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/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.List.Sublists
import Mathlib.Data.List.Zip
import Mathlib.Data.Multiset.Bind
import Mathlib.Data.Multiset.Range
/-!
# The powerset of a multiset
-/
namespace Multiset
open List
variable {α : Type*}
/-! ### powerset -/
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11215): TODO: Write a more efficient version
/-- A helper function for the powerset of a multiset. Given a list `l`, returns a list
of sublists of `l` as multisets. -/
def powersetAux (l : List α) : List (Multiset α) :=
(sublists l).map (↑)
theorem powersetAux_eq_map_coe {l : List α} : powersetAux l = (sublists l).map (↑) :=
rfl
@[simp]
theorem mem_powersetAux {l : List α} {s} : s ∈ powersetAux l ↔ s ≤ ↑l :=
Quotient.inductionOn s <| by simp [powersetAux_eq_map_coe, Subperm, and_comm]
/-- Helper function for the powerset of a multiset. Given a list `l`, returns a list
of sublists of `l` (using `sublists'`), as multisets. -/
def powersetAux' (l : List α) : List (Multiset α) :=
(sublists' l).map (↑)
theorem powersetAux_perm_powersetAux' {l : List α} : powersetAux l ~ powersetAux' l := by
rw [powersetAux_eq_map_coe]; exact (sublists_perm_sublists' _).map _
@[simp]
theorem powersetAux'_nil : powersetAux' (@nil α) = [0] :=
rfl
@[simp]
theorem powersetAux'_cons (a : α) (l : List α) :
powersetAux' (a :: l) = powersetAux' l ++ List.map (cons a) (powersetAux' l) := by
simp [powersetAux']
theorem powerset_aux'_perm {l₁ l₂ : List α} (p : l₁ ~ l₂) : powersetAux' l₁ ~ powersetAux' l₂ := by
induction p with
| nil => simp
| cons _ _ IH =>
simp only [powersetAux'_cons]
exact IH.append (IH.map _)
| swap a b =>
simp only [powersetAux'_cons, map_append, List.map_map, append_assoc]
apply Perm.append_left
rw [← append_assoc, ← append_assoc,
(by funext s; simp [cons_swap] : cons b ∘ cons a = cons a ∘ cons b)]
exact perm_append_comm.append_right _
| trans _ _ IH₁ IH₂ => exact IH₁.trans IH₂
theorem powersetAux_perm {l₁ l₂ : List α} (p : l₁ ~ l₂) : powersetAux l₁ ~ powersetAux l₂ :=
powersetAux_perm_powersetAux'.trans <|
(powerset_aux'_perm p).trans powersetAux_perm_powersetAux'.symm
--Porting note (https://github.com/leanprover-community/mathlib4/issues/11083): slightly slower implementation due to `map ofList`
/-- The power set of a multiset. -/
def powerset (s : Multiset α) : Multiset (Multiset α) :=
Quot.liftOn s
(fun l => (powersetAux l : Multiset (Multiset α)))
(fun _ _ h => Quot.sound (powersetAux_perm h))
theorem powerset_coe (l : List α) : @powerset α l = ((sublists l).map (↑) : List (Multiset α)) :=
congr_arg ((↑) : List (Multiset α) → Multiset (Multiset α)) powersetAux_eq_map_coe
@[simp]
theorem powerset_coe' (l : List α) : @powerset α l = ((sublists' l).map (↑) : List (Multiset α)) :=
Quot.sound powersetAux_perm_powersetAux'
@[simp]
theorem powerset_zero : @powerset α 0 = {0} :=
rfl
@[simp]
theorem powerset_cons (a : α) (s) : powerset (a ::ₘ s) = powerset s + map (cons a) (powerset s) :=
Quotient.inductionOn s fun l => by simp [Function.comp_def]
@[simp]
theorem mem_powerset {s t : Multiset α} : s ∈ powerset t ↔ s ≤ t :=
Quotient.inductionOn₂ s t <| by simp [Subperm, and_comm]
theorem map_single_le_powerset (s : Multiset α) : s.map singleton ≤ powerset s :=
Quotient.inductionOn s fun l => by
simp only [powerset_coe, quot_mk_to_coe, coe_le, map_coe]
show l.map (((↑) : List α → Multiset α) ∘ pure) <+~ (sublists l).map (↑)
rw [← List.map_map]
exact ((map_pure_sublist_sublists _).map _).subperm
@[simp]
theorem card_powerset (s : Multiset α) : card (powerset s) = 2 ^ card s :=
Quotient.inductionOn s <| by simp
theorem revzip_powersetAux {l : List α} ⦃x⦄ (h : x ∈ revzip (powersetAux l)) : x.1 + x.2 = ↑l := by
rw [revzip, powersetAux_eq_map_coe, ← map_reverse, zip_map, ← revzip, List.mem_map] at h
simp only [Prod.map_apply, Prod.exists] at h
rcases h with ⟨l₁, l₂, h, rfl, rfl⟩
exact Quot.sound (revzip_sublists _ _ _ h)
theorem revzip_powersetAux' {l : List α} ⦃x⦄ (h : x ∈ revzip (powersetAux' l)) :
x.1 + x.2 = ↑l := by
rw [revzip, powersetAux', ← map_reverse, zip_map, ← revzip, List.mem_map] at h
simp only [Prod.map_apply, Prod.exists] at h
rcases h with ⟨l₁, l₂, h, rfl, rfl⟩
exact Quot.sound (revzip_sublists' _ _ _ h)
theorem revzip_powersetAux_lemma {α : Type*} [DecidableEq α] (l : List α) {l' : List (Multiset α)}
(H : ∀ ⦃x : _ × _⦄, x ∈ revzip l' → x.1 + x.2 = ↑l) :
revzip l' = l'.map fun x => (x, (l : Multiset α) - x) := by
have :
Forall₂ (fun (p : Multiset α × Multiset α) (s : Multiset α) => p = (s, ↑l - s)) (revzip l')
((revzip l').map Prod.fst) := by
rw [forall₂_map_right_iff, forall₂_same]
rintro ⟨s, t⟩ h
dsimp
rw [← H h, add_tsub_cancel_left]
rw [← forall₂_eq_eq_eq, forall₂_map_right_iff]
simpa using this
theorem revzip_powersetAux_perm_aux' {l : List α} :
revzip (powersetAux l) ~ revzip (powersetAux' l) := by
haveI := Classical.decEq α
rw [revzip_powersetAux_lemma l revzip_powersetAux, revzip_powersetAux_lemma l revzip_powersetAux']
exact powersetAux_perm_powersetAux'.map _
theorem revzip_powersetAux_perm {l₁ l₂ : List α} (p : l₁ ~ l₂) :
revzip (powersetAux l₁) ~ revzip (powersetAux l₂) := by
haveI := Classical.decEq α
simp only [fun l : List α => revzip_powersetAux_lemma l revzip_powersetAux, coe_eq_coe.2 p]
exact (powersetAux_perm p).map _
/-! ### powersetCard -/
/-- Helper function for `powersetCard`. Given a list `l`, `powersetCardAux n l` is the list
of sublists of length `n`, as multisets. -/
def powersetCardAux (n : ℕ) (l : List α) : List (Multiset α) :=
sublistsLenAux n l (↑) []
theorem powersetCardAux_eq_map_coe {n} {l : List α} :
powersetCardAux n l = (sublistsLen n l).map (↑) := by
rw [powersetCardAux, sublistsLenAux_eq, append_nil]
@[simp]
theorem mem_powersetCardAux {n} {l : List α} {s} : s ∈ powersetCardAux n l ↔ s ≤ ↑l ∧ card s = n :=
Quotient.inductionOn s <| by
simp only [quot_mk_to_coe, powersetCardAux_eq_map_coe, List.mem_map, mem_sublistsLen,
coe_eq_coe, coe_le, Subperm, exists_prop, coe_card]
exact fun l₁ =>
⟨fun ⟨l₂, ⟨s, e⟩, p⟩ => ⟨⟨_, p, s⟩, p.symm.length_eq.trans e⟩,
fun ⟨⟨l₂, p, s⟩, e⟩ => ⟨_, ⟨s, p.length_eq.trans e⟩, p⟩⟩
@[simp]
theorem powersetCardAux_zero (l : List α) : powersetCardAux 0 l = [0] := by
simp [powersetCardAux_eq_map_coe]
@[simp]
theorem powersetCardAux_nil (n : ℕ) : powersetCardAux (n + 1) (@nil α) = [] :=
rfl
@[simp]
theorem powersetCardAux_cons (n : ℕ) (a : α) (l : List α) :
powersetCardAux (n + 1) (a :: l) =
powersetCardAux (n + 1) l ++ List.map (cons a) (powersetCardAux n l) := by
simp [powersetCardAux_eq_map_coe]
theorem powersetCardAux_perm {n} {l₁ l₂ : List α} (p : l₁ ~ l₂) :
powersetCardAux n l₁ ~ powersetCardAux n l₂ := by
induction' n with n IHn generalizing l₁ l₂
· simp
induction p with
| nil => rfl
| cons _ p IH =>
simp only [powersetCardAux_cons]
exact IH.append ((IHn p).map _)
| swap a b =>
simp only [powersetCardAux_cons, append_assoc]
apply Perm.append_left
cases n
· simp [Perm.swap]
simp only [powersetCardAux_cons, map_append, List.map_map]
rw [← append_assoc, ← append_assoc,
(by funext s; simp [cons_swap] : cons b ∘ cons a = cons a ∘ cons b)]
exact perm_append_comm.append_right _
| trans _ _ IH₁ IH₂ => exact IH₁.trans IH₂
/-- `powersetCard n s` is the multiset of all submultisets of `s` of length `n`. -/
def powersetCard (n : ℕ) (s : Multiset α) : Multiset (Multiset α) :=
Quot.liftOn s (fun l => (powersetCardAux n l : Multiset (Multiset α))) fun _ _ h =>
Quot.sound (powersetCardAux_perm h)
theorem powersetCard_coe' (n) (l : List α) : @powersetCard α n l = powersetCardAux n l :=
rfl
theorem powersetCard_coe (n) (l : List α) :
@powersetCard α n l = ((sublistsLen n l).map (↑) : List (Multiset α)) :=
congr_arg ((↑) : List (Multiset α) → Multiset (Multiset α)) powersetCardAux_eq_map_coe
@[simp]
theorem powersetCard_zero_left (s : Multiset α) : powersetCard 0 s = {0} :=
Quotient.inductionOn s fun l => by simp [powersetCard_coe']
theorem powersetCard_zero_right (n : ℕ) : @powersetCard α (n + 1) 0 = 0 :=
rfl
@[simp]
theorem powersetCard_cons (n : ℕ) (a : α) (s) :
powersetCard (n + 1) (a ::ₘ s) = powersetCard (n + 1) s + map (cons a) (powersetCard n s) :=
Quotient.inductionOn s fun l => by simp [powersetCard_coe']
theorem powersetCard_one (s : Multiset α) : powersetCard 1 s = s.map singleton :=
Quotient.inductionOn s fun l ↦ by
simp [powersetCard_coe, sublistsLen_one, map_reverse, Function.comp_def]
@[simp]
theorem mem_powersetCard {n : ℕ} {s t : Multiset α} : s ∈ powersetCard n t ↔ s ≤ t ∧ card s = n :=
Quotient.inductionOn t fun l => by simp [powersetCard_coe']
@[simp]
theorem card_powersetCard (n : ℕ) (s : Multiset α) :
card (powersetCard n s) = Nat.choose (card s) n :=
Quotient.inductionOn s <| by simp [powersetCard_coe]
theorem powersetCard_le_powerset (n : ℕ) (s : Multiset α) : powersetCard n s ≤ powerset s :=
Quotient.inductionOn s fun l => by
simp only [quot_mk_to_coe, powersetCard_coe, powerset_coe', coe_le]
exact ((sublistsLen_sublist_sublists' _ _).map _).subperm
theorem powersetCard_mono (n : ℕ) {s t : Multiset α} (h : s ≤ t) :
powersetCard n s ≤ powersetCard n t :=
leInductionOn h fun {l₁ l₂} h => by
simp only [powersetCard_coe, coe_le]
exact ((sublistsLen_sublist_of_sublist _ h).map _).subperm
@[simp]
theorem powersetCard_eq_empty {α : Type*} (n : ℕ) {s : Multiset α} (h : card s < n) :
powersetCard n s = 0 :=
card_eq_zero.mp (Nat.choose_eq_zero_of_lt h ▸ card_powersetCard _ _)
@[simp]
theorem powersetCard_card_add (s : Multiset α) {i : ℕ} (hi : 0 < i) :
s.powersetCard (card s + i) = 0 :=
powersetCard_eq_empty _ (Nat.lt_add_of_pos_right hi)
theorem powersetCard_map {β : Type*} (f : α → β) (n : ℕ) (s : Multiset α) :
powersetCard n (s.map f) = (powersetCard n s).map (map f) := by
induction' s using Multiset.induction with t s ih generalizing n
· cases n <;> simp [powersetCard_zero_left, powersetCard_zero_right]
· cases n <;> simp [ih, map_comp_cons]
theorem pairwise_disjoint_powersetCard (s : Multiset α) :
_root_.Pairwise fun i j => Disjoint (s.powersetCard i) (s.powersetCard j) :=
fun _ _ h ↦ disjoint_left.mpr fun hi hj ↦
h ((Multiset.mem_powersetCard.mp hi).2.symm.trans (Multiset.mem_powersetCard.mp hj).2)
theorem bind_powerset_len {α : Type*} (S : Multiset α) :
(bind (Multiset.range (card S + 1)) fun k => S.powersetCard k) = S.powerset := by
induction S using Quotient.inductionOn
simp_rw [quot_mk_to_coe, powerset_coe', powersetCard_coe, ← coe_range, coe_bind,
← List.map_flatMap, coe_card]
exact coe_eq_coe.mpr ((List.range_bind_sublistsLen_perm _).map _)
@[simp]
theorem nodup_powerset {s : Multiset α} : Nodup (powerset s) ↔ Nodup s :=
⟨fun h => (nodup_of_le (map_single_le_powerset _) h).of_map _,
Quotient.inductionOn s fun l h => by
| simp only [quot_mk_to_coe, powerset_coe', coe_nodup]
refine (nodup_sublists'.2 h).map_on ?_
exact fun x sx y sy e =>
(h.perm_iff_eq_of_sublist (mem_sublists'.1 sx) (mem_sublists'.1 sy)).1 (Quotient.exact e)⟩
| Mathlib/Data/Multiset/Powerset.lean | 281 | 285 |
/-
Copyright (c) 2021 Yourong Zang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yourong Zang, Yury Kudryashov
-/
import Mathlib.Data.Fintype.Option
import Mathlib.Topology.Homeomorph.Lemmas
import Mathlib.Topology.Sets.Opens
/-!
# The OnePoint Compactification
We construct the OnePoint compactification (the one-point compactification) of an arbitrary
topological space `X` and prove some properties inherited from `X`.
## Main definitions
* `OnePoint`: the OnePoint compactification, we use coercion for the canonical embedding
`X → OnePoint X`; when `X` is already compact, the compactification adds an isolated point
to the space.
* `OnePoint.infty`: the extra point
## Main results
* The topological structure of `OnePoint X`
* The connectedness of `OnePoint X` for a noncompact, preconnected `X`
* `OnePoint X` is `T₀` for a T₀ space `X`
* `OnePoint X` is `T₁` for a T₁ space `X`
* `OnePoint X` is normal if `X` is a locally compact Hausdorff space
## Tags
one-point compactification, Alexandroff compactification, compactness
-/
open Set Filter Topology
/-!
### Definition and basic properties
In this section we define `OnePoint X` to be the disjoint union of `X` and `∞`, implemented as
`Option X`. Then we restate some lemmas about `Option X` for `OnePoint X`.
-/
variable {X Y : Type*}
/-- The OnePoint extension of an arbitrary topological space `X` -/
def OnePoint (X : Type*) :=
Option X
/-- The repr uses the notation from the `OnePoint` locale. -/
instance [Repr X] : Repr (OnePoint X) :=
⟨fun o _ =>
match o with
| none => "∞"
| some a => "↑" ++ repr a⟩
namespace OnePoint
/-- The point at infinity -/
@[match_pattern] def infty : OnePoint X := none
@[inherit_doc]
scoped notation "∞" => OnePoint.infty
/-- Coercion from `X` to `OnePoint X`. -/
@[coe, match_pattern] def some : X → OnePoint X := Option.some
@[simp]
lemma some_eq_iff (x₁ x₂ : X) : (some x₁ = some x₂) ↔ (x₁ = x₂) := by
rw [iff_eq_eq]
exact Option.some.injEq x₁ x₂
instance : CoeTC X (OnePoint X) := ⟨some⟩
instance : Inhabited (OnePoint X) := ⟨∞⟩
protected lemma «forall» {p : OnePoint X → Prop} :
(∀ (x : OnePoint X), p x) ↔ p ∞ ∧ ∀ (x : X), p x :=
Option.forall
protected lemma «exists» {p : OnePoint X → Prop} :
(∃ x, p x) ↔ p ∞ ∨ ∃ (x : X), p x :=
Option.exists
instance [Fintype X] : Fintype (OnePoint X) :=
inferInstanceAs (Fintype (Option X))
instance infinite [Infinite X] : Infinite (OnePoint X) :=
inferInstanceAs (Infinite (Option X))
theorem coe_injective : Function.Injective ((↑) : X → OnePoint X) :=
Option.some_injective X
@[norm_cast]
theorem coe_eq_coe {x y : X} : (x : OnePoint X) = y ↔ x = y :=
coe_injective.eq_iff
@[simp]
theorem coe_ne_infty (x : X) : (x : OnePoint X) ≠ ∞ :=
nofun
@[simp]
theorem infty_ne_coe (x : X) : ∞ ≠ (x : OnePoint X) :=
nofun
/-- Recursor for `OnePoint` using the preferred forms `∞` and `↑x`. -/
@[elab_as_elim, induction_eliminator, cases_eliminator]
protected def rec {C : OnePoint X → Sort*} (infty : C ∞) (coe : ∀ x : X, C x) :
∀ z : OnePoint X, C z
| ∞ => infty
| (x : X) => coe x
/-- An elimination principle for `OnePoint`. -/
@[inline] protected def elim : OnePoint X → Y → (X → Y) → Y := Option.elim
@[simp] theorem elim_infty (y : Y) (f : X → Y) : ∞.elim y f = y := rfl
@[simp] theorem elim_some (y : Y) (f : X → Y) (x : X) : (some x).elim y f = f x := rfl
theorem isCompl_range_coe_infty : IsCompl (range ((↑) : X → OnePoint X)) {∞} :=
isCompl_range_some_none X
theorem range_coe_union_infty : range ((↑) : X → OnePoint X) ∪ {∞} = univ :=
range_some_union_none X
@[simp]
theorem insert_infty_range_coe : insert ∞ (range (@some X)) = univ :=
insert_none_range_some _
@[simp]
theorem range_coe_inter_infty : range ((↑) : X → OnePoint X) ∩ {∞} = ∅ :=
range_some_inter_none X
@[simp]
theorem compl_range_coe : (range ((↑) : X → OnePoint X))ᶜ = {∞} :=
compl_range_some X
theorem compl_infty : ({∞}ᶜ : Set (OnePoint X)) = range ((↑) : X → OnePoint X) :=
(@isCompl_range_coe_infty X).symm.compl_eq
theorem compl_image_coe (s : Set X) : ((↑) '' s : Set (OnePoint X))ᶜ = (↑) '' sᶜ ∪ {∞} := by
rw [coe_injective.compl_image_eq, compl_range_coe]
theorem ne_infty_iff_exists {x : OnePoint X} : x ≠ ∞ ↔ ∃ y : X, (y : OnePoint X) = x := by
induction x using OnePoint.rec <;> simp
instance canLift : CanLift (OnePoint X) X (↑) fun x => x ≠ ∞ :=
WithTop.canLift
theorem not_mem_range_coe_iff {x : OnePoint X} : x ∉ range some ↔ x = ∞ := by
rw [← mem_compl_iff, compl_range_coe, mem_singleton_iff]
theorem infty_not_mem_range_coe : ∞ ∉ range ((↑) : X → OnePoint X) :=
not_mem_range_coe_iff.2 rfl
theorem infty_not_mem_image_coe {s : Set X} : ∞ ∉ ((↑) : X → OnePoint X) '' s :=
not_mem_subset (image_subset_range _ _) infty_not_mem_range_coe
@[simp]
theorem coe_preimage_infty : ((↑) : X → OnePoint X) ⁻¹' {∞} = ∅ := by
ext
simp
/-- Extend a map `f : X → Y` to a map `OnePoint X → OnePoint Y`
by sending infinity to infinity. -/
protected def map (f : X → Y) : OnePoint X → OnePoint Y :=
Option.map f
@[simp] theorem map_infty (f : X → Y) : OnePoint.map f ∞ = ∞ := rfl
@[simp] theorem map_some (f : X → Y) (x : X) : (x : OnePoint X).map f = f x := rfl
@[simp] theorem map_id : OnePoint.map (id : X → X) = id := Option.map_id
theorem map_comp {Z : Type*} (f : Y → Z) (g : X → Y) :
OnePoint.map (f ∘ g) = OnePoint.map f ∘ OnePoint.map g :=
(Option.map_comp_map _ _).symm
/-!
### Topological space structure on `OnePoint X`
We define a topological space structure on `OnePoint X` so that `s` is open if and only if
* `(↑) ⁻¹' s` is open in `X`;
* if `∞ ∈ s`, then `((↑) ⁻¹' s)ᶜ` is compact.
Then we reformulate this definition in a few different ways, and prove that
`(↑) : X → OnePoint X` is an open embedding. If `X` is not a compact space, then we also prove
that `(↑)` has dense range, so it is a dense embedding.
-/
variable [TopologicalSpace X]
instance : TopologicalSpace (OnePoint X) where
IsOpen s := (∞ ∈ s → IsCompact (((↑) : X → OnePoint X) ⁻¹' s)ᶜ) ∧
IsOpen (((↑) : X → OnePoint X) ⁻¹' s)
isOpen_univ := by simp
isOpen_inter s t := by
rintro ⟨hms, hs⟩ ⟨hmt, ht⟩
refine ⟨?_, hs.inter ht⟩
rintro ⟨hms', hmt'⟩
simpa [compl_inter] using (hms hms').union (hmt hmt')
isOpen_sUnion S ho := by
suffices IsOpen ((↑) ⁻¹' ⋃₀ S : Set X) by
refine ⟨?_, this⟩
rintro ⟨s, hsS : s ∈ S, hs : ∞ ∈ s⟩
refine IsCompact.of_isClosed_subset ((ho s hsS).1 hs) this.isClosed_compl ?_
exact compl_subset_compl.mpr (preimage_mono <| subset_sUnion_of_mem hsS)
rw [preimage_sUnion]
exact isOpen_biUnion fun s hs => (ho s hs).2
variable {s : Set (OnePoint X)}
theorem isOpen_def :
IsOpen s ↔ (∞ ∈ s → IsCompact ((↑) ⁻¹' s : Set X)ᶜ) ∧ IsOpen ((↑) ⁻¹' s : Set X) :=
Iff.rfl
theorem isOpen_iff_of_mem' (h : ∞ ∈ s) :
IsOpen s ↔ IsCompact ((↑) ⁻¹' s : Set X)ᶜ ∧ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
theorem isOpen_iff_of_mem (h : ∞ ∈ s) :
IsOpen s ↔ IsClosed ((↑) ⁻¹' s : Set X)ᶜ ∧ IsCompact ((↑) ⁻¹' s : Set X)ᶜ := by
simp only [isOpen_iff_of_mem' h, isClosed_compl_iff, and_comm]
theorem isOpen_iff_of_not_mem (h : ∞ ∉ s) : IsOpen s ↔ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
theorem isClosed_iff_of_mem (h : ∞ ∈ s) : IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) := by
have : ∞ ∉ sᶜ := fun H => H h
rw [← isOpen_compl_iff, isOpen_iff_of_not_mem this, ← isOpen_compl_iff, preimage_compl]
theorem isClosed_iff_of_not_mem (h : ∞ ∉ s) :
IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) ∧ IsCompact ((↑) ⁻¹' s : Set X) := by
rw [← isOpen_compl_iff, isOpen_iff_of_mem (mem_compl h), ← preimage_compl, compl_compl]
@[simp]
theorem isOpen_image_coe {s : Set X} : IsOpen ((↑) '' s : Set (OnePoint X)) ↔ IsOpen s := by
rw [isOpen_iff_of_not_mem infty_not_mem_image_coe, preimage_image_eq _ coe_injective]
theorem isOpen_compl_image_coe {s : Set X} :
IsOpen ((↑) '' s : Set (OnePoint X))ᶜ ↔ IsClosed s ∧ IsCompact s := by
rw [isOpen_iff_of_mem, ← preimage_compl, compl_compl, preimage_image_eq _ coe_injective]
exact infty_not_mem_image_coe
@[simp]
theorem isClosed_image_coe {s : Set X} :
IsClosed ((↑) '' s : Set (OnePoint X)) ↔ IsClosed s ∧ IsCompact s := by
rw [← isOpen_compl_iff, isOpen_compl_image_coe]
/-- An open set in `OnePoint X` constructed from a closed compact set in `X` -/
def opensOfCompl (s : Set X) (h₁ : IsClosed s) (h₂ : IsCompact s) :
TopologicalSpace.Opens (OnePoint X) :=
⟨((↑) '' s)ᶜ, isOpen_compl_image_coe.2 ⟨h₁, h₂⟩⟩
theorem infty_mem_opensOfCompl {s : Set X} (h₁ : IsClosed s) (h₂ : IsCompact s) :
∞ ∈ opensOfCompl s h₁ h₂ :=
mem_compl infty_not_mem_image_coe
@[continuity]
theorem continuous_coe : Continuous ((↑) : X → OnePoint X) :=
continuous_def.mpr fun _s hs => hs.right
theorem isOpenMap_coe : IsOpenMap ((↑) : X → OnePoint X) := fun _ => isOpen_image_coe.2
theorem isOpenEmbedding_coe : IsOpenEmbedding ((↑) : X → OnePoint X) :=
.of_continuous_injective_isOpenMap continuous_coe coe_injective isOpenMap_coe
theorem isOpen_range_coe : IsOpen (range ((↑) : X → OnePoint X)) :=
isOpenEmbedding_coe.isOpen_range
theorem isClosed_infty : IsClosed ({∞} : Set (OnePoint X)) := by
rw [← compl_range_coe, isClosed_compl_iff]
exact isOpen_range_coe
theorem nhds_coe_eq (x : X) : 𝓝 ↑x = map ((↑) : X → OnePoint X) (𝓝 x) :=
(isOpenEmbedding_coe.map_nhds_eq x).symm
theorem nhdsWithin_coe_image (s : Set X) (x : X) :
𝓝[(↑) '' s] (x : OnePoint X) = map (↑) (𝓝[s] x) :=
(isOpenEmbedding_coe.isEmbedding.map_nhdsWithin_eq _ _).symm
theorem nhdsWithin_coe (s : Set (OnePoint X)) (x : X) : 𝓝[s] ↑x = map (↑) (𝓝[(↑) ⁻¹' s] x) :=
(isOpenEmbedding_coe.map_nhdsWithin_preimage_eq _ _).symm
theorem comap_coe_nhds (x : X) : comap ((↑) : X → OnePoint X) (𝓝 x) = 𝓝 x :=
(isOpenEmbedding_coe.isInducing.nhds_eq_comap x).symm
/-- If `x` is not an isolated point of `X`, then `x : OnePoint X` is not an isolated point
of `OnePoint X`. -/
instance nhdsNE_coe_neBot (x : X) [h : NeBot (𝓝[≠] x)] : NeBot (𝓝[≠] (x : OnePoint X)) := by
simpa [nhdsWithin_coe, preimage, coe_eq_coe] using h.map some
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_coe_neBot := nhdsNE_coe_neBot
theorem nhdsNE_infty_eq : 𝓝[≠] (∞ : OnePoint X) = map (↑) (coclosedCompact X) := by
refine (nhdsWithin_basis_open ∞ _).ext (hasBasis_coclosedCompact.map _) ?_ ?_
· rintro s ⟨hs, hso⟩
refine ⟨_, (isOpen_iff_of_mem hs).mp hso, ?_⟩
simp [Subset.rfl]
· rintro s ⟨h₁, h₂⟩
refine ⟨_, ⟨mem_compl infty_not_mem_image_coe, isOpen_compl_image_coe.2 ⟨h₁, h₂⟩⟩, ?_⟩
simp [compl_image_coe, ← diff_eq, subset_preimage_image]
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_infty_eq := nhdsNE_infty_eq
/-- If `X` is a non-compact space, then `∞` is not an isolated point of `OnePoint X`. -/
instance nhdsNE_infty_neBot [NoncompactSpace X] : NeBot (𝓝[≠] (∞ : OnePoint X)) := by
rw [nhdsNE_infty_eq]
infer_instance
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_infty_neBot := nhdsNE_infty_neBot
instance (priority := 900) nhdsNE_neBot [∀ x : X, NeBot (𝓝[≠] x)] [NoncompactSpace X]
(x : OnePoint X) : NeBot (𝓝[≠] x) :=
OnePoint.rec OnePoint.nhdsNE_infty_neBot (fun y => OnePoint.nhdsNE_coe_neBot y) x
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_neBot := nhdsNE_neBot
theorem nhds_infty_eq : 𝓝 (∞ : OnePoint X) = map (↑) (coclosedCompact X) ⊔ pure ∞ := by
rw [← nhdsNE_infty_eq, nhdsNE_sup_pure]
theorem tendsto_coe_infty : Tendsto (↑) (coclosedCompact X) (𝓝 (∞ : OnePoint X)) := by
rw [nhds_infty_eq]
exact Filter.Tendsto.mono_right tendsto_map le_sup_left
theorem hasBasis_nhds_infty :
(𝓝 (∞ : OnePoint X)).HasBasis (fun s : Set X => IsClosed s ∧ IsCompact s) fun s =>
(↑) '' sᶜ ∪ {∞} := by
rw [nhds_infty_eq]
exact (hasBasis_coclosedCompact.map _).sup_pure _
@[simp]
theorem comap_coe_nhds_infty : comap ((↑) : X → OnePoint X) (𝓝 ∞) = coclosedCompact X := by
simp [nhds_infty_eq, comap_sup, comap_map coe_injective]
theorem le_nhds_infty {f : Filter (OnePoint X)} :
f ≤ 𝓝 ∞ ↔ ∀ s : Set X, IsClosed s → IsCompact s → (↑) '' sᶜ ∪ {∞} ∈ f := by
simp only [hasBasis_nhds_infty.ge_iff, and_imp]
theorem ultrafilter_le_nhds_infty {f : Ultrafilter (OnePoint X)} :
(f : Filter (OnePoint X)) ≤ 𝓝 ∞ ↔ ∀ s : Set X, IsClosed s → IsCompact s → (↑) '' s ∉ f := by
simp only [le_nhds_infty, ← compl_image_coe, Ultrafilter.mem_coe,
Ultrafilter.compl_mem_iff_not_mem]
theorem tendsto_nhds_infty' {α : Type*} {f : OnePoint X → α} {l : Filter α} :
Tendsto f (𝓝 ∞) l ↔ Tendsto f (pure ∞) l ∧ Tendsto (f ∘ (↑)) (coclosedCompact X) l := by
| simp [nhds_infty_eq, and_comm]
theorem tendsto_nhds_infty {α : Type*} {f : OnePoint X → α} {l : Filter α} :
| Mathlib/Topology/Compactification/OnePoint.lean | 354 | 356 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.Group.Equiv.Basic
import Mathlib.Data.ENat.Lattice
import Mathlib.Data.Part
import Mathlib.Tactic.NormNum
/-!
# Natural numbers with infinity
The natural numbers and an extra `top` element `⊤`. This implementation uses `Part ℕ` as an
implementation. Use `ℕ∞` instead unless you care about computability.
## Main definitions
The following instances are defined:
* `OrderedAddCommMonoid PartENat`
* `CanonicallyOrderedAdd PartENat`
* `CompleteLinearOrder PartENat`
There is no additive analogue of `MonoidWithZero`; if there were then `PartENat` could
be an `AddMonoidWithTop`.
* `toWithTop` : the map from `PartENat` to `ℕ∞`, with theorems that it plays well
with `+` and `≤`.
* `withTopAddEquiv : PartENat ≃+ ℕ∞`
* `withTopOrderIso : PartENat ≃o ℕ∞`
## Implementation details
`PartENat` is defined to be `Part ℕ`.
`+` and `≤` are defined on `PartENat`, but there is an issue with `*` because it's not
clear what `0 * ⊤` should be. `mul` is hence left undefined. Similarly `⊤ - ⊤` is ambiguous
so there is no `-` defined on `PartENat`.
Before the `open scoped Classical` line, various proofs are made with decidability assumptions.
This can cause issues -- see for example the non-simp lemma `toWithTopZero` proved by `rfl`,
followed by `@[simp] lemma toWithTopZero'` whose proof uses `convert`.
## Tags
PartENat, ℕ∞
-/
open Part hiding some
/-- Type of natural numbers with infinity (`⊤`) -/
def PartENat : Type :=
Part ℕ
namespace PartENat
/-- The computable embedding `ℕ → PartENat`.
This coincides with the coercion `coe : ℕ → PartENat`, see `PartENat.some_eq_natCast`. -/
@[coe]
def some : ℕ → PartENat :=
Part.some
instance : Zero PartENat :=
⟨some 0⟩
instance : Inhabited PartENat :=
⟨0⟩
instance : One PartENat :=
⟨some 1⟩
instance : Add PartENat :=
⟨fun x y => ⟨x.Dom ∧ y.Dom, fun h => get x h.1 + get y h.2⟩⟩
instance (n : ℕ) : Decidable (some n).Dom :=
isTrue trivial
@[simp]
theorem dom_some (x : ℕ) : (some x).Dom :=
trivial
instance addCommMonoid : AddCommMonoid PartENat where
add := (· + ·)
zero := 0
add_comm _ _ := Part.ext' and_comm fun _ _ => add_comm _ _
zero_add _ := Part.ext' (iff_of_eq (true_and _)) fun _ _ => zero_add _
add_zero _ := Part.ext' (iff_of_eq (and_true _)) fun _ _ => add_zero _
add_assoc _ _ _ := Part.ext' and_assoc fun _ _ => add_assoc _ _ _
nsmul := nsmulRec
instance : AddCommMonoidWithOne PartENat :=
{ PartENat.addCommMonoid with
one := 1
natCast := some
natCast_zero := rfl
natCast_succ := fun _ => Part.ext' (iff_of_eq (true_and _)).symm fun _ _ => rfl }
theorem some_eq_natCast (n : ℕ) : some n = n :=
rfl
instance : CharZero PartENat where
cast_injective := Part.some_injective
/-- Alias of `Nat.cast_inj` specialized to `PartENat` -/
theorem natCast_inj {x y : ℕ} : (x : PartENat) = y ↔ x = y :=
Nat.cast_inj
@[simp]
theorem dom_natCast (x : ℕ) : (x : PartENat).Dom :=
trivial
@[simp]
theorem dom_ofNat (x : ℕ) [x.AtLeastTwo] : (ofNat(x) : PartENat).Dom :=
trivial
@[simp]
theorem dom_zero : (0 : PartENat).Dom :=
trivial
@[simp]
theorem dom_one : (1 : PartENat).Dom :=
trivial
instance : CanLift PartENat ℕ (↑) Dom :=
⟨fun n hn => ⟨n.get hn, Part.some_get _⟩⟩
instance : LE PartENat :=
⟨fun x y => ∃ h : y.Dom → x.Dom, ∀ hy : y.Dom, x.get (h hy) ≤ y.get hy⟩
instance : Top PartENat :=
⟨none⟩
instance : Bot PartENat :=
⟨0⟩
instance : Max PartENat :=
⟨fun x y => ⟨x.Dom ∧ y.Dom, fun h => x.get h.1 ⊔ y.get h.2⟩⟩
theorem le_def (x y : PartENat) :
x ≤ y ↔ ∃ h : y.Dom → x.Dom, ∀ hy : y.Dom, x.get (h hy) ≤ y.get hy :=
Iff.rfl
@[elab_as_elim]
protected theorem casesOn' {P : PartENat → Prop} :
∀ a : PartENat, P ⊤ → (∀ n : ℕ, P (some n)) → P a :=
Part.induction_on
@[elab_as_elim]
protected theorem casesOn {P : PartENat → Prop} : ∀ a : PartENat, P ⊤ → (∀ n : ℕ, P n) → P a := by
exact PartENat.casesOn'
-- not a simp lemma as we will provide a `LinearOrderedAddCommMonoidWithTop` instance later
theorem top_add (x : PartENat) : ⊤ + x = ⊤ :=
Part.ext' (iff_of_eq (false_and _)) fun h => h.left.elim
-- not a simp lemma as we will provide a `LinearOrderedAddCommMonoidWithTop` instance later
theorem add_top (x : PartENat) : x + ⊤ = ⊤ := by rw [add_comm, top_add]
@[simp]
theorem natCast_get {x : PartENat} (h : x.Dom) : (x.get h : PartENat) = x := by
exact Part.ext' (iff_of_true trivial h) fun _ _ => rfl
@[simp, norm_cast]
theorem get_natCast' (x : ℕ) (h : (x : PartENat).Dom) : get (x : PartENat) h = x := by
rw [← natCast_inj, natCast_get]
theorem get_natCast {x : ℕ} : get (x : PartENat) (dom_natCast x) = x :=
get_natCast' _ _
theorem coe_add_get {x : ℕ} {y : PartENat} (h : ((x : PartENat) + y).Dom) :
get ((x : PartENat) + y) h = x + get y h.2 := by
rfl
@[simp]
theorem get_add {x y : PartENat} (h : (x + y).Dom) : get (x + y) h = x.get h.1 + y.get h.2 :=
rfl
@[simp]
theorem get_zero (h : (0 : PartENat).Dom) : (0 : PartENat).get h = 0 :=
rfl
@[simp]
theorem get_one (h : (1 : PartENat).Dom) : (1 : PartENat).get h = 1 :=
rfl
@[simp]
theorem get_ofNat' (x : ℕ) [x.AtLeastTwo] (h : (ofNat(x) : PartENat).Dom) :
Part.get (ofNat(x) : PartENat) h = ofNat(x) :=
get_natCast' x h
nonrec theorem get_eq_iff_eq_some {a : PartENat} {ha : a.Dom} {b : ℕ} : a.get ha = b ↔ a = some b :=
get_eq_iff_eq_some
theorem get_eq_iff_eq_coe {a : PartENat} {ha : a.Dom} {b : ℕ} : a.get ha = b ↔ a = b := by
rw [get_eq_iff_eq_some]
rfl
theorem dom_of_le_of_dom {x y : PartENat} : x ≤ y → y.Dom → x.Dom := fun ⟨h, _⟩ => h
theorem dom_of_le_some {x : PartENat} {y : ℕ} (h : x ≤ some y) : x.Dom :=
dom_of_le_of_dom h trivial
theorem dom_of_le_natCast {x : PartENat} {y : ℕ} (h : x ≤ y) : x.Dom := by
exact dom_of_le_some h
instance decidableLe (x y : PartENat) [Decidable x.Dom] [Decidable y.Dom] : Decidable (x ≤ y) :=
if hx : x.Dom then
decidable_of_decidable_of_iff (le_def x y).symm
else
if hy : y.Dom then isFalse fun h => hx <| dom_of_le_of_dom h hy
else isTrue ⟨fun h => (hy h).elim, fun h => (hy h).elim⟩
instance partialOrder : PartialOrder PartENat where
le := (· ≤ ·)
le_refl _ := ⟨id, fun _ => le_rfl⟩
le_trans := fun _ _ _ ⟨hxy₁, hxy₂⟩ ⟨hyz₁, hyz₂⟩ =>
⟨hxy₁ ∘ hyz₁, fun _ => le_trans (hxy₂ _) (hyz₂ _)⟩
lt_iff_le_not_le _ _ := Iff.rfl
le_antisymm := fun _ _ ⟨hxy₁, hxy₂⟩ ⟨hyx₁, hyx₂⟩ =>
Part.ext' ⟨hyx₁, hxy₁⟩ fun _ _ => le_antisymm (hxy₂ _) (hyx₂ _)
theorem lt_def (x y : PartENat) : x < y ↔ ∃ hx : x.Dom, ∀ hy : y.Dom, x.get hx < y.get hy := by
rw [lt_iff_le_not_le, le_def, le_def, not_exists]
constructor
· rintro ⟨⟨hyx, H⟩, h⟩
by_cases hx : x.Dom
· use hx
intro hy
specialize H hy
specialize h fun _ => hy
rw [not_forall] at h
obtain ⟨hx', h⟩ := h
rw [not_le] at h
exact h
· specialize h fun hx' => (hx hx').elim
rw [not_forall] at h
obtain ⟨hx', h⟩ := h
exact (hx hx').elim
· rintro ⟨hx, H⟩
exact ⟨⟨fun _ => hx, fun hy => (H hy).le⟩, fun hxy h => not_lt_of_le (h _) (H _)⟩
noncomputable instance isOrderedAddMonoid : IsOrderedAddMonoid PartENat :=
{ add_le_add_left := fun a b ⟨h₁, h₂⟩ c =>
PartENat.casesOn c (by simp [top_add]) fun c =>
⟨fun h => And.intro (dom_natCast _) (h₁ h.2), fun h => by
simpa only [coe_add_get] using add_le_add_left (h₂ _) c⟩ }
instance semilatticeSup : SemilatticeSup PartENat :=
{ PartENat.partialOrder with
sup := (· ⊔ ·)
le_sup_left := fun _ _ => ⟨And.left, fun _ => le_sup_left⟩
le_sup_right := fun _ _ => ⟨And.right, fun _ => le_sup_right⟩
sup_le := fun _ _ _ ⟨hx₁, hx₂⟩ ⟨hy₁, hy₂⟩ =>
⟨fun hz => ⟨hx₁ hz, hy₁ hz⟩, fun _ => sup_le (hx₂ _) (hy₂ _)⟩ }
instance orderBot : OrderBot PartENat where
bot := ⊥
bot_le _ := ⟨fun _ => trivial, fun _ => Nat.zero_le _⟩
instance orderTop : OrderTop PartENat where
top := ⊤
le_top _ := ⟨fun h => False.elim h, fun hy => False.elim hy⟩
instance : ZeroLEOneClass PartENat where
zero_le_one := bot_le
/-- Alias of `Nat.cast_le` specialized to `PartENat` -/
theorem coe_le_coe {x y : ℕ} : (x : PartENat) ≤ y ↔ x ≤ y := Nat.cast_le
/-- Alias of `Nat.cast_lt` specialized to `PartENat` -/
theorem coe_lt_coe {x y : ℕ} : (x : PartENat) < y ↔ x < y := Nat.cast_lt
@[simp]
theorem get_le_get {x y : PartENat} {hx : x.Dom} {hy : y.Dom} : x.get hx ≤ y.get hy ↔ x ≤ y := by
conv =>
lhs
rw [← coe_le_coe, natCast_get, natCast_get]
theorem le_coe_iff (x : PartENat) (n : ℕ) : x ≤ n ↔ ∃ h : x.Dom, x.get h ≤ n := by
show (∃ h : True → x.Dom, _) ↔ ∃ h : x.Dom, x.get h ≤ n
simp only [forall_prop_of_true, dom_natCast, get_natCast']
theorem lt_coe_iff (x : PartENat) (n : ℕ) : x < n ↔ ∃ h : x.Dom, x.get h < n := by
simp only [lt_def, forall_prop_of_true, get_natCast', dom_natCast]
theorem coe_le_iff (n : ℕ) (x : PartENat) : (n : PartENat) ≤ x ↔ ∀ h : x.Dom, n ≤ x.get h := by
rw [← some_eq_natCast]
simp only [le_def, exists_prop_of_true, dom_some, forall_true_iff]
rfl
theorem coe_lt_iff (n : ℕ) (x : PartENat) : (n : PartENat) < x ↔ ∀ h : x.Dom, n < x.get h := by
rw [← some_eq_natCast]
simp only [lt_def, exists_prop_of_true, dom_some, forall_true_iff]
rfl
nonrec theorem eq_zero_iff {x : PartENat} : x = 0 ↔ x ≤ 0 :=
eq_bot_iff
theorem ne_zero_iff {x : PartENat} : x ≠ 0 ↔ ⊥ < x :=
bot_lt_iff_ne_bot.symm
theorem dom_of_lt {x y : PartENat} : x < y → x.Dom :=
PartENat.casesOn x not_top_lt fun _ _ => dom_natCast _
theorem top_eq_none : (⊤ : PartENat) = Part.none :=
rfl
@[simp]
theorem natCast_lt_top (x : ℕ) : (x : PartENat) < ⊤ :=
Ne.lt_top fun h => absurd (congr_arg Dom h) <| by simp only [dom_natCast]; exact true_ne_false
@[simp]
theorem zero_lt_top : (0 : PartENat) < ⊤ :=
natCast_lt_top 0
@[simp]
theorem one_lt_top : (1 : PartENat) < ⊤ :=
natCast_lt_top 1
@[simp]
theorem ofNat_lt_top (x : ℕ) [x.AtLeastTwo] : (ofNat(x) : PartENat) < ⊤ :=
natCast_lt_top x
@[simp]
theorem natCast_ne_top (x : ℕ) : (x : PartENat) ≠ ⊤ :=
ne_of_lt (natCast_lt_top x)
@[simp]
theorem zero_ne_top : (0 : PartENat) ≠ ⊤ :=
natCast_ne_top 0
@[simp]
theorem one_ne_top : (1 : PartENat) ≠ ⊤ :=
natCast_ne_top 1
@[simp]
theorem ofNat_ne_top (x : ℕ) [x.AtLeastTwo] : (ofNat(x) : PartENat) ≠ ⊤ :=
natCast_ne_top x
theorem not_isMax_natCast (x : ℕ) : ¬IsMax (x : PartENat) :=
not_isMax_of_lt (natCast_lt_top x)
theorem ne_top_iff {x : PartENat} : x ≠ ⊤ ↔ ∃ n : ℕ, x = n := by
simpa only [← some_eq_natCast] using Part.ne_none_iff
theorem ne_top_iff_dom {x : PartENat} : x ≠ ⊤ ↔ x.Dom := by
classical exact not_iff_comm.1 Part.eq_none_iff'.symm
theorem not_dom_iff_eq_top {x : PartENat} : ¬x.Dom ↔ x = ⊤ :=
Iff.not_left ne_top_iff_dom.symm
theorem ne_top_of_lt {x y : PartENat} (h : x < y) : x ≠ ⊤ :=
ne_of_lt <| lt_of_lt_of_le h le_top
theorem eq_top_iff_forall_lt (x : PartENat) : x = ⊤ ↔ ∀ n : ℕ, (n : PartENat) < x := by
constructor
| · rintro rfl n
exact natCast_lt_top _
| Mathlib/Data/Nat/PartENat.lean | 362 | 363 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Jeremy Avigad
-/
import Mathlib.Data.Set.Finite.Basic
import Mathlib.Data.Set.Finite.Range
import Mathlib.Data.Set.Lattice
import Mathlib.Topology.Defs.Filter
/-!
# Openness and closedness of a set
This file provides lemmas relating to the predicates `IsOpen` and `IsClosed` of a set endowed with
a topology.
## Implementation notes
Topology in mathlib heavily uses filters (even more than in Bourbaki). See explanations in
<https://leanprover-community.github.io/theories/topology.html>.
## References
* [N. Bourbaki, *General Topology*][bourbaki1966]
* [I. M. James, *Topologies and Uniformities*][james1999]
## Tags
topological space
-/
open Set Filter Topology
universe u v
/-- A constructor for topologies by specifying the closed sets,
and showing that they satisfy the appropriate conditions. -/
def TopologicalSpace.ofClosed {X : Type u} (T : Set (Set X)) (empty_mem : ∅ ∈ T)
(sInter_mem : ∀ A, A ⊆ T → ⋂₀ A ∈ T)
(union_mem : ∀ A, A ∈ T → ∀ B, B ∈ T → A ∪ B ∈ T) : TopologicalSpace X where
IsOpen X := Xᶜ ∈ T
isOpen_univ := by simp [empty_mem]
isOpen_inter s t hs ht := by simpa only [compl_inter] using union_mem sᶜ hs tᶜ ht
isOpen_sUnion s hs := by
simp only [Set.compl_sUnion]
exact sInter_mem (compl '' s) fun z ⟨y, hy, hz⟩ => hz ▸ hs y hy
section TopologicalSpace
variable {X : Type u} {ι : Sort v} {α : Type*} {x : X} {s s₁ s₂ t : Set X} {p p₁ p₂ : X → Prop}
lemma isOpen_mk {p h₁ h₂ h₃} : IsOpen[⟨p, h₁, h₂, h₃⟩] s ↔ p s := Iff.rfl
@[ext (iff := false)]
protected theorem TopologicalSpace.ext :
∀ {f g : TopologicalSpace X}, IsOpen[f] = IsOpen[g] → f = g
| ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, rfl => rfl
protected theorem TopologicalSpace.ext_iff {t t' : TopologicalSpace X} :
t = t' ↔ ∀ s, IsOpen[t] s ↔ IsOpen[t'] s :=
⟨fun h _ => h ▸ Iff.rfl, fun h => by ext; exact h _⟩
theorem isOpen_fold {t : TopologicalSpace X} : t.IsOpen s = IsOpen[t] s :=
rfl
variable [TopologicalSpace X]
theorem isOpen_iUnion {f : ι → Set X} (h : ∀ i, IsOpen (f i)) : IsOpen (⋃ i, f i) :=
isOpen_sUnion (forall_mem_range.2 h)
theorem isOpen_biUnion {s : Set α} {f : α → Set X} (h : ∀ i ∈ s, IsOpen (f i)) :
IsOpen (⋃ i ∈ s, f i) :=
isOpen_iUnion fun i => isOpen_iUnion fun hi => h i hi
theorem IsOpen.union (h₁ : IsOpen s₁) (h₂ : IsOpen s₂) : IsOpen (s₁ ∪ s₂) := by
rw [union_eq_iUnion]; exact isOpen_iUnion (Bool.forall_bool.2 ⟨h₂, h₁⟩)
lemma isOpen_iff_of_cover {f : α → Set X} (ho : ∀ i, IsOpen (f i)) (hU : (⋃ i, f i) = univ) :
IsOpen s ↔ ∀ i, IsOpen (f i ∩ s) := by
refine ⟨fun h i ↦ (ho i).inter h, fun h ↦ ?_⟩
rw [← s.inter_univ, inter_comm, ← hU, iUnion_inter]
exact isOpen_iUnion fun i ↦ h i
@[simp] theorem isOpen_empty : IsOpen (∅ : Set X) := by
rw [← sUnion_empty]; exact isOpen_sUnion fun a => False.elim
theorem Set.Finite.isOpen_sInter {s : Set (Set X)} (hs : s.Finite) (h : ∀ t ∈ s, IsOpen t) :
IsOpen (⋂₀ s) := by
induction s, hs using Set.Finite.induction_on with
| empty => rw [sInter_empty]; exact isOpen_univ
| insert _ _ ih =>
simp only [sInter_insert, forall_mem_insert] at h ⊢
exact h.1.inter (ih h.2)
theorem Set.Finite.isOpen_biInter {s : Set α} {f : α → Set X} (hs : s.Finite)
(h : ∀ i ∈ s, IsOpen (f i)) :
IsOpen (⋂ i ∈ s, f i) :=
sInter_image f s ▸ (hs.image _).isOpen_sInter (forall_mem_image.2 h)
theorem isOpen_iInter_of_finite [Finite ι] {s : ι → Set X} (h : ∀ i, IsOpen (s i)) :
IsOpen (⋂ i, s i) :=
(finite_range _).isOpen_sInter (forall_mem_range.2 h)
theorem isOpen_biInter_finset {s : Finset α} {f : α → Set X} (h : ∀ i ∈ s, IsOpen (f i)) :
IsOpen (⋂ i ∈ s, f i) :=
s.finite_toSet.isOpen_biInter h
@[simp]
theorem isOpen_const {p : Prop} : IsOpen { _x : X | p } := by by_cases p <;> simp [*]
theorem IsOpen.and : IsOpen { x | p₁ x } → IsOpen { x | p₂ x } → IsOpen { x | p₁ x ∧ p₂ x } :=
IsOpen.inter
@[simp] theorem isOpen_compl_iff : IsOpen sᶜ ↔ IsClosed s :=
⟨fun h => ⟨h⟩, fun h => h.isOpen_compl⟩
theorem TopologicalSpace.ext_iff_isClosed {X} {t₁ t₂ : TopologicalSpace X} :
t₁ = t₂ ↔ ∀ s, IsClosed[t₁] s ↔ IsClosed[t₂] s := by
rw [TopologicalSpace.ext_iff, compl_surjective.forall]
simp only [@isOpen_compl_iff _ _ t₁, @isOpen_compl_iff _ _ t₂]
alias ⟨_, TopologicalSpace.ext_isClosed⟩ := TopologicalSpace.ext_iff_isClosed
theorem isClosed_const {p : Prop} : IsClosed { _x : X | p } := ⟨isOpen_const (p := ¬p)⟩
@[simp] theorem isClosed_empty : IsClosed (∅ : Set X) := isClosed_const
@[simp] theorem isClosed_univ : IsClosed (univ : Set X) := isClosed_const
lemma IsOpen.isLocallyClosed (hs : IsOpen s) : IsLocallyClosed s :=
⟨_, _, hs, isClosed_univ, (inter_univ _).symm⟩
lemma IsClosed.isLocallyClosed (hs : IsClosed s) : IsLocallyClosed s :=
⟨_, _, isOpen_univ, hs, (univ_inter _).symm⟩
theorem IsClosed.union : IsClosed s₁ → IsClosed s₂ → IsClosed (s₁ ∪ s₂) := by
simpa only [← isOpen_compl_iff, compl_union] using IsOpen.inter
theorem isClosed_sInter {s : Set (Set X)} : (∀ t ∈ s, IsClosed t) → IsClosed (⋂₀ s) := by
simpa only [← isOpen_compl_iff, compl_sInter, sUnion_image] using isOpen_biUnion
theorem isClosed_iInter {f : ι → Set X} (h : ∀ i, IsClosed (f i)) : IsClosed (⋂ i, f i) :=
isClosed_sInter <| forall_mem_range.2 h
theorem isClosed_biInter {s : Set α} {f : α → Set X} (h : ∀ i ∈ s, IsClosed (f i)) :
IsClosed (⋂ i ∈ s, f i) :=
isClosed_iInter fun i => isClosed_iInter <| h i
@[simp]
theorem isClosed_compl_iff {s : Set X} : IsClosed sᶜ ↔ IsOpen s := by
rw [← isOpen_compl_iff, compl_compl]
alias ⟨_, IsOpen.isClosed_compl⟩ := isClosed_compl_iff
theorem IsOpen.sdiff (h₁ : IsOpen s) (h₂ : IsClosed t) : IsOpen (s \ t) :=
IsOpen.inter h₁ h₂.isOpen_compl
theorem IsClosed.inter (h₁ : IsClosed s₁) (h₂ : IsClosed s₂) : IsClosed (s₁ ∩ s₂) := by
rw [← isOpen_compl_iff] at *
rw [compl_inter]
exact IsOpen.union h₁ h₂
theorem IsClosed.sdiff (h₁ : IsClosed s) (h₂ : IsOpen t) : IsClosed (s \ t) :=
IsClosed.inter h₁ (isClosed_compl_iff.mpr h₂)
theorem Set.Finite.isClosed_biUnion {s : Set α} {f : α → Set X} (hs : s.Finite)
(h : ∀ i ∈ s, IsClosed (f i)) :
IsClosed (⋃ i ∈ s, f i) := by
simp only [← isOpen_compl_iff, compl_iUnion] at *
exact hs.isOpen_biInter h
lemma isClosed_biUnion_finset {s : Finset α} {f : α → Set X} (h : ∀ i ∈ s, IsClosed (f i)) :
IsClosed (⋃ i ∈ s, f i) :=
s.finite_toSet.isClosed_biUnion h
theorem isClosed_iUnion_of_finite [Finite ι] {s : ι → Set X} (h : ∀ i, IsClosed (s i)) :
IsClosed (⋃ i, s i) := by
simp only [← isOpen_compl_iff, compl_iUnion] at *
exact isOpen_iInter_of_finite h
theorem isClosed_imp {p q : X → Prop} (hp : IsOpen { x | p x }) (hq : IsClosed { x | q x }) :
IsClosed { x | p x → q x } := by
simpa only [imp_iff_not_or] using hp.isClosed_compl.union hq
theorem IsClosed.not : IsClosed { a | p a } → IsOpen { a | ¬p a } :=
isOpen_compl_iff.mpr
/-!
### Limits of filters in topological spaces
In this section we define functions that return a limit of a filter (or of a function along a
filter), if it exists, and a random point otherwise. These functions are rarely used in Mathlib,
most of the theorems are written using `Filter.Tendsto`. One of the reasons is that
`Filter.limUnder f g = x` is not equivalent to `Filter.Tendsto g f (𝓝 x)` unless the codomain is a
Hausdorff space and `g` has a limit along `f`.
-/
section lim
/-- If a filter `f` is majorated by some `𝓝 x`, then it is majorated by `𝓝 (Filter.lim f)`. We
formulate this lemma with a `[Nonempty X]` argument of `lim` derived from `h` to make it useful for
types without a `[Nonempty X]` instance. Because of the built-in proof irrelevance, Lean will unify
this instance with any other instance. -/
theorem le_nhds_lim {f : Filter X} (h : ∃ x, f ≤ 𝓝 x) : f ≤ 𝓝 (@lim _ _ (nonempty_of_exists h) f) :=
Classical.epsilon_spec h
/-- If `g` tends to some `𝓝 x` along `f`, then it tends to `𝓝 (Filter.limUnder f g)`. We formulate
this lemma with a `[Nonempty X]` argument of `lim` derived from `h` to make it useful for types
without a `[Nonempty X]` instance. Because of the built-in proof irrelevance, Lean will unify this
instance with any other instance. -/
theorem tendsto_nhds_limUnder {f : Filter α} {g : α → X} (h : ∃ x, Tendsto g f (𝓝 x)) :
Tendsto g f (𝓝 (@limUnder _ _ _ (nonempty_of_exists h) f g)) :=
le_nhds_lim h
theorem limUnder_of_not_tendsto [hX : Nonempty X] {f : Filter α} {g : α → X}
(h : ¬ ∃ x, Tendsto g f (𝓝 x)) :
limUnder f g = Classical.choice hX := by
simp_rw [Tendsto] at h
simp_rw [limUnder, lim, Classical.epsilon, Classical.strongIndefiniteDescription, dif_neg h]
end lim
end TopologicalSpace
| Mathlib/Topology/Basic.lean | 1,440 | 1,445 | |
/-
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.Solvable
import Mathlib.Algebra.Lie.Quotient
import Mathlib.Algebra.Lie.Normalizer
import Mathlib.Algebra.Order.Archimedean.Basic
import Mathlib.LinearAlgebra.Eigenspace.Basic
import Mathlib.RingTheory.Artinian.Module
import Mathlib.RingTheory.Nilpotent.Lemmas
/-!
# Nilpotent Lie algebras
Like groups, Lie algebras admit a natural concept of nilpotency. More generally, any Lie module
carries a natural concept of nilpotency. We define these here via the lower central series.
## Main definitions
* `LieModule.lowerCentralSeries`
* `LieModule.IsNilpotent`
* `LieModule.maxNilpotentSubmodule`
* `LieAlgebra.maxNilpotentIdeal`
## Tags
lie algebra, lower central series, nilpotent, max nilpotent ideal
-/
universe u v w w₁ w₂
section NilpotentModules
variable {R : Type u} {L : Type v} {M : Type w}
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M]
variable (k : ℕ) (N : LieSubmodule R L M)
namespace LieSubmodule
/-- A generalisation of the lower central series. The zeroth term is a specified Lie submodule of
a Lie module. In the case when we specify the top ideal `⊤` of the Lie algebra, regarded as a Lie
module over itself, we get the usual lower central series of a Lie algebra.
It can be more convenient to work with this generalisation when considering the lower central series
of a Lie submodule, regarded as a Lie module in its own right, since it provides a type-theoretic
expression of the fact that the terms of the Lie submodule's lower central series are also Lie
submodules of the enclosing Lie module.
See also `LieSubmodule.lowerCentralSeries_eq_lcs_comap` and
`LieSubmodule.lowerCentralSeries_map_eq_lcs` below, as well as `LieSubmodule.ucs`. -/
def lcs : LieSubmodule R L M → LieSubmodule R L M :=
(fun N => ⁅(⊤ : LieIdeal R L), N⁆)^[k]
@[simp]
theorem lcs_zero (N : LieSubmodule R L M) : N.lcs 0 = N :=
rfl
@[simp]
theorem lcs_succ : N.lcs (k + 1) = ⁅(⊤ : LieIdeal R L), N.lcs k⁆ :=
Function.iterate_succ_apply' (fun N' => ⁅⊤, N'⁆) k N
@[simp]
lemma lcs_sup {N₁ N₂ : LieSubmodule R L M} {k : ℕ} :
(N₁ ⊔ N₂).lcs k = N₁.lcs k ⊔ N₂.lcs k := by
induction k with
| zero => simp
| succ k ih => simp only [LieSubmodule.lcs_succ, ih, LieSubmodule.lie_sup]
end LieSubmodule
namespace LieModule
variable (R L M)
/-- The lower central series of Lie submodules of a Lie module. -/
def lowerCentralSeries : LieSubmodule R L M :=
(⊤ : LieSubmodule R L M).lcs k
@[simp]
theorem lowerCentralSeries_zero : lowerCentralSeries R L M 0 = ⊤ :=
rfl
@[simp]
theorem lowerCentralSeries_succ :
lowerCentralSeries R L M (k + 1) = ⁅(⊤ : LieIdeal R L), lowerCentralSeries R L M k⁆ :=
(⊤ : LieSubmodule R L M).lcs_succ k
private theorem coe_lowerCentralSeries_eq_int_aux (R₁ R₂ L M : Type*)
[CommRing R₁] [CommRing R₂] [AddCommGroup M]
[LieRing L] [LieAlgebra R₁ L] [LieAlgebra R₂ L] [Module R₁ M] [Module R₂ M] [LieRingModule L M]
[LieModule R₁ L M] (k : ℕ) :
let I := lowerCentralSeries R₂ L M k; let S : Set M := {⁅a, b⁆ | (a : L) (b ∈ I)}
(Submodule.span R₁ S : Set M) ≤ (Submodule.span R₂ S : Set M) := by
intro I S x hx
simp only [SetLike.mem_coe] at hx ⊢
induction hx using Submodule.closure_induction with
| zero => exact Submodule.zero_mem _
| add y z hy₁ hz₁ hy₂ hz₂ => exact Submodule.add_mem _ hy₂ hz₂
| smul_mem c y hy =>
obtain ⟨a, b, hb, rfl⟩ := hy
| rw [← smul_lie]
exact Submodule.subset_span ⟨c • a, b, hb, rfl⟩
theorem coe_lowerCentralSeries_eq_int [LieModule R L M] (k : ℕ) :
(lowerCentralSeries R L M k : Set M) = (lowerCentralSeries ℤ L M k : Set M) := by
| Mathlib/Algebra/Lie/Nilpotent.lean | 104 | 108 |
/-
Copyright (c) 2020 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Eric Wieser
-/
import Mathlib.Data.ENNReal.Holder
import Mathlib.MeasureTheory.Function.LpSeminorm.Basic
import Mathlib.MeasureTheory.Integral.MeanInequalities
import Mathlib.Tactic.Finiteness
/-!
# Compare Lp seminorms for different values of `p`
In this file we compare `MeasureTheory.eLpNorm'` and `MeasureTheory.eLpNorm` for different
exponents.
-/
open Filter ENNReal
open scoped Topology
namespace MeasureTheory
section SameSpace
variable {α ε ε' : Type*} {m : MeasurableSpace α} {μ : Measure α} {f : α → ε}
[TopologicalSpace ε] [ContinuousENorm ε]
[TopologicalSpace ε'] [ENormedAddMonoid ε']
theorem eLpNorm'_le_eLpNorm'_mul_rpow_measure_univ {p q : ℝ} (hp0_lt : 0 < p) (hpq : p ≤ q)
(hf : AEStronglyMeasurable f μ) :
eLpNorm' f p μ ≤ eLpNorm' f q μ * μ Set.univ ^ (1 / p - 1 / q) := by
have hq0_lt : 0 < q := lt_of_lt_of_le hp0_lt hpq
by_cases hpq_eq : p = q
· rw [hpq_eq, sub_self, ENNReal.rpow_zero, mul_one]
have hpq : p < q := lt_of_le_of_ne hpq hpq_eq
let g := fun _ : α => (1 : ℝ≥0∞)
have h_rw : (∫⁻ a, ‖f a‖ₑ ^ p ∂μ) = ∫⁻ a, (‖f a‖ₑ * g a) ^ p ∂μ :=
lintegral_congr fun a => by simp [g]
repeat' rw [eLpNorm'_eq_lintegral_enorm]
rw [h_rw]
let r := p * q / (q - p)
have hpqr : 1 / p = 1 / q + 1 / r := by field_simp [r, hp0_lt.ne', hq0_lt.ne']
calc
(∫⁻ a : α, (‖f a‖ₑ * g a) ^ p ∂μ) ^ (1 / p) ≤
(∫⁻ a : α, ‖f a‖ₑ ^ q ∂μ) ^ (1 / q) * (∫⁻ a : α, g a ^ r ∂μ) ^ (1 / r) :=
ENNReal.lintegral_Lp_mul_le_Lq_mul_Lr hp0_lt hpq hpqr μ hf.enorm aemeasurable_const
_ = (∫⁻ a : α, ‖f a‖ₑ ^ q ∂μ) ^ (1 / q) * μ Set.univ ^ (1 / p - 1 / q) := by
rw [hpqr]; simp [r, g]
theorem eLpNorm'_le_eLpNormEssSup_mul_rpow_measure_univ {q : ℝ} (hq_pos : 0 < q) :
eLpNorm' f q μ ≤ eLpNormEssSup f μ * μ Set.univ ^ (1 / q) := by
have h_le : (∫⁻ a : α, ‖f a‖ₑ ^ q ∂μ) ≤ ∫⁻ _ : α, eLpNormEssSup f μ ^ q ∂μ := by
refine lintegral_mono_ae ?_
have h_nnnorm_le_eLpNorm_ess_sup := enorm_ae_le_eLpNormEssSup f μ
exact h_nnnorm_le_eLpNorm_ess_sup.mono fun x hx => by gcongr
rw [eLpNorm', ← ENNReal.rpow_one (eLpNormEssSup f μ)]
nth_rw 2 [← mul_inv_cancel₀ (ne_of_lt hq_pos).symm]
rw [ENNReal.rpow_mul, one_div, ← ENNReal.mul_rpow_of_nonneg _ _ (by simp [hq_pos.le] : 0 ≤ q⁻¹)]
gcongr
rwa [lintegral_const] at h_le
theorem eLpNorm_le_eLpNorm_mul_rpow_measure_univ {p q : ℝ≥0∞} (hpq : p ≤ q)
(hf : AEStronglyMeasurable f μ) :
eLpNorm f p μ ≤ eLpNorm f q μ * μ Set.univ ^ (1 / p.toReal - 1 / q.toReal) := by
by_cases hp0 : p = 0
· simp [hp0, zero_le]
rw [← Ne] at hp0
have hp0_lt : 0 < p := lt_of_le_of_ne (zero_le _) hp0.symm
have hq0_lt : 0 < q := lt_of_lt_of_le hp0_lt hpq
by_cases hq_top : q = ∞
· simp only [hq_top, _root_.div_zero, one_div, ENNReal.toReal_top, sub_zero, eLpNorm_exponent_top,
GroupWithZero.inv_zero]
by_cases hp_top : p = ∞
· simp only [hp_top, ENNReal.rpow_zero, mul_one, ENNReal.toReal_top, sub_zero,
GroupWithZero.inv_zero, eLpNorm_exponent_top]
exact le_rfl
rw [eLpNorm_eq_eLpNorm' hp0 hp_top]
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0_lt.ne' hp_top
refine (eLpNorm'_le_eLpNormEssSup_mul_rpow_measure_univ hp_pos).trans (le_of_eq ?_)
congr
exact one_div _
have hp_lt_top : p < ∞ := hpq.trans_lt (lt_top_iff_ne_top.mpr hq_top)
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0_lt.ne' hp_lt_top.ne
rw [eLpNorm_eq_eLpNorm' hp0_lt.ne.symm hp_lt_top.ne, eLpNorm_eq_eLpNorm' hq0_lt.ne.symm hq_top]
have hpq_real : p.toReal ≤ q.toReal := ENNReal.toReal_mono hq_top hpq
exact eLpNorm'_le_eLpNorm'_mul_rpow_measure_univ hp_pos hpq_real hf
theorem eLpNorm'_le_eLpNorm'_of_exponent_le {p q : ℝ} (hp0_lt : 0 < p)
(hpq : p ≤ q) (μ : Measure α) [IsProbabilityMeasure μ] (hf : AEStronglyMeasurable f μ) :
eLpNorm' f p μ ≤ eLpNorm' f q μ := by
have h_le_μ := eLpNorm'_le_eLpNorm'_mul_rpow_measure_univ hp0_lt hpq hf
rwa [measure_univ, ENNReal.one_rpow, mul_one] at h_le_μ
theorem eLpNorm'_le_eLpNormEssSup {q : ℝ} (hq_pos : 0 < q) [IsProbabilityMeasure μ] :
eLpNorm' f q μ ≤ eLpNormEssSup f μ :=
(eLpNorm'_le_eLpNormEssSup_mul_rpow_measure_univ hq_pos).trans_eq (by simp [measure_univ])
theorem eLpNorm_le_eLpNorm_of_exponent_le {p q : ℝ≥0∞} (hpq : p ≤ q) [IsProbabilityMeasure μ]
(hf : AEStronglyMeasurable f μ) : eLpNorm f p μ ≤ eLpNorm f q μ :=
(eLpNorm_le_eLpNorm_mul_rpow_measure_univ hpq hf).trans (le_of_eq (by simp [measure_univ]))
theorem eLpNorm'_lt_top_of_eLpNorm'_lt_top_of_exponent_le {p q : ℝ} [IsFiniteMeasure μ]
(hf : AEStronglyMeasurable f μ) (hfq_lt_top : eLpNorm' f q μ < ∞) (hp_nonneg : 0 ≤ p)
(hpq : p ≤ q) : eLpNorm' f p μ < ∞ := by
rcases le_or_lt p 0 with hp_nonpos | hp_pos
· rw [le_antisymm hp_nonpos hp_nonneg]
simp
have hq_pos : 0 < q := lt_of_lt_of_le hp_pos hpq
calc
eLpNorm' f p μ ≤ eLpNorm' f q μ * μ Set.univ ^ (1 / p - 1 / q) :=
eLpNorm'_le_eLpNorm'_mul_rpow_measure_univ hp_pos hpq hf
_ < ∞ := by
rw [ENNReal.mul_lt_top_iff]
refine Or.inl ⟨hfq_lt_top, ENNReal.rpow_lt_top_of_nonneg ?_ (measure_ne_top μ Set.univ)⟩
rwa [le_sub_comm, sub_zero, one_div, one_div, inv_le_inv₀ hq_pos hp_pos]
theorem MemLp.mono_exponent {p q : ℝ≥0∞} [IsFiniteMeasure μ] (hfq : MemLp f q μ)
(hpq : p ≤ q) : MemLp f p μ := by
obtain ⟨hfq_m, hfq_lt_top⟩ := hfq
by_cases hp0 : p = 0
| · rwa [hp0, memLp_zero_iff_aestronglyMeasurable]
rw [← Ne] at hp0
refine ⟨hfq_m, ?_⟩
by_cases hp_top : p = ∞
· have hq_top : q = ∞ := by rwa [hp_top, top_le_iff] at hpq
rw [hp_top]
rwa [hq_top] at hfq_lt_top
have hp_pos : 0 < p.toReal := ENNReal.toReal_pos hp0 hp_top
by_cases hq_top : q = ∞
· rw [eLpNorm_eq_eLpNorm' hp0 hp_top]
rw [hq_top, eLpNorm_exponent_top] at hfq_lt_top
refine lt_of_le_of_lt (eLpNorm'_le_eLpNormEssSup_mul_rpow_measure_univ hp_pos) ?_
refine ENNReal.mul_lt_top hfq_lt_top ?_
exact ENNReal.rpow_lt_top_of_nonneg (by simp [hp_pos.le]) (measure_ne_top μ Set.univ)
have hq0 : q ≠ 0 := by
by_contra hq_eq_zero
have hp_eq_zero : p = 0 := le_antisymm (by rwa [hq_eq_zero] at hpq) (zero_le _)
rw [hp_eq_zero, ENNReal.toReal_zero] at hp_pos
exact (lt_irrefl _) hp_pos
have hpq_real : p.toReal ≤ q.toReal := ENNReal.toReal_mono hq_top hpq
rw [eLpNorm_eq_eLpNorm' hp0 hp_top]
rw [eLpNorm_eq_eLpNorm' hq0 hq_top] at hfq_lt_top
exact eLpNorm'_lt_top_of_eLpNorm'_lt_top_of_exponent_le hfq_m hfq_lt_top hp_pos.le hpq_real
@[deprecated (since := "2025-02-21")]
alias Memℒp.mono_exponent := MemLp.mono_exponent
| Mathlib/MeasureTheory/Function/LpSeminorm/CompareExp.lean | 121 | 147 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Algebra.Constructions
import Mathlib.Topology.Bases
import Mathlib.Algebra.Order.Group.Nat
import Mathlib.Topology.UniformSpace.Basic
/-!
# Theory of Cauchy filters in uniform spaces. Complete uniform spaces. Totally bounded subsets.
-/
universe u v
open Filter Function TopologicalSpace Topology Set UniformSpace Uniformity
variable {α : Type u} {β : Type v} [uniformSpace : UniformSpace α]
/-- A filter `f` is Cauchy if for every entourage `r`, there exists an
`s ∈ f` such that `s × s ⊆ r`. This is a generalization of Cauchy
sequences, because if `a : ℕ → α` then the filter of sets containing
cofinitely many of the `a n` is Cauchy iff `a` is a Cauchy sequence. -/
def Cauchy (f : Filter α) :=
NeBot f ∧ f ×ˢ f ≤ 𝓤 α
/-- A set `s` is called *complete*, if any Cauchy filter `f` such that `s ∈ f`
has a limit in `s` (formally, it satisfies `f ≤ 𝓝 x` for some `x ∈ s`). -/
def IsComplete (s : Set α) :=
∀ f, Cauchy f → f ≤ 𝓟 s → ∃ x ∈ s, f ≤ 𝓝 x
theorem Filter.HasBasis.cauchy_iff {ι} {p : ι → Prop} {s : ι → Set (α × α)} (h : (𝓤 α).HasBasis p s)
{f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ i, p i → ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s i :=
and_congr Iff.rfl <|
(f.basis_sets.prod_self.le_basis_iff h).trans <| by
simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm]
theorem cauchy_iff' {f : Filter α} :
Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, ∀ x ∈ t, ∀ y ∈ t, (x, y) ∈ s :=
(𝓤 α).basis_sets.cauchy_iff
theorem cauchy_iff {f : Filter α} : Cauchy f ↔ NeBot f ∧ ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s :=
cauchy_iff'.trans <| by
simp only [subset_def, Prod.forall, mem_prod_eq, and_imp, id, forall_mem_comm]
lemma cauchy_iff_le {l : Filter α} [hl : l.NeBot] :
Cauchy l ↔ l ×ˢ l ≤ 𝓤 α := by
simp only [Cauchy, hl, true_and]
theorem Cauchy.ultrafilter_of {l : Filter α} (h : Cauchy l) :
Cauchy (@Ultrafilter.of _ l h.1 : Filter α) := by
haveI := h.1
have := Ultrafilter.of_le l
exact ⟨Ultrafilter.neBot _, (Filter.prod_mono this this).trans h.2⟩
theorem cauchy_map_iff {l : Filter β} {f : β → α} :
Cauchy (l.map f) ↔ NeBot l ∧ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) := by
rw [Cauchy, map_neBot_iff, prod_map_map_eq, Tendsto]
theorem cauchy_map_iff' {l : Filter β} [hl : NeBot l] {f : β → α} :
Cauchy (l.map f) ↔ Tendsto (fun p : β × β => (f p.1, f p.2)) (l ×ˢ l) (𝓤 α) :=
cauchy_map_iff.trans <| and_iff_right hl
theorem Cauchy.mono {f g : Filter α} [hg : NeBot g] (h_c : Cauchy f) (h_le : g ≤ f) : Cauchy g :=
⟨hg, le_trans (Filter.prod_mono h_le h_le) h_c.right⟩
theorem Cauchy.mono' {f g : Filter α} (h_c : Cauchy f) (_ : NeBot g) (h_le : g ≤ f) : Cauchy g :=
h_c.mono h_le
theorem cauchy_nhds {a : α} : Cauchy (𝓝 a) :=
⟨nhds_neBot, nhds_prod_eq.symm.trans_le (nhds_le_uniformity a)⟩
theorem cauchy_pure {a : α} : Cauchy (pure a) :=
cauchy_nhds.mono (pure_le_nhds a)
theorem Filter.Tendsto.cauchy_map {l : Filter β} [NeBot l] {f : β → α} {a : α}
(h : Tendsto f l (𝓝 a)) : Cauchy (map f l) :=
cauchy_nhds.mono h
lemma Cauchy.mono_uniformSpace {u v : UniformSpace β} {F : Filter β} (huv : u ≤ v)
(hF : Cauchy (uniformSpace := u) F) : Cauchy (uniformSpace := v) F :=
⟨hF.1, hF.2.trans huv⟩
lemma cauchy_inf_uniformSpace {u v : UniformSpace β} {F : Filter β} :
Cauchy (uniformSpace := u ⊓ v) F ↔
Cauchy (uniformSpace := u) F ∧ Cauchy (uniformSpace := v) F := by
unfold Cauchy
rw [inf_uniformity (u := u), le_inf_iff, and_and_left]
lemma cauchy_iInf_uniformSpace {ι : Sort*} [Nonempty ι] {u : ι → UniformSpace β}
{l : Filter β} :
Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by
unfold Cauchy
rw [iInf_uniformity, le_iInf_iff, forall_and, forall_const]
lemma cauchy_iInf_uniformSpace' {ι : Sort*} {u : ι → UniformSpace β}
{l : Filter β} [l.NeBot] :
Cauchy (uniformSpace := ⨅ i, u i) l ↔ ∀ i, Cauchy (uniformSpace := u i) l := by
simp_rw [cauchy_iff_le (uniformSpace := _), iInf_uniformity, le_iInf_iff]
lemma cauchy_comap_uniformSpace {u : UniformSpace β} {α} {f : α → β} {l : Filter α} :
Cauchy (uniformSpace := comap f u) l ↔ Cauchy (map f l) := by
simp only [Cauchy, map_neBot_iff, prod_map_map_eq, map_le_iff_le_comap]
rfl
lemma cauchy_prod_iff [UniformSpace β] {F : Filter (α × β)} :
Cauchy F ↔ Cauchy (map Prod.fst F) ∧ Cauchy (map Prod.snd F) := by
simp_rw [instUniformSpaceProd, ← cauchy_comap_uniformSpace, ← cauchy_inf_uniformSpace]
theorem Cauchy.prod [UniformSpace β] {f : Filter α} {g : Filter β} (hf : Cauchy f) (hg : Cauchy g) :
Cauchy (f ×ˢ g) := by
have := hf.1; have := hg.1
simpa [cauchy_prod_iff, hf.1] using ⟨hf, hg⟩
/-- The common part of the proofs of `le_nhds_of_cauchy_adhp` and
`SequentiallyComplete.le_nhds_of_seq_tendsto_nhds`: if for any entourage `s`
one can choose a set `t ∈ f` of diameter `s` such that it contains a point `y`
with `(x, y) ∈ s`, then `f` converges to `x`. -/
theorem le_nhds_of_cauchy_adhp_aux {f : Filter α} {x : α}
(adhs : ∀ s ∈ 𝓤 α, ∃ t ∈ f, t ×ˢ t ⊆ s ∧ ∃ y, (x, y) ∈ s ∧ y ∈ t) : f ≤ 𝓝 x := by
-- Consider a neighborhood `s` of `x`
intro s hs
-- Take an entourage twice smaller than `s`
rcases comp_mem_uniformity_sets (mem_nhds_uniformity_iff_right.1 hs) with ⟨U, U_mem, hU⟩
-- Take a set `t ∈ f`, `t × t ⊆ U`, and a point `y ∈ t` such that `(x, y) ∈ U`
rcases adhs U U_mem with ⟨t, t_mem, ht, y, hxy, hy⟩
apply mem_of_superset t_mem
-- Given a point `z ∈ t`, we have `(x, y) ∈ U` and `(y, z) ∈ t × t ⊆ U`, hence `z ∈ s`
exact fun z hz => hU (prodMk_mem_compRel hxy (ht <| mk_mem_prod hy hz)) rfl
/-- If `x` is an adherent (cluster) point for a Cauchy filter `f`, then it is a limit point
for `f`. -/
theorem le_nhds_of_cauchy_adhp {f : Filter α} {x : α} (hf : Cauchy f) (adhs : ClusterPt x f) :
f ≤ 𝓝 x :=
le_nhds_of_cauchy_adhp_aux
(fun s hs => by
obtain ⟨t, t_mem, ht⟩ : ∃ t ∈ f, t ×ˢ t ⊆ s := (cauchy_iff.1 hf).2 s hs
use t, t_mem, ht
| exact forall_mem_nonempty_iff_neBot.2 adhs _ (inter_mem_inf (mem_nhds_left x hs) t_mem))
theorem le_nhds_iff_adhp_of_cauchy {f : Filter α} {x : α} (hf : Cauchy f) :
f ≤ 𝓝 x ↔ ClusterPt x f :=
⟨fun h => ClusterPt.of_le_nhds' h hf.1, le_nhds_of_cauchy_adhp hf⟩
nonrec theorem Cauchy.map [UniformSpace β] {f : Filter α} {m : α → β} (hf : Cauchy f)
(hm : UniformContinuous m) : Cauchy (map m f) :=
⟨hf.1.map _,
calc
map m f ×ˢ map m f = map (Prod.map m m) (f ×ˢ f) := Filter.prod_map_map_eq
| Mathlib/Topology/UniformSpace/Cauchy.lean | 141 | 151 |
/-
Copyright (c) 2020 Nicolò Cavalleri. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nicolò Cavalleri, Andrew Yang
-/
import Mathlib.RingTheory.Derivation.ToSquareZero
import Mathlib.RingTheory.Ideal.Cotangent
import Mathlib.RingTheory.IsTensorProduct
import Mathlib.RingTheory.EssentialFiniteness
import Mathlib.Algebra.Exact
import Mathlib.LinearAlgebra.TensorProduct.RightExactness
/-!
# The module of kaehler differentials
## Main results
- `KaehlerDifferential`: The module of kaehler differentials. For an `R`-algebra `S`, we provide
the notation `Ω[S⁄R]` for `KaehlerDifferential R S`.
Note that the slash is `\textfractionsolidus`.
- `KaehlerDifferential.D`: The derivation into the module of kaehler differentials.
- `KaehlerDifferential.span_range_derivation`: The image of `D` spans `Ω[S⁄R]` as an `S`-module.
- `KaehlerDifferential.linearMapEquivDerivation`:
The isomorphism `Hom_R(Ω[S⁄R], M) ≃ₗ[S] Der_R(S, M)`.
- `KaehlerDifferential.quotKerTotalEquiv`: An alternative description of `Ω[S⁄R]` as `S` copies
of `S` with kernel (`KaehlerDifferential.kerTotal`) generated by the relations:
1. `dx + dy = d(x + y)`
2. `x dy + y dx = d(x * y)`
3. `dr = 0` for `r ∈ R`
- `KaehlerDifferential.map`: Given a map between the arrows `R →+* A` and `S →+* B`, we have an
`A`-linear map `Ω[A⁄R] → Ω[B⁄S]`.
- `KaehlerDifferential.map_surjective`:
The sequence `Ω[B⁄R] → Ω[B⁄A] → 0` is exact.
- `KaehlerDifferential.exact_mapBaseChange_map`:
The sequence `B ⊗[A] Ω[A⁄R] → Ω[B⁄R] → Ω[B⁄A]` is exact.
- `KaehlerDifferential.exact_kerCotangentToTensor_mapBaseChange`:
If `A → B` is surjective with kernel `I`, then
the sequence `I/I² → B ⊗[A] Ω[A⁄R] → Ω[B⁄R]` is exact.
- `KaehlerDifferential.mapBaseChange_surjective`:
If `A → B` is surjective, then the sequence `B ⊗[A] Ω[A⁄R] → Ω[B⁄R] → 0` is exact.
## Future project
- Define the `IsKaehlerDifferential` predicate.
-/
suppress_compilation
section KaehlerDifferential
open scoped TensorProduct
open Algebra Finsupp
universe u v
variable (R : Type u) (S : Type v) [CommRing R] [CommRing S] [Algebra R S]
/-- The kernel of the multiplication map `S ⊗[R] S →ₐ[R] S`. -/
abbrev KaehlerDifferential.ideal : Ideal (S ⊗[R] S) :=
RingHom.ker (TensorProduct.lmul' R : S ⊗[R] S →ₐ[R] S)
variable {S}
theorem KaehlerDifferential.one_smul_sub_smul_one_mem_ideal (a : S) :
(1 : S) ⊗ₜ[R] a - a ⊗ₜ[R] (1 : S) ∈ KaehlerDifferential.ideal R S := by simp [RingHom.mem_ker]
variable {R}
variable {M : Type*} [AddCommGroup M] [Module R M] [Module S M] [IsScalarTower R S M]
/-- For a `R`-derivation `S → M`, this is the map `S ⊗[R] S →ₗ[S] M` sending `s ⊗ₜ t ↦ s • D t`. -/
def Derivation.tensorProductTo (D : Derivation R S M) : S ⊗[R] S →ₗ[S] M :=
TensorProduct.AlgebraTensorModule.lift ((LinearMap.lsmul S (S →ₗ[R] M)).flip D.toLinearMap)
theorem Derivation.tensorProductTo_tmul (D : Derivation R S M) (s t : S) :
D.tensorProductTo (s ⊗ₜ t) = s • D t := rfl
theorem Derivation.tensorProductTo_mul (D : Derivation R S M) (x y : S ⊗[R] S) :
D.tensorProductTo (x * y) =
TensorProduct.lmul' (S := S) R x • D.tensorProductTo y +
TensorProduct.lmul' (S := S) R y • D.tensorProductTo x := by
refine TensorProduct.induction_on x ?_ ?_ ?_
· rw [zero_mul, map_zero, map_zero, zero_smul, smul_zero, add_zero]
swap
· intro x₁ y₁ h₁ h₂
rw [add_mul, map_add, map_add, map_add, add_smul, smul_add, h₁, h₂, add_add_add_comm]
intro x₁ x₂
refine TensorProduct.induction_on y ?_ ?_ ?_
· rw [mul_zero, map_zero, map_zero, zero_smul, smul_zero, add_zero]
swap
· intro x₁ y₁ h₁ h₂
rw [mul_add, map_add, map_add, map_add, add_smul, smul_add, h₁, h₂, add_add_add_comm]
intro x y
simp only [TensorProduct.tmul_mul_tmul, Derivation.tensorProductTo,
TensorProduct.AlgebraTensorModule.lift_apply, TensorProduct.lift.tmul',
TensorProduct.lmul'_apply_tmul]
dsimp
rw [D.leibniz]
simp only [smul_smul, smul_add, mul_comm (x * y) x₁, mul_right_comm x₁ x₂, ← mul_assoc]
variable (R S)
/-- The kernel of `S ⊗[R] S →ₐ[R] S` is generated by `1 ⊗ s - s ⊗ 1` as a `S`-module. -/
theorem KaehlerDifferential.submodule_span_range_eq_ideal :
Submodule.span S (Set.range fun s : S => (1 : S) ⊗ₜ[R] s - s ⊗ₜ[R] (1 : S)) =
(KaehlerDifferential.ideal R S).restrictScalars S := by
apply le_antisymm
· rw [Submodule.span_le]
rintro _ ⟨s, rfl⟩
exact KaehlerDifferential.one_smul_sub_smul_one_mem_ideal _ _
· rintro x (hx : _ = _)
have : x - TensorProduct.lmul' (S := S) R x ⊗ₜ[R] (1 : S) = x := by
rw [hx, TensorProduct.zero_tmul, sub_zero]
rw [← this]
clear this hx
refine TensorProduct.induction_on x ?_ ?_ ?_
· rw [map_zero, TensorProduct.zero_tmul, sub_zero]; exact zero_mem _
· intro x y
have : x ⊗ₜ[R] y - (x * y) ⊗ₜ[R] (1 : S) = x • ((1 : S) ⊗ₜ y - y ⊗ₜ (1 : S)) := by
simp_rw [smul_sub, TensorProduct.smul_tmul', smul_eq_mul, mul_one]
rw [TensorProduct.lmul'_apply_tmul, this]
refine Submodule.smul_mem _ x ?_
apply Submodule.subset_span
exact Set.mem_range_self y
· intro x y hx hy
rw [map_add, TensorProduct.add_tmul, ← sub_add_sub_comm]
exact add_mem hx hy
theorem KaehlerDifferential.span_range_eq_ideal :
Ideal.span (Set.range fun s : S => (1 : S) ⊗ₜ[R] s - s ⊗ₜ[R] (1 : S)) =
KaehlerDifferential.ideal R S := by
apply le_antisymm
· rw [Ideal.span_le]
rintro _ ⟨s, rfl⟩
exact KaehlerDifferential.one_smul_sub_smul_one_mem_ideal _ _
· change (KaehlerDifferential.ideal R S).restrictScalars S ≤ (Ideal.span _).restrictScalars S
rw [← KaehlerDifferential.submodule_span_range_eq_ideal, Ideal.span]
conv_rhs => rw [← Submodule.span_span_of_tower S]
exact Submodule.subset_span
/-- The module of Kähler differentials (Kahler differentials, Kaehler differentials).
This is implemented as `I / I ^ 2` with `I` the kernel of the multiplication map `S ⊗[R] S →ₐ[R] S`.
To view elements as a linear combination of the form `s • D s'`, use
`KaehlerDifferential.tensorProductTo_surjective` and `Derivation.tensorProductTo_tmul`.
We also provide the notation `Ω[S⁄R]` for `KaehlerDifferential R S`.
Note that the slash is `\textfractionsolidus`.
-/
def KaehlerDifferential : Type v :=
(KaehlerDifferential.ideal R S).Cotangent
instance : AddCommGroup (KaehlerDifferential R S) := inferInstanceAs <|
AddCommGroup (KaehlerDifferential.ideal R S).Cotangent
instance KaehlerDifferential.module : Module (S ⊗[R] S) (KaehlerDifferential R S) :=
Ideal.Cotangent.moduleOfTower _
@[inherit_doc KaehlerDifferential]
notation:100 "Ω[" S "⁄" R "]" => KaehlerDifferential R S
instance : Nonempty (Ω[S⁄R]) := ⟨0⟩
instance KaehlerDifferential.module' {R' : Type*} [CommRing R'] [Algebra R' S]
[SMulCommClass R R' S] :
Module R' (Ω[S⁄R]) :=
Submodule.Quotient.module' _
instance : IsScalarTower S (S ⊗[R] S) (Ω[S⁄R]) :=
Ideal.Cotangent.isScalarTower _
instance KaehlerDifferential.isScalarTower_of_tower {R₁ R₂ : Type*} [CommRing R₁] [CommRing R₂]
[Algebra R₁ S] [Algebra R₂ S] [SMul R₁ R₂]
[SMulCommClass R R₁ S] [SMulCommClass R R₂ S] [IsScalarTower R₁ R₂ S] :
IsScalarTower R₁ R₂ (Ω[S⁄R]) :=
Submodule.Quotient.isScalarTower _ _
instance KaehlerDifferential.isScalarTower' : IsScalarTower R (S ⊗[R] S) (Ω[S⁄R]) :=
Submodule.Quotient.isScalarTower _ _
/-- The quotient map `I → Ω[S⁄R]` with `I` being the kernel of `S ⊗[R] S → S`. -/
def KaehlerDifferential.fromIdeal : KaehlerDifferential.ideal R S →ₗ[S ⊗[R] S] Ω[S⁄R] :=
(KaehlerDifferential.ideal R S).toCotangent
/-- (Implementation) The underlying linear map of the derivation into `Ω[S⁄R]`. -/
def KaehlerDifferential.DLinearMap : S →ₗ[R] Ω[S⁄R] :=
((KaehlerDifferential.fromIdeal R S).restrictScalars R).comp
((TensorProduct.includeRight.toLinearMap - TensorProduct.includeLeft.toLinearMap :
S →ₗ[R] S ⊗[R] S).codRestrict
((KaehlerDifferential.ideal R S).restrictScalars R)
(KaehlerDifferential.one_smul_sub_smul_one_mem_ideal R) :
_ →ₗ[R] _)
theorem KaehlerDifferential.DLinearMap_apply (s : S) :
KaehlerDifferential.DLinearMap R S s =
(KaehlerDifferential.ideal R S).toCotangent
⟨1 ⊗ₜ s - s ⊗ₜ 1, KaehlerDifferential.one_smul_sub_smul_one_mem_ideal R s⟩ := rfl
/-- The universal derivation into `Ω[S⁄R]`. -/
def KaehlerDifferential.D : Derivation R S (Ω[S⁄R]) :=
{ toLinearMap := KaehlerDifferential.DLinearMap R S
map_one_eq_zero' := by
dsimp [KaehlerDifferential.DLinearMap_apply, Ideal.toCotangent_apply]
congr
rw [sub_self]
leibniz' := fun a b => by
have : LinearMap.CompatibleSMul { x // x ∈ ideal R S } (Ω[S⁄R]) S (S ⊗[R] S) := inferInstance
dsimp [KaehlerDifferential.DLinearMap_apply]
rw [← LinearMap.map_smul_of_tower (ideal R S).toCotangent,
← LinearMap.map_smul_of_tower (ideal R S).toCotangent,
← map_add (ideal R S).toCotangent, Ideal.toCotangent_eq, pow_two]
convert Submodule.mul_mem_mul (KaehlerDifferential.one_smul_sub_smul_one_mem_ideal R a :)
(KaehlerDifferential.one_smul_sub_smul_one_mem_ideal R b :) using 1
simp only [AddSubgroupClass.coe_sub, Submodule.coe_add, Submodule.coe_mk,
TensorProduct.tmul_mul_tmul, mul_sub, sub_mul, mul_comm b, Submodule.coe_smul_of_tower,
smul_sub, TensorProduct.smul_tmul', smul_eq_mul, mul_one]
ring_nf }
theorem KaehlerDifferential.D_apply (s : S) :
KaehlerDifferential.D R S s =
(KaehlerDifferential.ideal R S).toCotangent
⟨1 ⊗ₜ s - s ⊗ₜ 1, KaehlerDifferential.one_smul_sub_smul_one_mem_ideal R s⟩ := rfl
theorem KaehlerDifferential.span_range_derivation :
Submodule.span S (Set.range <| KaehlerDifferential.D R S) = ⊤ := by
rw [_root_.eq_top_iff]
rintro x -
obtain ⟨⟨x, hx⟩, rfl⟩ := Ideal.toCotangent_surjective _ x
have : x ∈ (KaehlerDifferential.ideal R S).restrictScalars S := hx
rw [← KaehlerDifferential.submodule_span_range_eq_ideal] at this
suffices ∃ hx, (KaehlerDifferential.ideal R S).toCotangent ⟨x, hx⟩ ∈
Submodule.span S (Set.range <| KaehlerDifferential.D R S) by
exact this.choose_spec
refine Submodule.span_induction ?_ ?_ ?_ ?_ this
· rintro _ ⟨x, rfl⟩
refine ⟨KaehlerDifferential.one_smul_sub_smul_one_mem_ideal R x, ?_⟩
apply Submodule.subset_span
exact ⟨x, KaehlerDifferential.DLinearMap_apply R S x⟩
· exact ⟨zero_mem _, Submodule.zero_mem _⟩
· rintro x y - - ⟨hx₁, hx₂⟩ ⟨hy₁, hy₂⟩; exact ⟨add_mem hx₁ hy₁, Submodule.add_mem _ hx₂ hy₂⟩
· rintro r x - ⟨hx₁, hx₂⟩
exact ⟨((KaehlerDifferential.ideal R S).restrictScalars S).smul_mem r hx₁,
Submodule.smul_mem _ r hx₂⟩
/-- `Ω[S⁄R]` is trivial if `R → S` is surjective.
Also see `Algebra.FormallyUnramified.iff_subsingleton_kaehlerDifferential`. -/
| lemma KaehlerDifferential.subsingleton_of_surjective (h : Function.Surjective (algebraMap R S)) :
Subsingleton (Ω[S⁄R]) := by
suffices (⊤ : Submodule S (Ω[S⁄R])) ≤ ⊥ from
(subsingleton_iff_forall_eq 0).mpr fun y ↦ this trivial
rw [← KaehlerDifferential.span_range_derivation, Submodule.span_le]
rintro _ ⟨x, rfl⟩; obtain ⟨x, rfl⟩ := h x; simp
variable {R S}
/-- The linear map from `Ω[S⁄R]`, associated with a derivation. -/
def Derivation.liftKaehlerDifferential (D : Derivation R S M) : Ω[S⁄R] →ₗ[S] M := by
refine LinearMap.comp ((((KaehlerDifferential.ideal R S) •
(⊤ : Submodule (S ⊗[R] S) (KaehlerDifferential.ideal R S))).restrictScalars S).liftQ ?_ ?_)
(Submodule.Quotient.restrictScalarsEquiv S _).symm.toLinearMap
· exact D.tensorProductTo.comp ((KaehlerDifferential.ideal R S).subtype.restrictScalars S)
· intro x hx
rw [LinearMap.mem_ker]
refine Submodule.smul_induction_on ((Submodule.restrictScalars_mem _ _ _).mp hx) ?_ ?_
· rintro x hx y -
rw [RingHom.mem_ker] at hx
| Mathlib/RingTheory/Kaehler/Basic.lean | 245 | 264 |
/-
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.Defs
import Mathlib.Analysis.Calculus.ContDiff.FaaDiBruno
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Mul
/-!
# Higher differentiability of composition
We prove that the composition of `C^n` functions is `C^n`.
We also expand the API around `C^n` functions.
## Main results
* `ContDiff.comp` states that the composition of two `C^n` functions is `C^n`.
Similar results are given for `C^n` functions on domains.
## 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`.
## Tags
derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series
-/
noncomputable section
open scoped NNReal Nat ContDiff
universe u uE uF uG
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup AddCommGroup.toAddCommMonoid
open Set Fin Filter Function
open scoped Topology
variable {𝕜 : Type*} [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*} [NormedAddCommGroup X] [NormedSpace 𝕜 X] {s t : Set E} {f : E → F}
{g : F → G} {x x₀ : E} {b : E × F → G} {m n : WithTop ℕ∞} {p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Constants -/
section constants
theorem iteratedFDerivWithin_succ_const (n : ℕ) (c : F) :
iteratedFDerivWithin 𝕜 (n + 1) (fun _ : E ↦ c) s = 0 := by
induction n with
| zero =>
ext1
simp [iteratedFDerivWithin_succ_eq_comp_left, iteratedFDerivWithin_zero_eq_comp, comp_def]
| succ n IH =>
rw [iteratedFDerivWithin_succ_eq_comp_left, IH]
simp only [Pi.zero_def, comp_def, fderivWithin_const, map_zero]
@[simp]
theorem iteratedFDerivWithin_zero_fun {i : ℕ} :
iteratedFDerivWithin 𝕜 i (fun _ : E ↦ (0 : F)) s = 0 := by
cases i with
| zero => ext; simp
| succ i => apply iteratedFDerivWithin_succ_const
@[simp]
theorem iteratedFDeriv_zero_fun {n : ℕ} : (iteratedFDeriv 𝕜 n fun _ : E ↦ (0 : F)) = 0 :=
funext fun x ↦ by simp only [← iteratedFDerivWithin_univ, iteratedFDerivWithin_zero_fun]
theorem contDiff_zero_fun : ContDiff 𝕜 n fun _ : E => (0 : F) :=
analyticOnNhd_const.contDiff
/-- Constants are `C^∞`. -/
theorem contDiff_const {c : F} : ContDiff 𝕜 n fun _ : E => c :=
analyticOnNhd_const.contDiff
theorem contDiffOn_const {c : F} {s : Set E} : ContDiffOn 𝕜 n (fun _ : E => c) s :=
contDiff_const.contDiffOn
theorem contDiffAt_const {c : F} : ContDiffAt 𝕜 n (fun _ : E => c) x :=
contDiff_const.contDiffAt
theorem contDiffWithinAt_const {c : F} : ContDiffWithinAt 𝕜 n (fun _ : E => c) s x :=
contDiffAt_const.contDiffWithinAt
@[nontriviality]
theorem contDiff_of_subsingleton [Subsingleton F] : ContDiff 𝕜 n f := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiff_const
@[nontriviality]
theorem contDiffAt_of_subsingleton [Subsingleton F] : ContDiffAt 𝕜 n f x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffAt_const
@[nontriviality]
theorem contDiffWithinAt_of_subsingleton [Subsingleton F] : ContDiffWithinAt 𝕜 n f s x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffWithinAt_const
@[nontriviality]
theorem contDiffOn_of_subsingleton [Subsingleton F] : ContDiffOn 𝕜 n f s := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffOn_const
theorem iteratedFDerivWithin_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) (s : Set E) :
iteratedFDerivWithin 𝕜 n (fun _ : E ↦ c) s = 0 := by
cases n with
| zero => contradiction
| succ n => exact iteratedFDerivWithin_succ_const n c
theorem iteratedFDeriv_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) :
(iteratedFDeriv 𝕜 n fun _ : E ↦ c) = 0 := by
simp only [← iteratedFDerivWithin_univ, iteratedFDerivWithin_const_of_ne hn]
theorem iteratedFDeriv_succ_const (n : ℕ) (c : F) :
(iteratedFDeriv 𝕜 (n + 1) fun _ : E ↦ c) = 0 :=
iteratedFDeriv_const_of_ne (by simp) _
theorem contDiffWithinAt_singleton : ContDiffWithinAt 𝕜 n f {x} x :=
(contDiffWithinAt_const (c := f x)).congr (by simp) rfl
|
end constants
/-! ### Smoothness of linear functions -/
section linear
/-- Unbundled bounded linear functions are `C^n`. -/
| Mathlib/Analysis/Calculus/ContDiff/Basic.lean | 126 | 132 |
/-
Copyright (c) 2023 Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Richard M. Hill
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Derivative
import Mathlib.Algebra.Polynomial.Module.AEval
import Mathlib.RingTheory.Adjoin.Polynomial
import Mathlib.RingTheory.Derivation.Basic
/-!
# Derivations of univariate polynomials
In this file we prove that an `R`-derivation of `Polynomial R` is determined by its value on `X`.
We also provide a constructor `Polynomial.mkDerivation` that
builds a derivation from its value on `X`, and a linear equivalence
`Polynomial.mkDerivationEquiv` between `A` and `Derivation (Polynomial R) A`.
-/
noncomputable section
namespace Polynomial
section CommSemiring
variable {R A : Type*} [CommSemiring R]
/-- `Polynomial.derivative` as a derivation. -/
@[simps]
def derivative' : Derivation R R[X] R[X] where
toFun := derivative
map_add' _ _ := derivative_add
map_smul' := derivative_smul
map_one_eq_zero' := derivative_one
leibniz' f g := by simp [mul_comm, add_comm, derivative_mul]
variable [AddCommMonoid A] [Module R A] [Module (Polynomial R) A]
@[simp]
theorem derivation_C (D : Derivation R R[X] A) (a : R) : D (C a) = 0 :=
D.map_algebraMap a
@[simp]
theorem C_smul_derivation_apply (D : Derivation R R[X] A) (a : R) (f : R[X]) :
C a • D f = a • D f := by
have : C a • D f = D (C a * f) := by simp
rw [this, C_mul', D.map_smul]
@[ext]
theorem derivation_ext {D₁ D₂ : Derivation R R[X] A} (h : D₁ X = D₂ X) : D₁ = D₂ :=
Derivation.ext fun f => Derivation.eqOn_adjoin (Set.eqOn_singleton.2 h) <| by
simp only [adjoin_X, Algebra.coe_top, Set.mem_univ]
variable [IsScalarTower R (Polynomial R) A]
variable (R)
/-- The derivation on `R[X]` that takes the value `a` on `X`. -/
def mkDerivation : A →ₗ[R] Derivation R R[X] A where
toFun := fun a ↦ (LinearMap.toSpanSingleton R[X] A a).compDer derivative'
map_add' := fun a b ↦ by ext; simp
map_smul' := fun t a ↦ by ext; simp
lemma mkDerivation_apply (a : A) (f : R[X]) :
mkDerivation R a f = derivative f • a := by
rfl
@[simp]
theorem mkDerivation_X (a : A) : mkDerivation R a X = a := by simp [mkDerivation_apply]
lemma mkDerivation_one_eq_derivative' : mkDerivation R (1 : R[X]) = derivative' := by
ext : 1
simp [derivative']
lemma mkDerivation_one_eq_derivative (f : R[X]) : mkDerivation R (1 : R[X]) f = derivative f := by
rw [mkDerivation_one_eq_derivative']
rfl
/-- `Polynomial.mkDerivation` as a linear equivalence. -/
def mkDerivationEquiv : A ≃ₗ[R] Derivation R R[X] A :=
LinearEquiv.symm <|
{ invFun := mkDerivation R
toFun := fun D => D X
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl
left_inv := fun _ => derivation_ext <| mkDerivation_X _ _
right_inv := fun _ => mkDerivation_X _ _ }
|
@[simp] lemma mkDerivationEquiv_apply (a : A) :
mkDerivationEquiv R a = mkDerivation R a := by
| Mathlib/Algebra/Polynomial/Derivation.lean | 87 | 89 |
/-
Copyright (c) 2020 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash, Antoine Labelle
-/
import Mathlib.LinearAlgebra.Dual.Lemmas
import Mathlib.LinearAlgebra.Matrix.ToLin
/-!
# Contractions
Given modules $M, N$ over a commutative ring $R$, this file defines the natural linear maps:
$M^* \otimes M \to R$, $M \otimes M^* \to R$, and $M^* \otimes N → Hom(M, N)$, as well as proving
some basic properties of these maps.
## Tags
contraction, dual module, tensor product
-/
suppress_compilation
variable {ι : Type*} (R M N P Q : Type*)
-- Porting note: we need high priority for this to fire first; not the case in ML3
attribute [local ext high] TensorProduct.ext
section Contraction
open TensorProduct LinearMap Matrix Module
open TensorProduct
section CommSemiring
variable [CommSemiring R]
variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P] [AddCommMonoid Q]
variable [Module R M] [Module R N] [Module R P] [Module R Q]
variable [DecidableEq ι] [Fintype ι] (b : Basis ι R M)
/-- The natural left-handed pairing between a module and its dual. -/
def contractLeft : Module.Dual R M ⊗[R] M →ₗ[R] R :=
(uncurry _ _ _ _).toFun LinearMap.id
/-- The natural right-handed pairing between a module and its dual. -/
def contractRight : M ⊗[R] Module.Dual R M →ₗ[R] R :=
(uncurry _ _ _ _).toFun (LinearMap.flip LinearMap.id)
/-- The natural map associating a linear map to the tensor product of two modules. -/
def dualTensorHom : Module.Dual R M ⊗[R] N →ₗ[R] M →ₗ[R] N :=
let M' := Module.Dual R M
(uncurry R M' N (M →ₗ[R] N) : _ → M' ⊗ N →ₗ[R] M →ₗ[R] N) LinearMap.smulRightₗ
variable {R M N P Q}
@[simp]
theorem contractLeft_apply (f : Module.Dual R M) (m : M) : contractLeft R M (f ⊗ₜ m) = f m :=
rfl
@[simp]
theorem contractRight_apply (f : Module.Dual R M) (m : M) : contractRight R M (m ⊗ₜ f) = f m :=
rfl
@[simp]
theorem dualTensorHom_apply (f : Module.Dual R M) (m : M) (n : N) :
dualTensorHom R M N (f ⊗ₜ n) m = f m • n :=
rfl
@[simp]
theorem transpose_dualTensorHom (f : Module.Dual R M) (m : M) :
Dual.transpose (R := R) (dualTensorHom R M M (f ⊗ₜ m)) =
dualTensorHom R _ _ (Dual.eval R M m ⊗ₜ f) := by
ext f' m'
simp only [Dual.transpose_apply, coe_comp, Function.comp_apply, dualTensorHom_apply,
LinearMap.map_smulₛₗ, RingHom.id_apply, Algebra.id.smul_eq_mul, Dual.eval_apply,
LinearMap.smul_apply]
exact mul_comm _ _
@[simp]
theorem dualTensorHom_prodMap_zero (f : Module.Dual R M) (p : P) :
((dualTensorHom R M P) (f ⊗ₜ[R] p)).prodMap (0 : N →ₗ[R] Q) =
dualTensorHom R (M × N) (P × Q) ((f ∘ₗ fst R M N) ⊗ₜ inl R P Q p) := by
ext <;>
simp only [coe_comp, coe_inl, Function.comp_apply, prodMap_apply, dualTensorHom_apply,
fst_apply, Prod.smul_mk, LinearMap.zero_apply, smul_zero]
@[simp]
theorem zero_prodMap_dualTensorHom (g : Module.Dual R N) (q : Q) :
(0 : M →ₗ[R] P).prodMap ((dualTensorHom R N Q) (g ⊗ₜ[R] q)) =
dualTensorHom R (M × N) (P × Q) ((g ∘ₗ snd R M N) ⊗ₜ inr R P Q q) := by
ext <;>
simp only [coe_comp, coe_inr, Function.comp_apply, prodMap_apply, dualTensorHom_apply,
snd_apply, Prod.smul_mk, LinearMap.zero_apply, smul_zero]
theorem map_dualTensorHom (f : Module.Dual R M) (p : P) (g : Module.Dual R N) (q : Q) :
TensorProduct.map (dualTensorHom R M P (f ⊗ₜ[R] p)) (dualTensorHom R N Q (g ⊗ₜ[R] q)) =
dualTensorHom R (M ⊗[R] N) (P ⊗[R] Q) (dualDistrib R M N (f ⊗ₜ g) ⊗ₜ[R] p ⊗ₜ[R] q) := by
ext m n
simp only [compr₂_apply, mk_apply, map_tmul, dualTensorHom_apply, dualDistrib_apply, ←
smul_tmul_smul]
@[simp]
theorem comp_dualTensorHom (f : Module.Dual R M) (n : N) (g : Module.Dual R N) (p : P) :
dualTensorHom R N P (g ⊗ₜ[R] p) ∘ₗ dualTensorHom R M N (f ⊗ₜ[R] n) =
g n • dualTensorHom R M P (f ⊗ₜ p) := by
ext m
simp only [coe_comp, Function.comp_apply, dualTensorHom_apply, LinearMap.map_smul,
RingHom.id_apply, LinearMap.smul_apply]
rw [smul_comm]
/-- As a matrix, `dualTensorHom` evaluated on a basis element of `M* ⊗ N` is a matrix with a
single one and zeros elsewhere -/
theorem toMatrix_dualTensorHom {m : Type*} {n : Type*} [Fintype m] [Finite n] [DecidableEq m]
[DecidableEq n] (bM : Basis m R M) (bN : Basis n R N) (j : m) (i : n) :
toMatrix bM bN (dualTensorHom R M N (bM.coord j ⊗ₜ bN i)) = stdBasisMatrix i j 1 := by
ext i' j'
by_cases hij : i = i' ∧ j = j' <;>
simp [LinearMap.toMatrix_apply, Finsupp.single_eq_pi_single, hij]
rw [and_iff_not_or_not, Classical.not_not] at hij
rcases hij with hij | hij <;> simp [hij]
end CommSemiring
section CommRing
variable [CommRing R]
variable [AddCommGroup M] [AddCommGroup N] [AddCommGroup P] [AddCommGroup Q]
variable [Module R M] [Module R N] [Module R P] [Module R Q]
variable [DecidableEq ι] [Fintype ι] (b : Basis ι R M)
variable {R M N P Q}
/-- If `M` is free, the natural linear map $M^* ⊗ N → Hom(M, N)$ is an equivalence. This function
provides this equivalence in return for a basis of `M`. -/
-- We manually create simp-lemmas because `@[simps]` generates a malformed lemma
noncomputable def dualTensorHomEquivOfBasis : Module.Dual R M ⊗[R] N ≃ₗ[R] M →ₗ[R] N :=
LinearEquiv.ofLinear (dualTensorHom R M N)
(∑ i, TensorProduct.mk R _ N (b.dualBasis i) ∘ₗ (LinearMap.applyₗ (R := R) (b i)))
(by
ext f m
simp only [applyₗ_apply_apply, coeFn_sum, dualTensorHom_apply, mk_apply, id_coe, _root_.id,
Fintype.sum_apply, Function.comp_apply, Basis.coe_dualBasis, coe_comp, Basis.coord_apply, ←
f.map_smul, _root_.map_sum (dualTensorHom R M N), ← _root_.map_sum f, b.sum_repr])
(by
ext f m
simp only [applyₗ_apply_apply, coeFn_sum, dualTensorHom_apply, mk_apply, id_coe, _root_.id,
Fintype.sum_apply, Function.comp_apply, Basis.coe_dualBasis, coe_comp, compr₂_apply,
tmul_smul, smul_tmul', ← sum_tmul, Basis.sum_dual_apply_smul_coord])
@[simp]
theorem dualTensorHomEquivOfBasis_apply (x : Module.Dual R M ⊗[R] N) :
dualTensorHomEquivOfBasis b x = dualTensorHom R M N x := by
ext; rfl
@[simp]
theorem dualTensorHomEquivOfBasis_toLinearMap :
(dualTensorHomEquivOfBasis b).toLinearMap = dualTensorHom R M N :=
rfl
@[simp]
theorem dualTensorHomEquivOfBasis_symm_cancel_left (x : Module.Dual R M ⊗[R] N) :
(dualTensorHomEquivOfBasis b).symm (dualTensorHom R M N x) = x := by
rw [← dualTensorHomEquivOfBasis_apply b,
LinearEquiv.symm_apply_apply <| dualTensorHomEquivOfBasis (N := N) b]
@[simp]
theorem dualTensorHomEquivOfBasis_symm_cancel_right (x : M →ₗ[R] N) :
dualTensorHom R M N ((dualTensorHomEquivOfBasis b).symm x) = x := by
rw [← dualTensorHomEquivOfBasis_apply b, LinearEquiv.apply_symm_apply]
variable (R M N P Q)
variable [Module.Free R M] [Module.Finite R M]
/-- If `M` is finite free, the natural map $M^* ⊗ N → Hom(M, N)$ is an
equivalence. -/
@[simp]
noncomputable def dualTensorHomEquiv : Module.Dual R M ⊗[R] N ≃ₗ[R] M →ₗ[R] N :=
dualTensorHomEquivOfBasis (Module.Free.chooseBasis R M)
end CommRing
end Contraction
section HomTensorHom
open TensorProduct
|
open Module TensorProduct LinearMap
section CommRing
| Mathlib/LinearAlgebra/Contraction.lean | 186 | 189 |
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Multiset.ZeroCons
/-!
# Basic results on multisets
-/
-- No algebra should be required
assert_not_exists Monoid
universe v
open List Subtype Nat Function
variable {α : Type*} {β : Type v} {γ : Type*}
namespace Multiset
/-! ### `Multiset.toList` -/
section ToList
/-- Produces a list of the elements in the multiset using choice. -/
noncomputable def toList (s : Multiset α) :=
s.out
@[simp, norm_cast]
theorem coe_toList (s : Multiset α) : (s.toList : Multiset α) = s :=
s.out_eq'
@[simp]
theorem toList_eq_nil {s : Multiset α} : s.toList = [] ↔ s = 0 := by
rw [← coe_eq_zero, coe_toList]
theorem empty_toList {s : Multiset α} : s.toList.isEmpty ↔ s = 0 := by simp
@[simp]
theorem toList_zero : (Multiset.toList 0 : List α) = [] :=
toList_eq_nil.mpr rfl
@[simp]
theorem mem_toList {a : α} {s : Multiset α} : a ∈ s.toList ↔ a ∈ s := by
rw [← mem_coe, coe_toList]
@[simp]
theorem toList_eq_singleton_iff {a : α} {m : Multiset α} : m.toList = [a] ↔ m = {a} := by
rw [← perm_singleton, ← coe_eq_coe, coe_toList, coe_singleton]
@[simp]
theorem toList_singleton (a : α) : ({a} : Multiset α).toList = [a] :=
Multiset.toList_eq_singleton_iff.2 rfl
@[simp]
theorem length_toList (s : Multiset α) : s.toList.length = card s := by
rw [← coe_card, coe_toList]
end ToList
/-! ### Induction principles -/
/-- The strong induction principle for multisets. -/
@[elab_as_elim]
def strongInductionOn {p : Multiset α → Sort*} (s : Multiset α) (ih : ∀ s, (∀ t < s, p t) → p s) :
p s :=
(ih s) fun t _h =>
strongInductionOn t ih
termination_by card s
decreasing_by exact card_lt_card _h
theorem strongInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) (H) :
@strongInductionOn _ p s H = H s fun t _h => @strongInductionOn _ p t H := by
rw [strongInductionOn]
@[elab_as_elim]
theorem case_strongInductionOn {p : Multiset α → Prop} (s : Multiset α) (h₀ : p 0)
(h₁ : ∀ a s, (∀ t ≤ s, p t) → p (a ::ₘ s)) : p s :=
Multiset.strongInductionOn s fun s =>
Multiset.induction_on s (fun _ => h₀) fun _a _s _ ih =>
(h₁ _ _) fun _t h => ih _ <| lt_of_le_of_lt h <| lt_cons_self _ _
/-- Suppose that, given that `p t` can be defined on all supersets of `s` of cardinality less than
`n`, one knows how to define `p s`. Then one can inductively define `p s` for all multisets `s` of
cardinality less than `n`, starting from multisets of card `n` and iterating. This
can be used either to define data, or to prove properties. -/
def strongDownwardInduction {p : Multiset α → Sort*} {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁)
(s : Multiset α) :
card s ≤ n → p s :=
H s fun {t} ht _h =>
strongDownwardInduction H t ht
termination_by n - card s
decreasing_by simp_wf; have := (card_lt_card _h); omega
theorem strongDownwardInduction_eq {p : Multiset α → Sort*} {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁)
(s : Multiset α) :
strongDownwardInduction H s = H s fun ht _hst => strongDownwardInduction H _ ht := by
rw [strongDownwardInduction]
/-- Analogue of `strongDownwardInduction` with order of arguments swapped. -/
@[elab_as_elim]
def strongDownwardInductionOn {p : Multiset α → Sort*} {n : ℕ} :
∀ s : Multiset α,
(∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) →
card s ≤ n → p s :=
fun s H => strongDownwardInduction H s
theorem strongDownwardInductionOn_eq {p : Multiset α → Sort*} (s : Multiset α) {n : ℕ}
(H : ∀ t₁, (∀ {t₂ : Multiset α}, card t₂ ≤ n → t₁ < t₂ → p t₂) → card t₁ ≤ n → p t₁) :
s.strongDownwardInductionOn H = H s fun {t} ht _h => t.strongDownwardInductionOn H ht := by
dsimp only [strongDownwardInductionOn]
rw [strongDownwardInduction]
section Choose
variable (p : α → Prop) [DecidablePred p] (l : Multiset α)
/-- Given a proof `hp` that there exists a unique `a ∈ l` such that `p a`, `chooseX p l hp` returns
that `a` together with proofs of `a ∈ l` and `p a`. -/
def chooseX : ∀ _hp : ∃! a, a ∈ l ∧ p a, { a // a ∈ l ∧ p a } :=
Quotient.recOn l (fun l' ex_unique => List.chooseX p l' (ExistsUnique.exists ex_unique))
(by
intros a b _
funext hp
suffices all_equal : ∀ x y : { t // t ∈ b ∧ p t }, x = y by
apply all_equal
rintro ⟨x, px⟩ ⟨y, py⟩
rcases hp with ⟨z, ⟨_z_mem_l, _pz⟩, z_unique⟩
congr
calc
x = z := z_unique x px
_ = y := (z_unique y py).symm
)
/-- Given a proof `hp` that there exists a unique `a ∈ l` such that `p a`, `choose p l hp` returns
that `a`. -/
def choose (hp : ∃! a, a ∈ l ∧ p a) : α :=
chooseX p l hp
theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) :=
(chooseX p l hp).property
theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l :=
(choose_spec _ _ _).1
theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) :=
(choose_spec _ _ _).2
end Choose
variable (α) in
/-- The equivalence between lists and multisets of a subsingleton type. -/
def subsingletonEquiv [Subsingleton α] : List α ≃ Multiset α where
toFun := ofList
invFun :=
(Quot.lift id) fun (a b : List α) (h : a ~ b) =>
(List.ext_get h.length_eq) fun _ _ _ => Subsingleton.elim _ _
left_inv _ := rfl
right_inv m := Quot.inductionOn m fun _ => rfl
@[simp]
theorem coe_subsingletonEquiv [Subsingleton α] :
(subsingletonEquiv α : List α → Multiset α) = ofList :=
rfl
section SizeOf
set_option linter.deprecated false in
@[deprecated "Deprecated without replacement." (since := "2025-02-07")]
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Multiset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
induction s using Quot.inductionOn
exact List.sizeOf_lt_sizeOf_of_mem hx
end SizeOf
end Multiset
| Mathlib/Data/Multiset/Basic.lean | 2,735 | 2,736 | |
/-
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.SpecificLimits.Basic
import Mathlib.Topology.MetricSpace.IsometricSMul
/-!
# Hausdorff distance
The Hausdorff distance on subsets of a metric (or emetric) space.
Given two subsets `s` and `t` of a metric space, their Hausdorff distance is the smallest `d`
such that any point `s` is within `d` of a point in `t`, and conversely. This quantity
is often infinite (think of `s` bounded and `t` unbounded), and therefore better
expressed in the setting of emetric spaces.
## Main definitions
This files introduces:
* `EMetric.infEdist x s`, the infimum edistance of a point `x` to a set `s` in an emetric space
* `EMetric.hausdorffEdist s t`, the Hausdorff edistance of two sets in an emetric space
* Versions of these notions on metric spaces, called respectively `Metric.infDist`
and `Metric.hausdorffDist`
## Main results
* `infEdist_closure`: the edistance to a set and its closure coincide
* `EMetric.mem_closure_iff_infEdist_zero`: a point `x` belongs to the closure of `s` iff
`infEdist x s = 0`
* `IsCompact.exists_infEdist_eq_edist`: if `s` is compact and non-empty, there exists a point `y`
which attains this edistance
* `IsOpen.exists_iUnion_isClosed`: every open set `U` can be written as the increasing union
of countably many closed subsets of `U`
* `hausdorffEdist_closure`: replacing a set by its closure does not change the Hausdorff edistance
* `hausdorffEdist_zero_iff_closure_eq_closure`: two sets have Hausdorff edistance zero
iff their closures coincide
* the Hausdorff edistance is symmetric and satisfies the triangle inequality
* in particular, closed sets in an emetric space are an emetric space
(this is shown in `EMetricSpace.closeds.emetricspace`)
* versions of these notions on metric spaces
* `hausdorffEdist_ne_top_of_nonempty_of_bounded`: if two sets in a metric space
are nonempty and bounded in a metric space, they are at finite Hausdorff edistance.
## Tags
metric space, Hausdorff distance
-/
noncomputable section
open NNReal ENNReal Topology Set Filter Pointwise Bornology
universe u v w
variable {ι : Sort*} {α : Type u} {β : Type v}
namespace EMetric
section InfEdist
variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] {x y : α} {s t : Set α} {Φ : α → β}
/-! ### Distance of a point to a set as a function into `ℝ≥0∞`. -/
/-- The minimal edistance of a point to a set -/
def infEdist (x : α) (s : Set α) : ℝ≥0∞ :=
⨅ y ∈ s, edist x y
@[simp]
theorem infEdist_empty : infEdist x ∅ = ∞ :=
iInf_emptyset
theorem le_infEdist {d} : d ≤ infEdist x s ↔ ∀ y ∈ s, d ≤ edist x y := by
simp only [infEdist, le_iInf_iff]
/-- The edist to a union is the minimum of the edists -/
@[simp]
theorem infEdist_union : infEdist x (s ∪ t) = infEdist x s ⊓ infEdist x t :=
iInf_union
@[simp]
theorem infEdist_iUnion (f : ι → Set α) (x : α) : infEdist x (⋃ i, f i) = ⨅ i, infEdist x (f i) :=
iInf_iUnion f _
lemma infEdist_biUnion {ι : Type*} (f : ι → Set α) (I : Set ι) (x : α) :
infEdist x (⋃ i ∈ I, f i) = ⨅ i ∈ I, infEdist x (f i) := by simp only [infEdist_iUnion]
/-- The edist to a singleton is the edistance to the single point of this singleton -/
@[simp]
theorem infEdist_singleton : infEdist x {y} = edist x y :=
iInf_singleton
/-- The edist to a set is bounded above by the edist to any of its points -/
theorem infEdist_le_edist_of_mem (h : y ∈ s) : infEdist x s ≤ edist x y :=
iInf₂_le y h
/-- If a point `x` belongs to `s`, then its edist to `s` vanishes -/
theorem infEdist_zero_of_mem (h : x ∈ s) : infEdist x s = 0 :=
nonpos_iff_eq_zero.1 <| @edist_self _ _ x ▸ infEdist_le_edist_of_mem h
/-- The edist is antitone with respect to inclusion. -/
theorem infEdist_anti (h : s ⊆ t) : infEdist x t ≤ infEdist x s :=
iInf_le_iInf_of_subset h
/-- The edist to a set is `< r` iff there exists a point in the set at edistance `< r` -/
theorem infEdist_lt_iff {r : ℝ≥0∞} : infEdist x s < r ↔ ∃ y ∈ s, edist x y < r := by
simp_rw [infEdist, iInf_lt_iff, exists_prop]
/-- The edist of `x` to `s` is bounded by the sum of the edist of `y` to `s` and
the edist from `x` to `y` -/
theorem infEdist_le_infEdist_add_edist : infEdist x s ≤ infEdist y s + edist x y :=
calc
⨅ z ∈ s, edist x z ≤ ⨅ z ∈ s, edist y z + edist x y :=
iInf₂_mono fun _ _ => (edist_triangle _ _ _).trans_eq (add_comm _ _)
_ = (⨅ z ∈ s, edist y z) + edist x y := by simp only [ENNReal.iInf_add]
theorem infEdist_le_edist_add_infEdist : infEdist x s ≤ edist x y + infEdist y s := by
rw [add_comm]
exact infEdist_le_infEdist_add_edist
theorem edist_le_infEdist_add_ediam (hy : y ∈ s) : edist x y ≤ infEdist x s + diam s := by
simp_rw [infEdist, ENNReal.iInf_add]
refine le_iInf₂ fun i hi => ?_
calc
edist x y ≤ edist x i + edist i y := edist_triangle _ _ _
_ ≤ edist x i + diam s := add_le_add le_rfl (edist_le_diam_of_mem hi hy)
/-- The edist to a set depends continuously on the point -/
@[continuity]
theorem continuous_infEdist : Continuous fun x => infEdist x s :=
continuous_of_le_add_edist 1 (by simp) <| by
simp only [one_mul, infEdist_le_infEdist_add_edist, forall₂_true_iff]
/-- The edist to a set and to its closure coincide -/
theorem infEdist_closure : infEdist x (closure s) = infEdist x s := by
refine le_antisymm (infEdist_anti subset_closure) ?_
refine ENNReal.le_of_forall_pos_le_add fun ε εpos h => ?_
have ε0 : 0 < (ε / 2 : ℝ≥0∞) := by simpa [pos_iff_ne_zero] using εpos
have : infEdist x (closure s) < infEdist x (closure s) + ε / 2 :=
ENNReal.lt_add_right h.ne ε0.ne'
obtain ⟨y : α, ycs : y ∈ closure s, hy : edist x y < infEdist x (closure s) + ↑ε / 2⟩ :=
infEdist_lt_iff.mp this
obtain ⟨z : α, zs : z ∈ s, dyz : edist y z < ↑ε / 2⟩ := EMetric.mem_closure_iff.1 ycs (ε / 2) ε0
calc
infEdist x s ≤ edist x z := infEdist_le_edist_of_mem zs
_ ≤ edist x y + edist y z := edist_triangle _ _ _
_ ≤ infEdist x (closure s) + ε / 2 + ε / 2 := add_le_add (le_of_lt hy) (le_of_lt dyz)
_ = infEdist x (closure s) + ↑ε := by rw [add_assoc, ENNReal.add_halves]
/-- A point belongs to the closure of `s` iff its infimum edistance to this set vanishes -/
theorem mem_closure_iff_infEdist_zero : x ∈ closure s ↔ infEdist x s = 0 :=
⟨fun h => by
rw [← infEdist_closure]
exact infEdist_zero_of_mem h,
fun h =>
EMetric.mem_closure_iff.2 fun ε εpos => infEdist_lt_iff.mp <| by rwa [h]⟩
/-- Given a closed set `s`, a point belongs to `s` iff its infimum edistance to this set vanishes -/
theorem mem_iff_infEdist_zero_of_closed (h : IsClosed s) : x ∈ s ↔ infEdist x s = 0 := by
rw [← mem_closure_iff_infEdist_zero, h.closure_eq]
/-- The infimum edistance of a point to a set is positive if and only if the point is not in the
closure of the set. -/
theorem infEdist_pos_iff_not_mem_closure {x : α} {E : Set α} :
0 < infEdist x E ↔ x ∉ closure E := by
rw [mem_closure_iff_infEdist_zero, pos_iff_ne_zero]
theorem infEdist_closure_pos_iff_not_mem_closure {x : α} {E : Set α} :
0 < infEdist x (closure E) ↔ x ∉ closure E := by
rw [infEdist_closure, infEdist_pos_iff_not_mem_closure]
theorem exists_real_pos_lt_infEdist_of_not_mem_closure {x : α} {E : Set α} (h : x ∉ closure E) :
∃ ε : ℝ, 0 < ε ∧ ENNReal.ofReal ε < infEdist x E := by
rw [← infEdist_pos_iff_not_mem_closure, ENNReal.lt_iff_exists_real_btwn] at h
rcases h with ⟨ε, ⟨_, ⟨ε_pos, ε_lt⟩⟩⟩
exact ⟨ε, ⟨ENNReal.ofReal_pos.mp ε_pos, ε_lt⟩⟩
theorem disjoint_closedBall_of_lt_infEdist {r : ℝ≥0∞} (h : r < infEdist x s) :
Disjoint (closedBall x r) s := by
rw [disjoint_left]
intro y hy h'y
apply lt_irrefl (infEdist x s)
calc
infEdist x s ≤ edist x y := infEdist_le_edist_of_mem h'y
_ ≤ r := by rwa [mem_closedBall, edist_comm] at hy
_ < infEdist x s := h
/-- The infimum edistance is invariant under isometries -/
theorem infEdist_image (hΦ : Isometry Φ) : infEdist (Φ x) (Φ '' t) = infEdist x t := by
simp only [infEdist, iInf_image, hΦ.edist_eq]
@[to_additive (attr := simp)]
theorem infEdist_smul {M} [SMul M α] [IsIsometricSMul M α] (c : M) (x : α) (s : Set α) :
infEdist (c • x) (c • s) = infEdist x s :=
infEdist_image (isometry_smul _ _)
theorem _root_.IsOpen.exists_iUnion_isClosed {U : Set α} (hU : IsOpen U) :
∃ F : ℕ → Set α, (∀ n, IsClosed (F n)) ∧ (∀ n, F n ⊆ U) ∧ ⋃ n, F n = U ∧ Monotone F := by
obtain ⟨a, a_pos, a_lt_one⟩ : ∃ a : ℝ≥0∞, 0 < a ∧ a < 1 := exists_between zero_lt_one
let F := fun n : ℕ => (fun x => infEdist x Uᶜ) ⁻¹' Ici (a ^ n)
have F_subset : ∀ n, F n ⊆ U := fun n x hx ↦ by
by_contra h
have : infEdist x Uᶜ ≠ 0 := ((ENNReal.pow_pos a_pos _).trans_le hx).ne'
exact this (infEdist_zero_of_mem h)
refine ⟨F, fun n => IsClosed.preimage continuous_infEdist isClosed_Ici, F_subset, ?_, ?_⟩
· show ⋃ n, F n = U
refine Subset.antisymm (by simp only [iUnion_subset_iff, F_subset, forall_const]) fun x hx => ?_
have : ¬x ∈ Uᶜ := by simpa using hx
rw [mem_iff_infEdist_zero_of_closed hU.isClosed_compl] at this
have B : 0 < infEdist x Uᶜ := by simpa [pos_iff_ne_zero] using this
have : Filter.Tendsto (fun n => a ^ n) atTop (𝓝 0) :=
ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one a_lt_one
rcases ((tendsto_order.1 this).2 _ B).exists with ⟨n, hn⟩
simp only [mem_iUnion, mem_Ici, mem_preimage]
exact ⟨n, hn.le⟩
show Monotone F
intro m n hmn x hx
simp only [F, mem_Ici, mem_preimage] at hx ⊢
apply le_trans (pow_le_pow_right_of_le_one' a_lt_one.le hmn) hx
theorem _root_.IsCompact.exists_infEdist_eq_edist (hs : IsCompact s) (hne : s.Nonempty) (x : α) :
∃ y ∈ s, infEdist x s = edist x y := by
have A : Continuous fun y => edist x y := continuous_const.edist continuous_id
obtain ⟨y, ys, hy⟩ := hs.exists_isMinOn hne A.continuousOn
exact ⟨y, ys, le_antisymm (infEdist_le_edist_of_mem ys) (by rwa [le_infEdist])⟩
theorem exists_pos_forall_lt_edist (hs : IsCompact s) (ht : IsClosed t) (hst : Disjoint s t) :
∃ r : ℝ≥0, 0 < r ∧ ∀ x ∈ s, ∀ y ∈ t, (r : ℝ≥0∞) < edist x y := by
rcases s.eq_empty_or_nonempty with (rfl | hne)
· use 1
simp
obtain ⟨x, hx, h⟩ := hs.exists_isMinOn hne continuous_infEdist.continuousOn
have : 0 < infEdist x t :=
pos_iff_ne_zero.2 fun H => hst.le_bot ⟨hx, (mem_iff_infEdist_zero_of_closed ht).mpr H⟩
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 this with ⟨r, h₀, hr⟩
exact ⟨r, ENNReal.coe_pos.mp h₀, fun y hy z hz => hr.trans_le <| le_infEdist.1 (h hy) z hz⟩
end InfEdist
/-! ### The Hausdorff distance as a function into `ℝ≥0∞`. -/
/-- The Hausdorff edistance between two sets is the smallest `r` such that each set
is contained in the `r`-neighborhood of the other one -/
irreducible_def hausdorffEdist {α : Type u} [PseudoEMetricSpace α] (s t : Set α) : ℝ≥0∞ :=
(⨆ x ∈ s, infEdist x t) ⊔ ⨆ y ∈ t, infEdist y s
section HausdorffEdist
variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] {x : α} {s t u : Set α} {Φ : α → β}
/-- The Hausdorff edistance of a set to itself vanishes. -/
@[simp]
theorem hausdorffEdist_self : hausdorffEdist s s = 0 := by
simp only [hausdorffEdist_def, sup_idem, ENNReal.iSup_eq_zero]
exact fun x hx => infEdist_zero_of_mem hx
/-- The Haudorff edistances of `s` to `t` and of `t` to `s` coincide. -/
theorem hausdorffEdist_comm : hausdorffEdist s t = hausdorffEdist t s := by
simp only [hausdorffEdist_def]; apply sup_comm
/-- Bounding the Hausdorff edistance by bounding the edistance of any point
in each set to the other set -/
theorem hausdorffEdist_le_of_infEdist {r : ℝ≥0∞} (H1 : ∀ x ∈ s, infEdist x t ≤ r)
(H2 : ∀ x ∈ t, infEdist x s ≤ r) : hausdorffEdist s t ≤ r := by
simp only [hausdorffEdist_def, sup_le_iff, iSup_le_iff]
exact ⟨H1, H2⟩
/-- Bounding the Hausdorff edistance by exhibiting, for any point in each set,
another point in the other set at controlled distance -/
theorem hausdorffEdist_le_of_mem_edist {r : ℝ≥0∞} (H1 : ∀ x ∈ s, ∃ y ∈ t, edist x y ≤ r)
(H2 : ∀ x ∈ t, ∃ y ∈ s, edist x y ≤ r) : hausdorffEdist s t ≤ r := by
refine hausdorffEdist_le_of_infEdist (fun x xs ↦ ?_) (fun x xt ↦ ?_)
· rcases H1 x xs with ⟨y, yt, hy⟩
exact le_trans (infEdist_le_edist_of_mem yt) hy
· rcases H2 x xt with ⟨y, ys, hy⟩
exact le_trans (infEdist_le_edist_of_mem ys) hy
/-- The distance to a set is controlled by the Hausdorff distance. -/
theorem infEdist_le_hausdorffEdist_of_mem (h : x ∈ s) : infEdist x t ≤ hausdorffEdist s t := by
rw [hausdorffEdist_def]
refine le_trans ?_ le_sup_left
exact le_iSup₂ (α := ℝ≥0∞) x h
/-- If the Hausdorff distance is `< r`, then any point in one of the sets has
a corresponding point at distance `< r` in the other set. -/
theorem exists_edist_lt_of_hausdorffEdist_lt {r : ℝ≥0∞} (h : x ∈ s) (H : hausdorffEdist s t < r) :
∃ y ∈ t, edist x y < r :=
infEdist_lt_iff.mp <|
calc
infEdist x t ≤ hausdorffEdist s t := infEdist_le_hausdorffEdist_of_mem h
_ < r := H
/-- The distance from `x` to `s` or `t` is controlled in terms of the Hausdorff distance
between `s` and `t`. -/
theorem infEdist_le_infEdist_add_hausdorffEdist :
infEdist x t ≤ infEdist x s + hausdorffEdist s t :=
ENNReal.le_of_forall_pos_le_add fun ε εpos h => by
have ε0 : (ε / 2 : ℝ≥0∞) ≠ 0 := by simpa [pos_iff_ne_zero] using εpos
have : infEdist x s < infEdist x s + ε / 2 :=
ENNReal.lt_add_right (ENNReal.add_lt_top.1 h).1.ne ε0
obtain ⟨y : α, ys : y ∈ s, dxy : edist x y < infEdist x s + ↑ε / 2⟩ := infEdist_lt_iff.mp this
have : hausdorffEdist s t < hausdorffEdist s t + ε / 2 :=
ENNReal.lt_add_right (ENNReal.add_lt_top.1 h).2.ne ε0
obtain ⟨z : α, zt : z ∈ t, dyz : edist y z < hausdorffEdist s t + ↑ε / 2⟩ :=
exists_edist_lt_of_hausdorffEdist_lt ys this
calc
infEdist x t ≤ edist x z := infEdist_le_edist_of_mem zt
_ ≤ edist x y + edist y z := edist_triangle _ _ _
_ ≤ infEdist x s + ε / 2 + (hausdorffEdist s t + ε / 2) := add_le_add dxy.le dyz.le
_ = infEdist x s + hausdorffEdist s t + ε := by
simp [ENNReal.add_halves, add_comm, add_left_comm]
/-- The Hausdorff edistance is invariant under isometries. -/
theorem hausdorffEdist_image (h : Isometry Φ) :
| hausdorffEdist (Φ '' s) (Φ '' t) = hausdorffEdist s t := by
simp only [hausdorffEdist_def, iSup_image, infEdist_image h]
/-- The Hausdorff distance is controlled by the diameter of the union. -/
| Mathlib/Topology/MetricSpace/HausdorffDistance.lean | 318 | 321 |
/-
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.Defs
import Mathlib.Analysis.Calculus.ContDiff.FaaDiBruno
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Mul
/-!
# Higher differentiability of composition
We prove that the composition of `C^n` functions is `C^n`.
We also expand the API around `C^n` functions.
## Main results
* `ContDiff.comp` states that the composition of two `C^n` functions is `C^n`.
Similar results are given for `C^n` functions on domains.
## 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`.
## Tags
derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series
-/
noncomputable section
open scoped NNReal Nat ContDiff
universe u uE uF uG
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup AddCommGroup.toAddCommMonoid
open Set Fin Filter Function
open scoped Topology
variable {𝕜 : Type*} [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*} [NormedAddCommGroup X] [NormedSpace 𝕜 X] {s t : Set E} {f : E → F}
{g : F → G} {x x₀ : E} {b : E × F → G} {m n : WithTop ℕ∞} {p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Constants -/
section constants
theorem iteratedFDerivWithin_succ_const (n : ℕ) (c : F) :
iteratedFDerivWithin 𝕜 (n + 1) (fun _ : E ↦ c) s = 0 := by
induction n with
| zero =>
ext1
simp [iteratedFDerivWithin_succ_eq_comp_left, iteratedFDerivWithin_zero_eq_comp, comp_def]
| succ n IH =>
rw [iteratedFDerivWithin_succ_eq_comp_left, IH]
simp only [Pi.zero_def, comp_def, fderivWithin_const, map_zero]
@[simp]
theorem iteratedFDerivWithin_zero_fun {i : ℕ} :
iteratedFDerivWithin 𝕜 i (fun _ : E ↦ (0 : F)) s = 0 := by
cases i with
| zero => ext; simp
| succ i => apply iteratedFDerivWithin_succ_const
@[simp]
theorem iteratedFDeriv_zero_fun {n : ℕ} : (iteratedFDeriv 𝕜 n fun _ : E ↦ (0 : F)) = 0 :=
funext fun x ↦ by simp only [← iteratedFDerivWithin_univ, iteratedFDerivWithin_zero_fun]
theorem contDiff_zero_fun : ContDiff 𝕜 n fun _ : E => (0 : F) :=
analyticOnNhd_const.contDiff
/-- Constants are `C^∞`. -/
theorem contDiff_const {c : F} : ContDiff 𝕜 n fun _ : E => c :=
analyticOnNhd_const.contDiff
theorem contDiffOn_const {c : F} {s : Set E} : ContDiffOn 𝕜 n (fun _ : E => c) s :=
contDiff_const.contDiffOn
theorem contDiffAt_const {c : F} : ContDiffAt 𝕜 n (fun _ : E => c) x :=
contDiff_const.contDiffAt
theorem contDiffWithinAt_const {c : F} : ContDiffWithinAt 𝕜 n (fun _ : E => c) s x :=
contDiffAt_const.contDiffWithinAt
@[nontriviality]
theorem contDiff_of_subsingleton [Subsingleton F] : ContDiff 𝕜 n f := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiff_const
@[nontriviality]
theorem contDiffAt_of_subsingleton [Subsingleton F] : ContDiffAt 𝕜 n f x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffAt_const
@[nontriviality]
theorem contDiffWithinAt_of_subsingleton [Subsingleton F] : ContDiffWithinAt 𝕜 n f s x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffWithinAt_const
@[nontriviality]
theorem contDiffOn_of_subsingleton [Subsingleton F] : ContDiffOn 𝕜 n f s := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffOn_const
theorem iteratedFDerivWithin_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) (s : Set E) :
iteratedFDerivWithin 𝕜 n (fun _ : E ↦ c) s = 0 := by
cases n with
| zero => contradiction
| succ n => exact iteratedFDerivWithin_succ_const n c
theorem iteratedFDeriv_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) :
(iteratedFDeriv 𝕜 n fun _ : E ↦ c) = 0 := by
simp only [← iteratedFDerivWithin_univ, iteratedFDerivWithin_const_of_ne hn]
theorem iteratedFDeriv_succ_const (n : ℕ) (c : F) :
(iteratedFDeriv 𝕜 (n + 1) fun _ : E ↦ c) = 0 :=
iteratedFDeriv_const_of_ne (by simp) _
theorem contDiffWithinAt_singleton : ContDiffWithinAt 𝕜 n f {x} x :=
(contDiffWithinAt_const (c := f x)).congr (by simp) rfl
end constants
/-! ### Smoothness of linear functions -/
section linear
/-- Unbundled bounded linear functions are `C^n`. -/
theorem IsBoundedLinearMap.contDiff (hf : IsBoundedLinearMap 𝕜 f) : ContDiff 𝕜 n f :=
(ContinuousLinearMap.analyticOnNhd hf.toContinuousLinearMap univ).contDiff
theorem ContinuousLinearMap.contDiff (f : E →L[𝕜] F) : ContDiff 𝕜 n f :=
f.isBoundedLinearMap.contDiff
theorem ContinuousLinearEquiv.contDiff (f : E ≃L[𝕜] F) : ContDiff 𝕜 n f :=
(f : E →L[𝕜] F).contDiff
theorem LinearIsometry.contDiff (f : E →ₗᵢ[𝕜] F) : ContDiff 𝕜 n f :=
f.toContinuousLinearMap.contDiff
theorem LinearIsometryEquiv.contDiff (f : E ≃ₗᵢ[𝕜] F) : ContDiff 𝕜 n f :=
(f : E →L[𝕜] F).contDiff
/-- The identity is `C^n`. -/
theorem contDiff_id : ContDiff 𝕜 n (id : E → E) :=
IsBoundedLinearMap.id.contDiff
theorem contDiffWithinAt_id {s x} : ContDiffWithinAt 𝕜 n (id : E → E) s x :=
contDiff_id.contDiffWithinAt
theorem contDiffAt_id {x} : ContDiffAt 𝕜 n (id : E → E) x :=
contDiff_id.contDiffAt
theorem contDiffOn_id {s} : ContDiffOn 𝕜 n (id : E → E) s :=
contDiff_id.contDiffOn
/-- Bilinear functions are `C^n`. -/
theorem IsBoundedBilinearMap.contDiff (hb : IsBoundedBilinearMap 𝕜 b) : ContDiff 𝕜 n b :=
(hb.toContinuousLinearMap.analyticOnNhd_bilinear _).contDiff
/-- If `f` admits a Taylor series `p` in a set `s`, and `g` is linear, then `g ∘ f` admits a Taylor
series whose `k`-th term is given by `g ∘ (p k)`. -/
theorem HasFTaylorSeriesUpToOn.continuousLinearMap_comp {n : WithTop ℕ∞} (g : F →L[𝕜] G)
(hf : HasFTaylorSeriesUpToOn n f p s) :
HasFTaylorSeriesUpToOn n (g ∘ f) (fun x k => g.compContinuousMultilinearMap (p x k)) s where
zero_eq x hx := congr_arg g (hf.zero_eq x hx)
fderivWithin m hm x hx := (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin m => E) F G g).hasFDerivAt.comp_hasFDerivWithinAt x (hf.fderivWithin m hm x hx)
cont m hm := (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin m => E) F G g).continuous.comp_continuousOn (hf.cont m hm)
/-- Composition by continuous linear maps on the left preserves `C^n` functions in a domain
at a point. -/
theorem ContDiffWithinAt.continuousLinearMap_comp (g : F →L[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
match n with
| ω =>
obtain ⟨u, hu, p, hp, h'p⟩ := hf
refine ⟨u, hu, _, hp.continuousLinearMap_comp g, fun i ↦ ?_⟩
change AnalyticOn 𝕜
(fun x ↦ (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin i ↦ E) F G g) (p x i)) u
apply AnalyticOnNhd.comp_analyticOn _ (h'p i) (Set.mapsTo_univ _ _)
exact ContinuousLinearMap.analyticOnNhd _ _
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
exact ⟨u, hu, _, hp.continuousLinearMap_comp g⟩
/-- Composition by continuous linear maps on the left preserves `C^n` functions in a domain
at a point. -/
theorem ContDiffAt.continuousLinearMap_comp (g : F →L[𝕜] G) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (g ∘ f) x :=
ContDiffWithinAt.continuousLinearMap_comp g hf
/-- Composition by continuous linear maps on the left preserves `C^n` functions on domains. -/
theorem ContDiffOn.continuousLinearMap_comp (g : F →L[𝕜] G) (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (g ∘ f) s := fun x hx => (hf x hx).continuousLinearMap_comp g
/-- Composition by continuous linear maps on the left preserves `C^n` functions. -/
theorem ContDiff.continuousLinearMap_comp {f : E → F} (g : F →L[𝕜] G) (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n fun x => g (f x) :=
contDiffOn_univ.1 <| ContDiffOn.continuousLinearMap_comp _ (contDiffOn_univ.2 hf)
/-- The iterated derivative within a set of the composition with a linear map on the left is
obtained by applying the linear map to the iterated derivative. -/
theorem ContinuousLinearMap.iteratedFDerivWithin_comp_left {f : E → F} (g : F →L[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
g.compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) := by
rcases hf.contDiffOn' hi (by simp) with ⟨U, hU, hxU, hfU⟩
rw [← iteratedFDerivWithin_inter_open hU hxU, ← iteratedFDerivWithin_inter_open (f := f) hU hxU]
rw [insert_eq_of_mem hx] at hfU
exact .symm <| (hfU.ftaylorSeriesWithin (hs.inter hU)).continuousLinearMap_comp g
|>.eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl (hs.inter hU) ⟨hx, hxU⟩
/-- The iterated derivative of the composition with a linear map on the left is
obtained by applying the linear map to the iterated derivative. -/
theorem ContinuousLinearMap.iteratedFDeriv_comp_left {f : E → F} (g : F →L[𝕜] G)
(hf : ContDiffAt 𝕜 n f x) {i : ℕ} (hi : i ≤ n) :
iteratedFDeriv 𝕜 i (g ∘ f) x = g.compContinuousMultilinearMap (iteratedFDeriv 𝕜 i f x) := by
simp only [← iteratedFDerivWithin_univ]
exact g.iteratedFDerivWithin_comp_left hf.contDiffWithinAt uniqueDiffOn_univ (mem_univ x) hi
/-- The iterated derivative within a set of the composition with a linear equiv on the left is
obtained by applying the linear equiv to the iterated derivative. This is true without
differentiability assumptions. -/
theorem ContinuousLinearEquiv.iteratedFDerivWithin_comp_left (g : F ≃L[𝕜] G) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (i : ℕ) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(g : F →L[𝕜] G).compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) := by
induction' i with i IH generalizing x
· ext1 m
simp only [iteratedFDerivWithin_zero_apply, comp_apply,
ContinuousLinearMap.compContinuousMultilinearMap_coe, coe_coe]
· ext1 m
rw [iteratedFDerivWithin_succ_apply_left]
have Z : fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 i (g ∘ f) s) s x =
fderivWithin 𝕜 (g.continuousMultilinearMapCongrRight (fun _ : Fin i => E) ∘
iteratedFDerivWithin 𝕜 i f s) s x :=
fderivWithin_congr' (@IH) hx
simp_rw [Z]
rw [(g.continuousMultilinearMapCongrRight fun _ : Fin i => E).comp_fderivWithin (hs x hx)]
simp only [ContinuousLinearMap.coe_comp', ContinuousLinearEquiv.coe_coe, comp_apply,
ContinuousLinearEquiv.continuousMultilinearMapCongrRight_apply,
ContinuousLinearMap.compContinuousMultilinearMap_coe, EmbeddingLike.apply_eq_iff_eq]
rw [iteratedFDerivWithin_succ_apply_left]
/-- Composition with a linear isometry on the left preserves the norm of the iterated
derivative within a set. -/
theorem LinearIsometry.norm_iteratedFDerivWithin_comp_left {f : E → F} (g : F →ₗᵢ[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} (hi : i ≤ n) :
‖iteratedFDerivWithin 𝕜 i (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
have :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
g.toContinuousLinearMap.compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
g.toContinuousLinearMap.iteratedFDerivWithin_comp_left hf hs hx hi
rw [this]
apply LinearIsometry.norm_compContinuousMultilinearMap
/-- Composition with a linear isometry on the left preserves the norm of the iterated
derivative. -/
theorem LinearIsometry.norm_iteratedFDeriv_comp_left {f : E → F} (g : F →ₗᵢ[𝕜] G)
(hf : ContDiffAt 𝕜 n f x) {i : ℕ} (hi : i ≤ n) :
‖iteratedFDeriv 𝕜 i (g ∘ f) x‖ = ‖iteratedFDeriv 𝕜 i f x‖ := by
simp only [← iteratedFDerivWithin_univ]
exact g.norm_iteratedFDerivWithin_comp_left hf.contDiffWithinAt uniqueDiffOn_univ (mem_univ x) hi
/-- Composition with a linear isometry equiv on the left preserves the norm of the iterated
derivative within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left (g : F ≃ₗᵢ[𝕜] G) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (i : ℕ) :
‖iteratedFDerivWithin 𝕜 i (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
have :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(g : F →L[𝕜] G).compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
g.toContinuousLinearEquiv.iteratedFDerivWithin_comp_left f hs hx i
rw [this]
apply LinearIsometry.norm_compContinuousMultilinearMap g.toLinearIsometry
/-- Composition with a linear isometry equiv on the left preserves the norm of the iterated
derivative. -/
theorem LinearIsometryEquiv.norm_iteratedFDeriv_comp_left (g : F ≃ₗᵢ[𝕜] G) (f : E → F) (x : E)
(i : ℕ) : ‖iteratedFDeriv 𝕜 i (g ∘ f) x‖ = ‖iteratedFDeriv 𝕜 i f x‖ := by
rw [← iteratedFDerivWithin_univ, ← iteratedFDerivWithin_univ]
apply g.norm_iteratedFDerivWithin_comp_left f uniqueDiffOn_univ (mem_univ x) i
/-- Composition by continuous linear equivs on the left respects higher differentiability at a
point in a domain. -/
theorem ContinuousLinearEquiv.comp_contDiffWithinAt_iff (e : F ≃L[𝕜] G) :
ContDiffWithinAt 𝕜 n (e ∘ f) s x ↔ ContDiffWithinAt 𝕜 n f s x :=
⟨fun H => by
simpa only [Function.comp_def, e.symm.coe_coe, e.symm_apply_apply] using
H.continuousLinearMap_comp (e.symm : G →L[𝕜] F),
fun H => H.continuousLinearMap_comp (e : F →L[𝕜] G)⟩
/-- Composition by continuous linear equivs on the left respects higher differentiability at a
point. -/
theorem ContinuousLinearEquiv.comp_contDiffAt_iff (e : F ≃L[𝕜] G) :
ContDiffAt 𝕜 n (e ∘ f) x ↔ ContDiffAt 𝕜 n f x := by
simp only [← contDiffWithinAt_univ, e.comp_contDiffWithinAt_iff]
/-- Composition by continuous linear equivs on the left respects higher differentiability on
domains. -/
theorem ContinuousLinearEquiv.comp_contDiffOn_iff (e : F ≃L[𝕜] G) :
ContDiffOn 𝕜 n (e ∘ f) s ↔ ContDiffOn 𝕜 n f s := by
simp [ContDiffOn, e.comp_contDiffWithinAt_iff]
/-- Composition by continuous linear equivs on the left respects higher differentiability. -/
theorem ContinuousLinearEquiv.comp_contDiff_iff (e : F ≃L[𝕜] G) :
ContDiff 𝕜 n (e ∘ f) ↔ ContDiff 𝕜 n f := by
simp only [← contDiffOn_univ, e.comp_contDiffOn_iff]
/-- If `f` admits a Taylor series `p` in a set `s`, and `g` is linear, then `f ∘ g` admits a Taylor
series in `g ⁻¹' s`, whose `k`-th term is given by `p k (g v₁, ..., g vₖ)` . -/
theorem HasFTaylorSeriesUpToOn.compContinuousLinearMap
(hf : HasFTaylorSeriesUpToOn n f p s) (g : G →L[𝕜] E) :
HasFTaylorSeriesUpToOn n (f ∘ g) (fun x k => (p (g x) k).compContinuousLinearMap fun _ => g)
(g ⁻¹' s) := by
let A : ∀ m : ℕ, (E[×m]→L[𝕜] F) → G[×m]→L[𝕜] F := fun m h => h.compContinuousLinearMap fun _ => g
have hA : ∀ m, IsBoundedLinearMap 𝕜 (A m) := fun m =>
isBoundedLinearMap_continuousMultilinearMap_comp_linear g
constructor
· intro x hx
simp only [(hf.zero_eq (g x) hx).symm, Function.comp_apply]
change (p (g x) 0 fun _ : Fin 0 => g 0) = p (g x) 0 0
rw [ContinuousLinearMap.map_zero]
rfl
· intro m hm x hx
convert (hA m).hasFDerivAt.comp_hasFDerivWithinAt x
((hf.fderivWithin m hm (g x) hx).comp x g.hasFDerivWithinAt (Subset.refl _))
ext y v
change p (g x) (Nat.succ m) (g ∘ cons y v) = p (g x) m.succ (cons (g y) (g ∘ v))
rw [comp_cons]
· intro m hm
exact (hA m).continuous.comp_continuousOn <| (hf.cont m hm).comp g.continuous.continuousOn <|
Subset.refl _
/-- Composition by continuous linear maps on the right preserves `C^n` functions at a point on
a domain. -/
theorem ContDiffWithinAt.comp_continuousLinearMap {x : G} (g : G →L[𝕜] E)
(hf : ContDiffWithinAt 𝕜 n f s (g x)) : ContDiffWithinAt 𝕜 n (f ∘ g) (g ⁻¹' s) x := by
match n with
| ω =>
obtain ⟨u, hu, p, hp, h'p⟩ := hf
refine ⟨g ⁻¹' u, ?_, _, hp.compContinuousLinearMap g, ?_⟩
· refine g.continuous.continuousWithinAt.tendsto_nhdsWithin ?_ hu
exact (mapsTo_singleton.2 <| mem_singleton _).union_union (mapsTo_preimage _ _)
· intro i
change AnalyticOn 𝕜 (fun x ↦
ContinuousMultilinearMap.compContinuousLinearMapL (fun _ ↦ g) (p (g x) i)) (⇑g ⁻¹' u)
apply AnalyticOn.comp _ _ (Set.mapsTo_univ _ _)
· exact ContinuousLinearEquiv.analyticOn _ _
· exact (h'p i).comp (g.analyticOn _) (mapsTo_preimage _ _)
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
refine ⟨g ⁻¹' u, ?_, _, hp.compContinuousLinearMap g⟩
refine g.continuous.continuousWithinAt.tendsto_nhdsWithin ?_ hu
exact (mapsTo_singleton.2 <| mem_singleton _).union_union (mapsTo_preimage _ _)
/-- Composition by continuous linear maps on the right preserves `C^n` functions on domains. -/
theorem ContDiffOn.comp_continuousLinearMap (hf : ContDiffOn 𝕜 n f s) (g : G →L[𝕜] E) :
ContDiffOn 𝕜 n (f ∘ g) (g ⁻¹' s) := fun x hx => (hf (g x) hx).comp_continuousLinearMap g
/-- Composition by continuous linear maps on the right preserves `C^n` functions. -/
theorem ContDiff.comp_continuousLinearMap {f : E → F} {g : G →L[𝕜] E} (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n (f ∘ g) :=
contDiffOn_univ.1 <| ContDiffOn.comp_continuousLinearMap (contDiffOn_univ.2 hf) _
/-- The iterated derivative within a set of the composition with a linear map on the right is
obtained by composing the iterated derivative with the linear map. -/
theorem ContinuousLinearMap.iteratedFDerivWithin_comp_right {f : E → F} (g : G →L[𝕜] E)
(hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (h's : UniqueDiffOn 𝕜 (g ⁻¹' s)) {x : G}
(hx : g x ∈ s) {i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g :=
((((hf.of_le hi).ftaylorSeriesWithin hs).compContinuousLinearMap
g).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl h's hx).symm
/-- The iterated derivative within a set of the composition with a linear equiv on the right is
obtained by composing the iterated derivative with the linear equiv. -/
theorem ContinuousLinearEquiv.iteratedFDerivWithin_comp_right (g : G ≃L[𝕜] E) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) {x : G} (hx : g x ∈ s) (i : ℕ) :
iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g := by
induction' i with i IH generalizing x
· ext1
simp only [iteratedFDerivWithin_zero_apply, comp_apply,
ContinuousMultilinearMap.compContinuousLinearMap_apply]
· ext1 m
simp only [ContinuousMultilinearMap.compContinuousLinearMap_apply,
ContinuousLinearEquiv.coe_coe, iteratedFDerivWithin_succ_apply_left]
have : fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s)) (g ⁻¹' s) x =
fderivWithin 𝕜
(ContinuousLinearEquiv.continuousMultilinearMapCongrLeft _ (fun _x : Fin i => g) ∘
(iteratedFDerivWithin 𝕜 i f s ∘ g)) (g ⁻¹' s) x :=
fderivWithin_congr' (@IH) hx
rw [this, ContinuousLinearEquiv.comp_fderivWithin _ (g.uniqueDiffOn_preimage_iff.2 hs x hx)]
simp only [ContinuousLinearMap.coe_comp', ContinuousLinearEquiv.coe_coe, comp_apply,
ContinuousLinearEquiv.continuousMultilinearMapCongrLeft_apply,
ContinuousMultilinearMap.compContinuousLinearMap_apply]
rw [ContinuousLinearEquiv.comp_right_fderivWithin _ (g.uniqueDiffOn_preimage_iff.2 hs x hx),
ContinuousLinearMap.coe_comp', coe_coe, comp_apply, tail_def, tail_def]
/-- The iterated derivative of the composition with a linear map on the right is
obtained by composing the iterated derivative with the linear map. -/
theorem ContinuousLinearMap.iteratedFDeriv_comp_right (g : G →L[𝕜] E) {f : E → F}
(hf : ContDiff 𝕜 n f) (x : G) {i : ℕ} (hi : i ≤ n) :
iteratedFDeriv 𝕜 i (f ∘ g) x =
(iteratedFDeriv 𝕜 i f (g x)).compContinuousLinearMap fun _ => g := by
simp only [← iteratedFDerivWithin_univ]
exact g.iteratedFDerivWithin_comp_right hf.contDiffOn uniqueDiffOn_univ uniqueDiffOn_univ
(mem_univ _) hi
/-- Composition with a linear isometry on the right preserves the norm of the iterated derivative
within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right (g : G ≃ₗᵢ[𝕜] E) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) {x : G} (hx : g x ∈ s) (i : ℕ) :
‖iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x‖ = ‖iteratedFDerivWithin 𝕜 i f s (g x)‖ := by
have : iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g :=
g.toContinuousLinearEquiv.iteratedFDerivWithin_comp_right f hs hx i
rw [this, ContinuousMultilinearMap.norm_compContinuous_linearIsometryEquiv]
/-- Composition with a linear isometry on the right preserves the norm of the iterated derivative
within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDeriv_comp_right (g : G ≃ₗᵢ[𝕜] E) (f : E → F) (x : G)
(i : ℕ) : ‖iteratedFDeriv 𝕜 i (f ∘ g) x‖ = ‖iteratedFDeriv 𝕜 i f (g x)‖ := by
simp only [← iteratedFDerivWithin_univ]
apply g.norm_iteratedFDerivWithin_comp_right f uniqueDiffOn_univ (mem_univ (g x)) i
/-- Composition by continuous linear equivs on the right respects higher differentiability at a
point in a domain. -/
theorem ContinuousLinearEquiv.contDiffWithinAt_comp_iff (e : G ≃L[𝕜] E) :
ContDiffWithinAt 𝕜 n (f ∘ e) (e ⁻¹' s) (e.symm x) ↔ ContDiffWithinAt 𝕜 n f s x := by
constructor
· intro H
simpa [← preimage_comp, Function.comp_def] using H.comp_continuousLinearMap (e.symm : E →L[𝕜] G)
· intro H
rw [← e.apply_symm_apply x, ← e.coe_coe] at H
exact H.comp_continuousLinearMap _
/-- Composition by continuous linear equivs on the right respects higher differentiability at a
point. -/
theorem ContinuousLinearEquiv.contDiffAt_comp_iff (e : G ≃L[𝕜] E) :
ContDiffAt 𝕜 n (f ∘ e) (e.symm x) ↔ ContDiffAt 𝕜 n f x := by
rw [← contDiffWithinAt_univ, ← contDiffWithinAt_univ, ← preimage_univ]
exact e.contDiffWithinAt_comp_iff
/-- Composition by continuous linear equivs on the right respects higher differentiability on
domains. -/
theorem ContinuousLinearEquiv.contDiffOn_comp_iff (e : G ≃L[𝕜] E) :
ContDiffOn 𝕜 n (f ∘ e) (e ⁻¹' s) ↔ ContDiffOn 𝕜 n f s :=
⟨fun H => by simpa [Function.comp_def] using H.comp_continuousLinearMap (e.symm : E →L[𝕜] G),
fun H => H.comp_continuousLinearMap (e : G →L[𝕜] E)⟩
/-- Composition by continuous linear equivs on the right respects higher differentiability. -/
theorem ContinuousLinearEquiv.contDiff_comp_iff (e : G ≃L[𝕜] E) :
ContDiff 𝕜 n (f ∘ e) ↔ ContDiff 𝕜 n f := by
rw [← contDiffOn_univ, ← contDiffOn_univ, ← preimage_univ]
exact e.contDiffOn_comp_iff
end linear
/-! ### The Cartesian product of two C^n functions is C^n. -/
section prod
/-- If two functions `f` and `g` admit Taylor series `p` and `q` in a set `s`, then the cartesian
product of `f` and `g` admits the cartesian product of `p` and `q` as a Taylor series. -/
theorem HasFTaylorSeriesUpToOn.prodMk {n : WithTop ℕ∞}
(hf : HasFTaylorSeriesUpToOn n f p s) {g : E → G}
{q : E → FormalMultilinearSeries 𝕜 E G} (hg : HasFTaylorSeriesUpToOn n g q s) :
HasFTaylorSeriesUpToOn n (fun y => (f y, g y)) (fun y k => (p y k).prod (q y k)) s := by
set L := fun m => ContinuousMultilinearMap.prodL 𝕜 (fun _ : Fin m => E) F G
constructor
· intro x hx; rw [← hf.zero_eq x hx, ← hg.zero_eq x hx]; rfl
· intro m hm x hx
convert (L m).hasFDerivAt.comp_hasFDerivWithinAt x
((hf.fderivWithin m hm x hx).prodMk (hg.fderivWithin m hm x hx))
· intro m hm
exact (L m).continuous.comp_continuousOn ((hf.cont m hm).prodMk (hg.cont m hm))
@[deprecated (since := "2025-03-09")]
alias HasFTaylorSeriesUpToOn.prod := HasFTaylorSeriesUpToOn.prodMk
/-- The cartesian product of `C^n` functions at a point in a domain is `C^n`. -/
theorem ContDiffWithinAt.prodMk {s : Set E} {f : E → F} {g : E → G}
(hf : ContDiffWithinAt 𝕜 n f s x) (hg : ContDiffWithinAt 𝕜 n g s x) :
ContDiffWithinAt 𝕜 n (fun x : E => (f x, g x)) s x := by
match n with
| ω =>
obtain ⟨u, hu, p, hp, h'p⟩ := hf
obtain ⟨v, hv, q, hq, h'q⟩ := hg
refine ⟨u ∩ v, Filter.inter_mem hu hv, _,
(hp.mono inter_subset_left).prodMk (hq.mono inter_subset_right), fun i ↦ ?_⟩
change AnalyticOn 𝕜 (fun x ↦ ContinuousMultilinearMap.prodL _ _ _ _ (p x i, q x i)) (u ∩ v)
apply (LinearIsometryEquiv.analyticOnNhd _ _).comp_analyticOn _ (Set.mapsTo_univ _ _)
exact ((h'p i).mono inter_subset_left).prod ((h'q i).mono inter_subset_right)
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
rcases hg m hm with ⟨v, hv, q, hq⟩
exact ⟨u ∩ v, Filter.inter_mem hu hv, _,
(hp.mono inter_subset_left).prodMk (hq.mono inter_subset_right)⟩
@[deprecated (since := "2025-03-09")]
alias ContDiffWithinAt.prod := ContDiffWithinAt.prodMk
/-- The cartesian product of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.prodMk {s : Set E} {f : E → F} {g : E → G} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x : E => (f x, g x)) s := fun x hx =>
(hf x hx).prodMk (hg x hx)
@[deprecated (since := "2025-03-09")]
alias ContDiffOn.prod := ContDiffOn.prodMk
/-- The cartesian product of `C^n` functions at a point is `C^n`. -/
theorem ContDiffAt.prodMk {f : E → F} {g : E → G} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x : E => (f x, g x)) x :=
contDiffWithinAt_univ.1 <| hf.contDiffWithinAt.prodMk hg.contDiffWithinAt
@[deprecated (since := "2025-03-09")]
alias ContDiffAt.prod := ContDiffAt.prodMk
/-- The cartesian product of `C^n` functions is `C^n`. -/
theorem ContDiff.prodMk {f : E → F} {g : E → G} (hf : ContDiff 𝕜 n f) (hg : ContDiff 𝕜 n g) :
ContDiff 𝕜 n fun x : E => (f x, g x) :=
contDiffOn_univ.1 <| hf.contDiffOn.prodMk hg.contDiffOn
@[deprecated (since := "2025-03-09")]
alias ContDiff.prod := ContDiff.prodMk
end prod
section comp
/-!
### Composition of `C^n` functions
We show that the composition of `C^n` functions is `C^n`. One way to do this would be to
use the following simple inductive proof. Assume it is done for `n`.
Then, to check it for `n+1`, one needs to check that the derivative of `g ∘ f` is `C^n`, i.e.,
that `Dg(f x) ⬝ Df(x)` is `C^n`. The term `Dg (f x)` is the composition of two `C^n` functions, so
it is `C^n` by the inductive assumption. The term `Df(x)` is also `C^n`. Then, the matrix
multiplication is the application of a bilinear map (which is `C^∞`, and therefore `C^n`) to
`x ↦ (Dg(f x), Df x)`. As the composition of two `C^n` maps, it is again `C^n`, and we are done.
There are two difficulties in this proof.
The first one is that it is an induction over all Banach
spaces. In Lean, this is only possible if they belong to a fixed universe. One could formalize this
by first proving the statement in this case, and then extending the result to general universes
by embedding all the spaces we consider in a common universe through `ULift`.
The second one is that it does not work cleanly for analytic maps: for this case, we need to
exhibit a whole sequence of derivatives which are all analytic, not just finitely many of them, so
an induction is never enough at a finite step.
Both these difficulties can be overcome with some cost. However, we choose a different path: we
write down an explicit formula for the `n`-th derivative of `g ∘ f` in terms of derivatives of
`g` and `f` (this is the formula of Faa-Di Bruno) and use this formula to get a suitable Taylor
expansion for `g ∘ f`. Writing down the formula of Faa-Di Bruno is not easy as the formula is quite
intricate, but it is also useful for other purposes and once available it makes the proof here
essentially trivial.
-/
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x) (st : MapsTo f s t) :
ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
match n with
| ω =>
have h'f : ContDiffWithinAt 𝕜 ω f s x := hf
obtain ⟨u, hu, p, hp, h'p⟩ := h'f
obtain ⟨v, hv, q, hq, h'q⟩ := hg
let w := insert x s ∩ (u ∩ f ⁻¹' v)
have wv : w ⊆ f ⁻¹' v := fun y hy => hy.2.2
have wu : w ⊆ u := fun y hy => hy.2.1
refine ⟨w, ?_, fun y ↦ (q (f y)).taylorComp (p y), hq.comp (hp.mono wu) wv, ?_⟩
· apply inter_mem self_mem_nhdsWithin (inter_mem hu ?_)
apply (continuousWithinAt_insert_self.2 hf.continuousWithinAt).preimage_mem_nhdsWithin'
apply nhdsWithin_mono _ _ hv
simp only [image_insert_eq]
apply insert_subset_insert
exact image_subset_iff.mpr st
· have : AnalyticOn 𝕜 f w := by
have : AnalyticOn 𝕜 (fun y ↦ (continuousMultilinearCurryFin0 𝕜 E F).symm (f y)) w :=
((h'p 0).mono wu).congr fun y hy ↦ (hp.zero_eq' (wu hy)).symm
have : AnalyticOn 𝕜 (fun y ↦ (continuousMultilinearCurryFin0 𝕜 E F)
((continuousMultilinearCurryFin0 𝕜 E F).symm (f y))) w :=
AnalyticOnNhd.comp_analyticOn (LinearIsometryEquiv.analyticOnNhd _ _ ) this
(mapsTo_univ _ _)
simpa using this
exact analyticOn_taylorComp h'q (fun n ↦ (h'p n).mono wu) this wv
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
rcases hg m hm with ⟨v, hv, q, hq⟩
let w := insert x s ∩ (u ∩ f ⁻¹' v)
have wv : w ⊆ f ⁻¹' v := fun y hy => hy.2.2
have wu : w ⊆ u := fun y hy => hy.2.1
refine ⟨w, ?_, fun y ↦ (q (f y)).taylorComp (p y), hq.comp (hp.mono wu) wv⟩
apply inter_mem self_mem_nhdsWithin (inter_mem hu ?_)
apply (continuousWithinAt_insert_self.2 hf.continuousWithinAt).preimage_mem_nhdsWithin'
apply nhdsWithin_mono _ _ hv
simp only [image_insert_eq]
apply insert_subset_insert
exact image_subset_iff.mpr st
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.comp {s : Set E} {t : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g t)
(hf : ContDiffOn 𝕜 n f s) (st : MapsTo f s t) : ContDiffOn 𝕜 n (g ∘ f) s :=
fun x hx ↦ ContDiffWithinAt.comp x (hg (f x) (st hx)) (hf x hx) st
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.comp_inter
{s : Set E} {t : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g t)
(hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) :=
hg.comp (hf.mono inter_subset_left) inter_subset_right
@[deprecated (since := "2024-10-30")] alias ContDiffOn.comp' := ContDiffOn.comp_inter
/-- The composition of a `C^n` function on a domain with a `C^n` function is `C^n`. -/
theorem ContDiff.comp_contDiffOn {s : Set E} {g : F → G} {f : E → F} (hg : ContDiff 𝕜 n g)
(hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (g ∘ f) s :=
(contDiffOn_univ.2 hg).comp hf (mapsTo_univ _ _)
theorem ContDiffOn.comp_contDiff {s : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g s)
(hf : ContDiff 𝕜 n f) (hs : ∀ x, f x ∈ s) : ContDiff 𝕜 n (g ∘ f) := by
rw [← contDiffOn_univ] at *
exact hg.comp hf fun x _ => hs x
theorem ContDiffOn.image_comp_contDiff {s : Set E} {g : F → G} {f : E → F}
(hg : ContDiffOn 𝕜 n g (f '' s)) (hf : ContDiff 𝕜 n f) : ContDiffOn 𝕜 n (g ∘ f) s :=
hg.comp hf.contDiffOn (s.mapsTo_image f)
/-- The composition of `C^n` functions is `C^n`. -/
theorem ContDiff.comp {g : F → G} {f : E → F} (hg : ContDiff 𝕜 n g) (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n (g ∘ f) :=
contDiffOn_univ.1 <| ContDiffOn.comp (contDiffOn_univ.2 hg) (contDiffOn_univ.2 hf) (subset_univ _)
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp_of_eq {s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x) (st : MapsTo f s t)
(hy : f x = y) :
ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp x hf st
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_mem_nhdsWithin_image
{s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : t ∈ 𝓝[f '' s] f x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
(hg.mono_of_mem_nhdsWithin hs).comp x hf (subset_preimage_image f s)
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_mem_nhdsWithin_image_of_eq
{s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : t ∈ 𝓝[f '' s] f x) (hy : f x = y) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp_of_mem_nhdsWithin_image x hf hs
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp_inter {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) x :=
hg.comp x (hf.mono inter_subset_left) inter_subset_right
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp_inter_of_eq {s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F}
(x : E) (hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x) (hy : f x = y) :
ContDiffWithinAt 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) x := by
subst hy; exact hg.comp_inter x hf
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_preimage_mem_nhdsWithin
{s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : f ⁻¹' t ∈ 𝓝[s] x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
(hg.comp_inter x hf).mono_of_mem_nhdsWithin (inter_mem self_mem_nhdsWithin hs)
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_preimage_mem_nhdsWithin_of_eq
{s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : f ⁻¹' t ∈ 𝓝[s] x) (hy : f x = y) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp_of_preimage_mem_nhdsWithin x hf hs
theorem ContDiffAt.comp_contDiffWithinAt (x : E) (hg : ContDiffAt 𝕜 n g (f x))
(hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
hg.comp x hf (mapsTo_univ _ _)
theorem ContDiffAt.comp_contDiffWithinAt_of_eq {y : F} (x : E) (hg : ContDiffAt 𝕜 n g y)
(hf : ContDiffWithinAt 𝕜 n f s x) (hy : f x = y) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp_contDiffWithinAt x hf
/-- The composition of `C^n` functions at points is `C^n`. -/
nonrec theorem ContDiffAt.comp (x : E) (hg : ContDiffAt 𝕜 n g (f x)) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (g ∘ f) x :=
hg.comp x hf (mapsTo_univ _ _)
theorem ContDiff.comp_contDiffWithinAt {g : F → G} {f : E → F} (h : ContDiff 𝕜 n g)
(hf : ContDiffWithinAt 𝕜 n f t x) : ContDiffWithinAt 𝕜 n (g ∘ f) t x :=
haveI : ContDiffWithinAt 𝕜 n g univ (f x) := h.contDiffAt.contDiffWithinAt
this.comp x hf (subset_univ _)
theorem ContDiff.comp_contDiffAt {g : F → G} {f : E → F} (x : E) (hg : ContDiff 𝕜 n g)
(hf : ContDiffAt 𝕜 n f x) : ContDiffAt 𝕜 n (g ∘ f) x :=
hg.comp_contDiffWithinAt hf
theorem iteratedFDerivWithin_comp_of_eventually_mem {t : Set F}
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(ht : UniqueDiffOn 𝕜 t) (hs : UniqueDiffOn 𝕜 s) (hxs : x ∈ s) (hst : ∀ᶠ y in 𝓝[s] x, f y ∈ t)
{i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(ftaylorSeriesWithin 𝕜 g t (f x)).taylorComp (ftaylorSeriesWithin 𝕜 f s x) i := by
obtain ⟨u, hxu, huo, hfu, hgu⟩ : ∃ u, x ∈ u ∧ IsOpen u ∧
HasFTaylorSeriesUpToOn i f (ftaylorSeriesWithin 𝕜 f s) (s ∩ u) ∧
HasFTaylorSeriesUpToOn i g (ftaylorSeriesWithin 𝕜 g t) (f '' (s ∩ u)) := by
have hxt : f x ∈ t := hst.self_of_nhdsWithin hxs
have hf_tendsto : Tendsto f (𝓝[s] x) (𝓝[t] (f x)) :=
tendsto_nhdsWithin_iff.mpr ⟨hf.continuousWithinAt, hst⟩
have H₁ : ∀ᶠ u in (𝓝[s] x).smallSets,
HasFTaylorSeriesUpToOn i f (ftaylorSeriesWithin 𝕜 f s) u :=
hf.eventually_hasFTaylorSeriesUpToOn hs hxs hi
have H₂ : ∀ᶠ u in (𝓝[s] x).smallSets,
HasFTaylorSeriesUpToOn i g (ftaylorSeriesWithin 𝕜 g t) (f '' u) :=
hf_tendsto.image_smallSets.eventually (hg.eventually_hasFTaylorSeriesUpToOn ht hxt hi)
rcases (nhdsWithin_basis_open _ _).smallSets.eventually_iff.mp (H₁.and H₂)
with ⟨u, ⟨hxu, huo⟩, hu⟩
exact ⟨u, hxu, huo, hu (by simp [inter_comm])⟩
exact .symm <| (hgu.comp hfu (mapsTo_image _ _)).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl
(hs.inter huo) ⟨hxs, hxu⟩ |>.trans <| iteratedFDerivWithin_inter_open huo hxu
theorem iteratedFDerivWithin_comp {t : Set F} (hg : ContDiffWithinAt 𝕜 n g t (f x))
(hf : ContDiffWithinAt 𝕜 n f s x) (ht : UniqueDiffOn 𝕜 t) (hs : UniqueDiffOn 𝕜 s)
(hx : x ∈ s) (hst : MapsTo f s t) {i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(ftaylorSeriesWithin 𝕜 g t (f x)).taylorComp (ftaylorSeriesWithin 𝕜 f s x) i :=
iteratedFDerivWithin_comp_of_eventually_mem hg hf ht hs hx (eventually_mem_nhdsWithin.mono hst) hi
theorem iteratedFDeriv_comp (hg : ContDiffAt 𝕜 n g (f x)) (hf : ContDiffAt 𝕜 n f x)
{i : ℕ} (hi : i ≤ n) :
iteratedFDeriv 𝕜 i (g ∘ f) x =
(ftaylorSeries 𝕜 g (f x)).taylorComp (ftaylorSeries 𝕜 f x) i := by
simp only [← iteratedFDerivWithin_univ, ← ftaylorSeriesWithin_univ]
exact iteratedFDerivWithin_comp hg.contDiffWithinAt hf.contDiffWithinAt
uniqueDiffOn_univ uniqueDiffOn_univ (mem_univ _) (mapsTo_univ _ _) hi
end comp
/-!
### Smoothness of projections
-/
/-- The first projection in a product is `C^∞`. -/
theorem contDiff_fst : ContDiff 𝕜 n (Prod.fst : E × F → E) :=
IsBoundedLinearMap.contDiff IsBoundedLinearMap.fst
/-- Postcomposing `f` with `Prod.fst` is `C^n` -/
theorem ContDiff.fst {f : E → F × G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (f x).1 :=
contDiff_fst.comp hf
/-- Precomposing `f` with `Prod.fst` is `C^n` -/
theorem ContDiff.fst' {f : E → G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x : E × F => f x.1 :=
hf.comp contDiff_fst
/-- The first projection on a domain in a product is `C^∞`. -/
theorem contDiffOn_fst {s : Set (E × F)} : ContDiffOn 𝕜 n (Prod.fst : E × F → E) s :=
ContDiff.contDiffOn contDiff_fst
theorem ContDiffOn.fst {f : E → F × G} {s : Set E} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (f x).1) s :=
contDiff_fst.comp_contDiffOn hf
/-- The first projection at a point in a product is `C^∞`. -/
theorem contDiffAt_fst {p : E × F} : ContDiffAt 𝕜 n (Prod.fst : E × F → E) p :=
contDiff_fst.contDiffAt
/-- Postcomposing `f` with `Prod.fst` is `C^n` at `(x, y)` -/
theorem ContDiffAt.fst {f : E → F × G} {x : E} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (f x).1) x :=
contDiffAt_fst.comp x hf
/-- Precomposing `f` with `Prod.fst` is `C^n` at `(x, y)` -/
theorem ContDiffAt.fst' {f : E → G} {x : E} {y : F} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x : E × F => f x.1) (x, y) :=
ContDiffAt.comp (x, y) hf contDiffAt_fst
/-- Precomposing `f` with `Prod.fst` is `C^n` at `x : E × F` -/
theorem ContDiffAt.fst'' {f : E → G} {x : E × F} (hf : ContDiffAt 𝕜 n f x.1) :
ContDiffAt 𝕜 n (fun x : E × F => f x.1) x :=
hf.comp x contDiffAt_fst
/-- The first projection within a domain at a point in a product is `C^∞`. -/
theorem contDiffWithinAt_fst {s : Set (E × F)} {p : E × F} :
ContDiffWithinAt 𝕜 n (Prod.fst : E × F → E) s p :=
contDiff_fst.contDiffWithinAt
/-- The second projection in a product is `C^∞`. -/
theorem contDiff_snd : ContDiff 𝕜 n (Prod.snd : E × F → F) :=
IsBoundedLinearMap.contDiff IsBoundedLinearMap.snd
/-- Postcomposing `f` with `Prod.snd` is `C^n` -/
theorem ContDiff.snd {f : E → F × G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (f x).2 :=
contDiff_snd.comp hf
/-- Precomposing `f` with `Prod.snd` is `C^n` -/
theorem ContDiff.snd' {f : F → G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x : E × F => f x.2 :=
hf.comp contDiff_snd
/-- The second projection on a domain in a product is `C^∞`. -/
theorem contDiffOn_snd {s : Set (E × F)} : ContDiffOn 𝕜 n (Prod.snd : E × F → F) s :=
ContDiff.contDiffOn contDiff_snd
theorem ContDiffOn.snd {f : E → F × G} {s : Set E} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (f x).2) s :=
contDiff_snd.comp_contDiffOn hf
/-- The second projection at a point in a product is `C^∞`. -/
theorem contDiffAt_snd {p : E × F} : ContDiffAt 𝕜 n (Prod.snd : E × F → F) p :=
contDiff_snd.contDiffAt
/-- Postcomposing `f` with `Prod.snd` is `C^n` at `x` -/
theorem ContDiffAt.snd {f : E → F × G} {x : E} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (f x).2) x :=
contDiffAt_snd.comp x hf
/-- Precomposing `f` with `Prod.snd` is `C^n` at `(x, y)` -/
theorem ContDiffAt.snd' {f : F → G} {x : E} {y : F} (hf : ContDiffAt 𝕜 n f y) :
ContDiffAt 𝕜 n (fun x : E × F => f x.2) (x, y) :=
ContDiffAt.comp (x, y) hf contDiffAt_snd
/-- Precomposing `f` with `Prod.snd` is `C^n` at `x : E × F` -/
theorem ContDiffAt.snd'' {f : F → G} {x : E × F} (hf : ContDiffAt 𝕜 n f x.2) :
ContDiffAt 𝕜 n (fun x : E × F => f x.2) x :=
hf.comp x contDiffAt_snd
/-- The second projection within a domain at a point in a product is `C^∞`. -/
theorem contDiffWithinAt_snd {s : Set (E × F)} {p : E × F} :
ContDiffWithinAt 𝕜 n (Prod.snd : E × F → F) s p :=
contDiff_snd.contDiffWithinAt
section NAry
variable {E₁ E₂ E₃ : Type*}
variable [NormedAddCommGroup E₁] [NormedAddCommGroup E₂] [NormedAddCommGroup E₃]
[NormedSpace 𝕜 E₁] [NormedSpace 𝕜 E₂] [NormedSpace 𝕜 E₃]
theorem ContDiff.comp₂ {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} (hg : ContDiff 𝕜 n g)
(hf₁ : ContDiff 𝕜 n f₁) (hf₂ : ContDiff 𝕜 n f₂) : ContDiff 𝕜 n fun x => g (f₁ x, f₂ x) :=
hg.comp <| hf₁.prodMk hf₂
theorem ContDiffAt.comp₂ {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {x : F}
(hg : ContDiffAt 𝕜 n g (f₁ x, f₂ x))
(hf₁ : ContDiffAt 𝕜 n f₁ x) (hf₂ : ContDiffAt 𝕜 n f₂ x) :
ContDiffAt 𝕜 n (fun x => g (f₁ x, f₂ x)) x :=
hg.comp x (hf₁.prodMk hf₂)
theorem ContDiffAt.comp₂_contDiffWithinAt {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂}
{s : Set F} {x : F} (hg : ContDiffAt 𝕜 n g (f₁ x, f₂ x))
(hf₁ : ContDiffWithinAt 𝕜 n f₁ s x) (hf₂ : ContDiffWithinAt 𝕜 n f₂ s x) :
ContDiffWithinAt 𝕜 n (fun x => g (f₁ x, f₂ x)) s x :=
hg.comp_contDiffWithinAt x (hf₁.prodMk hf₂)
@[deprecated (since := "2024-10-30")]
alias ContDiffAt.comp_contDiffWithinAt₂ := ContDiffAt.comp₂_contDiffWithinAt
theorem ContDiff.comp₂_contDiffAt {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {x : F}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiffAt 𝕜 n f₁ x) (hf₂ : ContDiffAt 𝕜 n f₂ x) :
ContDiffAt 𝕜 n (fun x => g (f₁ x, f₂ x)) x :=
hg.contDiffAt.comp₂ hf₁ hf₂
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffAt₂ := ContDiff.comp₂_contDiffAt
theorem ContDiff.comp₂_contDiffWithinAt {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂}
{s : Set F} {x : F} (hg : ContDiff 𝕜 n g)
(hf₁ : ContDiffWithinAt 𝕜 n f₁ s x) (hf₂ : ContDiffWithinAt 𝕜 n f₂ s x) :
ContDiffWithinAt 𝕜 n (fun x => g (f₁ x, f₂ x)) s x :=
hg.contDiffAt.comp_contDiffWithinAt x (hf₁.prodMk hf₂)
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffWithinAt₂ := ContDiff.comp₂_contDiffWithinAt
theorem ContDiff.comp₂_contDiffOn {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {s : Set F}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiffOn 𝕜 n f₁ s) (hf₂ : ContDiffOn 𝕜 n f₂ s) :
ContDiffOn 𝕜 n (fun x => g (f₁ x, f₂ x)) s :=
hg.comp_contDiffOn <| hf₁.prodMk hf₂
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffOn₂ := ContDiff.comp₂_contDiffOn
theorem ContDiff.comp₃ {g : E₁ × E₂ × E₃ → G} {f₁ : F → E₁} {f₂ : F → E₂} {f₃ : F → E₃}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiff 𝕜 n f₁) (hf₂ : ContDiff 𝕜 n f₂) (hf₃ : ContDiff 𝕜 n f₃) :
ContDiff 𝕜 n fun x => g (f₁ x, f₂ x, f₃ x) :=
hg.comp₂ hf₁ <| hf₂.prodMk hf₃
theorem ContDiff.comp₃_contDiffOn {g : E₁ × E₂ × E₃ → G} {f₁ : F → E₁} {f₂ : F → E₂} {f₃ : F → E₃}
{s : Set F} (hg : ContDiff 𝕜 n g) (hf₁ : ContDiffOn 𝕜 n f₁ s) (hf₂ : ContDiffOn 𝕜 n f₂ s)
(hf₃ : ContDiffOn 𝕜 n f₃ s) : ContDiffOn 𝕜 n (fun x => g (f₁ x, f₂ x, f₃ x)) s :=
hg.comp₂_contDiffOn hf₁ <| hf₂.prodMk hf₃
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffOn₃ := ContDiff.comp₃_contDiffOn
end NAry
section SpecificBilinearMaps
theorem ContDiff.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} (hg : ContDiff 𝕜 n g)
(hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (g x).comp (f x) :=
isBoundedBilinearMap_comp.contDiff.comp₂ (g := fun p => p.1.comp p.2) hg hf
theorem ContDiffOn.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {s : Set X}
(hg : ContDiffOn 𝕜 n g s) (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (g x).comp (f x)) s :=
(isBoundedBilinearMap_comp (E := E) (F := F) (G := G)).contDiff.comp₂_contDiffOn hg hf
theorem ContDiffAt.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {x : X}
(hg : ContDiffAt 𝕜 n g x) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (g x).comp (f x)) x :=
(isBoundedBilinearMap_comp (E := E) (G := G)).contDiff.comp₂_contDiffAt hg hf
theorem ContDiffWithinAt.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {s : Set X} {x : X}
(hg : ContDiffWithinAt 𝕜 n g s x) (hf : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n (fun x => (g x).comp (f x)) s x :=
(isBoundedBilinearMap_comp (E := E) (G := G)).contDiff.comp₂_contDiffWithinAt hg hf
theorem ContDiff.clm_apply {f : E → F →L[𝕜] G} {g : E → F} (hf : ContDiff 𝕜 n f)
(hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n fun x => (f x) (g x) :=
isBoundedBilinearMap_apply.contDiff.comp₂ hf hg
theorem ContDiffOn.clm_apply {f : E → F →L[𝕜] G} {g : E → F} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x => (f x) (g x)) s :=
isBoundedBilinearMap_apply.contDiff.comp₂_contDiffOn hf hg
theorem ContDiffAt.clm_apply {f : E → F →L[𝕜] G} {g : E → F} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x => (f x) (g x)) x :=
isBoundedBilinearMap_apply.contDiff.comp₂_contDiffAt hf hg
theorem ContDiffWithinAt.clm_apply {f : E → F →L[𝕜] G} {g : E → F}
(hf : ContDiffWithinAt 𝕜 n f s x) (hg : ContDiffWithinAt 𝕜 n g s x) :
ContDiffWithinAt 𝕜 n (fun x => (f x) (g x)) s x :=
isBoundedBilinearMap_apply.contDiff.comp₂_contDiffWithinAt hf hg
theorem ContDiff.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} (hf : ContDiff 𝕜 n f)
(hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n fun x => (f x).smulRight (g x) :=
isBoundedBilinearMap_smulRight.contDiff.comp₂ (g := fun p => p.1.smulRight p.2) hf hg
theorem ContDiffOn.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x => (f x).smulRight (g x)) s :=
(isBoundedBilinearMap_smulRight (E := F)).contDiff.comp₂_contDiffOn hf hg
theorem ContDiffAt.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x => (f x).smulRight (g x)) x :=
(isBoundedBilinearMap_smulRight (E := F)).contDiff.comp₂_contDiffAt hf hg
theorem ContDiffWithinAt.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G}
(hf : ContDiffWithinAt 𝕜 n f s x) (hg : ContDiffWithinAt 𝕜 n g s x) :
ContDiffWithinAt 𝕜 n (fun x => (f x).smulRight (g x)) s x :=
(isBoundedBilinearMap_smulRight (E := F)).contDiff.comp₂_contDiffWithinAt hf hg
end SpecificBilinearMaps
section ClmApplyConst
/-- Application of a `ContinuousLinearMap` to a constant commutes with `iteratedFDerivWithin`. -/
theorem iteratedFDerivWithin_clm_apply_const_apply
{s : Set E} (hs : UniqueDiffOn 𝕜 s) {c : E → F →L[𝕜] G}
(hc : ContDiffOn 𝕜 n c s) {i : ℕ} (hi : i ≤ n) {x : E} (hx : x ∈ s) {u : F} {m : Fin i → E} :
(iteratedFDerivWithin 𝕜 i (fun y ↦ (c y) u) s x) m = (iteratedFDerivWithin 𝕜 i c s x) m u := by
induction i generalizing x with
| zero => simp
| succ i ih =>
replace hi : (i : WithTop ℕ∞) < n := lt_of_lt_of_le (by norm_cast; simp) hi
have h_deriv_apply : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 i (fun y ↦ (c y) u) s) s :=
(hc.clm_apply contDiffOn_const).differentiableOn_iteratedFDerivWithin hi hs
have h_deriv : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 i c s) s :=
hc.differentiableOn_iteratedFDerivWithin hi hs
simp only [iteratedFDerivWithin_succ_apply_left]
rw [← fderivWithin_continuousMultilinear_apply_const_apply (hs x hx) (h_deriv_apply x hx)]
rw [fderivWithin_congr' (fun x hx ↦ ih hi.le hx) hx]
rw [fderivWithin_clm_apply (hs x hx) (h_deriv.continuousMultilinear_apply_const _ x hx)
(differentiableWithinAt_const u)]
rw [fderivWithin_const_apply]
simp only [ContinuousLinearMap.flip_apply, ContinuousLinearMap.comp_zero, zero_add]
rw [fderivWithin_continuousMultilinear_apply_const_apply (hs x hx) (h_deriv x hx)]
/-- Application of a `ContinuousLinearMap` to a constant commutes with `iteratedFDeriv`. -/
theorem iteratedFDeriv_clm_apply_const_apply
{c : E → F →L[𝕜] G} (hc : ContDiff 𝕜 n c)
{i : ℕ} (hi : i ≤ n) {x : E} {u : F} {m : Fin i → E} :
(iteratedFDeriv 𝕜 i (fun y ↦ (c y) u) x) m = (iteratedFDeriv 𝕜 i c x) m u := by
simp only [← iteratedFDerivWithin_univ]
exact iteratedFDerivWithin_clm_apply_const_apply uniqueDiffOn_univ hc.contDiffOn hi (mem_univ _)
end ClmApplyConst
/-- The natural equivalence `(E × F) × G ≃ E × (F × G)` is smooth.
Warning: if you think you need this lemma, it is likely that you can simplify your proof by
reformulating the lemma that you're applying next using the tips in
Note [continuity lemma statement]
-/
theorem contDiff_prodAssoc {n : WithTop ℕ∞} : ContDiff 𝕜 n <| Equiv.prodAssoc E F G :=
(LinearIsometryEquiv.prodAssoc 𝕜 E F G).contDiff
/-- The natural equivalence `E × (F × G) ≃ (E × F) × G` is smooth.
Warning: see remarks attached to `contDiff_prodAssoc`
-/
theorem contDiff_prodAssoc_symm {n : WithTop ℕ∞} : ContDiff 𝕜 n <| (Equiv.prodAssoc E F G).symm :=
(LinearIsometryEquiv.prodAssoc 𝕜 E F G).symm.contDiff
/-! ### Bundled derivatives are smooth -/
section bundled
/-- One direction of `contDiffWithinAt_succ_iff_hasFDerivWithinAt`, but where all derivatives are
taken within the same set. Version for partial derivatives / functions with parameters. If `f x` is
a `C^n+1` family of functions and `g x` is a `C^n` family of points, then the derivative of `f x` at
`g x` depends in a `C^n` way on `x`. We give a general version of this fact relative to sets which
may not have unique derivatives, in the following form. If `f : E × F → G` is `C^n+1` at
`(x₀, g(x₀))` in `(s ∪ {x₀}) × t ⊆ E × F` and `g : E → F` is `C^n` at `x₀` within some set `s ⊆ E`,
then there is a function `f' : E → F →L[𝕜] G` that is `C^n` at `x₀` within `s` such that for all `x`
sufficiently close to `x₀` within `s ∪ {x₀}` the function `y ↦ f x y` has derivative `f' x` at `g x`
within `t ⊆ F`. For convenience, we return an explicit set of `x`'s where this holds that is a
subset of `s ∪ {x₀}`. We need one additional condition, namely that `t` is a neighborhood of
`g(x₀)` within `g '' s`. -/
theorem ContDiffWithinAt.hasFDerivWithinAt_nhds {f : E → F → G} {g : E → F} {t : Set F} (hn : n ≠ ∞)
{x₀ : E} (hf : ContDiffWithinAt 𝕜 (n + 1) (uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 n g s x₀) (hgt : t ∈ 𝓝[g '' s] g x₀) :
∃ v ∈ 𝓝[insert x₀ s] x₀, v ⊆ insert x₀ s ∧ ∃ f' : E → F →L[𝕜] G,
(∀ x ∈ v, HasFDerivWithinAt (f x) (f' x) t (g x)) ∧
ContDiffWithinAt 𝕜 n (fun x => f' x) s x₀ := by
have hst : insert x₀ s ×ˢ t ∈ 𝓝[(fun x => (x, g x)) '' s] (x₀, g x₀) := by
refine nhdsWithin_mono _ ?_ (nhdsWithin_prod self_mem_nhdsWithin hgt)
simp_rw [image_subset_iff, mk_preimage_prod, preimage_id', subset_inter_iff, subset_insert,
true_and, subset_preimage_image]
obtain ⟨v, hv, hvs, f_an, f', hvf', hf'⟩ :=
(contDiffWithinAt_succ_iff_hasFDerivWithinAt' hn).mp hf
refine
⟨(fun z => (z, g z)) ⁻¹' v ∩ insert x₀ s, ?_, inter_subset_right, fun z =>
(f' (z, g z)).comp (ContinuousLinearMap.inr 𝕜 E F), ?_, ?_⟩
· refine inter_mem ?_ self_mem_nhdsWithin
have := mem_of_mem_nhdsWithin (mem_insert _ _) hv
refine mem_nhdsWithin_insert.mpr ⟨this, ?_⟩
refine (continuousWithinAt_id.prodMk hg.continuousWithinAt).preimage_mem_nhdsWithin' ?_
rw [← nhdsWithin_le_iff] at hst hv ⊢
exact (hst.trans <| nhdsWithin_mono _ <| subset_insert _ _).trans hv
· intro z hz
have := hvf' (z, g z) hz.1
refine this.comp _ (hasFDerivAt_prodMk_right _ _).hasFDerivWithinAt ?_
exact mapsTo'.mpr (image_prodMk_subset_prod_right hz.2)
· exact (hf'.continuousLinearMap_comp <| (ContinuousLinearMap.compL 𝕜 F (E × F) G).flip
(ContinuousLinearMap.inr 𝕜 E F)).comp_of_mem_nhdsWithin_image x₀
(contDiffWithinAt_id.prodMk hg) hst
/-- The most general lemma stating that `x ↦ fderivWithin 𝕜 (f x) t (g x)` is `C^n`
at a point within a set.
To show that `x ↦ D_yf(x,y)g(x)` (taken within `t`) is `C^m` at `x₀` within `s`, we require that
* `f` is `C^n` at `(x₀, g(x₀))` within `(s ∪ {x₀}) × t` for `n ≥ m+1`.
* `g` is `C^m` at `x₀` within `s`;
* Derivatives are unique at `g(x)` within `t` for `x` sufficiently close to `x₀` within `s ∪ {x₀}`;
* `t` is a neighborhood of `g(x₀)` within `g '' s`; -/
theorem ContDiffWithinAt.fderivWithin'' {f : E → F → G} {g : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀)
(ht : ∀ᶠ x in 𝓝[insert x₀ s] x₀, UniqueDiffWithinAt 𝕜 t (g x)) (hmn : m + 1 ≤ n)
(hgt : t ∈ 𝓝[g '' s] g x₀) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
have : ∀ k : ℕ, k ≤ m → ContDiffWithinAt 𝕜 k (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
intro k hkm
obtain ⟨v, hv, -, f', hvf', hf'⟩ :=
(hf.of_le <| (add_le_add_right hkm 1).trans hmn).hasFDerivWithinAt_nhds (by simp)
(hg.of_le hkm) hgt
refine hf'.congr_of_eventuallyEq_insert ?_
filter_upwards [hv, ht]
exact fun y hy h2y => (hvf' y hy).fderivWithin h2y
match m with
| ω =>
obtain rfl : n = ω := by simpa using hmn
obtain ⟨v, hv, -, f', hvf', hf'⟩ := hf.hasFDerivWithinAt_nhds (by simp) hg hgt
refine hf'.congr_of_eventuallyEq_insert ?_
filter_upwards [hv, ht]
exact fun y hy h2y => (hvf' y hy).fderivWithin h2y
| ∞ =>
rw [contDiffWithinAt_infty]
exact fun k ↦ this k (by exact_mod_cast le_top)
| (m : ℕ) => exact this _ le_rfl
/-- A special case of `ContDiffWithinAt.fderivWithin''` where we require that `s ⊆ g⁻¹(t)`. -/
theorem ContDiffWithinAt.fderivWithin' {f : E → F → G} {g : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀)
(ht : ∀ᶠ x in 𝓝[insert x₀ s] x₀, UniqueDiffWithinAt 𝕜 t (g x)) (hmn : m + 1 ≤ n)
(hst : s ⊆ g ⁻¹' t) : ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ :=
hf.fderivWithin'' hg ht hmn <| mem_of_superset self_mem_nhdsWithin <| image_subset_iff.mpr hst
/-- A special case of `ContDiffWithinAt.fderivWithin'` where we require that `x₀ ∈ s` and there
are unique derivatives everywhere within `t`. -/
protected theorem ContDiffWithinAt.fderivWithin {f : E → F → G} {g : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀) (ht : UniqueDiffOn 𝕜 t) (hmn : m + 1 ≤ n) (hx₀ : x₀ ∈ s)
(hst : s ⊆ g ⁻¹' t) : ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
rw [← insert_eq_self.mpr hx₀] at hf
refine hf.fderivWithin' hg ?_ hmn hst
rw [insert_eq_self.mpr hx₀]
exact eventually_of_mem self_mem_nhdsWithin fun x hx => ht _ (hst hx)
/-- `x ↦ fderivWithin 𝕜 (f x) t (g x) (k x)` is smooth at a point within a set. -/
theorem ContDiffWithinAt.fderivWithin_apply {f : E → F → G} {g k : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀) (hk : ContDiffWithinAt 𝕜 m k s x₀) (ht : UniqueDiffOn 𝕜 t)
(hmn : m + 1 ≤ n) (hx₀ : x₀ ∈ s) (hst : s ⊆ g ⁻¹' t) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x) (k x)) s x₀ :=
(contDiff_fst.clm_apply contDiff_snd).contDiffAt.comp_contDiffWithinAt x₀
((hf.fderivWithin hg ht hmn hx₀ hst).prodMk hk)
/-- `fderivWithin 𝕜 f s` is smooth at `x₀` within `s`. -/
theorem ContDiffWithinAt.fderivWithin_right (hf : ContDiffWithinAt 𝕜 n f s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (fderivWithin 𝕜 f s) s x₀ :=
ContDiffWithinAt.fderivWithin
(ContDiffWithinAt.comp (x₀, x₀) hf contDiffWithinAt_snd <| prod_subset_preimage_snd s s)
contDiffWithinAt_id hs hmn hx₀s (by rw [preimage_id'])
/-- `x ↦ fderivWithin 𝕜 f s x (k x)` is smooth at `x₀` within `s`. -/
theorem ContDiffWithinAt.fderivWithin_right_apply
{f : F → G} {k : F → F} {s : Set F} {x₀ : F}
(hf : ContDiffWithinAt 𝕜 n f s x₀) (hk : ContDiffWithinAt 𝕜 m k s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 f s x (k x)) s x₀ :=
ContDiffWithinAt.fderivWithin_apply
(ContDiffWithinAt.comp (x₀, x₀) hf contDiffWithinAt_snd <| prod_subset_preimage_snd s s)
contDiffWithinAt_id hk hs hmn hx₀s (by rw [preimage_id'])
-- TODO: can we make a version of `ContDiffWithinAt.fderivWithin` for iterated derivatives?
theorem ContDiffWithinAt.iteratedFDerivWithin_right {i : ℕ} (hf : ContDiffWithinAt 𝕜 n f s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + i ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (iteratedFDerivWithin 𝕜 i f s) s x₀ := by
induction' i with i hi generalizing m
· simp only [CharP.cast_eq_zero, add_zero] at hmn
exact (hf.of_le hmn).continuousLinearMap_comp
((continuousMultilinearCurryFin0 𝕜 E F).symm : _ →L[𝕜] E [×0]→L[𝕜] F)
· rw [Nat.cast_succ, add_comm _ 1, ← add_assoc] at hmn
exact ((hi hmn).fderivWithin_right hs le_rfl hx₀s).continuousLinearMap_comp
((continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (i+1) ↦ E) F).symm :
_ →L[𝕜] E [×(i+1)]→L[𝕜] F)
@[deprecated (since := "2025-01-15")]
alias ContDiffWithinAt.iteratedFderivWithin_right := ContDiffWithinAt.iteratedFDerivWithin_right
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is smooth at `x₀`. -/
protected theorem ContDiffAt.fderiv {f : E → F → G} {g : E → F}
(hf : ContDiffAt 𝕜 n (Function.uncurry f) (x₀, g x₀)) (hg : ContDiffAt 𝕜 m g x₀)
(hmn : m + 1 ≤ n) : ContDiffAt 𝕜 m (fun x => fderiv 𝕜 (f x) (g x)) x₀ := by
simp_rw [← fderivWithin_univ]
refine (ContDiffWithinAt.fderivWithin hf.contDiffWithinAt hg.contDiffWithinAt uniqueDiffOn_univ
hmn (mem_univ x₀) ?_).contDiffAt univ_mem
rw [preimage_univ]
/-- `fderiv 𝕜 f` is smooth at `x₀`. -/
theorem ContDiffAt.fderiv_right (hf : ContDiffAt 𝕜 n f x₀) (hmn : m + 1 ≤ n) :
ContDiffAt 𝕜 m (fderiv 𝕜 f) x₀ :=
ContDiffAt.fderiv (ContDiffAt.comp (x₀, x₀) hf contDiffAt_snd) contDiffAt_id hmn
theorem ContDiffAt.iteratedFDeriv_right {i : ℕ} (hf : ContDiffAt 𝕜 n f x₀)
(hmn : m + i ≤ n) : ContDiffAt 𝕜 m (iteratedFDeriv 𝕜 i f) x₀ := by
rw [← iteratedFDerivWithin_univ, ← contDiffWithinAt_univ] at *
exact hf.iteratedFDerivWithin_right uniqueDiffOn_univ hmn trivial
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is smooth. -/
protected theorem ContDiff.fderiv {f : E → F → G} {g : E → F}
(hf : ContDiff 𝕜 m <| Function.uncurry f) (hg : ContDiff 𝕜 n g) (hnm : n + 1 ≤ m) :
ContDiff 𝕜 n fun x => fderiv 𝕜 (f x) (g x) :=
contDiff_iff_contDiffAt.mpr fun _ => hf.contDiffAt.fderiv hg.contDiffAt hnm
/-- `fderiv 𝕜 f` is smooth. -/
theorem ContDiff.fderiv_right (hf : ContDiff 𝕜 n f) (hmn : m + 1 ≤ n) :
ContDiff 𝕜 m (fderiv 𝕜 f) :=
contDiff_iff_contDiffAt.mpr fun _x => hf.contDiffAt.fderiv_right hmn
theorem ContDiff.iteratedFDeriv_right {i : ℕ} (hf : ContDiff 𝕜 n f)
(hmn : m + i ≤ n) : ContDiff 𝕜 m (iteratedFDeriv 𝕜 i f) :=
contDiff_iff_contDiffAt.mpr fun _x => hf.contDiffAt.iteratedFDeriv_right hmn
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is continuous. -/
theorem Continuous.fderiv {f : E → F → G} {g : E → F}
(hf : ContDiff 𝕜 n <| Function.uncurry f) (hg : Continuous g) (hn : 1 ≤ n) :
Continuous fun x => fderiv 𝕜 (f x) (g x) :=
(hf.fderiv (contDiff_zero.mpr hg) hn).continuous
/-- `x ↦ fderiv 𝕜 (f x) (g x) (k x)` is smooth. -/
theorem ContDiff.fderiv_apply {f : E → F → G} {g k : E → F}
(hf : ContDiff 𝕜 m <| Function.uncurry f) (hg : ContDiff 𝕜 n g) (hk : ContDiff 𝕜 n k)
(hnm : n + 1 ≤ m) : ContDiff 𝕜 n fun x => fderiv 𝕜 (f x) (g x) (k x) :=
(hf.fderiv hg hnm).clm_apply hk
/-- The bundled derivative of a `C^{n+1}` function is `C^n`. -/
theorem contDiffOn_fderivWithin_apply {s : Set E} {f : E → F} (hf : ContDiffOn 𝕜 n f s)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) :
ContDiffOn 𝕜 m (fun p : E × E => (fderivWithin 𝕜 f s p.1 : E →L[𝕜] F) p.2) (s ×ˢ univ) :=
((hf.fderivWithin hs hmn).comp contDiffOn_fst (prod_subset_preimage_fst _ _)).clm_apply
contDiffOn_snd
/-- If a function is at least `C^1`, its bundled derivative (mapping `(x, v)` to `Df(x) v`) is
continuous. -/
theorem ContDiffOn.continuousOn_fderivWithin_apply (hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s)
(hn : 1 ≤ n) :
ContinuousOn (fun p : E × E => (fderivWithin 𝕜 f s p.1 : E → F) p.2) (s ×ˢ univ) :=
(contDiffOn_fderivWithin_apply (m := 0) hf hs hn).continuousOn
/-- The bundled derivative of a `C^{n+1}` function is `C^n`. -/
theorem ContDiff.contDiff_fderiv_apply {f : E → F} (hf : ContDiff 𝕜 n f) (hmn : m + 1 ≤ n) :
ContDiff 𝕜 m fun p : E × E => (fderiv 𝕜 f p.1 : E →L[𝕜] F) p.2 := by
rw [← contDiffOn_univ] at hf ⊢
rw [← fderivWithin_univ, ← univ_prod_univ]
exact contDiffOn_fderivWithin_apply hf uniqueDiffOn_univ hmn
end bundled
section deriv
/-!
