder section OrderBot variable [OrderBot α] @[simp] theorem pred_bot : pred (⊥ : α) = ⊥ := isMin_bot.pred_eq theorem le_pred_iff_eq_bot : a ≤ pred a ↔ a = ⊥ := @succ_le_iff_eq_top αᵒᵈ _ _ _ _ theorem pred_lt_iff_ne_bot : pred a < a ↔ a ≠ ⊥ := @lt_succ_iff_ne_top αᵒᵈ _ _ _ _ end OrderBot section OrderTop variable [OrderTop α] [Nontrivial α] theorem pred_lt_top (a : α) : pred a < ⊤ := (pred_mono le_top).trans_lt <| pred_lt_of_not_isMin not_isMin_top theorem pred_ne_top (a : α) : pred a ≠ ⊤ := (pred_lt_top a).ne end OrderTop end PartialOrder section LinearOrder variable [LinearOrder α] [PredOrder α] {a b : α} theorem le_of_pred_lt {a b : α} : pred a < b → a ≤ b := fun h ↦ by by_contra! nh exact le_pred_of_lt nh |>.trans_lt h |>.false theorem pred_lt_iff_of_not_isMin (ha : ¬IsMin a) : pred a < b ↔ a ≤ b := ⟨le_of_pred_lt, (pred_lt_of_not_isMin ha).trans_le⟩ theorem pred_lt_pred_iff_of_not_isMin (ha : ¬IsMin a) (hb : ¬IsMin b) : pred a < pred b ↔ a < b := by rw [pred_lt_iff_of_not_isMin ha, le_pred_iff_of_not_isMin hb] theorem pred_le_pred_iff_of_not_isMin (ha : ¬IsMin a) (hb : ¬IsMin b) : pred a ≤ pred b ↔ a ≤ b := by rw [le_pred_iff_of_not_isMin hb, pred_lt_iff_of_not_isMin ha] theorem Ioi_pred_of_not_isMin (ha : ¬IsMin a) : Ioi (pred a) = Ici a := Set.ext fun _ => pred_lt_iff_of_not_isMin ha theorem Ioc_pred_left_of_not_isMin (ha : ¬IsMin a) : Ioc (pred a) b = Icc a b := by rw [← Ioi_inter_Iic, Ioi_pred_of_not_isMin ha, Ici_inter_Iic] theorem Ioo_pred_left_of_not_isMin (ha : ¬IsMin a) : Ioo (pred a) b = Ico a b := by rw [← Ioi_inter_Iio, Ioi_pred_of_not_isMin ha, Ici_inter_Iio] theorem pred_eq_pred_iff_of_not_isMin (ha : ¬IsMin a) (hb : ¬IsMin b) : pred a = pred b ↔ a = b := by rw [eq_iff_le_not_lt, eq_iff_le_not_lt, pred_le_pred_iff_of_not_isMin ha hb, pred_lt_pred_iff_of_not_isMin ha hb] theorem pred_le_iff_eq_or_le : pred a ≤ b ↔ b = pred a ∨ a ≤ b := by by_cases ha : IsMin a · rw [ha.pred_eq, or_iff_right_of_imp ge_of_eq] · rw [← pred_lt_iff_of_not_isMin ha, le_iff_eq_or_lt, eq_comm] theorem pred_lt_iff_eq_or_lt_of_not_isMin (ha : ¬IsMin a) : pred a < b ↔ a = b ∨ a < b := (pred_lt_iff_of_not_isMin ha).trans le_iff_eq_or_lt theorem not_isMax_pred [Nontrivial α] (a : α) : ¬ IsMax (pred a) := not_isMin_succ (α := αᵒᵈ) a theorem Ici_pred (a : α) : Ici (pred a) = insert (pred a) (Ici a) := ext fun _ => pred_le_iff_eq_or_le theorem Ioi_pred_eq_insert_of_not_isMin (ha : ¬IsMin a) : Ioi (pred a) = insert a (Ioi a) := by ext x; simp only [insert, mem_setOf, @eq_comm _ x a, mem_Ioi, Set.insert] exact pred_lt_iff_eq_or_lt_of_not_isMin ha theorem Icc_pred_left (h : pred a ≤ b) : Icc (pred a) b = insert (pred a) (Icc a b) := by simp_rw [← Ici_inter_Iic, Ici_pred, insert_inter_of_mem (mem_Iic.2 h)] theorem Ico_pred_left (h : pred a < b) : Ico (pred a) b = insert (pred a) (Ico a b) := by simp_rw [← Ici_inter_Iio, Ici_pred, insert_inter_of_mem (mem_Iio.2 h)] section NoMinOrder variable [NoMinOrder α] @[simp] theorem pred_lt_iff : pred a < b ↔ a ≤ b := pred_lt_iff_of_not_isMin <| not_isMin a theorem pred_le_pred_iff : pred a ≤ pred b ↔ a ≤ b := by simp theorem pred_lt_pred_iff : pred a < pred b ↔ a < b := by simp alias ⟨le_of_pred_le_pred, _⟩ := pred_le_pred_iff alias ⟨lt_of_pred_lt_pred, _⟩ := pred_lt_pred_iff -- TODO: prove for a pred-archimedean non-linear order with top @[simp] theorem Ioi_pred (a : α) : Ioi (pred a) = Ici a := Ioi_pred_of_not_isMin <| not_isMin a @[simp] theorem Ioc_pred_left (a b : α) : Ioc (pred a) b = Icc a b := Ioc_pred_left_of_not_isMin <| not_isMin _ -- TODO: prove for a pred-archimedean non-linear order @[simp] theorem Ioo_pred_left (a b : α) : Ioo (pred a) b = Ico a b := Ioo_pred_left_of_not_isMin <| not_isMin _ @[simp] theorem pred_eq_pred_iff : pred a = pred b ↔ a = b := by simp_rw [eq_iff_le_not_lt, pred_le_pred_iff, pred_lt_pred_iff] theorem pred_injective : Injective (pred : α → α) := fun _ _ => pred_eq_pred_iff.1 theorem pred_ne_pred_iff : pred a ≠ pred b ↔ a ≠ b := pred_injective.ne_iff alias ⟨_, pred_ne_pred⟩ := pred_ne_pred_iff