### One dimension
All results up to now have been expressed in terms of the general Fréchet derivative `fderiv`. For
maps defined on the field, the one-dimensional derivative `deriv` is often easier to use. In this
paragraph, we reformulate some higher smoothness results in terms of `deriv`.
-/
variable {f₂ : 𝕜 → F} {s₂ : Set 𝕜}
open ContinuousLinearMap (smulRight)
/-- A function is `C^(n + 1)` on a domain with unique derivatives if and only if it is
differentiable there, and its derivative (formulated with `derivWithin`) is `C^n`. -/
theorem contDiffOn_succ_iff_derivWithin (hs : UniqueDiffOn 𝕜 s₂) :
ContDiffOn 𝕜 (n + 1) f₂ s₂ ↔
DifferentiableOn 𝕜 f₂ s₂ ∧ (n = ω → AnalyticOn 𝕜 f₂ s₂) ∧
ContDiffOn 𝕜 n (derivWithin f₂ s₂) s₂ := by
rw [contDiffOn_succ_iff_fderivWithin hs, and_congr_right_iff]
intro _
constructor
· rintro ⟨h', h⟩
refine ⟨h', ?_⟩
have : derivWithin f₂ s₂ = (fun u : 𝕜 →L[𝕜] F => u 1) ∘ fderivWithin 𝕜 f₂ s₂ := by
ext x; rfl
simp_rw [this]
apply ContDiff.comp_contDiffOn _ h
exact (isBoundedBilinearMap_apply.isBoundedLinearMap_left _).contDiff
· rintro ⟨h', h⟩
refine ⟨h', ?_⟩
have : fderivWithin 𝕜 f₂ s₂ = smulRight (1 : 𝕜 →L[𝕜] 𝕜) ∘ derivWithin f₂ s₂ := by
ext x; simp [derivWithin]
simp only [this]
apply ContDiff.comp_contDiffOn _ h
have : IsBoundedBilinearMap 𝕜 fun _ : (𝕜 →L[𝕜] 𝕜) × F => _ := isBoundedBilinearMap_smulRight
exact (this.isBoundedLinearMap_right _).contDiff
theorem contDiffOn_infty_iff_derivWithin (hs : UniqueDiffOn 𝕜 s₂) :
ContDiffOn 𝕜 ∞ f₂ s₂ ↔ DifferentiableOn 𝕜 f₂ s₂ ∧ ContDiffOn 𝕜 ∞ (derivWithin f₂ s₂) s₂ := by
rw [show ∞ = ∞ + 1 by rfl, contDiffOn_succ_iff_derivWithin hs]
simp
@[deprecated (since := "2024-11-27")]
alias contDiffOn_top_iff_derivWithin := contDiffOn_infty_iff_derivWithin
/-- A function is `C^(n + 1)` on an open domain if and only if it is
differentiable there, and its derivative (formulated with `deriv`) is `C^n`. -/
theorem contDiffOn_succ_iff_deriv_of_isOpen (hs : IsOpen s₂) :
ContDiffOn 𝕜 (n + 1) f₂ s₂ ↔
DifferentiableOn 𝕜 f₂ s₂ ∧ (n = ω → AnalyticOn 𝕜 f₂ s₂) ∧
ContDiffOn 𝕜 n (deriv f₂) s₂ := by
rw [contDiffOn_succ_iff_derivWithin hs.uniqueDiffOn]
exact Iff.rfl.and (Iff.rfl.and (contDiffOn_congr fun _ => derivWithin_of_isOpen hs))
theorem contDiffOn_infty_iff_deriv_of_isOpen (hs : IsOpen s₂) :
ContDiffOn 𝕜 ∞ f₂ s₂ ↔ DifferentiableOn 𝕜 f₂ s₂ ∧ ContDiffOn 𝕜 ∞ (deriv f₂) s₂ := by
rw [show ∞ = ∞ + 1 by rfl, contDiffOn_succ_iff_deriv_of_isOpen hs]
simp
@[deprecated (since := "2024-11-27")]
alias contDiffOn_top_iff_deriv_of_isOpen := contDiffOn_infty_iff_deriv_of_isOpen
protected theorem ContDiffOn.derivWithin (hf : ContDiffOn 𝕜 n f₂ s₂) (hs : UniqueDiffOn 𝕜 s₂)
(hmn : m + 1 ≤ n) : ContDiffOn 𝕜 m (derivWithin f₂ s₂) s₂ :=
((contDiffOn_succ_iff_derivWithin hs).1 (hf.of_le hmn)).2.2
theorem ContDiffOn.deriv_of_isOpen (hf : ContDiffOn 𝕜 n f₂ s₂) (hs : IsOpen s₂) (hmn : m + 1 ≤ n) :
ContDiffOn 𝕜 m (deriv f₂) s₂ :=
(hf.derivWithin hs.uniqueDiffOn hmn).congr fun _ hx => (derivWithin_of_isOpen hs hx).symm
theorem ContDiffOn.continuousOn_derivWithin (h : ContDiffOn 𝕜 n f₂ s₂) (hs : UniqueDiffOn 𝕜 s₂)
(hn : 1 ≤ n) : ContinuousOn (derivWithin f₂ s₂) s₂ := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl] at hn
exact ((contDiffOn_succ_iff_derivWithin hs).1 (h.of_le hn)).2.2.continuousOn
theorem ContDiffOn.continuousOn_deriv_of_isOpen (h : ContDiffOn 𝕜 n f₂ s₂) (hs : IsOpen s₂)
(hn : 1 ≤ n) : ContinuousOn (deriv f₂) s₂ := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl] at hn
exact ((contDiffOn_succ_iff_deriv_of_isOpen hs).1 (h.of_le hn)).2.2.continuousOn
/-- A function is `C^(n + 1)` if and only if it is differentiable,
and its derivative (formulated in terms of `deriv`) is `C^n`. -/
theorem contDiff_succ_iff_deriv :
ContDiff 𝕜 (n + 1) f₂ ↔ Differentiable 𝕜 f₂ ∧ (n = ω → AnalyticOn 𝕜 f₂ univ) ∧
ContDiff 𝕜 n (deriv f₂) := by
simp only [← contDiffOn_univ, contDiffOn_succ_iff_deriv_of_isOpen, isOpen_univ,
differentiableOn_univ]
theorem contDiff_one_iff_deriv :
ContDiff 𝕜 1 f₂ ↔ Differentiable 𝕜 f₂ ∧ Continuous (deriv f₂) := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl, contDiff_succ_iff_deriv]
simp
theorem contDiff_infty_iff_deriv :
ContDiff 𝕜 ∞ f₂ ↔ Differentiable 𝕜 f₂ ∧ ContDiff 𝕜 ∞ (deriv f₂) := by
rw [show (∞ : WithTop ℕ∞) = ∞ + 1 from rfl, contDiff_succ_iff_deriv]
simp
@[deprecated (since := "2024-11-27")] alias contDiff_top_iff_deriv := contDiff_infty_iff_deriv
theorem ContDiff.continuous_deriv (h : ContDiff 𝕜 n f₂) (hn : 1 ≤ n) : Continuous (deriv f₂) := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl] at hn
exact (contDiff_succ_iff_deriv.mp (h.of_le hn)).2.2.continuous
theorem ContDiff.iterate_deriv :
∀ (n : ℕ) {f₂ : 𝕜 → F}, ContDiff 𝕜 ∞ f₂ → ContDiff 𝕜 ∞ (deriv^[n] f₂)
| 0, _, hf => hf
| n + 1, _, hf => ContDiff.iterate_deriv n (contDiff_infty_iff_deriv.mp hf).2
theorem ContDiff.iterate_deriv' (n : ℕ) :
∀ (k : ℕ) {f₂ : 𝕜 → F}, ContDiff 𝕜 (n + k : ℕ) f₂ → ContDiff 𝕜 n (deriv^[k] f₂)
| 0, _, hf => hf
| k + 1, _, hf => ContDiff.iterate_deriv' _ k (contDiff_succ_iff_deriv.mp hf).2.2
end deriv
| Mathlib/Analysis/Calculus/ContDiff/Basic.lean | 1,811 | 1,813 | |
/-
Copyright (c) 2021 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang, Yury Kudryashov
-/
import Mathlib.Order.UpperLower.Closure
import Mathlib.Order.UpperLower.Fibration
import Mathlib.Tactic.TFAE
import Mathlib.Topology.ContinuousOn
import Mathlib.Topology.Maps.OpenQuotient
/-!
# Inseparable points in a topological space
In this file we prove basic properties of the following notions defined elsewhere.
* `Specializes` (notation: `x ⤳ y`) : a relation saying that `𝓝 x ≤ 𝓝 y`;
* `Inseparable`: a relation saying that two points in a topological space have the same
neighbourhoods; equivalently, they can't be separated by an open set;
* `InseparableSetoid X`: same relation, as a `Setoid`;
* `SeparationQuotient X`: the quotient of `X` by its `InseparableSetoid`.
We also prove various basic properties of the relation `Inseparable`.
## Notations
- `x ⤳ y`: notation for `Specializes x y`;
- `x ~ᵢ y` is used as a local notation for `Inseparable x y`;
- `𝓝 x` is the neighbourhoods filter `nhds x` of a point `x`, defined elsewhere.
## Tags
topological space, separation setoid
-/
open Set Filter Function Topology List
variable {X Y Z α ι : Type*} {π : ι → Type*} [TopologicalSpace X] [TopologicalSpace Y]
[TopologicalSpace Z] [∀ i, TopologicalSpace (π i)] {x y z : X} {s : Set X} {f g : X → Y}
/-!
### `Specializes` relation
-/
/-- A collection of equivalent definitions of `x ⤳ y`. The public API is given by `iff` lemmas
below. -/
theorem specializes_TFAE (x y : X) :
TFAE [x ⤳ y,
pure x ≤ 𝓝 y,
∀ s : Set X , IsOpen s → y ∈ s → x ∈ s,
∀ s : Set X , IsClosed s → x ∈ s → y ∈ s,
y ∈ closure ({ x } : Set X),
closure ({ y } : Set X) ⊆ closure { x },
ClusterPt y (pure x)] := by
tfae_have 1 → 2 := (pure_le_nhds _).trans
tfae_have 2 → 3 := fun h s hso hy => h (hso.mem_nhds hy)
tfae_have 3 → 4 := fun h s hsc hx => of_not_not fun hy => h sᶜ hsc.isOpen_compl hy hx
tfae_have 4 → 5 := fun h => h _ isClosed_closure (subset_closure <| mem_singleton _)
tfae_have 6 ↔ 5 := isClosed_closure.closure_subset_iff.trans singleton_subset_iff
tfae_have 5 ↔ 7 := by
rw [mem_closure_iff_clusterPt, principal_singleton]
tfae_have 5 → 1 := by
refine fun h => (nhds_basis_opens _).ge_iff.2 ?_
rintro s ⟨hy, ho⟩
rcases mem_closure_iff.1 h s ho hy with ⟨z, hxs, rfl : z = x⟩
exact ho.mem_nhds hxs
tfae_finish
theorem specializes_iff_nhds : x ⤳ y ↔ 𝓝 x ≤ 𝓝 y :=
Iff.rfl
theorem Specializes.not_disjoint (h : x ⤳ y) : ¬Disjoint (𝓝 x) (𝓝 y) := fun hd ↦
absurd (hd.mono_right h) <| by simp [NeBot.ne']
theorem specializes_iff_pure : x ⤳ y ↔ pure x ≤ 𝓝 y :=
(specializes_TFAE x y).out 0 1
alias ⟨Specializes.nhds_le_nhds, _⟩ := specializes_iff_nhds
alias ⟨Specializes.pure_le_nhds, _⟩ := specializes_iff_pure
theorem ker_nhds_eq_specializes : (𝓝 x).ker = {y | y ⤳ x} := by
ext; simp [specializes_iff_pure, le_def]
theorem specializes_iff_forall_open : x ⤳ y ↔ ∀ s : Set X, IsOpen s → y ∈ s → x ∈ s :=
(specializes_TFAE x y).out 0 2
theorem Specializes.mem_open (h : x ⤳ y) (hs : IsOpen s) (hy : y ∈ s) : x ∈ s :=
specializes_iff_forall_open.1 h s hs hy
theorem IsOpen.not_specializes (hs : IsOpen s) (hx : x ∉ s) (hy : y ∈ s) : ¬x ⤳ y := fun h =>
hx <| h.mem_open hs hy
theorem specializes_iff_forall_closed : x ⤳ y ↔ ∀ s : Set X, IsClosed s → x ∈ s → y ∈ s :=
(specializes_TFAE x y).out 0 3
theorem Specializes.mem_closed (h : x ⤳ y) (hs : IsClosed s) (hx : x ∈ s) : y ∈ s :=
specializes_iff_forall_closed.1 h s hs hx
theorem IsClosed.not_specializes (hs : IsClosed s) (hx : x ∈ s) (hy : y ∉ s) : ¬x ⤳ y := fun h =>
hy <| h.mem_closed hs hx
theorem specializes_iff_mem_closure : x ⤳ y ↔ y ∈ closure ({x} : Set X) :=
(specializes_TFAE x y).out 0 4
alias ⟨Specializes.mem_closure, _⟩ := specializes_iff_mem_closure
theorem specializes_iff_closure_subset : x ⤳ y ↔ closure ({y} : Set X) ⊆ closure {x} :=
(specializes_TFAE x y).out 0 5
alias ⟨Specializes.closure_subset, _⟩ := specializes_iff_closure_subset
theorem specializes_iff_clusterPt : x ⤳ y ↔ ClusterPt y (pure x) :=
(specializes_TFAE x y).out 0 6
theorem Filter.HasBasis.specializes_iff {ι} {p : ι → Prop} {s : ι → Set X}
(h : (𝓝 y).HasBasis p s) : x ⤳ y ↔ ∀ i, p i → x ∈ s i :=
specializes_iff_pure.trans h.ge_iff
theorem specializes_rfl : x ⤳ x := le_rfl
@[refl]
theorem specializes_refl (x : X) : x ⤳ x :=
specializes_rfl
@[trans]
theorem Specializes.trans : x ⤳ y → y ⤳ z → x ⤳ z :=
le_trans
theorem specializes_of_eq (e : x = y) : x ⤳ y :=
e ▸ specializes_refl x
alias Specializes.of_eq := specializes_of_eq
theorem specializes_of_nhdsWithin (h₁ : 𝓝[s] x ≤ 𝓝[s] y) (h₂ : x ∈ s) : x ⤳ y :=
specializes_iff_pure.2 <|
calc
pure x ≤ 𝓝[s] x := le_inf (pure_le_nhds _) (le_principal_iff.2 h₂)
_ ≤ 𝓝[s] y := h₁
_ ≤ 𝓝 y := inf_le_left
theorem Specializes.map_of_continuousAt (h : x ⤳ y) (hy : ContinuousAt f y) : f x ⤳ f y :=
specializes_iff_pure.2 fun _s hs =>
mem_pure.2 <| mem_preimage.1 <| mem_of_mem_nhds <| hy.mono_left h hs
theorem Specializes.map (h : x ⤳ y) (hf : Continuous f) : f x ⤳ f y :=
h.map_of_continuousAt hf.continuousAt
theorem Topology.IsInducing.specializes_iff (hf : IsInducing f) : f x ⤳ f y ↔ x ⤳ y := by
simp only [specializes_iff_mem_closure, hf.closure_eq_preimage_closure_image, image_singleton,
mem_preimage]
@[deprecated (since := "2024-10-28")] alias Inducing.specializes_iff := IsInducing.specializes_iff
theorem subtype_specializes_iff {p : X → Prop} (x y : Subtype p) : x ⤳ y ↔ (x : X) ⤳ y :=
IsInducing.subtypeVal.specializes_iff.symm
@[simp]
theorem specializes_prod {x₁ x₂ : X} {y₁ y₂ : Y} : (x₁, y₁) ⤳ (x₂, y₂) ↔ x₁ ⤳ x₂ ∧ y₁ ⤳ y₂ := by
simp only [Specializes, nhds_prod_eq, prod_le_prod]
theorem Specializes.prod {x₁ x₂ : X} {y₁ y₂ : Y} (hx : x₁ ⤳ x₂) (hy : y₁ ⤳ y₂) :
(x₁, y₁) ⤳ (x₂, y₂) :=
specializes_prod.2 ⟨hx, hy⟩
theorem Specializes.fst {a b : X × Y} (h : a ⤳ b) : a.1 ⤳ b.1 := (specializes_prod.1 h).1
theorem Specializes.snd {a b : X × Y} (h : a ⤳ b) : a.2 ⤳ b.2 := (specializes_prod.1 h).2
@[simp]
theorem specializes_pi {f g : ∀ i, π i} : f ⤳ g ↔ ∀ i, f i ⤳ g i := by
simp only [Specializes, nhds_pi, pi_le_pi]
theorem not_specializes_iff_exists_open : ¬x ⤳ y ↔ ∃ S : Set X, IsOpen S ∧ y ∈ S ∧ x ∉ S := by
rw [specializes_iff_forall_open]
push_neg
rfl
theorem not_specializes_iff_exists_closed : ¬x ⤳ y ↔ ∃ S : Set X, IsClosed S ∧ x ∈ S ∧ y ∉ S := by
rw [specializes_iff_forall_closed]
push_neg
rfl
theorem IsOpen.continuous_piecewise_of_specializes [DecidablePred (· ∈ s)] (hs : IsOpen s)
(hf : Continuous f) (hg : Continuous g) (hspec : ∀ x, f x ⤳ g x) :
Continuous (s.piecewise f g) := by
have : ∀ U, IsOpen U → g ⁻¹' U ⊆ f ⁻¹' U := fun U hU x hx ↦ (hspec x).mem_open hU hx
rw [continuous_def]
intro U hU
rw [piecewise_preimage, ite_eq_of_subset_right _ (this U hU)]
exact hU.preimage hf |>.inter hs |>.union (hU.preimage hg)
theorem IsClosed.continuous_piecewise_of_specializes [DecidablePred (· ∈ s)] (hs : IsClosed s)
(hf : Continuous f) (hg : Continuous g) (hspec : ∀ x, g x ⤳ f x) :
Continuous (s.piecewise f g) := by
simpa only [piecewise_compl] using hs.isOpen_compl.continuous_piecewise_of_specializes hg hf hspec
attribute [local instance] specializationPreorder
/-- A continuous function is monotone with respect to the specialization preorders on the domain and
the codomain. -/
theorem Continuous.specialization_monotone (hf : Continuous f) : Monotone f :=
fun _ _ h => h.map hf
lemma closure_singleton_eq_Iic (x : X) : closure {x} = Iic x :=
Set.ext fun _ ↦ specializes_iff_mem_closure.symm
/-- A subset `S` of a topological space is stable under specialization
if `x ∈ S → y ∈ S` for all `x ⤳ y`. -/
def StableUnderSpecialization (s : Set X) : Prop :=
∀ ⦃x y⦄, x ⤳ y → x ∈ s → y ∈ s
/-- A subset `S` of a topological space is stable under specialization
if `x ∈ S → y ∈ S` for all `y ⤳ x`. -/
def StableUnderGeneralization (s : Set X) : Prop :=
∀ ⦃x y⦄, y ⤳ x → x ∈ s → y ∈ s
example {s : Set X} : StableUnderSpecialization s ↔ IsLowerSet s := Iff.rfl
example {s : Set X} : StableUnderGeneralization s ↔ IsUpperSet s := Iff.rfl
lemma IsClosed.stableUnderSpecialization {s : Set X} (hs : IsClosed s) :
StableUnderSpecialization s :=
fun _ _ e ↦ e.mem_closed hs
lemma IsOpen.stableUnderGeneralization {s : Set X} (hs : IsOpen s) :
StableUnderGeneralization s :=
fun _ _ e ↦ e.mem_open hs
@[simp]
lemma stableUnderSpecialization_compl_iff {s : Set X} :
StableUnderSpecialization sᶜ ↔ StableUnderGeneralization s :=
isLowerSet_compl
@[simp]
lemma stableUnderGeneralization_compl_iff {s : Set X} :
StableUnderGeneralization sᶜ ↔ StableUnderSpecialization s :=
isUpperSet_compl
alias ⟨_, StableUnderGeneralization.compl⟩ := stableUnderSpecialization_compl_iff
alias ⟨_, StableUnderSpecialization.compl⟩ := stableUnderGeneralization_compl_iff
lemma stableUnderSpecialization_univ : StableUnderSpecialization (univ : Set X) := isLowerSet_univ
lemma stableUnderSpecialization_empty : StableUnderSpecialization (∅ : Set X) := isLowerSet_empty
lemma stableUnderGeneralization_univ : StableUnderGeneralization (univ : Set X) := isUpperSet_univ
lemma stableUnderGeneralization_empty : StableUnderGeneralization (∅ : Set X) := isUpperSet_empty
lemma stableUnderSpecialization_sUnion (S : Set (Set X))
(H : ∀ s ∈ S, StableUnderSpecialization s) : StableUnderSpecialization (⋃₀ S) :=
isLowerSet_sUnion H
lemma stableUnderSpecialization_sInter (S : Set (Set X))
(H : ∀ s ∈ S, StableUnderSpecialization s) : StableUnderSpecialization (⋂₀ S) :=
isLowerSet_sInter H
lemma stableUnderGeneralization_sUnion (S : Set (Set X))
(H : ∀ s ∈ S, StableUnderGeneralization s) : StableUnderGeneralization (⋃₀ S) :=
isUpperSet_sUnion H
lemma stableUnderGeneralization_sInter (S : Set (Set X))
(H : ∀ s ∈ S, StableUnderGeneralization s) : StableUnderGeneralization (⋂₀ S) :=
isUpperSet_sInter H
lemma stableUnderSpecialization_iUnion {ι : Sort*} (S : ι → Set X)
(H : ∀ i, StableUnderSpecialization (S i)) : StableUnderSpecialization (⋃ i, S i) :=
isLowerSet_iUnion H
lemma stableUnderSpecialization_iInter {ι : Sort*} (S : ι → Set X)
(H : ∀ i, StableUnderSpecialization (S i)) : StableUnderSpecialization (⋂ i, S i) :=
isLowerSet_iInter H
lemma stableUnderGeneralization_iUnion {ι : Sort*} (S : ι → Set X)
(H : ∀ i, StableUnderGeneralization (S i)) : StableUnderGeneralization (⋃ i, S i) :=
isUpperSet_iUnion H
lemma stableUnderGeneralization_iInter {ι : Sort*} (S : ι → Set X)
(H : ∀ i, StableUnderGeneralization (S i)) : StableUnderGeneralization (⋂ i, S i) :=
isUpperSet_iInter H
lemma Union_closure_singleton_eq_iff {s : Set X} :
(⋃ x ∈ s, closure {x}) = s ↔ StableUnderSpecialization s :=
show _ ↔ IsLowerSet s by simp only [closure_singleton_eq_Iic, ← lowerClosure_eq, coe_lowerClosure]
lemma stableUnderSpecialization_iff_Union_eq {s : Set X} :
StableUnderSpecialization s ↔ (⋃ x ∈ s, closure {x}) = s :=
Union_closure_singleton_eq_iff.symm
alias ⟨StableUnderSpecialization.Union_eq, _⟩ := stableUnderSpecialization_iff_Union_eq
/-- A set is stable under specialization iff it is a union of closed sets. -/
lemma stableUnderSpecialization_iff_exists_sUnion_eq {s : Set X} :
StableUnderSpecialization s ↔ ∃ (S : Set (Set X)), (∀ s ∈ S, IsClosed s) ∧ ⋃₀ S = s := by
refine ⟨fun H ↦ ⟨(fun x : X ↦ closure {x}) '' s, ?_, ?_⟩, fun ⟨S, hS, e⟩ ↦ e ▸
stableUnderSpecialization_sUnion S (fun x hx ↦ (hS x hx).stableUnderSpecialization)⟩
· rintro _ ⟨_, _, rfl⟩; exact isClosed_closure
| · conv_rhs => rw [← H.Union_eq]
simp
| Mathlib/Topology/Inseparable.lean | 298 | 300 |
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Equiv
import Mathlib.Analysis.Calculus.FDeriv.Prod
import Mathlib.Analysis.Calculus.Monotone
import Mathlib.Topology.EMetricSpace.BoundedVariation
/-!
# Almost everywhere differentiability of functions with locally bounded variation
In this file we show that a bounded variation function is differentiable almost everywhere.
This implies that Lipschitz functions from the real line into finite-dimensional vector space
are also differentiable almost everywhere.
## Main definitions and results
* `LocallyBoundedVariationOn.ae_differentiableWithinAt` shows that a bounded variation
function into a finite dimensional real vector space is differentiable almost everywhere.
* `LipschitzOnWith.ae_differentiableWithinAt` is the same result for Lipschitz functions.
We also give several variations around these results.
-/
open scoped NNReal ENNReal Topology
open Set MeasureTheory Filter
variable {α : Type*} [LinearOrder α] {E : Type*} [PseudoEMetricSpace E]
/-! ## -/
variable {V : Type*} [NormedAddCommGroup V] [NormedSpace ℝ V] [FiniteDimensional ℝ V]
namespace LocallyBoundedVariationOn
/-- A bounded variation function into `ℝ` is differentiable almost everywhere. Superseded by
`ae_differentiableWithinAt_of_mem`. -/
theorem ae_differentiableWithinAt_of_mem_real {f : ℝ → ℝ} {s : Set ℝ}
(h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by
obtain ⟨p, q, hp, hq, rfl⟩ : ∃ p q, MonotoneOn p s ∧ MonotoneOn q s ∧ f = p - q :=
h.exists_monotoneOn_sub_monotoneOn
filter_upwards [hp.ae_differentiableWithinAt_of_mem, hq.ae_differentiableWithinAt_of_mem] with
x hxp hxq xs
exact (hxp xs).sub (hxq xs)
/-- A bounded variation function into a finite dimensional product vector space is differentiable
almost everywhere. Superseded by `ae_differentiableWithinAt_of_mem`. -/
theorem ae_differentiableWithinAt_of_mem_pi {ι : Type*} [Fintype ι] {f : ℝ → ι → ℝ} {s : Set ℝ}
(h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by
have A : ∀ i : ι, LipschitzWith 1 fun x : ι → ℝ => x i := fun i => LipschitzWith.eval i
have : ∀ i : ι, ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ (fun x : ℝ => f x i) s x := fun i ↦ by
apply ae_differentiableWithinAt_of_mem_real
exact LipschitzWith.comp_locallyBoundedVariationOn (A i) h
filter_upwards [ae_all_iff.2 this] with x hx xs
exact differentiableWithinAt_pi.2 fun i => hx i xs
/-- A real function into a finite dimensional real vector space with bounded variation on a set
is differentiable almost everywhere in this set. -/
theorem ae_differentiableWithinAt_of_mem {f : ℝ → V} {s : Set ℝ}
(h : LocallyBoundedVariationOn f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x := by
let A := (Basis.ofVectorSpace ℝ V).equivFun.toContinuousLinearEquiv
suffices H : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ (A ∘ f) s x by
filter_upwards [H] with x hx xs
have : f = (A.symm ∘ A) ∘ f := by
simp only [ContinuousLinearEquiv.symm_comp_self, Function.id_comp]
rw [this]
exact A.symm.differentiableAt.comp_differentiableWithinAt x (hx xs)
apply ae_differentiableWithinAt_of_mem_pi
exact A.lipschitz.comp_locallyBoundedVariationOn h
/-- A real function into a finite dimensional real vector space with bounded variation on a set
is differentiable almost everywhere in this set. -/
theorem ae_differentiableWithinAt {f : ℝ → V} {s : Set ℝ} (h : LocallyBoundedVariationOn f s)
(hs : MeasurableSet s) : ∀ᵐ x ∂volume.restrict s, DifferentiableWithinAt ℝ f s x := by
rw [ae_restrict_iff' hs]
exact h.ae_differentiableWithinAt_of_mem
/-- A real function into a finite dimensional real vector space with bounded variation
is differentiable almost everywhere. -/
theorem ae_differentiableAt {f : ℝ → V} (h : LocallyBoundedVariationOn f univ) :
∀ᵐ x, DifferentiableAt ℝ f x := by
filter_upwards [h.ae_differentiableWithinAt_of_mem] with x hx
rw [differentiableWithinAt_univ] at hx
exact hx (mem_univ _)
end LocallyBoundedVariationOn
/-- A real function into a finite dimensional real vector space which is Lipschitz on a set
is differentiable almost everywhere in this set. For the general Rademacher theorem assuming
that the source space is finite dimensional, see `LipschitzOnWith.ae_differentiableWithinAt_of_mem`.
-/
theorem LipschitzOnWith.ae_differentiableWithinAt_of_mem_real {C : ℝ≥0} {f : ℝ → V} {s : Set ℝ}
(h : LipschitzOnWith C f s) : ∀ᵐ x, x ∈ s → DifferentiableWithinAt ℝ f s x :=
h.locallyBoundedVariationOn.ae_differentiableWithinAt_of_mem
/-- A real function into a finite dimensional real vector space which is Lipschitz on a set
is differentiable almost everywhere in this set. For the general Rademacher theorem assuming
that the source space is finite dimensional, see `LipschitzOnWith.ae_differentiableWithinAt`. -/
theorem LipschitzOnWith.ae_differentiableWithinAt_real {C : ℝ≥0} {f : ℝ → V} {s : Set ℝ}
(h : LipschitzOnWith C f s) (hs : MeasurableSet s) :
∀ᵐ x ∂volume.restrict s, DifferentiableWithinAt ℝ f s x :=
h.locallyBoundedVariationOn.ae_differentiableWithinAt hs
/-- A real Lipschitz function into a finite dimensional real vector space is differentiable
almost everywhere. For the general Rademacher theorem assuming
that the source space is finite dimensional, see `LipschitzWith.ae_differentiableAt`. -/
theorem LipschitzWith.ae_differentiableAt_real {C : ℝ≥0} {f : ℝ → V} (h : LipschitzWith C f) :
∀ᵐ x, DifferentiableAt ℝ f x :=
(h.locallyBoundedVariationOn univ).ae_differentiableAt
| Mathlib/Analysis/BoundedVariation.lean | 501 | 507 | |
/-
Copyright (c) 2024 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.CategoryTheory.Filtered.Connected
import Mathlib.CategoryTheory.Limits.Types.Filtered
import Mathlib.CategoryTheory.Limits.Sifted
/-!
# Final functors with filtered (co)domain
If `C` is a filtered category, then the usual equivalent conditions for a functor `F : C ⥤ D` to be
final can be restated. We show:
* `final_iff_of_isFiltered`: a concrete description of finality which is sometimes a convenient way
to show that a functor is final.
* `final_iff_isFiltered_structuredArrow`: `F` is final if and only if `StructuredArrow d F` is
filtered for all `d : D`, which strengthens the usual statement that `F` is final if and only
if `StructuredArrow d F` is connected for all `d : D`.
* Under categories of objects of filtered categories are filtered and their forgetful functors
are final.
* If `D` is a filtered category and `F : C ⥤ D` is fully faithful and satisfies the additional
condition that for every `d : D` there is an object `c : D` and a morphism `d ⟶ F.obj c`, then
`C` is filtered and `F` is final.
* Finality and initiality of diagonal functors `diag : C ⥤ C × C` and of projection functors
of (co)structured arrow categories.
* Finality of `StructuredArrow.post`, given the finality of its arguments.
## References
* [M. Kashiwara, P. Schapira, *Categories and Sheaves*][Kashiwara2006], Section 3.2
-/
universe v₁ v₂ v₃ u₁ u₂ u₃
namespace CategoryTheory
open CategoryTheory.Limits CategoryTheory.Functor Opposite
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D] (F : C ⥤ D)
/-- If `StructuredArrow d F` is filtered for any `d : D`, then `F : C ⥤ D` is final. This is
simply because filtered categories are connected. More profoundly, the converse is also true if
`C` is filtered, see `final_iff_isFiltered_structuredArrow`. -/
theorem Functor.final_of_isFiltered_structuredArrow [∀ d, IsFiltered (StructuredArrow d F)] :
Final F where
out _ := IsFiltered.isConnected _
/-- If `CostructuredArrow F d` is filtered for any `d : D`, then `F : C ⥤ D` is initial. This is
simply because cofiltered categories are connectged. More profoundly, the converse is also true
if `C` is cofiltered, see `initial_iff_isCofiltered_costructuredArrow`. -/
theorem Functor.initial_of_isCofiltered_costructuredArrow
[∀ d, IsCofiltered (CostructuredArrow F d)] : Initial F where
out _ := IsCofiltered.isConnected _
theorem isFiltered_structuredArrow_of_isFiltered_of_exists [IsFilteredOrEmpty C]
(h₁ : ∀ d, ∃ c, Nonempty (d ⟶ F.obj c)) (h₂ : ∀ {d : D} {c : C} (s s' : d ⟶ F.obj c),
∃ (c' : C) (t : c ⟶ c'), s ≫ F.map t = s' ≫ F.map t) (d : D) :
IsFiltered (StructuredArrow d F) := by
have : Nonempty (StructuredArrow d F) := by
obtain ⟨c, ⟨f⟩⟩ := h₁ d
exact ⟨.mk f⟩
suffices IsFilteredOrEmpty (StructuredArrow d F) from IsFiltered.mk
refine ⟨fun f g => ?_, fun f g η μ => ?_⟩
· obtain ⟨c, ⟨t, ht⟩⟩ := h₂ (f.hom ≫ F.map (IsFiltered.leftToMax f.right g.right))
(g.hom ≫ F.map (IsFiltered.rightToMax f.right g.right))
refine ⟨.mk (f.hom ≫ F.map (IsFiltered.leftToMax f.right g.right ≫ t)), ?_, ?_, trivial⟩
· exact StructuredArrow.homMk (IsFiltered.leftToMax _ _ ≫ t) rfl
· exact StructuredArrow.homMk (IsFiltered.rightToMax _ _ ≫ t) (by simpa using ht.symm)
· refine ⟨.mk (f.hom ≫ F.map (η.right ≫ IsFiltered.coeqHom η.right μ.right)),
StructuredArrow.homMk (IsFiltered.coeqHom η.right μ.right) (by simp), ?_⟩
simpa using IsFiltered.coeq_condition _ _
theorem isCofiltered_costructuredArrow_of_isCofiltered_of_exists [IsCofilteredOrEmpty C]
(h₁ : ∀ d, ∃ c, Nonempty (F.obj c ⟶ d)) (h₂ : ∀ {d : D} {c : C} (s s' : F.obj c ⟶ d),
∃ (c' : C) (t : c' ⟶ c), F.map t ≫ s = F.map t ≫ s') (d : D) :
IsCofiltered (CostructuredArrow F d) := by
suffices IsFiltered (CostructuredArrow F d)ᵒᵖ from isCofiltered_of_isFiltered_op _
suffices IsFiltered (StructuredArrow (op d) F.op) from
IsFiltered.of_equivalence (costructuredArrowOpEquivalence _ _).symm
apply isFiltered_structuredArrow_of_isFiltered_of_exists
· intro d
obtain ⟨c, ⟨t⟩⟩ := h₁ d.unop
exact ⟨op c, ⟨Quiver.Hom.op t⟩⟩
· intro d c s s'
obtain ⟨c', t, ht⟩ := h₂ s.unop s'.unop
exact ⟨op c', Quiver.Hom.op t, Quiver.Hom.unop_inj ht⟩
/-- If `C` is filtered, then we can give an explicit condition for a functor `F : C ⥤ D` to
be final. The converse is also true, see `final_iff_of_isFiltered`. -/
theorem Functor.final_of_exists_of_isFiltered [IsFilteredOrEmpty C]
(h₁ : ∀ d, ∃ c, Nonempty (d ⟶ F.obj c)) (h₂ : ∀ {d : D} {c : C} (s s' : d ⟶ F.obj c),
∃ (c' : C) (t : c ⟶ c'), s ≫ F.map t = s' ≫ F.map t) : Functor.Final F := by
suffices ∀ d, IsFiltered (StructuredArrow d F) from final_of_isFiltered_structuredArrow F
exact isFiltered_structuredArrow_of_isFiltered_of_exists F h₁ h₂
/-- The inclusion of a terminal object is final. -/
theorem Functor.final_const_of_isTerminal [IsFiltered C] {X : D} (hX : IsTerminal X) :
((Functor.const C).obj X).Final :=
Functor.final_of_exists_of_isFiltered _ (fun _ => ⟨IsFiltered.nonempty.some, ⟨hX.from _⟩⟩)
(fun {_ c} _ _ => ⟨c, 𝟙 _, hX.hom_ext _ _⟩)
/-- The inclusion of the terminal object is final. -/
theorem Functor.final_const_terminal [IsFiltered C] [HasTerminal D] :
((Functor.const C).obj (⊤_ D)).Final :=
Functor.final_const_of_isTerminal terminalIsTerminal
/-- If `C` is cofiltered, then we can give an explicit condition for a functor `F : C ⥤ D` to
be final. The converse is also true, see `initial_iff_of_isCofiltered`. -/
theorem Functor.initial_of_exists_of_isCofiltered [IsCofilteredOrEmpty C]
(h₁ : ∀ d, ∃ c, Nonempty (F.obj c ⟶ d)) (h₂ : ∀ {d : D} {c : C} (s s' : F.obj c ⟶ d),
∃ (c' : C) (t : c' ⟶ c), F.map t ≫ s = F.map t ≫ s') : Functor.Initial F := by
suffices ∀ d, IsCofiltered (CostructuredArrow F d) from
initial_of_isCofiltered_costructuredArrow F
exact isCofiltered_costructuredArrow_of_isCofiltered_of_exists F h₁ h₂
/-- The inclusion of an initial object is initial. -/
theorem Functor.initial_const_of_isInitial [IsCofiltered C] {X : D} (hX : IsInitial X) :
((Functor.const C).obj X).Initial :=
Functor.initial_of_exists_of_isCofiltered _ (fun _ => ⟨IsCofiltered.nonempty.some, ⟨hX.to _⟩⟩)
(fun {_ c} _ _ => ⟨c, 𝟙 _, hX.hom_ext _ _⟩)
/-- The inclusion of the initial object is initial. -/
theorem Functor.initial_const_initial [IsCofiltered C] [HasInitial D] :
((Functor.const C).obj (⊥_ D)).Initial :=
Functor.initial_const_of_isInitial initialIsInitial
/-- In this situation, `F` is also final, see
`Functor.final_of_exists_of_isFiltered_of_fullyFaithful`. -/
theorem IsFilteredOrEmpty.of_exists_of_isFiltered_of_fullyFaithful [IsFilteredOrEmpty D] [F.Full]
[F.Faithful] (h : ∀ d, ∃ c, Nonempty (d ⟶ F.obj c)) : IsFilteredOrEmpty C where
cocone_objs c c' := by
obtain ⟨c₀, ⟨f⟩⟩ := h (IsFiltered.max (F.obj c) (F.obj c'))
exact ⟨c₀, F.preimage (IsFiltered.leftToMax _ _ ≫ f),
F.preimage (IsFiltered.rightToMax _ _ ≫ f), trivial⟩
cocone_maps {c c'} f g := by
obtain ⟨c₀, ⟨f₀⟩⟩ := h (IsFiltered.coeq (F.map f) (F.map g))
refine ⟨_, F.preimage (IsFiltered.coeqHom (F.map f) (F.map g) ≫ f₀), F.map_injective ?_⟩
simp [reassoc_of% (IsFiltered.coeq_condition (F.map f) (F.map g))]
/-- In this situation, `F` is also initial, see
`Functor.initial_of_exists_of_isCofiltered_of_fullyFaithful`. -/
theorem IsCofilteredOrEmpty.of_exists_of_isCofiltered_of_fullyFaithful [IsCofilteredOrEmpty D]
[F.Full] [F.Faithful] (h : ∀ d, ∃ c, Nonempty (F.obj c ⟶ d)) : IsCofilteredOrEmpty C := by
suffices IsFilteredOrEmpty Cᵒᵖ from isCofilteredOrEmpty_of_isFilteredOrEmpty_op _
refine IsFilteredOrEmpty.of_exists_of_isFiltered_of_fullyFaithful F.op (fun d => ?_)
obtain ⟨c, ⟨f⟩⟩ := h d.unop
exact ⟨op c, ⟨f.op⟩⟩
/-- In this situation, `F` is also final, see
`Functor.final_of_exists_of_isFiltered_of_fullyFaithful`. -/
theorem IsFiltered.of_exists_of_isFiltered_of_fullyFaithful [IsFiltered D] [F.Full] [F.Faithful]
(h : ∀ d, ∃ c, Nonempty (d ⟶ F.obj c)) : IsFiltered C :=
{ IsFilteredOrEmpty.of_exists_of_isFiltered_of_fullyFaithful F h with
nonempty := by
have : Nonempty D := IsFiltered.nonempty
obtain ⟨c, -⟩ := h (Classical.arbitrary D)
exact ⟨c⟩ }
/-- In this situation, `F` is also initial, see
`Functor.initial_of_exists_of_isCofiltered_of_fullyFaithful`. -/
theorem IsCofiltered.of_exists_of_isCofiltered_of_fullyFaithful [IsCofiltered D] [F.Full]
[F.Faithful] (h : ∀ d, ∃ c, Nonempty (F.obj c ⟶ d)) : IsCofiltered C :=
{ IsCofilteredOrEmpty.of_exists_of_isCofiltered_of_fullyFaithful F h with
nonempty := by
have : Nonempty D := IsCofiltered.nonempty
obtain ⟨c, -⟩ := h (Classical.arbitrary D)
exact ⟨c⟩ }
/-- In this situation, `C` is also filtered, see
`IsFilteredOrEmpty.of_exists_of_isFiltered_of_fullyFaithful`. -/
theorem Functor.final_of_exists_of_isFiltered_of_fullyFaithful [IsFilteredOrEmpty D] [F.Full]
[F.Faithful] (h : ∀ d, ∃ c, Nonempty (d ⟶ F.obj c)) : Final F := by
have := IsFilteredOrEmpty.of_exists_of_isFiltered_of_fullyFaithful F h
refine Functor.final_of_exists_of_isFiltered F h (fun {d c} s s' => ?_)
obtain ⟨c₀, ⟨f⟩⟩ := h (IsFiltered.coeq s s')
refine ⟨c₀, F.preimage (IsFiltered.coeqHom s s' ≫ f), ?_⟩
simp [reassoc_of% (IsFiltered.coeq_condition s s')]
/-- In this situation, `C` is also cofiltered, see
`IsCofilteredOrEmpty.of_exists_of_isCofiltered_of_fullyFaithful`. -/
theorem Functor.initial_of_exists_of_isCofiltered_of_fullyFaithful [IsCofilteredOrEmpty D] [F.Full]
[Faithful F] (h : ∀ d, ∃ c, Nonempty (F.obj c ⟶ d)) : Initial F := by
suffices Final F.op from initial_of_final_op _
refine Functor.final_of_exists_of_isFiltered_of_fullyFaithful F.op (fun d => ?_)
obtain ⟨c, ⟨f⟩⟩ := h d.unop
exact ⟨op c, ⟨f.op⟩⟩
/-- Any under category on a filtered or empty category is filtered.
(Note that under categories are always cofiltered since they have an initial object.) -/
instance IsFiltered.under [IsFilteredOrEmpty C] (c : C) : IsFiltered (Under c) :=
isFiltered_structuredArrow_of_isFiltered_of_exists _
(fun c' => ⟨c', ⟨𝟙 _⟩⟩)
(fun s s' => IsFilteredOrEmpty.cocone_maps s s') c
/-- Any over category on a cofiltered or empty category is cofiltered.
(Note that over categories are always filtered since they have a terminal object.) -/
instance IsCofiltered.over [IsCofilteredOrEmpty C] (c : C) : IsCofiltered (Over c) :=
isCofiltered_costructuredArrow_of_isCofiltered_of_exists _
(fun c' => ⟨c', ⟨𝟙 _⟩⟩)
(fun s s' => IsCofilteredOrEmpty.cone_maps s s') c
/-- The forgetful functor of the under category on any filtered or empty category is final. -/
instance Under.final_forget [IsFilteredOrEmpty C] (c : C) : Final (Under.forget c) :=
final_of_exists_of_isFiltered _
(fun c' => ⟨mk (IsFiltered.leftToMax c c'), ⟨IsFiltered.rightToMax c c'⟩⟩)
(fun {_} {x} s s' => by
use mk (x.hom ≫ IsFiltered.coeqHom s s')
use homMk (IsFiltered.coeqHom s s') (by simp)
simp only [forget_obj, id_obj, mk_right, const_obj_obj, forget_map, homMk_right]
rw [IsFiltered.coeq_condition])
/-- The forgetful functor of the over category on any cofiltered or empty category is initial. -/
instance Over.initial_forget [IsCofilteredOrEmpty C] (c : C) : Initial (Over.forget c) :=
initial_of_exists_of_isCofiltered _
(fun c' => ⟨mk (IsCofiltered.minToLeft c c'), ⟨IsCofiltered.minToRight c c'⟩⟩)
(fun {_} {x} s s' => by
use mk (IsCofiltered.eqHom s s' ≫ x.hom)
use homMk (IsCofiltered.eqHom s s') (by simp)
simp only [forget_obj, mk_left, forget_map, homMk_left]
rw [IsCofiltered.eq_condition])
| section LocallySmall
variable {C : Type v₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₁} D] (F : C ⥤ D)
/-- Implementation; use `Functor.Final.exists_coeq instead`. -/
| Mathlib/CategoryTheory/Filtered/Final.lean | 225 | 229 |
/-
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.SetTheory.Cardinal.Finite
import Mathlib.Data.Set.Finite.Powerset
/-!
# Noncomputable Set Cardinality
We define the cardinality of set `s` as a term `Set.encard s : ℕ∞` and a term `Set.ncard s : ℕ`.
The latter takes the junk value of zero if `s` is infinite. Both functions are noncomputable, and
are defined in terms of `ENat.card` (which takes a type as its argument); this file can be seen
as an API for the same function in the special case where the type is a coercion of a `Set`,
allowing for smoother interactions with the `Set` API.
`Set.encard` never takes junk values, so is more mathematically natural than `Set.ncard`, even
though it takes values in a less convenient type. It is probably the right choice in settings where
one is concerned with the cardinalities of sets that may or may not be infinite.
`Set.ncard` has a nicer codomain, but when using it, `Set.Finite` hypotheses are normally needed to
make sure its values are meaningful. More generally, `Set.ncard` is intended to be used over the
obvious alternative `Finset.card` when finiteness is 'propositional' rather than 'structural'.
When working with sets that are finite by virtue of their definition, then `Finset.card` probably
makes more sense. One setting where `Set.ncard` works nicely is in a type `α` with `[Finite α]`,
where every set is automatically finite. In this setting, we use default arguments and a simple
tactic so that finiteness goals are discharged automatically in `Set.ncard` theorems.
## Main Definitions
* `Set.encard s` is the cardinality of the set `s` as an extended natural number, with value `⊤` if
`s` is infinite.
* `Set.ncard s` is the cardinality of the set `s` as a natural number, provided `s` is Finite.
If `s` is Infinite, then `Set.ncard s = 0`.
* `toFinite_tac` is a tactic that tries to synthesize a `Set.Finite s` argument with
`Set.toFinite`. This will work for `s : Set α` where there is a `Finite α` instance.
## Implementation Notes
The theorems in this file are very similar to those in `Data.Finset.Card`, but with `Set` operations
instead of `Finset`. We first prove all the theorems for `Set.encard`, and then derive most of the
`Set.ncard` results as a consequence. Things are done this way to avoid reliance on the `Finset` API
for theorems about infinite sets, and to allow for a refactor that removes or modifies `Set.ncard`
in the future.
Nearly all the theorems for `Set.ncard` require finiteness of one or more of their arguments. We
provide this assumption with a default argument of the form `(hs : s.Finite := by toFinite_tac)`,
where `toFinite_tac` will find an `s.Finite` term in the cases where `s` is a set in a `Finite`
type.
Often, where there are two set arguments `s` and `t`, the finiteness of one follows from the other
in the context of the theorem, in which case we only include the ones that are needed, and derive
the other inside the proof. A few of the theorems, such as `ncard_union_le` do not require
finiteness arguments; they are true by coincidence due to junk values.
-/
namespace Set
variable {α β : Type*} {s t : Set α}
/-- The cardinality of a set as a term in `ℕ∞` -/
noncomputable def encard (s : Set α) : ℕ∞ := ENat.card s
@[simp] theorem encard_univ_coe (s : Set α) : encard (univ : Set s) = encard s := by
rw [encard, encard, ENat.card_congr (Equiv.Set.univ ↑s)]
theorem encard_univ (α : Type*) :
encard (univ : Set α) = ENat.card α := by
rw [encard, ENat.card_congr (Equiv.Set.univ α)]
theorem Finite.encard_eq_coe_toFinset_card (h : s.Finite) : s.encard = h.toFinset.card := by
have := h.fintype
rw [encard, ENat.card_eq_coe_fintype_card, toFinite_toFinset, toFinset_card]
theorem encard_eq_coe_toFinset_card (s : Set α) [Fintype s] : encard s = s.toFinset.card := by
have h := toFinite s
rw [h.encard_eq_coe_toFinset_card, toFinite_toFinset]
@[simp] theorem toENat_cardinalMk (s : Set α) : (Cardinal.mk s).toENat = s.encard := rfl
theorem toENat_cardinalMk_subtype (P : α → Prop) :
(Cardinal.mk {x // P x}).toENat = {x | P x}.encard :=
rfl
@[simp] theorem coe_fintypeCard (s : Set α) [Fintype s] : Fintype.card s = s.encard := by
simp [encard_eq_coe_toFinset_card]
@[simp, norm_cast] theorem encard_coe_eq_coe_finsetCard (s : Finset α) :
encard (s : Set α) = s.card := by
rw [Finite.encard_eq_coe_toFinset_card (Finset.finite_toSet s)]; simp
@[simp] theorem Infinite.encard_eq {s : Set α} (h : s.Infinite) : s.encard = ⊤ := by
have := h.to_subtype
rw [encard, ENat.card_eq_top_of_infinite]
@[simp] theorem encard_eq_zero : s.encard = 0 ↔ s = ∅ := by
rw [encard, ENat.card_eq_zero_iff_empty, isEmpty_subtype, eq_empty_iff_forall_not_mem]
@[simp] theorem encard_empty : (∅ : Set α).encard = 0 := by
rw [encard_eq_zero]
theorem nonempty_of_encard_ne_zero (h : s.encard ≠ 0) : s.Nonempty := by
rwa [nonempty_iff_ne_empty, Ne, ← encard_eq_zero]
theorem encard_ne_zero : s.encard ≠ 0 ↔ s.Nonempty := by
rw [ne_eq, encard_eq_zero, nonempty_iff_ne_empty]
@[simp] theorem encard_pos : 0 < s.encard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, encard_ne_zero]
protected alias ⟨_, Nonempty.encard_pos⟩ := encard_pos
@[simp] theorem encard_singleton (e : α) : ({e} : Set α).encard = 1 := by
rw [encard, ENat.card_eq_coe_fintype_card, Fintype.card_ofSubsingleton, Nat.cast_one]
theorem encard_union_eq (h : Disjoint s t) : (s ∪ t).encard = s.encard + t.encard := by
classical
simp [encard, ENat.card_congr (Equiv.Set.union h)]
theorem encard_insert_of_not_mem {a : α} (has : a ∉ s) : (insert a s).encard = s.encard + 1 := by
rw [← union_singleton, encard_union_eq (by simpa), encard_singleton]
theorem Finite.encard_lt_top (h : s.Finite) : s.encard < ⊤ := by
induction s, h using Set.Finite.induction_on with
| empty => simp
| insert hat _ ht' =>
rw [encard_insert_of_not_mem hat]
exact lt_tsub_iff_right.1 ht'
theorem Finite.encard_eq_coe (h : s.Finite) : s.encard = ENat.toNat s.encard :=
(ENat.coe_toNat h.encard_lt_top.ne).symm
theorem Finite.exists_encard_eq_coe (h : s.Finite) : ∃ (n : ℕ), s.encard = n :=
⟨_, h.encard_eq_coe⟩
@[simp] theorem encard_lt_top_iff : s.encard < ⊤ ↔ s.Finite :=
⟨fun h ↦ by_contra fun h' ↦ h.ne (Infinite.encard_eq h'), Finite.encard_lt_top⟩
@[simp] theorem encard_eq_top_iff : s.encard = ⊤ ↔ s.Infinite := by
rw [← not_iff_not, ← Ne, ← lt_top_iff_ne_top, encard_lt_top_iff, not_infinite]
alias ⟨_, encard_eq_top⟩ := encard_eq_top_iff
theorem encard_ne_top_iff : s.encard ≠ ⊤ ↔ s.Finite := by
simp
theorem finite_of_encard_le_coe {k : ℕ} (h : s.encard ≤ k) : s.Finite := by
rw [← encard_lt_top_iff]; exact h.trans_lt (WithTop.coe_lt_top _)
theorem finite_of_encard_eq_coe {k : ℕ} (h : s.encard = k) : s.Finite :=
finite_of_encard_le_coe h.le
theorem encard_le_coe_iff {k : ℕ} : s.encard ≤ k ↔ s.Finite ∧ ∃ (n₀ : ℕ), s.encard = n₀ ∧ n₀ ≤ k :=
⟨fun h ↦ ⟨finite_of_encard_le_coe h, by rwa [ENat.le_coe_iff] at h⟩,
fun ⟨_,⟨n₀,hs, hle⟩⟩ ↦ by rwa [hs, Nat.cast_le]⟩
@[simp]
theorem encard_prod : (s ×ˢ t).encard = s.encard * t.encard := by
simp [Set.encard, ENat.card_congr (Equiv.Set.prod ..)]
section Lattice
theorem encard_le_encard (h : s ⊆ t) : s.encard ≤ t.encard := by
rw [← union_diff_cancel h, encard_union_eq disjoint_sdiff_right]; exact le_self_add
@[deprecated (since := "2025-01-05")] alias encard_le_card := encard_le_encard
theorem encard_mono {α : Type*} : Monotone (encard : Set α → ℕ∞) :=
fun _ _ ↦ encard_le_encard
theorem encard_diff_add_encard_of_subset (h : s ⊆ t) : (t \ s).encard + s.encard = t.encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self, union_eq_self_of_subset_right h]
@[simp] theorem one_le_encard_iff_nonempty : 1 ≤ s.encard ↔ s.Nonempty := by
rw [nonempty_iff_ne_empty, Ne, ← encard_eq_zero, ENat.one_le_iff_ne_zero]
theorem encard_diff_add_encard_inter (s t : Set α) :
(s \ t).encard + (s ∩ t).encard = s.encard := by
rw [← encard_union_eq (disjoint_of_subset_right inter_subset_right disjoint_sdiff_left),
diff_union_inter]
theorem encard_union_add_encard_inter (s t : Set α) :
(s ∪ t).encard + (s ∩ t).encard = s.encard + t.encard := by
rw [← diff_union_self, encard_union_eq disjoint_sdiff_left, add_right_comm,
encard_diff_add_encard_inter]
theorem encard_eq_encard_iff_encard_diff_eq_encard_diff (h : (s ∩ t).Finite) :
s.encard = t.encard ↔ (s \ t).encard = (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_right_inj h.encard_lt_top.ne]
theorem encard_le_encard_iff_encard_diff_le_encard_diff (h : (s ∩ t).Finite) :
s.encard ≤ t.encard ↔ (s \ t).encard ≤ (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_le_add_iff_right h.encard_lt_top.ne]
theorem encard_lt_encard_iff_encard_diff_lt_encard_diff (h : (s ∩ t).Finite) :
s.encard < t.encard ↔ (s \ t).encard < (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_lt_add_iff_right h.encard_lt_top.ne]
theorem encard_union_le (s t : Set α) : (s ∪ t).encard ≤ s.encard + t.encard := by
rw [← encard_union_add_encard_inter]; exact le_self_add
theorem finite_iff_finite_of_encard_eq_encard (h : s.encard = t.encard) : s.Finite ↔ t.Finite := by
rw [← encard_lt_top_iff, ← encard_lt_top_iff, h]
theorem infinite_iff_infinite_of_encard_eq_encard (h : s.encard = t.encard) :
s.Infinite ↔ t.Infinite := by rw [← encard_eq_top_iff, h, encard_eq_top_iff]
theorem Finite.finite_of_encard_le {s : Set α} {t : Set β} (hs : s.Finite)
(h : t.encard ≤ s.encard) : t.Finite :=
encard_lt_top_iff.1 (h.trans_lt hs.encard_lt_top)
lemma Finite.eq_of_subset_of_encard_le' (ht : t.Finite) (hst : s ⊆ t) (hts : t.encard ≤ s.encard) :
s = t := by
rw [← zero_add (a := encard s), ← encard_diff_add_encard_of_subset hst] at hts
have hdiff := WithTop.le_of_add_le_add_right (ht.subset hst).encard_lt_top.ne hts
rw [nonpos_iff_eq_zero, encard_eq_zero, diff_eq_empty] at hdiff
exact hst.antisymm hdiff
theorem Finite.eq_of_subset_of_encard_le (hs : s.Finite) (hst : s ⊆ t)
(hts : t.encard ≤ s.encard) : s = t :=
(hs.finite_of_encard_le hts).eq_of_subset_of_encard_le' hst hts
theorem Finite.encard_lt_encard (hs : s.Finite) (h : s ⊂ t) : s.encard < t.encard :=
(encard_mono h.subset).lt_of_ne fun he ↦ h.ne (hs.eq_of_subset_of_encard_le h.subset he.symm.le)
theorem encard_strictMono [Finite α] : StrictMono (encard : Set α → ℕ∞) :=
fun _ _ h ↦ (toFinite _).encard_lt_encard h
theorem encard_diff_add_encard (s t : Set α) : (s \ t).encard + t.encard = (s ∪ t).encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self]
theorem encard_le_encard_diff_add_encard (s t : Set α) : s.encard ≤ (s \ t).encard + t.encard :=
(encard_mono subset_union_left).trans_eq (encard_diff_add_encard _ _).symm
theorem tsub_encard_le_encard_diff (s t : Set α) : s.encard - t.encard ≤ (s \ t).encard := by
rw [tsub_le_iff_left, add_comm]; apply encard_le_encard_diff_add_encard
theorem encard_add_encard_compl (s : Set α) : s.encard + sᶜ.encard = (univ : Set α).encard := by
rw [← encard_union_eq disjoint_compl_right, union_compl_self]
end Lattice
section InsertErase
variable {a b : α}
theorem encard_insert_le (s : Set α) (x : α) : (insert x s).encard ≤ s.encard + 1 := by
rw [← union_singleton, ← encard_singleton x]; apply encard_union_le
theorem encard_singleton_inter (s : Set α) (x : α) : ({x} ∩ s).encard ≤ 1 := by
rw [← encard_singleton x]; exact encard_le_encard inter_subset_left
theorem encard_diff_singleton_add_one (h : a ∈ s) :
(s \ {a}).encard + 1 = s.encard := by
rw [← encard_insert_of_not_mem (fun h ↦ h.2 rfl), insert_diff_singleton, insert_eq_of_mem h]
theorem encard_diff_singleton_of_mem (h : a ∈ s) :
(s \ {a}).encard = s.encard - 1 := by
rw [← encard_diff_singleton_add_one h, ← WithTop.add_right_inj WithTop.one_ne_top,
tsub_add_cancel_of_le (self_le_add_left _ _)]
theorem encard_tsub_one_le_encard_diff_singleton (s : Set α) (x : α) :
s.encard - 1 ≤ (s \ {x}).encard := by
rw [← encard_singleton x]; apply tsub_encard_le_encard_diff
theorem encard_exchange (ha : a ∉ s) (hb : b ∈ s) : (insert a (s \ {b})).encard = s.encard := by
rw [encard_insert_of_not_mem, encard_diff_singleton_add_one hb]
simp_all only [not_true, mem_diff, mem_singleton_iff, false_and, not_false_eq_true]
theorem encard_exchange' (ha : a ∉ s) (hb : b ∈ s) : (insert a s \ {b}).encard = s.encard := by
rw [← insert_diff_singleton_comm (by rintro rfl; exact ha hb), encard_exchange ha hb]
theorem encard_eq_add_one_iff {k : ℕ∞} :
s.encard = k + 1 ↔ (∃ a t, ¬a ∈ t ∧ insert a t = s ∧ t.encard = k) := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, ha⟩ := nonempty_of_encard_ne_zero (s := s) (by simp [h])
refine ⟨a, s \ {a}, fun h ↦ h.2 rfl, by rwa [insert_diff_singleton, insert_eq_of_mem], ?_⟩
rw [← WithTop.add_right_inj WithTop.one_ne_top, ← h,
encard_diff_singleton_add_one ha]
rintro ⟨a, t, h, rfl, rfl⟩
rw [encard_insert_of_not_mem h]
/-- Every set is either empty, infinite, or can have its `encard` reduced by a removal. Intended
for well-founded induction on the value of `encard`. -/
theorem eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt (s : Set α) :
s = ∅ ∨ s.encard = ⊤ ∨ ∃ a ∈ s, (s \ {a}).encard < s.encard := by
refine s.eq_empty_or_nonempty.elim Or.inl (Or.inr ∘ fun ⟨a,ha⟩ ↦
(s.finite_or_infinite.elim (fun hfin ↦ Or.inr ⟨a, ha, ?_⟩) (Or.inl ∘ Infinite.encard_eq)))
rw [← encard_diff_singleton_add_one ha]; nth_rw 1 [← add_zero (encard _)]
exact WithTop.add_lt_add_left hfin.diff.encard_lt_top.ne zero_lt_one
end InsertErase
section SmallSets
theorem encard_pair {x y : α} (hne : x ≠ y) : ({x, y} : Set α).encard = 2 := by
rw [encard_insert_of_not_mem (by simpa), ← one_add_one_eq_two,
WithTop.add_right_inj WithTop.one_ne_top, encard_singleton]
theorem encard_eq_one : s.encard = 1 ↔ ∃ x, s = {x} := by
refine ⟨fun h ↦ ?_, fun ⟨x, hx⟩ ↦ by rw [hx, encard_singleton]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
exact ⟨x, ((finite_singleton x).eq_of_subset_of_encard_le (by simpa) (by simp [h])).symm⟩
theorem encard_le_one_iff_eq : s.encard ≤ 1 ↔ s = ∅ ∨ ∃ x, s = {x} := by
rw [le_iff_lt_or_eq, lt_iff_not_le, ENat.one_le_iff_ne_zero, not_not, encard_eq_zero,
encard_eq_one]
theorem encard_le_one_iff : s.encard ≤ 1 ↔ ∀ a b, a ∈ s → b ∈ s → a = b := by
rw [encard_le_one_iff_eq, or_iff_not_imp_left, ← Ne, ← nonempty_iff_ne_empty]
refine ⟨fun h a b has hbs ↦ ?_,
fun h ⟨x, hx⟩ ↦ ⟨x, ((singleton_subset_iff.2 hx).antisymm' (fun y hy ↦ h _ _ hy hx))⟩⟩
obtain ⟨x, rfl⟩ := h ⟨_, has⟩
rw [(has : a = x), (hbs : b = x)]
theorem encard_le_one_iff_subsingleton : s.encard ≤ 1 ↔ s.Subsingleton := by
rw [encard_le_one_iff, Set.Subsingleton]
tauto
theorem one_lt_encard_iff_nontrivial : 1 < s.encard ↔ s.Nontrivial := by
rw [← not_iff_not, not_lt, Set.not_nontrivial_iff, ← encard_le_one_iff_subsingleton]
theorem one_lt_encard_iff : 1 < s.encard ↔ ∃ a b, a ∈ s ∧ b ∈ s ∧ a ≠ b := by
rw [← not_iff_not, not_exists, not_lt, encard_le_one_iff]; aesop
theorem exists_ne_of_one_lt_encard (h : 1 < s.encard) (a : α) : ∃ b ∈ s, b ≠ a := by
by_contra! h'
obtain ⟨b, b', hb, hb', hne⟩ := one_lt_encard_iff.1 h
apply hne
rw [h' b hb, h' b' hb']
theorem encard_eq_two : s.encard = 2 ↔ ∃ x y, x ≠ y ∧ s = {x, y} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, hne, hs⟩ ↦ by rw [hs, encard_pair hne]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton, encard_insert_of_not_mem (fun h ↦ h.2 rfl),
← one_add_one_eq_two, WithTop.add_right_inj (WithTop.one_ne_top), encard_eq_one] at h
obtain ⟨y, h⟩ := h
refine ⟨x, y, by rintro rfl; exact (h.symm.subset rfl).2 rfl, ?_⟩
rw [← h, insert_diff_singleton, insert_eq_of_mem hx]
theorem encard_eq_three {α : Type u_1} {s : Set α} :
encard s = 3 ↔ ∃ x y z, x ≠ y ∧ x ≠ z ∧ y ≠ z ∧ s = {x, y, z} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, z, hxy, hyz, hxz, hs⟩ ↦ ?_⟩
· obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton,
encard_insert_of_not_mem (fun h ↦ h.2 rfl), (by exact rfl : (3 : ℕ∞) = 2 + 1),
WithTop.add_right_inj WithTop.one_ne_top, encard_eq_two] at h
obtain ⟨y, z, hne, hs⟩ := h
refine ⟨x, y, z, ?_, ?_, hne, ?_⟩
· rintro rfl; exact (hs.symm.subset (Or.inl rfl)).2 rfl
· rintro rfl; exact (hs.symm.subset (Or.inr rfl)).2 rfl
rw [← hs, insert_diff_singleton, insert_eq_of_mem hx]
rw [hs, encard_insert_of_not_mem, encard_insert_of_not_mem, encard_singleton] <;> aesop
theorem Nat.encard_range (k : ℕ) : {i | i < k}.encard = k := by
convert encard_coe_eq_coe_finsetCard (Finset.range k) using 1
· rw [Finset.coe_range, Iio_def]
rw [Finset.card_range]
end SmallSets
theorem Finite.eq_insert_of_subset_of_encard_eq_succ (hs : s.Finite) (h : s ⊆ t)
(hst : t.encard = s.encard + 1) : ∃ a, t = insert a s := by
rw [← encard_diff_add_encard_of_subset h, add_comm, WithTop.add_left_inj hs.encard_lt_top.ne,
encard_eq_one] at hst
obtain ⟨x, hx⟩ := hst; use x; rw [← diff_union_of_subset h, hx, singleton_union]
theorem exists_subset_encard_eq {k : ℕ∞} (hk : k ≤ s.encard) : ∃ t, t ⊆ s ∧ t.encard = k := by
revert hk
refine ENat.nat_induction k (fun _ ↦ ⟨∅, empty_subset _, by simp⟩) (fun n IH hle ↦ ?_) ?_
· obtain ⟨t₀, ht₀s, ht₀⟩ := IH (le_trans (by simp) hle)
simp only [Nat.cast_succ] at *
have hne : t₀ ≠ s := by
rintro rfl; rw [ht₀, ← Nat.cast_one, ← Nat.cast_add, Nat.cast_le] at hle; simp at hle
obtain ⟨x, hx⟩ := exists_of_ssubset (ht₀s.ssubset_of_ne hne)
exact ⟨insert x t₀, insert_subset hx.1 ht₀s, by rw [encard_insert_of_not_mem hx.2, ht₀]⟩
simp only [top_le_iff, encard_eq_top_iff]
exact fun _ hi ↦ ⟨s, Subset.rfl, hi⟩
theorem exists_superset_subset_encard_eq {k : ℕ∞}
(hst : s ⊆ t) (hsk : s.encard ≤ k) (hkt : k ≤ t.encard) :
∃ r, s ⊆ r ∧ r ⊆ t ∧ r.encard = k := by
obtain (hs | hs) := eq_or_ne s.encard ⊤
· rw [hs, top_le_iff] at hsk; subst hsk; exact ⟨s, Subset.rfl, hst, hs⟩
obtain ⟨k, rfl⟩ := exists_add_of_le hsk
obtain ⟨k', hk'⟩ := exists_add_of_le hkt
| have hk : k ≤ encard (t \ s) := by
rw [← encard_diff_add_encard_of_subset hst, add_comm] at hkt
exact WithTop.le_of_add_le_add_right hs hkt
| Mathlib/Data/Set/Card.lean | 391 | 393 |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Yaël Dillies
-/
import Mathlib.Order.Cover
import Mathlib.Order.Interval.Finset.Defs
/-!
# Intervals as finsets
This file provides basic results about all the `Finset.Ixx`, which are defined in
`Order.Interval.Finset.Defs`.
In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of,
respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly
functions whose domain is a locally finite order. In particular, this file proves:
* `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿`
* `lt_iff_transGen_covBy`: `<` is the transitive closure of `⋖`
* `monotone_iff_forall_wcovBy`: Characterization of monotone functions
* `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions
## TODO
This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to
generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general,
what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure.
Complete the API. See
https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235
for some ideas.
-/
assert_not_exists MonoidWithZero Finset.sum
open Function OrderDual
open FinsetInterval
variable {ι α : Type*} {a a₁ a₂ b b₁ b₂ c x : α}
namespace Finset
section Preorder
variable [Preorder α]
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by
rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Icc_of_le⟩ := nonempty_Icc
@[simp]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ico_of_lt⟩ := nonempty_Ico
@[simp]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioc_of_lt⟩ := nonempty_Ioc
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo]
@[simp]
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff]
@[simp]
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff]
@[simp]
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff]
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff]
alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff
alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff
alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2)
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and, le_rfl]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and, le_refl]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true, le_rfl]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true, le_rfl]
theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1
theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1
theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2
theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2
@[gcongr]
theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by
simpa [← coe_subset] using Set.Icc_subset_Icc ha hb
@[gcongr]
theorem Ico_subset_Ico (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := by
simpa [← coe_subset] using Set.Ico_subset_Ico ha hb
@[gcongr]
theorem Ioc_subset_Ioc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := by
simpa [← coe_subset] using Set.Ioc_subset_Ioc ha hb
@[gcongr]
theorem Ioo_subset_Ioo (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := by
simpa [← coe_subset] using Set.Ioo_subset_Ioo ha hb
@[gcongr]
theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b :=
Icc_subset_Icc h le_rfl
@[gcongr]
theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b :=
Ico_subset_Ico h le_rfl
@[gcongr]
theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b :=
Ioc_subset_Ioc h le_rfl
@[gcongr]
theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b :=
Ioo_subset_Ioo h le_rfl
@[gcongr]
theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ :=
Icc_subset_Icc le_rfl h
@[gcongr]
theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ :=
Ico_subset_Ico le_rfl h
@[gcongr]
theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ :=
Ioc_subset_Ioc le_rfl h
@[gcongr]
theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ :=
Ioo_subset_Ioo le_rfl h
theorem Ico_subset_Ioo_left (h : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := by
rw [← coe_subset, coe_Ico, coe_Ioo]
exact Set.Ico_subset_Ioo_left h
theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := by
rw [← coe_subset, coe_Ioc, coe_Ioo]
exact Set.Ioc_subset_Ioo_right h
theorem Icc_subset_Ico_right (h : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico]
exact Set.Icc_subset_Ico_right h
theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := by
rw [← coe_subset, coe_Ioo, coe_Ico]
exact Set.Ioo_subset_Ico_self
theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := by
rw [← coe_subset, coe_Ioo, coe_Ioc]
exact Set.Ioo_subset_Ioc_self
theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ico, coe_Icc]
exact Set.Ico_subset_Icc_self
theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ioc, coe_Icc]
exact Set.Ioc_subset_Icc_self
theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b :=
Ioo_subset_Ico_self.trans Ico_subset_Icc_self
theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by
rw [← coe_subset, coe_Icc, coe_Icc, Set.Icc_subset_Icc_iff h₁]
theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ioo, Set.Icc_subset_Ioo_iff h₁]
theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico, Set.Icc_subset_Ico_iff h₁]
theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ :=
(Icc_subset_Ico_iff h₁.dual).trans and_comm
--TODO: `Ico_subset_Ioo_iff`, `Ioc_subset_Ioo_iff`
theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_left hI ha hb
theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_right hI ha hb
@[simp]
theorem Ioc_disjoint_Ioc_of_le {d : α} (hbc : b ≤ c) : Disjoint (Ioc a b) (Ioc c d) :=
disjoint_left.2 fun _ h1 h2 ↦ not_and_of_not_left _
((mem_Ioc.1 h1).2.trans hbc).not_lt (mem_Ioc.1 h2)
variable (a)
theorem Ico_self : Ico a a = ∅ :=
Ico_eq_empty <| lt_irrefl _
theorem Ioc_self : Ioc a a = ∅ :=
Ioc_eq_empty <| lt_irrefl _
theorem Ioo_self : Ioo a a = ∅ :=
Ioo_eq_empty <| lt_irrefl _
variable {a}
/-- A set with upper and lower bounds in a locally finite order is a fintype -/
def _root_.Set.fintypeOfMemBounds {s : Set α} [DecidablePred (· ∈ s)] (ha : a ∈ lowerBounds s)
(hb : b ∈ upperBounds s) : Fintype s :=
Set.fintypeSubset (Set.Icc a b) fun _ hx => ⟨ha hx, hb hx⟩
section Filter
theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) :
{x ∈ Ico a b | x < c} = ∅ :=
filter_false_of_mem fun _ hx => (hca.trans (mem_Ico.1 hx).1).not_lt
theorem Ico_filter_lt_of_right_le [DecidablePred (· < c)] (hbc : b ≤ c) :
{x ∈ Ico a b | x < c} = Ico a b :=
filter_true_of_mem fun _ hx => (mem_Ico.1 hx).2.trans_le hbc
theorem Ico_filter_lt_of_le_right [DecidablePred (· < c)] (hcb : c ≤ b) :
{x ∈ Ico a b | x < c} = Ico a c := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_right_comm]
exact and_iff_left_of_imp fun h => h.2.trans_le hcb
theorem Ico_filter_le_of_le_left {a b c : α} [DecidablePred (c ≤ ·)] (hca : c ≤ a) :
{x ∈ Ico a b | c ≤ x} = Ico a b :=
filter_true_of_mem fun _ hx => hca.trans (mem_Ico.1 hx).1
theorem Ico_filter_le_of_right_le {a b : α} [DecidablePred (b ≤ ·)] :
{x ∈ Ico a b | b ≤ x} = ∅ :=
filter_false_of_mem fun _ hx => (mem_Ico.1 hx).2.not_le
theorem Ico_filter_le_of_left_le {a b c : α} [DecidablePred (c ≤ ·)] (hac : a ≤ c) :
{x ∈ Ico a b | c ≤ x} = Ico c b := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_comm, and_left_comm]
exact and_iff_right_of_imp fun h => hac.trans h.1
theorem Icc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
{x ∈ Icc a b | x < c} = Icc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Icc.1 hx).2 h
theorem Ioc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
{x ∈ Ioc a b | x < c} = Ioc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Ioc.1 hx).2 h
theorem Iic_filter_lt_of_lt_right {α} [Preorder α] [LocallyFiniteOrderBot α] {a c : α}
[DecidablePred (· < c)] (h : a < c) : {x ∈ Iic a | x < c} = Iic a :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Iic.1 hx) h
variable (a b) [Fintype α]
theorem filter_lt_lt_eq_Ioo [DecidablePred fun j => a < j ∧ j < b] :
({j | a < j ∧ j < b} : Finset _) = Ioo a b := by ext; simp
theorem filter_lt_le_eq_Ioc [DecidablePred fun j => a < j ∧ j ≤ b] :
({j | a < j ∧ j ≤ b} : Finset _) = Ioc a b := by ext; simp
theorem filter_le_lt_eq_Ico [DecidablePred fun j => a ≤ j ∧ j < b] :
({j | a ≤ j ∧ j < b} : Finset _) = Ico a b := by ext; simp
theorem filter_le_le_eq_Icc [DecidablePred fun j => a ≤ j ∧ j ≤ b] :
({j | a ≤ j ∧ j ≤ b} : Finset _) = Icc a b := by ext; simp
end Filter
end LocallyFiniteOrder
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α]
@[simp]
theorem Ioi_eq_empty : Ioi a = ∅ ↔ IsMax a := by
rw [← coe_eq_empty, coe_Ioi, Set.Ioi_eq_empty_iff]
@[simp] alias ⟨_, _root_.IsMax.finsetIoi_eq⟩ := Ioi_eq_empty
@[simp] lemma Ioi_nonempty : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [nonempty_iff_ne_empty]
theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ∅ := Ioi_eq_empty.mpr isMax_top
@[simp]
theorem Ici_bot [OrderBot α] [Fintype α] : Ici (⊥ : α) = univ := by
ext a; simp only [mem_Ici, bot_le, mem_univ]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Ici : (Ici a).Nonempty := ⟨a, mem_Ici.2 le_rfl⟩
lemma nonempty_Ioi : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioi_of_not_isMax⟩ := nonempty_Ioi
@[simp]
theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a := by
simp [← coe_subset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Ici_subset_Ici⟩ := Ici_subset_Ici
@[simp]
theorem Ici_ssubset_Ici : Ici a ⊂ Ici b ↔ b < a := by
simp [← coe_ssubset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Ici_ssubset_Ici⟩ := Ici_ssubset_Ici
@[gcongr]
theorem Ioi_subset_Ioi (h : a ≤ b) : Ioi b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioi_subset_Ioi h
@[gcongr]
theorem Ioi_ssubset_Ioi (h : a < b) : Ioi b ⊂ Ioi a := by
simpa [← coe_ssubset] using Set.Ioi_ssubset_Ioi h
variable [LocallyFiniteOrder α]
theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Icc_subset_Ici_self
theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Ico_subset_Ici_self
theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioc_subset_Ioi_self
theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioo_subset_Ioi_self
theorem Ioc_subset_Ici_self : Ioc a b ⊆ Ici a :=
Ioc_subset_Icc_self.trans Icc_subset_Ici_self
theorem Ioo_subset_Ici_self : Ioo a b ⊆ Ici a :=
Ioo_subset_Ico_self.trans Ico_subset_Ici_self
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α]
@[simp]
theorem Iio_eq_empty : Iio a = ∅ ↔ IsMin a := Ioi_eq_empty (α := αᵒᵈ)
@[simp] alias ⟨_, _root_.IsMin.finsetIio_eq⟩ := Iio_eq_empty
@[simp] lemma Iio_nonempty : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [nonempty_iff_ne_empty]
theorem Iio_bot [OrderBot α] : Iio (⊥ : α) = ∅ := Iio_eq_empty.mpr isMin_bot
@[simp]
theorem Iic_top [OrderTop α] [Fintype α] : Iic (⊤ : α) = univ := by
ext a; simp only [mem_Iic, le_top, mem_univ]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Iic : (Iic a).Nonempty := ⟨a, mem_Iic.2 le_rfl⟩
lemma nonempty_Iio : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Iio_of_not_isMin⟩ := nonempty_Iio
@[simp]
theorem Iic_subset_Iic : Iic a ⊆ Iic b ↔ a ≤ b := by
simp [← coe_subset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Iic_subset_Iic⟩ := Iic_subset_Iic
@[simp]
theorem Iic_ssubset_Iic : Iic a ⊂ Iic b ↔ a < b := by
simp [← coe_ssubset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Iic_ssubset_Iic⟩ := Iic_ssubset_Iic
@[gcongr]
theorem Iio_subset_Iio (h : a ≤ b) : Iio a ⊆ Iio b := by
simpa [← coe_subset] using Set.Iio_subset_Iio h
@[gcongr]
theorem Iio_ssubset_Iio (h : a < b) : Iio a ⊂ Iio b := by
simpa [← coe_ssubset] using Set.Iio_ssubset_Iio h
variable [LocallyFiniteOrder α]
theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Icc_subset_Iic_self
theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Ioc_subset_Iic_self
theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ico_subset_Iio_self
theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ioo_subset_Iio_self
theorem Ico_subset_Iic_self : Ico a b ⊆ Iic b :=
Ico_subset_Icc_self.trans Icc_subset_Iic_self
theorem Ioo_subset_Iic_self : Ioo a b ⊆ Iic b :=
Ioo_subset_Ioc_self.trans Ioc_subset_Iic_self
theorem Iic_disjoint_Ioc (h : a ≤ b) : Disjoint (Iic a) (Ioc b c) :=
disjoint_left.2 fun _ hax hbcx ↦ (mem_Iic.1 hax).not_lt <| lt_of_le_of_lt h (mem_Ioc.1 hbcx).1
/-- An equivalence between `Finset.Iic a` and `Set.Iic a`. -/
def _root_.Equiv.IicFinsetSet (a : α) : Iic a ≃ Set.Iic a where
toFun b := ⟨b.1, coe_Iic a ▸ mem_coe.2 b.2⟩
invFun b := ⟨b.1, by rw [← mem_coe, coe_Iic a]; exact b.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end LocallyFiniteOrderBot
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α] {a : α}
theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := by
simpa [← coe_subset] using Set.Ioi_subset_Ici_self
theorem _root_.BddBelow.finite {s : Set α} (hs : BddBelow s) : s.Finite :=
let ⟨a, ha⟩ := hs
(Ici a).finite_toSet.subset fun _ hx => mem_Ici.2 <| ha hx
theorem _root_.Set.Infinite.not_bddBelow {s : Set α} : s.Infinite → ¬BddBelow s :=
mt BddBelow.finite
variable [Fintype α]
theorem filter_lt_eq_Ioi [DecidablePred (a < ·)] : ({x | a < x} : Finset _) = Ioi a := by ext; simp
theorem filter_le_eq_Ici [DecidablePred (a ≤ ·)] : ({x | a ≤ x} : Finset _) = Ici a := by ext; simp
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α] {a : α}
theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := by
simpa [← coe_subset] using Set.Iio_subset_Iic_self
theorem _root_.BddAbove.finite {s : Set α} (hs : BddAbove s) : s.Finite :=
hs.dual.finite
theorem _root_.Set.Infinite.not_bddAbove {s : Set α} : s.Infinite → ¬BddAbove s :=
mt BddAbove.finite
variable [Fintype α]
theorem filter_gt_eq_Iio [DecidablePred (· < a)] : ({x | x < a} : Finset _) = Iio a := by ext; simp
theorem filter_ge_eq_Iic [DecidablePred (· ≤ a)] : ({x | x ≤ a} : Finset _) = Iic a := by ext; simp
end LocallyFiniteOrderBot
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem Icc_bot [OrderBot α] : Icc (⊥ : α) a = Iic a := rfl
@[simp]
theorem Icc_top [OrderTop α] : Icc a (⊤ : α) = Ici a := rfl
@[simp]
theorem Ico_bot [OrderBot α] : Ico (⊥ : α) a = Iio a := rfl
@[simp]
theorem Ioc_top [OrderTop α] : Ioc a (⊤ : α) = Ioi a := rfl
theorem Icc_bot_top [BoundedOrder α] [Fintype α] : Icc (⊥ : α) (⊤ : α) = univ := by
rw [Icc_bot, Iic_top]
end LocallyFiniteOrder
variable [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α]
theorem disjoint_Ioi_Iio (a : α) : Disjoint (Ioi a) (Iio a) :=
disjoint_left.2 fun _ hab hba => (mem_Ioi.1 hab).not_lt <| mem_Iio.1 hba
end Preorder
section PartialOrder
variable [PartialOrder α] [LocallyFiniteOrder α] {a b c : α}
@[simp]
theorem Icc_self (a : α) : Icc a a = {a} := by rw [← coe_eq_singleton, coe_Icc, Set.Icc_self]
@[simp]
theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by
rw [← coe_eq_singleton, coe_Icc, Set.Icc_eq_singleton_iff]
theorem Ico_disjoint_Ico_consecutive (a b c : α) : Disjoint (Ico a b) (Ico b c) :=
disjoint_left.2 fun _ hab hbc => (mem_Ico.mp hab).2.not_le (mem_Ico.mp hbc).1
@[simp]
theorem Ici_top [OrderTop α] : Ici (⊤ : α) = {⊤} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩
@[simp]
theorem Iic_bot [OrderBot α] : Iic (⊥ : α) = {⊥} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩
section DecidableEq
| Mathlib/Order/Interval/Finset/Basic.lean | 560 | 560 | |
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Patrick Massot
-/
import Mathlib.Topology.Neighborhoods
/-!
# Neighborhoods of a set
In this file we define the filter `𝓝ˢ s` or `nhdsSet s` consisting of all neighborhoods of a set
`s`.
## Main Properties
There are a couple different notions equivalent to `s ∈ 𝓝ˢ t`:
* `s ⊆ interior t` using `subset_interior_iff_mem_nhdsSet`
* `∀ x : X, x ∈ t → s ∈ 𝓝 x` using `mem_nhdsSet_iff_forall`
* `∃ U : Set X, IsOpen U ∧ t ⊆ U ∧ U ⊆ s` using `mem_nhdsSet_iff_exists`
Furthermore, we have the following results:
* `monotone_nhdsSet`: `𝓝ˢ` is monotone
* In T₁-spaces, `𝓝ˢ`is strictly monotone and hence injective:
`strict_mono_nhdsSet`/`injective_nhdsSet`. These results are in `Mathlib.Topology.Separation`.
-/
open Set Filter Topology
variable {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {f : Filter X}
{s t s₁ s₂ t₁ t₂ : Set X} {x : X}
theorem nhdsSet_diagonal (X) [TopologicalSpace (X × X)] :
𝓝ˢ (diagonal X) = ⨆ (x : X), 𝓝 (x, x) := by
rw [nhdsSet, ← range_diag, ← range_comp]
rfl
theorem mem_nhdsSet_iff_forall : s ∈ 𝓝ˢ t ↔ ∀ x : X, x ∈ t → s ∈ 𝓝 x := by
simp_rw [nhdsSet, Filter.mem_sSup, forall_mem_image]
lemma nhdsSet_le : 𝓝ˢ s ≤ f ↔ ∀ x ∈ s, 𝓝 x ≤ f := by simp [nhdsSet]
theorem bUnion_mem_nhdsSet {t : X → Set X} (h : ∀ x ∈ s, t x ∈ 𝓝 x) : (⋃ x ∈ s, t x) ∈ 𝓝ˢ s :=
mem_nhdsSet_iff_forall.2 fun x hx => mem_of_superset (h x hx) <|
subset_iUnion₂ (s := fun x _ => t x) x hx
theorem subset_interior_iff_mem_nhdsSet : s ⊆ interior t ↔ t ∈ 𝓝ˢ s := by
simp_rw [mem_nhdsSet_iff_forall, subset_interior_iff_nhds]
theorem disjoint_principal_nhdsSet : Disjoint (𝓟 s) (𝓝ˢ t) ↔ Disjoint (closure s) t := by
rw [disjoint_principal_left, ← subset_interior_iff_mem_nhdsSet, interior_compl,
subset_compl_iff_disjoint_left]
theorem disjoint_nhdsSet_principal : Disjoint (𝓝ˢ s) (𝓟 t) ↔ Disjoint s (closure t) := by
rw [disjoint_comm, disjoint_principal_nhdsSet, disjoint_comm]
theorem mem_nhdsSet_iff_exists : s ∈ 𝓝ˢ t ↔ ∃ U : Set X, IsOpen U ∧ t ⊆ U ∧ U ⊆ s := by
rw [← subset_interior_iff_mem_nhdsSet, subset_interior_iff]
/-- A proposition is true on a set neighborhood of `s` iff it is true on a larger open set -/
theorem eventually_nhdsSet_iff_exists {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ s, p x) ↔ ∃ t, IsOpen t ∧ s ⊆ t ∧ ∀ x, x ∈ t → p x :=
mem_nhdsSet_iff_exists
/-- A proposition is true on a set neighborhood of `s`
iff it is eventually true near each point in the set. -/
theorem eventually_nhdsSet_iff_forall {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ s, p x) ↔ ∀ x, x ∈ s → ∀ᶠ y in 𝓝 x, p y :=
mem_nhdsSet_iff_forall
theorem hasBasis_nhdsSet (s : Set X) : (𝓝ˢ s).HasBasis (fun U => IsOpen U ∧ s ⊆ U) fun U => U :=
⟨fun t => by simp [mem_nhdsSet_iff_exists, and_assoc]⟩
@[simp]
lemma lift'_nhdsSet_interior (s : Set X) : (𝓝ˢ s).lift' interior = 𝓝ˢ s :=
(hasBasis_nhdsSet s).lift'_interior_eq_self fun _ ↦ And.left
lemma Filter.HasBasis.nhdsSet_interior {ι : Sort*} {p : ι → Prop} {s : ι → Set X} {t : Set X}
(h : (𝓝ˢ t).HasBasis p s) : (𝓝ˢ t).HasBasis p (interior <| s ·) :=
lift'_nhdsSet_interior t ▸ h.lift'_interior
theorem IsOpen.mem_nhdsSet (hU : IsOpen s) : s ∈ 𝓝ˢ t ↔ t ⊆ s := by
rw [← subset_interior_iff_mem_nhdsSet, hU.interior_eq]
/-- An open set belongs to its own set neighborhoods filter. -/
theorem IsOpen.mem_nhdsSet_self (ho : IsOpen s) : s ∈ 𝓝ˢ s := ho.mem_nhdsSet.mpr Subset.rfl
theorem principal_le_nhdsSet : 𝓟 s ≤ 𝓝ˢ s := fun _s hs =>
(subset_interior_iff_mem_nhdsSet.mpr hs).trans interior_subset
theorem subset_of_mem_nhdsSet (h : t ∈ 𝓝ˢ s) : s ⊆ t := principal_le_nhdsSet h
theorem Filter.Eventually.self_of_nhdsSet {p : X → Prop} (h : ∀ᶠ x in 𝓝ˢ s, p x) : ∀ x ∈ s, p x :=
principal_le_nhdsSet h
nonrec theorem Filter.EventuallyEq.self_of_nhdsSet {Y} {f g : X → Y} (h : f =ᶠ[𝓝ˢ s] g) :
EqOn f g s :=
h.self_of_nhdsSet
@[simp]
theorem nhdsSet_eq_principal_iff : 𝓝ˢ s = 𝓟 s ↔ IsOpen s := by
rw [← principal_le_nhdsSet.le_iff_eq, le_principal_iff, mem_nhdsSet_iff_forall,
isOpen_iff_mem_nhds]
alias ⟨_, IsOpen.nhdsSet_eq⟩ := nhdsSet_eq_principal_iff
@[simp]
theorem nhdsSet_interior : 𝓝ˢ (interior s) = 𝓟 (interior s) :=
isOpen_interior.nhdsSet_eq
@[simp]
theorem nhdsSet_singleton : 𝓝ˢ {x} = 𝓝 x := by simp [nhdsSet]
theorem mem_nhdsSet_interior : s ∈ 𝓝ˢ (interior s) :=
subset_interior_iff_mem_nhdsSet.mp Subset.rfl
@[simp]
theorem nhdsSet_empty : 𝓝ˢ (∅ : Set X) = ⊥ := by rw [isOpen_empty.nhdsSet_eq, principal_empty]
theorem mem_nhdsSet_empty : s ∈ 𝓝ˢ (∅ : Set X) := by simp
@[simp]
theorem nhdsSet_univ : 𝓝ˢ (univ : Set X) = ⊤ := by rw [isOpen_univ.nhdsSet_eq, principal_univ]
@[gcongr, mono]
theorem nhdsSet_mono (h : s ⊆ t) : 𝓝ˢ s ≤ 𝓝ˢ t :=
sSup_le_sSup <| image_subset _ h
theorem monotone_nhdsSet : Monotone (𝓝ˢ : Set X → Filter X) := fun _ _ => nhdsSet_mono
theorem nhds_le_nhdsSet (h : x ∈ s) : 𝓝 x ≤ 𝓝ˢ s :=
le_sSup <| mem_image_of_mem _ h
@[simp]
theorem nhdsSet_union (s t : Set X) : 𝓝ˢ (s ∪ t) = 𝓝ˢ s ⊔ 𝓝ˢ t := by
simp only [nhdsSet, image_union, sSup_union]
theorem union_mem_nhdsSet (h₁ : s₁ ∈ 𝓝ˢ t₁) (h₂ : s₂ ∈ 𝓝ˢ t₂) : s₁ ∪ s₂ ∈ 𝓝ˢ (t₁ ∪ t₂) := by
rw [nhdsSet_union]
exact union_mem_sup h₁ h₂
@[simp]
theorem nhdsSet_insert (x : X) (s : Set X) : 𝓝ˢ (insert x s) = 𝓝 x ⊔ 𝓝ˢ s := by
rw [insert_eq, nhdsSet_union, nhdsSet_singleton]
/- This inequality cannot be improved to an equality. For instance,
if `X` has two elements and the coarse topology and `s` and `t` are distinct singletons then
`𝓝ˢ (s ∩ t) = ⊥` while `𝓝ˢ s ⊓ 𝓝ˢ t = ⊤` and those are different. -/
theorem nhdsSet_inter_le (s t : Set X) : 𝓝ˢ (s ∩ t) ≤ 𝓝ˢ s ⊓ 𝓝ˢ t :=
(monotone_nhdsSet (X := X)).map_inf_le s t
theorem nhdsSet_iInter_le {ι : Sort*} (s : ι → Set X) : 𝓝ˢ (⋂ i, s i) ≤ ⨅ i, 𝓝ˢ (s i) :=
(monotone_nhdsSet (X := X)).map_iInf_le
theorem nhdsSet_sInter_le (s : Set (Set X)) : 𝓝ˢ (⋂₀ s) ≤ ⨅ x ∈ s, 𝓝ˢ x :=
(monotone_nhdsSet (X := X)).map_sInf_le
variable (s) in
theorem IsClosed.nhdsSet_le_sup (h : IsClosed t) : 𝓝ˢ s ≤ 𝓝ˢ (s ∩ t) ⊔ 𝓟 (tᶜ) :=
calc
𝓝ˢ s = 𝓝ˢ (s ∩ t ∪ s ∩ tᶜ) := by rw [Set.inter_union_compl s t]
_ = 𝓝ˢ (s ∩ t) ⊔ 𝓝ˢ (s ∩ tᶜ) := by rw [nhdsSet_union]
_ ≤ 𝓝ˢ (s ∩ t) ⊔ 𝓝ˢ (tᶜ) := sup_le_sup_left (monotone_nhdsSet inter_subset_right) _
_ = 𝓝ˢ (s ∩ t) ⊔ 𝓟 (tᶜ) := by rw [h.isOpen_compl.nhdsSet_eq]
variable (s) in
theorem IsClosed.nhdsSet_le_sup' (h : IsClosed t) :
𝓝ˢ s ≤ 𝓝ˢ (t ∩ s) ⊔ 𝓟 (tᶜ) := by rw [Set.inter_comm]; exact h.nhdsSet_le_sup s
theorem Filter.Eventually.eventually_nhdsSet {p : X → Prop} (h : ∀ᶠ y in 𝓝ˢ s, p y) :
∀ᶠ y in 𝓝ˢ s, ∀ᶠ x in 𝓝 y, p x :=
eventually_nhdsSet_iff_forall.mpr fun x x_in ↦
(eventually_nhdsSet_iff_forall.mp h x x_in).eventually_nhds
theorem Filter.Eventually.union_nhdsSet {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ (s ∪ t), p x) ↔ (∀ᶠ x in 𝓝ˢ s, p x) ∧ ∀ᶠ x in 𝓝ˢ t, p x := by
rw [nhdsSet_union, eventually_sup]
theorem Filter.Eventually.union {p : X → Prop} (hs : ∀ᶠ x in 𝓝ˢ s, p x) (ht : ∀ᶠ x in 𝓝ˢ t, p x) :
∀ᶠ x in 𝓝ˢ (s ∪ t), p x :=
Filter.Eventually.union_nhdsSet.mpr ⟨hs, ht⟩
theorem nhdsSet_iUnion {ι : Sort*} (s : ι → Set X) : 𝓝ˢ (⋃ i, s i) = ⨆ i, 𝓝ˢ (s i) := by
simp only [nhdsSet, image_iUnion, sSup_iUnion (β := Filter X)]
theorem eventually_nhdsSet_iUnion₂ {ι : Sort*} {p : ι → Prop} {s : ι → Set X} {P : X → Prop} :
(∀ᶠ x in 𝓝ˢ (⋃ (i) (_ : p i), s i), P x) ↔ ∀ i, p i → ∀ᶠ x in 𝓝ˢ (s i), P x := by
simp only [nhdsSet_iUnion, eventually_iSup]
theorem eventually_nhdsSet_iUnion {ι : Sort*} {s : ι → Set X} {P : X → Prop} :
(∀ᶠ x in 𝓝ˢ (⋃ i, s i), P x) ↔ ∀ i, ∀ᶠ x in 𝓝ˢ (s i), P x := by
simp only [nhdsSet_iUnion, eventually_iSup]
| Mathlib/Topology/NhdsSet.lean | 220 | 222 | |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot, Yury Kudryashov, Rémy Degenne
-/
import Mathlib.Data.Set.Subsingleton
import Mathlib.Order.Interval.Set.Defs
/-!
# Intervals
In any preorder, we define intervals (which on each side can be either infinite, open or closed)
using the following naming conventions:
- `i`: infinite
- `o`: open
- `c`: closed
Each interval has the name `I` + letter for left side + letter for right side.
For instance, `Ioc a b` denotes the interval `(a, b]`.
The definitions can be found in `Mathlib.Order.Interval.Set.Defs`.
This file contains basic facts on inclusion of and set operations on intervals
(where the precise statements depend on the order's properties;
statements requiring `LinearOrder` are in `Mathlib.Order.Interval.Set.LinearOrder`).
TODO: This is just the beginning; a lot of rules are missing
-/
assert_not_exists RelIso
open Function
open OrderDual (toDual ofDual)
variable {α : Type*}
namespace Set
section Preorder
variable [Preorder α] {a a₁ a₂ b b₁ b₂ c x : α}
instance decidableMemIoo [Decidable (a < x ∧ x < b)] : Decidable (x ∈ Ioo a b) := by assumption
instance decidableMemIco [Decidable (a ≤ x ∧ x < b)] : Decidable (x ∈ Ico a b) := by assumption
instance decidableMemIio [Decidable (x < b)] : Decidable (x ∈ Iio b) := by assumption
instance decidableMemIcc [Decidable (a ≤ x ∧ x ≤ b)] : Decidable (x ∈ Icc a b) := by assumption
instance decidableMemIic [Decidable (x ≤ b)] : Decidable (x ∈ Iic b) := by assumption
instance decidableMemIoc [Decidable (a < x ∧ x ≤ b)] : Decidable (x ∈ Ioc a b) := by assumption
instance decidableMemIci [Decidable (a ≤ x)] : Decidable (x ∈ Ici a) := by assumption
instance decidableMemIoi [Decidable (a < x)] : Decidable (x ∈ Ioi a) := by assumption
theorem left_mem_Ioo : a ∈ Ioo a b ↔ False := by simp [lt_irrefl]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp [le_refl]
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp [le_refl]
theorem left_mem_Ioc : a ∈ Ioc a b ↔ False := by simp [lt_irrefl]
theorem left_mem_Ici : a ∈ Ici a := by simp
theorem right_mem_Ioo : b ∈ Ioo a b ↔ False := by simp [lt_irrefl]
theorem right_mem_Ico : b ∈ Ico a b ↔ False := by simp [lt_irrefl]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp [le_refl]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp [le_refl]
theorem right_mem_Iic : a ∈ Iic a := by simp
@[simp]
theorem Ici_toDual : Ici (toDual a) = ofDual ⁻¹' Iic a :=
rfl
@[deprecated (since := "2025-03-20")]
alias dual_Ici := Ici_toDual
@[simp]
theorem Iic_toDual : Iic (toDual a) = ofDual ⁻¹' Ici a :=
rfl
@[deprecated (since := "2025-03-20")]
alias dual_Iic := Iic_toDual
@[simp]
theorem Ioi_toDual : Ioi (toDual a) = ofDual ⁻¹' Iio a :=
rfl
@[deprecated (since := "2025-03-20")]
alias dual_Ioi := Ioi_toDual
@[simp]
theorem Iio_toDual : Iio (toDual a) = ofDual ⁻¹' Ioi a :=
rfl
@[deprecated (since := "2025-03-20")]
alias dual_Iio := Iio_toDual
@[simp]
theorem Icc_toDual : Icc (toDual a) (toDual b) = ofDual ⁻¹' Icc b a :=
Set.ext fun _ => and_comm
@[deprecated (since := "2025-03-20")]
alias dual_Icc := Icc_toDual
@[simp]
theorem Ioc_toDual : Ioc (toDual a) (toDual b) = ofDual ⁻¹' Ico b a :=
Set.ext fun _ => and_comm
@[deprecated (since := "2025-03-20")]
alias dual_Ioc := Ioc_toDual
@[simp]
theorem Ico_toDual : Ico (toDual a) (toDual b) = ofDual ⁻¹' Ioc b a :=
Set.ext fun _ => and_comm
@[deprecated (since := "2025-03-20")]
alias dual_Ico := Ico_toDual
@[simp]
theorem Ioo_toDual : Ioo (toDual a) (toDual b) = ofDual ⁻¹' Ioo b a :=
Set.ext fun _ => and_comm
@[deprecated (since := "2025-03-20")]
alias dual_Ioo := Ioo_toDual
@[simp]
theorem Ici_ofDual {x : αᵒᵈ} : Ici (ofDual x) = toDual ⁻¹' Iic x :=
rfl
@[simp]
theorem Iic_ofDual {x : αᵒᵈ} : Iic (ofDual x) = toDual ⁻¹' Ici x :=
rfl
@[simp]
theorem Ioi_ofDual {x : αᵒᵈ} : Ioi (ofDual x) = toDual ⁻¹' Iio x :=
rfl
@[simp]
theorem Iio_ofDual {x : αᵒᵈ} : Iio (ofDual x) = toDual ⁻¹' Ioi x :=
rfl
@[simp]
theorem Icc_ofDual {x y : αᵒᵈ} : Icc (ofDual y) (ofDual x) = toDual ⁻¹' Icc x y :=
Set.ext fun _ => and_comm
@[simp]
theorem Ico_ofDual {x y : αᵒᵈ} : Ico (ofDual y) (ofDual x) = toDual ⁻¹' Ioc x y :=
Set.ext fun _ => and_comm
@[simp]
theorem Ioc_ofDual {x y : αᵒᵈ} : Ioc (ofDual y) (ofDual x) = toDual ⁻¹' Ico x y :=
Set.ext fun _ => and_comm
@[simp]
theorem Ioo_ofDual {x y : αᵒᵈ} : Ioo (ofDual y) (ofDual x) = toDual ⁻¹' Ioo x y :=
Set.ext fun _ => and_comm
@[simp]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b :=
⟨fun ⟨_, hx⟩ => hx.1.trans hx.2, fun h => ⟨a, left_mem_Icc.2 h⟩⟩
@[simp]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b :=
⟨fun ⟨_, hx⟩ => hx.1.trans_lt hx.2, fun h => ⟨a, left_mem_Ico.2 h⟩⟩
@[simp]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b :=
⟨fun ⟨_, hx⟩ => hx.1.trans_le hx.2, fun h => ⟨b, right_mem_Ioc.2 h⟩⟩
@[simp]
theorem nonempty_Ici : (Ici a).Nonempty :=
⟨a, left_mem_Ici⟩
@[simp]
theorem nonempty_Iic : (Iic a).Nonempty :=
⟨a, right_mem_Iic⟩
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b :=
⟨fun ⟨_, ha, hb⟩ => ha.trans hb, exists_between⟩
@[simp]
theorem nonempty_Ioi [NoMaxOrder α] : (Ioi a).Nonempty :=
exists_gt a
@[simp]
theorem nonempty_Iio [NoMinOrder α] : (Iio a).Nonempty :=
exists_lt a
theorem nonempty_Icc_subtype (h : a ≤ b) : Nonempty (Icc a b) :=
Nonempty.to_subtype (nonempty_Icc.mpr h)
theorem nonempty_Ico_subtype (h : a < b) : Nonempty (Ico a b) :=
Nonempty.to_subtype (nonempty_Ico.mpr h)
theorem nonempty_Ioc_subtype (h : a < b) : Nonempty (Ioc a b) :=
Nonempty.to_subtype (nonempty_Ioc.mpr h)
/-- An interval `Ici a` is nonempty. -/
instance nonempty_Ici_subtype : Nonempty (Ici a) :=
Nonempty.to_subtype nonempty_Ici
/-- An interval `Iic a` is nonempty. -/
instance nonempty_Iic_subtype : Nonempty (Iic a) :=
Nonempty.to_subtype nonempty_Iic
theorem nonempty_Ioo_subtype [DenselyOrdered α] (h : a < b) : Nonempty (Ioo a b) :=
Nonempty.to_subtype (nonempty_Ioo.mpr h)
/-- In an order without maximal elements, the intervals `Ioi` are nonempty. -/
instance nonempty_Ioi_subtype [NoMaxOrder α] : Nonempty (Ioi a) :=
Nonempty.to_subtype nonempty_Ioi
/-- In an order without minimal elements, the intervals `Iio` are nonempty. -/
instance nonempty_Iio_subtype [NoMinOrder α] : Nonempty (Iio a) :=
Nonempty.to_subtype nonempty_Iio
instance [NoMinOrder α] : NoMinOrder (Iio a) :=
⟨fun a =>
let ⟨b, hb⟩ := exists_lt (a : α)
⟨⟨b, lt_trans hb a.2⟩, hb⟩⟩
instance [NoMinOrder α] : NoMinOrder (Iic a) :=
⟨fun a =>
let ⟨b, hb⟩ := exists_lt (a : α)
⟨⟨b, hb.le.trans a.2⟩, hb⟩⟩
instance [NoMaxOrder α] : NoMaxOrder (Ioi a) :=
OrderDual.noMaxOrder (α := Iio (toDual a))
instance [NoMaxOrder α] : NoMaxOrder (Ici a) :=
OrderDual.noMaxOrder (α := Iic (toDual a))
@[simp]
theorem Icc_eq_empty (h : ¬a ≤ b) : Icc a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans hb)
@[simp]
theorem Ico_eq_empty (h : ¬a < b) : Ico a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans_lt hb)
@[simp]
theorem Ioc_eq_empty (h : ¬a < b) : Ioc a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans_le hb)
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans hb)
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
theorem Ico_self (a : α) : Ico a a = ∅ :=
Ico_eq_empty <| lt_irrefl _
theorem Ioc_self (a : α) : Ioc a a = ∅ :=
Ioc_eq_empty <| lt_irrefl _
theorem Ioo_self (a : α) : Ioo a a = ∅ :=
Ioo_eq_empty <| lt_irrefl _
@[simp]
theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a :=
⟨fun h => h <| left_mem_Ici, fun h _ hx => h.trans hx⟩
@[gcongr] alias ⟨_, _root_.GCongr.Ici_subset_Ici_of_le⟩ := Ici_subset_Ici
@[simp]
theorem Ici_ssubset_Ici : Ici a ⊂ Ici b ↔ b < a where
mp h := by
obtain ⟨ab, c, cb, ac⟩ := ssubset_iff_exists.mp h
exact lt_of_le_not_le (Ici_subset_Ici.mp ab) (fun h' ↦ ac (h'.trans cb))
mpr h := (ssubset_iff_of_subset (Ici_subset_Ici.mpr h.le)).mpr
⟨b, right_mem_Iic, fun h' => h.not_le h'⟩
@[gcongr] alias ⟨_, _root_.GCongr.Ici_ssubset_Ici_of_le⟩ := Ici_ssubset_Ici
@[simp]
theorem Iic_subset_Iic : Iic a ⊆ Iic b ↔ a ≤ b :=
@Ici_subset_Ici αᵒᵈ _ _ _
@[gcongr] alias ⟨_, _root_.GCongr.Iic_subset_Iic_of_le⟩ := Iic_subset_Iic
@[simp]
theorem Iic_ssubset_Iic : Iic a ⊂ Iic b ↔ a < b :=
@Ici_ssubset_Ici αᵒᵈ _ _ _
@[gcongr] alias ⟨_, _root_.GCongr.Iic_ssubset_Iic_of_le⟩ := Iic_ssubset_Iic
@[simp]
theorem Ici_subset_Ioi : Ici a ⊆ Ioi b ↔ b < a :=
⟨fun h => h left_mem_Ici, fun h _ hx => h.trans_le hx⟩
@[simp]
theorem Iic_subset_Iio : Iic a ⊆ Iio b ↔ a < b :=
⟨fun h => h right_mem_Iic, fun h _ hx => lt_of_le_of_lt hx h⟩
@[gcongr]
theorem Ioo_subset_Ioo (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans_lt hx₁, hx₂.trans_le h₂⟩
@[gcongr]
theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b :=
Ioo_subset_Ioo h le_rfl
@[gcongr]
theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ :=
Ioo_subset_Ioo le_rfl h
@[gcongr]
theorem Ico_subset_Ico (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans hx₁, hx₂.trans_le h₂⟩
@[gcongr]
theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b :=
Ico_subset_Ico h le_rfl
@[gcongr]
theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ :=
Ico_subset_Ico le_rfl h
@[gcongr]
theorem Icc_subset_Icc (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans hx₁, le_trans hx₂ h₂⟩
@[gcongr]
theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b :=
Icc_subset_Icc h le_rfl
@[gcongr]
theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ :=
Icc_subset_Icc le_rfl h
theorem Icc_subset_Ioo (ha : a₂ < a₁) (hb : b₁ < b₂) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ := fun _ hx =>
⟨ha.trans_le hx.1, hx.2.trans_lt hb⟩
theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := fun _ => And.left
theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := fun _ => And.right
theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := fun _ => And.right
@[gcongr]
theorem Ioc_subset_Ioc (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans_lt hx₁, hx₂.trans h₂⟩
@[gcongr]
theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b :=
Ioc_subset_Ioc h le_rfl
@[gcongr]
theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ :=
Ioc_subset_Ioc le_rfl h
theorem Ico_subset_Ioo_left (h₁ : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := fun _ =>
And.imp_left h₁.trans_le
theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := fun _ =>
And.imp_right fun h' => h'.trans_lt h
theorem Icc_subset_Ico_right (h₁ : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := fun _ =>
And.imp_right fun h₂ => h₂.trans_lt h₁
theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := fun _ => And.imp_left le_of_lt
theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := fun _ => And.imp_right le_of_lt
theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := fun _ => And.imp_right le_of_lt
theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := fun _ => And.imp_left le_of_lt
theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b :=
Subset.trans Ioo_subset_Ico_self Ico_subset_Icc_self
theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := fun _ => And.right
theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := fun _ => And.right
theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := fun _ => And.left
theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := fun _ => And.left
theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := fun _ hx => le_of_lt hx
theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := fun _ hx => le_of_lt hx
theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := fun _ => And.left
theorem Ioi_ssubset_Ici_self : Ioi a ⊂ Ici a :=
⟨Ioi_subset_Ici_self, fun h => lt_irrefl a (h le_rfl)⟩
theorem Iio_ssubset_Iic_self : Iio a ⊂ Iic a :=
@Ioi_ssubset_Ici_self αᵒᵈ _ _
theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans hx, hx'.trans h'⟩⟩
theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans_le hx, hx'.trans_lt h'⟩⟩
theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans hx, hx'.trans_lt h'⟩⟩
theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans_le hx, hx'.trans h'⟩⟩
theorem Icc_subset_Iio_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Iio b₂ ↔ b₁ < b₂ :=
⟨fun h => h ⟨h₁, le_rfl⟩, fun h _ ⟨_, hx'⟩ => hx'.trans_lt h⟩
theorem Icc_subset_Ioi_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioi a₂ ↔ a₂ < a₁ :=
⟨fun h => h ⟨le_rfl, h₁⟩, fun h _ ⟨hx, _⟩ => h.trans_le hx⟩
theorem Icc_subset_Iic_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Iic b₂ ↔ b₁ ≤ b₂ :=
⟨fun h => h ⟨h₁, le_rfl⟩, fun h _ ⟨_, hx'⟩ => hx'.trans h⟩
theorem Icc_subset_Ici_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ici a₂ ↔ a₂ ≤ a₁ :=
⟨fun h => h ⟨le_rfl, h₁⟩, fun h _ ⟨hx, _⟩ => h.trans hx⟩
theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊂ Icc a₂ b₂ :=
(ssubset_iff_of_subset (Icc_subset_Icc (le_of_lt ha) hb)).mpr
⟨a₂, left_mem_Icc.mpr hI, not_and.mpr fun f _ => lt_irrefl a₂ (ha.trans_le f)⟩
theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ :=
(ssubset_iff_of_subset (Icc_subset_Icc ha (le_of_lt hb))).mpr
⟨b₂, right_mem_Icc.mpr hI, fun f => lt_irrefl b₁ (hb.trans_le f.2)⟩
/-- If `a ≤ b`, then `(b, +∞) ⊆ (a, +∞)`. In preorders, this is just an implication. If you need
the equivalence in linear orders, use `Ioi_subset_Ioi_iff`. -/
@[gcongr]
theorem Ioi_subset_Ioi (h : a ≤ b) : Ioi b ⊆ Ioi a := fun _ hx => h.trans_lt hx
/-- If `a < b`, then `(b, +∞) ⊂ (a, +∞)`. In preorders, this is just an implication. If you need
the equivalence in linear orders, use `Ioi_ssubset_Ioi_iff`. -/
@[gcongr]
theorem Ioi_ssubset_Ioi (h : a < b) : Ioi b ⊂ Ioi a :=
(ssubset_iff_of_subset (Ioi_subset_Ioi h.le)).mpr ⟨b, h, lt_irrefl b⟩
/-- If `a ≤ b`, then `(b, +∞) ⊆ [a, +∞)`. In preorders, this is just an implication. If you need
the equivalence in dense linear orders, use `Ioi_subset_Ici_iff`. -/
theorem Ioi_subset_Ici (h : a ≤ b) : Ioi b ⊆ Ici a :=
Subset.trans (Ioi_subset_Ioi h) Ioi_subset_Ici_self
/-- If `a ≤ b`, then `(-∞, a) ⊆ (-∞, b)`. In preorders, this is just an implication. If you need
the equivalence in linear orders, use `Iio_subset_Iio_iff`. -/
@[gcongr]
theorem Iio_subset_Iio (h : a ≤ b) : Iio a ⊆ Iio b := fun _ hx => lt_of_lt_of_le hx h
/-- If `a < b`, then `(-∞, a) ⊂ (-∞, b)`. In preorders, this is just an implication. If you need
the equivalence in linear orders, use `Iio_ssubset_Iio_iff`. -/
@[gcongr]
theorem Iio_ssubset_Iio (h : a < b) : Iio a ⊂ Iio b :=
(ssubset_iff_of_subset (Iio_subset_Iio h.le)).mpr ⟨a, h, lt_irrefl a⟩
/-- If `a ≤ b`, then `(-∞, a) ⊆ (-∞, b]`. In preorders, this is just an implication. If you need
the equivalence in dense linear orders, use `Iio_subset_Iic_iff`. -/
theorem Iio_subset_Iic (h : a ≤ b) : Iio a ⊆ Iic b :=
Subset.trans (Iio_subset_Iio h) Iio_subset_Iic_self
theorem Ici_inter_Iic : Ici a ∩ Iic b = Icc a b :=
rfl
theorem Ici_inter_Iio : Ici a ∩ Iio b = Ico a b :=
rfl
theorem Ioi_inter_Iic : Ioi a ∩ Iic b = Ioc a b :=
rfl
theorem Ioi_inter_Iio : Ioi a ∩ Iio b = Ioo a b :=
rfl
theorem Iic_inter_Ici : Iic a ∩ Ici b = Icc b a :=
inter_comm _ _
theorem Iio_inter_Ici : Iio a ∩ Ici b = Ico b a :=
inter_comm _ _
theorem Iic_inter_Ioi : Iic a ∩ Ioi b = Ioc b a :=
inter_comm _ _
theorem Iio_inter_Ioi : Iio a ∩ Ioi b = Ioo b a :=
inter_comm _ _
theorem mem_Icc_of_Ioo (h : x ∈ Ioo a b) : x ∈ Icc a b :=
Ioo_subset_Icc_self h
theorem mem_Ico_of_Ioo (h : x ∈ Ioo a b) : x ∈ Ico a b :=
Ioo_subset_Ico_self h
theorem mem_Ioc_of_Ioo (h : x ∈ Ioo a b) : x ∈ Ioc a b :=
Ioo_subset_Ioc_self h
theorem mem_Icc_of_Ico (h : x ∈ Ico a b) : x ∈ Icc a b :=
Ico_subset_Icc_self h
theorem mem_Icc_of_Ioc (h : x ∈ Ioc a b) : x ∈ Icc a b :=
Ioc_subset_Icc_self h
theorem mem_Ici_of_Ioi (h : x ∈ Ioi a) : x ∈ Ici a :=
Ioi_subset_Ici_self h
theorem mem_Iic_of_Iio (h : x ∈ Iio a) : x ∈ Iic a :=
Iio_subset_Iic_self h
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Icc]
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Ico]
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Ioc]
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Ioo]
theorem _root_.IsTop.Iic_eq (h : IsTop a) : Iic a = univ :=
eq_univ_of_forall h
theorem _root_.IsBot.Ici_eq (h : IsBot a) : Ici a = univ :=
eq_univ_of_forall h
@[simp] theorem Ioi_eq_empty_iff : Ioi a = ∅ ↔ IsMax a := by
simp only [isMax_iff_forall_not_lt, eq_empty_iff_forall_not_mem, mem_Ioi]
@[simp] theorem Iio_eq_empty_iff : Iio a = ∅ ↔ IsMin a := Ioi_eq_empty_iff (α := αᵒᵈ)
@[simp] alias ⟨_, _root_.IsMax.Ioi_eq⟩ := Ioi_eq_empty_iff
@[simp] alias ⟨_, _root_.IsMin.Iio_eq⟩ := Iio_eq_empty_iff
@[simp] lemma Iio_nonempty : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [nonempty_iff_ne_empty]
@[simp] lemma Ioi_nonempty : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [nonempty_iff_ne_empty]
theorem Iic_inter_Ioc_of_le (h : a ≤ c) : Iic a ∩ Ioc b c = Ioc b a :=
ext fun _ => ⟨fun H => ⟨H.2.1, H.1⟩, fun H => ⟨H.2, H.1, H.2.trans h⟩⟩
theorem not_mem_Icc_of_lt (ha : c < a) : c ∉ Icc a b := fun h => ha.not_le h.1
theorem not_mem_Icc_of_gt (hb : b < c) : c ∉ Icc a b := fun h => hb.not_le h.2
theorem not_mem_Ico_of_lt (ha : c < a) : c ∉ Ico a b := fun h => ha.not_le h.1
theorem not_mem_Ioc_of_gt (hb : b < c) : c ∉ Ioc a b := fun h => hb.not_le h.2
theorem not_mem_Ioi_self : a ∉ Ioi a := lt_irrefl _
theorem not_mem_Iio_self : b ∉ Iio b := lt_irrefl _
theorem not_mem_Ioc_of_le (ha : c ≤ a) : c ∉ Ioc a b := fun h => lt_irrefl _ <| h.1.trans_le ha
theorem not_mem_Ico_of_ge (hb : b ≤ c) : c ∉ Ico a b := fun h => lt_irrefl _ <| h.2.trans_le hb
theorem not_mem_Ioo_of_le (ha : c ≤ a) : c ∉ Ioo a b := fun h => lt_irrefl _ <| h.1.trans_le ha
theorem not_mem_Ioo_of_ge (hb : b ≤ c) : c ∉ Ioo a b := fun h => lt_irrefl _ <| h.2.trans_le hb
section matched_intervals
@[simp] theorem Icc_eq_Ioc_same_iff : Icc a b = Ioc a b ↔ ¬a ≤ b where
mp h := by simpa using Set.ext_iff.mp h a
mpr h := by rw [Icc_eq_empty h, Ioc_eq_empty (mt le_of_lt h)]
@[simp] theorem Icc_eq_Ico_same_iff : Icc a b = Ico a b ↔ ¬a ≤ b where
mp h := by simpa using Set.ext_iff.mp h b
mpr h := by rw [Icc_eq_empty h, Ico_eq_empty (mt le_of_lt h)]
@[simp] theorem Icc_eq_Ioo_same_iff : Icc a b = Ioo a b ↔ ¬a ≤ b where
mp h := by simpa using Set.ext_iff.mp h b
mpr h := by rw [Icc_eq_empty h, Ioo_eq_empty (mt le_of_lt h)]
@[simp] theorem Ioc_eq_Ico_same_iff : Ioc a b = Ico a b ↔ ¬a < b where
mp h := by simpa using Set.ext_iff.mp h a
mpr h := by rw [Ioc_eq_empty h, Ico_eq_empty h]
@[simp] theorem Ioo_eq_Ioc_same_iff : Ioo a b = Ioc a b ↔ ¬a < b where
mp h := by simpa using Set.ext_iff.mp h b
mpr h := by rw [Ioo_eq_empty h, Ioc_eq_empty h]
@[simp] theorem Ioo_eq_Ico_same_iff : Ioo a b = Ico a b ↔ ¬a < b where
mp h := by simpa using Set.ext_iff.mp h a
mpr h := by rw [Ioo_eq_empty h, Ico_eq_empty h]
-- Mirrored versions of the above for `simp`.
@[simp] theorem Ioc_eq_Icc_same_iff : Ioc a b = Icc a b ↔ ¬a ≤ b :=
eq_comm.trans Icc_eq_Ioc_same_iff
@[simp] theorem Ico_eq_Icc_same_iff : Ico a b = Icc a b ↔ ¬a ≤ b :=
eq_comm.trans Icc_eq_Ico_same_iff
@[simp] theorem Ioo_eq_Icc_same_iff : Ioo a b = Icc a b ↔ ¬a ≤ b :=
eq_comm.trans Icc_eq_Ioo_same_iff
@[simp] theorem Ico_eq_Ioc_same_iff : Ico a b = Ioc a b ↔ ¬a < b :=
eq_comm.trans Ioc_eq_Ico_same_iff
@[simp] theorem Ioc_eq_Ioo_same_iff : Ioc a b = Ioo a b ↔ ¬a < b :=
eq_comm.trans Ioo_eq_Ioc_same_iff
@[simp] theorem Ico_eq_Ioo_same_iff : Ico a b = Ioo a b ↔ ¬a < b :=
eq_comm.trans Ioo_eq_Ico_same_iff
end matched_intervals
end Preorder
section PartialOrder
variable [PartialOrder α] {a b c : α}
@[simp]
theorem Icc_self (a : α) : Icc a a = {a} :=
Set.ext <| by simp [Icc, le_antisymm_iff, and_comm]
instance instIccUnique : Unique (Set.Icc a a) where
default := ⟨a, by simp⟩
uniq y := Subtype.ext <| by simpa using y.2
@[simp]
theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by
refine ⟨fun h => ?_, ?_⟩
· have hab : a ≤ b := nonempty_Icc.1 (h.symm.subst <| singleton_nonempty c)
exact
⟨eq_of_mem_singleton <| h ▸ left_mem_Icc.2 hab,
eq_of_mem_singleton <| h ▸ right_mem_Icc.2 hab⟩
· rintro ⟨rfl, rfl⟩
exact Icc_self _
lemma subsingleton_Icc_of_ge (hba : b ≤ a) : Set.Subsingleton (Icc a b) :=
fun _x ⟨hax, hxb⟩ _y ⟨hay, hyb⟩ ↦ le_antisymm
(le_implies_le_of_le_of_le hxb hay hba) (le_implies_le_of_le_of_le hyb hax hba)
@[simp] lemma subsingleton_Icc_iff {α : Type*} [LinearOrder α] {a b : α} :
Set.Subsingleton (Icc a b) ↔ b ≤ a := by
refine ⟨fun h ↦ ?_, subsingleton_Icc_of_ge⟩
contrapose! h
simp only [gt_iff_lt, not_subsingleton_iff]
exact ⟨a, ⟨le_refl _, h.le⟩, b, ⟨h.le, le_refl _⟩, h.ne⟩
@[simp]
theorem Icc_diff_left : Icc a b \ {a} = Ioc a b :=
ext fun x => by simp [lt_iff_le_and_ne, eq_comm, and_right_comm]
@[simp]
theorem Icc_diff_right : Icc a b \ {b} = Ico a b :=
ext fun x => by simp [lt_iff_le_and_ne, and_assoc]
@[simp]
theorem Ico_diff_left : Ico a b \ {a} = Ioo a b :=
ext fun x => by simp [and_right_comm, ← lt_iff_le_and_ne, eq_comm]
@[simp]
theorem Ioc_diff_right : Ioc a b \ {b} = Ioo a b :=
ext fun x => by simp [and_assoc, ← lt_iff_le_and_ne]
@[simp]
theorem Icc_diff_both : Icc a b \ {a, b} = Ioo a b := by
rw [insert_eq, ← diff_diff, Icc_diff_left, Ioc_diff_right]
@[simp]
theorem Ici_diff_left : Ici a \ {a} = Ioi a :=
ext fun x => by simp [lt_iff_le_and_ne, eq_comm]
@[simp]
theorem Iic_diff_right : Iic a \ {a} = Iio a :=
ext fun x => by simp [lt_iff_le_and_ne]
@[simp]
theorem Ico_diff_Ioo_same (h : a < b) : Ico a b \ Ioo a b = {a} := by
rw [← Ico_diff_left, diff_diff_cancel_left (singleton_subset_iff.2 <| left_mem_Ico.2 h)]
@[simp]
theorem Ioc_diff_Ioo_same (h : a < b) : Ioc a b \ Ioo a b = {b} := by
rw [← Ioc_diff_right, diff_diff_cancel_left (singleton_subset_iff.2 <| right_mem_Ioc.2 h)]
@[simp]
theorem Icc_diff_Ico_same (h : a ≤ b) : Icc a b \ Ico a b = {b} := by
rw [← Icc_diff_right, diff_diff_cancel_left (singleton_subset_iff.2 <| right_mem_Icc.2 h)]
@[simp]
theorem Icc_diff_Ioc_same (h : a ≤ b) : Icc a b \ Ioc a b = {a} := by
rw [← Icc_diff_left, diff_diff_cancel_left (singleton_subset_iff.2 <| left_mem_Icc.2 h)]
@[simp]
theorem Icc_diff_Ioo_same (h : a ≤ b) : Icc a b \ Ioo a b = {a, b} := by
rw [← Icc_diff_both, diff_diff_cancel_left]
simp [insert_subset_iff, h]
@[simp]
theorem Ici_diff_Ioi_same : Ici a \ Ioi a = {a} := by
rw [← Ici_diff_left, diff_diff_cancel_left (singleton_subset_iff.2 left_mem_Ici)]
@[simp]
theorem Iic_diff_Iio_same : Iic a \ Iio a = {a} := by
rw [← Iic_diff_right, diff_diff_cancel_left (singleton_subset_iff.2 right_mem_Iic)]
theorem Ioi_union_left : Ioi a ∪ {a} = Ici a :=
ext fun x => by simp [eq_comm, le_iff_eq_or_lt]
theorem Iio_union_right : Iio a ∪ {a} = Iic a :=
ext fun _ => le_iff_lt_or_eq.symm
theorem Ioo_union_left (hab : a < b) : Ioo a b ∪ {a} = Ico a b := by
rw [← Ico_diff_left, diff_union_self,
union_eq_self_of_subset_right (singleton_subset_iff.2 <| left_mem_Ico.2 hab)]
theorem Ioo_union_right (hab : a < b) : Ioo a b ∪ {b} = Ioc a b := by
simpa only [Ioo_toDual, Ico_toDual] using Ioo_union_left hab.dual
theorem Ioo_union_both (h : a ≤ b) : Ioo a b ∪ {a, b} = Icc a b := by
have : (Icc a b \ {a, b}) ∪ {a, b} = Icc a b := diff_union_of_subset fun
| x, .inl rfl => left_mem_Icc.mpr h
| x, .inr rfl => right_mem_Icc.mpr h
rw [← this, Icc_diff_both]
theorem Ioc_union_left (hab : a ≤ b) : Ioc a b ∪ {a} = Icc a b := by
rw [← Icc_diff_left, diff_union_self,
union_eq_self_of_subset_right (singleton_subset_iff.2 <| left_mem_Icc.2 hab)]
theorem Ico_union_right (hab : a ≤ b) : Ico a b ∪ {b} = Icc a b := by
simpa only [Ioc_toDual, Icc_toDual] using Ioc_union_left hab.dual
@[simp]
theorem Ico_insert_right (h : a ≤ b) : insert b (Ico a b) = Icc a b := by
rw [insert_eq, union_comm, Ico_union_right h]
@[simp]
theorem Ioc_insert_left (h : a ≤ b) : insert a (Ioc a b) = Icc a b := by
rw [insert_eq, union_comm, Ioc_union_left h]
@[simp]
theorem Ioo_insert_left (h : a < b) : insert a (Ioo a b) = Ico a b := by
rw [insert_eq, union_comm, Ioo_union_left h]
@[simp]
theorem Ioo_insert_right (h : a < b) : insert b (Ioo a b) = Ioc a b := by
rw [insert_eq, union_comm, Ioo_union_right h]
@[simp]
theorem Iio_insert : insert a (Iio a) = Iic a :=
ext fun _ => le_iff_eq_or_lt.symm
@[simp]
theorem Ioi_insert : insert a (Ioi a) = Ici a :=
ext fun _ => (or_congr_left eq_comm).trans le_iff_eq_or_lt.symm
theorem mem_Ici_Ioi_of_subset_of_subset {s : Set α} (ho : Ioi a ⊆ s) (hc : s ⊆ Ici a) :
s ∈ ({Ici a, Ioi a} : Set (Set α)) :=
by_cases
(fun h : a ∈ s =>
Or.inl <| Subset.antisymm hc <| by rw [← Ioi_union_left, union_subset_iff]; simp [*])
fun h =>
Or.inr <| Subset.antisymm (fun _ hx => lt_of_le_of_ne (hc hx) fun heq => h <| heq.symm ▸ hx) ho
theorem mem_Iic_Iio_of_subset_of_subset {s : Set α} (ho : Iio a ⊆ s) (hc : s ⊆ Iic a) :
s ∈ ({Iic a, Iio a} : Set (Set α)) :=
@mem_Ici_Ioi_of_subset_of_subset αᵒᵈ _ a s ho hc
theorem mem_Icc_Ico_Ioc_Ioo_of_subset_of_subset {s : Set α} (ho : Ioo a b ⊆ s) (hc : s ⊆ Icc a b) :
s ∈ ({Icc a b, Ico a b, Ioc a b, Ioo a b} : Set (Set α)) := by
classical
by_cases ha : a ∈ s <;> by_cases hb : b ∈ s
· refine Or.inl (Subset.antisymm hc ?_)
rwa [← Ico_diff_left, diff_singleton_subset_iff, insert_eq_of_mem ha, ← Icc_diff_right,
diff_singleton_subset_iff, insert_eq_of_mem hb] at ho
· refine Or.inr <| Or.inl <| Subset.antisymm ?_ ?_
· rw [← Icc_diff_right]
exact subset_diff_singleton hc hb
· rwa [← Ico_diff_left, diff_singleton_subset_iff, insert_eq_of_mem ha] at ho
· refine Or.inr <| Or.inr <| Or.inl <| Subset.antisymm ?_ ?_
· rw [← Icc_diff_left]
exact subset_diff_singleton hc ha
· rwa [← Ioc_diff_right, diff_singleton_subset_iff, insert_eq_of_mem hb] at ho
· refine Or.inr <| Or.inr <| Or.inr <| Subset.antisymm ?_ ho
rw [← Ico_diff_left, ← Icc_diff_right]
apply_rules [subset_diff_singleton]
theorem eq_left_or_mem_Ioo_of_mem_Ico {x : α} (hmem : x ∈ Ico a b) : x = a ∨ x ∈ Ioo a b :=
hmem.1.eq_or_gt.imp_right fun h => ⟨h, hmem.2⟩
theorem eq_right_or_mem_Ioo_of_mem_Ioc {x : α} (hmem : x ∈ Ioc a b) : x = b ∨ x ∈ Ioo a b :=
hmem.2.eq_or_lt.imp_right <| And.intro hmem.1
theorem eq_endpoints_or_mem_Ioo_of_mem_Icc {x : α} (hmem : x ∈ Icc a b) :
x = a ∨ x = b ∨ x ∈ Ioo a b :=
hmem.1.eq_or_gt.imp_right fun h => eq_right_or_mem_Ioo_of_mem_Ioc ⟨h, hmem.2⟩
theorem _root_.IsMax.Ici_eq (h : IsMax a) : Ici a = {a} :=
eq_singleton_iff_unique_mem.2 ⟨left_mem_Ici, fun _ => h.eq_of_ge⟩
theorem _root_.IsMin.Iic_eq (h : IsMin a) : Iic a = {a} :=
h.toDual.Ici_eq
theorem Ici_injective : Injective (Ici : α → Set α) := fun _ _ =>
eq_of_forall_ge_iff ∘ Set.ext_iff.1
theorem Iic_injective : Injective (Iic : α → Set α) := fun _ _ =>
eq_of_forall_le_iff ∘ Set.ext_iff.1
theorem Ici_inj : Ici a = Ici b ↔ a = b :=
Ici_injective.eq_iff
theorem Iic_inj : Iic a = Iic b ↔ a = b :=
Iic_injective.eq_iff
@[simp]
theorem Icc_inter_Icc_eq_singleton (hab : a ≤ b) (hbc : b ≤ c) : Icc a b ∩ Icc b c = {b} := by
rw [← Ici_inter_Iic, ← Iic_inter_Ici, inter_inter_inter_comm, Iic_inter_Ici]
simp [hab, hbc]
lemma Icc_eq_Icc_iff {d : α} (h : a ≤ b) :
Icc a b = Icc c d ↔ a = c ∧ b = d := by
refine ⟨fun heq ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
have h' : c ≤ d := by
by_contra contra; rw [Icc_eq_empty_iff.mpr contra, Icc_eq_empty_iff] at heq; contradiction
simp only [Set.ext_iff, mem_Icc] at heq
obtain ⟨-, h₁⟩ := (heq b).mp ⟨h, le_refl _⟩
obtain ⟨h₂, -⟩ := (heq a).mp ⟨le_refl _, h⟩
obtain ⟨h₃, -⟩ := (heq c).mpr ⟨le_refl _, h'⟩
obtain ⟨-, h₄⟩ := (heq d).mpr ⟨h', le_refl _⟩
exact ⟨le_antisymm h₃ h₂, le_antisymm h₁ h₄⟩
end PartialOrder
section OrderTop
@[simp]
theorem Ici_top [PartialOrder α] [OrderTop α] : Ici (⊤ : α) = {⊤} :=
isMax_top.Ici_eq
variable [Preorder α] [OrderTop α] {a : α}
theorem Ioi_top : Ioi (⊤ : α) = ∅ :=
isMax_top.Ioi_eq
@[simp]
theorem Iic_top : Iic (⊤ : α) = univ :=
isTop_top.Iic_eq
@[simp]
theorem Icc_top : Icc a ⊤ = Ici a := by simp [← Ici_inter_Iic]
@[simp]
theorem Ioc_top : Ioc a ⊤ = Ioi a := by simp [← Ioi_inter_Iic]
end OrderTop
section OrderBot
@[simp]
theorem Iic_bot [PartialOrder α] [OrderBot α] : Iic (⊥ : α) = {⊥} :=
isMin_bot.Iic_eq
variable [Preorder α] [OrderBot α] {a : α}
theorem Iio_bot : Iio (⊥ : α) = ∅ :=
isMin_bot.Iio_eq
@[simp]
theorem Ici_bot : Ici (⊥ : α) = univ :=
isBot_bot.Ici_eq
@[simp]
theorem Icc_bot : Icc ⊥ a = Iic a := by simp [← Ici_inter_Iic]
@[simp]
theorem Ico_bot : Ico ⊥ a = Iio a := by simp [← Ici_inter_Iio]
end OrderBot
theorem Icc_bot_top [Preorder α] [BoundedOrder α] : Icc (⊥ : α) ⊤ = univ := by simp
section Lattice
section Inf
variable [SemilatticeInf α]
@[simp]
theorem Iic_inter_Iic {a b : α} : Iic a ∩ Iic b = Iic (a ⊓ b) := by
ext x
simp [Iic]
@[simp]
theorem Ioc_inter_Iic (a b c : α) : Ioc a b ∩ Iic c = Ioc a (b ⊓ c) := by
rw [← Ioi_inter_Iic, ← Ioi_inter_Iic, inter_assoc, Iic_inter_Iic]
end Inf
section Sup
variable [SemilatticeSup α]
@[simp]
theorem Ici_inter_Ici {a b : α} : Ici a ∩ Ici b = Ici (a ⊔ b) := by
ext x
simp [Ici]
@[simp]
theorem Ico_inter_Ici (a b c : α) : Ico a b ∩ Ici c = Ico (a ⊔ c) b := by
rw [← Ici_inter_Iio, ← Ici_inter_Iio, ← Ici_inter_Ici, inter_right_comm]
end Sup
section Both
variable [Lattice α] {a b c a₁ a₂ b₁ b₂ : α}
theorem Icc_inter_Icc : Icc a₁ b₁ ∩ Icc a₂ b₂ = Icc (a₁ ⊔ a₂) (b₁ ⊓ b₂) := by
simp only [Ici_inter_Iic.symm, Ici_inter_Ici.symm, Iic_inter_Iic.symm]; ac_rfl
end Both
end Lattice
/-! ### Closed intervals in `α × β` -/
section Prod
variable {β : Type*} [Preorder α] [Preorder β]
@[simp]
theorem Iic_prod_Iic (a : α) (b : β) : Iic a ×ˢ Iic b = Iic (a, b) :=
rfl
@[simp]
theorem Ici_prod_Ici (a : α) (b : β) : Ici a ×ˢ Ici b = Ici (a, b) :=
rfl
theorem Ici_prod_eq (a : α × β) : Ici a = Ici a.1 ×ˢ Ici a.2 :=
rfl
theorem Iic_prod_eq (a : α × β) : Iic a = Iic a.1 ×ˢ Iic a.2 :=
rfl
@[simp]
theorem Icc_prod_Icc (a₁ a₂ : α) (b₁ b₂ : β) : Icc a₁ a₂ ×ˢ Icc b₁ b₂ = Icc (a₁, b₁) (a₂, b₂) := by
ext ⟨x, y⟩
simp [and_assoc, and_comm, and_left_comm]
theorem Icc_prod_eq (a b : α × β) : Icc a b = Icc a.1 b.1 ×ˢ Icc a.2 b.2 := by simp
end Prod
end Set
/-! ### Lemmas about intervals in dense orders -/
section Dense
variable (α) [Preorder α] [DenselyOrdered α] {x y : α}
instance : NoMinOrder (Set.Ioo x y) :=
⟨fun ⟨a, ha₁, ha₂⟩ => by
rcases exists_between ha₁ with ⟨b, hb₁, hb₂⟩
exact ⟨⟨b, hb₁, hb₂.trans ha₂⟩, hb₂⟩⟩
instance : NoMinOrder (Set.Ioc x y) :=
⟨fun ⟨a, ha₁, ha₂⟩ => by
rcases exists_between ha₁ with ⟨b, hb₁, hb₂⟩
exact ⟨⟨b, hb₁, hb₂.le.trans ha₂⟩, hb₂⟩⟩
instance : NoMinOrder (Set.Ioi x) :=
⟨fun ⟨a, ha⟩ => by
rcases exists_between ha with ⟨b, hb₁, hb₂⟩
exact ⟨⟨b, hb₁⟩, hb₂⟩⟩
instance : NoMaxOrder (Set.Ioo x y) :=
⟨fun ⟨a, ha₁, ha₂⟩ => by
rcases exists_between ha₂ with ⟨b, hb₁, hb₂⟩
exact ⟨⟨b, ha₁.trans hb₁, hb₂⟩, hb₁⟩⟩
instance : NoMaxOrder (Set.Ico x y) :=
⟨fun ⟨a, ha₁, ha₂⟩ => by
rcases exists_between ha₂ with ⟨b, hb₁, hb₂⟩
exact ⟨⟨b, ha₁.trans hb₁.le, hb₂⟩, hb₁⟩⟩
instance : NoMaxOrder (Set.Iio x) :=
⟨fun ⟨a, ha⟩ => by
rcases exists_between ha with ⟨b, hb₁, hb₂⟩
exact ⟨⟨b, hb₂⟩, hb₁⟩⟩
end Dense
/-! ### Intervals in `Prop` -/
namespace Set
@[simp] lemma Iic_False : Iic False = {False} := by aesop
@[simp] lemma Iic_True : Iic True = univ := by aesop
@[simp] lemma Ici_False : Ici False = univ := by aesop
@[simp] lemma Ici_True : Ici True = {True} := by aesop
lemma Iio_False : Iio False = ∅ := by aesop
@[simp] lemma Iio_True : Iio True = {False} := by aesop (add simp [Ioi, lt_iff_le_not_le])
@[simp] lemma Ioi_False : Ioi False = {True} := by aesop (add simp [Ioi, lt_iff_le_not_le])
lemma Ioi_True : Ioi True = ∅ := by aesop
end Set
| Mathlib/Order/Interval/Set/Basic.lean | 1,128 | 1,128 | |
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa
-/
import Mathlib.Data.Finsupp.Defs
/-!
# Locus of unequal values of finitely supported functions
Let `α N` be two Types, assume that `N` has a `0` and let `f g : α →₀ N` be finitely supported
functions.
## Main definition
* `Finsupp.neLocus f g : Finset α`, the finite subset of `α` where `f` and `g` differ.
In the case in which `N` is an additive group, `Finsupp.neLocus f g` coincides with
`Finsupp.support (f - g)`.
-/
variable {α M N P : Type*}
namespace Finsupp
variable [DecidableEq α]
section NHasZero
variable [DecidableEq N] [Zero N] (f g : α →₀ N)
/-- Given two finitely supported functions `f g : α →₀ N`, `Finsupp.neLocus f g` is the `Finset`
where `f` and `g` differ. This generalizes `(f - g).support` to situations without subtraction. -/
def neLocus (f g : α →₀ N) : Finset α :=
(f.support ∪ g.support).filter fun x => f x ≠ g x
@[simp]
theorem mem_neLocus {f g : α →₀ N} {a : α} : a ∈ f.neLocus g ↔ f a ≠ g a := by
simpa only [neLocus, Finset.mem_filter, Finset.mem_union, mem_support_iff,
and_iff_right_iff_imp] using Ne.ne_or_ne _
theorem not_mem_neLocus {f g : α →₀ N} {a : α} : a ∉ f.neLocus g ↔ f a = g a :=
mem_neLocus.not.trans not_ne_iff
@[simp]
theorem coe_neLocus : ↑(f.neLocus g) = { x | f x ≠ g x } := by
ext
exact mem_neLocus
@[simp]
theorem neLocus_eq_empty {f g : α →₀ N} : f.neLocus g = ∅ ↔ f = g :=
⟨fun h =>
ext fun a => not_not.mp (mem_neLocus.not.mp (Finset.eq_empty_iff_forall_not_mem.mp h a)),
fun h => h ▸ by simp only [neLocus, Ne, eq_self_iff_true, not_true, Finset.filter_False]⟩
@[simp]
theorem nonempty_neLocus_iff {f g : α →₀ N} : (f.neLocus g).Nonempty ↔ f ≠ g :=
Finset.nonempty_iff_ne_empty.trans neLocus_eq_empty.not
theorem neLocus_comm : f.neLocus g = g.neLocus f := by
simp_rw [neLocus, Finset.union_comm, ne_comm]
@[simp]
theorem neLocus_zero_right : f.neLocus 0 = f.support := by
ext
rw [mem_neLocus, mem_support_iff, coe_zero, Pi.zero_apply]
@[simp]
theorem neLocus_zero_left : (0 : α →₀ N).neLocus f = f.support :=
(neLocus_comm _ _).trans (neLocus_zero_right _)
end NHasZero
section NeLocusAndMaps
theorem subset_mapRange_neLocus [DecidableEq N] [Zero N] [DecidableEq M] [Zero M] (f g : α →₀ N)
{F : N → M} (F0 : F 0 = 0) : (f.mapRange F F0).neLocus (g.mapRange F F0) ⊆ f.neLocus g :=
fun x => by simpa only [mem_neLocus, mapRange_apply, not_imp_not] using congr_arg F
theorem zipWith_neLocus_eq_left [DecidableEq N] [Zero M] [DecidableEq P] [Zero P] [Zero N]
{F : M → N → P} (F0 : F 0 0 = 0) (f : α →₀ M) (g₁ g₂ : α →₀ N)
(hF : ∀ f, Function.Injective fun g => F f g) :
(zipWith F F0 f g₁).neLocus (zipWith F F0 f g₂) = g₁.neLocus g₂ := by
ext
simpa only [mem_neLocus] using (hF _).ne_iff
theorem zipWith_neLocus_eq_right [DecidableEq M] [Zero M] [DecidableEq P] [Zero P] [Zero N]
{F : M → N → P} (F0 : F 0 0 = 0) (f₁ f₂ : α →₀ M) (g : α →₀ N)
(hF : ∀ g, Function.Injective fun f => F f g) :
(zipWith F F0 f₁ g).neLocus (zipWith F F0 f₂ g) = f₁.neLocus f₂ := by
ext
simpa only [mem_neLocus] using (hF _).ne_iff
theorem mapRange_neLocus_eq [DecidableEq N] [DecidableEq M] [Zero M] [Zero N] (f g : α →₀ N)
{F : N → M} (F0 : F 0 = 0) (hF : Function.Injective F) :
(f.mapRange F F0).neLocus (g.mapRange F F0) = f.neLocus g := by
ext
simpa only [mem_neLocus] using hF.ne_iff
end NeLocusAndMaps
variable [DecidableEq N]
@[simp]
theorem neLocus_add_left [AddLeftCancelMonoid N] (f g h : α →₀ N) :
(f + g).neLocus (f + h) = g.neLocus h :=
zipWith_neLocus_eq_left _ _ _ _ add_right_injective
@[simp]
theorem neLocus_add_right [AddRightCancelMonoid N] (f g h : α →₀ N) :
(f + h).neLocus (g + h) = f.neLocus g :=
zipWith_neLocus_eq_right _ _ _ _ add_left_injective
section AddGroup
variable [AddGroup N] (f f₁ f₂ g g₁ g₂ : α →₀ N)
@[simp]
theorem neLocus_neg_neg : neLocus (-f) (-g) = f.neLocus g :=
mapRange_neLocus_eq _ _ neg_zero neg_injective
theorem neLocus_neg : neLocus (-f) g = f.neLocus (-g) := by rw [← neLocus_neg_neg, neg_neg]
theorem neLocus_eq_support_sub : f.neLocus g = (f - g).support := by
rw [← neLocus_add_right _ _ (-g), add_neg_cancel, neLocus_zero_right, sub_eq_add_neg]
@[simp]
theorem neLocus_sub_left : neLocus (f - g₁) (f - g₂) = neLocus g₁ g₂ := by
simp only [sub_eq_add_neg, neLocus_add_left, neLocus_neg_neg]
@[simp]
theorem neLocus_sub_right : neLocus (f₁ - g) (f₂ - g) = neLocus f₁ f₂ := by
simpa only [sub_eq_add_neg] using neLocus_add_right _ _ _
@[simp]
theorem neLocus_self_add_right : neLocus f (f + g) = g.support := by
rw [← neLocus_zero_left, ← neLocus_add_left f 0 g, add_zero]
@[simp]
theorem neLocus_self_add_left : neLocus (f + g) f = g.support := by
rw [neLocus_comm, neLocus_self_add_right]
@[simp]
theorem neLocus_self_sub_right : neLocus f (f - g) = g.support := by
rw [sub_eq_add_neg, neLocus_self_add_right, support_neg]
@[simp]
theorem neLocus_self_sub_left : neLocus (f - g) f = g.support := by
rw [neLocus_comm, neLocus_self_sub_right]
end AddGroup
| end Finsupp
| Mathlib/Data/Finsupp/NeLocus.lean | 154 | 155 |
/-
Copyright (c) 2020 Kevin Buzzard, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Equalizers
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Products
import Mathlib.CategoryTheory.Limits.Yoneda
import Mathlib.CategoryTheory.Preadditive.FunctorCategory
import Mathlib.CategoryTheory.Sites.SheafOfTypes
import Mathlib.CategoryTheory.Sites.EqualizerSheafCondition
import Mathlib.CategoryTheory.Limits.Constructions.EpiMono
/-!
# Sheaves taking values in a category
If C is a category with a Grothendieck topology, we define the notion of a sheaf taking values in
an arbitrary category `A`. We follow the definition in https://stacks.math.columbia.edu/tag/00VR,
noting that the presheaf of sets "defined above" can be seen in the comments between tags 00VQ and
00VR on the page <https://stacks.math.columbia.edu/tag/00VL>. The advantage of this definition is
that we need no assumptions whatsoever on `A` other than the assumption that the morphisms in `C`
and `A` live in the same universe.
* An `A`-valued presheaf `P : Cᵒᵖ ⥤ A` is defined to be a sheaf (for the topology `J`) iff for
every `E : A`, the type-valued presheaves of sets given by sending `U : Cᵒᵖ` to `Hom_{A}(E, P U)`
are all sheaves of sets, see `CategoryTheory.Presheaf.IsSheaf`.
* When `A = Type`, this recovers the basic definition of sheaves of sets, see
`CategoryTheory.isSheaf_iff_isSheaf_of_type`.
* A alternate definition in terms of limits, unconditionally equivalent to the original one:
see `CategoryTheory.Presheaf.isSheaf_iff_isLimit`.
* An alternate definition when `C` is small, has pullbacks and `A` has products is given by an
equalizer condition `CategoryTheory.Presheaf.IsSheaf'`. This is equivalent to the earlier
definition, shown in `CategoryTheory.Presheaf.isSheaf_iff_isSheaf'`.
* When `A = Type`, this is *definitionally* equal to the equalizer condition for presieves in
`CategoryTheory.Sites.SheafOfTypes`.
* When `A` has limits and there is a functor `s : A ⥤ Type` which is faithful, reflects isomorphisms
and preserves limits, then `P : Cᵒᵖ ⥤ A` is a sheaf iff the underlying presheaf of types
`P ⋙ s : Cᵒᵖ ⥤ Type` is a sheaf (`CategoryTheory.Presheaf.isSheaf_iff_isSheaf_forget`).
Cf https://stacks.math.columbia.edu/tag/0073, which is a weaker version of this statement (it's
only over spaces, not sites) and https://stacks.math.columbia.edu/tag/00YR (a), which
additionally assumes filtered colimits.
## Implementation notes
Occasionally we need to take a limit in `A` of a collection of morphisms of `C` indexed
by a collection of objects in `C`. This turns out to force the morphisms of `A` to be
in a sufficiently large universe. Rather than use `UnivLE` we prove some results for
a category `A'` instead, whose morphism universe of `A'` is defined to be `max u₁ v₁`, where
`u₁, v₁` are the universes for `C`. Perhaps after we get better at handling universe
inequalities this can be changed.
-/
universe w v₁ v₂ v₃ u₁ u₂ u₃
noncomputable section
namespace CategoryTheory
open Opposite CategoryTheory Category Limits Sieve
namespace Presheaf
variable {C : Type u₁} [Category.{v₁} C]
variable {A : Type u₂} [Category.{v₂} A]
variable (J : GrothendieckTopology C)
-- We follow https://stacks.math.columbia.edu/tag/00VL definition 00VR
/-- A sheaf of A is a presheaf P : Cᵒᵖ => A such that for every E : A, the
presheaf of types given by sending U : C to Hom_{A}(E, P U) is a sheaf of types. -/
@[stacks 00VR]
def IsSheaf (P : Cᵒᵖ ⥤ A) : Prop :=
∀ E : A, Presieve.IsSheaf J (P ⋙ coyoneda.obj (op E))
/-- Condition that a presheaf with values in a concrete category is separated for
a Grothendieck topology. -/
def IsSeparated (P : Cᵒᵖ ⥤ A) {FA : A → A → Type*} {CA : A → Type*}
[∀ X Y, FunLike (FA X Y) (CA X) (CA Y)] [ConcreteCategory A FA] : Prop :=
∀ (X : C) (S : Sieve X) (_ : S ∈ J X) (x y : ToType (P.obj (op X))),
(∀ (Y : C) (f : Y ⟶ X) (_ : S f), P.map f.op x = P.map f.op y) → x = y
section LimitSheafCondition
open Presieve Presieve.FamilyOfElements Limits
variable (P : Cᵒᵖ ⥤ A) {X : C} (S : Sieve X) (R : Presieve X) (E : Aᵒᵖ)
/-- Given a sieve `S` on `X : C`, a presheaf `P : Cᵒᵖ ⥤ A`, and an object `E` of `A`,
the cones over the natural diagram `S.arrows.diagram.op ⋙ P` associated to `S` and `P`
with cone point `E` are in 1-1 correspondence with sieve_compatible family of elements
for the sieve `S` and the presheaf of types `Hom (E, P -)`. -/
def conesEquivSieveCompatibleFamily :
(S.arrows.diagram.op ⋙ P).cones.obj E ≃
{ x : FamilyOfElements (P ⋙ coyoneda.obj E) (S : Presieve X) // x.SieveCompatible } where
toFun π :=
⟨fun _ f h => π.app (op ⟨Over.mk f, h⟩), fun X Y f g hf => by
apply (id_comp _).symm.trans
dsimp
exact π.naturality (Quiver.Hom.op (Over.homMk _ (by rfl)))⟩
invFun x :=
{ app := fun f => x.1 f.unop.1.hom f.unop.2
naturality := fun f f' g => by
refine Eq.trans ?_ (x.2 f.unop.1.hom g.unop.left f.unop.2)
dsimp
rw [id_comp]
convert rfl
rw [Over.w] }
left_inv _ := rfl
right_inv _ := rfl
variable {P S E}
variable {x : FamilyOfElements (P ⋙ coyoneda.obj E) S.arrows} (hx : SieveCompatible x)
/-- The cone corresponding to a sieve_compatible family of elements, dot notation enabled. -/
@[simp]
def _root_.CategoryTheory.Presieve.FamilyOfElements.SieveCompatible.cone :
Cone (S.arrows.diagram.op ⋙ P) where
pt := E.unop
π := (conesEquivSieveCompatibleFamily P S E).invFun ⟨x, hx⟩
/-- Cone morphisms from the cone corresponding to a sieve_compatible family to the natural
cone associated to a sieve `S` and a presheaf `P` are in 1-1 correspondence with amalgamations
of the family. -/
def homEquivAmalgamation :
(hx.cone ⟶ P.mapCone S.arrows.cocone.op) ≃ { t // x.IsAmalgamation t } where
toFun l := ⟨l.hom, fun _ f hf => l.w (op ⟨Over.mk f, hf⟩)⟩
invFun t := ⟨t.1, fun f => t.2 f.unop.1.hom f.unop.2⟩
left_inv _ := rfl
right_inv _ := rfl
variable (P S)
/-- Given sieve `S` and presheaf `P : Cᵒᵖ ⥤ A`, their natural associated cone is a limit cone
iff `Hom (E, P -)` is a sheaf of types for the sieve `S` and all `E : A`. -/
theorem isLimit_iff_isSheafFor :
Nonempty (IsLimit (P.mapCone S.arrows.cocone.op)) ↔
∀ E : Aᵒᵖ, IsSheafFor (P ⋙ coyoneda.obj E) S.arrows := by
dsimp [IsSheafFor]; simp_rw [compatible_iff_sieveCompatible]
rw [((Cone.isLimitEquivIsTerminal _).trans (isTerminalEquivUnique _ _)).nonempty_congr]
rw [Classical.nonempty_pi]; constructor
· intro hu E x hx
specialize hu hx.cone
rw [(homEquivAmalgamation hx).uniqueCongr.nonempty_congr] at hu
exact (unique_subtype_iff_existsUnique _).1 hu
· rintro h ⟨E, π⟩
let eqv := conesEquivSieveCompatibleFamily P S (op E)
rw [← eqv.left_inv π]
erw [(homEquivAmalgamation (eqv π).2).uniqueCongr.nonempty_congr]
rw [unique_subtype_iff_existsUnique]
exact h _ _ (eqv π).2
/-- Given sieve `S` and presheaf `P : Cᵒᵖ ⥤ A`, their natural associated cone admits at most one
morphism from every cone in the same category (i.e. over the same diagram),
iff `Hom (E, P -)`is separated for the sieve `S` and all `E : A`. -/
theorem subsingleton_iff_isSeparatedFor :
(∀ c, Subsingleton (c ⟶ P.mapCone S.arrows.cocone.op)) ↔
∀ E : Aᵒᵖ, IsSeparatedFor (P ⋙ coyoneda.obj E) S.arrows := by
constructor
· intro hs E x t₁ t₂ h₁ h₂
have hx := is_compatible_of_exists_amalgamation x ⟨t₁, h₁⟩
rw [compatible_iff_sieveCompatible] at hx
specialize hs hx.cone
rcases hs with ⟨hs⟩
simpa only [Subtype.mk.injEq] using (show Subtype.mk t₁ h₁ = ⟨t₂, h₂⟩ from
(homEquivAmalgamation hx).symm.injective (hs _ _))
· rintro h ⟨E, π⟩
let eqv := conesEquivSieveCompatibleFamily P S (op E)
constructor
rw [← eqv.left_inv π]
intro f₁ f₂
let eqv' := homEquivAmalgamation (eqv π).2
apply eqv'.injective
ext
apply h _ (eqv π).1 <;> exact (eqv' _).2
/-- A presheaf `P` is a sheaf for the Grothendieck topology `J` iff for every covering sieve
`S` of `J`, the natural cone associated to `P` and `S` is a limit cone. -/
theorem isSheaf_iff_isLimit :
IsSheaf J P ↔
∀ ⦃X : C⦄ (S : Sieve X), S ∈ J X → Nonempty (IsLimit (P.mapCone S.arrows.cocone.op)) :=
⟨fun h _ S hS => (isLimit_iff_isSheafFor P S).2 fun E => h E.unop S hS, fun h E _ S hS =>
(isLimit_iff_isSheafFor P S).1 (h S hS) (op E)⟩
/-- A presheaf `P` is separated for the Grothendieck topology `J` iff for every covering sieve
`S` of `J`, the natural cone associated to `P` and `S` admits at most one morphism from every
cone in the same category. -/
theorem isSeparated_iff_subsingleton :
(∀ E : A, Presieve.IsSeparated J (P ⋙ coyoneda.obj (op E))) ↔
∀ ⦃X : C⦄ (S : Sieve X), S ∈ J X → ∀ c, Subsingleton (c ⟶ P.mapCone S.arrows.cocone.op) :=
⟨fun h _ S hS => (subsingleton_iff_isSeparatedFor P S).2 fun E => h E.unop S hS, fun h E _ S hS =>
(subsingleton_iff_isSeparatedFor P S).1 (h S hS) (op E)⟩
/-- Given presieve `R` and presheaf `P : Cᵒᵖ ⥤ A`, the natural cone associated to `P` and
the sieve `Sieve.generate R` generated by `R` is a limit cone iff `Hom (E, P -)` is a
sheaf of types for the presieve `R` and all `E : A`. -/
theorem isLimit_iff_isSheafFor_presieve :
Nonempty (IsLimit (P.mapCone (generate R).arrows.cocone.op)) ↔
∀ E : Aᵒᵖ, IsSheafFor (P ⋙ coyoneda.obj E) R :=
(isLimit_iff_isSheafFor P _).trans (forall_congr' fun _ => (isSheafFor_iff_generate _).symm)
/-- A presheaf `P` is a sheaf for the Grothendieck topology generated by a pretopology `K`
iff for every covering presieve `R` of `K`, the natural cone associated to `P` and
`Sieve.generate R` is a limit cone. -/
theorem isSheaf_iff_isLimit_pretopology [HasPullbacks C] (K : Pretopology C) :
IsSheaf (K.toGrothendieck C) P ↔
∀ ⦃X : C⦄ (R : Presieve X),
R ∈ K X → Nonempty (IsLimit (P.mapCone (generate R).arrows.cocone.op)) := by
dsimp [IsSheaf]
simp_rw [isSheaf_pretopology]
exact
⟨fun h X R hR => (isLimit_iff_isSheafFor_presieve P R).2 fun E => h E.unop R hR,
fun h E X R hR => (isLimit_iff_isSheafFor_presieve P R).1 (h R hR) (op E)⟩
end LimitSheafCondition
variable {J}
/-- This is a wrapper around `Presieve.IsSheafFor.amalgamate` to be used below.
If `P`s a sheaf, `S` is a cover of `X`, and `x` is a collection of morphisms from `E`
to `P` evaluated at terms in the cover which are compatible, then we can amalgamate
the `x`s to obtain a single morphism `E ⟶ P.obj (op X)`. -/
def IsSheaf.amalgamate {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A}
(hP : Presheaf.IsSheaf J P) (S : J.Cover X) (x : ∀ I : S.Arrow, E ⟶ P.obj (op I.Y))
(hx : ∀ ⦃I₁ I₂ : S.Arrow⦄ (r : I₁.Relation I₂),
x I₁ ≫ P.map r.g₁.op = x I₂ ≫ P.map r.g₂.op) : E ⟶ P.obj (op X) :=
(hP _ _ S.condition).amalgamate (fun Y f hf => x ⟨Y, f, hf⟩) fun _ _ _ _ _ _ _ h₁ h₂ w =>
@hx { hf := h₁, .. } { hf := h₂, .. } { w := w, .. }
@[reassoc (attr := simp)]
theorem IsSheaf.amalgamate_map {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A}
(hP : Presheaf.IsSheaf J P) (S : J.Cover X) (x : ∀ I : S.Arrow, E ⟶ P.obj (op I.Y))
(hx : ∀ ⦃I₁ I₂ : S.Arrow⦄ (r : I₁.Relation I₂),
x I₁ ≫ P.map r.g₁.op = x I₂ ≫ P.map r.g₂.op)
(I : S.Arrow) :
hP.amalgamate S x hx ≫ P.map I.f.op = x _ := by
apply (hP _ _ S.condition).valid_glue
theorem IsSheaf.hom_ext {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A}
(hP : Presheaf.IsSheaf J P) (S : J.Cover X) (e₁ e₂ : E ⟶ P.obj (op X))
(h : ∀ I : S.Arrow, e₁ ≫ P.map I.f.op = e₂ ≫ P.map I.f.op) : e₁ = e₂ :=
(hP _ _ S.condition).isSeparatedFor.ext fun Y f hf => h ⟨Y, f, hf⟩
lemma IsSheaf.hom_ext_ofArrows
{P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) {I : Type*} {S : C} {X : I → C}
(f : ∀ i, X i ⟶ S) (hf : Sieve.ofArrows _ f ∈ J S) {E : A}
{x y : E ⟶ P.obj (op S)} (h : ∀ i, x ≫ P.map (f i).op = y ≫ P.map (f i).op) :
x = y := by
apply hP.hom_ext ⟨_, hf⟩
rintro ⟨Z, _, _, g, _, ⟨i⟩, rfl⟩
dsimp
rw [P.map_comp, reassoc_of% (h i)]
section
variable {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) {I : Type*} {S : C} {X : I → C}
(f : ∀ i, X i ⟶ S) (hf : Sieve.ofArrows _ f ∈ J S) {E : A}
(x : ∀ i, E ⟶ P.obj (op (X i)))
(hx : ∀ ⦃W : C⦄ ⦃i j : I⦄ (a : W ⟶ X i) (b : W ⟶ X j),
a ≫ f i = b ≫ f j → x i ≫ P.map a.op = x j ≫ P.map b.op)
include hP hf hx
lemma IsSheaf.existsUnique_amalgamation_ofArrows :
∃! (g : E ⟶ P.obj (op S)), ∀ (i : I), g ≫ P.map (f i).op = x i :=
(Presieve.isSheafFor_arrows_iff _ _).1
((Presieve.isSheafFor_iff_generate _).2 (hP E _ hf)) x (fun _ _ _ _ _ w => hx _ _ w)
@[deprecated (since := "2024-12-17")]
alias IsSheaf.exists_unique_amalgamation_ofArrows := IsSheaf.existsUnique_amalgamation_ofArrows
/-- If `P : Cᵒᵖ ⥤ A` is a sheaf and `f i : X i ⟶ S` is a covering family, then
a morphism `E ⟶ P.obj (op S)` can be constructed from a compatible family of
morphisms `x : E ⟶ P.obj (op (X i))`. -/
def IsSheaf.amalgamateOfArrows : E ⟶ P.obj (op S) :=
(hP.existsUnique_amalgamation_ofArrows f hf x hx).choose
@[reassoc (attr := simp)]
lemma IsSheaf.amalgamateOfArrows_map (i : I) :
hP.amalgamateOfArrows f hf x hx ≫ P.map (f i).op = x i :=
(hP.existsUnique_amalgamation_ofArrows f hf x hx).choose_spec.1 i
end
theorem isSheaf_of_iso_iff {P P' : Cᵒᵖ ⥤ A} (e : P ≅ P') : IsSheaf J P ↔ IsSheaf J P' :=
forall_congr' fun _ =>
⟨Presieve.isSheaf_iso J (isoWhiskerRight e _),
Presieve.isSheaf_iso J (isoWhiskerRight e.symm _)⟩
variable (J)
theorem isSheaf_of_isTerminal {X : A} (hX : IsTerminal X) :
Presheaf.IsSheaf J ((CategoryTheory.Functor.const _).obj X) := fun _ _ _ _ _ _ =>
⟨hX.from _, fun _ _ _ => hX.hom_ext _ _, fun _ _ => hX.hom_ext _ _⟩
end Presheaf
variable {C : Type u₁} [Category.{v₁} C]
variable (J : GrothendieckTopology C)
variable (A : Type u₂) [Category.{v₂} A]
/-- The category of sheaves taking values in `A` on a grothendieck topology. -/
structure Sheaf where
/-- the underlying presheaf -/
val : Cᵒᵖ ⥤ A
/-- the condition that the presheaf is a sheaf -/
cond : Presheaf.IsSheaf J val
namespace Sheaf
variable {J A}
/-- Morphisms between sheaves are just morphisms of presheaves. -/
@[ext]
structure Hom (X Y : Sheaf J A) where
/-- a morphism between the underlying presheaves -/
val : X.val ⟶ Y.val
@[simps id_val comp_val]
instance instCategorySheaf : Category (Sheaf J A) where
Hom := Hom
id _ := ⟨𝟙 _⟩
comp f g := ⟨f.val ≫ g.val⟩
id_comp _ := Hom.ext <| id_comp _
comp_id _ := Hom.ext <| comp_id _
assoc _ _ _ := Hom.ext <| assoc _ _ _
-- Let's make the inhabited linter happy.../sips
instance (X : Sheaf J A) : Inhabited (Hom X X) :=
⟨𝟙 X⟩
@[ext]
lemma hom_ext {X Y : Sheaf J A} (x y : X ⟶ Y) (h : x.val = y.val) : x = y :=
Sheaf.Hom.ext h
end Sheaf
/-- The inclusion functor from sheaves to presheaves. -/
@[simps]
def sheafToPresheaf : Sheaf J A ⥤ Cᵒᵖ ⥤ A where
obj := Sheaf.val
map f := f.val
map_id _ := rfl
map_comp _ _ := rfl
/-- The sections of a sheaf (i.e. evaluation as a presheaf on `C`). -/
abbrev sheafSections : Cᵒᵖ ⥤ Sheaf J A ⥤ A := (sheafToPresheaf J A).flip
/-- The sheaf sections functor on `X` is given by evaluation of presheaves on `X`. -/
@[simps!]
def sheafSectionsNatIsoEvaluation {X : C} :
(sheafSections J A).obj (op X) ≅ sheafToPresheaf J A ⋙ (evaluation _ _).obj (op X) :=
NatIso.ofComponents (fun _ ↦ Iso.refl _)
/-- The functor `Sheaf J A ⥤ Cᵒᵖ ⥤ A` is fully faithful. -/
@[simps]
def fullyFaithfulSheafToPresheaf : (sheafToPresheaf J A).FullyFaithful where
preimage f := ⟨f⟩
variable {J A} in
/-- The bijection `(X ⟶ Y) ≃ (X.val ⟶ Y.val)` when `X` and `Y` are sheaves. -/
abbrev Sheaf.homEquiv {X Y : Sheaf J A} : (X ⟶ Y) ≃ (X.val ⟶ Y.val) :=
(fullyFaithfulSheafToPresheaf J A).homEquiv
instance : (sheafToPresheaf J A).Full :=
(fullyFaithfulSheafToPresheaf J A).full
instance : (sheafToPresheaf J A).Faithful :=
(fullyFaithfulSheafToPresheaf J A).faithful
instance : (sheafToPresheaf J A).ReflectsIsomorphisms :=
(fullyFaithfulSheafToPresheaf J A).reflectsIsomorphisms
/-- This is stated as a lemma to prevent class search from forming a loop since a sheaf morphism is
monic if and only if it is monic as a presheaf morphism (under suitable assumption). -/
theorem Sheaf.Hom.mono_of_presheaf_mono {F G : Sheaf J A} (f : F ⟶ G) [h : Mono f.1] : Mono f :=
(sheafToPresheaf J A).mono_of_mono_map h
instance Sheaf.Hom.epi_of_presheaf_epi {F G : Sheaf J A} (f : F ⟶ G) [h : Epi f.1] : Epi f :=
(sheafToPresheaf J A).epi_of_epi_map h
theorem isSheaf_iff_isSheaf_of_type (P : Cᵒᵖ ⥤ Type w) :
Presheaf.IsSheaf J P ↔ Presieve.IsSheaf J P := by
constructor
· intro hP
refine Presieve.isSheaf_iso J ?_ (hP PUnit)
exact isoWhiskerLeft _ Coyoneda.punitIso ≪≫ P.rightUnitor
· intro hP X Y S hS z hz
refine ⟨fun x => (hP S hS).amalgamate (fun Z f hf => z f hf x) ?_, ?_, ?_⟩
· intro Y₁ Y₂ Z g₁ g₂ f₁ f₂ hf₁ hf₂ h
exact congr_fun (hz g₁ g₂ hf₁ hf₂ h) x
· intro Z f hf
funext x
apply Presieve.IsSheafFor.valid_glue
· intro y hy
funext x
apply (hP S hS).isSeparatedFor.ext
intro Y' f hf
rw [Presieve.IsSheafFor.valid_glue _ _ _ hf, ← hy _ hf]
rfl
/-- The sheaf of sections guaranteed by the sheaf condition. -/
@[simps]
def sheafOver {A : Type u₂} [Category.{v₂} A] {J : GrothendieckTopology C} (ℱ : Sheaf J A) (E : A) :
Sheaf J (Type _) where
val := ℱ.val ⋙ coyoneda.obj (op E)
cond := by
rw [isSheaf_iff_isSheaf_of_type]
exact ℱ.cond E
variable {J} in
lemma Presheaf.IsSheaf.isSheafFor {P : Cᵒᵖ ⥤ Type w} (hP : Presheaf.IsSheaf J P)
{X : C} (S : Sieve X) (hS : S ∈ J X) : Presieve.IsSheafFor P S.arrows := by
rw [isSheaf_iff_isSheaf_of_type] at hP
exact hP S hS
variable {A} in
lemma Presheaf.isSheaf_bot (P : Cᵒᵖ ⥤ A) : IsSheaf ⊥ P := fun _ ↦ Presieve.isSheaf_bot
/--
The category of sheaves on the bottom (trivial) Grothendieck topology is
equivalent to the category of presheaves.
-/
@[simps]
def sheafBotEquivalence : Sheaf (⊥ : GrothendieckTopology C) A ≌ Cᵒᵖ ⥤ A where
functor := sheafToPresheaf _ _
inverse :=
{ obj := fun P => ⟨P, Presheaf.isSheaf_bot P⟩
map := fun f => ⟨f⟩ }
unitIso := Iso.refl _
counitIso := Iso.refl _
instance : Inhabited (Sheaf (⊥ : GrothendieckTopology C) (Type w)) :=
⟨(sheafBotEquivalence _).inverse.obj ((Functor.const _).obj default)⟩
variable {J} {A}
/-- If the empty sieve is a cover of `X`, then `F(X)` is terminal. -/
def Sheaf.isTerminalOfBotCover (F : Sheaf J A) (X : C) (H : ⊥ ∈ J X) :
IsTerminal (F.1.obj (op X)) := by
refine @IsTerminal.ofUnique _ _ _ ?_
intro Y
choose t h using F.2 Y _ H (by tauto) (by tauto)
exact ⟨⟨t⟩, fun a => h.2 a (by tauto)⟩
section Preadditive
open Preadditive
variable [Preadditive A] {P Q : Sheaf J A}
instance sheafHomHasZSMul : SMul ℤ (P ⟶ Q) where
smul n f :=
Sheaf.Hom.mk
{ app := fun U => n • f.1.app U
naturality := fun U V i => by
induction' n with n ih n ih
· simp only [zero_smul, comp_zero, zero_comp]
· simpa only [add_zsmul, one_zsmul, comp_add, NatTrans.naturality, add_comp,
add_left_inj]
· simpa only [sub_smul, one_zsmul, comp_sub, NatTrans.naturality, sub_comp,
sub_left_inj] using ih }
instance : Sub (P ⟶ Q) where sub f g := Sheaf.Hom.mk <| f.1 - g.1
instance : Neg (P ⟶ Q) where neg f := Sheaf.Hom.mk <| -f.1
instance sheafHomHasNSMul : SMul ℕ (P ⟶ Q) where
smul n f :=
Sheaf.Hom.mk
{ app := fun U => n • f.1.app U
naturality := fun U V i => by
induction n with
| zero => simp only [zero_smul, comp_zero, zero_comp]
| succ n ih => simp only [Nat.succ_eq_add_one, add_smul, ih, one_nsmul, comp_add,
NatTrans.naturality, add_comp] }
instance : Zero (P ⟶ Q) where zero := Sheaf.Hom.mk 0
instance : Add (P ⟶ Q) where add f g := Sheaf.Hom.mk <| f.1 + g.1
@[simp]
theorem Sheaf.Hom.add_app (f g : P ⟶ Q) (U) : (f + g).1.app U = f.1.app U + g.1.app U :=
rfl
instance Sheaf.Hom.addCommGroup : AddCommGroup (P ⟶ Q) :=
Function.Injective.addCommGroup (fun f : Sheaf.Hom P Q => f.1)
(fun _ _ h => Sheaf.Hom.ext h) rfl (fun _ _ => rfl) (fun _ => rfl) (fun _ _ => rfl)
(fun _ _ => by aesop_cat) (fun _ _ => by aesop_cat)
instance : Preadditive (Sheaf J A) where
homGroup _ _ := Sheaf.Hom.addCommGroup
end Preadditive
end CategoryTheory
namespace CategoryTheory
open Opposite CategoryTheory Category Limits Sieve
namespace Presheaf
-- Under here is the equalizer story, which is equivalent if A has products (and doesn't
-- make sense otherwise). It's described in https://stacks.math.columbia.edu/tag/00VL,
-- between 00VQ and 00VR.
variable {C : Type u₁} [Category.{v₁} C]
-- `A` is a general category; `A'` is a variant where the morphisms live in a large enough
-- universe to guarantee that we can take limits in A of things coming from C.
-- I would have liked to use something like `UnivLE.{max v₁ u₁, v₂}` as a hypothesis on
-- `A`'s morphism universe rather than introducing `A'` but I can't get it to work.
-- So, for now, results which need max v₁ u₁ ≤ v₂ are just stated for `A'` and `P' : Cᵒᵖ ⥤ A'`
-- instead.
variable {A : Type u₂} [Category.{v₂} A]
variable {A' : Type u₂} [Category.{max v₁ u₁} A']
variable {B : Type u₃} [Category.{v₃} B]
variable (J : GrothendieckTopology C)
variable {U : C} (R : Presieve U)
variable (P : Cᵒᵖ ⥤ A) (P' : Cᵒᵖ ⥤ A')
section MultiequalizerConditions
/-- When `P` is a sheaf and `S` is a cover, the associated multifork is a limit. -/
def isLimitOfIsSheaf {X : C} (S : J.Cover X) (hP : IsSheaf J P) : IsLimit (S.multifork P) where
lift := fun E : Multifork _ => hP.amalgamate S (fun _ => E.ι _)
(fun _ _ r => E.condition ⟨r⟩)
fac := by
rintro (E : Multifork _) (a | b)
· apply hP.amalgamate_map
· rw [← E.w (WalkingMulticospan.Hom.fst b),
← (S.multifork P).w (WalkingMulticospan.Hom.fst b), ← assoc]
congr 1
apply hP.amalgamate_map
uniq := by
rintro (E : Multifork _) m hm
apply hP.hom_ext S
intro I
erw [hm (WalkingMulticospan.left I)]
symm
apply hP.amalgamate_map
theorem isSheaf_iff_multifork :
IsSheaf J P ↔ ∀ (X : C) (S : J.Cover X), Nonempty (IsLimit (S.multifork P)) := by
refine ⟨fun hP X S => ⟨isLimitOfIsSheaf _ _ _ hP⟩, ?_⟩
intro h E X S hS x hx
let T : J.Cover X := ⟨S, hS⟩
obtain ⟨hh⟩ := h _ T
let K : Multifork (T.index P) := Multifork.ofι _ E (fun I => x I.f I.hf)
(fun I => hx _ _ _ _ I.r.w)
use hh.lift K
dsimp; constructor
· intro Y f hf
apply hh.fac K (WalkingMulticospan.left ⟨Y, f, hf⟩)
· intro e he
apply hh.uniq K
rintro (a | b)
· apply he
· rw [← K.w (WalkingMulticospan.Hom.fst b), ←
(T.multifork P).w (WalkingMulticospan.Hom.fst b), ← assoc]
congr 1
apply he
variable {J P} in
/-- If `F : Cᵒᵖ ⥤ A` is a sheaf for a Grothendieck topology `J` on `C`,
and `S` is a cover of `X : C`, then the multifork `S.multifork F` is limit. -/
def IsSheaf.isLimitMultifork
(hP : Presheaf.IsSheaf J P) {X : C} (S : J.Cover X) : IsLimit (S.multifork P) := by
rw [Presheaf.isSheaf_iff_multifork] at hP
exact (hP X S).some
theorem isSheaf_iff_multiequalizer [∀ (X : C) (S : J.Cover X), HasMultiequalizer (S.index P)] :
IsSheaf J P ↔ ∀ (X : C) (S : J.Cover X), IsIso (S.toMultiequalizer P) := by
rw [isSheaf_iff_multifork]
refine forall₂_congr fun X S => ⟨?_, ?_⟩
· rintro ⟨h⟩
let e : P.obj (op X) ≅ multiequalizer (S.index P) :=
h.conePointUniqueUpToIso (limit.isLimit _)
exact (inferInstance : IsIso e.hom)
· intro h
refine ⟨IsLimit.ofIsoLimit (limit.isLimit _) (Cones.ext ?_ ?_)⟩
· apply (@asIso _ _ _ _ _ h).symm
· intro a
symm
simp
end MultiequalizerConditions
section
variable [HasProducts.{max u₁ v₁} A]
variable [HasProducts.{max u₁ v₁} A']
/-- The middle object of the fork diagram given in Equation (3) of [MM92], as well as the fork
diagram of the Stacks entry. -/
@[stacks 00VM "The middle object of the fork diagram there."]
def firstObj : A :=
∏ᶜ fun f : ΣV, { f : V ⟶ U // R f } => P.obj (op f.1)
/-- The left morphism of the fork diagram given in Equation (3) of [MM92], as well as the fork
diagram of the Stacks entry. -/
@[stacks 00VM "The left morphism the fork diagram there."]
def forkMap : P.obj (op U) ⟶ firstObj R P :=
Pi.lift fun f => P.map f.2.1.op
variable [HasPullbacks C]
/-- The rightmost object of the fork diagram of the Stacks entry, which
contains the data used to check a family of elements for a presieve is compatible.
-/
@[stacks 00VM "The rightmost object of the fork diagram there."]
def secondObj : A :=
∏ᶜ fun fg : (ΣV, { f : V ⟶ U // R f }) × ΣW, { g : W ⟶ U // R g } =>
P.obj (op (pullback fg.1.2.1 fg.2.2.1))
/-- The map `pr₀*` of the Stacks entry. -/
@[stacks 00VM "The map `pr₀*` there."]
def firstMap : firstObj R P ⟶ secondObj R P :=
Pi.lift fun _ => Pi.π _ _ ≫ P.map (pullback.fst _ _).op
/-- The map `pr₁*` of the Stacks entry. -/
@[stacks 00VM "The map `pr₁*` there."]
def secondMap : firstObj R P ⟶ secondObj R P :=
Pi.lift fun _ => Pi.π _ _ ≫ P.map (pullback.snd _ _).op
theorem w : forkMap R P ≫ firstMap R P = forkMap R P ≫ secondMap R P := by
apply limit.hom_ext
rintro ⟨⟨Y, f, hf⟩, ⟨Z, g, hg⟩⟩
simp only [firstMap, secondMap, forkMap, limit.lift_π, limit.lift_π_assoc, assoc, Fan.mk_π_app,
Subtype.coe_mk]
rw [← P.map_comp, ← op_comp, pullback.condition]
simp
/-- An alternative definition of the sheaf condition in terms of equalizers. This is shown to be
equivalent in `CategoryTheory.Presheaf.isSheaf_iff_isSheaf'`.
-/
def IsSheaf' (P : Cᵒᵖ ⥤ A) : Prop :=
∀ (U : C) (R : Presieve U) (_ : generate R ∈ J U), Nonempty (IsLimit (Fork.ofι _ (w R P)))
-- Again I wonder whether `UnivLE` can somehow be used to allow `s` to take
-- values in a more general universe.
/-- (Implementation). An auxiliary lemma to convert between sheaf conditions. -/
def isSheafForIsSheafFor' (P : Cᵒᵖ ⥤ A) (s : A ⥤ Type max v₁ u₁)
[∀ J, PreservesLimitsOfShape (Discrete.{max v₁ u₁} J) s] (U : C) (R : Presieve U) :
IsLimit (s.mapCone (Fork.ofι _ (w R P))) ≃
IsLimit (Fork.ofι _ (Equalizer.Presieve.w (P ⋙ s) R)) := by
let e : parallelPair (s.map (firstMap R P)) (s.map (secondMap R P)) ≅
parallelPair (Equalizer.Presieve.firstMap (P ⋙ s) R)
(Equalizer.Presieve.secondMap (P ⋙ s) R) := by
refine parallelPair.ext (PreservesProduct.iso s _) ((PreservesProduct.iso s _))
(limit.hom_ext (fun j => ?_)) (limit.hom_ext (fun j => ?_))
· dsimp [Equalizer.Presieve.firstMap, firstMap]
simp only [map_lift_piComparison, Functor.map_comp, limit.lift_π, Fan.mk_pt,
Fan.mk_π_app, assoc, piComparison_comp_π_assoc]
· dsimp [Equalizer.Presieve.secondMap, secondMap]
simp only [map_lift_piComparison, Functor.map_comp, limit.lift_π, Fan.mk_pt,
Fan.mk_π_app, assoc, piComparison_comp_π_assoc]
refine Equiv.trans (isLimitMapConeForkEquiv _ _) ?_
refine (IsLimit.postcomposeHomEquiv e _).symm.trans
(IsLimit.equivIsoLimit (Fork.ext (Iso.refl _) ?_))
dsimp [Equalizer.forkMap, forkMap, e, Fork.ι]
simp only [id_comp, map_lift_piComparison]
-- Remark : this lemma uses `A'` not `A`; `A'` is `A` but with a universe
-- restriction. Can it be generalised?
/-- The equalizer definition of a sheaf given by `isSheaf'` is equivalent to `isSheaf`. -/
theorem isSheaf_iff_isSheaf' : IsSheaf J P' ↔ IsSheaf' J P' := by
constructor
· intro h U R hR
refine ⟨?_⟩
apply coyonedaJointlyReflectsLimits
intro X
have q : Presieve.IsSheafFor (P' ⋙ coyoneda.obj X) _ := h X.unop _ hR
rw [← Presieve.isSheafFor_iff_generate] at q
rw [Equalizer.Presieve.sheaf_condition] at q
replace q := Classical.choice q
apply (isSheafForIsSheafFor' _ _ _ _).symm q
· intro h U X S hS
rw [Equalizer.Presieve.sheaf_condition]
refine ⟨?_⟩
refine isSheafForIsSheafFor' _ _ _ _ ?_
letI := preservesSmallestLimits_of_preservesLimits (coyoneda.obj (op U))
apply isLimitOfPreserves
apply Classical.choice (h _ S.arrows _)
simpa
end
section Concrete
theorem isSheaf_of_isSheaf_comp (s : A ⥤ B) [ReflectsLimitsOfSize.{v₁, max v₁ u₁} s]
(h : IsSheaf J (P ⋙ s)) : IsSheaf J P := by
rw [isSheaf_iff_isLimit] at h ⊢
exact fun X S hS ↦ (h S hS).map fun t ↦ isLimitOfReflects s t
theorem isSheaf_comp_of_isSheaf (s : A ⥤ B) [PreservesLimitsOfSize.{v₁, max v₁ u₁} s]
(h : IsSheaf J P) : IsSheaf J (P ⋙ s) := by
rw [isSheaf_iff_isLimit] at h ⊢
apply fun X S hS ↦ (h S hS).map fun t ↦ isLimitOfPreserves s t
theorem isSheaf_iff_isSheaf_comp (s : A ⥤ B) [HasLimitsOfSize.{v₁, max v₁ u₁} A]
[PreservesLimitsOfSize.{v₁, max v₁ u₁} s] [s.ReflectsIsomorphisms] :
IsSheaf J P ↔ IsSheaf J (P ⋙ s) := by
letI : ReflectsLimitsOfSize s := reflectsLimits_of_reflectsIsomorphisms
exact ⟨isSheaf_comp_of_isSheaf J P s, isSheaf_of_isSheaf_comp J P s⟩
/--
For a concrete category `(A, s)` where the forgetful functor `s : A ⥤ Type v` preserves limits and
reflects isomorphisms, and `A` has limits, an `A`-valued presheaf `P : Cᵒᵖ ⥤ A` is a sheaf iff its
underlying `Type`-valued presheaf `P ⋙ s : Cᵒᵖ ⥤ Type` is a sheaf.
Note this lemma applies for "algebraic" categories, eg groups, abelian groups and rings, but not
for the category of topological spaces, topological rings, etc since reflecting isomorphisms doesn't
hold.
-/
theorem isSheaf_iff_isSheaf_forget (s : A' ⥤ Type max v₁ u₁) [HasLimits A'] [PreservesLimits s]
[s.ReflectsIsomorphisms] : IsSheaf J P' ↔ IsSheaf J (P' ⋙ s) := by
have : HasLimitsOfSize.{v₁, max v₁ u₁} A' := hasLimitsOfSizeShrink.{_, _, u₁, 0} A'
have : PreservesLimitsOfSize.{v₁, max v₁ u₁} s := preservesLimitsOfSize_shrink.{_, 0, _, u₁} s
apply isSheaf_iff_isSheaf_comp
end Concrete
end Presheaf
end CategoryTheory
| Mathlib/CategoryTheory/Sites/Sheaf.lean | 735 | 738 | |
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson
-/
import Mathlib.Topology.Category.Profinite.Nobeling.Basic
import Mathlib.Topology.Category.Profinite.Nobeling.Induction
import Mathlib.Topology.Category.Profinite.Nobeling.Span
import Mathlib.Topology.Category.Profinite.Nobeling.Successor
import Mathlib.Topology.Category.Profinite.Nobeling.ZeroLimit
deprecated_module (since := "2025-04-13")
| Mathlib/Topology/Category/Profinite/Nobeling.lean | 1,716 | 1,723 | |
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Peter Nelson
-/
import Mathlib.Order.Antichain
/-!
# Minimality and Maximality
This file proves basic facts about minimality and maximality
of an element with respect to a predicate `P` on an ordered type `α`.
## Implementation Details
This file underwent a refactor from a version where minimality and maximality were defined using
sets rather than predicates, and with an unbundled order relation rather than a `LE` instance.
A side effect is that it has become less straightforward to state that something is minimal
with respect to a relation that is *not* defeq to the default `LE`.
One possible way would be with a type synonym,
and another would be with an ad hoc `LE` instance and `@` notation.
This was not an issue in practice anywhere in mathlib at the time of the refactor,
but it may be worth re-examining this to make it easier in the future; see the TODO below.
## TODO
* In the linearly ordered case, versions of lemmas like `minimal_mem_image` will hold with
`MonotoneOn`/`AntitoneOn` assumptions rather than the stronger `x ≤ y ↔ f x ≤ f y` assumptions.
* `Set.maximal_iff_forall_insert` and `Set.minimal_iff_forall_diff_singleton` will generalize to
lemmas about covering in the case of an `IsStronglyAtomic`/`IsStronglyCoatomic` order.
* `Finset` versions of the lemmas about sets.
* API to allow for easily expressing min/maximality with respect to an arbitrary non-`LE` relation.
* API for `MinimalFor`/`MaximalFor`
-/
assert_not_exists CompleteLattice
open Set OrderDual
variable {α : Type*} {P Q : α → Prop} {a x y : α}
section LE
variable [LE α]
@[simp] theorem minimal_toDual : Minimal (fun x ↦ P (ofDual x)) (toDual x) ↔ Maximal P x :=
Iff.rfl
alias ⟨Minimal.of_dual, Minimal.dual⟩ := minimal_toDual
@[simp] theorem maximal_toDual : Maximal (fun x ↦ P (ofDual x)) (toDual x) ↔ Minimal P x :=
Iff.rfl
alias ⟨Maximal.of_dual, Maximal.dual⟩ := maximal_toDual
@[simp] theorem minimal_false : ¬ Minimal (fun _ ↦ False) x := by
simp [Minimal]
@[simp] theorem maximal_false : ¬ Maximal (fun _ ↦ False) x := by
simp [Maximal]
@[simp] theorem minimal_true : Minimal (fun _ ↦ True) x ↔ IsMin x := by
simp [IsMin, Minimal]
@[simp] theorem maximal_true : Maximal (fun _ ↦ True) x ↔ IsMax x :=
minimal_true (α := αᵒᵈ)
@[simp] theorem minimal_subtype {x : Subtype Q} :
Minimal (fun x ↦ P x.1) x ↔ Minimal (P ⊓ Q) x := by
obtain ⟨x, hx⟩ := x
simp only [Minimal, Subtype.forall, Subtype.mk_le_mk, Pi.inf_apply, inf_Prop_eq]
tauto
@[simp] theorem maximal_subtype {x : Subtype Q} :
Maximal (fun x ↦ P x.1) x ↔ Maximal (P ⊓ Q) x :=
minimal_subtype (α := αᵒᵈ)
theorem maximal_true_subtype {x : Subtype P} : Maximal (fun _ ↦ True) x ↔ Maximal P x := by
obtain ⟨x, hx⟩ := x
simp [Maximal, hx]
theorem minimal_true_subtype {x : Subtype P} : Minimal (fun _ ↦ True) x ↔ Minimal P x := by
obtain ⟨x, hx⟩ := x
simp [Minimal, hx]
@[simp] theorem minimal_minimal : Minimal (Minimal P) x ↔ Minimal P x :=
⟨fun h ↦ h.prop, fun h ↦ ⟨h, fun _ hy hyx ↦ h.le_of_le hy.prop hyx⟩⟩
@[simp] theorem maximal_maximal : Maximal (Maximal P) x ↔ Maximal P x :=
minimal_minimal (α := αᵒᵈ)
/-- If `P` is down-closed, then minimal elements satisfying `P` are exactly the globally minimal
elements satisfying `P`. -/
theorem minimal_iff_isMin (hP : ∀ ⦃x y⦄, P y → x ≤ y → P x) : Minimal P x ↔ P x ∧ IsMin x :=
⟨fun h ↦ ⟨h.prop, fun _ h' ↦ h.le_of_le (hP h.prop h') h'⟩, fun h ↦ ⟨h.1, fun _ _ h' ↦ h.2 h'⟩⟩
/-- If `P` is up-closed, then maximal elements satisfying `P` are exactly the globally maximal
elements satisfying `P`. -/
theorem maximal_iff_isMax (hP : ∀ ⦃x y⦄, P y → y ≤ x → P x) : Maximal P x ↔ P x ∧ IsMax x :=
⟨fun h ↦ ⟨h.prop, fun _ h' ↦ h.le_of_ge (hP h.prop h') h'⟩, fun h ↦ ⟨h.1, fun _ _ h' ↦ h.2 h'⟩⟩
theorem Minimal.mono (h : Minimal P x) (hle : Q ≤ P) (hQ : Q x) : Minimal Q x :=
⟨hQ, fun y hQy ↦ h.le_of_le (hle y hQy)⟩
theorem Maximal.mono (h : Maximal P x) (hle : Q ≤ P) (hQ : Q x) : Maximal Q x :=
⟨hQ, fun y hQy ↦ h.le_of_ge (hle y hQy)⟩
theorem Minimal.and_right (h : Minimal P x) (hQ : Q x) : Minimal (fun x ↦ P x ∧ Q x) x :=
h.mono (fun _ ↦ And.left) ⟨h.prop, hQ⟩
theorem Minimal.and_left (h : Minimal P x) (hQ : Q x) : Minimal (fun x ↦ (Q x ∧ P x)) x :=
h.mono (fun _ ↦ And.right) ⟨hQ, h.prop⟩
theorem Maximal.and_right (h : Maximal P x) (hQ : Q x) : Maximal (fun x ↦ (P x ∧ Q x)) x :=
h.mono (fun _ ↦ And.left) ⟨h.prop, hQ⟩
theorem Maximal.and_left (h : Maximal P x) (hQ : Q x) : Maximal (fun x ↦ (Q x ∧ P x)) x :=
h.mono (fun _ ↦ And.right) ⟨hQ, h.prop⟩
| @[simp] theorem minimal_eq_iff : Minimal (· = y) x ↔ x = y := by
simp +contextual [Minimal]
@[simp] theorem maximal_eq_iff : Maximal (· = y) x ↔ x = y := by
simp +contextual [Maximal]
theorem not_minimal_iff (hx : P x) : ¬ Minimal P x ↔ ∃ y, P y ∧ y ≤ x ∧ ¬ (x ≤ y) := by
simp [Minimal, hx]
| Mathlib/Order/Minimal.lean | 124 | 131 |
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Julian Kuelshammer, Heather Macbeth, Mitchell Lee
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Derivative
import Mathlib.Algebra.Ring.NegOnePow
import Mathlib.Tactic.LinearCombination
/-!
# Chebyshev polynomials
The Chebyshev polynomials are families of polynomials indexed by `ℤ`,
with integral coefficients.
## Main definitions
* `Polynomial.Chebyshev.T`: the Chebyshev polynomials of the first kind.
* `Polynomial.Chebyshev.U`: the Chebyshev polynomials of the second kind.
* `Polynomial.Chebyshev.C`: the rescaled Chebyshev polynomials of the first kind (also known as the
Vieta–Lucas polynomials), given by $C_n(2x) = 2T_n(x)$.
* `Polynomial.Chebyshev.S`: the rescaled Chebyshev polynomials of the second kind (also known as the
Vieta–Fibonacci polynomials), given by $S_n(2x) = U_n(x)$.
## Main statements
* The formal derivative of the Chebyshev polynomials of the first kind is a scalar multiple of the
Chebyshev polynomials of the second kind.
* `Polynomial.Chebyshev.T_mul_T`, twice the product of the `m`-th and `k`-th Chebyshev polynomials
of the first kind is the sum of the `m + k`-th and `m - k`-th Chebyshev polynomials of the first
kind. There is a similar statement `Polynomial.Chebyshev.C_mul_C` for the `C` polynomials.
* `Polynomial.Chebyshev.T_mul`, the `(m * n)`-th Chebyshev polynomial of the first kind is the
composition of the `m`-th and `n`-th Chebyshev polynomials of the first kind. There is a similar
statement `Polynomial.Chebyshev.C_mul` for the `C` polynomials.
## Implementation details
Since Chebyshev polynomials have interesting behaviour over the complex numbers and modulo `p`,
we define them to have coefficients in an arbitrary commutative ring, even though
technically `ℤ` would suffice.
The benefit of allowing arbitrary coefficient rings, is that the statements afterwards are clean,
and do not have `map (Int.castRingHom R)` interfering all the time.
## References
[Lionel Ponton, _Roots of the Chebyshev polynomials: A purely algebraic approach_]
[ponton2020chebyshev]
## TODO
* Redefine and/or relate the definition of Chebyshev polynomials to `LinearRecurrence`.
* Add explicit formula involving square roots for Chebyshev polynomials
* Compute zeroes and extrema of Chebyshev polynomials.
* Prove that the roots of the Chebyshev polynomials (except 0) are irrational.
* Prove minimax properties of Chebyshev polynomials.
-/
namespace Polynomial.Chebyshev
open Polynomial
variable (R R' : Type*) [CommRing R] [CommRing R']
/-- `T n` is the `n`-th Chebyshev polynomial of the first kind. -/
-- Well-founded definitions are now irreducible by default;
-- as this was implemented before this change,
-- we just set it back to semireducible to avoid needing to change any proofs.
@[semireducible] noncomputable def T : ℤ → R[X]
| 0 => 1
| 1 => X
| (n : ℕ) + 2 => 2 * X * T (n + 1) - T n
| -((n : ℕ) + 1) => 2 * X * T (-n) - T (-n + 1)
termination_by n => Int.natAbs n + Int.natAbs (n - 1)
/-- Induction principle used for proving facts about Chebyshev polynomials. -/
@[elab_as_elim]
protected theorem induct (motive : ℤ → Prop)
(zero : motive 0)
(one : motive 1)
(add_two : ∀ (n : ℕ), motive (↑n + 1) → motive ↑n → motive (↑n + 2))
(neg_add_one : ∀ (n : ℕ), motive (-↑n) → motive (-↑n + 1) → motive (-↑n - 1)) :
∀ (a : ℤ), motive a :=
T.induct motive zero one add_two fun n hn hnm => by
simpa only [Int.negSucc_eq, neg_add] using neg_add_one n hn hnm
@[simp]
theorem T_add_two : ∀ n, T R (n + 2) = 2 * X * T R (n + 1) - T R n
| (k : ℕ) => T.eq_3 R k
| -(k + 1 : ℕ) => by linear_combination (norm := (simp [Int.negSucc_eq]; ring_nf)) T.eq_4 R k
theorem T_add_one (n : ℤ) : T R (n + 1) = 2 * X * T R n - T R (n - 1) := by
linear_combination (norm := ring_nf) T_add_two R (n - 1)
theorem T_sub_two (n : ℤ) : T R (n - 2) = 2 * X * T R (n - 1) - T R n := by
linear_combination (norm := ring_nf) T_add_two R (n - 2)
theorem T_sub_one (n : ℤ) : T R (n - 1) = 2 * X * T R n - T R (n + 1) := by
linear_combination (norm := ring_nf) T_add_two R (n - 1)
theorem T_eq (n : ℤ) : T R n = 2 * X * T R (n - 1) - T R (n - 2) := by
linear_combination (norm := ring_nf) T_add_two R (n - 2)
@[simp]
theorem T_zero : T R 0 = 1 := rfl
@[simp]
theorem T_one : T R 1 = X := rfl
theorem T_neg_one : T R (-1) = X := show 2 * X * 1 - X = X by ring
theorem T_two : T R 2 = 2 * X ^ 2 - 1 := by
simpa [pow_two, mul_assoc] using T_add_two R 0
@[simp]
theorem T_neg (n : ℤ) : T R (-n) = T R n := by
induction n using Polynomial.Chebyshev.induct with
| zero => rfl
| one => show 2 * X * 1 - X = X; ring
| add_two n ih1 ih2 =>
have h₁ := T_add_two R n
have h₂ := T_sub_two R (-n)
linear_combination (norm := ring_nf) (2 * (X : R[X])) * ih1 - ih2 - h₁ + h₂
| neg_add_one n ih1 ih2 =>
have h₁ := T_add_one R n
have h₂ := T_sub_one R (-n)
linear_combination (norm := ring_nf) (2 * (X : R[X])) * ih1 - ih2 + h₁ - h₂
theorem T_natAbs (n : ℤ) : T R n.natAbs = T R n := by
obtain h | h := Int.natAbs_eq n <;> nth_rw 2 [h]; simp
theorem T_neg_two : T R (-2) = 2 * X ^ 2 - 1 := by simp [T_two]
@[simp]
theorem T_eval_one (n : ℤ) : (T R n).eval 1 = 1 := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp
| one => simp
| add_two n ih1 ih2 => simp [T_add_two, ih1, ih2]; norm_num
| neg_add_one n ih1 ih2 => simp [T_sub_one, -T_neg, ih1, ih2]; norm_num
@[simp]
theorem T_eval_neg_one (n : ℤ) : (T R n).eval (-1) = n.negOnePow := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp
| one => simp
| add_two n ih1 ih2 =>
simp only [T_add_two, eval_sub, eval_mul, eval_ofNat, eval_X, mul_neg, mul_one, ih1,
Int.negOnePow_add, Int.negOnePow_one, Units.val_neg, Int.cast_neg, neg_mul, neg_neg, ih2,
Int.negOnePow_def 2]
norm_cast
norm_num
ring
| neg_add_one n ih1 ih2 =>
simp only [T_sub_one, eval_sub, eval_mul, eval_ofNat, eval_X, mul_neg, mul_one, ih1, neg_mul,
ih2, Int.negOnePow_add, Int.negOnePow_one, Units.val_neg, Int.cast_neg, sub_neg_eq_add,
Int.negOnePow_sub]
ring
/-- `U n` is the `n`-th Chebyshev polynomial of the second kind. -/
-- Well-founded definitions are now irreducible by default;
-- as this was implemented before this change,
-- we just set it back to semireducible to avoid needing to change any proofs.
@[semireducible] noncomputable def U : ℤ → R[X]
| 0 => 1
| 1 => 2 * X
| (n : ℕ) + 2 => 2 * X * U (n + 1) - U n
| -((n : ℕ) + 1) => 2 * X * U (-n) - U (-n + 1)
termination_by n => Int.natAbs n + Int.natAbs (n - 1)
@[simp]
theorem U_add_two : ∀ n, U R (n + 2) = 2 * X * U R (n + 1) - U R n
| (k : ℕ) => U.eq_3 R k
| -(k + 1 : ℕ) => by linear_combination (norm := (simp [Int.negSucc_eq]; ring_nf)) U.eq_4 R k
theorem U_add_one (n : ℤ) : U R (n + 1) = 2 * X * U R n - U R (n - 1) := by
linear_combination (norm := ring_nf) U_add_two R (n - 1)
theorem U_sub_two (n : ℤ) : U R (n - 2) = 2 * X * U R (n - 1) - U R n := by
linear_combination (norm := ring_nf) U_add_two R (n - 2)
theorem U_sub_one (n : ℤ) : U R (n - 1) = 2 * X * U R n - U R (n + 1) := by
linear_combination (norm := ring_nf) U_add_two R (n - 1)
theorem U_eq (n : ℤ) : U R n = 2 * X * U R (n - 1) - U R (n - 2) := by
linear_combination (norm := ring_nf) U_add_two R (n - 2)
@[simp]
theorem U_zero : U R 0 = 1 := rfl
@[simp]
theorem U_one : U R 1 = 2 * X := rfl
@[simp]
theorem U_neg_one : U R (-1) = 0 := by simpa using U_sub_one R 0
theorem U_two : U R 2 = 4 * X ^ 2 - 1 := by
have := U_add_two R 0
simp only [zero_add, U_one, U_zero] at this
linear_combination this
@[simp]
theorem U_neg_two : U R (-2) = -1 := by
simpa [zero_sub, Int.reduceNeg, U_neg_one, mul_zero, U_zero] using U_sub_two R 0
theorem U_neg_sub_one (n : ℤ) : U R (-n - 1) = -U R (n - 1) := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp
| one => simp
| add_two n ih1 ih2 =>
have h₁ := U_add_one R n
have h₂ := U_sub_two R (-n - 1)
linear_combination (norm := ring_nf) 2 * (X : R[X]) * ih1 - ih2 + h₁ + h₂
| neg_add_one n ih1 ih2 =>
have h₁ := U_eq R n
have h₂ := U_sub_two R (-n)
linear_combination (norm := ring_nf) 2 * (X : R[X]) * ih1 - ih2 + h₁ + h₂
theorem U_neg (n : ℤ) : U R (-n) = -U R (n - 2) := by simpa [sub_sub] using U_neg_sub_one R (n - 1)
@[simp]
theorem U_neg_sub_two (n : ℤ) : U R (-n - 2) = -U R n := by
simpa [sub_eq_add_neg, add_comm] using U_neg R (n + 2)
@[simp]
theorem U_eval_one (n : ℤ) : (U R n).eval 1 = n + 1 := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp
| one => simp; norm_num
| add_two n ih1 ih2 =>
simp only [U_add_two, eval_sub, eval_mul, eval_ofNat, eval_X, mul_one, ih1,
Int.cast_add, Int.cast_natCast, Int.cast_one, ih2, Int.cast_ofNat]
ring
| neg_add_one n ih1 ih2 =>
simp only [U_sub_one, eval_sub, eval_mul, eval_ofNat, eval_X, mul_one,
ih1, Int.cast_neg, Int.cast_natCast, ih2, Int.cast_add, Int.cast_one, Int.cast_sub,
sub_add_cancel]
ring
@[simp]
theorem U_eval_neg_one (n : ℤ) : (U R n).eval (-1) = n.negOnePow * (n + 1) := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp
| one => simp; norm_num
| add_two n ih1 ih2 =>
simp only [U_add_two, eval_sub, eval_mul, eval_ofNat, eval_X, mul_neg, mul_one, ih1,
Int.cast_add, Int.cast_natCast, Int.cast_one, neg_mul, ih2, Int.cast_ofNat, Int.negOnePow_add,
Int.negOnePow_def 2]
norm_cast
norm_num
ring
| neg_add_one n ih1 ih2 =>
simp only [U_sub_one, eval_sub, eval_mul, eval_ofNat, eval_X, mul_neg, mul_one, ih1,
Int.cast_neg, Int.cast_natCast, Int.negOnePow_neg, neg_mul, ih2, Int.cast_add, Int.cast_one,
Int.cast_sub, sub_add_cancel, Int.negOnePow_sub, Int.negOnePow_add]
norm_cast
norm_num
ring
theorem U_eq_X_mul_U_add_T (n : ℤ) : U R (n + 1) = X * U R n + T R (n + 1) := by
induction n using Polynomial.Chebyshev.induct with
| zero => simp [two_mul]
| one => simp [U_two, T_two]; ring
| add_two n ih1 ih2 =>
have h₁ := U_add_two R (n + 1)
have h₂ := U_add_two R n
have h₃ := T_add_two R (n + 1)
linear_combination (norm := ring_nf) -h₃ - (X : R[X]) * h₂ + h₁ + 2 * (X : R[X]) * ih1 - ih2
| neg_add_one n ih1 ih2 =>
have h₁ := U_add_two R (-n - 1)
have h₂ := U_add_two R (-n)
have h₃ := T_add_two R (-n)
linear_combination (norm := ring_nf) -h₃ + h₂ - (X : R[X]) * h₁ - ih2 + 2 * (X : R[X]) * ih1
theorem T_eq_U_sub_X_mul_U (n : ℤ) : T R n = U R n - X * U R (n - 1) := by
linear_combination (norm := ring_nf) - U_eq_X_mul_U_add_T R (n - 1)
theorem T_eq_X_mul_T_sub_pol_U (n : ℤ) : T R (n + 2) = X * T R (n + 1) - (1 - X ^ 2) * U R n := by
have h₁ := U_eq_X_mul_U_add_T R n
have h₂ := U_eq_X_mul_U_add_T R (n + 1)
have h₃ := U_add_two R n
linear_combination (norm := ring_nf) h₃ - h₂ + (X : R[X]) * h₁
theorem one_sub_X_sq_mul_U_eq_pol_in_T (n : ℤ) :
(1 - X ^ 2) * U R n = X * T R (n + 1) - T R (n + 2) := by
linear_combination T_eq_X_mul_T_sub_pol_U R n
|
/-- `C n` is the `n`th rescaled Chebyshev polynomial of the first kind (also known as a Vieta–Lucas
polynomial), given by $C_n(2x) = 2T_n(x)$. See `Polynomial.Chebyshev.C_comp_two_mul_X`. -/
@[semireducible] noncomputable def C : ℤ → R[X]
| 0 => 2
| 1 => X
| (n : ℕ) + 2 => X * C (n + 1) - C n
| Mathlib/RingTheory/Polynomial/Chebyshev.lean | 287 | 293 |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Yaël Dillies
-/
import Mathlib.Order.Cover
import Mathlib.Order.Interval.Finset.Defs
/-!
# Intervals as finsets
This file provides basic results about all the `Finset.Ixx`, which are defined in
`Order.Interval.Finset.Defs`.
In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of,
respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly
functions whose domain is a locally finite order. In particular, this file proves:
* `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿`
* `lt_iff_transGen_covBy`: `<` is the transitive closure of `⋖`
* `monotone_iff_forall_wcovBy`: Characterization of monotone functions
* `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions
## TODO
This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to
generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general,
what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure.
Complete the API. See
https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235
for some ideas.
-/
assert_not_exists MonoidWithZero Finset.sum
open Function OrderDual
open FinsetInterval
variable {ι α : Type*} {a a₁ a₂ b b₁ b₂ c x : α}
namespace Finset
section Preorder
variable [Preorder α]
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by
rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Icc_of_le⟩ := nonempty_Icc
@[simp]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ico_of_lt⟩ := nonempty_Ico
@[simp]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioc_of_lt⟩ := nonempty_Ioc
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo]
@[simp]
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff]
@[simp]
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff]
@[simp]
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff]
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff]
alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff
alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff
alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2)
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and, le_rfl]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and, le_refl]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true, le_rfl]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true, le_rfl]
theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1
theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1
theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2
theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2
@[gcongr]
theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by
simpa [← coe_subset] using Set.Icc_subset_Icc ha hb
@[gcongr]
theorem Ico_subset_Ico (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := by
simpa [← coe_subset] using Set.Ico_subset_Ico ha hb
@[gcongr]
theorem Ioc_subset_Ioc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := by
simpa [← coe_subset] using Set.Ioc_subset_Ioc ha hb
@[gcongr]
theorem Ioo_subset_Ioo (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := by
simpa [← coe_subset] using Set.Ioo_subset_Ioo ha hb
@[gcongr]
theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b :=
Icc_subset_Icc h le_rfl
@[gcongr]
theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b :=
Ico_subset_Ico h le_rfl
@[gcongr]
theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b :=
Ioc_subset_Ioc h le_rfl
@[gcongr]
theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b :=
Ioo_subset_Ioo h le_rfl
@[gcongr]
theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ :=
Icc_subset_Icc le_rfl h
@[gcongr]
theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ :=
Ico_subset_Ico le_rfl h
@[gcongr]
theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ :=
Ioc_subset_Ioc le_rfl h
@[gcongr]
theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ :=
Ioo_subset_Ioo le_rfl h
theorem Ico_subset_Ioo_left (h : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := by
rw [← coe_subset, coe_Ico, coe_Ioo]
exact Set.Ico_subset_Ioo_left h
theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := by
rw [← coe_subset, coe_Ioc, coe_Ioo]
exact Set.Ioc_subset_Ioo_right h
theorem Icc_subset_Ico_right (h : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico]
exact Set.Icc_subset_Ico_right h
theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := by
rw [← coe_subset, coe_Ioo, coe_Ico]
exact Set.Ioo_subset_Ico_self
theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := by
rw [← coe_subset, coe_Ioo, coe_Ioc]
exact Set.Ioo_subset_Ioc_self
theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ico, coe_Icc]
exact Set.Ico_subset_Icc_self
theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := by
rw [← coe_subset, coe_Ioc, coe_Icc]
exact Set.Ioc_subset_Icc_self
theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b :=
Ioo_subset_Ico_self.trans Ico_subset_Icc_self
theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ := by
rw [← coe_subset, coe_Icc, coe_Icc, Set.Icc_subset_Icc_iff h₁]
theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ioo, Set.Icc_subset_Ioo_iff h₁]
theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ := by
rw [← coe_subset, coe_Icc, coe_Ico, Set.Icc_subset_Ico_iff h₁]
theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ :=
(Icc_subset_Ico_iff h₁.dual).trans and_comm
--TODO: `Ico_subset_Ioo_iff`, `Ioc_subset_Ioo_iff`
theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_left hI ha hb
theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ := by
rw [← coe_ssubset, coe_Icc, coe_Icc]
exact Set.Icc_ssubset_Icc_right hI ha hb
@[simp]
theorem Ioc_disjoint_Ioc_of_le {d : α} (hbc : b ≤ c) : Disjoint (Ioc a b) (Ioc c d) :=
disjoint_left.2 fun _ h1 h2 ↦ not_and_of_not_left _
((mem_Ioc.1 h1).2.trans hbc).not_lt (mem_Ioc.1 h2)
variable (a)
theorem Ico_self : Ico a a = ∅ :=
Ico_eq_empty <| lt_irrefl _
theorem Ioc_self : Ioc a a = ∅ :=
Ioc_eq_empty <| lt_irrefl _
theorem Ioo_self : Ioo a a = ∅ :=
Ioo_eq_empty <| lt_irrefl _
variable {a}
/-- A set with upper and lower bounds in a locally finite order is a fintype -/
def _root_.Set.fintypeOfMemBounds {s : Set α} [DecidablePred (· ∈ s)] (ha : a ∈ lowerBounds s)
(hb : b ∈ upperBounds s) : Fintype s :=
Set.fintypeSubset (Set.Icc a b) fun _ hx => ⟨ha hx, hb hx⟩
section Filter
theorem Ico_filter_lt_of_le_left [DecidablePred (· < c)] (hca : c ≤ a) :
{x ∈ Ico a b | x < c} = ∅ :=
filter_false_of_mem fun _ hx => (hca.trans (mem_Ico.1 hx).1).not_lt
theorem Ico_filter_lt_of_right_le [DecidablePred (· < c)] (hbc : b ≤ c) :
{x ∈ Ico a b | x < c} = Ico a b :=
filter_true_of_mem fun _ hx => (mem_Ico.1 hx).2.trans_le hbc
theorem Ico_filter_lt_of_le_right [DecidablePred (· < c)] (hcb : c ≤ b) :
{x ∈ Ico a b | x < c} = Ico a c := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_right_comm]
exact and_iff_left_of_imp fun h => h.2.trans_le hcb
theorem Ico_filter_le_of_le_left {a b c : α} [DecidablePred (c ≤ ·)] (hca : c ≤ a) :
{x ∈ Ico a b | c ≤ x} = Ico a b :=
filter_true_of_mem fun _ hx => hca.trans (mem_Ico.1 hx).1
theorem Ico_filter_le_of_right_le {a b : α} [DecidablePred (b ≤ ·)] :
{x ∈ Ico a b | b ≤ x} = ∅ :=
filter_false_of_mem fun _ hx => (mem_Ico.1 hx).2.not_le
theorem Ico_filter_le_of_left_le {a b c : α} [DecidablePred (c ≤ ·)] (hac : a ≤ c) :
{x ∈ Ico a b | c ≤ x} = Ico c b := by
ext x
rw [mem_filter, mem_Ico, mem_Ico, and_comm, and_left_comm]
exact and_iff_right_of_imp fun h => hac.trans h.1
theorem Icc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
{x ∈ Icc a b | x < c} = Icc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Icc.1 hx).2 h
theorem Ioc_filter_lt_of_lt_right {a b c : α} [DecidablePred (· < c)] (h : b < c) :
{x ∈ Ioc a b | x < c} = Ioc a b :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Ioc.1 hx).2 h
theorem Iic_filter_lt_of_lt_right {α} [Preorder α] [LocallyFiniteOrderBot α] {a c : α}
[DecidablePred (· < c)] (h : a < c) : {x ∈ Iic a | x < c} = Iic a :=
filter_true_of_mem fun _ hx => lt_of_le_of_lt (mem_Iic.1 hx) h
variable (a b) [Fintype α]
theorem filter_lt_lt_eq_Ioo [DecidablePred fun j => a < j ∧ j < b] :
({j | a < j ∧ j < b} : Finset _) = Ioo a b := by ext; simp
theorem filter_lt_le_eq_Ioc [DecidablePred fun j => a < j ∧ j ≤ b] :
({j | a < j ∧ j ≤ b} : Finset _) = Ioc a b := by ext; simp
theorem filter_le_lt_eq_Ico [DecidablePred fun j => a ≤ j ∧ j < b] :
({j | a ≤ j ∧ j < b} : Finset _) = Ico a b := by ext; simp
theorem filter_le_le_eq_Icc [DecidablePred fun j => a ≤ j ∧ j ≤ b] :
({j | a ≤ j ∧ j ≤ b} : Finset _) = Icc a b := by ext; simp
end Filter
end LocallyFiniteOrder
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α]
@[simp]
theorem Ioi_eq_empty : Ioi a = ∅ ↔ IsMax a := by
rw [← coe_eq_empty, coe_Ioi, Set.Ioi_eq_empty_iff]
@[simp] alias ⟨_, _root_.IsMax.finsetIoi_eq⟩ := Ioi_eq_empty
@[simp] lemma Ioi_nonempty : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [nonempty_iff_ne_empty]
theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ∅ := Ioi_eq_empty.mpr isMax_top
@[simp]
theorem Ici_bot [OrderBot α] [Fintype α] : Ici (⊥ : α) = univ := by
ext a; simp only [mem_Ici, bot_le, mem_univ]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Ici : (Ici a).Nonempty := ⟨a, mem_Ici.2 le_rfl⟩
lemma nonempty_Ioi : (Ioi a).Nonempty ↔ ¬ IsMax a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioi_of_not_isMax⟩ := nonempty_Ioi
@[simp]
theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a := by
simp [← coe_subset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Ici_subset_Ici⟩ := Ici_subset_Ici
@[simp]
theorem Ici_ssubset_Ici : Ici a ⊂ Ici b ↔ b < a := by
simp [← coe_ssubset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Ici_ssubset_Ici⟩ := Ici_ssubset_Ici
@[gcongr]
theorem Ioi_subset_Ioi (h : a ≤ b) : Ioi b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioi_subset_Ioi h
@[gcongr]
theorem Ioi_ssubset_Ioi (h : a < b) : Ioi b ⊂ Ioi a := by
simpa [← coe_ssubset] using Set.Ioi_ssubset_Ioi h
variable [LocallyFiniteOrder α]
theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Icc_subset_Ici_self
theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := by
simpa [← coe_subset] using Set.Ico_subset_Ici_self
theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioc_subset_Ioi_self
theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := by
simpa [← coe_subset] using Set.Ioo_subset_Ioi_self
theorem Ioc_subset_Ici_self : Ioc a b ⊆ Ici a :=
Ioc_subset_Icc_self.trans Icc_subset_Ici_self
theorem Ioo_subset_Ici_self : Ioo a b ⊆ Ici a :=
Ioo_subset_Ico_self.trans Ico_subset_Ici_self
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α]
@[simp]
theorem Iio_eq_empty : Iio a = ∅ ↔ IsMin a := Ioi_eq_empty (α := αᵒᵈ)
@[simp] alias ⟨_, _root_.IsMin.finsetIio_eq⟩ := Iio_eq_empty
@[simp] lemma Iio_nonempty : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [nonempty_iff_ne_empty]
theorem Iio_bot [OrderBot α] : Iio (⊥ : α) = ∅ := Iio_eq_empty.mpr isMin_bot
@[simp]
theorem Iic_top [OrderTop α] [Fintype α] : Iic (⊤ : α) = univ := by
ext a; simp only [mem_Iic, le_top, mem_univ]
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma nonempty_Iic : (Iic a).Nonempty := ⟨a, mem_Iic.2 le_rfl⟩
lemma nonempty_Iio : (Iio a).Nonempty ↔ ¬ IsMin a := by simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Iio_of_not_isMin⟩ := nonempty_Iio
@[simp]
theorem Iic_subset_Iic : Iic a ⊆ Iic b ↔ a ≤ b := by
simp [← coe_subset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Iic_subset_Iic⟩ := Iic_subset_Iic
@[simp]
theorem Iic_ssubset_Iic : Iic a ⊂ Iic b ↔ a < b := by
simp [← coe_ssubset]
@[gcongr]
alias ⟨_, _root_.GCongr.Finset.Iic_ssubset_Iic⟩ := Iic_ssubset_Iic
@[gcongr]
theorem Iio_subset_Iio (h : a ≤ b) : Iio a ⊆ Iio b := by
simpa [← coe_subset] using Set.Iio_subset_Iio h
@[gcongr]
theorem Iio_ssubset_Iio (h : a < b) : Iio a ⊂ Iio b := by
simpa [← coe_ssubset] using Set.Iio_ssubset_Iio h
variable [LocallyFiniteOrder α]
theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Icc_subset_Iic_self
theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := by
simpa [← coe_subset] using Set.Ioc_subset_Iic_self
theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ico_subset_Iio_self
theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := by
simpa [← coe_subset] using Set.Ioo_subset_Iio_self
theorem Ico_subset_Iic_self : Ico a b ⊆ Iic b :=
Ico_subset_Icc_self.trans Icc_subset_Iic_self
theorem Ioo_subset_Iic_self : Ioo a b ⊆ Iic b :=
Ioo_subset_Ioc_self.trans Ioc_subset_Iic_self
theorem Iic_disjoint_Ioc (h : a ≤ b) : Disjoint (Iic a) (Ioc b c) :=
disjoint_left.2 fun _ hax hbcx ↦ (mem_Iic.1 hax).not_lt <| lt_of_le_of_lt h (mem_Ioc.1 hbcx).1
/-- An equivalence between `Finset.Iic a` and `Set.Iic a`. -/
def _root_.Equiv.IicFinsetSet (a : α) : Iic a ≃ Set.Iic a where
toFun b := ⟨b.1, coe_Iic a ▸ mem_coe.2 b.2⟩
invFun b := ⟨b.1, by rw [← mem_coe, coe_Iic a]; exact b.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end LocallyFiniteOrderBot
section LocallyFiniteOrderTop
variable [LocallyFiniteOrderTop α] {a : α}
theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := by
simpa [← coe_subset] using Set.Ioi_subset_Ici_self
theorem _root_.BddBelow.finite {s : Set α} (hs : BddBelow s) : s.Finite :=
let ⟨a, ha⟩ := hs
(Ici a).finite_toSet.subset fun _ hx => mem_Ici.2 <| ha hx
theorem _root_.Set.Infinite.not_bddBelow {s : Set α} : s.Infinite → ¬BddBelow s :=
mt BddBelow.finite
variable [Fintype α]
theorem filter_lt_eq_Ioi [DecidablePred (a < ·)] : ({x | a < x} : Finset _) = Ioi a := by ext; simp
theorem filter_le_eq_Ici [DecidablePred (a ≤ ·)] : ({x | a ≤ x} : Finset _) = Ici a := by ext; simp
end LocallyFiniteOrderTop
section LocallyFiniteOrderBot
variable [LocallyFiniteOrderBot α] {a : α}
theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := by
simpa [← coe_subset] using Set.Iio_subset_Iic_self
theorem _root_.BddAbove.finite {s : Set α} (hs : BddAbove s) : s.Finite :=
hs.dual.finite
theorem _root_.Set.Infinite.not_bddAbove {s : Set α} : s.Infinite → ¬BddAbove s :=
mt BddAbove.finite
variable [Fintype α]
theorem filter_gt_eq_Iio [DecidablePred (· < a)] : ({x | x < a} : Finset _) = Iio a := by ext; simp
theorem filter_ge_eq_Iic [DecidablePred (· ≤ a)] : ({x | x ≤ a} : Finset _) = Iic a := by ext; simp
end LocallyFiniteOrderBot
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem Icc_bot [OrderBot α] : Icc (⊥ : α) a = Iic a := rfl
@[simp]
theorem Icc_top [OrderTop α] : Icc a (⊤ : α) = Ici a := rfl
@[simp]
theorem Ico_bot [OrderBot α] : Ico (⊥ : α) a = Iio a := rfl
@[simp]
theorem Ioc_top [OrderTop α] : Ioc a (⊤ : α) = Ioi a := rfl
theorem Icc_bot_top [BoundedOrder α] [Fintype α] : Icc (⊥ : α) (⊤ : α) = univ := by
rw [Icc_bot, Iic_top]
end LocallyFiniteOrder
variable [LocallyFiniteOrderTop α] [LocallyFiniteOrderBot α]
theorem disjoint_Ioi_Iio (a : α) : Disjoint (Ioi a) (Iio a) :=
disjoint_left.2 fun _ hab hba => (mem_Ioi.1 hab).not_lt <| mem_Iio.1 hba
end Preorder
section PartialOrder
variable [PartialOrder α] [LocallyFiniteOrder α] {a b c : α}
@[simp]
theorem Icc_self (a : α) : Icc a a = {a} := by rw [← coe_eq_singleton, coe_Icc, Set.Icc_self]
@[simp]
theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by
rw [← coe_eq_singleton, coe_Icc, Set.Icc_eq_singleton_iff]
theorem Ico_disjoint_Ico_consecutive (a b c : α) : Disjoint (Ico a b) (Ico b c) :=
disjoint_left.2 fun _ hab hbc => (mem_Ico.mp hab).2.not_le (mem_Ico.mp hbc).1
@[simp]
theorem Ici_top [OrderTop α] : Ici (⊤ : α) = {⊤} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩
@[simp]
theorem Iic_bot [OrderBot α] : Iic (⊥ : α) = {⊥} := Icc_eq_singleton_iff.2 ⟨rfl, rfl⟩
section DecidableEq
variable [DecidableEq α]
@[simp]
theorem Icc_erase_left (a b : α) : (Icc a b).erase a = Ioc a b := by simp [← coe_inj]
@[simp]
theorem Icc_erase_right (a b : α) : (Icc a b).erase b = Ico a b := by simp [← coe_inj]
@[simp]
theorem Ico_erase_left (a b : α) : (Ico a b).erase a = Ioo a b := by simp [← coe_inj]
@[simp]
theorem Ioc_erase_right (a b : α) : (Ioc a b).erase b = Ioo a b := by simp [← coe_inj]
@[simp]
theorem Icc_diff_both (a b : α) : Icc a b \ {a, b} = Ioo a b := by simp [← coe_inj]
@[simp]
theorem Ico_insert_right (h : a ≤ b) : insert b (Ico a b) = Icc a b := by
rw [← coe_inj, coe_insert, coe_Icc, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ico_union_right h]
@[simp]
theorem Ioc_insert_left (h : a ≤ b) : insert a (Ioc a b) = Icc a b := by
rw [← coe_inj, coe_insert, coe_Ioc, coe_Icc, Set.insert_eq, Set.union_comm, Set.Ioc_union_left h]
@[simp]
theorem Ioo_insert_left (h : a < b) : insert a (Ioo a b) = Ico a b := by
rw [← coe_inj, coe_insert, coe_Ioo, coe_Ico, Set.insert_eq, Set.union_comm, Set.Ioo_union_left h]
@[simp]
theorem Ioo_insert_right (h : a < b) : insert b (Ioo a b) = Ioc a b := by
rw [← coe_inj, coe_insert, coe_Ioo, coe_Ioc, Set.insert_eq, Set.union_comm, Set.Ioo_union_right h]
@[simp]
theorem Icc_diff_Ico_self (h : a ≤ b) : Icc a b \ Ico a b = {b} := by simp [← coe_inj, h]
@[simp]
theorem Icc_diff_Ioc_self (h : a ≤ b) : Icc a b \ Ioc a b = {a} := by simp [← coe_inj, h]
@[simp]
theorem Icc_diff_Ioo_self (h : a ≤ b) : Icc a b \ Ioo a b = {a, b} := by simp [← coe_inj, h]
@[simp]
theorem Ico_diff_Ioo_self (h : a < b) : Ico a b \ Ioo a b = {a} := by simp [← coe_inj, h]
@[simp]
theorem Ioc_diff_Ioo_self (h : a < b) : Ioc a b \ Ioo a b = {b} := by simp [← coe_inj, h]
@[simp]
theorem Ico_inter_Ico_consecutive (a b c : α) : Ico a b ∩ Ico b c = ∅ :=
(Ico_disjoint_Ico_consecutive a b c).eq_bot
end DecidableEq
-- Those lemmas are purposefully the other way around
/-- `Finset.cons` version of `Finset.Ico_insert_right`. -/
theorem Icc_eq_cons_Ico (h : a ≤ b) : Icc a b = (Ico a b).cons b right_not_mem_Ico := by
classical rw [cons_eq_insert, Ico_insert_right h]
/-- `Finset.cons` version of `Finset.Ioc_insert_left`. -/
theorem Icc_eq_cons_Ioc (h : a ≤ b) : Icc a b = (Ioc a b).cons a left_not_mem_Ioc := by
classical rw [cons_eq_insert, Ioc_insert_left h]
/-- `Finset.cons` version of `Finset.Ioo_insert_right`. -/
theorem Ioc_eq_cons_Ioo (h : a < b) : Ioc a b = (Ioo a b).cons b right_not_mem_Ioo := by
classical rw [cons_eq_insert, Ioo_insert_right h]
/-- `Finset.cons` version of `Finset.Ioo_insert_left`. -/
theorem Ico_eq_cons_Ioo (h : a < b) : Ico a b = (Ioo a b).cons a left_not_mem_Ioo := by
classical rw [cons_eq_insert, Ioo_insert_left h]
theorem Ico_filter_le_left {a b : α} [DecidablePred (· ≤ a)] (hab : a < b) :
{x ∈ Ico a b | x ≤ a} = {a} := by
ext x
rw [mem_filter, mem_Ico, mem_singleton, and_right_comm, ← le_antisymm_iff, eq_comm]
exact and_iff_left_of_imp fun h => h.le.trans_lt hab
theorem card_Ico_eq_card_Icc_sub_one (a b : α) : #(Ico a b) = #(Icc a b) - 1 := by
classical
by_cases h : a ≤ b
· rw [Icc_eq_cons_Ico h, card_cons]
exact (Nat.add_sub_cancel _ _).symm
| · rw [Ico_eq_empty fun h' => h h'.le, Icc_eq_empty h, card_empty, Nat.zero_sub]
theorem card_Ioc_eq_card_Icc_sub_one (a b : α) : #(Ioc a b) = #(Icc a b) - 1 :=
@card_Ico_eq_card_Icc_sub_one αᵒᵈ _ _ _ _
| Mathlib/Order/Interval/Finset/Basic.lean | 644 | 648 |
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.LinearAlgebra.AffineSpace.Independent
import Mathlib.LinearAlgebra.AffineSpace.Pointwise
import Mathlib.LinearAlgebra.Basis.SMul
/-!
# Affine bases and barycentric coordinates
Suppose `P` is an affine space modelled on the module `V` over the ring `k`, and `p : ι → P` is an
affine-independent family of points spanning `P`. Given this data, each point `q : P` may be written
uniquely as an affine combination: `q = w₀ p₀ + w₁ p₁ + ⋯` for some (finitely-supported) weights
`wᵢ`. For each `i : ι`, we thus have an affine map `P →ᵃ[k] k`, namely `q ↦ wᵢ`. This family of
maps is known as the family of barycentric coordinates. It is defined in this file.
## The construction
Fixing `i : ι`, and allowing `j : ι` to range over the values `j ≠ i`, we obtain a basis `bᵢ` of `V`
defined by `bᵢ j = p j -ᵥ p i`. Let `fᵢ j : V →ₗ[k] k` be the corresponding dual basis and let
`fᵢ = ∑ j, fᵢ j : V →ₗ[k] k` be the corresponding "sum of all coordinates" form. Then the `i`th
barycentric coordinate of `q : P` is `1 - fᵢ (q -ᵥ p i)`.
## Main definitions
* `AffineBasis`: a structure representing an affine basis of an affine space.
* `AffineBasis.coord`: the map `P →ᵃ[k] k` corresponding to `i : ι`.
* `AffineBasis.coord_apply_eq`: the behaviour of `AffineBasis.coord i` on `p i`.
* `AffineBasis.coord_apply_ne`: the behaviour of `AffineBasis.coord i` on `p j` when `j ≠ i`.
* `AffineBasis.coord_apply`: the behaviour of `AffineBasis.coord i` on `p j` for general `j`.
* `AffineBasis.coord_apply_combination`: the characterisation of `AffineBasis.coord i` in terms
of affine combinations, i.e., `AffineBasis.coord i (w₀ p₀ + w₁ p₁ + ⋯) = wᵢ`.
## TODO
* Construct the affine equivalence between `P` and `{ f : ι →₀ k | f.sum = 1 }`.
-/
open Affine Set
open scoped Pointwise
universe u₁ u₂ u₃ u₄
/-- An affine basis is a family of affine-independent points whose span is the top subspace. -/
structure AffineBasis (ι : Type u₁) (k : Type u₂) {V : Type u₃} (P : Type u₄) [AddCommGroup V]
[AffineSpace V P] [Ring k] [Module k V] where
protected toFun : ι → P
protected ind' : AffineIndependent k toFun
protected tot' : affineSpan k (range toFun) = ⊤
variable {ι ι' G G' k V P : Type*} [AddCommGroup V] [AffineSpace V P]
namespace AffineBasis
section Ring
variable [Ring k] [Module k V] (b : AffineBasis ι k P) {s : Finset ι} {i j : ι} (e : ι ≃ ι')
/-- The unique point in a single-point space is the simplest example of an affine basis. -/
instance : Inhabited (AffineBasis PUnit k PUnit) :=
⟨⟨id, affineIndependent_of_subsingleton k id, by simp⟩⟩
instance instFunLike : FunLike (AffineBasis ι k P) ι P where
coe := AffineBasis.toFun
coe_injective' f g h := by cases f; cases g; congr
@[ext]
theorem ext {b₁ b₂ : AffineBasis ι k P} (h : (b₁ : ι → P) = b₂) : b₁ = b₂ :=
DFunLike.coe_injective h
theorem ind : AffineIndependent k b :=
b.ind'
theorem tot : affineSpan k (range b) = ⊤ :=
b.tot'
include b in
protected theorem nonempty : Nonempty ι :=
not_isEmpty_iff.mp fun hι => by
simpa only [@range_eq_empty _ _ hι, AffineSubspace.span_empty, bot_ne_top] using b.tot
/-- Composition of an affine basis and an equivalence of index types. -/
def reindex (e : ι ≃ ι') : AffineBasis ι' k P :=
⟨b ∘ e.symm, b.ind.comp_embedding e.symm.toEmbedding, by
| rw [e.symm.surjective.range_comp]
exact b.3⟩
| Mathlib/LinearAlgebra/AffineSpace/Basis.lean | 88 | 90 |
/-
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.Order.Group.Finset
import Mathlib.Algebra.Polynomial.Derivative
import Mathlib.Algebra.Polynomial.Eval.SMul
import Mathlib.Algebra.Polynomial.Roots
import Mathlib.RingTheory.EuclideanDomain
import Mathlib.RingTheory.UniqueFactorizationDomain.NormalizedFactors
/-!
# Theory of univariate polynomials
This file starts looking like the ring theory of $R[X]$
-/
noncomputable section
open Polynomial
namespace Polynomial
universe u v w y z
variable {R : Type u} {S : Type v} {k : Type y} {A : Type z} {a b : R} {n : ℕ}
section CommRing
variable [CommRing R]
theorem rootMultiplicity_sub_one_le_derivative_rootMultiplicity_of_ne_zero
(p : R[X]) (t : R) (hnezero : derivative p ≠ 0) :
p.rootMultiplicity t - 1 ≤ p.derivative.rootMultiplicity t :=
(le_rootMultiplicity_iff hnezero).2 <|
pow_sub_one_dvd_derivative_of_pow_dvd (p.pow_rootMultiplicity_dvd t)
theorem derivative_rootMultiplicity_of_root_of_mem_nonZeroDivisors
{p : R[X]} {t : R} (hpt : Polynomial.IsRoot p t)
(hnzd : (p.rootMultiplicity t : R) ∈ nonZeroDivisors R) :
(derivative p).rootMultiplicity t = p.rootMultiplicity t - 1 := by
by_cases h : p = 0
· simp only [h, map_zero, rootMultiplicity_zero]
obtain ⟨g, hp, hndvd⟩ := p.exists_eq_pow_rootMultiplicity_mul_and_not_dvd h t
set m := p.rootMultiplicity t
have hm : m - 1 + 1 = m := Nat.sub_add_cancel <| (rootMultiplicity_pos h).2 hpt
have hndvd : ¬(X - C t) ^ m ∣ derivative p := by
rw [hp, derivative_mul, dvd_add_left (dvd_mul_right _ _),
derivative_X_sub_C_pow, ← hm, pow_succ, hm, mul_comm (C _), mul_assoc,
dvd_cancel_left_mem_nonZeroDivisors (monic_X_sub_C t |>.pow _ |>.mem_nonZeroDivisors)]
rw [dvd_iff_isRoot, IsRoot] at hndvd ⊢
rwa [eval_mul, eval_C, mul_left_mem_nonZeroDivisors_eq_zero_iff hnzd]
have hnezero : derivative p ≠ 0 := fun h ↦ hndvd (by rw [h]; exact dvd_zero _)
exact le_antisymm (by rwa [rootMultiplicity_le_iff hnezero, hm])
(rootMultiplicity_sub_one_le_derivative_rootMultiplicity_of_ne_zero _ t hnezero)
theorem isRoot_iterate_derivative_of_lt_rootMultiplicity {p : R[X]} {t : R} {n : ℕ}
(hn : n < p.rootMultiplicity t) : (derivative^[n] p).IsRoot t :=
dvd_iff_isRoot.mp <| (dvd_pow_self _ <| Nat.sub_ne_zero_of_lt hn).trans
(pow_sub_dvd_iterate_derivative_of_pow_dvd _ <| p.pow_rootMultiplicity_dvd t)
open Finset in
theorem eval_iterate_derivative_rootMultiplicity {p : R[X]} {t : R} :
(derivative^[p.rootMultiplicity t] p).eval t =
(p.rootMultiplicity t).factorial • (p /ₘ (X - C t) ^ p.rootMultiplicity t).eval t := by
set m := p.rootMultiplicity t with hm
conv_lhs => rw [← p.pow_mul_divByMonic_rootMultiplicity_eq t, ← hm]
rw [iterate_derivative_mul, eval_finset_sum, sum_eq_single_of_mem _ (mem_range.mpr m.succ_pos)]
· rw [m.choose_zero_right, one_smul, eval_mul, m.sub_zero, iterate_derivative_X_sub_pow_self,
eval_natCast, nsmul_eq_mul]; rfl
· intro b hb hb0
rw [iterate_derivative_X_sub_pow, eval_smul, eval_mul, eval_smul, eval_pow,
Nat.sub_sub_self (mem_range_succ_iff.mp hb), eval_sub, eval_X, eval_C, sub_self,
zero_pow hb0, smul_zero, zero_mul, smul_zero]
theorem lt_rootMultiplicity_of_isRoot_iterate_derivative_of_mem_nonZeroDivisors
{p : R[X]} {t : R} {n : ℕ} (h : p ≠ 0)
(hroot : ∀ m ≤ n, (derivative^[m] p).IsRoot t)
(hnzd : (n.factorial : R) ∈ nonZeroDivisors R) :
n < p.rootMultiplicity t := by
by_contra! h'
replace hroot := hroot _ h'
simp only [IsRoot, eval_iterate_derivative_rootMultiplicity] at hroot
obtain ⟨q, hq⟩ := Nat.cast_dvd_cast (α := R) <| Nat.factorial_dvd_factorial h'
rw [hq, mul_mem_nonZeroDivisors] at hnzd
rw [nsmul_eq_mul, mul_left_mem_nonZeroDivisors_eq_zero_iff hnzd.1] at hroot
exact eval_divByMonic_pow_rootMultiplicity_ne_zero t h hroot
theorem lt_rootMultiplicity_of_isRoot_iterate_derivative_of_mem_nonZeroDivisors'
{p : R[X]} {t : R} {n : ℕ} (h : p ≠ 0)
(hroot : ∀ m ≤ n, (derivative^[m] p).IsRoot t)
(hnzd : ∀ m ≤ n, m ≠ 0 → (m : R) ∈ nonZeroDivisors R) :
n < p.rootMultiplicity t := by
apply lt_rootMultiplicity_of_isRoot_iterate_derivative_of_mem_nonZeroDivisors h hroot
clear hroot
induction n with
| zero =>
simp only [Nat.factorial_zero, Nat.cast_one]
exact Submonoid.one_mem _
| succ n ih =>
rw [Nat.factorial_succ, Nat.cast_mul, mul_mem_nonZeroDivisors]
exact ⟨hnzd _ le_rfl n.succ_ne_zero, ih fun m h ↦ hnzd m (h.trans n.le_succ)⟩
theorem lt_rootMultiplicity_iff_isRoot_iterate_derivative_of_mem_nonZeroDivisors
{p : R[X]} {t : R} {n : ℕ} (h : p ≠ 0)
(hnzd : (n.factorial : R) ∈ nonZeroDivisors R) :
n < p.rootMultiplicity t ↔ ∀ m ≤ n, (derivative^[m] p).IsRoot t :=
⟨fun hn _ hm ↦ isRoot_iterate_derivative_of_lt_rootMultiplicity <| hm.trans_lt hn,
fun hr ↦ lt_rootMultiplicity_of_isRoot_iterate_derivative_of_mem_nonZeroDivisors h hr hnzd⟩
theorem lt_rootMultiplicity_iff_isRoot_iterate_derivative_of_mem_nonZeroDivisors'
{p : R[X]} {t : R} {n : ℕ} (h : p ≠ 0)
(hnzd : ∀ m ≤ n, m ≠ 0 → (m : R) ∈ nonZeroDivisors R) :
n < p.rootMultiplicity t ↔ ∀ m ≤ n, (derivative^[m] p).IsRoot t :=
⟨fun hn _ hm ↦ isRoot_iterate_derivative_of_lt_rootMultiplicity <| Nat.lt_of_le_of_lt hm hn,
fun hr ↦ lt_rootMultiplicity_of_isRoot_iterate_derivative_of_mem_nonZeroDivisors' h hr hnzd⟩
theorem one_lt_rootMultiplicity_iff_isRoot_iterate_derivative
{p : R[X]} {t : R} (h : p ≠ 0) :
1 < p.rootMultiplicity t ↔ ∀ m ≤ 1, (derivative^[m] p).IsRoot t :=
lt_rootMultiplicity_iff_isRoot_iterate_derivative_of_mem_nonZeroDivisors h
(by rw [Nat.factorial_one, Nat.cast_one]; exact Submonoid.one_mem _)
theorem one_lt_rootMultiplicity_iff_isRoot
{p : R[X]} {t : R} (h : p ≠ 0) :
1 < p.rootMultiplicity t ↔ p.IsRoot t ∧ (derivative p).IsRoot t := by
rw [one_lt_rootMultiplicity_iff_isRoot_iterate_derivative h]
refine ⟨fun h ↦ ⟨h 0 (by norm_num), h 1 (by norm_num)⟩, fun ⟨h0, h1⟩ m hm ↦ ?_⟩
obtain (_|_|m) := m
exacts [h0, h1, by omega]
end CommRing
section IsDomain
variable [CommRing R] [IsDomain R]
theorem one_lt_rootMultiplicity_iff_isRoot_gcd
[GCDMonoid R[X]] {p : R[X]} {t : R} (h : p ≠ 0) :
1 < p.rootMultiplicity t ↔ (gcd p (derivative p)).IsRoot t := by
simp_rw [one_lt_rootMultiplicity_iff_isRoot h, ← dvd_iff_isRoot, dvd_gcd_iff]
theorem derivative_rootMultiplicity_of_root [CharZero R] {p : R[X]} {t : R} (hpt : p.IsRoot t) :
p.derivative.rootMultiplicity t = p.rootMultiplicity t - 1 := by
by_cases h : p = 0
· rw [h, map_zero, rootMultiplicity_zero]
exact derivative_rootMultiplicity_of_root_of_mem_nonZeroDivisors hpt <|
mem_nonZeroDivisors_of_ne_zero <| Nat.cast_ne_zero.2 ((rootMultiplicity_pos h).2 hpt).ne'
theorem rootMultiplicity_sub_one_le_derivative_rootMultiplicity [CharZero R] (p : R[X]) (t : R) :
p.rootMultiplicity t - 1 ≤ p.derivative.rootMultiplicity t := by
by_cases h : p.IsRoot t
· exact (derivative_rootMultiplicity_of_root h).symm.le
· rw [rootMultiplicity_eq_zero h, zero_tsub]
exact zero_le _
theorem lt_rootMultiplicity_of_isRoot_iterate_derivative
[CharZero R] {p : R[X]} {t : R} {n : ℕ} (h : p ≠ 0)
(hroot : ∀ m ≤ n, (derivative^[m] p).IsRoot t) :
n < p.rootMultiplicity t :=
lt_rootMultiplicity_of_isRoot_iterate_derivative_of_mem_nonZeroDivisors h hroot <|
mem_nonZeroDivisors_of_ne_zero <| Nat.cast_ne_zero.2 <| Nat.factorial_ne_zero n
theorem lt_rootMultiplicity_iff_isRoot_iterate_derivative
[CharZero R] {p : R[X]} {t : R} {n : ℕ} (h : p ≠ 0) :
n < p.rootMultiplicity t ↔ ∀ m ≤ n, (derivative^[m] p).IsRoot t :=
⟨fun hn _ hm ↦ isRoot_iterate_derivative_of_lt_rootMultiplicity <| Nat.lt_of_le_of_lt hm hn,
fun hr ↦ lt_rootMultiplicity_of_isRoot_iterate_derivative h hr⟩
/-- A sufficient condition for the set of roots of a nonzero polynomial `f` to be a subset of the
set of roots of `g` is that `f` divides `f.derivative * g`. Over an algebraically closed field of
characteristic zero, this is also a necessary condition.
See `isRoot_of_isRoot_iff_dvd_derivative_mul` -/
theorem isRoot_of_isRoot_of_dvd_derivative_mul [CharZero R] {f g : R[X]} (hf0 : f ≠ 0)
(hfd : f ∣ f.derivative * g) {a : R} (haf : f.IsRoot a) : g.IsRoot a := by
rcases hfd with ⟨r, hr⟩
have hdf0 : derivative f ≠ 0 := by
contrapose! haf
rw [eq_C_of_derivative_eq_zero haf] at hf0 ⊢
exact not_isRoot_C _ _ <| C_ne_zero.mp hf0
by_contra hg
have hdfg0 : f.derivative * g ≠ 0 := mul_ne_zero hdf0 (by rintro rfl; simp at hg)
have hr' := congr_arg (rootMultiplicity a) hr
rw [rootMultiplicity_mul hdfg0, derivative_rootMultiplicity_of_root haf,
rootMultiplicity_eq_zero hg, add_zero, rootMultiplicity_mul (hr ▸ hdfg0), add_comm,
Nat.sub_eq_iff_eq_add (Nat.succ_le_iff.2 ((rootMultiplicity_pos hf0).2 haf))] at hr'
omega
section NormalizationMonoid
variable [NormalizationMonoid R]
instance instNormalizationMonoid : NormalizationMonoid R[X] where
normUnit p :=
⟨C ↑(normUnit p.leadingCoeff), C ↑(normUnit p.leadingCoeff)⁻¹, by
rw [← RingHom.map_mul, Units.mul_inv, C_1], by rw [← RingHom.map_mul, Units.inv_mul, C_1]⟩
normUnit_zero := Units.ext (by simp)
normUnit_mul hp0 hq0 :=
Units.ext
(by
dsimp
rw [Ne, ← leadingCoeff_eq_zero] at *
rw [leadingCoeff_mul, normUnit_mul hp0 hq0, Units.val_mul, C_mul])
normUnit_coe_units u :=
Units.ext
(by
dsimp
rw [← mul_one u⁻¹, Units.val_mul, Units.eq_inv_mul_iff_mul_eq]
rcases Polynomial.isUnit_iff.1 ⟨u, rfl⟩ with ⟨_, ⟨w, rfl⟩, h2⟩
rw [← h2, leadingCoeff_C, normUnit_coe_units, ← C_mul, Units.mul_inv, C_1]
rfl)
@[simp]
theorem coe_normUnit {p : R[X]} : (normUnit p : R[X]) = C ↑(normUnit p.leadingCoeff) := by
simp [normUnit]
@[simp]
theorem leadingCoeff_normalize (p : R[X]) :
leadingCoeff (normalize p) = normalize (leadingCoeff p) := by simp [normalize_apply]
theorem Monic.normalize_eq_self {p : R[X]} (hp : p.Monic) : normalize p = p := by
simp only [Polynomial.coe_normUnit, normalize_apply, hp.leadingCoeff, normUnit_one,
Units.val_one, Polynomial.C.map_one, mul_one]
theorem roots_normalize {p : R[X]} : (normalize p).roots = p.roots := by
rw [normalize_apply, mul_comm, coe_normUnit, roots_C_mul _ (normUnit (leadingCoeff p)).ne_zero]
theorem normUnit_X : normUnit (X : Polynomial R) = 1 := by
have := coe_normUnit (R := R) (p := X)
rwa [leadingCoeff_X, normUnit_one, Units.val_one, map_one, Units.val_eq_one] at this
theorem X_eq_normalize : (X : Polynomial R) = normalize X := by
simp only [normalize_apply, normUnit_X, Units.val_one, mul_one]
end NormalizationMonoid
end IsDomain
section DivisionRing
variable [DivisionRing R] {p q : R[X]}
theorem degree_pos_of_ne_zero_of_nonunit (hp0 : p ≠ 0) (hp : ¬IsUnit p) : 0 < degree p :=
lt_of_not_ge fun h => by
rw [eq_C_of_degree_le_zero h] at hp0 hp
exact hp (IsUnit.map C (IsUnit.mk0 (coeff p 0) (mt C_inj.2 (by simpa using hp0))))
@[simp]
protected theorem map_eq_zero [Semiring S] [Nontrivial S] (f : R →+* S) : p.map f = 0 ↔ p = 0 := by
simp only [Polynomial.ext_iff]
congr!
simp [map_eq_zero, coeff_map, coeff_zero]
theorem map_ne_zero [Semiring S] [Nontrivial S] {f : R →+* S} (hp : p ≠ 0) : p.map f ≠ 0 :=
mt (Polynomial.map_eq_zero f).1 hp
@[simp]
theorem degree_map [Semiring S] [Nontrivial S] (p : R[X]) (f : R →+* S) :
degree (p.map f) = degree p :=
p.degree_map_eq_of_injective f.injective
@[simp]
theorem natDegree_map [Semiring S] [Nontrivial S] (f : R →+* S) :
natDegree (p.map f) = natDegree p :=
natDegree_eq_of_degree_eq (degree_map _ f)
@[simp]
theorem leadingCoeff_map [Semiring S] [Nontrivial S] (f : R →+* S) :
leadingCoeff (p.map f) = f (leadingCoeff p) := by
simp only [← coeff_natDegree, coeff_map f, natDegree_map]
theorem monic_map_iff [Semiring S] [Nontrivial S] {f : R →+* S} {p : R[X]} :
(p.map f).Monic ↔ p.Monic := by
rw [Monic, leadingCoeff_map, ← f.map_one, Function.Injective.eq_iff f.injective, Monic]
end DivisionRing
section Field
variable [Field R] {p q : R[X]}
theorem isUnit_iff_degree_eq_zero : IsUnit p ↔ degree p = 0 :=
⟨degree_eq_zero_of_isUnit, fun h =>
have : degree p ≤ 0 := by simp [*, le_refl]
have hc : coeff p 0 ≠ 0 := fun hc => by
rw [eq_C_of_degree_le_zero this, hc] at h; simp only [map_zero] at h; contradiction
isUnit_iff_dvd_one.2
⟨C (coeff p 0)⁻¹, by
conv in p => rw [eq_C_of_degree_le_zero this]
rw [← C_mul, mul_inv_cancel₀ hc, C_1]⟩⟩
/-- Division of polynomials. See `Polynomial.divByMonic` for more details. -/
def div (p q : R[X]) :=
C (leadingCoeff q)⁻¹ * (p /ₘ (q * C (leadingCoeff q)⁻¹))
/-- Remainder of polynomial division. See `Polynomial.modByMonic` for more details. -/
def mod (p q : R[X]) :=
p %ₘ (q * C (leadingCoeff q)⁻¹)
private theorem quotient_mul_add_remainder_eq_aux (p q : R[X]) : q * div p q + mod p q = p := by
by_cases h : q = 0
· simp only [h, zero_mul, mod, modByMonic_zero, zero_add]
· conv =>
rhs
rw [← modByMonic_add_div p (monic_mul_leadingCoeff_inv h)]
rw [div, mod, add_comm, mul_assoc]
private theorem remainder_lt_aux (p : R[X]) (hq : q ≠ 0) : degree (mod p q) < degree q := by
rw [← degree_mul_leadingCoeff_inv q hq]
exact degree_modByMonic_lt p (monic_mul_leadingCoeff_inv hq)
instance : Div R[X] :=
⟨div⟩
instance : Mod R[X] :=
⟨mod⟩
theorem div_def : p / q = C (leadingCoeff q)⁻¹ * (p /ₘ (q * C (leadingCoeff q)⁻¹)) :=
rfl
theorem mod_def : p % q = p %ₘ (q * C (leadingCoeff q)⁻¹) := rfl
theorem modByMonic_eq_mod (p : R[X]) (hq : Monic q) : p %ₘ q = p % q :=
show p %ₘ q = p %ₘ (q * C (leadingCoeff q)⁻¹) by
simp only [Monic.def.1 hq, inv_one, mul_one, C_1]
theorem divByMonic_eq_div (p : R[X]) (hq : Monic q) : p /ₘ q = p / q :=
show p /ₘ q = C (leadingCoeff q)⁻¹ * (p /ₘ (q * C (leadingCoeff q)⁻¹)) by
simp only [Monic.def.1 hq, inv_one, C_1, one_mul, mul_one]
theorem mod_X_sub_C_eq_C_eval (p : R[X]) (a : R) : p % (X - C a) = C (p.eval a) :=
modByMonic_eq_mod p (monic_X_sub_C a) ▸ modByMonic_X_sub_C_eq_C_eval _ _
theorem mul_div_eq_iff_isRoot : (X - C a) * (p / (X - C a)) = p ↔ IsRoot p a :=
divByMonic_eq_div p (monic_X_sub_C a) ▸ mul_divByMonic_eq_iff_isRoot
instance instEuclideanDomain : EuclideanDomain R[X] :=
{ Polynomial.commRing,
Polynomial.nontrivial with
quotient := (· / ·)
quotient_zero := by simp [div_def]
remainder := (· % ·)
r := _
r_wellFounded := degree_lt_wf
quotient_mul_add_remainder_eq := quotient_mul_add_remainder_eq_aux
remainder_lt := fun _ _ hq => remainder_lt_aux _ hq
mul_left_not_lt := fun _ _ hq => not_lt_of_ge (degree_le_mul_left _ hq) }
theorem mod_eq_self_iff (hq0 : q ≠ 0) : p % q = p ↔ degree p < degree q :=
⟨fun h => h ▸ EuclideanDomain.mod_lt _ hq0, fun h => by
classical
have : ¬degree (q * C (leadingCoeff q)⁻¹) ≤ degree p :=
not_le_of_gt <| by rwa [degree_mul_leadingCoeff_inv q hq0]
rw [mod_def, modByMonic, dif_pos (monic_mul_leadingCoeff_inv hq0)]
unfold divModByMonicAux
dsimp
simp only [this, false_and, if_false]⟩
theorem div_eq_zero_iff (hq0 : q ≠ 0) : p / q = 0 ↔ degree p < degree q :=
⟨fun h => by
have := EuclideanDomain.div_add_mod p q
rwa [h, mul_zero, zero_add, mod_eq_self_iff hq0] at this,
fun h => by
have hlt : degree p < degree (q * C (leadingCoeff q)⁻¹) := by
rwa [degree_mul_leadingCoeff_inv q hq0]
have hm : Monic (q * C (leadingCoeff q)⁻¹) := monic_mul_leadingCoeff_inv hq0
rw [div_def, (divByMonic_eq_zero_iff hm).2 hlt, mul_zero]⟩
theorem degree_add_div (hq0 : q ≠ 0) (hpq : degree q ≤ degree p) :
degree q + degree (p / q) = degree p := by
have : degree (p % q) < degree (q * (p / q)) :=
calc
degree (p % q) < degree q := EuclideanDomain.mod_lt _ hq0
_ ≤ _ := degree_le_mul_left _ (mt (div_eq_zero_iff hq0).1 (not_lt_of_ge hpq))
conv_rhs =>
rw [← EuclideanDomain.div_add_mod p q, degree_add_eq_left_of_degree_lt this, degree_mul]
theorem degree_div_le (p q : R[X]) : degree (p / q) ≤ degree p := by
by_cases hq : q = 0
· simp [hq]
· rw [div_def, mul_comm, degree_mul_leadingCoeff_inv _ hq]; exact degree_divByMonic_le _ _
theorem degree_div_lt (hp : p ≠ 0) (hq : 0 < degree q) : degree (p / q) < degree p := by
have hq0 : q ≠ 0 := fun hq0 => by simp [hq0] at hq
rw [div_def, mul_comm, degree_mul_leadingCoeff_inv _ hq0]
exact degree_divByMonic_lt _ (monic_mul_leadingCoeff_inv hq0) hp
(by rw [degree_mul_leadingCoeff_inv _ hq0]; exact hq)
theorem isUnit_map [Field k] (f : R →+* k) : IsUnit (p.map f) ↔ IsUnit p := by
simp_rw [isUnit_iff_degree_eq_zero, degree_map]
theorem map_div [Field k] (f : R →+* k) : (p / q).map f = p.map f / q.map f := by
if hq0 : q = 0 then simp [hq0]
else
rw [div_def, div_def, Polynomial.map_mul, map_divByMonic f (monic_mul_leadingCoeff_inv hq0),
Polynomial.map_mul, map_C, leadingCoeff_map, map_inv₀]
theorem map_mod [Field k] (f : R →+* k) : (p % q).map f = p.map f % q.map f := by
by_cases hq0 : q = 0
· simp [hq0]
· rw [mod_def, mod_def, leadingCoeff_map f, ← map_inv₀ f, ← map_C f, ← Polynomial.map_mul f,
map_modByMonic f (monic_mul_leadingCoeff_inv hq0)]
lemma natDegree_mod_lt [Field k] (p : k[X]) {q : k[X]} (hq : q.natDegree ≠ 0) :
(p % q).natDegree < q.natDegree := by
have hq' : q.leadingCoeff ≠ 0 := by
rw [leadingCoeff_ne_zero]
contrapose! hq
simp [hq]
rw [mod_def]
refine (natDegree_modByMonic_lt p ?_ ?_).trans_le ?_
· refine monic_mul_C_of_leadingCoeff_mul_eq_one ?_
rw [mul_inv_eq_one₀ hq']
· contrapose! hq
rw [← natDegree_mul_C_eq_of_mul_eq_one ((inv_mul_eq_one₀ hq').mpr rfl)]
simp [hq]
· exact natDegree_mul_C_le q q.leadingCoeff⁻¹
section
open EuclideanDomain
theorem gcd_map [Field k] [DecidableEq R] [DecidableEq k] (f : R →+* k) :
gcd (p.map f) (q.map f) = (gcd p q).map f :=
| GCD.induction p q (fun x => by simp_rw [Polynomial.map_zero, EuclideanDomain.gcd_zero_left])
fun x y _ ih => by rw [gcd_val, ← map_mod, ih, ← gcd_val]
end
| Mathlib/Algebra/Polynomial/FieldDivision.lean | 429 | 433 |
/-
Copyright (c) 2024 Geoffrey Irving. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Geoffrey Irving
-/
import Mathlib.Analysis.Analytic.Composition
import Mathlib.Analysis.Analytic.Constructions
import Mathlib.Analysis.Complex.CauchyIntegral
import Mathlib.Analysis.SpecialFunctions.Complex.LogDeriv
/-!
# Various complex special functions are analytic
`log`, and `cpow` are analytic, since they are differentiable.
-/
open Complex Set
open scoped Topology
variable {E : Type} [NormedAddCommGroup E] [NormedSpace ℂ E]
variable {f g : E → ℂ} {z : ℂ} {x : E} {s : Set E}
/-- `log` is analytic away from nonpositive reals -/
@[fun_prop]
theorem analyticAt_clog (m : z ∈ slitPlane) : AnalyticAt ℂ log z := by
rw [analyticAt_iff_eventually_differentiableAt]
filter_upwards [isOpen_slitPlane.eventually_mem m]
intro z m
exact differentiableAt_id.clog m
/-- `log` is analytic away from nonpositive reals -/
@[fun_prop]
theorem AnalyticAt.clog (fa : AnalyticAt ℂ f x) (m : f x ∈ slitPlane) :
AnalyticAt ℂ (fun z ↦ log (f z)) x :=
(analyticAt_clog m).comp fa
theorem AnalyticWithinAt.clog (fa : AnalyticWithinAt ℂ f s x) (m : f x ∈ slitPlane) :
AnalyticWithinAt ℂ (fun z ↦ log (f z)) s x :=
(analyticAt_clog m).comp_analyticWithinAt fa
/-- `log` is analytic away from nonpositive reals -/
theorem AnalyticOnNhd.clog (fs : AnalyticOnNhd ℂ f s) (m : ∀ z ∈ s, f z ∈ slitPlane) :
AnalyticOnNhd ℂ (fun z ↦ log (f z)) s :=
fun z n ↦ (analyticAt_clog (m z n)).comp (fs z n)
theorem AnalyticOn.clog (fs : AnalyticOn ℂ f s) (m : ∀ z ∈ s, f z ∈ slitPlane) :
AnalyticOn ℂ (fun z ↦ log (f z)) s :=
fun z n ↦ (analyticAt_clog (m z n)).analyticWithinAt.comp (fs z n) m
/-- `f z ^ g z` is analytic if `f z` is not a nonpositive real -/
theorem AnalyticWithinAt.cpow (fa : AnalyticWithinAt ℂ f s x) (ga : AnalyticWithinAt ℂ g s x)
(m : f x ∈ slitPlane) : AnalyticWithinAt ℂ (fun z ↦ f z ^ g z) s x := by
have e : (fun z ↦ f z ^ g z) =ᶠ[𝓝[insert x s] x] fun z ↦ exp (log (f z) * g z) := by
filter_upwards [(fa.continuousWithinAt_insert.eventually_ne (slitPlane_ne_zero m))]
intro z fz
simp only [fz, cpow_def, if_false]
| apply AnalyticWithinAt.congr_of_eventuallyEq_insert _ e
exact ((fa.clog m).mul ga).cexp
/-- `f z ^ g z` is analytic if `f z` is not a nonpositive real -/
@[fun_prop]
theorem AnalyticAt.cpow (fa : AnalyticAt ℂ f x) (ga : AnalyticAt ℂ g x)
(m : f x ∈ slitPlane) : AnalyticAt ℂ (fun z ↦ f z ^ g z) x := by
rw [← analyticWithinAt_univ] at fa ga ⊢
| Mathlib/Analysis/SpecialFunctions/Complex/Analytic.lean | 57 | 64 |
/-
Copyright (c) 2021 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.AffineScheme
import Mathlib.RingTheory.LocalProperties.Reduced
/-!
# Basic properties of schemes
We provide some basic properties of schemes
## Main definition
* `AlgebraicGeometry.IsIntegral`: A scheme is integral if it is nontrivial and all nontrivial
components of the structure sheaf are integral domains.
* `AlgebraicGeometry.IsReduced`: A scheme is reduced if all the components of the structure sheaf
are reduced.
-/
-- Explicit universe annotations were used in this file to improve performance https://github.com/leanprover-community/mathlib4/issues/12737
universe u
open TopologicalSpace Opposite CategoryTheory CategoryTheory.Limits TopCat Topology
namespace AlgebraicGeometry
variable (X : Scheme)
instance : T0Space X :=
T0Space.of_open_cover fun x => ⟨_, X.affineCover.covers x,
(X.affineCover.map x).opensRange.2, IsEmbedding.t0Space (Y := PrimeSpectrum _)
(isAffineOpen_opensRange (X.affineCover.map x)).isoSpec.schemeIsoToHomeo.isEmbedding⟩
instance : QuasiSober X := by
apply (config := { allowSynthFailures := true })
quasiSober_of_open_cover (Set.range fun x => Set.range <| (X.affineCover.map x).base)
· rintro ⟨_, i, rfl⟩; exact (X.affineCover.map_prop i).base_open.isOpen_range
· rintro ⟨_, i, rfl⟩
exact @IsOpenEmbedding.quasiSober _ _ _ _ _
(X.affineCover.map_prop i).base_open.isEmbedding.toHomeomorph.symm.isOpenEmbedding
PrimeSpectrum.quasiSober
· rw [Set.top_eq_univ, Set.sUnion_range, Set.eq_univ_iff_forall]
intro x; exact ⟨_, ⟨_, rfl⟩, X.affineCover.covers x⟩
instance {X : Scheme.{u}} : PrespectralSpace X :=
have (Y : Scheme.{u}) (_ : IsAffine Y) : PrespectralSpace Y :=
.of_isClosedEmbedding (Y := PrimeSpectrum _) _
Y.isoSpec.hom.homeomorph.isClosedEmbedding
have (i) : PrespectralSpace (X.affineCover.map i).opensRange.1 :=
this (X.affineCover.map i).opensRange (isAffineOpen_opensRange (X.affineCover.map i))
.of_isOpenCover X.affineCover.isOpenCover_opensRange
/-- A scheme `X` is reduced if all `𝒪ₓ(U)` are reduced. -/
class IsReduced : Prop where
component_reduced : ∀ U, _root_.IsReduced Γ(X, U) := by infer_instance
attribute [instance] IsReduced.component_reduced
|
theorem isReduced_of_isReduced_stalk [∀ x : X, _root_.IsReduced (X.presheaf.stalk x)] :
IsReduced X := by
refine ⟨fun U => ⟨fun s hs => ?_⟩⟩
apply Presheaf.section_ext X.sheaf U s 0
intro x hx
show (X.sheaf.presheaf.germ U x hx) s = (X.sheaf.presheaf.germ U x hx) 0
rw [RingHom.map_zero]
| Mathlib/AlgebraicGeometry/Properties.lean | 61 | 68 |
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.ShortComplex.Homology
/-!
# Quasi-isomorphisms of short complexes
This file introduces the typeclass `QuasiIso φ` for a morphism `φ : S₁ ⟶ S₂`
of short complexes (which have homology): the condition is that the induced
morphism `homologyMap φ` in homology is an isomorphism.
-/
namespace CategoryTheory
open Category Limits
namespace ShortComplex
variable {C : Type _} [Category C] [HasZeroMorphisms C]
{S₁ S₂ S₃ S₄ : ShortComplex C}
[S₁.HasHomology] [S₂.HasHomology] [S₃.HasHomology] [S₄.HasHomology]
/-- A morphism `φ : S₁ ⟶ S₂` of short complexes that have homology is a quasi-isomorphism if
the induced map `homologyMap φ : S₁.homology ⟶ S₂.homology` is an isomorphism. -/
class QuasiIso (φ : S₁ ⟶ S₂) : Prop where
/-- the homology map is an isomorphism -/
isIso' : IsIso (homologyMap φ)
instance QuasiIso.isIso (φ : S₁ ⟶ S₂) [QuasiIso φ] : IsIso (homologyMap φ) := QuasiIso.isIso'
lemma quasiIso_iff (φ : S₁ ⟶ S₂) :
QuasiIso φ ↔ IsIso (homologyMap φ) := by
constructor
· intro h
infer_instance
· intro h
exact ⟨h⟩
instance quasiIso_of_isIso (φ : S₁ ⟶ S₂) [IsIso φ] : QuasiIso φ :=
⟨(homologyMapIso (asIso φ)).isIso_hom⟩
instance quasiIso_comp (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃) [hφ : QuasiIso φ] [hφ' : QuasiIso φ'] :
QuasiIso (φ ≫ φ') := by
rw [quasiIso_iff] at hφ hφ' ⊢
rw [homologyMap_comp]
infer_instance
lemma quasiIso_of_comp_left (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃)
[hφ : QuasiIso φ] [hφφ' : QuasiIso (φ ≫ φ')] :
QuasiIso φ' := by
rw [quasiIso_iff] at hφ hφφ' ⊢
rw [homologyMap_comp] at hφφ'
exact IsIso.of_isIso_comp_left (homologyMap φ) (homologyMap φ')
lemma quasiIso_iff_comp_left (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃) [hφ : QuasiIso φ] :
QuasiIso (φ ≫ φ') ↔ QuasiIso φ' := by
constructor
· intro
exact quasiIso_of_comp_left φ φ'
· intro
exact quasiIso_comp φ φ'
lemma quasiIso_of_comp_right (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃)
[hφ' : QuasiIso φ'] [hφφ' : QuasiIso (φ ≫ φ')] :
QuasiIso φ := by
rw [quasiIso_iff] at hφ' hφφ' ⊢
rw [homologyMap_comp] at hφφ'
exact IsIso.of_isIso_comp_right (homologyMap φ) (homologyMap φ')
lemma quasiIso_iff_comp_right (φ : S₁ ⟶ S₂) (φ' : S₂ ⟶ S₃) [hφ' : QuasiIso φ'] :
QuasiIso (φ ≫ φ') ↔ QuasiIso φ := by
constructor
· intro
exact quasiIso_of_comp_right φ φ'
· intro
exact quasiIso_comp φ φ'
| lemma quasiIso_of_arrow_mk_iso (φ : S₁ ⟶ S₂) (φ' : S₃ ⟶ S₄) (e : Arrow.mk φ ≅ Arrow.mk φ')
[hφ : QuasiIso φ] : QuasiIso φ' := by
let α : S₃ ⟶ S₁ := e.inv.left
let β : S₂ ⟶ S₄ := e.hom.right
suffices φ' = α ≫ φ ≫ β by
rw [this]
infer_instance
simp only [α, β, Arrow.w_mk_right_assoc, Arrow.mk_left, Arrow.mk_right, Arrow.mk_hom,
← Arrow.comp_right, e.inv_hom_id, Arrow.id_right, comp_id]
| Mathlib/Algebra/Homology/ShortComplex/QuasiIso.lean | 83 | 91 |
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.FieldTheory.Finiteness
import Mathlib.LinearAlgebra.AffineSpace.Basis
import Mathlib.LinearAlgebra.FiniteDimensional.Lemmas
/-!
# Finite-dimensional subspaces of affine spaces.
This file provides a few results relating to finite-dimensional
subspaces of affine spaces.
## Main definitions
* `Collinear` defines collinear sets of points as those that span a
subspace of dimension at most 1.
-/
noncomputable section
open Affine
open scoped Finset
section AffineSpace'
variable (k : Type*) {V : Type*} {P : Type*}
variable {ι : Type*}
open AffineSubspace Module
variable [DivisionRing k] [AddCommGroup V] [Module k V] [AffineSpace V P]
/-- The `vectorSpan` of a finite set is finite-dimensional. -/
theorem finiteDimensional_vectorSpan_of_finite {s : Set P} (h : Set.Finite s) :
FiniteDimensional k (vectorSpan k s) :=
.span_of_finite k <| h.vsub h
/-- The vector span of a singleton is finite-dimensional. -/
instance finiteDimensional_vectorSpan_singleton (p : P) :
FiniteDimensional k (vectorSpan k {p}) :=
finiteDimensional_vectorSpan_of_finite _ (Set.finite_singleton p)
/-- The `vectorSpan` of a family indexed by a `Fintype` is
finite-dimensional. -/
instance finiteDimensional_vectorSpan_range [Finite ι] (p : ι → P) :
FiniteDimensional k (vectorSpan k (Set.range p)) :=
finiteDimensional_vectorSpan_of_finite k (Set.finite_range _)
/-- The `vectorSpan` of a subset of a family indexed by a `Fintype`
is finite-dimensional. -/
instance finiteDimensional_vectorSpan_image_of_finite [Finite ι] (p : ι → P) (s : Set ι) :
FiniteDimensional k (vectorSpan k (p '' s)) :=
finiteDimensional_vectorSpan_of_finite k (Set.toFinite _)
/-- The direction of the affine span of a finite set is
finite-dimensional. -/
theorem finiteDimensional_direction_affineSpan_of_finite {s : Set P} (h : Set.Finite s) :
FiniteDimensional k (affineSpan k s).direction :=
(direction_affineSpan k s).symm ▸ finiteDimensional_vectorSpan_of_finite k h
/-- The direction of the affine span of a singleton is finite-dimensional. -/
instance finiteDimensional_direction_affineSpan_singleton (p : P) :
FiniteDimensional k (affineSpan k {p}).direction := by
rw [direction_affineSpan]
infer_instance
/-- The direction of the affine span of a family indexed by a
`Fintype` is finite-dimensional. -/
instance finiteDimensional_direction_affineSpan_range [Finite ι] (p : ι → P) :
FiniteDimensional k (affineSpan k (Set.range p)).direction :=
finiteDimensional_direction_affineSpan_of_finite k (Set.finite_range _)
/-- The direction of the affine span of a subset of a family indexed
by a `Fintype` is finite-dimensional. -/
instance finiteDimensional_direction_affineSpan_image_of_finite [Finite ι] (p : ι → P) (s : Set ι) :
FiniteDimensional k (affineSpan k (p '' s)).direction :=
finiteDimensional_direction_affineSpan_of_finite k (Set.toFinite _)
/-- An affine-independent family of points in a finite-dimensional affine space is finite. -/
theorem finite_of_fin_dim_affineIndependent [FiniteDimensional k V] {p : ι → P}
(hi : AffineIndependent k p) : Finite ι := by
nontriviality ι; inhabit ι
rw [affineIndependent_iff_linearIndependent_vsub k p default] at hi
letI : IsNoetherian k V := IsNoetherian.iff_fg.2 inferInstance
exact
(Set.finite_singleton default).finite_of_compl (Set.finite_coe_iff.1 hi.finite_of_isNoetherian)
/-- An affine-independent subset of a finite-dimensional affine space is finite. -/
theorem finite_set_of_fin_dim_affineIndependent [FiniteDimensional k V] {s : Set ι} {f : s → P}
(hi : AffineIndependent k f) : s.Finite :=
@Set.toFinite _ s (finite_of_fin_dim_affineIndependent k hi)
variable {k}
/-- The `vectorSpan` of a finite subset of an affinely independent
family has dimension one less than its cardinality. -/
theorem AffineIndependent.finrank_vectorSpan_image_finset [DecidableEq P]
{p : ι → P} (hi : AffineIndependent k p) {s : Finset ι} {n : ℕ} (hc : #s = n + 1) :
finrank k (vectorSpan k (s.image p : Set P)) = n := by
classical
have hi' := hi.range.mono (Set.image_subset_range p ↑s)
have hc' : #(s.image p) = n + 1 := by rwa [s.card_image_of_injective hi.injective]
have hn : (s.image p).Nonempty := by simp [hc', ← Finset.card_pos]
rcases hn with ⟨p₁, hp₁⟩
have hp₁' : p₁ ∈ p '' s := by simpa using hp₁
rw [affineIndependent_set_iff_linearIndependent_vsub k hp₁', ← Finset.coe_singleton,
← Finset.coe_image, ← Finset.coe_sdiff, Finset.sdiff_singleton_eq_erase, ← Finset.coe_image]
at hi'
have hc : #(((s.image p).erase p₁).image (· -ᵥ p₁)) = n := by
rw [Finset.card_image_of_injective _ (vsub_left_injective _), Finset.card_erase_of_mem hp₁]
exact Nat.pred_eq_of_eq_succ hc'
rwa [vectorSpan_eq_span_vsub_finset_right_ne k hp₁, finrank_span_finset_eq_card, hc]
/-- The `vectorSpan` of a finite affinely independent family has
dimension one less than its cardinality. -/
theorem AffineIndependent.finrank_vectorSpan [Fintype ι] {p : ι → P} (hi : AffineIndependent k p)
{n : ℕ} (hc : Fintype.card ι = n + 1) : finrank k (vectorSpan k (Set.range p)) = n := by
classical
rw [← Finset.card_univ] at hc
rw [← Set.image_univ, ← Finset.coe_univ, ← Finset.coe_image]
exact hi.finrank_vectorSpan_image_finset hc
/-- The `vectorSpan` of a finite affinely independent family has dimension one less than its
cardinality. -/
lemma AffineIndependent.finrank_vectorSpan_add_one [Fintype ι] [Nonempty ι] {p : ι → P}
(hi : AffineIndependent k p) : finrank k (vectorSpan k (Set.range p)) + 1 = Fintype.card ι := by
rw [hi.finrank_vectorSpan (tsub_add_cancel_of_le _).symm, tsub_add_cancel_of_le] <;>
exact Fintype.card_pos
/-- The `vectorSpan` of a finite affinely independent family whose
cardinality is one more than that of the finite-dimensional space is
`⊤`. -/
theorem AffineIndependent.vectorSpan_eq_top_of_card_eq_finrank_add_one [FiniteDimensional k V]
[Fintype ι] {p : ι → P} (hi : AffineIndependent k p) (hc : Fintype.card ι = finrank k V + 1) :
vectorSpan k (Set.range p) = ⊤ :=
Submodule.eq_top_of_finrank_eq <| hi.finrank_vectorSpan hc
variable (k)
/-- The `vectorSpan` of `n + 1` points in an indexed family has
dimension at most `n`. -/
theorem finrank_vectorSpan_image_finset_le [DecidableEq P] (p : ι → P) (s : Finset ι) {n : ℕ}
(hc : #s = n + 1) : finrank k (vectorSpan k (s.image p : Set P)) ≤ n := by
classical
have hn : (s.image p).Nonempty := by
rw [Finset.image_nonempty, ← Finset.card_pos, hc]
apply Nat.succ_pos
rcases hn with ⟨p₁, hp₁⟩
rw [vectorSpan_eq_span_vsub_finset_right_ne k hp₁]
refine le_trans (finrank_span_finset_le_card (((s.image p).erase p₁).image fun p => p -ᵥ p₁)) ?_
rw [Finset.card_image_of_injective _ (vsub_left_injective p₁), Finset.card_erase_of_mem hp₁,
tsub_le_iff_right, ← hc]
apply Finset.card_image_le
/-- The `vectorSpan` of an indexed family of `n + 1` points has
dimension at most `n`. -/
theorem finrank_vectorSpan_range_le [Fintype ι] (p : ι → P) {n : ℕ} (hc : Fintype.card ι = n + 1) :
finrank k (vectorSpan k (Set.range p)) ≤ n := by
classical
rw [← Set.image_univ, ← Finset.coe_univ, ← Finset.coe_image]
rw [← Finset.card_univ] at hc
exact finrank_vectorSpan_image_finset_le _ _ _ hc
/-- The `vectorSpan` of an indexed family of `n + 1` points has dimension at most `n`. -/
lemma finrank_vectorSpan_range_add_one_le [Fintype ι] [Nonempty ι] (p : ι → P) :
finrank k (vectorSpan k (Set.range p)) + 1 ≤ Fintype.card ι :=
(le_tsub_iff_right <| Nat.succ_le_iff.2 Fintype.card_pos).1 <| finrank_vectorSpan_range_le _ _
(tsub_add_cancel_of_le <| Nat.succ_le_iff.2 Fintype.card_pos).symm
/-- `n + 1` points are affinely independent if and only if their
`vectorSpan` has dimension `n`. -/
theorem affineIndependent_iff_finrank_vectorSpan_eq [Fintype ι] (p : ι → P) {n : ℕ}
(hc : Fintype.card ι = n + 1) :
AffineIndependent k p ↔ finrank k (vectorSpan k (Set.range p)) = n := by
classical
have hn : Nonempty ι := by simp [← Fintype.card_pos_iff, hc]
obtain ⟨i₁⟩ := hn
rw [affineIndependent_iff_linearIndependent_vsub _ _ i₁,
linearIndependent_iff_card_eq_finrank_span, eq_comm,
vectorSpan_range_eq_span_range_vsub_right_ne k p i₁, Set.finrank]
rw [← Finset.card_univ] at hc
rw [Fintype.subtype_card]
simp [Finset.filter_ne', Finset.card_erase_of_mem, hc]
/-- `n + 1` points are affinely independent if and only if their
`vectorSpan` has dimension at least `n`. -/
theorem affineIndependent_iff_le_finrank_vectorSpan [Fintype ι] (p : ι → P) {n : ℕ}
(hc : Fintype.card ι = n + 1) :
AffineIndependent k p ↔ n ≤ finrank k (vectorSpan k (Set.range p)) := by
rw [affineIndependent_iff_finrank_vectorSpan_eq k p hc]
| constructor
· rintro rfl
rfl
· exact fun hle => le_antisymm (finrank_vectorSpan_range_le k p hc) hle
/-- `n + 2` points are affinely independent if and only if their
`vectorSpan` does not have dimension at most `n`. -/
theorem affineIndependent_iff_not_finrank_vectorSpan_le [Fintype ι] (p : ι → P) {n : ℕ}
| Mathlib/LinearAlgebra/AffineSpace/FiniteDimensional.lean | 196 | 203 |
/-
Copyright (c) 2020 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou
-/
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Support
import Mathlib.Data.Set.SymmDiff
/-!
# Indicator function
- `Set.indicator (s : Set α) (f : α → β) (a : α)` is `f a` if `a ∈ s` and is `0` otherwise.
- `Set.mulIndicator (s : Set α) (f : α → β) (a : α)` is `f a` if `a ∈ s` and is `1` otherwise.
## Implementation note
In mathematics, an indicator function or a characteristic function is a function
used to indicate membership of an element in a set `s`,
having the value `1` for all elements of `s` and the value `0` otherwise.
But since it is usually used to restrict a function to a certain set `s`,
we let the indicator function take the value `f x` for some function `f`, instead of `1`.
If the usual indicator function is needed, just set `f` to be the constant function `fun _ ↦ 1`.
The indicator function is implemented non-computably, to avoid having to pass around `Decidable`
arguments. This is in contrast with the design of `Pi.single` or `Set.piecewise`.
## Tags
indicator, characteristic
-/
assert_not_exists MonoidWithZero
open Function
variable {α β M N : Type*}
namespace Set
section One
variable [One M] [One N] {s t : Set α} {f g : α → M} {a : α}
/-- `Set.mulIndicator s f a` is `f a` if `a ∈ s`, `1` otherwise. -/
@[to_additive "`Set.indicator s f a` is `f a` if `a ∈ s`, `0` otherwise."]
noncomputable def mulIndicator (s : Set α) (f : α → M) (x : α) : M :=
haveI := Classical.decPred (· ∈ s)
if x ∈ s then f x else 1
@[to_additive (attr := simp)]
theorem piecewise_eq_mulIndicator [DecidablePred (· ∈ s)] : s.piecewise f 1 = s.mulIndicator f :=
funext fun _ => @if_congr _ _ _ _ (id _) _ _ _ _ Iff.rfl rfl rfl
@[to_additive]
theorem mulIndicator_apply (s : Set α) (f : α → M) (a : α) [Decidable (a ∈ s)] :
mulIndicator s f a = if a ∈ s then f a else 1 := by
unfold mulIndicator
congr
@[to_additive (attr := simp)]
theorem mulIndicator_of_mem (h : a ∈ s) (f : α → M) : mulIndicator s f a = f a :=
if_pos h
@[to_additive (attr := simp)]
theorem mulIndicator_of_not_mem (h : a ∉ s) (f : α → M) : mulIndicator s f a = 1 :=
if_neg h
@[to_additive]
theorem mulIndicator_eq_one_or_self (s : Set α) (f : α → M) (a : α) :
mulIndicator s f a = 1 ∨ mulIndicator s f a = f a := by
by_cases h : a ∈ s
· exact Or.inr (mulIndicator_of_mem h f)
· exact Or.inl (mulIndicator_of_not_mem h f)
@[to_additive (attr := simp)]
theorem mulIndicator_apply_eq_self : s.mulIndicator f a = f a ↔ a ∉ s → f a = 1 :=
letI := Classical.dec (a ∈ s)
ite_eq_left_iff.trans (by rw [@eq_comm _ (f a)])
@[to_additive (attr := simp)]
theorem mulIndicator_eq_self : s.mulIndicator f = f ↔ mulSupport f ⊆ s := by
simp only [funext_iff, subset_def, mem_mulSupport, mulIndicator_apply_eq_self, not_imp_comm]
@[to_additive]
theorem mulIndicator_eq_self_of_superset (h1 : s.mulIndicator f = f) (h2 : s ⊆ t) :
t.mulIndicator f = f := by
rw [mulIndicator_eq_self] at h1 ⊢
exact Subset.trans h1 h2
@[to_additive (attr := simp)]
theorem mulIndicator_apply_eq_one : mulIndicator s f a = 1 ↔ a ∈ s → f a = 1 :=
letI := Classical.dec (a ∈ s)
ite_eq_right_iff
@[to_additive (attr := simp)]
theorem mulIndicator_eq_one : (mulIndicator s f = fun _ => 1) ↔ Disjoint (mulSupport f) s := by
simp only [funext_iff, mulIndicator_apply_eq_one, Set.disjoint_left, mem_mulSupport,
not_imp_not]
@[to_additive (attr := simp)]
theorem mulIndicator_eq_one' : mulIndicator s f = 1 ↔ Disjoint (mulSupport f) s :=
| mulIndicator_eq_one
@[to_additive]
theorem mulIndicator_apply_ne_one {a : α} : s.mulIndicator f a ≠ 1 ↔ a ∈ s ∩ mulSupport f := by
| Mathlib/Algebra/Group/Indicator.lean | 103 | 106 |
/-
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
-/
import Mathlib.Combinatorics.SimpleGraph.Dart
import Mathlib.Data.FunLike.Fintype
import Mathlib.Logic.Embedding.Set
/-!
# Maps between graphs
This file defines two functions and three structures relating graphs.
The structures directly correspond to the classification of functions as
injective, surjective and bijective, and have corresponding notation.
## Main definitions
* `SimpleGraph.map`: the graph obtained by pushing the adjacency relation through
an injective function between vertex types.
* `SimpleGraph.comap`: the graph obtained by pulling the adjacency relation behind
an arbitrary function between vertex types.
* `SimpleGraph.induce`: the subgraph induced by the given vertex set, a wrapper around `comap`.
* `SimpleGraph.spanningCoe`: the supergraph without any additional edges, a wrapper around `map`.
* `SimpleGraph.Hom`, `G →g H`: a graph homomorphism from `G` to `H`.
* `SimpleGraph.Embedding`, `G ↪g H`: a graph embedding of `G` in `H`.
* `SimpleGraph.Iso`, `G ≃g H`: a graph isomorphism between `G` and `H`.
Note that a graph embedding is a stronger notion than an injective graph homomorphism,
since its image is an induced subgraph.
## Implementation notes
Morphisms of graphs are abbreviations for `RelHom`, `RelEmbedding` and `RelIso`.
To make use of pre-existing simp lemmas, definitions involving morphisms are
abbreviations as well.
-/
open Function
namespace SimpleGraph
variable {V W X : Type*} (G : SimpleGraph V) (G' : SimpleGraph W) {u v : V}
/-! ## Map and comap -/
/-- Given an injective function, there is a covariant induced map on graphs by pushing forward
the adjacency relation.
This is injective (see `SimpleGraph.map_injective`). -/
protected def map (f : V ↪ W) (G : SimpleGraph V) : SimpleGraph W where
Adj := Relation.Map G.Adj f f
symm a b := by -- Porting note: `obviously` used to handle this
rintro ⟨v, w, h, rfl, rfl⟩
use w, v, h.symm, rfl
loopless a := by -- Porting note: `obviously` used to handle this
rintro ⟨v, w, h, rfl, h'⟩
exact h.ne (f.injective h'.symm)
instance instDecidableMapAdj {f : V ↪ W} {a b} [Decidable (Relation.Map G.Adj f f a b)] :
Decidable ((G.map f).Adj a b) := ‹Decidable (Relation.Map G.Adj f f a b)›
@[simp]
theorem map_adj (f : V ↪ W) (G : SimpleGraph V) (u v : W) :
(G.map f).Adj u v ↔ ∃ u' v' : V, G.Adj u' v' ∧ f u' = u ∧ f v' = v :=
Iff.rfl
lemma map_adj_apply {G : SimpleGraph V} {f : V ↪ W} {a b : V} :
(G.map f).Adj (f a) (f b) ↔ G.Adj a b := by simp
theorem map_monotone (f : V ↪ W) : Monotone (SimpleGraph.map f) := by
rintro G G' h _ _ ⟨u, v, ha, rfl, rfl⟩
exact ⟨_, _, h ha, rfl, rfl⟩
@[simp] lemma map_id : G.map (Function.Embedding.refl _) = G :=
SimpleGraph.ext <| Relation.map_id_id _
@[simp] lemma map_map (f : V ↪ W) (g : W ↪ X) : (G.map f).map g = G.map (f.trans g) :=
SimpleGraph.ext <| Relation.map_map _ _ _ _ _
/-- Given a function, there is a contravariant induced map on graphs by pulling back the
adjacency relation.
This is one of the ways of creating induced graphs. See `SimpleGraph.induce` for a wrapper.
This is surjective when `f` is injective (see `SimpleGraph.comap_surjective`). -/
protected def comap (f : V → W) (G : SimpleGraph W) : SimpleGraph V where
Adj u v := G.Adj (f u) (f v)
symm _ _ h := h.symm
loopless _ := G.loopless _
@[simp] lemma comap_adj {G : SimpleGraph W} {f : V → W} :
(G.comap f).Adj u v ↔ G.Adj (f u) (f v) := Iff.rfl
@[simp] lemma comap_id {G : SimpleGraph V} : G.comap id = G := SimpleGraph.ext rfl
@[simp] lemma comap_comap {G : SimpleGraph X} (f : V → W) (g : W → X) :
(G.comap g).comap f = G.comap (g ∘ f) := rfl
instance instDecidableComapAdj (f : V → W) (G : SimpleGraph W) [DecidableRel G.Adj] :
DecidableRel (G.comap f).Adj := fun _ _ ↦ ‹DecidableRel G.Adj› _ _
lemma comap_symm (G : SimpleGraph V) (e : V ≃ W) :
G.comap e.symm.toEmbedding = G.map e.toEmbedding := by
ext; simp only [Equiv.apply_eq_iff_eq_symm_apply, comap_adj, map_adj, Equiv.toEmbedding_apply,
exists_eq_right_right, exists_eq_right]
lemma map_symm (G : SimpleGraph W) (e : V ≃ W) :
G.map e.symm.toEmbedding = G.comap e.toEmbedding := by rw [← comap_symm, e.symm_symm]
theorem comap_monotone (f : V ↪ W) : Monotone (SimpleGraph.comap f) := by
intro G G' h _ _ ha
exact h ha
@[simp]
theorem comap_map_eq (f : V ↪ W) (G : SimpleGraph V) : (G.map f).comap f = G := by
ext
simp
theorem leftInverse_comap_map (f : V ↪ W) :
Function.LeftInverse (SimpleGraph.comap f) (SimpleGraph.map f) :=
comap_map_eq f
theorem map_injective (f : V ↪ W) : Function.Injective (SimpleGraph.map f) :=
(leftInverse_comap_map f).injective
theorem comap_surjective (f : V ↪ W) : Function.Surjective (SimpleGraph.comap f) :=
| (leftInverse_comap_map f).surjective
theorem map_le_iff_le_comap (f : V ↪ W) (G : SimpleGraph V) (G' : SimpleGraph W) :
| Mathlib/Combinatorics/SimpleGraph/Maps.lean | 129 | 131 |
/-
Copyright (c) 2022 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.NumberTheory.BernoulliPolynomials
import Mathlib.MeasureTheory.Integral.IntervalIntegral.Basic
import Mathlib.Analysis.Calculus.Deriv.Polynomial
import Mathlib.Analysis.Fourier.AddCircle
import Mathlib.Analysis.PSeries
/-!
# Critical values of the Riemann zeta function
In this file we prove formulae for the critical values of `ζ(s)`, and more generally of Hurwitz
zeta functions, in terms of Bernoulli polynomials.
## Main results:
* `hasSum_zeta_nat`: the final formula for zeta values,
$$\zeta(2k) = \frac{(-1)^{(k + 1)} 2 ^ {2k - 1} \pi^{2k} B_{2 k}}{(2 k)!}.$$
* `hasSum_zeta_two` and `hasSum_zeta_four`: special cases given explicitly.
* `hasSum_one_div_nat_pow_mul_cos`: a formula for the sum `∑ (n : ℕ), cos (2 π i n x) / n ^ k` as
an explicit multiple of `Bₖ(x)`, for any `x ∈ [0, 1]` and `k ≥ 2` even.
* `hasSum_one_div_nat_pow_mul_sin`: a formula for the sum `∑ (n : ℕ), sin (2 π i n x) / n ^ k` as
an explicit multiple of `Bₖ(x)`, for any `x ∈ [0, 1]` and `k ≥ 3` odd.
-/
noncomputable section
open scoped Nat Real Interval
open Complex MeasureTheory Set intervalIntegral
local notation "𝕌" => UnitAddCircle
section BernoulliFunProps
/-! Simple properties of the Bernoulli polynomial, as a function `ℝ → ℝ`. -/
/-- The function `x ↦ Bₖ(x) : ℝ → ℝ`. -/
def bernoulliFun (k : ℕ) (x : ℝ) : ℝ :=
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli k)).eval x
theorem bernoulliFun_eval_zero (k : ℕ) : bernoulliFun k 0 = bernoulli k := by
rw [bernoulliFun, Polynomial.eval_zero_map, Polynomial.bernoulli_eval_zero, eq_ratCast]
theorem bernoulliFun_endpoints_eq_of_ne_one {k : ℕ} (hk : k ≠ 1) :
bernoulliFun k 1 = bernoulliFun k 0 := by
rw [bernoulliFun_eval_zero, bernoulliFun, Polynomial.eval_one_map, Polynomial.bernoulli_eval_one,
bernoulli_eq_bernoulli'_of_ne_one hk, eq_ratCast]
theorem bernoulliFun_eval_one (k : ℕ) : bernoulliFun k 1 = bernoulliFun k 0 + ite (k = 1) 1 0 := by
rw [bernoulliFun, bernoulliFun_eval_zero, Polynomial.eval_one_map, Polynomial.bernoulli_eval_one]
split_ifs with h
· rw [h, bernoulli_one, bernoulli'_one, eq_ratCast]
push_cast; ring
| · rw [bernoulli_eq_bernoulli'_of_ne_one h, add_zero, eq_ratCast]
theorem hasDerivAt_bernoulliFun (k : ℕ) (x : ℝ) :
HasDerivAt (bernoulliFun k) (k * bernoulliFun (k - 1) x) x := by
convert ((Polynomial.bernoulli k).map <| algebraMap ℚ ℝ).hasDerivAt x using 1
simp only [bernoulliFun, Polynomial.derivative_map, Polynomial.derivative_bernoulli k,
| Mathlib/NumberTheory/ZetaValues.lean | 59 | 64 |
/-
Copyright (c) 2017 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Stephen Morgan, Kim Morrison, Johannes Hölzl
-/
import Mathlib.CategoryTheory.EpiMono
import Mathlib.CategoryTheory.Functor.FullyFaithful
import Mathlib.Data.Set.CoeSort
import Mathlib.Tactic.PPWithUniv
import Mathlib.Tactic.ToAdditive
/-!
# The category `Type`.
In this section we set up the theory so that Lean's types and functions between them
can be viewed as a `LargeCategory` in our framework.
Lean can not transparently view a function as a morphism in this category, and needs a hint in
order to be able to type check. We provide the abbreviation `asHom f` to guide type checking,
as well as a corresponding notation `↾ f`. (Entered as `\upr `.)
We provide various simplification lemmas for functors and natural transformations valued in `Type`.
We define `uliftFunctor`, from `Type u` to `Type (max u v)`, and show that it is fully faithful
(but not, of course, essentially surjective).
We prove some basic facts about the category `Type`:
* epimorphisms are surjections and monomorphisms are injections,
* `Iso` is both `Iso` and `Equiv` to `Equiv` (at least within a fixed universe),
* every type level `IsLawfulFunctor` gives a categorical functor `Type ⥤ Type`
(the corresponding fact about monads is in `Mathlib/CategoryTheory/Monad/Types.lean`).
-/
namespace CategoryTheory
-- morphism levels before object levels. See note [CategoryTheory universes].
universe v v' w u u'
/- The `@[to_additive]` attribute is just a hint that expressions involving this instance can
still be additivized. -/
@[to_additive existing CategoryTheory.types]
instance types : LargeCategory (Type u) where
Hom a b := a → b
id _ := id
comp f g := g ∘ f
theorem types_hom {α β : Type u} : (α ⟶ β) = (α → β) :=
rfl
@[ext] theorem types_ext {α β : Type u} (f g : α ⟶ β) (h : ∀ a : α, f a = g a) : f = g := by
funext x
exact h x
theorem types_id (X : Type u) : 𝟙 X = id :=
rfl
theorem types_comp {X Y Z : Type u} (f : X ⟶ Y) (g : Y ⟶ Z) : f ≫ g = g ∘ f :=
rfl
@[simp]
theorem types_id_apply (X : Type u) (x : X) : (𝟙 X : X → X) x = x :=
rfl
@[simp]
theorem types_comp_apply {X Y Z : Type u} (f : X ⟶ Y) (g : Y ⟶ Z) (x : X) : (f ≫ g) x = g (f x) :=
rfl
@[simp]
theorem hom_inv_id_apply {X Y : Type u} (f : X ≅ Y) (x : X) : f.inv (f.hom x) = x :=
congr_fun f.hom_inv_id x
@[simp]
theorem inv_hom_id_apply {X Y : Type u} (f : X ≅ Y) (y : Y) : f.hom (f.inv y) = y :=
congr_fun f.inv_hom_id y
-- Unfortunately without this wrapper we can't use `CategoryTheory` idioms, such as `IsIso f`.
/-- `asHom f` helps Lean type check a function as a morphism in the category `Type`. -/
abbrev asHom {α β : Type u} (f : α → β) : α ⟶ β :=
f
@[inherit_doc]
scoped notation "↾" f:200 => CategoryTheory.asHom f
section
-- We verify the expected type checking behaviour of `asHom`
variable (α β γ : Type u) (f : α → β) (g : β → γ)
example : α → γ :=
↾f ≫ ↾g
example [IsIso (↾f)] : Mono (↾f) := by infer_instance
example [IsIso (↾f)] : ↾f ≫ inv (↾f) = 𝟙 α := by simp
end
namespace Functor
variable {J : Type u} [Category.{v} J]
/-- The sections of a functor `F : J ⥤ Type` are
the choices of a point `u j : F.obj j` for each `j`,
such that `F.map f (u j) = u j'` for every morphism `f : j ⟶ j'`.
We later use these to define limits in `Type` and in many concrete categories.
-/
def sections (F : J ⥤ Type w) : Set (∀ j, F.obj j) :=
{ u | ∀ {j j'} (f : j ⟶ j'), F.map f (u j) = u j' }
@[simp]
lemma sections_property {F : J ⥤ Type w} (s : (F.sections : Type _))
{j j' : J} (f : j ⟶ j') : F.map f (s.val j) = s.val j' :=
s.property f
lemma sections_ext_iff {F : J ⥤ Type w} {x y : F.sections} : x = y ↔ ∀ j, x.val j = y.val j :=
Subtype.ext_iff.trans funext_iff
variable (J)
/-- The functor which sends a functor to types to its sections. -/
@[simps]
def sectionsFunctor : (J ⥤ Type w) ⥤ Type max u w where
obj F := F.sections
map {F G} φ x := ⟨fun j => φ.app j (x.1 j), fun {j j'} f =>
(congr_fun (φ.naturality f) (x.1 j)).symm.trans (by simp [x.2 f])⟩
end Functor
namespace FunctorToTypes
variable {C : Type u} [Category.{v} C] (F G H : C ⥤ Type w) {X Y Z : C}
variable (σ : F ⟶ G) (τ : G ⟶ H)
@[simp]
theorem map_comp_apply (f : X ⟶ Y) (g : Y ⟶ Z) (a : F.obj X) :
(F.map (f ≫ g)) a = (F.map g) ((F.map f) a) := by simp [types_comp]
@[simp]
theorem map_id_apply (a : F.obj X) : (F.map (𝟙 X)) a = a := by simp [types_id]
theorem naturality (f : X ⟶ Y) (x : F.obj X) : σ.app Y ((F.map f) x) = (G.map f) (σ.app X x) :=
congr_fun (σ.naturality f) x
@[simp]
theorem comp (x : F.obj X) : (σ ≫ τ).app X x = τ.app X (σ.app X x) :=
rfl
@[simp]
| theorem eqToHom_map_comp_apply (p : X = Y) (q : Y = Z) (x : F.obj X) :
F.map (eqToHom q) (F.map (eqToHom p) x) = F.map (eqToHom <| p.trans q) x := by
| Mathlib/CategoryTheory/Types.lean | 151 | 152 |
/-
Copyright (c) 2021 Yourong Zang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yourong Zang, Yury Kudryashov
-/
import Mathlib.Data.Fintype.Option
import Mathlib.Topology.Homeomorph.Lemmas
import Mathlib.Topology.Sets.Opens
/-!
# The OnePoint Compactification
We construct the OnePoint compactification (the one-point compactification) of an arbitrary
topological space `X` and prove some properties inherited from `X`.
## Main definitions
* `OnePoint`: the OnePoint compactification, we use coercion for the canonical embedding
`X → OnePoint X`; when `X` is already compact, the compactification adds an isolated point
to the space.
* `OnePoint.infty`: the extra point
## Main results
* The topological structure of `OnePoint X`
* The connectedness of `OnePoint X` for a noncompact, preconnected `X`
* `OnePoint X` is `T₀` for a T₀ space `X`
* `OnePoint X` is `T₁` for a T₁ space `X`
* `OnePoint X` is normal if `X` is a locally compact Hausdorff space
## Tags
one-point compactification, Alexandroff compactification, compactness
-/
open Set Filter Topology
/-!
### Definition and basic properties
In this section we define `OnePoint X` to be the disjoint union of `X` and `∞`, implemented as
`Option X`. Then we restate some lemmas about `Option X` for `OnePoint X`.
-/
variable {X Y : Type*}
/-- The OnePoint extension of an arbitrary topological space `X` -/
def OnePoint (X : Type*) :=
Option X
/-- The repr uses the notation from the `OnePoint` locale. -/
instance [Repr X] : Repr (OnePoint X) :=
⟨fun o _ =>
match o with
| none => "∞"
| some a => "↑" ++ repr a⟩
namespace OnePoint
/-- The point at infinity -/
@[match_pattern] def infty : OnePoint X := none
@[inherit_doc]
scoped notation "∞" => OnePoint.infty
/-- Coercion from `X` to `OnePoint X`. -/
@[coe, match_pattern] def some : X → OnePoint X := Option.some
@[simp]
lemma some_eq_iff (x₁ x₂ : X) : (some x₁ = some x₂) ↔ (x₁ = x₂) := by
rw [iff_eq_eq]
exact Option.some.injEq x₁ x₂
instance : CoeTC X (OnePoint X) := ⟨some⟩
instance : Inhabited (OnePoint X) := ⟨∞⟩
protected lemma «forall» {p : OnePoint X → Prop} :
(∀ (x : OnePoint X), p x) ↔ p ∞ ∧ ∀ (x : X), p x :=
Option.forall
protected lemma «exists» {p : OnePoint X → Prop} :
(∃ x, p x) ↔ p ∞ ∨ ∃ (x : X), p x :=
Option.exists
instance [Fintype X] : Fintype (OnePoint X) :=
inferInstanceAs (Fintype (Option X))
instance infinite [Infinite X] : Infinite (OnePoint X) :=
inferInstanceAs (Infinite (Option X))
theorem coe_injective : Function.Injective ((↑) : X → OnePoint X) :=
Option.some_injective X
@[norm_cast]
theorem coe_eq_coe {x y : X} : (x : OnePoint X) = y ↔ x = y :=
coe_injective.eq_iff
@[simp]
theorem coe_ne_infty (x : X) : (x : OnePoint X) ≠ ∞ :=
nofun
@[simp]
theorem infty_ne_coe (x : X) : ∞ ≠ (x : OnePoint X) :=
nofun
/-- Recursor for `OnePoint` using the preferred forms `∞` and `↑x`. -/
@[elab_as_elim, induction_eliminator, cases_eliminator]
protected def rec {C : OnePoint X → Sort*} (infty : C ∞) (coe : ∀ x : X, C x) :
∀ z : OnePoint X, C z
| ∞ => infty
| (x : X) => coe x
/-- An elimination principle for `OnePoint`. -/
@[inline] protected def elim : OnePoint X → Y → (X → Y) → Y := Option.elim
@[simp] theorem elim_infty (y : Y) (f : X → Y) : ∞.elim y f = y := rfl
@[simp] theorem elim_some (y : Y) (f : X → Y) (x : X) : (some x).elim y f = f x := rfl
theorem isCompl_range_coe_infty : IsCompl (range ((↑) : X → OnePoint X)) {∞} :=
isCompl_range_some_none X
theorem range_coe_union_infty : range ((↑) : X → OnePoint X) ∪ {∞} = univ :=
range_some_union_none X
@[simp]
theorem insert_infty_range_coe : insert ∞ (range (@some X)) = univ :=
insert_none_range_some _
@[simp]
theorem range_coe_inter_infty : range ((↑) : X → OnePoint X) ∩ {∞} = ∅ :=
range_some_inter_none X
@[simp]
theorem compl_range_coe : (range ((↑) : X → OnePoint X))ᶜ = {∞} :=
compl_range_some X
theorem compl_infty : ({∞}ᶜ : Set (OnePoint X)) = range ((↑) : X → OnePoint X) :=
(@isCompl_range_coe_infty X).symm.compl_eq
theorem compl_image_coe (s : Set X) : ((↑) '' s : Set (OnePoint X))ᶜ = (↑) '' sᶜ ∪ {∞} := by
rw [coe_injective.compl_image_eq, compl_range_coe]
theorem ne_infty_iff_exists {x : OnePoint X} : x ≠ ∞ ↔ ∃ y : X, (y : OnePoint X) = x := by
induction x using OnePoint.rec <;> simp
instance canLift : CanLift (OnePoint X) X (↑) fun x => x ≠ ∞ :=
WithTop.canLift
theorem not_mem_range_coe_iff {x : OnePoint X} : x ∉ range some ↔ x = ∞ := by
rw [← mem_compl_iff, compl_range_coe, mem_singleton_iff]
theorem infty_not_mem_range_coe : ∞ ∉ range ((↑) : X → OnePoint X) :=
not_mem_range_coe_iff.2 rfl
theorem infty_not_mem_image_coe {s : Set X} : ∞ ∉ ((↑) : X → OnePoint X) '' s :=
not_mem_subset (image_subset_range _ _) infty_not_mem_range_coe
@[simp]
theorem coe_preimage_infty : ((↑) : X → OnePoint X) ⁻¹' {∞} = ∅ := by
ext
simp
/-- Extend a map `f : X → Y` to a map `OnePoint X → OnePoint Y`
by sending infinity to infinity. -/
protected def map (f : X → Y) : OnePoint X → OnePoint Y :=
Option.map f
@[simp] theorem map_infty (f : X → Y) : OnePoint.map f ∞ = ∞ := rfl
@[simp] theorem map_some (f : X → Y) (x : X) : (x : OnePoint X).map f = f x := rfl
@[simp] theorem map_id : OnePoint.map (id : X → X) = id := Option.map_id
theorem map_comp {Z : Type*} (f : Y → Z) (g : X → Y) :
OnePoint.map (f ∘ g) = OnePoint.map f ∘ OnePoint.map g :=
(Option.map_comp_map _ _).symm
/-!
### Topological space structure on `OnePoint X`
We define a topological space structure on `OnePoint X` so that `s` is open if and only if
* `(↑) ⁻¹' s` is open in `X`;
* if `∞ ∈ s`, then `((↑) ⁻¹' s)ᶜ` is compact.
Then we reformulate this definition in a few different ways, and prove that
`(↑) : X → OnePoint X` is an open embedding. If `X` is not a compact space, then we also prove
that `(↑)` has dense range, so it is a dense embedding.
-/
variable [TopologicalSpace X]
instance : TopologicalSpace (OnePoint X) where
IsOpen s := (∞ ∈ s → IsCompact (((↑) : X → OnePoint X) ⁻¹' s)ᶜ) ∧
IsOpen (((↑) : X → OnePoint X) ⁻¹' s)
isOpen_univ := by simp
isOpen_inter s t := by
rintro ⟨hms, hs⟩ ⟨hmt, ht⟩
refine ⟨?_, hs.inter ht⟩
rintro ⟨hms', hmt'⟩
simpa [compl_inter] using (hms hms').union (hmt hmt')
isOpen_sUnion S ho := by
suffices IsOpen ((↑) ⁻¹' ⋃₀ S : Set X) by
refine ⟨?_, this⟩
rintro ⟨s, hsS : s ∈ S, hs : ∞ ∈ s⟩
refine IsCompact.of_isClosed_subset ((ho s hsS).1 hs) this.isClosed_compl ?_
exact compl_subset_compl.mpr (preimage_mono <| subset_sUnion_of_mem hsS)
rw [preimage_sUnion]
exact isOpen_biUnion fun s hs => (ho s hs).2
variable {s : Set (OnePoint X)}
theorem isOpen_def :
IsOpen s ↔ (∞ ∈ s → IsCompact ((↑) ⁻¹' s : Set X)ᶜ) ∧ IsOpen ((↑) ⁻¹' s : Set X) :=
Iff.rfl
theorem isOpen_iff_of_mem' (h : ∞ ∈ s) :
IsOpen s ↔ IsCompact ((↑) ⁻¹' s : Set X)ᶜ ∧ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
theorem isOpen_iff_of_mem (h : ∞ ∈ s) :
IsOpen s ↔ IsClosed ((↑) ⁻¹' s : Set X)ᶜ ∧ IsCompact ((↑) ⁻¹' s : Set X)ᶜ := by
simp only [isOpen_iff_of_mem' h, isClosed_compl_iff, and_comm]
theorem isOpen_iff_of_not_mem (h : ∞ ∉ s) : IsOpen s ↔ IsOpen ((↑) ⁻¹' s : Set X) := by
simp [isOpen_def, h]
theorem isClosed_iff_of_mem (h : ∞ ∈ s) : IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) := by
have : ∞ ∉ sᶜ := fun H => H h
rw [← isOpen_compl_iff, isOpen_iff_of_not_mem this, ← isOpen_compl_iff, preimage_compl]
theorem isClosed_iff_of_not_mem (h : ∞ ∉ s) :
IsClosed s ↔ IsClosed ((↑) ⁻¹' s : Set X) ∧ IsCompact ((↑) ⁻¹' s : Set X) := by
rw [← isOpen_compl_iff, isOpen_iff_of_mem (mem_compl h), ← preimage_compl, compl_compl]
@[simp]
theorem isOpen_image_coe {s : Set X} : IsOpen ((↑) '' s : Set (OnePoint X)) ↔ IsOpen s := by
rw [isOpen_iff_of_not_mem infty_not_mem_image_coe, preimage_image_eq _ coe_injective]
theorem isOpen_compl_image_coe {s : Set X} :
IsOpen ((↑) '' s : Set (OnePoint X))ᶜ ↔ IsClosed s ∧ IsCompact s := by
rw [isOpen_iff_of_mem, ← preimage_compl, compl_compl, preimage_image_eq _ coe_injective]
exact infty_not_mem_image_coe
@[simp]
theorem isClosed_image_coe {s : Set X} :
IsClosed ((↑) '' s : Set (OnePoint X)) ↔ IsClosed s ∧ IsCompact s := by
rw [← isOpen_compl_iff, isOpen_compl_image_coe]
/-- An open set in `OnePoint X` constructed from a closed compact set in `X` -/
def opensOfCompl (s : Set X) (h₁ : IsClosed s) (h₂ : IsCompact s) :
TopologicalSpace.Opens (OnePoint X) :=
⟨((↑) '' s)ᶜ, isOpen_compl_image_coe.2 ⟨h₁, h₂⟩⟩
theorem infty_mem_opensOfCompl {s : Set X} (h₁ : IsClosed s) (h₂ : IsCompact s) :
∞ ∈ opensOfCompl s h₁ h₂ :=
mem_compl infty_not_mem_image_coe
@[continuity]
theorem continuous_coe : Continuous ((↑) : X → OnePoint X) :=
continuous_def.mpr fun _s hs => hs.right
theorem isOpenMap_coe : IsOpenMap ((↑) : X → OnePoint X) := fun _ => isOpen_image_coe.2
theorem isOpenEmbedding_coe : IsOpenEmbedding ((↑) : X → OnePoint X) :=
.of_continuous_injective_isOpenMap continuous_coe coe_injective isOpenMap_coe
theorem isOpen_range_coe : IsOpen (range ((↑) : X → OnePoint X)) :=
isOpenEmbedding_coe.isOpen_range
theorem isClosed_infty : IsClosed ({∞} : Set (OnePoint X)) := by
rw [← compl_range_coe, isClosed_compl_iff]
exact isOpen_range_coe
theorem nhds_coe_eq (x : X) : 𝓝 ↑x = map ((↑) : X → OnePoint X) (𝓝 x) :=
(isOpenEmbedding_coe.map_nhds_eq x).symm
theorem nhdsWithin_coe_image (s : Set X) (x : X) :
𝓝[(↑) '' s] (x : OnePoint X) = map (↑) (𝓝[s] x) :=
(isOpenEmbedding_coe.isEmbedding.map_nhdsWithin_eq _ _).symm
theorem nhdsWithin_coe (s : Set (OnePoint X)) (x : X) : 𝓝[s] ↑x = map (↑) (𝓝[(↑) ⁻¹' s] x) :=
(isOpenEmbedding_coe.map_nhdsWithin_preimage_eq _ _).symm
theorem comap_coe_nhds (x : X) : comap ((↑) : X → OnePoint X) (𝓝 x) = 𝓝 x :=
(isOpenEmbedding_coe.isInducing.nhds_eq_comap x).symm
/-- If `x` is not an isolated point of `X`, then `x : OnePoint X` is not an isolated point
of `OnePoint X`. -/
instance nhdsNE_coe_neBot (x : X) [h : NeBot (𝓝[≠] x)] : NeBot (𝓝[≠] (x : OnePoint X)) := by
simpa [nhdsWithin_coe, preimage, coe_eq_coe] using h.map some
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_coe_neBot := nhdsNE_coe_neBot
theorem nhdsNE_infty_eq : 𝓝[≠] (∞ : OnePoint X) = map (↑) (coclosedCompact X) := by
refine (nhdsWithin_basis_open ∞ _).ext (hasBasis_coclosedCompact.map _) ?_ ?_
· rintro s ⟨hs, hso⟩
refine ⟨_, (isOpen_iff_of_mem hs).mp hso, ?_⟩
simp [Subset.rfl]
· rintro s ⟨h₁, h₂⟩
refine ⟨_, ⟨mem_compl infty_not_mem_image_coe, isOpen_compl_image_coe.2 ⟨h₁, h₂⟩⟩, ?_⟩
simp [compl_image_coe, ← diff_eq, subset_preimage_image]
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_infty_eq := nhdsNE_infty_eq
/-- If `X` is a non-compact space, then `∞` is not an isolated point of `OnePoint X`. -/
instance nhdsNE_infty_neBot [NoncompactSpace X] : NeBot (𝓝[≠] (∞ : OnePoint X)) := by
rw [nhdsNE_infty_eq]
infer_instance
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_infty_neBot := nhdsNE_infty_neBot
instance (priority := 900) nhdsNE_neBot [∀ x : X, NeBot (𝓝[≠] x)] [NoncompactSpace X]
(x : OnePoint X) : NeBot (𝓝[≠] x) :=
OnePoint.rec OnePoint.nhdsNE_infty_neBot (fun y => OnePoint.nhdsNE_coe_neBot y) x
@[deprecated (since := "2025-03-02")]
alias nhdsWithin_compl_neBot := nhdsNE_neBot
theorem nhds_infty_eq : 𝓝 (∞ : OnePoint X) = map (↑) (coclosedCompact X) ⊔ pure ∞ := by
rw [← nhdsNE_infty_eq, nhdsNE_sup_pure]
theorem tendsto_coe_infty : Tendsto (↑) (coclosedCompact X) (𝓝 (∞ : OnePoint X)) := by
rw [nhds_infty_eq]
exact Filter.Tendsto.mono_right tendsto_map le_sup_left
theorem hasBasis_nhds_infty :
(𝓝 (∞ : OnePoint X)).HasBasis (fun s : Set X => IsClosed s ∧ IsCompact s) fun s =>
(↑) '' sᶜ ∪ {∞} := by
rw [nhds_infty_eq]
exact (hasBasis_coclosedCompact.map _).sup_pure _
@[simp]
theorem comap_coe_nhds_infty : comap ((↑) : X → OnePoint X) (𝓝 ∞) = coclosedCompact X := by
simp [nhds_infty_eq, comap_sup, comap_map coe_injective]
theorem le_nhds_infty {f : Filter (OnePoint X)} :
f ≤ 𝓝 ∞ ↔ ∀ s : Set X, IsClosed s → IsCompact s → (↑) '' sᶜ ∪ {∞} ∈ f := by
simp only [hasBasis_nhds_infty.ge_iff, and_imp]
theorem ultrafilter_le_nhds_infty {f : Ultrafilter (OnePoint X)} :
(f : Filter (OnePoint X)) ≤ 𝓝 ∞ ↔ ∀ s : Set X, IsClosed s → IsCompact s → (↑) '' s ∉ f := by
simp only [le_nhds_infty, ← compl_image_coe, Ultrafilter.mem_coe,
Ultrafilter.compl_mem_iff_not_mem]
theorem tendsto_nhds_infty' {α : Type*} {f : OnePoint X → α} {l : Filter α} :
Tendsto f (𝓝 ∞) l ↔ Tendsto f (pure ∞) l ∧ Tendsto (f ∘ (↑)) (coclosedCompact X) l := by
simp [nhds_infty_eq, and_comm]
theorem tendsto_nhds_infty {α : Type*} {f : OnePoint X → α} {l : Filter α} :
Tendsto f (𝓝 ∞) l ↔
∀ s ∈ l, f ∞ ∈ s ∧ ∃ t : Set X, IsClosed t ∧ IsCompact t ∧ MapsTo (f ∘ (↑)) tᶜ s :=
tendsto_nhds_infty'.trans <| by
simp only [tendsto_pure_left, hasBasis_coclosedCompact.tendsto_left_iff, forall_and,
and_assoc, exists_prop]
theorem continuousAt_infty' {Y : Type*} [TopologicalSpace Y] {f : OnePoint X → Y} :
ContinuousAt f ∞ ↔ Tendsto (f ∘ (↑)) (coclosedCompact X) (𝓝 (f ∞)) :=
tendsto_nhds_infty'.trans <| and_iff_right (tendsto_pure_nhds _ _)
theorem continuousAt_infty {Y : Type*} [TopologicalSpace Y] {f : OnePoint X → Y} :
ContinuousAt f ∞ ↔
∀ s ∈ 𝓝 (f ∞), ∃ t : Set X, IsClosed t ∧ IsCompact t ∧ MapsTo (f ∘ (↑)) tᶜ s :=
| continuousAt_infty'.trans <| by simp only [hasBasis_coclosedCompact.tendsto_left_iff, and_assoc]
theorem continuousAt_coe {Y : Type*} [TopologicalSpace Y] {f : OnePoint X → Y} {x : X} :
ContinuousAt f x ↔ ContinuousAt (f ∘ (↑)) x := by
rw [ContinuousAt, nhds_coe_eq, tendsto_map'_iff, ContinuousAt]; rfl
| Mathlib/Topology/Compactification/OnePoint.lean | 370 | 375 |
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Algebra.Order.Interval.Finset.Basic
import Mathlib.Order.Interval.Multiset
/-!
# Algebraic properties of multiset intervals
This file provides results about the interaction of algebra with `Multiset.Ixx`.
-/
variable {α : Type*}
namespace Multiset
variable [AddCommMonoid α] [PartialOrder α] [IsOrderedCancelAddMonoid α]
[ExistsAddOfLE α] [LocallyFiniteOrder α]
lemma map_add_left_Icc (a b c : α) : (Icc a b).map (c + ·) = Icc (c + a) (c + b) := by
classical rw [Icc, Icc, ← Finset.image_add_left_Icc, Finset.image_val,
((Finset.nodup _).map <| add_right_injective c).dedup]
lemma map_add_left_Ico (a b c : α) : (Ico a b).map (c + ·) = Ico (c + a) (c + b) := by
classical rw [Ico, Ico, ← Finset.image_add_left_Ico, Finset.image_val,
((Finset.nodup _).map <| add_right_injective c).dedup]
lemma map_add_left_Ioc (a b c : α) : (Ioc a b).map (c + ·) = Ioc (c + a) (c + b) := by
classical rw [Ioc, Ioc, ← Finset.image_add_left_Ioc, Finset.image_val,
((Finset.nodup _).map <| add_right_injective c).dedup]
lemma map_add_left_Ioo (a b c : α) : (Ioo a b).map (c + ·) = Ioo (c + a) (c + b) := by
classical rw [Ioo, Ioo, ← Finset.image_add_left_Ioo, Finset.image_val,
((Finset.nodup _).map <| add_right_injective c).dedup]
lemma map_add_right_Icc (a b c : α) : ((Icc a b).map fun x => x + c) = Icc (a + c) (b + c) := by
simp_rw [add_comm _ c]
exact map_add_left_Icc _ _ _
lemma map_add_right_Ico (a b c : α) : ((Ico a b).map fun x => x + c) = Ico (a + c) (b + c) := by
| simp_rw [add_comm _ c]
exact map_add_left_Ico _ _ _
| Mathlib/Algebra/Order/Interval/Multiset.lean | 42 | 44 |
/-
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) :
| Mathlib/CategoryTheory/Shift/Basic.lean | 333 | 335 |
/-
Copyright (c) 2020 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jujian Zhang, Johan Commelin
-/
import Mathlib.RingTheory.GradedAlgebra.Homogeneous.Ideal
import Mathlib.Topology.Category.TopCat.Basic
import Mathlib.Topology.Sets.Opens
import Mathlib.Data.Set.Subsingleton
/-!
# Projective spectrum of a graded ring
The projective spectrum of a graded commutative ring is the subtype of all homogeneous ideals that
are prime and do not contain the irrelevant ideal.
It is naturally endowed with a topology: the Zariski topology.
## Notation
- `R` is a commutative semiring;
- `A` is a commutative ring and an `R`-algebra;
- `𝒜 : ℕ → Submodule R A` is the grading of `A`;
## Main definitions
* `ProjectiveSpectrum 𝒜`: The projective spectrum of a graded ring `A`, or equivalently, the set of
all homogeneous ideals of `A` that is both prime and relevant i.e. not containing irrelevant
ideal. Henceforth, we call elements of projective spectrum *relevant homogeneous prime ideals*.
* `ProjectiveSpectrum.zeroLocus 𝒜 s`: The zero locus of a subset `s` of `A`
is the subset of `ProjectiveSpectrum 𝒜` consisting of all relevant homogeneous prime ideals that
contain `s`.
* `ProjectiveSpectrum.vanishingIdeal t`: The vanishing ideal of a subset `t` of
`ProjectiveSpectrum 𝒜` is the intersection of points in `t` (viewed as relevant homogeneous prime
ideals).
* `ProjectiveSpectrum.Top`: the topological space of `ProjectiveSpectrum 𝒜` endowed with the
Zariski topology.
-/
noncomputable section
open DirectSum Pointwise SetLike TopCat TopologicalSpace CategoryTheory Opposite
variable {R A : Type*}
variable [CommSemiring R] [CommRing A] [Algebra R A]
variable (𝒜 : ℕ → Submodule R A) [GradedAlgebra 𝒜]
/-- The projective spectrum of a graded commutative ring is the subtype of all homogeneous ideals
that are prime and do not contain the irrelevant ideal. -/
@[ext]
structure ProjectiveSpectrum where
asHomogeneousIdeal : HomogeneousIdeal 𝒜
isPrime : asHomogeneousIdeal.toIdeal.IsPrime
not_irrelevant_le : ¬HomogeneousIdeal.irrelevant 𝒜 ≤ asHomogeneousIdeal
attribute [instance] ProjectiveSpectrum.isPrime
namespace ProjectiveSpectrum
instance (x : ProjectiveSpectrum 𝒜) : Ideal.IsPrime x.asHomogeneousIdeal.toIdeal := x.isPrime
/-- The zero locus of a set `s` of elements of a commutative ring `A` is the set of all relevant
homogeneous prime ideals of the ring that contain the set `s`.
An element `f` of `A` can be thought of as a dependent function on the projective spectrum of `𝒜`.
At a point `x` (a homogeneous prime ideal) the function (i.e., element) `f` takes values in the
quotient ring `A` modulo the prime ideal `x`. In this manner, `zeroLocus s` is exactly the subset
of `ProjectiveSpectrum 𝒜` where all "functions" in `s` vanish simultaneously. -/
def zeroLocus (s : Set A) : Set (ProjectiveSpectrum 𝒜) :=
{ x | s ⊆ x.asHomogeneousIdeal }
@[simp]
theorem mem_zeroLocus (x : ProjectiveSpectrum 𝒜) (s : Set A) :
x ∈ zeroLocus 𝒜 s ↔ s ⊆ x.asHomogeneousIdeal :=
Iff.rfl
@[simp]
theorem zeroLocus_span (s : Set A) : zeroLocus 𝒜 (Ideal.span s) = zeroLocus 𝒜 s := by
ext x
exact (Submodule.gi _ _).gc s x.asHomogeneousIdeal.toIdeal
variable {𝒜}
/-- The vanishing ideal of a set `t` of points of the projective spectrum of a commutative ring `R`
is the intersection of all the relevant homogeneous prime ideals in the set `t`.
An element `f` of `A` can be thought of as a dependent function on the projective spectrum of `𝒜`.
At a point `x` (a homogeneous prime ideal) the function (i.e., element) `f` takes values in the
quotient ring `A` modulo the prime ideal `x`. In this manner, `vanishingIdeal t` is exactly the
ideal of `A` consisting of all "functions" that vanish on all of `t`. -/
def vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) : HomogeneousIdeal 𝒜 :=
⨅ (x : ProjectiveSpectrum 𝒜) (_ : x ∈ t), x.asHomogeneousIdeal
theorem coe_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) :
(vanishingIdeal t : Set A) =
{ f | ∀ x : ProjectiveSpectrum 𝒜, x ∈ t → f ∈ x.asHomogeneousIdeal } := by
ext f
rw [vanishingIdeal, SetLike.mem_coe, ← HomogeneousIdeal.mem_iff, HomogeneousIdeal.toIdeal_iInf,
Submodule.mem_iInf]
refine forall_congr' fun x => ?_
rw [HomogeneousIdeal.toIdeal_iInf, Submodule.mem_iInf, HomogeneousIdeal.mem_iff]
theorem mem_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (f : A) :
f ∈ vanishingIdeal t ↔ ∀ x : ProjectiveSpectrum 𝒜, x ∈ t → f ∈ x.asHomogeneousIdeal := by
rw [← SetLike.mem_coe, coe_vanishingIdeal, Set.mem_setOf_eq]
@[simp]
theorem vanishingIdeal_singleton (x : ProjectiveSpectrum 𝒜) :
vanishingIdeal ({x} : Set (ProjectiveSpectrum 𝒜)) = x.asHomogeneousIdeal := by
simp [vanishingIdeal]
theorem subset_zeroLocus_iff_le_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (I : Ideal A) :
t ⊆ zeroLocus 𝒜 I ↔ I ≤ (vanishingIdeal t).toIdeal :=
⟨fun h _ k => (mem_vanishingIdeal _ _).mpr fun _ j => (mem_zeroLocus _ _ _).mpr (h j) k, fun h =>
fun x j =>
(mem_zeroLocus _ _ _).mpr (le_trans h fun _ h => ((mem_vanishingIdeal _ _).mp h) x j)⟩
variable (𝒜)
/-- `zeroLocus` and `vanishingIdeal` form a galois connection. -/
theorem gc_ideal :
@GaloisConnection (Ideal A) (Set (ProjectiveSpectrum 𝒜))ᵒᵈ _ _
(fun I => zeroLocus 𝒜 I) fun t => (vanishingIdeal t).toIdeal :=
fun I t => subset_zeroLocus_iff_le_vanishingIdeal t I
/-- `zeroLocus` and `vanishingIdeal` form a galois connection. -/
theorem gc_set :
@GaloisConnection (Set A) (Set (ProjectiveSpectrum 𝒜))ᵒᵈ _ _
(fun s => zeroLocus 𝒜 s) fun t => vanishingIdeal t := by
have ideal_gc : GaloisConnection Ideal.span _ := (Submodule.gi A _).gc
simpa [zeroLocus_span, Function.comp_def] using GaloisConnection.compose ideal_gc (gc_ideal 𝒜)
theorem gc_homogeneousIdeal :
@GaloisConnection (HomogeneousIdeal 𝒜) (Set (ProjectiveSpectrum 𝒜))ᵒᵈ _ _
(fun I => zeroLocus 𝒜 I) fun t => vanishingIdeal t :=
fun I t => by
simpa [show I.toIdeal ≤ (vanishingIdeal t).toIdeal ↔ I ≤ vanishingIdeal t from Iff.rfl] using
subset_zeroLocus_iff_le_vanishingIdeal t I.toIdeal
theorem subset_zeroLocus_iff_subset_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) (s : Set A) :
t ⊆ zeroLocus 𝒜 s ↔ s ⊆ vanishingIdeal t :=
(gc_set _) s t
theorem subset_vanishingIdeal_zeroLocus (s : Set A) : s ⊆ vanishingIdeal (zeroLocus 𝒜 s) :=
(gc_set _).le_u_l s
theorem ideal_le_vanishingIdeal_zeroLocus (I : Ideal A) :
I ≤ (vanishingIdeal (zeroLocus 𝒜 I)).toIdeal :=
(gc_ideal _).le_u_l I
theorem homogeneousIdeal_le_vanishingIdeal_zeroLocus (I : HomogeneousIdeal 𝒜) :
I ≤ vanishingIdeal (zeroLocus 𝒜 I) :=
(gc_homogeneousIdeal _).le_u_l I
theorem subset_zeroLocus_vanishingIdeal (t : Set (ProjectiveSpectrum 𝒜)) :
t ⊆ zeroLocus 𝒜 (vanishingIdeal t) :=
(gc_ideal _).l_u_le t
theorem zeroLocus_anti_mono {s t : Set A} (h : s ⊆ t) : zeroLocus 𝒜 t ⊆ zeroLocus 𝒜 s :=
(gc_set _).monotone_l h
theorem zeroLocus_anti_mono_ideal {s t : Ideal A} (h : s ≤ t) :
zeroLocus 𝒜 (t : Set A) ⊆ zeroLocus 𝒜 (s : Set A) :=
(gc_ideal _).monotone_l h
theorem zeroLocus_anti_mono_homogeneousIdeal {s t : HomogeneousIdeal 𝒜} (h : s ≤ t) :
zeroLocus 𝒜 (t : Set A) ⊆ zeroLocus 𝒜 (s : Set A) :=
(gc_homogeneousIdeal _).monotone_l h
theorem vanishingIdeal_anti_mono {s t : Set (ProjectiveSpectrum 𝒜)} (h : s ⊆ t) :
vanishingIdeal t ≤ vanishingIdeal s :=
(gc_ideal _).monotone_u h
theorem zeroLocus_bot : zeroLocus 𝒜 ((⊥ : Ideal A) : Set A) = Set.univ :=
(gc_ideal 𝒜).l_bot
@[simp]
theorem zeroLocus_singleton_zero : zeroLocus 𝒜 ({0} : Set A) = Set.univ :=
zeroLocus_bot _
@[simp]
theorem zeroLocus_empty : zeroLocus 𝒜 (∅ : Set A) = Set.univ :=
(gc_set 𝒜).l_bot
@[simp]
theorem vanishingIdeal_univ : vanishingIdeal (∅ : Set (ProjectiveSpectrum 𝒜)) = ⊤ := by
simpa using (gc_ideal _).u_top
theorem zeroLocus_empty_of_one_mem {s : Set A} (h : (1 : A) ∈ s) : zeroLocus 𝒜 s = ∅ :=
Set.eq_empty_iff_forall_not_mem.mpr fun x hx =>
(inferInstance : x.asHomogeneousIdeal.toIdeal.IsPrime).ne_top <|
x.asHomogeneousIdeal.toIdeal.eq_top_iff_one.mpr <| hx h
@[simp]
theorem zeroLocus_singleton_one : zeroLocus 𝒜 ({1} : Set A) = ∅ :=
zeroLocus_empty_of_one_mem 𝒜 (Set.mem_singleton (1 : A))
@[simp]
theorem zeroLocus_univ : zeroLocus 𝒜 (Set.univ : Set A) = ∅ :=
zeroLocus_empty_of_one_mem _ (Set.mem_univ 1)
theorem zeroLocus_sup_ideal (I J : Ideal A) :
zeroLocus 𝒜 ((I ⊔ J : Ideal A) : Set A) = zeroLocus _ I ∩ zeroLocus _ J :=
(gc_ideal 𝒜).l_sup
theorem zeroLocus_sup_homogeneousIdeal (I J : HomogeneousIdeal 𝒜) :
zeroLocus 𝒜 ((I ⊔ J : HomogeneousIdeal 𝒜) : Set A) = zeroLocus _ I ∩ zeroLocus _ J :=
(gc_homogeneousIdeal 𝒜).l_sup
theorem zeroLocus_union (s s' : Set A) : zeroLocus 𝒜 (s ∪ s') = zeroLocus _ s ∩ zeroLocus _ s' :=
(gc_set 𝒜).l_sup
theorem vanishingIdeal_union (t t' : Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal (t ∪ t') = vanishingIdeal t ⊓ vanishingIdeal t' := by
ext1; exact (gc_ideal 𝒜).u_inf
theorem zeroLocus_iSup_ideal {γ : Sort*} (I : γ → Ideal A) :
zeroLocus _ ((⨆ i, I i : Ideal A) : Set A) = ⋂ i, zeroLocus 𝒜 (I i) :=
(gc_ideal 𝒜).l_iSup
theorem zeroLocus_iSup_homogeneousIdeal {γ : Sort*} (I : γ → HomogeneousIdeal 𝒜) :
zeroLocus _ ((⨆ i, I i : HomogeneousIdeal 𝒜) : Set A) = ⋂ i, zeroLocus 𝒜 (I i) :=
(gc_homogeneousIdeal 𝒜).l_iSup
theorem zeroLocus_iUnion {γ : Sort*} (s : γ → Set A) :
zeroLocus 𝒜 (⋃ i, s i) = ⋂ i, zeroLocus 𝒜 (s i) :=
(gc_set 𝒜).l_iSup
theorem zeroLocus_bUnion (s : Set (Set A)) :
zeroLocus 𝒜 (⋃ s' ∈ s, s' : Set A) = ⋂ s' ∈ s, zeroLocus 𝒜 s' := by
simp only [zeroLocus_iUnion]
theorem vanishingIdeal_iUnion {γ : Sort*} (t : γ → Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal (⋃ i, t i) = ⨅ i, vanishingIdeal (t i) :=
HomogeneousIdeal.toIdeal_injective <| by
convert (gc_ideal 𝒜).u_iInf; exact HomogeneousIdeal.toIdeal_iInf _
theorem zeroLocus_inf (I J : Ideal A) :
zeroLocus 𝒜 ((I ⊓ J : Ideal A) : Set A) = zeroLocus 𝒜 I ∪ zeroLocus 𝒜 J :=
Set.ext fun x => x.isPrime.inf_le
theorem union_zeroLocus (s s' : Set A) :
zeroLocus 𝒜 s ∪ zeroLocus 𝒜 s' = zeroLocus 𝒜 (Ideal.span s ⊓ Ideal.span s' : Ideal A) := by
rw [zeroLocus_inf]
simp
theorem zeroLocus_mul_ideal (I J : Ideal A) :
zeroLocus 𝒜 ((I * J : Ideal A) : Set A) = zeroLocus 𝒜 I ∪ zeroLocus 𝒜 J :=
Set.ext fun x => x.isPrime.mul_le
theorem zeroLocus_mul_homogeneousIdeal (I J : HomogeneousIdeal 𝒜) :
zeroLocus 𝒜 ((I * J : HomogeneousIdeal 𝒜) : Set A) = zeroLocus 𝒜 I ∪ zeroLocus 𝒜 J :=
Set.ext fun x => x.isPrime.mul_le
theorem zeroLocus_singleton_mul (f g : A) :
zeroLocus 𝒜 ({f * g} : Set A) = zeroLocus 𝒜 {f} ∪ zeroLocus 𝒜 {g} :=
Set.ext fun x => by simpa using x.isPrime.mul_mem_iff_mem_or_mem
@[simp]
theorem zeroLocus_singleton_pow (f : A) (n : ℕ) (hn : 0 < n) :
zeroLocus 𝒜 ({f ^ n} : Set A) = zeroLocus 𝒜 {f} :=
Set.ext fun x => by simpa using x.isPrime.pow_mem_iff_mem n hn
theorem sup_vanishingIdeal_le (t t' : Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal t ⊔ vanishingIdeal t' ≤ vanishingIdeal (t ∩ t') := by
intro r
rw [← HomogeneousIdeal.mem_iff, HomogeneousIdeal.toIdeal_sup, mem_vanishingIdeal,
Submodule.mem_sup]
rintro ⟨f, hf, g, hg, rfl⟩ x ⟨hxt, hxt'⟩
rw [HomogeneousIdeal.mem_iff, mem_vanishingIdeal] at hf hg
apply Submodule.add_mem <;> solve_by_elim
theorem mem_compl_zeroLocus_iff_not_mem {f : A} {I : ProjectiveSpectrum 𝒜} :
I ∈ (zeroLocus 𝒜 {f} : Set (ProjectiveSpectrum 𝒜))ᶜ ↔ f ∉ I.asHomogeneousIdeal := by
rw [Set.mem_compl_iff, mem_zeroLocus, Set.singleton_subset_iff]; rfl
/-- The Zariski topology on the prime spectrum of a commutative ring is defined via the closed sets
of the topology: they are exactly those sets that are the zero locus of a subset of the ring. -/
instance zariskiTopology : TopologicalSpace (ProjectiveSpectrum 𝒜) :=
TopologicalSpace.ofClosed (Set.range (ProjectiveSpectrum.zeroLocus 𝒜)) ⟨Set.univ, by simp⟩
(by
intro Zs h
rw [Set.sInter_eq_iInter]
let f : Zs → Set _ := fun i => Classical.choose (h i.2)
have H : (Set.iInter fun i ↦ zeroLocus 𝒜 (f i)) ∈ Set.range (zeroLocus 𝒜) :=
⟨_, zeroLocus_iUnion 𝒜 _⟩
convert H using 2
funext i
exact (Classical.choose_spec (h i.2)).symm)
(by
rintro _ ⟨s, rfl⟩ _ ⟨t, rfl⟩
exact ⟨_, (union_zeroLocus 𝒜 s t).symm⟩)
/-- The underlying topology of `Proj` is the projective spectrum of graded ring `A`. -/
def top : TopCat :=
TopCat.of (ProjectiveSpectrum 𝒜)
theorem isOpen_iff (U : Set (ProjectiveSpectrum 𝒜)) : IsOpen U ↔ ∃ s, Uᶜ = zeroLocus 𝒜 s := by
simp only [@eq_comm _ Uᶜ]; rfl
theorem isClosed_iff_zeroLocus (Z : Set (ProjectiveSpectrum 𝒜)) :
IsClosed Z ↔ ∃ s, Z = zeroLocus 𝒜 s := by rw [← isOpen_compl_iff, isOpen_iff, compl_compl]
theorem isClosed_zeroLocus (s : Set A) : IsClosed (zeroLocus 𝒜 s) := by
rw [isClosed_iff_zeroLocus]
exact ⟨s, rfl⟩
theorem zeroLocus_vanishingIdeal_eq_closure (t : Set (ProjectiveSpectrum 𝒜)) :
zeroLocus 𝒜 (vanishingIdeal t : Set A) = closure t := by
apply Set.Subset.antisymm
· rintro x hx t' ⟨ht', ht⟩
obtain ⟨fs, rfl⟩ : ∃ s, t' = zeroLocus 𝒜 s := by rwa [isClosed_iff_zeroLocus] at ht'
rw [subset_zeroLocus_iff_subset_vanishingIdeal] at ht
exact Set.Subset.trans ht hx
· rw [(isClosed_zeroLocus _ _).closure_subset_iff]
exact subset_zeroLocus_vanishingIdeal 𝒜 t
theorem vanishingIdeal_closure (t : Set (ProjectiveSpectrum 𝒜)) :
vanishingIdeal (closure t) = vanishingIdeal t := by
have : (vanishingIdeal (zeroLocus 𝒜 (vanishingIdeal t))).toIdeal = _ := (gc_ideal 𝒜).u_l_u_eq_u t
ext1
rw [zeroLocus_vanishingIdeal_eq_closure 𝒜 t] at this
exact this
section BasicOpen
/-- `basicOpen r` is the open subset containing all prime ideals not containing `r`. -/
def basicOpen (r : A) : TopologicalSpace.Opens (ProjectiveSpectrum 𝒜) where
carrier := { x | r ∉ x.asHomogeneousIdeal }
is_open' := ⟨{r}, Set.ext fun _ => Set.singleton_subset_iff.trans <| Classical.not_not.symm⟩
@[simp]
theorem mem_basicOpen (f : A) (x : ProjectiveSpectrum 𝒜) :
x ∈ basicOpen 𝒜 f ↔ f ∉ x.asHomogeneousIdeal :=
Iff.rfl
theorem mem_coe_basicOpen (f : A) (x : ProjectiveSpectrum 𝒜) :
x ∈ (↑(basicOpen 𝒜 f) : Set (ProjectiveSpectrum 𝒜)) ↔ f ∉ x.asHomogeneousIdeal :=
Iff.rfl
theorem isOpen_basicOpen {a : A} : IsOpen (basicOpen 𝒜 a : Set (ProjectiveSpectrum 𝒜)) :=
(basicOpen 𝒜 a).isOpen
@[simp]
theorem basicOpen_eq_zeroLocus_compl (r : A) :
(basicOpen 𝒜 r : Set (ProjectiveSpectrum 𝒜)) = (zeroLocus 𝒜 {r})ᶜ :=
Set.ext fun x => by simp only [Set.mem_compl_iff, mem_zeroLocus, Set.singleton_subset_iff]; rfl
@[simp]
theorem basicOpen_one : basicOpen 𝒜 (1 : A) = ⊤ :=
TopologicalSpace.Opens.ext <| by simp
@[simp]
theorem basicOpen_zero : basicOpen 𝒜 (0 : A) = ⊥ :=
TopologicalSpace.Opens.ext <| by simp
theorem basicOpen_mul (f g : A) : basicOpen 𝒜 (f * g) = basicOpen 𝒜 f ⊓ basicOpen 𝒜 g :=
TopologicalSpace.Opens.ext <| by simp [zeroLocus_singleton_mul]
theorem basicOpen_mul_le_left (f g : A) : basicOpen 𝒜 (f * g) ≤ basicOpen 𝒜 f := by
rw [basicOpen_mul 𝒜 f g]
exact inf_le_left
theorem basicOpen_mul_le_right (f g : A) : basicOpen 𝒜 (f * g) ≤ basicOpen 𝒜 g := by
rw [basicOpen_mul 𝒜 f g]
exact inf_le_right
@[simp]
theorem basicOpen_pow (f : A) (n : ℕ) (hn : 0 < n) : basicOpen 𝒜 (f ^ n) = basicOpen 𝒜 f :=
TopologicalSpace.Opens.ext <| by simpa using zeroLocus_singleton_pow 𝒜 f n hn
theorem basicOpen_eq_union_of_projection (f : A) :
basicOpen 𝒜 f = ⨆ i : ℕ, basicOpen 𝒜 (GradedAlgebra.proj 𝒜 i f) :=
TopologicalSpace.Opens.ext <|
Set.ext fun z => by
rw [mem_coe_basicOpen, mem_coe, iSup, TopologicalSpace.Opens.mem_sSup]
constructor <;> intro hz
· rcases show ∃ i, GradedAlgebra.proj 𝒜 i f ∉ z.asHomogeneousIdeal by
contrapose! hz with H
classical
rw [← DirectSum.sum_support_decompose 𝒜 f]
apply Ideal.sum_mem _ fun i _ => H i with ⟨i, hi⟩
exact ⟨basicOpen 𝒜 (GradedAlgebra.proj 𝒜 i f), ⟨i, rfl⟩, by rwa [mem_basicOpen]⟩
· obtain ⟨_, ⟨i, rfl⟩, hz⟩ := hz
exact fun rid => hz (z.1.2 i rid)
theorem isTopologicalBasis_basic_opens :
TopologicalSpace.IsTopologicalBasis
(Set.range fun r : A => (basicOpen 𝒜 r : Set (ProjectiveSpectrum 𝒜))) := by
apply TopologicalSpace.isTopologicalBasis_of_isOpen_of_nhds
· rintro _ ⟨r, rfl⟩
exact isOpen_basicOpen 𝒜
· rintro p U hp ⟨s, hs⟩
rw [← compl_compl U, Set.mem_compl_iff, ← hs, mem_zeroLocus, Set.not_subset] at hp
obtain ⟨f, hfs, hfp⟩ := hp
refine ⟨basicOpen 𝒜 f, ⟨f, rfl⟩, hfp, ?_⟩
rw [← Set.compl_subset_compl, ← hs, basicOpen_eq_zeroLocus_compl, compl_compl]
exact zeroLocus_anti_mono 𝒜 (Set.singleton_subset_iff.mpr hfs)
end BasicOpen
section Order
/-!
## The specialization order
We endow `ProjectiveSpectrum 𝒜` with a partial order,
where `x ≤ y` if and only if `y ∈ closure {x}`.
-/
instance : PartialOrder (ProjectiveSpectrum 𝒜) :=
PartialOrder.lift asHomogeneousIdeal fun ⟨_, _, _⟩ ⟨_, _, _⟩ => by simp only [mk.injEq, imp_self]
@[simp]
theorem as_ideal_le_as_ideal (x y : ProjectiveSpectrum 𝒜) :
x.asHomogeneousIdeal ≤ y.asHomogeneousIdeal ↔ x ≤ y :=
Iff.rfl
@[simp]
theorem as_ideal_lt_as_ideal (x y : ProjectiveSpectrum 𝒜) :
| x.asHomogeneousIdeal < y.asHomogeneousIdeal ↔ x < y :=
Iff.rfl
| Mathlib/AlgebraicGeometry/ProjectiveSpectrum/Topology.lean | 421 | 423 |
/-
Copyright (c) 2022 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Roblot
-/
import Mathlib.MeasureTheory.Group.GeometryOfNumbers
import Mathlib.MeasureTheory.Measure.Lebesgue.VolumeOfBalls
import Mathlib.NumberTheory.NumberField.CanonicalEmbedding.Basic
import Mathlib.Analysis.SpecialFunctions.Gamma.BohrMollerup
/-!
# Convex Bodies
The file contains the definitions of several convex bodies lying in the mixed space `ℝ^r₁ × ℂ^r₂`
associated to a number field of signature `K` and proves several existence theorems by applying
*Minkowski Convex Body Theorem* to those.
## Main definitions and results
* `NumberField.mixedEmbedding.convexBodyLT`: The set of points `x` such that `‖x w‖ < f w` for all
infinite places `w` with `f : InfinitePlace K → ℝ≥0`.
* `NumberField.mixedEmbedding.convexBodySum`: The set of points `x` such that
`∑ w real, ‖x w‖ + 2 * ∑ w complex, ‖x w‖ ≤ B`
* `NumberField.mixedEmbedding.exists_ne_zero_mem_ideal_lt`: Let `I` be a fractional ideal of `K`.
Assume that `f` is such that `minkowskiBound K I < volume (convexBodyLT K f)`, then there exists a
nonzero algebraic number `a` in `I` such that `w a < f w` for all infinite places `w`.
* `NumberField.mixedEmbedding.exists_ne_zero_mem_ideal_of_norm_le`: Let `I` be a fractional ideal
of `K`. Assume that `B` is such that `minkowskiBound K I < volume (convexBodySum K B)` (see
`convexBodySum_volume` for the computation of this volume), then there exists a nonzero algebraic
number `a` in `I` such that `|Norm a| < (B / d) ^ d` where `d` is the degree of `K`.
## Tags
number field, infinite places
-/
variable (K : Type*) [Field K]
namespace NumberField.mixedEmbedding
open NumberField NumberField.InfinitePlace Module
section convexBodyLT
open Metric NNReal
variable (f : InfinitePlace K → ℝ≥0)
/-- The convex body defined by `f`: the set of points `x : E` such that `‖x w‖ < f w` for all
infinite places `w`. -/
abbrev convexBodyLT : Set (mixedSpace K) :=
(Set.univ.pi (fun w : { w : InfinitePlace K // IsReal w } => ball 0 (f w))) ×ˢ
(Set.univ.pi (fun w : { w : InfinitePlace K // IsComplex w } => ball 0 (f w)))
theorem convexBodyLT_mem {x : K} :
mixedEmbedding K x ∈ (convexBodyLT K f) ↔ ∀ w : InfinitePlace K, w x < f w := by
simp_rw [mixedEmbedding, RingHom.prod_apply, Set.mem_prod, Set.mem_pi, Set.mem_univ,
forall_true_left, mem_ball_zero_iff, Pi.ringHom_apply, ← Complex.norm_real,
embedding_of_isReal_apply, Subtype.forall, ← forall₂_or_left, ← not_isReal_iff_isComplex, em,
forall_true_left, norm_embedding_eq]
theorem convexBodyLT_neg_mem (x : mixedSpace K) (hx : x ∈ (convexBodyLT K f)) :
-x ∈ (convexBodyLT K f) := by
simp only [Set.mem_prod, Prod.fst_neg, Set.mem_pi, Set.mem_univ, Pi.neg_apply,
mem_ball_zero_iff, norm_neg, Real.norm_eq_abs, forall_true_left, Subtype.forall,
Prod.snd_neg] at hx ⊢
exact hx
theorem convexBodyLT_convex : Convex ℝ (convexBodyLT K f) :=
Convex.prod (convex_pi (fun _ _ => convex_ball _ _)) (convex_pi (fun _ _ => convex_ball _ _))
open Fintype MeasureTheory MeasureTheory.Measure ENNReal
variable [NumberField K]
/-- The fudge factor that appears in the formula for the volume of `convexBodyLT`. -/
noncomputable abbrev convexBodyLTFactor : ℝ≥0 :=
(2 : ℝ≥0) ^ nrRealPlaces K * NNReal.pi ^ nrComplexPlaces K
theorem convexBodyLTFactor_ne_zero : convexBodyLTFactor K ≠ 0 :=
mul_ne_zero (pow_ne_zero _ two_ne_zero) (pow_ne_zero _ pi_ne_zero)
theorem one_le_convexBodyLTFactor : 1 ≤ convexBodyLTFactor K :=
one_le_mul (one_le_pow₀ one_le_two) (one_le_pow₀ (one_le_two.trans Real.two_le_pi))
open scoped Classical in
/-- The volume of `(ConvexBodyLt K f)` where `convexBodyLT K f` is the set of points `x`
such that `‖x w‖ < f w` for all infinite places `w`. -/
theorem convexBodyLT_volume :
volume (convexBodyLT K f) = (convexBodyLTFactor K) * ∏ w, (f w) ^ (mult w) := by
calc
_ = (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (2 * (f x.val))) *
∏ x : {w // InfinitePlace.IsComplex w}, ENNReal.ofReal (f x.val) ^ 2 * NNReal.pi := by
simp_rw [volume_eq_prod, prod_prod, volume_pi, pi_pi, Real.volume_ball, Complex.volume_ball]
_ = ((2 : ℝ≥0) ^ nrRealPlaces K
* (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (f x.val)))
* ((∏ x : {w // IsComplex w}, ENNReal.ofReal (f x.val) ^ 2) *
NNReal.pi ^ nrComplexPlaces K) := by
simp_rw [ofReal_mul (by norm_num : 0 ≤ (2 : ℝ)), Finset.prod_mul_distrib, Finset.prod_const,
Finset.card_univ, ofReal_ofNat, ofReal_coe_nnreal, coe_ofNat]
_ = (convexBodyLTFactor K) * ((∏ x : {w // InfinitePlace.IsReal w}, .ofReal (f x.val)) *
(∏ x : {w // IsComplex w}, ENNReal.ofReal (f x.val) ^ 2)) := by
simp_rw [convexBodyLTFactor, coe_mul, ENNReal.coe_pow]
ring
_ = (convexBodyLTFactor K) * ∏ w, (f w) ^ (mult w) := by
simp_rw [prod_eq_prod_mul_prod, coe_mul, coe_finset_prod, mult_isReal, mult_isComplex,
pow_one, ENNReal.coe_pow, ofReal_coe_nnreal]
variable {f}
/-- This is a technical result: quite often, we want to impose conditions at all infinite places
but one and choose the value at the remaining place so that we can apply
`exists_ne_zero_mem_ringOfIntegers_lt`. -/
theorem adjust_f {w₁ : InfinitePlace K} (B : ℝ≥0) (hf : ∀ w, w ≠ w₁ → f w ≠ 0) :
∃ g : InfinitePlace K → ℝ≥0, (∀ w, w ≠ w₁ → g w = f w) ∧ ∏ w, (g w) ^ mult w = B := by
classical
let S := ∏ w ∈ Finset.univ.erase w₁, (f w) ^ mult w
refine ⟨Function.update f w₁ ((B * S⁻¹) ^ (mult w₁ : ℝ)⁻¹), ?_, ?_⟩
· exact fun w hw => Function.update_of_ne hw _ f
· rw [← Finset.mul_prod_erase Finset.univ _ (Finset.mem_univ w₁), Function.update_self,
Finset.prod_congr rfl fun w hw => by rw [Function.update_of_ne (Finset.ne_of_mem_erase hw)],
← NNReal.rpow_natCast, ← NNReal.rpow_mul, inv_mul_cancel₀, NNReal.rpow_one, mul_assoc,
inv_mul_cancel₀, mul_one]
· rw [Finset.prod_ne_zero_iff]
exact fun w hw => pow_ne_zero _ (hf w (Finset.ne_of_mem_erase hw))
· rw [mult]; split_ifs <;> norm_num
end convexBodyLT
section convexBodyLT'
open Metric ENNReal NNReal
variable (f : InfinitePlace K → ℝ≥0) (w₀ : {w : InfinitePlace K // IsComplex w})
open scoped Classical in
/-- A version of `convexBodyLT` with an additional condition at a fixed complex place. This is
needed to ensure the element constructed is not real, see for example
`exists_primitive_element_lt_of_isComplex`.
-/
abbrev convexBodyLT' : Set (mixedSpace K) :=
(Set.univ.pi (fun w : { w : InfinitePlace K // IsReal w } ↦ ball 0 (f w))) ×ˢ
(Set.univ.pi (fun w : { w : InfinitePlace K // IsComplex w } ↦
if w = w₀ then {x | |x.re| < 1 ∧ |x.im| < (f w : ℝ) ^ 2} else ball 0 (f w)))
theorem convexBodyLT'_mem {x : K} :
mixedEmbedding K x ∈ convexBodyLT' K f w₀ ↔
(∀ w : InfinitePlace K, w ≠ w₀ → w x < f w) ∧
|(w₀.val.embedding x).re| < 1 ∧ |(w₀.val.embedding x).im| < (f w₀ : ℝ) ^ 2 := by
simp_rw [mixedEmbedding, RingHom.prod_apply, Set.mem_prod, Set.mem_pi, Set.mem_univ,
forall_true_left, Pi.ringHom_apply, mem_ball_zero_iff, ← Complex.norm_real,
embedding_of_isReal_apply, norm_embedding_eq, Subtype.forall]
refine ⟨fun ⟨h₁, h₂⟩ ↦ ⟨fun w h_ne ↦ ?_, ?_⟩, fun ⟨h₁, h₂⟩ ↦ ⟨fun w hw ↦ ?_, fun w hw ↦ ?_⟩⟩
· by_cases hw : IsReal w
· exact norm_embedding_eq w _ ▸ h₁ w hw
· specialize h₂ w (not_isReal_iff_isComplex.mp hw)
rw [apply_ite (w.embedding x ∈ ·), Set.mem_setOf_eq,
mem_ball_zero_iff, norm_embedding_eq] at h₂
rwa [if_neg (by exact Subtype.coe_ne_coe.1 h_ne)] at h₂
· simpa [if_true] using h₂ w₀.val w₀.prop
· exact h₁ w (ne_of_isReal_isComplex hw w₀.prop)
· by_cases h_ne : w = w₀
· simpa [h_ne]
· rw [if_neg (by exact Subtype.coe_ne_coe.1 h_ne)]
rw [mem_ball_zero_iff, norm_embedding_eq]
exact h₁ w h_ne
theorem convexBodyLT'_neg_mem (x : mixedSpace K) (hx : x ∈ convexBodyLT' K f w₀) :
-x ∈ convexBodyLT' K f w₀ := by
simp only [Set.mem_prod, Set.mem_pi, Set.mem_univ, mem_ball, dist_zero_right, Real.norm_eq_abs,
true_implies, Subtype.forall, Prod.fst_neg, Pi.neg_apply, norm_neg, Prod.snd_neg] at hx ⊢
convert hx using 3
split_ifs <;> simp
theorem convexBodyLT'_convex : Convex ℝ (convexBodyLT' K f w₀) := by
refine Convex.prod (convex_pi (fun _ _ => convex_ball _ _)) (convex_pi (fun _ _ => ?_))
split_ifs
· simp_rw [abs_lt]
refine Convex.inter ((convex_halfSpace_re_gt _).inter (convex_halfSpace_re_lt _))
((convex_halfSpace_im_gt _).inter (convex_halfSpace_im_lt _))
· exact convex_ball _ _
open MeasureTheory MeasureTheory.Measure
variable [NumberField K]
/-- The fudge factor that appears in the formula for the volume of `convexBodyLT'`. -/
noncomputable abbrev convexBodyLT'Factor : ℝ≥0 :=
(2 : ℝ≥0) ^ (nrRealPlaces K + 2) * NNReal.pi ^ (nrComplexPlaces K - 1)
theorem convexBodyLT'Factor_ne_zero : convexBodyLT'Factor K ≠ 0 :=
mul_ne_zero (pow_ne_zero _ two_ne_zero) (pow_ne_zero _ pi_ne_zero)
theorem one_le_convexBodyLT'Factor : 1 ≤ convexBodyLT'Factor K :=
one_le_mul (one_le_pow₀ one_le_two) (one_le_pow₀ (one_le_two.trans Real.two_le_pi))
open scoped Classical in
theorem convexBodyLT'_volume :
volume (convexBodyLT' K f w₀) = convexBodyLT'Factor K * ∏ w, (f w) ^ (mult w) := by
have vol_box : ∀ B : ℝ≥0, volume {x : ℂ | |x.re| < 1 ∧ |x.im| < B^2} = 4*B^2 := by
intro B
rw [← (Complex.volume_preserving_equiv_real_prod.symm).measure_preimage]
· simp_rw [Set.preimage_setOf_eq, Complex.measurableEquivRealProd_symm_apply]
rw [show {a : ℝ × ℝ | |a.1| < 1 ∧ |a.2| < B ^ 2} =
Set.Ioo (-1 : ℝ) (1 : ℝ) ×ˢ Set.Ioo (- (B : ℝ) ^ 2) ((B : ℝ) ^ 2) by
ext; simp_rw [Set.mem_setOf_eq, Set.mem_prod, Set.mem_Ioo, abs_lt]]
simp_rw [volume_eq_prod, prod_prod, Real.volume_Ioo, sub_neg_eq_add, one_add_one_eq_two,
← two_mul, ofReal_mul zero_le_two, ofReal_pow (coe_nonneg B), ofReal_ofNat,
ofReal_coe_nnreal, ← mul_assoc, show (2 : ℝ≥0∞) * 2 = 4 by norm_num]
· refine (MeasurableSet.inter ?_ ?_).nullMeasurableSet
· exact measurableSet_lt (measurable_norm.comp Complex.measurable_re) measurable_const
· exact measurableSet_lt (measurable_norm.comp Complex.measurable_im) measurable_const
calc
_ = (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (2 * (f x.val))) *
((∏ x ∈ Finset.univ.erase w₀, ENNReal.ofReal (f x.val) ^ 2 * pi) *
(4 * (f w₀) ^ 2)) := by
simp_rw [volume_eq_prod, prod_prod, volume_pi, pi_pi, Real.volume_ball]
rw [← Finset.prod_erase_mul _ _ (Finset.mem_univ w₀)]
congr 2
· refine Finset.prod_congr rfl (fun w' hw' ↦ ?_)
rw [if_neg (Finset.ne_of_mem_erase hw'), Complex.volume_ball]
· simpa only [ite_true] using vol_box (f w₀)
_ = ((2 : ℝ≥0) ^ nrRealPlaces K *
(∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (f x.val))) *
((∏ x ∈ Finset.univ.erase w₀, ENNReal.ofReal (f x.val) ^ 2) *
↑pi ^ (nrComplexPlaces K - 1) * (4 * (f w₀) ^ 2)) := by
simp_rw [ofReal_mul (by norm_num : 0 ≤ (2 : ℝ)), Finset.prod_mul_distrib, Finset.prod_const,
Finset.card_erase_of_mem (Finset.mem_univ _), Finset.card_univ, ofReal_ofNat,
ofReal_coe_nnreal, coe_ofNat]
_ = convexBodyLT'Factor K * (∏ x : {w // InfinitePlace.IsReal w}, ENNReal.ofReal (f x.val))
* (∏ x : {w // IsComplex w}, ENNReal.ofReal (f x.val) ^ 2) := by
rw [show (4 : ℝ≥0∞) = (2 : ℝ≥0) ^ 2 by norm_num, convexBodyLT'Factor, pow_add,
← Finset.prod_erase_mul _ _ (Finset.mem_univ w₀), ofReal_coe_nnreal]
simp_rw [coe_mul, ENNReal.coe_pow]
ring
_ = convexBodyLT'Factor K * ∏ w, (f w) ^ (mult w) := by
simp_rw [prod_eq_prod_mul_prod, coe_mul, coe_finset_prod, mult_isReal, mult_isComplex,
pow_one, ENNReal.coe_pow, ofReal_coe_nnreal, mul_assoc]
end convexBodyLT'
section convexBodySum
open ENNReal MeasureTheory Fintype
open scoped Real NNReal
variable [NumberField K] (B : ℝ)
variable {K}
/-- The function that sends `x : mixedSpace K` to `∑ w, ‖x.1 w‖ + 2 * ∑ w, ‖x.2 w‖`. It defines a
norm and it used to define `convexBodySum`. -/
noncomputable abbrev convexBodySumFun (x : mixedSpace K) : ℝ := ∑ w, mult w * normAtPlace w x
theorem convexBodySumFun_apply (x : mixedSpace K) :
convexBodySumFun x = ∑ w, mult w * normAtPlace w x := rfl
open scoped Classical in
theorem convexBodySumFun_apply' (x : mixedSpace K) :
convexBodySumFun x = ∑ w, ‖x.1 w‖ + 2 * ∑ w, ‖x.2 w‖ := by
simp_rw [convexBodySumFun_apply, sum_eq_sum_add_sum, mult_isReal, mult_isComplex,
Nat.cast_one, one_mul, Nat.cast_ofNat, normAtPlace_apply_of_isReal (Subtype.prop _),
normAtPlace_apply_of_isComplex (Subtype.prop _), Finset.mul_sum]
theorem convexBodySumFun_nonneg (x : mixedSpace K) :
0 ≤ convexBodySumFun x :=
Finset.sum_nonneg (fun _ _ => mul_nonneg (Nat.cast_pos.mpr mult_pos).le (normAtPlace_nonneg _ _))
theorem convexBodySumFun_neg (x : mixedSpace K) :
convexBodySumFun (- x) = convexBodySumFun x := by
simp_rw [convexBodySumFun, normAtPlace_neg]
theorem convexBodySumFun_add_le (x y : mixedSpace K) :
convexBodySumFun (x + y) ≤ convexBodySumFun x + convexBodySumFun y := by
simp_rw [convexBodySumFun, ← Finset.sum_add_distrib, ← mul_add]
exact Finset.sum_le_sum
fun _ _ ↦ mul_le_mul_of_nonneg_left (normAtPlace_add_le _ x y) (Nat.cast_pos.mpr mult_pos).le
theorem convexBodySumFun_smul (c : ℝ) (x : mixedSpace K) :
convexBodySumFun (c • x) = |c| * convexBodySumFun x := by
simp_rw [convexBodySumFun, normAtPlace_smul, ← mul_assoc, mul_comm, Finset.mul_sum, mul_assoc]
theorem convexBodySumFun_eq_zero_iff (x : mixedSpace K) :
convexBodySumFun x = 0 ↔ x = 0 := by
rw [← forall_normAtPlace_eq_zero_iff, convexBodySumFun, Finset.sum_eq_zero_iff_of_nonneg
fun _ _ ↦ mul_nonneg (Nat.cast_pos.mpr mult_pos).le (normAtPlace_nonneg _ _)]
conv =>
enter [1, w, hw]
rw [mul_left_mem_nonZeroDivisors_eq_zero_iff
(mem_nonZeroDivisors_iff_ne_zero.mpr <| Nat.cast_ne_zero.mpr mult_ne_zero)]
simp_rw [Finset.mem_univ, true_implies]
open scoped Classical in
theorem norm_le_convexBodySumFun (x : mixedSpace K) : ‖x‖ ≤ convexBodySumFun x := by
rw [norm_eq_sup'_normAtPlace]
refine (Finset.sup'_le_iff _ _).mpr fun w _ ↦ ?_
rw [convexBodySumFun_apply, ← Finset.univ.add_sum_erase _ (Finset.mem_univ w)]
refine le_add_of_le_of_nonneg ?_ ?_
· exact le_mul_of_one_le_left (normAtPlace_nonneg w x) one_le_mult
· exact Finset.sum_nonneg (fun _ _ => mul_nonneg (Nat.cast_pos.mpr mult_pos).le
(normAtPlace_nonneg _ _))
variable (K)
theorem convexBodySumFun_continuous :
Continuous (convexBodySumFun : mixedSpace K → ℝ) := by
refine continuous_finset_sum Finset.univ fun w ↦ ?_
obtain hw | hw := isReal_or_isComplex w
all_goals
· simp only [normAtPlace_apply_of_isReal, normAtPlace_apply_of_isComplex, hw]
fun_prop
/-- The convex body equal to the set of points `x : mixedSpace K` such that
`∑ w real, ‖x w‖ + 2 * ∑ w complex, ‖x w‖ ≤ B`. -/
abbrev convexBodySum : Set (mixedSpace K) := { x | convexBodySumFun x ≤ B }
open scoped Classical in
theorem convexBodySum_volume_eq_zero_of_le_zero {B} (hB : B ≤ 0) :
volume (convexBodySum K B) = 0 := by
obtain hB | hB := lt_or_eq_of_le hB
· suffices convexBodySum K B = ∅ by rw [this, measure_empty]
ext x
refine ⟨fun hx => ?_, fun h => h.elim⟩
rw [Set.mem_setOf] at hx
linarith [convexBodySumFun_nonneg x]
· suffices convexBodySum K B = { 0 } by rw [this, measure_singleton]
ext
rw [convexBodySum, Set.mem_setOf_eq, Set.mem_singleton_iff, hB, ← convexBodySumFun_eq_zero_iff]
exact (convexBodySumFun_nonneg _).le_iff_eq
theorem convexBodySum_mem {x : K} :
mixedEmbedding K x ∈ (convexBodySum K B) ↔
∑ w : InfinitePlace K, (mult w) * w.val x ≤ B := by
simp_rw [Set.mem_setOf_eq, convexBodySumFun, normAtPlace_apply]
rfl
theorem convexBodySum_neg_mem {x : mixedSpace K} (hx : x ∈ (convexBodySum K B)) :
-x ∈ (convexBodySum K B) := by
rw [Set.mem_setOf, convexBodySumFun_neg]
exact hx
theorem convexBodySum_convex : Convex ℝ (convexBodySum K B) := by
refine Convex_subadditive_le (fun _ _ => convexBodySumFun_add_le _ _) (fun c x h => ?_) B
convert le_of_eq (convexBodySumFun_smul c x)
exact (abs_eq_self.mpr h).symm
theorem convexBodySum_isBounded : Bornology.IsBounded (convexBodySum K B) := by
classical
refine Metric.isBounded_iff.mpr ⟨B + B, fun x hx y hy => ?_⟩
refine le_trans (norm_sub_le x y) (add_le_add ?_ ?_)
· exact le_trans (norm_le_convexBodySumFun x) hx
· exact le_trans (norm_le_convexBodySumFun y) hy
theorem convexBodySum_compact : IsCompact (convexBodySum K B) := by
classical
rw [Metric.isCompact_iff_isClosed_bounded]
refine ⟨?_, convexBodySum_isBounded K B⟩
convert IsClosed.preimage (convexBodySumFun_continuous K) (isClosed_Icc : IsClosed (Set.Icc 0 B))
ext
simp [convexBodySumFun_nonneg]
/-- The fudge factor that appears in the formula for the volume of `convexBodyLt`. -/
noncomputable abbrev convexBodySumFactor : ℝ≥0 :=
(2 : ℝ≥0) ^ nrRealPlaces K * (NNReal.pi / 2) ^ nrComplexPlaces K / (finrank ℚ K).factorial
|
theorem convexBodySumFactor_ne_zero : convexBodySumFactor K ≠ 0 := by
refine div_ne_zero ?_ <| Nat.cast_ne_zero.mpr (Nat.factorial_ne_zero _)
exact mul_ne_zero (pow_ne_zero _ two_ne_zero)
| Mathlib/NumberTheory/NumberField/CanonicalEmbedding/ConvexBody.lean | 368 | 371 |
/-
Copyright (c) 2020 Frédéric Dupuis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Frédéric Dupuis, Eric Wieser
-/
import Mathlib.LinearAlgebra.Multilinear.TensorProduct
import Mathlib.Tactic.AdaptationNote
import Mathlib.LinearAlgebra.Multilinear.Curry
/-!
# Tensor product of an indexed family of modules over commutative semirings
We define the tensor product of an indexed family `s : ι → Type*` of modules over commutative
semirings. We denote this space by `⨂[R] i, s i` and define it as `FreeAddMonoid (R × Π i, s i)`
quotiented by the appropriate equivalence relation. The treatment follows very closely that of the
binary tensor product in `LinearAlgebra/TensorProduct.lean`.
## Main definitions
* `PiTensorProduct R s` with `R` a commutative semiring and `s : ι → Type*` is the tensor product
of all the `s i`'s. This is denoted by `⨂[R] i, s i`.
* `tprod R f` with `f : Π i, s i` is the tensor product of the vectors `f i` over all `i : ι`.
This is bundled as a multilinear map from `Π i, s i` to `⨂[R] i, s i`.
* `liftAddHom` constructs an `AddMonoidHom` from `(⨂[R] i, s i)` to some space `F` from a
function `φ : (R × Π i, s i) → F` with the appropriate properties.
* `lift φ` with `φ : MultilinearMap R s E` is the corresponding linear map
`(⨂[R] i, s i) →ₗ[R] E`. This is bundled as a linear equivalence.
* `PiTensorProduct.reindex e` re-indexes the components of `⨂[R] i : ι, M` along `e : ι ≃ ι₂`.
* `PiTensorProduct.tmulEquiv` equivalence between a `TensorProduct` of `PiTensorProduct`s and
a single `PiTensorProduct`.
## Notations
* `⨂[R] i, s i` is defined as localized notation in locale `TensorProduct`.
* `⨂ₜ[R] i, f i` with `f : ∀ i, s i` is defined globally as the tensor product of all the `f i`'s.
## Implementation notes
* We define it via `FreeAddMonoid (R × Π i, s i)` with the `R` representing a "hidden" tensor
factor, rather than `FreeAddMonoid (Π i, s i)` to ensure that, if `ι` is an empty type,
the space is isomorphic to the base ring `R`.
* We have not restricted the index type `ι` to be a `Fintype`, as nothing we do here strictly
requires it. However, problems may arise in the case where `ι` is infinite; use at your own
caution.
* Instead of requiring `DecidableEq ι` as an argument to `PiTensorProduct` itself, we include it
as an argument in the constructors of the relation. A decidability instance still has to come
from somewhere due to the use of `Function.update`, but this hides it from the downstream user.
See the implementation notes for `MultilinearMap` for an extended discussion of this choice.
## TODO
* Define tensor powers, symmetric subspace, etc.
* API for the various ways `ι` can be split into subsets; connect this with the binary
tensor product.
* Include connection with holors.
* Port more of the API from the binary tensor product over to this case.
## Tags
multilinear, tensor, tensor product
-/
suppress_compilation
open Function
section Semiring
variable {ι ι₂ ι₃ : Type*}
variable {R : Type*} [CommSemiring R]
variable {R₁ R₂ : Type*}
variable {s : ι → Type*} [∀ i, AddCommMonoid (s i)] [∀ i, Module R (s i)]
variable {M : Type*} [AddCommMonoid M] [Module R M]
variable {E : Type*} [AddCommMonoid E] [Module R E]
variable {F : Type*} [AddCommMonoid F]
namespace PiTensorProduct
variable (R) (s)
/-- The relation on `FreeAddMonoid (R × Π i, s i)` that generates a congruence whose quotient is
the tensor product. -/
inductive Eqv : FreeAddMonoid (R × Π i, s i) → FreeAddMonoid (R × Π i, s i) → Prop
| of_zero : ∀ (r : R) (f : Π i, s i) (i : ι) (_ : f i = 0), Eqv (FreeAddMonoid.of (r, f)) 0
| of_zero_scalar : ∀ f : Π i, s i, Eqv (FreeAddMonoid.of (0, f)) 0
| of_add : ∀ (_ : DecidableEq ι) (r : R) (f : Π i, s i) (i : ι) (m₁ m₂ : s i),
Eqv (FreeAddMonoid.of (r, update f i m₁) + FreeAddMonoid.of (r, update f i m₂))
(FreeAddMonoid.of (r, update f i (m₁ + m₂)))
| of_add_scalar : ∀ (r r' : R) (f : Π i, s i),
Eqv (FreeAddMonoid.of (r, f) + FreeAddMonoid.of (r', f)) (FreeAddMonoid.of (r + r', f))
| of_smul : ∀ (_ : DecidableEq ι) (r : R) (f : Π i, s i) (i : ι) (r' : R),
Eqv (FreeAddMonoid.of (r, update f i (r' • f i))) (FreeAddMonoid.of (r' * r, f))
| add_comm : ∀ x y, Eqv (x + y) (y + x)
end PiTensorProduct
variable (R) (s)
/-- `PiTensorProduct R s` with `R` a commutative semiring and `s : ι → Type*` is the tensor
product of all the `s i`'s. This is denoted by `⨂[R] i, s i`. -/
def PiTensorProduct : Type _ :=
(addConGen (PiTensorProduct.Eqv R s)).Quotient
variable {R}
unsuppress_compilation in
/-- This enables the notation `⨂[R] i : ι, s i` for the pi tensor product `PiTensorProduct`,
given an indexed family of types `s : ι → Type*`. -/
scoped[TensorProduct] notation3:100"⨂["R"] "(...)", "r:(scoped f => PiTensorProduct R f) => r
open TensorProduct
namespace PiTensorProduct
section Module
instance : AddCommMonoid (⨂[R] i, s i) :=
{ (addConGen (PiTensorProduct.Eqv R s)).addMonoid with
add_comm := fun x y ↦
AddCon.induction_on₂ x y fun _ _ ↦
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.add_comm _ _ }
instance : Inhabited (⨂[R] i, s i) := ⟨0⟩
variable (R) {s}
/-- `tprodCoeff R r f` with `r : R` and `f : Π i, s i` is the tensor product of the vectors `f i`
over all `i : ι`, multiplied by the coefficient `r`. Note that this is meant as an auxiliary
definition for this file alone, and that one should use `tprod` defined below for most purposes. -/
def tprodCoeff (r : R) (f : Π i, s i) : ⨂[R] i, s i :=
AddCon.mk' _ <| FreeAddMonoid.of (r, f)
variable {R}
theorem zero_tprodCoeff (f : Π i, s i) : tprodCoeff R 0 f = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_scalar _
theorem zero_tprodCoeff' (z : R) (f : Π i, s i) (i : ι) (hf : f i = 0) : tprodCoeff R z f = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero _ _ i hf
theorem add_tprodCoeff [DecidableEq ι] (z : R) (f : Π i, s i) (i : ι) (m₁ m₂ : s i) :
tprodCoeff R z (update f i m₁) + tprodCoeff R z (update f i m₂) =
tprodCoeff R z (update f i (m₁ + m₂)) :=
Quotient.sound' <| AddConGen.Rel.of _ _ (Eqv.of_add _ z f i m₁ m₂)
theorem add_tprodCoeff' (z₁ z₂ : R) (f : Π i, s i) :
tprodCoeff R z₁ f + tprodCoeff R z₂ f = tprodCoeff R (z₁ + z₂) f :=
Quotient.sound' <| AddConGen.Rel.of _ _ (Eqv.of_add_scalar z₁ z₂ f)
theorem smul_tprodCoeff_aux [DecidableEq ι] (z : R) (f : Π i, s i) (i : ι) (r : R) :
tprodCoeff R z (update f i (r • f i)) = tprodCoeff R (r * z) f :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_smul _ _ _ _ _
theorem smul_tprodCoeff [DecidableEq ι] (z : R) (f : Π i, s i) (i : ι) (r : R₁) [SMul R₁ R]
[IsScalarTower R₁ R R] [SMul R₁ (s i)] [IsScalarTower R₁ R (s i)] :
tprodCoeff R z (update f i (r • f i)) = tprodCoeff R (r • z) f := by
have h₁ : r • z = r • (1 : R) * z := by rw [smul_mul_assoc, one_mul]
have h₂ : r • f i = (r • (1 : R)) • f i := (smul_one_smul _ _ _).symm
rw [h₁, h₂]
exact smul_tprodCoeff_aux z f i _
/-- Construct an `AddMonoidHom` from `(⨂[R] i, s i)` to some space `F` from a function
`φ : (R × Π i, s i) → F` with the appropriate properties. -/
def liftAddHom (φ : (R × Π i, s i) → F)
(C0 : ∀ (r : R) (f : Π i, s i) (i : ι) (_ : f i = 0), φ (r, f) = 0)
(C0' : ∀ f : Π i, s i, φ (0, f) = 0)
(C_add : ∀ [DecidableEq ι] (r : R) (f : Π i, s i) (i : ι) (m₁ m₂ : s i),
φ (r, update f i m₁) + φ (r, update f i m₂) = φ (r, update f i (m₁ + m₂)))
(C_add_scalar : ∀ (r r' : R) (f : Π i, s i), φ (r, f) + φ (r', f) = φ (r + r', f))
(C_smul : ∀ [DecidableEq ι] (r : R) (f : Π i, s i) (i : ι) (r' : R),
φ (r, update f i (r' • f i)) = φ (r' * r, f)) :
(⨂[R] i, s i) →+ F :=
(addConGen (PiTensorProduct.Eqv R s)).lift (FreeAddMonoid.lift φ) <|
AddCon.addConGen_le fun x y hxy ↦
match hxy with
| Eqv.of_zero r' f i hf =>
(AddCon.ker_rel _).2 <| by simp [FreeAddMonoid.lift_eval_of, C0 r' f i hf]
| Eqv.of_zero_scalar f =>
(AddCon.ker_rel _).2 <| by simp [FreeAddMonoid.lift_eval_of, C0']
| Eqv.of_add inst z f i m₁ m₂ =>
(AddCon.ker_rel _).2 <| by simp [FreeAddMonoid.lift_eval_of, @C_add inst]
| Eqv.of_add_scalar z₁ z₂ f =>
(AddCon.ker_rel _).2 <| by simp [FreeAddMonoid.lift_eval_of, C_add_scalar]
| Eqv.of_smul inst z f i r' =>
(AddCon.ker_rel _).2 <| by simp [FreeAddMonoid.lift_eval_of, @C_smul inst]
| Eqv.add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [AddMonoidHom.map_add, add_comm]
/-- Induct using `tprodCoeff` -/
@[elab_as_elim]
protected theorem induction_on' {motive : (⨂[R] i, s i) → Prop} (z : ⨂[R] i, s i)
(tprodCoeff : ∀ (r : R) (f : Π i, s i), motive (tprodCoeff R r f))
(add : ∀ x y, motive x → motive y → motive (x + y)) :
motive z := by
have C0 : motive 0 := by
have h₁ := tprodCoeff 0 0
rwa [zero_tprodCoeff] at h₁
refine AddCon.induction_on z fun x ↦ FreeAddMonoid.recOn x C0 ?_
simp_rw [AddCon.coe_add]
refine fun f y ih ↦ add _ _ ?_ ih
convert tprodCoeff f.1 f.2
section DistribMulAction
variable [Monoid R₁] [DistribMulAction R₁ R] [SMulCommClass R₁ R R]
variable [Monoid R₂] [DistribMulAction R₂ R] [SMulCommClass R₂ R R]
-- Most of the time we want the instance below this one, which is easier for typeclass resolution
-- to find.
instance hasSMul' : SMul R₁ (⨂[R] i, s i) :=
⟨fun r ↦
liftAddHom (fun f : R × Π i, s i ↦ tprodCoeff R (r • f.1) f.2)
(fun r' f i hf ↦ by simp_rw [zero_tprodCoeff' _ f i hf])
(fun f ↦ by simp [zero_tprodCoeff]) (fun r' f i m₁ m₂ ↦ by simp [add_tprodCoeff])
(fun r' r'' f ↦ by simp [add_tprodCoeff', mul_add]) fun z f i r' ↦ by
simp [smul_tprodCoeff, mul_smul_comm]⟩
instance : SMul R (⨂[R] i, s i) :=
PiTensorProduct.hasSMul'
theorem smul_tprodCoeff' (r : R₁) (z : R) (f : Π i, s i) :
r • tprodCoeff R z f = tprodCoeff R (r • z) f := rfl
protected theorem smul_add (r : R₁) (x y : ⨂[R] i, s i) : r • (x + y) = r • x + r • y :=
AddMonoidHom.map_add _ _ _
instance distribMulAction' : DistribMulAction R₁ (⨂[R] i, s i) where
smul := (· • ·)
smul_add _ _ _ := AddMonoidHom.map_add _ _ _
mul_smul r r' x :=
PiTensorProduct.induction_on' x (fun {r'' f} ↦ by simp [smul_tprodCoeff', smul_smul])
fun {x y} ihx ihy ↦ by simp_rw [PiTensorProduct.smul_add, ihx, ihy]
one_smul x :=
PiTensorProduct.induction_on' x (fun {r f} ↦ by rw [smul_tprodCoeff', one_smul])
fun {z y} ihz ihy ↦ by simp_rw [PiTensorProduct.smul_add, ihz, ihy]
smul_zero _ := AddMonoidHom.map_zero _
instance smulCommClass' [SMulCommClass R₁ R₂ R] : SMulCommClass R₁ R₂ (⨂[R] i, s i) :=
⟨fun {r' r''} x ↦
PiTensorProduct.induction_on' x (fun {xr xf} ↦ by simp only [smul_tprodCoeff', smul_comm])
fun {z y} ihz ihy ↦ by simp_rw [PiTensorProduct.smul_add, ihz, ihy]⟩
instance isScalarTower' [SMul R₁ R₂] [IsScalarTower R₁ R₂ R] :
IsScalarTower R₁ R₂ (⨂[R] i, s i) :=
⟨fun {r' r''} x ↦
PiTensorProduct.induction_on' x (fun {xr xf} ↦ by simp only [smul_tprodCoeff', smul_assoc])
fun {z y} ihz ihy ↦ by simp_rw [PiTensorProduct.smul_add, ihz, ihy]⟩
end DistribMulAction
-- Most of the time we want the instance below this one, which is easier for typeclass resolution
-- to find.
instance module' [Semiring R₁] [Module R₁ R] [SMulCommClass R₁ R R] : Module R₁ (⨂[R] i, s i) :=
{ PiTensorProduct.distribMulAction' with
add_smul := fun r r' x ↦
PiTensorProduct.induction_on' x
(fun {r f} ↦ by simp_rw [smul_tprodCoeff', add_smul, add_tprodCoeff'])
fun {x y} ihx ihy ↦ by simp_rw [PiTensorProduct.smul_add, ihx, ihy, add_add_add_comm]
zero_smul := fun x ↦
PiTensorProduct.induction_on' x
(fun {r f} ↦ by simp_rw [smul_tprodCoeff', zero_smul, zero_tprodCoeff])
fun {x y} ihx ihy ↦ by simp_rw [PiTensorProduct.smul_add, ihx, ihy, add_zero] }
-- shortcut instances
instance : Module R (⨂[R] i, s i) :=
PiTensorProduct.module'
instance : SMulCommClass R R (⨂[R] i, s i) :=
PiTensorProduct.smulCommClass'
instance : IsScalarTower R R (⨂[R] i, s i) :=
PiTensorProduct.isScalarTower'
variable (R) in
/-- The canonical `MultilinearMap R s (⨂[R] i, s i)`.
`tprod R fun i => f i` has notation `⨂ₜ[R] i, f i`. -/
def tprod : MultilinearMap R s (⨂[R] i, s i) where
toFun := tprodCoeff R 1
map_update_add' {_ f} i x y := (add_tprodCoeff (1 : R) f i x y).symm
map_update_smul' {_ f} i r x := by
rw [smul_tprodCoeff', ← smul_tprodCoeff (1 : R) _ i, update_idem, update_self]
unsuppress_compilation in
@[inherit_doc tprod]
notation3:100 "⨂ₜ["R"] "(...)", "r:(scoped f => tprod R f) => r
theorem tprod_eq_tprodCoeff_one :
⇑(tprod R : MultilinearMap R s (⨂[R] i, s i)) = tprodCoeff R 1 := rfl
@[simp]
theorem tprodCoeff_eq_smul_tprod (z : R) (f : Π i, s i) : tprodCoeff R z f = z • tprod R f := by
have : z = z • (1 : R) := by simp only [mul_one, Algebra.id.smul_eq_mul]
conv_lhs => rw [this]
rfl
/-- The image of an element `p` of `FreeAddMonoid (R × Π i, s i)` in the `PiTensorProduct` is
equal to the sum of `a • ⨂ₜ[R] i, m i` over all the entries `(a, m)` of `p`.
-/
lemma _root_.FreeAddMonoid.toPiTensorProduct (p : FreeAddMonoid (R × Π i, s i)) :
AddCon.toQuotient (c := addConGen (PiTensorProduct.Eqv R s)) p =
List.sum (List.map (fun x ↦ x.1 • ⨂ₜ[R] i, x.2 i) p.toList) := by
-- TODO: this is defeq abuse: `p` is not a `List`.
match p with
| [] => rw [FreeAddMonoid.toList_nil, List.map_nil, List.sum_nil]; rfl
| x :: ps =>
rw [FreeAddMonoid.toList_cons, List.map_cons, List.sum_cons, ← List.singleton_append,
← toPiTensorProduct ps, ← tprodCoeff_eq_smul_tprod]
rfl
/-- The set of lifts of an element `x` of `⨂[R] i, s i` in `FreeAddMonoid (R × Π i, s i)`. -/
def lifts (x : ⨂[R] i, s i) : Set (FreeAddMonoid (R × Π i, s i)) :=
{p | AddCon.toQuotient (c := addConGen (PiTensorProduct.Eqv R s)) p = x}
/-- An element `p` of `FreeAddMonoid (R × Π i, s i)` lifts an element `x` of `⨂[R] i, s i`
if and only if `x` is equal to the sum of `a • ⨂ₜ[R] i, m i` over all the entries
`(a, m)` of `p`.
-/
lemma mem_lifts_iff (x : ⨂[R] i, s i) (p : FreeAddMonoid (R × Π i, s i)) :
p ∈ lifts x ↔ List.sum (List.map (fun x ↦ x.1 • ⨂ₜ[R] i, x.2 i) p.toList) = x := by
simp only [lifts, Set.mem_setOf_eq, FreeAddMonoid.toPiTensorProduct]
/-- Every element of `⨂[R] i, s i` has a lift in `FreeAddMonoid (R × Π i, s i)`.
-/
lemma nonempty_lifts (x : ⨂[R] i, s i) : Set.Nonempty (lifts x) := by
existsi @Quotient.out _ (addConGen (PiTensorProduct.Eqv R s)).toSetoid x
simp only [lifts, Set.mem_setOf_eq]
rw [← AddCon.quot_mk_eq_coe]
erw [Quot.out_eq]
/-- The empty list lifts the element `0` of `⨂[R] i, s i`.
-/
lemma lifts_zero : 0 ∈ lifts (0 : ⨂[R] i, s i) := by
rw [mem_lifts_iff]; erw [List.map_nil]; rw [List.sum_nil]
/-- If elements `p,q` of `FreeAddMonoid (R × Π i, s i)` lift elements `x,y` of `⨂[R] i, s i`
respectively, then `p + q` lifts `x + y`.
-/
lemma lifts_add {x y : ⨂[R] i, s i} {p q : FreeAddMonoid (R × Π i, s i)}
(hp : p ∈ lifts x) (hq : q ∈ lifts y) : p + q ∈ lifts (x + y) := by
simp only [lifts, Set.mem_setOf_eq, AddCon.coe_add]
rw [hp, hq]
/-- If an element `p` of `FreeAddMonoid (R × Π i, s i)` lifts an element `x` of `⨂[R] i, s i`,
and if `a` is an element of `R`, then the list obtained by multiplying the first entry of each
element of `p` by `a` lifts `a • x`.
-/
lemma lifts_smul {x : ⨂[R] i, s i} {p : FreeAddMonoid (R × Π i, s i)} (h : p ∈ lifts x) (a : R) :
p.map (fun (y : R × Π i, s i) ↦ (a * y.1, y.2)) ∈ lifts (a • x) := by
rw [mem_lifts_iff] at h ⊢
rw [← h]
simp [Function.comp_def, mul_smul, List.smul_sum]
/-- Induct using scaled versions of `PiTensorProduct.tprod`. -/
@[elab_as_elim]
protected theorem induction_on {motive : (⨂[R] i, s i) → Prop} (z : ⨂[R] i, s i)
(smul_tprod : ∀ (r : R) (f : Π i, s i), motive (r • tprod R f))
(add : ∀ x y, motive x → motive y → motive (x + y)) :
motive z := by
simp_rw [← tprodCoeff_eq_smul_tprod] at smul_tprod
exact PiTensorProduct.induction_on' z smul_tprod add
@[ext]
theorem ext {φ₁ φ₂ : (⨂[R] i, s i) →ₗ[R] E}
(H : φ₁.compMultilinearMap (tprod R) = φ₂.compMultilinearMap (tprod R)) : φ₁ = φ₂ := by
refine LinearMap.ext ?_
refine fun z ↦
PiTensorProduct.induction_on' z ?_ fun {x y} hx hy ↦ by rw [φ₁.map_add, φ₂.map_add, hx, hy]
· intro r f
rw [tprodCoeff_eq_smul_tprod, φ₁.map_smul, φ₂.map_smul]
apply congr_arg
exact MultilinearMap.congr_fun H f
/-- The pure tensors (i.e. the elements of the image of `PiTensorProduct.tprod`) span
the tensor product. -/
theorem span_tprod_eq_top :
Submodule.span R (Set.range (tprod R)) = (⊤ : Submodule R (⨂[R] i, s i)) :=
Submodule.eq_top_iff'.mpr fun t ↦ t.induction_on
(fun _ _ ↦ Submodule.smul_mem _ _
(Submodule.subset_span (by simp only [Set.mem_range, exists_apply_eq_apply])))
(fun _ _ hx hy ↦ Submodule.add_mem _ hx hy)
end Module
section Multilinear
open MultilinearMap
variable {s}
section lift
/-- Auxiliary function to constructing a linear map `(⨂[R] i, s i) → E` given a
`MultilinearMap R s E` with the property that its composition with the canonical
`MultilinearMap R s (⨂[R] i, s i)` is the given multilinear map. -/
def liftAux (φ : MultilinearMap R s E) : (⨂[R] i, s i) →+ E :=
liftAddHom (fun p : R × Π i, s i ↦ p.1 • φ p.2)
(fun z f i hf ↦ by simp_rw [map_coord_zero φ i hf, smul_zero])
(fun f ↦ by simp_rw [zero_smul])
(fun z f i m₁ m₂ ↦ by simp_rw [← smul_add, φ.map_update_add])
(fun z₁ z₂ f ↦ by rw [← add_smul])
fun z f i r ↦ by simp [φ.map_update_smul, smul_smul, mul_comm]
theorem liftAux_tprod (φ : MultilinearMap R s E) (f : Π i, s i) : liftAux φ (tprod R f) = φ f := by
simp only [liftAux, liftAddHom, tprod_eq_tprodCoeff_one, tprodCoeff, AddCon.coe_mk']
-- The end of this proof was very different before https://github.com/leanprover/lean4/pull/2644:
-- rw [FreeAddMonoid.of, FreeAddMonoid.ofList, Equiv.refl_apply, AddCon.lift_coe]
-- dsimp [FreeAddMonoid.lift, FreeAddMonoid.sumAux]
-- show _ • _ = _
-- rw [one_smul]
erw [AddCon.lift_coe]
rw [FreeAddMonoid.of]
dsimp [FreeAddMonoid.ofList]
rw [← one_smul R (φ f)]
erw [Equiv.refl_apply]
convert one_smul R (φ f)
simp
theorem liftAux_tprodCoeff (φ : MultilinearMap R s E) (z : R) (f : Π i, s i) :
liftAux φ (tprodCoeff R z f) = z • φ f := rfl
theorem liftAux.smul {φ : MultilinearMap R s E} (r : R) (x : ⨂[R] i, s i) :
liftAux φ (r • x) = r • liftAux φ x := by
refine PiTensorProduct.induction_on' x ?_ ?_
· intro z f
rw [smul_tprodCoeff' r z f, liftAux_tprodCoeff, liftAux_tprodCoeff, smul_assoc]
· intro z y ihz ihy
rw [smul_add, (liftAux φ).map_add, ihz, ihy, (liftAux φ).map_add, smul_add]
/-- Constructing a linear map `(⨂[R] i, s i) → E` given a `MultilinearMap R s E` with the
property that its composition with the canonical `MultilinearMap R s E` is
the given multilinear map `φ`. -/
def lift : MultilinearMap R s E ≃ₗ[R] (⨂[R] i, s i) →ₗ[R] E where
toFun φ := { liftAux φ with map_smul' := liftAux.smul }
invFun φ' := φ'.compMultilinearMap (tprod R)
left_inv φ := by
ext
simp [liftAux_tprod, LinearMap.compMultilinearMap]
right_inv φ := by
ext
simp [liftAux_tprod]
map_add' φ₁ φ₂ := by
ext
simp [liftAux_tprod]
map_smul' r φ₂ := by
ext
simp [liftAux_tprod]
variable {φ : MultilinearMap R s E}
@[simp]
theorem lift.tprod (f : Π i, s i) : lift φ (tprod R f) = φ f :=
liftAux_tprod φ f
theorem lift.unique' {φ' : (⨂[R] i, s i) →ₗ[R] E}
(H : φ'.compMultilinearMap (PiTensorProduct.tprod R) = φ) : φ' = lift φ :=
ext <| H.symm ▸ (lift.symm_apply_apply φ).symm
theorem lift.unique {φ' : (⨂[R] i, s i) →ₗ[R] E} (H : ∀ f, φ' (PiTensorProduct.tprod R f) = φ f) :
φ' = lift φ :=
lift.unique' (MultilinearMap.ext H)
@[simp]
theorem lift_symm (φ' : (⨂[R] i, s i) →ₗ[R] E) : lift.symm φ' = φ'.compMultilinearMap (tprod R) :=
rfl
@[simp]
theorem lift_tprod : lift (tprod R : MultilinearMap R s _) = LinearMap.id :=
Eq.symm <| lift.unique' rfl
end lift
section map
variable {t t' : ι → Type*}
variable [∀ i, AddCommMonoid (t i)] [∀ i, Module R (t i)]
variable [∀ i, AddCommMonoid (t' i)] [∀ i, Module R (t' i)]
variable (g : Π i, t i →ₗ[R] t' i) (f : Π i, s i →ₗ[R] t i)
/--
Let `sᵢ` and `tᵢ` be two families of `R`-modules.
Let `f` be a family of `R`-linear maps between `sᵢ` and `tᵢ`, i.e. `f : Πᵢ sᵢ → tᵢ`,
then there is an induced map `⨂ᵢ sᵢ → ⨂ᵢ tᵢ` by `⨂ aᵢ ↦ ⨂ fᵢ aᵢ`.
This is `TensorProduct.map` for an arbitrary family of modules.
-/
def map : (⨂[R] i, s i) →ₗ[R] ⨂[R] i, t i :=
lift <| (tprod R).compLinearMap f
@[simp] lemma map_tprod (x : Π i, s i) :
map f (tprod R x) = tprod R fun i ↦ f i (x i) :=
lift.tprod _
-- No lemmas about associativity, because we don't have associativity of `PiTensorProduct` yet.
theorem map_range_eq_span_tprod :
LinearMap.range (map f) =
Submodule.span R {t | ∃ (m : Π i, s i), tprod R (fun i ↦ f i (m i)) = t} := by
rw [← Submodule.map_top, ← span_tprod_eq_top, Submodule.map_span, ← Set.range_comp]
apply congrArg; ext x
simp only [Set.mem_range, comp_apply, map_tprod, Set.mem_setOf_eq]
/-- Given submodules `p i ⊆ s i`, this is the natural map: `⨂[R] i, p i → ⨂[R] i, s i`.
This is `TensorProduct.mapIncl` for an arbitrary family of modules.
-/
@[simp]
def mapIncl (p : Π i, Submodule R (s i)) : (⨂[R] i, p i) →ₗ[R] ⨂[R] i, s i :=
map fun (i : ι) ↦ (p i).subtype
theorem map_comp : map (fun (i : ι) ↦ g i ∘ₗ f i) = map g ∘ₗ map f := by
ext
simp only [LinearMap.compMultilinearMap_apply, map_tprod, LinearMap.coe_comp, Function.comp_apply]
theorem lift_comp_map (h : MultilinearMap R t E) :
lift h ∘ₗ map f = lift (h.compLinearMap f) := by
ext
simp only [LinearMap.compMultilinearMap_apply, LinearMap.coe_comp, Function.comp_apply,
map_tprod, lift.tprod, MultilinearMap.compLinearMap_apply]
attribute [local ext high] ext
@[simp]
theorem map_id : map (fun i ↦ (LinearMap.id : s i →ₗ[R] s i)) = .id := by
ext
simp only [LinearMap.compMultilinearMap_apply, map_tprod, LinearMap.id_coe, id_eq]
@[simp]
protected theorem map_one : map (fun (i : ι) ↦ (1 : s i →ₗ[R] s i)) = 1 :=
map_id
protected theorem map_mul (f₁ f₂ : Π i, s i →ₗ[R] s i) :
map (fun i ↦ f₁ i * f₂ i) = map f₁ * map f₂ :=
map_comp f₁ f₂
/-- Upgrading `PiTensorProduct.map` to a `MonoidHom` when `s = t`. -/
@[simps]
def mapMonoidHom : (Π i, s i →ₗ[R] s i) →* ((⨂[R] i, s i) →ₗ[R] ⨂[R] i, s i) where
toFun := map
map_one' := PiTensorProduct.map_one
map_mul' := PiTensorProduct.map_mul
@[simp]
protected theorem map_pow (f : Π i, s i →ₗ[R] s i) (n : ℕ) :
map (f ^ n) = map f ^ n := MonoidHom.map_pow mapMonoidHom _ _
open Function in
private theorem map_add_smul_aux [DecidableEq ι] (i : ι) (x : Π i, s i) (u : s i →ₗ[R] t i) :
(fun j ↦ update f i u j (x j)) = update (fun j ↦ (f j) (x j)) i (u (x i)) := by
ext j
exact apply_update (fun i F => F (x i)) f i u j
open Function in
protected theorem map_update_add [DecidableEq ι] (i : ι) (u v : s i →ₗ[R] t i) :
map (update f i (u + v)) = map (update f i u) + map (update f i v) := by
ext x
simp only [LinearMap.compMultilinearMap_apply, map_tprod, map_add_smul_aux, LinearMap.add_apply,
MultilinearMap.map_update_add]
@[deprecated (since := "2024-11-03")] protected alias map_add := PiTensorProduct.map_update_add
open Function in
protected theorem map_update_smul [DecidableEq ι] (i : ι) (c : R) (u : s i →ₗ[R] t i) :
map (update f i (c • u)) = c • map (update f i u) := by
ext x
simp only [LinearMap.compMultilinearMap_apply, map_tprod, map_add_smul_aux, LinearMap.smul_apply,
MultilinearMap.map_update_smul]
@[deprecated (since := "2024-11-03")] protected alias map_smul := PiTensorProduct.map_update_smul
variable (R s t)
/-- The tensor of a family of linear maps from `sᵢ` to `tᵢ`, as a multilinear map of
the family.
-/
@[simps]
noncomputable def mapMultilinear :
MultilinearMap R (fun (i : ι) ↦ s i →ₗ[R] t i) ((⨂[R] i, s i) →ₗ[R] ⨂[R] i, t i) where
toFun := map
map_update_smul' _ _ _ _ := PiTensorProduct.map_update_smul _ _ _ _
map_update_add' _ _ _ _ := PiTensorProduct.map_update_add _ _ _ _
variable {R s t}
/--
Let `sᵢ` and `tᵢ` be families of `R`-modules.
Then there is an `R`-linear map between `⨂ᵢ Hom(sᵢ, tᵢ)` and `Hom(⨂ᵢ sᵢ, ⨂ tᵢ)` defined by
`⨂ᵢ fᵢ ↦ ⨂ᵢ aᵢ ↦ ⨂ᵢ fᵢ aᵢ`.
This is `TensorProduct.homTensorHomMap` for an arbitrary family of modules.
Note that `PiTensorProduct.piTensorHomMap (tprod R f)` is equal to `PiTensorProduct.map f`.
-/
def piTensorHomMap : (⨂[R] i, s i →ₗ[R] t i) →ₗ[R] (⨂[R] i, s i) →ₗ[R] ⨂[R] i, t i :=
lift.toLinearMap ∘ₗ lift (MultilinearMap.piLinearMap <| tprod R)
@[simp] lemma piTensorHomMap_tprod_tprod (f : Π i, s i →ₗ[R] t i) (x : Π i, s i) :
piTensorHomMap (tprod R f) (tprod R x) = tprod R fun i ↦ f i (x i) := by
simp [piTensorHomMap]
lemma piTensorHomMap_tprod_eq_map (f : Π i, s i →ₗ[R] t i) :
piTensorHomMap (tprod R f) = map f := by
ext; simp
/-- If `s i` and `t i` are linearly equivalent for every `i` in `ι`, then `⨂[R] i, s i` and
`⨂[R] i, t i` are linearly equivalent.
This is the n-ary version of `TensorProduct.congr`
-/
noncomputable def congr (f : Π i, s i ≃ₗ[R] t i) :
(⨂[R] i, s i) ≃ₗ[R] ⨂[R] i, t i :=
.ofLinear
(map (fun i ↦ f i))
(map (fun i ↦ (f i).symm))
(by ext; simp)
(by ext; simp)
@[simp]
theorem congr_tprod (f : Π i, s i ≃ₗ[R] t i) (m : Π i, s i) :
congr f (tprod R m) = tprod R (fun (i : ι) ↦ (f i) (m i)) := by
simp only [congr, LinearEquiv.ofLinear_apply, map_tprod, LinearEquiv.coe_coe]
@[simp]
theorem congr_symm_tprod (f : Π i, s i ≃ₗ[R] t i) (p : Π i, t i) :
(congr f).symm (tprod R p) = tprod R (fun (i : ι) ↦ (f i).symm (p i)) := by
simp only [congr, LinearEquiv.ofLinear_symm_apply, map_tprod, LinearEquiv.coe_coe]
/--
Let `sᵢ`, `tᵢ` and `t'ᵢ` be families of `R`-modules, then `f : Πᵢ sᵢ → tᵢ → t'ᵢ` induces an
element of `Hom(⨂ᵢ sᵢ, Hom(⨂ tᵢ, ⨂ᵢ t'ᵢ))` defined by `⨂ᵢ aᵢ ↦ ⨂ᵢ bᵢ ↦ ⨂ᵢ fᵢ aᵢ bᵢ`.
This is `PiTensorProduct.map` for two arbitrary families of modules.
This is `TensorProduct.map₂` for families of modules.
-/
def map₂ (f : Π i, s i →ₗ[R] t i →ₗ[R] t' i) :
(⨂[R] i, s i) →ₗ[R] (⨂[R] i, t i) →ₗ[R] ⨂[R] i, t' i :=
lift <| LinearMap.compMultilinearMap piTensorHomMap <| (tprod R).compLinearMap f
lemma map₂_tprod_tprod (f : Π i, s i →ₗ[R] t i →ₗ[R] t' i) (x : Π i, s i) (y : Π i, t i) :
map₂ f (tprod R x) (tprod R y) = tprod R fun i ↦ f i (x i) (y i) := by
simp [map₂]
/--
Let `sᵢ`, `tᵢ` and `t'ᵢ` be families of `R`-modules.
Then there is a function from `⨂ᵢ Hom(sᵢ, Hom(tᵢ, t'ᵢ))` to `Hom(⨂ᵢ sᵢ, Hom(⨂ tᵢ, ⨂ᵢ t'ᵢ))`
defined by `⨂ᵢ fᵢ ↦ ⨂ᵢ aᵢ ↦ ⨂ᵢ bᵢ ↦ ⨂ᵢ fᵢ aᵢ bᵢ`. -/
def piTensorHomMapFun₂ : (⨂[R] i, s i →ₗ[R] t i →ₗ[R] t' i) →
(⨂[R] i, s i) →ₗ[R] (⨂[R] i, t i) →ₗ[R] (⨂[R] i, t' i) :=
fun φ => lift <| LinearMap.compMultilinearMap piTensorHomMap <|
(lift <| MultilinearMap.piLinearMap <| tprod R) φ
theorem piTensorHomMapFun₂_add (φ ψ : ⨂[R] i, s i →ₗ[R] t i →ₗ[R] t' i) :
piTensorHomMapFun₂ (φ + ψ) = piTensorHomMapFun₂ φ + piTensorHomMapFun₂ ψ := by
dsimp [piTensorHomMapFun₂]; ext; simp only [map_add, LinearMap.compMultilinearMap_apply,
lift.tprod, add_apply, LinearMap.add_apply]
theorem piTensorHomMapFun₂_smul (r : R) (φ : ⨂[R] i, s i →ₗ[R] t i →ₗ[R] t' i) :
piTensorHomMapFun₂ (r • φ) = r • piTensorHomMapFun₂ φ := by
dsimp [piTensorHomMapFun₂]; ext; simp only [map_smul, LinearMap.compMultilinearMap_apply,
lift.tprod, smul_apply, LinearMap.smul_apply]
/--
Let `sᵢ`, `tᵢ` and `t'ᵢ` be families of `R`-modules.
Then there is an linear map from `⨂ᵢ Hom(sᵢ, Hom(tᵢ, t'ᵢ))` to `Hom(⨂ᵢ sᵢ, Hom(⨂ tᵢ, ⨂ᵢ t'ᵢ))`
defined by `⨂ᵢ fᵢ ↦ ⨂ᵢ aᵢ ↦ ⨂ᵢ bᵢ ↦ ⨂ᵢ fᵢ aᵢ bᵢ`.
This is `TensorProduct.homTensorHomMap` for two arbitrary families of modules.
-/
def piTensorHomMap₂ : (⨂[R] i, s i →ₗ[R] t i →ₗ[R] t' i) →ₗ[R]
(⨂[R] i, s i) →ₗ[R] (⨂[R] i, t i) →ₗ[R] (⨂[R] i, t' i) where
toFun := piTensorHomMapFun₂
map_add' x y := piTensorHomMapFun₂_add x y
map_smul' x y := piTensorHomMapFun₂_smul x y
@[simp] lemma piTensorHomMap₂_tprod_tprod_tprod
(f : ∀ i, s i →ₗ[R] t i →ₗ[R] t' i) (a : ∀ i, s i) (b : ∀ i, t i) :
piTensorHomMap₂ (tprod R f) (tprod R a) (tprod R b) = tprod R (fun i ↦ f i (a i) (b i)) := by
simp [piTensorHomMapFun₂, piTensorHomMap₂]
end map
section
variable (R M)
variable (s) in
/-- Re-index the components of the tensor power by `e`. -/
def reindex (e : ι ≃ ι₂) : (⨂[R] i : ι, s i) ≃ₗ[R] ⨂[R] i : ι₂, s (e.symm i) :=
let f := domDomCongrLinearEquiv' R R s (⨂[R] (i : ι₂), s (e.symm i)) e
let g := domDomCongrLinearEquiv' R R s (⨂[R] (i : ι), s i) e
#adaptation_note /-- v4.7.0-rc1
An alternative to the last two proofs would be `aesop (simp_config := {zetaDelta := true})`
or a wrapper macro to that effect. -/
LinearEquiv.ofLinear (lift <| f.symm <| tprod R) (lift <| g <| tprod R)
(by aesop (add norm simp [f, g]))
(by aesop (add norm simp [f, g]))
end
@[simp]
theorem reindex_tprod (e : ι ≃ ι₂) (f : Π i, s i) :
reindex R s e (tprod R f) = tprod R fun i ↦ f (e.symm i) := by
dsimp [reindex]
exact liftAux_tprod _ f
@[simp]
theorem reindex_comp_tprod (e : ι ≃ ι₂) :
(reindex R s e).compMultilinearMap (tprod R) =
(domDomCongrLinearEquiv' R R s _ e).symm (tprod R) :=
MultilinearMap.ext <| reindex_tprod e
theorem lift_comp_reindex (e : ι ≃ ι₂) (φ : MultilinearMap R (fun i ↦ s (e.symm i)) E) :
lift φ ∘ₗ (reindex R s e) = lift ((domDomCongrLinearEquiv' R R s _ e).symm φ) := by
ext; simp [reindex]
@[simp]
theorem lift_comp_reindex_symm (e : ι ≃ ι₂) (φ : MultilinearMap R s E) :
lift φ ∘ₗ (reindex R s e).symm = lift (domDomCongrLinearEquiv' R R s _ e φ) := by
ext; simp [reindex]
theorem lift_reindex
(e : ι ≃ ι₂) (φ : MultilinearMap R (fun i ↦ s (e.symm i)) E) (x : ⨂[R] i, s i) :
lift φ (reindex R s e x) = lift ((domDomCongrLinearEquiv' R R s _ e).symm φ) x :=
LinearMap.congr_fun (lift_comp_reindex e φ) x
@[simp]
theorem lift_reindex_symm
(e : ι ≃ ι₂) (φ : MultilinearMap R s E) (x : ⨂[R] i, s (e.symm i)) :
lift φ (reindex R s e |>.symm x) = lift (domDomCongrLinearEquiv' R R s _ e φ) x :=
LinearMap.congr_fun (lift_comp_reindex_symm e φ) x
@[simp]
theorem reindex_trans (e : ι ≃ ι₂) (e' : ι₂ ≃ ι₃) :
(reindex R s e).trans (reindex R _ e') = reindex R s (e.trans e') := by
apply LinearEquiv.toLinearMap_injective
ext f
simp only [LinearEquiv.trans_apply, LinearEquiv.coe_coe, reindex_tprod,
LinearMap.coe_compMultilinearMap, Function.comp_apply, MultilinearMap.domDomCongr_apply,
reindex_comp_tprod]
congr
theorem reindex_reindex (e : ι ≃ ι₂) (e' : ι₂ ≃ ι₃) (x : ⨂[R] i, s i) :
reindex R _ e' (reindex R s e x) = reindex R s (e.trans e') x :=
LinearEquiv.congr_fun (reindex_trans e e' : _ = reindex R s (e.trans e')) x
/-- This lemma is impractical to state in the dependent case. -/
@[simp]
theorem reindex_symm (e : ι ≃ ι₂) :
(reindex R (fun _ ↦ M) e).symm = reindex R (fun _ ↦ M) e.symm := by
ext x
simp only [reindex, domDomCongrLinearEquiv', LinearEquiv.coe_symm_mk, LinearEquiv.coe_mk,
LinearEquiv.ofLinear_symm_apply, Equiv.symm_symm_apply, LinearEquiv.ofLinear_apply,
Equiv.piCongrLeft'_symm]
@[simp]
theorem reindex_refl : reindex R s (Equiv.refl ι) = LinearEquiv.refl R _ := by
apply LinearEquiv.toLinearMap_injective
ext
simp only [Equiv.refl_symm, Equiv.refl_apply, reindex, domDomCongrLinearEquiv',
LinearEquiv.coe_symm_mk, LinearMap.compMultilinearMap_apply, LinearEquiv.coe_coe,
LinearEquiv.refl_toLinearMap, LinearMap.id_coe, id_eq]
erw [lift.tprod]
congr
variable {t : ι → Type*}
variable [∀ i, AddCommMonoid (t i)] [∀ i, Module R (t i)]
/-- Re-indexing the components of the tensor product by an equivalence `e` is compatible
with `PiTensorProduct.map`. -/
theorem map_comp_reindex_eq (f : Π i, s i →ₗ[R] t i) (e : ι ≃ ι₂) :
| map (fun i ↦ f (e.symm i)) ∘ₗ reindex R s e = reindex R t e ∘ₗ map f := by
ext m
simp only [LinearMap.compMultilinearMap_apply, LinearMap.coe_comp, LinearEquiv.coe_coe,
LinearMap.comp_apply, reindex_tprod, map_tprod]
theorem map_reindex (f : Π i, s i →ₗ[R] t i) (e : ι ≃ ι₂) (x : ⨂[R] i, s i) :
map (fun i ↦ f (e.symm i)) (reindex R s e x) = reindex R t e (map f x) :=
DFunLike.congr_fun (map_comp_reindex_eq _ _) _
| Mathlib/LinearAlgebra/PiTensorProduct.lean | 770 | 777 |
/-
Copyright (c) 2021 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Kim Morrison
-/
import Mathlib.Algebra.Field.Subfield.Defs
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.Order.Group.Pointwise.Interval
import Mathlib.Topology.Algebra.GroupWithZero
import Mathlib.Topology.Algebra.Ring.Basic
import Mathlib.Topology.Order.LocalExtr
/-!
# Topological fields
A topological division ring is a topological ring whose inversion function is continuous at every
non-zero element.
-/
variable {K : Type*} [DivisionRing K] [TopologicalSpace K]
/-- Left-multiplication by a nonzero element of a topological division ring is proper, i.e.,
inverse images of compact sets are compact. -/
theorem Filter.tendsto_cocompact_mul_left₀ [ContinuousMul K] {a : K} (ha : a ≠ 0) :
Filter.Tendsto (fun x : K => a * x) (Filter.cocompact K) (Filter.cocompact K) :=
Filter.tendsto_cocompact_mul_left (inv_mul_cancel₀ ha)
/-- Right-multiplication by a nonzero element of a topological division ring is proper, i.e.,
inverse images of compact sets are compact. -/
theorem Filter.tendsto_cocompact_mul_right₀ [ContinuousMul K] {a : K} (ha : a ≠ 0) :
Filter.Tendsto (fun x : K => x * a) (Filter.cocompact K) (Filter.cocompact K) :=
Filter.tendsto_cocompact_mul_right (mul_inv_cancel₀ ha)
/-- Compact hausdorff topological fields are finite. -/
instance (priority := 100) {K} [DivisionRing K] [TopologicalSpace K]
[IsTopologicalRing K] [CompactSpace K] [T2Space K] : Finite K := by
suffices DiscreteTopology K by
exact finite_of_compact_of_discrete
rw [discreteTopology_iff_isOpen_singleton_zero]
exact GroupWithZero.isOpen_singleton_zero
variable (K)
/-- A topological division ring is a division ring with a topology where all operations are
continuous, including inversion. -/
class IsTopologicalDivisionRing : Prop extends IsTopologicalRing K, HasContinuousInv₀ K
@[deprecated (since := "2025-03-25")] alias TopologicalDivisionRing := IsTopologicalDivisionRing
section Subfield
variable {α : Type*} [Field α] [TopologicalSpace α] [IsTopologicalDivisionRing α]
/-- The (topological-space) closure of a subfield of a topological field is
itself a subfield. -/
def Subfield.topologicalClosure (K : Subfield α) : Subfield α :=
{ K.toSubring.topologicalClosure with
carrier := _root_.closure (K : Set α)
inv_mem' := fun x hx => by
rcases eq_or_ne x 0 with (rfl | h)
· rwa [inv_zero]
· rw [← inv_coe_set, ← Set.image_inv_eq_inv]
exact mem_closure_image (continuousAt_inv₀ h) hx }
theorem Subfield.le_topologicalClosure (s : Subfield α) : s ≤ s.topologicalClosure :=
_root_.subset_closure
theorem Subfield.isClosed_topologicalClosure (s : Subfield α) :
IsClosed (s.topologicalClosure : Set α) :=
isClosed_closure
theorem Subfield.topologicalClosure_minimal (s : Subfield α) {t : Subfield α} (h : s ≤ t)
(ht : IsClosed (t : Set α)) : s.topologicalClosure ≤ t :=
closure_minimal h ht
end Subfield
section affineHomeomorph
/-!
This section is about affine homeomorphisms from a topological field `𝕜` to itself.
Technically it does not require `𝕜` to be a topological field, a topological ring that
happens to be a field is enough.
-/
variable {𝕜 : Type*} [Field 𝕜] [TopologicalSpace 𝕜] [IsTopologicalRing 𝕜]
/--
The map `fun x => a * x + b`, as a homeomorphism from `𝕜` (a topological field) to itself,
when `a ≠ 0`.
-/
@[simps]
def affineHomeomorph (a b : 𝕜) (h : a ≠ 0) : 𝕜 ≃ₜ 𝕜 where
toFun x := a * x + b
invFun y := (y - b) / a
left_inv x := by
simp only [add_sub_cancel_right]
exact mul_div_cancel_left₀ x h
right_inv y := by simp [mul_div_cancel₀ _ h]
theorem affineHomeomorph_image_Icc {𝕜 : Type*}
[Field 𝕜] [LinearOrder 𝕜] [IsStrictOrderedRing 𝕜] [TopologicalSpace 𝕜]
[IsTopologicalRing 𝕜] (a b c d : 𝕜) (h : 0 < a) :
affineHomeomorph a b h.ne' '' Set.Icc c d = Set.Icc (a * c + b) (a * d + b) := by
simp [h]
theorem affineHomeomorph_image_Ico {𝕜 : Type*}
[Field 𝕜] [LinearOrder 𝕜] [IsStrictOrderedRing 𝕜] [TopologicalSpace 𝕜]
[IsTopologicalRing 𝕜] (a b c d : 𝕜) (h : 0 < a) :
| affineHomeomorph a b h.ne' '' Set.Ico c d = Set.Ico (a * c + b) (a * d + b) := by
simp [h]
| Mathlib/Topology/Algebra/Field.lean | 112 | 114 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Benjamin Davidson
-/
import Mathlib.Algebra.Field.NegOnePow
import Mathlib.Algebra.Field.Periodic
import Mathlib.Algebra.QuadraticDiscriminant
import Mathlib.Analysis.SpecialFunctions.Exp
/-!
# Trigonometric functions
## Main definitions
This file contains the definition of `π`.
See also `Analysis.SpecialFunctions.Trigonometric.Inverse` and
`Analysis.SpecialFunctions.Trigonometric.Arctan` for the inverse trigonometric functions.
See also `Analysis.SpecialFunctions.Complex.Arg` and
`Analysis.SpecialFunctions.Complex.Log` for the complex argument function
and the complex logarithm.
## Main statements
Many basic inequalities on the real trigonometric functions are established.
The continuity of the usual trigonometric functions is proved.
Several facts about the real trigonometric functions have the proofs deferred to
`Analysis.SpecialFunctions.Trigonometric.Complex`,
as they are most easily proved by appealing to the corresponding fact for
complex trigonometric functions.
See also `Analysis.SpecialFunctions.Trigonometric.Chebyshev` for the multiple angle formulas
in terms of Chebyshev polynomials.
## Tags
sin, cos, tan, angle
-/
noncomputable section
open Topology Filter Set
namespace Complex
@[continuity, fun_prop]
theorem continuous_sin : Continuous sin := by
change Continuous fun z => (exp (-z * I) - exp (z * I)) * I / 2
fun_prop
@[fun_prop]
theorem continuousOn_sin {s : Set ℂ} : ContinuousOn sin s :=
continuous_sin.continuousOn
@[continuity, fun_prop]
theorem continuous_cos : Continuous cos := by
change Continuous fun z => (exp (z * I) + exp (-z * I)) / 2
fun_prop
@[fun_prop]
theorem continuousOn_cos {s : Set ℂ} : ContinuousOn cos s :=
continuous_cos.continuousOn
@[continuity, fun_prop]
theorem continuous_sinh : Continuous sinh := by
change Continuous fun z => (exp z - exp (-z)) / 2
fun_prop
@[continuity, fun_prop]
theorem continuous_cosh : Continuous cosh := by
change Continuous fun z => (exp z + exp (-z)) / 2
fun_prop
end Complex
namespace Real
variable {x y z : ℝ}
@[continuity, fun_prop]
theorem continuous_sin : Continuous sin :=
Complex.continuous_re.comp (Complex.continuous_sin.comp Complex.continuous_ofReal)
@[fun_prop]
theorem continuousOn_sin {s} : ContinuousOn sin s :=
continuous_sin.continuousOn
@[continuity, fun_prop]
theorem continuous_cos : Continuous cos :=
Complex.continuous_re.comp (Complex.continuous_cos.comp Complex.continuous_ofReal)
@[fun_prop]
theorem continuousOn_cos {s} : ContinuousOn cos s :=
continuous_cos.continuousOn
@[continuity, fun_prop]
theorem continuous_sinh : Continuous sinh :=
Complex.continuous_re.comp (Complex.continuous_sinh.comp Complex.continuous_ofReal)
@[continuity, fun_prop]
theorem continuous_cosh : Continuous cosh :=
Complex.continuous_re.comp (Complex.continuous_cosh.comp Complex.continuous_ofReal)
end Real
namespace Real
theorem exists_cos_eq_zero : 0 ∈ cos '' Icc (1 : ℝ) 2 :=
intermediate_value_Icc' (by norm_num) continuousOn_cos
⟨le_of_lt cos_two_neg, le_of_lt cos_one_pos⟩
/-- The number π = 3.14159265... Defined here using choice as twice a zero of cos in [1,2], from
which one can derive all its properties. For explicit bounds on π, see `Data.Real.Pi.Bounds`.