theorem pred_lt_iff_eq_or_lt : pred a < b ↔ a = b ∨ a < b := pred_lt_iff.trans le_iff_eq_or_lt theorem Ioi_pred_eq_insert (a : α) : Ioi (pred a) = insert a (Ioi a) :=
Mathlib/Order/SuccPred/Basic.lean
880
883
/- Copyright (c) 2019 Minchao Wu. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Minchao Wu, Chris Hughes, Mantas Bakšys -/ import Mathlib.Data.List.Basic import Mathlib.Order.BoundedOrder.Lattice import Mathlib.Data.List.Induction import Mathlib.Order.MinMax import Mathlib.Order.WithBot /-! # Minimum and maximum of lists ## Main definitions The main definitions are `argmax`, `argmin`, `minimum` and `maximum` for lists. `argmax f l` returns `some a`, where `a` of `l` that maximises `f a`. If there are `a b` such that `f a = f b`, it returns whichever of `a` or `b` comes first in the list. `argmax f [] = none` `minimum l` returns a `WithTop α`, the smallest element of `l` for nonempty lists, and `⊤` for `[]` -/ namespace List variable {α β : Type*} section ArgAux variable (r : α → α → Prop) [DecidableRel r] {l : List α} {o : Option α} {a : α} /-- Auxiliary definition for `argmax` and `argmin`. -/ def argAux (a : Option α) (b : α) : Option α := Option.casesOn a (some b) fun c => if r b c then some b else some c @[simp] theorem foldl_argAux_eq_none : l.foldl (argAux r) o = none ↔ l = [] ∧ o = none := List.reverseRecOn l (by simp) fun tl hd => by simp only [foldl_append, foldl_cons, argAux, foldl_nil, append_eq_nil_iff, and_false, false_and, iff_false] cases foldl (argAux r) o tl · simp · simp only [false_iff, not_and] split_ifs <;> simp private theorem foldl_argAux_mem (l) : ∀ a m : α, m ∈ foldl (argAux r) (some a) l → m ∈ a :: l := List.reverseRecOn l (by simp [eq_comm]) (by intro tl hd ih a m simp only [foldl_append, foldl_cons, foldl_nil, argAux] cases hf : foldl (argAux r) (some a) tl · simp +contextual · dsimp only split_ifs · simp +contextual · -- `finish [ih _ _ hf]` closes this goal simp only [List.mem_cons] at ih rcases ih _ _ hf with rfl | H · simp +contextual only [Option.mem_def, Option.some.injEq, find?, eq_comm, mem_cons, mem_append, mem_singleton, true_or, implies_true] · simp +contextual [@eq_comm _ _ m, H]) @[simp] theorem argAux_self (hr₀ : Irreflexive r) (a : α) : argAux r (some a) a = a := if_neg <| hr₀ _ theorem not_of_mem_foldl_argAux (hr₀ : Irreflexive r) (hr₁ : Transitive r) : ∀ {a m : α} {o : Option α}, a ∈ l → m ∈ foldl (argAux r) o l → ¬r a m := by induction' l using List.reverseRecOn with tl a ih · simp intro b m o hb ho rw [foldl_append, foldl_cons, foldl_nil, argAux] at ho rcases hf : foldl (argAux r) o tl with - | c · rw [hf] at ho rw [foldl_argAux_eq_none] at hf simp_all [hf.1, hf.2, hr₀ _] rw [hf, Option.mem_def] at ho dsimp only at ho split_ifs at ho with hac <;> rcases mem_append.1 hb with h | h <;> injection ho with ho <;> subst ho · exact fun hba => ih h hf (hr₁ hba hac) · simp_all [hr₀ _] · exact ih h hf · simp_all end ArgAux section Preorder variable [Preorder β] [DecidableLT β] {f : α → β} {l : List α} {a m : α} /-- `argmax f l` returns `some a`, where `f a` is maximal among the elements of `l`, in the sense that there is no `b ∈ l` with `f a < f b`. If `a`, `b` are such that `f a = f b`, it returns whichever of `a` or `b` comes first in the list. `argmax f [] = none`. -/ def argmax (f : α → β) (l : List α) : Option α := l.foldl (argAux fun b c => f c < f b) none /-- `argmin f l` returns `some a`, where `f a` is minimal among the elements of `l`, in the sense that there is no `b ∈ l` with `f b < f a`. If `a`, `b` are such that `f a = f b`, it returns whichever of `a` or `b` comes first in the list. `argmin f [] = none`. -/ def argmin (f : α → β) (l : List α) := l.foldl (argAux fun b c => f b < f c) none @[simp] theorem argmax_nil (f : α → β) : argmax f [] = none := rfl @[simp] theorem argmin_nil (f : α → β) : argmin f [] = none := rfl @[simp] theorem argmax_singleton {f : α → β} {a : α} : argmax f [a] = a := rfl @[simp] theorem argmin_singleton {f : α → β} {a : α} : argmin f [a] = a := rfl theorem not_lt_of_mem_argmax : a ∈ l → m ∈ argmax f l → ¬f m < f a := not_of_mem_foldl_argAux _ (fun x h => lt_irrefl (f x) h) (fun _ _ z hxy hyz => lt_trans (a := f z) hyz hxy) theorem not_lt_of_mem_argmin : a ∈ l → m ∈ argmin f l → ¬f a < f m := not_of_mem_foldl_argAux _ (fun x h => lt_irrefl (f x) h) (fun x _ _ hxy hyz => lt_trans (a := f x) hxy hyz) theorem argmax_concat (f : α → β) (a : α) (l : List α) : argmax f (l ++ [a]) = Option.casesOn (argmax f l) (some a) fun c => if f c < f a then some a else some c := by rw [argmax, argmax]; simp [argAux] theorem argmin_concat (f : α → β) (a : α) (l : List α) : argmin f (l ++ [a]) = Option.casesOn (argmin f l) (some a) fun c => if f a < f c then some a else some c := @argmax_concat _ βᵒᵈ _ _ _ _ _ theorem argmax_mem : ∀ {l : List α} {m : α}, m ∈ argmax f l → m ∈ l | [], m => by simp | hd :: tl, m => by simpa [argmax, argAux] using foldl_argAux_mem _ tl hd m theorem argmin_mem : ∀ {l : List α} {m : α}, m ∈ argmin f l → m ∈ l := @argmax_mem _ βᵒᵈ _ _ _ @[simp] theorem argmax_eq_none : l.argmax f = none ↔ l = [] := by simp [argmax] @[simp] theorem argmin_eq_none : l.argmin f = none ↔ l = [] := @argmax_eq_none _ βᵒᵈ _ _ _ _ end Preorder section LinearOrder variable [LinearOrder β] {f : α → β} {l : List α} {a m : α} theorem le_of_mem_argmax : a ∈ l → m ∈ argmax f l → f a ≤ f m := fun ha hm => le_of_not_lt <| not_lt_of_mem_argmax ha hm theorem le_of_mem_argmin : a ∈ l → m ∈ argmin f l → f m ≤ f a := @le_of_mem_argmax _ βᵒᵈ _ _ _ _ _ theorem argmax_cons (f : α → β) (a : α) (l : List α) : argmax f (a :: l) = Option.casesOn (argmax f l) (some a) fun c => if f a < f c then some c else some a := List.reverseRecOn l rfl fun hd tl ih => by rw [← cons_append, argmax_concat, ih, argmax_concat] rcases h : argmax f hd with - | m · simp [h] dsimp rw [← apply_ite, ← apply_ite] dsimp split_ifs <;> try rfl · exact absurd (lt_trans ‹f a < f m› ‹_›) ‹_› · cases (‹f a < f tl›.lt_or_lt _).elim ‹_› ‹_› theorem argmin_cons (f : α → β) (a : α) (l : List α) : argmin f (a :: l) = Option.casesOn (argmin f l) (some a) fun c => if f c < f a then some c else some a := @argmax_cons α βᵒᵈ _ _ _ _ variable [DecidableEq α] theorem index_of_argmax : ∀ {l : List α} {m : α}, m ∈ argmax f l → ∀ {a}, a ∈ l → f m ≤ f a → l.idxOf m ≤ l.idxOf a | [], m, _, _, _, _ => by simp | hd :: tl, m, hm, a, ha, ham => by simp only [idxOf_cons, argmax_cons, Option.mem_def] at hm ⊢ cases h : argmax f tl · rw [h] at hm simp_all rw [h] at hm dsimp only at hm simp only [cond_eq_if, beq_iff_eq] obtain ha | ha := ha <;> split_ifs at hm <;> injection hm with hm <;> subst hm · cases not_le_of_lt ‹_› ‹_› · rw [if_pos rfl] · rw [if_neg, if_neg] · exact Nat.succ_le_succ (index_of_argmax h (by assumption) ham) · exact ne_of_apply_ne f (lt_of_lt_of_le ‹_› ‹_›).ne · exact ne_of_apply_ne _ ‹f hd < f _›.ne · rw [if_pos rfl] exact Nat.zero_le _ theorem index_of_argmin : ∀ {l : List α} {m : α}, m ∈ argmin f l → ∀ {a}, a ∈ l → f a ≤ f m → l.idxOf m ≤ l.idxOf a := @index_of_argmax _ βᵒᵈ _ _ _ theorem mem_argmax_iff : m ∈ argmax f l ↔ m ∈ l ∧ (∀ a ∈ l, f a ≤ f m) ∧ ∀ a ∈ l, f m ≤ f a → l.idxOf m ≤ l.idxOf a := ⟨fun hm => ⟨argmax_mem hm, fun _ ha => le_of_mem_argmax ha hm, fun _ => index_of_argmax hm⟩, by rintro ⟨hml, ham, hma⟩ rcases harg : argmax f l with - | n · simp_all · have := _root_.le_antisymm (hma n (argmax_mem harg) (le_of_mem_argmax hml harg)) (index_of_argmax harg hml (ham _ (argmax_mem harg))) rw [(idxOf_inj hml (argmax_mem harg)).1 this, Option.mem_def]⟩ theorem argmax_eq_some_iff : argmax f l = some m ↔ m ∈ l ∧ (∀ a ∈ l, f a ≤ f m) ∧ ∀ a ∈ l, f m ≤ f a → l.idxOf m ≤ l.idxOf a := mem_argmax_iff theorem mem_argmin_iff : m ∈ argmin f l ↔ m ∈ l ∧ (∀ a ∈ l, f m ≤ f a) ∧ ∀ a ∈ l, f a ≤ f m → l.idxOf m ≤ l.idxOf a := @mem_argmax_iff _ βᵒᵈ _ _ _ _ _ theorem argmin_eq_some_iff : argmin f l = some m ↔ m ∈ l ∧ (∀ a ∈ l, f m ≤ f a) ∧ ∀ a ∈ l, f a ≤ f m → l.idxOf m ≤ l.idxOf a := mem_argmin_iff end LinearOrder section MaximumMinimum section Preorder variable [Preorder α] [DecidableLT α] {l : List α} {a m : α} /-- `maximum l` returns a `WithBot α`, the largest element of `l` for nonempty lists, and `⊥` for `[]` -/ def maximum (l : List α) : WithBot α := argmax id l /-- `minimum l` returns a `WithTop α`, the smallest element of `l` for nonempty lists, and `⊤` for `[]` -/ def minimum (l : List α) : WithTop α := argmin id l @[simp] theorem maximum_nil : maximum ([] : List α) = ⊥ := rfl @[simp] theorem minimum_nil : minimum ([] : List α) = ⊤ := rfl @[simp] theorem maximum_singleton (a : α) : maximum [a] = a := rfl @[simp] theorem minimum_singleton (a : α) : minimum [a] = a := rfl theorem maximum_mem {l : List α} {m : α} : (maximum l : WithTop α) = m → m ∈ l := argmax_mem theorem minimum_mem {l : List α} {m : α} : (minimum l : WithBot α) = m → m ∈ l := argmin_mem @[simp] theorem maximum_eq_bot {l : List α} : l.maximum = ⊥ ↔ l = [] := argmax_eq_none @[simp] theorem minimum_eq_top {l : List α} : l.minimum = ⊤ ↔ l = [] := argmin_eq_none theorem not_maximum_lt_of_mem : a ∈ l → (maximum l : WithBot α) = m → ¬m < a := not_lt_of_mem_argmax @[deprecated (since := "2024-12-29")] alias not_lt_maximum_of_mem := not_maximum_lt_of_mem theorem not_lt_minimum_of_mem : a ∈ l → (minimum l : WithTop α) = m → ¬a < m := not_lt_of_mem_argmin @[deprecated (since := "2024-12-29")] alias minimum_not_lt_of_mem := not_lt_minimum_of_mem theorem not_maximum_lt_of_mem' (ha : a ∈ l) : ¬maximum l < (a : WithBot α) := by cases h : l.maximum <;> simp_all [not_maximum_lt_of_mem ha] @[deprecated (since := "2024-12-29")] alias not_lt_maximum_of_mem' := not_maximum_lt_of_mem' theorem not_lt_minimum_of_mem' (ha : a ∈ l) : ¬(a : WithTop α) < minimum l := by cases h : l.minimum <;> simp_all [not_lt_minimum_of_mem ha] end Preorder section LinearOrder variable [LinearOrder α] {l : List α} {a m : α} theorem maximum_concat (a : α) (l : List α) : maximum (l ++ [a]) = max (maximum l) a := by simp only [maximum, argmax_concat, id] cases argmax id l · exact (max_eq_right bot_le).symm · simp [WithBot.some_eq_coe, max_def_lt, WithBot.coe_lt_coe] theorem le_maximum_of_mem : a ∈ l → (maximum l : WithBot α) = m → a ≤ m := le_of_mem_argmax theorem minimum_le_of_mem : a ∈ l → (minimum l : WithTop α) = m → m ≤ a := le_of_mem_argmin theorem le_maximum_of_mem' (ha : a ∈ l) : (a : WithBot α) ≤ maximum l := le_of_not_lt <| not_maximum_lt_of_mem' ha theorem minimum_le_of_mem' (ha : a ∈ l) : minimum l ≤ (a : WithTop α) := le_of_not_lt <| not_lt_minimum_of_mem' ha theorem minimum_concat (a : α) (l : List α) : minimum (l ++ [a]) = min (minimum l) a := @maximum_concat αᵒᵈ _ _ _ theorem maximum_cons (a : α) (l : List α) : maximum (a :: l) = max ↑a (maximum l) := List.reverseRecOn l (by simp [@max_eq_left (WithBot α) _ _ _ bot_le]) fun tl hd ih => by rw [← cons_append, maximum_concat, ih, maximum_concat, max_assoc] theorem minimum_cons (a : α) (l : List α) : minimum (a :: l) = min ↑a (minimum l) := @maximum_cons αᵒᵈ _ _ _ lemma maximum_append (l₁ l₂ : List α) : (l₁ ++ l₂).maximum = max l₁.maximum l₂.maximum := by induction l₁ with | nil => simp | cons _ _ ih => rw [maximum_cons, cons_append, maximum_cons, ih, ← max_assoc] lemma minimum_append (l₁ l₂ : List α) : (l₁ ++ l₂).minimum = min l₁.minimum l₂.minimum := @maximum_append αᵒᵈ _ _ _ theorem maximum_le_of_forall_le {b : WithBot α} (h : ∀ a ∈ l, a ≤ b) : l.maximum ≤ b := by induction l with | nil => simp | cons a l ih => simp only [maximum_cons, max_le_iff] exact ⟨h a (by simp), ih fun a w => h a (mem_cons.mpr (Or.inr w))⟩ theorem le_minimum_of_forall_le {b : WithTop α} (h : ∀ a ∈ l, b ≤ a) : b ≤ l.minimum := by induction l with | nil => simp | cons a l ih => simp only [minimum_cons, le_min_iff] exact ⟨h a (by simp), ih fun a w => h a (mem_cons.mpr (Or.inr w))⟩ theorem maximum_mono {l₁ l₂ : List α} (h : l₁ ⊆ l₂) : l₁.maximum ≤ l₂.maximum := maximum_le_of_forall_le fun _ ↦ (le_maximum_of_mem' <| h ·) theorem minimum_anti {l₁ l₂ : List α} (h : l₁ ⊆ l₂) : l₂.minimum ≤ l₁.minimum := @maximum_mono αᵒᵈ _ _ _ h theorem maximum_eq_coe_iff : maximum l = m ↔ m ∈ l ∧ ∀ a ∈ l, a ≤ m := by rw [maximum, ← WithBot.some_eq_coe, argmax_eq_some_iff] simp only [id_eq, and_congr_right_iff, and_iff_left_iff_imp] intro _ h a hal hma rw [_root_.le_antisymm hma (h a hal)] theorem minimum_eq_coe_iff : minimum l = m ↔ m ∈ l ∧ ∀ a ∈ l, m ≤ a := @maximum_eq_coe_iff αᵒᵈ _ _ _ theorem coe_le_maximum_iff : a ≤ l.maximum ↔ ∃ b, b ∈ l ∧ a ≤ b := by induction' l <;> simp [maximum_cons, *] theorem minimum_le_coe_iff : l.minimum ≤ a ↔ ∃ b, b ∈ l ∧ b ≤ a := by induction' l <;> simp [minimum_cons, *] theorem maximum_ne_bot_of_ne_nil (h : l ≠ []) : l.maximum ≠ ⊥ := match l, h with | _ :: _, _ => by simp [maximum_cons] theorem minimum_ne_top_of_ne_nil (h : l ≠ []) : l.minimum ≠ ⊤ := @maximum_ne_bot_of_ne_nil αᵒᵈ _ _ h
theorem maximum_ne_bot_of_length_pos (h : 0 < l.length) : l.maximum ≠ ⊥ := match l, h with | _ :: _, _ => by simp [maximum_cons] theorem minimum_ne_top_of_length_pos (h : 0 < l.length) : l.minimum ≠ ⊤ := maximum_ne_bot_of_length_pos (α := αᵒᵈ) h
Mathlib/Data/List/MinMax.lean
389
394
/- 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 -/ import Mathlib.Data.Finset.Basic import Mathlib.Data.Finset.Image /-! # Cardinality of a finite set This defines the cardinality of a `Finset` and provides induction principles for finsets. ## Main declarations * `Finset.card`: `#s : ℕ` returns the cardinality of `s : Finset α`. ### Induction principles * `Finset.strongInduction`: Strong induction * `Finset.strongInductionOn` * `Finset.strongDownwardInduction` * `Finset.strongDownwardInductionOn` * `Finset.case_strong_induction_on` * `Finset.Nonempty.strong_induction` -/ assert_not_exists Monoid open Function Multiset Nat variable {α β R : Type*} namespace Finset variable {s t : Finset α} {a b : α} /-- `s.card` is the number of elements of `s`, aka its cardinality. The notation `#s` can be accessed in the `Finset` locale. -/ def card (s : Finset α) : ℕ := Multiset.card s.1 @[inherit_doc] scoped prefix:arg "#" => Finset.card theorem card_def (s : Finset α) : #s = Multiset.card s.1 := rfl @[simp] lemma card_val (s : Finset α) : Multiset.card s.1 = #s := rfl @[simp] theorem card_mk {m nodup} : #(⟨m, nodup⟩ : Finset α) = Multiset.card m := rfl @[simp] theorem card_empty : #(∅ : Finset α) = 0 := rfl @[gcongr] theorem card_le_card : s ⊆ t → #s ≤ #t := Multiset.card_le_card ∘ val_le_iff.mpr @[mono] theorem card_mono : Monotone (@card α) := by apply card_le_card @[simp] lemma card_eq_zero : #s = 0 ↔ s = ∅ := Multiset.card_eq_zero.trans val_eq_zero lemma card_ne_zero : #s ≠ 0 ↔ s.Nonempty := card_eq_zero.ne.trans nonempty_iff_ne_empty.symm @[simp] lemma card_pos : 0 < #s ↔ s.Nonempty := Nat.pos_iff_ne_zero.trans card_ne_zero @[simp] lemma one_le_card : 1 ≤ #s ↔ s.Nonempty := card_pos alias ⟨_, Nonempty.card_pos⟩ := card_pos alias ⟨_, Nonempty.card_ne_zero⟩ := card_ne_zero theorem card_ne_zero_of_mem (h : a ∈ s) : #s ≠ 0 := (not_congr card_eq_zero).2 <| ne_empty_of_mem h @[simp] theorem card_singleton (a : α) : #{a} = 1 := Multiset.card_singleton _ theorem card_singleton_inter [DecidableEq α] : #({a} ∩ s) ≤ 1 := by obtain h | h := Finset.decidableMem a s · simp [Finset.singleton_inter_of_not_mem h] · simp [Finset.singleton_inter_of_mem h] @[simp] theorem card_cons (h : a ∉ s) : #(s.cons a h) = #s + 1 := Multiset.card_cons _ _ section InsertErase variable [DecidableEq α] @[simp] theorem card_insert_of_not_mem (h : a ∉ s) : #(insert a s) = #s + 1 := by rw [← cons_eq_insert _ _ h, card_cons] theorem card_insert_of_mem (h : a ∈ s) : #(insert a s) = #s := by rw [insert_eq_of_mem h] theorem card_insert_le (a : α) (s : Finset α) : #(insert a s) ≤ #s + 1 := by by_cases h : a ∈ s · rw [insert_eq_of_mem h] exact Nat.le_succ _ · rw [card_insert_of_not_mem h] section variable {a b c d e f : α} theorem card_le_two : #{a, b} ≤ 2 := card_insert_le _ _ theorem card_le_three : #{a, b, c} ≤ 3 := (card_insert_le _ _).trans (Nat.succ_le_succ card_le_two) theorem card_le_four : #{a, b, c, d} ≤ 4 := (card_insert_le _ _).trans (Nat.succ_le_succ card_le_three) theorem card_le_five : #{a, b, c, d, e} ≤ 5 := (card_insert_le _ _).trans (Nat.succ_le_succ card_le_four) theorem card_le_six : #{a, b, c, d, e, f} ≤ 6 := (card_insert_le _ _).trans (Nat.succ_le_succ card_le_five) end /-- If `a ∈ s` is known, see also `Finset.card_insert_of_mem` and `Finset.card_insert_of_not_mem`. -/ theorem card_insert_eq_ite : #(insert a s) = if a ∈ s then #s else #s + 1 := by by_cases h : a ∈ s · rw [card_insert_of_mem h, if_pos h] · rw [card_insert_of_not_mem h, if_neg h] @[simp] theorem card_pair_eq_one_or_two : #{a, b} = 1 ∨ #{a, b} = 2 := by simp [card_insert_eq_ite] tauto @[simp] theorem card_pair (h : a ≠ b) : #{a, b} = 2 := by rw [card_insert_of_not_mem (not_mem_singleton.2 h), card_singleton] /-- $\#(s \setminus \{a\}) = \#s - 1$ if $a \in s$. -/ @[simp] theorem card_erase_of_mem : a ∈ s → #(s.erase a) = #s - 1 := Multiset.card_erase_of_mem @[simp] theorem card_erase_add_one : a ∈ s → #(s.erase a) + 1 = #s := Multiset.card_erase_add_one
theorem card_erase_lt_of_mem : a ∈ s → #(s.erase a) < #s := Multiset.card_erase_lt_of_mem
Mathlib/Data/Finset/Card.lean
151
153
/- Copyright (c) 2020 Kenny Lau. All rights reserved. Released under Apache 2.0 license as described in the file LICENSE. Authors: Kenny Lau, Ken Lee, Chris Hughes -/ import Mathlib.Algebra.Group.Action.Units import Mathlib.Algebra.Group.Nat.Units import Mathlib.Algebra.GroupWithZero.Divisibility import Mathlib.Algebra.Ring.Divisibility.Basic import Mathlib.Algebra.Ring.Hom.Defs import Mathlib.Logic.Basic import Mathlib.Tactic.Ring /-! # Coprime elements of a ring or monoid ## Main definition * `IsCoprime x y`: that `x` and `y` are coprime, defined to be the existence of `a` and `b` such that `a * x + b * y = 1`. Note that elements with no common divisors (`IsRelPrime`) are not necessarily coprime, e.g., the multivariate polynomials `x₁` and `x₂` are not coprime. The two notions are equivalent in Bézout rings, see `isRelPrime_iff_isCoprime`. This file also contains lemmas about `IsRelPrime` parallel to `IsCoprime`. See also `RingTheory.Coprime.Lemmas` for further development of coprime elements. -/ universe u v section CommSemiring variable {R : Type u} [CommSemiring R] (x y z : R) /-- The proposition that `x` and `y` are coprime, defined to be the existence of `a` and `b` such that `a * x + b * y = 1`. Note that elements with no common divisors are not necessarily coprime, e.g., the multivariate polynomials `x₁` and `x₂` are not coprime. -/ def IsCoprime : Prop := ∃ a b, a * x + b * y = 1 variable {x y z} @[symm] theorem IsCoprime.symm (H : IsCoprime x y) : IsCoprime y x := let ⟨a, b, H⟩ := H ⟨b, a, by rw [add_comm, H]⟩ theorem isCoprime_comm : IsCoprime x y ↔ IsCoprime y x := ⟨IsCoprime.symm, IsCoprime.symm⟩ theorem isCoprime_self : IsCoprime x x ↔ IsUnit x := ⟨fun ⟨a, b, h⟩ => isUnit_of_mul_eq_one x (a + b) <| by rwa [mul_comm, add_mul], fun h => let ⟨b, hb⟩ := isUnit_iff_exists_inv'.1 h ⟨b, 0, by rwa [zero_mul, add_zero]⟩⟩ theorem isCoprime_zero_left : IsCoprime 0 x ↔ IsUnit x := ⟨fun ⟨a, b, H⟩ => isUnit_of_mul_eq_one x b <| by rwa [mul_zero, zero_add, mul_comm] at H, fun H => let ⟨b, hb⟩ := isUnit_iff_exists_inv'.1 H ⟨1, b, by rwa [one_mul, zero_add]⟩⟩ theorem isCoprime_zero_right : IsCoprime x 0 ↔ IsUnit x := isCoprime_comm.trans isCoprime_zero_left theorem not_isCoprime_zero_zero [Nontrivial R] : ¬IsCoprime (0 : R) 0 := mt isCoprime_zero_right.mp