Denoted `π`, once the `Real` namespace is opened. -/
protected noncomputable def pi : ℝ :=
2 * Classical.choose exists_cos_eq_zero
@[inherit_doc]
scoped notation "π" => Real.pi
@[simp]
theorem cos_pi_div_two : cos (π / 2) = 0 := by
rw [Real.pi, mul_div_cancel_left₀ _ (two_ne_zero' ℝ)]
exact (Classical.choose_spec exists_cos_eq_zero).2
theorem one_le_pi_div_two : (1 : ℝ) ≤ π / 2 := by
rw [Real.pi, mul_div_cancel_left₀ _ (two_ne_zero' ℝ)]
exact (Classical.choose_spec exists_cos_eq_zero).1.1
theorem pi_div_two_le_two : π / 2 ≤ 2 := by
rw [Real.pi, mul_div_cancel_left₀ _ (two_ne_zero' ℝ)]
exact (Classical.choose_spec exists_cos_eq_zero).1.2
theorem two_le_pi : (2 : ℝ) ≤ π :=
(div_le_div_iff_of_pos_right (show (0 : ℝ) < 2 by norm_num)).1
(by rw [div_self (two_ne_zero' ℝ)]; exact one_le_pi_div_two)
theorem pi_le_four : π ≤ 4 :=
(div_le_div_iff_of_pos_right (show (0 : ℝ) < 2 by norm_num)).1
(calc
π / 2 ≤ 2 := pi_div_two_le_two
_ = 4 / 2 := by norm_num)
@[bound]
theorem pi_pos : 0 < π :=
lt_of_lt_of_le (by norm_num) two_le_pi
@[bound]
theorem pi_nonneg : 0 ≤ π :=
pi_pos.le
theorem pi_ne_zero : π ≠ 0 :=
pi_pos.ne'
theorem pi_div_two_pos : 0 < π / 2 :=
half_pos pi_pos
theorem two_pi_pos : 0 < 2 * π := by linarith [pi_pos]
end Real
namespace Mathlib.Meta.Positivity
open Lean.Meta Qq
/-- Extension for the `positivity` tactic: `π` is always positive. -/
@[positivity Real.pi]
def evalRealPi : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(Real.pi) =>
assertInstancesCommute
pure (.positive q(Real.pi_pos))
| _, _, _ => throwError "not Real.pi"
end Mathlib.Meta.Positivity
namespace NNReal
open Real
open Real NNReal
/-- `π` considered as a nonnegative real. -/
noncomputable def pi : ℝ≥0 :=
⟨π, Real.pi_pos.le⟩
@[simp]
theorem coe_real_pi : (pi : ℝ) = π :=
rfl
theorem pi_pos : 0 < pi := mod_cast Real.pi_pos
theorem pi_ne_zero : pi ≠ 0 :=
pi_pos.ne'
end NNReal
namespace Real
@[simp]
theorem sin_pi : sin π = 0 := by
rw [← mul_div_cancel_left₀ π (two_ne_zero' ℝ), two_mul, add_div, sin_add, cos_pi_div_two]; simp
@[simp]
theorem cos_pi : cos π = -1 := by
rw [← mul_div_cancel_left₀ π (two_ne_zero' ℝ), mul_div_assoc, cos_two_mul, cos_pi_div_two]
norm_num
@[simp]
theorem sin_two_pi : sin (2 * π) = 0 := by simp [two_mul, sin_add]
@[simp]
theorem cos_two_pi : cos (2 * π) = 1 := by simp [two_mul, cos_add]
theorem sin_antiperiodic : Function.Antiperiodic sin π := by simp [sin_add]
theorem sin_periodic : Function.Periodic sin (2 * π) :=
sin_antiperiodic.periodic_two_mul
@[simp]
theorem sin_add_pi (x : ℝ) : sin (x + π) = -sin x :=
sin_antiperiodic x
@[simp]
theorem sin_add_two_pi (x : ℝ) : sin (x + 2 * π) = sin x :=
sin_periodic x
@[simp]
theorem sin_sub_pi (x : ℝ) : sin (x - π) = -sin x :=
sin_antiperiodic.sub_eq x
@[simp]
theorem sin_sub_two_pi (x : ℝ) : sin (x - 2 * π) = sin x :=
sin_periodic.sub_eq x
@[simp]
theorem sin_pi_sub (x : ℝ) : sin (π - x) = sin x :=
neg_neg (sin x) ▸ sin_neg x ▸ sin_antiperiodic.sub_eq'
@[simp]
theorem sin_two_pi_sub (x : ℝ) : sin (2 * π - x) = -sin x :=
sin_neg x ▸ sin_periodic.sub_eq'
@[simp]
theorem sin_nat_mul_pi (n : ℕ) : sin (n * π) = 0 :=
sin_antiperiodic.nat_mul_eq_of_eq_zero sin_zero n
@[simp]
theorem sin_int_mul_pi (n : ℤ) : sin (n * π) = 0 :=
sin_antiperiodic.int_mul_eq_of_eq_zero sin_zero n
@[simp]
theorem sin_add_nat_mul_two_pi (x : ℝ) (n : ℕ) : sin (x + n * (2 * π)) = sin x :=
sin_periodic.nat_mul n x
@[simp]
theorem sin_add_int_mul_two_pi (x : ℝ) (n : ℤ) : sin (x + n * (2 * π)) = sin x :=
sin_periodic.int_mul n x
@[simp]
theorem sin_sub_nat_mul_two_pi (x : ℝ) (n : ℕ) : sin (x - n * (2 * π)) = sin x :=
sin_periodic.sub_nat_mul_eq n
@[simp]
theorem sin_sub_int_mul_two_pi (x : ℝ) (n : ℤ) : sin (x - n * (2 * π)) = sin x :=
sin_periodic.sub_int_mul_eq n
@[simp]
theorem sin_nat_mul_two_pi_sub (x : ℝ) (n : ℕ) : sin (n * (2 * π) - x) = -sin x :=
sin_neg x ▸ sin_periodic.nat_mul_sub_eq n
@[simp]
theorem sin_int_mul_two_pi_sub (x : ℝ) (n : ℤ) : sin (n * (2 * π) - x) = -sin x :=
sin_neg x ▸ sin_periodic.int_mul_sub_eq n
theorem sin_add_int_mul_pi (x : ℝ) (n : ℤ) : sin (x + n * π) = (-1) ^ n * sin x :=
n.cast_negOnePow ℝ ▸ sin_antiperiodic.add_int_mul_eq n
theorem sin_add_nat_mul_pi (x : ℝ) (n : ℕ) : sin (x + n * π) = (-1) ^ n * sin x :=
sin_antiperiodic.add_nat_mul_eq n
theorem sin_sub_int_mul_pi (x : ℝ) (n : ℤ) : sin (x - n * π) = (-1) ^ n * sin x :=
n.cast_negOnePow ℝ ▸ sin_antiperiodic.sub_int_mul_eq n
theorem sin_sub_nat_mul_pi (x : ℝ) (n : ℕ) : sin (x - n * π) = (-1) ^ n * sin x :=
sin_antiperiodic.sub_nat_mul_eq n
theorem sin_int_mul_pi_sub (x : ℝ) (n : ℤ) : sin (n * π - x) = -((-1) ^ n * sin x) := by
simpa only [sin_neg, mul_neg, Int.cast_negOnePow] using sin_antiperiodic.int_mul_sub_eq n
theorem sin_nat_mul_pi_sub (x : ℝ) (n : ℕ) : sin (n * π - x) = -((-1) ^ n * sin x) := by
simpa only [sin_neg, mul_neg] using sin_antiperiodic.nat_mul_sub_eq n
theorem cos_antiperiodic : Function.Antiperiodic cos π := by simp [cos_add]
theorem cos_periodic : Function.Periodic cos (2 * π) :=
cos_antiperiodic.periodic_two_mul
@[simp]
theorem abs_cos_int_mul_pi (k : ℤ) : |cos (k * π)| = 1 := by
simp [abs_cos_eq_sqrt_one_sub_sin_sq]
@[simp]
theorem cos_add_pi (x : ℝ) : cos (x + π) = -cos x :=
cos_antiperiodic x
@[simp]
theorem cos_add_two_pi (x : ℝ) : cos (x + 2 * π) = cos x :=
cos_periodic x
@[simp]
theorem cos_sub_pi (x : ℝ) : cos (x - π) = -cos x :=
cos_antiperiodic.sub_eq x
@[simp]
theorem cos_sub_two_pi (x : ℝ) : cos (x - 2 * π) = cos x :=
cos_periodic.sub_eq x
@[simp]
theorem cos_pi_sub (x : ℝ) : cos (π - x) = -cos x :=
cos_neg x ▸ cos_antiperiodic.sub_eq'
@[simp]
theorem cos_two_pi_sub (x : ℝ) : cos (2 * π - x) = cos x :=
cos_neg x ▸ cos_periodic.sub_eq'
@[simp]
theorem cos_nat_mul_two_pi (n : ℕ) : cos (n * (2 * π)) = 1 :=
(cos_periodic.nat_mul_eq n).trans cos_zero
@[simp]
theorem cos_int_mul_two_pi (n : ℤ) : cos (n * (2 * π)) = 1 :=
(cos_periodic.int_mul_eq n).trans cos_zero
@[simp]
theorem cos_add_nat_mul_two_pi (x : ℝ) (n : ℕ) : cos (x + n * (2 * π)) = cos x :=
cos_periodic.nat_mul n x
@[simp]
theorem cos_add_int_mul_two_pi (x : ℝ) (n : ℤ) : cos (x + n * (2 * π)) = cos x :=
cos_periodic.int_mul n x
@[simp]
theorem cos_sub_nat_mul_two_pi (x : ℝ) (n : ℕ) : cos (x - n * (2 * π)) = cos x :=
cos_periodic.sub_nat_mul_eq n
@[simp]
theorem cos_sub_int_mul_two_pi (x : ℝ) (n : ℤ) : cos (x - n * (2 * π)) = cos x :=
cos_periodic.sub_int_mul_eq n
@[simp]
theorem cos_nat_mul_two_pi_sub (x : ℝ) (n : ℕ) : cos (n * (2 * π) - x) = cos x :=
cos_neg x ▸ cos_periodic.nat_mul_sub_eq n
@[simp]
theorem cos_int_mul_two_pi_sub (x : ℝ) (n : ℤ) : cos (n * (2 * π) - x) = cos x :=
cos_neg x ▸ cos_periodic.int_mul_sub_eq n
theorem cos_add_int_mul_pi (x : ℝ) (n : ℤ) : cos (x + n * π) = (-1) ^ n * cos x :=
n.cast_negOnePow ℝ ▸ cos_antiperiodic.add_int_mul_eq n
theorem cos_add_nat_mul_pi (x : ℝ) (n : ℕ) : cos (x + n * π) = (-1) ^ n * cos x :=
cos_antiperiodic.add_nat_mul_eq n
theorem cos_sub_int_mul_pi (x : ℝ) (n : ℤ) : cos (x - n * π) = (-1) ^ n * cos x :=
n.cast_negOnePow ℝ ▸ cos_antiperiodic.sub_int_mul_eq n
theorem cos_sub_nat_mul_pi (x : ℝ) (n : ℕ) : cos (x - n * π) = (-1) ^ n * cos x :=
cos_antiperiodic.sub_nat_mul_eq n
theorem cos_int_mul_pi_sub (x : ℝ) (n : ℤ) : cos (n * π - x) = (-1) ^ n * cos x :=
n.cast_negOnePow ℝ ▸ cos_neg x ▸ cos_antiperiodic.int_mul_sub_eq n
theorem cos_nat_mul_pi_sub (x : ℝ) (n : ℕ) : cos (n * π - x) = (-1) ^ n * cos x :=
cos_neg x ▸ cos_antiperiodic.nat_mul_sub_eq n
theorem cos_nat_mul_two_pi_add_pi (n : ℕ) : cos (n * (2 * π) + π) = -1 := by
simpa only [cos_zero] using (cos_periodic.nat_mul n).add_antiperiod_eq cos_antiperiodic
theorem cos_int_mul_two_pi_add_pi (n : ℤ) : cos (n * (2 * π) + π) = -1 := by
simpa only [cos_zero] using (cos_periodic.int_mul n).add_antiperiod_eq cos_antiperiodic
theorem cos_nat_mul_two_pi_sub_pi (n : ℕ) : cos (n * (2 * π) - π) = -1 := by
simpa only [cos_zero] using (cos_periodic.nat_mul n).sub_antiperiod_eq cos_antiperiodic
theorem cos_int_mul_two_pi_sub_pi (n : ℤ) : cos (n * (2 * π) - π) = -1 := by
simpa only [cos_zero] using (cos_periodic.int_mul n).sub_antiperiod_eq cos_antiperiodic
theorem sin_pos_of_pos_of_lt_pi {x : ℝ} (h0x : 0 < x) (hxp : x < π) : 0 < sin x :=
if hx2 : x ≤ 2 then sin_pos_of_pos_of_le_two h0x hx2
else
have : (2 : ℝ) + 2 = 4 := by norm_num
have : π - x ≤ 2 :=
sub_le_iff_le_add.2 (le_trans pi_le_four (this ▸ add_le_add_left (le_of_not_ge hx2) _))
sin_pi_sub x ▸ sin_pos_of_pos_of_le_two (sub_pos.2 hxp) this
theorem sin_pos_of_mem_Ioo {x : ℝ} (hx : x ∈ Ioo 0 π) : 0 < sin x :=
sin_pos_of_pos_of_lt_pi hx.1 hx.2
theorem sin_nonneg_of_mem_Icc {x : ℝ} (hx : x ∈ Icc 0 π) : 0 ≤ sin x := by
rw [← closure_Ioo pi_ne_zero.symm] at hx
exact
closure_lt_subset_le continuous_const continuous_sin
(closure_mono (fun y => sin_pos_of_mem_Ioo) hx)
theorem sin_nonneg_of_nonneg_of_le_pi {x : ℝ} (h0x : 0 ≤ x) (hxp : x ≤ π) : 0 ≤ sin x :=
sin_nonneg_of_mem_Icc ⟨h0x, hxp⟩
theorem sin_neg_of_neg_of_neg_pi_lt {x : ℝ} (hx0 : x < 0) (hpx : -π < x) : sin x < 0 :=
neg_pos.1 <| sin_neg x ▸ sin_pos_of_pos_of_lt_pi (neg_pos.2 hx0) (neg_lt.1 hpx)
theorem sin_nonpos_of_nonnpos_of_neg_pi_le {x : ℝ} (hx0 : x ≤ 0) (hpx : -π ≤ x) : sin x ≤ 0 :=
neg_nonneg.1 <| sin_neg x ▸ sin_nonneg_of_nonneg_of_le_pi (neg_nonneg.2 hx0) (neg_le.1 hpx)
@[simp]
theorem sin_pi_div_two : sin (π / 2) = 1 :=
have : sin (π / 2) = 1 ∨ sin (π / 2) = -1 := by
simpa [sq, mul_self_eq_one_iff] using sin_sq_add_cos_sq (π / 2)
this.resolve_right fun h =>
show ¬(0 : ℝ) < -1 by norm_num <|
h ▸ sin_pos_of_pos_of_lt_pi pi_div_two_pos (half_lt_self pi_pos)
theorem sin_add_pi_div_two (x : ℝ) : sin (x + π / 2) = cos x := by simp [sin_add]
theorem sin_sub_pi_div_two (x : ℝ) : sin (x - π / 2) = -cos x := by simp [sub_eq_add_neg, sin_add]
theorem sin_pi_div_two_sub (x : ℝ) : sin (π / 2 - x) = cos x := by simp [sub_eq_add_neg, sin_add]
theorem cos_add_pi_div_two (x : ℝ) : cos (x + π / 2) = -sin x := by simp [cos_add]
theorem cos_sub_pi_div_two (x : ℝ) : cos (x - π / 2) = sin x := by simp [sub_eq_add_neg, cos_add]
theorem cos_pi_div_two_sub (x : ℝ) : cos (π / 2 - x) = sin x := by
rw [← cos_neg, neg_sub, cos_sub_pi_div_two]
theorem cos_pos_of_mem_Ioo {x : ℝ} (hx : x ∈ Ioo (-(π / 2)) (π / 2)) : 0 < cos x :=
sin_add_pi_div_two x ▸ sin_pos_of_mem_Ioo ⟨by linarith [hx.1], by linarith [hx.2]⟩
theorem cos_nonneg_of_mem_Icc {x : ℝ} (hx : x ∈ Icc (-(π / 2)) (π / 2)) : 0 ≤ cos x :=
sin_add_pi_div_two x ▸ sin_nonneg_of_mem_Icc ⟨by linarith [hx.1], by linarith [hx.2]⟩
theorem cos_nonneg_of_neg_pi_div_two_le_of_le {x : ℝ} (hl : -(π / 2) ≤ x) (hu : x ≤ π / 2) :
0 ≤ cos x :=
cos_nonneg_of_mem_Icc ⟨hl, hu⟩
theorem cos_neg_of_pi_div_two_lt_of_lt {x : ℝ} (hx₁ : π / 2 < x) (hx₂ : x < π + π / 2) :
cos x < 0 :=
neg_pos.1 <| cos_pi_sub x ▸ cos_pos_of_mem_Ioo ⟨by linarith, by linarith⟩
theorem cos_nonpos_of_pi_div_two_le_of_le {x : ℝ} (hx₁ : π / 2 ≤ x) (hx₂ : x ≤ π + π / 2) :
cos x ≤ 0 :=
neg_nonneg.1 <| cos_pi_sub x ▸ cos_nonneg_of_mem_Icc ⟨by linarith, by linarith⟩
theorem sin_eq_sqrt_one_sub_cos_sq {x : ℝ} (hl : 0 ≤ x) (hu : x ≤ π) :
sin x = √(1 - cos x ^ 2) := by
rw [← abs_sin_eq_sqrt_one_sub_cos_sq, abs_of_nonneg (sin_nonneg_of_nonneg_of_le_pi hl hu)]
theorem cos_eq_sqrt_one_sub_sin_sq {x : ℝ} (hl : -(π / 2) ≤ x) (hu : x ≤ π / 2) :
cos x = √(1 - sin x ^ 2) := by
rw [← abs_cos_eq_sqrt_one_sub_sin_sq, abs_of_nonneg (cos_nonneg_of_mem_Icc ⟨hl, hu⟩)]
lemma cos_half {x : ℝ} (hl : -π ≤ x) (hr : x ≤ π) : cos (x / 2) = sqrt ((1 + cos x) / 2) := by
have : 0 ≤ cos (x / 2) := cos_nonneg_of_mem_Icc <| by constructor <;> linarith
rw [← sqrt_sq this, cos_sq, add_div, two_mul, add_halves]
lemma abs_sin_half (x : ℝ) : |sin (x / 2)| = sqrt ((1 - cos x) / 2) := by
rw [← sqrt_sq_eq_abs, sin_sq_eq_half_sub, two_mul, add_halves, sub_div]
lemma sin_half_eq_sqrt {x : ℝ} (hl : 0 ≤ x) (hr : x ≤ 2 * π) :
sin (x / 2) = sqrt ((1 - cos x) / 2) := by
rw [← abs_sin_half, abs_of_nonneg]
apply sin_nonneg_of_nonneg_of_le_pi <;> linarith
lemma sin_half_eq_neg_sqrt {x : ℝ} (hl : -(2 * π) ≤ x) (hr : x ≤ 0) :
sin (x / 2) = -sqrt ((1 - cos x) / 2) := by
rw [← abs_sin_half, abs_of_nonpos, neg_neg]
apply sin_nonpos_of_nonnpos_of_neg_pi_le <;> linarith
theorem sin_eq_zero_iff_of_lt_of_lt {x : ℝ} (hx₁ : -π < x) (hx₂ : x < π) : sin x = 0 ↔ x = 0 :=
⟨fun h => by
contrapose! h
cases h.lt_or_lt with
| inl h0 => exact (sin_neg_of_neg_of_neg_pi_lt h0 hx₁).ne
| inr h0 => exact (sin_pos_of_pos_of_lt_pi h0 hx₂).ne',
fun h => by simp [h]⟩
theorem sin_eq_zero_iff {x : ℝ} : sin x = 0 ↔ ∃ n : ℤ, (n : ℝ) * π = x :=
⟨fun h =>
⟨⌊x / π⌋,
le_antisymm (sub_nonneg.1 (Int.sub_floor_div_mul_nonneg _ pi_pos))
(sub_nonpos.1 <|
le_of_not_gt fun h₃ =>
(sin_pos_of_pos_of_lt_pi h₃ (Int.sub_floor_div_mul_lt _ pi_pos)).ne
(by simp [sub_eq_add_neg, sin_add, h, sin_int_mul_pi]))⟩,
fun ⟨_, hn⟩ => hn ▸ sin_int_mul_pi _⟩
theorem sin_ne_zero_iff {x : ℝ} : sin x ≠ 0 ↔ ∀ n : ℤ, (n : ℝ) * π ≠ x := by
rw [← not_exists, not_iff_not, sin_eq_zero_iff]
theorem sin_eq_zero_iff_cos_eq {x : ℝ} : sin x = 0 ↔ cos x = 1 ∨ cos x = -1 := by
rw [← mul_self_eq_one_iff, ← sin_sq_add_cos_sq x, sq, sq, ← sub_eq_iff_eq_add, sub_self]
exact ⟨fun h => by rw [h, mul_zero], eq_zero_of_mul_self_eq_zero ∘ Eq.symm⟩
theorem cos_eq_one_iff (x : ℝ) : cos x = 1 ↔ ∃ n : ℤ, (n : ℝ) * (2 * π) = x :=
⟨fun h =>
let ⟨n, hn⟩ := sin_eq_zero_iff.1 (sin_eq_zero_iff_cos_eq.2 (Or.inl h))
⟨n / 2,
(Int.emod_two_eq_zero_or_one n).elim
(fun hn0 => by
rwa [← mul_assoc, ← @Int.cast_two ℝ, ← Int.cast_mul,
Int.ediv_mul_cancel (Int.dvd_iff_emod_eq_zero.2 hn0)])
fun hn1 => by
rw [← Int.emod_add_ediv n 2, hn1, Int.cast_add, Int.cast_one, add_mul, one_mul, add_comm,
mul_comm (2 : ℤ), Int.cast_mul, mul_assoc, Int.cast_two] at hn
rw [← hn, cos_int_mul_two_pi_add_pi] at h
exact absurd h (by norm_num)⟩,
fun ⟨_, hn⟩ => hn ▸ cos_int_mul_two_pi _⟩
theorem cos_eq_one_iff_of_lt_of_lt {x : ℝ} (hx₁ : -(2 * π) < x) (hx₂ : x < 2 * π) :
cos x = 1 ↔ x = 0 :=
⟨fun h => by
rcases (cos_eq_one_iff _).1 h with ⟨n, rfl⟩
rw [mul_lt_iff_lt_one_left two_pi_pos] at hx₂
rw [neg_lt, neg_mul_eq_neg_mul, mul_lt_iff_lt_one_left two_pi_pos] at hx₁
norm_cast at hx₁ hx₂
obtain rfl : n = 0 := le_antisymm (by omega) (by omega)
simp, fun h => by simp [h]⟩
theorem sin_lt_sin_of_lt_of_le_pi_div_two {x y : ℝ} (hx₁ : -(π / 2) ≤ x) (hy₂ : y ≤ π / 2)
(hxy : x < y) : sin x < sin y := by
rw [← sub_pos, sin_sub_sin]
have : 0 < sin ((y - x) / 2) := by apply sin_pos_of_pos_of_lt_pi <;> linarith
have : 0 < cos ((y + x) / 2) := by refine cos_pos_of_mem_Ioo ⟨?_, ?_⟩ <;> linarith
positivity
theorem strictMonoOn_sin : StrictMonoOn sin (Icc (-(π / 2)) (π / 2)) := fun _ hx _ hy hxy =>
sin_lt_sin_of_lt_of_le_pi_div_two hx.1 hy.2 hxy
theorem cos_lt_cos_of_nonneg_of_le_pi {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y ≤ π) (hxy : x < y) :
cos y < cos x := by
rw [← sin_pi_div_two_sub, ← sin_pi_div_two_sub]
apply sin_lt_sin_of_lt_of_le_pi_div_two <;> linarith
theorem cos_lt_cos_of_nonneg_of_le_pi_div_two {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y ≤ π / 2)
(hxy : x < y) : cos y < cos x :=
cos_lt_cos_of_nonneg_of_le_pi hx₁ (hy₂.trans (by linarith)) hxy
theorem strictAntiOn_cos : StrictAntiOn cos (Icc 0 π) := fun _ hx _ hy hxy =>
cos_lt_cos_of_nonneg_of_le_pi hx.1 hy.2 hxy
theorem cos_le_cos_of_nonneg_of_le_pi {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y ≤ π) (hxy : x ≤ y) :
cos y ≤ cos x :=
(strictAntiOn_cos.le_iff_le ⟨hx₁.trans hxy, hy₂⟩ ⟨hx₁, hxy.trans hy₂⟩).2 hxy
theorem sin_le_sin_of_le_of_le_pi_div_two {x y : ℝ} (hx₁ : -(π / 2) ≤ x) (hy₂ : y ≤ π / 2)
(hxy : x ≤ y) : sin x ≤ sin y :=
(strictMonoOn_sin.le_iff_le ⟨hx₁, hxy.trans hy₂⟩ ⟨hx₁.trans hxy, hy₂⟩).2 hxy
theorem injOn_sin : InjOn sin (Icc (-(π / 2)) (π / 2)) :=
strictMonoOn_sin.injOn
theorem injOn_cos : InjOn cos (Icc 0 π) :=
strictAntiOn_cos.injOn
theorem surjOn_sin : SurjOn sin (Icc (-(π / 2)) (π / 2)) (Icc (-1) 1) := by
simpa only [sin_neg, sin_pi_div_two] using
intermediate_value_Icc (neg_le_self pi_div_two_pos.le) continuous_sin.continuousOn
theorem surjOn_cos : SurjOn cos (Icc 0 π) (Icc (-1) 1) := by
simpa only [cos_zero, cos_pi] using intermediate_value_Icc' pi_pos.le continuous_cos.continuousOn
theorem sin_mem_Icc (x : ℝ) : sin x ∈ Icc (-1 : ℝ) 1 :=
⟨neg_one_le_sin x, sin_le_one x⟩
theorem cos_mem_Icc (x : ℝ) : cos x ∈ Icc (-1 : ℝ) 1 :=
⟨neg_one_le_cos x, cos_le_one x⟩
theorem mapsTo_sin (s : Set ℝ) : MapsTo sin s (Icc (-1 : ℝ) 1) := fun x _ => sin_mem_Icc x
theorem mapsTo_cos (s : Set ℝ) : MapsTo cos s (Icc (-1 : ℝ) 1) := fun x _ => cos_mem_Icc x
theorem bijOn_sin : BijOn sin (Icc (-(π / 2)) (π / 2)) (Icc (-1) 1) :=
⟨mapsTo_sin _, injOn_sin, surjOn_sin⟩
theorem bijOn_cos : BijOn cos (Icc 0 π) (Icc (-1) 1) :=
⟨mapsTo_cos _, injOn_cos, surjOn_cos⟩
@[simp]
theorem range_cos : range cos = (Icc (-1) 1 : Set ℝ) :=
Subset.antisymm (range_subset_iff.2 cos_mem_Icc) surjOn_cos.subset_range
@[simp]
theorem range_sin : range sin = (Icc (-1) 1 : Set ℝ) :=
Subset.antisymm (range_subset_iff.2 sin_mem_Icc) surjOn_sin.subset_range
theorem range_cos_infinite : (range Real.cos).Infinite := by
rw [Real.range_cos]
exact Icc_infinite (by norm_num)
theorem range_sin_infinite : (range Real.sin).Infinite := by
rw [Real.range_sin]
exact Icc_infinite (by norm_num)
section CosDivSq
variable (x : ℝ)
/-- the series `sqrtTwoAddSeries x n` is `sqrt(2 + sqrt(2 + ... ))` with `n` square roots,
starting with `x`. We define it here because `cos (pi / 2 ^ (n+1)) = sqrtTwoAddSeries 0 n / 2`
-/
@[simp]
noncomputable def sqrtTwoAddSeries (x : ℝ) : ℕ → ℝ
| 0 => x
| n + 1 => √(2 + sqrtTwoAddSeries x n)
theorem sqrtTwoAddSeries_zero : sqrtTwoAddSeries x 0 = x := by simp
theorem sqrtTwoAddSeries_one : sqrtTwoAddSeries 0 1 = √2 := by simp
theorem sqrtTwoAddSeries_two : sqrtTwoAddSeries 0 2 = √(2 + √2) := by simp
theorem sqrtTwoAddSeries_zero_nonneg : ∀ n : ℕ, 0 ≤ sqrtTwoAddSeries 0 n
| 0 => le_refl 0
| _ + 1 => sqrt_nonneg _
theorem sqrtTwoAddSeries_nonneg {x : ℝ} (h : 0 ≤ x) : ∀ n : ℕ, 0 ≤ sqrtTwoAddSeries x n
| 0 => h
| _ + 1 => sqrt_nonneg _
theorem sqrtTwoAddSeries_lt_two : ∀ n : ℕ, sqrtTwoAddSeries 0 n < 2
| 0 => by norm_num
| n + 1 => by
refine lt_of_lt_of_le ?_ (sqrt_sq zero_lt_two.le).le
rw [sqrtTwoAddSeries, sqrt_lt_sqrt_iff, ← lt_sub_iff_add_lt']
· refine (sqrtTwoAddSeries_lt_two n).trans_le ?_
norm_num
· exact add_nonneg zero_le_two (sqrtTwoAddSeries_zero_nonneg n)
theorem sqrtTwoAddSeries_succ (x : ℝ) :
∀ n : ℕ, sqrtTwoAddSeries x (n + 1) = sqrtTwoAddSeries (√(2 + x)) n
| 0 => rfl
| n + 1 => by rw [sqrtTwoAddSeries, sqrtTwoAddSeries_succ _ _, sqrtTwoAddSeries]
theorem sqrtTwoAddSeries_monotone_left {x y : ℝ} (h : x ≤ y) :
∀ n : ℕ, sqrtTwoAddSeries x n ≤ sqrtTwoAddSeries y n
| 0 => h
| n + 1 => by
rw [sqrtTwoAddSeries, sqrtTwoAddSeries]
exact sqrt_le_sqrt (add_le_add_left (sqrtTwoAddSeries_monotone_left h _) _)
@[simp]
theorem cos_pi_over_two_pow : ∀ n : ℕ, cos (π / 2 ^ (n + 1)) = sqrtTwoAddSeries 0 n / 2
| 0 => by simp
| n + 1 => by
have A : (1 : ℝ) < 2 ^ (n + 1) := one_lt_pow₀ one_lt_two n.succ_ne_zero
have B : π / 2 ^ (n + 1) < π := div_lt_self pi_pos A
have C : 0 < π / 2 ^ (n + 1) := by positivity
rw [pow_succ, div_mul_eq_div_div, cos_half, cos_pi_over_two_pow n, sqrtTwoAddSeries,
add_div_eq_mul_add_div, one_mul, ← div_mul_eq_div_div, sqrt_div, sqrt_mul_self] <;>
linarith [sqrtTwoAddSeries_nonneg le_rfl n]
theorem sin_sq_pi_over_two_pow (n : ℕ) :
sin (π / 2 ^ (n + 1)) ^ 2 = 1 - (sqrtTwoAddSeries 0 n / 2) ^ 2 := by
rw [sin_sq, cos_pi_over_two_pow]
theorem sin_sq_pi_over_two_pow_succ (n : ℕ) :
sin (π / 2 ^ (n + 2)) ^ 2 = 1 / 2 - sqrtTwoAddSeries 0 n / 4 := by
rw [sin_sq_pi_over_two_pow, sqrtTwoAddSeries, div_pow, sq_sqrt, add_div, ← sub_sub]
· congr
· norm_num
· norm_num
· exact add_nonneg two_pos.le (sqrtTwoAddSeries_zero_nonneg _)
@[simp]
theorem sin_pi_over_two_pow_succ (n : ℕ) :
sin (π / 2 ^ (n + 2)) = √(2 - sqrtTwoAddSeries 0 n) / 2 := by
rw [eq_div_iff_mul_eq two_ne_zero, eq_comm, sqrt_eq_iff_eq_sq, mul_pow,
sin_sq_pi_over_two_pow_succ, sub_mul]
· congr <;> norm_num
· rw [sub_nonneg]
exact (sqrtTwoAddSeries_lt_two _).le
refine mul_nonneg (sin_nonneg_of_nonneg_of_le_pi ?_ ?_) zero_le_two
· positivity
· exact div_le_self pi_pos.le <| one_le_pow₀ one_le_two
@[simp]
theorem cos_pi_div_four : cos (π / 4) = √2 / 2 := by
trans cos (π / 2 ^ 2)
· congr
norm_num
· simp
@[simp]
theorem sin_pi_div_four : sin (π / 4) = √2 / 2 := by
trans sin (π / 2 ^ 2)
· congr
norm_num
· simp
@[simp]
theorem cos_pi_div_eight : cos (π / 8) = √(2 + √2) / 2 := by
trans cos (π / 2 ^ 3)
· congr
norm_num
· simp
@[simp]
theorem sin_pi_div_eight : sin (π / 8) = √(2 - √2) / 2 := by
trans sin (π / 2 ^ 3)
· congr
norm_num
· simp
@[simp]
theorem cos_pi_div_sixteen : cos (π / 16) = √(2 + √(2 + √2)) / 2 := by
trans cos (π / 2 ^ 4)
· congr
norm_num
· simp
@[simp]
theorem sin_pi_div_sixteen : sin (π / 16) = √(2 - √(2 + √2)) / 2 := by
trans sin (π / 2 ^ 4)
· congr
norm_num
· simp
@[simp]
theorem cos_pi_div_thirty_two : cos (π / 32) = √(2 + √(2 + √(2 + √2))) / 2 := by
trans cos (π / 2 ^ 5)
· congr
norm_num
· simp
@[simp]
theorem sin_pi_div_thirty_two : sin (π / 32) = √(2 - √(2 + √(2 + √2))) / 2 := by
trans sin (π / 2 ^ 5)
· congr
norm_num
· simp
-- This section is also a convenient location for other explicit values of `sin` and `cos`.
/-- The cosine of `π / 3` is `1 / 2`. -/
@[simp]
theorem cos_pi_div_three : cos (π / 3) = 1 / 2 := by
have h₁ : (2 * cos (π / 3) - 1) ^ 2 * (2 * cos (π / 3) + 2) = 0 := by
have : cos (3 * (π / 3)) = cos π := by
congr 1
ring
linarith [cos_pi, cos_three_mul (π / 3)]
rcases mul_eq_zero.mp h₁ with h | h
· linarith [pow_eq_zero h]
· have : cos π < cos (π / 3) := by
refine cos_lt_cos_of_nonneg_of_le_pi ?_ le_rfl ?_ <;> linarith [pi_pos]
linarith [cos_pi]
/-- The cosine of `π / 6` is `√3 / 2`. -/
@[simp]
theorem cos_pi_div_six : cos (π / 6) = √3 / 2 := by
rw [show (6 : ℝ) = 3 * 2 by norm_num, div_mul_eq_div_div, cos_half, cos_pi_div_three, one_add_div,
← div_mul_eq_div_div, two_add_one_eq_three, sqrt_div, sqrt_mul_self] <;> linarith [pi_pos]
/-- The square of the cosine of `π / 6` is `3 / 4` (this is sometimes more convenient than the
result for cosine itself). -/
theorem sq_cos_pi_div_six : cos (π / 6) ^ 2 = 3 / 4 := by
rw [cos_pi_div_six, div_pow, sq_sqrt] <;> norm_num
/-- The sine of `π / 6` is `1 / 2`. -/
@[simp]
theorem sin_pi_div_six : sin (π / 6) = 1 / 2 := by
rw [← cos_pi_div_two_sub, ← cos_pi_div_three]
congr
ring
/-- The square of the sine of `π / 3` is `3 / 4` (this is sometimes more convenient than the
result for cosine itself). -/
theorem sq_sin_pi_div_three : sin (π / 3) ^ 2 = 3 / 4 := by
rw [← cos_pi_div_two_sub, ← sq_cos_pi_div_six]
congr
ring
/-- The sine of `π / 3` is `√3 / 2`. -/
@[simp]
theorem sin_pi_div_three : sin (π / 3) = √3 / 2 := by
rw [← cos_pi_div_two_sub, ← cos_pi_div_six]
congr
ring
theorem quadratic_root_cos_pi_div_five :
letI c := cos (π / 5)
4 * c ^ 2 - 2 * c - 1 = 0 := by
set θ := π / 5 with hθ
set c := cos θ
set s := sin θ
suffices 2 * c = 4 * c ^ 2 - 1 by simp [this]
have hs : s ≠ 0 := by
rw [ne_eq, sin_eq_zero_iff, hθ]
push_neg
intro n hn
replace hn : n * 5 = 1 := by field_simp [mul_comm _ π, mul_assoc] at hn; norm_cast at hn
omega
suffices s * (2 * c) = s * (4 * c ^ 2 - 1) from mul_left_cancel₀ hs this
calc s * (2 * c) = 2 * s * c := by rw [← mul_assoc, mul_comm 2]
_ = sin (2 * θ) := by rw [sin_two_mul]
_ = sin (π - 2 * θ) := by rw [sin_pi_sub]
_ = sin (2 * θ + θ) := by congr; field_simp [hθ]; linarith
_ = sin (2 * θ) * c + cos (2 * θ) * s := sin_add (2 * θ) θ
_ = 2 * s * c * c + cos (2 * θ) * s := by rw [sin_two_mul]
_ = 2 * s * c * c + (2 * c ^ 2 - 1) * s := by rw [cos_two_mul]
_ = s * (2 * c * c) + s * (2 * c ^ 2 - 1) := by linarith
_ = s * (4 * c ^ 2 - 1) := by linarith
open Polynomial in
theorem Polynomial.isRoot_cos_pi_div_five :
(4 • X ^ 2 - 2 • X - C 1 : ℝ[X]).IsRoot (cos (π / 5)) := by
simpa using quadratic_root_cos_pi_div_five
/-- The cosine of `π / 5` is `(1 + √5) / 4`. -/
@[simp]
theorem cos_pi_div_five : cos (π / 5) = (1 + √5) / 4 := by
set c := cos (π / 5)
have : 4 * (c * c) + (-2) * c + (-1) = 0 := by
rw [← sq, neg_mul, ← sub_eq_add_neg, ← sub_eq_add_neg]
exact quadratic_root_cos_pi_div_five
have hd : discrim 4 (-2) (-1) = (2 * √5) * (2 * √5) := by norm_num [discrim, mul_mul_mul_comm]
rcases (quadratic_eq_zero_iff (by norm_num) hd c).mp this with h | h
· field_simp [h]; linarith
· absurd (show 0 ≤ c from cos_nonneg_of_mem_Icc <| by constructor <;> linarith [pi_pos.le])
rw [not_le, h]
exact div_neg_of_neg_of_pos (by norm_num [lt_sqrt]) (by positivity)
end CosDivSq
/-- `Real.sin` as an `OrderIso` between `[-(π / 2), π / 2]` and `[-1, 1]`. -/
def sinOrderIso : Icc (-(π / 2)) (π / 2) ≃o Icc (-1 : ℝ) 1 :=
(strictMonoOn_sin.orderIso _ _).trans <| OrderIso.setCongr _ _ bijOn_sin.image_eq
@[simp]
theorem coe_sinOrderIso_apply (x : Icc (-(π / 2)) (π / 2)) : (sinOrderIso x : ℝ) = sin x :=
rfl
theorem sinOrderIso_apply (x : Icc (-(π / 2)) (π / 2)) : sinOrderIso x = ⟨sin x, sin_mem_Icc x⟩ :=
rfl
@[simp]
theorem tan_pi_div_four : tan (π / 4) = 1 := by
rw [tan_eq_sin_div_cos, cos_pi_div_four, sin_pi_div_four]
have h : √2 / 2 > 0 := by positivity
exact div_self (ne_of_gt h)
@[simp]
theorem tan_pi_div_two : tan (π / 2) = 0 := by simp [tan_eq_sin_div_cos]
@[simp]
theorem tan_pi_div_six : tan (π / 6) = 1 / sqrt 3 := by
rw [tan_eq_sin_div_cos, sin_pi_div_six, cos_pi_div_six]
ring
@[simp]
theorem tan_pi_div_three : tan (π / 3) = sqrt 3 := by
rw [tan_eq_sin_div_cos, sin_pi_div_three, cos_pi_div_three]
ring
theorem tan_pos_of_pos_of_lt_pi_div_two {x : ℝ} (h0x : 0 < x) (hxp : x < π / 2) : 0 < tan x := by
rw [tan_eq_sin_div_cos]
exact div_pos (sin_pos_of_pos_of_lt_pi h0x (by linarith)) (cos_pos_of_mem_Ioo ⟨by linarith, hxp⟩)
theorem tan_nonneg_of_nonneg_of_le_pi_div_two {x : ℝ} (h0x : 0 ≤ x) (hxp : x ≤ π / 2) : 0 ≤ tan x :=
match lt_or_eq_of_le h0x, lt_or_eq_of_le hxp with
| Or.inl hx0, Or.inl hxp => le_of_lt (tan_pos_of_pos_of_lt_pi_div_two hx0 hxp)
| Or.inl _, Or.inr hxp => by simp [hxp, tan_eq_sin_div_cos]
| Or.inr hx0, _ => by simp [hx0.symm]
theorem tan_neg_of_neg_of_pi_div_two_lt {x : ℝ} (hx0 : x < 0) (hpx : -(π / 2) < x) : tan x < 0 :=
neg_pos.1 (tan_neg x ▸ tan_pos_of_pos_of_lt_pi_div_two (by linarith) (by linarith [pi_pos]))
theorem tan_nonpos_of_nonpos_of_neg_pi_div_two_le {x : ℝ} (hx0 : x ≤ 0) (hpx : -(π / 2) ≤ x) :
tan x ≤ 0 :=
neg_nonneg.1 (tan_neg x ▸ tan_nonneg_of_nonneg_of_le_pi_div_two (by linarith) (by linarith))
theorem strictMonoOn_tan : StrictMonoOn tan (Ioo (-(π / 2)) (π / 2)) := by
rintro x hx y hy hlt
rw [tan_eq_sin_div_cos, tan_eq_sin_div_cos,
div_lt_div_iff₀ (cos_pos_of_mem_Ioo hx) (cos_pos_of_mem_Ioo hy), mul_comm, ← sub_pos, ← sin_sub]
exact sin_pos_of_pos_of_lt_pi (sub_pos.2 hlt) <| by linarith [hx.1, hy.2]
theorem tan_lt_tan_of_lt_of_lt_pi_div_two {x y : ℝ} (hx₁ : -(π / 2) < x) (hy₂ : y < π / 2)
(hxy : x < y) : tan x < tan y :=
strictMonoOn_tan ⟨hx₁, hxy.trans hy₂⟩ ⟨hx₁.trans hxy, hy₂⟩ hxy
theorem tan_lt_tan_of_nonneg_of_lt_pi_div_two {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y < π / 2)
(hxy : x < y) : tan x < tan y :=
tan_lt_tan_of_lt_of_lt_pi_div_two (by linarith) hy₂ hxy
theorem injOn_tan : InjOn tan (Ioo (-(π / 2)) (π / 2)) :=
strictMonoOn_tan.injOn
theorem tan_inj_of_lt_of_lt_pi_div_two {x y : ℝ} (hx₁ : -(π / 2) < x) (hx₂ : x < π / 2)
(hy₁ : -(π / 2) < y) (hy₂ : y < π / 2) (hxy : tan x = tan y) : x = y :=
injOn_tan ⟨hx₁, hx₂⟩ ⟨hy₁, hy₂⟩ hxy
theorem tan_periodic : Function.Periodic tan π := by
simpa only [Function.Periodic, tan_eq_sin_div_cos] using sin_antiperiodic.div cos_antiperiodic
@[simp]
theorem tan_pi : tan π = 0 := by rw [tan_periodic.eq, tan_zero]
theorem tan_add_pi (x : ℝ) : tan (x + π) = tan x :=
tan_periodic x
theorem tan_sub_pi (x : ℝ) : tan (x - π) = tan x :=
tan_periodic.sub_eq x
theorem tan_pi_sub (x : ℝ) : tan (π - x) = -tan x :=
tan_neg x ▸ tan_periodic.sub_eq'
theorem tan_pi_div_two_sub (x : ℝ) : tan (π / 2 - x) = (tan x)⁻¹ := by
rw [tan_eq_sin_div_cos, tan_eq_sin_div_cos, inv_div, sin_pi_div_two_sub, cos_pi_div_two_sub]
theorem tan_nat_mul_pi (n : ℕ) : tan (n * π) = 0 :=
tan_zero ▸ tan_periodic.nat_mul_eq n
theorem tan_int_mul_pi (n : ℤ) : tan (n * π) = 0 :=
tan_zero ▸ tan_periodic.int_mul_eq n
theorem tan_add_nat_mul_pi (x : ℝ) (n : ℕ) : tan (x + n * π) = tan x :=
tan_periodic.nat_mul n x
theorem tan_add_int_mul_pi (x : ℝ) (n : ℤ) : tan (x + n * π) = tan x :=
tan_periodic.int_mul n x
theorem tan_sub_nat_mul_pi (x : ℝ) (n : ℕ) : tan (x - n * π) = tan x :=
tan_periodic.sub_nat_mul_eq n
theorem tan_sub_int_mul_pi (x : ℝ) (n : ℤ) : tan (x - n * π) = tan x :=
tan_periodic.sub_int_mul_eq n
theorem tan_nat_mul_pi_sub (x : ℝ) (n : ℕ) : tan (n * π - x) = -tan x :=
tan_neg x ▸ tan_periodic.nat_mul_sub_eq n
theorem tan_int_mul_pi_sub (x : ℝ) (n : ℤ) : tan (n * π - x) = -tan x :=
tan_neg x ▸ tan_periodic.int_mul_sub_eq n
theorem tendsto_sin_pi_div_two : Tendsto sin (𝓝[<] (π / 2)) (𝓝 1) := by
convert continuous_sin.continuousWithinAt.tendsto
simp
theorem tendsto_cos_pi_div_two : Tendsto cos (𝓝[<] (π / 2)) (𝓝[>] 0) := by
apply tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within
· convert continuous_cos.continuousWithinAt.tendsto
simp
· filter_upwards [Ioo_mem_nhdsLT (neg_lt_self pi_div_two_pos)] with x hx
exact cos_pos_of_mem_Ioo hx
theorem tendsto_tan_pi_div_two : Tendsto tan (𝓝[<] (π / 2)) atTop := by
convert tendsto_cos_pi_div_two.inv_tendsto_nhdsGT_zero.atTop_mul_pos zero_lt_one
tendsto_sin_pi_div_two using 1
simp only [Pi.inv_apply, ← div_eq_inv_mul, ← tan_eq_sin_div_cos]
theorem tendsto_sin_neg_pi_div_two : Tendsto sin (𝓝[>] (-(π / 2))) (𝓝 (-1)) := by
convert continuous_sin.continuousWithinAt.tendsto using 2
simp
theorem tendsto_cos_neg_pi_div_two : Tendsto cos (𝓝[>] (-(π / 2))) (𝓝[>] 0) := by
apply tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within
· convert continuous_cos.continuousWithinAt.tendsto
simp
· filter_upwards [Ioo_mem_nhdsGT (neg_lt_self pi_div_two_pos)] with x hx
exact cos_pos_of_mem_Ioo hx
theorem tendsto_tan_neg_pi_div_two : Tendsto tan (𝓝[>] (-(π / 2))) atBot := by
convert tendsto_cos_neg_pi_div_two.inv_tendsto_nhdsGT_zero.atTop_mul_neg (by norm_num)
tendsto_sin_neg_pi_div_two using 1
simp only [Pi.inv_apply, ← div_eq_inv_mul, ← tan_eq_sin_div_cos]
end Real
namespace Complex
open Real
theorem sin_eq_zero_iff_cos_eq {z : ℂ} : sin z = 0 ↔ cos z = 1 ∨ cos z = -1 := by
rw [← mul_self_eq_one_iff, ← sin_sq_add_cos_sq, sq, sq, ← sub_eq_iff_eq_add, sub_self]
exact ⟨fun h => by rw [h, mul_zero], eq_zero_of_mul_self_eq_zero ∘ Eq.symm⟩
@[simp]
theorem cos_pi_div_two : cos (π / 2) = 0 :=
calc
cos (π / 2) = Real.cos (π / 2) := by rw [ofReal_cos]; simp
_ = 0 := by simp
@[simp]
theorem sin_pi_div_two : sin (π / 2) = 1 :=
calc
sin (π / 2) = Real.sin (π / 2) := by rw [ofReal_sin]; simp
_ = 1 := by simp
@[simp]
theorem sin_pi : sin π = 0 := by rw [← ofReal_sin, Real.sin_pi]; simp
@[simp]
theorem cos_pi : cos π = -1 := by rw [← ofReal_cos, Real.cos_pi]; simp
@[simp]
theorem sin_two_pi : sin (2 * π) = 0 := by simp [two_mul, sin_add]
@[simp]
theorem cos_two_pi : cos (2 * π) = 1 := by simp [two_mul, cos_add]
theorem sin_antiperiodic : Function.Antiperiodic sin π := by simp [sin_add]
theorem sin_periodic : Function.Periodic sin (2 * π) :=
sin_antiperiodic.periodic_two_mul
theorem sin_add_pi (x : ℂ) : sin (x + π) = -sin x :=
sin_antiperiodic x
theorem sin_add_two_pi (x : ℂ) : sin (x + 2 * π) = sin x :=
sin_periodic x
theorem sin_sub_pi (x : ℂ) : sin (x - π) = -sin x :=
sin_antiperiodic.sub_eq x
theorem sin_sub_two_pi (x : ℂ) : sin (x - 2 * π) = sin x :=
sin_periodic.sub_eq x
theorem sin_pi_sub (x : ℂ) : sin (π - x) = sin x :=
neg_neg (sin x) ▸ sin_neg x ▸ sin_antiperiodic.sub_eq'
theorem sin_two_pi_sub (x : ℂ) : sin (2 * π - x) = -sin x :=
sin_neg x ▸ sin_periodic.sub_eq'
theorem sin_nat_mul_pi (n : ℕ) : sin (n * π) = 0 :=
sin_antiperiodic.nat_mul_eq_of_eq_zero sin_zero n
theorem sin_int_mul_pi (n : ℤ) : sin (n * π) = 0 :=
sin_antiperiodic.int_mul_eq_of_eq_zero sin_zero n
theorem sin_add_nat_mul_two_pi (x : ℂ) (n : ℕ) : sin (x + n * (2 * π)) = sin x :=
sin_periodic.nat_mul n x
theorem sin_add_int_mul_two_pi (x : ℂ) (n : ℤ) : sin (x + n * (2 * π)) = sin x :=
sin_periodic.int_mul n x
theorem sin_sub_nat_mul_two_pi (x : ℂ) (n : ℕ) : sin (x - n * (2 * π)) = sin x :=
sin_periodic.sub_nat_mul_eq n
theorem sin_sub_int_mul_two_pi (x : ℂ) (n : ℤ) : sin (x - n * (2 * π)) = sin x :=
sin_periodic.sub_int_mul_eq n
theorem sin_nat_mul_two_pi_sub (x : ℂ) (n : ℕ) : sin (n * (2 * π) - x) = -sin x :=
sin_neg x ▸ sin_periodic.nat_mul_sub_eq n
theorem sin_int_mul_two_pi_sub (x : ℂ) (n : ℤ) : sin (n * (2 * π) - x) = -sin x :=
sin_neg x ▸ sin_periodic.int_mul_sub_eq n
theorem cos_antiperiodic : Function.Antiperiodic cos π := by simp [cos_add]
theorem cos_periodic : Function.Periodic cos (2 * π) :=
cos_antiperiodic.periodic_two_mul
theorem cos_add_pi (x : ℂ) : cos (x + π) = -cos x :=
cos_antiperiodic x
theorem cos_add_two_pi (x : ℂ) : cos (x + 2 * π) = cos x :=
cos_periodic x
theorem cos_sub_pi (x : ℂ) : cos (x - π) = -cos x :=
cos_antiperiodic.sub_eq x
theorem cos_sub_two_pi (x : ℂ) : cos (x - 2 * π) = cos x :=
cos_periodic.sub_eq x
theorem cos_pi_sub (x : ℂ) : cos (π - x) = -cos x :=
cos_neg x ▸ cos_antiperiodic.sub_eq'
theorem cos_two_pi_sub (x : ℂ) : cos (2 * π - x) = cos x :=
cos_neg x ▸ cos_periodic.sub_eq'
theorem cos_nat_mul_two_pi (n : ℕ) : cos (n * (2 * π)) = 1 :=
(cos_periodic.nat_mul_eq n).trans cos_zero
theorem cos_int_mul_two_pi (n : ℤ) : cos (n * (2 * π)) = 1 :=
(cos_periodic.int_mul_eq n).trans cos_zero
theorem cos_add_nat_mul_two_pi (x : ℂ) (n : ℕ) : cos (x + n * (2 * π)) = cos x :=
cos_periodic.nat_mul n x
theorem cos_add_int_mul_two_pi (x : ℂ) (n : ℤ) : cos (x + n * (2 * π)) = cos x :=
cos_periodic.int_mul n x
theorem cos_sub_nat_mul_two_pi (x : ℂ) (n : ℕ) : cos (x - n * (2 * π)) = cos x :=
cos_periodic.sub_nat_mul_eq n
theorem cos_sub_int_mul_two_pi (x : ℂ) (n : ℤ) : cos (x - n * (2 * π)) = cos x :=
cos_periodic.sub_int_mul_eq n
theorem cos_nat_mul_two_pi_sub (x : ℂ) (n : ℕ) : cos (n * (2 * π) - x) = cos x :=
cos_neg x ▸ cos_periodic.nat_mul_sub_eq n
theorem cos_int_mul_two_pi_sub (x : ℂ) (n : ℤ) : cos (n * (2 * π) - x) = cos x :=
cos_neg x ▸ cos_periodic.int_mul_sub_eq n
theorem cos_nat_mul_two_pi_add_pi (n : ℕ) : cos (n * (2 * π) + π) = -1 := by
simpa only [cos_zero] using (cos_periodic.nat_mul n).add_antiperiod_eq cos_antiperiodic
theorem cos_int_mul_two_pi_add_pi (n : ℤ) : cos (n * (2 * π) + π) = -1 := by
simpa only [cos_zero] using (cos_periodic.int_mul n).add_antiperiod_eq cos_antiperiodic
theorem cos_nat_mul_two_pi_sub_pi (n : ℕ) : cos (n * (2 * π) - π) = -1 := by
simpa only [cos_zero] using (cos_periodic.nat_mul n).sub_antiperiod_eq cos_antiperiodic
theorem cos_int_mul_two_pi_sub_pi (n : ℤ) : cos (n * (2 * π) - π) = -1 := by
simpa only [cos_zero] using (cos_periodic.int_mul n).sub_antiperiod_eq cos_antiperiodic
theorem sin_add_pi_div_two (x : ℂ) : sin (x + π / 2) = cos x := by simp [sin_add]
theorem sin_sub_pi_div_two (x : ℂ) : sin (x - π / 2) = -cos x := by simp [sub_eq_add_neg, sin_add]
theorem sin_pi_div_two_sub (x : ℂ) : sin (π / 2 - x) = cos x := by simp [sub_eq_add_neg, sin_add]
theorem cos_add_pi_div_two (x : ℂ) : cos (x + π / 2) = -sin x := by simp [cos_add]
theorem cos_sub_pi_div_two (x : ℂ) : cos (x - π / 2) = sin x := by simp [sub_eq_add_neg, cos_add]
theorem cos_pi_div_two_sub (x : ℂ) : cos (π / 2 - x) = sin x := by
rw [← cos_neg, neg_sub, cos_sub_pi_div_two]
theorem tan_periodic : Function.Periodic tan π := by
simpa only [tan_eq_sin_div_cos] using sin_antiperiodic.div cos_antiperiodic
theorem tan_add_pi (x : ℂ) : tan (x + π) = tan x :=
tan_periodic x
theorem tan_sub_pi (x : ℂ) : tan (x - π) = tan x :=
tan_periodic.sub_eq x
theorem tan_pi_sub (x : ℂ) : tan (π - x) = -tan x :=
tan_neg x ▸ tan_periodic.sub_eq'
theorem tan_pi_div_two_sub (x : ℂ) : tan (π / 2 - x) = (tan x)⁻¹ := by
rw [tan_eq_sin_div_cos, tan_eq_sin_div_cos, inv_div, sin_pi_div_two_sub, cos_pi_div_two_sub]
theorem tan_nat_mul_pi (n : ℕ) : tan (n * π) = 0 :=
tan_zero ▸ tan_periodic.nat_mul_eq n
theorem tan_int_mul_pi (n : ℤ) : tan (n * π) = 0 :=
tan_zero ▸ tan_periodic.int_mul_eq n
theorem tan_add_nat_mul_pi (x : ℂ) (n : ℕ) : tan (x + n * π) = tan x :=
tan_periodic.nat_mul n x
theorem tan_add_int_mul_pi (x : ℂ) (n : ℤ) : tan (x + n * π) = tan x :=
tan_periodic.int_mul n x
theorem tan_sub_nat_mul_pi (x : ℂ) (n : ℕ) : tan (x - n * π) = tan x :=
tan_periodic.sub_nat_mul_eq n
theorem tan_sub_int_mul_pi (x : ℂ) (n : ℤ) : tan (x - n * π) = tan x :=
tan_periodic.sub_int_mul_eq n
theorem tan_nat_mul_pi_sub (x : ℂ) (n : ℕ) : tan (n * π - x) = -tan x :=
tan_neg x ▸ tan_periodic.nat_mul_sub_eq n
theorem tan_int_mul_pi_sub (x : ℂ) (n : ℤ) : tan (n * π - x) = -tan x :=
tan_neg x ▸ tan_periodic.int_mul_sub_eq n
theorem exp_antiperiodic : Function.Antiperiodic exp (π * I) := by simp [exp_add, exp_mul_I]
theorem exp_periodic : Function.Periodic exp (2 * π * I) :=
(mul_assoc (2 : ℂ) π I).symm ▸ exp_antiperiodic.periodic_two_mul
theorem exp_mul_I_antiperiodic : Function.Antiperiodic (fun x => exp (x * I)) π := by
simpa only [mul_inv_cancel_right₀ I_ne_zero] using exp_antiperiodic.mul_const I_ne_zero
theorem exp_mul_I_periodic : Function.Periodic (fun x => exp (x * I)) (2 * π) :=
exp_mul_I_antiperiodic.periodic_two_mul
@[simp]
theorem exp_pi_mul_I : exp (π * I) = -1 :=
exp_zero ▸ exp_antiperiodic.eq
@[simp]
theorem exp_two_pi_mul_I : exp (2 * π * I) = 1 :=
exp_periodic.eq.trans exp_zero
@[simp]
lemma exp_pi_div_two_mul_I : exp (π / 2 * I) = I := by
rw [← cos_add_sin_I, cos_pi_div_two, sin_pi_div_two, one_mul, zero_add]
@[simp]
lemma exp_neg_pi_div_two_mul_I : exp (-π / 2 * I) = -I := by
rw [← cos_add_sin_I, neg_div, cos_neg, cos_pi_div_two, sin_neg, sin_pi_div_two, zero_add, neg_mul,
one_mul]
@[simp]
theorem exp_nat_mul_two_pi_mul_I (n : ℕ) : exp (n * (2 * π * I)) = 1 :=
(exp_periodic.nat_mul_eq n).trans exp_zero
@[simp]
theorem exp_int_mul_two_pi_mul_I (n : ℤ) : exp (n * (2 * π * I)) = 1 :=
(exp_periodic.int_mul_eq n).trans exp_zero
@[simp]
theorem exp_add_pi_mul_I (z : ℂ) : exp (z + π * I) = -exp z :=
exp_antiperiodic z
@[simp]
theorem exp_sub_pi_mul_I (z : ℂ) : exp (z - π * I) = -exp z :=
exp_antiperiodic.sub_eq z
/-- A supporting lemma for the **Phragmen-Lindelöf principle** in a horizontal strip. If `z : ℂ`
belongs to a horizontal strip `|Complex.im z| ≤ b`, `b ≤ π / 2`, and `a ≤ 0`, then
$$\left|exp^{a\left(e^{z}+e^{-z}\right)}\right| \le e^{a\cos b \exp^{|re z|}}.$$
-/
theorem norm_exp_mul_exp_add_exp_neg_le_of_abs_im_le {a b : ℝ} (ha : a ≤ 0) {z : ℂ}
(hz : |z.im| ≤ b) (hb : b ≤ π / 2) :
‖exp (a * (exp z + exp (-z)))‖ ≤ Real.exp (a * Real.cos b * Real.exp |z.re|) := by
simp only [norm_exp, Real.exp_le_exp, re_ofReal_mul, add_re, exp_re, neg_im, Real.cos_neg, ←
add_mul, mul_assoc, mul_comm (Real.cos b), neg_re, ← Real.cos_abs z.im]
have : Real.exp |z.re| ≤ Real.exp z.re + Real.exp (-z.re) :=
apply_abs_le_add_of_nonneg (fun x => (Real.exp_pos x).le) z.re
refine mul_le_mul_of_nonpos_left (mul_le_mul this ?_ ?_ ((Real.exp_pos _).le.trans this)) ha
· exact
Real.cos_le_cos_of_nonneg_of_le_pi (_root_.abs_nonneg _)
(hb.trans <| half_le_self <| Real.pi_pos.le) hz
· refine Real.cos_nonneg_of_mem_Icc ⟨?_, hb⟩
exact (neg_nonpos.2 <| Real.pi_div_two_pos.le).trans ((_root_.abs_nonneg _).trans hz)
@[deprecated (since := "2025-02-16")] alias abs_exp_mul_exp_add_exp_neg_le_of_abs_im_le :=
norm_exp_mul_exp_add_exp_neg_le_of_abs_im_le
end Complex
| Mathlib/Analysis/SpecialFunctions/Trigonometric/Basic.lean | 1,314 | 1,315 | |
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad
-/
import Mathlib.Algebra.Group.Int.Defs
import Mathlib.Algebra.Order.Monoid.Defs
/-!
# The integers form a linear ordered group
This file contains the instance necessary to show that the integers are a linear ordered
additive group.
See note [foundational algebra order theory].
-/
-- We should need only a minimal development of sets in order to get here.
assert_not_exists Set.Subsingleton Ring
instance Int.instIsOrderedAddMonoid : IsOrderedAddMonoid ℤ where
add_le_add_left _ _ := Int.add_le_add_left
| Mathlib/Algebra/Order/Group/Int.lean | 57 | 57 | |
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Yury Kudryashov, Yaël Dillies
-/
import Mathlib.Algebra.Order.Invertible
import Mathlib.Algebra.Order.Module.OrderedSMul
import Mathlib.LinearAlgebra.AffineSpace.Midpoint
import Mathlib.LinearAlgebra.LinearIndependent.Lemmas
import Mathlib.LinearAlgebra.Ray
import Mathlib.Tactic.GCongr
/-!
# Segments in vector spaces
In a 𝕜-vector space, we define the following objects and properties.
* `segment 𝕜 x y`: Closed segment joining `x` and `y`.
* `openSegment 𝕜 x y`: Open segment joining `x` and `y`.
## Notations
We provide the following notation:
* `[x -[𝕜] y] = segment 𝕜 x y` in locale `Convex`
## TODO
Generalize all this file to affine spaces.
Should we rename `segment` and `openSegment` to `convex.Icc` and `convex.Ioo`? Should we also
define `clopenSegment`/`convex.Ico`/`convex.Ioc`?
-/
variable {𝕜 E F G ι : Type*} {M : ι → Type*}
open Function Set
open Pointwise Convex
section OrderedSemiring
variable [Semiring 𝕜] [PartialOrder 𝕜] [AddCommMonoid E]
section SMul
variable (𝕜) [SMul 𝕜 E] {s : Set E} {x y : E}
/-- Segments in a vector space. -/
def segment (x y : E) : Set E :=
{ z : E | ∃ a b : 𝕜, 0 ≤ a ∧ 0 ≤ b ∧ a + b = 1 ∧ a • x + b • y = z }
/-- Open segment in a vector space. Note that `openSegment 𝕜 x x = {x}` instead of being `∅` when
the base semiring has some element between `0` and `1`.
Denoted as `[x -[𝕜] y]` within the `Convex` namespace. -/
def openSegment (x y : E) : Set E :=
{ z : E | ∃ a b : 𝕜, 0 < a ∧ 0 < b ∧ a + b = 1 ∧ a • x + b • y = z }
@[inherit_doc] scoped[Convex] notation (priority := high) "[" x " -[" 𝕜 "] " y "]" => segment 𝕜 x y
theorem segment_eq_image₂ (x y : E) :
[x -[𝕜] y] =
(fun p : 𝕜 × 𝕜 => p.1 • x + p.2 • y) '' { p | 0 ≤ p.1 ∧ 0 ≤ p.2 ∧ p.1 + p.2 = 1 } := by
simp only [segment, image, Prod.exists, mem_setOf_eq, exists_prop, and_assoc]
theorem openSegment_eq_image₂ (x y : E) :
openSegment 𝕜 x y =
(fun p : 𝕜 × 𝕜 => p.1 • x + p.2 • y) '' { p | 0 < p.1 ∧ 0 < p.2 ∧ p.1 + p.2 = 1 } := by
simp only [openSegment, image, Prod.exists, mem_setOf_eq, exists_prop, and_assoc]
theorem segment_symm (x y : E) : [x -[𝕜] y] = [y -[𝕜] x] :=
Set.ext fun _ =>
⟨fun ⟨a, b, ha, hb, hab, H⟩ => ⟨b, a, hb, ha, (add_comm _ _).trans hab, (add_comm _ _).trans H⟩,
fun ⟨a, b, ha, hb, hab, H⟩ =>
⟨b, a, hb, ha, (add_comm _ _).trans hab, (add_comm _ _).trans H⟩⟩
theorem openSegment_symm (x y : E) : openSegment 𝕜 x y = openSegment 𝕜 y x :=
Set.ext fun _ =>
⟨fun ⟨a, b, ha, hb, hab, H⟩ => ⟨b, a, hb, ha, (add_comm _ _).trans hab, (add_comm _ _).trans H⟩,
fun ⟨a, b, ha, hb, hab, H⟩ =>
⟨b, a, hb, ha, (add_comm _ _).trans hab, (add_comm _ _).trans H⟩⟩
theorem openSegment_subset_segment (x y : E) : openSegment 𝕜 x y ⊆ [x -[𝕜] y] :=
fun _ ⟨a, b, ha, hb, hab, hz⟩ => ⟨a, b, ha.le, hb.le, hab, hz⟩
theorem segment_subset_iff :
[x -[𝕜] y] ⊆ s ↔ ∀ a b : 𝕜, 0 ≤ a → 0 ≤ b → a + b = 1 → a • x + b • y ∈ s :=
⟨fun H a b ha hb hab => H ⟨a, b, ha, hb, hab, rfl⟩, fun H _ ⟨a, b, ha, hb, hab, hz⟩ =>
hz ▸ H a b ha hb hab⟩
theorem openSegment_subset_iff :
openSegment 𝕜 x y ⊆ s ↔ ∀ a b : 𝕜, 0 < a → 0 < b → a + b = 1 → a • x + b • y ∈ s :=
⟨fun H a b ha hb hab => H ⟨a, b, ha, hb, hab, rfl⟩, fun H _ ⟨a, b, ha, hb, hab, hz⟩ =>
hz ▸ H a b ha hb hab⟩
end SMul
open Convex
section MulActionWithZero
variable (𝕜)
variable [ZeroLEOneClass 𝕜] [MulActionWithZero 𝕜 E]
theorem left_mem_segment (x y : E) : x ∈ [x -[𝕜] y] :=
⟨1, 0, zero_le_one, le_refl 0, add_zero 1, by rw [zero_smul, one_smul, add_zero]⟩
theorem right_mem_segment (x y : E) : y ∈ [x -[𝕜] y] :=
segment_symm 𝕜 y x ▸ left_mem_segment 𝕜 y x
end MulActionWithZero
section Module
variable (𝕜)
variable [ZeroLEOneClass 𝕜] [Module 𝕜 E] {s : Set E} {x y z : E}
@[simp]
theorem segment_same (x : E) : [x -[𝕜] x] = {x} :=
Set.ext fun z =>
⟨fun ⟨a, b, _, _, hab, hz⟩ => by
simpa only [(add_smul _ _ _).symm, mem_singleton_iff, hab, one_smul, eq_comm] using hz,
fun h => mem_singleton_iff.1 h ▸ left_mem_segment 𝕜 z z⟩
theorem insert_endpoints_openSegment (x y : E) :
insert x (insert y (openSegment 𝕜 x y)) = [x -[𝕜] y] := by
simp only [subset_antisymm_iff, insert_subset_iff, left_mem_segment, right_mem_segment,
openSegment_subset_segment, true_and]
rintro z ⟨a, b, ha, hb, hab, rfl⟩
refine hb.eq_or_gt.imp ?_ fun hb' => ha.eq_or_gt.imp ?_ fun ha' => ?_
· rintro rfl
rw [← add_zero a, hab, one_smul, zero_smul, add_zero]
· rintro rfl
rw [← zero_add b, hab, one_smul, zero_smul, zero_add]
· exact ⟨a, b, ha', hb', hab, rfl⟩
variable {𝕜}
theorem mem_openSegment_of_ne_left_right (hx : x ≠ z) (hy : y ≠ z) (hz : z ∈ [x -[𝕜] y]) :
z ∈ openSegment 𝕜 x y := by
rw [← insert_endpoints_openSegment] at hz
exact (hz.resolve_left hx.symm).resolve_left hy.symm
theorem openSegment_subset_iff_segment_subset (hx : x ∈ s) (hy : y ∈ s) :
openSegment 𝕜 x y ⊆ s ↔ [x -[𝕜] y] ⊆ s := by
simp only [← insert_endpoints_openSegment, insert_subset_iff, *, true_and]
end Module
end OrderedSemiring
open Convex
section OrderedRing
variable (𝕜) [Ring 𝕜] [PartialOrder 𝕜] [AddRightMono 𝕜]
[AddCommGroup E] [AddCommGroup F] [AddCommGroup G] [Module 𝕜 E] [Module 𝕜 F]
section DenselyOrdered
variable [ZeroLEOneClass 𝕜] [Nontrivial 𝕜] [DenselyOrdered 𝕜]
@[simp]
theorem openSegment_same (x : E) : openSegment 𝕜 x x = {x} :=
Set.ext fun z =>
⟨fun ⟨a, b, _, _, hab, hz⟩ => by
simpa only [← add_smul, mem_singleton_iff, hab, one_smul, eq_comm] using hz,
fun h : z = x => by
obtain ⟨a, ha₀, ha₁⟩ := DenselyOrdered.dense (0 : 𝕜) 1 zero_lt_one
refine ⟨a, 1 - a, ha₀, sub_pos_of_lt ha₁, add_sub_cancel _ _, ?_⟩
rw [← add_smul, add_sub_cancel, one_smul, h]⟩
end DenselyOrdered
theorem segment_eq_image (x y : E) :
[x -[𝕜] y] = (fun θ : 𝕜 => (1 - θ) • x + θ • y) '' Icc (0 : 𝕜) 1 :=
Set.ext fun _ =>
⟨fun ⟨a, b, ha, hb, hab, hz⟩ =>
⟨b, ⟨hb, hab ▸ le_add_of_nonneg_left ha⟩, hab ▸ hz ▸ by simp only [add_sub_cancel_right]⟩,
fun ⟨θ, ⟨hθ₀, hθ₁⟩, hz⟩ => ⟨1 - θ, θ, sub_nonneg.2 hθ₁, hθ₀, sub_add_cancel _ _, hz⟩⟩
theorem openSegment_eq_image (x y : E) :
openSegment 𝕜 x y = (fun θ : 𝕜 => (1 - θ) • x + θ • y) '' Ioo (0 : 𝕜) 1 :=
Set.ext fun _ =>
⟨fun ⟨a, b, ha, hb, hab, hz⟩ =>
⟨b, ⟨hb, hab ▸ lt_add_of_pos_left _ ha⟩, hab ▸ hz ▸ by simp only [add_sub_cancel_right]⟩,
fun ⟨θ, ⟨hθ₀, hθ₁⟩, hz⟩ => ⟨1 - θ, θ, sub_pos.2 hθ₁, hθ₀, sub_add_cancel _ _, hz⟩⟩
theorem segment_eq_image' (x y : E) :
[x -[𝕜] y] = (fun θ : 𝕜 => x + θ • (y - x)) '' Icc (0 : 𝕜) 1 := by
convert segment_eq_image 𝕜 x y using 2
simp only [smul_sub, sub_smul, one_smul]
abel
theorem openSegment_eq_image' (x y : E) :
openSegment 𝕜 x y = (fun θ : 𝕜 => x + θ • (y - x)) '' Ioo (0 : 𝕜) 1 := by
convert openSegment_eq_image 𝕜 x y using 2
simp only [smul_sub, sub_smul, one_smul]
abel
theorem segment_eq_image_lineMap (x y : E) : [x -[𝕜] y] =
AffineMap.lineMap x y '' Icc (0 : 𝕜) 1 := by
convert segment_eq_image 𝕜 x y using 2
exact AffineMap.lineMap_apply_module _ _ _
theorem openSegment_eq_image_lineMap (x y : E) :
openSegment 𝕜 x y = AffineMap.lineMap x y '' Ioo (0 : 𝕜) 1 := by
convert openSegment_eq_image 𝕜 x y using 2
exact AffineMap.lineMap_apply_module _ _ _
@[simp]
theorem image_segment (f : E →ᵃ[𝕜] F) (a b : E) : f '' [a -[𝕜] b] = [f a -[𝕜] f b] :=
Set.ext fun x => by
simp_rw [segment_eq_image_lineMap, mem_image, exists_exists_and_eq_and, AffineMap.apply_lineMap]
@[simp]
theorem image_openSegment (f : E →ᵃ[𝕜] F) (a b : E) :
f '' openSegment 𝕜 a b = openSegment 𝕜 (f a) (f b) :=
Set.ext fun x => by
simp_rw [openSegment_eq_image_lineMap, mem_image, exists_exists_and_eq_and,
AffineMap.apply_lineMap]
@[simp]
theorem vadd_segment [AddTorsor G E] [VAddCommClass G E E] (a : G) (b c : E) :
a +ᵥ [b -[𝕜] c] = [a +ᵥ b -[𝕜] a +ᵥ c] :=
image_segment 𝕜 ⟨_, LinearMap.id, fun _ _ => vadd_comm _ _ _⟩ b c
@[simp]
theorem vadd_openSegment [AddTorsor G E] [VAddCommClass G E E] (a : G) (b c : E) :
a +ᵥ openSegment 𝕜 b c = openSegment 𝕜 (a +ᵥ b) (a +ᵥ c) :=
image_openSegment 𝕜 ⟨_, LinearMap.id, fun _ _ => vadd_comm _ _ _⟩ b c
@[simp]
theorem mem_segment_translate (a : E) {x b c} : a + x ∈ [a + b -[𝕜] a + c] ↔ x ∈ [b -[𝕜] c] := by
simp_rw [← vadd_eq_add, ← vadd_segment, vadd_mem_vadd_set_iff]
@[simp]
theorem mem_openSegment_translate (a : E) {x b c : E} :
a + x ∈ openSegment 𝕜 (a + b) (a + c) ↔ x ∈ openSegment 𝕜 b c := by
simp_rw [← vadd_eq_add, ← vadd_openSegment, vadd_mem_vadd_set_iff]
theorem segment_translate_preimage (a b c : E) :
(fun x => a + x) ⁻¹' [a + b -[𝕜] a + c] = [b -[𝕜] c] :=
Set.ext fun _ => mem_segment_translate 𝕜 a
theorem openSegment_translate_preimage (a b c : E) :
(fun x => a + x) ⁻¹' openSegment 𝕜 (a + b) (a + c) = openSegment 𝕜 b c :=
Set.ext fun _ => mem_openSegment_translate 𝕜 a
theorem segment_translate_image (a b c : E) : (fun x => a + x) '' [b -[𝕜] c] = [a + b -[𝕜] a + c] :=
segment_translate_preimage 𝕜 a b c ▸ image_preimage_eq _ <| add_left_surjective a
theorem openSegment_translate_image (a b c : E) :
(fun x => a + x) '' openSegment 𝕜 b c = openSegment 𝕜 (a + b) (a + c) :=
openSegment_translate_preimage 𝕜 a b c ▸ image_preimage_eq _ <| add_left_surjective a
lemma segment_inter_subset_endpoint_of_linearIndependent_sub
{c x y : E} (h : LinearIndependent 𝕜 ![x - c, y - c]) :
[c -[𝕜] x] ∩ [c -[𝕜] y] ⊆ {c} := by
intro z ⟨hzt, hzs⟩
rw [segment_eq_image, mem_image] at hzt hzs
rcases hzt with ⟨p, ⟨p0, p1⟩, rfl⟩
rcases hzs with ⟨q, ⟨q0, q1⟩, H⟩
have Hx : x = (x - c) + c := by abel
have Hy : y = (y - c) + c := by abel
| rw [Hx, Hy, smul_add, smul_add] at H
have : c + q • (y - c) = c + p • (x - c) := by
convert H using 1 <;> simp [sub_smul]
| Mathlib/Analysis/Convex/Segment.lean | 265 | 267 |
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro
-/
import Mathlib.Data.Finset.Attach
import Mathlib.Data.Finset.Disjoint
import Mathlib.Data.Finset.Erase
import Mathlib.Data.Finset.Filter
import Mathlib.Data.Finset.Range
import Mathlib.Data.Finset.SDiff
import Mathlib.Data.Multiset.Basic
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Defs
import Mathlib.Data.Set.SymmDiff
/-!
# Basic lemmas on finite sets
This file contains lemmas on the interaction of various definitions on the `Finset` type.
For an explanation of `Finset` design decisions, please see `Mathlib/Data/Finset/Defs.lean`.
## Main declarations
### Main definitions
* `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element
satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate.
### Equivalences between finsets
* The `Mathlib/Logic/Equiv/Defs.lean` file describes a general type of equivalence, so look in there
for any lemmas. There is some API for rewriting sums and products from `s` to `t` given that
`s ≃ t`.
TODO: examples
## Tags
finite sets, finset
-/
-- Assert that we define `Finset` without the material on `List.sublists`.
-- Note that we cannot use `List.sublists` itself as that is defined very early.
assert_not_exists List.sublistsLen Multiset.powerset CompleteLattice Monoid
open Multiset Subtype Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
namespace Finset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
set_option linter.deprecated false in
@[deprecated "Deprecated without replacement." (since := "2025-02-07")]
theorem sizeOf_lt_sizeOf_of_mem [SizeOf α] {x : α} {s : Finset α} (hx : x ∈ s) :
SizeOf.sizeOf x < SizeOf.sizeOf s := by
cases s
dsimp [SizeOf.sizeOf, SizeOf.sizeOf, Multiset.sizeOf]
rw [Nat.add_comm]
refine lt_trans ?_ (Nat.lt_succ_self _)
exact Multiset.sizeOf_lt_sizeOf_of_mem hx
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-! #### union -/
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
@[simp]
theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by
simp only [disjoint_left, mem_union, or_imp, forall_and]
@[simp]
theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by
simp only [disjoint_right, mem_union, or_imp, forall_and]
/-! #### inter -/
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
omit [DecidableEq α] in
theorem disjoint_of_subset_iff_left_eq_empty (h : s ⊆ t) :
Disjoint s t ↔ s = ∅ :=
disjoint_of_le_iff_left_eq_bot h
lemma pairwiseDisjoint_iff {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint f ↔ ∀ ⦃i⦄, i ∈ s → ∀ ⦃j⦄, j ∈ s → (f i ∩ f j).Nonempty → i = j := by
simp [Set.PairwiseDisjoint, Set.Pairwise, Function.onFun, not_imp_comm (a := _ = _),
not_disjoint_iff_nonempty_inter]
end Lattice
instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance
instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le
/-! ### erase -/
section Erase
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
@[simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty :=
(hs.exists_ne a).imp <| by aesop
@[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by
simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)]
refine ⟨?_, fun hs ↦ hs.exists_ne a⟩
rintro ⟨b, hb, hba⟩
exact ⟨_, hb, _, ha, hba⟩
@[simp]
theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by
ext x
simp
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp +contextual only [mem_erase, mem_insert, and_congr_right_iff,
false_or, iff_self, imp_true_iff]
theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by
rw [erase_insert_eq_erase, erase_eq_of_not_mem h]
theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) :
erase (insert a s) b = insert a (erase s b) :=
ext fun x => by
have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h
simp only [mem_erase, mem_insert, and_or_left, this]
theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) :
erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by
simp only [cons_eq_insert, erase_insert_of_ne hb]
@[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s :=
ext fun x => by
simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and]
apply or_iff_right_of_imp
rintro rfl
exact h
lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by
aesop
lemma insert_erase_invOn :
Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} :=
⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩
theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s :=
calc
s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _
_ = _ := insert_erase h
theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩
obtain ⟨a, ht, hs⟩ := not_subset.1 h.2
exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩
theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s :=
ssubset_iff_exists_subset_erase.2
⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩
theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by
rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h]
theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by
simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp]
exact forall_congr' fun x => forall_swap
theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s :=
subset_insert_iff.1 <| Subset.rfl
theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) :=
subset_insert_iff.2 <| Subset.rfl
theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by
rw [subset_insert_iff, erase_eq_of_not_mem h]
theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by
rw [← subset_insert_iff, insert_eq_of_mem h]
theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a :=
fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h]
end Erase
lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) :
∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by
classical
obtain ⟨a, ha, b, hb, hab⟩ := hs
have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩
refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;>
simp [insert_erase this, insert_erase ha, *]
/-! ### sdiff -/
section Sdiff
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by
ext; aesop
-- TODO: Do we want to delete this lemma and `Finset.disjUnion_singleton`,
-- or instead add `Finset.union_singleton`/`Finset.singleton_union`?
theorem sdiff_singleton_eq_erase (a : α) (s : Finset α) : s \ {a} = erase s a := by
ext
rw [mem_erase, mem_sdiff, mem_singleton, and_comm]
-- This lemma matches `Finset.insert_eq` in functionality.
theorem erase_eq (s : Finset α) (a : α) : s.erase a = s \ {a} :=
(sdiff_singleton_eq_erase _ _).symm
theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by
simp_rw [erase_eq, disjoint_sdiff_comm]
lemma disjoint_insert_erase (ha : a ∉ t) : Disjoint (s.erase a) (insert a t) ↔ Disjoint s t := by
rw [disjoint_erase_comm, erase_insert ha]
lemma disjoint_erase_insert (ha : a ∉ s) : Disjoint (insert a s) (t.erase a) ↔ Disjoint s t := by
rw [← disjoint_erase_comm, erase_insert ha]
theorem disjoint_of_erase_left (ha : a ∉ t) (hst : Disjoint (s.erase a) t) : Disjoint s t := by
rw [← erase_insert ha, ← disjoint_erase_comm, disjoint_insert_right]
exact ⟨not_mem_erase _ _, hst⟩
theorem disjoint_of_erase_right (ha : a ∉ s) (hst : Disjoint s (t.erase a)) : Disjoint s t := by
rw [← erase_insert ha, disjoint_erase_comm, disjoint_insert_left]
exact ⟨not_mem_erase _ _, hst⟩
theorem inter_erase (a : α) (s t : Finset α) : s ∩ t.erase a = (s ∩ t).erase a := by
simp only [erase_eq, inter_sdiff_assoc]
@[simp]
theorem erase_inter (a : α) (s t : Finset α) : s.erase a ∩ t = (s ∩ t).erase a := by
simpa only [inter_comm t] using inter_erase a t s
theorem erase_sdiff_comm (s t : Finset α) (a : α) : s.erase a \ t = (s \ t).erase a := by
simp_rw [erase_eq, sdiff_right_comm]
theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by
rw [erase_inter, inter_erase]
theorem erase_union_distrib (s t : Finset α) (a : α) : (s ∪ t).erase a = s.erase a ∪ t.erase a := by
simp_rw [erase_eq, union_sdiff_distrib]
theorem insert_inter_distrib (s t : Finset α) (a : α) :
insert a (s ∩ t) = insert a s ∩ insert a t := by simp_rw [insert_eq, union_inter_distrib_left]
theorem erase_sdiff_distrib (s t : Finset α) (a : α) : (s \ t).erase a = s.erase a \ t.erase a := by
simp_rw [erase_eq, sdiff_sdiff, sup_sdiff_eq_sup le_rfl, sup_comm]
theorem erase_union_of_mem (ha : a ∈ t) (s : Finset α) : s.erase a ∪ t = s ∪ t := by
rw [← insert_erase (mem_union_right s ha), erase_union_distrib, ← union_insert, insert_erase ha]
theorem union_erase_of_mem (ha : a ∈ s) (t : Finset α) : s ∪ t.erase a = s ∪ t := by
rw [← insert_erase (mem_union_left t ha), erase_union_distrib, ← insert_union, insert_erase ha]
theorem sdiff_union_erase_cancel (hts : t ⊆ s) (ha : a ∈ t) : s \ t ∪ t.erase a = s.erase a := by
simp_rw [erase_eq, sdiff_union_sdiff_cancel hts (singleton_subset_iff.2 ha)]
theorem sdiff_insert (s t : Finset α) (x : α) : s \ insert x t = (s \ t).erase x := by
simp_rw [← sdiff_singleton_eq_erase, insert_eq, sdiff_sdiff_left', sdiff_union_distrib,
inter_comm]
theorem sdiff_insert_insert_of_mem_of_not_mem {s t : Finset α} {x : α} (hxs : x ∈ s) (hxt : x ∉ t) :
insert x (s \ insert x t) = s \ t := by
rw [sdiff_insert, insert_erase (mem_sdiff.mpr ⟨hxs, hxt⟩)]
theorem sdiff_erase (h : a ∈ s) : s \ t.erase a = insert a (s \ t) := by
rw [← sdiff_singleton_eq_erase, sdiff_sdiff_eq_sdiff_union (singleton_subset_iff.2 h), insert_eq,
union_comm]
theorem sdiff_erase_self (ha : a ∈ s) : s \ s.erase a = {a} := by
rw [sdiff_erase ha, Finset.sdiff_self, insert_empty_eq]
theorem erase_eq_empty_iff (s : Finset α) (a : α) : s.erase a = ∅ ↔ s = ∅ ∨ s = {a} := by
rw [← sdiff_singleton_eq_erase, sdiff_eq_empty_iff_subset, subset_singleton_iff]
--TODO@Yaël: Kill lemmas duplicate with `BooleanAlgebra`
theorem sdiff_disjoint : Disjoint (t \ s) s :=
disjoint_left.2 fun _a ha => (mem_sdiff.1 ha).2
theorem disjoint_sdiff : Disjoint s (t \ s) :=
sdiff_disjoint.symm
theorem disjoint_sdiff_inter (s t : Finset α) : Disjoint (s \ t) (s ∩ t) :=
disjoint_of_subset_right inter_subset_right sdiff_disjoint
end Sdiff
/-! ### attach -/
@[simp]
theorem attach_empty : attach (∅ : Finset α) = ∅ :=
rfl
@[simp]
theorem attach_nonempty_iff {s : Finset α} : s.attach.Nonempty ↔ s.Nonempty := by
simp [Finset.Nonempty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Nonempty.attach⟩ := attach_nonempty_iff
@[simp]
theorem attach_eq_empty_iff {s : Finset α} : s.attach = ∅ ↔ s = ∅ := by
simp [eq_empty_iff_forall_not_mem]
/-! ### filter -/
section Filter
variable (p q : α → Prop) [DecidablePred p] [DecidablePred q] {s t : Finset α}
theorem filter_singleton (a : α) : filter p {a} = if p a then {a} else ∅ := by
classical
ext x
simp only [mem_singleton, forall_eq, mem_filter]
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_cons_of_pos (a : α) (s : Finset α) (ha : a ∉ s) (hp : p a) :
filter p (cons a s ha) = cons a (filter p s) ((mem_of_mem_filter _).mt ha) :=
eq_of_veq <| Multiset.filter_cons_of_pos s.val hp
theorem filter_cons_of_neg (a : α) (s : Finset α) (ha : a ∉ s) (hp : ¬p a) :
filter p (cons a s ha) = filter p s :=
eq_of_veq <| Multiset.filter_cons_of_neg s.val hp
theorem disjoint_filter {s : Finset α} {p q : α → Prop} [DecidablePred p] [DecidablePred q] :
Disjoint (s.filter p) (s.filter q) ↔ ∀ x ∈ s, p x → ¬q x := by
constructor <;> simp +contextual [disjoint_left]
theorem disjoint_filter_filter' (s t : Finset α)
{p q : α → Prop} [DecidablePred p] [DecidablePred q] (h : Disjoint p q) :
Disjoint (s.filter p) (t.filter q) := by
simp_rw [disjoint_left, mem_filter]
rintro a ⟨_, hp⟩ ⟨_, hq⟩
rw [Pi.disjoint_iff] at h
simpa [hp, hq] using h a
theorem disjoint_filter_filter_neg (s t : Finset α) (p : α → Prop)
[DecidablePred p] [∀ x, Decidable (¬p x)] :
Disjoint (s.filter p) (t.filter fun a => ¬p a) :=
disjoint_filter_filter' s t disjoint_compl_right
theorem filter_disj_union (s : Finset α) (t : Finset α) (h : Disjoint s t) :
filter p (disjUnion s t h) = (filter p s).disjUnion (filter p t) (disjoint_filter_filter h) :=
eq_of_veq <| Multiset.filter_add _ _ _
theorem filter_cons {a : α} (s : Finset α) (ha : a ∉ s) :
filter p (cons a s ha) =
if p a then cons a (filter p s) ((mem_of_mem_filter _).mt ha) else filter p s := by
split_ifs with h
· rw [filter_cons_of_pos _ _ _ ha h]
· rw [filter_cons_of_neg _ _ _ ha h]
section
variable [DecidableEq α]
theorem filter_union (s₁ s₂ : Finset α) : (s₁ ∪ s₂).filter p = s₁.filter p ∪ s₂.filter p :=
ext fun _ => by simp only [mem_filter, mem_union, or_and_right]
theorem filter_union_right (s : Finset α) : s.filter p ∪ s.filter q = s.filter fun x => p x ∨ q x :=
ext fun x => by simp [mem_filter, mem_union, ← and_or_left]
theorem filter_mem_eq_inter {s t : Finset α} [∀ i, Decidable (i ∈ t)] :
(s.filter fun i => i ∈ t) = s ∩ t :=
ext fun i => by simp [mem_filter, mem_inter]
theorem filter_inter_distrib (s t : Finset α) : (s ∩ t).filter p = s.filter p ∩ t.filter p := by
ext
simp [mem_filter, mem_inter, and_assoc]
theorem filter_inter (s t : Finset α) : filter p s ∩ t = filter p (s ∩ t) := by
ext
simp only [mem_inter, mem_filter, and_right_comm]
theorem inter_filter (s t : Finset α) : s ∩ filter p t = filter p (s ∩ t) := by
rw [inter_comm, filter_inter, inter_comm]
theorem filter_insert (a : α) (s : Finset α) :
filter p (insert a s) = if p a then insert a (filter p s) else filter p s := by
ext x
split_ifs with h <;> by_cases h' : x = a <;> simp [h, h']
theorem filter_erase (a : α) (s : Finset α) : filter p (erase s a) = erase (filter p s) a := by
ext x
simp only [and_assoc, mem_filter, iff_self, mem_erase]
theorem filter_or (s : Finset α) : (s.filter fun a => p a ∨ q a) = s.filter p ∪ s.filter q :=
ext fun _ => by simp [mem_filter, mem_union, and_or_left]
theorem filter_and (s : Finset α) : (s.filter fun a => p a ∧ q a) = s.filter p ∩ s.filter q :=
ext fun _ => by simp [mem_filter, mem_inter, and_comm, and_left_comm, and_self_iff, and_assoc]
theorem filter_not (s : Finset α) : (s.filter fun a => ¬p a) = s \ s.filter p :=
ext fun a => by
simp only [Bool.decide_coe, Bool.not_eq_true', mem_filter, and_comm, mem_sdiff, not_and_or,
Bool.not_eq_true, and_or_left, and_not_self, or_false]
lemma filter_and_not (s : Finset α) (p q : α → Prop) [DecidablePred p] [DecidablePred q] :
s.filter (fun a ↦ p a ∧ ¬ q a) = s.filter p \ s.filter q := by
rw [filter_and, filter_not, ← inter_sdiff_assoc, inter_eq_left.2 (filter_subset _ _)]
theorem sdiff_eq_filter (s₁ s₂ : Finset α) : s₁ \ s₂ = filter (· ∉ s₂) s₁ :=
ext fun _ => by simp [mem_sdiff, mem_filter]
theorem subset_union_elim {s : Finset α} {t₁ t₂ : Set α} (h : ↑s ⊆ t₁ ∪ t₂) :
∃ s₁ s₂ : Finset α, s₁ ∪ s₂ = s ∧ ↑s₁ ⊆ t₁ ∧ ↑s₂ ⊆ t₂ \ t₁ := by
classical
refine ⟨s.filter (· ∈ t₁), s.filter (· ∉ t₁), ?_, ?_, ?_⟩
· simp [filter_union_right, em]
· intro x
simp
· intro x
simp only [not_not, coe_filter, Set.mem_setOf_eq, Set.mem_diff, and_imp]
intro hx hx₂
exact ⟨Or.resolve_left (h hx) hx₂, hx₂⟩
-- This is not a good simp lemma, as it would prevent `Finset.mem_filter` from firing
-- on, e.g. `x ∈ s.filter (Eq b)`.
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq'` with the equality the other way.
-/
theorem filter_eq [DecidableEq β] (s : Finset β) (b : β) :
s.filter (Eq b) = ite (b ∈ s) {b} ∅ := by
split_ifs with h
· ext
simp only [mem_filter, mem_singleton, decide_eq_true_eq]
refine ⟨fun h => h.2.symm, ?_⟩
rintro rfl
exact ⟨h, rfl⟩
· ext
simp only [mem_filter, not_and, iff_false, not_mem_empty, decide_eq_true_eq]
rintro m rfl
exact h m
/-- After filtering out everything that does not equal a given value, at most that value remains.
This is equivalent to `filter_eq` with the equality the other way.
-/
theorem filter_eq' [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => a = b) = ite (b ∈ s) {b} ∅ :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@eq_comm _ b]) (filter_eq s b)
theorem filter_ne [DecidableEq β] (s : Finset β) (b : β) :
(s.filter fun a => b ≠ a) = s.erase b := by
ext
simp only [mem_filter, mem_erase, Ne, decide_not, Bool.not_eq_true', decide_eq_false_iff_not]
tauto
theorem filter_ne' [DecidableEq β] (s : Finset β) (b : β) : (s.filter fun a => a ≠ b) = s.erase b :=
_root_.trans (filter_congr fun _ _ => by simp_rw [@ne_comm _ b]) (filter_ne s b)
theorem filter_union_filter_of_codisjoint (s : Finset α) (h : Codisjoint p q) :
s.filter p ∪ s.filter q = s :=
(filter_or _ _ _).symm.trans <| filter_true_of_mem fun x _ => h.top_le x trivial
theorem filter_union_filter_neg_eq [∀ x, Decidable (¬p x)] (s : Finset α) :
(s.filter p ∪ s.filter fun a => ¬p a) = s :=
filter_union_filter_of_codisjoint _ _ _ <| @codisjoint_hnot_right _ _ p
end
end Filter
/-! ### range -/
section Range
open Nat
variable {n m l : ℕ}
@[simp]
theorem range_filter_eq {n m : ℕ} : (range n).filter (· = m) = if m < n then {m} else ∅ := by
convert filter_eq (range n) m using 2
· ext
rw [eq_comm]
· simp
end Range
end Finset
/-! ### dedup on list and multiset -/
namespace Multiset
variable [DecidableEq α] {s t : Multiset α}
@[simp]
theorem toFinset_add (s t : Multiset α) : toFinset (s + t) = toFinset s ∪ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_inter (s t : Multiset α) : toFinset (s ∩ t) = toFinset s ∩ toFinset t :=
Finset.ext <| by simp
@[simp]
theorem toFinset_union (s t : Multiset α) : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by
ext; simp
@[simp]
theorem toFinset_eq_empty {m : Multiset α} : m.toFinset = ∅ ↔ m = 0 :=
Finset.val_inj.symm.trans Multiset.dedup_eq_zero
@[simp]
theorem toFinset_nonempty : s.toFinset.Nonempty ↔ s ≠ 0 := by
simp only [toFinset_eq_empty, Ne, Finset.nonempty_iff_ne_empty]
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty
@[simp]
theorem toFinset_filter (s : Multiset α) (p : α → Prop) [DecidablePred p] :
Multiset.toFinset (s.filter p) = s.toFinset.filter p := by
ext; simp
end Multiset
namespace List
variable [DecidableEq α] {l l' : List α} {a : α} {f : α → β}
{s : Finset α} {t : Set β} {t' : Finset β}
@[simp]
theorem toFinset_union (l l' : List α) : (l ∪ l').toFinset = l.toFinset ∪ l'.toFinset := by
ext
simp
@[simp]
theorem toFinset_inter (l l' : List α) : (l ∩ l').toFinset = l.toFinset ∩ l'.toFinset := by
ext
simp
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.toFinset_nonempty_of_ne⟩ := toFinset_nonempty_iff
@[simp]
theorem toFinset_filter (s : List α) (p : α → Bool) :
(s.filter p).toFinset = s.toFinset.filter (p ·) := by
ext; simp [List.mem_filter]
end List
namespace Finset
section ToList
@[simp]
theorem toList_eq_nil {s : Finset α} : s.toList = [] ↔ s = ∅ :=
Multiset.toList_eq_nil.trans val_eq_zero
theorem empty_toList {s : Finset α} : s.toList.isEmpty ↔ s = ∅ := by simp
@[simp]
theorem toList_empty : (∅ : Finset α).toList = [] :=
toList_eq_nil.mpr rfl
theorem Nonempty.toList_ne_nil {s : Finset α} (hs : s.Nonempty) : s.toList ≠ [] :=
mt toList_eq_nil.mp hs.ne_empty
theorem Nonempty.not_empty_toList {s : Finset α} (hs : s.Nonempty) : ¬s.toList.isEmpty :=
mt empty_toList.mp hs.ne_empty
end ToList
/-! ### choose -/
section Choose
variable (p : α → Prop) [DecidablePred p] (l : Finset α)
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the corresponding subtype. -/
def chooseX (hp : ∃! a, a ∈ l ∧ p a) : { a // a ∈ l ∧ p a } :=
Multiset.chooseX p l.val hp
/-- Given a finset `l` and a predicate `p`, associate to a proof that there is a unique element of
`l` satisfying `p` this unique element, as an element of the ambient type. -/
def choose (hp : ∃! a, a ∈ l ∧ p a) : α :=
chooseX p l hp
theorem choose_spec (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l ∧ p (choose p l hp) :=
(chooseX p l hp).property
theorem choose_mem (hp : ∃! a, a ∈ l ∧ p a) : choose p l hp ∈ l :=
(choose_spec _ _ _).1
theorem choose_property (hp : ∃! a, a ∈ l ∧ p a) : p (choose p l hp) :=
(choose_spec _ _ _).2
end Choose
end Finset
namespace Equiv
variable [DecidableEq α] {s t : Finset α}
open Finset
/-- The disjoint union of finsets is a sum -/
def Finset.union (s t : Finset α) (h : Disjoint s t) :
s ⊕ t ≃ (s ∪ t : Finset α) :=
Equiv.setCongr (coe_union _ _) |>.trans (Equiv.Set.union (disjoint_coe.mpr h)) |>.symm
@[simp]
theorem Finset.union_symm_inl (h : Disjoint s t) (x : s) :
Equiv.Finset.union s t h (Sum.inl x) = ⟨x, Finset.mem_union.mpr <| Or.inl x.2⟩ :=
rfl
@[simp]
theorem Finset.union_symm_inr (h : Disjoint s t) (y : t) :
Equiv.Finset.union s t h (Sum.inr y) = ⟨y, Finset.mem_union.mpr <| Or.inr y.2⟩ :=
rfl
/-- The type of dependent functions on the disjoint union of finsets `s ∪ t` is equivalent to the
type of pairs of functions on `s` and on `t`. This is similar to `Equiv.sumPiEquivProdPi`. -/
def piFinsetUnion {ι} [DecidableEq ι] (α : ι → Type*) {s t : Finset ι} (h : Disjoint s t) :
((∀ i : s, α i) × ∀ i : t, α i) ≃ ∀ i : (s ∪ t : Finset ι), α i :=
let e := Equiv.Finset.union s t h
sumPiEquivProdPi (fun b ↦ α (e b)) |>.symm.trans (.piCongrLeft (fun i : ↥(s ∪ t) ↦ α i) e)
/-- A finset is equivalent to its coercion as a set. -/
def _root_.Finset.equivToSet (s : Finset α) : s ≃ s.toSet where
toFun a := ⟨a.1, mem_coe.2 a.2⟩
invFun a := ⟨a.1, mem_coe.1 a.2⟩
left_inv := fun _ ↦ rfl
right_inv := fun _ ↦ rfl
end Equiv
namespace Multiset
variable [DecidableEq α]
@[simp]
lemma toFinset_replicate (n : ℕ) (a : α) :
(replicate n a).toFinset = if n = 0 then ∅ else {a} := by
ext x
simp only [mem_toFinset, Finset.mem_singleton, mem_replicate]
split_ifs with hn <;> simp [hn]
end Multiset
| Mathlib/Data/Finset/Basic.lean | 2,259 | 2,260 | |
/-
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 | 1,568 | 1,569 | |
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta
-/
import Mathlib.CategoryTheory.Sites.SheafOfTypes
import Mathlib.Order.Closure
/-!
# Closed sieves
A natural closure operator on sieves is a closure operator on `Sieve X` for each `X` which commutes
with pullback.
We show that a Grothendieck topology `J` induces a natural closure operator, and define what the
closed sieves are. The collection of `J`-closed sieves forms a presheaf which is a sheaf for `J`,
and further this presheaf can be used to determine the Grothendieck topology from the sheaf
predicate.
Finally we show that a natural closure operator on sieves induces a Grothendieck topology, and hence
that natural closure operators are in bijection with Grothendieck topologies.
## Main definitions
* `CategoryTheory.GrothendieckTopology.close`: Sends a sieve `S` on `X` to the set of arrows
which it covers. This has all the usual properties of a closure operator, as well as commuting
with pullback.
* `CategoryTheory.GrothendieckTopology.closureOperator`: The bundled `ClosureOperator` given
by `CategoryTheory.GrothendieckTopology.close`.
* `CategoryTheory.GrothendieckTopology.IsClosed`: A sieve `S` on `X` is closed for the topology `J`
if it contains every arrow it covers.
* `CategoryTheory.Functor.closedSieves`: The presheaf sending `X` to the collection of `J`-closed
sieves on `X`. This is additionally shown to be a sheaf for `J`, and if this is a sheaf for a
different topology `J'`, then `J' ≤ J`.
* `CategoryTheory.topologyOfClosureOperator`: A closure operator on the
set of sieves on every object which commutes with pullback additionally induces a Grothendieck
topology, giving a bijection with `CategoryTheory.GrothendieckTopology.closureOperator`.
## Tags
closed sieve, closure, Grothendieck topology
## References
* [S. MacLane, I. Moerdijk, *Sheaves in Geometry and Logic*][MM92]
-/
universe v u
namespace CategoryTheory
variable {C : Type u} [Category.{v} C]
variable (J₁ J₂ : GrothendieckTopology C)
namespace GrothendieckTopology
/-- The `J`-closure of a sieve is the collection of arrows which it covers. -/
@[simps]
def close {X : C} (S : Sieve X) : Sieve X where
arrows _ f := J₁.Covers S f
downward_closed hS := J₁.arrow_stable _ _ hS
/-- Any sieve is smaller than its closure. -/
theorem le_close {X : C} (S : Sieve X) : S ≤ J₁.close S :=
fun _ _ hg => J₁.covering_of_eq_top (S.pullback_eq_top_of_mem hg)
/-- A sieve is closed for the Grothendieck topology if it contains every arrow it covers.
In the case of the usual topology on a topological space, this means that the open cover contains
every open set which it covers.
Note this has no relation to a closed subset of a topological space.
-/
def IsClosed {X : C} (S : Sieve X) : Prop :=
∀ ⦃Y : C⦄ (f : Y ⟶ X), J₁.Covers S f → S f
/-- If `S` is `J₁`-closed, then `S` covers exactly the arrows it contains. -/
theorem covers_iff_mem_of_isClosed {X : C} {S : Sieve X} (h : J₁.IsClosed S) {Y : C} (f : Y ⟶ X) :
J₁.Covers S f ↔ S f :=
⟨h _, J₁.arrow_max _ _⟩
/-- Being `J`-closed is stable under pullback. -/
theorem isClosed_pullback {X Y : C} (f : Y ⟶ X) (S : Sieve X) :
J₁.IsClosed S → J₁.IsClosed (S.pullback f) :=
fun hS Z g hg => hS (g ≫ f) (by rwa [J₁.covers_iff, Sieve.pullback_comp])
/-- The closure of a sieve `S` is the largest closed sieve which contains `S` (justifying the name
"closure").
-/
theorem le_close_of_isClosed {X : C} {S T : Sieve X} (h : S ≤ T) (hT : J₁.IsClosed T) :
J₁.close S ≤ T :=
fun _ f hf => hT _ (J₁.superset_covering (Sieve.pullback_monotone f h) hf)
/-- The closure of a sieve is closed. -/
theorem close_isClosed {X : C} (S : Sieve X) : J₁.IsClosed (J₁.close S) :=
fun _ g hg => J₁.arrow_trans g _ S hg fun _ hS => hS
/-- A Grothendieck topology induces a natural family of closure operators on sieves. -/
@[simps! isClosed]
def closureOperator (X : C) : ClosureOperator (Sieve X) :=
.ofPred J₁.close J₁.IsClosed J₁.le_close J₁.close_isClosed fun _ _ ↦ J₁.le_close_of_isClosed
/-- The sieve `S` is closed iff its closure is equal to itself. -/
theorem isClosed_iff_close_eq_self {X : C} (S : Sieve X) : J₁.IsClosed S ↔ J₁.close S = S :=
(J₁.closureOperator _).isClosed_iff
theorem close_eq_self_of_isClosed {X : C} {S : Sieve X} (hS : J₁.IsClosed S) : J₁.close S = S :=
(J₁.isClosed_iff_close_eq_self S).1 hS
/-- Closing under `J` is stable under pullback. -/
theorem pullback_close {X Y : C} (f : Y ⟶ X) (S : Sieve X) :
J₁.close (S.pullback f) = (J₁.close S).pullback f := by
apply le_antisymm
· refine J₁.le_close_of_isClosed (Sieve.pullback_monotone _ (J₁.le_close S)) ?_
apply J₁.isClosed_pullback _ _ (J₁.close_isClosed _)
· intro Z g hg
change _ ∈ J₁ _
rw [← Sieve.pullback_comp]
apply hg
@[mono]
theorem monotone_close {X : C} : Monotone (J₁.close : Sieve X → Sieve X) :=
(J₁.closureOperator _).monotone
@[simp]
theorem close_close {X : C} (S : Sieve X) : J₁.close (J₁.close S) = J₁.close S :=
(J₁.closureOperator _).idempotent _
/--
The sieve `S` is in the topology iff its closure is the maximal sieve. This shows that the closure
operator determines the topology.
-/
theorem close_eq_top_iff_mem {X : C} (S : Sieve X) : J₁.close S = ⊤ ↔ S ∈ J₁ X := by
constructor
· intro h
apply J₁.transitive (J₁.top_mem X)
intro Y f hf
change J₁.close S f
rwa [h]
· intro hS
rw [eq_top_iff]
intro Y f _
apply J₁.pullback_stable _ hS
end GrothendieckTopology
/--
The presheaf sending each object to the set of `J`-closed sieves on it. This presheaf is a `J`-sheaf
(and will turn out to be a subobject classifier for the category of `J`-sheaves).
-/
@[simps]
def Functor.closedSieves : Cᵒᵖ ⥤ Type max v u where
obj X := { S : Sieve X.unop // J₁.IsClosed S }
map f S := ⟨S.1.pullback f.unop, J₁.isClosed_pullback f.unop _ S.2⟩
/-- The presheaf of `J`-closed sieves is a `J`-sheaf.
The proof of this is adapted from [MM92], Chapter III, Section 7, Lemma 1.
-/
theorem classifier_isSheaf : Presieve.IsSheaf J₁ (Functor.closedSieves J₁) := by
intro X S hS
rw [← Presieve.isSeparatedFor_and_exists_isAmalgamation_iff_isSheafFor]
refine ⟨?_, ?_⟩
· rintro x ⟨M, hM⟩ ⟨N, hN⟩ hM₂ hN₂
simp only [Functor.closedSieves_obj]
ext Y f
dsimp only [Subtype.coe_mk]
rw [← J₁.covers_iff_mem_of_isClosed hM, ← J₁.covers_iff_mem_of_isClosed hN]
have q : ∀ ⦃Z : C⦄ (g : Z ⟶ X) (_ : S g), M.pullback g = N.pullback g :=
fun Z g hg => congr_arg Subtype.val ((hM₂ g hg).trans (hN₂ g hg).symm)
have MSNS : M ⊓ S = N ⊓ S := by
ext Z g
rw [Sieve.inter_apply, Sieve.inter_apply]
simp only [and_comm]
apply and_congr_right
intro hg
rw [Sieve.mem_iff_pullback_eq_top, Sieve.mem_iff_pullback_eq_top, q g hg]
constructor
· intro hf
rw [J₁.covers_iff]
apply J₁.superset_covering (Sieve.pullback_monotone f inf_le_left)
rw [← MSNS]
apply J₁.arrow_intersect f M S hf (J₁.pullback_stable _ hS)
· intro hf
rw [J₁.covers_iff]
apply J₁.superset_covering (Sieve.pullback_monotone f inf_le_left)
rw [MSNS]
apply J₁.arrow_intersect f N S hf (J₁.pullback_stable _ hS)
· intro x hx
rw [Presieve.compatible_iff_sieveCompatible] at hx
let M := Sieve.bind S fun Y f hf => (x f hf).1
have : ∀ ⦃Y⦄ (f : Y ⟶ X) (hf : S f), M.pullback f = (x f hf).1 := by
intro Y f hf
apply le_antisymm
· rintro Z u ⟨W, g, f', hf', hg : (x f' hf').1 _, c⟩
rw [Sieve.mem_iff_pullback_eq_top,
← show (x (u ≫ f) _).1 = (x f hf).1.pullback u from congr_arg Subtype.val (hx f u hf)]
conv_lhs => congr; congr; rw [← c] -- Porting note: Originally `simp_rw [← c]`
rw [show (x (g ≫ f') _).1 = _ from congr_arg Subtype.val (hx f' g hf')]
apply Sieve.pullback_eq_top_of_mem _ hg
· apply Sieve.le_pullback_bind S fun Y f hf => (x f hf).1
refine ⟨⟨_, J₁.close_isClosed M⟩, ?_⟩
intro Y f hf
simp only [Functor.closedSieves_obj]
ext1
dsimp
rw [← J₁.pullback_close, this _ hf]
apply le_antisymm (J₁.le_close_of_isClosed le_rfl (x f hf).2) (J₁.le_close _)
/-- If presheaf of `J₁`-closed sieves is a `J₂`-sheaf then `J₁ ≤ J₂`. Note the converse is true by
`classifier_isSheaf` and `isSheaf_of_le`.
-/
theorem le_topology_of_closedSieves_isSheaf {J₁ J₂ : GrothendieckTopology C}
(h : Presieve.IsSheaf J₁ (Functor.closedSieves J₂)) : J₁ ≤ J₂ := by
intro X S hS
rw [← J₂.close_eq_top_iff_mem]
have : J₂.IsClosed (⊤ : Sieve X) := by
intro Y f _
trivial
suffices (⟨J₂.close S, J₂.close_isClosed S⟩ : Subtype _) = ⟨⊤, this⟩ by
rw [Subtype.ext_iff] at this
exact this
apply (h S hS).isSeparatedFor.ext
intro Y f hf
simp only [Functor.closedSieves_obj]
ext1
dsimp
rw [Sieve.pullback_top, ← J₂.pullback_close, S.pullback_eq_top_of_mem hf,
J₂.close_eq_top_iff_mem]
apply J₂.top_mem
/-- If being a sheaf for `J₁` is equivalent to being a sheaf for `J₂`, then `J₁ = J₂`. -/
theorem topology_eq_iff_same_sheaves {J₁ J₂ : GrothendieckTopology C} :
J₁ = J₂ ↔ ∀ P : Cᵒᵖ ⥤ Type max v u, Presieve.IsSheaf J₁ P ↔ Presieve.IsSheaf J₂ P := by
constructor
· rintro rfl
intro P
rfl
· intro h
apply le_antisymm
· apply le_topology_of_closedSieves_isSheaf
rw [h]
apply classifier_isSheaf
· apply le_topology_of_closedSieves_isSheaf
rw [← h]
apply classifier_isSheaf
/--
A closure (increasing, inflationary and idempotent) operation on sieves that commutes with pullback
induces a Grothendieck topology.
In fact, such operations are in bijection with Grothendieck topologies.
-/
@[simps]
def topologyOfClosureOperator (c : ∀ X : C, ClosureOperator (Sieve X))
(hc : ∀ ⦃X Y : C⦄ (f : Y ⟶ X) (S : Sieve X), c _ (S.pullback f) = (c _ S).pullback f) :
GrothendieckTopology C where
sieves X := { S | c X S = ⊤ }
top_mem' X := top_unique ((c X).le_closure _)
pullback_stable' X Y S f hS := by
rw [Set.mem_setOf_eq] at hS
rw [Set.mem_setOf_eq, hc, hS, Sieve.pullback_top]
transitive' X S hS R hR := by
rw [Set.mem_setOf_eq] at hS
rw [Set.mem_setOf_eq, ← (c X).idempotent, eq_top_iff, ← hS]
apply (c X).monotone fun Y f hf => _
intros Y f hf
rw [Sieve.mem_iff_pullback_eq_top, ← hc]
apply hR hf
/--
The topology given by the closure operator `J.close` on a Grothendieck topology is the same as `J`.
-/
theorem topologyOfClosureOperator_self :
(topologyOfClosureOperator J₁.closureOperator fun _ _ => J₁.pullback_close) = J₁ := by
ext X S
apply GrothendieckTopology.close_eq_top_iff_mem
theorem topologyOfClosureOperator_close (c : ∀ X : C, ClosureOperator (Sieve X))
(pb : ∀ ⦃X Y : C⦄ (f : Y ⟶ X) (S : Sieve X), c Y (S.pullback f) = (c X S).pullback f) (X : C)
(S : Sieve X) : (topologyOfClosureOperator c pb).close S = c X S := by
ext Y f
change c _ (Sieve.pullback f S) = ⊤ ↔ c _ S f
rw [pb, Sieve.mem_iff_pullback_eq_top]
end CategoryTheory
| Mathlib/CategoryTheory/Sites/Closed.lean | 294 | 297 | |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Chris Hughes
-/
import Mathlib.Algebra.Algebra.Defs
import Mathlib.Algebra.Polynomial.FieldDivision
import Mathlib.FieldTheory.Minpoly.Basic
import Mathlib.RingTheory.Adjoin.Basic
import Mathlib.RingTheory.FinitePresentation
import Mathlib.RingTheory.FiniteType
import Mathlib.RingTheory.Ideal.Quotient.Noetherian
import Mathlib.RingTheory.PowerBasis
import Mathlib.RingTheory.PrincipalIdealDomain
import Mathlib.RingTheory.Polynomial.Quotient
/-!
# Adjoining roots of polynomials
This file defines the commutative ring `AdjoinRoot f`, the ring R[X]/(f) obtained from a
commutative ring `R` and a polynomial `f : R[X]`. If furthermore `R` is a field and `f` is
irreducible, the field structure on `AdjoinRoot f` is constructed.
We suggest stating results on `IsAdjoinRoot` instead of `AdjoinRoot` to achieve higher
generality, since `IsAdjoinRoot` works for all different constructions of `R[α]`
including `AdjoinRoot f = R[X]/(f)` itself.
## Main definitions and results
The main definitions are in the `AdjoinRoot` namespace.
* `mk f : R[X] →+* AdjoinRoot f`, the natural ring homomorphism.
* `of f : R →+* AdjoinRoot f`, the natural ring homomorphism.
* `root f : AdjoinRoot f`, the image of X in R[X]/(f).
* `lift (i : R →+* S) (x : S) (h : f.eval₂ i x = 0) : (AdjoinRoot f) →+* S`, the ring
homomorphism from R[X]/(f) to S extending `i : R →+* S` and sending `X` to `x`.
* `lift_hom (x : S) (hfx : aeval x f = 0) : AdjoinRoot f →ₐ[R] S`, the algebra
homomorphism from R[X]/(f) to S extending `algebraMap R S` and sending `X` to `x`
* `equiv : (AdjoinRoot f →ₐ[F] E) ≃ {x // x ∈ f.aroots E}` a
bijection between algebra homomorphisms from `AdjoinRoot` and roots of `f` in `S`
-/
noncomputable section
open Polynomial
universe u v w
variable {R : Type u} {S : Type v} {K : Type w}
open Polynomial Ideal
/-- Adjoin a root of a polynomial `f` to a commutative ring `R`. We define the new ring
as the quotient of `R[X]` by the principal ideal generated by `f`. -/
def AdjoinRoot [CommRing R] (f : R[X]) : Type u :=
Polynomial R ⧸ (span {f} : Ideal R[X])
namespace AdjoinRoot
section CommRing
variable [CommRing R] (f : R[X])
instance instCommRing : CommRing (AdjoinRoot f) :=
Ideal.Quotient.commRing _
instance : Inhabited (AdjoinRoot f) :=
⟨0⟩
instance : DecidableEq (AdjoinRoot f) :=
Classical.decEq _
protected theorem nontrivial [IsDomain R] (h : degree f ≠ 0) : Nontrivial (AdjoinRoot f) :=
Ideal.Quotient.nontrivial
(by
simp_rw [Ne, span_singleton_eq_top, Polynomial.isUnit_iff, not_exists, not_and]
rintro x hx rfl
exact h (degree_C hx.ne_zero))
/-- Ring homomorphism from `R[x]` to `AdjoinRoot f` sending `X` to the `root`. -/
def mk : R[X] →+* AdjoinRoot f :=
Ideal.Quotient.mk _
@[elab_as_elim]
theorem induction_on {C : AdjoinRoot f → Prop} (x : AdjoinRoot f) (ih : ∀ p : R[X], C (mk f p)) :
C x :=
Quotient.inductionOn' x ih
/-- Embedding of the original ring `R` into `AdjoinRoot f`. -/
def of : R →+* AdjoinRoot f :=
(mk f).comp C
instance instSMulAdjoinRoot [DistribSMul S R] [IsScalarTower S R R] : SMul S (AdjoinRoot f) :=
Submodule.Quotient.instSMul' _
instance [DistribSMul S R] [IsScalarTower S R R] : DistribSMul S (AdjoinRoot f) :=
Submodule.Quotient.distribSMul' _
@[simp]
theorem smul_mk [DistribSMul S R] [IsScalarTower S R R] (a : S) (x : R[X]) :
a • mk f x = mk f (a • x) :=
rfl
theorem smul_of [DistribSMul S R] [IsScalarTower S R R] (a : S) (x : R) :
a • of f x = of f (a • x) := by rw [of, RingHom.comp_apply, RingHom.comp_apply, smul_mk, smul_C]
instance (R₁ R₂ : Type*) [SMul R₁ R₂] [DistribSMul R₁ R] [DistribSMul R₂ R] [IsScalarTower R₁ R R]
[IsScalarTower R₂ R R] [IsScalarTower R₁ R₂ R] (f : R[X]) :
IsScalarTower R₁ R₂ (AdjoinRoot f) :=
Submodule.Quotient.isScalarTower _ _
instance (R₁ R₂ : Type*) [DistribSMul R₁ R] [DistribSMul R₂ R] [IsScalarTower R₁ R R]
[IsScalarTower R₂ R R] [SMulCommClass R₁ R₂ R] (f : R[X]) :
SMulCommClass R₁ R₂ (AdjoinRoot f) :=
Submodule.Quotient.smulCommClass _ _
instance isScalarTower_right [DistribSMul S R] [IsScalarTower S R R] :
IsScalarTower S (AdjoinRoot f) (AdjoinRoot f) :=
Ideal.Quotient.isScalarTower_right
instance [Monoid S] [DistribMulAction S R] [IsScalarTower S R R] (f : R[X]) :
DistribMulAction S (AdjoinRoot f) :=
Submodule.Quotient.distribMulAction' _
/-- `R[x]/(f)` is `R`-algebra -/
@[stacks 09FX "second part"]
instance [CommSemiring S] [Algebra S R] : Algebra S (AdjoinRoot f) :=
Ideal.Quotient.algebra S
@[simp]
theorem algebraMap_eq : algebraMap R (AdjoinRoot f) = of f :=
rfl
variable (S) in
theorem algebraMap_eq' [CommSemiring S] [Algebra S R] :
algebraMap S (AdjoinRoot f) = (of f).comp (algebraMap S R) :=
rfl
theorem finiteType : Algebra.FiniteType R (AdjoinRoot f) :=
(Algebra.FiniteType.polynomial R).of_surjective _ (Ideal.Quotient.mkₐ_surjective R _)
theorem finitePresentation : Algebra.FinitePresentation R (AdjoinRoot f) :=
(Algebra.FinitePresentation.polynomial R).quotient (Submodule.fg_span_singleton f)
/-- The adjoined root. -/
def root : AdjoinRoot f :=
mk f X
variable {f}
instance hasCoeT : CoeTC R (AdjoinRoot f) :=
⟨of f⟩
/-- Two `R`-`AlgHom` from `AdjoinRoot f` to the same `R`-algebra are the same iff
they agree on `root f`. -/
@[ext]
theorem algHom_ext [Semiring S] [Algebra R S] {g₁ g₂ : AdjoinRoot f →ₐ[R] S}
(h : g₁ (root f) = g₂ (root f)) : g₁ = g₂ :=
Ideal.Quotient.algHom_ext R <| Polynomial.algHom_ext h
@[simp]
theorem mk_eq_mk {g h : R[X]} : mk f g = mk f h ↔ f ∣ g - h :=
Ideal.Quotient.eq.trans Ideal.mem_span_singleton
@[simp]
theorem mk_eq_zero {g : R[X]} : mk f g = 0 ↔ f ∣ g :=
mk_eq_mk.trans <| by rw [sub_zero]
@[simp]
theorem mk_self : mk f f = 0 :=
Quotient.sound' <| QuotientAddGroup.leftRel_apply.mpr (mem_span_singleton.2 <| by simp)
@[simp]
theorem mk_C (x : R) : mk f (C x) = x :=
rfl
@[simp]
theorem mk_X : mk f X = root f :=
rfl
theorem mk_ne_zero_of_degree_lt (hf : Monic f) {g : R[X]} (h0 : g ≠ 0) (hd : degree g < degree f) :
mk f g ≠ 0 :=
mk_eq_zero.not.2 <| hf.not_dvd_of_degree_lt h0 hd
theorem mk_ne_zero_of_natDegree_lt (hf : Monic f) {g : R[X]} (h0 : g ≠ 0)
(hd : natDegree g < natDegree f) : mk f g ≠ 0 :=
mk_eq_zero.not.2 <| hf.not_dvd_of_natDegree_lt h0 hd
@[simp]
theorem aeval_eq (p : R[X]) : aeval (root f) p = mk f p :=
Polynomial.induction_on p
(fun x => by
rw [aeval_C]
rfl)
(fun p q ihp ihq => by rw [map_add, RingHom.map_add, ihp, ihq]) fun n x _ => by
rw [map_mul, aeval_C, map_pow, aeval_X, RingHom.map_mul, mk_C, RingHom.map_pow, mk_X]
rfl
theorem adjoinRoot_eq_top : Algebra.adjoin R ({root f} : Set (AdjoinRoot f)) = ⊤ := by
refine Algebra.eq_top_iff.2 fun x => ?_
induction x using AdjoinRoot.induction_on with
| ih p => exact (Algebra.adjoin_singleton_eq_range_aeval R (root f)).symm ▸ ⟨p, aeval_eq p⟩
@[simp]
theorem eval₂_root (f : R[X]) : f.eval₂ (of f) (root f) = 0 := by
rw [← algebraMap_eq, ← aeval_def, aeval_eq, mk_self]
theorem isRoot_root (f : R[X]) : IsRoot (f.map (of f)) (root f) := by
rw [IsRoot, eval_map, eval₂_root]
theorem isAlgebraic_root (hf : f ≠ 0) : IsAlgebraic R (root f) :=
⟨f, hf, eval₂_root f⟩
theorem of.injective_of_degree_ne_zero [IsDomain R] (hf : f.degree ≠ 0) :
Function.Injective (AdjoinRoot.of f) := by
rw [injective_iff_map_eq_zero]
intro p hp
rw [AdjoinRoot.of, RingHom.comp_apply, AdjoinRoot.mk_eq_zero] at hp
by_cases h : f = 0
· exact C_eq_zero.mp (eq_zero_of_zero_dvd (by rwa [h] at hp))
· contrapose! hf with h_contra
rw [← degree_C h_contra]
apply le_antisymm (degree_le_of_dvd hp (by rwa [Ne, C_eq_zero])) _
rwa [degree_C h_contra, zero_le_degree_iff]
variable [CommRing S]
/-- Lift a ring homomorphism `i : R →+* S` to `AdjoinRoot f →+* S`. -/
def lift (i : R →+* S) (x : S) (h : f.eval₂ i x = 0) : AdjoinRoot f →+* S := by
apply Ideal.Quotient.lift _ (eval₂RingHom i x)
intro g H
rcases mem_span_singleton.1 H with ⟨y, hy⟩
rw [hy, RingHom.map_mul, coe_eval₂RingHom, h, zero_mul]
variable {i : R →+* S} {a : S} (h : f.eval₂ i a = 0)
@[simp]
theorem lift_mk (g : R[X]) : lift i a h (mk f g) = g.eval₂ i a :=
Ideal.Quotient.lift_mk _ _ _
@[simp]
theorem lift_root : lift i a h (root f) = a := by rw [root, lift_mk, eval₂_X]
@[simp]
theorem lift_of {x : R} : lift i a h x = i x := by rw [← mk_C x, lift_mk, eval₂_C]
@[simp]
theorem lift_comp_of : (lift i a h).comp (of f) = i :=
RingHom.ext fun _ => @lift_of _ _ _ _ _ _ _ h _
variable (f) [Algebra R S]
/-- Produce an algebra homomorphism `AdjoinRoot f →ₐ[R] S` sending `root f` to
a root of `f` in `S`. -/
def liftHom (x : S) (hfx : aeval x f = 0) : AdjoinRoot f →ₐ[R] S :=
{ lift (algebraMap R S) x hfx with
commutes' := fun r => show lift _ _ hfx r = _ from lift_of hfx }
@[simp]
theorem coe_liftHom (x : S) (hfx : aeval x f = 0) :
(liftHom f x hfx : AdjoinRoot f →+* S) = lift (algebraMap R S) x hfx :=
rfl
@[simp]
theorem aeval_algHom_eq_zero (ϕ : AdjoinRoot f →ₐ[R] S) : aeval (ϕ (root f)) f = 0 := by
have h : ϕ.toRingHom.comp (of f) = algebraMap R S := RingHom.ext_iff.mpr ϕ.commutes
rw [aeval_def, ← h, ← RingHom.map_zero ϕ.toRingHom, ← eval₂_root f, hom_eval₂]
rfl
@[simp]
theorem liftHom_eq_algHom (f : R[X]) (ϕ : AdjoinRoot f →ₐ[R] S) :
liftHom f (ϕ (root f)) (aeval_algHom_eq_zero f ϕ) = ϕ := by
suffices AlgHom.equalizer ϕ (liftHom f (ϕ (root f)) (aeval_algHom_eq_zero f ϕ)) = ⊤ by
exact (AlgHom.ext fun x => (SetLike.ext_iff.mp this x).mpr Algebra.mem_top).symm
rw [eq_top_iff, ← adjoinRoot_eq_top, Algebra.adjoin_le_iff, Set.singleton_subset_iff]
exact (@lift_root _ _ _ _ _ _ _ (aeval_algHom_eq_zero f ϕ)).symm
variable (hfx : aeval a f = 0)
@[simp]
theorem liftHom_mk {g : R[X]} : liftHom f a hfx (mk f g) = aeval a g :=
lift_mk hfx g
@[simp]
theorem liftHom_root : liftHom f a hfx (root f) = a :=
lift_root hfx
@[simp]
theorem liftHom_of {x : R} : liftHom f a hfx (of f x) = algebraMap _ _ x :=
lift_of hfx
section AdjoinInv
@[simp]
theorem root_isInv (r : R) : of _ r * root (C r * X - 1) = 1 := by
convert sub_eq_zero.1 ((eval₂_sub _).symm.trans <| eval₂_root <| C r * X - 1) <;>
simp only [eval₂_mul, eval₂_C, eval₂_X, eval₂_one]
theorem algHom_subsingleton {S : Type*} [CommRing S] [Algebra R S] {r : R} :
Subsingleton (AdjoinRoot (C r * X - 1) →ₐ[R] S) :=
⟨fun f g =>
algHom_ext
(@inv_unique _ _ (algebraMap R S r) _ _
(by rw [← f.commutes, ← map_mul, algebraMap_eq, root_isInv, map_one])
(by rw [← g.commutes, ← map_mul, algebraMap_eq, root_isInv, map_one]))⟩
end AdjoinInv
section Prime
variable {f}
theorem isDomain_of_prime (hf : Prime f) : IsDomain (AdjoinRoot f) :=
(Ideal.Quotient.isDomain_iff_prime (span {f} : Ideal R[X])).mpr <|
(Ideal.span_singleton_prime hf.ne_zero).mpr hf
|
theorem noZeroSMulDivisors_of_prime_of_degree_ne_zero [IsDomain R] (hf : Prime f)
(hf' : f.degree ≠ 0) : NoZeroSMulDivisors R (AdjoinRoot f) :=
haveI := isDomain_of_prime hf
NoZeroSMulDivisors.iff_algebraMap_injective.mpr (of.injective_of_degree_ne_zero hf')
| Mathlib/RingTheory/AdjoinRoot.lean | 322 | 327 |
/-
Copyright (c) 2021 Arthur Paulino. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Arthur Paulino, Kyle Miller
-/
import Mathlib.Combinatorics.SimpleGraph.Clique
import Mathlib.Data.ENat.Lattice
import Mathlib.Data.Nat.Lattice
import Mathlib.Data.Setoid.Partition
import Mathlib.Order.Antichain
import Mathlib.Data.Nat.Cast.Order.Ring
/-!
# Graph Coloring
This module defines colorings of simple graphs (also known as proper colorings in the literature).
A graph coloring is the attribution of "colors" to all of its vertices such that adjacent vertices
have different colors.
A coloring can be represented as a homomorphism into a complete graph, whose vertices represent
the colors.
## Main definitions
* `G.Coloring α` is the type of `α`-colorings of a simple graph `G`,
with `α` being the set of available colors. The type is defined to
be homomorphisms from `G` into the complete graph on `α`, and
colorings have a coercion to `V → α`.
* `G.Colorable n` is the proposition that `G` is `n`-colorable, which
is whether there exists a coloring with at most *n* colors.
* `G.chromaticNumber` is the minimal `n` such that `G` is `n`-colorable,
or `⊤` if it cannot be colored with finitely many colors.
(Cardinal-valued chromatic numbers are more niche, so we stick to `ℕ∞`.)
We write `G.chromaticNumber ≠ ⊤` to mean a graph is colorable with finitely many colors.
* `C.colorClass c` is the set of vertices colored by `c : α` in the coloring `C : G.Coloring α`.
* `C.colorClasses` is the set containing all color classes.
## TODO
* Gather material from:
* https://github.com/leanprover-community/mathlib/blob/simple_graph_matching/src/combinatorics/simple_graph/coloring.lean
* https://github.com/kmill/lean-graphcoloring/blob/master/src/graph.lean
* Trees
* Planar graphs
* Chromatic polynomials
* develop API for partial colorings, likely as colorings of subgraphs (`H.coe.Coloring α`)
-/
assert_not_exists Field
open Fintype Function
universe u v
namespace SimpleGraph
variable {V : Type u} (G : SimpleGraph V) {n : ℕ}
/-- An `α`-coloring of a simple graph `G` is a homomorphism of `G` into the complete graph on `α`.
This is also known as a proper coloring.
-/
abbrev Coloring (α : Type v) := G →g (⊤ : SimpleGraph α)
variable {G}
variable {α β : Type*} (C : G.Coloring α)
theorem Coloring.valid {v w : V} (h : G.Adj v w) : C v ≠ C w :=
C.map_rel h
/-- Construct a term of `SimpleGraph.Coloring` using a function that
assigns vertices to colors and a proof that it is as proper coloring.
(Note: this is a definitionally the constructor for `SimpleGraph.Hom`,
but with a syntactically better proper coloring hypothesis.)
-/
@[match_pattern]
def Coloring.mk (color : V → α) (valid : ∀ {v w : V}, G.Adj v w → color v ≠ color w) :
G.Coloring α :=
⟨color, @valid⟩
/-- The color class of a given color.
-/
def Coloring.colorClass (c : α) : Set V := { v : V | C v = c }
/-- The set containing all color classes. -/
def Coloring.colorClasses : Set (Set V) := (Setoid.ker C).classes
theorem Coloring.mem_colorClass (v : V) : v ∈ C.colorClass (C v) := rfl
theorem Coloring.colorClasses_isPartition : Setoid.IsPartition C.colorClasses :=
Setoid.isPartition_classes (Setoid.ker C)
theorem Coloring.mem_colorClasses {v : V} : C.colorClass (C v) ∈ C.colorClasses :=
⟨v, rfl⟩
theorem Coloring.colorClasses_finite [Finite α] : C.colorClasses.Finite :=
Setoid.finite_classes_ker _
theorem Coloring.card_colorClasses_le [Fintype α] [Fintype C.colorClasses] :
Fintype.card C.colorClasses ≤ Fintype.card α := by
simp only [colorClasses]
convert Setoid.card_classes_ker_le C
theorem Coloring.not_adj_of_mem_colorClass {c : α} {v w : V} (hv : v ∈ C.colorClass c)
(hw : w ∈ C.colorClass c) : ¬G.Adj v w := fun h => C.valid h (Eq.trans hv (Eq.symm hw))
theorem Coloring.color_classes_independent (c : α) : IsAntichain G.Adj (C.colorClass c) :=
fun _ hv _ hw _ => C.not_adj_of_mem_colorClass hv hw
-- TODO make this computable
noncomputable instance [Fintype V] [Fintype α] : Fintype (Coloring G α) := by
classical
change Fintype (RelHom G.Adj (⊤ : SimpleGraph α).Adj)
apply Fintype.ofInjective _ RelHom.coe_fn_injective
variable (G)
/-- Whether a graph can be colored by at most `n` colors. -/
def Colorable (n : ℕ) : Prop := Nonempty (G.Coloring (Fin n))
/-- The coloring of an empty graph. -/
def coloringOfIsEmpty [IsEmpty V] : G.Coloring α :=
Coloring.mk isEmptyElim fun {v} => isEmptyElim v
theorem colorable_of_isEmpty [IsEmpty V] (n : ℕ) : G.Colorable n :=
⟨G.coloringOfIsEmpty⟩
theorem isEmpty_of_colorable_zero (h : G.Colorable 0) : IsEmpty V := by
constructor
intro v
obtain ⟨i, hi⟩ := h.some v
exact Nat.not_lt_zero _ hi
@[simp]
lemma colorable_zero_iff : G.Colorable 0 ↔ IsEmpty V :=
⟨G.isEmpty_of_colorable_zero, fun _ ↦ G.colorable_of_isEmpty 0⟩
/-- The "tautological" coloring of a graph, using the vertices of the graph as colors. -/
def selfColoring : G.Coloring V := Coloring.mk id fun {_ _} => G.ne_of_adj
/-- The chromatic number of a graph is the minimal number of colors needed to color it.
This is `⊤` (infinity) iff `G` isn't colorable with finitely many colors.
If `G` is colorable, then `ENat.toNat G.chromaticNumber` is the `ℕ`-valued chromatic number. -/
noncomputable def chromaticNumber : ℕ∞ := ⨅ n ∈ setOf G.Colorable, (n : ℕ∞)
lemma chromaticNumber_eq_biInf {G : SimpleGraph V} :
G.chromaticNumber = ⨅ n ∈ setOf G.Colorable, (n : ℕ∞) := rfl
lemma chromaticNumber_eq_iInf {G : SimpleGraph V} :
G.chromaticNumber = ⨅ n : {m | G.Colorable m}, (n : ℕ∞) := by
rw [chromaticNumber, iInf_subtype]
lemma Colorable.chromaticNumber_eq_sInf {G : SimpleGraph V} {n} (h : G.Colorable n) :
G.chromaticNumber = sInf {n' : ℕ | G.Colorable n'} := by
rw [ENat.coe_sInf, chromaticNumber]
exact ⟨_, h⟩
/-- Given an embedding, there is an induced embedding of colorings. -/
def recolorOfEmbedding {α β : Type*} (f : α ↪ β) : G.Coloring α ↪ G.Coloring β where
toFun C := (Embedding.completeGraph f).toHom.comp C
inj' := by -- this was strangely painful; seems like missing lemmas about embeddings
intro C C' h
dsimp only at h
ext v
apply (Embedding.completeGraph f).inj'
change ((Embedding.completeGraph f).toHom.comp C) v = _
rw [h]
rfl
@[simp] lemma coe_recolorOfEmbedding (f : α ↪ β) :
⇑(G.recolorOfEmbedding f) = (Embedding.completeGraph f).toHom.comp := rfl
/-- Given an equivalence, there is an induced equivalence between colorings. -/
def recolorOfEquiv {α β : Type*} (f : α ≃ β) : G.Coloring α ≃ G.Coloring β where
toFun := G.recolorOfEmbedding f.toEmbedding
invFun := G.recolorOfEmbedding f.symm.toEmbedding
left_inv C := by
ext v
apply Equiv.symm_apply_apply
right_inv C := by
ext v
apply Equiv.apply_symm_apply
@[simp] lemma coe_recolorOfEquiv (f : α ≃ β) :
⇑(G.recolorOfEquiv f) = (Embedding.completeGraph f).toHom.comp := rfl
/-- There is a noncomputable embedding of `α`-colorings to `β`-colorings if
`β` has at least as large a cardinality as `α`. -/
noncomputable def recolorOfCardLE {α β : Type*} [Fintype α] [Fintype β]
(hn : Fintype.card α ≤ Fintype.card β) : G.Coloring α ↪ G.Coloring β :=
G.recolorOfEmbedding <| (Function.Embedding.nonempty_of_card_le hn).some
@[simp] lemma coe_recolorOfCardLE [Fintype α] [Fintype β] (hαβ : card α ≤ card β) :
⇑(G.recolorOfCardLE hαβ) =
(Embedding.completeGraph (Embedding.nonempty_of_card_le hαβ).some).toHom.comp := rfl
variable {G}
theorem Colorable.mono {n m : ℕ} (h : n ≤ m) (hc : G.Colorable n) : G.Colorable m :=
⟨G.recolorOfCardLE (by simp [h]) hc.some⟩
theorem Coloring.colorable [Fintype α] (C : G.Coloring α) : G.Colorable (Fintype.card α) :=
⟨G.recolorOfCardLE (by simp) C⟩
theorem colorable_of_fintype (G : SimpleGraph V) [Fintype V] : G.Colorable (Fintype.card V) :=
G.selfColoring.colorable
/-- Noncomputably get a coloring from colorability. -/
noncomputable def Colorable.toColoring [Fintype α] {n : ℕ} (hc : G.Colorable n)
(hn : n ≤ Fintype.card α) : G.Coloring α := by
rw [← Fintype.card_fin n] at hn
exact G.recolorOfCardLE hn hc.some
theorem Colorable.of_embedding {V' : Type*} {G' : SimpleGraph V'} (f : G ↪g G') {n : ℕ}
(h : G'.Colorable n) : G.Colorable n :=
⟨(h.toColoring (by simp)).comp f⟩
theorem colorable_iff_exists_bdd_nat_coloring (n : ℕ) :
G.Colorable n ↔ ∃ C : G.Coloring ℕ, ∀ v, C v < n := by
constructor
· rintro hc
have C : G.Coloring (Fin n) := hc.toColoring (by simp)
let f := Embedding.completeGraph (@Fin.valEmbedding n)
use f.toHom.comp C
intro v
exact Fin.is_lt (C.1 v)
· rintro ⟨C, Cf⟩
refine ⟨Coloring.mk ?_ ?_⟩
· exact fun v => ⟨C v, Cf v⟩
· rintro v w hvw
simp only [Fin.mk_eq_mk, Ne]
exact C.valid hvw
theorem colorable_set_nonempty_of_colorable {n : ℕ} (hc : G.Colorable n) :
{ n : ℕ | G.Colorable n }.Nonempty :=
⟨n, hc⟩
theorem chromaticNumber_bddBelow : BddBelow { n : ℕ | G.Colorable n } :=
⟨0, fun _ _ => zero_le _⟩
theorem Colorable.chromaticNumber_le {n : ℕ} (hc : G.Colorable n) : G.chromaticNumber ≤ n := by
rw [hc.chromaticNumber_eq_sInf]
norm_cast
apply csInf_le chromaticNumber_bddBelow
exact hc
theorem chromaticNumber_ne_top_iff_exists : G.chromaticNumber ≠ ⊤ ↔ ∃ n, G.Colorable n := by
rw [chromaticNumber]
convert_to ⨅ n : {m | G.Colorable m}, (n : ℕ∞) ≠ ⊤ ↔ _
· rw [iInf_subtype]
rw [← lt_top_iff_ne_top, ENat.iInf_coe_lt_top]
simp
theorem chromaticNumber_le_iff_colorable {n : ℕ} : G.chromaticNumber ≤ n ↔ G.Colorable n := by
refine ⟨fun h ↦ ?_, Colorable.chromaticNumber_le⟩
have : G.chromaticNumber ≠ ⊤ := (trans h (WithTop.coe_lt_top n)).ne
rw [chromaticNumber_ne_top_iff_exists] at this
obtain ⟨m, hm⟩ := this
rw [hm.chromaticNumber_eq_sInf, Nat.cast_le] at h
have := Nat.sInf_mem (⟨m, hm⟩ : {n' | G.Colorable n'}.Nonempty)
rw [Set.mem_setOf_eq] at this
exact this.mono h
theorem colorable_chromaticNumber {m : ℕ} (hc : G.Colorable m) :
G.Colorable (ENat.toNat G.chromaticNumber) := by
classical
rw [hc.chromaticNumber_eq_sInf, Nat.sInf_def]
· apply Nat.find_spec
· exact colorable_set_nonempty_of_colorable hc
theorem colorable_chromaticNumber_of_fintype (G : SimpleGraph V) [Finite V] :
G.Colorable (ENat.toNat G.chromaticNumber) := by
cases nonempty_fintype V
exact colorable_chromaticNumber G.colorable_of_fintype
theorem chromaticNumber_le_one_of_subsingleton (G : SimpleGraph V) [Subsingleton V] :
G.chromaticNumber ≤ 1 := by
rw [← Nat.cast_one, chromaticNumber_le_iff_colorable]
refine ⟨Coloring.mk (fun _ => 0) ?_⟩
intros v w
cases Subsingleton.elim v w
simp
theorem chromaticNumber_eq_zero_of_isempty (G : SimpleGraph V) [IsEmpty V] :
G.chromaticNumber = 0 := by
rw [← nonpos_iff_eq_zero, ← Nat.cast_zero, chromaticNumber_le_iff_colorable]
apply colorable_of_isEmpty
theorem isEmpty_of_chromaticNumber_eq_zero (G : SimpleGraph V) [Finite V]
(h : G.chromaticNumber = 0) : IsEmpty V := by
have h' := G.colorable_chromaticNumber_of_fintype
rw [h] at h'
exact G.isEmpty_of_colorable_zero h'
theorem chromaticNumber_pos [Nonempty V] {n : ℕ} (hc : G.Colorable n) : 0 < G.chromaticNumber := by
rw [hc.chromaticNumber_eq_sInf, Nat.cast_pos]
apply le_csInf (colorable_set_nonempty_of_colorable hc)
intro m hm
by_contra h'
simp only [not_le] at h'
obtain ⟨i, hi⟩ := hm.some (Classical.arbitrary V)
have h₁ : i < 0 := lt_of_lt_of_le hi (Nat.le_of_lt_succ h')
exact Nat.not_lt_zero _ h₁
theorem colorable_of_chromaticNumber_ne_top (h : G.chromaticNumber ≠ ⊤) :
G.Colorable (ENat.toNat G.chromaticNumber) := by
rw [chromaticNumber_ne_top_iff_exists] at h
obtain ⟨n, hn⟩ := h
exact colorable_chromaticNumber hn
theorem Colorable.mono_left {G' : SimpleGraph V} (h : G ≤ G') {n : ℕ} (hc : G'.Colorable n) :
G.Colorable n :=
⟨hc.some.comp (.ofLE h)⟩
theorem chromaticNumber_le_of_forall_imp {V' : Type*} {G' : SimpleGraph V'}
(h : ∀ n, G'.Colorable n → G.Colorable n) :
G.chromaticNumber ≤ G'.chromaticNumber := by
rw [chromaticNumber, chromaticNumber]
simp only [Set.mem_setOf_eq, le_iInf_iff]
intro m hc
have := h _ hc
rw [← chromaticNumber_le_iff_colorable] at this
exact this
theorem chromaticNumber_mono (G' : SimpleGraph V)
(h : G ≤ G') : G.chromaticNumber ≤ G'.chromaticNumber :=
chromaticNumber_le_of_forall_imp fun _ => Colorable.mono_left h
theorem chromaticNumber_mono_of_embedding {V' : Type*} {G' : SimpleGraph V'}
(f : G ↪g G') : G.chromaticNumber ≤ G'.chromaticNumber :=
chromaticNumber_le_of_forall_imp fun _ => Colorable.of_embedding f
lemma card_le_chromaticNumber_iff_forall_surjective [Fintype α] :
card α ≤ G.chromaticNumber ↔ ∀ C : G.Coloring α, Surjective C := by
| refine ⟨fun h C ↦ ?_, fun h ↦ ?_⟩
· rw [C.colorable.chromaticNumber_eq_sInf, Nat.cast_le] at h
intro i
by_contra! hi
let D : G.Coloring {a // a ≠ i} := ⟨fun v ↦ ⟨C v, hi v⟩, (C.valid · <| congr_arg Subtype.val ·)⟩
classical
exact Nat.not_mem_of_lt_sInf ((Nat.sub_one_lt_of_lt <| card_pos_iff.2 ⟨i⟩).trans_le h)
⟨G.recolorOfEquiv (equivOfCardEq <| by simp [Nat.pred_eq_sub_one]) D⟩
· simp only [chromaticNumber, Set.mem_setOf_eq, le_iInf_iff, Nat.cast_le, exists_prop]
| Mathlib/Combinatorics/SimpleGraph/Coloring.lean | 342 | 350 |
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Algebra.BigOperators.Group.Finset.Indicator
import Mathlib.Algebra.Module.BigOperators
import Mathlib.LinearAlgebra.AffineSpace.AffineSubspace.Basic
import Mathlib.LinearAlgebra.Finsupp.LinearCombination
import Mathlib.Tactic.FinCases
/-!
# Affine combinations of points
This file defines affine combinations of points.
## Main definitions
* `weightedVSubOfPoint` is a general weighted combination of
subtractions with an explicit base point, yielding a vector.
* `weightedVSub` uses an arbitrary choice of base point and is intended
to be used when the sum of weights is 0, in which case the result is
independent of the choice of base point.
* `affineCombination` adds the weighted combination to the arbitrary
base point, yielding a point rather than a vector, and is intended
to be used when the sum of weights is 1, in which case the result is
independent of the choice of base point.
These definitions are for sums over a `Finset`; versions for a
`Fintype` may be obtained using `Finset.univ`, while versions for a
`Finsupp` may be obtained using `Finsupp.support`.
## References
* https://en.wikipedia.org/wiki/Affine_space
-/
noncomputable section
open Affine
namespace Finset
theorem univ_fin2 : (univ : Finset (Fin 2)) = {0, 1} := by
ext x
fin_cases x <;> simp
variable {k : Type*} {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
variable [S : AffineSpace V P]
variable {ι : Type*} (s : Finset ι)
variable {ι₂ : Type*} (s₂ : Finset ι₂)
/-- A weighted sum of the results of subtracting a base point from the
given points, as a linear map on the weights. The main cases of
interest are where the sum of the weights is 0, in which case the sum
is independent of the choice of base point, and where the sum of the
weights is 1, in which case the sum added to the base point is
independent of the choice of base point. -/
def weightedVSubOfPoint (p : ι → P) (b : P) : (ι → k) →ₗ[k] V :=
∑ i ∈ s, (LinearMap.proj i : (ι → k) →ₗ[k] k).smulRight (p i -ᵥ b)
@[simp]
theorem weightedVSubOfPoint_apply (w : ι → k) (p : ι → P) (b : P) :
s.weightedVSubOfPoint p b w = ∑ i ∈ s, w i • (p i -ᵥ b) := by
simp [weightedVSubOfPoint, LinearMap.sum_apply]
/-- The value of `weightedVSubOfPoint`, where the given points are equal. -/
@[simp (high)]
theorem weightedVSubOfPoint_apply_const (w : ι → k) (p : P) (b : P) :
s.weightedVSubOfPoint (fun _ => p) b w = (∑ i ∈ s, w i) • (p -ᵥ b) := by
rw [weightedVSubOfPoint_apply, sum_smul]
lemma weightedVSubOfPoint_vadd (s : Finset ι) (w : ι → k) (p : ι → P) (b : P) (v : V) :
s.weightedVSubOfPoint (v +ᵥ p) b w = s.weightedVSubOfPoint p (-v +ᵥ b) w := by
simp [vadd_vsub_assoc, vsub_vadd_eq_vsub_sub, add_comm]
lemma weightedVSubOfPoint_smul {G : Type*} [Group G] [DistribMulAction G V] [SMulCommClass G k V]
(s : Finset ι) (w : ι → k) (p : ι → V) (b : V) (a : G) :
s.weightedVSubOfPoint (a • p) b w = a • s.weightedVSubOfPoint p (a⁻¹ • b) w := by
simp [smul_sum, smul_sub, smul_comm a (w _)]
/-- `weightedVSubOfPoint` gives equal results for two families of weights and two families of
points that are equal on `s`. -/
theorem weightedVSubOfPoint_congr {w₁ w₂ : ι → k} (hw : ∀ i ∈ s, w₁ i = w₂ i) {p₁ p₂ : ι → P}
(hp : ∀ i ∈ s, p₁ i = p₂ i) (b : P) :
s.weightedVSubOfPoint p₁ b w₁ = s.weightedVSubOfPoint p₂ b w₂ := by
simp_rw [weightedVSubOfPoint_apply]
refine sum_congr rfl fun i hi => ?_
rw [hw i hi, hp i hi]
/-- Given a family of points, if we use a member of the family as a base point, the
`weightedVSubOfPoint` does not depend on the value of the weights at this point. -/
theorem weightedVSubOfPoint_eq_of_weights_eq (p : ι → P) (j : ι) (w₁ w₂ : ι → k)
(hw : ∀ i, i ≠ j → w₁ i = w₂ i) :
s.weightedVSubOfPoint p (p j) w₁ = s.weightedVSubOfPoint p (p j) w₂ := by
simp only [Finset.weightedVSubOfPoint_apply]
congr
ext i
rcases eq_or_ne i j with h | h
· simp [h]
· simp [hw i h]
/-- The weighted sum is independent of the base point when the sum of
the weights is 0. -/
theorem weightedVSubOfPoint_eq_of_sum_eq_zero (w : ι → k) (p : ι → P) (h : ∑ i ∈ s, w i = 0)
(b₁ b₂ : P) : s.weightedVSubOfPoint p b₁ w = s.weightedVSubOfPoint p b₂ w := by
apply eq_of_sub_eq_zero
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply, ← sum_sub_distrib]
conv_lhs =>
congr
· skip
· ext
rw [← smul_sub, vsub_sub_vsub_cancel_left]
rw [← sum_smul, h, zero_smul]
/-- The weighted sum, added to the base point, is independent of the
base point when the sum of the weights is 1. -/
theorem weightedVSubOfPoint_vadd_eq_of_sum_eq_one (w : ι → k) (p : ι → P) (h : ∑ i ∈ s, w i = 1)
(b₁ b₂ : P) : s.weightedVSubOfPoint p b₁ w +ᵥ b₁ = s.weightedVSubOfPoint p b₂ w +ᵥ b₂ := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply, ← @vsub_eq_zero_iff_eq V,
vadd_vsub_assoc, vsub_vadd_eq_vsub_sub, ← add_sub_assoc, add_comm, add_sub_assoc, ←
sum_sub_distrib]
conv_lhs =>
congr
· skip
· congr
· skip
· ext
rw [← smul_sub, vsub_sub_vsub_cancel_left]
rw [← sum_smul, h, one_smul, vsub_add_vsub_cancel, vsub_self]
/-- The weighted sum is unaffected by removing the base point, if
present, from the set of points. -/
@[simp (high)]
theorem weightedVSubOfPoint_erase [DecidableEq ι] (w : ι → k) (p : ι → P) (i : ι) :
(s.erase i).weightedVSubOfPoint p (p i) w = s.weightedVSubOfPoint p (p i) w := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply]
apply sum_erase
rw [vsub_self, smul_zero]
/-- The weighted sum is unaffected by adding the base point, whether
or not present, to the set of points. -/
@[simp (high)]
theorem weightedVSubOfPoint_insert [DecidableEq ι] (w : ι → k) (p : ι → P) (i : ι) :
(insert i s).weightedVSubOfPoint p (p i) w = s.weightedVSubOfPoint p (p i) w := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply]
apply sum_insert_zero
rw [vsub_self, smul_zero]
/-- The weighted sum is unaffected by changing the weights to the
corresponding indicator function and adding points to the set. -/
theorem weightedVSubOfPoint_indicator_subset (w : ι → k) (p : ι → P) (b : P) {s₁ s₂ : Finset ι}
(h : s₁ ⊆ s₂) :
s₁.weightedVSubOfPoint p b w = s₂.weightedVSubOfPoint p b (Set.indicator (↑s₁) w) := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply]
exact Eq.symm <|
sum_indicator_subset_of_eq_zero w (fun i wi => wi • (p i -ᵥ b : V)) h fun i => zero_smul k _
/-- A weighted sum, over the image of an embedding, equals a weighted
sum with the same points and weights over the original
`Finset`. -/
theorem weightedVSubOfPoint_map (e : ι₂ ↪ ι) (w : ι → k) (p : ι → P) (b : P) :
(s₂.map e).weightedVSubOfPoint p b w = s₂.weightedVSubOfPoint (p ∘ e) b (w ∘ e) := by
simp_rw [weightedVSubOfPoint_apply]
exact Finset.sum_map _ _ _
/-- A weighted sum of pairwise subtractions, expressed as a subtraction of two
`weightedVSubOfPoint` expressions. -/
theorem sum_smul_vsub_eq_weightedVSubOfPoint_sub (w : ι → k) (p₁ p₂ : ι → P) (b : P) :
(∑ i ∈ s, w i • (p₁ i -ᵥ p₂ i)) =
s.weightedVSubOfPoint p₁ b w - s.weightedVSubOfPoint p₂ b w := by
simp_rw [weightedVSubOfPoint_apply, ← sum_sub_distrib, ← smul_sub, vsub_sub_vsub_cancel_right]
/-- A weighted sum of pairwise subtractions, where the point on the right is constant,
expressed as a subtraction involving a `weightedVSubOfPoint` expression. -/
theorem sum_smul_vsub_const_eq_weightedVSubOfPoint_sub (w : ι → k) (p₁ : ι → P) (p₂ b : P) :
(∑ i ∈ s, w i • (p₁ i -ᵥ p₂)) = s.weightedVSubOfPoint p₁ b w - (∑ i ∈ s, w i) • (p₂ -ᵥ b) := by
rw [sum_smul_vsub_eq_weightedVSubOfPoint_sub, weightedVSubOfPoint_apply_const]
/-- A weighted sum of pairwise subtractions, where the point on the left is constant,
expressed as a subtraction involving a `weightedVSubOfPoint` expression. -/
theorem sum_smul_const_vsub_eq_sub_weightedVSubOfPoint (w : ι → k) (p₂ : ι → P) (p₁ b : P) :
| (∑ i ∈ s, w i • (p₁ -ᵥ p₂ i)) = (∑ i ∈ s, w i) • (p₁ -ᵥ b) - s.weightedVSubOfPoint p₂ b w := by
rw [sum_smul_vsub_eq_weightedVSubOfPoint_sub, weightedVSubOfPoint_apply_const]
| Mathlib/LinearAlgebra/AffineSpace/Combination.lean | 187 | 189 |
/-
Copyright (c) 2020 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Joël Riou
-/
import Mathlib.CategoryTheory.ConcreteCategory.Basic
import Mathlib.CategoryTheory.Shift.Basic
import Mathlib.Data.Set.Subsingleton
import Mathlib.Algebra.Group.Int.Defs
/-!
# The category of graded objects
For any type `β`, a `β`-graded object over some category `C` is just
a function `β → C` into the objects of `C`.
We put the "pointwise" category structure on these, as the non-dependent specialization of
`CategoryTheory.Pi`.
We describe the `comap` functors obtained by precomposing with functions `β → γ`.
As a consequence a fixed element (e.g. `1`) in an additive group `β` provides a shift
functor on `β`-graded objects
When `C` has coproducts we construct the `total` functor `GradedObject β C ⥤ C`,
show that it is faithful, and deduce that when `C` is concrete so is `GradedObject β C`.
A covariant functoriality of `GradedObject β C` with respect to the index set `β` is also
introduced: if `p : I → J` is a map such that `C` has coproducts indexed by `p ⁻¹' {j}`, we
have a functor `map : GradedObject I C ⥤ GradedObject J C`.
-/
namespace CategoryTheory
open Category Limits
universe w v u
/-- A type synonym for `β → C`, used for `β`-graded objects in a category `C`. -/
def GradedObject (β : Type w) (C : Type u) : Type max w u :=
β → C
-- Satisfying the inhabited linter...
instance inhabitedGradedObject (β : Type w) (C : Type u) [Inhabited C] :
Inhabited (GradedObject β C) :=
⟨fun _ => Inhabited.default⟩
-- `s` is here to distinguish type synonyms asking for different shifts
/-- A type synonym for `β → C`, used for `β`-graded objects in a category `C`
with a shift functor given by translation by `s`.
-/
@[nolint unusedArguments]
abbrev GradedObjectWithShift {β : Type w} [AddCommGroup β] (_ : β) (C : Type u) : Type max w u :=
GradedObject β C
namespace GradedObject
variable {C : Type u} [Category.{v} C]
@[simps!]
instance categoryOfGradedObjects (β : Type w) : Category.{max w v} (GradedObject β C) :=
CategoryTheory.pi fun _ => C
@[ext]
lemma hom_ext {β : Type*} {X Y : GradedObject β C} (f g : X ⟶ Y) (h : ∀ x, f x = g x) : f = g := by
funext
apply h
/-- The projection of a graded object to its `i`-th component. -/
@[simps]
def eval {β : Type w} (b : β) : GradedObject β C ⥤ C where
obj X := X b
map f := f b
section
variable {β : Type*} (X Y : GradedObject β C)
/-- Constructor for isomorphisms in `GradedObject` -/
@[simps]
def isoMk (e : ∀ i, X i ≅ Y i) : X ≅ Y where
hom i := (e i).hom
inv i := (e i).inv
variable {X Y}
-- this lemma is not an instance as it may create a loop with `isIso_apply_of_isIso`
lemma isIso_of_isIso_apply (f : X ⟶ Y) [hf : ∀ i, IsIso (f i)] :
IsIso f := by
change IsIso (isoMk X Y (fun i => asIso (f i))).hom
infer_instance
instance isIso_apply_of_isIso (f : X ⟶ Y) [IsIso f] (i : β) : IsIso (f i) := by
change IsIso ((eval i).map f)
infer_instance
end
end GradedObject
namespace Iso
variable {C D E J : Type*} [Category C] [Category D] [Category E]
{X Y : GradedObject J C}
@[reassoc (attr := simp)]
lemma hom_inv_id_eval (e : X ≅ Y) (j : J) :
e.hom j ≫ e.inv j = 𝟙 _ := by
rw [← GradedObject.categoryOfGradedObjects_comp, e.hom_inv_id,
GradedObject.categoryOfGradedObjects_id]
@[reassoc (attr := simp)]
lemma inv_hom_id_eval (e : X ≅ Y) (j : J) :
e.inv j ≫ e.hom j = 𝟙 _ := by
rw [← GradedObject.categoryOfGradedObjects_comp, e.inv_hom_id,
GradedObject.categoryOfGradedObjects_id]
@[reassoc (attr := simp)]
lemma map_hom_inv_id_eval (e : X ≅ Y) (F : C ⥤ D) (j : J) :
F.map (e.hom j) ≫ F.map (e.inv j) = 𝟙 _ := by
rw [← F.map_comp, ← GradedObject.categoryOfGradedObjects_comp, e.hom_inv_id,
GradedObject.categoryOfGradedObjects_id, Functor.map_id]
@[reassoc (attr := simp)]
lemma map_inv_hom_id_eval (e : X ≅ Y) (F : C ⥤ D) (j : J) :
F.map (e.inv j) ≫ F.map (e.hom j) = 𝟙 _ := by
rw [← F.map_comp, ← GradedObject.categoryOfGradedObjects_comp, e.inv_hom_id,
GradedObject.categoryOfGradedObjects_id, Functor.map_id]
@[reassoc (attr := simp)]
lemma map_hom_inv_id_eval_app (e : X ≅ Y) (F : C ⥤ D ⥤ E) (j : J) (Y : D) :
(F.map (e.hom j)).app Y ≫ (F.map (e.inv j)).app Y = 𝟙 _ := by
rw [← NatTrans.comp_app, ← F.map_comp, hom_inv_id_eval,
Functor.map_id, NatTrans.id_app]
@[reassoc (attr := simp)]
lemma map_inv_hom_id_eval_app (e : X ≅ Y) (F : C ⥤ D ⥤ E) (j : J) (Y : D) :
(F.map (e.inv j)).app Y ≫ (F.map (e.hom j)).app Y = 𝟙 _ := by
rw [← NatTrans.comp_app, ← F.map_comp, inv_hom_id_eval,
Functor.map_id, NatTrans.id_app]
end Iso
namespace GradedObject
variable {C : Type u} [Category.{v} C]
section
variable (C)
/-- Pull back an `I`-graded object in `C` to a `J`-graded object along a function `J → I`. -/
abbrev comap {I J : Type*} (h : J → I) : GradedObject I C ⥤ GradedObject J C :=
Pi.comap (fun _ => C) h
@[simp]
theorem eqToHom_proj {I : Type*} {x x' : GradedObject I C} (h : x = x') (i : I) :
(eqToHom h : x ⟶ x') i = eqToHom (funext_iff.mp h i) := by
subst h
rfl
/-- The natural isomorphism comparing between
pulling back along two propositionally equal functions.
-/
@[simps]
def comapEq {β γ : Type w} {f g : β → γ} (h : f = g) : comap C f ≅ comap C g where
hom := { app := fun X b => eqToHom (by dsimp; simp only [h]) }
inv := { app := fun X b => eqToHom (by dsimp; simp only [h]) }
theorem comapEq_symm {β γ : Type w} {f g : β → γ} (h : f = g) :
comapEq C h.symm = (comapEq C h).symm := by aesop_cat
theorem comapEq_trans {β γ : Type w} {f g h : β → γ} (k : f = g) (l : g = h) :
comapEq C (k.trans l) = comapEq C k ≪≫ comapEq C l := by aesop_cat
theorem eqToHom_apply {β : Type w} {X Y : β → C} (h : X = Y) (b : β) :
(eqToHom h : X ⟶ Y) b = eqToHom (by rw [h]) := by
subst h
rfl
/-- The equivalence between β-graded objects and γ-graded objects,
given an equivalence between β and γ.
-/
@[simps]
def comapEquiv {β γ : Type w} (e : β ≃ γ) : GradedObject β C ≌ GradedObject γ C where
functor := comap C (e.symm : γ → β)
inverse := comap C (e : β → γ)
counitIso :=
(Pi.comapComp (fun _ => C) _ _).trans (comapEq C (by ext; simp))
unitIso :=
(comapEq C (by ext; simp)).trans (Pi.comapComp _ _ _).symm
end
instance hasShift {β : Type*} [AddCommGroup β] (s : β) : HasShift (GradedObjectWithShift s C) ℤ :=
hasShiftMk _ _
{ F := fun n => comap C fun b : β => b + n • s
zero := comapEq C (by aesop_cat) ≪≫ Pi.comapId β fun _ => C
add := fun m n => comapEq C (by ext; dsimp; rw [add_comm m n, add_zsmul, add_assoc]) ≪≫
(Pi.comapComp _ _ _).symm }
@[simp]
theorem shiftFunctor_obj_apply {β : Type*} [AddCommGroup β] (s : β) (X : β → C) (t : β) (n : ℤ) :
(shiftFunctor (GradedObjectWithShift s C) n).obj X t = X (t + n • s) :=
rfl
@[simp]
theorem shiftFunctor_map_apply {β : Type*} [AddCommGroup β] (s : β)
{X Y : GradedObjectWithShift s C} (f : X ⟶ Y) (t : β) (n : ℤ) :
(shiftFunctor (GradedObjectWithShift s C) n).map f t = f (t + n • s) :=
rfl
instance [HasZeroMorphisms C] (β : Type w) (X Y : GradedObject β C) :
Zero (X ⟶ Y) := ⟨fun _ => 0⟩
@[simp]
theorem zero_apply [HasZeroMorphisms C] (β : Type w) (X Y : GradedObject β C) (b : β) :
(0 : X ⟶ Y) b = 0 :=
rfl
instance hasZeroMorphisms [HasZeroMorphisms C] (β : Type w) :
HasZeroMorphisms.{max w v} (GradedObject β C) where
section
open ZeroObject
instance hasZeroObject [HasZeroObject C] [HasZeroMorphisms C] (β : Type w) :
HasZeroObject.{max w v} (GradedObject β C) := by
refine ⟨⟨fun _ => 0, fun X => ⟨⟨⟨fun b => 0⟩, fun f => ?_⟩⟩, fun X =>
⟨⟨⟨fun b => 0⟩, fun f => ?_⟩⟩⟩⟩ <;> aesop_cat
end
end GradedObject
namespace GradedObject
-- The universes get a little hairy here, so we restrict the universe level for the grading to 0.
-- Since we're typically interested in grading by ℤ or a finite group, this should be okay.
-- If you're grading by things in higher universes, have fun!
variable (β : Type)
variable (C : Type u) [Category.{v} C]
variable [HasCoproducts.{0} C]
section
/-- The total object of a graded object is the coproduct of the graded components.
-/
noncomputable def total : GradedObject β C ⥤ C where
obj X := ∐ fun i : β => X i
map f := Limits.Sigma.map fun i => f i
end
variable [HasZeroMorphisms C]
/--
The `total` functor taking a graded object to the coproduct of its graded components is faithful.
To prove this, we need to know that the coprojections into the coproduct are monomorphisms,
which follows from the fact we have zero morphisms and decidable equality for the grading.
-/
instance : (total β C).Faithful where
map_injective {X Y} f g w := by
ext i
replace w := Sigma.ι (fun i : β => X i) i ≫= w
erw [colimit.ι_map, colimit.ι_map] at w
simp? at * says simp only [Discrete.functor_obj_eq_as, Discrete.natTrans_app] at *
exact Mono.right_cancellation _ _ w
end GradedObject
namespace GradedObject
noncomputable section
variable (β : Type)
variable (C : Type (u + 1)) [LargeCategory C] [HasForget C] [HasCoproducts.{0} C]
[HasZeroMorphisms C]
instance : HasForget (GradedObject β C) where forget := total β C ⋙ forget C
instance : HasForget₂ (GradedObject β C) C where forget₂ := total β C
end
end GradedObject
namespace GradedObject
variable {I J K : Type*} {C : Type*} [Category C]
(X Y Z : GradedObject I C) (φ : X ⟶ Y) (e : X ≅ Y) (ψ : Y ⟶ Z) (p : I → J)
/-- If `X : GradedObject I C` and `p : I → J`, `X.mapObjFun p j` is the family of objects `X i`
for `i : I` such that `p i = j`. -/
abbrev mapObjFun (j : J) (i : p ⁻¹' {j}) : C := X i
variable (j : J)
/-- Given `X : GradedObject I C` and `p : I → J`, `X.HasMap p` is the condition that
for all `j : J`, the coproduct of all `X i` such `p i = j` exists. -/
abbrev HasMap : Prop := ∀ (j : J), HasCoproduct (X.mapObjFun p j)
variable {X Y} in
lemma hasMap_of_iso (e : X ≅ Y) (p: I → J) [HasMap X p] : HasMap Y p := fun j => by
have α : Discrete.functor (X.mapObjFun p j) ≅ Discrete.functor (Y.mapObjFun p j) :=
Discrete.natIso (fun ⟨i, _⟩ => (GradedObject.eval i).mapIso e)
exact hasColimit_of_iso α.symm
section
variable [X.HasMap p] [Y.HasMap p]
/-- Given `X : GradedObject I C` and `p : I → J`, `X.mapObj p` is the graded object by `J`
which in degree `j` consists of the coproduct of the `X i` such that `p i = j`. -/
noncomputable def mapObj : GradedObject J C := fun j => ∐ (X.mapObjFun p j)
/-- The canonical inclusion `X i ⟶ X.mapObj p j` when `i : I` and `j : J` are such
that `p i = j`. -/
noncomputable def ιMapObj (i : I) (j : J) (hij : p i = j) : X i ⟶ X.mapObj p j :=
Sigma.ι (X.mapObjFun p j) ⟨i, hij⟩
/-- Given `X : GradedObject I C`, `p : I → J` and `j : J`,
`CofanMapObjFun X p j` is the type `Cofan (X.mapObjFun p j)`. The point object of
such colimits cofans are isomorphic to `X.mapObj p j`, see `CofanMapObjFun.iso`. -/
abbrev CofanMapObjFun (j : J) : Type _ := Cofan (X.mapObjFun p j)
-- in order to use the cofan API, some definitions below
-- have a `simp` attribute rather than `simps`
/-- Constructor for `CofanMapObjFun X p j`. -/
@[simp]
def CofanMapObjFun.mk (j : J) (pt : C) (ι' : ∀ (i : I) (_ : p i = j), X i ⟶ pt) :
CofanMapObjFun X p j :=
Cofan.mk pt (fun ⟨i, hi⟩ => ι' i hi)
/-- The tautological cofan corresponding to the coproduct decomposition of `X.mapObj p j`. -/
@[simp]
noncomputable def cofanMapObj (j : J) : CofanMapObjFun X p j :=
CofanMapObjFun.mk X p j (X.mapObj p j) (fun i hi => X.ιMapObj p i j hi)
/-- Given `X : GradedObject I C`, `p : I → J` and `j : J`, `X.mapObj p j` satisfies
the universal property of the coproduct of those `X i` such that `p i = j`. -/
noncomputable def isColimitCofanMapObj (j : J) : IsColimit (X.cofanMapObj p j) :=
colimit.isColimit _
@[ext]
lemma mapObj_ext {A : C} {j : J} (f g : X.mapObj p j ⟶ A)
(hfg : ∀ (i : I) (hij : p i = j), X.ιMapObj p i j hij ≫ f = X.ιMapObj p i j hij ≫ g) :
f = g :=
Cofan.IsColimit.hom_ext (X.isColimitCofanMapObj p j) _ _ (fun ⟨i, hij⟩ => hfg i hij)
/-- This is the morphism `X.mapObj p j ⟶ A` constructed from a family of
morphisms `X i ⟶ A` for all `i : I` such that `p i = j`. -/
noncomputable def descMapObj {A : C} {j : J} (φ : ∀ (i : I) (_ : p i = j), X i ⟶ A) :
X.mapObj p j ⟶ A :=
Cofan.IsColimit.desc (X.isColimitCofanMapObj p j) (fun ⟨i, hi⟩ => φ i hi)
@[reassoc (attr := simp)]
lemma ι_descMapObj {A : C} {j : J}
(φ : ∀ (i : I) (_ : p i = j), X i ⟶ A) (i : I) (hi : p i = j) :
X.ιMapObj p i j hi ≫ X.descMapObj p φ = φ i hi := by
apply Cofan.IsColimit.fac
end
namespace CofanMapObjFun
lemma hasMap (c : ∀ j, CofanMapObjFun X p j) (hc : ∀ j, IsColimit (c j)) :
X.HasMap p := fun j => ⟨_, hc j⟩
variable {j X p}
variable [X.HasMap p]
variable {c : CofanMapObjFun X p j} (hc : IsColimit c)
/-- If `c : CofanMapObjFun X p j` is a colimit cofan, this is the induced
isomorphism `c.pt ≅ X.mapObj p j`. -/
noncomputable def iso : c.pt ≅ X.mapObj p j :=
IsColimit.coconePointUniqueUpToIso hc (X.isColimitCofanMapObj p j)
@[reassoc (attr := simp)]
lemma inj_iso_hom (i : I) (hi : p i = j) :
c.inj ⟨i, hi⟩ ≫ (c.iso hc).hom = X.ιMapObj p i j hi := by
apply IsColimit.comp_coconePointUniqueUpToIso_hom
@[reassoc (attr := simp)]
lemma ιMapObj_iso_inv (i : I) (hi : p i = j) :
X.ιMapObj p i j hi ≫ (c.iso hc).inv = c.inj ⟨i, hi⟩ := by
apply IsColimit.comp_coconePointUniqueUpToIso_inv
end CofanMapObjFun
variable {X Y}
variable [X.HasMap p] [Y.HasMap p]
/-- The canonical morphism of `J`-graded objects `X.mapObj p ⟶ Y.mapObj p` induced by
a morphism `X ⟶ Y` of `I`-graded objects and a map `p : I → J`. -/
noncomputable def mapMap : X.mapObj p ⟶ Y.mapObj p := fun j =>
X.descMapObj p (fun i hi => φ i ≫ Y.ιMapObj p i j hi)
@[reassoc (attr := simp)]
lemma ι_mapMap (i : I) (j : J) (hij : p i = j) :
X.ιMapObj p i j hij ≫ mapMap φ p j = φ i ≫ Y.ιMapObj p i j hij := by
simp only [mapMap, ι_descMapObj]
lemma congr_mapMap (φ₁ φ₂ : X ⟶ Y) (h : φ₁ = φ₂) : mapMap φ₁ p = mapMap φ₂ p := by
subst h
rfl
variable (X)
@[simp]
lemma mapMap_id : mapMap (𝟙 X) p = 𝟙 _ := by aesop_cat
variable {X Z}
@[simp, reassoc]
lemma mapMap_comp [Z.HasMap p] : mapMap (φ ≫ ψ) p = mapMap φ p ≫ mapMap ψ p := by aesop_cat
/-- The isomorphism of `J`-graded objects `X.mapObj p ≅ Y.mapObj p` induced by an
isomorphism `X ≅ Y` of graded objects and a map `p : I → J`. -/
@[simps]
noncomputable def mapIso : X.mapObj p ≅ Y.mapObj p where
hom := mapMap e.hom p
inv := mapMap e.inv p
variable (C)
/-- Given a map `p : I → J`, this is the functor `GradedObject I C ⥤ GradedObject J C` which
sends an `I`-object `X` to the graded object `X.mapObj p` which in degree `j : J` is given
by the coproduct of those `X i` such that `p i = j`. -/
@[simps]
noncomputable def map [∀ (j : J), HasColimitsOfShape (Discrete (p ⁻¹' {j})) C] :
GradedObject I C ⥤ GradedObject J C where
obj X := X.mapObj p
map φ := mapMap φ p
variable {C} (X Y)
variable (q : J → K) (r : I → K) (hpqr : ∀ i, q (p i) = r i)
section
variable (k : K) (c : ∀ (j : J), q j = k → X.CofanMapObjFun p j)
(hc : ∀ j hj, IsColimit (c j hj))
(c' : Cofan (fun (j : q ⁻¹' {k}) => (c j.1 j.2).pt)) (hc' : IsColimit c')
/-- Given maps `p : I → J`, `q : J → K` and `r : I → K` such that `q.comp p = r`,
`X : GradedObject I C`, `k : K`, the datum of cofans `X.CofanMapObjFun p j` for all
`j : J` and of a cofan for all the points of these cofans, this is a cofan of
type `X.CofanMapObjFun r k`, which is a colimit (see `isColimitCofanMapObjComp`) if the
given cofans are. -/
@[simp]
def cofanMapObjComp : X.CofanMapObjFun r k :=
CofanMapObjFun.mk _ _ _ c'.pt (fun i hi =>
(c (p i) (by rw [hpqr, hi])).inj ⟨i, rfl⟩ ≫ c'.inj (⟨p i, by
rw [Set.mem_preimage, Set.mem_singleton_iff, hpqr, hi]⟩))
/-- Given maps `p : I → J`, `q : J → K` and `r : I → K` such that `q.comp p = r`,
`X : GradedObject I C`, `k : K`, the cofan constructed by `cofanMapObjComp` is a colimit.
In other words, if we have, for all `j : J` such that `hj : q j = k`,
a colimit cofan `c j hj` which computes the coproduct of the `X i` such that `p i = j`,
and also a colimit cofan which computes the coproduct of the points of these `c j hj`, then
the point of this latter cofan computes the coproduct of the `X i` such that `r i = k`. -/
@[simp]
def isColimitCofanMapObjComp :
IsColimit (cofanMapObjComp X p q r hpqr k c c') :=
mkCofanColimit _
(fun s => Cofan.IsColimit.desc hc'
(fun ⟨j, (hj : q j = k)⟩ => Cofan.IsColimit.desc (hc j hj)
(fun ⟨i, (hi : p i = j)⟩ => s.inj ⟨i, by
simp only [Set.mem_preimage, Set.mem_singleton_iff, ← hpqr, hi, hj]⟩)))
(fun s ⟨i, (hi : r i = k)⟩ => by simp)
(fun s m hm => by
apply Cofan.IsColimit.hom_ext hc'
rintro ⟨j, rfl : q j = k⟩
apply Cofan.IsColimit.hom_ext (hc j rfl)
rintro ⟨i, rfl : p i = j⟩
dsimp
rw [Cofan.IsColimit.fac, Cofan.IsColimit.fac, ← hm]
dsimp
rw [assoc])
include hpqr in
lemma hasMap_comp [(X.mapObj p).HasMap q] : X.HasMap r :=
fun k => ⟨_, isColimitCofanMapObjComp X p q r hpqr k _
(fun j _ => X.isColimitCofanMapObj p j) _ ((X.mapObj p).isColimitCofanMapObj q k)⟩
end
variable [HasZeroMorphisms C] [DecidableEq J] (i : I) (j : J)
/-- The canonical inclusion `X i ⟶ X.mapObj p j` when `p i = j`, the zero morphism otherwise. -/
noncomputable def ιMapObjOrZero : X i ⟶ X.mapObj p j :=
if h : p i = j
then X.ιMapObj p i j h
else 0
lemma ιMapObjOrZero_eq (h : p i = j) : X.ιMapObjOrZero p i j = X.ιMapObj p i j h := dif_pos h
lemma ιMapObjOrZero_eq_zero (h : p i ≠ j) : X.ιMapObjOrZero p i j = 0 := dif_neg h
variable {X Y} in
@[reassoc (attr := simp)]
lemma ιMapObjOrZero_mapMap :
X.ιMapObjOrZero p i j ≫ mapMap φ p j = φ i ≫ Y.ιMapObjOrZero p i j := by
by_cases h : p i = j
· simp only [ιMapObjOrZero_eq _ _ _ _ h, ι_mapMap]
· simp only [ιMapObjOrZero_eq_zero _ _ _ _ h, zero_comp, comp_zero]
end GradedObject
end CategoryTheory
| Mathlib/CategoryTheory/GradedObject.lean | 526 | 531 | |
/-
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.ExactSequence
import Mathlib.Algebra.Homology.ShortComplex.Limits
import Mathlib.CategoryTheory.Abelian.Refinements
/-!
# The snake lemma
The snake lemma is a standard tool in homological algebra. The basic situation
is when we have a diagram as follows in an abelian category `C`, with exact rows:
L₁.X₁ ⟶ L₁.X₂ ⟶ L₁.X₃ ⟶ 0
| | |
|v₁₂.τ₁ |v₁₂.τ₂ |v₁₂.τ₃
v v v
0 ⟶ L₂.X₁ ⟶ L₂.X₂ ⟶ L₂.X₃
We shall think of this diagram as the datum of a morphism `v₁₂ : L₁ ⟶ L₂` in the
category `ShortComplex C` such that both `L₁` and `L₂` are exact, and `L₁.g` is epi
and `L₂.f` is a mono (which is equivalent to saying that `L₁.X₃` is the cokernel
of `L₁.f` and `L₂.X₁` is the kernel of `L₂.g`). Then, we may introduce the kernels
and cokernels of the vertical maps. In other words, we may introduce short complexes
`L₀` and `L₃` that are respectively the kernel and the cokernel of `v₁₂`. All these
data constitute a `SnakeInput C`.
Given such a `S : SnakeInput C`, we define a connecting homomorphism
`S.δ : L₀.X₃ ⟶ L₃.X₁` and show that it is part of an exact sequence
`L₀.X₁ ⟶ L₀.X₂ ⟶ L₀.X₃ ⟶ L₃.X₁ ⟶ L₃.X₂ ⟶ L₃.X₃`. Each of the four exactness
statement is first stated separately as lemmas `L₀_exact`, `L₁'_exact`,
`L₂'_exact` and `L₃_exact` and the full 6-term exact sequence is stated
as `snake_lemma`. This sequence can even be extended with an extra `0`
on the left (see `mono_L₀_f`) if `L₁.X₁ ⟶ L₁.X₂` is a mono (i.e. `L₁` is short exact),
and similarly an extra `0` can be added on the right (`epi_L₃_g`)
if `L₂.X₂ ⟶ L₂.X₃` is an epi (i.e. `L₂` is short exact).
These results were also obtained in the Liquid Tensor Experiment. The code and the proof
here are slightly easier because of the use of the category `ShortComplex C`,
the use of duality (which allows to construct only half of the sequence, and deducing
the other half by arguing in the opposite category), and the use of "refinements"
(see `CategoryTheory.Abelian.Refinements`) instead of a weak form of pseudo-elements.
-/
namespace CategoryTheory
open Category Limits Preadditive
variable (C : Type*) [Category C] [Abelian C]
namespace ShortComplex
/-- A snake input in an abelian category `C` consists of morphisms
of short complexes `L₀ ⟶ L₁ ⟶ L₂ ⟶ L₃` (which should be visualized vertically) such
that `L₀` and `L₃` are respectively the kernel and the cokernel of `L₁ ⟶ L₂`,
`L₁` and `L₂` are exact, `L₁.g` is epi and `L₂.f` is mono. -/
structure SnakeInput where
/-- the zeroth row -/
L₀ : ShortComplex C
/-- the first row -/
L₁ : ShortComplex C
/-- the second row -/
L₂ : ShortComplex C
/-- the third row -/
L₃ : ShortComplex C
/-- the morphism from the zeroth row to the first row -/
v₀₁ : L₀ ⟶ L₁
/-- the morphism from the first row to the second row -/
v₁₂ : L₁ ⟶ L₂
/-- the morphism from the second row to the third row -/
v₂₃ : L₂ ⟶ L₃
w₀₂ : v₀₁ ≫ v₁₂ = 0 := by aesop_cat
w₁₃ : v₁₂ ≫ v₂₃ = 0 := by aesop_cat
/-- `L₀` is the kernel of `v₁₂ : L₁ ⟶ L₂`. -/
h₀ : IsLimit (KernelFork.ofι _ w₀₂)
/-- `L₃` is the cokernel of `v₁₂ : L₁ ⟶ L₂`. -/
h₃ : IsColimit (CokernelCofork.ofπ _ w₁₃)
L₁_exact : L₁.Exact
epi_L₁_g : Epi L₁.g
L₂_exact : L₂.Exact
mono_L₂_f : Mono L₂.f
initialize_simps_projections SnakeInput (-h₀, -h₃)
namespace SnakeInput
attribute [reassoc (attr := simp)] w₀₂ w₁₃
attribute [instance] epi_L₁_g
attribute [instance] mono_L₂_f
variable {C}
variable (S : SnakeInput C)
/-- The snake input in the opposite category that is deduced from a snake input. -/
@[simps]
noncomputable def op : SnakeInput Cᵒᵖ where
L₀ := S.L₃.op
L₁ := S.L₂.op
L₂ := S.L₁.op
L₃ := S.L₀.op
epi_L₁_g := by dsimp; infer_instance
mono_L₂_f := by dsimp; infer_instance
v₀₁ := opMap S.v₂₃
v₁₂ := opMap S.v₁₂
v₂₃ := opMap S.v₀₁
w₀₂ := congr_arg opMap S.w₁₃
w₁₃ := congr_arg opMap S.w₀₂
h₀ := isLimitForkMapOfIsLimit' (ShortComplex.opEquiv C).functor _
(CokernelCofork.IsColimit.ofπOp _ _ S.h₃)
h₃ := isColimitCoforkMapOfIsColimit' (ShortComplex.opEquiv C).functor _
(KernelFork.IsLimit.ofιOp _ _ S.h₀)
L₁_exact := S.L₂_exact.op
L₂_exact := S.L₁_exact.op
@[reassoc (attr := simp)] lemma w₀₂_τ₁ : S.v₀₁.τ₁ ≫ S.v₁₂.τ₁ = 0 := by
rw [← comp_τ₁, S.w₀₂, zero_τ₁]
@[reassoc (attr := simp)] lemma w₀₂_τ₂ : S.v₀₁.τ₂ ≫ S.v₁₂.τ₂ = 0 := by
rw [← comp_τ₂, S.w₀₂, zero_τ₂]
@[reassoc (attr := simp)] lemma w₀₂_τ₃ : S.v₀₁.τ₃ ≫ S.v₁₂.τ₃ = 0 := by
rw [← comp_τ₃, S.w₀₂, zero_τ₃]
@[reassoc (attr := simp)] lemma w₁₃_τ₁ : S.v₁₂.τ₁ ≫ S.v₂₃.τ₁ = 0 := by
rw [← comp_τ₁, S.w₁₃, zero_τ₁]
@[reassoc (attr := simp)] lemma w₁₃_τ₂ : S.v₁₂.τ₂ ≫ S.v₂₃.τ₂ = 0 := by
rw [← comp_τ₂, S.w₁₃, zero_τ₂]
@[reassoc (attr := simp)] lemma w₁₃_τ₃ : S.v₁₂.τ₃ ≫ S.v₂₃.τ₃ = 0 := by
rw [← comp_τ₃, S.w₁₃, zero_τ₃]
/-- `L₀.X₁` is the kernel of `v₁₂.τ₁ : L₁.X₁ ⟶ L₂.X₁`. -/
noncomputable def h₀τ₁ : IsLimit (KernelFork.ofι S.v₀₁.τ₁ S.w₀₂_τ₁) :=
isLimitForkMapOfIsLimit' π₁ S.w₀₂ S.h₀
/-- `L₀.X₂` is the kernel of `v₁₂.τ₂ : L₁.X₂ ⟶ L₂.X₂`. -/
noncomputable def h₀τ₂ : IsLimit (KernelFork.ofι S.v₀₁.τ₂ S.w₀₂_τ₂) :=
isLimitForkMapOfIsLimit' π₂ S.w₀₂ S.h₀
/-- `L₀.X₃` is the kernel of `v₁₂.τ₃ : L₁.X₃ ⟶ L₂.X₃`. -/
noncomputable def h₀τ₃ : IsLimit (KernelFork.ofι S.v₀₁.τ₃ S.w₀₂_τ₃) :=
isLimitForkMapOfIsLimit' π₃ S.w₀₂ S.h₀
instance mono_v₀₁_τ₁ : Mono S.v₀₁.τ₁ := mono_of_isLimit_fork S.h₀τ₁
instance mono_v₀₁_τ₂ : Mono S.v₀₁.τ₂ := mono_of_isLimit_fork S.h₀τ₂
instance mono_v₀₁_τ₃ : Mono S.v₀₁.τ₃ := mono_of_isLimit_fork S.h₀τ₃
/-- The upper part of the first column of the snake diagram is exact. -/
lemma exact_C₁_up : (ShortComplex.mk S.v₀₁.τ₁ S.v₁₂.τ₁
(by rw [← comp_τ₁, S.w₀₂, zero_τ₁])).Exact :=
exact_of_f_is_kernel _ S.h₀τ₁
/-- The upper part of the second column of the snake diagram is exact. -/
lemma exact_C₂_up : (ShortComplex.mk S.v₀₁.τ₂ S.v₁₂.τ₂
(by rw [← comp_τ₂, S.w₀₂, zero_τ₂])).Exact :=
exact_of_f_is_kernel _ S.h₀τ₂
/-- The upper part of the third column of the snake diagram is exact. -/
lemma exact_C₃_up : (ShortComplex.mk S.v₀₁.τ₃ S.v₁₂.τ₃
(by rw [← comp_τ₃, S.w₀₂, zero_τ₃])).Exact :=
exact_of_f_is_kernel _ S.h₀τ₃
instance mono_L₀_f [Mono S.L₁.f] : Mono S.L₀.f := by
have : Mono (S.L₀.f ≫ S.v₀₁.τ₂) := by
rw [← S.v₀₁.comm₁₂]
apply mono_comp
exact mono_of_mono _ S.v₀₁.τ₂
/-- `L₃.X₁` is the cokernel of `v₁₂.τ₁ : L₁.X₁ ⟶ L₂.X₁`. -/
noncomputable def h₃τ₁ : IsColimit (CokernelCofork.ofπ S.v₂₃.τ₁ S.w₁₃_τ₁) :=
isColimitCoforkMapOfIsColimit' π₁ S.w₁₃ S.h₃
/-- `L₃.X₂` is the cokernel of `v₁₂.τ₂ : L₁.X₂ ⟶ L₂.X₂`. -/
noncomputable def h₃τ₂ : IsColimit (CokernelCofork.ofπ S.v₂₃.τ₂ S.w₁₃_τ₂) :=
isColimitCoforkMapOfIsColimit' π₂ S.w₁₃ S.h₃
/-- `L₃.X₃` is the cokernel of `v₁₂.τ₃ : L₁.X₃ ⟶ L₂.X₃`. -/
noncomputable def h₃τ₃ : IsColimit (CokernelCofork.ofπ S.v₂₃.τ₃ S.w₁₃_τ₃) :=
isColimitCoforkMapOfIsColimit' π₃ S.w₁₃ S.h₃
instance epi_v₂₃_τ₁ : Epi S.v₂₃.τ₁ := epi_of_isColimit_cofork S.h₃τ₁
instance epi_v₂₃_τ₂ : Epi S.v₂₃.τ₂ := epi_of_isColimit_cofork S.h₃τ₂
instance epi_v₂₃_τ₃ : Epi S.v₂₃.τ₃ := epi_of_isColimit_cofork S.h₃τ₃
/-- The lower part of the first column of the snake diagram is exact. -/
lemma exact_C₁_down : (ShortComplex.mk S.v₁₂.τ₁ S.v₂₃.τ₁
(by rw [← comp_τ₁, S.w₁₃, zero_τ₁])).Exact :=
exact_of_g_is_cokernel _ S.h₃τ₁
/-- The lower part of the second column of the snake diagram is exact. -/
lemma exact_C₂_down : (ShortComplex.mk S.v₁₂.τ₂ S.v₂₃.τ₂
(by rw [← comp_τ₂, S.w₁₃, zero_τ₂])).Exact :=
exact_of_g_is_cokernel _ S.h₃τ₂
/-- The lower part of the third column of the snake diagram is exact. -/
lemma exact_C₃_down : (ShortComplex.mk S.v₁₂.τ₃ S.v₂₃.τ₃
(by rw [← comp_τ₃, S.w₁₃, zero_τ₃])).Exact :=
exact_of_g_is_cokernel _ S.h₃τ₃
instance epi_L₃_g [Epi S.L₂.g] : Epi S.L₃.g := by
have : Epi (S.v₂₃.τ₂ ≫ S.L₃.g) := by
rw [S.v₂₃.comm₂₃]
apply epi_comp
exact epi_of_epi S.v₂₃.τ₂ _
lemma L₀_exact : S.L₀.Exact := by
rw [ShortComplex.exact_iff_exact_up_to_refinements]
intro A x₂ hx₂
obtain ⟨A₁, π₁, hπ₁, y₁, hy₁⟩ := S.L₁_exact.exact_up_to_refinements (x₂ ≫ S.v₀₁.τ₂)
(by rw [assoc, S.v₀₁.comm₂₃, reassoc_of% hx₂, zero_comp])
have hy₁' : y₁ ≫ S.v₁₂.τ₁ = 0 := by
simp only [← cancel_mono S.L₂.f, assoc, zero_comp, S.v₁₂.comm₁₂,
← reassoc_of% hy₁, w₀₂_τ₂, comp_zero]
obtain ⟨x₁, hx₁⟩ : ∃ x₁, x₁ ≫ S.v₀₁.τ₁ = y₁ := ⟨_, S.exact_C₁_up.lift_f y₁ hy₁'⟩
refine ⟨A₁, π₁, hπ₁, x₁, ?_⟩
simp only [← cancel_mono S.v₀₁.τ₂, assoc, ← S.v₀₁.comm₁₂, reassoc_of% hx₁, hy₁]
lemma L₃_exact : S.L₃.Exact := S.op.L₀_exact.unop
/-- The fiber product of `L₁.X₂` and `L₀.X₃` over `L₁.X₃`. This is an auxiliary
object in the construction of the morphism `δ : L₀.X₃ ⟶ L₃.X₁`. -/
noncomputable def P := pullback S.L₁.g S.v₀₁.τ₃
/-- The canonical map `P ⟶ L₂.X₂`. -/
noncomputable def φ₂ : S.P ⟶ S.L₂.X₂ := pullback.fst _ _ ≫ S.v₁₂.τ₂
@[reassoc (attr := simp)]
lemma lift_φ₂ {A : C} (a : A ⟶ S.L₁.X₂) (b : A ⟶ S.L₀.X₃) (h : a ≫ S.L₁.g = b ≫ S.v₀₁.τ₃) :
pullback.lift a b h ≫ S.φ₂ = a ≫ S.v₁₂.τ₂ := by
simp [φ₂]
/-- The canonical map `P ⟶ L₂.X₁`. -/
noncomputable def φ₁ : S.P ⟶ S.L₂.X₁ :=
S.L₂_exact.lift S.φ₂
(by simp only [φ₂, assoc, S.v₁₂.comm₂₃, pullback.condition_assoc, w₀₂_τ₃, comp_zero])
@[reassoc (attr := simp)] lemma φ₁_L₂_f : S.φ₁ ≫ S.L₂.f = S.φ₂ := S.L₂_exact.lift_f _ _
/-- The short complex that is part of an exact sequence `L₁.X₁ ⟶ P ⟶ L₀.X₃ ⟶ 0`. -/
noncomputable def L₀' : ShortComplex C where
X₁ := S.L₁.X₁
X₂ := S.P
X₃ := S.L₀.X₃
f := pullback.lift S.L₁.f 0 (by simp)
g := pullback.snd _ _
zero := by simp
@[reassoc (attr := simp)] lemma L₁_f_φ₁ : S.L₀'.f ≫ S.φ₁ = S.v₁₂.τ₁ := by
dsimp only [L₀']
simp only [← cancel_mono S.L₂.f, assoc, φ₁_L₂_f, φ₂, pullback.lift_fst_assoc,
S.v₁₂.comm₁₂]
instance : Epi S.L₀'.g := by dsimp only [L₀']; infer_instance
instance [Mono S.L₁.f] : Mono S.L₀'.f :=
mono_of_mono_fac (show S.L₀'.f ≫ pullback.fst _ _ = S.L₁.f by simp [L₀'])
lemma L₀'_exact : S.L₀'.Exact := by
rw [ShortComplex.exact_iff_exact_up_to_refinements]
intro A x₂ hx₂
dsimp [L₀'] at x₂ hx₂
obtain ⟨A', π, hπ, x₁, fac⟩ := S.L₁_exact.exact_up_to_refinements (x₂ ≫ pullback.fst _ _)
(by rw [assoc, pullback.condition, reassoc_of% hx₂, zero_comp])
exact ⟨A', π, hπ, x₁, pullback.hom_ext (by simpa [L₀'] using fac) (by simp [L₀', hx₂])⟩
/-- The connecting homomorphism `δ : L₀.X₃ ⟶ L₃.X₁`. -/
noncomputable def δ : S.L₀.X₃ ⟶ S.L₃.X₁ :=
S.L₀'_exact.desc (S.φ₁ ≫ S.v₂₃.τ₁) (by simp only [L₁_f_φ₁_assoc, w₁₃_τ₁])
@[reassoc (attr := simp)]
lemma snd_δ : (pullback.snd _ _ : S.P ⟶ _) ≫ S.δ = S.φ₁ ≫ S.v₂₃.τ₁ :=
S.L₀'_exact.g_desc _ _
/-- The pushout of `L₂.X₂` and `L₃.X₁` along `L₂.X₁`. -/
noncomputable def P' := pushout S.L₂.f S.v₂₃.τ₁
| lemma snd_δ_inr : (pullback.snd _ _ : S.P ⟶ _) ≫ S.δ ≫ (pushout.inr _ _ : _ ⟶ S.P') =
pullback.fst _ _ ≫ S.v₁₂.τ₂ ≫ pushout.inl _ _ := by
simp only [snd_δ_assoc, ← pushout.condition, φ₂, φ₁_L₂_f_assoc, assoc]
| Mathlib/Algebra/Homology/ShortComplex/SnakeLemma.lean | 276 | 278 |
/-
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.Defs
import Mathlib.Analysis.Calculus.ContDiff.FaaDiBruno
import Mathlib.Analysis.Calculus.FDeriv.Add
import Mathlib.Analysis.Calculus.FDeriv.Mul
/-!
# Higher differentiability of composition
We prove that the composition of `C^n` functions is `C^n`.
We also expand the API around `C^n` functions.
## Main results
* `ContDiff.comp` states that the composition of two `C^n` functions is `C^n`.
Similar results are given for `C^n` functions on domains.
## 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`.
## Tags
derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series
-/
noncomputable section
open scoped NNReal Nat ContDiff
universe u uE uF uG
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup AddCommGroup.toAddCommMonoid
open Set Fin Filter Function
open scoped Topology
variable {𝕜 : Type*} [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*} [NormedAddCommGroup X] [NormedSpace 𝕜 X] {s t : Set E} {f : E → F}
{g : F → G} {x x₀ : E} {b : E × F → G} {m n : WithTop ℕ∞} {p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Constants -/
section constants
theorem iteratedFDerivWithin_succ_const (n : ℕ) (c : F) :
iteratedFDerivWithin 𝕜 (n + 1) (fun _ : E ↦ c) s = 0 := by
induction n with
| zero =>
ext1
simp [iteratedFDerivWithin_succ_eq_comp_left, iteratedFDerivWithin_zero_eq_comp, comp_def]
| succ n IH =>
rw [iteratedFDerivWithin_succ_eq_comp_left, IH]
simp only [Pi.zero_def, comp_def, fderivWithin_const, map_zero]
@[simp]
theorem iteratedFDerivWithin_zero_fun {i : ℕ} :
iteratedFDerivWithin 𝕜 i (fun _ : E ↦ (0 : F)) s = 0 := by
cases i with
| zero => ext; simp
| succ i => apply iteratedFDerivWithin_succ_const
@[simp]
theorem iteratedFDeriv_zero_fun {n : ℕ} : (iteratedFDeriv 𝕜 n fun _ : E ↦ (0 : F)) = 0 :=
funext fun x ↦ by simp only [← iteratedFDerivWithin_univ, iteratedFDerivWithin_zero_fun]
theorem contDiff_zero_fun : ContDiff 𝕜 n fun _ : E => (0 : F) :=
analyticOnNhd_const.contDiff
/-- Constants are `C^∞`. -/
theorem contDiff_const {c : F} : ContDiff 𝕜 n fun _ : E => c :=
analyticOnNhd_const.contDiff
theorem contDiffOn_const {c : F} {s : Set E} : ContDiffOn 𝕜 n (fun _ : E => c) s :=
contDiff_const.contDiffOn
theorem contDiffAt_const {c : F} : ContDiffAt 𝕜 n (fun _ : E => c) x :=
contDiff_const.contDiffAt
theorem contDiffWithinAt_const {c : F} : ContDiffWithinAt 𝕜 n (fun _ : E => c) s x :=
contDiffAt_const.contDiffWithinAt
@[nontriviality]
theorem contDiff_of_subsingleton [Subsingleton F] : ContDiff 𝕜 n f := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiff_const
@[nontriviality]
theorem contDiffAt_of_subsingleton [Subsingleton F] : ContDiffAt 𝕜 n f x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffAt_const
@[nontriviality]
theorem contDiffWithinAt_of_subsingleton [Subsingleton F] : ContDiffWithinAt 𝕜 n f s x := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffWithinAt_const
@[nontriviality]
theorem contDiffOn_of_subsingleton [Subsingleton F] : ContDiffOn 𝕜 n f s := by
rw [Subsingleton.elim f fun _ => 0]; exact contDiffOn_const
theorem iteratedFDerivWithin_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) (s : Set E) :
iteratedFDerivWithin 𝕜 n (fun _ : E ↦ c) s = 0 := by
cases n with
| zero => contradiction
| succ n => exact iteratedFDerivWithin_succ_const n c
theorem iteratedFDeriv_const_of_ne {n : ℕ} (hn : n ≠ 0) (c : F) :
(iteratedFDeriv 𝕜 n fun _ : E ↦ c) = 0 := by
simp only [← iteratedFDerivWithin_univ, iteratedFDerivWithin_const_of_ne hn]
theorem iteratedFDeriv_succ_const (n : ℕ) (c : F) :
(iteratedFDeriv 𝕜 (n + 1) fun _ : E ↦ c) = 0 :=
iteratedFDeriv_const_of_ne (by simp) _
theorem contDiffWithinAt_singleton : ContDiffWithinAt 𝕜 n f {x} x :=
(contDiffWithinAt_const (c := f x)).congr (by simp) rfl
end constants
/-! ### Smoothness of linear functions -/
section linear
/-- Unbundled bounded linear functions are `C^n`. -/
theorem IsBoundedLinearMap.contDiff (hf : IsBoundedLinearMap 𝕜 f) : ContDiff 𝕜 n f :=
(ContinuousLinearMap.analyticOnNhd hf.toContinuousLinearMap univ).contDiff
theorem ContinuousLinearMap.contDiff (f : E →L[𝕜] F) : ContDiff 𝕜 n f :=
f.isBoundedLinearMap.contDiff
theorem ContinuousLinearEquiv.contDiff (f : E ≃L[𝕜] F) : ContDiff 𝕜 n f :=
(f : E →L[𝕜] F).contDiff
theorem LinearIsometry.contDiff (f : E →ₗᵢ[𝕜] F) : ContDiff 𝕜 n f :=
f.toContinuousLinearMap.contDiff
theorem LinearIsometryEquiv.contDiff (f : E ≃ₗᵢ[𝕜] F) : ContDiff 𝕜 n f :=
(f : E →L[𝕜] F).contDiff
/-- The identity is `C^n`. -/
theorem contDiff_id : ContDiff 𝕜 n (id : E → E) :=
IsBoundedLinearMap.id.contDiff
theorem contDiffWithinAt_id {s x} : ContDiffWithinAt 𝕜 n (id : E → E) s x :=
contDiff_id.contDiffWithinAt
theorem contDiffAt_id {x} : ContDiffAt 𝕜 n (id : E → E) x :=
contDiff_id.contDiffAt
theorem contDiffOn_id {s} : ContDiffOn 𝕜 n (id : E → E) s :=
contDiff_id.contDiffOn
/-- Bilinear functions are `C^n`. -/
theorem IsBoundedBilinearMap.contDiff (hb : IsBoundedBilinearMap 𝕜 b) : ContDiff 𝕜 n b :=
(hb.toContinuousLinearMap.analyticOnNhd_bilinear _).contDiff
/-- If `f` admits a Taylor series `p` in a set `s`, and `g` is linear, then `g ∘ f` admits a Taylor
series whose `k`-th term is given by `g ∘ (p k)`. -/
theorem HasFTaylorSeriesUpToOn.continuousLinearMap_comp {n : WithTop ℕ∞} (g : F →L[𝕜] G)
(hf : HasFTaylorSeriesUpToOn n f p s) :
HasFTaylorSeriesUpToOn n (g ∘ f) (fun x k => g.compContinuousMultilinearMap (p x k)) s where
zero_eq x hx := congr_arg g (hf.zero_eq x hx)
fderivWithin m hm x hx := (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin m => E) F G g).hasFDerivAt.comp_hasFDerivWithinAt x (hf.fderivWithin m hm x hx)
cont m hm := (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin m => E) F G g).continuous.comp_continuousOn (hf.cont m hm)
/-- Composition by continuous linear maps on the left preserves `C^n` functions in a domain
at a point. -/
theorem ContDiffWithinAt.continuousLinearMap_comp (g : F →L[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
match n with
| ω =>
obtain ⟨u, hu, p, hp, h'p⟩ := hf
refine ⟨u, hu, _, hp.continuousLinearMap_comp g, fun i ↦ ?_⟩
change AnalyticOn 𝕜
(fun x ↦ (ContinuousLinearMap.compContinuousMultilinearMapL 𝕜
(fun _ : Fin i ↦ E) F G g) (p x i)) u
apply AnalyticOnNhd.comp_analyticOn _ (h'p i) (Set.mapsTo_univ _ _)
exact ContinuousLinearMap.analyticOnNhd _ _
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
exact ⟨u, hu, _, hp.continuousLinearMap_comp g⟩
/-- Composition by continuous linear maps on the left preserves `C^n` functions in a domain
at a point. -/
theorem ContDiffAt.continuousLinearMap_comp (g : F →L[𝕜] G) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (g ∘ f) x :=
ContDiffWithinAt.continuousLinearMap_comp g hf
/-- Composition by continuous linear maps on the left preserves `C^n` functions on domains. -/
theorem ContDiffOn.continuousLinearMap_comp (g : F →L[𝕜] G) (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (g ∘ f) s := fun x hx => (hf x hx).continuousLinearMap_comp g
/-- Composition by continuous linear maps on the left preserves `C^n` functions. -/
theorem ContDiff.continuousLinearMap_comp {f : E → F} (g : F →L[𝕜] G) (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n fun x => g (f x) :=
contDiffOn_univ.1 <| ContDiffOn.continuousLinearMap_comp _ (contDiffOn_univ.2 hf)
/-- The iterated derivative within a set of the composition with a linear map on the left is
obtained by applying the linear map to the iterated derivative. -/
theorem ContinuousLinearMap.iteratedFDerivWithin_comp_left {f : E → F} (g : F →L[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
g.compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) := by
rcases hf.contDiffOn' hi (by simp) with ⟨U, hU, hxU, hfU⟩
rw [← iteratedFDerivWithin_inter_open hU hxU, ← iteratedFDerivWithin_inter_open (f := f) hU hxU]
rw [insert_eq_of_mem hx] at hfU
exact .symm <| (hfU.ftaylorSeriesWithin (hs.inter hU)).continuousLinearMap_comp g
|>.eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl (hs.inter hU) ⟨hx, hxU⟩
/-- The iterated derivative of the composition with a linear map on the left is
obtained by applying the linear map to the iterated derivative. -/
theorem ContinuousLinearMap.iteratedFDeriv_comp_left {f : E → F} (g : F →L[𝕜] G)
(hf : ContDiffAt 𝕜 n f x) {i : ℕ} (hi : i ≤ n) :
iteratedFDeriv 𝕜 i (g ∘ f) x = g.compContinuousMultilinearMap (iteratedFDeriv 𝕜 i f x) := by
simp only [← iteratedFDerivWithin_univ]
exact g.iteratedFDerivWithin_comp_left hf.contDiffWithinAt uniqueDiffOn_univ (mem_univ x) hi
/-- The iterated derivative within a set of the composition with a linear equiv on the left is
obtained by applying the linear equiv to the iterated derivative. This is true without
differentiability assumptions. -/
theorem ContinuousLinearEquiv.iteratedFDerivWithin_comp_left (g : F ≃L[𝕜] G) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (i : ℕ) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(g : F →L[𝕜] G).compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) := by
induction' i with i IH generalizing x
· ext1 m
simp only [iteratedFDerivWithin_zero_apply, comp_apply,
ContinuousLinearMap.compContinuousMultilinearMap_coe, coe_coe]
· ext1 m
rw [iteratedFDerivWithin_succ_apply_left]
have Z : fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 i (g ∘ f) s) s x =
fderivWithin 𝕜 (g.continuousMultilinearMapCongrRight (fun _ : Fin i => E) ∘
iteratedFDerivWithin 𝕜 i f s) s x :=
fderivWithin_congr' (@IH) hx
simp_rw [Z]
rw [(g.continuousMultilinearMapCongrRight fun _ : Fin i => E).comp_fderivWithin (hs x hx)]
simp only [ContinuousLinearMap.coe_comp', ContinuousLinearEquiv.coe_coe, comp_apply,
ContinuousLinearEquiv.continuousMultilinearMapCongrRight_apply,
ContinuousLinearMap.compContinuousMultilinearMap_coe, EmbeddingLike.apply_eq_iff_eq]
rw [iteratedFDerivWithin_succ_apply_left]
/-- Composition with a linear isometry on the left preserves the norm of the iterated
derivative within a set. -/
theorem LinearIsometry.norm_iteratedFDerivWithin_comp_left {f : E → F} (g : F →ₗᵢ[𝕜] G)
(hf : ContDiffWithinAt 𝕜 n f s x) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) {i : ℕ} (hi : i ≤ n) :
‖iteratedFDerivWithin 𝕜 i (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
have :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
g.toContinuousLinearMap.compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
g.toContinuousLinearMap.iteratedFDerivWithin_comp_left hf hs hx hi
rw [this]
apply LinearIsometry.norm_compContinuousMultilinearMap
/-- Composition with a linear isometry on the left preserves the norm of the iterated
derivative. -/
theorem LinearIsometry.norm_iteratedFDeriv_comp_left {f : E → F} (g : F →ₗᵢ[𝕜] G)
(hf : ContDiffAt 𝕜 n f x) {i : ℕ} (hi : i ≤ n) :
‖iteratedFDeriv 𝕜 i (g ∘ f) x‖ = ‖iteratedFDeriv 𝕜 i f x‖ := by
simp only [← iteratedFDerivWithin_univ]
exact g.norm_iteratedFDerivWithin_comp_left hf.contDiffWithinAt uniqueDiffOn_univ (mem_univ x) hi
/-- Composition with a linear isometry equiv on the left preserves the norm of the iterated
derivative within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_left (g : F ≃ₗᵢ[𝕜] G) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) (i : ℕ) :
‖iteratedFDerivWithin 𝕜 i (g ∘ f) s x‖ = ‖iteratedFDerivWithin 𝕜 i f s x‖ := by
have :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(g : F →L[𝕜] G).compContinuousMultilinearMap (iteratedFDerivWithin 𝕜 i f s x) :=
g.toContinuousLinearEquiv.iteratedFDerivWithin_comp_left f hs hx i
rw [this]
apply LinearIsometry.norm_compContinuousMultilinearMap g.toLinearIsometry
/-- Composition with a linear isometry equiv on the left preserves the norm of the iterated
derivative. -/
theorem LinearIsometryEquiv.norm_iteratedFDeriv_comp_left (g : F ≃ₗᵢ[𝕜] G) (f : E → F) (x : E)
(i : ℕ) : ‖iteratedFDeriv 𝕜 i (g ∘ f) x‖ = ‖iteratedFDeriv 𝕜 i f x‖ := by
rw [← iteratedFDerivWithin_univ, ← iteratedFDerivWithin_univ]
apply g.norm_iteratedFDerivWithin_comp_left f uniqueDiffOn_univ (mem_univ x) i
/-- Composition by continuous linear equivs on the left respects higher differentiability at a
point in a domain. -/
theorem ContinuousLinearEquiv.comp_contDiffWithinAt_iff (e : F ≃L[𝕜] G) :
ContDiffWithinAt 𝕜 n (e ∘ f) s x ↔ ContDiffWithinAt 𝕜 n f s x :=
⟨fun H => by
simpa only [Function.comp_def, e.symm.coe_coe, e.symm_apply_apply] using
H.continuousLinearMap_comp (e.symm : G →L[𝕜] F),
fun H => H.continuousLinearMap_comp (e : F →L[𝕜] G)⟩
/-- Composition by continuous linear equivs on the left respects higher differentiability at a
point. -/
theorem ContinuousLinearEquiv.comp_contDiffAt_iff (e : F ≃L[𝕜] G) :
ContDiffAt 𝕜 n (e ∘ f) x ↔ ContDiffAt 𝕜 n f x := by
simp only [← contDiffWithinAt_univ, e.comp_contDiffWithinAt_iff]
/-- Composition by continuous linear equivs on the left respects higher differentiability on
domains. -/
theorem ContinuousLinearEquiv.comp_contDiffOn_iff (e : F ≃L[𝕜] G) :
ContDiffOn 𝕜 n (e ∘ f) s ↔ ContDiffOn 𝕜 n f s := by
simp [ContDiffOn, e.comp_contDiffWithinAt_iff]
/-- Composition by continuous linear equivs on the left respects higher differentiability. -/
theorem ContinuousLinearEquiv.comp_contDiff_iff (e : F ≃L[𝕜] G) :
ContDiff 𝕜 n (e ∘ f) ↔ ContDiff 𝕜 n f := by
simp only [← contDiffOn_univ, e.comp_contDiffOn_iff]
/-- If `f` admits a Taylor series `p` in a set `s`, and `g` is linear, then `f ∘ g` admits a Taylor
series in `g ⁻¹' s`, whose `k`-th term is given by `p k (g v₁, ..., g vₖ)` . -/
theorem HasFTaylorSeriesUpToOn.compContinuousLinearMap
(hf : HasFTaylorSeriesUpToOn n f p s) (g : G →L[𝕜] E) :
HasFTaylorSeriesUpToOn n (f ∘ g) (fun x k => (p (g x) k).compContinuousLinearMap fun _ => g)
(g ⁻¹' s) := by
let A : ∀ m : ℕ, (E[×m]→L[𝕜] F) → G[×m]→L[𝕜] F := fun m h => h.compContinuousLinearMap fun _ => g
have hA : ∀ m, IsBoundedLinearMap 𝕜 (A m) := fun m =>
isBoundedLinearMap_continuousMultilinearMap_comp_linear g
constructor
· intro x hx
simp only [(hf.zero_eq (g x) hx).symm, Function.comp_apply]
change (p (g x) 0 fun _ : Fin 0 => g 0) = p (g x) 0 0
rw [ContinuousLinearMap.map_zero]
rfl
· intro m hm x hx
convert (hA m).hasFDerivAt.comp_hasFDerivWithinAt x
((hf.fderivWithin m hm (g x) hx).comp x g.hasFDerivWithinAt (Subset.refl _))
ext y v
change p (g x) (Nat.succ m) (g ∘ cons y v) = p (g x) m.succ (cons (g y) (g ∘ v))
rw [comp_cons]
· intro m hm
exact (hA m).continuous.comp_continuousOn <| (hf.cont m hm).comp g.continuous.continuousOn <|
Subset.refl _
/-- Composition by continuous linear maps on the right preserves `C^n` functions at a point on
a domain. -/
theorem ContDiffWithinAt.comp_continuousLinearMap {x : G} (g : G →L[𝕜] E)
(hf : ContDiffWithinAt 𝕜 n f s (g x)) : ContDiffWithinAt 𝕜 n (f ∘ g) (g ⁻¹' s) x := by
match n with
| ω =>
obtain ⟨u, hu, p, hp, h'p⟩ := hf
refine ⟨g ⁻¹' u, ?_, _, hp.compContinuousLinearMap g, ?_⟩
· refine g.continuous.continuousWithinAt.tendsto_nhdsWithin ?_ hu
exact (mapsTo_singleton.2 <| mem_singleton _).union_union (mapsTo_preimage _ _)
· intro i
change AnalyticOn 𝕜 (fun x ↦
ContinuousMultilinearMap.compContinuousLinearMapL (fun _ ↦ g) (p (g x) i)) (⇑g ⁻¹' u)
apply AnalyticOn.comp _ _ (Set.mapsTo_univ _ _)
· exact ContinuousLinearEquiv.analyticOn _ _
· exact (h'p i).comp (g.analyticOn _) (mapsTo_preimage _ _)
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
refine ⟨g ⁻¹' u, ?_, _, hp.compContinuousLinearMap g⟩
refine g.continuous.continuousWithinAt.tendsto_nhdsWithin ?_ hu
exact (mapsTo_singleton.2 <| mem_singleton _).union_union (mapsTo_preimage _ _)
/-- Composition by continuous linear maps on the right preserves `C^n` functions on domains. -/
theorem ContDiffOn.comp_continuousLinearMap (hf : ContDiffOn 𝕜 n f s) (g : G →L[𝕜] E) :
ContDiffOn 𝕜 n (f ∘ g) (g ⁻¹' s) := fun x hx => (hf (g x) hx).comp_continuousLinearMap g
/-- Composition by continuous linear maps on the right preserves `C^n` functions. -/
theorem ContDiff.comp_continuousLinearMap {f : E → F} {g : G →L[𝕜] E} (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n (f ∘ g) :=
contDiffOn_univ.1 <| ContDiffOn.comp_continuousLinearMap (contDiffOn_univ.2 hf) _
/-- The iterated derivative within a set of the composition with a linear map on the right is
obtained by composing the iterated derivative with the linear map. -/
theorem ContinuousLinearMap.iteratedFDerivWithin_comp_right {f : E → F} (g : G →L[𝕜] E)
(hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s) (h's : UniqueDiffOn 𝕜 (g ⁻¹' s)) {x : G}
(hx : g x ∈ s) {i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g :=
((((hf.of_le hi).ftaylorSeriesWithin hs).compContinuousLinearMap
g).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl h's hx).symm
/-- The iterated derivative within a set of the composition with a linear equiv on the right is
obtained by composing the iterated derivative with the linear equiv. -/
theorem ContinuousLinearEquiv.iteratedFDerivWithin_comp_right (g : G ≃L[𝕜] E) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) {x : G} (hx : g x ∈ s) (i : ℕ) :
iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g := by
induction' i with i IH generalizing x
· ext1
simp only [iteratedFDerivWithin_zero_apply, comp_apply,
ContinuousMultilinearMap.compContinuousLinearMap_apply]
· ext1 m
simp only [ContinuousMultilinearMap.compContinuousLinearMap_apply,
ContinuousLinearEquiv.coe_coe, iteratedFDerivWithin_succ_apply_left]
have : fderivWithin 𝕜 (iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s)) (g ⁻¹' s) x =
fderivWithin 𝕜
(ContinuousLinearEquiv.continuousMultilinearMapCongrLeft _ (fun _x : Fin i => g) ∘
(iteratedFDerivWithin 𝕜 i f s ∘ g)) (g ⁻¹' s) x :=
fderivWithin_congr' (@IH) hx
rw [this, ContinuousLinearEquiv.comp_fderivWithin _ (g.uniqueDiffOn_preimage_iff.2 hs x hx)]
simp only [ContinuousLinearMap.coe_comp', ContinuousLinearEquiv.coe_coe, comp_apply,
ContinuousLinearEquiv.continuousMultilinearMapCongrLeft_apply,
ContinuousMultilinearMap.compContinuousLinearMap_apply]
rw [ContinuousLinearEquiv.comp_right_fderivWithin _ (g.uniqueDiffOn_preimage_iff.2 hs x hx),
ContinuousLinearMap.coe_comp', coe_coe, comp_apply, tail_def, tail_def]
/-- The iterated derivative of the composition with a linear map on the right is
obtained by composing the iterated derivative with the linear map. -/
theorem ContinuousLinearMap.iteratedFDeriv_comp_right (g : G →L[𝕜] E) {f : E → F}
(hf : ContDiff 𝕜 n f) (x : G) {i : ℕ} (hi : i ≤ n) :
iteratedFDeriv 𝕜 i (f ∘ g) x =
(iteratedFDeriv 𝕜 i f (g x)).compContinuousLinearMap fun _ => g := by
simp only [← iteratedFDerivWithin_univ]
exact g.iteratedFDerivWithin_comp_right hf.contDiffOn uniqueDiffOn_univ uniqueDiffOn_univ
(mem_univ _) hi
/-- Composition with a linear isometry on the right preserves the norm of the iterated derivative
within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDerivWithin_comp_right (g : G ≃ₗᵢ[𝕜] E) (f : E → F)
(hs : UniqueDiffOn 𝕜 s) {x : G} (hx : g x ∈ s) (i : ℕ) :
‖iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x‖ = ‖iteratedFDerivWithin 𝕜 i f s (g x)‖ := by
have : iteratedFDerivWithin 𝕜 i (f ∘ g) (g ⁻¹' s) x =
(iteratedFDerivWithin 𝕜 i f s (g x)).compContinuousLinearMap fun _ => g :=
g.toContinuousLinearEquiv.iteratedFDerivWithin_comp_right f hs hx i
rw [this, ContinuousMultilinearMap.norm_compContinuous_linearIsometryEquiv]
/-- Composition with a linear isometry on the right preserves the norm of the iterated derivative
within a set. -/
theorem LinearIsometryEquiv.norm_iteratedFDeriv_comp_right (g : G ≃ₗᵢ[𝕜] E) (f : E → F) (x : G)
(i : ℕ) : ‖iteratedFDeriv 𝕜 i (f ∘ g) x‖ = ‖iteratedFDeriv 𝕜 i f (g x)‖ := by
simp only [← iteratedFDerivWithin_univ]
apply g.norm_iteratedFDerivWithin_comp_right f uniqueDiffOn_univ (mem_univ (g x)) i
/-- Composition by continuous linear equivs on the right respects higher differentiability at a
point in a domain. -/
theorem ContinuousLinearEquiv.contDiffWithinAt_comp_iff (e : G ≃L[𝕜] E) :
ContDiffWithinAt 𝕜 n (f ∘ e) (e ⁻¹' s) (e.symm x) ↔ ContDiffWithinAt 𝕜 n f s x := by
constructor
· intro H
simpa [← preimage_comp, Function.comp_def] using H.comp_continuousLinearMap (e.symm : E →L[𝕜] G)
· intro H
rw [← e.apply_symm_apply x, ← e.coe_coe] at H
exact H.comp_continuousLinearMap _
/-- Composition by continuous linear equivs on the right respects higher differentiability at a
point. -/
theorem ContinuousLinearEquiv.contDiffAt_comp_iff (e : G ≃L[𝕜] E) :
ContDiffAt 𝕜 n (f ∘ e) (e.symm x) ↔ ContDiffAt 𝕜 n f x := by
rw [← contDiffWithinAt_univ, ← contDiffWithinAt_univ, ← preimage_univ]
exact e.contDiffWithinAt_comp_iff
/-- Composition by continuous linear equivs on the right respects higher differentiability on
domains. -/
theorem ContinuousLinearEquiv.contDiffOn_comp_iff (e : G ≃L[𝕜] E) :
ContDiffOn 𝕜 n (f ∘ e) (e ⁻¹' s) ↔ ContDiffOn 𝕜 n f s :=
⟨fun H => by simpa [Function.comp_def] using H.comp_continuousLinearMap (e.symm : E →L[𝕜] G),
fun H => H.comp_continuousLinearMap (e : G →L[𝕜] E)⟩
/-- Composition by continuous linear equivs on the right respects higher differentiability. -/
theorem ContinuousLinearEquiv.contDiff_comp_iff (e : G ≃L[𝕜] E) :
ContDiff 𝕜 n (f ∘ e) ↔ ContDiff 𝕜 n f := by
rw [← contDiffOn_univ, ← contDiffOn_univ, ← preimage_univ]
exact e.contDiffOn_comp_iff
end linear
/-! ### The Cartesian product of two C^n functions is C^n. -/
section prod
/-- If two functions `f` and `g` admit Taylor series `p` and `q` in a set `s`, then the cartesian
product of `f` and `g` admits the cartesian product of `p` and `q` as a Taylor series. -/
theorem HasFTaylorSeriesUpToOn.prodMk {n : WithTop ℕ∞}
(hf : HasFTaylorSeriesUpToOn n f p s) {g : E → G}
{q : E → FormalMultilinearSeries 𝕜 E G} (hg : HasFTaylorSeriesUpToOn n g q s) :
HasFTaylorSeriesUpToOn n (fun y => (f y, g y)) (fun y k => (p y k).prod (q y k)) s := by
set L := fun m => ContinuousMultilinearMap.prodL 𝕜 (fun _ : Fin m => E) F G
constructor
· intro x hx; rw [← hf.zero_eq x hx, ← hg.zero_eq x hx]; rfl
· intro m hm x hx
convert (L m).hasFDerivAt.comp_hasFDerivWithinAt x
((hf.fderivWithin m hm x hx).prodMk (hg.fderivWithin m hm x hx))
· intro m hm
exact (L m).continuous.comp_continuousOn ((hf.cont m hm).prodMk (hg.cont m hm))
@[deprecated (since := "2025-03-09")]
alias HasFTaylorSeriesUpToOn.prod := HasFTaylorSeriesUpToOn.prodMk
/-- The cartesian product of `C^n` functions at a point in a domain is `C^n`. -/
theorem ContDiffWithinAt.prodMk {s : Set E} {f : E → F} {g : E → G}
(hf : ContDiffWithinAt 𝕜 n f s x) (hg : ContDiffWithinAt 𝕜 n g s x) :
ContDiffWithinAt 𝕜 n (fun x : E => (f x, g x)) s x := by
match n with
| ω =>
obtain ⟨u, hu, p, hp, h'p⟩ := hf
obtain ⟨v, hv, q, hq, h'q⟩ := hg
refine ⟨u ∩ v, Filter.inter_mem hu hv, _,
(hp.mono inter_subset_left).prodMk (hq.mono inter_subset_right), fun i ↦ ?_⟩
change AnalyticOn 𝕜 (fun x ↦ ContinuousMultilinearMap.prodL _ _ _ _ (p x i, q x i)) (u ∩ v)
apply (LinearIsometryEquiv.analyticOnNhd _ _).comp_analyticOn _ (Set.mapsTo_univ _ _)
exact ((h'p i).mono inter_subset_left).prod ((h'q i).mono inter_subset_right)
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
rcases hg m hm with ⟨v, hv, q, hq⟩
exact ⟨u ∩ v, Filter.inter_mem hu hv, _,
(hp.mono inter_subset_left).prodMk (hq.mono inter_subset_right)⟩
@[deprecated (since := "2025-03-09")]
alias ContDiffWithinAt.prod := ContDiffWithinAt.prodMk
/-- The cartesian product of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.prodMk {s : Set E} {f : E → F} {g : E → G} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x : E => (f x, g x)) s := fun x hx =>
(hf x hx).prodMk (hg x hx)
@[deprecated (since := "2025-03-09")]
alias ContDiffOn.prod := ContDiffOn.prodMk
/-- The cartesian product of `C^n` functions at a point is `C^n`. -/
theorem ContDiffAt.prodMk {f : E → F} {g : E → G} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x : E => (f x, g x)) x :=
contDiffWithinAt_univ.1 <| hf.contDiffWithinAt.prodMk hg.contDiffWithinAt
@[deprecated (since := "2025-03-09")]
alias ContDiffAt.prod := ContDiffAt.prodMk
/-- The cartesian product of `C^n` functions is `C^n`. -/
theorem ContDiff.prodMk {f : E → F} {g : E → G} (hf : ContDiff 𝕜 n f) (hg : ContDiff 𝕜 n g) :
ContDiff 𝕜 n fun x : E => (f x, g x) :=
contDiffOn_univ.1 <| hf.contDiffOn.prodMk hg.contDiffOn
@[deprecated (since := "2025-03-09")]
alias ContDiff.prod := ContDiff.prodMk
end prod
section comp
/-!
### Composition of `C^n` functions
We show that the composition of `C^n` functions is `C^n`. One way to do this would be to
use the following simple inductive proof. Assume it is done for `n`.
Then, to check it for `n+1`, one needs to check that the derivative of `g ∘ f` is `C^n`, i.e.,
that `Dg(f x) ⬝ Df(x)` is `C^n`. The term `Dg (f x)` is the composition of two `C^n` functions, so
it is `C^n` by the inductive assumption. The term `Df(x)` is also `C^n`. Then, the matrix
multiplication is the application of a bilinear map (which is `C^∞`, and therefore `C^n`) to
`x ↦ (Dg(f x), Df x)`. As the composition of two `C^n` maps, it is again `C^n`, and we are done.
There are two difficulties in this proof.
The first one is that it is an induction over all Banach
spaces. In Lean, this is only possible if they belong to a fixed universe. One could formalize this
by first proving the statement in this case, and then extending the result to general universes
by embedding all the spaces we consider in a common universe through `ULift`.
The second one is that it does not work cleanly for analytic maps: for this case, we need to
exhibit a whole sequence of derivatives which are all analytic, not just finitely many of them, so
an induction is never enough at a finite step.
Both these difficulties can be overcome with some cost. However, we choose a different path: we
write down an explicit formula for the `n`-th derivative of `g ∘ f` in terms of derivatives of
`g` and `f` (this is the formula of Faa-Di Bruno) and use this formula to get a suitable Taylor
expansion for `g ∘ f`. Writing down the formula of Faa-Di Bruno is not easy as the formula is quite
intricate, but it is also useful for other purposes and once available it makes the proof here
essentially trivial.
-/
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x) (st : MapsTo f s t) :
ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
match n with
| ω =>
have h'f : ContDiffWithinAt 𝕜 ω f s x := hf
obtain ⟨u, hu, p, hp, h'p⟩ := h'f
obtain ⟨v, hv, q, hq, h'q⟩ := hg
let w := insert x s ∩ (u ∩ f ⁻¹' v)
have wv : w ⊆ f ⁻¹' v := fun y hy => hy.2.2
have wu : w ⊆ u := fun y hy => hy.2.1
refine ⟨w, ?_, fun y ↦ (q (f y)).taylorComp (p y), hq.comp (hp.mono wu) wv, ?_⟩
· apply inter_mem self_mem_nhdsWithin (inter_mem hu ?_)
apply (continuousWithinAt_insert_self.2 hf.continuousWithinAt).preimage_mem_nhdsWithin'
apply nhdsWithin_mono _ _ hv
simp only [image_insert_eq]
apply insert_subset_insert
exact image_subset_iff.mpr st
· have : AnalyticOn 𝕜 f w := by
have : AnalyticOn 𝕜 (fun y ↦ (continuousMultilinearCurryFin0 𝕜 E F).symm (f y)) w :=
((h'p 0).mono wu).congr fun y hy ↦ (hp.zero_eq' (wu hy)).symm
have : AnalyticOn 𝕜 (fun y ↦ (continuousMultilinearCurryFin0 𝕜 E F)
((continuousMultilinearCurryFin0 𝕜 E F).symm (f y))) w :=
AnalyticOnNhd.comp_analyticOn (LinearIsometryEquiv.analyticOnNhd _ _ ) this
(mapsTo_univ _ _)
simpa using this
exact analyticOn_taylorComp h'q (fun n ↦ (h'p n).mono wu) this wv
| (n : ℕ∞) =>
intro m hm
rcases hf m hm with ⟨u, hu, p, hp⟩
rcases hg m hm with ⟨v, hv, q, hq⟩
let w := insert x s ∩ (u ∩ f ⁻¹' v)
have wv : w ⊆ f ⁻¹' v := fun y hy => hy.2.2
have wu : w ⊆ u := fun y hy => hy.2.1
refine ⟨w, ?_, fun y ↦ (q (f y)).taylorComp (p y), hq.comp (hp.mono wu) wv⟩
apply inter_mem self_mem_nhdsWithin (inter_mem hu ?_)
apply (continuousWithinAt_insert_self.2 hf.continuousWithinAt).preimage_mem_nhdsWithin'
apply nhdsWithin_mono _ _ hv
simp only [image_insert_eq]
apply insert_subset_insert
exact image_subset_iff.mpr st
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.comp {s : Set E} {t : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g t)
(hf : ContDiffOn 𝕜 n f s) (st : MapsTo f s t) : ContDiffOn 𝕜 n (g ∘ f) s :=
fun x hx ↦ ContDiffWithinAt.comp x (hg (f x) (st hx)) (hf x hx) st
/-- The composition of `C^n` functions on domains is `C^n`. -/
theorem ContDiffOn.comp_inter
{s : Set E} {t : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g t)
(hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) :=
hg.comp (hf.mono inter_subset_left) inter_subset_right
@[deprecated (since := "2024-10-30")] alias ContDiffOn.comp' := ContDiffOn.comp_inter
/-- The composition of a `C^n` function on a domain with a `C^n` function is `C^n`. -/
theorem ContDiff.comp_contDiffOn {s : Set E} {g : F → G} {f : E → F} (hg : ContDiff 𝕜 n g)
(hf : ContDiffOn 𝕜 n f s) : ContDiffOn 𝕜 n (g ∘ f) s :=
(contDiffOn_univ.2 hg).comp hf (mapsTo_univ _ _)
theorem ContDiffOn.comp_contDiff {s : Set F} {g : F → G} {f : E → F} (hg : ContDiffOn 𝕜 n g s)
(hf : ContDiff 𝕜 n f) (hs : ∀ x, f x ∈ s) : ContDiff 𝕜 n (g ∘ f) := by
rw [← contDiffOn_univ] at *
exact hg.comp hf fun x _ => hs x
theorem ContDiffOn.image_comp_contDiff {s : Set E} {g : F → G} {f : E → F}
(hg : ContDiffOn 𝕜 n g (f '' s)) (hf : ContDiff 𝕜 n f) : ContDiffOn 𝕜 n (g ∘ f) s :=
hg.comp hf.contDiffOn (s.mapsTo_image f)
/-- The composition of `C^n` functions is `C^n`. -/
theorem ContDiff.comp {g : F → G} {f : E → F} (hg : ContDiff 𝕜 n g) (hf : ContDiff 𝕜 n f) :
ContDiff 𝕜 n (g ∘ f) :=
contDiffOn_univ.1 <| ContDiffOn.comp (contDiffOn_univ.2 hg) (contDiffOn_univ.2 hf) (subset_univ _)
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp_of_eq {s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x) (st : MapsTo f s t)
(hy : f x = y) :
ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp x hf st
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_mem_nhdsWithin_image
{s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : t ∈ 𝓝[f '' s] f x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
(hg.mono_of_mem_nhdsWithin hs).comp x hf (subset_preimage_image f s)
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_mem_nhdsWithin_image_of_eq
{s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : t ∈ 𝓝[f '' s] f x) (hy : f x = y) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp_of_mem_nhdsWithin_image x hf hs
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp_inter {s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) x :=
hg.comp x (hf.mono inter_subset_left) inter_subset_right
/-- The composition of `C^n` functions at points in domains is `C^n`. -/
theorem ContDiffWithinAt.comp_inter_of_eq {s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F}
(x : E) (hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x) (hy : f x = y) :
ContDiffWithinAt 𝕜 n (g ∘ f) (s ∩ f ⁻¹' t) x := by
subst hy; exact hg.comp_inter x hf
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_preimage_mem_nhdsWithin
{s : Set E} {t : Set F} {g : F → G} {f : E → F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : f ⁻¹' t ∈ 𝓝[s] x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
(hg.comp_inter x hf).mono_of_mem_nhdsWithin (inter_mem self_mem_nhdsWithin hs)
/-- The composition of `C^n` functions at points in domains is `C^n`,
with a weaker condition on `s` and `t`. -/
theorem ContDiffWithinAt.comp_of_preimage_mem_nhdsWithin_of_eq
{s : Set E} {t : Set F} {g : F → G} {f : E → F} {y : F} (x : E)
(hg : ContDiffWithinAt 𝕜 n g t y) (hf : ContDiffWithinAt 𝕜 n f s x)
(hs : f ⁻¹' t ∈ 𝓝[s] x) (hy : f x = y) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp_of_preimage_mem_nhdsWithin x hf hs
theorem ContDiffAt.comp_contDiffWithinAt (x : E) (hg : ContDiffAt 𝕜 n g (f x))
(hf : ContDiffWithinAt 𝕜 n f s x) : ContDiffWithinAt 𝕜 n (g ∘ f) s x :=
hg.comp x hf (mapsTo_univ _ _)
theorem ContDiffAt.comp_contDiffWithinAt_of_eq {y : F} (x : E) (hg : ContDiffAt 𝕜 n g y)
(hf : ContDiffWithinAt 𝕜 n f s x) (hy : f x = y) : ContDiffWithinAt 𝕜 n (g ∘ f) s x := by
subst hy; exact hg.comp_contDiffWithinAt x hf
/-- The composition of `C^n` functions at points is `C^n`. -/
nonrec theorem ContDiffAt.comp (x : E) (hg : ContDiffAt 𝕜 n g (f x)) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (g ∘ f) x :=
hg.comp x hf (mapsTo_univ _ _)
theorem ContDiff.comp_contDiffWithinAt {g : F → G} {f : E → F} (h : ContDiff 𝕜 n g)
(hf : ContDiffWithinAt 𝕜 n f t x) : ContDiffWithinAt 𝕜 n (g ∘ f) t x :=
haveI : ContDiffWithinAt 𝕜 n g univ (f x) := h.contDiffAt.contDiffWithinAt
this.comp x hf (subset_univ _)
theorem ContDiff.comp_contDiffAt {g : F → G} {f : E → F} (x : E) (hg : ContDiff 𝕜 n g)
(hf : ContDiffAt 𝕜 n f x) : ContDiffAt 𝕜 n (g ∘ f) x :=
hg.comp_contDiffWithinAt hf
theorem iteratedFDerivWithin_comp_of_eventually_mem {t : Set F}
(hg : ContDiffWithinAt 𝕜 n g t (f x)) (hf : ContDiffWithinAt 𝕜 n f s x)
(ht : UniqueDiffOn 𝕜 t) (hs : UniqueDiffOn 𝕜 s) (hxs : x ∈ s) (hst : ∀ᶠ y in 𝓝[s] x, f y ∈ t)
{i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(ftaylorSeriesWithin 𝕜 g t (f x)).taylorComp (ftaylorSeriesWithin 𝕜 f s x) i := by
obtain ⟨u, hxu, huo, hfu, hgu⟩ : ∃ u, x ∈ u ∧ IsOpen u ∧
HasFTaylorSeriesUpToOn i f (ftaylorSeriesWithin 𝕜 f s) (s ∩ u) ∧
HasFTaylorSeriesUpToOn i g (ftaylorSeriesWithin 𝕜 g t) (f '' (s ∩ u)) := by
have hxt : f x ∈ t := hst.self_of_nhdsWithin hxs
have hf_tendsto : Tendsto f (𝓝[s] x) (𝓝[t] (f x)) :=
tendsto_nhdsWithin_iff.mpr ⟨hf.continuousWithinAt, hst⟩
have H₁ : ∀ᶠ u in (𝓝[s] x).smallSets,
HasFTaylorSeriesUpToOn i f (ftaylorSeriesWithin 𝕜 f s) u :=
hf.eventually_hasFTaylorSeriesUpToOn hs hxs hi
have H₂ : ∀ᶠ u in (𝓝[s] x).smallSets,
HasFTaylorSeriesUpToOn i g (ftaylorSeriesWithin 𝕜 g t) (f '' u) :=
hf_tendsto.image_smallSets.eventually (hg.eventually_hasFTaylorSeriesUpToOn ht hxt hi)
rcases (nhdsWithin_basis_open _ _).smallSets.eventually_iff.mp (H₁.and H₂)
with ⟨u, ⟨hxu, huo⟩, hu⟩
exact ⟨u, hxu, huo, hu (by simp [inter_comm])⟩
exact .symm <| (hgu.comp hfu (mapsTo_image _ _)).eq_iteratedFDerivWithin_of_uniqueDiffOn le_rfl
(hs.inter huo) ⟨hxs, hxu⟩ |>.trans <| iteratedFDerivWithin_inter_open huo hxu
theorem iteratedFDerivWithin_comp {t : Set F} (hg : ContDiffWithinAt 𝕜 n g t (f x))
(hf : ContDiffWithinAt 𝕜 n f s x) (ht : UniqueDiffOn 𝕜 t) (hs : UniqueDiffOn 𝕜 s)
(hx : x ∈ s) (hst : MapsTo f s t) {i : ℕ} (hi : i ≤ n) :
iteratedFDerivWithin 𝕜 i (g ∘ f) s x =
(ftaylorSeriesWithin 𝕜 g t (f x)).taylorComp (ftaylorSeriesWithin 𝕜 f s x) i :=
iteratedFDerivWithin_comp_of_eventually_mem hg hf ht hs hx (eventually_mem_nhdsWithin.mono hst) hi
theorem iteratedFDeriv_comp (hg : ContDiffAt 𝕜 n g (f x)) (hf : ContDiffAt 𝕜 n f x)
{i : ℕ} (hi : i ≤ n) :
iteratedFDeriv 𝕜 i (g ∘ f) x =
(ftaylorSeries 𝕜 g (f x)).taylorComp (ftaylorSeries 𝕜 f x) i := by
simp only [← iteratedFDerivWithin_univ, ← ftaylorSeriesWithin_univ]
exact iteratedFDerivWithin_comp hg.contDiffWithinAt hf.contDiffWithinAt
uniqueDiffOn_univ uniqueDiffOn_univ (mem_univ _) (mapsTo_univ _ _) hi
end comp
/-!
### Smoothness of projections
-/
/-- The first projection in a product is `C^∞`. -/
theorem contDiff_fst : ContDiff 𝕜 n (Prod.fst : E × F → E) :=
IsBoundedLinearMap.contDiff IsBoundedLinearMap.fst
/-- Postcomposing `f` with `Prod.fst` is `C^n` -/
theorem ContDiff.fst {f : E → F × G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (f x).1 :=
contDiff_fst.comp hf
/-- Precomposing `f` with `Prod.fst` is `C^n` -/
theorem ContDiff.fst' {f : E → G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x : E × F => f x.1 :=
hf.comp contDiff_fst
/-- The first projection on a domain in a product is `C^∞`. -/
theorem contDiffOn_fst {s : Set (E × F)} : ContDiffOn 𝕜 n (Prod.fst : E × F → E) s :=
ContDiff.contDiffOn contDiff_fst
theorem ContDiffOn.fst {f : E → F × G} {s : Set E} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (f x).1) s :=
contDiff_fst.comp_contDiffOn hf
/-- The first projection at a point in a product is `C^∞`. -/
theorem contDiffAt_fst {p : E × F} : ContDiffAt 𝕜 n (Prod.fst : E × F → E) p :=
contDiff_fst.contDiffAt
/-- Postcomposing `f` with `Prod.fst` is `C^n` at `(x, y)` -/
theorem ContDiffAt.fst {f : E → F × G} {x : E} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (f x).1) x :=
contDiffAt_fst.comp x hf
/-- Precomposing `f` with `Prod.fst` is `C^n` at `(x, y)` -/
theorem ContDiffAt.fst' {f : E → G} {x : E} {y : F} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x : E × F => f x.1) (x, y) :=
ContDiffAt.comp (x, y) hf contDiffAt_fst
/-- Precomposing `f` with `Prod.fst` is `C^n` at `x : E × F` -/
theorem ContDiffAt.fst'' {f : E → G} {x : E × F} (hf : ContDiffAt 𝕜 n f x.1) :
ContDiffAt 𝕜 n (fun x : E × F => f x.1) x :=
hf.comp x contDiffAt_fst
/-- The first projection within a domain at a point in a product is `C^∞`. -/
theorem contDiffWithinAt_fst {s : Set (E × F)} {p : E × F} :
ContDiffWithinAt 𝕜 n (Prod.fst : E × F → E) s p :=
contDiff_fst.contDiffWithinAt
/-- The second projection in a product is `C^∞`. -/
theorem contDiff_snd : ContDiff 𝕜 n (Prod.snd : E × F → F) :=
IsBoundedLinearMap.contDiff IsBoundedLinearMap.snd
/-- Postcomposing `f` with `Prod.snd` is `C^n` -/
theorem ContDiff.snd {f : E → F × G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (f x).2 :=
contDiff_snd.comp hf
/-- Precomposing `f` with `Prod.snd` is `C^n` -/
theorem ContDiff.snd' {f : F → G} (hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x : E × F => f x.2 :=
hf.comp contDiff_snd
/-- The second projection on a domain in a product is `C^∞`. -/
theorem contDiffOn_snd {s : Set (E × F)} : ContDiffOn 𝕜 n (Prod.snd : E × F → F) s :=
ContDiff.contDiffOn contDiff_snd
theorem ContDiffOn.snd {f : E → F × G} {s : Set E} (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (f x).2) s :=
contDiff_snd.comp_contDiffOn hf
/-- The second projection at a point in a product is `C^∞`. -/
theorem contDiffAt_snd {p : E × F} : ContDiffAt 𝕜 n (Prod.snd : E × F → F) p :=
contDiff_snd.contDiffAt
/-- Postcomposing `f` with `Prod.snd` is `C^n` at `x` -/
theorem ContDiffAt.snd {f : E → F × G} {x : E} (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (f x).2) x :=
contDiffAt_snd.comp x hf
/-- Precomposing `f` with `Prod.snd` is `C^n` at `(x, y)` -/
theorem ContDiffAt.snd' {f : F → G} {x : E} {y : F} (hf : ContDiffAt 𝕜 n f y) :
ContDiffAt 𝕜 n (fun x : E × F => f x.2) (x, y) :=
ContDiffAt.comp (x, y) hf contDiffAt_snd
/-- Precomposing `f` with `Prod.snd` is `C^n` at `x : E × F` -/
theorem ContDiffAt.snd'' {f : F → G} {x : E × F} (hf : ContDiffAt 𝕜 n f x.2) :
ContDiffAt 𝕜 n (fun x : E × F => f x.2) x :=
hf.comp x contDiffAt_snd
/-- The second projection within a domain at a point in a product is `C^∞`. -/
theorem contDiffWithinAt_snd {s : Set (E × F)} {p : E × F} :
ContDiffWithinAt 𝕜 n (Prod.snd : E × F → F) s p :=
contDiff_snd.contDiffWithinAt
section NAry
variable {E₁ E₂ E₃ : Type*}
variable [NormedAddCommGroup E₁] [NormedAddCommGroup E₂] [NormedAddCommGroup E₃]
[NormedSpace 𝕜 E₁] [NormedSpace 𝕜 E₂] [NormedSpace 𝕜 E₃]
theorem ContDiff.comp₂ {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} (hg : ContDiff 𝕜 n g)
(hf₁ : ContDiff 𝕜 n f₁) (hf₂ : ContDiff 𝕜 n f₂) : ContDiff 𝕜 n fun x => g (f₁ x, f₂ x) :=
hg.comp <| hf₁.prodMk hf₂
theorem ContDiffAt.comp₂ {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {x : F}
(hg : ContDiffAt 𝕜 n g (f₁ x, f₂ x))
(hf₁ : ContDiffAt 𝕜 n f₁ x) (hf₂ : ContDiffAt 𝕜 n f₂ x) :
ContDiffAt 𝕜 n (fun x => g (f₁ x, f₂ x)) x :=
hg.comp x (hf₁.prodMk hf₂)
theorem ContDiffAt.comp₂_contDiffWithinAt {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂}
{s : Set F} {x : F} (hg : ContDiffAt 𝕜 n g (f₁ x, f₂ x))
(hf₁ : ContDiffWithinAt 𝕜 n f₁ s x) (hf₂ : ContDiffWithinAt 𝕜 n f₂ s x) :
ContDiffWithinAt 𝕜 n (fun x => g (f₁ x, f₂ x)) s x :=
hg.comp_contDiffWithinAt x (hf₁.prodMk hf₂)
@[deprecated (since := "2024-10-30")]
alias ContDiffAt.comp_contDiffWithinAt₂ := ContDiffAt.comp₂_contDiffWithinAt
theorem ContDiff.comp₂_contDiffAt {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {x : F}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiffAt 𝕜 n f₁ x) (hf₂ : ContDiffAt 𝕜 n f₂ x) :
ContDiffAt 𝕜 n (fun x => g (f₁ x, f₂ x)) x :=
hg.contDiffAt.comp₂ hf₁ hf₂
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffAt₂ := ContDiff.comp₂_contDiffAt
theorem ContDiff.comp₂_contDiffWithinAt {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂}
{s : Set F} {x : F} (hg : ContDiff 𝕜 n g)
(hf₁ : ContDiffWithinAt 𝕜 n f₁ s x) (hf₂ : ContDiffWithinAt 𝕜 n f₂ s x) :
ContDiffWithinAt 𝕜 n (fun x => g (f₁ x, f₂ x)) s x :=
hg.contDiffAt.comp_contDiffWithinAt x (hf₁.prodMk hf₂)
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffWithinAt₂ := ContDiff.comp₂_contDiffWithinAt
theorem ContDiff.comp₂_contDiffOn {g : E₁ × E₂ → G} {f₁ : F → E₁} {f₂ : F → E₂} {s : Set F}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiffOn 𝕜 n f₁ s) (hf₂ : ContDiffOn 𝕜 n f₂ s) :
ContDiffOn 𝕜 n (fun x => g (f₁ x, f₂ x)) s :=
hg.comp_contDiffOn <| hf₁.prodMk hf₂
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffOn₂ := ContDiff.comp₂_contDiffOn
theorem ContDiff.comp₃ {g : E₁ × E₂ × E₃ → G} {f₁ : F → E₁} {f₂ : F → E₂} {f₃ : F → E₃}
(hg : ContDiff 𝕜 n g) (hf₁ : ContDiff 𝕜 n f₁) (hf₂ : ContDiff 𝕜 n f₂) (hf₃ : ContDiff 𝕜 n f₃) :
ContDiff 𝕜 n fun x => g (f₁ x, f₂ x, f₃ x) :=
hg.comp₂ hf₁ <| hf₂.prodMk hf₃
theorem ContDiff.comp₃_contDiffOn {g : E₁ × E₂ × E₃ → G} {f₁ : F → E₁} {f₂ : F → E₂} {f₃ : F → E₃}
{s : Set F} (hg : ContDiff 𝕜 n g) (hf₁ : ContDiffOn 𝕜 n f₁ s) (hf₂ : ContDiffOn 𝕜 n f₂ s)
(hf₃ : ContDiffOn 𝕜 n f₃ s) : ContDiffOn 𝕜 n (fun x => g (f₁ x, f₂ x, f₃ x)) s :=
hg.comp₂_contDiffOn hf₁ <| hf₂.prodMk hf₃
@[deprecated (since := "2024-10-30")]
alias ContDiff.comp_contDiffOn₃ := ContDiff.comp₃_contDiffOn
end NAry
section SpecificBilinearMaps
theorem ContDiff.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} (hg : ContDiff 𝕜 n g)
(hf : ContDiff 𝕜 n f) : ContDiff 𝕜 n fun x => (g x).comp (f x) :=
isBoundedBilinearMap_comp.contDiff.comp₂ (g := fun p => p.1.comp p.2) hg hf
theorem ContDiffOn.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {s : Set X}
(hg : ContDiffOn 𝕜 n g s) (hf : ContDiffOn 𝕜 n f s) :
ContDiffOn 𝕜 n (fun x => (g x).comp (f x)) s :=
(isBoundedBilinearMap_comp (E := E) (F := F) (G := G)).contDiff.comp₂_contDiffOn hg hf
theorem ContDiffAt.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {x : X}
(hg : ContDiffAt 𝕜 n g x) (hf : ContDiffAt 𝕜 n f x) :
ContDiffAt 𝕜 n (fun x => (g x).comp (f x)) x :=
(isBoundedBilinearMap_comp (E := E) (G := G)).contDiff.comp₂_contDiffAt hg hf
theorem ContDiffWithinAt.clm_comp {g : X → F →L[𝕜] G} {f : X → E →L[𝕜] F} {s : Set X} {x : X}
(hg : ContDiffWithinAt 𝕜 n g s x) (hf : ContDiffWithinAt 𝕜 n f s x) :
ContDiffWithinAt 𝕜 n (fun x => (g x).comp (f x)) s x :=
(isBoundedBilinearMap_comp (E := E) (G := G)).contDiff.comp₂_contDiffWithinAt hg hf
theorem ContDiff.clm_apply {f : E → F →L[𝕜] G} {g : E → F} (hf : ContDiff 𝕜 n f)
(hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n fun x => (f x) (g x) :=
isBoundedBilinearMap_apply.contDiff.comp₂ hf hg
theorem ContDiffOn.clm_apply {f : E → F →L[𝕜] G} {g : E → F} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x => (f x) (g x)) s :=
isBoundedBilinearMap_apply.contDiff.comp₂_contDiffOn hf hg
theorem ContDiffAt.clm_apply {f : E → F →L[𝕜] G} {g : E → F} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x => (f x) (g x)) x :=
isBoundedBilinearMap_apply.contDiff.comp₂_contDiffAt hf hg
theorem ContDiffWithinAt.clm_apply {f : E → F →L[𝕜] G} {g : E → F}
(hf : ContDiffWithinAt 𝕜 n f s x) (hg : ContDiffWithinAt 𝕜 n g s x) :
ContDiffWithinAt 𝕜 n (fun x => (f x) (g x)) s x :=
isBoundedBilinearMap_apply.contDiff.comp₂_contDiffWithinAt hf hg
theorem ContDiff.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} (hf : ContDiff 𝕜 n f)
(hg : ContDiff 𝕜 n g) : ContDiff 𝕜 n fun x => (f x).smulRight (g x) :=
isBoundedBilinearMap_smulRight.contDiff.comp₂ (g := fun p => p.1.smulRight p.2) hf hg
theorem ContDiffOn.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} (hf : ContDiffOn 𝕜 n f s)
(hg : ContDiffOn 𝕜 n g s) : ContDiffOn 𝕜 n (fun x => (f x).smulRight (g x)) s :=
(isBoundedBilinearMap_smulRight (E := F)).contDiff.comp₂_contDiffOn hf hg
theorem ContDiffAt.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G} (hf : ContDiffAt 𝕜 n f x)
(hg : ContDiffAt 𝕜 n g x) : ContDiffAt 𝕜 n (fun x => (f x).smulRight (g x)) x :=
(isBoundedBilinearMap_smulRight (E := F)).contDiff.comp₂_contDiffAt hf hg
theorem ContDiffWithinAt.smulRight {f : E → F →L[𝕜] 𝕜} {g : E → G}
(hf : ContDiffWithinAt 𝕜 n f s x) (hg : ContDiffWithinAt 𝕜 n g s x) :
ContDiffWithinAt 𝕜 n (fun x => (f x).smulRight (g x)) s x :=
(isBoundedBilinearMap_smulRight (E := F)).contDiff.comp₂_contDiffWithinAt hf hg
end SpecificBilinearMaps
section ClmApplyConst
/-- Application of a `ContinuousLinearMap` to a constant commutes with `iteratedFDerivWithin`. -/
theorem iteratedFDerivWithin_clm_apply_const_apply
{s : Set E} (hs : UniqueDiffOn 𝕜 s) {c : E → F →L[𝕜] G}
(hc : ContDiffOn 𝕜 n c s) {i : ℕ} (hi : i ≤ n) {x : E} (hx : x ∈ s) {u : F} {m : Fin i → E} :
(iteratedFDerivWithin 𝕜 i (fun y ↦ (c y) u) s x) m = (iteratedFDerivWithin 𝕜 i c s x) m u := by
induction i generalizing x with
| zero => simp
| succ i ih =>
replace hi : (i : WithTop ℕ∞) < n := lt_of_lt_of_le (by norm_cast; simp) hi
have h_deriv_apply : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 i (fun y ↦ (c y) u) s) s :=
(hc.clm_apply contDiffOn_const).differentiableOn_iteratedFDerivWithin hi hs
have h_deriv : DifferentiableOn 𝕜 (iteratedFDerivWithin 𝕜 i c s) s :=
hc.differentiableOn_iteratedFDerivWithin hi hs
simp only [iteratedFDerivWithin_succ_apply_left]
rw [← fderivWithin_continuousMultilinear_apply_const_apply (hs x hx) (h_deriv_apply x hx)]
rw [fderivWithin_congr' (fun x hx ↦ ih hi.le hx) hx]
rw [fderivWithin_clm_apply (hs x hx) (h_deriv.continuousMultilinear_apply_const _ x hx)
(differentiableWithinAt_const u)]
rw [fderivWithin_const_apply]
simp only [ContinuousLinearMap.flip_apply, ContinuousLinearMap.comp_zero, zero_add]
rw [fderivWithin_continuousMultilinear_apply_const_apply (hs x hx) (h_deriv x hx)]
/-- Application of a `ContinuousLinearMap` to a constant commutes with `iteratedFDeriv`. -/
theorem iteratedFDeriv_clm_apply_const_apply
{c : E → F →L[𝕜] G} (hc : ContDiff 𝕜 n c)
{i : ℕ} (hi : i ≤ n) {x : E} {u : F} {m : Fin i → E} :
(iteratedFDeriv 𝕜 i (fun y ↦ (c y) u) x) m = (iteratedFDeriv 𝕜 i c x) m u := by
simp only [← iteratedFDerivWithin_univ]
exact iteratedFDerivWithin_clm_apply_const_apply uniqueDiffOn_univ hc.contDiffOn hi (mem_univ _)
end ClmApplyConst
/-- The natural equivalence `(E × F) × G ≃ E × (F × G)` is smooth.
Warning: if you think you need this lemma, it is likely that you can simplify your proof by
reformulating the lemma that you're applying next using the tips in
Note [continuity lemma statement]
-/
theorem contDiff_prodAssoc {n : WithTop ℕ∞} : ContDiff 𝕜 n <| Equiv.prodAssoc E F G :=
(LinearIsometryEquiv.prodAssoc 𝕜 E F G).contDiff
/-- The natural equivalence `E × (F × G) ≃ (E × F) × G` is smooth.
Warning: see remarks attached to `contDiff_prodAssoc`
-/
theorem contDiff_prodAssoc_symm {n : WithTop ℕ∞} : ContDiff 𝕜 n <| (Equiv.prodAssoc E F G).symm :=
(LinearIsometryEquiv.prodAssoc 𝕜 E F G).symm.contDiff
/-! ### Bundled derivatives are smooth -/
section bundled
/-- One direction of `contDiffWithinAt_succ_iff_hasFDerivWithinAt`, but where all derivatives are
taken within the same set. Version for partial derivatives / functions with parameters. If `f x` is
a `C^n+1` family of functions and `g x` is a `C^n` family of points, then the derivative of `f x` at
`g x` depends in a `C^n` way on `x`. We give a general version of this fact relative to sets which
may not have unique derivatives, in the following form. If `f : E × F → G` is `C^n+1` at
`(x₀, g(x₀))` in `(s ∪ {x₀}) × t ⊆ E × F` and `g : E → F` is `C^n` at `x₀` within some set `s ⊆ E`,
then there is a function `f' : E → F →L[𝕜] G` that is `C^n` at `x₀` within `s` such that for all `x`
sufficiently close to `x₀` within `s ∪ {x₀}` the function `y ↦ f x y` has derivative `f' x` at `g x`
within `t ⊆ F`. For convenience, we return an explicit set of `x`'s where this holds that is a
subset of `s ∪ {x₀}`. We need one additional condition, namely that `t` is a neighborhood of
`g(x₀)` within `g '' s`. -/
theorem ContDiffWithinAt.hasFDerivWithinAt_nhds {f : E → F → G} {g : E → F} {t : Set F} (hn : n ≠ ∞)
{x₀ : E} (hf : ContDiffWithinAt 𝕜 (n + 1) (uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 n g s x₀) (hgt : t ∈ 𝓝[g '' s] g x₀) :
∃ v ∈ 𝓝[insert x₀ s] x₀, v ⊆ insert x₀ s ∧ ∃ f' : E → F →L[𝕜] G,
(∀ x ∈ v, HasFDerivWithinAt (f x) (f' x) t (g x)) ∧
ContDiffWithinAt 𝕜 n (fun x => f' x) s x₀ := by
have hst : insert x₀ s ×ˢ t ∈ 𝓝[(fun x => (x, g x)) '' s] (x₀, g x₀) := by
refine nhdsWithin_mono _ ?_ (nhdsWithin_prod self_mem_nhdsWithin hgt)
simp_rw [image_subset_iff, mk_preimage_prod, preimage_id', subset_inter_iff, subset_insert,
true_and, subset_preimage_image]
obtain ⟨v, hv, hvs, f_an, f', hvf', hf'⟩ :=
(contDiffWithinAt_succ_iff_hasFDerivWithinAt' hn).mp hf
refine
⟨(fun z => (z, g z)) ⁻¹' v ∩ insert x₀ s, ?_, inter_subset_right, fun z =>
(f' (z, g z)).comp (ContinuousLinearMap.inr 𝕜 E F), ?_, ?_⟩
· refine inter_mem ?_ self_mem_nhdsWithin
have := mem_of_mem_nhdsWithin (mem_insert _ _) hv
refine mem_nhdsWithin_insert.mpr ⟨this, ?_⟩
refine (continuousWithinAt_id.prodMk hg.continuousWithinAt).preimage_mem_nhdsWithin' ?_
rw [← nhdsWithin_le_iff] at hst hv ⊢
exact (hst.trans <| nhdsWithin_mono _ <| subset_insert _ _).trans hv
· intro z hz
have := hvf' (z, g z) hz.1
refine this.comp _ (hasFDerivAt_prodMk_right _ _).hasFDerivWithinAt ?_
exact mapsTo'.mpr (image_prodMk_subset_prod_right hz.2)
· exact (hf'.continuousLinearMap_comp <| (ContinuousLinearMap.compL 𝕜 F (E × F) G).flip
(ContinuousLinearMap.inr 𝕜 E F)).comp_of_mem_nhdsWithin_image x₀
(contDiffWithinAt_id.prodMk hg) hst
/-- The most general lemma stating that `x ↦ fderivWithin 𝕜 (f x) t (g x)` is `C^n`
at a point within a set.
To show that `x ↦ D_yf(x,y)g(x)` (taken within `t`) is `C^m` at `x₀` within `s`, we require that
* `f` is `C^n` at `(x₀, g(x₀))` within `(s ∪ {x₀}) × t` for `n ≥ m+1`.
* `g` is `C^m` at `x₀` within `s`;
* Derivatives are unique at `g(x)` within `t` for `x` sufficiently close to `x₀` within `s ∪ {x₀}`;
* `t` is a neighborhood of `g(x₀)` within `g '' s`; -/
theorem ContDiffWithinAt.fderivWithin'' {f : E → F → G} {g : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀)
(ht : ∀ᶠ x in 𝓝[insert x₀ s] x₀, UniqueDiffWithinAt 𝕜 t (g x)) (hmn : m + 1 ≤ n)
(hgt : t ∈ 𝓝[g '' s] g x₀) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
have : ∀ k : ℕ, k ≤ m → ContDiffWithinAt 𝕜 k (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
intro k hkm
obtain ⟨v, hv, -, f', hvf', hf'⟩ :=
(hf.of_le <| (add_le_add_right hkm 1).trans hmn).hasFDerivWithinAt_nhds (by simp)
(hg.of_le hkm) hgt
refine hf'.congr_of_eventuallyEq_insert ?_
filter_upwards [hv, ht]
exact fun y hy h2y => (hvf' y hy).fderivWithin h2y
match m with
| ω =>
obtain rfl : n = ω := by simpa using hmn
obtain ⟨v, hv, -, f', hvf', hf'⟩ := hf.hasFDerivWithinAt_nhds (by simp) hg hgt
refine hf'.congr_of_eventuallyEq_insert ?_
filter_upwards [hv, ht]
exact fun y hy h2y => (hvf' y hy).fderivWithin h2y
| ∞ =>
rw [contDiffWithinAt_infty]
exact fun k ↦ this k (by exact_mod_cast le_top)
| (m : ℕ) => exact this _ le_rfl
/-- A special case of `ContDiffWithinAt.fderivWithin''` where we require that `s ⊆ g⁻¹(t)`. -/
theorem ContDiffWithinAt.fderivWithin' {f : E → F → G} {g : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (insert x₀ s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀)
(ht : ∀ᶠ x in 𝓝[insert x₀ s] x₀, UniqueDiffWithinAt 𝕜 t (g x)) (hmn : m + 1 ≤ n)
(hst : s ⊆ g ⁻¹' t) : ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ :=
hf.fderivWithin'' hg ht hmn <| mem_of_superset self_mem_nhdsWithin <| image_subset_iff.mpr hst
/-- A special case of `ContDiffWithinAt.fderivWithin'` where we require that `x₀ ∈ s` and there
are unique derivatives everywhere within `t`. -/
protected theorem ContDiffWithinAt.fderivWithin {f : E → F → G} {g : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀) (ht : UniqueDiffOn 𝕜 t) (hmn : m + 1 ≤ n) (hx₀ : x₀ ∈ s)
(hst : s ⊆ g ⁻¹' t) : ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x)) s x₀ := by
rw [← insert_eq_self.mpr hx₀] at hf
refine hf.fderivWithin' hg ?_ hmn hst
rw [insert_eq_self.mpr hx₀]
exact eventually_of_mem self_mem_nhdsWithin fun x hx => ht _ (hst hx)
/-- `x ↦ fderivWithin 𝕜 (f x) t (g x) (k x)` is smooth at a point within a set. -/
theorem ContDiffWithinAt.fderivWithin_apply {f : E → F → G} {g k : E → F} {t : Set F}
(hf : ContDiffWithinAt 𝕜 n (Function.uncurry f) (s ×ˢ t) (x₀, g x₀))
(hg : ContDiffWithinAt 𝕜 m g s x₀) (hk : ContDiffWithinAt 𝕜 m k s x₀) (ht : UniqueDiffOn 𝕜 t)
(hmn : m + 1 ≤ n) (hx₀ : x₀ ∈ s) (hst : s ⊆ g ⁻¹' t) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 (f x) t (g x) (k x)) s x₀ :=
(contDiff_fst.clm_apply contDiff_snd).contDiffAt.comp_contDiffWithinAt x₀
((hf.fderivWithin hg ht hmn hx₀ hst).prodMk hk)
/-- `fderivWithin 𝕜 f s` is smooth at `x₀` within `s`. -/
theorem ContDiffWithinAt.fderivWithin_right (hf : ContDiffWithinAt 𝕜 n f s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (fderivWithin 𝕜 f s) s x₀ :=
ContDiffWithinAt.fderivWithin
(ContDiffWithinAt.comp (x₀, x₀) hf contDiffWithinAt_snd <| prod_subset_preimage_snd s s)
contDiffWithinAt_id hs hmn hx₀s (by rw [preimage_id'])
/-- `x ↦ fderivWithin 𝕜 f s x (k x)` is smooth at `x₀` within `s`. -/
theorem ContDiffWithinAt.fderivWithin_right_apply
{f : F → G} {k : F → F} {s : Set F} {x₀ : F}
(hf : ContDiffWithinAt 𝕜 n f s x₀) (hk : ContDiffWithinAt 𝕜 m k s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (fun x => fderivWithin 𝕜 f s x (k x)) s x₀ :=
ContDiffWithinAt.fderivWithin_apply
(ContDiffWithinAt.comp (x₀, x₀) hf contDiffWithinAt_snd <| prod_subset_preimage_snd s s)
contDiffWithinAt_id hk hs hmn hx₀s (by rw [preimage_id'])
-- TODO: can we make a version of `ContDiffWithinAt.fderivWithin` for iterated derivatives?
theorem ContDiffWithinAt.iteratedFDerivWithin_right {i : ℕ} (hf : ContDiffWithinAt 𝕜 n f s x₀)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + i ≤ n) (hx₀s : x₀ ∈ s) :
ContDiffWithinAt 𝕜 m (iteratedFDerivWithin 𝕜 i f s) s x₀ := by
induction' i with i hi generalizing m
· simp only [CharP.cast_eq_zero, add_zero] at hmn
exact (hf.of_le hmn).continuousLinearMap_comp
((continuousMultilinearCurryFin0 𝕜 E F).symm : _ →L[𝕜] E [×0]→L[𝕜] F)
· rw [Nat.cast_succ, add_comm _ 1, ← add_assoc] at hmn
exact ((hi hmn).fderivWithin_right hs le_rfl hx₀s).continuousLinearMap_comp
((continuousMultilinearCurryLeftEquiv 𝕜 (fun _ : Fin (i+1) ↦ E) F).symm :
_ →L[𝕜] E [×(i+1)]→L[𝕜] F)
@[deprecated (since := "2025-01-15")]
alias ContDiffWithinAt.iteratedFderivWithin_right := ContDiffWithinAt.iteratedFDerivWithin_right
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is smooth at `x₀`. -/
protected theorem ContDiffAt.fderiv {f : E → F → G} {g : E → F}
(hf : ContDiffAt 𝕜 n (Function.uncurry f) (x₀, g x₀)) (hg : ContDiffAt 𝕜 m g x₀)
(hmn : m + 1 ≤ n) : ContDiffAt 𝕜 m (fun x => fderiv 𝕜 (f x) (g x)) x₀ := by
simp_rw [← fderivWithin_univ]
refine (ContDiffWithinAt.fderivWithin hf.contDiffWithinAt hg.contDiffWithinAt uniqueDiffOn_univ
hmn (mem_univ x₀) ?_).contDiffAt univ_mem
rw [preimage_univ]
/-- `fderiv 𝕜 f` is smooth at `x₀`. -/
theorem ContDiffAt.fderiv_right (hf : ContDiffAt 𝕜 n f x₀) (hmn : m + 1 ≤ n) :
ContDiffAt 𝕜 m (fderiv 𝕜 f) x₀ :=
ContDiffAt.fderiv (ContDiffAt.comp (x₀, x₀) hf contDiffAt_snd) contDiffAt_id hmn
theorem ContDiffAt.iteratedFDeriv_right {i : ℕ} (hf : ContDiffAt 𝕜 n f x₀)
(hmn : m + i ≤ n) : ContDiffAt 𝕜 m (iteratedFDeriv 𝕜 i f) x₀ := by
rw [← iteratedFDerivWithin_univ, ← contDiffWithinAt_univ] at *
exact hf.iteratedFDerivWithin_right uniqueDiffOn_univ hmn trivial
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is smooth. -/
protected theorem ContDiff.fderiv {f : E → F → G} {g : E → F}
(hf : ContDiff 𝕜 m <| Function.uncurry f) (hg : ContDiff 𝕜 n g) (hnm : n + 1 ≤ m) :
ContDiff 𝕜 n fun x => fderiv 𝕜 (f x) (g x) :=
contDiff_iff_contDiffAt.mpr fun _ => hf.contDiffAt.fderiv hg.contDiffAt hnm
/-- `fderiv 𝕜 f` is smooth. -/
theorem ContDiff.fderiv_right (hf : ContDiff 𝕜 n f) (hmn : m + 1 ≤ n) :
ContDiff 𝕜 m (fderiv 𝕜 f) :=
contDiff_iff_contDiffAt.mpr fun _x => hf.contDiffAt.fderiv_right hmn
theorem ContDiff.iteratedFDeriv_right {i : ℕ} (hf : ContDiff 𝕜 n f)
(hmn : m + i ≤ n) : ContDiff 𝕜 m (iteratedFDeriv 𝕜 i f) :=
contDiff_iff_contDiffAt.mpr fun _x => hf.contDiffAt.iteratedFDeriv_right hmn
/-- `x ↦ fderiv 𝕜 (f x) (g x)` is continuous. -/
theorem Continuous.fderiv {f : E → F → G} {g : E → F}
(hf : ContDiff 𝕜 n <| Function.uncurry f) (hg : Continuous g) (hn : 1 ≤ n) :
Continuous fun x => fderiv 𝕜 (f x) (g x) :=
(hf.fderiv (contDiff_zero.mpr hg) hn).continuous
/-- `x ↦ fderiv 𝕜 (f x) (g x) (k x)` is smooth. -/
theorem ContDiff.fderiv_apply {f : E → F → G} {g k : E → F}
(hf : ContDiff 𝕜 m <| Function.uncurry f) (hg : ContDiff 𝕜 n g) (hk : ContDiff 𝕜 n k)
(hnm : n + 1 ≤ m) : ContDiff 𝕜 n fun x => fderiv 𝕜 (f x) (g x) (k x) :=
(hf.fderiv hg hnm).clm_apply hk
/-- The bundled derivative of a `C^{n+1}` function is `C^n`. -/
theorem contDiffOn_fderivWithin_apply {s : Set E} {f : E → F} (hf : ContDiffOn 𝕜 n f s)
(hs : UniqueDiffOn 𝕜 s) (hmn : m + 1 ≤ n) :
ContDiffOn 𝕜 m (fun p : E × E => (fderivWithin 𝕜 f s p.1 : E →L[𝕜] F) p.2) (s ×ˢ univ) :=
((hf.fderivWithin hs hmn).comp contDiffOn_fst (prod_subset_preimage_fst _ _)).clm_apply
contDiffOn_snd
/-- If a function is at least `C^1`, its bundled derivative (mapping `(x, v)` to `Df(x) v`) is
continuous. -/
theorem ContDiffOn.continuousOn_fderivWithin_apply (hf : ContDiffOn 𝕜 n f s) (hs : UniqueDiffOn 𝕜 s)
(hn : 1 ≤ n) :
ContinuousOn (fun p : E × E => (fderivWithin 𝕜 f s p.1 : E → F) p.2) (s ×ˢ univ) :=
(contDiffOn_fderivWithin_apply (m := 0) hf hs hn).continuousOn
/-- The bundled derivative of a `C^{n+1}` function is `C^n`. -/
theorem ContDiff.contDiff_fderiv_apply {f : E → F} (hf : ContDiff 𝕜 n f) (hmn : m + 1 ≤ n) :
ContDiff 𝕜 m fun p : E × E => (fderiv 𝕜 f p.1 : E →L[𝕜] F) p.2 := by
rw [← contDiffOn_univ] at hf ⊢
rw [← fderivWithin_univ, ← univ_prod_univ]
exact contDiffOn_fderivWithin_apply hf uniqueDiffOn_univ hmn
end bundled
section deriv
/-!
### One dimension
All results up to now have been expressed in terms of the general Fréchet derivative `fderiv`. For
maps defined on the field, the one-dimensional derivative `deriv` is often easier to use. In this
paragraph, we reformulate some higher smoothness results in terms of `deriv`.
-/
variable {f₂ : 𝕜 → F} {s₂ : Set 𝕜}
open ContinuousLinearMap (smulRight)
/-- A function is `C^(n + 1)` on a domain with unique derivatives if and only if it is
differentiable there, and its derivative (formulated with `derivWithin`) is `C^n`. -/
theorem contDiffOn_succ_iff_derivWithin (hs : UniqueDiffOn 𝕜 s₂) :
ContDiffOn 𝕜 (n + 1) f₂ s₂ ↔
DifferentiableOn 𝕜 f₂ s₂ ∧ (n = ω → AnalyticOn 𝕜 f₂ s₂) ∧
ContDiffOn 𝕜 n (derivWithin f₂ s₂) s₂ := by
rw [contDiffOn_succ_iff_fderivWithin hs, and_congr_right_iff]
intro _
constructor
· rintro ⟨h', h⟩
refine ⟨h', ?_⟩
have : derivWithin f₂ s₂ = (fun u : 𝕜 →L[𝕜] F => u 1) ∘ fderivWithin 𝕜 f₂ s₂ := by
ext x; rfl
simp_rw [this]
apply ContDiff.comp_contDiffOn _ h
exact (isBoundedBilinearMap_apply.isBoundedLinearMap_left _).contDiff
· rintro ⟨h', h⟩
refine ⟨h', ?_⟩
have : fderivWithin 𝕜 f₂ s₂ = smulRight (1 : 𝕜 →L[𝕜] 𝕜) ∘ derivWithin f₂ s₂ := by
ext x; simp [derivWithin]
simp only [this]
apply ContDiff.comp_contDiffOn _ h
have : IsBoundedBilinearMap 𝕜 fun _ : (𝕜 →L[𝕜] 𝕜) × F => _ := isBoundedBilinearMap_smulRight
exact (this.isBoundedLinearMap_right _).contDiff
theorem contDiffOn_infty_iff_derivWithin (hs : UniqueDiffOn 𝕜 s₂) :
ContDiffOn 𝕜 ∞ f₂ s₂ ↔ DifferentiableOn 𝕜 f₂ s₂ ∧ ContDiffOn 𝕜 ∞ (derivWithin f₂ s₂) s₂ := by
rw [show ∞ = ∞ + 1 by rfl, contDiffOn_succ_iff_derivWithin hs]
simp
@[deprecated (since := "2024-11-27")]
alias contDiffOn_top_iff_derivWithin := contDiffOn_infty_iff_derivWithin
/-- A function is `C^(n + 1)` on an open domain if and only if it is
differentiable there, and its derivative (formulated with `deriv`) is `C^n`. -/
theorem contDiffOn_succ_iff_deriv_of_isOpen (hs : IsOpen s₂) :
ContDiffOn 𝕜 (n + 1) f₂ s₂ ↔
DifferentiableOn 𝕜 f₂ s₂ ∧ (n = ω → AnalyticOn 𝕜 f₂ s₂) ∧
ContDiffOn 𝕜 n (deriv f₂) s₂ := by
rw [contDiffOn_succ_iff_derivWithin hs.uniqueDiffOn]
exact Iff.rfl.and (Iff.rfl.and (contDiffOn_congr fun _ => derivWithin_of_isOpen hs))
theorem contDiffOn_infty_iff_deriv_of_isOpen (hs : IsOpen s₂) :
ContDiffOn 𝕜 ∞ f₂ s₂ ↔ DifferentiableOn 𝕜 f₂ s₂ ∧ ContDiffOn 𝕜 ∞ (deriv f₂) s₂ := by
rw [show ∞ = ∞ + 1 by rfl, contDiffOn_succ_iff_deriv_of_isOpen hs]
simp
@[deprecated (since := "2024-11-27")]
alias contDiffOn_top_iff_deriv_of_isOpen := contDiffOn_infty_iff_deriv_of_isOpen
protected theorem ContDiffOn.derivWithin (hf : ContDiffOn 𝕜 n f₂ s₂) (hs : UniqueDiffOn 𝕜 s₂)
(hmn : m + 1 ≤ n) : ContDiffOn 𝕜 m (derivWithin f₂ s₂) s₂ :=
((contDiffOn_succ_iff_derivWithin hs).1 (hf.of_le hmn)).2.2
theorem ContDiffOn.deriv_of_isOpen (hf : ContDiffOn 𝕜 n f₂ s₂) (hs : IsOpen s₂) (hmn : m + 1 ≤ n) :
ContDiffOn 𝕜 m (deriv f₂) s₂ :=
(hf.derivWithin hs.uniqueDiffOn hmn).congr fun _ hx => (derivWithin_of_isOpen hs hx).symm
theorem ContDiffOn.continuousOn_derivWithin (h : ContDiffOn 𝕜 n f₂ s₂) (hs : UniqueDiffOn 𝕜 s₂)
(hn : 1 ≤ n) : ContinuousOn (derivWithin f₂ s₂) s₂ := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl] at hn
exact ((contDiffOn_succ_iff_derivWithin hs).1 (h.of_le hn)).2.2.continuousOn
theorem ContDiffOn.continuousOn_deriv_of_isOpen (h : ContDiffOn 𝕜 n f₂ s₂) (hs : IsOpen s₂)
(hn : 1 ≤ n) : ContinuousOn (deriv f₂) s₂ := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl] at hn
exact ((contDiffOn_succ_iff_deriv_of_isOpen hs).1 (h.of_le hn)).2.2.continuousOn
/-- A function is `C^(n + 1)` if and only if it is differentiable,
and its derivative (formulated in terms of `deriv`) is `C^n`. -/
theorem contDiff_succ_iff_deriv :
ContDiff 𝕜 (n + 1) f₂ ↔ Differentiable 𝕜 f₂ ∧ (n = ω → AnalyticOn 𝕜 f₂ univ) ∧
ContDiff 𝕜 n (deriv f₂) := by
simp only [← contDiffOn_univ, contDiffOn_succ_iff_deriv_of_isOpen, isOpen_univ,
differentiableOn_univ]
theorem contDiff_one_iff_deriv :
ContDiff 𝕜 1 f₂ ↔ Differentiable 𝕜 f₂ ∧ Continuous (deriv f₂) := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl, contDiff_succ_iff_deriv]
simp
theorem contDiff_infty_iff_deriv :
ContDiff 𝕜 ∞ f₂ ↔ Differentiable 𝕜 f₂ ∧ ContDiff 𝕜 ∞ (deriv f₂) := by
rw [show (∞ : WithTop ℕ∞) = ∞ + 1 from rfl, contDiff_succ_iff_deriv]
simp
@[deprecated (since := "2024-11-27")] alias contDiff_top_iff_deriv := contDiff_infty_iff_deriv
theorem ContDiff.continuous_deriv (h : ContDiff 𝕜 n f₂) (hn : 1 ≤ n) : Continuous (deriv f₂) := by
rw [show (1 : WithTop ℕ∞) = 0 + 1 from rfl] at hn
exact (contDiff_succ_iff_deriv.mp (h.of_le hn)).2.2.continuous
theorem ContDiff.iterate_deriv :
∀ (n : ℕ) {f₂ : 𝕜 → F}, ContDiff 𝕜 ∞ f₂ → ContDiff 𝕜 ∞ (deriv^[n] f₂)
| 0, _, hf => hf
| n + 1, _, hf => ContDiff.iterate_deriv n (contDiff_infty_iff_deriv.mp hf).2
theorem ContDiff.iterate_deriv' (n : ℕ) :
∀ (k : ℕ) {f₂ : 𝕜 → F}, ContDiff 𝕜 (n + k : ℕ) f₂ → ContDiff 𝕜 n (deriv^[k] f₂)
| 0, _, hf => hf
| k + 1, _, hf => ContDiff.iterate_deriv' _ k (contDiff_succ_iff_deriv.mp hf).2.2
end deriv
| Mathlib/Analysis/Calculus/ContDiff/Basic.lean | 2,104 | 2,107 | |
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Coeff
import Mathlib.Algebra.Polynomial.Degree.Lemmas
import Mathlib.RingTheory.PowerSeries.Basic
/-!
# Formal power series in one variable - Truncation
`PowerSeries.trunc n φ` truncates a (univariate) formal power series
to the polynomial that has the same coefficients as `φ`, for all `m < n`,
and `0` otherwise.
-/
noncomputable section
open Polynomial
open Finset (antidiagonal mem_antidiagonal)
namespace PowerSeries
open Finsupp (single)
variable {R : Type*}
section Trunc
variable [Semiring R]
open Finset Nat
/-- The `n`th truncation of a formal power series to a polynomial -/
def trunc (n : ℕ) (φ : R⟦X⟧) : R[X] :=
∑ m ∈ Ico 0 n, Polynomial.monomial m (coeff R m φ)
theorem coeff_trunc (m) (n) (φ : R⟦X⟧) :
(trunc n φ).coeff m = if m < n then coeff R m φ else 0 := by
simp [trunc, Polynomial.coeff_sum, Polynomial.coeff_monomial, Nat.lt_succ_iff]
@[simp]
theorem trunc_zero (n) : trunc n (0 : R⟦X⟧) = 0 :=
Polynomial.ext fun m => by
rw [coeff_trunc, LinearMap.map_zero, Polynomial.coeff_zero]
split_ifs <;> rfl
@[simp]
theorem trunc_one (n) : trunc (n + 1) (1 : R⟦X⟧) = 1 :=
Polynomial.ext fun m => by
rw [coeff_trunc, coeff_one, Polynomial.coeff_one]
split_ifs with h _ h'
· rfl
· rfl
· subst h'; simp at h
· rfl
@[simp]
theorem trunc_C (n) (a : R) : trunc (n + 1) (C R a) = Polynomial.C a :=
Polynomial.ext fun m => by
rw [coeff_trunc, coeff_C, Polynomial.coeff_C]
split_ifs with H <;> first |rfl|try simp_all
@[simp]
theorem trunc_add (n) (φ ψ : R⟦X⟧) : trunc n (φ + ψ) = trunc n φ + trunc n ψ :=
Polynomial.ext fun m => by
simp only [coeff_trunc, AddMonoidHom.map_add, Polynomial.coeff_add]
split_ifs with H
· rfl
· rw [zero_add]
theorem trunc_succ (f : R⟦X⟧) (n : ℕ) :
trunc n.succ f = trunc n f + Polynomial.monomial n (coeff R n f) := by
rw [trunc, Ico_zero_eq_range, sum_range_succ, trunc, Ico_zero_eq_range]
theorem natDegree_trunc_lt (f : R⟦X⟧) (n) : (trunc (n + 1) f).natDegree < n + 1 := by
rw [Nat.lt_succ_iff, natDegree_le_iff_coeff_eq_zero]
intros
rw [coeff_trunc]
split_ifs with h
· rw [lt_succ, ← not_lt] at h
contradiction
· rfl
@[simp] lemma trunc_zero' {f : R⟦X⟧} : trunc 0 f = 0 := rfl
theorem degree_trunc_lt (f : R⟦X⟧) (n) : (trunc n f).degree < n := by
rw [degree_lt_iff_coeff_zero]
intros
rw [coeff_trunc]
split_ifs with h
· rw [← not_le] at h
contradiction
· rfl
theorem eval₂_trunc_eq_sum_range {S : Type*} [Semiring S] (s : S) (G : R →+* S) (n) (f : R⟦X⟧) :
| (trunc n f).eval₂ G s = ∑ i ∈ range n, G (coeff R i f) * s ^ i := by
cases n with
| zero =>
rw [trunc_zero', range_zero, sum_empty, eval₂_zero]
| succ n =>
have := natDegree_trunc_lt f n
rw [eval₂_eq_sum_range' (hn := this)]
apply sum_congr rfl
| Mathlib/RingTheory/PowerSeries/Trunc.lean | 99 | 106 |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Yaël Dillies
-/
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
/-!
# Integral average of a function
In this file we define `MeasureTheory.average μ f` (notation: `⨍ x, f x ∂μ`) to be the average
value of `f` with respect to measure `μ`. It is defined as `∫ x, f x ∂((μ univ)⁻¹ • μ)`, so it
is equal to zero if `f` is not integrable or if `μ` is an infinite measure. If `μ` is a probability
measure, then the average of any function is equal to its integral.
For the average on a set, we use `⨍ x in s, f x ∂μ` (notation for `⨍ x, f x ∂(μ.restrict s)`). For
average w.r.t. the volume, one can omit `∂volume`.
Both have a version for the Lebesgue integral rather than Bochner.
We prove several version of the first moment method: An integrable function is below/above its
average on a set of positive measure:
* `measure_le_setLAverage_pos` for the Lebesgue integral
* `measure_le_setAverage_pos` for the Bochner integral
## Implementation notes
The average is defined as an integral over `(μ univ)⁻¹ • μ` so that all theorems about Bochner
integrals work for the average without modifications. For theorems that require integrability of a
function, we provide a convenience lemma `MeasureTheory.Integrable.to_average`.
## Tags
integral, center mass, average value
-/
open ENNReal MeasureTheory MeasureTheory.Measure Metric Set Filter TopologicalSpace Function
open scoped Topology ENNReal Convex
variable {α E F : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [CompleteSpace F] {μ ν : Measure α}
{s t : Set α}
/-!
### Average value of a function w.r.t. a measure
The (Bochner, Lebesgue) average value of a function `f` w.r.t. a measure `μ` (notation:
`⨍ x, f x ∂μ`, `⨍⁻ x, f x ∂μ`) is defined as the (Bochner, Lebesgue) integral divided by the total
measure, so it is equal to zero if `μ` is an infinite measure, and (typically) equal to infinity if
`f` is not integrable. If `μ` is a probability measure, then the average of any function is equal to
its integral.
-/
namespace MeasureTheory
section ENNReal
variable (μ) {f g : α → ℝ≥0∞}
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`, denoted `⨍⁻ x, f x ∂μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def laverage (f : α → ℝ≥0∞) := ∫⁻ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => laverage μ r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure.
It is equal to `(volume univ)⁻¹ * ∫⁻ x, f x`, so it takes value zero if the space has infinite
measure. In a probability space, the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x`, defined as `⨍⁻ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => laverage volume f) => r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ s)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `s` has infinite measure. If `s`
has measure `1`, then the average of any function is equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => laverage (Measure.restrict μ s) r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume s)⁻¹ * ∫⁻ x, f x`, so it takes value zero if `s` has infinite measure. If
`s` has measure `1`, then the average of any function is equal to its integral. -/
notation3 (prettyPrint := false)
"⨍⁻ "(...)" in "s", "r:60:(scoped f => laverage Measure.restrict volume s f) => r
@[simp]
theorem laverage_zero : ⨍⁻ _x, (0 : ℝ≥0∞) ∂μ = 0 := by rw [laverage, lintegral_zero]
@[simp]
theorem laverage_zero_measure (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂(0 : Measure α) = 0 := by simp [laverage]
theorem laverage_eq' (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂(μ univ)⁻¹ • μ := rfl
theorem laverage_eq (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = (∫⁻ x, f x ∂μ) / μ univ := by
rw [laverage_eq', lintegral_smul_measure, ENNReal.div_eq_inv_mul, smul_eq_mul]
theorem laverage_eq_lintegral [IsProbabilityMeasure μ] (f : α → ℝ≥0∞) :
⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by rw [laverage, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_mul_laverage [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
μ univ * ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, lintegral_zero_measure, laverage_zero_measure, mul_zero]
· rw [laverage_eq, ENNReal.mul_div_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
theorem setLAverage_eq (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = (∫⁻ x in s, f x ∂μ) / μ s := by rw [laverage_eq, restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias setLaverage_eq := setLAverage_eq
theorem setLAverage_eq' (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = ∫⁻ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [laverage_eq', restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias setLaverage_eq' := setLAverage_eq'
variable {μ}
theorem laverage_congr {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) : ⨍⁻ x, f x ∂μ = ⨍⁻ x, g x ∂μ := by
simp only [laverage_eq, lintegral_congr_ae h]
theorem setLAverage_congr (h : s =ᵐ[μ] t) : ⨍⁻ x in s, f x ∂μ = ⨍⁻ x in t, f x ∂μ := by
simp only [setLAverage_eq, setLIntegral_congr h, measure_congr h]
@[deprecated (since := "2025-04-22")] alias setLaverage_congr := setLAverage_congr
theorem setLAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍⁻ x in s, f x ∂μ = ⨍⁻ x in s, g x ∂μ := by
simp only [laverage_eq, setLIntegral_congr_fun hs h]
@[deprecated (since := "2025-04-22")] alias setLaverage_congr_fun := setLAverage_congr_fun
theorem laverage_lt_top (hf : ∫⁻ x, f x ∂μ ≠ ∞) : ⨍⁻ x, f x ∂μ < ∞ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq]
exact div_lt_top hf (measure_univ_ne_zero.2 hμ)
theorem setLAverage_lt_top : ∫⁻ x in s, f x ∂μ ≠ ∞ → ⨍⁻ x in s, f x ∂μ < ∞ :=
laverage_lt_top
@[deprecated (since := "2025-04-22")] alias setLaverage_lt_top := setLAverage_lt_top
theorem laverage_add_measure :
⨍⁻ x, f x ∂(μ + ν) =
μ univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂ν := by
by_cases hμ : IsFiniteMeasure μ; swap
· rw [not_isFiniteMeasure_iff] at hμ
simp [laverage_eq, hμ]
by_cases hν : IsFiniteMeasure ν; swap
· rw [not_isFiniteMeasure_iff] at hν
simp [laverage_eq, hν]
haveI := hμ; haveI := hν
simp only [← ENNReal.mul_div_right_comm, measure_mul_laverage, ← ENNReal.add_div,
← lintegral_add_measure, ← Measure.add_apply, ← laverage_eq]
theorem measure_mul_setLAverage (f : α → ℝ≥0∞) (h : μ s ≠ ∞) :
μ s * ⨍⁻ x in s, f x ∂μ = ∫⁻ x in s, f x ∂μ := by
have := Fact.mk h.lt_top
rw [← measure_mul_laverage, restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias measure_mul_setLaverage := measure_mul_setLAverage
theorem laverage_union (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ) :
⨍⁻ x in s ∪ t, f x ∂μ =
μ s / (μ s + μ t) * ⨍⁻ x in s, f x ∂μ + μ t / (μ s + μ t) * ⨍⁻ x in t, f x ∂μ := by
rw [restrict_union₀ hd ht, laverage_add_measure, restrict_apply_univ, restrict_apply_univ]
theorem laverage_union_mem_openSegment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in t, f x ∂μ) := by
refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), ENNReal.div_pos hs₀ <| add_ne_top.2 ⟨hsμ, htμ⟩,
ENNReal.div_pos ht₀ <| add_ne_top.2 ⟨hsμ, htμ⟩, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
theorem laverage_union_mem_segment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ [⨍⁻ x in s, f x ∂μ -[ℝ≥0∞] ⨍⁻ x in t, f x ∂μ] := by
by_cases hs₀ : μ s = 0
· rw [← ae_eq_empty] at hs₀
rw [restrict_congr_set (hs₀.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), zero_le _, zero_le _, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
theorem laverage_mem_openSegment_compl_self [IsFiniteMeasure μ] (hs : NullMeasurableSet s μ)
(hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) :
⨍⁻ x, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
laverage_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _)
@[simp]
theorem laverage_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : ℝ≥0∞) :
⨍⁻ _x, c ∂μ = c := by
simp only [laverage, lintegral_const, measure_univ, mul_one]
theorem setLAverage_const (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : ℝ≥0∞) : ⨍⁻ _x in s, c ∂μ = c := by
simp only [setLAverage_eq, lintegral_const, Measure.restrict_apply, MeasurableSet.univ,
univ_inter, div_eq_mul_inv, mul_assoc, ENNReal.mul_inv_cancel hs₀ hs, mul_one]
@[deprecated (since := "2025-04-22")] alias setLaverage_const := setLAverage_const
theorem laverage_one [IsFiniteMeasure μ] [NeZero μ] : ⨍⁻ _x, (1 : ℝ≥0∞) ∂μ = 1 :=
laverage_const _ _
theorem setLAverage_one (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) : ⨍⁻ _x in s, (1 : ℝ≥0∞) ∂μ = 1 :=
setLAverage_const hs₀ hs _
@[deprecated (since := "2025-04-22")] alias setLaverage_one := setLAverage_one
@[simp]
theorem laverage_mul_measure_univ (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
(⨍⁻ (a : α), f a ∂μ) * μ univ = ∫⁻ x, f x ∂μ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq, ENNReal.div_mul_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
theorem lintegral_laverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
∫⁻ _x, ⨍⁻ a, f a ∂μ ∂μ = ∫⁻ x, f x ∂μ := by
simp
theorem setLIntegral_setLAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ _x in s, ⨍⁻ a in s, f a ∂μ ∂μ = ∫⁻ x in s, f x ∂μ :=
lintegral_laverage _ _
@[deprecated (since := "2025-04-22")] alias setLintegral_setLaverage := setLIntegral_setLAverage
end ENNReal
section NormedAddCommGroup
variable (μ)
variable {f g : α → E}
/-- Average value of a function `f` w.r.t. a measure `μ`, denoted `⨍ x, f x ∂μ`.
It is equal to `(μ.real univ)⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def average (f : α → E) :=
∫ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of a function `f` w.r.t. a measure `μ`.
It is equal to `(μ.real univ)⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => average μ r
/-- Average value of a function `f` w.r.t. to the standard measure.
It is equal to `(volume.real univ)⁻¹ * ∫ x, f x`, so it takes value zero if `f` is not integrable
or if the space has infinite measure. In a probability space, the average of any function is equal
to its integral.
For the average on a set, use `⨍ x in s, f x`, defined as `⨍ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => average volume f) => r
/-- Average value of a function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ.real s)⁻¹ * ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable on
`s` or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is
equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => average (Measure.restrict μ s) r
/-- Average value of a function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume.real s)⁻¹ * ∫ x, f x`, so it takes value zero `f` is not integrable on `s`
or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is equal to
its integral. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => average (Measure.restrict volume s) f) => r
@[simp]
theorem average_zero : ⨍ _, (0 : E) ∂μ = 0 := by rw [average, integral_zero]
@[simp]
theorem average_zero_measure (f : α → E) : ⨍ x, f x ∂(0 : Measure α) = 0 := by
rw [average, smul_zero, integral_zero_measure]
@[simp]
theorem average_neg (f : α → E) : ⨍ x, -f x ∂μ = -⨍ x, f x ∂μ :=
integral_neg f
theorem average_eq' (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂(μ univ)⁻¹ • μ :=
rfl
theorem average_eq (f : α → E) : ⨍ x, f x ∂μ = (μ.real univ)⁻¹ • ∫ x, f x ∂μ := by
rw [average_eq', integral_smul_measure, ENNReal.toReal_inv, measureReal_def]
theorem average_eq_integral [IsProbabilityMeasure μ] (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rw [average, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_smul_average [IsFiniteMeasure μ] (f : α → E) :
μ.real univ • ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, integral_zero_measure, average_zero_measure, smul_zero]
· rw [average_eq, smul_inv_smul₀]
refine (ENNReal.toReal_pos ?_ <| measure_ne_top _ _).ne'
rwa [Ne, measure_univ_eq_zero]
theorem setAverage_eq (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = (μ.real s)⁻¹ • ∫ x in s, f x ∂μ := by
rw [average_eq, measureReal_restrict_apply_univ]
theorem setAverage_eq' (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = ∫ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [average_eq', restrict_apply_univ]
variable {μ}
theorem average_congr {f g : α → E} (h : f =ᵐ[μ] g) : ⨍ x, f x ∂μ = ⨍ x, g x ∂μ := by
simp only [average_eq, integral_congr_ae h]
theorem setAverage_congr (h : s =ᵐ[μ] t) : ⨍ x in s, f x ∂μ = ⨍ x in t, f x ∂μ := by
simp only [setAverage_eq, setIntegral_congr_set h, measureReal_congr h]
theorem setAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍ x in s, f x ∂μ = ⨍ x in s, g x ∂μ := by simp only [average_eq, setIntegral_congr_ae hs h]
theorem average_add_measure [IsFiniteMeasure μ] {ν : Measure α} [IsFiniteMeasure ν] {f : α → E}
(hμ : Integrable f μ) (hν : Integrable f ν) :
⨍ x, f x ∂(μ + ν) =
(μ.real univ / (μ.real univ + ν.real univ)) • ⨍ x, f x ∂μ +
(ν.real univ / (μ.real univ + ν.real univ)) • ⨍ x, f x ∂ν := by
simp only [div_eq_inv_mul, mul_smul, measure_smul_average, ← smul_add,
← integral_add_measure hμ hν, ← ENNReal.toReal_add (measure_ne_top μ _) (measure_ne_top ν _)]
rw [average_eq, measureReal_add_apply]
theorem average_pair [CompleteSpace E]
{f : α → E} {g : α → F} (hfi : Integrable f μ) (hgi : Integrable g μ) :
⨍ x, (f x, g x) ∂μ = (⨍ x, f x ∂μ, ⨍ x, g x ∂μ) :=
integral_pair hfi.to_average hgi.to_average
theorem measure_smul_setAverage (f : α → E) {s : Set α} (h : μ s ≠ ∞) :
μ.real s • ⨍ x in s, f x ∂μ = ∫ x in s, f x ∂μ := by
haveI := Fact.mk h.lt_top
rw [← measure_smul_average, measureReal_restrict_apply_univ]
theorem average_union {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ =
(μ.real s / (μ.real s + μ.real t)) • ⨍ x in s, f x ∂μ +
(μ.real t / (μ.real s + μ.real t)) • ⨍ x in t, f x ∂μ := by
haveI := Fact.mk hsμ.lt_top; haveI := Fact.mk htμ.lt_top
rw [restrict_union₀ hd ht, average_add_measure hfs hft, measureReal_restrict_apply_univ,
measureReal_restrict_apply_univ]
theorem average_union_mem_openSegment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞)
(hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in t, f x ∂μ) := by
replace hs₀ : 0 < μ.real s := ENNReal.toReal_pos hs₀ hsμ
replace ht₀ : 0 < μ.real t := ENNReal.toReal_pos ht₀ htμ
exact mem_openSegment_iff_div.mpr
⟨μ.real s, μ.real t, hs₀, ht₀, (average_union hd ht hsμ htμ hfs hft).symm⟩
theorem average_union_mem_segment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ)
(hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ [⨍ x in s, f x ∂μ -[ℝ] ⨍ x in t, f x ∂μ] := by
by_cases hse : μ s = 0
· rw [← ae_eq_empty] at hse
rw [restrict_congr_set (hse.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
mem_segment_iff_div.mpr
⟨μ.real s, μ.real t, ENNReal.toReal_nonneg, ENNReal.toReal_nonneg, ?_,
(average_union hd ht hsμ htμ hfs hft).symm⟩
calc
0 < μ.real s := ENNReal.toReal_pos hse hsμ
_ ≤ _ := le_add_of_nonneg_right ENNReal.toReal_nonneg
theorem average_mem_openSegment_compl_self [IsFiniteMeasure μ] {f : α → E} {s : Set α}
(hs : NullMeasurableSet s μ) (hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) (hfi : Integrable f μ) :
⨍ x, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
average_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _) hfi.integrableOn hfi.integrableOn
variable [CompleteSpace E]
@[simp]
theorem average_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : E) :
⨍ _x, c ∂μ = c := by
rw [average, integral_const, measureReal_def, measure_univ, ENNReal.toReal_one, one_smul]
theorem setAverage_const {s : Set α} (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : E) :
⨍ _ in s, c ∂μ = c :=
have := NeZero.mk hs₀; have := Fact.mk hs.lt_top; average_const _ _
theorem integral_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ _, ⨍ a, f a ∂μ ∂μ = ∫ x, f x ∂μ := by simp
theorem setIntegral_setAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) (s : Set α) :
∫ _ in s, ⨍ a in s, f a ∂μ ∂μ = ∫ x in s, f x ∂μ :=
integral_average _ _
theorem integral_sub_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ x, f x - ⨍ a, f a ∂μ ∂μ = 0 := by
by_cases hf : Integrable f μ
· rw [integral_sub hf (integrable_const _), integral_average, sub_self]
refine integral_undef fun h => hf ?_
convert h.add (integrable_const (⨍ a, f a ∂μ))
exact (sub_add_cancel _ _).symm
theorem setAverage_sub_setAverage (hs : μ s ≠ ∞) (f : α → E) :
∫ x in s, f x - ⨍ a in s, f a ∂μ ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_sub_average _ _
theorem integral_average_sub [IsFiniteMeasure μ] (hf : Integrable f μ) :
∫ x, ⨍ a, f a ∂μ - f x ∂μ = 0 := by
rw [integral_sub (integrable_const _) hf, integral_average, sub_self]
theorem setIntegral_setAverage_sub (hs : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∫ x in s, ⨍ a in s, f a ∂μ - f x ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_average_sub hf
end NormedAddCommGroup
theorem ofReal_average {f : α → ℝ} (hf : Integrable f μ) (hf₀ : 0 ≤ᵐ[μ] f) :
ENNReal.ofReal (⨍ x, f x ∂μ) = (∫⁻ x, ENNReal.ofReal (f x) ∂μ) / μ univ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [average_eq, smul_eq_mul, measureReal_def, ← toReal_inv, ofReal_mul toReal_nonneg,
ofReal_toReal (inv_ne_top.2 <| measure_univ_ne_zero.2 hμ),
ofReal_integral_eq_lintegral_ofReal hf hf₀, ENNReal.div_eq_inv_mul]
theorem ofReal_setAverage {f : α → ℝ} (hf : IntegrableOn f s μ) (hf₀ : 0 ≤ᵐ[μ.restrict s] f) :
ENNReal.ofReal (⨍ x in s, f x ∂μ) = (∫⁻ x in s, ENNReal.ofReal (f x) ∂μ) / μ s := by
simpa using ofReal_average hf hf₀
theorem toReal_laverage {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (hf' : ∀ᵐ x ∂μ, f x ≠ ∞) :
(⨍⁻ x, f x ∂μ).toReal = ⨍ x, (f x).toReal ∂μ := by
rw [average_eq, laverage_eq, smul_eq_mul, toReal_div, div_eq_inv_mul, ←
integral_toReal hf (hf'.mono fun _ => lt_top_iff_ne_top.2), measureReal_def]
theorem toReal_setLAverage {f : α → ℝ≥0∞} (hf : AEMeasurable f (μ.restrict s))
(hf' : ∀ᵐ x ∂μ.restrict s, f x ≠ ∞) :
(⨍⁻ x in s, f x ∂μ).toReal = ⨍ x in s, (f x).toReal ∂μ := by
simpa [laverage_eq] using toReal_laverage hf hf'
@[deprecated (since := "2025-04-22")] alias toReal_setLaverage := toReal_setLAverage
/-! ### First moment method -/
section FirstMomentReal
variable {N : Set α} {f : α → ℝ}
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_setAverage_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | f x ≤ ⨍ a in s, f a ∂μ}) := by
refine pos_iff_ne_zero.2 fun H => ?_
replace H : (μ.restrict s) {x | f x ≤ ⨍ a in s, f a ∂μ} = 0 := by
rwa [restrict_apply₀, inter_comm]
exact AEStronglyMeasurable.nullMeasurableSet_le hf.1 aestronglyMeasurable_const
haveI := Fact.mk hμ₁.lt_top
refine (integral_sub_average (μ.restrict s) f).not_gt ?_
refine (setIntegral_pos_iff_support_of_nonneg_ae ?_ ?_).2 ?_
· refine measure_mono_null (fun x hx ↦ ?_) H
simp only [Pi.zero_apply, sub_nonneg, mem_compl_iff, mem_setOf_eq, not_le] at hx
exact hx.le
· exact hf.sub (integrableOn_const.2 <| Or.inr <| lt_top_iff_ne_top.2 hμ₁)
· rwa [pos_iff_ne_zero, inter_comm, ← diff_compl, ← diff_inter_self_eq_diff, measure_diff_null]
refine measure_mono_null ?_ (measure_inter_eq_zero_of_restrict H)
exact inter_subset_inter_left _ fun a ha => (sub_eq_zero.1 <| of_not_not ha).le
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_setAverage_le_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | ⨍ a in s, f a ∂μ ≤ f x}) := by
simpa [integral_neg, neg_div] using measure_le_setAverage_pos hμ hμ₁ hf.neg
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_setAverage (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, f x ≤ ⨍ a in s, f a ∂μ :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_le_setAverage_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_setAverage_le (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, ⨍ a in s, f a ∂μ ≤ f x :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_setAverage_le_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
section FiniteMeasure
variable [IsFiniteMeasure μ]
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_average_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | f x ≤ ⨍ a, f a ∂μ} := by
simpa using measure_le_setAverage_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_average_le_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | ⨍ a, f a ∂μ ≤ f x} := by
simpa using measure_setAverage_le_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, f x ≤ ⨍ a, f a ∂μ :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_le_average_pos hμ hf).ne'
⟨x, hx⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, ⨍ a, f a ∂μ ≤ f x :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_average_le_pos hμ hf).ne'
⟨x, hx⟩
/-- **First moment method**. The minimum of an integrable function is smaller than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ f x ≤ ⨍ a, f a ∂μ := by
have := measure_le_average_pos hμ hf
rw [← measure_diff_null hN] at this
obtain ⟨x, hx, hxN⟩ := nonempty_of_measure_ne_zero this.ne'
exact ⟨x, hxN, hx⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ⨍ a, f a ∂μ ≤ f x := by
simpa [integral_neg, neg_div] using exists_not_mem_null_le_average hμ hf.neg hN
end FiniteMeasure
section ProbabilityMeasure
variable [IsProbabilityMeasure μ]
/-- **First moment method**. An integrable function is smaller than its integral on a set of
positive measure. -/
theorem measure_le_integral_pos (hf : Integrable f μ) : 0 < μ {x | f x ≤ ∫ a, f a ∂μ} := by
simpa only [average_eq_integral] using
measure_le_average_pos (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. An integrable function is greater than its integral on a set of
positive measure. -/
theorem measure_integral_le_pos (hf : Integrable f μ) : 0 < μ {x | ∫ a, f a ∂μ ≤ f x} := by
simpa only [average_eq_integral] using
measure_average_le_pos (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. The minimum of an integrable function is smaller than its integral. -/
theorem exists_le_integral (hf : Integrable f μ) : ∃ x, f x ≤ ∫ a, f a ∂μ := by
simpa only [average_eq_integral] using exists_le_average (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. The maximum of an integrable function is greater than its integral. -/
theorem exists_integral_le (hf : Integrable f μ) : ∃ x, ∫ a, f a ∂μ ≤ f x := by
simpa only [average_eq_integral] using exists_average_le (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. The minimum of an integrable function is smaller than its integral,
while avoiding a null set. -/
theorem exists_not_mem_null_le_integral (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ f x ≤ ∫ a, f a ∂μ := by
simpa only [average_eq_integral] using
exists_not_mem_null_le_average (IsProbabilityMeasure.ne_zero μ) hf hN
/-- **First moment method**. The maximum of an integrable function is greater than its integral,
while avoiding a null set. -/
theorem exists_not_mem_null_integral_le (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ∫ a, f a ∂μ ≤ f x := by
simpa only [average_eq_integral] using
exists_not_mem_null_average_le (IsProbabilityMeasure.ne_zero μ) hf hN
end ProbabilityMeasure
end FirstMomentReal
section FirstMomentENNReal
variable {N : Set α} {f : α → ℝ≥0∞}
/-- **First moment method**. A measurable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_setLAverage_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞)
(hf : AEMeasurable f (μ.restrict s)) : 0 < μ {x ∈ s | f x ≤ ⨍⁻ a in s, f a ∂μ} := by
obtain h | h := eq_or_ne (∫⁻ a in s, f a ∂μ) ∞
· simpa [mul_top, hμ₁, laverage, h, top_div_of_ne_top hμ₁, pos_iff_ne_zero] using hμ
have := measure_le_setAverage_pos hμ hμ₁ (integrable_toReal_of_lintegral_ne_top hf h)
rw [← setOf_inter_eq_sep, ← Measure.restrict_apply₀
(hf.aestronglyMeasurable.nullMeasurableSet_le aestronglyMeasurable_const)]
rw [← setOf_inter_eq_sep, ← Measure.restrict_apply₀
(hf.ennreal_toReal.aestronglyMeasurable.nullMeasurableSet_le aestronglyMeasurable_const),
← measure_diff_null (measure_eq_top_of_lintegral_ne_top hf h)] at this
refine this.trans_le (measure_mono ?_)
rintro x ⟨hfx, hx⟩
dsimp at hfx
rwa [← toReal_laverage hf, toReal_le_toReal hx (setLAverage_lt_top h).ne] at hfx
simp_rw [ae_iff, not_ne_iff]
exact measure_eq_top_of_lintegral_ne_top hf h
@[deprecated (since := "2025-04-22")] alias measure_le_setLaverage_pos := measure_le_setLAverage_pos
/-- **First moment method**. A measurable function is greater than its mean on a set of positive
measure. -/
theorem measure_setLAverage_le_pos (hμ : μ s ≠ 0) (hs : NullMeasurableSet s μ)
(hint : ∫⁻ a in s, f a ∂μ ≠ ∞) : 0 < μ {x ∈ s | ⨍⁻ a in s, f a ∂μ ≤ f x} := by
obtain hμ₁ | hμ₁ := eq_or_ne (μ s) ∞
· simp [setLAverage_eq, hμ₁]
| obtain ⟨g, hg, hgf, hfg⟩ := exists_measurable_le_lintegral_eq (μ.restrict s) f
have hfg' : ⨍⁻ a in s, f a ∂μ = ⨍⁻ a in s, g a ∂μ := by simp_rw [laverage_eq, hfg]
| Mathlib/MeasureTheory/Integral/Average.lean | 634 | 635 |
/-
Copyright (c) 2021 Alex Kontorovich, Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex Kontorovich, Heather Macbeth
-/
import Mathlib.Algebra.Group.Pointwise.Set.Lattice
import Mathlib.Algebra.GroupWithZero.Action.Pointwise.Set
import Mathlib.Algebra.Module.ULift
import Mathlib.GroupTheory.GroupAction.Defs
import Mathlib.Topology.Algebra.Constructions
import Mathlib.Topology.Algebra.Support
/-!
# Monoid actions continuous in the second variable
In this file we define class `ContinuousConstSMul`. We say `ContinuousConstSMul Γ T` if
`Γ` acts on `T` and for each `γ`, the map `x ↦ γ • x` is continuous. (This differs from
`ContinuousSMul`, which requires simultaneous continuity in both variables.)
## Main definitions
* `ContinuousConstSMul Γ T` : typeclass saying that the map `x ↦ γ • x` is continuous on `T`;
* `ProperlyDiscontinuousSMul`: says that the scalar multiplication `(•) : Γ → T → T`
is properly discontinuous, that is, for any pair of compact sets `K, L` in `T`, only finitely
many `γ:Γ` move `K` to have nontrivial intersection with `L`.
* `Homeomorph.smul`: scalar multiplication by an element of a group `Γ` acting on `T`
is a homeomorphism of `T`.
*`Homeomorph.smulOfNeZero`: if a group with zero `G₀` (e.g., a field) acts on `X` and `c : G₀`
is a nonzero element of `G₀`, then scalar multiplication by `c` is a homeomorphism of `X`;
* `Homeomorph.smul`: scalar multiplication by an element of a group `G` acting on `X`
is a homeomorphism of `X`.
## Main results
* `isOpenMap_quotient_mk'_mul` : The quotient map by a group action is open.
* `t2Space_of_properlyDiscontinuousSMul_of_t2Space` : The quotient by a discontinuous group
action of a locally compact t2 space is t2.
## Tags
Hausdorff, discrete group, properly discontinuous, quotient space
-/
assert_not_exists IsOrderedRing
open Topology Pointwise Filter Set TopologicalSpace
/-- Class `ContinuousConstSMul Γ T` says that the scalar multiplication `(•) : Γ → T → T`
is continuous in the second argument. We use the same class for all kinds of multiplicative
actions, including (semi)modules and algebras.
Note that both `ContinuousConstSMul α α` and `ContinuousConstSMul αᵐᵒᵖ α` are
weaker versions of `ContinuousMul α`. -/
class ContinuousConstSMul (Γ : Type*) (T : Type*) [TopologicalSpace T] [SMul Γ T] : Prop where
/-- The scalar multiplication `(•) : Γ → T → T` is continuous in the second argument. -/
continuous_const_smul : ∀ γ : Γ, Continuous fun x : T => γ • x
/-- Class `ContinuousConstVAdd Γ T` says that the additive action `(+ᵥ) : Γ → T → T`
is continuous in the second argument. We use the same class for all kinds of additive actions,
including (semi)modules and algebras.
Note that both `ContinuousConstVAdd α α` and `ContinuousConstVAdd αᵐᵒᵖ α` are
weaker versions of `ContinuousVAdd α`. -/
class ContinuousConstVAdd (Γ : Type*) (T : Type*) [TopologicalSpace T] [VAdd Γ T] : Prop where
/-- The additive action `(+ᵥ) : Γ → T → T` is continuous in the second argument. -/
continuous_const_vadd : ∀ γ : Γ, Continuous fun x : T => γ +ᵥ x
attribute [to_additive] ContinuousConstSMul
export ContinuousConstSMul (continuous_const_smul)
export ContinuousConstVAdd (continuous_const_vadd)
variable {M α β : Type*}
section SMul
variable [TopologicalSpace α] [SMul M α] [ContinuousConstSMul M α]
@[to_additive]
instance : ContinuousConstSMul (ULift M) α := ⟨fun γ ↦ continuous_const_smul (ULift.down γ)⟩
@[to_additive]
theorem Filter.Tendsto.const_smul {f : β → α} {l : Filter β} {a : α} (hf : Tendsto f l (𝓝 a))
(c : M) : Tendsto (fun x => c • f x) l (𝓝 (c • a)) :=
((continuous_const_smul _).tendsto _).comp hf
variable [TopologicalSpace β] {g : β → α} {b : β} {s : Set β}
@[to_additive]
nonrec theorem ContinuousWithinAt.const_smul (hg : ContinuousWithinAt g s b) (c : M) :
ContinuousWithinAt (fun x => c • g x) s b :=
hg.const_smul c
@[to_additive (attr := fun_prop)]
nonrec theorem ContinuousAt.const_smul (hg : ContinuousAt g b) (c : M) :
ContinuousAt (fun x => c • g x) b :=
hg.const_smul c
@[to_additive (attr := fun_prop)]
theorem ContinuousOn.const_smul (hg : ContinuousOn g s) (c : M) :
ContinuousOn (fun x => c • g x) s := fun x hx => (hg x hx).const_smul c
@[to_additive (attr := continuity, fun_prop)]
theorem Continuous.const_smul (hg : Continuous g) (c : M) : Continuous fun x => c • g x :=
(continuous_const_smul _).comp hg
/-- If a scalar is central, then its right action is continuous when its left action is. -/
@[to_additive "If an additive action is central, then its right action is continuous when its left
action is."]
instance ContinuousConstSMul.op [SMul Mᵐᵒᵖ α] [IsCentralScalar M α] :
ContinuousConstSMul Mᵐᵒᵖ α :=
⟨MulOpposite.rec' fun c => by simpa only [op_smul_eq_smul] using continuous_const_smul c⟩
@[to_additive]
instance MulOpposite.continuousConstSMul : ContinuousConstSMul M αᵐᵒᵖ :=
⟨fun c => MulOpposite.continuous_op.comp <| MulOpposite.continuous_unop.const_smul c⟩
@[to_additive]
instance : ContinuousConstSMul M αᵒᵈ := ‹ContinuousConstSMul M α›
@[to_additive]
instance OrderDual.continuousConstSMul' : ContinuousConstSMul Mᵒᵈ α :=
‹ContinuousConstSMul M α›
@[to_additive]
instance Prod.continuousConstSMul [SMul M β] [ContinuousConstSMul M β] :
ContinuousConstSMul M (α × β) :=
⟨fun _ => (continuous_fst.const_smul _).prodMk (continuous_snd.const_smul _)⟩
@[to_additive]
instance {ι : Type*} {γ : ι → Type*} [∀ i, TopologicalSpace (γ i)] [∀ i, SMul M (γ i)]
[∀ i, ContinuousConstSMul M (γ i)] : ContinuousConstSMul M (∀ i, γ i) :=
⟨fun _ => continuous_pi fun i => (continuous_apply i).const_smul _⟩
@[to_additive]
theorem IsCompact.smul {α β} [SMul α β] [TopologicalSpace β] [ContinuousConstSMul α β] (a : α)
{s : Set β} (hs : IsCompact s) : IsCompact (a • s) :=
hs.image (continuous_id.const_smul a)
@[to_additive]
theorem Specializes.const_smul {x y : α} (h : x ⤳ y) (c : M) : (c • x) ⤳ (c • y) :=
h.map (continuous_const_smul c)
@[to_additive]
theorem Inseparable.const_smul {x y : α} (h : Inseparable x y) (c : M) :
Inseparable (c • x) (c • y) :=
h.map (continuous_const_smul c)
@[to_additive]
theorem Topology.IsInducing.continuousConstSMul {N β : Type*} [SMul N β] [TopologicalSpace β]
{g : β → α} (hg : IsInducing g) (f : N → M) (hf : ∀ {c : N} {x : β}, g (c • x) = f c • g x) :
ContinuousConstSMul N β where
continuous_const_smul c := by
simpa only [Function.comp_def, hf, hg.continuous_iff] using hg.continuous.const_smul (f c)
@[deprecated (since := "2024-10-28")]
alias Inducing.continuousConstSMul := IsInducing.continuousConstSMul
end SMul
section Monoid
variable [TopologicalSpace α]
variable [Monoid M] [MulAction M α] [ContinuousConstSMul M α]
@[to_additive]
instance Units.continuousConstSMul : ContinuousConstSMul Mˣ α where
continuous_const_smul m := continuous_const_smul (m : M)
@[to_additive]
theorem smul_closure_subset (c : M) (s : Set α) : c • closure s ⊆ closure (c • s) :=
((Set.mapsTo_image _ _).closure <| continuous_const_smul c).image_subset
@[to_additive]
theorem smul_closure_orbit_subset (c : M) (x : α) :
c • closure (MulAction.orbit M x) ⊆ closure (MulAction.orbit M x) :=
(smul_closure_subset c _).trans <| closure_mono <| MulAction.smul_orbit_subset _ _
theorem isClosed_setOf_map_smul {N : Type*} [Monoid N] (α β) [MulAction M α] [MulAction N β]
[TopologicalSpace β] [T2Space β] [ContinuousConstSMul N β] (σ : M → N) :
IsClosed { f : α → β | ∀ c x, f (c • x) = σ c • f x } := by
simp only [Set.setOf_forall]
exact isClosed_iInter fun c => isClosed_iInter fun x =>
isClosed_eq (continuous_apply _) ((continuous_apply _).const_smul _)
end Monoid
section Group
variable {G : Type*} [TopologicalSpace α] [Group G] [MulAction G α] [ContinuousConstSMul G α]
@[to_additive]
theorem tendsto_const_smul_iff {f : β → α} {l : Filter β} {a : α} (c : G) :
Tendsto (fun x => c • f x) l (𝓝 <| c • a) ↔ Tendsto f l (𝓝 a) :=
⟨fun h => by simpa only [inv_smul_smul] using h.const_smul c⁻¹, fun h => h.const_smul _⟩
variable [TopologicalSpace β] {f : β → α} {b : β} {s : Set β}
@[to_additive]
theorem continuousWithinAt_const_smul_iff (c : G) :
ContinuousWithinAt (fun x => c • f x) s b ↔ ContinuousWithinAt f s b :=
tendsto_const_smul_iff c
@[to_additive]
theorem continuousOn_const_smul_iff (c : G) :
ContinuousOn (fun x => c • f x) s ↔ ContinuousOn f s :=
forall₂_congr fun _ _ => continuousWithinAt_const_smul_iff c
@[to_additive]
theorem continuousAt_const_smul_iff (c : G) :
ContinuousAt (fun x => c • f x) b ↔ ContinuousAt f b :=
tendsto_const_smul_iff c
@[to_additive]
theorem continuous_const_smul_iff (c : G) : (Continuous fun x => c • f x) ↔ Continuous f := by
simp only [continuous_iff_continuousAt, continuousAt_const_smul_iff]
/-- The homeomorphism given by scalar multiplication by a given element of a group `Γ` acting on
`T` is a homeomorphism from `T` to itself. -/
@[to_additive (attr := simps!)]
def Homeomorph.smul (γ : G) : α ≃ₜ α where
toEquiv := MulAction.toPerm γ
continuous_toFun := continuous_const_smul γ
continuous_invFun := continuous_const_smul γ⁻¹
/-- The homeomorphism given by affine-addition by an element of an additive group `Γ` acting on
`T` is a homeomorphism from `T` to itself. -/
add_decl_doc Homeomorph.vadd
@[to_additive]
theorem isOpenMap_smul (c : G) : IsOpenMap fun x : α => c • x :=
(Homeomorph.smul c).isOpenMap
@[to_additive]
theorem IsOpen.smul {s : Set α} (hs : IsOpen s) (c : G) : IsOpen (c • s) :=
| isOpenMap_smul c s hs
| Mathlib/Topology/Algebra/ConstMulAction.lean | 237 | 238 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.CharP.Two
import Mathlib.Data.Nat.Cast.Field
import Mathlib.Data.Nat.Factorization.Basic
import Mathlib.Data.Nat.Factorization.Induction
import Mathlib.Data.Nat.Periodic
/-!
# Euler's totient function
This file defines [Euler's totient function](https://en.wikipedia.org/wiki/Euler's_totient_function)
`Nat.totient n` which counts the number of naturals less than `n` that are coprime with `n`.
We prove the divisor sum formula, namely that `n` equals `φ` summed over the divisors of `n`. See
`sum_totient`. We also prove two lemmas to help compute totients, namely `totient_mul` and
`totient_prime_pow`.
-/
assert_not_exists Algebra LinearMap
open Finset
namespace Nat
/-- Euler's totient function. This counts the number of naturals strictly less than `n` which are
coprime with `n`. -/
def totient (n : ℕ) : ℕ := #{a ∈ range n | n.Coprime a}
@[inherit_doc]
scoped notation "φ" => Nat.totient
@[simp]
theorem totient_zero : φ 0 = 0 :=
rfl
@[simp]
theorem totient_one : φ 1 = 1 := rfl
theorem totient_eq_card_coprime (n : ℕ) : φ n = #{a ∈ range n | n.Coprime a} := rfl
/-- A characterisation of `Nat.totient` that avoids `Finset`. -/
theorem totient_eq_card_lt_and_coprime (n : ℕ) : φ n = Nat.card { m | m < n ∧ n.Coprime m } := by
let e : { m | m < n ∧ n.Coprime m } ≃ {x ∈ range n | n.Coprime x} :=
{ toFun := fun m => ⟨m, by simpa only [Finset.mem_filter, Finset.mem_range] using m.property⟩
invFun := fun m => ⟨m, by simpa only [Finset.mem_filter, Finset.mem_range] using m.property⟩
left_inv := fun m => by simp only [Subtype.coe_mk, Subtype.coe_eta]
right_inv := fun m => by simp only [Subtype.coe_mk, Subtype.coe_eta] }
rw [totient_eq_card_coprime, card_congr e, card_eq_fintype_card, Fintype.card_coe]
theorem totient_le (n : ℕ) : φ n ≤ n :=
((range n).card_filter_le _).trans_eq (card_range n)
theorem totient_lt (n : ℕ) (hn : 1 < n) : φ n < n :=
(card_lt_card (filter_ssubset.2 ⟨0, by simp [hn.ne', pos_of_gt hn]⟩)).trans_eq (card_range n)
@[simp]
theorem totient_eq_zero : ∀ {n : ℕ}, φ n = 0 ↔ n = 0
| 0 => by decide
| n + 1 =>
suffices ∃ x < n + 1, (n + 1).gcd x = 1 by simpa [totient, filter_eq_empty_iff]
⟨1 % (n + 1), mod_lt _ n.succ_pos, by rw [gcd_comm, ← gcd_rec, gcd_one_right]⟩
@[simp] theorem totient_pos {n : ℕ} : 0 < φ n ↔ 0 < n := by simp [pos_iff_ne_zero]
| instance neZero_totient {n : ℕ} [NeZero n] : NeZero n.totient :=
⟨(totient_pos.mpr <| NeZero.pos n).ne'⟩
theorem filter_coprime_Ico_eq_totient (a n : ℕ) :
#{x ∈ Ico n (n + a) | a.Coprime x} = totient a := by
| Mathlib/Data/Nat/Totient.lean | 68 | 72 |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Data.Set.SymmDiff
import Mathlib.Order.SuccPred.Relation
import Mathlib.Topology.Irreducible
/-!
# Connected subsets of topological spaces
In this file we define connected subsets of a topological spaces and various other properties and
classes related to connectivity.
## Main definitions
We define the following properties for sets in a topological space:
* `IsConnected`: a nonempty set that has no non-trivial open partition.
See also the section below in the module doc.
* `connectedComponent` is the connected component of an element in the space.
We also have a class stating that the whole space satisfies that property: `ConnectedSpace`
## On the definition of connected sets/spaces
In informal mathematics, connected spaces are assumed to be nonempty.
We formalise the predicate without that assumption as `IsPreconnected`.
In other words, the only difference is whether the empty space counts as connected.
There are good reasons to consider the empty space to be “too simple to be simple”
See also https://ncatlab.org/nlab/show/too+simple+to+be+simple,
and in particular
https://ncatlab.org/nlab/show/too+simple+to+be+simple#relationship_to_biased_definitions.
-/
open Set Function Topology TopologicalSpace Relation
universe u v
variable {α : Type u} {β : Type v} {ι : Type*} {π : ι → Type*} [TopologicalSpace α]
{s t u v : Set α}
section Preconnected
/-- A preconnected set is one where there is no non-trivial open partition. -/
def IsPreconnected (s : Set α) : Prop :=
∀ u v : Set α, IsOpen u → IsOpen v → s ⊆ u ∪ v → (s ∩ u).Nonempty → (s ∩ v).Nonempty →
(s ∩ (u ∩ v)).Nonempty
/-- A connected set is one that is nonempty and where there is no non-trivial open partition. -/
def IsConnected (s : Set α) : Prop :=
s.Nonempty ∧ IsPreconnected s
theorem IsConnected.nonempty {s : Set α} (h : IsConnected s) : s.Nonempty :=
h.1
theorem IsConnected.isPreconnected {s : Set α} (h : IsConnected s) : IsPreconnected s :=
h.2
theorem IsPreirreducible.isPreconnected {s : Set α} (H : IsPreirreducible s) : IsPreconnected s :=
fun _ _ hu hv _ => H _ _ hu hv
theorem IsIrreducible.isConnected {s : Set α} (H : IsIrreducible s) : IsConnected s :=
⟨H.nonempty, H.isPreirreducible.isPreconnected⟩
theorem isPreconnected_empty : IsPreconnected (∅ : Set α) :=
isPreirreducible_empty.isPreconnected
theorem isConnected_singleton {x} : IsConnected ({x} : Set α) :=
isIrreducible_singleton.isConnected
theorem isPreconnected_singleton {x} : IsPreconnected ({x} : Set α) :=
isConnected_singleton.isPreconnected
theorem Set.Subsingleton.isPreconnected {s : Set α} (hs : s.Subsingleton) : IsPreconnected s :=
hs.induction_on isPreconnected_empty fun _ => isPreconnected_singleton
/-- If any point of a set is joined to a fixed point by a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall {s : Set α} (x : α)
(H : ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) : IsPreconnected s := by
rintro u v hu hv hs ⟨z, zs, zu⟩ ⟨y, ys, yv⟩
have xs : x ∈ s := by
rcases H y ys with ⟨t, ts, xt, -, -⟩
exact ts xt
-- Porting note (https://github.com/leanprover-community/mathlib4/issues/11215): TODO: use `wlog xu : x ∈ u := hs xs using u v y z, v u z y`
cases hs xs with
| inl xu =>
rcases H y ys with ⟨t, ts, xt, yt, ht⟩
have := ht u v hu hv (ts.trans hs) ⟨x, xt, xu⟩ ⟨y, yt, yv⟩
exact this.imp fun z hz => ⟨ts hz.1, hz.2⟩
| inr xv =>
rcases H z zs with ⟨t, ts, xt, zt, ht⟩
have := ht v u hv hu (ts.trans <| by rwa [union_comm]) ⟨x, xt, xv⟩ ⟨z, zt, zu⟩
exact this.imp fun _ h => ⟨ts h.1, h.2.2, h.2.1⟩
/-- If any two points of a set are contained in a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall_pair {s : Set α}
(H : ∀ x ∈ s, ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) :
IsPreconnected s := by
rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩)
exacts [isPreconnected_empty, isPreconnected_of_forall x fun y => H x hx y]
/-- A union of a family of preconnected sets with a common point is preconnected as well. -/
theorem isPreconnected_sUnion (x : α) (c : Set (Set α)) (H1 : ∀ s ∈ c, x ∈ s)
(H2 : ∀ s ∈ c, IsPreconnected s) : IsPreconnected (⋃₀ c) := by
apply isPreconnected_of_forall x
rintro y ⟨s, sc, ys⟩
exact ⟨s, subset_sUnion_of_mem sc, H1 s sc, ys, H2 s sc⟩
theorem isPreconnected_iUnion {ι : Sort*} {s : ι → Set α} (h₁ : (⋂ i, s i).Nonempty)
(h₂ : ∀ i, IsPreconnected (s i)) : IsPreconnected (⋃ i, s i) :=
Exists.elim h₁ fun f hf => isPreconnected_sUnion f _ hf (forall_mem_range.2 h₂)
theorem IsPreconnected.union (x : α) {s t : Set α} (H1 : x ∈ s) (H2 : x ∈ t) (H3 : IsPreconnected s)
(H4 : IsPreconnected t) : IsPreconnected (s ∪ t) :=
sUnion_pair s t ▸ isPreconnected_sUnion x {s, t} (by rintro r (rfl | rfl | h) <;> assumption)
(by rintro r (rfl | rfl | h) <;> assumption)
theorem IsPreconnected.union' {s t : Set α} (H : (s ∩ t).Nonempty) (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ∪ t) := by
rcases H with ⟨x, hxs, hxt⟩
exact hs.union x hxs hxt ht
theorem IsConnected.union {s t : Set α} (H : (s ∩ t).Nonempty) (Hs : IsConnected s)
(Ht : IsConnected t) : IsConnected (s ∪ t) := by
rcases H with ⟨x, hx⟩
refine ⟨⟨x, mem_union_left t (mem_of_mem_inter_left hx)⟩, ?_⟩
exact Hs.isPreconnected.union x (mem_of_mem_inter_left hx) (mem_of_mem_inter_right hx)
Ht.isPreconnected
/-- The directed sUnion of a set S of preconnected subsets is preconnected. -/
theorem IsPreconnected.sUnion_directed {S : Set (Set α)} (K : DirectedOn (· ⊆ ·) S)
(H : ∀ s ∈ S, IsPreconnected s) : IsPreconnected (⋃₀ S) := by
rintro u v hu hv Huv ⟨a, ⟨s, hsS, has⟩, hau⟩ ⟨b, ⟨t, htS, hbt⟩, hbv⟩
obtain ⟨r, hrS, hsr, htr⟩ : ∃ r ∈ S, s ⊆ r ∧ t ⊆ r := K s hsS t htS
have Hnuv : (r ∩ (u ∩ v)).Nonempty :=
H _ hrS u v hu hv ((subset_sUnion_of_mem hrS).trans Huv) ⟨a, hsr has, hau⟩ ⟨b, htr hbt, hbv⟩
have Kruv : r ∩ (u ∩ v) ⊆ ⋃₀ S ∩ (u ∩ v) := inter_subset_inter_left _ (subset_sUnion_of_mem hrS)
exact Hnuv.mono Kruv
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsPreconnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(H : ∀ i ∈ t, IsPreconnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsPreconnected (⋃ n ∈ t, s n) := by
let R := fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t
have P : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen R i j →
∃ p, p ⊆ t ∧ i ∈ p ∧ j ∈ p ∧ IsPreconnected (⋃ j ∈ p, s j) := fun i hi j hj h => by
induction h with
| refl =>
refine ⟨{i}, singleton_subset_iff.mpr hi, mem_singleton i, mem_singleton i, ?_⟩
rw [biUnion_singleton]
exact H i hi
| @tail j k _ hjk ih =>
obtain ⟨p, hpt, hip, hjp, hp⟩ := ih hjk.2
refine ⟨insert k p, insert_subset_iff.mpr ⟨hj, hpt⟩, mem_insert_of_mem k hip,
mem_insert k p, ?_⟩
rw [biUnion_insert]
refine (H k hj).union' (hjk.1.mono ?_) hp
rw [inter_comm]
exact inter_subset_inter_right _ (subset_biUnion_of_mem hjp)
refine isPreconnected_of_forall_pair ?_
intro x hx y hy
obtain ⟨i : ι, hi : i ∈ t, hxi : x ∈ s i⟩ := mem_iUnion₂.1 hx
obtain ⟨j : ι, hj : j ∈ t, hyj : y ∈ s j⟩ := mem_iUnion₂.1 hy
obtain ⟨p, hpt, hip, hjp, hp⟩ := P i hi j hj (K i hi j hj)
exact ⟨⋃ j ∈ p, s j, biUnion_subset_biUnion_left hpt, mem_biUnion hip hxi,
mem_biUnion hjp hyj, hp⟩
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsConnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(ht : t.Nonempty) (H : ∀ i ∈ t, IsConnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨ht.some, ht.some_mem, (H _ ht.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_reflTransGen (fun i hi => (H i hi).isPreconnected) K⟩
/-- Preconnectedness of the iUnion of a family of preconnected sets
indexed by the vertices of a preconnected graph,
where two vertices are joined when the corresponding sets intersect. -/
theorem IsPreconnected.iUnion_of_reflTransGen {ι : Type*} {s : ι → Set α}
(H : ∀ i, IsPreconnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) :
IsPreconnected (⋃ n, s n) := by
rw [← biUnion_univ]
exact IsPreconnected.biUnion_of_reflTransGen (fun i _ => H i) fun i _ j _ => by
simpa [mem_univ] using K i j
theorem IsConnected.iUnion_of_reflTransGen {ι : Type*} [Nonempty ι] {s : ι → Set α}
(H : ∀ i, IsConnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) : IsConnected (⋃ n, s n) :=
⟨nonempty_iUnion.2 <| Nonempty.elim ‹_› fun i : ι => ⟨i, (H _).nonempty⟩,
IsPreconnected.iUnion_of_reflTransGen (fun i => (H i).isPreconnected) K⟩
section SuccOrder
open Order
variable [LinearOrder β] [SuccOrder β] [IsSuccArchimedean β]
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.iUnion_of_chain {s : β → Set α} (H : ∀ n, IsPreconnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsPreconnected (⋃ n, s n) :=
IsPreconnected.iUnion_of_reflTransGen H fun _ _ =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is connected. -/
theorem IsConnected.iUnion_of_chain [Nonempty β] {s : β → Set α} (H : ∀ n, IsConnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n, s n) :=
IsConnected.iUnion_of_reflTransGen H fun _ _ =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
/-- The iUnion of preconnected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.biUnion_of_chain {s : β → Set α} {t : Set β} (ht : OrdConnected t)
(H : ∀ n ∈ t, IsPreconnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) :
IsPreconnected (⋃ n ∈ t, s n) := by
have h1 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → k ∈ t := fun hi hj hk =>
ht.out hi hj (Ico_subset_Icc_self hk)
have h2 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → succ k ∈ t := fun hi hj hk =>
ht.out hi hj ⟨hk.1.trans <| le_succ _, succ_le_of_lt hk.2⟩
have h3 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → (s k ∩ s (succ k)).Nonempty :=
fun hi hj hk => K _ (h1 hi hj hk) (h2 hi hj hk)
refine IsPreconnected.biUnion_of_reflTransGen H fun i hi j hj => ?_
exact reflTransGen_of_succ _ (fun k hk => ⟨h3 hi hj hk, h1 hi hj hk⟩) fun k hk =>
⟨by rw [inter_comm]; exact h3 hj hi hk, h2 hj hi hk⟩
/-- The iUnion of connected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsConnected.biUnion_of_chain {s : β → Set α} {t : Set β} (hnt : t.Nonempty)
(ht : OrdConnected t) (H : ∀ n ∈ t, IsConnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨hnt.some, hnt.some_mem, (H _ hnt.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_chain ht (fun i hi => (H i hi).isPreconnected) K⟩
end SuccOrder
/-- Theorem of bark and tree: if a set is within a preconnected set and its closure, then it is
preconnected as well. See also `IsConnected.subset_closure`. -/
protected theorem IsPreconnected.subset_closure {s : Set α} {t : Set α} (H : IsPreconnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsPreconnected t :=
fun u v hu hv htuv ⟨_y, hyt, hyu⟩ ⟨_z, hzt, hzv⟩ =>
let ⟨p, hpu, hps⟩ := mem_closure_iff.1 (Ktcs hyt) u hu hyu
let ⟨q, hqv, hqs⟩ := mem_closure_iff.1 (Ktcs hzt) v hv hzv
let ⟨r, hrs, hruv⟩ := H u v hu hv (Subset.trans Kst htuv) ⟨p, hps, hpu⟩ ⟨q, hqs, hqv⟩
⟨r, Kst hrs, hruv⟩
/-- Theorem of bark and tree: if a set is within a connected set and its closure, then it is
connected as well. See also `IsPreconnected.subset_closure`. -/
protected theorem IsConnected.subset_closure {s : Set α} {t : Set α} (H : IsConnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsConnected t :=
⟨Nonempty.mono Kst H.left, IsPreconnected.subset_closure H.right Kst Ktcs⟩
/-- The closure of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.closure {s : Set α} (H : IsPreconnected s) :
IsPreconnected (closure s) :=
IsPreconnected.subset_closure H subset_closure Subset.rfl
/-- The closure of a connected set is connected as well. -/
protected theorem IsConnected.closure {s : Set α} (H : IsConnected s) : IsConnected (closure s) :=
IsConnected.subset_closure H subset_closure <| Subset.rfl
/-- The image of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.image [TopologicalSpace β] {s : Set α} (H : IsPreconnected s)
(f : α → β) (hf : ContinuousOn f s) : IsPreconnected (f '' s) := by
-- Unfold/destruct definitions in hypotheses
rintro u v hu hv huv ⟨_, ⟨x, xs, rfl⟩, xu⟩ ⟨_, ⟨y, ys, rfl⟩, yv⟩
rcases continuousOn_iff'.1 hf u hu with ⟨u', hu', u'_eq⟩
rcases continuousOn_iff'.1 hf v hv with ⟨v', hv', v'_eq⟩
-- Reformulate `huv : f '' s ⊆ u ∪ v` in terms of `u'` and `v'`
replace huv : s ⊆ u' ∪ v' := by
rw [image_subset_iff, preimage_union] at huv
replace huv := subset_inter huv Subset.rfl
rw [union_inter_distrib_right, u'_eq, v'_eq, ← union_inter_distrib_right] at huv
exact (subset_inter_iff.1 huv).1
-- Now `s ⊆ u' ∪ v'`, so we can apply `‹IsPreconnected s›`
obtain ⟨z, hz⟩ : (s ∩ (u' ∩ v')).Nonempty := by
refine H u' v' hu' hv' huv ⟨x, ?_⟩ ⟨y, ?_⟩ <;> rw [inter_comm]
exacts [u'_eq ▸ ⟨xu, xs⟩, v'_eq ▸ ⟨yv, ys⟩]
rw [← inter_self s, inter_assoc, inter_left_comm s u', ← inter_assoc, inter_comm s, inter_comm s,
← u'_eq, ← v'_eq] at hz
exact ⟨f z, ⟨z, hz.1.2, rfl⟩, hz.1.1, hz.2.1⟩
/-- The image of a connected set is connected as well. -/
protected theorem IsConnected.image [TopologicalSpace β] {s : Set α} (H : IsConnected s) (f : α → β)
(hf : ContinuousOn f s) : IsConnected (f '' s) :=
⟨image_nonempty.mpr H.nonempty, H.isPreconnected.image f hf⟩
theorem isPreconnected_closed_iff {s : Set α} :
IsPreconnected s ↔ ∀ t t', IsClosed t → IsClosed t' →
s ⊆ t ∪ t' → (s ∩ t).Nonempty → (s ∩ t').Nonempty → (s ∩ (t ∩ t')).Nonempty :=
⟨by
rintro h t t' ht ht' htt' ⟨x, xs, xt⟩ ⟨y, ys, yt'⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xt' : x ∉ t' := (h' xs).resolve_left (absurd xt)
have yt : y ∉ t := (h' ys).resolve_right (absurd yt')
have := h _ _ ht.isOpen_compl ht'.isOpen_compl h' ⟨y, ys, yt⟩ ⟨x, xs, xt'⟩
rw [← compl_union] at this
exact this.ne_empty htt'.disjoint_compl_right.inter_eq,
by
rintro h u v hu hv huv ⟨x, xs, xu⟩ ⟨y, ys, yv⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xv : x ∉ v := (h' xs).elim (absurd xu) id
have yu : y ∉ u := (h' ys).elim id (absurd yv)
have := h _ _ hu.isClosed_compl hv.isClosed_compl h' ⟨y, ys, yu⟩ ⟨x, xs, xv⟩
rw [← compl_union] at this
exact this.ne_empty huv.disjoint_compl_right.inter_eq⟩
theorem Topology.IsInducing.isPreconnected_image [TopologicalSpace β] {s : Set α} {f : α → β}
(hf : IsInducing f) : IsPreconnected (f '' s) ↔ IsPreconnected s := by
refine ⟨fun h => ?_, fun h => h.image _ hf.continuous.continuousOn⟩
rintro u v hu' hv' huv ⟨x, hxs, hxu⟩ ⟨y, hys, hyv⟩
rcases hf.isOpen_iff.1 hu' with ⟨u, hu, rfl⟩
rcases hf.isOpen_iff.1 hv' with ⟨v, hv, rfl⟩
replace huv : f '' s ⊆ u ∪ v := by rwa [image_subset_iff]
rcases h u v hu hv huv ⟨f x, mem_image_of_mem _ hxs, hxu⟩ ⟨f y, mem_image_of_mem _ hys, hyv⟩ with
⟨_, ⟨z, hzs, rfl⟩, hzuv⟩
exact ⟨z, hzs, hzuv⟩
@[deprecated (since := "2024-10-28")]
alias Inducing.isPreconnected_image := IsInducing.isPreconnected_image
/- TODO: The following lemmas about connection of preimages hold more generally for strict maps
(the quotient and subspace topologies of the image agree) whose fibers are preconnected. -/
theorem IsPreconnected.preimage_of_isOpenMap [TopologicalSpace β] {f : α → β} {s : Set β}
(hs : IsPreconnected s) (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsPreconnected (f ⁻¹' s) := fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by
refine hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
theorem IsPreconnected.preimage_of_isClosedMap [TopologicalSpace β] {s : Set β}
(hs : IsPreconnected s) {f : α → β} (hinj : Function.Injective f) (hf : IsClosedMap f)
(hsf : s ⊆ range f) : IsPreconnected (f ⁻¹' s) :=
isPreconnected_closed_iff.2 fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by
refine isPreconnected_closed_iff.1 hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
theorem IsConnected.preimage_of_isOpenMap [TopologicalSpace β] {s : Set β} (hs : IsConnected s)
{f : α → β} (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsConnected (f ⁻¹' s) :=
⟨hs.nonempty.preimage' hsf, hs.isPreconnected.preimage_of_isOpenMap hinj hf hsf⟩
theorem IsConnected.preimage_of_isClosedMap [TopologicalSpace β] {s : Set β} (hs : IsConnected s)
{f : α → β} (hinj : Function.Injective f) (hf : IsClosedMap f) (hsf : s ⊆ range f) :
IsConnected (f ⁻¹' s) :=
⟨hs.nonempty.preimage' hsf, hs.isPreconnected.preimage_of_isClosedMap hinj hf hsf⟩
theorem IsPreconnected.subset_or_subset (hu : IsOpen u) (hv : IsOpen v) (huv : Disjoint u v)
(hsuv : s ⊆ u ∪ v) (hs : IsPreconnected s) : s ⊆ u ∨ s ⊆ v := by
specialize hs u v hu hv hsuv
obtain hsu | hsu := (s ∩ u).eq_empty_or_nonempty
· exact Or.inr ((Set.disjoint_iff_inter_eq_empty.2 hsu).subset_right_of_subset_union hsuv)
· replace hs := mt (hs hsu)
simp_rw [Set.not_nonempty_iff_eq_empty, ← Set.disjoint_iff_inter_eq_empty,
disjoint_iff_inter_eq_empty.1 huv] at hs
exact Or.inl ((hs s.disjoint_empty).subset_left_of_subset_union hsuv)
theorem IsPreconnected.subset_left_of_subset_union (hu : IsOpen u) (hv : IsOpen v)
(huv : Disjoint u v) (hsuv : s ⊆ u ∪ v) (hsu : (s ∩ u).Nonempty) (hs : IsPreconnected s) :
s ⊆ u :=
Disjoint.subset_left_of_subset_union hsuv
(by
by_contra hsv
rw [not_disjoint_iff_nonempty_inter] at hsv
obtain ⟨x, _, hx⟩ := hs u v hu hv hsuv hsu hsv
exact Set.disjoint_iff.1 huv hx)
theorem IsPreconnected.subset_right_of_subset_union (hu : IsOpen u) (hv : IsOpen v)
(huv : Disjoint u v) (hsuv : s ⊆ u ∪ v) (hsv : (s ∩ v).Nonempty) (hs : IsPreconnected s) :
s ⊆ v :=
hs.subset_left_of_subset_union hv hu huv.symm (union_comm u v ▸ hsuv) hsv
/-- If a preconnected set `s` intersects an open set `u`, and limit points of `u` inside `s` are
contained in `u`, then the whole set `s` is contained in `u`. -/
theorem IsPreconnected.subset_of_closure_inter_subset (hs : IsPreconnected s) (hu : IsOpen u)
(h'u : (s ∩ u).Nonempty) (h : closure u ∩ s ⊆ u) : s ⊆ u := by
have A : s ⊆ u ∪ (closure u)ᶜ := by
intro x hx
by_cases xu : x ∈ u
· exact Or.inl xu
· right
intro h'x
exact xu (h (mem_inter h'x hx))
apply hs.subset_left_of_subset_union hu isClosed_closure.isOpen_compl _ A h'u
exact disjoint_compl_right.mono_right (compl_subset_compl.2 subset_closure)
theorem IsPreconnected.prod [TopologicalSpace β] {s : Set α} {t : Set β} (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ×ˢ t) := by
apply isPreconnected_of_forall_pair
rintro ⟨a₁, b₁⟩ ⟨ha₁, hb₁⟩ ⟨a₂, b₂⟩ ⟨ha₂, hb₂⟩
refine ⟨Prod.mk a₁ '' t ∪ flip Prod.mk b₂ '' s, ?_, .inl ⟨b₁, hb₁, rfl⟩, .inr ⟨a₂, ha₂, rfl⟩, ?_⟩
· rintro _ (⟨y, hy, rfl⟩ | ⟨x, hx, rfl⟩)
exacts [⟨ha₁, hy⟩, ⟨hx, hb₂⟩]
· exact (ht.image _ (by fun_prop)).union (a₁, b₂) ⟨b₂, hb₂, rfl⟩
⟨a₁, ha₁, rfl⟩ (hs.image _ (Continuous.prodMk_left _).continuousOn)
theorem IsConnected.prod [TopologicalSpace β] {s : Set α} {t : Set β} (hs : IsConnected s)
(ht : IsConnected t) : IsConnected (s ×ˢ t) :=
⟨hs.1.prod ht.1, hs.2.prod ht.2⟩
theorem isPreconnected_univ_pi [∀ i, TopologicalSpace (π i)] {s : ∀ i, Set (π i)}
(hs : ∀ i, IsPreconnected (s i)) : IsPreconnected (pi univ s) := by
rintro u v uo vo hsuv ⟨f, hfs, hfu⟩ ⟨g, hgs, hgv⟩
classical
rcases exists_finset_piecewise_mem_of_mem_nhds (uo.mem_nhds hfu) g with ⟨I, hI⟩
induction I using Finset.induction_on with
| empty =>
refine ⟨g, hgs, ⟨?_, hgv⟩⟩
simpa using hI
| insert i I _ ihI =>
rw [Finset.piecewise_insert] at hI
have := I.piecewise_mem_set_pi hfs hgs
refine (hsuv this).elim ihI fun h => ?_
set S := update (I.piecewise f g) i '' s i
have hsub : S ⊆ pi univ s := by
refine image_subset_iff.2 fun z hz => ?_
rwa [update_preimage_univ_pi]
exact fun j _ => this j trivial
have hconn : IsPreconnected S :=
(hs i).image _ (continuous_const.update i continuous_id).continuousOn
have hSu : (S ∩ u).Nonempty := ⟨_, mem_image_of_mem _ (hfs _ trivial), hI⟩
have hSv : (S ∩ v).Nonempty := ⟨_, ⟨_, this _ trivial, update_eq_self _ _⟩, h⟩
refine (hconn u v uo vo (hsub.trans hsuv) hSu hSv).mono ?_
exact inter_subset_inter_left _ hsub
@[simp]
theorem isConnected_univ_pi [∀ i, TopologicalSpace (π i)] {s : ∀ i, Set (π i)} :
IsConnected (pi univ s) ↔ ∀ i, IsConnected (s i) := by
simp only [IsConnected, ← univ_pi_nonempty_iff, forall_and, and_congr_right_iff]
refine fun hne => ⟨fun hc i => ?_, isPreconnected_univ_pi⟩
rw [← eval_image_univ_pi hne]
exact hc.image _ (continuous_apply _).continuousOn
/-- The connected component of a point is the maximal connected set
that contains this point. -/
def connectedComponent (x : α) : Set α :=
⋃₀ { s : Set α | IsPreconnected s ∧ x ∈ s }
open Classical in
/-- Given a set `F` in a topological space `α` and a point `x : α`, the connected
component of `x` in `F` is the connected component of `x` in the subtype `F` seen as
a set in `α`. This definition does not make sense if `x` is not in `F` so we return the
empty set in this case. -/
def connectedComponentIn (F : Set α) (x : α) : Set α :=
if h : x ∈ F then (↑) '' connectedComponent (⟨x, h⟩ : F) else ∅
theorem connectedComponentIn_eq_image {F : Set α} {x : α} (h : x ∈ F) :
connectedComponentIn F x = (↑) '' connectedComponent (⟨x, h⟩ : F) :=
dif_pos h
theorem connectedComponentIn_eq_empty {F : Set α} {x : α} (h : x ∉ F) :
connectedComponentIn F x = ∅ :=
dif_neg h
theorem mem_connectedComponent {x : α} : x ∈ connectedComponent x :=
mem_sUnion_of_mem (mem_singleton x) ⟨isPreconnected_singleton, mem_singleton x⟩
theorem mem_connectedComponentIn {x : α} {F : Set α} (hx : x ∈ F) :
x ∈ connectedComponentIn F x := by
simp [connectedComponentIn_eq_image hx, mem_connectedComponent, hx]
theorem connectedComponent_nonempty {x : α} : (connectedComponent x).Nonempty :=
⟨x, mem_connectedComponent⟩
theorem connectedComponentIn_nonempty_iff {x : α} {F : Set α} :
(connectedComponentIn F x).Nonempty ↔ x ∈ F := by
rw [connectedComponentIn]
split_ifs <;> simp [connectedComponent_nonempty, *]
theorem connectedComponentIn_subset (F : Set α) (x : α) : connectedComponentIn F x ⊆ F := by
rw [connectedComponentIn]
split_ifs <;> simp
theorem isPreconnected_connectedComponent {x : α} : IsPreconnected (connectedComponent x) :=
isPreconnected_sUnion x _ (fun _ => And.right) fun _ => And.left
theorem isPreconnected_connectedComponentIn {x : α} {F : Set α} :
IsPreconnected (connectedComponentIn F x) := by
rw [connectedComponentIn]; split_ifs
· exact IsInducing.subtypeVal.isPreconnected_image.mpr isPreconnected_connectedComponent
· exact isPreconnected_empty
theorem isConnected_connectedComponent {x : α} : IsConnected (connectedComponent x) :=
⟨⟨x, mem_connectedComponent⟩, isPreconnected_connectedComponent⟩
theorem isConnected_connectedComponentIn_iff {x : α} {F : Set α} :
IsConnected (connectedComponentIn F x) ↔ x ∈ F := by
simp_rw [← connectedComponentIn_nonempty_iff, IsConnected, isPreconnected_connectedComponentIn,
and_true]
theorem IsPreconnected.subset_connectedComponent {x : α} {s : Set α} (H1 : IsPreconnected s)
(H2 : x ∈ s) : s ⊆ connectedComponent x := fun _z hz => mem_sUnion_of_mem hz ⟨H1, H2⟩
theorem IsPreconnected.subset_connectedComponentIn {x : α} {F : Set α} (hs : IsPreconnected s)
(hxs : x ∈ s) (hsF : s ⊆ F) : s ⊆ connectedComponentIn F x := by
have : IsPreconnected (((↑) : F → α) ⁻¹' s) := by
refine IsInducing.subtypeVal.isPreconnected_image.mp ?_
rwa [Subtype.image_preimage_coe, inter_eq_right.mpr hsF]
have h2xs : (⟨x, hsF hxs⟩ : F) ∈ (↑) ⁻¹' s := by
rw [mem_preimage]
exact hxs
have := this.subset_connectedComponent h2xs
rw [connectedComponentIn_eq_image (hsF hxs)]
refine Subset.trans ?_ (image_subset _ this)
rw [Subtype.image_preimage_coe, inter_eq_right.mpr hsF]
theorem IsConnected.subset_connectedComponent {x : α} {s : Set α} (H1 : IsConnected s)
(H2 : x ∈ s) : s ⊆ connectedComponent x :=
H1.2.subset_connectedComponent H2
theorem IsPreconnected.connectedComponentIn {x : α} {F : Set α} (h : IsPreconnected F)
(hx : x ∈ F) : connectedComponentIn F x = F :=
(connectedComponentIn_subset F x).antisymm (h.subset_connectedComponentIn hx subset_rfl)
theorem connectedComponent_eq {x y : α} (h : y ∈ connectedComponent x) :
connectedComponent x = connectedComponent y :=
eq_of_subset_of_subset (isConnected_connectedComponent.subset_connectedComponent h)
(isConnected_connectedComponent.subset_connectedComponent
(Set.mem_of_mem_of_subset mem_connectedComponent
(isConnected_connectedComponent.subset_connectedComponent h)))
theorem connectedComponent_eq_iff_mem {x y : α} :
connectedComponent x = connectedComponent y ↔ x ∈ connectedComponent y :=
⟨fun h => h ▸ mem_connectedComponent, fun h => (connectedComponent_eq h).symm⟩
theorem connectedComponentIn_eq {x y : α} {F : Set α} (h : y ∈ connectedComponentIn F x) :
connectedComponentIn F x = connectedComponentIn F y := by
have hx : x ∈ F := connectedComponentIn_nonempty_iff.mp ⟨y, h⟩
simp_rw [connectedComponentIn_eq_image hx] at h ⊢
obtain ⟨⟨y, hy⟩, h2y, rfl⟩ := h
simp_rw [connectedComponentIn_eq_image hy, connectedComponent_eq h2y]
theorem connectedComponentIn_univ (x : α) : connectedComponentIn univ x = connectedComponent x :=
subset_antisymm
(isPreconnected_connectedComponentIn.subset_connectedComponent <|
mem_connectedComponentIn trivial)
(isPreconnected_connectedComponent.subset_connectedComponentIn mem_connectedComponent <|
subset_univ _)
theorem connectedComponent_disjoint {x y : α} (h : connectedComponent x ≠ connectedComponent y) :
Disjoint (connectedComponent x) (connectedComponent y) :=
Set.disjoint_left.2 fun _ h1 h2 =>
h ((connectedComponent_eq h1).trans (connectedComponent_eq h2).symm)
theorem isClosed_connectedComponent {x : α} : IsClosed (connectedComponent x) :=
closure_subset_iff_isClosed.1 <|
isConnected_connectedComponent.closure.subset_connectedComponent <|
subset_closure mem_connectedComponent
theorem Continuous.image_connectedComponent_subset [TopologicalSpace β] {f : α → β}
(h : Continuous f) (a : α) : f '' connectedComponent a ⊆ connectedComponent (f a) :=
(isConnected_connectedComponent.image f h.continuousOn).subset_connectedComponent
((mem_image f (connectedComponent a) (f a)).2 ⟨a, mem_connectedComponent, rfl⟩)
theorem Continuous.image_connectedComponentIn_subset [TopologicalSpace β] {f : α → β} {s : Set α}
{a : α} (hf : Continuous f) (hx : a ∈ s) :
f '' connectedComponentIn s a ⊆ connectedComponentIn (f '' s) (f a) :=
(isPreconnected_connectedComponentIn.image _ hf.continuousOn).subset_connectedComponentIn
(mem_image_of_mem _ <| mem_connectedComponentIn hx)
(image_subset _ <| connectedComponentIn_subset _ _)
theorem Continuous.mapsTo_connectedComponent [TopologicalSpace β] {f : α → β} (h : Continuous f)
(a : α) : MapsTo f (connectedComponent a) (connectedComponent (f a)) :=
mapsTo'.2 <| h.image_connectedComponent_subset a
theorem Continuous.mapsTo_connectedComponentIn [TopologicalSpace β] {f : α → β} {s : Set α}
(h : Continuous f) {a : α} (hx : a ∈ s) :
MapsTo f (connectedComponentIn s a) (connectedComponentIn (f '' s) (f a)) :=
mapsTo'.2 <| image_connectedComponentIn_subset h hx
theorem irreducibleComponent_subset_connectedComponent {x : α} :
irreducibleComponent x ⊆ connectedComponent x :=
isIrreducible_irreducibleComponent.isConnected.subset_connectedComponent mem_irreducibleComponent
@[mono]
theorem connectedComponentIn_mono (x : α) {F G : Set α} (h : F ⊆ G) :
connectedComponentIn F x ⊆ connectedComponentIn G x := by
by_cases hx : x ∈ F
· rw [connectedComponentIn_eq_image hx, connectedComponentIn_eq_image (h hx), ←
show ((↑) : G → α) ∘ inclusion h = (↑) from rfl, image_comp]
exact image_subset _ ((continuous_inclusion h).image_connectedComponent_subset ⟨x, hx⟩)
· rw [connectedComponentIn_eq_empty hx]
exact Set.empty_subset _
/-- A preconnected space is one where there is no non-trivial open partition. -/
class PreconnectedSpace (α : Type u) [TopologicalSpace α] : Prop where
/-- The universal set `Set.univ` in a preconnected space is a preconnected set. -/
isPreconnected_univ : IsPreconnected (univ : Set α)
export PreconnectedSpace (isPreconnected_univ)
/-- A connected space is a nonempty one where there is no non-trivial open partition. -/
class ConnectedSpace (α : Type u) [TopologicalSpace α] : Prop extends PreconnectedSpace α where
/-- A connected space is nonempty. -/
toNonempty : Nonempty α
attribute [instance 50] ConnectedSpace.toNonempty -- see Note [lower instance priority]
-- see Note [lower instance priority]
theorem isConnected_univ [ConnectedSpace α] : IsConnected (univ : Set α) :=
⟨univ_nonempty, isPreconnected_univ⟩
lemma preconnectedSpace_iff_univ : PreconnectedSpace α ↔ IsPreconnected (univ : Set α) :=
⟨fun h ↦ h.1, fun h ↦ ⟨h⟩⟩
lemma connectedSpace_iff_univ : ConnectedSpace α ↔ IsConnected (univ : Set α) :=
⟨fun h ↦ ⟨univ_nonempty, h.1.1⟩,
fun h ↦ ConnectedSpace.mk (toPreconnectedSpace := ⟨h.2⟩) ⟨h.1.some⟩⟩
theorem isPreconnected_range [TopologicalSpace β] [PreconnectedSpace α] {f : α → β}
(h : Continuous f) : IsPreconnected (range f) :=
@image_univ _ _ f ▸ isPreconnected_univ.image _ h.continuousOn
theorem isConnected_range [TopologicalSpace β] [ConnectedSpace α] {f : α → β} (h : Continuous f) :
IsConnected (range f) :=
⟨range_nonempty f, isPreconnected_range h⟩
theorem Function.Surjective.connectedSpace [ConnectedSpace α] [TopologicalSpace β]
{f : α → β} (hf : Surjective f) (hf' : Continuous f) : ConnectedSpace β := by
rw [connectedSpace_iff_univ, ← hf.range_eq]
exact isConnected_range hf'
instance Quotient.instConnectedSpace {s : Setoid α} [ConnectedSpace α] :
ConnectedSpace (Quotient s) :=
Quotient.mk'_surjective.connectedSpace continuous_coinduced_rng
theorem DenseRange.preconnectedSpace [TopologicalSpace β] [PreconnectedSpace α] {f : α → β}
(hf : DenseRange f) (hc : Continuous f) : PreconnectedSpace β :=
⟨hf.closure_eq ▸ (isPreconnected_range hc).closure⟩
theorem connectedSpace_iff_connectedComponent :
ConnectedSpace α ↔ ∃ x : α, connectedComponent x = univ := by
constructor
· rintro ⟨⟨x⟩⟩
exact
⟨x, eq_univ_of_univ_subset <| isPreconnected_univ.subset_connectedComponent (mem_univ x)⟩
· rintro ⟨x, h⟩
haveI : PreconnectedSpace α :=
⟨by rw [← h]; exact isPreconnected_connectedComponent⟩
exact ⟨⟨x⟩⟩
theorem preconnectedSpace_iff_connectedComponent :
PreconnectedSpace α ↔ ∀ x : α, connectedComponent x = univ := by
constructor
· intro h x
exact eq_univ_of_univ_subset <| isPreconnected_univ.subset_connectedComponent (mem_univ x)
· intro h
rcases isEmpty_or_nonempty α with hα | hα
· exact ⟨by rw [univ_eq_empty_iff.mpr hα]; exact isPreconnected_empty⟩
· exact ⟨by rw [← h (Classical.choice hα)]; exact isPreconnected_connectedComponent⟩
@[simp]
theorem PreconnectedSpace.connectedComponent_eq_univ {X : Type*} [TopologicalSpace X]
[h : PreconnectedSpace X] (x : X) : connectedComponent x = univ :=
preconnectedSpace_iff_connectedComponent.mp h x
instance [TopologicalSpace β] [PreconnectedSpace α] [PreconnectedSpace β] :
PreconnectedSpace (α × β) :=
⟨by
rw [← univ_prod_univ]
exact isPreconnected_univ.prod isPreconnected_univ⟩
instance [TopologicalSpace β] [ConnectedSpace α] [ConnectedSpace β] : ConnectedSpace (α × β) :=
⟨inferInstance⟩
instance [∀ i, TopologicalSpace (π i)] [∀ i, PreconnectedSpace (π i)] :
PreconnectedSpace (∀ i, π i) :=
⟨by rw [← pi_univ univ]; exact isPreconnected_univ_pi fun i => isPreconnected_univ⟩
instance [∀ i, TopologicalSpace (π i)] [∀ i, ConnectedSpace (π i)] : ConnectedSpace (∀ i, π i) :=
⟨inferInstance⟩
-- see Note [lower instance priority]
instance (priority := 100) PreirreducibleSpace.preconnectedSpace (α : Type u) [TopologicalSpace α]
[PreirreducibleSpace α] : PreconnectedSpace α :=
⟨isPreirreducible_univ.isPreconnected⟩
-- see Note [lower instance priority]
instance (priority := 100) IrreducibleSpace.connectedSpace (α : Type u) [TopologicalSpace α]
[IrreducibleSpace α] : ConnectedSpace α where toNonempty := IrreducibleSpace.toNonempty
theorem Subtype.preconnectedSpace {s : Set α} (h : IsPreconnected s) : PreconnectedSpace s where
isPreconnected_univ := by
rwa [← IsInducing.subtypeVal.isPreconnected_image, image_univ, Subtype.range_val]
theorem Subtype.connectedSpace {s : Set α} (h : IsConnected s) : ConnectedSpace s where
toPreconnectedSpace := Subtype.preconnectedSpace h.isPreconnected
toNonempty := h.nonempty.to_subtype
theorem isPreconnected_iff_preconnectedSpace {s : Set α} : IsPreconnected s ↔ PreconnectedSpace s :=
⟨Subtype.preconnectedSpace, fun h => by
simpa using isPreconnected_univ.image ((↑) : s → α) continuous_subtype_val.continuousOn⟩
theorem isConnected_iff_connectedSpace {s : Set α} : IsConnected s ↔ ConnectedSpace s :=
⟨Subtype.connectedSpace, fun h =>
⟨nonempty_subtype.mp h.2, isPreconnected_iff_preconnectedSpace.mpr h.1⟩⟩
end Preconnected
| Mathlib/Topology/Connected/Basic.lean | 1,027 | 1,047 | |
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Algebra.Squarefree.Basic
import Mathlib.FieldTheory.IntermediateField.Basic
import Mathlib.FieldTheory.Minpoly.Field
import Mathlib.RingTheory.Polynomial.Content
import Mathlib.RingTheory.PowerBasis
import Mathlib.Data.ENat.Lattice
/-!
# Separable polynomials
We define a polynomial to be separable if it is coprime with its derivative. We prove basic
properties about separable polynomials here.
## Main definitions
* `Polynomial.Separable f`: a polynomial `f` is separable iff it is coprime with its derivative.
* `IsSeparable K x`: an element `x` is separable over `K` iff the minimal polynomial of `x`
over `K` is separable.
* `Algebra.IsSeparable K L`: `L` is separable over `K` iff every element in `L` is separable
over `K`.
-/
universe u v w
open Polynomial Finset
namespace Polynomial
section CommSemiring
variable {R : Type u} [CommSemiring R] {S : Type v} [CommSemiring S]
/-- A polynomial is separable iff it is coprime with its derivative. -/
@[stacks 09H1 "first part"]
def Separable (f : R[X]) : Prop :=
IsCoprime f (derivative f)
theorem separable_def (f : R[X]) : f.Separable ↔ IsCoprime f (derivative f) :=
Iff.rfl
theorem separable_def' (f : R[X]) : f.Separable ↔ ∃ a b : R[X], a * f + b * (derivative f) = 1 :=
Iff.rfl
theorem not_separable_zero [Nontrivial R] : ¬Separable (0 : R[X]) := by
rintro ⟨x, y, h⟩
simp only [derivative_zero, mul_zero, add_zero, zero_ne_one] at h
theorem Separable.ne_zero [Nontrivial R] {f : R[X]} (h : f.Separable) : f ≠ 0 :=
(not_separable_zero <| · ▸ h)
@[simp]
theorem separable_one : (1 : R[X]).Separable :=
isCoprime_one_left
@[nontriviality]
theorem separable_of_subsingleton [Subsingleton R] (f : R[X]) : f.Separable := by
simp [Separable, IsCoprime, eq_iff_true_of_subsingleton]
theorem separable_X_add_C (a : R) : (X + C a).Separable := by
rw [separable_def, derivative_add, derivative_X, derivative_C, add_zero]
exact isCoprime_one_right
theorem separable_X : (X : R[X]).Separable := by
rw [separable_def, derivative_X]
exact isCoprime_one_right
theorem separable_C (r : R) : (C r).Separable ↔ IsUnit r := by
rw [separable_def, derivative_C, isCoprime_zero_right, isUnit_C]
theorem Separable.of_mul_left {f g : R[X]} (h : (f * g).Separable) : f.Separable := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_left (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_mul_right {f g : R[X]} (h : (f * g).Separable) : g.Separable := by
rw [mul_comm] at h
exact h.of_mul_left
theorem Separable.of_dvd {f g : R[X]} (hf : f.Separable) (hfg : g ∣ f) : g.Separable := by
rcases hfg with ⟨f', rfl⟩
exact Separable.of_mul_left hf
theorem separable_gcd_left {F : Type*} [Field F] [DecidableEq F[X]]
{f : F[X]} (hf : f.Separable) (g : F[X]) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hf (EuclideanDomain.gcd_dvd_left f g)
theorem separable_gcd_right {F : Type*} [Field F] [DecidableEq F[X]]
{g : F[X]} (f : F[X]) (hg : g.Separable) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hg (EuclideanDomain.gcd_dvd_right f g)
theorem Separable.isCoprime {f g : R[X]} (h : (f * g).Separable) : IsCoprime f g := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_right (IsCoprime.of_add_mul_left_right this)
theorem Separable.of_pow' {f : R[X]} :
∀ {n : ℕ} (_h : (f ^ n).Separable), IsUnit f ∨ f.Separable ∧ n = 1 ∨ n = 0
| 0 => fun _h => Or.inr <| Or.inr rfl
| 1 => fun h => Or.inr <| Or.inl ⟨pow_one f ▸ h, rfl⟩
| n + 2 => fun h => by
rw [pow_succ, pow_succ] at h
exact Or.inl (isCoprime_self.1 h.isCoprime.of_mul_left_right)
theorem Separable.of_pow {f : R[X]} (hf : ¬IsUnit f) {n : ℕ} (hn : n ≠ 0)
(hfs : (f ^ n).Separable) : f.Separable ∧ n = 1 :=
(hfs.of_pow'.resolve_left hf).resolve_right hn
theorem Separable.map {p : R[X]} (h : p.Separable) {f : R →+* S} : (p.map f).Separable :=
let ⟨a, b, H⟩ := h
⟨a.map f, b.map f, by
rw [derivative_map, ← Polynomial.map_mul, ← Polynomial.map_mul, ← Polynomial.map_add, H,
Polynomial.map_one]⟩
theorem _root_.Associated.separable {f g : R[X]}
(ha : Associated f g) (h : f.Separable) : g.Separable := by
obtain ⟨⟨u, v, h1, h2⟩, ha⟩ := ha
obtain ⟨a, b, h⟩ := h
refine ⟨a * v + b * derivative v, b * v, ?_⟩
replace h := congr($h * $(h1))
have h3 := congr(derivative $(h1))
simp only [← ha, derivative_mul, derivative_one] at h3 ⊢
calc
_ = (a * f + b * derivative f) * (u * v)
+ (b * f) * (derivative u * v + u * derivative v) := by ring1
_ = 1 := by rw [h, h3]; ring1
theorem _root_.Associated.separable_iff {f g : R[X]}
(ha : Associated f g) : f.Separable ↔ g.Separable := ⟨ha.separable, ha.symm.separable⟩
theorem Separable.mul_unit {f g : R[X]} (hf : f.Separable) (hg : IsUnit g) : (f * g).Separable :=
(associated_mul_unit_right f g hg).separable hf
theorem Separable.unit_mul {f g : R[X]} (hf : IsUnit f) (hg : g.Separable) : (f * g).Separable :=
(associated_unit_mul_right g f hf).separable hg
theorem Separable.eval₂_derivative_ne_zero [Nontrivial S] (f : R →+* S) {p : R[X]}
(h : p.Separable) {x : S} (hx : p.eval₂ f x = 0) :
(derivative p).eval₂ f x ≠ 0 := by
intro hx'
obtain ⟨a, b, e⟩ := h
apply_fun Polynomial.eval₂ f x at e
simp only [eval₂_add, eval₂_mul, hx, mul_zero, hx', add_zero, eval₂_one, zero_ne_one] at e
theorem Separable.aeval_derivative_ne_zero [Nontrivial S] [Algebra R S] {p : R[X]}
(h : p.Separable) {x : S} (hx : aeval x p = 0) :
aeval x (derivative p) ≠ 0 :=
h.eval₂_derivative_ne_zero (algebraMap R S) hx
variable (p q : ℕ)
theorem isUnit_of_self_mul_dvd_separable {p q : R[X]} (hp : p.Separable) (hq : q * q ∣ p) :
IsUnit q := by
obtain ⟨p, rfl⟩ := hq
apply isCoprime_self.mp
have : IsCoprime (q * (q * p))
(q * (derivative q * p + derivative q * p + q * derivative p)) := by
simp only [← mul_assoc, mul_add]
dsimp only [Separable] at hp
convert hp using 1
rw [derivative_mul, derivative_mul]
ring
exact IsCoprime.of_mul_right_left (IsCoprime.of_mul_left_left this)
theorem emultiplicity_le_one_of_separable {p q : R[X]} (hq : ¬IsUnit q) (hsep : Separable p) :
emultiplicity q p ≤ 1 := by
contrapose! hq
apply isUnit_of_self_mul_dvd_separable hsep
rw [← sq]
apply pow_dvd_of_le_emultiplicity
exact Order.add_one_le_of_lt hq
/-- A separable polynomial is square-free.
See `PerfectField.separable_iff_squarefree` for the converse when the coefficients are a perfect
field. -/
theorem Separable.squarefree {p : R[X]} (hsep : Separable p) : Squarefree p := by
classical
rw [squarefree_iff_emultiplicity_le_one p]
exact fun f => or_iff_not_imp_right.mpr fun hunit => emultiplicity_le_one_of_separable hunit hsep
end CommSemiring
section CommRing
variable {R : Type u} [CommRing R]
theorem separable_X_sub_C {x : R} : Separable (X - C x) := by
simpa only [sub_eq_add_neg, C_neg] using separable_X_add_C (-x)
theorem Separable.mul {f g : R[X]} (hf : f.Separable) (hg : g.Separable) (h : IsCoprime f g) :
(f * g).Separable := by
rw [separable_def, derivative_mul]
exact
((hf.mul_right h).add_mul_left_right _).mul_left ((h.symm.mul_right hg).mul_add_right_right _)
theorem separable_prod' {ι : Sort _} {f : ι → R[X]} {s : Finset ι} :
(∀ x ∈ s, ∀ y ∈ s, x ≠ y → IsCoprime (f x) (f y)) →
(∀ x ∈ s, (f x).Separable) → (∏ x ∈ s, f x).Separable := by
classical
exact Finset.induction_on s (fun _ _ => separable_one) fun a s has ih h1 h2 => by
simp_rw [Finset.forall_mem_insert, forall_and] at h1 h2; rw [prod_insert has]
exact
h2.1.mul (ih h1.2.2 h2.2)
(IsCoprime.prod_right fun i his => h1.1.2 i his <| Ne.symm <| ne_of_mem_of_not_mem his has)
open scoped Function in -- required for scoped `on` notation
theorem separable_prod {ι : Sort _} [Fintype ι] {f : ι → R[X]} (h1 : Pairwise (IsCoprime on f))
(h2 : ∀ x, (f x).Separable) : (∏ x, f x).Separable :=
separable_prod' (fun _x _hx _y _hy hxy => h1 hxy) fun x _hx => h2 x
theorem Separable.inj_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} {f : ι → R} {s : Finset ι}
(hfs : (∏ i ∈ s, (X - C (f i))).Separable) {x y : ι} (hx : x ∈ s) (hy : y ∈ s)
(hfxy : f x = f y) : x = y := by
classical
by_contra hxy
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase_of_ne_of_mem (Ne.symm hxy) hy), prod_insert (not_mem_erase _ _), ←
mul_assoc, hfxy, ← sq] at hfs
cases (hfs.of_mul_left.of_pow (not_isUnit_X_sub_C _) two_ne_zero).2
theorem Separable.injective_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} [Fintype ι] {f : ι → R}
(hfs : (∏ i, (X - C (f i))).Separable) : Function.Injective f := fun _x _y hfxy =>
hfs.inj_of_prod_X_sub_C (mem_univ _) (mem_univ _) hfxy
theorem nodup_of_separable_prod [Nontrivial R] {s : Multiset R}
(hs : Separable (Multiset.map (fun a => X - C a) s).prod) : s.Nodup := by
rw [Multiset.nodup_iff_ne_cons_cons]
rintro a t rfl
refine not_isUnit_X_sub_C a (isUnit_of_self_mul_dvd_separable hs ?_)
simpa only [Multiset.map_cons, Multiset.prod_cons] using mul_dvd_mul_left _ (dvd_mul_right _ _)
/-- If `IsUnit n` in a `CommRing R`, then `X ^ n - u` is separable for any unit `u`. -/
theorem separable_X_pow_sub_C_unit {n : ℕ} (u : Rˣ) (hn : IsUnit (n : R)) :
Separable (X ^ n - C (u : R)) := by
nontriviality R
rcases n.eq_zero_or_pos with (rfl | hpos)
· simp at hn
apply (separable_def' (X ^ n - C (u : R))).2
obtain ⟨n', hn'⟩ := hn.exists_left_inv
refine ⟨-C ↑u⁻¹, C (↑u⁻¹ : R) * C n' * X, ?_⟩
rw [derivative_sub, derivative_C, sub_zero, derivative_pow X n, derivative_X, mul_one]
calc
-C ↑u⁻¹ * (X ^ n - C ↑u) + C ↑u⁻¹ * C n' * X * (↑n * X ^ (n - 1)) =
C (↑u⁻¹ * ↑u) - C ↑u⁻¹ * X ^ n + C ↑u⁻¹ * C (n' * ↑n) * (X * X ^ (n - 1)) := by
simp only [C.map_mul, C_eq_natCast]
ring
_ = 1 := by
simp only [Units.inv_mul, hn', C.map_one, mul_one, ← pow_succ',
Nat.sub_add_cancel (show 1 ≤ n from hpos), sub_add_cancel]
/-- If `n = 0` in `R` and `b` is a unit, then `a * X ^ n + b * X + c` is separable. -/
theorem separable_C_mul_X_pow_add_C_mul_X_add_C
{n : ℕ} (a b c : R) (hn : (n : R) = 0) (hb : IsUnit b) :
(C a * X ^ n + C b * X + C c).Separable := by
set f := C a * X ^ n + C b * X + C c
obtain ⟨e, hb⟩ := hb.exists_left_inv
refine ⟨-derivative f, f + C e, ?_⟩
have hderiv : derivative f = C b := by
simp [hn, f, map_add derivative, derivative_C, derivative_X_pow]
rw [hderiv, right_distrib, ← add_assoc, neg_mul, mul_comm, neg_add_cancel, zero_add,
← map_mul, hb, map_one]
/-- If `R` is of characteristic `p`, `p ∣ n` and `b` is a unit,
then `a * X ^ n + b * X + c` is separable. -/
theorem separable_C_mul_X_pow_add_C_mul_X_add_C'
(p n : ℕ) (a b c : R) [CharP R p] (hn : p ∣ n) (hb : IsUnit b) :
(C a * X ^ n + C b * X + C c).Separable :=
separable_C_mul_X_pow_add_C_mul_X_add_C a b c ((CharP.cast_eq_zero_iff R p n).2 hn) hb
theorem rootMultiplicity_le_one_of_separable [Nontrivial R] {p : R[X]} (hsep : Separable p)
(x : R) : rootMultiplicity x p ≤ 1 := by
classical
by_cases hp : p = 0
· simp [hp]
rw [rootMultiplicity_eq_multiplicity, if_neg hp, ← Nat.cast_le (α := ℕ∞),
Nat.cast_one, ← (finiteMultiplicity_X_sub_C x hp).emultiplicity_eq_multiplicity]
apply emultiplicity_le_one_of_separable (not_isUnit_X_sub_C _) hsep
end CommRing
section IsDomain
variable {R : Type u} [CommRing R] [IsDomain R]
theorem count_roots_le_one [DecidableEq R] {p : R[X]} (hsep : Separable p) (x : R) :
p.roots.count x ≤ 1 := by
rw [count_roots p]
exact rootMultiplicity_le_one_of_separable hsep x
theorem nodup_roots {p : R[X]} (hsep : Separable p) : p.roots.Nodup := by
classical
exact Multiset.nodup_iff_count_le_one.mpr (count_roots_le_one hsep)
end IsDomain
section Field
variable {F : Type u} [Field F] {K : Type v} [Field K]
theorem separable_iff_derivative_ne_zero {f : F[X]} (hf : Irreducible f) :
f.Separable ↔ derivative f ≠ 0 :=
⟨fun h1 h2 => hf.not_isUnit <| isCoprime_zero_right.1 <| h2 ▸ h1, fun h =>
EuclideanDomain.isCoprime_of_dvd (mt And.right h) fun g hg1 _hg2 ⟨p, hg3⟩ hg4 =>
let ⟨u, hu⟩ := (hf.isUnit_or_isUnit hg3).resolve_left hg1
have : f ∣ derivative f := by
conv_lhs => rw [hg3, ← hu]
rwa [Units.mul_right_dvd]
not_lt_of_le (natDegree_le_of_dvd this h) <|
natDegree_derivative_lt <| mt derivative_of_natDegree_zero h⟩
attribute [local instance] Ideal.Quotient.field in
theorem separable_map {S} [CommRing S] [Nontrivial S] (f : F →+* S) {p : F[X]} :
(p.map f).Separable ↔ p.Separable := by
refine ⟨fun H ↦ ?_, fun H ↦ H.map⟩
obtain ⟨m, hm⟩ := Ideal.exists_maximal S
have := Separable.map H (f := Ideal.Quotient.mk m)
rwa [map_map, separable_def, derivative_map, isCoprime_map] at this
theorem separable_prod_X_sub_C_iff' {ι : Sort _} {f : ι → F} {s : Finset ι} :
(∏ i ∈ s, (X - C (f i))).Separable ↔ ∀ x ∈ s, ∀ y ∈ s, f x = f y → x = y :=
⟨fun hfs _ hx _ hy hfxy => hfs.inj_of_prod_X_sub_C hx hy hfxy, fun H => by
rw [← prod_attach]
exact
separable_prod'
(fun x _hx y _hy hxy =>
@pairwise_coprime_X_sub_C _ _ { x // x ∈ s } (fun x => f x)
(fun x y hxy => Subtype.eq <| H x.1 x.2 y.1 y.2 hxy) _ _ hxy)
fun _ _ => separable_X_sub_C⟩
theorem separable_prod_X_sub_C_iff {ι : Sort _} [Fintype ι] {f : ι → F} :
(∏ i, (X - C (f i))).Separable ↔ Function.Injective f :=
separable_prod_X_sub_C_iff'.trans <| by simp_rw [mem_univ, true_imp_iff, Function.Injective]
section CharP
variable (p : ℕ) [HF : CharP F p]
theorem separable_or {f : F[X]} (hf : Irreducible f) :
f.Separable ∨ ¬f.Separable ∧ ∃ g : F[X], Irreducible g ∧ expand F p g = f := by
classical
exact if H : derivative f = 0 then by
| rcases p.eq_zero_or_pos with (rfl | hp)
· haveI := CharP.charP_to_charZero F
have := natDegree_eq_zero_of_derivative_eq_zero H
| Mathlib/FieldTheory/Separable.lean | 352 | 354 |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Yaël Dillies
-/
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
/-!
# Integral average of a function
In this file we define `MeasureTheory.average μ f` (notation: `⨍ x, f x ∂μ`) to be the average
value of `f` with respect to measure `μ`. It is defined as `∫ x, f x ∂((μ univ)⁻¹ • μ)`, so it
is equal to zero if `f` is not integrable or if `μ` is an infinite measure. If `μ` is a probability
measure, then the average of any function is equal to its integral.
For the average on a set, we use `⨍ x in s, f x ∂μ` (notation for `⨍ x, f x ∂(μ.restrict s)`). For
average w.r.t. the volume, one can omit `∂volume`.
Both have a version for the Lebesgue integral rather than Bochner.
We prove several version of the first moment method: An integrable function is below/above its
average on a set of positive measure:
* `measure_le_setLAverage_pos` for the Lebesgue integral
* `measure_le_setAverage_pos` for the Bochner integral
## Implementation notes
The average is defined as an integral over `(μ univ)⁻¹ • μ` so that all theorems about Bochner
integrals work for the average without modifications. For theorems that require integrability of a
function, we provide a convenience lemma `MeasureTheory.Integrable.to_average`.
## Tags
integral, center mass, average value
-/
open ENNReal MeasureTheory MeasureTheory.Measure Metric Set Filter TopologicalSpace Function
open scoped Topology ENNReal Convex
variable {α E F : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [CompleteSpace F] {μ ν : Measure α}
{s t : Set α}
/-!
### Average value of a function w.r.t. a measure
The (Bochner, Lebesgue) average value of a function `f` w.r.t. a measure `μ` (notation:
`⨍ x, f x ∂μ`, `⨍⁻ x, f x ∂μ`) is defined as the (Bochner, Lebesgue) integral divided by the total
measure, so it is equal to zero if `μ` is an infinite measure, and (typically) equal to infinity if
`f` is not integrable. If `μ` is a probability measure, then the average of any function is equal to
its integral.
-/
namespace MeasureTheory
section ENNReal
variable (μ) {f g : α → ℝ≥0∞}
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`, denoted `⨍⁻ x, f x ∂μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def laverage (f : α → ℝ≥0∞) := ∫⁻ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => laverage μ r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure.
It is equal to `(volume univ)⁻¹ * ∫⁻ x, f x`, so it takes value zero if the space has infinite
measure. In a probability space, the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x`, defined as `⨍⁻ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => laverage volume f) => r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ s)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `s` has infinite measure. If `s`
has measure `1`, then the average of any function is equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => laverage (Measure.restrict μ s) r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume s)⁻¹ * ∫⁻ x, f x`, so it takes value zero if `s` has infinite measure. If
`s` has measure `1`, then the average of any function is equal to its integral. -/
notation3 (prettyPrint := false)
"⨍⁻ "(...)" in "s", "r:60:(scoped f => laverage Measure.restrict volume s f) => r
@[simp]
theorem laverage_zero : ⨍⁻ _x, (0 : ℝ≥0∞) ∂μ = 0 := by rw [laverage, lintegral_zero]
@[simp]
theorem laverage_zero_measure (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂(0 : Measure α) = 0 := by simp [laverage]
theorem laverage_eq' (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂(μ univ)⁻¹ • μ := rfl
theorem laverage_eq (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = (∫⁻ x, f x ∂μ) / μ univ := by
rw [laverage_eq', lintegral_smul_measure, ENNReal.div_eq_inv_mul, smul_eq_mul]
theorem laverage_eq_lintegral [IsProbabilityMeasure μ] (f : α → ℝ≥0∞) :
⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by rw [laverage, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_mul_laverage [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
μ univ * ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, lintegral_zero_measure, laverage_zero_measure, mul_zero]
· rw [laverage_eq, ENNReal.mul_div_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
theorem setLAverage_eq (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = (∫⁻ x in s, f x ∂μ) / μ s := by rw [laverage_eq, restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias setLaverage_eq := setLAverage_eq
theorem setLAverage_eq' (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = ∫⁻ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [laverage_eq', restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias setLaverage_eq' := setLAverage_eq'
variable {μ}
theorem laverage_congr {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) : ⨍⁻ x, f x ∂μ = ⨍⁻ x, g x ∂μ := by
simp only [laverage_eq, lintegral_congr_ae h]
theorem setLAverage_congr (h : s =ᵐ[μ] t) : ⨍⁻ x in s, f x ∂μ = ⨍⁻ x in t, f x ∂μ := by
simp only [setLAverage_eq, setLIntegral_congr h, measure_congr h]
@[deprecated (since := "2025-04-22")] alias setLaverage_congr := setLAverage_congr
theorem setLAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍⁻ x in s, f x ∂μ = ⨍⁻ x in s, g x ∂μ := by
simp only [laverage_eq, setLIntegral_congr_fun hs h]
@[deprecated (since := "2025-04-22")] alias setLaverage_congr_fun := setLAverage_congr_fun
theorem laverage_lt_top (hf : ∫⁻ x, f x ∂μ ≠ ∞) : ⨍⁻ x, f x ∂μ < ∞ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq]
exact div_lt_top hf (measure_univ_ne_zero.2 hμ)
theorem setLAverage_lt_top : ∫⁻ x in s, f x ∂μ ≠ ∞ → ⨍⁻ x in s, f x ∂μ < ∞ :=
laverage_lt_top
@[deprecated (since := "2025-04-22")] alias setLaverage_lt_top := setLAverage_lt_top
theorem laverage_add_measure :
⨍⁻ x, f x ∂(μ + ν) =
μ univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂ν := by
by_cases hμ : IsFiniteMeasure μ; swap
· rw [not_isFiniteMeasure_iff] at hμ
simp [laverage_eq, hμ]
by_cases hν : IsFiniteMeasure ν; swap
· rw [not_isFiniteMeasure_iff] at hν
simp [laverage_eq, hν]
haveI := hμ; haveI := hν
simp only [← ENNReal.mul_div_right_comm, measure_mul_laverage, ← ENNReal.add_div,
← lintegral_add_measure, ← Measure.add_apply, ← laverage_eq]
theorem measure_mul_setLAverage (f : α → ℝ≥0∞) (h : μ s ≠ ∞) :
μ s * ⨍⁻ x in s, f x ∂μ = ∫⁻ x in s, f x ∂μ := by
have := Fact.mk h.lt_top
rw [← measure_mul_laverage, restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias measure_mul_setLaverage := measure_mul_setLAverage
theorem laverage_union (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ) :
⨍⁻ x in s ∪ t, f x ∂μ =
μ s / (μ s + μ t) * ⨍⁻ x in s, f x ∂μ + μ t / (μ s + μ t) * ⨍⁻ x in t, f x ∂μ := by
rw [restrict_union₀ hd ht, laverage_add_measure, restrict_apply_univ, restrict_apply_univ]
theorem laverage_union_mem_openSegment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in t, f x ∂μ) := by
refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), ENNReal.div_pos hs₀ <| add_ne_top.2 ⟨hsμ, htμ⟩,
ENNReal.div_pos ht₀ <| add_ne_top.2 ⟨hsμ, htμ⟩, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
theorem laverage_union_mem_segment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ [⨍⁻ x in s, f x ∂μ -[ℝ≥0∞] ⨍⁻ x in t, f x ∂μ] := by
by_cases hs₀ : μ s = 0
· rw [← ae_eq_empty] at hs₀
rw [restrict_congr_set (hs₀.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), zero_le _, zero_le _, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
theorem laverage_mem_openSegment_compl_self [IsFiniteMeasure μ] (hs : NullMeasurableSet s μ)
(hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) :
⨍⁻ x, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
laverage_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _)
@[simp]
theorem laverage_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : ℝ≥0∞) :
⨍⁻ _x, c ∂μ = c := by
simp only [laverage, lintegral_const, measure_univ, mul_one]
theorem setLAverage_const (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : ℝ≥0∞) : ⨍⁻ _x in s, c ∂μ = c := by
simp only [setLAverage_eq, lintegral_const, Measure.restrict_apply, MeasurableSet.univ,
univ_inter, div_eq_mul_inv, mul_assoc, ENNReal.mul_inv_cancel hs₀ hs, mul_one]
@[deprecated (since := "2025-04-22")] alias setLaverage_const := setLAverage_const
theorem laverage_one [IsFiniteMeasure μ] [NeZero μ] : ⨍⁻ _x, (1 : ℝ≥0∞) ∂μ = 1 :=
laverage_const _ _
theorem setLAverage_one (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) : ⨍⁻ _x in s, (1 : ℝ≥0∞) ∂μ = 1 :=
setLAverage_const hs₀ hs _
@[deprecated (since := "2025-04-22")] alias setLaverage_one := setLAverage_one
@[simp]
theorem laverage_mul_measure_univ (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
(⨍⁻ (a : α), f a ∂μ) * μ univ = ∫⁻ x, f x ∂μ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq, ENNReal.div_mul_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
theorem lintegral_laverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
∫⁻ _x, ⨍⁻ a, f a ∂μ ∂μ = ∫⁻ x, f x ∂μ := by
simp
theorem setLIntegral_setLAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ _x in s, ⨍⁻ a in s, f a ∂μ ∂μ = ∫⁻ x in s, f x ∂μ :=
lintegral_laverage _ _
@[deprecated (since := "2025-04-22")] alias setLintegral_setLaverage := setLIntegral_setLAverage
end ENNReal
section NormedAddCommGroup
variable (μ)
variable {f g : α → E}
/-- Average value of a function `f` w.r.t. a measure `μ`, denoted `⨍ x, f x ∂μ`.
It is equal to `(μ.real univ)⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def average (f : α → E) :=
∫ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of a function `f` w.r.t. a measure `μ`.
It is equal to `(μ.real univ)⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => average μ r
/-- Average value of a function `f` w.r.t. to the standard measure.
It is equal to `(volume.real univ)⁻¹ * ∫ x, f x`, so it takes value zero if `f` is not integrable
or if the space has infinite measure. In a probability space, the average of any function is equal
to its integral.
For the average on a set, use `⨍ x in s, f x`, defined as `⨍ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => average volume f) => r
/-- Average value of a function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ.real s)⁻¹ * ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable on
`s` or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is
equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => average (Measure.restrict μ s) r
/-- Average value of a function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume.real s)⁻¹ * ∫ x, f x`, so it takes value zero `f` is not integrable on `s`
or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is equal to
its integral. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => average (Measure.restrict volume s) f) => r
@[simp]
theorem average_zero : ⨍ _, (0 : E) ∂μ = 0 := by rw [average, integral_zero]
@[simp]
theorem average_zero_measure (f : α → E) : ⨍ x, f x ∂(0 : Measure α) = 0 := by
rw [average, smul_zero, integral_zero_measure]
@[simp]
theorem average_neg (f : α → E) : ⨍ x, -f x ∂μ = -⨍ x, f x ∂μ :=
integral_neg f
theorem average_eq' (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂(μ univ)⁻¹ • μ :=
rfl
theorem average_eq (f : α → E) : ⨍ x, f x ∂μ = (μ.real univ)⁻¹ • ∫ x, f x ∂μ := by
rw [average_eq', integral_smul_measure, ENNReal.toReal_inv, measureReal_def]
theorem average_eq_integral [IsProbabilityMeasure μ] (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rw [average, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_smul_average [IsFiniteMeasure μ] (f : α → E) :
μ.real univ • ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, integral_zero_measure, average_zero_measure, smul_zero]
· rw [average_eq, smul_inv_smul₀]
refine (ENNReal.toReal_pos ?_ <| measure_ne_top _ _).ne'
rwa [Ne, measure_univ_eq_zero]
theorem setAverage_eq (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = (μ.real s)⁻¹ • ∫ x in s, f x ∂μ := by
rw [average_eq, measureReal_restrict_apply_univ]
theorem setAverage_eq' (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = ∫ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [average_eq', restrict_apply_univ]
variable {μ}
theorem average_congr {f g : α → E} (h : f =ᵐ[μ] g) : ⨍ x, f x ∂μ = ⨍ x, g x ∂μ := by
simp only [average_eq, integral_congr_ae h]
theorem setAverage_congr (h : s =ᵐ[μ] t) : ⨍ x in s, f x ∂μ = ⨍ x in t, f x ∂μ := by
simp only [setAverage_eq, setIntegral_congr_set h, measureReal_congr h]
theorem setAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍ x in s, f x ∂μ = ⨍ x in s, g x ∂μ := by simp only [average_eq, setIntegral_congr_ae hs h]
theorem average_add_measure [IsFiniteMeasure μ] {ν : Measure α} [IsFiniteMeasure ν] {f : α → E}
(hμ : Integrable f μ) (hν : Integrable f ν) :
⨍ x, f x ∂(μ + ν) =
(μ.real univ / (μ.real univ + ν.real univ)) • ⨍ x, f x ∂μ +
(ν.real univ / (μ.real univ + ν.real univ)) • ⨍ x, f x ∂ν := by
simp only [div_eq_inv_mul, mul_smul, measure_smul_average, ← smul_add,
← integral_add_measure hμ hν, ← ENNReal.toReal_add (measure_ne_top μ _) (measure_ne_top ν _)]
rw [average_eq, measureReal_add_apply]
theorem average_pair [CompleteSpace E]
{f : α → E} {g : α → F} (hfi : Integrable f μ) (hgi : Integrable g μ) :
⨍ x, (f x, g x) ∂μ = (⨍ x, f x ∂μ, ⨍ x, g x ∂μ) :=
integral_pair hfi.to_average hgi.to_average
theorem measure_smul_setAverage (f : α → E) {s : Set α} (h : μ s ≠ ∞) :
μ.real s • ⨍ x in s, f x ∂μ = ∫ x in s, f x ∂μ := by
haveI := Fact.mk h.lt_top
rw [← measure_smul_average, measureReal_restrict_apply_univ]
theorem average_union {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ =
(μ.real s / (μ.real s + μ.real t)) • ⨍ x in s, f x ∂μ +
(μ.real t / (μ.real s + μ.real t)) • ⨍ x in t, f x ∂μ := by
haveI := Fact.mk hsμ.lt_top; haveI := Fact.mk htμ.lt_top
rw [restrict_union₀ hd ht, average_add_measure hfs hft, measureReal_restrict_apply_univ,
measureReal_restrict_apply_univ]
theorem average_union_mem_openSegment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞)
(hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in t, f x ∂μ) := by
replace hs₀ : 0 < μ.real s := ENNReal.toReal_pos hs₀ hsμ
replace ht₀ : 0 < μ.real t := ENNReal.toReal_pos ht₀ htμ
exact mem_openSegment_iff_div.mpr
⟨μ.real s, μ.real t, hs₀, ht₀, (average_union hd ht hsμ htμ hfs hft).symm⟩
theorem average_union_mem_segment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ)
(hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ [⨍ x in s, f x ∂μ -[ℝ] ⨍ x in t, f x ∂μ] := by
by_cases hse : μ s = 0
· rw [← ae_eq_empty] at hse
rw [restrict_congr_set (hse.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
mem_segment_iff_div.mpr
⟨μ.real s, μ.real t, ENNReal.toReal_nonneg, ENNReal.toReal_nonneg, ?_,
(average_union hd ht hsμ htμ hfs hft).symm⟩
calc
0 < μ.real s := ENNReal.toReal_pos hse hsμ
_ ≤ _ := le_add_of_nonneg_right ENNReal.toReal_nonneg
theorem average_mem_openSegment_compl_self [IsFiniteMeasure μ] {f : α → E} {s : Set α}
(hs : NullMeasurableSet s μ) (hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) (hfi : Integrable f μ) :
⨍ x, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
average_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _) hfi.integrableOn hfi.integrableOn
variable [CompleteSpace E]
@[simp]
theorem average_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : E) :
⨍ _x, c ∂μ = c := by
rw [average, integral_const, measureReal_def, measure_univ, ENNReal.toReal_one, one_smul]
theorem setAverage_const {s : Set α} (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : E) :
⨍ _ in s, c ∂μ = c :=
have := NeZero.mk hs₀; have := Fact.mk hs.lt_top; average_const _ _
theorem integral_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ _, ⨍ a, f a ∂μ ∂μ = ∫ x, f x ∂μ := by simp
theorem setIntegral_setAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) (s : Set α) :
∫ _ in s, ⨍ a in s, f a ∂μ ∂μ = ∫ x in s, f x ∂μ :=
integral_average _ _
theorem integral_sub_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ x, f x - ⨍ a, f a ∂μ ∂μ = 0 := by
by_cases hf : Integrable f μ
· rw [integral_sub hf (integrable_const _), integral_average, sub_self]
refine integral_undef fun h => hf ?_
convert h.add (integrable_const (⨍ a, f a ∂μ))
exact (sub_add_cancel _ _).symm
theorem setAverage_sub_setAverage (hs : μ s ≠ ∞) (f : α → E) :
∫ x in s, f x - ⨍ a in s, f a ∂μ ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_sub_average _ _
theorem integral_average_sub [IsFiniteMeasure μ] (hf : Integrable f μ) :
∫ x, ⨍ a, f a ∂μ - f x ∂μ = 0 := by
rw [integral_sub (integrable_const _) hf, integral_average, sub_self]
theorem setIntegral_setAverage_sub (hs : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∫ x in s, ⨍ a in s, f a ∂μ - f x ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_average_sub hf
end NormedAddCommGroup
theorem ofReal_average {f : α → ℝ} (hf : Integrable f μ) (hf₀ : 0 ≤ᵐ[μ] f) :
ENNReal.ofReal (⨍ x, f x ∂μ) = (∫⁻ x, ENNReal.ofReal (f x) ∂μ) / μ univ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [average_eq, smul_eq_mul, measureReal_def, ← toReal_inv, ofReal_mul toReal_nonneg,
ofReal_toReal (inv_ne_top.2 <| measure_univ_ne_zero.2 hμ),
ofReal_integral_eq_lintegral_ofReal hf hf₀, ENNReal.div_eq_inv_mul]
theorem ofReal_setAverage {f : α → ℝ} (hf : IntegrableOn f s μ) (hf₀ : 0 ≤ᵐ[μ.restrict s] f) :
ENNReal.ofReal (⨍ x in s, f x ∂μ) = (∫⁻ x in s, ENNReal.ofReal (f x) ∂μ) / μ s := by
simpa using ofReal_average hf hf₀
theorem toReal_laverage {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (hf' : ∀ᵐ x ∂μ, f x ≠ ∞) :
(⨍⁻ x, f x ∂μ).toReal = ⨍ x, (f x).toReal ∂μ := by
rw [average_eq, laverage_eq, smul_eq_mul, toReal_div, div_eq_inv_mul, ←
integral_toReal hf (hf'.mono fun _ => lt_top_iff_ne_top.2), measureReal_def]
theorem toReal_setLAverage {f : α → ℝ≥0∞} (hf : AEMeasurable f (μ.restrict s))
(hf' : ∀ᵐ x ∂μ.restrict s, f x ≠ ∞) :
(⨍⁻ x in s, f x ∂μ).toReal = ⨍ x in s, (f x).toReal ∂μ := by
simpa [laverage_eq] using toReal_laverage hf hf'
@[deprecated (since := "2025-04-22")] alias toReal_setLaverage := toReal_setLAverage
/-! ### First moment method -/
section FirstMomentReal
variable {N : Set α} {f : α → ℝ}
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_setAverage_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | f x ≤ ⨍ a in s, f a ∂μ}) := by
refine pos_iff_ne_zero.2 fun H => ?_
replace H : (μ.restrict s) {x | f x ≤ ⨍ a in s, f a ∂μ} = 0 := by
rwa [restrict_apply₀, inter_comm]
exact AEStronglyMeasurable.nullMeasurableSet_le hf.1 aestronglyMeasurable_const
haveI := Fact.mk hμ₁.lt_top
refine (integral_sub_average (μ.restrict s) f).not_gt ?_
refine (setIntegral_pos_iff_support_of_nonneg_ae ?_ ?_).2 ?_
· refine measure_mono_null (fun x hx ↦ ?_) H
simp only [Pi.zero_apply, sub_nonneg, mem_compl_iff, mem_setOf_eq, not_le] at hx
exact hx.le
· exact hf.sub (integrableOn_const.2 <| Or.inr <| lt_top_iff_ne_top.2 hμ₁)
· rwa [pos_iff_ne_zero, inter_comm, ← diff_compl, ← diff_inter_self_eq_diff, measure_diff_null]
refine measure_mono_null ?_ (measure_inter_eq_zero_of_restrict H)
exact inter_subset_inter_left _ fun a ha => (sub_eq_zero.1 <| of_not_not ha).le
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_setAverage_le_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | ⨍ a in s, f a ∂μ ≤ f x}) := by
simpa [integral_neg, neg_div] using measure_le_setAverage_pos hμ hμ₁ hf.neg
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_setAverage (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, f x ≤ ⨍ a in s, f a ∂μ :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_le_setAverage_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_setAverage_le (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, ⨍ a in s, f a ∂μ ≤ f x :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_setAverage_le_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
section FiniteMeasure
variable [IsFiniteMeasure μ]
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_average_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | f x ≤ ⨍ a, f a ∂μ} := by
simpa using measure_le_setAverage_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_average_le_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | ⨍ a, f a ∂μ ≤ f x} := by
simpa using measure_setAverage_le_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, f x ≤ ⨍ a, f a ∂μ :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_le_average_pos hμ hf).ne'
⟨x, hx⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, ⨍ a, f a ∂μ ≤ f x :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_average_le_pos hμ hf).ne'
⟨x, hx⟩
/-- **First moment method**. The minimum of an integrable function is smaller than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ f x ≤ ⨍ a, f a ∂μ := by
have := measure_le_average_pos hμ hf
rw [← measure_diff_null hN] at this
obtain ⟨x, hx, hxN⟩ := nonempty_of_measure_ne_zero this.ne'
exact ⟨x, hxN, hx⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ⨍ a, f a ∂μ ≤ f x := by
simpa [integral_neg, neg_div] using exists_not_mem_null_le_average hμ hf.neg hN
end FiniteMeasure
section ProbabilityMeasure
| variable [IsProbabilityMeasure μ]
/-- **First moment method**. An integrable function is smaller than its integral on a set of
positive measure. -/
| Mathlib/MeasureTheory/Integral/Average.lean | 565 | 568 |
/-
Copyright (c) 2021 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Eric Wieser
-/
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.Dual.Lemmas
import Mathlib.LinearAlgebra.FiniteDimensional.Lemmas
import Mathlib.LinearAlgebra.Matrix.Diagonal
import Mathlib.LinearAlgebra.Matrix.DotProduct
import Mathlib.LinearAlgebra.Matrix.Dual
/-!
# Rank of matrices
The rank of a matrix `A` is defined to be the rank of range of the linear map corresponding to `A`.
This definition does not depend on the choice of basis, see `Matrix.rank_eq_finrank_range_toLin`.
## Main declarations
* `Matrix.rank`: the rank of a matrix
* `Matrix.cRank`: the rank of a matrix as a cardinal
* `Matrix.eRank`: the rank of a matrix as a term in `ℕ∞`.
-/
open Matrix
namespace Matrix
open Module Cardinal Set Submodule
universe ul um um₀ un un₀ uo uR
variable {l : Type ul} {m : Type um} {m₀ : Type um₀} {n : Type un} {n₀ : Type un₀} {o : Type uo}
variable {R : Type uR}
section Infinite
variable [Semiring R]
/-- The rank of a matrix, defined as the dimension of its column space, as a cardinal. -/
noncomputable def cRank (A : Matrix m n R) : Cardinal := Module.rank R <| span R <| range Aᵀ
lemma cRank_toNat_eq_finrank (A : Matrix m n R) :
A.cRank.toNat = Module.finrank R (span R (range A.col)) := rfl
lemma lift_cRank_submatrix_le (A : Matrix m n R) (r : m₀ → m) (c : n₀ → n) :
lift.{um} (A.submatrix r c).cRank ≤ lift.{um₀} A.cRank := by
have h : ((A.submatrix r id).submatrix id c).cRank ≤ (A.submatrix r id).cRank :=
Submodule.rank_mono <| span_mono <| by rintro _ ⟨x, rfl⟩; exact ⟨c x, rfl⟩
refine (Cardinal.lift_monotone h).trans ?_
let f : (m → R) →ₗ[R] (m₀ → R) := LinearMap.funLeft R R r
have h_eq : Submodule.map f (span R (range Aᵀ)) = span R (range (A.submatrix r id)ᵀ) := by
rw [LinearMap.map_span, ← image_univ, image_image, transpose_submatrix]
aesop
rw [cRank, ← h_eq]
have hwin := lift_rank_map_le f (span R (range Aᵀ))
simp_rw [← lift_umax] at hwin ⊢
exact hwin
/-- A special case of `lift_cRank_submatrix_le` for when `m₀` and `m` are in the same universe. -/
lemma cRank_submatrix_le {m m₀ : Type um} (A : Matrix m n R) (r : m₀ → m) (c : n₀ → n) :
(A.submatrix r c).cRank ≤ A.cRank := by
simpa using lift_cRank_submatrix_le A r c
lemma cRank_le_card_height [StrongRankCondition R] [Fintype m] (A : Matrix m n R) :
A.cRank ≤ Fintype.card m :=
(Submodule.rank_le (span R (range Aᵀ))).trans <| by rw [rank_fun']
lemma cRank_le_card_width [StrongRankCondition R] [Fintype n] (A : Matrix m n R) :
A.cRank ≤ Fintype.card n :=
(rank_span_le ..).trans <| by simpa using Cardinal.mk_range_le_lift (f := Aᵀ)
/-- The rank of a matrix, defined as the dimension of its column space, as a term in `ℕ∞`. -/
noncomputable def eRank (A : Matrix m n R) : ℕ∞ := A.cRank.toENat
lemma eRank_toNat_eq_finrank (A : Matrix m n R) :
A.eRank.toNat = Module.finrank R (span R (range A.col)) :=
toNat_toENat ..
lemma eRank_submatrix_le (A : Matrix m n R) (r : m₀ → m) (c : n₀ → n) :
(A.submatrix r c).eRank ≤ A.eRank := by
simpa using OrderHom.mono (β := ℕ∞) Cardinal.toENat <| lift_cRank_submatrix_le A r c
lemma eRank_le_card_width [StrongRankCondition R] (A : Matrix m n R) : A.eRank ≤ ENat.card n := by
wlog hfin : Finite n
· simp [ENat.card_eq_top.2 (by simpa using hfin)]
have _ := Fintype.ofFinite n
rw [ENat.card_eq_coe_fintype_card, eRank, toENat_le_nat]
exact A.cRank_le_card_width
lemma eRank_le_card_height [StrongRankCondition R] (A : Matrix m n R) : A.eRank ≤ ENat.card m := by
classical
wlog hfin : Finite m
· simp [ENat.card_eq_top.2 (by simpa using hfin)]
have _ := Fintype.ofFinite m
rw [ENat.card_eq_coe_fintype_card, eRank, toENat_le_nat]
exact A.cRank_le_card_height
end Infinite
variable [Fintype n] [Fintype o]
section CommRing
variable [CommRing R]
/-- The rank of a matrix is the rank of its image. -/
noncomputable def rank (A : Matrix m n R) : ℕ :=
finrank R <| LinearMap.range A.mulVecLin
@[simp]
theorem cRank_one [StrongRankCondition R] [DecidableEq m] :
(cRank (1 : Matrix m m R)) = lift.{uR} #m := by
have := nontrivial_of_invariantBasisNumber R
have h : LinearIndependent R (1 : Matrix m m R)ᵀ := by
convert Pi.linearIndependent_single_one m R
simp [funext_iff, Matrix.one_eq_pi_single]
rw [cRank, rank_span h, ← lift_umax, ← Cardinal.mk_range_eq_of_injective h.injective, lift_id']
@[simp] theorem eRank_one [StrongRankCondition R] [DecidableEq m] :
(eRank (1 : Matrix m m R)) = ENat.card m := by
rw [eRank, cRank_one, toENat_lift, ENat.card]
@[simp]
theorem rank_one [StrongRankCondition R] [DecidableEq n] :
rank (1 : Matrix n n R) = Fintype.card n := by
rw [rank, mulVecLin_one, LinearMap.range_id, finrank_top, finrank_pi]
@[simp]
theorem rank_zero [Nontrivial R] : rank (0 : Matrix m n R) = 0 := by
rw [rank, mulVecLin_zero, LinearMap.range_zero, finrank_bot]
@[simp]
theorem cRank_zero {m n : Type*} [Nontrivial R] : cRank (0 : Matrix m n R) = 0 := by
obtain hn | hn := isEmpty_or_nonempty n
· rw [cRank, range_eq_empty, span_empty, rank_bot]
rw [cRank, transpose_zero, range_zero, span_zero_singleton, rank_bot]
@[simp]
theorem eRank_zero {m n : Type*} [Nontrivial R] : eRank (0 : Matrix m n R) = 0 := by
simp [eRank]
theorem rank_le_card_width [StrongRankCondition R] (A : Matrix m n R) :
A.rank ≤ Fintype.card n := by
haveI : Module.Finite R (n → R) := Module.Finite.pi
haveI : Module.Free R (n → R) := Module.Free.pi _ _
exact A.mulVecLin.finrank_range_le.trans_eq (finrank_pi _)
theorem rank_le_width [StrongRankCondition R] {m n : ℕ} (A : Matrix (Fin m) (Fin n) R) :
A.rank ≤ n :=
A.rank_le_card_width.trans <| (Fintype.card_fin n).le
theorem rank_mul_le_left [StrongRankCondition R] (A : Matrix m n R) (B : Matrix n o R) :
(A * B).rank ≤ A.rank := by
rw [rank, rank, mulVecLin_mul]
exact Cardinal.toNat_le_toNat (LinearMap.rank_comp_le_left _ _) (rank_lt_aleph0 _ _)
theorem rank_mul_le_right [StrongRankCondition R] (A : Matrix m n R) (B : Matrix n o R) :
(A * B).rank ≤ B.rank := by
rw [rank, rank, mulVecLin_mul]
exact finrank_le_finrank_of_rank_le_rank (LinearMap.lift_rank_comp_le_right _ _)
(rank_lt_aleph0 _ _)
theorem rank_mul_le [StrongRankCondition R] (A : Matrix m n R) (B : Matrix n o R) :
(A * B).rank ≤ min A.rank B.rank :=
le_min (rank_mul_le_left _ _) (rank_mul_le_right _ _)
theorem rank_unit [StrongRankCondition R] [DecidableEq n] (A : (Matrix n n R)ˣ) :
(A : Matrix n n R).rank = Fintype.card n := by
apply le_antisymm (rank_le_card_width (A : Matrix n n R)) _
have := rank_mul_le_left (A : Matrix n n R) (↑A⁻¹ : Matrix n n R)
rwa [← Units.val_mul, mul_inv_cancel, Units.val_one, rank_one] at this
theorem rank_of_isUnit [StrongRankCondition R] [DecidableEq n] (A : Matrix n n R) (h : IsUnit A) :
A.rank = Fintype.card n := by
obtain ⟨A, rfl⟩ := h
exact rank_unit A
/-- Right multiplying by an invertible matrix does not change the rank -/
@[simp]
lemma rank_mul_eq_left_of_isUnit_det [DecidableEq n]
(A : Matrix n n R) (B : Matrix m n R) (hA : IsUnit A.det) :
(B * A).rank = B.rank := by
suffices Function.Surjective A.mulVecLin by
rw [rank, mulVecLin_mul, LinearMap.range_comp_of_range_eq_top _
(LinearMap.range_eq_top.mpr this), ← rank]
intro v
exact ⟨(A⁻¹).mulVecLin v, by simp [mul_nonsing_inv _ hA]⟩
/-- Left multiplying by an invertible matrix does not change the rank -/
@[simp]
lemma rank_mul_eq_right_of_isUnit_det [Fintype m] [DecidableEq m]
(A : Matrix m m R) (B : Matrix m n R) (hA : IsUnit A.det) :
(A * B).rank = B.rank := by
let b : Basis m R (m → R) := Pi.basisFun R m
replace hA : IsUnit (LinearMap.toMatrix b b A.mulVecLin).det := by
convert hA; rw [← LinearEquiv.eq_symm_apply]; rfl
have hAB : mulVecLin (A * B) = (LinearEquiv.ofIsUnitDet hA).comp (mulVecLin B) := by ext; simp
rw [rank, rank, hAB, LinearMap.range_comp, LinearEquiv.finrank_map_eq]
/-- Taking a subset of the rows and permuting the columns reduces the rank. -/
theorem rank_submatrix_le [StrongRankCondition R] [Fintype m] (f : n → m) (e : n ≃ m)
(A : Matrix m m R) : rank (A.submatrix f e) ≤ rank A := by
rw [rank, rank, mulVecLin_submatrix, LinearMap.range_comp, LinearMap.range_comp,
show LinearMap.funLeft R R e.symm = LinearEquiv.funCongrLeft R R e.symm from rfl,
LinearEquiv.range, Submodule.map_top]
exact Submodule.finrank_map_le _ _
theorem rank_reindex [Fintype n₀] (em : m ≃ m₀) (en : n ≃ n₀) (A : Matrix m n R) :
rank (A.reindex em en) = rank A := by
rw [rank, rank, mulVecLin_reindex, LinearMap.range_comp, LinearMap.range_comp,
LinearEquiv.range, Submodule.map_top, LinearEquiv.finrank_map_eq]
@[simp]
theorem rank_submatrix [Fintype n₀] (A : Matrix m n R) (em : m₀ ≃ m) (en : n₀ ≃ n) :
rank (A.submatrix em en) = rank A := by
simpa only [reindex_apply] using rank_reindex em.symm en.symm A
@[simp]
theorem lift_cRank_submatrix {n : Type un} (A : Matrix m n R) (em : m₀ ≃ m) (en : n₀ ≃ n) :
lift.{um} (cRank (A.submatrix em en)) = lift.{um₀} (cRank A) :=
(A.lift_cRank_submatrix_le em en).antisymm
<| by simpa using ((A.reindex em.symm en.symm).lift_cRank_submatrix_le em.symm en.symm)
/-- A special case of `lift_cRank_submatrix` for when the row types are in the same universe. -/
@[simp]
theorem cRank_submatrix {m₀ : Type um} {n : Type un} (A : Matrix m n R) (em : m₀ ≃ m)
(en : n₀ ≃ n) : cRank (A.submatrix em en) = cRank A := by
simpa [-lift_cRank_submatrix] using A.lift_cRank_submatrix em en
theorem lift_cRank_reindex {n : Type un} (A : Matrix m n R) (em : m ≃ m₀) (en : n ≃ n₀) :
lift.{um} (cRank (A.reindex em en)) = lift.{um₀} (cRank A) :=
lift_cRank_submatrix ..
/-- A special case of `lift_cRank_reindex` for when the row types are in the same universe. -/
theorem cRank_reindex {m₀ : Type um} {n : Type un} (A : Matrix m n R) (em : m ≃ m₀) (en : n ≃ n₀) :
cRank (A.reindex em en) = cRank A :=
cRank_submatrix ..
@[simp]
theorem eRank_submatrix {n : Type un} (A : Matrix m n R) (em : m₀ ≃ m) (en : n₀ ≃ n) :
eRank (A.submatrix em en) = eRank A := by
simpa [-lift_cRank_submatrix] using congr_arg Cardinal.toENat <| A.lift_cRank_submatrix em en
theorem eRank_reindex {m₀ : Type um} {n : Type un} (A : Matrix m n R) (em : m ≃ m₀) (en : n ≃ n₀) :
eRank (A.reindex em en) = eRank A :=
eRank_submatrix ..
theorem rank_eq_finrank_range_toLin [Finite m] [DecidableEq n] {M₁ M₂ : Type*} [AddCommGroup M₁]
[AddCommGroup M₂] [Module R M₁] [Module R M₂] (A : Matrix m n R) (v₁ : Basis m R M₁)
(v₂ : Basis n R M₂) : A.rank = finrank R (LinearMap.range (toLin v₂ v₁ A)) := by
cases nonempty_fintype m
let e₁ := (Pi.basisFun R m).equiv v₁ (Equiv.refl _)
let e₂ := (Pi.basisFun R n).equiv v₂ (Equiv.refl _)
have range_e₂ : LinearMap.range e₂ = ⊤ := by
rw [LinearMap.range_eq_top]
exact e₂.surjective
refine LinearEquiv.finrank_eq (e₁.ofSubmodules _ _ ?_)
rw [← LinearMap.range_comp, ← LinearMap.range_comp_of_range_eq_top (toLin v₂ v₁ A) range_e₂]
congr 1
apply LinearMap.pi_ext'
rintro i
apply LinearMap.ext_ring
have aux₁ := toLin_self (Pi.basisFun R n) (Pi.basisFun R m) A i
have aux₂ := Basis.equiv_apply (Pi.basisFun R n) i v₂
rw [toLin_eq_toLin', toLin'_apply'] at aux₁
rw [Pi.basisFun_apply] at aux₁ aux₂
simp only [e₁, e₂, LinearMap.comp_apply, LinearEquiv.coe_coe, Equiv.refl_apply,
aux₁, aux₂, LinearMap.coe_single, toLin_self, map_sum, LinearEquiv.map_smul, Basis.equiv_apply]
theorem rank_le_card_height [Fintype m] [StrongRankCondition R] (A : Matrix m n R) :
A.rank ≤ Fintype.card m := by
haveI : Module.Finite R (m → R) := Module.Finite.pi
haveI : Module.Free R (m → R) := Module.Free.pi _ _
exact (Submodule.finrank_le _).trans (finrank_pi R).le
theorem rank_le_height [StrongRankCondition R] {m n : ℕ} (A : Matrix (Fin m) (Fin n) R) :
A.rank ≤ m :=
A.rank_le_card_height.trans <| (Fintype.card_fin m).le
/-- The rank of a matrix is the rank of the space spanned by its columns. -/
theorem rank_eq_finrank_span_cols (A : Matrix m n R) :
A.rank = finrank R (Submodule.span R (Set.range A.col)) := by rw [rank, Matrix.range_mulVecLin]
@[simp]
theorem cRank_toNat_eq_rank (A : Matrix m n R) : A.cRank.toNat = A.rank := by
rw [cRank_toNat_eq_finrank, ← rank_eq_finrank_span_cols]
@[simp]
theorem eRank_toNat_eq_rank (A : Matrix m n R) : A.eRank.toNat = A.rank := by
rw [eRank_toNat_eq_finrank, ← rank_eq_finrank_span_cols]
| end CommRing
section Field
| Mathlib/Data/Matrix/Rank.lean | 294 | 297 |
/-
Copyright (c) 2021 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, María Inés de Frutos-Fernández, Filippo A. E. Nuccio
-/
import Mathlib.Data.Int.Interval
import Mathlib.FieldTheory.RatFunc.AsPolynomial
import Mathlib.RingTheory.Binomial
import Mathlib.RingTheory.HahnSeries.PowerSeries
import Mathlib.RingTheory.HahnSeries.Summable
import Mathlib.RingTheory.PowerSeries.Inverse
import Mathlib.RingTheory.PowerSeries.Trunc
import Mathlib.RingTheory.Localization.FractionRing
import Mathlib.Topology.UniformSpace.DiscreteUniformity
import Mathlib.Algebra.Group.Int.TypeTags
/-!