not_isUnit_zero lemma IsCoprime.intCast {R : Type*} [CommRing R] {a b : ℤ} (h : IsCoprime a b) : IsCoprime (a : R) (b : R) := by rcases h with ⟨u, v, H⟩ use u, v rw_mod_cast [H] exact Int.cast_one /-- If a 2-vector `p` satisfies `IsCoprime (p 0) (p 1)`, then `p ≠ 0`. -/ theorem IsCoprime.ne_zero [Nontrivial R] {p : Fin 2 → R} (h : IsCoprime (p 0) (p 1)) : p ≠ 0 := by rintro rfl exact not_isCoprime_zero_zero h theorem IsCoprime.ne_zero_or_ne_zero [Nontrivial R] (h : IsCoprime x y) : x ≠ 0 ∨ y ≠ 0 := by apply not_or_of_imp rintro rfl rfl exact not_isCoprime_zero_zero h theorem isCoprime_one_left : IsCoprime 1 x := ⟨1, 0, by rw [one_mul, zero_mul, add_zero]⟩ theorem isCoprime_one_right : IsCoprime x 1 := ⟨0, 1, by rw [one_mul, zero_mul, zero_add]⟩ theorem IsCoprime.dvd_of_dvd_mul_right (H1 : IsCoprime x z) (H2 : x ∣ y * z) : x ∣ y := by let ⟨a, b, H⟩ := H1 rw [← mul_one y, ← H, mul_add, ← mul_assoc, mul_left_comm] exact dvd_add (dvd_mul_left _ _) (H2.mul_left _) theorem IsCoprime.dvd_of_dvd_mul_left (H1 : IsCoprime x y) (H2 : x ∣ y * z) : x ∣ z := by let ⟨a, b, H⟩ := H1 rw [← one_mul z, ← H, add_mul, mul_right_comm, mul_assoc b] exact dvd_add (dvd_mul_left _ _) (H2.mul_left _) theorem IsCoprime.mul_left (H1 : IsCoprime x z) (H2 : IsCoprime y z) : IsCoprime (x * y) z := let ⟨a, b, h1⟩ := H1 let ⟨c, d, h2⟩ := H2 ⟨a * c, a * x * d + b * c * y + b * d * z, calc a * c * (x * y) + (a * x * d + b * c * y + b * d * z) * z _ = (a * x + b * z) * (c * y + d * z) := by ring _ = 1 := by rw [h1, h2, mul_one] ⟩ theorem IsCoprime.mul_right (H1 : IsCoprime x y) (H2 : IsCoprime x z) : IsCoprime x (y * z) := by rw [isCoprime_comm] at H1 H2 ⊢ exact H1.mul_left H2 theorem IsCoprime.mul_dvd (H : IsCoprime x y) (H1 : x ∣ z) (H2 : y ∣ z) : x * y ∣ z := by obtain ⟨a, b, h⟩ := H rw [← mul_one z, ← h, mul_add] apply dvd_add · rw [mul_comm z, mul_assoc] exact (mul_dvd_mul_left _ H2).mul_left _ · rw [mul_comm b, ← mul_assoc] exact (mul_dvd_mul_right H1 _).mul_right _ theorem IsCoprime.of_mul_left_left (H : IsCoprime (x * y) z) : IsCoprime x z := let ⟨a, b, h⟩ := H ⟨a * y, b, by rwa [mul_right_comm, mul_assoc]⟩ theorem IsCoprime.of_mul_left_right (H : IsCoprime (x * y) z) : IsCoprime y z := by rw [mul_comm] at H exact H.of_mul_left_left theorem IsCoprime.of_mul_right_left (H : IsCoprime x (y * z)) : IsCoprime x y := by rw [isCoprime_comm] at H ⊢ exact H.of_mul_left_left theorem IsCoprime.of_mul_right_right (H : IsCoprime x (y * z)) : IsCoprime x z := by rw [mul_comm] at H exact H.of_mul_right_left theorem IsCoprime.mul_left_iff : IsCoprime (x * y) z ↔ IsCoprime x z ∧ IsCoprime y z := ⟨fun H => ⟨H.of_mul_left_left, H.of_mul_left_right⟩, fun ⟨H1, H2⟩ => H1.mul_left H2⟩ theorem IsCoprime.mul_right_iff : IsCoprime x (y * z) ↔ IsCoprime x y ∧ IsCoprime x z := by rw [isCoprime_comm, IsCoprime.mul_left_iff, isCoprime_comm, @isCoprime_comm _ _ z] theorem IsCoprime.of_isCoprime_of_dvd_left (h : IsCoprime y z) (hdvd : x ∣ y) : IsCoprime x z := by obtain ⟨d, rfl⟩ := hdvd exact IsCoprime.of_mul_left_left h theorem IsCoprime.of_isCoprime_of_dvd_right (h : IsCoprime z y) (hdvd : x ∣ y) : IsCoprime z x := (h.symm.of_isCoprime_of_dvd_left hdvd).symm theorem IsCoprime.isUnit_of_dvd (H : IsCoprime x y) (d : x ∣ y) : IsUnit x := let ⟨k, hk⟩ := d isCoprime_self.1 <| IsCoprime.of_mul_right_left <| show IsCoprime x (x * k) from hk ▸ H theorem IsCoprime.isUnit_of_dvd' {a b x : R} (h : IsCoprime a b) (ha : x ∣ a) (hb : x ∣ b) : IsUnit x := (h.of_isCoprime_of_dvd_left ha).isUnit_of_dvd hb theorem IsCoprime.isRelPrime {a b : R} (h : IsCoprime a b) : IsRelPrime a b := fun _ ↦ h.isUnit_of_dvd' theorem IsCoprime.map (H : IsCoprime x y) {S : Type v} [CommSemiring S] (f : R →+* S) : IsCoprime (f x) (f y) := let ⟨a, b, h⟩ := H ⟨f a, f b, by rw [← f.map_mul, ← f.map_mul, ← f.map_add, h, f.map_one]⟩ theorem IsCoprime.of_add_mul_left_left (h : IsCoprime (x + y * z) y) : IsCoprime x y := let ⟨a, b, H⟩ := h ⟨a, a * z + b, by simpa only [add_mul, mul_add, add_assoc, add_comm, add_left_comm, mul_assoc, mul_comm, mul_left_comm] using H⟩ theorem IsCoprime.of_add_mul_right_left (h : IsCoprime (x + z * y) y) : IsCoprime x y := by rw [mul_comm] at h exact h.of_add_mul_left_left theorem IsCoprime.of_add_mul_left_right (h : IsCoprime x (y + x * z)) : IsCoprime x y := by rw [isCoprime_comm] at h ⊢ exact h.of_add_mul_left_left theorem IsCoprime.of_add_mul_right_right (h : IsCoprime x (y + z * x)) : IsCoprime x y := by rw [mul_comm] at h exact h.of_add_mul_left_right theorem IsCoprime.of_mul_add_left_left (h : IsCoprime (y * z + x) y) : IsCoprime x y := by rw [add_comm] at h exact h.of_add_mul_left_left theorem IsCoprime.of_mul_add_right_left (h : IsCoprime (z * y + x) y) : IsCoprime x y := by rw [add_comm] at h exact h.of_add_mul_right_left theorem IsCoprime.of_mul_add_left_right (h : IsCoprime x (x * z + y)) : IsCoprime x y := by rw [add_comm] at h exact h.of_add_mul_left_right theorem IsCoprime.of_mul_add_right_right (h : IsCoprime x (z * x + y)) : IsCoprime x y := by rw [add_comm] at h exact h.of_add_mul_right_right theorem IsRelPrime.of_add_mul_left_left (h : IsRelPrime (x + y * z) y) : IsRelPrime x y := fun _ hx hy ↦ h (dvd_add hx <| dvd_mul_of_dvd_left hy z) hy theorem IsRelPrime.of_add_mul_right_left (h : IsRelPrime (x + z * y) y) : IsRelPrime x y := (mul_comm z y ▸ h).of_add_mul_left_left theorem IsRelPrime.of_add_mul_left_right (h : IsRelPrime x (y + x * z)) : IsRelPrime x y := by rw [isRelPrime_comm] at h ⊢ exact h.of_add_mul_left_left theorem IsRelPrime.of_add_mul_right_right (h : IsRelPrime x (y + z * x)) : IsRelPrime x y := (mul_comm z x ▸ h).of_add_mul_left_right theorem IsRelPrime.of_mul_add_left_left (h : IsRelPrime (y * z + x) y) : IsRelPrime x y := (add_comm _ x ▸ h).of_add_mul_left_left theorem IsRelPrime.of_mul_add_right_left (h : IsRelPrime (z * y + x) y) : IsRelPrime x y := (add_comm _ x ▸ h).of_add_mul_right_left theorem IsRelPrime.of_mul_add_left_right (h : IsRelPrime x (x * z + y)) : IsRelPrime x y := (add_comm _ y ▸ h).of_add_mul_left_right theorem IsRelPrime.of_mul_add_right_right (h : IsRelPrime x (z * x + y)) : IsRelPrime x y := (add_comm _ y ▸ h).of_add_mul_right_right end CommSemiring section ScalarTower variable {R G : Type*} [CommSemiring R] [Group G] [MulAction G R] [SMulCommClass G R R] [IsScalarTower G R R] (x : G) (y z : R) theorem isCoprime_group_smul_left : IsCoprime (x • y) z ↔ IsCoprime y z := ⟨fun ⟨a, b, h⟩ => ⟨x • a, b, by rwa [smul_mul_assoc, ← mul_smul_comm]⟩, fun ⟨a, b, h⟩ => ⟨x⁻¹ • a, b, by rwa [smul_mul_smul_comm, inv_mul_cancel, one_smul]⟩⟩ theorem isCoprime_group_smul_right : IsCoprime y (x • z) ↔ IsCoprime y z := isCoprime_comm.trans <| (isCoprime_group_smul_left x z y).trans isCoprime_comm theorem isCoprime_group_smul : IsCoprime (x • y) (x • z) ↔ IsCoprime y z := (isCoprime_group_smul_left x y (x • z)).trans (isCoprime_group_smul_right x y z) end ScalarTower section CommSemiringUnit variable {R : Type*} [CommSemiring R] {x u v : R} theorem isCoprime_mul_unit_left_left (hu : IsUnit x) (y z : R) : IsCoprime (x * y) z ↔ IsCoprime y z := let ⟨u, hu⟩ := hu hu ▸ isCoprime_group_smul_left u y z theorem isCoprime_mul_unit_left_right (hu : IsUnit x) (y z : R) : IsCoprime y (x * z) ↔ IsCoprime y z := let ⟨u, hu⟩ := hu hu ▸ isCoprime_group_smul_right u y z theorem isCoprime_mul_unit_right_left (hu : IsUnit x) (y z : R) : IsCoprime (y * x) z ↔ IsCoprime y z := mul_comm x y ▸ isCoprime_mul_unit_left_left hu y z theorem isCoprime_mul_unit_right_right (hu : IsUnit x) (y z : R) : IsCoprime y (z * x) ↔ IsCoprime y z := mul_comm x z ▸ isCoprime_mul_unit_left_right hu y z theorem isCoprime_mul_units_left (hu : IsUnit u) (hv : IsUnit v) (y z : R) :
IsCoprime (u * y) (v * z) ↔ IsCoprime y z := Iff.trans (isCoprime_mul_unit_left_left hu _ _)
Mathlib/RingTheory/Coprime/Basic.lean
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