# Laurent Series
In this file we define `LaurentSeries R`, the formal Laurent series over `R`, here an *arbitrary*
type with a zero. They are denoted `R⸨X⸩`.
## Main Definitions
* Defines `LaurentSeries` as an abbreviation for `HahnSeries ℤ`.
* Defines `hasseDeriv` of a Laurent series with coefficients in a module over a ring.
* Provides a coercion from power series `R⟦X⟧` into `R⸨X⸩` given by `HahnSeries.ofPowerSeries`.
* Defines `LaurentSeries.powerSeriesPart`
* Defines the localization map `LaurentSeries.of_powerSeries_localization` which evaluates to
`HahnSeries.ofPowerSeries`.
* Embedding of rational functions into Laurent series, provided as a coercion, utilizing
the underlying `RatFunc.coeAlgHom`.
* Study of the `X`-Adic valuation on the ring of Laurent series over a field
* In `LaurentSeries.uniformContinuous_coeff` we show that sending a Laurent series to its `d`th
coefficient is uniformly continuous, ensuring that it sends a Cauchy filter `ℱ` in `K⸨X⸩`
to a Cauchy filter in `K`: since this latter is given the discrete topology, this provides an
element `LaurentSeries.Cauchy.coeff ℱ d` in `K` that serves as `d`th coefficient of the Laurent
series to which the filter `ℱ` converges.
## Main Results
* Basic properties of Hasse derivatives
### About the `X`-Adic valuation:
* The (integral) valuation of a power series is the order of the first non-zero coefficient, see
`LaurentSeries.intValuation_le_iff_coeff_lt_eq_zero`.
* The valuation of a Laurent series is the order of the first non-zero coefficient, see
`LaurentSeries.valuation_le_iff_coeff_lt_eq_zero`.
* Every Laurent series of valuation less than `(1 : ℤₘ₀)` comes from a power series, see
`LaurentSeries.val_le_one_iff_eq_coe`.
* The uniform space of `LaurentSeries` over a field is complete, formalized in the instance
`instLaurentSeriesComplete`.
* The field of rational functions is dense in `LaurentSeries`: this is the declaration
`LaurentSeries.coe_range_dense` and relies principally upon `LaurentSeries.exists_ratFunc_val_lt`,
stating that for every Laurent series `f` and every `γ : ℤₘ₀` one can find a rational function `Q`
such that the `X`-adic valuation `v` satisfies `v (f - Q) < γ`.
* In `LaurentSeries.valuation_compare` we prove that the extension of the `X`-adic valuation from
`RatFunc K` up to its abstract completion coincides, modulo the isomorphism with `K⸨X⸩`, with the
`X`-adic valuation on `K⸨X⸩`.
* The two declarations `LaurentSeries.mem_integers_of_powerSeries` and
`LaurentSeries.exists_powerSeries_of_memIntegers` show that an element in the completion of
`RatFunc K` is in the unit ball if and only if it comes from a power series through the isomorphism
`LaurentSeriesRingEquiv`.
* `LaurentSeries.powerSeriesAlgEquiv` is the `K`-algebra isomorphism between `K⟦X⟧`
and the unit ball inside the `X`-adic completion of `RatFunc K`.
## Implementation details
* Since `LaurentSeries` is just an abbreviation of `HahnSeries ℤ R`, the definition of the
coefficients is given in terms of `HahnSeries.coeff` and this forces sometimes to go back-and-forth
from `X : R⸨X⸩` to `single 1 1 : HahnSeries ℤ R`.
* To prove the isomorphism between the `X`-adic completion of `RatFunc K` and `K⸨X⸩` we construct
two completions of `RatFunc K`: the first (`LaurentSeries.ratfuncAdicComplPkg`) is its abstract
uniform completion; the second (`LaurentSeries.LaurentSeriesPkg`) is simply `K⸨X⸩`, once we prove
that it is complete and contains `RatFunc K` as a dense subspace. The isomorphism is the comparison
equivalence, expressing the mathematical idea that the completion "is unique". It is
`LaurentSeries.comparePkg`.
* For applications to `K⟦X⟧` it is actually more handy to use the *inverse* of the above
equivalence: `LaurentSeries.LaurentSeriesAlgEquiv` is the *topological, algebra equivalence*
`K⸨X⸩ ≃ₐ[K] RatFuncAdicCompl K`.
* In order to compare `K⟦X⟧` with the valuation subring in the `X`-adic completion of
`RatFunc K` we consider its alias `LaurentSeries.powerSeries_as_subring` as a subring of `K⸨X⸩`,
that is itself clearly isomorphic (via the inverse of `LaurentSeries.powerSeriesEquivSubring`)
to `K⟦X⟧`.
-/
universe u
open scoped PowerSeries
open HahnSeries Polynomial
noncomputable section
/-- `LaurentSeries R` is the type of formal Laurent series with coefficients in `R`, denoted `R⸨X⸩`.
It is implemented as a `HahnSeries` with value group `ℤ`.
-/
abbrev LaurentSeries (R : Type u) [Zero R] :=
HahnSeries ℤ R
variable {R : Type*}
namespace LaurentSeries
section
/-- `R⸨X⸩` is notation for `LaurentSeries R`. -/
scoped notation:9000 R "⸨X⸩" => LaurentSeries R
end
section HasseDeriv
/-- The Hasse derivative of Laurent series, as a linear map. -/
def hasseDeriv (R : Type*) {V : Type*} [AddCommGroup V] [Semiring R] [Module R V] (k : ℕ) :
V⸨X⸩ →ₗ[R] V⸨X⸩ where
toFun f := HahnSeries.ofSuppBddBelow (fun (n : ℤ) => (Ring.choose (n + k) k) • f.coeff (n + k))
(forallLTEqZero_supp_BddBelow _ (f.order - k : ℤ)
(fun _ h_lt ↦ by rw [coeff_eq_zero_of_lt_order <| lt_sub_iff_add_lt.mp h_lt, smul_zero]))
map_add' f g := by
ext
simp only [ofSuppBddBelow, coeff_add', Pi.add_apply, smul_add]
map_smul' r f := by
ext
simp only [ofSuppBddBelow, HahnSeries.coeff_smul, RingHom.id_apply, smul_comm r]
variable [Semiring R] {V : Type*} [AddCommGroup V] [Module R V]
@[simp]
theorem hasseDeriv_coeff (k : ℕ) (f : LaurentSeries V) (n : ℤ) :
(hasseDeriv R k f).coeff n = Ring.choose (n + k) k • f.coeff (n + k) :=
rfl
@[simp]
theorem hasseDeriv_zero : hasseDeriv R 0 = LinearMap.id (M := LaurentSeries V) := by
ext f n
simp
theorem hasseDeriv_single_add (k : ℕ) (n : ℤ) (x : V) :
hasseDeriv R k (single (n + k) x) = single n ((Ring.choose (n + k) k) • x) := by
ext m
dsimp only [hasseDeriv_coeff]
by_cases h : m = n
· simp [h]
· simp [h, show m + k ≠ n + k by omega]
@[simp]
theorem hasseDeriv_single (k : ℕ) (n : ℤ) (x : V) :
hasseDeriv R k (single n x) = single (n - k) ((Ring.choose n k) • x) := by
rw [← Int.sub_add_cancel n k, hasseDeriv_single_add, Int.sub_add_cancel n k]
theorem hasseDeriv_comp_coeff (k l : ℕ) (f : LaurentSeries V) (n : ℤ) :
(hasseDeriv R k (hasseDeriv R l f)).coeff n =
((Nat.choose (k + l) k) • hasseDeriv R (k + l) f).coeff n := by
rw [coeff_nsmul]
simp only [hasseDeriv_coeff, Pi.smul_apply, Nat.cast_add]
rw [smul_smul, mul_comm, ← Ring.choose_add_smul_choose (n + k), add_assoc, Nat.choose_symm_add,
smul_assoc]
@[simp]
theorem hasseDeriv_comp (k l : ℕ) (f : LaurentSeries V) :
hasseDeriv R k (hasseDeriv R l f) = (k + l).choose k • hasseDeriv R (k + l) f := by
ext n
simp [hasseDeriv_comp_coeff k l f n]
/-- The derivative of a Laurent series. -/
def derivative (R : Type*) {V : Type*} [AddCommGroup V] [Semiring R] [Module R V] :
LaurentSeries V →ₗ[R] LaurentSeries V :=
hasseDeriv R 1
@[simp]
theorem derivative_apply (f : LaurentSeries V) : derivative R f = hasseDeriv R 1 f := by
exact rfl
theorem derivative_iterate (k : ℕ) (f : LaurentSeries V) :
(derivative R)^[k] f = k.factorial • (hasseDeriv R k f) := by
ext n
induction k generalizing f with
| zero => simp
| succ k ih =>
rw [Function.iterate_succ, Function.comp_apply, ih, derivative_apply, hasseDeriv_comp,
Nat.choose_symm_add, Nat.choose_one_right, Nat.factorial, mul_nsmul]
@[simp]
theorem derivative_iterate_coeff (k : ℕ) (f : LaurentSeries V) (n : ℤ) :
((derivative R)^[k] f).coeff n = (descPochhammer ℤ k).smeval (n + k) • f.coeff (n + k) := by
rw [derivative_iterate, coeff_nsmul, Pi.smul_apply, hasseDeriv_coeff,
Ring.descPochhammer_eq_factorial_smul_choose, smul_assoc]
end HasseDeriv
section Semiring
variable [Semiring R]
instance : Coe R⟦X⟧ R⸨X⸩ :=
⟨HahnSeries.ofPowerSeries ℤ R⟩
@[simp]
theorem coeff_coe_powerSeries (x : R⟦X⟧) (n : ℕ) :
HahnSeries.coeff (x : R⸨X⸩) n = PowerSeries.coeff R n x := by
rw [ofPowerSeries_apply_coeff]
/-- This is a power series that can be multiplied by an integer power of `X` to give our
Laurent series. If the Laurent series is nonzero, `powerSeriesPart` has a nonzero
constant term. -/
def powerSeriesPart (x : R⸨X⸩) : R⟦X⟧ :=
PowerSeries.mk fun n => x.coeff (x.order + n)
@[simp]
theorem powerSeriesPart_coeff (x : R⸨X⸩) (n : ℕ) :
PowerSeries.coeff R n x.powerSeriesPart = x.coeff (x.order + n) :=
PowerSeries.coeff_mk _ _
@[simp]
theorem powerSeriesPart_zero : powerSeriesPart (0 : R⸨X⸩) = 0 := by
ext
simp [(PowerSeries.coeff _ _).map_zero] -- Note: this doesn't get picked up any more
@[simp]
theorem powerSeriesPart_eq_zero (x : R⸨X⸩) : x.powerSeriesPart = 0 ↔ x = 0 := by
constructor
· contrapose!
simp only [ne_eq]
intro h
rw [PowerSeries.ext_iff, not_forall]
refine ⟨0, ?_⟩
simp [coeff_order_ne_zero h]
· rintro rfl
simp
@[simp]
theorem single_order_mul_powerSeriesPart (x : R⸨X⸩) :
(single x.order 1 : R⸨X⸩) * x.powerSeriesPart = x := by
ext n
rw [← sub_add_cancel n x.order, coeff_single_mul_add, sub_add_cancel, one_mul]
by_cases h : x.order ≤ n
· rw [Int.eq_natAbs_of_nonneg (sub_nonneg_of_le h), coeff_coe_powerSeries,
powerSeriesPart_coeff, ← Int.eq_natAbs_of_nonneg (sub_nonneg_of_le h),
add_sub_cancel]
· rw [ofPowerSeries_apply, embDomain_notin_range]
· contrapose! h
exact order_le_of_coeff_ne_zero h.symm
· contrapose! h
simp only [Set.mem_range, RelEmbedding.coe_mk, Function.Embedding.coeFn_mk] at h
obtain ⟨m, hm⟩ := h
rw [← sub_nonneg, ← hm]
simp only [Nat.cast_nonneg]
theorem ofPowerSeries_powerSeriesPart (x : R⸨X⸩) :
ofPowerSeries ℤ R x.powerSeriesPart = single (-x.order) 1 * x := by
refine Eq.trans ?_ (congr rfl x.single_order_mul_powerSeriesPart)
rw [← mul_assoc, single_mul_single, neg_add_cancel, mul_one, ← C_apply, C_one, one_mul]
theorem X_order_mul_powerSeriesPart {n : ℕ} {f : R⸨X⸩} (hn : n = f.order) :
(PowerSeries.X ^ n * f.powerSeriesPart : R⟦X⟧) = f := by
simp only [map_mul, map_pow, ofPowerSeries_X, single_pow, nsmul_eq_mul, mul_one, one_pow, hn,
single_order_mul_powerSeriesPart]
end Semiring
instance [CommSemiring R] : Algebra R⟦X⟧ R⸨X⸩ := (HahnSeries.ofPowerSeries ℤ R).toAlgebra
@[simp]
theorem coe_algebraMap [CommSemiring R] :
⇑(algebraMap R⟦X⟧ R⸨X⸩) = HahnSeries.ofPowerSeries ℤ R :=
rfl
/-- The localization map from power series to Laurent series. -/
@[simps (config := { rhsMd := .all, simpRhs := true })]
instance of_powerSeries_localization [CommRing R] :
IsLocalization (Submonoid.powers (PowerSeries.X : R⟦X⟧)) R⸨X⸩ where
map_units' := by
rintro ⟨_, n, rfl⟩
refine ⟨⟨single (n : ℤ) 1, single (-n : ℤ) 1, ?_, ?_⟩, ?_⟩
· simp
· simp
· dsimp; rw [ofPowerSeries_X_pow]
surj' z := by
by_cases h : 0 ≤ z.order
· refine ⟨⟨PowerSeries.X ^ Int.natAbs z.order * powerSeriesPart z, 1⟩, ?_⟩
simp only [RingHom.map_one, mul_one, RingHom.map_mul, coe_algebraMap, ofPowerSeries_X_pow,
Submonoid.coe_one]
rw [Int.natAbs_of_nonneg h, single_order_mul_powerSeriesPart]
· refine ⟨⟨powerSeriesPart z, PowerSeries.X ^ Int.natAbs z.order, ⟨_, rfl⟩⟩, ?_⟩
simp only [coe_algebraMap, ofPowerSeries_powerSeriesPart]
rw [mul_comm _ z]
refine congr rfl ?_
rw [ofPowerSeries_X_pow, Int.ofNat_natAbs_of_nonpos]
exact le_of_not_ge h
exists_of_eq {x y} := by
rw [coe_algebraMap, ofPowerSeries_injective.eq_iff]
rintro rfl
exact ⟨1, rfl⟩
instance {K : Type*} [Field K] : IsFractionRing K⟦X⟧ K⸨X⸩ :=
IsLocalization.of_le (Submonoid.powers (PowerSeries.X : K⟦X⟧)) _
(powers_le_nonZeroDivisors_of_noZeroDivisors PowerSeries.X_ne_zero) fun _ hf =>
isUnit_of_mem_nonZeroDivisors <| map_mem_nonZeroDivisors _ HahnSeries.ofPowerSeries_injective hf
end LaurentSeries
namespace PowerSeries
open LaurentSeries
variable {R' : Type*} [Semiring R] [Ring R'] (f g : R⟦X⟧) (f' g' : R'⟦X⟧)
@[norm_cast]
theorem coe_zero : ((0 : R⟦X⟧) : R⸨X⸩) = 0 :=
(ofPowerSeries ℤ R).map_zero
@[norm_cast]
theorem coe_one : ((1 : R⟦X⟧) : R⸨X⸩) = 1 :=
(ofPowerSeries ℤ R).map_one
@[norm_cast]
theorem coe_add : ((f + g : R⟦X⟧) : R⸨X⸩) = f + g :=
(ofPowerSeries ℤ R).map_add _ _
@[norm_cast]
theorem coe_sub : ((f' - g' : R'⟦X⟧) : R'⸨X⸩) = f' - g' :=
(ofPowerSeries ℤ R').map_sub _ _
@[norm_cast]
theorem coe_neg : ((-f' : R'⟦X⟧) : R'⸨X⸩) = -f' :=
| (ofPowerSeries ℤ R').map_neg _
| Mathlib/RingTheory/LaurentSeries.lean | 327 | 328 |
/-
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
| Mathlib/Algebra/Polynomial/Roots.lean | 212 | 215 |
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Integral.FinMeasAdditive
/-!
# Extension of a linear function from indicators to L1
Given `T : Set α → E →L[ℝ] F` with `DominatedFinMeasAdditive μ T C`, we construct an extension
of `T` to integrable simple functions, which are finite sums of indicators of measurable sets
with finite measure, then to integrable functions, which are limits of integrable simple functions.
The main result is a continuous linear map `(α →₁[μ] E) →L[ℝ] F`.
This extension process is used to define the Bochner integral
in the `Mathlib.MeasureTheory.Integral.Bochner.Basic` file
and the conditional expectation of an integrable function
in `Mathlib.MeasureTheory.Function.ConditionalExpectation.CondexpL1`.
## Main definitions
- `setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F`: the extension of `T`
from indicators to L1.
- `setToFun μ T (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F`: a version of the
extension which applies to functions (with value 0 if the function is not integrable).
## Properties
For most properties of `setToFun`, we provide two lemmas. One version uses hypotheses valid on
all sets, like `T = T'`, and a second version which uses a primed name uses hypotheses on
measurable sets with finite measure, like `∀ s, MeasurableSet s → μ s < ∞ → T s = T' s`.
The lemmas listed here don't show all hypotheses. Refer to the actual lemmas for details.
Linearity:
- `setToFun_zero_left : setToFun μ 0 hT f = 0`
- `setToFun_add_left : setToFun μ (T + T') _ f = setToFun μ T hT f + setToFun μ T' hT' f`
- `setToFun_smul_left : setToFun μ (fun s ↦ c • (T s)) (hT.smul c) f = c • setToFun μ T hT f`
- `setToFun_zero : setToFun μ T hT (0 : α → E) = 0`
- `setToFun_neg : setToFun μ T hT (-f) = - setToFun μ T hT f`
If `f` and `g` are integrable:
- `setToFun_add : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g`
- `setToFun_sub : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g`
If `T` is verifies `∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x`:
- `setToFun_smul : setToFun μ T hT (c • f) = c • setToFun μ T hT f`
Other:
- `setToFun_congr_ae (h : f =ᵐ[μ] g) : setToFun μ T hT f = setToFun μ T hT g`
- `setToFun_measure_zero (h : μ = 0) : setToFun μ T hT f = 0`
If the space is also an ordered additive group with an order closed topology and `T` is such that
`0 ≤ T s x` for `0 ≤ x`, we also prove order-related properties:
- `setToFun_mono_left (h : ∀ s x, T s x ≤ T' s x) : setToFun μ T hT f ≤ setToFun μ T' hT' f`
- `setToFun_nonneg (hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f`
- `setToFun_mono (hfg : f ≤ᵐ[μ] g) : setToFun μ T hT f ≤ setToFun μ T hT g`
-/
noncomputable section
open scoped Topology NNReal
open Set Filter TopologicalSpace ENNReal
namespace MeasureTheory
variable {α E F F' G 𝕜 : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [NormedAddCommGroup F'] [NormedSpace ℝ F']
[NormedAddCommGroup G] {m : MeasurableSpace α} {μ : Measure α}
namespace L1
open AEEqFun Lp.simpleFunc Lp
namespace SimpleFunc
theorem norm_eq_sum_mul (f : α →₁ₛ[μ] G) :
‖f‖ = ∑ x ∈ (toSimpleFunc f).range, μ.real (toSimpleFunc f ⁻¹' {x}) * ‖x‖ := by
rw [norm_toSimpleFunc, eLpNorm_one_eq_lintegral_enorm]
have h_eq := SimpleFunc.map_apply (‖·‖ₑ) (toSimpleFunc f)
simp_rw [← h_eq, measureReal_def]
rw [SimpleFunc.lintegral_eq_lintegral, SimpleFunc.map_lintegral, ENNReal.toReal_sum]
· congr
ext1 x
rw [ENNReal.toReal_mul, mul_comm, ← ofReal_norm_eq_enorm,
ENNReal.toReal_ofReal (norm_nonneg _)]
· intro x _
by_cases hx0 : x = 0
· rw [hx0]; simp
· exact
ENNReal.mul_ne_top ENNReal.coe_ne_top
(SimpleFunc.measure_preimage_lt_top_of_integrable _ (SimpleFunc.integrable f) hx0).ne
section SetToL1S
variable [NormedField 𝕜] [NormedSpace 𝕜 E]
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
/-- Extend `Set α → (E →L[ℝ] F')` to `(α →₁ₛ[μ] E) → F'`. -/
def setToL1S (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : F :=
(toSimpleFunc f).setToSimpleFunc T
theorem setToL1S_eq_setToSimpleFunc (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S T f = (toSimpleFunc f).setToSimpleFunc T :=
rfl
@[simp]
theorem setToL1S_zero_left (f : α →₁ₛ[μ] E) : setToL1S (0 : Set α → E →L[ℝ] F) f = 0 :=
SimpleFunc.setToSimpleFunc_zero _
theorem setToL1S_zero_left' {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) : setToL1S T f = 0 :=
SimpleFunc.setToSimpleFunc_zero' h_zero _ (SimpleFunc.integrable f)
theorem setToL1S_congr (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) :
setToL1S T f = setToL1S T g :=
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) h
theorem setToL1S_congr_left (T T' : Set α → E →L[ℝ] F)
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁ₛ[μ] E) :
setToL1S T f = setToL1S T' f :=
SimpleFunc.setToSimpleFunc_congr_left T T' h (simpleFunc.toSimpleFunc f) (SimpleFunc.integrable f)
/-- `setToL1S` does not change if we replace the measure `μ` by `μ'` with `μ ≪ μ'`. The statement
uses two functions `f` and `f'` because they have to belong to different types, but morally these
are the same function (we have `f =ᵐ[μ] f'`). -/
theorem setToL1S_congr_measure {μ' : Measure α} (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hμ : μ ≪ μ')
(f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E) (h : (f : α → E) =ᵐ[μ] f') :
setToL1S T f = setToL1S T f' := by
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) ?_
refine (toSimpleFunc_eq_toFun f).trans ?_
suffices (f' : α → E) =ᵐ[μ] simpleFunc.toSimpleFunc f' from h.trans this
have goal' : (f' : α → E) =ᵐ[μ'] simpleFunc.toSimpleFunc f' := (toSimpleFunc_eq_toFun f').symm
exact hμ.ae_eq goal'
theorem setToL1S_add_left (T T' : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S (T + T') f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left T T'
theorem setToL1S_add_left' (T T' T'' : Set α → E →L[ℝ] F)
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1S T'' f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left' T T' T'' h_add (SimpleFunc.integrable f)
theorem setToL1S_smul_left (T : Set α → E →L[ℝ] F) (c : ℝ) (f : α →₁ₛ[μ] E) :
setToL1S (fun s => c • T s) f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left T c _
theorem setToL1S_smul_left' (T T' : Set α → E →L[ℝ] F) (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1S T' f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left' T T' c h_smul (SimpleFunc.integrable f)
theorem setToL1S_add (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f + g) = setToL1S T f + setToL1S T g := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_add T h_add (SimpleFunc.integrable f)
(SimpleFunc.integrable g)]
exact
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _)
(add_toSimpleFunc f g)
theorem setToL1S_neg {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f : α →₁ₛ[μ] E) : setToL1S T (-f) = -setToL1S T f := by
simp_rw [setToL1S]
have : simpleFunc.toSimpleFunc (-f) =ᵐ[μ] ⇑(-simpleFunc.toSimpleFunc f) :=
neg_toSimpleFunc f
rw [SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) this]
exact SimpleFunc.setToSimpleFunc_neg T h_add (SimpleFunc.integrable f)
theorem setToL1S_sub {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f - g) = setToL1S T f - setToL1S T g := by
rw [sub_eq_add_neg, setToL1S_add T h_zero h_add, setToL1S_neg h_zero h_add, sub_eq_add_neg]
theorem setToL1S_smul_real (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (c : ℝ)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul_real T h_add c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
theorem setToL1S_smul {E} [NormedAddCommGroup E] [NormedSpace ℝ E] [NormedSpace 𝕜 E]
[DistribSMul 𝕜 F] (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul T h_add h_smul c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
theorem norm_setToL1S_le (T : Set α → E →L[ℝ] F) {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * μ.real s) (f : α →₁ₛ[μ] E) :
‖setToL1S T f‖ ≤ C * ‖f‖ := by
rw [setToL1S, norm_eq_sum_mul f]
exact
SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm _
(SimpleFunc.integrable f)
theorem setToL1S_indicatorConst {T : Set α → E →L[ℝ] F} {s : Set α}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T)
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
have h_empty : T ∅ = 0 := h_zero _ MeasurableSet.empty measure_empty
rw [setToL1S_eq_setToSimpleFunc]
refine Eq.trans ?_ (SimpleFunc.setToSimpleFunc_indicator T h_empty hs x)
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact toSimpleFunc_indicatorConst hs hμs.ne x
theorem setToL1S_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) = T univ x :=
setToL1S_indicatorConst h_zero h_add MeasurableSet.univ (measure_lt_top _ _) x
section Order
variable {G'' G' : Type*}
[NormedAddCommGroup G'] [PartialOrder G'] [IsOrderedAddMonoid G'] [NormedSpace ℝ G']
[NormedAddCommGroup G''] [PartialOrder G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G'']
{T : Set α → G'' →L[ℝ] G'}
theorem setToL1S_mono_left {T T' : Set α → E →L[ℝ] G''} (hTT' : ∀ s x, T s x ≤ T' s x)
(f : α →₁ₛ[μ] E) : setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
theorem setToL1S_mono_left' {T T' : Set α → E →L[ℝ] G''}
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
omit [IsOrderedAddMonoid G''] in
theorem setToL1S_nonneg (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G''}
(hf : 0 ≤ f) : 0 ≤ setToL1S T f := by
simp_rw [setToL1S]
obtain ⟨f', hf', hff'⟩ := exists_simpleFunc_nonneg_ae_eq hf
replace hff' : simpleFunc.toSimpleFunc f =ᵐ[μ] f' :=
(Lp.simpleFunc.toSimpleFunc_eq_toFun f).trans hff'
rw [SimpleFunc.setToSimpleFunc_congr _ h_zero h_add (SimpleFunc.integrable _) hff']
exact
SimpleFunc.setToSimpleFunc_nonneg' T hT_nonneg _ hf' ((SimpleFunc.integrable f).congr hff')
theorem setToL1S_mono (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G''}
(hfg : f ≤ g) : setToL1S T f ≤ setToL1S T g := by
rw [← sub_nonneg] at hfg ⊢
rw [← setToL1S_sub h_zero h_add]
exact setToL1S_nonneg h_zero h_add hT_nonneg hfg
end Order
variable [NormedSpace 𝕜 F]
variable (α E μ 𝕜)
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[𝕜] F`. -/
def setToL1SCLM' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁ₛ[μ] E) →L[𝕜] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul T (fun _ => hT.eq_zero_of_measure_zero) hT.1 h_smul⟩
C fun f => norm_setToL1S_le T hT.2 f
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[ℝ] F`. -/
def setToL1SCLM {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
(α →₁ₛ[μ] E) →L[ℝ] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul_real T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩
C fun f => norm_setToL1S_le T hT.2 f
variable {α E μ 𝕜}
variable {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
@[simp]
theorem setToL1SCLM_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left _
theorem setToL1SCLM_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left' h_zero f
theorem setToL1SCLM_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' (fun _ _ _ => by rw [h]) f
theorem setToL1SCLM_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' h f
theorem setToL1SCLM_congr_measure {μ' : Measure α} (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (hμ : μ ≪ μ') (f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E)
(h : (f : α → E) =ᵐ[μ] f') : setToL1SCLM α E μ hT f = setToL1SCLM α E μ' hT' f' :=
setToL1S_congr_measure T (fun _ => hT.eq_zero_of_measure_zero) hT.1 hμ _ _ h
theorem setToL1SCLM_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.add hT') f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left T T' f
theorem setToL1SCLM_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT'' f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left' T T' T'' h_add f
theorem setToL1SCLM_smul_left (c : ℝ) (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.smul c) f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left T c f
theorem setToL1SCLM_smul_left' (c : ℝ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C')
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT' f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left' T T' c h_smul f
theorem norm_setToL1SCLM_le {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hC : 0 ≤ C) : ‖setToL1SCLM α E μ hT‖ ≤ C :=
LinearMap.mkContinuous_norm_le _ hC _
theorem norm_setToL1SCLM_le' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1SCLM α E μ hT‖ ≤ max C 0 :=
LinearMap.mkContinuous_norm_le' _ _
theorem setToL1SCLM_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F} {C : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1SCLM α E μ hT (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) =
T univ x :=
setToL1S_const (fun _ => hT.eq_zero_of_measure_zero) hT.1 x
section Order
variable {G' G'' : Type*}
[NormedAddCommGroup G''] [PartialOrder G''] [IsOrderedAddMonoid G''] [NormedSpace ℝ G'']
[NormedAddCommGroup G'] [PartialOrder G'] [IsOrderedAddMonoid G'] [NormedSpace ℝ G']
theorem setToL1SCLM_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
theorem setToL1SCLM_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
omit [IsOrderedAddMonoid G'] in
theorem setToL1SCLM_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1SCLM α G' μ hT f :=
setToL1S_nonneg (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hf
theorem setToL1SCLM_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G'}
(hfg : f ≤ g) : setToL1SCLM α G' μ hT f ≤ setToL1SCLM α G' μ hT g :=
setToL1S_mono (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hfg
end Order
end SetToL1S
end SimpleFunc
open SimpleFunc
section SetToL1
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
variable (𝕜) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F] [CompleteSpace F]
{T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
/-- Extend `Set α → (E →L[ℝ] F)` to `(α →₁[μ] E) →L[𝕜] F`. -/
def setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁[μ] E) →L[𝕜] F :=
(setToL1SCLM' α E 𝕜 μ hT h_smul).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top)
simpleFunc.isUniformInducing
variable {𝕜}
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁[μ] E) →L[ℝ] F`. -/
def setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F :=
(setToL1SCLM α E μ hT).extend (coeToLp α E ℝ) (simpleFunc.denseRange one_ne_top)
simpleFunc.isUniformInducing
theorem setToL1_eq_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1 hT f = setToL1SCLM α E μ hT f :=
uniformly_extend_of_ind simpleFunc.isUniformInducing (simpleFunc.denseRange one_ne_top)
(setToL1SCLM α E μ hT).uniformContinuous _
theorem setToL1_eq_setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (f : α →₁[μ] E) :
setToL1 hT f = setToL1' 𝕜 hT h_smul f :=
rfl
@[simp]
theorem setToL1_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left hT f, ContinuousLinearMap.zero_comp, ContinuousLinearMap.zero_apply]
theorem setToL1_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left' hT h_zero f, ContinuousLinearMap.zero_comp,
ContinuousLinearMap.zero_apply]
theorem setToL1_congr_left (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T')
(f : α →₁[μ] E) : setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM]
exact setToL1SCLM_congr_left hT' hT h.symm f
theorem setToL1_congr_left' (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁[μ] E) :
setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM]
exact (setToL1SCLM_congr_left' hT hT' h f).symm
theorem setToL1_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁[μ] E) :
setToL1 (hT.add hT') f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 (hT.add hT') = setToL1 hT + setToL1 hT' by
rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.add hT')) _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ (hT.add hT') f by
rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM, setToL1SCLM_add_left hT hT']
theorem setToL1_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁[μ] E) :
setToL1 hT'' f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 hT'' = setToL1 hT + setToL1 hT' by rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT'') _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ hT'' f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM,
setToL1SCLM_add_left' hT hT' hT'' h_add]
theorem setToL1_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α →₁[μ] E) :
setToL1 (hT.smul c) f = c • setToL1 hT f := by
suffices setToL1 (hT.smul c) = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.smul c)) _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ (hT.smul c) f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left c hT]
theorem setToL1_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁[μ] E) :
setToL1 hT' f = c • setToL1 hT f := by
suffices setToL1 hT' = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT') _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ hT' f by rw [← this]; simp [coeToLp]
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left' c hT hT' h_smul]
theorem setToL1_smul (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α →₁[μ] E) :
setToL1 hT (c • f) = c • setToL1 hT f := by
rw [setToL1_eq_setToL1' hT h_smul, setToL1_eq_setToL1' hT h_smul]
exact ContinuousLinearMap.map_smul _ _ _
theorem setToL1_simpleFunc_indicatorConst (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1 hT (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
rw [setToL1_eq_setToL1SCLM]
exact setToL1S_indicatorConst (fun s => hT.eq_zero_of_measure_zero) hT.1 hs hμs x
theorem setToL1_indicatorConstLp (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToL1 hT (indicatorConstLp 1 hs hμs x) = T s x := by
rw [← Lp.simpleFunc.coe_indicatorConst hs hμs x]
exact setToL1_simpleFunc_indicatorConst hT hs hμs.lt_top x
theorem setToL1_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1 hT (indicatorConstLp 1 MeasurableSet.univ (measure_ne_top _ _) x) = T univ x :=
setToL1_indicatorConstLp hT MeasurableSet.univ (measure_ne_top _ _) x
section Order
variable {G' G'' : Type*}
[NormedAddCommGroup G''] [PartialOrder G''] [OrderClosedTopology G''] [IsOrderedAddMonoid G'']
[NormedSpace ℝ G''] [CompleteSpace G'']
[NormedAddCommGroup G'] [PartialOrder G'] [NormedSpace ℝ G']
theorem setToL1_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁[μ] E) :
setToL1 hT f ≤ setToL1 hT' f := by
induction f using Lp.induction (hp_ne_top := one_ne_top) with
| @indicatorConst c s hs hμs =>
rw [setToL1_simpleFunc_indicatorConst hT hs hμs, setToL1_simpleFunc_indicatorConst hT' hs hμs]
exact hTT' s hs hμs c
| @add f g hf hg _ hf_le hg_le =>
rw [(setToL1 hT).map_add, (setToL1 hT').map_add]
exact add_le_add hf_le hg_le
| isClosed => exact isClosed_le (setToL1 hT).continuous (setToL1 hT').continuous
theorem setToL1_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToL1 hT f ≤ setToL1 hT' f :=
setToL1_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
theorem setToL1_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1 hT f := by
suffices ∀ f : { g : α →₁[μ] G' // 0 ≤ g }, 0 ≤ setToL1 hT f from
this (⟨f, hf⟩ : { g : α →₁[μ] G' // 0 ≤ g })
refine fun g =>
@isClosed_property { g : α →₁ₛ[μ] G' // 0 ≤ g } { g : α →₁[μ] G' // 0 ≤ g } _ _
(fun g => 0 ≤ setToL1 hT g)
(denseRange_coeSimpleFuncNonnegToLpNonneg 1 μ G' one_ne_top) ?_ ?_ g
· exact isClosed_le continuous_zero ((setToL1 hT).continuous.comp continuous_induced_dom)
· intro g
have : (coeSimpleFuncNonnegToLpNonneg 1 μ G' g : α →₁[μ] G') = (g : α →₁ₛ[μ] G') := rfl
rw [this, setToL1_eq_setToL1SCLM]
exact setToL1S_nonneg (fun s => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg g.2
theorem setToL1_mono [IsOrderedAddMonoid G']
{T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁[μ] G'}
(hfg : f ≤ g) : setToL1 hT f ≤ setToL1 hT g := by
rw [← sub_nonneg] at hfg ⊢
rw [← (setToL1 hT).map_sub]
exact setToL1_nonneg hT hT_nonneg hfg
end Order
theorem norm_setToL1_le_norm_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1 hT‖ ≤ ‖setToL1SCLM α E μ hT‖ :=
calc
‖setToL1 hT‖ ≤ (1 : ℝ≥0) * ‖setToL1SCLM α E μ hT‖ := by
refine
ContinuousLinearMap.opNorm_extend_le (setToL1SCLM α E μ hT) (coeToLp α E ℝ)
(simpleFunc.denseRange one_ne_top) fun x => le_of_eq ?_
rw [NNReal.coe_one, one_mul]
simp [coeToLp]
_ = ‖setToL1SCLM α E μ hT‖ := by rw [NNReal.coe_one, one_mul]
theorem norm_setToL1_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C)
(f : α →₁[μ] E) : ‖setToL1 hT f‖ ≤ C * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ C * ‖f‖ := mul_le_mul (norm_setToL1SCLM_le hT hC) le_rfl (norm_nonneg _) hC
theorem norm_setToL1_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
‖setToL1 hT f‖ ≤ max C 0 * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ max C 0 * ‖f‖ :=
mul_le_mul (norm_setToL1SCLM_le' hT) le_rfl (norm_nonneg _) (le_max_right _ _)
theorem norm_setToL1_le (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : ‖setToL1 hT‖ ≤ C :=
ContinuousLinearMap.opNorm_le_bound _ hC (norm_setToL1_le_mul_norm hT hC)
theorem norm_setToL1_le' (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1 hT‖ ≤ max C 0 :=
ContinuousLinearMap.opNorm_le_bound _ (le_max_right _ _) (norm_setToL1_le_mul_norm' hT)
theorem setToL1_lipschitz (hT : DominatedFinMeasAdditive μ T C) :
LipschitzWith (Real.toNNReal C) (setToL1 hT) :=
(setToL1 hT).lipschitz.weaken (norm_setToL1_le' hT)
/-- If `fs i → f` in `L1`, then `setToL1 hT (fs i) → setToL1 hT f`. -/
theorem tendsto_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) {ι}
(fs : ι → α →₁[μ] E) {l : Filter ι} (hfs : Tendsto fs l (𝓝 f)) :
Tendsto (fun i => setToL1 hT (fs i)) l (𝓝 <| setToL1 hT f) :=
((setToL1 hT).continuous.tendsto _).comp hfs
end SetToL1
end L1
section Function
variable [CompleteSpace F] {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} {f g : α → E}
variable (μ T)
open Classical in
/-- Extend `T : Set α → E →L[ℝ] F` to `(α → E) → F` (for integrable functions `α → E`). We set it to
0 if the function is not integrable. -/
def setToFun (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F :=
if hf : Integrable f μ then L1.setToL1 hT (hf.toL1 f) else 0
variable {μ T}
theorem setToFun_eq (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT f = L1.setToL1 hT (hf.toL1 f) :=
dif_pos hf
theorem L1.setToFun_eq_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
setToFun μ T hT f = L1.setToL1 hT f := by
rw [setToFun_eq hT (L1.integrable_coeFn f), Integrable.toL1_coeFn]
theorem setToFun_undef (hT : DominatedFinMeasAdditive μ T C) (hf : ¬Integrable f μ) :
setToFun μ T hT f = 0 :=
dif_neg hf
theorem setToFun_non_aestronglyMeasurable (hT : DominatedFinMeasAdditive μ T C)
(hf : ¬AEStronglyMeasurable f μ) : setToFun μ T hT f = 0 :=
setToFun_undef hT (not_and_of_not_left _ hf)
@[deprecated (since := "2025-04-09")]
alias setToFun_non_aEStronglyMeasurable := setToFun_non_aestronglyMeasurable
theorem setToFun_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α → E) :
setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
theorem setToFun_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α → E) : setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left' T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
theorem setToFun_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α → E) :
setToFun μ (T + T') (hT.add hT') f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left hT hT']
· simp_rw [setToFun_undef _ hf, add_zero]
theorem setToFun_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α → E) :
setToFun μ T'' hT'' f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left' hT hT' hT'' h_add]
· simp_rw [setToFun_undef _ hf, add_zero]
theorem setToFun_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α → E) :
setToFun μ (fun s => c • T s) (hT.smul c) f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left hT c]
· simp_rw [setToFun_undef _ hf, smul_zero]
theorem setToFun_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α → E) :
setToFun μ T' hT' f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left' hT hT' c h_smul]
· simp_rw [setToFun_undef _ hf, smul_zero]
@[simp]
theorem setToFun_zero (hT : DominatedFinMeasAdditive μ T C) : setToFun μ T hT (0 : α → E) = 0 := by
rw [Pi.zero_def, setToFun_eq hT (integrable_zero _ _ _)]
simp only [← Pi.zero_def]
rw [Integrable.toL1_zero, ContinuousLinearMap.map_zero]
@[simp]
theorem setToFun_zero_left {hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C} :
setToFun μ 0 hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left hT _
· exact setToFun_undef hT hf
theorem setToFun_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) : setToFun μ T hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left' hT h_zero _
· exact setToFun_undef hT hf
theorem setToFun_add (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g := by
rw [setToFun_eq hT (hf.add hg), setToFun_eq hT hf, setToFun_eq hT hg, Integrable.toL1_add,
(L1.setToL1 hT).map_add]
theorem setToFun_finset_sum' (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι)
{f : ι → α → E} (hf : ∀ i ∈ s, Integrable (f i) μ) :
setToFun μ T hT (∑ i ∈ s, f i) = ∑ i ∈ s, setToFun μ T hT (f i) := by
classical
revert hf
refine Finset.induction_on s ?_ ?_
· intro _
simp only [setToFun_zero, Finset.sum_empty]
· intro i s his ih hf
simp only [his, Finset.sum_insert, not_false_iff]
rw [setToFun_add hT (hf i (Finset.mem_insert_self i s)) _]
· rw [ih fun i hi => hf i (Finset.mem_insert_of_mem hi)]
· convert integrable_finset_sum s fun i hi => hf i (Finset.mem_insert_of_mem hi) with x
simp
theorem setToFun_finset_sum (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι) {f : ι → α → E}
(hf : ∀ i ∈ s, Integrable (f i) μ) :
(setToFun μ T hT fun a => ∑ i ∈ s, f i a) = ∑ i ∈ s, setToFun μ T hT (f i) := by
convert setToFun_finset_sum' hT s hf with a; simp
theorem setToFun_neg (hT : DominatedFinMeasAdditive μ T C) (f : α → E) :
setToFun μ T hT (-f) = -setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT hf.neg, Integrable.toL1_neg,
(L1.setToL1 hT).map_neg]
· rw [setToFun_undef hT hf, setToFun_undef hT, neg_zero]
rwa [← integrable_neg_iff] at hf
theorem setToFun_sub (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g := by
rw [sub_eq_add_neg, sub_eq_add_neg, setToFun_add hT hf hg.neg, setToFun_neg hT g]
theorem setToFun_smul [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F]
(hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α → E) : setToFun μ T hT (c • f) = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT, Integrable.toL1_smul',
L1.setToL1_smul hT h_smul c _]
· by_cases hr : c = 0
· rw [hr]; simp
· have hf' : ¬Integrable (c • f) μ := by rwa [integrable_smul_iff hr f]
rw [setToFun_undef hT hf, setToFun_undef hT hf', smul_zero]
theorem setToFun_congr_ae (hT : DominatedFinMeasAdditive μ T C) (h : f =ᵐ[μ] g) :
setToFun μ T hT f = setToFun μ T hT g := by
by_cases hfi : Integrable f μ
· have hgi : Integrable g μ := hfi.congr h
rw [setToFun_eq hT hfi, setToFun_eq hT hgi, (Integrable.toL1_eq_toL1_iff f g hfi hgi).2 h]
· have hgi : ¬Integrable g μ := by rw [integrable_congr h] at hfi; exact hfi
rw [setToFun_undef hT hfi, setToFun_undef hT hgi]
theorem setToFun_measure_zero (hT : DominatedFinMeasAdditive μ T C) (h : μ = 0) :
setToFun μ T hT f = 0 := by
have : f =ᵐ[μ] 0 := by simp [h, EventuallyEq]
rw [setToFun_congr_ae hT this, setToFun_zero]
theorem setToFun_measure_zero' (hT : DominatedFinMeasAdditive μ T C)
(h : ∀ s, MeasurableSet s → μ s < ∞ → μ s = 0) : setToFun μ T hT f = 0 :=
setToFun_zero_left' hT fun s hs hμs => hT.eq_zero_of_measure_zero hs (h s hs hμs)
theorem setToFun_toL1 (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT (hf.toL1 f) = setToFun μ T hT f :=
setToFun_congr_ae hT hf.coeFn_toL1
theorem setToFun_indicator_const (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToFun μ T hT (s.indicator fun _ => x) = T s x := by
rw [setToFun_congr_ae hT (@indicatorConstLp_coeFn _ _ _ 1 _ _ _ hs hμs x).symm]
rw [L1.setToFun_eq_setToL1 hT]
exact L1.setToL1_indicatorConstLp hT hs hμs x
theorem setToFun_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
(setToFun μ T hT fun _ => x) = T univ x := by
have : (fun _ : α => x) = Set.indicator univ fun _ => x := (indicator_univ _).symm
rw [this]
exact setToFun_indicator_const hT MeasurableSet.univ (measure_ne_top _ _) x
section Order
variable {G' G'' : Type*}
[NormedAddCommGroup G''] [PartialOrder G''] [OrderClosedTopology G''] [IsOrderedAddMonoid G'']
[NormedSpace ℝ G''] [CompleteSpace G'']
[NormedAddCommGroup G'] [PartialOrder G'] [NormedSpace ℝ G']
theorem setToFun_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α → E) :
setToFun μ T hT f ≤ setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf]; exact L1.setToL1_mono_left' hT hT' hTT' _
· simp_rw [setToFun_undef _ hf, le_rfl]
theorem setToFun_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToFun μ T hT f ≤ setToFun μ T' hT' f :=
setToFun_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
theorem setToFun_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α → G'}
(hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f := by
by_cases hfi : Integrable f μ
· simp_rw [setToFun_eq _ hfi]
refine L1.setToL1_nonneg hT hT_nonneg ?_
rw [← Lp.coeFn_le]
have h0 := Lp.coeFn_zero G' 1 μ
have h := Integrable.coeFn_toL1 hfi
filter_upwards [h0, h, hf] with _ h0a ha hfa
rw [h0a, ha]
exact hfa
· simp_rw [setToFun_undef _ hfi, le_rfl]
theorem setToFun_mono [IsOrderedAddMonoid G']
{T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α → G'}
(hf : Integrable f μ) (hg : Integrable g μ) (hfg : f ≤ᵐ[μ] g) :
setToFun μ T hT f ≤ setToFun μ T hT g := by
rw [← sub_nonneg, ← setToFun_sub hT hg hf]
refine setToFun_nonneg hT hT_nonneg (hfg.mono fun a ha => ?_)
rw [Pi.sub_apply, Pi.zero_apply, sub_nonneg]
exact ha
end Order
@[continuity]
theorem continuous_setToFun (hT : DominatedFinMeasAdditive μ T C) :
Continuous fun f : α →₁[μ] E => setToFun μ T hT f := by
simp_rw [L1.setToFun_eq_setToL1 hT]; exact ContinuousLinearMap.continuous _
/-- If `F i → f` in `L1`, then `setToFun μ T hT (F i) → setToFun μ T hT f`. -/
theorem tendsto_setToFun_of_L1 (hT : DominatedFinMeasAdditive μ T C) {ι} (f : α → E)
(hfi : Integrable f μ) {fs : ι → α → E} {l : Filter ι} (hfsi : ∀ᶠ i in l, Integrable (fs i) μ)
(hfs : Tendsto (fun i => ∫⁻ x, ‖fs i x - f x‖ₑ ∂μ) l (𝓝 0)) :
Tendsto (fun i => setToFun μ T hT (fs i)) l (𝓝 <| setToFun μ T hT f) := by
classical
let f_lp := hfi.toL1 f
let F_lp i := if hFi : Integrable (fs i) μ then hFi.toL1 (fs i) else 0
have tendsto_L1 : Tendsto F_lp l (𝓝 f_lp) := by
rw [Lp.tendsto_Lp_iff_tendsto_eLpNorm']
simp_rw [eLpNorm_one_eq_lintegral_enorm, Pi.sub_apply]
refine (tendsto_congr' ?_).mp hfs
filter_upwards [hfsi] with i hi
refine lintegral_congr_ae ?_
filter_upwards [hi.coeFn_toL1, hfi.coeFn_toL1] with x hxi hxf
simp_rw [F_lp, dif_pos hi, hxi, f_lp, hxf]
suffices Tendsto (fun i => setToFun μ T hT (F_lp i)) l (𝓝 (setToFun μ T hT f)) by
refine (tendsto_congr' ?_).mp this
filter_upwards [hfsi] with i hi
suffices h_ae_eq : F_lp i =ᵐ[μ] fs i from setToFun_congr_ae hT h_ae_eq
simp_rw [F_lp, dif_pos hi]
exact hi.coeFn_toL1
rw [setToFun_congr_ae hT hfi.coeFn_toL1.symm]
exact ((continuous_setToFun hT).tendsto f_lp).comp tendsto_L1
theorem tendsto_setToFun_approxOn_of_measurable (hT : DominatedFinMeasAdditive μ T C)
[MeasurableSpace E] [BorelSpace E] {f : α → E} {s : Set E} [SeparableSpace s]
(hfi : Integrable f μ) (hfm : Measurable f) (hs : ∀ᵐ x ∂μ, f x ∈ closure s) {y₀ : E}
(h₀ : y₀ ∈ s) (h₀i : Integrable (fun _ => y₀) μ) :
Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f hfm s y₀ h₀ n)) atTop
(𝓝 <| setToFun μ T hT f) :=
tendsto_setToFun_of_L1 hT _ hfi
(Eventually.of_forall (SimpleFunc.integrable_approxOn hfm hfi h₀ h₀i))
(SimpleFunc.tendsto_approxOn_L1_enorm hfm _ hs (hfi.sub h₀i).2)
theorem tendsto_setToFun_approxOn_of_measurable_of_range_subset
(hT : DominatedFinMeasAdditive μ T C) [MeasurableSpace E] [BorelSpace E] {f : α → E}
(fmeas : Measurable f) (hf : Integrable f μ) (s : Set E) [SeparableSpace s]
(hs : range f ∪ {0} ⊆ s) :
Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f fmeas s 0 (hs <| by simp) n)) atTop
(𝓝 <| setToFun μ T hT f) := by
refine tendsto_setToFun_approxOn_of_measurable hT hf fmeas ?_ _ (integrable_zero _ _ _)
exact Eventually.of_forall fun x => subset_closure (hs (Set.mem_union_left _ (mem_range_self _)))
/-- Auxiliary lemma for `setToFun_congr_measure`: the function sending `f : α →₁[μ] G` to
`f : α →₁[μ'] G` is continuous when `μ' ≤ c' • μ` for `c' ≠ ∞`. -/
theorem continuous_L1_toL1 {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞) (hμ'_le : μ' ≤ c' • μ) :
Continuous fun f : α →₁[μ] G =>
(Integrable.of_measure_le_smul hc' hμ'_le (L1.integrable_coeFn f)).toL1 f := by
by_cases hc'0 : c' = 0
· have hμ'0 : μ' = 0 := by rw [← Measure.nonpos_iff_eq_zero']; refine hμ'_le.trans ?_; simp [hc'0]
have h_im_zero :
(fun f : α →₁[μ] G =>
(Integrable.of_measure_le_smul hc' hμ'_le (L1.integrable_coeFn f)).toL1 f) =
0 := by
ext1 f; ext1; simp_rw [hμ'0]; simp only [ae_zero, EventuallyEq, eventually_bot]
rw [h_im_zero]
exact continuous_zero
rw [Metric.continuous_iff]
intro f ε hε_pos
use ε / 2 / c'.toReal
refine ⟨div_pos (half_pos hε_pos) (toReal_pos hc'0 hc'), ?_⟩
intro g hfg
rw [Lp.dist_def] at hfg ⊢
let h_int := fun f' : α →₁[μ] G => (L1.integrable_coeFn f').of_measure_le_smul hc' hμ'_le
have :
eLpNorm (⇑(Integrable.toL1 g (h_int g)) - ⇑(Integrable.toL1 f (h_int f))) 1 μ' =
eLpNorm (⇑g - ⇑f) 1 μ' :=
eLpNorm_congr_ae ((Integrable.coeFn_toL1 _).sub (Integrable.coeFn_toL1 _))
rw [this]
have h_eLpNorm_ne_top : eLpNorm (⇑g - ⇑f) 1 μ ≠ ∞ := by
rw [← eLpNorm_congr_ae (Lp.coeFn_sub _ _)]; exact Lp.eLpNorm_ne_top _
calc
(eLpNorm (⇑g - ⇑f) 1 μ').toReal ≤ (c' * eLpNorm (⇑g - ⇑f) 1 μ).toReal := by
refine toReal_mono (ENNReal.mul_ne_top hc' h_eLpNorm_ne_top) ?_
refine (eLpNorm_mono_measure (⇑g - ⇑f) hμ'_le).trans_eq ?_
rw [eLpNorm_smul_measure_of_ne_zero hc'0, smul_eq_mul]
simp
_ = c'.toReal * (eLpNorm (⇑g - ⇑f) 1 μ).toReal := toReal_mul
_ ≤ c'.toReal * (ε / 2 / c'.toReal) := by gcongr
_ = ε / 2 := by
refine mul_div_cancel₀ (ε / 2) ?_; rw [Ne, toReal_eq_zero_iff]; simp [hc', hc'0]
_ < ε := half_lt_self hε_pos
theorem setToFun_congr_measure_of_integrable {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞)
(hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) (hfμ : Integrable f μ) :
setToFun μ T hT f = setToFun μ' T hT' f := by
-- integrability for `μ` implies integrability for `μ'`.
have h_int : ∀ g : α → E, Integrable g μ → Integrable g μ' := fun g hg =>
Integrable.of_measure_le_smul hc' hμ'_le hg
-- We use `Integrable.induction`
apply hfμ.induction (P := fun f => setToFun μ T hT f = setToFun μ' T hT' f)
· intro c s hs hμs
have hμ's : μ' s ≠ ∞ := by
refine ((hμ'_le s).trans_lt ?_).ne
rw [Measure.smul_apply, smul_eq_mul]
exact ENNReal.mul_lt_top hc'.lt_top hμs
rw [setToFun_indicator_const hT hs hμs.ne, setToFun_indicator_const hT' hs hμ's]
· intro f₂ g₂ _ hf₂ hg₂ h_eq_f h_eq_g
rw [setToFun_add hT hf₂ hg₂, setToFun_add hT' (h_int f₂ hf₂) (h_int g₂ hg₂), h_eq_f, h_eq_g]
· refine isClosed_eq (continuous_setToFun hT) ?_
have :
(fun f : α →₁[μ] E => setToFun μ' T hT' f) = fun f : α →₁[μ] E =>
setToFun μ' T hT' ((h_int f (L1.integrable_coeFn f)).toL1 f) := by
ext1 f; exact setToFun_congr_ae hT' (Integrable.coeFn_toL1 _).symm
rw [this]
exact (continuous_setToFun hT').comp (continuous_L1_toL1 c' hc' hμ'_le)
· intro f₂ g₂ hfg _ hf_eq
have hfg' : f₂ =ᵐ[μ'] g₂ := (Measure.absolutelyContinuous_of_le_smul hμ'_le).ae_eq hfg
rw [← setToFun_congr_ae hT hfg, hf_eq, setToFun_congr_ae hT' hfg']
theorem setToFun_congr_measure {μ' : Measure α} (c c' : ℝ≥0∞) (hc : c ≠ ∞) (hc' : c' ≠ ∞)
(hμ_le : μ ≤ c • μ') (hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) :
setToFun μ T hT f = setToFun μ' T hT' f := by
by_cases hf : Integrable f μ
· exact setToFun_congr_measure_of_integrable c' hc' hμ'_le hT hT' f hf
· -- if `f` is not integrable, both `setToFun` are 0.
have h_int : ∀ g : α → E, ¬Integrable g μ → ¬Integrable g μ' := fun g =>
mt fun h => h.of_measure_le_smul hc hμ_le
simp_rw [setToFun_undef _ hf, setToFun_undef _ (h_int f hf)]
theorem setToFun_congr_measure_of_add_right {μ' : Measure α}
(hT_add : DominatedFinMeasAdditive (μ + μ') T C') (hT : DominatedFinMeasAdditive μ T C)
(f : α → E) (hf : Integrable f (μ + μ')) :
setToFun (μ + μ') T hT_add f = setToFun μ T hT f := by
refine setToFun_congr_measure_of_integrable 1 one_ne_top ?_ hT_add hT f hf
rw [one_smul]
nth_rw 1 [← add_zero μ]
exact add_le_add le_rfl bot_le
theorem setToFun_congr_measure_of_add_left {μ' : Measure α}
(hT_add : DominatedFinMeasAdditive (μ + μ') T C') (hT : DominatedFinMeasAdditive μ' T C)
(f : α → E) (hf : Integrable f (μ + μ')) :
setToFun (μ + μ') T hT_add f = setToFun μ' T hT f := by
refine setToFun_congr_measure_of_integrable 1 one_ne_top ?_ hT_add hT f hf
rw [one_smul]
nth_rw 1 [← zero_add μ']
exact add_le_add_right bot_le μ'
theorem setToFun_top_smul_measure (hT : DominatedFinMeasAdditive (∞ • μ) T C) (f : α → E) :
setToFun (∞ • μ) T hT f = 0 := by
refine setToFun_measure_zero' hT fun s _ hμs => ?_
rw [lt_top_iff_ne_top] at hμs
simp only [true_and, Measure.smul_apply, ENNReal.mul_eq_top, eq_self_iff_true,
top_ne_zero, Ne, not_false_iff, not_or, Classical.not_not, smul_eq_mul] at hμs
simp only [hμs.right, Measure.smul_apply, mul_zero, smul_eq_mul]
theorem setToFun_congr_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞)
(hT : DominatedFinMeasAdditive μ T C) (hT_smul : DominatedFinMeasAdditive (c • μ) T C')
(f : α → E) : setToFun μ T hT f = setToFun (c • μ) T hT_smul f := by
by_cases hc0 : c = 0
· simp [hc0] at hT_smul
have h : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0 := fun s hs _ => hT_smul.eq_zero hs
rw [setToFun_zero_left' _ h, setToFun_measure_zero]
simp [hc0]
refine setToFun_congr_measure c⁻¹ c ?_ hc_ne_top (le_of_eq ?_) le_rfl hT hT_smul f
· simp [hc0]
· rw [smul_smul, ENNReal.inv_mul_cancel hc0 hc_ne_top, one_smul]
theorem norm_setToFun_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E)
(hC : 0 ≤ C) : ‖setToFun μ T hT f‖ ≤ C * ‖f‖ := by
rw [L1.setToFun_eq_setToL1]; exact L1.norm_setToL1_le_mul_norm hT hC f
theorem norm_setToFun_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
‖setToFun μ T hT f‖ ≤ max C 0 * ‖f‖ := by
rw [L1.setToFun_eq_setToL1]; exact L1.norm_setToL1_le_mul_norm' hT f
theorem norm_setToFun_le (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) (hC : 0 ≤ C) :
‖setToFun μ T hT f‖ ≤ C * ‖hf.toL1 f‖ := by
rw [setToFun_eq hT hf]; exact L1.norm_setToL1_le_mul_norm hT hC _
theorem norm_setToFun_le' (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
‖setToFun μ T hT f‖ ≤ max C 0 * ‖hf.toL1 f‖ := by
rw [setToFun_eq hT hf]; exact L1.norm_setToL1_le_mul_norm' hT _
/-- Lebesgue dominated convergence theorem provides sufficient conditions under which almost
everywhere convergence of a sequence of functions implies the convergence of their image by
`setToFun`.
We could weaken the condition `bound_integrable` to require `HasFiniteIntegral bound μ` instead
(i.e. not requiring that `bound` is measurable), but in all applications proving integrability
is easier. -/
theorem tendsto_setToFun_of_dominated_convergence (hT : DominatedFinMeasAdditive μ T C)
{fs : ℕ → α → E} {f : α → E} (bound : α → ℝ)
(fs_measurable : ∀ n, AEStronglyMeasurable (fs n) μ) (bound_integrable : Integrable bound μ)
(h_bound : ∀ n, ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => fs n a) atTop (𝓝 (f a))) :
Tendsto (fun n => setToFun μ T hT (fs n)) atTop (𝓝 <| setToFun μ T hT f) := by
-- `f` is a.e.-measurable, since it is the a.e.-pointwise limit of a.e.-measurable functions.
have f_measurable : AEStronglyMeasurable f μ :=
aestronglyMeasurable_of_tendsto_ae _ fs_measurable h_lim
-- all functions we consider are integrable
have fs_int : ∀ n, Integrable (fs n) μ := fun n =>
bound_integrable.mono' (fs_measurable n) (h_bound _)
have f_int : Integrable f μ :=
⟨f_measurable,
hasFiniteIntegral_of_dominated_convergence bound_integrable.hasFiniteIntegral h_bound
h_lim⟩
-- it suffices to prove the result for the corresponding L1 functions
suffices
Tendsto (fun n => L1.setToL1 hT ((fs_int n).toL1 (fs n))) atTop
(𝓝 (L1.setToL1 hT (f_int.toL1 f))) by
convert this with n
· exact setToFun_eq hT (fs_int n)
· exact setToFun_eq hT f_int
-- the convergence of setToL1 follows from the convergence of the L1 functions
refine L1.tendsto_setToL1 hT _ _ ?_
-- up to some rewriting, what we need to prove is `h_lim`
rw [tendsto_iff_norm_sub_tendsto_zero]
have lintegral_norm_tendsto_zero :
Tendsto (fun n => ENNReal.toReal <| ∫⁻ a, ENNReal.ofReal ‖fs n a - f a‖ ∂μ) atTop (𝓝 0) :=
(tendsto_toReal zero_ne_top).comp
(tendsto_lintegral_norm_of_dominated_convergence fs_measurable
bound_integrable.hasFiniteIntegral h_bound h_lim)
convert lintegral_norm_tendsto_zero with n
rw [L1.norm_def]
congr 1
refine lintegral_congr_ae ?_
rw [← Integrable.toL1_sub]
refine ((fs_int n).sub f_int).coeFn_toL1.mono fun x hx => ?_
dsimp only
rw [hx, ofReal_norm_eq_enorm, Pi.sub_apply]
/-- Lebesgue dominated convergence theorem for filters with a countable basis -/
theorem tendsto_setToFun_filter_of_dominated_convergence (hT : DominatedFinMeasAdditive μ T C) {ι}
{l : Filter ι} [l.IsCountablyGenerated] {fs : ι → α → E} {f : α → E} (bound : α → ℝ)
(hfs_meas : ∀ᶠ n in l, AEStronglyMeasurable (fs n) μ)
(h_bound : ∀ᶠ n in l, ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => fs n a) l (𝓝 (f a))) :
Tendsto (fun n => setToFun μ T hT (fs n)) l (𝓝 <| setToFun μ T hT f) := by
rw [tendsto_iff_seq_tendsto]
intro x xl
have hxl : ∀ s ∈ l, ∃ a, ∀ b ≥ a, x b ∈ s := by rwa [tendsto_atTop'] at xl
have h :
{ x : ι | (fun n => AEStronglyMeasurable (fs n) μ) x } ∩
{ x : ι | (fun n => ∀ᵐ a ∂μ, ‖fs n a‖ ≤ bound a) x } ∈ l :=
inter_mem hfs_meas h_bound
obtain ⟨k, h⟩ := hxl _ h
rw [← tendsto_add_atTop_iff_nat k]
refine tendsto_setToFun_of_dominated_convergence hT bound ?_ bound_integrable ?_ ?_
· exact fun n => (h _ (self_le_add_left _ _)).1
· exact fun n => (h _ (self_le_add_left _ _)).2
· filter_upwards [h_lim]
refine fun a h_lin => @Tendsto.comp _ _ _ (fun n => x (n + k)) (fun n => fs n a) _ _ _ h_lin ?_
rwa [tendsto_add_atTop_iff_nat]
variable {X : Type*} [TopologicalSpace X] [FirstCountableTopology X]
theorem continuousWithinAt_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C)
{fs : X → α → E} {x₀ : X} {bound : α → ℝ} {s : Set X}
(hfs_meas : ∀ᶠ x in 𝓝[s] x₀, AEStronglyMeasurable (fs x) μ)
(h_bound : ∀ᶠ x in 𝓝[s] x₀, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, ContinuousWithinAt (fun x => fs x a) s x₀) :
ContinuousWithinAt (fun x => setToFun μ T hT (fs x)) s x₀ :=
tendsto_setToFun_filter_of_dominated_convergence hT bound ‹_› ‹_› ‹_› ‹_›
theorem continuousAt_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E}
{x₀ : X} {bound : α → ℝ} (hfs_meas : ∀ᶠ x in 𝓝 x₀, AEStronglyMeasurable (fs x) μ)
(h_bound : ∀ᶠ x in 𝓝 x₀, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, ContinuousAt (fun x => fs x a) x₀) :
ContinuousAt (fun x => setToFun μ T hT (fs x)) x₀ :=
tendsto_setToFun_filter_of_dominated_convergence hT bound ‹_› ‹_› ‹_› ‹_›
theorem continuousOn_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E}
{bound : α → ℝ} {s : Set X} (hfs_meas : ∀ x ∈ s, AEStronglyMeasurable (fs x) μ)
(h_bound : ∀ x ∈ s, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, ContinuousOn (fun x => fs x a) s) :
ContinuousOn (fun x => setToFun μ T hT (fs x)) s := by
intro x hx
refine continuousWithinAt_setToFun_of_dominated hT ?_ ?_ bound_integrable ?_
· filter_upwards [self_mem_nhdsWithin] with x hx using hfs_meas x hx
· filter_upwards [self_mem_nhdsWithin] with x hx using h_bound x hx
· filter_upwards [h_cont] with a ha using ha x hx
theorem continuous_setToFun_of_dominated (hT : DominatedFinMeasAdditive μ T C) {fs : X → α → E}
{bound : α → ℝ} (hfs_meas : ∀ x, AEStronglyMeasurable (fs x) μ)
(h_bound : ∀ x, ∀ᵐ a ∂μ, ‖fs x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, Continuous fun x => fs x a) : Continuous fun x => setToFun μ T hT (fs x) :=
continuous_iff_continuousAt.mpr fun _ =>
continuousAt_setToFun_of_dominated hT (Eventually.of_forall hfs_meas)
(Eventually.of_forall h_bound) ‹_› <|
h_cont.mono fun _ => Continuous.continuousAt
end Function
end MeasureTheory
| Mathlib/MeasureTheory/Integral/SetToL1.lean | 1,355 | 1,358 | |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.MeasureTheory.MeasurableSpace.Constructions
import Mathlib.Tactic.FunProp
/-!
# Measurable embeddings and equivalences
A measurable equivalence between measurable spaces is an equivalence
which respects the σ-algebras, that is, for which both directions of
the equivalence are measurable functions.
## Main definitions
* `MeasurableEmbedding`: a map `f : α → β` is called a *measurable embedding* if it is injective,
measurable, and sends measurable sets to measurable sets.
* `MeasurableEquiv`: an equivalence `α ≃ β` is a *measurable equivalence* if its forward and inverse
functions are measurable.
We prove a multitude of elementary lemmas about these, and one more substantial theorem:
* `MeasurableEmbedding.schroederBernstein`: the **measurable Schröder-Bernstein Theorem**: given
measurable embeddings `α → β` and `β → α`, we can find a measurable equivalence `α ≃ᵐ β`.
## Notation
* We write `α ≃ᵐ β` for measurable equivalences between the measurable spaces `α` and `β`.
This should not be confused with `≃ₘ` which is used for diffeomorphisms between manifolds.
## Tags
measurable equivalence, measurable embedding
-/
open Set Function Equiv MeasureTheory
universe uι
variable {α β γ δ δ' : Type*} {ι : Sort uι} {s t u : Set α}
/-- A map `f : α → β` is called a *measurable embedding* if it is injective, measurable, and sends
measurable sets to measurable sets. The latter assumption can be replaced with “`f` has measurable
inverse `g : Set.range f → α`”, see `MeasurableEmbedding.measurable_rangeSplitting`,
`MeasurableEmbedding.of_measurable_inverse_range`, and
`MeasurableEmbedding.of_measurable_inverse`.
One more interpretation: `f` is a measurable embedding if it defines a measurable equivalence to its
range and the range is a measurable set. One implication is formalized as
`MeasurableEmbedding.equivRange`; the other one follows from
`MeasurableEquiv.measurableEmbedding`, `MeasurableEmbedding.subtype_coe`, and
`MeasurableEmbedding.comp`. -/
structure MeasurableEmbedding [MeasurableSpace α] [MeasurableSpace β] (f : α → β) : Prop where
/-- A measurable embedding is injective. -/
protected injective : Injective f
/-- A measurable embedding is a measurable function. -/
protected measurable : Measurable f
/-- The image of a measurable set under a measurable embedding is a measurable set. -/
protected measurableSet_image' : ∀ ⦃s⦄, MeasurableSet s → MeasurableSet (f '' s)
attribute [fun_prop] MeasurableEmbedding.measurable
namespace MeasurableEmbedding
variable {mα : MeasurableSpace α} [MeasurableSpace β] [MeasurableSpace γ] {f : α → β} {g : β → γ}
theorem measurableSet_image (hf : MeasurableEmbedding f) :
MeasurableSet (f '' s) ↔ MeasurableSet s :=
⟨fun h => by simpa only [hf.injective.preimage_image] using hf.measurable h, fun h =>
hf.measurableSet_image' h⟩
theorem id : MeasurableEmbedding (id : α → α) :=
⟨injective_id, measurable_id, fun s hs => by rwa [image_id]⟩
theorem comp (hg : MeasurableEmbedding g) (hf : MeasurableEmbedding f) :
MeasurableEmbedding (g ∘ f) :=
⟨hg.injective.comp hf.injective, hg.measurable.comp hf.measurable, fun s hs => by
rwa [image_comp, hg.measurableSet_image, hf.measurableSet_image]⟩
theorem subtype_coe (hs : MeasurableSet s) : MeasurableEmbedding ((↑) : s → α) where
injective := Subtype.coe_injective
measurable := measurable_subtype_coe
measurableSet_image' := fun _ => MeasurableSet.subtype_image hs
theorem measurableSet_range (hf : MeasurableEmbedding f) : MeasurableSet (range f) := by
rw [← image_univ]
| exact hf.measurableSet_image' MeasurableSet.univ
theorem measurableSet_preimage (hf : MeasurableEmbedding f) {s : Set β} :
| Mathlib/MeasureTheory/MeasurableSpace/Embedding.lean | 90 | 92 |
/-
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
| Mathlib/Algebra/Lie/Weights/Basic.lean | 316 | 319 |
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Family
/-! # Ordinal exponential
In this file we define the power function and the logarithm function on ordinals. The two are
related by the lemma `Ordinal.opow_le_iff_le_log : b ^ c ≤ x ↔ c ≤ log b x` for nontrivial inputs
`b`, `c`.
-/
noncomputable section
open Function Set Equiv Order
open scoped Cardinal Ordinal
universe u v w
namespace Ordinal
/-- The ordinal exponential, defined by transfinite recursion.
We call this `opow` in theorems in order to disambiguate from other exponentials. -/
instance instPow : Pow Ordinal Ordinal :=
⟨fun a b ↦ if a = 0 then 1 - b else
limitRecOn b 1 (fun _ x ↦ x * a) fun o _ f ↦ ⨆ x : Iio o, f x.1 x.2⟩
private theorem opow_of_ne_zero {a b : Ordinal} (h : a ≠ 0) : a ^ b =
limitRecOn b 1 (fun _ x ↦ x * a) fun o _ f ↦ ⨆ x : Iio o, f x.1 x.2 :=
if_neg h
/-- `0 ^ a = 1` if `a = 0` and `0 ^ a = 0` otherwise. -/
theorem zero_opow' (a : Ordinal) : 0 ^ a = 1 - a :=
if_pos rfl
theorem zero_opow_le (a : Ordinal) : (0 : Ordinal) ^ a ≤ 1 := by
rw [zero_opow']
exact sub_le_self 1 a
| Mathlib/SetTheory/Ordinal/Exponential.lean | 42 | 42 | |
/-
Copyright (c) 2022 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.CategoryTheory.EpiMono
/-!
# Balanced categories
A category is called balanced if any morphism that is both monic and epic is an isomorphism.
Balanced categories arise frequently. For example, categories in which every monomorphism
(or epimorphism) is strong are balanced. Examples of this are abelian categories and toposes, such
as the category of types.
-/
universe v u
namespace CategoryTheory
variable {C : Type u} [Category.{v} C]
section
variable (C)
/-- A category is called balanced if any morphism that is both monic and epic is an isomorphism. -/
class Balanced : Prop where
isIso_of_mono_of_epi : ∀ {X Y : C} (f : X ⟶ Y) [Mono f] [Epi f], IsIso f
end
theorem isIso_of_mono_of_epi [Balanced C] {X Y : C} (f : X ⟶ Y) [Mono f] [Epi f] : IsIso f :=
Balanced.isIso_of_mono_of_epi _
theorem isIso_iff_mono_and_epi [Balanced C] {X Y : C} (f : X ⟶ Y) : IsIso f ↔ Mono f ∧ Epi f :=
⟨fun _ => ⟨inferInstance, inferInstance⟩, fun ⟨_, _⟩ => isIso_of_mono_of_epi _⟩
section
attribute [local instance] isIso_of_mono_of_epi
instance balanced_opposite [Balanced C] : Balanced Cᵒᵖ :=
{ isIso_of_mono_of_epi := fun f fmono fepi => by
rw [← Quiver.Hom.op_unop f]
exact isIso_of_op _ }
| end
end CategoryTheory
| Mathlib/CategoryTheory/Balanced.lean | 51 | 54 |
/-
Copyright (c) 2024 Brendan Murphy. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Brendan Murphy
-/
import Mathlib.RingTheory.Regular.IsSMulRegular
import Mathlib.RingTheory.Artinian.Module
import Mathlib.RingTheory.Nakayama
import Mathlib.Algebra.Equiv.TransferInstance
import Mathlib.RingTheory.LocalRing.MaximalIdeal.Basic
import Mathlib.RingTheory.Noetherian.Basic
/-!
# Regular sequences and weakly regular sequences
The notion of a regular sequence is fundamental in commutative algebra.
Properties of regular sequences encode information about singularities of a
ring and regularity of a sequence can be tested homologically.
However the notion of a regular sequence is only really sensible for Noetherian local rings.
TODO: Koszul regular sequences, H_1-regular sequences, quasi-regular sequences, depth.
## Tags
module, regular element, regular sequence, commutative algebra
-/
universe u v
open scoped Pointwise
variable {R S M M₂ M₃ M₄ : Type*}
namespace Ideal
variable [Semiring R] [Semiring S]
/-- The ideal generated by a list of elements. -/
abbrev ofList (rs : List R) := span { r | r ∈ rs }
@[simp] lemma ofList_nil : (ofList [] : Ideal R) = ⊥ :=
have : { r | r ∈ [] } = ∅ := Set.eq_empty_of_forall_not_mem (fun _ => List.not_mem_nil)
Eq.trans (congrArg span this) span_empty
@[simp] lemma ofList_append (rs₁ rs₂ : List R) :
ofList (rs₁ ++ rs₂) = ofList rs₁ ⊔ ofList rs₂ :=
have : { r | r ∈ rs₁ ++ rs₂ } = _ := Set.ext (fun _ => List.mem_append)
Eq.trans (congrArg span this) (span_union _ _)
lemma ofList_singleton (r : R) : ofList [r] = span {r} :=
congrArg span (Set.ext fun _ => List.mem_singleton)
@[simp] lemma ofList_cons (r : R) (rs : List R) :
ofList (r::rs) = span {r} ⊔ ofList rs :=
Eq.trans (ofList_append [r] rs) (congrArg (· ⊔ _) (ofList_singleton r))
@[simp] lemma map_ofList (f : R →+* S) (rs : List R) :
map f (ofList rs) = ofList (rs.map f) :=
Eq.trans (map_span f { r | r ∈ rs }) <| congrArg span <|
Set.ext (fun _ => List.mem_map.symm)
lemma ofList_cons_smul {R} [CommSemiring R] (r : R) (rs : List R) {M}
[AddCommMonoid M] [Module R M] (N : Submodule R M) :
ofList (r :: rs) • N = r • N ⊔ ofList rs • N := by
rw [ofList_cons, Submodule.sup_smul, Submodule.ideal_span_singleton_smul]
end Ideal
namespace Submodule
lemma smul_top_le_comap_smul_top [Semiring R] [AddCommMonoid M]
[AddCommMonoid M₂] [Module R M] [Module R M₂] (I : Ideal R)
(f : M →ₗ[R] M₂) : I • ⊤ ≤ comap f (I • ⊤) :=
map_le_iff_le_comap.mp <| le_of_eq_of_le (map_smul'' _ _ _) <|
smul_mono_right _ le_top
variable (M) [CommRing R] [AddCommGroup M] [AddCommGroup M₂]
[Module R M] [Module R M₂] (r : R) (rs : List R)
/-- The equivalence between M ⧸ (r₀, r₁, …, rₙ)M and (M ⧸ r₀M) ⧸ (r₁, …, rₙ) (M ⧸ r₀M). -/
def quotOfListConsSMulTopEquivQuotSMulTopInner :
(M ⧸ (Ideal.ofList (r :: rs) • ⊤ : Submodule R M)) ≃ₗ[R]
QuotSMulTop r M ⧸ (Ideal.ofList rs • ⊤ : Submodule R (QuotSMulTop r M)) :=
quotEquivOfEq _ _ (Ideal.ofList_cons_smul r rs ⊤) ≪≫ₗ
(quotientQuotientEquivQuotientSup (r • ⊤) (Ideal.ofList rs • ⊤)).symm ≪≫ₗ
quotEquivOfEq _ _ (by rw [map_smul'', map_top, range_mkQ])
/-- The equivalence between M ⧸ (r₀, r₁, …, rₙ)M and (M ⧸ (r₁, …, rₙ)) ⧸ r₀ (M ⧸ (r₁, …, rₙ)). -/
def quotOfListConsSMulTopEquivQuotSMulTopOuter :
(M ⧸ (Ideal.ofList (r :: rs) • ⊤ : Submodule R M)) ≃ₗ[R]
QuotSMulTop r (M ⧸ (Ideal.ofList rs • ⊤ : Submodule R M)) :=
quotEquivOfEq _ _ (Eq.trans (Ideal.ofList_cons_smul r rs ⊤) (sup_comm _ _)) ≪≫ₗ
(quotientQuotientEquivQuotientSup (Ideal.ofList rs • ⊤) (r • ⊤)).symm ≪≫ₗ
quotEquivOfEq _ _ (by rw [map_pointwise_smul, map_top, range_mkQ])
variable {M}
lemma quotOfListConsSMulTopEquivQuotSMulTopInner_naturality (f : M →ₗ[R] M₂) :
(quotOfListConsSMulTopEquivQuotSMulTopInner M₂ r rs).toLinearMap ∘ₗ
mapQ _ _ _ (smul_top_le_comap_smul_top (Ideal.ofList (r :: rs)) f) =
mapQ _ _ _ (smul_top_le_comap_smul_top _ (QuotSMulTop.map r f)) ∘ₗ
(quotOfListConsSMulTopEquivQuotSMulTopInner M r rs).toLinearMap :=
quot_hom_ext _ _ _ fun _ => rfl
lemma top_eq_ofList_cons_smul_iff :
(⊤ : Submodule R M) = Ideal.ofList (r :: rs) • ⊤ ↔
(⊤ : Submodule R (QuotSMulTop r M)) = Ideal.ofList rs • ⊤ := by
conv => congr <;> rw [eq_comm, ← subsingleton_quotient_iff_eq_top]
exact (quotOfListConsSMulTopEquivQuotSMulTopInner M r rs).toEquiv.subsingleton_congr
end Submodule
namespace RingTheory.Sequence
open scoped TensorProduct List
open Function Submodule QuotSMulTop
variable (S M)
section Definitions
/-
In theory, regularity of `rs : List α` on `M` makes sense as soon as
`[Monoid α]`, `[AddCommGroup M]`, and `[DistribMulAction α M]`.
Instead of `Ideal.ofList (rs.take i) • (⊤ : Submodule R M)` we use
`⨆ (j : Fin i), rs[j] • (⊤ : AddSubgroup M)`.
However it's not clear that this is a useful generalization.
If we add the assumption `[SMulCommClass α α M]` this is essentially the same
as focusing on the commutative ring case, by passing to the monoid ring
`ℤ[abelianization of α]`.
-/
variable [CommRing R] [AddCommGroup M] [Module R M]
open Ideal
/-- A sequence `[r₁, …, rₙ]` is weakly regular on `M` iff `rᵢ` is regular on
`M⧸(r₁, …, rᵢ₋₁)M` for all `1 ≤ i ≤ n`. -/
@[mk_iff]
structure IsWeaklyRegular (rs : List R) : Prop where
regular_mod_prev : ∀ i (h : i < rs.length),
IsSMulRegular (M ⧸ (ofList (rs.take i) • ⊤ : Submodule R M)) rs[i]
lemma isWeaklyRegular_iff_Fin (rs : List R) :
IsWeaklyRegular M rs ↔ ∀ (i : Fin rs.length),
IsSMulRegular (M ⧸ (ofList (rs.take i) • ⊤ : Submodule R M)) rs[i] :=
Iff.trans (isWeaklyRegular_iff M rs) (Iff.symm Fin.forall_iff)
/-- A weakly regular sequence `rs` on `M` is regular if also `M/rsM ≠ 0`. -/
@[mk_iff]
structure IsRegular (rs : List R) : Prop extends IsWeaklyRegular M rs where
top_ne_smul : (⊤ : Submodule R M) ≠ Ideal.ofList rs • ⊤
end Definitions
section Congr
variable {S M} [CommRing R] [CommRing S] [AddCommGroup M] [AddCommGroup M₂]
[Module R M] [Module S M₂]
{σ : R →+* S} {σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
open DistribMulAction AddSubgroup in
private lemma _root_.AddHom.map_smul_top_toAddSubgroup_of_surjective
{f : M →+ M₂} {as : List R} {bs : List S} (hf : Function.Surjective f)
(h : List.Forall₂ (fun r s => ∀ x, f (r • x) = s • f x) as bs) :
(Ideal.ofList as • ⊤ : Submodule R M).toAddSubgroup.map f =
(Ideal.ofList bs • ⊤ : Submodule S M₂).toAddSubgroup := by
induction h with
| nil =>
convert AddSubgroup.map_bot f using 1 <;>
rw [Ideal.ofList_nil, bot_smul, bot_toAddSubgroup]
| @cons r s _ _ h _ ih =>
conv => congr <;> rw [Ideal.ofList_cons, sup_smul, sup_toAddSubgroup,
ideal_span_singleton_smul, pointwise_smul_toAddSubgroup,
top_toAddSubgroup, pointwise_smul_def]
apply DFunLike.ext (f.comp (toAddMonoidEnd R M r))
((toAddMonoidEnd S M₂ s).comp f) at h
rw [AddSubgroup.map_sup, ih, map_map, h, ← map_map,
map_top_of_surjective f hf]
lemma _root_.AddEquiv.isWeaklyRegular_congr {e : M ≃+ M₂} {as bs}
(h : List.Forall₂ (fun (r : R) (s : S) => ∀ x, e (r • x) = s • e x) as bs) :
IsWeaklyRegular M as ↔ IsWeaklyRegular M₂ bs := by
conv => congr <;> rw [isWeaklyRegular_iff_Fin]
let e' i : (M ⧸ (Ideal.ofList (as.take i) • ⊤ : Submodule R M)) ≃+
M₂ ⧸ (Ideal.ofList (bs.take i) • ⊤ : Submodule S M₂) :=
QuotientAddGroup.congr _ _ e <|
AddHom.map_smul_top_toAddSubgroup_of_surjective e.surjective <|
List.forall₂_take i h
refine (finCongr h.length_eq).forall_congr @fun _ => (e' _).isSMulRegular_congr ?_
exact (mkQ_surjective _).forall.mpr fun _ => congrArg (mkQ _) (h.get _ _ _)
lemma _root_.LinearEquiv.isWeaklyRegular_congr' (e : M ≃ₛₗ[σ] M₂) (rs : List R) :
IsWeaklyRegular M rs ↔ IsWeaklyRegular M₂ (rs.map σ) :=
e.toAddEquiv.isWeaklyRegular_congr <| List.forall₂_map_right_iff.mpr <|
List.forall₂_same.mpr fun r _ x => e.map_smul' r x
lemma _root_.LinearEquiv.isWeaklyRegular_congr [Module R M₂] (e : M ≃ₗ[R] M₂) (rs : List R) :
IsWeaklyRegular M rs ↔ IsWeaklyRegular M₂ rs :=
Iff.trans (e.isWeaklyRegular_congr' rs) <| iff_of_eq <| congrArg _ rs.map_id
lemma _root_.AddEquiv.isRegular_congr {e : M ≃+ M₂} {as bs}
(h : List.Forall₂ (fun (r : R) (s : S) => ∀ x, e (r • x) = s • e x) as bs) :
IsRegular M as ↔ IsRegular M₂ bs := by
conv => congr <;> rw [isRegular_iff, ne_eq, eq_comm,
← subsingleton_quotient_iff_eq_top]
let e' := QuotientAddGroup.congr _ _ e <|
AddHom.map_smul_top_toAddSubgroup_of_surjective e.surjective h
exact and_congr (e.isWeaklyRegular_congr h) e'.subsingleton_congr.not
lemma _root_.LinearEquiv.isRegular_congr' (e : M ≃ₛₗ[σ] M₂) (rs : List R) :
IsRegular M rs ↔ IsRegular M₂ (rs.map σ) :=
e.toAddEquiv.isRegular_congr <| List.forall₂_map_right_iff.mpr <|
List.forall₂_same.mpr fun r _ x => e.map_smul' r x
lemma _root_.LinearEquiv.isRegular_congr [Module R M₂] (e : M ≃ₗ[R] M₂) (rs : List R) :
IsRegular M rs ↔ IsRegular M₂ rs :=
Iff.trans (e.isRegular_congr' rs) <| iff_of_eq <| congrArg _ rs.map_id
end Congr
lemma isWeaklyRegular_map_algebraMap_iff [CommRing R] [CommRing S]
[Algebra R S] [AddCommGroup M] [Module R M] [Module S M]
[IsScalarTower R S M] (rs : List R) :
IsWeaklyRegular M (rs.map (algebraMap R S)) ↔ IsWeaklyRegular M rs :=
(AddEquiv.refl M).isWeaklyRegular_congr <| List.forall₂_map_left_iff.mpr <|
List.forall₂_same.mpr fun r _ => algebraMap_smul S r
variable [CommRing R] [AddCommGroup M] [AddCommGroup M₂] [AddCommGroup M₃]
[AddCommGroup M₄] [Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
@[simp]
lemma isWeaklyRegular_cons_iff (r : R) (rs : List R) :
IsWeaklyRegular M (r :: rs) ↔
IsSMulRegular M r ∧ IsWeaklyRegular (QuotSMulTop r M) rs :=
have := Eq.trans (congrArg (· • ⊤) Ideal.ofList_nil) (bot_smul ⊤)
let e i := quotOfListConsSMulTopEquivQuotSMulTopInner M r (rs.take i)
Iff.trans (isWeaklyRegular_iff_Fin _ _) <| Iff.trans Fin.forall_iff_succ <|
and_congr ((quotEquivOfEqBot _ this).isSMulRegular_congr r) <|
Iff.trans (forall_congr' fun i => (e i).isSMulRegular_congr (rs.get i))
(isWeaklyRegular_iff_Fin _ _).symm
lemma isWeaklyRegular_cons_iff' (r : R) (rs : List R) :
IsWeaklyRegular M (r :: rs) ↔
IsSMulRegular M r ∧
IsWeaklyRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) :=
Iff.trans (isWeaklyRegular_cons_iff M r rs) <| and_congr_right' <|
Iff.symm <| isWeaklyRegular_map_algebraMap_iff (R ⧸ Ideal.span {r}) _ rs
@[simp]
lemma isRegular_cons_iff (r : R) (rs : List R) :
IsRegular M (r :: rs) ↔
IsSMulRegular M r ∧ IsRegular (QuotSMulTop r M) rs := by
rw [isRegular_iff, isRegular_iff, isWeaklyRegular_cons_iff M r rs,
| ne_eq, top_eq_ofList_cons_smul_iff, and_assoc]
lemma isRegular_cons_iff' (r : R) (rs : List R) :
IsRegular M (r :: rs) ↔
IsSMulRegular M r ∧ IsRegular (QuotSMulTop r M)
(rs.map (Ideal.Quotient.mk (Ideal.span {r}))) := by
conv => congr <;> rw [isRegular_iff, ne_eq]
rw [isWeaklyRegular_cons_iff', ← restrictScalars_inj R (R ⧸ _),
| Mathlib/RingTheory/Regular/RegularSequence.lean | 255 | 262 |
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Mario Carneiro
-/
import Mathlib.Algebra.Field.IsField
import Mathlib.Data.Fin.VecNotation
import Mathlib.Data.Nat.Choose.Sum
import Mathlib.LinearAlgebra.Finsupp.LinearCombination
import Mathlib.RingTheory.Ideal.Maximal
import Mathlib.Tactic.FinCases
/-!
# Ideals over a ring
This file contains an assortment of definitions and results for `Ideal R`,
the type of (left) ideals over a ring `R`.
Note that over commutative rings, left ideals and two-sided ideals are equivalent.
## Implementation notes
`Ideal R` is implemented using `Submodule R R`, where `•` is interpreted as `*`.
## TODO
Support right ideals, and two-sided ideals over non-commutative rings.
-/
variable {ι α β F : Type*}
open Set Function
open Pointwise
section Semiring
namespace Ideal
variable {α : ι → Type*} [Π i, Semiring (α i)] (I : Π i, Ideal (α i))
section Pi
/-- `Πᵢ Iᵢ` as an ideal of `Πᵢ Rᵢ`. -/
def pi : Ideal (Π i, α i) where
carrier := { x | ∀ i, x i ∈ I i }
zero_mem' i := (I i).zero_mem
add_mem' ha hb i := (I i).add_mem (ha i) (hb i)
smul_mem' a _b hb i := (I i).mul_mem_left (a i) (hb i)
theorem mem_pi (x : Π i, α i) : x ∈ pi I ↔ ∀ i, x i ∈ I i :=
Iff.rfl
instance (priority := low) [∀ i, (I i).IsTwoSided] : (pi I).IsTwoSided :=
⟨fun _b hb i ↦ mul_mem_right _ _ (hb i)⟩
end Pi
section Commute
variable {α : Type*} [Semiring α] (I : Ideal α) {a b : α}
theorem add_pow_mem_of_pow_mem_of_le_of_commute {m n k : ℕ}
(ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hk : m + n ≤ k + 1)
(hab : Commute a b) :
(a + b) ^ k ∈ I := by
simp_rw [hab.add_pow, ← Nat.cast_comm]
apply I.sum_mem
intro c _
apply mul_mem_left
by_cases h : m ≤ c
· rw [hab.pow_pow]
exact I.mul_mem_left _ (I.pow_mem_of_pow_mem ha h)
· refine I.mul_mem_left _ (I.pow_mem_of_pow_mem hb ?_)
omega
theorem add_pow_add_pred_mem_of_pow_mem_of_commute {m n : ℕ}
(ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hab : Commute a b) :
(a + b) ^ (m + n - 1) ∈ I :=
I.add_pow_mem_of_pow_mem_of_le_of_commute ha hb (by rw [← Nat.sub_le_iff_le_add]) hab
end Commute
end Ideal
end Semiring
section CommSemiring
variable {a b : α}
-- A separate namespace definition is needed because the variables were historically in a different
-- order.
namespace Ideal
variable [CommSemiring α] (I : Ideal α)
theorem add_pow_mem_of_pow_mem_of_le {m n k : ℕ}
(ha : a ^ m ∈ I) (hb : b ^ n ∈ I) (hk : m + n ≤ k + 1) :
(a + b) ^ k ∈ I :=
I.add_pow_mem_of_pow_mem_of_le_of_commute ha hb hk (Commute.all ..)
theorem add_pow_add_pred_mem_of_pow_mem {m n : ℕ}
(ha : a ^ m ∈ I) (hb : b ^ n ∈ I) :
(a + b) ^ (m + n - 1) ∈ I :=
I.add_pow_add_pred_mem_of_pow_mem_of_commute ha hb (Commute.all ..)
theorem pow_multiset_sum_mem_span_pow [DecidableEq α] (s : Multiset α) (n : ℕ) :
s.sum ^ (Multiset.card s * n + 1) ∈
span ((s.map fun (x : α) ↦ x ^ (n + 1)).toFinset : Set α) := by
induction' s using Multiset.induction_on with a s hs
· simp
simp only [Finset.coe_insert, Multiset.map_cons, Multiset.toFinset_cons, Multiset.sum_cons,
Multiset.card_cons, add_pow]
refine Submodule.sum_mem _ ?_
intro c _hc
rw [mem_span_insert]
by_cases h : n + 1 ≤ c
· refine ⟨a ^ (c - (n + 1)) * s.sum ^ ((Multiset.card s + 1) * n + 1 - c) *
((Multiset.card s + 1) * n + 1).choose c, 0, Submodule.zero_mem _, ?_⟩
rw [mul_comm _ (a ^ (n + 1))]
simp_rw [← mul_assoc]
rw [← pow_add, add_zero, add_tsub_cancel_of_le h]
· use 0
simp_rw [zero_mul, zero_add]
refine ⟨_, ?_, rfl⟩
replace h : c ≤ n := Nat.lt_succ_iff.mp (not_le.mp h)
have : (Multiset.card s + 1) * n + 1 - c = Multiset.card s * n + 1 + (n - c) := by
rw [add_mul, one_mul, add_assoc, add_comm n 1, ← add_assoc, add_tsub_assoc_of_le h]
rw [this, pow_add]
simp_rw [mul_assoc, mul_comm (s.sum ^ (Multiset.card s * n + 1)), ← mul_assoc]
exact mul_mem_left _ _ hs
theorem sum_pow_mem_span_pow {ι} (s : Finset ι) (f : ι → α) (n : ℕ) :
(∑ i ∈ s, f i) ^ (s.card * n + 1) ∈ span ((fun i => f i ^ (n + 1)) '' s) := by
classical
simpa only [Multiset.card_map, Multiset.map_map, comp_apply, Multiset.toFinset_map,
Finset.coe_image, Finset.val_toFinset] using pow_multiset_sum_mem_span_pow (s.1.map f) n
theorem span_pow_eq_top (s : Set α) (hs : span s = ⊤) (n : ℕ) :
span ((fun (x : α) => x ^ n) '' s) = ⊤ := by
rw [eq_top_iff_one]
rcases n with - | n
· obtain rfl | ⟨x, hx⟩ := eq_empty_or_nonempty s
· rw [Set.image_empty, hs]
trivial
· exact subset_span ⟨_, hx, pow_zero _⟩
rw [eq_top_iff_one, span, Finsupp.mem_span_iff_linearCombination] at hs
rcases hs with ⟨f, hf⟩
have hf : (f.support.sum fun a => f a * a) = 1 := hf -- Porting note: was `change ... at hf`
have := sum_pow_mem_span_pow f.support (fun a => f a * a) n
rw [hf, one_pow] at this
refine span_le.mpr ?_ this
rintro _ hx
simp_rw [Set.mem_image] at hx
rcases hx with ⟨x, _, rfl⟩
have : span ({(x : α) ^ (n + 1)} : Set α) ≤ span ((fun x : α => x ^ (n + 1)) '' s) := by
rw [span_le, Set.singleton_subset_iff]
exact subset_span ⟨x, x.prop, rfl⟩
refine this ?_
rw [mul_pow, mem_span_singleton]
exact ⟨f x ^ (n + 1), mul_comm _ _⟩
theorem span_range_pow_eq_top (s : Set α) (hs : span s = ⊤) (n : s → ℕ) :
span (Set.range fun x ↦ x.1 ^ n x) = ⊤ := by
have ⟨t, hts, mem⟩ := Submodule.mem_span_finite_of_mem_span ((eq_top_iff_one _).mp hs)
refine top_unique ((span_pow_eq_top _ ((eq_top_iff_one _).mpr mem) <|
t.attach.sup fun x ↦ n ⟨x, hts x.2⟩).ge.trans <| span_le.mpr ?_)
rintro _ ⟨x, hxt, rfl⟩
rw [← Nat.sub_add_cancel (Finset.le_sup <| t.mem_attach ⟨x, hxt⟩)]
simp_rw [pow_add]
exact mul_mem_left _ _ (subset_span ⟨_, rfl⟩)
theorem prod_mem {ι : Type*} {f : ι → α} {s : Finset ι}
(I : Ideal α) {i : ι} (hi : i ∈ s) (hfi : f i ∈ I) :
∏ i ∈ s, f i ∈ I := by
classical
rw [Finset.prod_eq_prod_diff_singleton_mul hi]
exact Ideal.mul_mem_left _ _ hfi
end Ideal
end CommSemiring
section DivisionSemiring
variable {K : Type*} [DivisionSemiring K] (I : Ideal K)
namespace Ideal
variable (K) in
/-- A bijection between (left) ideals of a division ring and `{0, 1}`, sending `⊥` to `0`
and `⊤` to `1`. -/
def equivFinTwo [DecidableEq (Ideal K)] : Ideal K ≃ Fin 2 where
toFun := fun I ↦ if I = ⊥ then 0 else 1
invFun := ![⊥, ⊤]
left_inv := fun I ↦ by rcases eq_bot_or_top I with rfl | rfl <;> simp
right_inv := fun i ↦ by fin_cases i <;> simp
instance : Finite (Ideal K) := let _i := Classical.decEq (Ideal K); ⟨equivFinTwo K⟩
/-- Ideals of a `DivisionSemiring` are a simple order. Thanks to the way abbreviations work,
this automatically gives an `IsSimpleModule K` instance. -/
instance isSimpleOrder : IsSimpleOrder (Ideal K) :=
⟨eq_bot_or_top⟩
end Ideal
end DivisionSemiring
-- TODO: consider moving the lemmas below out of the `Ring` namespace since they are
-- about `CommSemiring`s.
namespace Ring
variable {R : Type*} [CommSemiring R]
theorem exists_not_isUnit_of_not_isField [Nontrivial R] (hf : ¬IsField R) :
∃ (x : R) (_hx : x ≠ (0 : R)), ¬IsUnit x := by
have : ¬_ := fun h => hf ⟨exists_pair_ne R, mul_comm, h⟩
simp_rw [isUnit_iff_exists_inv]
push_neg at this ⊢
obtain ⟨x, hx, not_unit⟩ := this
exact ⟨x, hx, not_unit⟩
theorem not_isField_iff_exists_ideal_bot_lt_and_lt_top [Nontrivial R] :
¬IsField R ↔ ∃ I : Ideal R, ⊥ < I ∧ I < ⊤ := by
constructor
· intro h
obtain ⟨x, nz, nu⟩ := exists_not_isUnit_of_not_isField h
use Ideal.span {x}
rw [bot_lt_iff_ne_bot, lt_top_iff_ne_top]
exact ⟨mt Ideal.span_singleton_eq_bot.mp nz, mt Ideal.span_singleton_eq_top.mp nu⟩
· rintro ⟨I, bot_lt, lt_top⟩ hf
obtain ⟨x, mem, ne_zero⟩ := SetLike.exists_of_lt bot_lt
rw [Submodule.mem_bot] at ne_zero
obtain ⟨y, hy⟩ := hf.mul_inv_cancel ne_zero
rw [lt_top_iff_ne_top, Ne, Ideal.eq_top_iff_one, ← hy] at lt_top
exact lt_top (I.mul_mem_right _ mem)
theorem not_isField_iff_exists_prime [Nontrivial R] :
¬IsField R ↔ ∃ p : Ideal R, p ≠ ⊥ ∧ p.IsPrime :=
not_isField_iff_exists_ideal_bot_lt_and_lt_top.trans
⟨fun ⟨I, bot_lt, lt_top⟩ =>
let ⟨p, hp, le_p⟩ := I.exists_le_maximal (lt_top_iff_ne_top.mp lt_top)
⟨p, bot_lt_iff_ne_bot.mp (lt_of_lt_of_le bot_lt le_p), hp.isPrime⟩,
fun ⟨p, ne_bot, Prime⟩ => ⟨p, bot_lt_iff_ne_bot.mpr ne_bot, lt_top_iff_ne_top.mpr Prime.1⟩⟩
/-- Also see `Ideal.isSimpleOrder` for the forward direction as an instance when `R` is a
division (semi)ring.
This result actually holds for all division semirings, but we lack the predicate to state it. -/
theorem isField_iff_isSimpleOrder_ideal : IsField R ↔ IsSimpleOrder (Ideal R) := by
cases subsingleton_or_nontrivial R
· exact
⟨fun h => (not_isField_of_subsingleton _ h).elim, fun h =>
(false_of_nontrivial_of_subsingleton <| Ideal R).elim⟩
rw [← not_iff_not, Ring.not_isField_iff_exists_ideal_bot_lt_and_lt_top, ← not_iff_not]
push_neg
simp_rw [lt_top_iff_ne_top, bot_lt_iff_ne_bot, ← or_iff_not_imp_left, not_ne_iff]
exact ⟨fun h => ⟨h⟩, fun h => h.2⟩
/-- When a ring is not a field, the maximal ideals are nontrivial. -/
theorem ne_bot_of_isMaximal_of_not_isField [Nontrivial R] {M : Ideal R} (max : M.IsMaximal)
(not_field : ¬IsField R) : M ≠ ⊥ := by
rintro h
rw [h] at max
rcases max with ⟨⟨_h1, h2⟩⟩
obtain ⟨I, hIbot, hItop⟩ := not_isField_iff_exists_ideal_bot_lt_and_lt_top.mp not_field
exact ne_of_lt hItop (h2 I hIbot)
end Ring
namespace Ideal
variable {R : Type*} [CommSemiring R] [Nontrivial R]
theorem bot_lt_of_maximal (M : Ideal R) [hm : M.IsMaximal] (non_field : ¬IsField R) : ⊥ < M := by
rcases Ring.not_isField_iff_exists_ideal_bot_lt_and_lt_top.1 non_field with ⟨I, Ibot, Itop⟩
constructor; · simp
intro mle
apply lt_irrefl (⊤ : Ideal R)
have : M = ⊥ := eq_bot_iff.mpr mle
rw [← this] at Ibot
rwa [hm.1.2 I Ibot] at Itop
end Ideal
| Mathlib/RingTheory/Ideal/Basic.lean | 608 | 612 | |
/-
Copyright (c) 2023 Alex Keizer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex Keizer
-/
import Mathlib.Data.Vector.Basic
import Mathlib.Data.Vector.Snoc
/-!
This file establishes a set of normalization lemmas for `map`/`mapAccumr` operations on vectors
-/
variable {α β γ ζ σ σ₁ σ₂ φ : Type*} {n : ℕ} {s : σ} {s₁ : σ₁} {s₂ : σ₂}
namespace List
namespace Vector
/-!
## Fold nested `mapAccumr`s into one
-/
section Fold
section Unary
variable (xs : Vector α n) (f₁ : β → σ₁ → σ₁ × γ) (f₂ : α → σ₂ → σ₂ × β)
@[simp]
theorem mapAccumr_mapAccumr :
mapAccumr f₁ (mapAccumr f₂ xs s₂).snd s₁
= let m := (mapAccumr (fun x s =>
let r₂ := f₂ x s.snd
let r₁ := f₁ r₂.snd s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs (s₁, s₂))
(m.fst.fst, m.snd) := by
induction xs using Vector.revInductionOn generalizing s₁ s₂ <;> simp_all
@[simp]
theorem mapAccumr_map {s : σ₁} (f₂ : α → β) :
(mapAccumr f₁ (map f₂ xs) s) = (mapAccumr (fun x s => f₁ (f₂ x) s) xs s) := by
induction xs using Vector.revInductionOn generalizing s <;> simp_all
@[simp]
theorem map_mapAccumr {s : σ₂} (f₁ : β → γ) :
(map f₁ (mapAccumr f₂ xs s).snd) = (mapAccumr (fun x s =>
let r := (f₂ x s); (r.fst, f₁ r.snd)
) xs s).snd := by
induction xs using Vector.revInductionOn generalizing s <;> simp_all
@[simp]
theorem map_map (f₁ : β → γ) (f₂ : α → β) :
map f₁ (map f₂ xs) = map (fun x => f₁ <| f₂ x) xs := by
induction xs <;> simp_all
theorem map_pmap {p : α → Prop} (f₁ : β → γ) (f₂ : (a : α) → p a → β) (H : ∀ x ∈ xs.toList, p x):
map f₁ (pmap f₂ xs H) = pmap (fun x hx => f₁ <| f₂ x hx) xs H := by
induction xs <;> simp_all
theorem pmap_map {p : β → Prop} (f₁ : (b : β) → p b → γ) (f₂ : α → β)
(H : ∀ x ∈ (xs.map f₂).toList, p x):
pmap f₁ (map f₂ xs) H = pmap (fun x hx => f₁ (f₂ x) hx) xs (by simpa using H) := by
induction xs <;> simp_all
end Unary
section Binary
variable (xs : Vector α n) (ys : Vector β n)
@[simp]
theorem mapAccumr₂_mapAccumr_left (f₁ : γ → β → σ₁ → σ₁ × ζ) (f₂ : α → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ (mapAccumr f₂ xs s₂).snd ys s₁)
= let m := (mapAccumr₂ (fun x y s =>
let r₂ := f₂ x s.snd
let r₁ := f₁ r₂.snd y s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs ys (s₁, s₂))
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem map₂_map_left (f₁ : γ → β → ζ) (f₂ : α → γ) :
map₂ f₁ (map f₂ xs) ys = map₂ (fun x y => f₁ (f₂ x) y) xs ys := by
induction xs, ys using Vector.revInductionOn₂ <;> simp_all
@[simp]
theorem mapAccumr₂_mapAccumr_right (f₁ : α → γ → σ₁ → σ₁ × ζ) (f₂ : β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ xs (mapAccumr f₂ ys s₂).snd s₁)
= let m := (mapAccumr₂ (fun x y s =>
let r₂ := f₂ y s.snd
let r₁ := f₁ x r₂.snd s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs ys (s₁, s₂))
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem map₂_map_right (f₁ : α → γ → ζ) (f₂ : β → γ) :
map₂ f₁ xs (map f₂ ys) = map₂ (fun x y => f₁ x (f₂ y)) xs ys := by
induction xs, ys using Vector.revInductionOn₂ <;> simp_all
@[simp]
theorem mapAccumr_mapAccumr₂ (f₁ : γ → σ₁ → σ₁ × ζ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr f₁ (mapAccumr₂ f₂ xs ys s₂).snd s₁)
= let m := mapAccumr₂ (fun x y s =>
let r₂ := f₂ x y s.snd
let r₁ := f₁ r₂.snd s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem map_map₂ (f₁ : γ → ζ) (f₂ : α → β → γ) :
map f₁ (map₂ f₂ xs ys) = map₂ (fun x y => f₁ <| f₂ x y) xs ys := by
induction xs, ys using Vector.revInductionOn₂ <;> simp_all
@[simp]
theorem mapAccumr₂_mapAccumr₂_left_left (f₁ : γ → α → σ₁ → σ₁ × φ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ (mapAccumr₂ f₂ xs ys s₂).snd xs s₁)
= let m := mapAccumr₂ (fun x y (s₁, s₂) =>
let r₂ := f₂ x y s₂
let r₁ := f₁ r₂.snd x s₁
((r₁.fst, r₂.fst), r₁.snd)
)
xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem mapAccumr₂_mapAccumr₂_left_right
(f₁ : γ → β → σ₁ → σ₁ × φ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ (mapAccumr₂ f₂ xs ys s₂).snd ys s₁)
= let m := mapAccumr₂ (fun x y (s₁, s₂) =>
let r₂ := f₂ x y s₂
let r₁ := f₁ r₂.snd y s₁
((r₁.fst, r₂.fst), r₁.snd)
)
xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem mapAccumr₂_mapAccumr₂_right_left (f₁ : α → γ → σ₁ → σ₁ × φ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ xs (mapAccumr₂ f₂ xs ys s₂).snd s₁)
= let m := mapAccumr₂ (fun x y (s₁, s₂) =>
let r₂ := f₂ x y s₂
let r₁ := f₁ x r₂.snd s₁
((r₁.fst, r₂.fst), r₁.snd)
)
xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem mapAccumr₂_mapAccumr₂_right_right (f₁ : β → γ → σ₁ → σ₁ × φ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ ys (mapAccumr₂ f₂ xs ys s₂).snd s₁)
= let m := mapAccumr₂ (fun x y (s₁, s₂) =>
let r₂ := f₂ x y s₂
let r₁ := f₁ y r₂.snd s₁
((r₁.fst, r₂.fst), r₁.snd)
)
xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
end Binary
end Fold
/-!
## Bisimulations
We can prove two applications of `mapAccumr` equal by providing a bisimulation relation that relates
the initial states.
That is, by providing a relation `R : σ₁ → σ₁ → Prop` such that `R s₁ s₂` implies that `R` also
relates any pair of states reachable by applying `f₁` to `s₁` and `f₂` to `s₂`, with any possible
input values.
-/
section Bisim
variable {xs : Vector α n}
theorem mapAccumr_bisim {f₁ : α → σ₁ → σ₁ × β} {f₂ : α → σ₂ → σ₂ × β} {s₁ : σ₁} {s₂ : σ₂}
(R : σ₁ → σ₂ → Prop) (h₀ : R s₁ s₂)
(hR : ∀ {s q} a, R s q → R (f₁ a s).1 (f₂ a q).1 ∧ (f₁ a s).2 = (f₂ a q).2) :
R (mapAccumr f₁ xs s₁).fst (mapAccumr f₂ xs s₂).fst
∧ (mapAccumr f₁ xs s₁).snd = (mapAccumr f₂ xs s₂).snd := by
induction xs using Vector.revInductionOn generalizing s₁ s₂
next => exact ⟨h₀, rfl⟩
next xs x ih =>
rcases (hR x h₀) with ⟨hR, _⟩
simp only [mapAccumr_snoc, ih hR, true_and]
| congr 1
theorem mapAccumr_bisim_tail {f₁ : α → σ₁ → σ₁ × β} {f₂ : α → σ₂ → σ₂ × β} {s₁ : σ₁} {s₂ : σ₂}
(h : ∃ R : σ₁ → σ₂ → Prop, R s₁ s₂ ∧
∀ {s q} a, R s q → R (f₁ a s).1 (f₂ a q).1 ∧ (f₁ a s).2 = (f₂ a q).2) :
(mapAccumr f₁ xs s₁).snd = (mapAccumr f₂ xs s₂).snd := by
rcases h with ⟨R, h₀, hR⟩
exact (mapAccumr_bisim R h₀ hR).2
theorem mapAccumr₂_bisim {ys : Vector β n} {f₁ : α → β → σ₁ → σ₁ × γ}
{f₂ : α → β → σ₂ → σ₂ × γ} {s₁ : σ₁} {s₂ : σ₂}
(R : σ₁ → σ₂ → Prop) (h₀ : R s₁ s₂)
| Mathlib/Data/Vector/MapLemmas.lean | 192 | 203 |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Yaël Dillies
-/
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
/-!
# Integral average of a function
In this file we define `MeasureTheory.average μ f` (notation: `⨍ x, f x ∂μ`) to be the average
value of `f` with respect to measure `μ`. It is defined as `∫ x, f x ∂((μ univ)⁻¹ • μ)`, so it
is equal to zero if `f` is not integrable or if `μ` is an infinite measure. If `μ` is a probability
measure, then the average of any function is equal to its integral.
For the average on a set, we use `⨍ x in s, f x ∂μ` (notation for `⨍ x, f x ∂(μ.restrict s)`). For
average w.r.t. the volume, one can omit `∂volume`.
Both have a version for the Lebesgue integral rather than Bochner.
We prove several version of the first moment method: An integrable function is below/above its
average on a set of positive measure:
* `measure_le_setLAverage_pos` for the Lebesgue integral
* `measure_le_setAverage_pos` for the Bochner integral
## Implementation notes
The average is defined as an integral over `(μ univ)⁻¹ • μ` so that all theorems about Bochner
integrals work for the average without modifications. For theorems that require integrability of a
function, we provide a convenience lemma `MeasureTheory.Integrable.to_average`.
## Tags
integral, center mass, average value
-/
open ENNReal MeasureTheory MeasureTheory.Measure Metric Set Filter TopologicalSpace Function
open scoped Topology ENNReal Convex
variable {α E F : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [CompleteSpace F] {μ ν : Measure α}
{s t : Set α}
/-!
### Average value of a function w.r.t. a measure
The (Bochner, Lebesgue) average value of a function `f` w.r.t. a measure `μ` (notation:
`⨍ x, f x ∂μ`, `⨍⁻ x, f x ∂μ`) is defined as the (Bochner, Lebesgue) integral divided by the total
measure, so it is equal to zero if `μ` is an infinite measure, and (typically) equal to infinity if
`f` is not integrable. If `μ` is a probability measure, then the average of any function is equal to
its integral.
-/
namespace MeasureTheory
section ENNReal
variable (μ) {f g : α → ℝ≥0∞}
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`, denoted `⨍⁻ x, f x ∂μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def laverage (f : α → ℝ≥0∞) := ∫⁻ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => laverage μ r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure.
It is equal to `(volume univ)⁻¹ * ∫⁻ x, f x`, so it takes value zero if the space has infinite
measure. In a probability space, the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x`, defined as `⨍⁻ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => laverage volume f) => r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ s)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `s` has infinite measure. If `s`
has measure `1`, then the average of any function is equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => laverage (Measure.restrict μ s) r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume s)⁻¹ * ∫⁻ x, f x`, so it takes value zero if `s` has infinite measure. If
`s` has measure `1`, then the average of any function is equal to its integral. -/
notation3 (prettyPrint := false)
"⨍⁻ "(...)" in "s", "r:60:(scoped f => laverage Measure.restrict volume s f) => r
@[simp]
theorem laverage_zero : ⨍⁻ _x, (0 : ℝ≥0∞) ∂μ = 0 := by rw [laverage, lintegral_zero]
@[simp]
theorem laverage_zero_measure (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂(0 : Measure α) = 0 := by simp [laverage]
theorem laverage_eq' (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂(μ univ)⁻¹ • μ := rfl
theorem laverage_eq (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = (∫⁻ x, f x ∂μ) / μ univ := by
rw [laverage_eq', lintegral_smul_measure, ENNReal.div_eq_inv_mul, smul_eq_mul]
theorem laverage_eq_lintegral [IsProbabilityMeasure μ] (f : α → ℝ≥0∞) :
⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by rw [laverage, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_mul_laverage [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
μ univ * ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by
| rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, lintegral_zero_measure, laverage_zero_measure, mul_zero]
| Mathlib/MeasureTheory/Integral/Average.lean | 118 | 119 |
/-
Copyright (c) 2017 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Stephen Morgan, Kim Morrison
-/
import Mathlib.CategoryTheory.Products.Basic
/-!
# Lemmas about functors out of product categories.
-/
open CategoryTheory
namespace CategoryTheory.Bifunctor
universe v₁ v₂ v₃ u₁ u₂ u₃
variable {C : Type u₁} {D : Type u₂} {E : Type u₃}
variable [Category.{v₁} C] [Category.{v₂} D] [Category.{v₃} E]
@[simp]
theorem map_id (F : C × D ⥤ E) (X : C) (Y : D) :
F.map ((𝟙 X, 𝟙 Y) : (X, Y) ⟶ (X, Y)) = 𝟙 (F.obj (X, Y)) :=
F.map_id (X, Y)
@[simp]
theorem map_id_comp (F : C × D ⥤ E) (W : C) {X Y Z : D} (f : X ⟶ Y) (g : Y ⟶ Z) :
F.map ((𝟙 W, f ≫ g) : (W, X) ⟶ (W, Z)) =
F.map ((𝟙 W, f) : (W, X) ⟶ (W, Y)) ≫ F.map ((𝟙 W, g) : (W, Y) ⟶ (W, Z)) := by
rw [← Functor.map_comp, prod_comp, Category.comp_id]
@[simp]
theorem map_comp_id (F : C × D ⥤ E) (X Y Z : C) (W : D) (f : X ⟶ Y) (g : Y ⟶ Z) :
F.map ((f ≫ g, 𝟙 W) : (X, W) ⟶ (Z, W)) =
F.map ((f, 𝟙 W) : (X, W) ⟶ (Y, W)) ≫ F.map ((g, 𝟙 W) : (Y, W) ⟶ (Z, W)) := by
rw [← Functor.map_comp, prod_comp, Category.comp_id]
|
@[simp]
theorem diagonal (F : C × D ⥤ E) (X X' : C) (f : X ⟶ X') (Y Y' : D) (g : Y ⟶ Y') :
F.map ((𝟙 X, g) : (X, Y) ⟶ (X, Y')) ≫ F.map ((f, 𝟙 Y') : (X, Y') ⟶ (X', Y')) =
| Mathlib/CategoryTheory/Products/Bifunctor.lean | 38 | 41 |
/-
Copyright (c) 2022 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.Orientation
import Mathlib.Data.Complex.FiniteDimensional
import Mathlib.Data.Complex.Orientation
import Mathlib.Tactic.LinearCombination
/-!
# Oriented two-dimensional real inner product spaces
This file defines constructions specific to the geometry of an oriented two-dimensional real inner
product space `E`.
## Main declarations
* `Orientation.areaForm`: an antisymmetric bilinear form `E →ₗ[ℝ] E →ₗ[ℝ] ℝ` (usual notation `ω`).
Morally, when `ω` is evaluated on two vectors, it gives the oriented area of the parallelogram
they span. (But mathlib does not yet have a construction of oriented area, and in fact the
construction of oriented area should pass through `ω`.)
* `Orientation.rightAngleRotation`: an isometric automorphism `E ≃ₗᵢ[ℝ] E` (usual notation `J`).
This automorphism squares to -1. In a later file, rotations (`Orientation.rotation`) are defined,
in such a way that this automorphism is equal to rotation by 90 degrees.
* `Orientation.basisRightAngleRotation`: for a nonzero vector `x` in `E`, the basis `![x, J x]`
for `E`.
* `Orientation.kahler`: a complex-valued real-bilinear map `E →ₗ[ℝ] E →ₗ[ℝ] ℂ`. Its real part is the
inner product and its imaginary part is `Orientation.areaForm`. For vectors `x` and `y` in `E`,
the complex number `o.kahler x y` has modulus `‖x‖ * ‖y‖`. In a later file, oriented angles
(`Orientation.oangle`) are defined, in such a way that the argument of `o.kahler x y` is the
oriented angle from `x` to `y`.
## Main results
* `Orientation.rightAngleRotation_rightAngleRotation`: the identity `J (J x) = - x`
* `Orientation.nonneg_inner_and_areaForm_eq_zero_iff_sameRay`: `x`, `y` are in the same ray, if
and only if `0 ≤ ⟪x, y⟫` and `ω x y = 0`
* `Orientation.kahler_mul`: the identity `o.kahler x a * o.kahler a y = ‖a‖ ^ 2 * o.kahler x y`
* `Complex.areaForm`, `Complex.rightAngleRotation`, `Complex.kahler`: the concrete
interpretations of `areaForm`, `rightAngleRotation`, `kahler` for the oriented real inner
product space `ℂ`
* `Orientation.areaForm_map_complex`, `Orientation.rightAngleRotation_map_complex`,
`Orientation.kahler_map_complex`: given an orientation-preserving isometry from `E` to `ℂ`,
expressions for `areaForm`, `rightAngleRotation`, `kahler` as the pullback of their concrete
interpretations on `ℂ`
## Implementation notes
Notation `ω` for `Orientation.areaForm` and `J` for `Orientation.rightAngleRotation` should be
defined locally in each file which uses them, since otherwise one would need a more cumbersome
notation which mentions the orientation explicitly (something like `ω[o]`). Write
```
local notation "ω" => o.areaForm
local notation "J" => o.rightAngleRotation
```
-/
noncomputable section
open scoped RealInnerProductSpace ComplexConjugate
open Module
lemma FiniteDimensional.of_fact_finrank_eq_two {K V : Type*} [DivisionRing K]
[AddCommGroup V] [Module K V] [Fact (finrank K V = 2)] : FiniteDimensional K V :=
.of_fact_finrank_eq_succ 1
attribute [local instance] FiniteDimensional.of_fact_finrank_eq_two
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [Fact (finrank ℝ E = 2)]
(o : Orientation ℝ E (Fin 2))
namespace Orientation
/-- An antisymmetric bilinear form on an oriented real inner product space of dimension 2 (usual
notation `ω`). When evaluated on two vectors, it gives the oriented area of the parallelogram they
span. -/
irreducible_def areaForm : E →ₗ[ℝ] E →ₗ[ℝ] ℝ := by
let z : E [⋀^Fin 0]→ₗ[ℝ] ℝ ≃ₗ[ℝ] ℝ :=
AlternatingMap.constLinearEquivOfIsEmpty.symm
let y : E [⋀^Fin 1]→ₗ[ℝ] ℝ →ₗ[ℝ] E →ₗ[ℝ] ℝ :=
LinearMap.llcomp ℝ E (E [⋀^Fin 0]→ₗ[ℝ] ℝ) ℝ z ∘ₗ AlternatingMap.curryLeftLinearMap
exact y ∘ₗ AlternatingMap.curryLeftLinearMap (R' := ℝ) o.volumeForm
local notation "ω" => o.areaForm
theorem areaForm_to_volumeForm (x y : E) : ω x y = o.volumeForm ![x, y] := by simp [areaForm]
@[simp]
theorem areaForm_apply_self (x : E) : ω x x = 0 := by
rw [areaForm_to_volumeForm]
refine o.volumeForm.map_eq_zero_of_eq ![x, x] ?_ (?_ : (0 : Fin 2) ≠ 1)
· simp
| · norm_num
| Mathlib/Analysis/InnerProductSpace/TwoDim.lean | 106 | 106 |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Kim Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Reverse
import Mathlib.Algebra.Regular.SMul
/-!
# Theory of monic polynomials
We give several tools for proving that polynomials are monic, e.g.
`Monic.mul`, `Monic.map`, `Monic.pow`.
-/
noncomputable section
open Finset
open Polynomial
namespace Polynomial
universe u v y
variable {R : Type u} {S : Type v} {a b : R} {m n : ℕ} {ι : Type y}
section Semiring
variable [Semiring R] {p q r : R[X]}
theorem monic_zero_iff_subsingleton : Monic (0 : R[X]) ↔ Subsingleton R :=
subsingleton_iff_zero_eq_one
theorem not_monic_zero_iff : ¬Monic (0 : R[X]) ↔ (0 : R) ≠ 1 :=
(monic_zero_iff_subsingleton.trans subsingleton_iff_zero_eq_one.symm).not
theorem monic_zero_iff_subsingleton' :
Monic (0 : R[X]) ↔ (∀ f g : R[X], f = g) ∧ ∀ a b : R, a = b :=
Polynomial.monic_zero_iff_subsingleton.trans
⟨by
intro
simp [eq_iff_true_of_subsingleton], fun h => subsingleton_iff.mpr h.2⟩
theorem Monic.as_sum (hp : p.Monic) :
p = X ^ p.natDegree + ∑ i ∈ range p.natDegree, C (p.coeff i) * X ^ i := by
conv_lhs => rw [p.as_sum_range_C_mul_X_pow, sum_range_succ_comm]
suffices C (p.coeff p.natDegree) = 1 by rw [this, one_mul]
exact congr_arg C hp
theorem ne_zero_of_ne_zero_of_monic (hp : p ≠ 0) (hq : Monic q) : q ≠ 0 := by
rintro rfl
rw [Monic.def, leadingCoeff_zero] at hq
rw [← mul_one p, ← C_1, ← hq, C_0, mul_zero] at hp
exact hp rfl
theorem Monic.map [Semiring S] (f : R →+* S) (hp : Monic p) : Monic (p.map f) := by
unfold Monic
nontriviality
have : f p.leadingCoeff ≠ 0 := by
rw [show _ = _ from hp, f.map_one]
exact one_ne_zero
rw [Polynomial.leadingCoeff, coeff_map]
suffices p.coeff (p.map f).natDegree = 1 by simp [this]
rwa [natDegree_eq_of_degree_eq (degree_map_eq_of_leadingCoeff_ne_zero f this)]
theorem monic_C_mul_of_mul_leadingCoeff_eq_one {b : R} (hp : b * p.leadingCoeff = 1) :
Monic (C b * p) := by
unfold Monic
nontriviality
rw [leadingCoeff_mul' _] <;> simp [leadingCoeff_C b, hp]
theorem monic_mul_C_of_leadingCoeff_mul_eq_one {b : R} (hp : p.leadingCoeff * b = 1) :
Monic (p * C b) := by
unfold Monic
nontriviality
rw [leadingCoeff_mul' _] <;> simp [leadingCoeff_C b, hp]
theorem monic_of_degree_le (n : ℕ) (H1 : degree p ≤ n) (H2 : coeff p n = 1) : Monic p :=
Decidable.byCases
(fun H : degree p < n => eq_of_zero_eq_one (H2 ▸ (coeff_eq_zero_of_degree_lt H).symm) _ _)
fun H : ¬degree p < n => by
rwa [Monic, Polynomial.leadingCoeff, natDegree, (lt_or_eq_of_le H1).resolve_left H]
theorem monic_X_pow_add {n : ℕ} (H : degree p < n) : Monic (X ^ n + p) :=
monic_of_degree_le n
(le_trans (degree_add_le _ _) (max_le (degree_X_pow_le _) (le_of_lt H)))
(by rw [coeff_add, coeff_X_pow, if_pos rfl, coeff_eq_zero_of_degree_lt H, add_zero])
variable (a) in
theorem monic_X_pow_add_C {n : ℕ} (h : n ≠ 0) : (X ^ n + C a).Monic :=
monic_X_pow_add <| (lt_of_le_of_lt degree_C_le
(by simp only [Nat.cast_pos, Nat.pos_iff_ne_zero, ne_eq, h, not_false_eq_true]))
theorem monic_X_add_C (x : R) : Monic (X + C x) :=
pow_one (X : R[X]) ▸ monic_X_pow_add_C x one_ne_zero
theorem Monic.mul (hp : Monic p) (hq : Monic q) : Monic (p * q) :=
letI := Classical.decEq R
if h0 : (0 : R) = 1 then
haveI := subsingleton_of_zero_eq_one h0
Subsingleton.elim _ _
else by
have : p.leadingCoeff * q.leadingCoeff ≠ 0 := by
simp [Monic.def.1 hp, Monic.def.1 hq, Ne.symm h0]
rw [Monic.def, leadingCoeff_mul' this, Monic.def.1 hp, Monic.def.1 hq, one_mul]
theorem Monic.pow (hp : Monic p) : ∀ n : ℕ, Monic (p ^ n)
| 0 => monic_one
| n + 1 => by
rw [pow_succ]
exact (Monic.pow hp n).mul hp
theorem Monic.add_of_left (hp : Monic p) (hpq : degree q < degree p) : Monic (p + q) := by
rwa [Monic, add_comm, leadingCoeff_add_of_degree_lt hpq]
theorem Monic.add_of_right (hq : Monic q) (hpq : degree p < degree q) : Monic (p + q) := by
rwa [Monic, leadingCoeff_add_of_degree_lt hpq]
theorem Monic.of_mul_monic_left (hp : p.Monic) (hpq : (p * q).Monic) : q.Monic := by
contrapose! hpq
rw [Monic.def] at hpq ⊢
rwa [leadingCoeff_monic_mul hp]
theorem Monic.of_mul_monic_right (hq : q.Monic) (hpq : (p * q).Monic) : p.Monic := by
contrapose! hpq
rw [Monic.def] at hpq ⊢
rwa [leadingCoeff_mul_monic hq]
namespace Monic
lemma comp (hp : p.Monic) (hq : q.Monic) (h : q.natDegree ≠ 0) : (p.comp q).Monic := by
nontriviality R
have : (p.comp q).natDegree = p.natDegree * q.natDegree :=
natDegree_comp_eq_of_mul_ne_zero <| by simp [hp.leadingCoeff, hq.leadingCoeff]
rw [Monic.def, Polynomial.leadingCoeff, this, coeff_comp_degree_mul_degree h, hp.leadingCoeff,
hq.leadingCoeff, one_pow, mul_one]
lemma comp_X_add_C (hp : p.Monic) (r : R) : (p.comp (X + C r)).Monic := by
nontriviality R
refine hp.comp (monic_X_add_C _) fun ha ↦ ?_
rw [natDegree_X_add_C] at ha
exact one_ne_zero ha
@[simp]
theorem natDegree_eq_zero_iff_eq_one (hp : p.Monic) : p.natDegree = 0 ↔ p = 1 := by
constructor <;> intro h
swap
· rw [h]
exact natDegree_one
have : p = C (p.coeff 0) := by
rw [← Polynomial.degree_le_zero_iff]
rwa [Polynomial.natDegree_eq_zero_iff_degree_le_zero] at h
rw [this]
rw [← h, ← Polynomial.leadingCoeff, Monic.def.1 hp, C_1]
@[simp]
theorem degree_le_zero_iff_eq_one (hp : p.Monic) : p.degree ≤ 0 ↔ p = 1 := by
rw [← hp.natDegree_eq_zero_iff_eq_one, natDegree_eq_zero_iff_degree_le_zero]
theorem natDegree_mul (hp : p.Monic) (hq : q.Monic) :
(p * q).natDegree = p.natDegree + q.natDegree := by
nontriviality R
apply natDegree_mul'
simp [hp.leadingCoeff, hq.leadingCoeff]
theorem degree_mul_comm (hp : p.Monic) (q : R[X]) : (p * q).degree = (q * p).degree := by
by_cases h : q = 0
· simp [h]
rw [degree_mul', hp.degree_mul]
· exact add_comm _ _
· rwa [hp.leadingCoeff, one_mul, leadingCoeff_ne_zero]
nonrec theorem natDegree_mul' (hp : p.Monic) (hq : q ≠ 0) :
(p * q).natDegree = p.natDegree + q.natDegree := by
rw [natDegree_mul']
simpa [hp.leadingCoeff, leadingCoeff_ne_zero]
theorem natDegree_mul_comm (hp : p.Monic) (q : R[X]) : (p * q).natDegree = (q * p).natDegree := by
by_cases h : q = 0
· simp [h]
rw [hp.natDegree_mul' h, Polynomial.natDegree_mul', add_comm]
simpa [hp.leadingCoeff, leadingCoeff_ne_zero]
theorem not_dvd_of_natDegree_lt (hp : Monic p) (h0 : q ≠ 0) (hl : natDegree q < natDegree p) :
¬p ∣ q := by
rintro ⟨r, rfl⟩
rw [hp.natDegree_mul' <| right_ne_zero_of_mul h0] at hl
exact hl.not_le (Nat.le_add_right _ _)
theorem not_dvd_of_degree_lt (hp : Monic p) (h0 : q ≠ 0) (hl : degree q < degree p) : ¬p ∣ q :=
Monic.not_dvd_of_natDegree_lt hp h0 <| natDegree_lt_natDegree h0 hl
theorem nextCoeff_mul (hp : Monic p) (hq : Monic q) :
nextCoeff (p * q) = nextCoeff p + nextCoeff q := by
nontriviality
simp only [← coeff_one_reverse]
rw [reverse_mul] <;> simp [hp.leadingCoeff, hq.leadingCoeff, mul_coeff_one, add_comm]
theorem nextCoeff_pow (hp : p.Monic) (n : ℕ) : (p ^ n).nextCoeff = n • p.nextCoeff := by
induction n with
| zero => rw [pow_zero, zero_smul, ← map_one (f := C), nextCoeff_C_eq_zero]
| succ n ih => rw [pow_succ, (hp.pow n).nextCoeff_mul hp, ih, succ_nsmul]
theorem eq_one_of_map_eq_one {S : Type*} [Semiring S] [Nontrivial S] (f : R →+* S) (hp : p.Monic)
(map_eq : p.map f = 1) : p = 1 := by
nontriviality R
have hdeg : p.degree = 0 := by
rw [← degree_map_eq_of_leadingCoeff_ne_zero f _, map_eq, degree_one]
· rw [hp.leadingCoeff, f.map_one]
exact one_ne_zero
have hndeg : p.natDegree = 0 :=
WithBot.coe_eq_coe.mp ((degree_eq_natDegree hp.ne_zero).symm.trans hdeg)
convert eq_C_of_degree_eq_zero hdeg
rw [← hndeg, ← Polynomial.leadingCoeff, hp.leadingCoeff, C.map_one]
theorem natDegree_pow (hp : p.Monic) (n : ℕ) : (p ^ n).natDegree = n * p.natDegree := by
induction n with
| zero => simp
| succ n hn => rw [pow_succ, (hp.pow n).natDegree_mul hp, hn, Nat.succ_mul, add_comm]
end Monic
@[simp]
theorem natDegree_pow_X_add_C [Nontrivial R] (n : ℕ) (r : R) : ((X + C r) ^ n).natDegree = n := by
rw [(monic_X_add_C r).natDegree_pow, natDegree_X_add_C, mul_one]
theorem Monic.eq_one_of_isUnit (hm : Monic p) (hpu : IsUnit p) : p = 1 := by
nontriviality R
obtain ⟨q, h⟩ := hpu.exists_right_inv
have := hm.natDegree_mul' (right_ne_zero_of_mul_eq_one h)
rw [h, natDegree_one, eq_comm, add_eq_zero] at this
exact hm.natDegree_eq_zero_iff_eq_one.mp this.1
theorem Monic.isUnit_iff (hm : p.Monic) : IsUnit p ↔ p = 1 :=
⟨hm.eq_one_of_isUnit, fun h => h.symm ▸ isUnit_one⟩
theorem eq_of_monic_of_associated (hp : p.Monic) (hq : q.Monic) (hpq : Associated p q) : p = q := by
obtain ⟨u, rfl⟩ := hpq
rw [(hp.of_mul_monic_left hq).eq_one_of_isUnit u.isUnit, mul_one]
end Semiring
section CommSemiring
variable [CommSemiring R] {p : R[X]}
theorem monic_multiset_prod_of_monic (t : Multiset ι) (f : ι → R[X]) (ht : ∀ i ∈ t, Monic (f i)) :
Monic (t.map f).prod := by
revert ht
refine t.induction_on ?_ ?_; · simp
intro a t ih ht
rw [Multiset.map_cons, Multiset.prod_cons]
| exact (ht _ (Multiset.mem_cons_self _ _)).mul (ih fun _ hi => ht _ (Multiset.mem_cons_of_mem hi))
theorem monic_prod_of_monic (s : Finset ι) (f : ι → R[X]) (hs : ∀ i ∈ s, Monic (f i)) :
Monic (∏ i ∈ s, f i) :=
monic_multiset_prod_of_monic s.1 f hs
| Mathlib/Algebra/Polynomial/Monic.lean | 255 | 260 |
/-
Copyright (c) 2022 Michael Stoll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Stoll
-/
import Mathlib.NumberTheory.LegendreSymbol.QuadraticChar.Basic
import Mathlib.NumberTheory.GaussSum
/-!
# Quadratic characters of finite fields
Further facts relying on Gauss sums.
-/
/-!
### Basic properties of the quadratic character
We prove some properties of the quadratic character.
We work with a finite field `F` here.
The interesting case is when the characteristic of `F` is odd.
-/
section SpecialValues
open ZMod MulChar
variable {F : Type*} [Field F] [Fintype F]
/-- The value of the quadratic character at `2` -/
theorem quadraticChar_two [DecidableEq F] (hF : ringChar F ≠ 2) :
quadraticChar F 2 = χ₈ (Fintype.card F) :=
IsQuadratic.eq_of_eq_coe (quadraticChar_isQuadratic F) isQuadratic_χ₈ hF
((quadraticChar_eq_pow_of_char_ne_two' hF 2).trans (FiniteField.two_pow_card hF))
/-- `2` is a square in `F` iff `#F` is not congruent to `3` or `5` mod `8`. -/
theorem FiniteField.isSquare_two_iff :
IsSquare (2 : F) ↔ Fintype.card F % 8 ≠ 3 ∧ Fintype.card F % 8 ≠ 5 := by
classical
by_cases hF : ringChar F = 2
· have h := FiniteField.even_card_of_char_two hF
simp only [FiniteField.isSquare_of_char_two hF, true_iff]
omega
· have h := FiniteField.odd_card_of_char_ne_two hF
rw [← quadraticChar_one_iff_isSquare (Ring.two_ne_zero hF), quadraticChar_two hF,
χ₈_nat_eq_if_mod_eight]
omega
/-- The value of the quadratic character at `-2` -/
theorem quadraticChar_neg_two [DecidableEq F] (hF : ringChar F ≠ 2) :
quadraticChar F (-2) = χ₈' (Fintype.card F) := by
rw [(by norm_num : (-2 : F) = -1 * 2), map_mul, χ₈'_eq_χ₄_mul_χ₈, quadraticChar_neg_one hF,
quadraticChar_two hF, @cast_natCast _ (ZMod 4) _ _ _ (by decide : 4 ∣ 8)]
|
/-- `-2` is a square in `F` iff `#F` is not congruent to `5` or `7` mod `8`. -/
theorem FiniteField.isSquare_neg_two_iff :
IsSquare (-2 : F) ↔ Fintype.card F % 8 ≠ 5 ∧ Fintype.card F % 8 ≠ 7 := by
| Mathlib/NumberTheory/LegendreSymbol/QuadraticChar/GaussSum.lean | 56 | 59 |
/-
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.Nat.ModEq
import Mathlib.Data.Nat.Prime.Basic
import Mathlib.NumberTheory.Zsqrtd.Basic
/-!
# Pell's equation and Matiyasevic's theorem
This file solves Pell's equation, i.e. integer solutions to `x ^ 2 - d * y ^ 2 = 1`
*in the special case that `d = a ^ 2 - 1`*.
This is then applied to prove Matiyasevic's theorem that the power
function is Diophantine, which is the last key ingredient in the solution to Hilbert's tenth
problem. For the definition of Diophantine function, see `NumberTheory.Dioph`.
For results on Pell's equation for arbitrary (positive, non-square) `d`, see
`NumberTheory.Pell`.
## Main definition
* `pell` is a function assigning to a natural number `n` the `n`-th solution to Pell's equation
constructed recursively from the initial solution `(0, 1)`.
## Main statements
* `eq_pell` shows that every solution to Pell's equation is recursively obtained using `pell`
* `matiyasevic` shows that a certain system of Diophantine equations has a solution if and only if
the first variable is the `x`-component in a solution to Pell's equation - the key step towards
Hilbert's tenth problem in Davis' version of Matiyasevic's theorem.
* `eq_pow_of_pell` shows that the power function is Diophantine.
## Implementation notes
The proof of Matiyasevic's theorem doesn't follow Matiyasevic's original account of using Fibonacci
numbers but instead Davis' variant of using solutions to Pell's equation.
## References
* [M. Carneiro, _A Lean formalization of Matiyasevič's theorem_][carneiro2018matiyasevic]
* [M. Davis, _Hilbert's tenth problem is unsolvable_][MR317916]
## Tags
Pell's equation, Matiyasevic's theorem, Hilbert's tenth problem
-/
namespace Pell
open Nat
section
variable {d : ℤ}
/-- The property of being a solution to the Pell equation, expressed
as a property of elements of `ℤ√d`. -/
def IsPell : ℤ√d → Prop
| ⟨x, y⟩ => x * x - d * y * y = 1
theorem isPell_norm : ∀ {b : ℤ√d}, IsPell b ↔ b * star b = 1
| ⟨x, y⟩ => by simp [Zsqrtd.ext_iff, IsPell, mul_comm]; ring_nf
theorem isPell_iff_mem_unitary : ∀ {b : ℤ√d}, IsPell b ↔ b ∈ unitary (ℤ√d)
| ⟨x, y⟩ => by rw [unitary.mem_iff, isPell_norm, mul_comm (star _), and_self_iff]
theorem isPell_mul {b c : ℤ√d} (hb : IsPell b) (hc : IsPell c) : IsPell (b * c) :=
isPell_norm.2 (by simp [mul_comm, mul_left_comm c, mul_assoc,
star_mul, isPell_norm.1 hb, isPell_norm.1 hc])
theorem isPell_star : ∀ {b : ℤ√d}, IsPell b ↔ IsPell (star b)
| ⟨x, y⟩ => by simp [IsPell, Zsqrtd.star_mk]
end
section
variable {a : ℕ} (a1 : 1 < a)
private def d (_a1 : 1 < a) :=
a * a - 1
@[simp]
theorem d_pos : 0 < d a1 :=
tsub_pos_of_lt (mul_lt_mul a1 (le_of_lt a1) (by decide) (Nat.zero_le _) : 1 * 1 < a * a)
-- TODO(lint): Fix double namespace issue
/-- The Pell sequences, i.e. the sequence of integer solutions to `x ^ 2 - d * y ^ 2 = 1`, where
`d = a ^ 2 - 1`, defined together in mutual recursion. -/
--@[nolint dup_namespace]
def pell : ℕ → ℕ × ℕ
| 0 => (1, 0)
| n+1 => ((pell n).1 * a + d a1 * (pell n).2, (pell n).1 + (pell n).2 * a)
/-- The Pell `x` sequence. -/
def xn (n : ℕ) : ℕ :=
(pell a1 n).1
/-- The Pell `y` sequence. -/
def yn (n : ℕ) : ℕ :=
(pell a1 n).2
@[simp]
theorem pell_val (n : ℕ) : pell a1 n = (xn a1 n, yn a1 n) :=
show pell a1 n = ((pell a1 n).1, (pell a1 n).2) from
match pell a1 n with
| (_, _) => rfl
@[simp]
theorem xn_zero : xn a1 0 = 1 :=
rfl
@[simp]
theorem yn_zero : yn a1 0 = 0 :=
rfl
@[simp]
theorem xn_succ (n : ℕ) : xn a1 (n + 1) = xn a1 n * a + d a1 * yn a1 n :=
rfl
@[simp]
theorem yn_succ (n : ℕ) : yn a1 (n + 1) = xn a1 n + yn a1 n * a :=
rfl
theorem xn_one : xn a1 1 = a := by simp
theorem yn_one : yn a1 1 = 1 := by simp
/-- The Pell `x` sequence, considered as an integer sequence. -/
def xz (n : ℕ) : ℤ :=
xn a1 n
/-- The Pell `y` sequence, considered as an integer sequence. -/
def yz (n : ℕ) : ℤ :=
yn a1 n
section
/-- The element `a` such that `d = a ^ 2 - 1`, considered as an integer. -/
def az (a : ℕ) : ℤ :=
a
end
include a1 in
theorem asq_pos : 0 < a * a :=
le_trans (le_of_lt a1)
(by have := @Nat.mul_le_mul_left 1 a a (le_of_lt a1); rwa [mul_one] at this)
theorem dz_val : ↑(d a1) = az a * az a - 1 :=
have : 1 ≤ a * a := asq_pos a1
by rw [Pell.d, Int.ofNat_sub this]; rfl
@[simp]
theorem xz_succ (n : ℕ) : (xz a1 (n + 1)) = xz a1 n * az a + d a1 * yz a1 n :=
rfl
@[simp]
theorem yz_succ (n : ℕ) : yz a1 (n + 1) = xz a1 n + yz a1 n * az a :=
rfl
/-- The Pell sequence can also be viewed as an element of `ℤ√d` -/
def pellZd (n : ℕ) : ℤ√(d a1) :=
⟨xn a1 n, yn a1 n⟩
@[simp]
theorem pellZd_re (n : ℕ) : (pellZd a1 n).re = xn a1 n :=
rfl
@[simp]
theorem pellZd_im (n : ℕ) : (pellZd a1 n).im = yn a1 n :=
rfl
theorem isPell_nat {x y : ℕ} : IsPell (⟨x, y⟩ : ℤ√(d a1)) ↔ x * x - d a1 * y * y = 1 :=
⟨fun h =>
(Nat.cast_inj (R := ℤ)).1
(by rw [Int.ofNat_sub (Int.le_of_ofNat_le_ofNat <| Int.le.intro_sub _ h)]; exact h),
fun h =>
show ((x * x : ℕ) - (d a1 * y * y : ℕ) : ℤ) = 1 by
rw [← Int.ofNat_sub <| le_of_lt <| Nat.lt_of_sub_eq_succ h, h]; rfl⟩
@[simp]
theorem pellZd_succ (n : ℕ) : pellZd a1 (n + 1) = pellZd a1 n * ⟨a, 1⟩ := by ext <;> simp
theorem isPell_one : IsPell (⟨a, 1⟩ : ℤ√(d a1)) :=
show az a * az a - d a1 * 1 * 1 = 1 by simp [dz_val]
theorem isPell_pellZd : ∀ n : ℕ, IsPell (pellZd a1 n)
| 0 => rfl
| n + 1 => by
let o := isPell_one a1
simpa using Pell.isPell_mul (isPell_pellZd n) o
@[simp]
theorem pell_eqz (n : ℕ) : xz a1 n * xz a1 n - d a1 * yz a1 n * yz a1 n = 1 :=
isPell_pellZd a1 n
@[simp]
theorem pell_eq (n : ℕ) : xn a1 n * xn a1 n - d a1 * yn a1 n * yn a1 n = 1 :=
let pn := pell_eqz a1 n
have h : (↑(xn a1 n * xn a1 n) : ℤ) - ↑(d a1 * yn a1 n * yn a1 n) = 1 := by
repeat' rw [Int.natCast_mul]; exact pn
have hl : d a1 * yn a1 n * yn a1 n ≤ xn a1 n * xn a1 n :=
Nat.cast_le.1 <| Int.le.intro _ <| add_eq_of_eq_sub' <| Eq.symm h
(Nat.cast_inj (R := ℤ)).1 (by rw [Int.ofNat_sub hl]; exact h)
instance dnsq : Zsqrtd.Nonsquare (d a1) :=
⟨fun n h =>
have : n * n + 1 = a * a := by rw [← h]; exact Nat.succ_pred_eq_of_pos (asq_pos a1)
have na : n < a := Nat.mul_self_lt_mul_self_iff.1 (by rw [← this]; exact Nat.lt_succ_self _)
have : (n + 1) * (n + 1) ≤ n * n + 1 := by rw [this]; exact Nat.mul_self_le_mul_self na
have : n + n ≤ 0 :=
@Nat.le_of_add_le_add_right _ (n * n + 1) _ (by ring_nf at this ⊢; assumption)
Nat.ne_of_gt (d_pos a1) <| by
rwa [Nat.eq_zero_of_le_zero ((Nat.le_add_left _ _).trans this)] at h⟩
theorem xn_ge_a_pow : ∀ n : ℕ, a ^ n ≤ xn a1 n
| 0 => le_refl 1
| n + 1 => by
simp only [_root_.pow_succ, xn_succ]
exact le_trans (Nat.mul_le_mul_right _ (xn_ge_a_pow n)) (Nat.le_add_right _ _)
theorem n_lt_xn (n) : n < xn a1 n :=
lt_of_lt_of_le (Nat.lt_pow_self a1) (xn_ge_a_pow a1 n)
theorem x_pos (n) : 0 < xn a1 n :=
lt_of_le_of_lt (Nat.zero_le n) (n_lt_xn a1 n)
theorem eq_pell_lem : ∀ (n) (b : ℤ√(d a1)), 1 ≤ b → IsPell b →
b ≤ pellZd a1 n → ∃ n, b = pellZd a1 n
| 0, _ => fun h1 _ hl => ⟨0, @Zsqrtd.le_antisymm _ (dnsq a1) _ _ hl h1⟩
| n + 1, b => fun h1 hp h =>
have a1p : (0 : ℤ√(d a1)) ≤ ⟨a, 1⟩ := trivial
have am1p : (0 : ℤ√(d a1)) ≤ ⟨a, -1⟩ := show (_ : Nat) ≤ _ by simp; exact Nat.pred_le _
have a1m : (⟨a, 1⟩ * ⟨a, -1⟩ : ℤ√(d a1)) = 1 := isPell_norm.1 (isPell_one a1)
if ha : (⟨↑a, 1⟩ : ℤ√(d a1)) ≤ b then
let ⟨m, e⟩ :=
eq_pell_lem n (b * ⟨a, -1⟩) (by rw [← a1m]; exact mul_le_mul_of_nonneg_right ha am1p)
(isPell_mul hp (isPell_star.1 (isPell_one a1)))
(by
have t := mul_le_mul_of_nonneg_right h am1p
rwa [pellZd_succ, mul_assoc, a1m, mul_one] at t)
⟨m + 1, by
rw [show b = b * ⟨a, -1⟩ * ⟨a, 1⟩ by rw [mul_assoc, Eq.trans (mul_comm _ _) a1m]; simp,
pellZd_succ, e]⟩
else
suffices ¬1 < b from ⟨0, show b = 1 from (Or.resolve_left (lt_or_eq_of_le h1) this).symm⟩
fun h1l => by
obtain ⟨x, y⟩ := b
exact by
have bm : (_ * ⟨_, _⟩ : ℤ√d a1) = 1 := Pell.isPell_norm.1 hp
have y0l : (0 : ℤ√d a1) < ⟨x - x, y - -y⟩ :=
sub_lt_sub h1l fun hn : (1 : ℤ√d a1) ≤ ⟨x, -y⟩ => by
have t := mul_le_mul_of_nonneg_left hn (le_trans zero_le_one h1)
rw [bm, mul_one] at t
exact h1l t
have yl2 : (⟨_, _⟩ : ℤ√_) < ⟨_, _⟩ :=
show (⟨x, y⟩ - ⟨x, -y⟩ : ℤ√d a1) < ⟨a, 1⟩ - ⟨a, -1⟩ from
sub_lt_sub ha fun hn : (⟨x, -y⟩ : ℤ√d a1) ≤ ⟨a, -1⟩ => by
have t := mul_le_mul_of_nonneg_right
(mul_le_mul_of_nonneg_left hn (le_trans zero_le_one h1)) a1p
rw [bm, one_mul, mul_assoc, Eq.trans (mul_comm _ _) a1m, mul_one] at t
exact ha t
simp only [sub_self, sub_neg_eq_add] at y0l; simp only [Zsqrtd.neg_re, add_neg_cancel,
Zsqrtd.neg_im, neg_neg] at yl2
exact
match y, y0l, (yl2 : (⟨_, _⟩ : ℤ√_) < ⟨_, _⟩) with
| 0, y0l, _ => y0l (le_refl 0)
| (y + 1 : ℕ), _, yl2 =>
yl2
(Zsqrtd.le_of_le_le (by simp [sub_eq_add_neg])
(let t := Int.ofNat_le_ofNat_of_le (Nat.succ_pos y)
add_le_add t t))
| Int.negSucc _, y0l, _ => y0l trivial
theorem eq_pellZd (b : ℤ√(d a1)) (b1 : 1 ≤ b) (hp : IsPell b) : ∃ n, b = pellZd a1 n :=
let ⟨n, h⟩ := @Zsqrtd.le_arch (d a1) b
eq_pell_lem a1 n b b1 hp <|
h.trans <| by
rw [Zsqrtd.natCast_val]
exact
Zsqrtd.le_of_le_le (Int.ofNat_le_ofNat_of_le <| le_of_lt <| n_lt_xn _ _)
(Int.ofNat_zero_le _)
/-- Every solution to **Pell's equation** is recursively obtained from the initial solution
`(1,0)` using the recursion `pell`. -/
theorem eq_pell {x y : ℕ} (hp : x * x - d a1 * y * y = 1) : ∃ n, x = xn a1 n ∧ y = yn a1 n :=
have : (1 : ℤ√(d a1)) ≤ ⟨x, y⟩ :=
match x, hp with
| 0, (hp : 0 - _ = 1) => by rw [zero_tsub] at hp; contradiction
| x + 1, _hp =>
Zsqrtd.le_of_le_le (Int.ofNat_le_ofNat_of_le <| Nat.succ_pos x) (Int.ofNat_zero_le _)
let ⟨m, e⟩ := eq_pellZd a1 ⟨x, y⟩ this ((isPell_nat a1).2 hp)
⟨m,
match x, y, e with
| _, _, rfl => ⟨rfl, rfl⟩⟩
theorem pellZd_add (m) : ∀ n, pellZd a1 (m + n) = pellZd a1 m * pellZd a1 n
| 0 => (mul_one _).symm
| n + 1 => by rw [← add_assoc, pellZd_succ, pellZd_succ, pellZd_add _ n, ← mul_assoc]
theorem xn_add (m n) : xn a1 (m + n) = xn a1 m * xn a1 n + d a1 * yn a1 m * yn a1 n := by
injection pellZd_add a1 m n with h _
zify
rw [h]
simp [pellZd]
theorem yn_add (m n) : yn a1 (m + n) = xn a1 m * yn a1 n + yn a1 m * xn a1 n := by
injection pellZd_add a1 m n with _ h
zify
rw [h]
simp [pellZd]
theorem pellZd_sub {m n} (h : n ≤ m) : pellZd a1 (m - n) = pellZd a1 m * star (pellZd a1 n) := by
let t := pellZd_add a1 n (m - n)
rw [add_tsub_cancel_of_le h] at t
rw [t, mul_comm (pellZd _ n) _, mul_assoc, isPell_norm.1 (isPell_pellZd _ _), mul_one]
theorem xz_sub {m n} (h : n ≤ m) :
xz a1 (m - n) = xz a1 m * xz a1 n - d a1 * yz a1 m * yz a1 n := by
rw [sub_eq_add_neg, ← mul_neg]
exact congr_arg Zsqrtd.re (pellZd_sub a1 h)
theorem yz_sub {m n} (h : n ≤ m) : yz a1 (m - n) = xz a1 n * yz a1 m - xz a1 m * yz a1 n := by
rw [sub_eq_add_neg, ← mul_neg, mul_comm, add_comm]
exact congr_arg Zsqrtd.im (pellZd_sub a1 h)
theorem xy_coprime (n) : (xn a1 n).Coprime (yn a1 n) :=
Nat.coprime_of_dvd' fun k _ kx ky => by
let p := pell_eq a1 n
rw [← p]
exact Nat.dvd_sub (kx.mul_left _) (ky.mul_left _)
theorem strictMono_y : StrictMono (yn a1)
| _, 0, h => absurd h <| Nat.not_lt_zero _
| m, n + 1, h => by
have : yn a1 m ≤ yn a1 n :=
Or.elim (lt_or_eq_of_le <| Nat.le_of_succ_le_succ h) (fun hl => le_of_lt <| strictMono_y hl)
fun e => by rw [e]
simp only [yn_succ, gt_iff_lt]; refine lt_of_le_of_lt ?_ (Nat.lt_add_of_pos_left <| x_pos a1 n)
rw [← mul_one (yn a1 m)]
exact mul_le_mul this (le_of_lt a1) (Nat.zero_le _) (Nat.zero_le _)
theorem strictMono_x : StrictMono (xn a1)
| _, 0, h => absurd h <| Nat.not_lt_zero _
| m, n + 1, h => by
have : xn a1 m ≤ xn a1 n :=
Or.elim (lt_or_eq_of_le <| Nat.le_of_succ_le_succ h) (fun hl => le_of_lt <| strictMono_x hl)
fun e => by rw [e]
simp only [xn_succ, gt_iff_lt]
refine lt_of_lt_of_le (lt_of_le_of_lt this ?_) (Nat.le_add_right _ _)
have t := Nat.mul_lt_mul_of_pos_left a1 (x_pos a1 n)
rwa [mul_one] at t
theorem yn_ge_n : ∀ n, n ≤ yn a1 n
| 0 => Nat.zero_le _
| n + 1 =>
show n < yn a1 (n + 1) from lt_of_le_of_lt (yn_ge_n n) (strictMono_y a1 <| Nat.lt_succ_self n)
theorem y_mul_dvd (n) : ∀ k, yn a1 n ∣ yn a1 (n * k)
| 0 => dvd_zero _
| k + 1 => by
rw [Nat.mul_succ, yn_add]; exact dvd_add (dvd_mul_left _ _) ((y_mul_dvd _ k).mul_right _)
theorem y_dvd_iff (m n) : yn a1 m ∣ yn a1 n ↔ m ∣ n :=
⟨fun h =>
Nat.dvd_of_mod_eq_zero <|
(Nat.eq_zero_or_pos _).resolve_right fun hp => by
have co : Nat.Coprime (yn a1 m) (xn a1 (m * (n / m))) :=
Nat.Coprime.symm <| (xy_coprime a1 _).coprime_dvd_right (y_mul_dvd a1 m (n / m))
have m0 : 0 < m :=
m.eq_zero_or_pos.resolve_left fun e => by
rw [e, Nat.mod_zero] at hp;rw [e] at h
exact _root_.ne_of_lt (strictMono_y a1 hp) (eq_zero_of_zero_dvd h).symm
rw [← Nat.mod_add_div n m, yn_add] at h
exact
not_le_of_gt (strictMono_y _ <| Nat.mod_lt n m0)
(Nat.le_of_dvd (strictMono_y _ hp) <|
co.dvd_of_dvd_mul_right <|
(Nat.dvd_add_iff_right <| (y_mul_dvd _ _ _).mul_left _).2 h),
fun ⟨k, e⟩ => by rw [e]; apply y_mul_dvd⟩
theorem xy_modEq_yn (n) :
∀ k, xn a1 (n * k) ≡ xn a1 n ^ k [MOD yn a1 n ^ 2] ∧ yn a1 (n * k) ≡
k * xn a1 n ^ (k - 1) * yn a1 n [MOD yn a1 n ^ 3]
| | 0 => by constructor <;> simpa using Nat.ModEq.refl _
| k + 1 => by
let ⟨hx, hy⟩ := xy_modEq_yn n k
| Mathlib/NumberTheory/PellMatiyasevic.lean | 390 | 392 |
/-
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 | 975 | 995 | |
/-
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.MeasureTheory.Measure.AEMeasurable
/-!
# Typeclasses for measurability of operations
In this file we define classes `MeasurableMul` etc and prove dot-style lemmas
(`Measurable.mul`, `AEMeasurable.mul` etc). For binary operations we define two typeclasses:
- `MeasurableMul` says that both left and right multiplication are measurable;
- `MeasurableMul₂` says that `fun p : α × α => p.1 * p.2` is measurable,
and similarly for other binary operations. The reason for introducing these classes is that in case
of topological space `α` equipped with the Borel `σ`-algebra, instances for `MeasurableMul₂`
etc require `α` to have a second countable topology.
We define separate classes for `MeasurableDiv`/`MeasurableSub`
because on some types (e.g., `ℕ`, `ℝ≥0∞`) division and/or subtraction are not defined as `a * b⁻¹` /
`a + (-b)`.
For instances relating, e.g., `ContinuousMul` to `MeasurableMul` see file
`MeasureTheory.BorelSpace`.
## Implementation notes
For the heuristics of `@[to_additive]` it is important that the type with a multiplication
(or another multiplicative operations) is the first (implicit) argument of all declarations.
## Tags
measurable function, arithmetic operator
## TODO
* Uniformize the treatment of `pow` and `smul`.
* Use `@[to_additive]` to send `MeasurablePow` to `MeasurableSMul₂`.
* This might require changing the definition (swapping the arguments in the function that is
in the conclusion of `MeasurableSMul`.)
-/
open MeasureTheory
open scoped Pointwise
universe u v
variable {α : Type*}
/-!
### Binary operations: `(· + ·)`, `(· * ·)`, `(· - ·)`, `(· / ·)`
-/
/-- We say that a type has `MeasurableAdd` if `(· + c)` and `(· + c)` are measurable functions.
For a typeclass assuming measurability of `uncurry (· + ·)` see `MeasurableAdd₂`. -/
class MeasurableAdd (M : Type*) [MeasurableSpace M] [Add M] : Prop where
measurable_const_add : ∀ c : M, Measurable (c + ·)
measurable_add_const : ∀ c : M, Measurable (· + c)
export MeasurableAdd (measurable_const_add measurable_add_const)
/-- We say that a type has `MeasurableAdd₂` if `uncurry (· + ·)` is a measurable functions.
For a typeclass assuming measurability of `(c + ·)` and `(· + c)` see `MeasurableAdd`. -/
class MeasurableAdd₂ (M : Type*) [MeasurableSpace M] [Add M] : Prop where
measurable_add : Measurable fun p : M × M => p.1 + p.2
export MeasurableAdd₂ (measurable_add)
/-- We say that a type has `MeasurableMul` if `(c * ·)` and `(· * c)` are measurable functions.
For a typeclass assuming measurability of `uncurry (*)` see `MeasurableMul₂`. -/
@[to_additive]
class MeasurableMul (M : Type*) [MeasurableSpace M] [Mul M] : Prop where
measurable_const_mul : ∀ c : M, Measurable (c * ·)
measurable_mul_const : ∀ c : M, Measurable (· * c)
export MeasurableMul (measurable_const_mul measurable_mul_const)
/-- We say that a type has `MeasurableMul₂` if `uncurry (· * ·)` is a measurable functions.
For a typeclass assuming measurability of `(c * ·)` and `(· * c)` see `MeasurableMul`. -/
@[to_additive MeasurableAdd₂]
class MeasurableMul₂ (M : Type*) [MeasurableSpace M] [Mul M] : Prop where
measurable_mul : Measurable fun p : M × M => p.1 * p.2
export MeasurableMul₂ (measurable_mul)
section Mul
variable {M α β : Type*} [MeasurableSpace M] [Mul M] {m : MeasurableSpace α}
{mβ : MeasurableSpace β} {f g : α → M} {μ : Measure α}
@[to_additive (attr := fun_prop, measurability)]
theorem Measurable.const_mul [MeasurableMul M] (hf : Measurable f) (c : M) :
Measurable fun x => c * f x :=
(measurable_const_mul c).comp hf
@[to_additive (attr := fun_prop, measurability)]
theorem AEMeasurable.const_mul [MeasurableMul M] (hf : AEMeasurable f μ) (c : M) :
AEMeasurable (fun x => c * f x) μ :=
(MeasurableMul.measurable_const_mul c).comp_aemeasurable hf
@[to_additive (attr := fun_prop, measurability)]
theorem Measurable.mul_const [MeasurableMul M] (hf : Measurable f) (c : M) :
Measurable fun x => f x * c :=
(measurable_mul_const c).comp hf
@[to_additive (attr := fun_prop, measurability)]
theorem AEMeasurable.mul_const [MeasurableMul M] (hf : AEMeasurable f μ) (c : M) :
AEMeasurable (fun x => f x * c) μ :=
(measurable_mul_const c).comp_aemeasurable hf
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem Measurable.mul [MeasurableMul₂ M] (hf : Measurable f) (hg : Measurable g) :
Measurable fun a => f a * g a :=
measurable_mul.comp (hf.prodMk hg)
/-- Compositional version of `Measurable.mul` for use by `fun_prop`. -/
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))
"Compositional version of `Measurable.add` for use by `fun_prop`."]
lemma Measurable.mul' [MeasurableMul₂ M] {f g : α → β → M} {h : α → β} (hf : Measurable ↿f)
(hg : Measurable ↿g) (hh : Measurable h) : Measurable fun a ↦ (f a * g a) (h a) := by
simp; fun_prop
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem AEMeasurable.mul' [MeasurableMul₂ M] (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (f * g) μ :=
measurable_mul.comp_aemeasurable (hf.prodMk hg)
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem AEMeasurable.mul [MeasurableMul₂ M] (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (fun a => f a * g a) μ :=
measurable_mul.comp_aemeasurable (hf.prodMk hg)
@[to_additive]
instance (priority := 100) MeasurableMul₂.toMeasurableMul [MeasurableMul₂ M] :
MeasurableMul M :=
⟨fun _ => measurable_const.mul measurable_id, fun _ => measurable_id.mul measurable_const⟩
@[to_additive]
instance Pi.measurableMul {ι : Type*} {α : ι → Type*} [∀ i, Mul (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableMul (α i)] : MeasurableMul (∀ i, α i) :=
⟨fun _ => measurable_pi_iff.mpr fun i => (measurable_pi_apply i).const_mul _, fun _ =>
measurable_pi_iff.mpr fun i => (measurable_pi_apply i).mul_const _⟩
@[to_additive Pi.measurableAdd₂]
instance Pi.measurableMul₂ {ι : Type*} {α : ι → Type*} [∀ i, Mul (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableMul₂ (α i)] : MeasurableMul₂ (∀ i, α i) :=
⟨measurable_pi_iff.mpr fun _ => measurable_fst.eval.mul measurable_snd.eval⟩
end Mul
/-- A version of `measurable_div_const` that assumes `MeasurableMul` instead of
`MeasurableDiv`. This can be nice to avoid unnecessary type-class assumptions. -/
@[to_additive "A version of `measurable_sub_const` that assumes `MeasurableAdd` instead of
`MeasurableSub`. This can be nice to avoid unnecessary type-class assumptions."]
theorem measurable_div_const' {G : Type*} [DivInvMonoid G] [MeasurableSpace G] [MeasurableMul G]
(g : G) : Measurable fun h => h / g := by simp_rw [div_eq_mul_inv, measurable_mul_const]
/-- This class assumes that the map `β × γ → β` given by `(x, y) ↦ x ^ y` is measurable. -/
class MeasurablePow (β γ : Type*) [MeasurableSpace β] [MeasurableSpace γ] [Pow β γ] : Prop where
measurable_pow : Measurable fun p : β × γ => p.1 ^ p.2
export MeasurablePow (measurable_pow)
/-- `Monoid.Pow` is measurable. -/
instance Monoid.measurablePow (M : Type*) [Monoid M] [MeasurableSpace M] [MeasurableMul₂ M] :
MeasurablePow M ℕ :=
⟨measurable_from_prod_countable fun n => by
induction' n with n ih
· simp only [pow_zero, ← Pi.one_def, measurable_one]
· simp only [pow_succ]
exact ih.mul measurable_id⟩
section Pow
variable {β γ α : Type*} [MeasurableSpace β] [MeasurableSpace γ] [Pow β γ] [MeasurablePow β γ]
{m : MeasurableSpace α} {μ : Measure α} {f : α → β} {g : α → γ}
@[aesop safe 20 apply (rule_sets := [Measurable]), fun_prop]
theorem Measurable.pow (hf : Measurable f) (hg : Measurable g) : Measurable fun x => f x ^ g x :=
measurable_pow.comp (hf.prodMk hg)
@[aesop safe 20 apply (rule_sets := [Measurable]), fun_prop]
theorem AEMeasurable.pow (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (fun x => f x ^ g x) μ :=
measurable_pow.comp_aemeasurable (hf.prodMk hg)
@[fun_prop, measurability]
theorem Measurable.pow_const (hf : Measurable f) (c : γ) : Measurable fun x => f x ^ c :=
hf.pow measurable_const
@[fun_prop, measurability]
theorem AEMeasurable.pow_const (hf : AEMeasurable f μ) (c : γ) :
AEMeasurable (fun x => f x ^ c) μ :=
hf.pow aemeasurable_const
@[fun_prop, measurability]
theorem Measurable.const_pow (hg : Measurable g) (c : β) : Measurable fun x => c ^ g x :=
measurable_const.pow hg
@[fun_prop, measurability]
theorem AEMeasurable.const_pow (hg : AEMeasurable g μ) (c : β) :
AEMeasurable (fun x => c ^ g x) μ :=
aemeasurable_const.pow hg
end Pow
/-- We say that a type has `MeasurableSub` if `(c - ·)` and `(· - c)` are measurable
functions. For a typeclass assuming measurability of `uncurry (-)` see `MeasurableSub₂`. -/
class MeasurableSub (G : Type*) [MeasurableSpace G] [Sub G] : Prop where
measurable_const_sub : ∀ c : G, Measurable (c - ·)
measurable_sub_const : ∀ c : G, Measurable (· - c)
export MeasurableSub (measurable_const_sub measurable_sub_const)
/-- We say that a type has `MeasurableSub₂` if `uncurry (· - ·)` is a measurable functions.
For a typeclass assuming measurability of `(c - ·)` and `(· - c)` see `MeasurableSub`. -/
class MeasurableSub₂ (G : Type*) [MeasurableSpace G] [Sub G] : Prop where
measurable_sub : Measurable fun p : G × G => p.1 - p.2
export MeasurableSub₂ (measurable_sub)
/-- We say that a type has `MeasurableDiv` if `(c / ·)` and `(· / c)` are measurable functions.
For a typeclass assuming measurability of `uncurry (· / ·)` see `MeasurableDiv₂`. -/
@[to_additive]
class MeasurableDiv (G₀ : Type*) [MeasurableSpace G₀] [Div G₀] : Prop where
measurable_const_div : ∀ c : G₀, Measurable (c / ·)
measurable_div_const : ∀ c : G₀, Measurable (· / c)
export MeasurableDiv (measurable_const_div measurable_div_const)
/-- We say that a type has `MeasurableDiv₂` if `uncurry (· / ·)` is a measurable functions.
For a typeclass assuming measurability of `(c / ·)` and `(· / c)` see `MeasurableDiv`. -/
@[to_additive MeasurableSub₂]
class MeasurableDiv₂ (G₀ : Type*) [MeasurableSpace G₀] [Div G₀] : Prop where
measurable_div : Measurable fun p : G₀ × G₀ => p.1 / p.2
export MeasurableDiv₂ (measurable_div)
section Div
variable {G α β : Type*} [MeasurableSpace G] [Div G] {m : MeasurableSpace α}
{mβ : MeasurableSpace β} {f g : α → G} {μ : Measure α}
@[to_additive (attr := fun_prop, measurability)]
theorem Measurable.const_div [MeasurableDiv G] (hf : Measurable f) (c : G) :
Measurable fun x => c / f x :=
(MeasurableDiv.measurable_const_div c).comp hf
@[to_additive (attr := fun_prop, measurability)]
theorem AEMeasurable.const_div [MeasurableDiv G] (hf : AEMeasurable f μ) (c : G) :
AEMeasurable (fun x => c / f x) μ :=
(MeasurableDiv.measurable_const_div c).comp_aemeasurable hf
@[to_additive (attr := fun_prop, measurability)]
theorem Measurable.div_const [MeasurableDiv G] (hf : Measurable f) (c : G) :
Measurable fun x => f x / c :=
(MeasurableDiv.measurable_div_const c).comp hf
@[to_additive (attr := fun_prop, measurability)]
theorem AEMeasurable.div_const [MeasurableDiv G] (hf : AEMeasurable f μ) (c : G) :
AEMeasurable (fun x => f x / c) μ :=
(MeasurableDiv.measurable_div_const c).comp_aemeasurable hf
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem Measurable.div [MeasurableDiv₂ G] (hf : Measurable f) (hg : Measurable g) :
Measurable fun a => f a / g a :=
measurable_div.comp (hf.prodMk hg)
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
lemma Measurable.div' [MeasurableDiv₂ G] {f g : α → β → G} {h : α → β} (hf : Measurable ↿f)
(hg : Measurable ↿g) (hh : Measurable h) : Measurable fun a ↦ (f a / g a) (h a) := by
simp; fun_prop
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem AEMeasurable.div' [MeasurableDiv₂ G] (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (f / g) μ :=
measurable_div.comp_aemeasurable (hf.prodMk hg)
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem AEMeasurable.div [MeasurableDiv₂ G] (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (fun a => f a / g a) μ :=
measurable_div.comp_aemeasurable (hf.prodMk hg)
@[to_additive]
instance (priority := 100) MeasurableDiv₂.toMeasurableDiv [MeasurableDiv₂ G] :
MeasurableDiv G :=
⟨fun _ => measurable_const.div measurable_id, fun _ => measurable_id.div measurable_const⟩
@[to_additive]
instance Pi.measurableDiv {ι : Type*} {α : ι → Type*} [∀ i, Div (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableDiv (α i)] : MeasurableDiv (∀ i, α i) :=
⟨fun _ => measurable_pi_iff.mpr fun i => (measurable_pi_apply i).const_div _, fun _ =>
measurable_pi_iff.mpr fun i => (measurable_pi_apply i).div_const _⟩
@[to_additive Pi.measurableSub₂]
instance Pi.measurableDiv₂ {ι : Type*} {α : ι → Type*} [∀ i, Div (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableDiv₂ (α i)] : MeasurableDiv₂ (∀ i, α i) :=
⟨measurable_pi_iff.mpr fun _ => measurable_fst.eval.div measurable_snd.eval⟩
@[measurability]
theorem measurableSet_eq_fun {m : MeasurableSpace α} {E} [MeasurableSpace E] [AddGroup E]
[MeasurableSingletonClass E] [MeasurableSub₂ E] {f g : α → E} (hf : Measurable f)
(hg : Measurable g) : MeasurableSet { x | f x = g x } := by
suffices h_set_eq : { x : α | f x = g x } = { x | (f - g) x = (0 : E) } by
rw [h_set_eq]
exact (hf.sub hg) measurableSet_eq
ext
simp_rw [Set.mem_setOf_eq, Pi.sub_apply, sub_eq_zero]
@[measurability]
lemma measurableSet_eq_fun' {β : Type*} [AddCommMonoid β] [PartialOrder β]
[CanonicallyOrderedAdd β] [Sub β] [OrderedSub β]
{_ : MeasurableSpace β} [MeasurableSub₂ β] [MeasurableSingletonClass β]
{f g : α → β} (hf : Measurable f) (hg : Measurable g) :
MeasurableSet {x | f x = g x} := by
have : {a | f a = g a} = {a | (f - g) a = 0} ∩ {a | (g - f) a = 0} := by
ext
simp only [Set.mem_setOf_eq, Pi.sub_apply, tsub_eq_zero_iff_le, Set.mem_inter_iff]
exact ⟨fun h ↦ ⟨h.le, h.symm.le⟩, fun h ↦ le_antisymm h.1 h.2⟩
rw [this]
exact ((hf.sub hg) (measurableSet_singleton 0)).inter ((hg.sub hf) (measurableSet_singleton 0))
theorem nullMeasurableSet_eq_fun {E} [MeasurableSpace E] [AddGroup E] [MeasurableSingletonClass E]
[MeasurableSub₂ E] {f g : α → E} (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
NullMeasurableSet { x | f x = g x } μ := by
apply (measurableSet_eq_fun hf.measurable_mk hg.measurable_mk).nullMeasurableSet.congr
filter_upwards [hf.ae_eq_mk, hg.ae_eq_mk] with x hfx hgx
change (hf.mk f x = hg.mk g x) = (f x = g x)
simp only [hfx, hgx]
theorem measurableSet_eq_fun_of_countable {m : MeasurableSpace α} {E} [MeasurableSpace E]
[MeasurableSingletonClass E] [Countable E] {f g : α → E} (hf : Measurable f)
(hg : Measurable g) : MeasurableSet { x | f x = g x } := by
have : { x | f x = g x } = ⋃ j, { x | f x = j } ∩ { x | g x = j } := by
ext1 x
simp only [Set.mem_setOf_eq, Set.mem_iUnion, Set.mem_inter_iff, exists_eq_right']
rw [this]
refine MeasurableSet.iUnion fun j => MeasurableSet.inter ?_ ?_
· exact hf (measurableSet_singleton j)
· exact hg (measurableSet_singleton j)
theorem ae_eq_trim_of_measurable {α E} {m m0 : MeasurableSpace α} {μ : Measure α}
[MeasurableSpace E] [AddGroup E] [MeasurableSingletonClass E] [MeasurableSub₂ E]
(hm : m ≤ m0) {f g : α → E} (hf : Measurable[m] f) (hg : Measurable[m] g) (hfg : f =ᵐ[μ] g) :
f =ᵐ[μ.trim hm] g := by
rwa [Filter.EventuallyEq, ae_iff, trim_measurableSet_eq hm _]
exact @MeasurableSet.compl α _ m (@measurableSet_eq_fun α m E _ _ _ _ _ _ hf hg)
end Div
/-- We say that a type has `MeasurableNeg` if `x ↦ -x` is a measurable function. -/
class MeasurableNeg (G : Type*) [Neg G] [MeasurableSpace G] : Prop where
measurable_neg : Measurable (Neg.neg : G → G)
/-- We say that a type has `MeasurableInv` if `x ↦ x⁻¹` is a measurable function. -/
@[to_additive]
class MeasurableInv (G : Type*) [Inv G] [MeasurableSpace G] : Prop where
measurable_inv : Measurable (Inv.inv : G → G)
export MeasurableInv (measurable_inv)
export MeasurableNeg (measurable_neg)
@[to_additive]
instance (priority := 100) measurableDiv_of_mul_inv (G : Type*) [MeasurableSpace G]
[DivInvMonoid G] [MeasurableMul G] [MeasurableInv G] : MeasurableDiv G where
measurable_const_div c := by
convert measurable_inv.const_mul c using 1
ext1
apply div_eq_mul_inv
measurable_div_const c := by
convert measurable_id.mul_const c⁻¹ using 1
ext1
apply div_eq_mul_inv
section Inv
variable {G α : Type*} [Inv G] [MeasurableSpace G] [MeasurableInv G] {m : MeasurableSpace α}
{f : α → G} {μ : Measure α}
@[to_additive (attr := fun_prop, measurability)]
theorem Measurable.inv (hf : Measurable f) : Measurable fun x => (f x)⁻¹ :=
measurable_inv.comp hf
@[to_additive (attr := fun_prop, measurability)]
theorem AEMeasurable.inv (hf : AEMeasurable f μ) : AEMeasurable (fun x => (f x)⁻¹) μ :=
measurable_inv.comp_aemeasurable hf
@[to_additive (attr := simp)]
theorem measurable_inv_iff {G : Type*} [InvolutiveInv G] [MeasurableSpace G] [MeasurableInv G]
{f : α → G} : (Measurable fun x => (f x)⁻¹) ↔ Measurable f :=
⟨fun h => by simpa only [inv_inv] using h.inv, fun h => h.inv⟩
@[to_additive (attr := simp)]
theorem aemeasurable_inv_iff {G : Type*} [InvolutiveInv G] [MeasurableSpace G] [MeasurableInv G]
{f : α → G} : AEMeasurable (fun x => (f x)⁻¹) μ ↔ AEMeasurable f μ :=
⟨fun h => by simpa only [inv_inv] using h.inv, fun h => h.inv⟩
@[deprecated (since := "2025-04-09")]
alias measurable_inv_iff₀ := measurable_inv_iff
@[deprecated (since := "2025-04-09")]
alias aemeasurable_inv_iff₀ := aemeasurable_inv_iff
@[to_additive]
instance Pi.measurableInv {ι : Type*} {α : ι → Type*} [∀ i, Inv (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableInv (α i)] : MeasurableInv (∀ i, α i) :=
⟨measurable_pi_iff.mpr fun i => (measurable_pi_apply i).inv⟩
@[to_additive]
theorem MeasurableSet.inv {s : Set G} (hs : MeasurableSet s) : MeasurableSet s⁻¹ :=
measurable_inv hs
@[to_additive]
theorem measurableEmbedding_inv [InvolutiveInv α] [MeasurableInv α] :
MeasurableEmbedding (Inv.inv (α := α)) :=
⟨inv_injective, measurable_inv, fun s hs ↦ s.image_inv_eq_inv ▸ hs.inv⟩
end Inv
@[to_additive]
theorem Measurable.mul_iff_right {G : Type*} [MeasurableSpace G] [MeasurableSpace α] [CommGroup G]
[MeasurableMul₂ G] [MeasurableInv G] {f g : α → G} (hf : Measurable f) :
Measurable (f * g) ↔ Measurable 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 AEMeasurable.mul_iff_right {G : Type*} [MeasurableSpace G] [MeasurableSpace α] [CommGroup G]
[MeasurableMul₂ G] [MeasurableInv G] {μ : Measure α} {f g : α → G} (hf : AEMeasurable f μ) :
AEMeasurable (f * g) μ ↔ AEMeasurable g μ :=
⟨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 Measurable.mul_iff_left {G : Type*} [MeasurableSpace G] [MeasurableSpace α] [CommGroup G]
[MeasurableMul₂ G] [MeasurableInv G] {f g : α → G} (hf : Measurable f) :
Measurable (g * f) ↔ Measurable g :=
mul_comm g f ▸ Measurable.mul_iff_right hf
@[to_additive]
theorem AEMeasurable.mul_iff_left {G : Type*} [MeasurableSpace G] [MeasurableSpace α] [CommGroup G]
[MeasurableMul₂ G] [MeasurableInv G] {μ : Measure α} {f g : α → G} (hf : AEMeasurable f μ) :
AEMeasurable (g * f) μ ↔ AEMeasurable g μ :=
mul_comm g f ▸ AEMeasurable.mul_iff_right hf
/-- `DivInvMonoid.Pow` is measurable. -/
instance DivInvMonoid.measurableZPow (G : Type u) [DivInvMonoid G] [MeasurableSpace G]
[MeasurableMul₂ G] [MeasurableInv G] : MeasurablePow G ℤ :=
⟨measurable_from_prod_countable fun n => by
rcases n with n | n
· simp_rw [Int.ofNat_eq_coe, zpow_natCast]
exact measurable_id.pow_const _
· simp_rw [zpow_negSucc]
exact (measurable_id.pow_const (n + 1)).inv⟩
@[to_additive]
instance (priority := 100) measurableDiv₂_of_mul_inv (G : Type*) [MeasurableSpace G]
[DivInvMonoid G] [MeasurableMul₂ G] [MeasurableInv G] : MeasurableDiv₂ G :=
⟨by
simp only [div_eq_mul_inv]
exact measurable_fst.mul measurable_snd.inv⟩
-- See note [lower instance priority]
instance (priority := 100) MeasurableDiv.toMeasurableInv [MeasurableSpace α] [Group α]
[MeasurableDiv α] : MeasurableInv α where
measurable_inv := by simpa using measurable_const_div (1 : α)
/-- We say that the action of `M` on `α` has `MeasurableConstVAdd` if for each `c` the map
`x ↦ c +ᵥ x` is a measurable function. -/
class MeasurableConstVAdd (M α : Type*) [VAdd M α] [MeasurableSpace α] : Prop where
measurable_const_vadd : ∀ c : M, Measurable (c +ᵥ · : α → α)
/-- We say that the action of `M` on `α` has `MeasurableConstSMul` if for each `c` the map
`x ↦ c • x` is a measurable function. -/
@[to_additive]
class MeasurableConstSMul (M α : Type*) [SMul M α] [MeasurableSpace α] : Prop where
measurable_const_smul : ∀ c : M, Measurable (c • · : α → α)
/-- We say that the action of `M` on `α` has `MeasurableVAdd` if for each `c` the map `x ↦ c +ᵥ x`
is a measurable function and for each `x` the map `c ↦ c +ᵥ x` is a measurable function. -/
class MeasurableVAdd (M α : Type*) [VAdd M α] [MeasurableSpace M] [MeasurableSpace α]
extends MeasurableConstVAdd M α where
measurable_vadd_const : ∀ x : α, Measurable (· +ᵥ x : M → α)
/-- We say that the action of `M` on `α` has `MeasurableSMul` if for each `c` the map `x ↦ c • x`
is a measurable function and for each `x` the map `c ↦ c • x` is a measurable function. -/
@[to_additive]
class MeasurableSMul (M α : Type*) [SMul M α] [MeasurableSpace M] [MeasurableSpace α]
extends MeasurableConstSMul M α where
measurable_smul_const : ∀ x : α, Measurable (· • x : M → α)
/-- We say that the action of `M` on `α` has `MeasurableVAdd₂` if the map
`(c, x) ↦ c +ᵥ x` is a measurable function. -/
class MeasurableVAdd₂ (M α : Type*) [VAdd M α] [MeasurableSpace M] [MeasurableSpace α] :
Prop where
measurable_vadd : Measurable (Function.uncurry (· +ᵥ ·) : M × α → α)
/-- We say that the action of `M` on `α` has `Measurable_SMul₂` if the map
`(c, x) ↦ c • x` is a measurable function. -/
@[to_additive MeasurableVAdd₂]
class MeasurableSMul₂ (M α : Type*) [SMul M α] [MeasurableSpace M] [MeasurableSpace α] :
Prop where
measurable_smul : Measurable (Function.uncurry (· • ·) : M × α → α)
export MeasurableConstVAdd (measurable_const_vadd)
export MeasurableConstSMul (measurable_const_smul)
export MeasurableVAdd (measurable_vadd_const)
export MeasurableSMul (measurable_smul_const)
export MeasurableSMul₂ (measurable_smul)
export MeasurableVAdd₂ (measurable_vadd)
@[to_additive]
instance measurableSMul_of_mul (M : Type*) [Mul M] [MeasurableSpace M] [MeasurableMul M] :
MeasurableSMul M M where
measurable_const_smul := measurable_id.const_mul
measurable_smul_const := measurable_id.mul_const
@[to_additive]
instance measurableSMul₂_of_mul (M : Type*) [Mul M] [MeasurableSpace M] [MeasurableMul₂ M] :
MeasurableSMul₂ M M :=
⟨measurable_mul⟩
@[to_additive]
instance Submonoid.instMeasurableConstSMul {M α} [MeasurableSpace α] [Monoid M] [MulAction M α]
[MeasurableConstSMul M α] (s : Submonoid M) : MeasurableConstSMul s α where
measurable_const_smul c := by simpa only using measurable_const_smul (c : M)
@[to_additive]
instance Submonoid.instMeasurableSMul {M α} [MeasurableSpace M] [MeasurableSpace α] [Monoid M]
[MulAction M α] [MeasurableSMul M α] (s : Submonoid M) : MeasurableSMul s α where
measurable_smul_const x := (measurable_smul_const (M := M) x).comp measurable_subtype_coe
@[to_additive]
instance Subgroup.instMeasurableConstSMul {G α} [MeasurableSpace α] [Group G] [MulAction G α]
[MeasurableConstSMul G α] (s : Subgroup G) : MeasurableConstSMul s α :=
s.toSubmonoid.instMeasurableConstSMul
@[to_additive]
instance Subgroup.instMeasurableSMul {G α} [MeasurableSpace G] [MeasurableSpace α] [Group G]
[MulAction G α] [MeasurableSMul G α] (s : Subgroup G) : MeasurableSMul s α :=
s.toSubmonoid.instMeasurableSMul
section SMul
variable {M X α β : Type*} [MeasurableSpace X] [SMul M X]
{m : MeasurableSpace α} {mβ : MeasurableSpace β} {μ : Measure α} {f : α → M} {g : α → X}
section MeasurableConstSMul
variable [MeasurableConstSMul M X]
@[to_additive (attr := fun_prop, measurability)]
lemma Measurable.const_smul (hg : Measurable g) (c : M) : Measurable (c • g) :=
(measurable_const_smul c).comp hg
/-- Compositional version of `Measurable.const_smul` for use by `fun_prop`. -/
@[to_additive (attr := fun_prop)
"Compositional version of `Measurable.const_vadd` for use by `fun_prop`."]
lemma Measurable.fun_const_smul {g : α → β → X} {h : α → β} (hg : Measurable ↿g) (hh : Measurable h)
(c : M) : Measurable fun a ↦ (c • g a) (h a) :=
(hg.comp <| measurable_id.prodMk hh).const_smul _
@[deprecated (since := "2025-04-23")] alias Measurable.const_smul' := Measurable.fun_const_smul
@[to_additive (attr := fun_prop, measurability)]
lemma AEMeasurable.fun_const_smul (hg : AEMeasurable g μ) (c : M) : AEMeasurable (c • g ·) μ :=
(measurable_const_smul c).comp_aemeasurable hg
@[deprecated (since := "2025-04-23")] alias AEMeasurable.const_smul' := AEMeasurable.fun_const_smul
@[to_additive (attr := fun_prop, measurability)]
lemma AEMeasurable.const_smul (hf : AEMeasurable g μ) (c : M) : AEMeasurable (c • g) μ :=
hf.fun_const_smul c
@[to_additive]
instance Pi.instMeasurableConstSMul {ι : Type*} {α : ι → Type*} [∀ i, SMul M (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableConstSMul M (α i)] :
MeasurableConstSMul M (∀ i, α i) where
measurable_const_smul _ := measurable_pi_iff.2 fun i ↦ (measurable_pi_apply i).const_smul _
/-- If a scalar is central, then its right action is measurable when its left action is. -/
@[to_additive]
nonrec instance MulOpposite.instMeasurableConstSMul [SMul M α] [SMul Mᵐᵒᵖ α] [IsCentralScalar M α]
[MeasurableConstSMul M α] : MeasurableConstSMul Mᵐᵒᵖ α where
measurable_const_smul := by simpa using measurable_const_smul
end MeasurableConstSMul
variable [MeasurableSpace M]
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem Measurable.smul [MeasurableSMul₂ M X] (hf : Measurable f) (hg : Measurable g) :
Measurable fun x => f x • g x :=
measurable_smul.comp (hf.prodMk hg)
/-- Compositional version of `Measurable.smul` for use by `fun_prop`. -/
@[to_additive (attr := fun_prop)
"Compositional version of `Measurable.vadd` for use by `fun_prop`."]
lemma Measurable.smul' [MeasurableSMul₂ M X] {f : α → β → M} {g : α → β → X} {h : α → β}
(hf : Measurable ↿f) (hg : Measurable ↿g) (hh : Measurable h) :
Measurable fun a ↦ (f a • g a) (h a) := by simp; fun_prop
@[to_additive (attr := fun_prop, aesop safe 20 apply (rule_sets := [Measurable]))]
theorem AEMeasurable.smul [MeasurableSMul₂ M X] {μ : Measure α} (hf : AEMeasurable f μ)
(hg : AEMeasurable g μ) : AEMeasurable (fun x => f x • g x) μ :=
MeasurableSMul₂.measurable_smul.comp_aemeasurable (hf.prodMk hg)
@[to_additive]
instance (priority := 100) MeasurableSMul₂.toMeasurableSMul [MeasurableSMul₂ M X] :
MeasurableSMul M X where
measurable_const_smul _ := measurable_const.smul measurable_id
measurable_smul_const _ := measurable_id.smul measurable_const
variable [MeasurableSMul M X]
@[to_additive (attr := fun_prop, measurability)]
theorem Measurable.smul_const (hf : Measurable f) (y : X) : Measurable fun x => f x • y :=
(MeasurableSMul.measurable_smul_const y).comp hf
@[to_additive (attr := fun_prop, measurability)]
theorem AEMeasurable.smul_const (hf : AEMeasurable f μ) (y : X) :
AEMeasurable (fun x => f x • y) μ :=
(MeasurableSMul.measurable_smul_const y).comp_aemeasurable hf
@[to_additive]
instance Pi.measurableSMul {ι : Type*} {α : ι → Type*} [∀ i, SMul M (α i)]
[∀ i, MeasurableSpace (α i)] [∀ i, MeasurableSMul M (α i)] :
MeasurableSMul M (∀ i, α i) where
measurable_smul_const _ := measurable_pi_iff.2 fun _ ↦ measurable_smul_const _
/-- `AddMonoid.SMul` is measurable. -/
instance AddMonoid.measurableSMul_nat₂ (M : Type*) [AddMonoid M] [MeasurableSpace M]
[MeasurableAdd₂ M] : MeasurableSMul₂ ℕ M :=
⟨by
suffices Measurable fun p : M × ℕ => p.2 • p.1 by apply this.comp measurable_swap
refine measurable_from_prod_countable fun n => ?_
induction' n with n ih
· simp only [zero_smul, ← Pi.zero_def, measurable_zero]
· simp only [succ_nsmul]
exact ih.add measurable_id⟩
/-- `SubNegMonoid.SMulInt` is measurable. -/
instance SubNegMonoid.measurableSMul_int₂ (M : Type*) [SubNegMonoid M] [MeasurableSpace M]
[MeasurableAdd₂ M] [MeasurableNeg M] : MeasurableSMul₂ ℤ M :=
⟨by
suffices Measurable fun p : M × ℤ => p.2 • p.1 by apply this.comp measurable_swap
refine measurable_from_prod_countable fun n => ?_
cases n with
| ofNat n =>
simp only [Int.ofNat_eq_coe, natCast_zsmul]
exact measurable_const_smul _
| negSucc n =>
simp only [negSucc_zsmul]
exact (measurable_const_smul _).neg⟩
end SMul
section IterateMulAct
variable {α : Type*} {_ : MeasurableSpace α} {f : α → α}
@[to_additive]
theorem Measurable.measurableSMul₂_iterateMulAct (h : Measurable f) :
MeasurableSMul₂ (IterateMulAct f) α where
measurable_smul :=
suffices Measurable fun p : α × IterateMulAct f ↦ f^[p.2.val] p.1 from this.comp measurable_swap
measurable_from_prod_countable fun n ↦ h.iterate n.val
@[to_additive (attr := simp)]
theorem measurableSMul_iterateMulAct : MeasurableSMul (IterateMulAct f) α ↔ Measurable f :=
⟨fun _ ↦ measurable_const_smul (IterateMulAct.mk (f := f) 1), fun h ↦
have := h.measurableSMul₂_iterateMulAct; inferInstance⟩
@[to_additive (attr := simp)]
theorem measurableSMul₂_iterateMulAct : MeasurableSMul₂ (IterateMulAct f) α ↔ Measurable f :=
⟨fun _ ↦ measurableSMul_iterateMulAct.mp inferInstance,
Measurable.measurableSMul₂_iterateMulAct⟩
end IterateMulAct
section MulAction
variable {G G₀ M β α : Type*} [MeasurableSpace β] [MeasurableSpace α] {f : α → β} {μ : Measure α}
section Group
variable {G : Type*} [Group G] [MulAction G β] [MeasurableConstSMul G β]
@[to_additive]
theorem measurable_const_smul_iff (c : G) : (Measurable fun x => c • f x) ↔ Measurable f :=
⟨fun h => by simpa [inv_smul_smul, Pi.smul_def] using h.const_smul c⁻¹, fun h => h.const_smul c⟩
@[to_additive]
theorem aemeasurable_const_smul_iff (c : G) :
AEMeasurable (fun x => c • f x) μ ↔ AEMeasurable f μ :=
⟨fun h => by simpa [inv_smul_smul, Pi.smul_def] using h.const_smul c⁻¹, fun h => h.const_smul c⟩
end Group
section Monoid
variable [Monoid M] [MulAction M β]
section MeasurableConstSMul
variable [MeasurableConstSMul M β]
@[to_additive]
instance Units.instMeasurableConstSMul : MeasurableConstSMul Mˣ β where
measurable_const_smul c := measurable_const_smul (c : M)
@[to_additive]
nonrec theorem IsUnit.measurable_const_smul_iff {c : M} (hc : IsUnit c) :
(Measurable fun x => c • f x) ↔ Measurable f :=
let ⟨u, hu⟩ := hc
hu ▸ measurable_const_smul_iff u
@[to_additive]
nonrec theorem IsUnit.aemeasurable_const_smul_iff {c : M} (hc : IsUnit c) :
AEMeasurable (fun x => c • f x) μ ↔ AEMeasurable f μ :=
let ⟨u, hu⟩ := hc
hu ▸ aemeasurable_const_smul_iff u
end MeasurableConstSMul
section MeasurableSMul
variable [MeasurableSpace M] [MeasurableSMul M β]
@[to_additive]
instance Units.instMeasurableSpace : MeasurableSpace Mˣ := .comap Units.val ‹_›
@[to_additive]
instance Units.measurableSMul : MeasurableSMul Mˣ β where
measurable_smul_const x :=
(measurable_smul_const x : Measurable fun c : M => c • x).comp MeasurableSpace.le_map_comap
end MeasurableSMul
end Monoid
section GroupWithZero
variable [GroupWithZero G₀] [MeasurableSpace G₀] [MulAction G₀ β] [MeasurableSMul G₀ β]
theorem measurable_const_smul_iff₀ {c : G₀} (hc : c ≠ 0) :
(Measurable fun x => c • f x) ↔ Measurable f :=
(IsUnit.mk0 c hc).measurable_const_smul_iff
theorem aemeasurable_const_smul_iff₀ {c : G₀} (hc : c ≠ 0) :
AEMeasurable (fun x => c • f x) μ ↔ AEMeasurable f μ :=
(IsUnit.mk0 c hc).aemeasurable_const_smul_iff
end GroupWithZero
end MulAction
/-!
### Opposite monoid
-/
section Opposite
open MulOpposite
@[to_additive]
instance MulOpposite.instMeasurableSpace {α : Type*} [h : MeasurableSpace α] :
MeasurableSpace αᵐᵒᵖ :=
MeasurableSpace.map op h
| @[to_additive]
theorem measurable_mul_op {α : Type*} [MeasurableSpace α] : Measurable (op : α → αᵐᵒᵖ) := fun _ =>
id
| Mathlib/MeasureTheory/Group/Arithmetic.lean | 765 | 767 |
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.TwoDim
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic
/-!
# Oriented angles.
This file defines oriented angles in real inner product spaces.
## Main definitions
* `Orientation.oangle` is the oriented angle between two vectors with respect to an orientation.
## Implementation notes
The definitions here use the `Real.angle` type, angles modulo `2 * π`. For some purposes,
angles modulo `π` are more convenient, because results are true for such angles with less
configuration dependence. Results that are only equalities modulo `π` can be represented
modulo `2 * π` as equalities of `(2 : ℤ) • θ`.
## References
* Evan Chen, Euclidean Geometry in Mathematical Olympiads.
-/
noncomputable section
open Module Complex
open scoped Real RealInnerProductSpace ComplexConjugate
namespace Orientation
attribute [local instance] Complex.finrank_real_complex_fact
variable {V V' : Type*}
variable [NormedAddCommGroup V] [NormedAddCommGroup V']
variable [InnerProductSpace ℝ V] [InnerProductSpace ℝ V']
variable [Fact (finrank ℝ V = 2)] [Fact (finrank ℝ V' = 2)] (o : Orientation ℝ V (Fin 2))
local notation "ω" => o.areaForm
/-- The oriented angle from `x` to `y`, modulo `2 * π`. If either vector is 0, this is 0.
See `InnerProductGeometry.angle` for the corresponding unoriented angle definition. -/
def oangle (x y : V) : Real.Angle :=
Complex.arg (o.kahler x y)
/-- Oriented angles are continuous when the vectors involved are nonzero. -/
@[fun_prop]
theorem continuousAt_oangle {x : V × V} (hx1 : x.1 ≠ 0) (hx2 : x.2 ≠ 0) :
ContinuousAt (fun y : V × V => o.oangle y.1 y.2) x := by
refine (Complex.continuousAt_arg_coe_angle ?_).comp ?_
· exact o.kahler_ne_zero hx1 hx2
exact ((continuous_ofReal.comp continuous_inner).add
((continuous_ofReal.comp o.areaForm'.continuous₂).mul continuous_const)).continuousAt
/-- If the first vector passed to `oangle` is 0, the result is 0. -/
@[simp]
theorem oangle_zero_left (x : V) : o.oangle 0 x = 0 := by simp [oangle]
/-- If the second vector passed to `oangle` is 0, the result is 0. -/
@[simp]
theorem oangle_zero_right (x : V) : o.oangle x 0 = 0 := by simp [oangle]
/-- If the two vectors passed to `oangle` are the same, the result is 0. -/
@[simp]
theorem oangle_self (x : V) : o.oangle x x = 0 := by
rw [oangle, kahler_apply_self, ← ofReal_pow]
convert QuotientAddGroup.mk_zero (AddSubgroup.zmultiples (2 * π))
apply arg_ofReal_of_nonneg
positivity
/-- If the angle between two vectors is nonzero, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : x ≠ 0 := by
rintro rfl; simp at h
/-- If the angle between two vectors is nonzero, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : y ≠ 0 := by
rintro rfl; simp at h
/-- If the angle between two vectors is nonzero, the vectors are not equal. -/
theorem ne_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : x ≠ y := by
rintro rfl; simp at h
/-- If the angle between two vectors is `π`, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π`, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π`, the vectors are not equal. -/
theorem ne_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : x ≠ y :=
o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π / 2`, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π / 2`, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π / 2`, the vectors are not equal. -/
theorem ne_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : x ≠ y :=
o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `-π / 2`, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) :
x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `-π / 2`, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) :
y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `-π / 2`, the vectors are not equal. -/
theorem ne_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) : x ≠ y :=
o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the sign of the angle between two vectors is nonzero, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
/-- If the sign of the angle between two vectors is nonzero, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
/-- If the sign of the angle between two vectors is nonzero, the vectors are not equal. -/
theorem ne_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : x ≠ y :=
o.ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
/-- If the sign of the angle between two vectors is positive, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : x ≠ 0 :=
o.left_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is positive, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : y ≠ 0 :=
o.right_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is positive, the vectors are not equal. -/
theorem ne_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : x ≠ y :=
o.ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is negative, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : x ≠ 0 :=
o.left_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is negative, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : y ≠ 0 :=
o.right_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is negative, the vectors are not equal. -/
theorem ne_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : x ≠ y :=
o.ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- Swapping the two vectors passed to `oangle` negates the angle. -/
theorem oangle_rev (x y : V) : o.oangle y x = -o.oangle x y := by
simp only [oangle, o.kahler_swap y x, Complex.arg_conj_coe_angle]
/-- Adding the angles between two vectors in each order results in 0. -/
@[simp]
theorem oangle_add_oangle_rev (x y : V) : o.oangle x y + o.oangle y x = 0 := by
simp [o.oangle_rev y x]
/-- Negating the first vector passed to `oangle` adds `π` to the angle. -/
theorem oangle_neg_left {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
o.oangle (-x) y = o.oangle x y + π := by
simp only [oangle, map_neg]
convert Complex.arg_neg_coe_angle _
exact o.kahler_ne_zero hx hy
/-- Negating the second vector passed to `oangle` adds `π` to the angle. -/
theorem oangle_neg_right {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
o.oangle x (-y) = o.oangle x y + π := by
simp only [oangle, map_neg]
convert Complex.arg_neg_coe_angle _
exact o.kahler_ne_zero hx hy
/-- Negating the first vector passed to `oangle` does not change twice the angle. -/
@[simp]
theorem two_zsmul_oangle_neg_left (x y : V) :
(2 : ℤ) • o.oangle (-x) y = (2 : ℤ) • o.oangle x y := by
by_cases hx : x = 0
· simp [hx]
· by_cases hy : y = 0
· simp [hy]
· simp [o.oangle_neg_left hx hy]
/-- Negating the second vector passed to `oangle` does not change twice the angle. -/
@[simp]
theorem two_zsmul_oangle_neg_right (x y : V) :
(2 : ℤ) • o.oangle x (-y) = (2 : ℤ) • o.oangle x y := by
by_cases hx : x = 0
· simp [hx]
· by_cases hy : y = 0
· simp [hy]
· simp [o.oangle_neg_right hx hy]
/-- Negating both vectors passed to `oangle` does not change the angle. -/
@[simp]
theorem oangle_neg_neg (x y : V) : o.oangle (-x) (-y) = o.oangle x y := by simp [oangle]
/-- Negating the first vector produces the same angle as negating the second vector. -/
theorem oangle_neg_left_eq_neg_right (x y : V) : o.oangle (-x) y = o.oangle x (-y) := by
rw [← neg_neg y, oangle_neg_neg, neg_neg]
/-- The angle between the negation of a nonzero vector and that vector is `π`. -/
@[simp]
theorem oangle_neg_self_left {x : V} (hx : x ≠ 0) : o.oangle (-x) x = π := by
simp [oangle_neg_left, hx]
/-- The angle between a nonzero vector and its negation is `π`. -/
@[simp]
theorem oangle_neg_self_right {x : V} (hx : x ≠ 0) : o.oangle x (-x) = π := by
simp [oangle_neg_right, hx]
/-- Twice the angle between the negation of a vector and that vector is 0. -/
theorem two_zsmul_oangle_neg_self_left (x : V) : (2 : ℤ) • o.oangle (-x) x = 0 := by
by_cases hx : x = 0 <;> simp [hx]
/-- Twice the angle between a vector and its negation is 0. -/
theorem two_zsmul_oangle_neg_self_right (x : V) : (2 : ℤ) • o.oangle x (-x) = 0 := by
by_cases hx : x = 0 <;> simp [hx]
/-- Adding the angles between two vectors in each order, with the first vector in each angle
negated, results in 0. -/
@[simp]
theorem oangle_add_oangle_rev_neg_left (x y : V) : o.oangle (-x) y + o.oangle (-y) x = 0 := by
rw [oangle_neg_left_eq_neg_right, oangle_rev, neg_add_cancel]
/-- Adding the angles between two vectors in each order, with the second vector in each angle
negated, results in 0. -/
@[simp]
theorem oangle_add_oangle_rev_neg_right (x y : V) : o.oangle x (-y) + o.oangle y (-x) = 0 := by
rw [o.oangle_rev (-x), oangle_neg_left_eq_neg_right, add_neg_cancel]
/-- Multiplying the first vector passed to `oangle` by a positive real does not change the
angle. -/
@[simp]
theorem oangle_smul_left_of_pos (x y : V) {r : ℝ} (hr : 0 < r) :
o.oangle (r • x) y = o.oangle x y := by simp [oangle, Complex.arg_real_mul _ hr]
/-- Multiplying the second vector passed to `oangle` by a positive real does not change the
angle. -/
@[simp]
theorem oangle_smul_right_of_pos (x y : V) {r : ℝ} (hr : 0 < r) :
o.oangle x (r • y) = o.oangle x y := by simp [oangle, Complex.arg_real_mul _ hr]
/-- Multiplying the first vector passed to `oangle` by a negative real produces the same angle
as negating that vector. -/
@[simp]
theorem oangle_smul_left_of_neg (x y : V) {r : ℝ} (hr : r < 0) :
o.oangle (r • x) y = o.oangle (-x) y := by
rw [← neg_neg r, neg_smul, ← smul_neg, o.oangle_smul_left_of_pos _ _ (neg_pos_of_neg hr)]
/-- Multiplying the second vector passed to `oangle` by a negative real produces the same angle
as negating that vector. -/
@[simp]
theorem oangle_smul_right_of_neg (x y : V) {r : ℝ} (hr : r < 0) :
o.oangle x (r • y) = o.oangle x (-y) := by
rw [← neg_neg r, neg_smul, ← smul_neg, o.oangle_smul_right_of_pos _ _ (neg_pos_of_neg hr)]
/-- The angle between a nonnegative multiple of a vector and that vector is 0. -/
@[simp]
theorem oangle_smul_left_self_of_nonneg (x : V) {r : ℝ} (hr : 0 ≤ r) : o.oangle (r • x) x = 0 := by
rcases hr.lt_or_eq with (h | h)
· simp [h]
· simp [h.symm]
/-- The angle between a vector and a nonnegative multiple of that vector is 0. -/
@[simp]
theorem oangle_smul_right_self_of_nonneg (x : V) {r : ℝ} (hr : 0 ≤ r) : o.oangle x (r • x) = 0 := by
rcases hr.lt_or_eq with (h | h)
· simp [h]
· simp [h.symm]
/-- The angle between two nonnegative multiples of the same vector is 0. -/
@[simp]
theorem oangle_smul_smul_self_of_nonneg (x : V) {r₁ r₂ : ℝ} (hr₁ : 0 ≤ r₁) (hr₂ : 0 ≤ r₂) :
o.oangle (r₁ • x) (r₂ • x) = 0 := by
rcases hr₁.lt_or_eq with (h | h)
· simp [h, hr₂]
· simp [h.symm]
/-- Multiplying the first vector passed to `oangle` by a nonzero real does not change twice the
angle. -/
@[simp]
theorem two_zsmul_oangle_smul_left_of_ne_zero (x y : V) {r : ℝ} (hr : r ≠ 0) :
(2 : ℤ) • o.oangle (r • x) y = (2 : ℤ) • o.oangle x y := by
rcases hr.lt_or_lt with (h | h) <;> simp [h]
/-- Multiplying the second vector passed to `oangle` by a nonzero real does not change twice the
angle. -/
@[simp]
theorem two_zsmul_oangle_smul_right_of_ne_zero (x y : V) {r : ℝ} (hr : r ≠ 0) :
(2 : ℤ) • o.oangle x (r • y) = (2 : ℤ) • o.oangle x y := by
rcases hr.lt_or_lt with (h | h) <;> simp [h]
/-- Twice the angle between a multiple of a vector and that vector is 0. -/
@[simp]
theorem two_zsmul_oangle_smul_left_self (x : V) {r : ℝ} : (2 : ℤ) • o.oangle (r • x) x = 0 := by
rcases lt_or_le r 0 with (h | h) <;> simp [h]
/-- Twice the angle between a vector and a multiple of that vector is 0. -/
@[simp]
theorem two_zsmul_oangle_smul_right_self (x : V) {r : ℝ} : (2 : ℤ) • o.oangle x (r • x) = 0 := by
rcases lt_or_le r 0 with (h | h) <;> simp [h]
/-- Twice the angle between two multiples of a vector is 0. -/
@[simp]
theorem two_zsmul_oangle_smul_smul_self (x : V) {r₁ r₂ : ℝ} :
(2 : ℤ) • o.oangle (r₁ • x) (r₂ • x) = 0 := by by_cases h : r₁ = 0 <;> simp [h]
/-- If the spans of two vectors are equal, twice angles with those vectors on the left are
equal. -/
theorem two_zsmul_oangle_left_of_span_eq {x y : V} (z : V) (h : (ℝ ∙ x) = ℝ ∙ y) :
(2 : ℤ) • o.oangle x z = (2 : ℤ) • o.oangle y z := by
rw [Submodule.span_singleton_eq_span_singleton] at h
rcases h with ⟨r, rfl⟩
exact (o.two_zsmul_oangle_smul_left_of_ne_zero _ _ (Units.ne_zero _)).symm
/-- If the spans of two vectors are equal, twice angles with those vectors on the right are
equal. -/
theorem two_zsmul_oangle_right_of_span_eq (x : V) {y z : V} (h : (ℝ ∙ y) = ℝ ∙ z) :
(2 : ℤ) • o.oangle x y = (2 : ℤ) • o.oangle x z := by
rw [Submodule.span_singleton_eq_span_singleton] at h
rcases h with ⟨r, rfl⟩
exact (o.two_zsmul_oangle_smul_right_of_ne_zero _ _ (Units.ne_zero _)).symm
/-- If the spans of two pairs of vectors are equal, twice angles between those vectors are
equal. -/
theorem two_zsmul_oangle_of_span_eq_of_span_eq {w x y z : V} (hwx : (ℝ ∙ w) = ℝ ∙ x)
(hyz : (ℝ ∙ y) = ℝ ∙ z) : (2 : ℤ) • o.oangle w y = (2 : ℤ) • o.oangle x z := by
rw [o.two_zsmul_oangle_left_of_span_eq y hwx, o.two_zsmul_oangle_right_of_span_eq x hyz]
/-- The oriented angle between two vectors is zero if and only if the angle with the vectors
swapped is zero. -/
theorem oangle_eq_zero_iff_oangle_rev_eq_zero {x y : V} : o.oangle x y = 0 ↔ o.oangle y x = 0 := by
rw [oangle_rev, neg_eq_zero]
/-- The oriented angle between two vectors is zero if and only if they are on the same ray. -/
theorem oangle_eq_zero_iff_sameRay {x y : V} : o.oangle x y = 0 ↔ SameRay ℝ x y := by
rw [oangle, kahler_apply_apply, Complex.arg_coe_angle_eq_iff_eq_toReal, Real.Angle.toReal_zero,
Complex.arg_eq_zero_iff]
simpa using o.nonneg_inner_and_areaForm_eq_zero_iff_sameRay x y
/-- The oriented angle between two vectors is `π` if and only if the angle with the vectors
swapped is `π`. -/
theorem oangle_eq_pi_iff_oangle_rev_eq_pi {x y : V} : o.oangle x y = π ↔ o.oangle y x = π := by
rw [oangle_rev, neg_eq_iff_eq_neg, Real.Angle.neg_coe_pi]
/-- The oriented angle between two vectors is `π` if and only they are nonzero and the first is
on the same ray as the negation of the second. -/
theorem oangle_eq_pi_iff_sameRay_neg {x y : V} :
o.oangle x y = π ↔ x ≠ 0 ∧ y ≠ 0 ∧ SameRay ℝ x (-y) := by
rw [← o.oangle_eq_zero_iff_sameRay]
constructor
· intro h
by_cases hx : x = 0; · simp [hx, Real.Angle.pi_ne_zero.symm] at h
by_cases hy : y = 0; · simp [hy, Real.Angle.pi_ne_zero.symm] at h
refine ⟨hx, hy, ?_⟩
rw [o.oangle_neg_right hx hy, h, Real.Angle.coe_pi_add_coe_pi]
· rintro ⟨hx, hy, h⟩
rwa [o.oangle_neg_right hx hy, ← Real.Angle.sub_coe_pi_eq_add_coe_pi, sub_eq_zero] at h
/-- The oriented angle between two vectors is zero or `π` if and only if those two vectors are
not linearly independent. -/
theorem oangle_eq_zero_or_eq_pi_iff_not_linearIndependent {x y : V} :
o.oangle x y = 0 ∨ o.oangle x y = π ↔ ¬LinearIndependent ℝ ![x, y] := by
rw [oangle_eq_zero_iff_sameRay, oangle_eq_pi_iff_sameRay_neg,
sameRay_or_ne_zero_and_sameRay_neg_iff_not_linearIndependent]
/-- The oriented angle between two vectors is zero or `π` if and only if the first vector is zero
or the second is a multiple of the first. -/
theorem oangle_eq_zero_or_eq_pi_iff_right_eq_smul {x y : V} :
o.oangle x y = 0 ∨ o.oangle x y = π ↔ x = 0 ∨ ∃ r : ℝ, y = r • x := by
rw [oangle_eq_zero_iff_sameRay, oangle_eq_pi_iff_sameRay_neg]
refine ⟨fun h => ?_, fun h => ?_⟩
· rcases h with (h | ⟨-, -, h⟩)
· by_cases hx : x = 0; · simp [hx]
obtain ⟨r, -, rfl⟩ := h.exists_nonneg_left hx
exact Or.inr ⟨r, rfl⟩
· by_cases hx : x = 0; · simp [hx]
obtain ⟨r, -, hy⟩ := h.exists_nonneg_left hx
refine Or.inr ⟨-r, ?_⟩
simp [hy]
· rcases h with (rfl | ⟨r, rfl⟩); · simp
by_cases hx : x = 0; · simp [hx]
rcases lt_trichotomy r 0 with (hr | hr | hr)
· rw [← neg_smul]
exact Or.inr ⟨hx, smul_ne_zero hr.ne hx,
SameRay.sameRay_pos_smul_right x (Left.neg_pos_iff.2 hr)⟩
· simp [hr]
· exact Or.inl (SameRay.sameRay_pos_smul_right x hr)
/-- The oriented angle between two vectors is not zero or `π` if and only if those two vectors
are linearly independent. -/
theorem oangle_ne_zero_and_ne_pi_iff_linearIndependent {x y : V} :
o.oangle x y ≠ 0 ∧ o.oangle x y ≠ π ↔ LinearIndependent ℝ ![x, y] := by
rw [← not_or, ← not_iff_not, Classical.not_not,
oangle_eq_zero_or_eq_pi_iff_not_linearIndependent]
/-- Two vectors are equal if and only if they have equal norms and zero angle between them. -/
theorem eq_iff_norm_eq_and_oangle_eq_zero (x y : V) : x = y ↔ ‖x‖ = ‖y‖ ∧ o.oangle x y = 0 := by
rw [oangle_eq_zero_iff_sameRay]
constructor
· rintro rfl
simp; rfl
· rcases eq_or_ne y 0 with (rfl | hy)
· simp
rintro ⟨h₁, h₂⟩
obtain ⟨r, hr, rfl⟩ := h₂.exists_nonneg_right hy
have : ‖y‖ ≠ 0 := by simpa using hy
obtain rfl : r = 1 := by
apply mul_right_cancel₀ this
simpa [norm_smul, abs_of_nonneg hr] using h₁
simp
/-- Two vectors with equal norms are equal if and only if they have zero angle between them. -/
theorem eq_iff_oangle_eq_zero_of_norm_eq {x y : V} (h : ‖x‖ = ‖y‖) : x = y ↔ o.oangle x y = 0 :=
⟨fun he => ((o.eq_iff_norm_eq_and_oangle_eq_zero x y).1 he).2, fun ha =>
(o.eq_iff_norm_eq_and_oangle_eq_zero x y).2 ⟨h, ha⟩⟩
/-- Two vectors with zero angle between them are equal if and only if they have equal norms. -/
theorem eq_iff_norm_eq_of_oangle_eq_zero {x y : V} (h : o.oangle x y = 0) : x = y ↔ ‖x‖ = ‖y‖ :=
⟨fun he => ((o.eq_iff_norm_eq_and_oangle_eq_zero x y).1 he).1, fun hn =>
(o.eq_iff_norm_eq_and_oangle_eq_zero x y).2 ⟨hn, h⟩⟩
/-- Given three nonzero vectors, the angle between the first and the second plus the angle
between the second and the third equals the angle between the first and the third. -/
@[simp]
theorem oangle_add {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle x y + o.oangle y z = o.oangle x z := by
simp_rw [oangle]
rw [← Complex.arg_mul_coe_angle, o.kahler_mul y x z]
· congr 1
exact mod_cast Complex.arg_real_mul _ (by positivity : 0 < ‖y‖ ^ 2)
· exact o.kahler_ne_zero hx hy
· exact o.kahler_ne_zero hy hz
/-- Given three nonzero vectors, the angle between the second and the third plus the angle
between the first and the second equals the angle between the first and the third. -/
@[simp]
theorem oangle_add_swap {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle y z + o.oangle x y = o.oangle x z := by rw [add_comm, o.oangle_add hx hy hz]
/-- Given three nonzero vectors, the angle between the first and the third minus the angle
between the first and the second equals the angle between the second and the third. -/
@[simp]
theorem oangle_sub_left {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle x z - o.oangle x y = o.oangle y z := by
rw [sub_eq_iff_eq_add, o.oangle_add_swap hx hy hz]
/-- Given three nonzero vectors, the angle between the first and the third minus the angle
between the second and the third equals the angle between the first and the second. -/
@[simp]
theorem oangle_sub_right {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle x z - o.oangle y z = o.oangle x y := by rw [sub_eq_iff_eq_add, o.oangle_add hx hy hz]
/-- Given three nonzero vectors, adding the angles between them in cyclic order results in 0. -/
@[simp]
theorem oangle_add_cyc3 {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle x y + o.oangle y z + o.oangle z x = 0 := by simp [hx, hy, hz]
/-- Given three nonzero vectors, adding the angles between them in cyclic order, with the first
vector in each angle negated, results in π. If the vectors add to 0, this is a version of the
sum of the angles of a triangle. -/
@[simp]
theorem oangle_add_cyc3_neg_left {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle (-x) y + o.oangle (-y) z + o.oangle (-z) x = π := by
rw [o.oangle_neg_left hx hy, o.oangle_neg_left hy hz, o.oangle_neg_left hz hx,
show o.oangle x y + π + (o.oangle y z + π) + (o.oangle z x + π) =
o.oangle x y + o.oangle y z + o.oangle z x + (π + π + π : Real.Angle) by abel,
o.oangle_add_cyc3 hx hy hz, Real.Angle.coe_pi_add_coe_pi, zero_add, zero_add]
/-- Given three nonzero vectors, adding the angles between them in cyclic order, with the second
vector in each angle negated, results in π. If the vectors add to 0, this is a version of the
sum of the angles of a triangle. -/
@[simp]
theorem oangle_add_cyc3_neg_right {x y z : V} (hx : x ≠ 0) (hy : y ≠ 0) (hz : z ≠ 0) :
o.oangle x (-y) + o.oangle y (-z) + o.oangle z (-x) = π := by
simp_rw [← oangle_neg_left_eq_neg_right, o.oangle_add_cyc3_neg_left hx hy hz]
/-- Pons asinorum, oriented vector angle form. -/
theorem oangle_sub_eq_oangle_sub_rev_of_norm_eq {x y : V} (h : ‖x‖ = ‖y‖) :
o.oangle x (x - y) = o.oangle (y - x) y := by simp [oangle, h]
/-- The angle at the apex of an isosceles triangle is `π` minus twice a base angle, oriented
vector angle form. -/
theorem oangle_eq_pi_sub_two_zsmul_oangle_sub_of_norm_eq {x y : V} (hn : x ≠ y) (h : ‖x‖ = ‖y‖) :
o.oangle y x = π - (2 : ℤ) • o.oangle (y - x) y := by
rw [two_zsmul]
nth_rw 1 [← o.oangle_sub_eq_oangle_sub_rev_of_norm_eq h]
rw [eq_sub_iff_add_eq, ← oangle_neg_neg, ← add_assoc]
have hy : y ≠ 0 := by
rintro rfl
rw [norm_zero, norm_eq_zero] at h
exact hn h
have hx : x ≠ 0 := norm_ne_zero_iff.1 (h.symm ▸ norm_ne_zero_iff.2 hy)
convert o.oangle_add_cyc3_neg_right (neg_ne_zero.2 hy) hx (sub_ne_zero_of_ne hn.symm) using 1
simp
/-- The angle between two vectors, with respect to an orientation given by `Orientation.map`
with a linear isometric equivalence, equals the angle between those two vectors, transformed by
the inverse of that equivalence, with respect to the original orientation. -/
@[simp]
theorem oangle_map (x y : V') (f : V ≃ₗᵢ[ℝ] V') :
(Orientation.map (Fin 2) f.toLinearEquiv o).oangle x y = o.oangle (f.symm x) (f.symm y) := by
simp [oangle, o.kahler_map]
@[simp]
protected theorem _root_.Complex.oangle (w z : ℂ) :
Complex.orientation.oangle w z = Complex.arg (conj w * z) := by
simp [oangle, mul_comm z]
/-- The oriented angle on an oriented real inner product space of dimension 2 can be evaluated in
terms of a complex-number representation of the space. -/
theorem oangle_map_complex (f : V ≃ₗᵢ[ℝ] ℂ)
(hf : Orientation.map (Fin 2) f.toLinearEquiv o = Complex.orientation) (x y : V) :
o.oangle x y = Complex.arg (conj (f x) * f y) := by
rw [← Complex.oangle, ← hf, o.oangle_map]
iterate 2 rw [LinearIsometryEquiv.symm_apply_apply]
/-- Negating the orientation negates the value of `oangle`. -/
theorem oangle_neg_orientation_eq_neg (x y : V) : (-o).oangle x y = -o.oangle x y := by
simp [oangle]
/-- The inner product of two vectors is the product of the norms and the cosine of the oriented
angle between the vectors. -/
theorem inner_eq_norm_mul_norm_mul_cos_oangle (x y : V) :
⟪x, y⟫ = ‖x‖ * ‖y‖ * Real.Angle.cos (o.oangle x y) := by
by_cases hx : x = 0; · simp [hx]
by_cases hy : y = 0; · simp [hy]
rw [oangle, Real.Angle.cos_coe, Complex.cos_arg, o.norm_kahler]
· simp only [kahler_apply_apply, real_smul, add_re, ofReal_re, mul_re, I_re, ofReal_im]
field_simp
· exact o.kahler_ne_zero hx hy
/-- The cosine of the oriented angle between two nonzero vectors is the inner product divided by
the product of the norms. -/
theorem cos_oangle_eq_inner_div_norm_mul_norm {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
Real.Angle.cos (o.oangle x y) = ⟪x, y⟫ / (‖x‖ * ‖y‖) := by
rw [o.inner_eq_norm_mul_norm_mul_cos_oangle]
field_simp [norm_ne_zero_iff.2 hx, norm_ne_zero_iff.2 hy]
/-- The cosine of the oriented angle between two nonzero vectors equals that of the unoriented
angle. -/
theorem cos_oangle_eq_cos_angle {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
Real.Angle.cos (o.oangle x y) = Real.cos (InnerProductGeometry.angle x y) := by
rw [o.cos_oangle_eq_inner_div_norm_mul_norm hx hy, InnerProductGeometry.cos_angle]
/-- The oriented angle between two nonzero vectors is plus or minus the unoriented angle. -/
theorem oangle_eq_angle_or_eq_neg_angle {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
o.oangle x y = InnerProductGeometry.angle x y ∨
o.oangle x y = -InnerProductGeometry.angle x y :=
Real.Angle.cos_eq_real_cos_iff_eq_or_eq_neg.1 <| o.cos_oangle_eq_cos_angle hx hy
/-- The unoriented angle between two nonzero vectors is the absolute value of the oriented angle,
converted to a real. -/
theorem angle_eq_abs_oangle_toReal {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
InnerProductGeometry.angle x y = |(o.oangle x y).toReal| := by
have h0 := InnerProductGeometry.angle_nonneg x y
have hpi := InnerProductGeometry.angle_le_pi x y
rcases o.oangle_eq_angle_or_eq_neg_angle hx hy with (h | h)
· rw [h, eq_comm, Real.Angle.abs_toReal_coe_eq_self_iff]
exact ⟨h0, hpi⟩
· rw [h, eq_comm, Real.Angle.abs_toReal_neg_coe_eq_self_iff]
exact ⟨h0, hpi⟩
/-- If the sign of the oriented angle between two vectors is zero, either one of the vectors is
zero or the unoriented angle is 0 or π. -/
theorem eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero {x y : V}
(h : (o.oangle x y).sign = 0) :
x = 0 ∨ y = 0 ∨ InnerProductGeometry.angle x y = 0 ∨ InnerProductGeometry.angle x y = π := by
by_cases hx : x = 0; · simp [hx]
by_cases hy : y = 0; · simp [hy]
rw [o.angle_eq_abs_oangle_toReal hx hy]
rw [Real.Angle.sign_eq_zero_iff] at h
rcases h with (h | h) <;> simp [h, Real.pi_pos.le]
/-- 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 {w x y z : V}
(h : InnerProductGeometry.angle w x = InnerProductGeometry.angle y z)
(hs : (o.oangle w x).sign = (o.oangle y z).sign) : o.oangle w x = o.oangle y z := by
by_cases h0 : (w = 0 ∨ x = 0) ∨ y = 0 ∨ z = 0
· have hs' : (o.oangle w x).sign = 0 ∧ (o.oangle y z).sign = 0 := by
rcases h0 with ((rfl | rfl) | rfl | rfl)
· simpa using hs.symm
· simpa using hs.symm
· simpa using hs
· simpa using hs
rcases hs' with ⟨hswx, hsyz⟩
have h' : InnerProductGeometry.angle w x = π / 2 ∧ InnerProductGeometry.angle y z = π / 2 := by
rcases h0 with ((rfl | rfl) | rfl | rfl)
· simpa using h.symm
· simpa using h.symm
· simpa using h
· simpa using h
rcases h' with ⟨hwx, hyz⟩
have hpi : π / 2 ≠ π := by
intro hpi
rw [div_eq_iff, eq_comm, ← sub_eq_zero, mul_two, add_sub_cancel_right] at hpi
· exact Real.pi_pos.ne.symm hpi
· exact two_ne_zero
have h0wx : w = 0 ∨ x = 0 := by
have h0' := o.eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero hswx
simpa [hwx, Real.pi_pos.ne.symm, hpi] using h0'
have h0yz : y = 0 ∨ z = 0 := by
have h0' := o.eq_zero_or_angle_eq_zero_or_pi_of_sign_oangle_eq_zero hsyz
simpa [hyz, Real.pi_pos.ne.symm, hpi] using h0'
rcases h0wx with (h0wx | h0wx) <;> rcases h0yz with (h0yz | h0yz) <;> simp [h0wx, h0yz]
· push_neg at h0
rw [Real.Angle.eq_iff_abs_toReal_eq_of_sign_eq hs]
rwa [o.angle_eq_abs_oangle_toReal h0.1.1 h0.1.2,
o.angle_eq_abs_oangle_toReal h0.2.1 h0.2.2] at h
/-- If the signs of two oriented angles between nonzero vectors 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 {w x y z : V} (hw : w ≠ 0) (hx : x ≠ 0) (hy : y ≠ 0)
(hz : z ≠ 0) (hs : (o.oangle w x).sign = (o.oangle y z).sign) :
InnerProductGeometry.angle w x = InnerProductGeometry.angle y z ↔
o.oangle w x = o.oangle y z := by
refine ⟨fun h => o.oangle_eq_of_angle_eq_of_sign_eq h hs, fun h => ?_⟩
rw [o.angle_eq_abs_oangle_toReal hw hx, o.angle_eq_abs_oangle_toReal hy hz, h]
/-- The oriented angle between two vectors equals the unoriented angle if the sign is positive. -/
theorem oangle_eq_angle_of_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) :
o.oangle x y = InnerProductGeometry.angle x y := by
by_cases hx : x = 0; · exfalso; simp [hx] at h
by_cases hy : y = 0; · exfalso; simp [hy] at h
refine (o.oangle_eq_angle_or_eq_neg_angle hx hy).resolve_right ?_
intro hxy
rw [hxy, Real.Angle.sign_neg, neg_eq_iff_eq_neg, ← SignType.neg_iff, ← not_le] at h
exact h (Real.Angle.sign_coe_nonneg_of_nonneg_of_le_pi (InnerProductGeometry.angle_nonneg _ _)
(InnerProductGeometry.angle_le_pi _ _))
/-- The oriented angle between two vectors equals minus the unoriented angle if the sign is
negative. -/
theorem oangle_eq_neg_angle_of_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) :
o.oangle x y = -InnerProductGeometry.angle x y := by
by_cases hx : x = 0; · exfalso; simp [hx] at h
by_cases hy : y = 0; · exfalso; simp [hy] at h
refine (o.oangle_eq_angle_or_eq_neg_angle hx hy).resolve_left ?_
intro hxy
rw [hxy, ← SignType.neg_iff, ← not_le] at h
exact h (Real.Angle.sign_coe_nonneg_of_nonneg_of_le_pi (InnerProductGeometry.angle_nonneg _ _)
(InnerProductGeometry.angle_le_pi _ _))
|
/-- The oriented angle between two nonzero vectors is zero if and only if the unoriented angle
is zero. -/
theorem oangle_eq_zero_iff_angle_eq_zero {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
o.oangle x y = 0 ↔ InnerProductGeometry.angle x y = 0 := by
refine ⟨fun h => ?_, fun h => ?_⟩
· simpa [o.angle_eq_abs_oangle_toReal hx hy]
· have ha := o.oangle_eq_angle_or_eq_neg_angle hx hy
rw [h] at ha
| Mathlib/Geometry/Euclidean/Angle/Oriented/Basic.lean | 658 | 666 |
/-
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 _ _ _
| Mathlib/Topology/MetricSpace/Pseudo/Defs.lean | 326 | 327 |
/-
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.QuadraticForm.IsometryEquiv
/-! # Quadratic form on product and pi types
## Main definitions
* `QuadraticForm.prod Q₁ Q₂`: the quadratic form constructed elementwise on a product
* `QuadraticForm.pi Q`: the quadratic form constructed elementwise on a pi type
## Main results
* `QuadraticForm.Equivalent.prod`, `QuadraticForm.Equivalent.pi`: quadratic forms are equivalent
if their components are equivalent
* `QuadraticForm.nonneg_prod_iff`, `QuadraticForm.nonneg_pi_iff`: quadratic forms are positive-
semidefinite if and only if their components are positive-semidefinite.
* `QuadraticForm.posDef_prod_iff`, `QuadraticForm.posDef_pi_iff`: quadratic forms are positive-
definite if and only if their components are positive-definite.
## Implementation notes
Many of the lemmas in this file could be generalized into results about sums of positive and
non-negative elements, and would generalize to any map `Q` where `Q 0 = 0`, not just quadratic
forms specifically.
-/
universe u v w
variable {ι : Type*} {R : Type*} {M₁ M₂ N₁ N₂ P : Type*} {Mᵢ Nᵢ : ι → Type*}
namespace QuadraticMap
section Prod
section Semiring
variable [CommSemiring R]
variable [AddCommMonoid M₁] [AddCommMonoid M₂] [AddCommMonoid N₁] [AddCommMonoid N₂]
variable [AddCommMonoid P]
variable [Module R M₁] [Module R M₂] [Module R N₁] [Module R N₂] [Module R P]
/-- Construct a quadratic form on a product of two modules from the quadratic form on each module.
-/
@[simps!]
def prod (Q₁ : QuadraticMap R M₁ P) (Q₂ : QuadraticMap R M₂ P) : QuadraticMap R (M₁ × M₂) P :=
Q₁.comp (LinearMap.fst _ _ _) + Q₂.comp (LinearMap.snd _ _ _)
/-- An isometry between quadratic forms generated by `QuadraticForm.prod` can be constructed
from a pair of isometries between the left and right parts. -/
@[simps toLinearEquiv]
def IsometryEquiv.prod
{Q₁ : QuadraticMap R M₁ P} {Q₂ : QuadraticMap R M₂ P}
{Q₁' : QuadraticMap R N₁ P} {Q₂' : QuadraticMap R N₂ P}
(e₁ : Q₁.IsometryEquiv Q₁') (e₂ : Q₂.IsometryEquiv Q₂') :
(Q₁.prod Q₂).IsometryEquiv (Q₁'.prod Q₂') where
map_app' x := congr_arg₂ (· + ·) (e₁.map_app x.1) (e₂.map_app x.2)
toLinearEquiv := LinearEquiv.prodCongr e₁.toLinearEquiv e₂.toLinearEquiv
/-- `LinearMap.inl` as an isometry. -/
@[simps!]
def Isometry.inl (Q₁ : QuadraticMap R M₁ P) (Q₂ : QuadraticMap R M₂ P) : Q₁ →qᵢ (Q₁.prod Q₂) where
toLinearMap := LinearMap.inl R _ _
map_app' m₁ := by simp
/-- `LinearMap.inr` as an isometry. -/
@[simps!]
def Isometry.inr (Q₁ : QuadraticMap R M₁ P) (Q₂ : QuadraticMap R M₂ P) : Q₂ →qᵢ (Q₁.prod Q₂) where
toLinearMap := LinearMap.inr R _ _
map_app' m₁ := by simp
variable (M₂) in
/-- `LinearMap.fst` as an isometry, when the second space has the zero quadratic form. -/
@[simps!]
def Isometry.fst (Q₁ : QuadraticMap R M₁ P) : (Q₁.prod (0 : QuadraticMap R M₂ P)) →qᵢ Q₁ where
toLinearMap := LinearMap.fst R _ _
map_app' m₁ := by simp
variable (M₁) in
/-- `LinearMap.snd` as an isometry, when the first space has the zero quadratic form. -/
@[simps!]
def Isometry.snd (Q₂ : QuadraticMap R M₂ P) : ((0 : QuadraticMap R M₁ P).prod Q₂) →qᵢ Q₂ where
toLinearMap := LinearMap.snd R _ _
map_app' m₁ := by simp
@[simp]
lemma Isometry.fst_comp_inl (Q₁ : QuadraticMap R M₁ P) :
(fst M₂ Q₁).comp (inl Q₁ (0 : QuadraticMap R M₂ P)) = .id _ :=
ext fun _ => rfl
@[simp]
lemma Isometry.snd_comp_inr (Q₂ : QuadraticMap R M₂ P) :
(snd M₁ Q₂).comp (inr (0 : QuadraticMap R M₁ P) Q₂) = .id _ :=
ext fun _ => rfl
@[simp]
lemma Isometry.snd_comp_inl (Q₂ : QuadraticMap R M₂ P) :
(snd M₁ Q₂).comp (inl (0 : QuadraticMap R M₁ P) Q₂) = 0 :=
ext fun _ => rfl
@[simp]
lemma Isometry.fst_comp_inr (Q₁ : QuadraticMap R M₁ P) :
(fst M₂ Q₁).comp (inr Q₁ (0 : QuadraticMap R M₂ P)) = 0 :=
ext fun _ => rfl
theorem Equivalent.prod {Q₁ : QuadraticMap R M₁ P} {Q₂ : QuadraticMap R M₂ P}
{Q₁' : QuadraticMap R N₁ P} {Q₂' : QuadraticMap R N₂ P} (e₁ : Q₁.Equivalent Q₁')
(e₂ : Q₂.Equivalent Q₂') : (Q₁.prod Q₂).Equivalent (Q₁'.prod Q₂') :=
Nonempty.map2 IsometryEquiv.prod e₁ e₂
/-- `LinearEquiv.prodComm` is isometric. -/
@[simps!]
def IsometryEquiv.prodComm (Q₁ : QuadraticMap R M₁ P) (Q₂ : QuadraticMap R M₂ P) :
(Q₁.prod Q₂).IsometryEquiv (Q₂.prod Q₁) where
toLinearEquiv := LinearEquiv.prodComm _ _ _
map_app' _ := add_comm _ _
/-- `LinearEquiv.prodProdProdComm` is isometric. -/
@[simps!]
def IsometryEquiv.prodProdProdComm
(Q₁ : QuadraticMap R M₁ P) (Q₂ : QuadraticMap R M₂ P)
(Q₃ : QuadraticMap R N₁ P) (Q₄ : QuadraticMap R N₂ P) :
((Q₁.prod Q₂).prod (Q₃.prod Q₄)).IsometryEquiv ((Q₁.prod Q₃).prod (Q₂.prod Q₄)) where
toLinearEquiv := LinearEquiv.prodProdProdComm _ _ _ _ _
map_app' _ := add_add_add_comm _ _ _ _
/-- If a product is anisotropic then its components must be. The converse is not true. -/
theorem anisotropic_of_prod
{Q₁ : QuadraticMap R M₁ P} {Q₂ : QuadraticMap R M₂ P} (h : (Q₁.prod Q₂).Anisotropic) :
Q₁.Anisotropic ∧ Q₂.Anisotropic := by
simp_rw [Anisotropic, prod_apply, Prod.forall, Prod.mk_eq_zero] at h
constructor
· intro x hx
refine (h x 0 ?_).1
rw [hx, zero_add, map_zero]
· intro x hx
refine (h 0 x ?_).2
rw [hx, add_zero, map_zero]
theorem nonneg_prod_iff [Preorder P] [AddLeftMono P]
{Q₁ : QuadraticMap R M₁ P} {Q₂ : QuadraticMap R M₂ P} :
(∀ x, 0 ≤ (Q₁.prod Q₂) x) ↔ (∀ x, 0 ≤ Q₁ x) ∧ ∀ x, 0 ≤ Q₂ x := by
simp_rw [Prod.forall, prod_apply]
constructor
| · intro h
constructor
· intro x; simpa only [add_zero, map_zero] using h x 0
· intro x; simpa only [zero_add, map_zero] using h 0 x
· rintro ⟨h₁, h₂⟩ x₁ x₂
exact add_nonneg (h₁ x₁) (h₂ x₂)
theorem posDef_prod_iff [PartialOrder P] [AddLeftMono P]
{Q₁ : QuadraticMap R M₁ P} {Q₂ : QuadraticMap R M₂ P} :
(Q₁.prod Q₂).PosDef ↔ Q₁.PosDef ∧ Q₂.PosDef := by
simp_rw [posDef_iff_nonneg, nonneg_prod_iff]
| Mathlib/LinearAlgebra/QuadraticForm/Prod.lean | 150 | 160 |
/-
Copyright (c) 2021 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Data.Fintype.List
import Mathlib.Data.Fintype.OfMap
/-!
# Cycles of a list
Lists have an equivalence relation of whether they are rotational permutations of one another.
This relation is defined as `IsRotated`.
Based on this, we define the quotient of lists by the rotation relation, called `Cycle`.
We also define a representation of concrete cycles, available when viewing them in a goal state or
via `#eval`, when over representable types. For example, the cycle `(2 1 4 3)` will be shown
as `c[2, 1, 4, 3]`. Two equal cycles may be printed differently if their internal representation
is different.
-/
assert_not_exists MonoidWithZero
namespace List
variable {α : Type*} [DecidableEq α]
/-- Return the `z` such that `x :: z :: _` appears in `xs`, or `default` if there is no such `z`. -/
def nextOr : ∀ (_ : List α) (_ _ : α), α
| [], _, default => default
| [_], _, default => default
-- Handles the not-found and the wraparound case
| y :: z :: xs, x, default => if x = y then z else nextOr (z :: xs) x default
@[simp]
theorem nextOr_nil (x d : α) : nextOr [] x d = d :=
rfl
@[simp]
theorem nextOr_singleton (x y d : α) : nextOr [y] x d = d :=
rfl
@[simp]
theorem nextOr_self_cons_cons (xs : List α) (x y d : α) : nextOr (x :: y :: xs) x d = y :=
if_pos rfl
theorem nextOr_cons_of_ne (xs : List α) (y x d : α) (h : x ≠ y) :
nextOr (y :: xs) x d = nextOr xs x d := by
rcases xs with - | ⟨z, zs⟩
· rfl
· exact if_neg h
/-- `nextOr` does not depend on the default value, if the next value appears. -/
theorem nextOr_eq_nextOr_of_mem_of_ne (xs : List α) (x d d' : α) (x_mem : x ∈ xs)
(x_ne : x ≠ xs.getLast (ne_nil_of_mem x_mem)) : nextOr xs x d = nextOr xs x d' := by
induction' xs with y ys IH
· cases x_mem
rcases ys with - | ⟨z, zs⟩
· simp at x_mem x_ne
contradiction
by_cases h : x = y
· rw [h, nextOr_self_cons_cons, nextOr_self_cons_cons]
· rw [nextOr, nextOr, IH]
· simpa [h] using x_mem
· simpa using x_ne
theorem mem_of_nextOr_ne {xs : List α} {x d : α} (h : nextOr xs x d ≠ d) : x ∈ xs := by
induction' xs with y ys IH
· simp at h
rcases ys with - | ⟨z, zs⟩
· simp at h
· by_cases hx : x = y
· simp [hx]
· rw [nextOr_cons_of_ne _ _ _ _ hx] at h
simpa [hx] using IH h
theorem nextOr_concat {xs : List α} {x : α} (d : α) (h : x ∉ xs) : nextOr (xs ++ [x]) x d = d := by
induction' xs with z zs IH
· simp
· obtain ⟨hz, hzs⟩ := not_or.mp (mt mem_cons.2 h)
rw [cons_append, nextOr_cons_of_ne _ _ _ _ hz, IH hzs]
theorem nextOr_mem {xs : List α} {x d : α} (hd : d ∈ xs) : nextOr xs x d ∈ xs := by
revert hd
suffices ∀ xs' : List α, (∀ x ∈ xs, x ∈ xs') → d ∈ xs' → nextOr xs x d ∈ xs' by
exact this xs fun _ => id
intro xs' hxs' hd
induction' xs with y ys ih
· exact hd
rcases ys with - | ⟨z, zs⟩
· exact hd
rw [nextOr]
split_ifs with h
· exact hxs' _ (mem_cons_of_mem _ mem_cons_self)
· exact ih fun _ h => hxs' _ (mem_cons_of_mem _ h)
/-- Given an element `x : α` of `l : List α` such that `x ∈ l`, get the next
element of `l`. This works from head to tail, (including a check for last element)
so it will match on first hit, ignoring later duplicates.
For example:
* `next [1, 2, 3] 2 _ = 3`
* `next [1, 2, 3] 3 _ = 1`
* `next [1, 2, 3, 2, 4] 2 _ = 3`
* `next [1, 2, 3, 2] 2 _ = 3`
* `next [1, 1, 2, 3, 2] 1 _ = 1`
-/
def next (l : List α) (x : α) (h : x ∈ l) : α :=
nextOr l x (l.get ⟨0, length_pos_of_mem h⟩)
/-- Given an element `x : α` of `l : List α` such that `x ∈ l`, get the previous
element of `l`. This works from head to tail, (including a check for last element)
so it will match on first hit, ignoring later duplicates.
* `prev [1, 2, 3] 2 _ = 1`
* `prev [1, 2, 3] 1 _ = 3`
* `prev [1, 2, 3, 2, 4] 2 _ = 1`
* `prev [1, 2, 3, 4, 2] 2 _ = 1`
* `prev [1, 1, 2] 1 _ = 2`
-/
def prev : ∀ l : List α, ∀ x ∈ l, α
| [], _, h => by simp at h
| [y], _, _ => y
| y :: z :: xs, x, h =>
if hx : x = y then getLast (z :: xs) (cons_ne_nil _ _)
else if x = z then y else prev (z :: xs) x (by simpa [hx] using h)
variable (l : List α) (x : α)
@[simp]
theorem next_singleton (x y : α) (h : x ∈ [y]) : next [y] x h = y :=
rfl
@[simp]
theorem prev_singleton (x y : α) (h : x ∈ [y]) : prev [y] x h = y :=
rfl
theorem next_cons_cons_eq' (y z : α) (h : x ∈ y :: z :: l) (hx : x = y) :
next (y :: z :: l) x h = z := by rw [next, nextOr, if_pos hx]
@[simp]
theorem next_cons_cons_eq (z : α) (h : x ∈ x :: z :: l) : next (x :: z :: l) x h = z :=
next_cons_cons_eq' l x x z h rfl
theorem next_ne_head_ne_getLast (h : x ∈ l) (y : α) (h : x ∈ y :: l) (hy : x ≠ y)
(hx : x ≠ getLast (y :: l) (cons_ne_nil _ _)) :
next (y :: l) x h = next l x (by simpa [hy] using h) := by
rw [next, next, nextOr_cons_of_ne _ _ _ _ hy, nextOr_eq_nextOr_of_mem_of_ne]
· rwa [getLast_cons] at hx
exact ne_nil_of_mem (by assumption)
· rwa [getLast_cons] at hx
theorem next_cons_concat (y : α) (hy : x ≠ y) (hx : x ∉ l)
(h : x ∈ y :: l ++ [x] := mem_append_right _ (mem_singleton_self x)) :
next (y :: l ++ [x]) x h = y := by
rw [next, nextOr_concat]
· rfl
· simp [hy, hx]
theorem next_getLast_cons (h : x ∈ l) (y : α) (h : x ∈ y :: l) (hy : x ≠ y)
(hx : x = getLast (y :: l) (cons_ne_nil _ _)) (hl : Nodup l) : next (y :: l) x h = y := by
rw [next, get, ← dropLast_append_getLast (cons_ne_nil y l), hx, nextOr_concat]
subst hx
intro H
obtain ⟨_ | k, hk, hk'⟩ := getElem_of_mem H
· rw [← Option.some_inj] at hk'
rw [← getElem?_eq_getElem, dropLast_eq_take, getElem?_take_of_lt, getElem?_cons_zero,
Option.some_inj] at hk'
· exact hy (Eq.symm hk')
rw [length_cons]
exact length_pos_of_mem (by assumption)
suffices k + 1 = l.length by simp [this] at hk
rcases l with - | ⟨hd, tl⟩
· simp at hk
· rw [nodup_iff_injective_get] at hl
rw [length, Nat.succ_inj]
refine Fin.val_eq_of_eq <| @hl ⟨k, Nat.lt_of_succ_lt <| by simpa using hk⟩
⟨tl.length, by simp⟩ ?_
rw [← Option.some_inj] at hk'
rw [← getElem?_eq_getElem, dropLast_eq_take, getElem?_take_of_lt, getElem?_cons_succ,
getElem?_eq_getElem, Option.some_inj] at hk'
· rw [get_eq_getElem, hk']
simp only [getLast_eq_getElem, length_cons, Nat.succ_eq_add_one, Nat.succ_sub_succ_eq_sub,
Nat.sub_zero, get_eq_getElem, getElem_cons_succ]
simpa using hk
theorem prev_getLast_cons' (y : α) (hxy : x ∈ y :: l) (hx : x = y) :
prev (y :: l) x hxy = getLast (y :: l) (cons_ne_nil _ _) := by cases l <;> simp [prev, hx]
@[simp]
theorem prev_getLast_cons (h : x ∈ x :: l) :
prev (x :: l) x h = getLast (x :: l) (cons_ne_nil _ _) :=
prev_getLast_cons' l x x h rfl
theorem prev_cons_cons_eq' (y z : α) (h : x ∈ y :: z :: l) (hx : x = y) :
prev (y :: z :: l) x h = getLast (z :: l) (cons_ne_nil _ _) := by rw [prev, dif_pos hx]
theorem prev_cons_cons_eq (z : α) (h : x ∈ x :: z :: l) :
prev (x :: z :: l) x h = getLast (z :: l) (cons_ne_nil _ _) :=
prev_cons_cons_eq' l x x z h rfl
theorem prev_cons_cons_of_ne' (y z : α) (h : x ∈ y :: z :: l) (hy : x ≠ y) (hz : x = z) :
prev (y :: z :: l) x h = y := by
cases l
· simp [prev, hy, hz]
· rw [prev, dif_neg hy, if_pos hz]
theorem prev_cons_cons_of_ne (y : α) (h : x ∈ y :: x :: l) (hy : x ≠ y) :
prev (y :: x :: l) x h = y :=
prev_cons_cons_of_ne' _ _ _ _ _ hy rfl
theorem prev_ne_cons_cons (y z : α) (h : x ∈ y :: z :: l) (hy : x ≠ y) (hz : x ≠ z) :
prev (y :: z :: l) x h = prev (z :: l) x (by simpa [hy] using h) := by
cases l
· simp [hy, hz] at h
· rw [prev, dif_neg hy, if_neg hz]
theorem next_mem (h : x ∈ l) : l.next x h ∈ l :=
nextOr_mem (get_mem _ _)
theorem prev_mem (h : x ∈ l) : l.prev x h ∈ l := by
rcases l with - | ⟨hd, tl⟩
· simp at h
induction' tl with hd' tl hl generalizing hd
· simp
· by_cases hx : x = hd
· simp only [hx, prev_cons_cons_eq]
exact mem_cons_of_mem _ (getLast_mem _)
· rw [prev, dif_neg hx]
split_ifs with hm
· exact mem_cons_self
· exact mem_cons_of_mem _ (hl _ _)
theorem next_getElem (l : List α) (h : Nodup l) (i : Nat) (hi : i < l.length) :
next l l[i] (get_mem _ _) =
(l[(i + 1) % l.length]'(Nat.mod_lt _ (i.zero_le.trans_lt hi))) :=
match l, h, i, hi with
| [], _, i, hi => by simp at hi
| [_], _, _, _ => by simp
| x::y::l, _h, 0, h0 => by
have h₁ : (x :: y :: l)[0] = x := by simp
rw [next_cons_cons_eq' _ _ _ _ _ h₁]
simp
| x::y::l, hn, i+1, hi => by
have hx' : (x :: y :: l)[i+1] ≠ x := by
intro H
suffices (i + 1 : ℕ) = 0 by simpa
rw [nodup_iff_injective_get] at hn
refine Fin.val_eq_of_eq (@hn ⟨i + 1, hi⟩ ⟨0, by simp⟩ ?_)
simpa using H
have hi' : i ≤ l.length := Nat.le_of_lt_succ (Nat.succ_lt_succ_iff.1 hi)
rcases hi'.eq_or_lt with (hi' | hi')
· subst hi'
rw [next_getLast_cons]
· simp [hi', get]
· rw [getElem_cons_succ]; exact get_mem _ _
· exact hx'
· simp [getLast_eq_getElem]
· exact hn.of_cons
· rw [next_ne_head_ne_getLast _ _ _ _ _ hx']
· simp only [getElem_cons_succ]
rw [next_getElem (y::l), ← getElem_cons_succ (a := x)]
· congr
dsimp
rw [Nat.mod_eq_of_lt (Nat.succ_lt_succ_iff.2 hi'),
Nat.mod_eq_of_lt (Nat.succ_lt_succ_iff.2 (Nat.succ_lt_succ_iff.2 hi'))]
· simp [Nat.mod_eq_of_lt (Nat.succ_lt_succ_iff.2 hi'), hi']
· exact hn.of_cons
· rw [getLast_eq_getElem]
intro h
have := nodup_iff_injective_get.1 hn h
simp at this; simp [this] at hi'
· rw [getElem_cons_succ]; exact get_mem _ _
@[deprecated (since := "2025-02-015")] alias next_get := next_getElem
-- Unused variable linter incorrectly reports that `h` is unused here.
set_option linter.unusedVariables false in
theorem prev_getElem (l : List α) (h : Nodup l) (i : Nat) (hi : i < l.length) :
prev l l[i] (get_mem _ _) =
(l[(i + (l.length - 1)) % l.length]'(Nat.mod_lt _ (by omega))) :=
match l with
| [] => by simp at hi
| x::l => by
induction l generalizing i x with
| nil => simp
| cons y l hl =>
rcases i with (_ | _ | i)
· simp [getLast_eq_getElem]
· simp only [mem_cons, nodup_cons] at h
push_neg at h
simp only [zero_add, getElem_cons_succ, getElem_cons_zero,
List.prev_cons_cons_of_ne _ _ _ _ h.left.left.symm, length, add_comm,
Nat.add_sub_cancel_left, Nat.mod_self]
· rw [prev_ne_cons_cons]
· convert hl i.succ y h.of_cons (Nat.le_of_succ_le_succ hi) using 1
have : ∀ k hk, (y :: l)[k] = (x :: y :: l)[k + 1]'(Nat.succ_lt_succ hk) := by
simp
rw [this]
congr
simp only [Nat.add_succ_sub_one, add_zero, length]
simp only [length, Nat.succ_lt_succ_iff] at hi
set k := l.length
rw [Nat.succ_add, ← Nat.add_succ, Nat.add_mod_right, Nat.succ_add, ← Nat.add_succ _ k,
Nat.add_mod_right, Nat.mod_eq_of_lt, Nat.mod_eq_of_lt]
· exact Nat.lt_succ_of_lt hi
· exact Nat.succ_lt_succ (Nat.lt_succ_of_lt hi)
· intro H
suffices i.succ.succ = 0 by simpa
suffices Fin.mk _ hi = ⟨0, by omega⟩ by rwa [Fin.mk.inj_iff] at this
rw [nodup_iff_injective_get] at h
apply h; rw [← H]; simp
· intro H
suffices i.succ.succ = 1 by simpa
suffices Fin.mk _ hi = ⟨1, by omega⟩ by rwa [Fin.mk.inj_iff] at this
rw [nodup_iff_injective_get] at h
apply h; rw [← H]; simp
@[deprecated (since := "2025-02-15")] alias prev_get := prev_getElem
theorem pmap_next_eq_rotate_one (h : Nodup l) : (l.pmap l.next fun _ h => h) = l.rotate 1 := by
apply List.ext_getElem
· simp
· intros
rw [getElem_pmap, getElem_rotate, next_getElem _ h]
theorem pmap_prev_eq_rotate_length_sub_one (h : Nodup l) :
(l.pmap l.prev fun _ h => h) = l.rotate (l.length - 1) := by
apply List.ext_getElem
· simp
· intro n hn hn'
rw [getElem_rotate, getElem_pmap, prev_getElem _ h]
theorem prev_next (l : List α) (h : Nodup l) (x : α) (hx : x ∈ l) :
prev l (next l x hx) (next_mem _ _ _) = x := by
obtain ⟨n, hn, rfl⟩ := getElem_of_mem hx
simp only [next_getElem, prev_getElem, h, Nat.mod_add_mod]
rcases l with - | ⟨hd, tl⟩
· simp at hn
· have : (n + 1 + length tl) % (length tl + 1) = n := by
rw [length_cons] at hn
rw [add_assoc, add_comm 1, Nat.add_mod_right, Nat.mod_eq_of_lt hn]
simp only [length_cons, Nat.succ_sub_succ_eq_sub, Nat.sub_zero, Nat.succ_eq_add_one, this]
theorem next_prev (l : List α) (h : Nodup l) (x : α) (hx : x ∈ l) :
next l (prev l x hx) (prev_mem _ _ _) = x := by
obtain ⟨n, hn, rfl⟩ := getElem_of_mem hx
simp only [next_getElem, prev_getElem, h, Nat.mod_add_mod]
rcases l with - | ⟨hd, tl⟩
· simp at hn
· have : (n + length tl + 1) % (length tl + 1) = n := by
rw [length_cons] at hn
rw [add_assoc, Nat.add_mod_right, Nat.mod_eq_of_lt hn]
simp [this]
theorem prev_reverse_eq_next (l : List α) (h : Nodup l) (x : α) (hx : x ∈ l) :
prev l.reverse x (mem_reverse.mpr hx) = next l x hx := by
obtain ⟨k, hk, rfl⟩ := getElem_of_mem hx
have lpos : 0 < l.length := k.zero_le.trans_lt hk
have key : l.length - 1 - k < l.length := by omega
rw [← getElem_pmap l.next (fun _ h => h) (by simpa using hk)]
simp_rw [getElem_eq_getElem_reverse (l := l), pmap_next_eq_rotate_one _ h]
rw [← getElem_pmap l.reverse.prev fun _ h => h]
· simp_rw [pmap_prev_eq_rotate_length_sub_one _ (nodup_reverse.mpr h), rotate_reverse,
length_reverse, Nat.mod_eq_of_lt (Nat.sub_lt lpos Nat.succ_pos'),
Nat.sub_sub_self (Nat.succ_le_of_lt lpos)]
rw [getElem_eq_getElem_reverse]
· simp [Nat.sub_sub_self (Nat.le_sub_one_of_lt hk)]
· simpa
theorem next_reverse_eq_prev (l : List α) (h : Nodup l) (x : α) (hx : x ∈ l) :
next l.reverse x (mem_reverse.mpr hx) = prev l x hx := by
convert (prev_reverse_eq_next l.reverse (nodup_reverse.mpr h) x (mem_reverse.mpr hx)).symm
exact (reverse_reverse l).symm
theorem isRotated_next_eq {l l' : List α} (h : l ~r l') (hn : Nodup l) {x : α} (hx : x ∈ l) :
l.next x hx = l'.next x (h.mem_iff.mp hx) := by
obtain ⟨k, hk, rfl⟩ := getElem_of_mem hx
obtain ⟨n, rfl⟩ := id h
rw [next_getElem _ hn]
simp_rw [getElem_eq_getElem_rotate _ n k]
rw [next_getElem _ (h.nodup_iff.mp hn), getElem_eq_getElem_rotate _ n]
simp [add_assoc]
theorem isRotated_prev_eq {l l' : List α} (h : l ~r l') (hn : Nodup l) {x : α} (hx : x ∈ l) :
l.prev x hx = l'.prev x (h.mem_iff.mp hx) := by
rw [← next_reverse_eq_prev _ hn, ← next_reverse_eq_prev _ (h.nodup_iff.mp hn)]
exact isRotated_next_eq h.reverse (nodup_reverse.mpr hn) _
end List
open List
/-- `Cycle α` is the quotient of `List α` by cyclic permutation.
Duplicates are allowed.
-/
def Cycle (α : Type*) : Type _ :=
Quotient (IsRotated.setoid α)
namespace Cycle
variable {α : Type*}
/-- The coercion from `List α` to `Cycle α` -/
@[coe] def ofList : List α → Cycle α :=
Quot.mk _
instance : Coe (List α) (Cycle α) :=
⟨ofList⟩
@[simp]
theorem coe_eq_coe {l₁ l₂ : List α} : (l₁ : Cycle α) = (l₂ : Cycle α) ↔ l₁ ~r l₂ :=
@Quotient.eq _ (IsRotated.setoid _) _ _
@[simp]
theorem mk_eq_coe (l : List α) : Quot.mk _ l = (l : Cycle α) :=
rfl
@[simp]
theorem mk''_eq_coe (l : List α) : Quotient.mk'' l = (l : Cycle α) :=
rfl
theorem coe_cons_eq_coe_append (l : List α) (a : α) :
(↑(a :: l) : Cycle α) = (↑(l ++ [a]) : Cycle α) :=
Quot.sound ⟨1, by rw [rotate_cons_succ, rotate_zero]⟩
/-- The unique empty cycle. -/
def nil : Cycle α :=
([] : List α)
@[simp]
theorem coe_nil : ↑([] : List α) = @nil α :=
rfl
@[simp]
theorem coe_eq_nil (l : List α) : (l : Cycle α) = nil ↔ l = [] :=
coe_eq_coe.trans isRotated_nil_iff
/-- For consistency with `EmptyCollection (List α)`. -/
instance : EmptyCollection (Cycle α) :=
⟨nil⟩
@[simp]
theorem empty_eq : ∅ = @nil α :=
rfl
instance : Inhabited (Cycle α) :=
⟨nil⟩
/-- An induction principle for `Cycle`. Use as `induction s`. -/
@[elab_as_elim, induction_eliminator]
theorem induction_on {C : Cycle α → Prop} (s : Cycle α) (H0 : C nil)
(HI : ∀ (a) (l : List α), C ↑l → C ↑(a :: l)) : C s :=
Quotient.inductionOn' s fun l => by
refine List.recOn l ?_ ?_ <;> simp only [mk''_eq_coe, coe_nil]
assumption'
/-- For `x : α`, `s : Cycle α`, `x ∈ s` indicates that `x` occurs at least once in `s`. -/
def Mem (s : Cycle α) (a : α) : Prop :=
Quot.liftOn s (fun l => a ∈ l) fun _ _ e => propext <| e.mem_iff
instance : Membership α (Cycle α) :=
⟨Mem⟩
@[simp]
theorem mem_coe_iff {a : α} {l : List α} : a ∈ (↑l : Cycle α) ↔ a ∈ l :=
Iff.rfl
@[simp]
theorem not_mem_nil (a : α) : a ∉ nil :=
List.not_mem_nil
instance [DecidableEq α] : DecidableEq (Cycle α) := fun s₁ s₂ =>
Quotient.recOnSubsingleton₂' s₁ s₂ fun _ _ => decidable_of_iff' _ Quotient.eq''
instance [DecidableEq α] (x : α) (s : Cycle α) : Decidable (x ∈ s) :=
Quotient.recOnSubsingleton' s fun l => show Decidable (x ∈ l) from inferInstance
/-- Reverse a `s : Cycle α` by reversing the underlying `List`. -/
nonrec def reverse (s : Cycle α) : Cycle α :=
Quot.map reverse (fun _ _ => IsRotated.reverse) s
@[simp]
theorem reverse_coe (l : List α) : (l : Cycle α).reverse = l.reverse :=
rfl
@[simp]
theorem mem_reverse_iff {a : α} {s : Cycle α} : a ∈ s.reverse ↔ a ∈ s :=
Quot.inductionOn s fun _ => mem_reverse
@[simp]
theorem reverse_reverse (s : Cycle α) : s.reverse.reverse = s :=
Quot.inductionOn s fun _ => by simp
@[simp]
theorem reverse_nil : nil.reverse = @nil α :=
rfl
/-- The length of the `s : Cycle α`, which is the number of elements, counting duplicates. -/
def length (s : Cycle α) : ℕ :=
Quot.liftOn s List.length fun _ _ e => e.perm.length_eq
@[simp]
theorem length_coe (l : List α) : length (l : Cycle α) = l.length :=
rfl
@[simp]
theorem length_nil : length (@nil α) = 0 :=
rfl
@[simp]
theorem length_reverse (s : Cycle α) : s.reverse.length = s.length :=
Quot.inductionOn s fun _ => List.length_reverse
/-- A `s : Cycle α` that is at most one element. -/
def Subsingleton (s : Cycle α) : Prop :=
s.length ≤ 1
theorem subsingleton_nil : Subsingleton (@nil α) := Nat.zero_le _
theorem length_subsingleton_iff {s : Cycle α} : Subsingleton s ↔ length s ≤ 1 :=
Iff.rfl
@[simp]
theorem subsingleton_reverse_iff {s : Cycle α} : s.reverse.Subsingleton ↔ s.Subsingleton := by
simp [length_subsingleton_iff]
theorem Subsingleton.congr {s : Cycle α} (h : Subsingleton s) :
∀ ⦃x⦄ (_hx : x ∈ s) ⦃y⦄ (_hy : y ∈ s), x = y := by
induction' s using Quot.inductionOn with l
simp only [length_subsingleton_iff, length_coe, mk_eq_coe, le_iff_lt_or_eq, Nat.lt_add_one_iff,
length_eq_zero_iff, length_eq_one_iff, Nat.not_lt_zero, false_or] at h
rcases h with (rfl | ⟨z, rfl⟩) <;> simp
/-- A `s : Cycle α` that is made up of at least two unique elements. -/
def Nontrivial (s : Cycle α) : Prop :=
∃ x y : α, x ≠ y ∧ x ∈ s ∧ y ∈ s
@[simp]
theorem nontrivial_coe_nodup_iff {l : List α} (hl : l.Nodup) :
Nontrivial (l : Cycle α) ↔ 2 ≤ l.length := by
rw [Nontrivial]
rcases l with (_ | ⟨hd, _ | ⟨hd', tl⟩⟩)
· simp
· simp
· simp only [mem_cons, exists_prop, mem_coe_iff, List.length, Ne, Nat.succ_le_succ_iff,
Nat.zero_le, iff_true]
refine ⟨hd, hd', ?_, by simp⟩
simp only [not_or, mem_cons, nodup_cons] at hl
exact hl.left.left
@[simp]
theorem nontrivial_reverse_iff {s : Cycle α} : s.reverse.Nontrivial ↔ s.Nontrivial := by
simp [Nontrivial]
theorem length_nontrivial {s : Cycle α} (h : Nontrivial s) : 2 ≤ length s := by
obtain ⟨x, y, hxy, hx, hy⟩ := h
induction' s using Quot.inductionOn with l
rcases l with (_ | ⟨hd, _ | ⟨hd', tl⟩⟩)
· simp at hx
· simp only [mem_coe_iff, mk_eq_coe, mem_singleton] at hx hy
simp [hx, hy] at hxy
· simp [Nat.succ_le_succ_iff]
/-- The `s : Cycle α` contains no duplicates. -/
nonrec def Nodup (s : Cycle α) : Prop :=
Quot.liftOn s Nodup fun _l₁ _l₂ e => propext <| e.nodup_iff
@[simp]
nonrec theorem nodup_nil : Nodup (@nil α) :=
nodup_nil
@[simp]
theorem nodup_coe_iff {l : List α} : Nodup (l : Cycle α) ↔ l.Nodup :=
Iff.rfl
@[simp]
theorem nodup_reverse_iff {s : Cycle α} : s.reverse.Nodup ↔ s.Nodup :=
Quot.inductionOn s fun _ => nodup_reverse
theorem Subsingleton.nodup {s : Cycle α} (h : Subsingleton s) : Nodup s := by
induction' s using Quot.inductionOn with l
obtain - | ⟨hd, tl⟩ := l
· simp
· have : tl = [] := by simpa [Subsingleton, length_eq_zero_iff, Nat.succ_le_succ_iff] using h
simp [this]
theorem Nodup.nontrivial_iff {s : Cycle α} (h : Nodup s) : Nontrivial s ↔ ¬Subsingleton s := by
rw [length_subsingleton_iff]
induction s using Quotient.inductionOn'
simp only [mk''_eq_coe, nodup_coe_iff] at h
simp [h, Nat.succ_le_iff]
/-- The `s : Cycle α` as a `Multiset α`.
-/
def toMultiset (s : Cycle α) : Multiset α :=
Quotient.liftOn' s (↑) fun _ _ h => Multiset.coe_eq_coe.mpr h.perm
@[simp]
theorem coe_toMultiset (l : List α) : (l : Cycle α).toMultiset = l :=
rfl
@[simp]
theorem nil_toMultiset : nil.toMultiset = (0 : Multiset α) :=
rfl
@[simp]
theorem card_toMultiset (s : Cycle α) : Multiset.card s.toMultiset = s.length :=
Quotient.inductionOn' s (by simp)
@[simp]
theorem toMultiset_eq_nil {s : Cycle α} : s.toMultiset = 0 ↔ s = Cycle.nil :=
Quotient.inductionOn' s (by simp)
/-- The lift of `list.map`. -/
| def map {β : Type*} (f : α → β) : Cycle α → Cycle β :=
Quotient.map' (List.map f) fun _ _ h => h.map _
@[simp]
theorem map_nil {β : Type*} (f : α → β) : map f nil = nil :=
rfl
@[simp]
theorem map_coe {β : Type*} (f : α → β) (l : List α) : map f ↑l = List.map f l :=
rfl
| Mathlib/Data/List/Cycle.lean | 618 | 628 |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl
-/
import Mathlib.MeasureTheory.Integral.Lebesgue.Basic
import Mathlib.MeasureTheory.Integral.Lebesgue.Countable
import Mathlib.MeasureTheory.Integral.Lebesgue.MeasurePreserving
import Mathlib.MeasureTheory.Integral.Lebesgue.Norm
deprecated_module (since := "2025-04-13")
| Mathlib/MeasureTheory/Integral/Lebesgue.lean | 250 | 253 | |
/-
Copyright (c) 2020 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Algebra.Group.Conj
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Subgroup.Ker
/-!
# Basic results on subgroups
We prove basic results on the definitions of subgroups. The bundled subgroups use bundled monoid
homomorphisms.
Special thanks goes to Amelia Livingston and Yury Kudryashov for their help and inspiration.
## Main definitions
Notation used here:
- `G N` are `Group`s
- `A` is an `AddGroup`
- `H K` are `Subgroup`s of `G` or `AddSubgroup`s of `A`
- `x` is an element of type `G` or type `A`
- `f g : N →* G` are group homomorphisms
- `s k` are sets of elements of type `G`
Definitions in the file:
* `Subgroup.prod H K` : the product of subgroups `H`, `K` of groups `G`, `N` respectively, `H × K`
is a subgroup of `G × N`
## Implementation notes
Subgroup inclusion is denoted `≤` rather than `⊆`, although `∈` is defined as
membership of a subgroup's underlying set.
## Tags
subgroup, subgroups
-/
assert_not_exists OrderedAddCommMonoid Multiset Ring
open Function
open scoped Int
variable {G G' G'' : Type*} [Group G] [Group G'] [Group G'']
variable {A : Type*} [AddGroup A]
section SubgroupClass
variable {M S : Type*} [DivInvMonoid M] [SetLike S M] [hSM : SubgroupClass S M] {H K : S}
variable [SetLike S G] [SubgroupClass S G]
@[to_additive]
theorem div_mem_comm_iff {a b : G} : a / b ∈ H ↔ b / a ∈ H :=
inv_div b a ▸ inv_mem_iff
end SubgroupClass
namespace Subgroup
variable (H K : Subgroup G)
@[to_additive]
protected theorem div_mem_comm_iff {a b : G} : a / b ∈ H ↔ b / a ∈ H :=
div_mem_comm_iff
variable {k : Set G}
open Set
variable {N : Type*} [Group N] {P : Type*} [Group P]
/-- Given `Subgroup`s `H`, `K` of groups `G`, `N` respectively, `H × K` as a subgroup of `G × N`. -/
@[to_additive prod
"Given `AddSubgroup`s `H`, `K` of `AddGroup`s `A`, `B` respectively, `H × K`
as an `AddSubgroup` of `A × B`."]
def prod (H : Subgroup G) (K : Subgroup N) : Subgroup (G × N) :=
{ Submonoid.prod H.toSubmonoid K.toSubmonoid with
inv_mem' := fun hx => ⟨H.inv_mem' hx.1, K.inv_mem' hx.2⟩ }
@[to_additive coe_prod]
theorem coe_prod (H : Subgroup G) (K : Subgroup N) :
(H.prod K : Set (G × N)) = (H : Set G) ×ˢ (K : Set N) :=
rfl
@[to_additive mem_prod]
theorem mem_prod {H : Subgroup G} {K : Subgroup N} {p : G × N} : p ∈ H.prod K ↔ p.1 ∈ H ∧ p.2 ∈ K :=
Iff.rfl
open scoped Relator in
@[to_additive prod_mono]
theorem prod_mono : ((· ≤ ·) ⇒ (· ≤ ·) ⇒ (· ≤ ·)) (@prod G _ N _) (@prod G _ N _) :=
fun _s _s' hs _t _t' ht => Set.prod_mono hs ht
@[to_additive prod_mono_right]
theorem prod_mono_right (K : Subgroup G) : Monotone fun t : Subgroup N => K.prod t :=
prod_mono (le_refl K)
@[to_additive prod_mono_left]
theorem prod_mono_left (H : Subgroup N) : Monotone fun K : Subgroup G => K.prod H := fun _ _ hs =>
prod_mono hs (le_refl H)
@[to_additive prod_top]
theorem prod_top (K : Subgroup G) : K.prod (⊤ : Subgroup N) = K.comap (MonoidHom.fst G N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_fst]
@[to_additive top_prod]
theorem top_prod (H : Subgroup N) : (⊤ : Subgroup G).prod H = H.comap (MonoidHom.snd G N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_snd]
@[to_additive (attr := simp) top_prod_top]
theorem top_prod_top : (⊤ : Subgroup G).prod (⊤ : Subgroup N) = ⊤ :=
(top_prod _).trans <| comap_top _
@[to_additive (attr := simp) bot_prod_bot]
theorem bot_prod_bot : (⊥ : Subgroup G).prod (⊥ : Subgroup N) = ⊥ :=
SetLike.coe_injective <| by simp [coe_prod]
@[deprecated (since := "2025-03-11")]
alias _root_.AddSubgroup.bot_sum_bot := AddSubgroup.bot_prod_bot
@[to_additive le_prod_iff]
theorem le_prod_iff {H : Subgroup G} {K : Subgroup N} {J : Subgroup (G × N)} :
J ≤ H.prod K ↔ map (MonoidHom.fst G N) J ≤ H ∧ map (MonoidHom.snd G N) J ≤ K := by
simpa only [← Subgroup.toSubmonoid_le] using Submonoid.le_prod_iff
@[to_additive prod_le_iff]
theorem prod_le_iff {H : Subgroup G} {K : Subgroup N} {J : Subgroup (G × N)} :
H.prod K ≤ J ↔ map (MonoidHom.inl G N) H ≤ J ∧ map (MonoidHom.inr G N) K ≤ J := by
simpa only [← Subgroup.toSubmonoid_le] using Submonoid.prod_le_iff
@[to_additive (attr := simp) prod_eq_bot_iff]
theorem prod_eq_bot_iff {H : Subgroup G} {K : Subgroup N} : H.prod K = ⊥ ↔ H = ⊥ ∧ K = ⊥ := by
simpa only [← Subgroup.toSubmonoid_inj] using Submonoid.prod_eq_bot_iff
@[to_additive closure_prod]
theorem closure_prod {s : Set G} {t : Set N} (hs : 1 ∈ s) (ht : 1 ∈ t) :
closure (s ×ˢ t) = (closure s).prod (closure t) :=
le_antisymm
(closure_le _ |>.2 <| Set.prod_subset_prod_iff.2 <| .inl ⟨subset_closure, subset_closure⟩)
(prod_le_iff.2 ⟨
map_le_iff_le_comap.2 <| closure_le _ |>.2 fun _x hx => subset_closure ⟨hx, ht⟩,
map_le_iff_le_comap.2 <| closure_le _ |>.2 fun _y hy => subset_closure ⟨hs, hy⟩⟩)
/-- Product of subgroups is isomorphic to their product as groups. -/
@[to_additive prodEquiv
"Product of additive subgroups is isomorphic to their product
as additive groups"]
def prodEquiv (H : Subgroup G) (K : Subgroup N) : H.prod K ≃* H × K :=
{ Equiv.Set.prod (H : Set G) (K : Set N) with map_mul' := fun _ _ => rfl }
section Pi
variable {η : Type*} {f : η → Type*}
-- defined here and not in Algebra.Group.Submonoid.Operations to have access to Algebra.Group.Pi
/-- A version of `Set.pi` for submonoids. Given an index set `I` and a family of submodules
`s : Π i, Submonoid f i`, `pi I s` is the submonoid of dependent functions `f : Π i, f i` such that
`f i` belongs to `Pi I s` whenever `i ∈ I`. -/
@[to_additive "A version of `Set.pi` for `AddSubmonoid`s. Given an index set `I` and a family
of submodules `s : Π i, AddSubmonoid f i`, `pi I s` is the `AddSubmonoid` of dependent functions
`f : Π i, f i` such that `f i` belongs to `pi I s` whenever `i ∈ I`."]
def _root_.Submonoid.pi [∀ i, MulOneClass (f i)] (I : Set η) (s : ∀ i, Submonoid (f i)) :
Submonoid (∀ i, f i) where
carrier := I.pi fun i => (s i).carrier
one_mem' i _ := (s i).one_mem
mul_mem' hp hq i hI := (s i).mul_mem (hp i hI) (hq i hI)
variable [∀ i, Group (f i)]
/-- A version of `Set.pi` for subgroups. Given an index set `I` and a family of submodules
`s : Π i, Subgroup f i`, `pi I s` is the subgroup of dependent functions `f : Π i, f i` such that
`f i` belongs to `pi I s` whenever `i ∈ I`. -/
@[to_additive
"A version of `Set.pi` for `AddSubgroup`s. Given an index set `I` and a family
of submodules `s : Π i, AddSubgroup f i`, `pi I s` is the `AddSubgroup` of dependent functions
`f : Π i, f i` such that `f i` belongs to `pi I s` whenever `i ∈ I`."]
def pi (I : Set η) (H : ∀ i, Subgroup (f i)) : Subgroup (∀ i, f i) :=
{ Submonoid.pi I fun i => (H i).toSubmonoid with
inv_mem' := fun hp i hI => (H i).inv_mem (hp i hI) }
@[to_additive]
theorem coe_pi (I : Set η) (H : ∀ i, Subgroup (f i)) :
(pi I H : Set (∀ i, f i)) = Set.pi I fun i => (H i : Set (f i)) :=
rfl
@[to_additive]
theorem mem_pi (I : Set η) {H : ∀ i, Subgroup (f i)} {p : ∀ i, f i} :
p ∈ pi I H ↔ ∀ i : η, i ∈ I → p i ∈ H i :=
Iff.rfl
@[to_additive]
theorem pi_top (I : Set η) : (pi I fun i => (⊤ : Subgroup (f i))) = ⊤ :=
ext fun x => by simp [mem_pi]
@[to_additive]
theorem pi_empty (H : ∀ i, Subgroup (f i)) : pi ∅ H = ⊤ :=
ext fun x => by simp [mem_pi]
@[to_additive]
theorem pi_bot : (pi Set.univ fun i => (⊥ : Subgroup (f i))) = ⊥ :=
(eq_bot_iff_forall _).mpr fun p hp => by
simp only [mem_pi, mem_bot] at *
ext j
exact hp j trivial
@[to_additive]
theorem le_pi_iff {I : Set η} {H : ∀ i, Subgroup (f i)} {J : Subgroup (∀ i, f i)} :
J ≤ pi I H ↔ ∀ i : η, i ∈ I → map (Pi.evalMonoidHom f i) J ≤ H i := by
constructor
· intro h i hi
rintro _ ⟨x, hx, rfl⟩
exact (h hx) _ hi
· intro h x hx i hi
exact h i hi ⟨_, hx, rfl⟩
@[to_additive (attr := simp)]
theorem mulSingle_mem_pi [DecidableEq η] {I : Set η} {H : ∀ i, Subgroup (f i)} (i : η) (x : f i) :
Pi.mulSingle i x ∈ pi I H ↔ i ∈ I → x ∈ H i := by
constructor
· intro h hi
simpa using h i hi
· intro h j hj
by_cases heq : j = i
· subst heq
simpa using h hj
· simp [heq, one_mem]
@[to_additive]
theorem pi_eq_bot_iff (H : ∀ i, Subgroup (f i)) : pi Set.univ H = ⊥ ↔ ∀ i, H i = ⊥ := by
classical
simp only [eq_bot_iff_forall]
constructor
· intro h i x hx
have : MonoidHom.mulSingle f i x = 1 :=
h (MonoidHom.mulSingle f i x) ((mulSingle_mem_pi i x).mpr fun _ => hx)
simpa using congr_fun this i
· exact fun h x hx => funext fun i => h _ _ (hx i trivial)
end Pi
end Subgroup
namespace Subgroup
variable {H K : Subgroup G}
variable (H)
/-- A subgroup is characteristic if it is fixed by all automorphisms.
Several equivalent conditions are provided by lemmas of the form `Characteristic.iff...` -/
structure Characteristic : Prop where
/-- `H` is fixed by all automorphisms -/
fixed : ∀ ϕ : G ≃* G, H.comap ϕ.toMonoidHom = H
attribute [class] Characteristic
instance (priority := 100) normal_of_characteristic [h : H.Characteristic] : H.Normal :=
⟨fun a ha b => (SetLike.ext_iff.mp (h.fixed (MulAut.conj b)) a).mpr ha⟩
end Subgroup
namespace AddSubgroup
variable (H : AddSubgroup A)
/-- An `AddSubgroup` is characteristic if it is fixed by all automorphisms.
Several equivalent conditions are provided by lemmas of the form `Characteristic.iff...` -/
structure Characteristic : Prop where
/-- `H` is fixed by all automorphisms -/
fixed : ∀ ϕ : A ≃+ A, H.comap ϕ.toAddMonoidHom = H
attribute [to_additive] Subgroup.Characteristic
attribute [class] Characteristic
instance (priority := 100) normal_of_characteristic [h : H.Characteristic] : H.Normal :=
⟨fun a ha b => (SetLike.ext_iff.mp (h.fixed (AddAut.conj b)) a).mpr ha⟩
end AddSubgroup
namespace Subgroup
variable {H K : Subgroup G}
@[to_additive]
theorem characteristic_iff_comap_eq : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.comap ϕ.toMonoidHom = H :=
⟨Characteristic.fixed, Characteristic.mk⟩
@[to_additive]
theorem characteristic_iff_comap_le : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.comap ϕ.toMonoidHom ≤ H :=
characteristic_iff_comap_eq.trans
⟨fun h ϕ => le_of_eq (h ϕ), fun h ϕ =>
le_antisymm (h ϕ) fun g hg => h ϕ.symm ((congr_arg (· ∈ H) (ϕ.symm_apply_apply g)).mpr hg)⟩
@[to_additive]
theorem characteristic_iff_le_comap : H.Characteristic ↔ ∀ ϕ : G ≃* G, H ≤ H.comap ϕ.toMonoidHom :=
characteristic_iff_comap_eq.trans
⟨fun h ϕ => ge_of_eq (h ϕ), fun h ϕ =>
le_antisymm (fun g hg => (congr_arg (· ∈ H) (ϕ.symm_apply_apply g)).mp (h ϕ.symm hg)) (h ϕ)⟩
@[to_additive]
theorem characteristic_iff_map_eq : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.map ϕ.toMonoidHom = H := by
simp_rw [map_equiv_eq_comap_symm']
exact characteristic_iff_comap_eq.trans ⟨fun h ϕ => h ϕ.symm, fun h ϕ => h ϕ.symm⟩
@[to_additive]
theorem characteristic_iff_map_le : H.Characteristic ↔ ∀ ϕ : G ≃* G, H.map ϕ.toMonoidHom ≤ H := by
simp_rw [map_equiv_eq_comap_symm']
exact characteristic_iff_comap_le.trans ⟨fun h ϕ => h ϕ.symm, fun h ϕ => h ϕ.symm⟩
@[to_additive]
theorem characteristic_iff_le_map : H.Characteristic ↔ ∀ ϕ : G ≃* G, H ≤ H.map ϕ.toMonoidHom := by
simp_rw [map_equiv_eq_comap_symm']
exact characteristic_iff_le_comap.trans ⟨fun h ϕ => h ϕ.symm, fun h ϕ => h ϕ.symm⟩
@[to_additive]
instance botCharacteristic : Characteristic (⊥ : Subgroup G) :=
characteristic_iff_le_map.mpr fun _ϕ => bot_le
@[to_additive]
instance topCharacteristic : Characteristic (⊤ : Subgroup G) :=
characteristic_iff_map_le.mpr fun _ϕ => le_top
variable (H)
section Normalizer
variable {H}
@[to_additive]
theorem normalizer_eq_top_iff : H.normalizer = ⊤ ↔ H.Normal :=
eq_top_iff.trans
⟨fun h => ⟨fun a ha b => (h (mem_top b) a).mp ha⟩, fun h a _ha b =>
⟨fun hb => h.conj_mem b hb a, fun hb => by rwa [h.mem_comm_iff, inv_mul_cancel_left] at hb⟩⟩
variable (H) in
@[to_additive]
theorem normalizer_eq_top [h : H.Normal] : H.normalizer = ⊤ :=
normalizer_eq_top_iff.mpr h
variable {N : Type*} [Group N]
/-- The preimage of the normalizer is contained in the normalizer of the preimage. -/
@[to_additive "The preimage of the normalizer is contained in the normalizer of the preimage."]
theorem le_normalizer_comap (f : N →* G) :
H.normalizer.comap f ≤ (H.comap f).normalizer := fun x => by
simp only [mem_normalizer_iff, mem_comap]
intro h n
simp [h (f n)]
/-- The image of the normalizer is contained in the normalizer of the image. -/
@[to_additive "The image of the normalizer is contained in the normalizer of the image."]
theorem le_normalizer_map (f : G →* N) : H.normalizer.map f ≤ (H.map f).normalizer := fun _ => by
simp only [and_imp, exists_prop, mem_map, exists_imp, mem_normalizer_iff]
rintro x hx rfl n
constructor
· rintro ⟨y, hy, rfl⟩
use x * y * x⁻¹, (hx y).1 hy
simp
· rintro ⟨y, hyH, hy⟩
use x⁻¹ * y * x
rw [hx]
simp [hy, hyH, mul_assoc]
@[to_additive]
theorem comap_normalizer_eq_of_le_range {f : N →* G} (h : H ≤ f.range) :
comap f H.normalizer = (comap f H).normalizer := by
apply le_antisymm (le_normalizer_comap f)
rw [← map_le_iff_le_comap]
apply (le_normalizer_map f).trans
rw [map_comap_eq_self h]
@[to_additive]
theorem subgroupOf_normalizer_eq {H N : Subgroup G} (h : H ≤ N) :
H.normalizer.subgroupOf N = (H.subgroupOf N).normalizer :=
comap_normalizer_eq_of_le_range (h.trans_eq N.range_subtype.symm)
@[to_additive]
theorem normal_subgroupOf_iff_le_normalizer (h : H ≤ K) :
(H.subgroupOf K).Normal ↔ K ≤ H.normalizer := by
rw [← subgroupOf_eq_top, subgroupOf_normalizer_eq h, normalizer_eq_top_iff]
@[to_additive]
theorem normal_subgroupOf_iff_le_normalizer_inf :
(H.subgroupOf K).Normal ↔ K ≤ (H ⊓ K).normalizer :=
inf_subgroupOf_right H K ▸ normal_subgroupOf_iff_le_normalizer inf_le_right
@[to_additive]
instance (priority := 100) normal_in_normalizer : (H.subgroupOf H.normalizer).Normal :=
(normal_subgroupOf_iff_le_normalizer H.le_normalizer).mpr le_rfl
@[to_additive]
theorem le_normalizer_of_normal_subgroupOf [hK : (H.subgroupOf K).Normal] (HK : H ≤ K) :
K ≤ H.normalizer :=
(normal_subgroupOf_iff_le_normalizer HK).mp hK
@[to_additive]
theorem subset_normalizer_of_normal {S : Set G} [hH : H.Normal] : S ⊆ H.normalizer :=
(@normalizer_eq_top _ _ H hH) ▸ le_top
@[to_additive]
theorem le_normalizer_of_normal [H.Normal] : K ≤ H.normalizer := subset_normalizer_of_normal
@[to_additive]
theorem inf_normalizer_le_normalizer_inf : H.normalizer ⊓ K.normalizer ≤ (H ⊓ K).normalizer :=
fun _ h g ↦ and_congr (h.1 g) (h.2 g)
variable (G) in
/-- Every proper subgroup `H` of `G` is a proper normal subgroup of the normalizer of `H` in `G`. -/
def _root_.NormalizerCondition :=
∀ H : Subgroup G, H < ⊤ → H < normalizer H
/-- Alternative phrasing of the normalizer condition: Only the full group is self-normalizing.
This may be easier to work with, as it avoids inequalities and negations. -/
theorem _root_.normalizerCondition_iff_only_full_group_self_normalizing :
NormalizerCondition G ↔ ∀ H : Subgroup G, H.normalizer = H → H = ⊤ := by
apply forall_congr'; intro H
simp only [lt_iff_le_and_ne, le_normalizer, le_top, Ne]
tauto
variable (H)
end Normalizer
end Subgroup
namespace Group
variable {s : Set G}
/-- Given a set `s`, `conjugatesOfSet s` is the set of all conjugates of
the elements of `s`. -/
def conjugatesOfSet (s : Set G) : Set G :=
⋃ a ∈ s, conjugatesOf a
theorem mem_conjugatesOfSet_iff {x : G} : x ∈ conjugatesOfSet s ↔ ∃ a ∈ s, IsConj a x := by
rw [conjugatesOfSet, Set.mem_iUnion₂]
simp only [conjugatesOf, isConj_iff, Set.mem_setOf_eq, exists_prop]
theorem subset_conjugatesOfSet : s ⊆ conjugatesOfSet s := fun (x : G) (h : x ∈ s) =>
mem_conjugatesOfSet_iff.2 ⟨x, h, IsConj.refl _⟩
theorem conjugatesOfSet_mono {s t : Set G} (h : s ⊆ t) : conjugatesOfSet s ⊆ conjugatesOfSet t :=
Set.biUnion_subset_biUnion_left h
theorem conjugates_subset_normal {N : Subgroup G} [tn : N.Normal] {a : G} (h : a ∈ N) :
conjugatesOf a ⊆ N := by
rintro a hc
obtain ⟨c, rfl⟩ := isConj_iff.1 hc
exact tn.conj_mem a h c
theorem conjugatesOfSet_subset {s : Set G} {N : Subgroup G} [N.Normal] (h : s ⊆ N) :
conjugatesOfSet s ⊆ N :=
Set.iUnion₂_subset fun _x H => conjugates_subset_normal (h H)
/-- The set of conjugates of `s` is closed under conjugation. -/
theorem conj_mem_conjugatesOfSet {x c : G} :
x ∈ conjugatesOfSet s → c * x * c⁻¹ ∈ conjugatesOfSet s := fun H => by
rcases mem_conjugatesOfSet_iff.1 H with ⟨a, h₁, h₂⟩
exact mem_conjugatesOfSet_iff.2 ⟨a, h₁, h₂.trans (isConj_iff.2 ⟨c, rfl⟩)⟩
end Group
namespace Subgroup
open Group
variable {s : Set G}
/-- The normal closure of a set `s` is the subgroup closure of all the conjugates of
elements of `s`. It is the smallest normal subgroup containing `s`. -/
def normalClosure (s : Set G) : Subgroup G :=
closure (conjugatesOfSet s)
theorem conjugatesOfSet_subset_normalClosure : conjugatesOfSet s ⊆ normalClosure s :=
subset_closure
theorem subset_normalClosure : s ⊆ normalClosure s :=
Set.Subset.trans subset_conjugatesOfSet conjugatesOfSet_subset_normalClosure
theorem le_normalClosure {H : Subgroup G} : H ≤ normalClosure ↑H := fun _ h =>
subset_normalClosure h
/-- The normal closure of `s` is a normal subgroup. -/
instance normalClosure_normal : (normalClosure s).Normal :=
⟨fun n h g => by
refine Subgroup.closure_induction (fun x hx => ?_) ?_ (fun x y _ _ ihx ihy => ?_)
(fun x _ ihx => ?_) h
· exact conjugatesOfSet_subset_normalClosure (conj_mem_conjugatesOfSet hx)
· simpa using (normalClosure s).one_mem
· rw [← conj_mul]
exact mul_mem ihx ihy
· rw [← conj_inv]
exact inv_mem ihx⟩
/-- The normal closure of `s` is the smallest normal subgroup containing `s`. -/
theorem normalClosure_le_normal {N : Subgroup G} [N.Normal] (h : s ⊆ N) : normalClosure s ≤ N := by
intro a w
refine closure_induction (fun x hx => ?_) ?_ (fun x y _ _ ihx ihy => ?_) (fun x _ ihx => ?_) w
· exact conjugatesOfSet_subset h hx
· exact one_mem _
· exact mul_mem ihx ihy
· exact inv_mem ihx
theorem normalClosure_subset_iff {N : Subgroup G} [N.Normal] : s ⊆ N ↔ normalClosure s ≤ N :=
⟨normalClosure_le_normal, Set.Subset.trans subset_normalClosure⟩
@[gcongr]
theorem normalClosure_mono {s t : Set G} (h : s ⊆ t) : normalClosure s ≤ normalClosure t :=
normalClosure_le_normal (Set.Subset.trans h subset_normalClosure)
theorem normalClosure_eq_iInf :
normalClosure s = ⨅ (N : Subgroup G) (_ : Normal N) (_ : s ⊆ N), N :=
le_antisymm (le_iInf fun _ => le_iInf fun _ => le_iInf normalClosure_le_normal)
(iInf_le_of_le (normalClosure s)
(iInf_le_of_le (by infer_instance) (iInf_le_of_le subset_normalClosure le_rfl)))
@[simp]
theorem normalClosure_eq_self (H : Subgroup G) [H.Normal] : normalClosure ↑H = H :=
le_antisymm (normalClosure_le_normal rfl.subset) le_normalClosure
theorem normalClosure_idempotent : normalClosure ↑(normalClosure s) = normalClosure s :=
normalClosure_eq_self _
theorem closure_le_normalClosure {s : Set G} : closure s ≤ normalClosure s := by
simp only [subset_normalClosure, closure_le]
@[simp]
theorem normalClosure_closure_eq_normalClosure {s : Set G} :
normalClosure ↑(closure s) = normalClosure s :=
le_antisymm (normalClosure_le_normal closure_le_normalClosure) (normalClosure_mono subset_closure)
/-- The normal core of a subgroup `H` is the largest normal subgroup of `G` contained in `H`,
as shown by `Subgroup.normalCore_eq_iSup`. -/
def normalCore (H : Subgroup G) : Subgroup G where
carrier := { a : G | ∀ b : G, b * a * b⁻¹ ∈ H }
one_mem' a := by rw [mul_one, mul_inv_cancel]; exact H.one_mem
inv_mem' {_} h b := (congr_arg (· ∈ H) conj_inv).mp (H.inv_mem (h b))
mul_mem' {_ _} ha hb c := (congr_arg (· ∈ H) conj_mul).mp (H.mul_mem (ha c) (hb c))
theorem normalCore_le (H : Subgroup G) : H.normalCore ≤ H := fun a h => by
rw [← mul_one a, ← inv_one, ← one_mul a]
exact h 1
instance normalCore_normal (H : Subgroup G) : H.normalCore.Normal :=
⟨fun a h b c => by
rw [mul_assoc, mul_assoc, ← mul_inv_rev, ← mul_assoc, ← mul_assoc]; exact h (c * b)⟩
theorem normal_le_normalCore {H : Subgroup G} {N : Subgroup G} [hN : N.Normal] :
N ≤ H.normalCore ↔ N ≤ H :=
⟨ge_trans H.normalCore_le, fun h_le n hn g => h_le (hN.conj_mem n hn g)⟩
theorem normalCore_mono {H K : Subgroup G} (h : H ≤ K) : H.normalCore ≤ K.normalCore :=
normal_le_normalCore.mpr (H.normalCore_le.trans h)
theorem normalCore_eq_iSup (H : Subgroup G) :
H.normalCore = ⨆ (N : Subgroup G) (_ : Normal N) (_ : N ≤ H), N :=
le_antisymm
(le_iSup_of_le H.normalCore
(le_iSup_of_le H.normalCore_normal (le_iSup_of_le H.normalCore_le le_rfl)))
(iSup_le fun _ => iSup_le fun _ => iSup_le normal_le_normalCore.mpr)
@[simp]
theorem normalCore_eq_self (H : Subgroup G) [H.Normal] : H.normalCore = H :=
le_antisymm H.normalCore_le (normal_le_normalCore.mpr le_rfl)
theorem normalCore_idempotent (H : Subgroup G) : H.normalCore.normalCore = H.normalCore :=
H.normalCore.normalCore_eq_self
end Subgroup
namespace MonoidHom
variable {N : Type*} {P : Type*} [Group N] [Group P] (K : Subgroup G)
open Subgroup
section Ker
variable {M : Type*} [MulOneClass M]
@[to_additive prodMap_comap_prod]
theorem prodMap_comap_prod {G' : Type*} {N' : Type*} [Group G'] [Group N'] (f : G →* N)
(g : G' →* N') (S : Subgroup N) (S' : Subgroup N') :
(S.prod S').comap (prodMap f g) = (S.comap f).prod (S'.comap g) :=
SetLike.coe_injective <| Set.preimage_prod_map_prod f g _ _
@[deprecated (since := "2025-03-11")]
alias _root_.AddMonoidHom.sumMap_comap_sum := AddMonoidHom.prodMap_comap_prod
@[to_additive ker_prodMap]
theorem ker_prodMap {G' : Type*} {N' : Type*} [Group G'] [Group N'] (f : G →* N) (g : G' →* N') :
(prodMap f g).ker = f.ker.prod g.ker := by
rw [← comap_bot, ← comap_bot, ← comap_bot, ← prodMap_comap_prod, bot_prod_bot]
@[deprecated (since := "2025-03-11")]
alias _root_.AddMonoidHom.ker_sumMap := AddMonoidHom.ker_prodMap
@[to_additive (attr := simp)]
lemma ker_fst : ker (fst G G') = .prod ⊥ ⊤ := SetLike.ext fun _ => (iff_of_eq (and_true _)).symm
@[to_additive (attr := simp)]
lemma ker_snd : ker (snd G G') = .prod ⊤ ⊥ := SetLike.ext fun _ => (iff_of_eq (true_and _)).symm
end Ker
end MonoidHom
namespace Subgroup
variable {N : Type*} [Group N] (H : Subgroup G)
@[to_additive]
theorem Normal.map {H : Subgroup G} (h : H.Normal) (f : G →* N) (hf : Function.Surjective f) :
(H.map f).Normal := by
rw [← normalizer_eq_top_iff, ← top_le_iff, ← f.range_eq_top_of_surjective hf, f.range_eq_map,
← H.normalizer_eq_top]
exact le_normalizer_map _
end Subgroup
namespace Subgroup
open MonoidHom
variable {N : Type*} [Group N] (f : G →* N)
/-- The preimage of the normalizer is equal to the normalizer of the preimage of a surjective
function. -/
@[to_additive
"The preimage of the normalizer is equal to the normalizer of the preimage of
a surjective function."]
theorem comap_normalizer_eq_of_surjective (H : Subgroup G) {f : N →* G}
(hf : Function.Surjective f) : H.normalizer.comap f = (H.comap f).normalizer :=
comap_normalizer_eq_of_le_range fun x _ ↦ hf x
@[deprecated (since := "2025-03-13")]
alias comap_normalizer_eq_of_injective_of_le_range := comap_normalizer_eq_of_le_range
@[deprecated (since := "2025-03-13")]
alias _root_.AddSubgroup.comap_normalizer_eq_of_injective_of_le_range :=
AddSubgroup.comap_normalizer_eq_of_le_range
/-- The image of the normalizer is equal to the normalizer of the image of an isomorphism. -/
@[to_additive
"The image of the normalizer is equal to the normalizer of the image of an
isomorphism."]
theorem map_equiv_normalizer_eq (H : Subgroup G) (f : G ≃* N) :
H.normalizer.map f.toMonoidHom = (H.map f.toMonoidHom).normalizer := by
ext x
simp only [mem_normalizer_iff, mem_map_equiv]
rw [f.toEquiv.forall_congr]
intro
simp
/-- The image of the normalizer is equal to the normalizer of the image of a bijective
function. -/
@[to_additive
"The image of the normalizer is equal to the normalizer of the image of a bijective
function."]
theorem map_normalizer_eq_of_bijective (H : Subgroup G) {f : G →* N} (hf : Function.Bijective f) :
H.normalizer.map f = (H.map f).normalizer :=
map_equiv_normalizer_eq H (MulEquiv.ofBijective f hf)
end Subgroup
namespace MonoidHom
variable {G₁ G₂ G₃ : Type*} [Group G₁] [Group G₂] [Group G₃]
variable (f : G₁ →* G₂) (f_inv : G₂ → G₁)
/-- Auxiliary definition used to define `liftOfRightInverse` -/
@[to_additive "Auxiliary definition used to define `liftOfRightInverse`"]
def liftOfRightInverseAux (hf : Function.RightInverse f_inv f) (g : G₁ →* G₃) (hg : f.ker ≤ g.ker) :
G₂ →* G₃ where
toFun b := g (f_inv b)
map_one' := hg (hf 1)
map_mul' := by
intro x y
rw [← g.map_mul, ← mul_inv_eq_one, ← g.map_inv, ← g.map_mul, ← g.mem_ker]
apply hg
rw [f.mem_ker, f.map_mul, f.map_inv, mul_inv_eq_one, f.map_mul]
simp only [hf _]
@[to_additive (attr := simp)]
theorem liftOfRightInverseAux_comp_apply (hf : Function.RightInverse f_inv f) (g : G₁ →* G₃)
(hg : f.ker ≤ g.ker) (x : G₁) : (f.liftOfRightInverseAux f_inv hf g hg) (f x) = g x := by
dsimp [liftOfRightInverseAux]
rw [← mul_inv_eq_one, ← g.map_inv, ← g.map_mul, ← g.mem_ker]
apply hg
rw [f.mem_ker, f.map_mul, f.map_inv, mul_inv_eq_one]
simp only [hf _]
/-- `liftOfRightInverse f hf g hg` is the unique group homomorphism `φ`
* such that `φ.comp f = g` (`MonoidHom.liftOfRightInverse_comp`),
* where `f : G₁ →+* G₂` has a RightInverse `f_inv` (`hf`),
* and `g : G₂ →+* G₃` satisfies `hg : f.ker ≤ g.ker`.
See `MonoidHom.eq_liftOfRightInverse` for the uniqueness lemma.
```
G₁.
| \
f | \ g
| \
v \⌟
G₂----> G₃
∃!φ
```
-/
@[to_additive
"`liftOfRightInverse f f_inv hf g hg` is the unique additive group homomorphism `φ`
* such that `φ.comp f = g` (`AddMonoidHom.liftOfRightInverse_comp`),
* where `f : G₁ →+ G₂` has a RightInverse `f_inv` (`hf`),
* and `g : G₂ →+ G₃` satisfies `hg : f.ker ≤ g.ker`.
See `AddMonoidHom.eq_liftOfRightInverse` for the uniqueness lemma.
```
G₁.
| \\
f | \\ g
| \\
v \\⌟
G₂----> G₃
∃!φ
```"]
def liftOfRightInverse (hf : Function.RightInverse f_inv f) :
{ g : G₁ →* G₃ // f.ker ≤ g.ker } ≃ (G₂ →* G₃) where
toFun g := f.liftOfRightInverseAux f_inv hf g.1 g.2
invFun φ := ⟨φ.comp f, fun x hx ↦ mem_ker.mpr <| by simp [mem_ker.mp hx]⟩
left_inv g := by
ext
simp only [comp_apply, liftOfRightInverseAux_comp_apply, Subtype.coe_mk]
right_inv φ := by
ext b
simp [liftOfRightInverseAux, hf b]
/-- A non-computable version of `MonoidHom.liftOfRightInverse` for when no computable right
inverse is available, that uses `Function.surjInv`. -/
@[to_additive (attr := simp)
"A non-computable version of `AddMonoidHom.liftOfRightInverse` for when no
computable right inverse is available."]
noncomputable abbrev liftOfSurjective (hf : Function.Surjective f) :
{ g : G₁ →* G₃ // f.ker ≤ g.ker } ≃ (G₂ →* G₃) :=
f.liftOfRightInverse (Function.surjInv hf) (Function.rightInverse_surjInv hf)
@[to_additive (attr := simp)]
theorem liftOfRightInverse_comp_apply (hf : Function.RightInverse f_inv f)
(g : { g : G₁ →* G₃ // f.ker ≤ g.ker }) (x : G₁) :
(f.liftOfRightInverse f_inv hf g) (f x) = g.1 x :=
f.liftOfRightInverseAux_comp_apply f_inv hf g.1 g.2 x
@[to_additive (attr := simp)]
theorem liftOfRightInverse_comp (hf : Function.RightInverse f_inv f)
(g : { g : G₁ →* G₃ // f.ker ≤ g.ker }) : (f.liftOfRightInverse f_inv hf g).comp f = g :=
MonoidHom.ext <| f.liftOfRightInverse_comp_apply f_inv hf g
@[to_additive]
theorem eq_liftOfRightInverse (hf : Function.RightInverse f_inv f) (g : G₁ →* G₃)
(hg : f.ker ≤ g.ker) (h : G₂ →* G₃) (hh : h.comp f = g) :
h = f.liftOfRightInverse f_inv hf ⟨g, hg⟩ := by
simp_rw [← hh]
exact ((f.liftOfRightInverse f_inv hf).apply_symm_apply _).symm
end MonoidHom
variable {N : Type*} [Group N]
namespace Subgroup
-- Here `H.Normal` is an explicit argument so we can use dot notation with `comap`.
@[to_additive]
theorem Normal.comap {H : Subgroup N} (hH : H.Normal) (f : G →* N) : (H.comap f).Normal :=
⟨fun _ => by simp +contextual [Subgroup.mem_comap, hH.conj_mem]⟩
@[to_additive]
instance (priority := 100) normal_comap {H : Subgroup N} [nH : H.Normal] (f : G →* N) :
(H.comap f).Normal :=
nH.comap _
-- Here `H.Normal` is an explicit argument so we can use dot notation with `subgroupOf`.
@[to_additive]
theorem Normal.subgroupOf {H : Subgroup G} (hH : H.Normal) (K : Subgroup G) :
(H.subgroupOf K).Normal :=
hH.comap _
@[to_additive]
instance (priority := 100) normal_subgroupOf {H N : Subgroup G} [N.Normal] :
(N.subgroupOf H).Normal :=
Subgroup.normal_comap _
theorem map_normalClosure (s : Set G) (f : G →* N) (hf : Surjective f) :
(normalClosure s).map f = normalClosure (f '' s) := by
have : Normal (map f (normalClosure s)) := Normal.map inferInstance f hf
apply le_antisymm
· simp [map_le_iff_le_comap, normalClosure_le_normal, coe_comap,
← Set.image_subset_iff, subset_normalClosure]
· exact normalClosure_le_normal (Set.image_subset f subset_normalClosure)
theorem comap_normalClosure (s : Set N) (f : G ≃* N) :
normalClosure (f ⁻¹' s) = (normalClosure s).comap f := by
have := Set.preimage_equiv_eq_image_symm s f.toEquiv
simp_all [comap_equiv_eq_map_symm, map_normalClosure s (f.symm : N →* G) f.symm.surjective]
lemma Normal.of_map_injective {G H : Type*} [Group G] [Group H] {φ : G →* H}
(hφ : Function.Injective φ) {L : Subgroup G} (n : (L.map φ).Normal) : L.Normal :=
L.comap_map_eq_self_of_injective hφ ▸ n.comap φ
theorem Normal.of_map_subtype {K : Subgroup G} {L : Subgroup K}
(n : (Subgroup.map K.subtype L).Normal) : L.Normal :=
n.of_map_injective K.subtype_injective
end Subgroup
namespace Subgroup
section SubgroupNormal
@[to_additive]
theorem normal_subgroupOf_iff {H K : Subgroup G} (hHK : H ≤ K) :
(H.subgroupOf K).Normal ↔ ∀ h k, h ∈ H → k ∈ K → k * h * k⁻¹ ∈ H :=
⟨fun hN h k hH hK => hN.conj_mem ⟨h, hHK hH⟩ hH ⟨k, hK⟩, fun hN =>
{ conj_mem := fun h hm k => hN h.1 k.1 hm k.2 }⟩
@[to_additive prod_addSubgroupOf_prod_normal]
instance prod_subgroupOf_prod_normal {H₁ K₁ : Subgroup G} {H₂ K₂ : Subgroup N}
[h₁ : (H₁.subgroupOf K₁).Normal] [h₂ : (H₂.subgroupOf K₂).Normal] :
((H₁.prod H₂).subgroupOf (K₁.prod K₂)).Normal where
conj_mem n hgHK g :=
⟨h₁.conj_mem ⟨(n : G × N).fst, (mem_prod.mp n.2).1⟩ hgHK.1
⟨(g : G × N).fst, (mem_prod.mp g.2).1⟩,
h₂.conj_mem ⟨(n : G × N).snd, (mem_prod.mp n.2).2⟩ hgHK.2
⟨(g : G × N).snd, (mem_prod.mp g.2).2⟩⟩
@[deprecated (since := "2025-03-11")]
alias _root_.AddSubgroup.sum_addSubgroupOf_sum_normal := AddSubgroup.prod_addSubgroupOf_prod_normal
@[to_additive prod_normal]
instance prod_normal (H : Subgroup G) (K : Subgroup N) [hH : H.Normal] [hK : K.Normal] :
(H.prod K).Normal where
conj_mem n hg g :=
⟨hH.conj_mem n.fst (Subgroup.mem_prod.mp hg).1 g.fst,
hK.conj_mem n.snd (Subgroup.mem_prod.mp hg).2 g.snd⟩
@[deprecated (since := "2025-03-11")]
alias _root_.AddSubgroup.sum_normal := AddSubgroup.prod_normal
@[to_additive]
theorem inf_subgroupOf_inf_normal_of_right (A B' B : Subgroup G)
[hN : (B'.subgroupOf B).Normal] : ((A ⊓ B').subgroupOf (A ⊓ B)).Normal := by
rw [normal_subgroupOf_iff_le_normalizer_inf] at hN ⊢
rw [inf_inf_inf_comm, inf_idem]
exact le_trans (inf_le_inf A.le_normalizer hN) (inf_normalizer_le_normalizer_inf)
@[to_additive]
theorem inf_subgroupOf_inf_normal_of_left {A' A : Subgroup G} (B : Subgroup G)
[hN : (A'.subgroupOf A).Normal] : ((A' ⊓ B).subgroupOf (A ⊓ B)).Normal := by
rw [normal_subgroupOf_iff_le_normalizer_inf] at hN ⊢
rw [inf_inf_inf_comm, inf_idem]
exact le_trans (inf_le_inf hN B.le_normalizer) (inf_normalizer_le_normalizer_inf)
@[to_additive]
instance normal_inf_normal (H K : Subgroup G) [hH : H.Normal] [hK : K.Normal] : (H ⊓ K).Normal :=
⟨fun n hmem g => ⟨hH.conj_mem n hmem.1 g, hK.conj_mem n hmem.2 g⟩⟩
@[to_additive]
theorem normal_iInf_normal {ι : Type*} {a : ι → Subgroup G}
(norm : ∀ i : ι, (a i).Normal) : (iInf a).Normal := by
constructor
intro g g_in_iInf h
rw [Subgroup.mem_iInf] at g_in_iInf ⊢
intro i
exact (norm i).conj_mem g (g_in_iInf i) h
@[to_additive]
theorem SubgroupNormal.mem_comm {H K : Subgroup G} (hK : H ≤ K) [hN : (H.subgroupOf K).Normal]
{a b : G} (hb : b ∈ K) (h : a * b ∈ H) : b * a ∈ H := by
have := (normal_subgroupOf_iff hK).mp hN (a * b) b h hb
rwa [mul_assoc, mul_assoc, mul_inv_cancel, mul_one] at this
/-- Elements of disjoint, normal subgroups commute. -/
@[to_additive "Elements of disjoint, normal subgroups commute."]
theorem commute_of_normal_of_disjoint (H₁ H₂ : Subgroup G) (hH₁ : H₁.Normal) (hH₂ : H₂.Normal)
(hdis : Disjoint H₁ H₂) (x y : G) (hx : x ∈ H₁) (hy : y ∈ H₂) : Commute x y := by
suffices x * y * x⁻¹ * y⁻¹ = 1 by
show x * y = y * x
· rw [mul_assoc, mul_eq_one_iff_eq_inv] at this
simpa
apply hdis.le_bot
constructor
· suffices x * (y * x⁻¹ * y⁻¹) ∈ H₁ by simpa [mul_assoc]
exact H₁.mul_mem hx (hH₁.conj_mem _ (H₁.inv_mem hx) _)
· show x * y * x⁻¹ * y⁻¹ ∈ H₂
apply H₂.mul_mem _ (H₂.inv_mem hy)
apply hH₂.conj_mem _ hy
@[to_additive]
theorem normal_subgroupOf_of_le_normalizer {H N : Subgroup G}
(hLE : H ≤ N.normalizer) : (N.subgroupOf H).Normal := by
rw [normal_subgroupOf_iff_le_normalizer_inf]
exact (le_inf hLE H.le_normalizer).trans inf_normalizer_le_normalizer_inf
@[to_additive]
theorem normal_subgroupOf_sup_of_le_normalizer {H N : Subgroup G}
(hLE : H ≤ N.normalizer) : (N.subgroupOf (H ⊔ N)).Normal := by
rw [normal_subgroupOf_iff_le_normalizer le_sup_right]
exact sup_le hLE le_normalizer
end SubgroupNormal
end Subgroup
namespace IsConj
open Subgroup
theorem normalClosure_eq_top_of {N : Subgroup G} [hn : N.Normal] {g g' : G} {hg : g ∈ N}
{hg' : g' ∈ N} (hc : IsConj g g') (ht : normalClosure ({⟨g, hg⟩} : Set N) = ⊤) :
normalClosure ({⟨g', hg'⟩} : Set N) = ⊤ := by
obtain ⟨c, rfl⟩ := isConj_iff.1 hc
have h : ∀ x : N, (MulAut.conj c) x ∈ N := by
rintro ⟨x, hx⟩
exact hn.conj_mem _ hx c
have hs : Function.Surjective (((MulAut.conj c).toMonoidHom.restrict N).codRestrict _ h) := by
rintro ⟨x, hx⟩
refine ⟨⟨c⁻¹ * x * c, ?_⟩, ?_⟩
· have h := hn.conj_mem _ hx c⁻¹
rwa [inv_inv] at h
simp only [MonoidHom.codRestrict_apply, MulEquiv.coe_toMonoidHom, MulAut.conj_apply, coe_mk,
MonoidHom.restrict_apply, Subtype.mk_eq_mk, ← mul_assoc, mul_inv_cancel, one_mul]
rw [mul_assoc, mul_inv_cancel, mul_one]
rw [eq_top_iff, ← MonoidHom.range_eq_top.2 hs, MonoidHom.range_eq_map]
refine le_trans (map_mono (eq_top_iff.1 ht)) (map_le_iff_le_comap.2 (normalClosure_le_normal ?_))
rw [Set.singleton_subset_iff, SetLike.mem_coe]
simp only [MonoidHom.codRestrict_apply, MulEquiv.coe_toMonoidHom, MulAut.conj_apply, coe_mk,
MonoidHom.restrict_apply, mem_comap]
exact subset_normalClosure (Set.mem_singleton _)
end IsConj
namespace ConjClasses
/-- The conjugacy classes that are not trivial. -/
def noncenter (G : Type*) [Monoid G] : Set (ConjClasses G) :=
{x | x.carrier.Nontrivial}
@[simp] lemma mem_noncenter {G} [Monoid G] (g : ConjClasses G) :
g ∈ noncenter G ↔ g.carrier.Nontrivial := Iff.rfl
end ConjClasses
/-- Suppose `G` acts on `M` and `I` is a subgroup of `M`.
The inertia subgroup of `I` is the subgroup of `G` whose action is trivial mod `I`. -/
def AddSubgroup.inertia {M : Type*} [AddGroup M] (I : AddSubgroup M) (G : Type*)
[Group G] [MulAction G M] : Subgroup G where
carrier := { σ | ∀ x, σ • x - x ∈ I }
mul_mem' {a b} ha hb x := by simpa [mul_smul] using add_mem (ha (b • x)) (hb x)
one_mem' := by simp [zero_mem]
inv_mem' {a} ha x := by simpa using sub_mem_comm_iff.mp (ha (a⁻¹ • x))
@[simp] lemma AddSubgroup.mem_inertia {M : Type*} [AddGroup M] {I : AddSubgroup M} {G : Type*}
[Group G] [MulAction G M] {σ : G} : σ ∈ I.inertia G ↔ ∀ x, σ • x - x ∈ I := .rfl
| Mathlib/Algebra/Group/Subgroup/Basic.lean | 3,070 | 3,072 | |
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.MeasureTheory.Measure.AEMeasurable
/-!
# Typeclasses for measurability of lattice operations
In this file we define classes `MeasurableSup` and `MeasurableInf` and prove dot-style
lemmas (`Measurable.sup`, `AEMeasurable.sup` etc). For binary operations we define two typeclasses:
- `MeasurableSup` says that both left and right sup are measurable;
- `MeasurableSup₂` says that `fun p : α × α => p.1 ⊔ p.2` is measurable,
and similarly for other binary operations. The reason for introducing these classes is that in case
of topological space `α` equipped with the Borel `σ`-algebra, instances for `MeasurableSup₂`
etc require `α` to have a second countable topology.
For instances relating, e.g., `ContinuousSup` to `MeasurableSup` see file
`MeasureTheory.BorelSpace`.
## Tags
measurable function, lattice operation
-/
open MeasureTheory
/-- We say that a type has `MeasurableSup` if `(c ⊔ ·)` and `(· ⊔ c)` are measurable functions.
For a typeclass assuming measurability of `uncurry (· ⊔ ·)` see `MeasurableSup₂`. -/
class MeasurableSup (M : Type*) [MeasurableSpace M] [Max M] : Prop where
measurable_const_sup : ∀ c : M, Measurable (c ⊔ ·)
measurable_sup_const : ∀ c : M, Measurable (· ⊔ c)
/-- We say that a type has `MeasurableSup₂` if `uncurry (· ⊔ ·)` is a measurable functions.
For a typeclass assuming measurability of `(c ⊔ ·)` and `(· ⊔ c)` see `MeasurableSup`. -/
class MeasurableSup₂ (M : Type*) [MeasurableSpace M] [Max M] : Prop where
measurable_sup : Measurable fun p : M × M => p.1 ⊔ p.2
export MeasurableSup₂ (measurable_sup)
export MeasurableSup (measurable_const_sup measurable_sup_const)
/-- We say that a type has `MeasurableInf` if `(c ⊓ ·)` and `(· ⊓ c)` are measurable functions.
For a typeclass assuming measurability of `uncurry (· ⊓ ·)` see `MeasurableInf₂`. -/
class MeasurableInf (M : Type*) [MeasurableSpace M] [Min M] : Prop where
measurable_const_inf : ∀ c : M, Measurable (c ⊓ ·)
measurable_inf_const : ∀ c : M, Measurable (· ⊓ c)
/-- We say that a type has `MeasurableInf₂` if `uncurry (· ⊓ ·)` is a measurable functions.
For a typeclass assuming measurability of `(c ⊓ ·)` and `(· ⊓ c)` see `MeasurableInf`. -/
class MeasurableInf₂ (M : Type*) [MeasurableSpace M] [Min M] : Prop where
measurable_inf : Measurable fun p : M × M => p.1 ⊓ p.2
export MeasurableInf₂ (measurable_inf)
export MeasurableInf (measurable_const_inf measurable_inf_const)
variable {M : Type*} [MeasurableSpace M]
section OrderDual
instance (priority := 100) OrderDual.instMeasurableSup [Min M] [MeasurableInf M] :
MeasurableSup Mᵒᵈ :=
⟨@measurable_const_inf M _ _ _, @measurable_inf_const M _ _ _⟩
instance (priority := 100) OrderDual.instMeasurableInf [Max M] [MeasurableSup M] :
MeasurableInf Mᵒᵈ :=
⟨@measurable_const_sup M _ _ _, @measurable_sup_const M _ _ _⟩
instance (priority := 100) OrderDual.instMeasurableSup₂ [Min M] [MeasurableInf₂ M] :
MeasurableSup₂ Mᵒᵈ :=
⟨@measurable_inf M _ _ _⟩
instance (priority := 100) OrderDual.instMeasurableInf₂ [Max M] [MeasurableSup₂ M] :
MeasurableInf₂ Mᵒᵈ :=
⟨@measurable_sup M _ _ _⟩
end OrderDual
variable {α : Type*} {m : MeasurableSpace α} {μ : Measure α} {f g : α → M}
section Sup
variable [Max M]
section MeasurableSup
variable [MeasurableSup M]
@[measurability]
theorem Measurable.const_sup (hf : Measurable f) (c : M) : Measurable fun x => c ⊔ f x :=
(measurable_const_sup c).comp hf
@[measurability]
theorem AEMeasurable.const_sup (hf : AEMeasurable f μ) (c : M) :
AEMeasurable (fun x => c ⊔ f x) μ :=
(MeasurableSup.measurable_const_sup c).comp_aemeasurable hf
@[measurability]
theorem Measurable.sup_const (hf : Measurable f) (c : M) : Measurable fun x => f x ⊔ c :=
(measurable_sup_const c).comp hf
@[measurability]
theorem AEMeasurable.sup_const (hf : AEMeasurable f μ) (c : M) :
AEMeasurable (fun x => f x ⊔ c) μ :=
(measurable_sup_const c).comp_aemeasurable hf
end MeasurableSup
section MeasurableSup₂
variable [MeasurableSup₂ M]
@[measurability]
theorem Measurable.sup' (hf : Measurable f) (hg : Measurable g) : Measurable (f ⊔ g) :=
measurable_sup.comp (hf.prodMk hg)
@[measurability]
theorem Measurable.sup (hf : Measurable f) (hg : Measurable g) : Measurable fun a => f a ⊔ g a :=
measurable_sup.comp (hf.prodMk hg)
@[measurability]
theorem AEMeasurable.sup' (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (f ⊔ g) μ :=
measurable_sup.comp_aemeasurable (hf.prodMk hg)
@[measurability]
theorem AEMeasurable.sup (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (fun a => f a ⊔ g a) μ :=
measurable_sup.comp_aemeasurable (hf.prodMk hg)
instance (priority := 100) MeasurableSup₂.toMeasurableSup : MeasurableSup M :=
⟨fun _ => measurable_const.sup measurable_id, fun _ => measurable_id.sup measurable_const⟩
end MeasurableSup₂
end Sup
section Inf
variable [Min M]
section MeasurableInf
variable [MeasurableInf M]
@[measurability]
theorem Measurable.const_inf (hf : Measurable f) (c : M) : Measurable fun x => c ⊓ f x :=
(measurable_const_inf c).comp hf
@[measurability]
theorem AEMeasurable.const_inf (hf : AEMeasurable f μ) (c : M) :
AEMeasurable (fun x => c ⊓ f x) μ :=
(MeasurableInf.measurable_const_inf c).comp_aemeasurable hf
@[measurability]
theorem Measurable.inf_const (hf : Measurable f) (c : M) : Measurable fun x => f x ⊓ c :=
(measurable_inf_const c).comp hf
@[measurability]
theorem AEMeasurable.inf_const (hf : AEMeasurable f μ) (c : M) :
AEMeasurable (fun x => f x ⊓ c) μ :=
(measurable_inf_const c).comp_aemeasurable hf
end MeasurableInf
section MeasurableInf₂
variable [MeasurableInf₂ M]
@[measurability]
theorem Measurable.inf' (hf : Measurable f) (hg : Measurable g) : Measurable (f ⊓ g) :=
measurable_inf.comp (hf.prodMk hg)
@[measurability]
theorem Measurable.inf (hf : Measurable f) (hg : Measurable g) : Measurable fun a => f a ⊓ g a :=
measurable_inf.comp (hf.prodMk hg)
@[measurability]
theorem AEMeasurable.inf' (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (f ⊓ g) μ :=
measurable_inf.comp_aemeasurable (hf.prodMk hg)
@[measurability]
theorem AEMeasurable.inf (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
AEMeasurable (fun a => f a ⊓ g a) μ :=
measurable_inf.comp_aemeasurable (hf.prodMk hg)
instance (priority := 100) MeasurableInf₂.to_hasMeasurableInf : MeasurableInf M :=
⟨fun _ => measurable_const.inf measurable_id, fun _ => measurable_id.inf measurable_const⟩
end MeasurableInf₂
end Inf
section SemilatticeSup
open Finset
variable {δ : Type*} [MeasurableSpace δ] [SemilatticeSup α] [MeasurableSup₂ α]
@[measurability]
theorem Finset.measurable_sup' {ι : Type*} {s : Finset ι} (hs : s.Nonempty) {f : ι → δ → α}
(hf : ∀ n ∈ s, Measurable (f n)) : Measurable (s.sup' hs f) :=
Finset.sup'_induction hs _ (fun _f hf _g hg => hf.sup hg) fun n hn => hf n hn
@[measurability]
theorem Finset.measurable_range_sup' {f : ℕ → δ → α} {n : ℕ} (hf : ∀ k ≤ n, Measurable (f k)) :
Measurable ((range (n + 1)).sup' nonempty_range_succ f) := by
simp_rw [← Nat.lt_succ_iff] at hf
refine Finset.measurable_sup' _ ?_
simpa [Finset.mem_range]
@[measurability]
theorem Finset.measurable_range_sup'' {f : ℕ → δ → α} {n : ℕ} (hf : ∀ k ≤ n, Measurable (f k)) :
Measurable fun x => (range (n + 1)).sup' nonempty_range_succ fun k => f k x := by
convert Finset.measurable_range_sup' hf using 1
ext x
simp
end SemilatticeSup
| Mathlib/MeasureTheory/Order/Lattice.lean | 256 | 260 | |
/-
Copyright (c) 2020 Kevin Buzzard, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Equalizers
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Products
import Mathlib.CategoryTheory.Limits.Yoneda
import Mathlib.CategoryTheory.Preadditive.FunctorCategory
import Mathlib.CategoryTheory.Sites.SheafOfTypes
import Mathlib.CategoryTheory.Sites.EqualizerSheafCondition
import Mathlib.CategoryTheory.Limits.Constructions.EpiMono
/-!
# Sheaves taking values in a category
If C is a category with a Grothendieck topology, we define the notion of a sheaf taking values in
an arbitrary category `A`. We follow the definition in https://stacks.math.columbia.edu/tag/00VR,
noting that the presheaf of sets "defined above" can be seen in the comments between tags 00VQ and
00VR on the page <https://stacks.math.columbia.edu/tag/00VL>. The advantage of this definition is
that we need no assumptions whatsoever on `A` other than the assumption that the morphisms in `C`
and `A` live in the same universe.
* An `A`-valued presheaf `P : Cᵒᵖ ⥤ A` is defined to be a sheaf (for the topology `J`) iff for
every `E : A`, the type-valued presheaves of sets given by sending `U : Cᵒᵖ` to `Hom_{A}(E, P U)`
are all sheaves of sets, see `CategoryTheory.Presheaf.IsSheaf`.
* When `A = Type`, this recovers the basic definition of sheaves of sets, see
`CategoryTheory.isSheaf_iff_isSheaf_of_type`.
* A alternate definition in terms of limits, unconditionally equivalent to the original one:
see `CategoryTheory.Presheaf.isSheaf_iff_isLimit`.
* An alternate definition when `C` is small, has pullbacks and `A` has products is given by an
equalizer condition `CategoryTheory.Presheaf.IsSheaf'`. This is equivalent to the earlier
definition, shown in `CategoryTheory.Presheaf.isSheaf_iff_isSheaf'`.
* When `A = Type`, this is *definitionally* equal to the equalizer condition for presieves in
`CategoryTheory.Sites.SheafOfTypes`.
* When `A` has limits and there is a functor `s : A ⥤ Type` which is faithful, reflects isomorphisms
and preserves limits, then `P : Cᵒᵖ ⥤ A` is a sheaf iff the underlying presheaf of types
`P ⋙ s : Cᵒᵖ ⥤ Type` is a sheaf (`CategoryTheory.Presheaf.isSheaf_iff_isSheaf_forget`).
Cf https://stacks.math.columbia.edu/tag/0073, which is a weaker version of this statement (it's
only over spaces, not sites) and https://stacks.math.columbia.edu/tag/00YR (a), which
additionally assumes filtered colimits.
## Implementation notes
Occasionally we need to take a limit in `A` of a collection of morphisms of `C` indexed
by a collection of objects in `C`. This turns out to force the morphisms of `A` to be
in a sufficiently large universe. Rather than use `UnivLE` we prove some results for
a category `A'` instead, whose morphism universe of `A'` is defined to be `max u₁ v₁`, where
`u₁, v₁` are the universes for `C`. Perhaps after we get better at handling universe
inequalities this can be changed.
-/
universe w v₁ v₂ v₃ u₁ u₂ u₃
noncomputable section
namespace CategoryTheory
open Opposite CategoryTheory Category Limits Sieve
namespace Presheaf
variable {C : Type u₁} [Category.{v₁} C]
variable {A : Type u₂} [Category.{v₂} A]
variable (J : GrothendieckTopology C)
-- We follow https://stacks.math.columbia.edu/tag/00VL definition 00VR
/-- A sheaf of A is a presheaf P : Cᵒᵖ => A such that for every E : A, the
presheaf of types given by sending U : C to Hom_{A}(E, P U) is a sheaf of types. -/
@[stacks 00VR]
def IsSheaf (P : Cᵒᵖ ⥤ A) : Prop :=
∀ E : A, Presieve.IsSheaf J (P ⋙ coyoneda.obj (op E))
/-- Condition that a presheaf with values in a concrete category is separated for
a Grothendieck topology. -/
def IsSeparated (P : Cᵒᵖ ⥤ A) {FA : A → A → Type*} {CA : A → Type*}
[∀ X Y, FunLike (FA X Y) (CA X) (CA Y)] [ConcreteCategory A FA] : Prop :=
∀ (X : C) (S : Sieve X) (_ : S ∈ J X) (x y : ToType (P.obj (op X))),
(∀ (Y : C) (f : Y ⟶ X) (_ : S f), P.map f.op x = P.map f.op y) → x = y
section LimitSheafCondition
open Presieve Presieve.FamilyOfElements Limits
variable (P : Cᵒᵖ ⥤ A) {X : C} (S : Sieve X) (R : Presieve X) (E : Aᵒᵖ)
/-- Given a sieve `S` on `X : C`, a presheaf `P : Cᵒᵖ ⥤ A`, and an object `E` of `A`,
the cones over the natural diagram `S.arrows.diagram.op ⋙ P` associated to `S` and `P`
with cone point `E` are in 1-1 correspondence with sieve_compatible family of elements
for the sieve `S` and the presheaf of types `Hom (E, P -)`. -/
def conesEquivSieveCompatibleFamily :
(S.arrows.diagram.op ⋙ P).cones.obj E ≃
{ x : FamilyOfElements (P ⋙ coyoneda.obj E) (S : Presieve X) // x.SieveCompatible } where
toFun π :=
⟨fun _ f h => π.app (op ⟨Over.mk f, h⟩), fun X Y f g hf => by
apply (id_comp _).symm.trans
dsimp
exact π.naturality (Quiver.Hom.op (Over.homMk _ (by rfl)))⟩
invFun x :=
{ app := fun f => x.1 f.unop.1.hom f.unop.2
naturality := fun f f' g => by
refine Eq.trans ?_ (x.2 f.unop.1.hom g.unop.left f.unop.2)
dsimp
rw [id_comp]
convert rfl
rw [Over.w] }
left_inv _ := rfl
right_inv _ := rfl
variable {P S E}
variable {x : FamilyOfElements (P ⋙ coyoneda.obj E) S.arrows} (hx : SieveCompatible x)
/-- The cone corresponding to a sieve_compatible family of elements, dot notation enabled. -/
@[simp]
def _root_.CategoryTheory.Presieve.FamilyOfElements.SieveCompatible.cone :
Cone (S.arrows.diagram.op ⋙ P) where
pt := E.unop
π := (conesEquivSieveCompatibleFamily P S E).invFun ⟨x, hx⟩
/-- Cone morphisms from the cone corresponding to a sieve_compatible family to the natural
cone associated to a sieve `S` and a presheaf `P` are in 1-1 correspondence with amalgamations
of the family. -/
def homEquivAmalgamation :
(hx.cone ⟶ P.mapCone S.arrows.cocone.op) ≃ { t // x.IsAmalgamation t } where
toFun l := ⟨l.hom, fun _ f hf => l.w (op ⟨Over.mk f, hf⟩)⟩
invFun t := ⟨t.1, fun f => t.2 f.unop.1.hom f.unop.2⟩
left_inv _ := rfl
right_inv _ := rfl
variable (P S)
/-- Given sieve `S` and presheaf `P : Cᵒᵖ ⥤ A`, their natural associated cone is a limit cone
iff `Hom (E, P -)` is a sheaf of types for the sieve `S` and all `E : A`. -/
theorem isLimit_iff_isSheafFor :
Nonempty (IsLimit (P.mapCone S.arrows.cocone.op)) ↔
∀ E : Aᵒᵖ, IsSheafFor (P ⋙ coyoneda.obj E) S.arrows := by
dsimp [IsSheafFor]; simp_rw [compatible_iff_sieveCompatible]
rw [((Cone.isLimitEquivIsTerminal _).trans (isTerminalEquivUnique _ _)).nonempty_congr]
rw [Classical.nonempty_pi]; constructor
· intro hu E x hx
specialize hu hx.cone
rw [(homEquivAmalgamation hx).uniqueCongr.nonempty_congr] at hu
exact (unique_subtype_iff_existsUnique _).1 hu
· rintro h ⟨E, π⟩
let eqv := conesEquivSieveCompatibleFamily P S (op E)
rw [← eqv.left_inv π]
erw [(homEquivAmalgamation (eqv π).2).uniqueCongr.nonempty_congr]
rw [unique_subtype_iff_existsUnique]
exact h _ _ (eqv π).2
/-- Given sieve `S` and presheaf `P : Cᵒᵖ ⥤ A`, their natural associated cone admits at most one
morphism from every cone in the same category (i.e. over the same diagram),
iff `Hom (E, P -)`is separated for the sieve `S` and all `E : A`. -/
theorem subsingleton_iff_isSeparatedFor :
(∀ c, Subsingleton (c ⟶ P.mapCone S.arrows.cocone.op)) ↔
∀ E : Aᵒᵖ, IsSeparatedFor (P ⋙ coyoneda.obj E) S.arrows := by
constructor
· intro hs E x t₁ t₂ h₁ h₂
have hx := is_compatible_of_exists_amalgamation x ⟨t₁, h₁⟩
rw [compatible_iff_sieveCompatible] at hx
specialize hs hx.cone
rcases hs with ⟨hs⟩
simpa only [Subtype.mk.injEq] using (show Subtype.mk t₁ h₁ = ⟨t₂, h₂⟩ from
(homEquivAmalgamation hx).symm.injective (hs _ _))
· rintro h ⟨E, π⟩
let eqv := conesEquivSieveCompatibleFamily P S (op E)
constructor
rw [← eqv.left_inv π]
intro f₁ f₂
let eqv' := homEquivAmalgamation (eqv π).2
apply eqv'.injective
ext
apply h _ (eqv π).1 <;> exact (eqv' _).2
/-- A presheaf `P` is a sheaf for the Grothendieck topology `J` iff for every covering sieve
`S` of `J`, the natural cone associated to `P` and `S` is a limit cone. -/
theorem isSheaf_iff_isLimit :
IsSheaf J P ↔
∀ ⦃X : C⦄ (S : Sieve X), S ∈ J X → Nonempty (IsLimit (P.mapCone S.arrows.cocone.op)) :=
⟨fun h _ S hS => (isLimit_iff_isSheafFor P S).2 fun E => h E.unop S hS, fun h E _ S hS =>
(isLimit_iff_isSheafFor P S).1 (h S hS) (op E)⟩
/-- A presheaf `P` is separated for the Grothendieck topology `J` iff for every covering sieve
`S` of `J`, the natural cone associated to `P` and `S` admits at most one morphism from every
cone in the same category. -/
theorem isSeparated_iff_subsingleton :
(∀ E : A, Presieve.IsSeparated J (P ⋙ coyoneda.obj (op E))) ↔
∀ ⦃X : C⦄ (S : Sieve X), S ∈ J X → ∀ c, Subsingleton (c ⟶ P.mapCone S.arrows.cocone.op) :=
⟨fun h _ S hS => (subsingleton_iff_isSeparatedFor P S).2 fun E => h E.unop S hS, fun h E _ S hS =>
(subsingleton_iff_isSeparatedFor P S).1 (h S hS) (op E)⟩
/-- Given presieve `R` and presheaf `P : Cᵒᵖ ⥤ A`, the natural cone associated to `P` and
the sieve `Sieve.generate R` generated by `R` is a limit cone iff `Hom (E, P -)` is a
sheaf of types for the presieve `R` and all `E : A`. -/
theorem isLimit_iff_isSheafFor_presieve :
Nonempty (IsLimit (P.mapCone (generate R).arrows.cocone.op)) ↔
∀ E : Aᵒᵖ, IsSheafFor (P ⋙ coyoneda.obj E) R :=
(isLimit_iff_isSheafFor P _).trans (forall_congr' fun _ => (isSheafFor_iff_generate _).symm)
/-- A presheaf `P` is a sheaf for the Grothendieck topology generated by a pretopology `K`
iff for every covering presieve `R` of `K`, the natural cone associated to `P` and
`Sieve.generate R` is a limit cone. -/
theorem isSheaf_iff_isLimit_pretopology [HasPullbacks C] (K : Pretopology C) :
IsSheaf (K.toGrothendieck C) P ↔
∀ ⦃X : C⦄ (R : Presieve X),
R ∈ K X → Nonempty (IsLimit (P.mapCone (generate R).arrows.cocone.op)) := by
dsimp [IsSheaf]
simp_rw [isSheaf_pretopology]
exact
⟨fun h X R hR => (isLimit_iff_isSheafFor_presieve P R).2 fun E => h E.unop R hR,
fun h E X R hR => (isLimit_iff_isSheafFor_presieve P R).1 (h R hR) (op E)⟩
end LimitSheafCondition
variable {J}
/-- This is a wrapper around `Presieve.IsSheafFor.amalgamate` to be used below.
If `P`s a sheaf, `S` is a cover of `X`, and `x` is a collection of morphisms from `E`
to `P` evaluated at terms in the cover which are compatible, then we can amalgamate
the `x`s to obtain a single morphism `E ⟶ P.obj (op X)`. -/
def IsSheaf.amalgamate {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A}
(hP : Presheaf.IsSheaf J P) (S : J.Cover X) (x : ∀ I : S.Arrow, E ⟶ P.obj (op I.Y))
(hx : ∀ ⦃I₁ I₂ : S.Arrow⦄ (r : I₁.Relation I₂),
x I₁ ≫ P.map r.g₁.op = x I₂ ≫ P.map r.g₂.op) : E ⟶ P.obj (op X) :=
(hP _ _ S.condition).amalgamate (fun Y f hf => x ⟨Y, f, hf⟩) fun _ _ _ _ _ _ _ h₁ h₂ w =>
@hx { hf := h₁, .. } { hf := h₂, .. } { w := w, .. }
@[reassoc (attr := simp)]
theorem IsSheaf.amalgamate_map {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A}
(hP : Presheaf.IsSheaf J P) (S : J.Cover X) (x : ∀ I : S.Arrow, E ⟶ P.obj (op I.Y))
(hx : ∀ ⦃I₁ I₂ : S.Arrow⦄ (r : I₁.Relation I₂),
x I₁ ≫ P.map r.g₁.op = x I₂ ≫ P.map r.g₂.op)
(I : S.Arrow) :
hP.amalgamate S x hx ≫ P.map I.f.op = x _ := by
apply (hP _ _ S.condition).valid_glue
theorem IsSheaf.hom_ext {A : Type u₂} [Category.{v₂} A] {E : A} {X : C} {P : Cᵒᵖ ⥤ A}
(hP : Presheaf.IsSheaf J P) (S : J.Cover X) (e₁ e₂ : E ⟶ P.obj (op X))
(h : ∀ I : S.Arrow, e₁ ≫ P.map I.f.op = e₂ ≫ P.map I.f.op) : e₁ = e₂ :=
(hP _ _ S.condition).isSeparatedFor.ext fun Y f hf => h ⟨Y, f, hf⟩
lemma IsSheaf.hom_ext_ofArrows
{P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) {I : Type*} {S : C} {X : I → C}
(f : ∀ i, X i ⟶ S) (hf : Sieve.ofArrows _ f ∈ J S) {E : A}
{x y : E ⟶ P.obj (op S)} (h : ∀ i, x ≫ P.map (f i).op = y ≫ P.map (f i).op) :
x = y := by
apply hP.hom_ext ⟨_, hf⟩
rintro ⟨Z, _, _, g, _, ⟨i⟩, rfl⟩
dsimp
rw [P.map_comp, reassoc_of% (h i)]
section
variable {P : Cᵒᵖ ⥤ A} (hP : Presheaf.IsSheaf J P) {I : Type*} {S : C} {X : I → C}
(f : ∀ i, X i ⟶ S) (hf : Sieve.ofArrows _ f ∈ J S) {E : A}
(x : ∀ i, E ⟶ P.obj (op (X i)))
(hx : ∀ ⦃W : C⦄ ⦃i j : I⦄ (a : W ⟶ X i) (b : W ⟶ X j),
a ≫ f i = b ≫ f j → x i ≫ P.map a.op = x j ≫ P.map b.op)
include hP hf hx
lemma IsSheaf.existsUnique_amalgamation_ofArrows :
∃! (g : E ⟶ P.obj (op S)), ∀ (i : I), g ≫ P.map (f i).op = x i :=
(Presieve.isSheafFor_arrows_iff _ _).1
((Presieve.isSheafFor_iff_generate _).2 (hP E _ hf)) x (fun _ _ _ _ _ w => hx _ _ w)
@[deprecated (since := "2024-12-17")]
alias IsSheaf.exists_unique_amalgamation_ofArrows := IsSheaf.existsUnique_amalgamation_ofArrows
/-- If `P : Cᵒᵖ ⥤ A` is a sheaf and `f i : X i ⟶ S` is a covering family, then
a morphism `E ⟶ P.obj (op S)` can be constructed from a compatible family of
morphisms `x : E ⟶ P.obj (op (X i))`. -/
def IsSheaf.amalgamateOfArrows : E ⟶ P.obj (op S) :=
(hP.existsUnique_amalgamation_ofArrows f hf x hx).choose
@[reassoc (attr := simp)]
lemma IsSheaf.amalgamateOfArrows_map (i : I) :
hP.amalgamateOfArrows f hf x hx ≫ P.map (f i).op = x i :=
(hP.existsUnique_amalgamation_ofArrows f hf x hx).choose_spec.1 i
end
theorem isSheaf_of_iso_iff {P P' : Cᵒᵖ ⥤ A} (e : P ≅ P') : IsSheaf J P ↔ IsSheaf J P' :=
forall_congr' fun _ =>
⟨Presieve.isSheaf_iso J (isoWhiskerRight e _),
Presieve.isSheaf_iso J (isoWhiskerRight e.symm _)⟩
variable (J)
theorem isSheaf_of_isTerminal {X : A} (hX : IsTerminal X) :
Presheaf.IsSheaf J ((CategoryTheory.Functor.const _).obj X) := fun _ _ _ _ _ _ =>
⟨hX.from _, fun _ _ _ => hX.hom_ext _ _, fun _ _ => hX.hom_ext _ _⟩
end Presheaf
variable {C : Type u₁} [Category.{v₁} C]
variable (J : GrothendieckTopology C)
variable (A : Type u₂) [Category.{v₂} A]
/-- The category of sheaves taking values in `A` on a grothendieck topology. -/
structure Sheaf where
/-- the underlying presheaf -/
val : Cᵒᵖ ⥤ A
/-- the condition that the presheaf is a sheaf -/
cond : Presheaf.IsSheaf J val
namespace Sheaf
variable {J A}
/-- Morphisms between sheaves are just morphisms of presheaves. -/
@[ext]
structure Hom (X Y : Sheaf J A) where
/-- a morphism between the underlying presheaves -/
val : X.val ⟶ Y.val
@[simps id_val comp_val]
instance instCategorySheaf : Category (Sheaf J A) where
Hom := Hom
id _ := ⟨𝟙 _⟩
comp f g := ⟨f.val ≫ g.val⟩
id_comp _ := Hom.ext <| id_comp _
comp_id _ := Hom.ext <| comp_id _
assoc _ _ _ := Hom.ext <| assoc _ _ _
-- Let's make the inhabited linter happy.../sips
instance (X : Sheaf J A) : Inhabited (Hom X X) :=
⟨𝟙 X⟩
@[ext]
lemma hom_ext {X Y : Sheaf J A} (x y : X ⟶ Y) (h : x.val = y.val) : x = y :=
Sheaf.Hom.ext h
end Sheaf
/-- The inclusion functor from sheaves to presheaves. -/
@[simps]
def sheafToPresheaf : Sheaf J A ⥤ Cᵒᵖ ⥤ A where
obj := Sheaf.val
map f := f.val
map_id _ := rfl
map_comp _ _ := rfl
/-- The sections of a sheaf (i.e. evaluation as a presheaf on `C`). -/
abbrev sheafSections : Cᵒᵖ ⥤ Sheaf J A ⥤ A := (sheafToPresheaf J A).flip
/-- The sheaf sections functor on `X` is given by evaluation of presheaves on `X`. -/
@[simps!]
def sheafSectionsNatIsoEvaluation {X : C} :
(sheafSections J A).obj (op X) ≅ sheafToPresheaf J A ⋙ (evaluation _ _).obj (op X) :=
NatIso.ofComponents (fun _ ↦ Iso.refl _)
/-- The functor `Sheaf J A ⥤ Cᵒᵖ ⥤ A` is fully faithful. -/
@[simps]
def fullyFaithfulSheafToPresheaf : (sheafToPresheaf J A).FullyFaithful where
preimage f := ⟨f⟩
variable {J A} in
/-- The bijection `(X ⟶ Y) ≃ (X.val ⟶ Y.val)` when `X` and `Y` are sheaves. -/
abbrev Sheaf.homEquiv {X Y : Sheaf J A} : (X ⟶ Y) ≃ (X.val ⟶ Y.val) :=
(fullyFaithfulSheafToPresheaf J A).homEquiv
instance : (sheafToPresheaf J A).Full :=
(fullyFaithfulSheafToPresheaf J A).full
instance : (sheafToPresheaf J A).Faithful :=
(fullyFaithfulSheafToPresheaf J A).faithful
instance : (sheafToPresheaf J A).ReflectsIsomorphisms :=
(fullyFaithfulSheafToPresheaf J A).reflectsIsomorphisms
/-- This is stated as a lemma to prevent class search from forming a loop since a sheaf morphism is
monic if and only if it is monic as a presheaf morphism (under suitable assumption). -/
theorem Sheaf.Hom.mono_of_presheaf_mono {F G : Sheaf J A} (f : F ⟶ G) [h : Mono f.1] : Mono f :=
(sheafToPresheaf J A).mono_of_mono_map h
instance Sheaf.Hom.epi_of_presheaf_epi {F G : Sheaf J A} (f : F ⟶ G) [h : Epi f.1] : Epi f :=
(sheafToPresheaf J A).epi_of_epi_map h
theorem isSheaf_iff_isSheaf_of_type (P : Cᵒᵖ ⥤ Type w) :
Presheaf.IsSheaf J P ↔ Presieve.IsSheaf J P := by
constructor
· intro hP
refine Presieve.isSheaf_iso J ?_ (hP PUnit)
exact isoWhiskerLeft _ Coyoneda.punitIso ≪≫ P.rightUnitor
· intro hP X Y S hS z hz
refine ⟨fun x => (hP S hS).amalgamate (fun Z f hf => z f hf x) ?_, ?_, ?_⟩
· intro Y₁ Y₂ Z g₁ g₂ f₁ f₂ hf₁ hf₂ h
exact congr_fun (hz g₁ g₂ hf₁ hf₂ h) x
· intro Z f hf
funext x
apply Presieve.IsSheafFor.valid_glue
· intro y hy
funext x
apply (hP S hS).isSeparatedFor.ext
intro Y' f hf
rw [Presieve.IsSheafFor.valid_glue _ _ _ hf, ← hy _ hf]
rfl
/-- The sheaf of sections guaranteed by the sheaf condition. -/
@[simps]
def sheafOver {A : Type u₂} [Category.{v₂} A] {J : GrothendieckTopology C} (ℱ : Sheaf J A) (E : A) :
Sheaf J (Type _) where
val := ℱ.val ⋙ coyoneda.obj (op E)
cond := by
rw [isSheaf_iff_isSheaf_of_type]
exact ℱ.cond E
variable {J} in
lemma Presheaf.IsSheaf.isSheafFor {P : Cᵒᵖ ⥤ Type w} (hP : Presheaf.IsSheaf J P)
{X : C} (S : Sieve X) (hS : S ∈ J X) : Presieve.IsSheafFor P S.arrows := by
rw [isSheaf_iff_isSheaf_of_type] at hP
exact hP S hS
variable {A} in
lemma Presheaf.isSheaf_bot (P : Cᵒᵖ ⥤ A) : IsSheaf ⊥ P := fun _ ↦ Presieve.isSheaf_bot
/--
The category of sheaves on the bottom (trivial) Grothendieck topology is
equivalent to the category of presheaves.
-/
@[simps]
def sheafBotEquivalence : Sheaf (⊥ : GrothendieckTopology C) A ≌ Cᵒᵖ ⥤ A where
functor := sheafToPresheaf _ _
inverse :=
{ obj := fun P => ⟨P, Presheaf.isSheaf_bot P⟩
map := fun f => ⟨f⟩ }
unitIso := Iso.refl _
counitIso := Iso.refl _
instance : Inhabited (Sheaf (⊥ : GrothendieckTopology C) (Type w)) :=
⟨(sheafBotEquivalence _).inverse.obj ((Functor.const _).obj default)⟩
variable {J} {A}
/-- If the empty sieve is a cover of `X`, then `F(X)` is terminal. -/
def Sheaf.isTerminalOfBotCover (F : Sheaf J A) (X : C) (H : ⊥ ∈ J X) :
IsTerminal (F.1.obj (op X)) := by
refine @IsTerminal.ofUnique _ _ _ ?_
intro Y
choose t h using F.2 Y _ H (by tauto) (by tauto)
exact ⟨⟨t⟩, fun a => h.2 a (by tauto)⟩
section Preadditive
open Preadditive
variable [Preadditive A] {P Q : Sheaf J A}
instance sheafHomHasZSMul : SMul ℤ (P ⟶ Q) where
smul n f :=
Sheaf.Hom.mk
{ app := fun U => n • f.1.app U
naturality := fun U V i => by
induction' n with n ih n ih
· simp only [zero_smul, comp_zero, zero_comp]
· simpa only [add_zsmul, one_zsmul, comp_add, NatTrans.naturality, add_comp,
add_left_inj]
· simpa only [sub_smul, one_zsmul, comp_sub, NatTrans.naturality, sub_comp,
sub_left_inj] using ih }
instance : Sub (P ⟶ Q) where sub f g := Sheaf.Hom.mk <| f.1 - g.1
instance : Neg (P ⟶ Q) where neg f := Sheaf.Hom.mk <| -f.1
instance sheafHomHasNSMul : SMul ℕ (P ⟶ Q) where
smul n f :=
Sheaf.Hom.mk
{ app := fun U => n • f.1.app U
naturality := fun U V i => by
induction n with
| zero => simp only [zero_smul, comp_zero, zero_comp]
| succ n ih => simp only [Nat.succ_eq_add_one, add_smul, ih, one_nsmul, comp_add,
NatTrans.naturality, add_comp] }
instance : Zero (P ⟶ Q) where zero := Sheaf.Hom.mk 0
instance : Add (P ⟶ Q) where add f g := Sheaf.Hom.mk <| f.1 + g.1
@[simp]
theorem Sheaf.Hom.add_app (f g : P ⟶ Q) (U) : (f + g).1.app U = f.1.app U + g.1.app U :=
rfl
instance Sheaf.Hom.addCommGroup : AddCommGroup (P ⟶ Q) :=
Function.Injective.addCommGroup (fun f : Sheaf.Hom P Q => f.1)
(fun _ _ h => Sheaf.Hom.ext h) rfl (fun _ _ => rfl) (fun _ => rfl) (fun _ _ => rfl)
(fun _ _ => by aesop_cat) (fun _ _ => by aesop_cat)
instance : Preadditive (Sheaf J A) where
homGroup _ _ := Sheaf.Hom.addCommGroup
end Preadditive
end CategoryTheory
namespace CategoryTheory
open Opposite CategoryTheory Category Limits Sieve
namespace Presheaf
-- Under here is the equalizer story, which is equivalent if A has products (and doesn't
-- make sense otherwise). It's described in https://stacks.math.columbia.edu/tag/00VL,
-- between 00VQ and 00VR.
variable {C : Type u₁} [Category.{v₁} C]
-- `A` is a general category; `A'` is a variant where the morphisms live in a large enough
-- universe to guarantee that we can take limits in A of things coming from C.
-- I would have liked to use something like `UnivLE.{max v₁ u₁, v₂}` as a hypothesis on
-- `A`'s morphism universe rather than introducing `A'` but I can't get it to work.
-- So, for now, results which need max v₁ u₁ ≤ v₂ are just stated for `A'` and `P' : Cᵒᵖ ⥤ A'`
-- instead.
variable {A : Type u₂} [Category.{v₂} A]
variable {A' : Type u₂} [Category.{max v₁ u₁} A']
variable {B : Type u₃} [Category.{v₃} B]
variable (J : GrothendieckTopology C)
variable {U : C} (R : Presieve U)
variable (P : Cᵒᵖ ⥤ A) (P' : Cᵒᵖ ⥤ A')
section MultiequalizerConditions
/-- When `P` is a sheaf and `S` is a cover, the associated multifork is a limit. -/
def isLimitOfIsSheaf {X : C} (S : J.Cover X) (hP : IsSheaf J P) : IsLimit (S.multifork P) where
lift := fun E : Multifork _ => hP.amalgamate S (fun _ => E.ι _)
(fun _ _ r => E.condition ⟨r⟩)
fac := by
rintro (E : Multifork _) (a | b)
· apply hP.amalgamate_map
· rw [← E.w (WalkingMulticospan.Hom.fst b),
← (S.multifork P).w (WalkingMulticospan.Hom.fst b), ← assoc]
congr 1
apply hP.amalgamate_map
uniq := by
rintro (E : Multifork _) m hm
apply hP.hom_ext S
intro I
erw [hm (WalkingMulticospan.left I)]
symm
apply hP.amalgamate_map
theorem isSheaf_iff_multifork :
IsSheaf J P ↔ ∀ (X : C) (S : J.Cover X), Nonempty (IsLimit (S.multifork P)) := by
refine ⟨fun hP X S => ⟨isLimitOfIsSheaf _ _ _ hP⟩, ?_⟩
intro h E X S hS x hx
let T : J.Cover X := ⟨S, hS⟩
obtain ⟨hh⟩ := h _ T
let K : Multifork (T.index P) := Multifork.ofι _ E (fun I => x I.f I.hf)
(fun I => hx _ _ _ _ I.r.w)
use hh.lift K
dsimp; constructor
· intro Y f hf
apply hh.fac K (WalkingMulticospan.left ⟨Y, f, hf⟩)
· intro e he
apply hh.uniq K
rintro (a | b)
· apply he
· rw [← K.w (WalkingMulticospan.Hom.fst b), ←
(T.multifork P).w (WalkingMulticospan.Hom.fst b), ← assoc]
congr 1
apply he
variable {J P} in
/-- If `F : Cᵒᵖ ⥤ A` is a sheaf for a Grothendieck topology `J` on `C`,
and `S` is a cover of `X : C`, then the multifork `S.multifork F` is limit. -/
def IsSheaf.isLimitMultifork
(hP : Presheaf.IsSheaf J P) {X : C} (S : J.Cover X) : IsLimit (S.multifork P) := by
rw [Presheaf.isSheaf_iff_multifork] at hP
exact (hP X S).some
theorem isSheaf_iff_multiequalizer [∀ (X : C) (S : J.Cover X), HasMultiequalizer (S.index P)] :
IsSheaf J P ↔ ∀ (X : C) (S : J.Cover X), IsIso (S.toMultiequalizer P) := by
rw [isSheaf_iff_multifork]
refine forall₂_congr fun X S => ⟨?_, ?_⟩
· rintro ⟨h⟩
let e : P.obj (op X) ≅ multiequalizer (S.index P) :=
h.conePointUniqueUpToIso (limit.isLimit _)
exact (inferInstance : IsIso e.hom)
· intro h
refine ⟨IsLimit.ofIsoLimit (limit.isLimit _) (Cones.ext ?_ ?_)⟩
· apply (@asIso _ _ _ _ _ h).symm
· intro a
symm
simp
end MultiequalizerConditions
section
variable [HasProducts.{max u₁ v₁} A]
variable [HasProducts.{max u₁ v₁} A']
/-- The middle object of the fork diagram given in Equation (3) of [MM92], as well as the fork
diagram of the Stacks entry. -/
@[stacks 00VM "The middle object of the fork diagram there."]
def firstObj : A :=
∏ᶜ fun f : ΣV, { f : V ⟶ U // R f } => P.obj (op f.1)
/-- The left morphism of the fork diagram given in Equation (3) of [MM92], as well as the fork
diagram of the Stacks entry. -/
@[stacks 00VM "The left morphism the fork diagram there."]
def forkMap : P.obj (op U) ⟶ firstObj R P :=
Pi.lift fun f => P.map f.2.1.op
variable [HasPullbacks C]
/-- The rightmost object of the fork diagram of the Stacks entry, which
contains the data used to check a family of elements for a presieve is compatible.
-/
@[stacks 00VM "The rightmost object of the fork diagram there."]
def secondObj : A :=
∏ᶜ fun fg : (ΣV, { f : V ⟶ U // R f }) × ΣW, { g : W ⟶ U // R g } =>
P.obj (op (pullback fg.1.2.1 fg.2.2.1))
/-- The map `pr₀*` of the Stacks entry. -/
@[stacks 00VM "The map `pr₀*` there."]
def firstMap : firstObj R P ⟶ secondObj R P :=
Pi.lift fun _ => Pi.π _ _ ≫ P.map (pullback.fst _ _).op
/-- The map `pr₁*` of the Stacks entry. -/
@[stacks 00VM "The map `pr₁*` there."]
def secondMap : firstObj R P ⟶ secondObj R P :=
Pi.lift fun _ => Pi.π _ _ ≫ P.map (pullback.snd _ _).op
theorem w : forkMap R P ≫ firstMap R P = forkMap R P ≫ secondMap R P := by
apply limit.hom_ext
rintro ⟨⟨Y, f, hf⟩, ⟨Z, g, hg⟩⟩
simp only [firstMap, secondMap, forkMap, limit.lift_π, limit.lift_π_assoc, assoc, Fan.mk_π_app,
Subtype.coe_mk]
rw [← P.map_comp, ← op_comp, pullback.condition]
simp
/-- An alternative definition of the sheaf condition in terms of equalizers. This is shown to be
equivalent in `CategoryTheory.Presheaf.isSheaf_iff_isSheaf'`.
-/
def IsSheaf' (P : Cᵒᵖ ⥤ A) : Prop :=
∀ (U : C) (R : Presieve U) (_ : generate R ∈ J U), Nonempty (IsLimit (Fork.ofι _ (w R P)))
-- Again I wonder whether `UnivLE` can somehow be used to allow `s` to take
-- values in a more general universe.
/-- (Implementation). An auxiliary lemma to convert between sheaf conditions. -/
def isSheafForIsSheafFor' (P : Cᵒᵖ ⥤ A) (s : A ⥤ Type max v₁ u₁)
[∀ J, PreservesLimitsOfShape (Discrete.{max v₁ u₁} J) s] (U : C) (R : Presieve U) :
IsLimit (s.mapCone (Fork.ofι _ (w R P))) ≃
IsLimit (Fork.ofι _ (Equalizer.Presieve.w (P ⋙ s) R)) := by
let e : parallelPair (s.map (firstMap R P)) (s.map (secondMap R P)) ≅
parallelPair (Equalizer.Presieve.firstMap (P ⋙ s) R)
(Equalizer.Presieve.secondMap (P ⋙ s) R) := by
refine parallelPair.ext (PreservesProduct.iso s _) ((PreservesProduct.iso s _))
(limit.hom_ext (fun j => ?_)) (limit.hom_ext (fun j => ?_))
· dsimp [Equalizer.Presieve.firstMap, firstMap]
simp only [map_lift_piComparison, Functor.map_comp, limit.lift_π, Fan.mk_pt,
Fan.mk_π_app, assoc, piComparison_comp_π_assoc]
· dsimp [Equalizer.Presieve.secondMap, secondMap]
simp only [map_lift_piComparison, Functor.map_comp, limit.lift_π, Fan.mk_pt,
Fan.mk_π_app, assoc, piComparison_comp_π_assoc]
refine Equiv.trans (isLimitMapConeForkEquiv _ _) ?_
refine (IsLimit.postcomposeHomEquiv e _).symm.trans
(IsLimit.equivIsoLimit (Fork.ext (Iso.refl _) ?_))
dsimp [Equalizer.forkMap, forkMap, e, Fork.ι]
simp only [id_comp, map_lift_piComparison]
-- Remark : this lemma uses `A'` not `A`; `A'` is `A` but with a universe
-- restriction. Can it be generalised?
/-- The equalizer definition of a sheaf given by `isSheaf'` is equivalent to `isSheaf`. -/
theorem isSheaf_iff_isSheaf' : IsSheaf J P' ↔ IsSheaf' J P' := by
constructor
· intro h U R hR
refine ⟨?_⟩
apply coyonedaJointlyReflectsLimits
intro X
have q : Presieve.IsSheafFor (P' ⋙ coyoneda.obj X) _ := h X.unop _ hR
rw [← Presieve.isSheafFor_iff_generate] at q
rw [Equalizer.Presieve.sheaf_condition] at q
replace q := Classical.choice q
apply (isSheafForIsSheafFor' _ _ _ _).symm q
· intro h U X S hS
rw [Equalizer.Presieve.sheaf_condition]
refine ⟨?_⟩
refine isSheafForIsSheafFor' _ _ _ _ ?_
letI := preservesSmallestLimits_of_preservesLimits (coyoneda.obj (op U))
apply isLimitOfPreserves
apply Classical.choice (h _ S.arrows _)
simpa
end
section Concrete
theorem isSheaf_of_isSheaf_comp (s : A ⥤ B) [ReflectsLimitsOfSize.{v₁, max v₁ u₁} s]
(h : IsSheaf J (P ⋙ s)) : IsSheaf J P := by
rw [isSheaf_iff_isLimit] at h ⊢
exact fun X S hS ↦ (h S hS).map fun t ↦ isLimitOfReflects s t
theorem isSheaf_comp_of_isSheaf (s : A ⥤ B) [PreservesLimitsOfSize.{v₁, max v₁ u₁} s]
(h : IsSheaf J P) : IsSheaf J (P ⋙ s) := by
rw [isSheaf_iff_isLimit] at h ⊢
apply fun X S hS ↦ (h S hS).map fun t ↦ isLimitOfPreserves s t
theorem isSheaf_iff_isSheaf_comp (s : A ⥤ B) [HasLimitsOfSize.{v₁, max v₁ u₁} A]
[PreservesLimitsOfSize.{v₁, max v₁ u₁} s] [s.ReflectsIsomorphisms] :
IsSheaf J P ↔ IsSheaf J (P ⋙ s) := by
letI : ReflectsLimitsOfSize s := reflectsLimits_of_reflectsIsomorphisms
exact ⟨isSheaf_comp_of_isSheaf J P s, isSheaf_of_isSheaf_comp J P s⟩
/--
For a concrete category `(A, s)` where the forgetful functor `s : A ⥤ Type v` preserves limits and
reflects isomorphisms, and `A` has limits, an `A`-valued presheaf `P : Cᵒᵖ ⥤ A` is a sheaf iff its
underlying `Type`-valued presheaf `P ⋙ s : Cᵒᵖ ⥤ Type` is a sheaf.
Note this lemma applies for "algebraic" categories, eg groups, abelian groups and rings, but not
for the category of topological spaces, topological rings, etc since reflecting isomorphisms doesn't
hold.
-/
theorem isSheaf_iff_isSheaf_forget (s : A' ⥤ Type max v₁ u₁) [HasLimits A'] [PreservesLimits s]
[s.ReflectsIsomorphisms] : IsSheaf J P' ↔ IsSheaf J (P' ⋙ s) := by
have : HasLimitsOfSize.{v₁, max v₁ u₁} A' := hasLimitsOfSizeShrink.{_, _, u₁, 0} A'
have : PreservesLimitsOfSize.{v₁, max v₁ u₁} s := preservesLimitsOfSize_shrink.{_, 0, _, u₁} s
apply isSheaf_iff_isSheaf_comp
end Concrete
end Presheaf
end CategoryTheory
| Mathlib/CategoryTheory/Sites/Sheaf.lean | 730 | 733 | |
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Group.Unbundled.Int
import Mathlib.Algebra.Ring.Nat
import Mathlib.Data.Int.GCD
/-!
# Congruences modulo a natural number
This file defines the equivalence relation `a ≡ b [MOD n]` on the natural numbers,
and proves basic properties about it such as the Chinese Remainder Theorem
`modEq_and_modEq_iff_modEq_mul`.
## Notations
`a ≡ b [MOD n]` is notation for `nat.ModEq n a b`, which is defined to mean `a % n = b % n`.
## Tags
ModEq, congruence, mod, MOD, modulo
-/
assert_not_exists OrderedAddCommMonoid Function.support
namespace Nat
/-- Modular equality. `n.ModEq a b`, or `a ≡ b [MOD n]`, means that `a - b` is a multiple of `n`. -/
def ModEq (n a b : ℕ) :=
a % n = b % n
@[inherit_doc]
notation:50 a " ≡ " b " [MOD " n "]" => ModEq n a b
variable {m n a b c d : ℕ}
-- Since `ModEq` is semi-reducible, we need to provide the decidable instance manually
instance : Decidable (ModEq n a b) := inferInstanceAs <| Decidable (a % n = b % n)
namespace ModEq
@[refl]
protected theorem refl (a : ℕ) : a ≡ a [MOD n] := rfl
protected theorem rfl : a ≡ a [MOD n] :=
ModEq.refl _
instance : IsRefl _ (ModEq n) :=
⟨ModEq.refl⟩
@[symm]
protected theorem symm : a ≡ b [MOD n] → b ≡ a [MOD n] :=
Eq.symm
@[trans]
protected theorem trans : a ≡ b [MOD n] → b ≡ c [MOD n] → a ≡ c [MOD n] :=
Eq.trans
instance : Trans (ModEq n) (ModEq n) (ModEq n) where
trans := Nat.ModEq.trans
protected theorem comm : a ≡ b [MOD n] ↔ b ≡ a [MOD n] :=
⟨ModEq.symm, ModEq.symm⟩
end ModEq
theorem modEq_zero_iff_dvd : a ≡ 0 [MOD n] ↔ n ∣ a := by rw [ModEq, zero_mod, dvd_iff_mod_eq_zero]
theorem _root_.Dvd.dvd.modEq_zero_nat (h : n ∣ a) : a ≡ 0 [MOD n] :=
modEq_zero_iff_dvd.2 h
theorem _root_.Dvd.dvd.zero_modEq_nat (h : n ∣ a) : 0 ≡ a [MOD n] :=
h.modEq_zero_nat.symm
theorem modEq_iff_dvd : a ≡ b [MOD n] ↔ (n : ℤ) ∣ b - a := by
rw [ModEq, eq_comm, ← Int.natCast_inj, Int.natCast_mod, Int.natCast_mod,
Int.emod_eq_emod_iff_emod_sub_eq_zero, Int.dvd_iff_emod_eq_zero]
alias ⟨ModEq.dvd, modEq_of_dvd⟩ := modEq_iff_dvd
/-- A variant of `modEq_iff_dvd` with `Nat` divisibility -/
theorem modEq_iff_dvd' (h : a ≤ b) : a ≡ b [MOD n] ↔ n ∣ b - a := by
rw [modEq_iff_dvd, ← Int.natCast_dvd_natCast, Int.ofNat_sub h]
theorem mod_modEq (a n) : a % n ≡ a [MOD n] :=
mod_mod _ _
namespace ModEq
lemma of_dvd (d : m ∣ n) (h : a ≡ b [MOD n]) : a ≡ b [MOD m] :=
modEq_of_dvd <| Int.ofNat_dvd.mpr d |>.trans h.dvd
protected theorem mul_left' (c : ℕ) (h : a ≡ b [MOD n]) : c * a ≡ c * b [MOD c * n] := by
unfold ModEq at *; rw [mul_mod_mul_left, mul_mod_mul_left, h]
@[gcongr]
protected theorem mul_left (c : ℕ) (h : a ≡ b [MOD n]) : c * a ≡ c * b [MOD n] :=
(h.mul_left' _).of_dvd (dvd_mul_left _ _)
protected theorem mul_right' (c : ℕ) (h : a ≡ b [MOD n]) : a * c ≡ b * c [MOD n * c] := by
rw [mul_comm a, mul_comm b, mul_comm n]; exact h.mul_left' c
@[gcongr]
protected theorem mul_right (c : ℕ) (h : a ≡ b [MOD n]) : a * c ≡ b * c [MOD n] := by
rw [mul_comm a, mul_comm b]; exact h.mul_left c
@[gcongr]
protected theorem mul (h₁ : a ≡ b [MOD n]) (h₂ : c ≡ d [MOD n]) : a * c ≡ b * d [MOD n] :=
(h₂.mul_left _).trans (h₁.mul_right _)
@[gcongr]
protected theorem pow (m : ℕ) (h : a ≡ b [MOD n]) : a ^ m ≡ b ^ m [MOD n] := by
induction m with
| zero => rfl
| succ d hd =>
rw [Nat.pow_succ, Nat.pow_succ]
exact hd.mul h
@[gcongr]
protected theorem add (h₁ : a ≡ b [MOD n]) (h₂ : c ≡ d [MOD n]) : a + c ≡ b + d [MOD n] := by
rw [modEq_iff_dvd, Int.natCast_add, Int.natCast_add, add_sub_add_comm]
exact Int.dvd_add h₁.dvd h₂.dvd
@[gcongr]
protected theorem add_left (c : ℕ) (h : a ≡ b [MOD n]) : c + a ≡ c + b [MOD n] :=
ModEq.rfl.add h
@[gcongr]
protected theorem add_right (c : ℕ) (h : a ≡ b [MOD n]) : a + c ≡ b + c [MOD n] :=
h.add ModEq.rfl
protected theorem add_left_cancel (h₁ : a ≡ b [MOD n]) (h₂ : a + c ≡ b + d [MOD n]) :
c ≡ d [MOD n] := by
simp only [modEq_iff_dvd, Int.natCast_add] at *
rw [add_sub_add_comm] at h₂
convert Int.dvd_sub h₂ h₁ using 1
rw [add_sub_cancel_left]
protected theorem add_left_cancel' (c : ℕ) (h : c + a ≡ c + b [MOD n]) : a ≡ b [MOD n] :=
ModEq.rfl.add_left_cancel h
protected theorem add_right_cancel (h₁ : c ≡ d [MOD n]) (h₂ : a + c ≡ b + d [MOD n]) :
a ≡ b [MOD n] := by
rw [add_comm a, add_comm b] at h₂
exact h₁.add_left_cancel h₂
protected theorem add_right_cancel' (c : ℕ) (h : a + c ≡ b + c [MOD n]) : a ≡ b [MOD n] :=
ModEq.rfl.add_right_cancel h
/-- Cancel left multiplication on both sides of the `≡` and in the modulus.
For cancelling left multiplication in the modulus, see `Nat.ModEq.of_mul_left`. -/
protected theorem mul_left_cancel' {a b c m : ℕ} (hc : c ≠ 0) :
c * a ≡ c * b [MOD c * m] → a ≡ b [MOD m] := by
simp only [modEq_iff_dvd, Int.natCast_mul, ← Int.mul_sub]
exact fun h => (Int.dvd_of_mul_dvd_mul_left (Int.ofNat_ne_zero.mpr hc) h)
protected theorem mul_left_cancel_iff' {a b c m : ℕ} (hc : c ≠ 0) :
c * a ≡ c * b [MOD c * m] ↔ a ≡ b [MOD m] :=
⟨ModEq.mul_left_cancel' hc, ModEq.mul_left' _⟩
/-- Cancel right multiplication on both sides of the `≡` and in the modulus.
For cancelling right multiplication in the modulus, see `Nat.ModEq.of_mul_right`. -/
protected theorem mul_right_cancel' {a b c m : ℕ} (hc : c ≠ 0) :
a * c ≡ b * c [MOD m * c] → a ≡ b [MOD m] := by
simp only [modEq_iff_dvd, Int.natCast_mul, ← Int.sub_mul]
exact fun h => (Int.dvd_of_mul_dvd_mul_right (Int.ofNat_ne_zero.mpr hc) h)
protected theorem mul_right_cancel_iff' {a b c m : ℕ} (hc : c ≠ 0) :
a * c ≡ b * c [MOD m * c] ↔ a ≡ b [MOD m] :=
⟨ModEq.mul_right_cancel' hc, ModEq.mul_right' _⟩
/-- Cancel left multiplication in the modulus.
For cancelling left multiplication on both sides of the `≡`, see `nat.modeq.mul_left_cancel'`. -/
lemma of_mul_left (m : ℕ) (h : a ≡ b [MOD m * n]) : a ≡ b [MOD n] := by
rw [modEq_iff_dvd] at *
exact (dvd_mul_left (n : ℤ) (m : ℤ)).trans h
/-- Cancel right multiplication in the modulus.
For cancelling right multiplication on both sides of the `≡`, see `nat.modeq.mul_right_cancel'`. -/
lemma of_mul_right (m : ℕ) : a ≡ b [MOD n * m] → a ≡ b [MOD n] := mul_comm m n ▸ of_mul_left _
theorem of_div (h : a / c ≡ b / c [MOD m / c]) (ha : c ∣ a) (ha : c ∣ b) (ha : c ∣ m) :
a ≡ b [MOD m] := by convert h.mul_left' c <;> rwa [Nat.mul_div_cancel']
end ModEq
lemma modEq_sub (h : b ≤ a) : a ≡ b [MOD a - b] := (modEq_of_dvd <| by rw [Int.ofNat_sub h]).symm
lemma modEq_one : a ≡ b [MOD 1] := modEq_of_dvd <| one_dvd _
@[simp] lemma modEq_zero_iff : a ≡ b [MOD 0] ↔ a = b := by rw [ModEq, mod_zero, mod_zero]
@[simp] lemma add_modEq_left : n + a ≡ a [MOD n] := by rw [ModEq, add_mod_left]
@[simp] lemma add_modEq_right : a + n ≡ a [MOD n] := by rw [ModEq, add_mod_right]
namespace ModEq
theorem le_of_lt_add (h1 : a ≡ b [MOD m]) (h2 : a < b + m) : a ≤ b :=
(le_total a b).elim id fun h3 =>
Nat.le_of_sub_eq_zero
(eq_zero_of_dvd_of_lt ((modEq_iff_dvd' h3).mp h1.symm) (by omega))
theorem add_le_of_lt (h1 : a ≡ b [MOD m]) (h2 : a < b) : a + m ≤ b :=
le_of_lt_add (add_modEq_right.trans h1) (by omega)
theorem dvd_iff (h : a ≡ b [MOD m]) (hdm : d ∣ m) : d ∣ a ↔ d ∣ b := by
simp only [← modEq_zero_iff_dvd]
replace h := h.of_dvd hdm
exact ⟨h.symm.trans, h.trans⟩
theorem gcd_eq (h : a ≡ b [MOD m]) : gcd a m = gcd b m := by
have h1 := gcd_dvd_right a m
have h2 := gcd_dvd_right b m
exact
dvd_antisymm (dvd_gcd ((h.dvd_iff h1).mp (gcd_dvd_left a m)) h1)
(dvd_gcd ((h.dvd_iff h2).mpr (gcd_dvd_left b m)) h2)
lemma eq_of_abs_lt (h : a ≡ b [MOD m]) (h2 : |(b : ℤ) - a| < m) : a = b := by
apply Int.ofNat.inj
rw [eq_comm, ← sub_eq_zero]
exact Int.eq_zero_of_abs_lt_dvd h.dvd h2
lemma eq_of_lt_of_lt (h : a ≡ b [MOD m]) (ha : a < m) (hb : b < m) : a = b :=
h.eq_of_abs_lt <| Int.abs_sub_lt_of_lt_lt ha hb
/-- To cancel a common factor `c` from a `ModEq` we must divide the modulus `m` by `gcd m c` -/
lemma cancel_left_div_gcd (hm : 0 < m) (h : c * a ≡ c * b [MOD m]) : a ≡ b [MOD m / gcd m c] := by
let d := gcd m c
have hmd := gcd_dvd_left m c
have hcd := gcd_dvd_right m c
rw [modEq_iff_dvd]
refine @Int.dvd_of_dvd_mul_right_of_gcd_one (m / d) (c / d) (b - a) ?_ ?_
· show (m / d : ℤ) ∣ c / d * (b - a)
rw [mul_comm, ← Int.mul_ediv_assoc (b - a) (Int.natCast_dvd_natCast.mpr hcd), mul_comm]
apply Int.ediv_dvd_ediv (Int.natCast_dvd_natCast.mpr hmd)
rw [Int.mul_sub]
exact modEq_iff_dvd.mp h
· show Int.gcd (m / d) (c / d) = 1
simp only [d, ← Int.natCast_div, Int.gcd_natCast_natCast (m / d) (c / d),
gcd_div hmd hcd, Nat.div_self (gcd_pos_of_pos_left c hm)]
/-- To cancel a common factor `c` from a `ModEq` we must divide the modulus `m` by `gcd m c` -/
lemma cancel_right_div_gcd (hm : 0 < m) (h : a * c ≡ b * c [MOD m]) : a ≡ b [MOD m / gcd m c] := by
apply cancel_left_div_gcd hm
simpa [mul_comm] using h
lemma cancel_left_div_gcd' (hm : 0 < m) (hcd : c ≡ d [MOD m]) (h : c * a ≡ d * b [MOD m]) :
a ≡ b [MOD m / gcd m c] :=
(h.trans <| hcd.symm.mul_right b).cancel_left_div_gcd hm
lemma cancel_right_div_gcd' (hm : 0 < m) (hcd : c ≡ d [MOD m]) (h : a * c ≡ b * d [MOD m]) :
a ≡ b [MOD m / gcd m c] :=
(h.trans <| hcd.symm.mul_left b).cancel_right_div_gcd hm
/-- A common factor that's coprime with the modulus can be cancelled from a `ModEq` -/
lemma cancel_left_of_coprime (hmc : gcd m c = 1) (h : c * a ≡ c * b [MOD m]) : a ≡ b [MOD m] := by
rcases m.eq_zero_or_pos with (rfl | hm)
· simp only [gcd_zero_left] at hmc
simp only [gcd_zero_left, hmc, one_mul, modEq_zero_iff] at h
subst h
rfl
simpa [hmc] using h.cancel_left_div_gcd hm
/-- A common factor that's coprime with the modulus can be cancelled from a `ModEq` -/
lemma cancel_right_of_coprime (hmc : gcd m c = 1) (h : a * c ≡ b * c [MOD m]) : a ≡ b [MOD m] :=
cancel_left_of_coprime hmc <| by simpa [mul_comm] using h
end ModEq
/-- The natural number less than `lcm n m` congruent to `a` mod `n` and `b` mod `m` -/
def chineseRemainder' (h : a ≡ b [MOD gcd n m]) : { k // k ≡ a [MOD n] ∧ k ≡ b [MOD m] } :=
if hn : n = 0 then ⟨a, by
rw [hn, gcd_zero_left] at h; constructor
· rfl
· exact h⟩
else
if hm : m = 0 then ⟨b, by
rw [hm, gcd_zero_right] at h; constructor
· exact h.symm
· rfl⟩
else
⟨let (c, d) := xgcd n m; Int.toNat ((n * c * b + m * d * a) / gcd n m % lcm n m), by
rw [xgcd_val]
dsimp
rw [modEq_iff_dvd, modEq_iff_dvd,
Int.toNat_of_nonneg (Int.emod_nonneg _ (Int.natCast_ne_zero.2 (lcm_ne_zero hn hm)))]
have hnonzero : (gcd n m : ℤ) ≠ 0 := by
norm_cast
rw [Nat.gcd_eq_zero_iff, not_and]
exact fun _ => hm
have hcoedvd : ∀ t, (gcd n m : ℤ) ∣ t * (b - a) := fun t => h.dvd.mul_left _
have := gcd_eq_gcd_ab n m
constructor <;> rw [Int.emod_def, ← sub_add] <;>
refine Int.dvd_add ?_ (dvd_mul_of_dvd_left ?_ _) <;>
try norm_cast
· rw [← sub_eq_iff_eq_add'] at this
rw [← this, Int.sub_mul, ← add_sub_assoc, add_comm, add_sub_assoc, ← Int.mul_sub,
Int.add_ediv_of_dvd_left, Int.mul_ediv_cancel_left _ hnonzero,
Int.mul_ediv_assoc _ h.dvd, ← sub_sub, sub_self, zero_sub, Int.dvd_neg, mul_assoc]
· exact dvd_mul_right _ _
norm_cast
exact dvd_mul_right _ _
· exact dvd_lcm_left n m
· rw [← sub_eq_iff_eq_add] at this
rw [← this, Int.sub_mul, sub_add, ← Int.mul_sub, Int.sub_ediv_of_dvd,
Int.mul_ediv_cancel_left _ hnonzero, Int.mul_ediv_assoc _ h.dvd, ← sub_add, sub_self,
zero_add, mul_assoc]
· exact dvd_mul_right _ _
· exact hcoedvd _
· exact dvd_lcm_right n m⟩
/-- The natural number less than `n*m` congruent to `a` mod `n` and `b` mod `m` -/
def chineseRemainder (co : n.Coprime m) (a b : ℕ) : { k // k ≡ a [MOD n] ∧ k ≡ b [MOD m] } :=
chineseRemainder' (by convert @modEq_one a b)
theorem chineseRemainder'_lt_lcm (h : a ≡ b [MOD gcd n m]) (hn : n ≠ 0) (hm : m ≠ 0) :
↑(chineseRemainder' h) < lcm n m := by
dsimp only [chineseRemainder']
rw [dif_neg hn, dif_neg hm, Subtype.coe_mk, xgcd_val, ← Int.toNat_natCast (lcm n m)]
have lcm_pos := Int.natCast_pos.mpr (Nat.pos_of_ne_zero (lcm_ne_zero hn hm))
exact (Int.toNat_lt_toNat lcm_pos).mpr (Int.emod_lt_of_pos _ lcm_pos)
theorem chineseRemainder_lt_mul (co : n.Coprime m) (a b : ℕ) (hn : n ≠ 0) (hm : m ≠ 0) :
↑(chineseRemainder co a b) < n * m :=
lt_of_lt_of_le (chineseRemainder'_lt_lcm _ hn hm) (le_of_eq co.lcm_eq_mul)
theorem mod_lcm (hn : a ≡ b [MOD n]) (hm : a ≡ b [MOD m]) : a ≡ b [MOD lcm n m] :=
Nat.modEq_iff_dvd.mpr <| Int.coe_lcm_dvd (Nat.modEq_iff_dvd.mp hn) (Nat.modEq_iff_dvd.mp hm)
theorem chineseRemainder_modEq_unique (co : n.Coprime m) {a b z}
(hzan : z ≡ a [MOD n]) (hzbm : z ≡ b [MOD m]) : z ≡ chineseRemainder co a b [MOD n*m] := by
simpa [Nat.Coprime.lcm_eq_mul co] using
mod_lcm (hzan.trans ((chineseRemainder co a b).prop.1).symm)
(hzbm.trans ((chineseRemainder co a b).prop.2).symm)
theorem modEq_and_modEq_iff_modEq_mul {a b m n : ℕ} (hmn : m.Coprime n) :
a ≡ b [MOD m] ∧ a ≡ b [MOD n] ↔ a ≡ b [MOD m * n] :=
⟨fun h => by
rw [Nat.modEq_iff_dvd, Nat.modEq_iff_dvd, ← Int.dvd_natAbs, Int.natCast_dvd_natCast,
← Int.dvd_natAbs, Int.natCast_dvd_natCast] at h
rw [Nat.modEq_iff_dvd, ← Int.dvd_natAbs, Int.natCast_dvd_natCast]
exact hmn.mul_dvd_of_dvd_of_dvd h.1 h.2,
fun h => ⟨h.of_mul_right _, h.of_mul_left _⟩⟩
theorem coprime_of_mul_modEq_one (b : ℕ) {a n : ℕ} (h : a * b ≡ 1 [MOD n]) : a.Coprime n := by
obtain ⟨g, hh⟩ := Nat.gcd_dvd_right a n
rw [Nat.coprime_iff_gcd_eq_one, ← Nat.dvd_one, ← Nat.modEq_zero_iff_dvd]
calc
1 ≡ a * b [MOD a.gcd n] := (hh ▸ h).symm.of_mul_right g
_ ≡ 0 * b [MOD a.gcd n] := (Nat.modEq_zero_iff_dvd.mpr (Nat.gcd_dvd_left _ _)).mul_right b
_ = 0 := by rw [zero_mul]
theorem add_mod_add_ite (a b c : ℕ) :
((a + b) % c + if c ≤ a % c + b % c then c else 0) = a % c + b % c :=
have : (a + b) % c = (a % c + b % c) % c := ((mod_modEq _ _).add <| mod_modEq _ _).symm
if hc0 : c = 0 then by simp [hc0, Nat.mod_zero]
else by
rw [this]
split_ifs with h
· have h2 : (a % c + b % c) / c < 2 :=
Nat.div_lt_of_lt_mul
(by
rw [mul_two]
exact
add_lt_add (Nat.mod_lt _ (Nat.pos_of_ne_zero hc0))
(Nat.mod_lt _ (Nat.pos_of_ne_zero hc0)))
have h0 : 0 < (a % c + b % c) / c := Nat.div_pos h (Nat.pos_of_ne_zero hc0)
rw [← @add_right_cancel_iff _ _ _ (c * ((a % c + b % c) / c)), add_comm _ c, add_assoc,
mod_add_div, le_antisymm (le_of_lt_succ h2) h0, mul_one, add_comm]
· rw [Nat.mod_eq_of_lt (lt_of_not_ge h), add_zero]
theorem add_mod_of_add_mod_lt {a b c : ℕ} (hc : a % c + b % c < c) :
(a + b) % c = a % c + b % c := by rw [← add_mod_add_ite, if_neg (not_le_of_lt hc), add_zero]
theorem add_mod_add_of_le_add_mod {a b c : ℕ} (hc : c ≤ a % c + b % c) :
(a + b) % c + c = a % c + b % c := by rw [← add_mod_add_ite, if_pos hc]
theorem add_div_eq_of_add_mod_lt {a b c : ℕ} (hc : a % c + b % c < c) :
(a + b) / c = a / c + b / c :=
if hc0 : c = 0 then by simp [hc0]
else by rw [Nat.add_div (Nat.pos_of_ne_zero hc0), if_neg (not_le_of_lt hc), add_zero]
protected theorem add_div_of_dvd_right {a b c : ℕ} (hca : c ∣ a) : (a + b) / c = a / c + b / c :=
if h : c = 0 then by simp [h]
else
add_div_eq_of_add_mod_lt
(by
rw [Nat.mod_eq_zero_of_dvd hca, zero_add]
exact Nat.mod_lt _ (zero_lt_of_ne_zero h))
protected theorem add_div_of_dvd_left {a b c : ℕ} (hca : c ∣ b) : (a + b) / c = a / c + b / c := by
rwa [add_comm, Nat.add_div_of_dvd_right, add_comm]
theorem add_div_eq_of_le_mod_add_mod {a b c : ℕ} (hc : c ≤ a % c + b % c) (hc0 : 0 < c) :
(a + b) / c = a / c + b / c + 1 := by rw [Nat.add_div hc0, if_pos hc]
theorem add_div_le_add_div (a b c : ℕ) : a / c + b / c ≤ (a + b) / c :=
if hc0 : c = 0 then by simp [hc0]
else by rw [Nat.add_div (Nat.pos_of_ne_zero hc0)]; exact Nat.le_add_right _ _
theorem le_mod_add_mod_of_dvd_add_of_not_dvd {a b c : ℕ} (h : c ∣ a + b) (ha : ¬c ∣ a) :
c ≤ a % c + b % c :=
by_contradiction fun hc => by
have : (a + b) % c = a % c + b % c := add_mod_of_add_mod_lt (lt_of_not_ge hc)
simp_all [dvd_iff_mod_eq_zero]
theorem odd_mul_odd {n m : ℕ} : n % 2 = 1 → m % 2 = 1 → n * m % 2 = 1 := by
simpa [Nat.ModEq] using @ModEq.mul 2 n 1 m 1
theorem odd_mul_odd_div_two {m n : ℕ} (hm1 : m % 2 = 1) (hn1 : n % 2 = 1) :
m * n / 2 = m * (n / 2) + m / 2 :=
have hn0 : 0 < n := Nat.pos_of_ne_zero fun h => by simp_all
mul_right_injective₀ two_ne_zero <| by
dsimp
rw [mul_add, two_mul_odd_div_two hm1, mul_left_comm, two_mul_odd_div_two hn1,
two_mul_odd_div_two (Nat.odd_mul_odd hm1 hn1), Nat.mul_sub, mul_one, ←
Nat.add_sub_assoc (by omega), Nat.sub_add_cancel (Nat.le_mul_of_pos_right m hn0)]
theorem odd_of_mod_four_eq_one {n : ℕ} : n % 4 = 1 → n % 2 = 1 := by
simpa [ModEq] using @ModEq.of_mul_left 2 n 1 2
theorem odd_of_mod_four_eq_three {n : ℕ} : n % 4 = 3 → n % 2 = 1 := by
simpa [ModEq] using @ModEq.of_mul_left 2 n 3 2
/-- A natural number is odd iff it has residue `1` or `3` mod `4`. -/
theorem odd_mod_four_iff {n : ℕ} : n % 2 = 1 ↔ n % 4 = 1 ∨ n % 4 = 3 :=
have help : ∀ m : ℕ, m < 4 → m % 2 = 1 → m = 1 ∨ m = 3 := by decide
⟨fun hn =>
help (n % 4) (mod_lt n (by omega)) <| (mod_mod_of_dvd n (by decide : 2 ∣ 4)).trans hn,
fun h => Or.elim h odd_of_mod_four_eq_one odd_of_mod_four_eq_three⟩
lemma mod_eq_of_modEq {a b n} (h : a ≡ b [MOD n]) (hb : b < n) : a % n = b :=
Eq.trans h (mod_eq_of_lt hb)
end Nat
| Mathlib/Data/Nat/ModEq.lean | 489 | 491 | |
/-
Copyright (c) 2022 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.Probability.Kernel.Defs
/-!
# Basic kernels
This file contains basic results about kernels in general and definitions of some particular
kernels.
## Main definitions
* `ProbabilityTheory.Kernel.deterministic (f : α → β) (hf : Measurable f)`:
kernel `a ↦ Measure.dirac (f a)`.
* `ProbabilityTheory.Kernel.id`: the identity kernel, deterministic kernel for
the identity function.
* `ProbabilityTheory.Kernel.copy α`: the deterministic kernel that maps `x : α` to
the Dirac measure at `(x, x) : α × α`.
* `ProbabilityTheory.Kernel.discard α`: the Markov kernel to the type `Unit`.
* `ProbabilityTheory.Kernel.swap α β`: the deterministic kernel that maps `(x, y)` to
the Dirac measure at `(y, x)`.
* `ProbabilityTheory.Kernel.const α (μβ : measure β)`: constant kernel `a ↦ μβ`.
* `ProbabilityTheory.Kernel.restrict κ (hs : MeasurableSet s)`: kernel for which the image of
`a : α` is `(κ a).restrict s`.
Integral: `∫⁻ b, f b ∂(κ.restrict hs a) = ∫⁻ b in s, f b ∂(κ a)`
* `ProbabilityTheory.Kernel.comapRight`: Kernel with value `(κ a).comap f`,
for a measurable embedding `f`. That is, for a measurable set `t : Set β`,
`ProbabilityTheory.Kernel.comapRight κ hf a t = κ a (f '' t)`
* `ProbabilityTheory.Kernel.piecewise (hs : MeasurableSet s) κ η`: the kernel equal to `κ`
on the measurable set `s` and to `η` on its complement.
## Main statements
-/
assert_not_exists MeasureTheory.integral
open MeasureTheory
open scoped ENNReal
namespace ProbabilityTheory
variable {α β ι : Type*} {mα : MeasurableSpace α} {mβ : MeasurableSpace β} {κ : Kernel α β}
namespace Kernel
section Deterministic
/-- Kernel which to `a` associates the dirac measure at `f a`. This is a Markov kernel. -/
noncomputable def deterministic (f : α → β) (hf : Measurable f) : Kernel α β where
toFun a := Measure.dirac (f a)
measurable' := by
refine Measure.measurable_of_measurable_coe _ fun s hs => ?_
simp_rw [Measure.dirac_apply' _ hs]
exact measurable_one.indicator (hf hs)
theorem deterministic_apply {f : α → β} (hf : Measurable f) (a : α) :
deterministic f hf a = Measure.dirac (f a) :=
rfl
theorem deterministic_apply' {f : α → β} (hf : Measurable f) (a : α) {s : Set β}
(hs : MeasurableSet s) : deterministic f hf a s = s.indicator (fun _ => 1) (f a) := by
rw [deterministic]
change Measure.dirac (f a) s = s.indicator 1 (f a)
simp_rw [Measure.dirac_apply' _ hs]
/-- Because of the measurability field in `Kernel.deterministic`, `rw [h]` will not rewrite
`deterministic f hf` to `deterministic g ⋯`. Instead one can do `rw [deterministic_congr h]`. -/
theorem deterministic_congr {f g : α → β} {hf : Measurable f} (h : f = g) :
deterministic f hf = deterministic g (h ▸ hf) := by
conv_lhs => enter [1]; rw [h]
instance isMarkovKernel_deterministic {f : α → β} (hf : Measurable f) :
IsMarkovKernel (deterministic f hf) :=
⟨fun a => by rw [deterministic_apply hf]; infer_instance⟩
theorem lintegral_deterministic' {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
(hf : Measurable f) : ∫⁻ x, f x ∂deterministic g hg a = f (g a) := by
rw [deterministic_apply, lintegral_dirac' _ hf]
@[simp]
theorem lintegral_deterministic {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
[MeasurableSingletonClass β] : ∫⁻ x, f x ∂deterministic g hg a = f (g a) := by
rw [deterministic_apply, lintegral_dirac (g a) f]
theorem setLIntegral_deterministic' {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
(hf : Measurable f) {s : Set β} (hs : MeasurableSet s) [Decidable (g a ∈ s)] :
∫⁻ x in s, f x ∂deterministic g hg a = if g a ∈ s then f (g a) else 0 := by
rw [deterministic_apply, setLIntegral_dirac' hf hs]
@[simp]
theorem setLIntegral_deterministic {f : β → ℝ≥0∞} {g : α → β} {a : α} (hg : Measurable g)
[MeasurableSingletonClass β] (s : Set β) [Decidable (g a ∈ s)] :
∫⁻ x in s, f x ∂deterministic g hg a = if g a ∈ s then f (g a) else 0 := by
rw [deterministic_apply, setLIntegral_dirac f s]
end Deterministic
section Id
/-- The identity kernel, that maps `x : α` to the Dirac measure at `x`. -/
protected noncomputable
def id : Kernel α α := Kernel.deterministic id measurable_id
instance : IsMarkovKernel (Kernel.id : Kernel α α) := by rw [Kernel.id]; infer_instance
lemma id_apply (a : α) : Kernel.id a = Measure.dirac a := by
rw [Kernel.id, deterministic_apply, id_def]
lemma lintegral_id' {f : α → ℝ≥0∞} (hf : Measurable f) (a : α) :
∫⁻ a, f a ∂(@Kernel.id α mα a) = f a := by
rw [id_apply, lintegral_dirac' _ hf]
lemma lintegral_id [MeasurableSingletonClass α] {f : α → ℝ≥0∞} (a : α) :
∫⁻ a, f a ∂(@Kernel.id α mα a) = f a := by
rw [id_apply, lintegral_dirac]
end Id
section Copy
/-- The deterministic kernel that maps `x : α` to the Dirac measure at `(x, x) : α × α`. -/
noncomputable
def copy (α : Type*) [MeasurableSpace α] : Kernel α (α × α) :=
Kernel.deterministic (fun x ↦ (x, x)) (measurable_id.prod measurable_id)
instance : IsMarkovKernel (copy α) := by rw [copy]; infer_instance
lemma copy_apply (a : α) : copy α a = Measure.dirac (a, a) := by simp [copy, deterministic_apply]
end Copy
section Discard
/-- The Markov kernel to the `Unit` type. -/
noncomputable
def discard (α : Type*) [MeasurableSpace α] : Kernel α Unit :=
Kernel.deterministic (fun _ ↦ ()) measurable_const
instance : IsMarkovKernel (discard α) := by rw [discard]; infer_instance
@[simp]
lemma discard_apply (a : α) : discard α a = Measure.dirac () := deterministic_apply _ _
end Discard
section Swap
/-- The deterministic kernel that maps `(x, y)` to the Dirac measure at `(y, x)`. -/
noncomputable
def swap (α β : Type*) [MeasurableSpace α] [MeasurableSpace β] : Kernel (α × β) (β × α) :=
Kernel.deterministic Prod.swap measurable_swap
instance : IsMarkovKernel (swap α β) := by rw [swap]; infer_instance
/-- See `swap_apply'` for a fully applied version of this lemma. -/
lemma swap_apply (ab : α × β) : swap α β ab = Measure.dirac ab.swap := by
rw [swap, deterministic_apply]
/-- See `swap_apply` for a partially applied version of this lemma. -/
lemma swap_apply' (ab : α × β) {s : Set (β × α)} (hs : MeasurableSet s) :
swap α β ab s = s.indicator 1 ab.swap := by
rw [swap_apply, Measure.dirac_apply' _ hs]
end Swap
section Const
/-- Constant kernel, which always returns the same measure. -/
def const (α : Type*) {β : Type*} [MeasurableSpace α] {_ : MeasurableSpace β} (μβ : Measure β) :
Kernel α β where
toFun _ := μβ
measurable' := measurable_const
@[simp]
theorem const_apply (μβ : Measure β) (a : α) : const α μβ a = μβ :=
rfl
@[simp]
lemma const_zero : const α (0 : Measure β) = 0 := by
ext x s _; simp [const_apply]
lemma const_add (β : Type*) [MeasurableSpace β] (μ ν : Measure α) :
const β (μ + ν) = const β μ + const β ν := by ext; simp
lemma sum_const [Countable ι] (μ : ι → Measure β) :
Kernel.sum (fun n ↦ const α (μ n)) = const α (Measure.sum μ) := rfl
instance const.instIsFiniteKernel {μβ : Measure β} [IsFiniteMeasure μβ] :
IsFiniteKernel (const α μβ) :=
⟨⟨μβ Set.univ, measure_lt_top _ _, fun _ => le_rfl⟩⟩
instance const.instIsSFiniteKernel {μβ : Measure β} [SFinite μβ] :
IsSFiniteKernel (const α μβ) :=
⟨fun n ↦ const α (sfiniteSeq μβ n), fun n ↦ inferInstance, by rw [sum_const, sum_sfiniteSeq]⟩
instance const.instIsMarkovKernel {μβ : Measure β} [hμβ : IsProbabilityMeasure μβ] :
IsMarkovKernel (const α μβ) :=
⟨fun _ => hμβ⟩
instance const.instIsZeroOrMarkovKernel {μβ : Measure β} [hμβ : IsZeroOrProbabilityMeasure μβ] :
IsZeroOrMarkovKernel (const α μβ) := by
rcases eq_zero_or_isProbabilityMeasure μβ with rfl | h
· simp only [const_zero]
infer_instance
· infer_instance
lemma isSFiniteKernel_const [Nonempty α] {μβ : Measure β} :
IsSFiniteKernel (const α μβ) ↔ SFinite μβ :=
⟨fun h ↦ h.sFinite (Classical.arbitrary α), fun _ ↦ inferInstance⟩
@[simp]
theorem lintegral_const {f : β → ℝ≥0∞} {μ : Measure β} {a : α} :
∫⁻ x, f x ∂const α μ a = ∫⁻ x, f x ∂μ := by rw [const_apply]
@[simp]
theorem setLIntegral_const {f : β → ℝ≥0∞} {μ : Measure β} {a : α} {s : Set β} :
∫⁻ x in s, f x ∂const α μ a = ∫⁻ x in s, f x ∂μ := by rw [const_apply]
end Const
/-- In a countable space with measurable singletons, every function `α → MeasureTheory.Measure β`
defines a kernel. -/
def ofFunOfCountable [MeasurableSpace α] {_ : MeasurableSpace β} [Countable α]
[MeasurableSingletonClass α] (f : α → Measure β) : Kernel α β where
toFun := f
measurable' := measurable_of_countable f
section Restrict
variable {s t : Set β}
/-- Kernel given by the restriction of the measures in the image of a kernel to a set. -/
protected noncomputable def restrict (κ : Kernel α β) (hs : MeasurableSet s) : Kernel α β where
toFun a := (κ a).restrict s
measurable' := by
refine Measure.measurable_of_measurable_coe _ fun t ht => ?_
simp_rw [Measure.restrict_apply ht]
exact Kernel.measurable_coe κ (ht.inter hs)
theorem restrict_apply (κ : Kernel α β) (hs : MeasurableSet s) (a : α) :
κ.restrict hs a = (κ a).restrict s :=
rfl
theorem restrict_apply' (κ : Kernel α β) (hs : MeasurableSet s) (a : α) (ht : MeasurableSet t) :
κ.restrict hs a t = (κ a) (t ∩ s) := by
rw [restrict_apply κ hs a, Measure.restrict_apply ht]
@[simp]
theorem restrict_univ : κ.restrict MeasurableSet.univ = κ := by
ext1 a
rw [Kernel.restrict_apply, Measure.restrict_univ]
@[simp]
theorem lintegral_restrict (κ : Kernel α β) (hs : MeasurableSet s) (a : α) (f : β → ℝ≥0∞) :
∫⁻ b, f b ∂κ.restrict hs a = ∫⁻ b in s, f b ∂κ a := by rw [restrict_apply]
@[simp]
theorem setLIntegral_restrict (κ : Kernel α β) (hs : MeasurableSet s) (a : α) (f : β → ℝ≥0∞)
(t : Set β) : ∫⁻ b in t, f b ∂κ.restrict hs a = ∫⁻ b in t ∩ s, f b ∂κ a := by
rw [restrict_apply, Measure.restrict_restrict' hs]
instance IsFiniteKernel.restrict (κ : Kernel α β) [IsFiniteKernel κ] (hs : MeasurableSet s) :
IsFiniteKernel (κ.restrict hs) := by
refine ⟨⟨IsFiniteKernel.bound κ, IsFiniteKernel.bound_lt_top κ, fun a => ?_⟩⟩
rw [restrict_apply' κ hs a MeasurableSet.univ]
exact measure_le_bound κ a _
instance IsSFiniteKernel.restrict (κ : Kernel α β) [IsSFiniteKernel κ] (hs : MeasurableSet s) :
IsSFiniteKernel (κ.restrict hs) := by
refine ⟨⟨fun n => Kernel.restrict (seq κ n) hs, inferInstance, ?_⟩⟩
ext1 a
simp_rw [sum_apply, restrict_apply, ← Measure.restrict_sum _ hs, ← sum_apply, kernel_sum_seq]
end Restrict
section ComapRight
variable {γ : Type*} {mγ : MeasurableSpace γ} {f : γ → β}
/-- Kernel with value `(κ a).comap f`, for a measurable embedding `f`. That is, for a measurable set
`t : Set β`, `ProbabilityTheory.Kernel.comapRight κ hf a t = κ a (f '' t)`. -/
noncomputable def comapRight (κ : Kernel α β) (hf : MeasurableEmbedding f) : Kernel α γ where
toFun a := (κ a).comap f
measurable' := by
refine Measure.measurable_measure.mpr fun t ht => ?_
have : (fun a => Measure.comap f (κ a) t) = fun a => κ a (f '' t) := by
ext1 a
rw [Measure.comap_apply _ hf.injective _ _ ht]
exact fun s' hs' ↦ hf.measurableSet_image.mpr hs'
rw [this]
exact Kernel.measurable_coe _ (hf.measurableSet_image.mpr ht)
theorem comapRight_apply (κ : Kernel α β) (hf : MeasurableEmbedding f) (a : α) :
comapRight κ hf a = Measure.comap f (κ a) :=
rfl
theorem comapRight_apply' (κ : Kernel α β) (hf : MeasurableEmbedding f) (a : α) {t : Set γ}
(ht : MeasurableSet t) : comapRight κ hf a t = κ a (f '' t) := by
rw [comapRight_apply,
Measure.comap_apply _ hf.injective (fun s => hf.measurableSet_image.mpr) _ ht]
@[simp]
lemma comapRight_id (κ : Kernel α β) : comapRight κ MeasurableEmbedding.id = κ := by
ext _ _ hs; rw [comapRight_apply' _ _ _ hs]; simp
theorem IsMarkovKernel.comapRight (κ : Kernel α β) (hf : MeasurableEmbedding f)
(hκ : ∀ a, κ a (Set.range f) = 1) : IsMarkovKernel (comapRight κ hf) := by
refine ⟨fun a => ⟨?_⟩⟩
rw [comapRight_apply' κ hf a MeasurableSet.univ]
simp only [Set.image_univ, Subtype.range_coe_subtype, Set.setOf_mem_eq]
exact hκ a
instance IsFiniteKernel.comapRight (κ : Kernel α β) [IsFiniteKernel κ]
(hf : MeasurableEmbedding f) : IsFiniteKernel (comapRight κ hf) := by
refine ⟨⟨IsFiniteKernel.bound κ, IsFiniteKernel.bound_lt_top κ, fun a => ?_⟩⟩
rw [comapRight_apply' κ hf a .univ]
exact measure_le_bound κ a _
protected instance IsSFiniteKernel.comapRight (κ : Kernel α β) [IsSFiniteKernel κ]
(hf : MeasurableEmbedding f) : IsSFiniteKernel (comapRight κ hf) := by
refine ⟨⟨fun n => comapRight (seq κ n) hf, inferInstance, ?_⟩⟩
ext1 a
rw [sum_apply]
simp_rw [comapRight_apply _ hf]
have :
(Measure.sum fun n => Measure.comap f (seq κ n a)) =
Measure.comap f (Measure.sum fun n => seq κ n a) := by
ext1 t ht
rw [Measure.comap_apply _ hf.injective (fun s' => hf.measurableSet_image.mpr) _ ht,
Measure.sum_apply _ ht, Measure.sum_apply _ (hf.measurableSet_image.mpr ht)]
congr with n : 1
rw [Measure.comap_apply _ hf.injective (fun s' => hf.measurableSet_image.mpr) _ ht]
rw [this, measure_sum_seq]
end ComapRight
section Piecewise
variable {η : Kernel α β} {s : Set α} {hs : MeasurableSet s} [DecidablePred (· ∈ s)]
/-- `ProbabilityTheory.Kernel.piecewise hs κ η` is the kernel equal to `κ` on the measurable set `s`
and to `η` on its complement. -/
def piecewise (hs : MeasurableSet s) (κ η : Kernel α β) : Kernel α β where
toFun a := if a ∈ s then κ a else η a
measurable' := κ.measurable.piecewise hs η.measurable
theorem piecewise_apply (a : α) : piecewise hs κ η a = if a ∈ s then κ a else η a :=
rfl
theorem piecewise_apply' (a : α) (t : Set β) :
piecewise hs κ η a t = if a ∈ s then κ a t else η a t := by
rw [piecewise_apply]; split_ifs <;> rfl
instance IsMarkovKernel.piecewise [IsMarkovKernel κ] [IsMarkovKernel η] :
IsMarkovKernel (piecewise hs κ η) := by
refine ⟨fun a => ⟨?_⟩⟩
rw [piecewise_apply', measure_univ, measure_univ, ite_self]
instance IsFiniteKernel.piecewise [IsFiniteKernel κ] [IsFiniteKernel η] :
IsFiniteKernel (piecewise hs κ η) := by
refine ⟨⟨max (IsFiniteKernel.bound κ) (IsFiniteKernel.bound η), ?_, fun a => ?_⟩⟩
· exact max_lt (IsFiniteKernel.bound_lt_top κ) (IsFiniteKernel.bound_lt_top η)
rw [piecewise_apply']
exact (ite_le_sup _ _ _).trans (sup_le_sup (measure_le_bound _ _ _) (measure_le_bound _ _ _))
protected instance IsSFiniteKernel.piecewise [IsSFiniteKernel κ] [IsSFiniteKernel η] :
IsSFiniteKernel (piecewise hs κ η) := by
refine ⟨⟨fun n => piecewise hs (seq κ n) (seq η n), inferInstance, ?_⟩⟩
ext1 a
simp_rw [sum_apply, Kernel.piecewise_apply]
split_ifs <;> exact (measure_sum_seq _ a).symm
theorem lintegral_piecewise (a : α) (g : β → ℝ≥0∞) :
∫⁻ b, g b ∂piecewise hs κ η a = if a ∈ s then ∫⁻ b, g b ∂κ a else ∫⁻ b, g b ∂η a := by
simp_rw [piecewise_apply]; split_ifs <;> rfl
theorem setLIntegral_piecewise (a : α) (g : β → ℝ≥0∞) (t : Set β) :
∫⁻ b in t, g b ∂piecewise hs κ η a =
if a ∈ s then ∫⁻ b in t, g b ∂κ a else ∫⁻ b in t, g b ∂η a := by
simp_rw [piecewise_apply]; split_ifs <;> rfl
end Piecewise
lemma exists_ae_eq_isMarkovKernel {μ : Measure α}
(h : ∀ᵐ a ∂μ, IsProbabilityMeasure (κ a)) (h' : μ ≠ 0) :
∃ (η : Kernel α β), (κ =ᵐ[μ] η) ∧ IsMarkovKernel η := by
classical
obtain ⟨s, s_meas, μs, hs⟩ : ∃ s, MeasurableSet s ∧ μ s = 0
∧ ∀ a ∉ s, IsProbabilityMeasure (κ a) := by
refine ⟨toMeasurable μ {a | ¬ IsProbabilityMeasure (κ a)}, measurableSet_toMeasurable _ _,
by simpa [measure_toMeasurable] using h, ?_⟩
intro a ha
contrapose! ha
exact subset_toMeasurable _ _ ha
obtain ⟨a, ha⟩ : sᶜ.Nonempty := by
contrapose! h'; simpa [μs, h'] using measure_univ_le_add_compl s (μ := μ)
refine ⟨Kernel.piecewise s_meas (Kernel.const _ (κ a)) κ, ?_, ?_⟩
· filter_upwards [measure_zero_iff_ae_nmem.1 μs] with b hb
simp [hb, piecewise]
· refine ⟨fun b ↦ ?_⟩
by_cases hb : b ∈ s
· simpa [hb, piecewise] using hs _ ha
· simpa [hb, piecewise] using hs _ hb
end Kernel
end ProbabilityTheory
| Mathlib/Probability/Kernel/Basic.lean | 731 | 734 | |
/-
Copyright (c) 2019 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Lu-Ming Zhang
-/
import Mathlib.Data.Matrix.Invertible
import Mathlib.Data.Matrix.Kronecker
import Mathlib.LinearAlgebra.FiniteDimensional.Basic
import Mathlib.LinearAlgebra.Matrix.Adjugate
import Mathlib.LinearAlgebra.Matrix.SemiringInverse
import Mathlib.LinearAlgebra.Matrix.ToLin
import Mathlib.LinearAlgebra.Matrix.Trace
/-!
# Nonsingular inverses
In this file, we define an inverse for square matrices of invertible determinant.
For matrices that are not square or not of full rank, there is a more general notion of
pseudoinverses which we do not consider here.
The definition of inverse used in this file is the adjugate divided by the determinant.
We show that dividing the adjugate by `det A` (if possible), giving a matrix `A⁻¹` (`nonsing_inv`),
will result in a multiplicative inverse to `A`.
Note that there are at least three different inverses in mathlib:
* `A⁻¹` (`Inv.inv`): alone, this satisfies no properties, although it is usually used in
conjunction with `Group` or `GroupWithZero`. On matrices, this is defined to be zero when no
inverse exists.
* `⅟A` (`invOf`): this is only available in the presence of `[Invertible A]`, which guarantees an
inverse exists.
* `Ring.inverse A`: this is defined on any `MonoidWithZero`, and just like `⁻¹` on matrices, is
defined to be zero when no inverse exists.
We start by working with `Invertible`, and show the main results:
* `Matrix.invertibleOfDetInvertible`
* `Matrix.detInvertibleOfInvertible`
* `Matrix.isUnit_iff_isUnit_det`
* `Matrix.mul_eq_one_comm`
After this we define `Matrix.inv` and show it matches `⅟A` and `Ring.inverse A`.
The rest of the results in the file are then about `A⁻¹`
## References
* https://en.wikipedia.org/wiki/Cramer's_rule#Finding_inverse_matrix
## Tags
matrix inverse, cramer, cramer's rule, adjugate
-/
namespace Matrix
universe u u' v
variable {l : Type*} {m : Type u} {n : Type u'} {α : Type v}
open Matrix Equiv Equiv.Perm Finset
/-! ### Matrices are `Invertible` iff their determinants are -/
section Invertible
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
/-- If `A.det` has a constructive inverse, produce one for `A`. -/
def invertibleOfDetInvertible [Invertible A.det] : Invertible A where
invOf := ⅟ A.det • A.adjugate
mul_invOf_self := by
rw [mul_smul_comm, mul_adjugate, smul_smul, invOf_mul_self, one_smul]
invOf_mul_self := by
rw [smul_mul_assoc, adjugate_mul, smul_smul, invOf_mul_self, one_smul]
theorem invOf_eq [Invertible A.det] [Invertible A] : ⅟ A = ⅟ A.det • A.adjugate := by
letI := invertibleOfDetInvertible A
convert (rfl : ⅟ A = _)
/-- `A.det` is invertible if `A` has a left inverse. -/
def detInvertibleOfLeftInverse (h : B * A = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [mul_comm, ← det_mul, h, det_one]
invOf_mul_self := by rw [← det_mul, h, det_one]
/-- `A.det` is invertible if `A` has a right inverse. -/
def detInvertibleOfRightInverse (h : A * B = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [← det_mul, h, det_one]
invOf_mul_self := by rw [mul_comm, ← det_mul, h, det_one]
/-- If `A` has a constructive inverse, produce one for `A.det`. -/
def detInvertibleOfInvertible [Invertible A] : Invertible A.det :=
detInvertibleOfLeftInverse A (⅟ A) (invOf_mul_self _)
theorem det_invOf [Invertible A] [Invertible A.det] : (⅟ A).det = ⅟ A.det := by
letI := detInvertibleOfInvertible A
convert (rfl : _ = ⅟ A.det)
/-- Together `Matrix.detInvertibleOfInvertible` and `Matrix.invertibleOfDetInvertible` form an
equivalence, although both sides of the equiv are subsingleton anyway. -/
@[simps]
def invertibleEquivDetInvertible : Invertible A ≃ Invertible A.det where
toFun := @detInvertibleOfInvertible _ _ _ _ _ A
invFun := @invertibleOfDetInvertible _ _ _ _ _ A
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
/-- Given a proof that `A.det` has a constructive inverse, lift `A` to `(Matrix n n α)ˣ` -/
def unitOfDetInvertible [Invertible A.det] : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ A (invertibleOfDetInvertible A)
/-- When lowered to a prop, `Matrix.invertibleEquivDetInvertible` forms an `iff`. -/
theorem isUnit_iff_isUnit_det : IsUnit A ↔ IsUnit A.det := by
simp only [← nonempty_invertible_iff_isUnit, (invertibleEquivDetInvertible A).nonempty_congr]
@[simp]
theorem isUnits_det_units (A : (Matrix n n α)ˣ) : IsUnit (A : Matrix n n α).det :=
isUnit_iff_isUnit_det _ |>.mp A.isUnit
/-! #### Variants of the statements above with `IsUnit` -/
theorem isUnit_det_of_invertible [Invertible A] : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfInvertible A)
variable {A B}
theorem isUnit_det_of_left_inverse (h : B * A = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfLeftInverse _ _ h)
theorem isUnit_det_of_right_inverse (h : A * B = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfRightInverse _ _ h)
theorem det_ne_zero_of_left_inverse [Nontrivial α] (h : B * A = 1) : A.det ≠ 0 :=
(isUnit_det_of_left_inverse h).ne_zero
theorem det_ne_zero_of_right_inverse [Nontrivial α] (h : A * B = 1) : A.det ≠ 0 :=
(isUnit_det_of_right_inverse h).ne_zero
end Invertible
section Inv
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem isUnit_det_transpose (h : IsUnit A.det) : IsUnit Aᵀ.det := by
rw [det_transpose]
exact h
/-! ### A noncomputable `Inv` instance -/
/-- The inverse of a square matrix, when it is invertible (and zero otherwise). -/
noncomputable instance inv : Inv (Matrix n n α) :=
⟨fun A => Ring.inverse A.det • A.adjugate⟩
theorem inv_def (A : Matrix n n α) : A⁻¹ = Ring.inverse A.det • A.adjugate :=
rfl
theorem nonsing_inv_apply_not_isUnit (h : ¬IsUnit A.det) : A⁻¹ = 0 := by
rw [inv_def, Ring.inverse_non_unit _ h, zero_smul]
theorem nonsing_inv_apply (h : IsUnit A.det) : A⁻¹ = (↑h.unit⁻¹ : α) • A.adjugate := by
rw [inv_def, ← Ring.inverse_unit h.unit, IsUnit.unit_spec]
/-- The nonsingular inverse is the same as `invOf` when `A` is invertible. -/
@[simp]
theorem invOf_eq_nonsing_inv [Invertible A] : ⅟ A = A⁻¹ := by
letI := detInvertibleOfInvertible A
rw [inv_def, Ring.inverse_invertible, invOf_eq]
/-- Coercing the result of `Units.instInv` is the same as coercing first and applying the
nonsingular inverse. -/
@[simp, norm_cast]
theorem coe_units_inv (A : (Matrix n n α)ˣ) : ↑A⁻¹ = (A⁻¹ : Matrix n n α) := by
letI := A.invertible
rw [← invOf_eq_nonsing_inv, invOf_units]
/-- The nonsingular inverse is the same as the general `Ring.inverse`. -/
theorem nonsing_inv_eq_ringInverse : A⁻¹ = Ring.inverse A := by
by_cases h_det : IsUnit A.det
· cases (A.isUnit_iff_isUnit_det.mpr h_det).nonempty_invertible
rw [← invOf_eq_nonsing_inv, Ring.inverse_invertible]
· have h := mt A.isUnit_iff_isUnit_det.mp h_det
rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit A h_det]
@[deprecated (since := "2025-04-22")]
alias nonsing_inv_eq_ring_inverse := nonsing_inv_eq_ringInverse
theorem transpose_nonsing_inv : A⁻¹ᵀ = Aᵀ⁻¹ := by
rw [inv_def, inv_def, transpose_smul, det_transpose, adjugate_transpose]
theorem conjTranspose_nonsing_inv [StarRing α] : A⁻¹ᴴ = Aᴴ⁻¹ := by
rw [inv_def, inv_def, conjTranspose_smul, det_conjTranspose, adjugate_conjTranspose,
Ring.inverse_star]
/-- The `nonsing_inv` of `A` is a right inverse. -/
@[simp]
theorem mul_nonsing_inv (h : IsUnit A.det) : A * A⁻¹ = 1 := by
cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, mul_invOf_self]
/-- The `nonsing_inv` of `A` is a left inverse. -/
@[simp]
theorem nonsing_inv_mul (h : IsUnit A.det) : A⁻¹ * A = 1 := by
cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, invOf_mul_self]
instance [Invertible A] : Invertible A⁻¹ := by
rw [← invOf_eq_nonsing_inv]
infer_instance
@[simp]
theorem inv_inv_of_invertible [Invertible A] : A⁻¹⁻¹ = A := by
simp only [← invOf_eq_nonsing_inv, invOf_invOf]
@[simp]
theorem mul_nonsing_inv_cancel_right (B : Matrix m n α) (h : IsUnit A.det) : B * A * A⁻¹ = B := by
simp [Matrix.mul_assoc, mul_nonsing_inv A h]
@[simp]
theorem mul_nonsing_inv_cancel_left (B : Matrix n m α) (h : IsUnit A.det) : A * (A⁻¹ * B) = B := by
simp [← Matrix.mul_assoc, mul_nonsing_inv A h]
@[simp]
theorem nonsing_inv_mul_cancel_right (B : Matrix m n α) (h : IsUnit A.det) : B * A⁻¹ * A = B := by
simp [Matrix.mul_assoc, nonsing_inv_mul A h]
@[simp]
theorem nonsing_inv_mul_cancel_left (B : Matrix n m α) (h : IsUnit A.det) : A⁻¹ * (A * B) = B := by
simp [← Matrix.mul_assoc, nonsing_inv_mul A h]
@[simp]
theorem mul_inv_of_invertible [Invertible A] : A * A⁻¹ = 1 :=
mul_nonsing_inv A (isUnit_det_of_invertible A)
@[simp]
theorem inv_mul_of_invertible [Invertible A] : A⁻¹ * A = 1 :=
nonsing_inv_mul A (isUnit_det_of_invertible A)
@[simp]
theorem mul_inv_cancel_right_of_invertible (B : Matrix m n α) [Invertible A] : B * A * A⁻¹ = B :=
mul_nonsing_inv_cancel_right A B (isUnit_det_of_invertible A)
@[simp]
theorem mul_inv_cancel_left_of_invertible (B : Matrix n m α) [Invertible A] : A * (A⁻¹ * B) = B :=
mul_nonsing_inv_cancel_left A B (isUnit_det_of_invertible A)
@[simp]
theorem inv_mul_cancel_right_of_invertible (B : Matrix m n α) [Invertible A] : B * A⁻¹ * A = B :=
nonsing_inv_mul_cancel_right A B (isUnit_det_of_invertible A)
@[simp]
theorem inv_mul_cancel_left_of_invertible (B : Matrix n m α) [Invertible A] : A⁻¹ * (A * B) = B :=
nonsing_inv_mul_cancel_left A B (isUnit_det_of_invertible A)
theorem inv_mul_eq_iff_eq_mul_of_invertible (A B C : Matrix n n α) [Invertible A] :
A⁻¹ * B = C ↔ B = A * C :=
⟨fun h => by rw [← h, mul_inv_cancel_left_of_invertible],
fun h => by rw [h, inv_mul_cancel_left_of_invertible]⟩
theorem mul_inv_eq_iff_eq_mul_of_invertible (A B C : Matrix n n α) [Invertible A] :
B * A⁻¹ = C ↔ B = C * A :=
⟨fun h => by rw [← h, inv_mul_cancel_right_of_invertible],
fun h => by rw [h, mul_inv_cancel_right_of_invertible]⟩
lemma inv_mulVec_eq_vec {A : Matrix n n α} [Invertible A]
{u v : n → α} (hM : u = A.mulVec v) : A⁻¹.mulVec u = v := by
rw [hM, Matrix.mulVec_mulVec, Matrix.inv_mul_of_invertible, Matrix.one_mulVec]
lemma mul_right_injective_of_invertible [Invertible A] :
Function.Injective (fun (x : Matrix n m α) => A * x) :=
fun _ _ h => by simpa only [inv_mul_cancel_left_of_invertible] using congr_arg (A⁻¹ * ·) h
lemma mul_left_injective_of_invertible [Invertible A] :
Function.Injective (fun (x : Matrix m n α) => x * A) :=
fun a x hax => by simpa only [mul_inv_cancel_right_of_invertible] using congr_arg (· * A⁻¹) hax
lemma mul_right_inj_of_invertible [Invertible A] {x y : Matrix n m α} : A * x = A * y ↔ x = y :=
(mul_right_injective_of_invertible A).eq_iff
lemma mul_left_inj_of_invertible [Invertible A] {x y : Matrix m n α} : x * A = y * A ↔ x = y :=
(mul_left_injective_of_invertible A).eq_iff
end Inv
section InjectiveMul
variable [Fintype n] [Fintype m] [DecidableEq m] [CommRing α]
lemma mul_left_injective_of_inv (A : Matrix m n α) (B : Matrix n m α) (h : A * B = 1) :
Function.Injective (fun x : Matrix l m α => x * A) := fun _ _ g => by
simpa only [Matrix.mul_assoc, Matrix.mul_one, h] using congr_arg (· * B) g
lemma mul_right_injective_of_inv (A : Matrix m n α) (B : Matrix n m α) (h : A * B = 1) :
Function.Injective (fun x : Matrix m l α => B * x) :=
fun _ _ g => by simpa only [← Matrix.mul_assoc, Matrix.one_mul, h] using congr_arg (A * ·) g
end InjectiveMul
section vecMul
section Semiring
variable {R : Type*} [Semiring R]
theorem vecMul_surjective_iff_exists_left_inverse
[DecidableEq n] [Fintype m] [Finite n] {A : Matrix m n R} :
Function.Surjective A.vecMul ↔ ∃ B : Matrix n m R, B * A = 1 := by
cases nonempty_fintype n
refine ⟨fun h ↦ ?_, fun ⟨B, hBA⟩ y ↦ ⟨y ᵥ* B, by simp [hBA]⟩⟩
choose rows hrows using (h <| Pi.single · 1)
refine ⟨Matrix.of rows, Matrix.ext fun i j => ?_⟩
rw [mul_apply_eq_vecMul, one_eq_pi_single, ← hrows]
rfl
theorem mulVec_surjective_iff_exists_right_inverse
[DecidableEq m] [Finite m] [Fintype n] {A : Matrix m n R} :
Function.Surjective A.mulVec ↔ ∃ B : Matrix n m R, A * B = 1 := by
cases nonempty_fintype m
refine ⟨fun h ↦ ?_, fun ⟨B, hBA⟩ y ↦ ⟨B *ᵥ y, by simp [hBA]⟩⟩
choose cols hcols using (h <| Pi.single · 1)
refine ⟨(Matrix.of cols)ᵀ, Matrix.ext fun i j ↦ ?_⟩
rw [one_eq_pi_single, Pi.single_comm, ← hcols j]
rfl
end Semiring
variable [DecidableEq m] {R K : Type*} [CommRing R] [Field K] [Fintype m]
theorem vecMul_surjective_iff_isUnit {A : Matrix m m R} :
Function.Surjective A.vecMul ↔ IsUnit A := by
rw [vecMul_surjective_iff_exists_left_inverse, exists_left_inverse_iff_isUnit]
theorem mulVec_surjective_iff_isUnit {A : Matrix m m R} :
Function.Surjective A.mulVec ↔ IsUnit A := by
rw [mulVec_surjective_iff_exists_right_inverse, exists_right_inverse_iff_isUnit]
theorem vecMul_injective_iff_isUnit {A : Matrix m m K} :
Function.Injective A.vecMul ↔ IsUnit A := by
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· rw [← vecMul_surjective_iff_isUnit]
exact LinearMap.surjective_of_injective (f := A.vecMulLinear) h
change Function.Injective A.vecMulLinear
rw [← LinearMap.ker_eq_bot, LinearMap.ker_eq_bot']
intro c hc
replace h := h.invertible
simpa using congr_arg A⁻¹.vecMulLinear hc
theorem mulVec_injective_iff_isUnit {A : Matrix m m K} :
Function.Injective A.mulVec ↔ IsUnit A := by
rw [← isUnit_transpose, ← vecMul_injective_iff_isUnit]
simp_rw [vecMul_transpose]
theorem linearIndependent_rows_iff_isUnit {A : Matrix m m K} :
LinearIndependent K A.row ↔ IsUnit A := by
rw [← col_transpose, ← mulVec_injective_iff, ← coe_mulVecLin, mulVecLin_transpose,
← vecMul_injective_iff_isUnit, coe_vecMulLinear]
theorem linearIndependent_cols_iff_isUnit {A : Matrix m m K} :
LinearIndependent K A.col ↔ IsUnit A := by
rw [← row_transpose, linearIndependent_rows_iff_isUnit, isUnit_transpose]
theorem vecMul_surjective_of_invertible (A : Matrix m m R) [Invertible A] :
Function.Surjective A.vecMul :=
vecMul_surjective_iff_isUnit.2 <| isUnit_of_invertible A
theorem mulVec_surjective_of_invertible (A : Matrix m m R) [Invertible A] :
Function.Surjective A.mulVec :=
mulVec_surjective_iff_isUnit.2 <| isUnit_of_invertible A
theorem vecMul_injective_of_invertible (A : Matrix m m K) [Invertible A] :
Function.Injective A.vecMul :=
vecMul_injective_iff_isUnit.2 <| isUnit_of_invertible A
theorem mulVec_injective_of_invertible (A : Matrix m m K) [Invertible A] :
Function.Injective A.mulVec :=
mulVec_injective_iff_isUnit.2 <| isUnit_of_invertible A
theorem linearIndependent_rows_of_invertible (A : Matrix m m K) [Invertible A] :
LinearIndependent K A.row :=
linearIndependent_rows_iff_isUnit.2 <| isUnit_of_invertible A
theorem linearIndependent_cols_of_invertible (A : Matrix m m K) [Invertible A] :
LinearIndependent K A.col :=
linearIndependent_cols_iff_isUnit.2 <| isUnit_of_invertible A
end vecMul
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem nonsing_inv_cancel_or_zero : A⁻¹ * A = 1 ∧ A * A⁻¹ = 1 ∨ A⁻¹ = 0 := by
by_cases h : IsUnit A.det
· exact Or.inl ⟨nonsing_inv_mul _ h, mul_nonsing_inv _ h⟩
· exact Or.inr (nonsing_inv_apply_not_isUnit _ h)
theorem det_nonsing_inv_mul_det (h : IsUnit A.det) : A⁻¹.det * A.det = 1 := by
rw [← det_mul, A.nonsing_inv_mul h, det_one]
@[simp]
theorem det_nonsing_inv : A⁻¹.det = Ring.inverse A.det := by
by_cases h : IsUnit A.det
· cases h.nonempty_invertible
letI := invertibleOfDetInvertible A
rw [Ring.inverse_invertible, ← invOf_eq_nonsing_inv, det_invOf]
cases isEmpty_or_nonempty n
· rw [det_isEmpty, det_isEmpty, Ring.inverse_one]
· rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit _ h, det_zero ‹_›]
theorem isUnit_nonsing_inv_det (h : IsUnit A.det) : IsUnit A⁻¹.det :=
isUnit_of_mul_eq_one _ _ (A.det_nonsing_inv_mul_det h)
@[simp]
theorem nonsing_inv_nonsing_inv (h : IsUnit A.det) : A⁻¹⁻¹ = A :=
calc
A⁻¹⁻¹ = 1 * A⁻¹⁻¹ := by rw [Matrix.one_mul]
_ = A * A⁻¹ * A⁻¹⁻¹ := by rw [A.mul_nonsing_inv h]
_ = A := by
rw [Matrix.mul_assoc, A⁻¹.mul_nonsing_inv (A.isUnit_nonsing_inv_det h), Matrix.mul_one]
theorem isUnit_nonsing_inv_det_iff {A : Matrix n n α} : IsUnit A⁻¹.det ↔ IsUnit A.det := by
rw [Matrix.det_nonsing_inv, isUnit_ringInverse]
@[simp]
theorem isUnit_nonsing_inv_iff {A : Matrix n n α} : IsUnit A⁻¹ ↔ IsUnit A := by
simp_rw [isUnit_iff_isUnit_det, isUnit_nonsing_inv_det_iff]
-- `IsUnit.invertible` lifts the proposition `IsUnit A` to a constructive inverse of `A`.
/-- A version of `Matrix.invertibleOfDetInvertible` with the inverse defeq to `A⁻¹` that is
therefore noncomputable. -/
noncomputable def invertibleOfIsUnitDet (h : IsUnit A.det) : Invertible A :=
⟨A⁻¹, nonsing_inv_mul A h, mul_nonsing_inv A h⟩
/-- A version of `Matrix.unitOfDetInvertible` with the inverse defeq to `A⁻¹` that is therefore
noncomputable. -/
noncomputable def nonsingInvUnit (h : IsUnit A.det) : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ _ (invertibleOfIsUnitDet A h)
theorem unitOfDetInvertible_eq_nonsingInvUnit [Invertible A.det] :
unitOfDetInvertible A = nonsingInvUnit A (isUnit_of_invertible _) := by
ext
rfl
variable {A} {B}
/-- If matrix A is left invertible, then its inverse equals its left inverse. -/
theorem inv_eq_left_inv (h : B * A = 1) : A⁻¹ = B :=
letI := invertibleOfLeftInverse _ _ h
invOf_eq_nonsing_inv A ▸ invOf_eq_left_inv h
/-- If matrix A is right invertible, then its inverse equals its right inverse. -/
theorem inv_eq_right_inv (h : A * B = 1) : A⁻¹ = B :=
inv_eq_left_inv (mul_eq_one_comm.2 h)
section InvEqInv
variable {C : Matrix n n α}
/-- The left inverse of matrix A is unique when existing. -/
theorem left_inv_eq_left_inv (h : B * A = 1) (g : C * A = 1) : B = C := by
rw [← inv_eq_left_inv h, ← inv_eq_left_inv g]
/-- The right inverse of matrix A is unique when existing. -/
theorem right_inv_eq_right_inv (h : A * B = 1) (g : A * C = 1) : B = C := by
rw [← inv_eq_right_inv h, ← inv_eq_right_inv g]
/-- The right inverse of matrix A equals the left inverse of A when they exist. -/
theorem right_inv_eq_left_inv (h : A * B = 1) (g : C * A = 1) : B = C := by
rw [← inv_eq_right_inv h, ← inv_eq_left_inv g]
theorem inv_inj (h : A⁻¹ = B⁻¹) (h' : IsUnit A.det) : A = B := by
refine left_inv_eq_left_inv (mul_nonsing_inv _ h') ?_
rw [h]
refine mul_nonsing_inv _ ?_
rwa [← isUnit_nonsing_inv_det_iff, ← h, isUnit_nonsing_inv_det_iff]
end InvEqInv
variable (A)
@[simp]
theorem inv_zero : (0 : Matrix n n α)⁻¹ = 0 := by
rcases subsingleton_or_nontrivial α with ht | ht
· simp [eq_iff_true_of_subsingleton]
rcases (Fintype.card n).zero_le.eq_or_lt with hc | hc
· rw [eq_comm, Fintype.card_eq_zero_iff] at hc
haveI := hc
ext i
exact (IsEmpty.false i).elim
· have hn : Nonempty n := Fintype.card_pos_iff.mp hc
refine nonsing_inv_apply_not_isUnit _ ?_
simp [hn]
noncomputable instance : InvOneClass (Matrix n n α) :=
{ Matrix.one, Matrix.inv with inv_one := inv_eq_left_inv (by simp) }
theorem inv_smul (k : α) [Invertible k] (h : IsUnit A.det) : (k • A)⁻¹ = ⅟ k • A⁻¹ :=
inv_eq_left_inv (by simp [h, smul_smul])
theorem inv_smul' (k : αˣ) (h : IsUnit A.det) : (k • A)⁻¹ = k⁻¹ • A⁻¹ :=
inv_eq_left_inv (by simp [h, smul_smul])
theorem inv_adjugate (A : Matrix n n α) (h : IsUnit A.det) : (adjugate A)⁻¹ = h.unit⁻¹ • A := by
refine inv_eq_left_inv ?_
rw [smul_mul, mul_adjugate, Units.smul_def, smul_smul, h.val_inv_mul, one_smul]
section Diagonal
/-- `diagonal v` is invertible if `v` is -/
def diagonalInvertible {α} [NonAssocSemiring α] (v : n → α) [Invertible v] :
Invertible (diagonal v) :=
Invertible.map (diagonalRingHom n α) v
theorem invOf_diagonal_eq {α} [Semiring α] (v : n → α) [Invertible v] [Invertible (diagonal v)] :
⅟ (diagonal v) = diagonal (⅟ v) := by
rw [@Invertible.congr _ _ _ _ _ (diagonalInvertible v) rfl]
rfl
/-- `v` is invertible if `diagonal v` is -/
def invertibleOfDiagonalInvertible (v : n → α) [Invertible (diagonal v)] : Invertible v where
invOf := diag (⅟ (diagonal v))
invOf_mul_self :=
funext fun i => by
letI : Invertible (diagonal v).det := detInvertibleOfInvertible _
rw [invOf_eq, diag_smul, adjugate_diagonal, diag_diagonal]
dsimp
rw [mul_assoc, prod_erase_mul _ _ (Finset.mem_univ _), ← det_diagonal]
exact mul_invOf_self _
mul_invOf_self :=
funext fun i => by
letI : Invertible (diagonal v).det := detInvertibleOfInvertible _
rw [invOf_eq, diag_smul, adjugate_diagonal, diag_diagonal]
dsimp
rw [mul_left_comm, mul_prod_erase _ _ (Finset.mem_univ _), ← det_diagonal]
exact mul_invOf_self _
/-- Together `Matrix.diagonalInvertible` and `Matrix.invertibleOfDiagonalInvertible` form an
equivalence, although both sides of the equiv are subsingleton anyway. -/
@[simps]
def diagonalInvertibleEquivInvertible (v : n → α) : Invertible (diagonal v) ≃ Invertible v where
toFun := @invertibleOfDiagonalInvertible _ _ _ _ _ _
invFun := @diagonalInvertible _ _ _ _ _ _
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
/-- When lowered to a prop, `Matrix.diagonalInvertibleEquivInvertible` forms an `iff`. -/
@[simp]
theorem isUnit_diagonal {v : n → α} : IsUnit (diagonal v) ↔ IsUnit v := by
simp only [← nonempty_invertible_iff_isUnit,
(diagonalInvertibleEquivInvertible v).nonempty_congr]
theorem inv_diagonal (v : n → α) : (diagonal v)⁻¹ = diagonal (Ring.inverse v) := by
rw [nonsing_inv_eq_ringInverse]
by_cases h : IsUnit v
· have := isUnit_diagonal.mpr h
cases this.nonempty_invertible
cases h.nonempty_invertible
rw [Ring.inverse_invertible, Ring.inverse_invertible, invOf_diagonal_eq]
· have := isUnit_diagonal.not.mpr h
rw [Ring.inverse_non_unit _ h, Pi.zero_def, diagonal_zero, Ring.inverse_non_unit _ this]
end Diagonal
/-- The inverse of a 1×1 or 0×0 matrix is always diagonal.
While we could write this as `of fun _ _ => Ring.inverse (A default default)` on the RHS, this is
less useful because:
* It wouldn't work for 0×0 matrices.
* More things are true about diagonal matrices than constant matrices, and so more lemmas exist.
`Matrix.diagonal_unique` can be used to reach this form, while `Ring.inverse_eq_inv` can be used
to replace `Ring.inverse` with `⁻¹`.
-/
@[simp]
theorem inv_subsingleton [Subsingleton m] [Fintype m] [DecidableEq m] (A : Matrix m m α) :
A⁻¹ = diagonal fun i => Ring.inverse (A i i) := by
rw [inv_def, adjugate_subsingleton, smul_one_eq_diagonal]
congr! with i
exact det_eq_elem_of_subsingleton _ _
section Woodbury
variable [Fintype m] [DecidableEq m]
variable (A : Matrix n n α) (U : Matrix n m α) (C : Matrix m m α) (V : Matrix m n α)
/-- The **Woodbury Identity** (`⁻¹` version). -/
theorem add_mul_mul_inv_eq_sub (hA : IsUnit A) (hC : IsUnit C) (hAC : IsUnit (C⁻¹ + V * A⁻¹ * U)) :
(A + U * C * V)⁻¹ = A⁻¹ - A⁻¹ * U * (C⁻¹ + V * A⁻¹ * U)⁻¹ * V * A⁻¹ := by
obtain ⟨_⟩ := hA.nonempty_invertible
obtain ⟨_⟩ := hC.nonempty_invertible
obtain ⟨iAC⟩ := hAC.nonempty_invertible
simp only [← invOf_eq_nonsing_inv] at iAC
letI := invertibleAddMulMul A U C V
simp only [← invOf_eq_nonsing_inv]
apply invOf_add_mul_mul
end Woodbury
@[simp]
theorem inv_inv_inv (A : Matrix n n α) : A⁻¹⁻¹⁻¹ = A⁻¹ := by
by_cases h : IsUnit A.det
· rw [nonsing_inv_nonsing_inv _ h]
· simp [nonsing_inv_apply_not_isUnit _ h]
/-- The `Matrix` version of `inv_add_inv'` -/
theorem inv_add_inv {A B : Matrix n n α} (h : IsUnit A ↔ IsUnit B) :
A⁻¹ + B⁻¹ = A⁻¹ * (A + B) * B⁻¹ := by
simpa only [nonsing_inv_eq_ringInverse] using Ring.inverse_add_inverse h
/-- The `Matrix` version of `inv_sub_inv'` -/
theorem inv_sub_inv {A B : Matrix n n α} (h : IsUnit A ↔ IsUnit B) :
A⁻¹ - B⁻¹ = A⁻¹ * (B - A) * B⁻¹ := by
simpa only [nonsing_inv_eq_ringInverse] using Ring.inverse_sub_inverse h
theorem mul_inv_rev (A B : Matrix n n α) : (A * B)⁻¹ = B⁻¹ * A⁻¹ := by
simp only [inv_def]
rw [Matrix.smul_mul, Matrix.mul_smul, smul_smul, det_mul, adjugate_mul_distrib,
Ring.mul_inverse_rev]
/-- A version of `List.prod_inv_reverse` for `Matrix.inv`. -/
theorem list_prod_inv_reverse : ∀ l : List (Matrix n n α), l.prod⁻¹ = (l.reverse.map Inv.inv).prod
| [] => by rw [List.reverse_nil, List.map_nil, List.prod_nil, inv_one]
| A::Xs => by
rw [List.reverse_cons', List.map_concat, List.prod_concat, List.prod_cons,
mul_inv_rev, list_prod_inv_reverse Xs]
/-- One form of **Cramer's rule**. See `Matrix.mulVec_cramer` for a stronger form. -/
@[simp]
theorem det_smul_inv_mulVec_eq_cramer (A : Matrix n n α) (b : n → α) (h : IsUnit A.det) :
A.det • A⁻¹ *ᵥ b = cramer A b := by
rw [cramer_eq_adjugate_mulVec, A.nonsing_inv_apply h, ← smul_mulVec_assoc, smul_smul,
h.mul_val_inv, one_smul]
/-- One form of **Cramer's rule**. See `Matrix.mulVec_cramer` for a stronger form. -/
@[simp]
theorem det_smul_inv_vecMul_eq_cramer_transpose (A : Matrix n n α) (b : n → α) (h : IsUnit A.det) :
A.det • b ᵥ* A⁻¹ = cramer Aᵀ b := by
rw [← A⁻¹.transpose_transpose, vecMul_transpose, transpose_nonsing_inv, ← det_transpose,
Aᵀ.det_smul_inv_mulVec_eq_cramer _ (isUnit_det_transpose A h)]
/-! ### Inverses of permutated matrices
Note that the simp-normal form of `Matrix.reindex` is `Matrix.submatrix`, so we prove most of these
results about only the latter.
-/
section Submatrix
variable [Fintype m]
variable [DecidableEq m]
/-- `A.submatrix e₁ e₂` is invertible if `A` is -/
def submatrixEquivInvertible (A : Matrix m m α) (e₁ e₂ : n ≃ m) [Invertible A] :
Invertible (A.submatrix e₁ e₂) :=
invertibleOfRightInverse _ ((⅟ A).submatrix e₂ e₁) <| by
rw [Matrix.submatrix_mul_equiv, mul_invOf_self, submatrix_one_equiv]
/-- `A` is invertible if `A.submatrix e₁ e₂` is -/
def invertibleOfSubmatrixEquivInvertible (A : Matrix m m α) (e₁ e₂ : n ≃ m)
[Invertible (A.submatrix e₁ e₂)] : Invertible A :=
invertibleOfRightInverse _ ((⅟ (A.submatrix e₁ e₂)).submatrix e₂.symm e₁.symm) <| by
have : A = (A.submatrix e₁ e₂).submatrix e₁.symm e₂.symm := by simp
conv in _ * _ =>
congr
rw [this]
rw [Matrix.submatrix_mul_equiv, mul_invOf_self, submatrix_one_equiv]
theorem invOf_submatrix_equiv_eq (A : Matrix m m α) (e₁ e₂ : n ≃ m) [Invertible A]
[Invertible (A.submatrix e₁ e₂)] : ⅟ (A.submatrix e₁ e₂) = (⅟ A).submatrix e₂ e₁ := by
| rw [@Invertible.congr _ _ _ _ _ (submatrixEquivInvertible A e₁ e₂) rfl]
rfl
| Mathlib/LinearAlgebra/Matrix/NonsingularInverse.lean | 678 | 680 |
/-
Copyright (c) 2017 Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Mario Carneiro
-/
import Mathlib.Algebra.Ring.CharZero
import Mathlib.Algebra.Star.Basic
import Mathlib.Data.Real.Basic
import Mathlib.Order.Interval.Set.UnorderedInterval
import Mathlib.Tactic.Ring
/-!
# The complex numbers
The complex numbers are modelled as ℝ^2 in the obvious way and it is shown that they form a field
of characteristic zero. The result that the complex numbers are algebraically closed, see
`FieldTheory.AlgebraicClosure`.
-/
assert_not_exists Multiset Algebra
open Set Function
/-! ### Definition and basic arithmetic -/
/-- Complex numbers consist of two `Real`s: a real part `re` and an imaginary part `im`. -/
structure Complex : Type where
/-- The real part of a complex number. -/
re : ℝ
/-- The imaginary part of a complex number. -/
im : ℝ
@[inherit_doc] notation "ℂ" => Complex
namespace Complex
open ComplexConjugate
noncomputable instance : DecidableEq ℂ :=
Classical.decEq _
/-- The equivalence between the complex numbers and `ℝ × ℝ`. -/
@[simps apply]
def equivRealProd : ℂ ≃ ℝ × ℝ where
toFun z := ⟨z.re, z.im⟩
invFun p := ⟨p.1, p.2⟩
left_inv := fun ⟨_, _⟩ => rfl
right_inv := fun ⟨_, _⟩ => rfl
@[simp]
theorem eta : ∀ z : ℂ, Complex.mk z.re z.im = z
| ⟨_, _⟩ => rfl
-- We only mark this lemma with `ext` *locally* to avoid it applying whenever terms of `ℂ` appear.
theorem ext : ∀ {z w : ℂ}, z.re = w.re → z.im = w.im → z = w
| ⟨_, _⟩, ⟨_, _⟩, rfl, rfl => rfl
attribute [local ext] Complex.ext
lemma «forall» {p : ℂ → Prop} : (∀ x, p x) ↔ ∀ a b, p ⟨a, b⟩ := by aesop
lemma «exists» {p : ℂ → Prop} : (∃ x, p x) ↔ ∃ a b, p ⟨a, b⟩ := by aesop
theorem re_surjective : Surjective re := fun x => ⟨⟨x, 0⟩, rfl⟩
theorem im_surjective : Surjective im := fun y => ⟨⟨0, y⟩, rfl⟩
@[simp]
theorem range_re : range re = univ :=
re_surjective.range_eq
@[simp]
theorem range_im : range im = univ :=
im_surjective.range_eq
/-- The natural inclusion of the real numbers into the complex numbers. -/
@[coe]
def ofReal (r : ℝ) : ℂ :=
⟨r, 0⟩
instance : Coe ℝ ℂ :=
⟨ofReal⟩
@[simp, norm_cast]
theorem ofReal_re (r : ℝ) : Complex.re (r : ℂ) = r :=
rfl
@[simp, norm_cast]
theorem ofReal_im (r : ℝ) : (r : ℂ).im = 0 :=
rfl
theorem ofReal_def (r : ℝ) : (r : ℂ) = ⟨r, 0⟩ :=
rfl
@[simp, norm_cast]
theorem ofReal_inj {z w : ℝ} : (z : ℂ) = w ↔ z = w :=
⟨congrArg re, by apply congrArg⟩
theorem ofReal_injective : Function.Injective ((↑) : ℝ → ℂ) := fun _ _ => congrArg re
instance canLift : CanLift ℂ ℝ (↑) fun z => z.im = 0 where
prf z hz := ⟨z.re, ext rfl hz.symm⟩
/-- The product of a set on the real axis and a set on the imaginary axis of the complex plane,
denoted by `s ×ℂ t`. -/
def reProdIm (s t : Set ℝ) : Set ℂ :=
re ⁻¹' s ∩ im ⁻¹' t
@[deprecated (since := "2024-12-03")] protected alias Set.reProdIm := reProdIm
@[inherit_doc]
infixl:72 " ×ℂ " => reProdIm
theorem mem_reProdIm {z : ℂ} {s t : Set ℝ} : z ∈ s ×ℂ t ↔ z.re ∈ s ∧ z.im ∈ t :=
Iff.rfl
instance : Zero ℂ :=
⟨(0 : ℝ)⟩
instance : Inhabited ℂ :=
⟨0⟩
@[simp]
theorem zero_re : (0 : ℂ).re = 0 :=
rfl
@[simp]
theorem zero_im : (0 : ℂ).im = 0 :=
rfl
@[simp, norm_cast]
theorem ofReal_zero : ((0 : ℝ) : ℂ) = 0 :=
rfl
@[simp]
theorem ofReal_eq_zero {z : ℝ} : (z : ℂ) = 0 ↔ z = 0 :=
ofReal_inj
theorem ofReal_ne_zero {z : ℝ} : (z : ℂ) ≠ 0 ↔ z ≠ 0 :=
not_congr ofReal_eq_zero
instance : One ℂ :=
⟨(1 : ℝ)⟩
@[simp]
theorem one_re : (1 : ℂ).re = 1 :=
rfl
@[simp]
theorem one_im : (1 : ℂ).im = 0 :=
rfl
@[simp, norm_cast]
theorem ofReal_one : ((1 : ℝ) : ℂ) = 1 :=
rfl
@[simp]
theorem ofReal_eq_one {z : ℝ} : (z : ℂ) = 1 ↔ z = 1 :=
ofReal_inj
theorem ofReal_ne_one {z : ℝ} : (z : ℂ) ≠ 1 ↔ z ≠ 1 :=
not_congr ofReal_eq_one
instance : Add ℂ :=
⟨fun z w => ⟨z.re + w.re, z.im + w.im⟩⟩
@[simp]
theorem add_re (z w : ℂ) : (z + w).re = z.re + w.re :=
rfl
@[simp]
theorem add_im (z w : ℂ) : (z + w).im = z.im + w.im :=
rfl
-- replaced by `re_ofNat`
-- replaced by `im_ofNat`
@[simp, norm_cast]
theorem ofReal_add (r s : ℝ) : ((r + s : ℝ) : ℂ) = r + s :=
Complex.ext_iff.2 <| by simp [ofReal]
-- replaced by `Complex.ofReal_ofNat`
instance : Neg ℂ :=
⟨fun z => ⟨-z.re, -z.im⟩⟩
@[simp]
theorem neg_re (z : ℂ) : (-z).re = -z.re :=
rfl
@[simp]
theorem neg_im (z : ℂ) : (-z).im = -z.im :=
rfl
@[simp, norm_cast]
theorem ofReal_neg (r : ℝ) : ((-r : ℝ) : ℂ) = -r :=
Complex.ext_iff.2 <| by simp [ofReal]
instance : Sub ℂ :=
⟨fun z w => ⟨z.re - w.re, z.im - w.im⟩⟩
instance : Mul ℂ :=
⟨fun z w => ⟨z.re * w.re - z.im * w.im, z.re * w.im + z.im * w.re⟩⟩
@[simp]
theorem mul_re (z w : ℂ) : (z * w).re = z.re * w.re - z.im * w.im :=
rfl
@[simp]
theorem mul_im (z w : ℂ) : (z * w).im = z.re * w.im + z.im * w.re :=
rfl
@[simp, norm_cast]
theorem ofReal_mul (r s : ℝ) : ((r * s : ℝ) : ℂ) = r * s :=
Complex.ext_iff.2 <| by simp [ofReal]
theorem re_ofReal_mul (r : ℝ) (z : ℂ) : (r * z).re = r * z.re := by simp [ofReal]
theorem im_ofReal_mul (r : ℝ) (z : ℂ) : (r * z).im = r * z.im := by simp [ofReal]
lemma re_mul_ofReal (z : ℂ) (r : ℝ) : (z * r).re = z.re * r := by simp [ofReal]
lemma im_mul_ofReal (z : ℂ) (r : ℝ) : (z * r).im = z.im * r := by simp [ofReal]
theorem ofReal_mul' (r : ℝ) (z : ℂ) : ↑r * z = ⟨r * z.re, r * z.im⟩ :=
ext (re_ofReal_mul _ _) (im_ofReal_mul _ _)
/-! ### The imaginary unit, `I` -/
/-- The imaginary unit. -/
def I : ℂ :=
⟨0, 1⟩
@[simp]
theorem I_re : I.re = 0 :=
rfl
@[simp]
theorem I_im : I.im = 1 :=
rfl
@[simp]
theorem I_mul_I : I * I = -1 :=
Complex.ext_iff.2 <| by simp
theorem I_mul (z : ℂ) : I * z = ⟨-z.im, z.re⟩ :=
Complex.ext_iff.2 <| by simp
@[simp] lemma I_ne_zero : (I : ℂ) ≠ 0 := mt (congr_arg im) zero_ne_one.symm
theorem mk_eq_add_mul_I (a b : ℝ) : Complex.mk a b = a + b * I :=
Complex.ext_iff.2 <| by simp [ofReal]
@[simp]
theorem re_add_im (z : ℂ) : (z.re : ℂ) + z.im * I = z :=
Complex.ext_iff.2 <| by simp [ofReal]
theorem mul_I_re (z : ℂ) : (z * I).re = -z.im := by simp
theorem mul_I_im (z : ℂ) : (z * I).im = z.re := by simp
theorem I_mul_re (z : ℂ) : (I * z).re = -z.im := by simp
theorem I_mul_im (z : ℂ) : (I * z).im = z.re := by simp
@[simp]
theorem equivRealProd_symm_apply (p : ℝ × ℝ) : equivRealProd.symm p = p.1 + p.2 * I := by
ext <;> simp [Complex.equivRealProd, ofReal]
/-- The natural `AddEquiv` from `ℂ` to `ℝ × ℝ`. -/
@[simps! +simpRhs apply symm_apply_re symm_apply_im]
def equivRealProdAddHom : ℂ ≃+ ℝ × ℝ :=
{ equivRealProd with map_add' := by simp }
theorem equivRealProdAddHom_symm_apply (p : ℝ × ℝ) :
equivRealProdAddHom.symm p = p.1 + p.2 * I := equivRealProd_symm_apply p
/-! ### Commutative ring instance and lemmas -/
/- We use a nonstandard formula for the `ℕ` and `ℤ` actions to make sure there is no
diamond from the other actions they inherit through the `ℝ`-action on `ℂ` and action transitivity
defined in `Data.Complex.Module`. -/
instance : Nontrivial ℂ :=
domain_nontrivial re rfl rfl
namespace SMul
-- The useless `0` multiplication in `smul` is to make sure that
-- `RestrictScalars.module ℝ ℂ ℂ = Complex.module` definitionally.
-- instance made scoped to avoid situations like instance synthesis
-- of `SMul ℂ ℂ` trying to proceed via `SMul ℂ ℝ`.
/-- Scalar multiplication by `R` on `ℝ` extends to `ℂ`. This is used here and in
`Matlib.Data.Complex.Module` to transfer instances from `ℝ` to `ℂ`, but is not
needed outside, so we make it scoped. -/
scoped instance instSMulRealComplex {R : Type*} [SMul R ℝ] : SMul R ℂ where
smul r x := ⟨r • x.re - 0 * x.im, r • x.im + 0 * x.re⟩
end SMul
open scoped SMul
section SMul
variable {R : Type*} [SMul R ℝ]
theorem smul_re (r : R) (z : ℂ) : (r • z).re = r • z.re := by simp [(· • ·), SMul.smul]
theorem smul_im (r : R) (z : ℂ) : (r • z).im = r • z.im := by simp [(· • ·), SMul.smul]
@[simp]
theorem real_smul {x : ℝ} {z : ℂ} : x • z = x * z :=
rfl
end SMul
instance addCommGroup : AddCommGroup ℂ :=
{ zero := (0 : ℂ)
add := (· + ·)
neg := Neg.neg
sub := Sub.sub
nsmul := fun n z => n • z
zsmul := fun n z => n • z
zsmul_zero' := by intros; ext <;> simp [smul_re, smul_im]
nsmul_zero := by intros; ext <;> simp [smul_re, smul_im]
nsmul_succ := by intros; ext <;> simp [smul_re, smul_im] <;> ring
zsmul_succ' := by intros; ext <;> simp [smul_re, smul_im] <;> ring
zsmul_neg' := by intros; ext <;> simp [smul_re, smul_im] <;> ring
add_assoc := by intros; ext <;> simp <;> ring
zero_add := by intros; ext <;> simp
add_zero := by intros; ext <;> simp
add_comm := by intros; ext <;> simp <;> ring
neg_add_cancel := by intros; ext <;> simp }
instance addGroupWithOne : AddGroupWithOne ℂ :=
{ Complex.addCommGroup with
natCast := fun n => ⟨n, 0⟩
natCast_zero := by
ext <;> simp [Nat.cast, AddMonoidWithOne.natCast_zero]
natCast_succ := fun _ => by ext <;> simp [Nat.cast, AddMonoidWithOne.natCast_succ]
intCast := fun n => ⟨n, 0⟩
intCast_ofNat := fun _ => by ext <;> rfl
intCast_negSucc := fun n => by
ext
· simp [AddGroupWithOne.intCast_negSucc]
show -(1 : ℝ) + (-n) = -(↑(n + 1))
simp [Nat.cast_add, add_comm]
· simp [AddGroupWithOne.intCast_negSucc]
show im ⟨n, 0⟩ = 0
rfl
one := 1 }
instance commRing : CommRing ℂ :=
{ addGroupWithOne with
mul := (· * ·)
npow := @npowRec _ ⟨(1 : ℂ)⟩ ⟨(· * ·)⟩
add_comm := by intros; ext <;> simp <;> ring
left_distrib := by intros; ext <;> simp [mul_re, mul_im] <;> ring
right_distrib := by intros; ext <;> simp [mul_re, mul_im] <;> ring
zero_mul := by intros; ext <;> simp
mul_zero := by intros; ext <;> simp
mul_assoc := by intros; ext <;> simp <;> ring
one_mul := by intros; ext <;> simp
mul_one := by intros; ext <;> simp
mul_comm := by intros; ext <;> simp <;> ring }
/-- This shortcut instance ensures we do not find `Ring` via the noncomputable `Complex.field`
instance. -/
instance : Ring ℂ := by infer_instance
/-- This shortcut instance ensures we do not find `CommSemiring` via the noncomputable
`Complex.field` instance. -/
instance : CommSemiring ℂ :=
inferInstance
/-- This shortcut instance ensures we do not find `Semiring` via the noncomputable
`Complex.field` instance. -/
instance : Semiring ℂ :=
inferInstance
/-- The "real part" map, considered as an additive group homomorphism. -/
def reAddGroupHom : ℂ →+ ℝ where
toFun := re
map_zero' := zero_re
map_add' := add_re
@[simp]
theorem coe_reAddGroupHom : (reAddGroupHom : ℂ → ℝ) = re :=
rfl
/-- The "imaginary part" map, considered as an additive group homomorphism. -/
def imAddGroupHom : ℂ →+ ℝ where
toFun := im
map_zero' := zero_im
map_add' := add_im
@[simp]
theorem coe_imAddGroupHom : (imAddGroupHom : ℂ → ℝ) = im :=
rfl
/-! ### Cast lemmas -/
instance instNNRatCast : NNRatCast ℂ where nnratCast q := ofReal q
instance instRatCast : RatCast ℂ where ratCast q := ofReal q
@[simp, norm_cast] lemma ofReal_ofNat (n : ℕ) [n.AtLeastTwo] : ofReal ofNat(n) = ofNat(n) := rfl
@[simp, norm_cast] lemma ofReal_natCast (n : ℕ) : ofReal n = n := rfl
@[simp, norm_cast] lemma ofReal_intCast (n : ℤ) : ofReal n = n := rfl
@[simp, norm_cast] lemma ofReal_nnratCast (q : ℚ≥0) : ofReal q = q := rfl
@[simp, norm_cast] lemma ofReal_ratCast (q : ℚ) : ofReal q = q := rfl
@[simp]
lemma re_ofNat (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℂ).re = ofNat(n) := rfl
@[simp] lemma im_ofNat (n : ℕ) [n.AtLeastTwo] : (ofNat(n) : ℂ).im = 0 := rfl
@[simp, norm_cast] lemma natCast_re (n : ℕ) : (n : ℂ).re = n := rfl
@[simp, norm_cast] lemma natCast_im (n : ℕ) : (n : ℂ).im = 0 := rfl
@[simp, norm_cast] lemma intCast_re (n : ℤ) : (n : ℂ).re = n := rfl
@[simp, norm_cast] lemma intCast_im (n : ℤ) : (n : ℂ).im = 0 := rfl
@[simp, norm_cast] lemma re_nnratCast (q : ℚ≥0) : (q : ℂ).re = q := rfl
@[simp, norm_cast] lemma im_nnratCast (q : ℚ≥0) : (q : ℂ).im = 0 := rfl
@[simp, norm_cast] lemma ratCast_re (q : ℚ) : (q : ℂ).re = q := rfl
@[simp, norm_cast] lemma ratCast_im (q : ℚ) : (q : ℂ).im = 0 := rfl
lemma re_nsmul (n : ℕ) (z : ℂ) : (n • z).re = n • z.re := smul_re ..
lemma im_nsmul (n : ℕ) (z : ℂ) : (n • z).im = n • z.im := smul_im ..
lemma re_zsmul (n : ℤ) (z : ℂ) : (n • z).re = n • z.re := smul_re ..
lemma im_zsmul (n : ℤ) (z : ℂ) : (n • z).im = n • z.im := smul_im ..
@[simp] lemma re_nnqsmul (q : ℚ≥0) (z : ℂ) : (q • z).re = q • z.re := smul_re ..
@[simp] lemma im_nnqsmul (q : ℚ≥0) (z : ℂ) : (q • z).im = q • z.im := smul_im ..
@[simp] lemma re_qsmul (q : ℚ) (z : ℂ) : (q • z).re = q • z.re := smul_re ..
@[simp] lemma im_qsmul (q : ℚ) (z : ℂ) : (q • z).im = q • z.im := smul_im ..
@[norm_cast] lemma ofReal_nsmul (n : ℕ) (r : ℝ) : ↑(n • r) = n • (r : ℂ) := by simp
@[norm_cast] lemma ofReal_zsmul (n : ℤ) (r : ℝ) : ↑(n • r) = n • (r : ℂ) := by simp
/-! ### Complex conjugation -/
/-- This defines the complex conjugate as the `star` operation of the `StarRing ℂ`. It
is recommended to use the ring endomorphism version `starRingEnd`, available under the
notation `conj` in the locale `ComplexConjugate`. -/
instance : StarRing ℂ where
star z := ⟨z.re, -z.im⟩
star_involutive x := by simp only [eta, neg_neg]
star_mul a b := by ext <;> simp [add_comm] <;> ring
star_add a b := by ext <;> simp [add_comm]
@[simp]
theorem conj_re (z : ℂ) : (conj z).re = z.re :=
rfl
@[simp]
theorem conj_im (z : ℂ) : (conj z).im = -z.im :=
rfl
@[simp]
theorem conj_ofReal (r : ℝ) : conj (r : ℂ) = r :=
Complex.ext_iff.2 <| by simp [star]
@[simp]
theorem conj_I : conj I = -I :=
Complex.ext_iff.2 <| by simp
theorem conj_natCast (n : ℕ) : conj (n : ℂ) = n := map_natCast _ _
theorem conj_ofNat (n : ℕ) [n.AtLeastTwo] : conj (ofNat(n) : ℂ) = ofNat(n) :=
map_ofNat _ _
theorem conj_neg_I : conj (-I) = I := by simp
theorem conj_eq_iff_real {z : ℂ} : conj z = z ↔ ∃ r : ℝ, z = r :=
⟨fun h => ⟨z.re, ext rfl <| eq_zero_of_neg_eq (congr_arg im h)⟩, fun ⟨h, e⟩ => by
rw [e, conj_ofReal]⟩
theorem conj_eq_iff_re {z : ℂ} : conj z = z ↔ (z.re : ℂ) = z :=
conj_eq_iff_real.trans ⟨by rintro ⟨r, rfl⟩; simp [ofReal], fun h => ⟨_, h.symm⟩⟩
theorem conj_eq_iff_im {z : ℂ} : conj z = z ↔ z.im = 0 :=
⟨fun h => add_self_eq_zero.mp (neg_eq_iff_add_eq_zero.mp (congr_arg im h)), fun h =>
ext rfl (neg_eq_iff_add_eq_zero.mpr (add_self_eq_zero.mpr h))⟩
@[simp]
theorem star_def : (Star.star : ℂ → ℂ) = conj :=
rfl
/-! ### Norm squared -/
/-- The norm squared function. -/
@[pp_nodot]
def normSq : ℂ →*₀ ℝ where
toFun z := z.re * z.re + z.im * z.im
map_zero' := by simp
map_one' := by simp
map_mul' z w := by
dsimp
ring
theorem normSq_apply (z : ℂ) : normSq z = z.re * z.re + z.im * z.im :=
rfl
@[simp]
theorem normSq_ofReal (r : ℝ) : normSq r = r * r := by
simp [normSq, ofReal]
@[simp]
theorem normSq_natCast (n : ℕ) : normSq n = n * n := normSq_ofReal _
@[simp]
theorem normSq_intCast (z : ℤ) : normSq z = z * z := normSq_ofReal _
@[simp]
theorem normSq_ratCast (q : ℚ) : normSq q = q * q := normSq_ofReal _
@[simp]
theorem normSq_ofNat (n : ℕ) [n.AtLeastTwo] :
normSq (ofNat(n) : ℂ) = ofNat(n) * ofNat(n) :=
normSq_natCast _
@[simp]
theorem normSq_mk (x y : ℝ) : normSq ⟨x, y⟩ = x * x + y * y :=
rfl
theorem normSq_add_mul_I (x y : ℝ) : normSq (x + y * I) = x ^ 2 + y ^ 2 := by
rw [← mk_eq_add_mul_I, normSq_mk, sq, sq]
theorem normSq_eq_conj_mul_self {z : ℂ} : (normSq z : ℂ) = conj z * z := by
ext <;> simp [normSq, mul_comm, ofReal]
theorem normSq_zero : normSq 0 = 0 := by simp
theorem normSq_one : normSq 1 = 1 := by simp
@[simp]
theorem normSq_I : normSq I = 1 := by simp [normSq]
theorem normSq_nonneg (z : ℂ) : 0 ≤ normSq z :=
add_nonneg (mul_self_nonneg _) (mul_self_nonneg _)
theorem normSq_eq_zero {z : ℂ} : normSq z = 0 ↔ z = 0 :=
⟨fun h =>
ext (eq_zero_of_mul_self_add_mul_self_eq_zero h)
(eq_zero_of_mul_self_add_mul_self_eq_zero <| (add_comm _ _).trans h),
fun h => h.symm ▸ normSq_zero⟩
@[simp]
theorem normSq_pos {z : ℂ} : 0 < normSq z ↔ z ≠ 0 :=
(normSq_nonneg z).lt_iff_ne.trans <| not_congr (eq_comm.trans normSq_eq_zero)
@[simp]
theorem normSq_neg (z : ℂ) : normSq (-z) = normSq z := by simp [normSq]
@[simp]
theorem normSq_conj (z : ℂ) : normSq (conj z) = normSq z := by simp [normSq]
theorem normSq_mul (z w : ℂ) : normSq (z * w) = normSq z * normSq w :=
normSq.map_mul z w
theorem normSq_add (z w : ℂ) : normSq (z + w) = normSq z + normSq w + 2 * (z * conj w).re := by
dsimp [normSq]; ring
theorem re_sq_le_normSq (z : ℂ) : z.re * z.re ≤ normSq z :=
le_add_of_nonneg_right (mul_self_nonneg _)
theorem im_sq_le_normSq (z : ℂ) : z.im * z.im ≤ normSq z :=
le_add_of_nonneg_left (mul_self_nonneg _)
theorem mul_conj (z : ℂ) : z * conj z = normSq z :=
Complex.ext_iff.2 <| by simp [normSq, mul_comm, sub_eq_neg_add, add_comm, ofReal]
theorem add_conj (z : ℂ) : z + conj z = (2 * z.re : ℝ) :=
Complex.ext_iff.2 <| by simp [two_mul, ofReal]
/-- The coercion `ℝ → ℂ` as a `RingHom`. -/
def ofRealHom : ℝ →+* ℂ where
toFun x := (x : ℂ)
map_one' := ofReal_one
map_zero' := ofReal_zero
map_mul' := ofReal_mul
map_add' := ofReal_add
@[simp] lemma ofRealHom_eq_coe (r : ℝ) : ofRealHom r = r := rfl
variable {α : Type*}
@[simp] lemma ofReal_comp_add (f g : α → ℝ) : ofReal ∘ (f + g) = ofReal ∘ f + ofReal ∘ g :=
map_comp_add ofRealHom ..
@[simp] lemma ofReal_comp_sub (f g : α → ℝ) : ofReal ∘ (f - g) = ofReal ∘ f - ofReal ∘ g :=
map_comp_sub ofRealHom ..
@[simp] lemma ofReal_comp_neg (f : α → ℝ) : ofReal ∘ (-f) = -(ofReal ∘ f) :=
map_comp_neg ofRealHom _
lemma ofReal_comp_nsmul (n : ℕ) (f : α → ℝ) : ofReal ∘ (n • f) = n • (ofReal ∘ f) :=
map_comp_nsmul ofRealHom ..
lemma ofReal_comp_zsmul (n : ℤ) (f : α → ℝ) : ofReal ∘ (n • f) = n • (ofReal ∘ f) :=
map_comp_zsmul ofRealHom ..
@[simp] lemma ofReal_comp_mul (f g : α → ℝ) : ofReal ∘ (f * g) = ofReal ∘ f * ofReal ∘ g :=
map_comp_mul ofRealHom ..
@[simp] lemma ofReal_comp_pow (f : α → ℝ) (n : ℕ) : ofReal ∘ (f ^ n) = (ofReal ∘ f) ^ n :=
map_comp_pow ofRealHom ..
@[simp]
theorem I_sq : I ^ 2 = -1 := by rw [sq, I_mul_I]
@[simp]
lemma I_pow_three : I ^ 3 = -I := by rw [pow_succ, I_sq, neg_one_mul]
@[simp]
theorem I_pow_four : I ^ 4 = 1 := by rw [(by norm_num : 4 = 2 * 2), pow_mul, I_sq, neg_one_sq]
lemma I_pow_eq_pow_mod (n : ℕ) : I ^ n = I ^ (n % 4) := by
conv_lhs => rw [← Nat.div_add_mod n 4]
simp [pow_add, pow_mul, I_pow_four]
@[simp]
theorem sub_re (z w : ℂ) : (z - w).re = z.re - w.re :=
rfl
@[simp]
theorem sub_im (z w : ℂ) : (z - w).im = z.im - w.im :=
rfl
@[simp, norm_cast]
theorem ofReal_sub (r s : ℝ) : ((r - s : ℝ) : ℂ) = r - s :=
Complex.ext_iff.2 <| by simp [ofReal]
@[simp, norm_cast]
theorem ofReal_pow (r : ℝ) (n : ℕ) : ((r ^ n : ℝ) : ℂ) = (r : ℂ) ^ n := by
induction n <;> simp [*, ofReal_mul, pow_succ]
theorem sub_conj (z : ℂ) : z - conj z = (2 * z.im : ℝ) * I :=
Complex.ext_iff.2 <| by simp [two_mul, sub_eq_add_neg, ofReal]
theorem normSq_sub (z w : ℂ) : normSq (z - w) = normSq z + normSq w - 2 * (z * conj w).re := by
rw [sub_eq_add_neg, normSq_add]
simp only [RingHom.map_neg, mul_neg, neg_re, normSq_neg]
ring
/-! ### Inversion -/
noncomputable instance : Inv ℂ :=
⟨fun z => conj z * ((normSq z)⁻¹ : ℝ)⟩
theorem inv_def (z : ℂ) : z⁻¹ = conj z * ((normSq z)⁻¹ : ℝ) :=
rfl
@[simp]
theorem inv_re (z : ℂ) : z⁻¹.re = z.re / normSq z := by simp [inv_def, division_def, ofReal]
@[simp]
theorem inv_im (z : ℂ) : z⁻¹.im = -z.im / normSq z := by simp [inv_def, division_def, ofReal]
@[simp, norm_cast]
theorem ofReal_inv (r : ℝ) : ((r⁻¹ : ℝ) : ℂ) = (r : ℂ)⁻¹ :=
Complex.ext_iff.2 <| by simp [ofReal]
protected theorem inv_zero : (0⁻¹ : ℂ) = 0 := by
rw [← ofReal_zero, ← ofReal_inv, inv_zero]
protected theorem mul_inv_cancel {z : ℂ} (h : z ≠ 0) : z * z⁻¹ = 1 := by
rw [inv_def, ← mul_assoc, mul_conj, ← ofReal_mul, mul_inv_cancel₀ (mt normSq_eq_zero.1 h),
ofReal_one]
noncomputable instance instDivInvMonoid : DivInvMonoid ℂ where
lemma div_re (z w : ℂ) : (z / w).re = z.re * w.re / normSq w + z.im * w.im / normSq w := by
simp [div_eq_mul_inv, mul_assoc, sub_eq_add_neg]
lemma div_im (z w : ℂ) : (z / w).im = z.im * w.re / normSq w - z.re * w.im / normSq w := by
simp [div_eq_mul_inv, mul_assoc, sub_eq_add_neg, add_comm]
|
/-! ### Field instance and lemmas -/
| Mathlib/Data/Complex/Basic.lean | 677 | 678 |
/-
Copyright (c) 2019 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Algebra.Bilinear
import Mathlib.Algebra.Algebra.Opposite
import Mathlib.Algebra.Group.Pointwise.Finset.Basic
import Mathlib.Algebra.Group.Pointwise.Set.BigOperators
import Mathlib.Algebra.Module.Submodule.Pointwise
import Mathlib.Algebra.Ring.NonZeroDivisors
import Mathlib.Algebra.Ring.Submonoid.Pointwise
import Mathlib.Data.Set.Semiring
import Mathlib.GroupTheory.GroupAction.SubMulAction.Pointwise
/-!
# Multiplication and division of submodules of an algebra.
An interface for multiplication and division of sub-R-modules of an R-algebra A is developed.
## Main definitions
Let `R` be a commutative ring (or semiring) and let `A` be an `R`-algebra.
* `1 : Submodule R A` : the R-submodule R of the R-algebra A
* `Mul (Submodule R A)` : multiplication of two sub-R-modules M and N of A is defined to be
the smallest submodule containing all the products `m * n`.
* `Div (Submodule R A)` : `I / J` is defined to be the submodule consisting of all `a : A` such
that `a • J ⊆ I`
It is proved that `Submodule R A` is a semiring, and also an algebra over `Set A`.
Additionally, in the `Pointwise` locale we promote `Submodule.pointwiseDistribMulAction` to a
`MulSemiringAction` as `Submodule.pointwiseMulSemiringAction`.
When `R` is not necessarily commutative, and `A` is merely a `R`-module with a ring structure
such that `IsScalarTower R A A` holds (equivalent to the data of a ring homomorphism `R →+* A`
by `ringHomEquivModuleIsScalarTower`), we can still define `1 : Submodule R A` and
`Mul (Submodule R A)`, but `1` is only a left identity, not necessarily a right one.
## Tags
multiplication of submodules, division of submodules, submodule semiring
-/
universe uι u v
open Algebra Set MulOpposite
open Pointwise
namespace SubMulAction
variable {R : Type u} {A : Type v} [CommSemiring R] [Semiring A] [Algebra R A]
theorem algebraMap_mem (r : R) : algebraMap R A r ∈ (1 : SubMulAction R A) :=
⟨r, (algebraMap_eq_smul_one r).symm⟩
theorem mem_one' {x : A} : x ∈ (1 : SubMulAction R A) ↔ ∃ y, algebraMap R A y = x :=
exists_congr fun r => by rw [algebraMap_eq_smul_one]
end SubMulAction
namespace Submodule
section Module
variable {R : Type u} [Semiring R] {A : Type v} [Semiring A] [Module R A]
-- TODO: Why is this in a file about `Algebra`?
-- TODO: potentially change this back to `LinearMap.range (Algebra.linearMap R A)`
-- once a version of `Algebra` without the `commutes'` field is introduced.
-- See issue https://github.com/leanprover-community/mathlib4/issues/18110.
/-- `1 : Submodule R A` is the submodule `R ∙ 1` of `A`.
-/
instance one : One (Submodule R A) :=
⟨LinearMap.range (LinearMap.toSpanSingleton R A 1)⟩
theorem one_eq_span : (1 : Submodule R A) = R ∙ 1 :=
(LinearMap.span_singleton_eq_range _ _ _).symm
theorem le_one_toAddSubmonoid : 1 ≤ (1 : Submodule R A).toAddSubmonoid := by
rintro x ⟨n, rfl⟩
exact ⟨n, show (n : R) • (1 : A) = n by rw [Nat.cast_smul_eq_nsmul, nsmul_one]⟩
@[simp]
theorem toSubMulAction_one : (1 : Submodule R A).toSubMulAction = 1 :=
SetLike.ext fun _ ↦ by rw [one_eq_span, SubMulAction.mem_one]; exact mem_span_singleton
theorem one_eq_span_one_set : (1 : Submodule R A) = span R 1 :=
one_eq_span
@[simp]
theorem one_le {P : Submodule R A} : (1 : Submodule R A) ≤ P ↔ (1 : A) ∈ P := by
simp [one_eq_span]
variable {M : Type*} [AddCommMonoid M] [Module R M] [Module A M] [IsScalarTower R A M]
instance : SMul (Submodule R A) (Submodule R M) where
smul A' M' :=
{ __ := A'.toAddSubmonoid • M'.toAddSubmonoid
smul_mem' := fun r m hm ↦ AddSubmonoid.smul_induction_on hm
(fun a ha m hm ↦ by rw [← smul_assoc]; exact AddSubmonoid.smul_mem_smul (A'.smul_mem r ha) hm)
fun m₁ m₂ h₁ h₂ ↦ by rw [smul_add]; exact (A'.1 • M'.1).add_mem h₁ h₂ }
section
variable {I J : Submodule R A} {N P : Submodule R M}
theorem smul_toAddSubmonoid : (I • N).toAddSubmonoid = I.toAddSubmonoid • N.toAddSubmonoid := rfl
theorem smul_mem_smul {r} {n} (hr : r ∈ I) (hn : n ∈ N) : r • n ∈ I • N :=
AddSubmonoid.smul_mem_smul hr hn
theorem smul_le : I • N ≤ P ↔ ∀ r ∈ I, ∀ n ∈ N, r • n ∈ P :=
AddSubmonoid.smul_le
@[simp, norm_cast]
lemma coe_set_smul : (I : Set A) • N = I • N :=
set_smul_eq_of_le _ _ _
(fun _ _ hr hx ↦ smul_mem_smul hr hx)
(smul_le.mpr fun _ hr _ hx ↦ mem_set_smul_of_mem_mem hr hx)
@[elab_as_elim]
theorem smul_induction_on {p : M → Prop} {x} (H : x ∈ I • N) (smul : ∀ r ∈ I, ∀ n ∈ N, p (r • n))
(add : ∀ x y, p x → p y → p (x + y)) : p x :=
AddSubmonoid.smul_induction_on H smul add
/-- Dependent version of `Submodule.smul_induction_on`. -/
@[elab_as_elim]
theorem smul_induction_on' {x : M} (hx : x ∈ I • N) {p : ∀ x, x ∈ I • N → Prop}
(smul : ∀ (r : A) (hr : r ∈ I) (n : M) (hn : n ∈ N), p (r • n) (smul_mem_smul hr hn))
(add : ∀ x hx y hy, p x hx → p y hy → p (x + y) (add_mem ‹_› ‹_›)) : p x hx := by
refine Exists.elim ?_ fun (h : x ∈ I • N) (H : p x h) ↦ H
exact smul_induction_on hx (fun a ha x hx ↦ ⟨_, smul _ ha _ hx⟩)
fun x y ⟨_, hx⟩ ⟨_, hy⟩ ↦ ⟨_, add _ _ _ _ hx hy⟩
theorem smul_mono (hij : I ≤ J) (hnp : N ≤ P) : I • N ≤ J • P :=
AddSubmonoid.smul_le_smul hij hnp
theorem smul_mono_left (h : I ≤ J) : I • N ≤ J • N :=
smul_mono h le_rfl
instance : CovariantClass (Submodule R A) (Submodule R M) HSMul.hSMul LE.le :=
⟨fun _ _ => smul_mono le_rfl⟩
variable (I J N P)
@[simp]
theorem smul_bot : I • (⊥ : Submodule R M) = ⊥ :=
toAddSubmonoid_injective <| AddSubmonoid.addSubmonoid_smul_bot _
@[simp]
theorem bot_smul : (⊥ : Submodule R A) • N = ⊥ :=
le_bot_iff.mp <| smul_le.mpr <| by rintro _ rfl _ _; rw [zero_smul]; exact zero_mem _
theorem smul_sup : I • (N ⊔ P) = I • N ⊔ I • P :=
toAddSubmonoid_injective <| by
simp only [smul_toAddSubmonoid, sup_toAddSubmonoid, AddSubmonoid.addSubmonoid_smul_sup]
theorem sup_smul : (I ⊔ J) • N = I • N ⊔ J • N :=
le_antisymm (smul_le.mpr fun mn hmn p hp ↦ by
obtain ⟨m, hm, n, hn, rfl⟩ := mem_sup.mp hmn
rw [add_smul]; exact add_mem_sup (smul_mem_smul hm hp) <| smul_mem_smul hn hp)
(sup_le (smul_mono_left le_sup_left) <| smul_mono_left le_sup_right)
protected theorem smul_assoc {B} [Semiring B] [Module R B] [Module A B] [Module B M]
[IsScalarTower R A B] [IsScalarTower R B M] [IsScalarTower A B M]
(I : Submodule R A) (J : Submodule R B) (N : Submodule R M) :
(I • J) • N = I • J • N :=
le_antisymm
(smul_le.2 fun _ hrsij t htn ↦ smul_induction_on hrsij
(fun r hr s hs ↦ smul_assoc r s t ▸ smul_mem_smul hr (smul_mem_smul hs htn))
fun x y ↦ (add_smul x y t).symm ▸ add_mem)
(smul_le.2 fun r hr _ hsn ↦ smul_induction_on hsn
(fun j hj n hn ↦ (smul_assoc r j n).symm ▸ smul_mem_smul (smul_mem_smul hr hj) hn)
fun m₁ m₂ ↦ (smul_add r m₁ m₂) ▸ add_mem)
theorem smul_iSup {ι : Sort*} {I : Submodule R A} {t : ι → Submodule R M} :
I • (⨆ i, t i)= ⨆ i, I • t i :=
toAddSubmonoid_injective <| by
simp only [smul_toAddSubmonoid, iSup_toAddSubmonoid, AddSubmonoid.smul_iSup]
theorem iSup_smul {ι : Sort*} {t : ι → Submodule R A} {N : Submodule R M} :
(⨆ i, t i) • N = ⨆ i, t i • N :=
le_antisymm (smul_le.mpr fun t ht s hs ↦ iSup_induction _ (motive := (· • s ∈ _)) ht
(fun i t ht ↦ mem_iSup_of_mem i <| smul_mem_smul ht hs)
(by simp_rw [zero_smul]; apply zero_mem) fun x y ↦ by simp_rw [add_smul]; apply add_mem)
(iSup_le fun i ↦ Submodule.smul_mono_left <| le_iSup _ i)
protected theorem one_smul : (1 : Submodule R A) • N = N := by
refine le_antisymm (smul_le.mpr fun r hr m hm ↦ ?_) fun m hm ↦ ?_
· obtain ⟨r, rfl⟩ := hr
rw [LinearMap.toSpanSingleton_apply, smul_one_smul]; exact N.smul_mem r hm
· rw [← one_smul A m]; exact smul_mem_smul (one_le.mp le_rfl) hm
theorem smul_subset_smul : (↑I : Set A) • (↑N : Set M) ⊆ (↑(I • N) : Set M) :=
AddSubmonoid.smul_subset_smul
end
variable [IsScalarTower R A A]
/-- Multiplication of sub-R-modules of an R-module A that is also a semiring. The submodule `M * N`
consists of finite sums of elements `m * n` for `m ∈ M` and `n ∈ N`. -/
instance mul : Mul (Submodule R A) where
mul := (· • ·)
variable (S T : Set A) {M N P Q : Submodule R A} {m n : A}
theorem mul_mem_mul (hm : m ∈ M) (hn : n ∈ N) : m * n ∈ M * N :=
smul_mem_smul hm hn
theorem mul_le : M * N ≤ P ↔ ∀ m ∈ M, ∀ n ∈ N, m * n ∈ P :=
smul_le
theorem mul_toAddSubmonoid (M N : Submodule R A) :
(M * N).toAddSubmonoid = M.toAddSubmonoid * N.toAddSubmonoid := rfl
@[elab_as_elim]
protected theorem mul_induction_on {C : A → Prop} {r : A} (hr : r ∈ M * N)
(hm : ∀ m ∈ M, ∀ n ∈ N, C (m * n)) (ha : ∀ x y, C x → C y → C (x + y)) : C r :=
smul_induction_on hr hm ha
/-- A dependent version of `mul_induction_on`. -/
@[elab_as_elim]
protected theorem mul_induction_on' {C : ∀ r, r ∈ M * N → Prop}
(mem_mul_mem : ∀ m (hm : m ∈ M) n (hn : n ∈ N), C (m * n) (mul_mem_mul hm hn))
(add : ∀ x hx y hy, C x hx → C y hy → C (x + y) (add_mem hx hy)) {r : A} (hr : r ∈ M * N) :
C r hr :=
smul_induction_on' hr mem_mul_mem add
variable (M)
@[simp]
theorem mul_bot : M * ⊥ = ⊥ :=
smul_bot _
@[simp]
theorem bot_mul : ⊥ * M = ⊥ :=
bot_smul _
protected theorem one_mul : (1 : Submodule R A) * M = M :=
Submodule.one_smul _
variable {M}
@[mono]
theorem mul_le_mul (hmp : M ≤ P) (hnq : N ≤ Q) : M * N ≤ P * Q :=
smul_mono hmp hnq
theorem mul_le_mul_left (h : M ≤ N) : M * P ≤ N * P :=
smul_mono_left h
theorem mul_le_mul_right (h : N ≤ P) : M * N ≤ M * P :=
smul_mono_right _ h
theorem mul_comm_of_commute (h : ∀ m ∈ M, ∀ n ∈ N, Commute m n) : M * N = N * M :=
toAddSubmonoid_injective <| AddSubmonoid.mul_comm_of_commute h
variable (M N P)
theorem mul_sup : M * (N ⊔ P) = M * N ⊔ M * P :=
smul_sup _ _ _
theorem sup_mul : (M ⊔ N) * P = M * P ⊔ N * P :=
sup_smul _ _ _
theorem mul_subset_mul : (↑M : Set A) * (↑N : Set A) ⊆ (↑(M * N) : Set A) :=
smul_subset_smul _ _
lemma restrictScalars_mul {A B C} [Semiring A] [Semiring B] [Semiring C]
[SMul A B] [Module A C] [Module B C] [IsScalarTower A C C] [IsScalarTower B C C]
[IsScalarTower A B C] {I J : Submodule B C} :
(I * J).restrictScalars A = I.restrictScalars A * J.restrictScalars A :=
rfl
variable {ι : Sort uι}
theorem iSup_mul (s : ι → Submodule R A) (t : Submodule R A) : (⨆ i, s i) * t = ⨆ i, s i * t :=
iSup_smul
theorem mul_iSup (t : Submodule R A) (s : ι → Submodule R A) : (t * ⨆ i, s i) = ⨆ i, t * s i :=
smul_iSup
/-- Sub-`R`-modules of an `R`-module form an idempotent semiring. -/
instance : NonUnitalSemiring (Submodule R A) where
__ := toAddSubmonoid_injective.semigroup _ mul_toAddSubmonoid
zero_mul := bot_mul
mul_zero := mul_bot
left_distrib := mul_sup
right_distrib := sup_mul
instance : Pow (Submodule R A) ℕ where
pow s n := npowRec n s
theorem pow_eq_npowRec {n : ℕ} : M ^ n = npowRec n M := rfl
protected theorem pow_zero : M ^ 0 = 1 := rfl
protected theorem pow_succ {n : ℕ} : M ^ (n + 1) = M ^ n * M := rfl
protected theorem pow_add {m n : ℕ} (h : n ≠ 0) : M ^ (m + n) = M ^ m * M ^ n :=
npowRec_add m n h _ M.one_mul
protected theorem pow_one : M ^ 1 = M := by
rw [Submodule.pow_succ, Submodule.pow_zero, Submodule.one_mul]
/-- `Submodule.pow_succ` with the right hand side commuted. -/
protected theorem pow_succ' {n : ℕ} (h : n ≠ 0) : M ^ (n + 1) = M * M ^ n := by
rw [add_comm, M.pow_add h, Submodule.pow_one]
theorem pow_toAddSubmonoid {n : ℕ} (h : n ≠ 0) : (M ^ n).toAddSubmonoid = M.toAddSubmonoid ^ n := by
induction n with
| zero => exact (h rfl).elim
| succ n ih =>
rw [Submodule.pow_succ, pow_succ, mul_toAddSubmonoid]
cases n with
| zero => rw [Submodule.pow_zero, pow_zero, one_mul, ← mul_toAddSubmonoid, Submodule.one_mul]
| succ n => rw [ih n.succ_ne_zero]
theorem le_pow_toAddSubmonoid {n : ℕ} : M.toAddSubmonoid ^ n ≤ (M ^ n).toAddSubmonoid := by
obtain rfl | hn := Decidable.eq_or_ne n 0
· rw [Submodule.pow_zero, pow_zero]
exact le_one_toAddSubmonoid
· exact (pow_toAddSubmonoid M hn).ge
theorem pow_subset_pow {n : ℕ} : (↑M : Set A) ^ n ⊆ ↑(M ^ n : Submodule R A) :=
trans AddSubmonoid.pow_subset_pow (le_pow_toAddSubmonoid M)
theorem pow_mem_pow {x : A} (hx : x ∈ M) (n : ℕ) : x ^ n ∈ M ^ n :=
pow_subset_pow _ <| Set.pow_mem_pow hx
lemma restrictScalars_pow {A B C : Type*} [Semiring A] [Semiring B]
[Semiring C] [SMul A B] [Module A C] [Module B C]
[IsScalarTower A C C] [IsScalarTower B C C] [IsScalarTower A B C]
{I : Submodule B C} :
∀ {n : ℕ}, (hn : n ≠ 0) → (I ^ n).restrictScalars A = I.restrictScalars A ^ n
| 1, _ => by simp [Submodule.pow_one]
| n + 2, _ => by
simp [Submodule.pow_succ (n := n + 1), restrictScalars_mul, restrictScalars_pow n.succ_ne_zero]
end Module
variable {ι : Sort uι}
variable {R : Type u} [CommSemiring R]
section AlgebraSemiring
variable {A : Type v} [Semiring A] [Algebra R A]
variable (S T : Set A) {M N P Q : Submodule R A} {m n : A}
theorem one_eq_range : (1 : Submodule R A) = LinearMap.range (Algebra.linearMap R A) := by
rw [one_eq_span, LinearMap.span_singleton_eq_range,
LinearMap.toSpanSingleton_eq_algebra_linearMap]
theorem algebraMap_mem (r : R) : algebraMap R A r ∈ (1 : Submodule R A) := by
simp [one_eq_range]
@[simp]
theorem mem_one {x : A} : x ∈ (1 : Submodule R A) ↔ ∃ y, algebraMap R A y = x := by
simp [one_eq_range]
protected theorem map_one {A'} [Semiring A'] [Algebra R A'] (f : A →ₐ[R] A') :
map f.toLinearMap (1 : Submodule R A) = 1 := by
ext
simp
@[simp]
theorem map_op_one :
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) (1 : Submodule R A) = 1 := by
ext x
induction x
simp
@[simp]
theorem comap_op_one :
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) (1 : Submodule R Aᵐᵒᵖ) = 1 := by
ext
simp
@[simp]
theorem map_unop_one :
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) (1 : Submodule R Aᵐᵒᵖ) = 1 := by
rw [← comap_equiv_eq_map_symm, comap_op_one]
@[simp]
theorem comap_unop_one :
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) (1 : Submodule R A) = 1 := by
rw [← map_equiv_eq_comap_symm, map_op_one]
theorem mul_eq_map₂ : M * N = map₂ (LinearMap.mul R A) M N :=
le_antisymm (mul_le.mpr fun _m hm _n ↦ apply_mem_map₂ _ hm)
(map₂_le.mpr fun _m hm _n ↦ mul_mem_mul hm)
variable (R M N)
theorem span_mul_span : span R S * span R T = span R (S * T) := by
rw [mul_eq_map₂]; apply map₂_span_span
lemma mul_def : M * N = span R (M * N : Set A) := by simp [← span_mul_span]
variable {R} (P Q)
protected theorem mul_one : M * 1 = M := by
conv_lhs => rw [one_eq_span, ← span_eq M]
rw [span_mul_span]
simp
protected theorem map_mul {A'} [Semiring A'] [Algebra R A'] (f : A →ₐ[R] A') :
map f.toLinearMap (M * N) = map f.toLinearMap M * map f.toLinearMap N :=
calc
map f.toLinearMap (M * N) = ⨆ i : M, (N.map (LinearMap.mul R A i)).map f.toLinearMap := by
rw [mul_eq_map₂]; apply map_iSup
_ = map f.toLinearMap M * map f.toLinearMap N := by
rw [mul_eq_map₂]
apply congr_arg sSup
ext S
constructor <;> rintro ⟨y, hy⟩
· use ⟨f y, mem_map.mpr ⟨y.1, y.2, rfl⟩⟩
refine Eq.trans ?_ hy
ext
simp
· obtain ⟨y', hy', fy_eq⟩ := mem_map.mp y.2
use ⟨y', hy'⟩
refine Eq.trans ?_ hy
rw [f.toLinearMap_apply] at fy_eq
ext
simp [fy_eq]
theorem map_op_mul :
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) (M * N) =
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) N *
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) M := by
apply le_antisymm
· simp_rw [map_le_iff_le_comap]
refine mul_le.2 fun m hm n hn => ?_
rw [mem_comap, map_equiv_eq_comap_symm, map_equiv_eq_comap_symm]
show op n * op m ∈ _
exact mul_mem_mul hn hm
· refine mul_le.2 (MulOpposite.rec' fun m hm => MulOpposite.rec' fun n hn => ?_)
rw [Submodule.mem_map_equiv] at hm hn ⊢
exact mul_mem_mul hn hm
theorem comap_unop_mul :
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) (M * N) =
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) N *
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) M := by
simp_rw [← map_equiv_eq_comap_symm, map_op_mul]
theorem map_unop_mul (M N : Submodule R Aᵐᵒᵖ) :
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) (M * N) =
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) N *
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) M :=
have : Function.Injective (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) :=
LinearEquiv.injective _
map_injective_of_injective this <| by
rw [← map_comp, map_op_mul, ← map_comp, ← map_comp, LinearEquiv.comp_coe,
LinearEquiv.symm_trans_self, LinearEquiv.refl_toLinearMap, map_id, map_id, map_id]
theorem comap_op_mul (M N : Submodule R Aᵐᵒᵖ) :
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) (M * N) =
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) N *
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) M := by
simp_rw [comap_equiv_eq_map_symm, map_unop_mul]
section
variable {α : Type*} [Monoid α] [DistribMulAction α A] [SMulCommClass α R A]
instance [IsScalarTower α A A] : IsScalarTower α (Submodule R A) (Submodule R A) where
smul_assoc a S T := by
rw [← S.span_eq, ← T.span_eq, smul_span, smul_eq_mul, smul_eq_mul, span_mul_span, span_mul_span,
smul_span, smul_mul_assoc]
instance [SMulCommClass α A A] : SMulCommClass α (Submodule R A) (Submodule R A) where
smul_comm a S T := by
rw [← S.span_eq, ← T.span_eq, smul_span, smul_eq_mul, smul_eq_mul, span_mul_span, span_mul_span,
smul_span, mul_smul_comm]
instance [SMulCommClass A α A] : SMulCommClass (Submodule R A) α (Submodule R A) :=
have := SMulCommClass.symm A α A; .symm ..
end
section
open Pointwise
/-- `Submodule.pointwiseNeg` distributes over multiplication.
This is available as an instance in the `Pointwise` locale. -/
protected def hasDistribPointwiseNeg {A} [Ring A] [Algebra R A] : HasDistribNeg (Submodule R A) :=
toAddSubmonoid_injective.hasDistribNeg _ neg_toAddSubmonoid mul_toAddSubmonoid
scoped[Pointwise] attribute [instance] Submodule.hasDistribPointwiseNeg
end
section DecidableEq
theorem mem_span_mul_finite_of_mem_span_mul {R A} [Semiring R] [AddCommMonoid A] [Mul A]
[Module R A] {S : Set A} {S' : Set A} {x : A} (hx : x ∈ span R (S * S')) :
∃ T T' : Finset A, ↑T ⊆ S ∧ ↑T' ⊆ S' ∧ x ∈ span R (T * T' : Set A) := by
classical
obtain ⟨U, h, hU⟩ := mem_span_finite_of_mem_span hx
obtain ⟨T, T', hS, hS', h⟩ := Finset.subset_mul h
use T, T', hS, hS'
have h' : (U : Set A) ⊆ T * T' := by assumption_mod_cast
have h'' := span_mono h' hU
assumption
end DecidableEq
theorem mul_eq_span_mul_set (s t : Submodule R A) : s * t = span R ((s : Set A) * (t : Set A)) := by
rw [mul_eq_map₂]; exact map₂_eq_span_image2 _ s t
theorem mem_span_mul_finite_of_mem_mul {P Q : Submodule R A} {x : A} (hx : x ∈ P * Q) :
∃ T T' : Finset A, (T : Set A) ⊆ P ∧ (T' : Set A) ⊆ Q ∧ x ∈ span R (T * T' : Set A) :=
Submodule.mem_span_mul_finite_of_mem_span_mul
(by rwa [← Submodule.span_eq P, ← Submodule.span_eq Q, Submodule.span_mul_span] at hx)
variable {M N P}
theorem mem_span_singleton_mul {x y : A} : x ∈ span R {y} * P ↔ ∃ z ∈ P, y * z = x := by
simp_rw [mul_eq_map₂, map₂_span_singleton_eq_map, mem_map, LinearMap.mul_apply_apply]
theorem mem_mul_span_singleton {x y : A} : x ∈ P * span R {y} ↔ ∃ z ∈ P, z * y = x := by
simp_rw [mul_eq_map₂, map₂_span_singleton_eq_map_flip, mem_map, LinearMap.flip_apply,
LinearMap.mul_apply_apply]
lemma span_singleton_mul {x : A} {p : Submodule R A} :
Submodule.span R {x} * p = x • p := ext fun _ ↦ mem_span_singleton_mul
lemma mem_smul_iff_inv_mul_mem {S} [DivisionSemiring S] [Algebra R S] {x : S} {p : Submodule R S}
{y : S} (hx : x ≠ 0) : y ∈ x • p ↔ x⁻¹ * y ∈ p := by
constructor
· rintro ⟨a, ha : a ∈ p, rfl⟩; simpa [inv_mul_cancel_left₀ hx]
· exact fun h ↦ ⟨_, h, by simp [mul_inv_cancel_left₀ hx]⟩
lemma mul_mem_smul_iff {S} [CommRing S] [Algebra R S] {x : S} {p : Submodule R S} {y : S}
(hx : x ∈ nonZeroDivisors S) :
x * y ∈ x • p ↔ y ∈ p := by
simp [mem_smul_pointwise_iff_exists, mul_cancel_left_mem_nonZeroDivisors hx]
variable (M N) in
theorem mul_smul_mul_eq_smul_mul_smul (x y : R) : (x * y) • (M * N) = (x • M) * (y • N) := by
ext
refine ⟨?_, fun hx ↦ Submodule.mul_induction_on hx ?_ fun _ _ hx hy ↦ Submodule.add_mem _ hx hy⟩
· rintro ⟨_, hx, rfl⟩
rw [DistribMulAction.toLinearMap_apply]
refine Submodule.mul_induction_on hx (fun m hm n hn ↦ ?_) (fun _ _ hn hm ↦ ?_)
· rw [mul_smul_mul_comm]
exact mul_mem_mul (smul_mem_pointwise_smul m x M hm) (smul_mem_pointwise_smul n y N hn)
· rw [smul_add]
exact Submodule.add_mem _ hn hm
· rintro _ ⟨m, hm, rfl⟩ _ ⟨n, hn, rfl⟩
simp_rw [DistribMulAction.toLinearMap_apply, smul_mul_smul_comm]
exact smul_mem_pointwise_smul _ _ _ (mul_mem_mul hm hn)
/-- Sub-R-modules of an R-algebra form an idempotent semiring. -/
instance idemSemiring : IdemSemiring (Submodule R A) where
__ := instNonUnitalSemiring
one_mul := Submodule.one_mul
mul_one := Submodule.mul_one
bot_le _ := bot_le
variable (M)
theorem span_pow (s : Set A) : ∀ n : ℕ, span R s ^ n = span R (s ^ n)
| 0 => by rw [pow_zero, pow_zero, one_eq_span_one_set]
| n + 1 => by rw [pow_succ, pow_succ, span_pow s n, span_mul_span]
theorem pow_eq_span_pow_set (n : ℕ) : M ^ n = span R ((M : Set A) ^ n) := by
rw [← span_pow, span_eq]
/-- Dependent version of `Submodule.pow_induction_on_left`. -/
@[elab_as_elim]
protected theorem pow_induction_on_left' {C : ∀ (n : ℕ) (x), x ∈ M ^ n → Prop}
(algebraMap : ∀ r : R, C 0 (algebraMap _ _ r) (algebraMap_mem r))
(add : ∀ x y i hx hy, C i x hx → C i y hy → C i (x + y) (add_mem ‹_› ‹_›))
(mem_mul : ∀ m (hm : m ∈ M), ∀ (i x hx), C i x hx → C i.succ (m * x)
((pow_succ' M i).symm ▸ (mul_mem_mul hm hx)))
{n : ℕ} {x : A}
(hx : x ∈ M ^ n) : C n x hx := by
induction n generalizing x with
| zero =>
rw [pow_zero] at hx
obtain ⟨r, rfl⟩ := mem_one.mp hx
exact algebraMap r
| succ n n_ih =>
revert hx
simp_rw [pow_succ']
exact fun hx ↦ Submodule.mul_induction_on' (fun m hm x ih => mem_mul _ hm _ _ _ (n_ih ih))
(fun x hx y hy Cx Cy => add _ _ _ _ _ Cx Cy) hx
/-- Dependent version of `Submodule.pow_induction_on_right`. -/
@[elab_as_elim]
protected theorem pow_induction_on_right' {C : ∀ (n : ℕ) (x), x ∈ M ^ n → Prop}
(algebraMap : ∀ r : R, C 0 (algebraMap _ _ r) (algebraMap_mem r))
(add : ∀ x y i hx hy, C i x hx → C i y hy → C i (x + y) (add_mem ‹_› ‹_›))
(mul_mem :
∀ i x hx, C i x hx →
∀ m (hm : m ∈ M), C i.succ (x * m) (mul_mem_mul hx hm))
{n : ℕ} {x : A} (hx : x ∈ M ^ n) : C n x hx := by
induction n generalizing x with
| zero =>
rw [pow_zero] at hx
obtain ⟨r, rfl⟩ := mem_one.mp hx
exact algebraMap r
| succ n n_ih =>
revert hx
simp_rw [pow_succ]
exact fun hx ↦ Submodule.mul_induction_on' (fun m hm x ih => mul_mem _ _ hm (n_ih _) _ ih)
(fun x hx y hy Cx Cy => add _ _ _ _ _ Cx Cy) hx
/-- To show a property on elements of `M ^ n` holds, it suffices to show that it holds for scalars,
is closed under addition, and holds for `m * x` where `m ∈ M` and it holds for `x` -/
@[elab_as_elim]
protected theorem pow_induction_on_left {C : A → Prop} (hr : ∀ r : R, C (algebraMap _ _ r))
(hadd : ∀ x y, C x → C y → C (x + y)) (hmul : ∀ m ∈ M, ∀ (x), C x → C (m * x)) {x : A} {n : ℕ}
(hx : x ∈ M ^ n) : C x :=
Submodule.pow_induction_on_left' M (C := fun _ a _ => C a) hr
(fun x y _i _hx _hy => hadd x y)
(fun _m hm _i _x _hx => hmul _ hm _) hx
/-- To show a property on elements of `M ^ n` holds, it suffices to show that it holds for scalars,
is closed under addition, and holds for `x * m` where `m ∈ M` and it holds for `x` -/
@[elab_as_elim]
protected theorem pow_induction_on_right {C : A → Prop} (hr : ∀ r : R, C (algebraMap _ _ r))
(hadd : ∀ x y, C x → C y → C (x + y)) (hmul : ∀ x, C x → ∀ m ∈ M, C (x * m)) {x : A} {n : ℕ}
(hx : x ∈ M ^ n) : C x :=
Submodule.pow_induction_on_right' (M := M) (C := fun _ a _ => C a) hr
(fun x y _i _hx _hy => hadd x y)
(fun _i _x _hx => hmul _) hx
/-- `Submonoid.map` as a `RingHom`, when applied to an `AlgHom`. -/
@[simps]
def mapHom {A'} [Semiring A'] [Algebra R A'] (f : A →ₐ[R] A') :
Submodule R A →+* Submodule R A' where
toFun := map f.toLinearMap
map_zero' := Submodule.map_bot _
map_add' := (Submodule.map_sup · · _)
map_one' := Submodule.map_one _
map_mul' := (Submodule.map_mul · · _)
theorem mapHom_id : mapHom (.id R A) = .id _ := RingHom.ext map_id
/-- The ring of submodules of the opposite algebra is isomorphic to the opposite ring of
submodules. -/
@[simps apply symm_apply]
def equivOpposite : Submodule R Aᵐᵒᵖ ≃+* (Submodule R A)ᵐᵒᵖ where
toFun p := op <| p.comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ)
invFun p := p.unop.comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A)
left_inv _ := SetLike.coe_injective <| rfl
right_inv _ := unop_injective <| SetLike.coe_injective rfl
map_add' p q := by simp [comap_equiv_eq_map_symm, ← op_add]
map_mul' _ _ := congr_arg op <| comap_op_mul _ _
protected theorem map_pow {A'} [Semiring A'] [Algebra R A'] (f : A →ₐ[R] A') (n : ℕ) :
map f.toLinearMap (M ^ n) = map f.toLinearMap M ^ n :=
map_pow (mapHom f) M n
theorem comap_unop_pow (n : ℕ) :
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) (M ^ n) =
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) M ^ n :=
(equivOpposite : Submodule R Aᵐᵒᵖ ≃+* _).symm.map_pow (op M) n
theorem comap_op_pow (n : ℕ) (M : Submodule R Aᵐᵒᵖ) :
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) (M ^ n) =
comap (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) M ^ n :=
op_injective <| (equivOpposite : Submodule R Aᵐᵒᵖ ≃+* _).map_pow M n
theorem map_op_pow (n : ℕ) :
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) (M ^ n) =
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ) : A →ₗ[R] Aᵐᵒᵖ) M ^ n := by
rw [map_equiv_eq_comap_symm, map_equiv_eq_comap_symm, comap_unop_pow]
theorem map_unop_pow (n : ℕ) (M : Submodule R Aᵐᵒᵖ) :
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) (M ^ n) =
map (↑(opLinearEquiv R : A ≃ₗ[R] Aᵐᵒᵖ).symm : Aᵐᵒᵖ →ₗ[R] A) M ^ n := by
rw [← comap_equiv_eq_map_symm, ← comap_equiv_eq_map_symm, comap_op_pow]
/-- `span` is a semiring homomorphism (recall multiplication is pointwise multiplication of subsets
on either side). -/
@[simps]
def span.ringHom : SetSemiring A →+* Submodule R A where
toFun s := Submodule.span R (SetSemiring.down s)
map_zero' := span_empty
map_one' := one_eq_span.symm
map_add' := span_union
map_mul' s t := by simp_rw [SetSemiring.down_mul, span_mul_span]
section
variable {α : Type*} [Monoid α] [MulSemiringAction α A] [SMulCommClass α R A]
/-- The action on a submodule corresponding to applying the action to every element.
This is available as an instance in the `Pointwise` locale.
This is a stronger version of `Submodule.pointwiseDistribMulAction`. -/
protected def pointwiseMulSemiringAction : MulSemiringAction α (Submodule R A) where
__ := Submodule.pointwiseDistribMulAction
smul_mul r x y := Submodule.map_mul x y <| MulSemiringAction.toAlgHom R A r
smul_one r := Submodule.map_one <| MulSemiringAction.toAlgHom R A r
scoped[Pointwise] attribute [instance] Submodule.pointwiseMulSemiringAction
end
end AlgebraSemiring
section AlgebraCommSemiring
variable {A : Type v} [CommSemiring A] [Algebra R A]
variable {M N : Submodule R A} {m n : A}
theorem mul_mem_mul_rev (hm : m ∈ M) (hn : n ∈ N) : n * m ∈ M * N :=
mul_comm m n ▸ mul_mem_mul hm hn
variable (M N)
protected theorem mul_comm : M * N = N * M :=
le_antisymm (mul_le.2 fun _r hrm _s hsn => mul_mem_mul_rev hsn hrm)
(mul_le.2 fun _r hrn _s hsm => mul_mem_mul_rev hsm hrn)
/-- Sub-R-modules of an R-algebra A form a semiring. -/
instance : IdemCommSemiring (Submodule R A) :=
{ Submodule.idemSemiring with mul_comm := Submodule.mul_comm }
theorem prod_span {ι : Type*} (s : Finset ι) (M : ι → Set A) :
(∏ i ∈ s, Submodule.span R (M i)) = Submodule.span R (∏ i ∈ s, M i) := by
letI := Classical.decEq ι
refine Finset.induction_on s ?_ ?_
· simp [one_eq_span, Set.singleton_one]
· intro _ _ H ih
| rw [Finset.prod_insert H, Finset.prod_insert H, ih, span_mul_span]
theorem prod_span_singleton {ι : Type*} (s : Finset ι) (x : ι → A) :
(∏ i ∈ s, span R ({x i} : Set A)) = span R {∏ i ∈ s, x i} := by
| Mathlib/Algebra/Algebra/Operations.lean | 738 | 741 |
/-
Copyright (c) 2017 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Tim Baumann, Stephen Morgan, Kim Morrison, Floris van Doorn
-/
import Mathlib.Tactic.CategoryTheory.Reassoc
/-!
# Isomorphisms
This file defines isomorphisms between objects of a category.
## Main definitions
- `structure Iso` : a bundled isomorphism between two objects of a category;
- `class IsIso` : an unbundled version of `iso`;
note that `IsIso f` is a `Prop`, and only asserts the existence of an inverse.
Of course, this inverse is unique, so it doesn't cost us much to use choice to retrieve it.
- `inv f`, for the inverse of a morphism with `[IsIso f]`
- `asIso` : convert from `IsIso` to `Iso` (noncomputable);
- `of_iso` : convert from `Iso` to `IsIso`;
- standard operations on isomorphisms (composition, inverse etc)
## Notations
- `X ≅ Y` : same as `Iso X Y`;
- `α ≪≫ β` : composition of two isomorphisms; it is called `Iso.trans`
## Tags
category, category theory, isomorphism
-/
universe v u
-- morphism levels before object levels. See note [CategoryTheory universes].
namespace CategoryTheory
open Category
/-- An isomorphism (a.k.a. an invertible morphism) between two objects of a category.
The inverse morphism is bundled.
See also `CategoryTheory.Core` for the category with the same objects and isomorphisms playing
the role of morphisms. -/
@[stacks 0017]
structure Iso {C : Type u} [Category.{v} C] (X Y : C) where
/-- The forward direction of an isomorphism. -/
hom : X ⟶ Y
/-- The backwards direction of an isomorphism. -/
inv : Y ⟶ X
/-- Composition of the two directions of an isomorphism is the identity on the source. -/
hom_inv_id : hom ≫ inv = 𝟙 X := by aesop_cat
/-- Composition of the two directions of an isomorphism in reverse order
is the identity on the target. -/
inv_hom_id : inv ≫ hom = 𝟙 Y := by aesop_cat
attribute [reassoc (attr := simp)] Iso.hom_inv_id Iso.inv_hom_id
/-- Notation for an isomorphism in a category. -/
infixr:10 " ≅ " => Iso -- type as \cong or \iso
variable {C : Type u} [Category.{v} C] {X Y Z : C}
namespace Iso
@[ext]
theorem ext ⦃α β : X ≅ Y⦄ (w : α.hom = β.hom) : α = β :=
suffices α.inv = β.inv by
cases α
cases β
cases w
cases this
rfl
calc
α.inv = α.inv ≫ β.hom ≫ β.inv := by rw [Iso.hom_inv_id, Category.comp_id]
_ = (α.inv ≫ α.hom) ≫ β.inv := by rw [Category.assoc, ← w]
_ = β.inv := by rw [Iso.inv_hom_id, Category.id_comp]
/-- Inverse isomorphism. -/
@[symm]
def symm (I : X ≅ Y) : Y ≅ X where
hom := I.inv
inv := I.hom
@[simp]
theorem symm_hom (α : X ≅ Y) : α.symm.hom = α.inv :=
rfl
@[simp]
theorem symm_inv (α : X ≅ Y) : α.symm.inv = α.hom :=
rfl
@[simp]
theorem symm_mk {X Y : C} (hom : X ⟶ Y) (inv : Y ⟶ X) (hom_inv_id) (inv_hom_id) :
Iso.symm { hom, inv, hom_inv_id := hom_inv_id, inv_hom_id := inv_hom_id } =
{ hom := inv, inv := hom, hom_inv_id := inv_hom_id, inv_hom_id := hom_inv_id } :=
rfl
@[simp]
theorem symm_symm_eq {X Y : C} (α : X ≅ Y) : α.symm.symm = α := rfl
theorem symm_bijective {X Y : C} : Function.Bijective (symm : (X ≅ Y) → _) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm_eq, symm_symm_eq⟩
@[simp]
theorem symm_eq_iff {X Y : C} {α β : X ≅ Y} : α.symm = β.symm ↔ α = β :=
symm_bijective.injective.eq_iff
theorem nonempty_iso_symm (X Y : C) : Nonempty (X ≅ Y) ↔ Nonempty (Y ≅ X) :=
⟨fun h => ⟨h.some.symm⟩, fun h => ⟨h.some.symm⟩⟩
/-- Identity isomorphism. -/
@[refl, simps]
def refl (X : C) : X ≅ X where
hom := 𝟙 X
inv := 𝟙 X
instance : Inhabited (X ≅ X) := ⟨Iso.refl X⟩
theorem nonempty_iso_refl (X : C) : Nonempty (X ≅ X) := ⟨default⟩
@[simp]
theorem refl_symm (X : C) : (Iso.refl X).symm = Iso.refl X := rfl
/-- Composition of two isomorphisms -/
@[simps]
def trans (α : X ≅ Y) (β : Y ≅ Z) : X ≅ Z where
hom := α.hom ≫ β.hom
inv := β.inv ≫ α.inv
@[simps]
instance instTransIso : Trans (α := C) (· ≅ ·) (· ≅ ·) (· ≅ ·) where
trans := trans
/-- Notation for composition of isomorphisms. -/
infixr:80 " ≪≫ " => Iso.trans -- type as `\ll \gg`.
@[simp]
theorem trans_mk {X Y Z : C} (hom : X ⟶ Y) (inv : Y ⟶ X) (hom_inv_id) (inv_hom_id)
(hom' : Y ⟶ Z) (inv' : Z ⟶ Y) (hom_inv_id') (inv_hom_id') (hom_inv_id'') (inv_hom_id'') :
Iso.trans ⟨hom, inv, hom_inv_id, inv_hom_id⟩ ⟨hom', inv', hom_inv_id', inv_hom_id'⟩ =
⟨hom ≫ hom', inv' ≫ inv, hom_inv_id'', inv_hom_id''⟩ :=
rfl
@[simp]
theorem trans_symm (α : X ≅ Y) (β : Y ≅ Z) : (α ≪≫ β).symm = β.symm ≪≫ α.symm :=
rfl
@[simp]
theorem trans_assoc {Z' : C} (α : X ≅ Y) (β : Y ≅ Z) (γ : Z ≅ Z') :
(α ≪≫ β) ≪≫ γ = α ≪≫ β ≪≫ γ := by
ext; simp only [trans_hom, Category.assoc]
@[simp]
theorem refl_trans (α : X ≅ Y) : Iso.refl X ≪≫ α = α := by ext; apply Category.id_comp
@[simp]
theorem trans_refl (α : X ≅ Y) : α ≪≫ Iso.refl Y = α := by ext; apply Category.comp_id
@[simp]
theorem symm_self_id (α : X ≅ Y) : α.symm ≪≫ α = Iso.refl Y :=
ext α.inv_hom_id
@[simp]
theorem self_symm_id (α : X ≅ Y) : α ≪≫ α.symm = Iso.refl X :=
ext α.hom_inv_id
@[simp]
theorem symm_self_id_assoc (α : X ≅ Y) (β : Y ≅ Z) : α.symm ≪≫ α ≪≫ β = β := by
rw [← trans_assoc, symm_self_id, refl_trans]
@[simp]
theorem self_symm_id_assoc (α : X ≅ Y) (β : X ≅ Z) : α ≪≫ α.symm ≪≫ β = β := by
rw [← trans_assoc, self_symm_id, refl_trans]
theorem inv_comp_eq (α : X ≅ Y) {f : X ⟶ Z} {g : Y ⟶ Z} : α.inv ≫ f = g ↔ f = α.hom ≫ g :=
⟨fun H => by simp [H.symm], fun H => by simp [H]⟩
theorem eq_inv_comp (α : X ≅ Y) {f : X ⟶ Z} {g : Y ⟶ Z} : g = α.inv ≫ f ↔ α.hom ≫ g = f :=
(inv_comp_eq α.symm).symm
theorem comp_inv_eq (α : X ≅ Y) {f : Z ⟶ Y} {g : Z ⟶ X} : f ≫ α.inv = g ↔ f = g ≫ α.hom :=
⟨fun H => by simp [H.symm], fun H => by simp [H]⟩
theorem eq_comp_inv (α : X ≅ Y) {f : Z ⟶ Y} {g : Z ⟶ X} : g = f ≫ α.inv ↔ g ≫ α.hom = f :=
(comp_inv_eq α.symm).symm
theorem inv_eq_inv (f g : X ≅ Y) : f.inv = g.inv ↔ f.hom = g.hom :=
have : ∀ {X Y : C} (f g : X ≅ Y), f.hom = g.hom → f.inv = g.inv := fun f g h => by rw [ext h]
⟨this f.symm g.symm, this f g⟩
theorem hom_comp_eq_id (α : X ≅ Y) {f : Y ⟶ X} : α.hom ≫ f = 𝟙 X ↔ f = α.inv := by
rw [← eq_inv_comp, comp_id]
theorem comp_hom_eq_id (α : X ≅ Y) {f : Y ⟶ X} : f ≫ α.hom = 𝟙 Y ↔ f = α.inv := by
rw [← eq_comp_inv, id_comp]
theorem inv_comp_eq_id (α : X ≅ Y) {f : X ⟶ Y} : α.inv ≫ f = 𝟙 Y ↔ f = α.hom :=
hom_comp_eq_id α.symm
theorem comp_inv_eq_id (α : X ≅ Y) {f : X ⟶ Y} : f ≫ α.inv = 𝟙 X ↔ f = α.hom :=
comp_hom_eq_id α.symm
theorem hom_eq_inv (α : X ≅ Y) (β : Y ≅ X) : α.hom = β.inv ↔ β.hom = α.inv := by
rw [← symm_inv, inv_eq_inv α.symm β, eq_comm]
rfl
/-- The bijection `(Z ⟶ X) ≃ (Z ⟶ Y)` induced by `α : X ≅ Y`. -/
@[simps]
def homToEquiv (α : X ≅ Y) {Z : C} : (Z ⟶ X) ≃ (Z ⟶ Y) where
toFun f := f ≫ α.hom
invFun g := g ≫ α.inv
left_inv := by aesop_cat
right_inv := by aesop_cat
/-- The bijection `(X ⟶ Z) ≃ (Y ⟶ Z)` induced by `α : X ≅ Y`. -/
@[simps]
def homFromEquiv (α : X ≅ Y) {Z : C} : (X ⟶ Z) ≃ (Y ⟶ Z) where
toFun f := α.inv ≫ f
invFun g := α.hom ≫ g
left_inv := by aesop_cat
right_inv := by aesop_cat
end Iso
/-- `IsIso` typeclass expressing that a morphism is invertible. -/
class IsIso (f : X ⟶ Y) : Prop where
/-- The existence of an inverse morphism. -/
out : ∃ inv : Y ⟶ X, f ≫ inv = 𝟙 X ∧ inv ≫ f = 𝟙 Y
/-- The inverse of a morphism `f` when we have `[IsIso f]`.
-/
noncomputable def inv (f : X ⟶ Y) [I : IsIso f] : Y ⟶ X :=
Classical.choose I.1
namespace IsIso
@[simp]
theorem hom_inv_id (f : X ⟶ Y) [I : IsIso f] : f ≫ inv f = 𝟙 X :=
(Classical.choose_spec I.1).left
@[simp]
theorem inv_hom_id (f : X ⟶ Y) [I : IsIso f] : inv f ≫ f = 𝟙 Y :=
(Classical.choose_spec I.1).right
-- FIXME putting @[reassoc] on the `hom_inv_id` above somehow unfolds `inv`
-- This happens even if we make `inv` irreducible!
-- I don't understand how this is happening: it is likely a bug.
-- attribute [reassoc] hom_inv_id inv_hom_id
-- #print hom_inv_id_assoc
-- theorem CategoryTheory.IsIso.hom_inv_id_assoc {X Y : C} (f : X ⟶ Y) [I : IsIso f]
-- {Z : C} (h : X ⟶ Z),
-- f ≫ Classical.choose (_ : Exists fun inv ↦ f ≫ inv = 𝟙 X ∧ inv ≫ f = 𝟙 Y) ≫ h = h := ...
@[simp]
theorem hom_inv_id_assoc (f : X ⟶ Y) [I : IsIso f] {Z} (g : X ⟶ Z) : f ≫ inv f ≫ g = g := by
simp [← Category.assoc]
@[simp]
theorem inv_hom_id_assoc (f : X ⟶ Y) [I : IsIso f] {Z} (g : Y ⟶ Z) : inv f ≫ f ≫ g = g := by
simp [← Category.assoc]
end IsIso
lemma Iso.isIso_hom (e : X ≅ Y) : IsIso e.hom :=
⟨e.inv, by simp, by simp⟩
lemma Iso.isIso_inv (e : X ≅ Y) : IsIso e.inv := e.symm.isIso_hom
attribute [instance] Iso.isIso_hom Iso.isIso_inv
open IsIso
/-- Reinterpret a morphism `f` with an `IsIso f` instance as an `Iso`. -/
noncomputable def asIso (f : X ⟶ Y) [IsIso f] : X ≅ Y :=
⟨f, inv f, hom_inv_id f, inv_hom_id f⟩
-- Porting note: the `IsIso f` argument had been instance implicit,
-- but we've changed it to implicit as a `rw` in `Mathlib.CategoryTheory.Closed.Functor`
-- was failing to generate it by typeclass search.
@[simp]
theorem asIso_hom (f : X ⟶ Y) {_ : IsIso f} : (asIso f).hom = f :=
rfl
-- Porting note: the `IsIso f` argument had been instance implicit,
-- but we've changed it to implicit as a `rw` in `Mathlib.CategoryTheory.Closed.Functor`
-- was failing to generate it by typeclass search.
@[simp]
theorem asIso_inv (f : X ⟶ Y) {_ : IsIso f} : (asIso f).inv = inv f :=
rfl
namespace IsIso
-- see Note [lower instance priority]
instance (priority := 100) epi_of_iso (f : X ⟶ Y) [IsIso f] : Epi f where
left_cancellation g h w := by
rw [← IsIso.inv_hom_id_assoc f g, w, IsIso.inv_hom_id_assoc f h]
-- see Note [lower instance priority]
instance (priority := 100) mono_of_iso (f : X ⟶ Y) [IsIso f] : Mono f where
right_cancellation g h w := by
rw [← Category.comp_id g, ← Category.comp_id h, ← IsIso.hom_inv_id f,
← Category.assoc, w, ← Category.assoc]
@[aesop apply safe (rule_sets := [CategoryTheory])]
theorem inv_eq_of_hom_inv_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (hom_inv_id : f ≫ g = 𝟙 X) :
inv f = g := by
apply (cancel_epi f).mp
simp [hom_inv_id]
theorem inv_eq_of_inv_hom_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (inv_hom_id : g ≫ f = 𝟙 Y) :
inv f = g := by
apply (cancel_mono f).mp
simp [inv_hom_id]
@[aesop apply safe (rule_sets := [CategoryTheory])]
theorem eq_inv_of_hom_inv_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (hom_inv_id : f ≫ g = 𝟙 X) :
g = inv f :=
(inv_eq_of_hom_inv_id hom_inv_id).symm
theorem eq_inv_of_inv_hom_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (inv_hom_id : g ≫ f = 𝟙 Y) :
g = inv f :=
(inv_eq_of_inv_hom_id inv_hom_id).symm
instance id (X : C) : IsIso (𝟙 X) := ⟨⟨𝟙 X, by simp⟩⟩
variable {f : X ⟶ Y} {h : Y ⟶ Z}
instance inv_isIso [IsIso f] : IsIso (inv f) :=
(asIso f).isIso_inv
/- The following instance has lower priority for the following reason:
Suppose we are given `f : X ≅ Y` with `X Y : Type u`.
Without the lower priority, typeclass inference cannot deduce `IsIso f.hom`
because `f.hom` is defeq to `(fun x ↦ x) ≫ f.hom`, triggering a loop. -/
instance (priority := 900) comp_isIso [IsIso f] [IsIso h] : IsIso (f ≫ h) :=
(asIso f ≪≫ asIso h).isIso_hom
/--
The composition of isomorphisms is an isomorphism. Here the arguments of type `IsIso` are
explicit, to make this easier to use with the `refine` tactic, for instance.
-/
lemma comp_isIso' (_ : IsIso f) (_ : IsIso h) : IsIso (f ≫ h) := inferInstance
@[simp]
theorem inv_id : inv (𝟙 X) = 𝟙 X := by
apply inv_eq_of_hom_inv_id
simp
@[simp, reassoc]
theorem inv_comp [IsIso f] [IsIso h] : inv (f ≫ h) = inv h ≫ inv f := by
apply inv_eq_of_hom_inv_id
simp
@[simp]
theorem inv_inv [IsIso f] : inv (inv f) = f := by
apply inv_eq_of_hom_inv_id
simp
@[simp]
theorem Iso.inv_inv (f : X ≅ Y) : inv f.inv = f.hom := by
apply inv_eq_of_hom_inv_id
simp
@[simp]
theorem Iso.inv_hom (f : X ≅ Y) : inv f.hom = f.inv := by
apply inv_eq_of_hom_inv_id
simp
@[simp]
theorem inv_comp_eq (α : X ⟶ Y) [IsIso α] {f : X ⟶ Z} {g : Y ⟶ Z} : inv α ≫ f = g ↔ f = α ≫ g :=
(asIso α).inv_comp_eq
@[simp]
theorem eq_inv_comp (α : X ⟶ Y) [IsIso α] {f : X ⟶ Z} {g : Y ⟶ Z} : g = inv α ≫ f ↔ α ≫ g = f :=
(asIso α).eq_inv_comp
@[simp]
theorem comp_inv_eq (α : X ⟶ Y) [IsIso α] {f : Z ⟶ Y} {g : Z ⟶ X} : f ≫ inv α = g ↔ f = g ≫ α :=
(asIso α).comp_inv_eq
@[simp]
theorem eq_comp_inv (α : X ⟶ Y) [IsIso α] {f : Z ⟶ Y} {g : Z ⟶ X} : g = f ≫ inv α ↔ g ≫ α = f :=
(asIso α).eq_comp_inv
theorem of_isIso_comp_left {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [IsIso (f ≫ g)] :
IsIso g := by
rw [← id_comp g, ← inv_hom_id f, assoc]
infer_instance
theorem of_isIso_comp_right {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso g] [IsIso (f ≫ g)] :
IsIso f := by
rw [← comp_id f, ← hom_inv_id g, ← assoc]
infer_instance
theorem of_isIso_fac_left {X Y Z : C} {f : X ⟶ Y} {g : Y ⟶ Z} {h : X ⟶ Z} [IsIso f]
[hh : IsIso h] (w : f ≫ g = h) : IsIso g := by
rw [← w] at hh
haveI := hh
exact of_isIso_comp_left f g
theorem of_isIso_fac_right {X Y Z : C} {f : X ⟶ Y} {g : Y ⟶ Z} {h : X ⟶ Z} [IsIso g]
[hh : IsIso h] (w : f ≫ g = h) : IsIso f := by
rw [← w] at hh
haveI := hh
exact of_isIso_comp_right f g
end IsIso
open IsIso
theorem eq_of_inv_eq_inv {f g : X ⟶ Y} [IsIso f] [IsIso g] (p : inv f = inv g) : f = g := by
apply (cancel_epi (inv f)).1
rw [inv_hom_id, p, inv_hom_id]
theorem IsIso.inv_eq_inv {f g : X ⟶ Y} [IsIso f] [IsIso g] : inv f = inv g ↔ f = g :=
Iso.inv_eq_inv (asIso f) (asIso g)
theorem hom_comp_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} : g ≫ f = 𝟙 X ↔ f = inv g :=
(asIso g).hom_comp_eq_id
theorem comp_hom_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} : f ≫ g = 𝟙 Y ↔ f = inv g :=
(asIso g).comp_hom_eq_id
theorem inv_comp_eq_id (g : X ⟶ Y) [IsIso g] {f : X ⟶ Y} : inv g ≫ f = 𝟙 Y ↔ f = g :=
(asIso g).inv_comp_eq_id
theorem comp_inv_eq_id (g : X ⟶ Y) [IsIso g] {f : X ⟶ Y} : f ≫ inv g = 𝟙 X ↔ f = g :=
(asIso g).comp_inv_eq_id
theorem isIso_of_hom_comp_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} (h : g ≫ f = 𝟙 X) : IsIso f := by
rw [(hom_comp_eq_id _).mp h]
infer_instance
theorem isIso_of_comp_hom_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} (h : f ≫ g = 𝟙 Y) : IsIso f := by
rw [(comp_hom_eq_id _).mp h]
infer_instance
namespace Iso
@[aesop apply safe (rule_sets := [CategoryTheory])]
theorem inv_ext {f : X ≅ Y} {g : Y ⟶ X} (hom_inv_id : f.hom ≫ g = 𝟙 X) : f.inv = g :=
((hom_comp_eq_id f).1 hom_inv_id).symm
@[aesop apply safe (rule_sets := [CategoryTheory])]
theorem inv_ext' {f : X ≅ Y} {g : Y ⟶ X} (hom_inv_id : f.hom ≫ g = 𝟙 X) : g = f.inv :=
(hom_comp_eq_id f).1 hom_inv_id
/-!
All these cancellation lemmas can be solved by `simp [cancel_mono]` (or `simp [cancel_epi]`),
but with the current design `cancel_mono` is not a good `simp` lemma,
because it generates a typeclass search.
When we can see syntactically that a morphism is a `mono` or an `epi`
because it came from an isomorphism, it's fine to do the cancellation via `simp`.
In the longer term, it might be worth exploring making `mono` and `epi` structures,
rather than typeclasses, with coercions back to `X ⟶ Y`.
Presumably we could write `X ↪ Y` and `X ↠ Y`.
-/
@[simp]
theorem cancel_iso_hom_left {X Y Z : C} (f : X ≅ Y) (g g' : Y ⟶ Z) :
f.hom ≫ g = f.hom ≫ g' ↔ g = g' := by
simp only [cancel_epi]
@[simp]
theorem cancel_iso_inv_left {X Y Z : C} (f : Y ≅ X) (g g' : Y ⟶ Z) :
f.inv ≫ g = f.inv ≫ g' ↔ g = g' := by
simp only [cancel_epi]
@[simp]
theorem cancel_iso_hom_right {X Y Z : C} (f f' : X ⟶ Y) (g : Y ≅ Z) :
f ≫ g.hom = f' ≫ g.hom ↔ f = f' := by
simp only [cancel_mono]
@[simp]
theorem cancel_iso_inv_right {X Y Z : C} (f f' : X ⟶ Y) (g : Z ≅ Y) :
f ≫ g.inv = f' ≫ g.inv ↔ f = f' := by
simp only [cancel_mono]
/-
Unfortunately cancelling an isomorphism from the right of a chain of compositions is awkward.
We would need separate lemmas for each chain length (worse: for each pair of chain lengths).
We provide two more lemmas, for case of three morphisms, because this actually comes up in practice,
but then stop.
-/
@[simp]
theorem cancel_iso_hom_right_assoc {W X X' Y Z : C} (f : W ⟶ X) (g : X ⟶ Y) (f' : W ⟶ X')
(g' : X' ⟶ Y) (h : Y ≅ Z) : f ≫ g ≫ h.hom = f' ≫ g' ≫ h.hom ↔ f ≫ g = f' ≫ g' := by
simp only [← Category.assoc, cancel_mono]
@[simp]
theorem cancel_iso_inv_right_assoc {W X X' Y Z : C} (f : W ⟶ X) (g : X ⟶ Y) (f' : W ⟶ X')
(g' : X' ⟶ Y) (h : Z ≅ Y) : f ≫ g ≫ h.inv = f' ≫ g' ≫ h.inv ↔ f ≫ g = f' ≫ g' := by
simp only [← Category.assoc, cancel_mono]
section
variable {D : Type*} [Category D] {X Y : C} (e : X ≅ Y)
@[reassoc (attr := simp)]
lemma map_hom_inv_id (F : C ⥤ D) :
F.map e.hom ≫ F.map e.inv = 𝟙 _ := by
rw [← F.map_comp, e.hom_inv_id, F.map_id]
@[reassoc (attr := simp)]
lemma map_inv_hom_id (F : C ⥤ D) :
F.map e.inv ≫ F.map e.hom = 𝟙 _ := by
rw [← F.map_comp, e.inv_hom_id, F.map_id]
end
end Iso
namespace Functor
universe u₁ v₁ u₂ v₂
variable {D : Type u₂}
variable [Category.{v₂} D]
/-- A functor `F : C ⥤ D` sends isomorphisms `i : X ≅ Y` to isomorphisms `F.obj X ≅ F.obj Y` -/
@[simps]
def mapIso (F : C ⥤ D) {X Y : C} (i : X ≅ Y) : F.obj X ≅ F.obj Y where
hom := F.map i.hom
inv := F.map i.inv
@[simp]
theorem mapIso_symm (F : C ⥤ D) {X Y : C} (i : X ≅ Y) : F.mapIso i.symm = (F.mapIso i).symm :=
rfl
@[simp]
theorem mapIso_trans (F : C ⥤ D) {X Y Z : C} (i : X ≅ Y) (j : Y ≅ Z) :
F.mapIso (i ≪≫ j) = F.mapIso i ≪≫ F.mapIso j := by
ext; apply Functor.map_comp
@[simp]
theorem mapIso_refl (F : C ⥤ D) (X : C) : F.mapIso (Iso.refl X) = Iso.refl (F.obj X) :=
Iso.ext <| F.map_id X
instance map_isIso (F : C ⥤ D) (f : X ⟶ Y) [IsIso f] : IsIso (F.map f) :=
(F.mapIso (asIso f)).isIso_hom
@[simp]
theorem map_inv (F : C ⥤ D) {X Y : C} (f : X ⟶ Y) [IsIso f] : F.map (inv f) = inv (F.map f) := by
apply eq_inv_of_hom_inv_id
simp [← F.map_comp]
@[reassoc]
theorem map_hom_inv (F : C ⥤ D) {X Y : C} (f : X ⟶ Y) [IsIso f] :
F.map f ≫ F.map (inv f) = 𝟙 (F.obj X) := by simp
@[reassoc]
theorem map_inv_hom (F : C ⥤ D) {X Y : C} (f : X ⟶ Y) [IsIso f] :
| F.map (inv f) ≫ F.map f = 𝟙 (F.obj Y) := by simp
end Functor
| Mathlib/CategoryTheory/Iso.lean | 560 | 562 |
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Function.LpSeminorm.Basic
/-!
# Chebyshev-Markov inequality in terms of Lp seminorms
In this file we formulate several versions of the Chebyshev-Markov inequality
in terms of the `MeasureTheory.eLpNorm` seminorm.
-/
open scoped NNReal ENNReal
namespace MeasureTheory
variable {α E : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E]
{p : ℝ≥0∞} (μ : Measure α) {f : α → E}
theorem pow_mul_meas_ge_le_eLpNorm (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞)
(hf : AEStronglyMeasurable f μ) (ε : ℝ≥0∞) :
| (ε * μ { x | ε ≤ (‖f x‖₊ : ℝ≥0∞) ^ p.toReal }) ^ (1 / p.toReal) ≤ eLpNorm f p μ := by
rw [eLpNorm_eq_lintegral_rpow_enorm hp_ne_zero hp_ne_top]
gcongr
exact mul_meas_ge_le_lintegral₀ (hf.enorm.pow_const _) ε
theorem mul_meas_ge_le_pow_eLpNorm (hp_ne_zero : p ≠ 0) (hp_ne_top : p ≠ ∞)
| Mathlib/MeasureTheory/Function/LpSeminorm/ChebyshevMarkov.lean | 23 | 28 |
/-
Copyright (c) 2020 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Algebra.Order.Group.Multiset
import Mathlib.Data.Setoid.Basic
import Mathlib.Data.Vector.Basic
import Mathlib.Logic.Nontrivial.Basic
import Mathlib.Tactic.ApplyFun
/-!
# Symmetric powers
This file defines symmetric powers of a type. The nth symmetric power
consists of homogeneous n-tuples modulo permutations by the symmetric
group.
The special case of 2-tuples is called the symmetric square, which is
addressed in more detail in `Data.Sym.Sym2`.
TODO: This was created as supporting material for `Sym2`; it
needs a fleshed-out interface.
## Tags
symmetric powers
-/
assert_not_exists MonoidWithZero
open List (Vector)
open Function
/-- The nth symmetric power is n-tuples up to permutation. We define it
as a subtype of `Multiset` since these are well developed in the
library. We also give a definition `Sym.sym'` in terms of vectors, and we
show these are equivalent in `Sym.symEquivSym'`.
-/
def Sym (α : Type*) (n : ℕ) :=
{ s : Multiset α // Multiset.card s = n }
/-- The canonical map to `Multiset α` that forgets that `s` has length `n` -/
@[coe] def Sym.toMultiset {α : Type*} {n : ℕ} (s : Sym α n) : Multiset α :=
s.1
instance Sym.hasCoe (α : Type*) (n : ℕ) : CoeOut (Sym α n) (Multiset α) :=
⟨Sym.toMultiset⟩
-- The following instance should be constructed by a deriving handler.
-- https://github.com/leanprover-community/mathlib4/issues/380
instance {α : Type*} {n : ℕ} [DecidableEq α] : DecidableEq (Sym α n) :=
inferInstanceAs <| DecidableEq <| Subtype _
/-- This is the `List.Perm` setoid lifted to `Vector`.
See note [reducible non-instances].
-/
abbrev List.Vector.Perm.isSetoid (α : Type*) (n : ℕ) : Setoid (Vector α n) :=
(List.isSetoid α).comap Subtype.val
attribute [local instance] Vector.Perm.isSetoid
-- Copy over the `DecidableRel` instance across the definition.
-- (Although `List.Vector.Perm.isSetoid` is an `abbrev`, `List.isSetoid` is not.)
instance {α : Type*} {n : ℕ} [DecidableEq α] :
DecidableRel (· ≈ · : List.Vector α n → List.Vector α n → Prop) :=
fun _ _ => List.decidablePerm _ _
namespace Sym
variable {α β : Type*} {n n' m : ℕ} {s : Sym α n} {a b : α}
theorem coe_injective : Injective ((↑) : Sym α n → Multiset α) :=
Subtype.coe_injective
@[simp, norm_cast]
theorem coe_inj {s₁ s₂ : Sym α n} : (s₁ : Multiset α) = s₂ ↔ s₁ = s₂ :=
coe_injective.eq_iff
@[ext] theorem ext {s₁ s₂ : Sym α n} (h : (s₁ : Multiset α) = ↑s₂) : s₁ = s₂ :=
coe_injective h
@[simp]
theorem val_eq_coe (s : Sym α n) : s.1 = ↑s :=
rfl
/-- Construct an element of the `n`th symmetric power from a multiset of cardinality `n`.
-/
@[match_pattern]
abbrev mk (m : Multiset α) (h : Multiset.card m = n) : Sym α n :=
⟨m, h⟩
/-- The unique element in `Sym α 0`. -/
@[match_pattern]
def nil : Sym α 0 :=
⟨0, Multiset.card_zero⟩
@[simp]
theorem coe_nil : ↑(@Sym.nil α) = (0 : Multiset α) :=
rfl
/-- Inserts an element into the term of `Sym α n`, increasing the length by one.
-/
@[match_pattern]
def cons (a : α) (s : Sym α n) : Sym α n.succ :=
⟨a ::ₘ s.1, by rw [Multiset.card_cons, s.2]⟩
@[inherit_doc]
infixr:67 " ::ₛ " => cons
@[simp]
theorem cons_inj_right (a : α) (s s' : Sym α n) : a ::ₛ s = a ::ₛ s' ↔ s = s' :=
Subtype.ext_iff.trans <| (Multiset.cons_inj_right _).trans Subtype.ext_iff.symm
@[simp]
theorem cons_inj_left (a a' : α) (s : Sym α n) : a ::ₛ s = a' ::ₛ s ↔ a = a' :=
Subtype.ext_iff.trans <| Multiset.cons_inj_left _
theorem cons_swap (a b : α) (s : Sym α n) : a ::ₛ b ::ₛ s = b ::ₛ a ::ₛ s :=
Subtype.ext <| Multiset.cons_swap a b s.1
theorem coe_cons (s : Sym α n) (a : α) : (a ::ₛ s : Multiset α) = a ::ₘ s :=
rfl
/-- This is the quotient map that takes a list of n elements as an n-tuple and produces an nth
symmetric power.
-/
def ofVector : List.Vector α n → Sym α n :=
fun x => ⟨↑x.val, (Multiset.coe_card _).trans x.2⟩
/-- This is the quotient map that takes a list of n elements as an n-tuple and produces an nth
symmetric power.
-/
instance : Coe (List.Vector α n) (Sym α n) where coe x := ofVector x
@[simp]
theorem ofVector_nil : ↑(Vector.nil : List.Vector α 0) = (Sym.nil : Sym α 0) :=
rfl
@[simp]
theorem ofVector_cons (a : α) (v : List.Vector α n) :
↑(Vector.cons a v) = a ::ₛ (↑v : Sym α n) := by
cases v
rfl
@[simp]
theorem card_coe : Multiset.card (s : Multiset α) = n := s.prop
/-- `α ∈ s` means that `a` appears as one of the factors in `s`.
-/
instance : Membership α (Sym α n) :=
⟨fun s a => a ∈ s.1⟩
instance decidableMem [DecidableEq α] (a : α) (s : Sym α n) : Decidable (a ∈ s) :=
s.1.decidableMem _
@[simp, norm_cast] lemma coe_mk (s : Multiset α) (h : Multiset.card s = n) : mk s h = s := rfl
@[simp]
theorem mem_mk (a : α) (s : Multiset α) (h : Multiset.card s = n) : a ∈ mk s h ↔ a ∈ s :=
Iff.rfl
lemma «forall» {p : Sym α n → Prop} :
(∀ s : Sym α n, p s) ↔ ∀ (s : Multiset α) (hs : Multiset.card s = n), p (Sym.mk s hs) := by
simp [Sym]
lemma «exists» {p : Sym α n → Prop} :
(∃ s : Sym α n, p s) ↔ ∃ (s : Multiset α) (hs : Multiset.card s = n), p (Sym.mk s hs) := by
simp [Sym]
@[simp]
theorem not_mem_nil (a : α) : ¬ a ∈ (nil : Sym α 0) :=
Multiset.not_mem_zero a
@[simp]
theorem mem_cons : a ∈ b ::ₛ s ↔ a = b ∨ a ∈ s :=
Multiset.mem_cons
@[simp]
theorem mem_coe : a ∈ (s : Multiset α) ↔ a ∈ s :=
Iff.rfl
theorem mem_cons_of_mem (h : a ∈ s) : a ∈ b ::ₛ s :=
Multiset.mem_cons_of_mem h
theorem mem_cons_self (a : α) (s : Sym α n) : a ∈ a ::ₛ s :=
Multiset.mem_cons_self a s.1
theorem cons_of_coe_eq (a : α) (v : List.Vector α n) : a ::ₛ (↑v : Sym α n) = ↑(a ::ᵥ v) :=
Subtype.ext <| by
cases v
rfl
open scoped List in
theorem sound {a b : List.Vector α n} (h : a.val ~ b.val) : (↑a : Sym α n) = ↑b :=
Subtype.ext <| Quotient.sound h
/-- `erase s a h` is the sym that subtracts 1 from the
multiplicity of `a` if a is present in the sym. -/
def erase [DecidableEq α] (s : Sym α (n + 1)) (a : α) (h : a ∈ s) : Sym α n :=
⟨s.val.erase a, (Multiset.card_erase_of_mem h).trans <| s.property.symm ▸ n.pred_succ⟩
@[simp]
theorem erase_mk [DecidableEq α] (m : Multiset α)
(hc : Multiset.card m = n + 1) (a : α) (h : a ∈ m) :
(mk m hc).erase a h =mk (m.erase a)
(by rw [Multiset.card_erase_of_mem h, hc, Nat.add_one, Nat.pred_succ]) :=
rfl
@[simp]
theorem coe_erase [DecidableEq α] {s : Sym α n.succ} {a : α} (h : a ∈ s) :
(s.erase a h : Multiset α) = Multiset.erase s a :=
rfl
@[simp]
theorem cons_erase [DecidableEq α] {s : Sym α n.succ} {a : α} (h : a ∈ s) : a ::ₛ s.erase a h = s :=
coe_injective <| Multiset.cons_erase h
@[simp]
theorem erase_cons_head [DecidableEq α] (s : Sym α n) (a : α)
(h : a ∈ a ::ₛ s := mem_cons_self a s) : (a ::ₛ s).erase a h = s :=
coe_injective <| Multiset.erase_cons_head a s.1
/-- Another definition of the nth symmetric power, using vectors modulo permutations. (See `Sym`.)
-/
def Sym' (α : Type*) (n : ℕ) :=
Quotient (Vector.Perm.isSetoid α n)
/-- This is `cons` but for the alternative `Sym'` definition.
-/
def cons' {α : Type*} {n : ℕ} : α → Sym' α n → Sym' α (Nat.succ n) := fun a =>
Quotient.map (Vector.cons a) fun ⟨_, _⟩ ⟨_, _⟩ h => List.Perm.cons _ h
@[inherit_doc]
scoped notation a " :: " b => cons' a b
/-- Multisets of cardinality n are equivalent to length-n vectors up to permutations.
-/
def symEquivSym' {α : Type*} {n : ℕ} : Sym α n ≃ Sym' α n :=
Equiv.subtypeQuotientEquivQuotientSubtype _ _ (fun _ => by rfl) fun _ _ => by rfl
theorem cons_equiv_eq_equiv_cons (α : Type*) (n : ℕ) (a : α) (s : Sym α n) :
(a::symEquivSym' s) = symEquivSym' (a ::ₛ s) := by
rcases s with ⟨⟨l⟩, _⟩
rfl
instance instZeroSym : Zero (Sym α 0) :=
⟨⟨0, rfl⟩⟩
@[simp] theorem toMultiset_zero : toMultiset (0 : Sym α 0) = 0 := rfl
instance : EmptyCollection (Sym α 0) :=
⟨0⟩
theorem eq_nil_of_card_zero (s : Sym α 0) : s = nil :=
Subtype.ext <| Multiset.card_eq_zero.1 s.2
instance uniqueZero : Unique (Sym α 0) :=
⟨⟨nil⟩, eq_nil_of_card_zero⟩
/-- `replicate n a` is the sym containing only `a` with multiplicity `n`. -/
def replicate (n : ℕ) (a : α) : Sym α n :=
⟨Multiset.replicate n a, Multiset.card_replicate _ _⟩
theorem replicate_succ {a : α} {n : ℕ} : replicate n.succ a = a ::ₛ replicate n a :=
rfl
theorem coe_replicate : (replicate n a : Multiset α) = Multiset.replicate n a :=
rfl
theorem val_replicate : (replicate n a).val = Multiset.replicate n a := by
rw [val_eq_coe, coe_replicate]
@[simp]
theorem mem_replicate : b ∈ replicate n a ↔ n ≠ 0 ∧ b = a :=
Multiset.mem_replicate
theorem eq_replicate_iff : s = replicate n a ↔ ∀ b ∈ s, b = a := by
rw [Subtype.ext_iff, val_replicate, Multiset.eq_replicate]
exact and_iff_right s.2
theorem exists_mem (s : Sym α n.succ) : ∃ a, a ∈ s :=
Multiset.card_pos_iff_exists_mem.1 <| s.2.symm ▸ n.succ_pos
theorem exists_cons_of_mem {s : Sym α (n + 1)} {a : α} (h : a ∈ s) : ∃ t, s = a ::ₛ t := by
obtain ⟨m, h⟩ := Multiset.exists_cons_of_mem h
have : Multiset.card m = n := by
apply_fun Multiset.card at h
rw [s.2, Multiset.card_cons, add_left_inj] at h
exact h.symm
use ⟨m, this⟩
apply Subtype.ext
exact h
theorem exists_eq_cons_of_succ (s : Sym α n.succ) : ∃ (a : α) (s' : Sym α n), s = a ::ₛ s' := by
obtain ⟨a, ha⟩ := exists_mem s
classical exact ⟨a, s.erase a ha, (cons_erase ha).symm⟩
theorem eq_replicate {a : α} {n : ℕ} {s : Sym α n} : s = replicate n a ↔ ∀ b ∈ s, b = a :=
Subtype.ext_iff.trans <| Multiset.eq_replicate.trans <| and_iff_right s.prop
theorem eq_replicate_of_subsingleton [Subsingleton α] (a : α) {n : ℕ} (s : Sym α n) :
s = replicate n a :=
eq_replicate.2 fun _ _ => Subsingleton.elim _ _
instance [Subsingleton α] (n : ℕ) : Subsingleton (Sym α n) :=
⟨by
cases n
· simp [eq_iff_true_of_subsingleton]
· intro s s'
obtain ⟨b, -⟩ := exists_mem s
rw [eq_replicate_of_subsingleton b s', eq_replicate_of_subsingleton b s]⟩
instance inhabitedSym [Inhabited α] (n : ℕ) : Inhabited (Sym α n) :=
⟨replicate n default⟩
instance inhabitedSym' [Inhabited α] (n : ℕ) : Inhabited (Sym' α n) :=
⟨Quotient.mk' (List.Vector.replicate n default)⟩
instance (n : ℕ) [IsEmpty α] : IsEmpty (Sym α n.succ) :=
⟨fun s => by
obtain ⟨a, -⟩ := exists_mem s
exact isEmptyElim a⟩
instance (n : ℕ) [Unique α] : Unique (Sym α n) :=
Unique.mk' _
theorem replicate_right_inj {a b : α} {n : ℕ} (h : n ≠ 0) : replicate n a = replicate n b ↔ a = b :=
Subtype.ext_iff.trans (Multiset.replicate_right_inj h)
theorem replicate_right_injective {n : ℕ} (h : n ≠ 0) :
Function.Injective (replicate n : α → Sym α n) := fun _ _ => (replicate_right_inj h).1
instance (n : ℕ) [Nontrivial α] : Nontrivial (Sym α (n + 1)) :=
(replicate_right_injective n.succ_ne_zero).nontrivial
/-- A function `α → β` induces a function `Sym α n → Sym β n` by applying it to every element of
the underlying `n`-tuple. -/
def map {n : ℕ} (f : α → β) (x : Sym α n) : Sym β n :=
⟨x.val.map f, by simp⟩
@[simp]
theorem mem_map {n : ℕ} {f : α → β} {b : β} {l : Sym α n} :
b ∈ Sym.map f l ↔ ∃ a, a ∈ l ∧ f a = b :=
Multiset.mem_map
/-- Note: `Sym.map_id` is not simp-normal, as simp ends up unfolding `id` with `Sym.map_congr` -/
@[simp]
theorem map_id' {α : Type*} {n : ℕ} (s : Sym α n) : Sym.map (fun x : α => x) s = s := by
ext; simp only [map, Multiset.map_id', ← val_eq_coe]
theorem map_id {α : Type*} {n : ℕ} (s : Sym α n) : Sym.map id s = s := by
ext; simp only [map, id_eq, Multiset.map_id', ← val_eq_coe]
@[simp]
theorem map_map {α β γ : Type*} {n : ℕ} (g : β → γ) (f : α → β) (s : Sym α n) :
Sym.map g (Sym.map f s) = Sym.map (g ∘ f) s :=
Subtype.ext <| by dsimp only [Sym.map]; simp
@[simp]
theorem map_zero (f : α → β) : Sym.map f (0 : Sym α 0) = (0 : Sym β 0) :=
rfl
@[simp]
theorem map_cons {n : ℕ} (f : α → β) (a : α) (s : Sym α n) : (a ::ₛ s).map f = f a ::ₛ s.map f :=
ext <| Multiset.map_cons _ _ _
@[congr]
theorem map_congr {f g : α → β} {s : Sym α n} (h : ∀ x ∈ s, f x = g x) : map f s = map g s :=
Subtype.ext <| Multiset.map_congr rfl h
@[simp]
theorem map_mk {f : α → β} {m : Multiset α} {hc : Multiset.card m = n} :
map f (mk m hc) = mk (m.map f) (by simp [hc]) :=
rfl
@[simp]
theorem coe_map (s : Sym α n) (f : α → β) : ↑(s.map f) = Multiset.map f s :=
rfl
theorem map_injective {f : α → β} (hf : Injective f) (n : ℕ) :
Injective (map f : Sym α n → Sym β n) := fun _ _ h =>
coe_injective <| Multiset.map_injective hf <| coe_inj.2 h
/-- Mapping an equivalence `α ≃ β` using `Sym.map` gives an equivalence between `Sym α n` and
`Sym β n`. -/
@[simps]
def equivCongr (e : α ≃ β) : Sym α n ≃ Sym β n where
toFun := map e
invFun := map e.symm
left_inv x := by rw [map_map, Equiv.symm_comp_self, map_id]
right_inv x := by rw [map_map, Equiv.self_comp_symm, map_id]
/-- "Attach" a proof that `a ∈ s` to each element `a` in `s` to produce
an element of the symmetric power on `{x // x ∈ s}`. -/
def attach (s : Sym α n) : Sym { x // x ∈ s } n :=
⟨s.val.attach, by (conv_rhs => rw [← s.2, ← Multiset.card_attach])⟩
@[simp]
theorem attach_mk {m : Multiset α} {hc : Multiset.card m = n} :
attach (mk m hc) = mk m.attach (Multiset.card_attach.trans hc) :=
rfl
@[simp]
theorem coe_attach (s : Sym α n) : (s.attach : Multiset { a // a ∈ s }) =
Multiset.attach (s : Multiset α) :=
rfl
theorem attach_map_coe (s : Sym α n) : s.attach.map (↑) = s :=
coe_injective <| Multiset.attach_map_val _
@[simp]
theorem mem_attach (s : Sym α n) (x : { x // x ∈ s }) : x ∈ s.attach :=
Multiset.mem_attach _ _
@[simp]
theorem attach_nil : (nil : Sym α 0).attach = nil :=
rfl
@[simp]
theorem attach_cons (x : α) (s : Sym α n) :
(cons x s).attach =
cons ⟨x, mem_cons_self _ _⟩ (s.attach.map fun x => ⟨x, mem_cons_of_mem x.prop⟩) :=
coe_injective <| Multiset.attach_cons _ _
/-- Change the length of a `Sym` using an equality.
The simp-normal form is for the `cast` to be pushed outward. -/
protected def cast {n m : ℕ} (h : n = m) : Sym α n ≃ Sym α m where
toFun s := ⟨s.val, s.2.trans h⟩
invFun s := ⟨s.val, s.2.trans h.symm⟩
left_inv _ := Subtype.ext rfl
right_inv _ := Subtype.ext rfl
@[simp]
theorem cast_rfl : Sym.cast rfl s = s :=
Subtype.ext rfl
@[simp]
theorem cast_cast {n'' : ℕ} (h : n = n') (h' : n' = n'') :
Sym.cast h' (Sym.cast h s) = Sym.cast (h.trans h') s :=
rfl
@[simp]
theorem coe_cast (h : n = m) : (Sym.cast h s : Multiset α) = s :=
rfl
@[simp]
theorem mem_cast (h : n = m) : a ∈ Sym.cast h s ↔ a ∈ s :=
Iff.rfl
/-- Append a pair of `Sym` terms. -/
def append (s : Sym α n) (s' : Sym α n') : Sym α (n + n') :=
⟨s.1 + s'.1, by rw [Multiset.card_add, s.2, s'.2]⟩
@[simp]
theorem append_inj_right (s : Sym α n) {t t' : Sym α n'} : s.append t = s.append t' ↔ t = t' :=
Subtype.ext_iff.trans <| (add_right_inj _).trans Subtype.ext_iff.symm
@[simp]
theorem append_inj_left {s s' : Sym α n} (t : Sym α n') : s.append t = s'.append t ↔ s = s' :=
Subtype.ext_iff.trans <| (add_left_inj _).trans Subtype.ext_iff.symm
theorem append_comm (s : Sym α n') (s' : Sym α n') :
s.append s' = Sym.cast (add_comm _ _) (s'.append s) := by
ext
simp [append, add_comm]
@[simp, norm_cast]
theorem coe_append (s : Sym α n) (s' : Sym α n') : (s.append s' : Multiset α) = s + s' :=
rfl
theorem mem_append_iff {s' : Sym α m} : a ∈ s.append s' ↔ a ∈ s ∨ a ∈ s' :=
Multiset.mem_add
/-- `a ↦ {a}` as an equivalence between `α` and `Sym α 1`. -/
@[simps apply]
def oneEquiv : α ≃ Sym α 1 where
toFun a := ⟨{a}, by simp⟩
invFun s := (Equiv.subtypeQuotientEquivQuotientSubtype
(·.length = 1) _ (fun _ ↦ Iff.rfl) (fun l l' ↦ by rfl) s).liftOn
(fun l ↦ l.1.head <| List.length_pos_iff.mp <| by simp)
fun ⟨_, _⟩ ⟨_, h⟩ ↦ fun perm ↦ by
obtain ⟨a, rfl⟩ := List.length_eq_one_iff.mp h
exact List.eq_of_mem_singleton (perm.mem_iff.mp <| List.head_mem _)
left_inv a := by rfl
right_inv := by rintro ⟨⟨l⟩, h⟩; obtain ⟨a, rfl⟩ := List.length_eq_one_iff.mp h; rfl
/-- Fill a term `m : Sym α (n - i)` with `i` copies of `a` to obtain a term of `Sym α n`.
This is a convenience wrapper for `m.append (replicate i a)` that adjusts the term using
`Sym.cast`. -/
def fill (a : α) (i : Fin (n + 1)) (m : Sym α (n - i)) : Sym α n :=
Sym.cast (Nat.sub_add_cancel i.is_le) (m.append (replicate i a))
theorem coe_fill {a : α} {i : Fin (n + 1)} {m : Sym α (n - i)} :
(fill a i m : Multiset α) = m + replicate i a :=
rfl
theorem mem_fill_iff {a b : α} {i : Fin (n + 1)} {s : Sym α (n - i)} :
a ∈ Sym.fill b i s ↔ (i : ℕ) ≠ 0 ∧ a = b ∨ a ∈ s := by
rw [fill, mem_cast, mem_append_iff, or_comm, mem_replicate]
open Multiset
/-- Remove every `a` from a given `Sym α n`.
Yields the number of copies `i` and a term of `Sym α (n - i)`. -/
def filterNe [DecidableEq α] (a : α) (m : Sym α n) : Σ i : Fin (n + 1), Sym α (n - i) :=
⟨⟨m.1.count a, (count_le_card _ _).trans_lt <| by rw [m.2, Nat.lt_succ_iff]⟩,
m.1.filter (a ≠ ·),
Nat.eq_sub_of_add_eq <|
Eq.trans
(by
rw [← countP_eq_card_filter, add_comm]
simp only [eq_comm, Ne, count]
rw [← card_eq_countP_add_countP _ _])
m.2⟩
theorem sigma_sub_ext {m₁ m₂ : Σ i : Fin (n + 1), Sym α (n - i)} (h : (m₁.2 : Multiset α) = m₂.2) :
m₁ = m₂ :=
Sigma.subtype_ext
(Fin.ext <| by
rw [← Nat.sub_sub_self (Nat.le_of_lt_succ m₁.1.is_lt), ← m₁.2.2, val_eq_coe, h,
← val_eq_coe, m₂.2.2, Nat.sub_sub_self (Nat.le_of_lt_succ m₂.1.is_lt)])
h
theorem fill_filterNe [DecidableEq α] (a : α) (m : Sym α n) :
(m.filterNe a).2.fill a (m.filterNe a).1 = m :=
Sym.ext
(by
rw [coe_fill, filterNe, ← val_eq_coe, Subtype.coe_mk, Fin.val_mk]
ext b; dsimp
rw [count_add, count_filter, Sym.coe_replicate, count_replicate]
obtain rfl | h := eq_or_ne a b
· rw [if_pos rfl, if_neg (not_not.2 rfl), zero_add]
· rw [if_pos h, if_neg h, add_zero])
theorem filter_ne_fill
[DecidableEq α] (a : α) (m : Σ i : Fin (n + 1), Sym α (n - i)) (h : a ∉ m.2) :
(m.2.fill a m.1).filterNe a = m :=
sigma_sub_ext
(by
rw [filterNe, ← val_eq_coe, Subtype.coe_mk, val_eq_coe, coe_fill]
rw [filter_add, filter_eq_self.2, add_eq_left, eq_zero_iff_forall_not_mem]
· intro b hb
rw [mem_filter, Sym.mem_coe, mem_replicate] at hb
exact hb.2 hb.1.2.symm
· exact fun a ha ha' => h <| ha'.symm ▸ ha)
theorem count_coe_fill_self_of_not_mem [DecidableEq α] {a : α} {i : Fin (n + 1)} {s : Sym α (n - i)}
(hx : a ∉ s) :
count a (fill a i s : Multiset α) = i := by
simp [coe_fill, coe_replicate, hx]
theorem count_coe_fill_of_ne [DecidableEq α] {a x : α} {i : Fin (n + 1)} {s : Sym α (n - i)}
(hx : x ≠ a) :
count x (fill a i s : Multiset α) = count x s := by
suffices x ∉ Multiset.replicate i a by simp [coe_fill, coe_replicate, this]
simp [Multiset.mem_replicate, hx]
end Sym
section Equiv
/-! ### Combinatorial equivalences -/
variable {α : Type*} {n : ℕ}
open Sym
namespace SymOptionSuccEquiv
| /-- Function from the symmetric product over `Option` splitting on whether or not
it contains a `none`. -/
def encode [DecidableEq α] (s : Sym (Option α) n.succ) : Sym (Option α) n ⊕ Sym α n.succ :=
if h : none ∈ s then Sum.inl (s.erase none h)
else
Sum.inr
(s.attach.map fun o =>
| Mathlib/Data/Sym/Basic.lean | 573 | 579 |
/-
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.SetTheory.Cardinal.Finite
import Mathlib.Data.Set.Finite.Powerset
/-!
# Noncomputable Set Cardinality
We define the cardinality of set `s` as a term `Set.encard s : ℕ∞` and a term `Set.ncard s : ℕ`.
The latter takes the junk value of zero if `s` is infinite. Both functions are noncomputable, and
are defined in terms of `ENat.card` (which takes a type as its argument); this file can be seen
as an API for the same function in the special case where the type is a coercion of a `Set`,
allowing for smoother interactions with the `Set` API.
`Set.encard` never takes junk values, so is more mathematically natural than `Set.ncard`, even
though it takes values in a less convenient type. It is probably the right choice in settings where
one is concerned with the cardinalities of sets that may or may not be infinite.
`Set.ncard` has a nicer codomain, but when using it, `Set.Finite` hypotheses are normally needed to
make sure its values are meaningful. More generally, `Set.ncard` is intended to be used over the
obvious alternative `Finset.card` when finiteness is 'propositional' rather than 'structural'.
When working with sets that are finite by virtue of their definition, then `Finset.card` probably
makes more sense. One setting where `Set.ncard` works nicely is in a type `α` with `[Finite α]`,
where every set is automatically finite. In this setting, we use default arguments and a simple
tactic so that finiteness goals are discharged automatically in `Set.ncard` theorems.
## Main Definitions
* `Set.encard s` is the cardinality of the set `s` as an extended natural number, with value `⊤` if
`s` is infinite.
* `Set.ncard s` is the cardinality of the set `s` as a natural number, provided `s` is Finite.
If `s` is Infinite, then `Set.ncard s = 0`.
* `toFinite_tac` is a tactic that tries to synthesize a `Set.Finite s` argument with
`Set.toFinite`. This will work for `s : Set α` where there is a `Finite α` instance.
## Implementation Notes
The theorems in this file are very similar to those in `Data.Finset.Card`, but with `Set` operations
instead of `Finset`. We first prove all the theorems for `Set.encard`, and then derive most of the
`Set.ncard` results as a consequence. Things are done this way to avoid reliance on the `Finset` API
for theorems about infinite sets, and to allow for a refactor that removes or modifies `Set.ncard`
in the future.
Nearly all the theorems for `Set.ncard` require finiteness of one or more of their arguments. We
provide this assumption with a default argument of the form `(hs : s.Finite := by toFinite_tac)`,
where `toFinite_tac` will find an `s.Finite` term in the cases where `s` is a set in a `Finite`
type.
Often, where there are two set arguments `s` and `t`, the finiteness of one follows from the other
in the context of the theorem, in which case we only include the ones that are needed, and derive
the other inside the proof. A few of the theorems, such as `ncard_union_le` do not require
finiteness arguments; they are true by coincidence due to junk values.
-/
namespace Set
variable {α β : Type*} {s t : Set α}
/-- The cardinality of a set as a term in `ℕ∞` -/
noncomputable def encard (s : Set α) : ℕ∞ := ENat.card s
@[simp] theorem encard_univ_coe (s : Set α) : encard (univ : Set s) = encard s := by
rw [encard, encard, ENat.card_congr (Equiv.Set.univ ↑s)]
theorem encard_univ (α : Type*) :
encard (univ : Set α) = ENat.card α := by
rw [encard, ENat.card_congr (Equiv.Set.univ α)]
theorem Finite.encard_eq_coe_toFinset_card (h : s.Finite) : s.encard = h.toFinset.card := by
have := h.fintype
rw [encard, ENat.card_eq_coe_fintype_card, toFinite_toFinset, toFinset_card]
theorem encard_eq_coe_toFinset_card (s : Set α) [Fintype s] : encard s = s.toFinset.card := by
have h := toFinite s
rw [h.encard_eq_coe_toFinset_card, toFinite_toFinset]
@[simp] theorem toENat_cardinalMk (s : Set α) : (Cardinal.mk s).toENat = s.encard := rfl
theorem toENat_cardinalMk_subtype (P : α → Prop) :
(Cardinal.mk {x // P x}).toENat = {x | P x}.encard :=
rfl
@[simp] theorem coe_fintypeCard (s : Set α) [Fintype s] : Fintype.card s = s.encard := by
simp [encard_eq_coe_toFinset_card]
@[simp, norm_cast] theorem encard_coe_eq_coe_finsetCard (s : Finset α) :
encard (s : Set α) = s.card := by
rw [Finite.encard_eq_coe_toFinset_card (Finset.finite_toSet s)]; simp
@[simp] theorem Infinite.encard_eq {s : Set α} (h : s.Infinite) : s.encard = ⊤ := by
have := h.to_subtype
rw [encard, ENat.card_eq_top_of_infinite]
@[simp] theorem encard_eq_zero : s.encard = 0 ↔ s = ∅ := by
rw [encard, ENat.card_eq_zero_iff_empty, isEmpty_subtype, eq_empty_iff_forall_not_mem]
@[simp] theorem encard_empty : (∅ : Set α).encard = 0 := by
rw [encard_eq_zero]
theorem nonempty_of_encard_ne_zero (h : s.encard ≠ 0) : s.Nonempty := by
rwa [nonempty_iff_ne_empty, Ne, ← encard_eq_zero]
theorem encard_ne_zero : s.encard ≠ 0 ↔ s.Nonempty := by
rw [ne_eq, encard_eq_zero, nonempty_iff_ne_empty]
@[simp] theorem encard_pos : 0 < s.encard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, encard_ne_zero]
protected alias ⟨_, Nonempty.encard_pos⟩ := encard_pos
@[simp] theorem encard_singleton (e : α) : ({e} : Set α).encard = 1 := by
rw [encard, ENat.card_eq_coe_fintype_card, Fintype.card_ofSubsingleton, Nat.cast_one]
theorem encard_union_eq (h : Disjoint s t) : (s ∪ t).encard = s.encard + t.encard := by
classical
simp [encard, ENat.card_congr (Equiv.Set.union h)]
theorem encard_insert_of_not_mem {a : α} (has : a ∉ s) : (insert a s).encard = s.encard + 1 := by
rw [← union_singleton, encard_union_eq (by simpa), encard_singleton]
theorem Finite.encard_lt_top (h : s.Finite) : s.encard < ⊤ := by
induction s, h using Set.Finite.induction_on with
| empty => simp
| insert hat _ ht' =>
rw [encard_insert_of_not_mem hat]
exact lt_tsub_iff_right.1 ht'
theorem Finite.encard_eq_coe (h : s.Finite) : s.encard = ENat.toNat s.encard :=
(ENat.coe_toNat h.encard_lt_top.ne).symm
theorem Finite.exists_encard_eq_coe (h : s.Finite) : ∃ (n : ℕ), s.encard = n :=
⟨_, h.encard_eq_coe⟩
@[simp] theorem encard_lt_top_iff : s.encard < ⊤ ↔ s.Finite :=
⟨fun h ↦ by_contra fun h' ↦ h.ne (Infinite.encard_eq h'), Finite.encard_lt_top⟩
@[simp] theorem encard_eq_top_iff : s.encard = ⊤ ↔ s.Infinite := by
rw [← not_iff_not, ← Ne, ← lt_top_iff_ne_top, encard_lt_top_iff, not_infinite]
alias ⟨_, encard_eq_top⟩ := encard_eq_top_iff
theorem encard_ne_top_iff : s.encard ≠ ⊤ ↔ s.Finite := by
simp
theorem finite_of_encard_le_coe {k : ℕ} (h : s.encard ≤ k) : s.Finite := by
rw [← encard_lt_top_iff]; exact h.trans_lt (WithTop.coe_lt_top _)
theorem finite_of_encard_eq_coe {k : ℕ} (h : s.encard = k) : s.Finite :=
finite_of_encard_le_coe h.le
theorem encard_le_coe_iff {k : ℕ} : s.encard ≤ k ↔ s.Finite ∧ ∃ (n₀ : ℕ), s.encard = n₀ ∧ n₀ ≤ k :=
⟨fun h ↦ ⟨finite_of_encard_le_coe h, by rwa [ENat.le_coe_iff] at h⟩,
fun ⟨_,⟨n₀,hs, hle⟩⟩ ↦ by rwa [hs, Nat.cast_le]⟩
@[simp]
theorem encard_prod : (s ×ˢ t).encard = s.encard * t.encard := by
simp [Set.encard, ENat.card_congr (Equiv.Set.prod ..)]
section Lattice
theorem encard_le_encard (h : s ⊆ t) : s.encard ≤ t.encard := by
rw [← union_diff_cancel h, encard_union_eq disjoint_sdiff_right]; exact le_self_add
@[deprecated (since := "2025-01-05")] alias encard_le_card := encard_le_encard
theorem encard_mono {α : Type*} : Monotone (encard : Set α → ℕ∞) :=
fun _ _ ↦ encard_le_encard
theorem encard_diff_add_encard_of_subset (h : s ⊆ t) : (t \ s).encard + s.encard = t.encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self, union_eq_self_of_subset_right h]
@[simp] theorem one_le_encard_iff_nonempty : 1 ≤ s.encard ↔ s.Nonempty := by
rw [nonempty_iff_ne_empty, Ne, ← encard_eq_zero, ENat.one_le_iff_ne_zero]
theorem encard_diff_add_encard_inter (s t : Set α) :
(s \ t).encard + (s ∩ t).encard = s.encard := by
rw [← encard_union_eq (disjoint_of_subset_right inter_subset_right disjoint_sdiff_left),
diff_union_inter]
theorem encard_union_add_encard_inter (s t : Set α) :
(s ∪ t).encard + (s ∩ t).encard = s.encard + t.encard := by
rw [← diff_union_self, encard_union_eq disjoint_sdiff_left, add_right_comm,
encard_diff_add_encard_inter]
theorem encard_eq_encard_iff_encard_diff_eq_encard_diff (h : (s ∩ t).Finite) :
s.encard = t.encard ↔ (s \ t).encard = (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_right_inj h.encard_lt_top.ne]
theorem encard_le_encard_iff_encard_diff_le_encard_diff (h : (s ∩ t).Finite) :
s.encard ≤ t.encard ↔ (s \ t).encard ≤ (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_le_add_iff_right h.encard_lt_top.ne]
theorem encard_lt_encard_iff_encard_diff_lt_encard_diff (h : (s ∩ t).Finite) :
s.encard < t.encard ↔ (s \ t).encard < (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_lt_add_iff_right h.encard_lt_top.ne]
theorem encard_union_le (s t : Set α) : (s ∪ t).encard ≤ s.encard + t.encard := by
rw [← encard_union_add_encard_inter]; exact le_self_add
theorem finite_iff_finite_of_encard_eq_encard (h : s.encard = t.encard) : s.Finite ↔ t.Finite := by
rw [← encard_lt_top_iff, ← encard_lt_top_iff, h]
theorem infinite_iff_infinite_of_encard_eq_encard (h : s.encard = t.encard) :
s.Infinite ↔ t.Infinite := by rw [← encard_eq_top_iff, h, encard_eq_top_iff]
theorem Finite.finite_of_encard_le {s : Set α} {t : Set β} (hs : s.Finite)
(h : t.encard ≤ s.encard) : t.Finite :=
encard_lt_top_iff.1 (h.trans_lt hs.encard_lt_top)
lemma Finite.eq_of_subset_of_encard_le' (ht : t.Finite) (hst : s ⊆ t) (hts : t.encard ≤ s.encard) :
s = t := by
rw [← zero_add (a := encard s), ← encard_diff_add_encard_of_subset hst] at hts
have hdiff := WithTop.le_of_add_le_add_right (ht.subset hst).encard_lt_top.ne hts
rw [nonpos_iff_eq_zero, encard_eq_zero, diff_eq_empty] at hdiff
exact hst.antisymm hdiff
theorem Finite.eq_of_subset_of_encard_le (hs : s.Finite) (hst : s ⊆ t)
(hts : t.encard ≤ s.encard) : s = t :=
(hs.finite_of_encard_le hts).eq_of_subset_of_encard_le' hst hts
theorem Finite.encard_lt_encard (hs : s.Finite) (h : s ⊂ t) : s.encard < t.encard :=
(encard_mono h.subset).lt_of_ne fun he ↦ h.ne (hs.eq_of_subset_of_encard_le h.subset he.symm.le)
theorem encard_strictMono [Finite α] : StrictMono (encard : Set α → ℕ∞) :=
fun _ _ h ↦ (toFinite _).encard_lt_encard h
theorem encard_diff_add_encard (s t : Set α) : (s \ t).encard + t.encard = (s ∪ t).encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self]
theorem encard_le_encard_diff_add_encard (s t : Set α) : s.encard ≤ (s \ t).encard + t.encard :=
(encard_mono subset_union_left).trans_eq (encard_diff_add_encard _ _).symm
theorem tsub_encard_le_encard_diff (s t : Set α) : s.encard - t.encard ≤ (s \ t).encard := by
rw [tsub_le_iff_left, add_comm]; apply encard_le_encard_diff_add_encard
theorem encard_add_encard_compl (s : Set α) : s.encard + sᶜ.encard = (univ : Set α).encard := by
rw [← encard_union_eq disjoint_compl_right, union_compl_self]
end Lattice
section InsertErase
variable {a b : α}
theorem encard_insert_le (s : Set α) (x : α) : (insert x s).encard ≤ s.encard + 1 := by
rw [← union_singleton, ← encard_singleton x]; apply encard_union_le
theorem encard_singleton_inter (s : Set α) (x : α) : ({x} ∩ s).encard ≤ 1 := by
rw [← encard_singleton x]; exact encard_le_encard inter_subset_left
theorem encard_diff_singleton_add_one (h : a ∈ s) :
(s \ {a}).encard + 1 = s.encard := by
rw [← encard_insert_of_not_mem (fun h ↦ h.2 rfl), insert_diff_singleton, insert_eq_of_mem h]
theorem encard_diff_singleton_of_mem (h : a ∈ s) :
(s \ {a}).encard = s.encard - 1 := by
rw [← encard_diff_singleton_add_one h, ← WithTop.add_right_inj WithTop.one_ne_top,
tsub_add_cancel_of_le (self_le_add_left _ _)]
theorem encard_tsub_one_le_encard_diff_singleton (s : Set α) (x : α) :
s.encard - 1 ≤ (s \ {x}).encard := by
rw [← encard_singleton x]; apply tsub_encard_le_encard_diff
theorem encard_exchange (ha : a ∉ s) (hb : b ∈ s) : (insert a (s \ {b})).encard = s.encard := by
rw [encard_insert_of_not_mem, encard_diff_singleton_add_one hb]
simp_all only [not_true, mem_diff, mem_singleton_iff, false_and, not_false_eq_true]
theorem encard_exchange' (ha : a ∉ s) (hb : b ∈ s) : (insert a s \ {b}).encard = s.encard := by
rw [← insert_diff_singleton_comm (by rintro rfl; exact ha hb), encard_exchange ha hb]
theorem encard_eq_add_one_iff {k : ℕ∞} :
s.encard = k + 1 ↔ (∃ a t, ¬a ∈ t ∧ insert a t = s ∧ t.encard = k) := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, ha⟩ := nonempty_of_encard_ne_zero (s := s) (by simp [h])
refine ⟨a, s \ {a}, fun h ↦ h.2 rfl, by rwa [insert_diff_singleton, insert_eq_of_mem], ?_⟩
rw [← WithTop.add_right_inj WithTop.one_ne_top, ← h,
encard_diff_singleton_add_one ha]
rintro ⟨a, t, h, rfl, rfl⟩
rw [encard_insert_of_not_mem h]
/-- Every set is either empty, infinite, or can have its `encard` reduced by a removal. Intended
for well-founded induction on the value of `encard`. -/
theorem eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt (s : Set α) :
s = ∅ ∨ s.encard = ⊤ ∨ ∃ a ∈ s, (s \ {a}).encard < s.encard := by
refine s.eq_empty_or_nonempty.elim Or.inl (Or.inr ∘ fun ⟨a,ha⟩ ↦
(s.finite_or_infinite.elim (fun hfin ↦ Or.inr ⟨a, ha, ?_⟩) (Or.inl ∘ Infinite.encard_eq)))
rw [← encard_diff_singleton_add_one ha]; nth_rw 1 [← add_zero (encard _)]
exact WithTop.add_lt_add_left hfin.diff.encard_lt_top.ne zero_lt_one
end InsertErase
section SmallSets
theorem encard_pair {x y : α} (hne : x ≠ y) : ({x, y} : Set α).encard = 2 := by
rw [encard_insert_of_not_mem (by simpa), ← one_add_one_eq_two,
WithTop.add_right_inj WithTop.one_ne_top, encard_singleton]
theorem encard_eq_one : s.encard = 1 ↔ ∃ x, s = {x} := by
refine ⟨fun h ↦ ?_, fun ⟨x, hx⟩ ↦ by rw [hx, encard_singleton]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
exact ⟨x, ((finite_singleton x).eq_of_subset_of_encard_le (by simpa) (by simp [h])).symm⟩
theorem encard_le_one_iff_eq : s.encard ≤ 1 ↔ s = ∅ ∨ ∃ x, s = {x} := by
rw [le_iff_lt_or_eq, lt_iff_not_le, ENat.one_le_iff_ne_zero, not_not, encard_eq_zero,
encard_eq_one]
theorem encard_le_one_iff : s.encard ≤ 1 ↔ ∀ a b, a ∈ s → b ∈ s → a = b := by
rw [encard_le_one_iff_eq, or_iff_not_imp_left, ← Ne, ← nonempty_iff_ne_empty]
refine ⟨fun h a b has hbs ↦ ?_,
fun h ⟨x, hx⟩ ↦ ⟨x, ((singleton_subset_iff.2 hx).antisymm' (fun y hy ↦ h _ _ hy hx))⟩⟩
obtain ⟨x, rfl⟩ := h ⟨_, has⟩
rw [(has : a = x), (hbs : b = x)]
theorem encard_le_one_iff_subsingleton : s.encard ≤ 1 ↔ s.Subsingleton := by
rw [encard_le_one_iff, Set.Subsingleton]
tauto
theorem one_lt_encard_iff_nontrivial : 1 < s.encard ↔ s.Nontrivial := by
rw [← not_iff_not, not_lt, Set.not_nontrivial_iff, ← encard_le_one_iff_subsingleton]
theorem one_lt_encard_iff : 1 < s.encard ↔ ∃ a b, a ∈ s ∧ b ∈ s ∧ a ≠ b := by
rw [← not_iff_not, not_exists, not_lt, encard_le_one_iff]; aesop
theorem exists_ne_of_one_lt_encard (h : 1 < s.encard) (a : α) : ∃ b ∈ s, b ≠ a := by
by_contra! h'
obtain ⟨b, b', hb, hb', hne⟩ := one_lt_encard_iff.1 h
apply hne
rw [h' b hb, h' b' hb']
theorem encard_eq_two : s.encard = 2 ↔ ∃ x y, x ≠ y ∧ s = {x, y} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, hne, hs⟩ ↦ by rw [hs, encard_pair hne]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton, encard_insert_of_not_mem (fun h ↦ h.2 rfl),
← one_add_one_eq_two, WithTop.add_right_inj (WithTop.one_ne_top), encard_eq_one] at h
obtain ⟨y, h⟩ := h
refine ⟨x, y, by rintro rfl; exact (h.symm.subset rfl).2 rfl, ?_⟩
rw [← h, insert_diff_singleton, insert_eq_of_mem hx]
theorem encard_eq_three {α : Type u_1} {s : Set α} :
encard s = 3 ↔ ∃ x y z, x ≠ y ∧ x ≠ z ∧ y ≠ z ∧ s = {x, y, z} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, z, hxy, hyz, hxz, hs⟩ ↦ ?_⟩
· obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton,
encard_insert_of_not_mem (fun h ↦ h.2 rfl), (by exact rfl : (3 : ℕ∞) = 2 + 1),
WithTop.add_right_inj WithTop.one_ne_top, encard_eq_two] at h
obtain ⟨y, z, hne, hs⟩ := h
refine ⟨x, y, z, ?_, ?_, hne, ?_⟩
· rintro rfl; exact (hs.symm.subset (Or.inl rfl)).2 rfl
· rintro rfl; exact (hs.symm.subset (Or.inr rfl)).2 rfl
rw [← hs, insert_diff_singleton, insert_eq_of_mem hx]
rw [hs, encard_insert_of_not_mem, encard_insert_of_not_mem, encard_singleton] <;> aesop
theorem Nat.encard_range (k : ℕ) : {i | i < k}.encard = k := by
convert encard_coe_eq_coe_finsetCard (Finset.range k) using 1
· rw [Finset.coe_range, Iio_def]
rw [Finset.card_range]
end SmallSets
theorem Finite.eq_insert_of_subset_of_encard_eq_succ (hs : s.Finite) (h : s ⊆ t)
(hst : t.encard = s.encard + 1) : ∃ a, t = insert a s := by
rw [← encard_diff_add_encard_of_subset h, add_comm, WithTop.add_left_inj hs.encard_lt_top.ne,
encard_eq_one] at hst
obtain ⟨x, hx⟩ := hst; use x; rw [← diff_union_of_subset h, hx, singleton_union]
theorem exists_subset_encard_eq {k : ℕ∞} (hk : k ≤ s.encard) : ∃ t, t ⊆ s ∧ t.encard = k := by
revert hk
refine ENat.nat_induction k (fun _ ↦ ⟨∅, empty_subset _, by simp⟩) (fun n IH hle ↦ ?_) ?_
· obtain ⟨t₀, ht₀s, ht₀⟩ := IH (le_trans (by simp) hle)
simp only [Nat.cast_succ] at *
have hne : t₀ ≠ s := by
rintro rfl; rw [ht₀, ← Nat.cast_one, ← Nat.cast_add, Nat.cast_le] at hle; simp at hle
obtain ⟨x, hx⟩ := exists_of_ssubset (ht₀s.ssubset_of_ne hne)
exact ⟨insert x t₀, insert_subset hx.1 ht₀s, by rw [encard_insert_of_not_mem hx.2, ht₀]⟩
simp only [top_le_iff, encard_eq_top_iff]
exact fun _ hi ↦ ⟨s, Subset.rfl, hi⟩
theorem exists_superset_subset_encard_eq {k : ℕ∞}
(hst : s ⊆ t) (hsk : s.encard ≤ k) (hkt : k ≤ t.encard) :
∃ r, s ⊆ r ∧ r ⊆ t ∧ r.encard = k := by
obtain (hs | hs) := eq_or_ne s.encard ⊤
· rw [hs, top_le_iff] at hsk; subst hsk; exact ⟨s, Subset.rfl, hst, hs⟩
obtain ⟨k, rfl⟩ := exists_add_of_le hsk
obtain ⟨k', hk'⟩ := exists_add_of_le hkt
have hk : k ≤ encard (t \ s) := by
rw [← encard_diff_add_encard_of_subset hst, add_comm] at hkt
exact WithTop.le_of_add_le_add_right hs hkt
obtain ⟨r', hr', rfl⟩ := exists_subset_encard_eq hk
refine ⟨s ∪ r', subset_union_left, union_subset hst (hr'.trans diff_subset), ?_⟩
rw [encard_union_eq (disjoint_of_subset_right hr' disjoint_sdiff_right)]
section Function
variable {s : Set α} {t : Set β} {f : α → β}
theorem InjOn.encard_image (h : InjOn f s) : (f '' s).encard = s.encard := by
rw [encard, ENat.card_image_of_injOn h, encard]
theorem encard_congr (e : s ≃ t) : s.encard = t.encard := by
rw [← encard_univ_coe, ← encard_univ_coe t, encard_univ, encard_univ, ENat.card_congr e]
theorem _root_.Function.Injective.encard_image (hf : f.Injective) (s : Set α) :
(f '' s).encard = s.encard :=
hf.injOn.encard_image
theorem _root_.Function.Embedding.encard_le (e : s ↪ t) : s.encard ≤ t.encard := by
rw [← encard_univ_coe, ← e.injective.encard_image, ← Subtype.coe_injective.encard_image]
exact encard_mono (by simp)
theorem encard_image_le (f : α → β) (s : Set α) : (f '' s).encard ≤ s.encard := by
obtain (h | h) := isEmpty_or_nonempty α
· rw [s.eq_empty_of_isEmpty]; simp
rw [← (f.invFunOn_injOn_image s).encard_image]
apply encard_le_encard
exact f.invFunOn_image_image_subset s
theorem Finite.injOn_of_encard_image_eq (hs : s.Finite) (h : (f '' s).encard = s.encard) :
InjOn f s := by
obtain (h' | hne) := isEmpty_or_nonempty α
· rw [s.eq_empty_of_isEmpty]; simp
rw [← (f.invFunOn_injOn_image s).encard_image] at h
rw [injOn_iff_invFunOn_image_image_eq_self]
exact hs.eq_of_subset_of_encard_le' (f.invFunOn_image_image_subset s) h.symm.le
theorem encard_preimage_of_injective_subset_range (hf : f.Injective) (ht : t ⊆ range f) :
(f ⁻¹' t).encard = t.encard := by
rw [← hf.encard_image, image_preimage_eq_inter_range, inter_eq_self_of_subset_left ht]
lemma encard_preimage_of_bijective (hf : f.Bijective) (t : Set β) : (f ⁻¹' t).encard = t.encard :=
encard_preimage_of_injective_subset_range hf.injective (by simp [hf.surjective.range_eq])
theorem encard_le_encard_of_injOn (hf : MapsTo f s t) (f_inj : InjOn f s) :
s.encard ≤ t.encard := by
rw [← f_inj.encard_image]; apply encard_le_encard; rintro _ ⟨x, hx, rfl⟩; exact hf hx
theorem Finite.exists_injOn_of_encard_le [Nonempty β] {s : Set α} {t : Set β} (hs : s.Finite)
(hle : s.encard ≤ t.encard) : ∃ (f : α → β), s ⊆ f ⁻¹' t ∧ InjOn f s := by
classical
obtain (rfl | h | ⟨a, has, -⟩) := s.eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt
· simp
· exact (encard_ne_top_iff.mpr hs h).elim
obtain ⟨b, hbt⟩ := encard_pos.1 ((encard_pos.2 ⟨_, has⟩).trans_le hle)
have hle' : (s \ {a}).encard ≤ (t \ {b}).encard := by
rwa [← WithTop.add_le_add_iff_right WithTop.one_ne_top,
encard_diff_singleton_add_one has, encard_diff_singleton_add_one hbt]
obtain ⟨f₀, hf₀s, hinj⟩ := exists_injOn_of_encard_le hs.diff hle'
simp only [preimage_diff, subset_def, mem_diff, mem_singleton_iff, mem_preimage, and_imp] at hf₀s
use Function.update f₀ a b
rw [← insert_eq_of_mem has, ← insert_diff_singleton, injOn_insert (fun h ↦ h.2 rfl)]
simp only [mem_diff, mem_singleton_iff, not_true, and_false, insert_diff_singleton, subset_def,
mem_insert_iff, mem_preimage, ne_eq, Function.update_apply, forall_eq_or_imp, ite_true, and_imp,
mem_image, ite_eq_left_iff, not_exists, not_and, not_forall, exists_prop, and_iff_right hbt]
refine ⟨?_, ?_, fun x hxs hxa ↦ ⟨hxa, (hf₀s x hxs hxa).2⟩⟩
· rintro x hx; split_ifs with h
· assumption
· exact (hf₀s x hx h).1
exact InjOn.congr hinj (fun x ⟨_, hxa⟩ ↦ by rwa [Function.update_of_ne])
termination_by encard s
theorem Finite.exists_bijOn_of_encard_eq [Nonempty β] (hs : s.Finite) (h : s.encard = t.encard) :
∃ (f : α → β), BijOn f s t := by
obtain ⟨f, hf, hinj⟩ := hs.exists_injOn_of_encard_le h.le; use f
convert hinj.bijOn_image
rw [(hs.image f).eq_of_subset_of_encard_le (image_subset_iff.mpr hf)
(h.symm.trans hinj.encard_image.symm).le]
end Function
section ncard
open Nat
/-- A tactic (for use in default params) that applies `Set.toFinite` to synthesize a `Set.Finite`
term. -/
syntax "toFinite_tac" : tactic
macro_rules
| `(tactic| toFinite_tac) => `(tactic| apply Set.toFinite)
/-- A tactic useful for transferring proofs for `encard` to their corresponding `card` statements -/
syntax "to_encard_tac" : tactic
macro_rules
| `(tactic| to_encard_tac) => `(tactic|
simp only [← Nat.cast_le (α := ℕ∞), ← Nat.cast_inj (R := ℕ∞), Nat.cast_add, Nat.cast_one])
/-- The cardinality of `s : Set α` . Has the junk value `0` if `s` is infinite -/
noncomputable def ncard (s : Set α) : ℕ := ENat.toNat s.encard
theorem ncard_def (s : Set α) : s.ncard = ENat.toNat s.encard := rfl
theorem Finite.cast_ncard_eq (hs : s.Finite) : s.ncard = s.encard := by
rwa [ncard, ENat.coe_toNat_eq_self, ne_eq, encard_eq_top_iff, Set.Infinite, not_not]
lemma ncard_le_encard (s : Set α) : s.ncard ≤ s.encard := ENat.coe_toNat_le_self _
theorem Nat.card_coe_set_eq (s : Set α) : Nat.card s = s.ncard := by
obtain (h | h) := s.finite_or_infinite
· have := h.fintype
rw [ncard, h.encard_eq_coe_toFinset_card, Nat.card_eq_fintype_card,
toFinite_toFinset, toFinset_card, ENat.toNat_coe]
have := infinite_coe_iff.2 h
rw [ncard, h.encard_eq, Nat.card_eq_zero_of_infinite, ENat.toNat_top]
theorem ncard_eq_toFinset_card (s : Set α) (hs : s.Finite := by toFinite_tac) :
s.ncard = hs.toFinset.card := by
rw [← Nat.card_coe_set_eq, @Nat.card_eq_fintype_card _ hs.fintype,
@Finite.card_toFinset _ _ hs.fintype hs]
theorem ncard_eq_toFinset_card' (s : Set α) [Fintype s] :
s.ncard = s.toFinset.card := by
simp [← Nat.card_coe_set_eq, Nat.card_eq_fintype_card]
lemma cast_ncard {s : Set α} (hs : s.Finite) :
(s.ncard : Cardinal) = Cardinal.mk s := @Nat.cast_card _ hs
theorem encard_le_coe_iff_finite_ncard_le {k : ℕ} : s.encard ≤ k ↔ s.Finite ∧ s.ncard ≤ k := by
rw [encard_le_coe_iff, and_congr_right_iff]
exact fun hfin ↦ ⟨fun ⟨n₀, hn₀, hle⟩ ↦ by rwa [ncard_def, hn₀, ENat.toNat_coe],
fun h ↦ ⟨s.ncard, by rw [hfin.cast_ncard_eq], h⟩⟩
theorem Infinite.ncard (hs : s.Infinite) : s.ncard = 0 := by
rw [← Nat.card_coe_set_eq, @Nat.card_eq_zero_of_infinite _ hs.to_subtype]
@[gcongr]
theorem ncard_le_ncard (hst : s ⊆ t) (ht : t.Finite := by toFinite_tac) :
s.ncard ≤ t.ncard := by
rw [← Nat.cast_le (α := ℕ∞), ht.cast_ncard_eq, (ht.subset hst).cast_ncard_eq]
exact encard_mono hst
theorem ncard_mono [Finite α] : @Monotone (Set α) _ _ _ ncard := fun _ _ ↦ ncard_le_ncard
@[simp] theorem ncard_eq_zero (hs : s.Finite := by toFinite_tac) :
s.ncard = 0 ↔ s = ∅ := by
rw [← Nat.cast_inj (R := ℕ∞), hs.cast_ncard_eq, Nat.cast_zero, encard_eq_zero]
@[simp, norm_cast] theorem ncard_coe_Finset (s : Finset α) : (s : Set α).ncard = s.card := by
rw [ncard_eq_toFinset_card _, Finset.finite_toSet_toFinset]
theorem ncard_univ (α : Type*) : (univ : Set α).ncard = Nat.card α := by
rcases finite_or_infinite α with h | h
· have hft := Fintype.ofFinite α
rw [ncard_eq_toFinset_card, Finite.toFinset_univ, Finset.card_univ, Nat.card_eq_fintype_card]
rw [Nat.card_eq_zero_of_infinite, Infinite.ncard]
exact infinite_univ
@[simp] theorem ncard_empty (α : Type*) : (∅ : Set α).ncard = 0 := by
rw [ncard_eq_zero]
theorem ncard_pos (hs : s.Finite := by toFinite_tac) : 0 < s.ncard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, Ne, ncard_eq_zero hs, nonempty_iff_ne_empty]
protected alias ⟨_, Nonempty.ncard_pos⟩ := ncard_pos
theorem ncard_ne_zero_of_mem {a : α} (h : a ∈ s) (hs : s.Finite := by toFinite_tac) : s.ncard ≠ 0 :=
((ncard_pos hs).mpr ⟨a, h⟩).ne.symm
theorem finite_of_ncard_ne_zero (hs : s.ncard ≠ 0) : s.Finite :=
s.finite_or_infinite.elim id fun h ↦ (hs h.ncard).elim
theorem finite_of_ncard_pos (hs : 0 < s.ncard) : s.Finite :=
finite_of_ncard_ne_zero hs.ne.symm
theorem nonempty_of_ncard_ne_zero (hs : s.ncard ≠ 0) : s.Nonempty := by
rw [nonempty_iff_ne_empty]; rintro rfl; simp at hs
@[simp] theorem ncard_singleton (a : α) : ({a} : Set α).ncard = 1 := by
simp [ncard]
theorem ncard_singleton_inter (a : α) (s : Set α) : ({a} ∩ s).ncard ≤ 1 := by
rw [← Nat.cast_le (α := ℕ∞), (toFinite _).cast_ncard_eq, Nat.cast_one]
apply encard_singleton_inter
@[simp]
theorem ncard_prod : (s ×ˢ t).ncard = s.ncard * t.ncard := by
simp [ncard, ENat.toNat_mul]
@[simp]
theorem ncard_powerset (s : Set α) (hs : s.Finite := by toFinite_tac) :
(𝒫 s).ncard = 2 ^ s.ncard := by
have h := Cardinal.mk_powerset s
rw [← cast_ncard hs.powerset, ← cast_ncard hs] at h
norm_cast at h
section InsertErase
@[simp] theorem ncard_insert_of_not_mem {a : α} (h : a ∉ s) (hs : s.Finite := by toFinite_tac) :
(insert a s).ncard = s.ncard + 1 := by
rw [← Nat.cast_inj (R := ℕ∞), (hs.insert a).cast_ncard_eq, Nat.cast_add, Nat.cast_one,
hs.cast_ncard_eq, encard_insert_of_not_mem h]
theorem ncard_insert_of_mem {a : α} (h : a ∈ s) : ncard (insert a s) = s.ncard := by
rw [insert_eq_of_mem h]
theorem ncard_insert_le (a : α) (s : Set α) : (insert a s).ncard ≤ s.ncard + 1 := by
obtain hs | hs := s.finite_or_infinite
· to_encard_tac; rw [hs.cast_ncard_eq, (hs.insert _).cast_ncard_eq]; apply encard_insert_le
rw [(hs.mono (subset_insert a s)).ncard]
exact Nat.zero_le _
theorem ncard_insert_eq_ite {a : α} [Decidable (a ∈ s)] (hs : s.Finite := by toFinite_tac) :
ncard (insert a s) = if a ∈ s then s.ncard else s.ncard + 1 := by
by_cases h : a ∈ s
· rw [ncard_insert_of_mem h, if_pos h]
· rw [ncard_insert_of_not_mem h hs, if_neg h]
theorem ncard_le_ncard_insert (a : α) (s : Set α) : s.ncard ≤ (insert a s).ncard := by
classical
refine
s.finite_or_infinite.elim (fun h ↦ ?_) (fun h ↦ by (rw [h.ncard]; exact Nat.zero_le _))
rw [ncard_insert_eq_ite h]; split_ifs <;> simp
@[simp] theorem ncard_pair {a b : α} (h : a ≠ b) : ({a, b} : Set α).ncard = 2 := by
rw [ncard_insert_of_not_mem, ncard_singleton]; simpa
@[simp] theorem ncard_diff_singleton_add_one {a : α} (h : a ∈ s)
(hs : s.Finite := by toFinite_tac) : (s \ {a}).ncard + 1 = s.ncard := by
to_encard_tac; rw [hs.cast_ncard_eq, hs.diff.cast_ncard_eq,
encard_diff_singleton_add_one h]
@[simp] theorem ncard_diff_singleton_of_mem {a : α} (h : a ∈ s) (hs : s.Finite := by toFinite_tac) :
(s \ {a}).ncard = s.ncard - 1 :=
eq_tsub_of_add_eq (ncard_diff_singleton_add_one h hs)
theorem ncard_diff_singleton_lt_of_mem {a : α} (h : a ∈ s) (hs : s.Finite := by toFinite_tac) :
(s \ {a}).ncard < s.ncard := by
rw [← ncard_diff_singleton_add_one h hs]; apply lt_add_one
theorem ncard_diff_singleton_le (s : Set α) (a : α) : (s \ {a}).ncard ≤ s.ncard := by
obtain hs | hs := s.finite_or_infinite
· apply ncard_le_ncard diff_subset hs
convert zero_le (α := ℕ) _
exact (hs.diff (by simp : Set.Finite {a})).ncard
theorem pred_ncard_le_ncard_diff_singleton (s : Set α) (a : α) : s.ncard - 1 ≤ (s \ {a}).ncard := by
rcases s.finite_or_infinite with hs | hs
· by_cases h : a ∈ s
· rw [ncard_diff_singleton_of_mem h hs]
rw [diff_singleton_eq_self h]
apply Nat.pred_le
convert Nat.zero_le _
rw [hs.ncard]
theorem ncard_exchange {a b : α} (ha : a ∉ s) (hb : b ∈ s) : (insert a (s \ {b})).ncard = s.ncard :=
congr_arg ENat.toNat <| encard_exchange ha hb
theorem ncard_exchange' {a b : α} (ha : a ∉ s) (hb : b ∈ s) :
(insert a s \ {b}).ncard = s.ncard := by
rw [← ncard_exchange ha hb, ← singleton_union, ← singleton_union, union_diff_distrib,
@diff_singleton_eq_self _ b {a} fun h ↦ ha (by rwa [← mem_singleton_iff.mp h])]
lemma odd_card_insert_iff {a : α} (ha : a ∉ s) (hs : s.Finite := by toFinite_tac) :
Odd (insert a s).ncard ↔ Even s.ncard := by
rw [ncard_insert_of_not_mem ha hs, Nat.odd_add]
simp only [Nat.odd_add, ← Nat.not_even_iff_odd, Nat.not_even_one, iff_false, Decidable.not_not]
lemma even_card_insert_iff {a : α} (ha : a ∉ s) (hs : s.Finite := by toFinite_tac) :
Even (insert a s).ncard ↔ Odd s.ncard := by
rw [ncard_insert_of_not_mem ha hs, Nat.even_add_one, Nat.not_even_iff_odd]
end InsertErase
variable {f : α → β}
theorem ncard_image_le (hs : s.Finite := by toFinite_tac) : (f '' s).ncard ≤ s.ncard := by
to_encard_tac; rw [hs.cast_ncard_eq, (hs.image _).cast_ncard_eq]; apply encard_image_le
theorem ncard_image_of_injOn (H : Set.InjOn f s) : (f '' s).ncard = s.ncard :=
congr_arg ENat.toNat <| H.encard_image
theorem injOn_of_ncard_image_eq (h : (f '' s).ncard = s.ncard) (hs : s.Finite := by toFinite_tac) :
Set.InjOn f s := by
rw [← Nat.cast_inj (R := ℕ∞), hs.cast_ncard_eq, (hs.image _).cast_ncard_eq] at h
exact hs.injOn_of_encard_image_eq h
theorem ncard_image_iff (hs : s.Finite := by toFinite_tac) :
(f '' s).ncard = s.ncard ↔ Set.InjOn f s :=
⟨fun h ↦ injOn_of_ncard_image_eq h hs, ncard_image_of_injOn⟩
theorem ncard_image_of_injective (s : Set α) (H : f.Injective) : (f '' s).ncard = s.ncard :=
ncard_image_of_injOn fun _ _ _ _ h ↦ H h
theorem ncard_preimage_of_injective_subset_range {s : Set β} (H : f.Injective)
(hs : s ⊆ Set.range f) :
(f ⁻¹' s).ncard = s.ncard := by
rw [← ncard_image_of_injective _ H, image_preimage_eq_iff.mpr hs]
theorem fiber_ncard_ne_zero_iff_mem_image {y : β} (hs : s.Finite := by toFinite_tac) :
{ x ∈ s | f x = y }.ncard ≠ 0 ↔ y ∈ f '' s := by
refine ⟨nonempty_of_ncard_ne_zero, ?_⟩
rintro ⟨z, hz, rfl⟩
exact @ncard_ne_zero_of_mem _ ({ x ∈ s | f x = f z }) z (mem_sep hz rfl)
(hs.subset (sep_subset _ _))
@[simp] theorem ncard_map (f : α ↪ β) : (f '' s).ncard = s.ncard :=
ncard_image_of_injective _ f.inj'
@[simp] theorem ncard_subtype (P : α → Prop) (s : Set α) :
{ x : Subtype P | (x : α) ∈ s }.ncard = (s ∩ setOf P).ncard := by
convert (ncard_image_of_injective _ (@Subtype.coe_injective _ P)).symm
ext x
simp [← and_assoc, exists_eq_right]
theorem ncard_inter_le_ncard_left (s t : Set α) (hs : s.Finite := by toFinite_tac) :
(s ∩ t).ncard ≤ s.ncard :=
ncard_le_ncard inter_subset_left hs
theorem ncard_inter_le_ncard_right (s t : Set α) (ht : t.Finite := by toFinite_tac) :
(s ∩ t).ncard ≤ t.ncard :=
ncard_le_ncard inter_subset_right ht
theorem eq_of_subset_of_ncard_le (h : s ⊆ t) (h' : t.ncard ≤ s.ncard)
(ht : t.Finite := by toFinite_tac) : s = t :=
ht.eq_of_subset_of_encard_le' h
(by rwa [← Nat.cast_le (α := ℕ∞), ht.cast_ncard_eq, (ht.subset h).cast_ncard_eq] at h')
theorem subset_iff_eq_of_ncard_le (h : t.ncard ≤ s.ncard) (ht : t.Finite := by toFinite_tac) :
s ⊆ t ↔ s = t :=
⟨fun hst ↦ eq_of_subset_of_ncard_le hst h ht, Eq.subset'⟩
theorem map_eq_of_subset {f : α ↪ α} (h : f '' s ⊆ s) (hs : s.Finite := by toFinite_tac) :
f '' s = s :=
eq_of_subset_of_ncard_le h (ncard_map _).ge hs
theorem sep_of_ncard_eq {a : α} {P : α → Prop} (h : { x ∈ s | P x }.ncard = s.ncard) (ha : a ∈ s)
(hs : s.Finite := by toFinite_tac) : P a :=
sep_eq_self_iff_mem_true.mp (eq_of_subset_of_ncard_le (by simp) h.symm.le hs) _ ha
theorem ncard_lt_ncard (h : s ⊂ t) (ht : t.Finite := by toFinite_tac) :
s.ncard < t.ncard := by
rw [← Nat.cast_lt (α := ℕ∞), ht.cast_ncard_eq, (ht.subset h.subset).cast_ncard_eq]
exact (ht.subset h.subset).encard_lt_encard h
theorem ncard_strictMono [Finite α] : @StrictMono (Set α) _ _ _ ncard :=
fun _ _ h ↦ ncard_lt_ncard h
theorem ncard_eq_of_bijective {n : ℕ} (f : ∀ i, i < n → α)
(hf : ∀ a ∈ s, ∃ i, ∃ h : i < n, f i h = a) (hf' : ∀ (i) (h : i < n), f i h ∈ s)
(f_inj : ∀ (i j) (hi : i < n) (hj : j < n), f i hi = f j hj → i = j) : s.ncard = n := by
let f' : Fin n → α := fun i ↦ f i.val i.is_lt
suffices himage : s = f' '' Set.univ by
rw [← Fintype.card_fin n, ← Nat.card_eq_fintype_card, ← Set.ncard_univ, himage]
exact ncard_image_of_injOn <| fun i _hi j _hj h ↦ Fin.ext <| f_inj i.val j.val i.is_lt j.is_lt h
ext x
simp only [image_univ, mem_range]
refine ⟨fun hx ↦ ?_, fun ⟨⟨i, hi⟩, hx⟩ ↦ hx ▸ hf' i hi⟩
obtain ⟨i, hi, rfl⟩ := hf x hx
use ⟨i, hi⟩
theorem ncard_congr {t : Set β} (f : ∀ a ∈ s, β) (h₁ : ∀ a ha, f a ha ∈ t)
(h₂ : ∀ a b ha hb, f a ha = f b hb → a = b) (h₃ : ∀ b ∈ t, ∃ a ha, f a ha = b) :
s.ncard = t.ncard := by
set f' : s → t := fun x ↦ ⟨f x.1 x.2, h₁ _ _⟩
have hbij : f'.Bijective := by
constructor
· rintro ⟨x, hx⟩ ⟨y, hy⟩ hxy
simp only [f', Subtype.mk.injEq] at hxy ⊢
exact h₂ _ _ hx hy hxy
rintro ⟨y, hy⟩
obtain ⟨a, ha, rfl⟩ := h₃ y hy
simp only [Subtype.mk.injEq, Subtype.exists]
exact ⟨_, ha, rfl⟩
simp_rw [← Nat.card_coe_set_eq]
exact Nat.card_congr (Equiv.ofBijective f' hbij)
theorem ncard_le_ncard_of_injOn {t : Set β} (f : α → β) (hf : ∀ a ∈ s, f a ∈ t) (f_inj : InjOn f s)
(ht : t.Finite := by toFinite_tac) :
s.ncard ≤ t.ncard := by
have hle := encard_le_encard_of_injOn hf f_inj
to_encard_tac; rwa [ht.cast_ncard_eq, (ht.finite_of_encard_le hle).cast_ncard_eq]
theorem exists_ne_map_eq_of_ncard_lt_of_maps_to {t : Set β} (hc : t.ncard < s.ncard) {f : α → β}
(hf : ∀ a ∈ s, f a ∈ t) (ht : t.Finite := by toFinite_tac) :
∃ x ∈ s, ∃ y ∈ s, x ≠ y ∧ f x = f y := by
by_contra h'
simp only [Ne, exists_prop, not_exists, not_and, not_imp_not] at h'
exact (ncard_le_ncard_of_injOn f hf h' ht).not_lt hc
theorem le_ncard_of_inj_on_range {n : ℕ} (f : ℕ → α) (hf : ∀ i < n, f i ∈ s)
(f_inj : ∀ i < n, ∀ j < n, f i = f j → i = j) (hs : s.Finite := by toFinite_tac) :
n ≤ s.ncard := by
rw [ncard_eq_toFinset_card _ hs]
apply Finset.le_card_of_inj_on_range <;> simpa
theorem surj_on_of_inj_on_of_ncard_le {t : Set β} (f : ∀ a ∈ s, β) (hf : ∀ a ha, f a ha ∈ t)
(hinj : ∀ a₁ a₂ ha₁ ha₂, f a₁ ha₁ = f a₂ ha₂ → a₁ = a₂) (hst : t.ncard ≤ s.ncard)
(ht : t.Finite := by toFinite_tac) :
∀ b ∈ t, ∃ a ha, b = f a ha := by
intro b hb
set f' : s → t := fun x ↦ ⟨f x.1 x.2, hf _ _⟩
have finj : f'.Injective := by
rintro ⟨x, hx⟩ ⟨y, hy⟩ hxy
simp only [f', Subtype.mk.injEq] at hxy ⊢
apply hinj _ _ hx hy hxy
have hft := ht.fintype
have hft' := Fintype.ofInjective f' finj
set f'' : ∀ a, a ∈ s.toFinset → β := fun a h ↦ f a (by simpa using h)
convert @Finset.surj_on_of_inj_on_of_card_le _ _ _ t.toFinset f'' _ _ _ _ (by simpa) using 1
· simp [f'']
· simp [f'', hf]
· intros a₁ a₂ ha₁ ha₂ h
rw [mem_toFinset] at ha₁ ha₂
exact hinj _ _ ha₁ ha₂ h
rwa [← ncard_eq_toFinset_card', ← ncard_eq_toFinset_card']
theorem inj_on_of_surj_on_of_ncard_le {t : Set β} (f : ∀ a ∈ s, β) (hf : ∀ a ha, f a ha ∈ t)
(hsurj : ∀ b ∈ t, ∃ a ha, f a ha = b) (hst : s.ncard ≤ t.ncard) ⦃a₁⦄ (ha₁ : a₁ ∈ s) ⦃a₂⦄
(ha₂ : a₂ ∈ s) (ha₁a₂ : f a₁ ha₁ = f a₂ ha₂) (hs : s.Finite := by toFinite_tac) :
a₁ = a₂ := by
classical
set f' : s → t := fun x ↦ ⟨f x.1 x.2, hf _ _⟩
have hsurj : f'.Surjective := by
rintro ⟨y, hy⟩
obtain ⟨a, ha, rfl⟩ := hsurj y hy
simp only [Subtype.mk.injEq, Subtype.exists]
exact ⟨_, ha, rfl⟩
haveI := hs.fintype
haveI := Fintype.ofSurjective _ hsurj
set f'' : ∀ a, a ∈ s.toFinset → β := fun a h ↦ f a (by simpa using h)
exact
@Finset.inj_on_of_surj_on_of_card_le _ _ _ t.toFinset f''
(fun a ha ↦ by { rw [mem_toFinset] at ha ⊢; exact hf a ha }) (by simpa)
(by { rwa [← ncard_eq_toFinset_card', ← ncard_eq_toFinset_card'] }) a₁
(by simpa) a₂ (by simpa) (by simpa)
@[simp] theorem ncard_coe {α : Type*} (s : Set α) :
Set.ncard (Set.univ : Set (Set.Elem s)) = s.ncard :=
Set.ncard_congr (fun a ha ↦ ↑a) (fun a ha ↦ a.prop) (by simp) (by simp)
@[simp] lemma ncard_graphOn (s : Set α) (f : α → β) : (s.graphOn f).ncard = s.ncard := by
rw [← ncard_image_of_injOn fst_injOn_graph, image_fst_graphOn]
section Lattice
theorem ncard_union_add_ncard_inter (s t : Set α) (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) : (s ∪ t).ncard + (s ∩ t).ncard = s.ncard + t.ncard := by
to_encard_tac; rw [hs.cast_ncard_eq, ht.cast_ncard_eq, (hs.union ht).cast_ncard_eq,
(hs.subset inter_subset_left).cast_ncard_eq, encard_union_add_encard_inter]
theorem ncard_inter_add_ncard_union (s t : Set α) (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) : (s ∩ t).ncard + (s ∪ t).ncard = s.ncard + t.ncard := by
rw [add_comm, ncard_union_add_ncard_inter _ _ hs ht]
theorem ncard_union_le (s t : Set α) : (s ∪ t).ncard ≤ s.ncard + t.ncard := by
obtain (h | h) := (s ∪ t).finite_or_infinite
· to_encard_tac
rw [h.cast_ncard_eq, (h.subset subset_union_left).cast_ncard_eq,
(h.subset subset_union_right).cast_ncard_eq]
apply encard_union_le
rw [h.ncard]
apply zero_le
theorem ncard_union_eq (h : Disjoint s t) (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) : (s ∪ t).ncard = s.ncard + t.ncard := by
to_encard_tac
rw [hs.cast_ncard_eq, ht.cast_ncard_eq, (hs.union ht).cast_ncard_eq, encard_union_eq h]
theorem ncard_diff_add_ncard_of_subset (h : s ⊆ t) (ht : t.Finite := by toFinite_tac) :
(t \ s).ncard + s.ncard = t.ncard := by
to_encard_tac
rw [ht.cast_ncard_eq, (ht.subset h).cast_ncard_eq, ht.diff.cast_ncard_eq,
encard_diff_add_encard_of_subset h]
theorem ncard_diff (hst : s ⊆ t) (hs : s.Finite := by toFinite_tac) :
(t \ s).ncard = t.ncard - s.ncard := by
obtain ht | ht := t.finite_or_infinite
· rw [← ncard_diff_add_ncard_of_subset hst ht, add_tsub_cancel_right]
· rw [ht.ncard, Nat.zero_sub, (ht.diff hs).ncard]
lemma cast_ncard_sdiff {R : Type*} [AddGroupWithOne R] (hst : s ⊆ t) (ht : t.Finite) :
((t \ s).ncard : R) = t.ncard - s.ncard := by
rw [ncard_diff hst (ht.subset hst), Nat.cast_sub (ncard_le_ncard hst ht)]
theorem ncard_le_ncard_diff_add_ncard (s t : Set α) (ht : t.Finite := by toFinite_tac) :
s.ncard ≤ (s \ t).ncard + t.ncard := by
rcases s.finite_or_infinite with hs | hs
· to_encard_tac
rw [ht.cast_ncard_eq, hs.cast_ncard_eq, hs.diff.cast_ncard_eq]
apply encard_le_encard_diff_add_encard
convert Nat.zero_le _
rw [hs.ncard]
theorem le_ncard_diff (s t : Set α) (hs : s.Finite := by toFinite_tac) :
t.ncard - s.ncard ≤ (t \ s).ncard :=
tsub_le_iff_left.mpr (by rw [add_comm]; apply ncard_le_ncard_diff_add_ncard _ _ hs)
theorem ncard_diff_add_ncard (s t : Set α) (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) :
(s \ t).ncard + t.ncard = (s ∪ t).ncard := by
rw [← ncard_union_eq disjoint_sdiff_left hs.diff ht, diff_union_self]
theorem diff_nonempty_of_ncard_lt_ncard (h : s.ncard < t.ncard) (hs : s.Finite := by toFinite_tac) :
(t \ s).Nonempty := by
rw [Set.nonempty_iff_ne_empty, Ne, diff_eq_empty]
exact fun h' ↦ h.not_le (ncard_le_ncard h' hs)
theorem exists_mem_not_mem_of_ncard_lt_ncard (h : s.ncard < t.ncard)
(hs : s.Finite := by toFinite_tac) : ∃ e, e ∈ t ∧ e ∉ s :=
diff_nonempty_of_ncard_lt_ncard h hs
@[simp] theorem ncard_inter_add_ncard_diff_eq_ncard (s t : Set α)
(hs : s.Finite := by toFinite_tac) : (s ∩ t).ncard + (s \ t).ncard = s.ncard := by
rw [← ncard_union_eq (disjoint_of_subset_left inter_subset_right disjoint_sdiff_right)
(hs.inter_of_left _) hs.diff, union_comm, diff_union_inter]
theorem ncard_eq_ncard_iff_ncard_diff_eq_ncard_diff (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) : s.ncard = t.ncard ↔ (s \ t).ncard = (t \ s).ncard := by
rw [← ncard_inter_add_ncard_diff_eq_ncard s t hs, ← ncard_inter_add_ncard_diff_eq_ncard t s ht,
inter_comm, add_right_inj]
theorem ncard_le_ncard_iff_ncard_diff_le_ncard_diff (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) : s.ncard ≤ t.ncard ↔ (s \ t).ncard ≤ (t \ s).ncard := by
rw [← ncard_inter_add_ncard_diff_eq_ncard s t hs, ← ncard_inter_add_ncard_diff_eq_ncard t s ht,
inter_comm, add_le_add_iff_left]
theorem ncard_lt_ncard_iff_ncard_diff_lt_ncard_diff (hs : s.Finite := by toFinite_tac)
(ht : t.Finite := by toFinite_tac) : s.ncard < t.ncard ↔ (s \ t).ncard < (t \ s).ncard := by
rw [← ncard_inter_add_ncard_diff_eq_ncard s t hs, ← ncard_inter_add_ncard_diff_eq_ncard t s ht,
inter_comm, add_lt_add_iff_left]
theorem ncard_add_ncard_compl (s : Set α) (hs : s.Finite := by toFinite_tac)
(hsc : sᶜ.Finite := by toFinite_tac) : s.ncard + sᶜ.ncard = Nat.card α := by
rw [← ncard_univ, ← ncard_union_eq (@disjoint_compl_right _ _ s) hs hsc, union_compl_self]
theorem eq_univ_iff_ncard [Finite α] (s : Set α) :
s = univ ↔ ncard s = Nat.card α := by
rw [← compl_empty_iff, ← ncard_eq_zero, ← ncard_add_ncard_compl s, left_eq_add]
lemma even_ncard_compl_iff [Finite α] (heven : Even (Nat.card α)) (s : Set α) :
Even sᶜ.ncard ↔ Even s.ncard := by
simp [compl_eq_univ_diff, ncard_diff (subset_univ _ : s ⊆ Set.univ),
Nat.even_sub (ncard_le_ncard (subset_univ _ : s ⊆ Set.univ)),
(ncard_univ _).symm ▸ heven]
lemma odd_ncard_compl_iff [Finite α] (heven : Even (Nat.card α)) (s : Set α) :
Odd sᶜ.ncard ↔ Odd s.ncard := by
rw [← Nat.not_even_iff_odd, even_ncard_compl_iff heven, Nat.not_even_iff_odd]
end Lattice
/-- Given a subset `s` of a set `t`, of sizes at most and at least `n` respectively, there exists a
set `u` of size `n` which is both a superset of `s` and a subset of `t`. -/
lemma exists_subsuperset_card_eq {n : ℕ} (hst : s ⊆ t) (hsn : s.ncard ≤ n) (hnt : n ≤ t.ncard) :
∃ u, s ⊆ u ∧ u ⊆ t ∧ u.ncard = n := by
obtain ht | ht := t.infinite_or_finite
· rw [ht.ncard, Nat.le_zero, ← ht.ncard] at hnt
exact ⟨t, hst, Subset.rfl, hnt.symm⟩
lift s to Finset α using ht.subset hst
lift t to Finset α using ht
obtain ⟨u, hsu, hut, hu⟩ := Finset.exists_subsuperset_card_eq (mod_cast hst) (by simpa using hsn)
(mod_cast hnt)
exact ⟨u, mod_cast hsu, mod_cast hut, mod_cast hu⟩
/-- We can shrink a set to any smaller size. -/
lemma exists_subset_card_eq {n : ℕ} (hns : n ≤ s.ncard) : ∃ t ⊆ s, t.ncard = n := by
simpa using exists_subsuperset_card_eq s.empty_subset (by simp) hns
theorem Infinite.exists_subset_ncard_eq {s : Set α} (hs : s.Infinite) (k : ℕ) :
∃ t, t ⊆ s ∧ t.Finite ∧ t.ncard = k := by
have := hs.to_subtype
obtain ⟨t', -, rfl⟩ := @Infinite.exists_subset_card_eq s univ infinite_univ k
refine ⟨Subtype.val '' (t' : Set s), by simp, Finite.image _ (by simp), ?_⟩
rw [ncard_image_of_injective _ Subtype.coe_injective]
simp
theorem Infinite.exists_superset_ncard_eq {s t : Set α} (ht : t.Infinite) (hst : s ⊆ t)
(hs : s.Finite) {k : ℕ} (hsk : s.ncard ≤ k) : ∃ s', s ⊆ s' ∧ s' ⊆ t ∧ s'.ncard = k := by
obtain ⟨s₁, hs₁, hs₁fin, hs₁card⟩ := (ht.diff hs).exists_subset_ncard_eq (k - s.ncard)
refine ⟨s ∪ s₁, subset_union_left, union_subset hst (hs₁.trans diff_subset), ?_⟩
rwa [ncard_union_eq (disjoint_of_subset_right hs₁ disjoint_sdiff_right) hs hs₁fin, hs₁card,
add_tsub_cancel_of_le]
theorem exists_subset_or_subset_of_two_mul_lt_ncard {n : ℕ} (hst : 2 * n < (s ∪ t).ncard) :
∃ r : Set α, n < r.ncard ∧ (r ⊆ s ∨ r ⊆ t) := by
classical
have hu := finite_of_ncard_ne_zero ((Nat.zero_le _).trans_lt hst).ne.symm
rw [ncard_eq_toFinset_card _ hu,
Finite.toFinset_union (hu.subset subset_union_left)
(hu.subset subset_union_right)] at hst
obtain ⟨r', hnr', hr'⟩ := Finset.exists_subset_or_subset_of_two_mul_lt_card hst
exact ⟨r', by simpa, by simpa using hr'⟩
/-! ### Explicit description of a set from its cardinality -/
@[simp] theorem ncard_eq_one : s.ncard = 1 ↔ ∃ a, s = {a} := by
refine ⟨fun h ↦ ?_, by rintro ⟨a, rfl⟩; rw [ncard_singleton]⟩
have hft := (finite_of_ncard_ne_zero (ne_zero_of_eq_one h)).fintype
simp_rw [ncard_eq_toFinset_card', @Finset.card_eq_one _ (toFinset s)] at h
refine h.imp fun a ha ↦ ?_
simp_rw [Set.ext_iff, mem_singleton_iff]
simp only [Finset.ext_iff, mem_toFinset, Finset.mem_singleton] at ha
exact ha
theorem exists_eq_insert_iff_ncard (hs : s.Finite := by toFinite_tac) :
(∃ a ∉ s, insert a s = t) ↔ s ⊆ t ∧ s.ncard + 1 = t.ncard := by
classical
rcases t.finite_or_infinite with ht | ht
· rw [ncard_eq_toFinset_card _ hs, ncard_eq_toFinset_card _ ht,
← @Finite.toFinset_subset_toFinset _ _ _ hs ht, ← Finset.exists_eq_insert_iff]
convert Iff.rfl using 2; simp only [Finite.mem_toFinset]
ext x
simp [Finset.ext_iff, Set.ext_iff]
simp only [ht.ncard, exists_prop, add_eq_zero, and_false, iff_false, not_exists, not_and,
reduceCtorEq]
rintro x - rfl
exact ht (hs.insert x)
theorem ncard_le_one (hs : s.Finite := by toFinite_tac) :
s.ncard ≤ 1 ↔ ∀ a ∈ s, ∀ b ∈ s, a = b := by
simp_rw [ncard_eq_toFinset_card _ hs, Finset.card_le_one, Finite.mem_toFinset]
@[simp] theorem ncard_le_one_iff_subsingleton [Finite s] :
s.ncard ≤ 1 ↔ s.Subsingleton :=
ncard_le_one <| inferInstanceAs (Finite s)
theorem ncard_le_one_iff (hs : s.Finite := by toFinite_tac) :
s.ncard ≤ 1 ↔ ∀ {a b}, a ∈ s → b ∈ s → a = b := by
rw [ncard_le_one hs]
tauto
theorem ncard_le_one_iff_eq (hs : s.Finite := by toFinite_tac) :
s.ncard ≤ 1 ↔ s = ∅ ∨ ∃ a, s = {a} := by
obtain rfl | ⟨x, hx⟩ := s.eq_empty_or_nonempty
· exact iff_of_true (by simp) (Or.inl rfl)
rw [ncard_le_one_iff hs]
refine ⟨fun h ↦ Or.inr ⟨x, (singleton_subset_iff.mpr hx).antisymm' fun y hy ↦ h hy hx⟩, ?_⟩
rintro (rfl | ⟨a, rfl⟩)
· exact (not_mem_empty _ hx).elim
simp_rw [mem_singleton_iff] at hx ⊢; subst hx
simp only [forall_eq_apply_imp_iff, imp_self, implies_true]
theorem ncard_le_one_iff_subset_singleton [Nonempty α]
(hs : s.Finite := by toFinite_tac) :
s.ncard ≤ 1 ↔ ∃ x : α, s ⊆ {x} := by
simp_rw [ncard_eq_toFinset_card _ hs, Finset.card_le_one_iff_subset_singleton,
Finite.toFinset_subset, Finset.coe_singleton]
/-- A `Set` of a subsingleton type has cardinality at most one. -/
theorem ncard_le_one_of_subsingleton [Subsingleton α] (s : Set α) : s.ncard ≤ 1 := by
rw [ncard_eq_toFinset_card]
exact Finset.card_le_one_of_subsingleton _
theorem one_lt_ncard (hs : s.Finite := by toFinite_tac) :
1 < s.ncard ↔ ∃ a ∈ s, ∃ b ∈ s, a ≠ b := by
simp_rw [ncard_eq_toFinset_card _ hs, Finset.one_lt_card, Finite.mem_toFinset]
theorem one_lt_ncard_iff (hs : s.Finite := by toFinite_tac) :
1 < s.ncard ↔ ∃ a b, a ∈ s ∧ b ∈ s ∧ a ≠ b := by
rw [one_lt_ncard hs]
simp only [exists_prop, exists_and_left]
lemma one_lt_ncard_of_nonempty_of_even (hs : Set.Finite s) (hn : Set.Nonempty s := by toFinite_tac)
(he : Even (s.ncard)) : 1 < s.ncard := by
rw [← Set.ncard_pos hs] at hn
have : s.ncard ≠ 1 := fun h ↦ by simp [h] at he
omega
theorem two_lt_ncard_iff (hs : s.Finite := by toFinite_tac) :
2 < s.ncard ↔ ∃ a b c, a ∈ s ∧ b ∈ s ∧ c ∈ s ∧ a ≠ b ∧ a ≠ c ∧ b ≠ c := by
simp_rw [ncard_eq_toFinset_card _ hs, Finset.two_lt_card_iff, Finite.mem_toFinset]
| theorem two_lt_ncard (hs : s.Finite := by toFinite_tac) :
2 < s.ncard ↔ ∃ a ∈ s, ∃ b ∈ s, ∃ c ∈ s, a ≠ b ∧ a ≠ c ∧ b ≠ c := by
simp only [two_lt_ncard_iff hs, exists_and_left, exists_prop]
| Mathlib/Data/Set/Card.lean | 1,072 | 1,075 |
/-
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.GroupTheory.Perm.Cycle.Basic
/-!
# Closure results for permutation groups
* This file contains several closure results:
* `closure_isCycle` : The symmetric group is generated by cycles
* `closure_cycle_adjacent_swap` : The symmetric group is generated by
a cycle and an adjacent transposition
* `closure_cycle_coprime_swap` : The symmetric group is generated by
a cycle and a coprime transposition
* `closure_prime_cycle_swap` : The symmetric group is generated by
a prime cycle and a transposition
-/
open Equiv Function Finset
variable {ι α β : Type*}
namespace Equiv.Perm
section Generation
variable [Finite β]
open Subgroup
theorem closure_isCycle : closure { σ : Perm β | IsCycle σ } = ⊤ := by
classical
cases nonempty_fintype β
exact
top_le_iff.mp (le_trans (ge_of_eq closure_isSwap) (closure_mono fun _ => IsSwap.isCycle))
variable [DecidableEq α] [Fintype α]
theorem closure_cycle_adjacent_swap {σ : Perm α} (h1 : IsCycle σ) (h2 : σ.support = univ) (x : α) :
closure ({σ, swap x (σ x)} : Set (Perm α)) = ⊤ := by
let H := closure ({σ, swap x (σ x)} : Set (Perm α))
have h3 : σ ∈ H := subset_closure (Set.mem_insert σ _)
have h4 : swap x (σ x) ∈ H := subset_closure (Set.mem_insert_of_mem _ (Set.mem_singleton _))
have step1 : ∀ n : ℕ, swap ((σ ^ n) x) ((σ ^ (n + 1) : Perm α) x) ∈ H := by
intro n
induction n with
| zero => exact subset_closure (Set.mem_insert_of_mem _ (Set.mem_singleton _))
| succ n ih =>
convert H.mul_mem (H.mul_mem h3 ih) (H.inv_mem h3)
simp_rw [mul_swap_eq_swap_mul, mul_inv_cancel_right, pow_succ', coe_mul, comp_apply]
have step2 : ∀ n : ℕ, swap x ((σ ^ n) x) ∈ H := by
intro n
induction n with
| zero =>
simp only [pow_zero, coe_one, id_eq, swap_self, Set.mem_singleton_iff]
convert H.one_mem
| succ n ih =>
by_cases h5 : x = (σ ^ n) x
· rw [pow_succ', mul_apply, ← h5]
exact h4
by_cases h6 : x = (σ ^ (n + 1) : Perm α) x
· rw [← h6, swap_self]
exact H.one_mem
rw [swap_comm, ← swap_mul_swap_mul_swap h5 h6]
exact H.mul_mem (H.mul_mem (step1 n) ih) (step1 n)
have step3 : ∀ y : α, swap x y ∈ H := by
intro y
have hx : x ∈ univ := Finset.mem_univ x
rw [← h2, mem_support] at hx
have hy : y ∈ univ := Finset.mem_univ y
rw [← h2, mem_support] at hy
obtain ⟨n, hn⟩ := IsCycle.exists_pow_eq h1 hx hy
rw [← hn]
exact step2 n
have step4 : ∀ y z : α, swap y z ∈ H := by
intro y z
by_cases h5 : z = x
· rw [h5, swap_comm]
exact step3 y
by_cases h6 : z = y
· rw [h6, swap_self]
exact H.one_mem
rw [← swap_mul_swap_mul_swap h5 h6, swap_comm z x]
exact H.mul_mem (H.mul_mem (step3 y) (step3 z)) (step3 y)
rw [eq_top_iff, ← closure_isSwap, closure_le]
rintro τ ⟨y, z, _, h6⟩
rw [h6]
exact step4 y z
theorem closure_cycle_coprime_swap {n : ℕ} {σ : Perm α} (h0 : Nat.Coprime n (Fintype.card α))
(h1 : IsCycle σ) (h2 : σ.support = Finset.univ) (x : α) :
| closure ({σ, swap x ((σ ^ n) x)} : Set (Perm α)) = ⊤ := by
rw [← Finset.card_univ, ← h2, ← h1.orderOf] at h0
obtain ⟨m, hm⟩ := exists_pow_eq_self_of_coprime h0
have h2' : (σ ^ n).support = univ := Eq.trans (support_pow_coprime h0) h2
have h1' : IsCycle ((σ ^ n) ^ (m : ℤ)) := by rwa [← hm] at h1
replace h1' : IsCycle (σ ^ n) :=
h1'.of_pow (le_trans (support_pow_le σ n) (ge_of_eq (congr_arg support hm)))
rw [eq_top_iff, ← closure_cycle_adjacent_swap h1' h2' x, closure_le, Set.insert_subset_iff]
exact
⟨Subgroup.pow_mem (closure _) (subset_closure (Set.mem_insert σ _)) n,
Set.singleton_subset_iff.mpr (subset_closure (Set.mem_insert_of_mem _ (Set.mem_singleton _)))⟩
theorem closure_prime_cycle_swap {σ τ : Perm α} (h0 : (Fintype.card α).Prime) (h1 : IsCycle σ)
| Mathlib/GroupTheory/Perm/Closure.lean | 96 | 108 |
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